data is the new oil

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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

Hollenbach, ‘Technology and Collective Action: The Effect of Cell Phone Coverage on Political Violence in Africa’, American Political Science Review 107:2 (May 2013). 14.Michael Palmer, ‘Data is the New Oil’, blog post, ANA, November 2006, ana.blogs.com. 15.‘The world’s most valuable resource is no longer oil, but data’, Economist, May 6, 2017, economist.com. 16.David Reid, ‘Mastercard’s boss just told a Saudi audience that “data is the new oil”’, CNBC, October 24, 2017, cnbc.com. 17.Stephen Kerr MP, Kevin Brennan MP, debate on ‘Leaving the EU: Data Protection’, October 12, 2017, transcript. 18.Palmer, ‘Data is the New Oil’. 19.For details of imperial classification and forced naming, see James C. Scott, Seeing Like a State, New Haven, CT: Yale University Press, 1998. 20.Arundhati Roy, ‘The End of Imagination’, Guardian, August 1, 1998, theguardian.com. 21.Sandia National Laboratories, ‘Expert Judgment on Markers to Deter Inadvertent Human Intrusion into the Waste Isolation Pilot Plant’, report, SAND92-1382 / UC-721, page F-49, available at wipp.energy.gov. 22.And into Eternity … Communication over 10000s of Years: How Will We Tell our Children’s Children Where the Nuclear Waste is?

The historical association between military, government, and corporate interests on the one hand, and the development of new technologies on the other, makes this clear. The effects are seen everywhere. And yet we continue to place an inordinate value upon information that locks us into repeated cycles of violence, destruction, and death. Given our long history of doing exactly the same thing with other commodities, this realisation should not and cannot be dismissed. The phrase ‘data is the new oil’ was apparently coined in 2006 by Clive Humby, the British mathematician and architect of the Tesco Clubcard, a supermarket reward programme.14 Since then, it has been repeated and amplified, first by marketers, then by entrepreneurs, and ultimately by business leaders and policy makers. In May 2017, the Economist devoted an entire issue to the proposition, declaring that ‘smartphones and the internet have made data abundant, ubiquitous and far more valuable … By collecting more data, a firm has more scope to improve its products, which attracts more users, generating even more data, and so on.’15 The president and CEO of Mastercard told an audience in Saudi Arabia, the world’s largest producer of actual oil, that data could be as effective as crude as a means of generating wealth (he also said it was a ‘public good’).16 In British parliamentary debates on leaving the European Union, data’s oily qualities were cited by Members of Parliament on both sides.17 Yet few such citations address the implications of long-term, systemic and global reliance on such a poisonous material, or the dubious circumstances of its extraction.


pages: 502 words: 107,657

Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die by Eric Siegel

Albert Einstein, algorithmic trading, Amazon Mechanical Turk, Apple's 1984 Super Bowl advert, backtesting, Black Swan, book scanning, bounce rate, business intelligence, business process, butter production in bangladesh, call centre, Charles Lindbergh, commoditize, computer age, conceptual framework, correlation does not imply causation, crowdsourcing, dark matter, data is the new oil, en.wikipedia.org, Erik Brynjolfsson, Everything should be made as simple as possible, experimental subject, Google Glasses, happiness index / gross national happiness, job satisfaction, Johann Wolfgang von Goethe, lifelogging, Machine translation of "The spirit is willing, but the flesh is weak." to Russian and back, mass immigration, Moneyball by Michael Lewis explains big data, Nate Silver, natural language processing, Netflix Prize, Network effects, Norbert Wiener, personalized medicine, placebo effect, prediction markets, Ray Kurzweil, recommendation engine, risk-adjusted returns, Ronald Coase, Search for Extraterrestrial Intelligence, self-driving car, sentiment analysis, Shai Danziger, software as a service, speech recognition, statistical model, Steven Levy, text mining, the scientific method, The Signal and the Noise by Nate Silver, The Wisdom of Crowds, Thomas Bayes, Thomas Davenport, Turing test, Watson beat the top human players on Jeopardy!, X Prize, Yogi Berra, zero-sum game

The idea is simple, although that doesn’t make it easy. The challenge is tackled by a systematic, scientific means to develop and continually improve prediction—to literally learn to predict. The solution is machine learning—computers automatically developing new knowledge and capabilities by furiously feeding on modern society’s greatest and most potent unnatural resource: data. “Feed Me!”—Food for Thought for the Machine Data is the new oil. —European Consumer Commissioner Meglena Kuneva The only source of knowledge is experience. —Albert Einstein In God we trust. All others must bring data. —William Edwards Deming (a business professor famous for work in manufacturing) Most people couldn’t be less interested in data. It can seem like such dry, boring stuff. It’s a vast, endless regiment of recorded facts and figures, each alone as mundane as the most banal tweet, “I just bought some new sneakers!”

This is the assumption behind the leap of faith an organization takes when undertaking PA. Budgeting the staff and tools for a PA project requires this leap, knowing not what specifically will be discovered and yet trusting that something will be. Sitting on an expert panel at Predictive Analytics World, leading UK consultant Tom Khabaza put it this way: “Projects never fail due to lack of patterns.” With The Data Effect in mind, the scientist rests easy. Data is the new oil. It’s this century’s greatest possession and often considered an organization’s most important strategic asset. Several thought leaders have dubbed it as such—“the new oil”—including European Consumer Commissioner Meglena Kuneva, who also calls it “the new currency of the digital world.” It’s not a hyperbole. In 2012, Apple Inc. overtook Exxon Mobil Corporation, the world’s largest oil company, as the most valuable publicly traded company in the world.

Olofson, Susan Feldman, Steve Conway, Matthew Eastwood, and Natalya Yezhkova, “Worldwide Big Data Technology and Services 2012–2012 Forecast,” ICD Analyze the Future, March 2012, Doc #233485. www.idc.com/getdoc.jsp?containerId=233485. The Prediction Effect: Tom Khabaza says, “There are always patterns.” Tom Khabaza, “Nine Laws of Data Mining—Part 2,” Data Mining & Predictive Analytics, edited by Tom Khabaza, January 14, 2012. http://khabaza.codimension.net/index_files/Page346.htm. “Personal data is the new oil of the Internet and the new currency of the digital world”: Meglena Kuneva, European Consumer Commissioner, March 2009, “Personal Data: The Emergence of a New Asset Class,” An Initiative of the World Economic Forum, January 2011. http://gerdleonhard.typepad.com/files/wef_ittc_personaldatanewasset_report_2011.pdf. Table: Bizarre and Surprising Insights—Consumer Behavior (Chapter 3) Guys literally drool over sports cars: James Warren, “Just the Thought of New Revenue Makes Mouths Water,” New York Times, September 29, 2011. www.nytimes.com/2011/09/30/us/just-the-thought-of-new-revenue-makes-mouths-water.html.


