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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
. ,” Huffington Post, December 6, 2017, www.huffingtonpost.com/michael-lazar/the-average-american-auto_b_9405176.html. 39. Lauren Day, “Uber Driver Says Driving Isn’t Worth It,” KMIR, July 19, 2017, www.kmir.com/story/35926469/uber-driver-says-driving-isnt-worth-it. 40. Griswold, “Inside Uber’s Unsettling Alliance.” 41. Wells, Attoh, and Cullen, “The Work Lives of Uber Drivers.” 42. Alex Rosenblat, “How Uber’s Alliance with Montréal Drivers Turns Labo[u]r’s Tactics On Its Head,” Uber Screeds, August 4, 2016, https://medium.com/uber-screeds/how-ubers-alliance-with-montr%C3%A9al-drivers-turns-labo-u-r-s-tactics-on-its-head-af490b252dae. 43. Alex Rosenblat, “Is Your Uber/Lyft Driver in Stealth Mode?” Uber Screeds, July 19, 2016, https://medium.com/uber-screeds/is-your-uber-driver-in-hiding-484696894139. 44. Mike Isaac, “Uber’s C.E.O. Plays with Fire,” New York Times, April 23, 2017, www.nytimes.com/2017/04/23/technology/travis-kalanick-pushes-uber-and-himself-to-the-precipice.html; Ali Griswold, “Oversharing: Waymo Hits Uber Where It Hurts, Instacart Talks Cash-Flow, and Airbnb Dorm Rooms,” Quartz, April 25, 2017. 45.
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. Both dispatch fares through an automated system (Uber claims the nearest driver is dispatched, while Lyft claims the nearest driver is dispatched and determines how long a driver has been waiting for a dispatch).
Jessica, “New Survey: Drivers Choose Uber for Its Flexibility and Convenience,” Uber Newsroom, December 7, 2015, https://newsroom.uber.com/driver-partner-survey/. 6. Lyft, “Explore,” February 14, 2018, www.lyft.com/. 7. Uber, “Get there,” February 14, 2018, www.uber.com/. 8. Harry Campbell, “2018 Uber and Lyft Driver Survey Results—The Rideshare Guy,” February 26, 2018, The Rideshare Guy, https://therideshareguy.com/2018-uber-and-lyft-driver-survey-results-the-rideshare-guy/. Index Aasim (driver), 153–54 Abbott, Greg, 176 Abraham (driver), 124–25 acceptance of rides. See ride acceptance policies accidents, automobile, 4, 187, 201 Adnan (driver), 29–30, 37 advertisement campaigns: algorithmic technology and, 112; and earnings claims, 61, 63, 64; of Fiverr, 27, 35–36; of Uber, 25, 34–37, 76–77, 76 fig.
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
The report has frequently been referred to as a “paper,” but given that it was paid for by Uber and was not subjected to any external review the word “report” is more accurate. 55 For example, Ellen Huet at Forbes, Jacob Davidson at Time, Andrea Peterson at the Washington Post. 56 Peterson, “The Missing Data Point from Uber’s Driver Analysis.” 57 Baker, “Ubernomics.” 58 Guendelsberger, “Infographic.” 59 Booth, “Uber Whistleblower Exposes Breach in Driver-Approval Process.” 60 Biddle, “Uber Driver.” 61 Skinner, “California Prosecutors Say Uber’s Background Checks Missed Convicts.” 62 Said, “As Uber, Lyft, Sidecar Grow, so Do Concerns of Disabled.” 63 Wieczner, “Why the Disabled Are Suing Uber and Lyft.” 64 Trautman, “Will Uber Serve Customers With Disabilities?” 65 Strochlic, “Uber.” 66 Redmond, “Does Airbnb Have an ADA Problem?” 67 Peterson, “Uber Does Not Care about Racism, It Cares about Money.” 68 Wilonsky, “On the Same Day Dallas Task Force Begins Debating Car-for-Hire Rules, Cab Industry Sues Chicago over Uber, Lyft”; Peck, “Uber’s New Delivery Service Only Caters To D.C.’s White Neighborhoods.” 69 Hall and Krueger, “An Analysis of the Labor Market for Uber’s Driver-Partners in the United States.” 70 Edelman and Luca, Digital Discrimination: The Case of Airbnb.com. 71 Todisco, “Share and Share Alike?”
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?”
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/. Gansky, Lisa.
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
Shutdowns for SideCar, RelayRides Highlight Hurdles for Car- and Ride-Sharing Startups,” Wall Street Journal, May 15, 2013, http://blogs.wsj.com/venturecapital/2013/05/15/n-y-shutdowns-for-sidecar-relayrides-highlight-hurdles-for-car-and-ride-sharing-startups/. 25. “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.
“Family of 6-Year-Old Girl Killed by Uber Driver Settles Lawsuit,” ABC7 News, July 14, 2015, http://abc7news.com/business/family-of-6-year-old-girl-killed-by-uber-driver-settles-lawsuit/852108/. 18. “Uber’s Marketing Program to Recruit Drivers: Operation SLOG,” Uber, August 26, 2014, https://newsroom.uber.com/ubers-marketing-program-to-recruit-drivers-operation-slog/. 19. Laurie Segall, “Uber Rival Accuses Car Service of Dirty Tactics,” CNN Money, January 24, 2014, http://money.cnn.com/2014/01/24/technology/social/uber-gett/. 20. Mickey Rapkin, “Uber Cab Confessions,” GQ, February 27, 2014, http://www.gq.com/story/uber-cab-confessions. 21. Ryan Lawler, “Lyft Launches in 24 New Markets, Cuts Fares by Another 10%,” TechCrunch, April 24, 2014, https://techcrunch.com/2014/04/24/lyft-24-new-cities/. 22. Kara Swisher, “Man and Uber Man,” Vanity Fair, December 2014, http://www.vanityfair.com/news/2014/12/uber-travis-kalanick-controversy. 23. Sara Ashley O’Brien, “15 Questions with… John Zimmer,” CNN, http://money.cnn.com/interactive/technology/15-questions-with-john-zimmer/. 24.
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.
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
Kalanick and his partner, Ryan Graves, grinned; the crowd was stunned. While Uber had “Heaven,” Kalanick also held court over “Hell.” That was the nickname of one of Uber’s most highly guarded and extremely valuable internal programs; “Hell” was devised to monitor the locations of all Uber drivers who also drove for Lyft. Uber employees at headquarters would create fake Lyft accounts, which tracked nearby vehicles—up to eight per fake account. Information about those vehicles was then sent back to Uber and stored in a database. “Hell” created a way for Uber to monitor the real-time positions of Lyft drivers. And because many of those drivers worked for Uber as well, Uber could monitor the rates Lyft was offering for drivers and outbid them, thereby swaying drivers to work more regularly for Uber. “Hell,” as Sullivan saw it, was sneaky.
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.
NOTES PROLOGUE xiii Hales had promised: Karen Weise, “This Is How Uber Takes Over a City,” Bloomberg Businessweek, June 23, 2015, https://www.bloomberg.com/news/features/2015-06-23/this-is-how-uber-takes-over-a-city. xiv built into the cement floor: Max Chafkin, “What Makes Uber Run,” Fast Company, September 8, 2015, https://www.fastcompany.com/3050250/what-makes-uber-run. xv would later tell reporters: Weise, “This Is How Uber Takes Over a City.” xiv the advertisements said: Alyson Shontell, “10 Ads That Show What A Circus the War Between Uber and Lyft Has Become,” Business Insider, August 13, 2014, https://www.businessinsider.com/10-uber-lyft-war-ads-2014-8#heres-a-similar-ad-that-suggests-ubers-are-better-than-taxis-9. Chapter 1: X TO THE X 3 according to a letter: Kara Swisher and Johana Bhuiyan, “Uber CEO Kalanick Advised Employees on Sex Rules for a Company Celebration in 2013 ‘Miami Letter,’ ” Recode, June 8, 2017, https://www.recode.net/2017/6/8/15765514/2013-miami-letter-uber-ceo-kalanick-employees-sex-rules-company-celebration. 4 “fast-growing”, “pugnacious”, a “juggernaut”: Kara Swisher, “Man and Uber Man,” Vanity Fair, November 5, 2014, https://www.vanityfair.com/news/2014/12/uber-travis-kalanick-controversy. 6 a noun coined in 2013: Aileen Lee, “Welcome to the Unicorn Club: Learning From Billion-Dollar Startups,” TechCrunch, October 31, 2013, https://techcrunch.com/2013/11/02/welcome-to-the-unicorn-club/. 6 under fire for emails: Sam Biddle, “ ‘Fuck Bitches Get Leid,’ the Sleazy Frat Emails of Snapchat’s CEO,” Valleywag, May 28, 2014, http://valleywag.gawker.com/fuck-bitches-get-leid-the-sleazy-frat-emails-of-snap-1582604137. 6 Dropbox and Airbnb: Jack Morse, “Bros Attempt to Kick Kids Off Mission Soccer Field,” Uptown Almanac, October 9, 2014, https://uptownalmanac.com/2014/10/bros-try-kick-kids-soccer-field. 11 “philosophy of work”: Brad Stone, The Upstarts: How Uber, Airbnb, and the Killer Companies of the New Silicon Valley Are Changing the World (New York: Little Brown, 2017). 11 Fourteen core leadership principles: “Leadership Priciples,” Amazon, https://www.amazon.jobs/principles. 13 employee explained the term: Alyson Shontell, “A Leaked Internal Uber Presentation Shows What the Company Really Values in Its Employees,” Business Insider, November 19, 2014, https://www.businessinsider.com/uber-employee-competencies-fierceness-and-super-pumpedness-2014-11.
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.
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. “For a company so confident that it’s a single-horse race, they’ve historically been quite scared of us,” says Zimmer. As Lyft has discussed stakes with investors, he says, Uber has “tried to talk to whoever we’re talking to, somehow knowing sometimes pretty close to when we’re talking to them and sometimes offering discounts, as long as they agree not to invest in us.”
Gupta says that as Uber builds critical mass in a city, the volume of rides drives a virtuous cycle of efficiency, enabling Uber to eliminate the guarantees and become profitable. By early 2016 Uber was profitable in 108 cities, about a fourth of the total. 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.
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 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.
If we’ve drawn the map correctly, all of its components will show up in other companies that are building twenty-first-century services. A BUSINESS MODEL MAP OF UBER AND LYFT One company at the center of many emerging trends is Uber, a center it shares with Lyft, its biggest competitor in the United States; Didi Chuxing in China; and other on-demand car companies around the world. Matt Cohler, an early Facebook employee turned venture capitalist who became an early investor in Uber, noted that the smartphone is becoming “a remote control for real life.” Uber and Lyft drive home the notion that the Internet is no longer just something that provides access to media content, but instead unlocks real-world services. Uber began as so many startups do, not as a transformative big idea but just with an entrepreneur “scratching his own itch.”
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. Drivers provide their own cars, earning additional income from a resource they have already paid for that is often idle, or allowing them to help pay for a resource that they are then able to use in other parts of their lives. Meanwhile, Uber and Lyft avoid the capital expense of owning their own fleets of cars. Passengers Who Expect Transportation On Demand. Much as Michael Schrage outlined in Who Do You Want Your Customers to Become?, Uber and Lyft are asking their consumers to become the kind of people who expect a car to be available as easily as they had previously come to expect access to online content.
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
How Is that Possible?” Slate, July 6, 2015. http://www.slate.com/articles/business/moneybox/2015/07/airbnb_disrupting_hotels_it_hasn_t_happened_yet_and_both_are_thriving_what.html. 30. Jennifer Surane, “New York’s Taxi Medallion Business Is Hurting. Thanks to Uber and Lyft.” Skift, July 15, 2015. http://skift.com/2015/07/15/new-yorks-taxi-medallion-business-is-hurting-thanks-to-uber-and-lyft. 31. Josh Barro, “Taxi Mogul, Filing Bankruptcy, Sees Uber-Citibank Plot,” New York Times, July 22, 2015. http://www.nytimes.com/2015/07/23/upshot/taxi-mogul-filing-bankruptcy-sees-a-uber-citibank-plot.html?abt=0002&abg=1. 32. Andrey Fradkin, “Search Frictions and the Design of Online Marketplaces,” September 30, 2015. http://andreyfradkin.com/assets/SearchFrictions.pdf. 33. Thomas Piketty, Capital in the 21st Century (Cambridge, MA: Harvard University Press, 2014), 571. 34.
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. Although often in the news because of the bruising battles it has waged with Uber for market share, Lyft projects a decidedly kinder and gentler feel than their larger competitor, even as they have graduated from the giant pink mustaches to a more subtle branding strategy. Their co-founder and president John Zimmer, with whom I have had many fascinating conversations over the years, has famously said that he doesn’t see Lyft as competing with Uber, but rather, as competing with “people driving alone.”13 “For me, personally, it was my interest in hospitality,” Zimmer told me, when I asked him about his motivation for starting Lyft. “There are two main pieces in hospitality success: providing an amazing, delightful experience, and having high occupancy.
Around the world, governments spend billions of dollars building elaborate public transit systems, often imposing crippling costs of both money and inconvenience on their city economies. Could apps like Lyft promise a different approach to building urban transportation infrastructure, foreshadowing a new kind of crowd-based public-private partnership, one that uses digital technology to tap into decentralized excess capacity rather than creating new monolithic centralized systems? The Rise of the On-Demand Workforce One of the things that set Lyft and Uber apart from Airbnb is that the weekly time commitment of their “providers”—the folks who are sharing their time and assets to provide a service through the platform—is markedly higher. Although David Estrada, Lyft’s (then) head of government relations, told me in 2014 that two-thirds of Lyft’s drivers drive less than 15 hours a week, that’s still a number approaching what might be considered a “part-time occupation” of sorts.
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
co.uk/terms, archived at https://perma.cc/XTH7-Q8V4) attempts to set up functionally equivalent legal structures. 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 (!)
