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pages: 343 words: 91,080

Uberland: How Algorithms Are Rewriting the Rules of Work by Alex Rosenblat

"side hustle", Affordable Care Act / Obamacare, Airbnb, Amazon Mechanical Turk, autonomous vehicles, barriers to entry, basic income, big-box store, call centre, cashless society, Cass Sunstein, choice architecture, collaborative economy, collective bargaining, creative destruction, crowdsourcing, disruptive innovation, don't be evil, Donald Trump, en.wikipedia.org, future of work, gender pay gap, gig economy, Google Chrome, income inequality, information asymmetry, Jaron Lanier, job automation, job satisfaction, Lyft, marginal employment, Mark Zuckerberg, move fast and break things, Network effects, new economy, obamacare, performance metric, Peter Thiel, price discrimination, Ralph Waldo Emerson, regulatory arbitrage, ride hailing / ride sharing, self-driving car, sharing economy, Silicon Valley, Silicon Valley ideology, Skype, social software, stealth mode startup, Steve Jobs, strikebreaker, TaskRabbit, Tim Cook: Apple, transportation-network company, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, union organizing, universal basic income, urban planning, Wolfgang Streeck, Zipcar

The latter publications are reproduced in part and cited throughout the text of this book, with the permission of my coauthors. APPENDIX TWO RIDEHAILING BEYOND UBER Meet Lyft, the Younger Twin Uber may be the dominant player on the ridehail stage, but many Uber drivers work simultaneously for Lyft and other competitors. Lyft was founded in 2012 in the United States: by 2017, it had become available in forty states.1 Lyft achieved an $11 billion valuation by the fall of 2017.2 Recode reported that Second Measure, a research firm that tracks credit card purchases, determined that Lyft had 23.4 percent of the ridehail market share in the United States and Uber had 74.3 percent.3 The corporate practices of Uber and Lyft in managing drivers aren’t identical, but their similarities vastly outnumber their differences. They both track drivers’ ride-acceptance and cancellation rates.

Still not defining active, Lyft says its active drivers increased to 700,000 by November 2017. Yet Uber and Lyft are so similar in the ways their drivers are dispatched, evaluated, and managed that drivers often treat them interchangeably, to the point where some get confused in describing their Uber or Lyft experiences. A driver might be frustrated at Uber for not respecting a rule set by Lyft, for example, but for the most part this ambiguity centers on issues of pay, safety, and policies. For example, both services use an algorithm to raise prices in times of high demand, but Uber calls this a “surge” while Lyft calls it “prime time.” Even in an Uber-dominated ecosystem, Lyft is part of the equation; I even heard about it from drivers in Canada, where Lyft launched its first operations in Toronto at the end of 2017. Among most drivers I meet in person, and the countless number I’ve observed in online forums, there is a near-universal consensus that Lyft treats its drivers better than Uber, such as through friendlier communications.

Uber is important not only as a company but also as a political scapegoat for unwashed feelings people have about technology and society. In my travels, some regional differences have emerged over time in how drivers assess Uber and Lyft. In Salt Lake City, Lyft seems to offer enough work that drivers don’t need to seek work from more than one company. When drivers choose to work for Lyft, it’s not necessarily out of an antipathy they developed toward Uber. And in Atlanta, Nicholas Stewart told me he prefers to drive for Uber over Lyft because “they’ve been more loyal to me, so to speak.” He went on to say, “I know a lot of the management team. And, when I need an issue solved, it’s easier to get in touch with Uber than it is to get in touch with Lyft. They have more on-the-ground support than Lyft. That’s been frustrating not only for me but a lot of other drivers as well.” Notes INTRODUCTION 1. An investigation by Bloomberg reporter Eric Newcomer found drivers setting up to sleep in parking lots all over the country.


pages: 265 words: 69,310

What's Yours Is Mine: Against the Sharing Economy by Tom Slee

4chan, Airbnb, Amazon Mechanical Turk, asset-backed security, barriers to entry, Berlin Wall, big-box store, bitcoin, blockchain, citizen journalism, collaborative consumption, congestion charging, Credit Default Swap, crowdsourcing, data acquisition, David Brooks, don't be evil, gig economy, Hacker Ethic, income inequality, informal economy, invisible hand, Jacob Appelbaum, Jane Jacobs, Jeff Bezos, Khan Academy, Kibera, Kickstarter, license plate recognition, Lyft, Marc Andreessen, Mark Zuckerberg, move fast and break things, move fast and break things, natural language processing, Netflix Prize, Network effects, new economy, Occupy movement, openstreetmap, Paul Graham, peer-to-peer, peer-to-peer lending, Peter Thiel, pre–internet, principal–agent problem, profit motive, race to the bottom, Ray Kurzweil, recommendation engine, rent control, ride hailing / ride sharing, sharing economy, Silicon Valley, Snapchat, software is eating the world, South of Market, San Francisco, TaskRabbit, The Nature of the Firm, Thomas L Friedman, transportation-network company, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, ultimatum game, urban planning, WikiLeaks, winner-take-all economy, Y Combinator, Zipcar

Gambetta, Diego, and Michael Bacharach. “Trust in Signs.” In Trust in Society, 148–84, n.d. Gannes, Liz. “Competition Brings Lyft, Sidecar and Uber Closer to Cloning Each Other.” AllThingsD. Accessed May 22, 2015. http://allthingsd.com/20131116/competition-brings-lyft-sidecar-and-uber-closer-to-cloning-each-other-and-cabs/. ———. “Lyft Sells Zimride Carpool Service to Rental-Car Giant Enterprise.” AllThingsD, July 12, 2013. http://allthingsd.com/20130712/lyft-sells-zimride-carpool-service-to-rental-car-giant-enterprise/. ———. “Zimride Turns Regular Cars Into Taxis With New Ride-Sharing App, Lyft,” May 22, 2012. http://allthingsd.com/20120522/zimride-turns-regular-cars-into-taxis-with-new-ride-sharing-app-lyft/. Gans, Joshua. “Is Uber Really in a Fight to the Death?” Digitopoly, November 25, 2014. http://www.digitopoly.org/2014/11/25/is-uber-really-in-a-fight-to-the-death/.

Chapter 4 1 Shaheen, “Transportation Network Companies and Ridesourcing.” 2 Gansky, The Mesh: Why the Future of Business Is Sharing. 3 Bardhi and Eckhardt, “Access-Based Consumption: The Case of Car Sharing.” 4 University of Chicago Press Journals, “Sharing Isn’t Always Caring.” 5 Kell, “Avis to Buy Car-Sharing Service Zipcar.” 6 Zipcar, “Green Benefits.” 7 Sadowski, “Hey, Ride-Sharing Services. Stop Greenwashing!” 8 Schor, “Debating the Sharing Economy.” 9 Gannes, “Zimride Turns Regular Cars Into Taxis With New Ride-Sharing App, Lyft.” 10 Gustin, “Lyft-Off: Car-Sharing Start-Up Raises $60 Million Led by Andreessen Horowitz.” 11 Ibid. 12 Gannes, “Zimride Turns Regular Cars Into Taxis With New Ride-­Sharing App, Lyft.” 13 Gannes, “Lyft Sells Zimride Carpool Service to Rental-Car Giant Enterprise.” 14 Gannes, “Competition Brings Lyft, Sidecar and Uber Closer to Cloning Each Other.” 15 Lawler, “A Look Inside Lyft’s Financial Forecast For 2015 And Beyond.” 16 D’Onfro, “Uber CEO Founded The Company Because He Wanted To Be A ‘Baller In San Francisco.’” 17 Meelen and Frenken, “Stop Saying Uber Is Part Of The Sharing ­Economy.” 18 Scola, “The Black Car Company That People Love to Hate.” 19 Kalanick, “Uber Policy White Paper 1.0.” 20 Hall and Krueger, “An Analysis of the Labor Market for Uber’s Driver-Partners in the United States.” 21 Geron, “California Becomes First State To Regulate Ridesharing Services Lyft, Sidecar, UberX.” 22 Ferguson, “Recent Transportation Network Company Ordinances.” 23 California Public Utilities Commission, “Transportation Network Companies.” 24 Hirsch, “Taxi Trouble.” 25 Watters, “The MOOC Revolution That Wasn’t.” 26 Trafford, “Is John Tory Facing an Uber Battle at City Hall?”

But there were limits to the number of inter-city rides that students would take, and Zimride had bigger ambitions. In 2012, Zimride launched Lyft, an app that paired riders and passengers for short-distance rides (within a city, rather than between cities).9 The idea sounds like a carpool ride-matching service, but Lyft made another decision to scale up their offering: it made it possible for drivers to earn enough on a ride that they would undertake journeys that they would not otherwise take. Instead of picking up someone who is going their way and sharing the expenses of the journey (as in carpooling), Lyft drivers would find out where your rider wanted to go and take them there (for money). At first, Lyft maintained its community feel. Lyft cars were identified by a large and kind-of-corny big pink moustache. Riders were expected to sit up front, and rides would start with a fist-bump: quite a different practice compared to traditional North American taxi rides.


pages: 373 words: 112,822

The Upstarts: How Uber, Airbnb, and the Killer Companies of the New Silicon Valley Are Changing the World by Brad Stone

Affordable Care Act / Obamacare, Airbnb, Amazon Web Services, Andy Kessler, autonomous vehicles, Ben Horowitz, Boris Johnson, Burning Man, call centre, Chuck Templeton: OpenTable:, collaborative consumption, East Village, fixed income, Google X / Alphabet X, housing crisis, inflight wifi, Jeff Bezos, Justin.tv, Kickstarter, Lyft, Marc Andreessen, Mark Zuckerberg, Menlo Park, Mitch Kapor, Necker cube, obamacare, Paul Graham, peer-to-peer, Peter Thiel, race to the bottom, rent control, ride hailing / ride sharing, Ruby on Rails, Sand Hill Road, self-driving car, semantic web, sharing economy, side project, Silicon Valley, Silicon Valley startup, Skype, South of Market, San Francisco, Startup school, Steve Jobs, TaskRabbit, Tony Hsieh, transportation-network company, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, ubercab, Y Combinator, Y2K, Zipcar

“Lyft Will Launch in Brooklyn & Queens,” Lyft Blog, July 8, 2014, https://blog.lyft.com/posts/2014/7/8/lyft-launches-in-new-yorks-outer-boroughs. 26. Brady Dale, “Lyft Launch Party with Q-Tip, Without Actually Launching,” Technical.ly Brooklyn, July 14, 2014, http://technical.ly/brooklyn/2014/07/14/lyft-brooklyn-launches/. 27. “Lyft Launches in NYC,” Lyft Blog, July 25, 2014, https://blog.lyft.com/posts/2014/7/25/lyft-launches-in-nyc. 28. Casey Newton, “This Is Uber’s Playbook for Sabotaging Lyft,” Verge, August 26, 2014, http://www.theverge.com/2014/8/26/6067663/this-is-ubers-playbook-for-sabotaging-lyft. 29. In September 2012, I washed cars for the Cherry service in San Francisco and was mentored and reviewed by an older washer, Kenny Chen. “Brad needs to look out for traffic,” he wrote; Brad Stone, “My Life as a TaskRabbit,” Bloomberg.com, September 13, 2012, http://www.bloomberg.com/news/articles/2012-09-13/my-life-as-a-taskrabbit. 30.

retorted Kalanick, who later couldn’t recall whether he was joking or if he had been responding to an actual rumor. For a brief period in 2014, Lyft had been ready to throw in the towel, and representatives approached Uber about combining the companies. Kalanick and Emil Michael went to dinner with Lyft president John Zimmer and Andreessen Horowitz partner John O’Farrell to discuss a deal, according to three people who were privy to the conversations. The meal was friendly, despite the heated rivalry. But Lyft’s expectations were high. In exchange for selling Lyft to Uber, Lyft’s backers wanted an 18 percent stake in Uber. Uber offered 8 percent; Kalanick wasn’t a fan of mergers to begin with and wasn’t about to hand over a fifth of his prize. Neither party would budge, and the talks fell apart. Lyft recovered quickly. That spring, with unconventional sources of capital now flooding into Silicon Valley, it raised $250 million from a consortium of investors that included hedge fund Coatue Management, Chinese e-commerce giant Alibaba, and the Founders Fund, the investment vehicle of PayPal co-founder Peter Thiel, and it expanded into twenty-four new U.S. cities, thirteen of which were midsize markets where Uber did not yet operate.21 The battle was on again.

“We feel Lyft is coming in here to take us out of business,” Nancy Soria of the New York Association of Independent Taxi Drivers told the tech blog Technical.ly.26 Later that night, Zimmer and Estrada heard the TLC was preparing an injunction. On a conference call with general counsel Kristin Sverchek and Lyft’s outside lawyer, an impassioned Zimmer argued that they should go ahead anyway and wanted to get himself arrested for the cause. The lawyers laughed—but he was serious. Together they persuaded him that it would be a bad idea. “I don’t want to think about you in jail,” Sverchek told him. “It’s not something I can stomach.” Backed into a corner, Lyft caved. For the first time in its history, Lyft introduced a service using professional drivers instead of regular people driving their own cars.27 In New York, Lyft would look like the original incarnation of Uber, deploying only licensed drivers. From there the battle between Uber and Lyft devolved further. In public, they accused each other of slogging—ordering and canceling rides and proffering rewards to each other’s drivers to defect.28 In private, an even more rancorous struggle played out.


pages: 444 words: 127,259

Super Pumped: The Battle for Uber by Mike Isaac

"side hustle", activist fund / activist shareholder / activist investor, Airbnb, Albert Einstein, always be closing, Amazon Web Services, Andy Kessler, autonomous vehicles, Ayatollah Khomeini, barriers to entry, Bay Area Rapid Transit, Burning Man, call centre, Chris Urmson, Chuck Templeton: OpenTable:, citizen journalism, Clayton Christensen, cloud computing, corporate governance, creative destruction, don't be evil, Donald Trump, Elon Musk, family office, gig economy, Google Glasses, Google X / Alphabet X, high net worth, Jeff Bezos, John Markoff, Kickstarter, Lyft, Marc Andreessen, Mark Zuckerberg, mass immigration, Menlo Park, Mitch Kapor, money market fund, moral hazard, move fast and break things, move fast and break things, Network effects, new economy, off grid, peer-to-peer, pets.com, Richard Florida, ride hailing / ride sharing, Sand Hill Road, self-driving car, shareholder value, side project, Silicon Valley, Silicon Valley startup, skunkworks, Snapchat, software as a service, software is eating the world, South China Sea, South of Market, San Francisco, sovereign wealth fund, special economic zone, Steve Jobs, TaskRabbit, the payments system, Tim Cook: Apple, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, ubercab, union organizing, upwardly mobile, Y Combinator

Zimmer would soon get a call from the investor, apologizing and backing out of Lyft’s latest series. Wherever Lyft went, Uber showed up to harass them. One of Lyft’s most effective grassroots tactics was holding what they called “driver events,” small parties for a hundred people that Lyft was trying to court as drivers. These events—replete with booze, pizza, cakes, and party games—often endeared the drivers to Lyft; people who attended them felt like the company actually cared about them. Kalanick made sure to ruin those for Lyft, too. He’d send his own employees to the events, where they would show up in jet black T-shirts—Uber’s signature color—carrying plates filled with cookies, each with the word “Uber” written in icing. Each Uber employee had a referral code printed on the back of their T-shirt. The codes were for Lyft drivers to enter when they signed up for Uber, earning them a bonus.

Kalanick began to sweat. Lyft, at that point running out of money and on the verge of surrender, benefitted enormously from the backlash. People began to ditch Uber and switch over to Lyft. (Protest felt good, but people still needed to be able to call a car sometimes.) Lyft’s executives then pulled a well-executed PR stunt, publicly donating $1 million to the American Civil Liberties Union over four years, making themselves look like white knights while Uber was groveling before Trump. The resultant surge in ridership brought Lyft back from the brink of failure. At last showing positive signs of growth, Lyft soon attracted investment from Kohlberg Kravis Roberts, the private equity firm, buoying the ride-hailing company with more than a half-billion dollars in additional capital. Lyft’s fundraising sunk Kalanick’s spirits.

“They’re breaking the law!” Geidt and Graves said to the indifferent regulators. Though Sunil Paul’s efforts with Sidecar weren’t taking off, Lyft was gaining traction quickly. People loved the stupid pink mustaches. In theory, regulators were against Lyft’s antics; after all, the company was breaking rules. Uber had been recruiting drivers for some time, but within limits; all of Uber’s drivers were licensed livery vehicle operators registered with local transportation offices. Lyft turned that on its head. The mustachioed startup invited anyone with a car and an ordinary Class C driver’s license to start driving for Lyft. But as one Uber employee competing with Lyft at the time said, “The law isn’t what is written. It’s what is enforced.” To Kalanick’s dismay, SF transit authorities weren’t enforcing a damn thing.


pages: 190 words: 62,941

Wild Ride: Inside Uber's Quest for World Domination by Adam Lashinsky

"side hustle", Airbnb, always be closing, Amazon Web Services, autonomous vehicles, Ayatollah Khomeini, business process, Chuck Templeton: OpenTable:, cognitive dissonance, corporate governance, DARPA: Urban Challenge, Donald Trump, Elon Musk, gig economy, Golden Gate Park, Google X / Alphabet X, information retrieval, Jeff Bezos, Lyft, Marc Andreessen, Mark Zuckerberg, megacity, Menlo Park, new economy, pattern recognition, price mechanism, ride hailing / ride sharing, Sand Hill Road, self-driving car, Silicon Valley, Silicon Valley startup, Skype, Snapchat, South of Market, San Francisco, sovereign wealth fund, statistical model, Steve Jobs, TaskRabbit, Tony Hsieh, transportation-network company, Travis Kalanick, turn-by-turn navigation, Uber and Lyft, Uber for X, uber lyft, ubercab, young professional

Sharing was a misnomer, given that Lyft’s drivers were out to make a buck every bit as much as Uber’s. But by promoting the fiction of a friendly gesture rather than a transaction, Lyft could make an argument, however thin, that its trips weren’t commercial. If so, Lyft reasoned they weren’t illegal taxi rides and didn’t fall under any regulator’s jurisdiction. In reality, Uber worked only with licensed livery drivers; Lyft’s drivers were freelancing amateurs. Yet Lyft had one critical similarity with Uber in that its smartphone app adopted the push-a-button/get-a-ride simplicity that catapulted Uber into the limelight. The two companies were a study in contrasts, especially in their origins. Uber grew out of the San Francisco “brogrammer” culture and Garrett Camp’s delight in rolling in style. Lyft sprang from the idealistic mind of Logan Green, who’d served on the Santa Barbara, California, public transit board when he was a university student in that seaside town.

If investment hurt potential profitability, competition was a much bigger problem. During the first week of 2016 Uber’s primary competitor in the United States, Lyft, announced a partnership with and investment by General Motors. GM agreed to invest $500 million, with plans to build its self-driving car capacity on the strength of Lyft’s national network. Lyft gave GM a seat at the technology table. GM provided Lyft with money, which it promptly began using to take market share from Uber in crucial markets, including San Francisco and Los Angeles. Lyft’s market share in major markets typically had been around 20 percent. In early 2016, with Uber attempting to squeeze costs out of its operations, Lyft began taking share, growing its share to as much as 37 percent, by Uber’s calculations, in San Francisco. With similar products, market share was simply a function of price.

Uber owned up to “Operation SLOG,” saying its recruitment drive was fair competition. But after allowing Lyft to build one new market under its nose, Uber was ever vigilant about not letting it happen again. Both companies maintained a constant dialogue with their drivers, aiming to refine their offerings as well as to glean competitive intelligence. When Uber caught wind around the same time that Lyft was about to launch a carpooling service, Lyft Line, Uber announced UberPool, its own carpool product, the night before. Lyft would prove a stubborn number two. It raised first tens of millions, then hundreds of millions of dollars. Its most prominent early backer was Andreessen Horowitz, the same firm that had snubbed Uber in 2011. Lyft would continue to feel stymied by Uber, and not just in the competition for riders.


pages: 375 words: 88,306

The Sharing Economy: The End of Employment and the Rise of Crowd-Based Capitalism by Arun Sundararajan

additive manufacturing, Airbnb, AltaVista, Amazon Mechanical Turk, autonomous vehicles, barriers to entry, basic income, bitcoin, blockchain, Burning Man, call centre, collaborative consumption, collaborative economy, collective bargaining, commoditize, corporate social responsibility, cryptocurrency, David Graeber, distributed ledger, employer provided health coverage, Erik Brynjolfsson, Ethereum, ethereum blockchain, Frank Levy and Richard Murnane: The New Division of Labor, future of work, George Akerlof, gig economy, housing crisis, Howard Rheingold, information asymmetry, Internet of things, inventory management, invisible hand, job automation, job-hopping, Kickstarter, knowledge worker, Kula ring, Lyft, Marc Andreessen, megacity, minimum wage unemployment, moral hazard, moral panic, Network effects, new economy, Oculus Rift, pattern recognition, peer-to-peer, peer-to-peer lending, peer-to-peer model, peer-to-peer rental, profit motive, purchasing power parity, race to the bottom, recommendation engine, regulatory arbitrage, rent control, Richard Florida, ride hailing / ride sharing, Robert Gordon, Ronald Coase, Ross Ulbricht, Second Machine Age, self-driving car, sharing economy, Silicon Valley, smart contracts, Snapchat, social software, supply-chain management, TaskRabbit, The Nature of the Firm, total factor productivity, transaction costs, transportation-network company, two-sided market, Uber and Lyft, Uber for X, uber lyft, universal basic income, Zipcar

Might the same hold true for our future regulatory structures? Lyft—Hospitality in Transportation A few blocks down the street from Airbnb’s shiny new corporate headquarters at 888 Brannan in San Francisco’s SoMa district is a small building at 568 Brannan, the site of Lyft’s original offices. In it’s simplest form, Lyft is a chauffeured car, on demand. You open the app, you tell it where you are, it shows you cars nearby, you request a car, and you get picked up in a few minutes. In a more sophisticated use case, you turn on your Lyft app when you drive to work, put in your destination, and others who might want to travel a similar route can pay you a little for a seat in your car. Carpooling on demand, but flexibly, on your own schedule. Over the years, my Lyft drivers have included stand-up comedians, software engineers, deejays, schoolteachers, a retired CIO, a digital marketing executive between jobs, and numerous college students.

(Noticing the branded corporate swag I was carrying from a different company at the end of our meeting, Emily grabbed one of these pink mustaches from an office cabinet and tossed it to me before I left. It is still in my office, and has attracted many a puzzled look from my students over the years.) My first Lyft driver was an artist who was driving her car to earn some extra money while she pursued her art. There was no formal fare in 2012, since Lyft was not yet legally allowed to offer “taxi” service, but instead, the app suggested a “donation” to my driver in exchange for her being nice enough to come to where I was, pick me up, and give me a ride. A high point of the visit was the opportunity I got to try on a Lyft employee’s Halloween costume. He had dressed up as a Lyft car, using a skillfully constructed cardboard contraption. Three years later, Lyft had raised over a billion dollars in venture capital (including $100 million from the legendary investor Carl Icahn) and was in 60 cities around the United States.

Over the years, my Lyft drivers have included stand-up comedians, software engineers, deejays, schoolteachers, a retired CIO, a digital marketing executive between jobs, and numerous college students. Taking a Lyft is a completely different customer experience from hailing a cab. You sit in the front seat and have a conversation with a peer. It is like getting a ride with a new acquaintance. I visited Lyft at 568 Brannan in fall 2012 at the invitation of Emily Castor, an early employee who is currently their self-described “resident transportation wonk,” and who was kind enough back then to accelerate my approval as a Lyft passenger so that I could use their service to get to the meeting. The car that came to pick me up was instantly recognizable, adorned with Lyft’s giant pink mustache. (Noticing the branded corporate swag I was carrying from a different company at the end of our meeting, Emily grabbed one of these pink mustaches from an office cabinet and tossed it to me before I left.


pages: 561 words: 157,589

WTF?: What's the Future and Why It's Up to Us by Tim O'Reilly

4chan, Affordable Care Act / Obamacare, Airbnb, Alvin Roth, Amazon Mechanical Turk, Amazon Web Services, artificial general intelligence, augmented reality, autonomous vehicles, barriers to entry, basic income, Bernie Madoff, Bernie Sanders, Bill Joy: nanobots, bitcoin, blockchain, Bretton Woods, Brewster Kahle, British Empire, business process, call centre, Capital in the Twenty-First Century by Thomas Piketty, Captain Sullenberger Hudson, Chuck Templeton: OpenTable:, Clayton Christensen, clean water, cloud computing, cognitive dissonance, collateralized debt obligation, commoditize, computer vision, corporate governance, corporate raider, creative destruction, crowdsourcing, Danny Hillis, data acquisition, deskilling, DevOps, Donald Davies, Donald Trump, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Filter Bubble, Firefox, Flash crash, full employment, future of work, George Akerlof, gig economy, glass ceiling, Google Glasses, Gordon Gekko, gravity well, greed is good, Guido van Rossum, High speed trading, hiring and firing, Home mortgage interest deduction, Hyperloop, income inequality, index fund, informal economy, information asymmetry, Internet Archive, Internet of things, invention of movable type, invisible hand, iterative process, Jaron Lanier, Jeff Bezos, jitney, job automation, job satisfaction, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Kevin Kelly, Khan Academy, Kickstarter, knowledge worker, Kodak vs Instagram, Lao Tzu, Larry Wall, Lean Startup, Leonard Kleinrock, Lyft, Marc Andreessen, Mark Zuckerberg, market fundamentalism, Marshall McLuhan, McMansion, microbiome, microservices, minimum viable product, mortgage tax deduction, move fast and break things, move fast and break things, Network effects, new economy, Nicholas Carr, obamacare, Oculus Rift, packet switching, PageRank, pattern recognition, Paul Buchheit, peer-to-peer, peer-to-peer model, Ponzi scheme, race to the bottom, Ralph Nader, randomized controlled trial, RFC: Request For Comment, Richard Feynman, Richard Stallman, ride hailing / ride sharing, Robert Gordon, Robert Metcalfe, Ronald Coase, Sam Altman, school choice, Second Machine Age, secular stagnation, self-driving car, SETI@home, shareholder value, Silicon Valley, Silicon Valley startup, skunkworks, Skype, smart contracts, Snapchat, Social Responsibility of Business Is to Increase Its Profits, social web, software as a service, software patent, spectrum auction, speech recognition, Stephen Hawking, Steve Ballmer, Steve Jobs, Steven Levy, Stewart Brand, strong AI, TaskRabbit, telepresence, the built environment, The Future of Employment, the map is not the territory, The Nature of the Firm, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, Thomas Davenport, transaction costs, transcontinental railway, transportation-network company, Travis Kalanick, trickle-down economics, Uber and Lyft, Uber for X, uber lyft, ubercab, universal basic income, US Airways Flight 1549, VA Linux, Watson beat the top human players on Jeopardy!, We are the 99%, web application, Whole Earth Catalog, winner-take-all economy, women in the workforce, Y Combinator, yellow journalism, zero-sum game, Zipcar

In 2007 Logan Green and John Zimmer had founded a peer-to-peer service called Zimride, which was focused on matching drivers and passengers for long intercity rides. In 2012, Sunil’s work inspired them to launch a new service, called Lyft, which offered the first public peer-to-peer ride-sharing service for local pickup not by professional drivers, but by “your friend with a car.” Sunil, late to the party despite being way early, launched Sidecar at about the same time. (It was still in private beta when Lyft launched publicly.) But by the time Sidecar went out to raise money, Uber and Lyft had already built huge venture capital war chests, and Sidecar was unable to compete in a capital-intensive business. It went out of business at the end of 2015. Uber responded to Lyft with UberX, and the ride-sharing landscape as we know it today was born. Lyft has continued to innovate, with Lyft Line (which Uber matched as UberPool), consistent with Zimmer and Green’s original vision to create a modern version of the peer-to-peer public transportation network similar to the one they’d seen during youthful travels in Zimbabwe, and which had inspired them to create first Zimride and then Lyft.

Here’s a possible business model map for Uber or Lyft like the one Dan and Meredith Beam drew for Southwest Airlines. What are some of the core elements of this business model? Replacing Ownership with Access. In the long run, Uber and Lyft are not competing with taxicab companies, but with car ownership. After all, if you can summon a car and driver at low cost via the touch of a button on your phone, why should you bother owning one at all, especially if you live in the city? Uber and Lyft do for car ownership what music services like Spotify did for music CDs, and Netflix and Amazon Prime did for DVDs. They are replacing ownership with access. “I tell people I live in LA like it’s New York. Uber and Lyft are my public transit station,” said one customer in Los Angeles. Uber and Lyft also replace ownership with access for the companies themselves.

Unlike the taxi industry, which creates an artificial scarcity by issuing a limited number of “medallions,” Uber and Lyft use market mechanisms to find the optimum number of drivers, with an algorithm that raises prices if there are not enough drivers on the road in a particular location or at a particular time. While customers initially complained, using market forces to balance the competing desires of buyers and sellers has helped Uber and Lyft to achieve an equilibrium of supply and demand in close to real time. There are other signals in addition to surge pricing that Uber and Lyft use to tell drivers that more (or fewer) of them are needed. Incentives to drivers, especially when entering new cities, has been one reason why Uber and Lyft have had to spend so much money to enter new markets. There are those who equate this behavior to dumping—selling goods and services below cost in order to dominate the market and drive out other sellers, only to raise prices once a monopoly position is earned.


pages: 491 words: 77,650

Humans as a Service: The Promise and Perils of Work in the Gig Economy by Jeremias Prassl

3D printing, Affordable Care Act / Obamacare, Airbnb, Amazon Mechanical Turk, Andrei Shleifer, autonomous vehicles, barriers to entry, call centre, cashless society, Clayton Christensen, collaborative consumption, collaborative economy, collective bargaining, creative destruction, crowdsourcing, disruptive innovation, Donald Trump, Erik Brynjolfsson, full employment, future of work, George Akerlof, gig economy, global supply chain, hiring and firing, income inequality, information asymmetry, invisible hand, Jeff Bezos, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Kickstarter, low skilled workers, Lyft, Mahatma Gandhi, Mark Zuckerberg, market friction, means of production, moral hazard, Network effects, new economy, obamacare, pattern recognition, platform as a service, Productivity paradox, race to the bottom, regulatory arbitrage, remote working, ride hailing / ride sharing, Robert Gordon, Ronald Coase, Rosa Parks, Second Machine Age, secular stagnation, self-driving car, shareholder value, sharing economy, Silicon Valley, Silicon Valley ideology, Simon Singh, software as a service, Steve Jobs, TaskRabbit, The Future of Employment, The Market for Lemons, The Nature of the Firm, The Rise and Fall of American Growth, transaction costs, transportation-network company, Travis Kalanick, two tier labour market, two-sided market, Uber and Lyft, Uber for X, uber lyft, union organizing, working-age population

House of Commons Business, Innovation and Skills Committee, Employment Practices at Sports Direct: 3rd Report of Session 2016/17 (HC 2016–17, 219), 3. 34. ‘Swalwell, Issa announce the Sharing Economy Caucus’, Eric Swalwell press release (12 May 2015), https://swalwell.house.gov/media-center/press-releases/ swalwell-issa-announce-sharing-economy-caucus, archived at https://perma. cc/7SN7-M4XG. Ride platform Lyft was ‘excited to continue that conversa- tion in Washington, D.C.’: ‘Lyft joins Sharing Economy Caucus’, Lyft Blog (13 May 2015), https://blog.lyft.com/posts/2015/5/13/lyft-joins-sharing-economy- caucus, archived at https://perma.cc/875C-N376. It was focused on limiting regulation—not least by ensuring more favourable tax treatment. Other oper- ators similarly called for changes to help ‘participants [who] feel the sting of the taxman when filing season comes around’: John Kartch, ‘Meet the congres- sional Sharing Economy Caucus’, Forbes (15 May 2015), http://www.forbes.

Brhmie Balaram, ‘RSA calls for new approach to regulating the sharing econ- omy’, RSA (13 January 2016), http://www.thersa.org/about-us/media/2016/ rsa-calls-for-new-approach-to-regulating-the-sharing-economy, archived at https://perma.cc/NC5L-2ZH7: ‘But this isn’t the story of David and Goliath in the sharing economy . . . These companies are networked monopolies that depend on the value created by their users to keep expanding.’ 27. Ellen Huet, ‘Lyft buys carpooling startup Hitch to grow Lyft line’, Forbes (22 September 2014), http://www.forbes.com/sites/ellenhuet/2014/09/22/lyft- buys-carpooling-startup-hitch-to-grow-lyft-line/#5bb922452b59, archived at https://perma.cc/5H9D-Q44U; Lora Kolodny, ‘Zimride acquires Cherry but won’t offer car-washing service’, The Wall Street Journal (26 March 2013), http:// blogs.wsj.com/venturecapital/2013/03/26/zimride-acquires-cherry-but- wont-offer-car-washing-service/, archived at https://perma.cc/Z52R-B4K8 28.

We return to a legal analysis of these terms in Chapter 5. 50. Julia Tomassetti, ‘Does Uber redefine the firm? The postindustrial corporation and advanced information technology’ (2016) 34(1) Hofstra Labor and Employment Law Journal 239, 293: Uber and Lyft sublimate their agency in the production of ride services into algo- rithms, programming, and technology management. The metaphor of the ‘platform’ transforms Uber and Lyft from subjects into spaces. It evokes a passive space to be inhabited by active agents—drivers and passengers. For example, Lyft argues that drivers’ ‘low ratings [are] given by passengers, not Lyft. Uber argued that passengers, and not Uber, controlled drivers’ work. The companies ventriloquize a disinterested machine.’ We also encounter more localised terminology, such as discussion of the ‘1099 economy’ in the United States, after the tax form independent workers—and those taking payment for fish in cash (!)


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New Power: How Power Works in Our Hyperconnected World--And How to Make It Work for You by Jeremy Heimans, Henry Timms

"side hustle", 3D printing, 4chan, Affordable Care Act / Obamacare, Airbnb, augmented reality, autonomous vehicles, battle of ideas, Benjamin Mako Hill, bitcoin, blockchain, British Empire, Chris Wanstrath, Columbine, Corn Laws, crowdsourcing, David Attenborough, Donald Trump, Elon Musk, Ferguson, Missouri, future of work, game design, gig economy, hiring and firing, IKEA effect, income inequality, informal economy, job satisfaction, Jony Ive, Kibera, Kickstarter, Lean Startup, Lyft, Mark Zuckerberg, Minecraft, Network effects, new economy, Nicholas Carr, obamacare, Occupy movement, profit motive, race to the bottom, ride hailing / ride sharing, rolodex, Saturday Night Live, sharing economy, Silicon Valley, six sigma, Snapchat, social web, TaskRabbit, the scientific method, transaction costs, Travis Kalanick, Uber and Lyft, uber lyft, upwardly mobile, web application, WikiLeaks

A third was to encourage regular meet-ups for drivers, funded by Lyft, because “the bonds you create with each other strengthen our community, too.” At the same time that Uber’s drivers were turning against the platform to organize pickets, Lyft was helping its drivers organize picnics. Every one of the new initiatives was proudly displayed on the Lyft blog, with a driver credited for each idea, alongside testimonials from Lyft riders, celebrating what great human beings Lyft drivers are. As @rounditrosie wrote, “I love @Lyft drivers because they are artists, bakers, med students, retirees and the coolest people in LA. #ThankYourLyftDriver.” While some of this might feel like sugarcoating on a bitter pill, it worked because Lyft’s instincts so consistently demonstrated new power values. The platform owners were transparent and open to super-participants about the financial challenge they faced.

I think that’s the sense that you get, right from the onset, that Lyft does care.” Campbell explains that Uber seems at pains to keep itself at a distance from the lived experience of their drivers: “Uber actually had a policy where they don’t allow their corporate employees to be Uber drivers, where Lyft is almost the opposite. They highly encourage their employees to be drivers.” Lyft tries to show it cares, too, in how it offers drivers incentives. Lyft has always offered riders the opportunity to tip drivers; Uber only introduced this feature in 2017 under pressure from drivers and besieged by crisis. Lyft also takes a different approach to rewarding their most committed drivers, operating a sliding scale that reduces Lyft’s commission based on how many hours a driver works. The most dedicated, who chalk up fifty hours a week, “basically get your entire commission back.”

“Even with [our] better service”: John Zimmer, “Standing Together: Community Update from John,” The Hub (blog), February 2, 2016. www.thehub.lyft.com “the bonds you create”: Ibid. “I love @Lyft drivers”: Cori Online, “#ThankYourLyftDriver,” Lyft (blog), January 31, 2016. www.blog.lyft.com. “As a new Lyft driver”: Harry Campbell, discussion with authors, February 16, 2016. “basically get your entire commission”: Timothy B. Lee, “Lyft Says Its Drivers Can Make $35 an Hour,” Vox, December 17, 2014. “One of the things that Uber drivers”: Harry Campbell, discussion with authors. “shared norms, values”: Arun Sundararajan, “What Airbnb Gets About Culture That Uber Doesn’t,” Harvard Business Review, November 27, 2014. Other quotes in this paragraph are from the same source. In a 2017 survey: Laura Sydell, “Survey Finds Lyft Drivers Happier Than Uber, Though Pay Has Declined,” NPR, January 21, 2017. To take another example, YouTube’s Partner Program: Todd Spangler, “YouTube Standardizes Ad-Revenue Split for All Partners, but Offers Upside Potential,” Variety, November 1, 2013.


pages: 289

Hustle and Gig: Struggling and Surviving in the Sharing Economy by Alexandrea J. Ravenelle

"side hustle", active transport: walking or cycling, Affordable Care Act / Obamacare, Airbnb, Amazon Mechanical Turk, barriers to entry, basic income, Broken windows theory, call centre, Capital in the Twenty-First Century by Thomas Piketty, cashless society, Clayton Christensen, clean water, collaborative consumption, collective bargaining, creative destruction, crowdsourcing, disruptive innovation, Downton Abbey, East Village, Erik Brynjolfsson, full employment, future of work, gig economy, Howard Zinn, income inequality, informal economy, job automation, low skilled workers, Lyft, minimum wage unemployment, Mitch Kapor, Network effects, new economy, New Urbanism, obamacare, Panopticon Jeremy Bentham, passive income, peer-to-peer, peer-to-peer model, performance metric, precariat, rent control, ride hailing / ride sharing, Ronald Reagan, sharing economy, Silicon Valley, strikebreaker, TaskRabbit, telemarketer, the payments system, Tim Cook: Apple, transaction costs, Travis Kalanick, Triangle Shirtwaist Factory, Uber and Lyft, Uber for X, uber lyft, ubercab, universal basic income, Upton Sinclair, urban planning, very high income, white flight, working poor, Zipcar

Although in many cities Uber partially subsidized the cuts by temporarily reducing the commissions it collected from drivers, that wasn’t the case in New York in July 2014, when Uber continued to collect 20 percent of the reduced fares. While drivers who utilize both platforms often view Lyft more favorably, Lyft has also cut rates—reducing fares nationwide in April 2014 by as much as 30 percent.41 Table 2 shows how some New York City uberX rates have changed. Within four years, uberX drivers saw their per-minute rate cut in half, their mile rate reduced by 42 percent, and their base fare slashed by a whopping 58 percent. The minimum price for a ride decreased by about a third. Table 2 UberX Rates in New York City, 2014 to 2018 In addition to reducing rates, both services have also changed their commissions. When Lyft reduced rates in 2014, it “temporarily eliminated its 20% commission ‘to provide our growing driver community with peace of mind’ during the price drop.”

You don’t want to make the opportunity for crime any easier than it is.”9 In part because Uber and Lyft drivers do not carry cash and are prohibited from picking up street hails in New York or accepting cash payments, there’s an expectation that they’re less likely to be robbed. The lack of protections for drivers also appears to be part of the ethos of the sharing economy, where the app-based invisibility of payment, partnered with user profiles, promotes the idea of trustworthiness and small-town safety. When you request an Uber or Lyft, the company is supposed to have your name, credit card number, billing address, and photo on file—a taxicab driver simply has an anonymous figure on the side of the road. Indeed, as noted earlier, when Lyft, with its motto “Your friend with a car,” began operating, passengers were even encouraged to sit in the front seat, further reducing a driver’s options in case of a dangerous situation.10 However, as I’ve pointed out, the app-based profiles may provide a false sense of security—it’s entirely likely that the information included is fake or otherwise useless, and drivers can still find themselves in situations that they perceive as dangerous and illegal.

Although early sites such as couchsurfing.com and ShareSomeSugar.com didn’t charge fees, most current “sharing economy” sites do charge them. An Airbnb host isn’t so much “sharing” her home or “hosting guests” as she is renting her home out. TaskRabbit assistants and Kitchensurfing chefs aren’t “sharing” their services but being paid. Likewise, even though Uber and Lyft describe themselves as “ride-sharing,” charging for private vehicle transportation is simply a taxi or chauffer service by any other name. While Lyft (slogan: “Your friend with a car”) originally encouraged riders to “sit in the front seat like a friend, rather than in the backseat like a fare,” such “friendship” didn’t eliminate the need to pay the fare.12 The reinvention of terms isn’t limited to the companies themselves but can also carry over into descriptions of the services by researchers.


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Gigged: The End of the Job and the Future of Work by Sarah Kessler

Affordable Care Act / Obamacare, Airbnb, Amazon Mechanical Turk, basic income, bitcoin, blockchain, business cycle, call centre, cognitive dissonance, collective bargaining, crowdsourcing, David Attenborough, Donald Trump, East Village, Elon Musk, financial independence, future of work, game design, gig economy, income inequality, information asymmetry, Jeff Bezos, job automation, law of one price, Lyft, Mark Zuckerberg, market clearing, minimum wage unemployment, new economy, payday loans, post-work, profit maximization, QR code, race to the bottom, ride hailing / ride sharing, Second Machine Age, self-driving car, shareholder value, sharing economy, Silicon Valley, Snapchat, TaskRabbit, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, union organizing, universal basic income, working-age population, Works Progress Administration, Y Combinator

April 27, 2016. http://fortune.com/2016/04/27/uber-gig-economy/. 6   Wartzman, Working in the Gig Economy. 7   Oisin, Hanrahan. We Must Protect the On-Demand Economy to Protect the Future of Work. Wired. November 9, 2015. https://www.wired.com/2015/11/we-must-protect-the-on-demand-economy-to-protect-the-future-of-work/. 8   Lyft Blog. Lyft × Honest Dollar: Introducing Savings and Retirement Solutions for Lyft Drivers. November 19, 2015. https://blog.lyft.com/posts/lyft-x-honest-dollar. 9   Bureau of Labor Statistics. National Compensation Survey: Employee Benefits in the United States, March 2014. September 2014. EPILOGUE 1   Press release. Workers and US Government Cheated Out of Billions in Stolen Wages and Lost Tax Revenue. National Employment Law Project. February 19, 2014. 2   Newton, Casey.

“The much-touted virtues of flexibility, independence and creativity offered by gig work might be true for some workers under some conditions,” she said in a speech at an annual conference for the New America Foundation in Washington, “but for many, the gig economy is simply the next step in a losing effort to build some economic security in a world where all the benefits are floating to the top 10 percent.”21 The speech wasn’t exactly about the gig economy: “The problems facing gig workers are much like the problems facing millions of other workers,” Warren noted. But the headlines were definitely about the gig economy: “Elizabeth Warren Takes on Uber, Lyft and the ‘Gig Economy’”;22 “Elizabeth Warren Calls for Increased Regulations on Uber, Lyft, and the ‘Gig Economy’”;23 “Elizabeth Warren Slams Uber and Lyft.”24 In her speech, Warren had acknowledged that talking about TaskRabbit, Uber, and Lyft was “very hip.” It seemed she was right. Sometimes politicians and labor leaders didn’t even need to frame their positions within the context of the gig economy to have them interpreted that way. The media did it for them. When the Labor Department’s Wage and Hour Division published new guidance on worker classification in July 2015 (which would later be rescinded by the Trump administration), it did not mention Uber.

Harvard Business Review. July 5, 2017. https://hbr.org/2017/07/lots-of-employees-get-misclassified-as-contractors-heres-why-it-matters. 3   Gandel, Stephen. Uber-nomics: Here’s What It Would Cost Uber to Pay Its Drivers as Employees. Fortune. September 17, 2015. http://fortune.com/2015/09/17/ubernomics/. And on Lyft see: Levine, Dan, and Heather Somerville. Lyft Drivers, If Employees, Owed Millions More—Court Documents. Reuters. March 20, 2016. https://www.reuters.com/article/us-lyft-drivers-pay-exclusive/exclusive-lyft-drivers-if-employees-owed-millions-more-court-documents-idUSKCN0WM0NO?feedType=RSS&feedName=technologyNews. 4   Chayka, Kyle. It’s Like Uber for Janitors, with One Huge Difference. Bloomberg. October 9, 2015. https://www.bloomberg.com/news/features/2015-10-09/it-s-like-uber-for-janitors-with-one-big-difference%0A. 5   Kessler, Sarah.


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Peers Inc: How People and Platforms Are Inventing the Collaborative Economy and Reinventing Capitalism by Robin Chase

Airbnb, Amazon Web Services, Andy Kessler, banking crisis, barriers to entry, basic income, Benevolent Dictator For Life (BDFL), bitcoin, blockchain, Burning Man, business climate, call centre, car-free, cloud computing, collaborative consumption, collaborative economy, collective bargaining, commoditize, congestion charging, creative destruction, crowdsourcing, cryptocurrency, decarbonisation, different worldview, do-ocracy, don't be evil, Elon Musk, en.wikipedia.org, Ethereum, ethereum blockchain, Ferguson, Missouri, Firefox, frictionless, Gini coefficient, hive mind, income inequality, index fund, informal economy, Intergovernmental Panel on Climate Change (IPCC), Internet of things, Jane Jacobs, Jeff Bezos, jimmy wales, job satisfaction, Kickstarter, Lean Startup, Lyft, means of production, megacity, Minecraft, minimum viable product, Network effects, new economy, Oculus Rift, openstreetmap, optical character recognition, pattern recognition, peer-to-peer, peer-to-peer lending, peer-to-peer model, Richard Stallman, ride hailing / ride sharing, Ronald Coase, Ronald Reagan, Satoshi Nakamoto, Search for Extraterrestrial Intelligence, self-driving car, shareholder value, sharing economy, Silicon Valley, six sigma, Skype, smart cities, smart grid, Snapchat, sovereign wealth fund, Steve Crocker, Steve Jobs, Steven Levy, TaskRabbit, The Death and Life of Great American Cities, The Future of Employment, The Nature of the Firm, transaction costs, Turing test, turn-by-turn navigation, Uber and Lyft, uber lyft, Zipcar

The skills, knowledge, and precise expertise found among peers give big companies immediate access to local partners, because the peers are the already established partners in these collaborations. Take Lyft, a website and mobile app that lets car owners turn their personal cars into taxis. Lyft’s platform aggregates the excess capacity available in both the owners’ free time and their idle cars to create a service that offers rides seven days a week, twenty-four hours a day. Lyft does what companies can do best: It performs criminal and driving background checks on the drivers, provides insurance, negotiates with regulators, markets the service to customers, and ensures quality and consistency. Lyft also built the easy-to-use app and collects the payments. Taken together, what Lyft does is beyond the talents, time, or budget of any single individual. Likewise, the peers—in this case, individual car owners and drivers acting as free agents—do what is expensive and difficult for the company.

6 BlaBlaCar raised $100 million in July 2014. 2014 proved to be a banner year for companies using this collaborative approach: over $3 trillion raised. Lyft raised $250 million, and Uber an astounding $3 billion. These are the companies that cracked the kernel platform-building stage, are experiencing the exuberant growth of the everybody-welcome stage, and are therefore the ones who raised the most money. While a good fraction of the value is likely the result of a bubble, the potential of the three Peers Inc miracles to deliver—based on fast-paced growth, fast learning, and speedy low-cost localization—is worth a lot to investors. In the summer of 2014, I was at a roundtable meeting at the Aspen Institute. One of the participants suggested that the huge valuations for Peers Inc companies gives these startups large amounts of “cheap” capital to play with, and therefore the ability to buy growth rather than earn it. Lyft and Uber are fierce competitors in the new app-based medallion-free taxi market.

