transportation-network company

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pages: 265 words: 69,310

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

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

Randall, and Bryce Glass. Building Web Reputation Systems. O’Reilly Media, 2010. Fenske, Sarah. “After Our Uber Exposé, Their PR Team Tried to Dupe Us.” L.A. Weekly, October 29, 2014. Ferguson, Jordan. “Recent Transportation Network Company Ordinances.” Best Best and Krieger LLP, October 30, 2014. Fernholtz, Tim. “Is Uber Costing New Yorkers $1.2 Billion Worth of Lost Time?” Quartz, July 10, 2015. Fink, Erica.

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?” 27 Paris, “Electric ‘Boris Cars’ Are Coming to London – How Do They Work in Paris?” 28 Biddle, “Here Are the Internal Documents That Prove Uber Is a Money Loser.” 29 Kalanick and Swisher, “Uber CEO: We’re in a Political Battle with an ‘Assh*le.’” 30 Kalanick, “A Leader for the Uber Campaign.” 31 Dempsey, “Taxi Industry Regulation, Deregulation, and Reregulation.” 32 Rosen, “The Knowledge, London’s Legendary Taxi-Driver Test, Puts Up a Fight in the Age of GPS.” 33 Leisy, “TAXICAB DEREGULATION AND REREGULATION IN SEATTLE: LESSONS LEARNED.” 34 Sadlak, “Taxicab Deregulation.” 35 Dubinsky, Gollom, and Rieti, “Cab Driving Riskier than Police Work.” 36 Dale, “Council Votes to Overhaul Toronto Taxi Industry.” 37 Gans, “Is Uber Really in a Fight to the Death?”

When Airbnb ran into business permit problems in Grand Rapids, Michigan or when a neighborhood council threatened to ban Airbnb in Silver Lake, California, it was Peers that rallied Airbnb hosts to lobby councilors on the company’s behalf. When Seattle City Council decided that Lyft and Uber were breaking taxi regulations, it was Peers that mobilized supporters to sign petitions. And these efforts were not in vain: they succeeded in getting councils to back down, and in one of the organization’s most important victories they got the state of California to recognize a new category of transit organization called “Transportation Network Companies,” which created a framework within which Lyft, Uber, Sidecar, and others could operate legally, and which has been imitated in several other states since. In the summer of 2014, Peers listed 75 partner organizations on its web site, and the list gives a snapshot of the Sharing Economy landscape as it hit the mainstream. Spanish company Gudog is “a platform that brings together dog owners and trustworthy dog sitters”; with BoatBound you can “find the perfect boat with or without a captain”; if you prefer eating to boating, you can go to Cookening, a web site where “your host cooks and shares a meal with you, at his or her place.”

pages: 257 words: 64,285

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,, 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

During the long transition, those who cannot afford such cars may come to be vilified as the cause of crashes. —— While people, animals, weather, larger cargo needs, and so on are still potential confounding factors, autonomous vehicles interacting with only autonomous vehicles should be much easier to design and manage than autonomous vehicles in mixed traffic. The next chapter considers how Transport Network Companies such as Lyft and Uber compete with taxis. But with their added labor, such services are too expensive for most people for frequent mobility.173 In contrast, autonomous vehicles total costs will be significantly lower, making it feasible that larger numbers of people replace their personal car (which is parked 23 out of 24 hours) with one that comes on-demand. Discussion: Thought Experiment: "Ze Car, Ze Car."

The car-shedding question remains: how many households will surrender a second (or first) car for the occasional trip?185 Is the market thick enough that the likelihood of finding a car nearby is high enough that it is reliable enough to use? With Car2Go there is no guarantee there will be a car within walking distance. Efforts to rebalance the fleet can be costly. This is where other services (taxi, transport network companies, transit) come in as backups. This is also where autonomous vehicles can be important. Nevertheless, people prefer not to think about every transaction. If they are charged per use, they use less. But they are less happy and more determined to get a car of their own to avoid transaction costs. Cars of course have costs of their own, but they are less frequent and less obvious. If the charges are invisible though, people may not think about them.

In contrast with traditional taxis, the passenger sits shotgun (in the front row passenger seat), and is expected to have a conversation with the driver (which happens in some taxis, though not always). Anecdotally, it appears people who drive for Lyft are more likely to be (though not universally) American citizens or long-term residents, and since they own their own car, less likely to be poor, recently landed immigrants who comprise the taxi drivers in many cities. Lyft is in many ways simply an app with a back-end (rather, 'cloud-based') dispatch service. They claim to be a "transport network company whose mobile-phone application facilitates peer-to-peer ridesharing by enabling passengers who need a ride to request one from drivers who have a car." They insist the drivers are independent (as are the riders). The difference between this and a taxi dispatcher is thin. 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).

pages: 491 words: 77,650

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

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

Industry efforts to create so-called ride-sharing laws are a good case study. Details vary across juris- dictions, but one common goal emerges: to deny workers’ employment status and ensure that platforms are defined as mere intermediaries. In June 2016, free-market think tank R Street’s map of state-level legisla- tion listed only five US states that had not enacted some form of transport network company (TNC) regulation.60 At first glance, these measures set out a balanced approach, permitting on-demand platforms to operate and subjecting them to basic standards, from driver verification to insurance requirements. Upon closer investigation, however, it becomes clear that new legislation frequently favours platforms’ interests. As a Reuters investigation in late 2015 highlighted, key industry players were often closely involved in drafting the laws—many of which contain provisions designed to classify drivers as independent contractors, beyond the scope of state-level employment law protection.61 In some cases, this is achieved through explicit carve-outs.

Screening Mechanical Turk workers’ (Carnegie Mellon University 2010) pubs/note1552-downs.pdf, archived at; ‘The myth of low cost, high quality on Amazon’s Mechanical Turk’, TurkerNation (30 January 2014), of-Low-Cost-High-Quality-on-Amazon-s-Mechanical-Turk, archived at https:// 5. Yanbo Ge, Christopher R. Knittel, Don MacKenzie, and Stephen Zoepf, Racial and Gender Discrimination in Transportation Network Companies (2016) NBER Working Paper No. 22776; Joshua Barrie, ‘This CEO says he has a 3.4 rating on Uber because he’s gay’, Business Insider UK (16 February 2015), http://uk.–2, archived at Other passengers feel that the relative ano- nymity provided by ride-sharing platforms is an improvement on taxis: see Jenna Wortham, ‘Ubering while black’, Medium (23 October 2014), https://medium.

