lump of labour

The Weightless World: Strategies for Managing the Digital Economy
by Diane Coyle
Published 29 Oct 1998

As the London School of Economics expert Richard Layard has argued,21 if you increase the supply of labour by providing a jobs guarantee, the real wage level will fall, demand for labour will rise. In a market economy, the jobs will be created, at a lower wage, many of them in the private sector. For there is no fixed number of jobs in the economy — the so-called ‘lump of labour fallacy’. If the wage rate is altered by a change in labour supply, the demand for labour will change too. The unemployed can take the new low-paid jobs if they want them, and not if they do not. But the government has offered what it could. What governments cannot do is change the world back to the way it was before.

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In so far as there is a rationale behind local hostility to immigrants, it tends to take the form of the fear that ‘they’ are stealing ‘our’ jobs. Thus getting a US Green Card requires proof that the would-be immigrant is not filling a job for which a US citizen is available. The fear is off-target, based on the ‘lump of labour’ fallacy discussed in Chapter 2.A new supply of cheap labour expands the number of jobs available, but cuts the wage paid. Immigrants do not steal jobs but they do compete down wages. A native San Franciscan might be able to afford an ‘illegal’ Mexican nanny, when once she would have gone without or opted for day nurseries because nannies’ wages were too high before the latest influx of Hispanic immigration into California.

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This has been a popular proposal in France, where the government introduced a subsidy for companies that increase their workforce by 10 per cent by reducing working hours for existing employees. But this falls into the trap of assuming there is a fixed pot of work available to be shared more or less fairly — the ‘lump of labour’ fallacy, as economists call it. It does not escape from the tyranny of thinking about people’s options in terms of jobs and not-jobs. For an alternative vision, let’s turn to science fiction. Neal Stephenson’s view about how people will make their way in the world in Snow Crash is at The Weightless World 232 least as plausible as the jobbist outlook.

A World Without Work: Technology, Automation, and How We Should Respond
by Daniel Susskind
Published 14 Jan 2020

It was, he wrote, a belief “firmly entertained by a large section of our working-classes, that for a man … to do his level best—is inconsistent … with loyalty to the cause of labour.” He called this the “theory of the Lump of Labour”: it held “that there is a certain fixed amount of work to be done, and that it is best, in the interests of the workmen, that each man shall take care not to do too much work, in order that thus the Lump of Labour may be spread out thin over the whole body of workpeople.”30 Schloss called this way of thinking “a noteworthy fallacy.” The error with it, he pointed out, is that the “lump of work” is in fact not fixed.

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,” New York Times Magazine, 1 April 2014; for politicians, see Georgia Graham, “Robots Will Take Over Middle-Class Professions, Says Minister,” Telegraph, 8 July 2014. 29.  David Schloss, Methods of Industrial Remuneration (London: Williams and Norgate, 1898). The text has been archived online at https://ia902703.us.archive.org/30/items/methodsofindustr00schl/methodsofindustr00schl.pdf. The Economist website has an entry on the “lump of labour fallacy” and David Schloss at http://www.economist.com/economics-a-to-z/l. Tom Walker, an economist, has written at length about the idea and its origins, too; see, for instance, “Why Economists Dislike a Lump of Labor,” Review of Social Economy 65, no. 3 (2007): 279–91. 30.  Schloss, Methods of Industrial Remuneration, p. 81. 31.  

Exponential: How Accelerating Technology Is Leaving Us Behind and What to Do About It
by Azeem Azhar
Published 6 Sep 2021

It goes against the folksy economic belief that there is only so much work to go around, and that upsetting the equilibrium of the labour force – by increasing female labour participation, or allowing immigration, or using robots – will reduce the available work for workers. But this belief is nonsense. It’s a form of zero-sum thinking that has largely been dispensed with by economic theory and historical evidence. Economists call it the ‘lump of labour fallacy’. In truth, the development of new technologies also creates new needs – as one technology displaces the existing ones, new sectors of the economy are brought into existence. Those new sectors have needs that must be met by suitably skilled workers. To see how this works in practice, I’d like you to meet Sid Karunaratne.