Demystifying Smart Cities by Anders Lisdorf

3D printing, artificial general intelligence, autonomous vehicles, bitcoin, business intelligence, business process, chief data officer, clean water, cloud computing, computer vision, continuous integration, crowdsourcing, data is the new oil, digital twin, distributed ledger, don't be evil, Elon Musk, en.wikipedia.org, facts on the ground, Google Glasses, income inequality, Infrastructure as a Service, Internet of things, Masdar, microservices, Minecraft, platform as a service, ransomware, RFID, ride hailing / ride sharing, risk tolerance, self-driving car, smart cities, smart meter, software as a service, speech recognition, Stephen Hawking, Steve Jobs, Steve Wozniak, Stuxnet, Thomas Bayes, Turing test, urban sprawl, zero-sum game

First, we will consider the different types of networks that exist and look at their different properties and look at real-world examples of how connectivity is provided in cities. Chapter 3 is about devices which are at the core of smart city solutions. We will consider what a device is and how they connect in distributed solutions. This is what is typically referred to as the Internet of Things. We look at the challenges of managing thousands or even millions of devices and what it takes to secure them. Chapter 4 is about data. Some say data is the new oil; regardless of whether that is true, it is a crucial aspect to understand since all data is not the same and needs to be secured and managed differently. Recent increased concern about privacy and exponential growth in unstructured sensor data will be addressed. Chapter 5 is about intelligence, in particular artificial intelligence (AI) . AI offers a lot of potential in many aspects of human life also in the context of cities, but it is important to understand the different forces that affect adoption of AI solutions in a private and a public context.

It will sap the powers of those trying to innovate and will divert attention from things that are considered valuable in the organization. © Anders Lisdorf 2020 A. LisdorfDemystifying Smart Citieshttps://doi.org/10.1007/978-1-4842-5377-9_9 9. Build the data refinery: Because cities run on data Anders Lisdorf1 (1)Copenhagen, Denmark From raw data to useful information “Data is the new oil!” Mathematician and IT architect Clive Humby seems to have been the first to coin the phrase in 2006 where he helped Tesco develop from a fledgling UK retail chain to an intercontinental titan that rivals the likes of Walmart and Carrefour, through the use of data. This was done with the Tesco loyalty program that pioneered offers targeted to particular segments. Several people have reiterated the concept subsequently.


pages: 345 words: 75,660

Prediction Machines: The Simple Economics of Artificial Intelligence by Ajay Agrawal, Joshua Gans, Avi Goldfarb

"Robert Solow", Ada Lovelace, AI winter, Air France Flight 447, Airbus A320, artificial general intelligence, autonomous vehicles, basic income, Bayesian statistics, Black Swan, blockchain, call centre, Capital in the Twenty-First Century by Thomas Piketty, Captain Sullenberger Hudson, collateralized debt obligation, computer age, creative destruction, Daniel Kahneman / Amos Tversky, data acquisition, data is the new oil, deskilling, disruptive innovation, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, everywhere but in the productivity statistics, Google Glasses, high net worth, ImageNet competition, income inequality, information retrieval, inventory management, invisible hand, job automation, John Markoff, Joseph Schumpeter, Kevin Kelly, Lyft, Minecraft, Mitch Kapor, Moneyball by Michael Lewis explains big data, Nate Silver, new economy, On the Economy of Machinery and Manufactures, pattern recognition, performance metric, profit maximization, QWERTY keyboard, race to the bottom, randomized controlled trial, Ray Kurzweil, ride hailing / ride sharing, Second Machine Age, self-driving car, shareholder value, Silicon Valley, statistical model, Stephen Hawking, Steve Jobs, Steven Levy, strong AI, The Future of Employment, The Signal and the Noise by Nate Silver, Tim Cook: Apple, Turing test, Uber and Lyft, uber lyft, US Airways Flight 1549, Vernor Vinge, Watson beat the top human players on Jeopardy!, William Langewiesche, Y Combinator, zero-sum game

First eBook Edition: Apr 2018 ISBN: 978-1-63369-567-2 eISBN: 978-1-63369-568-9 To our families, colleagues, students, and startups who inspired us to think clearly and deeply about artificial intelligence. Contents Cover Title Page Copyright Dedication Acknowledgments 1. Introduction: Machine Intelligence 2. Cheap Changes Everything Part One: Prediction 3. Prediction Machine Magic 4. Why It’s Called Intelligence 5. Data Is the New Oil 6. The New Division of Labor Part Two: Decision Making 7. Unpacking Decisions 8. The Value of Judgment 9. Predicting Judgment 10. Taming Complexity 11. Fully Automated Decision Making Part Three: Tools 12. Deconstructing Work Flows 13. Decomposing Decisions 14. Job Redesign Part Four: Strategy 15. AI in the C-Suite 16. When AI Transforms Your Business 17. Your Learning Strategy 18.

Recent advances in machine learning are often referred to as advances in artificial intelligence because: (1) systems predicated on this technique learn and improve over time; (2) these systems produce significantly more-accurate predictions than other approaches under certain conditions, and some experts argue that prediction is central to intelligence; and (3) the enhanced prediction accuracy of these systems enable them to perform tasks, such as translation and navigation, that were previously considered the exclusive domain of human intelligence. We remain agnostic on the link between prediction and intelligence. None of our conclusions rely on taking a position on whether advances in prediction represent advances in intelligence. We focus on the consequences of a drop in the cost of prediction, not a drop in the cost of intelligence. 5 Data Is the New Oil Hal Varian, the chief economist at Google, channeling Coca-Cola’s Robert Goizueta, said in 2013, “[A] billion hours ago, modern homo sapiens emerged. A billion minutes ago, Christianity began. A billion seconds ago, the IBM PC was released. A billion Google searches ago … was this morning.”1 Google isn’t the only company with extraordinary amounts of data. From large companies like Facebook and Microsoft to local governments and startups, data collection is cheaper and easier than ever before.


pages: 713 words: 93,944

Seven Databases in Seven Weeks: A Guide to Modern Databases and the NoSQL Movement by Eric Redmond, Jim Wilson, Jim R. Wilson

AGPL, Amazon Web Services, create, read, update, delete, data is the new oil, database schema, Debian, domain-specific language, en.wikipedia.org, fault tolerance, full text search, general-purpose programming language, Kickstarter, linked data, MVC pattern, natural language processing, node package manager, random walk, recommendation engine, Ruby on Rails, Skype, social graph, web application

From Jim: First, I have to thank my family; Ruthy, your boundless patience and encouragement have been heartwarming. Emma and Jimmy, you’re two smart cookies, and your daddy loves you always. Also a special thanks to all the unsung heroes who monitor IRC, message boards, mailing lists, and bug systems ready to help anyone who needs you. Your dedication to open source keeps these projects kicking. Copyright © 2012, The Pragmatic Bookshelf. Preface It has been said that data is the new oil. If this is so, then databases are the fields, the refineries, the drills, and the pumps. Data is stored in databases, and if you’re interested in tapping into it, then coming to grips with the modern equipment is a great start. Databases are tools; they are the means to an end. Each database has its own story and its own way of looking at the world. The more you understand them, the better you will be at harnessing the latent power in the ever-growing corpus of data at your disposal.