., Paul Krugman, ‘Robot geometry (very wonkish)’, Financial Times (20 March 2017), https://krugman.blogs.nytimes.com/2017/03/20/robot-geome- try-very-wonkish, archived at https://perma.cc/KGF7-YKRS; Robert Gordon, The Rise and Fall of American Growth (Princeton University Press 2016). 71. Uber contests these allegations: Mike Isaac, ‘How Uber deceives the authorities worldwide’, The New York Times (3 March 2017), http://www.nytimes. com/2017/03/03/technology/uber-greyball-programme-evade-authorities. html?_r=1, archived at https://perma.cc/G48X-RUV7; Julia Carrie Wong, ‘Greyball: how Uber used secret software to dodge the law’, The Guardian (4 March 2017), http://www.theguardian.com/technology/2017/mar/03/uber- secret-programme-greyball-resignation-ed-baker, archived at https://perma. cc/CVR6-BR3R; Amir Efrati, ‘Uber’s top secret “Hell” program exploited Lyft’s vulnerability’, The Information (12 April 2017), http://www.theinformation .com/ubers-top-secret-hell-programme-exploited-lyfts-vulnerability, archived at https://perma.cc/7TQX-UJ4M; Julia Carrie Wong, ‘Uber’s secret Hell program violated drivers’ privacy, class-action suit claims’, The Guardian (25 April 2017), http://www.theguardian.com/technology/2017/apr/24/uber-hell-programme- driver-privacy-lyft-spying, archived at https://perma.cc/35ZK-DVKC 72.
Ryan Calo and Alex Rosenblat, ‘The taking economy: Uber, information, and power’ (2017) Working Paper, 40. 46. Shu-Yi Oei and Diane Ring, ‘Can sharing be taxed?’ (2016) 93(4) Washington University Law Review 989, 1056ff. 47. Miriam Cherry, ‘Beyond misclassification: the digital transformation of work’ (2016) 37(2) Comparative Labor Law and Policy Journal 577, 586 (citations omitted). 48. Chris, ‘DUI rates decline in Uber cities’, Uber Newsroom (6 May 2014), https:// newsroom.uber.com/us-illinois/dui-rates-decline-in-uber-cities/, archived at https://perma.cc/GN7W-YLNN. Drink driving became one of the key argu- ments used by ride-sharing advocates once Uber and Lyft ceased to operate in Austin, Texas: Lindsay Liepman, ‘DWI arrests spike after Uber/Lyft leave Austin’, CBS: Austin (23 June 2016), http://keyetv.com/news/local/dwi-arrests-spike- after-uberlyft-leave-austin, archived at https://perma.cc/E5A3-9KAP 49.
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
Charles, Illinois; and Miami. In Boston in January 2015, an Uber driver was attacked by an off-duty police officer.18 Research comparing the experiences of for-hire drivers in New York and Boston found that a number of Uber drivers carried weapons, in violation of Uber policy, or employed neutralization strategies, such as refusing to engage with passengers, to protect themselves.19 Many of these physical assaults were caught on camera and posted to YouTube, quickly going viral and drawing public outrage. A Miami doctor who assaulted her Uber driver was fired from her hospital, and an Orange County Taco Bell executive who beat up his Uber driver was also fired. But these are only the incidences that are caught on tape. Cameras are not required by Uber or Lyft, and many drivers, whether owing to the expense or to concerns about the legality of the cameras, don’t have them.
New York: Vintage. Wingfield, Nick, and Mike Isaac. 2015. “Seattle Will Allow Uber and Lyft Drivers to Form Unions.” New York Times, December 14. Wise, Scott, and Jon Burkett. 2016. “‘He Was Trying to Kill Me’: Uber Driver Attacked on I-95.” WTVR.com, April 25. Worstall, Tim. 2016. “US Median Household Income Is Now Back to Pre-recession Peak.” Forbes, August 8. Worthman, Jenna. 2011. “With a Start-Up Company, a Ride Is Just a Tap of an App Away.” New York Times, May 3. Wright, Colleen. 2015. “Uber Says Proposed Freeze on Licenses in New York City Would Limit Competition.” New York Times, July 1. Young, Maggie. 2016. “I Was Sexually Assaulted by My Uber Passenger.” Bustle, February 26. Youshaei, Jon. 2015. “The Uberpreneur: How an Uber Driver Makes $252,000 a Year.” Forbes, February 4. Yuhas, Alan. 2015.
Sleeping with a passenger is a violation of Uber rules, but the freedom to do so highlights the flexibility of the app. A driver who rents a yellow taxicab for a shift has a limited amount of time to earn back that cost. The driver of a black car has a dispatcher to contend with and a preset shift. But as the Uber advertisements remind potential workers, when one drives with Uber, this means: “No shifts, no boss, no limits.” As a result, drivers can log out of the platform, and then log back in a few minutes or hours later. The flexibility of the app makes sleeping with passengers much more possible than a traditional car service does. How often do app-based drivers have sex with their passengers? It’s hard to say, and it’s doubtful that Uber or Lyft will be researching or publicizing such statistics anytime soon.
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
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. Why a New Generation of Uber for X Businesses Rejected the Uber for X Model. Fast Company.
Abe’s solution to this problem was to drive around with a megaphone. One of his fellow protestors leaned out the back window announcing, in the tone and cadence that someone might use during a fire drill, “Do not use Uber. Use Lyft or Sidecar. Take a cab. Take the bus.” Another video Abe posted in the Uber Freedom Facebook group showed a driver pulling up to another car. He rolled down his window. “You work Uber?” the driver asked, in broken English. The other driver confirmed that yes, he did. “This weekend is a strike, you know? I work Uber too. This weekend, strike. Only Lyft, no Uber.” The other driver started to drive away, but the man filming the video kept yelling at him. “No Uber! Fuck Uber!” At a victory dinner later that night, Abe watched himself on the local news. A few days later, the tech blog Pando published a story headlined “The Medium Is the Movement: Abe Husein Is a Labor Leader for Our Times.”8 From the outside, Abe’s strike looked like a genuine, grassroots effort to stand up to a giant company.
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. Invariably, mainstream media coverage of the memo did.25 Never mind that, as a US senator in 2007, President Obama had introduced legislation that proposed closing a loophole employers used to classify their employees as contractors.
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
To dig into these dynamics a bit more deeply, let’s turn to the sharply contrasting ways that Uber and Lyft—two ridesharing apps with very similar businesses—are managing their new power communities. This juxtaposition tells us a lot about the connections among platforms, super-participants, and participants, and the factors that can bring them closer together, or drive them farther apart. ORGANIZING PICKETS VS. ORGANIZING PICNICS: THE BIG DIFFERENCE BETWEEN UBER AND LYFT The battle of Uber vs. Lyft has become the Coke vs. Pepsi of the new power economy. The two companies are both chasing the same drivers and riders. They live in fierce and unfriendly competition, with Uber well ahead, having scaled much faster and expanded globally, leading to a valuation over ten times that of Lyft, but with Lyft posing a real threat in some of Uber’s biggest markets. The functionality of the two platforms is very similar.
“your friend with a car”: Dimosthenis Kefallonitis, “Lyft.me, Your Friend with a Car,” Consumer Value Creation, January 22, 2014. Uber is defined by its remoteness: Alanna Petroff, “The Rise and Fall of Uber CEO Travis Kalanick,” CNNMoney, June 21, 2017. “The reason Uber”: Chris Smith, “Uber Wants to ‘Get Rid of the Dude in the Car’ with Driverless Taxi Service,” TechRadar, May 8, 2014. It all began when Uber: Caroline O’Donovan, “Uber Just Cut Fares in 80 North American Cities,” BuzzFeed, January 9, 2016. “In true Uber fashion”: Harry Campbell, “Uber to Cut Rates in More Than 100 Cities,” The Rideshare Guy (blog), January 8, 2016. www.therideshareguy.com. “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.
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.” Not so for Uber. These differences have a real impact on drivers—who, according to Campbell, largely prefer to drive for Lyft—as well as an interesting effect on the rider-driver relationship.
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
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?
See Peer organizations See also Platforms Summers, Larry, 116 Supply, right-sizing, 37–38 Surge pricing, 129–130 Sustainability, 255–256 Global Forest Watch, 228, 230–232 opening strategy for peer review, 179–180 smartphones as platform, 87 Unilever, 226–228 See also Climate change Taxes, 159–160 carbon, 95, 192, 247 funding public goods, 200 paying for universal benefits, 192 Taxis, regulation, vs. Uber, 149–151. See also G-Auto, Lyft, Uber Taxpayers, and open standards, 147 Tcherneva, Pavlina R., 196 Technology and changing need for regulation, 149–153 features, 14 platforms replacing people, 187 resulting unemployment, 191 Telemedicine, 81–82 Tesla, 177–178 Theses, three building blocks, 11–12 Thinking, Fast and Slow, 86 3-D printers, as peer industry, 176 3D Robotics, 53–54 350.org, 232–233 Timing, key criterion for success, 56 TopCoder, 66, 83 Torvalds, Linus, 109–110, 208 Trade School, 203–204 Transaction cost, zero, 13–14 Transparency, 129–133. See also Openness Transportation and CO2 emissions, 93–94 innovation. See BlaBlaCar; G-Auto; GoLoco; LaZooz; Lyft; Ridesharing; Uber; Zipcar urban, 7–9, 188–189 Trip chaining, 30 Trulia, 41 Tunisia, mesh network, 246–247 “Turn Down the Heat: Why a 4°C Warmer World Must Be Avoided,” 90 Twitter and political activism, 83–84 shutting down APIs, 120–121 Uber benefits to peers, 50–51 disgruntled drivers, 123, 253–254 “everybody welcome” phase, 111–112 regulation, vs. taxis, 149–151 surge pricing, 129–130 and user choice, 141 UK National Health Service, 144–145 Unemployment, through automation, 191 Unilever, 226–229 United States Army, opening to innovation, 169–170 User choice, 141–142 uShip, 94 Value, shared, 201–202 Van Schewick, Barbara, 140–141 Veniam, 276 Venture capitalists, different worldviews, 10–11 Vidal, Christophe, 176 Volunteer coordinators, 210–211 Von Ahn, Luis, 27–28, 78–80 Wages, and productivity, 196–197, 197 Wales, Jimmy, 110 Waze, 30–31, 70 Weather Channel, The, 41 WhatsApp growth compared to Skype, 112–113 number of users, 77 use of existing structure, 46, 76–77 Whitney, Patrick, 80 WiFi, additional spectrum, 147 Wikipedia, early development, 110 Woolard, Caroline, 203–204 Worker protection laws, 156 World Bank climate change report, 90–91 World Resource Institute.
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.
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.
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
Payment is automatic unless you want to change your payment. 190 Source various, including Oxford Dictionaries http://www.oxforddictionaries.com/definition/english/taxi 191 Bregman, Susan (2015-04-23) Uber and Lyft claim carpooling success. TheTransitWire.com. http://www.thetransitwire.com/2015/04/23/uber-lyft-claim-carpooling-success/ 192 DeAmicis, Carmel (2015-07-18) How Didi Kuaidi Plans to Destroy Uber in China. Re/Code. http://recode.net/2015/07/18/how-didi-kuaidi-plans-to-destroy-uber-in-china/ 193 A longer discussion of our skepticism is here: Levinson (2014-12-01) "It is a Small Market After All" Transportationist blog. http://transportationist.org/2014/12/01/its-a-small-market-after-all-es-gibt-einen-kleinen-markt-uber-alles/ 194 French, Sally (2015-07-01) "An 8-year-old's take on 'Uber for kids'" MarketWatch https://secure.marketwatch.com/story/an-8-year-olds-take-on-uber-for-kids-2015-07-01 195 Zimmerman, Eilene (2016-04-13) "Ride-Hailing Start-Ups Compete in ‘Uber for Children’ Niche” New York Times. http://www.nytimes.com/2016/04/14/business/smallbusiness/ride-sharing-start-ups-compete-in-uber-for-children-niche.html 196 Hatmaker, Taylor (2014-09-08) "Taxi service by women for women launching in New York."
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. As these services become widespread, humans will undoubtedly develop new forms of elitism. Venture capitalists believe these will be very successful companies. Uber has been valued at over $40 Billion.
A taxi is "a car licensed to transport passengers in return for payment of a fare, usually fitted with a taximeter."190 So for taxicabs, the arrangement between the rider and the passenger is mediated by the government (which licenses the vehicles). Are Lyft drivers licensed to transport passengers for payment? This is a major point of contention. They are licensed drivers, and any licensed driver (above a certain age and level of experience) is eligible to carry passengers. The cars are private cars (at least sometimes) though that is little different than how taxis operate in other parts of the world. Many Singaporean taxi drivers will take fares when going between where they are going anyway, but otherwise treat the taxis as a personal vehicle. Lyft now does jitney (shared taxi, dollar van, informal transport) type services, dubbed Lyft Line. (Uber has the similar UberPool) These serve either one pickup going to multiple destinations, or multiple pickups going to one destination, or multiple origins to multiple destinations, and compete with both taxi and public transit.
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.
Chris Gayomali, “The Two Startups that Joined the $40 Billion Club in 2014,” Fast Company, December 30, 2014, http://www.fastcompany.com/3040367/the-two-startups-that-joined-the-40-billion-club-in-2014. 2. Kara Swisher, “Man and Uber Man,” Vanity Fair, December 2014; Jessica Kwong, “Head of SF Taxis to Retire,” San Francisco Examiner, May 30, 2014; Alison Griswold, “The Million-Dollar New York City Taxi Medallion May Be a Thing of the Past,” Slate, December 1, 2014, http://www.slate.com/blogs/moneybox/2014/12/01/new_york_taxi_medallions_did_tlc_transaction_data_inflate_the_price_of_driving.html. 3. Swisher, “Man and Uber Man.” 4. Zack Kanter, “How Uber’s Autonomous Cars Will Destroy 10 Million Jobs and Reshape the Economy by 2025,” CBS SF Bay Area, sanfrancisco.cbslocal.com/2015/01/27/how-ubers-autonomous-cars-will-destroy-10-million-jobs-and-reshape-the-economy-by-2025-lyft-google-zack-kanter/. 5. Swisher, “Man and Uber Man.” 6. Marc Andreessen, “Why Software Is Eating the World,” Wall Street Journal, August 20, 2011, http://www.wsj.com/articles/SB10001424053111903480904576512250915629460. 7.