Both have experienced fast growth and expansion in the few years since their founding (Uber in 2009, Lyft in 2012). And now both are engaged in price wars, each reducing fares to attract passengers and lowering their commissions to attract peer drivers. Neither has any competitive intellectual property. Uber’s competitive advantage was once in the deals it had negotiated with local limo companies and individual drivers. But nothing prevents drivers from agreeing to drive for both companies or prospective passengers from having both apps on their smartphones. It is my experience with Zipcar and its competitors that customers choose based on a combination of convenience (the technology), price, and proximity. Both Uber and Lyft have business models and apps that appear to work; can the market sustain both? Buying (bribing) users too early in a company’s life cycle will just eat up a lot of money and won’t produce anything lasting.


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The End of Traffic and the Future of Transport: Second Edition by David Levinson, Kevin Krizek

2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 3D printing, American Society of Civil Engineers: Report Card, autonomous vehicles, barriers to entry, Bay Area Rapid Transit, big-box store, Chris Urmson, collaborative consumption, commoditize, crowdsourcing, DARPA: Urban Challenge, dematerialisation, Elon Musk, en.wikipedia.org, Google Hangouts, Induced demand, intermodal, invention of the printing press, jitney, John Markoff, labor-force participation, lifelogging, Lyft, means of production, megacity, Menlo Park, Network effects, Occam's razor, oil shock, place-making, post-work, Ray Kurzweil, rent-seeking, ride hailing / ride sharing, Robert Gordon, self-driving car, sharing economy, Silicon Valley, Skype, smart cities, technological singularity, Tesla Model S, the built environment, Thomas Kuhn: the structure of scientific revolutions, transaction costs, transportation-network company, Uber and Lyft, Uber for X, uber lyft, urban renewal, women in the workforce, working-age population, Yom Kippur War, zero-sum game, Zipcar

(Though it would not be exactly fixed routes, one could imagine regular runs with a known coterie of passengers). This is at a lower rate than the traditional single party taxi-like service. While these services are at the time of this writing only in San Francisco and New York, Lyft now claims that Lyft Line comprises 50% of Lyft's rides in San Francisco and 30% in New York.191 (Not all of Lyft Line customers wind up in a shared ride, they just indicate a willingness to for a lower fare, and get the lower fare regardless of whether another passenger can be found). The ease of making ride requests and payments is what drives many folks to choose Uber or Lyft over traditional taxis. We suspect differentiating status and class is another important element. Users are hip enough and wealthy enough to use the new technology and not have to sit where others from other classes have sat before.

You might have thought ridesharing was the same as carpooling. And it is, if you think of modern ridesharing drivers as your friends giving you a lift (or in the name of one company a Lyft), not for money, but for a voluntary donation or paying for half the costs, like the carpooling service and app Carma enables. Whether this attempt to skirt the rules and regulations of taxis succeeds is a battle to be fought out in thousands of local markets globally. In markets where an agreement has been reached, the donation results in an actual charge and the process—enabled by smartphones—is taking off.189 The car you get with Lyft (or UberX) is the driver's personal car, not a fleet vehicle; it varies. David's first Lyft ride and Kevin's second UberX was in a Mercedes. Kevin's first UberX ride was at the San Francisco Airport from Rafaello who telephoned saying he was in the white Prius at the stop-light by the end of the airport terminal.

Kevin proceeded to the supposed Prius and open the back door to enter the car—much to a woman's astonishment and disdain. He walked to the next white Prius and fortunately found Rafaello (and the correct car). These social dynamics matter to services like Lyft. In contrast with traditional taxis, the passenger sits shotgun (in the front row passenger seat), and is expected to have a conversation with the driver (which happens in some taxis, though not always). Anecdotally, it appears people who drive for Lyft are more likely to be (though not universally) American citizens or long-term residents, and since they own their own car, less likely to be poor, recently landed immigrants who comprise the taxi drivers in many cities. Lyft is in many ways simply an app with a back-end (rather, 'cloud-based') dispatch service. They claim to be a "transport network company whose mobile-phone application facilitates peer-to-peer ridesharing by enabling passengers who need a ride to request one from drivers who have a car."


Seeking SRE: Conversations About Running Production Systems at Scale by David N. Blank-Edelman

Affordable Care Act / Obamacare, algorithmic trading, Amazon Web Services, bounce rate, business continuity plan, business process, cloud computing, cognitive bias, cognitive dissonance, commoditize, continuous integration, crowdsourcing, dark matter, database schema, Debian, defense in depth, DevOps, domain-specific language, en.wikipedia.org, fault tolerance, fear of failure, friendly fire, game design, Grace Hopper, information retrieval, Infrastructure as a Service, Internet of things, invisible hand, iterative process, Kubernetes, loose coupling, Lyft, Marc Andreessen, microservices, minimum viable product, MVC pattern, performance metric, platform as a service, pull request, RAND corporation, remote working, Richard Feynman, risk tolerance, Ruby on Rails, search engine result page, self-driving car, sentiment analysis, Silicon Valley, single page application, Snapchat, software as a service, software is eating the world, source of truth, the scientific method, Toyota Production System, web application, WebSocket, zero day

As of this writing, Lyft (and most other users of Envoy) is moving toward a fully centralized configuration system supported by a complete set of discovery APIs. The net result of deploying Envoy at Lyft has been that developers no longer consider the network when building applications. When network problems do occur, developers have the tooling in place to help discover and remediate the issue quickly. The networking substrate deployed at Lyft has increased developer productivity, increased overall success rate, and decreased Mean Time to Recovery (MTTR) during incidents. Operating Envoy at Lyft As I already described, for better or worse Lyft does not have an SRE-like job title. Instead, all developers are expected to be reliability engineers as well. I lead the network team at Lyft, and in addition to developing Envoy we also operate it. Although I have strong opinions about the emergence of DevOps culture in general (out of scope for this chapter), for a system component such as Envoy, I think having the developers of the system also operate it has been a forcing function toward making sure the service mesh truly lives up to the hype of creating a transparent network.

Fully managed solutions include SmartStack (built on HAProxy) and Istio (built on Envoy and now also supporting Linkerd). What follows is a short description of Lyft’s transition from a monolithic application to a complete service mesh architecture built on top of Envoy. This is by no means the only service mesh success story, but it’s one I am familiar with (I am the creator of Envoy) and will hopefully provide some flavor to the generic service mesh architecture description that most of this chapter has endeavored to describe. The Origin and Development of Envoy at Lyft By early 2015, Lyft had a primarily monolithic PHP application backed by MongoDB along with tens of microservices written in Python. The application at that time was deployed in a single region within AWS. Lyft had decided to make the jump to a microservice architecture for the same reasons that almost everyone else does: decoupling and increased agility.

The network is inherently unreliable. Lyft developers were having a tremendous amount of trouble debugging network failures and tail latency issues. In some cases, planned services were aborted and more features were added to the monolith because the network was deemed too unreliable to support the workloads. It’s important to also note that Lyft does not currently have an SRE-like job title; all developers are expected to operate their services at a high level of reliability. (The industry move toward DevOps is extremely interesting and worthy of its own chapter; I touch on some of the implications as it relates to Lyft’s service mesh migration in a few moments.) Envoy began development in the same early 2015 timeframe. The goal of the project was to build a very high-performance network substrate that Lyft developers trusted and would ultimately be fully transparent.


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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

This has naturally led to intense competition between the two companies, and Uber infamously resorted to a playbook to create interaction failure on Lyft using questionable tactics. Uber decided to target interaction failure on Lyft by contracting third-party agents to use disposable phones to hail Lyft taxies. Before the Lyft taxi arrived at its pickup location, the Uber-contracted agent would cancel the ride. With so many cancelations on the Lyft platform, drivers would become frustrated driving for Lyft and, in some cases, switch to Uber. A smaller number of drivers on the Lyft platform meant longer waiting times for traveler. This would, in turn, frustrate travelers, eventually spurring them to abandon the platform. When multihoming costs are low, producers and consumers may easily participate on multiple platforms.

Producers and consumers who experience interaction failure become discouraged from participating further and eventually abandon the platform. THE UBER–LYFT WAR Interaction failure is especially important for on-demand platforms. Imagine a consumer requesting a service and never being served with a solution. Imagine, in turn, a producer receiving a request and preparing to fulfill that request, only to find that the request is canceled. In both cases, the respective consumer or producer may become discouraged and decide to abandon the platform. In some of the largest cities, drivers drive for both Uber and Lyft, as well as other competitors. It’s not uncommon for these drivers to switch between the two platforms multiple times a day. With a limited supply of drivers in a city and the cost for a driver to connect to an additional platform being so small, drivers multihome on both Uber and Lyft. This has naturally led to intense competition between the two companies, and Uber infamously resorted to a playbook to create interaction failure on Lyft using questionable tactics.

For more details, please visit http://platformthinkinglabs.com/about/sangeet-choudary/ TABLE OF CONTENTS Preface 1.0 AN INTRODUCTION TO INTERACTION-FIRST BUSINESSES 1.1 Building The Next Big Thing 1.2 The Platform Manifesto 1.3 The Rise Of The Interaction-First Business 1.4 The Platform Stack 1.5 The Inner Workings Of Platform Scale Conclusion 2.0 DESIGNING THE INTERACTION-FIRST PLATFORM Introduction 2.1 The New New Value 2.2 Uber’s Drivers, Google’s Crawlers And GE's Machines 2.3 Building An Interaction-First Platform Business 2.4 Uber, Etsy, And The Internet Of Everybody 2.5 Personalization Mechanics 2.6 The Core Interaction 2.7 Pull-Facilitate-Match 2.8 The Platform Canvas 2.9 Emergence 3.0 BUILDING INTERACTION-FIRST PLATFORMS Introduction 3.1 Interaction Drivers 3.2 Building User Contribution Systems 3.3 Frictionless Like Instagram 3.4 The Creation Of Cumulative Value 3.5 The Traction-Friction Matrix 3.6 Sampling Costs 3.7 Trust Drives Interaction 3.8 Uber Vs. Lyft And Interaction Failure 3.9 Interaction Ownership And The TaskRabbit Problem 4.0 SOLVING CHICKEN-AND-EGG PROBLEMS Introduction 4.1 A Design Pattern For Sparking Interactions 4.2 Activating The Standalone Mode 4.3 How Paypal And Reddit Faked Their Way To Traction 4.4 Every Producer Organizes Their Own Party 4.5 Bringing In The Ladies 4.6 The Curious Case Of New Payment Mechanisms 4.7 Drink Your Own Kool Aid 4.8 Beg, Borrow, Steal And The World Of Supply Proxies 4.9 Disrupting Craigslist 4.10 Starting With Micromarkets 4.11 From Twitter To Tinder 5.0 VIRALITY: SCALE IN A NETWORKED WORLD Introduction 5.1 Transitioning To Platform Scale 5.2 Instagram’s Moonshot Moment 5.3 Going Viral 5.4 Architecting Diseases 5.5 A Design-First Approach To Viral Growth 5.6 Building Viral Engines 5.7 The Viral Canvas 6.0 REVERSE NETWORK EFFECTS Introduction 6.1 A Scaling Framework For Platforms 6.2 Reverse Network Effects 6.3 Manifestations Of Reverse Network Effects 6.4 Designing The Anti-Viral, Anti-Social Network Epilogue Platform Scale (n): Business scale powered by the ability to leverage and orchestrate a global connected ecosystem of producers and consumers toward efficient value creation and exchange.


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

In early 2015, both Uber and Lyft began experimenting with a new ride-sharing service that complements their familiar call-a-taxi business model. The new services, known as UberPool and Lyft Line, allow two or more passengers traveling in the same direction to find one another and share a ride, thereby reducing their cost while increasing the revenues enjoyed by the driver. Lyft cofounder Logan Green says that ride-sharing was always part of the Lyft idea. The initial version of Lyft, he explains, was designed to attract an initial customer base “in every market.” Having achieved that, he continues, “Now we get to play that next card and start matching up people to take rides.”3 Uber isn’t taking the competition lightly. To try to ensure that its ride-sharing service out-competes Lyft’s, Uber has joined the bidding for Here, a digital mapping service owned by Nokia that is the chief alternative to Google Maps.

And the greater the winner-take-all forces, the more vicious the platform competition. In the market for ride-sharing transportation services, the absence of distinct user needs and the presence of strong network effects explains the fierce rivalry between Uber and Lyft. Each side has ruthlessly poached the other’s drivers by offering referral bounties and cash incentives. Some of the alleged tactics border on the unethical. For example, Lyft has accused Uber of ordering, then cancelling, more than 5,000 rides in order to clog the Lyft service. Uber denied the specific charge. But there’s no doubt that both companies are convinced that only one is likely to survive their rivalry, and that each is determined to do whatever it takes to be the one left standing.23 As we’ve seen, the nature of competition in the world of platforms is very different from that in the world of traditional pipeline businesses.

Varian, “The Art of Standards Wars,” California Management Review 41, no. 2 (1999): 8–32. 22. Bill Gurley, “All Revenue Is Not Created Equal: Keys to the 10X Revenue Club,” Above the Crowd, May 24, 2011, http://abovethecrowd.com/2011/05/24/all-revenue-is-not-created-equal-the-keys-to-the-10x-revenue-club/. 23. Douglas MacMillan, “The Fiercest Rivalry in Tech: Uber vs. Lyft,” Wall Street Journal, August 11, 2014; C. Newton, “This is Uber’s Playbook for Sabotaging Lyft,” The Verge, August 26, 2014, http://www.theverge .com/2014/8/26/6067663/this-is-ubers-playbook-for-sabotaging-lyft. CHAPTER 11: POLICY 1. Kevin Boudreau and Andrei Hagiu, Platform Rules: Multi-Sided Platforms as Regulators (Cheltenham, UK: Edward Elgar, 2009), 163–89. 2. Malhotra and Van Alstyne, “The Dark Side of the Sharing Economy.” 3. Felix Gillette and Sheelah Kolhatkar, “Airbnb’s Battle for New York,” Businessweek, June 19, 2014, http://www.bloomberg .com/bw/articles/2014-06-19/airbnb-in-new-york-sharing-startup-fights-for-largest-market. 4.


pages: 472 words: 80,835

Life as a Passenger: How Driverless Cars Will Change the World by David Kerrigan

3D printing, Airbnb, airport security, Albert Einstein, autonomous vehicles, big-box store, butterfly effect, call centre, car-free, Cesare Marchetti: Marchetti’s constant, Chris Urmson, commoditize, computer vision, congestion charging, connected car, DARPA: Urban Challenge, deskilling, disruptive innovation, edge city, Elon Musk, en.wikipedia.org, future of work, invention of the wheel, Just-in-time delivery, loss aversion, Lyft, Marchetti’s constant, Mars Rover, megacity, Menlo Park, Metcalfe’s law, Minecraft, Nash equilibrium, New Urbanism, QWERTY keyboard, Ralph Nader, RAND corporation, Ray Kurzweil, ride hailing / ride sharing, Rodney Brooks, Sam Peltzman, self-driving car, sensor fusion, Silicon Valley, Simon Kuznets, smart cities, Snapchat, Stanford marshmallow experiment, Steve Jobs, technoutopianism, the built environment, Thorstein Veblen, traffic fines, transit-oriented development, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, Unsafe at Any Speed, urban planning, urban sprawl, Yogi Berra, young professional, zero-sum game, Zipcar

America’s love affair with driving seems to be cooling off, while our obsession with urban living is heating up. The new player in the mix of urban life is cars on demand, either on a trip basis with a driver with a service like Uber or Lyft, or on a usage basis - with a service like Zipcar - essentially rental by the hour or by subscription. Taxis have long been a popular way to get around when driving yourself doesn’t suit or isn’t possible. But the modernisation of taxis via the smartphone has given the concept a new lease of life. As of May 2017, leading on-demand provider Uber operates in over 580 cities and saw over $20 billion of bookings in 12 months. Rival company Lyft provides over 20 million rides per month. Ride sharing is currently responsible for about 4 percent of the miles traveled by car globally and Morgan Stanley believe the number will be nearly 30 percent by the year 2030.[59] We’ll look at ownership and its alternatives in more detail in Chapter 5.

Uber CEO Travis Kalanick believes that driverless cars pose an existential risk to Uber,[117] and they are working hard to catch up with others in the area. Their big fear is that if someone else develops driverless cars first and launches a fleet of vehicles, they would be able to offer rides at a fraction of the cost that Uber charge, where the bulk of the ride cost is the cost of the driver. In May 2017, Uber’s biggest rival in the US, Lyft, announced a partnership with Waymo, just as Waymo and Uber were embroiled in a legal battle over Intellectual Property concerning LiDAR.[118] Baidu China's top online search firm Baidu said in 2015 it aims to put self-driving vehicles on the road in three years and mass produce them within five years, after it set up a business unit to oversee all its efforts related to automobiles.[119] In a surprise follow up announcement, Baidu revealed it would make its driverless cars technology, including its vehicle platform, hardware platform, software platform and cloud data services, freely available to others, particularly car manufacturers, to develop autonomous vehicles.[120] A Baidu driverless car prototype.

Plenty of “unassailable” market leaders have missed cusps and fallen away. Think Kodak, Borders, Blockbuster, music companies, newspapers. The major car manufacturers don’t want to be the “horse” of a new “horseless carriage” era. The line between the agile technology sector and the lumbering powerhouse automotive industries is blurring. The rise of rideshare and ride hailing companies such as Uber and Lyft means that transportation is being tied ever more closely to your cell phone, while autonomous driving technology will require turning your car into a supercomputer. But these developments are expensive: Carmakers’ R&D budgets jumped 61 percent, to $137 billion from 2010 to 2014. Fiat Chrysler America CEO, Sergio Marchionne, has said he believes it makes no sense for carmakers to spend billions of dollars developing competing, yet largely identical systems.


pages: 285 words: 58,517

The Network Imperative: How to Survive and Grow in the Age of Digital Business Models by Barry Libert, Megan Beck

active measures, Airbnb, Amazon Web Services, asset allocation, autonomous vehicles, big data - Walmart - Pop Tarts, business intelligence, call centre, Clayton Christensen, cloud computing, commoditize, crowdsourcing, disintermediation, diversification, Douglas Engelbart, Douglas Engelbart, future of work, Google Glasses, Google X / Alphabet X, Infrastructure as a Service, intangible asset, Internet of things, invention of writing, inventory management, iterative process, Jeff Bezos, job satisfaction, Kevin Kelly, Kickstarter, late fees, Lyft, Mark Zuckerberg, Oculus Rift, pirate software, ride hailing / ride sharing, self-driving car, sharing economy, Silicon Valley, Silicon Valley startup, six sigma, software as a service, software patent, Steve Jobs, subscription business, TaskRabbit, Travis Kalanick, uber lyft, Wall-E, women in the workforce, Zipcar

General Motors (GM) is coming enthusiastically, albeit a bit late, to the innovative ride-sharing market with a $500 million investment in Lyft as part of Lyft’s latest $1 billion venture financing round. Although a shift from car ownership to car sharing, and even further to autonomous vehicles, could be a risky disruption to their market, GM’s leaders have decided to embrace the changing business model landscape in transportation and innovate what they do and how they do it. Daniel Ammann, GM’s president, said, “We think there’s going to be more change in the world of mobility in the next five years than there has been in the last 50,” and GM is getting ready for that change.1 From that perspective, Lyft is an excellent partner who will help GM turn their views of the market upside down. Lyft’s president John Zimmer stated, “We strongly believe that autonomous vehicle go-to-market strategy is through a network, not through individual car ownership.”

Lyft’s president John Zimmer stated, “We strongly believe that autonomous vehicle go-to-market strategy is through a network, not through individual car ownership.” According to executives at both GM and Lyft, they will start work on developing a network of self-driving vehicles—a challenge to Google, Tesla, and Uber, which are also devoting resources to this innovation.2 Openness Makes Space for Ongoing Change Will GM’s self-driving-car aspiration create value for the firm? Will its investment in Lyft lead to automotive leadership in ten years? We couldn’t say. But so far its openness to adaptation and new ideas shows potential for future growth and transformation. We’ve now reached the last of the principles to be considered for a network orchestrator business model, and it points us to the mental model. Whereas the first nine principles emphasize specific shifts that network orchestrators make in order to better enable their outward-looking, co-creative business models, the final principle is about your own openness to making these shifts and to taking in and adapting to new information in general—whether it’s from your customers, employee groups, or the market.

Other network companies access the physical assets of the network, such as Uber making use of customers’ cars, or Airbnb making use of customers’ real estate. The task of managing external assets, however, is entirely different from managing those owned by your firm. To maintain and grow access to a network’s assets, you must carefully manage the sentiment and engagement of the network itself. If Uber doesn’t keep its drivers happy, there are other ride-sharing networks such as Lyft and Sidecar ready to take them into the fold. Let’s reflect on your organization and pinpoint where you lie on the spectrum from tangible to intangible. Ask yourself these questions, and then mark on the scale of tangible (1) to intangible (10) where your company falls on the spectrum. What are the most important assets of your company? What percentage are tangible? Intangible? How much capital and time, by percentage, does your firm allocate to the management of intangible assets?


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

The first free thing I got was a bright pink coupon that I fished out of a basket next to a cash register. The coupon bestowed a free introductory taxi ride from the city’s second-largest “app-based pickup service,” Lyft. I found the corporate vowel swapping obnoxious. (Couldn’t it just be Lift?) Ditto the twee mustache logo. But I was much too “frugal,” as my wife put it, to refuse a $25 value on aesthetic grounds. So I installed the Lyft app on my phone, allowed the company to track my geospatial location and who knows what else, and then summoned a car to carry me and my luggage to my new digs across town. When I looked up, there was a car puttering away by the curb. I’d never used an app like Lyft before, and it didn’t seem possible that my ride had shown up so fast. I stood around futilely scanning the horizon for a few minutes. The driver didn’t seem annoyed.

Who would pay for it? Unions? No. Corporations? No. I had it: The competition. Here again Uber pointed the way. The company had run an ingeniously underhanded dirty tricks campaign against its largest rival, Lyft, by ordering, then canceling, thousands of rides. The hope was that Lyft’s drivers, frustrated by the cancellations, would come work for Uber. Then there was Operation SLOG—“Supplying Long-term Operations Growth”—a “marketing program” revealed by the Verge that involved undercover recruiters equipped with “burner phones, credit cards, and driver kits,” charged with hailing rides on Lyft and then persuading the drivers to defect to Uber. “Not only does Uber know about this, they’re actively encouraging these actions day to day and, in doing so, are flat-out lying both to their customers, the media, and their investors,” one whistleblower told the Verge.

Apart from a fleeting barrage of finger wagging by ineffectual do-gooders such as Juno and Lyft, the company’s campaign of competitive sabotage was an unalloyed success. Perhaps the only thing keeping other startups from adopting similar tactics was a lack of know-how. And a sense of propriety. Which was not a problem for me. * * * My idea was truly disruptive, in the sense that it was both dubiously legal and potentially profitable. I sought to apply proven methods of corporate subversion to a market that was woefully neglected by established players in the tech industry. The idea was so simple, I was surprised it hadn’t been done yet. If Uber could use stealthy labor-organizing-style tactics in its campaign to poach drivers from Lyft, why shouldn’t Lyft retaliate by covertly funding an actual employee union drive at Uber?


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

At a deeper level, what the interface entrepreneurs are asking is for us to share (and monetize) our time: the founders of Lyft are motivated not just by profit but by the loneliness of the average commuter stuck in his car.36 These companies encourage us to dedicate our hours to others, often in appeals that blend the allure of wages for labor with something more socially complex. Where Uber sells a kind of elite independence to both its drivers and riders (figure 4.3), Lyft is selling a different and more intimate kind of social contact (figure 4.4). The company only recently abandoned its directive that drivers festoon their cars with quirky pink moustaches, and many drivers still assume passengers will sit companionably in the front seat, rather than the rear. Figure 4.4 Lyft advertising takes a very different tack from Uber. For companies like Lyft and more deliberately intimate interface layer systems like the dating app Tindr, the “sharing economy” is not about money at all, but about that experience of companionship.

Courtesy of Ian Bogost, http://bogost.com/games/cow_clicker/. Figure 4.2: The cartoon maps Uber provides for its drivers and passengers via the Google Play Store. Figure 4.3: Uber’s homepage offers a message of simultaneous elitism and equality (image from July 2014). Source: Uber, http://mascola.com/insights/ubers-lost-positoning-luxury-car-service/. Figure 4.4: Lyft advertising takes a very different tack from Uber. Source: http://www.adweek.com/news/technology/lyft-hopes-accelerate-first-integrated-ad-campaign-159619. Figure 4.5: Amazon Mechanical Turk Interface for Managing Workers. © 2016, Amazon Web Services, Inc. or its affiliates. All rights reserved. http://docs.aws.amazon.com/AWSMechTurk/latest/RequesterUI/ViewingWorkerDetails.html. Figure 4.6: An engraving of the Turk from Karl Gottlieb von Windisch’s 1784 book Inanimate Reason.

Figure 3.3 The atomized ideal of Netflix’s abstraction aesthetic. Figure 3.4 Screenshot of House of Cards opening credits: a city devoid of people. Figure 4.1 Cow Clicker screenshot. Figure 4.2 The cartoon maps Uber provides for its drivers and passengers via the Google Play Store. Figure 4.3 Uber’s homepage offers a message of simultaneous elitism and equality (image from July 2014). Figure 4.4 Lyft advertising takes a very different tack from Uber. Figure 4.5 Amazon Mechanical Turk Interface for Managing Workers. Figure 4.6 An engraving of the Turk from Karl Gottlieb von Windisch’s 1784 book Inanimate Reason. Figure 5.1 The blockchain, a system for transparent, public accounting of Bitcoin transactions. Figure 6.1 Vannevar Bush’s Memex. Acknowledgments This book owes its existence to the generosity and support of many people and institutions.


pages: 195 words: 52,701

Better Buses, Better Cities by Steven Higashide

Affordable Care Act / Obamacare, autonomous vehicles, business process, congestion charging, decarbonisation, Elon Musk, Hyperloop, income inequality, intermodal, jitney, Lyft, mass incarceration, Pareto efficiency, performance metric, place-making, self-driving car, Silicon Valley, six sigma, smart cities, transportation-network company, Uber and Lyft, Uber for X, uber lyft, urban planning, urban sprawl, walkable city, white flight, young professional

It’s a similar story with Uber, Lyft, and the rest of the app-enabled ride companies (known as transportation network companies [TNCs]). They have exploded in popularity. In 2012 (the year Lyft debuted and the year after Uber launched in New York City) Americans took 1.4 billion trips in for-hire vehicles, mostly taxis. By 2017, this had grown to 3.3 billion, mostly in Ubers and Lyfts.21 But (if you’ll recall the NACTO diagram from earlier) a single lane of a city street can carry perhaps 1,600 people an hour in cars; no advanced routing algorithm can magically fit more people into Chicago’s State Street or Los Angeles’ Hollywood Boulevard. Only the spatial magic of public transportation can accomplish that. These technologies also have yet to prove they can offer affordable mobility. Most of Uber and Lyft’s customers are wealthy.

But bus speeds have continued to get worse in recent years, falling to 7.4 mph in 2016.12 The same story has been seen in many of America’s cities. In Philadelphia, bus speeds fell every year from 2014 to 2017, and most buses travel below 12 mph.13 Average vehicle speeds have decreased at most transit agencies since 2012, according to the National Transit Database.14 Among the culprits is the enormous increase in Uber and Lyft rides; Amazon and other retailers have also led to a doubling in urban freight traffic associated with online shopping.15 This means even more can go wrong for buses and is going wrong for their riders. Cities have to break out the toolkit and start fixing the streets for transit. Unbunch My Bus Most bus routes are governed by a schedule that tells them when to leave the terminal and when to stop at specific stops.

In 2018, the Boston Transportation Department announced it would create its first-ever “transit team,” a five-person unit that will manage and implement transit priority projects.40 As urban traffic continues to worsen, cities need to design streets, draw routes, and structure organizations to provide fast and dependable transit. “We’re creating this circle where we provide good service, people appreciate it and they demand it, and so we have to provide it and keep improving it,” Bryant said. “The competition . . . the single occupant vehicle and Uber and Lyft . . . is getting better and better. We have to keep up with that competition, and in order to do that, this circle needs to continue to accelerate and expand.” 04 Make the Bus Walkable and Dignified On a Saturday afternoon in April 2010, Raquel Nelson, her 4-year-old son A.J., and her two other children (aged 2 and 9 years) stepped off the bus across the street from their apartment in Marietta, Georgia.


The New Map: Energy, Climate, and the Clash of Nations by Daniel Yergin

3D printing, 9 dash line, activist fund / activist shareholder / activist investor, addicted to oil, Admiral Zheng, Albert Einstein, American energy revolution, Asian financial crisis, autonomous vehicles, Ayatollah Khomeini, Bakken shale, Bernie Sanders, BRICs, British Empire, coronavirus, COVID-19, Covid-19, decarbonisation, Deng Xiaoping, disruptive innovation, distributed generation, Donald Trump, Edward Snowden, Elon Musk, energy security, energy transition, failed state, gig economy, global pandemic, global supply chain, hydraulic fracturing, Indoor air pollution, Intergovernmental Panel on Climate Change (IPCC), inventory management, James Watt: steam engine, Kickstarter, LNG terminal, Lyft, Malacca Straits, Malcom McLean invented shipping containers, Masdar, mass incarceration, megacity, Mikhail Gorbachev, mutually assured destruction, new economy, off grid, oil rush, oil shale / tar sands, oil shock, open economy, paypal mafia, peak oil, pension reform, price mechanism, purchasing power parity, RAND corporation, rent-seeking, ride hailing / ride sharing, Ronald Reagan, self-driving car, Silicon Valley, smart cities, South China Sea, sovereign wealth fund, supply-chain management, trade route, Travis Kalanick, Uber and Lyft, uber lyft, ubercab, UNCLOS, UNCLOS, uranium enrichment, women in the workforce

A more efficient transportation system would raise auto “occupancy” to a much higher level. Green and Zimmer connected, and in 2012 began to offer short rides in San Francisco. They called the new venture Lyft. Anyone could be a driver. In contrast to the upmarket “private driver” black car of early Uber, they provided Lyft drivers with pink mustaches to affix to the front of their cars. “Friendliness” and fist bumps were Lyft’s mode, a studied contrast to Uber’s ersatz limousine. Uber wasted no time in striking back, launching its own service with ordinary drivers. “We chose to compete,” Kalanick wrote in a blog post.3 And compete Uber did, and fiercely so. Its new business model was UberX, which adopted Lyft’s model and enrolled nonprofessional drivers who could work as little or as much as they wanted. They would be contractors, not employees. In other words, it’s a BYOC model—Bring Your Own Car.

In other words, it’s a BYOC model—Bring Your Own Car. Uber drivers, 60 percent of whom have other jobs, have become prime examples for what became known as the “gig economy.” Both Uber and Lyft also rolled out modern versions of carpooling services that match up a rider with another rider in close proximity headed to nearby destinations. Uber and Lyft rolled forward, opening in city after city. Customers, initially many of them millennials, were quickly won over. In its quest to expand, Uber went to war with local taxicab drivers and owners and transportation regulators, all of whom opposed it as an unregulated taxi company. It called its approach “principled confrontation.” Others called it outright aggression. Uber did not wait for permission to enter a city. It would just appear and start demonstrating the value it delivered.

It was also charged with deploying software covertly and illegally to deceive regulators and undermine Lyft. In June 2017, Uber retained former U.S. attorney general Eric Holder, who ended up recommending forty-seven actions to improve Uber’s “workplace” culture. A week later, five of the biggest investors in Uber dispatched a letter to Kalanick, who was on a trip to Chicago. The message was simple. He was fired. He was replaced by Dara Khosrowshahi, who had been CEO of the online travel company Expedia.6 By then, the ride-hailing industry was already well established; Uber alone had two million drivers worldwide, and “Uber” had the status of a verb. The growth in ride hailing had proved exponential. In San Francisco alone, Uber’s revenues were in the billions, compared to less than $200 million for taxis. By 2017, Uber was operating in 540 cities around the world; Lyft, 290 in the United States.


The Ethical Algorithm: The Science of Socially Aware Algorithm Design by Michael Kearns, Aaron Roth

23andMe, affirmative action, algorithmic trading, Alvin Roth, Bayesian statistics, bitcoin, cloud computing, computer vision, crowdsourcing, Edward Snowden, Elon Musk, Filter Bubble, general-purpose programming language, Google Chrome, ImageNet competition, Lyft, medical residency, Nash equilibrium, Netflix Prize, p-value, Pareto efficiency, performance metric, personalized medicine, pre–internet, profit motive, quantitative trading / quantitative finance, RAND corporation, recommendation engine, replication crisis, ride hailing / ride sharing, Robert Bork, Ronald Coase, self-driving car, short selling, sorting algorithm, speech recognition, statistical model, Stephen Hawking, superintelligent machines, telemarketer, Turing machine, two-sided market, Vilfredo Pareto

Of course, you don’t—but you take note. And at the end of the day, you are amused to find that again the sender was right, and LYFT was down more than 5 percent. The next day you get another email saying LYFT will go down again. The next day, yet another—LYFT will end the day up. This goes on for ten days, and every day the sender correctly predicts the direction of the stock. At first you were just curious, but now you are starting to really pay attention. After a few days you suspected that the sender might be a Lyft employee who is giving you illegal tips based on inside information. But you then discovered that there’s really not been any news or events to support this hypothesis, or to explain the seemingly random movements of LYFT. Finally, on the eleventh day, the sender emails you a request. He wants you to pay him to continue giving you stock recommendations.

Waiting for you in your inbox is a message with the subject line “Hot Stock Tip!” Inside, you find a prediction: shares of Lyft, the recently listed ride-sharing company (NASDAQ:LYFT), are going to end the day up. You should buy some now! Of course, you don’t take this advice—how did it get past your spam filter? But the prediction is specific enough that you remember it, and you check Google Finance after the close of the market. Sure enough, LYFT shares ended the day up. Amusing, but not terribly surprising—if the sender had merely flipped a coin and guessed, he would have been right about the direction of the stock half the time. The next day, you get another email from the same person. It tells you that today LYFT is going to end the day down, and you should short-sell it. Of course, you don’t—but you take note.

Should you view his demonstrated streak of ten correct predictions as convincing? Since you have some scientific training, you decide to formulate a null hypothesis and see if you can convincingly reject it. Your null hypothesis is that this fellow is no better at predicting stock movements than the flip of a coin—on any particular day, the probability that he correctly guesses the directional movement of LYFT is 50 percent. You go on to compute the p-value corresponding to your null hypothesis—the probability that if the null hypothesis were true, you would have observed something as extreme as you did: ten correct predictions in a row. Well, if the sender had only a 50 percent chance of getting the answer right on any given day, then the chance that he would get it right ten days in a row—the p-value—would be only about .0009, the probability of flipping a coin ten times in a row and getting heads each time.


pages: 296 words: 98,018

Winners Take All: The Elite Charade of Changing the World by Anand Giridharadas

"side hustle", activist lawyer, affirmative action, Airbnb, Bernie Sanders, bitcoin, Burning Man, Capital in the Twenty-First Century by Thomas Piketty, carried interest, cognitive dissonance, collective bargaining, corporate raider, corporate social responsibility, crowdsourcing, David Brooks, David Heinemeier Hansson, deindustrialization, disintermediation, Donald Trump, Edward Snowden, Elon Musk, friendly fire, global pandemic, high net worth, hiring and firing, housing crisis, Hyperloop, income inequality, invisible hand, Jeff Bezos, Kibera, Kickstarter, land reform, Lyft, Marc Andreessen, Mark Zuckerberg, new economy, Occupy movement, offshore financial centre, Panopticon Jeremy Bentham, Parag Khanna, Paul Graham, Peter Thiel, plutocrats, Plutocrats, profit maximization, risk tolerance, rolodex, Ronald Reagan, shareholder value, sharing economy, side project, Silicon Valley, Silicon Valley startup, Skype, Social Responsibility of Business Is to Increase Its Profits, Steven Pinker, technoutopianism, The Chicago School, The Fortune at the Bottom of the Pyramid, the High Line, The Wealth of Nations by Adam Smith, Thomas L Friedman, too big to fail, Travis Kalanick, trickle-down economics, Uber and Lyft, uber lyft, Upton Sinclair, Vilfredo Pareto, working poor, zero-sum game

Judge Chhabria similarly cited and tore down Lyft’s claim to be “an uninterested bystander of sorts, merely furnishing a platform that allows drivers and riders to connect.” He wrote: Lyft concerns itself with far more than simply connecting random users of its platform. It markets itself to customers as an on-demand ride service, and it actively seeks out those customers. It gives drivers detailed instructions about how to conduct themselves. Notably, Lyft’s own drivers’ guide and FAQs state that drivers are “driving for Lyft.” Therefore, the argument that Lyft is merely a platform, and that drivers perform no service for Lyft, is not a serious one. The judges believed Uber and Lyft to be more powerful than they were willing to admit, but they also conceded that the companies did not have the same power over employees as an old-economy employer like Walmart. “The jury in this case will be handed a square peg and asked to choose between two round holes,” Judge Chhabria wrote.

The case inspired the judges in the two cases, Edward Chen and Vince Chhabria, to grapple thoughtfully with the question of where power lurks in a new networked age. It was no surprise that Uber and Lyft took the rebel position. Like Airbnb, Uber and Lyft claimed not to be powerful. Uber argued that it was just a technology firm facilitating links between passengers and drivers, not a car service. The drivers who had signed contracts were robust agents of their own destiny. Judge Chen derided this argument. “Uber is no more a ‘technology company,’ ” he wrote, “than Yellow Cab is a ‘technology company’ because it uses CB radios to dispatch taxi cabs, John Deere is a ‘technology company’ because it uses computers and robots to manufacture lawn mowers, or Domino Sugar is a ‘technology company’ because it uses modern irrigation techniques to grow its sugar cane.” Judge Chhabria similarly cited and tore down Lyft’s claim to be “an uninterested bystander of sorts, merely furnishing a platform that allows drivers and riders to connect.”

Airbnb’s response to California’s charges is also contained in the above document. For Judge Chen’s ruling on Uber, see his “Order Denying Defendant Uber Technologies, Inc.’s Motion for Summary Judgment” in O’Connor v. Uber, Case No. C-13-3826 EMC, United States District Court for the Northern District of California, Docket No. 211. For Judge Chhabria’s ruling on Lyft, see his “Order Denying Cross-motions for Summary Judgment” in Cotter v. Lyft, Case No. 13-cv-04065-VC, United States District Court for the Northern District of California, Dockets No. 69 and 74. On Bill Gates’s faith in technology’s leveling powers, see his book The Road Ahead (New York: Viking, 1995). On Mark Zuckerberg and Priscilla Chan’s faith in the Internet’s powers, see their “Letter to Our Daughter” (Zuckerberg’s Facebook page, December 2015).


Virtual Competition by Ariel Ezrachi, Maurice E. Stucke

Airbnb, Albert Einstein, algorithmic trading, barriers to entry, cloud computing, collaborative economy, commoditize, corporate governance, crony capitalism, crowdsourcing, Daniel Kahneman / Amos Tversky, David Graeber, demand response, disintermediation, disruptive innovation, double helix, Downton Abbey, Erik Brynjolfsson, experimental economics, Firefox, framing effect, Google Chrome, index arbitrage, information asymmetry, interest rate derivative, Internet of things, invisible hand, Jean Tirole, John Markoff, Joseph Schumpeter, Kenneth Arrow, light touch regulation, linked data, loss aversion, Lyft, Mark Zuckerberg, market clearing, market friction, Milgram experiment, multi-sided market, natural language processing, Network effects, new economy, offshore financial centre, pattern recognition, prediction markets, price discrimination, price stability, profit maximization, profit motive, race to the bottom, rent-seeking, Richard Thaler, ride hailing / ride sharing, road to serfdom, Robert Bork, Ronald Reagan, self-driving car, sharing economy, Silicon Valley, Skype, smart cities, smart meter, Snapchat, social graph, Steve Jobs, supply-chain management, telemarketer, The Chicago School, The Myth of the Rational Market, The Wealth of Nations by Adam Smith, too big to fail, transaction costs, Travis Kalanick, turn-by-turn navigation, two-sided market, Uber and Lyft, Uber for X, uber lyft, Watson beat the top human players on Jeopardy!, women in the workforce, yield management

Uber, Always the Ride You Want: The Best Way to Get Wherever You’re Going, https://www.uber.com/ride. Sarah Ashley O’Brien, “NYC Uber Drivers Protest Rate Cuts,” CNN Money (February 1, 2016), http://money.cnn.com/2016/02/01/technology/uber-nyc -protest/index.html?sr =twCNN020116uber-nyc-protest0317PMVODtopPhoto &linkId=20849630; Lyft, Nashville Drivers Make Up to $6000/Month Driving Your Car, https://www.lyft.com/drive-for-lyft?im=& inc= 6000& t=month &kw=Nashville%20Drivers& utm _ source =bing& utm _medium= search& utm _campaign=Driver_BNA _v2 _ Search _Brand _ All_Lyft& utm _term=lyft%20 com%20driver&adgroup =lyft _driver&device = c& matchtype =b. Uber, “Dynamic Pricing 101 | Uber,” YouTube (December 2014), https://www .youtube.com/watch?v=76q7PDnxWuE. Annie Lowrey, “Is Uber’s Surge-Pricing an Example of High-Tech Gouging?,” New York Times Magazine, January 10, 2014, http://www.nytimes.com/2014 /01/12/magazine/is-ubers-surge-pricing-an-example-of-high-tech-gouging .html?

Uber later apologized and refunded the charge.26 Thus, Uber’s algorithm determines for hundreds of competing drivers the base price for the trip, when to implement a surge price, for which areas, for how long, and to what extent. Granted, the customer can compare the Uber price to alternatives (such as taxis or other car ser vice platforms like Lyft), but as more customers and drivers rely on Uber’s platform, one may wonder what effect its algorithm could have on the market price. To illustrate, let us suppose Uber is the dominant car ser vice platform in Nashville. Let us also assume taxis, for various reasons, are not a significant competitive restraint. What, if any, competition is left? Uber drivers do not offer discounts, as Uber’s pricing algorithm determines the fare. Nor will Uber drivers necessarily compete by offering better ser vice. One study of Uber and Lyft drivers found that they “distanced themselves from one another by checking other drivers’ locations on the map so that they did not compete with each other for passenger requests.

Matt Weinberger, “Microsoft Could See an Opportunity to Poke Google in the Eye with Uber Investment,” Business Insider UK (July 31, 2015), http://www.businessinsider.com/microsoft-and-google-are-uber-investors -2015-7. Nathaniel Mott, “Uber Should Fear the Company Formerly Known as Google,” Gigaom (August 11, 2015), https://gigaom.com/2015/08/11/uber-vs -alphabet-google/. Weinberger, “Microsoft Could See an Opportunity to Poke Google in the Eye with Uber Investment.” Douglas MacMillan, “GM Invests $500 Million in Lyft, Plans System for Self-Driving Cars,” Wall Street Journal, January 4, 2016, http://www.wsj.com /article _email/gm-invests-500-million-in-lyft-plans-system-for-self-driving -cars-1451914204-lMyQjAxMTI2NTA2NDEwODQyWj. Coupons.com, Form 10-K for 2014 (2014), 17; Yelp Inc., Form 10-Q for the Quarterly Period Ended June 30, 2015 (2015), 33, http://www.sec.gov /Archives/edgar/data/1345016/000120677415002479/yelp_10q.htm. “The number of people who access information about local businesses through mobile devices, including smartphones, tablets and handheld computers, has increased dramatically over the past few years and is expected to continue to increase.


pages: 307 words: 90,634

Insane Mode: How Elon Musk's Tesla Sparked an Electric Revolution to End the Age of Oil by Hamish McKenzie

Airbnb, Albert Einstein, augmented reality, autonomous vehicles, barriers to entry, basic income, Bay Area Rapid Transit, Ben Horowitz, business climate, car-free, carbon footprint, Chris Urmson, Clayton Christensen, cleantech, Colonization of Mars, connected car, crony capitalism, Deng Xiaoping, disruptive innovation, Donald Trump, Elon Musk, Google Glasses, Hyperloop, Internet of things, Jeff Bezos, John Markoff, low earth orbit, Lyft, Marc Andreessen, margin call, Mark Zuckerberg, megacity, Menlo Park, Nikolai Kondratiev, oil shale / tar sands, paypal mafia, Peter Thiel, ride hailing / ride sharing, Ronald Reagan, self-driving car, Shenzhen was a fishing village, short selling, side project, Silicon Valley, Silicon Valley startup, Snapchat, South China Sea, special economic zone, stealth mode startup, Steve Jobs, Tesla Model S, Tim Cook: Apple, Uber and Lyft, uber lyft, universal basic income, urban planning, urban sprawl, Zipcar

Santa Clara–based graphics chipmaker Nvidia has added hundreds of engineers to its auto-focused teams in the past few years. “We didn’t start out to be an auto company,” Danny Shapiro, Nvidia’s senior director of automotive, told the Times. “But everything that is changing a car has nothing to do with the auto industry of the past.” Start-ups have spotted the opportunity, too, of course. Uber and Lyft, both based in San Francisco, are hogging the early spoils in the ride-sharing market. Younger companies like Mountain View’s Smartcar (infrastructure for the connected car), San Francisco’s Reviver (digital license plates), and Palo Alto’s Nauto (AI-powered autonomous driving) are pursuing other software-related opportunities. Meanwhile, electric power-train companies like Wrightspeed (heavy-duty trucks), Zero (motorcycles), and Proterra (buses) are also in the area and have collectively raised hundreds of millions of dollars in funding.

Meanwhile, electric power-train companies like Wrightspeed (heavy-duty trucks), Zero (motorcycles), and Proterra (buses) are also in the area and have collectively raised hundreds of millions of dollars in funding. On the autonomous-driving side of things, Alphabet (formerly Google), which has logged several million self-driving-car test miles, continues to lead the pack. At the end of 2016, it created a new business division, called Waymo, for its autonomous driving technology. In May 2017, Waymo and Lyft announced that they would work together on developing the technology, and later in the year, Alphabet invested $1 billion in the start-up. Others, like Cruise Automation (which GM acquired for $1 billion) and Comma.ai, which offers open-source autonomous driving technology in the same vein as Google’s Android mobile operating system, are chasing hard. Baidu, China’s leading Internet search company, has an autonomous-driving research center in Sunnyvale.

The trifecta of electrification, autonomous driving, and car-sharing programs had convinced her that “we are literally on the cusp of the biggest transformation since the invention of the automobile.” The Bolt is just one of GM’s two dozen vehicle models in the United States, and Fletcher referred to it as a component of the company’s expanding “mobility play.” In 2016, GM acquired the self-driving car start-up Cruise for a billion dollars and invested about half that amount in the ride-sharing company Lyft, giving the auto giant a firm footing in the trifecta of areas that Fletcher said was transforming the industry. “The Bolt EV is the tipping point that kicks all that off,” she said. Because we spoke long in advance of the Model 3’s public availability, Fletcher wouldn’t be drawn out on the question of whether the car was a Model 3 competitor (“You’re asking about something that I don’t know what it is”), preferring to focus on bigger-picture matters.


pages: 527 words: 147,690

Terms of Service: Social Media and the Price of Constant Connection by Jacob Silverman

23andMe, 4chan, A Declaration of the Independence of Cyberspace, Airbnb, airport security, Amazon Mechanical Turk, augmented reality, basic income, Brian Krebs, California gold rush, call centre, cloud computing, cognitive dissonance, commoditize, correlation does not imply causation, Credit Default Swap, crowdsourcing, don't be evil, drone strike, Edward Snowden, feminist movement, Filter Bubble, Firefox, Flash crash, game design, global village, Google Chrome, Google Glasses, hive mind, income inequality, informal economy, information retrieval, Internet of things, Jaron Lanier, jimmy wales, Kevin Kelly, Kickstarter, knowledge economy, knowledge worker, late capitalism, license plate recognition, life extension, lifelogging, Lyft, Mark Zuckerberg, Mars Rover, Marshall McLuhan, mass incarceration, meta analysis, meta-analysis, Minecraft, move fast and break things, move fast and break things, national security letter, Network effects, new economy, Nicholas Carr, Occupy movement, optical character recognition, payday loans, Peter Thiel, postindustrial economy, prediction markets, pre–internet, price discrimination, price stability, profit motive, quantitative hedge fund, race to the bottom, Ray Kurzweil, recommendation engine, rent control, RFID, ride hailing / ride sharing, self-driving car, sentiment analysis, shareholder value, sharing economy, Silicon Valley, Silicon Valley ideology, Snapchat, social graph, social intelligence, social web, sorting algorithm, Steve Ballmer, Steve Jobs, Steven Levy, TaskRabbit, technoutopianism, telemarketer, transportation-network company, Travis Kalanick, Turing test, Uber and Lyft, Uber for X, uber lyft, universal basic income, unpaid internship, women in the workforce, Y Combinator, Zipcar

In the case of Lyft, potential drivers have to apply for work through their Facebook accounts. Once a driver is approved, he receives a fluffy pink mustache to affix to the front of his car. Customers call for a Lyft car through a smartphone app, choosing a driver by looking at his name, his rating, and photos of him and his car. Once the customer gets inside, the driver is supposed to offer his passenger a fist bump. For a while, Lyft passengers didn’t pay a fare—since that would have made Lyft seem too much like a taxi company, exposing them to certain municipal regulations—and instead were asked to offer a suggested donation. Later, Lyft instituted minimum fares and a “Prime Time amount,” its euphemism for ratcheting up fares during busy hours. After each ride, customers rate the driver, and drivers who have average ratings below 4.5 stars will be fired. In what’s supposed to represent a quid pro quo, customers get rated as well, meaning that you might not receive future rides if you accrue a bad score.