Not-So-Good For: Because of the high degree of interconnectedness between nodes, graph databases are generally not suitable for network partitioning. Spidering the graph quickly means you can’t afford network hops to other database nodes, so graph databases don’t scale out well. It’s likely that if you use a graph database, it’ll be one piece of a larger system, with the bulk of the data stored elsewhere and only the relationships maintained in the graph. 9.2 Making a Choice As we said at the beginning, data is the new oil. We sit upon a vast ocean of data, yet until it’s refined into information, it’s unusable (and with a more crude comparison, there’s a lot of money in data these days). The ease of collecting and ultimately storing, mining, and refining the data out there starts with the database you choose. Deciding which database to choose is often more complex than merely considering which genre maps best to a given domain’s data.


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

The study found that sales derived from data harvesting have grown by 44.9 percent over the past two years. That’s faster than in the online publishing, data processing, and information services industry itself, according to U.S. Bureau of Economic Analysis data. If the current trends hold, our data will be worth $197.7 billion by 2022—more than the total value of American agricultural output. That is resource extraction on a massive scale. If data is the new oil, then the United States is the Saudi Arabia of the digital era. The leading Internet platform companies are the new Aramco and ExxonMobil.54 Data is the new fuel for growth in multiple industries, from manufacturing to retail to financial services. But unlike other assets, it doesn’t necessarily fuel job growth, but rather, profit growth. And those profits tend to be diverted directly into executives’ and shareholders’ wallets.

I’d argue that while we are spending the time to figure out exactly how to regulate and curb the power of Big Tech, we should also make sure that it isn’t mining our biggest natural resource for free. As we learned earlier in this book, the extraction of personal data is America’s fastest growing industry, one that will be worth $197.7 billion by 2022 if current trends hold—more than the total value of American agricultural output.5 If data is the new oil, then the United States is the Saudi Arabia of the digital era. The leading Internet platform companies are the new Aramco and ExxonMobil. But the tech platform companies are not the only ones in the digital surveillance business. Data brokers such as credit bureaus, healthcare firms, and credit card companies collect and sell all sorts of sensitive personal user data to other businesses and organizations that do not have the scale to collect it themselves.


pages: 239 words: 70,206

Data-Ism: The Revolution Transforming Decision Making, Consumer Behavior, and Almost Everything Else by Steve Lohr

"Robert Solow", 23andMe, Affordable Care Act / Obamacare, Albert Einstein, big data - Walmart - Pop Tarts, bioinformatics, business cycle, business intelligence, call centre, cloud computing, computer age, conceptual framework, Credit Default Swap, crowdsourcing, Daniel Kahneman / Amos Tversky, Danny Hillis, data is the new oil, David Brooks, East Village, Edward Snowden, Emanuel Derman, Erik Brynjolfsson, everywhere but in the productivity statistics, Frederick Winslow Taylor, Google Glasses, impulse control, income inequality, indoor plumbing, industrial robot, informal economy, Internet of things, invention of writing, Johannes Kepler, John Markoff, John von Neumann, lifelogging, Mark Zuckerberg, market bubble, meta analysis, meta-analysis, money market fund, natural language processing, obamacare, pattern recognition, payday loans, personalized medicine, precision agriculture, pre–internet, Productivity paradox, RAND corporation, rising living standards, Robert Gordon, Second Machine Age, self-driving car, Silicon Valley, Silicon Valley startup, six sigma, skunkworks, speech recognition, statistical model, Steve Jobs, Steven Levy, The Design of Experiments, the scientific method, Thomas Kuhn: the structure of scientific revolutions, unbanked and underbanked, underbanked, Von Neumann architecture, Watson beat the top human players on Jeopardy!

“Without the technology to analyze the data, it’s useless,” Zhou notes. “Now, it’s getting to be valuable.” In September 2014, Zhou left IBM to start her own company. The idea, she says, is inspired by the work she did at IBM, and researchers there will continue to pursue the underlying technologies she developed in service of corporations. But Zhou has her eye on the consumer market. If data is the new oil, she says, then we are all data wells, and potentially valuable ones. The data-infused profiles of a person’s traits and values, Zhou says, should be exploited by the individual as a kind of currency in exchange for truly personalized products, services, and advice from businesses, with tailored pricing as well. Even a prototype was months away when we spoke just after she departed from IBM, but her ambition is to help alter the terms of trade in digital commerce.


pages: 222 words: 70,132

Move Fast and Break Things: How Facebook, Google, and Amazon Cornered Culture and Undermined Democracy by Jonathan Taplin

1960s counterculture, affirmative action, Affordable Care Act / Obamacare, Airbnb, Amazon Mechanical Turk, American Legislative Exchange Council, Apple's 1984 Super Bowl advert, back-to-the-land, barriers to entry, basic income, battle of ideas, big data - Walmart - Pop Tarts, bitcoin, Brewster Kahle, Buckminster Fuller, Burning Man, Clayton Christensen, commoditize, creative destruction, crony capitalism, crowdsourcing, data is the new oil, David Brooks, David Graeber, don't be evil, Donald Trump, Douglas Engelbart, Douglas Engelbart, Dynabook, Edward Snowden, Elon Musk, equal pay for equal work, Erik Brynjolfsson, future of journalism, future of work, George Akerlof, George Gilder, Google bus, Hacker Ethic, Howard Rheingold, income inequality, informal economy, information asymmetry, information retrieval, Internet Archive, Internet of things, invisible hand, Jaron Lanier, Jeff Bezos, job automation, John Markoff, John Maynard Keynes: technological unemployment, John von Neumann, Joseph Schumpeter, Kevin Kelly, Kickstarter, labor-force participation, life extension, Marc Andreessen, Mark Zuckerberg, Menlo Park, Metcalfe’s law, Mother of all demos, move fast and break things, move fast and break things, natural language processing, Network effects, new economy, Norbert Wiener, offshore financial centre, packet switching, Paul Graham, paypal mafia, Peter Thiel, plutocrats, Plutocrats, pre–internet, Ray Kurzweil, recommendation engine, rent-seeking, revision control, Robert Bork, Robert Gordon, Robert Metcalfe, Ronald Reagan, Ross Ulbricht, Sam Altman, Sand Hill Road, secular stagnation, self-driving car, sharing economy, Silicon Valley, Silicon Valley ideology, smart grid, Snapchat, software is eating the world, Steve Jobs, Stewart Brand, technoutopianism, The Chicago School, The Market for Lemons, The Rise and Fall of American Growth, Tim Cook: Apple, trade route, transfer pricing, Travis Kalanick, trickle-down economics, Tyler Cowen: Great Stagnation, universal basic income, unpaid internship, We wanted flying cars, instead we got 140 characters, web application, Whole Earth Catalog, winner-take-all economy, women in the workforce, Y Combinator