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Abu Dhabi, UAE, 250 Acemoglu, Daron, 139 Acorn Computers, 16, 21 Ada Lovelace Institute, 8 additive manufacturing, 43–4, 46, 48, 88, 166, 169, 175–9 Adidas, 176 advertising, 94, 112–13, 116, 117, 227–8 AdWords, 227 aeroponics, 171 Afghanistan, 38, 205 Africa, 177–8, 182–3 Aftenposten, 216 Age of Spiritual Machines, The (Kurzweil), 77 agglomeration, 181 Air Jordan sneakers, 102 Airbnb, 102, 188 aircraft, 49–50 Alexandria, Egypt, 180 AlexNet, 33 Algeciras, HMM 61 Alibaba, 48, 102, 108, 111, 122 Alipay, 111 Allen, Robert, 80 Alphabet, 65, 113–14, 131, 163 aluminium, 170 Amazon, 65, 67–8, 94, 104, 108, 112, 122, 135–6 Alexa, 25, 117 automation, 135–6, 137, 139, 154 collective bargaining and, 163 Covid-19 pandemic (2020–21), 135–6 drone sales, 206 Ecobee and, 117 Go stores, 136 Kiva Systems acquisition (2012), 136 management, 154 Mechanical Turk, 142–3, 144, 145 monopoly, 115, 117, 122 Prime, 136, 154 R&D, 67–8, 113 Ami Pro, 99 Amiga, 16 Anarkali, Lahore, 102 anchoring bias, 74 Android, 85, 94, 117, 120 Angola, 186 Ant Brain, 111 Ant Financial, 111–12 antitrust laws, 114, 119–20 Apache HTTP Server, 242 Appelbaum, Binyamin, 63 Apple, 47, 62, 65, 85, 94, 104, 108, 112, 122 App Store, 105, 112, 115 chip production, 113 Covid-19 pandemic (2019–21), 222–3 data collection, 228 iOS, 85 iPhone, 47, 62, 85, 94, 105 media subscription, 112 watches, 112 APT33 hacker group, 198 Aral, Sinan, 238 Aramco, 108, 198 Armenia, 206–7 Arthur, William Brian, 110, 123 artificial intelligence, 4, 8, 31–4, 54, 88, 113, 249 academic brain drain, 118 automation, 125–42 data and, 31–2, 142 data network effect, 106–7 drone technology and, 208, 214 education and, 88 employment and, 126–7 healthcare and, 88, 103 job interviews and, 153 regulation of, 187, 188 arXiv, 59 Asana, 151 Asian Development Bank, 193 Aslam, Yaseen, 148 Assembly Bill 5 (California, 2019), 148 asymmetric conflict, 206 AT&T, 76, 100 Atari, 16 attack surfaces, 192–3, 196, 209, 210 Aurora, 141 Australia, 102, 197 automation, 125–42 autonomous weapons, 208, 214 Azerbaijan, 173, 206–7 Ballmer, Steve, 85 Bangladesh, 175 banking, 122, 237 Barcelona, Catalonia, 188 Barlow, John Perry, 184 Barrons, Richard, 195, 211 Bartlett, Albert, 73 batteries, 40, 51, 53–4, 250, 251 Battle of the Overpass (1937), 162 Bayraktar TB2 drone, 206 Bee Gees, 72 Bekar, Clifford, 45 Bell Labs, 18 Bell Telephone Company, 100 Benioff, Marc, 108–9 Bentham, Jeremy, 152 Berlin Wall, fall of (1989), 4 Bermuda, 119 Berners-Lee, Timothy, 55, 100, 160, 239 Bessen, James, 46 Bezos, Jeffrey, 135–6 BGI, 41 Biden, Joseph, 225 Bing, 107 biological weapons, 207, 213 biology, 10, 39, 40–42, 44, 46 genome sequencing, 40–41, 90, 229, 234, 245–7, 250, 252 synthetic biology, 42, 46, 69, 174, 245, 250 biopolymers, 42 bits, 18 Black Death (1346–53), 12 BlackBerry, 120 Blair, Tony, 81 Bletchley Park, Buckinghamshire, 22 blitzscaling, 110 Blockbuster, 138 BMW, 177 Boeing, 51, 236 Bol.com, 103 Bollywood, 181 Boole, George, 18 Bork, Robert, 114–15, 117, 119 Bosworth, Andrew, 233 Boyer, Pascal, 75 Boyle, James, 234 BP, 92, 158 brain, 77 Braudel, Fernand, 75 Brave, 242 Brazil, 202 Bremmer, Ian, 187 Bretton Woods Conference (1944), 87 Brexit (2016–20), 6, 168 British Broadcasting Corporation (BBC), 87, 129, 191 Brookings Institution, 130 BT, 123 Bulgaria, 145 Bundy, Willard Legrand, 149 Busan, South Korea, 56 business, 82, 92–124 diminishing returns to scale, 93, 108 economic dynamism and, 117 economies of scale, 50, 92 growth, 110–13 increasing returns to scale, 108–10 intangible economy, 104–7, 118, 156, 175, 180 linear value chains, 101 market share, 93–6, 111 monopolies, 10, 71, 94, 95, 114–24 network effect, 96–101 platform model, 101–3, 219 re-localisation, 11, 166–79, 187, 252, 255 state-sized companies, 11, 67 superstar companies, 10, 94–6 supply chains, 61–2, 166–7, 169, 175, 187, 252, 255 taxation of, 96, 118–19 Butler, Nick, 179 ByteDance, 28 C40 initiative, 189 Cambridge University, 127, 188 cancer, 57–8, 127 Capitol building storming (2021), 225 car industry, 93 carbon emissions, 35, 90, 251 Carlaw, Kenneth, 45 Carnegie, Andrew, 112 Carnegie Mellon University, 131 Catholic Church, 83, 88 censorship, 216–17, 224–6, 236 Central Intelligence Agency (CIA), 194 Cerebras, 34 cervical smears, 57–8 chemical weapons, 207, 213 Chen, Brian, 228 chewing gum, 78 Chicago Pile-1 reactor, 64 Chile, 170 China automation in, 127, 137 brainwave reading in, 152 Covid-19 pandemic (2019–21), 245 drone technology in, 207 Great Firewall, 186, 201 Greater Bay Area, 182 horizontal expansion in, 111–12 manufacturing in, 176 misinformation campaigns, 203 raw materials, demand for, 178 Singles’ Day, 48 social credit systems, 230 superstar companies in, 95 US, relations with, 166 chips, 19–22, 28–9, 48–9, 52, 113, 251 Christchurch massacre (2019), 236 Christensen, Clayton, 24 CIPD, 153 cities, 11, 75, 169, 179–84, 188, 255 Clegg, Nick, 225–6, 235 climate change, 90, 169, 187, 189, 251, 252 cloud computing, 85, 112 Cloudflare, 200 cluster bombs, 213 CNN, 185, 190 coal, 40, 65, 172 Coase, Ronald, 92 Coca-Cola, 93 code is law, 220–22, 235 cold fusion, 113–14 Cold War (1947–91), 194, 212, 213 collective bargaining, 147, 149, 154, 156, 162–5 Colombia, 145 colonialism, 167 Columbus, Christopher, 4 combination, 53–7 Comical Ali, 201 commons, 234–5, 241–3, 256 companies, see business comparative advantage, 170 complex systems, 2 compounding, 22–3, 28 CompuServe, 100 computing, 4, 10, 15–36, 44, 46, 249 artificial intelligence, 4, 8, 31–4, 54, 88 cloud computing, 85, 112 internet, 47–8, 55, 65, 84 Law of Accelerating Returns, 30–31, 33, 35 machining, 43 Moore’s Law, see Moore’s Law quantum computing, 35 transistors, 18–22, 28–9, 48–9, 52 conflict, 87, 189, 190–215 attack surfaces, 192–3, 196, 209, 210 cyberattacks, 11, 114, 140, 181, 187, 190–200, 209–14, 256 de-escalation, 212–13 drone technology, 11, 192, 204–9, 214, 256 institutional change and, 87 misinformation, 11, 191, 192, 200–204, 209, 212, 217, 225 new wars, 194 non-proliferation, 213–14 re-localisation and, 189, 193, 194, 209 consent of the networked, 223 Costco, 67 Coursera, 58 Covid-19 pandemic (2019–21), 12–13, 59, 78–9, 131, 245–9 automation and, 127, 135, 136 cities and, 183 contact-tracing apps, 222–3 gig economy and, 146 lockdowns, 12, 152, 176, 183, 246 manufacturing and, 176 misinformation and, 202–4, 247–8 preprint servers and, 60 recession (2020–21), 178 remote working and, 146, 151, 153 supply chains and, 169, 246 vaccines, 12, 202, 211, 245–7 workplace cultures and, 151, 152 cranks, 54 credit ratings, 162, 229 critical thinking skills, 212 Croatia, 145 Crocker, David, 55 crowdsourcing, 143–4 Cuba, 203 Cuban missile crisis (1962), 99, 212 cultural lag, 85 cyberattacks, 11, 114, 140, 181, 187, 190–200, 209–14, 256 CyberPeace Institute, 214 Daniel, Simon, 173–4 Dar es Salaam, Tanzania, 183 Darktrace, 197 data, 8, 11, 71, 217–19, 226–31, 235, 237–42, 256 AI and, 8, 32, 33, 58, 106 compensation for, 239 commons, 242 cyberattacks and, 196 doppelgängers, 219, 226, 228, 239 interoperability and, 237–9 network effects, 106–7, 111 protection laws, 186, 226 rights, 240 Daugherty, Paul, 141 DDT (dichlorodiphenyltrichloroe thane), 253 death benefits, 151 Dediu, Horace, 24, 30 deep learning, 32–4, 54, 58, 127 deforestation, 251 dehumanisation, 71, 154, 158 deindustrialisation, 168 Deliveroo, 154, 163 Delphi, 100 dematerialised techniques, 166, 175 Denmark, 58, 160, 199–200, 257 Deutsche Bank, 130 Diamandis, Peter, 5 Dickens, Charles, 80 digital cameras, 83–4 Digital Geneva Convention, 211 Digital Markets Act (EU, 2020), 122 digital minilateralism, 188 Digital Nations group, 188 Digital Services Act (EU, 2020), 123 diminishing returns, 93, 108 disinformation, see misinformation DoorDash, 147, 148, 248 dot-com bubble (1995–2000), 8, 108, 150 Double Irish tax loophole, 119 DoubleClick, 117 drone technology, 11, 192, 204–9, 214, 256 Dubai, UAE, 43 Duke University, 234 dystopia, 208, 230, 253 Eagan, Nicole, 197 eBay, 98, 121 Ecobee, 120 economies of scale, 50, 92 Economist, The, 8, 65, 119, 183, 239 economists, 63 Edelman, 3 education artificial intelligence and, 88 media literacy, 211–12 Egypt, 145, 186 Elance, 144 electric cars, 51, 69, 75, 173–4, 177, 250 electricity, 26, 45, 46, 54, 157, 249–50 see also energy Electronic Frontier Foundation, 184 email, 6, 55 embodied institutions, 82 employment, 10, 71, 125–65 automation, 125–42 collective bargaining, 147, 149, 154, 156, 162–5 dehumanisation and, 71, 154, 158 flexicurity, 160–61, 257 gig economy, 10, 71, 142–9, 153, 162, 164, 239, 252, 255 income inequality, 155–8, 161, 168 lump of labour fallacy, 139 management, 149–54, 158–9 protections, 85–6, 147–9 reskilling, 159–60 universal basic income (UBI), 160, 189 Enclosure, 234–5, 241 energy, 11, 37–8, 39–40, 44, 46, 172–4, 250 cold fusion, 113–14 fossil fuels, 40, 159, 172, 250 gravitational potential, 53 solar power, 37–8, 53, 65, 77, 82, 90, 171, 172, 173, 249, 250, 251 storage, 40, 53, 114, 173–4, 250, 251 wind power, 39–40, 52 Energy Vault, 53–4, 173 Engels, Friedrich, 81 Engels’ pause, 80, 81 environmental movement, 73 Epic Games, 116 estate agents, 100 Estonia, 188, 190–91, 200, 211 Etzion Airbase, Sinai Peninsula, 195 European Commission, 116, 122, 123 European Space Agency, 56 European Union, 6, 82, 147, 186, 226 Excel, 99 exogeny, 2 exponential gap, 9, 10, 67–91, 70, 89, 253 cyber security and, 193 institutions and, 9, 10, 79–88, 90 mathematical understanding and, 71–5 predictions and, 75–9 price declines and, 68–9 superstar companies and, 10, 94–124 exponential growth bias, 73 Exponential View, 8–9 externalities, 97 extremism, 232–4 ExxonMobil, 65, 92 Facebook, 27, 28, 65, 94, 104, 108, 122, 216–17, 