Nov. 12, 2013. blog.sfgate.com/techchron/2013/11/12/internet-axiom-github-airbnb. 235 “Prime Time amount”: Salvador Rodriguez. “Lyft Also Will Instate Fares in California, Ditching Donation System.” Los Angeles Times. Nov. 15, 2013. latimes.com/business/technology/la-fi-tn-lyft-minimum-fares-california-20131115,0,1699156.story. 235 Rating drivers: “A Sense of Place.” Economist. Oct. 25, 2012. economist.com/news/special-report/21565007-geography-matters-much-ever-despite-digital-revolution-says-patrick-lane. 236 “That’s part of the strategy”: Alyson Shontell. “My Nightmare Experience as a TaskRabbit Drone.” Business Insider. Dec. 7, 2011. businessinsider.com/confessions-of-a-task-rabbit-2011-12. 236 deactivating drivers’ accounts: Rachel Swan. “Chopped Livery: StartUps Revolutionize the Cab Industry.” SF Weekly. March 27, 2013. sfweekly.com/2013-03-27/news/uber-lyft-sidecar-cabs-sfmta. 238 San Francisco evictions: Steven T.

The sharing economy includes some online labor outlets, such as TaskRabbit, in which independent contractors perform menial tasks, such as fetching groceries or assembling furniture, for small fees. Companies such as Lyft, Uber, and Sidecar provide taxi-type services, but they almost never call themselves taxi or transportation companies. This is because the transportation industry is highly regulated, something that Uber would like to disrupt. Government, with its pernicious regulatory apparatus, is simply making the market inefficient and costing consumers and businesspeople in both cash and intimacy with one another. (For a time, Travis Kalanick, Uber’s founder, used a cropped cover of Ayn Rand’s Atlas Shrugged for his Twitter avatar before replacing it with a drawing of Alexander Hamilton’s face. Promoting individual economic liberty is presented as part of the company’s mandate.) In the case of Lyft, potential drivers have to apply for work through their Facebook accounts.


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

These southeastern startups are also invested in by Japanese tech conglomerate SoftBank, which has strategically put money behind one ride-hailing entrant in each region, including Didi in China. In a repeat of Uber’s saga in China, regional leader Grab—backed by Didi, SoftBank, and Alibaba—acquired Uber’s Southeast Asian business in 2018, then merged it. Don’t look for Didi to try entering the United States and compete with Uber on its home turf. Uber and Lyft are already too well entrenched, and battles for position have intensified with Lyft claiming a 35 market share next to dominant Uber, which faced several troubling scandals. With both now publicly traded companies, they could spark a sharing economy IPO parade. But there’s a lot of headway to be made. When Will Didi Make Money? Getting to profitability has remained a struggle for the privately held Didi, as with many fast-growth tech companies in China.

China’s tech titans have invested in and acquired startups and cutting-edge emerging companies throughout leading hubs worldwide, formed Sand Hill Road venture capital units, set up R&D outfits close to engineering talent, and angled into Hollywood moviemaking in a bid for soft power. In this outward reach, China investment in US tech companies reached $51.4 billion from 2010 through 2018, led by megadeals in America’s top trophy startups Uber, Lyft, and Magic Leap.35 Recent US regulatory hurdles and a Beijing crackdown on high-priced, debt-laden deals have curbed the action. But the innovation engine keeps going, and so does venture capital from Silicon Valley and China funds to fuel it. In the wake of heightened regulations and uncertainty, Chinese tech deal makers are shifting to smaller, highly strategic transactions in the United States and turning to more welcoming markets internationally.

The most acquisitive by far is Tencent with 146 deals and $25.7 billion of investment, followed by Alibaba with 51 deals and its part-owned Alipay with 2 deals and $3.7 billion in volume, and Baidu with 28 tech investments at $4.1 billion.2 China’s dragons have teamed up with top-tier US-based venture firms Mayfield and New Enterprise Associates, private equity firms General Atlantic and Carlyle Group, corporate strategic investors General Motors and Warner Brothers, and Japan’s acquisitive SoftBank. They’ve invested in US ride-hailing leaders Uber and Lyft, electric-carmaker Tesla, and augmented reality innovator Magic Leap. These Chinese tech titans have taken their cues directly from Silicon Valley venture capitalists. They’ve scoured the Valley for promising startups and based their operations not far from Menlo Park’s storied Sand Hill Road firms that backed winners Google, Facebook, and eBay. Tencent opened an office in a converted church in tech-wealthy Palo Alto, home to Stanford University, and has expanded nearby to a much larger California base.


pages: 389 words: 87,758

No Ordinary Disruption: The Four Global Forces Breaking All the Trends by Richard Dobbs, James Manyika

2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, access to a mobile phone, additive manufacturing, Airbnb, Amazon Mechanical Turk, American Society of Civil Engineers: Report Card, autonomous vehicles, Bakken shale, barriers to entry, business cycle, business intelligence, Carmen Reinhart, central bank independence, cloud computing, corporate governance, creative destruction, crowdsourcing, demographic dividend, deskilling, disintermediation, disruptive innovation, distributed generation, Erik Brynjolfsson, financial innovation, first square of the chessboard, first square of the chessboard / second half of the chessboard, Gini coefficient, global supply chain, global village, hydraulic fracturing, illegal immigration, income inequality, index fund, industrial robot, intangible asset, Intergovernmental Panel on Climate Change (IPCC), Internet of things, inventory management, job automation, Just-in-time delivery, Kenneth Rogoff, Kickstarter, knowledge worker, labor-force participation, low skilled workers, Lyft, M-Pesa, mass immigration, megacity, mobile money, Mohammed Bouazizi, Network effects, new economy, New Urbanism, oil shale / tar sands, oil shock, old age dependency ratio, openstreetmap, peer-to-peer lending, pension reform, private sector deleveraging, purchasing power parity, quantitative easing, recommendation engine, Report Card for America’s Infrastructure, RFID, ride hailing / ride sharing, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Silicon Valley startup, Skype, smart cities, Snapchat, sovereign wealth fund, spinning jenny, stem cell, Steve Jobs, supply-chain management, TaskRabbit, The Great Moderation, trade route, transaction costs, Travis Kalanick, uber lyft, urban sprawl, Watson beat the top human players on Jeopardy!, working-age population, Zipcar

Bill Gurley, “A deeper look at Uber’s dynamic pricing model,” Above the Crowd, March 11, 2014, http://abovethecrowd.com/20l4/03/11/a-deeper-look-at-ubers-dynamic-pricing-model/; Matthew Panzarino, “Leaked Uber numbers, which we’ve confirmed, point to over $1B gross, $213M revenue,” TechCrunch, December 4, 2013, http://techcrunch.com/2013/12/04/leaked-uber-numbers-which-weve-confirmed-point-to-over-1b-gross-revenue-213m-revenue. 47. Salvador Rodriguez, “Lyft surpasses 1 million rides, expands to Washington, D.C.,” Los Angeles Times, August 9, 2013, http://articles.latimes.com/2013/aug/09/business/la-fi-tn-lyft-1-million-washington-dc-20130808. 48. “AHA statistical update: Heart disease and stroke statistics—2013 update,” American Heart Association, Circulation 2013:127:e6–e245, December 12, 2012. 49. “Medtronic launches CareLink Express™ Service” (press release), Medtronic, August 14, 2012, http://newsroom.medtronic.com/phoenix.zhtml?

Using an app, commuters can scan the barcodes of life-size pictures of grocery items on the walls and screen doors of the railway platform and have the groceries delivered to their homes the same day. The service was so popular that in one year, Homeplus expanded its virtual stores to more than twenty bus stops. US start-up Instacart now offers customers in ten cities the ability to order goods from multiple stores through one website and get them delivered in one hour. Car-sharing services such as Zipcar and Lyft and transport services such as Uber are becoming increasingly popular among urban residents who have chosen not to purchase their own cars. The growing ubiquity of such shared services may be hard to replicate outside dense urban environments, but they are not unique to developed economies. In many emerging-market cities, similar services are already routinely offered though informal arrangements with mom-and-pop stores and service providers in local communities and neighborhoods.

Data-as-service start-ups are booming, and giants such as IBM, Microsoft, Oracle, and SAP have spent billions of dollars in the past several years snapping up companies that develop software for advanced data analytics. In fact, intangible digital assets—such as behavioral data on consumers and tracking data from logistics—can be the seeds of entirely new products and services. The disruption in taxi services is one example. Uber uses algorithms to determine “surge” prices in times of peak demand.46 Lyft, another on-demand ride-sharing start-up, employs a “happy hour” pricing model to lower rates in times of soft demand.47 Health care is another example of a sector where the marriage of data, analytical models, and decision-support tools—all key components of digital capital—can create immense economic value, improve customer experience, and create difficult-to-replicate capabilities. Some five million Americans suffer from congestive heart failure, which is treatable with drug therapy or implantable devices.48 Medtronic has built an industry first, CareLink Express Service, a remote heart-monitoring network that connects implanted cardiac monitoring devices to sites where physicians can remotely view and interpret data, improving the quality and efficiency of patient care in the process.


pages: 340 words: 92,904

Street Smart: The Rise of Cities and the Fall of Cars by Samuel I. Schwartz

2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, active transport: walking or cycling, Affordable Care Act / Obamacare, American Society of Civil Engineers: Report Card, autonomous vehicles, car-free, City Beautiful movement, collaborative consumption, congestion charging, crowdsourcing, desegregation, Enrique Peñalosa, Ford paid five dollars a day, Frederick Winslow Taylor, if you build it, they will come, Induced demand, intermodal, invention of the wheel, lake wobegon effect, Loma Prieta earthquake, longitudinal study, Lyft, Masdar, megacity, meta analysis, meta-analysis, moral hazard, Nate Silver, oil shock, Productivity paradox, Ralph Nader, rent control, ride hailing / ride sharing, Rosa Parks, self-driving car, skinny streets, smart cities, smart grid, smart transportation, the built environment, the map is not the territory, transportation-network company, Uber and Lyft, Uber for X, uber lyft, Unsafe at Any Speed, urban decay, urban planning, urban renewal, walkable city, Wall-E, white flight, white picket fence, Works Progress Administration, Yogi Berra, Zipcar

You don’t have to spend ten years learning the commuting ropes to know whether the train or bus you’re on is an express or a local, or even when it’s going to show up. You just need a smartphone. Smartphones are also all that’s needed to take advantage of other revolutionary new transportation options: ridesharing services like Via, car-sharing like Zipcar, and—especially—dispatchable taxi services like Uber and Lyft.c However, these and other cool new businesses didn’t create Millennial distaste for driving. They just exploited it. The question remains: why do Millennials find the automobile so much less desirable than their parents, grandparents, and great-grandparents did? Woodbridge, Virginia, is a small suburb about twenty miles south of Washington, DC. Many of the fifty-five thousand residents commute to Washington each day and return home to the leafy suburbs replete with cul-de-sacs and single-family homes.

(In fact, my professor brother, forty years after rejecting me as a physics has-been, invited me to a physics PhD candidate’s defense of her thesis, which mathematically described the flow of traffic on highways. Now who’s the scientist?) Actually, although Uber is often described as a ridesharing company, the “sharing” part is a little disingenuous. In fact, the only sharing that applies to most of the trips taken by travelers using Uber or Lyft (though not VIA) comes from the drivers sharing their cars with passengers. What these companies actually do is ride-matching.d The basic structure of the business is fairly simple. Drivers pass background checks (of themselves and their cars; in some places, like New York, they are also required to have a specialized license). They are given either dedicated phones or apps for their existing phones.

(A few earlier incarnations confuse matters, but that’s when the mobile app at the center of the service, which handled reservations, payment, and driver ratings, went live.) At the time, the base fee was $8 plus $5 a mile and a $15 minimum. Two years later, the company launched the UberX program which expanded the service to offer “sharing” for essentially any driver who could pass the background check and owned an acceptable car. That was when things started to heat up. Competitors like Sidecar (launched January of 2012) and Lyft (founded summer of 2012 as an extension of an earlier city-to-city ridesharing service known as Zimride) noticed the potential upside for a business that could extract revenue from travelers without actually investing in anything as expensive as buses, trains, or even cars; all that they needed were software algorithms and marketing. Though the California Public Utilities Commission, under pressure from existing taxi services, shut them all down, it allowed them to reopen the following year as what the state of California now calls “Transportation Network Companies.”


pages: 270 words: 79,180

The Middleman Economy: How Brokers, Agents, Dealers, and Everyday Matchmakers Create Value and Profit by Marina Krakovsky

Affordable Care Act / Obamacare, Airbnb, Al Roth, Ben Horowitz, Black Swan, buy low sell high, Chuck Templeton: OpenTable:, Credit Default Swap, cross-subsidies, crowdsourcing, disintermediation, diversified portfolio, experimental economics, George Akerlof, Goldman Sachs: Vampire Squid, income inequality, index fund, information asymmetry, Jean Tirole, Joan Didion, Kenneth Arrow, Lean Startup, Lyft, Marc Andreessen, Mark Zuckerberg, market microstructure, Martin Wolf, McMansion, Menlo Park, Metcalfe’s law, moral hazard, multi-sided market, Network effects, patent troll, Paul Graham, Peter Thiel, pez dispenser, ride hailing / ride sharing, Robert Metcalfe, Sand Hill Road, sharing economy, Silicon Valley, social graph, supply-chain management, TaskRabbit, The Market for Lemons, too big to fail, trade route, transaction costs, two-sided market, Uber for X, uber lyft, ultimatum game, Y Combinator

In fact, this is one of the oldest roles for middlemen there is. The Truckless Trucking Company * * * Long before there was Lyft and before there was Uber, and well before mobile devices or even the Internet, there was C. H. Robinson. The company, founded back in 1905, in 2014 ranked #220 on the Fortune 500, the annual list of the highest-grossing companies in the United States. Its annual revenues of $12.7 billion put C. H. Robinson just ahead of household brands Toys ‘R’ Us and Nordstrom and well above Facebook and Harley-Davidson. If you haven’t heard of this behemoth from Eden Prairie, Minnesota, it’s only because its customers are other businesses: rather than arranging rides for busy urbanites, as Lyft and Uber do, C. H. Robinson acts as freight broker for companies that need to quickly find truckload capacity to carry freight from one factory, warehouse, or retailer to another.

“One way to look at middlemen,” Maples says, “is that because of the advent of the Internet, the world has become more ‘inter-networked.’”14 More people, companies, and products are connected than ever. In this highly connected world, “things and entities that accelerate connections are going to be more valuable,” Maples believes.15 This idea is self-evident when you think of core Internet technologies and social networking tools that speed up our personal connections; it is also true of middleman businesses Maples has backed, such as Chegg, Lyft, and TaskRabbit, that speed up connections between buyers and sellers. Perhaps more surprisingly, it is also true of many human middlemen, including venture capitalists like Maples himself: great at spotting high-potential entrepreneurial ideas, effective venture capitalists (VCs) command the space between entrepreneurs and the limited partners (LPs) who entrust VCs with their capital. For the LPs, a venture capitalist connects their investment dollars with business ideas capable of generating high returns; for the entrepreneurs with these promising ideas, the venture capitalist channels the LPs’ dollars toward the ideas and also helps entrepreneurs quickly form other important connections—to talent, to trusted advisors, and, if all goes well, all the way to the stock market.16 The rest of us benefit, too, whenever we enjoy the products and services of innovative entrepreneurial ventures, because without the VCs, the most high-flying companies might never get off the ground.

Bridges as Two-Sided Markets * * * Lacking both experience and theoretical knowledge, she didn’t realize that the bridge she was trying to build had the interesting properties of what economists call a two-sided market. These days, two-sided markets (sometimes called two-sided networks or two-sided platforms) are everywhere because many of today’s Internet start-ups are middlemen businesses of exactly this type: whether you’re talking about connecting homeowners with guests (Airbnb) or drivers with fares (Lyft and Uber) workers with small jobs (TaskRabbit) restaurants with diners wanting take-out meals (GrubHub, Eat24) or doctors with patients (ZocDoc), you’re describing a two-sided market. At the same time, and maybe not coincidentally, the study of two-sided markets has become a popular field among academics, with many opinions about what counts as a two-sided market. One researcher I talked to, economist Marc Rysman of Boston University, told me there have been so many papers proposing their own definitions that he was “almost embarrassed to have participated in that literature.”35 Under some definitions, just about any market is two-sided, but such an inclusiveness makes the label useless.


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

Akerlof, “Writing the ‘The Market for “Lemons”’: A Personal and Interpretive Essay,” Nobelprize.org, November 14, 2003, http://www.nobelprize.org/nobel_prizes/economic-sciences/laureates/2001/akerlof-article.html. 207 “if this paper were correct”: Ibid. 207 50 million rides per month: Eric Newcomer, “Lyft Is Gaining on Uber as It Spends Big for Growth,” Bloomberg, last modified April 14, 2016, https://www.bloomberg.com/news/articles/2016-04-14/lyft-is-gaining-on-uber-as-it-spends-big-for-growth. 208 In 2013, California passed regulations: Tomio Geron, “California Becomes First State to Regulate Ridesharing Services Lyft, Sidecar, UberX,” Forbes, September 19, 2013, http://www.forbes.com/sites/tomiogeron/2013/09/19/california-becomes-first-state-to-regulate-ridesharing-services-lyft-sidecar-uberx/#6b22c10967fe. 208 by August 2016, BlaBlaCar still did not require them: BlaBlaCar, “Frequently Asked Questions: Is It Safe for Me to Enter My Govt.

The great majority of Uber’s ride suppliers were not professional chauffeurs; they were simply people who wanted to make money with their labor and their cars. So how did this huge market overcome severe information asymmetries? In 2013, California passed regulations mandating that transportation network companies (TNCs) such as Uber and Lyft conduct criminal background checks on their drivers. These checks certainly provided some reassurance, but they were not the whole story. After all, UberX and its competitor Lyft both grew rapidly before background checks were in place, and by August 2016, BlaBlaCar still did not require them for its drivers. Instead, these companies used their platforms’ user interfaces to overcome the information asymmetries that plagued their markets. In particular, they asked all parties to rate each other after each transaction, and they prominently displayed everyone’s cumulative ratings.§ In addition, TNCs typically keep detailed records of each trip, using data from phones’ GPS sensors.

Our favorite label for such platforms, which we first heard from artificial intelligence rock star Andrew Ng, is “O2O,” which means “online to offline.” We like this shorthand because it captures the heart of the phenomenon: the spread from the online world to the offline world of network effects, bundles of complements, and at least some of the economics of free, perfect, and instant. By the end of 2016, O2O platforms existed in a wide range of industries: Lyft and Uber for urban transportation, Airbnb for lodging, Grubhub and Caviar for food delivery, Honor for in-home health care, and many others. All of these companies are working to productively (and eventually profitably) bring together the economics of bits with those of atoms. Very often the physical inventory being offered on these platforms is perishable, as with spaces in exercise studios or nights of lodging, but sometimes it’s not.


pages: 340 words: 100,151

Secrets of Sand Hill Road: Venture Capital and How to Get It by Scott Kupor

activist fund / activist shareholder / activist investor, Airbnb, Amazon Web Services, asset allocation, barriers to entry, Ben Horowitz, carried interest, cloud computing, corporate governance, cryptocurrency, discounted cash flows, diversification, diversified portfolio, estate planning, family office, fixed income, high net worth, index fund, information asymmetry, Lean Startup, low cost airline, Lyft, Marc Andreessen, Myron Scholes, Network effects, Paul Graham, pets.com, price stability, ride hailing / ride sharing, rolodex, Sand Hill Road, shareholder value, Silicon Valley, software as a service, sovereign wealth fund, Startup school, Travis Kalanick, uber lyft, VA Linux, Y Combinator, zero-sum game

We mentioned Airbnb earlier in the context of discussing market size to illustrate that the answer to this question might not always be obvious. Now let’s look at Lyft as a way to show how you can best position market size as an entrepreneur. When Lyft was getting started (Lyft actually started as another company called Zimride, a long-distance ride-sharing company), it wasn’t obvious how big the market for ride-sharing could be. A lot of people evaluating the financing opportunity started with the existing taxi market as a proxy for market size and made some assumptions about what percentage of that market a ride-sharing service could reasonably capture. That line of thinking was perfectly logical, but the entrepreneurs didn’t stop there. Rather, they made the case—convincingly at least to us at Andreessen Horowitz—that that line of reasoning was too myopic. Instead, Lyft argued that the taxi market was too limiting because people made assumptions about the availability of taxis, the security of taxis, and the convenience of hailing taxis in choosing whether to in fact order a taxi.

See also limited partners (LPs) iPhone, 130 Isabella, Queen of Spain, 53 J Curve, 75–76, 76 JOBS Act (2012), 36, 261, 263 jobs created by venture-backed companies, 4 Kalanick, Travis, 172–173 Kauffman Foundation, 4 Kelleher, Herb, 46–47 Kerrest, Frederic, 132 Keynes, John Maynard, 17 last round valuation method, 77, 78–79 law firms and attorneys, 91, 102, 125, 286 Lehman Brothers, 12 Levandowski, Anthony, 102 liability and business judgement rule (BJR), 216–218, 222 and compliance and good corporate governance, 206–207 and D&O insurance, 183 and WARN statutes, 243 and winding down the company, 243–245 life cycle of venture capital, 7–8, 114–115, 268 life cycles of funds, 66–67, 68, 152 limited liability companies (LLCs), 93 limited partners (LPs), 53–68, 69–90 about, 69–71 benchmarks of, 54 capital raised from, 2 and clawbacks, 80–81 and co-investments of general partners, 86–87 and dot.com boom, 10 and exit of VC after IPO, 266–267 goals of, 56 and GP–LP relationship, 70–71, 85–88 inflation’s effect on success of, 56–57 relationship of VCs to, 69–71 and secondary offering of shares, 268 and suspension of GPs, 87–88 and taxation, 70–71, 93, 94 types of, 54–57 types of investments made by, 57–59 Yale University endowment, 54, 59–65 limited partnership agreement (LPA), 71–83 and carried interest, 74–77, 82 on expectations for GP, 87 and GP–LP relationship, 85–88 “hurdle rates” in, 83 on investment domain, 85–86 and J Curve, 75–76, 76 and management fee, 72–74, 81 “preferred returns” in, 83 recycling/reinvesting provisions in, 81 on suspension of GPs, 87–88 and valuation marks, 76–83 liquidation, voting on, 176–177 liquidation preference and comparing finance deals, 192–193 and conversion of preferred shares to common shares, 162–163, 164 and preferred shareholders, 162–163, 177 reducing/eliminating, in difficult financings, 177, 234–236, 240 and term sheets, 155–159, 279 liquidity, 258–259, 265–266 Livingston, Jessica, 20 lockup agreements, 265–266 LoudCloud, 12–18 author’s experience at, 2, 12–13, 14–15 business of, 13 decision to go public, 15–17 EDS’s acquisition of, 18 valuation of, 121–122 loyalty, duty of, 212, 215, 218 Lyft, 45, 127–128 management fees, 72–74, 81 management incentive plans and Bloodhound case, 237–239 and double-dipping prohibition, 241–242 following difficult financings, 241–242 and Trados case, 221, 226–227, 229–230 wrong incentives created with, 242 market checks, 237, 238, 239 market size and Airbnb, 52, 127 and evaluation of early-stage companies, 50–52 and Lyft, 127–128 and pitching to venture capitalists, 127–130 and raising money from venture capitalists, 114–115 McKelvey, Jim, 133 McKinnon, Todd, 132 median ten-year returns in venture capital, 30 mergers & acquisitions.

Many people are undoubtedly familiar with the concept of product-market fit. Popularized by Steve Blank and Eric Ries, product-market fit speaks to a product being so attractive to customers in the marketplace that they recognize the problem it was intended to solve and feel compelled to purchase the product. Consumer “delight” and repeat purchasing are the classic hallmarks of product-market fit. Airbnb has this, as do Instacart, Pinterest, Lyft, Facebook, and Instagram, among others. As consumers, we almost can’t imagine what we did before these products existed. Again, it is an organic pull on customers, resulting from the breakthrough nature of the product and its fitness to the market problem at which it is directed. The equivalent in founder evaluation for VCs is founder-market fit. As a corollary to the product-first company, founder-market fit speaks to the unique characteristics of this founding team to pursue the instant opportunity.


Autonomous Driving: How the Driverless Revolution Will Change the World by Andreas Herrmann, Walter Brenner, Rupert Stadler

Airbnb, Airbus A320, augmented reality, autonomous vehicles, blockchain, call centre, carbon footprint, cleantech, computer vision, conceptual framework, connected car, crowdsourcing, cyber-physical system, DARPA: Urban Challenge, data acquisition, demand response, digital map, disruptive innovation, Elon Musk, fault tolerance, fear of failure, global supply chain, industrial cluster, intermodal, Internet of things, Jeff Bezos, Lyft, manufacturing employment, market fundamentalism, Mars Rover, Masdar, megacity, Pearl River Delta, peer-to-peer rental, precision agriculture, QWERTY keyboard, RAND corporation, ride hailing / ride sharing, self-driving car, sensor fusion, sharing economy, Silicon Valley, smart cities, smart grid, smart meter, Steve Jobs, Tesla Model S, Tim Cook: Apple, uber lyft, upwardly mobile, urban planning, Zipcar

Ford’s former CEO, Mark Fields, has announced that the autopilot is to be democratised by providing inexpensive mobility to as many people as possible. He plans to develop Ford into a mobility service, offering driving services with autonomous vehicles (similar to Uber) and producing the cars for such a service itself. General Motors has invested enormously in the mobility platform Lyft, announcing plans to set up an on-demand network of self-driving cars. John Zimmer, president of Lyft, expects car ownership in megacities to be of little importance in 10 years. In 2016, Lyft already organised about 14.6 million rides per month, three times as many as a year before. So far, Cadillac is the only General Motors brand equipped with the technology for autonomous driving. It is well known that Hyundai has made substantial investments in artificial intelligence in order to create the technological basis for connected and autonomous cars.

Ownership Access and Sharing User as Use of one’s Rental car sharing, business-to-consumer (DriveNow, driver own car Car2Go) and peer-to-peer (Croove, Getaround) User as passenger Use of a taxi Ride sharing (Uber, Lyft) and carpooling (BlaBlaCar) Source: The authors. Note: Mobility apps can link up the various modes of transportation so that the user can identify the fastest and most convenient way to get from one place to another. The Sharing Economy 343 sharing (DriveNow, car2go, Flinkster, Mobility, ReachNow, ZipCar) and with peer-to-peer car sharing (Drivy, Tamyca, Croove, CarUnity, Sharoo, Turo, Getaround), users have to drive the cars themselves. With ride sharing (Uber, Lyft, myTaxi) or carpooling (BlaBlaCar), they are driven by a chauffeur. So far, most sharing models have been station based (A-to-A), i.e. the customers have to drop off the vehicle where they picked it up.

It is an economic exchange; consumers are more interested in reducing costs and increasing convenience than they are in fostering social relationships with the company or other consumers. For example, we are currently seeing the rise of Uber in the short-term ride-sharing market. Uber’s core values are its pricing, reliability and convenience better, faster and cheaper than a taxi. In comparison, Lyft, which offers an almost identical service, positions itself as friendly we’re your friend with a car and part of your community greet your driver with a fist bump. Lyft has not seen at all as much growth as Uber; one reason is because they put too much emphasis on consumers’ desire to bond with each other rather than gain access to a vehicle. Meanwhile, there are hundreds of car-sharing providers all over the world: Zipcar is well established in North America and Orix, Park24, PPzuche and EVCard operate in Japan and China.


pages: 305 words: 79,303

The Four: How Amazon, Apple, Facebook, and Google Divided and Conquered the World by Scott Galloway

activist fund / activist shareholder / activist investor, additive manufacturing, Affordable Care Act / Obamacare, Airbnb, Amazon Web Services, Apple II, autonomous vehicles, barriers to entry, Ben Horowitz, Bernie Sanders, big-box store, Bob Noyce, Brewster Kahle, business intelligence, California gold rush, cloud computing, commoditize, cuban missile crisis, David Brooks, disintermediation, don't be evil, Donald Trump, Elon Musk, follow your passion, future of journalism, future of work, global supply chain, Google Earth, Google Glasses, Google X / Alphabet X, Internet Archive, invisible hand, Jeff Bezos, Jony Ive, Khan Academy, longitudinal study, Lyft, Mark Zuckerberg, meta analysis, meta-analysis, Network effects, new economy, obamacare, Oculus Rift, offshore financial centre, passive income, Peter Thiel, profit motive, race to the bottom, RAND corporation, ride hailing / ride sharing, risk tolerance, Robert Mercer, Robert Shiller, Robert Shiller, Search for Extraterrestrial Intelligence, self-driving car, sentiment analysis, shareholder value, Silicon Valley, Snapchat, software is eating the world, speech recognition, Stephen Hawking, Steve Ballmer, Steve Jobs, Steve Wozniak, Stewart Brand, supercomputer in your pocket, Tesla Model S, Tim Cook: Apple, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, undersea cable, Whole Earth Catalog, winner-take-all economy, working poor, young professional

“Uber is the world’s largest job creator, adding about 50,000 drivers per month, says board member.” Business Insider. March 15, 2015. http://www.businessinsider.com/uber-offering-50000-jobs-per-month-to-drivers-2015-3. 22. Uber Estimate. http://uberestimator.com/cities. 23. Nelson, Laura J. “Uber and Lyft have devastated L.A.’s taxi industry, city records show.” Los Angeles Times. April 14, 2016. http://www.latimes.com/local/lanow/la-me-ln-uber-lyft-taxis-la-20160413-story.html. 24. Schneider, Todd W. “Taxi, Uber, and Lyft Usage in New York City.” February 2017. http://toddwschneider.com/posts/taxi-uber-lyft-usage-new-york-city/. 25. “Scott Galloway: Switch to Nintendo.” 26. Deamicis, Carmel. “Uber Expands Its Same-Day Delivery Service: ‘It’s No Longer an Experiment’.” Recode. October 14, 2015. https://www.recode.net/2015/10/14/11619548/uber-gets-serious-about-delivery-its-no-longer-an-experiment. 27.

If you’re a decathlete, the key is to find the event with the greatest variance in performance and own it. Uber is a great product, but I’d challenge you to identify (without knowing which ride-sharing platform you booked through) the difference between Uber, Lyft, Curb, and Didi Chuxing. The category is a 10x improvement over cabs and black cars, but there is an increasing sameness among ride-sharing players. This has likely been the case for a while, but Uber’s CEO frat rock (that is, shit for brains) behavior has prompted people to discover on their own that Lyft is the same thing. The Airbnb platform takes on greater importance as an arbiter of trust, as there is greater variance in the product—a houseboat in Marin vs. a townhouse in South Kensington. United Airlines has more differentiation than Uber right now, as they can drag someone off a plane (due to their fuck-up), but if you need to get from San Francisco to Denver (United hubs), you’re going to forgive, because that United flight is highly differentiated (only choice).

Uber faces challenges on this factor along two fronts. First, its CEO is an asshole, or at least he’s perceived as an asshole. This fact gave rise to a few instances where consumers were encouraged to delete the app, and many did. Where the firm likely lost $10 billion plus in value in forty-eight hours was not the number of people who deleted the app, but the discovery of substitutes, as Uber isn’t vertical, and Lyft was able to access many of the same drivers. It’s not just the CEO throwing up on himself. In 2014, an Uber senior vice president suggested—in the presence of a journalist—that Uber hire opposition researchers to dig up dirt on journalists who wrote unflattering stories about the company. There have been a series of reports that Uber management uses the technology’s ability to track riders in real time for entertainment or other personal reasons, including members of the press.27 In France, Uber ran an ad campaign that, at best, was sexist, and arguably suggested that Uber was a great way to hire an escort service.28 In 2016, Uber paid a $20,000 fine as part of an investigation by the New York attorney general into the misuse of its tracking capability.29 Worst of all, Uber’s likability took a major hit with Susan Fowler’s corporate sexual discrimination charges in February 2017.30 Actions by midlevel and C-level management ranged from callous to reprehensible in dozens of instances.


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

She found that, not surprisingly, while Uber itself took most of the upside of the business, drivers were often left to bear the cost and the downsides of the disruptive technology on their own. Lyft, Uber’s biggest competitor, has always been known as the kinder, gentler ridesharing company, in part because its CEO Logan Green has been more inclined to discuss the downsides of the sharing economy in a thoughtful and open way (that and the fact that he hasn’t been caught on a dashcam screaming at his own drivers). Green is, for example, concerned about the potential mass displacement of drivers in the United States (which represents the largest single category of work for men with a high school degree or less) by autonomous vehicles. Drivers themselves have reported being able to make more money on Lyft relative to Uber, and have higher levels of job satisfaction. (Lyft was first to allow tipping to drivers.)11 Unfortunately, these things fall at the margins.

The demise of companies like Jawbone and the lack of excitement about new IPOs are just two signs of the bubble economy in the Valley. Burgeoning debt is another. Netflix, for example, recently raised $2 billion through a junk bond offering to fund new content.21 It will be interesting to see how the next round of big anticipated IPOs goes—or if they go at all. Many top tech companies have opted to stay private longer, bidding up their valuations and raising expectations. Both Uber and Lyft completed disappointing IPOs as I was finishing this book. I suspect they won’t be the only companies unable to live up to the hype. I’m thinking in particular of Elon Musk’s SpaceX, but also Peter Thiel’s Palantir, which has been scaling back its thirteen-course lobster tail and sashimi lunches in anticipation of its public offering (probably a good idea, given that the company has yet to turn a profit in its fourteen-year history, despite having a valuation of $20 billion).22 Today’s darlings can so easily become tomorrow’s discards; as I finish this book, SoftBank, the bloated Japanese tech investment firm, has just scrapped its $16 billion plan to buy a stake in WeWork.

It could therefore demand almost anything it wanted from those who needed that network—and its data—to develop their own businesses. And, by the same token, Facebook could deny anyone access to those massive amounts of user data (which is the only reason other businesses are interested in being on Facebook in the first place), for any reason. As the 250 pages of emails and documents released by British lawmakers revealed, companies who were not considered competitive with Facebook, including Airbnb, Lyft, and Netflix, got preferred access to data, as did the Royal Bank of Canada and a number of other nontech businesses. But those companies that Facebook viewed as competition, like Vine (a Twitter-owned video app), were denied or even shut out of the company’s network altogether. Indeed, after Twitter released Vine in 2013, Facebook shut off Twitter’s access to Facebook friends data at Zuckerberg’s behest.1 Meanwhile, the emails revealed that Zuckerberg discussed charging app developers for access to Facebook user data, while also forcing them to share their own user data with Facebook’s network; email debates show that the company even considered restricting developer access to certain kinds of data unless the developers bought advertising on Facebook.


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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

After all, the drivers and laborers who make Uber, Lyft, Grubhub, DoorDash, Postmates, Fiverr, and TaskRabbit work can choose when and where they work with unprecedented control. Realistically, though, many of the workers in the gig economy need money. That’s why they’re side hustling. They’re underemployed or unemployed, and the minimal extra income they earn from these services—85 percent make less than $500 a month—is helping them make ends meet. That doesn’t sound like the ultimate in entrepreneurial freedom. But there’s something more troubling about the fact that one in four Americans is now participating in the gig economy. By turning work into a series of app-mediated transactions, we’re actually narrowing the scope of their participation to something closer to the opposite of entrepreneurialism. When you work at Lyft full time, you’re (hopefully) looking for ways to grow and serve Lyft all the time.

When you work at Lyft full time, you’re (hopefully) looking for ways to grow and serve Lyft all the time. If you see something worth doing, you might just do it. But when you drive for Lyft as a gig, your relationship is read-only. You transact, but you do not serve the bigger picture. Why would you? And that’s the problem. If we move toward an economy where everyone is paid “by the drink,” we run the risk of eliminating good corporate citizenship. If we thin slice the work too much, we’ll watch as “that’s not my job” becomes a mantra and a way of life. And that disconnection will rise at precisely the moment when we need all hands and minds on deck to invent the future. Compensation in Action Transparent Compensation. Considering the significance we attach to compensation, it’s somewhat surprising that the subject is taboo.

Evolutionary Organizations AES Askinosie Chocolate Automattic Basecamp Black Lives Matter Blinkist Bridgewater Buffer Burning Man Buurtzorg BvdV charity: water Crisp David Allen Company dm-drogerie markt elbdudler Endenburg Elektrotechniek Enspiral Equinor Evangelical School Berlin Centre Everlane FAVI Gini GitLab Gumroad Haier Handelsbanken Haufe-umantis Heiligenfeld Hengeler Mueller Herman Miller HolacracyOne Ian Martin Group / Fitzii Incentro John Lewis Joint Special Operations Command Kickstarter Lumiar Schools Medium Menlo Innovations Mondragon Morning Star Nearsoft Netflix Nucor Orpheus Chamber Orchestra Patagonia Phelps Agency Pixar Premium-Cola Promon Group Red Hat School in the Cloud Schuberg Philis Semco Group Spotify stok Sun Hydraulics Treehouse USS Santa Fe Valve Whole Foods W. L. Gore WP Haton Zalando Technology Zappos Zingerman’s Sources of Inspiration Airbnb Amazon Chipotle Chobani Danone North America Etsy Facebook GitHub Google Johnsonville Lyft Quicken Loans Slack Southwest Airlines Stack Overflow Toyota Warby Parker WeWork Wikimedia Zapier USING THE OS CANVAS The canvas can provoke incredible conversations and powerful stories. It can help you and your team identify what to amplify and what to change. It can even help you find unexpected sources of inspiration. But for your first foray into what can be an emotional and challenging conversation, we recommend a lightly structured workshop format that has proven to be both safe and effective.


pages: 244 words: 66,977

Subscribed: Why the Subscription Model Will Be Your Company's Future - and What to Do About It by Tien Tzuo, Gabe Weisert

3D printing, Airbnb, airport security, Amazon Web Services, augmented reality, autonomous vehicles, blockchain, Build a better mousetrap, business cycle, business intelligence, business process, call centre, cloud computing, cognitive dissonance, connected car, death of newspapers, digital twin, double entry bookkeeping, Elon Musk, factory automation, fiat currency, Internet of things, inventory management, iterative process, Jeff Bezos, Kevin Kelly, Lean Startup, Lyft, manufacturing employment, minimum viable product, natural language processing, Network effects, Nicholas Carr, nuclear winter, pets.com, profit maximization, race to the bottom, ride hailing / ride sharing, Sand Hill Road, shareholder value, Silicon Valley, skunkworks, smart meter, social graph, software as a service, spice trade, Steve Ballmer, Steve Jobs, subscription business, Tim Cook: Apple, transport as a service, Uber and Lyft, uber lyft, Y2K, Zipcar

The company may take a short-term profitability hit, but the goal is to gain long-term customer loyalty in a very young and turbulent market—and this customer loyalty is becoming more and more important as ridesharing becomes a commodity. Here in the Bay Area, the Uber and Lyft markets are really fluid. I’ll frequently toggle between the two services—lots of the cars even feature both logos in their windshields. There’s very little brand loyalty on my part. Now contrast that with my Amazon Prime experience. All due respect to other potential ecommerce vendors, but Amazon has my business, in no small part due to Amazon Prime—they hooked me with the free shipping, and now I’ve got music, movies, and all sorts of other services. I’m not going anywhere. Uber and Lyft are both vying for that same lock-in effect by offering discounted services around consistent consumption patterns—in other words, they’re going after my commute. As Lyft president John Zimmer, anticipating fully autonomous vehicles, told The New York Times: “The cost of owning a car is $9,000 a year.

Netflix was still delivering monthly DVDs in the mail, but it was already killing Blockbuster and changing how we consumed media. Online streaming was just around the corner (as many people have pointed out, Reed Hastings called it Netflix for a reason). Zipcar was also a really interesting new concept. It was initially seen as an hourly competitor to Hertz and Budget, but you could already see new ideas opening up around cars and transportation, which Uber and Lyft capitalized on later. And of course the iPhone had just come out—at the time it was more of a fun, plug-and-play app container, but there was the potential for geolocation, identity, messaging. As bandwidth increased and platform costs decreased, there was a logical progression going on toward on-demand, digitally enabled services. And it was happening everywhere. That’s when we decided to start a new company called Zuora.

But what came as a surprise was that 80 percent of people we polled had Zipcar memberships. Yes, there were massive limitations to Zipcar—you had to live in a city, for example. But we could see that the next revisions of this concept (give me the ride, not the car) were just going to get better and better. That experience let us see a future world where car ownership would not be necessary. Today more than 60 million riders use Uber and Lyft. These ridesharing services have ushered in a whole new set of consumer priorities: Why buy a car at all, when all you need to do to get from point A to point B is pull out your phone? Why can’t I just subscribe to transportation the same way I subscribe to electricity and internet access? But wait, you might say. Uber isn’t a subscription service—there are no monthly fees. I disagree. It sure looks and feels like a digital subscription service to me.


pages: 173 words: 53,564

Fair Shot: Rethinking Inequality and How We Earn by Chris Hughes

"side hustle", basic income, Donald Trump, effective altruism, Elon Musk, end world poverty, full employment, future of journalism, gig economy, high net worth, income inequality, invisible hand, Jeff Bezos, job automation, knowledge economy, labor-force participation, Lyft, M-Pesa, Mark Zuckerberg, meta analysis, meta-analysis, new economy, oil rush, payday loans, Peter Singer: altruism, Potemkin village, precariat, randomized controlled trial, ride hailing / ride sharing, Ronald Reagan, Second Machine Age, self-driving car, side project, Silicon Valley, TaskRabbit, The Bell Curve by Richard Herrnstein and Charles Murray, traveling salesman, trickle-down economics, uber lyft, universal basic income, winner-take-all economy, working poor, working-age population, zero-sum game

Instead of reaching for a pair of barber shears, they reach for their smartphones and register to become Lyft drivers and Postmates delivery people. TaskRabbiters pitch in to assemble furniture, rake leaves, or even stand in line to buy theater tickets or a newly released iPhone. In some cases, these contract jobs are a godsend because they help workers who only get part-time hours elsewhere to supplement their income, as laborers have done since the beginning of time. We often think of millennials in these jobs, the masters of the art of the “side hustle,” but the numbers show it isn’t just millennials doing contingent work. A quarter of the working-age population in the United States and Europe engage in some type of independently paid gig, some by choice, but many out of necessity. People who find work through apps like Lyft and TaskRabbit get a lot of attention, but they are the tip of the iceberg.

They arrived in 1929, just in time for the stock market’s collapse. For the next two years, my grandparents lived alongside 11 other people in a standalone house in Philadelphia’s Frankford neighborhood. Lacking any education or nonfarm skills, my grandfather decided that he would become a barber. In my imagination, I see a Southern kid roaming about a dense Philadelphia neighborhood waiting for a client in need, like a Lyft or Uber driver of today except with a pair of scissors in hand. My grandfather had cut hair—he had those shears to prove it—but he had never really been a barber like the barbers I would later see as an adult. (The bowl cuts he gave me as a kid confirmed that he had failed to develop any meaningful skill.) Crammed in like sardines with his family in a new city, he learned to make do because anything that contributed to the family’s income, even a few dollars, helped.

The jobs that disappeared first were the ones that required manual, routine labor, like in automobile manufacturing, historically one of the largest employers in the area. The world’s largest automobile manufacturer, General Motors, made twice as many cars in 2011 as it made 55 years earlier with a third of the workforce. A single worker in 1955 made 8 cars; in 2011, 43. To be sure, at the same time as technological advancements have destroyed jobs, they have created others, like Lyft drivers and Walmart workers. But the new jobs often require different skills, are unreliable, and pay worse. Walmart employees working less than 30 hours a week have no benefits, insurance, vacation, or paid leave, and what’s more, they are lucky to make $15 an hour. That’s a far cry from a factory worker who, at least in one region of Ohio, used to make $40 an hour or more, including the value of benefits.


pages: 242 words: 73,728

Give People Money by Annie Lowrey

"Robert Solow", affirmative action, Affordable Care Act / Obamacare, agricultural Revolution, Airbnb, airport security, autonomous vehicles, barriers to entry, basic income, Bernie Sanders, bitcoin, clean water, collective bargaining, computer age, crowdsourcing, cryptocurrency, deindustrialization, desegregation, Donald Trump, Edward Glaeser, Elon Musk, ending welfare as we know it, everywhere but in the productivity statistics, full employment, gender pay gap, gig economy, Google Earth, Home mortgage interest deduction, income inequality, indoor plumbing, information asymmetry, Jaron Lanier, jitney, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Kickstarter, Kodak vs Instagram, labor-force participation, late capitalism, Lyft, M-Pesa, Mahatma Gandhi, Mark Zuckerberg, mass incarceration, McMansion, Menlo Park, mobile money, mortgage tax deduction, new economy, obamacare, Peter Thiel, post scarcity, post-work, Potemkin village, precariat, randomized controlled trial, ride hailing / ride sharing, Robert Bork, Ronald Reagan, Sam Altman, self-driving car, Silicon Valley, single-payer health, Steve Jobs, TaskRabbit, The Future of Employment, theory of mind, total factor productivity, Turing test, two tier labour market, Uber and Lyft, uber lyft, universal basic income, uranium enrichment, War on Poverty, Watson beat the top human players on Jeopardy!, We wanted flying cars, instead we got 140 characters, women in the workforce, working poor, World Values Survey, Y Combinator

There’s no way to get ahead doing this.” The drivers explained how and why in vivid detail. “There were more and more people jumping on to Lyft and Uber, especially Uber, and then at one point, Uber was doing this special thing to try and get more passengers, where they did a discount or they took out the service charge for passengers,” Heather Smith, an Uber and Lyft driver, told me. (I agreed to withhold her real last name, to avoid retaliation by her employers.) “When I would look at my breakdown of payment, I was basically seeing them pay themselves and then take half the service charge and then pay me. I said, ‘Fuck it. Good-bye, Uber.’ ” She told me that she did make decent money mentoring new drivers for Lyft. “Well, they didn’t compensate for me doing the calls and stuff like that, but once I would meet with the person and do a mentor session, which is usually like thirty minutes, forty-five at the max, then I would be paid $35 just for that session,” she said.

The economy gets rid of bad jobs while creating better new ones. Workers do adjust, if not always easily. In part, they adjust by moving. Millions of workers have left Detroit and the Rust Belt, for instance, heading to the sunny service economy of the Southwest or to the oil economy of the Gulf of Mexico. They also adjust by switching industries. On my way to Detroit, in a moment of Tom Friedman–esque folly, I asked the Lyft driver taking me to the Baltimore airport what he thought of the company’s plans to shift to driverless cars and the potential that he would soon be out of a job. “It’s worrisome,” he conceded. “But I’m thinking of trying to get some education to become someone to service them. You’re not going to just be able to take those cars into the shop, with the regular guys who are used to fixing the old models.

