technological unemployment

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

But it is still helpful in highlighting what should actually be worrying us about the future: not a world without any work at all, as some predict, but a world without enough work for everyone to do. There is a tendency to treat technological unemployment as a radical discontinuity from economic life today, to dismiss it as a fantastical idea plucked out of the ether by overly neurotic shock-haired economists. By exploring how technological unemployment might actually happen, we will see why that attitude is a mistake. It is not a coincidence that, today, worries about economic inequality are intensifying at the exact same time that anxiety about automation is growing. These two problems—inequality and technological unemployment—are very closely related. Today, the labor market is the main way that we share out economic prosperity in society: most people’s jobs are their main, if not their only, source of income.

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To adapt the old saying, nothing in life can be said to be certain, except death, taxes—and this relentless process of task encroachment. 6 Frictional Technological Unemployment When John Maynard Keynes popularized the term “technological unemployment” about ninety years ago, he prophesied that we would “hear a great deal in the years to come” about it.1 Despite his clarity about the threat, however, and his prescience about the anxiety that would accompany it, he did not really explain how technological unemployment would happen. He described it as arising “due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour,” but offered very few specifics.

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When he is found out, his punishment is to stand, for eternity, in a pool of water up to his chin, surrounded by trees bursting with fruit—but the water recedes from his lips whenever he tries to take a sip, and the tree branches swing away when he reaches out to pick their bounty.2 The story of Tantalus, which gives us the word tantalize, captures the spirit of one kind of technological unemployment, which we can think of as “frictional” technological unemployment. In this situation, there is still work to be done by human beings: the problem is that not all workers are able to reach out and take it up.3 Frictional technological unemployment does not necessarily mean there will be fewer jobs for human beings to do. For the next decade or so, in almost all economies, the substituting force that displaces workers is likely to be overwhelmed by the complementing force that raises the demand for their work elsewhere.

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

AI researchers and others hastened to warn us (rightly) not to throw the baby of AI out with the bathwater of unfriendly superintelligence, and the debate is now more nuanced. Technological unemployment and the economic singularity So for me at least, the term “singularity” no longer seems so awkward. And it seems reasonable to apply it to another event which is likely to take place well before the technological singularity. I call this event “the economic singularity”. There is a lot of talk in the media at the moment about technological unemployment – the process of people becoming unemployed because machines can do any job that they could do, and do it cheaper, faster and better.

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Nevertheless we must try to peer into the hazy future if we are to prepare ourselves for it. In this book I will argue that technological unemployment is not happening yet (or at least, not much), that it will happen in the next few decades, and that it can be a very good thing indeed – if we prepare for it, and manage the transition successfully. Naturally, there are challenges. As we will see, a lot of people believe that Universal Basic Income (UBI) is a silver bullet that will solve the problem of technological unemployment. UBI is a guaranteed income paid to all citizens simply because they are citizens. It may take some time for the idea of UBI to be accepted, especially in the USA, where resistance to anything that smacks of socialism is often fierce – almost visceral.

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The History of Automation 11 2.1 – The industrial revolution 11 2.2 – The information revolution 13 2.3 – The Automation story so far 15 2.3 – The Automation story so far 15 2.4 – The Luddite fallacy 20 3 – Is it different this time? 23 3.1 – Prophets of change 24 3.2 – Academic and consultancy studies 30 3.3 – Crying wolf 34 3.4 – AI to date 37 3.5 – Exponential future 46 3.6 – What people do 52 3.7 – Related technologies 55 3.8 – The poster child for technological unemployment: self-driving vehicles 67 3.9 – Who's next? 74 3.10 – Jobs or no jobs 84 3.11 – What's the problem? 93 3.12 – Conclusion: yes, it’s different this time 95 4. - A timeline 97 4.1 – Un-forecasts 97 4.2 – 2021 100 4.3 – 2031 102 4.4 – 2041 105 5. - The Challenges 108 5.1 – Economic contraction 109 5.2 – Distribution 110 5.3 – Meaning 118 5.4 – Allocation 121 5.5 – Cohesion 124 6. - Scenarios 128 6.1 – No Change 128 6.2 – Racing with the machines 130 6.3 – Capitalism + UBI 132 6.4 – Fracture 133 6.5 – Collapse 134 6.6 – Protopia 135 Chapter 7.

Narrative Economics: How Stories Go Viral and Drive Major Economic Events
by Robert J. Shiller
Published 14 Oct 2019

But this 1929 story was beginning to have an impact. A decade earlier, a new phrase had appeared in the English language to describe the effects of labor-saving inventions. The phrase was technological unemployment. This phrase appeared first in 1917, but it started its epidemic upswing in 1928. The count for technological unemployment skyrockets in the 1930s in Google Ngrams into an epidemic curve much like the Ebola epidemic curve in Figure 3.1. The technological unemployment curve peaked in 1933, the worst year of the Great Depression. A parallel epidemic occurred with the term power age, which is now mostly gone. The power age referred to the perception that activities once done by muscle are now done by powerful machines.

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By 1880, only a fifth of the US labor force worked in agriculture, and the narratives focused instead on new fuel-powered and electronic machines, threatening the jobs to which agricultural people fled from the farms. (Less than 2% of the US workforce is in agriculture today.) Technological unemployment became a new and persistent worry. It is curious that the narrative epidemic of technological unemployment began in 1928, a time of prosperity well before the Great Depression. Still, 1928 was a time of heightened concern about unemployment, which was blamed entirely on technological unemployment and not connected in public talk to any weakness in the US economy. Philip Snowden, former and future chancellor of the Exchequer in the United Kingdom, wrote in the New York Times in 1928 that the United States, then the leader in developing labor-saving devices, had a unique problem of technological unemployment: But if other countries are compelled to follow America in specialization and in the displacement of human labor, the problem of unemployment in these countries will assume the feature of the existing unemployment problem in America.

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In other words, the problem is to free the human being from slavery to the iron man.18 By the 1920s, there was much talk about “efficiency experts” whose “time and motion studies” treated workers as if they were machines. The experts’ goals were to eliminate any unnecessary motions, thereby saving time and labor cost. Like other narratives that took form in the late 1920s and went viral in the Great Depression of the 1930s, efficiency was associated with technological unemployment. How did the epidemic of technological unemployment fears start? In March 1928, US senator Robert Wagner stated his belief that unemployment was much higher than recognized, and he asked the Department of Labor to do a study of unemployment. Later that month, the department delivered the study that produced the first official unemployment rates published by the US government.

Free Money for All: A Basic Income Guarantee Solution for the Twenty-First Century
by Mark Walker
Published 29 Nov 2015

Consider this deductive argument: Premise 1: People wrongly claimed that automation would result in massive technological unemployment during 1811–2014. 104 FREE MONEY FOR ALL Premise 2: If people wrongly claimed that automation would result in massive technological unemployment during 1811–2014, then people who claim in 2014 that robots will result in massive technological unemployment are wrong. Conclusion: People who claim in 2014 that robotics will result in massive technological unemployment are wrong. If we accept Premises 1 and 2, then we are logically forced to accept the conclusion. With inductive arguments, it is possible to accept the premises but deny the conclusion.

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Despite Chicken Little’s horrendous track record of failure in predicting technological unemployment, I think the prediction of technological unemployment is sound. The Nature of the Debate between Chicken Little and the Economists Thus far, I have merely rehearsed the outlines of a familiar debate. It is easy to get the impression that we are at an argumentative impasse. On one hand, the case for Chicken Little is based on the observation that computers and robotics are making inroads into so many sectors of the economy: agriculture, mining, construction, manufacturing, PEACE, ROBOTS, AND TECHNOLOGICAL UNEMPLOYMENT 103 retail, professional services, teaching, health care, and food services, to name but a few.

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The remedy is BIG: BIG will help ease us peacefully into the new economic reality. In other words, the argument is that BIG is an effective means to thwart the threat to peace precipitated by the robotic revolution. Technological Unemployment One way to analyze the threat to employment from robotics is to consider all the jobs presently done by humans that could soon be performed by robots. Let us fast-forward 20 years and imagine you PEACE, ROBOTS, AND TECHNOLOGICAL UNEMPLOYMENT 95 need to do a little shopping. You go to your local Walmart and pick up a few groceries and other household items. On the way to your office, you realize you forgot to buy an electric razor, so you order one through Amazon on your cell phone.

Future Politics: Living Together in a World Transformed by Tech
by Jamie Susskind
Published 3 Sep 2018

What’s the harm in sharpening our intellectual tools while we still have time? The analysis in this chapter is organized in four stages. We begin with the technological unemployment thesis itself. Next, we look at the work paradigm, the idea that we need work for income, status, OUP CORRECTED PROOF – FINAL, 26/05/18, SPi РЕЛИЗ ПОДГОТОВИЛА ГРУППА "What's News" VK.COM/WSNWS Technological Unemployment 297 and wellbeing. We then consider three responses to technological unemployment from within the work paradigm: treating work as a scarce resource, giving people a right to work, and trying to resist automation altogether.

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It can’t be right that algorithms of justice are entrusted to an engineering community that is overwhelmingly made up of men.27 African-Americans receive about 10 per cent of computer science degrees and make up about 14 per cent of the overall workforce, but make up less than 3 per cent of computing occupations in Silicon Valley.28 At the very least, a workforce more representative of the public might mean greater awareness of the social implications of any given application of code. For now, it’s time to leave algorithmic injustice and turn to another potential challenge for social justice in the digital lifeworld: technological unemployment. OUP CORRECTED PROOF – FINAL, 26/05/18, SPi РЕЛИЗ ПОДГОТОВИЛА ГРУППА "What's News" VK.COM/WSNWS SEVENTEEN Technological Unemployment ‘it is the machine which possesses skill and strength in place of the worker, is itself the virtuoso, with a soul of its own in the mechanical laws acting through it’ Karl Marx, Fragment on Machines (1861) Do you work to live or live to work?

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In 2015 Richard Susskind (the world’s leading authority on legal technology, also my dad) and Daniel Susskind (one of the world’s most acclaimed young economists, also my brother) together published The Future of the Professions, in which they predicted the gradual replacement of human professionals by digital systems.4 In 2018 Daniel Susskind will publish a new book on the topic which, with fraternal pride, I expect to become the definitive work. It would be an act of family betrayal if I didn’t at least consider the idea of technological unemployment in this book. (I know, I know, we’re a strange family.) Clan loyalty aside, no responsible citizen can now ignore the prospect, accepted by growing ranks of economists, that in the future there may not be enough human work to go around. I call this the technological unemployment thesis. I don’t seek to assess in detail the economic case for and against it. I acknowledge that there are respectable thinkers who think it’s flawed.

The End of Work
by Jeremy Rifkin
Published 28 Dec 1994

Nearly $46 out of every $100 of new capital went to the military economy.55 Even with the addition of a permanent military-industrial complex, the postwar boom was threatened by continued technological unemployment in the 1950S and 1960s resulting from breakthroughs in automation. New products-especially television and consumer electronics-helped cushion the blow and provide jobs for workers displaced by machines in other industries. The service sector also grew significantly, in part to fill the vacuum left by millions of women leaving the home to work in the economy. Government spending continued to provide jobs as well, dampening the effect of technological unemployment. In 1929 government spending was only 12 percent of the gross national product.

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ll The failure to adequately address the question of technological unemployment is partially the fault of organized labor. The voice of millions of working Americans, the labor movement waffled repeatedly on the issue of automation, only to eventually cast its lot with management, to the detriment of its own constituency. The father of cybernetics, Norbert Weiner, who perhaps more than any other human being was in a position to clearly perceive the long-term consequences of the new automation technologies, warned of the dangers of widespread and permanent technological unemployment He wrote, "If these changes in the demand for labor come upon us in a haphazard and ill-organized way, we may well be in for the greatest period of unemployment we have yet seen."12 Weiner became so fearful of the high-tech future he and his colleagues were creating that he wrote an extraordinary letter to Walter Reuther, president of the United Auto Workers, pleading for an audience.

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Published simultaneously in Canada Library of Congress Cataloging-in-Publication Data Rifkin, Jeremy. The end of work: the decline of the global labor force and the dawn of the post-market era I Jeremy Rifkin. p. cm. "A Jeremy P. Tarcher/Putnam book." Includes bibliographical references and index. ISBN 0-87477-779-8 1. Technological unemployment. I. Title. HD6331.R533 1995 94-12394 CIP 33l·13' 7042-dc20 Design by Lee Fukui Printed in the United States of America 1 2 3 4 5 6 7 8 9 10 This book is printed on acid-free paper. @ In memory of my father, Milton Rifkin, who understood, better than anyone I know, the workings of the marketplace For my mother, Vivette Rifkin, who personifzes the volunteer spirit in American society For Ernestine Royster and her family and their dream of a better tomorrow Contents Acknowledgments Foreword by Robert L.

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

In the professions, though, our general view is that this (often nostalgic) preference for the old ways of working will be too high a price to pay, especially if the quality of service is demonstrably lower than that provided by a machine. 7.3. Technological unemployment? In 1930, speculating about ‘the economic possibilities for our grandchildren’, John Maynard Keynes introduced the concept of ‘technological unemployment’.23 The basic idea is simple—that new technologies might put people out of work. The question to which we now turn is whether there will be technological unemployment in the professions in the very long term. The short answer is, ‘there will’. We can find no economic law that will somehow secure employment for professionals in the face of increasingly capable machines.24 However, it is uncertain how extensive the job-loss will be.

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In this and the following section we explain why there is uncertainty here, and we provide a new framework for thinking in a systematic way about technological unemployment in the professions. By way of preface, we need to be careful with the term ‘employment’. Our interest is not simply in whether technology might put professionals out of work, but also how well paid any work is. A future where there is full employment but with wages below subsistence level would be a worry. Our focus, then, is on the future of what we call ‘reasonably-paid’ employment. Hotdogs To tackle the question of technological unemployment, we find it helpful to work with a simplified story, one that we base on a discussion of ‘hotdogs’ by Paul Krugman, a Nobel Laureate in economics.25 Imagine a company that hires people to make hotdogs, and that this involves just three tasks—preparing the sausage, baking the bun, and putting the hotdog together.

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Whether as optimist or pessimist, however, we suggest that it is only when we consider all three questions together that can we say anything reliable about the consequences of increasingly capable machines on reasonably-paid employment. Taken together, our three questions lead us to the crux of the debate on technological unemployment. If new technologies create a large quantity of new additional tasks, and these are of a type in which people rather than machines have the advantage, then concerns about technological unemployment are misplaced. On the other hand, if new technologies do not create many additional tasks, or if the tasks that they do create are of a type in which machines, rather than people, have the advantage, then technological employment, to a greater or lesser extent, will follow. 7.4.

Fully Automated Luxury Communism
by Aaron Bastani
Published 10 Jun 2019

For Fukuyama the end of history signalled a world defined by economic calculation and ‘the endless solving of technical problems, environmental concerns, and the satisfaction of sophisticated consumer demands’. And yet the present moment, defined by challenges such as rising temperatures, technological unemployment, income inequality and societal ageing – to name just a few – poses questions which extend beyond mere technical competence. If Fukuyama’s words were naive in 1992, then in the decade that followed the financial crisis of 2008 they became positively ridiculous. Indeed, he admitted as much in a book he published on identity in 2018.

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They are climate change and the consequences of global warming; resource scarcity – particularly for energy, minerals and fresh water; societal ageing, as life expectancy increases and birth rates concurrently fall; a growing surplus of global poor who form an ever-larger ‘unnecessariat’; and, perhaps most critically, a new machine age which will herald ever-greater technological unemployment as progressively more physical and cognitive labour is performed by machines, rather than humans. Confronting such crises is the basis of FALC. Capitalism, at least as we know it, is about to end. What matters is what comes next. The claim that capitalism will end, is, for capitalist realism, like saying a triangle doesn’t have three sides or that the law of gravity no longer applies while an apple falls from a tree.

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From Crisis to Utopia Ours is a finite world marked by constraints. To a large extent, these constraints define the five crises set to radically shape the course of the coming century. Together, these crises – encompassing climate change, resource scarcity, ever-larger surplus populations, ageing and technological unemployment as a result of automation – are set to undermine capitalism’s ability to reproduce itself. That is because they could dissolve some of its key features like the presumption of constant expansion and infinite resources, production for profit, and workers having to sell their labour. In 1984 the futurist Stewart Brand made the now-iconic declaration ‘Information wants to be free.’

Automation and the Future of Work
by Aaron Benanav
Published 3 Nov 2020

Would we be able to adapt our institutions to realize the dream of human freedom that a new age of intelligent machines might make possible? Or would that dream turn out to be a nightmare of mass technological unemployment? In two New Left Review articles published in 2019, I identified a new automation discourse propounded by liberal, right-wing, and left analysts alike. Asking just these sorts of questions, automation theorists arrive at a provocative conclusion: mass technological unemployment is coming and can be managed only by the provision of universal basic income, since large sections of the population will lose access to the wages they need to survive.

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However, over the past decade, this talk has crystalized into an influential social theory that purports not only to analyze current technologies and predict their future, but also to explore the consequences of technological change for society at large. The automation discourse rests on four principal propositions. First, it argues, workers are already being displaced by ever more advanced machines, resulting in rising levels of “technological unemployment.” Second, this displacement is a sure sign that we are on the verge of achieving a largely automated society, in which nearly all work will be performed by self-moving machines and intelligent computers. Third, although automation should entail humanity’s collective liberation from toil, we live in a society where most people must work in order to live, meaning this dream may well turn out to be a nightmare.4 Fourth, therefore, the only way to prevent a mass-unemployment catastrophe—like the one unfolding in the United States in 2020, although for very different reasons—is to institute a universal basic income (UBI), breaking the connection between the size of the incomes people earn and the amount of work they do.

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Robert Reich, former labor secretary under Bill Clinton, expressed similar fears: we will soon reach a point “where technology is displacing so many jobs, not just menial jobs but also professional jobs, that we’re going to have to take seriously the notion of a universal basic income.” Clinton’s former Treasury secretary, Lawrence Summers, made the same admission: once-“stupid” ideas about technological unemployment now seem increasingly smart, he said, as workers’ wages stagnate and economic inequality rises. The discourse even became the basis of a long-shot presidential campaign for 2020: Andrew Yang, Obama’s former “Ambassador of Global Entrepreneurship,” penned his own tome on automation titled The War on Normal People and ran a futuristic campaign on a “Humanity First” platform, introducing UBI into mainstream American politics for the first time in two generations.

Give People Money
by Annie Lowrey
Published 10 Jul 2018

UBI’s strange bedfellows put forward a dizzying kaleidoscope of arguments, drawing on everything from feminist theory to environmental policy to political philosophy to studies of work incentives to sociological work on racism. Perhaps the most prominent argument for a UBI has to do with technological unemployment—the prospect that robots will soon take all of our jobs. Economists at Oxford University estimate that about half of American jobs, including millions and millions of white-collar ones, are susceptible to imminent elimination due to technological advances. Analysts are warning that Armageddon is coming for truck drivers, warehouse box packers, pharmacists, accountants, legal assistants, cashiers, translators, medical diagnosticians, stockbrokers, home appraisers—I could go on.

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This seems a particularly prevalent concern given how many men have dropped out of the labor force of late, pushed by stagnant wages and pulled, perhaps, by the low-cost marvels of gaming and streaming. With a UBI, the country would lose the ingenuity and productivity of a large share of its greatest asset: its people. More than that, a UBI implemented to fight technological unemployment might mean giving up on American workers, paying them off rather than figuring out how to integrate them into a vibrant, tech-fueled economy. Economists of all political persuasions have voiced similar concerns. And a UBI would do all of this at extraordinary expense. Let’s say that we wanted to give every American $1,000 a month in cash.

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And self-driving cars are not the only technology on the horizon with the potential to dramatically reduce the need for human work. Today’s Cassandras are warning that there is scarcely a job out there that is not at risk. If you have recently heard of UBI, there is a good chance that it is because of these driverless cars and the intensifying concern about technological unemployment writ large. Elon Musk of Tesla, for instance, has argued that the large-scale automation of the transportation sector is imminent. “Twenty years is a short period of time to have something like 12 [to] 15 percent of the workforce be unemployed,” he said at the World Government Summit in Dubai in 2017.

Race Against the Machine: How the Digital Revolution Is Accelerating Innovation, Driving Productivity, and Irreversibly Transforming Employment and the Economy
by Erik Brynjolfsson
Published 23 Jan 2012

contestants are shown answers and must ask questions that would yield these answers. Chapter 3. Creative Destruction: The Economics of Accelerating Technology and Disappearing Jobs We are being afflicted with a new disease of which some readers may not yet have heard the name, but of which they will hear a great deal in the years to come—namely, technological unemployment. This means unemployment due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour. —John Maynard Keynes, 1930 The individual technologies and the broader technological acceleration discussed in Chapter 2 are creating enormous value.