218, 219, 221–2, 223 advertising business, 94, 228 censorship on, 216–17, 224–6, 236 collective bargaining and, 164 data collection on, 228, 239–40 extremism and, 233–4 Instagram acquisition (2012), 117, 120 integrity teams, 234 interoperability, 237–8 Kenosha unrest shooting (2020), 224 misinformation on, 201, 225 network effect and, 98, 223 Oculus acquisition (2014), 117 pay at, 156–7 Phan photo controversy (2016), 216–17, 224, 225 platform model, 101 polarisation and, 233 relationship status on, 221–2 Rohingya ethnic cleansing (2018), 224, 225 US presidential election (2016), 217 WhatsApp acquisition (2014), 117 facial recognition, 152, 208 Factory Act (UK, 1833), 81 Fairchild Semiconductor, 19, 21 fake news, 201–4 family dinners, 86 farming, 170–72, 251 Farrar, James, 148 fax machines, 97 Federal Aviation Administration (US), 236 feedback loops, 3, 13 fertilizers, 35, 90 5G, 203 Financial Conduct Authority, 122 Financial Times, 183 Finland, 160, 211–12 Fitbit, 158 Fiverr, 144 flashing of headlights, 83 flexicurity, 160, 257 flints, 42 flywheels, 54 Ford, 54, 92, 162 Ford, Gerald, 114 Ford, Henry, 54, 162 Ford, Martin, 125 Fortnite, 116 fossil fuels, 40, 159, 172 France, 100, 138, 139, 147, 163 free-market economics, 63–4 freelance work, 10, 71, 142–9 Frey, Carl, 129, 134, 141 Friedman, Milton, 63–4, 241 Friedman, Thomas, 167 FriendFeed, 238 Friendster, 26 Fudan University, 245 fund management, 132 Galilei, Galileo, 83 gaming, 86 Gates, Bill, 17, 25, 84 gender, 6 General Agreement on Tariffs and Trade, 87 General Data Protection Regulation (GDPR), 226 General Electric, 52 General Motors, 92, 125, 130 general purpose technologies, 10, 45–8 generative adversarial networks (GANs), 58 Geneva Conventions, 193, 199, 209 Genghis Khan, 44 GEnie, 100 genome sequencing, 40–41, 90, 229, 234, 245–7, 250, 252 Germany, 75, 134, 147 Giddens, Anthony, 82 gig economy, 10, 71, 142–9, 153, 162, 164, 239, 252, 255 Gilbreth, Lillian, 150 Ginsparg, Paul, 59 GitHub, 58, 60 GlaxoSmithKline, 229–30 global financial crisis (2007–9), 168 Global Hawk drones, 206 global positioning systems (GPS), 197 globalisation, 11, 62, 64, 156, 166, 167–71, 177, 179, 187, 193 internet and, 185 conflict and, 189, 193, 194 Glocer, Thomas, 56 Go (game), 132 GOAT, 102 Gojek, 103 Golden Triangle, 170 Goldman Sachs, 151 Goodfellow, Ian, 58 Google, 5, 35, 36, 94, 98, 104, 108, 115, 122 advertising business, 94, 112–13, 116, 117, 227 Android, 85, 94, 117, 120 chip production, 113 Covid-19 pandemic (2019–21), 222–3 data network effect, 106–7 death benefits, 151 Double Irish tax loophole, 119 Maps, 113 quantum computing, 35 R&D, 114, 118 vertical integration, 112–13, 116 X, 114 YouTube acquisition (2006), 112, 117 Gopher, 59, 100 GPT-3, 33 Graeber, David, 133–4 Grand Bazaar, Istanbul, 102 Graphcore, 34, 35 graphics chips, 34 Grateful Dead, The, 184 gravitational potential energy, 53 gravity bombs, 195 Greater Bay Area, China, 182 Greenberg, Andy, 199 Gross, Bill, 53 Grove, Andrew, 17 GRU (Glavnoje Razvedyvatel’noje Upravlenije), 199 Guangzhou, Guangdong, 182 Guardian, 8, 125, 154, 226, 227 Guiyang, Guizhou, 166 H1N1 virus, 75 Habermas, Jürgen, 218 Hard Times (Dickens), 80 Hardin, Garrett, 241 Harop drones, 207–8 Harpy drones, 207–8 Harvard University, 150, 218, 220, 221, 253 healthcare artificial intelligence and, 57–8, 88, 103 data and, 230, 239, 250–51 wearable devices and, 158, 251 Helsinki, Finland, 160 Herlev Hospital, Denmark, 58 Hinton, Geoffrey, 32, 126–7 HIPA Act (US, 1996), 230 Hitachi, 152 Hobbes, Thomas, 210 Hoffman, Josh, 174 Hoffman, Reid, 110, 111 Holmes, Edward, 245 homophily, 231–4 Hong Kong, 182 horizontal expansion, 111–12, 218 Houston Islam protests (2016), 203 Houthis, 206 Howe, Jeff, 143 Hsinchu, Taiwan, 181 Hughes, Chris, 217 Hull, Charles, 43 Human + Machine (Daugherty), 141 human brain, 77 human genome, 40–41, 90, 229, 234, 250 human resources, 150 Hussein, Saddam, 195 Hyaline, 174 hydroponics, 171 hyperinflation, 75 IBM, 17, 21, 47, 98 IDC, 219 Ideal-X, 61 Ikea, 144 Illumina, 41 Ilves, Toomas Hendrik, 190 ImageNet, 32 immigration, 139, 168, 183–4 Impossible Foods, 69 Improv, 99 income inequality, 155–8, 161, 168 India, 103, 145, 181, 186, 224, 253, 254 Indonesia, 103 Industrial Revolution (1760–1840), 79–81, 157, 235 informational networks, 59–60 ING, 178 innovation, 14, 117 Innovator’s Dilemma, The (Christensen), 24 Instagram, 84, 117, 120, 121, 237 institutions, 9, 10, 79–88, 90–91 path dependence, 86–7 punctuated equilibrium, 87–8 intangible economy, 104–7, 118, 156, 175, 180 integrated circuits, 19 Intel, 16–17, 19, 163 intellectual property law, 82 Intermediate-Range Nuclear Forces Treaty (1987), 237 International Alliance of App-Based Transport Workers, 164 International Court of Justice, 224 International Criminal Court, 208 International Energy Agency, 77, 82 International Labour Organization, 131 International Monetary Fund (IMF), 87, 167, 187 international organisations, 82 International Organization for Standardization, 55, 61 International Rescue Committee, 184 International Telecommunication Union, 55 internet, 7, 47–8, 55, 65, 72, 75, 84–5, 88, 115, 184–6 code is law, 220–22, 235 data and, 11, 32, 71 informational networks, 59–60 localisation, 185–6 lockdowns and, 12 network effect, 100–101 online shopping, 48, 61, 62, 75, 94, 102, 135 platform model and, 102 public sphere and, 223 standardisation, 55 Wi-Fi, 151 interoperability, 55, 120–22, 237–9, 241, 243, 256–7 iPhone, 47, 62, 85, 94, 115, 175 Iran, 186, 196, 198, 203, 206 Iraq, 195–6, 201, 209 Ireland, 57–8, 119 Islamic State, 194, 233 Israel, 37, 188, 195–6, 198, 206, 207–8 Istanbul, Turkey, 102 Jacobs, Jane, 182 Japan, 37, 152, 171, 174 Jasanoff, Sheila, 253 JD.com, 137 Jena, Rajesh, 127 Jio, 103 job interviews, 153, 156 John Paul II, Pope, 83 Johnson, Boris, 79 Jumia, 103 just in time supply chains, 61–2 Kahneman, Daniel, 74 KakaoTalk, 27 Kaldor, Mary, 194 Kapor, Mitchell, 99 Karunaratne, Sid, 140–41, 151 Kenosha unrest shooting (2020), 224 Keynes, John Maynard, 126, 158 Khan, Lina, 119 Khartoum, Sudan, 183 Kim Jong-un, 198 King’s College London, 179 Kiva Systems, 136 Kobo360, 145 Kodak, 83–4, 88 Kranzberg, Melvin, 254 Krizhevsky, Alex, 32–3, 34 Kubursi, Atif, 178 Kurdistan Workers’ Party, 206 Kurzweil, Ray, 29–31, 33, 35, 77 Lagos, Nigeria, 182 Lahore, Pakistan, 102 landmines, 213 Law of Accelerating Returns, 30–31, 33, 35 Laws of Motion, 20 learning by doing, 48, 53 Leggatt, George, 148 Lemonade, 56 Lessig, Larry, 220–21 Leviathan (Hobbes), 210 Li Fei-Fei, 32 life expectancy, 25, 26 light bulbs, 44, 157 Lime, 27 Limits to Growth, The (Meadows et al.), 73 linear value chains, 101 LinkedIn, 26, 110, 121, 237, 238 Linkos Group, 197 Linux OS, 242 Lipsey, Richard, 45 lithium-ion batteries, 40, 51 lithium, 170 localism, 11, 166–90, 252, 255 log files, 227 logarithmic scales, 20 logic gates, 18 logistic curve, 25, 30, 51, 52, 69–70 London, England, 180, 181, 183 London Underground, 133–4 looms, 157 Lordstown Strike (1972), 125 Lotus Development Corporation, 99 Luddites, 125, 253 Lufa Farms, 171–2 Luminate, 240 lump of labour fallacy, 139 Lusaka, Zambia, 15 Lyft, 146, 148 machine learning, 31–4, 54, 58, 88, 127, 129, 143 MacKinnon, Rebecca, 223 Maersk, 197, 199, 211 malaria, 253 Malaysia Airlines Flight 17 shootdown (2014), 199 Malta, 114 Malthus, Thomas, 72–3 malware, 197 Man with the Golden Gun, The (1974 film), 37 manufacturing, 10, 39, 42–4, 46, 166–7, 175–9 additive, 43–4, 46, 48, 88, 166, 169, 175–9 automation and, 130 re-localisation, 175–9 subtractive, 42–3 market saturation, 25–8, 51, 52 market share, 93–6, 111 Marshall, Alfred, 97 Massachusetts Institute of Technology, 18, 147, 202, 238 Mastercard, 98 May, Theresa, 183 Mayors for a Guaranteed Income, 189 McCarthy, John, 31 McKinsey, 76, 94 McMaster University, 178 measles, 246 Mechanical Turk, 142–3, 144, 145 media literacy, 211–12 meningitis, 246 Mexico, 202 microorganisms, 42, 46, 69 Microsoft, 16–17, 65, 84–5, 88, 98–9, 100, 105, 108, 122, 221 Bing, 107 cloud computing, 85 data collection, 228 Excel, 99 internet and, 84–5, 100 network effect and, 99 Office software, 98–9, 110, 152 Windows, 85, 98–9 Workplace Productivity scores, 152 Mill, John Stuart, 193 miniaturisation, 34–5 minimum wage, 147, 161 misinformation, 11, 191, 192, 200–204, 209, 212, 217, 225, 247–8 mobile phones, 76, 121 see also smartphones; telecom companies Moderna, 245, 247 Moixa, 174 Mondelez, 197, 211 Mongol Empire (1206–1368), 44 monopolies, 10, 71, 94, 95, 114–24, 218, 255 Monopoly (board game), 82 Montreal, Quebec, 171 mood detection systems, 152 Moore, Gordon, 19, 48 Moore’s Law, 19–22, 26, 28–9, 31, 34, 63, 64, 74 artificial intelligence and, 32, 33–4 Kodak and, 83 price and, 41–2, 51, 68–9 as social fact, 29, 49 superstar companies and, 95 time, relationship with, 48–9 Moravec, Hans, 131 Moravec’s paradox, 131–2 Motorola, 76 Mount Mercy College, Cork, 57 Mozilla Firefox, 242 Mumbai, India, 181 mumps, 246 muskets, 54–5 MySpace, 26–7 Nadella, Satya, 85 Nagorno-Karabakh War (2020), 206–7 napalm, 216 NASA (National Aeronautics and Space Administration), 56 Natanz nuclear site, Iran, 196 National Health Service (NHS), 87 nationalism, 168, 186 NATO (North Atlantic Treaty Organization), 191, 213 Netflix, 104, 107, 109, 136, 137, 138, 139, 151, 248 Netherlands, 103 Netscape Communicator, 6 networks, 58–62 network effects, 96–101, 106, 110, 121, 223 neural networks, 32–4 neutral, technology as, 5, 220–21, 254 new wars, 194 New York City, New York, 180, 183 New York Times, 3, 125, 190, 228 New Zealand, 188, 236 Newton, Isaac, 20 Nigeria, 103, 145, 182, 254 Niinistö, Sauli, 212 Nike, 102 nitrogen fertilizers, 35 Nixon, Richard, 25, 114 Nobel Prize, 64, 74, 241 Nokia, 120 non-state actors, 194, 