The reader may wonder what an exploration of the Koch brothers has to do with our larger story. The answer is externalities. Like the Kochs, Google and Facebook are in the extraction industry—their business model is to extract as much personal data from as many people in the world at the lowest possible price and to resell that data to as many companies as possible at the highest possible price—data is the new oil. And like Koch Industries, Google and Facebook create externalities during the extraction process. Brewster Kahle, founder of the Internet Archive, outlined some of these externalities: Edward Snowden showed we’ve inadvertently built the world’s largest surveillance network with the web. China can make it impossible for people there to read things, and just a few big service providers are the de facto organizers of your experience.


pages: 281 words: 71,242

World Without Mind: The Existential Threat of Big Tech by Franklin Foer

artificial general intelligence, back-to-the-land, Berlin Wall, big data - Walmart - Pop Tarts, big-box store, Buckminster Fuller, citizen journalism, Colonization of Mars, computer age, creative destruction, crowdsourcing, data is the new oil, don't be evil, Donald Trump, Double Irish / Dutch Sandwich, Douglas Engelbart, Edward Snowden, Electric Kool-Aid Acid Test, Elon Musk, Fall of the Berlin Wall, Filter Bubble, global village, Google Glasses, Haight Ashbury, hive mind, income inequality, intangible asset, Jeff Bezos, job automation, John Markoff, Kevin Kelly, knowledge economy, Law of Accelerating Returns, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, means of production, move fast and break things, move fast and break things, new economy, New Journalism, Norbert Wiener, offshore financial centre, PageRank, Peace of Westphalia, Peter Thiel, planetary scale, Ray Kurzweil, self-driving car, Silicon Valley, Singularitarianism, software is eating the world, Steve Jobs, Steven Levy, Stewart Brand, strong AI, supply-chain management, the medium is the message, the scientific method, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Thomas L Friedman, Thorstein Veblen, Upton Sinclair, Vernor Vinge, Whole Earth Catalog, yellow journalism

History hasn’t perfectly repeated itself, but we’ve reached the hardened end of Wu’s cycle. We need to entertain the possibility that the monopolies of our day may be even more firmly entrenched than the giants in whose path they stride. One of the reasons for the growing distance between the tech companies and their competition is that they have such a large stockpile of a precious asset. • • • ONE OF THE CLICHÉS OF OUR TIME: Data is the new oil. This felt like hyperbole when first articulated, but now feels perfectly apt. “Data” is a bloodless word, but what it represents is hardly bloodless. It’s the record of our actions: what we read, what we watch, where we travel over the course of a day, what we purchase, our correspondence, our search inquiries, the thoughts we begin to type and then delete. With enough data, it is possible to see correlations and find patterns.


Work in the Future The Automation Revolution-Palgrave MacMillan (2019) by Robert Skidelsky Nan Craig

3D printing, Airbnb, algorithmic trading, Amazon Web Services, anti-work, artificial general intelligence, autonomous vehicles, basic income, business cycle, cloud computing, collective bargaining, correlation does not imply causation, creative destruction, data is the new oil, David Graeber, David Ricardo: comparative advantage, deindustrialization, deskilling, disintermediation, Donald Trump, Erik Brynjolfsson, feminist movement, Frederick Winslow Taylor, future of work, gig economy, global supply chain, income inequality, informal economy, Internet of things, Jarndyce and Jarndyce, Jarndyce and Jarndyce, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Joseph Schumpeter, knowledge economy, Loebner Prize, low skilled workers, Lyft, Mark Zuckerberg, means of production, moral panic, Network effects, new economy, off grid, pattern recognition, post-work, Ronald Coase, Second Machine Age, self-driving car, sharing economy, Steve Jobs, strong AI, technoutopianism, The Chicago School, The Future of Employment, the market place, The Nature of the Firm, The Wealth of Nations by Adam Smith, Thorstein Veblen, Turing test, Uber for X, uber lyft, universal basic income, wealth creators, working poor

That is the power of network effects, and once they reach a crucial tipping point, they grow and grow and grow. The other aspect that leads to a monopoly is the ability to extract and control data. By situating themselves between all these different groups, platforms position themselves in a space where they can collect a lot of data. Any interaction that happens on the platform becomes a piece of information that can then be fed into things like machine learning. If data is the new oil, platforms are the new oil rigs. Their intermediary nature allows them to build a moat around their business since as they collect more and more data, it become increasingly difficult for the competitors to beat them. The result is again a tendency towards monopolisation, as the data-rich get richer. The final reason for the monopoly tendency is path dependency. Once a platform becomes dominant, they create a whole series of entrenched and dependent groups interested in maintaining the platform’s dominance.


pages: 269 words: 70,543

Tech Titans of China: How China's Tech Sector Is Challenging the World by Innovating Faster, Working Harder, and Going Global by Rebecca Fannin

Airbnb, augmented reality, autonomous vehicles, blockchain, call centre, cashless society, Chuck Templeton: OpenTable:, cloud computing, computer vision, connected car, corporate governance, cryptocurrency, data is the new oil, Deng Xiaoping, digital map, disruptive innovation, Donald Trump, El Camino Real, Elon Musk, family office, fear of failure, glass ceiling, global supply chain, income inequality, industrial robot, Internet of things, invention of movable type, Jeff Bezos, Kickstarter, knowledge worker, Lyft, Mark Zuckerberg, megacity, Menlo Park, money market fund, Network effects, new economy, peer-to-peer lending, personalized medicine, Peter Thiel, QR code, RFID, ride hailing / ride sharing, Sand Hill Road, self-driving car, sharing economy, Shenzhen was a fishing village, Silicon Valley, Silicon Valley startup, Skype, smart cities, smart transportation, Snapchat, social graph, software as a service, South China Sea, sovereign wealth fund, speech recognition, stealth mode startup, Steve Jobs, supply-chain management, Tim Cook: Apple, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, urban planning, winner-take-all economy, Y Combinator, young professional