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But there’s a limit to this adjustment. Shortly after the Luddites began smashing the machinery that they thought threatened their jobs, the economist David Ricardo, who initially thought that advances in technology would benefit all, developed an abstract model that showed the possibility of technological unemployment. The basic idea was that at some point, the equilibrium wages for workers might fall below the level needed for subsistence. A rational human would see no point in taking a job at a wage that low, so the worker would go unemployed and the work would be done by a machine instead. Of course, this was only an abstract model.

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As technology continues to advance in the second half of the chessboard, taking on jobs and tasks that used to belong only to human workers, one can imagine a time in the future when more and more jobs are more cheaply done by machines than humans. And indeed, the wages of unskilled workers have trended downward for over 30 years, at least in the United States. We also now understand that technological unemployment can occur even when wages are still well above subsistence if there are downward rigidities that prevent them from falling as quickly as advances in technology reduce the costs of automation. Minimum wage laws, unemployment insurance, health benefits, prevailing wage laws, and long-term contracts—not to mention custom and psychology—make it difficult to rapidly reduce wages.3 Furthermore, employers will often find wage cuts damaging to morale.

The Technology Trap: Capital, Labor, and Power in the Age of Automation
by Carl Benedikt Frey
Published 17 Jun 2019

In the early 1930s, discussions of machines stealing citizens’ jobs were featured in radio talk shows, films, and academic conferences, and the Committee on Labor of the House of Representatives even held several hearings on the subject.3 The return of machinery angst cannot be explained in complete isolation from the Great Depression, which certainly exacerbated and prolonged concerns about technological unemployment. Yet the latter was not the cause of the former. As the economic historian Gregory Woirol has pointed out, “The honor of starting the technological unemployment debates belongs to Secretary of Labor James J. Davis.”4 In a 1927 speech, two years before the outbreak of the Great Depression, Davis was the first to take note of the technological challenges facing labor: For a long time it was thought impossible to turn out machines capable of replacing human skill in the making of glass.

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However, his later analysis suggested the opposite: mechanization, he found, had been a key factor in unemployment.12 As economists today still struggle to isolate the share of nonemployment attributable to technology, it should be no surprise that research efforts of the 1930s faced similar challenges. At the time, Leo Wolman, who served in the National Recovery Administration during the Great Depression, pointed at several empirical issues limiting progress in studies of technological unemployment, of which many seemed hard to overcome.13 Despite statistical challenges, the emerging consensus among contemporary economists was that there was technological unemployment, albeit of temporary nature. The likes of Paul H. Douglas, Alvin Hansen, and Rexford G. Tugwell all argued that labor market rigidities were impeding the process by which workers would be reabsorbed into new jobs: the expense of moving between locations, the human drags of retraining, and the psychological pressures of job loss made adjustment costly and hard.

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The first few introductions of electronic computers into the workplace sparked a panic about the threat of automation to jobs in the news media, and the upsurge in unemployment that came with the three post–Korean War recessions led people to connect the two. Looking back in 1965, Robert Solow noted: “Whenever there is both rapid technological change and high unemployment the two will inevitably be connected in people’s minds. So it is not surprising that technological unemployment was a live subject during the depression of the 1930s, nor that the debate has now revived.”18 As noted above, the technological unemployment debate actually predated the Great Depression. However, machinery angst in the twentieth century was clearly cyclical, and this time it followed an upswing in unemployment after the Korean War. Though it is hard to detect much progression in the nature of the debate, our vocabulary bears witness to the progression of technology: the discussions of the 1950s and 1960s centered on the new popular term “automation.”19 Just like “technological unemployment” in the 1930s, “automation” and its discontents became one of the defining themes of the postwar years.

Work in the Future The Automation Revolution-Palgrave MacMillan (2019)
by Robert Skidelsky Nan Craig
Published 15 Mar 2020

Of course, the way we react to change depends not only on the problem but also on the assumptions we hold about what would constitute a good outcome. Both David Graeber and Rachel Kay favour reducing human work, while Irmgard Nübler focuses on how technological unemployment can be mitigated and job growth maintained. David Graeber argues that the future of technological unemployment predicted by J.M. Keynes has in fact come to pass—but that we have compensated for the lack of work by creating millions of make-work jobs with little purpose. He recommends giving people the means to leave pointless jobs by severing livelihood from work through a universal basic income.

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In the past, it has not only created new jobs but reduced the hours of work per job. This could also repeat itself. On the other hand, there is the view that, whatever may have been true in the past, we have now reached a tipping point—or soon will— when the advent of intelligent machines is simply going to destroy existing jobs faster than it creates new jobs. If so, technological unemployment would turn from its relatively benign past process into a virulent involuntary one. There are several issues worth discussing, keeping those two views in mind. First of all is history. What do the long run data of population growth, employment growth, hours of work, earnings per hour worked since the industrial revolution tell us?

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This process, he warned, was unlikely be smooth. 1 Heretical Essays in the Philosophy of History, 97. R. Skidelsky (*) Centre for Global Studies, London, UK e-mail: skidelskyr@parliament.uk © The Author(s) 2020 R. Skidelsky, N. Craig (eds.), Work in the Future, https://doi.org/10.1007/978-3-030-21134-9_2 9 10 R. Skidelsky We are being afflicted with a new disease … namely technological unemployment. This means unemployment due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour. But this is only a temporary phase of maladjustment. All this means in the long run that mankind is solving its economic problem.2 Ever since machinery became an active part of industrial production, redundancy has been seen either as a promise or a threat.

Basic Income And The Left
by henningmeyer
Published 16 May 2018

The current use of social policy to control the individual’s contact with the labour market atomises individuals and NO NEED FOR BASIC INCOME: FIVE POLICIES TO DEAL WITH THE THREAT OF TECHNOLOGICAL UNEMPLOYMENT segments society. Basic income has the potential to BY HENNING MEYER (27 MARCH 2017) enable a new set of more direct relationships among citizens, and a more balanced relation of citizens with the state. The potential threat of technological unemployment is one of the most hotly debated economic issues of our times: in boardrooms and trade union offices but also increasingly amongst policy-makers. The catch-all term ‘digital’ may have been added to numerous political concepts in recent years but beyond such branding there has been very little debate of substance about what a comprehensive policy response to this threat should be.

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Universal Basic Income: A Disarmingly Simple Idea – And Fad 10. Unconditional Basic Income Is A Dead End 11. Basic Income Is A Tonic Catalyser: A Response To Anke Hassel 12. Basic Income And Institutional Transformation 13. No Need For Basic Income: Five Policies To Deal With The Threat Of Technological Unemployment 14. Citizen’s Income: Both Feasible And Useful 15. UBI: A Bad Idea For The Welfare State 16. What Is An Unconditional Basic Income? A Response To Rothstein v 1 5 AUTHORS 12 21 28 37 45 Louise Haagh is a Reader in Politics at the Univer‐ sity of York, co-editor of the academic journal Basic 52 Income Studies and chair of the Basic Income Earth Network.

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The idea is, of course, not new but has logical change is likely to make existing skills obso‐ had numerous incarnations over many decades and lete ever more quickly so it would be quite easy to been presented as a solution for quite different lose the ability to work and remain stuck on basic problems. The one that concerns us here is simply income quasi-permanently. whether the UBI could be a solution for large-scale technological unemployment or temporary labour market dislocations that could result from acceler‐ ated technological change. When examining the issue in detail it becomes clear that a basic income would not solve many of the key issues. There are several reasons for this. This point in turn raises the question of inequality.

The Blockchain Alternative: Rethinking Macroeconomic Policy and Economic Theory
by Kariappa Bheemaiah
Published 26 Feb 2017

Thus, as the definition of capitalism begins to involve the democratic state to a greater degree, we should also use this opportunity to see how we can address the problems of technological unemployment, education, productivity changes, inequality, and ageism. One solution pathway could lie with helicopter money and universal basic income. Helicopter Drops and Universal Basic Income Refresh your memory and think about the last time you heard these “keywords ”: technological unemployment, income inequality, stagnant wages, poverty, regulatory gridlock. If you are a regular follower of the news, then the chances are that you may have heard these terms almost on a weekly basis.

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It also investigates if these changes could offer sovereign states a new way to produce money and looks at alternatives other than inflation and interest rates to govern monetary policy. Finally, it reviews different scenarios of how this new structure can be used to implement innovative policies, such as overt money finance and universal basic income, which could help address issues such as income inequality and technological unemployment that currently threaten most economies. While the purpose of the book it to shed more light on the implications of the widespread use of Blockchain technology, the growing diversity within the currency space cannot be fully excluded from the discussion. As the blockchain gains more traction in formal financial circles, its first manifestation in the form of Bitcoin is increasingly being excluded from the dialogue.

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As stated by Daniel Nadler, CEO of Kensho, at a Milken conference (2016), “It’s not just associates and VPs … [it’s] also the thousands of software engineers [at banks] …. Those jobs are going to get decimated, literally.” Advantages: greater inclusion, increased competition, data standardization Risks: compliance costs, regulation blocks risk monitoring, and technological unemployment 4. Capital Markets Stance: Business-facing Main technologies: Trading Algorithms, Big Data, Neural Nets, Machine/Deep Learning, AI If we were to increase the scale, speed, and volume of the transactions and services stated in the private wealth management industry, we would find ourselves in the high-frequency trading (HFT) world of capital markets , which encompasses the trade and management of private equity, commodities, and derivatives.

The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies
by Erik Brynjolfsson and Andrew McAfee
Published 20 Jan 2014

His essay looked past the immediate hard times of the Great Depression and offered a prediction: “We are being afflicted with a new disease of which some readers may not yet have heard the name, but of which they will hear a great deal in the years to come—namely, technological unemployment. This means unemployment due to our discovery of means of economizing the use of labor outrunning the pace at which we can find new uses for labor.”15 The extended joblessness of the Great Depression seemed to confirm Keynes’s ideas, but it eventually eased. Then came World War II and its insatiable demands for labor, both on the battlefield and the home front, and the threat of technological unemployment receded. After the war ended, the debate about technology’s impact on the labor force resumed and took on new life once computers appeared.

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This is the core of the economic argument that technological unemployment is impossible. KEYNES DISAGREED. He thought that in the long run, demand would not be perfectly inelastic. That is, ever lower (quality-adjusted) prices would not necessarily mean we would consume ever more goods and services. Instead, we would become satiated and choose to consume less. He predicted that this would lead to a dramatic reduction in working hours to as few as fifteen per week as less and less labor was needed to produce all the goods and services that people demanded.23 However, it’s hard to see this type of technological unemployment as an economic problem.

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This is the possibility that Wassily Leontief had in mind his 1983 article when he speculated that many workers could end up permanently unemployed, like horses unable to adjust to the invention of the tractors.26 Once one concedes that it takes time for workers and organizations to adjust to technical change, then it becomes apparent that accelerating technical change can lead to widening gaps and increasing possibilities for technological unemployment. Faster technological progress may ultimately bring greater wealth and longer lifespans, but it also requires faster adjustments by both people and institutions. With apologies to Keynes, in the long run we may not be dead, but we will still need jobs. The third argument for technological unemployment may be the most troubling of all. It goes beyond “temporary” maladjustments. As described in detail in chapters 8 and 9, recent advances in technology have created both winners and losers via skill-biased technical change, capital-biased technical change, and the proliferation of superstars in winner-take-all markets.

Machines of Loving Grace: The Quest for Common Ground Between Humans and Robots
by John Markoff
Published 24 Aug 2015

A 2014 working paper released by the National Bureau of Economic Research confirmed the trend, and yet Henry Siu, an associate professor at the University of British Columbia and one of the authors of the report, clung to the conventional Keynesian view on technological unemployment. He explained: “Over the very long run, technological progress is good for everybody, but over shorter time horizons, it’s not that everybody’s a winner.”1 It is probably worth noting that Keynes also pointed out that in the long run, we are all dead. Indeed, Keynes’s actuarial logic is impeccable, but his economic logic is now under assault. There is an emerging perspective among technologists and some economists that Keynesian assumptions about technological unemployment—that individual jobs are lost but the overall amount of work stays constant—no longer hold true.

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It is quite likely that we will soon have the opportunity to conduct a parallel experiment in the First World. The idea of a basic income is already on the political agenda in Europe. Raised by the Nixon administration in the form of a negative income tax in 1969, the idea is currently not politically acceptable in the United States. However, that will change quickly if technological unemployment becomes widespread. What will happen if our labor is no longer needed? If jobs for warehouse workers, garbage collectors, doctors, lawyers, and journalists are displaced by technology? It is of course impossible to know this future, but I suspect society will find that humans are hardwired to work or find an equivalent way to produce something of value in the future.

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Indeed, the headings in the report have proven true over the years: “Computers Are Becoming Faster, Smaller, and Less Expensive”; “Computing Power Will Become Available Much the Same as Electricity and Telephone Service Are Today”; “Information Itself Will Become Inexpensive and Readily Available”; “Computers Will Become Easier to Use”; “Computers Will Be Used to Process Pictorial Images and Graphic Information”; and “Computers Will Be Used to Process Language,” among others. Yet the consensus that emerged from the report would be the traditional Keynesian view that “technology eliminated jobs, not work.” The report concluded that technological displacement would be a temporary but necessary stepping-stone for economic growth. The debate over the future of technological unemployment dissipated as the economy heated up, in part as a consequence of the Vietnam War, and the postwar civil strife in the late 1960s further sidelined the question. A decade and a half after he had issued his first warnings about the consequences of automated machines, Wiener turned his thoughts to religion and technology while remaining a committed humanist.

The Lights in the Tunnel
by Martin Ford
Published 28 May 2011

In 1930, as the world plunged into the Great Depression, John Maynard Keynes wrote an essay entitled “Economic Possibilities for our Grandchildren.”52 In his essay, Keynes coined the term “technological unemployment,” writing: We are being inflicted with a new disease of which some readers many not yet have heard the name, but of which they will hear a great deal in the years to come—namely, technological unemployment. This means unemployment due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour.* *[ Today, when economists discuss the causes of the Great Depression, they tend to focus almost exclusively on the monetary policy of the Federal Reserve.

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While there is little double that the overly restrictive policies of the Fed prolonged the Depression and perhaps turned a run of the mill recession into a disaster, it should not be forgotten that there was a widespread belief at the time that the technological unemployment (and the resulting plunge in consumer demand) that Keynes spoke of played an important role. Even Albert Einstein expressed this opinion when asked for his take on the causes of the Depression during a visit to the United States in 1933. ] Keynes recognized that, in 1930, technological unemployment would be a temporary phenomenon and that the economy would eventually absorb the excess workers. The main thrust of his essay was to attempt to look much further into the future.

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The Lights in the Tunnel: Automation, Accelerating Technology and the Economy of the Future / Martin Ford p. cm. Includes bibliographical references ISBN-10 1-4486-5981-7 ISBN-13 978-1-4486-5981-4 1. Economics—Future Trends 2. Economics—Impact of Advanced Technology on 3. Artificial Intelligence and Robotics 4. Computer Technology and Civilization 5. Technological Unemployment I. Title The scanning, uploading and distribution of this book via the Internet without the permission of the publisher is illegal. Please purchase only authorized electronic editions. Your support of the author’s rights is appreciated. This book is available for purchase in paper and electronic formats at: www.TheLightsintheTunnel.com CONTENTS A Note to Kindle Users Introduction Chapter 1: The Tunnel The Mass Market Visualizing the Mass Market Automation Comes to the Tunnel A Reality Check Summarizing Chapter 2: Acceleration The Rich Get Richer World Computational Capability Grid and Cloud Computing Meltdown Diminishing Returns Offshoring and Drive-Through Banking Short Lived Jobs Traditional Jobs: The “Average” Lights in the Tunnel A Tale of Two Jobs “Software” Jobs and Artificial Intelligence Automation, Offshoring and Small Business “Hardware” Jobs and Robotics “Interface” Jobs The Next “Killer App” Military Robotics Robotics and Offshoring Nanotechnology and its Impact on Employment The Future of College Education Econometrics: Looking Backward The Luddite Fallacy A More Ambitious View of Future Technological Progress: The Singularity A War on Technology Chapter 3: Danger The Predictive Nature of Markets The 2008-2009 Recession Offshoring and Factory Migration Reconsidering Conventional Views about the Future The China Fallacy The Future of Manufacturing India and Offshoring Economic and National Security Implications for the United States Solutions Labor and Capital Intensive Industries: The Tipping Point The Average Worker and the Average Machine Capital Intensive Industries are “Free Riders” The Problem with Payroll Taxes The “Workerless” Payroll Tax “Progressive” Wage Deductions Defeating the Lobbyists A More Conventional View of the Future The Risk of Inaction Chapter 4: Transition The Basis of the Free Market Economy: Incentives Preserving the Market Recapturing Wages Positive Aspects of Jobs The Power of Inequality Where the Free Market Fails: Externalities Creating a Virtual Job Smoothing the Business Cycle and Reducing Economic Risk The Market Economy of the Future An International View Transitioning to the New Model Keynesian Grandchildren Transition in the Tunnel Chapter 5: The Green Light Attacking Poverty Fundamental Economic Constraints Removing the Constraints The Evolution toward Consumption The Green Light Appendix / Final Thoughts Are the ideas presented in this book WRONG?

Power and Progress: Our Thousand-Year Struggle Over Technology and Prosperity
by Daron Acemoglu and Simon Johnson
Published 15 May 2023

The full sentence reads: “We, the people, ought to be made sensible, that it is not in breaking the laws of commerce, which are the laws of nature, and consequently the laws of God, that we are to place our hope of softening the Divine displeasure to remove any calamity under which we suffer, or which hangs over us.” “The fact is, that monopoly…” is from Thelwall (1796, 21), and a partial version is in Thompson (1966, 185). Chapter 1: Control over Technology It is useful to briefly review the historical debates surrounding the notion of technological unemployment and David Ricardo’s views on machinery, which are discussed in this chapter. The idea of technological unemployment resulting from improvements in production methods is often attributed to John Maynard Keynes (1930 [1966]). In reality, this idea significantly predates Keynes. Several authors in the eighteenth century worried about labor-displacing technological change.

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He also followed the statement we provide in the text with this line: “But this is only a temporary phase of maladjustment. All this means in the long-run that mankind is solving its economic problem” (364, italics in original). Despite Keynes’s stature in the profession, his views on technological unemployment, like those of Ricardo before him, did not have a major impact on the mainstream. Paul Douglas (1930a, 1930b) discussed technological unemployment independently of Keynes, at the same time or even before him. But Douglas, like Gottfried Haberler (1932), argued that the market mechanism would almost automatically restore employment even if machinery displaced some workers from their jobs.

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“Ideology and Early English Working-Class History: Edward Thompson and His Critics.” Social History 1, no. 2: 219‒238. Dorn, David. 2009. Essays on Inequality, Spatial Interaction, and the Demand for Skills. PhD diss., University of St. Gallen. Douglas, Paul H. 1930a. “Technological Unemployment.” American Federationist 37, no. 8 (August): 923‒950. Douglas, Paul H. 1930b. “Technological Unemployment: Measurement of Elasticity of Demand as a Basis of Prediction of Labor Displacement.” Bulletin of Taylor Society 15, no. 6: 254‒270. Drandakis, E. M., and Edmund Phelps. 1966. “A Model of Induced Invention, Growth and Distribution.” Economic Journal 76:823‒840.

The Glass Cage: Automation and Us
by Nicholas Carr
Published 28 Sep 2014

Although Brynjolfsson and McAfee were anything but technophobes—they remained “hugely optimistic” about the ability of computers and robots to boost productivity and improve people’s lives over the long run—they made a strong case that technological unemployment was real, that it had become pervasive, and that it would likely get much worse. Human beings, they warned, were losing the race against the machine.24 Their ebook was like a match thrown onto a dry field. It sparked a vigorous and sometimes caustic debate among economists, a debate that soon drew the attention of journalists. The phrase “technological unemployment,” which had faded from use after the Great Depression, took a new grip on the public mind. At the start of 2013, the TV news program 60 Minutes ran a segment, called “March of the Machines,” that examined how businesses were using new technologies in place of workers at warehouses, hospitals, law firms, and manufacturing plants.

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The more we saw machines as our foes, the more we yearned for them to be our friends. “We are being afflicted,” wrote the great British economist John Maynard Keynes in 1930, “with a new disease of which some readers may not yet have heard the name, but of which they will hear a great deal in the years to come—namely, technological unemployment.” The ability of machines to take over jobs had outpaced the economy’s ability to create valuable new work for people to do. But the problem, Keynes assured his readers, was merely a symptom of “a temporary phase of maladjustment.” Growth and prosperity would return. Per-capita income would rise.

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The drum-like rhythm marches forward, giving the stirring conclusion—“back to work”—an air of inevitability. To those listening, Kennedy’s words must have sounded like the end of the story. But they weren’t. They were the end of one chapter, and a new chapter had already begun. WORRIES ABOUT technological unemployment have been on the rise again, particularly in the United States. The recession of the early 1990s, which saw exalted U.S. companies such as General Motors, IBM, and Boeing fire tens of thousands of workers in massive “restructurings,” prompted fears that new technologies, particularly cheap computers and clever software, were about to wipe out middle-class jobs.