213 North Korea, 198 North Macedonia, 200–201 Norway, 173, 216 NotPetya malware, 197, 199–200, 211, 213 Novell, 98 Noyce, Robert, 19 NSO Group, 214 nuclear weapons, 193, 195–6, 212, 237 Nuremberg Trials (1945–6), 208 O’Reilly, Tim, 107 O’Sullivan, Laura, 57–8, 60 Obama, Barack, 205, 214, 225 Ocado, 137 Ocasio-Cortez, Alexandria, 239 Oculus, 117 oDesk, 144 Ofcom, 8 Ofoto, 84 Ogburn, William, 85 oil industry, 172, 250 Houthi drone attacks (2019), 206 OAPEC crisis (1973–4), 37, 258 Shamoon attack (2012), 198 Standard Oil breakup (1911), 93–4 Olduvai, Tanzania, 42 online shopping, 48, 61, 62, 75, 94, 102, 135 open-source software, 242 Openreach, 123 Operation Opera (1981), 195–6, 209 opium, 38 Orange, 121 Organisation for Economic Co-operation and Development (OECD), 119, 167 Osborne Computer Corporation, 16 Osborne, Michael, 129 Osirak nuclear reactor, Iraq, 195–6, 209 Ostrom, Elinor, 241 Oxford University, 129, 134, 203, 226 pace of change, 3 pagers, 87 Pakistan, 145, 205 palladium, 170 PalmPilot, 173 panopticon, 152 Paris, France, 181, 183 path dependence, 86 PayPal, 98, 110 PC clones, 17 PeerIndex, 8, 201, 237 Pegasus, 214 PeoplePerHour, 144 PepsiCo, 93 Perez, Carlota, 46–7 pernicious polarization, 232 perpetual motion, 95, 106, 107, 182 Petersen, Michael Bang, 75 Phan Thi Kim Phuc, 216–17, 224, 225 pharmaceutical industry, 6, 93, 250 phase transitions, 4 Philippines, 186, 203 Phillips Exeter Academy, 150 phishing scams, 211 Phoenix, Arizona, 134 photolithography, 19 Pigou, Arthur Cecil, 97 Piketty, Thomas, 160 Ping An Good Doctor, 103, 250 Pix Moving, 166, 169, 175 PKK (Partîya Karkerên Kurdistanê), 206 Planet Labs, 69 platforms, 101–3, 219 PlayStation, 86 plough, 157 Polanyi, Michael, 133 polarisation, 231–4 polio, 246 population, 72–3 Portify, 162 Postel, Jon, 55 Postings, Robert, 233 Predator drones, 205, 206 preprints, 59–60 price gouging, 93 price of technology, 22, 68–9 computing, 68–9, 191, 249 cyber-weapons, 191–2 drones, 192 genome sequencing, 41–2, 252 renewable energy, 39–40, 250 printing press, 45 public sphere, 218, 221, 223 Pulitzer Prize, 216 punctuated equilibrium, 87–8 al-Qaeda, 205, 210–11 Qatar, 198 quantum computing, 35 quantum physics, 29 quarantines, 12, 152, 176, 183, 246 R&D (research and development), 67–8, 113, 118 racial bias, 231 racism, 225, 231, 234 radicalisation pathways, 233 radiologists, 126 Raford, Noah, 43 Raz, Ze’ev, 195, 209 RB, 197 re-localisation, 11, 166–90, 253, 255 conflict and, 189, 193, 194, 209 Reagan, Ronald, 64, 163 religion, 6, 82, 83 resilience, 257 reskilling, 159–60 responsibility gap, 209 Restrepo, Pascual, 139 Reuters, 8, 56, 132 revolutions, 87 Ricardo, David, 169–70, 177 rights, 240–41 Rise of the Robots, The (Ford), 125 Rittenhouse, Kyle, 224 Roche, 67 Rockefeller, John, 93 Rohingyas, 224 Rome, ancient, 180 Rose, Carol, 243 Rotterdam, Netherlands, 56 Rule of Law, 82 running shoes, 102, 175–6 Russell, Stuart, 31, 118 Russian Federation, 122 disinformation campaigns, 203 Estonia cyberattacks (2007), 190–91, 200 Finland, relations with, 212 Nagorno-Karabakh War (2020), 206 nuclear weapons, 237 Ukraine cyberattacks (2017), 197, 199–200 US election interference (2016), 217 Yandex, 122 S-curve, 25, 30, 51, 52, 69–70 al-Sahhaf, Muhammad Saeed, 201 Salesforce, 108–9 Saliba, Samer, 184 salt, 114 Samsung, 93, 228 San Francisco, California, 181 Sandel, Michael, 218 Sanders, Bernard, 163 Sandworm, 197, 199–200, 211 Santander, 95 Sasson, Steve, 83 satellites, 56–7, 69 Saturday Night Fever (1977 soundtrack), 72 Saudi Arabia, 108, 178, 198, 203, 206 Schmidt, Eric, 5 Schwarz Gruppe, 67 Second Machine Age, The (Brynjolfsson and McAfee), 129 self-driving vehicles, 78, 134–5, 141 semiconductors, 18–22, 28–9, 48–9, 52, 113, 251 September 11 attacks (2001), 205, 210–11 Shamoon virus, 198 Shanghai, China, 56 Shannon, Claude, 18 Sharp, 16 Shenzhen, Guangdong, 182 shipping containers, 61–2, 63 shopping, 48, 61, 62, 75, 94, 102, 135 Siemens, 196 silicon chips, see chips Silicon Valley, 5, 7, 15, 24, 65, 110, 129, 223 Sinai Peninsula, 195 Sinclair ZX81, 15, 17, 21, 36 Singapore, 56 Singles’ Day, 48 Singularity University, 5 SixDegrees, 26 Skydio R1 drone, 208 smartphones, 22, 26, 46, 47–8, 65, 86, 88, 105, 111, 222 Smith, Adam, 169–70 sneakers, 102, 175–6 Snow, Charles Percy, 7 social credit systems, 230 social media, 26–8 censorship on, 216–17, 224–6, 236 collective bargaining and, 164 data collection on, 228 interoperability, 121, 237–8 market saturation, 25–8 misinformation on, 192, 201–4, 217, 247–8 network effect, 98, 223 polarisation and, 231–4 software as a service, 109 solar power, 37–8, 53, 65, 77, 82, 90, 171, 172, 173, 249, 250, 251 SolarWinds, 200 Solberg, Erna, 216 South Africa, 170 South Korea, 188, 198, 202 Southey, Robert, 80 sovereignty, 185, 199, 214 Soviet Union (1922–91), 185, 190, 194, 212 Spain, 170, 188 Spanish flu pandemic (1918–20), 75 Speedfactory, Ansbach, 176 Spire, 69 Spotify, 69 Sputnik 1 orbit (1957), 64, 83 stagflation, 63 Standard and Poor, 104 Standard Oil, 93–4 standardisation, 54–7, 61, 62 Stanford University, 32, 58 Star Wars franchise, 99 state-sized companies, 11, 67 see also superstar companies states, 82 stirrups, 44 Stockholm International Peace Research Institute, 208 Stockton, California, 160 strategic snowflakes, 211 stress tests, 237 Stuxnet, 196, 214 Sudan, 183 superstar companies, 10, 11, 67, 94–124, 218–26, 252, 255 blitzscaling, 110 collective bargaining and, 163 horizontal expansion, 111–12, 218 increasing returns to scale, 108–10 innovation and, 117–18 intangible economy, 104–7, 118, 156 interoperability and, 120–22, 237–9 monopolies, 114–24, 218 network effect, 96–101, 121 platform model, 101–3, 219 taxation of, 118–19 vertical expansion, 112–13 workplace cultures, 151 supply chains, 61–2, 166–7, 169, 175, 187, 252 surveillance, 152–3, 158 Surviving AI (Chace), 129 Sutskever, Ilya, 32 synthetic biology, 42, 46, 69, 174, 245, 250 Syria, 186 Taiwan, 181, 212 Talkspace, 144 Tallinn, Estonia, 190 Tang, Audrey, 212 Tanzania, 42, 183 TaskRabbit, 144 Tasmania, Australia, 197 taxation, 10, 63, 96, 118–19 gig economy and, 146 superstar companies and, 118–19 Taylor, Frederick Winslow, 150, 152, 153, 154 Tel Aviv, Israel, 181 telecom companies, 122–3 Tencent, 65, 104, 108, 122 territorial sovereignty, 185, 199, 214 Tesco, 67, 93 Tesla, 69, 78, 113 Thailand, 176, 203 Thatcher, Margaret, 64, 163 Thelen, Kathleen, 87 Thiel, Peter, 110–11 3D printing, see additive manufacturing TikTok, 28, 69, 159–60, 219 Tisné, Martin, 240 Tomahawk missiles, 207 Toyota, 95 trade networks, 61–2, 166–7, 169, 175 trade unions, see collective bargaining Trading Places (1983 film), 132 Tragedy of the Commons, The (Hardin), 241 transistors, 18–22, 28–9, 48–9, 52, 113, 251 transparency, 236 Treaty of Westphalia (1648), 199 TRS-80, 16 Trump, Donald, 79, 119, 166, 201, 225, 237 Tufekci, Zeynep, 233 Turing, Alan, 18, 22 Turkey, 102, 176, 186, 198, 202, 206, 231 Tversky, Amos, 74 23andMe, 229–30 Twilio, 151 Twitch, 225 Twitter, 65, 201, 202, 219, 223, 225, 237 two cultures, 7, 8 Uber, 69, 94, 102, 103, 106, 142, 144, 145 Assembly Bill 5 (California, 2019), 148 engineering jobs, 156 London ban (2019), 183, 188 London protest (2016), 153 pay at, 147, 156 satisfaction levels at, 146 Uber BV v Aslam (2021), 148 UiPath, 130 Ukraine, 197, 199 Unilever, 153 Union of Concerned Scientists, 56 unions, see collective bargaining United Arab Emirates, 43, 198, 250 United Autoworkers Union, 162 United Kingdom BBC, 87 Biobank, 242 Brexit (2016–20), 6, 168 collective bargaining in, 163 Covid-19 epidemic (2020–21), 79, 203 DDT in, 253 digital minilateralism, 188 drone technology in, 207 flashing of headlights in, 83 Golden Triangle, 170 Google and, 116 Industrial Revolution (1760–1840), 79–81 Luddite rebellion (1811–16), 125, 253 misinformation in, 203, 204 National Cyber Force, 200 NHS, 87 self-employment in, 148 telecom companies in, 123 Thatcher government (1979–90), 64, 163 United Nations, 87, 88, 188 United States antitrust law in, 114 automation in, 127 Battle of the Overpass (1937), 162 Capitol building storming (2021), 225 China, relations with, 166 Cold War (1947–91), 194, 212, 213 collective bargaining in, 163 Covid-19 epidemic (2020–21), 79, 202–4 Cyber Command, 200, 210 DDT in, 253 drone technology in, 205, 214 economists in, 63 HIPA Act (1996), 230 Kenosha unrest shooting (2020), 224 Lordstown Strike (1972), 125 manufacturing in, 130 misinformation in, 202–4 mobile phones in, 76 nuclear weapons, 237 Obama administration (2009–17), 205, 214 polarisation in, 232 presidential election (2016), 199, 201, 217 presidential election (2020), 202–3 Reagan administration (1981–9), 64, 163 self-employment in, 148 September 11 attacks (2001), 205, 210–11 shipping containers in, 61 shopping in, 48 solar energy research, 37 Standard Oil breakup (1911), 93–4 taxation in, 63, 119 Trump administration (2017–21), 79, 119, 166, 168, 201, 225, 237 Vietnam War (1955–75), 216 War on Terror (2001–), 205 universal basic income (UBI), 160, 189 universal service obligation, 122 University of Cambridge, 127, 188 University of Chicago, 63 University of Colorado, 73 University of Delaware, 55 University of Oxford, 129, 134, 203, 226 University of Southern California, 55 unwritten rules, 82 Uppsala Conflict Data Program, 194 UpWork, 145–6 USB (Universal Serial Bus), 51 Ut, Nick, 216 utility providers, 122–3 vaccines, 12, 202, 211, 245–7 Vail, Theodore, 100 value-free, technology as, 5, 220–21, 254 Veles, North Macedonia, 200–201 Véliz, Carissa, 226 Venezuela, 75 venture capitalists, 117 vertical expansion, 112–13, 116 vertical farms, 171–2, 251 video games, 86 Vietnam, 61, 175, 216 Virological, 245 Visa, 98 VisiCalc, 99 Vodafone, 121 Vogels, Werner, 68 Wag!