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. We’ll look at ownership and its alternatives in more detail in Chapter 5.
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. 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. 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. A Baidu driverless car prototype.
Fleets of self-driving vehicles could, he says, replace all car, taxi and bus trips in a city, providing as much mobility with far fewer vehicles” says Luis Martinez of the International Transport Forum, a division of the OECD. A January 2013 Columbia University study suggested that with a fleet of just 9,000 autonomous cars, Uber could replace every taxicab in New York City, and that passengers would wait an average of 36 seconds for a ride that costs about $0.50 per mile. Such convenience and low cost would make car ownership a dubious financial choice. A 2010 report from UC Berkeley’s Transportation Sustainability Research Center found that one car-share vehicle could remove 9 to 13 vehicles from the road, either because households decided to ditch their personal automobile or significantly delay the purchase of one. One survey suggests that every car added to the fleets of Uber and Lyft leads to 32 fewer car sales, meaning potential “lost sales” by 2020 of over 1 million cars. While that only looks at changes in car purchasing in selected urban areas, and doesn’t take account of any changing usage patterns, brought about by driverless cars, that might increase VMT, it is enough to make car manufacturers sit up and take notice.
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
Figure 3.4: Screenshot of House of Cards opening credits: a city devoid of people. Source: Netflix. Figure 4.1: Cow Clicker Screenshot. 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.
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.
Ibid., 89–90. 30. Markoff, Machines of Loving Grace, 68–75. 31. “Radio 4 Revives Hitchhiker’s Game,” 4. 32. Belsky, “The Interface Layer.” 33. Kleinman, “You’re Allowed to Tip Your Uber Driver (and Maybe You Should)”; “Do I Need to Tip My Driver?” 34. Knack, “Pay As You Park.” 35. Stein, “Baby, You Can Drive My Car.” 36. Lawler, “Lyft-Off.” 37. See an extensive list of such incidents at: “The Comprehensive List of Uber Incidents, Assaults and Accusations.” 38. Wortham, “Ubering While Black”; Rivoli, Marcius, and Greene, “Taxi Driver Fined $25K for Refusing Ride to Black Family.” 39. Wortham, “Ubering While Black.” 40. Sandvig, “Seeing the Sort: The Aesthetic and Industrial Defense of ‘The Algorithm.’” 41. Carruth, “The Digital Cloud and the Micropolitics of Energy,” 342. 42. Much of the following section is based on McClelland’s remarkable exposé of cloud warehouse labor practices: McClelland, “I Was a Warehouse Wage Slave.” 43.
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 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. Operation SLOG reportedly began with in-person meetings between drivers and Uber high-level marketing staff, and the ongoing encouragement included emails with pep talks and follow-up instructions.
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? Come to think of it, why shouldn’t any company that wanted to gain an edge over a competitor do this? It made intuitive sense on a business level, especially given how focused most American companies were on near-term results. In the long term, of course, the idea had the potential to turn the rapacious tendencies of capitalism against itself, by tricking corporations into underwriting the growth of the labor movement.
The spurious notion Jill Lepore, “The Disruption Machine,” New Yorker, June 23, 2014; Samantha Murphy, “Facebook Changes Its ‘Move Fast and Break Things’ Motto,” April 30, 2014, mashable.com; Katy Waldman, “Let’s Break Shit: A Short History of Silicon Valley’s Favorite Phrase,” December 5, 2014, slate.com. No More Woof Marc Lallanilla, “Speak, Fido: Device Promises Dog Translations,” January 3, 2014, livescience.com. Here again Uber pointed the way Erica Fink, “Uber’s Dirty Tricks Quantified: Rival Counts 5,560 Canceled Rides,” August 12, 2014, cnn.com. Operation SLOG Casey Newton, “This Is Uber’s Playbook for Sabotaging Lyft,” August 26, 2014, theverge.com. launched with $50 million in cash Amy Schatz, “Pressing Fwd.us: How Silicon Valley’s $50 Million Bet on Immigration Stalled,” October 15, 2014, recode.net. spent nearly $2 million on lobbying Senate Office of Public Records via opensecrets.org. The Zuckerberg-backed group Joshio Meronek, “Mark Zuckerberg’s Immigration Hustle,” March 12, 2015, fusion.net; Matt Smith, Jennifer Gollan, and Adithya Sambamurthy, “Job Brokers Steal Wages, Entrap Indian Tech Workers in US,” October 27, 2014, revealnews.org.
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
For example, Yelp, Facebook, LinkedIn, TripAdvisor, and Pinterest depend entirely on intangible contributions from the network. 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.
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.
—Mark Fields, CEO, Ford Motor Company VISUALIZING YOUR ORGANIZATION AS A DIGITAL NETWORK, even in a small portion of the business, is a similar leap to the one made fifteen or more years ago by every great leader telling her teams and boards, “We need to get our organization online.” Most people did not know what that meant, but the best made the leap. To be sure, every industry is undergoing a change, including those grounded in physical assets—transportation and lodging. You’ve heard of Uber, and probably Lyft, and maybe even their car-sharing grandparent Zipcar—not to mention Getaround, RelayRides, Greenwheels, GoCar, and many more. Car sharing and driving-as-a-service are available in more than a thousand cities around the world. The accessibility and convenience of these options are a threat to the car industry as well as the taxi and limousine industries, as millennials seem happy to get around without either a driver’s license or car ownership.
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
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?_r = 0. Jay Hathaway, “Uber Turned on Surge Pricing for People Fleeing Sydney Hostage Scene,” December 15, 2014, http://gawker.com/uber-turned-on -surge-pricing-for-people-fleeing-sydney-1671193132; Brian Ries & Jenni Ryall, “Uber Intros Surge Pricing during Sydney Hostage Siege, Then Notes to Pages 51–52 27. 28. 29. 30. 31. 32. 275 Backtracks after User Outcry,” December 15, 2014, http://mashable.com/2014 /12/14/uber-sydney-surge-pricing/#lnLL3YYzXSqM.
Instead, under its “[n]o cash, no tip, no hassle” policy, Uber’s algorithm sets the price and automatically charges the passenger’s credit card on fi le.22 Uber takes between 20 and 25 percent of the fare; the driver gets the rest.23 Uber’s dynamic pricing algorithm provides passengers a baseline standard fare, which increases when consumer demand in a location exceeds the supply of available drivers.24 For example, during a New York snowstorm, some rides on Uber cost 8.25 times more than normal.25 Controversially, the algorithm was also reported to have implemented significant surge fees of up to four times the normal rate when demand for rides escalated in the midst of a hostage situation in downtime Sydney. 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.
The super-platform needs the apps to attract users, but, once it becomes powerful, it can harm the independent app developer in many ways. The super-platform at any moment may favor its own operations downstream over those provided by Uber. To put it differently, Uber’s biggest nightmare is not some obnoxious taxi commissioner seeking to hold on to a crumbling monopoly by refusing Uber entry into his city, nor is it another carservice platform like Lyft. The real fright comes from super-platforms like Google and Apple. Consumers may benefit from Uber’s fright when Uber improves ser vice, maintains competitive prices, and increases its investment in research and development. But Uber also sees the long shadow of the super-platforms, and realizes that it will likely be at a significant competitive disadvantage over the long run. Uber must now develop its own driverless car technology (or partner with a car manufacturer that does).
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.
Andrew J. Hawkins, “The Boring Company’s Chicago Project Seems Awfully Cheap for Something So Big.” The Verge, June 14, 2018. https://www.theverge.com/2018/6/14/17464612/boring-company-chicago-elon-musk-cost-estimate 21. Bruce Schaller, “The New Automobility: Lyft, Uber and the Future of American Cities.” Schaller Consulting, July 25, 2018. http://www.schallerconsult.com/rideservices/automobility.pdf 22. Yves Smith, “Uber Is Headed for a Crash.” New York, December 4, 2018. http://nymag.com/intelligencer/2018/12/will-uber-survive-the-next-decade.html 23. California Air Resources Board, “2018 Progress Report: California’s Sustainable Communities and Climate Protection Act.” November 2018. https://ww2.arb.ca.gov/sites/default/files/2018-11/Final2018Report_SB150_112618_02_Report.pdf 24.
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.
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
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. Uber drivers, 60 percent of whom have other jobs, have become prime examples for what became known as the “gig economy.”
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. In the United States, Uber had about 70 percent of ride hailing and Lyft, 30 percent. Internationally, in addition to DiDi, other major players have emerged, including Gett in Europe and Ola in India. Overall, ride hailing could be a very big industry. But the industry still had a major challenge—to prove that it could be profitable. In May 2019, Uber went public with an $82 billion valuation. But the costs of running it were greater than its revenues.
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. In the face of the inevitable counterattack, it would mobilize riders and drivers to bombard the regulators and politicians with phone calls and emails.
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
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.”
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 California Department of Fair Employment and Housing’s allegations against Airbnb are contained here: www.dfeh.ca.gov/wp-content/uploads/sites/32/2017/06/04-19-17-Airbnb-DFEH-Agreement-Signed-DFEH-1-1.pdf (accessed September 2017). 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).
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
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.
That can make for a difficult situation for drivers, who have to work to pay off the cost of their car or license, and for riders, who may complain of an insufficient number of taxis, but it’s a more transparent system than that touted by Uber, in which everything is controlled by the company. In a traditional taxi system, a city taxi commission helps look out for the interests of customers, drivers, and owners alike. There are also protections in place for customers. If you live in New York City, like I do, a taxi that picks you up in Manhattan is legally obliged to take you wherever you want to go, including to one of the other boroughs (with the meter running the whole time, of course). Unless you are violent, disruptive, or otherwise problematic, the driver can’t refuse you a ride based on your skin color or some star rating you’ve accumulated. You can also expect to pay a standard fare, unlike with Uber and Lyft, which are known to institute surge pricing to leverage high demand. Uber claims that surge pricing represents a market-based solution and offers a fair price based on availability.
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.
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
If truck drivers are no longer on the roads, all those people will feel the pain, too. Then you can look at the people who drive taxis, Ubers, and Lyfts. Many taxi drivers have already switched to driving for the ride-sharing companies, but when robotaxis and self-driving Ubers are widespread, many of those jobs will be at risk. Some observers believe that the advent of the autonomous era could have a measurable impact on capitalism as we know it. Revenue from fuel taxes will go down, presumably to be replaced by other sources of income. Parking revenue—including fines—may well all but disappear. Speeding tickets and driver registrations will be greatly reduced. These developments are going to affect how governments make money and citizens spend it. Robin Chase, the former CEO of car-sharing company Zipcar, and now the executive chairman of vehicle-communications company Veniam, has called for a universal basic income to offset the losses that will be brought on by an era of automation.
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.
Standing behind a table with another Volkswagen-branded signboard behind him, Müller, white-haired and lean, told reporters that the company had initiated the biggest transformation in its history. VW would reshape itself to become one of the world’s leading providers of sustainable transport. “The term evolution would be too weak for what we’re facing,” Müller declared. Three weeks earlier, following GM’s investment in Lyft and on the same day that Toyota announced a strategic partnership with Uber, VW had announced that it would invest $300 million in the ridebooking app Gett. Within days of that news, the German media were reporting rumors that VW planned to spend up to $11 billion on an advanced battery factory that would rival Tesla’s Gigafactory. (In March 2018, the company announced that it would spend $25 billion to secure batteries for electric-vehicle production at sixteen of its factories.)
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
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. Didi cut back on subsidizing drivers and passengers on a large scale after the Uber battle ended, but it was still losing hundreds of millions of dollars, caught up in a cash-burn spiral of subsidies and discounts.6 The company’s goal of turning a profit in 2018 on net revenues of close to $1 billion7 evaporated as losses reached $1.6 billion that year.
This service is meant to attract a young on-the-go population who order food by mobile app. Former Uber CEO Travis Kalanick is working on a similar idea with his Los Angeles–based startup CloudKitchens, so perhaps this innovative concept will become better known in the United States. The sharing economy has arisen in China with the uptake of mobile apps and payments and a young consumer population that enjoys experimenting with new things. The appeal of ride hailing is the ability to tap on a mobile screen and secure a driver to take you where you want to go for less than a taxi fare, then step out of the car without dealing with cash. Didi has proven to be an innovator in ride hailing, a segment that has gotten a lot of attention with the recent public offerings of Uber and Lyft in the United States. One Didi service sends a driver to your personal car when you’ve had too much to drink.
Didi has been dealing with the crisis by introducing several safety measures in China that include verifying its drivers with facial recognition tests, installing emergency buttons for both drivers and passengers, and such extreme measures as using the driver’s phone to audio record trips—with the passenger’s consent—that are stored and then deleted at Didi within one week. Not sure if Uber will be trying this out in the United States. The Traffic Brain In some other realms, Didi sees a brighter horizon. The company is focusing on expanding outside China, investing more in AI systems and autonomous driving, conducting research at a Silicon Valley lab, and planning an electric vehicle network of 10 million by 2028. Like Uber and Lyft experimenting with new self-driving thrills, Didi is testing self-driving vehicles in four cities in China and the United States and has a grand plan to launch driver-less taxis soon. Robo taxis are already a reality in China—and the United States.
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.