L. 176 Chen, Keith 122 Davies, Paul 174 Cherry 38 Davies, Rob 151 Cherry, Miriam 97, 99, 132, 173, 174, 184 Day, Iris 177 chess robots 1, 6 Deakin, Simon 36, 112, 130, 131, 152, 172, China 12, 38, 153 174, 177, 178, 184, 185 Chowdhry, Amit 181 deductions from pay 15, 19, 60, 63, 67 Christenson, Clayton M. 39 Deep Blue 1 ‘churn’/worker turnover 68 Deliveroo 2, 11, 12, 13, 115 Clark, Shelby 46 collective action by drivers 113 classificatory schemes 13, 28–9, 147 contractual prohibitions 66–7 misclassification 95, 96–100 employment litigation 99 Clement, Barrie 162 internal guidelines 43–4 Clover, Charles 153 safety and liability 122–3 Coase, Ronald 19, 94, 101, 172 wage rates 65 Coase’s theory 19, 20 delivery apps 2 Codagnone, Cristiano 150 demand fluctuations 78 Cohen, Molly 36, 37, 152, 157 Denmark 36 ‘collaborative consumption’ 42 deregulation 37, 40 (see also regulation) collective action 113–15 Dholakia, Utpal 150 collective bargaining rights 48, 65, 82 Didi 2, 12, 38 commission deductions 15, 19, 60, 63, 67 differential wage rates 109–11 commodification of work 76, 77, 110 digital disruption 49, 50 competition 88 ‘digital feudalism’ 83 consumer demand 17–18 digital innovation see innovation consumer protection 10, 112, 121, 128–9 digital market manipulation 123 safety and liability 122–3, 128–9 digital payment systems 5 * * * Index 193 digital work intermediation 5, 11, 13–16 borderline cases 100 disability discrimination 62, 121 identifying the employer 100 discriminatory practices 62, 94, 113, easy cases 102–3 121, 180 functional concept of the disputes 66 employer 101–2, 104 disruptive innovation 39–40, 49, 50, 95 genuine entrepreneurs 103 dockyards 78, 79–80 harder cases 103–4 ‘doublespeak’ 31–50, 71, 95, 97–8, 133 multiple employers 103 Doug H 160, 163 platforms as employers 102–3 down-time 60, 65, 76, 77 ‘independent worker’ 48 Downs, Julie 180 misclassification 95, 96–100 Drake, Barbara 168 ‘personal scope question’ 93 drink driving 133, 184–5 employment taxes 125–7 Dzieza, Josh 163 Engels, Friedrich 81, 168 ‘entrepreneur-coordinator’ 101 economic crises 145 entrepreneurship 6, 8, 21, 32, 42, 43, economic drivers 7, 18–24 45–6, 50, 52 (see also micro- Edwards, Jim 146 entrepreneurs) efficiency 7 autonomy 53–5 Elejalde-Ruiz, Alexia 175 algorithmic control and 55–8 ‘elite worker’ status 61, 67 sanctions and 61–3 ‘emperor’s new clothes’ 71 wages and 58–61 empirical studies 28–9 freedom 8, 14, 27, 29, 47, 49, 51, 52, employer responsibility 104 53, 55, 65–8, 69, 85, 96, 108, 110, employment contracts 94 112, 113 bilateral relationships 100 on-demand trap and 68–70 employment law 4, 9, 10, 38, 84 risk and 86 (see also regulation) genuine entrepreneurs 102, 103 continuing importance 139–40 misclassification 96–7, 98, 101 control/protection trade-off 93–4, 95 ‘personal scope question’ 93 European Union 107, 111, 112, 178 self-determination 63–5 flexibility and environmental impacts 21, 26 innovation and 90 Estlund, Cynthia 137, 185 measuring working time 105–7 Estonia 127 mutuality of obligation 174 Estrada, David 41 new proposals 46–9 euphemisms 44–5 rebalancing the scales 107–8 European Union law 107, 111, 112, 178 collective action 113–15 exploitation 26–7 portable ratings 111–13 Ezrachi, Ariel 150 surge pricing 108–11 ‘risk function’ 131, 132 Facebook 35, 57 workers’ rights 105 FairCrowdWork 114, 179 rights vs flexibility 115–17 Farrell, Sean 164 employment litigation FedEx 97 FedEx 97, 173 feedback 5, 15–16 France 99 Feeney, Matthew 35, 151 Uber 45, 48, 54–5, 98, 99, 106, 115 Field, Frank 26 UK 45, 48, 98–9, 106, 115 financial losses 22–3 US 54–5, 97, 98, 99 ‘financially strapped’ 29 employment status 21, 45, 47 Finkin, Matthew 74, 84, 166, 169 * * * 194 Index Fiverr 12, 13, 24, 78 historical precedents and CEO 17 problems 72, 73–85 Fleischer, Victor 20, 147 rebranding work 4–6, 32 flexibility 8, 10, 12, 107, 108 labour as a technology 5–6 vs rights 115–17 market entrants 88 food-delivery apps 12 matching 13, 14, 18–20 Foodora 2, 12 monopoly power 23–4, 28 Foucault, Michel 55, 159 network effects 23–4 founding myths 34–5 overview 2–3 Fox, Justin 182 perils 6, 26–8, 31 fragmented labour markets 83, 84, 86, platform paradox 5 90, 113 platforms as a service 7–8 France 78 consumer protection 10 employment litigation 99 potential 6, 7, 12, 24–6, 31 Labour Code 114, 176, 179 regulation 9–10 (see also regulation) regulatory battles 36 real cost of on-demand services 119, tax liability 126 121–2 (see also structural ‘free agents’ 28–9 imbalances) Freedland, Mark 174, 175 regulation see regulation Freedman, Judith 111, 178 regulatory arbitrage 20–2 freedom 8, 14, 27, 29, 47, 49, 51, 52, 53, size of the phenomenon 16–17, 145–6 55, 65–8, 69, 85, 96, 108, 110, work on demand 11–29 112, 113 gigwork 13 on-demand trap and 68–70 Giliker, Paula 183 risk and 86 global economic crises 145 Frey, Carl 136, 185 Goodley, Simon 173 Fried, Ina 183 GPS 5, 57 Greenhouse, Steven 66, 164 Gardner-Selby, W. 185 Griswold, Alison 164, 181 gender parity 144 (see also Grossman, Nick 46 discriminatory practices) Gumtree 20 Germany Gurley, Bill 161 regulatory battles 36 Guyoncourt, Sally 178 workers’ rights 114 gift vouchers 105 Hacker, Jacob 86, 170 gig economy Hall, Jonathan 60, 162, 165 business models 12–13, 44, 100 Hammond, Philip 126, 182 cash burn 22–3 Hancock, Matthew 46, 166 clash of narratives 8 Handy 18 classification 13, 28–9 Hardy, Tess 176 critics 2, 3, 8 Harman, Greg 163 digital work intermediation 5, 11, Harris, Seth 48, 49, 105, 157, 175 13–16 Hatton, Erin 82, 169 economic drivers 7, 18–24 Heap, Lisa 177 empirical studies 28–9 Helpling 2 employment law and see employment Hemel, Daniel 147, 170 law Hesketh, Scott 181 enthusiasts 3, 4, 8 hiring practices: historical gigwork vs crowdwork 13 perspective 78, 79 growth 17–18 historical