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

The resultant economic uncertainty is creating widespread insecurity; this supports calls for a basic income as the only feasible way of restoring economic security, to keep that uncertainty under some form of social control. The Economist has argued that, while a basic income might be the answer if there were mass technological unemployment, there was no need for it yet. ‘The basic income is an answer to a problem that has not yet materialised.’20 However, this presumes that the primary rationale for a basic income is the advent of technological unemployment whereas, as the first chapters of this book have tried to explain, most advocates of basic income justify it on quite other grounds, as a response, albeit partial, to economic insecurity, social injustice and freedom denied.

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The Frankfurt School psychoanalyst Erich Fromm advocated a ‘universal subsistence guarantee’ in a famous 1955 book, The Sane Society, and in a later essay, ‘The Psychological Aspects of the Guaranteed Income’. But the labourist welfare state was then in its ascendancy and his voice and that of others went unheeded. What might be called the third wave came in the 1960s, predominantly in the United States, at a time of rising concern over ‘structural’ and ‘technological’ unemployment. This was famously associated with the 1972 proposal by President Richard Nixon for a Family Assistance Plan, a form of negative income tax. He refused to use the term ‘guaranteed annual income’, and it would be an exaggeration to see Nixon as a convert to the basic income cause. He believed in supporting ‘the working poor’, by which was meant those in low-paid jobs, ignoring the many forms of unpaid work.

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Galbraith, and by sociologists, most notably New York Senator Daniel Patrick Moynihan, who, although a Democrat, had a strong influence on Nixon’s proposed Family Assistance Plan.10 The fourth wave could be said to have started in a quiet way with the establishment of the Basic Income European (now Earth) Network (BIEN) in 1986. After attracting a steady stream of converts, the wave gathered real momentum in the wake of the financial crash of 2007–8. Since then a wide range of economists and commentators have come out in support of some variant or another of basic income, often associated with fears of technological unemployment, growing inequality and high unemployment. Supporters in this fourth wave include: Nobel Prize winners James Buchanan, Herbert Simon, Angus Deaton, Christopher Pissarides and Joseph Stiglitz; academics Tony Atkinson, Robert Skidelsky and Robert Reich, former Secretary of Labour under Bill Clinton; prominent economic journalists Sam Brittan and Martin Wolf; and leading figures in the BIEN movement, such as German sociologist Claus Offe and the Belgian philosopher Philippe van Parijs.

Thinking Machines: The Inside Story of Artificial Intelligence and Our Race to Build the Future
by Luke Dormehl
Published 10 Aug 2016

It was a line from The Simpsons, although it seemed strangely appropriate given what had happened. It read: ‘I for one welcome our new robot overlords.’ A World of Technological Unemployment Ken Jennings’ crack was as neat a summary as you could hope for when it comes to dealing with one of the perceived dark sides of Artificial Intelligence. Forget leather jacket-wearing Austrian robots trying to take over the world, the real imminent threat AI systems pose relate to our jobs. The phrase ‘technological unemployment’ was first coined by a British economist named John Maynard Keynes in 1930. In a speculative essay entitled ‘Economic Possibilities for our Grandchildren’, Keynes predicted that the world was on the brink of a revolution regarding the speed, efficiency and ‘human effort’ involved with a wide variety of industries.

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To do this, he or she used a long stick (usually a bamboo) to tap on the bedroom window of clients; not moving on to the next house until they were positive that the occupant was awake. Needless to say, knocker-ups were permanently disadvantaged when the French inventor Antoine Redier patented an adjustable mechanical alarm clock in 1847. Not all technological unemployment has been quite so obscure as the lonely death of the knocker-up. The economist Gregory Clark has convincingly argued that the working horse was one of the biggest victims of the invention of the internal combustion engine. According to Clark, there were 3.25 million working horses in England in 1901.

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Speaking at an event called the Hixon Symposium on Cerebral Mechanisms in Behavior, at the California Institute of Technology, McCulloch told the assembled audience: As the Industrial Revolution concludes in bigger and better bombs, an intellectual revolution opens with bigger and better robots. The former revolution replaced muscles by energy, and was limited by the law of the conservation of energy, or of mass-energy. The new revolution threatens us, the thinkers, with technological unemployment, for it will replace brains with machines limited by the law that entropy never decreases. These machines, whose evolution competition will compel us to foster, raise the appropriate question: ‘Why is the mind in the head?’ McCulloch’s last point is the most pertinent one. The Industrial Age leaders of industry assumed it was their intelligence that would protect them from technological replacement.

The Future Is Faster Than You Think: How Converging Technologies Are Transforming Business, Industries, and Our Lives
by Peter H. Diamandis and Steven Kotler
Published 28 Jan 2020

If we’re going to make the shift to sustainable at the speed required, then we the people are both the obstacle and the opportunity. Economic Risks: The Threat of Technological Unemployment When it comes to dangers heading our way, the environment gets top billing, but it’s lately been sharing the limelight with automation. Robots and AI, our headlines increasingly declare, are coming for our jobs. In recent years, major consultancies such as McKinsey, Gartner, and Deloitte have all issued reports saying technological unemployment is unavoidable. One Oxford University study found 47 percent of all US jobs are threatened over the next few decades, and that number could be as high as 85 percent in the rest of the world.

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Yet, as human labor costs continue to climb, robots won’t just be coming, they’ll be here, there, and everywhere. It’s going to become increasingly difficult for store owners to justify human workers who call in sick, show up late, and can easily get injured. Robots work 24-7. They never take a day off, never need a bathroom break, health insurance, or family leave. Going forward, this means technological unemployment will become more of an issue—and more on this in Part Three—but in retail, the robotic benefits for both companies and customers are considerable. 3-D Printing and Retail In 2010, Kevin Rustagi was frustrated. So were his friends Aman Advano, Kit Hickey, and Gihan Amarasiriwardena.

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We’ll unpack economic relocations, climate-change migrations, virtual worlds explorations, outer space colonization, and hive-mind collaborations—or the quintet of mass movements that will reshape the demographics of the globe and the nature of society over the next hundred years. We’ll begin by turning our attention to the ongoing water crisis, then expand into climate change and species die-off, before shifting focus to technological unemployment, rogue AIs, and other threats that go bump in the exponential night. Water Woes In 2018, the United Nations Intergovernmental Panel on Climate Change released their “Special Report on Global Warming,” which reached a stark conclusion: We humans have broken the planet. By falling in love with industrial technology and failing to address the environmental devastation it produced, humanity has put the Earth—what Carl Sagan once called, “the only home we have ever known”—on a crash course with disaster.

Surviving AI: The Promise and Peril of Artificial Intelligence
by Calum Chace
Published 28 Jul 2015

Throughout, Surviving AI remains clear and jargon-free, enabling newcomers to the subject to understand why many of today’s most prominent thinkers have felt compelled to speak out publicly about it. David Wood, chair, London Futurists Artificial intelligence is the most important technology of our era. Technological unemployment could force us to adopt an entirely new economic structure, and the creation of superintelligence would be the biggest event in human history. Surviving AI is a first-class introduction to all of this. Brad Feld, co-founder Techstars The promises and perils of machine superintelligence are much debated nowadays.

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It wasn’t and couldn’t have been predicted in advance, but in hindsight what could be more logical than our most powerful technology, AI, becoming available to most of us in the form of a communication device? Thirty years ago we didn’t know how the mobile phone market would develop. Today we don’t know how the digital disruption which is transforming so many industries will evolve over the next thirty years. We don’t know whether technological unemployment will be the result of the automation of jobs by AI, or whether humans will find new jobs in the way we have done since the start of the industrial revolution. What is the equivalent of the smartphone phenomenon for digital disruption and automation? Chances are it will be something different from what most people expect today, but it will look entirely natural and predictable in hindsight.

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The fear that automation would lead to mass unemployment is not new. In 1930, the British economist John Maynard Keynes wrote “We are being afflicted with a new disease of which some readers may not yet have heard the name, but of which they will hear a great deal in the years to come – namely technological unemployment. This means unemployment due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour.” (19) Decades later, in the late 1970s, a powerful BBC Horizon documentary called Now the Chips are Down alerted a new generation to the idea (and showcased some truly appalling ties.) (20) Up to now the replacement of humans by machines has been a gradual process.

Innovation and Its Enemies
by Calestous Juma
Published 20 Mar 2017

Existing copyright laws and practices, despite their long history of evolution and adaptation, failed to protect music creators.19 The loss of employment as a result of technological advances in the recording industry was coined “technological unemployment.” Indeed, “The AFM contends that the unrestricted commercial use of records is detrimental to the employment of musicians. In this respect it has often referred to the problem of ‘technological unemployment,’ pointing to the unilateral reproducibility of the record and to the wide use that may be made of it.”20 With the mass production of records and their substitution for live performances, musicians became displaced and increasingly unemployed.

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The creation of the RIAA marked a significant transition in establishing a support organization for the recording industry. It represented recognition of recording music as a new feature of the economic landscape. Many of the challenges regarding technological unemployment and protection of incumbent interests that the AFM had to address were passed on to the RIAA but in a different age of rapid technological change. Conclusions Anxiety over technological unemployment played a key role in fueling concerns over recorded music. The fear of job displacement remains one of the most important sources of concern over new technologies. Although much of the anxiety is overstated, the threat of job dislocation is often real.

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Many musicians were receptive to the limitations and benefits of technology and created their records accordingly. The recording limitations began to filter into stage performance. Musicians were restricted to three-minute songs in the recording studio and they soon kept their songs to that length on stage too. Playing Second Fiddle Technological unemployment is one of the most potent sources of innovation resistance. As the economic historian Joel Mokyr writes, “New knowledge displaces existing skills and threatens rents: technological change leads to substantial losses sustained by those who own specific assets dedicated to the existing technology.”18 If we apply this statement to music, it is evident that the surge of recording technologies led to job losses for live musicians.

Robots Will Steal Your Job, But That's OK: How to Survive the Economic Collapse and Be Happy
by Pistono, Federico
Published 14 Oct 2012

I noticed that often people tend to fall for this kind logical fallacy. If you can find one example of a person that cannot be replaced by machines, then the argument of technological unemployment is invalid. On the contrary, I would argue that if you have to rely on that single special example to present your argument in favour of humans, you have just proved my point. That the average person within that job type is bound to fall victim to technological unemployment. Now imagine if a few big players (Google, Amazon.com), that are collecting millions of terabytes of personal information about our reading habits, decide to enter the market of automated journalism.

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Thanks to the ingenuity of the human mind and the need for growth, markets always find a way, especially in the ever-connected and globalised mass market we live in today. In this book I will try to avoid picking either side based on belief, gut feeling, or hunch. Rather, I will attempt to create an informed logical reasoning, based on the evidence that we have so far. The book is divided into three parts. First, we will explore the topic of technological unemployment, and its impact on work and society – I chose to focus on the US economy, but the same line of argument works for most the industrialised world. In the second part we will look into the nature of work itself, and the relationship between work and happiness. The last part is a bold attempt to provide some practical suggestions on how to deal with the issues presented in the first two parts.

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His 2009 book The Lights in the Tunnel: Automation, Accelerating Technology and the Economy of the Future aims to show how automation will inevitably lead to structural unemployment, and millions of people, both skilled and unskilled workers, will soon find themselves out of the workforce, with little to no chance of getting back in. Ford has since written many articles on major news websites, thereby bringing the issue of technological unemployment back into the public eye. He has also been a source of inspiration to me, when I decided to write this book. However, just as with Brynjolfsson’s book, I do not think his solutions are feasible; nor, in most cases, desirable. I think all of these authors have identified a real problem, and they tried to propose solutions to that problem using their knowledge, skills, analysis, and background.

The Innovation Illusion: How So Little Is Created by So Many Working So Hard
by Fredrik Erixon and Bjorn Weigel
Published 3 Oct 2016

Harking back to Marx’s “reserve army of the unemployed” – the theory that real wages cannot grow or follow productivity49 – some now claim that while productivity has increased, jobs and wages have not, or that the age-old correlation between productivity and wages has turned against the interests of labor. The decoupling thesis is an old myth that has refused to go away. It tends to emerge when unemployment is exceptionally high – and now, when merged with the thesis of an innovation revolution, it has raised the fear of technological unemployment to new heights. The modern version of decoupling is specious, to say the least. It requires a considerable leap of the imagination to claim that the corporate sector has been thriving on shrinking or slow-growing labor income over the past decades. While there is a postcrisis trend of unusually high profit margins in some countries, the long-term trend for the US, the UK, France, Italy, Belgium, and other advanced economies is stable, prone to mean reversion, and not exactly ammunition for the Marxian view of capital using and abusing labor.50 Even in Germany, where profit margins accelerated remarkably fast in the decade leading up to 2005, there has lately been a corrective return to the mean.

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This may seem like an extreme example, but the thrust of serious analysis suggests that productivity growth does not decrease demand for labor and that the relationship between productivity and unemployment is trivial. Productivity growth, however, changes the composition of labor. Naturally, productivity growth and innovation can lead to capital substituting for labor, and it is generally acknowledged that economies have technological unemployment. Yet such employment tends to be short term. Productivity growth creates more output, and unless there are serious distortions in the economy, it leads to a greater demand sucking up unutilized labor, and in the aggregate, productivity and employment tend to follow each other. At that level, there is no total economy trade-off between labor and productivity, even if companies and industries can face that choice.55 A study by the McKinsey Global Institute, a chiffrephile agent in the world of management consultants, brings home that point about short- and long-term effects.

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What is more, some used the example to paint a picture of the Chinese manufacturing sector, poisoning the climate with record levels of carbon emissions but not with the legitimate excuse of raising welfare through industrialization. Martin Ford’s prediction seemed prescient: “The greatest risk is that we could face a ‘perfect storm’ – a situation where technological unemployment and environmental impact unfold roughly in parallel, reinforcing and perhaps even amplifying each other.”78 Gou was serious about Foxconn’s future in the world of robots. Foxconn had developed a “Foxbot” in 2007, and the shift followed the transition of China’s economy into the higher echelons of the value chain.

Bourgeois Dignity: Why Economics Can't Explain the Modern World
by Deirdre N. McCloskey
Published 15 Nov 2011

R., 601 James, Clive, 235; tuberculosis and despair, 9, 10 James, Henry: business, 590 James VI & I, 112, 177, 336 Japan: and England in eighteenth century, 481; imperialism, resource based, 482; jinkaku, dignity, xiv; Tokugawa, and economy, 482 Jardine, Lisa: on Bacon, 677n14 Jaume, Lucien: general interest, 338; on Robert de Lamennais, 682n9; quotes Taveneaux, 682n8 Jaworski, Taylor: property without kings, 112 Jensen, Hans Siggaard: acknowledged, xxxix; windmills, 659n22 Jews: and anti–trade, 303, 600; dignity in Europe, 406; Dutch, 346; English, 307, 346; Hasidim, 385; The Jew of Malta, 305, 307; Khrushchev on, 541; Mokyr on innovation among, 427–428; outsider success, 479; Poland, 347 job protection, 74, 539; and building codes, 625; effect on poor, 74; Epstein on, 206; leftist, 544; of middle class and middle aged, 575; for non-youth, 54; Reich on, 40; Reich productionist, 41; in South Africa, 606; and technological unemployment, 57; and Walmart, 619 jobs: competition among, equalizing, 33; and consumers, 619; Cowen on technological loss of, 62; created, 62; racial discrimination in, 48, 509; as slots, xxxiii, 63; Smith on preserving, 464; sweatshop, 572; and sweet talk, 491, 496. See also job protection; Reich, Robert; technological unemployment; wage slavery Jobs, Steve: creative destruction, 362 Johansson, Sheila, 517 Johns Hopkins: on Harvard College, 679n15 Johnson, Noel: acknowledged, xxxviii Johnson, Samuel, 87, 151, chap. 17; quotes Addison, 673n15 John XXII, Pope: and medieval communism, 383, 451–452 Jones, Barbara, 95 Jones, Eric, 279, 280; Arabic numerals, 322; on culture, 693n1; English guilds, 414; fragmentation, 396; timing of Great Enrichment, 534 Jönsson, Sten: appropriate banker, 541–542; on heritability, 695n6 Jorde, L.

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Some students of the economy, such as Robert Gordon, Lawrence Summers, Erik Brynjolfsson, Andrew McFee, Edmund Phelps, Edward E. Gordon, Jeffrey Sachs, Laurence Kotlikoff, and Tyler Cowen, have argued recently that countries in the position of the United States, on the frontier of betterment, are facing a slowdown, with a skill shortage, and that technological unemployment will be the result.1 Maybe. The economists would acknowledge that in the past couple of centuries numerous other learned commentators have predicted similar slowdowns—such as the Keynesian economists in the late 1930s and the 1940s, confident in their theory of “stagnationism”—only to find their predictions once again falsified by the continuing Great Enrichment.2 The classical economists of the first three-quarters of the nineteenth century, Marx included, expected landlords, or in Marx’s case capitalists, to engorge the national product.

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But soon. Tyler Cowen, for example, an economist I admire, spends many pages of his recent book Average Is Over (2013) describing breathlessly “the increasing productivity of intelligent machines,” such as those used for dating services. Your fate is determined, he says, by how you answer the technological-unemployment question: “Are you good at working with intelligent machines or not? . . . This is the wave that will lift or that will dump you.”4 He concedes that “it was true in the great Industrial Revolution of the nineteenth century and it is true now: machines do not put us all out of work, as eventually machines will create jobs.”5 I italicize the words amazing in an economist of Cowen’s ability.

Humans as a Service: The Promise and Perils of Work in the Gig Economy
by Jeremias Prassl
Published 7 May 2018

In the short term, however, ‘the very rapidity of these changes is hurting us and bringing difficult problems to solve’:1 We are being afflicted with a new disease of which some readers may not yet have heard the name, but of which they will hear a great deal in the years to come—namely, technological unemployment. This means unemployment due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour.2 Similar fears have been voiced throughout the past century. President Kennedy, for example, regarded maintaining full employment ‘as the major domestic challenge, really, of the ’60s . . . when automation, of course, is replacing men’.3 Reality, however, couldn’t be further from vision of ‘three-hour shifts or a fifteen-hour week’.4 What happened?

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Technology makes us more productive, reducing prices and raising real income. As we become better off, our appetite for more products and services creates new job opportunities in emerging industries: think of the miner retrained as a computer engineer. Over the past few years, the spectre of technological unemployment has nonetheless returned to haunt us: whether it’s the rise of artificial intelli- gence or the advent of self-driving cars, the robots are said to be coming for Humans as a Service: The Promise and Perils of Work in the Gig Economy. First Edition. Jeremias Prassl. © Jeremias Prassl 2018.

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As Professor Cynthia Estlund puts it: ‘Automation is an entirely lawful—indeed, almost unassailable—way to avoid the costs of employing people.’8 The cost of employment protection, she argues, will be felt particularly harshly by low-income workers: ‘Especially at the bottom of the labor market, raising the floor on wages, benefits, and working condi- tions strengthens the business case for automation of technically automata- ble jobs.’9 This is correct as a matter of labour economics—as long as jobs are automatable. The extent to which machine learning can grapple with plat- form-based work, however, is much more contested than some authors would have us think. Upon closer inspection, it is not at all clear to what extent the latest wave of technological unemployment will affect the gig economy. The Limits of Automation Automation does have huge impacts on the labour market—not least in terms of accentuating income inequality. But is it really a looming threat to the low-skill, low-wage work characteristic of many gig-economy plat- forms? There are good reasons to doubt claims that the rise of the robots * * * 138 Epilogue will spell the end of the gig economy.

Rise of the Robots: Technology and the Threat of a Jobless Future
by Martin Ford
Published 4 May 2015

However, as we’ll see, many of these assumptions rest on uncertain foundations: the story is sure to be far more complicated. Indeed, the frightening reality is that if we don’t recognize and adapt to the implications of advancing technology, we may face the prospect of a “perfect storm” where the impacts from soaring inequality, technological unemployment, and climate change unfold roughly in parallel, and in some ways amplify and reinforce each other. In Silicon Valley the phrase “disruptive technology” is tossed around on a casual basis. No one doubts that technology has the power to devastate entire industries and upend specific sectors of the economy and job market.

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A 2010 report authored by Barry Bluestone and Mark Melnik of Northeastern University predicts that by 2018, there may be as many as 5 million unfilled jobs in the United States as a direct result of the graying workforce and that “30 to 40 percent of all projected additional jobs in the social sector”—which the authors define as including areas like health care, education, community service, arts, and government—could “go begging unless older workers move into them and make them their encore careers.”26 This is obviously a prediction very much at odds with the argument I’ve been putting forth in these pages. So which vision of the future is correct? Are we headed toward widespread technological unemployment and even more inequality, or will wages finally begin to rise again as employers scramble to find working-age people to fill available jobs? The impact of retiring workers in the United States is fairly mild compared to the genuine demographic crises faced by many other advanced countries, especially Japan.