On-demand, gig-economy firms usually do not hire their drivers or shoppers or delivery workers, instead classifying them as contractors and buying their services. That means that the companies are not subject to minimum-wage rules. They do not need to divert their workers’ paychecks into unemployment-insurance funds or Social Security. They are not required to offer health care to workers who spend full-time hours on the clock. Many Uber and Lyft drivers feel the companies had misled them, promising, if not employment in a traditional sense, a stake in something. “When you sign up, they refer to you as a partner,” Seth McGrath, a forty-year-old Uber driver, chimed in, as everyone around the table nodded. “Which is so not true. They keep you at arm’s length, right? You can’t call anyone. You can’t talk to a warm body.” The sudden rise of gig-economy jobs in many ways feels like the apotheosis of the past half century of workplace trends.


pages: 288 words: 66,996

Travel While You Work: The Ultimate Guide to Running a Business From Anywhere by Mish Slade

Airbnb, Atul Gawande, business process, Checklist Manifesto, cloud computing, crowdsourcing, Firefox, Google Chrome, Google Hangouts, Inbox Zero, job automation, Kickstarter, low cost airline, Lyft, remote working, side project, Skype, speech recognition, turn-by-turn navigation, uber lyft

For example: Uber (www.worktravel.co/uber) currently operates in cities in 55 countries. Here's the full list: www.worktravel.co/ubercities. Note: if you use the link www.worktravel.co/uber to sign up to Uber, you'll get a free ride (worth up to about $15). My Taxi (www.worktravel.co/mytaxi) does the same thing as Uber, but has presence in Spain – where Uber is currently banned. There's also Lyft (www.worktravel.co/lyft), but that currently only operates in certain US cities. Gett (www.worktravel.co/gett) is similar to Lyft and Uber, but the pricing remains consistent (there's no "surge pricing", and you can book cabs in advance. Gett currently operates in the USA, UK, Israel and Russia – but many other countries are coming on board soon. There are also city-specific taxi apps; have a search for "taxi app [city]" and see what comes up (or ask a local).

CHAPTER 1: SETTLE IN FAST Maps, directions and notekeeping Google Keep (note-taking app): www.worktravel.co/keep Google Maps: www.worktravel.co/gmaps Google Maps – how to store destinations as favourites: www.worktravel.co/mapfaves Google Maps Directions: www.worktravel.co/directions Google Maps list of offline maps: www.worktravel.co/offlinemaps Google Maps - how to download an offline map: www.worktravel.co/offlinemaps2 OsmAnd (offline maps with navigation): www.worktravel.co/osmand Here Maps (offline maps): www.worktravel.co//here Taxis Uber (taxi app): www.worktravel.co/uber Uber (list of cities): www.worktravel.co/ubercities MyTaxi (taxi app): www.worktravel.co/mytaxi Lyft (taxi app): www.worktravel.co/lyft Gett (taxi app): www.worktravel.co/gett Languages/translation Google Translate: www.worktravel.co/gtranslate XE (currency conversion): www.worktravel.co/xe Anki (flashcard app): www.worktravel.co/anki Duolingo (language learning): www.worktravel.co/duolingo Michel Thomas (language learning): www.worktravel.co/michel Money/cost of living Numbeo (cost of living in different cities): www.worktravel.co/numbeo GlobeTipping (global tipping app for iPhone): www.worktravel.co/globetipping Global Tip Calculator Pro (global tipping app for Android): www.worktravel.co/globalpro SIM cards Prepaid with Data (info on SIM cards around the world): www.worktravel.co/prepaid TripAdvisor forum (search for info on "monthly prepaid SIM 3G": www.worktravel.co/taforum Lonely Planet forum (has useful Q&As about SIMs around the world): www.worktravel.co/planetforum Restaurant, cafe, attraction, etc. reviews and info Foursquare (good for Europe): www.worktravel.co/foursquare Yelp (good for US and Europe): www.worktravel.co/yelp Spotted by Locals: www.worktravel.co/spotted Tabelog (Japan): www.worktravel.co/tabelog Vayable (marketplace where locals offer unique tours): www.worktravel.co/vayable) Receive mail Poste Restante (Wikipedia page): www.worktravel.co/post Amazon Lockers: www.worktravel.co/locker DHL Packstations (pickup lockers in Germany): www.worktravel.co/packstation Doddle (pickup lockers in the UK): www.worktravel.co/doddle My Pick Box (pickup lockers in Spain): www.worktravel.co/pickup Parcel (get all mail delivered to a unique address, which they'll then deliver at a convenient time): www.worktravel.co/parcel Mail-forwarding services UK Postbox: www.worktravel.co/ukpost Earth Class Mail (USA): www.worktravel.co/earthclass ClevverMail (Germany): www.worktravel.co/clevver Aussie Mail Man: www.worktravel.co/aussie Find/make friends Find A Nomad: www.worktravel.co/findanomad Create Your Nomadtopia: www.worktravel.co/topia ShareDesk (coworking spaces): www.worktravel.co/sharedesk Fitness Walking/cycling/running: OsmAnd (offline maps): www.worktravel.co/osmand Ride With GPS (routes): www.worktravel.co/gps Lanyard (for holding phone and following route while running/cycling): www.worktravel.co/lanyard Apartment-friendly exercise videos: Fitness Blender: www.worktravel.co/blender DDP Yoga: www.worktravel.co/ddp Do You Yoga: www.worktravel.co/yoga Focus T25: www.worktravel.co/t25 Sleek Technique: www.worktravel.co/sleek Community fitness: Project Awesome (London): www.worktravel.co/awesome November Project (USA): www.worktravel.co/november CHAPTER 2: GET TO GRIPS WITH MONEY AND TAXES Credit/debit card charges If you're from the UK… Comparison of debit card fees: www.worktravel.co/ukdebit Comparison of credit card fees: www.worktravel.co/ukcredit Best specialist travel credit cards: www.worktravel.co/uktravelcredit Info about travel debit cards: www.worktravel.co/uktraveldebit Supercard (still in testing phase at the time of writing, and only currently available for UK residents): www.worktravel.co/supercard Number26 (still in testing phase at the time of writing, and also available throughout the rest of Europe): www.worktravel.co/26 If you're from the US… List of credit cards that don't charge a foreign transaction fee: www.worktravel.co/ustravelcredit List of banks and their debit card transaction/ATM fees: www.worktravel.co/ustraveldebit Info about avoiding credit/debit card transaction fees: www.worktravel.co/avoidfees Charles Schwab (reimburses ATM fees): www.worktravel.co/schwab If you're from Australia… Info on credit/debit cards and fees: www.worktravel.co/finder More info in the book if you're from anywhere else!


pages: 257 words: 90,857

Everything's Trash, but It's Okay by Phoebe Robinson

23andMe, Airbnb, Bernie Madoff, Bernie Sanders, crack epidemic, Donald Trump, double helix, Downton Abbey, Elon Musk, feminist movement, Firefox, Lyft, Mahatma Gandhi, Mark Zuckerberg, Rosa Parks, Silicon Valley, Silicon Valley startup, Tim Cook: Apple, uber lyft

We all have; however, in the age of #TimesUp and #MeToo, when people are thrown the softball of defending trans women yet fail to do so . . . Say it with me, y’all: Feminism! I was rooting for you; we were all rooting for you! Sadly, this is a sentiment I have expressed often over my course of being a feminist, but I probably felt it most in the days and weeks following the Trump election. I spent days after the election gathering my bearings. I would cry in Lyfts. Or get on the phone with my dad and talk to him for hours. Or do comedy shows because laughter is a great reprieve from anger. During this time, hurt, rage, restlessness, and a litany of other emotions layered on top of each like winter clothing during a ski trip, and pretty soon a call to action was formed. And not like the BS call to action like when a friend sends a mass email telling people to subscribe to their YouTube page, or the one I got recently from college friends whose ten-year wedding anniversary is coming up, so they’re asking people to donate money so they can celebrate their marriage.

If you’re unsure, use a Who Wants to Be a Millionaire lifeline or something. I wouldn’t judge your journey. But to be this sloppy makes my vajeen and I quote the great scholar of our time, music producer/American Idol judge Randy Jackson: “It’s gonna be a ‘no’ from me, dawg.” Thirdly. Sowwie not sowwie, but last I checked, my name is not “White Girl Murder Victim in the First Five Minutes of Criminal Minds,” so, no, I will not be taking a Lyft to your crib so I can be murderized. Coretta Scott King didn’t go through all she went through for me to go out like that. In my mind, she worked her tail off so I can work my way onto the Obamas’ holiday-card recipient list. In all seriousness, this is the kind of grossness hetero broads deal with no matter the dating app—Tinder, Match.com, Bumble, Raya, etc.—but I decided to not let it discourage me completely, and I remained on Tinder for another week.

Anyway, one of the first results that popped up was an article by Psychology Today, so I clicked on the link and this was the opening paragraph: Workaholism is a soul-destroying addiction that changes people’s personality and the values they live by. It distorts the reality of each family member, threatens family security and often leads to family break-up. Tragically, workaholics eventually suffer the loss of personal and professional integrity. Gahtdamn, Psychology Today! This is how you open?!?! You’re at a twelve (my Lyft driver blasting Metallica at 11:45 P.M. in his compact Toyota Corolla), and I need you to be at a two (the volume my music is at when I’m at the checkout counter and have to spend five minutes correcting the cashier’s spelling of my first name). In all seriousness, while the picture that Psychology Today painted is accurate for plenty of workaholics, it wasn’t for me. My family was not on the verge of falling apart because I was juggling two podcasts, nor had my professional integrity been compromised, leading to my committing a white-collar crime.


pages: 443 words: 98,113

The Corruption of Capitalism: Why Rentiers Thrive and Work Does Not Pay by Guy Standing

3D printing, Airbnb, Albert Einstein, Amazon Mechanical Turk, Asian financial crisis, asset-backed security, bank run, banking crisis, basic income, Ben Bernanke: helicopter money, Bernie Sanders, Big bang: deregulation of the City of London, bilateral investment treaty, Bonfire of the Vanities, Boris Johnson, Bretton Woods, business cycle, Capital in the Twenty-First Century by Thomas Piketty, carried interest, cashless society, central bank independence, centre right, Clayton Christensen, collapse of Lehman Brothers, collective bargaining, credit crunch, crony capitalism, crowdsourcing, debt deflation, declining real wages, deindustrialization, disruptive innovation, Doha Development Round, Donald Trump, Double Irish / Dutch Sandwich, ending welfare as we know it, eurozone crisis, falling living standards, financial deregulation, financial innovation, Firefox, first-past-the-post, future of work, gig economy, Goldman Sachs: Vampire Squid, Growth in a Time of Debt, housing crisis, income inequality, information retrieval, intangible asset, invention of the steam engine, investor state dispute settlement, James Watt: steam engine, job automation, John Maynard Keynes: technological unemployment, labour market flexibility, light touch regulation, Long Term Capital Management, lump of labour, Lyft, manufacturing employment, Mark Zuckerberg, market clearing, Martin Wolf, means of production, mini-job, Mont Pelerin Society, moral hazard, mortgage debt, mortgage tax deduction, Neil Kinnock, non-tariff barriers, North Sea oil, Northern Rock, nudge unit, Occupy movement, offshore financial centre, oil shale / tar sands, open economy, openstreetmap, patent troll, payday loans, peer-to-peer lending, plutocrats, Plutocrats, Ponzi scheme, precariat, quantitative easing, remote working, rent control, rent-seeking, ride hailing / ride sharing, Right to Buy, Robert Gordon, Ronald Coase, Ronald Reagan, Sam Altman, savings glut, Second Machine Age, secular stagnation, sharing economy, Silicon Valley, Silicon Valley startup, Simon Kuznets, sovereign wealth fund, Stephen Hawking, Steve Ballmer, structural adjustment programs, TaskRabbit, The Chicago School, The Future of Employment, the payments system, The Rise and Fall of American Growth, Thomas Malthus, Thorstein Veblen, too big to fail, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, Y Combinator, zero-sum game, Zipcar

A feature of all these companies is that they require full access to their clients’ bank accounts and other personal data, which they use to determine whether to provide loans, what interest rate to charge and for how long to lend. THE PLATFORM DEBT MACHINE The misnamed ‘sharing economy’ is also fostering indebtedness. App-based taxi services, such as Uber and Lyft, have tie-ups with lenders that enable drivers to buy vehicles on credit. Big car companies are becoming involved. In January 2016, General Motors announced a deal with Lyft, under which it would supply rental vehicles to Lyft drivers. In 2015, Ford introduced a pilot scheme in London and six US cities allowing customers buying cars on credit to rent them out through peer-to-peer car rental platform companies. The idea is that customers will be more likely to buy a car through Ford Credit, and keep up regular instalments, if they can earn extra income by renting it out.

In 2015, it had 1.5 million listings, ranging from spare beds to castles in 34,000 cities and over 190 countries, and had more rooms on its books than some of the world’s largest hotel chains. On the retail side, one and a half million ‘makers’ sell jewellery, clothing and accessories through the online marketplace Etsy, giving small-scale artisans access to buyers all over the world. Some platforms are in direct competition with older forms of service. These include Uber, its US rival Lyft and imitators elsewhere such as GrabTaxi, operating in Southeast Asia, Ola in India and Didi Kuaidi in China. BlaBlaCar, a French start-up originally called Covoiturage, is a car-sharing platform that enables drivers making long journeys to share the cost by ‘selling’ empty seats. BlaBlaCar does not compete with taxis, since its average trip is 200 miles (320 kilometres). However, it could be said to compete with coaches and trains.

The platforms maximise profits through ownership and control of the technological apparatus, protected by patents and other forms of intellectual property rights, and by the exploitation of labour through tasking and unpaid work. Labour brokers are rentiers, earning a lot for doing little, if we accept their claim that they are just providing technology to put clients in touch with ‘independent contractors’ of services. Thus, Uber and rival Lyft insist they are technology, not transport companies. As platform-based tasking expands, it will be appreciated just how isolated the precariat is in this zone, in constant competition with one another. The atomisation drives down wages and transfers costs, risk and uncertainty onto the precariat. So far at least, taskers have had minimal means or opportunities to coalesce.41 The ‘sharing economy’ has a cultural dimension as well.


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

Municipal and national politicians have come to Scholz and me, among others, in search of policies to consider and evidence they will work. The city of Barcelona has taken steps to enshrine platform cooperativism into its economic strategies. After Austin, Texas, required Uber and Lyft drivers to perform standard safety screenings, the companies pulled their services from the city in May 2015, and the city council aided in the formation of a new co-op taxi company and a nonprofit ride-sharing app; the replacements worked so well that Uber and Lyft paid millions of dollars in lobbying to force their way back before Austin became an example. Meanwhile, UK Labour Party leader Jeremy Corbyn issued a “Digital Democracy Manifesto” that included “platform cooperatives” among its eight planks.26 The challenge of such digital democracy goes beyond local tweaks.

What’s more, the airport was planning to change the whole system, just as Green Taxi organized to claim its market share. The airport’s website had a notice about an impending contract bid for taxi companies, replacing the permits. This could reshape the city’s taxi business and make or break Green Taxi’s plan to cooperativize—and unionize, with CWA—one-third of the market. The airport’s new regime affected only taxi companies, but it had everything to do with the influx of apps. Unlike taxis, Uber and Lyft drivers faced no restrictions on their airport usage. They often drove nicer cars and spoke better English; they were more likely to be white. In December 2014, the app drivers made 10,822 trips through the airport, compared to 30,535 by taxis. A year later, for the first time, app-based airport trips exceeded the taxis, and they’d done so every month since. As taxi companies prepared to fight among themselves under the still-unpublished new rules, Silicon Valley’s expansion proceeded unrestrained—even welcomed by the relevant authorities.

To that end, he and his crisis-ridden co-owners pooled more than $1.5 million to put one-third of Denver’s taxi industry under worker control. Self-driving cars hadn’t come to the city’s roads yet, but Wall Street’s anticipation of them was fueling investment in the big apps, which put pressure on the taxi market and motivated so many drivers to set off on their own. The disruption was already happening, and Green Taxi had been born of it. In the beginning, before Uber and Lyft and even checkered taxicabs, there was sharing. At least that’s the story according to Dominik Wind, a German environmental activist with a genial smile and a penchant for conspiracy theories. Years ago, out of curiosity, Wind visited Samoa for half a year; he found that people shared tools, provisions, and sexual partners with their neighbors. Less encumbered by industrial civilization, they appeared to share with an ease and forthrightness long forgotten in the world Wind knew back home.


pages: 327 words: 90,542

The Age of Stagnation: Why Perpetual Growth Is Unattainable and the Global Economy Is in Peril by Satyajit Das

"Robert Solow", 9 dash line, accounting loophole / creative accounting, additive manufacturing, Airbnb, Albert Einstein, Alfred Russel Wallace, Anton Chekhov, Asian financial crisis, banking crisis, Berlin Wall, bitcoin, Bretton Woods, BRICs, British Empire, business cycle, business process, business process outsourcing, call centre, capital controls, Capital in the Twenty-First Century by Thomas Piketty, Carmen Reinhart, Clayton Christensen, cloud computing, collaborative economy, colonial exploitation, computer age, creative destruction, cryptocurrency, currency manipulation / currency intervention, David Ricardo: comparative advantage, declining real wages, Deng Xiaoping, deskilling, disintermediation, disruptive innovation, Downton Abbey, Emanuel Derman, energy security, energy transition, eurozone crisis, financial innovation, financial repression, forward guidance, Francis Fukuyama: the end of history, full employment, gig economy, Gini coefficient, global reserve currency, global supply chain, Goldman Sachs: Vampire Squid, happiness index / gross national happiness, Honoré de Balzac, hydraulic fracturing, Hyman Minsky, illegal immigration, income inequality, income per capita, indoor plumbing, informal economy, Innovator's Dilemma, intangible asset, Intergovernmental Panel on Climate Change (IPCC), Jane Jacobs, John Maynard Keynes: technological unemployment, Kenneth Rogoff, knowledge economy, knowledge worker, light touch regulation, liquidity trap, Long Term Capital Management, low skilled workers, Lyft, Mahatma Gandhi, margin call, market design, Marshall McLuhan, Martin Wolf, Mikhail Gorbachev, mortgage debt, mortgage tax deduction, new economy, New Urbanism, offshore financial centre, oil shale / tar sands, oil shock, old age dependency ratio, open economy, passive income, peak oil, peer-to-peer lending, pension reform, plutocrats, Plutocrats, Ponzi scheme, Potemkin village, precariat, price stability, profit maximization, pushing on a string, quantitative easing, race to the bottom, Ralph Nader, Rana Plaza, rent control, rent-seeking, reserve currency, ride hailing / ride sharing, rising living standards, risk/return, Robert Gordon, Ronald Reagan, Satyajit Das, savings glut, secular stagnation, seigniorage, sharing economy, Silicon Valley, Simon Kuznets, Slavoj Žižek, South China Sea, sovereign wealth fund, TaskRabbit, The Chicago School, The Great Moderation, The inhabitant of London could order by telephone, sipping his morning tea in bed, the various products of the whole earth, the market place, the payments system, The Spirit Level, Thorstein Veblen, Tim Cook: Apple, too big to fail, total factor productivity, trade route, transaction costs, uber lyft, unpaid internship, Unsafe at Any Speed, Upton Sinclair, Washington Consensus, We are the 99%, WikiLeaks, Y2K, Yom Kippur War, zero-coupon bond, zero-sum game

The economy that benefits everyone focuses on transport (Uber, Lyft, Sidecar, GetTaxi, Hailo), short-term accommodation (Airbnb, HomeAway), small tasks (TaskRabbit, Fiverr), grocery-shopping services (Instacart), home-cooked meals (Feastly), on-demand delivery services (Postmates, Favor), pet transport (DogVacay, Rover), car rental (RelayRides, Getaround), boat rental (Boatbound), and tool rental (Zilok). Its cheerleaders frame the sharing economy in lofty utopian terms: it's not business, but a social movement, transforming relationships between people in a new form of Internet intimacy. Customers are not getting cheap services, but being helped by new, interesting friends. Providers are engaged in rich and diverse work, gaining valuable independence and flexibility. Lyft's slogan is “Your Friend with a Car.” Airbnb and Feastly urge hosts and guests to share photos and communicate to build trust.

Some things remain the same. Researchers have found that, accounting for other variables, Airbnb guests pay black hosts less than they do white ones.8 The sharing economy, in reality, relies on disintermediating existing businesses and minimizing regulatory costs. Amateur chauffeurs, chefs, and personal assistants now perform, at a lower cost, work once undertaken by full-time professionals. Airbnb, Lyft, and others do not always comply with regulations designed to ensure a minimum level of skill, standard of performance, safety and security, and insurance coverage. Taxi and hire-car drivers have protested about services that undercut their often regulated charges and livelihoods. There have been anecdotes about orgies in Airbnb-rented properties, and accidents or assaults involving ride-sharing drivers.

Uber has obtained financing of more than US$1.5 billion, valuing the business at US$40 billion—a higher valuation than traditional car hire companies such as Hertz and Avis, and publicly listed transport companies such as Delta Air Lines, American Airlines, and United Continental. Airbnb has a higher value than all but the biggest hotel chains. Given the high stakes, competition is fierce, unethical, and unsavory. Uber has admitted trying to disrupt Lyft's fundraising efforts. It does not welcome criticism, allegedly considering spending a million dollars to hire researchers to uncover information on the personal lives of reporters critical of its service in order to discredit them. TaskRabbit makes it difficult for the bunnies to communicate with each other, preventing them from organizing or unionizing. In the latest technology gold rush, venture capital investors are speculating on businesses that effectively broker arrangements between customers and workers, betting that low prices will create mass markets for services once reserved for the wealthy.


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

Feeding more activity to the ledger simply cedes more of humanity and business alike to a growth-centric industrial model that was invented to thwart us to begin with. That’s the problem with any of the many new ways we have of earning income through previously off-the-books activities. On the one hand, they create thrilling new forms of peer-to-peer commerce. eBay lets us sell our attic junk. Web site Airbnb lets us rent out our extra bedrooms to travelers. Smartphone apps Uber and Lyft let us use our vehicles to give people rides, for money. Unlike many of the other platforms we’ve looked at so far, these opportunities don’t lead to power-law distributions, because a car or home can be hired only by one person at a time. As long as you’re listed on the network and have decent reviews, you should do as well as anyone else. From the consumer’s side, these apps are amazing. If you need a ride, you can open Uber and see a map of the area along with tiny icons for the available cars.

Their ads show people sharing an extra bedroom and a place at the family table, but the statistics reveal that the vast majority (87 percent) of hosts leave their homes in order to rent them.37 Homes become amateur hotels, as the original residents try to live off the arbitrage between the rent they pay, the rent they earn, and the cost of living somewhere other than home. Even if you are having trouble finding work in the digital economy, you no longer have an excuse for being entirely off the books. Just don’t let the landlord find out what you’re doing. Likewise, the amateur taxi networks of Uber and Lyft are great ways for otherwise “underemployed” vehicle owners to make a few extra bucks. There’s no reason now to leave a worthwhile asset or hour off the books—even if the underemployed are really underpaid freelancers working a whole lot of hours already. These apps are not about sharing space in a vehicle—like driving a friend to the train station—they’re about monetizing unemployed people’s time and stuff.

Perhaps—but with a twist: the new businesses of the digital era aren’t stand-alone companies like stores or manufacturers but, as they say, entire platforms. This makes them capable of reconfiguring their whole sectors almost overnight. They aren’t just the operators—they are the environment. To become an entire environment, however, a platform must win a rather complete monopoly of its sector. Uber can’t leverage anything if it’s just one of several competing ride-sharing apps. That’s why the company must behave so aggressively. Uber’s rival, Lyft, documented over 5,000 canceled calls made to its drivers by Uber recruiters, allegedly in an effort to get drivers to change platforms.26 It’s not that there’s too little market share to go around; it’s that Uber doesn’t mean to remain a taxi-hailing application. In order to become our delivery service, errand runner, and default app for every other transportation-related function, Uber first has to own ride-sharing completely.


pages: 393 words: 91,257

The Coming of Neo-Feudalism: A Warning to the Global Middle Class by Joel Kotkin

Admiral Zheng, Andy Kessler, autonomous vehicles, basic income, Bernie Sanders, call centre, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, Cass Sunstein, clean water, creative destruction, deindustrialization, demographic transition, don't be evil, Donald Trump, edge city, Elon Musk, European colonialism, financial independence, Francis Fukuyama: the end of history, gig economy, Gini coefficient, Google bus, guest worker program, Hans Rosling, housing crisis, income inequality, informal economy, Jane Jacobs, Jaron Lanier, Jeff Bezos, job automation, job satisfaction, Joseph Schumpeter, land reform, liberal capitalism, life extension, low skilled workers, Lyft, Mark Zuckerberg, market fundamentalism, Martin Wolf, mass immigration, megacity, Nate Silver, new economy, New Urbanism, Occupy movement, Parag Khanna, Peter Thiel, plutocrats, Plutocrats, post-industrial society, post-work, postindustrial economy, postnationalism / post nation state, precariat, profit motive, RAND corporation, Ray Kurzweil, rent control, Richard Florida, road to serfdom, Robert Gordon, Sam Altman, Satyajit Das, sharing economy, Silicon Valley, smart cities, Steve Jobs, Stewart Brand, superstar cities, The Death and Life of Great American Cities, The Future of Employment, The Rise and Fall of American Growth, Thomas L Friedman, too big to fail, trade route, Travis Kalanick, Uber and Lyft, uber lyft, universal basic income, unpaid internship, upwardly mobile, We are the 99%, Wolfgang Streeck, women in the workforce, working-age population, Y Combinator

The instability in employment is widely seen as one reason for the country’s ultra-low birth rate.15 Many of today’s “precariat” work in the contingent “gig” economy, associated with firms such as Uber and Lyft. These companies and their progressive allies, including David Plouffe (who managed Barack Obama’s presidential campaign in 2008), like to speak of a “sharing” economy that is “democratizing capitalism” by returning control of the working day to the individual. They point to opportunities that the gig economy provides for people to make extra money using their own cars or homes. The corporate image of companies like Uber and Lyft features moonlighting drivers saving up cash for a family vacation or a fancy date while providing a convenient service for customers—the ultimate win-win.16 Yet for most gig workers there’s not very much that is democratic or satisfying in it.

CHAPTER 18 The Totalitarian Urban Future The new urban paradigm elevates efficiency and central control above privacy local autonomy class diversity and broad-based property ownership. The same oligarchs who dominate our commercial culture, seek to profit from manipulating our moods, and influence the behavior of our children want to structure our living environment as well.1 Major tech firms—Y Combinator, Lyft, Cisco, Google, Facebook—are aiming to build what they call the “smart city.” Promoted as a way to improve efficiency in urban services, these plans will also provide more opportunity for oligarchs to monitor our lives, as well as sell more advertising. The “smart city” would replace organic urban growth with a regime running on algorithms designed to rationalize our activities and control our way of life.2 This urban vision appeals to tech oligarchs’ belief that their mission is to “change the world,” not simply make money by meeting customers’ needs and desires.

Silicon Valley first grew out of the suburbs, but many tech leaders now believe that “urbanization is a moral imperative,” writes Greg Ferenstein.6 If startups in suburban garages represented the individualism of cranky inventors and entrepreneurs, the future Silicon Valley will feature densely packed apartment complexes for workers who will become ever more corporate and controlled.7 The focus on apartment living for employees makes some sense for tech companies—like Facebook, Lyft, Salesforce, Square, Twitter, Yelp, and Google—that rely on a youthful, childless workforce.8 This kind of urban experience does not spur individuals toward independent adulthood and family formation, but recreates “life as close to the college experience as possible,” as Ferenstein notes, or a kind of prolonged adolescence.9 With traditional family-friendly housing near their workplaces out of reach for all but the wealthiest people, most tech employees will live in something like dormitories, perhaps well into their thirties.


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

She generated enough cash flow from those bedrooms that she was able to buy another home, move out, and then rent out the whole house. She now earns between $1,000 and $1,800 a month from her Airbnb property. Uber/Lyft You can earn money on your schedule. You give rides when you want and earn as much as you want, with the potential to make great money. Thirty hours of driving per week can generate up to $1,000 on average. You get paid weekly and your fares are automatically deposited. Additionally, this is a unique way to monetize your car, especially if you have a car loan. You could buy a new car and pay it off as an Uber or Lyft driver. In late 2016, I was visiting London to deliver a keynote address. I had an Uber driver pick me up, and we struck up a conversation. He was a refugee from Afghanistan. He was generating $6,000 U.S. per month as an Uber driver.

He pays for all registration, insurance, maintenance, and fuel costs. The drivers simply spend their time and drive, and generate about $4,000 per month net after their rental fee. For these drivers, $7,000 can support their families for an entire year back in Afghanistan. Akram’s plan is to upgrade his fleet to fifty cars. There are thirty other refugees on the waiting list to take up his offer. And even if you don’t want to drive for Uber or Lyft, you can still make money with them. There are plenty of people who have a driver’s license but don’t own a car. If you have an under-utilized car that’s just sitting in your garage and depreciating in value, you can rent it out to ridesharing drivers. You can now list your car on HyreCar.com. An average car owner has the potential to generate up to $12,000 per year, providing a good source of passive income.

Keohohou, Nicki Kets de Vries, Manfred keystone habits Kiyosaki, Robert Komisar, Randy Kroc, Ray L labor markets, technology’s transformation of Lavie, Peretz Lemony Snicket Lending Club leverage, and Cash Flow Insurance and content and creating greater returns and credit scores and current assets and entrepreneurship and real estate investments liabilities, and insurance vs. debt liberated entrepreneurs life boards, creating life insurance, combining with long-term care insurance as protective expense whole life insurance lifestyle, and cash flow cutting expenses of and freedom and Growth investment strategies and loan debt Linchpin (Godin) LinkedIn liquidity, and Cash Flow Insurance of checking and savings accounts and economic cycles and failure of conventional investments of Growth investments and real estate investments and reducing debt and tax lien certificates Litecoin “Live Like You Were Dying” (song) Living Wealthy Accounts LLCs loads, on mutual funds loans, and Cash Flow Index and credit scores and economic cycles for real estate investments restructuring from retirement plans against whole life insurance policies See also debt location, and real estate investments and storage unit construction Loehr, Jim long-term care insurance Loopnet Lyft, as entrepreneurial opportunity Lynch, Peter M Mackay, Harvey “mailbox money” myth maintenance, and storage units Mandela, Nelson Marcus Aurelius market conditions, and business startup investments and real estate investments market cycles See also economic cycles market demand, and entrepreneurial opportunities Mastermind Principle materialism, and the American dream and simplicity Maxwell, John McCain, John McCoy, Dan meals, as tax deduction meaning, and generosity medical insurance, as protective expense Melish, Stephanie mental capital mental energy mentors, and building your inner circle microcredit Mill, John Stuart mindfulness mindset, of abundance changing components of a strong and control and debt and hiring employees and limitations and Living Wealthy Accounts and quitting your job and real estate investments and resourcefulness strengthening mineral rights mobile apps, as entrepreneurial opportunity Moffat, Kyle Momentum investments, and active vs. passive income streams business startups cryptocurrencies description of gold and silver speculation and Growth investment strategies investing in people and Passive Income Ratio private equity investments purchasing distressed businesses understanding financial reports Monero monetary policies, and economic cycles moneylenders money managers fees money mastery Moody, D.


pages: 371 words: 108,317

The Inevitable: Understanding the 12 Technological Forces That Will Shape Our Future by Kevin Kelly

A Declaration of the Independence of Cyberspace, AI winter, Airbnb, Albert Einstein, Amazon Web Services, augmented reality, bank run, barriers to entry, Baxter: Rethink Robotics, bitcoin, blockchain, book scanning, Brewster Kahle, Burning Man, cloud computing, commoditize, computer age, connected car, crowdsourcing, dark matter, dematerialisation, Downton Abbey, Edward Snowden, Elon Musk, Filter Bubble, Freestyle chess, game design, Google Glasses, hive mind, Howard Rheingold, index card, indoor plumbing, industrial robot, Internet Archive, Internet of things, invention of movable type, invisible hand, Jaron Lanier, Jeff Bezos, job automation, John Markoff, Kevin Kelly, Kickstarter, lifelogging, linked data, Lyft, M-Pesa, Marc Andreessen, Marshall McLuhan, means of production, megacity, Minecraft, Mitch Kapor, multi-sided market, natural language processing, Netflix Prize, Network effects, new economy, Nicholas Carr, old-boy network, peer-to-peer, peer-to-peer lending, personalized medicine, placebo effect, planetary scale, postindustrial economy, recommendation engine, RFID, ride hailing / ride sharing, Rodney Brooks, self-driving car, sharing economy, Silicon Valley, slashdot, Snapchat, social graph, social web, software is eating the world, speech recognition, Stephen Hawking, Steven Levy, Ted Nelson, the scientific method, transport as a service, two-sided market, Uber for X, uber lyft, Watson beat the top human players on Jeopardy!, Whole Earth Review, zero-sum game

Our attention has moved away from stocks of solid goods to flows of intangibles, like copies. We value not only the atoms in a thing, but their immaterial arrangement and design and, even more, their ability to adapt and flow in response to our needs. Formerly solid products made of steel and leather are now sold as fluid services that keep updating. Your solid car parked in a driveway has been transformed into a personal on-demand transportation service supplied by Uber, Lyft, Zip, and Sidecar—which are improving faster than automobiles are. Grocery shopping is no longer a hit-or-miss affair; now a steady flow of household replenishables streams into our homes uninterrupted. You get a better telephone every few months because a flow of new operating systems install themselves on your smartphone, adding new features and new benefits that in the past would have required new hardware.

Anyone who wants to earn some money can drive, so there are often more Uber drivers than taxis, especially during peak demand times. And to make it vastly cheaper (in normal use), if you are willing to share a ride, Uber will match two or three riders going to approximately the same place at the same time to split the fare. These UberPool shared-ride fares might be one quarter the cost of a taxi. Relying on Uber (or its competitors, like Lyft) is a no-brainer. While Uber is well known, the same on-demand “access” model is disrupting dozens of other industries, one after another. In the past few years thousands of entrepreneurs seeking funding have pitched venture capitalists for an “Uber for X,” where X is any business where customers still have to wait. Examples of X include: three different Uber for flowers (Florist Now, ProFlowers, BloomThat), three Uber for laundry, two Uber for lawn mowing (Mowdo, Lawnly), an Uber for tech support (Geekatoo), an Uber for doctor house calls, and three Uber for legal marijuana delivery (Eaze, Canary, Meadow), plus a hundred more.

Hire a company to drive you to your destination (taxi). 3. Rent a company-owned car, drive yourself (Hertz rental). 4. Hire a peer to drive you to your destination (Uber). 5. Rent a car from a peer, drive yourself (RelayRides). 6. Hire a company to drive you with shared passengers along a fixed route (bus). 7. Hire a peer to drive you with shared passengers to your destination (Lyft Line). 8. Hire a peer to drive you with shared passengers going to a fixed destination (BlaBlaCar). There are variations upon the variations. Hire the service Shuddle to pick up someone else, like a child at school; some call it an Uber for kids. Sidecar is like Uber, except it runs a reverse auction. You set the price you are willing to pay and let drivers bid to pick you up. There are dozens of emerging companies (like SherpaShare) aimed at serving the drivers instead of riders, helping them manage more than one system and optimizing their routes.


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

Uber’s ability to raise billions of dollars has allowed it to subsidize its service to attract more drivers and passengers, reinforcing the network effects of its two-sided marketplace. Plentiful capital has also allowed it to expand aggressively into other markets in an attempt to beat its competition to critical scale. Even after a scandal-plagued 2017, Uber still dwarfs its US archrival Lyft. In July 2017, Lyft announced that it had reached one million rides per day, a milestone that Uber achieved at the end of 2014. During the dismal days of the dot-com bust, Google followed the blitzscaling playbook by using a distribution deal with AOL to dramatically expand its AdWords business. The deal, first announced in May 2002, gave AOL an 85 percent share of the revenue generated by AOL searches powered by Google, with a guaranteed minimum of $150 million per year.

From Captain to Admiral At the time of the writing of this book, the ridesharing company Uber was Silicon Valley’s most valuable start-up (and second globally to its frenemy, China’s Didi Chuxing), despite having spent most of 2017 in the news for a number of serious problems and scandals. Some of these issues were due to clearly unethical behavior, including internal problems, such as the sexual harassment reported by the former Uber engineer Susan Fowler, and various external attempts to subvert free competition, regulation, and the press, such as creating fake accounts to poach drivers from its rival Lyft (as reported by The Verge), developing software (Greyball) to prevent law enforcement and regulators from accessing the service, and then-COO Emil Michael suggesting that the company spend money to hire opposition researchers to intimidate journalists. This kind of behavior is unacceptable, regardless of the size or stage of the company undertaking it, and has rightfully been widely condemned.

With these advantages and disadvantages in mind, here are a few specific management techniques or “hacks” that large companies can use when they set out to blitzscale. BLITZSCALING HACKS One productive hack to help your existing company blitzscale is to find ways to leverage people and businesses with prior blitzscaling experience. One obvious play is to partner with a blitzscaling start-up. For example, GM responded to the rise of Uber and the corresponding threat it represents to the market for cars for human drivers by investing $500 million in Lyft, Uber’s blitzscaling rival. GM also hedged its bets by acquiring Cruise for its self-driving car technology. A less obvious technique is to leverage the knowledge of venture capitalists. Venture capitalists are keen fans of blitzscaling and the returns it brings, even if they didn’t know the specific term before the book came out. If you ask them to become minority investors in your project, they will provide a realistic assessment of your situation.


pages: 383 words: 81,118

Matchmakers: The New Economics of Multisided Platforms by David S. Evans, Richard Schmalensee

Airbnb, Alvin Roth, big-box store, business process, cashless society, Chuck Templeton: OpenTable:, creative destruction, Deng Xiaoping, disruptive innovation, if you build it, they will come, information asymmetry, Internet Archive, invention of movable type, invention of the printing press, invention of the telegraph, invention of the telephone, Jean Tirole, John Markoff, Lyft, M-Pesa, market friction, market microstructure, mobile money, multi-sided market, Network effects, Productivity paradox, profit maximization, purchasing power parity, QR code, ride hailing / ride sharing, sharing economy, Silicon Valley, Snapchat, Steve Jobs, Tim Cook: Apple, transaction costs, two-sided market, Uber for X, uber lyft, ubercab, Victor Gruen, winner-take-all economy

It can’t make up for this deficit by having many restaurants that aren’t relevant to the people making the reservations. OpenTable’s “go narrow/go deep” strategy worked because it ultimately secured critical mass in cities where it had signed up enough popular restaurants and engaged enough diners that the positive indirect network effects between these two kinds of customers ignited further growth on both sides. Lyft, Yelp, Instacart, and other businesses that provide local services have followed similar strategies. But the point also applies to multisided platforms that are trying to differentiate their offerings. If a mall developer decides to create a high-end shopping mall, it must get high-end stores to lease space at the mall, and it must persuade well-off shoppers to go to the mall. Packing the mall with people who aren’t able to shop at expensive stores won’t help it persuade high-end stores to lease space, and renting space to downscale stores won’t attract high-end shoppers.

They used to act as intermediaries between people looking to travel and travel-related businesses such as airlines and hotels. Two-sided matchmakers operating from the Cloud, such as Expedia, offer more efficient and cheaper alternatives. According to the US Bureau of Labor Statistics, there were forty-four travel agents for every hundred thousand people in the United States in 2000. That had declined by 55 percent, to only twenty per hundred thousand people in 2014.33 Uber, along with similar companies such as Lyft and Didi Kuaidi, has created a great deal of value for consumers and drivers. But the traditional taxicab business is threatened as a result. Taxi drivers worldwide are protesting and trying to stop these new matchmakers. If they don’t, the traditional taxi business will likely go into terminal decline. This may already have begun. The prices of taxi medallions—which provide a permanent right to drive a taxicab in some cities—are falling.34 Medallion prices declined 23 percent in New York City between 2013 and 2015.35 In part III of this book, we present case studies of two major examples of creative destruction.

BlaBlaCar, “Terms and Conditions,” https://www.blablacar.co.uk/blog/terms-and-conditions. 22. eBay, “Rules & Policy,” http://pages.ebay.com/help/policies/overview.html. 23. Apple Developer, “App Store Review Guidelines,” https://developer.apple.com/app-store/review/guidelines/. 24. Tomer Sarid, “7 Reasons Your App Could Get Rejected by Apple (And How to Avoid It),” como blog, April 29, 2015, http://blog.como.com/2015/04/7-reasons-app-rejected-by-apple/. 25. For general discussions, see Jason Tanz, “How Airbnb and Lyft Finally Got Americans to Trust Each Other,” Wired, April 23, 2014, http://www.wired.com/2014/04/trust-in-the-share-economy/; Liran Einav, Chiara Farronato, and Jonathan Levin, “Peer-to-Peer Markets,” NBER working paper 21496, 2015, section 2.3, http://www.nber.org/papers/w21496. 26. OpenTable, “OpenTable Terms of Use,” http://www.opentable.com/info/agreement.aspx. 27. Matt Rosoff, “Google Has Stopped Punishing JC Penney,” Business Insider, May 25, 2011, http://www.businessinsider.com/google-has-stopped-punishing-jc-penney-2011-5. 28.


pages: 425 words: 112,220

The Messy Middle: Finding Your Way Through the Hardest and Most Crucial Part of Any Bold Venture by Scott Belsky

23andMe, 3D printing, Airbnb, Albert Einstein, Anne Wojcicki, augmented reality, autonomous vehicles, Ben Horowitz, bitcoin, blockchain, Chuck Templeton: OpenTable:, commoditize, correlation does not imply causation, cryptocurrency, delayed gratification, DevOps, Donald Trump, Elon Musk, endowment effect, hiring and firing, Inbox Zero, iterative process, Jeff Bezos, knowledge worker, Lean Startup, Lyft, Mark Zuckerberg, Marshall McLuhan, minimum viable product, move fast and break things, move fast and break things, NetJets, Network effects, new economy, old-boy network, pattern recognition, Paul Graham, ride hailing / ride sharing, Silicon Valley, slashdot, Snapchat, Steve Jobs, subscription business, TaskRabbit, the medium is the message, Travis Kalanick, Uber for X, uber lyft, Y Combinator, young professional

KEEP YOUR OPPONENTS IN THE GAME Aside from being a source of energy for your own productivity, your competitors play a critical role in the health of your industry. Over time, every company in a field builds on one another and helps expand the potential size of the market. For example, in the ride-sharing space, Uber launched on-demand cars before Lyft, Lyft launched a carpooling option before Uber, then Uber launched a tool for drivers to pick up fares at the end of their shift on their way home before Lyft, then Lyft provided “prescheduled rides” before Uber, and the list goes on. Of course, the real winner here is the consumer, who gets a more evolved product offering from the endless competition between two companies. Be grateful to your competitors for never letting your product—and process—become too comfortable. Isolation and the lack of any credible threat leads to complacency.

., 199–202 founder-product fit, 256 Founders, 126 Four Hour Body, The (Ferriss), 283 free radicals, 137–39 French Revolution, 200, 201 friction, 37–39, 210, 371, 372 Fried, Jason, 90 fringe, 58 frugality, 140–42 Game of Thrones, 270 Gates, Bill, 295 Gebbia, Joe, 88–89, 311 General Electric (GE), 125, 130, 143, 327 Getable, 356–57 Gibson, William, 257 Giffon, Jeremy, 294 Gigerenzer, Gerd, 285 Gilbert, Dan, 196–97 Glei, Jocelyn, 181 goals, long-term, 26–27, 66, 299, 304, 350 Godin, Seth, 297, 298, 337–38 Goldberg, Dave, 39 Goldman Sachs, 125, 143, 240–41, 341 Google, 24, 25, 60, 67, 83, 93, 101, 139, 189, 239, 366–67 Maps, 210 Project Aristotle, 122 Trends, 301–2 government and politics, corporate, 46–48 grafting talent, 119–25 Graham, Paul, 193 Grant, Adam, 39 Grant, Angela, 108 grit, 62–63 Grit: The Power of Passion and Perseverance (Duckworth), 62 groups, 38–39, 107, 203–4 Gunatillake, Rohan, 360 Gurley, Bill, 79, 311 Gut Feelings (Gigerenzer), 285 hardship, 38, 39 Harvard Business Review, 39, 250 Harvard Business School, 117, 122, 160, 214, 262 Hashemi, Sam, 164–65 Hastings, Reed, 83–84, 126 HBO, 270 Heiferman, Scott, 168, 243–44 Higa, James, 141 Hindu theology, 374 hiring: adversity and, 110–11 discussions and, 112–13 diversity and, 106–9, 110 and initiative vs. experience, 103–5 of polarizing people, 114–15 and resourcefulness vs. resources, 100–102 talent and, 119–25 Hogan-Brun, Gabrielle, 107–8 Homebrew, 294, 359 honeymoon phase, 209 Hope, Bradley, 306, 307 Horowitz, Ben, 29–30 House Party, 265 humility, 56, 193, 331, 350 passion and, 248–50 Huxley, Aldous, 204 Hyer, Tim, 356–57 identity, 358–60, 362–63 if-onlys, 74 ignorance, 308–9 Illustrator, 10, 144, 162, 270 imagination, 326–28, 336 immune system: of society, 35, 36, 60 of team, 116–18, 119, 127 impact, 31 Improv Everywhere, 113 incrementalism, 207, 242–44, 289 influence, and credit, 330–32 information-gap theory, 272 initiative vs. experience, in hiring, 103–5 innovation, 57, 60, 102, 106–7, 118, 143, 183, 204, 250 inbred, 245–46 mistakes and unexpected in, 324–25 insecurity work, 66–67, 68 Instagram, 36, 44, 174, 189, 227, 235–36, 335, 349 institutions, 354 intention, 175 internet, 258 intuition, 294–96, 300–304, 321 inverted-U behavior, 272–73 investment, 78, 290 iPad, 48, 250, 306 iPhone, 63, 250, 273, 374 iPod, 63, 295, 374 Jaffe, Eric, 272 Jenks, Patty, 84 Jobs, Steve, 40–41, 63, 64, 141, 295 Johnstone, Ollie, 222 Jones, Malcolm, 104 Journal of Experimental Psychology, 228 Joymode, 295 June, 226–27 Jung, Carl, 56, 115 Kalina, Noah, 190 Kalmikoff, Jeffrey, 267–68 Kane, Becky, 229 Kaplan, Stanley, 358–59 Kay, Alan, 308 Kerr, Steve, 125 King, Stephen, 220 Klout, 295 Krop, 187 Laja, Peep, 162 language, multilingualism and, 107–9 laziness, vanity, and selfishness, 235–37 LCD Soundsystem, 92 leaders, leadership, 127, 147, 205, 277, 331 delegation and, 166–69 internal marketing and, 158–60 70/20/10 model for development of, 125 as stewards vs. owners, 258–61 timing and, 288–89 “lean start-up” methodology, 194 learning, 63–64, 366–67 LearnVest, 65–66 Lehrer, Jonah, 272 Levie, Aaron, 83, 224 Levo League, 73 LeWitt, Sol, 58 life expectancy, 26 Lightroom, 270 Linguanomics: What Is the Market Potential of Multilingualism? (Hogan-Brun), 107 LinkedIn, 181, 258 listening, 321 lists, 374 living and dying, 26, 368–69, 373–75 Livingston, Jessica, 101–2 local maxima, 242, 243–44, 289 Loewenstein, George, 272 long-term goals, 26–27, 66, 299, 304, 350 Loup Ventures, 35 Louvre Pyramid, 200–202 Lyft, 191 Macdonald, Hugo, 37–38 Macworld, 295 Maeda, John, 107, 186, 308, 354 magic of engagement, 273 Making Ideas Happen (Belsky), 159, 190, 222 Managed by Q, 221 Marcus Aurelius, 39 market-product fit, 256 Marquet, David, 167 Mastercard, 275, 303–4 Match.com, 259 Maupassant, Guy de, 201 maximizers, 229, 284–85 McKenna, Luke, 217 McKinsey & Company, 72 Meerkat, 265 meetings, 44, 78, 176 Meetup, 168, 243–44 Mehta, Monica, 26 merchandising, internal, 158–60 metrics and measures, 28, 29, 297–99 microwave ovens, 325 middle, 1, 3–4, 7–8, 14–15, 20, 40, 209, 211, 375 volatility of, 1, 4, 6, 8, 12, 14–16, 21, 209 milestones, 25, 27, 31, 40 minimum viable product (MVP), 86, 186, 195, 252 Minshew, Kathryn, 72–73 misalignment, 153–55 mistakes, 324–25, 336 Mitterand, François, 201 Mix, 256 Mizrahi, Isaac, 324 mock-ups, 161–63 momentum, 29 money, raising, 30–31, 102 Monocle, 37 Morin, Dave, 273 motivation, 24 multilingualism, 107–9 Murphy, James, 92 Muse, The, 72, 73 Musk, Elon, 168, 273 Muslims, 302–3 Myspace, 89, 187–88, 349 mystery, 271–73 naivety, 308–9 Narayan, Shantanu, 289 narrative and storytelling, 40–42, 75, 87, 271 building, before product, 255–57 culture and, 134–36 National Day of Unplugging, 328 naysayers, 295 negotiation, 286–87 Negroponte, Nicholas, 107 Nest, 63 Netflix, 83–84, 126 networking, 138–39 networks, 258–61, 283, 284, 320–21 Newsweek, 38 New York Times, 63, 122, 275 Next, 141 99U Conference, 9–10, 26, 138, 167, 181, 197, 220, 221, 360 no, saying, 282–84, 285, 319, 371, 372 Noguchi, Isamu, 141 noise and signal, 320–21 Northwestern Mutual, 66 novelty, and utility, 240–41 NPR, 196 “NYC Deli Problem,” 174 Oates, Joyce Carol, 192 OBECALP, 59–61 obsession, 104–5, 229, 313, 326 Oculus, 350 Odeo, 36 office space, 140–41 openness, 308–9, 350 OpenTable, 79 opinions, 64, 305–7, 317 opportunities, 282–85, 319, 324, 325, 371 optimization, 8, 14–15, 16, 93–338 see also product, optimizing; self, optimizing; team, optimizing Option B: Facing Adversity, Building Resilience, and Finding Joy (Sandberg and Grant), 39 options, managing, 284–85 organizational debt, 178–79 outlasting, 90 outsiders, 88, 105 Page, Larry, 60 Pain, 59 Paperless Post, 239 Paradox of Choice, The: Why More Is Less (Schwartz), 284 parallel processing, 33 parenting, 371, 372 Partpic, 120 passion, empathy and humility before, 248–50 path of least resistance, 85 patience, 78, 80–85, 196 cultural systems for, 81–82, 85 personal pursuit of, 84–85 structural systems for, 83–84, 85 “pebbles” and “boulders,” 182, 268 Pei, I.