…

.), 73 linear value chains, 101 LinkedIn, 26, 110, 121, 237, 238 Linkos Group, 197 Linux OS, 242 Lipsey, Richard, 45 lithium-ion batteries, 40, 51 lithium, 170 localism, 11, 166–90, 252, 255 log files, 227 logarithmic scales, 20 logic gates, 18 logistic curve, 25, 30, 51, 52, 69–70 London, England, 180, 181, 183 London Underground, 133–4 looms, 157 Lordstown Strike (1972), 125 Lotus Development Corporation, 99 Luddites, 125, 253 Lufa Farms, 171–2 Luminate, 240 lump of labour fallacy, 139 Lusaka, Zambia, 15 Lyft, 146, 148 machine learning, 31–4, 54, 58, 88, 127, 129, 143 MacKinnon, Rebecca, 223 Maersk, 197, 199, 211 malaria, 253 Malaysia Airlines Flight 17 shootdown (2014), 199 Malta, 114 Malthus, Thomas, 72–3 malware, 197 Man with the Golden Gun, The (1974 film), 37 manufacturing, 10, 39, 42–4, 46, 166–7, 175–9 additive, 43–4, 46, 48, 88, 166, 169, 175–9 automation and, 130 re-localisation, 175–9 subtractive, 42–3 market saturation, 25–8, 51, 52 market share, 93–6, 111 Marshall, Alfred, 97 Massachusetts Institute of Technology, 18, 147, 202, 238 Mastercard, 98 May, Theresa, 183 Mayors for a Guaranteed Income, 189 McCarthy, John, 31 McKinsey, 76, 94 McMaster University, 178 measles, 246 Mechanical Turk, 142–3, 144, 145 media literacy, 211–12 meningitis, 246 Mexico, 202 microorganisms, 42, 46, 69 Microsoft, 16–17, 65, 84–5, 88, 98–9, 100, 105, 108, 122, 221 Bing, 107 cloud computing, 85 data collection, 228 Excel, 99 internet and, 84–5, 100 network effect and, 99 Office software, 98–9, 110, 152 Windows, 85, 98–9 Workplace Productivity scores, 152 Mill, John Stuart, 193 miniaturisation, 34–5 minimum wage, 147, 161 misinformation, 11, 191, 192, 200–204, 209, 212, 217, 225, 247–8 mobile phones, 76, 121 see also smartphones; telecom companies Moderna, 245, 247 Moixa, 174 Mondelez, 197, 211 Mongol Empire (1206–1368), 44 monopolies, 10, 71, 94, 95, 114–24, 218, 255 Monopoly (board game), 82 Montreal, Quebec, 171 mood detection systems, 152 Moore, Gordon, 19, 48 Moore’s Law, 19–22, 26, 28–9, 31, 34, 63, 64, 74 artificial intelligence and, 32, 33–4 Kodak and, 83 price and, 41–2, 51, 68–9 as social fact, 29, 49 superstar companies and, 95 time, relationship with, 48–9 Moravec, Hans, 131 Moravec’s paradox, 131–2 Motorola, 76 Mount Mercy College, Cork, 57 Mozilla Firefox, 242 Mumbai, India, 181 mumps, 246 muskets, 54–5 MySpace, 26–7 Nadella, Satya, 85 Nagorno-Karabakh War (2020), 206–7 napalm, 216 NASA (National Aeronautics and Space Administration), 56 Natanz nuclear site, Iran, 196 National Health Service (NHS), 87 nationalism, 168, 186 NATO (North Atlantic Treaty Organization), 191, 213 Netflix, 104, 107, 109, 136, 137, 138, 139, 151, 248 Netherlands, 103 Netscape Communicator, 6 networks, 58–62 network effects, 96–101, 106, 110, 121, 223 neural networks, 32–4 neutral, technology as, 5, 220–21, 254 new wars, 194 New York City, New York, 180, 183 New York Times, 3, 125, 190, 228 New Zealand, 188, 236 Newton, Isaac, 20 Nigeria, 103, 145, 182, 254 Niinistö, Sauli, 212 Nike, 102 nitrogen fertilizers, 35 Nixon, Richard, 25, 114 Nobel Prize, 64, 74, 241 Nokia, 120 non-state actors, 194, 213 North Korea, 198 North Macedonia, 200–201 Norway, 173, 216 NotPetya malware, 197, 199–200, 211, 213 Novell, 98 Noyce, Robert, 19 NSO Group, 214 nuclear weapons, 193, 195–6, 212, 237 Nuremberg Trials (1945–6), 208 O’Reilly, Tim, 107 O’Sullivan, Laura, 57–8, 60 Obama, Barack, 205, 214, 225 Ocado, 137 Ocasio-Cortez, Alexandria, 239 Oculus, 117 oDesk, 144 Ofcom, 8 Ofoto, 84 Ogburn, William, 85 oil industry, 172, 250 Houthi drone attacks (2019), 206 OAPEC crisis (1973–4), 37, 258 Shamoon attack (2012), 198 Standard Oil breakup (1911), 93–4 Olduvai, Tanzania, 42 online shopping, 48, 61, 62, 75, 94, 102, 135 open-source software, 242 Openreach, 123 Operation Opera (1981), 195–6, 209 opium, 38 Orange, 121 Organisation for Economic Co-operation and Development (OECD), 119, 167 Osborne Computer Corporation, 16 Osborne, Michael, 129 Osirak nuclear reactor, Iraq, 195–6, 209 Ostrom, Elinor, 241 Oxford University, 129, 134, 203, 226 pace of change, 3 pagers, 87 Pakistan, 145, 205 palladium, 170 PalmPilot, 173 panopticon, 152 Paris, France, 181, 183 path dependence, 86 PayPal, 98, 110 PC clones, 17 PeerIndex, 8, 201, 237 Pegasus, 214 PeoplePerHour, 144 PepsiCo, 93 Perez, Carlota, 46–7 pernicious polarization, 232 perpetual motion, 95, 106, 107, 182 Petersen, Michael Bang, 75 Phan Thi Kim Phuc, 216–17, 224, 225 pharmaceutical industry, 6, 93, 250 phase transitions, 4 Philippines, 186, 203 Phillips Exeter Academy, 150 phishing scams, 211 Phoenix, Arizona, 134 photolithography, 19 Pigou, Arthur Cecil, 97 Piketty, Thomas, 160 Ping An Good Doctor, 103, 250 Pix Moving, 166, 169, 175 PKK (Partîya Karkerên Kurdistanê), 206 Planet Labs, 69 platforms, 101–3, 219 PlayStation, 86 plough, 157 Polanyi, Michael, 133 polarisation, 231–4 polio, 246 population, 72–3 Portify, 162 Postel, Jon, 55 Postings, Robert, 233 Predator drones, 205, 206 preprints, 59–60 price gouging, 93 price of technology, 22, 68–9 computing, 68–9, 191, 249 cyber-weapons, 191–2 drones, 192 genome sequencing, 41–2, 252 renewable energy, 39–40, 250 printing press, 45 public sphere, 218, 221, 223 Pulitzer Prize, 216 punctuated equilibrium, 87–8 al-Qaeda, 205, 210–11 Qatar, 198 quantum computing, 35 quantum physics, 29 quarantines, 12, 152, 176, 183, 246 R&D (research and development), 67–8, 113, 118 racial bias, 231 racism, 225, 231, 234 radicalisation pathways, 233 radiologists, 126 Raford, Noah, 43 Raz, Ze’ev, 195, 209 RB, 197 re-localisation, 11, 166–90, 253, 255 conflict and, 189, 193, 194, 209 Reagan, Ronald, 64, 163 religion, 6, 82, 83 resilience, 257 reskilling, 159–60 responsibility gap, 209 Restrepo, Pascual, 139 Reuters, 8, 56, 132 revolutions, 87 Ricardo, David, 169–70, 177 rights, 240–41 Rise of the Robots, The (Ford), 125 Rittenhouse, Kyle, 224 Roche, 67 Rockefeller, John, 93 Rohingyas, 224 Rome, ancient, 180 Rose, Carol, 243 Rotterdam, Netherlands, 56 Rule of Law, 82 running shoes, 102, 175–6 Russell, Stuart, 31, 118 Russian Federation, 122 disinformation campaigns, 203 Estonia cyberattacks (2007), 190–91, 200 Finland, relations with, 212 Nagorno-Karabakh War (2020), 206 nuclear weapons, 237 Ukraine cyberattacks (2017), 197, 199–200 US election interference (2016), 217 Yandex, 122 S-curve, 25, 30, 51, 52, 69–70 al-Sahhaf, Muhammad Saeed, 201 Salesforce, 108–9 Saliba, Samer, 184 salt, 114 Samsung, 93, 228 San Francisco, California, 181 Sandel, Michael, 218 Sanders, Bernard, 163 Sandworm, 197, 199–200, 211 Santander, 95 Sasson, Steve, 83 satellites, 56–7, 69 Saturday Night Fever (1977 soundtrack), 72 Saudi Arabia, 108, 178, 198, 203, 206 Schmidt, Eric, 5 Schwarz Gruppe, 67 Second Machine Age, The (Brynjolfsson and McAfee), 129 self-driving vehicles, 78, 134–5, 141 semiconductors, 18–22, 28–9, 48–9, 52, 113, 251 September 11 attacks (2001), 205, 210–11 Shamoon virus, 198 Shanghai, China, 56 Shannon, Claude, 18 Sharp, 16 Shenzhen, Guangdong, 182 shipping containers, 61–2, 63 shopping, 48, 61, 62, 75, 94, 102, 135 Siemens, 196 silicon chips, see chips Silicon Valley, 5, 7, 15, 24, 65, 110, 129, 223 Sinai Peninsula, 195 Sinclair ZX81, 15, 17, 21, 36 Singapore, 56 Singles’ Day, 48 Singularity University, 5 SixDegrees, 26 Skydio R1 drone, 208 smartphones, 22, 26, 46, 47–8, 65, 86, 88, 105, 111, 222 Smith, Adam, 169–70 sneakers, 102, 175–6 Snow, Charles Percy, 7 social credit systems, 230 social media, 26–8 censorship on, 216–17, 224–6, 236 collective bargaining and, 164 data collection on, 228 interoperability, 121, 237–8 market saturation, 25–8 misinformation on, 192, 201–4, 217, 247–8 network effect, 98, 223 polarisation and, 231–4 software as a service, 109 solar power, 37–8, 53, 65, 77, 82, 90, 171, 172, 173, 249, 250, 251 SolarWinds, 200 Solberg, Erna, 216 South Africa, 170 South Korea, 188, 198, 202 Southey, Robert, 80 sovereignty, 185, 199, 214 Soviet Union (1922–91), 185, 190, 194, 212 Spain, 170, 188 Spanish flu pandemic (1918–20), 75 Speedfactory, Ansbach, 176 Spire, 69 Spotify, 69 Sputnik 1 orbit (1957), 64, 83 stagflation, 63 Standard and Poor, 104 Standard Oil, 93–4 standardisation, 54–7, 61, 62 Stanford University, 32, 58 Star Wars franchise, 99 state-sized companies, 11, 67 see also superstar companies states, 82 stirrups, 44 Stockholm International Peace Research Institute, 208 Stockton, California, 160 strategic snowflakes, 211 stress tests, 237 Stuxnet, 196, 214 Sudan, 183 superstar companies, 10, 11, 67, 94–124, 218–26, 252, 255 blitzscaling, 110 collective bargaining and, 163 horizontal expansion, 111–12, 218 increasing returns to scale, 108–10 innovation and, 117–18 intangible economy, 104–7, 118, 156 interoperability and, 120–22, 237–9 monopolies, 114–24, 218 network effect, 96–101, 121 platform model, 101–3, 219 taxation of, 118–19 vertical expansion, 112–13 workplace cultures, 151 supply chains, 61–2, 166–7, 169, 175, 187, 252 surveillance, 152–3, 158 Surviving AI (Chace), 129 Sutskever, Ilya, 32 synthetic biology, 42, 46, 69, 174, 245, 250 Syria, 186 Taiwan, 181, 212 Talkspace, 144 Tallinn, Estonia, 190 Tang, Audrey, 212 Tanzania, 42, 183 TaskRabbit, 144 Tasmania, Australia, 197 taxation, 10, 63, 96, 118–19 gig economy and, 146 superstar companies and, 118–19 Taylor, Frederick Winslow, 150, 152, 153, 154 Tel Aviv, Israel, 181 telecom companies, 122–3 Tencent, 65, 104, 108, 122 territorial sovereignty, 185, 199, 214 Tesco, 67, 93 Tesla, 69, 78, 113 Thailand, 176, 203 Thatcher, Margaret, 64, 163 Thelen, Kathleen, 87 Thiel, Peter, 110–11 3D printing, see additive manufacturing TikTok, 28, 69, 159–60, 219 Tisné, Martin, 240 Tomahawk missiles, 207 Toyota, 95 trade networks, 61–2, 166–7, 169, 175 trade unions, see collective bargaining Trading Places (1983 film), 132 Tragedy of the Commons, The (Hardin), 241 transistors, 18–22, 28–9, 48–9, 52, 113, 251 transparency, 236 Treaty of Westphalia (1648), 199 TRS-80, 16 Trump, Donald, 79, 119, 166, 201, 225, 237 Tufekci, Zeynep, 233 Turing, Alan, 18, 22 Turkey, 102, 176, 186, 198, 202, 206, 231 Tversky, Amos, 74 23andMe, 229–30 Twilio, 151 Twitch, 225 Twitter, 65, 201, 202, 219, 223, 225, 237 two cultures, 7, 8 Uber, 69, 94, 102, 103, 106, 142, 144, 145 Assembly Bill 5 (California, 2019), 148 engineering jobs, 156 London ban (2019), 183, 188 London protest (2016), 153 pay at, 147, 156 satisfaction levels at, 146 Uber BV v Aslam (2021), 148 UiPath, 130 Ukraine, 197, 199 Unilever, 153 Union of Concerned Scientists, 56 unions, see collective bargaining United Arab Emirates, 43, 198, 250 United Autoworkers Union, 162 United Kingdom BBC, 87 Biobank, 242 Brexit (2016–20), 6, 168 collective bargaining in, 163 Covid-19 epidemic (2020–21), 79, 203 DDT in, 253 digital minilateralism, 188 drone technology in, 207 flashing of headlights in, 83 Golden Triangle, 170 Google and, 116 Industrial Revolution (1760–1840), 79–81 Luddite rebellion (1811–16), 125, 253 misinformation in, 203, 204 National Cyber Force, 200 NHS, 87 self-employment in, 148 telecom companies in, 123 Thatcher government (1979–90), 64, 163 United Nations, 87, 88, 188 United States antitrust law in, 114 automation in, 127 Battle of the Overpass (1937), 162 Capitol building storming (2021), 225 China, relations with, 166 Cold War (1947–91), 194, 212, 213 collective bargaining in, 163 Covid-19 epidemic (2020–21), 79, 202–4 Cyber Command, 200, 210 DDT in, 253 drone technology in, 205, 214 economists in, 63 HIPA Act (1996), 230 Kenosha unrest shooting (2020), 224 Lordstown Strike (1972), 125 manufacturing in, 130 misinformation in, 202–4 mobile phones in, 76 nuclear weapons, 237 Obama administration (2009–17), 205, 214 polarisation in, 232 presidential election (2016), 199, 201, 217 presidential election (2020), 202–3 Reagan administration (1981–9), 64, 163 self-employment in, 148 September 11 attacks (2001), 205, 210–11 shipping containers in, 61 shopping in, 48 solar energy research, 37 Standard Oil breakup (1911), 93–4 taxation in, 63, 119 Trump administration (2017–21), 79, 119, 166, 168, 201, 225, 237 Vietnam War (1955–75), 216 War on Terror (2001–), 205 universal basic income (UBI), 160, 189 universal service obligation, 122 University of Cambridge, 127, 188 University of Chicago, 63 University of Colorado, 73 University of Delaware, 55 University of Oxford, 129, 134, 203, 226 University of Southern California, 55 unwritten rules, 82 Uppsala Conflict Data Program, 194 UpWork, 145–6 USB (Universal Serial Bus), 51 Ut, Nick, 216 utility providers, 122–3 vaccines, 12, 202, 211, 245–7 Vail, Theodore, 100 value-free, technology as, 5, 220–21, 254 Veles, North Macedonia, 200–201 Véliz, Carissa, 226 Venezuela, 75 venture capitalists, 117 vertical expansion, 112–13, 116 vertical farms, 171–2, 251 video games, 86 Vietnam, 61, 175, 216 Virological, 245 Visa, 98 VisiCalc, 99 Vodafone, 121 Vogels, Werner, 68 Wag!

Cogs and Monsters: What Economics Is, and What It Should Be
by Diane Coyle
Published 11 Oct 2021

Specialisation and exchange, either domestic or international, are the source of the transformative economic growth of the past quarter millennium. They are the drivers of the global supply chains now under attack for reasons of national advantage or resilience during a crisis. Common sense finds it equally hard to accept that jobs have no objective existence in the economy separate from the people who currently do them (the ‘lump of labour fallacy’), or that it can be a good thing for the economy’s growth rate if some businesses are allowed to fail. Applied economists have a pragmatic common language for assembling evidence and discussing policy. Disagreements concern the details of empirical methods or the interpretation of evidence.