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In the next chapter, we’ll take a balanced look at some of these truly advanced, and far more speculative, technologies. It may well be that these breakthroughs will remain science fiction for the foreseeable future—but if they are ultimately realized, that would dramatically amplify the risk of soaring technological unemployment and income inequality, and perhaps lead to scenarios even more dangerous than the economic risks we’ve focused on so far. * Not all robots are used in production, of course. There are also consumer robots. Suppose you someday own a personal robot, capable of doing things around the house.

How to Fix the Future: Staying Human in the Digital Age
by Andrew Keen
Published 1 Mar 2018

But over the last few years, as the zeitgeist has zigged from optimism to pessimism about our technological future, more and more pundits have joined our ranks. Now everyone, it seems, is penning polemics against surveillance capitalism, big data monopolists, the ignorance of the online crowd, juvenile Silicon Valley billionaires, fake news, antisocial social networks, mass technological unemployment, digital addiction, and the existential risk of smart algorithms. The world has caught up with my arguments. Nobody calls me the Antichrist anymore. Timing—as I know all too well from my day job as a serial entrepreneur of mostly ill-timed start-ups—is everything. Having written three books exposing the dark side of the digital revolution, I think the time is now right for something more positive.

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“Taking drivers out of the equation would also increase the company’s profits: Self-driving cars give Uber 100 percent of the fare, the company would no longer have to subsidize driver pay and the cars can run nearly 24 hours a day.”58 And, as you’ll remember, the Columbia University economist Jeffrey Sachs warns us that there is now an urgency to the issue of technological unemployment, not just in transportation, but throughout every sector of the economy. So what should we do when private superpowers like Uber make 100 percent of their profit by replacing their 1.5 million drivers with smart machines? How can we fix a future in which algorithms replace not only vast swatches of the manual labor force, but also skilled workers like lawyers, doctors, and engineers?

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Five hundred years after the publication of Utopia, More’s Renaissance humanism—with its focus on realizing the “happiness of life,” is back in vogue. It never went away completely, of course. In the nineteenth century, a youthful Karl Marx kept it alive. Today, however, rather than Utopia or communism, it now goes under the name of “universal basic income.” This is the idea that, in our age of rising technological unemployment and inequality, the government will give all its citizens—rich and poor, young and old, male and female alike—a living wage whether or not they have a job. “Money for Nothing” one headline about universal basic income thus says.4 “Sighing for Paradise to Come” declares another about the future as a cornucopia of “technological abundance in which paid work is optional and no one goes without.”5 Paradise or not, everyone today, it seems, both inside and outside Silicon Valley, is talking about universal basic income as the fix to the looming joblessness crisis of our smart machine age in which we will all become members of what Yuval Noah Harari calls the “useless class.”6 Its many proponents include libertarian technologists like the Y Combinator CEO Sam Altman, who is funding a trial in Oakland around it, as well as more traditional progressives such as the American labor organizer Andy Stern, the former president of the Service Employees International Union, who has written a book in favor of its implementation in the United States.7 Local and national governments all over the globe—from Canada and Finland to Brazil, Holland, and Switzerland—are experimenting with referendums or pilot projects to reinvent the social security systems of the industrial age.

Made to Break: Technology and Obsolescence in America
by Giles Slade
Published 14 Apr 2006

The explicit purpose of these machines, which proliferated after 1928, was to replace human sales clerks. In 1932 Billboard magazine recorded that such machines give “the appearance of taking away jobs from people who might work.”24 That same year, Fortune published an anonymous essay condemning the “technological unemployment”that had led to “a serious decline in the number of wage earners in basic industries.” This essay marked the firs time that “obsolescence” was used to describe the social reality that human workers could be replaced by machines. “Obsolete Men”—like Jonathan Swift’s A Modest Proposal—contained bitter satire: “For some two or three millions of years the world’s work was done by a patent, automatic, self-cooling mechanism of levers, joints and complicated controls with a maximum life of about three score years and ten, an average effici nt working day of eight to twelve hours, an intermittent power production of one-tenth of one horsepower, and certain vernal vagaries for which there was no adequate explanation in the laws of physics . . .

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The crisis of the Depression required that society be restructured by engineers and economists around the principle of production for the use and prosperity of the many, rather than the profi of the few.33 Most of the utopian plans—technocratic or otherwise—that emerged during that troubled year of 1932 spoke of the need for a body of experts who would restructure society so as to achieve a balance between supply and demand.Such a balance would eliminate technological unemployment. But to the ears of America’s business community, what technocrats advocated in a variety of pamphlets like the Continental Committee’s Plan of Plenty began to sound genuinely threatening. Herbert Hoover’s defeat in the November 1932 elections and Roosevelt’s loud promise of something called “a New Deal” already had them feeling vulnerable.

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THE BUSINESSMAN’S UTOPIA Like technocracy, “planned obsolescence” was conceived during the desperate year of 1932. And in its early incarnation, it too focused on restructuring society around a body of experts whose mandate was to achieve an equilibrium of supply and demand that would eliminate technological unemployment. Unlike technocracy, however, planned obsolescence was not a movement. It was the idea of one man, a successful Manhattan real estate broker by the name of Bernard London. London lived well south of Columbia University, on elegant Central Park West, but his extensive contacts in Manhattan’s architectural, Jewish, Masonic, and academic communities may have included early members of the technocracy group.35 All we really know about him is that he began his career as a builder in Russia.

Inventing the Future: Postcapitalism and a World Without Work
by Nick Srnicek and Alex Williams
Published 1 Oct 2015

In a third situation, labour-saving technologies can be of such general use that they diffuse across the entire economy, dampening the overall demand for labour.24 In this circumstance, even if new industries are created, they will require increasingly less labour because these technologies have a wide range of applicability.25 If any of the above conditions hold, then technological change can lead to increased unemployment. As we will see, there are good reasons to believe a number of these conditions do hold. But while technological unemployment is the most prominent reason today for swelling surplus populations, it is not the only one. Another mechanism that actively changes the size of the surplus is one we have already noted: primitive accumulation.26 This is not just an origin story of capitalism, but also an ongoing process that involves the transformation of pre-capitalist subsistence economies into capitalist economies.

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The apogee of this approach was the postwar period, when working-class struggle and conservative concern with social order positioned full employment as a necessary economic goal.119 In this brief ‘golden age’ of capitalism, unemployment was kept to a minimum, and capital had to seek out pre-capitalist populations around the world in order to expand and accumulate.120 For the most part, job growth was achieved through healthy economic growth that increased the demand for labour.121 Historically, growth of the national economy has often been important in warding off the effects of technological unemployment – either by increasing the output of existing industries or by inventing new industries to employ the displaced workers. For instance, during the latter half of the 1800s, the rise in capital goods output created jobs that offset the surplus population newly released from the agricultural sector.122 In the prewar and postwar eras, growth in manufacturing jobs was sustained by the rise of mass consumerism and surges in government military spending.123 Today, we can see similar attempts at creating new markets through accumulation by dispossession – turning public or common goods into privatised (and monetised) commodities.

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What is needed, therefore, is a counter-hegemonic approach to work: a project that would overturn existing ideas about the necessity and desirability of work, and the imposition of suffering as a basis for remuneration. The media is already changing the conditions of possibility – positioning UBI as not only a possible solution, but increasingly as a necessary solution to problems of technological unemployment. These hegemonic trends should be amplified. The dominance of the work ethic also runs up against the changing material basis of the economy. Capitalism demands that people work in order to make a living, yet it is increasingly unable to generate enough jobs. The tensions between the value accorded to the work ethic and these material changes will only heighten the potential for transformation of the system.

Utopias: A Brief History From Ancient Writings to Virtual Communities
by Howard P. Segal
Published 20 May 2012

During the Great Depression of the 1930s, for the first time in American history the public held inventors, engineers, and scientists responsible for economic bad times as greedy industrialists— most notably, President Herbert Hoover, a distinguished mining The American Utopias and Utopians and Their Critics 83 engineer before he entered politics. Nevertheless, the very machinery that had helped to create “technological unemployment” was almost never smashed by laid-off workers. Not wishing to oppose technological progress—and in so doing risk being scorned as “un-American”—workers and their union leaders have traditionally sought only their fair share of economic benefits from mechanization and reduced costs of production, or, as necessary, unemployment insurance or retraining assistance.

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Hobsbawm, “The Machine Breakers,” in Labouring Men: Studies in the History of Labour (London: Weidenfeld and Nicolson, 1964), 5–22; Malcolm I. Thomis, The Luddites: Machine Breaking in Regency England (New York: Schocken, 1972); and Brian J. Bailey, The Luddite Rebellion (New York: New York University Press, 1998). 12 See Amy Sue Bix, Inventing Ourselves Out of Jobs? America’s Debate Over Technological Unemployment, 1929–1981 (Baltimore, MD: Johns Hopkins University Press, 2000). 13 On the opportunity to purchase the Unabomber’s plot of land— minus the cabin—see Michael E. Altman, “Unabomber’s Secluded Plot of Land for Sale,” Harvard Crimson, December 6, 2010, http:// www.thecrimson.com/article/2010/12/6/harvard-kaczynski-currently-plot.

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Bedford, Henry F., Seabrook Station: Citizen Politics and Nuclear Power (Amherst, MA: University of Massachusetts Press, 1990). Bess, Michale, The Light-Green Society: Ecology and Technological Modernity in France, 1960–2000 (Chicago, IL: University of Chicago Press, 2003). Bix, Amy Sue, Inventing Ourselves Out of Jobs? America’s Debate Over Technological Unemployment, 1929–1981 (Baltimore, MD: Johns Hopkins University Press, 2000). Brown, Valerie A., John A. Harris, and Jacqueline Y. Russell, eds., Tackling Wicked Problems: Through the Transdisciplinary Imagination (Washington and London: Earthscan/James and James, 2010). Bueno de Mesquita, Bruce, The Predictioneer’s Game: Using the Logic of Brazen Self-Interest to See and Shape the Future (New York: Random House, 2009).

MegaThreats: Ten Dangerous Trends That Imperil Our Future, and How to Survive Them
by Nouriel Roubini
Published 17 Oct 2022

In Japan, where the average worker is older than elsewhere in the industrial world, the solution to aging is not migration. Instead, Japanese employers have accelerated the move toward robotics and automation. Employers worldwide are likely to go the same route, putting algorithms to work instead of humans. Workers from abroad competing for fewer jobs—as technological unemployment surges—will exacerbate the backlash against immigration. Indeed, the migration policies of the Biden administration have ended up being not very different from those of the nativist Trump administration: faced with an influx of economic, climate, and political refugees from Central America, Biden ended up restricting entry into the United States.

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“Capitalist production,” he warned, “develops technology, and the combining together of various processes into a social whole, only by sapping the original sources of all wealth—the soil and the laborer.”27 In 1930, John Maynard Keynes contemplated “Economic Possibilities for Our Grandchildren”: We are being afflicted with a new disease of which some readers may not yet have heard the name, but of which they will hear a great deal in the years to come—namely, technological unemployment. This means unemployment due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour.28 Keynes foresaw only “a temporary phase of maladjustment.” He was largely correct, at least until now. “All this means in the long run that mankind is solving its economic problem,” he wrote.

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Tesla founder Elon Musk welcomes AI that controls electric cars his company makes, but putting AI in ultimate charge worries him. “It’s fine if you’ve got Marcus Aurelius as the emperor,” Musk told The Economist, “but not so good if you have Caligula.”44 No one knows how long it will take for severe structural technological unemployment to make most workers irrelevant. But even the interim looks rocky, prone to negative demand shocks. All signs indicate that AI alternatives will drive down wages and salaries, and that downward drive affects a problem that is already festering. As people earn less, inequality will grow.

Human Compatible: Artificial Intelligence and the Problem of Control
by Stuart Russell
Published 7 Oct 2019

Research centers are springing up all over the world to understand what is likely to happen.16 The titles of Martin Ford’s Rise of the Robots: Technology and the Threat of a Jobless Future17 and Calum Chace’s The Economic Singularity: Artificial Intelligence and the Death of Capitalism18 do a pretty good job of summarizing the concern. Although, as will soon become evident, I am by no means qualified to opine on what is essentially a matter for economists,19 I suspect that the issue is too important to leave entirely to them. The issue of technological unemployment was brought to the fore in a famous article, “Economic Possibilities for Our Grandchildren,” by John Maynard Keynes. He wrote the article in 1930, when the Great Depression had created mass unemployment in Britain, but the topic has a much longer history. Aristotle, in Book I of his Politics, presents the main point quite clearly: For if every instrument could accomplish its own work, obeying or anticipating the will of others . . . if, in like manner, the shuttle would weave and the plectrum touch the lyre without a hand to guide them, chief workmen would not want servants, nor masters slaves.

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Other leading economists have also sounded the alarm, including Nobel laureates Robert Shiller, Mike Spence, and Paul Krugman; Klaus Schwab, head of the World Economic Forum; and Larry Summers, former chief economist of the World Bank and Treasury secretary under President Bill Clinton. Those arguing against the notion of technological unemployment often point to bank tellers, whose work can be done in part by ATMs, and retail cashiers, whose work is sped up by barcodes and RFID tags on merchandise. It is often claimed that these occupations are growing because of technology. Indeed, the number of tellers in the United States roughly doubled from 1970 to 2010, although it should be noted that the US population grew by 50 percent and the financial sector by over 400 percent in the same period,22 so it is difficult to attribute all, or perhaps any, of the employment growth to ATMs.

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Examples of research centers studying the impact of technology on employment are the Work and Intelligent Tools and Systems group at Berkeley, the Future of Work and Workers project at the Center for Advanced Study in the Behavioral Sciences at Stanford, and the Future of Work Initiative at Carnegie Mellon University. 17. A pessimistic take on future technological unemployment: Martin Ford, Rise of the Robots: Technology and the Threat of a Jobless Future (Basic Books, 2015). 18. Calum Chace, The Economic Singularity: Artificial Intelligence and the Death of Capitalism (Three Cs, 2016). 19. For an excellent collection of essays, see Ajay Agrawal, Joshua Gans, and Avi Goldfarb, eds., The Economics of Artificial Intelligence: An Agenda (National Bureau of Economic Research, 2019). 20.

The Coming Wave: Technology, Power, and the Twenty-First Century's Greatest Dilemma
by Mustafa Suleyman
Published 4 Sep 2023

THE AUTOMATION DEBATE In the years since I co-founded DeepMind, no AI policy debate has been given more airtime than the future of work—to the point of oversaturation. Here was the original thesis. In the past, new technologies put people out of work, producing what the economist John Maynard Keynes called “technological unemployment.” In Keynes’s view, this was a good thing, with increasing productivity freeing up time for further innovation and leisure. Examples of tech-related displacement are myriad. The introduction of power looms put old-fashioned weavers out of business; motorcars meant that carriage makers and horse stables were no longer needed; lightbulb factories did great as candlemakers went bust.

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Brian, 56 artificial capable intelligence (ACI), vii, 77–78, 115, 164, 210 artificial general intelligence (AGI) catastrophe scenarios and, 209, 210 chatbots and, 114 DeepMind founding and, 8 defined, vii, 51 gorilla problem and, 115–16 gradual nature of, 75 superintelligence and, 75, 77, 78, 115 yet to come, 73–74 artificial intelligence (AI) aspirations for, 7–8 autonomy and, 114, 115 as basis of coming wave, 55 benefits of, 10–11 catastrophe scenarios and, 208, 209–11 chatbots, 64, 68, 70, 113–14 Chinese development of, 120–21 choke points in, 251 climate change and, 139 consciousness and, 74, 75 contradictions and, 202 costs of, 64, 68 current applications, 61–62 current capabilities of, 8–9 cyberattacks and, 162–63, 166–67 defined, vii early experiments in, 51–54 efficiency of, 68–69 ego and, 140 ethics and, 254 explanation and, 243 future of, 78 future ubiquity of, 284–85 global reach of, 9–10 hallucination problem and, 243 human brain as fixed target, 67–68 hyper-evolution and, 109 invisibility of, 73 limitations of, 73 medical applications, 110 military applications, 104, 165 Modern Turing Test, 76–77, 78, 115, 190, 210 narrow nature of, 73–74 near-term capabilities, 77 omni-use technology and, 111, 130 openness imperative and, 128–29 potential of, 56, 70, 135 as priority, 60 profit motive and, 134, 135, 136 proliferation of, 68–69 protein structure and, 88–89 red teaming and, 246 regulation attempts, 229, 260–61 research unpredictability and, 130 robotics and, 95, 96, 98 safety and, 241, 243–44 scaling hypothesis, 67–68, 74 self-critical culture and, 270 sentience claims, 72, 75 skepticism about, 72, 179 surveillance and, 193–94, 195, 196 synthetic biology and, 89–90, 109 technological unemployment and, 177–81 Turing test, 75 See also coming wave; deep learning; machine learning arXiv, 129 Asilomar principles, 269–70, 272–73 ASML, 251 asymmetrical impact, 105–7, 234 Atlantis, 5 Atmanirbhar Bharat program (India), 125–26 attention, 63 attention maps, 63 audits, 245–48, 267 Aum Shinrikyo, 212–13, 214 authoritarianism, 153, 158–59, 191–96, 216–17 autocomplete, 63 automated drug discovery, 110 automation, 177–81 autonomy, 105, 113–15, 166, 234 Autor, David, 179 al-Awlaki, Anwar, 171 B backpropagation, 59 bad actor empowerment, 165–66, 208, 266 See also terrorism B corps, 258 Bell, Alexander Graham, 31 Benz, Carl, 24, 285 Berg, Paul, 269–70 BGI Group, 122 bias, 69–70, 239–40 Bioforge, 86 Biological Weapons Convention, 241, 263 biotech.

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See disinformation/misinformation Mitchell, Melanie, 73 Model T, 24 Modern Turing Test, 76–77, 78, 115, 190, 210 Mojica, Francisco, 129–30 Montreal Protocol (1987), 45, 263 Moore, Gordon, 32–33, 35 Moore’s Law, 32–33, 67, 81, 108 Motorwagen, 24 Mumford, Lewis, 29, 217 mutually assured destruction, 43 N nanotechnology, 101 narrow path, defined, viii National Laboratory for Quantum Information Sciences (China), 122 nation-state fragility amplifiers, vii, 11 AI and, 166–67 authoritarianism and, 158–59 bad actor empowerment and, 165–66, 168 cyberattacks and, 160–63 democracies and, 158, 185 disinformation and, 169–73 fragility and, 152–54 globalization and, 155–56 inadvertent, 173–77 military applications and, 167–69 power and, 163–64 technological unemployment and, 177–81 nation-states containment and, 143, 159 economic inequality and, 153–54 equilibrium of, 147 functions of, 158 importance of, 151–52 regulation and, 230–31 technology symbiosis with, 156–58 trust and, 152–53 See also geopolitics; governments; nation-state fragility amplifiers Neuralink, 91 neural networks, 59, 64 See also deep learning 1984 (Orwell), 196 Nobel, Alfred, 35 Nordhaus, William, 30–31 North Korea, 44, 161 NotPetya, 161–62, 163 Noyce, Robert, 32 nuclear technology arms race rhetoric and, 126 catastrophe and, 205 containment of, 42–45, 264–65 development of, 41–42 ego and, 141 safety and, 241 NVIDIA, 130, 250, 251 O Odin, 82 offensive vs. defensive capabilities, 157, 234 off-grid living, 198 off switches, 244–45 omni-use technology, 105, 110–12 AI and, 111, 130 containment and, 233 contradictions and, 202 power and, 182 regulation and, 229–30 OpenAI, 62, 64, 69, 251 openness imperative, 127–29 opioids, 36 Oppenheimer, J.

The Fourth Industrial Revolution
by Klaus Schwab
Published 11 Jan 2016

We need, however, to also recognize and manage the negative impacts it can have, particularly with regard to inequality, employment and labour markets. 3.1.2 Employment Despite the potential positive impact of technology on economic growth, it is nonetheless essential to address its possible negative impact, at least in the short term, on the labour market. Fears about the impact of technology on jobs are not new. In 1931, the economist John Maynard Keynes famously warned about widespread technological unemployment “due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour”.22 This proved to be wrong but what if this time it were true? Over the past few years, the debate has been reignited by evidence of computers substituting for a number of jobs, most notably bookkeepers, cashiers and telephone operators.

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There are roughly two opposing camps when it comes to the impact of emerging technologies on the labour market: those who believe in a happy ending – in which workers displaced by technology will find new jobs, and where technology will unleash a new era of prosperity; and those who believe it will lead to a progressive social and political Armageddon by creating technological unemployment on a massive scale. History shows that the outcome is likely to be somewhere in the middle. The question is: What should we do to foster more positive outcomes and help those caught in the transition? It has always been the case that technological innovation destroys some jobs, which it replaces in turn with new ones in a different activity and possibly in another place.