But he emphasizes that China is catching up at an astonishingly rapid rate in implementing the technology in practical ways. China has an advantage based on large numbers of well-trained AI talent, a supportive government policy, and access to a vast amount of data sets powering AI and gleaned from China’s world-leading number of internet and mobile phone users, he notes. In the age of AI, data is the new oil, so China is the new Saudi Arabia, says Lee, author of AI Superpowers.4 His venture investment firm in Beijing, Sinovation Ventures, which I’ve visited multiple times, is betting on AI’s future. Lee, who is widely known for his pioneering work in speech recognition and artificial intelligence, is an investor in five Chinese AI companies worth more than $1 billion. Two that are in the forefront are Megvii, a Chinese developer of facial recognition system Face++, and 4Paradigm, a machine learning software for detecting fraud in insurance and banking.


pages: 677 words: 206,548

Future Crimes: Everything Is Connected, Everyone Is Vulnerable and What We Can Do About It by Marc Goodman

23andMe, 3D printing, active measures, additive manufacturing, Affordable Care Act / Obamacare, Airbnb, airport security, Albert Einstein, algorithmic trading, artificial general intelligence, Asilomar, Asilomar Conference on Recombinant DNA, augmented reality, autonomous vehicles, Baxter: Rethink Robotics, Bill Joy: nanobots, bitcoin, Black Swan, blockchain, borderless world, Brian Krebs, business process, butterfly effect, call centre, Charles Lindbergh, Chelsea Manning, cloud computing, cognitive dissonance, computer vision, connected car, corporate governance, crowdsourcing, cryptocurrency, data acquisition, data is the new oil, Dean Kamen, disintermediation, don't be evil, double helix, Downton Abbey, drone strike, Edward Snowden, Elon Musk, Erik Brynjolfsson, Filter Bubble, Firefox, Flash crash, future of work, game design, global pandemic, Google Chrome, Google Earth, Google Glasses, Gordon Gekko, high net worth, High speed trading, hive mind, Howard Rheingold, hypertext link, illegal immigration, impulse control, industrial robot, Intergovernmental Panel on Climate Change (IPCC), Internet of things, Jaron Lanier, Jeff Bezos, job automation, John Harrison: Longitude, John Markoff, Joi Ito, Jony Ive, Julian Assange, Kevin Kelly, Khan Academy, Kickstarter, knowledge worker, Kuwabatake Sanjuro: assassination market, Law of Accelerating Returns, Lean Startup, license plate recognition, lifelogging, litecoin, low earth orbit, M-Pesa, Mark Zuckerberg, Marshall McLuhan, Menlo Park, Metcalfe’s law, MITM: man-in-the-middle, mobile money, more computing power than Apollo, move fast and break things, move fast and break things, Nate Silver, national security letter, natural language processing, obamacare, Occupy movement, Oculus Rift, off grid, offshore financial centre, optical character recognition, Parag Khanna, pattern recognition, peer-to-peer, personalized medicine, Peter H. Diamandis: Planetary Resources, Peter Thiel, pre–internet, RAND corporation, ransomware, Ray Kurzweil, refrigerator car, RFID, ride hailing / ride sharing, Rodney Brooks, Ross Ulbricht, Satoshi Nakamoto, Second Machine Age, security theater, self-driving car, shareholder value, Silicon Valley, Silicon Valley startup, Skype, smart cities, smart grid, smart meter, Snapchat, social graph, software as a service, speech recognition, stealth mode startup, Stephen Hawking, Steve Jobs, Steve Wozniak, strong AI, Stuxnet, supply-chain management, technological singularity, telepresence, telepresence robot, Tesla Model S, The Future of Employment, The Wisdom of Crowds, Tim Cook: Apple, trade route, uranium enrichment, Wall-E, Watson beat the top human players on Jeopardy!, Wave and Pay, We are Anonymous. We are Legion, web application, Westphalian system, WikiLeaks, Y Combinator, zero day

CHAPTER 3: MOORE’S OUTLAWS The World of Exponentials The Crime Singularity Control the Code, Control the World CHAPTER 4: YOU’RE NOT THE CUSTOMER, YOU’RE THE PRODUCT Our Growing Digital World—What They Never Told You The Social Network and Its Inventory—You You’re Leaking—How They Do It The Most Expensive Things in Life Are Free Terms and Conditions Apply (Against You) Mobile Me Pilfering Your Data? There’s an App for That Location, Location, Location CHAPTER 5: THE SURVEILLANCE ECONOMY You Thought Hackers Were Bad? Meet the Data Brokers Analyzing You But I’ve Got Nothing to Hide Privacy Risks and Other Unpleasant Surprises Opening Pandora’s Virtual Box Knowledge Is Power, Code Is King, and Orwell Was Right CHAPTER 6: BIG DATA, BIG RISK Data Is the New Oil Bad Stewards, Good Victims, or Both? Data Brokers Are Poor Stewards of Your Data Too Social Networking Ills Illicit Data: The Lifeblood of Identity Theft Stalkers, Bullies, and Exes—Oh My! Online Threats to Minors Haters Gonna Hate Burglary 2.0 Targeted Scams and Targeted Killings Counterintelligence Implications of Leaked Government Data So No Online Profile Is Better, Right? The Spy Who Liked Me CHAPTER 7: I.T.