Medallion-holding incumbents found it difficult to reverse their losses, because Uber’s two-sided network effects, smooth user interface and user experience, and ample capital were formidable advantages. Attempts to build competing platforms such as Lyft in the United States and Hailo in Europe did not slow down the fast-growing startup. The only thing that could, it sometimes seemed, was regulation. Utility Players? The legality of the Uber platform has been challenged around the world, and new rules and statutes about transportation services have been proposed and passed. It is sometimes hard to avoid the impression that they were written with Uber and its platform peers in mind, and with the intent of handicapping them. Lawmakers in France, for example, outlawed UberX’s close relative UberPop in 2014 and imposed fines on Uber and key managers. And as of early 2017, Uber was prohibited altogether in Vancouver, Canada. In finance, as in urban transportation, regulation was at times the incumbents’ best defense against digital upstarts.
Unless this inherent information asymmetry was overcome, the market for person-to-person rides would never take off. But by March of 2016, Uber was handling 50 million rides per month in the United States. 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.
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
Though I have to admit that another part of the reason I find VIA, Uber, and their ridesharing competitors so fascinating is that so many of the people who are now working on these kinds of complex traffic problems are, like me, lapsed physicists, using sophisticated mathematics to improve the world of transportation. (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).
The concerns about business practices, which include threatening journalists and making false reservations with competitors to limit their performance, aren’t really in the same category. It’s not that they’re not important, but that they’re not integral to the ride-matching business model. Complaints that come from drivers are a little different. So long as Lyft and Uber and the others are in competition with one another, they’re going to be under pressure to cut prices, which inevitably comes out of the pockets of their drivers. And so long as they’re able to offer such great service by saturating neighborhoods with cars, they’re not just competing with other companies. Uber’s own drivers are, inevitably, competing with one another, and a significant number of them are working for what amounts to a little above minimum wage. In Los Angeles, the largest US market for the most popular service, uberX, drivers average less than $17 an hour before gas and tolls.
Salt Lake City is in the process of building eighty-seven miles of bike paths. c According to Hal Johnson, UTA’s manager of Project Development, campus parking—ten thousand total spaces—was at 96 percent capacity in the fall of 2001. By 2013, that had dropped to 70 percent, entirely because of the number of students using the University Line. d At Uber, ridesharing—people traveling from roughly the same origin to about the same destination, while splitting the cost of the trip at a discount—is rare enough that it has its own name: uberPOOL. e Lyft, the Avis to Uber’s Hertz, operates in a third as many markets. f I’m considering trademarking the term: Total gridlock™. g If you’re thinking that creative industry is another Humpty Dumpty phrase, you’re right. h One quintillion bytes. And, yes, I had to look it up. CHAPTER 8 TUXEDOS ON THE SUBWAY Transportation Anywhere, Anytime, and for Everybody MORE THAN FORTY YEARS AGO, WHEN I WAS IN GRADUATE SCHOOL AT the University of Pennsylvania, my mentor and advisor, Vukan Vuchic, often compared the state of transit systems in the United States with those in European cities.
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
“Creative destruction whips through corporate America,” Innosight Executive Briefing, winter 2012, www.innosight.com/innovation-resources/strategy-innovation/upload/creative-destruction-whips-through-corporate-america_final2012.pdf. 44. Ibid. 45. Ibid. 46. 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.
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.
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
v=UwMhGsKeYo4&t=3s. 21. Shontell, Alyson. “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’.”
Where it hurts is in the distraction among management, costing them the ability to attract and retain the best talent—where the war is won or lost in a digital age. Beyond the PR and management crises, Uber’s likability risk comes from a more fundamental place than management’s bro behavior. Uber is undoubtedly a disruptor in the great tradition of Silicon Valley disruptors. Unfortunately for Uber, the market it’s disrupting is a heavily regulated one, and Uber benefits greatly by its attitude that it is not subject to the same regulations as traditional taxis. It believes, and the market has rewarded this belief, that it can hire whomever it wants to drive, and it can charge whatever it wants. Meanwhile, its taxi competition has no such freedom in most markets. Nor does Uber necessarily play fair with its ride-sharing competitors, such as Lyft. There have been several reported incidents of Uber employees engaged in organized efforts to sabotage the competition by ordering and canceling rides from those competitors repeatedly—something like a real-world denial-of-service attack.31 At an even broader level, Uber’s business model has been attacked for undermining employment relationships and creating unstable, low-wage work that can dry up without recourse.
Meanwhile, FedEx, UPS, and DHL are about to get a lesson in disruption. Uber checks almost every box in the T Algorithm: differentiated product, access to visionary capital, global reach, big data skills. That said, beyond execution (no small thing) Uber has only one obstacle, but it is a significant one, to getting to a trillion-dollar valuation: likability. 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.
Don't Be Evil: How Big Tech Betrayed Its Founding Principles--And All of US by Rana Foroohar
"side hustle", accounting loophole / creative accounting, Airbnb, AltaVista, autonomous vehicles, banking crisis, barriers to entry, Bernie Madoff, Bernie Sanders, bitcoin, book scanning, Brewster Kahle, Burning Man, call centre, cashless society, cleantech, cloud computing, cognitive dissonance, Colonization of Mars, computer age, corporate governance, creative destruction, Credit Default Swap, cryptocurrency, data is the new oil, death of newspapers, Deng Xiaoping, disintermediation, don't be evil, Donald Trump, drone strike, Edward Snowden, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Etonian, Filter Bubble, future of work, game design, gig economy, global supply chain, Gordon Gekko, greed is good, income inequality, informal economy, information asymmetry, intangible asset, Internet Archive, Internet of things, invisible hand, Jaron Lanier, Jeff Bezos, job automation, job satisfaction, Kenneth Rogoff, life extension, light touch regulation, Lyft, Mark Zuckerberg, Marshall McLuhan, Martin Wolf, Menlo Park, move fast and break things, move fast and break things, Network effects, new economy, offshore financial centre, PageRank, patent troll, paypal mafia, Peter Thiel, pets.com, price discrimination, profit maximization, race to the bottom, recommendation engine, ride hailing / ride sharing, Robert Bork, Sand Hill Road, search engine result page, self-driving car, shareholder value, sharing economy, Shoshana Zuboff, Silicon Valley, Silicon Valley startup, smart cities, Snapchat, South China Sea, sovereign wealth fund, Steve Jobs, Steven Levy, subscription business, supply-chain management, TaskRabbit, Telecommunications Act of 1996, The Chicago School, the new new thing, Tim Cook: Apple, too big to fail, Travis Kalanick, trickle-down economics, Uber and Lyft, Uber for X, uber lyft, Upton Sinclair, WikiLeaks, zero-sum game
The Plight of the Gig Worker “Gig work” seems to have reached a new apex with the rise of companies like Uber. Consider the typical non-medallion taxi driver in New York, who might work for three or more companies at once: Uber, Lyft, and perhaps even an unlicensed cab firm. There is some truth to the claim that such people are essentially entrepreneurs, with all the freedom that working for themselves entails. With Uber, drivers set their own hours and are in a sense their own boss, something Kalanick always lauded as highly empowering. “There is a core independence and dignity you get when you control your own time,” he told me in 2015. Fair enough. But that’s about all Uber drivers are in control of. They have no say in the company’s pricing, which changes regularly depending on the level of demand and often means lowering rates to get more people into Uber cars. That varies based on the algorithm; according to my own anecdotal interviews with drivers in NYC, it has been decreasing as Uber has built its market share, and is around 20 percent now, as opposed to roughly 30 percent for the local independent cab services that some people in the neighborhood still use.
Moreover, because Uber self-identifies as a technology company rather than a transportation company, it avoids complying with protections like the Americans with Disabilities Act, that would normally apply to this type of work. In her book Uberland, the social scientist Alex Rosenblat rode five thousand miles with numerous Uber drivers in twenty-five cities across the United States and Canada. 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).
After New York Times reporter Jodi Kantor did a front-page exposé about the topic in 2014, then-chairman Howard Schultz was forced to apologize and promise to clean up the company’s scheduling system.16 Yet, at Starbucks and, alas, at most other retailers, algorithmic scheduling has become the norm—just like “surge” pricing at Uber or Lyft. Clearly, the advent of the high-tech gig economy means different things to different kinds of workers. For the Uber driver or the delivery person, it may feel like a kind of neo-serfdom. They get no pension, health insurance, or worker-rights protection, and work at the mercy of metrics. Many of the drivers profiled in Rosenblat’s book struggle to make much more than minimum wage, after paying for their car, their gas, maintenance, self-employment taxes, and so on. Certainly, in my own interviews with Uber drivers, I’ve found that most see a tight trade-off between the benefits of their theoretical freedom and the fact that always-on technology can actually mean less flexibility than they might have in a higher-quality job.
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
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.
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.
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.
This is similar to the discussion in the chapter on Enforcers of state-of-the-art reputation systems that can sometimes do a better and more efficient job of eliciting good behavior than government institutions. You might say Maples prefers to back what is righteous rather than what is legal. Why does he love pitches in that legal gray area? “Those could be good businesses to fund because a lot of times there are not a lot of competitors,” he explains. (Even though Uber has a competing ride-sharing service, UberX, Maples points out that Lyft started before Uber launched UberX.) Whether the laws eventually side with the entrepreneur’s venture or against it is a huge risk—the kind that many people are afraid to take—but that is precisely what makes the bet attractive; if it turns out to be right, the gain will be enormous and, because it is a nonconsensus venture, it won’t be shared by many others. Notice that it is also an external risk, and not an internal one: the entrepreneur has no incentive to undermine the VC’s goals by shirking, for example, because doing so would sabotage the entrepreneur.
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.
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
If you are on the board of a company, you need to keep confidential any information that you learn in the course of your tenure. We talked earlier about the opportunity costs of a VC making an investment. Among the reasons for this are that a VC can only sit on so many boards, so every time she fills up a slot on her dance card, she necessarily reduces her availability to invest in other companies. Another form of opportunity cost comes from conflicts: as a VC you can’t really invest in Facebook and Friendster or Lyft and Uber. Rather, the decision to invest in a company likely means that you are conflicted out of other companies that are directly competitive. To be clear, there is no prohibition against this, but the convention of the business makes this hard to do—as a VC you are lending your name and your firm’s brand to your investments, so it’s hard to invest in direct competitors without creating challenges for both companies in the marketplace.
Raising capital—This is an obvious one, but interestingly has declined in importance over the years as a major driver for companies to go public. It used to be that companies needed to go public because the private market tapped out pretty quickly when you started to contemplate raising $100 million-plus financing rounds. Now those are a dime a dozen, and we see some companies raising billions of dollars in the private marketplace—e.g., Uber, Lyft, Airbnb, and Pinterest, among others. There’s an ongoing chicken-and-egg debate about what created this—did the big financial players start investing in the private markets because startups were delaying going public, or did startups start delaying going public because they could raise huge sums of money in the private markets? It’s not worth debating here, other than to note that the attraction of the public markets as an important source of large capital raises is clearly diminished.
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.
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.
“Was that enough to live on in Pittsburgh?” “No.” Companies like Uber can pay their workers so little because they are often not employees. 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.
The sudden rise of gig-economy jobs in many ways feels like the apotheosis of the past half century of workplace trends. Private-equity partners and venture capitalists have shunted billions and billions of dollars to start-ups seeking to disrupt brick-and-mortar businesses, vault over workplace protections, pay peanuts, employ close to no one, and offer no benefits or job security. Uber is just the biggest and most visible of these players. Others include the freelance-services marketplace Fiverr, Uber’s ridesharing rival Lyft, the grocery delivery company Instacart, and the do-anything handyman service TaskRabbit, now part of Ikea. Nobody quite knows the size of the diverse and chaotic and fast-changing pool of workers serving these businesses, but estimates drift as high as 45 million. For all these start-ups, the basic business model is the same.
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
It knows your usage history (your home, your work, your common destinations) and uses that information to customize its service for you. And thanks to its partnership with Spotify, it even knows your favorite music. Oh, and guess what? Uber does in fact offer monthly subscriptions. Right now Uber is testing a flat-rate subscription service in several cities. Users can pay a monthly fee in exchange for bundles of reduced-rate trips with no surge pricing. In other words, Uber will cut you a deal on rides in exchange for steady business. 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.
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. Uber has your ID and all your payment particulars, and it employs usage-based pricing so that you pay for only what you use. It knows your usage history (your home, your work, your common destinations) and uses that information to customize its service for you.
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. Let’s say we offer a $500 monthly plan in which you can tap a button and get access to transportation whenever you want it, and you get to choose your room-on-wheels experience.
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.
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
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.
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.
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.
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
Former business owners become Uber’s unprotected contractors.* Market pricing and competition are replaced by a monopoly’s algorithmic price-fixing. Creative destruction? 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.
For instance, imagine a platform-independent Uber, owned by the drivers who use it. There’s no server to maintain, no venture capital to pay back, no new verticals or horizontals in which to expand, no acquisition, and no exit. There are just drivers whose labor and vehicles constitute ownership of the enterprise. One such experiment, La’Zooz, is a blockchain-managed ridesharing app, where the currency (Zooz) is mined through “proof of movement.”97 So instead of supplying and driving cars as underpaid freelancers for Uber or Lyft, drivers are co-owners of a transportation collective organized through distributed protocols. Could such platform cooperatives catch on? The basic behavior of downloading an app in order to work or rent property has already been anchored in users by Airbnb, Uber, TaskRabbit, Mechanical Turk, and countless others.
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. Pick a car based on its location, the driver’s ratings, and the estimated price. The driver finds you based on your own GPS location and your profile picture.
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
Before you use one, find out from Wikitravel if you need to be aware of any taxi scams, and which taxi companies are the most widely trusted. You can also make use of a number of taxi apps. 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.
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!
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.
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
Hot markets make it easier to attract the capital and talent (especially capital) to plow into blitzscaling. Uber is a clear example of how access to capital can fund aggressive and inefficient growth that may confer long-term strategic benefits. 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.
Just remember to save a few ships to fend off attacks from those pesky pirates! 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.
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.
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
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. The promise to customers is that you don’t need a lawn mower or washing machine or to pick up flowers, because someone else will do that for you—on your command, at your convenience, in real time—at a price you can’t refuse.
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.
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.
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
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. Sweden, where over 80 percent of all transactions are digital, is almost there.
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.
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
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.