Rule of the Robots: How Artificial Intelligence Will Transform Everything
by Martin Ford
Published 13 Sep 2021

So far, however, history shows that the economy has generally adjusted to advancing technology by creating new employment opportunities and that these new jobs often require more skills and pay higher wages. One of the most extreme historical examples of technologically-induced job losses—and a case study often cited by those who are skeptical that technological unemployment will ever pose a problem—concerns the mechanization of agriculture in the United States. In the late 1800s, about half of American workers were engaged in farming. Today, the number is between one and two percent. The advent of tractors, combine harvesters and other agricultural technology irreversibly vaporized millions of jobs.

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These things are difficult to quantify with economic analysis, but I would argue they alone make artificial intelligence an indispensable tool that we simply cannot afford to leave on the table, even as it comes coupled with unprecedented economic and social risks. The key challenge before us is to find ways to address downsides like technological unemployment and increased inequality while continuing to invest in AI and fully leverage the advantages the technology will bring. The fundamental economic challenge we will face is one of distribution. The potential economic gains associated with artificial intelligence are undeniable, but there is absolutely no guarantee that these benefits will be shared broadly or fairly across the population.

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I hope that some of these experiments might eventually include my idea of incorporating incentives. The data generated through basic income experiments will allow us to craft a program that will scale effectively and help ensure broad-based prosperity in a future shaped increasingly by AI. THE POTENTIAL FOR technological unemployment and increasing inequality is just one of the major concerns that comes coupled with the rise of artificial intelligence. The next two chapters will focus on a range of other dangers that are already becoming apparent or are likely to arise as the technology progresses. Footnote i Our time traveler is based on former Treasury Secretary and Director of the National Economic Council Lawrence Summers, who made the estimate of a quarter to a third of working age men being out of the workforce by 2050 in November 2016.

Work: A History of How We Spend Our Time
by James Suzman
Published 2 Sep 2020

Even more importantly, it is now far from certain whether or not the service sector will be able to accommodate all of those whose work will be determined superfluous to requirements by the next tide of automation, whose waves are already licking against the shores of this last refuge of working men and women in the post-industrial age. 15 The New Disease ‘We are being afflicted with a new disease of which some readers may not yet have heard the name, but of which they will hear a great deal in the years to come – namely, technological unemployment,’ warned John Maynard Keynes when describing his post-work utopia. ‘This means unemployment due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour,’ he added. It was a sensible clarification for his 1930s audience. People had worried about the possibility of their trades or livelihoods being elbowed out by new technologies and ways of working ever since the Industrial Revolution shifted into second gear.

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The rapid expansion of services is also why despite the widespread automation of many once commonplace roles in many countries, from ticket sellers at train stations to checkout attendants in supermarkets, until recently discussion about the potential of automation to cannibalise the workplace remained largely confined to a few technology hubs, corporate boardrooms and academic journals. That all changed in September 2013, when Carl Frey and Michael Osborne from Oxford University published the results of a research project to assess the accuracy of John Maynard Keynes’s predictions about technological unemployment. The reason that the Oxford study caused such a stir was because Frey and Osborne concluded that not only were robots already queuing at the factory gates but that they had fixed their beady little robot-eyes on nearly half of all existing jobs in the United States. Based on a survey of 702 different professions, they reckoned that 47 per cent of all current jobs in the USA had ‘high risk’ of being automated out of existence by as early as 2030.

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Instead it now seems likely that several distinctive Homo sapiens lineages that shared a common ancestor around half a million years ago evolved in parallel with one another, and appeared near-simultaneously around 300,000 years ago in North Africa, southern Africa and the East African Rift Valley, and that all people today are made up of a mosaic of genetic features inherited from all of them. That all changed in September 2013, when Carl Frey and Michael Osborne from Oxford University published the results of a research project to assess the accuracy of John Maynard Keynes’s predictions about technological unemployment. Cooking not only makes meat more palatable; it also vastly extends the range of plant foods that we can eat. Many tubers, stalks, leaves and fruits that are indigestible – or even poisonous – raw are both nutritious and flavoursome when cooked. Eating uncooked nettles, for example, is a recipe for pain.

AI Superpowers: China, Silicon Valley, and the New World Order
by Kai-Fu Lee
Published 14 Sep 2018

It’s a subject that deeply worries many economists, technologists, and futurists, myself included. I believe that as the four waves of AI spread across the global economy, they have the potential to wrench open ever greater economic divides between the haves and have-nots, leading to widespread technological unemployment. As Hao’s story so vividly illustrates, these chasms in wealth and class can morph into something much deeper: economic divisions that tear at the fabric of our society and challenge our sense of human dignity and purpose. Massive productivity gains will come from the automation of profit-generating tasks, but they will also eliminate jobs for huge numbers of workers.

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Over the long term, technological progress never truly leads to an actual reduction in jobs or rise in unemployment. It’s a simple and elegant explanation of the ever-increasing material wealth and relatively stable job markets in the industrialized world. It also serves as a lucid rebuttal to a series of “boy who cried wolf” moments around technological unemployment. Ever since the Industrial Revolution, people have feared that everything from weaving looms to tractors to ATMs will lead to massive job losses. But each time, increasing productivity has paired with the magic of the market to smooth things out. Economists who look to history—and the corporate juggernauts who will profit tremendously from AI—use these examples from the past to dismiss claims of AI-induced unemployment in the future.

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Recently, the idea has captured the imagination of the Silicon Valley elite, with giants of the industry like the prestigious Silicon Valley startup accelerator Y Combinator president Sam Altman and Facebook cofounder Chris Hughes sponsoring research and funding basic income pilot programs. Whereas GMI was initially crafted as a cure for poverty in normal economic times, Silicon Valley’s surging interest in the programs sees them as solutions for widespread technological unemployment due to AI. The bleak predictions of broad unemployment and unrest have put many of the Silicon Valley elite on edge. People who have spent their careers preaching the gospel of disruption appear to have suddenly woken up to the fact that when you disrupt an industry, you also disrupt and displace real human beings within it.

The Big Nine: How the Tech Titans and Their Thinking Machines Could Warp Humanity
by Amy Webb
Published 5 Mar 2019

So in place of coordinated national strategies to build organizational capacity inside the government, to build and strengthen our international alliances, and to prepare our military for the future of warfare, the United States has subjugated AI to the revolving door of politics. Instead of funding basic research into AI, the federal government has effectively outsourced R&D to the commercial sector and the whims of Wall Street. Rather than treating AI as an opportunity for new job creation and growth, American lawmakers see only widespread technological unemployment. In turn they blame US tech giants, when they could invite these companies to participate in the uppermost levels of strategic planning (such as it exists) within the government. Our AI pioneers have no choice but to constantly compete with each other for a trusted, direct connection with you, me, our schools, our hospitals, our cities, and our businesses.

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Yet some choices that once made us uniquely human—like May-December romances or dating someone our parents don’t approve of—are less available to us now. In America, society is beginning to feel uncomfortably Huxleian, as we acquiesce, get married, and have babies with our fellow Apples, or Google Blues, or Amazons. Just as predicted, AI and automation begin to obviate jobs—far more jobs than we’d anticipated. The widespread technological unemployment that had long been on the horizon arrived, but not at all how we’d imagined. We were prepared for unemployed truck drivers, factory workers, and laborers, but our projections were wrong. We kept assuming that robots would take over all the blue-collar jobs, but it turns out that building physical robots capable of doing all that physical labor was a far more difficult task than we’d ever imagined, while cognitive tasks were easier to program and replicate.

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In addition to personal and household PDRs, every business and nonprofit is now registered, too, with an Organization Data Record. Yet scores of people in America and our strategic ally countries are out of work. Without a broad enough social safety net in place, Western economies are in sharp decline, as we have yet to recuperate from waves of unanticipated technological unemployment. This has created vulnerabilities—and a window for Chinese investment. Soon, government leaders are forced to choose between economic viability and democratic ideals—an especially difficult decision for politicians facing reelection and under pressure to solve immediate problems at home.

The New Class War: Saving Democracy From the Metropolitan Elite
by Michael Lind
Published 20 Feb 2020

A “robot tax” has been endorsed by French socialist Benoît Hamon and American capitalist Bill Gates, to fund a UBI as a solution to the as-yet-nonexistent problem of mass technological unemployment. But if robots were cheap and common enough to cause mass unemployment, the commoditized robot industry might not generate enough profit to support a massively expanded welfare state; you might as well try to pay for a universal basic income with a microwave oven tax. If, on the other hand, robots were scarce and selling for a premium, technological unemployment would not be a problem—and the robot tax perversely would encourage the substitution of low-wage workers for advanced machines, putting the Industrial Revolution into reverse.

The State and the Stork: The Population Debate and Policy Making in US History
by Derek S. Hoff
Published 30 May 2012

He was also on shaky ground predicting a constant ratio between the resourceintensive and non-resource-intensive share of national wealth, as the latter was steadily increasing. 79. “U.S. Census Errors Told at Congress,” New York Times, July 31, 1937. 80. A leading participant in the technological unemployment debate was William Ogburn, an eminent sociologist at the University of Chicago firmly entrenched in population circles and a founding officer of the PAA. 81. Amy Sue Bix, Inventing Ourselves Out of Jobs? America’s Debate over Technological Unemployment, 1929–1981 (Baltimore: Johns Hopkins University Press, 2000). 82. Guy Irving Burch, “No Cause for Alarm: An Answer to Dr. Dublin,” Birth Control Review 15 (December 1931): 365. 83.

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A stationary population thus has the advantage over a growing population that it can put more emphasis on producing for itself and less on producing for the future, which should mean more consumption goods per capita and higher living standards.”77 Whelpton acknowledged that a larger population created economies of scale in manufacturing, but he averred that these gains were outweighed by the loss from lower returns and productivity in agriculture.78 Speaking to a reporter at the 1937 World Population Congress in Paris about slowing US population growth, he said, “Most of us agree it is a good thing, leading to a higher standard of living.”79 Whelpton downplayed any link between overpopulation and the de- chapter 3 90 cade’s unprecedented unemployment, but some supporters of a lower population tapped into a broader debate about technologically induced unemployment.80 Shrugging off a discourse from the prosperous 1920s heralding the onset of a technology-based utopia, labor leaders, economists, and producers of popular culture lamented the machine’s alleged displacement of the worker.81 The prospect of reduced technological unemployment thus provided another point in favor of the stable population. Guy Irving Burch, founder of the Population Reference Bureau, a clearinghouse for demographic information as well as a Malthusian, pro–birth control pressure group, concluded, “We don’t need a lot of unskilled labors [sic], because already the invention of labor saving devices is throwing millions out of employment.”82 At times, this argument spilled over into the critique that capitalism demands (or at least capitalist elites insist upon) a surplus of labor to keep wages low.

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Walter Heller labeled the GOP’s tendency to identify structural unemployment a cop-out—another way of saying Americans should simply accept high unemployment (CEA, “A Second Look at Economic Policy in 1961,” March 17, 1961, JFK Papers, President’s Office Files, Staff Memoranda, Box 63A, Folder “Heller, Walter W., 1961”). 20. See Amy Sue Bix, Inventing Ourselves Out of Jobs? America’s Debate over Technological Unemployment, 1929–1981 (Baltimore: Johns Hopkins University Press, 2000), esp. chap. 8; and Henry J. Aaron, Politics and the Professors: The Great Society in Perspective (Washington, D.C.: Brookings Institution, 1978), chap. 4. 21. Bix, Inventing Ourselves Out of Jobs, 255. 22. Ibid., 250–54. 23. For the manpower issue in the 1950s, see Henry David, Manpower Policies for a Democratic Society: The Final Statement of the Council (New York: Columbia University Press for the National Manpower Council, 1965). 24.

A Pelican Introduction Economics: A User's Guide
by Ha-Joon Chang
Published 26 May 2014

It takes time for people to search for new jobs and for companies to find the right people. The result is that some people end up spending some time unemployed in the process. This is known as frictional unemployment. Some skills are not wanted any more: technological unemployment Then there is unemployment due to the mismatch between the types of workers demanded and the available workers. This is usually known as technological unemployment or structural unemployment. This is unemployment that we have seen in movies like Roger and Me, the first movie made by Mike Moore, in which he documents the consequence of the closure of a GM car factory in his town, Flint, Michigan, or in The Full Monty, in which six unemployed steel workers in Sheffield, UK, after a draining period of unemployment, launch themselves as a male stripper group.

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In reality, smooth transitions almost never happen, if you leave things to the market alone. Even with systematic government subsidies and institutional supports for retraining and relocation (e.g., a bridging loan to buy a house where the new job is before the current one is sold), as used in the Scandinavian countries, it is a struggle to eliminate technological unemployment. Governments and unions create unemployment: political unemployment Believing in the modern version of Say’s Law, many Neoclassical economists have argued that, except in the short run, the law of supply and demand ensures that everyone who wants to work will find a job at the going wage rates.

System Error: Where Big Tech Went Wrong and How We Can Reboot
by Rob Reich , Mehran Sahami and Jeremy M. Weinstein
Published 6 Sep 2021

These empirical disagreements mirror the overhyped rhetoric that always seems to accompany a new wave of technological change. In the 1930s, the English economist John Maynard Keynes worried aloud that “we are being afflicted with a new disease of which some readers may not yet have heard the name, but of which they will hear a great deal in the years to come—namely, technological unemployment.” Two decades later, the Harvard economist Wassily Leontief opined, “I do not see that the new industries can employ everybody who wants a job.” But for everyone worried about mass unemployment, there are those with a more optimistic take. Hal Varian, the current chief economist at Google, assessed the potential employment losses from AI as follows: “If ‘displace more jobs’ means ‘eliminate dull, repetitive, and unpleasant work’ the answer would be yes.”

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only 9 percent of jobs are truly threatened: “Automation and Independent Work in a Digital Economy,” Organisation for Economic Co-operation and Development, May 2016, https://www.oecd.org/els/emp/Policy%20brief%20-%20Automation%20and%20Independent%20Work%20in%20a%20Digital%20Economy.pdf. “technological unemployment”: John Maynard Keynes, “Economic Possibilities for Our Grandchildren (1930),” in Essays in Persuasion (New York: W. W. Norton & Company, 1963), 358–83. Harvard economist Wassily Leontief: Charlotte Curtis, “Machines vs. Workers,” New York Times, February 8, 1983, https://www.nytimes.com/1983/02/08/arts/machines-vs-workers.html.

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See also Y Combinator start-up mindset, xxi “Statement on the Purpose of a Corporation” (Business Roundtable), 181 Stiglitz, Joseph, 254 stock options, 26–28 substantive fairness, 92–93 success disasters, 20–21 Sundar Pichai, 64–65 Sundararajan, Arun, 49 Sunflower Movement, Taiwan, 242 supervised data, 85–86 Supreme Court of the United States, 199, 201 surveillance capitalism, 115, 121–22 surveillance society, 151 surveillance technologies, 21, 112, 113–14, 125–26 Swartz, Aaron, xxi–xxvi, 44 Sweeney, Latanya, 130 Swift, Taylor, 111–12 systemic problems in a democracy, 239–43 Taiwan, 242–43, 261–62 Tang, Audrey, 242–43 Taylor, Frederick, and Taylorism, 14 technological innovation overview, 240 balancing the competing values created by, 240–43, 258 Clipper Chip technology, 115–16 deceleration in, 52 democratic resolution of rival values, xxxiii–xxxiv externalities created by, xxvii failure to examine potential societal harm, xxi and governance, 52–53 insider argument for a reflective stance, 254 instant wealth as a priority, xxv–xxvi maximizing benefits while minimizing harms, xiii–xiv, 65 See also algorithmic decision-making; governance; innovation technological unemployment, 174–76 technologists enablers of, xxviii funding for OpenAI’, 234 governing us vs. governing them, xxviii–xxix, 68–69, 257–63 lack of diversity, 17, 41 legislative ignorance of, 66–68 libertarian tendencies, 25, 52, 67 new masters of the universe, 22–23 optimizing facial recognition software, 17 small group of humans make choices for all of us, 11, 25–26 transforming education to create civic-minded technologists, 251 See also optimization mindset technology, 21, 53–59, 169, 174, 237–39 Telecommunications Act (1996), 60, 61, 62 telegraph, 56–57 telephone system, 60 Terman, Frederick, 28–29 terrorist attack, San Bernardino, California, 72 Theranos, xxx Thiel, Peter, 28, 38, 42, 52 Thrun, Sebastian, 154 Time magazine, 30 transparency of algorithmic decisions, 105, 107–9 and control, 134 Facebook Oversight Board, 215–16 requiring internet platforms to disclose information on credibility of sources, 225–26 “Traveling Salesperson Problem” (TSP), 12–13 Triangle Waist Company fire in 1911, 53–55 Trolley Problem, the, 155 truck drivers and trucking industry, 175 Trump, Donald J., xi, 187–88, 215 Tuskegee experiment, xxxi Twitter as digital civic square, 21 leaders surprised by ways the platform could do harm, 254 Trump’s access denied after January 6, 2021, xi–xii, 187–88 See also big tech platforms ultimatum game, 91 unicorns, 37–38, 39, 43 United Kingdom, 165, 218, 254, 260–62 United Nations Development Programme (UNDP), 173 United States Postal Service, 3–4 universal basic income (UBI), 182–84, 185 University College London Jeremy Bentham display, 120–21, 124 unsupervised data, 85 US Air Force Academy, 103 US Capitol assault (Jan. 6, 2021), xi-xii, xxvi, 115, 187, 209, 215, 223 US Census Bureau, 41 US Department of Justice (DOJ), 257 US Federation of Worker Cooperatives, 180 US security forces and message encryption, 128–29 USA PATRIOT Act, 116 user engagement in online platforms, 40 user-centric privacy, 149–50 utilitarianism, 9, 121, 168, 245 Vacca, James, 104–5 values overview, xvii, xxix balancing the competing values created by innovation, 240–43, 258 expressing ourselves in support of each other, 178 free expression, democracy, individual dignity at risk online, 190–91 freedom as, 172–73 goals assessment for evaluating efficiency vs. values, 15–16 replacing governance by big tech with process of deciding, xxix resolving trade-offs between rival values, xxxi–xxxiii, 45 at risk from new, unregulated innovations, 56 of tech leaders as expert rulers, 67–68 See also dignity, fairness, free speech, privacy, safety, security Varian, Hal, 174 venture capital, inequality in distribution of, 41 venture capitalists (VCs), 25–49 ecosystem of, 31–33 funding Soylent, 8 funds as investment vehicles for their LPs, 38–39 hackers and, 28, 52, 68 high value exits, 40–41 increasing numbers of, 39 narrow view of success as white, male, nerd, 41 optimizing from multiple starting points, 43–45 and scalability of businesses, xxviii and Silicon Valley, 17, 26–28 at Stanford showcasing their new companies, 42–45 unicorns, search for, 37–38, 39, 43 Vestager, Margrethe, 252–53, 255 virtual reality, the experience machine, 167–69 Waal, Frans de, 92 Wales, Jimmy, 195 Walker, Darren, 180 Wall Street Journal, 42–43 Warren, Elizabeth, 181, 256 washing machines and laundry, 157–58 watch time metric, 34 Watchdog.net, xxiii Weapons of Math Destruction (O’Neil), 98 Weinberg, Gabriel, 135–36 Weinstein, Jeremy, xv–xvi, 72 Weld, William, 130 Western Union, 57 Westin, Alan, 137–38 WhatsApp, 127–28 Wheeler, Tom, 63, 76 Whitt, Richard, 149 “Why Software Is Eating the World” (Wall Street Journal), 42–43 Wikipedia, 195–96 Wikipedia conference, xxiii–xxiv Wilde, Oscar, 63 winner-take-all, disruption vs. democracy, 51–76 overview, 51–53 democracy and regulation of technology, 68–73 democracy as a guardrail, 73–76 government’s complicity in absence of regulation, 59–63 innovation vs. regulation, 53–59 and Plato’s philosopher kings, 63–68 Wisconsin’s COMPAS system, 88, 98 Wong, Nicole, 40, 254 worker cooperatives, 180 workers’ compensation benefit, 55 workplace safety, 53–54, 55 World Economic Forum 1996, Davos, Switzerland, 25 World Health Organization, 154 World Wide Web, 29, 30.

New Laws of Robotics: Defending Human Expertise in the Age of AI
by Frank Pasquale
Published 14 May 2020

New laws of robotics should be similar, articulating broad principles while delegating specific authority to dedicated regulators with long experience in technical fields.8 NEW LAWS OF ROBOTICS With these goals in mind, four new laws of robotics will be explored and advanced in this book: Robotic systems and AI should complement professionals, not replace them.9 Clashing projections of technological unemployment drive popular discussions of the future of work. Some experts predict that almost every job is destined to be whittled away by technological advance. Others point out roadblocks on the path to automation. The question for policymakers is, Which of these barriers to robotization make sense, and which deserve scrutiny and removal?