perspective 72, 73–85 ‘humans as a service’ 3–6 Hitch 38 * * * Index 195 Hitlin, Paul 162 Internet Holtgrewe, Ursula 169 collective action 113 HomeJoy 132 Third Wave 73 Hook, Leslie 153 Irani, Lilly 6, 114, 142, 162, 179 Horan, Hubert 22, 148 Isaac, Mike 170, 171 Horowith, Sara 144 Issa, Darrell 41 hostile takeovers 111–12 Howe, Jeff 7, 11, 142 jargon 42–5 Huet, Ellen 153 Jensen, Vernon 167, 168, 170 Human Intelligence Tasks (HITs) 60, 93 Jobs, Steve 35 ‘humans as a service’ 3–6 joint and several liability 104 historical precedents and problems 72, Justia Trademarks 143 73–85 rebranding work 4–6, 32, 40–50 Kalanick, Travis 43, 86 Hunter, Rachel 106, 176 Kalman, Frank 16, 144 Huws, Ursula 27, 141, 150 Kaminska, Izabella 22–3, 44, 90, 148, 156, 169, 171, 172 ‘idle’ time 60, 65, 76, 77 Kaplow, Louis 184 illegal practices 57 Kasparov, Garry 1 immigrant workers 77 Katz, Lawrence 16 incentive structures 67–8 Katz, Vanessa 116, 179 independent contractors 21 Kaufman, Micha 17, 145, 149 Independent Workers Union of Great Kempelen, Wolfgang von 1 Britain (IWGB) 113, 179 Kennedy, John F. 135, 185 industrialization 75 Kenya 36 industry narratives 32–3, 49–50 Kessler, Sarah 151 information asymmetries 32, 54, 87, 131 Keynes, John Maynard 135, 185 innovation 3, 6, 8, 9, 10, 31, 32, 42, 45–6, King, Tom, Lord King of Bridgwater 71 110 cheap labour and 89 Kirk, David 133, 184 disruptive innovation 39–40, 49, 95 Kitchell, Susan 166 historical precedents and problems 72, Klemperer, Paul 165 73–85 Krueger, Alan 16, 48, 49, 60, 105, 106, incentives 86–90 157, 162, 165, 175 myths 72, 83 Krugman, Paul 170 obstacles to 88–90 Kucera, David 186 paradox 72, 87 problematic aspects 85–90 labour law see employment law productivity and 87 Lagarde, Christine 86, 170 shifting risk 85–6 Leimeister, Jan Marco 13 workers’ interests and 89–90 Leonard, Andrew 33, 151 innovation law perspective 36 Lewis, Mervyn 168 ‘Innovation Paradox’ 9 Liepman, Lindsay 184 insecure work 9, 10, 12, 27, 42, 107 Lloyd-Jones, Roger 168 historical perspective 80, 81 loan facilities 68 insurance 123 lobbying groups 32, 47, 48 intermediaries 83 (see also digital work Lobel, Orly 11, 37–8 intermediation) low-paid work 9, 26–7, 40–2, historical perspective 79–80 59, 61 International Labour Organization low-skilled work 76, 77, 82 (ILO) 4, 83, 97, 169, 173 automation and 138 * * * 196 Index Lukes, Steven 159 Murgia, Madhumita 182 Lyft 2, 12, 13, 38, 41, 42, 76 mutuality of obligation 174 algorithmic control mechanisms 56 network effects 23–4 regulatory battles 35 Newcomer, Eric 148, 165 Uber’s competitive strategies 88 Newton, Casey 164 Nowag, Julian 183 McAfee, Andrew 137, 138, 185 Machiavelli, Niccolo 93, 172 O’Connor, Sarah 43, 155 machine learning 136, 137 ODesk 60 McCurry, Justin 186 O’Donovan, Caroline 144, 164, 181 Malone, Tom 73 Oei, Shu-Yi 124, 125, 132, 147, 182, 184 Mamertino, Mariano 161, 163 Ola 2, 12 market entrants 88 on-demand trap 68–70 market manipulation 123 on-demand work 11– 29 Markowitz, Harry 184 real cost of on-demand services 119, Marsh, Grace 182 121–2 (see also structural Marshall, Aarian 186 imbalances) Martens, Bertin 150 Orwell, George 31, 151 Marvit, Moshe 142 Osborne, Hilary 164 Marx, Patricia 119–20, 180 Osborne, Michael 136, 185 matching 13, 14, 18–20 outsourcing Maugham, Jolyon 182 agencies 40 Mayhew, Henry 77, 78, 79, 167 ‘web services’ 2 Mechanical Turk 1, 2, 6 outwork industry 74–5, 76–7, 79, 80, 89 mental harm 57–8 Owen, Jonathan 178 Meyer, Jared 149 ‘micro-entrepreneurs’ 8, 21, 46, 49, Padget, Marty 186 52–3, 63 Pannick, David, Lord Pannick 110 ‘micro-wages’ 27 Pasquale, Frank 8, 40, 154 middlemen 80 Peck, Jessica Lynn 26 minimum wage levels 3, 9, 21, 26, 27, 59, peer-to-peer collaboration 42, 43 94, 104, 105 32–3 minimum working hour guarantees 108 performance standard probations 61 misidentification 95, 96–100 personal data 112, 178 mobile payment mechanisms 5 ‘personal scope question’ 93 monopoly power 23–4, 28 Pissarides, Christopher 19, 147 Morris, David Z. 171 platform paradox 5 Morris, Gillian 174 platform responsibility 122–3, 128 MTurk 2, 3, 4, 11, 12, 24–5, 76, 139, platforms as a service 7–8 161–2, 163 consumer protection 10 algorithmic control mechanisms 56 regulation 9–10 (see also regulation) business model 100, 101, 103, 104 Plouffe, David 154 commission deductions 63 Poe, Edgar Allen 1 digital work intermediation 14, 15 Polanyi’s paradox 138–9 matching 19 political activism 114 payment in gift vouchers 105 portable ratings 111–13 quality control 120 Porter, Eduardo 171 TurkOpticon 114 ‘postindustrial corporations’ 20 wage rates 59, 60, 61 Postmates 57, 63, 121 * * * Index 197 Poyntz, Juliet Stuart 168 structural imbalances 130, 131 Prassl, Jeremias 174, 175, 176, 177, robots 136–7 178, 183 Mechanical Turk 1, 6 precarious work 9, 10, 12, 27, 42, 107 Rodgers, Joan 177 historical perspective 80, 81 Rodriguez, Joe Fitzgerald 181 price quotes 121–2 Rönnmar, Mia 175 surge pricing 58, 108–11, 122 Roosevelt, Franklin D. 133, 185 Primack, Dan 148 Rosenblat, Alex 54, 56, 65, 123, 131, 159, productivity 87 160, 163, 164, 182, 184 public discourse 69 Rosenblat, Joel 165 public health implications 27 Rubery, Jill 84, 169 punishment 57 (see also sanctions) Ryall, Jenny 181 quality control 5, 80, 120 safe harbours 47, 49 safety and liability 122–3, 128–9 rating mechanisms 5, 15–16, 53–4 sanctions 61–3 (see also punishment) algorithms 54, 55, 87–8 Sandbu, Martin 87, 170 discrimination 62, 113 Scheiber, Noam 164 portable ratings 111–13 Schmiechen, James 167, 168, 169 sanctions and 61–3 Schumpeter, Joseph 133 rebranding work 4–6, 32, 40–50 self-dealing 123 regulation 9–10 (see also employment law) self-determination 36–7, 47, 63–5 industry narratives 32–3, 49–50 (see also autonomy) new proposals 31, 46–9, 50 self-driving cars 89, 137 