cryptocurrency

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pages: 457 words: 128,838

The Age of Cryptocurrency: How Bitcoin and Digital Money Are Challenging the Global Economic Order by Paul Vigna, Michael J. Casey

Airbnb, altcoin, bank run, banking crisis, bitcoin, blockchain, Bretton Woods, buy and hold, California gold rush, capital controls, carbon footprint, clean water, collaborative economy, collapse of Lehman Brothers, Columbine, Credit Default Swap, cryptocurrency, David Graeber, disintermediation, Edward Snowden, Elon Musk, Ethereum, ethereum blockchain, fiat currency, financial innovation, Firefox, Flash crash, Fractional reserve banking, hacker house, Hernando de Soto, high net worth, informal economy, intangible asset, Internet of things, inventory management, Joi Ito, Julian Assange, Kickstarter, Kuwabatake Sanjuro: assassination market, litecoin, Long Term Capital Management, Lyft, M-Pesa, Marc Andreessen, Mark Zuckerberg, McMansion, means of production, Menlo Park, mobile money, money: store of value / unit of account / medium of exchange, Nelson Mandela, Network effects, new economy, new new economy, Nixon shock, offshore financial centre, payday loans, Pearl River Delta, peer-to-peer, peer-to-peer lending, pets.com, Ponzi scheme, prediction markets, price stability, profit motive, QR code, RAND corporation, regulatory arbitrage, rent-seeking, reserve currency, Robert Shiller, Robert Shiller, Ross Ulbricht, Satoshi Nakamoto, seigniorage, shareholder value, sharing economy, short selling, Silicon Valley, Silicon Valley startup, Skype, smart contracts, special drawing rights, Spread Networks laid a new fibre optics cable between New York and Chicago, Steve Jobs, supply-chain management, Ted Nelson, The Great Moderation, the market place, the payments system, The Wealth of Nations by Adam Smith, too big to fail, transaction costs, tulip mania, Turing complete, Tyler Cowen: Great Stagnation, Uber and Lyft, uber lyft, underbanked, WikiLeaks, Y Combinator, Y2K, zero-sum game, Zimmermann PGP

But that’s not what the proponents of this technology foresee—especially those in the cryptocurrency sector. They believe that decentralization is just getting started and that the centralized economic and political establishments—even governments and nation-states, those ultimate centralized loci of power—will be disrupted by it. If so, cryptocurrencies and blockchain technology could ride that wave triumphantly. A phrase from Mastercoin’s David Johnston that some in the cryptocurrency community call Johnston’s law could come true: “Everything that can be decentralized will be decentralized.” This especially optimistic view of cryptocurrency technology’s potential runs up against the many obstacles that it faces. But if we set aside cryptocurrencies for a moment, it’s hard not to believe that the decentralizing trend has momentum.

While business adopters could be the most powerful catalysts for change, they will watch how consumers and the general public view bitcoin and other cryptocurrencies before jumping. Most consumers may never show sufficient support. Consumer-focused digital-wallet, payment-processing, and bitcoin-depository services such as Coinbase, Bitreserve, Circle Internet Financial, and Xapo are making it easier to use cryptocurrencies and safer for the general public, trying to erase the lingering memory of Mt. Gox. But little evidence suggests that they’ve managed to reach people beyond the small groups of tech-minded early adopters and cryptocurrency enthusiasts currently using it. Perhaps cryptocurrency’s reputation has been forever ruined by bad press. Add to that public image the headache of capital-gains-tax tracking now required in the United States, as well as the regulatory burdens that make it hard for cryptocurrency providers to seamlessly reach ordinary consumers, and it’s possible that this new form of money will never gain appeal.

Well, keeping our imagination hats on, we could foresee a set of international standards to define what governments can and can’t do with digital money, maybe some sort of international board of cryptocurrency regulators to align rules and regulations that pertain to independent cryptocurrencies such as bitcoin. But given that nation-states have trouble keeping control of decentralized, leaderless cryptocurrencies, it’s fair to say international law would be even harder to impose. After all, there is no fully endorsed international criminal court; the one in The Hague isn’t recognized by Washington. The international realm exists in a state of quasi anarchy—a perfect fit for borderless cryptocurrencies. Some international agreements do stick, such as the Bretton Woods system of pegged currencies established in 1944 amid the crisis of World War II (and ended when President Nixon squelched the gold standard in 1971). Might a cryptocurrency crisis goad governments into another such sweeping agreement?


pages: 349 words: 102,827

The Infinite Machine: How an Army of Crypto-Hackers Is Building the Next Internet With Ethereum by Camila Russo

4chan, Airbnb, algorithmic trading, altcoin, always be closing, Any sufficiently advanced technology is indistinguishable from magic, Asian financial crisis, bitcoin, blockchain, Burning Man, crowdsourcing, cryptocurrency, distributed ledger, diversification, Donald Trump, East Village, Ethereum, ethereum blockchain, Flash crash, Google Glasses, Google Hangouts, hacker house, Internet of things, Mark Zuckerberg, Maui Hawaii, mobile money, new economy, peer-to-peer, Peter Thiel, pets.com, Ponzi scheme, prediction markets, QR code, reserve currency, RFC: Request For Comment, Richard Stallman, Robert Shiller, Robert Shiller, Sand Hill Road, Satoshi Nakamoto, semantic web, sharing economy, side project, Silicon Valley, Skype, slashdot, smart contracts, South of Market, San Francisco, the payments system, too big to fail, tulip mania, Turing complete, Uber for X

Like predators pouncing at the smell of blood, crypto’s “enemies” started coming down hard on the nascent industry. South Korean police and tax authorities raided two of the largest cryptocurrency exchanges, and the country’s regulators said they were planning greater oversight on trading platforms. China, which had already banned cryptocurrency exchanges in 2017, said it would escalate its crackdown as alternative trading venues continued to pop up. In India, the finance minister said the government would take measures to eliminate the use of cryptocurrencies in the payments system because they are not legal tender. A record $500 million heist at Japanese exchange Coincheck further spooked the market. Facebook banned cryptocurrency ads and US banks cut off credit card purchases of cryptocurrencies. And that was only January. At the end of the month, US regulators made it clear that the couple of ICO cases it had gone after in 2017 had been just the beginning.

For the old chain to keep growing, someone had to be connected to the old network and spend energy to confirm blocks on a blockchain with a worthless cryptocurrency. The old chain was like a parallel universe where pre-fork Ethereum was left intact. Everyone’s accounts held the same amount of coins they had at the time, and funds were still stuck in the “dark DAO.” But the cryptocurrency held there wasn’t ether. It was this parallel chain’s own cryptocurrency. Ether was only mined on the new chain. Blockchains are supposed to work on economic incentives, but in this case, the old Ethereum chain, which was later called Ethereum Classic, emerged from people who ignored immediate economic incentives and instead spent time and money to make sure an immutable Ethereum chain survived. Maybe the chain’s cryptocurrency would later gain in value and they would be compensated. “We believe in decentralized, censorship-resistant, permissionless blockchains.

High up on the list of distractions was the eye-watering growth of the cryptocurrency market. At the market peak on the first days of 2018, the value of digital assets had ballooned to over $800 billion from around $15 billion a year earlier. Thousands of new cryptocurrencies had sprung up in that time. But Vitalik wasn’t happy. “So total cryptocoin market cap just hit $0.5T today. But have we *earned* it?” Vitalik tweeted on December 12, 2017. “How many unbanked people have we banked?” he wrote, and continued to ask, how many applications have a significant number of users or are moving large amounts of volume? How many people have been protected from hyperinflation? In a series of tweets, he questioned whether cryptocurrencies’ impact so far was enough to justify the size of the market. “The answer to all of these questions is definitely not zero, and in some cases it’s quite significant,” he wrote.


pages: 296 words: 86,610

The Bitcoin Guidebook: How to Obtain, Invest, and Spend the World's First Decentralized Cryptocurrency by Ian Demartino

3D printing, AltaVista, altcoin, bitcoin, blockchain, buy low sell high, capital controls, cloud computing, corporate governance, crowdsourcing, cryptocurrency, distributed ledger, Edward Snowden, Elon Musk, Ethereum, ethereum blockchain, fiat currency, Firefox, forensic accounting, global village, GnuPG, Google Earth, Haight Ashbury, Jacob Appelbaum, Kevin Kelly, Kickstarter, litecoin, M-Pesa, Marc Andreessen, Marshall McLuhan, Oculus Rift, peer-to-peer, peer-to-peer lending, Ponzi scheme, prediction markets, QR code, ransomware, Ross Ulbricht, Satoshi Nakamoto, self-driving car, Skype, smart contracts, Steven Levy, the medium is the message, underbanked, WikiLeaks, Zimmermann PGP

If you would like to donate to the author, you can do so with the following QR code: Bitcoin Address: 3Bi1fhng5LfoDzue5MTfGw9PgHNKKgRkVt Disclaimer: Although I have attempted to make this book as accurate as possible, cryptocurrencies are complex and constantly evolving. So it is worth mentioning right off the bat: do your own research—things can change from month to month and week to week. I also make no claim to the legitimacy of the companies mentioned in this book, as their status can change at any time. Keywords altcoin: Short for “alternative cryptocurrency”; another cryptocurrency similar to Bitcoin. There are more than a thousand altcoins currently in existence; most are nearly exact copies of more successful cryptocurrencies, but some very innovative ones have been produced as well. ASIC: Application-specific integrated circuit. A piece of hardware designed to do one thing and one thing only. In the cryptocurrency world, it mines for a specific algorithm (SHA256, Scrypt, etc.).

As mentioned, Bitcoin doesn’t just bring basic banking to those without banking access; it also has the potential to bring advanced banking abilities to users around the world. Bitcoin 2.0 projects, as they are often called, can involve Bitcoin or other cryptocurrencies. The main idea behind these projects is that the blockchain and blockchain technologies can be used to transfer and keep track of holdings of valuables other than Bitcoin or other digital currencies. Even if a 2.0 project is not built off of Bitcoin, like Ethereum, increased investment and interest in cryptocurrencies as a whole tend to increase Bitcoin’s value as well. Since Bitcoin is currently the most successful, secure, and popular cryptocurrency, any increased interest in cryptocurrencies as a whole has a positive effect on Bitcoin’s price. The first example of a “2.0” cryptocurrency was Namecoin, which, in addition to being a currency, acted as a distributed domain name registrar free from the control of any government, individual or group.

Afterward, merge mining became a popular feature in a lot of smaller cryptocurrencies. Dogecoin isn’t the future of Internet currency, as even its most adamant supporters admit. But that doesn’t mean it doesn’t have a place in the meantime. It has already passed all expectations and the rest of the cryptocurrency scene could learn a lot from Dogecoin’s community and its successes. Ripple/Stellar Ripple Labs technically existed before Bitcoin itself.6 It was originally a payment processor not all that different from PayPal. After Satoshi Nakamoto’s white paper was published and Bitcoin’s subsequent rise, the company decided to launch its own cryptocurrency, called Ripple. Ripple is different than Bitcoin and most other currencies. Many in the community argue that it isn’t a “true” cryptocurrency because of its centralized nature, and they might have a point.


pages: 271 words: 52,814

Blockchain: Blueprint for a New Economy by Melanie Swan

23andMe, Airbnb, altcoin, Amazon Web Services, asset allocation, banking crisis, basic income, bioinformatics, bitcoin, blockchain, capital controls, cellular automata, central bank independence, clean water, cloud computing, collaborative editing, Conway's Game of Life, crowdsourcing, cryptocurrency, disintermediation, Edward Snowden, en.wikipedia.org, Ethereum, ethereum blockchain, fault tolerance, fiat currency, financial innovation, Firefox, friendly AI, Hernando de Soto, intangible asset, Internet Archive, Internet of things, Khan Academy, Kickstarter, lifelogging, litecoin, Lyft, M-Pesa, microbiome, Network effects, new economy, peer-to-peer, peer-to-peer lending, peer-to-peer model, personalized medicine, post scarcity, prediction markets, QR code, ride hailing / ride sharing, Satoshi Nakamoto, Search for Extraterrestrial Intelligence, SETI@home, sharing economy, Skype, smart cities, smart contracts, smart grid, software as a service, technological singularity, Turing complete, uber lyft, unbanked and underbanked, underbanked, web application, WikiLeaks

Fifth, there could be a RealJobs module connecting local employers with students for topical internships and jobs with industry exposure and job force readiness training, all in a rewards-structured environment. There are several efforts under way to support students learning about and using cryptocurrencies on university campuses. The student-founded Campus Cryptocurrency Network counts 150 clubs in its network as of September 2014 and is a primary resource for students interested in starting campus cryptocurrency clubs. In the future, this network could be the standard repository for templated Campuscoin applications. Likewise, students founded and operate theBitcoin Association of Berkeley and organized their first hackathon in November 2014. MIT, with the MIT Bitcoin Project, has made a significant commitment to encourage the use and awareness of cryptocurrency among students, and it plans to give half a million dollars’ worth of Bitcoin to undergraduates. Students were invited to claim their $100 of Bitcoin per person in October 2014.169 Stanford University has made an effort to develop cryptography courses, which it offers for free online.

CryptoCoins News, updated November 17, 2014. https://www.cryptocoinsnews.com/spanish-bank-bankinter-invests-bitcoin-startup-coinffeine/. 37 Mac, R. “PayPal Takes Baby Step Toward Bitcoin, Partners with Cryptocurrency Processors.” Forbes, September 23, 2014. http://www.forbes.com/sites/ryanmac/2014/09/23/paypal-takes-small-step-toward-bitcoin-partners-with-cryptocurrency-processors/. 38 Bensinger, G. “eBay Payments Unit in Talks to Accept Bitcoin.” The Wall Street Journal, August 14, 2014. http://online.wsj.com/articles/ebay-payment-unit-in-talks-to-accept-bitcoin-1408052917. 39 Cordell, D. “Fidor Bank Partners with Kraken to Create Cryptocurrency Bank.” CryptoCoins News, updated November 2, 2014. https://www.cryptocoinsnews.com/fidor-bank-partners-kraken-create-cryptocurrency-bank/. 40 Casey, M.J. “TeraExchange Unveils First U.S.-Regulated Bitcoin Swaps Exchange.” The Wall Street Journal, September 12, 2014. http://teraexchange.com/news/2014_9_12_Tera_WSJ.pdf. 41 Rizzo, P.

New York: Dutton Publishing, 2013. 194 Antonopoulos, A.M. Mastering Bitcoin: Unlocking Digital Crypto-Currencies. Sebastopol, CA: O’Reilly Media, 2014. 195 Bostrom, N. Superintelligence: Paths, Dangers, Strategies. Oxford, UK: Oxford University Press, 2014. 196 Swan, M. “Blockchain-Enforced Friendly AI.” Crypto Money Expo, December 5, 2014. http://cryptomoneyexpo.com/expos/inv2/#schedule and http://youtu.be/qdGoRep5iT0/. Index A address, How a Cryptocurrency Works Airbnb, Government Regulation Alexandria, Freedom of Speech/Anti-Censorship Applications: Alexandria and Ostel altcoin, Summary: Blockchain 1.0 in Practical Use altcoin wallet, How a Cryptocurrency Works alternative currencies, Summary: Blockchain 1.0 in Practical Use-Relation to Fiat Currency, Cryptocurrency Basics-Ledra Capital Mega Master Blockchain List anti-censorship, Freedom of Speech/Anti-Censorship Applications: Alexandria and Ostel APIs, Blockchain Development Platforms and APIs Aráoz, Manuel, Proof of Existence archiving, Blockchain Ecosystem: Decentralized Storage, Communication, and Computation art (see digital art) artificial intelligence (AI), The Blockchain as a Path to Artificial Intelligence, Blockchain AI: Consensus as the Mechanism to Foster “Friendly” AI-Smart Contract Advocates on Behalf of Digital Intelligence artworks, Smart Property (see also digital art) Ascribe, Monegraph: Online Graphics Protection autocitation, Blockchain Academic Publishing: Journalcoin automated digital asset protection, Digital Asset Proof as an Automated Feature automatic markets, Automatic Markets and Tradenets autonomy, Smart Contracts B bandwidth, Technical Challenges banking industry (see financial services) betting, Bitcoin Prediction Markets, Smart Contracts big data, Blockchain Layer Could Facilitate Big Data’s Predictive Task Automation .bit domains, Namecoin: Decentralized Domain Name System "Bitbank", Financial Services Bitcoin colored coins, Smart Property concept, Preface digital divide of, Digital Divide of Bitcoin M2M/IoT payment network, M2M/IoT Bitcoin Payment Network to Enable the Machine Economy MOOCs, Blockchain Learning: Bitcoin MOOCs and Smart Contract Literacy neutrality, Blockchain Neutrality origins and applications overview, What Is Bitcoin?


pages: 161 words: 44,488

The Business Blockchain: Promise, Practice, and Application of the Next Internet Technology by William Mougayar

Airbnb, airport security, Albert Einstein, altcoin, Amazon Web Services, bitcoin, Black Swan, blockchain, business process, centralized clearinghouse, Clayton Christensen, cloud computing, cryptocurrency, disintermediation, distributed ledger, Edward Snowden, en.wikipedia.org, Ethereum, ethereum blockchain, fault tolerance, fiat currency, fixed income, global value chain, Innovator's Dilemma, Internet of things, Kevin Kelly, Kickstarter, market clearing, Network effects, new economy, peer-to-peer, peer-to-peer lending, prediction markets, pull request, QR code, ride hailing / ride sharing, Satoshi Nakamoto, sharing economy, smart contracts, social web, software as a service, too big to fail, Turing complete, web application

Luckily, within a pure Bitcoin world, that potential global bank is you, if you are armed with a cryptocurrency wallet. A local cryptocurrency wallet skirts some of the legalities that existing banks and bank look-alikes (cryptocurrency exchanges) need to adhere to, but without breaking any laws. You take “your bank” with you wherever you travel, and as long as that wallet has local onramps and bridges into the non-cryptocurrency terrestrial world, then you have a version of a global bank in your pocket. This backdrop about the evolution of consumer-based cryptocurrency trading is important, because it demonstrates that we can achieve another form of connectedness by virtue of the blockchain itself, achieving a SWIFT-like3 effect. The 50 or so cryptocurrency exchanges that exist in various parts of the world are not overtly linked together, yet they are seamlessly connected by the blockchain.

One of the challenging issues with cryptocurrencies is their price volatility, which is enough to keep most consumers away. In a 2014 paper describing a method for stabilizing cryptocurrency, Robert Sams quoted Nick Szabo: “The main volatility in bitcoin comes from variability in speculation, which in turn is due to the genuine uncertainty about its future. More efficient liquidity mechanisms do not help reduce genuine uncertainty.” As cryptocurrency gains more acceptance and understanding, its future will be less uncertain, resulting in a more stable and gradual adoption curve. Cryptocurrency can have a “production” role for compensating miners who win rewards when they successfully validate transactions. Cryptocurrency can also have a “consumption” role when paying a small fee for running a smart contract (e.g., Ethereum’s ETH), or as a transaction fee equivalent (e.g., Ripple’s XRP or Bitcoin’s BTC).

In addition to venture capital, crowdfunding by self-issuing cryptocurrency or crypto-tokens is also another funding option. This approach carries some risks and uncertainty, due to lower external accountability controls. Although viable for certain cases, the success rates are not better than venture capital-funded startups. Volatility of Cryptocurrency Cryptocurrency volatility is a usage and confidence deterrent, but it is expected that volatility will gradually stabilize, tracking the increasing maturity and market adoption of the underlying technology behind each cryptocurrency. Eventually, bad actors and speculators will progressively become an insignificant minority with little to no impact on the overall health of cryptocurrencies. Onboarding New Users Most users cannot handle increased usage complexity, especially when the underlying technology is complex (the blockchain).


pages: 135 words: 26,407

How to DeFi by Coingecko, Darren Lau, Sze Jin Teh, Kristian Kho, Erina Azmi, Tm Lee, Bobby Ong

algorithmic trading, asset allocation, Bernie Madoff, bitcoin, blockchain, buy and hold, capital controls, collapse of Lehman Brothers, cryptocurrency, distributed ledger, diversification, Ethereum, ethereum blockchain, fiat currency, Firefox, information retrieval, litecoin, margin call, new economy, passive income, payday loans, peer-to-peer, prediction markets, QR code, reserve currency, smart contracts, tulip mania, two-sided market

This may be convenient as you do not need to worry about private key security but you only have to worry about account credentials security just like how you would have to protect your email account. However, by trusting a third party with your cryptocurrencies, you open yourself up to the risk of the custodian losing your cryptocurrencies through mismanagement or hacks. There have been numerous incidents of custodial wallets losing their cryptocurrencies with the most prominent example being Mt. Gox lost over 850,000 bitcoin worth over $450 million in 2014. By using a non-custodial wallet, you trust no external party and only yourself to ensure that your cryptocurrencies are safe. However, by using a non-custodial wallet, you pass the burden of security to yourself and you have to be fully equipped to store your private keys safely. If you lose your private keys, you will lose access to your cryptocurrencies too. At CoinGecko, we believe in the “not your keys, not your coin” mantra.

(Ameer Rosic) https://blockgeeks.com/guides/ethereum-gas/ The trillion-dollar case for ETH (Lucas Campbell) https://bankless.substack.com/p/the-trillion-dollar-case-for-eth-eb6 Ethereum: The Digital Finance Stack (David Hoffman) https://medium.com/pov-crypto/ethereum-the-digital-finance-stack-4ba988c6c14b Ether: A New Model for Money (David Hoffman) https://medium.com/pov-crypto/ether-a-new-model-for-money-17365b5535ba Chapter Four: Ethereum Wallets A wallet is a user-friendly interface to the blockchain network. It manages your private keys, which are basically keys to the lock on your cryptocurrencies’ vault. Wallets allow you to receive, store and send cryptocurrencies. ~ Custodial vs Non-Custodial There are two kinds of wallets, custodial and non-custodial wallets. Custodial wallets are wallets where third-parties keep and maintain control over your cryptocurrencies on your behalf. Non-custodial wallets are wallets where you take full control and ownership of your cryptocurrencies. This is similar to the mantra espoused by many people in the blockchain industry to “be your own bank”. By using a custodial wallet, you trust an external party to store your coins safely. This may be convenient as you do not need to worry about private key security but you only have to worry about account credentials security just like how you would have to protect your email account.

For example, you can use CoinGecko's API to fetch the current market price of cryptocurrencies on your website. B Buy and Hold This refers to a TokenSets trading strategy which realigns to its target allocation to prevent overexposure to one coin and spreads risk over multiple tokens. Bonding Curve A bonding curve is a mathematical curve that defines a dynamic relationship between price and token supply. Bonding curves act as an automated market maker where as the number of supply of a token decreases, the price of the token increases. It is useful as it helps buyers and sellers to access an instant market without the need of intermediaries. C Cryptocurrency Exchange (Cryptoexchange) It is a digital exchange that helps users exchange cryptocurrencies. For some exchanges, they also facilitate users to trade fiat currencies to cryptocurrencies. Custodian Custodian refers to the third party to have control over your assets.


pages: 309 words: 54,839

Attack of the 50 Foot Blockchain: Bitcoin, Blockchain, Ethereum & Smart Contracts by David Gerard

altcoin, Amazon Web Services, augmented reality, Bernie Madoff, bitcoin, blockchain, Blythe Masters, Bretton Woods, clean water, cloud computing, collateralized debt obligation, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, cryptocurrency, distributed ledger, Ethereum, ethereum blockchain, Extropian, fiat currency, financial innovation, Firefox, Flash crash, Fractional reserve banking, index fund, Internet Archive, Internet of things, Kickstarter, litecoin, M-Pesa, margin call, Network effects, peer-to-peer, Peter Thiel, pets.com, Ponzi scheme, Potemkin village, prediction markets, quantitative easing, RAND corporation, ransomware, Ray Kurzweil, Ross Ulbricht, Ruby on Rails, Satoshi Nakamoto, short selling, Silicon Valley, Silicon Valley ideology, Singularitarianism, slashdot, smart contracts, South Sea Bubble, tulip mania, Turing complete, Turing machine, WikiLeaks

Crypto: in this context, an abbreviation for cryptocurrency or crypto asset. In non-cryptocurrency use, the term is short for “cryptography.” Crypto asset: the general class of cryptographic things that aren’t necessarily cryptocurrency, but can be traded like it, e.g. tokens in a smart contract running on Ethereum. Cryptocurrency: Bitcoin and its various copies. Cypherpunks: a mailing list for cryptography enthusiasts against the forces of oppression, i.e. any government anywhere. Heavy on the anarcho-capitalism. Most of the ideas that became Bitcoin started here. DAO: see The DAO. Dapp: a “distributed application,” a fancy name for a smart contract in Ethereum. Darknet: sites only available via Tor, where you can buy illegal goods and services using a cryptocurrency. Distributed ledger technology: a euphemism for blockchain.

There are loose plans to move to Proof of Stake.296 (For a while during the second crypto bubble, you could actually make money mining ether on last year’s video card, which led to a small gold rush in the video cards themselves,297 and an ensuing glut of burnt-out cards on the second-hand market.) Ethereum’s pitch has always been ridiculously aspirational. It’s a “smart contracts platform,” it’s a “worldwide distributed computer,” at one point Wikipedia called it “Web 3.0,” at another a “publishing platform.” Anything other than a cryptocurrency. To this day, drive-by editors occasionally swing by the Ethereum article in Wikipedia to remove the word “cryptocurrency.” Of course, the cryptocurrency is overwhelmingly the main use, and that the cryptocurrency will go to the moon is the main hope. Ethereum has a block time of around 14 to 16 seconds (Bitcoin’s is 10 minutes). How do blocks make it across the network in that time? Well, often they don’t (though blocks only being a few kilobytes helps298). So there are about 7% valid but orphaned blocks.299 A miner can store up to two failed blocks in their block as “uncles,” and the miners of the blocks that became uncles get some reward too; Ethereum picks the highest-scoring chain, and uncles give a block a higher score.

By October 2016, Bitcoin regularly had around 40,000 unconfirmed transactions in the mempool at any time, and in May 2017 it peaked at 200,000.197 The possible solutions are: Increase the block size, which will increase centralisation even further – big blocks take longer to propagate, and the blockchain becomes even more unwieldy. (Though that ship really sailed in 2013). Sidechains: bolt on a completely different non-Bitcoin cryptocurrency, and do all the real transactions there. (This is presently vapourware.) It is unclear why anyone would create a usable alternate cryptocurrency then peg it to Bitcoin, rather than just use it in its own right. The Lightning Network: bolt on a completely different non-Bitcoin network, and do all the real transactions there. (This is also vapourware.) Use a different cryptocurrency that hasn’t clogged yet. (The darknets are exploring this option.) The Bitcoin community is now sufficiently dysfunctional that even such a simple proposal as “OK, let’s increase the block size to two megabytes” led to community schisms, code forks, retributive DDOS attacks, death threats,198 a split between the Chinese miners and the American core programmers … and plenty of other clear evidence that this and other problems in the Bitcoin protocol will never be fixed by a consensus process.


pages: 348 words: 97,277

The Truth Machine: The Blockchain and the Future of Everything by Paul Vigna, Michael J. Casey

3D printing, additive manufacturing, Airbnb, altcoin, Amazon Web Services, barriers to entry, basic income, Berlin Wall, Bernie Madoff, bitcoin, blockchain, blood diamonds, Blythe Masters, business process, buy and hold, carbon footprint, cashless society, cloud computing, computer age, computerized trading, conceptual framework, Credit Default Swap, crowdsourcing, cryptocurrency, cyber-physical system, dematerialisation, disintermediation, distributed ledger, Donald Trump, double entry bookkeeping, Edward Snowden, Elon Musk, Ethereum, ethereum blockchain, failed state, fault tolerance, fiat currency, financial innovation, financial intermediation, global supply chain, Hernando de Soto, hive mind, informal economy, intangible asset, Internet of things, Joi Ito, Kickstarter, linked data, litecoin, longitudinal study, Lyft, M-Pesa, Marc Andreessen, market clearing, mobile money, money: store of value / unit of account / medium of exchange, Network effects, off grid, pets.com, prediction markets, pre–internet, price mechanism, profit maximization, profit motive, ransomware, rent-seeking, RFID, ride hailing / ride sharing, Ross Ulbricht, Satoshi Nakamoto, self-driving car, sharing economy, Silicon Valley, smart contracts, smart meter, Snapchat, social web, software is eating the world, supply-chain management, Ted Nelson, the market place, too big to fail, trade route, transaction costs, Travis Kalanick, Turing complete, Uber and Lyft, uber lyft, unbanked and underbanked, underbanked, universal basic income, web of trust, zero-sum game

But Symbiont had jettisoned other Bitcoin features, including those that obviate the need for banks as payment intermediaries. Most notably, this system did not include its own native cryptocurrency for rewarding miners and for maintaining a permissionless system of validation. In essence, Symbiont was promising “blockchain without bitcoin”—it would maintain the fast, secure, and cheap distributed network model, and a truth machine at its center that validated transactions, but it was not leaderless, permissionless, and open to all. It was a blockchain that Wall Street could control. Whether it’s possible to separate bitcoin, ether, or any cryptocurrency from a blockchain is yet to be long-term tested. Some digital currency aficionados argue that stripping out the internal cryptocurrency would destroy the integrity of a blockchain. Without a native digital currency with which to reward and incentivize transaction validation, a permissionless network won’t arise, which falls short of what many see as the prerequisite for a truly decentralized system of value exchange.

Some of that money went to hire people like Mike Hearn, a once prominent Bitcoin developer who dramatically turned his back on the cryptocurrency community with an “I quit” blog post complaining about the bitter infighting. R3 also hired Ian Grigg—who later left to join EOS—another prominent onetime rebel from the cryptocurrency space. Leading its research team was the ever-thoughtful and well-regarded full-time IBM blockchain guru Richard Gendal-Brown. These were serious engineering hires. Before their arrival, R3 had also signed on Tim Swanson as research director. Swanson was a distributed ledger/blockchain analyst who was briefly enthused by Bitcoin but who later became disillusioned with the cryptocurrency’s ideologues. He became a vocal, anti-Bitcoin gadfly who seemed to delight in mocking its travails. Of a similar breed was Preston Byrne, the general counsel of Eris Ltd., later called Monax, which designed private blockchains for banks and a variety of other companies.

The book’s title uses the definite article form to acknowledge the catalytic role that the original Bitcoin blockchain played in unleashing this field. *For background on the Cypherpunk movement from the San Francisco Bay Area and the role it played in the development of cryptocurrencies, see our previous book, The Age of Cryptocurrency. *A noteworthy caveat is that, if and when scientists create a truly functioning quantum computer, this level of cryptography could indeed be crackable. But that idea is not only a long way off; if it were to arrive, it would render all cybersecurity systems, not just Bitcoin’s, unworkable. Nonetheless, cryptocurrency designers are already working on quantum-proof systems that, in theory, will resist quantum attacks.


pages: 416 words: 106,532

Cryptoassets: The Innovative Investor's Guide to Bitcoin and Beyond: The Innovative Investor's Guide to Bitcoin and Beyond by Chris Burniske, Jack Tatar

Airbnb, altcoin, asset allocation, asset-backed security, autonomous vehicles, bitcoin, blockchain, Blythe Masters, business cycle, business process, buy and hold, capital controls, Carmen Reinhart, Clayton Christensen, clean water, cloud computing, collateralized debt obligation, commoditize, correlation coefficient, creative destruction, Credit Default Swap, credit default swaps / collateralized debt obligations, cryptocurrency, disintermediation, distributed ledger, diversification, diversified portfolio, Donald Trump, Elon Musk, en.wikipedia.org, Ethereum, ethereum blockchain, fiat currency, financial innovation, fixed income, George Gilder, Google Hangouts, high net worth, Jeff Bezos, Kenneth Rogoff, Kickstarter, Leonard Kleinrock, litecoin, Marc Andreessen, Mark Zuckerberg, market bubble, money market fund, money: store of value / unit of account / medium of exchange, moral hazard, Network effects, packet switching, passive investing, peer-to-peer, peer-to-peer lending, Peter Thiel, pets.com, Ponzi scheme, prediction markets, quantitative easing, RAND corporation, random walk, Renaissance Technologies, risk tolerance, risk-adjusted returns, Robert Shiller, Robert Shiller, Ross Ulbricht, Satoshi Nakamoto, Sharpe ratio, Silicon Valley, Simon Singh, Skype, smart contracts, social web, South Sea Bubble, Steve Jobs, transaction costs, tulip mania, Turing complete, Uber for X, Vanguard fund, WikiLeaks, Y2K

Then a scandal hit and the prime minister was forced to resign because of his involvement with the Panama Papers.44 This led to the growth in popularity of a political party known as the Pirate Party, which had a favorable view on cryptocurrencies.45 Suddenly there was speculation46 that Iceland could revisit the potential for Auroracoin and its role as a national cryptocurrency.47 As acceptance grows and politics change, it will be interesting to watch what happens next for the Icelandic cryptocurrency. Auroracoin is a cautionary tale for both investors and developers. What began as a seemingly powerful and compelling use case for a cryptoasset suffered from its inability to provide value to the audience it sought to impact. Icelanders were given a cryptocurrency with little education and means to use it. Unsurprisingly, the value of the asset collapsed and most considered it dead. Nevertheless, cryptocurrencies rarely die entirely, and Auroracoin may have interesting times ahead if its developer team can figure out a way forward.

This bizarre merger of a cryptoasset and pop culture is not surprising considering 2013 was the year that the price of bitcoin ranged from $13 in January to over $1,000 in early December.39 The power and enthusiasm of Dogecoin’s user community shouldn’t be dismissed, even if we encourage the innovative investor to do ample due diligence on it as an investment. While Dogecoin had its flaws, it continues to exist and has taught the cryptocurrency space valuable lessons about gathering community support in an Internet era. AURORACOIN: ICELAND’S NATIONAL CRYPTOCURRENCY? Much like the anonymous Satoshi, Auroracoin’s creator also had a fictitious name: Baldur Friggjar Óðinsson. Baldur created Auroracoin based on Litecoin’s code and decided to “air-drop” the cryptocurrency to Icelanders with the intent of providing 50 percent of all auroracoin in existence to residents. The hope was that such a distribution would jump-start national use of the cryptocurrency. A key to Baldur’s plan was his access to the government’s national identification system, which led speculators to believe mistakenly that Auroracoin was sponsored by the Icelandic government.

By the end of 2016, Monero had the fifth largest network value of any cryptocurrency and was the top performing digital currency in 2016, with a price increase over the year of 2,760 percent. This clearly demonstrates the level of interest in privacy protecting cryptocurrency. Some of that interest, no doubt, comes from less than savory sources. Dash Another cryptocurrency targeting privacy and fungibility is Dash. It launched its blockchain a few months before Monero, on January 19, 2014. Its lead developer, Evan Duffield, created Dash by forking the Bitcoin protocol and implementing a coin focused on privacy and speedy settlement of transactions. The Dash white paper that Duffield coauthored outlined his intent: A crypto-currency based on Bitcoin, the work of Satoshi Nakamoto, with various improvements such as a two-tier incentivized network, known as the Masternode network.


Mastering Blockchain, Second Edition by Imran Bashir

3D printing, altcoin, augmented reality, autonomous vehicles, bitcoin, blockchain, business process, carbon footprint, centralized clearinghouse, cloud computing, connected car, cryptocurrency, data acquisition, Debian, disintermediation, disruptive innovation, distributed ledger, domain-specific language, en.wikipedia.org, Ethereum, ethereum blockchain, fault tolerance, fiat currency, Firefox, full stack developer, general-purpose programming language, gravity well, interest rate swap, Internet of things, litecoin, loose coupling, MITM: man-in-the-middle, MVC pattern, Network effects, new economy, node package manager, Oculus Rift, peer-to-peer, platform as a service, prediction markets, QR code, RAND corporation, Real Time Gross Settlement, reversible computing, RFC: Request For Comment, RFID, ride hailing / ride sharing, Satoshi Nakamoto, single page application, smart cities, smart contracts, smart grid, smart meter, supply-chain management, transaction costs, Turing complete, Turing machine, web application, x509 certificate

Another difference is that ICOs by design usually require investors to invest using cryptocurrencies and payouts are paid using cryptocurrencies, most commonly this is the new token (a new cryptocurrency) introduced by the ICO. This can also be Fiat currency, but most commonly cryptocurrency is used. For example, in the Ethereum crowdfunding campaign a new token, Ether was introduced. The name token sale for crowdfunding is also quite popular and both terms are used interchangeably. ICO are also called crowd sales. When a new blockchain based application or organization is launched, a new token can be launched with it as a token to access and use the application and also to gain incentives that are paid in the very same token that has been introduced by the ICO. This token is released to the public in exchange of some already established cryptocurrency (for example, Bitcoin or Ethereum) or Fiat currency.

In addition to Tier 1, Tier 2 and Tier 3, or Tier X in the future, the following represents my own vision of what blockchain technology eventually could become as this technology advances: Blockchain 1.0: This tier was introduced with the invention of Bitcoin, and it is primarily used for cryptocurrencies. Also, as Bitcoin was the first implementation of cryptocurrencies, it makes sense to categorize this first generation of blockchain technology to include only cryptographic currencies. All alternative cryptocurrencies as well as Bitcoin fall into this category. It includes core applications such as payments and applications. This generation started in 2009 when Bitcoin was released and ended in early 2010. Blockchain 2.0: This second blockchain generation is used by financial services and smart contracts.

Smart contracts can be programmed to perform any actions that blockchain users need and according to their specific business requirements. Transferring value between peers: Blockchain enables the transfer of value between its users via tokens. Tokens can be thought of as a carrier of value. Generation of cryptocurrency: This feature is optional depending on the type of blockchain in use. A blockchain can create cryptocurrency as an incentive to its miners who validate the transactions and spend resources to secure the blockchain. We will discuss cryptocurrencies in great detail in Chapter 5, Introducing Bitcoin. Smart property: It is now possible to link a digital or physical asset to the blockchain in such a secure and precise manner that it cannot be claimed by anyone else. You are in full control of your asset, and it cannot be double-spent or double-owned.


pages: 218 words: 68,648

Confessions of a Crypto Millionaire: My Unlikely Escape From Corporate America by Dan Conway

Affordable Care Act / Obamacare, Airbnb, bank run, basic income, bitcoin, blockchain, buy and hold, cloud computing, cognitive dissonance, corporate governance, crowdsourcing, cryptocurrency, disruptive innovation, distributed ledger, double entry bookkeeping, Ethereum, ethereum blockchain, fault tolerance, financial independence, gig economy, Gordon Gekko, Haight Ashbury, high net worth, job satisfaction, litecoin, Marc Andreessen, Mitch Kapor, obamacare, offshore financial centre, Ponzi scheme, prediction markets, rent control, reserve currency, Ronald Coase, Satoshi Nakamoto, Silicon Valley, smart contracts, Steve Jobs, supercomputer in your pocket, Turing complete, Uber for X, universal basic income, upwardly mobile

I wrote about how blockchain could prevent fraud and embezzlement (“Organized Crime Hates Ethereum”), cut the bullshit and bring back integrity (“Your Sourpuss Grandpa Will Love Blockchain”), simplify and verify medical records (“Presidential Health on the Blockchain”), and prevent data breaches (“Yahoo’s Data Breach and the $12B Antidote”). I also wrote a piece with recommendations for PR professionals working in crypto (“Mainstream PR, Meet Cryptocurrency”) as if I were a grizzled veteran rather than someone figuring out if I could make a living in the space. Through one of Eileen’s contacts at the venture capital firm Redpoint, I won my first crypto account, a well-known and respected early cryptocurrency wallet company called BitGo. Their CEO, Mike Belshe, was a sharp pioneer in the space. I impressed him with my knowledge of the cryptocurrency universe, which by that time was extensive, up to a certain technical point. He brought me aboard to work on an upcoming launch. Eileen and I were relieved. We had no idea if projects and companies in this space would pay for PR until they did.

In a few instances, I’ve changed identifying details for these people and families to further screen their identities. Although I write in detail about my experiences in cryptocurrency and other financial and business matters, this is a memoir and a commentary rather than a book of business advice. Readers who are seeking information and advice about business matters should consult resources other than this book. As a style point, throughout this book I capitalize Bitcoin and Ethereum when I refer to their blockchains. I do not capitalize bitcoin and ether when I refer to these currencies. Prologue When the Financial Times interviewed me for a story about cryptocurrency millionaires in March 2018, I told them the unvarnished truth: “I invested because I wanted the underdogs to win, for once—losers like me who didn’t make the rules and didn’t have the money… We’d been forced to tweet corporate philanthropy hashtags, and we weren’t going to take it anymore.”

Nor was I able to follow a path leading me away from corporate America. Throughout my career, escape was always on my mind, though I had limited means to achieve it. Then I discovered Bitcoin and Ethereum, technologies based on an entirely new organizing principle. A priesthood of true believers said cryptocurrencies could disrupt the banks, corporations, and other organizations that ran society. Or at least provide an alternative to them. I could fund these networks by buying bitcoin and ether, the cryptocurrencies that power their blockchains. I could help change the world and get rich ... not necessarily in that order. The Onion has created a helpful guide to this new technology. It begins with a simple Q&A: Q: What is Blockchain? A: Do you want to talk science shit or do you want to make some fucking money?


pages: 960 words: 125,049

Mastering Ethereum: Building Smart Contracts and DApps by Andreas M. Antonopoulos, Gavin Wood Ph. D.

Amazon Web Services, bitcoin, blockchain, continuous integration, cryptocurrency, Debian, domain-specific language, don't repeat yourself, Edward Snowden, en.wikipedia.org, Ethereum, ethereum blockchain, fault tolerance, fiat currency, Firefox, Google Chrome, intangible asset, Internet of things, litecoin, move fast and break things, move fast and break things, node package manager, peer-to-peer, Ponzi scheme, prediction markets, pull request, QR code, Ruby on Rails, Satoshi Nakamoto, sealed-bid auction, sharing economy, side project, smart contracts, transaction costs, Turing complete, Turing machine, Vickrey auction, web application, WebSocket

In summary, the use of a recovery word list to encode the seed for an HD wallet makes for the easiest way to safely export, transcribe, record on paper, read without error, and import a private key set into another wallet. Wallet Best Practices As cryptocurrency wallet technology has matured, certain common industry standards have emerged that make wallets broadly interoperable, easy to use, secure, and flexible. These standards also allow wallets to derive keys for multiple different cryptocurrencies, all from a single mnemonic. These common standards are: Mnemonic code words, based on BIP-39 HD wallets, based on BIP-32 Multipurpose HD wallet structure, based on BIP-43 Multicurrency and multiaccount wallets, based on BIP-44 These standards may change or be obsoleted by future developments, but for now they form a set of interlocking technologies that have become the de facto wallet standard for most blockchain platforms and their cryptocurrencies. The standards have been adopted by a broad range of software and hardware wallets, making all these wallets interoperable.

contract data type, Contract Definition contract definition, Solidity, Contract Definition contract destruction, Contract Constructor and selfdestruct contract invocation, Transmitting a Data Payload to an EOA or Contract contract name modification/constructor security threatpreventative techniques, Preventative Techniques real-world example: Rubixi, Real-World Example: Rubixi vulnerability, The Vulnerability contract object, Contract Inheritance-Contract Inheritance convert function (Vyper), Variable Typecasting counterparty risk, Counterparty Risk cryplet, Computation Oracles cryptographic hash functions, Cryptographic Hash Functions-Which Hash Function Am I Using? cryptography, Cryptography-Conclusionsasymmetric (see public key cryptography) defined, Cryptography Ethereum addresses and, Ethereum Addresses-Detecting an error in an EIP-55 encoded address hash functions, Cryptographic Hash Functions-Which Hash Function Am I Using? keys and addresses, Keys and Addresses public key cryptography and cryptocurrency, Public Key Cryptography and Cryptocurrency-Public Key Cryptography and Cryptocurrency public keys, Public Keys-Elliptic Curve Libraries CryptoRoulette honey pot, Real-World Examples: OpenAddressLottery and CryptoRoulette Honey Pots currency units, Ether Currency Units D DAG (directed acyclic graph), Ethash: Ethereum’s Proof-of-Work Algorithm Dagger-Hashimoto algorithm, Ethash: Ethereum’s Proof-of-Work Algorithm DAO (Decentralized Autonomous Organization), Ethereum’s Four Stages of Development, The Decentralized Autonomous Organization (The DAO)-Timeline of the DAO Hard Forkabout, The Decentralized Autonomous Organization (The DAO) and Ethereum Classic origins, Ethereum Classic (ETC) defined, Quick Glossary hard fork, The DAO Hard Fork-Timeline of the DAO Hard Fork reentrancy attack, Real-World Example: The DAO, DApp governance Dapp, Testing Smart Contracts dapp.tools, dapp.tools DApps (decentralized applications), Decentralized Applications (DApps)-ConclusionsAuction DApp example, A Basic DApp Example: Auction DApp-From App to DApp(see also Auction DApp) backend (smart contract), Backend (Smart Contract) data storage, Data Storage decentralized message communication protocols, Decentralized Message Communications Protocols defined, Quick Glossary elements of, What Is a DApp?

Unlike with Bitcoin, orphaned blocks in Ethereum can be included by newer blocks as ommers and receive a partial block reward. The term “ommer” is the preferred gender-neutral term for the sibling of a parent node, but this is also sometimes referred to as an “uncle.” Parity One of the most prominent interoperable implementations of the Ethereum client software. Private key See “secret key.” Proof of stake (PoS) A method by which a cryptocurrency blockchain protocol aims to achieve distributed consensus. PoS asks users to prove ownership of a certain amount of cryptocurrency (their “stake” in the network) in order to be able to participate in the validation of transactions. Proof of work (PoW) A piece of data (the proof) that requires significant computation to find. In Ethereum, miners must find a numeric solution to the Ethash algorithm that meets a network-wide difficulty target. Public key A number, derived via a one-way function from a private key, which can be shared publicly and used by anyone to verify a digital signature made with the corresponding private key.


pages: 275 words: 84,980

Before Babylon, Beyond Bitcoin: From Money That We Understand to Money That Understands Us (Perspectives) by David Birch

agricultural Revolution, Airbnb, bank run, banks create money, bitcoin, blockchain, Bretton Woods, British Empire, Broken windows theory, Burning Man, business cycle, capital controls, cashless society, Clayton Christensen, clockwork universe, creative destruction, credit crunch, cross-subsidies, crowdsourcing, cryptocurrency, David Graeber, dematerialisation, Diane Coyle, disruptive innovation, distributed ledger, double entry bookkeeping, Ethereum, ethereum blockchain, facts on the ground, fault tolerance, fiat currency, financial exclusion, financial innovation, financial intermediation, floating exchange rates, Fractional reserve banking, index card, informal economy, Internet of things, invention of the printing press, invention of the telegraph, invention of the telephone, invisible hand, Irish bank strikes, Isaac Newton, Jane Jacobs, Kenneth Rogoff, knowledge economy, Kuwabatake Sanjuro: assassination market, large denomination, M-Pesa, market clearing, market fundamentalism, Marshall McLuhan, Martin Wolf, mobile money, money: store of value / unit of account / medium of exchange, new economy, Northern Rock, Pingit, prediction markets, price stability, QR code, quantitative easing, railway mania, Ralph Waldo Emerson, Real Time Gross Settlement, reserve currency, Satoshi Nakamoto, seigniorage, Silicon Valley, smart contracts, social graph, special drawing rights, technoutopianism, the payments system, The Wealth of Nations by Adam Smith, too big to fail, transaction costs, tulip mania, wage slave, Washington Consensus, wikimedia commons

Chapter 13 Counting on cryptography A purely peer-to-peer version of electronic cash would allow online payments to be sent directly from one party to another without going through a financial institution. — ‘Satoshi Nakamoto’ (2008) Having said earlier that the iconic technology of money is the plastic card, right now the iconic money of the future seems to be cryptocurrency. Spurred on by the widespread interest in Bitcoin, there are many people looking at the concept and wondering whether cryptocurrency – money that depends on cryptography rather than the belief of a community – might be a feature in the emerging money landscape. There are, of course, cryptocurrencies other than Bitcoin and cryptocurrencies that are yet to be invented (Birch 2015), but if we use Bitcoin as the case study then it seems the jury is out. Stefan Brands, a leading cryptographer and one of the pioneers of digital currency, describes Bitcoin as ‘clever’ and is loath to denigrate it, but he believes that, fundamentally, it is structured like ‘a pyramid scheme’ that rewards early adopters (Wallace 2011) – a charge also levelled by other observers of the financial markets (Robinson 2014).

The post-industrial economy needs a new kind of money, not one devised by representatives of the status quo, and it won’t be the single galactic currency of science fiction imagination (we can’t even make a single currency work between Germany and Greece, let alone between Ganymede and Gamma Centauri) but thousands, even millions, of currencies. Crypto-alternatives Not only will there be cryptocurrencies beyond Bitcoin and not only will they be better – more powerful and more efficient – there will also be a great many of them as the cost of launching a digital currency falls. Without launching into a treatise on cryptocurrencies, I think it would be useful to take a quick look at a couple of the newer cryptocurrencies on the block (pun intended) to give a sense of the spectrum of possibilities. Ethereum Ethereum is comparable to Bitcoin, in that it uses a blockchain, but it was designed to provide a better platform for shared ledger applications.

Participants can therefore choose which other participants they want to include in their ‘consensus quorum’ (Kelleher 2015). Rather than target consumers, Ripple targets banks, positioning itself as an efficient intermediary for payments, remittances and cross-border exchanges. It makes payments using its native cryptocurrency, ‘the ripple’ (XRP), by having users make digitally signed updates to its ledger and leaves the users to determine which other users they do or not trust for the purposes of consensus. Zcash As I write, at the end of 2016, the newest kid on the block is Zcash: a cryptocurrency with the added special sauce of genuine anonymity, rather than the pseudonymity that got some people into trouble when they used the Satoshi system for various nefarious purposes. The claim of Zcash’s founders is that it is true electronic cash because it shares the characteristics of cash, such as fungibility.


pages: 273 words: 72,024

Bitcoin for the Befuddled by Conrad Barski

Airbnb, AltaVista, altcoin, bitcoin, blockchain, buttonwood tree, cryptocurrency, Debian, en.wikipedia.org, Ethereum, ethereum blockchain, fiat currency, Isaac Newton, MITM: man-in-the-middle, money: store of value / unit of account / medium of exchange, Network effects, node package manager, p-value, peer-to-peer, price discovery process, QR code, Satoshi Nakamoto, self-driving car, SETI@home, software as a service, the payments system, Yogi Berra

If Bitcoin volatility continues to decrease, this trend may give Bitcoin a significant advantage over future cryptocurrencies: Because Bitcoin is guaranteed to be the oldest cryptocurrency, new currencies might be unable to catch up in this “volatility race,” and Bitcoin will always remain less volatile than upstarts. If Bitcoin maintains advantages in terms of network effects and volatility, it may make sense for new cryptocurrencies to use pegging to link themselves to the Bitcoin network instead of trying to replace the Bitcoin network entirely. Recently, two well-known cryptocurrency developers and entrepreneurs, Adam Back and Austin Hill, have suggested that the value of new cryptocurrencies could be directly linked one-to-one with the value of a bitcoin by using cryptography to allow coins to “ jump” between block-chains using clever algorithms.

Recently, two well-known cryptocurrency developers and entrepreneurs, Adam Back and Austin Hill, have suggested that the value of new cryptocurrencies could be directly linked one-to-one with the value of a bitcoin by using cryptography to allow coins to “ jump” between block-chains using clever algorithms. If this idea succeeds, it may be possible to create cryptocurrencies with new technological advancements into side chains of Bitcoin. Side chains are separate blockchains with different rules that share the same pool of coins as Bitcoin, allowing the new currency to share the same volatility (or lack thereof, potentially) and network benefits as Bitcoin proper. If the side chain idea (or a similar peg-based idea) is successful, future cryptocurrencies would benefit from Bitcoin’s existence and even augment it rather than replace it. For these reasons, Bitcoin might never be entirely replaced by other cryptocurrencies. That being said, if a cryptocurrency is created that really is so much better than Bitcoin that we all switch, that wouldn’t really be a bad outcome, would it?

Of course, we have no way of knowing what fantastic features a new currency would need such that it could supplant Bitcoin. However, three main reasons exist to believe that Bitcoin may be able survive the onslaught of newcomers: network effects, the nature of cryptocurrency volatility, and the recent development of cryptocurrency-pegging technology. The network effect is the simple concept that people want to use a currency only if other people will accept it as payment. The more users a currency has, the more useful it is. This creates a natural barrier for the adoption of new currencies (and certainly has hindered the adoption of Bitcoin relative to traditional currencies in its first few years). Currently, Bitcoin has the largest adoption of any cryptocurrency, so newer ones would need to have easily distinguishable advantages over Bitcoin to overcome its network advantage. But how does volatility factor in?


pages: 218 words: 62,889

Sabotage: The Financial System's Nasty Business by Anastasia Nesvetailova, Ronen Palan

algorithmic trading, bank run, banking crisis, barriers to entry, Basel III, Bernie Sanders, big-box store, bitcoin, Black-Scholes formula, blockchain, Blythe Masters, bonus culture, Bretton Woods, business process, collateralized debt obligation, corporate raider, Credit Default Swap, credit default swaps / collateralized debt obligations, cryptocurrency, distributed ledger, diversification, Double Irish / Dutch Sandwich, en.wikipedia.org, Eugene Fama: efficient market hypothesis, financial innovation, financial intermediation, financial repression, fixed income, gig economy, Gordon Gekko, high net worth, Hyman Minsky, information asymmetry, interest rate derivative, interest rate swap, Joseph Schumpeter, Kenneth Arrow, litecoin, London Interbank Offered Rate, London Whale, Long Term Capital Management, margin call, market fundamentalism, mortgage debt, new economy, Northern Rock, offshore financial centre, Paul Samuelson, peer-to-peer lending, plutocrats, Plutocrats, Ponzi scheme, price mechanism, regulatory arbitrage, rent-seeking, reserve currency, Ross Ulbricht, shareholder value, short selling, smart contracts, sovereign wealth fund, Thorstein Veblen, too big to fail

While some markets centred in London have achieved great efficiencies in terms of liquidity and scale (for instance, in foreign exchange trading), the network of city-based financial institutions, as well as law and accounting firms, has been essential to making possible schemes that play a key role in regulatory arbitrage, tax avoidance and money laundering. Cryptocurrencies have the potential to become ‘super tax havens’.6 In fact evidence suggests that they already are. To date there exist no effective enforcement mechanisms to track the online movement of bitcoins or other cryptocurrencies. According to one estimate, if even 1 per cent of funds currently sitting in offshore accounts were transferred into bitcoin, the value of this virtual currency would grow exponentially. Since the number of bitcoins in circulation is currently capped at twenty-one million, if these billions of offshore dollars migrate to that cryptocurrency, the worth of a single bitcoin could rise to nearly $3m.7 E-wallets exist in no physical location, are not subject to taxation at the source, and do not require the assistance of expensive financial intermediaries such as Mossack Fonseca to administer.

Moreover, there are no government officials in sight, intent on padding their own pockets and building their own little bureaucratic empires. Is it not what free-market capitalism is all about? The problem with bitcoin and other copycat cryptocurrencies, Kaminska argues, lies in the security/access paradox. ‘If the sector is easily accessible (highly competitive) it’s not secure, and if it’s secure it’s not easily accessible. Put differently, the more entrants there are, the easier it is for criminal enterprises to exploit the sector for their own ends.’15 And that is exactly what is happening in the cryptocurrency space. Or worse. Serious crime, such as child pornography, and drugs and arms trading, are attracted to cryptocurrencies because of its efficiency, secrecy and speed. Petty crime, like selling medicine online or ghost-writing essays for inept students, also uses crypto for secrecy.16 Blockchain-based innovations have become the favourite method of payment in the criminal underworld.

‘As a steroid dealer and user… I think of bitcoin as the solution to the problem of illegal tender, our so-called “paper money” economy,’ says a personal trainer who accepts the cryptocurrency in payment for his pharmaceutical services. When informed that the sixteenth Amendment of the US Constitution allows the federal government to tax all income from whatever source derived, the trainer shrugged. ‘I don’t believe in that… I never signed or accepted the Constitution, but bitcoin is real. It’s real money and it can’t be stolen from me.’19 The IRS successfully sued Coinbase, a leading cryptocurrency exchange, to gain access to its customer records. The IRS showed the court that only 802 people reported gains or losses from Bitcoin in 2015. (The court ordered Coinbase to identify more than 14,000 customer accounts to the IRS.) In one survey of more than 2,000 American cryptocurrency owners some 57 per cent of respondents said they’d realized gains on their crypto investments, that is, profits the IRS considers taxable.20 Fifty-nine per cent of Americans said they had never reported any such gains to the IRS.21 Data from one popular tax preparation service shows that only a minuscule proportion – just 0.04 per cent – of US tax filers reported cryptocurrency gains or losses to the IRS in the first half of 2018.


pages: 361 words: 97,787

The Curse of Cash by Kenneth S Rogoff

Andrei Shleifer, Asian financial crisis, bank run, Ben Bernanke: helicopter money, Berlin Wall, bitcoin, blockchain, Boris Johnson, Bretton Woods, business cycle, capital controls, Carmen Reinhart, cashless society, central bank independence, cryptocurrency, debt deflation, disruptive innovation, distributed ledger, Edward Snowden, Ethereum, ethereum blockchain, eurozone crisis, Fall of the Berlin Wall, fiat currency, financial exclusion, financial intermediation, financial repression, forward guidance, frictionless, full employment, George Akerlof, German hyperinflation, illegal immigration, inflation targeting, informal economy, interest rate swap, Isaac Newton, Johann Wolfgang von Goethe, Johannes Kepler, Kenneth Rogoff, labor-force participation, large denomination, liquidity trap, money market fund, money: store of value / unit of account / medium of exchange, moral hazard, moveable type in China, New Economic Geography, offshore financial centre, oil shock, open economy, payday loans, price stability, purchasing power parity, quantitative easing, RAND corporation, RFID, savings glut, secular stagnation, seigniorage, The Great Moderation, the payments system, The Rise and Fall of American Growth, transaction costs, unbanked and underbanked, unconventional monetary instruments, underbanked, unorthodox policies, Y2K, yield curve

A lot of truly fascinating science supports the different systems, and one can find many excellent treatments.2 Governments around the world have already begun regulating cryptocurrencies more aggressively. In the United States, Bitcoin wallets must now comply with anti-money-laundering rules, and the Internal Revenue Service has begun to issue rulings on how Bitcoin earnings should be taxed. The European Union, too, is in the process of intensifying its regulations. Where governments have the greatest leverage is in regulating how financial institutions interact with cryptocurrencies. In China, although trading in cryptocurrencies between individuals is legal at present, financial institutions are proscribed from buying, selling, and insuring these currencies or any derivative products. Advanced countries have temporarily taken a more hands-off approach, but this will not last forever.

They have deep conviction that with encrypted digital currencies like Bitcoin, someday no one will have to trust banks, either. For true believers in the promise of cryptocurrencies, trying to find ways of improving the current system, as this book aims to do, is a waste of time. Better to fast-forward to the brave new world where governments are no longer in the payments picture and no longer even control the unit of account. With all due respect to promising security advances offered by public ledger technology and the ingenious algorithms embodied in some of the new “currencies,” the view that Bitcoin—or any other cryptocurrency—is going to replace the dollar anytime soon is quite naive. As currency innovators have learned over the millennia, it is hard to stay on top of the government indefinitely in a game where the latter can keep adjusting the rules until it wins.

In the extreme, the quantitative effect of a Bencoin on banks’ lending capacities could be absolutely as dramatic as the Chicago plan (chapter 6) that effectively forces all private money substitutes to be 100% backed by government debt. Much would depend on regulation, however, including what alternatives private financial institutions were allowed to offer. CRYPTOCURRENCIES AND PRIVACY You might be wondering why I have framed the discussion of cryptocurrencies in terms of their security protocol and not their privacy features. It is true that much of the early publicity for Bitcoin surrounded dodgy retail merchants or underworld marketplaces, such as Silk Road, but the landscape is constantly evolving. For example, for many years, people regarded Bitcoin as a way to do anonymous transactions that the government can never detect.


pages: 304 words: 91,566

Bitcoin Billionaires: A True Story of Genius, Betrayal, and Redemption by Ben Mezrich

"side hustle", airport security, Albert Einstein, bank run, Ben Horowitz, bitcoin, blockchain, Burning Man, buttonwood tree, cryptocurrency, East Village, El Camino Real, Elon Musk, family office, fault tolerance, fiat currency, financial innovation, game design, Isaac Newton, Marc Andreessen, Mark Zuckerberg, Menlo Park, Metcalfe’s law, new economy, offshore financial centre, paypal mafia, peer-to-peer, Peter Thiel, Ponzi scheme, QR code, Ronald Reagan, Ross Ulbricht, Sand Hill Road, Satoshi Nakamoto, Schrödinger's Cat, self-driving car, side project, Silicon Valley, Skype, smart contracts, South of Market, San Francisco, Steve Jobs, transaction costs, zero-sum game

Epilogue WHERE ARE THEY NOW … ? Much as The Accidental Billionaires and The Social Network strove to tell the story of Facebook’s founding—that first year of inception and adoption—Bitcoin Billionaires is an origin story, both of the characters within these pages, and of the cryptocurrency itself. We’ve watched Facebook grow and change over the past decade, and similarly, it will be interesting to see where Bitcoin goes. In my opinion, the story of this new era of cryptocurrencies is just beginning. One of the greatest strikes against cryptocurrencies has always been their volatility, which the past year has only served to highlight. Since I started writing this book, the price of Bitcoin has declined more than seventy percent; at the same time, the crypto industry has grown by leaps and bounds, with new companies aimed at servicing, profiting from, and building on this novel technology that springs up every day.

A huge voice in the crypto world and a controversial figure online (with over half a million followers on Twitter), at the moment Ver is involved in what has essentially been described as a civil war in the Bitcoin community; Ver and a group of like-minded Bitcoiners have broken off to form “Bitcoin Cash,” which takes the cryptocurrency in a different direction in terms of scaling and block size, with a goal of turning it into something that could more easily supplant cash. Ver continues to invest in crypto-related companies and spends much of his time running Bitcoin.com, whose team has recently surpassed a hundred people. Bitcoin.com endeavors to build the tools to allow anyone to interact financially and without government supervision with everyone else in the world. * * * Erik Voorhees currently resides in Denver, Colorado, and is the CEO and founder of a cryptocurrency exchange company called Shapeshift, which allows customers to exchange one form of cryptocurrency for another instantaneously. Originally, the company did not collect personal data on its users, or hold any of the currencies in its accounts.

An article in the Wall Street Journal published September 28, 2018, entitled “How Dirty Money Disappears into the Black Hole of Cryptocurrency,” alleged that as much as $9 million in illegally obtained funds had been “laundered” through Shapeshift, as part of $88.6 million of fraudulent funds moving through a total of forty-six crypto exchanges; Voorhees refuted the report, maintaining that Shapeshift uses “blockchain forensics” to weed out money launderers and that Wall Street Journal’s reporters didn’t understand the data. * * * After being introduced to Bitcoin by the Winklevoss twins, banking heir Matthew Mellon rapidly became one of cryptocurrencies’ biggest advocates, building a massive fortune first in Bitcoin, then in the cryptocurrency XRP—a digital currency developed by the company Ripple in 2012. On April 16, 2018, at the age of fifty-four, Matthew Mellon passed away suddenly on the way to a drug rehab center in Cancun, Mexico, where he hoped to overcome an opioid dependency.


pages: 170 words: 49,193

The People vs Tech: How the Internet Is Killing Democracy (And How We Save It) by Jamie Bartlett

Ada Lovelace, Airbnb, Amazon Mechanical Turk, Andrew Keen, autonomous vehicles, barriers to entry, basic income, Bernie Sanders, bitcoin, blockchain, Boris Johnson, central bank independence, Chelsea Manning, cloud computing, computer vision, creative destruction, cryptocurrency, Daniel Kahneman / Amos Tversky, Dominic Cummings, Donald Trump, Edward Snowden, Elon Musk, Filter Bubble, future of work, gig economy, global village, Google bus, hive mind, Howard Rheingold, information retrieval, Internet of things, Jeff Bezos, job automation, John Maynard Keynes: technological unemployment, Julian Assange, manufacturing employment, Mark Zuckerberg, Marshall McLuhan, Menlo Park, meta analysis, meta-analysis, mittelstand, move fast and break things, move fast and break things, Network effects, Nicholas Carr, off grid, Panopticon Jeremy Bentham, payday loans, Peter Thiel, prediction markets, QR code, ransomware, Ray Kurzweil, recommendation engine, Renaissance Technologies, ride hailing / ride sharing, Robert Mercer, Ross Ulbricht, Sam Altman, Satoshi Nakamoto, Second Machine Age, sharing economy, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, smart cities, smart contracts, smart meter, Snapchat, Stanford prison experiment, Steve Jobs, Steven Levy, strong AI, TaskRabbit, technological singularity, technoutopianism, Ted Kaczynski, the medium is the message, the scientific method, The Spirit Level, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, theory of mind, too big to fail, ultimatum game, universal basic income, WikiLeaks, World Values Survey, Y Combinator

I don’t think our current banking system is perfect, but if these cryptocurrencies really take off it will create a lot of problems. First, it would be harder for government to raise income tax at source. At the very least it would mean an increase in self-assessment, which usually means a diminished tax return, partly due to confusion and difficulty with monitoring.7 There would surely be an increase in tax evasion too, along with a rise in money laundering, since it could be done using cryptocurrencies without the hassle of legal business fronts or official bank accounts.8 (Bitcoin has a public ledger but other cryptocurrencies, like Monero and Dash are even harder to follow.) Who knows? Some businesses might put themselves entirely on a blockchain, and be paid entirely with untraceable cryptocurrency. Authorities in various countries have started to look more closely into how to tax cryptocurrencies – although at the moment this has mostly concerned capital gains rather than income or spending taxes.9 If history is anything to go by, the most crypto-savvy will be able to engage in all sorts of spectacular and untraceable tax evasion, and a greater burden will fall on an increasingly aggrieved and angry middle class.