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“Success” may even be defined as assistance to professionals knowledgeable and committed enough to know when to trust the machine and when to rely on their own judgment. THE BENEFIT OF COST Technocratic visions of rapid, expansive automation generate a strange tension at the core of contemporary economic policy. When the question of technological unemployment confronts, say, the US Council of Economic Advisors, the World Economic Forum, or the International Monetary Fund, experts sternly warn that tens of millions of jobs are about to be replaced by robots.75 Focused on our role as producers, this is a discussion framed by gloom and urgency.

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For example, technology advisors in the Obama administration hosted high-level workshops on the economic consequences of AI and robotics.47 A common theme among speakers was an insistence that automation is far from matching human capabilities in many areas, and that automation, done well, would require intense investment in fields such as health care and education.48 Yet at the same time, neoliberal progressives were consistently pushing policies to disrupt health care and education, reducing the flow of funds into these sectors, accelerating degree programs, and tightening the budgets of hospitals and other caregiving institutions. Some even explicitly connected this agenda to the alleged need for more military spending (feeding into the arms races mentioned above). Centrists around the world have adopted these policies, as have more conservative parties. In an economy in which technological unemployment is a major threat, one would think they would be thankful for new positions at hospitals, nursing homes, schools, and universities. But too many economists remain conflicted, anxious about maintaining some arbitrary caps on spending in certain sectors while oblivious to unnecessary cost growth in others.49 There is nothing intrinsically more rewarding about working an assembly line than providing, say, physical therapy or companionship to the injured, disabled, and elderly.

Move Fast and Break Things: How Facebook, Google, and Amazon Cornered Culture and Undermined Democracy
by Jonathan Taplin
Published 17 Apr 2017

Peter Lee, who led the artificial intelligence group at Microsoft Research, vowed to “work toward contributing to an internet that represents the best, not the worst, of humanity.” That might be harder than he thinks. In 1930 the British economist John Maynard Keynes wrote that in the future we would have to worry about “technological unemployment… due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour.” It could be that in the next ten years we will have arrived at the point where Keynes’s prophecy comes true. A 2013 paper by Carl Benedikt Frey and Michael Osborne of Oxford University suggested that 47 percent of US jobs are at high risk of being automated.

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But the New Yorker writer Tad Friend confronted Andreessen with our present reality: “When I brought up the raft of data suggesting that intra-country inequality is in fact increasing, even as it decreases when averaged across the globe—America’s wealth gap is the widest it’s been since the government began measuring it—Andreessen rerouted the conversation, saying that such gaps were ‘a skills problem,’ and that as robots ate the old, boring jobs humanity should simply retool.” Characterizing Keynes’s “technological unemployment” as just a “skills problem” seems shortsighted. The notion that a fifty-year-old autoworker replaced by a robot is going to retrain himself as a software coder and apply for work at Google seems to be a pipe dream that only someone as rich and insulated as Marc Andreessen could conceive.

The War on Normal People: The Truth About America's Disappearing Jobs and Why Universal Basic Income Is Our Future
by Andrew Yang
Published 2 Apr 2018

The fortunate among us have left him behind, but we understand his appeal all too well. He’s still there waiting—ready to take over in case our lives fall apart. FIFTEEN THE SHAPE WE’RE IN/DISINTEGRATION The progress of a few fortunate decades can too easily be swept away by a few years of trouble. —RYAN AVENT The challenges of job loss and technological unemployment are among the most significant faced by our society in history. They are even more daunting than any external enemy because both the enemy and the victims are hard to identify. When a few hundred workers get replaced or a plant closes, the people around them notice and the community suffers.

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Membership in organizations like the PTA, the Red Cross, labor unions, and recreational leagues has declined by between 25 and 50 percent since the 1960s. Even time spent on informal socializing and visiting is down by a similar level. Our social capital has been declining for a long time, and there is no sign of a reversal. All of these things make addressing technological unemployment harder. We no longer believe we’re capable of turning things around without something dramatic changing. Among the things being questioned is our capitalist system. Among young people, polls show a very high degree of sympathy for other types of economies, in part because they’ve witnessed capitalism’s failures and excesses these past years.

How Much Is Enough?: Money and the Good Life
by Robert Skidelsky and Edward Skidelsky
Published 18 Jun 2012

“We are suffering,” he wrote, “not from the rheumatics of old age, but from the growing pains of over-rapid changes, from the painfulness of readjustment between one economic period and another.” The Depression was, at least in part, a symptom of “technological unemployment”—that is, “unemployment due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour.” Technological unemployment pointed to a workless future, but one which was voluntary, not compelled. Keynes deployed economic logic in the service of prophecy. Basing his idea on historical rates of capital accumulation and technical progress, Keynes proposed that if capital equipment continued to grow at 2 percent a year, and “technical efficiency” at 1 percent, “the standard of life in progressive countries one hundred years hence will be between four and eight times as high as it is today.”

The Autonomous Revolution: Reclaiming the Future We’ve Sold to Machines
by William Davidow and Michael Malone
Published 18 Feb 2020

The other correlated parts that have to change to reduce cultural lag are our systems of governance, beliefs, habits, cultural norms, and values. Almost a century ago John Maynard Keynes foresaw many of the economic and cultural challenges we are now facing. Keynes was deeply worried about a new societal dysfunction—technological unemployment (what he called job loss due to automation).6 He knew then, just as we know now, how difficult it would be for people who were threatened by change to adapt to it, and he accurately foresaw the stresses that rapid increases in productivity would exert on our value system. In 1930, in his now-classic article, “Economic Possibilities for Our Grandchildren,” Keynes postulated the end of the Protestant work ethic—one of our most basic values—and imagined a time when the accumulation of wealth would no longer be of high social importance: [T]echnical improvements in manufacture and transport have been proceeding at a greater rate in the last ten years than ever before in history.

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In quite a few years—in our own lifetimes I mean—we may be able to perform all the operations of agriculture, mining, and manufacture with a quarter of the human effort to which we have been accustomed. For the moment the very rapidity of these changes is hurting us and bringing difficult problems to solve…. We are being afflicted with a new disease … namely, technological unemployment…. … I would predict that the standard of life in progressive countries one hundred years hence will be between four and eight times as high as it is to-day…. … This means that the economic problem is not—if we look into the future—the permanent problem of the human race…. The strenuous purposeful money-makers may carry all of us along with them into the lap of economic abundance.

Blood in the Machine: The Origins of the Rebellion Against Big Tech
by Brian Merchant
Published 25 Sep 2023

Philadelphia: Thomas Wardle, 1840. Mueller, Gavin. Breaking Things at Work: The Luddites Were Right about Why You Hate Your Job. London and New York: Verso, 2021. Munger, Mike. “Division of Labor,” EconLib, n.d., www.econlib.org/library/Enc/DivisionofLabor.html. Noble, David. Progress without People: New Technology, Unemployment, and the Message of Resistance. Toronto: Between the Lines, 1995. Noble, David. “Present Tense Technology: Technology’s Politics.” Democracy: A Journal of Political Renewal and Radical Change, vol. 4, no. 2 (1983), 8–24. Oakes, James. Slavery and Freedom: An Interpretation of the Old South.

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“collective bargaining by riot” Eric Hobsbawm, “The Machine Breakers,” Past and Present, no. 1 (February 1952), 57–70; in Eric Hobsbawm, Labouring Men: Studies in the History of Labour (London: Weidenfeld and Nicolson, 1964; Charlottesville: University of Virginia Press, 1965), 5–22. 21. “the present tense” David Noble, Progress without People: New Technology, Unemployment, and the Message of Resistance (Toronto: Between the Lines, 1995). 22. In 1710 Machine-breaking incident recounted in Gravener Henson, The Civil, Political, and Mechanical History of the Framework-Knitters in Europe and America (Nottingham, UK, 1831), 95. 23. “thousands of women dressed in white” From “Honouring Trowbridge Martyr Thomas Helliker at Wreath-Laying,” Wiltshire Times, March 2, 2020.

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Seven of us near your Dwelling House have agreed that if you do not refrain from Your Threshing Machine we will Thresh Your Rick with Fire & Bathe Your Body in Blood.” 4. “of all the machine-breaking movements” Eric Hobsbawm and George Rudé, Captain Swing (London: Lawrence and Wishart, 1969), 460. 5. in “the present tense” David Noble, Progress without People: New Technology, Unemployment, and the Message of Resistance (Toronto: Between the Lines, 1995). 6. “discredited once and for all” Geoffrey Bernstein. Unpublished paper cited by David Noble, “General Ludd and Captain Swing: Machine Breaking as Tactic and Strategy” (1981). 7. There was no natural, united drive toward progress In order to answer for this, the study of political economy sprang forth; as Maxine Berg explains in Machinery Question, the business class “had to find an explanation for the economic and social impact of the machine.

The Classical School
by Callum Williams
Published 19 May 2020

In fact, there is plenty to suggest that Say did not think that capitalist societies were destined to reach full employment eventually. For instance, Say was clearly worried a great deal about what economists today would call “technological unemployment”. That could lead to a steady state, where supply equalled demand, but where a certain class of people were structurally excluded from the economy. The “equality between aggregate supply and demand”, argue Ernesto Screpanti and Stefano Zamagni, “can occur at any employment level”. Say developed his theory of technological unemployment on his trip to England. As Schoorl notes, Say could not help but notice “the great distress of the class of just simply workmen”.

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

Some are utopian, such as the postcapitalism of Paul Mason, imagining an era of free information and information sharing.17 Some are decidedly dystopian, where the robots – or rather their owners – are in control and mass joblessness is coupled with a ‘panopticon’ state subjecting the proles to intrusive surveillance, medicalised therapy and brain control. The pessimists paint a ‘world without work’.18 With every technological revolution there is a scare that machines will cause ‘technological unemployment’. This time, the Jeremiahs seem a majority. Fortunately, we are still in the early stages, when collective action can assert democratic control. Whether or not they will do so in the future, the technologies have not yet produced mass unemployment. 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.

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So, while technology is not necessarily destroying jobs, it is helping to destroy the old income distribution system, creating a rental wedge between profits, which are growing and becoming more concentrated, and wages, which are falling and becoming more volatile and uncertain. The threat is technology-induced inequality, not technological unemployment. THE SECOND GILDED AGE Today, we are living in a Second Gilded Age – with one significant difference. In the first, which ended in the Great Crash of 1929, inequality grew sharply but wages on average rose as well. The Second Gilded Age has also involved growing inequality, but this time real wages on average have stagnated or fallen.

Red Flags: Why Xi's China Is in Jeopardy
by George Magnus
Published 10 Sep 2018

There is a new school of thought that argues that inflation might not pick up because labour shortages won’t happen thanks to the arrival of robots and artificial intelligence that could drive millions of people out of work, contributing to chronic technological unemployment. As a result, we will end up in a low-wage economy in which poverty and income inequality will become widespread. We have never had sustained and large technological unemployment before, though it is hard to be sure about new technologies, which are about the substitution of both brawn and brain. There will undoubtedly be difficult years ahead but I lean towards a less dystopian outcome in which modern technologies will create new jobs and demand for new goods and services, which are no easier for us to identify today than they were for previous generations confronted with their technological challenges.

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

They were protesting against increasing automation, which they claimed was resulting in layoffs and an inhumane increase in what managers expected of workers.3 In other words, we’ve seen the ‘rise of the robots’ before. Anxieties like these usually crop up during periods of rapid technological change. And it’s not just the workers themselves. The economist John Maynard Keynes popularised the idea of ‘technological unemployment’ in 1928, when he noted, ‘The increase of technical efficiency has been taking place faster than we can deal with the problem of labour absorption’ – that is, the ability to find work for workers.4 Now we have entered the Exponential Age, new technology appears to be challenging workers’ raison d’être once again.

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A more open question, however, is what this actually means for workers. The threat of automation looms large in our collective imagination. The rise of newly automated workplaces raises the prospect of mass redundancy. And it is framed as a more existential threat than Keynes’s fears of technological unemployment. Soon, we are told, we’ll reach a point where automated systems will render most of us unemployed and unemployable. In 2016, for example, Geoffrey Hinton – one of the AI pioneers we met earlier – publicly mused on the prospects of radiologists, the specialist doctors who deal with X-rays, computerised tomography and magnetic resonance imaging scans.

21 Lessons for the 21st Century
by Yuval Noah Harari
Published 29 Aug 2018

Minister Hotovely: The Solution Is Greater Israel without Gaza’, Jewish Press, 25 August 2013; ‘Israeli Minister: The Bible Says West Bank Is Ours’, Al Jazeera, 24 February 2017. 11 Katie Reilly, ‘Read Barack Obama’s Final Speech to the United Nations as President’, Time, 20 September 2016. 2. Work 1 Gregory R. Woirol, The Technological Unemployment and Structural Unemployment Debates (Westport, CT: Greenwood Press, 1996), 18–20; Amy Sue Bix, Inventing Ourselves out of Jobs? America’s Debate over Technological Unemployment, 1929–1981 (Baltimore: Johns Hopkins University Press, 2000), 1–8; Joel Mokyr, Chris Vickers and Nicolas L. Ziebarth, ‘The History of Technological Anxiety and the Future of Economic Growth: Is This Time Different?’

Ellul, Jacques-The Technological Society-Vintage Books (1964)
by Unknown
Published 7 Jun 2012

This is an inevitable consequence of tech­ nique. In the crude order of things, these workers are simply thrown out of work. Capitalism is blamed for tlus state of affairs and we are told that technique itself is not responsible for technological unemployment and that the establishment of socialism would set things right. The capitalist replies: “Technological unemployment always dies out of itself. For example, it creates certain new activi­ ties which will in the long run create employment for qualified workers.” This appears to be a dreadful prospect because it implies a readaptation in time and a more or less lengthy period of un­ employment.

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Belgium,348 Bergson, Henri,439 Berlin Institute of Applied Psy­ chology,368 Bertolino, on standardization, ail, Caillois, Roger, 42s calculatingmachine, electronic, 16, 89, 163, 429-30; see also auto­ mation; cybernetics Camichel,Charles, 10,93 Canada: police power in, 103; vitrification process undertaken in, 109 capitalism, 5,53,56,104,144,184, 197, 201, 236, 364, 418; and technical automatism, 81-2; and technological unemployment, 103; use of statistical data re­ stricted by, 169; and norms in economic techniqueof interven­ tion, 172; technique as factor in destruction of, 198, 236-7; state, 245, 247; technique of humanrelationsin, 356 Carnegie, Dale, 341 Cartwright, Edmund, 112 Castelli, Enrico, 329n. Castro, Fidel, ig7 Castro, J. de, 104,107,108 CatotheElder, 36 Caus.

Radical Technologies: The Design of Everyday Life
by Adam Greenfield
Published 29 May 2017

Out of this unwillingness, these people have set out to devise technical systems that are more capable than we are ourselves, along any axis or dimension of evaluation you might care to mention: systems that are stronger and faster than we are; that have finer perception and greater endurance; that never, ever succumb to boredom, fatigue or disgust; and that are capable of operating without human oversight or guidance, indefinitely. We are, of course, talking about using robots and automated systems to replace human labor. The great twentieth-century economist John Maynard Keynes had foreseen much of this early on, coining the expression “technological unemployment” sometime around 1928.1 He saw, with almost clairvoyant perspicacity, that societies might eventually automate away the jobs much of their labor force depended on, and his insight is borne out in recent United States government estimates that an American worker making less than $20 an hour now has an 83 percent chance of losing their job to automation.2 But what Keynes concluded—that the eclipse of human labor by technical systems would necessarily compel a turn toward a full-leisure society—has not come to pass, not even remotely.

…

“Guaranteed Income’s Moment in the Sun,” Remapping Debate, April 24, 2013, remappingdebate.org; Rutger Bregman, “Nixon’s Basic Income Plan,” Jacobin, May 5, 2016. 51.Will Grice, “Finland Plans to Give Every Citizen 800 Euros a Month and Scrap Benefits,” Independent, December 6, 2015; Tracy Brown Hamilton, “The Netherlands’ Upcoming Money-for-Nothing Experiment,” Atlantic, June 21, 2016. 52.John Danaher, “Will Life Be Worth Living in a World Without Work? Technological Unemployment and the Meaning of Life,” Science and Engineering Ethics, forthcoming, philpapers.org/archive/DANWLB.pdf 53.Hannah Arendt, The Human Condition, Chicago: University of Chicago Press, 1958. 54.Amos Zeeberg, “Alienation Is Killing Americans and Japanese,” Nautilus, June 1, 2016. 8Machine learning 1.Rob Kitchin, The Data Revolution: Big Data, Open Data, Data Infrastructures and their Consequences, London: Sage Publications, 2014. 2.Daniel Rosenberg, “Data Before the Fact,” in Lisa Gitelman, ed., “Raw Data” Is an Oxymoron, Cambridge, MA: MIT Press, 2013. 3.These questions are explored in greater depth in the excellent Critical Algorithm Studies reading list maintained by Tarleton Gillespie and Nick Seaver of Microsoft Research’s Social Media Collective: socialmediacollective.org/reading-lists/critical-algorithm-studies. 4.Nick Bostrom, Superintelligence: Paths, Dangers, Strategies, Oxford, UK: Oxford University Press, 2014. 5.For those inclined to dig deeper into such subjects, Andrey Kurenkov’s history of neural networks is fantastic: andreykurenkov.com/writing/a-brief-history-of-neural-nets-and-deep-learning. 6.Alistair Barr, “Google Mistakenly Tags Black People as ‘Gorillas,’ Showing Limits of Algorithms,” Wall Street Journal, July 1, 2015. 7.Aditya Khosla et al., “Novel dataset for Fine-Grained Image Categorization,” First Workshop on Fine-Grained Visual Categorization, IEEE Conference on Computer Vision and Pattern Recognition, 2011, vision.stanford.edu/aditya86/ImageNetDogs; ImageNet, “Large Scale Visual Recognition Challenge 2012,” image-net.org/challenges/LSVRC/2012. 8.David M.

The People vs. Democracy: Why Our Freedom Is in Danger and How to Save It
by Yascha Mounk
Published 15 Feb 2018

The EU and Welfare State Reform in Italy and Spain,” Comparative European Politics 13 (2015): 56–76; Mark Blyth, Austerity: The History of a Dangerous Idea (Oxford: Oxford University Press, 2013), especially ch. 3; and Matt Pickles, “Greek Tragedy for Education Opportunities,” BBC News, September 30, 2015, http://www.bbc.co.uk/news/business-34384671. 10. See Horst Feldmann, “Technological Unemployment in Industrial Countries,” Journal of Evolutionary Economics 23 (2013): 1099–1126. But consider also more skeptical voices, like James E. Bessen, “How Computer Automation Affects Occupations: Technology, Jobs, and Skills,” Law and Economics Research Paper no. 15–49, Boston University School of Law, October 3, 2016, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2690435. For a consideration of a swath of potential policy responses, see Yvonne A. Stevens and Gary E. Marchant, “Policy Solutions to Technological Unemployment,” in Surviving the Machine Age, ed.

The People vs Tech: How the Internet Is Killing Democracy (And How We Save It)
by Jamie Bartlett
Published 4 Apr 2018

I don’t take these predictions all that seriously. Many of these applications are still young. Every new technological revolution unleashes similar speculation, and it is often wide of the mark. Even our wisest heads get it wrong – back in the 1930s John Maynard Keynes believed that the UK was witnessing ‘technological unemployment’, as the ability of machines to take over jobs outpaced the economy’s ability to generate new ones. We’ve had tech-led disruption before, and we have usually found new (and often better) jobs. After all, machines tend to drive up productivity, which in turn stimulates more investment and demand.3 A recent analysis of the American workforce between 1982 and 2012 found that employment grew in several areas where computers were used (gaming, graphic design and programming).4 And in many instances, productivity gains driven by technology won’t mean fewer jobs, but rather improvements in current ones.

Democracy at Work: A Cure for Capitalism
by Richard D. Wolff
Published 1 Oct 2012

The extent to which worker-directors are also rotated through management functions would further differentiate a WSDE-based economy from capitalism. To take a final example, consider that an economic system built upon WSDEs might well be generally concerned about slipping back toward a capitalist system. To that end, it would seek to avoid crises or cycles of the sorts caused in capitalism by overproduction, underconsumption, technological unemployment, and so on. It would work to overcome the social problems created under capitalism when an enterprise discovers a new way to produce output with less labor input, encounters a loss of public desire for its products, or finds that it has overestimated the demand for its output. One way to accomplish this would be to create a fund (by surplus distributions from WSDE boards) and a government agency to administer it.