The producers don’t have any direct interaction with the subscribers. Like Zappos, with this single-sided approach, Netflix is completely in control of its customer relationships. As a platform that enables drivers to deal directly with riders, Uber relies on its drivers to make some decisions that a single-sided firm might make for them. Uber drivers can decide when to drive and what to drive—subject to some constraints to ensure it is a good vehicle. But Uber controls the prices the drivers can charge. Technology has made it possible to apply versions of Uber’s model linking service providers to customers in a wide range of other areas. For example, HourlyNerd competes with traditional management consulting firms by linking businesses and experts. And Coursera competes with traditional universities by linking teachers and students.
It has become a leading operating system for workhouse computers and powers the core of the Android operating system for smartphones. The Android operating system for mobile phones relies on the core portion of Linux known as the kernel. 24. Leena Rao, “Ubercab takes the hassle out of booking a car service,” TechCrunch, July 5, 2010, http://techcrunch.com/2010/07/05/ubercab-takes-the-hassle-out-of-booking-a-car-service/. 25. Uber Newsroom, “Our Commitment to Safety,” December 17, 2014, http://newsroom.uber.com/2014/12/our-commitment-to-safety/; Uber, “60 Countries: Available Locally, Expanding Globally,” https://www.uber.com/cities. 26. Google Inc., “Form 10-K for the Period Ending December 31, 2014,” http://investor.google.com/pdf/20141231_google_10K.pdf; Greg Sterling, “Report: Google had $12 billion in Mobile Search Revenue, 75 Percent from iOS,” Marketing Land, May 28, 2015, http://marketingland.com/report-google-had-12-billion-in-mobile-search-revenue-75-percent-from-ios-130248; Facebook Inc., “Form 10-Q for the Period Ending March 31, 2015,” http://investor.fb.com/common/download/sec.cfm?
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 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. It is worth noting here that the kinds of trade unions that exist today have come quite far from the early forms of unions.
Even more troubling is the fact that some platform companies even seek to evade the rules that clearly do apply to them. Uber’s South African entity (Uber Technologies SA) was recently taken to the Commission for Conciliation, Mediation and Arbitration (CCMA) by a trade union on behalf of some Uber drivers who were ‘deactivated’ from the platform.9 The union demanded that Uber Technologies recognize drivers as employees and so give workers the protections afforded to employees under South African labour law. Uber appealed the decision at the Labour Court. The court decided that the case could not proceed – not because it had no merit, but rather because the claim was made against the wrong Uber entity. It turns out that Uber International Holding(s) BV, a company based in the Netherlands, owns the Uber software application, and, as such, all South African drivers are in a contract with Uber BV rather than Uber SA.
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
And what will happen to all of the small towns built off the trucking economy?” Driverless Ubers may indeed threaten the gig economy freelancers we met earlier—the schoolteachers who drive for rideshare services in order to pay their bills. (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.
., 71, 85 Gates, Bill, 226 Gender “class ceiling,” 10, 31 devaluation framework of care work, 76–77, 128–29 motherhood bias, 5–6, 10, 31 pay gap, 16, 51, 76, 104, 151–52 “precarious manhood” theory, 150–51, 262 rethinking traditional roles, 262 TV and, 220–21 Uber and Lyft driver-teachers, 150–51 Gender Equality Law Center (GELC), 29, 30 Geography and basic budget threshold, 99 Georgetown University, 56 George Washington University, 57 Germany day care, 80 parental leave, 26 Gerson, Kathleen, 75, 196 Gifted-and-talented programs, 135, 136 Gig economy, 147–63, 172. See also Uber teacher-driver-fathers “Glass ceiling,” 10, 29 “Global care chain,” 112 Globalization, 183 Global Wealth Report, 7 Goffman, Erving, 28 GoFundMe, 62, 152 Goldman, Belle, 183–84 Goldstein, Dana, 82–83 Goodwill, 33, 35 Gothamist, 183 Gould, Elise, 253 Great Britain.
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. Also, the devaluing of caring professions doesn’t just hurt women like those you’ve met in the preceding chapters.
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.
Garrett’s first company, StumbleUpon, was four syllables, often misspelled by its users, and Garrett learned from the experience how much easier it is for a product to spread when you spend some time focused on the concept and brand first. Ever since, the companies he has cofounded, like Uber, Spot, and Mix, all started with a simple concept around discoverability and accessibility—and brands that were straightforward, memorable, and easy to associate with a new meaning. When developing new products, Garrett develops a narrative, which includes the overall concept and brand, even before hiring a team. For the concept, Garrett focuses on something that was small and accessible only to some people—like using a private driver or accessing great restaurants—and then imagines what the world would look like if such experiences were discoverable and accessible to everyone. For Uber, the narrative of allowing anyone to summon (or be) a personal driver was the kernel that preceded even the first inkling of the product.
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
Whereas firms once had to spend large amounts to invest in the computing equipment and expertise needed for their businesses, today’s start-ups have flourished because they can simply rent hardware and software from the cloud. 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).
Facebook’s own services would be provided for free, but other services would have to partner with Facebook and go through its platform, effectively enclosing the entirety of the internet into Mark Zuckerberg’s silo.31 While rejected in India, the Free Basics service is now active in 37 countries and used by over 25 million people.32 Uber is also effectively building up a system that funnels passengers into its system. The decreased demand for non-Uber cabs means a decreased supply of non-Uber drivers, as more and more of the services move onto Uber. As more passengers turn to Uber’s platform, non-Uber cab drivers will lose out and be forced onto Uber’s platform if they are to survive. The same holds for passengers: as fewer non-Uber cabs roam the streets, the only way to guarantee a cab will eventually be through Uber’s platform. The field of industrial platform is also almost certain to resolve into a series of enclosed spaces, as Siemens and GE are unable (and unwilling) to communicate with each other.
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
THE FUTURE: FROM UBER TO SUBER We’ve covered a lot of ground in this chapter. Now let’s pull all the strands of innovation together in just one scenario. Consider service aggregators like Uber and Lyft. Uber is an app-based ride-sharing network of drivers who are willing to give other people a lift for a fee. To use Uber, you download the Uber app, create an account, and provide Uber with your credit card information. When you use the app to request a car, it asks you to select the type of car you want and marks your location on a map. The app will keep you posted on the availability and whereabouts of your prospective driver. At the end of the ride, Uber automatically charges your credit card. If you don’t want to give the default tip, then you need to change your billing settings on Uber’s Web site.29 Uber Technologies, Inc., the company behind the development and operation of the Uber app, retains a share of the price paid for every ride.
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.
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. Others aggregate equipment and handymen through their centralized, proprietary platforms and then resell them. In the process, they collect data for commercial exploitation.
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
Not only does the company control sensitive information about the journeys people take, but senior company officials, at least in the early days of the company, showed a willingness to abuse that power. 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.
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. These ideas are setting us on a path to a peer-to-peer economy. What blockchain technology says is, “Why stop at Uber?” Why do we even need this particular company, which takes 25 percent from each ride and has a reputation for abusing its “God’s View” knowledge of passengers’ rides?
See permissioned (private) blockchains Procivis proof-of-stake algorithm proof of work prosumers Protocol Labs Provenance public key infrastructure (PKI) Pureswaran, Veena R3 CEV consortium ransom attacks Ravikant, Naval Realini, Carol re-architecting record keeping and proof-of-stake algorithm and supply chains and trust See also ledger-keeping Reddit refugee camps Regenor, James reputation scoring Reuschel, Peter Rhodes, Yorke ride-sharing Commuterz Lyft reputation scoring Uber Ripple Labs Rivest Co. Rockefeller Foundation Rosenfeld, Meni rotating savings and credit associations (ROSCAs) Russia Safaricom Santori, Marco Sawtooth Lake scalability and Bitcoin and Ethereum and permissionless systems Schneiderman, Eric Schneier, Bruce Schwab, Klaus Secure Sockets Layer (SSL) Security and Exchange Commission Segregation Witness (SegWit) SegWit2x self-sovereign identities.
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 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. I asked him if he owned the Toyota Prius he was driving. He said, “No.”
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. Also, your car is protected under HyreCar’s industry ridesharing insurance. Poshmark People buy or sell their clothing via Poshmark’s mobile app.
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.
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.
Like the scarlet letter in Nathaniel Hawthorne's novel, every evaluation has the potential to affect the rest of someone's life, without a reliable mechanism for redress. Behind the 1960s peace, love, and flowers of the sharing economy, it is Darwinian capitalism. 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.
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.
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
The things that keep others out of Uber’s sandbox, so to speak, aren’t so different from the regulatory shenanigans that its predecessors resorted to. You try to erect what economists call barriers to entry, which are, almost by definition, market frictions. 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.
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.
If the market maker does the job right, the two sides work together a lot more often and do so more efficiently than in his absence. The Champagne wardens ensured that the merchant of Prato got paid, other traders took notice, and the Champagne fairs thrived. Successful internet platforms, such as eBay, Uber, and Amazon, have similarly figured out ways of making most transactions run smoothly and acting as arbitrator in those that don’t (and, in Uber’s case, using a proprietary algorithm that governs how to connect drivers and customers). The market maker can screen out undesirables from all sides of the platform, but as cases like eBay and Uber suggest, often the job is left to platform participants themselves. The platform manager makes customer feedback possible, and in theory, the wisdom of crowds takes care of the rest, solving the asymmetric information problem that George Akerlof identified as the enemy of market function back in 1970.
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.
That is reportedly what happened at Uber. For several years after its founding in 2009, Uber was the hottest tech unicorn in the world. Getting a job at the San Francisco ride-sharing company was like winning a golden ticket. But Uber’s managers took full advantage of that. Uber became a toxic, stressful place to work, with bullying, allegations of sexual harassment, and a notoriously cruel culture. “It’s a money cult” is how a former worker described Uber to BuzzFeed in 2017. “People are putting up with massive amounts of abuse, mental abuse.” Workers tolerated the punishing grind because they didn’t want to lose their stock options. “The equity, people see that as their future, their retirement, the reason they moved to America, or why they moved across the country,” one former employee said. In Uber’s culture of fear, employees were overloaded with work, forced to come in during the middle of the night to handle emergencies, and sometimes humiliated by managers in front of their peers.
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
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. In the extreme form, the relation between regulator and business mutates into crony capitalism.
OECD, “Taxi Services” suggests that the number of taxis in Paris actually went down between the early 1930s and the late 1960s, and that the number of taxi licenses only increased by 1,000 in the 40 years between 1967 and 2007. 3.OECD, “Taxi Services,” 110. 4.Mawad and Fouquet, “Paris Police ‘Boers’ Pursuing Uber Drivers.” 5.Drozdiak, “Uber Launches Petition over Brussels UberPop Ban.” 6.Sheftalovich, “‘Scrooge’ Brussels Mayor Dampens Uber’s Christmas Spirit.” 7.BBC, “Uber Banned in Germany.” 8.New York City capped the number of yellow cab medallions to 16,900 in 1937. Now, however, there are only about 13,500 such licenses issued. 9.Zingales, A Capitalism for the People, 4. 10.Thomas, Investment Incentives and the Global Competition for Capital. 11.Derviş, “Is Uber a Threat to Democracy?” 12.OECD, Businesses’ Views on Red Tape. 13.Olson, The Logic of Collective Action. 14.Sellar and Yeatman, 1066 and All That. 15.This anecdote is from Diamandis and Kotler, Abundance. 16.Acemoglu and Robinson, Why Nations Fail. 17.Downes, “Fewer, Faster, Smarter.” 18.Goodwin, “The History of Mobile Phones.” 19.Rogers and Ramsey, “Tesla to Stop Selling Electric Cars in New Jersey.” 20.Lepore, “How Santa Monica Will Enforce Its Airbnb Ban.” 21.Coldwell, “Airbnb’s Legal Troubles.” 22.Tabarrok, “Book Review: ‘Innovation Breakdown’.” 23.Gulfo, Innovation Breakdown. 24.Kay, “Miracles of Productivity Hidden in the Modern Home.” 25.Erixon, “EU Policies on Online Entrepreneurship.” 26.Tabarrok, “Book Review: ‘Innovation Breakdown’.” 27.CSDD, “Growing Protocol Design Complexity.” 28.Grabowski and Hansen, “Cost of Developing a New Drug.” 29.Herper, “The Truly Staggering Cost of Inventing New Drugs.” 30.Roy, “Stifling New Cures.” 31.CSDD, “Growing Protocol Design Complexity.” 32.Basu and Hassenplug, “Patient Access to Medical Devices.” 33.That figure is for 2010 when one of the authors was given a guided tour of the FedEx hub. 34.Button and Christensen, “Unleashing Innovation.” 35.Comin and Hobijn, “Technology Diffusion and Postwar Growth.” 36.Agarwal and Gort, “First-Mover Advantage.” 37.Jaffe and Trajtenberg, Patents, Citations and Innovations. 38.Mansfield, “How Rapidly Does New Industrial Technology Leak Out?”
Its opponents are calling for it to be either forced out of business or regulated to make it behave and operate just like every other taxi firm it competes with. As you might have guessed, the company in question is Uber – the San Francisco-based transport network company offering services via an app. UberPop, its peer-to-peer car-sharing service using unlicensed drivers, closed in France following the men’s arrest and all the protests against the service. Trade unions had taken strike action in protest against Uber, and some of them became violent. They burnt tires and aggressively harassed Uber drivers and their passengers. Parisian police authorities had previously tried to slow the company’s expansion by ruling that taxis could not turn up sooner than 15 minutes after the booking had been made. The move was directed against Uber, which offered a faster service than the incumbent companies. France also introduced a new transport law in 2014, ruling that only licensed taxi companies were allowed to show the real-time location of a car on a map – an innovation that first gained Uber prominence among the taxi-riding community.
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.