opponents 31, 33–4 sexual assaults 121, 180–1 Disruptive Davids 34–7 sexual discrimination 62, 144, 180 disruptive innovation theory ‘sham self-employment’ 97 39–40, 49 sharing economy 7, 20, 51 New Goliaths 37–40 critics 32–3 regulatory battles 35–7, 47–9 disruptive innovation 39, 49 safe harbours 47, 49 enthusiasts 61 self-regulation 36–7, 47 Sharing Economy UK 33, 37 shaping 32–3, 45–9 sharing platforms 116 regulatory arbitrage 20 –2, 147 Shavell, Steven 184 regulatory experimentation 36 Shleifer, Andrei 111, 178 Reich, Robert 108, 176 Shontell, Alyson 161 Relay Rides 46 Silberman, Six 61, 114, 162, 163, 179 ‘reluctants’ 29 Silver, James 156, 158 reputation algorithms 54 Singer, Natasha 43, 155, 156 ride-sharing/ridesharing 2, 21, 38, 41 Slee, Tom 32, 53, 142, 151, 155, 158, 159 (see also taxi apps) Smith, Adam 73 algorithmic control mechanisms 55–6 Smith, Jennifer 170 business model 102–3 Smith, Yves 148 discriminatory practices 62, 121 social media 114 maltreatment of passengers 121 social partners 10, 94 ride-sharing laws 47 social security contributions 21, 125–7 Ries, Brian 181 social security provision 3, 48, 131 Ring, Diane 124, 125, 132, 147, 182, 184 sociological critique 27–8 Risak, Martin 102, 175 specialization 75 risk shift 85–6 Spera 51, 158 * * * 198 Index Sports Direct 40–1 taxi regulation 21, 36, 37, 38, 114 Standage, Tom 141 vetting procedures 121 standardized tasks 76 tech:NYC 33 Stark, Luke 54, 56, 65, 159, 160, 163, 164 technological exceptionalism 6, 128 start-up loans 68 technological innovation see innovation Stefano, Valerio De 84, 169 technology 5–6, 27 Stigler, George 32, 151 unemployment and 135, 137, 140 Stone, Katherine 67, 165 terminology 42–5 structural imbalances time pressure 57 business model 130–2 Titova, Jurate 183 digital market manipulation 123 TNC, see transportation network levelling the playing field 127–32 company platform responsibility 122–3, 128 Tolentino, Jia 166 real cost of on-demand services 119, Tomassetti, Julia 20, 147, 156, 171 121–2 Tomlinson, Daniel 163 safety and liability 128–9 trade unions 65, 113, 114, 178, 179 sustainability 132–3 transaction cost 19 tax obligations 123–4, 129, 131, 132 transport network company (TNC) employment taxes and social regulation 47–8 security contributions 125–7 Truck arrangements 105 VAT 124–5, 129 Tsotsis, Alex 151 Stucke, Maurice 150 TurkOpticon 114, 162, 163, 179 Sullivan, Mike 180 Summers, Lawrence 111, 131, 178, 184 Uber 2, 11, 12, 43 Sundararajan, Arun 36, 37, 41, 73, 74, 75, algorithmic control mechanisms 56, 151, 152, 157, 166, 167 57, 58 Supiot, Alain 130–1, 177, 184 arbitration 165 surge pricing 58, 108–11, 122 autonomous vehicles and 89 survey responses 120 ‘churn’/worker turnover 68 Swalwell, Eric 41, 154 commission deductions 63 competitive strategies 88 takeovers 111–12 consumer demand 18 ‘task economies’ 76, 77, 79 control mechanisms 54 Task Rabbit 2, 12, 13, 46, 143–4, 163 creation of new job business model 100, 101, 160 opportunities 77–8 company law 56 digital work intermediation 14, 15 contractual prohibitions 66 disruptive innovation 39 digital work intermediation 14, 15–16 driver income projections 51 financial losses 22 Driver-Partner Stories 25, 149 founding myth 34–5 driver-rating system 158, 160 regulatory arbitrage 20 employment litigation terms of service 44, 53, 122, 158, 181 France 99 wage rates 64 UK 45, 48, 98, 106, 115 working conditions 57 US 54–5, 99 Taylor, Frederick 52–3, 72, 158 financial losses 22, 23 tax laws 84 ‘Greyball’ 88, 170 tax obligations 123–4, 129, 131, 132 ‘Hell’ 88, 170 employment taxes and social security loss-making tactics and market share 64 contributions 125–7 monopoly power 23 VAT 124–5, 129 positive externality claims 132–3 taxi apps 12, 20 regulatory arbitrage 20 * * * Index 199 regulatory battles 35, 36 Vaidhyanathan, Siva 40, 154 resistance to unionization 65, 178 value creation 18–19, 20 risk shift 86 van de Casteele, Mounia 182 safety and liability 122–3, 180–1 VAT 124–5, 129 sale of Chinese operation 38 Verhage, Julie 147 surge pricing 58, 122 vicarious liability 128 tax liability 125, 126, 127 unexpected benefits 26 wage rates 58–61, 64, 65 wage rates 58, 59, 60–1, 64, 65, 127 Wakabayashi, Daisuke 171 working conditions 113, 178 Warne, Dan 115 UberLUX 14 Warner, Mark 16 UberX 14, 51, 60 Warren, Elizabeth 127, 183 UK Webb, Beatrice and Sidney 80, 168 collective action 113 Weil, David 83, 169 employment litigation 45, 48, 98–9, 106 welfare state 130, 131 tax liability 124–5, 126 Wilkinson, Frank 84, 130, 131, 169, unemployment 135, 137, 140, 145 172, 184, 185 Union Square Ventures 46 Wong, Julia Carrie 170 unionization 10, 65, 113, 114, 178, 179 work on demand 11–29 ‘unpooling’ 147 worker classification 28–9, 147 Unterschutz, Joanna 178 misclassification 95, 96–100 Upwork 12, 76, 144 workers’ rights 105 algorithmic control mechanisms 56 vs flexibility 115–17 business model 100, 160 working conditions 57, 68–9 commission deductions 63, 67 historical perspective 77, 81 US Uber 113, 178 discriminatory practices 121 working time 105–7 employment litigation 54–5, 97, 98, 99 Wosskow, Debbie 157 regulatory battles 36, 47 Wujczyk, Marcin 178 tax liabilities 126–7 taxi regulation 36, 114 Yates, Joanne 73 transport network company (TNC) YouTube 58 regulation 47–8 user ratings 5, 15–16, 53–4, 55 Zaleski, Olivia 165 portable ratings 111–13 zero-hours contracts 40, 41, 107 sanctions and 61–3 Zuckerberg, Mark 35 * * * Document Outline Cover Humans as a Service: The Promise and Perils of Work in the Gig Economy Copyright Dedication Contents Introduction Welcome to the Gig Economy Humans as a Service Rebranding Work The Platform Paradox Labour as a Technology Making the Gig Economy Work Platforms as a Service Exploring the Gig Economy Charting Solutions A Broader Perspective 1.