The Zero Marginal Cost Society: The Internet of Things, the Collaborative Commons, and the Eclipse of Capitalism
by Jeremy Rifkin
Published 31 Mar 2014

They were also dramatically reducing the amount of human labor needed to produce goods and services. Keynes even introduced a new term, which he told his readers, you “will hear a great deal in the years to come—namely, technological unemployment. This means unemployment due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour.” Keynes hastened to add that technological unemployment, while vexing in the short run, is a great boon in the long run because it means “that mankind is solving its economic problem.”7 Keynes believed that “a point may soon be reached, much sooner perhaps than we are all of us aware of, when these [economic] needs are satisfied in the sense that we prefer to devote our further energies to non-economic purposes.”8 He looked expectantly to a future in which machines would produce an abundance of nearly free goods and services, liberating the human race from toil and hardships and freeing the human mind from a preoccupation with strictly pecuniary interests to focus more on the “arts for life” and the quest for transcendence.

Robot Rules: Regulating Artificial Intelligence
by Jacob Turner
Published 29 Oct 2018

This book provides a roadmap for a new set of regulations, asking not just what the rules should be but—more importantly—who should shape them and how can they be upheld. There is much fear and confusion surrounding AI and other developments in computing. A lot has already been written on near-term problems including data privacy and technological unemployment.4 Many writers have also speculated about events in the distant future, such as an AI apocalypse at one extreme,5 or a time when AI will bring a new age of peace and prosperity, at the other.6 All these matters are important, but they are not the focus of this book. The discussion here is not about robots taking our jobs, or taking over the world.

…

They lost economically with the decline of well-paid jobs for people without qualifications and culturally, too, with the disappearance of a distinct working-class culture and the marginalisation of their views in the public conversation72 Why are these trends relevant to the question of whether to grant legal personality to AI? Though this book is not about the economic impact of AI and technological unemployment, this is undeniably a major concern for world economies and populations. White collar jobs may be increasingly threatened by AI, but nonetheless it remains likely that jobs requiring less skill and training will be replaced first, not least because those taking the relevant decisions are often skilled individuals who will not be keen to cannibalize their own jobs or those of their immediate friends and family.

Evil Geniuses: The Unmaking of America: A Recent History
by Kurt Andersen
Published 14 Sep 2020

Wells depicted the utopia of The Shape of Things to Come—their friend John Maynard Keynes saw the economic future.*1 “We are being afflicted with a new disease,” he wrote in a speculative essay called “Economic Possibilities for Our Grandchildren,” a disease of which “readers will hear a great deal in the years to come—namely, technological unemployment. This means unemployment due to our discovery of means of economizing the use of labor outrunning the pace at which we can find new uses for labor.” It would become a bigger and bigger problem, the founder of macroeconomics warned, and in about a century—that is, around 2030—it would finally require a major rethink of how we organize economies.

…

One of the main challenges will be changing what Harari calls the moral viewpoint. We need to think of his scary wolf, AI and robots, not necessarily as a terrifying predator. Instead, they can be like the gray wolves that we tamed thousands of years ago and turned into humans’ best friend—dogs. Technological unemployment and its approaching endgame are indeed an existential threat, but they’re also a potentially grand existential opportunity. And taking advantage will first require a shift by the United States to some kind of economic democracy, taking the power away from big business and the rich to write all the rules only to serve themselves.

Futureproof: 9 Rules for Humans in the Age of Automation
by Kevin Roose
Published 9 Mar 2021

The most prominent public figure to sound the alarm, the New York businessman Andrew Yang, ran for the Democratic nomination for president in 2020 on a promise to give all Americans a $1,000-a-month “freedom dividend” to cushion the blow of automation. He didn’t win, but his warning of a looming AI revolution entered the zeitgeist and pushed the conversation about technological unemployment into the mainstream. Fears of job-killing machines aren’t new. In fact, they date back to roughly 350 b.c.e., when Aristotle mused that automated weavers and self-playing harps could reduce the demand for slave labor. Since then, machine-related anxieties have ebbed and flowed, often peaking during periods of rapid technological change.