(The calculation is actually incorrect: when I asked him, May explained that Cyphernomicon was only a first draft, and that he’d never got round to checking it as carefully as he would have liked.) 4 As explained in Attack of the 50-Foot Blockchain by David Gerard (CreateSpace, 2017), Szabo has studied law, and seems to take quite a cautious approach to this issue, unlike others. 5 Kelly Murnane, ‘Ransomware as a Service Being Offered for $39 on the Dark Net’, www.forbes.com, 15 July 2016. 6 See Gerard, Attack of the 50-Foot Blockchain for an excellent discussion of this issue. 7 Annie Nova, ‘“Wild west” days are over for cryptocurrencies, as IRS steps up enforcement’, www.cnbc.com, 17 January 2018. 8 ‘A Simple Guide to Safely and Effectively Tumbling (Mixing) Bitcoin’, https://darknetmarkets.org, 10 July 2015. ‘Can the taxman identify owners of cryptocurrencies? www.nomoretax.eu, 7 September 2017. 9 IRS is going after Coinbase, ordering it last year to hand over details of 14,000 people who carried out big transactions; Robert Wood, ‘Bitcoin Tax Troubles Get More Worrisome’, www.forbes.com, 4 December 2017. 10 Amanda Taub ‘How Stable Are Democracies?

A COUPLE OF YEARS ago I was invited to Prague to give a talk at the ‘Institute of Cryptoanarchy’. Pavol, a mildly secretive hacker who uses several pseudonyms, was organising a gathering of programmers, libertarians and crypto-anarchists. The theme, according to the programme that he emailed over, was decentralised. ‘The concept of the authoritative state is gradually becoming obsolete,’ it read. ‘The rise of sharing economies with reputation models, digital contracts and cryptocurrencies makes the role of central governments useless.’ The Institute of Cryptoanarchy is housed in a large three-storey building in central Prague called ‘Parralel Polis’. It was set up in 2014 by a handful of artists and cryptography enthusiasts who wanted to explore ways of using technology to carve out more space for individual freedom. In 1968 Prague was the scene of the ‘Spring’ attempt by citizens to wrest freedoms from the Soviet Union.


pages: 233 words: 66,446

Bitcoin: The Future of Money? by Dominic Frisby

3D printing, altcoin, bank run, banking crisis, banks create money, barriers to entry, bitcoin, blockchain, capital controls, Chelsea Manning, cloud computing, computer age, cryptocurrency, disintermediation, Ethereum, ethereum blockchain, fiat currency, fixed income, friendly fire, game design, Isaac Newton, Julian Assange, land value tax, litecoin, M-Pesa, mobile money, money: store of value / unit of account / medium of exchange, Occupy movement, Peter Thiel, Ponzi scheme, prediction markets, price stability, QR code, quantitative easing, railway mania, Ronald Reagan, Ross Ulbricht, Satoshi Nakamoto, Silicon Valley, Skype, slashdot, smart contracts, Snapchat, Stephen Hawking, Steve Jobs, Ted Nelson, too big to fail, transaction costs, Turing complete, War on Poverty, web application, WikiLeaks

Bitcointalk.org is the biggest forum – a good place to get opinions and stories (as well as all the usual misinformation you find on chat boards). Coinmarketcap.com is a useful site to introduce yourself to the altcoins. It gives you price information about the hundred biggest cryptocurrencies, as well links to their sites. For those with an interest in finance, I would also single out cryptocomposite.com. Its CC10 Index measures the performance of the top ten cryptocurrencies in real time. It’s almost certain to become the benchmark when tracker funds, ETFs and other financial vehicles eventually arrive to play the price of cryptocurrencies. As for vehicles to invest in block chain tech, they are coming – of that you can be sure – but they have not yet arrived. As this book goes to press, Ehereum is accepting investment – but you need bitcoins to invest.

A Billion-Dollar Hedge Fund Manager and a Super-Smart Mathematician Forecast the Future 10. Should You Buy In? 11. The People’s Money Appendix I: A Beginner’s Guide to Buying Bitcoins Appendix II: Who Is Satoshi? The Usual Suspects Acknowledgements Bibliography Notes Subscribers Author’s Note I have called this book Bitcoin: The Future of Money? Really, I should have called it Cryptocurrency: The Future of Money? Bitcoin is just one of many cryptocurrencies (don’t worry, I’ll explain what that means). It is, arguably, not even the first. But it is the first that works. And it is the one that has caught everyone’s attention. Rather as people say ‘Scotch tape’ or ‘Sellotape’ instead of ‘sticky-back plastic’, Bitcoin is the name everybody knows – hence my choice of title. I have quoted extensively from online forums and chat boards.

But with the failure of companies such as MtGox, you can bet there are many stories that are as disheartening as the above are amusing. The world of crypto-currencies (there are now over 300 altcoins) has attracted all sorts of crooks and fraudsters, as well as those who religiously think they are changing the world. There are scams and get-rich-quick schemes galore. It has become a free-for-all, like the gold rushes of the Wild West. Over time, things should settle. But one of the things you quickly notice is the sense of humour to it all. Many altcoins are based around a joke – ‘Coinye West’, for example. (When my father read this he asked, ‘What’s the joke?’) Many are simply in it for the laugh. Dogecoin is, according to its website, ‘an open source peer-to-peer cryptocurrency, favored by Shiba Inus worldwide’. (Shibu Inus are petite Japanese dogs that have a surprised look on their faces.)


pages: 87 words: 25,823

The Politics of Bitcoin: Software as Right-Wing Extremism by David Golumbia

3D printing, A Declaration of the Independence of Cyberspace, Affordable Care Act / Obamacare, bitcoin, blockchain, Burning Man, crony capitalism, cryptocurrency, currency peg, distributed ledger, Elon Musk, en.wikipedia.org, Ethereum, ethereum blockchain, Extropian, fiat currency, Fractional reserve banking, George Gilder, jimmy wales, litecoin, Marc Andreessen, money: store of value / unit of account / medium of exchange, Mont Pelerin Society, new economy, obamacare, Peter Thiel, Philip Mirowski, risk tolerance, Ronald Reagan, Satoshi Nakamoto, seigniorage, Silicon Valley, Singularitarianism, smart contracts, Stewart Brand, technoutopianism, The Chicago School, Travis Kalanick, WikiLeaks

Bitcoin is therefore considered pseudonymous (Beigel 2015): it is not fully anonymous, since every transaction is recorded, but determining the true identities of those involved in the transactions requires more information than is directly available in the network. The possibility of identifying those true identities and the potential methods for obscuring them altogether are live topics of discussion in the cryptocurrency community (see, e.g., Meiklejohn and Orlandi 2015). The Bitcoin software does not exist in a single physical location, or in one virtual “cloud” location: it is not hosted by a company like Level 3 or, for that matter, Amazon or Google. Instances of the Bitcoin software run on thousands or tens of thousands of computers all over the world. It depends for its continued life not on any one of those computers, but on the many machines that make up the network.

This fact alone has raised significant questions about Bitcoin’s claim to “democratize” or “decentralize” currency operations, in part because the system is exposed to the “51 percent problem”: if one entity controls more than 51 percent of the mining operations at any one time (something which was at one point unthinkable, but which now has happened at least once), it could, at least theoretically, “change the rules of Bitcoin at any time” (Felten 2014; also see Otar 2015). The amount of power consumed by blockchain operations is large enough that it has suggested to some that Bitcoin itself is “unsustainable” (Malmo 2015). The use of cryptographic techniques is what gives Bitcoin and other technologies like it the descriptive term cryptocurrency. The Bitcoin program is currently “capped,” permitting only twenty-one million coins to be “mined.” It is limited in this way because its developers believe that the total number of coins in circulation has an impact on the value of the currency. This is an economic rather than a computer science argument, and it is one with which few economists agree. To some extent it derives from Austrian economics and from the monetarist view of inflation propounded by Milton Friedman and others, but it flies in the face of easily observed facts.

One could scarcely ask for a more textbook example of not just inflation but hyperinflation: the fast and brutal destruction of value for those who hold the instrument. There is nothing mysterious about this: gold itself (like all other commodities, whether limited in supply or not) routinely inflates and deflates, without regard to the total amount of the metal available. Yet Bitcoin advocates continue to advertise the cryptocurrency as if it is immune from inflation, discounting the hard evidence before their own eyes. Quite a few apparently responsible pieces (e.g. Vigna and Casey 2015) have made claims like this at the same time that Bitcoin has been experiencing not just inflation but hyperinflation of exactly the sort Federal Reserve “critics” claim to fear most. The Bitcoin software has a distinct origin point, in a 2008 paper titled “Bitcoin: A Peer-to-Peer Electronic Cash System,” by a pseudonymous author who called himself “Satoshi Nakamoto.”


pages: 410 words: 119,823

Radical Technologies: The Design of Everyday Life by Adam Greenfield

3D printing, Airbnb, augmented reality, autonomous vehicles, bank run, barriers to entry, basic income, bitcoin, blockchain, business intelligence, business process, call centre, cellular automata, centralized clearinghouse, centre right, Chuck Templeton: OpenTable:, cloud computing, collective bargaining, combinatorial explosion, Computer Numeric Control, computer vision, Conway's Game of Life, cryptocurrency, David Graeber, dematerialisation, digital map, disruptive innovation, distributed ledger, drone strike, Elon Musk, Ethereum, ethereum blockchain, facts on the ground, fiat currency, global supply chain, global village, Google Glasses, IBM and the Holocaust, industrial robot, informal economy, information retrieval, Internet of things, James Watt: steam engine, Jane Jacobs, Jeff Bezos, job automation, John Conway, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, joint-stock company, Kevin Kelly, Kickstarter, late capitalism, license plate recognition, lifelogging, M-Pesa, Mark Zuckerberg, means of production, megacity, megastructure, minimum viable product, money: store of value / unit of account / medium of exchange, natural language processing, Network effects, New Urbanism, Occupy movement, Oculus Rift, Pareto efficiency, pattern recognition, Pearl River Delta, performance metric, Peter Eisenman, Peter Thiel, planetary scale, Ponzi scheme, post scarcity, post-work, RAND corporation, recommendation engine, RFID, rolodex, Satoshi Nakamoto, self-driving car, sentiment analysis, shareholder value, sharing economy, Silicon Valley, smart cities, smart contracts, social intelligence, sorting algorithm, special economic zone, speech recognition, stakhanovite, statistical model, stem cell, technoutopianism, Tesla Model S, the built environment, The Death and Life of Great American Cities, The Future of Employment, transaction costs, Uber for X, undersea cable, universal basic income, urban planning, urban sprawl, Whole Earth Review, WikiLeaks, women in the workforce

And even in a small way, the chance to live in an environment we’ve fashioned ourselves, using tools we ourselves have crafted. True to its roots, digital fabrication is helping us work out the shape of the future, one experiment at a time. We remain at the proof-of-concept stage: we now know that in principle, these things can be done. But all the social and intellectual heavy lifting begins now. 5 Cryptocurrency The computational guarantee of value All written accounts of the technological development we know as “the blockchain” begin and end the same way. They note its origins in the cryptocurrency called Bitcoin, and go on to explain how Bitcoin’s obscure, pseudonymous, possibly even multiple inventor “Satoshi Nakamoto” used it to solve the problems of trust that had foxed all previous attempts at networked digital money. They all make much of the blockchain’s potential to transform the way we exchange value, in every context and at every level of society.

How would this work? While formally open to anyone, a DAO presents would-be investors with barriers to entry only a little less onerous than those of participation in the traditional equities market. One invests in a DAO by purchasing “vote tokens” denominated in whatever cryptocurrency the organization runs on, in most cases Ether, and this means going through all the steps of downloading and setting up a suitable wallet. Once purchased, tokens allow the investor to share in profits realized by the DAO, also denominated in cryptocurrency, and they carry voting rights to a degree proportional to the magnitude of the investment. The tokens themselves would fluctuate in value on the open market, in principle appreciating like any other equity should the DAO’s ventures meet with success. (If tokens sound an awful lot like shares of stock, you’re not wrong.

., the light on your door to show that you’re home. One has to become a cybernetician to remain a humanist. Peter Sloterdijk Contents Introduction: Paris year zero 1.Smartphone: The networking of the self 2.The internet of things: A planetary mesh of perception and response 3.Augmented reality: An interactive overlay on the world 4.Digital fabrication: Towards a political economy of matter 5.Cryptocurrency: The computational guarantee of value 6.Blockchain beyond Bitcoin: A trellis for posthuman institutions 7.Automation: The annihilation of work 8.Machine learning: The algorithmic production of knowledge 9.Artificial intelligence: The eclipse of human discretion 10.Radical technologies: The design of everyday life Conclusion: Of tetrapods and tactics—radical technologies and everyday life Acknowledgements Notes Index Introduction Paris year zero It’s a few moments before six in Paris, on a damp evening in early spring.


pages: 515 words: 126,820

Blockchain Revolution: How the Technology Behind Bitcoin Is Changing Money, Business, and the World by Don Tapscott, Alex Tapscott

Airbnb, altcoin, asset-backed security, autonomous vehicles, barriers to entry, bitcoin, blockchain, Blythe Masters, Bretton Woods, business process, buy and hold, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, clean water, cloud computing, cognitive dissonance, commoditize, corporate governance, corporate social responsibility, creative destruction, Credit Default Swap, crowdsourcing, cryptocurrency, disintermediation, disruptive innovation, distributed ledger, Donald Trump, double entry bookkeeping, Edward Snowden, Elon Musk, Erik Brynjolfsson, Ethereum, ethereum blockchain, failed state, fiat currency, financial innovation, Firefox, first square of the chessboard, first square of the chessboard / second half of the chessboard, future of work, Galaxy Zoo, George Gilder, glass ceiling, Google bus, Hernando de Soto, income inequality, informal economy, information asymmetry, intangible asset, interest rate swap, Internet of things, Jeff Bezos, jimmy wales, Kickstarter, knowledge worker, Kodak vs Instagram, Lean Startup, litecoin, Lyft, M-Pesa, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, means of production, microcredit, mobile money, money market fund, Network effects, new economy, Oculus Rift, off grid, pattern recognition, peer-to-peer, peer-to-peer lending, peer-to-peer model, performance metric, Peter Thiel, planetary scale, Ponzi scheme, prediction markets, price mechanism, Productivity paradox, QR code, quantitative easing, ransomware, Ray Kurzweil, renewable energy credits, rent-seeking, ride hailing / ride sharing, Ronald Coase, Ronald Reagan, Satoshi Nakamoto, Second Machine Age, seigniorage, self-driving car, sharing economy, Silicon Valley, Skype, smart contracts, smart grid, social graph, social intelligence, social software, standardized shipping container, Stephen Hawking, Steve Jobs, Steve Wozniak, Stewart Brand, supply-chain management, TaskRabbit, The Fortune at the Bottom of the Pyramid, The Nature of the Firm, The Wisdom of Crowds, transaction costs, Turing complete, Turing test, Uber and Lyft, uber lyft, unbanked and underbanked, underbanked, unorthodox policies, wealth creators, X Prize, Y2K, Zipcar

God being the ultimate in confessional discretion, no party would learn anything more about the other parties’ inputs than they could learn from their own inputs and the output.”4 His point was powerful: Doing business on the Internet requires a leap of faith. Because the infrastructure lacks the much-needed security, we often have little choice but to treat the middlemen as if they were deities. A decade later in 2008, the global financial industry crashed. Perhaps propitiously, a pseudonymous person or persons named Satoshi Nakamoto outlined a new protocol for a peer-to-peer electronic cash system using a cryptocurrency called bitcoin. Cryptocurrencies (digital currencies) are different from traditional fiat currencies because they are not created or controlled by countries. This protocol established a set of rules—in the form of distributed computations—that ensured the integrity of the data exchanged among these billions of devices without going through a trusted third party. This seemingly subtle act set off a spark that has excited, terrified, or otherwise captured the imagination of the computing world and has spread like wildfire to businesses, governments, privacy advocates, social development activists, media theorists, and journalists, to name a few, everywhere.

For doing the right thing—that is, correctly stating that an event happened, who won a sporting match, or who won an election—they receive more reputation points. Maintaining the integrity of the system has other monetary benefits: the more reputation points you have, the more markets you can make, and thus the more fees you can charge. In Augur’s words, “our prediction markets eliminate counterparty risks, centralized servers, and create a global market by employing cryptocurrencies including bitcoin, ether, and stable cryptocurrencies. All funds are stored in smart contracts, and no one can steal the money.”83 Augur resolves the issue of unethical contracts by having a zero-tolerance policy for crime. To Augur’s leadership team, human imagination is the only practical limit to the utility of prediction markets. On Augur, anyone can post a clearly defined prediction about anything with a clear end date—from the trivial, “Will Brad Pitt and Angelina Jolie divorce?”

Central banks could simply begin holding reserves in bitcoin, as they do in other currencies, and assets such as gold. They could also require financial institutions to hold reserves at the central bank in these nonstate currencies. These holdings would enable a central bank to perform their monetary role in both fiat and cryptocurrencies. Sounds prudent, right? When considering financial stability relative to monetary policy, Wilkins said, “The implications [for monetary policy] of electronic money depend on how it’s denominated.” She suggested in a recent speech that “e-money,” as she called it, could be denominated by a government in a national currency or as a cryptocurrency.49 A digital currency denominated in Canadian dollars would be easy to manage, she said. If anything, it would help a central bank to respond more quickly. Most likely, we will see a combination of the two: central banks will hold and manage alternative blockchain-based currencies as they do foreign reserves and will explore converting fiat currency to so-called e-money through a blockchain-based ledger.


pages: 290 words: 72,046

5 Day Weekend: Freedom to Make Your Life and Work Rich With Purpose by Nik Halik, Garrett B. Gunderson

Airbnb, bitcoin, Buckminster Fuller, business process, clean water, collaborative consumption, cryptocurrency, delayed gratification, diversified portfolio, en.wikipedia.org, estate planning, Ethereum, fear of failure, fiat currency, financial independence, glass ceiling, Grace Hopper, Home mortgage interest deduction, Isaac Newton, litecoin, Lyft, market fundamentalism, microcredit, minimum viable product, mortgage debt, mortgage tax deduction, Nelson Mandela, passive income, peer-to-peer, peer-to-peer rental, Ponzi scheme, quantitative easing, Ralph Waldo Emerson, ride hailing / ride sharing, sharing economy, side project, Skype, TaskRabbit, traveling salesman, uber lyft

The adoption rate of cryptocurrencies is increasing daily with banks, corporations, and governments recognizing its mainstream popularity. The current leading cryptocurrencies are Bitcoin, Ethereum, Litecoin, Monero, Dash, and Ripple. A popular way to buy and sell cryptocurrencies and create your own digital currency “wallet” is to use a platform like Coinbase.com or Bittrex.com. Speculative investors should be aware there are risks involved in the investment and use of cryptocurrencies, such as fraud and security of the platforms. Cryptocurrencies can be electronically stolen, and there is no recourse for the individual. Other ways to invest in cryptocurrencies include either mining them or participating in an Initial Coin Offering (ICO) of new crypto coins. Investing in cryptocurrencies, like all Momentum investments, means higher potential returns and higher potential losses.

In this example, silver is undervalued and primed for acquisition. Cryptocurrencies Cryptocurrency is a decentralized digital cash system that uses cryptography to secure transactions. Considered to be the money of the future, it has become a global phenomenon, not only in the tech industry but also in the investment sector. Cryptocurrency is not issued by any central authority, which renders it immune to any government interference or manipulation. They regulate themselves and are governed by the laws of mathematics. Cryptocurrencies make it easier to transfer funds between two parties in a transaction, and with minimal processing fees compared to the steep fees charged by most financial institutions. The adoption rate of cryptocurrencies is increasing daily with banks, corporations, and governments recognizing its mainstream popularity.

Investing in cryptocurrencies, like all Momentum investments, means higher potential returns and higher potential losses. There’s a lot of volatility, which creates trading opportunities. And there’s been a big market run-up. Yet, cryptocurrencies will continue to have significant long-term potential. For more information on cryptocurrencies, visit 5DayWeekend.com. Code: P12 Wrap Up In conclusion, I want to stress that you should reinvest all proceeds from Momentum investments back into cash flow–optimized Growth investments that pay a steady cash flow. If you strike gold with a Momentum investment or land a unicorn tech startup with a $1 billion valuation, you don’t want to treat it like winning the lottery and spend all that cash on toys and vacations. All liabilities should be purchased using your solid foundation of cash-flowing assets. These assets continually replenish your bank account.


pages: 364 words: 99,897

The Industries of the Future by Alec Ross

23andMe, 3D printing, Airbnb, algorithmic trading, AltaVista, Anne Wojcicki, autonomous vehicles, banking crisis, barriers to entry, Bernie Madoff, bioinformatics, bitcoin, blockchain, Brian Krebs, British Empire, business intelligence, call centre, carbon footprint, cloud computing, collaborative consumption, connected car, corporate governance, Credit Default Swap, cryptocurrency, David Brooks, disintermediation, Dissolution of the Soviet Union, distributed ledger, Edward Glaeser, Edward Snowden, en.wikipedia.org, Erik Brynjolfsson, fiat currency, future of work, global supply chain, Google X / Alphabet X, industrial robot, Internet of things, invention of the printing press, Jaron Lanier, Jeff Bezos, job automation, John Markoff, Joi Ito, Kickstarter, knowledge economy, knowledge worker, lifelogging, litecoin, M-Pesa, Marc Andreessen, Mark Zuckerberg, Mikhail Gorbachev, mobile money, money: store of value / unit of account / medium of exchange, Nelson Mandela, new economy, offshore financial centre, open economy, Parag Khanna, paypal mafia, peer-to-peer, peer-to-peer lending, personalized medicine, Peter Thiel, precision agriculture, pre–internet, RAND corporation, Ray Kurzweil, recommendation engine, ride hailing / ride sharing, Rubik’s Cube, Satoshi Nakamoto, selective serotonin reuptake inhibitor (SSRI), self-driving car, sharing economy, Silicon Valley, Silicon Valley startup, Skype, smart cities, social graph, software as a service, special economic zone, supply-chain management, supply-chain management software, technoutopianism, The Future of Employment, Travis Kalanick, underbanked, Vernor Vinge, Watson beat the top human players on Jeopardy!, women in the workforce, Y Combinator, young professional

Bitcoin, a new transnational currency released in the midst of the financial crisis in 2008–2009, offers a case study for the future of currency as the code-ification of money intensifies. Bitcoin is a “digital currency”—a currency that is stored in code and traded online. It is also a “cryptocurrency,” a term that is often used interchangeably with “digital currency” but signifies that the currency uses cryptographic methods in an attempt to make it secure. Bitcoin has become the world’s first cryptocurrency to gain widespread use. Although there are dozens of cryptocurrencies, it is currently the largest and most influential. At first glance, Bitcoin looks kind of like PayPal in that it offers a way to pay for goods online, with no physical interaction needed. As of the 2014 holiday season, some 21,000 merchants accepted bitcoins, including household names like Victoria’s Secret, Amazon, eBay, and Kmart.

Ripple is backed by Marc Andreessen’s VC firm Andreessen Horowitz and Peter Thiel’s Founder’s Fund. Most Silicon Valley figures push back whenever another cryptocurrency is mentioned. Investor Chamath Paliyipatiya believes Bitcoin will continue to dominate the space. “I don’t want to comment on other currencies because they’re all irrelevant,” he says. “It’s about Bitcoin, so we should talk about Bitcoin.” Former CEO John Donahoe of eBay, one of the first companies to establish a trust-based commerce network online, said, “I don’t know what Bitcoin will look like ten years from now, but I do think cryptocurrency and digital currency are growing technologies with tremendous potential. There is no reason why you shouldn’t have almost perfectly secure transfer of money with traceability. Cryptocurrency and digital currency are here to stay. And it will get more powerful, not less.”

And it will get more powerful, not less.” So what will be the future digital currency landscape? When I think of cryptocurrencies, I think of the search engines of the 1990s—WebCrawler, AltaVista, Lycos, Infoseek, Ask Jeeves, MSN Search, Yahoo!—and wonder if there is a Google among them. I think the vast majority of the cryptocurrencies in circulation today will disappear to nothing, but the category will endure. I think that the cryptocurrency that breaks out (whether it is Bitcoin or another) will shed its cryptolibertarian roots and embrace the responsibilities that come with being economically significant. This includes doing away with anonymity and pseudo-anonymity. There are too many economic benefits, particularly in markets with unstable currencies and a reliance on remittances. There are many possibilities for the blockchain technology beyond its function as a currency, and once some applications come to market and achieve meaningful scale, people in power who have misunderstood it or haven’t realized its full potential will see its benefits.


pages: 611 words: 130,419

Narrative Economics: How Stories Go Viral and Drive Major Economic Events by Robert J. Shiller

agricultural Revolution, Albert Einstein, algorithmic trading, Andrei Shleifer, autonomous vehicles, bank run, banking crisis, basic income, bitcoin, blockchain, business cycle, butterfly effect, buy and hold, Capital in the Twenty-First Century by Thomas Piketty, Cass Sunstein, central bank independence, collective bargaining, computerized trading, corporate raider, correlation does not imply causation, cryptocurrency, Daniel Kahneman / Amos Tversky, debt deflation, disintermediation, Donald Trump, Edmond Halley, Elon Musk, en.wikipedia.org, Ethereum, ethereum blockchain, full employment, George Akerlof, germ theory of disease, German hyperinflation, Gunnar Myrdal, Gödel, Escher, Bach, Hacker Ethic, implied volatility, income inequality, inflation targeting, invention of radio, invention of the telegraph, Jean Tirole, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, litecoin, market bubble, money market fund, moral hazard, Northern Rock, nudge unit, Own Your Own Home, Paul Samuelson, Philip Mirowski, plutocrats, Plutocrats, Ponzi scheme, publish or perish, random walk, Richard Thaler, Robert Shiller, Robert Shiller, Ronald Reagan, Rubik’s Cube, Satoshi Nakamoto, secular stagnation, shareholder value, Silicon Valley, speech recognition, Steve Jobs, Steven Pinker, stochastic process, stocks for the long run, superstar cities, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, theory of mind, Thorstein Veblen, traveling salesman, trickle-down economics, tulip mania, universal basic income, Watson beat the top human players on Jeopardy!, We are the 99%, yellow journalism, yield curve, Yom Kippur War

In using the pronoun they, the teller of the “They say that” narrative conveys that there is a constellation of narratives featuring or told by seemingly authoritative persons. The borders of such narrative constellations may be redrawn from time to time, with a particular narrative borrowing contagion from other currently contagious narratives. As we’ve seen, cryptocurrencies are backed by a constellation of related narratives, with a few main stars and thousands or millions of smaller stars. As of 2018, nearly two thousand cryptocurrencies competed with the original Bitcoin. Each of these cryptocurrencies is a story of entrepreneurship, of eager developers with an idea. But the largest constellation of cryptocurrency stories focuses on Bitcoin-related stories. In one narrative, the popular singer Lily Allen turned down an offer in 2009 to do one performance and be paid in Bitcoin. This narrative has a memorable punch line: Allen is kicking herself in regret today, for if she’d accepted the offer and held on to her Bitcoin, she would have been a billionaire by 2017.4 Stories like this one help sustain the growth of the Bitcoin narrative and Bitcoin prices by invoking people’s feelings of regret for not discovering the investment themselves.

How did Bitcoin’s value go from $0 to $300 billion in just a few years? The beginnings of Bitcoin date to 2008, when a paper titled “Bitcoin: A Peer-to-Peer Electronic Cash System,” signed by Satoshi Nakamoto, was distributed to a mailing list. In 2009, the first cryptocurrency, called Bitcoin, was launched based on ideas in that paper. Cryptocurrencies are computer-managed public ledger entries that can function as money, so long as people value these entries as money and use them for purchases and sales. There is an impressive mathematical theory underlying cryptocurrencies, but the theory does not identify what might cause people to value them or to believe that other people will also think they have value. Often, detractors describe the valuation of Bitcoin as nothing more than a speculative bubble. Legendary investor Warren Buffett said, “It’s a gambling device.”1 Critics find its story similar to the famous tulip mania narrative in the Netherlands in the 1630s, when speculators drove up the price of tulip bulbs to such heights that one bulb was worth about as much as a house.

It was built as a reaction against corrupt governments and financial institutions. It was not solely created for the sake of improving financial technology. But some people adulterate this truth. In reality, Bitcoin was meant to function as a monetary weapon, as a cryptocurrency poised to undermine authority.5 Most Bitcoin enthusiasts might not describe their enthusiasm in such extreme terms, but this passage seems to capture a central element of their narrative. Both cryptocurrencies and blockchains (the accounting systems for the cryptocurrencies, which are by design maintained democratically and anonymously by large numbers of individuals and supposedly beyond the regulation of any government) seem to have great emotional appeal for some people, kindling deep feelings about their position and role in society.


pages: 472 words: 117,093

Machine, Platform, Crowd: Harnessing Our Digital Future by Andrew McAfee, Erik Brynjolfsson

"Robert Solow", 3D printing, additive manufacturing, AI winter, Airbnb, airline deregulation, airport security, Albert Einstein, Amazon Mechanical Turk, Amazon Web Services, artificial general intelligence, augmented reality, autonomous vehicles, backtesting, barriers to entry, bitcoin, blockchain, British Empire, business cycle, business process, carbon footprint, Cass Sunstein, centralized clearinghouse, Chris Urmson, cloud computing, cognitive bias, commoditize, complexity theory, computer age, creative destruction, crony capitalism, crowdsourcing, cryptocurrency, Daniel Kahneman / Amos Tversky, Dean Kamen, discovery of DNA, disintermediation, disruptive innovation, distributed ledger, double helix, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Ethereum, ethereum blockchain, everywhere but in the productivity statistics, family office, fiat currency, financial innovation, George Akerlof, global supply chain, Hernando de Soto, hive mind, information asymmetry, Internet of things, inventory management, iterative process, Jean Tirole, Jeff Bezos, jimmy wales, John Markoff, joint-stock company, Joseph Schumpeter, Kickstarter, law of one price, longitudinal study, Lyft, Machine translation of "The spirit is willing, but the flesh is weak." to Russian and back, Marc Andreessen, Mark Zuckerberg, meta analysis, meta-analysis, Mitch Kapor, moral hazard, multi-sided market, Myron Scholes, natural language processing, Network effects, new economy, Norbert Wiener, Oculus Rift, PageRank, pattern recognition, peer-to-peer lending, performance metric, plutocrats, Plutocrats, precision agriculture, prediction markets, pre–internet, price stability, principal–agent problem, Ray Kurzweil, Renaissance Technologies, Richard Stallman, ride hailing / ride sharing, risk tolerance, Ronald Coase, Satoshi Nakamoto, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Skype, slashdot, smart contracts, Snapchat, speech recognition, statistical model, Steve Ballmer, Steve Jobs, Steven Pinker, supply-chain management, TaskRabbit, Ted Nelson, The Market for Lemons, The Nature of the Firm, Thomas Davenport, Thomas L Friedman, too big to fail, transaction costs, transportation-network company, traveling salesman, Travis Kalanick, two-sided market, Uber and Lyft, Uber for X, uber lyft, ubercab, Watson beat the top human players on Jeopardy!, winner-take-all economy, yield management, zero day

Questions were raised about why the hacker would attempt this exploit, since the ethers siphoned off couldn’t immediately be converted into dollars or any other fiat currency. One explanation, advanced by Daniel Krawisz of the Satoshi Nakamoto Institute, was that the hacker could have made approximately $3 million by shorting ethers in one of the cryptocurrency exchanges operating online, correctly betting that once the hack became public, the ether’s value would plummet. But the important questions were not about the hacker’s motivations. They were instead about the vulnerabilities of cryptocurrencies and smart contracts revealed by the exploit. The Nakamoto Institute’s withering assessment was that Ethereum was “doomed.” Its combination of poor programming and terms of use that essentially made this lousy programming legally binding spelled disaster. Believers in the dream of decentralizing all the things, however, weren’t yet ready to give up.

The fact that the concentration was occurring within China was particularly troubling. The government there had a long tradition of overseeing its financial institutions closely and sometimes intervening in them directly, and this kind of activity seems fundamentally at odds with the cryptocurrency dream of complete freedom from government meddling. Having control over Bitcoin and the blockchain behind the great firewall of China, many felt, would turn the dream into a nightmare. The Technologies of Disruption . . . The troubles experienced by The DAO and the Bitcoin-mining network highlight a fundamental question about the rise of cryptocurrencies, smart contracts, powerful platforms, and other recent digital developments. The question, which we posed at the start of this chapter, is a simple one: Are companies becoming passé? As we get better at writing smart contracts, building networks that brilliantly combine self-interest and collective benefit, and increasingly democratizing powerful tools for production and innovation, will we still rely so much on industrial-era companies to get work done?

Governments have not yet shown much willingness to create digital dollars, euros, yen, renminbi, and so on.‡ So Nakamoto proposed, with considerable ambition, to create an entirely new and completely independent digital currency, called Bitcoin. Because it relied heavily on many of the same algorithms and mathematics as cryptography (the art and science of making and breaking codes), Bitcoin came to be known as a “cryptocurrency.” American dollars, Japanese yen, Turkish lira, Nigerian naira, and all the other money issued by nations around the world, meanwhile, are called “fiat currencies” because they exist by government fiat, or order; governments simply declare them to be legal tender.§ Existing combinations of “crypto” code and math helped Nakamoto solve the tough problem of identifying who owned Bitcoins as they got used over time and all over the web to pay for things.


pages: 269 words: 79,285

Silk Road by Eileen Ormsby

4chan, bitcoin, blockchain, Brian Krebs, corporate governance, cryptocurrency, Edward Snowden, fiat currency, Firefox, Julian Assange, litecoin, Mark Zuckerberg, Network effects, peer-to-peer, Ponzi scheme, profit motive, Right to Buy, Ross Ulbricht, Satoshi Nakamoto, stealth mode startup, Ted Nelson, trade route, Turing test, web application, WikiLeaks

Atlantis not only tried to poach Silk Road’s customers, but the owners were determined to lure new clientele on to Tor and into the world of online drug dealing. They set up a presence on the clearweb, advertising their wares and services on Reddit and in cryptocurrency forums. They had a culture of being responsive to member suggestions and requests and were proactive in messaging members about scams. One Silk Road member said, ‘The admins over at Atlantis are very flexible, and they have implemented almost all the reasonable suggestions that people have made to the admins here. I think in a year’s time the road will either adapt, or die.’ Instead of bitcoin, Atlantis initially accepted only litecoin, a new form of cryptocurrency. It was odd that the site didn’t accept bitcoin, which by now had become widely used not only on the black markets but increasingly for legitimate purposes.

It explained how to download the technologies that would enable you to find and use the drug marketplace. Soon afterwards, Wordpress closed the gateway and any attempts to access it returned an error message: ‘silkroad420.wordpress.com is no longer available. This site has been archived or suspended for a violation of our Terms of Service.’ Altoid also registered and posted in the bitcoin discussion forums at bitcointalk.org. Bitcoin at the time was a fledgling cryptocurrency, virtually worthless, and the forum’s members were debating whether it could be used to enable online commerce anonymously. Specifically, they were considering whether it was viable to facilitate buying and selling heroin. In a lengthy thread called ‘A Heroin Store’, on 29 January 2011 altoid (who had only registered that day) helpfully chimed in: What an awesome thread! You guys have a ton of great ideas.

the poster wrote on 12 February 2011 in a blatant advertisement for his ecstasy. ‘Ships stealth/vac sealed regular airmail. Pretty much the only guarantee in the online vending world going, also no way to prove you paid – all transactions are decentralized and anonymous.’ Maxvendor mentioned that payment would be made by bitcoin. Bitcoin is the preferred method of payment for goods and services on the dark web. Known as a ‘cryptocurrency’, it is a digital currency that uses cryptography for security. It exists only in cyberspace. Online multiplayer games such as Second Life use a virtual currency that has value and can be exchanged for real things outside of the game. Bitcoin is similar, but far more sophisticated. It wasn’t until 1 March 2011 that a thread brazenly and blatantly advertising Silk Road was started in the bitcoin forums by a user known as ‘silkroad’; the thread was called ‘Silk Road anonymous marketplace: feedback requested’.


pages: 309 words: 79,414

Going Dark: The Secret Social Lives of Extremists by Julia Ebner

23andMe, 4chan, Airbnb, anti-communist, anti-globalists, augmented reality, Ayatollah Khomeini, bitcoin, blockchain, Boris Johnson, citizen journalism, cognitive dissonance, crowdsourcing, cryptocurrency, Donald Trump, Elon Musk, feminist movement, game design, glass ceiling, Google Earth, job satisfaction, Mark Zuckerberg, mass immigration, Menlo Park, Mikhail Gorbachev, Network effects, off grid, pattern recognition, pre–internet, QAnon, RAND corporation, ransomware, rising living standards, self-driving car, Silicon Valley, Skype, Snapchat, social intelligence, Steve Jobs, Transnistria, WikiLeaks, zero day

On Telegram and the Dark Net, terrorists have increasingly called on their sympathisers to donate in cryptocurrencies.11 For example, the Al-Qaeda-linked organisation al-Sadaqa campaigned for bitcoin donations in November 2017, while Indonesian ISIS leader Bahrun Naim used the cryptocurrency to transfer money to his followers.12 Bitcoin transactions, however, can be tracked, and wallets are easily traced back to their owners due to the highly transparent blockchain technology this cryptocurrency is built on. As a result, many extremists have resorted to anonymous cryptocurrencies such as Monero, ‘which best maintains our privacy’, as neo-Nazi hacker Weev put it. From alternative social media and news channels to extremist messaging apps and cryptocurrencies, the changes that new media ecosystems are undergoing resemble those that are under way in the political landscape. The loss of trust in the mainstream benefits the radical fringes: an increasing number of users turn their backs on established social media outlets.

Available at https://www.forbes.com/sites/billybambrough/2018/08/06/bitcoin-donations-to-neo-nazis-are-climbing-ahead-of-this-weekends-unite-the-right-rally/#3e1fb0c769ac. 11Nikita Malik, ‘Terror in the Dark: How Terrorists Use Encryption, the Dark Net and Cryptocurrencies’, Henry Jackson Society, April 2018. Available at https://henryjacksonsociety.org/publications/terror-in-the-dark-how-terrorists-use-encryption-the-darknet-and-cryptocurrencies/. And David Carlisle, ‘Cryptocurrencies and Terrorist Financing: A Risk, But Hold the Panic’, RUSI, March 2017. Available at https://rusi.org/commentary/cryptocurrencies-and-terrorist-financing-risk-hold-panic. 12Ibid. 8: follow q 1In this chapter, my conversations with roughly a dozen QAnon adherents were synthesised into a just few characters for better readability. 2For more information about these classic conspiracy theories see C.

The alternative crowdsourcing platform was used to fund anti-democratic projects such as the maintenance of the world’s biggest neo-Nazi platforms Daily Stormer and Stormfront and hacking activities of the white supremacist Weev (see pp. 217–26). For example, Weev received $1.8 million cryptocurrency donations to his visible wallet address, which was tracked by Bambenek. He may have accumulated additional sums in his non-public wallets.10 Likewise, jihadists have attracted large sums through cryptocurrency donations. A pro-ISIS group was even able to generate enough money to reward its ‘cyber-jihadists’. ‘We have exchanged parts of our bitcoins to equip the brothers who helped in our last missions with computers,’ one of the group’s members wrote in their private chat group in December 2017. On Telegram and the Dark Net, terrorists have increasingly called on their sympathisers to donate in cryptocurrencies.11 For example, the Al-Qaeda-linked organisation al-Sadaqa campaigned for bitcoin donations in November 2017, while Indonesian ISIS leader Bahrun Naim used the cryptocurrency to transfer money to his followers.12 Bitcoin transactions, however, can be tracked, and wallets are easily traced back to their owners due to the highly transparent blockchain technology this cryptocurrency is built on.


pages: 326 words: 91,559

Everything for Everyone: The Radical Tradition That Is Shaping the Next Economy by Nathan Schneider

1960s counterculture, Affordable Care Act / Obamacare, Airbnb, altcoin, Amazon Mechanical Turk, back-to-the-land, basic income, Berlin Wall, Bernie Sanders, bitcoin, blockchain, Brewster Kahle, Burning Man, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, Clayton Christensen, collaborative economy, collective bargaining, Community Supported Agriculture, corporate governance, creative destruction, crowdsourcing, cryptocurrency, Debian, disruptive innovation, do-ocracy, Donald Knuth, Donald Trump, Edward Snowden, Elon Musk, Ethereum, ethereum blockchain, Food sovereignty, four colour theorem, future of work, gig economy, Google bus, hydraulic fracturing, Internet Archive, Jeff Bezos, jimmy wales, joint-stock company, Joseph Schumpeter, Julian Assange, Kickstarter, Lyft, M-Pesa, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, mass immigration, means of production, multi-sided market, new economy, offshore financial centre, old-boy network, Peter H. Diamandis: Planetary Resources, post-work, precariat, premature optimization, pre–internet, profit motive, race to the bottom, Richard Florida, Richard Stallman, ride hailing / ride sharing, Sam Altman, Satoshi Nakamoto, self-driving car, shareholder value, sharing economy, Silicon Valley, Slavoj Žižek, smart contracts, Steve Jobs, Steve Wozniak, Stewart Brand, transaction costs, Turing test, Uber and Lyft, uber lyft, underbanked, undersea cable, universal basic income, Upton Sinclair, Vanguard fund, white flight, Whole Earth Catalog, WikiLeaks, women in the workforce, working poor, Y Combinator, Y2K, Zipcar

A certain style of evangelistic piety prevails in the Bitcoin “space,” as participants in the burgeoning industry tend to call it. (From the “wallet” software used to manage accounts to the “coins” in virtual circulation, cryptocurrency jargon relies on the most physical of metaphors.) Optimism is the dominant idiom among enthusiasts, but at times it has seemed to rest less on any genuine belief than on an anxiety not to see their bitcoins further depreciate. “Some of the New York Bitcoin Center guys are pretty religious,” said Tim Swanson, an early analyst who had written two self-published e-books on cryptocurrencies. Before that, while living in China, he built his own graphics-chip miners. But Swanson grew increasingly skeptical that Bitcoin would unsettle the existing finance megaliths. “You have centralization without the benefits of centralization,” he told me.

At first he shut himself away in a house in Catalonia, but when that became too restrictive, he left for France, where he’d be farther from the Spanish police and less recognizable in public. With not much else to do, he began learning all he could about cryptocurrencies. Friends of his had already been building Bitcoin-related software. Calafou had been a center for Bitcoin development; Vitalik Buterin spent time there while developing the ideas behind Ethereum. But Duran noticed the market-adulating speculation that tended to pervade the cryptocurrency scene and wondered whether the technology could be used for better ends. “I was thinking about how to hack something like this to fund the Integral Revolution,” he recalled. Among the hundreds of Bitcoin clones out there, each with its particular tweaks to the code, Duran found FairCoin.

The trick to making this hack work was as much a matter of organizing as it was of tech. The more that local cooperatives became part of the network and used its tools, the more faircoins would be worth in cryptocurrency markets, where wide adoption helps make a coin valuable. To build the community, therefore, was simultaneously to finance it. If the price of faircoins reached the price of bitcoins now, for instance, Duran’s initial investment would be worth billions. The plan has since far out-earned his bank loans. At the end of our time together, Duran sent me some faircoin to cover his share of the apartment we stayed in; during the cryptocurrency boom of 2017, with shady ICOs and crypto-millionaires blowing up everywhere, that reimbursement multiplied to one hundred times its original value. New collaborators were flocking to FairCoop to be part of at least one corner of this inflationary universe that was engineering something that wasn’t ruthlessly speculative.


Bit by Bit: How P2P Is Freeing the World by Jeffrey Tucker

Affordable Care Act / Obamacare, Airbnb, airport security, altcoin, bank run, bitcoin, blockchain, business cycle, crowdsourcing, cryptocurrency, disintermediation, distributed ledger, Fractional reserve banking, George Gilder, Google Hangouts, informal economy, invisible hand, Kickstarter, litecoin, Lyft, obamacare, Occupy movement, peer-to-peer, peer-to-peer lending, QR code, ride hailing / ride sharing, Ross Ulbricht, Satoshi Nakamoto, sharing economy, Silicon Valley, Skype, TaskRabbit, the payments system, uber lyft

Some are serious, many are scams, and most fall somewhere in between. They do provide an excellent testing ground for future developments in cryptocurrency. Question: Are they scams? What is pump and dump? Answer: As in any sector, there are scams, among which is “pump and dump,” meaning that developers release a coin, fuel the hype, and then sell it. Which ones are real and which ones are not is impossible to say. There are serious risks to such altcoins and it will be some time before the altcoin market becomes stable and reasonably disciplined by market forces. This is part of what happens in any startup technology. Question: Can you tell me about one or two popular altcoins? How are they different? Will they replace bitcoin? Answer: Litecoin is the second most popular cryptocurrency. It is based on a different algorithm from bitcoin, and it has an infinite inflation rate.

They depend on personal identity. That means that anyone without a card or a bank or a certified identity that a third party trusts cannot get involved. They are excluded. So far as anyone knows, this could be somewhere between 2.5 and 4 billion people in the world. This is where cryptocurrency comes in. It restores money as real property. It moves on a ledger system that requires no trust relationship and no third party certification. It works entirely peerto-peer. Remember the case I mentioned in the beginning, the one in which I bought a cup of coffee with cash? Cryptocurrency allows that type of property exchange to take place between any two parties anywhere in the world. The entire chargeback system that has been constructed by government becomes completely irrelevant. I hadn’t thought about this point entirely until this past weekend.

He draws attention to the most impressive feature of the digital revolution: equipotency, or the equal distribution of power through technological innovation. Equipotency is an extension of the universal right to self-determination. It is necessarily disruptive to traditional forms of power. This radical vision of what’s possible is only hinted at in many of the emerging commercial relationships he discusses in this book. These technologies point to a future very different from what we’ve known. Tucker returns often to the example of cryptocurrency. Money as an institution has been largely held captive by public authority for hundreds of years, if not a thousand years or even more. But in 2009, we saw a break from this long history with “blockchain” technology that lives on a distributed network, is managed by open-source code, and can potentially operate as a marketbased currency for the world. Overstock.com was an early mover in this space.


pages: 430 words: 68,225

Blockchain Basics: A Non-Technical Introduction in 25 Steps by Daniel Drescher

bitcoin, blockchain, business process, central bank independence, collaborative editing, cryptocurrency, disintermediation, disruptive innovation, distributed ledger, Ethereum, ethereum blockchain, fiat currency, job automation, linked data, peer-to-peer, place-making, Satoshi Nakamoto, smart contracts, transaction costs

It addresses the three big questions that arise when being introduced to a new technology: What is it? Why do we need it? How does it work? What You Cannot Expect from This Book The book is deliberately agnostic to the application of the blockchain. While cryptocurrencies in general and Bitcoin in particular are prominent applica- tions of the blockchain, this book explains the blockchain as a general tech- nology. This approach has been chosen in order to highlight generic concepts and technical patterns of the blockchain instead of focusing on a specific and narrow application case. Hence, this book is: • Not a text specifically about Bitcoin or any other cryptocurrency • Not a text solely about one specific blockchain application • Not a text about proofing the mathematical foundations of the blockchain • Not a text about programming a blockchain • Not a text about the legal consequences and implications of the blockchain • Not a text about the social, economic, or ethical impacts of the blockchain on our society or humankind in general However, some of these points are addressed to some extent at appropriate points in this book.

This particular new money connects its application goal, the management of ownership of a new kind of money, with the need to have a trustworthy instrument of payment for compensating its contributors. I am talking about Bitcoin. The Bitcoin system not only manages ownership of the new digital money in a purely distributed peer-to-peer system but it also compensates its peers with the money to whose integrity they contribute. Due to the fact that the blockchain relies heavily on cryptography, this new kind of money is also called cryptographic money or cryptocurrency for short. As a rule of thumb, you could say that Bitcoin and many other cryptographic currencies are like bakeries that pay their employees with the bread they produce, with the dif- ference being that the bread they produce is actually a new digital currency. Outlook This step highlighted the importance of the instrument of payment used to compensate the peers of the blockchain. This step is the last of a series of steps, which focus on the fundamental principles of the blockchain individually.

• The instrument of payment used to compensate peers has an impact on major aspects of the blockchain such as: • Integrity • Openness • The distributed nature • The philosophy of the system 188 Chapter 20 | Paying for Integrity • Desirable properties of an instrument of payment for compensating peers are: • Being available in digital form • Being accepted in the real world • Being accepted in all countries • Not being the subject to capital movement restrictions • Being trustworthy • Not being controlled by one single central organization or state • A cryptocurrency is an independent digital currency whose ownership is managed by a blockchain that uses it as an instrument of payment for compensating its peers for maintaining the integrity of the system. S T E P 21 Bringing the Pieces Together More than just the sum of its pieces This step is the summit of this book’s intellectual journey toward an understanding of the blockchain. While Steps 9-20 explored the individual concepts that make up the blockchain in isolation, this step brings all these pieces together.


pages: 387 words: 112,868

Digital Gold: Bitcoin and the Inside Story of the Misfits and Millionaires Trying to Reinvent Money by Nathaniel Popper

4chan, Airbnb, Apple's 1984 Super Bowl advert, banking crisis, Ben Horowitz, bitcoin, blockchain, Burning Man, buy and hold, capital controls, Colonization of Mars, crowdsourcing, cryptocurrency, David Graeber, Edward Snowden, Elon Musk, Extropian, fiat currency, Fractional reserve banking, Jeff Bezos, Julian Assange, Kickstarter, life extension, litecoin, lone genius, M-Pesa, Marc Andreessen, Mark Zuckerberg, Occupy movement, peer-to-peer, peer-to-peer lending, Peter Thiel, Ponzi scheme, price stability, QR code, Ross Ulbricht, Satoshi Nakamoto, Silicon Valley, Simon Singh, Skype, slashdot, smart contracts, Startup school, stealth mode startup, the payments system, transaction costs, tulip mania, WikiLeaks

He and Satoshi communicated regularly and fell into an easy rapport. While Satoshi never discussed anything personal in these e-mails, he would banter with Martti about little things. In one e-mail, Satoshi pointed to a recent exchange on the Bitcoin e-mail list in which a user referred to Bitcoin as a “cryptocurrency,” referring to the cryptographic functions that made it run. “Maybe it’s a word we should use when describing Bitcoin. Do you like it?” Satoshi asked. “It sounds good,” Martti replied. “A peer to peer cryptocurrency could be the slogan.” As the year went on they also worked out other details, like the Bitcoin logo, which they mocked up on their computers and sent back and forth, coming up, finally, with a B with two lines coming out of the bottom and top. They also batted back and forth potential improvements to the software.

DURING HIS TWO-WEEK stay in the United States, Bobby Lee visited his brother Charlie, who had quit his job at Google over the summer and joined Coinbase to work on Bitcoin full-time. Bobby showed up at the company’s makeshift offices in a converted three-bedroom apartment a day after the company announced the $25 million investment from Andreessen Horowitz. Charlie Lee didn’t need to work another day of his life. Litecoin, his alternative cryptocurrency, which was a slightly faster, lightweight version of Bitcoin, had now become the second-most-popular cryptocurrency in what was becoming an increasingly crowded field of Bitcoin knockoffs. In part because of Charlie’s transparency in launching Litecoin, people trusted it and were betting that it would be, as Charlie had intended, the silver to Bitcoin’s gold. In November the value of all the outstanding Litecoins had briefly surpassed $1 billion.

Krugman focused largely on Bitcoin’s claim to be a currency, given the difficulty it seemed to have fulfilling one of the basic roles of money: serving as a reliable store of value. Why would people store their wealth in Bitcoin if they knew the value was going to fluctuate so violently? Krugman asked. Cowen, meanwhile, argued that Bitcoin was going to have difficulty sustaining its value as new and better-designed cryptocurrencies came along and drew users away from it. Some people were, indeed, already choosing to hold Litecoin, Charlie Lee’s creation, and a hip, younger cryptocurrency, Dogecoin. But a deeper strain lurking beneath these critiques was an awareness that one of the fundamental premises that had driven Bitcoin’s popularity seemed, increasingly, to have been disproved. Many early Bitcoiners, particularly in the libertarian camp, had believed that the Federal Reserve’s efforts to stimulate the economy in the wake of the financial crisis, by pumping lots of new money into banks, would devalue the dollar and lead to high inflation, similar to what had happened in Argentina.


pages: 492 words: 118,882

The Blockchain Alternative: Rethinking Macroeconomic Policy and Economic Theory by Kariappa Bheemaiah

accounting loophole / creative accounting, Ada Lovelace, Airbnb, algorithmic trading, asset allocation, autonomous vehicles, balance sheet recession, bank run, banks create money, Basel III, basic income, Ben Bernanke: helicopter money, bitcoin, blockchain, Bretton Woods, business cycle, business process, call centre, capital controls, Capital in the Twenty-First Century by Thomas Piketty, cashless society, cellular automata, central bank independence, Claude Shannon: information theory, cloud computing, cognitive dissonance, collateralized debt obligation, commoditize, complexity theory, constrained optimization, corporate governance, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, crowdsourcing, cryptocurrency, David Graeber, deskilling, Diane Coyle, discrete time, disruptive innovation, distributed ledger, diversification, double entry bookkeeping, Ethereum, ethereum blockchain, fiat currency, financial innovation, financial intermediation, Flash crash, floating exchange rates, Fractional reserve banking, full employment, George Akerlof, illegal immigration, income inequality, income per capita, inflation targeting, information asymmetry, interest rate derivative, inventory management, invisible hand, John Maynard Keynes: technological unemployment, John von Neumann, joint-stock company, Joseph Schumpeter, Kenneth Arrow, Kenneth Rogoff, Kevin Kelly, knowledge economy, large denomination, liquidity trap, London Whale, low skilled workers, M-Pesa, Marc Andreessen, market bubble, market fundamentalism, Mexican peso crisis / tequila crisis, MITM: man-in-the-middle, money market fund, money: store of value / unit of account / medium of exchange, mortgage debt, natural language processing, Network effects, new economy, Nikolai Kondratiev, offshore financial centre, packet switching, Pareto efficiency, pattern recognition, peer-to-peer lending, Ponzi scheme, precariat, pre–internet, price mechanism, price stability, private sector deleveraging, profit maximization, QR code, quantitative easing, quantitative trading / quantitative finance, Ray Kurzweil, Real Time Gross Settlement, rent control, rent-seeking, Satoshi Nakamoto, Satyajit Das, savings glut, seigniorage, Silicon Valley, Skype, smart contracts, software as a service, software is eating the world, speech recognition, statistical model, Stephen Hawking, supply-chain management, technology bubble, The Chicago School, The Future of Employment, The Great Moderation, the market place, The Nature of the Firm, the payments system, the scientific method, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, too big to fail, trade liberalization, transaction costs, Turing machine, Turing test, universal basic income, Von Neumann architecture, Washington Consensus

NY, for example, has begun providing a business license (BitLicense), which obliges virtual 132 Chapter 3 ■ Innovating Capitalism currency companies to adhere to a specific licensing regime), and who is using it (miners, banks, users, exchanges…). In other countries, the situation is the same and at present there is no legal consensus as to the status of cryptocurrencies.15 The definition and legal acceptance of cryptocurrencies is a primary impairment to its widescale use. Apart from these two impediments, there are also other differences between cryptocurrencies and state fiat. Staying with the legal angle, it is the acceptance of legal tender that determines the use of a currency. Central banks already compete with currencies issued by other central banks within their own states and, to a domestic central bank, a private money is essentially a foreign currency as its monetary policy is governed by an entity that is outside the domestic government’s jurisdiction (Andolfatto, 2016).

In spite of this choice-based interpretation of what can be legally accepted as money, the same rule is not extended to cryptocurrencies, as they use their own denomination, i.e., they are not electronic, digital, or virtual forms of a particular currency. They are different from known currencies and, as none of them have been declared as the official currency of a state, they do not have a legal tender capacity. Thus, no creditor is obliged to accept payment with it to discharge a debtor of its debt (ECB, 2015). This means that virtual currencies can be used only as contractual money, when there is an agreement between buyer and seller in order to accept a given virtual currency as a means of payment (ECB, 2015). The legalese revolving around cryptocurrencies is even more complicated in the US, where it differs according to how it is being used (does it fall under the purview of the SEC, the CFTC, or FinCEN?)

the significant computational energy that is expended in the proofs-of-work process (which helps manage the ledger and makes double-spending attacks excessively expensive), as it has to broadcast results on the network 2. the fixed supply: this provides little or no flexibility for policy aimed at controlling its volatility As the Bank of England asked “whether central banks should themselves make use of such technology to issue digital currencies,” researchers from University College London responded by creating RSCoin, a cryptocurrency framework that separates the generation of the money supply from the maintenance of the transaction ledger. This framework is different from other cryptocurrencies in that the supply is centralized. Thus, the model is ideal for adoption by central banks and in line with the proposals that have been made in this chapter. Some of the stated benefits of RSCoin include: 152 • Unlike traditional fiat money, RSCoin provides the government with a transparent transaction ledger, a distributed system for maintaining it, and a globally visible monetary supply.


pages: 316 words: 117,228

The Code of Capital: How the Law Creates Wealth and Inequality by Katharina Pistor

"Robert Solow", Andrei Shleifer, Asian financial crisis, asset-backed security, barriers to entry, Bernie Madoff, bilateral investment treaty, bitcoin, blockchain, Bretton Woods, business cycle, business process, Capital in the Twenty-First Century by Thomas Piketty, Carmen Reinhart, central bank independence, collateralized debt obligation, colonial rule, conceptual framework, Corn Laws, corporate governance, creative destruction, Credit Default Swap, credit default swaps / collateralized debt obligations, cryptocurrency, Donald Trump, double helix, Edward Glaeser, Ethereum, ethereum blockchain, facts on the ground, financial innovation, financial intermediation, fixed income, Francis Fukuyama: the end of history, full employment, global reserve currency, Hernando de Soto, income inequality, intangible asset, investor state dispute settlement, invisible hand, joint-stock company, joint-stock limited liability company, Joseph Schumpeter, Kenneth Rogoff, land reform, land tenure, London Interbank Offered Rate, Long Term Capital Management, means of production, money market fund, moral hazard, offshore financial centre, phenotype, Ponzi scheme, price mechanism, price stability, profit maximization, railway mania, regulatory arbitrage, reserve currency, Ronald Coase, Satoshi Nakamoto, secular stagnation, self-driving car, shareholder value, Silicon Valley, smart contracts, software patent, sovereign wealth fund, The Nature of the Firm, The Wealth of Nations by Adam Smith, Thorstein Veblen, time value of money, too big to fail, trade route, transaction costs, Wolfgang Streeck

Nonetheless, by altering the code, the pragmatists entered into a Faustian bargain; they conceded that the digital code is malleable and that there is room for human intervention and discretion, after all. It remains to be seen how this opening will be used in the future. Drawing from the history of the legal code of capital, it might be good advice for the social utopists among the digital coders to watch out for the lead coders and monitor their relationships with the most resourceful among the legacy investors. Cryptocurrencies The alchemy of money has bedeviled fortune hunters forever, and the coders of cryptocurrencies are no exception. Bitcoin, a digital cryptocurrency based on blockchain technology, was one of the hottest assets in 2017. When it was launched in 2009, it was lauded as a new form of money without a state, and its most fervent advocates were crypto-anarchists who wished to create a new world beyond big finance and the corruptibility of state power. Soon, however, the gold rush set in and drew characters from every walk of life into the fold, including money launderers, gamblers, fortune hunters, and even high finance.

Without it, they would be doomed whenever private demand for these assets dries up. Cryptocurrencies promise greater purity than either state or private money in theory, but in reality, they are deeply infected by the same features that afflict the real world of money, namely, credit, instability, and power. As noted, proof of sufficient funds is required before a Bitcoin transaction closes and the complete chain of verified transaction is recorded on an immutable digital ledger. Yet, 200 c h a P te r 8 nobody prevents investors from buying Bitcoin on credit, which will have to be paid back in state money, whatever the future price of Bitcoin might be when the debt becomes due. The purity of Bitcoin was also compromised when the cryptocurrency was admitted to futures trading on the Chicago Mercantile Exchange.45 In a futures trade, parties are betting on the ability to predict future price movements, but they will have to deliver, even if they lose.

Creating scarcity was meant to boost its value and to avoid the temptation of inflating the currency to please powerful players. Yet, this limit on the money supply also seems to be fraying around the edges. New variants of the original cryptocurrencies can be coined by creating a hard fork in the original protocol; they may not be identical with the original Bitcoin, but they still create new money. It has even become possible to buy fractions of Bitcoin, which creates the illusion of an expanding pie, even when the only change is the size of each slice. Returning to the question whether Bitcoin is money, it is certainly true that the cryptocurrency has shown that artificial scarcity combined with a dearth of alternative assets that promise superlative returns (if only temporarily) can create huge demand. That alone, however, does not turn it into money in the true sense of the word.


pages: 446 words: 117,660

Arguing With Zombies: Economics, Politics, and the Fight for a Better Future by Paul Krugman

affirmative action, Affordable Care Act / Obamacare, Andrei Shleifer, Asian financial crisis, bank run, banking crisis, basic income, Berlin Wall, Bernie Madoff, bitcoin, blockchain, Bonfire of the Vanities, business cycle, capital asset pricing model, carbon footprint, Carmen Reinhart, central bank independence, centre right, Climategate, cognitive dissonance, cryptocurrency, David Ricardo: comparative advantage, different worldview, Donald Trump, Edward Glaeser, employer provided health coverage, Eugene Fama: efficient market hypothesis, Fall of the Berlin Wall, fiat currency, financial deregulation, financial innovation, financial repression, frictionless, frictionless market, fudge factor, full employment, Growth in a Time of Debt, hiring and firing, illegal immigration, income inequality, index fund, indoor plumbing, invisible hand, job automation, John Snow's cholera map, Joseph Schumpeter, Kenneth Rogoff, knowledge worker, labor-force participation, large denomination, liquidity trap, London Whale, market bubble, market clearing, market fundamentalism, means of production, New Urbanism, obamacare, oil shock, open borders, Paul Samuelson, plutocrats, Plutocrats, Ponzi scheme, price stability, quantitative easing, road to serfdom, Robert Gordon, Robert Shiller, Robert Shiller, Ronald Reagan, secular stagnation, The Chicago School, The Great Moderation, the map is not the territory, The Wealth of Nations by Adam Smith, trade liberalization, transaction costs, universal basic income, very high income, working-age population

But you’re supposed to be sure that a Bitcoin is real without knowing who issued it, so you need the digital equivalent of biting a gold coin to be sure it’s the real deal, and the costs of producing something that satisfies that test have to be high enough to discourage fraud. In other words, cryptocurrency enthusiasts are effectively celebrating the use of cutting-edge technology to set the monetary system back three hundred years. Why would you want to do that? What problem does it solve? I have yet to see a clear answer to that question. Bear in mind that conventional money generally does its job quite well. Transaction costs are low. The purchasing power of a dollar a year from now is highly predictable—orders of magnitude more predictable than that of a Bitcoin. Using a bank account means trusting a bank, but by and large banks justify that trust, far more so than the firms that hold cryptocurrency tokens. So why change to a form of money that works far less well? Indeed, eight years after Bitcoin was launched, cryptocurrencies have made very few inroads into actual commerce.