…

., 182 L’Etranger (Camus), 87 liberalisation, 38, 68–69, 196 licenses, 59 life expectancy, 145 living standards, 143–47, 172, 194 loans, 109, 147, 158 lobbying, 29, 64–65, 69, 149 logic, 33, 47, 89–91 London School of Economics, 17 London Underground, 62–63 Long-Term Capital Management (LTCM), 23 Lucas, Robert, 75 Lucas Critique, 103 lump of labour fallacy, 78 machine learning (ML), 12–13, 137, 141, 160–61, 187 MacKenzie, Donald, 23–24, 26 macroeconomics: agglomeration and, 127, 132, 202, 207; aggregate behaviour and, 3, 40, 42, 71–72, 100–102, 106, 113, 122–23, 141, 176–77, 201–2; criticism of, 17; empirical work and, 74, 100; forecasting and, 3, 12, 36–37, 76, 101–2, 112; globalisation and, 110, 132, 139, 154, 164, 193–94, 196, 213; Great Depression and, 17; Gross Domestic Product (GDP) and, 13, 101, 113, 151; inflation and, 12–13, 17, 36, 73, 113; innovation and, 37, 71, 102; Keynes and, 73, 75, 151, 191; Keynesian, 151; markets as a process and, 37–45; models and, 21 (see also models); outsider context and, 12, 100–3, 112–14; politics and, 76; progress and, 151; public responsibilities and, 17, 21, 31, 36–37, 71–76, 85–86; separation protocol and, 124; statistics and, 101–2, 113, 131; twenty-first-century policy and, 191 Malthus, Thomas, 48 Mandel, Michael, 96–97 Mankiw, Greg, 86 manufacturing, 105, 149–50, 172, 178, 195–98 marginal costs, 128, 174, 200, 208 Marglin, Steve, 16, 193 Market Abuse Regulation (MAR), 27n5 Markets, State and People (Coyle), 114, 212 Marshall, Alfred, 132 Marshall Aid, 190 Marx, Karl, 48 McFadden, Daniel, 59 Merton, Robert C., 23–24, 28 Merton, Robert K., 22–23 #metoo, 9 microeconomics, 2, 12, 37, 58, 92, 101, 110–11, 121, 209 microfoundations, 90 Microsoft, 133, 170, 173 Millenium Bug, 155 models: abstract mathematics and, 2; ad hoc, 89–92, 94, 150; agents and, 21, 81, 102, 109, 118, 179, 209; assumptions in, 21–22, 35, 46–47, 62–63, 90–94, 119, 137, 154, 177, 209; behavioural, 22, 35, 47, 63, 88, 92–93, 119, 136, 154; Black-Scholes-Merton, 23–25, 28; business, 139, 165, 197; causality and, 2, 94–95, 102; changing economies and, 168, 176–77, 179–80; complexity and, 2, 49, 94, 102, 106, 179–80; counterfactuals and, 97–98, 158, 161, 198, 208; forecasting and, 17, 74, 101–2, 113; frictions and, 22, 113, 136, 154, 182; Great Financial Crisis (GFC) and, 31, 101, 113; inflation and, 30, 113; influence of, 23; Korzybski on, 89; moral issues and, 129; Nash equilibrium and, 90–91; objective of, 89–90; outsider context and, 55, 88–103, 106, 109, 113; over-fitting, 95; platform, 197; progress and, 139, 151–52, 154, 159–61; rationality and, 21–22, 31, 35, 45–48, 62, 71, 88–103, 117–18; reality building by, 23; Scott on, 63; transaction costs and, 168; twenty-first-century policy and, 185–86, 189, 191, 197, 209 Modern Monetary Theory (MMT), 75, 102 monetarism, 16, 71, 73, 75 monopolies, 20, 29, 42 Monti, Mario, 67–69 Mont Pèlerin Society, 31, 191, 193–94 Moore’s Law, 170, 184 moral issues: Atkinson and, 129; causality and, 96; Cook and, 150; ethics, 4, 34, 39, 100, 105, 115, 119–24; fairness, 43, 45–46, 166; models and, 129; outsider context and, 96, 106–8; progress and, 148, 150; rationality and, 117; Sandel on, 34, 39, 43, 107, 119; Stern and, 148 MySpace, 205 Nash equilibrium, 90–91 National Health Service (NHS), 44–45, 77 “Nature and Significance of Economic Science, The” (Robbins), 121 neoliberalism, 3, 15, 193–94 network effects: competition and, 202, 205; economies of scale and, 127, 174, 177, 185, 199–201, 209; fixed costs and, 174, 177, 179, 185–86, 200; indirect, 174; twenty-first-century policy and, 185, 199–202, 205, 209; progress and, 141 New Deal, 193 New Public Management, 33, 106–7, 119, 187 New York Times, 19 Nobel Prize, 21, 23, 35, 44, 47, 59, 63, 92, 109, 140, 209 Nordhaus, William, 170 normative economics: decision making and, 110, 114, 120; Friedman and, 104, 121; Gelman and, 108; policy implications and, 125–26; positive economics and, 10, 104, 108, 114, 120–21, 125, 146; progress and, 146; welfare and, 114, 120, 134 nuclear arms race, 190 Obama, Barack, 75 Occupy movement, 19, 131 Office for Budget Responsibility, 66 Office for National Statistics, 171 OPEC, 192 OpenTable, 142, 175, 200 opportunity cost, 56, 58, 80, 156 optimisation, 48, 118, 188 Organisation for Economic Co-operation and Development (OECD), 130, 132, 164, 190 Ormerod, Paul, 106 Oscar awards, 108 Ostrom, Elinor, 63–64 outsider context: behavioural economics and, 88, 92–93, 100, 103–9; causality and, 94–96, 99–105; competition and, 98, 105; consumers and, 92, 96, 98, 100–102, 105, 108–9; decision making and, 93; Great Financial Crisis (GFC) and, 87–88, 101, 110, 112–14; growth and, 12, 97, 101n1, 111; interventions and, 87, 94, 104, 106; macroeconomics and, 12, 100–103, 112–14; methodology for, 88–103; models and, 55, 88–103, 106, 109, 113; politics and, 106, 110; regulation and, 109; technology and, 103; welfare and, 105–7, 114 outsourcing, 139, 195–97 Oxfam, 95–96 Packard, Vance, 109 Papademos, Lucas, 67 Pareto criterion, 121–23, 126–27, 129 patents, 140 pensions, 18, 37, 60, 65, 146 Perez, Carlotta, 189 performativity, 11, 23, 30, 211 Peste, La (Camus), 108 Petty, William, 148 Phillips machine, 135–37, 151, 192 Pigou, A.

The Future of the Professions: How Technology Will Transform the Work of Human Experts
by Richard Susskind and Daniel Susskind
Published 24 Aug 2015

They argue that the pessimists’ account relies on the ‘lump of labour fallacy’—a term given by economists to the belief that there is some fixed quantity of reasonably-paid work, a given ‘lump’ of labour that is to be divided up and parcelled out either to people or to machines. The optimists rightly note that this is wrong, and make an argument based on Question 1. If a new technology is more productive, it will increase output, there will be more work that has to be done, and so more tasks for people to do. There is no fixed ‘lump’ of labour, and instead the quantity of reasonably-paid work will grow over time.

The Wealth of Humans: Work, Power, and Status in the Twenty-First Century
by Ryan Avent
Published 20 Sep 2016

THE DIFFICULTY IN MANAGING A LABOUR GLUT To say that humanity has too many workers is to defy a basic tenet of economics. Labour is not supposed to work like that. When someone suggests that there are too many people around to do the work society needs done, he is said to be under the influence of the ‘lump of labour’ fallacy: the view that there is only so much work to go around – the lump. This view leads to policies such as those designed to lower the retirement age in order to create more work for the young. If we believe this basic theory, then we should certainly worry about the rise of machines. Economists, however, are generally of the opinion that the economy works quite differently.