LeT simply processed the data the public was leaking and leveraged them in real time to kill more people and outmaneuver authorities. That was terrorism in the digital age circa 2008. What might terrorists do with the technologies available today? What will they do with the technologies of tomorrow? The lesson of Mumbai is that exponential change applies not just for good but for evil as well. Data Is the New Oil Data is constantly being generated by everything around us. Every digital process, sensor, mobile phone, GPS device, car engine, medical lab test, credit card transaction, hotel door lock, report card, and social media exchange produces data. Smart phones are turning human beings into human sensors, generating vast sums of information about us. As a result, children born today will live their entire lives in the shadow of a massive digital footprint, with some 92 percent of infants already having an online presence.


pages: 282 words: 81,873

Live Work Work Work Die: A Journey Into the Savage Heart of Silicon Valley by Corey Pein

23andMe, 4chan, affirmative action, Affordable Care Act / Obamacare, Airbnb, Amazon Mechanical Turk, Anne Wojcicki, artificial general intelligence, bank run, barriers to entry, Benevolent Dictator For Life (BDFL), Bernie Sanders, bitcoin, Build a better mousetrap, California gold rush, cashless society, colonial rule, computer age, cryptocurrency, data is the new oil, disruptive innovation, Donald Trump, Douglas Hofstadter, Elon Musk, Extropian, gig economy, Google bus, Google Glasses, Google X / Alphabet X, hacker house, hive mind, illegal immigration, immigration reform, Internet of things, invisible hand, Isaac Newton, Jeff Bezos, job automation, Kevin Kelly, Khan Academy, Law of Accelerating Returns, Lean Startup, life extension, Lyft, Mahatma Gandhi, Marc Andreessen, Mark Zuckerberg, Menlo Park, minimum viable product, move fast and break things, move fast and break things, mutually assured destruction, obamacare, passive income, patent troll, Paul Graham, peer-to-peer lending, Peter H. Diamandis: Planetary Resources, Peter Thiel, platform as a service, plutocrats, Plutocrats, Ponzi scheme, post-work, Ray Kurzweil, regulatory arbitrage, rent control, RFID, Robert Mercer, rolodex, Ronald Reagan, Ross Ulbricht, Ruby on Rails, Sam Altman, Sand Hill Road, Scientific racism, self-driving car, sharing economy, side project, Silicon Valley, Silicon Valley startup, Singularitarianism, Skype, Snapchat, social software, software as a service, source of truth, South of Market, San Francisco, Startup school, stealth mode startup, Steve Jobs, Steve Wozniak, TaskRabbit, technological singularity, technoutopianism, telepresence, too big to fail, Travis Kalanick, tulip mania, Uber for X, uber lyft, ubercab, upwardly mobile, Vernor Vinge, X Prize, Y Combinator

Log in to continue. Click yes to agree. Ding! You have notifications. Could that be your boss? Shouldn’t you be working? Why are you reading this? Click. Swipe. Share. We insist. Anxious? Have some dopamine. Ding! Have some more. Boredom was once possible. Idle hands made tremendous things. Today, no one is idle. Everybody’s working, even when they tell themselves they’re taking a break. It is said that “data is the new oil.” But we are the data; the new oil is us. And unlike oil, we are a renewable resource. The startup bubble that began around 2005 ended approximately twelve years later without fanfare. Easy money for half-baked startups dried up, as did the initial public stock offerings of overhyped companies. Wannabe entrepreneurs, a demographic that once declared, “San Francisco or bust,” are now increasingly amenable to gentrifying more affordable cities such as Pittsburgh or Detroit instead.


pages: 337 words: 103,522

The Creativity Code: How AI Is Learning to Write, Paint and Think by Marcus Du Sautoy

3D printing, Ada Lovelace, Albert Einstein, Alvin Roth, Andrew Wiles, Automated Insights, Benoit Mandelbrot, Claude Shannon: information theory, computer vision, correlation does not imply causation, crowdsourcing, data is the new oil, Donald Trump, double helix, Douglas Hofstadter, Elon Musk, Erik Brynjolfsson, Fellow of the Royal Society, Flash crash, Gödel, Escher, Bach, Henri Poincaré, Jacquard loom, John Conway, Kickstarter, Loebner Prize, mandelbrot fractal, Minecraft, music of the spheres, Narrative Science, natural language processing, Netflix Prize, PageRank, pattern recognition, Paul Erdős, Peter Thiel, random walk, Ray Kurzweil, recommendation engine, Rubik’s Cube, Second Machine Age, Silicon Valley, speech recognition, Turing test, Watson beat the top human players on Jeopardy!, wikimedia commons

One of the users said she was a closet lesbian mother and that the data about her movie preferences could have revealed this fact. That you might be able to infer sexual orientation or political leanings from your movie preferences has led to this being called the Brokeback Mountain factor. Eventually the case was settled out of court, but it led to Netflix cancelling the second round of the competition. Data is the new oil, but we are spilling it all over the internet. Who owns that data and what can be done with it is going to be a major question for society as we head into a future fuelled by this oil. How to train your algorithm You may feel there is something scary about algorithms telling you what you might like if it means you will never see things it thinks you won’t like. Personally, I really enjoy being directed towards new music that I might not have found by myself.


pages: 346 words: 97,330

Ghost Work: How to Stop Silicon Valley From Building a New Global Underclass by Mary L. Gray, Siddharth Suri

Affordable Care Act / Obamacare, Amazon Mechanical Turk, augmented reality, autonomous vehicles, barriers to entry, basic income, big-box store, bitcoin, blue-collar work, business process, business process outsourcing, call centre, Capital in the Twenty-First Century by Thomas Piketty, cloud computing, collaborative consumption, collective bargaining, computer vision, corporate social responsibility, crowdsourcing, data is the new oil, deindustrialization, deskilling, don't be evil, Donald Trump, Elon Musk, employer provided health coverage, en.wikipedia.org, equal pay for equal work, Erik Brynjolfsson, financial independence, Frank Levy and Richard Murnane: The New Division of Labor, future of work, gig economy, glass ceiling, global supply chain, hiring and firing, ImageNet competition, industrial robot, informal economy, information asymmetry, Jeff Bezos, job automation, knowledge economy, low skilled workers, low-wage service sector, market friction, Mars Rover, natural language processing, new economy, passive income, pattern recognition, post-materialism, post-work, race to the bottom, Rana Plaza, recommendation engine, ride hailing / ride sharing, Ronald Coase, Second Machine Age, sentiment analysis, sharing economy, Shoshana Zuboff, side project, Silicon Valley, Silicon Valley startup, Skype, software as a service, speech recognition, spinning jenny, Stephen Hawking, The Future of Employment, The Nature of the Firm, transaction costs, two-sided market, union organizing, universal basic income, Vilfredo Pareto, women in the workforce, Works Progress Administration, Y Combinator

They also rely on people doing ghost work to improve their services’ algorithms and artificial intelligence by cleaning up training data from large stores of proprietary data. Tech companies collect and archive information about how people use their sites. Data such as top search-query terms, popular song choices, and mouse cursor movements can be harvested to fuel product development. If customer data is the new oil, the people doing ghost work operate the rigs. The biggest difference between MTurk and tech companies’ internal platforms, like UHRS, is that MTurk recruits and sells labor as well as the platform work site itself, while, on big tech companies’ platforms, a third party—a vendor management system (VMS)—recruits and supplies ghost work labor. All of this is to say that vendor management systems create yet another layer of opaqueness, acting as a broker finding people willing to do ghost work on contract, under nondisclosure agreements.21 For example, Google used vendor management systems to populate its enigmatic ghost work platform, EWOQ.