But central banking, in which private banks held their reserves as deposits at the central bank rather than in gold or silver, greatly reduced this need, and the shift to fiat money eliminated it almost completely. Meanwhile, people gradually shifted away from cash transactions, first toward payments by check, then to credit and debit cards and other digital methods. Set against this history, the enthusiasm for cryptocurrencies seems very odd, because it goes exactly in the opposite of the long-run trend. Instead of near-frictionless transactions, we have high costs of doing business, because transferring a Bitcoin or other cryptocurrency unit requires providing a complete history of past transactions. Instead of money created by the click of a mouse, we have money that must be mined—created through resource-intensive computations. And these costs aren’t incidental, something that can be innovated away. As Markus Brunnermeier and Joseph Abadi point out, the high costs—making it expensive to create a new Bitcoin, or transfer an existing one—are essential to the project of creating confidence in a decentralized system.

We all know the answer: tax evasion, illicit activity, etc. And much of that is outside the U.S., with estimates suggesting that foreigners hold more than half of U.S. currency. Clearly, cryptocurrencies are in effect competing for some of the same business: very few people are using Bitcoin to pay their bills, but some people are using it to buy drugs, subvert elections, and so on. And the examples of both gold and large-denomination banknotes suggest that this kind of demand could support a lot of asset value. So does this mean that crypto, even if it isn’t the transformative technology its backers claim, may not be a bubble? Well, this is where tethering—or, more precisely, its absence for cryptocurrencies—comes in. In normal life, people don’t worry about where the value of green pieces of paper bearing portraits of dead presidents comes from: we accept dollar notes because other people will accept dollar notes.


pages: 200 words: 47,378

The Internet of Money by Andreas M. Antonopoulos

AltaVista, altcoin, bitcoin, blockchain, clean water, cognitive dissonance, cryptocurrency, disruptive innovation, Ethereum, ethereum blockchain, financial exclusion, global reserve currency, litecoin, London Interbank Offered Rate, Marc Andreessen, Oculus Rift, packet switching, peer-to-peer lending, Ponzi scheme, QR code, ransomware, reserve currency, Satoshi Nakamoto, self-driving car, Skype, smart contracts, the medium is the message, trade route, underbanked, WikiLeaks, zero-sum game

That required people to grasp not only how this unorthodox technology worked but also its profound promise for society. No one has done more than Andreas Antonopoulos to get them over that hurdle. Read him. It will make you wiser. — Michael J. Casey, co-author The Age of Cryptocurrency: How Bitcoin and Digital Money are Challenging the Global Economic Order Foreword By Don Tapscott In early 2014, my son Alex and I began the research for our book Blockchain Revolution. I had been working on the 20th anniversary edition of The Digital Economy and reflecting on the last two decades and what’s next, I had become fascinated by Bitcoin and cryptocurrencies. Meanwhile, Alex was an executive with the investment bank Canaccord Genuity. He noticed the growing enthusiasm of early stage bitcoin and blockchain companies in 2013 and began leading his firm’s efforts in the space.

The euro is a digital currency, the US dollar is a digital currency. Less than 8 percent of these currencies exist in physical form; the rest is bits on ledgers. But the fundamental difference is that these ledgers are controlled by centralized organizations, whereas in bitcoin, they’re not. Bitcoin has a decentralized network, an open network. "Bitcoin isn’t a digital currency. It’s a cryptocurrency. It’s a network-centric money." Bitcoin isn’t a digital currency. It’s a cryptocurrency. It’s a network-centric money. I really like the idea of a network-centric money. A network that allows you to replace trust in institutions, trust in hierarchies, with trust on the network. The network acting as a massively diffuse arbiter of truth, resolving any disagreements about transactions and security in a way where no one has control. 3.7.

Really all of these things are forms of expression, and that comes back to the original point: that currency, in the end, is really a form of language. It’s a language by which we communicate our expectations and desires of value, and now that we can do it on such a massive scale, now that everyone can create currency, our choices will really matter. We’re past the zero-sum game. This isn’t about nation-states anymore. This isn’t about who adopts bitcoin first or who adopts cryptocurrencies first, because the internet is adopting cryptocurrencies, and the internet is the world’s largest economy. It is the first transnational economy, and it needs a transnational currency. "This isn’t about nation-states anymore. The internet is the world’s largest economy. It is the first transnational economy, and it needs a transnational currency." 7.7. Currency Creates Sovereignty To summarize, we’ve inverted the very basic and most fundamental equation of currency.


pages: 267 words: 82,580

The Dark Net by Jamie Bartlett

3D printing, 4chan, bitcoin, blockchain, brain emulation, carbon footprint, creative destruction, crowdsourcing, cryptocurrency, deindustrialization, Edward Snowden, Filter Bubble, Francis Fukuyama: the end of history, global village, Google Chrome, Howard Rheingold, Internet of things, invention of writing, Johann Wolfgang von Goethe, Julian Assange, Kuwabatake Sanjuro: assassination market, life extension, litecoin, longitudinal study, Mark Zuckerberg, Marshall McLuhan, moral hazard, moral panic, Occupy movement, pre–internet, Ray Kurzweil, Ross Ulbricht, Satoshi Nakamoto, Skype, slashdot, technological singularity, technoutopianism, Ted Kaczynski, The Coming Technological Singularity, Turing test, Vernor Vinge, WikiLeaks, Zimmermann PGP

He fears its radical libertarian potential is being diluted. ‘The Bitcoin Foundation says, “Oh we need to make it better for the consumers.” No we don’t! What these people forget is that Satoshi himself was political.’ Satoshi Tim May and the cypherpunks hadn’t invented digital crypto-currencies, but they’d seen what they might do. The honour goes to a cryptographer called David Chaum. Although he never attended a meeting, his work on anonymous payment systems was an inspiration for many cypherpunks, including May. The basic principle of a crypto-currency is that each unit of the currency is a string of unique numbers that users can send one another online. But strings of numbers can be easily copied and spent several times over, which makes them valueless. Chaum solved this problem by creating a single centralised ledger, which kept a record of each person’s transaction to verify that each unit of currency wasn’t in two places at once.

fn3 Typically, an administrator is in charge of the entire page or group, while a moderator has specific powers to edit or delete other users’ posts. Chapter 3 Into Galt’s Gulch We the Cypherpunks are dedicated to building anonymous systems. Eric Hughes, ‘A Cypherpunk’s Manifesto’ (1993) A LARGE ABANDONED Pizza Express in north London is an unusual place to start a revolution. But seventy of us have turned up to hear a computer coder named Amir Taaki explain how the crypto-currency Bitcoin will change the world. We share the space with a dozen slightly confused-looking squatters who have recently taken up residence here. Cans of lager are being passed around, and there is a fug of cigarette smoke in the air, which gives the whole event a rebellious edge, especially for the non-smoking sedentary audience members like me. There is a hush, as an unshaven man with short dark hair and a thin ponytail walks to the front of the room.

It set the tone perfectly for what would follow: ‘For a fraction of the investment in time, money and effort I might expend in trying to convince the state to abolish wiretapping and all forms of censorship,’ wrote Hammill, ‘I can teach every libertarian who’s interested how to use cryptography to abolish them unilaterally.’ The list quickly grew to include hundreds of subscribers who were soon posting every day: exchanging ideas, discussing developments, proposing and testing cyphers. This remarkable email list predicted, developed or invented almost every technique now employed by computer users to avoid government surveillance. Tim May proposed, among other things, secure crypto-currencies, a tool enabling people to browse the web anonymously, an unregulated marketplace – which he called ‘BlackNet’ – where anything could be bought or sold without being tracked, and a prototype anonymous whistleblowing system. The cypherpunks were troublemakers: controversial, radical, unrelenting, but also practical. They made things. Someone would write a piece of software, post it to the list, and others would test it and improve it.


pages: 443 words: 116,832

The Hacker and the State: Cyber Attacks and the New Normal of Geopolitics by Ben Buchanan

active measures, Bernie Sanders, bitcoin, blockchain, borderless world, Brian Krebs, British Empire, Cass Sunstein, citizen journalism, credit crunch, cryptocurrency, cuban missile crisis, data acquisition, Donald Trump, drone strike, Edward Snowden, family office, hive mind, Internet Archive, Jacob Appelbaum, John Markoff, John von Neumann, Julian Assange, Kickstarter, kremlinology, MITM: man-in-the-middle, Nate Silver, profit motive, RAND corporation, ransomware, risk tolerance, Robert Hanssen: Double agent, rolodex, Ronald Reagan, Silicon Valley, South China Sea, Steve Jobs, Stuxnet, technoutopianism, undersea cable, uranium enrichment, Vladimir Vetrov: Farewell Dossier, WikiLeaks, zero day

The list of targets included the World Bank, central banks from countries such as Brazil, Chile, and Mexico, and many other prominent financial firms.16 Nor did the North Koreans limit themselves to seeking out traditional currencies. Their campaign included a series of efforts to steal increasingly valuable cryptocurrencies like Bitcoin from unsuspecting users all over the world. They also targeted a significant number of Bitcoin exchanges, including a major one in South Korea known as YouBit. In that case, the exchange lost 17 percent of its financial assets to North Korean hackers, though it refused to specify how much that amounted to in absolute terms.17 One estimate from Group-IB, a cybersecurity company, pegged North Korea’s profit from some of their little-noticed operations against cryptocurrency exchanges at more than $500 million.18 While it is impossible to confirm this estimate or the details of the hacks on cryptocurrency exchanges, the size of the reported loss emphasizes the degree to which the North Koreans have plundered smaller and more private financial institutions, almost entirely out of view.

Jose Pagliery, “North Korea-Linked Hackers Are Attacking Banks Worldwide,” CNN, April 4, 2017. 17. Elizabeth Shim, “North Korea Targeted Bitcoin Exchange in Hacking Attempt, Expert Says,” UPI, August 24, 2017; Timothy W. Martin, Eun-Young Joeng, and Steven Russolillo, “North Korea Is Suspected in Bitcoin Heist,” Wall Street Journal, December 20, 2017. 18. Because the thefts are of cryptocurrency, their estimated dollar values fluctuate with the price of the currency. David Canellis, “North Korean Hacker Crew Steals $571M in Cryptocurrency across 5 Attacks,” The Next Web (TNW) News, October 19, 2018. 19. Kaspersky Lab Global Research and Analysis Team, “Lazarus Under the Hood,” report, April 3, 2017; Dmitry Volkov, “Lazarus Arisen Architecture, Techniques, and Attribution,” Group-IB Threat Intelligence Department, May 30, 2017; Kate Kochetkova, “What Is Known About the Lazarus Group: Sony Hack, Military Espionage, Attacks on Korean Banks and Other Crimes,” Kaspersky Daily, February 24, 2016. 20.

Beginning at the end of March 2016, the GRU, the Russian military intelligence agency tied to the blackout operations in Ukraine, got in on the action. The NSA and broader cybersecurity community had watched these hackers for years, too.10 The GRU’s efforts were well organized, with clear division of labor. Some units focused on developing malicious code, while others focused on gaining access to targets. Still others focused on mining cryptocurrencies such as bitcoin, which the GRU used to pay for online hacking infrastructure that made operations harder to trace. Other units focused on public-facing efforts, which would soon be quite important.11 Whether the GRU knew of the other Russian intelligence activity against the DNC is uncertain.12 The GRU began an operation against the Democratic Party, targeting the DNC, the Clinton campaign, and the Democratic Congressional Campaign Committee, or DCCC, which helps Democrats win elections to the House of Representatives.


pages: 492 words: 141,544

Red Moon by Kim Stanley Robinson

artificial general intelligence, basic income, blockchain, Brownian motion, correlation does not imply causation, cryptocurrency, Deng Xiaoping, gig economy, Hyperloop, illegal immigration, income inequality, invisible hand, low earth orbit, Magellanic Cloud, megacity, precariat, Schrödinger's Cat, seigniorage, strong AI, Turing machine, universal basic income, zero-sum game

That it had been caused by legal actions taken by millions of Americans intent on changing the political system made John Semple think that although it was confusing, there might be some promise in it. How many Americans were part of this takeback of their federal government from global finance was unclear, but the Householders’ Union now claimed two hundred million active members. Meanwhile, back in China, John said, individual savings accounts were shifting at such a rate to carboncoin and other cryptocurrencies that withdrawals from the state-owned banks had been temporarily banned, as well as all traffic in cryptocurrencies of any kind. But stopping speculation in these currencies didn’t actually stop people from using them for exchanges. All this was now only a sideshow to the widespread street demonstrations, but possibly more important in the end. Demonstrations came and went, but law remained, money remained. Still, it was looking less and less likely that the policy of waiting for the demonstrations to sputter out, a tactic that had worked for many decades now, would succeed this time, or succeed fast enough.

T-bill prices were falling, dragging down the dollar and the markets, and all to an accelerating degree—right at a moment when one would have thought that financial stability would be high on both governments’ lists of priorities. The dollar’s troubles weren’t really helping the renminbi, or any of the other national currencies or cryptocurrencies that China had stockpiled in its half century of trade surpluses. On the contrary, every sector of world finance seemed to be suffering except for the cryptocurrency called carboncoin, which was some kind of money created by a confirmable history of carbon drawdown or equivalent environmental actions, valid for subsistence spending only. What this virtual currency would come to in the real world no one could know, and the fact that millions of people had withdrawn their savings from normal seigniorage currencies to invest in such a murky new form of money, meaning, in the end, value and trust and exchangeability, was just another frightening destabilization to add to all the rest.

“But I was told they found the poison that killed Chang on his hand.” “I know. It made him sick too. But he had no reason to do it.” “Not that we know of. These two might have gotten caught up in something, you never know. There’s a lot of IP theft still going on, also a lot of pay-to-play. Sometimes those payola deals go sour.” “I know.” Val had been sent to the moon precisely to look into just such a problem. A cryptocurrency called “US Dollars” was being offered in the black cloud, supposedly redeemable in real dollars, and there was evidence suggesting some of the monster servers involved were located on the moon. Only the Chinese had such powerful computers up here, or so it was believed, so it was a tricky situation, smacking of cyberwarfare, and Valerie had been sent up to see if she could discover anything on station, using her Chinese language ability and her fiscal skills, and the expertise she could call on back home.


pages: 188 words: 40,950

The Case for Universal Basic Income by Louise Haagh

back-to-the-land, basic income, battle of ideas, Bertrand Russell: In Praise of Idleness, bitcoin, blockchain, cryptocurrency, delayed gratification, Diane Coyle, full employment, future of work, housing crisis, income inequality, job-hopping, land reform, low skilled workers, Mark Zuckerberg, mini-job, moral hazard, new economy, offshore financial centre, precariat, race to the bottom, rent control, road to serfdom, Silicon Valley, Skype, smart contracts, trickle-down economics, universal basic income

McKinsey, ‘The World at Work’, p. 2. 36. http://www.undp.org/content/undp/en/home/mdgoverview/post-2015-development-agenda.html 37. See further https://www.mein-grundeinkommen.de/infos/in-english 38. Conversations with leading members of the campaign group MeinGrundincommen, at the websummit in Lisbon on 6 November 2017. 39. Conversations with a backer of the new cryptocurrency EOS, which formally launched in June 2018. EOS is a third-generation cryptocurrency (CC), following Bitcoin, which was created in 2008, and Etherium, which was released in 2013. EOS, like the previous CCs, is based on computer algorithms. Investors buy currency tokens at a set value. Etherium set up smart contracts to regulate transaction relationships. EOS is seeking to generate formal arbitration boards. 40. According to one estimate, the value of Etherium grew more than 11-fold between April 2017, when its value stood at around $50 per token, and the end of the year, when it had risen to $730. https://globalcoinreport.com/current-eos-consistency-might-be-the-start-of-something-extraordinary/ 41.

In the case of a German group of activists who are distributing annual ‘basic incomes’ to the value of €12,000 per annum from a fund of over €1.5 million raised since 2014, the intention is to demonstrate that the principle of sharing works to generate social trust where states have failed, as hostile income security policies have reduced take-up over the last ten years.37 Asked about the inherent problems in crowdfunding – for example, such systems do not cover everyone, only those who join, and they are not reliable as financial systems, as they have no central bank propping them up – the reply is that public systems have had a chance and have fallen short.38 Other alternative initiatives to fund a basic income come from the corporate world, in particular Silicon Valley. An entrepreneurial group heavily involved in blockchain has set aside ‘somewhere between 200 and 300 million’ dollars for philanthropic causes, and funding a large-scale basic income experiment is a prime contender.39 Asked if such systems are not prone to capture by criminals and inherently unstable, an entrepreneur staking his candidacy for governing the latest cryptocurrency, EOS, on promoting basic income funding via blockchain, pointed out that several of the existing blockchains are already ‘the size of states’.40 Explaining why he favours universal basic income as a philanthropic goal, he observed, ‘I am from India originally, and look at the mess the Indian government is making of social security.’41 What do these examples tell us? They reveal that the will and the money to fund large-scale basic income experiments are out there, but outside the framework of states.

According to one estimate, the value of Etherium grew more than 11-fold between April 2017, when its value stood at around $50 per token, and the end of the year, when it had risen to $730. https://globalcoinreport.com/current-eos-consistency-might-be-the-start-of-something-extraordinary/ 41. A debate is ongoing within EOS about governance: should votes be based on the size of investments, or one-wallet (or account) one-vote, as currently? A splinter group calling itself EOS evolution prefers the democratic formula. 42. As an investor in Etherium, interviewed in April 2018, noted, the value of cryptocurrencies is always deeply affected by political crises, such as in Zimbabwe and the Syrian crisis, when states fail and citizens lose a foothold in political communities. 43. Arendt, H. 1958, The Human Condition, Chicago, IL: Chicago University Press, p. 52. 44. Le Roux, P., 2006, Session ‘Poverty and Its Remedies in South Africa’, BIEN Congress, Cape Town, 3 November. 45. Dutrey, A.P., 2007, ‘Successful Targeting?


pages: 254 words: 76,064

Whiplash: How to Survive Our Faster Future by Joi Ito, Jeff Howe

3D printing, Albert Michelson, Amazon Web Services, artificial general intelligence, basic income, Bernie Sanders, bitcoin, Black Swan, blockchain, Burning Man, buy low sell high, Claude Shannon: information theory, cloud computing, Computer Numeric Control, conceptual framework, crowdsourcing, cryptocurrency, data acquisition, disruptive innovation, Donald Trump, double helix, Edward Snowden, Elon Musk, Ferguson, Missouri, fiat currency, financial innovation, Flash crash, frictionless, game design, Gerolamo Cardano, informal economy, interchangeable parts, Internet Archive, Internet of things, Isaac Newton, Jeff Bezos, John Harrison: Longitude, Joi Ito, Khan Academy, Kickstarter, Mark Zuckerberg, microbiome, Nate Silver, Network effects, neurotypical, Oculus Rift, pattern recognition, peer-to-peer, pirate software, pre–internet, prisoner's dilemma, Productivity paradox, race to the bottom, RAND corporation, random walk, Ray Kurzweil, Ronald Coase, Ross Ulbricht, Satoshi Nakamoto, self-driving car, SETI@home, side project, Silicon Valley, Silicon Valley startup, Simon Singh, Singularitarianism, Skype, slashdot, smart contracts, Steve Ballmer, Steve Jobs, Steven Levy, Stewart Brand, Stuxnet, supply-chain management, technological singularity, technoutopianism, The Nature of the Firm, the scientific method, The Signal and the Noise by Nate Silver, There's no reason for any individual to have a computer in his home - Ken Olsen, Thomas Kuhn: the structure of scientific revolutions, universal basic income, unpaid internship, uranium enrichment, urban planning, WikiLeaks

He recently said that “many of the ideas that we ended up doing at Apple came out of the MIT Media Lab.”40 As many of Negroponte’s predictions came true, the world became digital and computers empowered people and things to connect to each other effectively, cheaply, and in a sophisticated way; the world became more open, networked, and complex, pushing the Lab into new fields such as social networks, big data, economics, civics, cities, cryptocurrencies, and other areas that became more concrete and accessible as the Internet, computers, and devices opened these domains to new thinking and innovation. Meanwhile, the Internet and computers also dramatically lowered the cost of invention, sharing, collaboration, and distribution, which substantially increased the places where interesting work was going on and the interconnectedness of this work.

In an essay describing the system, he wrote, “The root problem with conventional currency is all the trust that’s required to make it work. The central bank must be trusted not to debase the currency, but the history of fiat currencies is full of breaches of that trust. Banks must be trusted to hold our money and transfer it electronically, but they lend it out in waves of credit bubbles with barely a fraction in reserve.” He may have embedded another comment on his motivation for creating the cryptocurrency into the genesis block, in a parameter that reads, “The Times 03/Jan/2009 Chancellor on brink of second bailout for banks.”22 Just days after the creation of the genesis block, which produced fifty bitcoins, Satoshi released the first version of the open-source Bitcoin software platform. Written in C++, it was, according to Dan Kaminsky, the Internet security guru, nearly impenetrable. In a 2011 interview with the New Yorker, Kaminsky said, “When I first looked at the code, I was sure I was going to be able to break it.

In fact, Andresen believes that one of the reasons Satoshi stepped away from the project in April 2011 was that his desire to control the code was incompatible with building the community of developers it needed, some of whom have contributed enormously to the source code in the past five years. (It’s worth noting that Andresen himself had his commit access—his ability to make changes to the Bitcoin Core source code—revoked in May 2016.)12 Even as Satoshi’s presence began to fade, other members of the Bitcoin community were building an infrastructure around the cryptocurrency. New Liberty Standard established an exchange rate in October 2009 (1,309.03 bitcoins to the dollar, based on the cost of the electricity needed to mine bitcoins at the time).13 In February 2010, the Bitcoin Market became the first Bitcoin currency exchange—a place where bitcoins could be purchased with fiat currencies, or converted into more traditional forms of money. May 2010 saw the first real-world Bitcoin transaction, when Laszlo Hanyecz of Jacksonville, Florida, offered 10,000 BTC for two pizzas.


pages: 268 words: 76,702

The System: Who Owns the Internet, and How It Owns Us by James Ball

Bill Duvall, bitcoin, blockchain, Chelsea Manning, cryptocurrency, don't be evil, Donald Trump, Douglas Engelbart, Edward Snowden, en.wikipedia.org, Firefox, Frank Gehry, Internet of things, invention of movable type, Jeff Bezos, jimmy wales, Julian Assange, Kickstarter, Leonard Kleinrock, Marc Andreessen, Mark Zuckerberg, Menlo Park, Minecraft, Mother of all demos, move fast and break things, move fast and break things, Network effects, Oculus Rift, packet switching, patent troll, Peter Thiel, pre–internet, ransomware, RFC: Request For Comment, risk tolerance, Ronald Reagan, Rubik’s Cube, self-driving car, Shoshana Zuboff, Silicon Valley, Silicon Valley startup, Skype, Snapchat, Steve Crocker, Stuxnet, The Chicago School, undersea cable, uranium enrichment, WikiLeaks, yield management, zero day

‘There are many signs that attackers have gone from the stereotypical somebody working out of their mom’s basement,’ Meckl says. ‘These are criminal organisations that are constantly shifting their technical expertise and investments in different types of attacks because the profitability landscape shifts. When Bitcoin was really high, people worried a lot of coin miners’ malware was going out there. They were leveraging your computer to mine cryptocurrency for themselves and taking their own energy costs out of the equation, so they can become profitable. Now that cryptocurrency seems to be crashing at the moment, people are shifting back to other types of attacks … stealing passwords or credit cards.’ Jeff Greene reflects that the internet has ended up in a very strange place – though not necessarily one that’s bad for his business. ‘It would be great if we had to manufacture bad news or a mandate,’ he muses, imagining a world where there were few enough real online threats that he would have to overhype them to get the attention of lawmakers, before noting that there’s enough real trouble that no one would need to do so.

In December 2017, suspicions were raised when traffic destined for Facebook, Microsoft, Google, Apple and others was briefly re-routed – for around three minutes at a time – via Russia, in a move which would have represented a test of a proof-of-concept attack (or could have been a mistake, of course).15 In April 2018, an attacker managed to re-route a selection of IP addresses operated by an Amazon service and use them to defraud people of around $150,000 in cryptocurrencies.16 And in that July, a day before the country was due to be hit by street protests, traffic for the popular encrypted messaging app Telegram was re-routed via Iran.17 The YouTube/Pakistan incident is now more than ten years in the past, and nothing has changed with BGP, and nothing seems likely to. Major incidents centring on either BGP mistakes or blatant misuse now emerge every few months, and could easily already have resulted in the interception of sensitive messages, or the theft of major intellectual property: if such attacks are done subtly, they never even come to garner the niche headlines they currently get.

Google is a big database of search queries, query histories and retrieval results, and web pages. Three of the big web giants that we think of are databases. Your account balance, my account balance is being maintained in a database.’ For Wenger the database insight is a particularly exciting one because he is a believer in blockchain, a relatively new technology best known for being what powers Bitcoin and similar cryptocurrencies – but at its core is a distributed database technology over which no one party theoretically has control. To its advocates, this could disrupt the online data oligopoly – but to its critics it’s a convoluted and unproven technology with many side effects. ‘The re-centralising force for the internet was these databases,’ says Wenger. ‘These databases are extraordinarily powerful and valuable because I as the maintainer of the database am the only one who sees everything and everybody else just sees a tiny sliver of it.


pages: 285 words: 86,853

What Algorithms Want: Imagination in the Age of Computing by Ed Finn

Airbnb, Albert Einstein, algorithmic trading, Amazon Mechanical Turk, Amazon Web Services, bitcoin, blockchain, Chuck Templeton: OpenTable:, Claude Shannon: information theory, commoditize, Credit Default Swap, crowdsourcing, cryptocurrency, disruptive innovation, Donald Knuth, Douglas Engelbart, Douglas Engelbart, Elon Musk, factory automation, fiat currency, Filter Bubble, Flash crash, game design, Google Glasses, Google X / Alphabet X, High speed trading, hiring and firing, invisible hand, Isaac Newton, iterative process, Jaron Lanier, Jeff Bezos, job automation, John Conway, John Markoff, Just-in-time delivery, Kickstarter, late fees, lifelogging, Loebner Prize, Lyft, Mother of all demos, Nate Silver, natural language processing, Netflix Prize, new economy, Nicholas Carr, Norbert Wiener, PageRank, peer-to-peer, Peter Thiel, Ray Kurzweil, recommendation engine, Republic of Letters, ride hailing / ride sharing, Satoshi Nakamoto, self-driving car, sharing economy, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, social graph, software studies, speech recognition, statistical model, Steve Jobs, Steven Levy, Stewart Brand, supply-chain management, TaskRabbit, technological singularity, technoutopianism, The Coming Technological Singularity, the scientific method, The Signal and the Noise by Nate Silver, The Structural Transformation of the Public Sphere, The Wealth of Nations by Adam Smith, transaction costs, traveling salesman, Turing machine, Turing test, Uber and Lyft, Uber for X, uber lyft, urban planning, Vannevar Bush, Vernor Vinge, wage slave

Index Abortion, 64 Abstraction, 10 aesthetics and, 83, 87–112 arbitrage and, 161 Bogost and, 49, 92–95 capitalism and, 165 context and, 24 cryptocurrency and, 160–180 culture machines and, 54 (see also Culture machines) cybernetics and, 28, 30, 34 desire for answer and, 25 discarded information and, 50 effective computability and, 28, 33 ethos of information and, 159 high frequency trading (HFT) and imagination and, 185, 189, 192, 194 interfaces and, 52, 54, 92, 96, 103, 108, 110–111 ladder of, 82–83 language and, 2, 24 Marxism and, 165 meaning and, 36 money and, 153, 159, 161, 165–167, 171–175 Netflix and, 87–112, 205n36 politics of, 45 pragmatist approach and, 19–21 process and, 2, 52, 54 reality and, 205n36 Siri and, 64–65, 82–84 Turing Machine and, 23 (see also Turing Machine) Uber and, 124–126, 129 Wiener and, 28–29, 30 work of algorithms and, 113, 120, 123–136, 139–149 Adams, Douglas, 123 Adams, Henry, 80–81 Adaptive systems, 50, 63, 72, 92, 174, 176, 186, 191 Addiction, 114–115, 118–119, 121–122, 176 AdSense, 158–159 Advent of the Algorithm, The (Berlinski), 9, 24 Advertisements AdSense and, 158–159 algorithmic arbitrage and, 111, 161 Apple and, 65 cultural calculus of waiting and, 34 as cultural latency, 159 emotional appeals of, 148 Facebook and, 113–114 feedback systems and, 145–148 Google and, 66, 74, 156, 158–160 Habermas on, 175 Netflix and, 98, 100, 102, 104, 107–110 Uber and, 125 Aesthetics abstraction and, 83, 87–112 arbitrage and, 109–112, 175 culture machines and, 55 House of Cards and, 92, 98–112 Netflix Quantum Theory and, 91–97 personalization and, 11, 97–103 of production, 12 work of algorithms and, 123, 129, 131, 138–147 Agre, Philip, 178–179 Airbnb, 124, 127 Algebra, 17 Algorithmic reading, 52–56 Algorithmic trading, 12, 20, 99, 155 Algorithms abstraction and, 2 (see also Abstraction) arbitrage and, 12, 51, 97, 110–112, 119, 121, 124, 127, 130–134, 140, 151, 160, 162, 169, 171, 176 Berlinski on, 9, 24, 30, 36, 181 Bitcoin and, 160–180 black boxes and, 7, 15–16, 47–48, 51, 55, 64, 72, 92–93, 96, 136, 138, 146–147, 153, 162, 169–171, 179 blockchains and, 163–168, 171, 177, 179 Bogost and, 16, 33, 49 Church-Turing thesis and, 23–26, 39–41, 73 consciousness and, 2, 4, 8, 22–23, 36–37, 40, 76–79, 154, 176, 178, 182, 184 DARPA and, 11, 57–58, 87 desire and, 21–26, 37, 41, 47, 49, 52, 79–82, 93–96, 121, 159, 189–192 effective computability and, 10, 13, 21–29, 33–37, 40–49, 52–54, 58, 62, 64, 72–76, 81, 93, 192–193 Elliptic Curve Digital Signature Algorithm and, 163 embodiment and, 26–32 encryption, 153, 162–163 enframing and, 118–119 Enlightenment and, 27, 30, 38, 45, 68–71, 73 experimental humanities and, 192–196 Facebook and, 20 (see also Facebook) faith and, 7–9, 12, 16, 78, 80, 152, 162, 166, 168 gamification and, 12, 114–116, 120, 123–127, 133 ghost in the machine and, 55, 95 halting states and, 41–46 high frequency trading (HFT) and, 151–158, 168–169, 177 how to think about, 36–41 ideology and, 7, 9, 18, 20–23, 26, 33, 38, 42, 46–47, 54, 64, 69, 130, 144, 155, 160–162, 167, 169, 194 imagination and, 11, 55–56, 181–196 implementation and, 47–52 intelligent assistants and, 11, 57, 62, 64–65, 77 intimacy and, 4, 11, 35, 54, 65, 74–78, 82–85, 97, 102, 107, 128–130, 172, 176, 185–189 Knuth and, 17–18 language and, 24–28, 33–41, 44, 51, 54–55 machine learning and, 2, 15, 28, 42, 62, 66, 71, 85, 90, 112, 181–184, 191 mathematical logic and, 2 meaning and, 35–36, 38, 44–45, 50, 54–55 metaphor and, 32–36 Netflix Prize and, 87–91 neural networks and, 28, 31, 39, 182–183, 185 one-way functions and, 162–163 pragmatist approach and, 18–25, 42, 58, 62 process and, 41–46 programmable culture and, 169–175 quest for perfect knowledge and, 13, 65, 71, 73, 190 rise of culture machines and, 15–21 (see also Culture machines) Siri and, 59 (see also Siri) traveling salesman problem and Turing Machine and, 9 (see also Turing Machine) as vehicle of computation, 5 wants of, 81–85 Weizenbaum and, 33–40 work of, 113–149 worship of, 192 Al-Khwārizmī, Abū ‘Abdullāh Muhammad ibn Mūsā, 17 Alphabet Corporation, 66, 155 AlphaGo, 182, 191 Amazon algorithmic arbitrage and, 124 artificial intelligence (AI) and, 135–145 Bezos and, 174 Bitcoin and, 169 business model of, 20–21, 93–94 cloud warehouses and, 131–132, 135–145 disruptive technologies and, 124 effective computability and, 42 efficiency algorithms and, 134 interface economy and, 124 Kindle and, 195 Kiva Systems and, 134 Mechanical Turk and, 135–145 personalization and, 97 physical logistics of, 13, 131 pickers and, 132–134 pragmatic approach and, 18 product improvement and, 42 robotics and, 134 simplification ethos and, 97 worker conditions and, 132–134, 139–140 Android, 59 Anonymous, 112, 186 AOL, 75 Apple, 81 augmenting imagination and, 186 black box of, 169 cloud warehouse of, 131 company value of, 158 effective computability and, 42 efficiency algorithms and, 134 Foxconn and, 133–134 global computation infrastructure of, 131 iOS App Store and, 59{tab} iTunes and, 161 massive infrastructure of, 131 ontology and, 62–63, 65 physical logistics of, 131 pragmatist approach and, 18 product improvement and, 42 programmable culture and, 169 search and, 87 Siri and, 57 (see also Siri) software and, 59, 62 SRI International and, 57, 59 Application Program Interfaces (APIs), 7, 113 Apps culture machines and, 15 Facebook and, 9, 113–115, 149 Her and, 83 identity and, 6 interfaces and, 8, 124, 145 iOS App Store and, 59 Lyft and, 128, 145 Netflix and, 91, 94, 102 third-party, 114–115 Uber and, 124, 145 Arab Spring, 111, 186 Arbesman, Samuel, 188–189 Arbitrage algorithmic, 12, 51, 97, 110–112, 119, 121, 124, 127, 130–134, 140, 151, 160, 162, 169, 171, 176 Bitcoin and, 51, 169–171, 175–179 cultural, 12, 94, 121, 134, 152, 159 differing values and, 121–122 Facebook and, 111 Google and, 111 high frequency trading (HFT) and, 151–158, 168–169, 177 interface economy and, 123–131, 139–140, 145, 147 labor and, 97, 112, 123–145 market issues and, 152, 161 mining value and, 176–177 money and, 151–152, 155–163, 169–171, 175–179 Netflix and, 94, 97, 109–112 PageRank and, 159 pricing, 12 real-time, 12 trumping content and, 13 valuing culture and, 155–160 Archimedes, 18 Artificial intelligence (AI) adaptive systems and, 50, 63, 72, 92, 174, 176, 186, 191 Amazon and, 135–145 anthropomorphism and, 83, 181 anticipation and, 73–74 artificial, 135–141 automata and, 135–138 DARPA and, 11, 57–58, 87 Deep Blue and, 135–138 DeepMind and, 28, 66, 181–182 desire and, 79–82 ELIZA and, 34 ghost in the machine and, 55, 95 HAL and, 181 homeostat and, 199n42 human brain and, 29 intellectual history of, 61 intelligent assistants and, 11, 57, 62, 64–65, 77 intimacy and, 75–76 job elimination and, 133 McCulloch-Pitts Neuron and, 28, 39 machine learning and, 2, 15, 28, 42, 62, 66, 71, 85, 90, 112, 181–186 Mechanical Turk and, 12, 135–145 natural language processing (NLP) and, 62–63 neural networks and, 28, 31, 39, 182–183, 185 OS One (Her) and, 77 renegade independent, 191 Samantha (Her) and, 77–85, 154, 181 Siri and, 57, 61 (see also Siri) Turing test and, 43, 79–82, 87, 138, 142, 182 Art of Computer Programming, The (Knuth), 17 Ashby, Ross, 199n42 Asimov, Isaac, 45 Atlantic, The (magazine), 7, 92, 170 Automation, 122, 134, 144, 188 Autopoiesis, 28–30 Babbage, Charles, 8 Banks, Iain, 191 Barnet, Belinda, 43–44 Bayesian analysis, 182 BBC, 170 BellKor’s Pragmatic Chaos (Netflix), 89–90 Berlinski, David, 9, 24, 30, 36, 181, 184 Bezos, Jeff, 174 Big data, 11, 15–16, 62–63, 90, 110 Biology, 2, 4, 26–33, 36–37, 80, 133, 139, 185 Bitcoin, 12–13 arbitrage and, 51, 169–171, 175–179 blockchains and, 163–168, 171–172, 177, 179 computationalist approach and cultural processing and, 178 eliminating vulnerability and, 161–162 Elliptic Curve Digital Signature Algorithm and, 163 encryption and, 162–163 as glass box, 162 intrinsic value and, 165 labor and, 164, 178 legitimacy and, 178 market issues and, 163–180 miners and, 164–168, 171–172, 175–179 Nakamoto and, 161–162, 165–167 one-way functions and, 162–163 programmable culture and, 169–175 transaction fees and, 164–165 transparency and, 160–164, 168, 171, 177–178 trust and, 166–168 Blockbuster, 99 Blockchains, 163–168, 171–172, 177, 179 Blogs early web curation and, 156 Facebook algorithms and, 178 Gawker Media and, 170–175 journalistic principles and, 173, 175 mining value and, 175, 178 Netflix and, 91–92 turker job conditions and, 139 Uber and, 130 Bloom, Harold, 175 Bogost, Ian abstraction and, 92–95 algorithms and, 16, 33, 49 cathedral of computation and, 6–8, 27, 33, 49, 51 computation and, 6–10, 16 Cow Clicker and, 12, 116–123 Enlightenment and, 8 gamification and, 12, 114–116, 120, 123–127, 133 Netflix and, 92–95 Boolean conjunctions, 51 Bosker, Bianca, 58 Bostrom, Nick, 45 Bowker, Geoffrey, 28, 110 Boxley Abbey, 137 Brain Pickings (Popova), 175 Brain plasticity, 38, 191 Brand, Stewart, 3, 29 Brazil (film), 142 Breaking Bad (TV series), 101 Brin, Sergei, 57, 155–156 Buffett, Warren, 174 Burr, Raymond, 95 Bush, Vannevar, 18, 186–189, 195 Business models Amazon and, 20–21, 93–94, 96 cryptocurrency and, 160–180 Facebook and, 20 FarmVille and, 115 Google and, 20–21, 71–72, 93–94, 96, 155, 159 Netflix and, 87–88 Uber and, 54, 93–94, 96 Business of Enlightenment, The (Darnton) 68, 68 Calculus, 24, 26, 30, 34, 44–45, 98, 148, 186 CALO, 57–58, 63, 65, 67, 79, 81 Campbell, Joseph, 94 Campbell, Murray, 138 Capitalism, 12, 105 cryptocurrency and, 160, 165–168, 170–175 faking it and, 146–147 Gawker Media and, 170–175 identity and, 146–147 interface economy and, 127, 133 labor and, 165 public sphere and, 172–173 venture, 9, 124, 174 Captology, 113 Carr, Nicholas, 38 Carruth, Allison, 131 Castronova, Edward, 121 Cathedral and the Bazaar, The (Raymond), 6 Cathedral of computation, 6–10, 27, 33, 49, 51 Chess, 135–138, 144–145 Chun, Wendy Hui Kyong, 3, 16, 33, 35–36, 42, 104 Church, Alonzo, 23– 24, 42 Church-Turing thesis, 23–26, 39–41 Cinematch (Netflix), 88–90, 95 Citizens United case, 174 Clark, Andy, 37, 39–40 Cloud warehouses Amazon and, 135–145 interface economy and, 131–145 Mechanical Turk and, 135–145 worker conditions and, 132–134, 139–140 CNN, 170 Code.

Drawing on the historical figure of the automaton, a remarkable collection of Mechanical Turk-powered poetry titled Of the Subcontract, and Adam Smith’s conception of empathy in his Theory of Moral Sentiments, I explore the consequences of computational capitalism on politics, empathy, and social value. The root of the algorithmic sea change is the reimagination of value in computational terms. Chapter 5 leads with the flash crash in 2010 and the growing dominance of algorithmic trading in international markets (described by journalist Michael Lewis’s Flash Boys, among others) to frame a reading of Bitcoin and related cryptocurrencies. By defining the unit of exchange through computational cycles, Bitcoin fundamentally shifts the faith-based community of currency from a materialist to an algorithmic value system. Algorithmic arbitrage is forcing similar transitions in the attribution of value and meaning in many spaces of cultural exchange, from Facebook to journalism. The fundamental shift from valuing the cultural object itself to valuing the networks of relations that the object establishes or supports leads to new practices and aesthetics of production, where form and genre give way to memes and nebulous collaborative works.

Google Now requests permission to access our search histories, physical location, and other data in order to provide its services, and in return it promises to organize not just the present but the near future temporalities of its users. It will suggest when to leave for the next meeting, factoring in traffic, creating an intimate, personal reminder system arbitraging public and private data. As we come to grips with the consequences of the deep interlacing of cultural value and algorithmic arbitrage, the ideals of anonymity and untraceable commerce have become more and more appealing. Cryptocurrency Google’s expanding role as a kind of central utility for arbitrage and cultural valuation online has brought some of the dot-com era’s fondest dreams to life, but in an unexpectedly quiet, backroom way. The futurists Peter Schwartz and Peter Leyden offered one of the best-known expressions of that era’s visions in 1997 with “The Long Boom,” published in that bulletin of the digital revolution, Wired magazine.23 Schwartz offered many predictions centered on five waves of technological change, but a persistent pivot point for the transcendental Wired future was a new kind of computational arbitrage for capitalism that freed commerce from the historical relics of bureaucratic regulation, physical specie, and sovereign control.


pages: 50 words: 15,603

Orwell Versus the Terrorists: A Digital Short by Jamie Bartlett

augmented reality, barriers to entry, bitcoin, blockchain, crowdsourcing, cryptocurrency, Edward Snowden, Ethereum, ethereum blockchain, Kuwabatake Sanjuro: assassination market, Satoshi Nakamoto, technoutopianism, Zimmermann PGP

According to a recent poll by Ipsos-Mori and the Royal Statistics Society (2014), only between 4 and 7 per cent of respondents say they have a high level of trust in institutions such as media, internet companies, telecommunications companies and insurance companies to use data appropriately. fn3 You’ve probably heard of this pseudonymous digital cash because it was, and still is, the currency of choice on the illegal online drugs markets. fn4 And increasingly, I predict, politics. Although no political parties – save the occasional fringe party – have given any thought to what crypto-currencies might mean. What does a modern centre-left party think of crypto-currency, or of blockchain decentralisation? They have no idea. Orwell I’ve interviewed many of the people in the frontline of the battle, the people behind the extraordinary innovation currently taking place. They see the question of online privacy as the digital front in a battle over individual liberty: a rejection of internet surveillance and censorship that they believe has come to dominate modern life online.

And there are even more revolutionary plans in the pipeline. An alternative way of organising the internet is being built as we speak, an internet where no one is in control, where no one can find you or shut you down, where no one can manipulate your content. A decentralised world that is both private and impossible to censor. Back in 2009, in an obscure cryptography chat forum, a mysterious man called Satoshi Nakamoto invented the crypto-currency Bitcoin.fn3 It turns out the real genius of Bitcoin was not the currency at all, but the way that it works. Bitcoin creates an immutable, unchangeable public copy of every transaction ever made by its users, which is hosted and verified by every computer that downloads the software. This public copy is called the ‘blockchain’. Pretty soon, enthusiasts figured out that the blockchain system could be used for anything.


pages: 156 words: 15,746

Personal Finance with Python by Max Humber

asset allocation, backtesting, bitcoin, cryptocurrency, en.wikipedia.org, Ethereum, passive income, web application

Footnotes 1 https://www.anaconda.com/ 2 https://docs.anaconda.com/anaconda/install/ 3 www.numpy.org/ 4 https://www.crummy.com/software/BeautifulSoup/ 5 https://jupyter.org/ 6 https://nteract.io/ 7 https://github.com/nteract/nteract/blob/master/USER_GUIDE.md 8 https://stackoverflow.com/questions/39438049/how-to-set-the-default-python-path-for-anaconda © Max Humber 2018 Max HumberPersonal Finance with Pythonhttps://doi.org/10.1007/978-1-4842-3802-8_2 2. Profit Max Humber1 (1)Toronto, Ontario, Canada You know, you got to spend money to make money. —Chief Keef A couple of weeks ago my grandma asked me if she should put some money into Bitcoin. I didn’t know what to tell her. But I knew that in a book about finance I would have to at least give Bitcoin and cryptocurrencies at least a little bit of lip service. For the uninitiated, cryptocurrencies like Bitcoin (and Ethereum, Dogecoin, and Zcash) are digital assets that are designed to function as a medium of exchange and that use cryptography to secure transactions, to control the creation of new money, and to verify asset transfer. Because I think it’s hilarious, I’m going to use Dogecoin1 as the glue for the rest of this chapter. But honestly, these ideas extend beyond Dogecoin (and crypto for that matter).

With everything now inside of a class, we can instantiate a currency converter with this: API_KEY = os.environ.get("OPX_KEY") c = CurrencyConverter(['CAD', 'USD'], API_KEY) Converting values now just requires us to use the .convert method. print(c.convert(3000, 'CAD', 'USD')) print(c.convert(5000, 'USD', 'CAD')) 2302.35 6515.08 show_alternative The Open Exchange Rates API is incredibly robust, and it actually includes access points for alternative cryptocurrencies. This means that it’s totally legit to instantiate a new CurrencyConverter with ETH (Ethereum), BTC (Bitcoin), and DOGE (Dogecoin) on top of CAD and USD. c = CurrencyConverter(['CAD', 'USD', 'DOGE', 'ETH', 'BTC'], API_KEY) With all the currencies stored inside of a dictionary attached to the CurrencyConverter object: c.rates_ {'BTC': 0.00013350885, 'CAD': 1.303016, 'DOGE': 289.975486957, 'ETH': 0.0017451855, 'USD': 1} we can, again, run the .convert method and find out that $3,000 CAD is equal to the following: c.convert(3000, 'CAD', 'DOGE') 667625.31 .apply The whole point of this chapter was to figure out what the values from previous chapter were in USD instead of CAD.


The Rise of Carry: The Dangerous Consequences of Volatility Suppression and the New Financial Order of Decaying Growth and Recurring Crisis by Tim Lee, Jamie Lee, Kevin Coldiron

active measures, Asian financial crisis, asset-backed security, backtesting, bank run, Bernie Madoff, Bretton Woods, business cycle, capital asset pricing model, Capital in the Twenty-First Century by Thomas Piketty, collapse of Lehman Brothers, collateralized debt obligation, Credit Default Swap, credit default swaps / collateralized debt obligations, cryptocurrency, debt deflation, distributed ledger, diversification, financial intermediation, Flash crash, global reserve currency, implied volatility, income inequality, inflation targeting, labor-force participation, Long Term Capital Management, Lyft, margin call, market bubble, money market fund, money: store of value / unit of account / medium of exchange, moral hazard, negative equity, Network effects, Ponzi scheme, purchasing power parity, quantitative easing, random walk, rent-seeking, reserve currency, rising living standards, risk/return, sharing economy, short selling, sovereign wealth fund, Uber and Lyft, uber lyft, yield curve

But if the monetary base does not correspond to a claim on the economy’s real asset base—for example, hypothetically, if a central bank creates highpowered money (such as cash currency) but holds no assets of any worth— then money and wealth (meaning “genuine wealth”) would become completely detached from each other. The claim that this should not be allowed to happen is rooted in the idea that there is no such thing as a free lunch, but it could be said to be also tied up with the notion that money is, at core, based on trust. Existing cryptocurrencies do not have the property of being linked to the economy’s asset base in any way. The provenance of a holding 212 THE RISE OF CARRY of crypto­currencies is instead achieved through the distributed ledger rather than as a financial claim. But cryptocurrencies do have a significant cost of production, meaning that the contention that they will develop into an alternative or even a superior form of money cannot be dismissed out of hand. The ultimate solution to the problem of money could be technology that allows the use of assets—whether shares, bonds, property, or otherwise — directly as a medium of exchange.

—the anti-carry regime would be very similar to the carry regime. In such an anti-carry regime, there would still be fiat money, and presumably there would still be central banks, Beyond the Vanishing Point 211 or at least some arm of government with monopoly power over the creation of money. Spiraling inflation, however, could lead to the further development of alternative monies, which would ultimately replace fiat money. The emergence of cryptocurrencies has been an early sign that the fundamental, long-run monetary instability that lies behind the financial carry regime is already undermining trust in fiat money. Classically, the three functions that money fulfills are as a medium of exchange, a store of value, and a unit of account, the store of value being the crucial attribute in this respect. But these functions are related to each other; if money’s utility as a store of value becomes critically undermined, it is then likely to become less viable as a medium of exchange.

It would eliminate the possibility of bank runs, in exchange for each currency holder accepting a small amount of day-to-day variability in purchasing power depending on the performance of the particular assets that the currency holder owns. With modern, liquid, electronic financial markets, such a solution may now be technologically possible. It could be implemented through a distributed ledger like cryptocurrencies, or through competing centralized private “banks” (which would be something between mutual funds and banks as understood today), or even through a service provided by a government monopoly. At the moment such a solution seems unlikely to be widely accepted, as both the status quo and revealed preferences of the public seem to favor taking the risk of runs and crises over accepting floating purchasing power in normal conditions.


pages: 395 words: 116,675

The Evolution of Everything: How New Ideas Emerge by Matt Ridley

"Robert Solow", affirmative action, Affordable Care Act / Obamacare, Albert Einstein, Alfred Russel Wallace, AltaVista, altcoin, anthropic principle, anti-communist, bank run, banking crisis, barriers to entry, bitcoin, blockchain, Boris Johnson, British Empire, Broken windows theory, Columbian Exchange, computer age, Corn Laws, cosmological constant, creative destruction, Credit Default Swap, crony capitalism, crowdsourcing, cryptocurrency, David Ricardo: comparative advantage, demographic transition, Deng Xiaoping, discovery of DNA, Donald Davies, double helix, Downton Abbey, Edward Glaeser, Edward Lorenz: Chaos theory, Edward Snowden, endogenous growth, epigenetics, Ethereum, ethereum blockchain, facts on the ground, falling living standards, Ferguson, Missouri, financial deregulation, financial innovation, Frederick Winslow Taylor, Geoffrey West, Santa Fe Institute, George Gilder, George Santayana, Gunnar Myrdal, Henri Poincaré, hydraulic fracturing, imperial preference, income per capita, indoor plumbing, interchangeable parts, Intergovernmental Panel on Climate Change (IPCC), invisible hand, Isaac Newton, Jane Jacobs, Jeff Bezos, joint-stock company, Joseph Schumpeter, Kenneth Arrow, Kevin Kelly, Khan Academy, knowledge economy, land reform, Lao Tzu, long peace, Lyft, M-Pesa, Mahatma Gandhi, Mark Zuckerberg, means of production, meta analysis, meta-analysis, mobile money, money: store of value / unit of account / medium of exchange, Mont Pelerin Society, moral hazard, Necker cube, obamacare, out of africa, packet switching, peer-to-peer, phenotype, Pierre-Simon Laplace, price mechanism, profit motive, RAND corporation, random walk, Ray Kurzweil, rent-seeking, reserve currency, Richard Feynman, rising living standards, road to serfdom, Ronald Coase, Ronald Reagan, Satoshi Nakamoto, Second Machine Age, sharing economy, smart contracts, South Sea Bubble, Steve Jobs, Steven Pinker, The Wealth of Nations by Adam Smith, Thorstein Veblen, transaction costs, twin studies, uber lyft, women in the workforce

As Dominic Frisby remarks, not only has bitcoin’s evolution so far been chaotic, unplanned and organic, but the people around it are ‘an eclectic mix of all sorts from the computer whizz to the con artist to the economist; from the opportunist to the altruist to the activist’. None the less, it is worth remarking just how much the humble bitcoin has achieved in a world where it has no intrinsic value whatsoever, which bodes well for future crypto-currencies online. There are now more than three hundred rival online crypto-currencies competing with bitcoins – altcoins, they are called – and though none has yet gained anything like the market share of bitcoin, it may only be a matter of time. Just imagine what might happen if decentralised crypto-currencies really do take off. If people started putting their savings in them, and financial firms started offering interesting crypto-currency-based products, governments would find their room for manoeuvre much diminished. They could not borrow profligately, or tax rapaciously, or spend freely without looking over their shoulders to see what it might do to their currency against (say) bitcoin.

He started printing money in Iraq, but the quality was poor, counterfeiting was easy and the quantity was too high, causing inflation. However, the Swiss-made dinars remained in circulation, and began to diverge in value from the local ones. Since there were no more being made, people saw them as a store of value and they held their value against the dollar. And then came bitcoins. The implications of crypto-currencies, and their recent evolution, are profound; they go well beyond the subject of money. They give us a glimpse of the future evolution of the internet itself. 16 The Evolution of the Internet Nothing can be made from nothing – once we see that’s so, Already we are on the way to what we want to know: What can things be fashioned from? And how is it without The machinations of the gods, all things can come about?

This firm has gleaming corporate offices and the power to hand out domain names. In general I remain optimistic that the forces of evolution will outwit the forces of command and control, and the internet will continue to provide a free space for all. But only because of human ingenuity staying one step ahead of the dirigistes. Perhaps the most profoundly important of the internet’s offspring will be digital currencies independent of government: bitcoin, or the crypto-currencies that will come after it. ‘I think that the Internet is going to be one of the major forces for reducing the role of government. The one thing that’s missing, but that will soon be developed, is a reliable e-cash,’ said Milton Friedman. And it is not just e-cash; it is the technology behind bitcoin that could finally decentralise not just the internet but society too. The blockchain technology that makes bitcoin work has far-reaching implications.


pages: 501 words: 114,888

The Future Is Faster Than You Think: How Converging Technologies Are Transforming Business, Industries, and Our Lives by Peter H. Diamandis, Steven Kotler

Ada Lovelace, additive manufacturing, Airbnb, Albert Einstein, Amazon Mechanical Turk, augmented reality, autonomous vehicles, barriers to entry, bitcoin, blockchain, blood diamonds, Burning Man, call centre, cashless society, Charles Lindbergh, Clayton Christensen, clean water, cloud computing, Colonization of Mars, computer vision, creative destruction, crowdsourcing, cryptocurrency, Dean Kamen, delayed gratification, dematerialisation, digital twin, disruptive innovation, Edward Glaeser, Edward Lloyd's coffeehouse, Elon Musk, en.wikipedia.org, epigenetics, Erik Brynjolfsson, Ethereum, ethereum blockchain, experimental economics, food miles, game design, Geoffrey West, Santa Fe Institute, gig economy, Google X / Alphabet X, gravity well, hive mind, housing crisis, Hyperloop, indoor plumbing, industrial robot, informal economy, Intergovernmental Panel on Climate Change (IPCC), Internet of things, invention of the telegraph, Isaac Newton, Jaron Lanier, Jeff Bezos, job automation, Joseph Schumpeter, Kevin Kelly, Kickstarter, late fees, Law of Accelerating Returns, life extension, lifelogging, loss aversion, Lyft, M-Pesa, Mary Lou Jepsen, mass immigration, megacity, meta analysis, meta-analysis, microbiome, mobile money, multiplanetary species, Narrative Science, natural language processing, Network effects, new economy, New Urbanism, Oculus Rift, out of africa, packet switching, peer-to-peer lending, Peter H. Diamandis: Planetary Resources, Peter Thiel, QR code, RAND corporation, Ray Kurzweil, RFID, Richard Feynman, Richard Florida, ride hailing / ride sharing, risk tolerance, Satoshi Nakamoto, Second Machine Age, self-driving car, Silicon Valley, Skype, smart cities, smart contracts, smart grid, Snapchat, sovereign wealth fund, special economic zone, stealth mode startup, stem cell, Stephen Hawking, Steve Jobs, Steven Pinker, Stewart Brand, supercomputer in your pocket, supply-chain management, technoutopianism, Tesla Model S, Tim Cook: Apple, transaction costs, Uber and Lyft, uber lyft, unbanked and underbanked, underbanked, urban planning, Watson beat the top human players on Jeopardy!, We wanted flying cars, instead we got 140 characters, X Prize

Finally, the system is transparent because everyone on the network can see every transaction on the network—which is how the double-spend problem was actually solved. The real innovation, though, is how transactions are recorded in the ledger. In normal financial exchanges, when money is moved around, a trusted third party is needed: If I cut you a check, it’s a third party, typically a bank, who ensures I have the cash to cover it. But cryptocurrencies remove the middleman from the exchange, instead validating transactions with every computer on the network. Once deemed valid, the record of that transaction is bundled with other records into a “block,” then added to the record of all prior blocks (the “chain”). By cutting out the middleman and bringing accounting into the digital age, blockchain is doing to banks what the internet did to traditional media: gutting them.

Blockchain has seen serious increases in recent years, as have voice-activated interface technologies (like Alexa). AI is also on the rise, with investments climbing from $5.4 billion in 2017 to $9.3 billion in 2018. And biotechnology experienced a similar boom, rising from $11.8 billion in 2017 to $14.4 billion in 2018. Yet, when it comes to raising staggering sums of money in an eyeblink, little can compare with initial coin offerings (or ICOs). Emerging out of the cryptocurrency realm, ICOs are a new form of crowdfunding underpinned by blockchain technology. Startups can raise capital by creating and selling their own virtual currency—called either “tokens” or “coins.” These tokens give you ownership in the company (or, at least, voting power) and the promise of future profits, or can take the form of a security, representing fractional ownership of a piece of real estate or the like.

When it launched its ICO in August 2017, the project raised $257 million in only thirty days. The first $135 million was raised in the first hour alone. Yet they didn’t even have a working product. Far from an isolated incident, one month prior to Filecoin’s success, Tezos, a self-governing currency (billed as a Bitcoin-update), raised $232 million in just thirteen days. Then there’s the EOS token, one of the most popular cryptocurrencies trading today, which brought in a record-breaking $4 billion from its yearlong ICO. And these token trends are not slowing down. The number of ICOs per quarter has also ballooned, from roughly a dozen during the first quarter of 2017, to over a hundred by the last quarter of 2017, and there’s been even more activity since. Yet, forget ICOs for a moment. When it comes to the mother lode of deployable capital, the real heavyweight title belongs to sovereign wealth funds (SWFs).


pages: 448 words: 117,325

Click Here to Kill Everybody: Security and Survival in a Hyper-Connected World by Bruce Schneier

23andMe, 3D printing, autonomous vehicles, barriers to entry, bitcoin, blockchain, Brian Krebs, business process, cloud computing, cognitive bias, computer vision, connected car, corporate governance, crowdsourcing, cryptocurrency, cuban missile crisis, Daniel Kahneman / Amos Tversky, David Heinemeier Hansson, Donald Trump, drone strike, Edward Snowden, Elon Musk, fault tolerance, Firefox, Flash crash, George Akerlof, industrial robot, information asymmetry, Internet of things, invention of radio, job automation, job satisfaction, John Markoff, Kevin Kelly, license plate recognition, loose coupling, market design, medical malpractice, Minecraft, MITM: man-in-the-middle, move fast and break things, move fast and break things, national security letter, Network effects, pattern recognition, profit maximization, Ralph Nader, RAND corporation, ransomware, Rodney Brooks, Ross Ulbricht, security theater, self-driving car, Shoshana Zuboff, Silicon Valley, smart cities, smart transportation, Snapchat, Stanislav Petrov, Stephen Hawking, Stuxnet, The Market for Lemons, too big to fail, Uber for X, Unsafe at Any Speed, uranium enrichment, Valery Gerasimov, web application, WikiLeaks, zero day

Harney (31 Mar 2016), “Scary new scam could swipe all your closing money,” Chicago Tribune, http://www.chicagotribune.com/classified/realestate/ct-re-0403-kenneth-harney-column-20160331-column.html. 75Turns out that the answer is: plenty: Brian Krebs (12 Oct 2012), “The scrap value of a hacked PC, revisited,” Krebs on Security, https://krebsonsecurity.com/2012/10/the-scrap-value-of-a-hacked-pc-revisited. 75Botnets can be used for all sorts of things: Dan Goodin (2 Feb 2018), “Cryptocurrency botnets are rendering some companies unable to operate,” Ars Technica, https://arstechnica.com/information-technology/2018/02/cryptocurrency-botnets-generate-millions-but-exact-huge-cost-on-victims. 75Hackers use bots to commit click fraud: White Ops (20 Dec 2016), “The Methbot operation,” https://www.whiteops.com/hubfs/Resources/WO_Methbot_Operation_WP.pdf. 76“The CaaS model provides easy access”: Rob Wainwright et al. (15 Mar 2017), “European Union serious and organized crime threat assessment: Crime in the age of technology,” Europol, https://www.europol.europa.eu/activities-services/main-reports/european-union-serious-and-organised-crime-threat-assessment-2017. 76They sell hacking tools: Nicolas Rapp and Robert Hackett (25 Oct 2017), “A hacker’s tool kit,” Fortune, http://fortune.com/2017/10/25/cybercrime-spyware-marketplace.

Catherine Stupp (22 Nov 2016), “Five member states want EU-wide laws on encryption,” Euractiv, https://www.euractiv.com/section/social-europe-jobs/news/five-member-states-want-eu-wide-laws-on-encryption. 195Separately, the EU is considering legislation: Samuel Gibbs (19 Jun 2017), “EU seeks to outlaw ‘backdoors’ in new data privacy proposals,” Guardian, https://www.theguardian.com/technology/2017/jun/19/eu-outlaw-backdoors-new-data-privacy-proposals-uk-government-encrypted-communications-whatsapp. 195Australia is also trying to mandate access: Rachel Baxendale (14 Jul 2017), “Laws could force companies to unlock encrypted messages of terrorists,” Australian, http://www.theaustralian.com.au/national-affairs/laws-could-force-companies-to-unlock-encrypted-messages-of-terrorists/news-story/ed481d29c956dfac93610 61a60dcf590. 195In Brazil, courts temporarily shut down: Vinod Sreeharsha (19 Jul 2016), “WhatsApp is briefly shut down in Brazil for a third time,” New York Times, https://www.nytimes.com/2016/07/20/technology/whatsapp-is-briefly-shut-down-in-brazil-for-a-third-time.html. 195Egypt blocked the encrypted: Mariella Moon (20 Dec 2016), “Egypt has blocked encrypted messaging app Signal,” Engadget, https://www.engadget.com/2016/12/20/egypt-blocks-signal. 195And both Russia: Patrick Howell O’Neill (20 Jun 2016), “Russian bill requires encryption backdoors in all messenger apps,” Daily Dot, https://www.dailydot.com/layer8/encryption-backdoor-russia-fsb. Adam Maida (18 Jul 2017), “Online and on all fronts: Russia’s assault on freedom of expression,” Human Rights Watch, https://www.hrw.org/report/2017/07/18/online-and-all-fronts/russias-assault-freedom-expression. Kenneth Rapoza (16 Oct 2017), “Russia fines cryptocurrency world’s preferred messaging app, Telegram,” Forbes, https://www.forbes.com/sites/kenrapoza/2017/10/16/russia-fines-cryptocurrency-worlds-preferred-messaging-app-telegram. 195and China: Benjamin Haas (29 Jul 2017), “China blocks WhatsApp services as censors tighten grip on internet,” Guardian, https://www.theguardian.com/technology/2017/jul/19/china-blocks-whatsapp-services-as-censors-tighten-grip-on-internet. 196If a company like Apple received: Mallory Locklear (23 Oct 2017), “FBI tried and failed to unlock 7,000 encrypted devices,” Engadget, https://www.engadget.com/2017/10/23/fbi-failed-unlock-7-000-encrypted-devices. 196“Any measure that weakens encryption”: Fred Upton et al. (20 Dec 2016), “Encryption working group year-end report,” House Judiciary Committee and House Energy and Commerce Committee Encryption Working Group, US House of Representatives, https://judiciary.house.gov/wp-content/uploads/2016/12/20161220EWGFINALReport.pdf. 196“My personal view is that we should”: Steve Cannane (9 Nov 2017), “Cracking down on encryption could ‘make it easier for hackers’ to penetrate private services,” ABC News Australia, http://www.abc.net.au/news/2017-11-10/former-mi5-chief-says-encryption-cut-could-lead-to-more-hacking/9136746. 196If Apple adds a backdoor: Lily Hay Newman (21 Apr 2017), “Encrypted chat took over.