However, Airbnb owns no physical assets and is worth almost $10 billion. That’s more than the value of Hyatt Hotels, which has 45,000 employees spread across 549 properties. And while Hyatt’s business is comparatively flat, Airbnb’s number of room-nights delivered is growing exponentially. At its current pace, Airbnb will be the biggest hotelier in the world by late 2015. Similarly, Uber, the Airbnb of cars—Uber converts private automobiles into taxis—has been valued at $17 billion. Like Airbnb, Uber has no assets, no workforce (to speak of) and is also growing exponentially. If you don’t find these valuations sufficiently eye-opening, go back and read them again—this time reminding yourself that each of these Exponential Organizations is fewer than six years old. As we saw with Waze in Chapter Two, there are two fundamental drivers that enable ExOs to achieve this level of scalability.
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
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. From the protests of cab drivers, you would think the sky had fallen.
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 vision is that you will be able to summon a car using your smartphone.
“Number of Motor Vehicles Registered in the United States from 1990 to 2017,” Statista, www.statista.com/statistics/183505/number-of-vehicles-in-the-united-states-since-1990/ (accessed June 27, 2019); and Jared Green, “500 Million Reasons to Rethink the Parking Lot,” Grist, June 7, 2012, http://grist.org/cities/500-million-reasons-to-rethink-the-parking-lot/ (accessed June 27, 2019). 20. Emily Badger, “Now We Know How Many Drivers Uber Has—and Have a Better Idea of What They’re Making,” Washington Post, January 22, 2015, https://www.washingtonpost.com/news/wonk/wp/2016/01/20/now-we-know-how-many-drivers-uber-has-and-have-a-better-idea-of-what-theyre-making/?noredirect=on; and Kate Rogers, “Who’s Your Uber Driver? More of Them Are Women: Survey,” CNBC, December 8, 2015, http://www.cnbc.com/2015/12/08/whos-your-uber-driver-more-of-them-are-women-survey.html (accessed June 27, 2019). 21. Independent Cab Co., http://www.taxi4u.com/calculate.html; and Uber Los Angeles, https://www.uber.com/cities/los-angeles (accessed June 27, 2019). 22. “Cost of Owning and Operating Vehicle in U.S. Increases Nearly Two Percent According to AAA’s 2013 ‘Your Driving Costs’ Study,” AAA Newsroom, April 16, 2013, http://newsroom.aaa.com/2013/04/cost-of-owning-and-operating-vehicle-in-u-s-increases-nearly-two-percent-according-to-aaas-2013-your-driving-costs-study/ (accessed June 27, 2019). 23.
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. Most are not like the middle-class driver in Uber ads, picking up some extra cash for luxuries.
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.
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.
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
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. When it comes to rides on shared bikes, China is outpacing the United States at an astounding ratio of three hundred to one.
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.
The O2O revolution was about bringing that same e-commerce convenience to the purchase of real-world services, things that can’t be put in a cardboard box and shipped across country, like hot food, a ride to the bar, or a new haircut. Silicon Valley gave birth to one of the first transformational O2O models: ride-sharing. Uber used cell phones and personal cars to change how people got around cities in the United States and then around the world. Chinese companies like Didi Chuxing quickly copied the business model and adapted it to local conditions, with Didi eventually driving Uber out of China and now battling it in global markets. Uber may have given an early glimpse of O2O, but it was Chinese companies that would take the core strengths of that model and apply it to transforming dozens of other industries. Chinese cities were the perfect laboratory for experimentation.
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.
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.
And given its popularity, it seems to speak for a sector of opinion that is intractably opposed to all forms of market action. So what does this publication say about the sharing economy? “Uber is part of a new wave of corporations that make up what’s called the ‘sharing economy,’” writes Avi Asher-Schapiro in the strangely titled article “Against Sharing.” “The premise is seductive in its simplicity: people have skills, and customers want services. Silicon Valley plays matchmaker, churning out apps that pair workers with work. Now, anyone can rent out an apartment with Airbnb, become a cabbie through Uber, or clean houses using Homejoy.” So far, so good. But then the writer dives deep into the ideological thicket: “under the guise of innovation and progress, companies are stripping away worker protections, pushing down wages, and flouting government regulations.”
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
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. Cities have embarked on varied paths, resulting in patchwork regulation. Taxi industries and their allies in city halls have engaged companies like Uber in pitched battles, leading to at-times violent taxi strikes in Paris, a high-stakes political battle in New York City, and legislative tugs-of-war in Seattle, Toronto, and Rio.
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.
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.
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.
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
Interestingly, their defense is all about categorization. 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.
This bigotry is nearly invisible in the world of yellow cabs, but it would be hard to hide in Uber. They’ve built a new “architecture of trust” that re-frames the rules and relationships between passengers and drivers. The design of these information systems is tricky. Before pickup, Uber drivers and passengers see each other’s ratings and may decline a ride based on the number of stars. After a ride, drivers see the rating they’re given but not the review. Passengers see neither. Drivers are told by Uber not to solicit 5-star ratings, nor confront passengers about low ratings, but both do occur. Balancing privacy and transparency for optimal performance and trust in the system requires constant tuning. Figure 1-5. Rideshares rely on trust and ratings. Despite these challenges, Uber has built a platform that integrates mobile phones, social networks, and GPS to disrupt the business of transport.
But that’s how our eleven year old daughter explained my experiment with Uber and Airbnb to my wife. Yes, once again, I’m making myself uncomfortable. I’m an advisor to the School of Library and Information Science at San José State University. Since 2009, the program has embraced a 100% online model. Ironically, I’m here for a face to face meeting. And I’m using this visit to California as an opportunity to dip my toes into the infamous sharing economy. So, I’m not in a cab, and I’m not hitchhiking. I’m in a black town car with an Uber-qualified driver named Gustavo. I hailed him via mobile app. I must admit it was fun watching the little black car icon drive to my location. I already know a bit about my driver. He’s passed Uber’s insurance and background checks and has a 5 star rating. At the end of my flat rate ride (paid by phone) I can rate him and even write a review.
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
(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.
“one very, very strange year”: Susan Fowler, “Reflecting on One Very, Very Strange Year at Uber,” SusanJFowler.com, February 19, 2017, accessed August 19, 2018, https://www.susanjfowler.com/blog/2017/2/19/reflecting-on-one-very-strange-year-at-uber. stalk their ex-girlfriends: Will Evans, “Uber Said It Protects You from Spying. Security Sources Say Otherwise,” Reveal News, December 12, 2016, accessed August 19, 2018, https://www.revealnews.org/article/uber-said-it-protects-you-from-spying-security-sources-say-otherwise. after a female journalist: Sarah Lacy, “Uber Executive Said the Company Would Spend ‘A Million Dollars’ to Shut Me Up,” Time, November 14, 2017, accessed August 19, 2018, http://time.com/5023287/uber-threatened-journalist-sarah-lacy. he calls it “Boob-er”: Mickey Rapkin, “Uber Cab Confessions,” GQ, February 27, 2014, accessed August 19, 2018, www.gq.com/story/uber-cab-confessions.
When she told HR and top management, they said her manager was a “high performer” and this was his first offense, so “they wouldn’t feel comfortable giving him anything other than a warning and a stern talking-to.” That didn’t seem true, though. Fowler later encountered other Uber women who’d previously reported the same man for the same behavior. When Fowler continued to complain about how female employees were treated, HR officials struck back in a creepy fashion—demanding the personal email addresses the women used, implying the women were part of a conspiracy, and telling Fowler that “people of certain genders and ethnic backgrounds” may not be suited for coding jobs. About a week after that, Fowler fled Uber for a new job. She wrote her story up on the blog post, but, hey: Another blog post complaining about sexism in the valley? What impact could that have? A huge one, it turns out. Uber’s board had already been hit with years of bad press about its employees’ behavior. Employees had used a “God View” internal mapping tool to help ex-boyfriends stalk their ex-girlfriends; a senior executive had threatened to send private investigators after a female journalist.
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.
Most importantly, we are able to rate the quality of the experience, affording Uber the opportunity to improve the overall service and weed out substandard drivers or vehicles. A recent Quartz article1 identified that up to 30 per cent of Uber drivers in the United States have never had a bank account—many operated previously as taxi drivers in the cash economy. To be a driver on Uber, however, drivers need a minimum of a debit card to get paid. So Uber has had to solve this problem by allowing drivers to sign up for a bank account as part of the Uber driver application process, in real time. Unsurprisingly, this makes Uber the largest acquirer of small business bank accounts in the United States today, bigger than Wells Fargo, BofA and Chase combined. You’ve probably never thought of Uber as an acquirer of small business bank accounts, but if you’re an Uber driver and Uber can give you a debit card that enables you to get paid—then why would you go to a bank branch to open an account instead?
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.
For example, Ethereum defines a smart contract/Dapp as a transaction protocol that executes the terms of a contract or group of contracts on a cryptographic blockchain.65 Our working definition of a Dapp is an application that runs on a network in a distributed fashion with participant information securely (and possibly pseudonymously) protected and operation execution decentralized across network nodes. Some current examples are listed in Table 2-4. There is OpenBazaar (a decentralized Craigslist), LaZooz (a decentralized Uber), Twister (a decentralized Twitter), Bitmessage (decentralized SMS), and Storj (decentralized file storage). Table 2-4. Sample list of Dapps Project name and URL Activity Centralized equivalent OpenBazaar https://openbazaar.org/ Buy/sell items in local physical world Craigslist LaZooz http://lazooz.org/ Ridesharing, including Zooz, a proof-of-movement coin Uber Twister http://twister.net.co/ Social networking, peer-to-peer microblogging66 Twitter/Facebook Gems http://getgems.org/ Social networking, token-based social messaging Twitter/SMS Bitmessage https://bitmessage.org Secure messaging (individual or broadcast) SMS services Storj http://storj.io/ File storage Dropbox Swarm https://www.swarm.co/ Koinify https://koinify.com/ bitFlyer http://fundflyer.bitflyer.jp/ Cryptocurrency crowdfunding platforms Kickstarter, Indiegogo venture capital funding In a collaborative white paper, another group offers a stronger-form definition of a Dapp.67 In their view, the Dapp must have three features.
Here, more efficient, larger, more scalable, more trackable systems are sought for the distribution of consumable resources like gas and electricity, transportation quanta (i.e., Uber/LaZooz, self-driving vehicles, or automated pod transport systems envisioned in the farther future), clean water, food, health-care services, relief aid, crisis-response supplies, and even emotional support or mental-performance coaching (for individuals permissioned in consumer EEG rigs). This is the idea of using the demurrage concept in other network systems to dynamically, automatically redistribute resources for optimization. The concept is combining networks and demurrage currency to enable new functionality like dynamic automatic redistribution across network nodes and enable the predictive and on-demand smart clustering of resources where needed. Some examples are predicting and delivering an increased load of Ubers and cabs to the airport when more flights are due to arrive, and preparing available electricity units on hotter days and fuel oil units on colder days.
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.
Ultimately, the version access pattern should be as stable as promised in accompanying documentation, and developers should have the option to opt into new versions while maintaining stability on previous versions. 134 | Chapter 7: Managing Change Expert Advice From the outset, we knew that there would be iterations in our API—Uber just moves too fast for there not to be. Therefore, each endpoint is versioned and makes it easy to access historical docs. —Chris Messina, developer experience lead at Uber Updating URI components is one strategy that many API providers use to define version schemes. These are often inserted as a base for the URI, before the specification of a resource-like entity. For exam‐ ple, take Uber’s ride requests API endpoint, https:// api.uber.c om/v1.2/requests. In this example, v1.2 is inserted before the requests resource. This is similar to the scheme for Twit‐ ter’s Ads API, in which 2 is the version: https:/ /adsapi.twitter.c om/2/accounts.
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.
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.
Other findings consistent with these are collected from opinion polls conducted by various industry groups, insurance institutes, and consumer advocacy groups and available at Saferoads.org. 8.Christopher Mele, “In a Retreat, Uber Ends Its Self-Driving Car Experiment in San Francisco,” New York Times, December 22, 2016, http://www.nytimes.com/2016/12/21/technology/san-francisco-california-uber-driverless-car-.html?hp&action=click&pgtype=Homepage&clickSource=story-heading&module=first-column-region®ion=top-news &WT.nav=top-news&_r=0. 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.
That would appear to be the plan.11 And in fact municipal financing for public transportation has declined sharply; mass transit ridership is down, and its infrastructure is crumbling in many cities. Meanwhile, Uber continues to lose billions of dollars every year ($14 billion between 2014 and 2018). If one allows oneself to become curious about this last fact, the story of Uber becomes quite interesting. In 2019, the transportation industry consultant Hubert Horan published a study of Uber’s economics and concluded that the firm has no hope of ever turning a profit. It “not only lacks powerful competitive advantages, but it is actually less efficient than the competitors it has been driving out of business.”12 It turns out, on closer inspection, that Uber never intended to turn a profit from driving people around in a competitive market. By having earlier investors massively subsidize rides through low fares, the firm aimed for “growth at all costs,” knowing that there are segments of the investment world that regard explosive growth as “the only important determinant of how start-up companies should be valued.”
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.
It’s how more and more people are working, whether they want to or not. Welcome to the Freelance Society. THE UBER-IZATION OF WORK Uber is the best known of these new kinds of businesses. It is nothing more than a temp agency, in which the predominant job on offer is that of a taxi driver (more recently Uber is trying other related services, such as courier or delivery person). Drivers are not treated as employees but as freelance contractors, and most drivers, after they subtract their considerable driving expenses, don’t earn any more than taxis drivers. Indeed, many Uber drivers complain they don’t earn minimum wage, much less a living wage. They receive no safety-net benefits and can be cut off the app-based platform at any time. Recently Uber cut off hundreds of drivers (and possibly over a thousand) in Los Angeles and San Francisco because those drivers’ “acceptance rate” was too low.
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.
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
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. What is Uber’s plan? Here we see that even Uber doesn’t think the business model they pioneered is likely to succeed. They want to grow big—to monopolise taxi services. Yet their next goal is to replace drivers with self-driving cars and build a massive moat around their business that no one else can compete with.