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

In a ridesharer’s marketplace, the companies that collect the most data and assemble the biggest fleets are the ones that will offer the lowest wait times and cheapest rides. Cheap and quick are the two biggest factors impacting consumer choice in this kind of market. What brand of car ridersharers are sharing matters a lot less. Most of the time, if the vehicle is clean and neat, consumers won’t even notice what brand the car is—similar to how most of us feel about Uber or Lyft today. So, if a half-a-dozen different vehicles are all it takes to please the customer, then a wave of car company extinction is going to follow our wave of car company consolidation. Big auto won’t be the only industry impacted. America has almost half-a-million parking spaces. In a recent survey, MIT professor of urban planning Eran Ben-Joseph reported that, in many major US cities, “parking lots cover more than a third of the land area,” while the nation as a whole has set aside an area larger than Delaware and Rhode Island combined for our vehicles.

Blockchain solves this problem as well, providing people with a digital ID that will follow them around the internet. What can we do with this identity? Own our own data, for one. Blockchain IDs could also facilitate fair and accurate voting. Lastly, if your identity can be established, then a reputation score can easily be attached. This score allows for things like peer-to-peer ridesharing, which today require trusted third parties named “Uber” and “Lyft.” In the same way that blockchain can validate identity, it can also validate any asset—for example, ensuring that your engagement ring isn’t a blood diamond. Land titles are another opportunity, especially since a considerable portion of the planet lives on land they don’t own, or not officially. Consider Haiti. The combination of earthquakes, dictatorships, and forced evacuations makes determining who actually owns which bits of property a giant quagmire.

As of January 2019, Wealthfront had $11 billion under management, while Betterment was at $14 billion. While robo-advisors still account for only roughly 1 percent of total U.S. investment, Business Insider Intelligence estimates that number will climb to $4.6 trillion by 2022. Finally we come to our last category, using money to pay for things. But we already know this story. When was the last time you dropped coins into a toll booth? Or paid cash for a cab ride? In fact, Uber and Lyft allow us to get around a city without a wallet. Couple cashier-less stores like Amazon Go with services like Uber Eats and these wallet-less ways are about to become the new normal. Denmark stopped printing money in 2017. The year prior, in an attempt to expand mobile banking and demonetize the country’s gray-market economy, India recalled 86 percent of its cash. Vietnam wants retail to be 90 percent cashless by 2020.


pages: 207 words: 59,298

The Gig Economy: A Critical Introduction by Jamie Woodcock, Mark Graham

Airbnb, Amazon Mechanical Turk, autonomous vehicles, barriers to entry, British Empire, business process, business process outsourcing, call centre, collective bargaining, commoditize, corporate social responsibility, crowdsourcing, David Graeber, deindustrialization, disintermediation, en.wikipedia.org, full employment, future of work, gender pay gap, gig economy, global value chain, informal economy, information asymmetry, inventory management, Jaron Lanier, Jeff Bezos, job automation, knowledge economy, Lyft, mass immigration, means of production, Network effects, new economy, Panopticon Jeremy Bentham, planetary scale, precariat, rent-seeking, RFID, ride hailing / ride sharing, Ronald Reagan, self-driving car, sentiment analysis, sharing economy, Silicon Valley, Silicon Valley ideology, TaskRabbit, The Future of Employment, transaction costs, Travis Kalanick, two-sided market, Uber and Lyft, Uber for X, uber lyft, union organizing, women in the workforce, working poor, young professional

Designed by the English philosopher and social theorist, Jeremy Bentham, the panopticon is an architectural design for a prison in which a single prison guard can watch all the inmates simultaneously without them knowing whether they are being watched, thus inducing self-regulating behaviour. 10. See Wiessner, D. (2018) US court revives challenge to Seattle’s Uber, Lyft union law. Reuters, 11 May. Available at: https://www.reuters.com/article/us-uber-seattle-unions/u-s-court-revives-challenge-to-seattles-uber-lyft-union-law-idUSKBN1IC27C Conclusion: What next for the gig economy? The gig economy is not just a synonym for algorithmic wizardry, large datasets and cutting-edge technologies. Whenever we think (or indeed research or write) about work, it is important to remember that work necessarily involves workers. This means actual people with complex lives, working in relationships with each other.

This resistance is happening within structurally difficult conditions, often in grey areas of legality, or even taking place illegally. This is because, in many locales, the self-employed are not allowed to form trade unions like workers or employees are. In those places, doing so is seen as operating like a price-setting cartel rather than simply providing a means for workers to bargain over their pay. In fact, the US Chamber of Commerce, of which Uber and Lyft are members, has argued in a Seattle court that ‘by allowing drivers to bargain over their pay, which is based on fares received from passengers, the city would permit them to essentially fix prices in violation of federal antitrust law.’10 This measure has been seen as an attempt to prevent the Teamsters from organizing Uber drivers in Seattle. The threats of legal injunctions mean that workers are not only having an effect on the gig economy, but are redefining what organizing and trade unionism mean today.


pages: 339 words: 88,732

The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies by Erik Brynjolfsson, Andrew McAfee

"Robert Solow", 2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 3D printing, access to a mobile phone, additive manufacturing, Airbnb, Albert Einstein, Amazon Mechanical Turk, Amazon Web Services, American Society of Civil Engineers: Report Card, Any sufficiently advanced technology is indistinguishable from magic, autonomous vehicles, barriers to entry, basic income, Baxter: Rethink Robotics, British Empire, business cycle, business intelligence, business process, call centre, Charles Lindbergh, Chuck Templeton: OpenTable:, clean water, combinatorial explosion, computer age, computer vision, congestion charging, corporate governance, creative destruction, crowdsourcing, David Ricardo: comparative advantage, digital map, employer provided health coverage, en.wikipedia.org, Erik Brynjolfsson, factory automation, falling living standards, Filter Bubble, first square of the chessboard / second half of the chessboard, Frank Levy and Richard Murnane: The New Division of Labor, Freestyle chess, full employment, G4S, game design, global village, happiness index / gross national happiness, illegal immigration, immigration reform, income inequality, income per capita, indoor plumbing, industrial robot, informal economy, intangible asset, inventory management, James Watt: steam engine, Jeff Bezos, jimmy wales, job automation, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joseph Schumpeter, Kevin Kelly, Khan Academy, knowledge worker, Kodak vs Instagram, law of one price, low skilled workers, Lyft, Mahatma Gandhi, manufacturing employment, Marc Andreessen, Mark Zuckerberg, Mars Rover, mass immigration, means of production, Narrative Science, Nate Silver, natural language processing, Network effects, new economy, New Urbanism, Nicholas Carr, Occupy movement, oil shale / tar sands, oil shock, pattern recognition, Paul Samuelson, payday loans, post-work, price stability, Productivity paradox, profit maximization, Ralph Nader, Ray Kurzweil, recommendation engine, Report Card for America’s Infrastructure, Robert Gordon, Rodney Brooks, Ronald Reagan, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Simon Kuznets, six sigma, Skype, software patent, sovereign wealth fund, speech recognition, statistical model, Steve Jobs, Steven Pinker, Stuxnet, supply-chain management, TaskRabbit, technological singularity, telepresence, The Bell Curve by Richard Herrnstein and Charles Murray, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, total factor productivity, transaction costs, Tyler Cowen: Great Stagnation, Vernor Vinge, Watson beat the top human players on Jeopardy!, winner-take-all economy, Y2K

Some services bring these two models together and let people offer a combination of labor and assets over the Internet. When Andy needed to have his motorcycle towed to another state in 2010, he found the right person for the job—someone with both time and a trailer on their hands—on uShip. Lyft, founded in 2011, allows people to effectively turn their cars into taxis whenever they want, giving crosstown rides to others. In an effort to avoid opposition from taxi regulators and other authorities, Lyft does not set fees or rates. It instead suggests to customers a ‘donation’ that they should offer to the person who just gave them a lift. As the story of Lyft highlights, there are many legal and regulatory issues that will need to be resolved as the peer economy grows. While we certainly acknowledge the need to ensure public safety, we hope that regulation in this new area will not be stifling and that the peer economy will continue to grow.

Kintinuous Kiva Klapper, Leora Kline, Patrick Knack Kochan, Tom Kopecky, Karen Kremer, Michael Krieger, Mike Krueger, Alan Krugman, Paul Kurzweil, Ray Kuznets, Simon labor: capital replacement of churn in crowdsourcing of demand elasticity and digital partnerships with digitization and; see also “winner-take-all” markets incentives for input limits on non-digitized recessions and skill matrix for see also employment; productivity; wages labor, skilled: benefits of technology for contribution of immigration to creation of labor, unskilled: declining wages of technology’s replacement of Laeven, Luc Lakhani, Karim land taxes Leiserson, William Leonard, John Leontief, Wassily Levine, Uri Levy, Frank Lickel, Charles LIDAR Liebling, A. J. Lindbergh, Charles LinkedIn Lionbridge living standards, calculation of Lohr, Steve London, congestion charging in Longitude Prize Loria, Roberto Luca, Michael Ludd, Ned Luddite Fallacy Lusardi, Annamaria Lyft machine-to-machine (M2M) communication Macintosh Madigan, Kathleen Mandel, Michael Mankiw, Greg manufacturing: automation in importance of infrastructure to inelastic demand in organizational coinventions in U.S. employment in wages in maps, digital Marberry, Mike Marbles, Jenna Mariel boatlift Marshall, Alfred Marx, Karl massive online open courses (MOOCs) McAfee, Andrew McCarthy, John McDevitt, Ryan McFadden, Daniel McKinsey Mechanical Turk medicine: AI use in automation in diagnostic Memorial Sloan-Kettering Cancer Center “meta-ideas,” Michel, Jean-Baptiste Microsoft Milgrom, Paul military, U.S., robot use by Minsky, Marvin MIT, Computer Science and Artificial Intelligence Lab at Mitchell, Tom Mitra, Sugata MITx Monster.com Montessori, Maria Monthly Labor Review Moore, Gordon Moore’s Law in business in computing persistence of spread of Moravec, Hans Moravec’s paradox Morris, Ian mortgages Mullis, Kary multidimensional poverty index Munster, Gene Murnane, Richard Murray, Charles music, digitization of Nader, Ralph Narrative Science NASA National Academy of Sciences National Association of Realtors National Bureau of Economic Research National Review Nature of Technology, The (Arthur) Neiman, Brent New Digital Age, The (Schmidt and Cohen) New Division of Labor, The (Levy and Murnane) Newell, Al new growth theory New York Times Next Convergence, The (Spence) Nike Nixon, Richard Nordhaus, William numbers: development of large Occupy movement oDesk Oh, Joo Hee Olshansky, S.


pages: 320 words: 90,526

Squeezed: Why Our Families Can't Afford America by Alissa Quart

Affordable Care Act / Obamacare, Airbnb, Automated Insights, autonomous vehicles, barriers to entry, basic income, Bernie Sanders, business intelligence, Donald Trump, Downton Abbey, East Village, Elon Musk, full employment, future of work, gig economy, glass ceiling, haute couture, income inequality, Jaron Lanier, job automation, late capitalism, Lyft, minimum wage unemployment, moral panic, new economy, nuclear winter, obamacare, Ponzi scheme, post-work, precariat, price mechanism, rent control, ride hailing / ride sharing, school choice, sharing economy, Silicon Valley, Skype, Snapchat, surplus humans, TaskRabbit, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, union organizing, universal basic income, upwardly mobile, wages for housework, women in the workforce, working poor

(“Life would be so much easier if we had personal assistants for our children,” exclaims the website for one such company, Kid Care Concierge, of Bridgewater, New Jersey. Kid Care Concierge, a “personalized and exclusive concierge service firm, establish[es] a harmonious work-life balance for busy families.”) For the more affluent, there’s now even an on-demand ride-and-care service for children in Southern California and the Bay Area called Zūm; an expensive car service like Lyft, Zūm ferries children ages five to eighteen to and from school or to team practices and music lessons, with child care provided before or after the rides for an additional fee. But such services are not affordable for late-night store and chain-restaurant workers. Indeed, as Rachel Cusk writes in her memoir of how the wealthy deploy day care: “The deep-pile nanny, the nanny who exists to cushion the impact of parenthood, was, I discovered, the preserve of the wealthy.

Yet, stripped of its “generous” veneer, Uber’s teacher-driver campaigns are also sharing in a more twisted Silicon Valley fantasy: low taxes, good schools, and teachers who drive you home after your expense-account meal with a venture capitalist! These conglomerates are gargantuan outfits that offer short-term, cheap services delivered by “independent” contractors. They have become hugely successful by trading labor across platforms over which workers have little to no say. There was also a gendered element of this dark Silicon Valley fantasia. Of the dozen Uber and Lyft driver-teachers I spoke to in 2016, most were also parents, and almost all were men. (Of course, this is often true of the workers employed by these services.) It made me wonder whether men were sometimes more willing to literally drive the extra mile to retain their class status. After all, these men were also affected by the American societal amnesia about the cost of raising a family. Both parents routinely now work more time or additional jobs or stranger hours, or all of the above.

(Ironies compound: as the writer Douglas Rushkoff has noted, today’s drivers are themselves now part of the research and development for what will most likely be the driverless future, building up a company with their labor in preparation for a time when the company will do away with them.) “Our demand is to freeze all the subsidies for the research on autonomous vehicles until there is a plan for workers who are going to lose their jobs,” Lerner said. As part of this effort, NYCC regularly puts together conference calls between dozens of taxi, Uber, and Lyft drivers. They discuss how they’ve all gotten massive loans to buy cars for Uber and how they are still going to be paying off these loans when the robots come for their jobs—the robot vehicles Uber has promised within the decade. The robot-fearing Middle Precariat also includes parts of the legal profession: robots are threatening higher-end jobs, including those usually carried out by humans handling information.


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

Perhaps even a world where we own our data and can protect our privacy and personal security. An open world where everyone can contribute to our technology infrastructure, rather than a world of walled gardens where big companies offer proprietary apps. A world where billions of excluded people can now participate in the global economy and share in its largesse. Here’s a preview. Creating a True Peer-to-Peer Sharing Economy Pundits often refer to Airbnb, Uber, Lyft, TaskRabbit, and others as platforms for the “sharing economy.” It’s a nice notion—that peers create and share in value. But these businesses have little to do with sharing. In fact, they are successful precisely because they do not share—they aggregate. It is an aggregating economy. Uber is a $65 billion corporation that aggregates driving services. Airbnb, the $25 billion Silicon Valley darling, aggregates vacant rooms.

They aggregate the willingness of suppliers to sell their excess capacity (cars, equipment, vacant rooms, handyman skills) through a centralized platform and then resell them, all while collecting valuable data for further commercial exploitation. Companies like Uber have cracked the code for large-scale service aggregation and distribution. Airbnb competes with hotels on travel accommodations; Lyft and Uber challenge taxi and limousine companies; Zipcar, before it was purchased by Avis, challenged traditional car rental companies with its hip convenience and convenient hourly rentals. Many of these companies have globalized the merchandising of traditional local, small-scale services—like bed-and-breakfasts, taxis, and handypersons. They use digital technologies to tap into so-called underutilized, time-based resources like real estate (apartment bedrooms), vehicles (between-call taxis), and people (retirees and capable people who can’t get full-time jobs).

For Benkler, “Blockchain enables people to translate their willingness to work together into a set of reliable accounting—of rights, assets, deeds, contributions, uses—that displaces some of what a company like Uber does. So that if drivers want to set up their own Uber and replace Uber with a pure cooperative, blockchain enables that.” He emphasized the word enable. To him, “There’s a difference between enabling and moving the world in a new direction.” He said, “People still have to want to do it, to take the risk of doing it.”31 So get ready for blockchain Airbnb, blockchain Uber, blockchain Lyft, blockchain Task Rabbit, and blockchain everything wherever there is an opportunity for real sharing and for value creation to work together in a cooperative way and receive most of the value they create. 4. The Metering Economy Perhaps blockchain technology can take us beyond the sharing economy into a metering economy where we can rent out and meter the use of our excess capacity. One problem with the actual sharing economy, where, for example, home owners agree to share power tools or small farming equipment, fishing gear, a woodworking shop, garage or parking, and more, was that it was just too much of a hassle.


pages: 441 words: 96,534

Streetfight: Handbook for an Urban Revolution by Janette Sadik-Khan

autonomous vehicles, bike sharing scheme, Boris Johnson, business cycle, call centre, car-free, carbon footprint, clean water, congestion charging, crowdsourcing, digital map, edge city, Edward Glaeser, en.wikipedia.org, Enrique Peñalosa, Hyperloop, Induced demand, Jane Jacobs, Loma Prieta earthquake, Lyft, New Urbanism, place-making, self-driving car, sharing economy, the built environment, The Death and Life of Great American Cities, the High Line, transportation-network company, Uber and Lyft, uber lyft, urban decay, urban planning, urban renewal, urban sprawl, walkable city, white flight, Works Progress Administration, Zipcar

While we adapt our cities to a new age and update the legacy hardware of our streets to serve more varied purposes, the software also needs updating to help us use our streets more efficiently. If this book does nothing else but remind planners to follow the people, then they should also be able to see how new technologies are driving a new, shared economy in transportation that holds the key to creating safer, more accessible, and softer streets. With a couple of clicks we can get a ride with Uber or Lyft, grab a shared bike or car, or navigate a city we’ve never been in before. New smartphone apps are making it possible to avoid traffic jams, locate bus and subway services, and walk to points of interest. These software bits are much less expensive than the atoms of hard infrastructure and are dramatically increasing the rate of innovation on our streets, giving way to a bigger vision with mobility on demand and changing the way we travel in our cities.

A future with autonomous vehicles, delivery drones, and unified payment systems is on the near-term horizon. This wave of change has landed on our streets, and these changes will advance how we get around cities and use our streets. A smartphone can eliminate the anxiety of getting around, whether you’re in Boston, Bangalore, or Buenos Aires. But these new apps also pose big questions. While new transportation services like Uber and Lyft (called transportation network companies or TNCs in transport-speak), or shared-vehicle services like Car2Go, Zipcar, and Bridj, are using technology to dramatically lower the operating and entry costs for taxi and car services, they raise questions about social equity, safety, and the true costs of these popular services. Without a regulatory framework, cities could see outcomes that run counter to goals of mobility, sustainability, accessibility, and social equity.

The organizing principle is based on the view that how you get around is something that is provided for you—a service—instead of something you have to own, like a car. If all channels of public transportation—buses, trains, taxis, car pools, and car share—are integrated, citizens could pick a bundled package of these services, starting with, say, a €95 ($106) monthly transportation subscription for unlimited public transport in the city and also up to 100 kilometers (62 miles) of on-demand car services such as Uber or Hailo or Lyft. If subscribers need to visit relatives in the country or go camping for the weekend, they are entitled to up to 500 kilometers (310 miles) of shared-car use. If subscribers stay within these usage levels, they pay only that flat fee. More expensive options would let users get door-to-door shared taxi service plus public transport plus domestic transportation anywhere in the country via public transportation.


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

The Internet put us on this disintermediating path some time ago, well before the blockchain came along. But it’s worth noting that at the heart of each new Internet application that cuts out some incumbent middleman there has typically been a technology that helps humans deal with their perennial mistrust issues. Who would have thought a decade ago that people would feel comfortable riding in the car of some stranger they’d just discovered on their phones? Well, Uber and Lyft got us over that trust barrier by incorporating a reputation scoring system for both drivers and passengers, one that was only made possible because of the expansion of social networks and communication. Their model showed that if we can resolve our trust issues with technology and give people confidence to transact, those people are willing and able to go into direct exchanges with complete strangers.

In November 2014, Uber launched an investigation into the actions of its New York general manager, Josh Mohrer, after BuzzFeed journalist Johana Bhuiyan reported that he had used the God’s view feature to monitor her movements. The outcry over this and other privacy concerns led to a settlement with New York Attorney General Eric Schneiderman in which Uber agreed to encrypt riders’ names and geolocation data. It’s certainly not hard to see that Uber and its main competitor, Lyft, have quickly enmeshed themselves in our daily lives. When the name of your company becomes a verb—Xerox, Google, Uber—you know you’ve arrived. But for all the branding associated with democratizing transportation, and with allowing drivers and passengers to come together and “ride-share,” Uber is really a centralization play. It’s not about disintermediation at all. This for-profit company is the gatekeeper for every deal that gets struck between every driver and every passenger, and for that it takes 25 percent each time.

See also crowdfunding know-your-customer (KYC) know-your-machine Larimer, Daniel ledger-keeping and Bitcoin double-entry bookkeeping history of triple-entry bookkeeping value of Lehman Brothers Lemieux, Victoria L. Leondrino Exchange Lessig, Lawrence Levine, Matt Lewis, Michael Lightning Network Linux Foundation Litecoin Llanos, Juan Lloyd’s of London LO3 Energy Lovejoy, James Loyyal Lubin, Joseph Ludwin, Adam Lyft Lykke Madoff, Bernie Maidsafe Malaysian Airlines flight MH370 Marshall, George C. Marshall Plan Masters, Blythe May, Tim Mediachain MedRec Merkle Tree Metastable Capital Metz, Cade Micali, Silvio microfinance Microsoft Miller, Erick Miller, Mark S. MIT Media Lab MIT Media Lab’s Digital Currency Initiative Mizrahi, Alex MME Modi, Narendra Monax Monero monetary and banking systems central bank fiat digital currency and community connections and digital counterfeiting mobile money systems money laundering See also cryptocurrency; financial sector Moore’s law Mooti Morehead, Dan Mozilla M-Pesa Nakamoto, Satoshi (pseudonymous Bitcoin creator) Nasdaq Nelson, Ted New America Foundation New York Department of Financial Services Niederauer, Duncan North American Bitcoin Conference Norway Obama, Barack Occupy Wall Street Ocean Health Coin off-chain environment Olsen, Richard open protocols open-source systems and movement and art and innovation challenges of Cryptokernel (CK) and data storage and financial sector and health care sector and honest accounting Hyperledger and identity and permissioned systems and registries and ride-sharing and tokens See also Ethereum organized crime Pacioli, Luca Pantera Capital Parity Wallet peer-to-peer commerce and economy Pentland, Alex “Sandy” Perkins Coie permissioned (private) blockchains advantages of challenges of and cryptocurrency-less systems definition of and finance sector open-source development of scalability of and security and supply chains permissionless blockchains Bitcoin and Cypherpunks Ethereum financial sector and identity information mobile money systems and scalability and trusted computing Pink Army Cooperative Plasma Polkadot Polychain Capital Poon, Joseph practical byzantine fault tolerance (PBFT) pre-mining pre-selling private blockchains.


pages: 340 words: 97,723

The Big Nine: How the Tech Titans and Their Thinking Machines Could Warp Humanity by Amy Webb

Ada Lovelace, AI winter, Airbnb, airport security, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, artificial general intelligence, Asilomar, autonomous vehicles, Bayesian statistics, Bernie Sanders, bioinformatics, blockchain, Bretton Woods, business intelligence, Cass Sunstein, Claude Shannon: information theory, cloud computing, cognitive bias, complexity theory, computer vision, crowdsourcing, cryptocurrency, Daniel Kahneman / Amos Tversky, Deng Xiaoping, distributed ledger, don't be evil, Donald Trump, Elon Musk, Filter Bubble, Flynn Effect, gig economy, Google Glasses, Grace Hopper, Gödel, Escher, Bach, Inbox Zero, Internet of things, Jacques de Vaucanson, Jeff Bezos, Joan Didion, job automation, John von Neumann, knowledge worker, Lyft, Mark Zuckerberg, Menlo Park, move fast and break things, move fast and break things, natural language processing, New Urbanism, one-China policy, optical character recognition, packet switching, pattern recognition, personalized medicine, RAND corporation, Ray Kurzweil, ride hailing / ride sharing, Rodney Brooks, Rubik’s Cube, Sand Hill Road, Second Machine Age, self-driving car, SETI@home, side project, Silicon Valley, Silicon Valley startup, skunkworks, Skype, smart cities, South China Sea, sovereign wealth fund, speech recognition, Stephen Hawking, strong AI, superintelligent machines, technological singularity, The Coming Technological Singularity, theory of mind, Tim Cook: Apple, trade route, Turing machine, Turing test, uber lyft, Von Neumann architecture, Watson beat the top human players on Jeopardy!, zero day

Alibaba sold to 515 million customers in 2017 alone, and that year its Singles’ Day Festival—a sort of Black Friday meets the Academy Awards in China—saw $25 billion in online purchases from 812 million orders on a single day.40 China has the largest digital market in the world regardless of how you measure it: more than a trillion dollars spent annually, more than a billion people online, and $30 billion invested in venture deals in the world’s most important tech companies.41 Chinese investors were involved in 7–10% of all funding of tech startups in the United States between 2012 and 2017—that’s a significant concentration of wealth pouring in from just one region.42 The BAT are now well established in Seattle and Silicon Valley, operating out of satellite offices that include spaces along Menlo Park’s fabled Sand Hill Road. During the past five years, the BAT invested significant money in Tesla, Uber, Lyft, Magic Leap (the mixed-reality headset and platform maker), and more. Venture investment from BAT companies is attractive not just because they move quickly and have a lot of cash but because a BAT deal typically means a lucrative entrée into the Chinese market, which can otherwise be impossible to penetrate. For example, a small Kansas City–based face recognition startup called Zoloz was acquired by Alibaba for $100 million in 2016; it became a core component of the Alipay payment service and, in the process, gained access to hundreds of millions of users without having to contend with strict privacy laws in Europe or the potential threat of privacy lawsuits in the US.

Early experiments proved successful as hundreds of thousands of people donated their idle processing time to all kinds of worthy projects around the world, supporting projects like the Quake-Catcher Network, which looks for seismic activity, and SETI@home, which searches for extraterrestrial life out in the universe. By 2018, some clever entrepreneurs had figured out how to repurpose those networks for the gig economy v2.0. Rather than driving for Uber or Lyft, freelancers could install “gigware” to earn money for idle time. The latest gigware lets third-party businesses use our devices in exchange for credits or real money we can spend elsewhere. Like the early days of ride-sharing services, a lot of people left the traditional workforce to stake their claim in this new iteration of the gig economy. They quit their jobs and tried to scrape together a living simply by leasing out access to their devices.

There is no way to sugarcoat Amazon families: they’re poor, even if they have free access to cool gadgets. Families are locked into their PDRs, and that designation travels with them. It’s easier for a Google Yellow family to port into the Blue or even Green level than an Amazon to port into the Apple system. That’s why most families opted-in to Google when they had the opportunity. Your status is visible to all of the AIs you interact with. Self-driving taxi services like Lyft, Uber, and CitiCar don’t pick up Amazon riders with as much frequency, and cars sent to them tend not to be as nice. Waymo cars exclusively pick up Googlers. For Greens, the car is preset to the rider’s desired temperature and ambient lighting scheme, and it drives along the rider’s preferred routes. Yellows are subjected to advertising their entire trip. Advertising isn’t the only headache for Yellow Googlers.


pages: 116 words: 31,356

Platform Capitalism by Nick Srnicek

3D printing, additive manufacturing, Airbnb, Amazon Mechanical Turk, Amazon Web Services, Capital in the Twenty-First Century by Thomas Piketty, cloud computing, collaborative economy, collective bargaining, deindustrialization, deskilling, disintermediation, future of work, gig economy, Infrastructure as a Service, Internet of things, Jean Tirole, Jeff Bezos, knowledge economy, knowledge worker, liquidity trap, low skilled workers, Lyft, Mark Zuckerberg, means of production, mittelstand, multi-sided market, natural language processing, Network effects, new economy, Oculus Rift, offshore financial centre, pattern recognition, platform as a service, quantitative easing, RFID, ride hailing / ride sharing, Robert Gordon, self-driving car, sharing economy, Shoshana Zuboff, Silicon Valley, Silicon Valley startup, software as a service, TaskRabbit, the built environment, total factor productivity, two-sided market, Uber and Lyft, Uber for X, uber lyft, unconventional monetary instruments, unorthodox policies, Zipcar

As a result, Airbnb, Slack, Uber, and many other start-ups use AWS.79 Uber further relies on Google for mapping, Twilio for texting, SendGrid for emailing, and Braintree for payments: it is a lean platform built on other platforms. These companies have also offloaded costs from their balance sheets and shifted them to their workers: things like investment costs (accommodations for Airbnb, vehicles for Uber and Lyft), maintenance costs, insurance costs, and depreciation costs. Firms such as Instacart (which delivers groceries) have also outsourced delivery costs to food suppliers (e.g. Pepsi) and to retailers (e.g. Whole Foods) in return for advertising space.80 However, even with this support, Instacart remains unprofitable on 60 per cent of its business, and that is before the rather large costs of office space or the salaries of its core team are taken into account.81 The lack of profitability has led to the predictable measure of cutting back on wages – a notably widespread phenomenon among lean platforms.

The convergence thesis helps explain why Google is lobbying with Uber on self-driving cars and why Amazon and Microsoft have been discussing partnerships with German automakers on the cloud platform required by self-driving cars.28 Alibaba and Apple have made major investments in Didi, Apple’s partnership being particularly strategic, given that iPhones are the major interface to taxi services. And nearly all of the major platforms are working to develop medical data platforms. The trend to convergence is igniting international competition as well: intense struggles occur in India and China over who will dominate the ride-sharing industry (Uber, Didi, Lyft) and who will dominate e-commerce (Amazon, Alibaba, Flipkart). Alibaba is already the largest e-commerce site in the world as measured by the volume of its sales,29 and Flipkart is valued at around $15 billion. Under the pressures of competition and the subsequent imperative to expand, we should expect these platforms to acquire as many companies as they need. Even second-tier platforms like Twitter and Yahoo are potential purchases, given the vast cash glut being held by the top tier of platforms (indeed, as I wrote this book, Microsoft purchased LinkedIn for $26 billion, gaining access to data on the changing interests, skills, and jobs of millions of workers).


pages: 667 words: 149,811

Economic Dignity by Gene Sperling

active measures, Affordable Care Act / Obamacare, autonomous vehicles, basic income, Bernie Sanders, Cass Sunstein, collective bargaining, corporate governance, David Brooks, desegregation, Detroit bankruptcy, Donald Trump, Double Irish / Dutch Sandwich, Elon Musk, employer provided health coverage, Erik Brynjolfsson, Ferguson, Missouri, full employment, gender pay gap, ghettoisation, gig economy, Gini coefficient, guest worker program, Gunnar Myrdal, housing crisis, income inequality, invisible hand, job automation, job satisfaction, labor-force participation, late fees, liberal world order, longitudinal study, low skilled workers, Lyft, Mark Zuckerberg, market fundamentalism, mass incarceration, mental accounting, meta analysis, meta-analysis, minimum wage unemployment, obamacare, offshore financial centre, payday loans, price discrimination, profit motive, race to the bottom, RAND corporation, randomized controlled trial, Richard Thaler, ride hailing / ride sharing, Ronald Reagan, Rosa Parks, Second Machine Age, secular stagnation, shareholder value, Silicon Valley, single-payer health, speech recognition, The Chicago School, The Future of Employment, The Wealth of Nations by Adam Smith, Toyota Production System, traffic fines, Triangle Shirtwaist Factory, Uber and Lyft, uber lyft, union organizing, universal basic income, War on Poverty, working poor, young professional, zero-sum game

As UberX was launching in 2012, of the nearly two million in-home workers like housekeepers, childcare workers, and direct-care aides—overwhelmingly women and a majority people of color—only 12 percent received health insurance from their job, and only 7 percent received a pension plan.14 According to a survey by the National Domestic Workers Alliance, fewer than 2 percent of domestic workers in 2011 received retirement or pension benefits from their primary employer, and only 4 percent received employer-provided health insurance; 65 percent of domestic workers did not have any health insurance.15 Even today, few realize that before the ride-sharing revolution, the taxi drivers that people used for generations rarely had health-care coverage or qualified for unemployment insurance or any help during downturns and recessions.16 For example, a 2007 study of New York City cabdrivers found they were generally classified as independent contractors—just as Uber and Lyft drivers are now—and did not qualify for overtime pay despite typically working more than seventy hours a week. A large majority lacked health insurance, despite substantial risk of on-the-job injuries.17 These facts may not have been easily captured in traditional job growth statistics or GDP measurements, but they mattered to people’s lives. Here’s another example: neither GDP nor job volume nor median income captures the economic pain felt by millions of working women suffering sexual harassment or sexual violence.

She did not realize she was an independent contractor, and not a traditional employee, until she was eight months pregnant and asked for maternity leave. Not only was she denied maternity leave, but the next day she was fired, and because she was not an employee, she did not have access to unemployment insurance.8 With so much riding on whether you receive a W-2 or a 1099, unions and worker advocates are correct to make the fight over misclassification a top-tier economic battle and insist that millions of gig workers—including most Uber and Lyft drivers—should be classified as employees, as they successfully did in a hard-fought 2019 legislative battle in California.9 This is the right fight under our current structure. Too many workers today get the worst of all worlds. They have neither the true autonomy and flexibility of being their own boss nor the economic benefits and security of being a W-2 employee where at a minimum their employer pays its half of Social Security and Medicare payroll taxes and ensures they are part of the unemployment insurance system.

INDEPENDENT CONTRACTORS In 1914, the Lehigh Valley Coal Company claimed that it was “not in the business of coal mining at all” but merely gave miners access to its mines and then bought coal from those miners. Lehigh argued that these miners were not employees and accordingly were not covered by the workers’ compensation statute at issue. Judge Learned Hand rejected this argument as “absurd,” since these miners “carr[y] on the company’s only business” of owning mines and selling coal.49 Lyft, Uber, and FedEx drivers likely would use Hand’s “absurd” language to describe the denial of their status as “employees.” In our modern economy, gig workers and independent contractors are a large and growing group. However, many have not been able to achieve economic security. In response, workers have organized strikes and protests overcoming challenges inherent in organizing these groups. As organizer and driver Rebecca Stack-Martinez notes, “There is no directory out there of who’s driving, how many drivers, how we can reach them.


pages: 252 words: 73,131

The Inner Lives of Markets: How People Shape Them—And They Shape Us by Tim Sullivan

"Robert Solow", Airbnb, airport security, Al Roth, Alvin Roth, Andrei Shleifer, attribution theory, autonomous vehicles, barriers to entry, Brownian motion, business cycle, buy and hold, centralized clearinghouse, Chuck Templeton: OpenTable:, clean water, conceptual framework, constrained optimization, continuous double auction, creative destruction, deferred acceptance, Donald Trump, Edward Glaeser, experimental subject, first-price auction, framing effect, frictionless, fundamental attribution error, George Akerlof, Goldman Sachs: Vampire Squid, Gunnar Myrdal, helicopter parent, information asymmetry, Internet of things, invisible hand, Isaac Newton, iterative process, Jean Tirole, Jeff Bezos, Johann Wolfgang von Goethe, John Nash: game theory, John von Neumann, Joseph Schumpeter, Kenneth Arrow, late fees, linear programming, Lyft, market clearing, market design, market friction, medical residency, multi-sided market, mutually assured destruction, Nash equilibrium, Occupy movement, Pareto efficiency, Paul Samuelson, Peter Thiel, pets.com, pez dispenser, pre–internet, price mechanism, price stability, prisoner's dilemma, profit motive, proxy bid, RAND corporation, ride hailing / ride sharing, Robert Shiller, Robert Shiller, Ronald Coase, school choice, school vouchers, sealed-bid auction, second-price auction, second-price sealed-bid, sharing economy, Silicon Valley, spectrum auction, Steve Jobs, Tacoma Narrows Bridge, technoutopianism, telemarketer, The Market for Lemons, The Wisdom of Crowds, Thomas Malthus, Thorstein Veblen, trade route, transaction costs, two-sided market, uber lyft, uranium enrichment, Vickrey auction, Vilfredo Pareto, winner-take-all economy

Amazon and eBay serve this market-making role for buyers and sellers of just about everything; Angie’s List does it for plumbers, electricians, and other contractors on one side and those looking to fix or renovate their homes on the other. There need not be only two sides: Google’s Android is a meeting point for makers of smart phones like LG and Samsung, app designers, and consumers. The business networking service LinkedIn similarly brings together corporate recruiters, job hunters or employees, and advertisers. The list goes on, including some of the recent “sharing economy” companies that have gotten so much attention: Uber, Lyft, Airbnb, Postmates, and many other online marketplaces. The market maker faces a delicate balancing act in satisfying the needs and wants of each side. And indeed a platform isn’t much good unless all sides agree to participate. Just as no one would visit a supermarket that stocked only a limited supply of cornflakes, eBay wouldn’t get many visitors if the only items for bid were a couple of old Pez dispensers.

They’re the strategies Uber and every other business employs to try to keep customers from choosing freely among competing options in the marketplace, whether by driving competitors out of business or finding ways of keeping customers from shopping around. Sometimes, as we’ve learned from Uber in recent years, it can be a dirty business. They’ve been accused of misleading drivers on expected earnings (an information friction in the labor market) and calling then canceling rides from competing service Lyft (a friction in the market for rides), among other underhanded methods. So yes, you want to build that game-changing app. But to get your $60 billion valuation, you need to create as many frictions as possible for everyone else. Although proponents of the sharing economy tout its ability to reduce market frictions, the only way they’re going to make the kinds of profits they (and their investors) want is to create new ones.

.), 164–165 kidneys sales, 160–161 transplant exchange algorithm, 162–166 King Rat (Clavell), 175–177 Klein, Joel, 143–144 labor markets, 48, 64–66 labor theory of value, 23 ladies night at bars, 123 laundry service platform, 112 lemon markets theory, 44–51, 58–59, 64, 112 “Let Them Eat Pollution” (article), 167 life insurance, 1840s, 153 Lincoln Elementary, 1–2 Little, I. M. D., 22 Liu, Qihong, 128–129 Lyft car service, 173 MAD (doctrine of nuclear deterrence by mutually assured destruction), 26 mail-in-bids, for auctions, 83–84 “The Market for Lemons” (Akerlof), 44–51, 64 market frictions, 169–174 market fundamentalists, 16–17 market insights, 14–15 market makers, 107–110, 118–121 markets 18th-century book, 90–91 competitive, 35, 124–126, 172–174, 180–181 design, 133, 137–142 dysfunction of, 36, 75–77, 143 economics of platform, 107–112 equilibrium, 33 fixed-price versus auctions, 96–97 food bank system, 154–160 image problem of, 152–153 labor, 48, 64–66 lemon, 44–51, 58–59, 64, 112 multisided, 108–112, 118–124 one-sided, 108–112 in POW camps, 4, 7–13, 175–177 rules for platform, 112–117 school choice in Sweden, 151–152 selfishness in, 177–179 technology and, 169–173 trade with uninformed parties, 166–169 transformation of, 13–17 two-sided, 108–112, 118–124 See also auctions; economics; platforms Marx, Karl, 20, 23 matching problems middle school dance partners, 131–132, 134, 137–140 student to school, 138–139, 141–142, 143–149 mathematics algebraic topology, 44–45 economic theory transformed by, 15, 19–27 game theory, 136 general equilibrium model, 29, 31–34, 36–37, 40, 45, 76 kidney exchange algorithm, 163–165 models, 20, 24–25, 30 in real world economics, 35–37 Samuelson connecting economics and, 28–29 Shapley-Gale algorithm, 137–140 Matsuzaka, Daisuke, 79–81, 87–89 Maxwell, James Clark, 24 McManus, Brian, 73–75 mechanism design, 133, 134 medical residency programs, 140 merchant from Prato, 105–107 middle school dance-matching, 131–132, 134, 137–140 Milgrom, Paul, 70–71, 98, 102–103 mobile market platform, 116 modeling applied theory, 45, 50, 75–76 competition, 35, 166, 172–173 congestion pricing, 86, 94 dysfunction of, 75–77 economic, 15, 24–29 mathematical, 20, 24–25, 30 reality-based economic, 35–37, 45, 49–51, 141 models auction, 82–84 eBay, 43, 46, 48 general equilibrium, 31–34, 36–37, 40, 76 lemons, 44–51, 58–59, 64, 112 Solow, 35 See also platforms; signaling model Moldovanu, Benny, 90–91 money burning costs, 70–71 money-back guarantees, 69–71 Morals & Markets: The Development of Life Insurance in the United States (Zelizer), 153 Morgenstern, Oskar, 25–27 mortality rates, of Japanese vs German POW camps, 10–13 MS-13 gang, 67 multisided markets, 108–112, 118–124 multisided platform, 14 multiunit Vickrey auction, 93 Murphy, Frank, 9 Nasar, Sylvia, 29 Nash, John, 32 National Archives’ World War II Prisoners of War Data File, 11 network externalities, 121–124 New England Program for Kidney Exchange, 164–165 New York Department of Education, 143–144, 145, 149 Nobel Prize in Economics, 34 See also Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel noncustomers, paying, 123–124 Nordstrom’s return policy, 69–70 no-risk money-back guarantees, 69–71 normal good, 180 no-trade rule, Japanese POW camps, 10–13 nuclear deterrence, 26 Omidyar, Pierre, 39–40 one-sided markets, 108–112 online retail, 41–43, 52–55 optimized efficiency, 85–86, 133 organ sales, 160–161 organizations, sick, 142–143 out-of-town bids, for auctions, 83–84 Pareto, Vilfredo, 20, 21–22 Pareto efficiency, 22 Penny Black stamp, 82–84 Percy P.


pages: 185 words: 43,609

Zero to One: Notes on Startups, or How to Build the Future by Peter Thiel, Blake Masters

Airbnb, Albert Einstein, Andrew Wiles, Andy Kessler, Berlin Wall, cleantech, cloud computing, crony capitalism, discounted cash flows, diversified portfolio, don't be evil, Elon Musk, eurozone crisis, income inequality, Jeff Bezos, Lean Startup, life extension, lone genius, Long Term Capital Management, Lyft, Marc Andreessen, Mark Zuckerberg, minimum viable product, Nate Silver, Network effects, new economy, paypal mafia, Peter Thiel, pets.com, profit motive, Ralph Waldo Emerson, Ray Kurzweil, self-driving car, shareholder value, Silicon Valley, Silicon Valley startup, Singularitarianism, software is eating the world, Steve Jobs, strong AI, Ted Kaczynski, Tesla Model S, uber lyft, Vilfredo Pareto, working poor

Consider the Silicon Valley startups that have harnessed the spare capacity that is all around us but often ignored. Before Airbnb, travelers had little choice but to pay high prices for a hotel room, and property owners couldn’t easily and reliably rent out their unoccupied space. Airbnb saw untapped supply and unaddressed demand where others saw nothing at all. The same is true of private car services Lyft and Uber. Few people imagined that it was possible to build a billion-dollar business by simply connecting people who want to go places with people willing to drive them there. We already had state-licensed taxicabs and private limousines; only by believing in and looking for secrets could you see beyond the convention to an opportunity hidden in plain sight. The same reason that so many internet companies, including Facebook, are often underestimated—their very simplicity—is itself an argument for secrets.