Encryption is beneficial to society, even though the evildoers can use it to secure their communications and devices as well as anyone else. This is not a universally held position. There is strong pressure to weaken encryption, not only from totalitarian governments that want to spy on their citizens but from politicians and law enforcement officials in democracies, who see encryption as a tool used by criminals, terrorists, and—with the advent of cryptocurrencies—people who want to buy drugs and launder money. I, and many security technologists, have argued that the FBI’s demands for backdoors are just too dangerous. Of course, criminals and terrorists have used, are using, and will continue to use, encryption to hide their plots from the authorities, just as they will use many other aspects of society’s capabilities and infrastructure. In general, we recognize that cars, restaurants, and telecommunications can be used by both honest and dishonest people.


pages: 213 words: 70,742

Notes From an Apocalypse: A Personal Journey to the End of the World and Back by Mark O'Connell

Berlin Wall, bitcoin, blockchain, California gold rush, carbon footprint, Carrington event, clean water, Colonization of Mars, conceptual framework, cryptocurrency, disruptive innovation, diversified portfolio, Donald Trump, Donner party, Elon Musk, high net worth, Jeff Bezos, life extension, low earth orbit, Marc Andreessen, Mikhail Gorbachev, mutually assured destruction, New Urbanism, off grid, Peter Thiel, post-work, Sam Altman, Silicon Valley, Stephen Hawking, Steven Pinker, the built environment, yield curve

Amid a thicket of analogies to the medieval collapse of feudal power structures, the book also managed, a decade before the invention of Bitcoin, to make some impressively accurate predictions about the advent of online economies and cryptocurrencies. Its four-hundred-odd pages of near-hysterical orotundity can roughly be broken down into the following sequence of propositions: 1) The democratic nation-state basically operates like a criminal cartel, forcing honest citizens to surrender large portions of their wealth to pay for stuff like roads and hospitals and schools. 2) The rise of the Internet, and the advent of cryptocurrencies, will make it impossible for governments to intervene in private transactions and to tax incomes, thereby liberating individuals from the political protection racket of democracy. 3) The state will consequently become obsolete as a political entity. 4) Out of this wreckage will emerge a new global dispensation, in which a “cognitive elite” will rise to power and influence, as a class of sovereign individuals “commanding vastly greater resources” who will no longer be subject to the power of nation-states and will redesign governments to suit their ends.

As discreetly as I could, I slipped my phone from my trouser pocket and entered the address into its browser, and I found myself on the website of a cryptocurrency founded by Mars Society members who had intended it to act both as a source of funding for Mars colonization projects and as the eventual colony’s de facto currency. “Marscoin,” I read, “is dedicated to supporting the colonization of Mars and other space-related projects intended to get humans living and thriving off of planet earth. Simply by using and investing in Marscoin, you are contributing to a serious bootstrapping effort to further a colony on Mars.” There seemed to be a general consensus in Mars colonization circles that the financial system of the colonies would inevitably be based in some or other cryptocurrency. (That there was a high degree of crossover between the enthusiasts of human settlement of Mars and blockchain fundamentalists was not especially surprising, given that both were of disproportionate interest to the libertarian wing of the geek community.)

He was feeling his way toward a kind of grand unified system he’d tentatively started referring to as “Thielism.” This had arisen out of Silicon Valley libertarianism, he said, and encompassed a range of convictions about technology and the human future. A belief in monopoly capitalism. The mining and exploitation of personal data. Radical extension of life spans through technological means. Cryptocurrency as a method of evading both government regulation and the taxation on which nation-states depended. Above all, a belief in the emergence of a new “sovereign individual.” “It’s about radical individualism,” he explained. “It’s survival-of-the-fittest, a belief in the rights of the wealthiest and most powerful among us to do whatever the fuck they want, including living forever. Thielism doesn’t necessarily represent a human apocalypse, per se.


pages: 366 words: 94,209

Throwing Rocks at the Google Bus: How Growth Became the Enemy of Prosperity by Douglas Rushkoff

activist fund / activist shareholder / activist investor, Airbnb, algorithmic trading, Amazon Mechanical Turk, Andrew Keen, bank run, banking crisis, barriers to entry, bitcoin, blockchain, Burning Man, business process, buy and hold, buy low sell high, California gold rush, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, centralized clearinghouse, citizen journalism, clean water, cloud computing, collaborative economy, collective bargaining, colonial exploitation, Community Supported Agriculture, corporate personhood, corporate raider, creative destruction, crowdsourcing, cryptocurrency, disintermediation, diversified portfolio, Elon Musk, Erik Brynjolfsson, Ethereum, ethereum blockchain, fiat currency, Firefox, Flash crash, full employment, future of work, gig economy, Gini coefficient, global supply chain, global village, Google bus, Howard Rheingold, IBM and the Holocaust, impulse control, income inequality, index fund, iterative process, Jaron Lanier, Jeff Bezos, jimmy wales, job automation, Joseph Schumpeter, Kickstarter, loss aversion, Lyft, Marc Andreessen, Mark Zuckerberg, market bubble, market fundamentalism, Marshall McLuhan, means of production, medical bankruptcy, minimum viable product, Mitch Kapor, Naomi Klein, Network effects, new economy, Norbert Wiener, Oculus Rift, passive investing, payday loans, peer-to-peer lending, Peter Thiel, post-industrial society, profit motive, quantitative easing, race to the bottom, recommendation engine, reserve currency, RFID, Richard Stallman, ride hailing / ride sharing, Ronald Reagan, Satoshi Nakamoto, Second Machine Age, shareholder value, sharing economy, Silicon Valley, Snapchat, social graph, software patent, Steve Jobs, TaskRabbit, The Future of Employment, trade route, transportation-network company, Turing test, Uber and Lyft, Uber for X, uber lyft, unpaid internship, Y Combinator, young professional, zero-sum game, Zipcar

For almost five years, the Bitcoin network and its pool of bitcoins grew, while users exchanged bitcoins for products such as thumb drives, alpaca socks, and, yes, drugs. The fact that people transact through cryptographic keys instead of names or e-mail addresses lets them make purchases anonymously. Since there’s no credit-card statement at the end of the month listing the illicit goods and services someone may have purchased, cryptocurrency became popular on black markets and earned a reputation as money for criminals. Then in late 2013, something interesting, if all too predictable, happened. Whether in response to the high-profile bust of an illicit online bitcoin-based marketplace known as the Silk Road or to the growing participation of Chinese users, Wall Street suddenly seized on bitcoins as a new instrument for speculative investing.

To do that, we may have to turn not to a collectively negotiated digital file but to one another. MONEY IS A VERB As creatures of a digital age, our first impulse is often to apply some algorithm, computer program, or other technological solution to a problem. Bitcoin is just such an approach, turning the massive processing power of distributed personal computers to verifying the exchange of value. In using such a technology, we learn to trust the cryptocurrency’s open-source algorithms over the bankers and authorities who may have abused that privilege in the past. In blockchain we trust. Of course, the underlying assumption is that people can’t trust one another enough to transact directly without the constant threat of double-dealing, fraud, or nondelivery of services. By implementing a money system that encourages us to put our faith in technology, we again usurp whatever social bonds our marketplaces may afford us.

This makes it harder for anyone but the platform monopolist to make money by standing still—and even the platform monopolists are losing their grasp on the economy. Money alone won’t buy security, and everyone is going to have to learn how to invest through work, active participation, and assets other than cash. Not to worry: this isn’t all happening so fast. As disappointing as it may be to the revolutionaries among us, the traditional debt-based investment economy is not flipping into a real-time, distributed, peer-to-peer, cryptocurrency marketplace overnight. Those of us with jobs and families and mortgages ignore the investment markets at our own peril. And there are still ways to invest plain old money that capitalize on the current economic transition without overly compromising our potential for a more equitable economic future. I’ll briefly touch on some of these strategies now because, believe it or not, there are readers who came for this alone and have been skimming to this point.


pages: 121 words: 36,908

Four Futures: Life After Capitalism by Peter Frase

Airbnb, basic income, bitcoin, business cycle, call centre, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, cryptocurrency, deindustrialization, Edward Snowden, Erik Brynjolfsson, Ferguson, Missouri, fixed income, full employment, future of work, high net worth, income inequality, industrial robot, informal economy, Intergovernmental Panel on Climate Change (IPCC), iterative process, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, litecoin, mass incarceration, means of production, Occupy movement, pattern recognition, peak oil, plutocrats, Plutocrats, post-work, postindustrial economy, price mechanism, private military company, Ray Kurzweil, Robert Gordon, Second Machine Age, self-driving car, sharing economy, Silicon Valley, smart meter, TaskRabbit, technoutopianism, The Future of Employment, Thomas Malthus, Tyler Cowen: Great Stagnation, universal basic income, Wall-E, Watson beat the top human players on Jeopardy!, We are the 99%, Wolfgang Streeck

The rediscovery of the need for central banking and government regulation is good for a laugh at the expense of a gaggle of libertarian young men, but it tells us little about the future. Bitcoin is not the only cryptocurrency, however, even though it has the most exchange value in traditional currencies, and has certainly been the most widely promoted. Innumerable rivals exist, based on slight variations of the Bitcoin code, going by names like Litecoin and Quarkcoin. Many of these are opportunistic rivals driven by speculators. They are little better than traditional stock market pump-and-dump scams, in which a few promoters talk up the value of a company so that others will bid up its price, and then sell off their own holdings before the suckers realize what’s happening. For the purposes of this chapter, however, the most interesting cryptocurrency is the one that is generally regarded as a silly joke: Dogecoin. In its rise and fall we can see a promising mechanism that may have been introduced prematurely into a society that was not ready for it.

The authors of the study quipped that Wikipedia had become “the encyclopedia that anyone who understands the norms, socializes him or herself, dodges the impersonal wall of semi-automated rejection and still wants to voluntarily contribute his or her time and energy can edit.”28 Bitcoins, Doges, and Whuffie A contemporary reader of Doctorow’s book may find that the concept of “Whuffie” resonates more than it used to, because of the renewed prominence of invented nonstate currencies—in particular, the distributed cryptocurrency Bitcoin. As an accounting system that maintains an artificially scarce points system that is nevertheless not tied to the traditional money and banking system, it is of some limited economic interest. But it turns out that Bitcoin, for all its media hype, may be less significant than some other alternative currencies that currently lack its pretentions. The partisans of Bitcoin aspire for it to substitute for capitalist money.


pages: 477 words: 144,329

How Money Became Dangerous by Christopher Varelas

activist fund / activist shareholder / activist investor, Airbnb, airport security, barriers to entry, basic income, bitcoin, blockchain, Bonfire of the Vanities, California gold rush, cashless society, corporate raider, crack epidemic, cryptocurrency, discounted cash flows, disintermediation, diversification, diversified portfolio, Donald Trump, dumpster diving, fiat currency, fixed income, friendly fire, full employment, Gordon Gekko, greed is good, interest rate derivative, John Meriwether, Kickstarter, Long Term Capital Management, mandatory minimum, mobile money, mortgage debt, pensions crisis, pets.com, pre–internet, profit motive, risk tolerance, Saturday Night Live, shareholder value, side project, Silicon Valley, Steve Jobs, technology bubble, The Predators' Ball, too big to fail, universal basic income, zero day

And a lot of that evolution has been fueled by a loss of trust in government and our financial institutions. Consider the rise of cryptocurrencies. People have become so comfortable with alternate forms of currency, while simultaneously disillusioned with our traditional financial structures, that they’re willing to put their money into something that an anonymous entity created and is nearly impossible to use for anything legal other than speculation and trading. Stories are common of people having mortgaged their houses to buy Bitcoin. They may not trust the bank, but they’ll trust sinking their savings into a currency with little history and unproven legitimacy. That’s how cynical we have become, how disconnected we now are from conventional forms of money. A recent trend in Silicon Valley—which capitalizes on the popularity of cryptocurrency—is to issue an initial coin offering (ICO) when raising funding.

A lot of people believe that what will survive the crypto bubble will be the infrastructure, rather than many of the currencies themselves. Blockchain is a digital ledger originally created to record Bitcoin transactions, but it has since found a multitude of other valuable uses. Blockchain, as the infrastructure that allows the majority of cryptocurrencies to operate, is the shovel salesman, just like Equinix was for the internet, while the cryptocurrencies are the gold seekers or the startups. One use of Blockchain that will have a dramatic impact on wealth management and the way we look at value will be the ability to divide an asset into as many parts as desired and sell those to third parties. Any asset, in theory—including your house or even your future earnings potential—would be eligible to be parsed and sold, creating a world in which partial ownership across existing and potential new asset classes would likely be the norm.

., 201 corporate raiders, 82, 84, 88, 89, 94, 96, 103–4, 360 as activist investors, 104, 106, 360 in Pretty Woman, 98, 100–102 see also hostile takeovers credit: five c’s of, 13, 42, 205 spreadsheets used for analysis in, 19–20, 24 worthiness, 22 credit cards, 233 in e-commerce, 232–33, 244, 245 Credit Suisse, 263–64, 273–74, 340 Crisanti, Jim, 203 cryptocurrencies, 245–46, 308 Culligan, 164–68, 182 currency(ies), 245–46 cryptocurrencies, 245–46, 308 phone minutes as, 245 Cutler, Carol, 207 Daily Stormer, 304 Danni’s Hard Drive, 226, 227, 231–33 data centers, 224–25, 227–28, 231 Equinix, 228, 230–31, 237–47 “naked woman in the server room” story and, 223–26, 232 security at, 225 Davis, Mark, 156–58, 165, 166, 221–22 DEA (Drug Enforcement Administration), 31–33, 34, 39, 40 Deasy, John, 351 DEC (Digital Equipment Corporation), 227–28 defense and aerospace companies, see aerospace and defense companies Defense Department, 124 Denham, Bob, 324 Denny’s, 154 Depression, Great, 51, 189 derivatives, 316–19, 324 de Vries, Peter, 81 Diamond, Neil, 321 diamond and gold wholesalers, see jewelry industry Diamond Club, 15 Dii Group, 213 Dimon, Jamie, 196, 197 Disney, 81–90, 85, 86, 111, 304 Eisner at, 88, 89, 109 Epcot Center, 86 films, 88, 102, 148–49 Steinberg’s hostile takeover attempt, 81–84, 86–91, 98, 102–4, 111 Touchstone Pictures, 88, 102 Disney, Roy, 85 Disney, Walt, 84–86, 87, 103, 112 Disney Channel, 299, 301, 302 Disneyland, 84, 85, 103, 112, 148, 288–90, 314 author’s career at, 4, 5, 10, 11–13, 40, 45, 61, 71, 81–85, 89–90, 106–12, 148, 158, 289, 290 Café Orleans at, 81, 106–12, 289 in Pretty Woman, 106 privilege and, 289–90 Disney World, 85–86 Dominguez, Bernardo, 132 Dominica, 285, 286 dotcom bubble, 175, 211, 214, 228–31, 233–34, 236, 238, 240, 243, 244, 267, 322 Doughty, Caitlin, 301 Douglas, Michael, 98 Drexel Burnham Lambert, 91–96, 188 author’s offer from, 91, 93, 94–95 bankruptcy of, 96 Milken at, 91–94 Ducasse, Alain, 168, 169 Dunkin’ Donuts, 294 earthquake, Whittier Narrows, 34–35 eBay, 233 Ebbers, Bernie, 212, 238 e-commerce, 232–33, 244, 245 Economic Consequences of the Peace, The (Keynes), 280 Economist, 245 Eisner, Michael, 88, 89, 109 Elmassian, George, 25, 31, 32, 34, 38 Elmassian, Richard, 25, 31–33, 38 Enron, 171, 177 Epcot Center, 86 Equinix, 228, 230–31, 237–47 Escobar, Pablo, 39 Euripides, 9 Evoqua, 182 exchange-traded funds (ETFs), 105 F9 mistake, 127 Facebook, 294, 305 Family Ties, 97–98 Fargo, William, 230 Federal Reserve, 370 FedEx, 127 Feuerstein, Don, 57 FICO score, 22 Finance Leaders Fellowship program, 371 financial crisis of 2008, 1–2, 7, 76, 211, 215, 259, 307 Equinix and, 242 financial supermarkets and, 211 see also Great Recession financial supermarkets, 204, 214–15, 361 financial crisis and, 211 Weill’s model of, with Citi, 189–90, 195, 196, 200, 209, 211 financial system, financial industry, 6, 328–30 causes of society’s dysfunctional relationship with money, 359–63 citizens’ disconnection from government finance, 328–29, 343–44, 351, 353, 362 clashes sparked by financial unrest and collapse, 355–58 compensation in, see compensation complexity of, 260–61, 277 estimated worth of financial instruments in the world, 209 net financial burden, 329–30 people’s feelings about working in, 277 preppers and, 306 see also Wall Street financial system, reform of, 363–64 accountability for public officials, 369 action items for banking system and investment management, 364–66 action items for each of us, 368–70 action items for government, 366–68 changing compensation structures to align incentives with investment horizons, 364 community engagement, 369–70 creating federal-level oversight or review board for pension systems, 366–67 creating independent review processes, 364–65 education in financial and economic matters, 368 forming culture or values committees, 365–66 requiring finance background for treasurers and other financial officers, 367 simplicity of regulations, 367–68 Fiorina, Carly, 190, 194–95 Fitzgerald, F.


pages: 756 words: 120,818

The Levelling: What’s Next After Globalization by Michael O’sullivan

"Robert Solow", 3D printing, Airbnb, algorithmic trading, bank run, banking crisis, barriers to entry, Bernie Sanders, bitcoin, Black Swan, blockchain, Boris Johnson, Branko Milanovic, Bretton Woods, British Empire, business cycle, business process, capital controls, Celtic Tiger, central bank independence, cloud computing, continuation of politics by other means, corporate governance, credit crunch, cryptocurrency, deglobalization, deindustrialization, disruptive innovation, distributed ledger, Donald Trump, eurozone crisis, financial innovation, first-past-the-post, fixed income, Geoffrey West, Santa Fe Institute, Gini coefficient, global value chain, housing crisis, income inequality, Intergovernmental Panel on Climate Change (IPCC), knowledge economy, liberal world order, Long Term Capital Management, longitudinal study, market bubble, minimum wage unemployment, new economy, Northern Rock, offshore financial centre, open economy, pattern recognition, Peace of Westphalia, performance metric, private military company, quantitative easing, race to the bottom, reserve currency, Robert Gordon, Robert Shiller, Robert Shiller, Ronald Reagan, Scramble for Africa, secular stagnation, Silicon Valley, Sinatra Doctrine, South China Sea, South Sea Bubble, special drawing rights, supply-chain management, The inhabitant of London could order by telephone, sipping his morning tea in bed, the various products of the whole earth, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, total factor productivity, trade liberalization, tulip mania, Valery Gerasimov, Washington Consensus

Many of them will have failed to spot the emergence of the new trend but are quick to align themselves with it (which tells us more about the labor market than about anything else: people align their careers with hot trends). For instance, the December 2017 spike in the price of bitcoin was accompanied by a raft of new research opinions on the cryptocurrency from new cryptocoin brokers and large banks. For what it is worth, my own view on cryptocurrencies is that the future will be characterized as “Blockchain everywhere, bitcoin nowhere”—that is, the distributed ledger technology behind bitcoin will become more pervasive across economic sectors, but bitcoin will fail to prove itself as a currency proper and will live out an existence as a lurid, speculative asset.* To return to the business of forecasting, I am also often struck by the number of times that bodies like the IMF and central banks follow up a crisis or market event with a downward adjustment to their GDP forecasts.

In this context, the aim of this chapter is to set the scene for the rest of the book by sketching the consequences of the tide’s going out: showing that the world has run out of breath economically and run out of patience politically, and that in places the long-term expectations of wealth and income are tapering downward and the established rules of the road for our world are being undercut. “The Pace of Change Has Never Been This Fast” The reader might respond by asking, Won’t technology solve all of these problems? Today, there is such a dazzling array of new problem-solving technologies—from gene editing and digital health care to sleep masks to cryptocurrencies to lifestyle apps—that we might consider most of our material problems to be solvable. For instance, French author Nicolas Santolaria has written a book, Comment j’ai sous-traité ma vie (How I outsourced my life), in which he describes his attempt to outsource as many chores and lifestyle tasks as possible to apps, including dating apps that let him pay to have someone “pre–chat up,” if that’s the right phrase, partners he is interested in dating.

Technology’s role in the zeitgeist is manifest in many of the more intriguing economic puzzles that confound us. It reveals itself in the role of algorithmic and computer-based trading in financial markets, in the massive changes it has enabled in how we work, and in the structure of the labor market. Moreover, technology has manifestly been the enabler of enormous structural changes in retail and consumer goods and in the rise of new financial assets from exchange-traded funds (ETFs) to cryptocurrencies. Keynes’s snapshot gives a sense of what globalization is: the increasing interdependence and integration of economies, markets, nations, and cultures. It also shows up the parallels between the world of the first wave of globalization and the world of today. In this respect, it is worth journeying back in time to see how globalization first formed and—importantly, given the threats to it today—how it ended and what lessons we can learn.


pages: 444 words: 84,486

Radicalized by Cory Doctorow

activist fund / activist shareholder / activist investor, Affordable Care Act / Obamacare, Bernie Sanders, call centre, crowdsourcing, cryptocurrency, Edward Snowden, Flash crash, G4S, high net worth, information asymmetry, license plate recognition, obamacare, old-boy network, six sigma, TaskRabbit

She prodded a headline and learned that Boulangism had been a ghost ship for at least six months because that’s how long security researchers had been contacting the company to tell it that all its user data—passwords, log-ins, ordering and billing details—had been hanging out there on the public internet with no password or encryption. There were ransom notes in the database, records inserted by hackers demanding cryptocurrency payouts in exchange for keeping the dirty secret of Boulangism’s shitty data handling. No one had even seen them. Boulangism’s share price had declined by 98 percent over the past year. There might not even be a Boulangism anymore. When Salima had pictured Boulangism, she’d imagined the French bakery that was on the toaster’s idle-screen, dusted with flour, woodblock tables with serried ranks of crusty loaves.

The cops had served no-knock warrants on all four, gone in with guns drawn and SWAT backup—but had somehow managed to fail to shoot any of them in the process. Joe took some comfort in that. Social media exploded with the personal lives of these four guys, who were, to put it mildly, basic as fuck. They had bullshit jobs: jobs that no one, not even them, thought worth doing. One was a management consultant. One was a customer service manager for a call center. One was an ad-tech programmer. One was a marketing specialist for cryptocurrency startups. All shared one trait: they’d watched the slow death of an insured loved one who’d been denied coverage. In an earlier age, they’d have stewed in private misery, become alcoholics, shot themselves. Instead, they’d followed simple online instructions for starting a message board and hosting it on a bulletproof server accessible only via the Tor network. They hadn’t detonated bombs or gone on a shooting spree—they hadn’t even egged on the people who had.

Instead, he stopped at a CVS and bought four different kinds of over-the-counter sleeping pills, and drew up a chart on some scrap printer paper from the guest room and kept track, looking for a pill that gave him the most sleep with the least hangover. What he really wanted was some Ambien, which he’d tried a couple times in college when he was too wound up to sleep and a buddy had helped him out. There were lots of places to get Ambien cheap and prescription-free, using darkweb markets. He even had some cryptocurrency he’d speculated on when it seemed like it wouldn’t ever stop rising. Might as well spend it now before it was completely worthless. But of course, he couldn’t remember the obscure .onion addresses for the marketplaces, and the only one he knew by heart was Fuckriff’s, and before he could stop himself or even remember that the site had gone down, he was logging in. The log-in banner informed him that the site was back up, with all the accounts intact but all the archives securely deleted.


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The Fifth Domain: Defending Our Country, Our Companies, and Ourselves in the Age of Cyber Threats by Richard A. Clarke, Robert K. Knake

A Declaration of the Independence of Cyberspace, Affordable Care Act / Obamacare, Airbnb, Albert Einstein, Amazon Web Services, autonomous vehicles, barriers to entry, bitcoin, Black Swan, blockchain, borderless world, business cycle, business intelligence, call centre, Cass Sunstein, cloud computing, cognitive bias, commoditize, computer vision, corporate governance, cryptocurrency, data acquisition, DevOps, don't be evil, Donald Trump, Edward Snowden, Exxon Valdez, global village, immigration reform, Infrastructure as a Service, Internet of things, Jeff Bezos, Julian Assange, Kubernetes, Mark Zuckerberg, Metcalfe’s law, MITM: man-in-the-middle, move fast and break things, move fast and break things, Network effects, open borders, platform as a service, Ponzi scheme, ransomware, Richard Thaler, Sand Hill Road, Schrödinger's Cat, self-driving car, shareholder value, Silicon Valley, Silicon Valley startup, Skype, smart cities, Snapchat, software as a service, Steven Levy, Stuxnet, technoutopianism, Tim Cook: Apple, undersea cable, WikiLeaks, Y2K, zero day

Automation and artificial intelligence have the potential to erase much of the attacker’s advantage. Yet, at the same time, attackers are looking at how they can use these tools as well. Quantum computing could provide both impossible-to-break protection for data and the ability to crack all current forms of encryption. Blockchain, which many technologists think could lead to fundamentally more secure protection of data, has for the time being found its biggest use in cryptocurrency, a technology that is decidedly giving an advantage to attackers by allowing criminals to move their ill-gotten gains around anonymously. These technology trends could shift the balance in either direction. It is up to us to determine which way the scales will tip. The Pentagon has long identified four primary domains of conflict: land, sea, air, and space. In recent years, cyberspace has come to be known as the “fifth domain.”

Cloudy with a Chance of Security There is a bumper sticker that is ubiquitous on the back of laptops at hacking conventions like Black Hat and DEF CON. With a wink and a nod, it reads: MY OTHER COMPUTER IS . . . YOURS. Stealing computing resources from universities, corporations, and individuals used to be common practice, even among the “gray hat” hacking world that was more interested in research and less in criminal profit. While cyber criminals still use stolen computer resources for mining cryptocurrencies and for carrying out DDoS attacks, when they need real computing power or to hide their tracks, they turn to the same company that you do for your socks and kitchen supplies: Amazon. With a stolen credit card or a compromised account, criminals can spin up a virtual server on Amazon as easily as you can buy an ebook. According to data from Spamhaus, a nonprofit corporation that tracks online spam propagation, Amazon is one of the worst sources of all kinds of malicious cyber activity.

No matter how innocent or authentic an email appears, do not click any link or open any attachment contained within it without first checking the sender’s email address, or hovering over the link with your mouse to make sure that it really does go to the website it claims to go to. If the email is not legitimate, just delete it. You can lose everything on your device by slipping up just once. (Remember the gullible employee, Dave, from chapter 4? Don’t be Dave.) When your device becomes compromised, the attacker can use your computer’s power to participate in a flood attack on another network, or secretly steal your computational power to mine cryptocurrencies like Bitcoin. So, while they are not stealing data, files, or money from you, they are nonetheless hurting somebody somewhere with your computer. Without your knowing it, your machine is being used to do bad things. Every Move You Make, Every Step You Take It may or may not be a security risk, but it is more than a little creepy to think that somebody is watching you. Who wants a GRU officer in wintry Tula, during a boring shift posting Green Party propaganda on Facebook, amusing himself by seeing what’s going on in your house?


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Financial Freedom: A Proven Path to All the Money You Will Ever Need by Grant Sabatier

"side hustle", 8-hour work day, Airbnb, anti-work, asset allocation, bitcoin, buy and hold, cryptocurrency, diversified portfolio, Donald Trump, financial independence, fixed income, follow your passion, full employment, Home mortgage interest deduction, index fund, loss aversion, Lyft, money market fund, mortgage debt, mortgage tax deduction, passive income, remote working, ride hailing / ride sharing, risk tolerance, Skype, stocks for the long run, stocks for the long term, TaskRabbit, the rule of 72, time value of money, uber lyft, Vanguard fund

Don’t worry, it won’t take long for you to find your sweet spot—the point at which you are invested in a way that will make you as much money as possible while still letting you sleep at night. Over time, you’ll also get more comfortable taking calculated risks to make even more money. You can invest in a wide variety of things like art, wine, commodities, currencies, cryptocurrencies, domains, furniture, collectibles, businesses, and tons of other things. While you can make money investing in any of these things, for the purposes of this chapter, we’re not going to focus on investing in physical assets (like art, wine, or collectibles) or speculative financial instruments (like cryptocurrencies). Never invest in anything you don’t understand. Don’t put your money in investments that your friends or family or a financial advisor or someone you just met told you to invest in without understanding exactly what you are investing in and what the risk/reward trade-off is.

This is all meant to say, be cautious with your individual stock investments, and if you are just starting out, don’t invest more than 5 percent of your net worth into individual stocks. What is not included in the chart opposite are a few stocks that I lost money on and sold during this period (these amounted to less than $5,000 in losses), my investment in the Bitcoin cryptocurrency (which is highly speculative, and I don’t recommend investing any more than 1 percent of your net worth in any cryptocurrency), or any of my real estate investments. Investments 2010 2011 2012 2013 2014 2015 Index Funds Vanguard Total Stock Market Index Fund (shares) 520 4894 6903 9821 12552 14616 price per share (as of last day of year) $31.57 $31.30 $35.65 $46.69 $51.60 $50.79 Total Value $16,416 $153,182 $246,092 $458,542 $647,683 $742,347 Vanguard Total International Stock Index (shares) 1892 2785 3218 3449 price per share (as of last day of year) $25.05 $28.01 $26.00 $24.24 Total Value $47,395 $78,008 $83,668 $83,604 Individual Stocks Amazon (shares) 30 200 200 300 300 400 price per share (as of last day of year, adjusted for splits) $180.00 $173.10 $250.87 $398.79 $310.35 $675.89 Total Value $5,400 $34,620 $50,174 $119,637 $93,105 $270,356 Facebook (shares) 800 900 900 1070 price per share (as of last day of year, adjusted for splits) $25.91 $54.65 $78.02 $104.66 Total Value $20,728 $49,185 $70,218 $111,986 Apple (shares) 100 100 100 300 300 400 price per share (as of last day of year, adjusted for splits) $41.46 $52.05 $69.00 $74.57 $104.86 $101.70 Total Value $4,146 $5,205 $6,900 $22,371 $31,458 $40,680 Total Income $43,000 $294,000 $233,000 $248,000 $239,000 $271,000 Savings Rate 53.49% 40.68% 55.97% 68.10% 57.45% 60.48% Total Invested Each Year $23,000 $119,610 $130,402 $168,895 $137,317 $163,901 Total invested in Portfolio $23,000 $142,610 $273,012 $441,907 $579,224 $743,125 Total Percentage Growth 12.88% 35.34% 36.00% 64.68% 59.89% 68.07% Portfolio Total $25,962 $193,007 $371,289 $727,743 $926,132 $1,248,973 CONCLUSION The more you invest, the more your money will grow.

., 61, 132, 159, 175, 179, 205 housing and real estate in, 64–65, 67, 146, 271, 274, 279 clothing, 77, 122–23, 159, 180, 188 expenses and, 52, 58–59, 62, 65, 120, 127, 133, 136, 142–43 compounding, 59, 85, 176, 305 expenses and, 59, 75, 138 investing and, 22–23, 33, 35, 43–44, 46–49, 72–75, 84, 94, 96, 100, 108,114, 143, 169, 210, 237, 246–47, 258, 265, 285, 289–91, 296 job hacking and, 162, 169 money growth and, 2, 21–23, 33, 35, 76 retiring and, 21–24, 39, 43–44, 46–49, 61, 74 side hustles and, 108, 111, 185 your number and, 55–56, 59, 72–74 consulting, 21, 107, 123, 192, 194 cost of living, 63–65, 278, 312 credit, credit scores, 21, 85, 151, 190, 268–69, 271, 273–74, 307 credit cards, 7, 16, 51, 120, 130, 306 daily habits and, 89–90 net worth and, 77, 81–82 and paying down debt, 84–85 of Sabatier, 151–52, 214 side hustles and, 190, 192 transportation and, 148, 150–52 cryptocurrencies, 211, 256 daily habits, 17, 216, 305 expenses and, 54, 88–90, 135 riches and, 88–92 of Sabatier, 11, 90–91, 135 debts, debt, 15–16, 51, 57, 130, 307–8 investing and, 276–77 net worth and, 76–82, 91 paying down, 83–86, 88–89, 91–92 of Sabatier, 7–8, 84 your number and, 13, 36, 51 dependent care FSAs, 250–51 digital marketing, 20, 109, 124, 175, 181–82, 191, 193–94, 207 dividends, 22, 25, 46, 111, 220, 232, 235, 238, 252, 255, 264, 292, 297 dog walking, 104, 110, 133, 179, 181, 183–84, 188–89, 197–99, 201–2, 208 domain name flipping, 20, 109, 181–82 donations, 2–3, 52, 62, 65, 307, 316 down payments: low, 268–69, 271–72, 274 real estate investing and, 147, 263, 265–66, 268–74, 279, 285 education, 6, 12, 133, 181–82 expenses and, 55–56, 130, 147 investing and, 251, 278 living richer life and, 313–15 net worth and, 77, 81–82 and paying down debt, 84–85 side hustles and, 193–96, 209 student loans and, 8, 55–56, 77, 81–82, 84–85, 130, 147, 313 emergency funds, 43, 214, 273 emotions, 38, 86–89, 91–92, 207, 285, 316 employment, 1, 3, 5–11, 63, 77, 298 benefits of, 9, 14, 105–7, 156–61, 173, 177, 302 bonuses and, 159, 161, 163, 169, 259, 262 enterprise mindset and, 104–10, 119 equity in, 105, 160–61 full-time, 104–11, 113, 119, 122, 155–80, 183, 187, 191, 193–96, 203, 208, 250, 278, 290, 300 future-optimization framework and, 301–3 incomes and, 122–25, 139, 153, 179, 193, 203 investing and, 16, 21, 26, 86, 92, 156, 158, 214, 224, 226–28, 239–40, 245–46, 250, 259, 262, 271, 278, 287–88, 290 job hacking and, 14, 105–7, 155–78 lifestyle and, 57–58, 60–61 living richer life and, 312–15, 317 long-term strategy for, 174–77 and meanings of financial freedom, 15, 18 part-time, 36, 39, 61, 108, 297 promotions and, 58, 105, 161 raises and, 11, 14, 105, 107, 159, 162–73, 177–78, 300–302, 315, 317 and relationship between time and money, 32–34 retiring and, 19–21, 26, 29–31, 34–35, 39, 47, 60–61, 68 of Sabatier, 5–10, 33, 35–36, 58, 104, 124, 148, 151, 162, 175–76 Sabatier’s parents and, 28–29 savings and, 20–21, 26, 30, 95, 313, 315 short-term strategies for, 156–73 side hustles and, 104, 108–10, 179–80, 183, 187, 191–96, 203, 208, 300 and thinking about money before buying, 128–29, 131 transportation and, 147–48 unemployment and, 5, 7–8 working remotely and, 11, 14, 106–7, 156, 158–60, 165–66, 177, 187, 315 your market value and, 163–67, 169–71, 173–74, 177–78 your number and, 13, 36 and your value to your company, 163–64, 167–70, 173, 177–78 Enron, 231 enterprise mindset, 103–19, 155, 300 employment and, 104–10, 119 entrepreneurship and, 104, 108, 110–13, 119 investing and, 103–4, 106, 113–19, 180 side hustles and, 104, 108–13, 119, 180 entertainment, 53, 62, 65, 142–43, 189 entrepreneurship, 2, 10, 20 enterprise mindset and, 104, 108, 110–13, 119 side hustles and, 104, 110–13, 119, 189–90, 194, 200, 207 equity, 309 job hacking and, 105–6, 160–61 real estate and, 266, 268, 270, 273, 276–78 exchange traded funds (ETFs), 222, 226, 229, 232, 234, 237, 243, 258 expenses, 3, 11, 16, 31–32, 35–40, 96–103, 124–54, 300 affordability and, 17–18, 21, 25, 57, 63, 67, 105, 126–31, 139 budgeting and, 13, 140, 143, 147, 152 building wealth and, 93–94, 118 comparing price percentages and, 131–32, 134, 139 for convenience, 133–35, 139 daily habits and, 54, 88–90, 135 enterprise mindset and, 103, 105, 111, 118 future-optimization framework and, 306–8 and future value of money, 136–37, 139 happiness and, 125–27, 138–39 housing and, 3, 9–10, 21, 25, 52, 54, 58–61, 63–67, 127, 130–31,133–34, 140–47, 154 incomes and, 21, 50, 124, 127–33, 135, 142–44 inflation and, 24–25, 45 investing and, 47, 51, 59, 128, 131, 133, 136–37, 141–44, 214, 263, 267, 271–72, 276, 280–82, 284–85, 287, 289–92, 295, 297, 313 job hacking and, 105, 156, 168 lifestyle and, 17–18, 21, 57–63 living richer life and, 313, 315–17 net worth and, 83, 130 onetime future, 55–56 and paying down debt, 84–85 and per-use costs of items, 135–36, 139 purchasing power and, 24–27, 45, 127 recurring, 50, 54–55, 135, 138 retiring and, 21, 24–28, 39–40, 42–43, 45, 47–56, 60–61, 69–70, 74 of Sabatier, 7, 17–18, 38, 42–43, 58, 61–62, 132–36, 138, 307–8, 311–12 savings and, 42–43, 74, 96–101, 120–21, 126–28, 130, 132–33, 137–38, 140–44, 153–54 side hustles and, 14, 69–70, 188–90, 192, 199, 207, 209 and thinking about money before buying, 120–21, 125–39 trading and, 132–33, 139 value and, 120, 126–27 your number and, 13, 36–38, 50–57, 59–60, 62–66, 68–70, 75, 135, 137, 276 Facebook, 58, 189, 196, 304 investing in, 228, 256–57 Fidelity, 228, 232–33, 252 fiduciaries, 212 financial advisors, 11–12, 50, 87, 131 fees of, 225–28, 260, 296, 309 investing and, 210–12, 225–28, 235, 260, 296 financial freedom: levels of, 16–17 meanings of, 15–18, 36 529 plans, 251 flexible spending accounts (FSAs), 156–57, 177, 250–51 food, 2, 30, 38, 83, 180 expenses and, 25, 52, 54–55, 58, 61–62, 65–66, 132–36, 140–43, 151–54 inflation and, 25, 35 of Sabatier, 5–7, 132, 135, 153 savings and, 142–43, 152–54 your number and, 52, 54–55 foreclosures, 283, 286 four fund investments, 235–36 401(k) accounts: employer contributions to, 21, 26, 86, 92, 156, 158, 239–40, 245–46 fees of, 224, 226–29 investing in, 79, 216, 218, 223–24, 226–29, 236–47, 249–51, 254,258–59, 262, 293–95, 298–99, 301–2 job hacking and, 105, 156–58 retiring and, 20–21, 26–28, 45 savings rates and, 95, 118 403(b) accounts, 224, 228–29, 236–37, 241–46, 249, 254, 262, 293, 295, 298 457(b) accounts, 241–45, 251, 254, 293, 298 frugality, 28, 35, 38, 314 future-optimization framework, 300–310 chilling and hustling in, 309–10 executing consistently in, 305–8, 310 focusing intensely and learning to say no in, 303–5, 310 just getting started in, 301–3, 310 principles of, 301–9 sharing and asking for help in, 308–10 geographic arbitrage, 67 Glassdoor, 21, 165, 177 gold, investing in, 229, 237, 262 Google, 9, 107, 149, 161, 166, 175 investing and, 233, 237, 284 side hustles and, 182, 189, 200 Graham, Benjamin, 255 Hamptons, N.Y., 63 health, healthcare, 1–2, 8, 19, 25, 33, 64, 297, 316 expenses and, 53, 58, 65, 142 insurance and, 53, 105, 156–57, 247 investing and, 234, 241, 243, 246–47, 250–52 job hacking and, 156–57, 177 of Sabatier, 309–10 your number and, 53, 56 health savings accounts (HSAs), 156–57, 177, 241, 243, 246–47, 250–52, 293, 298 hobbies, 34, 53, 189, 191, 195–96 home inspectors, 284, 286 homes, housing, 2, 9–11, 30, 38, 179 affordability of, 49, 270–75 and cost of living, 63–65 expenses and, 3, 9–10, 21, 25, 52, 54, 58–61, 63–67, 127, 130–31, 133–34, 140–47, 154 hacking of, 145–47, 154, 264, 285 inflation and, 25, 35, 45, 67 investing and, 213, 263–64, 270–75, 279, 283–84 lifestyle and, 58–60, 62–63, 65–66 living rent-free and, 144–47 living richer life and, 313–15 location and, 63–67 net worth and, 76, 79, 83, 91 renting vs. buying of, 266–68, 302 retiring and, 45, 49, 52, 54, 56, 60, 144 of Sabatier, 5–7, 9–10, 61, 63–64, 84, 143–44, 147, 274–75 savings and, 63, 67, 141–47, 154 your number and, 52, 54, 66–67 see also real estate house-sitting, 58, 63, 145–47, 154 incomes, 1–3, 7–17, 26–39, 86–87, 90–119, 148, 300 building wealth and, 93–94, 118 compounding and, 94, 111, 108 daily habits and, 90, 92 employment and, 122–25, 139, 153, 179, 193, 203 enterprise mindset and, 103–19 expenses and, 21, 50, 124, 127–33, 135, 142–44 food and, 152–53 future-optimization framework and, 303, 306–10 housing and, 143–44, 146–47 investing and, 8, 16, 30, 43, 82–83, 91, 104, 114–19, 179, 181, 210–16, 218, 220, 224–25, 230, 233–35, 237, 239–41, 243–54, 258–60, 262, 270–71, 275–80, 285, 287–94, 296–98, 314 job hacking and, 14, 105–6, 155–57, 159–60, 162–80 lifestyle and, 57, 59–60 living richer life and, 312–15, 317–18 net worth and, 77, 83, 91 passive, 14–15, 34, 39, 43, 74, 109, 111–14, 119, 188–89, 192, 209–10,260, 278, 289, 298, 306–7 real hourly rates of, 121–25, 129, 134–35, 139, 307 recurring, 68–70, 75, 109 and relationship between time and money, 32–34 rental, 43, 68–69, 83, 111, 147, 189, 266, 271, 276–79, 288–89, 306 retiring and, 20–21, 24, 26–28, 30, 35, 39, 42–43, 46, 50, 60–61, 69, 74 of Sabatier, 1–2, 7–10, 17, 20, 30, 38, 42–43, 103–4, 118, 124, 135, 175–76, 181, 183, 194, 202, 205, 214, 217, 220, 302, 307–9, 311 savings and, 20–21, 24, 26–28, 33, 94–101, 108, 115–18, 170, 258, 312–13, 315 side hustles and, 9, 14, 42, 68–70, 74, 95, 104, 108–13, 119, 122, 153, 175–76, 179–84, 187–209, 216, 220, 289–91, 298, 306 your number and, 36–39, 68–70, 74, 82–83, 91, 169, 180, 189 index funds, 24, 230–38 building your own, 236–38, 261 dividends of, 232, 235, 238 fees of, 225–26, 228, 232, 234–36, 238 international, 235–36 investing in, 215, 222–23, 225–26, 228, 232–38, 254–57, 261–62 large-cap, 236–38 mid-cap, 236–38 most popular, 232–33, 237 returns of, 215, 222–23 small-cap, 236–38 socially responsible, 234–35 individual retirement accounts (IRAs), 28, 95, 118 investing in, 223, 226, 228, 237, 241–43, 246–49, 254–55, 262, 293, 295–96, 298–99, 302 opening and maxing out of, 247–49 see also specific individual retirement accounts inflation: housing and, 25, 35, 45, 67 investing and, 22, 25, 35, 39–42, 46, 114, 138, 213–14, 219, 264, 290 lifestyle and, 57, 62 retiring and, 24–28, 40–42, 45–46, 94 savings and, 8–9, 24–28 and value of money, 25–27, 35, 43, 88 your number and, 36, 56 insurance, 313 expenses and, 52–53, 62, 65, 142, 148 healthcare and, 53, 105, 156–57, 247 housing and, 65, 273–74 investing and, 267, 273–74 job hacking and, 105, 156–57, 177 Intelligent Investor, The (Graham), 255 interest, 88–89, 131, 147, 313 compounding and, 22–23, 55, 59, 73–74, 169, 176 investing and, 85–86, 108, 115–17, 179, 214–15, 220–23, 239–40, 266, 268–76, 281 net worth and, 77–82 and paying down debt, 84–86, 89, 92 retiring and, 24, 26, 28, 45, 47–49, 51 savings and, 88, 143–44 your number and, 51, 55–56 Internal Revenue Service (IRS), 49n, 213, 248, 268, 293 internet, 30, 52, 103, 109, 123, 156, 181 investments, investing, 2–3, 8–12, 14, 30–31, 33–37, 90, 184, 210–302 automation and, 216–17, 258–59, 262, 302, 307, 312 compounding and, 22–23, 33, 35, 43–44, 46–49, 72–75, 84, 94, 96, 100, 108, 114, 169, 210, 237, 246–47, 258, 265, 285, 289–91, 296 determining target asset allocation in, 217–24, 261 dividends and, 22, 25, 46, 111, 220, 232, 235, 238, 252, 255, 264, 292, 297 emergency funds and, 43, 214 emotions and, 86–88, 285 enterprise mindset and, 103–4, 106, 113–19, 180 expenses and, 47, 51, 59, 128, 131, 133, 136–37, 141–44, 214, 263, 267, 271–72, 276, 280–82, 284–85, 287, 289–92, 295, 297, 313 fast-track strategy for, 210–62 fees of, 211–12, 224–38, 252, 260–61, 267, 296, 300, 307 figuring out how much money you have for, 216–17, 260–61 financial freedom levels and, 16–17 future-optimization framework and, 301–2, 306–8 gambling vs., 210–11 how to contribute to, 244–51 inflation and, 22, 25, 35, 39–42, 46, 114, 138, 213–14, 219, 264, 290 international, 216, 229–30, 235–36 job hacking and, 106, 156–58, 161–62, 168–69 lifestyle and, 57, 59–61, 259, 267, 278 living off them, 287–99, 312, 314 living richer life and, 312–17 long-term, 22, 213, 216, 230–32, 253–55, 260, 275–78, 286, 289 maxing out of, 211, 213, 239–51, 262 net worth and, 76–79, 82–83, 91, 108, 146, 223, 256, 268, 273, 276 and paying down debt, 84–86, 88, 92 rates of, 216–18, 259, 262, 302 real estate and, 2, 43, 119, 131, 146–47, 212–13, 237, 256, 260,262–86, 289, 300, 302 rebalancing of, 223–24, 236, 238, 261, 307 retiring and, 8–9, 21–28, 39–44, 46–51, 54–56, 60–61, 74–75, 179, 212, 215–22, 226, 229, 239, 242, 244–48, 251, 275, 287–92, 294–99 returns of, 22, 43–44, 46, 211, 213, 215, 222–23, 228, 239–40, 243, 245–46, 252, 254–55, 257–62, 264–66, 271–72, 274, 280, 285, 289–92, 294, 296, 300, 312–13 of Sabatier, 9–10, 30, 36, 95, 108, 114–18, 144, 181–83, 213–14,216–17, 220, 236, 256–57, 274–75, 285–86, 308 savings and, 95, 114–19, 143–44, 153–54, 213–17, 225, 239, 254, 258, 267–68, 273, 285, 287 selection of, 228–31, 254–55, 261–62 short-term, 213–16, 230, 260, 275, 286 side hustles and, 69–70, 95, 108, 113, 179–83, 187–88, 190, 192, 208, 216, 218, 220, 249–50, 259, 262, 264, 289–91, 298 taxes and, 46, 114, 211–15, 218, 224, 228, 232, 237, 239–55, 260, 262–68, 270–72, 275–77, 281–82, 285, 288, 291–300, 315 withdrawals from, 39–44, 46–49, 51, 54–56, 61, 66, 68–70, 239–45, 247–48, 251–54, 260, 262, 287–99 your number and, 37, 47, 49–51, 54–56, 66, 68–70, 72–74, 82–83, 91, 137, 179, 181, 210, 213, 216, 221, 259–60, 275–76, 287–89 see also under bonds; brokerage accounts; incomes; stocks, stock market iShares, 232, 234 Kelly, Brian (The Points Guy), 192 lawyers, law firms, 95, 144, 167, 193–94, 205, 224, 280, 313–14 website building for, 181–82, 194, 202 liabilities, 76–82, 91, 265 lifestyle, 28, 74, 158 expenses and, 17–18, 21, 57–63 housing and, 58–60, 62–63, 65–66 investing and, 57, 59–61, 259, 267, 278 of Sabatier, 9, 61–62 side hustles and, 111, 113, 191, 207–9 your number and, 15, 37, 59–60, 62 limited liability companies (LLCs), 179, 189–90, 309 load fees, 224 loans, 89, 151, 215 expenses and, 130–31, 147 investing and, 260, 263–64, 268–69, 271, 273, 279, 281, 285–86 net worth and, 77, 81–82 paying down, 84–85 preapproved, 281, 286 to students, 8, 55–56, 77, 81–82, 84–85, 130, 147, 313 Los Angeles, Calif., 148, 159, 271–72, 282 loss aversion, 88 Millennial Money, 11, 107, 146, 156, 164, 166, 168–69, 182 model portfolios, 229 Money Talk Cards, 305, 308 mopeds, 20, 109, 148, 182 mortgages, 52, 58, 66, 81–84, 131, 151 adjustable rate (ARMs), 268–70 fifteen–year, 269–70, 274 fixed rate (FRMs), 268–69, 274 investing and, 263–64, 266–77, 281, 283, 285–86 net worth and, 77, 81–82 preapproved, 281, 286 savings and, 146, 154 thirty-year, 269–70 mutual funds, 226, 229, 241, 243, 258 net worth, 13, 76–83, 122, 300, 312 calculation of, 76–77, 91 definition of, 82–83, 91 future-optimization framework and, 305–6, 308 investing and, 76–79, 82–83, 91, 108, 146, 223, 256, 268, 273, 276 negative, 82, 130–31 real estate and, 77–79, 83, 146 of Sabatier, 9–10, 82, 108, 114 savings and, 76, 79, 82, 146 side hustles and, 77, 108 and thinking about money before buying, 130–31, 137 your number and, 82–83, 91 New York City, 15, 150, 152, 166 housing and real estate in, 63–67, 271, 282, 315 1 percent rule, 281–82 passions, 2–3, 9, 33–35, 127 analysis of, 191–94, 209 in retirement, 297, 299 side hustles and, 11, 188, 191–96, 209 present value formula, 55–56 private mortgage insurance (PMI), 273–74 real estate: affordability of, 267, 270–75 and being prepared to walk away from deals, 285–86 buying and holding, 275, 286 case for, 264–66 criteria to follow for, 280–81, 285–86 finding properties and, 280–86 flipping of, 275–76, 286 with high rent appreciation potential, 281–82, 286 investing and, 2, 43, 119, 131, 146–47, 212–13, 237, 256, 260, 262–86, 289, 300, 302 net worth and, 77–79, 83, 146 refinancing of, 268, 270, 273 scaling in, 278–80, 286 test driving neighborhoods and, 284, 286 and thinking about money before buying, 127, 130–31, 133 see also homes, housing real estate agents, 182, 194, 283 real estate investment trusts (REITs), 237, 262 Realtors, 194, 279, 281–83, 286 recruiters, recruiting, 163, 165–66, 170, 173, 177, 192 retiring, retirement, 1, 8–12, 18–31, 34–36, 38–56, 308, 310 housing and, 45, 49, 52, 54, 60, 144 how much money actually needed for, 44–49 inflation and, 24–28, 40–42, 45–46, 94 investing and, 8–9, 21–28, 39–44, 46–51, 54–56, 60–61, 74–75, 179, 212, 215–22, 226, 229, 239, 242, 244–48, 251, 275, 287–92, 294–99 with less money at thirty than at sixty, 38–39, 47, 54 lifestyle and, 60–61, 74 living richer life and, 313, 315–16 and money for rest of your life, 42–44 and paying down debt, 84, 86 rewriting of, 28–31 of Sabatier, 8, 35, 45, 275 savings and, 8–9, 11, 20–22, 24–30, 38–40, 44–49, 51, 54–56, 60–61, 74, 94–96, 141, 144, 251 side hustles and, 43–44, 61, 69–70, 74, 179, 188, 192 time and, 19, 27, 45–47, 49n, 297–99 Trinity study and, 39–44 your number and, 36, 49–56, 68–70, 72–74 ride-sharing, 52, 109, 148 side hustles and, 183, 187, 190 risks, risk, 10, 16, 40, 49, 309 daily habits and, 89, 91–92 emotions and, 87–88 investing and, 14, 87, 106, 113–14, 211, 213, 215, 217–23, 229–30, 235, 237–38, 255–56, 260–61, 263–64, 269, 271, 279, 285, 289–91, 301, 317 side hustles and, 108, 112–13, 194, 202, 204 Robin, Vicki, 1–3, 32 robo-advisors, 212 Roth 401(k) accounts, 241, 243–45, 294, 298 Roth IRA accounts: conversion ladder for, 295, 298–99 investing in, 79, 95, 214, 218, 228, 241, 243–44, 247–49, 251, 258, 294–96, 298–99, 302 Rule of 72, 59, 75 Run the Trap, 191 S&P 500, 228, 232–38, 261 San Francisco, Calif., 64, 271, 282 savings, saving, 3, 5–11, 140–54 building wealth and, 93–94, 118 compounding and, 55, 59, 72, 94, 96, 143 daily habits and, 88–90 emotions and, 87–88 enterprise mindset and, 103, 107, 113–17 expenses and, 42–43, 74, 96–101, 120–21, 126–28, 130, 132–33, 137–38,140–44, 153–54 financial freedom levels and, 16–17 food and, 142–43, 152–54 future-optimization framework and, 301, 303, 305–6 housing and, 63, 67, 141–47, 154 inflation and, 8–9, 24–28 investing and, 95, 114–19, 143–44, 153–54, 213–17, 225, 239, 254, 258, 267–68, 273, 285, 287 job hacking and, 107, 159–60, 163, 170, 177 lifestyle and, 57–58, 60–61 living richer life and, 312–17 net worth and, 76, 79, 82, 146 rates of, 11, 13, 20–21, 24, 26–28, 33, 89, 94–101, 108, 114–19, 141,143, 213, 216–18, 256–58, 260, 300, 302–3, 305–6, 312–15, 317 retiring and, 8–9, 11, 20–22, 24–30, 38–40, 44–49, 51, 54–56, 60–61, 74, 94–96, 141, 144, 251 of Sabatier, 5–7, 9–11, 30, 45, 63, 95, 138, 143–44, 148, 151–53, 216–17, 256–57, 300, 302, 311–12 side hustles and, 113, 179 time and, 32–33, 94, 96–101, 118 transportation and, 141–43, 147–52, 154 your number and, 36–37, 39, 51, 54–56, 59, 68, 70–75, 94–95, 97–101, 118, 137, 141 see also health savings accounts saying no, 127, 208, 303–5, 310, 312 Charles Schwab, 232–33, 252 search engine optimization (SEO) projects, 175, 182 sequence-of-returns risk, 290–91 short sales, 283, 286 side hustles, 11, 14, 90, 153, 179–209, 300, 317 benefits of, 109–10, 185, 189 competitive analysis for, 200–203, 205, 209 enterprise mindset and, 104, 108–13, 119, 180 evaluation framework for, 190–209 in evenings, 186 figuring out what to charge for, 201–4, 209 future-optimization framework and, 301–3, 306 getting your first sale and, 204–6 hiring others for, 109, 111–13, 119, 206–7 in in-between moments, 187–89 incomes and, see under incomes investing and, 69–70, 95, 108, 113, 179–83, 187–88, 190, 192, 208, 216, 218, 220, 249–50, 259, 262, 264, 289–91, 298 job hacking and, 156, 160, 175 and knowing when to scale, 206–9 LLCs and, 179, 189–90 in mornings, 185 net worth and, 77, 108 retiring and, 43–44, 61, 69–70, 74, 179, 188, 192 of Sabatier, 9, 20, 58, 95, 104, 108–9, 175–76, 181–83, 185–86, 188, 194–95, 202–3, 205, 207–8 skills and, 109, 119, 175, 190–97, 201–2, 209 supply and demand for, 179, 182, 189, 194, 197–204, 206, 209 taxes and, 189–90, 249 time and, 108, 111, 180–87, 190, 199–200, 202–3, 207–9, 303 transportation and, 148, 187, 189, 192–93, 196, 208 on weekends, 186 and working for someone else vs. for yourself, 183–84, 207–9 your number and, 69–70, 179–81, 189, 209 your story in, 204–5 simplified employee pension individual retirement accounts (SEP IRAs), 79, 218, 228, 241, 243, 249–51 skills, 10, 51, 104, 133 analysis of, 191–94, 209 job hacking and, 14, 105, 156, 159, 164–66, 169, 174–78 learning new ones, 195–96, 209 retiring and, 34, 44 side hustles and, 109, 119, 175, 190–97, 201–2, 209 Social Security, 8, 26, 45n, 249, 269 expenses and, 53, 128, 141–42 Solo 401(k) accounts, 241, 243, 249–50 stocks, stock market, 160 buying individual, 254–57 compounding and, 22, 72 dividends paid by, 22, 25, 46, 111 emotions and, 86–87 international, 216, 229–30, 235–36 investing in, 2, 9, 17, 24–26, 34, 39–42, 46–47, 84, 86–87, 104, 114, 119, 162, 211–26, 228–38, 241–42, 244, 252–58, 260–62, 264–65, 273–79, 285, 287, 289–91, 297 past performance of, 222–23 and paying down debt, 84–86 retiring and, 39–44, 46–49 selection of, 228–29, 230–31, 255, 261 your number and, 36, 72 target date funds, 228–29, 238 taxes, 59, 64, 77, 83–84, 88, 102, 143 deductions and, 84, 128, 189–90, 240–42, 245–52, 254, 266–68, 276, 294,296–98 enterprise mindset and, 103, 114, 118 future-optimization framework and, 307–9 inflation and, 25, 45 investing and, 46, 114, 211–15, 218, 224, 228, 232, 235, 237, 239–55, 260, 262–68, 270–72, 275–77, 281–82, 285, 288, 291–99, 300, 315 job hacking and, 157–58 real hourly income rates and, 122–25, 129 retiring and, 19, 27, 45–47, 49n, 297–99 of Sabatier, 7–8 savings rates and, 95–96, 118 side hustles and, 189–90, 249 and thinking about money before buying, 120, 127–30 your number and, 52–53, 68–69 1031 exchanges, 264–65, 275 three fund investments, 235–36 time, 2, 10, 63, 153 compounding and, 22, 33, 305 daily habits and, 90–91 enterprise mindset and, 103, 105–6, 108, 111, 118–19, 300 expenses and, 32, 75, 129–30, 133–39 future-optimization framework and, 301, 303–5, 307–10 investing and, 33–34, 118, 133, 210, 212, 214–15, 224, 239, 283, 308 job hacking and, 105–6, 155–56, 160–64, 166–68, 170–73, 177–78 living richer life and, 312, 314–17 real hourly income rates and, 121–25, 129, 134–35, 139, 307 relationship between money and, 19, 32–35, 106, 111, 113, 121, 129, 133, 184, 188, 207–10, 303–4, 307–8, 310 retirement and, 19, 27, 45–47, 49n, 297–99 savings and, 32–33, 94, 96–101, 118 side hustles and, 108, 111, 180–87, 190, 199–200, 202–3, 207–9, 303 transportation and, 32–33, 148 Top Five Regrets of the Dying, The (Ware), 29–30 total stock market funds, see index funds trading, 132–33, 139 transportation, 32–35, 64, 91, 213, 297, 299, 313 expenses and, 25, 52, 54, 58–59, 61–62, 65–66, 75, 127, 140–43, 147–52, 154 housing and, 65–66, 145 job hacking and, 156–60 lifestyle and, 58–59, 61–62 real hourly income rates and, 122–25, 139 of Sabatier, 148, 151–52 savings and, 141–43, 147–52, 154 side hustles and, 148, 187, 189, 192–93, 196, 208 time and, 32–33, 148 travel-hacking and, 148–52, 154 your number and, 52, 54, 59 Trinity study, 39–44 vacations, 6, 9, 17, 28, 34, 52, 91, 105, 156, 187, 192, 278 expenses and, 130–31, 147 valuables, 52, 77–79, 83 value investing, 255 Vanguard, 212, 215, 234, 252 500 Index Fund Admiral Shares (VFIAX), 232–33 500 Index Fund Investor Shares (VFINX), 228, 232–33 Total Stock Market ETF (VTI), 222, 226, 232 Total Stock Market Index Fund (VTSAX), 228, 232–33, 257 Volkswagen (VW) campers, 8, 109, 182 Wang, Jim, 192 Ware, Bronnie, 29–30 wealth, 2–3, 16, 28, 38, 230 building of, 6, 11–12, 76, 86, 88, 93–94, 103, 118 daily habits and, 88–90 emotions and, 86, 88 job hacking and, 155, 162 net worth and, 76, 82 website building, 20, 58, 104, 175, 194–95, 201–3, 205, 207 for law firms, 181–82, 194, 202 We Need Diverse Books, 314–15 Your Money or Your Life (Robin and Dominguez), 2–3, 32 your number, 77, 307 breaking it down into smaller goals, 70–76 calculation and recalculation of, 13, 15, 44, 49–57, 66–69, 72, 75–76,82–83, 288–89, 300 definition of, 13, 82, 91 expenses and, 13, 36–38, 50–57, 59–60, 62–66, 68–70, 75, 135, 137, 276 housing and, 52, 54, 66–67 incomes and, 36–39, 68–70, 74, 82–83, 91, 169, 180, 189 investing and, 37, 47, 49–51, 54–56, 66, 68–70, 72–74, 82–83, 91, 137, 179, 181, 210, 213, 216, 221, 259–60, 275–76, 287–89 job hacking and, 155, 169, 174 lifestyle and, 15, 37, 59–60, 62 living richer life and, 312, 316 net worth and, 82–83, 91 of Sabatier, 12–13, 36 savings and, 36–37, 39, 51, 54–56, 59, 68, 70–75, 94–95, 97–101, 118, 137, 141 side hustles and, 69–70, 179–81, 189, 208 ABCDEFGHIJKLMNOPQRSTUVWXYZ ABOUT THE AUTHOR Grant Sabatier, called "The Millennial Millionaire" by CNBC, is the Founder of MillennialMoney.com, which has reached over 10 million readers.


pages: 463 words: 105,197

Radical Markets: Uprooting Capitalism and Democracy for a Just Society by Eric Posner, E. Weyl

3D printing, activist fund / activist shareholder / activist investor, Affordable Care Act / Obamacare, Airbnb, Amazon Mechanical Turk, anti-communist, augmented reality, basic income, Berlin Wall, Bernie Sanders, Branko Milanovic, business process, buy and hold, carbon footprint, Cass Sunstein, Clayton Christensen, cloud computing, collective bargaining, commoditize, Corn Laws, corporate governance, crowdsourcing, cryptocurrency, Donald Trump, Elon Musk, endowment effect, Erik Brynjolfsson, Ethereum, feminist movement, financial deregulation, Francis Fukuyama: the end of history, full employment, George Akerlof, global supply chain, guest worker program, hydraulic fracturing, Hyperloop, illegal immigration, immigration reform, income inequality, income per capita, index fund, informal economy, information asymmetry, invisible hand, Jane Jacobs, Jaron Lanier, Jean Tirole, Joseph Schumpeter, Kenneth Arrow, labor-force participation, laissez-faire capitalism, Landlord’s Game, liberal capitalism, low skilled workers, Lyft, market bubble, market design, market friction, market fundamentalism, mass immigration, negative equity, Network effects, obamacare, offshore financial centre, open borders, Pareto efficiency, passive investing, patent troll, Paul Samuelson, performance metric, plutocrats, Plutocrats, pre–internet, random walk, randomized controlled trial, Ray Kurzweil, recommendation engine, rent-seeking, Richard Thaler, ride hailing / ride sharing, risk tolerance, road to serfdom, Robert Shiller, Robert Shiller, Ronald Coase, Rory Sutherland, Second Machine Age, second-price auction, self-driving car, shareholder value, sharing economy, Silicon Valley, Skype, special economic zone, spectrum auction, speech recognition, statistical model, stem cell, telepresence, Thales and the olive presses, Thales of Miletus, The Death and Life of Great American Cities, The Future of Employment, The Market for Lemons, The Nature of the Firm, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, Thorstein Veblen, trade route, transaction costs, trickle-down economics, Uber and Lyft, uber lyft, universal basic income, urban planning, Vanguard fund, women in the workforce, Zipcar

Such a system combines the best of both tipping and rating, creating a real cost to expressing enthusiasm, but also discouraging free-riding and allowing other participants to benefit from the feedback. A version of this system is being implemented by a social network called Akasha, based on the increasingly prominent Ethereum cryptocurrency.48 QV fits with the framework of cryptocurrencies, which require formal governance rules to allow for the decentralized management they rely on, so using it also for social aggregation in such a context is natural. However, the exact implementation is unclear at the time of this writing, and not available to the public; much in the world of cryptocurrencies is secretive. However, we hope that broader use of QV in these contexts will provide a more powerful test than political polling of how QV would work if adopted in social settings where norms and values would adapt to its use.