It is astonishing that a company can lose $7.5 billion in two years, have never made a profit in its entire existence, and yet still be heralded as the next big thing for capitalism. Rather than survive by making profits, Uber survives through venture capital welfare: constant injections of new funding from investors. Looking closely at Uber’s funding rounds, what becomes apparent is that there is more and more suspicion from the investors. In the most recent funding round, for instance, the investor group SoftBank actually demanded that Uber take a 30 percent cut on their very high valuation.4 Effectively, Uber is finding it increasingly difficult to convince investors of its ability to generate profits even in the long-term. Uber also faces future challenges. The first example of these is regulators. The expansion of Uber’s particular employment relationship— where workers are deemed contractors rather than employees—has only succeeded by running ahead of regulators and introducing these new labour practices before regulators know what to do.
There have been court cases about the way in which Uber handles its employees. And Uber is presently facing the threat of being banned from London due to Farr (2015). Jourdan and Ruwitch (2016). 4 Somerville (2018). 2 3 136 N. Srnicek avoidance of regulators’ requests.5 So regulators are putting significant restrictions on what the Uber model can do. The other challenge is that Uber and other lean platforms are facing worker struggles. 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.
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
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. Hill, Steven, How the “Uber Economy” and Runaway Capitalism are Screwing American Workers (New York: St. Martin’s Press, 2015). 21. Csikszentmihalyi, Mihaly, Flow: The Psychology of Optimal Experience (New York: Harper Perennial, 2008).
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.
Hanauer, Nick, and David Rolf, “Shared Security, Shared Growth,” Democracy Journal, no. 27, Summer 2015. democracy-journal.org/magazine/37/shared-security-shared-growth/ 12. Hill, Steven, “The Future of Work in the Uber Economy,” Boston Review, July 22, 2015. bostonreview.net/us/steven-hill-uber-economy-individual-security-accounts 13. Reich, Robert, “The Upsurge in Uncertain Work,” Robert Reich, August 23, 2015. robertreich.org/post/127426324745 14. Reich, Robert, “Inequality for All Q&A” (video). www.dailykos.com/story/2014/3/26/1287365/-Robert-Reich-Universal-Basic-Income-In-The-US-Almost-Inevitable 15. 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.
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.
The Internet Is Not the Answer by Andrew Keen
"Robert Solow", 3D printing, A Declaration of the Independence of Cyberspace, Airbnb, AltaVista, Andrew Keen, augmented reality, Bay Area Rapid Transit, Berlin Wall, bitcoin, Black Swan, Bob Geldof, Burning Man, Cass Sunstein, citizen journalism, Clayton Christensen, clean water, cloud computing, collective bargaining, Colonization of Mars, computer age, connected car, creative destruction, cuban missile crisis, David Brooks, disintermediation, disruptive innovation, Donald Davies, Downton Abbey, Edward Snowden, Elon Musk, Erik Brynjolfsson, Fall of the Berlin Wall, Filter Bubble, Francis Fukuyama: the end of history, Frank Gehry, Frederick Winslow Taylor, frictionless, full employment, future of work, gig economy, global village, Google bus, Google Glasses, Hacker Ethic, happiness index / gross national happiness, income inequality, index card, informal economy, information trail, Innovator's Dilemma, Internet of things, Isaac Newton, Jaron Lanier, Jeff Bezos, job automation, Joi Ito, Joseph Schumpeter, Julian Assange, Kevin Kelly, Kickstarter, Kodak vs Instagram, Lean Startup, libertarian paternalism, lifelogging, Lyft, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, Martin Wolf, Metcalfe’s law, move fast and break things, move fast and break things, Nate Silver, Nelson Mandela, Network effects, new economy, Nicholas Carr, nonsequential writing, Norbert Wiener, Norman Mailer, Occupy movement, packet switching, PageRank, Panopticon Jeremy Bentham, Paul Graham, peer-to-peer, peer-to-peer rental, Peter Thiel, plutocrats, Plutocrats, Potemkin village, precariat, pre–internet, RAND corporation, Ray Kurzweil, ride hailing / ride sharing, Robert Metcalfe, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Silicon Valley ideology, Skype, smart cities, Snapchat, social web, South of Market, San Francisco, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, TaskRabbit, Ted Nelson, telemarketer, The Future of Employment, the medium is the message, the new new thing, Thomas L Friedman, Travis Kalanick, Tyler Cowen: Great Stagnation, Uber for X, uber lyft, urban planning, Vannevar Bush, Whole Earth Catalog, WikiLeaks, winner-take-all economy, working poor, Y Combinator
Andreessen Horowitz has also ventured into the car-sharing market, where it is backing a 2012 San Francisco–based middleman called Lyft, a mobile phone app that enables peer-to-peer ride sharing. But the best-known startup in the transportation-sharing sector is Uber, a John Doerr–backed company that also has received a quarter-billion-dollar investment from Google Ventures. Founded in late 2009 by Travis Kalanick, by the summer of 2014 Uber was operating in 130 cities around the world, employing around 1,000 people, and, in a June 2014 investment round of $1.2 billion, was valued at $18.2 billion, a record for a private startup company. It made Kalanick a paper billionaire and gave his four-year-old startup with its 1,000 employees almost the same valuation as that of Avis and Hertz combined,114 companies which together employ almost 60,000 people. “Everybody’s Private Driver” Uber markets its distributed taxi network, and in July 2013 also introduced “UberCHOPPER,” a $3,000 private helicopter service which whirled wealthy New Yorkers over to the exclusive Hamptons.115 “Blair Waldorf, Don Draper, and Jay Gatsby got nothing on you,” Uber boasted in advertising UberCHOPPER.
The Alien Overlord Spaceships Outside the San Francisco hotel, the future had arrived and, to paraphrase William Gibson, it was distributed most unequally. Uber limousines lined up outside the club to whisk Silicon Valley’s successful young failures around town. Cars from rival transportation networks hovered hopefully around the hotel, too—companies like Lyft, Sidecar, and the fleet of me-too mobile-ride-hailing startups trying to out-Uber Travis Kalanick’s $18 billion market leader. Some of the people scrambling for a living as networked drivers were themselves aspiring entrepreneurs with billion-dollar startup ideas of their own.27 So even in these unlicensed cabs, it was impossible to get away from the pitches for the next WhatsApp, Airbnb, or Uber, which pitches, sadly, were mostly just a glorified form of begging. “San Francisco,” as one observer about the digital gold rush dryly noted, is “full of people walking around with 1.2% of nothing.”28 The streets of San Francisco were also full of buses.
Uber immediately deactivated what they call their “partner’s” account, saying that he “was not providing service on the Uber system during the time of the accident.”11 How generous. And happy 2014 to all our partners, Uber might have added. So much for shared responsibility in the sharing economy. No wonder Kalanick’s own drivers, whom he calls “transportation entrepreneurs,” are picketing Uber. And no wonder that the parents of Sofia Liu, the San Francisco girl killed by the Uber driver, are suing Uber itself in a wrongful-death lawsuit. It’s not just drivers and pedestrians who are being killed by Uber. If you don’t like it, walk, Uber tells its customers, with Kalanickian tact, about a service that uses “surge” pricing—a euphemism for price gouging—which has resulted in fares being 700–800% above normal on holidays or in bad weather.12 During a particularly ferocious December 2013 snowstorm in New York City, one unfortunate Uber rider paid $94 for a trip of less than two miles that took just eleven minutes.13 Even the rich and famous are being outrageously ripped off by the unregulated Uber service, with Jessica Seinfeld, Jerry’s wife, being charged $415 during that same December storm to take her kid across Manhattan.14 Along with other startups such as Joe Gebbia’s Airbnb and the labor network TaskRabbit, Uber’s business model is based upon circumventing supposedly archaic twentieth-century regulations to create a “what you want when you want it” twenty-first-century economy.
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.
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.
According to Danny Lange, former head of machine learning at Uber, the technology has finally broken out of the research lab and is fast becoming “the cornerstone of business disruption.”d a. “Artificial Intelligence and Life in 2030,” Stanford One Hundred Year Study on Artificial Intelligence (AI100), September 2016, https://ai100.stanford.edu/sites/default/files/ai_100_report_0831fnl.pdf. b. John McCarthy and Ed Feigenbaum, “Arthur Samuel: Pioneer in Machine Learning,” Stanford Infolab, http://infolab.stanford.edu/pub/voy/museum/samuel.html, accessed October 23, 2017. c. Cade Metz, “How Google’s AI Viewed the Move No Human Could Understand,” Wired, March 14, 2016, https://www.wired.com/2016/03/googles-ai-viewed-move-no-human-understand/. d. Daniel Lange, “Making Uber Smarter with Machine Learning,” presentation at Machine Learning Innovation Summit, San Francisco, June 8–9, 2016. 2 Accounting for Robots AI in Corporate Functions Money laundering is a major concern for financial institutions, which can face heavy fines and stiff regulatory restrictions for any infractions.
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.
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.
In 2018, far more Americans were fearful of computers replacing them in the workforce68 (30.7 percent) than in earlier years (25.3 percent in 2017 and 16.6 percent in 2016). Our fear of unemployment is justified when our safety net has too many holes: 52.9 percent of Americans in 2018 were afraid or very afraid of high medical bills.69 And our employment options are limited. The “gig” economy, like driving for Uber while renting out a bedroom on Airbnb, will not provide medical benefits and secure us financially in retirement. Avoiding corporate America is harder, as there are far fewer new businesses in the United States being created70 (as a share of the US economy) since the late 1970s. And even corporate America is getting smaller: Fewer public firms exist today in the United States than in the 1970s. So as the balance of power has shifted away from individuals, our very economic survival seems to be at stake.
The Wealth of Humans: Work, Power, and Status in the Twenty-First Century by Ryan Avent
"Robert Solow", 3D printing, Airbnb, American energy revolution, assortative mating, autonomous vehicles, Bakken shale, barriers to entry, basic income, Bernie Sanders, BRICs, business cycle, call centre, Capital in the Twenty-First Century by Thomas Piketty, Clayton Christensen, cloud computing, collective bargaining, computer age, creative destruction, dark matter, David Ricardo: comparative advantage, deindustrialization, dematerialisation, Deng Xiaoping, deskilling, disruptive innovation, Dissolution of the Soviet Union, Donald Trump, Downton Abbey, Edward Glaeser, Erik Brynjolfsson, eurozone crisis, everywhere but in the productivity statistics, falling living standards, first square of the chessboard, first square of the chessboard / second half of the chessboard, Ford paid five dollars a day, Francis Fukuyama: the end of history, future of work, gig economy, global supply chain, global value chain, hydraulic fracturing, income inequality, indoor plumbing, industrial robot, intangible asset, interchangeable parts, Internet of things, inventory management, invisible hand, James Watt: steam engine, Jeff Bezos, John Maynard Keynes: Economic Possibilities for our Grandchildren, Joseph-Marie Jacquard, knowledge economy, low skilled workers, lump of labour, Lyft, manufacturing employment, Marc Andreessen, mass immigration, means of production, new economy, performance metric, pets.com, post-work, price mechanism, quantitative easing, Ray Kurzweil, rent-seeking, reshoring, rising living standards, Robert Gordon, Ronald Coase, savings glut, Second Machine Age, secular stagnation, self-driving car, sharing economy, Silicon Valley, single-payer health, software is eating the world, supply-chain management, supply-chain management software, TaskRabbit, The Future of Employment, The Nature of the Firm, The Rise and Fall of American Growth, The Spirit Level, The Wealth of Nations by Adam Smith, trade liberalization, transaction costs, Tyler Cowen: Great Stagnation, Uber and Lyft, Uber for X, uber lyft, very high income, working-age population
Today’s labour victories, when they occur, tend to come from straightforward issues for which it is easy to muster broad, passionate electoral support: policies such as a rise in the minimum wage or a reduction in immigration. The more complex negotiations that occurred a generation or two ago, when labour had a seat at the political table, tend not to occur any longer. That could change. Drivers for car-sharing firms, such as Uber and Lyft, are battling to unionize. Unionization could eventually come to other sectors of the economy in which large pools of on-demand labour sell their time through market-making apps as well. Unionization would yield uncertain direct benefits to workers within these firms, though. Short-run concessions wrung from ownership might simply accelerate the pace of automation: troublesome labour tends to encourage the deployment of robots, whether the setting is a factory in Shenzhen or a car on California streets.
It is growing every day, though from a very small base. Uber, one of the larger contributors to it, has several hundred thousand drivers worldwide.12 In a global labour force of billions that doesn’t begin to move the needle. Part-time work increased in importance during the economic crisis of 2008–9, but has ebbed as economic conditions have improved. Still, there is indisputably the opportunity for significant growth in the future. The question is whether the gig economy will lead to the suspension of the trilemma. The trilemma implies that to scare up enough consumer demand for ‘gigs’, the price – of the Uber trip or the TaskRabbit errand, for example – must be low. That, in turn, means that pay must be low. Uber driver wages can’t rise to too high a level or Uber will accelerate automation. Similarly, TaskRabbit tasks can’t be too expensive, or people will only use the service on rare, higher value occasions, reducing the labour-absorbing power of the service.
In doing so it allowed relatively unskilled drivers to enter the business in vast numbers; many more people can operate a smartphone than can learn the entire maze that is London. It routinized and deskilled the labour involved. The cleverness of the technology at work and the business model are such that the cost of cab rides to users is often lower than the cost of taking a traditional cab, while Uber drivers, according to one analysis at least, earn more money per hour than traditional drivers: about $19 per hour compared to roughly $13 per hour for taxi drivers as a whole. (Cheaper cab rides can occur alongside higher wages because Uber’s technology allows drivers to use their time more effectively.)6 The parallel is not perfect, however. Uber’s success rests on the clever sidestepping of taxicab and employment regulation (tricks that have earned it significant legal scrutiny and which may not survive sustained legal challenges). Yet the firm’s business does demonstrate how the technological deskilling of an occupation can lead to both a better experience for consumers and better pay for some workers.