Kaczynski, Ted Karim, Jawed Karp, Alex, 11.1, 12.1 Kasparov, Garry Katrina, Hurricane Kennedy, Anthony Kesey, Ken Kessler, Andy Kurzweil, Ray last mover, 11.1, 13.1 last mover advantage lean startup, 2.1, 6.1, 6.2 Levchin, Max, 4.1, 10.1, 12.1, 14.1 Levie, Aaron lifespan life tables LinkedIn, 5.1, 10.1, 12.1 Loiseau, Bernard Long-Term Capital Management (LTCM) Lord of the Rings (Tolkien) luck, 6.1, 6.2, 6.3, 6.4 Lucretius Lyft MacBook machine learning Madison, James Madrigal, Alexis Manhattan Project Manson, Charles manufacturing marginal cost marketing Marx, Karl, 4.1, 6.1, 6.2, 6.3 Masters, Blake, prf.1, 11.1 Mayer, Marissa Medicare Mercedes-Benz MiaSolé, 13.1, 13.2 Michelin Microsoft, 3.1, 3.2, 3.3, 4.1, 5.1, 14.1 mobile computing mobile credit card readers Mogadishu monopoly, monopolies, 3.1, 3.2, 3.3, 5.1, 7.1, 8.1 building of characteristics of in cleantech creative dynamism of new lies of profits of progress and sales and of Tesla Morrison, Jim Mosaic browser music recording industry Musk, Elon, 4.1, 6.1, 11.1, 13.1, 13.2, 13.3 Napster, 5.1, 14.1 NASA, 6.1, 11.1 NASDAQ, 2.1, 13.1 National Security Agency (NSA) natural gas natural secrets Navigator browser Netflix Netscape NetSecure network effects, 5.1, 5.2 New Economy, 2.1, 2.2 New York Times, 13.1, 14.1 New York Times Nietzsche, Friedrich Nokia nonprofits, 13.1, 13.2 Nosek, Luke, 9.1, 14.1 Nozick, Robert nutrition Oedipus, 14.1, 14.2 OfficeJet OmniBook online pet store market Oracle Outliers (Gladwell) ownership Packard, Dave Page, Larry Palantir, prf.1, 7.1, 10.1, 11.1, 12.1 PalmPilots, 2.1, 5.1, 11.1 Pan, Yu Panama Canal Pareto, Vilfredo Pareto principle Parker, Sean, 5.1, 14.1 Part-time employees patents path dependence PayPal, prf.1, 2.1, 3.1, 4.1, 4.2, 4.3, 5.1, 5.2, 5.3, 8.1, 9.1, 9.2, 10.1, 10.2, 10.3, 10.4, 11.1, 11.2, 12.1, 12.2, 14.1 founders of, 14.1 future cash flows of investors in “PayPal Mafia” PCs Pearce, Dave penicillin perfect competition, 3.1, 3.2 equilibrium of Perkins, Tom perk war Perot, Ross, 2.1, 12.1, 12.2 pessimism Petopia.com Pets.com, 4.1, 4.2 PetStore.com pharmaceutical companies philanthropy philosophy, indefinite physics planning, 2.1, 6.1, 6.2 progress without Plato politics, 6.1, 11.1 indefinite polling pollsters pollution portfolio, diversified possession power law, 7.1, 7.2, 7.3 of distribution of venture capital Power Sellers (eBay) Presley, Elvis Priceline.com Prince Procter & Gamble profits, 2.1, 3.1, 3.2, 3.3 progress, 6.1, 6.2 future of without planning proprietary technology, 5.1, 5.2, 13.1 public opinion public relations Pythagoras Q-Cells Rand, Ayn Rawls, John, 6.1, 6.2 Reber, John recession, of mid-1990 recruiting, 10.1, 12.1 recurrent collapse, bm1.1, bm1.2 renewable energy industrial index research and development resources, 12.1, bm1.1 restaurants, 3.1, 3.2, 5.1 risk risk aversion Romeo and Juliet (Shakespeare) Romulus and Remus Roosevelt, Theodore Royal Society Russia Sacks, David sales, 2.1, 11.1, 13.1 complex as hidden to non-customers personal Sandberg, Sheryl San Francisco Bay Area savings scale, economies of Scalia, Antonin scaling up scapegoats Schmidt, Eric search engines, prf.1, 3.1, 5.1 secrets, 8.1, 13.1 about people case for finding of looking for using self-driving cars service businesses service economy Shakespeare, William, 4.1, 7.1 Shark Tank Sharma, Suvi Shatner, William Siebel, Tom Siebel Systems Silicon Valley, 1.1, 2.1, 2.2, 2.3, 5.1, 5.2, 6.1, 7.1, 10.1, 11.1 Silver, Nate Simmons, Russel, 10.1, 14.1 singularity smartphones, 1.1, 12.1 social entrepreneurship Social Network, The social networks, prf.1, 5.1 Social Security software engineers software startups, 5.1, 6.1 solar energy, 13.1, 13.2, 13.3, 13.4 Solaria Solyndra, 13.1, 13.2, 13.3, 13.4, 13.5 South Korea space shuttle SpaceX, prf.1, 10.1, 11.1 Spears, Britney SpectraWatt, 13.1, 13.2 Spencer, Herbert, 6.1, 6.2 Square, 4.1, 6.1 Stanford Sleep Clinic startups, prf.1, 1.1, 5.1, 6.1, 6.2, 7.1 assigning responsibilities in cash flow at as cults disruption by during dot-com mania economies of scale and foundations of founder’s paradox in lessons of dot-com mania for power law in public relations in sales and staff of target market for uniform of venture capital and steam engine Stoppelman, Jeremy string theory strong AI substitution, complementarity vs.


pages: 252 words: 78,780

Lab Rats: How Silicon Valley Made Work Miserable for the Rest of Us by Dan Lyons

Airbnb, Amazon Web Services, Apple II, augmented reality, autonomous vehicles, basic income, bitcoin, blockchain, business process, call centre, Clayton Christensen, clean water, collective bargaining, corporate governance, corporate social responsibility, creative destruction, cryptocurrency, David Heinemeier Hansson, Donald Trump, Elon Musk, Ethereum, ethereum blockchain, full employment, future of work, gig economy, Gordon Gekko, greed is good, hiring and firing, housing crisis, income inequality, informal economy, Jeff Bezos, job automation, job satisfaction, job-hopping, John Gruber, Joseph Schumpeter, Kevin Kelly, knowledge worker, Lean Startup, loose coupling, Lyft, Marc Andreessen, Mark Zuckerberg, McMansion, Menlo Park, Milgram experiment, minimum viable product, Mitch Kapor, move fast and break things, move fast and break things, new economy, Panopticon Jeremy Bentham, Paul Graham, paypal mafia, Peter Thiel, plutocrats, Plutocrats, precariat, RAND corporation, remote working, RFID, ride hailing / ride sharing, Ronald Reagan, Rubik’s Cube, Ruby on Rails, Sam Altman, Sand Hill Road, self-driving car, shareholder value, Silicon Valley, Silicon Valley startup, six sigma, Skype, Social Responsibility of Business Is to Increase Its Profits, software is eating the world, Stanford prison experiment, stem cell, Steve Jobs, Steve Wozniak, Stewart Brand, TaskRabbit, telemarketer, Tesla Model S, Thomas Davenport, Tony Hsieh, Toyota Production System, traveling salesman, Travis Kalanick, tulip mania, Uber and Lyft, Uber for X, uber lyft, universal basic income, web application, Whole Earth Catalog, Y Combinator, young professional

But then came the onslaught of new drivers working for services like Uber and Lyft, and rates plummeted for everyone, so low that nobody could make a living as a driver anymore. Schifter was putting in seventeen-hour days, sometimes earning as little as $4 an hour. He fell into debt. He missed a mortgage payment and was in danger of losing his home. “I have been financially ruined,” he wrote. “I will not be a slave working for chump change. I would rather be dead.” Silicon Valley promotes the gig economy as an innovative new industry that is creating jobs for millions of people. But the jobs being created are mostly bad ones. Meanwhile, gig-economy companies threaten established industries. Airbnb steals business from hotels. Uber and Lyft have hurt business at car-rental companies like Hertz and Avis, and have utterly decimated the taxi and livery business.

But as magical as these companies may be, there’s one thing unicorns seem unable to do—turn a profit. Tesla, Spotify, Dropbox, Box, Snap, Square, Workday, Cloudera, Okta, Blue Apron, Roku, MongoDB, Redfin, Yext, Forescout, Docusign, Smartsheet—they’re all publicly traded, and they all lose money, and in some cases a lot of it, sometimes for years and years, long after they go public. Other unicorns like Uber, Lyft, Airbnb, Slack, Pinterest, WeWork, Vice Media, Magic Leap, Bloom Energy, and Postmates remain privately held, but reportedly don’t turn a profit. As I write this, a tech start-up called Domo is attempting to offer shares to the public even though the company lost $360 million over the past two years, on sales of just $183 million, meaning Domo loses two dollars for every dollar it took in. This is madness.


pages: 292 words: 85,151

Exponential Organizations: Why New Organizations Are Ten Times Better, Faster, and Cheaper Than Yours (And What to Do About It) by Salim Ismail, Yuri van Geest

23andMe, 3D printing, Airbnb, Amazon Mechanical Turk, Amazon Web Services, augmented reality, autonomous vehicles, Baxter: Rethink Robotics, Ben Horowitz, bioinformatics, bitcoin, Black Swan, blockchain, Burning Man, business intelligence, business process, call centre, chief data officer, Chris Wanstrath, Clayton Christensen, clean water, cloud computing, cognitive bias, collaborative consumption, collaborative economy, commoditize, corporate social responsibility, cross-subsidies, crowdsourcing, cryptocurrency, dark matter, Dean Kamen, dematerialisation, discounted cash flows, disruptive innovation, distributed ledger, Edward Snowden, Elon Musk, en.wikipedia.org, Ethereum, ethereum blockchain, game design, Google Glasses, Google Hangouts, Google X / Alphabet X, gravity well, hiring and firing, Hyperloop, industrial robot, Innovator's Dilemma, intangible asset, Internet of things, Iridium satellite, Isaac Newton, Jeff Bezos, Joi Ito, Kevin Kelly, Kickstarter, knowledge worker, Kodak vs Instagram, Law of Accelerating Returns, Lean Startup, life extension, lifelogging, loose coupling, loss aversion, low earth orbit, Lyft, Marc Andreessen, Mark Zuckerberg, market design, means of production, minimum viable product, natural language processing, Netflix Prize, NetJets, Network effects, new economy, Oculus Rift, offshore financial centre, PageRank, pattern recognition, Paul Graham, paypal mafia, peer-to-peer, peer-to-peer model, Peter H. Diamandis: Planetary Resources, Peter Thiel, prediction markets, profit motive, publish or perish, Ray Kurzweil, recommendation engine, RFID, ride hailing / ride sharing, risk tolerance, Ronald Coase, Second Machine Age, self-driving car, sharing economy, Silicon Valley, skunkworks, Skype, smart contracts, Snapchat, social software, software is eating the world, speech recognition, stealth mode startup, Stephen Hawking, Steve Jobs, subscription business, supply-chain management, TaskRabbit, telepresence, telepresence robot, Tony Hsieh, transaction costs, Travis Kalanick, Tyler Cowen: Great Stagnation, uber lyft, urban planning, WikiLeaks, winner-take-all economy, X Prize, Y Combinator, zero-sum game

“Unlike digital marketing, where ROI is sustained almost as soon as spending happens, communities are a long-term investment that is significantly more strategic,” says social business thought leader Dion Hinchcliffe. “Additionally, communities with CxO participation are far more likely to be best-in-class.” Create a platform to automate peer-to-peer engagement. GitHub, for example, has its members rate and review other members’ code. Airbnb hosts and users fill out evaluation forms; taxi disrupters Uber, Lyft and Sidecar encourage clients and drivers to rate one another; and the news platform Reddit invites users to vote on stories. In 2013, Reddit, which has just fifty-one employees, most of whom manage the platform, saw 731 million unique visitors cast 6.7 billion votes on 41 million stories. Talk about a platform…(More on this later.) Tony Hsieh, CEO of Las Vegas-based Zappos, was inspired by the Burning Man community to combine both physical and trait-based communities within his Las Vegas Downtown Project.

GE, in conjunction with TechShop, Skillshare and Quirky, launched a similar initiative last year in Chicago called GE Garages. As with Staff on Demand, ExOs retain their flexibility precisely by not owning assets, even in strategic areas. This practice optimizes flexibility and allows the enterprise to scale incredibly quickly as it obviates the need for staff to manage those assets. Just as Waze piggybacked off its users’ smartphones, Uber, Lyft, BlaBlaCar and Sidecar leverage under-utilized cars. (If you own a car, it sits empty about 93 percent of the time.) The latest wave of non-asset businesses is something called Collaborative Consumption, a concept evangelized by Rachel Botsman and Roo Rogers in their book, What’s Mine is Yours: The Rise of Collaborative Consumption. The book pushes the sharing philosophy forward by establishing information-enabled assets of all kinds, from textbooks to gardening tools to housing—assets and resources that are abundant and widely available.

DIY Drones, GitHub, Wikipedia) Engagement of Community & Crowd 6) Do you actively convert “the Crowd” (general public) into Community members?* ( ) We use standard techniques like PR to increase awareness ( ) We leverage social media for marketing purposes ( ) We use gamification and incentive competitions to turn crowd into community ( ) Our products and services are inherently designed to convert crowd into Community (e.g. shareable memes like the Lyft mustache or Hotmail signature) 7) To what extent do you use Gamification or Incentive Competitions?* ( ) We use gamification/incentive competitions for internal motivation only (e.g. salesperson of the month) ( ) We use basic gamification externally (e.g. loyalty programs, frequent flyer programs) ( ) We build gamification/incentive competitions into our products and services (e.g. Foursquare) ( ) We use gamification/incentive competitions to drive ideation and product development (e.g.


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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

Individuals migrate from being employees to “entrepreneurs.” The sharing economy will have great impact in areas where expensive, privately owned assets are underutilized. Automobiles are one such asset. Privately owned automobiles spend as much as 95 percent of their time parked.42 That means the average car is driven approximately nine hours a week. A number of sharing services have emerged with a goal of monetizing those idle hours. Uber and Lyft are already household names. The twentieth-century relic Zipcar is now owned by Avis.43 New aspirants keep emerging. Getaround allows neighbors to rent cars from other neighbors by the hour, while a competing service, Turo, focuses on longer-term rentals.44 Turo’s website claims that owners can cover their monthly car payments by renting their cars for as few as nine days a month. It claims to operate from 4,700 cities, provide owners with liability insurance, and deliver cars directly to their renters.45 BlaBlaCar, a European service, allows its more than 35 million members to locate other members who are going where they want to so they can hitch a ride.46 Looming in the future, when the self-driving car arrives, are driverless types of Uber services.

The most advanced cars can drive themselves onto freeways, requiring help from their drivers only when they get into difficult situations. Meanwhile, broadband communications and social networking have made ride and car sharing and other new transportation paradigms more efficient. Suddenly the full-time jobs of 250,000 U.S. taxi and chauffeur drivers are at risk of being taken away by 400,000 mostly part-time drivers for Uber, Lyft, and other services.20 Cab companies are already having a difficult time competing. That’s not surprising: cab fares in Los Angeles are $2.70 per mile, while Uber charges about $1.00.21 The oversupply of Uber drivers drives down the price of the service and the value of the work done by drivers. There are other economic impacts as well. Some consumers are discovering that using Uber and occasionally renting a Zipcar or Car2Go is so convenient and cost-efficient that they can get rid of their own cars altogether and just ride and rent.

See also newspaper industry Kasparov, Garry, 46 Keynes, John Maynard, 187–189, 192, 194 Kuznets, Simon, 66–67, 68 labor productivity, 57–58, 105 law enforcement, 115 laws and regulations, 18 antitrust, 93, 160 compliance, voluntary, 190 cybercrime, 172, 175–176 cyber currency, 176–177 fake news, 169–170 privacy protection, 128–130 social phase change increasing, 160–161, 193 workers’ rights, 30–31, 160. See also governance rules and systems leadership, 7, 189, 190, 194 legal system and services, 104, 114 Lending Club, 80, 81 Lenoir, Étienne, 53 Leviathan (Hobbes), 161, 169 liberty, threats to: action necessary to combat, 180, 190, 193, 194 in China, 115 data collection factors and evolution in, 13, 116–117, 123–128 historical protections for, 113–114 Libra, 10 life expectancy, 166 Lyft, 84, 100 Madison, James, 113–114 management systems. See business models; governance rules and systems manufacturing industry, xii, 33–34, 53 Marxist philosophy, 31 massively multiplayer online role-playing games (MMORPGs), 16–17, 137 Maybach, Wilhelm, 53 McNamee, Roger, 149 media industry: business model shifts in, 9–10, 72–73 customers becoming products in, 120–123 music, 72–73, 87 physical to virtual transformations in, 9–10, 11, 50, 65, 73, 98–99 printing press in origins of mass, 28 substitutional equivalence’s impact on job market, 72–73, 98–99.


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The Innovation Illusion: How So Little Is Created by So Many Working So Hard by Fredrik Erixon, Bjorn Weigel

"Robert Solow", Airbnb, Albert Einstein, American ideology, asset allocation, autonomous vehicles, barriers to entry, Basel III, Bernie Madoff, bitcoin, Black Swan, blockchain, BRICs, Burning Man, business cycle, Capital in the Twenty-First Century by Thomas Piketty, Cass Sunstein, Clayton Christensen, Colonization of Mars, commoditize, corporate governance, corporate social responsibility, creative destruction, crony capitalism, dark matter, David Graeber, David Ricardo: comparative advantage, discounted cash flows, distributed ledger, Donald Trump, Elon Musk, Erik Brynjolfsson, fear of failure, first square of the chessboard / second half of the chessboard, Francis Fukuyama: the end of history, George Gilder, global supply chain, global value chain, Google Glasses, Google X / Alphabet X, Gordon Gekko, high net worth, hiring and firing, Hyman Minsky, income inequality, income per capita, index fund, industrial robot, Internet of things, Jeff Bezos, job automation, job satisfaction, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, joint-stock company, Joseph Schumpeter, Just-in-time delivery, Kevin Kelly, knowledge economy, laissez-faire capitalism, Lyft, manufacturing employment, Mark Zuckerberg, market design, Martin Wolf, mass affluent, means of production, Mont Pelerin Society, Network effects, new economy, offshore financial centre, pensions crisis, Peter Thiel, Potemkin village, price mechanism, principal–agent problem, Productivity paradox, QWERTY keyboard, RAND corporation, Ray Kurzweil, rent-seeking, risk tolerance, risk/return, Robert Gordon, Ronald Coase, Ronald Reagan, savings glut, Second Machine Age, secular stagnation, Silicon Valley, Silicon Valley startup, Skype, sovereign wealth fund, Steve Ballmer, Steve Jobs, Steve Wozniak, technological singularity, telemarketer, The Chicago School, The Future of Employment, The Nature of the Firm, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, too big to fail, total factor productivity, transaction costs, transportation-network company, tulip mania, Tyler Cowen: Great Stagnation, uber lyft, University of East Anglia, unpaid internship, Vanguard fund, Yogi Berra

Other taxi firms and the trade unions had been attacking Uber cars and in early 2015 a court in Frankfurt ruled to ban UberPop, threatening it with a fine of up to €250,000 if the law is violated.7 Other German city authorities have followed Frankfurt’s lead, and countries like Italy, Spain, and the Netherlands have also banned the peer-to-peer service, all citing violations of commercial licenses as reason to expel Uber from the market. In Johannesburg, São Paolo, New York, and other metropolitan cities in the world, the company faces similar charges. New York Mayor Bill de Blasio tried to rehash an old regulation, restricting the growth of car-riding services like Uber, Sidecar, and Lyft to 1 percent a year, seemingly copying the thinking behind the taxi regulation in New York that has capped the number of yellow cab medallions.8 In Miami, these companies are banned. There is a bigger story about regulation embedded in these examples. Anchored among incumbents’ existing structures, regulation all too often helps to saturate or cement markets. While many existing firms complain about the effects of regulations, they know how to manage business under them and, if they are skilled operators, they can turn government interventions in their favor.

; Cecchetti and Kharroubi, “Reassessing the Impact of Finance on Growth.” 57.Swagel, “The Financial Crisis.” 58.Cecchetti and Kharroubi, “Why Growth in Finance Is a Drag on the Real Economy.” 59.Christensen, Kaufman, and Shih, “Innovation Killers,” 1–2. 60.Piketty, Capital in the Twenty-First Century, 264–81. 4 The Rise and Rise Again of Corporate Managerialism 1.Martti, Nokia: The Inside Story. 2.Steinbock, The Nokia Revolution. 3.Ahmad, Nokia’s Smartphone Problem. 4.Kuittinen, “Nokia Sells Handset Business to Microsoft.” 5.Lomas, “Nokia’s $7.2BN Devices & Services Exit.” 6.Cheng, “It’s Official: Motorola Mobility Now Belongs to Lenovo.” 7.Bass, “Microsoft’s Concept Videos.” 8.Jenkins, “Jenkins: Only Bill Gates Can Change Microsoft.” 9.Yarow, “Here’s What Steve Ballmer Thought about the iPhone.” 10.A good survey of companies failing at exits is McGrath, The End of Competitive Advantage. 11.Steinberg, “Among the First to Fall at I.B.M.” 12.Crainer, “‘Saving Big Blue.’” 13.Clinch, “How Apple Prompted This Country’s Downgrade.” 14.Schumpeter, Capitalism, Socialism and Democracy, 132. 15.Coase, “The Nature of the Firm,” 388. 16.Oliver Williamson, who received the Nobel Prize in economics for his work on economic governance, developed the idea of firm boundaries and put the emphasis on the internal or endogenous capacity of the firm to generate output that is more competitive than the market. 17.Santos and Eisenhardt, “Organizational Boundaries and Theories of Organization,” 491. 18.Coase, “The Nature of the Firm,” 390. 19.Coase, “The Nature of the Firm,” 404–5. 20.Zenger, Felin, and Bigelow, “Theories of the Firm–Market Boundary.” 21.Tett, The Silo Effect. 22.Morieux, “How Too Many Rules at Work Keep You from Getting Things Done.” 23.See, for instance, Caliendo and Rossi-Hansberg, “The Impact of Trade on Organization and Productivity.” 24.Zhou, “Coordination Costs, Organization Structure and Firm Growth.” 25.Langlois and Everett, “Complexity, Genuine Uncertainty, and the Economics of Organization”; Joskow, “Vertical Integration.” 26.Strom, “Big Companies Pay Later.” 27.Rajan and Zingales, “The Firm as a Dedicated Hierarchy.” 28.Bhide, The Origin and Evolution of New Business, 94. 29.Rajan and Zingales, “The Firm as a Dedicated Hierarchy,” 7. 30.Teece, “Profiting from Technological Innovation.” 31.Jensen, “Agency Cost of Free Cash Flow, Corporate Finance, and Takeovers.” 32.Stein, “Agency, Information and Corporate Investment”; Matvos and Seru, “Resource Allocation within Firms.” 33.See Berger and Ofek, “Diversification’s Effect on Firm Value”; Rajan, Servaes, and Zingales, “The Cost of Diversity.” 34.Scharfstein and Stein, “The Dark Side of Internal Capital Markets.” 35.Scharfstein and Stein. “The Dark Side of Internal Capital Markets.” 36.Büthe and Mattli, The New Global Rulers. 37.Kelly, “The Majority of iPhone Users Admit to ‘Blind Loyalty.’” 38.Kelly, “The Majority of iPhone Users Admit to ‘Blind Loyalty.’” 39.Johnson, De Lyfte Landet, 21. 40.All quotes are from Galbraith, The New Industrial State, 19. 41.Morieux, “Smart Rules.” 42.Bain & Co., “Busy CEOs.” 43.Langlois and Cosgel, “Frank Knight on Risk.” 44.Decker et al., “The Role of Entrepreneurship,” 10. 45.Harvard Business Review, Harvard Business Review on Strategies for Growth, 25–6. 46.Byrne, “The Man Who Invented Management.” 47.Porter, “How Competitive Forces Shape Strategy.” 48.Stephenson, “What Causes Top Management Teams to Make Poor Strategic Decisions?”

Jaruzelski, Barry, Volker Staack, and Brad Goehle, “Proven Paths to Innovation Success: Ten Years of Research Reveal the Best R&D Strategies for the Decade Ahead.” Global Innovation 1000, strategy+business, 77 (2014): 1–18. Jenkins, Holman W., “Jenkins: Only Bill Gates Can Change Microsoft.” Wall Street Journal, Aug. 27, 2013. At http://www.wsj.com/articles/SB10001424127887323906804579038852114518482. Jensen, Michael C., “Agency Cost of Free Cash Flow, Corporate Finance, and Takeovers.” American Economic Review, 76.2 (1986). Johnson, Anders, De Lyfte Landet: En Berättelse om Svenska Entreprenörer. Svenskt Näringsliv, 2002. Johnson, Steve, “Gulf States Redirect SWF Cash.” Financial Times, May 20, 2012. At http://www.ft.com/intl/cms/s/0/da57657e-a016-11e1-90f3-00144feabdc0.html#axzz3ode29Nn5. Johnston, Donald J., “Globalise or Fossilise!” OECD Observer, 219 (1999): 3. Jonquières, Guy de, “Who Is Afraid of China’s High-Tech Challenge?” ECIPE Policy Brief No. 7/2013, European Centre for International Political Economy, Sept. 2013.


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

The smartphone, the distributed network, open-source technology, the app economy, the global spread of the Internet, the invention of value-carrying peer-to-peer transmission services, the mobilization and personalization of the online experience—all of 5 these trends and technologies have been invented, gradually emerged, or matured in the last ten years. Right now, we can experience a form of commercial relationship that was unknown just a decade ago. If you need a ride in a major city, you can pull up the smartphone app for Uber or Lyft and have a car arrive in minutes. It’s amazing to users because they get their first taste of what consumer service in taxis really feels like. It’s luxury at a reasonable price. If your sink is leaking, you can click TaskRabbit. If you need a place to stay, you can count on Airbnb. In Manhattan, you can depend on WunWun to deliver just about anything to your door, from toothpaste to a new desktop computer.

The opponents of markets just can’t reconcile themselves to embracing the very thing they have supposedly advocated for generations: popular empowerment. Who could possibly be against such innovations? The answer is rather obvious: entrenched economic interests who stand to lose their old-world, government-regulated, and governmentprotected monopolies. Municipal taxi services, for example, feel deeply threatened by services such as Uber, Lyft, and Sidecar, which allow anyone to become a transportation service provider. The established monopolies are lobbying governments to crack down and are experiencing some modicum of success. San Francisco’s district attorney has sent threatening letters to companies that have vastly improved transportation, warning that they must make major changes in their business models. This reaction, he assured the public, is not because he is against innovation and consumer service.


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

David Johnston is a senior board member at the Mastercoin Foundation, the body that coordinates the funding for the Mastercoin project, which offers a special software platform for developers to design special decentralized applications that can run on top of the bitcoin blockchain. He says blockchain technology “will supercharge the sharing economy,” that emerging trend in which apartment owners use Airbnb.com to rent out quasi hotel rooms and car owners sign up as self-employed taxidrivers for smartphone-based Uber and Lyft. The idea is that if we can decentralize the economy and foster multiple forms of peer-to-peer exchanges, people will figure out profitable ways to turn much of what they own or control into a marketable service. Johnston is known for having coined the term DApp, for “decentralized autonomous application,” to describe the kind of specialized software programs that could thrive in blockchain-based settings.

Got some extra computing power sitting on your desktop? Share it with those who need it. Got a car sitting idle in your driveway? Share that. Got a big idea? Share it online and raise the money online to fund it. Business symbols of this era so far include the personal-apartment rental site Airbnb, the crowdfunding site Kickstarter, the peer-to-peer lending network Lending Club, and the taxi services controlled by individual car owners Uber and Lyft. In some respects these new business models are extensions of a process that began far earlier with the advent of the Internet. While no self-respecting bitcoiner would ever describe Google or Facebook as decentralized institutions, not with their corporate-controlled servers and vast databases of customers’ personal information, these giant Internet firms of our day got there by encouraging peer-to-peer and middleman-free activities.

Unlike a blockchain model, the lending is done in a centralized way in which the investor must trust the company itself, but the middleman-less mechanism has some of the same effects as projects touted by cryptocurrency advocates. Other big companies are also looking to figure out an adaptive response to the onset of new crowd- and sharing-based business models such as those employed by Uber, Airbnb, and Lyft. Silicon Valley–based Crowd Companies, which advises old-world companies on how to survive in this new economy, boasts an impressive list of clients, among them Visa, Home Depot, Hyatt, General Electric, Walmart, Coca-Cola, and FedEx. All are trying to figure out how to adapt their businesses to a centerless economy. What about the payments industry? Well, it looks to be dabbling in all three strategies in response to the challenge from cryptocurrencies.


pages: 511 words: 132,682

Competition Overdose: How Free Market Mythology Transformed Us From Citizen Kings to Market Servants by Maurice E. Stucke, Ariel Ezrachi

affirmative action, Airbnb, Albert Einstein, Andrei Shleifer, Bernie Sanders, Boeing 737 MAX, Cass Sunstein, choice architecture, cloud computing, commoditize, corporate governance, Corrections Corporation of America, Credit Default Swap, crony capitalism, delayed gratification, Donald Trump, en.wikipedia.org, George Akerlof, gig economy, Goldman Sachs: Vampire Squid, Google Chrome, greed is good, hedonic treadmill, income inequality, income per capita, information asymmetry, invisible hand, job satisfaction, labor-force participation, late fees, loss aversion, low skilled workers, Lyft, mandatory minimum, Mark Zuckerberg, market fundamentalism, mass incarceration, Menlo Park, meta analysis, meta-analysis, Milgram experiment, mortgage debt, Network effects, out of africa, payday loans, Ponzi scheme, precariat, price anchoring, price discrimination, profit maximization, profit motive, race to the bottom, Richard Thaler, ride hailing / ride sharing, Robert Bork, Robert Shiller, Robert Shiller, Ronald Reagan, shareholder value, Shoshana Zuboff, Silicon Valley, Snapchat, Social Responsibility of Business Is to Increase Its Profits, Stanford prison experiment, Stephen Hawking, The Chicago School, The Market for Lemons, The Myth of the Rational Market, The Wealth of Nations by Adam Smith, Thomas Davenport, Thorstein Veblen, Tim Cook: Apple, too big to fail, transaction costs, Uber and Lyft, uber lyft, ultimatum game, Vanguard fund, winner-take-all economy

Median net worth of Gen X households at the same age was about $15,100”). 14.Martha Ross and Natalie Holmes, “Meet the Millions of Young Adults Who Are Out of Work,” Brookings Institution, April 9, 2019, https://brook.gs/2UveFHI. 15.To illustrate how the digital economy can shift the risk from the powerful tech platforms to the worker, consider Uber and Lyft drivers. When the ride-sharing app enters into a new city, it needs to attract drivers. The first few drivers initially have a lot of power, as Uber and Lyft need to hold onto them (while recruiting even more drivers). They could possibly demand better wages. But as Uber and Lyft keep adding drivers, each driver now becomes slightly more expendable. As their numbers swell from a dozen to a few hundred and then a few thousand, each driver must compete even more fiercely for work, while each driver has even less power to negotiate for better wages and benefits. 16.Brief for the United States and the Federal Trade Commission as Amici Curiae in Support of Appellant and in Favor of Reversal, Chamber of Commerce of the United States of Am. v.

As for Generation Z (defined as those born in the mid-1990s to the early or mid-2000s) 17 percent of young adults ages eighteen to twenty-four are out of work in mid to large cities in the United States, totaling 2.3 million young people.14 They and future generations will likely join the swelling ranks of “precariats”—those clinging precariously to their current economic rung, while bearing ever greater risks in the digital economy.15 Should they try to organize to secure fairer wages, as many Uber and Lyft drivers attempted to do in Seattle in 2015, they can expect the government to intervene—and not on their behalf. Competition is inherently good, the FTC and DOJ will tell the court: Antitrust law “forbids independent contractors from collectively negotiating the terms of their engagement.”16 That’s price-fixing, which “is at the very core of the harms the antitrust laws seek to address.”17 Unionizing, which may be the only remedy left to the powerless, has also come under attack, in part for being anticompetitive—the very same rationale we saw that sent union leaders (and socialists) to jail under the Sherman Antitrust Act of 1890.


pages: 307 words: 88,180

AI Superpowers: China, Silicon Valley, and the New World Order by Kai-Fu Lee

AI winter, Airbnb, Albert Einstein, algorithmic trading, artificial general intelligence, autonomous vehicles, barriers to entry, basic income, business cycle, cloud computing, commoditize, computer vision, corporate social responsibility, creative destruction, crony capitalism, Deng Xiaoping, deskilling, Donald Trump, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, full employment, future of work, gig economy, Google Chrome, happiness index / gross national happiness, if you build it, they will come, ImageNet competition, income inequality, informal economy, Internet of things, invention of the telegraph, Jeff Bezos, job automation, John Markoff, Kickstarter, knowledge worker, Lean Startup, low skilled workers, Lyft, mandatory minimum, Mark Zuckerberg, Menlo Park, minimum viable product, natural language processing, new economy, pattern recognition, pirate software, profit maximization, QR code, Ray Kurzweil, recommendation engine, ride hailing / ride sharing, risk tolerance, Robert Mercer, Rodney Brooks, Rubik’s Cube, Sam Altman, Second Machine Age, self-driving car, sentiment analysis, sharing economy, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, Skype, special economic zone, speech recognition, Stephen Hawking, Steve Jobs, strong AI, The Future of Employment, Travis Kalanick, Uber and Lyft, uber lyft, universal basic income, urban planning, Y Combinator

Digital payments cracked open the black box of real-world consumer purchases, giving these companies a precise, real-time data map of consumer behavior. Peer-to-peer transactions added a new layer of social data atop those economic transactions. The country’s bike-sharing revolution has carpeted its cities in IoT transportation devices that color in the texture of urban life. They trace tens of millions of commutes, trips to the store, rides home, and first dates, dwarfing companies like Uber and Lyft in both quantity and granularity of data. The numbers for these categories lay bare the China-U.S. gap in these key industries. Recent estimates have Chinese companies outstripping U.S. competitors ten to one in quantity of food deliveries and fifty to one in spending on mobile payments. China’s e-commerce purchases are roughly double the U.S. totals, and the gap is only growing. Data on total trips through ride-hailing apps is somewhat scarce, but during the height of competition between Uber and Didi, self-reported numbers from the two companies had Didi’s rides in China at four times the total of Uber’s global rides.

People like Alibaba founder Jack Ma know how dangerous a ragtag bunch of insurgents can be when battling a monolithic foreign giant. So instead of seeking to both squash those startups and outcompete Silicon Valley, they’re throwing their lot in with the locals. RIDE-HAILING RUMBLE There are already some precedents for the Chinese approach. Ever since Didi drove Uber out of China, it has invested in and partnered with local startups fighting to do the same thing in other countries: Lyft in the United States, Ola in India, Grab in Singapore, Taxify in Estonia, and Careem in the Middle East. After investing in Brazil’s 99 Taxi in 2017, Didi outright acquired the company in early 2018. Together these startups have formed a global anti-Uber alliance, one that runs on Chinese money and benefits from Chinese know-how. After taking on Didi’s investments, some of the startups have even rebuilt their apps in Didi’s image, and others are planning to tap into Didi’s strength in AI: optimizing driver matching, automatically adjudicating rider-driver disputes, and eventually rolling out autonomous vehicles.

., 207 Kübler-Ross, Elisabeth, 188 Kurzweil, Ray, 140–41 L labor unions, decline of, 150 The Lean Startup, 44 lean startup methodology, 44–45 LeCun, Yann, 86, 88, 90, 93 Lee, Kai-Fu birth of first child, 177–79 cancer diagnosis, 176–77, 181–83, 225 epitaphs of, 180–81, 194 family of, 175–76, 177–79, 184–87, 193–94, 195, 225 Master Hsing Yun and, 187–90, 195 regrets of, 185–87, 188 research on lymphoma, 190–92 venture capital industry and, ix, xi, 3, 52 will of, 183–85 work obsession, 175–80 Lee Sedol, 3 legal decisions by judges, 115–16 Lenovo, 89 Li, Robin, 37 lifelong learning, 204 life purpose, loss of, 21 Li Keqiang, 62–63 LinkedIn, 39 Liu Qingfeng, 105 liveness algorithm, 118 love AI as opportunity to refocus on, 176–77, 196, 210 centrality of, in human experience, 198, 199, 225, 231–32 Lee’s cancer and refocus on, 193–96 Master Hsing Yun’s wisdom about, 189–90, 195 new social contract and, 200–201 regrets about not sharing, 185, 186–87, 195 service-focused impact investing and, 217 Luddite fallacy, 147–48, 151 Lyft, 79, 137 lymphoma, 176, 183, 190–92, 194 M Ma, Jack, 34–37, 60–61, 66–67, 137 machine learning advances in, recent, 160–61 algorithms, 40. See also algorithms, AI chips and, 96 data and, 56 deep learning as part of, 6, 94 economy driven by, 25, 84, 91, 94–95 social investment stipend and, 221–22 machine reading, 161 machine translation, 104, 161 Manhattan Project, 85 Manpower, 47–48 market-driven startups, 26–27, 45 mass entrepreneurship and mass innovation, 54, 62–68, 99 McAfee, Andrew, 148–49, 150 McCarthy, John, 7 McKinsey Global Institute, 159–60 medical diagnosis, 113–15, 167, 195, 211.


pages: 168 words: 50,647

The End of Jobs: Money, Meaning and Freedom Without the 9-To-5 by Taylor Pearson

"side hustle", Airbnb, barriers to entry, Ben Horowitz, Black Swan, call centre, cloud computing, commoditize, creative destruction, David Heinemeier Hansson, Elon Musk, en.wikipedia.org, Frederick Winslow Taylor, future of work, Google Hangouts, Kevin Kelly, Kickstarter, knowledge economy, knowledge worker, loss aversion, low skilled workers, Lyft, Marc Andreessen, Mark Zuckerberg, market fragmentation, means of production, Oculus Rift, passive income, passive investing, Peter Thiel, remote working, Ronald Reagan: Tear down this wall, sharing economy, side project, Silicon Valley, Skype, software as a service, software is eating the world, Startup school, Steve Jobs, Steve Wozniak, Stewart Brand, telemarketer, Thomas Malthus, Uber and Lyft, uber lyft, unpaid internship, Watson beat the top human players on Jeopardy!, web application, Whole Earth Catalog

A market opportunity that would have been available to a few thousand people that could afford to build a hotel is now available to a few million people that may have a spare bedroom. There are not many more houses now in the U.S. than there were 5 years ago, but AirBnB has created more inventory (extra rooms to stay in) without creating more supply (building hotels). Uber and Lyft have done for the taxi industry what AirBnB has done for the hotel industry—anyone with a car can become a taxi driver by signing up online to drive for the service. In the past it was difficult and expensive to become a taxi driver. Some cities require drivers to invest tens of thousands of dollars to buy a medallion just to drive a taxi. Uber and Lyft now let anyone do the work by instead going through a background check. A lot of people use this as supplemental income when making a job transition. They don’t have to invest thousands of dollars—they can just sign up on the website and make a few thousand bucks a month between jobs.


pages: 165 words: 50,798

Intertwingled: Information Changes Everything by Peter Morville

A Pattern Language, Airbnb, Albert Einstein, Arthur Eddington, augmented reality, Bernie Madoff, Black Swan, business process, Cass Sunstein, cognitive dissonance, collective bargaining, disruptive innovation, index card, information retrieval, Internet of things, Isaac Newton, iterative process, Jane Jacobs, John Markoff, Lean Startup, Lyft, minimum viable product, Mother of all demos, Nelson Mandela, Paul Graham, peer-to-peer, RFID, Richard Thaler, ride hailing / ride sharing, Schrödinger's Cat, self-driving car, semantic web, sharing economy, Silicon Valley, Silicon Valley startup, source of truth, Steve Jobs, Stewart Brand, Ted Nelson, The Death and Life of Great American Cities, the scientific method, The Wisdom of Crowds, theory of mind, uber lyft, urban planning, urban sprawl, Vannevar Bush, zero-sum game

Uber insists they are not a taxi company nor a limo service. They simply match drivers and passengers. So they aren’t subject to established regulations, licensing, or insurance requirements. Uber isn’t alone in this argument. They have competition. For instance, there’s Lyft, a peer-to-peer rideshare whose drivers don’t charge “fares” but receive “donations” from passengers who are encouraged to sit in the front seat and give the driver a fistbump. Their tagline is “your friend with a car.” Do we need any more evidence that a Lyft is not a taxi? Meanwhile, taxis aren’t standing still. They’re adopting e-hail apps that enable passengers to book regular taxis with their mobile device. In short, from lawsuits to competition, Uber has plenty of problems. This is to be expected. Disruptive innovation inevitably provokes a response.


pages: 197 words: 49,296

The Future We Choose: Surviving the Climate Crisis by Christiana Figueres, Tom Rivett-Carnac

3D printing, Airbnb, autonomous vehicles, Berlin Wall, carbon footprint, clean water, David Attenborough, decarbonisation, dematerialisation, Donald Trump, en.wikipedia.org, F. W. de Klerk, Fall of the Berlin Wall, income inequality, Intergovernmental Panel on Climate Change (IPCC), Internet of things, Jeff Bezos, job automation, Lyft, Mahatma Gandhi, Martin Wolf, mass immigration, Nelson Mandela, new economy, ride hailing / ride sharing, self-driving car, smart grid, sovereign wealth fund, the scientific method, trade route, uber lyft, urban planning, urban sprawl, Yogi Berra

Yeager, “Vintage Cars with Electric-Heart Transplants,” New York Times, January 10, 2019, https://www.nytimes.com/​2019/​01/​10/​business/​electric-conversions-classic-cars.html. 21. United Nations Department of Economic and Social Affairs, “68% of the World Population Projected to Live in Urban Areas by 2050, Says UN,” May 16, 2018, https://www.un.org/​development/​desa/​en/​news/​population/​2018-revision-of-world-urbanization-prospects.html. 22. David Dudley, “The Guy from Lyft Is Coming for Your Car,” CityLab, September 19, 2016, https://www.citylab.com/​transportation/​2016/​09/​the-guy-from-lyft-is-coming-for-your-car/​500600/. 23. Annie Rosenthal, “How 3D Printing Could Revolutionize the Future of Development,” Medium, May 1, 2018, https://medium.com/​@plus_socialgood/​how-3d-printing-could-revolutionize-the-future-of-development-54a270d6186d; Elizabeth Royte, “What Lies Ahead for 3-D Printing?” Smithsonian, May 2013, https://www.smithsonianmag.com/​science-nature/​what-lies-ahead-for-3-d-printing-37498558/. 24.


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

Governments around the world use auctions based on Vickrey’s ideas to sell licenses to use radio spectrum. Facebook, Google, and Bing use a system derived from Vickrey’s auction to allocate advertising space on their web pages. Vickrey’s insights about urban planning and congestion pricing are slowly changing the face of cities, and they play an important role in the pricing policies of ride-hailing apps like Uber and Lyft.2 However, none of these applications reflects the ambition that sparked Vickrey’s work. When Vickrey won the Nobel Prize, he reportedly hoped to use the award as a “bully pulpit” to bring George’s transformative ideas and the radical potential of mechanism design to a broader audience.3 Yet Vickrey died of a heart attack three days after learning of his prize. Even had he lived, Vickrey may have struggled to inspire the public.

Leaders, political campaigns, and political scientists have begun to explore whether using QV to elicit public opinions allows them to more accurately answer the questions so crucial to their jobs: how can we form a platform and reach compromises that will respect the strongly held views of a range of citizens? In the coming years, experiments with QV will offer a proving ground for the practical utility of QV. RATING AND SOCIAL AGGREGATION Rating and social aggregation systems fuel today’s digital economy. Reputation systems are the crucial trust mechanisms that allow “sharing economy” services like Airbnb, VRBO, Uber, and Lyft to win consumer acceptance and give providers the confidence to adopt the system.46 They play a core role in the popular search services offered by Amazon, Google, Apple’s app store, and Yelp. Yet a growing body of evidence suggests these systems are badly broken. As noted above, almost all reviews cluster toward five stars, and a few at one star, making the resulting feedback biased and what statisticians call “noisy,” that is, not very accurate.47 Other online platforms, such as Facebook, Reddit, Twitter, and Instagram, gather limited information because they only allow “likes,” and other limited forms of response, rather than allowing participants to exhibit exceptional enthusiasm, or distaste, for particular content.