Steel and, 174 Monopoly (game), 43 monopsony, 190, 199–201, 223, 234, 238–41, 255 Moore’s Law, 286–87 mortgages, 65–66, 70, 74–75, 130, 157 Morton, Fiona Scott, 191 Mullainathan, Sendhil, 114 Musk, Elon, 30 Muslims, 129, 131 mutual funds, 181–82, 193 Myerson, Roger, 50–51, 66, 69 Naidu, Suresh, 240 Napster, 212 National Health Service, 291 Nationalist revolution, 46 Nazis, 93–94 neoliberalism, 5, 9, 11, 24, 255 Nepal, 151–53, 157 Netflix, 221, 289–91, 314n17 network effects, 211, 236, 238, 243 neural networks, 214–19 New Deal, 176, 200 New World, 136 New Zealand, 10, 159 Nielsen, Jakob, 212 Nielsen ratings, 230 Niemöller, Martin, 94 Nobel Prize, xxi, 40, 49–50, 57, 66–68, 92, 97, 236, 278 Obamacare, 114–15, 116 Occupy Wall Street, 3 oligopsony, 234 Oman, 158 one-person-one-vote (1p1v) system, 82–84, 94, 109, 119, 122–24, 304n36, 306n51 open markets, 21–22, 24 OpenTrac, 30–31, 30–32 opt-out rules, 194, 274 Orange Is the New Black (TV series), 221 Organisation for Economic Cooperation and Development (OECD), 141, 147–49, 159–61, 171 ownership: banking industry and, 183, 184; capitalism and, 34–36, 39, 45–49, 75, 78–79; common, 31, 41–42, 49, 52, 54–55, 61, 147, 187–88, 253 (see also common ownership self-assessed tax [COST]); competition and, 20–21, 41, 49–55, 79; control and, 178–81, 183–85, 193; democracy and, 81–82, 89, 101, 105, 118, 124; developers and, 26, 30–33, 105; efficiency and, 34–38, 43, 48–52, 55, 58–60, 67, 69, 73; entrepreneurs and, xiv, 35, 39, 129, 144–45, 159, 173, 177, 203, 209–12, 224, 226, 256; feudalism and, 16, 34–35, 37, 41, 61, 68, 136, 230–33, 239; holdout risk and, 33, 62, 71–72, 88, 299n28; homeowners and, 17, 26, 33, 42, 56–57, 65; inequality and, 42, 45, 75, 79, 253; intellectual property and, 26, 38, 48, 72, 210, 212, 239; labor and, 146–47, 245, 247; land, 31–33, 38–39, 41, 68, 105, 173; landlords and, 37, 43, 70, 136, 201–2; liberalism and, 17–19, 26–27; liquidity and, 31, 69, 177–79, 194, 301n49; partial common, 52, 298n7; partnerships and, 52–54, 57, 174; peasants and, 35–37, 61, 136; property as monopoly and, 30–34, 37–44, 48–62, 65, 68, 72, 77, 79; public goods and, 253 (see also public goods); Quadratic Voting (QV) and, 105; Radical Markets and, 170, 173, 177–90, 193, 195, 199–200; self-assessment and, 31, 55–56, 61–62, 70, 72, 258, 260, 270, 302n63; shareholders and, 118, 170, 178–84, 189, 193–95; Smith on, 17–18; state, 19, 39, 42, 48 Page, Larry, 211 Pandora, 289, 292 Pareto efficiency, 110 partnerships, 52–54, 57, 174 PayPal, 212 Peloponnesian War, 83 pencils, 278–79 pensions, 157, 181 phalanx system, 83 Philosophical Radicals, 4, 16, 20, 22–23, 95 Pierson, Paul, 191 PNC Bank, 183, 184 Poland, 47 polls: elections and, 13, 111; Likert surveys and, 111–16, 120, 306n53; market research and, 111–16; Quadratic Voting (QV) and, 111–16, 118, 303n17; Trump and, 296n20 pollution, 44, 65, 98–105, 137, 299n28 populism, 3, 12–14, 146, 261, 265, 296n16 portfolio theory, 180 poverty, xv; COST and, 259; extreme, 164; Galbraith on, 125; George on, 36–37, 43, 250; migrants and, 166; peasants and, 35–37, 61, 136; serfs and, 35, 48, 231–32, 236, 255; slavery and, xiv, 1, 19, 23, 37, 96, 136, 255, 260; slums and, xiii, xviii, 17; prices: auctions and, xv–xix, 49–51, 70–71, 97, 99, 147–49, 156–57, 300n34; common ownership self-assessed tax (COST) and, 62–63, 67–77, 256, 258, 263, 275, 300n43, 317n18; competition and, 20–22, 25, 173, 175, 180, 185–90, 193, 201, 204, 244; computers and, 21; controls for, 132; democracy and, 92, 97–102; indexing and, 185–91, 302n63; Internet and, 21; labor and, 132, 156, 207, 212, 221, 235, 243–44; liberalism and, 7, 8, 17–22, 25–27; markets and, 278–80, 284–85; markup, 7, 8, 60; monopoly, 58–59, 179, 258, 300n43; property and, 31–42, 47–64, 67–77; public leases and, 69–72; Quadratic Voting (QV) and, 263, 275; Radical Markets and, 170–75, 179–80, 185–90, 193, 201, 204; resale price maintenance and, 200–201 private goods, 97, 99, 110, 122–24, 253, 262, 264, 271–72, 303n17 privatization, xiv, 9 “Problem of Social Cost, The” (Coase), 48 productivity, 9–10, 16, 38, 57, 73, 123, 240–41, 247, 254–55, 258, 278 profits: common ownership self-assessed tax (COST) and, 275, 300n43; democracy and, 99; human capital and, 258; inequality and, 6–7; labor and, 163, 208–9, 234, 258, 260; liberalism and, 6–7, 17–18; lobbyists and, 262; moral values and, 271; ownership and, 33, 59–60, 68, 78, 299n28; Radical Markets and, 171, 178–79, 185–89, 193, 199, 201 programmers, 163, 208–9, 214, 217, 219, 224 Progress and Poverty (George), 36–37, 43, 250 Progressive movement, 45, 137, 174–75, 200, 203, 262 property, xiv; capitalism and, 34–36, 39, 45–49, 75, 78–79; central planning and, 39–42, 46–48, 62; common ownership self-assessed tax (COST) and, 31, 61–79, 271–74, 300n43, 301n47; competition and, 41, 49–55, 79; democracy and, 83, 88, 96, 99; developers and, 26, 30–33, 105; efficiency and, 34–38, 43, 48–52, 55, 58–60, 67, 69, 73; eminent domain and, 33, 62, 89; feudalism and, 16, 34–35, 37, 41, 61, 68, 136, 230–33, 239; freedom and, 34–39; George on, 36–37, 42–46, 49, 51, 59, 66; gift of nature and, 40; hoarding of, 255; holdout risk and, 33, 62, 71–72, 88, 299n28; homeowners and, 17, 26, 33, 42, 56–57, 65; inequality and, 42, 45, 75, 79, 253; investment in, 33, 35, 37, 43, 49–54, 58–61, 66–67, 71, 73, 76–78, 255, 299n28; labor and, 34–39, 45, 67, 73–79, 136, 147, 210, 212, 239; laissez-faire and, 253; landlords and, 37, 43, 70, 136, 201–2; landowners and, 31–33, 38–39, 41, 68, 105, 173; liberalism and, 17–18, 25–28; liquidity and, 31, 69, 177–79, 194, 301n49; markets and, 40–45, 282; monopolies and, 34–39; ownership and, 30–34, 37–44, 48–62, 65, 68, 72, 77, 79; partnerships and, 52–54, 57, 174; peasants and, 35–37, 61, 136; prices and, 31–42, 47–64, 67–77; private, 25, 28, 34–42, 48–52, 61–62, 68, 76, 78, 99, 177, 253, 271–72, 299n28, 301n46; public goods and, 41, 73, 253; public leases and, 69–72; Quadratic Voting (QV) and, 273; Radical Markets and, 173, 177, 272; reform and, 35, 37, 39, 46; regulations and, 46–48, 299n27; right of way and, 32–33; rights of, 35, 48–49, 51–52, 88, 173, 210; self-assessment and, 31, 55–56, 61–62, 70, 72, 258, 260, 270, 302n63; socialism and, 37–42, 45–49; taxes and, 28, 31, 42–44, 51, 55–70, 73–76, 301n36; turnover rate and, 58–61, 64, 76; United States and, 36, 38, 45, 47–48, 51; wealth and, 36, 38, 40, 45, 55, 61, 73–79 Proposition 8, 89 “Protection and Real Wages” (Stolper and Samuelson), 142 psychology, 67, 78, 111, 114, 233, 238, 248, 290 public goods: collective decisions and, 98; common ownership self-assessed tax (COST) and, 256; democracy and, 28, 97–100, 107, 110, 120, 123, 126; globalization and, 265; labor and, 147; markets and, 271; property and, 41, 73, 253; Quadratic Voting (QV) and, 110, 120, 123–26, 256, 264, 272; selfishness and, 270; Smith on, 16 public leases, 69–72 “Pure Theory of Public Expenditure, The” (Samuelson), 97 Qatar, 158 Qin dynasty, 46 Quadratic Voting (QV): 1p1v and, 82–84, 94, 109, 119, 122–24, 304n36, 306n51; Arrow’s Theorem and, 303n17; auctions and, xvii–xix; broader application of, 118–19, 273–74; collective decisions and, 110–11, 118–20, 122, 124, 273, 303n17, 304n36; common ownership self-assessed tax (COST) and, 123–25, 194, 261–63, 273, 275, 286; competition and, 304n36; corporate governance and, 194; cryptocurrencies and, 117–18; democracy and, 105–22; efficiency and, 110, 126, 256; elections and, 115, 119–21, 268, 306n52; equality and, 264; free-rider problem and, 107–8; globalization and, 266–69; governance and, 117, 122, 266–69; growth and, 123; happiness and, 108–10, 306n52; immigrants and, 261, 266–69, 273; inequality and, 264; legal issues and, 267, 275; liberalism and, 268; Likert surveys and, 111–16, 120, 306n53; markets and, 122–23, 256, 272, 286, 304n36; methodology of, 105–10; monetizing, 263–64; monopolies and, 272; nature of currency and, 122–23; optimality and, 108–9, 120, 286; ownership and, 105; Pareto efficiency and, 110; political effects of, 261–64; polls and, 111–16, 118, 303n17; prices and, 263, 275; property and, 273; proportional, 106–7; public goods and, 110, 120, 123–26, 256, 264, 272; Radical Markets and, 82–126, 194, 272; rating and, 117–18; reform and, 95, 105–6; scope of trade and, 122–23; social aggregation and, 117–18; society and, 272–73; software flaw and, 305n44; square root function and, 82; taxes and, 263, 275; technology and, 264; testing of, 111, 114–18; voice credits and, 80–82, 105, 113, 117, 119, 121–23, 251, 263–64, 267, 269; wealth and, 256–57, 261–64, 267–68, 272–73, 275, 286 Quarfoot, David, 114 reCAPTCHA, 235–36 Reddit, 117 Red Queen phenomenon, 176–77, 184 Red Terror, 93 reform: academics and, 2–3; antitrust policies and, 23, 48, 174–77, 180, 184–86, 191, 197–203, 242, 255, 262, 286; auctions and, xv–xvii, 49–51, 70–71, 97, 99, 147–49, 156–57; common ownership self-assessed tax (COST) and, 298n7; George and, 23; globalization and, 255; immigrants and, 129, 153; labor and, 129, 153, 240, 247, 255; liberalism and, 2–4, 23–25, 255; property and, 35, 37, 39, 46; Quadratic Voting (QV) and, 105 (see also Quadratic Voting [QV]); Radical Markets and, 95, 105–6, 181, 191; regulations and, 239–45 (see also regulations); taxes and, 274–75; United Kingdom and, 95–96 Reform Act of 1832, 95 refugees, 130, 140, 145 regulations: banking, 98–99; capitalism and, 262; Coase on, 299n27; competition and, 262; democracy and, 98–100, 123; deregulation and, 3, 9, 24; discrimination and, 272; elitism and, 3; environmental, 265, 291; labor and, 138, 155–56, 165, 239–45, 266; liberalism and, 3, 9, 18, 24; property and, 46–48, 299n27; Radical Markets and, 176, 180, 189, 191, 194, 197, 203 religion, 15, 17, 19, 55, 78, 81, 85–90, 94, 129, 145, 272 resale price maintenance, 200–201 revolutions, 36, 41, 46, 86, 88, 90–92, 95, 224, 255, 273, 277 Ricardo, David, 133 Rio de Janeiro, xiii–xiv, 105 robber barons, 175, 199–200 Robinson Crusoe (DeFoe), 132 robots, 222, 248, 251, 254, 287 Rockefeller, John D., 174–75 Roemer, John, 240 Roman Catholic Church, 85, 94 Roman Republic, 84 Roosevelt, Franklin D., 176 Roosevelt, Theodore, 175 Rousseau, Jean-Jacques, 86 Russia, 12, 13, 46 same-sex marriage, 89 sample complexity, 218 Samuelson, Paul, 97–98, 106–7, 142–43 Sanders, Bernie, 12 Satterthwaite, Mark, 50–51, 66, 69 Saudia Arabia, 158–59 savings: growth and, 6; labor and, 150–51; mercantilism and, 132; Radical Markets and, 169, 172, 181; retirement, 171–72, 260, 274; squandering, 123 Schmalz, Martin, 189 Schumpter, Joseph, 47 Segal, Ilya, 52 self-assessment, 31, 55–56, 61–62, 70, 72, 258, 260, 270, 302n63 self-driving cars, 230 serfs, 35, 48, 231–32, 236, 255 Shafir, Eldar, 114 Shalizi, Cosma, 281 shallow nets, 216–19 shareholders, 118, 170, 178–84, 189, 193–95 Sherman Antitrust Act, 174, 262 Show Boat (film), 209 Silicon Valley, 211 Silk Road, 131 Singapore, 160 siren servers, 220–24, 230–41, 243 Siri, 219, 248 Skype, 155, 202 slavery, xiv, 1, 19, 23, 37, 96, 136, 255, 260 slums, xiii, xviii, 17 Smith, Adam, xix–xx, 4; capitalism and, 34–35; competition and, 17; diamond-water paradox and, 224–25; efficiency and, 37; immigrants and, 132–33; inequality and, 22; markets and, 16–17, 21–22; monopolies and, 173; Wealth of Nations and, 22 social aggregation, 117–18 Social Democratic Party, 45 social dividend, 41, 43, 49, 73–75, 147, 256–59, 263, 269, 298n13, 302n63 socialism: central planning and, 39–42, 47, 277, 281; George and, 37, 45, 137, 250, 253; German right and, 94; industry and, 45; irrationality of capitalism and, 39 (see also capitalism); labor and, 137, 299n24; laissez-faire and, 250, 253; markets and, 277–78, 281; Marx and, 137, 277; property and, 37–42, 45–49; radical democracy and, 94; Radical Markets and, 293; Sanders and, 12; Schumpeter on, 47; von Mises and, 278; workers’ cooperatives and, 299n24 social media, 251–52; data and, 202, 212, 231, 233–36; democracy and, 117, 126; Facebook, xxi, 28, 50, 117, 202, 205–9, 212–13, 220–21, 231–48, 289; Instagram, 117, 202, 207; Reddit, 117; Twitter, 117, 221; WhatsApp, 202; Yelp, 63, 117 Social Security, 274 Southwest, 191 sovereignty, 1, 16, 86, 131–32 Soviet Union, 1, 19, 46–47, 277–78, 281–82, 288 spam, 210, 245 special interest groups, 25, 98, 256 Spense, A.


pages: 237 words: 67,154

Ours to Hack and to Own: The Rise of Platform Cooperativism, a New Vision for the Future of Work and a Fairer Internet by Trebor Scholz, Nathan Schneider

1960s counterculture, activist fund / activist shareholder / activist investor, Airbnb, Amazon Mechanical Turk, barriers to entry, basic income, bitcoin, blockchain, Build a better mousetrap, Burning Man, capital controls, citizen journalism, collaborative economy, collaborative editing, collective bargaining, commoditize, conceptual framework, crowdsourcing, cryptocurrency, Debian, deskilling, disintermediation, distributed ledger, Ethereum, ethereum blockchain, future of work, gig economy, Google bus, hiring and firing, income inequality, information asymmetry, Internet of things, Jacob Appelbaum, Jeff Bezos, job automation, Julian Assange, Kickstarter, lake wobegon effect, low skilled workers, Lyft, Mark Zuckerberg, means of production, minimum viable product, moral hazard, Network effects, new economy, offshore financial centre, openstreetmap, peer-to-peer, post-work, profit maximization, race to the bottom, ride hailing / ride sharing, SETI@home, shareholder value, sharing economy, Shoshana Zuboff, Silicon Valley, smart cities, smart contracts, Snapchat, TaskRabbit, technoutopianism, transaction costs, Travis Kalanick, Uber for X, uber lyft, union organizing, universal basic income, Whole Earth Catalog, WikiLeaks, women in the workforce, Zipcar

Project Name: FairCoop Completed by: Enric Duran Location: Earth URL: fair.coop FairCoop is not about offering a specific service but building a full economic ecosystem for a postcapitalist society. In this sense, the ecosystem is what is going to be offered, offering individuals, collectives, cooperatives, and social companies a set of tools for connecting with and supporting each other and anyone aiming to make real, radical social change. FairCoop does not have a legal entity at the moment, so there is not a legal basis for ownership. FairCoin is a peer-to-peer cryptocurrency based in free software, so in that sense nobody owns it; everyone who has some faircoins and runs the wallet software is part of the decentralized ownership of the currency system. Governance takes place in an open, participatory process through online assemblies every month and open discussions that can be accessed at the Fair.Coop site. Openness is the main characteristic of the FairCoop development.

However, to deliver the AI-powered features that near-future users will demand, applications will need to draw upon sophisticated industrial-strength AI software services and harness powerful clusters of data-mining server farms. This stuff doesn’t come cheap. Free, open, and radically decentralized AI isn’t a thing yet, but blockchain-based platforms like Ethereum and Backfeed could offer decentralized alternatives to the corporate cloud. More libre but not gratis, as you’ll pay for decentralization with cryptocurrency. In its infancy, Ethereum is far more expensive than the Amazon cloud but with laughable performance and capability by comparison. Can you afford to wait for the decentralized solution or do you accept that a corporate cloud is presently your only viable high-performance and affordable option? Co-ops require novel legal frameworks. Starting a conventional tech startup incurs tremendous legal costs that even make the cloud seem like a bargain.

Cities can then invite local companies, cooperatives, civil society organizations, and tech entrepreneurs to come in and offer innovative services on top of that infrastructure. One example is the European Commission’s CAPS program, which has invested around €60 million on collaborative and open platforms to pilot bottom-up, citizen-led projects with strong social impact such as the D-CENT project (http://dcentproject.eu), developing distributed and privacy-aware tools for direct democracy and cryptocurrencies for economic empowerment. Initiatives like these can help ensure that the data produced by platforms, devices, sensors, and software doesn’t get locked down in corporate silos, but becomes available for the public good. Investing public resources for piloting innovative, cooperative platforms is necessary to enable credible alternatives to the current data paradigms exploited by the dominant platforms—integrating economy, technology, society, and policy, which would otherwise remain fragmented and lead to market concentration and regulatory breakdowns.


pages: 385 words: 111,113

Augmented: Life in the Smart Lane by Brett King

23andMe, 3D printing, additive manufacturing, Affordable Care Act / Obamacare, agricultural Revolution, Airbnb, Albert Einstein, Amazon Web Services, Any sufficiently advanced technology is indistinguishable from magic, Apple II, artificial general intelligence, asset allocation, augmented reality, autonomous vehicles, barriers to entry, bitcoin, blockchain, business intelligence, business process, call centre, chief data officer, Chris Urmson, Clayton Christensen, clean water, congestion charging, crowdsourcing, cryptocurrency, deskilling, different worldview, disruptive innovation, distributed generation, distributed ledger, double helix, drone strike, Elon Musk, Erik Brynjolfsson, Fellow of the Royal Society, fiat currency, financial exclusion, Flash crash, Flynn Effect, future of work, gig economy, Google Glasses, Google X / Alphabet X, Hans Lippershey, Hyperloop, income inequality, industrial robot, information asymmetry, Internet of things, invention of movable type, invention of the printing press, invention of the telephone, invention of the wheel, James Dyson, Jeff Bezos, job automation, job-hopping, John Markoff, John von Neumann, Kevin Kelly, Kickstarter, Kodak vs Instagram, Leonard Kleinrock, lifelogging, low earth orbit, low skilled workers, Lyft, M-Pesa, Mark Zuckerberg, Marshall McLuhan, megacity, Metcalfe’s law, Minecraft, mobile money, money market fund, more computing power than Apollo, Network effects, new economy, obamacare, Occupy movement, Oculus Rift, off grid, packet switching, pattern recognition, peer-to-peer, Ray Kurzweil, RFID, ride hailing / ride sharing, Robert Metcalfe, Satoshi Nakamoto, Second Machine Age, selective serotonin reuptake inhibitor (SSRI), self-driving car, sharing economy, Shoshana Zuboff, Silicon Valley, Silicon Valley startup, Skype, smart cities, smart grid, smart transportation, Snapchat, social graph, software as a service, speech recognition, statistical model, stem cell, Stephen Hawking, Steve Jobs, Steve Wozniak, strong AI, TaskRabbit, technological singularity, telemarketer, telepresence, telepresence robot, Tesla Model S, The Future of Employment, Tim Cook: Apple, trade route, Travis Kalanick, Turing complete, Turing test, uber lyft, undersea cable, urban sprawl, V2 rocket, Watson beat the top human players on Jeopardy!, white picket fence, WikiLeaks

Dave Asprey, New York Times Bestselling Author of The Bulletproof Diet “You may think you’ve heard all there is to know about the dramatic changes to come in our digital future. Well, prepare to have your mind blown... again. In a crowded field of prognosticators, Brett King stands out for his clearly articulated vision of how technology is changing who we are.” Michael J. Casey, author of The Age of Cryptocurrency: How Bitcoin and Digital Money are Challenging the Global Economic Order “As one of the world’s most followed and provocative voices in digital finance, Brett King has once again thrown down the gauntlet. Brett’s vision of the future should be required reading for governments, think-tanks, investors, or basically anyone wondering how transformational technologies like artificial intelligence, robotics, Bitcoin and gene-editing may impact our society.”

Can you guess which countries gave birth to “bucks”, “clams”, “loonies”, “dough”, “shtuka”, “two bob” and “moola” when it comes to describing money? Money is vitally important, if not central, to commerce in society, but when presented with the concept that cash might disappear or that the use of physical currency is in decline, you will get passionate responses from large swathes of the population diametrically opposed to even the thought of such a shift. When a new cryptocurrency like Bitcoin emerges, you’ll likewise have those who are passionate in their belief that Bitcoin will replace all existing currencies on the planet and eliminate the need for a conventional banking system, as opposed to those who think Bitcoin is purely an instrument for geeks and/or criminals who want total cross-border anonymity for their transactions. The fact is that “hard” cash is actually a relatively new concept in the modern world.

The earliest recorded such currency from 3000 BC was called a “shekel”, which carried the distinction of being both a measure of weight and an early form of currency. Shells were used by many nations in the Americas, Asia and Pacific. The ancient Greeks, however, were the first to mint actual coins back around 600 to 650 BC, and by the 1st century such coins were increasingly the most standard form of monetary value exchange around the world. Making Money More Efficient Today, cryptocurrencies like Bitcoin are emerging as a type of next generation currency. While classifying Bitcoin as a currency is the most logical characterisation for most of the public at large, it is by design something that is more efficient than traditional currency, resembling more closely something like the digital equivalent of the shekel in terms of mechanics or valuation. The problem money faces today is that it is not particularly efficient for the various types of commerce that are rapidly emerging.


pages: 571 words: 106,255

The Bitcoin Standard: The Decentralized Alternative to Central Banking by Saifedean Ammous

Airbnb, altcoin, bank run, banks create money, bitcoin, Black Swan, blockchain, Bretton Woods, British Empire, business cycle, capital controls, central bank independence, conceptual framework, creative destruction, cryptocurrency, currency manipulation / currency intervention, currency peg, delayed gratification, disintermediation, distributed ledger, Ethereum, ethereum blockchain, fiat currency, fixed income, floating exchange rates, Fractional reserve banking, full employment, George Gilder, global reserve currency, high net worth, invention of the telegraph, Isaac Newton, iterative process, jimmy wales, Joseph Schumpeter, market bubble, market clearing, means of production, money: store of value / unit of account / medium of exchange, moral hazard, Network effects, Paul Samuelson, peer-to-peer, Peter Thiel, price mechanism, price stability, profit motive, QR code, ransomware, reserve currency, Richard Feynman, risk tolerance, Satoshi Nakamoto, secular stagnation, smart contracts, special drawing rights, Stanford marshmallow experiment, The Nature of the Firm, the payments system, too big to fail, transaction costs, Walter Mischel, zero-sum game

In fact they work well under zero intelligence—a zero‐intelligence crowd, under the right design, works better than a Soviet‐style management composed of maximally intelligent humans. Which is why Bitcoin is an excellent idea. It fulfills the needs of the complex system, not because it is a cryptocurrency, but precisely because it has no owner, no authority that can decide on its fate. It is owned by the crowd, its users. And it now has a track record of several years, enough for it to be an animal in its own right. For other cryptocurrencies to compete, they need to have such a Hayekian property. Bitcoin is a currency without a government. But, one may ask, didn't we have gold, silver, and other metals, another class of currencies without a government? Not quite. When you trade gold, you trade “loco” Hong Kong and end up receiving a claim on a stock there, which you might need to move to New Jersey.

Further, even if such a political and monetary transformation were possible, Bitcoin's diminishing supply growth rate is likely to continue to make it an attractive speculative bet for many, which would in itself cause it to grow further and acquire a larger monetary role. In my assessment, a global monetary return to gold might be the most significant threat to Bitcoin, yet it is both unlikely to happen and unlikely to destroy Bitcoin completely. Another possibility for derailing Bitcoin would be through the invention of a new form of sound money that is superior to Bitcoin. Many seem to think that the other cryptocurrencies that mimic Bitcoin could achieve this, but it is my firm belief that none of the coins that copy Bitcoin's design can compete with Bitcoin on being sound money, for reasons discussed at length in the next section of the chapter, primarily: Bitcoin is the only truly decentralized digital currency which has grown spontaneously as a finely balanced equilibrium between miners, coders, and users, none of whom can control it.

Profit and Loss. Ludwig von Mises Institute, 2008. _____. Socialism: An Economic and Sociological Analysis. Ludwig von Mises Institute, Auburn, AL. 2008 (1922). _____. The Theory of Money and Credit, 2nd ed. Irvington‐on‐Hudson, New York: Foundation for Economic Education, 1971. Nakamoto, Satoshi. Bitcoin: A Peer‐to‐Peer Electronic Cash System (n.p., 2008). Narayanan, Arvind et al. Bitcoin and Cryptocurrency Technologies: A Comprehensive Introduction. Princeton University Press, 2016. Paar, Christof, Bart Preneel and Jan Pelzl. Understanding Cryptography: A Textbook for Students and Practitioners. Springer, 2009. Philippon, Thomas, and Ariell Reshef. “An International Look at the Growth of Modern Finance.” Journal of Economic Perspectives 27, no. 2 (2013): 73–96. Popper, Nathaniel. Digital Gold.


pages: 352 words: 80,030

The New Silk Roads: The Present and Future of the World by Peter Frankopan

active measures, Berlin Wall, bitcoin, blockchain, Boris Johnson, cashless society, clean water, cryptocurrency, Deng Xiaoping, don't be evil, Donald Trump, Ethereum, ethereum blockchain, F. W. de Klerk, failed state, Fall of the Berlin Wall, global supply chain, illegal immigration, income inequality, invisible hand, land reform, Mark Zuckerberg, mass incarceration, Nelson Mandela, purchasing power parity, ransomware, Rubik’s Cube, smart cities, South China Sea, sovereign wealth fund, trade route, trickle-down economics, UNCLOS, urban planning, WikiLeaks, zero-sum game

As well as everything else, the Silk Roads acted as ‘gene corridors’ for humans and for flora and fauna alike.6 Then there is new research that links the origins of Yiddish with commercial exchange across Asia and claims that its evolution was connected to measures designed to protect the security of transactions by devising a language that could only be understand by a select few.7 This has obvious resonance in the world of the twenty-first century, where crypto-currencies and blockchain technology seek to solve the problem of how to enable traders to complete transactions securely. Or there is the startling evidence from new-generation ice-core technology that can be used to shed fresh light on the devastating impact of the Black Death by showing the extent of the collapse in metal production in the mid-fourteenth century.8 Documents declassified in 2017 recording meetings held between the British minister in Washington in 1952, Sir Christopher Steel, and the assistant secretary of state Henry Byroade to discuss a coup to depose the prime minister of Iran help us gain a clearer understanding of how the ill-fated plans took shape.9 The release of previously secret US nuclear strike plans from the early part of the Cold War likewise help reveal important insights into American military and strategic planning – and contemporary assessments of how best to neutralise the Soviet Union in the event of war.10 These are just a small number of examples to show how historians continue to use different techniques to refine and improve their understanding of the past.

There are real dangers in concentrating only on matters that are of parachial importance when so many other more significant and challenging problems require and demand attention. * The rapid development of new technologies is also a significant difficulty to address, in terms of trying to predict the impact these will have in the coming years – and working out how to prepare accordingly for a world where artificial intelligence (AI), robotics, machine learning, Blockchain, Ethereum and more will change the way we live, love, work and communicate. Then there are cryptocurrencies like Bitcoin, which, while exciting for digital pioneers, seem most obviously of interest to those who seek to keep their transactions secure and away from prying eyes – including those who deal in illicit substances or goods, or who prefer to keep potentially taxable revenue away from the authorities. Ironically, the impact of decentralised digital currencies might prove more important for states seeking to continue to engage in trade in the face of pressures – such as sanctions – where the dominance of the dollar, euro and the yen in international transactions makes large-scale trade in other currencies impractical, inconvenient or impossible.

Peter Frankopan Oxford, September 2018 Index Abbas, Mahmoud here Abbasi, Shahid Khaqan here Abdrakhmanov, Kairat here Abdulkodirzoda, Saidmukarram here Ablyazov, Mukhtar here Abramovich, Roman here Afghan Heritage Mapping Partnership here Afghanistan here, here, here, here, here, here, here, here, here, here, here, here, here China and here US policy and here, here, here, here, here, here, here, here, here see also TAPI pipeline Africa China and here, here, here, here US policy and here, here African Standby Force here Agni-V missiles here Ahmed, Abiy here Airbus here airline pilots, shortage of here Albright, Madeleine here Alternative für Deutschland (AfD) here Altmaier, Peter here aluminium prices here Angola here Aral Sea here Araqi, Hamidreza here Armenia here, here, here artificial intelligence here, here, here, here Ashgabat agreement here Asian Development Bank here, here Asif, Khawaja here al-Assad, Bashar here, here Astana International Financial Centre here Australia here, here, here, here, here, here Azerbaijan here, here, here, here Bahgeri, Mohammad here Baku–Tbilisi–Kars railway here Balochistan, murder of schoolteachers here Bambawale, Gautam here Bangalore here Bangladesh here Bannon, Steve here Beishembiev, Erik here Belarus here, here Berdymukhamedov, Gurbanguly here Berlin Wall, fall of here, here big data here bin Laden family here Black Death here Boeing here, here, here Bolton, John here, here Boucher, Richard A. here boxing, banned in Tajikistan here Brahmaputra River hydrology here Brexit here, here, here, here, here Britain First here Brunson, Andrew here Bryant, Kobe here Byroade, Henry here Cambodia here, here, here, here ‘carrier-killer’ missiles here Carter, General Sir Nick here CASA-1000 power project here Caspian Sea here, here, here, here, here Çavuşoğlu, Mevlüt here, here, here Chabahar port here Chen Xiaodong here Cheng Quanguo here China access to IT here ageing population here and artificial intelligence here Belt and Road Initiative, development here Belt and Road Initiative, reservations here, here economic weakness here, here economic development here, here end of One Child policy here energy projects here environmental problems here, here and European Union here football, in Han-dynasty here ‘great wall of iron’ here intellectual property theft here, here joins WTO here maritime expansion here, here, here, here military exercises here and overseas debt levels here relations with India here, here, here relations with Iran here, here, here relations with Pakistan here relations with Russia here, here relations with Saudi Arabia here retail market here rivalry with US here, here, here science programme here security concerns here seeks global leadership role here sensitivity over Taiwan here Siberian land purchases here telecoms here urbanisation here, here US corporations and here China Development Bank here China–Pakistan Economic Corridor here, here, here Chinese army here climate change here, here, here, here, here Clinton, Bill here Clinton, Hillary here Coats, Dan here Cohn, Gary here Collins, Michael here Columbus, Christopher here commercial courts here Communications Compatibility and Security Agreement (COMSCA) here Community of Latin American and Caribbean States (CELAC) here Congo here Crimea, annexation of here, here, here, here, here cryptocurrencies here, here Davidson, Admiral Philip D. here Dawood, Abdul Razak here de Klerk, F. W. here Deng Xiaoping here, here, here Desai, Lord here dictatorial leaders here Djibouti here Doklam Plateau here Dominican Republic here, here donkeys here drones here, here, here, here Duan, Rachel here Dunford, General Joseph here Duterte, Rodrigo here Dzagaryan, Levan here East China Sea here East Jerusalem Hospital Network here El Salvador here, here, here Ellena, Jean-Claude here Erdoğan, Recep Tayyip here, here, here, here, here and annexation of Crimea here Essar Oil here Eurasian Economic Union here, here, here European Monetary Fund here European Union (EU) here, here, here, here, here Exxon here Facebook here, here Fernandes, Tony here Fiat Chrysler here Fierravanti-Wells, Concetta here FinTech here Foges, Clare here football here, here Fox, Vincente here Franz Ferdinand, Archduke here freedom of speech here Gabriel, Sigmar here Galkynysh gas field here, here Gama, Vasco da here Gao Feng here, here General Electric here, here General Motors here Germany here, here, here, here Ghadir-class submarines here Ghani, Ashraf here, here Gilmour, Andrew here Giuliani, Rudy here, here Goldberg, Jeffrey here Google here, here Gorazde massacre here Gove, Michael here Grand Tours here ‘Great Game’ here Grenell, Richard here Guam here Gul, Abdulhamit here Gülen, Fethullah here Gulf War here Gwadar port here, here, here, here Haase, Richard here Hagel, Chuck here Hahn, Johannes here Haiti here Haley, Nikki here, here Hamas here, here Hambantota port here, here Harris, Admiral Harry B. here, here Haspel, Gina here heroin here Hezbollah here Hillman, Jonathan here Hitler, Adolf here Hong Kong here, here Hook, Brian here Hu Lianhe here Hun Sen here hydrated magnesium silicate here hydroelectric projects here, here India economic development here Eurasian trade here intimidation of journalists here military exercises here relations with China here, here, here relations with Iran here, here relations with Pakistan here, here relations with Russia here and US–Turkey crisis here water resources here US policy and here, here see also TAPI pipeline Indian Ocean here Indonesia here, here Infosys Technologies here intellectual property theft here, here International Atomic Agency here, here International Wushu competition here International Yoga Day here Iran electricity exports here foreign interventions here nuclear deal here, here, here, here relations with Russia here relations with Saudi Arabia here street protests here US policy and risk of escalation here, here Iraq here, here, here, here, here, here, here, here, here, here, here, here, here, here ISIS here, here Israel–Palestine conflict here, here, here Ivanov, Gjorge here Jahangiri, Es’haq here Japan here, here, here Jerusalem here Jiang Shigong here Jin Liqun here Johnson, Boris here Juncker, Jean-Claude here, here Karimov, Islam here Kashmir here, here Kazakhstan here, here, here, here, here, here, here, here, here, here, here, here relations with China here Kelly, John here Kelly, Tom here Kenyatta, Uhuru here Khamenei, Ayatollah Ali here, here, here Khan, Imran here Khan, Khurram Dastgir here Khorgos ‘dry port’ here Kiam, Victor here Kim Jong-un here, here, here King of Zhao here Kipling, Rudyard here Kishanganga dam here Kissinger, Henry here, here, here Koolhaas, Rem here Korean War here Ku Klux Klan here Kushner, Jared here Kyrgyzstan here, here, here, here, here, here, here Lagarde, Christine here, here, here Lahore metro here Lake Baikal here Laos here, here, here Lapis Lazuli corridor here Latin America, China and here Lavrov, Sergei here, here, here, here Le Maire, Bruno here Le Pen, Marine here Le Yucheng here Li Keqiang here, here Li Yonghong here Libya here Lighthizer, Robert here, here Lisbon Treaty here Liu He here Ma, Jack here Maas, Heiko here, here McKenzie, Lt General Kenneth F. here McMaster, H.


pages: 302 words: 73,581

Platform Scale: How an Emerging Business Model Helps Startups Build Large Empires With Minimum Investment by Sangeet Paul Choudary

3D printing, Airbnb, Amazon Web Services, barriers to entry, bitcoin, blockchain, business process, Chuck Templeton: OpenTable:, Clayton Christensen, collaborative economy, commoditize, crowdsourcing, cryptocurrency, data acquisition, frictionless, game design, hive mind, Internet of things, invisible hand, Kickstarter, Lean Startup, Lyft, M-Pesa, Marc Andreessen, Mark Zuckerberg, means of production, multi-sided market, Network effects, new economy, Paul Graham, recommendation engine, ride hailing / ride sharing, shareholder value, sharing economy, Silicon Valley, Skype, Snapchat, social graph, social software, software as a service, software is eating the world, Spread Networks laid a new fibre optics cable between New York and Chicago, TaskRabbit, the payments system, too big to fail, transport as a service, two-sided market, Uber and Lyft, Uber for X, uber lyft, Wave and Pay

Similarly, Waze, an Israeli traffic prediction app, crowdsources driving information from multiple drivers while simultaneously using algorithms to determine authenticity before distributing traffic conditions to the wider community. Wikipedia and Waze reimagine the organization of the traditional production function, away from supply chains and onto platforms. They provide an early glimpse into a future where value creation may not need a supply chain, instead being orchestrated via a network of connected users on a platform. h. Cryptocurrencies Platform theory helps to explain the workings of cryptocurrencies, like Bitcoin. Decentralized management – through mechanisms like the blockchain – has the potential to change governance structures for the next generation of platforms, much like social feedback tools power curation on many of the current generation of platforms. While we do not explore Bitcoin in detail in this book, the principles laid out apply equally well to understanding all emerging platforms that the book may not explicitly cover.

Platform Scale explains the design of a family of emerging digital business models that enables today’s startups to achieve rapid scale: the platform business model. The many manifestations of the platform business model - social media, the peer economy, cryptocurrencies, APIs and developer ecosystems, the Internet of things, crowdsourcing models, and many others - are becoming increasingly relevant. Yet, most new platform ideas fail because the business design and growth strategies involved in building platforms are not well understood. Platform Scale is a builder’s manual for anyone building a platform business today. It lays out a structured approach to designing and growing a platform business model and addresses the key factors that lead to the success and failure of these businesses.


pages: 309 words: 81,975

Brave New Work: Are You Ready to Reinvent Your Organization? by Aaron Dignan

"side hustle", activist fund / activist shareholder / activist investor, Airbnb, Albert Einstein, autonomous vehicles, basic income, Bertrand Russell: In Praise of Idleness, bitcoin, Black Swan, blockchain, Buckminster Fuller, Burning Man, butterfly effect, cashless society, Clayton Christensen, clean water, cognitive bias, cognitive dissonance, corporate governance, corporate social responsibility, correlation does not imply causation, creative destruction, crony capitalism, crowdsourcing, cryptocurrency, David Heinemeier Hansson, deliberate practice, DevOps, disruptive innovation, don't be evil, Elon Musk, endowment effect, Ethereum, ethereum blockchain, Frederick Winslow Taylor, future of work, gender pay gap, Geoffrey West, Santa Fe Institute, gig economy, Google X / Alphabet X, hiring and firing, hive mind, income inequality, information asymmetry, Internet of things, Jeff Bezos, job satisfaction, Kevin Kelly, Kickstarter, Lean Startup, loose coupling, loss aversion, Lyft, Marc Andreessen, Mark Zuckerberg, minimum viable product, new economy, Paul Graham, race to the bottom, remote working, Richard Thaler, shareholder value, Silicon Valley, six sigma, smart contracts, Social Responsibility of Business Is to Increase Its Profits, software is eating the world, source of truth, Stanford marshmallow experiment, Steve Jobs, TaskRabbit, the High Line, too big to fail, Toyota Production System, uber lyft, universal basic income, Y Combinator, zero-sum game

That ambition is at the heart of an emerging class of decentralized autonomous organizations (DAOs), which leverage blockchain and cryptocurrencies to create products and services without central control. The best explanation of this controversial new form of organization comes from Cointelegraph, an independent online publication that covers the future of money. “Imagine a vending machine that not only takes money from you and gives you a snack in return but also uses that money to automatically re-order the goods. This machine also orders cleaning services and pays its rent all by itself. Moreover, as you put money into that machine, you and its other users have a say in what snacks it will order and how often it should be cleaned. It has no managers, all of those processes were pre-written into code.” Developers, leveraging what they have learned in creating cryptocurrencies such as Bitcoin and Ethereum, are pioneering a new generation of decentralized applications that allow organizations to operate like that magical vending machine.

Entrepreneurial skills are prized above Ivy League admission. New forms of universal basic income are being tested for their ability to provide for our basic human needs while also encouraging us to use and share our gifts—through entrepreneurship, service, and community. New forms of currency and means of exchange provide alternatives to the current model of borrowing money lent at interest. Blockchain and cryptocurrencies enable massively distributed collaboration via decentralized autonomous organizations and other alternatives to traditional incorporation or partnership. A new type of thinking is essential if mankind is to survive and move toward higher levels. —Albert Einstein Is a future like that even possible? It depends who you ask. A legacy economist might scoff, but a renegade economist such as Kate Raworth would say we have no choice.


pages: 297 words: 84,009

Big Business: A Love Letter to an American Anti-Hero by Tyler Cowen

23andMe, Affordable Care Act / Obamacare, augmented reality, barriers to entry, Bernie Sanders, bitcoin, blockchain, Bretton Woods, cloud computing, cognitive dissonance, corporate governance, corporate social responsibility, correlation coefficient, creative destruction, crony capitalism, cryptocurrency, dark matter, David Brooks, David Graeber, don't be evil, Donald Trump, Elon Musk, employer provided health coverage, experimental economics, Filter Bubble, financial innovation, financial intermediation, global reserve currency, global supply chain, Google Glasses, income inequality, Internet of things, invisible hand, Jeff Bezos, late fees, Mark Zuckerberg, mobile money, money market fund, mortgage debt, Network effects, new economy, Nicholas Carr, obamacare, offshore financial centre, passive investing, payday loans, peer-to-peer lending, Peter Thiel, pre–internet, price discrimination, profit maximization, profit motive, RAND corporation, rent-seeking, reserve currency, ride hailing / ride sharing, risk tolerance, Ronald Coase, shareholder value, Silicon Valley, Silicon Valley startup, Skype, Snapchat, Social Responsibility of Business Is to Increase Its Profits, Steve Jobs, The Nature of the Firm, Tim Cook: Apple, too big to fail, transaction costs, Tyler Cowen: Great Stagnation, ultimatum game, WikiLeaks, women in the workforce, World Values Survey, Y Combinator

It competes with gold as a hedge and unorthodox store of value, and you can use it as a currency to buy (legal) marijuana, a transaction that, because of federal regulations, the regular banking system cannot support. It enables a blockchain as a new medium for recording, storing, and verifying information and common agreement as to who owns what. It remains to be seen how much Bitcoin, along with other cryptocurrencies and more generally the blockchain, will prove transformational. It might not even hold its market value. But that is how innovation usually proceeds. Innovators try lots of new approaches; some are discarded, others take off, and yet others evolve into something more useful with the passage of time. So far Bitcoin and some of the other cryptocurrencies have defied the skeptics. Maybe they will have taken a tumble by the time you are reading this, but nonetheless, they are signs of an active process of dynamic innovation. Are you frustrated by how the credit card system works?

class Clinton, Hillary Coase, Ronald cognition cognitive dissonance cognitive efficiency cognitive strengths Collison, Patrick and John compensating differential conspiracy theories control firms co-ops copyright corporations attempts to sway public opinion downside of personalization public dislike of Countrywide “creative destruction” credit cards credit card information credit card system privacy and crony capitalism business influence on government class and multinational corporations overview privilege and state monopoly status quo bias See also capitalism cryptocurrencies See also Bitcoin Csikszentmihalyi, Mihaly Curry, Stephen CVS cybersecurity “daily effective experiences” See also Kahneman, Daniel; Krueger, Alan Daley, William Damaske, Sarah Damore, James daycare defense spending DejaNews Democratic Party Desan, Mathieu Deutsche Bank discrimination Dollar General Dow Scrubbing Bubbles Dream of the Red Chamber DuckDuckGo Dying for a Paycheck (Pfeffer) eBay education email employment/unemployment European Union ex post Exxon eyeglass companies Facebook advertising and AI and “anti-diversity memo” censorship and China and competition and complaints about employees “filter bubble” income inequality and information and innovation and monopoly and News Feed politics and privacy and Russian-manipulated content venture capital and See also Zuckerberg, Mark facial recognition technology “fake news” See also media Fama, Eugene fast-food Fehr, Ernst Ferguson, Niall financial crisis financial sector America as tax and banking haven American stock performance banks “too big” global importance of US growth information technology and intermediation overview venture capital and American innovation Financial Times fintech flow Ford Motor Company Foreign Corrupt Practices Act Foroohar, Rana fraud, businesses and CEOs in laboratory games comparative perspective cross-cultural game theory nonprofits vs. for-profits overview research on corporate behavior spread of information and tax gap trust and free trade French, Kenneth Friedman, Milton Friendster Fritzon, Katarina fundraising Gabaix, Xavier Gates, Bill GDP General Agreement on Tariffs and Trade General Electric General Motors Gilens, Martin Glass-Steagall Act Gmail Goetzmann, William N.


pages: 304 words: 80,143

The Autonomous Revolution: Reclaiming the Future We’ve Sold to Machines by William Davidow, Michael Malone

2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, agricultural Revolution, Airbnb, American Society of Civil Engineers: Report Card, Automated Insights, autonomous vehicles, basic income, bitcoin, blockchain, blue-collar work, Bob Noyce, business process, call centre, cashless society, citizen journalism, Clayton Christensen, collaborative consumption, collaborative economy, collective bargaining, creative destruction, crowdsourcing, cryptocurrency, disintermediation, disruptive innovation, distributed ledger, en.wikipedia.org, Erik Brynjolfsson, Filter Bubble, Francis Fukuyama: the end of history, Geoffrey West, Santa Fe Institute, gig economy, Gini coefficient, Hyperloop, income inequality, industrial robot, Internet of things, invention of agriculture, invention of movable type, invention of the printing press, invisible hand, Jane Jacobs, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joseph Schumpeter, license plate recognition, Lyft, Mark Zuckerberg, mass immigration, Network effects, new economy, peer-to-peer lending, QWERTY keyboard, ransomware, Richard Florida, Robert Gordon, Ronald Reagan, Second Machine Age, self-driving car, sharing economy, Shoshana Zuboff, Silicon Valley, Simon Kuznets, Snapchat, speech recognition, Stuxnet, TaskRabbit, The Death and Life of Great American Cities, The Rise and Fall of American Growth, the scientific method, trade route, Turing test, Uber and Lyft, uber lyft, universal basic income, uranium enrichment, urban planning, zero day, zero-sum game, Zipcar

Activities we used to do in physical space are being transferred to virtual space. Relationships that used to be carried out over coffee are continued over social networks. When crime, terror, and war all move to virtual space, the troops become automatons that do not bleed. Private citizens and military groups alike have access to intercontinental cyber-missiles carrying nuclear cyber-bombs. Crypto-currencies like BitCoin and the Ether may displace the coins and bills that are issued by nations. Games that used to be played on boards or on ballfields get moved to virtual space with participants from all over the world. Virtual teams play MMORPGs (massively multiplayer online role-playing games), slaying monsters and dragons. Unlike activities in physical space, many cyber-actions are almost infinitely scalable and come with close to zero incremental costs.

Bots can be used to recruit thousands of online devices to flood targeted websites with so many messages that they are overwhelmed and can no longer service customers. Companies from Airbnb and Amazon to Starbucks, Twitter, Visa, and Zillow have been victims of these “denial of service” attacks. Then there are ransomware attacks, in which viruses seize control of computers and encrypt user files unless the user is willing to pay a ransom in a cryptocurrency. In some cases, malware can direct the system to shut down and erase itself, or, as in the case of Stuxnet, speed up until it destroys itself. Cyber weapons can disrupt or shut down power grids and communication, transportation, and financial networks, and bring commercial operations to a standstill. They can and do cause tremendous physical damage as well. Cybersecurity Ventures estimates the cost of cybercrime at $3 trillion in 2015 and projects that it will rise to $6 trillion by 2021.45 To put this number in perspective, that represents about 4 percent of the gross domestic product for the world.46 To date, most of the damage done by cyber criminals/terrorists/warriors has been economic.

See customers/consumers; retail sector cookies, Internet, 89, 116, 117–118, 128 corporations. See commercial entities Craigslist, 62, 87 credit cards: cash contrasted with, 41–42 cost of and security risk with, 74–76 cyber/mobile payment systems replacing, 10, 76–77, 81–82, 171, 186 emergence and scale timeline of, 82 information equivalents for, 76–77 credit rating agencies, 118–119, 126, 130 crowd-sourcing, 70–71 cryptocurrency. See cyber currencies cultural lag, 38, 181, 187, 189–190, 192 cultural norms: of Agricultural Revolution, 151–152 Autonomous Revolution’s requirement of new, 151, 153–157, 159 of Industrial Revolution, 152–153, 182–183 customers/consumers: algorithmic prisons for, 126, 127 data collection protections for, 127–128 industrial robots in relation to, xii information equivalences for, 43–44 as products, 120–123.


pages: 154 words: 47,880

The System: Who Rigged It, How We Fix It by Robert B. Reich

affirmative action, Affordable Care Act / Obamacare, Bernie Madoff, Bernie Sanders, business cycle, clean water, collective bargaining, corporate governance, corporate raider, corporate social responsibility, Credit Default Swap, crony capitalism, cryptocurrency, Donald Trump, ending welfare as we know it, financial deregulation, Gordon Gekko, immigration reform, income inequality, Jeff Bezos, job automation, London Whale, Long Term Capital Management, market fundamentalism, mass incarceration, mortgage debt, Occupy movement, Ponzi scheme, race to the bottom, Robert Bork, Ronald Reagan, shareholder value, too big to fail, trickle-down economics, union organizing, women in the workforce, working poor, zero-sum game

It assembles iPhones in China both because wages are low there and because Apple’s Chinese contractor can quickly mobilize workers from company dormitories at almost any hour of the day or night. It is dangerous to believe that the top executives of corporations headquartered in the United States have a special allegiance to America. In July 2019, the U.S. Senate held hearings on Facebook’s planned cryptocurrency, Libra. Facebook executives cautioned that the firm must be allowed to create this currency or “some other country [that is, China] will.” But Facebook’s motive had nothing whatever to do with stopping China or any other country from creating its own cryptocurrency. Like JPMorgan, Facebook wants to be free to make as much money as it can, wherever it can. After all, Facebook has spent much of the last decade trying to curry favor with the Chinese in hopes of getting permission to operate Facebook apps there. Evidence of Facebook’s lack of allegiance to America is evident from the fact that the worldwide association it established for Libra is located in Switzerland, home of famously lax banking laws.


pages: 357 words: 95,986

Inventing the Future: Postcapitalism and a World Without Work by Nick Srnicek, Alex Williams

3D printing, additive manufacturing, air freight, algorithmic trading, anti-work, back-to-the-land, banking crisis, basic income, battle of ideas, blockchain, Boris Johnson, Bretton Woods, business cycle, call centre, capital controls, carbon footprint, Cass Sunstein, centre right, collective bargaining, crowdsourcing, cryptocurrency, David Graeber, decarbonisation, deindustrialization, deskilling, Doha Development Round, Elon Musk, Erik Brynjolfsson, Ferguson, Missouri, financial independence, food miles, Francis Fukuyama: the end of history, full employment, future of work, gender pay gap, housing crisis, income inequality, industrial robot, informal economy, intermodal, Internet Archive, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Kickstarter, late capitalism, liberation theology, Live Aid, low skilled workers, manufacturing employment, market design, Martin Wolf, mass immigration, mass incarceration, means of production, minimum wage unemployment, Mont Pelerin Society, neoliberal agenda, New Urbanism, Occupy movement, oil shale / tar sands, oil shock, patent troll, pattern recognition, Paul Samuelson, Philip Mirowski, post scarcity, post-work, postnationalism / post nation state, precariat, price stability, profit motive, quantitative easing, reshoring, Richard Florida, rising living standards, road to serfdom, Robert Gordon, Ronald Reagan, Second Machine Age, secular stagnation, self-driving car, Slavoj Žižek, social web, stakhanovite, Steve Jobs, surplus humans, the built environment, The Chicago School, The Future of Employment, Tyler Cowen: Great Stagnation, universal basic income, wages for housework, We are the 99%, women in the workforce, working poor, working-age population

A series of emerging contemporary phenomena must be thought through carefully: for instance, the causes and effects of secular stagnation; the transformations invoked by the shift to an informational, post-scarcity economy; the changes wrought by the introduction of full automation and a universal basic income; the possible approaches to collectivising automated manufacturing and services; the progressive potentials of alternative approaches to quantitative easing; the most effective ways to decarbonise the means of production; the implications of dark pools for financial instability – and so on. Equally, research should be revived on what postcapitalism might look like in practice. Beyond a few outdated classics, very little research has been done to think through an alternative economic system – even less so in the wake of emerging technologies like additive manufacturing, self-driving vehicles and soft AI.68 What role, for instance, could non-state cryptocurrencies have? How does one measure value if not by abstract or concrete labour? How can ecological concerns be fully accounted for in a postcapitalist economic framework? What mechanism can replace the market and overcome the socialist calculation problem?69 And what are the likely effects of the possible tendency for the rate of profit to fall?70 Building a postcapitalist world is as much a technical task as a political one, and in order to begin thinking about it, the left needs to overcome its general aversion to formal modelling and mathematics.

It would mean building upon the post-nation-state territory of ‘the stack’ – that global infrastructure that enables our digital world today.26 A new type of production is already visible at the leading edges of contemporary technology. Additive manufacturing and the automation of work portend the possibility of production based on flexibility, decentralisation and post-scarcity for some goods. The rapid automation of logistics presents the utopian possibility of a globally interconnected system in which parts and goods can be shipped rapidly and efficiently without human labour. Cryptocurrencies and their block-chain technology could bring forth a new money of the commons, divorced from capitalist forms.27 The democratic guidance of the economy is also accelerated by emerging technologies. Famously, Oscar Wilde once said that the problem with socialism was that it took up too many evenings. Increasing economic democracy could require us to devote an overwhelming amount of time to discussions and decisions over the minutiae of everyday life.28 The use of computing technology is essential in avoiding this problem, both by simplifying the decisions to be made and by automating decisions collectively deemed to be irrelevant.