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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,, 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

“New LAX Rule: Taxi Drivers Who Discriminate Will Lose Permits,” CBS Los Angeles, February 2, 2016,; Yanbo Ge, Christopher R. Knittel, Don MacKenzie, and Stephen Zoepf, “How Apps Like Uber Perpetuate the Cab Industry’s Racial Discrimination,” Alternet, January 6, 2017, 2. Yanbo Ge, Christopher R. Knittel, Don MacKenzie, and Stephen Zoepf, “Racial and Gender Discrimination in Transportation Network Companies,” National Bureau of Economic Research, October 2016, 3. Andrew Beinstein and Ted Sumers, “How Uber Engineering Increases Safe Driving with Telematics,” UBER Engineering, June 29, 2016, 4. In other publicly reported incidents of sexual harassment by passengers, drivers similarly cite weak communications from Uber in responding to their incidents.

Kimberly Reeves, “Uber’s Big Win: Texas Ridesharing Rules Bill Passes through Senate,” Austin Business Journal, May 17, 2017, 31. HR 100, 85 Cong. (2017) (enacted), 32. Joy Borkholder, Mariah Montgomery, Miya Saika Chen, and Rebecca Smith, “Uber State Interference: How Transportation Network Companies Buy, Bully, and Bamboozle Their Way to Deregulation,” National Employment Law Project and the Partnership for Working Families, January 2018, 33. Rosenblat, “Uber’s Drive-By Politics.” 34. Mike Ramsey and Douglas MacMillan, “Carnegie Mellon Reels after Uber Lures away Researchers,” Wall Street Journal, May 31, 2015, 35.

Darrell Etherington, “Lyft Raises $1 Billion at $11 Billion Valuation Led by Alphabet’s CapitalG,” Tech Crunch, October 19, 2017, 3. Rani Molla, “Uber’s Market Share Has Taken a Big Hit,” Recode, August 31, 2017, 4. San Francisco County Transportation Authority, “TNCs Today: A Profile of San Francisco Transportation Network Company Activity,” June 2017, 5. Jessica, “New Survey: Drivers Choose Uber for Its Flexibility and Convenience,” Uber Newsroom, December 7, 2015, 6. Lyft, “Explore,” February 14, 2018, 7. Uber, “Get there,” February 14, 2018, 8. Harry Campbell, “2018 Uber and Lyft Driver Survey Results—The Rideshare Guy,” February 26, 2018, The Rideshare Guy,

pages: 195 words: 52,701

Better Buses, Better Cities by Steven Higashide

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

Musk claimed he would create an “electric skate” system that would carry private cars and small pods carrying up to sixteen people each. The actual carrying capacity of this hypothetical system? About 2,000 passengers an hour.20 In other words, the electric skate will carry far fewer people than the Chicago Transit Authority’s Blue Line subway, which already goes to O’Hare. 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.

Five months before she released the ad that helped propel her into national politics, Pressley was standing with advocates at the LivableStreets Alliance, calling for bus-only lanes on Boston’s streets.23 Conclusion Winning Mindsets and Growing Movements When you compare the fortunes of bus systems in different places in the United States and around the world, you begin to realize that the extended decline of bus ridership in some cities is not an inevitable consequence of changes in demographics, technologies, or consumer preferences. It’s a consequence of stasis. Many transit systems have held still while cities, markets, and technologies around them have transformed. Where people live and work is changing every year. Deliveries, transportation network companies, and an influx of high-income people to central cities together have put more vehicles on the road, worsening traffic. And thanks to the rise of Uber and Lyft, bikeshare, and scooters, there are more ways for people to get around cities than ever. Yet in many cities, the most effective way to move the masses has stood still. Many agencies still dispatch buses using a schedule, knowing full well that active management is the only way to defeat bunching.

pages: 472 words: 117,093

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

"Robert Solow", 3D printing, additive manufacturing, AI winter, Airbnb, airline deregulation, airport security, Albert Einstein, Amazon Mechanical Turk, Amazon Web Services, artificial general intelligence, augmented reality, autonomous vehicles, backtesting, barriers to entry, bitcoin, blockchain, British Empire, business cycle, business process, carbon footprint, Cass Sunstein, centralized clearinghouse, Chris Urmson, cloud computing, cognitive bias, commoditize, complexity theory, computer age, creative destruction, crony capitalism, crowdsourcing, cryptocurrency, Daniel Kahneman / Amos Tversky, Dean Kamen, discovery of DNA, disintermediation, disruptive innovation, distributed ledger, double helix, Elon Musk,, 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