Scott, 174 Ford, 185–87, 193, 240, 243, 311n30 France, 10, 12, 13, 90, 127–30, 139, 141, 182, 210 free access, 43, 211 free data, 209, 220, 224, 231–35, 239 free-rider problem, 107–8 Free: The Future of a Radical Prize (Anderson), 212 free trade, 23, 131–33, 136, 266 French Revolution, 46, 86, 90, 277 Friedman, Milton, xiii, xix Galbraith, John Kenneth, 125–26, 240 Galeano, Eduardo, 140 General Agreements on Tariffs and Trade (GATT), 138 General Theory of Employment, Money and Interest, The (Keynes), 1 George, Henry, 4; capitalism and, 36–37; inequality and, xix–xx; labor and, 137; laissez-faire and, 45, 250, 253; Progress and Poverty and, 36–37, 43, 240; Progressive movement and, 174–75; property and, 36–37, 42–46, 49, 51, 59, 66; reform and, 23; socialism and, 37, 45, 137, 250, 253; Vickrey and, xx–xxii Germany, 10, 12, 13, 45, 77, 93–94, 131, 135, 139 Gibbons, Robert, 52 Giegel, Josh, 32–33 Gilded Age, 174, 262 globalization: backlash against, 265; capital flows and, 265; common ownership self-assessed tax (COST) and, 269–70; foreign products and, 130; General Agreement on Tariffs and Trade (GATT) and, 138; growth and, 257–58; imbalance in, 264–65; immigrants and, 28, 127–30, 132, 141–53, 156–66, 256–57, 261, 266–69, 273, 308n19; inequality and, 8, 9, 134, 135, 165; internationalism and, 140, 160–67; international trade and, 14, 22, 132, 137–38, 140, 142, 265, 270; investment and, 140–41; labor and, 130, 137–40; liberalism and, 255; public goods and, 265; Quadratic Voting (QV) and, 266–69; reform and, 255; VIP program and, 265–66 Glorious Revolution, 86, 95 GM, 185–87, 193, 196, 243 Goeree, Jacob, 304n34 Google, xxi, 314n29; advertising and, 202, 211–13, 220, 234; algorithms and, 289; asset managers and, 171; Brin and, 211; data and, 28, 202, 207–13, 219–20, 224, 231–36, 241–42, 246; immigrants and, 149–51, 154, 163, 169; Page and, 211; re-CAPTCHA and, 235–36; search and, 117, 202, 213, 233, 235 Google Assistant, 219 Gray, Mary, 233–34 Great Depression, 3, 17, 46, 176 Great Recession, 181–82 Greece, 55, 83–84, 90, 131, 296n16 gridlock, 84, 88, 122–24, 261, 267 Groves, Theodore, 99–100, 102, 105 growth, economic: capitalism’s slowing of, 3; common ownership self-assessed tax (COST) and, 73, 256; entrenched privilege and, 4; entrepreneurial sectors and, 144; equal distribution of, 148; globalization and, 257–58; index funds and, 181; inequality and, 3, 5, 8–9, 11, 23–24, 123, 148, 256–57; investment and, 181; liberalism and, 3–11, 23–24, 29; monopsony and, 199, 241; productivity, 254–55; quadratic, 103–5, 123; savings and, 6; stagnation and, 257–58; technology and, 255; wage, 190, 201 guest workers, 140, 150–51, 308n32 Gulf Cooperation Council (GCC), 158–65, 265–66 gun rights, 15, 76, 81, 90, 105–9, 116, 127 H1–B program, 149, 154, 162–63 Hacker, Jacob, 191 Haiti, 127–30, 153 Hajjar, 168–71 Handmaid’s Tale, The (Atwood), 18–19 happiness: Bentham on, 95–96, 98; Quadratic Voting (QV) and, 108–10, 306n52; utilitarian principle and, 95 Harberger, Arnold, 56–59 Hardin, Garrett, 44 Hayek, Friedrich, xix, 47–48, 278, 286 health issues, 100–101, 113, 151–52, 154, 266, 290–91 Her (film), 254 Hicks, John, 68 Hitler, Adolf, 3–94 Hobbes, Thomas, 85 holdout, 33, 62, 71–72, 88, 299n28 homeowners, 17, 26, 33, 42, 56–57, 65 Horizontal Merger Guidelines, 186 House of Cards (TV series), 221 human capital, 130, 258–61, 264, 293 Hume, David, 132 Hylland, Aanund, 100 immigrants: auctioning visas and, 147–49; au pair program and, 154–55, 161; common ownership self-assessed tax (COST) and, 261, 269, 273; data as labor and, 256; DeFoe on, 132; democratizing visas and, 149–57; education and, 14, 143–44, 148; elitism and, 3, 146, 166; English language and, 151, 155, 165, 251; Europe and, 139–40; expansion of existing migration and, 142–46; family reunification programs and, 150, 152; free trade and, 131–33, 136; George on, 137; globalization and, 28, 127–30, 132, 141–53, 156–66, 256–57, 261, 266–69, 273, 308n19; guest workers and, 140, 150–51, 308n32; H1–B program and, 149, 154, 162–63; Haitian, 127–30, 153; human trafficking and, 158; illegal, 130, 139, 143, 152–53, 158, 160, 165–66, 268; Irish, 137; J-1 program and, 154, 161, 273; labor and, 28, 127–30, 132, 141–53, 156–66, 256–57, 261, 266–69, 273, 308n19; legal issues and, 130, 139, 143, 152–53, 158; living standards and, 148, 153, 257; logic of free migration and, 132–37; Marx on, 137; mercantilism and, 132; Mexico and, 139–40; Mill on, 137; New World and, 136; populism and, 14; Quadratic Voting (QV) and, 261, 266–69, 273; refugees and, 130, 140, 145; skill levels of, 143–47, 150, 159–65; Smith on, 132–33; sponsors and, 129, 149–65, 273; Stolper-Samuelson Theorem and, 142–43; Syrian, 116, 140, 145; taxes and, 143–45, 156; technology and, 256–57; transportation costs and, 141; unlimited immigration and, 142; Visas Between Individuals Program (VIP) and, 150, 153, 156–66, 261, 265–66, 269; wages and, 143, 154, 158, 161–62, 165, 308n19; World Bank studies and, 140; xenophobia and, 3, 166 Immorlica, Nicole, 306n52 impossibility theorem, 92 income distribution, 4–8, 12, 74, 133, 223 index funds, 172, 181–82, 185–91, 194–95, 302n63, 310n16 India, 15, 21, 134–35, 149, 173, 206 industrial revolution, 36, 255 inequality: Brazil and, xiv; common ownership self-assessed tax (COST) and, 256–59; crosscountry analysis of, 134–35; democracy and, 123; evolution of, 133–34; George and, xix–xx; global, 8, 9, 134, 135, 165; growth and, 3, 5, 8–9, 11, 23–24, 123, 148, 256–57; growth in, 4–8; immigrants and, 266 (see also immigrants); income distribution and, 4–8, 12, 74, 133; institutional investment and, 187; labor and, 133–35, 141, 148, 163–65, 223; legal issues and, 22; liberalism and, 2–11, 22–25; living standards and, 3, 11, 13, 133, 135, 148, 153, 254, 257; measurement of, 133; minorities and, 12, 14–15, 19, 23–27, 85–90, 93–97, 101, 106, 110, 181, 194, 273, 303n14, 304n36; ownership and, 42, 45, 75, 79, 253; Quadratic Voting (QV) and, 264; Radical Markets and, 174, 176, 199, 257; slavery and, xiv, 1, 19, 23, 37, 96, 136, 255, 260; Smith on, 22; stagnequality and, 276; US Civil Rights movement and, 24 inflation, 8–9, 11, 149 innovation: competition and, 202–3; neural networks and, 214–19; robots and, 222, 248, 251, 254, 287; supersonic trains and, 30–32; technology and, 34, 71, 172, 187, 189, 202, 258 Innovator’s Dilemma, The (Christensen), 202 Instagram, 117, 202, 207 intellectual property, 26, 38, 48, 72, 210, 212, 239 International Monetary Fund (IMF), 138, 141, 267 international trade, 14, 22, 132, 137–42, 265, 270 Internet, 27, 51, 71; data and, 210–12, 224, 232, 235, 238–39, 242, 246–48; dot-com bubble and, 211; free access and, 211; high prices of, 21; online services and, 211, 235; user fees and, 211 “In the Soviet Union, Optimization Problem Solves You” (Shalizi), 281 Israel, 71 Italy, 10, 12, 13, 21 It’s a Wonderful Life (film), 17 J-1 visa program, 154, 161, 273 Jackson, Andrew, 14 James II, King of England, 86 Japan, 10, 12, 13, 80–81, 105–8 Jefferson, Thomas, 86 Jevons, William Stanley, 41, 50, 66, 224 Jonze, Spike, 254 JP Morgan, 171, 183, 184, 191 judicial activism, 124 Jury Theorem, 90–92 Kapital, Das (Marx), 239 Kasparov, Gary, 213 Keynes, John Maynard, 1, 9, 11 Kingsley, Sara, 234 Klemperer, Paul, 52 Korea, 11, 13, 71, 251 Kuwait, 158 labor: artisan, 206, 222; auctioning visas and, 147–49; au pair program and, 154–55, 161; automation of, 222–23, 251, 254; border issues and, 28, 130, 133, 139–40, 142, 144, 161, 164–65, 242, 256, 264–66; capitalism and, 136–37, 143, 159, 165, 211, 224, 231, 239–40, 316n4; collective bargaining and, 240–41; competition and, 145, 158, 162–63, 220, 234, 236, 239, 243, 245, 256, 266; cooperatives and, 118, 126, 261, 267, 299n24; cost of, 129, 200; craftsmen and, 17, 35; data and, 209–13, 246–49; democracy and, 122, 147, 149–57; digital economy and, 208–9 (see also digital economy); education and, 140, 143–44, 148, 150, 158, 170–71, 232, 248, 258–60; efficiency and, 130, 148, 240–41, 246; Engels on, 239–40; as entertainment, 233–39, 248–49; entrepreneurs and, xiv, 35, 39, 129, 144–45, 159, 173, 177, 203, 209–12, 224, 226, 256; equality and, 147, 166, 239, 257; exploitation of, 154, 157–58, 239–40; farm, 17, 34–35, 37–38, 61, 72, 135, 142, 179, 283–85; feudalism and, 16, 34–35, 37, 41, 61, 68, 136, 230–33, 239; free trade and, 131–33, 136; General Agreement on Tariffs and Trade (GATT) and, 138; George and, 137; globalization and, 130, 137–40, 264–65 (see also globalization); guest workers and, 140, 150–51, 308n32; H1–B program and, 149, 154, 162–63; human capital and, 130, 258–60, 264; human trafficking and, 158; illegal aliens and, 160, 165–66, 268; immigrants and, 28, 127–30, 132, 141–53, 156–66, 256–57, 261, 266–69, 273, 308n19; income distribution and, 4–8, 12, 74; inequality and, 133–35, 141, 148, 163–65, 223; J-1 program and, 154, 161, 273; job displacement and, 222, 316n4; manufacturing and, 77, 122, 162, 174, 185–86, 190, 279; markets and, 255–60, 265–66, 268–69, 273–74, 280, 285; mercantilism and, 131–32; 136, 243; monopsony and, 190, 199–201, 223, 234, 238–41, 255; optimality and, 231, 243; pensions and, 157, 181; prices and, 132, 156, 207, 212, 221, 235, 243–44; productivity and, 9–10, 16, 38, 57, 73, 123, 240–41, 247, 254–55, 258, 278; programmers and, 163, 208–9, 214, 217, 219, 224; Radical Markets and, 132, 147, 158, 199–201, 243, 246–49; Red Queen phenomenon and, 176–77; reform and, 129, 153, 240, 247, 255; resale price maintenance and, 201; retirement and, 171–72, 260, 274; rise of data work and, 209–13; robots and, 222, 248, 251, 254, 287; serfs and, 35, 48, 231–32, 236, 255; skilled, 130, 144–47, 154, 159, 161–63, 180, 279; slave, xiv, 1, 19, 23, 37, 96, 136, 255, 260; socialism and, 137, 299n24; Stolper-Samuelson Theorem and, 142–43; technology and, 210–13, 219, 222–23, 236–41, 244, 251, 253–59, 265, 293, 316n4; unemployment and, 9–11, 190, 200, 209, 223, 239, 255–56; unions and, 23, 94, 118, 200, 240–45, 316n4; unpaid, 210, 233–39, 248–49; unskilled, 163, 266; visas and, 158 (see also visas); wages and, 5 (see also wages); wealth and, 130–43, 146, 148, 159–66, 209, 226, 239, 246; women’s work and, 209, 313n4; Workers International and, 45 Labor Party, 45 laissez-faire, 45, 250, 253, 277 landlords, 37, 43, 70, 136, 201–2 landowners, 31–33, 38–39, 41, 68, 105, 173 Lange, Oskar, 47, 277, 280, 282, 286–88, 298n13 Lanier, Jaron, 208, 220–24, 233, 237, 313n2, 315n48 land value taxation, 31, 42–44, 56, 61 Latin America, 10, 57, 130, 138, 140 Law of the Sea Authority, 267 Ledyard, John, 100 Lenin, Vladimir, 46 Lerner, Abba, 280 liberalism: capitalism and, 3, 17, 22–27; central planning and, 19–20; competition and, 6, 17, 20–28; conflict and, 12–16; crisis in, 1–29; democracy and, 3–4, 25, 80, 86, 90; efficiency and, 17, 24, 28; elitism and, 3, 15–16, 25–28; equality and, 4, 8, 24, 29; globalization and, 255; governance and, 3, 16; growth and, 3–11, 23–24, 29; industry and, 19, 22, 24; inequality and, 2–11, 22–25; labor and, 5–12, 21–23, 26, 28, 141, 164; markets and, 16–29; monopolies and, 6, 16, 21–23, 28; neoliberalism and, 5, 9, 11, 24, 255; ownership and, 17–19, 26–27; prices and, 7, 8, 17–22, 25–27; profits and, 6–7, 17–18; property and, 17–18, 25–28; Quadratic Voting (QV) and, 268; reform and, 2–4, 23–25, 255; regulations and, 3, 9, 18, 24; stagnation and, 8–11; taxes and, 5, 9, 23–24; values of, 1, 18; wages and, 5, 7, 10, 19; wealth and, 4–17, 22–24, 255–56 Ligett, Katrina, 306n52 Likert, Rensis, 111 Likert surveys, 111–16, 120, 306n53 LinkedIn, 202 liquidity, 31, 69, 177–79, 194, 301n49 living standards, 3, 11, 13, 133, 135, 148, 153, 254, 257–58 lobbying, 98–99, 189–90, 198, 203, 262, 312n50 Locke, John, 86 Lyft, xxi, 117 McAfee, Preston, 50 machine learning (ML), 315n48; algorithms and, 208, 214, 219, 221, 281–82, 289–93; automated video editing and, 208; consumers and, 238; core idea of, 214; data evaluation by, 238; diamond-water paradox and, 224–25; diminishing returns and, 229–30; distribution of complexity and, 228; facial recognition and, 208, 216–19; factories for thinking machines and, 213–20; humanproduced data for, 208–9; marginal value and, 224–28, 247; neural networks and, 214–19; overfitting and, 217–18; payment systems for, 224–30; productivity and, 208–9; Radical Markets for, 247; siren servers and, 220–24, 230–41, 243; technofeudalism and, 230–33; technooptimists and, 254–55, 316n2; techno-pessimists and, 254–55, 316n2; Vapnik and, 217; worker displacement and, 222 McKelvey, Richard, 94 Macron, Emmanuel, 129 Madison, James, 87 Magie, Elizabeth, 43 majority rule, 27, 83–89, 92–97, 100–101, 121, 306n51 Malkiel, Burton G., 309n14 managers, 40, 129, 157, 171–72, 178–81, 193, 209, 266, 279, 284, 311n27 manufacturing, 77, 122, 162, 174, 185–86, 190, 279 Mao Tse-tung, 46 marginal cost, 101–3, 107, 109 marginal revolution, 41, 47, 224 marginal value, 103, 224–28, 247, 304n35 Market Fundamentalists, xix, xvi–xvii markets; as antiquated computers, 286–88; auctions and, xv–xix, 49–51, 70–71, 97, 99, 147–49, 156–57; border issues and, 22–23, 25, 28, 130, 133, 139–40, 142, 144, 161, 164–65, 242, 256, 264–66; capitalism and, 278, 288, 304n36; central planning and, 277–85, 288–93; Coase on, 40, 48–51, 299n26; for collective decisions, 97–105; colonialism and, 8, 131; common ownership self-assessed tax (COST) and, 270, 286; competition and, 25–28, 109 (see also competition); computers and, 277, 280–93; concentration of, 186, 204; consumers and, 19, 47, 117, 172, 175, 186, 190–91, 197–98, 220, 238, 242–43, 247–48, 256, 262, 270, 280, 287–91; control and, 178–81, 183–85, 193, 198, 235; democracy and, 97–105, 262, 276; discontents and, 16–19; diversification and, 171–72, 180–81, 185, 191–92, 194–96, 310n22, 310n24; dot-com bubble and, 211; efficiency and, 180, 277–85; equilibrium and, 293, 305n40; expansion of, 256; exports and, 46, 132; Federal Trade Commission (FTC) and, 176, 186; feudalism and, 16, 34–35, 37, 41, 61, 68, 136, 230–33, 239; free trade and, 23, 131–33, 136, 266; General Agreement on Tariffs and Trade (GATT) and, 138; globalization and, 265 (see also globalization); Great Depression and, 3, 17, 46, 176; Great Recession and, 181–82; immigrants and, 132–37; imports and, 132; international trade and, 14, 22, 132, 138, 140, 142, 265, 270; Internet and, 211; labor and, 255–60, 265–69, 273–74, 280, 285; liberalism and, 16–29; liquidity and, 31, 69, 177–79, 194, 301n49; manufacturing and, 77, 122, 162, 174, 185–86, 190, 279; marginal value and, 103, 224–28, 247; mercantilism and, 131–32; mergers and, 176, 178, 186–90, 197, 200, 202–3; monopsony and, 190, 199–201, 223, 234, 238–41, 255; open, 21–22, 24; as parallel processors, 282–86; passivity and, 171–72, 192, 196–97, 272, 274; Philosophical Radicals and, 4, 16, 20, 22–23, 95; power and, 6–8, 21, 25–28, 186, 190, 200, 234, 241, 255–56, 261, 271, 316n3; prices and, 278–80, 284–85; property and, 282; public goods and, 271; Quadratic Voting (QV) and, 122–23, 256, 272, 286, 304n36; Red Queen phenomenon and, 176–77, 184; scope of trade and, 122–23; sea power and, 131; Smith on, 16–17, 21–22; socialism and, 277–78, 281; stock, 8, 78, 171, 179, 181, 193, 211, 275; Stolper-Samuelson Theorem and, 142–43; tariffs and, 138, 266; technology and, 203, 286–87, 292; trade barriers and, 14; tragedy of the commons and, 44; without property, 40–45 Marx, Karl, 2, 19, 39, 46, 78, 137, 239–40, 277, 297n25 Means, Gardiner, 177–78, 183, 193–94 Mechanical Turk, 230–31, 234 Menger, Karl, 41, 47, 224 mercantilism, 96, 131–32 mergers, 176, 178, 186–90, 197, 200, 202–3 Mexico, 15, 139–41, 143, 148 micropayments, 210, 212 Microsoft, 2, 202, 209, 211, 219, 231, 238–39, 315n46 Milgrom, Paul, 50, 71 Mill, James, 35, 96 Mill, John Stuart, 4, 20, 96, 137 minorities: democracy and, 85–90, 93–97, 101, 106, 110; inequality and, 12, 14–15, 19, 23–27, 85–90, 93–97, 101, 106, 110, 181, 194, 273, 303n14, 304n36; religious, 87–88; tyrannies and, 23, 25, 88, 96–100, 106, 108; voting and, 303n14 mixed constitution, 84–85 Modern Corporation and Private Property, The (Berle and Means), 177–78 Modiface, 318n10 Mohammad, 131 monarchies, 85–86, 91, 95, 160 monopolies: American Tobacco Company and, 174; antitrust policies and, 23, 48, 174–77, 180, 184–86, 191, 197–203, 242, 255, 262, 286; Aristotle on, 172; capitalism and, 22–23, 34–39, 44, 46–49, 132, 136, 173, 177, 179, 199, 258, 262; Clayton Act and, 176–77, 197, 311n25; common ownership self-assessed tax (COST) and, 256–61, 270, 300n43; competition and, 174; consumers and, 175, 186, 197–98; corporate control and, 168–204; deadweight loss and, 173; democracy and, 125; Federal Trade Commission (FTC) and, 176, 186; feudalism and, 16, 34–35, 37, 41, 61, 68, 136, 230–33, 239; Gilded Age and, 174, 262; labor and, 132, 136, 243; land monopolization and, 42–43; legal issues and, 173–77, 196–99, 262; liberalism and, 6, 16, 21–23, 28; mergers and, 176, 178, 186–90, 197, 200, 202–3; natural, 48; prices and, 58–59, 179, 258, 300n43; problem of, 6, 34, 38–42, 48–52, 57, 66, 71, 196, 199, 298n7, 298n9, 299n28; property and, 34–39; Quadratic Voting (QV) and, 272; Radical Markets and, 172–79, 185, 190, 196, 199–204, 272; Red Queen phenomenon and, 176–77; resale price maintenance and, 200–201; robber barons and, 175, 199–200; Section 7 and, 196–97, 311n25; Sherman Antitrust Act and, 174, 262; Smith on, 173; Standard Oil Company and, 174–75; United States v.


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

Webopedia. http://www.webopedia.com/TERM/P/public_key_cryptography.html. 3 Hof, R. “Seven Months After FDA Slapdown, 23andMe Returns with New Health Report Submission.” Forbes, June 20, 2014. http://www.forbes.com/sites/roberthof/2014/06/20/seven-months-after-fda-slapdown-23andme-returns-with-new-health-report-submission/. 4 Knight, H. and B. Evangelista. “S.F., L.A. Threaten Uber, Lyft, Sidecar with Legal Action.” SFGATE, September 25, 2041. http://m.sfgate.com/bayarea/article/S-F-L-A-threaten-Uber-Lyft-Sidecar-with-5781328.php. 5 Although it is not strictly impossible for two files to have the same hash, the number of 64-character hashes is vastly greater than the number of files that humanity can foreseeably create. This is similar to the cryptographic standard that even though a scheme could be cracked, the calculation would take longer than the history of the universe. 6 Nakamoto, S.


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

Uber flooded the streets in cities worldwide with cars, which was terrific for riders—but less so for drivers, many of whom began to find it harder and harder to piece together a steady living, given the frenetic competition on the streets. (In New York City alone, in 2018 there were only 13,578 traditional taxis, but the number of ride-hail drives had exploded to 80,000.) Certainly, drivers who were only doing it for spare money were thrilled to have a way to quickly pick up some extra pocket money; Uber and Lyft made it possible to do driving as piecework. But it was bad news for anyone looking to drive as a reliably steady gig, a job that historically has been one of the easier-to-acquire forms of work for immigrants in big cities. “What Uber and Lyft have done is come into the industry and wreck it,” as the Nigerian cabdriver Nnamdi Uwazie told NBC. By 2017, several cabdrivers had committed suicide and blamed the ride-hail firms for destabilizing their work so massively that it wasn’t possible to rely on driving for a predictable income.

Assuming a student performs well and it’s a well-connected university, high-profile employers fight over hiring top computer science graduates. Indeed, those universities are so well connected to internships at major firms that many grads have offers in hand before they’re finished with their coursework. When I hung out with two students who’d graduated the year before from Columbia University’s computer science program, one had been scouted by Facebook, Microsoft, and a database firm in New York, and the other had juggled offers from Lyft and Twitter. “This is what it’s like for basically everyone who came out of our program,” they told me. And founders of high-tech start-ups tend to hire the friends they met at college; get into the right class and it’s a ticket to a well-financed tech job. The upshot is a growing stampede of students eager to study computer science. The number of US university undergraduates declaring it as their major doubled from 2011 to 2015—a mere four years.

See minority coders law/lawyers, ref1 Lazowska, Ed, ref1 LBGT tech employees, ref1 LDX, ref1 LeapChat.org, ref1 LeCun, Yann, ref1 Lee, Cynthia, ref1, ref2 Lee, Jennifer 8, ref1 Lee, Kai-Fu, ref1, ref2 Legend of Zelda, The (game), ref1 Leibniz, Gottfried, ref1 Leopold, Jason, ref1 Leslie, Sarah Jane, ref1 Levchin, Max, ref1, ref2 Levy, Josh, ref1 Levy, Steven, ref1, ref2, ref3 Lewis, Clayton, ref1 Li, Fei-Fei, ref1 libertarianism, in coding community, ref1, ref2, ref3 Lichterman, Ruth, ref1 Like button (Facebook), ref1 LINC, ref1 Linux, ref1, ref2 LiveJournal, ref1 Loewenstern, Andrew, ref1 Logic, ref1 lone genius working feverishly stereotype. See 10X coders Lopp, Michael, ref1 Losse, Kate, ref1 Lotus Notes, ref1 Lovelace, Ada, ref1 Lucy Parsons Lab, ref1 Lund, Kátia, ref1 Lyft, ref1 McCarthy, John, ref1 McClure, Dave, ref1 McFarlane, Jill, ref1 McKellar, Jessica, ref1 McNulty, Kathleen, ref1 Madison, James, ref1 Magic Leap, ref1 Malhotra, Neil, ref1 malware, ref1 Manning, Chelsea, ref1 MapReduce, ref1 Margolis, Jane, ref1, ref2 Marlinspike, Moxie, ref1 Martínez, Antonio Garcia, ref1 Martiros, Hayk, ref1 Mason, Hilary, ref1, ref2, ref3 Masters of Deception, ref1 Matrix, The (film), ref1, ref2, ref3 May, Tim, ref1, ref2 Meebo, ref1 Meituan, ref1 #metoo, ref1 mental health issues, ref1 meritocracy myth, ref1, ref2 “brilliant jerk” downside of worship of coder merit, ref1 code as arbiter of what is great, ref1, ref2 as coping mechanism for high school/corporate life social orders, ref1 fortune, role of, ref1 great ideas, value of, ref1 Levchin/PayPal and, ref1 open source software and, ref1, ref2 PayPal and, ref1, ref2 political views of coders and (See politics, of coders) provenance of, ref1 self-taught individuals, acceptance of, ref1, ref2 side effects of belief in, ref1 10x coders and, ref1, ref2, ref3 women and minorities, lack of, ref1 Zuckerberg on, ref1 Metasploit, ref1 Microsoft, ref1, ref2, ref3 microtargeting, ref1 Miller, Robyn, ref1 Minecraft, ref1 minority coders bifurcation in pay and prestige of coding jobs available to, ref1 computer science degree drop-out rates, in 1980s onward, ref1 hostile work environment encountered by, ref1, ref2 lack of, ref1, ref2 LBGT employees, harassment faced by, ref1 mistaken for security or housekeeping personnel, ref1 percentage in workplace, 2017, ref1 Mirai botnet, ref1 MIT AI lab hackers, in 1960s and early 1970s, ref1 privacy versus secrecy clashes at, in 1960s and 1970s, ref1 Wilkes’ early work at Lincoln Labs, ref1 “Mixing Math and Motherhood” (Businessweek), ref1 moderators, ref1 Molnar, Charles, ref1 Moses, Robert, ref1 Moskovitz, Dustin, ref1 Mozilla, ref1 Mr.


Designing Web APIs: Building APIs That Developers Love by Brenda Jin, Saurabh Sahni, Amir Shevat

active measures, Amazon Web Services, augmented reality, blockchain, business process, continuous integration, create, read, update, delete, Google Hangouts, if you build it, they will come, Lyft, MITM: man-in-the-middle, premature optimization, pull request, Silicon Valley, Snapchat, software as a service, the market place, uber lyft, web application, WebSocket

Most com‐ panies offer multiple developer programs through their developer relations and marketing teams. To define the developer programs that you need to run, you need to perform a breadth and depth analysis. Breadth and Depth Analysis Most developer ecosystems are composed of a few big players and a lot of midsize and small players, as illustrated in Figure 10-1. Con‐ sider the following about the mobile ecosystem: you have a few big mobile app developers—Uber, Lyft, Facebook, Supercell, and so forth—as well as many, many other app developers working in smaller companies building mobile apps. 185 Figure 10-1. Developer tiers Developers (and hence developer programs) can be categorized along two axes, as shown in Figure 10-2: Depth axis The deep developer audience refers to the top partners or top clients that will use your API. You will need to spend more time with these top partners and clients to get them to use it.

Hackathons are also expensive in terms of time and resources, so if you do not invite the right people, track signups, and gather product insights, your management might see this effort as a waste of time and money. Hackathons can be very big, with a lot of API companies working together to help developers innovate. Slack has sponsored a hacka‐ thon with 2,000 developers, together with companies such as Lyft, Stripe, Google, Amazon, and Microsoft. Each company provided training materials, engineers to support the hackers, and prizes for the best projects. Hackathons contribute to developer awareness and proficiency, they connect the API product team and developers at large, and they help collect product feedback and build empathy for developer problems. Speaking at Events and Event Sponsorships A lot of companies hire full-time advocates to speak at events around the world.


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

Millennials will be the first modern generation to work in multiple “micro-careers” at the same time, leaving the traditional full-time job or working week behind. “Work” is more likely to behave like a marketplace in the cloud than behind a desk at a traditional corporation. While a central skill set or career anchor will be entirely probable, most will be entrepreneurs, and many will have their side gigs. For instance, Uber, Lyft and Sidecar are platforms that give people a way to leverage their cars and time to make money. TaskRabbit is a market for odd jobs. Airbnb lets you rent out any extra rooms in your home. Etsy is a market for the handmade knick-knacks or 3D print designs that you make at home. DesignCrowd, 99designs and CrowdSPRING all offer freelance design resources that bid logos and other designs for your dollars.

Many thousands of different jobs, entrepreneurial start-ups or self-employment opportunities, with hundreds of different options of profession. A citizen can choose from dozens of jobs, and change careers or professions. 8. The ability to walk, bike, taxi or take public transportation to work or play, without having to own a vehicle or needing to have a driver’s licence. People in most cities are now able to call an Uber or Lyft via a smartphone. 9. The ability for quick access to an airport that enables travel to anywhere on earth within a day, and to many destinations within a few hours. 10. The ability to take advantage of the economies of scale that a city offers, to reduce the total costs of energy, transportation, fresh food, equipment and services, with options such as buying in bulk, taking advantage of competition in the same market and making use of shared-economy apps that allow joint ownership or shared use. 11.

Stores will become inefficient distribution models for a vast swathe of products, especially where advice is currently part of the experience. By 2030 to 2035, we’ll regularly download products for printing at home, inclusive of electrical circuits, displays and other tech. Our kids won’t own the stuff we own today as revised notions of ownership come to reshape asset management. Airbnb, SocialFlight, Lyft, Sailo and others are only the first wave of shared asset systems. In the future, you’ll be able to take a different car to work every day (autonomous, self-driving vehicles) at a much cheaper rate than you could ever do owning a car of your own, live month by month or week by week in a different room and work in a different workspace every day. Because these experiences are personalised, it will still feel like our own personal style is shining through.


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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

But they seemed not to appreciate that their lifestyle might disturb the quiet equilibrium that had preceded their arrival. With a range of new services catering to their needs, delivered by startups of their peers, the hipsters and bros eventually provoked a reaction. Tangible manifestations of their presence, like the luxury buses that took them to jobs at Google, Facebook, Apple, and other companies down in Silicon Valley, drew protests from peeved locals. An explosion of Uber and Lyft vehicles jammed the city’s streets, dramatically increasing commute times. Insensitive blog posts, inappropriate business behavior, and higher housing costs ensured that locals would neither forgive nor forget. * * * — ZUCK ENJOYED THE KIND OF privileged childhood one would expect for a white male whose parents were medical professionals living in a beautiful suburb. As a student at Harvard, he had the idea for Facebook.

I would like to think that Silicon Valley can earn a living without killing millions of jobs in other industries. In the mid-seventies and eighties, when the US first restructured its economy around information technology, tech enabled companies to eliminate layers of middle management, but the affected people were rapidly absorbed in more attractive sectors of the economy. That is no longer the case. The economy is creating part-time jobs with no benefits and no security—driving for Uber or Lyft, for example—but not creating jobs that support a middle-class lifestyle, in part because that has not been a priority. One opportunity for the government is to create tax incentives for tech businesses (and others) to retrain and create jobs for workers threatened by recent changes in the economy. Teaching everyone to code is not the answer, as coding will likely be an early target for automation through artificial intelligence.

., 18 Khan, Lina, 136 Khanna, Ro, 226–27 Kleiner Perkins Caufield & Byers, 26, 27 Klobuchar, Amy, 128, 207, 222 Koebler, Jason, 229–30 Kogan, Aleksandr, 181–87, 189, 190, 197 Kranzberg, Melvin, ix Labor, U.S. Department of, 200 Lange, Christian Lous, 1 Lanier, Jaron, 69, 129, 135 Lee, Yanghee, 179 Levchin, Max, 48 libertarianism, 43–45, 49, 102, 123 Licklider, J. C. R., 33 LinkedIn, 38, 48, 98, 104, 110, 173 local area networks (LANs), 35 Lofgren, Zoe, 221–27 Lotus Development, 27 Luján, Ben, 211 Lustig, Robert, 167 Lyft, 50, 263 Lynn, Barry, 155, 285–86 Macedonia, 125 magic, 82–83, 101 Maher, Katherine, 178 Makeoutclub, 55 March for Our Lives, 243, 250, 275 Marinelli, Louis, 114 Markey, Edward, 167 Match.com, 218 Mayfield Fund, 147 McCain, John, 207 McGinn, Tavis, 167–69, 172, 174 McGovern, George, 20 McKean, Erin, 230–31 McNamee, Ann, 5–6, 23, 159 McNamee, George, 22 McNamee, Roger, 18–30 as advisor to Zuckerberg, 1, 5, 13–16, 57–60, 64, 78 childhood of, 18–19 Elevation Partners firm of, 13–14, 17–18, 30, 61, 72, 147 email to Zuckerberg and Sandberg, 4–6, 149, 152, 160–61, 280, 297–300 heart surgery of, 29 at Integral Capital Partners, 27–28, 61 as investor in Facebook, 1, 17–18, 59 as investor in technology, 1, 7, 21, 24–30, 56–57 music career of, 8, 19, 22, 23, 25 op-ed for Recode, 5–7, 297–300 op-ed for USA Today, 118 parents of, 18–21 and Sandberg’s joining of Facebook, 5, 16, 60, 61 at Silver Lake Partners, 28–30 strokes suffered by, 29 at T.


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The Gig Economy: The Complete Guide to Getting Better Work, Taking More Time Off, and Financing the Life You Want by Diane Mulcahy

Affordable Care Act / Obamacare, Airbnb, Amazon Mechanical Turk, basic income, Clayton Christensen, cognitive bias, collective bargaining, creative destruction, David Brooks, deliberate practice, diversification, diversified portfolio, fear of failure, financial independence, future of work, gig economy, helicopter parent, Home mortgage interest deduction, housing crisis, job satisfaction, Kickstarter, loss aversion, low skilled workers, Lyft, mass immigration, mental accounting, minimum wage unemployment, mortgage tax deduction, negative equity, passive income, Paul Graham, remote working, risk tolerance, Robert Shiller, Robert Shiller, Silicon Valley, Snapchat, TaskRabbit, Uber and Lyft, uber lyft, universal basic income, wage slave, Y Combinator, Zipcar

He calls his proposal “libertarianism with a safety net.”15 Allow Contractors to Collectively Bargain The National Labor Relations Act applies only to employees, thus excluding independent contractors from the ability to bargain collectively. In the past, contractor attempts to unionize and bargain have been thwarted by invoking antitrust laws. The argument is that contractors who collectively bargain to set common rates are essentially colluding, which violates antitrust laws. However, in December 2015, the Seattle City Council voted to extend collective bargaining rights to Uber and Lyft drivers.16 In March, the U.S. Chamber of Commerce sued the city of Seattle, saying that the ordinance violates antitrust laws.17 California is expected to introduce a similar bill covering independent contractors who work on on-demand platforms. What most of these proposals have in common is that they attempt to improve the current labor market by eliminating an employer’s ability to arbitrage between employees and contractors, and support worker choices about how to work.

Harford, Tim, “An Economist’s Dreams of a Fairer Gig Economy,” Tim Harfor, December 29, 2015. next.ft.com/content/1280a92e-a405-11e5-873f-68411a84f346Web 16. Beekman, Daniel, “The Seattle City Council Voted 8-0 Monday Afternoon to Enact Councilmember Mike O’Brien’s Ordinance, Giving Taxi, For-Hire and Uber Drivers the Ability to Unionize,” December 16, 2015. www.seattletimes.com/seattle-news/politics/unions-for-taxi-uber-drivers-seattle-council-votes-today/ 17. Somerville, Heather, and Dan Levine, “US Chamber of Commerce Sues Seattle over Uber, Lyft Ordinance,” Reuters, March 3, 2016. www.reuters.com/article/us-uber-tech-seattle-chamberofcommerce-idUSKCN0W52SD 18. Gallup, “What Everyone in the World Wants: A Good Job,” June 9, 2015 www.gallup.com/businessjournal/183527/everyone-world-wants-good-job.aspx 19. Ton, Zeynep, “Why ‘Good Jobs’ are Good for Retailers,” Harvard Business Review, January-February 2012. issue. hbr.org/2012/01/why-good-jobs-are-good-for-retailers 20.


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Human + Machine: Reimagining Work in the Age of AI by Paul R. Daugherty, H. James Wilson

3D printing, AI winter, algorithmic trading, Amazon Mechanical Turk, augmented reality, autonomous vehicles, blockchain, business process, call centre, carbon footprint, cloud computing, computer vision, correlation does not imply causation, crowdsourcing, digital twin, disintermediation, Douglas Hofstadter, en.wikipedia.org, Erik Brynjolfsson, friendly AI, future of work, industrial robot, Internet of things, inventory management, iterative process, Jeff Bezos, job automation, job satisfaction, knowledge worker, Lyft, natural language processing, personalized medicine, precision agriculture, Ray Kurzweil, recommendation engine, RFID, ride hailing / ride sharing, risk tolerance, Rodney Brooks, Second Machine Age, self-driving car, sensor fusion, sentiment analysis, Shoshana Zuboff, Silicon Valley, software as a service, speech recognition, telepresence, telepresence robot, text mining, the scientific method, uber lyft

These same technologists (76 percent) suggest that the top solution is to use some sort of visual output that provides analytics and a dashboard with other metrics.12 It’s a simple solution that can reduce opacity in the system—and keep humans firmly in the loop. Here, the role of the explainer is key. Even if the entire mind of an AI system can’t be known, some insights into its inner workings can be very beneficial. Explainers should understand both what’s useful for people to see in a visualization and what’s important for the system to share. Minimize “Moral Crumple Zones” For services like Uber, Lyft, and Amazon’s Mechanical Turk, AI-based software is augmenting some management roles: it doles out tasks, gives feedback and ratings, and helps people track progress toward goals. AI-enhanced management is a necessary innovation if these companies’ business models are to scale and employ hundreds of thousands of people worldwide. But while management can offload certain activities, it can’t offload underlying responsibility for how they are administered.

., 76 Laws of Robotics, 128–129 leadership, 14–15, 153–181, 213 blended culture and, 166–174 data supply chains and, 174–179 in enterprise processes, 58–59 in manufacturing, 38 in marketing and sales, 100 in normalizing AI, 190–191 in R&D, 83 in reimagining processes, 154, 180–181 learning deep reinforcement, 21–22 distributed, 22 reinforcement, 62 in robotic arms, 24–26 semi-supervised, 62 sensors and, 24–26 supervised, 60 unsupervised, 61–62 See also machine-learning technologies Leefeldt, Ed, 99 Lee Hecht Harrison, 199 legal issues. See ethical, moral, legal issues Lenovo, 76 LinkedIn, 51, 198 Local Interpretable Model-Agnostic Explanations (LIME), 125 local search capabilities, 63 logistics, 31 L’Oreal, 31 Lowebot, 91 Lowe’s, 91 Lyft, 169 machine-learning technologies in agriculture, 35–37 in complaint processes, 47–48 definition of, 60 ethics and, 130–131 glossary on, 60–63 history of, 24, 41–44 job creation and, 11 in marketing and sales, 10–11 in onboarding machines, 27 in robotic arms, 21–23 supply chains and, 34 machine relations managers, 11, 131–132 machine time, 187 machine-vision algorithms, 32–33 maintenance, 183–184 AI-enabled, 26–27, 29 augmentation in, 143 at GE, 27, 29 management, 12, 152 administration responsibility and, 169–172 ethics compliance, 79, 129–130 in normalizing AI, 190–191 of process reimagining, 108–109 mannequins, 89, 90, 100 manufacturing job creation in, 20 jobs lost in, 19 trainers in, 116–117 unfilled jobs in, 210 marketing and sales, 10–11, 85–101 brands and, 87, 92–97 data analytics in, 98 empowering salespeople in, 90, 92 personalization in, 86, 89–90, 91, 96–97 staffing and, 88–89 Mars Exploration Rovers, 200–201 Masnick, Mike, 49 Matternet, 151 Matthews, Kayla, 198 Mayhem, 57 Mayo Clinic, 188 McCarthy, John, 40, 41 Mechanical Turk, 169 MELDS (mindset, experimentation, leadership, data, skills) principles, 12–16.


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A Generation of Sociopaths: How the Baby Boomers Betrayed America by Bruce Cannon Gibney

1960s counterculture, 2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, affirmative action, Affordable Care Act / Obamacare, American Society of Civil Engineers: Report Card, Bernie Madoff, Bernie Sanders, Bretton Woods, business cycle, buy and hold, carbon footprint, Charles Lindbergh, cognitive dissonance, collapse of Lehman Brothers, collateralized debt obligation, corporate personhood, Corrections Corporation of America, currency manipulation / currency intervention, Daniel Kahneman / Amos Tversky, dark matter, Deng Xiaoping, Donald Trump, Downton Abbey, Edward Snowden, Elon Musk, ending welfare as we know it, equal pay for equal work, failed state, financial deregulation, Francis Fukuyama: the end of history, future of work, gender pay gap, gig economy, Haight Ashbury, Home mortgage interest deduction, Hyperloop, illegal immigration, impulse control, income inequality, Intergovernmental Panel on Climate Change (IPCC), invisible hand, Jane Jacobs, Kitchen Debate, labor-force participation, Long Term Capital Management, Lyft, Mark Zuckerberg, market bubble, mass immigration, mass incarceration, McMansion, medical bankruptcy, Menlo Park, Mont Pelerin Society, moral hazard, mortgage debt, mortgage tax deduction, neoliberal agenda, Network effects, obamacare, offshore financial centre, oil shock, operation paperclip, plutocrats, Plutocrats, Ponzi scheme, price stability, quantitative easing, Ralph Waldo Emerson, RAND corporation, rent control, ride hailing / ride sharing, risk tolerance, Robert Shiller, Robert Shiller, Ronald Reagan, Rubik’s Cube, school choice, secular stagnation, self-driving car, shareholder value, short selling, side project, Silicon Valley, smart grid, Snapchat, source of truth, stem cell, Steve Jobs, Stewart Brand, survivorship bias, TaskRabbit, The Wealth of Nations by Adam Smith, Tim Cook: Apple, too big to fail, War on Poverty, white picket fence, Whole Earth Catalog, women in the workforce, Y2K, Yom Kippur War, zero-sum game

Still, years of economic mediocrity notwithstanding, there always seemed to be a few good things to invest in, if you were in the right place at the right time. For me, in 1998, that thing was PayPal (my college roommate cofounded the company, and I bought some early shares); in 2004, it was Facebook (my then boss made the first outside investment in the social network, and I worked as a junior associate on part of that deal). Later, I made personal investments in SpaceX, Lyft, Palantir, and DeepMind, which are not all household names, though they have succeeded well enough. But these companies were exceptions, very rare ones. I mention them less to establish my credibility as a prognosticator than to show the value of socially funded innovation (every company I mentioned was built on technologies pioneered by government grants or research) and, most important, to show the overwhelming importance of luck in a stagnating economy.

The gig economy and other “alternative work arrangements” accounted for quite a lot of recent job growth, probably at least a third of all jobs created, and per preliminary findings by Harvard’s Lawrence Katz and Princeton’s Alan Krueger, perhaps “all of the net employment growth in the U.S. economy from 2005–2015 appears to have occurred in alternative work arrangements” (emphasis original; in a recent update, the authors revised “all” to a no-less-unsettling “94 percent”).17 And this returns us to Downton Abbey—before World War I, huge numbers of English were employed “in service,” thanks to social inertia, inequality, and technological change. With gigs, this is happening again, only now the chauffeur comes in the livery of Lyft’s pink moustache, not Downton’s white tails. And this time, there will be no intermarriage between passenger and driver à la Lady Sybil and Tom, especially in the coming decades when the driver becomes a robot. The Dowager Countess of Grantham has become Lady Brenda of the Colonies, residing in Sun City, Arizona, couriered from aquarobics to gerontologist by rideshare and nursed by a contractor workforce, often composed of the immigrants her ex-governor Jan Brewer so detested.18 At least, however, there’s still staff; indeed, Lady Brenda can expect more, albeit younger, browner, poorer, and occasionally inanimate.

* Technically, the title of first Boomer PM was held by Kim Campbell, but she lasted less than 5 months. Harper lasted nine years. * For most purposes, people in prisons don’t count toward the unemployment rate, though they are basically unemployed, and were US incarceration rates at developed world norms, unemployment would be about half a point higher. * Another disclosure: I have invested in several gig companies, like TaskRabbit and Lyft, because a few years ago I began to suspect that gigs were the future of work. * One of which apparently went to the most recent Madame Trump, a skilled… model. A special class of H-1B visas exists for just these exceptional people. * Judge (sic) Kimba Wood’s nanny appears to have been properly hired under prior applicable laws; her sin was failing to respond forthrightly to the White House’s specific questions about nannies


Super Thinking: The Big Book of Mental Models by Gabriel Weinberg, Lauren McCann

affirmative action, Affordable Care Act / Obamacare, Airbnb, Albert Einstein, anti-pattern, Anton Chekhov, autonomous vehicles, bank run, barriers to entry, Bayesian statistics, Bernie Madoff, Bernie Sanders, Black Swan, Broken windows theory, business process, butterfly effect, Cal Newport, Clayton Christensen, cognitive dissonance, commoditize, correlation does not imply causation, crowdsourcing, Daniel Kahneman / Amos Tversky, David Attenborough, delayed gratification, deliberate practice, discounted cash flows, disruptive innovation, Donald Trump, Douglas Hofstadter, Edward Lorenz: Chaos theory, Edward Snowden, effective altruism, Elon Musk, en.wikipedia.org, experimental subject, fear of failure, feminist movement, Filter Bubble, framing effect, friendly fire, fundamental attribution error, Gödel, Escher, Bach, hindsight bias, housing crisis, Ignaz Semmelweis: hand washing, illegal immigration, income inequality, information asymmetry, Isaac Newton, Jeff Bezos, John Nash: game theory, lateral thinking, loss aversion, Louis Pasteur, Lyft, mail merge, Mark Zuckerberg, meta analysis, meta-analysis, Metcalfe’s law, Milgram experiment, minimum viable product, moral hazard, mutually assured destruction, Nash equilibrium, Network effects, nuclear winter, offshore financial centre, p-value, Parkinson's law, Paul Graham, peak oil, Peter Thiel, phenotype, Pierre-Simon Laplace, placebo effect, Potemkin village, prediction markets, premature optimization, price anchoring, principal–agent problem, publication bias, recommendation engine, remote working, replication crisis, Richard Feynman, Richard Feynman: Challenger O-ring, Richard Thaler, ride hailing / ride sharing, Robert Metcalfe, Ronald Coase, Ronald Reagan, school choice, Schrödinger's Cat, selection bias, Shai Danziger, side project, Silicon Valley, Silicon Valley startup, speech recognition, statistical model, Steve Jobs, Steve Wozniak, Steven Pinker, survivorship bias, The Present Situation in Quantum Mechanics, the scientific method, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, transaction costs, uber lyft, ultimatum game, uranium enrichment, urban planning, Vilfredo Pareto, wikimedia commons

For example, suppose you are thinking about a company that involves people renting out their expensive power tools, which usually sit dormant in their garages. If you realize that the concept of critical mass applies to this business, then you know that there is some threshold that needs to be reached before it could be viable. In this case, you need enough tools available for rent in a community to satisfy initial customer demand, much as you need enough Lyft drivers in a city for people to begin relying on the service. That is super thinking, because once you have determined that this business model can be partially explained through the lens of critical mass, you can start to reason about it at a higher level, asking and answering questions like these: What density of tools is needed to reach the critical mass point in a given area? How far away can two tools be to count toward the same critical mass point in that area?

Consider the Silicon Valley startups that have harnessed the spare capacity that is all around us but often ignored. Before Airbnb, travelers had little choice but to pay high prices for a hotel room, and property owners couldn’t easily and reliably rent out their unoccupied space. Airbnb saw untapped supply and unaddressed demand where others saw nothing at all. The same is true of private car services Lyft and Uber. Few people imagined that it was possible to build a billion-dollar business by simply connecting people who want to go places with people willing to drive them there. We already had state-licensed taxicabs and private limousines; only by believing in and looking for secrets could you see beyond the convention to an opportunity hidden in plain sight. A secret can be an idea that no one else has thought of, but it can also be an idea about how to achieve something that everyone else currently thinks is too risky.