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Acemoglu, Daron ageing populations agency, concept of Airbnb Amazon American Medical Association (AMA) anarchism Andreessen, Marc Anglo-Saxon economies Apple the iPhone the iPod artisanal goods and services Atkinson, Anthony Atlanta, Georgia austerity policies automation in car plants fully autonomous trucks of ‘green jobs’ during industrial revolution installation work as resistant to low-pay as check on of menial/routine work self-driving cars and technological deskilling automobiles assembly-line techniques automated car plants and dematerialization early days of car industry fully autonomous trucks self-driving cars baseball Baumol, William Belgium Bernanke, Ben Bezos, Jeff black plague (late Middle Ages) Boston, Massachusetts Brazil BRIC era Bridgewater Associates Britain deindustrialization education in extensions of franchise in financial crisis (2008) Great Exhibition (London 1851) housing wealth in and industrial revolution Labour Party in liberalization in political fractionalization in real wages in social capital in surpassed by US as leading nation wage subsidies in Brontë, Charlotte Brynjolfsson, Erik bubbles, asset-price Buffalo Bill (William Cody) BuzzFeed Cairncross, Frances, The Death of Distance (1997) capital ‘deepening’ infrastructure investment investment in developing world career, concept of cars see automobiles Catalan nationalism Central African Republic central banks Chait, Jonathan Charlotte chemistry, industrial Chicago meat packers in nineteenth-century expansion of World’s Columbia Exposition (1893) China Deng Xiaoping’s reforms economic slow-down in era of rapid growth foreign-exchange reserves ‘green jobs’ in illiberal institutions in inequality in iPod assembly in technological transformation in wage levels in Chorus (content-management system) Christensen, Clayton Cisco cities artisanal goods and services building-supply restrictions growth of and housing costs and industrial revolution and information membership battles in rich/skilled and social capital clerical work climate change Clinton, Hillary Coase, Ronald Columbia University, School of Mines communications technology communism communities of affinity computing app-based companies capability thresholds cloud services cycles of experimentation desktop market disk-drive industry ‘enterprise software’ products exponential progress narrative as general purpose technology hardware and software infrastructure history of ‘Moore’s Law’ and productivity switches transistors vacuum tubes see also digital revolution; software construction industry regulations on Corbyn, Jeremy Corliss steam engine corporate power Cowen, Tyler craft producers Craigslist creative destruction the Crystal Palace, London Dalio, Ray Dallas, Texas debt deindustrialization demand, chronically weak dematerialization Detroit developing economies and capital investment and digital revolution era of rapid growth and industrialization pockets of wealth in and ‘reshoring’ phenomenon and sharp slowdown and social capital see also emerging economies digital revolution and agency and company cultures and developing economies and distance distribution of benefits of dotcom tech boom emergence of and global imbalances and highly skilled few and industrial institutions and information flows investment in social capital niche markets pace of change and paradox of potential productivity and output and secular stagnation start-ups and technological deskilling techno-optimism techno-pessimism as tectonic economic transformation and trading patterns web journalism see also automation; computing; globalization discrimination and exclusion ‘disruption’, phenomenon of distribution of wealth see inequality; redistribution; wealth and income distribution dotcom boom eBay economics, classical The Economist education in emerging economies during industrial revolution racial segregation in USA and scarcity see also university education electricity Ellison, Glenn Ellison, Sara Fisher emerging economies deindustrialization economic growth in education in foreign-exchange reserves growth in global supply chains highly skilled workers in see also developing economies employment and basic income policy cheap labour as boost to and dot.com boom in Europe and financial crisis (2008) ‘green jobs’ low-pay sector minimum wage impact niche markets in public sector ‘reshoring’ phenomenon as rising globally and social contexts and social membership as source of personal identity and structural change trilemma in USA see also labour; wages Engels, Friedrich environmental issues Etsy euro- zone Europe extreme populist politics liberalized economies political fractionalization in European Union Facebook face-recognition technology factors of production land see also capital; labour ‘Factory Asia’ factory work assembly-line techniques during industrial revolution family fascism Federal Reserve financial crisis (2008) financial markets cross-border capital flows in developing economies Finland firms and companies Coase’s work on core competencies culture of dark matter (intangible capital) and dematerialization and ‘disruption’ ‘firm-specific’ knowledge and information flows internal incentive structures pay of top executives shifting boundaries of social capital of and social wealth start-ups Ford, Martin, Rise of the Robots (2015) Ford Motor Company fracking France franchise, electoral Friedman, Milton Fukuyama, Francis Gates, Bill gender discrimination general purpose technologies enormous benefits from exponential progress and skilled labour supporting infrastructure and time lags see also digital revolution Germany ‘gig economy’ Glaeser, Ed global economy growth in supply chains imbalances lack of international cooperation savings glut and social consensus globalization hyperglobalization and secular stagnation and separatist movements Goldman Sachs Google Gordon, Robert Gothenburg, Sweden Great Depression Great Depression (1930s) Great Exhibition, London (1851) Great Recession Great Stagnation Greece ‘green jobs’ growth, economic battle over spoils of boom (1994-2005) and classical economists as consistent in rich countries decline of ‘labour share’ dotcom boom emerging economies gains not flowing to workers and industrial revolution Kaldor’s ‘stylized facts of’ and Keynes during liberal era pie metaphor in post-war period and quality of institutions and rich/elite cities rich-poor nation gap and skilled labour guilds Hansen, Alvin Hayes, Chris, The Twilight of the Elites healthcare and medicine hedge funds and private equity firms Holmes, Oliver Wendell Hong Kong housing in Bay-Area NIMBY campaigns against soaring prices pre-2008 crisis zoning and regulations Houston, Texas Huffington Post human capital Hungary IBM identity, personal immigration and ethno-nationalist separatism and labour markets in Nordic countries and social capital income distribution see inequality; redistribution; wealth and income distribution India Indonesia industrial revolution automation during and economic growth and growth of cities need for better-educated workers and productivity ‘second revolution’ and social change and wages and World’s Fairs inequality and education levels between firms and housing wealth during industrial revolution during liberal era between nations pay of top executives rise of in emerging economies and secular stagnation in Sweden wild contingency of wealth see also rich people; wealth and income distribution inflation in 1970s hyperinflation information technology see computing Intel interest rates International Space Station (ISS) iRobot ISIS Italy Jacksonville, Florida Jacquard, Joseph Marie Japan journalism Kaldor, Nicholas Keynes, John Maynard Kurzweil. Ray labour abundance as good problem bargaining power cognitive but repetitive collective bargaining and demographic issues discrimination and exclusion global growth of workforce and immigration liberalization in 1970s/80s ‘lump of labour’ fallacy occupational licences organized and proximity reallocation to growing industries retraining and skill acquisition and scarcity and social value work as a positive good see also employment Labour Party, British land scarcity Latvia Le Pen, Jean-Marie Le Pen, Marine legal profession Lehman Brothers collapse (2008) Lepore, Jill liberalization, economic (from 1970s) Linkner, Josh, The Road to Reinvention London Lucas, Robert Lyft maker-taker distinction Malthus, Reverend Thomas Manchester Mandel, Michael Mankiw, Gregory marketing and public relations Marshall, Alfred Marx, Karl Mason, Paul, Postcapitalism (2015) McAfee, Andrew medicine and healthcare ‘mercantilist’ world Mercedes Benz Mexico Microsoft mineral industries minimum wage Mokyr, Joel Monroe, President James MOOCs (‘massive open online courses’) Moore, Gordon mortality rates Mosaic (web browser) music, digital nation states big communities of affinity inequality between as loci of redistribution and social capital nationalist and separatist movements Netherlands Netscape New York City Newsweek NIMBYism Nordic and Scandinavian economies North Carolina North Dakota Obama, Barack oil markets O’Neill, Jim Oracle Orbán, Viktor outsourcing Peretti, Jonah Peterson Institute for International Economics pets.com Philadelphia Centennial Fair (1876) Philippines Phoenix, Arizona Piketty, Thomas, Capital in the Twenty-First Century (2013) Poland political institutions politics fractionalization in Europe future/emerging narratives geopolitical forces human wealth narrative left-wing looming upheaval/conflict Marxism nationalist and separatist movements past unrest and conflict polarization in USA radicalism and extremism realignment revolutionary right-wing rise of populist outsiders and scarcity social membership battles Poor Laws, British print media advertising revenue productivity agricultural artisanal goods and services Baumol’s Cost Disease and cities and dematerialization and digital revolution and employment trilemma and financial crisis (2008) and Henry Ford growth data in higher education of highly skilled few and industrial revolution minimum wage impact paradox of in service sector and specialization and wage rates see also factors of production professional, technical or managerial work and education levels and emerging economies the highly skilled few and industrial revolution and ‘offshoring’ professional associations skilled cities professional associations profits Progressive Policy Institute property values proximity public spending Putnam, Robert Quakebot quantitative easing Race Against the Machine, Brynjolfsson and McAfee (2011) railways Raleigh, North Carolina Reagan, Ronald redistribution and geopolitical forces during liberal era methods of nation state as locus of as a necessity as politically hard and societal openness wealth as human rent, economic Republican Party, US ‘reshoring’ phenomenon Resseger, Matthew retail sector retirement age Ricardo, David rich people and maker-taker distinction wild contingency of wealth Robinson, James robots Rodrik, Dani Romney, Mitt rule of law Russia San Francisco San Jose Sanders, Bernie sanitation SAP Saudi Arabia savings glut, global ‘Say’s Law’ Scalia, Antonin Scandinavian and Nordic economies scarcity and labour political effects of Schleicher, David Schwartz, Anna scientists Scotland Sears Second World War secular stagnation global spread of possible solutions shale deposits sharing economies Silicon Valley Singapore skilled workers and education levels and falling wages the highly skilled few and industrial revolution ‘knowledge-intensive’ goods and services reshoring phenomenon technological deskilling see also professional, technical or managerial work Slack (chat service) Slate (web publication) smartphone culture Smith, Adam social capital and American Constitution baseball metaphor and cities ‘deepening’ definition/nature of and dematerialization and developing economies and erosion of institutions of firms and companies and good government and housing wealth and immigration and income distribution during industrial revolution and liberalization and nation-states productive application of and rich-poor nation gap and Adam Smith and start-ups social class conflict middle classes and NIMBYism social conditioning of labour force working classes social democratic model social reform social wealth and social membership software ‘enterprise software’ products supply-chain management Solow, Robert Somalia South Korea Soviet Union, dissolution of (1991) specialization Star Trek state, role of steam power Subramanian, Arvind suburbanization Sweden Syriza party Taiwan TaskRabbit taxation telegraphy Tesla, Nikola Thatcher, Margaret ‘tiger’ economies of South-East Asia Time Warner Toyota trade China as ‘mega-trader’ ‘comparative advantage’ theory and dematerialization global supply chains liberalization shaping of by digital revolution Adam Smith on trade unions transhumanism transport technology self-driving cars Trump, Donald Twitter Uber UK Independence Party United States of America (USA) 2016 Presidential election campaign average income Bureau of Labour Statistics (BLS) Constitution deindustrialization education in employment in ethno-nationalist diversity of financial crisis (2008) housing costs in housing wealth in individualism in industrialization in inequality in Jim Crow segregation labour scarcity in Young America liberalization in minimum wage in political polarization in post-crisis profit rates productivity boom of 1990s real wage data rising debt levels secular stagnation in shale revolution in social capital in and social wealth surpasses Britain as leading nation wage subsidies in university education advanced degrees downward mobility of graduates MOOCs (‘massive open online courses’) and productivity see also education urbanization utopias, post-work Victoria, Queen video-gamers Virginia, US state Volvo Vox wages basic income policy Baumol’s Cost Disease cheap labour and employment growth and dot.com boom and financial crisis (2008) and flexibility and Henry Ford government subsidies and housing costs and immigration and industrial revolution low-pay as check on automation minimum wage and productivity the ‘reservation wage’ as rising in China rising in emerging economies and scarcity in service sector and skill-upgrading approach stagnation of and supply of graduates Wandsworth Washington D.C.

The Health Gap: The Challenge of an Unequal World
by Michael Marmot
Published 9 Sep 2015

A friend, a professor at a prestigious US university, tells me that half the full professors in his school are over seventy and some are in their eighties. It seems obvious that the old should step aside to make way for the young. There are only so many jobs to go around, and if the old won’t move the young can’t have them. Obvious, but wrong. The idea that older people are blocking jobs for younger people – the ‘lump of labour’ hypothesis – has been debunked as a myth.10 The flaw is to assume that there is a fixed number of jobs. The evidence shows that, in general, the higher the participation of older people in the labour market the higher the employment rate of younger people – more jobs for the old and more jobs for the young.

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., here Lewis, Michael, here Lexington, Kentucky, here libertarians, here, here life expectancy, here, here, here, here among Australian aboriginals, here disability-free, here, here and education, here, here, here, here in former communist states, here and mental health, here and national income, here US compared with Cuba, here Lithuania, here, here, here Liverpool, here, here, here ‘living wage’, here loans, low-interest, here lobbying, here Los Angeles, here ‘lump of labour’ hypothesis, here Lundberg, Ole, here lung cancer, here, here lung disease, here, here, here, here luxury travel, here Macao, here, here McDonald’s, here McMunn, Anne, here Macoumbi, Pascoual, here Madrid, indignados protests, here, here Maimonides, here malaria, here, here, here, here, here Malawi, here male adult mortality, here, here Mali, here, here Malmö, here, here Malta, here Manchester, here, here, here Maoris, here, here, here, here Marmot Review, see Fair Society, Healthy Lives marriage, here Marx, Karl, here maternal mortality, here, here, here maternity leave, paid, here Matsumoto, Scott, here Meaney, Michael, here Medicaid, here Mediterranean diet, here Mengele, Joseph, here mental health, here, here, here, here, here, here, here and access to green space, here and adverse childhood experience, here and austerity, here and fear of crime, here and job insecurity, here and unemployment, here meritocracy, here Mexico, here, here, here, here, here education and cash transfers, here, here Millennium Birth Cohort Study, here, here Minimum Income for Healthy Living, here, here, here Mitchell, Richard, here Modern Times, here Morris, Jerry, here, here Moser, Kath, here Mozambique, infant mortality, here Mullainathan, Sendhil, here Murphy, Kevin, here, here Muscatelli, Anton, here Mustard, Fraser, here Mwana Mwende project, here Nathanson, Vivienne, here Native Americans, here Navarro, Vicente, here NEETs, here, here neoliberalism, here, here, here, here, here Nepal, here, here Neruda, Pablo, here Netherlands, here, here New Guinea, here, here NEWS group, here, here Nietzsche, Friedrich, here, here Niger, here nitrogen dioxide, here, here non-human primates, here Nordic countries and commission report, here and social protection, here, here, here, here, here see also individual countries Norway, here, here, here, here, here, here life expectancy and education, here, here Nottingham, here Nozick, Robert, here obesity, here, here, here, here, here, here, here, here in children, here, here and diabetes, here and disincentives, here food corporations and, here genetic and environmental factors in, here and migrant studies, here and rational choice theory, here social gradient in, here, here, here, here in women, here, here Office of Budget Responsibility, here Olympic Games, here opera, here Organisation for Economic Co-operation and Development (OECD), here, here, here, here, here, here, here organisational justice, here Orwell, George, here Osler, Sir William, here Panorama, here Papua New Guinea, here ‘paradox of thrift’, here Paraguay, here, here, here parenting, here, here, here, here and work–life balance, here pay, low, here pensions, here, here, here, here Perkins, Charlie, here Peru, here, here, here physical activity and cognitive function, here green space and, here Pickett, Kate, here Pierson, Paul, here, here Piketty, Thomas, here, here, here, here Pinker, Steven, here Pinochet, General Augusto, here PISA scores, here, here, here, here, here Poland, here, here, here, here Popham, Frank, here Porgy and Bess, here poverty, here, here, here, here, here, here, here and aboriginal populations, here, here absolute and relative, here, here child poverty, here, here, here, here, here and choice, here and early childhood development, here, here effect on cognitive function, here and urban unrest, here and work, here Power, Chris, here pregnancy, here preventive health care, here ‘proportionate universalism’, here puberty, and smoking here public transport, here, here, here, here, here, here, here, here Ramazzini, Bernardino, here RAND Corporation, here, here, here rational choice theory, here, here, here rats, and brain development, here Rawls, John, here, here Reid, Donald, here Reinhart, Carmen, here, here reproduction, control over, here retirement, here reverse causation, here Reykjavik Zoo, here Rio de Janeiro, here, here Rogoff, Kenneth, here, here Rolling Stones, here Romania, here Romney, Mitt, here Rose, Geoffrey, here Roth, Philip, here Royal College of Physicians, here Royal Swedish Academy of Science, here Russia, here, here, here and alcohol use, here life expectancy, here, here, here, here Sachs, Jeffrey, here, here St Andrews, here San Diego, here Sandel, Michael, here, here Sapolsky, Robert, here Scottish Health Survey, here Seattle, here Self Employed Women’s Association (SEWA), here, here, here, here Sen, Amartya, here, here, here, here, here, here, here, here, here, here, here and Jean Drèze, here, here, here, here serotonin, here sexuality, here, here see also reproduction, control over sexually transmitted infections, here, here Shafir, Eldar, here Shakespeare, William, here, here, here, here Shanghai, here Shaw, George Bernard, here, here Shepherd, Jonathan, here shootings, here Siegrist, Johannes, here Sierra Leone, here, here, here Singapore, here, here Slovakia, here Slovenia, here, here smallpox vaccinations, here Smith, Adam, here Smith, Jim, here smoking, here, here, here, here, here, here, here, here declining rates of, here, here and education, here and public policy, here social gradient in, here, here and tobacco companies, here and unemployment, here Snowdon, Christopher, here social cohesion, here, here, here, here, here, here, here social mobility, here, here social protection, here ‘social rights’, here Social Science and Medicine, here Soundarya Cleaning Cooperative, here South Korea, here, here, here, here Spain, here, here, here Spectator, here sports sponsorship, here Sri Lanka, here Stafford, Mai, here Steptoe, Andrew, here Stiglitz, Joseph, here, here, here, here, here stroke, here, here, here structural adjustments, here, here Stuckler, David, here suicide, here, here, here, here, here and aboriginal populations, here, here and Indian cotton farmers, here and unemployment, here, here suicide, attempted, here Sulabh International, here Sun, here Sure Start programme, here Surinam, here Sutton, Willie, here Swansea, here Sweden, here, here, here, here, here, here, here life expectancy and education, here, here male adult mortality, here, here Swedish Commission on Equity in Health, here Syme, Leonard, here, here, here Taiwan, here, here Tanzania, here taxation, here Thailand, here Thatcher, Margaret, here Theorell, Tores, here tobacco companies, here Topel Robert, here Tottenham riots, here Tower Hamlets, here, here Townsend, Peter, here trade unions, here, here, here, here traffic calming measures, here Tressell, Robert, here ‘Triangle that Moves the Mountain’, here, here trickle-down economics, here, here Truman, Harry S., here tuberculosis, here, here, here, here Tunisia, here Turandot, here, here Turkey, here, here Uganda, here, here unemployment, here, here, here, here, here, here, here and mental health, here and suicide, here, here youth unemployment, here, here, here, here UNICEF, here, here United Kingdom alcohol consumption, here capital:income ratio, here and child well-being, here cost of childcare, here and economic recovery, here, here education system, here, here disability-free life expectancy, here founding of welfare state, here health-care system, here income inequalities, here, here literacy levels, here male adult mortality, here PISA score, here politics and economics, here and poverty in work, here, here poverty levels, here, here prison population, here social attitudes, here and social interventions, here social mobility, here ‘strivers and scroungers’ rhetoric, here, here and taxation, here unemployment, here use of tables for meals, here United Nations Development Programme (UNDP), here, here, here, here United States of America air pollution, here, here alcohol consumption, here capital:income ratio, here child poverty, here and child well-being, here cotton subsidies, here and economic recovery, here education system, here, here, here female life expectancy, here and gang violence, here health-care system, here, here income inequalities, here, here, here, here international comparisons, here, here, here lack of paid maternity leave, here life expectancy and education, here male adult mortality, here, here, here maternal mortality, here, here obesity levels, here, here, here, here PISA score, here politics and economics, here and poverty in work, here poverty levels, here prison population, here race and disadvantage, here, here, here, here, here social disadvantage and health, here social mobility, here suicide rate, here and taxation, here US Centers for Disease Control and Prevention, here US Department of Justice, here US Federal Reserve Bank, here US National Academy of Science (NAS), here, here, here, here University of Sydney, here urban planning, here Uruguay, here, here, here, here utilitarianism, here, here, here Vågerö, Denny, here valuation of life, here Victoria Longitudinal Study, here Vietnam, here, here violence, here domestic (intimate partner), here, here, here Virchow, Rudolf, here vulture funds, here, here Wales, youth unemployment in, here walking speed, here Washington Consensus, here, here, here welfare spending, here West Arnhem College, here Westminster, life expectancy in, here Whitehall Studies, here, here, here, here, here, here, here wife-beating, here Wilde, Oscar, here, here Wilkinson, Richard, here willingness-to-pay methodology, here, here Wolfe, Tom, here, here women and alcohol use, here and cash-transfer schemes, here A Note on the Author Born in England and educated in Australia, Sir Michael Marmot is Professor of Epidemiology and Public Health at UCL.