., 305 Spotify, 146–48 stacks, 295–96, 298 Stallman, Richard, 243 standard partnership creativity and, 119, 120 defined, 37 demand for routine skills and, 321 HiPPO and, 45, 59 inversion of, 56–60 modified by data-driven decision making, 46–60 structure of, 31 Starbucks, 185 statistical pattern recognition, 69, 72–74, 81–82, 84 statistical prediction, 41 status quo bias, 21 steampunk, 273 Sterling, Bruce, 295, 298 S3 (Amazon Web Service), 143 Stites-Clayton, Evan, 263 STR, 221 “stranger-danger” bias, 210 streaming services, 146–48 Street, Sam, 184 Street Bump, 162–63 Stripe, 171–74, 205 structured interviews, 57 students, gifted, 40 Sturdivant, Jeremy, 286 subscription services, 147–48 suitcase words, 113 Suleyman, Mustafa, 78 “superforecasters,” 60–61 supervised learning, 76 supply and demand; See also demand; demand curves; supply curves O2O platforms for matching, 193 platforms and, 153–57 and revenue management, 47 supply curves, 154–56 Supreme Court, US, 40–41 surge pricing, 55 Svirsky, Dan, 209n Sweeney, Latanya, 51–52 Swift, Taylor, 148 switching costs, 216–17, 219 Sydney, Australia, hostage incident (2014), 55 symbolic artificial intelligence, 69–72 introduction of, 69–70 reasons for failure of, 70–72 synthetic biology, 271–72 systems integration, 142 System 1/System 2 reasoning, 35–46 and confirmation bias, 57 defined, 35–36 and second-machine-age companies, 325 undetected biases and, 42–45 weaknesses of, 38–41 Szabo, Nick, 292, 294–95 Tabarrok, Alex, 208–9 Tapscott, Alex, 298 Tapscott, Don, 298 Tarantino, Quentin, 136n TaskRabbit, 261, 265 taxi companies, Uber’s effect on, 201 TCE (transaction cost economics), 312–16 TechCrunch, 296 technology (generally) effect on employment and wages, 332–33 effect on workplace, 334 as tool, 330–31 Teespring, 263–64 Teh, Yee-Whye, 76 telephones, 129–30, 134–35 tenure predictions, 39 Tesla (self-driving automobile), 81–82, 97 Tetlock, Philip, 59 text messages, 140–41 Thank You for Being Late (Friedman), 135 theories, scientific, 116–17 theory of the firm, See TCE (transaction cost economics) Thierer, Adam, 272 “thin” companies, 9 Thingiverse, 274 Thinking, Fast and Slow (Kahneman), 36, 43 Thomas, Rob, 262 Thomke, Stefan, 62–63 3D printing, 105–7, 112–13, 273, 308 Thrun, Sebastian, 324–25 TNCs (transportation network companies), 208 TØ.com, 290 Tomasello, Michael, 322 Topcoder, 254, 260–61 Torvalds, Linus, 240–45 tourists, lodging needs of, 222–23 Tower Records, 131, 134 trade, international, 291 trading, investment, 266–70, 290 Transfix, 188, 197, 205 transparency, 325 transportation network companies (TNCs), 208; See also specific companies, e.g.: Uber Transportation Security Administration (TSA), 89 Tresset, Patrick, 117 trucking industry, 188 T-shirts, 264 tumors, 3D modeling of, 106 Turing, Alan, 66, 67n Tuscon Citizen, 132 TV advertising, 48–51 Tversky, Amos, 35 Twitter, 234 two-sided networks credit cards, 214–16 Postmates, 184–85 pricing in, 213–16, 220 pricing power of, 210–11 switching costs, 216–17 Uber, 200, 201, 218–19 two-sided platforms, 174, 179–80 Two Sigma, 267 Uber driver background checks, 208 future of, 319–20 information asymmetry management, 207–8 lack of assets owned by, 6–7 as means of leveraging assets, 196–97 network effects, 193, 218 as O2O platform, 186 origins, 200–202 and Paris terrorist attack, 55 pricing decisions, 212–15, 218–19 rapid growth of, 9 regulation of, 201–2 reputational systems, 209 routing problems, 194 separate apps for drivers and riders, 214 and Sydney hostage incident, 54–55 value proposition as compared to Airbnb, 222 UberPool, 9, 201, 212 UberPop, 202 UberX, 200–201, 208, 212, 213n Udacity, 324–25 unbundling, 145–48, 313–14 unit drive, 20, 23 Universal Music Group, 134 University of Louisville, 11 University of Nicosia, 289 unlimited service ClassPass Unlimited, 178–79, 184 Postmates Plus Unlimited, 185 Rent the Runway, 187–88 unsupervised learning, 76, 80–81 Upwork, 189, 261 Urmson, Chris, 82 used car market, information asymmetry and, 207 Usenet, 229, 271 user experience/interface as platforms’ best weapon, 211 and successful platforms, 169–74 users, as code developers, 242 “Uses of Knowledge in Society, The” (Hayek), 235–37 utilization rate, O2O platforms, 196–97 Van Alstyne, Marshall, 148 Van As, Richard, 272–74 Vancouver, Canada, Uber prohibition in, 202 venture capital, DAO vs., 302 verifiability, 248 verifiable/reversible contributions, 242–43 Verizon, 96, 232n Veronica Mars (movie), 262 Veronica Mars (TV show), 261–62 Viant, 171 video games, AI research and, 75 videos, crowd-generated, 231–32 Viper, 163 virtualization, 89–93; See also robotics vision, Cambrian Explosion and, 95 “Voice of America” (Wright), 229–30 von Hippel, Eric, 265 wage declines, 332 Wagner, Dan, 48–50 Waldfogel, Joel, 144 Wales, Jimmy, 234, 246–48 Walgreens, 185 Walmart, 7, 47 Wanamaker, John, 8–9 warehousing, 102–3, 188 Warner Brothers, 262 Warner Music Group, 134 Washington Post, 132 Washio, 191n waste reduction, 197 Watson (IBM supercomputer) health claim processing, 83 Jeopardy!

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. Instead, these companies used their platforms’ user interfaces to overcome the information asymmetries that plagued their markets.

pages: 340 words: 92,904

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

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

Competitors like Sidecar (launched January of 2012) and Lyft (founded summer of 2012 as an extension of an earlier city-to-city ridesharing service known as Zimride) noticed the potential upside for a business that could extract revenue from travelers without actually investing in anything as expensive as buses, trains, or even cars; all that they needed were software algorithms and marketing. Though the California Public Utilities Commission, under pressure from existing taxi services, shut them all down, it allowed them to reopen the following year as what the state of California now calls “Transportation Network Companies.” Uber, by far the biggest kid on the ridesharing block, expanded to Paris, Toronto, and London in 2012, and hasn’t looked back. By 2015 you could download the Uber app to your smartphone and request an Uber pickup in more than two hundred cities in forty-five countries.e This kind of growth attracts all sorts of attention. USA Today picked Uber as their “tech company of the year” in 2013, and venture capitalists have invested so much in the company that, as of the end of 2014, it had a valuation somewhere north of $40 billion.

Ferguson, 215 and positive feedback, 213 and racial discrimination, 214–219 redistributive or vertical, 214 return-to-source or horizontal, 214 and TEA-21, SAFETEA, and MAP-21 bills, 213–214, 214n See also Transportation Transportation infrastructure, 228–230 and ASCE Report Card on roads, 206–208 building and maintaining, 229–230 car-centric, future of, 69–70 deficient and obsolete, 228–229 investment in, 228–229 See also Bridges; Roads; Transportation Transportation Network Companies, 199 Transportation network(s) and attractors, 163–164, 166 in Boston, 166, 167, 188 and cars, 180 in Charleston, 166–170 and destination, 164, 165 and geometry, 163 in Houston, 171–173, 220 multimodal/multinodal, 61, 157, 163–165, 169, 180–181 in New York City, 48–63, 212 in Paris, 166–167, 167 (map) and power grid, comparison between, 208 and reliability and frequency, 170–171 and route maps, 170 and routes, 165 in Salt Lake City, 191–195 in San Francisco, 188 and transport modes, 164–165 and trip generation, 163–165 in Vancouver, 160–163, 165, 218 in Zurich, 174–180, 208–209 See also Grids; Transportation; Transportation systems Transportation policy and politics, 224–227 See also Transportation Transportation system(s), 156–158, 213 and connectivity, 159–160 in crisis, 61–63 and efficiency and flexibility, 156–157 and environmental concerns, 62 and gasoline, dependence on, 62 and grid patterns, 158 (see also Grids) and mobile transport devices, 209–210 and peak demand, 206 and smart cities, 208–210 See also Grids; Transportation; Transportation networks TRAX (Utah), 192–193, 194–195 Trevelyan, George Macauley, 94–95 Triborough Bridge, 30 Trip generation, 133, 163–165, 180 Trolley car, 6, 9 Trolleybus, 163, 163n, 169, 174, 175, 176, 179 Trust, 99 Tunnel engineering, 17 Uber (ride-matching/sharing service), 75, 196–205, 198n, 235 complaints against, 199–201 and liability insurance, 202–203 and surge pricing, 200, 201 and VIM, 203–204 See also Ride-matching/sharing services UberX, 199 Underhill, Paco, 143 United Cities Motor Transport, 9n United Kingdom, 116 United States leading cause of death in, 134 walking and cycling in, 150–151 University College London, 239 University of Hawaii, 231 University of Michigan, Transportation Research Institute, 73, 79 University of West Virginia, 232 Urban heat islands, 118–119 Urban Land Institute, 84 Urban living, 83–85, 84n, 85n and Millennials, 111–112 and public transit, and liberals versus conservatives, 225–226 versus suburban living, 70, 86–88, 110–112 and walking (see Walkability) See also Cities Urban Space for Pedestrians (Zupan and Pushkarev), 147 US Army, Cross-Country Motor Transport Train, 15 US Department of Defense, 183 Advanced Research Projects Agency, 233 US Department of Transportation, 209 USA Today, 199 Utah, 192–195 Utah Transit Authority (UTA), 193–195, 193n Value of a Statistical Life (VSL), 40–42 Vancouver, British Columbia, 167, 180, 218 transportation network in, 160–163, 165, 218 Vanderbilt, William K., 14, 14n Vehicle miles traveled.