., 91 Kodak, 302–3, 308–10, 312 Koenigswald, Gustav Heinrich Ralph von, 50 Kohl’s, 15 Kopelman, Josh, 301 Korea, 229, 231, 235, 238 Kristof, Nicholas, 254 Krokodil, 49 Kruger, Justin, 269 Kuhn, Thomas, 24 Kutcher, Ashton, 121 labor market, 283–84 laggards, 116–17 landlords, 178, 179, 182, 188 Laplace, Pierre-Simon, 132 large numbers, law of, 143–44 Latané, Bibb, 259 late majority, 116–17 lateral thinking, 201 law of diminishing returns, 81–83 law of diminishing utility, 81–82 law of inertia, 102–3, 105–8, 110, 112, 113, 119, 120, 129, 290, 296 law of large numbers, 143–44 law of small numbers, 143, 144 Lawson, Jerry, 289 lawsuits, 231 leadership, 248, 255, 260, 265, 271, 275, 276, 278–80 learned helplessness, 22–23 learning, 262, 269, 295 from past events, 271–72 learning curve, 269 Le Chatelier, Henri-Louis, 193 Le Chatelier’s principle, 193–94 left to their own devices, 275 Leibniz, Gottfried, 291 lemons into lemonade, 121 Lernaean Hydra, 51 Levav, Jonathan, 63 lever, 78 leverage, 78–80, 83, 115 high-leverage activities, 79–81, 83, 107, 113 leveraged buyout, 79 leveraging up, 78–79 Levitt, Steven, 44–45 Levitt, Theodore, 296 Lewis, Michael, 289 Lichtenstein, Sarah, 17 lightning, 145 liking, 216–17, 220 Lincoln, Abraham, 97 Lindy effect, 105, 106, 112 line in the sand, 238 LinkedIn, 7 littering, 41, 42 Lloyd, William, 37 loans, 180, 182–83 lobbyists, 216, 306 local optimum, 195–96 lock-in, 305 lock in your gains, 90 long-term negative scenarios, 60 loose versus tight, in organizational culture, 274 Lorenz, Edward, 121 loss, 91 loss aversion, 90–91 loss leader strategy, 236–37 lost at sea, 68 lottery, 85–86, 126, 145 low-context communication, 273–74 low-hanging fruit, 81 loyalists versus mercenaries, 276–77 luck, 128 making your own, 122 luck surface area, 122, 124, 128 Luft, Joseph, 196 LuLaRoe, 217 lung cancer, 133–34, 173 Lyautey, Hubert, 276 Lyft, ix, 288 Madoff, Bernie, 232 magnetic resonance imaging (MRI), 291 magnets, 194 maker’s schedule versus manager’s schedule, 277–78 Making of Economic Society, The (Heilbroner), 49 mammograms, 160–61 management debt, 56 manager’s schedule versus maker’s schedule, 277–78 managing to the person, 255 Manhattan Project, 195 Man in the High Castle, The (Dick), 201 manipulative insincerity, 264 man-month, 279 Mansfield, Peter, 291 manufacturer’s suggested retail price (MSRP), 15 margin of error, 154 markets, 42–43, 46–47, 106 failure in, 47–49 labor, 283–84 market norms versus social norms, 222–24 market power, 283–85, 312 product/market fit, 292–96, 302 secondary, 281–82 winner-take-most, 308 marriage: divorce, 231, 305 same-sex, 117, 118 Maslow, Abraham, 177, 270–71 Maslow’s hammer, xi, 177, 255, 297, 317 Maslow’s hierarchy of needs, 270–71 mathematics, ix–x, 3, 4, 132, 178 Singapore math, 23–24 matrices, 2 × 2, 125–26 consensus-contrarian, 285–86, 290 consequence-conviction, 265–66 Eisenhower Decision Matrix, 72–74, 89, 124, 125 of knowns and unknowns, 197–98 payoff, 212–15, 238 radical candor, 263–64 scatter plot on top of, 126 McCain, John, 241 mean, 146, 149, 151 regression to, 146, 286 standard deviation from, 149, 150–51, 154 variance from, 149 measles, 39, 40 measurable target, 49–50 median, 147 Medicare, 54–55 meetings, 113 weekly one-on-one, 262–63 Megginson, Leon, 101 mental models, vii–xii, 2, 3, 31, 35, 65, 131, 289, 315–17 mentorship, 23, 260, 262, 264, 265 mercenaries versus loyalists, 276–77 Merck, 283 merry-go-round, 108 meta-analysis, 172–73 Metcalfe, Robert, 118 Metcalfe’s law, 118 #MeToo movement, 113 metrics, 137 proxy, 139 Michaels, 15 Microsoft, 241 mid-mortems, 92 Miklaszewski, Jim, 196 Milgram, Stanley, 219, 220 military, 141, 229, 279, 294, 300 milkshakes, 297 Miller, Reggie, 246 Mills, Alan, 58 Mindset: The New Psychology of Success (Dweck), 266 mindset, fixed, 266–67, 272 mindset, growth, 266–67 minimum viable product (MVP), 7–8, 81, 294 mirroring, 217 mission, 276 mission statement, 68 MIT, 53, 85 moats, 302–5, 307–8, 310, 312 mode, 147 Moltke, Helmuth von, 7 momentum, 107–10, 119, 129 Monday morning quarterbacking, 271 Moneyball (Lewis), 289 monopolies, 283, 285 Monte Carlo fallacy, 144 Monte Carlo simulation, 195 Moore, Geoffrey, 311 moral hazard, 43–45, 47 most respectful interpretation (MRI), 19–20 moths, 99–101 Mountain Dew, 35 moving target, 136 multiple discovery, 291–92 multiplication, ix, xi multitasking, 70–72, 74, 76, 110 Munger, Charlie, viii, x–xi, 30, 286, 318 Murphy, Edward, 65 Murphy’s law, 64–65, 132 Musk, Elon, 5, 302 mutually assured destruction (MAD), 231 MVP (minimum viable product), 7–8, 81, 294 Mylan, 283 mythical man-month, 279 name-calling, 226 NASA, 4, 32, 33 Nash, John, 213 Nash equilibrium, 213–14, 226, 235 National Football League (NFL), 225–26 National Institutes of Health, 36 National Security Agency, 52 natural selection, 99–100, 102, 291, 295 nature versus nurture, 249–50 negative compounding, 85 negative externalities, 41–43, 47 negative returns, 82–83, 93 negotiations, 127–28 net benefit, 181–82, 184 Netflix, 69, 95, 203 net present value (NPV), 86, 181 network effects, 117–20, 308 neuroticism, 250 New Orleans, La., 41 Newport, Cal, 72 news headlines, 12–13, 221 newspapers, 106 Newsweek, 290 Newton, Isaac, 102, 291 New York Times, 27, 220, 254 Nielsen Holdings, 217 ninety-ninety rule, 89 Nintendo, 296 Nobel Prize, 32, 42, 220, 291, 306 nocebo effect, 137 nodes, 118, 119 No Fly List, 53–54 noise and signal, 311 nonresponse bias, 140, 142, 143 normal distribution (bell curve), 150–52, 153, 163–66, 191 North Korea, 229, 231, 238 north star, 68–70, 275 nothing in excess, 60 not ready for prime time, 242 “now what” questions, 291 NPR, 239 nuclear chain reaction, viii, 114, 120 nuclear industry, 305–6 nuclear option, 238 Nuclear Regulatory Commission (NRC), 305–6 nuclear weapons, 114, 118, 195, 209, 230–31, 233, 238 nudging, 13–14 null hypothesis, 163, 164 numbers, 130, 146 large, law of, 143–44 small, law of, 143, 144 see also data; statistics nurses, 284 Oakland Athletics, 289 Obama, Barack, 64, 241 objective versus subjective, in organizational culture, 274 obnoxious aggression, 264 observe, orient, decide, act (OODA), 294–95 observer effect, 52, 54 observer-expectancy bias, 136, 139 Ockham’s razor, 8–10 Odum, William E., 38 oil, 105–6 Olympics, 209, 246–48, 285 O’Neal, Shaquille, 246 one-hundred-year floods, 192 Onion, 211–12 On the Origin of Species by Means of Natural Selection (Darwin), 100 OODA loop, 294–95 openness to experience, 250 Operation Ceasefire, 232 opinion, diversity of, 205, 206 opioids, 36 opportunity cost, 76–77, 80, 83, 179, 182, 188, 305 of capital, 77, 179, 182 optimistic probability bias, 33 optimization, premature, 7 optimums, local and global, 195–96 optionality, preserving, 58–59 Oracle, 231, 291, 299 order, 124 balance between chaos and, 128 organizations: culture in, 107–8, 113, 273–80, 293 size and growth of, 278–79 teams in, see teams ostrich with its head in the sand, 55 out-group bias, 127 outliers, 148 Outliers (Gladwell), 261 overfitting, 10–11 overwork, 82 Paine, Thomas, 221–22 pain relievers, 36, 137 Pampered Chef, 217 Pangea, 24–25 paradigm shift, 24, 289 paradox of choice, 62–63 parallel processing, 96 paranoia, 308, 309, 311 Pareto, Vilfredo, 80 Pareto principle, 80–81 Pariser, Eli, 17 Parkinson, Cyril, 74–75, 89 Parkinson’s law, 89 Parkinson’s Law (Parkinson), 74–75 Parkinson’s law of triviality, 74, 89 passwords, 94, 97 past, 201, 271–72, 309–10 Pasteur, Louis, 26 path dependence, 57–59, 194 path of least resistance, 88 Patton, Bruce, 19 Pauling, Linus, 220 payoff matrix, 212–15, 238 PayPal, 72, 291, 296 peak, 105, 106, 112 peak oil, 105 Penny, Jonathon, 52 pent-up energy, 112 perfect, 89–90 as enemy of the good, 61, 89–90 personality traits, 249–50 person-month, 279 perspective, 11 persuasion, see influence models perverse incentives, 50–51, 54 Peter, Laurence, 256 Peter principle, 256, 257 Peterson, Tom, 108–9 Petrified Forest National Park, 217–18 Pew Research, 53 p-hacking, 169, 172 phishing, 97 phones, 116–17, 290 photography, 302–3, 308–10 physics, x, 114, 194, 293 quantum, 200–201 pick your battles, 238 Pinker, Steven, 144 Pirahã, x Pitbull, 36 pivoting, 295–96, 298–301, 308, 311, 312 placebo, 137 placebo effect, 137 Planck, Max, 24 Playskool, 111 Podesta, John, 97 point of no return, 244 Polaris, 67–68 polarity, 125–26 police, in organizations and projects, 253–54 politics, 70, 104 ads and statements in, 225–26 elections, 206, 218, 233, 241, 271, 293, 299 failure and, 47 influence in, 216 predictions in, 206 polls and surveys, 142–43, 152–54, 160 approval ratings, 152–54, 158 employee engagement, 140, 142 postmortems, 32, 92 Potemkin village, 228–29 potential energy, 112 power, 162 power drills, 296 power law distribution, 80–81 power vacuum, 259–60 practice, deliberate, 260–62, 264, 266 precautionary principle, 59–60 Predictably Irrational (Ariely), 14, 222–23 predictions and forecasts, 132, 173 market for, 205–7 superforecasters and, 206–7 PredictIt, 206 premature optimization, 7 premises, see principles pre-mortems, 92 present bias, 85, 87, 93, 113 preserving optionality, 58–59 pressure point, 112 prices, 188, 231, 299 arbitrage and, 282–83 bait and switch and, 228, 229 inflation in, 179–80, 182–83 loss leader strategy and, 236–37 manufacturer’s suggested retail, 15 monopolies and, 283 principal, 44–45 principal-agent problem, 44–45 principles (premises), 207 first, 4–7, 31, 207 prior, 159 prioritizing, 68 prisoners, 63, 232 prisoner’s dilemma, 212–14, 226, 234–35, 244 privacy, 55 probability, 132, 173, 194 bias, optimistic, 33 conditional, 156 probability distributions, 150, 151 bell curve (normal), 150–52, 153, 163–66, 191 Bernoulli, 152 central limit theorem and, 152–53, 163 fat-tailed, 191 power law, 80–81 sample, 152–53 pro-con lists, 175–78, 185, 189 procrastination, 83–85, 87, 89 product development, 294 product/market fit, 292–96, 302 promotions, 256, 275 proximate cause, 31, 117 proxy endpoint, 137 proxy metric, 139 psychology, 168 Psychology of Science, The (Maslow), 177 Ptolemy, Claudius, 8 publication bias, 170, 173 public goods, 39 punching above your weight, 242 p-values, 164, 165, 167–69, 172 Pygmalion effect, 267–68 Pyrrhus, King, 239 Qualcomm, 231 quantum physics, 200–201 quarantine, 234 questions: now what, 291 what if, 122, 201 why, 32, 33 why now, 291 quick and dirty, 234 quid pro quo, 215 Rabois, Keith, 72, 265 Rachleff, Andy, 285–86, 292–93 radical candor, 263–64 Radical Candor (Scott), 263 radiology, 291 randomized controlled experiment, 136 randomness, 201 rats, 51 Rawls, John, 21 Regan, Ronald, 183 real estate agents, 44–45 recessions, 121–22 reciprocity, 215–16, 220, 222, 229, 289 recommendations, 217 red line, 238 referrals, 217 reframe the problem, 96–97 refugee asylum cases, 144 regression to the mean, 146, 286 regret, 87 regulations, 183–84, 231–32 regulatory capture, 305–7 reinventing the wheel, 92 relationships, 53, 55, 63, 91, 111, 124, 159, 271, 296, 298 being locked into, 305 dating, 8–10, 95 replication crisis, 168–72 Republican Party, 104 reputation, 215 research: meta-analysis of, 172–73 publication bias and, 170, 173 systematic reviews of, 172, 173 see also experiments resonance, 293–94 response bias, 142, 143 responsibility, diffusion of, 259 restaurants, 297 menus at, 14, 62 RetailMeNot, 281 retaliation, 238 returns: diminishing, 81–83 negative, 82–83, 93 reversible decisions, 61–62 revolving door, 306 rewards, 275 Riccio, Jim, 306 rise to the occasion, 268 risk, 43, 46, 90, 288 cost-benefit analysis and, 180 de-risking, 6–7, 10, 294 moral hazard and, 43–45, 47 Road Ahead, The (Gates), 69 Roberts, Jason, 122 Roberts, John, 27 Rogers, Everett, 116 Rogers, William, 31 Rogers Commission Report, 31–33 roles, 256–58, 260, 271, 293 roly-poly toy, 111–12 root cause, 31–33, 234 roulette, 144 Rubicon River, 244 ruinous empathy, 264 Rumsfeld, Donald, 196–97, 247 Rumsfeld’s Rule, 247 Russia, 218, 241 Germany and, 70, 238–39 see also Soviet Union Sacred Heart University (SHU), 217, 218 sacrifice play, 239 Sagan, Carl, 220 sales, 81, 216–17 Salesforce, 299 same-sex marriage, 117, 118 Sample, Steven, 28 sample distribution, 152–53 sample size, 143, 160, 162, 163, 165–68, 172 Sánchez, Ricardo, 234 sanctions and fines, 232 Sanders, Bernie, 70, 182, 293 Sayre, Wallace, 74 Sayre’s law, 74 scarcity, 219, 220 scatter plot, 126 scenario analysis (scenario planning), 198–99, 201–3, 207 schools, see education and schools Schrödinger, Erwin, 200 Schrödinger’s cat, 200 Schultz, Howard, 296 Schwartz, Barry, 62–63 science, 133, 220 cargo cult, 315–16 Scientific Autobiography and other Papers (Planck), 24 scientific evidence, 139 scientific experiments, see experiments scientific method, 101–2, 294 scorched-earth tactics, 243 Scott, Kim, 263 S curves, 117, 120 secondary markets, 281–82 second law of thermodynamics, 124 secrets, 288–90, 292 Securities and Exchange Commission, U.S., 228 security, false sense of, 44 security services, 229 selection, adverse, 46–47 selection bias, 139–40, 143, 170 self-control, 87 self-fulfilling prophecies, 267 self-serving bias, 21, 272 Seligman, Martin, 22 Semmelweis, Ignaz, 25–26 Semmelweis reflex, 26 Seneca, Marcus, 60 sensitivity analysis, 181–82, 185, 188 dynamic, 195 Sequoia Capital, 291 Sessions, Roger, 8 sexual predators, 113 Shakespeare, William, 105 Sheets Energy Strips, 36 Shermer, Michael, 133 Shirky, Clay, 104 Shirky principle, 104, 112 Short History of Nearly Everything, A (Bryson), 50 short-termism, 55–56, 58, 60, 68, 85 side effects, 137 signal and noise, 311 significance, 167 statistical, 164–67, 170 Silicon Valley, 288, 289 simulations, 193–95 simultaneous invention, 291–92 Singapore math, 23–24 Sir David Attenborough, RSS, 35 Skeptics Society, 133 sleep meditation app, 162–68 slippery slope argument, 235 slow (high-concentration) thinking, 30, 33, 70–71 small numbers, law of, 143, 144 smartphones, 117, 290, 309, 310 smoking, 41, 42, 133–34, 139, 173 Snap, 299 Snowden, Edward, 52, 53 social engineering, 97 social equality, 117 social media, 81, 94, 113, 217–19, 241 Facebook, 18, 36, 94, 119, 219, 233, 247, 305, 308 Instagram, 220, 247, 291, 310 YouTube, 220, 291 social networks, 117 Dunbar’s number and, 278 social norms versus market norms, 222–24 social proof, 217–20, 229 societal change, 100–101 software, 56, 57 simulations, 192–94 solitaire, 195 solution space, 97 Somalia, 243 sophomore slump, 145–46 South Korea, 229, 231, 238 Soviet Union: Germany and, 70, 238–39 Gosplan in, 49 in Cold War, 209, 235 space exploration, 209 spacing effect, 262 Spain, 243–44 spam, 37, 161, 192–93, 234 specialists, 252–53 species, 120 spending, 38, 74–75 federal, 75–76 spillover effects, 41, 43 sports, 82–83 baseball, 83, 145–46, 289 football, 226, 243 Olympics, 209, 246–48, 285 Spotify, 299 spreadsheets, 179, 180, 182, 299 Srinivasan, Balaji, 301 standard deviation, 149, 150–51, 154 standard error, 154 standards, 93 Stanford Law School, x Starbucks, 296 startup business idea, 6–7 statistics, 130–32, 146, 173, 289, 297 base rate in, 157, 159, 160 base rate fallacy in, 157, 158, 170 Bayesian, 157–60 confidence intervals in, 154–56, 159 confidence level in, 154, 155, 161 frequentist, 158–60 p-hacking in, 169, 172 p-values in, 164, 165, 167–69, 172 standard deviation in, 149, 150–51, 154 standard error in, 154 statistical significance, 164–67, 170 summary, 146, 147 see also data; experiments; probability distributions Staubach, Roger, 243 Sternberg, Robert, 290 stock and flow diagrams, 192 Stone, Douglas, 19 stop the bleeding, 234 strategy, 107–8 exit, 242–43 loss leader, 236–37 pivoting and, 295–96, 298–301, 308, 311, 312 tactics versus, 256–57 strategy tax, 103–4, 112 Stiglitz, Joseph, 306 straw man, 225–26 Streisand, Barbra, 51 Streisand effect, 51, 52 Stroll, Cliff, 290 Structure of Scientific Revolutions, The (Kuhn), 24 subjective versus objective, in organizational culture, 274 suicide, 218 summary statistics, 146, 147 sunk-cost fallacy, 91 superforecasters, 206–7 Superforecasting (Tetlock), 206–7 super models, viii–xii super thinking, viii–ix, 3, 316, 318 surface area, 122 luck, 122, 124, 128 surgery, 136–37 Surowiecki, James, 203–5 surrogate endpoint, 137 surveys, see polls and surveys survivorship bias, 140–43, 170, 272 sustainable competitive advantage, 283, 285 switching costs, 305 systematic review, 172, 173 systems thinking, 192, 195, 198 tactics, 256–57 Tajfel, Henri, 127 take a step back, 298 Taleb, Nassim Nicholas, 2, 105 talk past each other, 225 Target, 236, 252 target, measurable, 49–50 taxes, 39, 40, 56, 104, 193–94 T cells, 194 teams, 246–48, 275 roles in, 256–58, 260 size of, 278 10x, 248, 249, 255, 260, 273, 280, 294 Tech, 83 technical debt, 56, 57 technologies, 289–90, 295 adoption curves of, 115 adoption life cycles of, 116–17, 129, 289, 290, 311–12 disruptive, 308, 310–11 telephone, 118–19 temperature: body, 146–50 thermostats and, 194 tennis, 2 10,000-Hour Rule, 261 10x individuals, 247–48 10x teams, 248, 249, 255, 260, 273, 280, 294 terrorism, 52, 234 Tesla, Inc., 300–301 testing culture, 50 Tetlock, Philip E., 206–7 Texas sharpshooter fallacy, 136 textbooks, 262 Thaler, Richard, 87 Theranos, 228 thermodynamics, 124 thermostats, 194 Thiel, Peter, 72, 288, 289 thinking: black-and-white, 126–28, 168, 272 convergent, 203 counterfactual, 201, 272, 309–10 critical, 201 divergent, 203 fast (low-concentration), 30, 70–71 gray, 28 inverse, 1–2, 291 lateral, 201 outside the box, 201 slow (high-concentration), 30, 33, 70–71 super, viii–ix, 3, 316, 318 systems, 192, 195, 198 writing and, 316 Thinking, Fast and Slow (Kahneman), 30 third story, 19, 92 thought experiment, 199–201 throwing good money after bad, 91 throwing more money at the problem, 94 tight versus loose, in organizational culture, 274 timeboxing, 75 time: management of, 38 as money, 77 work and, 89 tipping point, 115, 117, 119, 120 tit-for-tat, 214–15 Tōgō Heihachirō, 241 tolerance, 117 tools, 95 too much of a good thing, 60 top idea in your mind, 71, 72 toxic culture, 275 Toys “R” Us, 281 trade-offs, 77–78 traditions, 275 tragedy of the commons, 37–40, 43, 47, 49 transparency, 307 tribalism, 28 Trojan horse, 228 Truman Show, The, 229 Trump, Donald, 15, 206, 293 Trump: The Art of the Deal (Trump and Schwartz), 15 trust, 20, 124, 215, 217 trying too hard, 82 Tsushima, Battle of, 241 Tupperware, 217 TurboTax, 104 Turner, John, 127 turn lemons into lemonade, 121 Tversky, Amos, 9, 90 Twain, Mark, 106 Twitter, 233, 234, 296 two-front wars, 70 type I error, 161 type II error, 161 tyranny of small decisions, 38, 55 Tyson, Mike, 7 Uber, 231, 275, 288, 290 Ulam, Stanislaw, 195 ultimatum game, 224, 244 uncertainty, 2, 132, 173, 180, 182, 185 unforced error, 2, 10, 33 unicorn candidate, 257–58 unintended consequences, 35–36, 53–55, 57, 64–65, 192, 232 Union of Concerned Scientists (UCS), 306 unique value proposition, 211 University of Chicago, 144 unknown knowns, 198, 203 unknowns: known, 197–98 unknown, 196–98, 203 urgency, false, 74 used car market, 46–47 U.S.


pages: 386 words: 113,709

Why We Drive: Toward a Philosophy of the Open Road by Matthew B. Crawford

1960s counterculture, Airbus A320, airport security, augmented reality, autonomous vehicles, Bernie Sanders, Boeing 737 MAX, British Empire, Burning Man, call centre, collective bargaining, crony capitalism, deskilling, digital map, don't be evil, Donald Trump, Elon Musk, en.wikipedia.org, Fellow of the Royal Society, gig economy, Google Earth, hive mind, income inequality, informal economy, Internet of things, Jane Jacobs, labour mobility, Lyft, Network effects, New Journalism, New Urbanism, Nicholas Carr, Ponzi scheme, Ralph Nader, ride hailing / ride sharing, Ronald Reagan, Sam Peltzman, security theater, self-driving car, sharing economy, Shoshana Zuboff, Silicon Valley, smart cities, social graph, social intelligence, Stephen Hawking, technoutopianism, the built environment, The Death and Life of Great American Cities, the High Line, too big to fail, traffic fines, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, Unsafe at Any Speed, urban planning, Wall-E, Works Progress Administration

Mike Isaac, “Uber Defies California Regulators with Self-Driving Car Service,” New York Times, December 16, 2016, https://www.nytimes.com/2016/12/16/technology/uber-defies-california-regulators-with-self-driving-car-service.html. 9.John Harris, “With Trump and Uber, the Driverless Future Could Turn into a Nightmare,” Guardian, December 16, 2016, https://www.theguardian.com/commentisfree/2016/dec/16/trump-uber-driverless-future-jobs-go. 10.These are the findings of the city’s transport department as characterized by Nicole Gelinas in “Why Uber’s Investors May Lose Their Lunch,” New York Post, December 26, 2017, available at https://www.manhattan-institute.org/html/why-ubers-investors-may-lose-their-lunch-10847.html. 11.“Uber and Lyft Want to Replace Public Buses,” New York Public Transit Association, August 16, 2016, https://nytransit.org/resources/transit-tncs/207-uber-and-lyft-want-to-replace-public-buses. 12.Huber Horan, “Uber’s Path of Destruction,” American Affairs 3, no. 2 (Summer 2019). 13.Horan, “Uber’s Path of Destruction.” Horan cites structural problems that are intrinsic to the taxi market, requiring extra-market remedies. For example, as with all urban transport modes, taxi demand has “extreme temporal and geographic peaks,” leading to a combination of overcapacity at slow hours and scarcity at peak demand.

“[R]elieving drivers of even one aspect of the driving task results in reports of increased driver drowsiness and reduced vigilance when driving on open stretches of road” according to the findings of A. Dufour, “Driving Assistance Technologies and Vigilance: Impact of Speed Limiters and Cruise Control on Drivers’ Vigilance,” presentation at the International Transport Forum (Paris, France, April 15, 2014), as characterized in Casner et al., “The Challenges of Partially Automated Driving.” 6.“Lyft Co-founder Says Human Drivers Could Soon Be Illegal in America,” according to a headline in Business Insider, December 15, 2016. In November 2017 in Automotive News, Bob Lutz, the head of GM, suggested that driving will be outlawed in twenty years. Bob Lutz, “Kiss the Good Times Goodbye,” Automotive News, November 5, 2017, http://www.autonews.com/apps/pbcs.dll/article?AID=/20171105/INDUSTRY_REDESIGNED/171109944/industry-redesigned-bob-lutz. 7.Ian Bogost, “Will Robocars Kick Humans off City Streets?”


pages: 233 words: 64,702

China's Disruptors: How Alibaba, Xiaomi, Tencent, and Other Companies Are Changing the Rules of Business by Edward Tse

3D printing, Airbnb, Airbus A320, Asian financial crisis, barriers to entry, bilateral investment treaty, business process, capital controls, commoditize, conceptual framework, corporate governance, creative destruction, crowdsourcing, currency manipulation / currency intervention, David Graeber, Deng Xiaoping, disruptive innovation, experimental economics, global supply chain, global value chain, high net worth, industrial robot, Joseph Schumpeter, Lyft, money market fund, offshore financial centre, Pearl River Delta, reshoring, rising living standards, risk tolerance, Silicon Valley, Skype, Snapchat, sovereign wealth fund, special economic zone, speech recognition, Steve Jobs, thinkpad, trade route, wealth creators, working-age population

And it has also invested in several venture capital funds so as to have access to news about fast-growing start-ups that it might be able to introduce to China. Alibaba’s interest in American companies has also grown rapidly. Even before its New York listing, its U.S. investment team had spent more than $500 million buying minority stakes in shipping service Shoprunner, mobile messaging application Tango, luxury e-commerce business 1stDibs, and travel-sharing business Lyft. As they internationalize, Chinese companies will hire an ever greater number and range of foreign executives and other staff who can bring expertise unavailable in China. These people will bring knowledge of how to structure and run global operations, how to develop capabilities where Chinese business are currently weak such as marketing, and how best to enter markets such as the United States that are very different from China’s.

., 93–94 Konka, 76 Koo, Victor, 158–59, 160, 218 Krugman, Paul, 9 Kutcher, Ashton, 129 Lardy, Nicholas, 17 Lau, Martin, 136 Lau, Ricky, 225 Lee, Hudson, 196 Lee, Kai-fu, 111–12 legal infrastructure, 114 Legend, 44 Legend Holdings, 112, 126 Lei Jun, 11, 12, 57, 67, 81, 112, 162, 197, 226 Lenovo, 11, 20, 44, 54, 67, 75, 89, 112, 139, 140, 148, 171 expansion by, 124–29, 130 revenue of, 125–26, 127, 128 Leung, Antony, 224 Levi’s, 195 Li, Richard, 85–86 Li, Robin, 11, 49, 50, 64, 81, 88, 139 liberalization, 44, 55, 71, 72, 75, 78–79, 152, 154, 166–67, 178, 181, 210, 211, 223 of interest rates, 40, 152–53 Li Dongsheng, 148 Liebherr, 5–6 Lifan, 76 Li Ka-shing, 85 Li Keqiang, 210, 215 Lin Bin, 68 Li Shufu, 12, 44, 47, 131–34, 138, 175, 185 Little Emperors, 51–53 Liu Chuanzhi, 54, 171 Liu Junling, 96 Liu Mingkang, 149 Loncin, 76 L’Oréal, 205 Lu Guanqiu, 130 Lyft, 135 Ma, Jack, 10, 33–40, 41, 47, 50, 54–55, 60–61, 62–63, 64, 86, 136, 148, 197, 201, 221 background of, 36–37 environmental work of, 60, 168, 169–70 and U.S. IPO of Alibaba, 33, 85, 90 Ma, Pony, 11, 49, 50, 60, 64, 81, 85, 86, 88, 197, 201 McDonald’s, 180 McFarlan, F. Warren, 93–94 McGrath, Rita Gunther, 99 Manganese Bronze, 133 manufacturing, 109–10 Mao Zedong, 13, 42, 51 Cultural Revolution instigated by, 4, 42, 43 Marks and Spencer, 194 media, 157–62, 213 medical research, 109 Meituan.com, 53, 191 Metallurgical Corporation, 124 MG Rover, 136–37 Mi, 68 see also Xiaomi Miasolé, 123 Microsoft, 112 middle-income trap, 213–14 Mindray Medical International, 122–23, 178 mining, 119, 163 Mitchell, James, 136 motorcycles, 47, 76, 95, 100, 178 Motorola Mobility, 127, 128, 129, 136 Nan Fung, 224 Nanjing Auto, 136 Naspers, 86, 194 National People’s Congress, 43, 81 Navarro, Peter, 9 Nestlé, 194, 196 New Citizens Movement, 170 New York Stock Exchange, 33, 52, 159, 206 Nexen, 119–20 Nike, 195 Nissan, 180 Noah Wealth Management, 12, 150, 153, 212 Nokia, 102, 112 Nortel, 102 open markets, 71, 72–77, 83, 85, 88, 97 Panda W, 205–7, 208, 225 Pan Shiyi, 48 People’s Liberation Army, 101–2 Pepsi, 180 Pew Research Center, 219 piracy, 9, 75, 199 pollution, 115, 209, 212, 217, 221 Pope, Larry, 22 pride, 41, 55, 57, 61, 123 private-equity funds, 79 Procter & Gamble, 12, 175, 177 products, updating of, 97 property rights, 81, 170 Pudong New Area, 224 Putzmeister, 130 Qihoo 360, 84, 113 Qingdao Refrigerator Factory, 4–5 see also Haier Qingqi, 76 QQ, 85, 86, 160, 185, 201 Reckitt Benckiser, 194, 196 Red Packet, 88 Red Rice smartphone, 69 Renault/Nissan, 133 Renren, 52–53 Ren Zhengfei, 11, 43–44, 54, 60, 101–3, 175, 200 Rio Tinto, 119 robots, 110 Roche Diagnostics, 155 Roewe, 137 Russia, 13, 68 doctorates in, 108 oligarchs in, 17 SAIC Motor Corp, 136–37 Samsung, 67, 68, 89, 128 Sany, 178 Sanyo Electric, 7 Schumpeter, Joseph, 163 Sehgal, Aditya, 196 Sequoia Capital, 113, 150 SF Express, 100 shared heritage, 55, 61–64 Shen, Neil, 113 Shenzhen Stock Exchange, 156 Shunwei China, 112 Siemens, 102 Silicon Graphics, 112 Silicon Valley, 18 Silk Road, 57 Sina Weibo, 69, 87–88, 161, 170, 191 Singapore, 68, 100, 155 SingPost, 100 Sino Iron mine, 124 Sinovac Biotech, 109 Sky City, 217–18, 221 Skype, 129 smartphones, 9, 11, 67–70, 75, 89, 128, 135, 139 Smithfield Foods, 22, 120 Softbank, 37, 156, 194 SOHO China, 48 Sohu, 158, 159 sourcing networks, 188 South China Morning Post, 37 South Korea, 121, 141 special economic zones, 43 Standard Chartered, 151 State Administration of Press, Publication, Radio, Film, and Television, 219 State Council, 215 state-owned enterprises, 9–10, 13–14, 36, 40, 76, 80, 119, 137, 158, 164, 176, 179–80, 209, 213 strategy+business, 49–50 Su, Sam, 196 subsidies, 9, 163 Surprise (series), 160 Sze Man Bok, 43, 176, 177 Tabarrok, Alex, 113 Taikang Life Insurance, 45, 55, 148 Taiwan, 68, 121, 214 Taizhou, 44 Tang dynasty, 28–29, 229 Tango, 135 Tan Wanxin, 13 Taobao, 34–35, 38, 40, 184 TCL, 76, 84, 148 Tedjarati, Shane, 190, 196 telecoms, 103–4, 122, 178 television, 76, 158, 178, 219 Tencent, 11, 18, 39, 52, 60, 80, 81, 83–84, 85–88, 90, 101, 135, 136, 151, 158, 159, 161, 162, 185, 191, 201, 222, 225 founding of, 49, 85 innovation by, 94, 113 Naspers’ purchase of stake in, 86, 194 overseas listing of, 89 revenue of, 87 Tenpay system of, 36 Tenpay, 36, 87 Tesco, 180 Tetra Pak, 196 ThinkPad, 128 Third Plenum of the 18th Party Congress, 211, 214, 215 Thomas Group, 177–78 3D printing, 110–11 360 Mobile Assistant, 84 Tian, Lawrence, 147–48 Tiananmen Square, 44 Tingyi, 180 Tmall, 36, 38, 87, 184, 195, 206 Tmall Global, 195 Toyota, 133, 180 TPG Capital, 225 transport, 115 Tsai, Joe, 37 Twitter, 87, 222 United Kingdom, doctorates in, 108 United States, 18 doctorates in, 108 R&D spending in, 107 technological supremacy of, 106 urbanization, 28, 115, 214 Uyghurs, 53 Vanke, 148 Vantone Holdings, 46, 148 vehicles, 115 venture capital, 79 Vipshop, 84, 113, 206 Volkswagen, 133, 137, 179, 180 Volvo, 123, 131, 132, 133, 134, 138, 185 wage pressure, 98 Wallerstein, David, 136 Wal-Mart, 96, 194 Wanda E-Commerce, 88 Wang, Diane, 12, 57 Wang, Victor, 145–47, 167, 168–69, 171 Wang Jianlin, 48, 88, 172 Wang Jingbo, 12, 150, 152 Wang Shi, 148 Wang Wei, 147–48 Wang Xing, 52–53 Wanxiang, 130, 134, 178 Ward, Stephen, 126 water, 6, 25, 106, 188 WeChat, 18–19, 84, 87, 88, 139, 160, 185, 191, 201, 212 Wen Jiabao, 147 WhatsApp, 18–19, 191 WH Group, 21–22, 120 Wong, Jessica, 205–7, 208, 210, 214, 225 World Economic Forum, 147 World Health Organization (WHO), 114 World Trade Organization, 6, 16, 37–38, 47, 122, 222 Xiangcai Securities, 150 Xiaomi, 11, 12, 57, 67–70, 75, 77, 89, 101, 128, 139, 162, 191–92, 197, 226 innovation by, 94, 112, 113 Xiaonei, 52–53 Xi Jinping, 78, 80, 152, 160, 165, 167, 168, 170, 181, 210–11, 213, 223, 229 Xu, William, 222 Xue, Charles, 161, 170 Xu Lianjie, 12, 43, 53, 175–78, 200 Yabuli, 145, 147, 149, 166 Yahoo, 194 Yang Yuanqing, 11, 125–26, 128, 148 Yao, Frank, 205–7, 210, 214, 225 Yihaodian, 11, 89, 95–97, 194 Yinlu, 194 Yoga IdeaPad, 127 Youku Tudou, 84, 114, 158–60, 161, 162, 209, 212, 218 YouTube, 158, 218 yuan, 9 Yu’e Bao, 39, 40, 153, 212 Yu Gang, 11, 94–96, 100, 112 Yum!


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

They need to understand the parameters and patterns that govern their working environment. A protective legal framework is not only essential to guarantee the right to organize and the freedom of expression but it can help to guard against platform-based child labor, wage theft, arbitrary behavior, litigation, and excessive workplace surveillance along the lines of the “reputation systems” of companies like Lyft and Uber that “deactivate” drivers if their ratings fall below 4.5 stars. Crowd workers should have a right to know what they are working on instead of contributing to mysterious projects posted by anonymous consignors. At its heart, platform cooperativism is not about any particular technology but the politics of lived acts of cooperation. Soon, we may no longer have to contend with websites and apps but, more and more, with 5G wireless services (more mobile work), protocols, and AI.

–based worker cooperative like Sunkist (formerly the California Fruit Exchange, an entity that has, since 1893, been entirely owned by citrus fruit growers), has thrived, where other types of cooperatives have failed to emerge at scale. Perhaps the businesses that have fueled much of the world’s economic growth in recent decades have instead been in highly competitive industries, leveraging specialized high-variance talent and requiring large technological investments. But if one thinks about it, today’s sharing-economy platforms do exhibit some characteristics in common with Sunkist, and a worker-owned equivalent to Lyft and Uber seems quite feasible. Point-to-point urban transportation is a fairly uniform service in an industry with a limited amount of competition. Once the technology associated with “e-hail” and logistics is commoditized, which it will be, the economic fundamentals for the emergence of a platform cooperative would appear to be in place. More important, the network effects associated with ridesharing are geographically concentrated.


pages: 212 words: 69,846

The Nation City: Why Mayors Are Now Running the World by Rahm Emanuel

Affordable Care Act / Obamacare, Airbnb, blockchain, carbon footprint, clean water, deindustrialization, Donald Trump, Edward Glaeser, Enrique Peñalosa, Filter Bubble, income inequality, informal economy, Jane Jacobs, Kickstarter, Lyft, megacity, new economy, New Urbanism, offshore financial centre, payday loans, ride hailing / ride sharing, Ronald Reagan, Silicon Valley, The Death and Life of Great American Cities, the High Line, transcontinental railway, Uber and Lyft, uber lyft, urban planning, War on Poverty, white flight, working poor

I had encouraged President Obama to create and fund it in his budget, and we were the first applicants. (Funny how that happened.) We also found some money in a federal program called Congestion Mitigation and Air Quality Improvement. We had a start, but we needed more. So I put on my dancing shoes and went down to Springfield. I cajoled our state to change TIF regulations so we could apply TIFs to transportation. We also levied a first-ever fee on the ride-sharing companies Uber and Lyft, which raised $16 million in its first year (2017). We used that money to raise $180 million in bonds to be used for capital improvement. We did this—the biggest modernization of our transit system in the city’s history—without raising our tax rates or fare increases, and without a new federal transportation bill. Finding the money is more complicated than it should be. This is how a mayor can and must work the levers to get things done for a city.

The idea is to help the students cope with such feelings as frustration and to “think about their thinking.” This is vitally important: Much of the violence we see in our cities is impulsive, an overreaction to provocation. I loved the program from the beginning, and I did much to enhance and boost its reach. We funded some of it from a $10.4 million settlement we received after we sued Uber and Lyft for inadequate background checks on their drivers. This idea was hatched at the University of Chicago Crime Lab. We started to scale it up, and it now reaches 7,000 young men and is being copied by other cities, such as Boston. The goal is to reach all young men in crime-ridden neighborhoods by ensuring they are in a mentoring program from seventh to eleventh grades. Chicago is on track to achieve that goal this year.


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

After an initial setback as workers were unsure how to organise and fight for their rights in these new business models, the last year has seen workers striking back in increasingly significant ways. Uber drivers, for instance are attempting to build unions; Deliveroo drivers are attempting to as well; and many of these lean platform companies are facing a number of lawsuits. Uber had to pay $100 million in one settlement; Lyft had to pay $27 million in another settlement; Postmates is currently facing an $800 million suit.6 One lawsuit for Uber estimated they would owe drivers $852 million if they were deemed employees and not independent contractors. Uber retorted that it would only be $429 million.7 The result of this worker pushback is that these very low margin businesses are going to become even more unprofitable in the future, and the business model is unlikely to expand much further.

., 160 Keune, Maarten, 180 Keynes, John Maynard, 6, 9, 11, 27, 60, 61, 160, 161, 176 King, Martin Luther, 171 Knowledge (tacit vs. explicit), 127 Komlosy, Andrea, 4, 75 Kubrick, Stanley, 26 Kurzweil, Raymond, 101, 103, 104 Kuznets, Simon, 190 L Labour, 3, 10, 11, 13–16, 18–21, 29, 34–36, 38, 43–46, 55, 59, 65–70, 73–76, 85–87, 89, 90, 93, 94, 96, 114, 125, 126, 128, 130, 131, 141, 158, 165, 176–180, 183–184, 189, 190, 192–196, 199–200 Labour market polarisation, 67, 70, 126 Labour markets, 67, 68, 70, 87, 90, 96, 125, 126, 128, 130, 131, 141, 178, 183–184, 189, 192, 193, 195, 196, 199–200 Labour-saving effect, 86 Lall, Sanjaya, 193 Language translation, 105, 106 Latent Damage Act 1986, 127 Law automation of, 145, 152, 153 ethics, 145–153 Lawrence, Mathew, 177 Layton, E., 58 Le Bon, Gustave, 101 Lee, Richard, 26 Legal search/legal discovery, 148–150 208 Index Leisure, 3, 10, 11, 19, 27, 48, 55, 56, 59–62, 65, 77, 79, 117, 118, 159, 161, 178, 180, 182, 184, 191, 195 Levy, Frank, 126 List, Friedrich, 193 Love, 55, 74, 76, 99, 103, 106, 112, 118 Low-income jobs, 96 Loyalty, 69 Luddites, 2, 14, 18, 35, 59, 94, 96 Lyft, 136 M Machine learning, 59, 84, 90, 91, 96, 138, 139 Machines, 2, 5, 10, 12–15, 17, 19, 20, 35, 36, 38, 59, 84–87, 90–96, 99–103, 105–107, 109–121, 127–131, 138, 139, 145, 147, 148, 160, 168, 191 Machine vision, 120 Malthusian, 19 Man, Henrik de, 79 Management, 27, 30, 41, 69, 70 management theory/ organisational theory (see also Scientific management) Mann, Michael, 46 Manual work, 1 Manufacturing, 86, 87, 90, 94, 95, 176, 184, 198 Markets/market forces, 5, 6, 21, 38, 44–46, 67, 68, 70, 79, 85–88, 90, 96, 120, 125, 126, 128, 130, 131, 140, 141, 150, 152, 159, 164, 165, 171, 178, 183, 189–193, 195, 196, 198–200 Marx, Karl, 17, 18, 27, 56–59, 61, 62, 78 Matrimonial relationships, 37 McCormack, Win, 159 Meaning, 4, 9, 10, 19, 25, 54, 57, 58, 66, 73, 76, 78, 79, 84, 106, 116, 176, 180 Mechanisation, 15, 17, 19, 20, 192 Meckling, W., 55 Méda, Dominique, 183 Medical diagnosis (automation of ), 128, 129 Menger, Pierre-Michel, 4 Mental labour, 3 Meritocracy, 28 Middle-income jobs, 90, 93, 94 Migration, 40, 47 Minimum wage, 67, 69 Mining, 26, 38, 197 Mokyr, J., 59 Monopolies, 6, 136, 138–140 Morals/morality, 48, 77, 159, 160, 162, 164, 166, 167 Moravec’s paradox, 131 Murnane, Richard, 126 N Nagel, Thomas, 100, 102 National Living wage, 184 Needs vs.


pages: 621 words: 123,678

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

It’s also worth noting that all of my side hustles were things I didn’t learn in school, need a college degree for, or have to work through another company to do. There are two ways you can make money side hustling: you can work for someone else or work for yourself. If you are side hustling for someone else, the money you can make will always be limited by the number of hours you have in the day. It’s really tough to get off your nine-to-five job and hop in a Lyft to drive all night. Sure, it gives you flexibility and freedom, but no matter how much you drive for Lyft or deliver for Postmates, you’ll always be limited to your own hours and will make only as much money as those companies are willing to pay you. In other words, these gigs are not scalable. Working for yourself allows you to make a lot of money doing something that you love and gives you more control. Matt could have easily worked for someone else’s dog-walking company and made $10 per hour, but by launching his own company, he gets to make money, not only on the time he spends walking dogs, but also on the time his employees spend walking dogs.

You can use that 53 minutes each day to read a book or take a nap, listen to a podcast, or even earn some extra cash by selling something online or working on one of your side gigs. If you have a couple of friends or neighbors who drive the same direction as you, then carpooling is a simple way to cut costs, one that might be even more affordable than public transportation. Another option is ride-sharing using a service like Uber, Lyft, or Waze. In some locations, ride-sharing might even be cheaper than owning a car. I know people in Los Angeles, one of the most car-dependent cities on the planet, who use ride-sharing services to get everywhere because they’re so inexpensive. THE ART OF TRAVEL-HACKING Get out and explore the world. It’s never been easier to travel for less. While travel-hacking takes some work, with a little effort you can travel for a lot less.


Early Retirement Guide: 40 is the new 65 by Manish Thakur

"side hustle", Airbnb, diversified portfolio, financial independence, hedonic treadmill, index fund, Lyft, passive income, passive investing, risk tolerance, Robert Shiller, Robert Shiller, time value of money, uber lyft, Vanguard fund, Zipcar

This is less of a life change than biking or walking, but also has the big effect of less financial waste. When it comes down to it, owning a large, powerful car is an expensive luxury that most people don't remotely get close to using to the fullest, and don't even realize the kind of luxury they have. Here are several conscientious spending alternatives: 1. Carpooling to work and split the cost of gas. 2. Signing up for a car sharing service such as Zipcar or Car2Go. 3. Use Uber or Lyft if the longer distance rides are rarer and signing up for a car sharing service doesn't add up. Get free rides just by signing up with these links and try them out if you haven't yet Savings: $8,800 Challenges: 1. Compare the cost of public transportation to all the costs of owning a car, there's probably a significant difference. 2. Take public transportation or carpool to work with coworkers and use the freed up time to relax, prepare for the day, read a book, or even learn a new professional skill. 3.


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

Of course, because experimentation necessarily means making what you will later regard as mistakes, experiments also have costs. You will try foods you don’t like. If you keep trying new foods in the hope of finding some ideal, you are missing out on a lot of good meals. Judgment, whether by deliberation or experimentation, is costly. Knowing Why You Are Doing Something Prediction is at the heart of a move toward self-driving cars and the rise of platforms such as Uber and Lyft: choosing a route between origin and destination. Car navigation devices have been around for a few decades, built into cars themselves or as stand-alone devices. But the proliferation of internet-connected mobile devices has changed the data that providers of navigation software receive. For instance, before Google acquired it, the Israeli startup Waze generated accurate traffic maps by tracking the routes drivers chose.

See also jobs “Lady Lovelace’s Objection,” 13 Lambrecht, Anja, 196 language translation, 25–27, 107–108 laws of robotics, 115 learning -by-using, 182–183 in the cloud vs. on the ground, 188–189, 202 experience and, 191 in-house and on-the-job, 185 language translation, 26–27 pathways to, 182–184 privacy and data for, 189–190 reinforcement, 13, 145, 183–184 by simulation, 187–188 strategy for, 179–194 supervised, 183 trade-offs in performance and, 181–182 when to deploy and, 184–187 Lederman, Mara, 168–169 Lee, Kai-Fu, 219 Lee Se-dol, 8 legal documents, redacting, 53–54, 68 legal issues, 115–117 Lewis, Michael, 56 Li, Danielle, 58 liability, 117, 195–198 lighting, cost of, 11 London cabbies, 76–78 Lovelace, Ada, 12, 13 Lyft, 88–89 Lytvyn, Max, 96 machine learning, 18 adversarial, 187–188 churn prediction and, 32–36 complexity and, 103–110 from data, 45–47 feedback for, 46–47 flexibility in, 36 judgment and, 83 one-shot, 60 regression compared with, 32–35 statistics and prediction and, 37–40 techniques, 8–9 transformation of prediction by, 37–40 Mailmobile, 103 management AI’s impact on, 3 by exception, 67–68 Mastercard, 25 mathematics, made cheap by computers, 12, 14 Mazda, 124 MBA programs, student recruitment for, 127–129, 133–139 McAfee, Andrew, 91 Mejdal, Sig, 161 Microsoft, 9–10, 176, 180, 202–204, 215, 217 Tay chatbot, 204–205 mining, automation in, 112–114 Misra, Sanjog, 93–94 mobile-first strategy, 179–180 Mobileye, 15 modeling, 99, 100–102 Moneyball (Lewis), 56, 161–162 monitoring of predictions, 66–67 multivariate regression, 33–34 music, digital, 12, 61 Musk, Elon, 209, 210, 221 Mutual Benefit Life, 124–125 Napster, 61 NASA, 14 National Science and Technology Council (NSTC), 222–223 navigation apps, 77–78, 88–90, 106 Netscape, 9–10 neural networks, 13 New Economy, 10 New York City Fire Department, 197 New York Times, 8, 218 Nordhaus, William, 11 Norvig, Peter, 180 Nosko, Chris, 199 Novak, Sharon, 169–170 Numenta, 223 Nymi, 201 Oakland Athletics, 56, 161–162 Obama, Barack, 217–218 objectives, identifying, 139 object recognition, 7, 28–29 Olympics, Rio, 114–115 omitted variables, 62 one-shot learning, 60 On Intelligence (Hawkins), 39 Open AI, 210 optimization, search engine, 64 oracles, 23 organizational structure, 161–162 Osborne, Michael, 149 Otto, 157–158 outcomes in decision making, 74–76, 134–138 job redesign and, 142 outsourcing, 169–170, 171 Page, Larry, 179 Paravisini, Daniel, 66–67 pattern recognition, 145–147 Pavlov, Ivan, 183 payoff calculations, 78–81 in drug discovery, 136 judgment in, 87–88 Pell, Barney, 2 performance, trade-offs between learning and, 181–182, 187 performance reviews, 172–173 photography digital, 14 sports, automation of, 114–115 Pichai, Sundar, 179–180 Piketty, Thomas, 213 Pilbara, Australia, mining in, 112–114 policy, 3, 210 power calculations, 48 prediction, 23–30 about the present, 23–24 behavior affected by, 23 bias in, 34–35 complements to, 15 consequences of cheap, 29 credit card fraud prevention and, 24–25 in decision making, 74–76, 134–138 definition of, 13, 24 by exception, 67–68 human strengths in, 60 human weaknesses in, 54–58 improvements in, 25–29 as intelligence, 2–3, 29, 31–41 in language translation, 25–27 machine weaknesses in, 58–65 made cheap, 13–15 selling, 176–177 techniques, 13 unanticipated correlations and, 36–37 of what a human would do, 95–102 predictive text, 130 preferences, 88–90, 96–97, 98 selling consumer, 176–177 presidential elections, 59 prices effects of reduced AI, 9–11 human judgment in, 100 sales causality and, 63–64 for ZipRecruiter, 93–94 privacy issues, 19, 49, 98 China and, 219–220 country differences in, 219–221 data collection, 189–190 probabilistic programming, 38, 40 processes.


pages: 293 words: 78,439

Dual Transformation: How to Reposition Today's Business While Creating the Future by Scott D. Anthony, Mark W. Johnson

activist fund / activist shareholder / activist investor, additive manufacturing, Affordable Care Act / Obamacare, Airbnb, Amazon Web Services, autonomous vehicles, barriers to entry, Ben Horowitz, blockchain, business process, business process outsourcing, call centre, Clayton Christensen, cloud computing, commoditize, corporate governance, creative destruction, crowdsourcing, death of newspapers, disintermediation, disruptive innovation, distributed ledger, diversified portfolio, Internet of things, invention of hypertext, inventory management, Jeff Bezos, job automation, job satisfaction, Joseph Schumpeter, Kickstarter, late fees, Lean Startup, Lyft, M-Pesa, Marc Andreessen, Mark Zuckerberg, Minecraft, obamacare, Parag Khanna, Paul Graham, peer-to-peer lending, pez dispenser, recommendation engine, self-driving car, shareholder value, side project, Silicon Valley, Skype, software as a service, software is eating the world, Steve Jobs, the market place, the scientific method, Thomas Kuhn: the structure of scientific revolutions, transfer pricing, uber lyft, Watson beat the top human players on Jeopardy!, Y Combinator, Zipcar

Automobile Manufacturing Knowing the demographics of most business book readers, we imagine that for you, one of the most meaningful events in life was the day you were old enough to get a piece of laminated plastic that allowed you to drive a car. Freedom! There’s a reason many songs in the 1950s and 1960s were about cars. Heavy investment in a world-class road infrastructure. Cheap gas. Affordable cars. If you combine them, as The Mamas and the Papas sang in 1966, you could “go where you wanna go.” The world changes, always. Now consumers summon Uber or Lyft from their smart phones to g