Index 1968, 16–7, 63, 188n33 15M, 11, 22 abstraction, 10, 15, 36, 44, 81 additive manufacturing, 110, 143, 150, 182 affect, 7–8, 113–4, 140–1 afro-futurism, 139, 141 AI (artificial intelligence), 110, 143 alienation, 14–5, 82 algorithmic trading, 111 Allende, Salvador, 148, 149 alternativism, 194n95 Althusser, Louis, 81, 141–2 anti-globalisation, 3, 159, 162 anti-war, 3, 5, 22, 162 Apple, 146, Arab Spring, 131, 159 Argentina, 37–9, 173 authenticity, 10–1, 15, 27, 82, 180 automation, 1–2, 86, 88–9, 94–5, 97–8, 104–5, 109–17, 122, 127, 130, 143, 150–1, 167, 171–4, 181–2, 203n15, 212n121, 214n161, 215n9, 218n45 banking, 43–6, 61, 147 Beveridge Report, 118 big data, 110, 111 Bolshevik Revolution, 131 Bolsheviks, 137 Russian Revolution, 139 Brazil, 75, 119, 147, 157, 169 Bretton Woods, 61–2 Brown, Michael, 173 care labour, 113–4 Chicago School, 51, 59–60 Chile, 52, 62, 148, 149, 150 China, 87, 89, 97, 170 class, 14, 16–7, 20–1, 25, 53, 64–5, 87, 91, 96–102, 116, 120, 122–3, 126–7, 132–3, 155–62, 170, 173–4, 189n1, 206n44, 233n119, 233n4, 233n5, 234n18 Cleaver, Eldridge, 91–2 climate change, 13–4, 116 colonialism, 73, 75–6, 96–7, 225n3 common sense, 9–11, 21–2, 40, 54–5, 58–60, 63–7, 72, 131–7 communisation, 92, 225n5 competitive subjects, 63–5, 99, 124 complex systems, 13–4, conspiracy theories, 14–5 cosmism, 139 Critchley, Simon, 72 cryptocurrencies, 143, 182 Cybersyn, 149–150 debt, 9, 22, 35–6, 94 demands, 6–7, 30, 33, 107–8, 130, 159–62, 167 no demands, 7, 34–5, 107, 186n3 non-reformist demands, 108 transitional demands, 215n5 democracy, 31–3, 182 direct democracy, 27–9, 31–3, 164, 190n8 direct action, 6, 11, 27–9, 35–6 education, 64, 99, 104, 141–5, 165–6 Egypt, 32–4, 190n21 energy, 2, 16,19,41, 42–43, 116, 147, 148, 150–51, 164, 171, 178, 179, 182, 183 Engels, Friedrich, 79 Erhard, Ludwig, 57 ethics, 42 work ethic, 124–6 evictions, 8, 12, 36 feminism, 18–21, 122, 138, 161 Fisher, Antony, 58–9, 196n34 food miles, 42–3 fracking, 8 France, 17, 62, 149, 167 free time, 80, 115–6, 120–1, 167, 219n50 freedom, 63–5, 120–1, 126–7, 180–1 negative freedom, 79 synthetic freedom, 78–83 Friedman, Milton, 56, 59–61 full employment, 98–100 future, 1, 71–5, 175–8, 181–3 G20, 6, 94 gender, 21, 41, 90, 122 Germany, 45, 56–7 ghettos, 95–6 Gramsci, Antonio, 132, 165 Graeber, David, 33 grand narratives, 73–4 Great Depression, 46, 65, 99–101, 114–5 Harvey, David, 135 Hayek, Friedrich, 54–6 Holzer, Jenny, 175, 178 horizontalism, 18, 26–39 housing, 8, 28, 35, 48, 77, 80, 95, 96, 148, 159, 167, 168, humanism, 81–3, 180–1 hyperstition, 74–5, 138–9 Iceland, 34, 164 idleness, 85–6 immediacy, 10–1 immigration, 101–2, 161 India, 87, 97–8, 130 inequality, 22, 80, 93–4 informal economy, 95–8, 203n10, 206n44, 210n95 Institute of Economic Affairs, 58–9 Iranian Revolution, 131 Jameson, Fredric, 14, 92, 198n10 Japan, 147 Jimmy Reid Foundation, 117 jobless recovery, 94–5 Jobs, Steve, 179 Johnson, Boris, 172 Kalecki, Michał, 120 Krugman, Paul, 118 labour, 2, 3,9, 17, 20, 21, 33, 38, 48, 52, 58, 61–3, 74, 79, 81, 83, 85–143, 148, 150, 151, 156–8, 161, 163–181, 182 Laclau, Ernesto, 155, 159 Lafargue, Paul, 115, language, 81, 132, 160, 164–5 leisure, 85–6 Leninism, 17, 131, 188n33 Live Aid, 8 localism, 40–6 locavorism, 41–2 Lucas Aerospace, 147 Luxemburg, Rosa, 15 Lyotard, Francois, 73, 74 Manhattan Institute for Policy Research, 58, 59 marches, 6, 30, 49 Marikana massacre, 170 Marinaleda, 48 Marx, Karl, 73, 79, 85, 86, 92, 115, 119, 121, 122, 132, 142, 156, 158, 180 Mattick, Paul, 92, 118 media, 2, 7–8, 31, 36, 52, 58, 60, 63, 67, 88, 118, 125–6, 129, 133–5, 163–5, 176, 182 Mirowski, Philip, 66 modernity, 23, 63, 69–85, 86, 131, 176, 181 modernisation, 23, 60, 63, 137, 174 Mont Pelerin Society, 54, 86, 134, 164, 166 MPS, 55, 56, 58, 66, 67, 134 Move Your Money, 44 Murray, Charles, 59 Musk, Elon, 179 National Union of Rail, Maritime and Transport Workers, 172 negative solidarity, 20, 37 neoliberalism, 3, 12, 20–3, 47, 49, 51–67, 70, 72, 108, 116, 117, 119, 121, 124, 134, 141, 142, 148, 156, 176, 179, 183 neoliberal, 7, 9, 14–16, 20, 21, 37, 47, 49, 73, 93, 99, 118, 126, 127, 129, 131–2, 134, 135, 162, 169, 174, 176, 181 New Economics Foundation, 117, 144 new left, 18–22 New Zealand, 151 occupations, 5, 7, 10, 11, 29–31, 34, 49, 94, 172 Occupy Wall Street, 3, 6, 7, 11, 18, 22, 26, 29–38, 126, 133, 158, 159, 160, 162, 189n1 ordoliberals, 54, 57 organic intellectual, 165–6 Overton Window, 134, 139 Partido dos Trabalhadores, 169 parties, political, 2, 10, 16, 17, 18, 20, 21, 30, 34, 39, 46, 59, 105, 116, 118, 124, 129, 162, 164, 168, 169 personal savings, 94 Piketty, Thomas, 140 Plan C, 117 planning, 1, 15, 56, 141, 142, 149, 151, 182 Plant, Sadie, 82 Podemos, 159, 160, 169 police, 6, 30, 33, 36, 37, 102, 133, 161, 168, 171, 173 postcapitalism, 17, 38, 130, 143, 145, 150, 151, 158, 168, 178, 180 postcapitalist, 12, 15, 16, 32, 34, 83, 109, 115, 126, 136, 143, 145, 150, 152, 153, 157, 179, 180 Post-Crash Economic Society, 143 post-work, 23, 69, 83, 85, 86, 105, 107–127, 129, 130, 138, 140, 141, 153, 155, 156, 158, 161, 163, 164, 167, 174, 175, 176, 177, 178 Pou Chen Group, 170 power, 1, 2, 7, 9, 10, 14, 15, 18–21, 26, 28–30, 33, 36, 43, 46, 48, 49, 59, 61, 62, 65, 73, 78, 79, 80, 81, 87, 88, 93, 100, 108, 111, 116, 120, 123, 127, 130–5, 146, 148, 151, 153, 155–74, 175, 176, 179, 180, 182 precarity, 9, 86, 88, 93, 94, 95, 98, 104, 121, 123, 126, 130, 156, 157, 166, 167, 173, 174 precarious, 2, 64, 117, 129, 167 Precarious Workers Brigade, 117 premature deindustrialisation, 97, 98 primitive accumulation, 87, 89, 90, 96, 97 prison, 90, 102, 103, 119, 133 incarceration, 102, 103, 104, 105, 161 productivity, 74, 88, 97, 110–17, 125, 150, 167 progress, 21, 23, 46, 71–5, 77, 107, 114, 115, 120, 126, 131, 138, 179, 180 protests, 1, 7, 18, 22, 28, 31, 37, 49, 66, 153, 164 psychopathologies, 64 radio-frequency identification, 110 race, 14, 31, 90, 102, 103, 140, 156, 171, 172 Reagan, Ronald, 60, 62, 66, 70 Republican Party (US), 135 resistance, 2, 5, 12, 15, 30, 35, 46–8, 49, 69, 72, 74, 83, 114, 124, 134, 158, 173, 181 Rethinking Economics, 143 Robinson, Joan, 87 Roboticisation, 110, 209n69 mechanisation, 95, 101 Rolling Jubilee, 9 Samuelson, Paul, 142 second machine age, 111 secular stagnation, 143 self-driving cars, 110, 111, 113, 173 shadow work, 115 slavery, 74, 90, 95, 103 slow food, 41, 42 slum, 86, 96–8, 102, 104 social democracy, 3, 17, 46, 66, 70, 167, 176 social democratic, 10, 13, 16, 17, 19, 21, 22, 47, 57, 72, 80, 98, 100, 108, 123, 127, 168 social media, 1, 8, 182 South Africa, 119, 157, 170 Spain, 12, 22, 34, 35, 45, 159, 164 stagflation, 19, 27, 61, 65, 100 Stalinist, 17, 18, 137 strategy, 12, 20, 26, 49, 56, 67, 117, 127, 131–3, 136, 148, 153, 156, 163, 164 strategic, 8, 9, 11, 12, 14, 15, 17, 18, 25, 28, 29, 35, 49, 52, 55, 66, 70, 77, 108, 116, 131, 135, 157, 162, 163, 164, 170, 171, 173, 174 strikes, 9, 10, 28, 36, 37, 116, 120, 157, 167, 170–3 suicide, 94 surplus populations, 40, 86, 88–94, 96–97, 101–3, 104, 105, 120, 130, 166–7, 173, 203n10 Syriza, 159, 160 tactics, 6, 10, 11, 15, 18, 19, 26, 28, 39, 40, 49, 157, 164, 171–4 Tahrir Square, 32, 34 Taylorism, 152 technology, 1, 3, 72, 81, 88, 89, 98, 109, 110, 111, 129, 136, 137, 145–8, 150–3, 178, 179, 182 Thatcher, Margaret, 59, 60, 62, 66, 70, 72, 100 think tanks, 16, 55, 56, 58, 59, 60, 63, 67, 117, 134, 135, 165 trade unions, 10, 27, 47, 59, 61, 62, 71, 105, 116, 117, 124, 129, 148, 162, 166 labour unions, 16, 171 unions, 17, 18, 20, 27, 30, 44 UK Uncut, 126 unemployment, 20, 56, 60, 79, 86–98, 99, 100, 101, 101, 102, 115, 116, 118, 121, 123, 125, 127, 129, 147, 159, 161, 168, 170, 173, 207n44 United Automobile Workers, 170 United Kingdom UK, 8, 20, 40, 42, 45, 52, 54, 56, 58, 61, 62, 92, 93, 94, 117, 118, 126, 144, 147, 151, 172 United States, 8, 18, 29, 36, 44, 45, 59, 62, 78, 92, 95, 103, 114, 118, 123, 133, 135, 138, 167 America, 6, 16, 30, 38, 47, 56, 62, 76, 95, 97, 98, 100, 101, 102, 103, 110, 164 universal basic income, 108, 118, 123, 127, 140, 143 basic income, 80, 108, 118, 119, 120, 121, 122, 123, 124, 127, 129, 130, 140, 143, 164, 165, 167 universalism, 69, 70, 75–8, 83, 119, 132, 175, 197n1, 199n40 USSR, 62, 63, 79, 139 Soviet Union, 57, 70, 74, 139 utopia, 3, 28, 32, 35, 48, 54, 58, 60, 66, 69, 70, 72, 108, 113, 114, 132, 136, 137, 138, 139, 140, 141, 143, 145, 146, 150, 153, 177, 179, 181, 182 vanguard functions, 163 Venezuela, 169 wages, 2, 71, 87, 90, 91, 93, 94, 97, 98, 101, 111, 120, 122, 125, 156, 166, 167 welfare, 14, 38, 57, 59, 61, 62, 63, 64, 71, 73, 90, 100, 101, 103, 105, 118, 119, 122, 124 Wilde, Oscar, 182 withdrawal, 11, 47, 48, 69, 131, 182 exit, 47, 48, 181 escape, 3, 9, 11, 38, 69, 107, 114, 139, 165, 178 work, 1, 2, 16, 17, 23, 32, 36, 41, 44, 47, 64, 71, 85, 86, 90–6, 98, 100, 101, 103–5, 108, 109, 110–7, 120–7, 130, 131, 132, 133, 134, 136, 140, 141, 142, 143, 147, 150, 151, 152, 157, 163, 165, 166, 170, 173, 174, 176, 177, 178, 181 wage labour, 74, 85, 86, 87, 89, 90, 92, 103, 104, 105, 120, 136, 141, 180 job, 2, 38, 41, 47, 48, 63, 64, 79, 85, 86, 88, 89, 90, 93, 94, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 110, 111, 113, 114–23, 124, 125, 126, 129, 147, 148, 161, 166, 167, 171 worker-controlled factories, 38, 39 workfare, 59, 100, 104 World Trade Organisation, 6 World War II, 46, 54, 56, 57, 115, 156 Zapatistas, 11, 22, 26, 35 zero-hours contracts, 93 Žižek, Slavoj, 140 Zuccotti Park, 31, 32


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Tribe of Mentors: Short Life Advice From the Best in the World by Timothy Ferriss

23andMe, A Pattern Language, agricultural Revolution, Airbnb, Albert Einstein, Bayesian statistics, bitcoin, Black Swan, blockchain, Brownian motion, Buckminster Fuller, Clayton Christensen, cloud computing, cognitive dissonance, Colonization of Mars, corporate social responsibility, cryptocurrency, David Heinemeier Hansson, dematerialisation, don't be evil, double helix, effective altruism, Elon Musk, Ethereum, ethereum blockchain, family office, fear of failure, Gary Taubes, Geoffrey West, Santa Fe Institute, Google Hangouts, Gödel, Escher, Bach, haute couture, helicopter parent, high net worth, In Cold Blood by Truman Capote, income inequality, index fund, Jeff Bezos, job satisfaction, Johann Wolfgang von Goethe, Kevin Kelly, Lao Tzu, Law of Accelerating Returns, Lyft, Mahatma Gandhi, Marc Andreessen, Marshall McLuhan, Mikhail Gorbachev, minimum viable product, move fast and break things, move fast and break things, Naomi Klein, non-fiction novel, Peter Thiel, profit motive, Ralph Waldo Emerson, Ray Kurzweil, Saturday Night Live, side project, Silicon Valley, Skype, smart cities, smart contracts, Snapchat, Steve Jobs, Steven Pinker, Stewart Brand, TaskRabbit, Tesla Model S, too big to fail, Turing machine, uber lyft, web application, Whole Earth Catalog, Y Combinator

And really, thank you so much for your interest. I’ll be kicking myself when the book comes out. –W “I’d rather give an understated good recommendation: be interdisciplinary . . . the interactions between [fields] tend to very often inform strategic and protocol decisions.” Vitalik Buterin TW: @VitalikButerin Reddit: /u/vbuterin VITALIK BUTERIN is the creator of Ethereum. He first discovered blockchain and cryptocurrency technologies through Bitcoin in 2011, and was immediately excited by the technology and its potential. He co-founded Bitcoin magazine in September 2011, and after two and a half years looking at what the existing blockchain technology and applications had to offer, wrote the Ethereum white paper in November 2013. He now leads Ethereum’s research team, working on future versions of the Ethereum protocol.

When you feel overwhelmed or unfocused, what do you do? I sit and desire ideas. “Trusted third parties are security holes.” Nick Szabo TW: @NickSzabo4 unenumerated.blogspot.com NICK SZABO is a polymath. The breadth and depth of his interests and knowledge are truly astounding. He’s a computer scientist, legal scholar, and cryptographer best known for his pioneering research in digital contracts and cryptocurrency. The phrase and concept of “smart contracts” were developed by Nick with the goal of bringing what he calls the “highly evolved” practices of contract law and practice to the design of electronic commerce protocols between strangers on the Internet. Nick also designed Bit Gold, which many consider the precursor to Bitcoin. * * * What is the book (or books) you’ve given most as a gift, and why?

I’m a startup founder, and there is always something or other to do. Here are some approaches that have helped: I started saying no to all external meeting requests as a rule of thumb. External meetings should be initiated by me (doesn’t happen that often) and not initiated by others. Saying no to all involvements outside of my startup, such as being an advisor to some other startup or project, investing in or trading some crypto­currency where I have domain expertise, etc. There is only one job/role that I can think about. No exceptions. Letting other people on my team deal with external invitations, calls, meetings, events, etc. Build strong connections with your team and stay updated on things through them. In other words, the team members are a filter for all the invitations and distractions. Important stuff has a way of bubbling up and you won’t miss out.


pages: 209 words: 53,236

The Scandal of Money by George Gilder

Affordable Care Act / Obamacare, bank run, Bernie Sanders, bitcoin, blockchain, borderless world, Bretton Woods, capital controls, Capital in the Twenty-First Century by Thomas Piketty, Carmen Reinhart, central bank independence, Claude Shannon: information theory, Clayton Christensen, cloud computing, corporate governance, cryptocurrency, currency manipulation / currency intervention, Daniel Kahneman / Amos Tversky, Deng Xiaoping, disintermediation, Donald Trump, fiat currency, financial innovation, Fractional reserve banking, full employment, George Gilder, glass ceiling, Home mortgage interest deduction, index fund, indoor plumbing, industrial robot, inflation targeting, informal economy, Innovator's Dilemma, Internet of things, invisible hand, Isaac Newton, Jeff Bezos, John von Neumann, Joseph Schumpeter, Kenneth Rogoff, knowledge economy, Law of Accelerating Returns, Marc Andreessen, Mark Zuckerberg, Menlo Park, Metcalfe’s law, money: store of value / unit of account / medium of exchange, mortgage tax deduction, obamacare, Paul Samuelson, Peter Thiel, Ponzi scheme, price stability, Productivity paradox, purchasing power parity, quantitative easing, quantitative trading / quantitative finance, Ray Kurzweil, reserve currency, road to serfdom, Robert Gordon, Robert Metcalfe, Ronald Reagan, Sand Hill Road, Satoshi Nakamoto, Search for Extraterrestrial Intelligence, secular stagnation, seigniorage, Silicon Valley, smart grid, South China Sea, special drawing rights, The Great Moderation, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, Tim Cook: Apple, time value of money, too big to fail, transaction costs, trickle-down economics, Turing machine, winner-take-all economy, yield curve, zero-sum game

The eminent Austrian offered similar objections to a proposal for private money backed by gold: “It would turn out to be a very good investment, for the reason that because of the increased demand for gold the value of gold would go up; but that very fact would make it very unsuitable as money.”4 Ametrano adds, “The unfeasibility of a bitcoin [or gold] loan is similar to that of a bitcoin or [gold] salary: neither a borrower nor an employer would want to face the risk of seeing her debt or salary liabilities growing a hundredfold in a few years.”5 He concludes, “This is the cryptocurrency paradox: In the successful attempt to get rid of any centralized monetary authority using the Bitcoin protocol, the bitcoin currency has inadvertently thrown away the flexibility of an elastic monetary policy.” In a presentation to the Bank of Italy, Ametrano rejected the idea that bitcoin will lose its instability with wider adoption: “This is indeed true, but not at all sufficient for stable prices, as demonstrated by the need of monetary actions to stabilize even globally accepted currencies such as the Euro and US dollar.”6 One can imagine the eminent men of Banca d’Italia nodding solemnly at this observation.

“E-Commerce Speeds Up, Hits Record High Share of Retail Sales,” MarketWatch (blog), August 15, 2014, http://blogs.marketwatch.com/capitolreport/2014/08/15/e-commerce-speeds-up-hits-record-high-share-of-retail-sales/. 3.Susan Vranica, “The Secret about On-Line Ad Traffic, One-Third is Bogus,” Wall Street Journal, March 23, 2014, http://www.wsj.com/articles/SB10001424052702304026304579453253860786362. 4.Nick Szabo, “Macroscale Replicator,” October 19, 1995. 5.Szabo’s blog, Unenumerated, is published online by Forbes.com. All the quotations here are from the Unenumerated archive. 6.Richard Vigilante, personal communication. CHAPTER 8: WHERE “HAYEKS” GO WRONG 1.Ferdinando M. Ametrano, “Hayek Money: The Cryptocurrency Price Stability Solution,” Social Science Research Network, revised July 5, 2015, http://ssrn.com/abstract=2425270, 54. Ametrano’s paper was shortlisted as a finalist for the Blockchain Awards, category Visionary Academic Paper, at the Bitcoin Foundation Conference 2014, but it lost to Nakamoto’s original breakthrough paper. 2.Ibid., 5–6. 3.Ibid., 10. 4.Ibid., 20; and Friedrich A. Hayek, Denationalization of Money—The Argument Refined, 3rd ed.


pages: 182 words: 53,802

The Production of Money: How to Break the Power of Banks by Ann Pettifor

Ben Bernanke: helicopter money, Bernie Madoff, Bernie Sanders, bitcoin, blockchain, borderless world, Bretton Woods, capital controls, Carmen Reinhart, central bank independence, clean water, credit crunch, Credit Default Swap, cryptocurrency, David Graeber, David Ricardo: comparative advantage, debt deflation, decarbonisation, distributed ledger, Donald Trump, eurozone crisis, fiat currency, financial deregulation, financial innovation, financial intermediation, financial repression, fixed income, Fractional reserve banking, full employment, Hyman Minsky, inflation targeting, interest rate derivative, invisible hand, John Maynard Keynes: Economic Possibilities for our Grandchildren, Joseph Schumpeter, Kenneth Rogoff, Kickstarter, light touch regulation, London Interbank Offered Rate, market fundamentalism, Martin Wolf, mobile money, Naomi Klein, neoliberal agenda, offshore financial centre, Paul Samuelson, Ponzi scheme, pushing on a string, quantitative easing, rent-seeking, Satyajit Das, savings glut, secular stagnation, The Chicago School, the market place, Thomas Malthus, Tobin tax, too big to fail

In a recent blog, Financial Times journalist Izabella Kaminska argued that financial technology fads follow a pattern similar to new music designated first as ‘hip’ and ‘cool’ but which then fades and becomes ‘so last year’. In the same way, for her as an investigative journalist, Blur (bitcoin) evolved into a love of Radiohead (blockchain). But Radiohead (blockchain) was adopted too quickly by those who then compromised the likeability of the entire Indy genre (cryptocurrency). It was time consequently to turn to drum and bass (private blockchains). But drum and bass was being cross-polluted by Indy rock enthusiasts (cryptocurrency enthusiasts) so it became time to embrace something totally radical and segregated, i.e. go backwards to an ironic appreciation of Barry Manilow abandoning all refs to modern musical phenomena (Distributed Ledger Technology). Which puts us roughly at the point where cheesy revivalism should be turning into a general love of the all time provable greats (old school centralised ledger technology, but you know, digitally remastered).


We Are the Nerds: The Birth and Tumultuous Life of Reddit, the Internet's Culture Laboratory by Christine Lagorio-Chafkin

4chan, Airbnb, Amazon Web Services, Bernie Sanders, big-box store, bitcoin, blockchain, Brewster Kahle, Burning Man, crowdsourcing, cryptocurrency, David Heinemeier Hansson, Donald Trump, East Village, game design, Golden Gate Park, hiring and firing, Internet Archive, Jacob Appelbaum, Jeff Bezos, jimmy wales, Joi Ito, Justin.tv, Kickstarter, Lean Startup, Lyft, Marc Andreessen, Mark Zuckerberg, medical residency, minimum viable product, natural language processing, Paul Buchheit, Paul Graham, paypal mafia, Peter Thiel, plutocrats, Plutocrats, QR code, recommendation engine, RFID, rolodex, Ruby on Rails, Sam Altman, Sand Hill Road, Saturday Night Live, self-driving car, semantic web, side project, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, slashdot, Snapchat, social web, South of Market, San Francisco, Startup school, Stephen Hawking, Steve Jobs, Steve Wozniak, technoutopianism, uber lyft, web application, WikiLeaks, Y Combinator

“We are thinking about creating a cryptocurrency and making it exchangeable (backed) by those shares of reddit, and then distributing the currency to the community. The investors have explicitly agreed to this in their investment terms,” he wrote. “Nothing like this has ever been done before.” The post had a disclaimer at its top: “CAVEAT: KEEP IN MIND THAT THIS PLAN COULD TOTALLY FAIL.” * * * The year 2014 was a turnaround year for cryptocurrency; major retailers such as Overstock, Microsoft, and Dell began accepting Bitcoin, and to payments-startup insiders, some of the hottest scrappy San Francisco upstarts—Coinbase, Ripple—were in digital currency. Wong thought, if anything could manage his vision for distributing tiny fractions of dollars to Redditors, the blockchain might work. He hired a cryptocurrency engineer, Ryan X.

Alex Angel in Portland was told that Wong’s offer to work remotely was no longer valid; she would need to move to San Francisco. Angel, the former rocket scientist who’d transformed her life and career to work for Reddit ever since that day at the Colbert rally when she was just a college kid in her alien T-shirt, said no. She had a life in Portland. She resigned and took the severance. Also dismissed: cryptocurrency engineer Ryan X. Charles, who later said he was given no reasonable opportunity to pitch to the new administration his digital creation harnessing blockchain technology, which Wong had hired him to develop. There were others. Every few weeks, someone would not show up to the Wednesday all-hands meeting, and stop appearing on online chat—and everyone else would be left to speculate what happened.


pages: 484 words: 114,613

No Filter: The Inside Story of Instagram by Sarah Frier

Airbnb, Amazon Web Services, blockchain, Clayton Christensen, cloud computing, cryptocurrency, Donald Trump, Elon Musk, Frank Gehry, Jeff Bezos, Marc Andreessen, Mark Zuckerberg, Menlo Park, Minecraft, move fast and break things, move fast and break things, Network effects, new economy, Oculus Rift, Peter Thiel, ride hailing / ride sharing, side project, Silicon Valley, Silicon Valley startup, Snapchat, Steve Jobs, TaskRabbit, Tony Hsieh, Travis Kalanick, ubercab, Zipcar

The consensus was that the team had always been high maintenance, asking for slightly bigger desks, longer bathroom doors that reached all the way to the floor, and conference rooms that were off-limits to other Facebook employees. If they wanted to leave in a huff at the slightest suggestion of making the investment worth it, after Zuckerberg had made them both billionaires, then good riddance. “I find attacking the people and company that made you a billionaire, and went to an unprecedented extent to shield and accommodate you for years, low-class,” David Marcus, the Facebook executive in charge of a new cryptocurrency initiative, later wrote publicly. “It’s actually a whole new standard of low-class.” It showed what could happen if, as an acquired company, you didn’t realize you were still beholden to Facebook’s needs. But Systrom and Krieger felt like they’d been much more reasonable. Besides their ad business, they’d suffered all those IGTV meetings and talks of “cannibalization.” They’d begrudgingly built more prominent ways to navigate to Facebook from Instagram.

They had their eye on one of Facebook’s top leaders, Adam Mosseri, who had been at the company for almost a decade. With a background as a designer, he ran Facebook’s news feed. He had been waging battles to improve the product’s look and feel. He also happened to be good at Instagram, with an account full of aesthetically pleasing cityscapes and nature shots. They needed someone new on product. Kevin Weil, whom Systrom recruited in from Twitter in 2016, had left to join Facebook’s new cryptocurrency group, Libra, which would try to develop a global form of money to rival the U.S. dollar. So Systrom and Krieger recruited Mosseri to replace Weil. Instagram employees were skeptical of their choice and wondered if the Instagram cofounders had had a choice at all. Amid the tension with Facebook, nobody was sure if the founders really wanted Mosseri, or if they’d been forced to bring him in so that Instagram could be more tightly controlled by Facebook.

News, 154, 192 escapism, 23, 209, 217, 239, 241 Escobar, Pablo, 238 Eswein, Liz, 43–44, 48, 82 Everson, Carolyn, 120–21 Eye Candy, 242 Facebook, xviii, 7, 10, 19, 39, 111, 181, 217, 222, 227, 246, 248, 253 advertising agencies’ relationship with, 120–21, 124 advertising business of, 75, 77, 91–92, 94, 96, 105, 118–19, 125, 149–50, 163, 217, 224 algorithmic personalization approach of, 91, 103, 128, 162, 163, 208, 209, 210–12, 215, 221, 224, 259 board of, 57, 63, 125, 191 business model of, 258–59 business team at, 222 Cambridge Analytica scandal at, 258, 259, 267 celebrity outreach of, 127–28, 156 Communications Decency Act and, 41 communications team at, 211, 222 “connect the world” goal of, 91, 149, 162 content policing at, 43, 97, 259, 260–61 Creative Labs at, 124 Creative Labs Skunk Works at, 191 cryptocurrency initiative at, 257, 263 data collection by, 89, 90, 91–92, 93, 122, 125, 143, 149, 258–59 dominance of, in social network world, 78, 88, 121, 124, 151, 209, 253, 255 early IG acquisition interest of, 28 edge stories of, 209–10 employee handbook of, 65, 93, 106, 228 engineering team at, 60, 62 ephemeral sharing on, 191, 193, 214, 215–16, 217 fake news scandal at, 210–11, 224–25, 234, 250–51, 255 “family of apps” bundled together with, 255–56, 259, 267–68, 277, 279 as friend-based network, 20, 31, 80 “friend coefficient” of, 91 global partnerships team at, 148 Gowalla acquired by, 51 growth as overarching goal at, xvii, 9, 91–92, 96, 150–51, 160, 209, 276 growth team at, 90, 92, 93, 95, 122, 177, 223, 260, 268 hackathons hosted by, 124, 187 hacker culture at, 93, 102 hierarchy reshuffle at, 255–56 hyperlinks on, 80, 210 as ideological echo chamber, 220–21 IG photo sharing to, 37 IG’s access to infrastructure and resources at, 96, 159, 162, 225, 249–50 IG’s access to infrastructure and resources denied by, 262, 268–69 IG’s cannibalization of, as issue at, 223, 226, 227–28, 257, 280 IG seen as threat to, xvii, 38, 57, 63–64, 77–78, 90, 95, 252–53, 270 IG’s growing resentment of, 254, 262, 263, 274 IG’s independence at, 54, 63, 65, 67, 89, 96, 106, 118, 121, 124, 209, 222–23 IG’s integration at, 100–101, 114, 223 IG users’ mistrust of, 100, 197 integrity team at, 259–60, 271 Internet.org division of, 124 IPO of, 56, 58, 74, 84, 128, 150 leadership team at, 222 link added from IG to, 228, 257 link to IG removed from, 228, 269 live video on, 261 lockdowns at, 108, 256, 269–70 Lookalike Audience tool of, 213 Menlo Park headquarters of, 66–68, 179, 200, 203, 210, 254 Mentions app of, 156 mobile advertising of, 105, 150 mobile troubles of, 93, 98 Mobile Uploads album on, 28 mounting tensions between IG and, 262, 263, 274 network effects of, 77–78 news feed on, 81, 91, 94, 96, 163, 211–12, 215, 259, 263, 264, 269 Nextstop acquired by, 32 Onavo acquired by, 122, 123, 181 1-billion-user milestone reached by, 88, 265 operations team at, 225 Palo Alto office of, 15, 88, 107 Paper app of, 156 partnerships team at, 50, 148, 200 photos launched by, 7 Poke app of, 115–16, 124, 191 policy team at, 211, 225, 232 politics and, 209–13 privacy issues at, 54, 92, 94, 264 privacy scandals at, 28, 154, 255, 267 public policy team at, 211 Riffs app of, 191 Saverin and, 15 scale and, 98, 103, 143, 225, 265 Slingshot app of, 191 tagging friends on, 7, 90 technology team at, 24, 26, 95, 214 trending topics module of, 207, 210 2-billion-user milestone reached by, 252 video on, 109, 215, 253–54 virality on, 162, 209, 211, 215, 251, 260 WhatsApp acquired by, 125, 202, 255 Yahoo!


Martin Kleppmann-Designing Data-Intensive Applications. The Big Ideas Behind Reliable, Scalable and Maintainable Systems-O’Reilly (2017) by Unknown

active measures, Amazon Web Services, bitcoin, blockchain, business intelligence, business process, c2.com, cloud computing, collaborative editing, commoditize, conceptual framework, cryptocurrency, database schema, DevOps, distributed ledger, Donald Knuth, Edward Snowden, Ethereum, ethereum blockchain, fault tolerance, finite state, Flash crash, full text search, general-purpose programming language, informal economy, information retrieval, Internet of things, iterative process, John von Neumann, Kubernetes, loose coupling, Marc Andreessen, microservices, natural language processing, Network effects, packet switching, peer-to-peer, performance metric, place-making, premature optimization, recommendation engine, Richard Feynman, self-driving car, semantic web, Shoshana Zuboff, social graph, social web, software as a service, software is eating the world, sorting algorithm, source of truth, SPARQL, speech recognition, statistical model, undersea cable, web application, WebSocket, wikimedia commons

A transaction log can be made tamper-proof by periodically signing it with a hardware security module, but that does not guarantee that the right transactions went into the log in the first place. It would be interesting to use cryptographic tools to prove the integrity of a system in a way that is robust to a wide range of hardware and software issues, and even poten‐ tially malicious actions. Cryptocurrencies, blockchains, and distributed ledger tech‐ nologies such as Bitcoin, Ethereum, Ripple, Stellar, and various others [71, 72, 73] have sprung up to explore this area. I am not qualified to comment on the merits of these technologies as currencies or mechanisms for agreeing contracts. However, from a data systems point of view they contain some interesting ideas. Essentially, they are distributed databases, with a data model and transaction mechanism, in which different replicas can be hosted by mutually untrusting organizations.

The transaction throughput of Bitcoin is rather low, albeit for political and economic reasons more than for technical ones. However, the integrity checking aspects are interesting. Cryptographic auditing and integrity checking often relies on Merkle trees [74], which are trees of hashes that can be used to efficiently prove that a record appears in some dataset (and a few other things). Outside of the hype of cryptocurrencies, certif‐ icate transparency is a security technology that relies on Merkle trees to check the val‐ idity of TLS/SSL certificates [75, 76]. 532 | Chapter 12: The Future of Data Systems I could imagine integrity-checking and auditing algorithms, like those of certificate transparency and distributed ledgers, becoming more widely used in data systems in general. Some work will be needed to make them equally scalable as systems without cryptographic auditing, and to keep the performance penalty as low as possible.