pages: 375 words: 88,306

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

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

First, an SRO must establish credibility early on through its performance. Second, self-regulatory actors must demonstrate strong enforcement capabilities. Third, SROs must be perceived as legitimate and independent. And finally, an SRO must take advantage of participants’ reputational concerns and social capital.26 The state of California has pioneered a self-regulatory approach for one sector of the sharing economy, through the creation of Transportation Network Companies (TNCs) in 2013. As described in detail by Catherine Sandoval, the commissioner of the California Public Utilities Commission (CPUC), at the 2015 Federal Trade Commission workshop about the sharing economy, this represents an interesting partnership between government and sharing economy platforms. Here’s how it works. The CPUC has defined a set of standards that drivers of smartphone-based point-to-point urban transportation vehicles (taxis) need to conform to.

background screening, 50–51 contractor classification and, 160, 161 new social safety net and, 191 platform, 43–44 platform independence, 194 pricing, supply, and merchandizing, 194 TechCrunch, 11 Telang, Rahul, 112 Teran, Dan, 160 “There’s an Uber for Everything” (Fowler), 11 Thierer, Adam, 146 Thin sharing economies, 34 Threadless, 76 ThreeBirdNest, 107, 125, 177 3-D printing, 57–58 Thumbtack, 3, 6, 77, 164 Tiger Global Management, 25 TimeRepublik, 35 TimesFree, 43 Timms, Henry, 23, 136 Tincq, Benjamin, 23–25, 199 Tool libraries, 15 Total factor productivity (TFP), 116–117 Trade School, 43, 82 Traity, 64–65, 98 Transparency, mandated, 157 Transportation Network Companies (TNCs), 153 Trust, 4, 6, 12, 28, 35, 39, 47–50 brand-based, 144–146 history of (in world trade), 142–143 digitization of, 60–65 reputation and, 97–98 Tujia, 6, 121 Tumblr, 85 Turkle, Sherry, 45 Turo, 3, 80, 107, 177, 190 Tusk, Bradley, 136 Tuzhilin, Alexander, 112 Twitter, 29, 85 Uber, 2, 3, 6, 10, 19, 48, 154, 161, 186, 197, 203 class-action lawsuit and, 160 consumer behavior changed by “data Darwinism” and, 200–201 data science and, 157, 200–201 driver classifications, 159, 160, 176, 182, 183 driver protests, 200 entrepreneurial nature of, 192, 194 financing of, 25 gift economy aspects, 35 impact on traditional taxis, 122–123 local network effects, 119–120 as microbusiness, 77, 113 new social safety net and, 191 platform, 84 platform independence, 194 pricing, supply, and merchandizing, 194, 195 regulatory challenges, 135 social capital and, 62, 64 trust and, 145 UberPool, 66 “Uber Alles” (Surowecki), 19 Ulbricht, Ross, 86 Union Square Ventures (USV), 17, 23, 25, 85–86, 90, 157, 189 United States Conference of Mayors, 131, 147 Universal Avenue, 77 UnSYSTEM, 85–86 Upwork, 77, 162, 163.

pages: 441 words: 96,534

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

autonomous vehicles, bike sharing scheme, Boris Johnson, business cycle, call centre, car-free, carbon footprint, clean water, congestion charging, crowdsourcing, digital map, edge city, Edward Glaeser,, 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

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

See also Congestion pricing addressing by road-building and widening projects, 61–64 capacity of roads and, 61–64 economic costs of, 41 volume of roads and, 64 Traffic fatalities, 207–31 2008 strategic plan, 211–12 Diarrassouba on First Avenue, 207–8 of older New Yorkers, 214–15 speed limits and, 64–65, 213–15 statistics on, 2, 14, 144, 208–9, 211, 219–20, 228 Times Square, 92, 102 Traffic lights, 92–93, 211–12 Traffic safety, 210–31 advocacy groups and, 230–31 bikes and, 214, 221–24 campaign and projects, 214–20 counterproductive policies, 224–28 Delancey Street redesign, 215, 216, 217, 217 DOT study, 212–15 global issues, 228–29 measuring, 211 New York City ranking, 210 Traffic signals, 38–39, 54, 85, 261–62 TransLink, 67–68 TransMilenio, 234–35 Transportation Alternatives (TA), xiv, 177, 230 Transportation costs, 27–30 Transportation Department, New York City (NYCDOT), 13–15. See also specific projects chief mission, xiv–xvi DOT Academy, 39 head count, xiv–xv implementation of projects, xvi job offer by Bloomberg, xi–xii, xiii, xiv, 37 Planning and Sustainability Division, 38 PlaNYC. See PlaNYC Transportation Department, United States (USDOT), 212, 229–30, 238 Transportation network companies (TNCs), 284–85 Transport for London, 129, 132, 258 Triborough Bridge and Tunnel Authority, 15 Tri-State Transportation Campaign, xiv, 177, 236 Trottenberg, Polly, 229–30 Trucks and trucking, 277–78 Turner, Matthew, 62 Twelve-foot lanes, 49–51 23rd Street, Madison Square plaza, 85, 86, 86–89, 88 Two-way model street, 56–59, 57 rearranging, 58–59, 58–59 U Uber, 284–85 Union Square, 85, 93 United Nations (UN), 15, 228 United States Department of Transportation (USDOT), 212, 229–30, 238 University of Toronto, 62 Urban density.

pages: 190 words: 62,941

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

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

“My favorite thing in going from Del Monte and government to a start-up was how fast things moved,” she says. “We were a bunch of happy warriors.” State legislatures are quirky places, often meeting only part time, and 2015 happened to be a big year for Uber because most states were in session. Kay monitored the various jurisdictions where Uber was under attack. A Seattle ordinance, for example, capped “transportation network companies,” or TNCs, at one hundred vehicles at a time. Kay worked on legislation in Colorado, which swung from regulation so restrictive it would shut down Uber in Denver to passing one of the first laws that lightly regulated and legalized ridesharing throughout the state. She eventually moved on to Las Vegas, the first city Uber pulled out of and where it eventually won the right to do business—in 2015.