pages: 382 words: 105,819

Zucked: Waking Up to the Facebook Catastrophe by Roger McNamee

4chan, Albert Einstein, algorithmic trading, AltaVista, Amazon Web Services, barriers to entry, Bernie Sanders, Boycotts of Israel, Cass Sunstein, cloud computing, computer age, cross-subsidies, data is the new oil, Donald Trump, Douglas Engelbart, Douglas Engelbart, Electric Kool-Aid Acid Test, Elon Musk, Filter Bubble, game design, income inequality, Internet of things, Jaron Lanier, Jeff Bezos, John Markoff, laissez-faire capitalism, Lean Startup, light touch regulation, Lyft, Marc Andreessen, Mark Zuckerberg, market bubble, Menlo Park, Metcalfe’s law, minimum viable product, Mother of all demos, move fast and break things, move fast and break things, Network effects, paypal mafia, Peter Thiel, pets.com, post-work, profit maximization, profit motive, race to the bottom, recommendation engine, Robert Mercer, Ronald Reagan, Sand Hill Road, self-driving car, Silicon Valley, Silicon Valley startup, Skype, Snapchat, social graph, software is eating the world, Stephen Hawking, Steve Jobs, Steven Levy, Stewart Brand, The Chicago School, Tim Cook: Apple, two-sided market, Uber and Lyft, Uber for X, uber lyft, Upton Sinclair, WikiLeaks, Yom Kippur War

Facebook, Google, and Amazon have constructed protective moats around their businesses, exploiting network effects and intellectual property to limit the ability of startups to access users and generate value from advertising. The platforms have also used a variety of techniques to limit would-be competitors’ access to capital. In economic terms, Facebook, Google, and Amazon exploited their economic power to reduce competition. Regulators are reconsidering their hands-off policies. Past bragging by internet platforms—statements like “software is eating the world” and “data is the new oil”—has invited greater scrutiny. User data has value, even if users do not understand that to be the case. We know this because Facebook and Google are two of the most valuable companies ever created, and their businesses are based on monetizing user data. Harm is increasingly evident, and policy makers and regulators are taking notice. The challenge is to apply existing regulatory frameworks to a relatively new industry.


pages: 422 words: 104,457

Dragnet Nation: A Quest for Privacy, Security, and Freedom in a World of Relentless Surveillance by Julia Angwin

AltaVista, Ayatollah Khomeini, barriers to entry, bitcoin, Chelsea Manning, Chuck Templeton: OpenTable:, clean water, crowdsourcing, cuban missile crisis, data is the new oil, David Graeber, Debian, Edward Snowden, Filter Bubble, Firefox, GnuPG, Google Chrome, Google Glasses, informal economy, Jacob Appelbaum, John Markoff, Julian Assange, Marc Andreessen, market bubble, market design, medical residency, meta analysis, meta-analysis, mutually assured destruction, Panopticon Jeremy Bentham, prediction markets, price discrimination, randomized controlled trial, RFID, Robert Shiller, Ronald Reagan, security theater, Silicon Valley, Silicon Valley startup, Skype, smart meter, Steven Levy, Upton Sinclair, WikiLeaks, Y2K, zero-sum game, Zimmermann PGP

Tracking is so crucial to the industry that in 2013 Randall Rothenberg, the president of the Interactive Advertising Bureau, said that if the industry lost its ability to track people, “billions of dollars in Internet advertising and hundreds of thousands of jobs dependent on it would disappear.” Meglena Kuneva, a member of the European Commission, summed it up best in 2009 when she said: “Personal data is the new oil of the Internet and the new currency of the digital world.” * * * If you were to build a taxonomy of trackers it would look something like this: GOVERNMENT • Incidental collectors. Agencies that collect data in their normal course of business, such as state motor vehicle registries and the IRS, but are not directly in the data business. • Investigators. Agencies that collect data about suspects as part of law enforcement investigations, such as the FBI and local police


pages: 396 words: 117,149

The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World by Pedro Domingos

Albert Einstein, Amazon Mechanical Turk, Arthur Eddington, basic income, Bayesian statistics, Benoit Mandelbrot, bioinformatics, Black Swan, Brownian motion, cellular automata, Claude Shannon: information theory, combinatorial explosion, computer vision, constrained optimization, correlation does not imply causation, creative destruction, crowdsourcing, Danny Hillis, data is the new oil, double helix, Douglas Hofstadter, Erik Brynjolfsson, experimental subject, Filter Bubble, future of work, global village, Google Glasses, Gödel, Escher, Bach, information retrieval, job automation, John Markoff, John Snow's cholera map, John von Neumann, Joseph Schumpeter, Kevin Kelly, lone genius, mandelbrot fractal, Mark Zuckerberg, Moneyball by Michael Lewis explains big data, Narrative Science, Nate Silver, natural language processing, Netflix Prize, Network effects, NP-complete, off grid, P = NP, PageRank, pattern recognition, phenotype, planetary scale, pre–internet, random walk, Ray Kurzweil, recommendation engine, Richard Feynman, scientific worldview, Second Machine Age, self-driving car, Silicon Valley, social intelligence, speech recognition, Stanford marshmallow experiment, statistical model, Stephen Hawking, Steven Levy, Steven Pinker, superintelligent machines, the scientific method, The Signal and the Noise by Nate Silver, theory of mind, Thomas Bayes, transaction costs, Turing machine, Turing test, Vernor Vinge, Watson beat the top human players on Jeopardy!, white flight, zero-sum game

The same dynamic happens in any market where there’s lots of choice and lots of data. The race is on, and whoever learns fastest wins. It doesn’t stop with understanding customers better: companies can apply machine learning to every aspect of their operations, provided data is available, and data is pouring in from computers, communication devices, and ever-cheaper and more ubiquitous sensors. “Data is the new oil” is a popular refrain, and as with oil, refining it is big business. IBM, as well plugged into the corporate world as anyone, has organized its growth strategy around providing analytics to companies. Businesses look at data as a strategic asset: What data do I have that my competitors don’t? How can I take advantage of it? What data do my competitors have that I don’t? In the same way that a bank without databases can’t compete with a bank that has them, a company without machine learning can’t keep up with one that uses it.


pages: 421 words: 110,406

Platform Revolution: How Networked Markets Are Transforming the Economy--And How to Make Them Work for You by Sangeet Paul Choudary, Marshall W. van Alstyne, Geoffrey G. Parker