More: The 10,000-Year Rise of the World Economy
by Philip Coggan
Published 6 Feb 2020

If more workers mean lower wages, then how come the rise in the global population from 1 billion to 7 billion hasn’t led to mass poverty? The obvious answer is that each worker is also a source of demand. Each immigrant spends the money they earn on local goods and services. Economists talk about the “lump of labour” fallacy; a belief that there is only a certain amount of work to do. The fallacy has been used to argue that women should stay out of the workforce to leave more jobs for men, and that older workers should retire early to create jobs for the young. Immigration may have an impact on the real wages of unskilled labour.

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On the political right, many have blamed immigration; they argue that an influx of unskilled workers has driven down wages by increasing the supply of labour. However, immigrants are not just workers, they are also consumers; as well as increasing the supply of labour, they increase the demand for goods. This “lump of labour” fallacy is hard to kill (see Chapter 9). As noted earlier in the book, the real culprit could be found elsewhere. A study by the IMF found that the reason for around half the decline in labour’s share of GDP was the impact of technology, as employers were able to automate low-skilled jobs. Another quarter of the shift was down to globalisation; companies in the developed world were shifting jobs to low-wage countries in the rest of the world.39 The sluggish overall level of growth that followed the financial crisis led some economists to rethink their previous models.

Inequality and the 1%
by Danny Dorling
Published 6 Oct 2014

The government says we cannot afford this, but that is clearly incorrect. The state pension is roughly the same as Jobseekers’ Allowance. Every older worker who wishes to retire but cannot without a state pension could create a job for someone unemployed. There may not be a fixed amount of work available, a ‘lump of labour’, but there is a finite pay chest. Compared to young people, older retired people are much more likely to take up voluntary work in the community – and thus increase social capital. There is also less of a stigma attached to being retired than to being unemployed, resulting in less depression and other mental illness.

The Economic Singularity: Artificial Intelligence and the Death of Capitalism
by Calum Chace
Published 17 Jul 2016

This money can then be spent to buy more of the item, or other items, thereby raising demand generally, and creating jobs. This assumes, however, that the money freed up is not spent on expensive assets that generate no employment, or invested in companies that employ very few people. Economists also point out that the Luddite fallacy also depends on a misapprehension about economics called the “Lump of Labour Fallacy”, which is the idea that there is a certain, fixed amount of work available, and if machines do some of it then there is inevitably less for humans to do. In fact, economies are more organic and more flexible: they respond to shifts, and innovate to grow. New jobs are created as old ones disappear and the former outnumber the latter.

A Pelican Introduction: Basic Income
by Guy Standing
Published 3 May 2017

He told the American media group Bloomberg, ‘It’s not like the fall of the auto and steel industries. That hit just a sector of the country. This will be widespread. People will realize that we don’t have a storm anymore; we have a tsunami.’16 Nevertheless, there are reasons to be sceptical about the prospect of a jobless or even workless future. It is the latest version of the ‘lump of labour fallacy’, the idea that there is only a certain amount of labour and work to be done, so that if more of it can be automated or done by intelligent robots, human workers will be rendered redundant. In any case, very few jobs can be automated in their entirety. The suggestion in a much-cited study17 that nearly half of all US jobs are vulnerable to automation has been challenged by, among others, the OECD, which puts the figure of jobs ‘at risk’ at 9 per cent for industrialized countries.18 That said, the nature of jobs will undoubtedly change, perhaps rapidly.

The Great Divergence: America's Growing Inequality Crisis and What We Can Do About It
by Timothy Noah
Published 23 Apr 2012

News, working in consultation with the economist Heidi Shierholz of the Washington-based Economic Policy Institute, a liberal-leaning think tank, calculated that the middle class shrank by about 6 percent between 1980 and 2009. 5. Rose, Social Stratification, 27–28; and Rose, Rebound, 103. 6. Economists call this the “lump of labor fallacy.” The term was coined by the British economist David F. Schloss, who wrote in 1891: “The theory of the Lump of Labour will be seen to rest upon the utterly untenable supposition that a fixed amount of work exists, which has to be done, and will be done, irrespective of the conditions under which the work is done, and, in particular, irrespective of the efficiency of the labour employed; and that, the more work is done by any one workman, the less work remains to be done by all other workmen… The character of this fallacy will best be understood [through]… the precisely similar objection to a man’s using the best available tools; in other words, with the popular objection to the use of motor power and machinery.

The Precariat: The New Dangerous Class
by Guy Standing
Published 27 Feb 2011

It is all very well for economists to claim that jobs will come in non-tradable sectors. A POLITICS OF PARADISE 177 What we are learning is that most activities are tradable. Expecting jobs to be the means by which inequality is reduced is whistling in the wind. Jobs will not disappear. To think otherwise is to accept the ‘lump of labour fallacy’. But many if not most will be low paying and insecure. Capital funds can be used to accumulate financial returns to help pay for a basic income. There are precedents. The Alaska Permanent Fund, established in 1976, was set up to distribute part of the profits from oil production to every legal resident of Alaska.

The Corruption of Capitalism: Why Rentiers Thrive and Work Does Not Pay
by Guy Standing
Published 13 Jul 2016

Although measured unemployment is higher than a few decades ago, this must be seen in the context of population growth and globalisation, in which the world’s labour supply has more than tripled. There are more jobs than at any time in history. One difficulty is that many analysts interpret ‘disruption’ – a favoured word – as the destruction of jobs in general and the simple replacement of labour by robots and automation. This rests on the ‘lump of labour fallacy’ – the assumption that there is only a certain amount of labour to be done; if machines can do more at less cost, then workers (particularly those with ‘low skills’) will be displaced. But there is not a fixed amount of labour and work to be done. Sooner or later, commentators cite the Luddite riots that began in 1809, when self-employed weavers smashed machines.

Welcome to Britain: Fixing Our Broken Immigration System
by Colin Yeo;
Published 15 Feb 2020

While surveys show that the public can and do distinguish between high- and low-skilled migrants when questions are put to them, there is little evidence that these niceties come into play when ‘immigration’ is discussed as a supposedly simple, generic, broad issue – as it is, for example, during an election campaign. There are plenty of commonplace myths regarding economics and immigration that feed this narrative, such as the ‘lump of labour fallacy’ – the idea that an economy includes a finite number of jobs – or that immigration suppresses wages. That these enduring myths are false is irrelevant; they are widely believed by the public and by many in the media and the political classes. By promoting increased immigration, taking ownership of immigration as an issue but making a purely economic case for increased immigration levels, Labour ensured that its record was always going to be vulnerable to later attack.

Them and Us: How Immigrants and Locals Can Thrive Together
by Philippe Legrain
Published 14 Oct 2020

Not only would this condemn them to worse lives in almost every respect, it would amount to a punitive tax on the much higher incomes that they could earn in rich countries; doctors in Nigeria typically earn only $560 (£430) a month.25 Women are particularly likely to emigrate from countries that deny them rights to those that offer them many more; how is it ethical to deny them those rights?26 Next consider the economics. Previous chapters showed that the belief that migrants take local jobs is generally false because there isn’t a fixed number of jobs to go around. Economists call this the ‘lump-of-labour fallacy’. But the brain-drain argument is in many ways analogous to that fallacy. Just as it is mistaken to claim that every job taken by a migrant is one less for locals, it is incorrect to believe that every doctor who moves to a rich country entails one less for poor countries. There isn’t a fixed number of doctors to go around.

Small Men on the Wrong Side of History: The Decline, Fall and Unlikely Return of Conservatism
by Ed West
Published 19 Mar 2020

I think I snapped while reading Michael Morpurgo’s version of The Pied Piper of Hamelin (2011), in which a bunch of ruddy-faced toff kids live it up in luxury while some poor urban (and multiracial, because they’re the goodies) urchins are left to starve, which is obviously an allegory of Thatcherism. At one point the Pied Piper refuses a large payment because, he says: ‘When one man becomes rich, ten others become poor.’1 I’m not an unswerving free-marketer by any means but I blurted out as I read this, ‘That’s just not true, you know that, right? That’s the lump of Labour fallacy!’ My daughters didn’t seem that interested for some reason, although they were four and three at the time. Still fuming, I googled Morpurgo’s net worth and found he’d made over £15 million in a decade!2 There must be dozens of people homeless as a result, the bastard. Children’s stories in the past weren’t like this.