The opposite of bounded. 558 | Glossary Index A aborts (transactions), 222, 224 in two-phase commit, 356 performance of optimistic concurrency con‐ trol, 266 retrying aborted transactions, 231 abstraction, 21, 27, 222, 266, 321 access path (in network model), 37, 60 accidental complexity, removing, 21 accountability, 535 ACID properties (transactions), 90, 223 atomicity, 223, 228 consistency, 224, 529 durability, 226 isolation, 225, 228 acknowledgements (messaging), 445 active/active replication (see multi-leader repli‐ cation) active/passive replication (see leader-based rep‐ lication) ActiveMQ (messaging), 137, 444 distributed transaction support, 361 ActiveRecord (object-relational mapper), 30, 232 actor model, 138 (see also message-passing) comparison to Pregel model, 425 comparison to stream processing, 468 Advanced Message Queuing Protocol (see AMQP) aerospace systems, 6, 10, 305, 372 aggregation data cubes and materialized views, 101 in batch processes, 406 in stream processes, 466 aggregation pipeline query language, 48 Agile, 22 minimizing irreversibility, 414, 497 moving faster with confidence, 532 Unix philosophy, 394 agreement, 365 (see also consensus) Airflow (workflow scheduler), 402 Ajax, 131 Akka (actor framework), 139 algorithms algorithm correctness, 308 B-trees, 79-83 for distributed systems, 306 hash indexes, 72-75 mergesort, 76, 402, 405 red-black trees, 78 SSTables and LSM-trees, 76-79 all-to-all replication topologies, 175 AllegroGraph (database), 50 ALTER TABLE statement (SQL), 40, 111 Amazon Dynamo (database), 177 Amazon Web Services (AWS), 8 Kinesis Streams (messaging), 448 network reliability, 279 postmortems, 9 RedShift (database), 93 S3 (object storage), 398 checking data integrity, 530 amplification of bias, 534 of failures, 364, 495 Index | 559 of tail latency, 16, 207 write amplification, 84 AMQP (Advanced Message Queuing Protocol), 444 (see also messaging systems) comparison to log-based messaging, 448, 451 message ordering, 446 analytics, 90 comparison to transaction processing, 91 data warehousing (see data warehousing) parallel query execution in MPP databases, 415 predictive (see predictive analytics) relation to batch processing, 411 schemas for, 93-95 snapshot isolation for queries, 238 stream analytics, 466 using MapReduce, analysis of user activity events (example), 404 anti-caching (in-memory databases), 89 anti-entropy, 178 Apache ActiveMQ (see ActiveMQ) Apache Avro (see Avro) Apache Beam (see Beam) Apache BookKeeper (see BookKeeper) Apache Cassandra (see Cassandra) Apache CouchDB (see CouchDB) Apache Curator (see Curator) Apache Drill (see Drill) Apache Flink (see Flink) Apache Giraph (see Giraph) Apache Hadoop (see Hadoop) Apache HAWQ (see HAWQ) Apache HBase (see HBase) Apache Helix (see Helix) Apache Hive (see Hive) Apache Impala (see Impala) Apache Jena (see Jena) Apache Kafka (see Kafka) Apache Lucene (see Lucene) Apache MADlib (see MADlib) Apache Mahout (see Mahout) Apache Oozie (see Oozie) Apache Parquet (see Parquet) Apache Qpid (see Qpid) Apache Samza (see Samza) Apache Solr (see Solr) Apache Spark (see Spark) 560 | Index Apache Storm (see Storm) Apache Tajo (see Tajo) Apache Tez (see Tez) Apache Thrift (see Thrift) Apache ZooKeeper (see ZooKeeper) Apama (stream analytics), 466 append-only B-trees, 82, 242 append-only files (see logs) Application Programming Interfaces (APIs), 5, 27 for batch processing, 403 for change streams, 456 for distributed transactions, 361 for graph processing, 425 for services, 131-136 (see also services) evolvability, 136 RESTful, 133 SOAP, 133 application state (see state) approximate search (see similarity search) archival storage, data from databases, 131 arcs (see edges) arithmetic mean, 14 ASCII text, 119, 395 ASN.1 (schema language), 127 asynchronous networks, 278, 553 comparison to synchronous networks, 284 formal model, 307 asynchronous replication, 154, 553 conflict detection, 172 data loss on failover, 157 reads from asynchronous follower, 162 Asynchronous Transfer Mode (ATM), 285 atomic broadcast (see total order broadcast) atomic clocks (caesium clocks), 294, 295 (see also clocks) atomicity (concurrency), 553 atomic increment-and-get, 351 compare-and-set, 245, 327 (see also compare-and-set operations) replicated operations, 246 write operations, 243 atomicity (transactions), 223, 228, 553 atomic commit, 353 avoiding, 523, 528 blocking and nonblocking, 359 in stream processing, 360, 477 maintaining derived data, 453 for multi-object transactions, 229 for single-object writes, 230 auditability, 528-533 designing for, 531 self-auditing systems, 530 through immutability, 460 tools for auditable data systems, 532 availability, 8 (see also fault tolerance) in CAP theorem, 337 in service level agreements (SLAs), 15 Avro (data format), 122-127 code generation, 127 dynamically generated schemas, 126 object container files, 125, 131, 414 reader determining writer’s schema, 125 schema evolution, 123 use in Hadoop, 414 awk (Unix tool), 391 AWS (see Amazon Web Services) Azure (see Microsoft) B B-trees (indexes), 79-83 append-only/copy-on-write variants, 82, 242 branching factor, 81 comparison to LSM-trees, 83-85 crash recovery, 82 growing by splitting a page, 81 optimizations, 82 similarity to dynamic partitioning, 212 backpressure, 441, 553 in TCP, 282 backups database snapshot for replication, 156 integrity of, 530 snapshot isolation for, 238 use for ETL processes, 405 backward compatibility, 112 BASE, contrast to ACID, 223 bash shell (Unix), 70, 395, 503 batch processing, 28, 389-431, 553 combining with stream processing lambda architecture, 497 unifying technologies, 498 comparison to MPP databases, 414-418 comparison to stream processing, 464 comparison to Unix, 413-414 dataflow engines, 421-423 fault tolerance, 406, 414, 422, 442 for data integration, 494-498 graphs and iterative processing, 424-426 high-level APIs and languages, 403, 426-429 log-based messaging and, 451 maintaining derived state, 495 MapReduce and distributed filesystems, 397-413 (see also MapReduce) measuring performance, 13, 390 outputs, 411-413 key-value stores, 412 search indexes, 411 using Unix tools (example), 391-394 Bayou (database), 522 Beam (dataflow library), 498 bias, 534 big ball of mud, 20 Bigtable data model, 41, 99 binary data encodings, 115-128 Avro, 122-127 MessagePack, 116-117 Thrift and Protocol Buffers, 117-121 binary encoding based on schemas, 127 by network drivers, 128 binary strings, lack of support in JSON and XML, 114 BinaryProtocol encoding (Thrift), 118 Bitcask (storage engine), 72 crash recovery, 74 Bitcoin (cryptocurrency), 532 Byzantine fault tolerance, 305 concurrency bugs in exchanges, 233 bitmap indexes, 97 blockchains, 532 Byzantine fault tolerance, 305 blocking atomic commit, 359 Bloom (programming language), 504 Bloom filter (algorithm), 79, 466 BookKeeper (replicated log), 372 Bottled Water (change data capture), 455 bounded datasets, 430, 439, 553 (see also batch processing) bounded delays, 553 in networks, 285 process pauses, 298 broadcast hash joins, 409 Index | 561 brokerless messaging, 442 Brubeck (metrics aggregator), 442 BTM (transaction coordinator), 356 bulk synchronous parallel (BSP) model, 425 bursty network traffic patterns, 285 business data processing, 28, 90, 390 byte sequence, encoding data in, 112 Byzantine faults, 304-306, 307, 553 Byzantine fault-tolerant systems, 305, 532 Byzantine Generals Problem, 304 consensus algorithms and, 366 C caches, 89, 553 and materialized views, 101 as derived data, 386, 499-504 database as cache of transaction log, 460 in CPUs, 99, 338, 428 invalidation and maintenance, 452, 467 linearizability, 324 CAP theorem, 336-338, 554 Cascading (batch processing), 419, 427 hash joins, 409 workflows, 403 cascading failures, 9, 214, 281 Cascalog (batch processing), 60 Cassandra (database) column-family data model, 41, 99 compaction strategy, 79 compound primary key, 204 gossip protocol, 216 hash partitioning, 203-205 last-write-wins conflict resolution, 186, 292 leaderless replication, 177 linearizability, lack of, 335 log-structured storage, 78 multi-datacenter support, 184 partitioning scheme, 213 secondary indexes, 207 sloppy quorums, 184 cat (Unix tool), 391 causal context, 191 (see also causal dependencies) causal dependencies, 186-191 capturing, 191, 342, 494, 514 by total ordering, 493 causal ordering, 339 in transactions, 262 sending message to friends (example), 494 562 | Index causality, 554 causal ordering, 339-343 linearizability and, 342 total order consistent with, 344, 345 consistency with, 344-347 consistent snapshots, 340 happens-before relationship, 186 in serializable transactions, 262-265 mismatch with clocks, 292 ordering events to capture, 493 violations of, 165, 176, 292, 340 with synchronized clocks, 294 CEP (see complex event processing) certificate transparency, 532 chain replication, 155 linearizable reads, 351 change data capture, 160, 454 API support for change streams, 456 comparison to event sourcing, 457 implementing, 454 initial snapshot, 455 log compaction, 456 changelogs, 460 change data capture, 454 for operator state, 479 generating with triggers, 455 in stream joins, 474 log compaction, 456 maintaining derived state, 452 Chaos Monkey, 7, 280 checkpointing in batch processors, 422, 426 in high-performance computing, 275 in stream processors, 477, 523 chronicle data model, 458 circuit-switched networks, 284 circular buffers, 450 circular replication topologies, 175 clickstream data, analysis of, 404 clients calling services, 131 pushing state changes to, 512 request routing, 214 stateful and offline-capable, 170, 511 clocks, 287-299 atomic (caesium) clocks, 294, 295 confidence interval, 293-295 for global snapshots, 294 logical (see logical clocks) skew, 291-294, 334 slewing, 289 synchronization and accuracy, 289-291 synchronization using GPS, 287, 290, 294, 295 time-of-day versus monotonic clocks, 288 timestamping events, 471 cloud computing, 146, 275 need for service discovery, 372 network glitches, 279 shared resources, 284 single-machine reliability, 8 Cloudera Impala (see Impala) clustered indexes, 86 CODASYL model, 36 (see also network model) code generation with Avro, 127 with Thrift and Protocol Buffers, 118 with WSDL, 133 collaborative editing multi-leader replication and, 170 column families (Bigtable), 41, 99 column-oriented storage, 95-101 column compression, 97 distinction between column families and, 99 in batch processors, 428 Parquet, 96, 131, 414 sort order in, 99-100 vectorized processing, 99, 428 writing to, 101 comma-separated values (see CSV) command query responsibility segregation (CQRS), 462 commands (event sourcing), 459 commits (transactions), 222 atomic commit, 354-355 (see also atomicity; transactions) read committed isolation, 234 three-phase commit (3PC), 359 two-phase commit (2PC), 355-359 commutative operations, 246 compaction of changelogs, 456 (see also log compaction) for stream operator state, 479 of log-structured storage, 73 issues with, 84 size-tiered and leveled approaches, 79 CompactProtocol encoding (Thrift), 119 compare-and-set operations, 245, 327 implementing locks, 370 implementing uniqueness constraints, 331 implementing with total order broadcast, 350 relation to consensus, 335, 350, 352, 374 relation to transactions, 230 compatibility, 112, 128 calling services, 136 properties of encoding formats, 139 using databases, 129-131 using message-passing, 138 compensating transactions, 355, 461, 526 complex event processing (CEP), 465 complexity distilling in theoretical models, 310 hiding using abstraction, 27 of software systems, managing, 20 composing data systems (see unbundling data‐ bases) compute-intensive applications, 3, 275 concatenated indexes, 87 in Cassandra, 204 Concord (stream processor), 466 concurrency actor programming model, 138, 468 (see also message-passing) bugs from weak transaction isolation, 233 conflict resolution, 171, 174 detecting concurrent writes, 184-191 dual writes, problems with, 453 happens-before relationship, 186 in replicated systems, 161-191, 324-338 lost updates, 243 multi-version concurrency control (MVCC), 239 optimistic concurrency control, 261 ordering of operations, 326, 341 reducing, through event logs, 351, 462, 507 time and relativity, 187 transaction isolation, 225 write skew (transaction isolation), 246-251 conflict-free replicated datatypes (CRDTs), 174 conflicts conflict detection, 172 causal dependencies, 186, 342 in consensus algorithms, 368 in leaderless replication, 184 Index | 563 in log-based systems, 351, 521 in nonlinearizable systems, 343 in serializable snapshot isolation (SSI), 264 in two-phase commit, 357, 364 conflict resolution automatic conflict resolution, 174 by aborting transactions, 261 by apologizing, 527 convergence, 172-174 in leaderless systems, 190 last write wins (LWW), 186, 292 using atomic operations, 246 using custom logic, 173 determining what is a conflict, 174, 522 in multi-leader replication, 171-175 avoiding conflicts, 172 lost updates, 242-246 materializing, 251 relation to operation ordering, 339 write skew (transaction isolation), 246-251 congestion (networks) avoidance, 282 limiting accuracy of clocks, 293 queueing delays, 282 consensus, 321, 364-375, 554 algorithms, 366-368 preventing split brain, 367 safety and liveness properties, 365 using linearizable operations, 351 cost of, 369 distributed transactions, 352-375 in practice, 360-364 two-phase commit, 354-359 XA transactions, 361-364 impossibility of, 353 membership and coordination services, 370-373 relation to compare-and-set, 335, 350, 352, 374 relation to replication, 155, 349 relation to uniqueness constraints, 521 consistency, 224, 524 across different databases, 157, 452, 462, 492 causal, 339-348, 493 consistent prefix reads, 165-167 consistent snapshots, 156, 237-242, 294, 455, 500 (see also snapshots) 564 | Index crash recovery, 82 enforcing constraints (see constraints) eventual, 162, 322 (see also eventual consistency) in ACID transactions, 224, 529 in CAP theorem, 337 linearizability, 324-338 meanings of, 224 monotonic reads, 164-165 of secondary indexes, 231, 241, 354, 491, 500 ordering guarantees, 339-352 read-after-write, 162-164 sequential, 351 strong (see linearizability) timeliness and integrity, 524 using quorums, 181, 334 consistent hashing, 204 consistent prefix reads, 165 constraints (databases), 225, 248 asynchronously checked, 526 coordination avoidance, 527 ensuring idempotence, 519 in log-based systems, 521-524 across multiple partitions, 522 in two-phase commit, 355, 357 relation to consensus, 374, 521 relation to event ordering, 347 requiring linearizability, 330 Consul (service discovery), 372 consumers (message streams), 137, 440 backpressure, 441 consumer offsets in logs, 449 failures, 445, 449 fan-out, 11, 445, 448 load balancing, 444, 448 not keeping up with producers, 441, 450, 502 context switches, 14, 297 convergence (conflict resolution), 172-174, 322 coordination avoidance, 527 cross-datacenter, 168, 493 cross-partition ordering, 256, 294, 348, 523 services, 330, 370-373 coordinator (in 2PC), 356 failure, 358 in XA transactions, 361-364 recovery, 363 copy-on-write (B-trees), 82, 242 CORBA (Common Object Request Broker Architecture), 134 correctness, 6 auditability, 528-533 Byzantine fault tolerance, 305, 532 dealing with partial failures, 274 in log-based systems, 521-524 of algorithm within system model, 308 of compensating transactions, 355 of consensus, 368 of derived data, 497, 531 of immutable data, 461 of personal data, 535, 540 of time, 176, 289-295 of transactions, 225, 515, 529 timeliness and integrity, 524-528 corruption of data detecting, 519, 530-533 due to pathological memory access, 529 due to radiation, 305 due to split brain, 158, 302 due to weak transaction isolation, 233 formalization in consensus, 366 integrity as absence of, 524 network packets, 306 on disks, 227 preventing using write-ahead logs, 82 recovering from, 414, 460 Couchbase (database) durability, 89 hash partitioning, 203-204, 211 rebalancing, 213 request routing, 216 CouchDB (database) B-tree storage, 242 change feed, 456 document data model, 31 join support, 34 MapReduce support, 46, 400 replication, 170, 173 covering indexes, 86 CPUs cache coherence and memory barriers, 338 caching and pipelining, 99, 428 increasing parallelism, 43 CRDTs (see conflict-free replicated datatypes) CREATE INDEX statement (SQL), 85, 500 credit rating agencies, 535 Crunch (batch processing), 419, 427 hash joins, 409 sharded joins, 408 workflows, 403 cryptography defense against attackers, 306 end-to-end encryption and authentication, 519, 543 proving integrity of data, 532 CSS (Cascading Style Sheets), 44 CSV (comma-separated values), 70, 114, 396 Curator (ZooKeeper recipes), 330, 371 curl (Unix tool), 135, 397 cursor stability, 243 Cypher (query language), 52 comparison to SPARQL, 59 D data corruption (see corruption of data) data cubes, 102 data formats (see encoding) data integration, 490-498, 543 batch and stream processing, 494-498 lambda architecture, 497 maintaining derived state, 495 reprocessing data, 496 unifying, 498 by unbundling databases, 499-515 comparison to federated databases, 501 combining tools by deriving data, 490-494 derived data versus distributed transac‐ tions, 492 limits of total ordering, 493 ordering events to capture causality, 493 reasoning about dataflows, 491 need for, 385 data lakes, 415 data locality (see locality) data models, 27-64 graph-like models, 49-63 Datalog language, 60-63 property graphs, 50 RDF and triple-stores, 55-59 query languages, 42-48 relational model versus document model, 28-42 data protection regulations, 542 data systems, 3 about, 4 Index | 565 concerns when designing, 5 future of, 489-544 correctness, constraints, and integrity, 515-533 data integration, 490-498 unbundling databases, 499-515 heterogeneous, keeping in sync, 452 maintainability, 18-22 possible faults in, 221 reliability, 6-10 hardware faults, 7 human errors, 9 importance of, 10 software errors, 8 scalability, 10-18 unreliable clocks, 287-299 data warehousing, 91-95, 554 comparison to data lakes, 415 ETL (extract-transform-load), 92, 416, 452 keeping data systems in sync, 452 schema design, 93 slowly changing dimension (SCD), 476 data-intensive applications, 3 database triggers (see triggers) database-internal distributed transactions, 360, 364, 477 databases archival storage, 131 comparison of message brokers to, 443 dataflow through, 129 end-to-end argument for, 519-520 checking integrity, 531 inside-out, 504 (see also unbundling databases) output from batch workflows, 412 relation to event streams, 451-464 (see also changelogs) API support for change streams, 456, 506 change data capture, 454-457 event sourcing, 457-459 keeping systems in sync, 452-453 philosophy of immutable events, 459-464 unbundling, 499-515 composing data storage technologies, 499-504 designing applications around dataflow, 504-509 566 | Index observing derived state, 509-515 datacenters geographically distributed, 145, 164, 278, 493 multi-tenancy and shared resources, 284 network architecture, 276 network faults, 279 replication across multiple, 169 leaderless replication, 184 multi-leader replication, 168, 335 dataflow, 128-139, 504-509 correctness of dataflow systems, 525 differential, 504 message-passing, 136-139 reasoning about, 491 through databases, 129 through services, 131-136 dataflow engines, 421-423 comparison to stream processing, 464 directed acyclic graphs (DAG), 424 partitioning, approach to, 429 support for declarative queries, 427 Datalog (query language), 60-63 datatypes binary strings in XML and JSON, 114 conflict-free, 174 in Avro encodings, 122 in Thrift and Protocol Buffers, 121 numbers in XML and JSON, 114 Datomic (database) B-tree storage, 242 data model, 50, 57 Datalog query language, 60 excision (deleting data), 463 languages for transactions, 255 serial execution of transactions, 253 deadlocks detection, in two-phase commit (2PC), 364 in two-phase locking (2PL), 258 Debezium (change data capture), 455 declarative languages, 42, 554 Bloom, 504 CSS and XSL, 44 Cypher, 52 Datalog, 60 for batch processing, 427 recursive SQL queries, 53 relational algebra and SQL, 42 SPARQL, 59 delays bounded network delays, 285 bounded process pauses, 298 unbounded network delays, 282 unbounded process pauses, 296 deleting data, 463 denormalization (data representation), 34, 554 costs, 39 in derived data systems, 386 materialized views, 101 updating derived data, 228, 231, 490 versus normalization, 462 derived data, 386, 439, 554 from change data capture, 454 in event sourcing, 458-458 maintaining derived state through logs, 452-457, 459-463 observing, by subscribing to streams, 512 outputs of batch and stream processing, 495 through application code, 505 versus distributed transactions, 492 deterministic operations, 255, 274, 554 accidental nondeterminism, 423 and fault tolerance, 423, 426 and idempotence, 478, 492 computing derived data, 495, 526, 531 in state machine replication, 349, 452, 458 joins, 476 DevOps, 394 differential dataflow, 504 dimension tables, 94 dimensional modeling (see star schemas) directed acyclic graphs (DAGs), 424 dirty reads (transaction isolation), 234 dirty writes (transaction isolation), 235 discrimination, 534 disks (see hard disks) distributed actor frameworks, 138 distributed filesystems, 398-399 decoupling from query engines, 417 indiscriminately dumping data into, 415 use by MapReduce, 402 distributed systems, 273-312, 554 Byzantine faults, 304-306 cloud versus supercomputing, 275 detecting network faults, 280 faults and partial failures, 274-277 formalization of consensus, 365 impossibility results, 338, 353 issues with failover, 157 limitations of distributed transactions, 363 multi-datacenter, 169, 335 network problems, 277-286 quorums, relying on, 301 reasons for using, 145, 151 synchronized clocks, relying on, 291-295 system models, 306-310 use of clocks and time, 287 distributed transactions (see transactions) Django (web framework), 232 DNS (Domain Name System), 216, 372 Docker (container manager), 506 document data model, 30-42 comparison to relational model, 38-42 document references, 38, 403 document-oriented databases, 31 many-to-many relationships and joins, 36 multi-object transactions, need for, 231 versus relational model convergence of models, 41 data locality, 41 document-partitioned indexes, 206, 217, 411 domain-driven design (DDD), 457 DRBD (Distributed Replicated Block Device), 153 drift (clocks), 289 Drill (query engine), 93 Druid (database), 461 Dryad (dataflow engine), 421 dual writes, problems with, 452, 507 duplicates, suppression of, 517 (see also idempotence) using a unique ID, 518, 522 durability (transactions), 226, 554 duration (time), 287 measurement with monotonic clocks, 288 dynamic partitioning, 212 dynamically typed languages analogy to schema-on-read, 40 code generation and, 127 Dynamo-style databases (see leaderless replica‐ tion) E edges (in graphs), 49, 403 property graph model, 50 edit distance (full-text search), 88 effectively-once semantics, 476, 516 Index | 567 (see also exactly-once semantics) preservation of integrity, 525 elastic systems, 17 Elasticsearch (search server) document-partitioned indexes, 207 partition rebalancing, 211 percolator (stream search), 467 usage example, 4 use of Lucene, 79 ElephantDB (database), 413 Elm (programming language), 504, 512 encodings (data formats), 111-128 Avro, 122-127 binary variants of JSON and XML, 115 compatibility, 112 calling services, 136 using databases, 129-131 using message-passing, 138 defined, 113 JSON, XML, and CSV, 114 language-specific formats, 113 merits of schemas, 127 representations of data, 112 Thrift and Protocol Buffers, 117-121 end-to-end argument, 277, 519-520 checking integrity, 531 publish/subscribe streams, 512 enrichment (stream), 473 Enterprise JavaBeans (EJB), 134 entities (see vertices) epoch (consensus algorithms), 368 epoch (Unix timestamps), 288 equi-joins, 403 erasure coding (error correction), 398 Erlang OTP (actor framework), 139 error handling for network faults, 280 in transactions, 231 error-correcting codes, 277, 398 Esper (CEP engine), 466 etcd (coordination service), 370-373 linearizable operations, 333 locks and leader election, 330 quorum reads, 351 service discovery, 372 use of Raft algorithm, 349, 353 Ethereum (blockchain), 532 Ethernet (networks), 276, 278, 285 packet checksums, 306, 519 568 | Index Etherpad (collaborative editor), 170 ethics, 533-543 code of ethics and professional practice, 533 legislation and self-regulation, 542 predictive analytics, 533-536 amplifying bias, 534 feedback loops, 536 privacy and tracking, 536-543 consent and freedom of choice, 538 data as assets and power, 540 meaning of privacy, 539 surveillance, 537 respect, dignity, and agency, 543, 544 unintended consequences, 533, 536 ETL (extract-transform-load), 92, 405, 452, 554 use of Hadoop for, 416 event sourcing, 457-459 commands and events, 459 comparison to change data capture, 457 comparison to lambda architecture, 497 deriving current state from event log, 458 immutability and auditability, 459, 531 large, reliable data systems, 519, 526 Event Store (database), 458 event streams (see streams) events, 440 deciding on total order of, 493 deriving views from event log, 461 difference to commands, 459 event time versus processing time, 469, 477, 498 immutable, advantages of, 460, 531 ordering to capture causality, 493 reads as, 513 stragglers, 470, 498 timestamp of, in stream processing, 471 EventSource (browser API), 512 eventual consistency, 152, 162, 308, 322 (see also conflicts) and perpetual inconsistency, 525 evolvability, 21, 111 calling services, 136 graph-structured data, 52 of databases, 40, 129-131, 461, 497 of message-passing, 138 reprocessing data, 496, 498 schema evolution in Avro, 123 schema evolution in Thrift and Protocol Buffers, 120 schema-on-read, 39, 111, 128 exactly-once semantics, 360, 476, 516 parity with batch processors, 498 preservation of integrity, 525 exclusive mode (locks), 258 eXtended Architecture transactions (see XA transactions) extract-transform-load (see ETL) F Facebook Presto (query engine), 93 React, Flux, and Redux (user interface libra‐ ries), 512 social graphs, 49 Wormhole (change data capture), 455 fact tables, 93 failover, 157, 554 (see also leader-based replication) in leaderless replication, absence of, 178 leader election, 301, 348, 352 potential problems, 157 failures amplification by distributed transactions, 364, 495 failure detection, 280 automatic rebalancing causing cascading failures, 214 perfect failure detectors, 359 timeouts and unbounded delays, 282, 284 using ZooKeeper, 371 faults versus, 7 partial failures in distributed systems, 275-277, 310 fan-out (messaging systems), 11, 445 fault tolerance, 6-10, 555 abstractions for, 321 formalization in consensus, 365-369 use of replication, 367 human fault tolerance, 414 in batch processing, 406, 414, 422, 425 in log-based systems, 520, 524-526 in stream processing, 476-479 atomic commit, 477 idempotence, 478 maintaining derived state, 495 microbatching and checkpointing, 477 rebuilding state after a failure, 478 of distributed transactions, 362-364 transaction atomicity, 223, 354-361 faults, 6 Byzantine faults, 304-306 failures versus, 7 handled by transactions, 221 handling in supercomputers and cloud computing, 275 hardware, 7 in batch processing versus distributed data‐ bases, 417 in distributed systems, 274-277 introducing deliberately, 7, 280 network faults, 279-281 asymmetric faults, 300 detecting, 280 tolerance of, in multi-leader replication, 169 software errors, 8 tolerating (see fault tolerance) federated databases, 501 fence (CPU instruction), 338 fencing (preventing split brain), 158, 302-304 generating fencing tokens, 349, 370 properties of fencing tokens, 308 stream processors writing to databases, 478, 517 Fibre Channel (networks), 398 field tags (Thrift and Protocol Buffers), 119-121 file descriptors (Unix), 395 financial data, 460 Firebase (database), 456 Flink (processing framework), 421-423 dataflow APIs, 427 fault tolerance, 422, 477, 479 Gelly API (graph processing), 425 integration of batch and stream processing, 495, 498 machine learning, 428 query optimizer, 427 stream processing, 466 flow control, 282, 441, 555 FLP result (on consensus), 353 FlumeJava (dataflow library), 403, 427 followers, 152, 555 (see also leader-based replication) foreign keys, 38, 403 forward compatibility, 112 forward decay (algorithm), 16 Index | 569 Fossil (version control system), 463 shunning (deleting data), 463 FoundationDB (database) serializable transactions, 261, 265, 364 fractal trees, 83 full table scans, 403 full-text search, 555 and fuzzy indexes, 88 building search indexes, 411 Lucene storage engine, 79 functional reactive programming (FRP), 504 functional requirements, 22 futures (asynchronous operations), 135 fuzzy search (see similarity search) G garbage collection immutability and, 463 process pauses for, 14, 296-299, 301 (see also process pauses) genome analysis, 63, 429 geographically distributed datacenters, 145, 164, 278, 493 geospatial indexes, 87 Giraph (graph processing), 425 Git (version control system), 174, 342, 463 GitHub, postmortems, 157, 158, 309 global indexes (see term-partitioned indexes) GlusterFS (distributed filesystem), 398 GNU Coreutils (Linux), 394 GoldenGate (change data capture), 161, 170, 455 (see also Oracle) Google Bigtable (database) data model (see Bigtable data model) partitioning scheme, 199, 202 storage layout, 78 Chubby (lock service), 370 Cloud Dataflow (stream processor), 466, 477, 498 (see also Beam) Cloud Pub/Sub (messaging), 444, 448 Docs (collaborative editor), 170 Dremel (query engine), 93, 96 FlumeJava (dataflow library), 403, 427 GFS (distributed file system), 398 gRPC (RPC framework), 135 MapReduce (batch processing), 390 570 | Index (see also MapReduce) building search indexes, 411 task preemption, 418 Pregel (graph processing), 425 Spanner (see Spanner) TrueTime (clock API), 294 gossip protocol, 216 government use of data, 541 GPS (Global Positioning System) use for clock synchronization, 287, 290, 294, 295 GraphChi (graph processing), 426 graphs, 555 as data models, 49-63 example of graph-structured data, 49 property graphs, 50 RDF and triple-stores, 55-59 versus the network model, 60 processing and analysis, 424-426 fault tolerance, 425 Pregel processing model, 425 query languages Cypher, 52 Datalog, 60-63 recursive SQL queries, 53 SPARQL, 59-59 Gremlin (graph query language), 50 grep (Unix tool), 392 GROUP BY clause (SQL), 406 grouping records in MapReduce, 406 handling skew, 407 H Hadoop (data infrastructure) comparison to distributed databases, 390 comparison to MPP databases, 414-418 comparison to Unix, 413-414, 499 diverse processing models in ecosystem, 417 HDFS distributed filesystem (see HDFS) higher-level tools, 403 join algorithms, 403-410 (see also MapReduce) MapReduce (see MapReduce) YARN (see YARN) happens-before relationship, 340 capturing, 187 concurrency and, 186 hard disks access patterns, 84 detecting corruption, 519, 530 faults in, 7, 227 sequential write throughput, 75, 450 hardware faults, 7 hash indexes, 72-75 broadcast hash joins, 409 partitioned hash joins, 409 hash partitioning, 203-205, 217 consistent hashing, 204 problems with hash mod N, 210 range queries, 204 suitable hash functions, 203 with fixed number of partitions, 210 HAWQ (database), 428 HBase (database) bug due to lack of fencing, 302 bulk loading, 413 column-family data model, 41, 99 dynamic partitioning, 212 key-range partitioning, 202 log-structured storage, 78 request routing, 216 size-tiered compaction, 79 use of HDFS, 417 use of ZooKeeper, 370 HDFS (Hadoop Distributed File System), 398-399 (see also distributed filesystems) checking data integrity, 530 decoupling from query engines, 417 indiscriminately dumping data into, 415 metadata about datasets, 410 NameNode, 398 use by Flink, 479 use by HBase, 212 use by MapReduce, 402 HdrHistogram (numerical library), 16 head (Unix tool), 392 head vertex (property graphs), 51 head-of-line blocking, 15 heap files (databases), 86 Helix (cluster manager), 216 heterogeneous distributed transactions, 360, 364 heuristic decisions (in 2PC), 363 Hibernate (object-relational mapper), 30 hierarchical model, 36 high availability (see fault tolerance) high-frequency trading, 290, 299 high-performance computing (HPC), 275 hinted handoff, 183 histograms, 16 Hive (query engine), 419, 427 for data warehouses, 93 HCatalog and metastore, 410 map-side joins, 409 query optimizer, 427 skewed joins, 408 workflows, 403 Hollerith machines, 390 hopping windows (stream processing), 472 (see also windows) horizontal scaling (see scaling out) HornetQ (messaging), 137, 444 distributed transaction support, 361 hot spots, 201 due to celebrities, 205 for time-series data, 203 in batch processing, 407 relieving, 205 hot standbys (see leader-based replication) HTTP, use in APIs (see services) human errors, 9, 279, 414 HyperDex (database), 88 HyperLogLog (algorithm), 466 I I/O operations, waiting for, 297 IBM DB2 (database) distributed transaction support, 361 recursive query support, 54 serializable isolation, 242, 257 XML and JSON support, 30, 42 electromechanical card-sorting machines, 390 IMS (database), 36 imperative query APIs, 46 InfoSphere Streams (CEP engine), 466 MQ (messaging), 444 distributed transaction support, 361 System R (database), 222 WebSphere (messaging), 137 idempotence, 134, 478, 555 by giving operations unique IDs, 518, 522 idempotent operations, 517 immutability advantages of, 460, 531 Index | 571 deriving state from event log, 459-464 for crash recovery, 75 in B-trees, 82, 242 in event sourcing, 457 inputs to Unix commands, 397 limitations of, 463 Impala (query engine) for data warehouses, 93 hash joins, 409 native code generation, 428 use of HDFS, 417 impedance mismatch, 29 imperative languages, 42 setting element styles (example), 45 in doubt (transaction status), 358 holding locks, 362 orphaned transactions, 363 in-memory databases, 88 durability, 227 serial transaction execution, 253 incidents cascading failures, 9 crashes due to leap seconds, 290 data corruption and financial losses due to concurrency bugs, 233 data corruption on hard disks, 227 data loss due to last-write-wins, 173, 292 data on disks unreadable, 309 deleted items reappearing, 174 disclosure of sensitive data due to primary key reuse, 157 errors in transaction serializability, 529 gigabit network interface with 1 Kb/s throughput, 311 network faults, 279 network interface dropping only inbound packets, 279 network partitions and whole-datacenter failures, 275 poor handling of network faults, 280 sending message to ex-partner, 494 sharks biting undersea cables, 279 split brain due to 1-minute packet delay, 158, 279 vibrations in server rack, 14 violation of uniqueness constraint, 529 indexes, 71, 555 and snapshot isolation, 241 as derived data, 386, 499-504 572 | Index B-trees, 79-83 building in batch processes, 411 clustered, 86 comparison of B-trees and LSM-trees, 83-85 concatenated, 87 covering (with included columns), 86 creating, 500 full-text search, 88 geospatial, 87 hash, 72-75 index-range locking, 260 multi-column, 87 partitioning and secondary indexes, 206-209, 217 secondary, 85 (see also secondary indexes) problems with dual writes, 452, 491 SSTables and LSM-trees, 76-79 updating when data changes, 452, 467 Industrial Revolution, 541 InfiniBand (networks), 285 InfiniteGraph (database), 50 InnoDB (storage engine) clustered index on primary key, 86 not preventing lost updates, 245 preventing write skew, 248, 257 serializable isolation, 257 snapshot isolation support, 239 inside-out databases, 504 (see also unbundling databases) integrating different data systems (see data integration) integrity, 524 coordination-avoiding data systems, 528 correctness of dataflow systems, 525 in consensus formalization, 365 integrity checks, 530 (see also auditing) end-to-end, 519, 531 use of snapshot isolation, 238 maintaining despite software bugs, 529 Interface Definition Language (IDL), 117, 122 intermediate state, materialization of, 420-423 internet services, systems for implementing, 275 invariants, 225 (see also constraints) inversion of control, 396 IP (Internet Protocol) unreliability of, 277 ISDN (Integrated Services Digital Network), 284 isolation (in transactions), 225, 228, 555 correctness and, 515 for single-object writes, 230 serializability, 251-266 actual serial execution, 252-256 serializable snapshot isolation (SSI), 261-266 two-phase locking (2PL), 257-261 violating, 228 weak isolation levels, 233-251 preventing lost updates, 242-246 read committed, 234-237 snapshot isolation, 237-242 iterative processing, 424-426 J Java Database Connectivity (JDBC) distributed transaction support, 361 network drivers, 128 Java Enterprise Edition (EE), 134, 356, 361 Java Message Service (JMS), 444 (see also messaging systems) comparison to log-based messaging, 448, 451 distributed transaction support, 361 message ordering, 446 Java Transaction API (JTA), 355, 361 Java Virtual Machine (JVM) bytecode generation, 428 garbage collection pauses, 296 process reuse in batch processors, 422 JavaScript in MapReduce querying, 46 setting element styles (example), 45 use in advanced queries, 48 Jena (RDF framework), 57 Jepsen (fault tolerance testing), 515 jitter (network delay), 284 joins, 555 by index lookup, 403 expressing as relational operators, 427 in relational and document databases, 34 MapReduce map-side joins, 408-410 broadcast hash joins, 409 merge joins, 410 partitioned hash joins, 409 MapReduce reduce-side joins, 403-408 handling skew, 407 sort-merge joins, 405 parallel execution of, 415 secondary indexes and, 85 stream joins, 472-476 stream-stream join, 473 stream-table join, 473 table-table join, 474 time-dependence of, 475 support in document databases, 42 JOTM (transaction coordinator), 356 JSON Avro schema representation, 122 binary variants, 115 for application data, issues with, 114 in relational databases, 30, 42 representing a résumé (example), 31 Juttle (query language), 504 K k-nearest neighbors, 429 Kafka (messaging), 137, 448 Kafka Connect (database integration), 457, 461 Kafka Streams (stream processor), 466, 467 fault tolerance, 479 leader-based replication, 153 log compaction, 456, 467 message offsets, 447, 478 request routing, 216 transaction support, 477 usage example, 4 Ketama (partitioning library), 213 key-value stores, 70 as batch process output, 412 hash indexes, 72-75 in-memory, 89 partitioning, 201-205 by hash of key, 203, 217 by key range, 202, 217 dynamic partitioning, 212 skew and hot spots, 205 Kryo (Java), 113 Kubernetes (cluster manager), 418, 506 L lambda architecture, 497 Lamport timestamps, 345 Index | 573 Large Hadron Collider (LHC), 64 last write wins (LWW), 173, 334 discarding concurrent writes, 186 problems with, 292 prone to lost updates, 246 late binding, 396 latency instability under two-phase locking, 259 network latency and resource utilization, 286 response time versus, 14 tail latency, 15, 207 leader-based replication, 152-161 (see also replication) failover, 157, 301 handling node outages, 156 implementation of replication logs change data capture, 454-457 (see also changelogs) statement-based, 158 trigger-based replication, 161 write-ahead log (WAL) shipping, 159 linearizability of operations, 333 locking and leader election, 330 log sequence number, 156, 449 read-scaling architecture, 161 relation to consensus, 367 setting up new followers, 155 synchronous versus asynchronous, 153-155 leaderless replication, 177-191 (see also replication) detecting concurrent writes, 184-191 capturing happens-before relationship, 187 happens-before relationship and concur‐ rency, 186 last write wins, 186 merging concurrently written values, 190 version vectors, 191 multi-datacenter, 184 quorums, 179-182 consistency limitations, 181-183, 334 sloppy quorums and hinted handoff, 183 read repair and anti-entropy, 178 leap seconds, 8, 290 in time-of-day clocks, 288 leases, 295 implementation with ZooKeeper, 370 574 | Index need for fencing, 302 ledgers, 460 distributed ledger technologies, 532 legacy systems, maintenance of, 18 less (Unix tool), 397 LevelDB (storage engine), 78 leveled compaction, 79 Levenshtein automata, 88 limping (partial failure), 311 linearizability, 324-338, 555 cost of, 335-338 CAP theorem, 336 memory on multi-core CPUs, 338 definition, 325-329 implementing with total order broadcast, 350 in ZooKeeper, 370 of derived data systems, 492, 524 avoiding coordination, 527 of different replication methods, 332-335 using quorums, 334 relying on, 330-332 constraints and uniqueness, 330 cross-channel timing dependencies, 331 locking and leader election, 330 stronger than causal consistency, 342 using to implement total order broadcast, 351 versus serializability, 329 LinkedIn Azkaban (workflow scheduler), 402 Databus (change data capture), 161, 455 Espresso (database), 31, 126, 130, 153, 216 Helix (cluster manager) (see Helix) profile (example), 30 reference to company entity (example), 34 Rest.li (RPC framework), 135 Voldemort (database) (see Voldemort) Linux, leap second bug, 8, 290 liveness properties, 308 LMDB (storage engine), 82, 242 load approaches to coping with, 17 describing, 11 load testing, 16 load balancing (messaging), 444 local indexes (see document-partitioned indexes) locality (data access), 32, 41, 555 in batch processing, 400, 405, 421 in stateful clients, 170, 511 in stream processing, 474, 478, 508, 522 location transparency, 134 in the actor model, 138 locks, 556 deadlock, 258 distributed locking, 301-304, 330 fencing tokens, 303 implementation with ZooKeeper, 370 relation to consensus, 374 for transaction isolation in snapshot isolation, 239 in two-phase locking (2PL), 257-261 making operations atomic, 243 performance, 258 preventing dirty writes, 236 preventing phantoms with index-range locks, 260, 265 read locks (shared mode), 236, 258 shared mode and exclusive mode, 258 in two-phase commit (2PC) deadlock detection, 364 in-doubt transactions holding locks, 362 materializing conflicts with, 251 preventing lost updates by explicit locking, 244 log sequence number, 156, 449 logic programming languages, 504 logical clocks, 293, 343, 494 for read-after-write consistency, 164 logical logs, 160 logs (data structure), 71, 556 advantages of immutability, 460 compaction, 73, 79, 456, 460 for stream operator state, 479 creating using total order broadcast, 349 implementing uniqueness constraints, 522 log-based messaging, 446-451 comparison to traditional messaging, 448, 451 consumer offsets, 449 disk space usage, 450 replaying old messages, 451, 496, 498 slow consumers, 450 using logs for message storage, 447 log-structured storage, 71-79 log-structured merge tree (see LSMtrees) replication, 152, 158-161 change data capture, 454-457 (see also changelogs) coordination with snapshot, 156 logical (row-based) replication, 160 statement-based replication, 158 trigger-based replication, 161 write-ahead log (WAL) shipping, 159 scalability limits, 493 loose coupling, 396, 419, 502 lost updates (see updates) LSM-trees (indexes), 78-79 comparison to B-trees, 83-85 Lucene (storage engine), 79 building indexes in batch processes, 411 similarity search, 88 Luigi (workflow scheduler), 402 LWW (see last write wins) M machine learning ethical considerations, 534 (see also ethics) iterative processing, 424 models derived from training data, 505 statistical and numerical algorithms, 428 MADlib (machine learning toolkit), 428 magic scaling sauce, 18 Mahout (machine learning toolkit), 428 maintainability, 18-22, 489 defined, 23 design principles for software systems, 19 evolvability (see evolvability) operability, 19 simplicity and managing complexity, 20 many-to-many relationships in document model versus relational model, 39 modeling as graphs, 49 many-to-one and many-to-many relationships, 33-36 many-to-one relationships, 34 MapReduce (batch processing), 390, 399-400 accessing external services within job, 404, 412 comparison to distributed databases designing for frequent faults, 417 diversity of processing models, 416 diversity of storage, 415 Index | 575 comparison to stream processing, 464 comparison to Unix, 413-414 disadvantages and limitations of, 419 fault tolerance, 406, 414, 422 higher-level tools, 403, 426 implementation in Hadoop, 400-403 the shuffle, 402 implementation in MongoDB, 46-48 machine learning, 428 map-side processing, 408-410 broadcast hash joins, 409 merge joins, 410 partitioned hash joins, 409 mapper and reducer functions, 399 materialization of intermediate state, 419-423 output of batch workflows, 411-413 building search indexes, 411 key-value stores, 412 reduce-side processing, 403-408 analysis of user activity events (exam‐ ple), 404 grouping records by same key, 406 handling skew, 407 sort-merge joins, 405 workflows, 402 marshalling (see encoding) massively parallel processing (MPP), 216 comparison to composing storage technolo‐ gies, 502 comparison to Hadoop, 414-418, 428 master-master replication (see multi-leader replication) master-slave replication (see leader-based repli‐ cation) materialization, 556 aggregate values, 101 conflicts, 251 intermediate state (batch processing), 420-423 materialized views, 101 as derived data, 386, 499-504 maintaining, using stream processing, 467, 475 Maven (Java build tool), 428 Maxwell (change data capture), 455 mean, 14 media monitoring, 467 median, 14 576 | Index meeting room booking (example), 249, 259, 521 membership services, 372 Memcached (caching server), 4, 89 memory in-memory databases, 88 durability, 227 serial transaction execution, 253 in-memory representation of data, 112 random bit-flips in, 529 use by indexes, 72, 77 memory barrier (CPU instruction), 338 MemSQL (database) in-memory storage, 89 read committed isolation, 236 memtable (in LSM-trees), 78 Mercurial (version control system), 463 merge joins, MapReduce map-side, 410 mergeable persistent data structures, 174 merging sorted files, 76, 402, 405 Merkle trees, 532 Mesos (cluster manager), 418, 506 message brokers (see messaging systems) message-passing, 136-139 advantages over direct RPC, 137 distributed actor frameworks, 138 evolvability, 138 MessagePack (encoding format), 116 messages exactly-once semantics, 360, 476 loss of, 442 using total order broadcast, 348 messaging systems, 440-451 (see also streams) backpressure, buffering, or dropping mes‐ sages, 441 brokerless messaging, 442 event logs, 446-451 comparison to traditional messaging, 448, 451 consumer offsets, 449 replaying old messages, 451, 496, 498 slow consumers, 450 message brokers, 443-446 acknowledgements and redelivery, 445 comparison to event logs, 448, 451 multiple consumers of same topic, 444 reliability, 442 uniqueness in log-based messaging, 522 Meteor (web framework), 456 microbatching, 477, 495 microservices, 132 (see also services) causal dependencies across services, 493 loose coupling, 502 relation to batch/stream processors, 389, 508 Microsoft Azure Service Bus (messaging), 444 Azure Storage, 155, 398 Azure Stream Analytics, 466 DCOM (Distributed Component Object Model), 134 MSDTC (transaction coordinator), 356 Orleans (see Orleans) SQL Server (see SQL Server) migrating (rewriting) data, 40, 130, 461, 497 modulus operator (%), 210 MongoDB (database) aggregation pipeline, 48 atomic operations, 243 BSON, 41 document data model, 31 hash partitioning (sharding), 203-204 key-range partitioning, 202 lack of join support, 34, 42 leader-based replication, 153 MapReduce support, 46, 400 oplog parsing, 455, 456 partition splitting, 212 request routing, 216 secondary indexes, 207 Mongoriver (change data capture), 455 monitoring, 10, 19 monotonic clocks, 288 monotonic reads, 164 MPP (see massively parallel processing) MSMQ (messaging), 361 multi-column indexes, 87 multi-leader replication, 168-177 (see also replication) handling write conflicts, 171 conflict avoidance, 172 converging toward a consistent state, 172 custom conflict resolution logic, 173 determining what is a conflict, 174 linearizability, lack of, 333 replication topologies, 175-177 use cases, 168 clients with offline operation, 170 collaborative editing, 170 multi-datacenter replication, 168, 335 multi-object transactions, 228 need for, 231 Multi-Paxos (total order broadcast), 367 multi-table index cluster tables (Oracle), 41 multi-tenancy, 284 multi-version concurrency control (MVCC), 239, 266 detecting stale MVCC reads, 263 indexes and snapshot isolation, 241 mutual exclusion, 261 (see also locks) MySQL (database) binlog coordinates, 156 binlog parsing for change data capture, 455 circular replication topology, 175 consistent snapshots, 156 distributed transaction support, 361 InnoDB storage engine (see InnoDB) JSON support, 30, 42 leader-based replication, 153 performance of XA transactions, 360 row-based replication, 160 schema changes in, 40 snapshot isolation support, 242 (see also InnoDB) statement-based replication, 159 Tungsten Replicator (multi-leader replica‐ tion), 170 conflict detection, 177 N nanomsg (messaging library), 442 Narayana (transaction coordinator), 356 NATS (messaging), 137 near-real-time (nearline) processing, 390 (see also stream processing) Neo4j (database) Cypher query language, 52 graph data model, 50 Nephele (dataflow engine), 421 netcat (Unix tool), 397 Netflix Chaos Monkey, 7, 280 Network Attached Storage (NAS), 146, 398 network model, 36 Index | 577 graph databases versus, 60 imperative query APIs, 46 Network Time Protocol (see NTP) networks congestion and queueing, 282 datacenter network topologies, 276 faults (see faults) linearizability and network delays, 338 network partitions, 279, 337 timeouts and unbounded delays, 281 next-key locking, 260 nodes (in graphs) (see vertices) nodes (processes), 556 handling outages in leader-based replica‐ tion, 156 system models for failure, 307 noisy neighbors, 284 nonblocking atomic commit, 359 nondeterministic operations accidental nondeterminism, 423 partial failures in distributed systems, 275 nonfunctional requirements, 22 nonrepeatable reads, 238 (see also read skew) normalization (data representation), 33, 556 executing joins, 39, 42, 403 foreign key references, 231 in systems of record, 386 versus denormalization, 462 NoSQL, 29, 499 transactions and, 223 Notation3 (N3), 56 npm (package manager), 428 NTP (Network Time Protocol), 287 accuracy, 289, 293 adjustments to monotonic clocks, 289 multiple server addresses, 306 numbers, in XML and JSON encodings, 114 O object-relational mapping (ORM) frameworks, 30 error handling and aborted transactions, 232 unsafe read-modify-write cycle code, 244 object-relational mismatch, 29 observer pattern, 506 offline systems, 390 (see also batch processing) 578 | Index stateful, offline-capable clients, 170, 511 offline-first applications, 511 offsets consumer offsets in partitioned logs, 449 messages in partitioned logs, 447 OLAP (online analytic processing), 91, 556 data cubes, 102 OLTP (online transaction processing), 90, 556 analytics queries versus, 411 workload characteristics, 253 one-to-many relationships, 30 JSON representation, 32 online systems, 389 (see also services) Oozie (workflow scheduler), 402 OpenAPI (service definition format), 133 OpenStack Nova (cloud infrastructure) use of ZooKeeper, 370 Swift (object storage), 398 operability, 19 operating systems versus databases, 499 operation identifiers, 518, 522 operational transformation, 174 operators, 421 flow of data between, 424 in stream processing, 464 optimistic concurrency control, 261 Oracle (database) distributed transaction support, 361 GoldenGate (change data capture), 161, 170, 455 lack of serializability, 226 leader-based replication, 153 multi-table index cluster tables, 41 not preventing write skew, 248 partitioned indexes, 209 PL/SQL language, 255 preventing lost updates, 245 read committed isolation, 236 Real Application Clusters (RAC), 330 recursive query support, 54 snapshot isolation support, 239, 242 TimesTen (in-memory database), 89 WAL-based replication, 160 XML support, 30 ordering, 339-352 by sequence numbers, 343-348 causal ordering, 339-343 partial order, 341 limits of total ordering, 493 total order broadcast, 348-352 Orleans (actor framework), 139 outliers (response time), 14 Oz (programming language), 504 P package managers, 428, 505 packet switching, 285 packets corruption of, 306 sending via UDP, 442 PageRank (algorithm), 49, 424 paging (see virtual memory) ParAccel (database), 93 parallel databases (see massively parallel pro‐ cessing) parallel execution of graph analysis algorithms, 426 queries in MPP databases, 216 Parquet (data format), 96, 131 (see also column-oriented storage) use in Hadoop, 414 partial failures, 275, 310 limping, 311 partial order, 341 partitioning, 199-218, 556 and replication, 200 in batch processing, 429 multi-partition operations, 514 enforcing constraints, 522 secondary index maintenance, 495 of key-value data, 201-205 by key range, 202 skew and hot spots, 205 rebalancing partitions, 209-214 automatic or manual rebalancing, 213 problems with hash mod N, 210 using dynamic partitioning, 212 using fixed number of partitions, 210 using N partitions per node, 212 replication and, 147 request routing, 214-216 secondary indexes, 206-209 document-based partitioning, 206 term-based partitioning, 208 serial execution of transactions and, 255 Paxos (consensus algorithm), 366 ballot number, 368 Multi-Paxos (total order broadcast), 367 percentiles, 14, 556 calculating efficiently, 16 importance of high percentiles, 16 use in service level agreements (SLAs), 15 Percona XtraBackup (MySQL tool), 156 performance describing, 13 of distributed transactions, 360 of in-memory databases, 89 of linearizability, 338 of multi-leader replication, 169 perpetual inconsistency, 525 pessimistic concurrency control, 261 phantoms (transaction isolation), 250 materializing conflicts, 251 preventing, in serializability, 259 physical clocks (see clocks) pickle (Python), 113 Pig (dataflow language), 419, 427 replicated joins, 409 skewed joins, 407 workflows, 403 Pinball (workflow scheduler), 402 pipelined execution, 423 in Unix, 394 point in time, 287 polyglot persistence, 29 polystores, 501 PostgreSQL (database) BDR (multi-leader replication), 170 causal ordering of writes, 177 Bottled Water (change data capture), 455 Bucardo (trigger-based replication), 161, 173 distributed transaction support, 361 foreign data wrappers, 501 full text search support, 490 leader-based replication, 153 log sequence number, 156 MVCC implementation, 239, 241 PL/pgSQL language, 255 PostGIS geospatial indexes, 87 preventing lost updates, 245 preventing write skew, 248, 261 read committed isolation, 236 recursive query support, 54 representing graphs, 51 Index | 579 serializable snapshot isolation (SSI), 261 snapshot isolation support, 239, 242 WAL-based replication, 160 XML and JSON support, 30, 42 pre-splitting, 212 Precision Time Protocol (PTP), 290 predicate locks, 259 predictive analytics, 533-536 amplifying bias, 534 ethics of (see ethics) feedback loops, 536 preemption of datacenter resources, 418 of threads, 298 Pregel processing model, 425 primary keys, 85, 556 compound primary key (Cassandra), 204 primary-secondary replication (see leaderbased replication) privacy, 536-543 consent and freedom of choice, 538 data as assets and power, 540 deleting data, 463 ethical considerations (see ethics) legislation and self-regulation, 542 meaning of, 539 surveillance, 537 tracking behavioral data, 536 probabilistic algorithms, 16, 466 process pauses, 295-299 processing time (of events), 469 producers (message streams), 440 programming languages dataflow languages, 504 for stored procedures, 255 functional reactive programming (FRP), 504 logic programming, 504 Prolog (language), 61 (see also Datalog) promises (asynchronous operations), 135 property graphs, 50 Cypher query language, 52 Protocol Buffers (data format), 117-121 field tags and schema evolution, 120 provenance of data, 531 publish/subscribe model, 441 publishers (message streams), 440 punch card tabulating machines, 390 580 | Index pure functions, 48 putting computation near data, 400 Q Qpid (messaging), 444 quality of service (QoS), 285 Quantcast File System (distributed filesystem), 398 query languages, 42-48 aggregation pipeline, 48 CSS and XSL, 44 Cypher, 52 Datalog, 60 Juttle, 504 MapReduce querying, 46-48 recursive SQL queries, 53 relational algebra and SQL, 42 SPARQL, 59 query optimizers, 37, 427 queueing delays (networks), 282 head-of-line blocking, 15 latency and response time, 14 queues (messaging), 137 quorums, 179-182, 556 for leaderless replication, 179 in consensus algorithms, 368 limitations of consistency, 181-183, 334 making decisions in distributed systems, 301 monitoring staleness, 182 multi-datacenter replication, 184 relying on durability, 309 sloppy quorums and hinted handoff, 183 R R-trees (indexes), 87 RabbitMQ (messaging), 137, 444 leader-based replication, 153 race conditions, 225 (see also concurrency) avoiding with linearizability, 331 caused by dual writes, 452 dirty writes, 235 in counter increments, 235 lost updates, 242-246 preventing with event logs, 462, 507 preventing with serializable isolation, 252 write skew, 246-251 Raft (consensus algorithm), 366 sensitivity to network problems, 369 term number, 368 use in etcd, 353 RAID (Redundant Array of Independent Disks), 7, 398 railways, schema migration on, 496 RAMCloud (in-memory storage), 89 ranking algorithms, 424 RDF (Resource Description Framework), 57 querying with SPARQL, 59 RDMA (Remote Direct Memory Access), 276 read committed isolation level, 234-237 implementing, 236 multi-version concurrency control (MVCC), 239 no dirty reads, 234 no dirty writes, 235 read path (derived data), 509 read repair (leaderless replication), 178 for linearizability, 335 read replicas (see leader-based replication) read skew (transaction isolation), 238, 266 as violation of causality, 340 read-after-write consistency, 163, 524 cross-device, 164 read-modify-write cycle, 243 read-scaling architecture, 161 reads as events, 513 real-time collaborative editing, 170 near-real-time processing, 390 (see also stream processing) publish/subscribe dataflow, 513 response time guarantees, 298 time-of-day clocks, 288 rebalancing partitions, 209-214, 556 (see also partitioning) automatic or manual rebalancing, 213 dynamic partitioning, 212 fixed number of partitions, 210 fixed number of partitions per node, 212 problems with hash mod N, 210 recency guarantee, 324 recommendation engines batch process outputs, 412 batch workflows, 403, 420 iterative processing, 424 statistical and numerical algorithms, 428 records, 399 events in stream processing, 440 recursive common table expressions (SQL), 54 redelivery (messaging), 445 Redis (database) atomic operations, 243 durability, 89 Lua scripting, 255 single-threaded execution, 253 usage example, 4 redundancy hardware components, 7 of derived data, 386 (see also derived data) Reed–Solomon codes (error correction), 398 refactoring, 22 (see also evolvability) regions (partitioning), 199 register (data structure), 325 relational data model, 28-42 comparison to document model, 38-42 graph queries in SQL, 53 in-memory databases with, 89 many-to-one and many-to-many relation‐ ships, 33 multi-object transactions, need for, 231 NoSQL as alternative to, 29 object-relational mismatch, 29 relational algebra and SQL, 42 versus document model convergence of models, 41 data locality, 41 relational databases eventual consistency, 162 history, 28 leader-based replication, 153 logical logs, 160 philosophy compared to Unix, 499, 501 schema changes, 40, 111, 130 statement-based replication, 158 use of B-tree indexes, 80 relationships (see edges) reliability, 6-10, 489 building a reliable system from unreliable components, 276 defined, 6, 22 hardware faults, 7 human errors, 9 importance of, 10 of messaging systems, 442 Index | 581 software errors, 8 Remote Method Invocation (Java RMI), 134 remote procedure calls (RPCs), 134-136 (see also services) based on futures, 135 data encoding and evolution, 136 issues with, 134 using Avro, 126, 135 using Thrift, 135 versus message brokers, 137 repeatable reads (transaction isolation), 242 replicas, 152 replication, 151-193, 556 and durability, 227 chain replication, 155 conflict resolution and, 246 consistency properties, 161-167 consistent prefix reads, 165 monotonic reads, 164 reading your own writes, 162 in distributed filesystems, 398 leaderless, 177-191 detecting concurrent writes, 184-191 limitations of quorum consistency, 181-183, 334 sloppy quorums and hinted handoff, 183 monitoring staleness, 182 multi-leader, 168-177 across multiple datacenters, 168, 335 handling write conflicts, 171-175 replication topologies, 175-177 partitioning and, 147, 200 reasons for using, 145, 151 single-leader, 152-161 failover, 157 implementation of replication logs, 158-161 relation to consensus, 367 setting up new followers, 155 synchronous versus asynchronous, 153-155 state machine replication, 349, 452 using erasure coding, 398 with heterogeneous data systems, 453 replication logs (see logs) reprocessing data, 496, 498 (see also evolvability) from log-based messaging, 451 request routing, 214-216 582 | Index approaches to, 214 parallel query execution, 216 resilient systems, 6 (see also fault tolerance) response time as performance metric for services, 13, 389 guarantees on, 298 latency versus, 14 mean and percentiles, 14 user experience, 15 responsibility and accountability, 535 REST (Representational State Transfer), 133 (see also services) RethinkDB (database) document data model, 31 dynamic partitioning, 212 join support, 34, 42 key-range partitioning, 202 leader-based replication, 153 subscribing to changes, 456 Riak (database) Bitcask storage engine, 72 CRDTs, 174, 191 dotted version vectors, 191 gossip protocol, 216 hash partitioning, 203-204, 211 last-write-wins conflict resolution, 186 leaderless replication, 177 LevelDB storage engine, 78 linearizability, lack of, 335 multi-datacenter support, 184 preventing lost updates across replicas, 246 rebalancing, 213 search feature, 209 secondary indexes, 207 siblings (concurrently written values), 190 sloppy quorums, 184 ring buffers, 450 Ripple (cryptocurrency), 532 rockets, 10, 36, 305 RocksDB (storage engine), 78 leveled compaction, 79 rollbacks (transactions), 222 rolling upgrades, 8, 112 routing (see request routing) row-oriented storage, 96 row-based replication, 160 rowhammer (memory corruption), 529 RPCs (see remote procedure calls) Rubygems (package manager), 428 rules (Datalog), 61 S safety and liveness properties, 308 in consensus algorithms, 366 in transactions, 222 sagas (see compensating transactions) Samza (stream processor), 466, 467 fault tolerance, 479 streaming SQL support, 466 sandboxes, 9 SAP HANA (database), 93 scalability, 10-18, 489 approaches for coping with load, 17 defined, 22 describing load, 11 describing performance, 13 partitioning and, 199 replication and, 161 scaling up versus scaling out, 146 scaling out, 17, 146 (see also shared-nothing architecture) scaling up, 17, 146 scatter/gather approach, querying partitioned databases, 207 SCD (slowly changing dimension), 476 schema-on-read, 39 comparison to evolvable schema, 128 in distributed filesystems, 415 schema-on-write, 39 schemaless databases (see schema-on-read) schemas, 557 Avro, 122-127 reader determining writer’s schema, 125 schema evolution, 123 dynamically generated, 126 evolution of, 496 affecting application code, 111 compatibility checking, 126 in databases, 129-131 in message-passing, 138 in service calls, 136 flexibility in document model, 39 for analytics, 93-95 for JSON and XML, 115 merits of, 127 schema migration on railways, 496 Thrift and Protocol Buffers, 117-121 schema evolution, 120 traditional approach to design, fallacy in, 462 searches building search indexes in batch processes, 411 k-nearest neighbors, 429 on streams, 467 partitioned secondary indexes, 206 secondaries (see leader-based replication) secondary indexes, 85, 557 partitioning, 206-209, 217 document-partitioned, 206 index maintenance, 495 term-partitioned, 208 problems with dual writes, 452, 491 updating, transaction isolation and, 231 secondary sorts, 405 sed (Unix tool), 392 self-describing files, 127 self-joins, 480 self-validating systems, 530 semantic web, 57 semi-synchronous replication, 154 sequence number ordering, 343-348 generators, 294, 344 insufficiency for enforcing constraints, 347 Lamport timestamps, 345 use of timestamps, 291, 295, 345 sequential consistency, 351 serializability, 225, 233, 251-266, 557 linearizability versus, 329 pessimistic versus optimistic concurrency control, 261 serial execution, 252-256 partitioning, 255 using stored procedures, 253, 349 serializable snapshot isolation (SSI), 261-266 detecting stale MVCC reads, 263 detecting writes that affect prior reads, 264 distributed execution, 265, 364 performance of SSI, 265 preventing write skew, 262-265 two-phase locking (2PL), 257-261 index-range locks, 260 performance, 258 Serializable (Java), 113 Index | 583 serialization, 113 (see also encoding) service discovery, 135, 214, 372 using DNS, 216, 372 service level agreements (SLAs), 15 service-oriented architecture (SOA), 132 (see also services) services, 131-136 microservices, 132 causal dependencies across services, 493 loose coupling, 502 relation to batch/stream processors, 389, 508 remote procedure calls (RPCs), 134-136 issues with, 134 similarity to databases, 132 web services, 132, 135 session windows (stream processing), 472 (see also windows) sessionization, 407 sharding (see partitioning) shared mode (locks), 258 shared-disk architecture, 146, 398 shared-memory architecture, 146 shared-nothing architecture, 17, 146-147, 557 (see also replication) distributed filesystems, 398 (see also distributed filesystems) partitioning, 199 use of network, 277 sharks biting undersea cables, 279 counting (example), 46-48 finding (example), 42 website about (example), 44 shredding (in relational model), 38 siblings (concurrent values), 190, 246 (see also conflicts) similarity search edit distance, 88 genome data, 63 k-nearest neighbors, 429 single-leader replication (see leader-based rep‐ lication) single-threaded execution, 243, 252 in batch processing, 406, 421, 426 in stream processing, 448, 463, 522 size-tiered compaction, 79 skew, 557 584 | Index clock skew, 291-294, 334 in transaction isolation read skew, 238, 266 write skew, 246-251, 262-265 (see also write skew) meanings of, 238 unbalanced workload, 201 compensating for, 205 due to celebrities, 205 for time-series data, 203 in batch processing, 407 slaves (see leader-based replication) sliding windows (stream processing), 472 (see also windows) sloppy quorums, 183 (see also quorums) lack of linearizability, 334 slowly changing dimension (data warehouses), 476 smearing (leap seconds adjustments), 290 snapshots (databases) causal consistency, 340 computing derived data, 500 in change data capture, 455 serializable snapshot isolation (SSI), 261-266, 329 setting up a new replica, 156 snapshot isolation and repeatable read, 237-242 implementing with MVCC, 239 indexes and MVCC, 241 visibility rules, 240 synchronized clocks for global snapshots, 294 snowflake schemas, 95 SOAP, 133 (see also services) evolvability, 136 software bugs, 8 maintaining integrity, 529 solid state drives (SSDs) access patterns, 84 detecting corruption, 519, 530 faults in, 227 sequential write throughput, 75 Solr (search server) building indexes in batch processes, 411 document-partitioned indexes, 207 request routing, 216 usage example, 4 use of Lucene, 79 sort (Unix tool), 392, 394, 395 sort-merge joins (MapReduce), 405 Sorted String Tables (see SSTables) sorting sort order in column storage, 99 source of truth (see systems of record) Spanner (database) data locality, 41 snapshot isolation using clocks, 295 TrueTime API, 294 Spark (processing framework), 421-423 bytecode generation, 428 dataflow APIs, 427 fault tolerance, 422 for data warehouses, 93 GraphX API (graph processing), 425 machine learning, 428 query optimizer, 427 Spark Streaming, 466 microbatching, 477 stream processing on top of batch process‐ ing, 495 SPARQL (query language), 59 spatial algorithms, 429 split brain, 158, 557 in consensus algorithms, 352, 367 preventing, 322, 333 using fencing tokens to avoid, 302-304 spreadsheets, dataflow programming capabili‐ ties, 504 SQL (Structured Query Language), 21, 28, 43 advantages and limitations of, 416 distributed query execution, 48 graph queries in, 53 isolation levels standard, issues with, 242 query execution on Hadoop, 416 résumé (example), 30 SQL injection vulnerability, 305 SQL on Hadoop, 93 statement-based replication, 158 stored procedures, 255 SQL Server (database) data warehousing support, 93 distributed transaction support, 361 leader-based replication, 153 preventing lost updates, 245 preventing write skew, 248, 257 read committed isolation, 236 recursive query support, 54 serializable isolation, 257 snapshot isolation support, 239 T-SQL language, 255 XML support, 30 SQLstream (stream analytics), 466 SSDs (see solid state drives) SSTables (storage format), 76-79 advantages over hash indexes, 76 concatenated index, 204 constructing and maintaining, 78 making LSM-Tree from, 78 staleness (old data), 162 cross-channel timing dependencies, 331 in leaderless databases, 178 in multi-version concurrency control, 263 monitoring for, 182 of client state, 512 versus linearizability, 324 versus timeliness, 524 standbys (see leader-based replication) star replication topologies, 175 star schemas, 93-95 similarity to event sourcing, 458 Star Wars analogy (event time versus process‐ ing time), 469 state derived from log of immutable events, 459 deriving current state from the event log, 458 interplay between state changes and appli‐ cation code, 507 maintaining derived state, 495 maintenance by stream processor in streamstream joins, 473 observing derived state, 509-515 rebuilding after stream processor failure, 478 separation of application code and, 505 state machine replication, 349, 452 statement-based replication, 158 statically typed languages analogy to schema-on-write, 40 code generation and, 127 statistical and numerical algorithms, 428 StatsD (metrics aggregator), 442 stdin, stdout, 395, 396 Stellar (cryptocurrency), 532 Index | 585 stock market feeds, 442 STONITH (Shoot The Other Node In The Head), 158 stop-the-world (see garbage collection) storage composing data storage technologies, 499-504 diversity of, in MapReduce, 415 Storage Area Network (SAN), 146, 398 storage engines, 69-104 column-oriented, 95-101 column compression, 97-99 defined, 96 distinction between column families and, 99 Parquet, 96, 131 sort order in, 99-100 writing to, 101 comparing requirements for transaction processing and analytics, 90-96 in-memory storage, 88 durability, 227 row-oriented, 70-90 B-trees, 79-83 comparing B-trees and LSM-trees, 83-85 defined, 96 log-structured, 72-79 stored procedures, 161, 253-255, 557 and total order broadcast, 349 pros and cons of, 255 similarity to stream processors, 505 Storm (stream processor), 466 distributed RPC, 468, 514 Trident state handling, 478 straggler events, 470, 498 stream processing, 464-481, 557 accessing external services within job, 474, 477, 478, 517 combining with batch processing lambda architecture, 497 unifying technologies, 498 comparison to batch processing, 464 complex event processing (CEP), 465 fault tolerance, 476-479 atomic commit, 477 idempotence, 478 microbatching and checkpointing, 477 rebuilding state after a failure, 478 for data integration, 494-498 586 | Index maintaining derived state, 495 maintenance of materialized views, 467 messaging systems (see messaging systems) reasoning about time, 468-472 event time versus processing time, 469, 477, 498 knowing when window is ready, 470 types of windows, 472 relation to databases (see streams) relation to services, 508 search on streams, 467 single-threaded execution, 448, 463 stream analytics, 466 stream joins, 472-476 stream-stream join, 473 stream-table join, 473 table-table join, 474 time-dependence of, 475 streams, 440-451 end-to-end, pushing events to clients, 512 messaging systems (see messaging systems) processing (see stream processing) relation to databases, 451-464 (see also changelogs) API support for change streams, 456 change data capture, 454-457 derivative of state by time, 460 event sourcing, 457-459 keeping systems in sync, 452-453 philosophy of immutable events, 459-464 topics, 440 strict serializability, 329 strong consistency (see linearizability) strong one-copy serializability, 329 subjects, predicates, and objects (in triplestores), 55 subscribers (message streams), 440 (see also consumers) supercomputers, 275 surveillance, 537 (see also privacy) Swagger (service definition format), 133 swapping to disk (see virtual memory) synchronous networks, 285, 557 comparison to asynchronous networks, 284 formal model, 307 synchronous replication, 154, 557 chain replication, 155 conflict detection, 172 system models, 300, 306-310 assumptions in, 528 correctness of algorithms, 308 mapping to the real world, 309 safety and liveness, 308 systems of record, 386, 557 change data capture, 454, 491 treating event log as, 460 systems thinking, 536 T t-digest (algorithm), 16 table-table joins, 474 Tableau (data visualization software), 416 tail (Unix tool), 447 tail vertex (property graphs), 51 Tajo (query engine), 93 Tandem NonStop SQL (database), 200 TCP (Transmission Control Protocol), 277 comparison to circuit switching, 285 comparison to UDP, 283 connection failures, 280 flow control, 282, 441 packet checksums, 306, 519, 529 reliability and duplicate suppression, 517 retransmission timeouts, 284 use for transaction sessions, 229 telemetry (see monitoring) Teradata (database), 93, 200 term-partitioned indexes, 208, 217 termination (consensus), 365 Terrapin (database), 413 Tez (dataflow engine), 421-423 fault tolerance, 422 support by higher-level tools, 427 thrashing (out of memory), 297 threads (concurrency) actor model, 138, 468 (see also message-passing) atomic operations, 223 background threads, 73, 85 execution pauses, 286, 296-298 memory barriers, 338 preemption, 298 single (see single-threaded execution) three-phase commit, 359 Thrift (data format), 117-121 BinaryProtocol, 118 CompactProtocol, 119 field tags and schema evolution, 120 throughput, 13, 390 TIBCO, 137 Enterprise Message Service, 444 StreamBase (stream analytics), 466 time concurrency and, 187 cross-channel timing dependencies, 331 in distributed systems, 287-299 (see also clocks) clock synchronization and accuracy, 289 relying on synchronized clocks, 291-295 process pauses, 295-299 reasoning about, in stream processors, 468-472 event time versus processing time, 469, 477, 498 knowing when window is ready, 470 timestamp of events, 471 types of windows, 472 system models for distributed systems, 307 time-dependence in stream joins, 475 time-of-day clocks, 288 timeliness, 524 coordination-avoiding data systems, 528 correctness of dataflow systems, 525 timeouts, 279, 557 dynamic configuration of, 284 for failover, 158 length of, 281 timestamps, 343 assigning to events in stream processing, 471 for read-after-write consistency, 163 for transaction ordering, 295 insufficiency for enforcing constraints, 347 key range partitioning by, 203 Lamport, 345 logical, 494 ordering events, 291, 345 Titan (database), 50 tombstones, 74, 191, 456 topics (messaging), 137, 440 total order, 341, 557 limits of, 493 sequence numbers or timestamps, 344 total order broadcast, 348-352, 493, 522 consensus algorithms and, 366-368 Index | 587 implementation in ZooKeeper and etcd, 370 implementing with linearizable storage, 351 using, 349 using to implement linearizable storage, 350 tracking behavioral data, 536 (see also privacy) transaction coordinator (see coordinator) transaction manager (see coordinator) transaction processing, 28, 90-95 comparison to analytics, 91 comparison to data warehousing, 93 transactions, 221-267, 558 ACID properties of, 223 atomicity, 223 consistency, 224 durability, 226 isolation, 225 compensating (see compensating transac‐ tions) concept of, 222 distributed transactions, 352-364 avoiding, 492, 502, 521-528 failure amplification, 364, 495 in doubt/uncertain status, 358, 362 two-phase commit, 354-359 use of, 360-361 XA transactions, 361-364 OLTP versus analytics queries, 411 purpose of, 222 serializability, 251-266 actual serial execution, 252-256 pessimistic versus optimistic concur‐ rency control, 261 serializable snapshot isolation (SSI), 261-266 two-phase locking (2PL), 257-261 single-object and multi-object, 228-232 handling errors and aborts, 231 need for multi-object transactions, 231 single-object writes, 230 snapshot isolation (see snapshots) weak isolation levels, 233-251 preventing lost updates, 242-246 read committed, 234-238 transitive closure (graph algorithm), 424 trie (data structure), 88 triggers (databases), 161, 441 implementing change data capture, 455 implementing replication, 161 588 | Index triple-stores, 55-59 SPARQL query language, 59 tumbling windows (stream processing), 472 (see also windows) in microbatching, 477 tuple spaces (programming model), 507 Turtle (RDF data format), 56 Twitter constructing home timelines (example), 11, 462, 474, 511 DistributedLog (event log), 448 Finagle (RPC framework), 135 Snowflake (sequence number generator), 294 Summingbird (processing library), 497 two-phase commit (2PC), 353, 355-359, 558 confusion with two-phase locking, 356 coordinator failure, 358 coordinator recovery, 363 how it works, 357 issues in practice, 363 performance cost, 360 transactions holding locks, 362 two-phase locking (2PL), 257-261, 329, 558 confusion with two-phase commit, 356 index-range locks, 260 performance of, 258 type checking, dynamic versus static, 40 U UDP (User Datagram Protocol) comparison to TCP, 283 multicast, 442 unbounded datasets, 439, 558 (see also streams) unbounded delays, 558 in networks, 282 process pauses, 296 unbundling databases, 499-515 composing data storage technologies, 499-504 federation versus unbundling, 501 need for high-level language, 503 designing applications around dataflow, 504-509 observing derived state, 509-515 materialized views and caching, 510 multi-partition data processing, 514 pushing state changes to clients, 512 uncertain (transaction status) (see in doubt) uniform consensus, 365 (see also consensus) uniform interfaces, 395 union type (in Avro), 125 uniq (Unix tool), 392 uniqueness constraints asynchronously checked, 526 requiring consensus, 521 requiring linearizability, 330 uniqueness in log-based messaging, 522 Unix philosophy, 394-397 command-line batch processing, 391-394 Unix pipes versus dataflow engines, 423 comparison to Hadoop, 413-414 comparison to relational databases, 499, 501 comparison to stream processing, 464 composability and uniform interfaces, 395 loose coupling, 396 pipes, 394 relation to Hadoop, 499 UPDATE statement (SQL), 40 updates preventing lost updates, 242-246 atomic write operations, 243 automatically detecting lost updates, 245 compare-and-set operations, 245 conflict resolution and replication, 246 using explicit locking, 244 preventing write skew, 246-251 V validity (consensus), 365 vBuckets (partitioning), 199 vector clocks, 191 (see also version vectors) vectorized processing, 99, 428 verification, 528-533 avoiding blind trust, 530 culture of, 530 designing for auditability, 531 end-to-end integrity checks, 531 tools for auditable data systems, 532 version control systems, reliance on immutable data, 463 version vectors, 177, 191 capturing causal dependencies, 343 versus vector clocks, 191 Vertica (database), 93 handling writes, 101 replicas using different sort orders, 100 vertical scaling (see scaling up) vertices (in graphs), 49 property graph model, 50 Viewstamped Replication (consensus algo‐ rithm), 366 view number, 368 virtual machines, 146 (see also cloud computing) context switches, 297 network performance, 282 noisy neighbors, 284 reliability in cloud services, 8 virtualized clocks in, 290 virtual memory process pauses due to page faults, 14, 297 versus memory management by databases, 89 VisiCalc (spreadsheets), 504 vnodes (partitioning), 199 Voice over IP (VoIP), 283 Voldemort (database) building read-only stores in batch processes, 413 hash partitioning, 203-204, 211 leaderless replication, 177 multi-datacenter support, 184 rebalancing, 213 reliance on read repair, 179 sloppy quorums, 184 VoltDB (database) cross-partition serializability, 256 deterministic stored procedures, 255 in-memory storage, 89 output streams, 456 secondary indexes, 207 serial execution of transactions, 253 statement-based replication, 159, 479 transactions in stream processing, 477 W WAL (write-ahead log), 82 web services (see services) Web Services Description Language (WSDL), 133 webhooks, 443 webMethods (messaging), 137 WebSocket (protocol), 512 Index | 589 windows (stream processing), 466, 468-472 infinite windows for changelogs, 467, 474 knowing when all events have arrived, 470 stream joins within a window, 473 types of windows, 472 winners (conflict resolution), 173 WITH RECURSIVE syntax (SQL), 54 workflows (MapReduce), 402 outputs, 411-414 key-value stores, 412 search indexes, 411 with map-side joins, 410 working set, 393 write amplification, 84 write path (derived data), 509 write skew (transaction isolation), 246-251 characterizing, 246-251, 262 examples of, 247, 249 materializing conflicts, 251 occurrence in practice, 529 phantoms, 250 preventing in snapshot isolation, 262-265 in two-phase locking, 259-261 options for, 248 write-ahead log (WAL), 82, 159 writes (database) atomic write operations, 243 detecting writes affecting prior reads, 264 preventing dirty writes with read commit‐ ted, 235 WS-* framework, 133 (see also services) WS-AtomicTransaction (2PC), 355 590 | Index X XA transactions, 355, 361-364 heuristic decisions, 363 limitations of, 363 xargs (Unix tool), 392, 396 XML binary variants, 115 encoding RDF data, 57 for application data, issues with, 114 in relational databases, 30, 41 XSL/XPath, 45 Y Yahoo!


pages: 1,237 words: 227,370

Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems by Martin Kleppmann

active measures, Amazon Web Services, bitcoin, blockchain, business intelligence, business process, c2.com, cloud computing, collaborative editing, commoditize, conceptual framework, cryptocurrency, database schema, DevOps, distributed ledger, Donald Knuth, Edward Snowden, Ethereum, ethereum blockchain, fault tolerance, finite state, Flash crash, full text search, general-purpose programming language, informal economy, information retrieval, Infrastructure as a Service, Internet of things, iterative process, John von Neumann, Kubernetes, loose coupling, Marc Andreessen, microservices, natural language processing, Network effects, packet switching, peer-to-peer, performance metric, place-making, premature optimization, recommendation engine, Richard Feynman, self-driving car, semantic web, Shoshana Zuboff, social graph, social web, software as a service, software is eating the world, sorting algorithm, source of truth, SPARQL, speech recognition, statistical model, undersea cable, web application, WebSocket, wikimedia commons

A transaction log can be made tamper-proof by periodically signing it with a hardware security module, but that does not guarantee that the right transactions went into the log in the first place. It would be interesting to use cryptographic tools to prove the integrity of a system in a way that is robust to a wide range of hardware and software issues, and even potentially malicious actions. Cryptocurrencies, blockchains, and distributed ledger technologies such as Bitcoin, Ethereum, Ripple, Stellar, and various others [71, 72, 73] have sprung up to explore this area. I am not qualified to comment on the merits of these technologies as currencies or mechanisms for agreeing contracts. However, from a data systems point of view they contain some interesting ideas. Essentially, they are distributed databases, with a data model and transaction mechanism, in which different replicas can be hosted by mutually untrusting organizations.

The transaction throughput of Bitcoin is rather low, albeit for political and economic reasons more than for technical ones. However, the integrity checking aspects are interesting. Cryptographic auditing and integrity checking often relies on Merkle trees [74], which are trees of hashes that can be used to efficiently prove that a record appears in some dataset (and a few other things). Outside of the hype of cryptocurrencies, certificate transparency is a security technology that relies on Merkle trees to check the validity of TLS/SSL certificates [75, 76]. I could imagine integrity-checking and auditing algorithms, like those of certificate transparency and distributed ledgers, becoming more widely used in data systems in general. Some work will be needed to make them equally scalable as systems without cryptographic auditing, and to keep the performance penalty as low as possible.

batch processing, Relational Model Versus Document Model, Batch Processing-Summary, Glossarycombining with stream processinglambda architecture, The lambda architecture unifying technologies, Unifying batch and stream processing comparison to MPP databases, Comparing Hadoop to Distributed Databases-Designing for frequent faults comparison to stream processing, Processing Streams comparison to Unix, Philosophy of batch process outputs-Philosophy of batch process outputs dataflow engines, Dataflow engines-Discussion of materialization fault tolerance, Bringing related data together in the same place, Philosophy of batch process outputs, Fault tolerance, Messaging Systems for data integration, Batch and Stream Processing-Unifying batch and stream processing graphs and iterative processing, Graphs and Iterative Processing-Parallel execution high-level APIs and languages, MapReduce workflows, High-Level APIs and Languages-Specialization for different domains log-based messaging and, Replaying old messages maintaining derived state, Maintaining derived state MapReduce and distributed filesystems, MapReduce and Distributed Filesystems-Key-value stores as batch process output(see also MapReduce) measuring performance, Describing Performance, Batch Processing outputs, The Output of Batch Workflows-Key-value stores as batch process outputkey-value stores, Key-value stores as batch process output search indexes, Building search indexes using Unix tools (example), Batch Processing with Unix Tools-Sorting versus in-memory aggregation Bayou (database), Uniqueness in log-based messaging Beam (dataflow library), Unifying batch and stream processing bias, Bias and discrimination big ball of mud, Simplicity: Managing Complexity Bigtable data model, Data locality for queries, Column Compression binary data encodings, Binary encoding-The Merits of SchemasAvro, Avro-Code generation and dynamically typed languages MessagePack, Binary encoding-Binary encoding Thrift and Protocol Buffers, Thrift and Protocol Buffers-Datatypes and schema evolution binary encodingbased on schemas, The Merits of Schemas by network drivers, The Merits of Schemas binary strings, lack of support in JSON and XML, JSON, XML, and Binary Variants BinaryProtocol encoding (Thrift), Thrift and Protocol Buffers Bitcask (storage engine), Hash Indexescrash recovery, Hash Indexes Bitcoin (cryptocurrency), Tools for auditable data systemsByzantine fault tolerance, Byzantine Faults concurrency bugs in exchanges, Weak Isolation Levels bitmap indexes, Column Compression blockchains, Tools for auditable data systemsByzantine fault tolerance, Byzantine Faults blocking atomic commit, Three-phase commit Bloom (programming language), Designing Applications Around Dataflow Bloom filter (algorithm), Performance optimizations, Stream analytics BookKeeper (replicated log), Allocating work to nodes Bottled Water (change data capture), Implementing change data capture bounded datasets, Summary, Stream Processing, Glossary(see also batch processing) bounded delays, Glossaryin networks, Synchronous Versus Asynchronous Networks process pauses, Response time guarantees broadcast hash joins, Broadcast hash joins brokerless messaging, Direct messaging from producers to consumers Brubeck (metrics aggregator), Direct messaging from producers to consumers BTM (transaction coordinator), Introduction to two-phase commit bulk synchronous parallel (BSP) model, The Pregel processing model bursty network traffic patterns, Can we not simply make network delays predictable?


pages: 320 words: 87,853

The Black Box Society: The Secret Algorithms That Control Money and Information by Frank Pasquale

Affordable Care Act / Obamacare, algorithmic trading, Amazon Mechanical Turk, American Legislative Exchange Council, asset-backed security, Atul Gawande, bank run, barriers to entry, basic income, Berlin Wall, Bernie Madoff, Black Swan, bonus culture, Brian Krebs, business cycle, call centre, Capital in the Twenty-First Century by Thomas Piketty, Chelsea Manning, Chuck Templeton: OpenTable:, cloud computing, collateralized debt obligation, computerized markets, corporate governance, Credit Default Swap, credit default swaps / collateralized debt obligations, crowdsourcing, cryptocurrency, Debian, don't be evil, drone strike, Edward Snowden, en.wikipedia.org, Fall of the Berlin Wall, Filter Bubble, financial innovation, financial thriller, fixed income, Flash crash, full employment, Goldman Sachs: Vampire Squid, Google Earth, Hernando de Soto, High speed trading, hiring and firing, housing crisis, informal economy, information asymmetry, information retrieval, interest rate swap, Internet of things, invisible hand, Jaron Lanier, Jeff Bezos, job automation, Julian Assange, Kevin Kelly, knowledge worker, Kodak vs Instagram, kremlinology, late fees, London Interbank Offered Rate, London Whale, Marc Andreessen, Mark Zuckerberg, mobile money, moral hazard, new economy, Nicholas Carr, offshore financial centre, PageRank, pattern recognition, Philip Mirowski, precariat, profit maximization, profit motive, quantitative easing, race to the bottom, recommendation engine, regulatory arbitrage, risk-adjusted returns, Satyajit Das, search engine result page, shareholder value, Silicon Valley, Snapchat, social intelligence, Spread Networks laid a new fibre optics cable between New York and Chicago, statistical arbitrage, statistical model, Steven Levy, the scientific method, too big to fail, transaction costs, two-sided market, universal basic income, Upton Sinclair, value at risk, WikiLeaks, zero-sum game

We can be sure the “wealth defense industry” is redoubling its investments in avoiding future leaks. Dan Froomkin, “ ‘Wealth Defense Industry’ NOTES TO PAGES 56–60 245 Protects 1% from the Rabble and Its Taxes,” Huffi ngton Post (blog), December 13, 2011, http://www.huffi ngtonpost .com /dan-froomkin /wealth-defense -industry-p_b_1145825.html. 214. Omri Marian, “Are Cryptocurrencies Super Tax Havens?,” Michigan Law Review First Impressions 112 (2013): 38–48. Available at http://www.michigan lawreview.org/articles/are-cryptocurrencies-em-super-em-tax-havens. 215. Frank Pasquale, “Grand Bargains for Big Data: The Emerging Law of Health Information,” Maryland Law Review 72 (2013): 682–772. 216. On the new economy as a system of social control and modulation, see Julie Cohen, Configuring the Networked Self (New Haven, CT: Yale University Press, 2012). 217.

It does not address the real problems of invasive data collection or unfair data use. 56 THE BLACK BOX SOCIETY Full-Disclosure Future Even if absolute secrecy could somehow be democratized with a universally available cheap encryption tool, would we really want it? I don’t think I want the NSA blinded to real terrorist plots. If someone developed a fleet of poison-dart drones, I’d want the authorities to know. I wouldn’t want so-called “cryptocurrencies” hiding ever more money from the tax authorities and further undermining public finances.214 Biosurveillance helps public health authorities spot emerging epidemics. Monitoring helps us understand the flow of traffic, energy, food, and medicines.215 So while hiding—the temptingly symmetrical solution to surveillance—may be alluring on the surface, it’s not a good bet. The ability to hide— and to detect the hiders— is so comprehensively commodified that only the rich and connected can win that game.


pages: 237 words: 74,109

Uncanny Valley: A Memoir by Anna Wiener

autonomous vehicles, back-to-the-land, basic income, blockchain, Burning Man, call centre, charter city, cloud computing, cognitive bias, cognitive dissonance, commoditize, crowdsourcing, cryptocurrency, Extropian, future of work, Golden Gate Park, housing crisis, Jane Jacobs, job automation, knowledge worker, Lean Startup, means of production, medical residency, new economy, New Urbanism, passive income, pull request, rent control, ride hailing / ride sharing, Sand Hill Road, self-driving car, sharing economy, side project, Silicon Valley, Silicon Valley startup, social web, South of Market, San Francisco, special economic zone, technoutopianism, telepresence, telepresence robot, union organizing, universal basic income, unpaid internship, urban planning, urban renewal, women in the workforce, Y2K, young professional

Years prior, we had conducted an off-again, on-again, casual noncommitment, which had mostly consisted of him explaining things and then apologizing. “Email is about as secure as a postcard,” he’d remind me, as we wandered between families at the farmers market in Fort Greene Park. “You don’t expect your mailman to read it, but he could.” I had listened patiently as he tried to teach me about cryptocurrencies and the promise of the blockchain, the shortcomings of two-factor authentication, the necessity of end-to-end encryption, the inevitability of data breaches. The romance didn’t last, but in its wake we had fallen into a rhythm of exchanging insecure emails on niche topics, like 1980s interface design, binary code, and public-domain art, and occasionally meeting for chaste, geriatric cultural activities.

While the interface could be intimidating to people who were not programmers, the public product was still used and abused like any other social technology that relied on free, user-generated content. The Terms of Service team handled copyright takedowns, trademark infringement, and spam; user deaths and COPPA violations. We took over the work of the Hazmat group, evaluating threats of violence, cryptocurrency scams, phishing sites, suicide notes, and conspiracy theories. We puzzled over reports of Great Firewall circumvention. We ran emails claiming to be from the Russian government through translation software and passed them to Legal with spinning question-mark emojis. We sifted through reports of harassment, revenge porn, child porn, and terrorist content. We pinged our more technical coworkers to examine malware and purportedly malicious scripts.


pages: 286 words: 87,401

Blitzscaling: The Lightning-Fast Path to Building Massively Valuable Companies by Reid Hoffman, Chris Yeh

activist fund / activist shareholder / activist investor, Airbnb, Amazon Web Services, autonomous vehicles, bitcoin, blockchain, Bob Noyce, business intelligence, Chuck Templeton: OpenTable:, cloud computing, crowdsourcing, cryptocurrency, Daniel Kahneman / Amos Tversky, database schema, discounted cash flows, Elon Musk, Firefox, forensic accounting, George Gilder, global pandemic, Google Hangouts, Google X / Alphabet X, hydraulic fracturing, Hyperloop, inventory management, Isaac Newton, Jeff Bezos, Joi Ito, Khan Academy, late fees, Lean Startup, Lyft, M-Pesa, Marc Andreessen, margin call, Mark Zuckerberg, minimum viable product, move fast and break things, move fast and break things, Network effects, Oculus Rift, oil shale / tar sands, Paul Buchheit, Paul Graham, Peter Thiel, pre–internet, recommendation engine, ride hailing / ride sharing, Sam Altman, Sand Hill Road, Saturday Night Live, self-driving car, shareholder value, sharing economy, Silicon Valley, Silicon Valley startup, Skype, smart grid, social graph, software as a service, software is eating the world, speech recognition, stem cell, Steve Jobs, subscription business, Tesla Model S, thinkpad, transaction costs, transport as a service, Travis Kalanick, Uber for X, uber lyft, web application, winner-take-all economy, Y Combinator, yellow journalism

On the other hand, rules usually exist for a reason. You need to have some humility when breaking rules and recognize that you might not understand all the consequences. It’s not always cheating to break the rules, but it is always a high-beta activity, hence the need for caution and compassion. A present-day example of a field where there are both ethical and unethical pirates is the rapid development of cryptocurrencies like Bitcoin and initial coin offerings (ICOs) as a financing tool. The start-ups that are creating currencies and holding ICOs are operating in a legal gray area and likely breaking rules. Some of these start-ups are ethical pirates who are working to change the rules for everyone. Others are sociopathic criminals who are simply trying to collect as much money as possible before the window closes and devil take the hindmost.

But what if the Blitzscaling Era is just getting started? So far, blitzscaling has been concentrated in software and the Internet, but it’s likely to reshape our physical infrastructure or even our bodies in the future. Artificial intelligence will soon be ubiquitous, thanks to self-driving vehicles and better machine learning. Technology innovations in the life sciences, such as CRISPR gene editing, may change the fabric of life itself. Cryptocurrencies and blockchain technology may change the role of governments and corporations in global finance and commerce. New technologies are emerging rapidly and promise to change everything—again. These new technologies will enable new business models, which in turn will create new industries. In the history of high tech, platform shifts, such as the move from mainframes to client-server or the move from the Web to mobile, have represented huge opportunities.


pages: 301 words: 85,263

New Dark Age: Technology and the End of the Future by James Bridle

AI winter, Airbnb, Alfred Russel Wallace, Automated Insights, autonomous vehicles, back-to-the-land, Benoit Mandelbrot, Bernie Sanders, bitcoin, British Empire, Brownian motion, Buckminster Fuller, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, cognitive bias, cognitive dissonance, combinatorial explosion, computer vision, congestion charging, cryptocurrency, data is the new oil, Donald Trump, Douglas Engelbart, Douglas Engelbart, Douglas Hofstadter, drone strike, Edward Snowden, fear of failure, Flash crash, Google Earth, Haber-Bosch Process, hive mind, income inequality, informal economy, Internet of things, Isaac Newton, John von Neumann, Julian Assange, Kickstarter, late capitalism, lone genius, mandelbrot fractal, meta analysis, meta-analysis, Minecraft, mutually assured destruction, natural language processing, Network effects, oil shock, p-value, pattern recognition, peak oil, recommendation engine, road to serfdom, Robert Mercer, Ronald Reagan, self-driving car, Silicon Valley, Silicon Valley ideology, Skype, social graph, sorting algorithm, South China Sea, speech recognition, Spread Networks laid a new fibre optics cable between New York and Chicago, stem cell, Stuxnet, technoutopianism, the built environment, the scientific method, Uber for X, undersea cable, University of East Anglia, uranium enrichment, Vannevar Bush, WikiLeaks

In response to vast increases in data storage and computational capacity in the last decade, the amount of energy used by data centres has doubled every four years, and is expected to triple in the next ten years. A study in Japan suggested that by 2030, the power requirements for digital services alone would outstrip the entire nation’s current generation capacity.19 Even technologies that make explicit claims to radically transform society are not exempt. The cryptocurrency Bitcoin, which is intended to disrupt hierarchical and centralised financial systems, requires the energy of nine US homes to perform a single transaction; and if its growth continues, by 2019 it will require the annual power output of the entire United States to sustain itself.20 Moreover, these figures reflect processing power, but do not account for the wider network of digital activities empowered by computation.