3D printing, Affordable Care Act / Obamacare, Airbnb, Alvin Roth, Amazon Mechanical Turk, Amazon Web Services, Andrei Shleifer, Apple's 1984 Super Bowl advert, autonomous vehicles, barriers to entry, big data - Walmart - Pop Tarts, bitcoin, blockchain, business cycle, business process, buy low sell high, chief data officer, Chuck Templeton: OpenTable:, clean water, cloud computing, connected car, corporate governance, crowdsourcing, data acquisition, data is the new oil, digital map, discounted cash flows, disintermediation, Edward Glaeser, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, financial innovation, Haber-Bosch Process, High speed trading, information asymmetry, Internet of things, inventory management, invisible hand, Jean Tirole, Jeff Bezos, jimmy wales, John Markoff, Khan Academy, Kickstarter, Lean Startup, Lyft, Marc Andreessen, market design, Metcalfe’s law, multi-sided market, Network effects, new economy, payday loans, peer-to-peer lending, Peter Thiel, pets.com, pre–internet, price mechanism, recommendation engine, RFID, Richard Stallman, ride hailing / ride sharing, Robert Metcalfe, Ronald Coase, Satoshi Nakamoto, self-driving car, shareholder value, sharing economy, side project, Silicon Valley, Skype, smart contracts, smart grid, Snapchat, software is eating the world, Steve Jobs, TaskRabbit, The Chicago School, the payments system, Tim Cook: Apple, transaction costs, Travis Kalanick, two-sided market, Uber and Lyft, Uber for X, uber lyft, winner-take-all economy, zero-sum game, Zipcar

As of 2011, there were more than three thousand games on Facebook, collectively weakening Zynga’s individual bargaining power.20 The startup’s response may be to sell, to fight back through multihoming, or to expand into other business arenas. Zynga, for example, now multihomes on Tencent’s QQ social network and on the Apple and Google mobile platforms, as well as offering its own cloud service. HOW PLATFORMS COMPETE (3): LEVERAGING THE VALUE OF DATA One of the clichés of the Internet economy is the saying “Data is the new oil”—and like most clichés, it contains a lot of truth. Data can be a source of enormous value to platform businesses, and well-run firms are using data to shore up their competitive positions in a wide variety of ways. Platform businesses can use data to improve their competitive performance in two general ways—tactically and strategically. An example of tactical data use is in the performance of A/B testing, to optimize particular tools or features of the platform.


pages: 497 words: 144,283

Connectography: Mapping the Future of Global Civilization by Parag Khanna

"Robert Solow", 1919 Motor Transport Corps convoy, 2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 9 dash line, additive manufacturing, Admiral Zheng, affirmative action, agricultural Revolution, Airbnb, Albert Einstein, amateurs talk tactics, professionals talk logistics, Amazon Mechanical Turk, Asian financial crisis, asset allocation, autonomous vehicles, banking crisis, Basel III, Berlin Wall, bitcoin, Black Swan, blockchain, borderless world, Boycotts of Israel, Branko Milanovic, BRICs, British Empire, business intelligence, call centre, capital controls, charter city, clean water, cloud computing, collateralized debt obligation, commoditize, complexity theory, continuation of politics by other means, corporate governance, corporate social responsibility, credit crunch, crony capitalism, crowdsourcing, cryptocurrency, cuban missile crisis, data is the new oil, David Ricardo: comparative advantage, deglobalization, deindustrialization, dematerialisation, Deng Xiaoping, Detroit bankruptcy, digital map, disruptive innovation, diversification, Doha Development Round, edge city, Edward Snowden, Elon Musk, energy security, Ethereum, ethereum blockchain, European colonialism, eurozone crisis, failed state, Fall of the Berlin Wall, family office, Ferguson, Missouri, financial innovation, financial repression, fixed income, forward guidance, global supply chain, global value chain, global village, Google Earth, Hernando de Soto, high net worth, Hyperloop, ice-free Arctic, if you build it, they will come, illegal immigration, income inequality, income per capita, industrial cluster, industrial robot, informal economy, Infrastructure as a Service, interest rate swap, Intergovernmental Panel on Climate Change (IPCC), Internet of things, Isaac Newton, Jane Jacobs, Jaron Lanier, John von Neumann, Julian Assange, Just-in-time delivery, Kevin Kelly, Khyber Pass, Kibera, Kickstarter, LNG terminal, low cost airline, low cost carrier, low earth orbit, manufacturing employment, mass affluent, mass immigration, megacity, Mercator projection, Metcalfe’s law, microcredit, mittelstand, Monroe Doctrine, mutually assured destruction, New Economic Geography, new economy, New Urbanism, off grid, offshore financial centre, oil rush, oil shale / tar sands, oil shock, openstreetmap, out of africa, Panamax, Parag Khanna, Peace of Westphalia, peak oil, Pearl River Delta, Peter Thiel, Philip Mirowski, plutocrats, Plutocrats, post-oil, post-Panamax, private military company, purchasing power parity, QWERTY keyboard, race to the bottom, Rana Plaza, rent-seeking, reserve currency, Robert Gordon, Robert Shiller, Robert Shiller, Ronald Coase, Scramble for Africa, Second Machine Age, sharing economy, Shenzhen was a fishing village, Silicon Valley, Silicon Valley startup, six sigma, Skype, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, South China Sea, South Sea Bubble, sovereign wealth fund, special economic zone, spice trade, Stuxnet, supply-chain management, sustainable-tourism, TaskRabbit, telepresence, the built environment, The inhabitant of London could order by telephone, sipping his morning tea in bed, the various products of the whole earth, Tim Cook: Apple, trade route, transaction costs, UNCLOS, uranium enrichment, urban planning, urban sprawl, WikiLeaks, young professional, zero day

Whether these governments seek to monitor, filter, or protect digital flows, the geographic (and legal) location of servers, cables, routers, and data centers now matters as much as the geography of oil pipelines. The differences are crucial, however. Internet data can be replicated infinitely and exist in multiple places at the same time. Additionally, it can be rerouted or smuggled “in” to its destination, while the receiver has the ability to come “out” as well to access it. If data is the new oil, it is certainly much more slippery. It is true that the Internet is no longer a truly borderless, parallel universe. Even Twitter, the world’s most free and unfiltered medium of one-to-many expression, preemptively restricts content banned in various countries, while Google Maps loads tailored maps approved by national authorities based on the user’s server location. Yet even if software or data services have to be customized to national restrictions such as after the EU’s 2015 decision invalidating the “Safe Harbor” agreement with the United States, these represent only partial frictions, not blockages.