pages: 561 words: 157,589

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

4chan, Affordable Care Act / Obamacare, Airbnb, Alvin Roth, Amazon Mechanical Turk, Amazon Web Services, artificial general intelligence, augmented reality, autonomous vehicles, barriers to entry, basic income, Bernie Madoff, Bernie Sanders, Bill Joy: nanobots, bitcoin, blockchain, Bretton Woods, Brewster Kahle, British Empire, business process, call centre, Capital in the Twenty-First Century by Thomas Piketty, Captain Sullenberger Hudson, Chuck Templeton: OpenTable:, Clayton Christensen, clean water, cloud computing, cognitive dissonance, collateralized debt obligation, commoditize, computer vision, corporate governance, corporate raider, creative destruction, crowdsourcing, Danny Hillis, data acquisition, deskilling, DevOps, Donald Davies, Donald Trump, Elon Musk,, 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

After initial skepticism, Uber copied the peer-to-peer model a year later. Driven by an aggressive CEO, a stronger technical focus on logistics and marketplace incentives, a take-no-prisoners corporate culture, and huge amounts of capital, it has spent billions to outpace its rivals. Lyft is still a strong contender in the United States, gaining, but in distant second place. The amount of capital raised turned out to be surprisingly important. While the transportation network companies, or TNCs, as they are sometimes called, don’t have to spend money buying cars, they have spent billions on marketing, subsidized fares, and driver incentives in a race to build the biggest network of customers and drivers. Uber’s willingness to sidestep regulators was also part of its success. Sidecar and Lyft spent time working with the California Public Utilities Commission to craft new rules to legitimize their novel approach.

Algorithmic dispatch and routing is in its early stages; to think otherwise is to believe that the evolution of Google Search ended in 1998 with the invention of PageRank. For this multi-factor optimization to work, though, Uber and Lyft have to make a deep commitment to evolving their algorithms to take into account all of the stakeholders in their marketplace. It is not clear that they are doing so. Understanding the differences between means and ends is a good way to help untangle the regulatory disagreements between the TNCs (transportation network companies) and taxi and limousine regulators. Both parties want enough safe, qualified drivers available to meet the needs of any passenger who wants a ride, but not so many drivers that drivers don’t make enough money to keep up their cars and give good service. The regulators believe that the best way to achieve these objectives is to limit the number of drivers, and to certify those drivers in advance by issuing special business licenses.

pages: 294 words: 82,438

Simple Rules: How to Thrive in a Complex World by Donald Sull, Kathleen M. Eisenhardt

Affordable Care Act / Obamacare, Airbnb, asset allocation, Atul Gawande, barriers to entry, Basel III, Berlin Wall, carbon footprint, Checklist Manifesto, complexity theory, Craig Reynolds: boids flock, Credit Default Swap, Daniel Kahneman / Amos Tversky, diversification, drone strike,, European colonialism, Exxon Valdez, facts on the ground, Fall of the Berlin Wall, haute cuisine, invention of the printing press, Isaac Newton, Kickstarter, late fees, Lean Startup, Louis Pasteur, Lyft, Moneyball by Michael Lewis explains big data, Nate Silver, Network effects, obamacare, Paul Graham, performance metric, price anchoring, RAND corporation, risk/return, Saturday Night Live, sharing economy, Silicon Valley, Startup school, statistical model, Steve Jobs, TaskRabbit, The Signal and the Noise by Nate Silver, transportation-network company, two-sided market, Wall-E, web application, Y Combinator, Zipcar

They soon launched Air Mattress Bed & Breakfast, later Airbnb. Airbnb is among the most successful of the shared-economy companies. Unlike many traditional businesses, shared-economy companies have no single base of customers. Rather, these companies provide two-sided markets that connect sellers (or people with something to share) with buyers (who are willing to pay for the product or service)—like the transportation-network company Lyft, which connects passengers who need a ride to drivers who have a car, and TaskRabbit, an errand-outsourcing company that connects people who need something done with “taskers” who will do the job. For Airbnb, it’s connecting local residents with room to spare and travelers who need a place to stay. To grow, shared-economy companies have to keep both sides of the market—sellers and buyers—happy.

pages: 366 words: 94,209

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

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

“Worldwide Revenue of Major Toy Companies in 2012 (in Million U.S. Dollars),”, 2015. 22. Media Squat, WFMU, June 8, 2009. 23. Megan Rose Dickey, “We Talked to Uber Drivers—Here’s How Much They Really Make,”, July 18, 2014. 24. Aaron Sankin, “Why New York Taxis Are Powerless Against Uber’s Price War,”, July 8, 2014. 25. Don Jergler, “Transportation Network Companies, Uber Liability Gap Worry Insurers,”, February 10, 2014. 26. Tim Bradshaw, “Uber’s Tactics Pay Off as It Goes Head to Head with US Rival,”, September 11, 2014. 27. Fred Wilson, “Platform Monopolies,”, July 13, 2014. 28. David Streitfeld, “Amazon, a Friendly Giant as Long as It’s Fed,”, July 12, 2014. 29. Venkatesh Rao, “Why Amazon Is the Best Strategic Player in Tech,”, December 14, 2011. 30.

pages: 373 words: 112,822

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

Affordable Care Act / Obamacare, Airbnb, Amazon Web Services, Andy Kessler, autonomous vehicles, Ben Horowitz, Boris Johnson, Burning Man, call centre, Chuck Templeton: OpenTable:, collaborative consumption, East Village, fixed income, Google X / Alphabet X, housing crisis, inflight wifi, Jeff Bezos,, 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

Zafar agreed and threw the driver out of the auditorium. The decision by the five PUC commissioners on the ridesharing companies was ultimately unanimous. Under Michael Peevey’s influential direction, and with letters of support from Mayor Ed Lee in San Francisco and Mayor Eric Garcetti in Los Angeles, Peevey and the four other commissioners voted to formally legalize ridesharing, classified the firms as “transportation network companies,” and said they would revisit the ruling in a year. The new rules required the companies to, among other things, report the average number of hours and miles each driver spent on the road every year—a requirement Uber would subsequently ignore, racking up millions in fines.27 It also reiterated that the companies were required to hold a million dollars in supplemental insurance to cover drivers, but only while passengers were in their car—a provision that was soon shown to be tragically inadequate.28 Nevertheless, the ruling legitimized the TNCs and gave them ammunition for coming legal fights in other states and countries.

pages: 504 words: 126,835

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

But it has been forced to take a crash course in the political and legal grammar of innovation, because it has faced mounting opposition from competitors, trade unions, and authorities. 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.

pages: 527 words: 147,690

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

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

When a group of Uber drivers assembled outside the company’s headquarters to protest their firing, the company’s general manager said that the drivers weren’t employees and that, when they were fired, it simply amounted to deactivating the drivers’ accounts. The given reason? Low ratings from passengers. This insouciance is built into Uber, which calls itself a software company, or alternatively, a transportation network company, rather than a taxi company. (Sidecar identifies as a peer-to-peer ride-sharing service.) Uber is also known for flouting local laws by setting up business in a new city without speaking to officials responsible for managing the transport sector. There’s a great deal of unacknowledged work involved in the sharing economy. Drivers have to keep their cars clean and insured, with no help from the company nominally employing them.