., 139 Commission on Government Secrecy, 169 complex systems about, 2–3 aggregation of, 40 high-frequency trading, 14, 106–7, 108, 122, 124 complicity computational logic, 184–5 Freedom of Information, 161–2, 165, 192 global mass surveillance, 179–80 Glomar response, 165, 186 public key cryptography, 167–8 computation calculating machines, 27 Electronic Numerical Integrator and Computer (ENIAC), 27, 27–30, 33 flight trackers, 35–6, 36 IBM Selective Sequence Electronic Calculator (SSEC), 30, 30–2, 31, 146 opaqueness of, 40 computational logic, 184–5 computational thinking about, 4 evolution of, 248 importance of, 44–5 Concorde, 69, 70, 71 conspiracy chemtrails, 192–5, 206–8, 214 conspiracy theories, 195, 198–9, 205 contrails, 196–8, 197, 214 global warming, 73, 193, 214 9/11 terrorist attacks, 203–4, 206 ‘Conspiracy as Governance’ (Assange), 183 contrails, 196–8, 197, 214 Copenhagen Climate Change Conference (COP15), 199 Cowen, Deborah, 132 Credit Suisse, 109 cryptocurrency, 63 Cumulus homogenitus, 195–6 cyborg chess, 159 D Dabiq (online magazine), 212 Dallaire, Roméo, 243 darkness, 11–2 “Darkness” (poem), 201–2 dark pools, 108–9 DARPA (Defense Advanced Research Projects Agency), 33 Darwin, Charles, 78 data abundance of, 83–4, 131 big, 84 importance of, 245–6 realistic accounting of, 247 thirst for, 246 data dredging, 90–1 Debord, Guy, 103 DEC (Digital Equipment Corporation), 33 Decyben SAS, 110 Deep Blue, 148–9, 157–60 DeepDream, 153, 154–5 DeepFace software, 140 defeat devices, 120 Defense Advanced Research Projects Agency (DARPA), 33 de Solla Price, Derek, 91–2, 93 Diffie-Hellman key exchange, 167 digital culture, 64–5 Digital Equipment Corporation (DEC), 33 digital networks, mapping, 104 digitisation, 108 ‘Discussion of the Possibility of Weather Control’ lecture, 26 diurnal temperature range (DTR), 204 DNA sequencing, 93 D-Notices, 179 domain name system, 79 doomsday vault, 52–3 Dow Jones Industrial Average, 121–2 drones, 161–2 drug discovery/research, 94–5 DTR (diurnal temperature range), 204 Duffy, Carol Ann, 201 Dunne, Carey, 194–5 E Elberling, Bo, 57 electromagnetic networks, 104 Electronic Computer Project, 27 Electronic Frontier Foundation, 177 Electronic Numerical Integrator and Computer (ENIAC), 27, 27–30, 33 Elements of Chemistry (Lavoisier), 208–9 Elkins, Caroline, 183–4 Ellis, James, 167 encoded biases, 142 ‘End of Theory’ (Anderson), 83–4, 146 Engelbart, Douglas, 79 ENIAC (Electronic Numerical Integrator and Computer), 27, 27–30, 33 Enlightenment, 10 Environmental Protection Agency (EPA), 119–20 EPA (Environmental Protection Agency), 119–20 Epagogix, 130 epidemic type aftershock sequence (ETAS) model, 145–6 Epimetheus, 132–4 Equinix LD4, 104 Eroom’s law, 86, 93–6 ETAS (epidemic type aftershock sequence) model, 145–6 Euronext Data Center, 104, 105, 106 Evangelismos Hospital, 130–1 evolution, theory of, 78 exploitation, 229–30 Eyjafjallajökull, eruption of, 200–1, 202 F Facebook, 39–40, 156–7 facial recognition, 141 Fairchild Semiconductor, 80 Farage, Nigel, 194 Fat Man bomb, 25 Fermi, Enrico, 250 Ferranti Mark I, 78 fiat anima, 19–20 fiat lux, 19–20 Finger Family, 221–2, 224, 227 ‘Five Eyes,’ 174 Flash Boys (Lewis), 111–2 flash crash, 121–2, 130–1 FlightRadar24, 36, 189, 191 flight trackers, 35–6, 36 ‘Fourteen Eyes,’ 174 Fowler, R.H., 45 Frankenstein (Shelley), 201 fraud, 86–8, 91 Freedom of Information, 161–2, 165, 192 Friends’ Ambulance Unit, 20 Fuller, Buckminster, 71 Futurama exhibit, 30–1 ‘Future Uses of High Speed Computing in Meteorology’ lecture, 26 G Gail, William B., 72–3 Galton, Francis, 140 game developers, 130 Gates’s law, 83 GCHQ (Government Communications Headquarters), 167, 174, 176–9, 189 genocide, 243 ghost cars (Uber), 118–9 G-INFO, 190 global mass surveillance, 179–80 Global Positioning System (GPS), 36–7, 42–3 Global Seed Vault, 54 global warming, 73, 193, 214 Glomar response, 165, 186 Godard, Jean-Luc, 143 Google, 84, 139, 230, 242 Google Alerts, 190 Google Brain project, 139, 148, 149, 156 Google Earth, 35–6 Google Home, 128–9 Google Maps, 177 Google Translate, 147–8, 156 Government Communications Headquarters (GCHQ), 167, 174, 176–9, 189 GPS (Global Positioning System), 36–7, 42–3 Graves, Robert, 159 Gravity’s Rainbow (Pynchon), 128 gray zone, 212–4 Great Nōbi Earthquake, 145 Greenland, 57–8 Green Revolution, 53 Greyball programme, 119, 120 guardianship, 251–2 H Hankins, Thomas, 102 Haraway, Donna, 12 Harvard Mark I machine, 30 Hayek, Friedrich, 156–7 The Road to Serfdom, 139 The Sensory Order: An Inquiry into the Foundations of Theoretical Psychology, 138–9 HealthyFoodHouse.com (website), 231–2 Heller, Joseph Catch-22, 187–8 Hermes, 134 Hersh, Seymour, 164 Hewlett-Packard, 143 hidden technological processes, 120 high-frequency trading, 14, 106–7, 108, 122, 124 high-throughput screening (HTS), 95–6 Hillingdon Hospital, 110–1, 111 Hippo programme, 32 Hofstadter, Douglas, 205–6 Hola Massacre, 170 homogenitus, 195, 196 Horn, Roni, 50, 201 How-Old.net facial recognition programme, 141 ‘How the World Wide Web Just Happened’ lecture, 78 HTS (high-throughput screening), 95–6 Hughes, Howard, 163 Hughes Glomar Explorer, 163–5 human genome project, 93 Human Interference Task Force, 251 human violence, 202 Humby, Clive, 245, 246 Hwang Woo-suk, 86–8 hyperobjects, 73, 75, 76, 194 hypertext, 79 I IBM Selective Sequence Electronic Calculator (SSEC), 30, 30–2, 31, 146 ICAO (International Civil Aviation Organisation), 68 ICARDA (International Center for Agricultural Research in the Dry Areas), 53–4, 55 ICT, 60–2 image recognition, 139–40 Infinite Fun Space, 149–50, 156 information networks, 62 information superhighway, 10 Infowars (Jones), 207 In Place of Fear (Bevan), 110 Institute of the Aeronautical Sciences, 26 integrated circuits, 79, 80 Intel, 80 International Center for Agricultural Research in the Dry Areas (ICARDA), 53–4, 55 International Civil Aviation Organisation (ICAO), 68 International Cloud Atlas, 195 Internet Research Agency, 235, 237 Inuit Knowledge and Climate Change, 199 The Invisibles (Morrison), 196–7 Isaksen, Ketil, 54 ISIL, 212–3 J Jameson, Fredric, 205 Jelinek, Frederick, 146–7 Jones, Alex Infowars, 207 Joshi, Manoj, 68–9 journalism, automated, 123–4 just-in-time manufacturing, 117 K K-129, 162–3 Karma Police operation, 175 Kasparov, Garry, 148–9, 157–8 Keeling Curve, 74, 74 Kennedy, John F., 169–70 Kinder Eggs, 215–6 Kiva robots, 114 Klein, Mark, 176–7 Kodak, 143 Krakatoa, eruption of, 202 Kunuk, Zacharias, 199, 200 Kuznets curve, 113 L Large Hadron Collider, 93 Lavoisier, Antoine, 78 Elements of Chemistry, 208–9 Lawson, Robert, 175–6 LD4, 104, 105 Leave Campaign, 194 Leibniz, Gottfried Wilhelm, 78 Levy, David, 158, 159 Lewis, Michael Flash Boys, 111–2 LifeSphere, 125 literacy in systems, 3–4 Lockheed Ocean Systems, 163 Logan, Walt (pseudonym), 165 Lombroso, Cesare, 140 London Stock Exchange, 110–1 Lovecraft, H.P., 11, 249 ‘low-hanging fruit,’ 93–4 M Macedonia, 233–4 machine learning algorithms, 222 machine thought, 146 machine translation, 147 magnetism, 77 Malaysian Airlines, 66 manganese noodles, 163–4 Manhattan Project, 24–30, 248 Mara, Jane Muthoni, 170 Mark I Perceptron, 136–8, 137 Maslow’s hierarchy of needs, 128–9 Matthews, James Tilly, 208–10, 209 Mauro, Ian, 199 McCarthy, Joe, 205 McGovern, Thomas, 57–8 McKay Brothers, 107, 110 memex, 24 Mercer, Robert, 236 Merkel, Angela, 174 metalanguage, 3, 5 middens, 56 migrated archive, 170–1 Minds, 150 miniaturisation principle, 81 Mirai, 129 mobile phones, 126 The Modern Prometheus (Shelley), 201 monoculture, 55–6 Moore, Gordon, 80, 80, 83 Moore’s law, 80–3, 92–4 Mordvintsev, Alexander, 154 Morgellons, 211, 214 Morrison, Grant The Invisibles, 196–7 Morton, Timothy, 73, 194 Mount Tambora, eruption of, 201 Moynihan, Daniel Patrick, 169 Munch, Edvard The Scream, 202 Mutua, Ndiku, 170 N NarusInsight, 177 NASA Ames Advanced Concepts Flight Simulator, 42 Natanz Nuclear Facility, 129 National Centre for Atmospheric Science, 68–9 National Geospatial-Intelligence Agency, 243 National Health Service (NHS), 110 National Mining Association, 64 National Reconnaissance Office, 168, 243 National Security Agency (NSA), 167, 174, 177–8, 183, 242–3, 249–50 National Security Strategy, 59 natural gas, 48 neoliberalism, 138–9 network, 5, 9 networks, 249 Newton, Isaac, 78 NewYorkTimesPolitics.com, 221 New York World’s Fair, 30–1 NHS (National Health Service), 110 9/11 terrorist attacks, 203–4, 206 ‘Nine Eyes,’ 174 1984 (Orwell), 242 NORAD (North American Air Defense Command), 33 North American Air Defense Command (NORAD), 33 ‘The Nor’ project, 104 Not Aviation, 190–1 NSA (National Security Agency), 167, 174, 177–8, 183, 242–3, 249–50 nuclear fusion, 97–8, 100 nuclear warfare, 28 Numerical Prediction (Richardson), 45 Nyingi, Wambugu Wa, 170 Nzili, Paulo Muoka, 170 O Obama, Barack, 180, 206, 231 Official Secrets Act, 189 Omori, Fusakichi, 145 Omori’s Law, 145 Operation Castle, 97 Operation Legacy, 171–2 Optic Nerve programme, 174 Optometrist Algorithm, 99–101, 160 O’Reilly, James, 185–6 Orwell, George 1984, 242 ‘Outline of Weather Proposal’ (Zworykin), 25–6 P Paglen, Trevor, 144 ‘paranoid style,’ 205–6 Patriot Act, 178 Penrose, Roger, 20 Perceptron, 136–8, 137 permafrost, 47–9, 56–7 p-hacking, 89–91 Phillippi, Harriet Ann, 165 photophone, 19–20 Pichai, Sundar, 139 Piketty, Thomas Capital in the Twenty-First Century, 112 Pincher, Chapman, 175–6 Pitt, William, 208 Plague-Cloud, 195, 202 Poitras, Laura, 175 Polaroid, 143 ‘predictive policing’ systems, 144–6 PredPol software, 144, 146 Priestley, Joseph, 78, 208, 209 prion diseases, 50, 50–1 PRISM operation, 173 product spam, 125–6 Project Echelon, 190 Prometheus, 132–4, 198 psychogeography, 103 public key cryptography, 167–8 pure language, 156 Putin, Vladimir, 235 Pynchon, Thomas Gravity’s Rainbow, 128 Q Qajaa, 56, 57 quality control failure of, 92–3 in science, 91 Quidsi, 113–4 R racial profiling, 143–4 racism, 143–4 ‘radiation cats,’ 251 raw computing, 82–3 Reagan, Ronald, 36–7 Reed, Harry, 29 refractive index of the atmosphere, 62 Regin malware, 175 replicability, 88–9 Reproducibility Project, 89 resistance, modes of, 120 Reuter, Paul, 107 Review Group on Intelligence and Communications Technologies, 181 Richardson, Lewis Fry, 20–1, 29, 68 Numerical Prediction, 45 Weather Prediction by Numerical Process, 21–3 Richardson number, 68 The Road to Serfdom (Hayek), 139 Robinson, Kim Stanley Aurora, 128 robots, workers vs., 116 ‘Rogeting,’ 88 Romney, Mitt, 206–7 Rosenblatt, Frank, 137 Roy, Arundhati, 250 Royal Aircraft Establishment, 188–9 Ruskin, John, 17–20, 195, 202 Rwanda, 243, 244, 245 S Sabetta, 48 SABRE (Semi-Automated Business Research Environment), 35, 38 SAGE (Semi-Automatic Ground Environment), 33, 34, 35 Samsung, 127 Scheele, Carl Wilhelm, 78 Schmidt, Eric, 241–5 The Scream (Munch), 202 Sedol, Lee, 149, 157–8 seed banks, 52–6 Seed Vault, 55 seismic sensors, 48 self-excitation, 145 ‘semantic analyser,’ 177 Semi-Automated Business Research Environment (SABRE), 35, 38 Semi-Automatic Ground Environment (SAGE), 33, 34, 35 semiconductors, 82 The Sensory Order: An Inquiry into the Foundations of Theoretical Psychology (Hayek), 138–9 Shelley, Mary Frankenstein, 201 The Modern Prometheus, 201 SIGINT Seniors Europe, 174 simulation, conflating approximation with, 34–5 Singapore Exchange, 122–3 smart products, 127–8, 131 Smith, Robert Elliott, 152 smoking gun, 183–4, 186 Snowden, Edward, 173–5, 178 software about, 82–3 AlphaGo, 149, 156–8 Assistant, 152 AutoAwesome, 152 DeepFace, 140 Greyball programme, 119, 120 Hippo programme, 32 How-Old.net facial recognition programme, 141 Optic Nerve programme, 174 PredPol, 144, 146 Translate, 146 Solnit, Rebecca, 11–2 solutionism, 4 space telescopes, 168–9 speed of light, 107 Spread Networks, 107 SSEC (IBM Selective Sequence Electronic Calculator), 30, 30–2, 31, 146 Stapel, Diederik, 87–8 Stapledon, Olaf, 20 steam engines, 77 Stellar Wind, 176 Stewart, Elizabeth ‘Betsy,’ 30–1, 31 Steyerl, Hito, 126 stock exchanges, 108 ‘The Storm-Cloud of the Nineteenth Century’ lecture series, 17–9 Stratus homogenitus, 195–6 studios, 130 Stuxnet, 129–30 surveillance about, 243–4 complicity in, 185 computational excesses of, 180–1 devices for, 104 Svalbard archipelago, 51–2, 54 Svalbard Global Seed Vault, 52–3 Svalbard Treaty (1920), 52 Swiss National Bank, 123 Syed, Omar, 158–9 systemic literacy, 5–6 T Taimyr Peninsula, 47–8 Targeted Individuals, 210–1 The Task of the Translator (Benjamin), 147, 155–6 TCP (Transmission Control Protocol), 79 technology acceleration of, 2 complex, 2–3 opacity of, 119 Teletubbies, 217 television, children’s, 216–7 Tesco Clubcard, 245 thalidomide, 95 Thatcher, Margaret, 177 theory of evolution, 78 thermal power plants, 196 Three Guineas (Woolf), 12 Three Laws of Robotics (Asimov), 157 Tillmans, Wolfgang, 71 tools, 13–4 To Photograph the Details of a Dark Horse in Low Light exhibition, 143 totalitarianism, collectivism vs., 139 Toy Freaks, 225–6 transistors, 79, 80 Translate software, 146 translation algorithms, 84 Transmission Control Protocol (TCP), 79 Tri Alpha Energy, 98–101 Trinity test, 25 trolling, 231 Trump, Donald, 169–70, 194–5, 206, 207, 236 trust, science and, 91 trusted source, 220 Tuktoyaktuk Peninsula, 49 turbulence, 65–9 tyranny of techne, 132 U Uber, 117–9, 127 UberEats app, 120–1 unboxing videos, 216, 219 United Airlines, 66–7 Uniting and Strengthening America by Fulfilling Rights and Ending Eavesdropping, Dragnet-collection and Online Monitoring Act (USA FREEDOM Act), 178 USA FREEDOM Act (2015), 178 US Drug Efficacy Amendment (1962), 95 V van Helden, Albert, 102 Veles, objectification of, 235 Verizon, 173 VHF omnidirectional radio range (VOR) installations, 104 Vigilant Telecom, 110–1 Volkswagen, 119–20 von Neumann, John about, 25 ‘Can We Survive Technology?


pages: 499 words: 144,278

Coders: The Making of a New Tribe and the Remaking of the World by Clive Thompson

2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 4chan, 8-hour work day, Ada Lovelace, AI winter, Airbnb, Amazon Web Services, Asperger Syndrome, augmented reality, Ayatollah Khomeini, barriers to entry, basic income, Bernie Sanders, bitcoin, blockchain, blue-collar work, Brewster Kahle, Brian Krebs, Broken windows theory, call centre, cellular automata, Chelsea Manning, clean water, cloud computing, cognitive dissonance, computer vision, Conway's Game of Life, crowdsourcing, cryptocurrency, Danny Hillis, David Heinemeier Hansson, don't be evil, don't repeat yourself, Donald Trump, dumpster diving, Edward Snowden, Elon Musk, Erik Brynjolfsson, Ernest Rutherford, Ethereum, ethereum blockchain, Firefox, Frederick Winslow Taylor, game design, glass ceiling, Golden Gate Park, Google Hangouts, Google X / Alphabet X, Grace Hopper, Guido van Rossum, Hacker Ethic, HyperCard, illegal immigration, ImageNet competition, Internet Archive, Internet of things, Jane Jacobs, John Markoff, Jony Ive, Julian Assange, Kickstarter, Larry Wall, lone genius, Lyft, Marc Andreessen, Mark Shuttleworth, Mark Zuckerberg, Menlo Park, microservices, Minecraft, move fast and break things, move fast and break things, Nate Silver, Network effects, neurotypical, Nicholas Carr, Oculus Rift, PageRank, pattern recognition, Paul Graham, paypal mafia, Peter Thiel, pink-collar, planetary scale, profit motive, ransomware, recommendation engine, Richard Stallman, ride hailing / ride sharing, Rubik’s Cube, Ruby on Rails, Sam Altman, Satoshi Nakamoto, Saturday Night Live, self-driving car, side project, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, single-payer health, Skype, smart contracts, Snapchat, social software, software is eating the world, sorting algorithm, South of Market, San Francisco, speech recognition, Steve Wozniak, Steven Levy, TaskRabbit, the High Line, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, universal basic income, urban planning, Wall-E, Watson beat the top human players on Jeopardy!, WikiLeaks, women in the workforce, Y Combinator, Zimmermann PGP, éminence grise

That ranges from Bitcoin—a currency specifically designed to create money that couldn’t be controlled by dough-printing central banks—to Ethereum, a way of creating “smart contracts” that, its adherents hope, would allow commerce so frictionless and decentralized that even lawyers wouldn’t be necessary: The instant someone performed the service you’d contracted them to do for you, the digital cash would arrive in their digital wallet. One survey of people in the cryptocurrency community found that fully 27 percent called themselves libertarian, more than double the rate Pew Research Center found in the general population. At first blush, it’s not hard to figure out why there’d be a strong Venn overlap between coders and libertarians. Both inhabit realms where first principles and logic are heavily touted. They’re also arenas heavily populated by young guys—who often have little experience with the messy priors and injustices of the real world, and thus are prone to breezily hand wave these aside.

COBOL and BASIC were the targets back then—but today, that snobbishness is leveled at the web languages so many newbies and underrepresented coders use as their on-ramp: JavaScript, HTML, CSS. As the pink-collar ghetto emerges in the front end, the self-appointed alpha nerds flee it. These days, they’re less and less interested in web or app development and are moving into emerging areas like blockchain—Bitcoin and other cryptocurrencies—or machine learning. They’re fields that are newly technically challenging; serious machine-learning work requires some genuinely mathematical thinking (and, if you practice it at a high level, formal computer science education). And these coders know that these skills are the most lucrative, because they’re necessary for the hot venture-capital-soaked fields like robotics and self-driving cars.

trio of coworkers: Laura Fitzpatrick, “Brief History of YouTube,” Time, May 31, 2010, accessed August 18, 2018, http://content.time.com/time/magazine/article/0,9171,1990787,00.html. one person, Bobby Murphy: Alex Hern, “Snapchat Boss Evan Spiegel on the App That Made Him One of the World’s Youngest Billionaires,” Guardian, December 5, 2017, https://www.theguardian.com/technology/2017/dec/05/snapchat-boss-evan-spiegel-on-the-app-that-made-him-one-of-the-worlds-youngest-billionaires. the pseudonymous “Satoshi Nakamoto”: Joshua Davis, “The Crypto-Currency,” New Yorker, October 10, 2011, accessed August 18, 2018, https://www.newyorker.com/magazine/2011/10/10/the-crypto-currency. first-person shooter video games: Chris Kohler, “Q&A: Doom’s Creator Looks Back on 20 Years of Demonic Mayhem,” Wired, December 10, 2013, accessed August 18, 2018, https://www.wired.com/2013/12/john-carmack-doom. “‘QA team put together’”: Joel Spolsky, “Top Five (Wrong) Reasons You Don’t Have Testers,” Joel on Software (blog), April 30, 2000, accessed August 18, 2018, https://www.joelonsoftware.com/2000/04/30/top-five-wrong-reasons-you-dont-have-testers.


pages: 807 words: 154,435

Radical Uncertainty: Decision-Making for an Unknowable Future by Mervyn King, John Kay

"Robert Solow", Airbus A320, Albert Einstein, Albert Michelson, algorithmic trading, Antoine Gombaud: Chevalier de Méré, Arthur Eddington, autonomous vehicles, availability heuristic, banking crisis, Barry Marshall: ulcers, battle of ideas, Benoit Mandelbrot, bitcoin, Black Swan, Bonfire of the Vanities, Brownian motion, business cycle, business process, capital asset pricing model, central bank independence, collapse of Lehman Brothers, correlation does not imply causation, credit crunch, cryptocurrency, cuban missile crisis, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, demographic transition, discounted cash flows, disruptive innovation, diversification, diversified portfolio, Donald Trump, easy for humans, difficult for computers, Edmond Halley, Edward Lloyd's coffeehouse, Edward Thorp, Elon Musk, Ethereum, Eugene Fama: efficient market hypothesis, experimental economics, experimental subject, fear of failure, feminist movement, financial deregulation, George Akerlof, germ theory of disease, Hans Rosling, Ignaz Semmelweis: hand washing, income per capita, incomplete markets, inflation targeting, information asymmetry, invention of the wheel, invisible hand, Jeff Bezos, Johannes Kepler, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Snow's cholera map, John von Neumann, Kenneth Arrow, Long Term Capital Management, loss aversion, Louis Pasteur, mandelbrot fractal, market bubble, market fundamentalism, Moneyball by Michael Lewis explains big data, Nash equilibrium, Nate Silver, new economy, Nick Leeson, Northern Rock, oil shock, Paul Samuelson, peak oil, Peter Thiel, Philip Mirowski, Pierre-Simon Laplace, popular electronics, price mechanism, probability theory / Blaise Pascal / Pierre de Fermat, quantitative trading / quantitative finance, railway mania, RAND corporation, rent-seeking, Richard Feynman, Richard Thaler, risk tolerance, risk-adjusted returns, Robert Shiller, Robert Shiller, Ronald Coase, sealed-bid auction, shareholder value, Silicon Valley, Simon Kuznets, Socratic dialogue, South Sea Bubble, spectrum auction, Steve Ballmer, Steve Jobs, Steve Wozniak, Tacoma Narrows Bridge, Thales and the olive presses, Thales of Miletus, The Chicago School, the map is not the territory, The Market for Lemons, The Nature of the Firm, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Thomas Bayes, Thomas Davenport, Thomas Malthus, Toyota Production System, transaction costs, ultimatum game, urban planning, value at risk, World Values Survey, Yom Kippur War, zero-sum game

But central banks report many different quantitative measures of ‘the money supply’ and the expression M in a mathematical model is as imprecise as the confused references to ‘money supply’ in much popular writing. And what is meant by ‘money’ is temporally and geographically specific. Money is dollars in the US, and euros in Europe. Not so long ago, money was gold and silver. For the inhabitants of Yap in the Caroline Islands, money was Rai, heavy circles of limestone with a hole in the middle. Some people think that crypto-currencies such as Bitcoin and Ethereum are ‘money’. Numbers are essential to economic analysis. But economic data and economic models are never descriptive of ‘the world as it really is’. Economic interpretation is always the product of a social context or theory. Expressing uncertainty When we are wondering whether the man in the compound is bin Laden or what happened to the Mary Celeste , whether the second Smith child is a girl or whether Joyce met Lenin, probabilities are unhelpful.

The same overreach and reaction to it was repeated almost immediately in other emerging markets in the decade that followed, in the ‘new economy’ bubble of 1999, and during the convergence of interest rates across the Continent which followed the adoption of the euro. And in all these cases investors lost very large amounts of money as greater realism finally set in. The collapse of a narrative is a more rapid process than its transmission. And as we write, the financial press is full of perhaps the thinnest story since tulips to give rise to a bubble – the imagined future takeover of the world monetary system by crypto-currencies. Like other popular fictions, the Bitcoin phenomenon combines several perennial narratives – in this case, a libertarian vision of a world free of state intervention, the power of a magic technology, and the mystery of ‘money creation’. Round-up at Jackson Hole In the 1980s, bond markets, once staid backwaters of the financial system, became the focus of an exciting new narrative based on securitisation.

., 295 , 407 , 412 business cycles, 347 business history (academic discipline), 286 business schools, 318 business strategy: approach in 1970s, 183 ; approach in 1980s, 181–2 ; aspirations confused with, 181–2 , 183–4 ; business plans, 223–4 , 228 ; collections of capabilities, 274–7 ; and the computer industry, 27–31 ; corporate takeovers, 256–7 ; Lampert at Sears, 287–9 , 292 ; Henry Mintzberg on, 296 , 410 ; motivational proselytisation, 182–3 , 184 ; quantification mistaken for understanding, 180–1 , 183 ; and reference narratives, 286–90 , 296–7 ; risk maps, 297 ; Rumelt’s MBA classes, 10 , 178–80 ; Shell’s scenario planning, 223 , 295 ; Sloan at General Motors, 286–7 ; strategy weekends, 180–3 , 194 , 296 , 407 ; three common errors, 183–4 ; vision or mission statements, 181–2 , 184 Buxton, Jedediah, 225 Calas, Jean, 199 California, 48–9 Cambridge Growth Project, 340 Canadian fishing industry, 368–9 , 370 , 423 , 424 cancer, screening for, 66–7 Candler, Graham, 352 , 353–6 , 399 Cardiff City Football Club, 265 Carlsen, Magnus, 175 , 273 Carnegie, Andrew, 427 Carnegie Mellon University, 135 Carré, Dr Matt, 267–8 Carroll, Lewis, Through the Looking-Glass , 93–4 , 218 , 344 , 346 ; ‘Jabberwocky’, 91–2 , 94 , 217 Carron works (near Falkirk), 253 Carter, Jimmy, 8 , 119 , 120 , 123 , 262–3 cartography, 391 Casio, 27 , 31 Castro, Fidel, 278–9 cave paintings, 216 central banks, 5 , 7 , 95 , 96 , 103–5 , 285–6 , 348–9 , 350 , 351 , 356–7 Central Pacific Railroad, 48 Centre for the Study of Existential Risk, 39 Chabris, Christopher, 140 Challenger disaster (1986), 373 , 374 Chamberlain, Neville, 24–5 Chandler, Alfred, Strategy and Structure , 286 Chariots of Fire (film, 1981), 273 Charles II, King, 383 Chelsea Football Club, 265 chess, 173 , 174 , 175 , 266 , 273 , 346 Chicago economists, 36 , 72–4 , 86 , 92 , 111–14 , 133–7 , 158 , 257–8 , 307 , 342–3 , 381–2 Chicago Mercantile Exchange, 423 chimpanzees, 161–2 , 178 , 274 China, 4–5 , 419–20 , 430 cholera, 283 Churchill, Winston: character of, 25–6 , 168 , 169 , 170 ; fondness for gambling, 81 , 168 ; as hedgehog not fox, 222 ; on Montgomery, 293 ; restores gold standard (1925), 25–6 , 269 ; The Second World War , 187 ; Second World War leadership, 24–5 , 26 , 119 , 167 , 168–9 , 170 , 184 , 187 , 266 , 269 Citibank, 255 Civil War, American, 188 , 266 , 290 Clapham, John, 253 Clark, Sally, 197–8 , 200 , 202 , 204 , 206 Clausewitz, Carl von, On War , 433 climate systems, 101–2 Club of Rome, 361 , 362 Coase, Ronald, 286 , 342 Cochran, Johnnie, 198 , 217 Cochrane, John, 93 coffee houses, 55–6 cognitive illusions, 141–2 Cohen, Jonathan, 206–7 Colbert, Jean-Baptiste, 411 Cold War, 293–4 , 306–7 Collier, Paul, 276–7 Columbia disaster (2003), 373 Columbia University, 117 , 118 , 120 Columbus, Christopher, 4 , 21 Colyvan, Mark, 225 Comet aircraft, 23–4 , 228 communication: communicative rationality, 172 , 267–77 , 279–82 , 412 , 414–16 ; and decision-making, 17 , 231 , 272–7 , 279–82 , 398–9 , 408 , 412 , 413–17 , 432 ; eusociality, 172–3 , 274 ; and good doctors, 185 , 398–9 ; human capacity for, 159 , 161 , 162 , 172–3 , 216 , 272–7 , 408 ; and ill-defined concepts, 98–9 ; and intelligibility, 98 ; language, 98 , 99–100 , 159 , 162 , 173 , 226 ; linguistic ambiguity, 98–100 ; and reasoning, 265–8 , 269–77 ; and the smartphone, 30 ; the ‘wisdom of crowds’, 47 , 413–14 Community Reinvestment Act (USA, 1977), 207 comparative advantage model, 249–50 , 251–2 , 253 computer technologies, 27–31 , 173–4 , 175–7 , 185–6 , 227 , 411 ; big data, 208 , 327 , 388–90 ; CAPTCHA text, 387 ; dotcom boom, 228 ; and economic models, 339–40 ; machine learning, 208 Condit, Phil, 228 Condorcet, Nicolas de, 199–200 consumer price index, 330 , 331 conviction narrative theory, 227–30 Corinthians (New Testament), 402 corporate takeovers, 256–7 corporations, large, 27–31 , 122 , 123 , 286–90 , 408–10 , 412 , 415 Cosmides, Leda, 165 Cretaceous–Paleogene extinction, 32 , 39 , 71–2 Crick, Francis, 156 cricket, 140–1 , 237 , 263–5 crime novels, classic, 218 crosswords, 218 crypto-currencies, 96 , 316 Csikszentmihalyi, Mihaly, 140 , 264 Cuba, 278–80 ; Cuban Missile Crisis, 279–81 , 299 , 412 Custer, George, 293 Cutty Sark (whisky producer), 325 Daily Express , 242–3 , 244 Damasio, Antonio, 171 Dardanelles expedition (1915), 25 Darwin, Charles, 156 , 157 Davenport, Thomas, 374 Dawkins, Richard, 156 de Havilland company, 23–4 Debreu, Gerard, 254 , 343–4 decision theory, xvi ; critiques of ‘American school’, 133–7 ; definition of rationality, 133–4 ; derived from deductive reasoning, 138 ; Ellsberg’s ‘ambiguity aversion’, 135 ; expected utility , 111–14 , 115–18 , 124–5 , 127 , 128 – 30 , 135 , 400 , 435–44 ; hegemony of optimisation, 40–2 , 110–14 ; as unable to solve mysteries, 34 , 44 , 47 ; and work of Savage, 442–3 decision-making under uncertainty: and adaptation, 102 , 401 ; Allais paradox, 133–7 , 437 , 440–3 ; axiomatic approach extended to, xv , 40–2 , 110–14 , 133–7 , 257–9 , 420–1 ; ‘bounded rationality concept, 149–53 ; as collaborative process, 17 , 155 , 162 , 176 , 411–15 , 431–2 ; and communication, 17 , 231 , 272–7 , 279–82 , 398–9 , 408 , 412 , 413–17 , 432 ; communicative rationality, 172 , 267–77 , 279–82 , 412 , 414–16 ; completeness axiom, 437–8 ; continuity axiom, 438–40 ; Cuban Missile Crisis, 279–81 , 299 , 412 ; ‘decision weights’ concept, 121 ; disasters attributed to chance, 266–7 ; doctors, 184–6 , 194 , 398–9 ; and emotions, 227–9 , 411 ; ‘evidence-based policy’, 404 , 405 ; excessive attention to prior probabilities, 184–5 , 210 ; expected utility , 111–14 , 115–18 , 124–5 , 127 , 128–30 , 135 , 400 , 435–44 ; first-rate decision-makers, 285 ; framing of problems, 261 , 362 , 398–400 ; good strategies for radical uncertainty, 423–5 ; and hindsight, 263 ; independence axiom, 440–4 ; judgement as unavoidable, 176 ; Klein’s ‘primed recognition decision-making’, 399 ; Gary Klein’s work on, 151–2 , 167 ; and luck, 263–6 ; practical decision-making, 22–6 , 46–7 , 48–9 , 81–2 , 151 , 171–2 , 176–7 , 255 , 332 , 383 , 395–6 , 398–9 ; and practical knowledge, 22–6 , 195 , 255 , 352 , 382–8 , 395–6 , 405 , 414–15 , 431 ; and prior opinions, 179–80 , 184–5 , 210 ; ‘prospect theory’, 121 ; public sector processes, 183 , 355 , 415 ; puzzle– mystery distinction, 20–4 , 32–4 , 48–9 , 64–8 , 100 , 155 , 173–7 , 218 , 249 , 398 , 400–1 ; qualities needed for success, 179–80 ; reasoning as not decision-making, 268–71 ; and ‘resulting’, 265–7 ; ‘risk as feelings’ perspective, 128–9 , 310 ; robustness and resilience, 123 , 294–8 , 332 , 335 , 374 , 423–5 ; and role of economists, 397–401 ; Rumelt’s ‘diagnosis’, 184–5 , 194–5 ; ‘satisficing’ (’good enough’ outcomes), 150 , 167 , 175 , 415 , 416 ; search for a workable solution, 151–2 , 167 ; by securities traders, 268–9 ; ‘shock’ and ‘shift’ labels, 42 , 346 , 347 , 348 , 406–7 ; simple heuristics, rules of thumb, 152 ; and statistical discrimination, 207–9 , 415 ; triumph of probabilistic reasoning, 20 , 40–2 , 72–84 , 110–14 ; von Neumann– Morgenstern axioms, 111 , 133 , 435–44 ; see also business strategy deductive reasoning, 137–8 , 147 , 235 , 388 , 389 , 398 Deep Blue, 175 DeepMind, 173–4 The Deer Hunter (film, 1978), 438 democracy, representative, 292 , 319 , 414 demographic issues, 253 , 358–61 , 362–3 ; EU migration models, 369–70 , 372 Denmark, 426 , 427 , 428 , 430 dentistry, 387–8 , 394 Derek, Bo, 97 dermatologists, 88–9 Digital Equipment Corporation (DEC), 27 , 31 dinosaurs, extinction of, 32 , 39 , 71–2 , 383 , 402 division of labour, 161 , 162 , 172–3 , 216 , 249 DNA, 156 , 198 , 201 , 204 ‘domino theory’, 281 Donoghue, Denis, 226 dotcom boom, 316 , 402 Doyle, Arthur Conan, 34 , 224–5 , 253 Drapers Company, 328 Drescher, Melvin, 248–9 Drucker, Peter, Concept of the Corporation (1946), 286 , 287 Duhem–Quine hypothesis, 259–60 Duke, Annie, 263 , 268 , 273 Dulles, John Foster, 293 Dutch tulip craze (1630s), 315 Dyson, Frank, 259 earthquakes, 237–8 , 239 Eco, Umberto, The Name of the Rose , 204 Econometrica , 134 econometrics, 134 , 340–1 , 346 , 356 economic models: of 1950s and 1960s, 339–40 ; Akerlof model, 250–1 , 252 , 253 , 254 ; ‘analogue economies’ of Lucas, 345 , 346 ; artificial/complex, xiv–xv , 21 , 92–3 , 94 ; ‘asymmetric information’ model, 250–1 , 254–5 ; capital asset pricing model (CAPM), 307–8 , 309 , 320 , 332 ; comparative advantage model, 249–50 , 251–2 , 253 ; cost-benefit analysis obsession, 404 ; diversification of risk, 304–5 , 307–9 , 317–18 , 334–7 ; econometric models, 340–1 , 346 , 356 ; economic rent model, 253–4 ; efficient market hypothesis, 252 , 254 , 308–9 , 318 , 320 , 332 , 336–7 ; efficient portfolio model, 307–8 , 309 , 318 , 320 , 332–4 , 366 ; failure over 2007–08 crisis, xv , 6–7 , 260 , 311–12 , 319 , 339 , 349–50 , 357 , 367–8 , 399 , 407 , 423–4 ; falsificationist argument, 259–60 ; forecasting models, 7 , 15–16 , 68 , 96 , 102–5 , 347–50 , 403–4 ; Goldman Sachs risk models, 6–7 , 9 , 68 , 202 , 246–7 ; ‘grand auction’ of Arrow and Debreu, 343–5 ; inadequacy of forecasting models, 347–50 , 353–4 , 403–4 ; invented numbers in, 312–13 , 320 , 363–4 , 365 , 371 , 373 , 404 , 405 , 423 ; Keynesian, 339–40 ; Lucas critique, 341 , 348 , 354 ; Malthus’ population growth model, 253 , 358–61 , 362–3 ; misuse/abuse of, 312–13 , 320 , 371–4 , 405 ; need for, 404–5 ; need for pluralism of, 276–7 ; pension models, 312–13 , 328–9 , 405 , 423 , 424 ; pre-crisis risk models, 6–7 , 9 , 68 , 202 , 246–7 , 260 , 311–12 , 319 , 320–1 , 339 ; purpose of, 346 ; quest for large-world model, 392 ; ‘rational expectations theory, 342–5 , 346–50 ; real business cycle theory, 348 , 352–4 ; role of incentives, 408–9 ; ‘shift’ label, 406–7 ; ‘shock’ label, 346–7 , 348 , 406–7 ; ‘training base’ (historical data series), 406 ; Value at risk models (VaR), 366–8 , 405 , 424 ; Viniar problem (problem of model failure), 6–7 , 58 , 68 , 109 , 150 , 176 , 202 , 241 , 242 , 246–7 , 331 , 366–8 ; ‘wind tunnel’ models, 309 , 339 , 392 ; winner’s curse model, 256–7 ; World Economic Outlook, 349 ; see also axiomatic rationality; maximising behaviour; optimising behaviour; small world models Economic Policy Symposium, Jackson Hole, 317–18 economics: adverse selection process, 250–1 , 327 ; aggregate output and GDP, 95 ; ambiguity of variables/concepts, 95–6 , 99–100 ; appeal of probability theory, 42–3 ; ‘bubbles’, 315–16 ; business cycles, 45–6 , 347 ; Chicago School, 36 , 72–4 , 86 , 92 , 111–14 , 133–7 , 158 , 257–8 , 307 , 342–3 , 381–2 ; data as essential, 388–90 ; division of labour, 161 , 162 , 172–3 , 216 , 249 ; and evolutionary mechanisms, 158–9 ; ‘expectations’ concept, 97–8 , 102–3 , 121–2 , 341–2 ; forecasts and future planning as necessary, 103 ; framing of problems, 261 , 362 , 398–400 ; ‘grand auction’ of Arrow and Debreu, 343–5 ; hegemony of optimisation, 40–2 , 110 – 14 ; Hicks–Samuelson axioms, 435–6 ; market fundamentalism, 220 ; market price equilibrium, 254 , 343–4 , 381–2 ; markets as necessarily incomplete, 344 , 345 , 349 ; Marshall’s definition of, 381 , 382 ; as ‘non-stationary’, 16 , 35–6 , 45–6 , 102 , 236 , 339–41 , 349 , 350 , 394–6 ; oil shock (1973), 223 ; Phillips curve, 340 ; and ‘physics envy’, 387 , 388 ; and power laws, 238–9 ; as practical knowledge, 381 , 382–3 , 385–8 , 398 , 399 , 405 ; public role of the social scientist, 397–401 ; reciprocity in a modern economy, 191–2 , 328–9 ; and reflexivity, 35–6 , 309 , 394 ; risk and volatility, 124–5 , 310 , 333 , 335–6 , 421–3 ; Romer’s ‘mathiness’, 93–4 , 95 ; shift or structural break, 236 ; Adam Smith’s ‘invisible hand’, 163 , 254 , 343 ; social context of, 17 ; sources of data, 389 , 390 ; surge in national income since 1800, 161 ; systems as non-linear, 102 ; teaching’s emphasis on quantitative methods, 389 ; validity of research findings, 245 ‘Economists Free Ride, Does Anyone Else?’


pages: 146 words: 34,934

The Latte Factor: Why You Don't Have to Be Rich to Live Rich by David Bach, John David Mann

cryptocurrency, financial independence, late fees, time value of money

Sometimes the simplest truths are the easiest to overlook. Or to dismiss as . . . well, as too simple. Not dramatic enough. “You know that expression about how you eat an elephant?” Zoey took a sip of her latte and nodded. “One bite at a time.” “Well, that’s exactly how you build a fortune. One dollar at a time. But here’s how most people think you get rich: you win the lottery. You get lucky, and a friend gives you a tip on a new cryptocurrency or great tech stock no one else knows about yet.” Zoey thought of Jeffrey and his surefire plan to launch the next Instagram. “Or you get an inheritance. A piano falls on that accident-prone great-aunt.” (Good memory, Zoey thought with a smile.) “Or maybe you find buried treasure in your backyard. And you know what they all have in common? They’re all dressed-up versions of the same vague fruitless hope: Someday my ship will come in.


pages: 380 words: 109,724

Don't Be Evil: How Big Tech Betrayed Its Founding Principles--And All of US by Rana Foroohar

"side hustle", accounting loophole / creative accounting, Airbnb, AltaVista, autonomous vehicles, banking crisis, barriers to entry, Bernie Madoff, Bernie Sanders, bitcoin, book scanning, Brewster Kahle, Burning Man, call centre, cashless society, cleantech, cloud computing, cognitive dissonance, Colonization of Mars, computer age, corporate governance, creative destruction, Credit Default Swap, cryptocurrency, data is the new oil, death of newspapers, Deng Xiaoping, disintermediation, don't be evil, Donald Trump, drone strike, Edward Snowden, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Etonian, Filter Bubble, future of work, game design, gig economy, global supply chain, Gordon Gekko, greed is good, income inequality, informal economy, information asymmetry, intangible asset, Internet Archive, Internet of things, invisible hand, Jaron Lanier, Jeff Bezos, job automation, job satisfaction, Kenneth Rogoff, life extension, light touch regulation, Lyft, Mark Zuckerberg, Marshall McLuhan, Martin Wolf, Menlo Park, move fast and break things, move fast and break things, Network effects, new economy, offshore financial centre, PageRank, patent troll, paypal mafia, Peter Thiel, pets.com, price discrimination, profit maximization, race to the bottom, recommendation engine, ride hailing / ride sharing, Robert Bork, Sand Hill Road, search engine result page, self-driving car, shareholder value, sharing economy, Shoshana Zuboff, Silicon Valley, Silicon Valley startup, smart cities, Snapchat, South China Sea, sovereign wealth fund, Steve Jobs, Steven Levy, subscription business, supply-chain management, TaskRabbit, Telecommunications Act of 1996, The Chicago School, the new new thing, Tim Cook: Apple, too big to fail, Travis Kalanick, trickle-down economics, Uber and Lyft, Uber for X, uber lyft, Upton Sinclair, WikiLeaks, zero-sum game

Netflix, Amazon, and, even to a certain extent, Apple, who are relative newcomers to the entertainment business, are no longer content being the uncontested leaders in the video streaming market; now they are also dominant content producers, becoming in effect TV and movie studios, spending billions of dollars (in the case of Netflix and Amazon) on original television programming,42 a move that has left the previous titans of the entertainment business scrambling to match them (hence the recent massive industry mergers of AT&T and Time Warner). Google has lurched into the transportation business with its bid to create a self-driving car, and Facebook is trying to launch its own finance system with the creation of a bespoke cryptocurrency, Libra (Apple has already teamed up with Goldman Sachs on a credit card). Big Tech, in other words, doesn’t just want to become a leader in one sector. It wants to become the platform for everything, the operating system for your life. This is arguably something that Amazon has done best so far. Today Amazon is so much more than “the everything store,” as journalist Brad Stone called it in his book of that name.

“Will Big Tech’s involvement in finance lead to a more diverse and competitive financial system, or to new forms of concentration, market power, and systemic importance?” he asked. “Is the expansion of Big Tech powered by efficiency gains? Or by the cost advantage of circumventing the current regulatory system?” It’s a question that is ever more pressing as Facebook attempts to launch its own cryptocurrency. The jury is still out on whether Big Tech will destabilize global finance. Meanwhile, Carstens and regulators in both the United States and Europe are looking carefully at whether the predictive algorithms and machine learning offered up by Apple, Amazon, Facebook, and others moving into the finance business are increasing or decreasing stability in the financial sector. One particular area of concern is how Big Tech firms use machines rather than human relationships to judge customers (thus circumventing many of the “know your customer” rules that govern traditional banking).


pages: 349 words: 114,038

Culture & Empire: Digital Revolution by Pieter Hintjens

4chan, airport security, AltaVista, anti-communist, anti-pattern, barriers to entry, Bill Duvall, bitcoin, blockchain, business climate, business intelligence, business process, Chelsea Manning, clean water, commoditize, congestion charging, Corn Laws, correlation does not imply causation, cryptocurrency, Debian, Edward Snowden, failed state, financial independence, Firefox, full text search, German hyperinflation, global village, GnuPG, Google Chrome, greed is good, Hernando de Soto, hiring and firing, informal economy, intangible asset, invisible hand, James Watt: steam engine, Jeff Rulifson, Julian Assange, Kickstarter, M-Pesa, mass immigration, mass incarceration, mega-rich, MITM: man-in-the-middle, mutually assured destruction, Naomi Klein, national security letter, Nelson Mandela, new economy, New Urbanism, Occupy movement, offshore financial centre, packet switching, patent troll, peak oil, pre–internet, private military company, race to the bottom, rent-seeking, reserve currency, RFC: Request For Comment, Richard Feynman, Richard Stallman, Ross Ulbricht, Satoshi Nakamoto, security theater, selection bias, Skype, slashdot, software patent, spectrum auction, Steve Crocker, Steve Jobs, Steven Pinker, Stuxnet, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, trade route, transaction costs, twin studies, union organizing, wealth creators, web application, WikiLeaks, Y2K, zero day, Zipf's Law

It is safe to assume that e-gold was deliberately targeted, not because it allowed terrorists to collect money (US dollars work much better for that), rather, because it was a viable digital currency. The use of anti-money-laundering regulations and the PATRIOT Act to attack a digital currency is, I'd claim, a good indicator of how seriously the currency threatens to succeed. The same year that e-gold died, its successor popped up in the form of BitCoin, the first credible crypto-currency. While e-gold based its denomination on the tangible value of gold coins, BitCoin is backed by nothing more than mathematics. This has led people to accuse it of being a pyramid scheme, destined for collapse. BitCoin works by "mining" new coins as a side effect of doing the cryptographic bookkeeping for other people, processing the so-called "transaction chains." In the beginning, when transaction chains were short, they were easy to process, and people could mine thousands of coins on their PCs.

If the BitCoin network survives the different attacks that seem inevitable -- and I give it a 50-50 chance of surviving -- the crypto currency will get a natural monopoly for on-line commerce. At a certain point buying or selling BitCoin for dollars or Euros will not be so important: people will simply hold and spend BitCoin. If the network does not survive the attack, the currency will die, and other crypto-currencies will take its place. Either way, the Spider will lose this particular fight, and the Para-state will eventually (it may take decades) find itself facing a truly independent financial system. Licensed to Make a Killing When I see sustained, multilateral action against systems as organic and valuable as Hawala and BitCoin, my first response is to slice up the official story and look for the lies.


pages: 394 words: 117,982

The Perfect Weapon: War, Sabotage, and Fear in the Cyber Age by David E. Sanger

active measures, autonomous vehicles, Bernie Sanders, bitcoin, British Empire, call centre, Cass Sunstein, Chelsea Manning, computer age, cryptocurrency, cuban missile crisis, Donald Trump, drone strike, Edward Snowden, Google Chrome, Google Earth, Jacob Appelbaum, John Markoff, Mark Zuckerberg, MITM: man-in-the-middle, mutually assured destruction, RAND corporation, ransomware, Sand Hill Road, Silicon Valley, Silicon Valley ideology, Skype, South China Sea, Steve Jobs, Steven Levy, Stuxnet, Tim Cook: Apple, too big to fail, undersea cable, uranium enrichment, Valery Gerasimov, WikiLeaks, zero day

Computer users throughout the country all saw the same broken-English message pop onto their screens. It announced that everything on the hard drives of their computers had been encrypted: “Oops, your important files have been encrypted…Perhaps you are busy looking to recover your files, but don’t waste your time.” It went on to make the dubious claim that if they paid $300 in Bitcoin, the hard-to-trace cryptocurrency, their data would be unlocked. The attack was designed to look like a national shakedown scheme. It wasn’t. The hackers weren’t after money, and they didn’t get much. This was “NotPetya”—so nicknamed by Kaspersky Lab, which was itself suspected by the US government of providing back doors to the Russian government via its profitable security products. (The attack got its odd-sounding name because cyber-threat experts, trying to understand the inner dynamics of the attack, found elements in it that were similar to malware called “Petya” used in an attack the year before.)

If it had been a physical bank heist, it would have been considered one of the largest and most brilliant in modern times. (By comparison, the great Brinks heist of 1950, in Boston’s North End, swept up only about $2.7 million, worth about ten times that in modern currency.) After the Sony hacks, the North had good reason to believe that any retaliation for their cyber exploits would be minimal, and they were right. There was no penalty for the Bangladesh bank attack, or cryptocurrency heists that followed. “Cyber is a tailor-made instrument of power for them,” Chris Inglis, a former deputy director of the National Security Agency, told me. “There’s a low cost of entry, it’s largely asymmetrical, there’s some degree of anonymity and stealth in its use. It can hold large swaths of nation-state infrastructure and private-sector infrastructure at risk. It’s a source of income.”


pages: 453 words: 117,893

What Would the Great Economists Do?: How Twelve Brilliant Minds Would Solve Today's Biggest Problems by Linda Yueh

"Robert Solow", 3D printing, additive manufacturing, Asian financial crisis, augmented reality, bank run, banking crisis, basic income, Ben Bernanke: helicopter money, Berlin Wall, Bernie Sanders, Big bang: deregulation of the City of London, bitcoin, Branko Milanovic, Bretton Woods, BRICs, business cycle, Capital in the Twenty-First Century by Thomas Piketty, clean water, collective bargaining, computer age, Corn Laws, creative destruction, credit crunch, Credit Default Swap, cryptocurrency, currency peg, dark matter, David Ricardo: comparative advantage, debt deflation, declining real wages, deindustrialization, Deng Xiaoping, Doha Development Round, Donald Trump, endogenous growth, everywhere but in the productivity statistics, Fall of the Berlin Wall, fear of failure, financial deregulation, financial innovation, Financial Instability Hypothesis, fixed income, forward guidance, full employment, Gini coefficient, global supply chain, Gunnar Myrdal, Hyman Minsky, income inequality, index card, indoor plumbing, industrial robot, information asymmetry, intangible asset, invisible hand, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, joint-stock company, Joseph Schumpeter, laissez-faire capitalism, land reform, lateral thinking, life extension, low-wage service sector, manufacturing employment, market bubble, means of production, mittelstand, Mont Pelerin Society, moral hazard, mortgage debt, negative equity, Nelson Mandela, non-tariff barriers, Northern Rock, Occupy movement, oil shale / tar sands, open economy, paradox of thrift, Paul Samuelson, price mechanism, price stability, Productivity paradox, purchasing power parity, quantitative easing, RAND corporation, rent control, rent-seeking, reserve currency, reshoring, road to serfdom, Robert Shiller, Robert Shiller, Ronald Coase, Ronald Reagan, school vouchers, secular stagnation, Shenzhen was a fishing village, Silicon Valley, Simon Kuznets, special economic zone, Steve Jobs, The Chicago School, The Wealth of Nations by Adam Smith, Thomas Malthus, too big to fail, total factor productivity, trade liberalization, universal basic income, unorthodox policies, Washington Consensus, We are the 99%, women in the workforce, working-age population

In 1976, a couple of years after he won the Nobel Prize, Hayek published The Denationalization of Money, where he ventured his idea that money should be issued by private firms rather than the government. His reckoning was that competition between money providers would favour the most stable of the currencies in circulation. The same competition would also enforce self-regulation. The work was widely derided. Milton Friedman pointed out that there was nothing in current law to prevent bilateral trade using any medium of exchange accepted by all parties. Curiously, the recent rise of cryptocurrencies, such as Bitcoin, which are digital currencies that can be used to make purchases on the internet, are an example of non-governmental money. Nevertheless, Hayek’s body of work had made an impression on the politicians who would introduce free-market economics into the British and American economies in the 1980s. Hayek had been associated with a London-based think tank, the Institute of Economic Affairs (IEA) since its establishment in 1955.

Buccleuch, Henry Scott, 3rd Duke of budget deficits and austerity Burns, Arthur Burns, Mary business cycle theory Fisher Hayek Schumpeter Callaghan, James Cambridge School see also Keynes, John Maynard; Marshall, Alfred; Robinson, Joan Cambridge University Girton College Kings College Newnham College St Johns and women Canon capital accumulation capital investment capitalism in aftermath of 2008 financial crisis and communism derivation of term and Engels and the financial crisis of 2008 free-market and Hayek inequality and capitalist economies laissez-faire see laissez-faire and Marx and the Occupy movement and Schumpeterian ‘creative destruction’ socialism vs welfare state capitalism car industry Carney, Mark Carter, Jimmy Case, Elizabeth central banks Bank of England Bank of Japan European Central Bank Fed see Federal Reserve forward guidance macroprudential policy monetary policy tools see also quantitative easing (QE) Chamberlin, Edward Chicago School see also Friedman, Milton Chile China 1949 revolution asset management companies banking system Beijing Consensus Communist Party corporate debt Cultural Revolution domestic innovation economic transformation ‘effect’/‘price’ employment system entrepreneurs exports Five Year Plan (1953) foreign direct investment (FDI) and Germany industrialization and reindustrialization inequality innovation challenge legal institutions manufacturing Maoism and Marx national debt openness ‘paradox’ poverty reduction privatization R&D investment regional free trade agreement renminbi (RMB) as second largest economy services sector shadow banking smartphones social networks trade-to GDP ratio and the USSR wage increases women Churchill, Winston class Engels’ The Condition of the Working Class in England and Marx middle see middle class and Ricardo wage earner class Classical School of economics see also Mill, John Stuart; Ricardo, David; Smith, Adam Clinton, Bill Clinton, Hillary cloth clothing Coase, Ronald Cold War Collectivist Economic Planning collectivization Collier, Paul Columbia University communism Bolshevik Party and capitalism Chinese Communist League First International Marxism see Marxism and Robinson Socialist/Second International Third International USSR see Soviet Union Vietnamese vs welfare state capitalism Communist League comparative advantage theory competition ‘competing down’ (Schumpeter) imperfect between money providers perfect and Robinson wages and competitiveness computers Conard, Ed construction consultancy firms consumerism consumption and comparative advantage theory consumer spending and marginal utility analysis convergence hypothesis corn, free trade in Corn Laws repeal and Ricardo corporate debt Cowles Commission Crafts, Nicholas crafts credit crunch credit default swaps (CDS) credit rating Crimean War crypto-currencies currency crises first-generation second-generation third-generation currency stability Cyprus death duties debt Chinese corporate debt-deflation spiral and government bonds indexation and protection from and Minsky’s financial instability hypothesis mortgage debt national see national debt private corporate as share of GDP decentralization defence deflation debt-deflation spiral Fisher and combating deflation Japan self-fulfilling deindustrialization and globalization premature reversing/reindustrialization and trade US Deng Xiaoping depression see Great Depression (1930s); Long Depression (1880s); recession/depression diminishing returns to capital distributive lag model Douglas, David, Lord Reston Douglas, Janet DuPont East Asian ‘tiger’ economies see also Hong Kong; Singapore; South Korea; Taiwan eastern Europe Eastman Kodak Econometric Society Econometrica economic development challenges and Beijing Consensus financial/currency crises and institutions and Lewis model Myanmar and North and path dependence poverty eradication/reduction South Africa Sustainable Development Goals Vietnam and Washington Consensus economic equilibrium economic freedom economic growth and austerity barriers convergence hypothesis development challenges see economic development challenges drivers of 2 see also innovation; institutions; public investment; technology endogenous growth theories inclusive growth through investment Japan’s growth and Japan’s ‘lost decades’ Lewis model mercantilist doctrine of and new technologies policy debates on raising and poverty reduction and productivity debate/challenge slow growth and the future Solow model UK government’s renewed focus on and unemployment Economic Journal economic rent Ricardo’s theory of economies ‘animal spirits’ of crises see financial crises deflation see deflation emerging see emerging economies equilibrium in GDP see gross domestic product global macroeconomic imbalances growth of see economic growth inequality and capitalist economies inflation see inflation and international trade and investment see investment; public investment national debt see national debt QE see quantitative easing rebalancing of recession see recession/depression services economy see services sector and stagnant wages state intervention Economist education higher role in reducing inequality universal Eliot, T.


pages: 389 words: 119,487

21 Lessons for the 21st Century by Yuval Noah Harari

1960s counterculture, accounting loophole / creative accounting, affirmative action, Affordable Care Act / Obamacare, agricultural Revolution, algorithmic trading, augmented reality, autonomous vehicles, Ayatollah Khomeini, basic income, Bernie Sanders, bitcoin, blockchain, Boris Johnson, call centre, Capital in the Twenty-First Century by Thomas Piketty, carbon-based life, cognitive dissonance, computer age, computer vision, cryptocurrency, cuban missile crisis, decarbonisation, deglobalization, Donald Trump, failed state, Filter Bubble, Francis Fukuyama: the end of history, Freestyle chess, gig economy, glass ceiling, Google Glasses, illegal immigration, Intergovernmental Panel on Climate Change (IPCC), Internet of things, invisible hand, job automation, knowledge economy, liberation theology, Louis Pasteur, low skilled workers, Mahatma Gandhi, Mark Zuckerberg, mass immigration, means of production, Menlo Park, meta analysis, meta-analysis, Mohammed Bouazizi, mutually assured destruction, Naomi Klein, obamacare, pattern recognition, post-work, purchasing power parity, race to the bottom, RAND corporation, Ronald Reagan, Rosa Parks, Scramble for Africa, self-driving car, Silicon Valley, Silicon Valley startup, transatlantic slave trade, Tyler Cowen: Great Stagnation, universal basic income, uranium enrichment, Watson beat the top human players on Jeopardy!, zero-sum game

Already today, computers have made the financial system so complicated that few humans can understand it. As AI improves, we might soon reach a point when no human can make sense of finance any more. What will that do to the political process? Can you imagine a government that waits humbly for an algorithm to approve its budget or its new tax reform? Meanwhile peer-to-peer blockchain networks and cryptocurrencies like bitcoin might completely revamp the monetary system, so that radical tax reforms will be inevitable. For example, it might become impossible or irrelevant to tax dollars, because most transactions will not involve a clear-cut exchange of national currency, or any currency at all. Governments might therefore need to invent entirely new taxes – perhaps a tax on information (which will be both the most important asset in the economy, and the only thing exchanged in numerous transactions).

Abbasid caliphs 94 Abraham, prophet 182–3, 186, 187, 274 advertising 36, 50, 53, 54, 77–8, 87, 97, 113, 114, 267 Afghanistan 101, 112, 153, 159, 172, 210 Africa 8, 13, 20, 58, 76, 79, 100, 103–4, 107, 139, 147, 150–1, 152, 168, 182, 184, 223, 226, 229, 239 see also under individual nation name African Americans 67, 150, 152, 227 agriculture 171, 185; animals and 71, 118–19, 224; automation of jobs in 19–20, 29; climate change and modern industrial 116, 117; hierarchical societies and birth of 73–4, 185, 266–7; religion and 128–30 Aisne, third Battle of the (1918) 160 Akhenaten, Pharaoh 191 Al-Aqsa mosque, Jerusalem 15 al-Baghdadi, Abu Bakr 98 Algeria 144, 145 algorithms see artificial intelligence (AI) Ali, Husayn ibn 288 Alibaba (online retailer) 50 Allah 104, 128, 130, 204, 271–2, 289 AlphaZero 31, 123 al-Qaeda 162, 168 Amazon (online retailer) 39, 40, 50, 52, 91, 267–8 Amazon rainforest 116 Amos, prophet 188 Amritsar massacre (1919) 10 Andéol, Emilie 102 animals xi, 73, 86, 98–9, 182, 190, 218, 245; distinct social behaviours 94–5; ecological collapse and 71, 116, 118–19, 224; farm animals, subjugation of 71, 118–19, 224; morality and 187–8, 200; religious sacrifice of 190 anti-Semitism 142, 143, 194, 195, 235–6 see also Jews Apple (technology company) 91, 178 Arab Spring xi, 91 Arjuna (hero of Bhagavadgita) 269–70, 271, 299 art, AI and 25–8, 55–6, 182 artificial intelligence (AI) xiii, xiv; art and 25–8, 55–6, 182; authority shift from humans to 43, 44–72, 78, 268; biochemical algorithms and 20, 21, 25–8, 47–8, 56, 59, 251, 299; cars and see cars; centaurs (human-AI teams) 29, 30–1; communism and 35, 38; consciousness and 68–72, 122, 245–6; creativity and 25–8, 32; data ownership and 77–81; dating and 263; decision-making and 36–7, 50–61; democracy and see democracy; digital dictatorships and xii, 43, 61–8, 71, 79–80, 121; discrimination and 59–60, 67–8, 75–6; education and 32, 34, 35, 38 39, 40–1, 259–68; emotional detection/manipulation 25–8, 51–2, 53, 70, 79–80, 265, 267; equality and xi, 8, 9, 13, 41, 71–2, 73–81, 246; ethics and 56–61; free will and 46–9; games and 29, 31–2, 123; globalisation and threat of 38–40; government and xii, 6, 7–9, 34–5, 37–43, 48, 53, 61–8, 71, 77–81, 87, 90, 121, 267, 268; healthcare and 22–3, 24–5, 28, 48–9, 50; intuition and 20–1, 47; liberty and 44–72; manipulation of human beings 7, 25–8, 46, 48, 50–6, 68–72, 78, 79–80, 86, 96, 245–55, 265, 267, 268; nationalism and 120–6; regulation of 6, 22, 34–5, 61, 77–81, 123; science fiction and 245–55, 268; surveillance systems and 63–5; unique non-human abilities of 21–2; war and 61–8, 123–4 see also war; weapons and see weapons; work and 8, 18, 19–43 see also work Ashoka, Emperor of India 191–2, 286 Ashura 288, 289 Asia 16, 39, 100, 103, 275 see also under individual nation name Assyrian Empire 171 Athenian democracy, ancient 95–6 attention, technology and human 71, 77–8, 87, 88–91 Australia 13, 54, 116, 145, 150, 183, 187, 232–3 Aztecs 182, 289 Babri Mosque, Ayodhya 291 Babylonian Empire 188, 189 Baidu (technology company) 23, 40, 48, 77, 267–8 Bangladesh 38–9, 273 bank loans, AI and 67 behavioural economics 20, 147, 217 Belgium 103, 165, 172 Bellaigue, Christopher de 94 Berko, Anat 233 bestiality, secular ethics and 205–6 bewilderment, age of xiii, 17, 215, 257 Bhagavadgita 269–70, 271, 299 Bhardwaj, Maharishi 181 Bible 127, 131–2, 133, 186–90, 198, 199, 200, 206, 233, 234–5, 240, 241, 272, 298 Big Data xii, 18, 25, 47, 48, 49, 53, 63, 64, 68, 71–2, 268 biometric sensors 23, 49, 50, 52, 64, 79, 92 biotechnology xii, xiv, 1, 6, 7, 8, 16, 17, 18, 21, 33–4, 41, 48, 66, 75, 80, 83, 88, 109, 121, 122, 176, 211, 251–2, 267 see also under individual area of biotechnology bioterrorism 167, 169 Bismarck, Otto von 98–9 bitcoin 6 Black Death 164 Blair, Tony 168 blockchain 6, 8 blood libel 235–6 body, human: bioengineered 41, 259, 265; body farms 34; technology and distraction from 88–92 Bolshevik Revolution (1917) 15, 248 Bonaparte, Napoleon 96, 178, 231, 284 Book of Mormon 198, 235, 240 Book of the Dead, Egyptian 235 Bouazizi, Mohamed xi brain: biochemical algorithms of 20, 21, 47, 48; brain-computer interfaces 92, 260; brainwashing 242–4, 255, 267, 295; decision-making and 50, 52; equality and 75, 79; flexibility and age of 264–5; free will and 250–2, 255; hominid 122; marketing and 267; meditation and 311, 313–14, 316, 317 Brazil 4, 7, 12, 76, 101, 103, 118, 130 Brexit referendum (2016) 5, 9, 11, 15, 45–6, 93, 99, 115 Brihadaranyaka Upanishad 283–4, 302–3 Britain 5, 9, 10, 11, 13, 15, 44–5, 94, 99, 108, 115, 139, 143, 150, 165, 172, 178, 182, 232–3, 243 Brussels bombings (March, 2016) 160 Buddha/Buddhism 58, 102, 136, 183, 184, 186, 190, 196, 278, 291, 302–6, 315 Bulgaria 169, 195, 227 Burma 304–5 Bush, George W. 4, 168, 176, 178 Caesar, Julius 96, 179 California, U.S. 8, 39, 85, 88, 148, 172, 177, 178, 200, 266 Cambridge Analytica 80, 86 Cambridge University 12, 45, 194 Cameron, David 45, 46 Canaan 189, 190, 289, 291 Canada 13, 38, 74, 107 capitalism xii, 11, 16, 35, 38, 55, 68, 76, 77, 96, 105–6, 108, 113, 130, 131, 132, 134, 135, 148, 210, 217, 245, 273, 292, 309 carbon dioxide 117 care industry 24–5 Caro, Rabbi Joseph 195 cars 133, 135; accidents and 23–4, 54, 56–7, 114, 159, 160; choosing 78; GPS/navigation and 54; self-driving 22, 23–4, 33, 41, 56–7, 58–9, 60–1, 63, 168 Catalan Independence 124, 125 Catholics 108, 132, 133, 137, 213, 292, 299 centaurs (human-AI teams) 29, 30 Chad 103, 119 Chaucer, Geoffrey: Canterbury Tales 235–6 Chemosh 191 chess 29, 31–2, 123, 180 Chigaku, Tanaka 305 child labour 33, 224 chimpanzees 94–5, 98, 122, 187–8, 200, 242 China xi, 4, 5, 8, 9, 10, 12, 13, 15, 64, 76, 100, 104, 105, 106, 107, 109, 113, 114, 115, 118, 119, 120, 121, 135, 145, 150, 151, 159, 168, 169, 171, 172–3, 175, 176, 177–8, 180, 181, 182, 183, 184, 185, 186, 193, 201, 227–8, 232, 251, 259–60, 262, 274, 284–5 Chinese Communist Party 5 Christianity 13, 55, 58, 96, 98, 126, 128–30, 131, 132, 133, 134–5, 137, 142, 143, 148, 183, 184–6, 187, 188, 189–90, 191, 192, 193, 194, 196, 199, 200, 203, 204, 208, 212–13, 233, 234–5, 236, 253, 282, 283, 288, 289, 291, 294, 296, 308; Orthodox 13, 15, 137, 138, 183, 237, 282, 308 Churchill, Winston 53, 108, 243 civilisation, single world xi, 5, 92, 95–109, 110, 138; ‘clash of civilisations’ thesis and 93–8; economics and 105–6; European civilisation and 95–6, 108–9; human tribes and 98–100; science and 107–8 ‘clash of civilisations’ 93–4 climate change x, xi, 15, 75–6, 78, 108, 109, 116–20, 121, 122–3, 124, 127, 128, 130, 133, 138, 168, 195, 219, 223, 228, 244, 265 Clinton, Bill 4, 168, 176 Clinton, Hillary 8, 97, 236 Cnut the Great, King of the Danes 105 Coca-Cola 50,