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.
Suez Canal tablet computing technological advance technology, prf.1, 1.1, 1.2, 2.1, 2.2, 2.3 American fear of complementarity and globalization and proprietary technology companies terrorism Tesla Motors, 10.1, 13.1, 13.2 Thailand Theory of Justice, A (Rawls) Timberlake, Justin Time magazine Tolkien, J.R.R. Tolstoy, Leo Tom Sawyer (char.) Toyota Tumblr 27 Club Twitter, 5.1, 6.1 Uber Unabomber VCs, rules of “veil of ignorance” venture capital power law in venture fund, J-curve of successful, 7.1 vertical progress viral marketing Virgin Atlantic Airways Virgin Group Virgin Records Wagner Wall Street Journal Warby Parker Watson web browsers Western Union White, Phil Wiles, Andrew Wilson, Andrew Winehouse, Amy World Wide Web Xanadu X.com Yahoo!, 2.1, 3.1, 3.2, 5.1, 6.1 Yammer Yelp YouTube, 10.1, 12.1 ZocDoc Zuckerberg, Mark, prf.1, 5.1, 6.1, 14.1 Zynga About the Authors Peter Thiel is an entrepreneur and investor.
Disrupted: My Misadventure in the Start-Up Bubble by Dan Lyons
activist fund / activist shareholder / activist investor, Airbnb, Ben Horowitz, Bernie Madoff, bitcoin, call centre, cleantech, cloud computing, corporate governance, disruptive innovation, dumpster diving, fear of failure, Filter Bubble, Golden Gate Park, Google Glasses, Googley, Gordon Gekko, hiring and firing, Jeff Bezos, Lean Startup, Lyft, Marc Andreessen, Mark Zuckerberg, Menlo Park, minimum viable product, new economy, Paul Graham, pre–internet, quantitative easing, ride hailing / ride sharing, Rosa Parks, Sand Hill Road, sharing economy, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, Skype, Snapchat, software as a service, South of Market, San Francisco, Stanford prison experiment, Steve Ballmer, Steve Jobs, Steve Wozniak, telemarketer, tulip mania, uber lyft, Y Combinator, éminence grise
Trotsky clears his throat and says, “Okay—anybody else?” We spend an hour listening to various lame ideas. One is called Uber-a-Marketer, and it’s a ripoff of a promotion that Uber did with a vaccine service, where you could have a nurse with a flu shot driven to your door. With Uber-a-Marketer, you’d pay some money, or win some kind of competition, and HubSpot would send one of its marketing people to your office and teach you how to do marketing. After all, we’re the best marketing team on the planet! People would kill to have us teach them about marketing! This idea actually generates some responses. But someone worries that Uber might not want to play ball with us. What happens then? We could go to Lyft, or some other car service. I chime in, saying that I love this idea but maybe there’s a way to kick it up a notch and make it even more dramatic: “Why not have a marketing person parachute in?”
During my time at HubSpot, I was shocked to see how badly managed the company was and how packs of inexperienced twenty-something employees were being turned loose and given huge responsibility with little or no oversight. In the world of start-ups that is now the norm, not the exception. The consequences are just what you would expect. Employees at Uber, the ride-sharing company, have used a “God View” feature to stalk people using the service, including a BuzzFeed journalist. Re/code, a tech blog, claims other companies have done the same, including Lyft, a rival to Uber; Swipe, a photo-sharing app; and Basis, which makes a “health watch” that tracks people’s heart rates, sleep patterns, and other personal information. In the early days at Facebook, the young employees had a master password to gain access to anyone’s account, according to a book by a former Facebook employee.
At a traditional company she would have been owed a week or two of vacation pay, but from HubSpot, she got nothing. Think about how many hundreds of people churn in and out of a place like HubSpot, and you can see how the savings add up. Another way to drive down labor costs is to deny people employee status in the first place. Uber, the ride-sharing company, saves money by categorizing drivers as independent contractors rather than employees. Uber insists drivers prefer this because they enjoy more freedom. Uber and others in the “share economy” are creating a new form of serfdom, an underclass of quasi-employees who receive low pay and no benefits. As former secretary of labor Robert Reich put it in a June 2015 Facebook post: “The ‘share economy’ is bunk; it’s becoming a ‘share the scraps’ economy.” Tech companies also are pushing the U.S. government to increase the number of skilled foreign workers who can enter the country on H-1B visas.
Who Gets What — and Why: The New Economics of Matchmaking and Market Design by Alvin E. Roth
Affordable Care Act / Obamacare, Airbnb, algorithmic trading, barriers to entry, Berlin Wall, bitcoin, Build a better mousetrap, centralized clearinghouse, Chuck Templeton: OpenTable:, commoditize, computer age, computerized markets, crowdsourcing, deferred acceptance, desegregation, experimental economics, first-price auction, Flash crash, High speed trading, income inequality, Internet of things, invention of agriculture, invisible hand, Jean Tirole, law of one price, Lyft, market clearing, market design, medical residency, obamacare, proxy bid, road to serfdom, school choice, sealed-bid auction, second-price auction, second-price sealed-bid, Silicon Valley, spectrum auction, Spread Networks laid a new fibre optics cable between New York and Chicago, Steve Jobs, The Wealth of Nations by Adam Smith, two-sided market, uber lyft, undersea cable
Just as Airbnb competes with hotels by making a market for bedrooms, the transportation company Uber competes with taxis by making a market for limos and private cars. In most cities, only taxis have the right to pick passengers up on the street, while limousine services can pick customers up only if they have made a reservation in advance. Those reservations used to take time to arrange. So although limos worked fine for a scheduled trip to the airport or for a fleet of black cars for a conference, if you stepped outside and it was raining, or checked out of a hotel after a leisurely breakfast, hailing a taxi was much easier. Once again, smartphones changed all that. Now you can call a limo almost as easily as a taxi. So a lot of limos that once sat idle are now readily available. And that’s just the beginning. UberX and companies such as Lyft are even more like Airbnb: they are starting to make a market for the vacant passenger seats in private cars.
In much the same way, if you were a host renting your room to a stranger on Airbnb, a driver answering a call for a car on Uber, or someone selling some item to a stranger on Craigslist, you would be glad to have some assurances about the buyer. And if you were the buyer, you might want some assurances about the host, the driver, or the private seller. So far, I’ve mostly talked about market safety. But I also want to put in a word for reliability. Both safety and reliability fit under the general heading of making a market trustworthy. When you order a car on Uber, you want to know not just that you will get a safe driver and that the car won’t be a wreck, but also that the car will arrive promptly. Just as important, before you download the Uber app on your smartphone, you want to know that the system won’t be buggy, slow, or inaccurate (that is, the car will be able to find you).
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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
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.
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?
., 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.
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.
Second, they had sensors affixed to them—their eyes and ears most importantly—that fed contextual data to their brains to ensure that they put their knowledge to good use. But so did other people. No London cabbie became worse at their job because of navigation apps. Instead, millions of other non-cabbies became a lot better. The cabbies’ knowledge was no longer a scarce commodity, opening up cabbies to competition from ride-sharing platforms like Uber. That other drivers could show up with “The Knowledge” on their phones and predictions of the fastest routes meant they could provide equivalent service. When high-quality machine prediction became cheap, human prediction declined in value, so the cabbies were worse off. The number of rides in London’s black cabs fell. Instead, other people provided the same service. These others also had driving skills and human sensors, complementary assets that went up in value as prediction became cheap.
The Airbnb Story: How Three Ordinary Guys Disrupted an Industry, Made Billions...and Created Plenty of Controversy by Leigh Gallagher
Airbnb, Amazon Web Services, barriers to entry, Ben Horowitz, Bernie Sanders, cloud computing, crowdsourcing, don't be evil, Donald Trump, East Village, Elon Musk, housing crisis, iterative process, Jeff Bezos, Jony Ive, Justin.tv, Lyft, Marc Andreessen, Mark Zuckerberg, medical residency, Menlo Park, Network effects, Paul Buchheit, Paul Graham, performance metric, Peter Thiel, RFID, Sam Altman, Sand Hill Road, Saturday Night Live, sharing economy, side project, Silicon Valley, Silicon Valley startup, South of Market, San Francisco, Startup school, Steve Jobs, TaskRabbit, the payments system, Tony Hsieh, Travis Kalanick, uber lyft, Y Combinator, yield management
This kind of “sharing”—this hyperpersonal opening up of the most intimate and safest aspect of one’s life to a stranger—is not present when you hire a person to fix a leak on TaskRabbit, or when you get into someone’s air-conditioned black car for a silent ride to the airport with your head in your phone. More than anything else, it is this aspect of Airbnb that distinguishes it from Uber, Lyft, and any other of its sharing-economy peers. Elisa Schreiber, marketing partner at Greylock Partners, an investor in the company, summarized this distinction concisely after we got to talking about it one day. “Uber is transactional,” she said. “Airbnb is humanity.” Unfortunately, as we are about to see and as Airbnb has learned, despite its best intentions, that “humanity” can be a frustrating thing. It is not always well meaning, and it is not always good. 4 The Bad and the Ugly * * * * * * Our product is real life.
In what became a valuable reverse mentorship, Donahoe also quizzed Chesky for his advice on design and innovation and on how eBay could maintain characteristics of being young and nimble. From Jeff Weiner, Chesky learned the importance of removing those managers who weren’t performing. From Salesforce.com CEO Marc Benioff he learned how to push his executive team. He also had access to an informal support group among his current-generation start-up peers, including Travis Kalanick of Uber, Drew Houston of Dropbox, Jack Dorsey of Square, and John Zimmer of Lyft, all sharing their individual lessons about everything from running start-ups to balancing friends, relationships, and other elements of young founder life. A key principle of Chesky’s sourcing strategy was to become creative with identifying just who the experts were, and seeking out sources in unexpected disciplines. So, for instance, Chesky approached former CIA director George Tenet, not for trust and safety but to talk about culture (“How do you get people to feel committed in a place where everyone’s a spy?”
Chapter 2: Building a Company 35 “How to Start a Startup”: Sam Altman, “How to Start a Startup,” lecture with Alfred Lin and Brian Chesky, video, accessed October 10, 2016, http://startupclass.samaltman.com/courses/lec10/. 36 (six new core values in 2013): The six core values put in place in 2013 were “Host,” “Champion the Mission,” “Every Frame Matters,” “Be a cereal entrepreneur,” “Simplify,” and “Embrace the Adventure.” 41 in the first half of 2016 alone: “Uber Loses at Least $1.2 Billion in First Half of 2016,” Bloomberg BusinessWeek, August 25, 2016, https://www.bloomberg.com/news/articles/2016-08-25/uber-loses-at-least-1-2-billion-in-first-half-of-2016. 45 a surge in bookings: Owen Thomas, “How a Caltech Ph.D. Turned Airbnb into a Billion-Dollar Travel Magazine,” Business Insider, June 28, 2012, http://www.businessinsider.com/airbnb-joe-zadeh-photography-program-2012-6. 46 according to TechCrunch: M. G. Siegler, “Airbnb Tucked In Nearly 800% Growth in 2010; Caps Off The Year with a Slick Video,” TechCrunch, January 6, 2011, https://techcrunch.com/2011/01/06/airbnb-2010/. 47 just $7.8 million: Tricia Duryee, “Airbnb Raises $112 Million for Vacation Rental Business,” AllThingsD, July 24, 2011, http://allthingsd.com/20110724/airbnb-raises-112-million-for-vacation-rental-business/. 48 Lacy, then at TechCrunch: “Brian Chesky on the Success of Airbnb,” interview by Sarah Lacy, TechCrunch, video, December 26, 2011, https://techcrunch.com/video/brian-chesky-on-the-success-of-airbnb/517158894/. 49 claimed ten thousand listings: Alexia Tsotsis, “Airbnb Freaks Out Over Wimdu,” TechCrunch, June 9, 2011, https://techcrunch.com/2011/06/09/airbnb. 49 (“Technology-Enabled Blitzscaling”): Reid Hoffman, “Blitzscaling 18: Brian Chesky on Launching Airbnb and the Challenges of Scale,” Stanford University, November 30, 2015, https://www.youtube.com/watch?
Bezonomics: How Amazon Is Changing Our Lives and What the World's Best Companies Are Learning From It by Brian Dumaine
activist fund / activist shareholder / activist investor, AI winter, Airbnb, Amazon Web Services, Atul Gawande, autonomous vehicles, basic income, Bernie Sanders, Black Swan, call centre, Chris Urmson, cloud computing, corporate raider, creative destruction, Danny Hillis, Donald Trump, Elon Musk, Erik Brynjolfsson, future of work, gig economy, Google Glasses, Google X / Alphabet X, income inequality, industrial robot, Internet of things, Jeff Bezos, job automation, Joseph Schumpeter, Kevin Kelly, Lyft, Marc Andreessen, Mark Zuckerberg, money market fund, natural language processing, pets.com, plutocrats, Plutocrats, race to the bottom, ride hailing / ride sharing, Sand Hill Road, self-driving car, shareholder value, Silicon Valley, Silicon Valley startup, Snapchat, speech recognition, Steve Jobs, Stewart Brand, supply-chain management, Tim Cook: Apple, too big to fail, Travis Kalanick, Uber and Lyft, uber lyft, universal basic income, wealth creators, web application, Whole Earth Catalog
Nor is Amazon content to fully depend on the local post office or delivery companies such as UPS to move their packages over that crucial last mile from the warehouse to the customer. In 2018, Amazon said it would buy twenty thousand Mercedes vans to launch a program whereby entrepreneurs could, with Amazon’s help, start their own local delivery companies. The company also has a program called Amazon Flex that makes it possible for Uber and Lyft drivers to deliver packages. It’s also experimenting with drone deliveries. It made its first such test delivery in England in 2016 when a drone carried an Amazon Fire TV and a bag of popcorn to a customer near Cambridge. From the time the customer clicked the buy button to the time the drone landed at his home was only thirteen minutes. As big as they are, UPS and