The Globalization of Inequality
by François Bourguignon
Published 1 Aug 2012

See also emerging economies development aid, 148–53, 157 development gap, 34–35, 83 Di Bao program, 166 discrimination: ghettos and, 66– 67; immigrants and, 64, 66, 127; labor and, 64–66, 69, 132, 142, 180–81; non-­material inequalites and, 64–66, 69; racial, 65; women and, 64–65, 103 disinflation, 95, 102, 110 distribution, 10n1, 186; capital-­ labor split and, 55–58, 60; efficiency and, 142–45; evolution of inequality and, 41, 42t, 44t, 45, 46t, 48–59, 64, 71–72; fairer globalization and, 148, 153, 156–73, 175, 178; geographical disequilibria and, 83; Gini coefficient and, 18 (see also Gini coefficient); global, 18–19, 25, 29, 39, 41, 46t, 121, 124–38, 141– 45, 156; growth and, 49–50, 188; international, 17–18, 30, 148; median of, 31; OECD countries and, 10–11, 12n3; policy and, 26, 72, 135, 188; range of, 16; real earnings loss and, 78; redistribution and, 4, 7, 37 (see also redistribution); rise in inequality and, 74, 77–79, 82, 85, 90–92, 94–96, 99, 103–4, 106–7, 112, 114–15; Southern perspective on, 82–85; standard of living and, 16, 18 (see also standard of living); taxes and, 37, 92–94 (see also taxes); Theil coefficient and, 18–19, 37–38, 194 distribution (cont.) 52; transfers and, 4, 14, 48, 105, 110, 130, 135–36, 142, 148, 153, 158–67, 170, 175, 181, 183, 187; wage, 3, 78–79, 107 Divided We Stand report, 52 Doha negotiations, 154 drugs, 66, 133 Dubai, 127 Economic Partnership Agreements (EPAs), 156 education, 34, 187; college, 132; evolution of inequality and, 61, 65–68; fairer globalization and, 149, 152, 167–73, 180–81; globalization and, 132, 140, 143; labor and, 168, 180; Millennium Development Goals and, 149– 50; national inequality and, 167–73; poverty and, 24; preschool, 169–70; redistribution and, 149, 152, 167–73; rise in inequality and, 111; taxes and, 167–73; tuition and, 170 efficiency: data transfer technology and, 78; deregulation and, 94, 96, 105, 108; economic, 1, 4, 6, 111, 116, 119, 129–33, 135, 140–45, 158, 164, 167, 171, 181; emerging economies and, 78; equality and, 116, 129–31; fairness and, 8, 129– 31; globalization and, 1, 4, 6, 8, 36, 78, 94, 96, 105, 108, 111, 116, 118–19, 129–35, 140–45, 157–58, 164, 167, 170–71, 175, 180–81, 188; human capital and, 175; import substitution and, 34, 180; inefficiency and, 105, 129–30, 132–33, 135, 140, 170–71, 180, 188; labor Index and, 175; loss of, 142, 164; opportunity and, 142–45; Pareto, 130n5; privatization and, 94, 96, 105, 108; redistribution and, 142–45; rents and, 180; social tensions and, 188; spontaneous redistribution and, 133; taxes and, 170; technology and, 78; weak institutions and, 36; wealth of nations and, 1 elitism, 182; fairer globalization and, 151, 165; globalization and, 127n4, 136, 138; rise in inequality and, 4, 6–7 emerging economies: Africa and, 122–23 (see also Africa); competition and, 178, 187–88; conditional cash transfers and, 165– 66; credit cards and, 165; domestic markets and, 120, 125; efficient data transfer and, 78; evolution of inequality and, 57; fairer globalization and, 147, 154, 158, 165–66, 177–78, 182; global inequality and, 40, 77– 80, 82, 109, 113, 115, 188–89; globalization and, 117, 119–22, 125–27; institutions and, 109– 12; Kuznets curve and, 113; labor and, 77; natural resources and, 127; profits and, 117; rise in inequality and, 109–12; structural adjustment and, 109– 12; taxes and, 165; trends in, 57; Washington consensus and, 109–10, 153 entrepreneurs, 83, 92, 96, 131–32, 135, 143, 170–71, 188 equality: efficiency and, 116, 129– 31; policy for, 184–89; relative gap and, 18, 28, 30, 31–32, 36 Ethiopia, 21–22, 46t, 155 Index195 European Union (EU), 24, 156, 174, 177 Everything But Arms (EBA) initiative, 155 evolution of inequality: Africa and, 46t, 54–55; Brazil and, 46t, 55, 59, 70; capital and, 55–58, 60, 73; China and, 47, 53, 57–60; consumption and, 42t, 44t; convergence and, 65, 69; credit and, 61; crises and, 48, 50, 54, 57, 73–74; developed countries and, 47, 52–53, 56, 59–64, 66; developing countries and, 47, 53–55, 57, 63, 68; distribution and, 41, 42t, 44t, 45, 46t, 48–59, 64, 71– 72; education and, 61, 65–68; elitism and, 4, 6–7, 46t; emerging economies and, 57; exceptions and, 52–53; France and, 46t, 51f, 52–53, 55, 58, 59n8, 62–63, 66, 70–71; ghettos and, 66–67; Gini coefficient and, 39, 42t, 44t, 48, 50, 51f, 53, 58–59; Great Depression and, 48; growth and, 33, 49–50, 54; India and, 54, 57, 59–60; institutions and, 55, 69; investment and, 56; labor and, 55–58, 60; markets and, 48–50, 53–54, 64, 69; national income inequality and, 48–52; non-­monetary inequalities and, 49, 60–70; normalization and, 41, 43–44; opportunity and, 61–62, 68, 70–71; perceptions of inequality and, 69–73; policy and, 55, 72; primary income and, 48–50, 58; production and, 57; productivity and, 63; profit and, 56; reform and, 54, 72; rise in inequality in, 48–52, 73, 77–80, 91–95, 97–98, 102–8; risk and, 63, 66; standard of living and, 41, 43– 45, 46t, 53–55, 58, 60–62, 67, 69, 73; surveys and, 42t, 43–45, 56, 68n17, 69–71; taxes and, 12–14, 37, 48, 50, 56n5; Theil coefficient and, 42; United Kingdom and, 46t, 50, 51f, 59, 67, 68n17; United States and, 2, 4–6, 9, 11, 21, 33, 46t, 47–50, 51f, 58, 59n9, 66–70, 73; wealth and, 58–60 executives, 73, 88–89, 97, 174 expenditure per capita, 13, 15, 42t, 44t exports: deindustrialization and, 76, 82; fairer globalization and, 147, 154–55, 176, 178; globalization and, 124, 128; rise in inequality and, 76, 82–84 fairer globalization: Africa and, 147, 151, 154–56, 179, 183; African Growth Opportunity Act (AGOA) and, 155; Bolsa Familia and, 166; Brazil and, 150, 154, 166–68, 173; capital and, 158–62, 167, 171, 175, 182; China and, 150, 154, 165–66, 172, 178; competition and, 155, 169, 173, 176–79, 182; consumers and, 177–78; consumption and, 159, 177; convergence and, 146–47, 157; correcting national inequalities and, 158–80; credit and, 164–65, 172, 180; crises and, 163, 176; deregulation and, 173; developed countries and, 150, 154–57, 160, 162, 164, 168–72, 176, 178–79, 181; developing countries and, 154, 166; development aid and, 196 fairer globalization (cont.) 148–53, 157; Di Bao program and, 166; distribution and, 148, 153, 156–73, 175, 178; Economic Partnership Agreements (EPAs) and, 156; education and, 149, 152, 167–73; 180–81; elitism and, 151, 165; emerging economies and, 147, 154, 158, 165–66, 177–78, 182; Everything But Arms (EBA) initiative and, 155; exports and, 147, 154–55, 176, 178; France and, 147, 159–61, 164, 169, 175, 177; Gini coefficient and, 156, 166; goods and services sector and, 180; growth and, 147–52, 155, 162, 167–68, 171, 177, 180, 183; health issues and, 152, 166; imports and, 154, 177–78, 180; India and, 150, 154, 165– 66, 172; inheritance and, 170– 73; institutions and, 151, 168, 174–75; international trade and, 176–77; investment and, 150, 155, 157, 160, 170, 174, 179; liberalization and, 156, 179; markets and, 147–48, 154–58, 168, 173–75, 178–81; Millennium Development Goals and, 149–50; national inequality and, 147, 158; opportunity and, 155, 167, 170, 172; policy and, 147–53, 157, 167–73, 175, 177, 179–83; poverty and, 147–52, 164, 166, 175; prices and, 147– 48, 176, 178, 182; primary income and, 158, 163n10, 167, 173; production and, 155–57, 167, 176, 178–79; productivity and, 155, 177–78; profit and, 173, 176; Progresa program and, Index 166; protectionism and, 7, 147, 154, 157, 176–79; redistribution and, 148, 153, 156–73, 175, 178; reform and, 151, 161, 163, 168–69; regulation and, 152, 173–76, 181–82; risk and, 148, 154, 156, 159, 164, 171, 174–75, 178; standard of living and, 146–48, 154, 156–58, 160, 165, 168–69; surveys and, 169; taxes and, 148, 158–73, 175, 181–83; technology and, 156, 173; TRIPS and, 156; United Kingdom and, 163, 169; United States and, 155, 159–61, 163– 64, 169, 174–75, 182; wealth and, 162, 164, 167, 170–73 Fitoussi, Jean-­Paul, 14 France: evolution of inequality and, 46t, 51f, 52–53, 55, 58, 59n8, 62–63, 66, 70–71; fairer globalization and, 147, 159–61, 164, 169, 175, 177; Gini coefficient of, 20; global inequality and, 2, 9, 11, 20–21; offshoring and, 81; rise in inequality and, 80, 88, 92–93, 95, 97, 99, 103; soccer and, 87; wage deductions and, 159 G7 countries, 56 G20 countries, 182 Garcia-­Panalosa, Cecilia, 107 Gates, Bill, 5–6, 70, 150 Germany, 2, 21, 46t, 50, 51f, 80, 88, 92 Ghana, 46t, 54 ghettos, 66–67 Giertz, Seth, 160–61 Gini coefficient: Brazil and, 22; Current Population Survey and, 21; evolution of inequality and, Index197 39, 42t, 44t, 48, 50, 51f, 53, 58– 59; fairer globalization and, 156, 166; France and, 20; historical perspective on, 27–28; meaning of, 18–19; purchasing power parity and, 28; rise in inequality and, 110; United States and, 21; wealth inequality and, 58–60 Glass-­Steagall Act, 174n15 global distribution, 18–19, 25, 29, 39, 41, 46t, 121, 156 global inequality: Africa and, 16, 21, 23, 30–31, 34, 36; between countries, 2–3, 5, 7, 9, 16–19, 23, 33, 36, 38–39, 42–45, 47, 53, 58, 68, 90–91, 107, 117–19, 123, 128, 153; Brazil and, 21– 23; crises and, 20, 38–41; cross-­ country heterogeneity and, 13; definition of, 3–4, 9–10, 25–26, 30–32, 39; developed countries and, 10–11, 21, 34–39; developing countries and, 10–11, 13, 21, 32, 34–39; effects of, 38–40; emerging economies and, 40, 77–80, 82, 109, 113, 115, 188– 89; at the end of the 2000s, 20– 25; evolution of inequality and, 41 (see also evolution of inequality); expenditure per capita and, 13, 15, 42t, 44t; France and, 2, 9, 11, 20–21; globalization and, 117–18, 121–23, 128; great gap and, 33–36; historic turning point for, 25–32; Human Development Report and, 25; institutions and, 36; measuring, 10– 20; Millennium Development Goals and, 149–50, 185; normalization and, 13, 15, 22–23, 26, 29; OECD Database on Household Income Distribution and Poverty and, 11–12; policy and, 185–89; Povcal database and, 10, 12, 42t, 43, 44t; prices and, 27–28, 74, 80, 84, 91–92, 94, 97, 110; profit and, 13; reduction of, 2, 185–86; relative gap and, 18, 28, 30–32, 36; rise of, 2–4, 7; risk and, 20; standard of living and, 10–26, 29, 31–33, 36, 39; surveys on, 10, 12–15, 20n10, 21–22, 29, 42t, 43–45; technology and, 3–4, 34–35; trend reversal in, 37–38; within countries, 2, 5–7, 9, 16, 30, 33, 35–45, 47, 113–14, 118, 124– 29, 184–85, 189 globalization: Africa and, 122–23, 126–27; Asian dragons and, 34, 82; Brazil and, 127, 133; capital and, 117, 125–26, 132, 137; China and, 120–22, 128; competition and, 117–18, 130, 186 (see also competition); as complex historical phenomenon, 1–2; consumption and, 137–39; convergence and, 120–22, 125; credit and, 131–32, 137–40; crises and, 119–22, 125, 135–39, 142; debate over, 1; deindustrialization in developed countries and, 75–82; democratic societies and, 135–36; deregulation and, 95–99; developed countries and, 117, 119, 121, 127n4, 128, 133, 143; developing countries and, 121, 127n4, 128, 132, 143; education and, 132, 140, 143; efficiency and, 1, 4, 6, 8, 36, 78, 94, 96, 105, 108, 111, 116, 118–19, 129–35, 140–45, 157–58, 164, 167, 170–71, 175, 180–81, 188; elitism and, 127n4, 136, 138; 198 globalization (cont.) emerging economies and, 117, 119–22, 125–27; exports and, 124, 128; fairer, 146–83 (see also fairer globalization); future of inequality between countries and, 119–22; global inequality and, 117–18, 121–23, 128; goods and services sector and, 127, 130; growth and, 118–29, 134–39; health issues and, 140– 41, 144; Heckscher-­Ohlin model and, 76; imports and, 119, 124; inequality within countries and, 124–29; inheritance and, 144–45; institutions and, 124; as instrument for modernization, 1; international trade and, 3, 75–76, 78–79, 83, 112, 114, 176–77; investment and, 119, 130, 134–35, 143; laissez-­faire approach and, 118, 129; markets and, 118, 120–21, 124–37, 140, 143–44; as moral threat, 1; national inequality and, 119; negative consequences of inequality and, 131–42; opportunity and, 133–34, 139, 142–44; as panacea, 1; policy and, 118–19, 124, 126, 128–31, 139, 143–44; poverty and, 117, 123, 126–27, 134, 144; prices and, 118, 122, 126, 136–38; primary income and, 135, 143–44; production and, 119, 124, 126, 129, 131, 133, 137; productivity and, 120, 125, 127, 144; profit and, 117; redistribution and, 121, 124–38, 141–45; reform and, 124, 126–27, 138; regulation and, 136; rise in inequality and, 117–18; risk and, 127–28, Index 137–39, 144; shocks and, 38, 55, 91–92, 175; Southern perspective on, 82–85; standard of living and, 120–23, 126, 138, 143; surveys and, 127n4, 141n15; taxes and, 74, 89n10, 91–94, 104, 114–15, 129–30, 135–36, 142–45; technology and, 86–91, 118–20, 125; trends and, 118; United States and, 135–39; wealth and, 74, 95, 98, 125, 127, 129, 131–32, 139, 143–45 Great Depression, 48 Greece, 46t, 135 gross domestic product (GDP) measurement: Current Population Survey and, 21; evolution of inequality and, 41–45, 56–57; fairer globalization and, 123, 127, 165–66, 176; global inequality and, 13–15, 20–21, 23, 26, 27f, 29–30, 39; normalization and, 29, 41, 43–45; rise in inequality and, 94; Sen-­Stiglitz-­ Fitoussi report and, 14 Gross National Income (GNI), 148–49 Growing Unequal report, 52 growth, 4; African Growth Opportunity Act (AGOA) and, 155; constraints and, 35; consumption and, 13–15, 42t, 44t, 80, 137–39, 159, 177; convergence and, 16; determinants of, 34; distribution and, 49–50, 188; emerging economies and, 125 (see also emerging economies); evolution of inequality and, 33, 49–50, 54; fairer globalization and, 147–52, 155, 162, 167–68, 171, 177, 180, 183; GDP mea- Index199 surement of, 30, 39 (see also gross domestic product (GDP) measurement); globalization and, 118–29, 134–39; great gap in, 33–36; import substitution and, 34, 180; inflation and, 50, 95, 102, 110; negative, 31; political reversals and, 36; poverty and, 28–29; production and, 3, 34–35, 57, 74, 76–81, 84–86, 119, 124, 126, 129, 131, 133, 137, 155–57, 167, 176, 178–79; rate of, 15, 29–35, 79, 125, 185; recession and, 6, 31, 99, 120; relative gap and, 18, 20, 30–32, 36; rise in inequality and, 75, 79, 82, 84, 109–12; trends in, 40, 121 health issues, 24, 187; fairer globalization and, 152, 166; globalization and, 140–41, 144; public healthcare and, 37, 111, 140 Heckscher-­Ohlin model, 76 Hong Kong, 34, 82, 174 housing, 12, 61, 137 human capital, 74, 167, 175 Human Development Report, 25 Ibrahimovich, Zlata, 87 IKEA, 172 immigrants, 64, 66, 127 imports: fairer globalization and, 154, 177–78, 180; globalization and, 119, 124; import substitution and, 34, 180; rise in inequality and, 80 income: average, 9, 18, 21, 29–30, 43, 72; bonuses and, 87, 174; convergence and, 16; currency conversion and, 11; definition of, 45; deindustrialization and, 75–82; developed/developing countries and, 5, 36; disposable, 20, 22, 24, 48, 50, 51f, 74, 91, 163; distribution of, 3 (see also distribution); executives and, 73, 88–89, 97, 174; family, 10; financial operators and, 87–88, 90–91; gap in, 3, 5–6, 27f, 33– 36, 42t, 44t, 149; GDP measurement and, 13–15, 20–21, 23, 26, 27f, 29–30, 39, 41–45, 56–57, 94, 123, 127, 165–66, 176; high, 50, 52, 56, 85–93, 97–99, 140, 143, 158–62, 164, 189; household, 10–12, 43, 45, 50, 58, 105, 107, 137, 163, 177; inequality in, 2, 4, 41, 48–50, 56–64, 68, 70, 72–73, 83, 98, 102–3, 107–8, 114, 125, 132– 34, 137, 140–41, 143–44, 163; inflation and, 50, 95, 102, 110; international scale for, 17–18, 23, 30; lawyers and, 89–90; mean, 17, 20n10, 27f, 42t, 44t; median, 6, 49, 71, 102–3, 106; minimum wage and, 52–53, 100, 102–8, 175, 177; national, 7, 16–19, 30, 43, 48–52, 60, 73, 84n6, 125, 149, 153, 172; OECD Database on Household Income Distribution and Poverty and, 11; opportunity and, 5; payroll and, 53, 93, 100, 104, 107, 175; pension systems and, 167; per capita, 20, 25, 29–30, 42t, 45, 48, 55–56, 120; portfolios and, 88; poverty and, 1, 11, 15n6, 19–20, 22–25, 28–29, 32, 44t, 109, 117, 123, 126–27, 134, 144, 147–52, 164, 166, 175; primary, 48–50, 58, 135, 143–44, 158, 163n10, 167, 173; 200 income (cont.) purchasing power and, 11, 13, 19–24, 27f, 28, 50, 80, 144, 158, 178; real earnings loss and, 78; relative gap and, 18, 28, 30, 31– 32, 36; superstars and, 85–87, 89–90; taxes and, 37, 89n10, 92–93, 145, 159, 161–65, 170 (see also taxes); technology and, 34, 180; virtual, 12; wage inequality and, 51–53, 79, 101–3, 106, 108; wage ladder effects and, 78–79; wealth inequality and, 58–60; women and, 64– 65, 103 India: evolution of inequality and, 54, 57, 59–60; fairer globalization and, 150, 154, 165– 66, 172; household consumption and, 15; international trade and, 75; Kuznets hypothesis and, 113; rise in inequality and, 2, 15–16, 19, 30, 34, 46t, 75, 83, 90, 112–13; taxes and, 165 Indonesia, 30, 46t, 54, 111, 127 industrialization: deindustrialization and, 1, 75–82, 102, 120, 188; labor and, 1, 26, 29, 33, 35, 54, 82, 84, 102, 113, 120, 127, 179, 188 Industrial Revolution, 26, 29, 33, 35 inequality: between countries, 2–3, 5, 7, 9, 16–19, 23, 33, 36, 38– 39, 42–45, 47, 53, 58, 68, 90– 91, 107, 117–19, 123, 128, 153; efficiency and, 1, 4, 6, 8, 36, 78, 94, 96, 105, 108, 111, 116, 118– 19, 129–35, 140–45, 157–58, 164, 167, 170–71, 175, 180–81, 188; Gini coefficient and, 18 (see Index also Gini coefficient); income, 2, 4, 41, 48–50, 56–64, 68, 70, 72–73, 83, 98, 102–3, 107–8, 114, 125, 132–34, 137, 140–41, 143–44, 163; international, 17; inverted U curve and, 54, 113; measurement of, 18; negative consequences of, 131–42; non-­ monetary, 49, 60–70; perceptions of, 69–73; social tensions and, 188; standard of living and, 18 (see also standard of living); Theil coefficient and, 18–19, 37–38, 42; wealth, 58–60; within countries, 2, 5–7, 9, 16, 30, 33, 37–45, 47, 113–14, 118, 124–29, 184–85, 189 infant mortality, 150 inflation, 50, 95, 102, 110 inheritance: fairer globalization and, 170–73; globalization and, 144–45; rise in inequality and, 93 institutions: deregulation and, 91– 112 (see also deregulation); disinflation and, 95, 102, 110; emerging economies and, 109– 12; evolution of inequality and, 55, 69; fairer globalization and, 151, 168, 174–75; global inequality and, 36; globalization and, 124; markets and, 91–92; privatization and, 94–109; reform and, 91–112; rise in inequality and, 91–112, 114; structural adjustment and, 109– 12; taxes and, 92–94; “too big to fail” concept and, 174–75; Washington consensus and, 109–10, 153 International Development Association, 149 Index201 international income scale, 17–18, 23, 30 International Labor Organization, 51 International Monetary Fund (IMF), 54, 57, 84, 90, 109–10 international trade: capital mobility and, 74; China and, 75; de­ industrialization and, 75–76, 78–79; effect of new players, 75–76; Heckscher-­Ohlin model and, 76; India and, 75; offshoring and, 81–82; rise in inequality and, 75–76, 78–79, 83, 112, 114; Soviet Union and, 75; theory of, 76; wage ladder effects and, 78–79 inverted U curve, 54, 113 investment: direct, 76, 79; evolution of inequality and, 56; fairer globalization and, 150, 155, 157, 160, 170, 174, 179; foreign, 83, 85, 112, 155, 157, 160, 179; globalization and, 119, 130, 134– 35, 143; production and, 119; public services and, 143; re-­ investment and, 56; rise in inequality and, 76, 79, 82–83, 85, 92, 97–98, 112; taxes and, 92 Ivory Coast, 54 Japan, 34, 46t, 51f, 103 job training, 34, 181, 187 Kenya, 46t, 54 kidnapping, 133 Kuznets, Simon, 113, 126 labor: agriculture and, 12, 82, 84, 122–23, 127–28, 132, 155; artists and, 86–87; bonuses and, 87, 174; capital and, 3–4, 55– 58, 60, 158, 161n7, 185; capital mobility and, 3; cheap, 77, 117; costs of, 81, 100, 104–5, 117, 176, 187; decline in share of national income and, 73; deindustrialization and, 75–82; demand for, 168; deregulation and, 99– 109; discrimination and, 64–66, 69, 132, 142, 180–81; distribution of income and, 175 (see also distribution); education and, 168, 180; efficiency and, 96–97, 175; emerging economies and, 77; entrepreneurs and, 83, 92, 96, 131–32, 135, 143, 170–71, 188; evolution of inequality and, 55–58, 60; excess, 81, 83; executives and, 73, 88–89, 97, 174; goods and services sector and, 13, 73, 80, 85, 91, 102, 127, 130, 180; growth and, 154, 179; immigrant, 64, 66, 127; increased mobility and, 90–91; industrialization and, 1, 26, 29, 33, 35, 54, 80, 82, 84, 102, 113, 120, 127, 179, 188; inflation and, 50, 95, 102, 110; International Labor Organization and, 51; job training and, 34, 181, 187; manufacturing and, 57, 80–82, 84, 123, 154–55, 157; median wage and, 49, 71, 102– 3, 106; minimum wage and, 52– 53, 100, 102–8, 175, 177; mobility of, 185; offshoring and, 81–82; payroll and, 53, 93, 100, 104, 107, 175; pension systems and, 167; portfolios and, 88; poverty and, 1, 11, 15n6, 19– 20, 22–25, 28–29, 32, 44t, 109, 117, 123, 126–27, 134, 144, 147–52, 164, 166, 175; 202 labor (cont.) privatization and, 99–109; productivity and, 63, 79, 81–82, 89, 100, 102, 104, 114, 120, 125, 127, 144, 155, 177–78; protectionism and, 7, 147, 154, 157, 176–79; real earnings loss and, 78; reserve, 84; security and, 133; skilled, 76–78, 82–83, 86, 90, 114, 117, 126, 176; standard of living and, 69 (see also standard of living); superstars and, 85, 87, 89–90; supply of, 130– 31, 164; taxes and, 159–60, 171; technology and, 85–91 (see also technology); unemployment and, 37, 39, 53, 62–63, 66, 69, 77, 94, 100–108, 164, 175–76; unions and, 100–106, 108, 156, 179; unskilled, 3, 76–77, 79, 83, 105, 117, 154; wage inequality and, 51–53, 79, 101–3, 106, 108; wage ladder effects and, 78–79; women and, 64–65, 103, 114; writers and, 86–87 Lady Gaga, 5–6 laissez-­faire approach, 118, 129 Latin America, 9, 34, 36, 54–55, 58, 109–11, 155, 165–66, 168, 180 lawyers, 89–90 liberalization: capital and, 96; customs, 156; deregulation and, 96–99, 108–9, 112 (see also deregulation); fairer globalization and, 156, 179; mobility of capital and, 115; policy effects of, 97–99; Reagan administration and, 91; recession and, 6, 31, 99, 120; rise in inequality and, 76, 91, 93, 96–99, 108–9, 112, 115; tax rates and, 93 Luxembourg, 16, 19 Index Madonna, 71 Malaysia, 127 manufacturing: deindustrialization and, 75–82, 84, 123; emerging economies and, 57, 84; fairer globalization and, 154–55, 157; France and, 81; offshoring and, 81–82; United Kingdom and, 80; United States and, 80 markets: competition and, 76–77, 79–82, 84, 86, 94–98, 102, 104, 115–18, 130, 155, 169, 173, 176–79, 182, 186–88; credit, 131; deindustrialization and, 1, 75–82, 102, 120, 188; deregulation and, 91–92, 99–109 (see also deregulation); development gap and, 34–35, 83; Economic Partnership Agreements (EPAs) and, 156; effect of new players, 75–76; emerging economies and, 120 (see also emerging economies); entrepreneurs and, 83, 92, 96, 131–32, 135, 143, 170–71, 188; evolution of inequality and, 48–50, 53–54, 64, 69; exports and, 76, 82–84, 124, 128, 147, 154–55, 176, 178; fairer globalization and, 147–48, 154–58, 168, 173–75, 178–81; GDP measurement and, 13–15, 20–21, 23, 26, 27f, 29–30, 39, 41–45, 56–57, 94, 123, 127, 165–66, 176; globalization and, 35, 118, 120–21, 124–37, 140, 143–44; Heckscher-­Ohlin model and, 76; housing, 12, 61, 137; imports and, 1, 34, 80, 119, 124, 154, 177–78, 180; institutions and, 91–112; international trade and, 3, 75–76, 78–79, 83, 112, 114, 176–77; labor and, Index203 144 (see also labor); liberalization and, 112 (see also liberalization); monopolies and, 94, 111, 127, 136; offshoring and, 81– 82; protectionism and, 7, 147, 154, 157, 176–79; purchasing power and, 11, 13, 19–24, 27f, 28, 50, 80, 144, 158, 178; reform and, 54 (see also reform); regulation and, 74 (see also regulation); rise in inequality and, 74, 76– 79, 83, 86, 90–112, 114; shocks and, 38, 55, 91–92, 175; single market and, 76; South-­South exchange and, 35; TRIPS and, 156 median wage, 49, 71, 102–3, 106 Mexico, 46t, 57, 59, 109–10, 133, 166, 172 middle class, 51, 71, 93, 109, 133– 34, 136, 140 Milanovic, Branko, 4–5, 17n8, 29n16 Millennium Development Goals, 149–50, 185 minerals, 84, 127 minimum wage, 52–53, 100, 102– 8, 175, 177 monopolies, 94, 111, 127, 136 Morocco, 173 Morrisson, Christian, 28 movies, 87 Murtin, Fabrice, 28 national inequality, 2–4; correcting, 158–80; education and, 167–73; fairer globalization and, 147, 158; Gini coefficient and, 27 (see also Gini coefficient); globalization and, 119; market regulation and, 173–75; protectionism and, 147, 157, 176–79; redistribution and, 158–73, 175, 178; rise in, 6, 48– 52, 115, 204; taxes and, 158–73, 175, 181–83 natural resources, 84–85, 92, 122, 126–28, 127, 151 Netherlands, 46t, 50, 66, 70, 102 Nigeria, 9, 46t, 54, 127, 151 non-­monetary inequalities: access and, 61, 67–68; capability and, 61; differences in environment and, 66–68; discrimination and, 64–66, 69; employment precariousness and, 63–64; evolution of inequality and, 49, 60–70; intergenerational mobility and, 68; opportunities and, 49, 60– 70; social justice and, 60, 70; unemployment and, 62–63 normalization: evolution of inequality and, 41, 43–44; GDP measurement and, 29, 41, 43– 45; global inequality and, 13, 15, 22–23, 26, 29 Occupy Wall Street movement, 6, 135 OECD countries, 27t; evolution of inequality and, 42t, 43, 44t, 50– 52, 64, 65n13; fairer globalization and, 149, 159, 162, 164– 65; Gini coefficient and, 51; income distribution and, 51; relaxation of regulation and, 99; restrictive, 64; rise in inequality and, 50–51, 94, 99, 102, 106n18, 107; social programs and, 94; standard of living and, 11–12, 43, 50–52, 64, 94, 99, 102, 107, 120, 149, 159, 162, 164–65; U-­shaped curve on income and, 50 OECD Database on Household 204 Income Distribution and Poverty, 11–12 offshoring, 81–82 oil, 92, 127 opportunity, 5; African Growth Opportunity Act (AGOA) and, 155; as capability, 61; efficiency and, 142–45; evolution of inequality and, 61–62, 68, 70–71; fairer globalization and, 155, 167, 170, 172; globalization and, 133–34, 139, 142–44; redistribution and, 142–45; rise in inequality and, 102 Pakistan, 46t, 111 Pareto efficiency, 130n5 Pavarotti, Luciano, 86–87 payroll, 53, 93, 100, 104, 107, 175 Pearson Commission, 149 pension systems, 167 Perotti, Roberto, 134 Philippines, 46t, 111 Pickett, Kate, 140 Piketty, Thomas, 4, 48, 59n8, 60, 89n10, 125, 160n4 PISA survey, 169–70 policy, 4; adjustment, 109, 153; Cold War and, 149, 153; convergence and, 147–48; development aid and, 148–53; distributive, 26, 72, 135, 188; educational, 149, 152, 167–73; evolution of inequality and, 55, 72; fairer globalization and, 147–53, 157–58, 167–73, 175–83; Glass-­Steagall Act and, 174n15; global inequality and, 185–89; globalization and, 118–19, 124, 126, 128–31, 139, 143–44; globalizing equality and, 184–89; import substi- Index tution and, 34; Millennium Development Goals and, 149– 50, 185; poverty reduction and, 147–48; protectionist, 7, 99– 100, 107–8, 147, 154, 157, 176–79; reform and, 74 (see also reform); rise in inequality and, 34, 74–75, 85, 94, 97, 99– 100, 104, 106–11, 114–16; social, 7; standard of living and, 147–48 population growth, 28–29, 110, 183 portfolios, 88 Povcal database, 10, 12, 42t, 43, 44t poverty, 1, 44t, 109; Collier on, 23; convergence and, 147–48; criminal activity and, 133–34; definition of, 24; development aid and, 147–52; fairer globalization and, 147–52, 164, 166, 175; ghettos and, 66–67; global inequality and, 11, 15n6, 19–20, 22–25, 28–29, 32; globalization and, 117, 123, 126–27, 134, 144; growth and, 28–29; measurement of, 23–24; Millennium Development Goals and, 149– 50, 185; OECD Database on Household Income Distribution and Poverty and, 11–12; reduction policies for, 147–48; traps of, 144, 150, 164 prices: commodity, 84, 182; exports and, 178; factor, 74, 126; fairer globalization and, 147–48, 176, 178, 182; global inequality and, 27–28, 74, 80, 84, 91–92, 94, 97, 110; globalization and, 118, 122, 126, 136–38; imports and, 80; international compari- Index205 sons of, 11; lower, 94, 137; oil, 92; rise in inequality and, 74, 80, 84, 91–92, 94, 97, 110; rising, 110, 122, 178; shocks and, 38, 55, 91–92, 175; statistics on, 11, 27; subsidies and, 109–10, 175 primary income: evolution of inequality and, 48–50, 58; fairer globalization and, 158, 163n10, 167, 173; globalization and, 135, 143–44 privatization: deregulation and, 94–112; efficiency and, 94, 96, 105, 108; globalization of finance and, 95–99; institutions and, 94–109; labor market and, 99–109; reform and, 94–109; telecommunications and, 111 production: deindustrialization and, 75–82; evolution of inequality and, 57; fairer globalization and, 155–57, 167, 176, 178–79; globalization and, 119, 124, 126, 129, 131, 133, 137; growth and, 3, 34–35, 57, 74, 76–81, 84–86, 119, 124, 126, 129, 131, 133, 137, 155–57, 167, 176, 178–79; material investment and, 119; North vs.

The Third Pillar: How Markets and the State Leave the Community Behind
by Raghuram Rajan
Published 26 Feb 2019

Before we end this chapter, we need to discuss three issues. First, to what extent should some of the support beyond the Beveridge level of care, for those who have not saved money or paid for insurance, be decided and administered by the community? Second, should we prepare for increasing technological unemployment with schemes like a universal basic income? Third, how do we pay for the entitlements that have already been committed to, as well as the outstanding government debt, even before we embark on creating new entitlements? COMMUNITY-DETERMINED ADDITIONAL SUPPORT The basic level of economic support in case of unemployment, disability, or old age should have no conditions attached.

…

It is to give every adult in the country a universal basic income (UBI), which will be enough to live a decent life, with no questions asked. The difference from the basic support we discussed above is that UBI would be set at much higher levels, and paid to everyone regardless of need. There is an ongoing debate about whether those who fear technological unemployment are too pessimistic, underestimating the ability of markets and human ingenuity to find productive uses for unemployed humans. History suggests the optimists have been right thus far, but this time could be different. UBI, in principle, is extremely simple. Each adult would get a monthly check for themselves and their dependents.

Utopia for Realists: The Case for a Universal Basic Income, Open Borders, and a 15-Hour Workweek
by Rutger Bregman
Published 13 Sep 2014

Employees have been worrying about the rising tide of automation for 200 years now, and for 200 years, employers have been assuring them that new jobs will naturally materialize to take their place. After all, if you look at the year 1800, 74% of all Americans were farmers, whereas by 1900 this figure was down to 31%, and by 2000 to a mere 3%.19 Yet this hasn’t led to mass unemployment. And look at Keynes writing in the 1930s about the “new disease” of “technological unemployment” that would soon be making headlines; when he died in 1946, everything still was peachy. Over the 1950s and 1960s the American automotive industry experienced successive waves of automation, yet wages and work opportunities both continued their steady rise. A study conducted in 1963 demonstrated that though new technologies had wiped out 13 million jobs over the previous decade, they had also created 20 million new ones.

Basic Income: A Radical Proposal for a Free Society and a Sane Economy
by Philippe van Parijs and Yannick Vanderborght
Published 20 Mar 2017

Even so, Â�there are two considerations that make this aveÂ�nue unpromising. One of them is well formulated by labor Â� leader Andy Stern. Â�Because of the importance he attaches to work in giving purpose to our lives, he writes, “it was only natuÂ�ral that my initial thought for a solution to the coming tsunami of technological unemployment would be to guarantee a job for Â�every American who wants one.” However, further reflection made him change his mind: “Inevitably, a handful of Â�people in a government agency would end up deciding the value of a parÂ�ticÂ�uÂ�lar job or category of work for the entire country at the expense of individual differences and choice.

…

Creating New Money: A Monetary Reform for the Information Age. London: New Economics Foundation. Huet, François. 1853. Le Règne social du christianisme. Paris: Firmin Didot and Brussels: Decq. Huff, Gerald. 2015. “Should We Be Afraid, Very Afraid? A Rebuttal of the Most Common Arguments against a Â�Future of Technological Unemployment.” Basic Income blogpost, May 25. https://Â�medium╉.Â�com╉/Â�basic╉-Â�income╉/Â�should╉-Â�we╉-Â�be╉-Â�afraid╉-Â�very╉-Â�afraid╉-Â�4f7013a5137c. Hum, Derek, and Wayne Simpson. 1991. Income Maintenance, Work Effort, and the Canadian Mincome Experiment. Ottawa: Economic Council of Canada.

Money and Government: The Past and Future of Economics
by Robert Skidelsky
Published 13 Nov 2018

But now machine intelligence is improving at such a rapid rate that the distinction between capital and labour is blurring. New technology may, indeed, create as many jobs as it destroys, but the new workers will be machines, not humans. For the first time in history, human labour may be being made redundant faster than new human employment is being found for it; i.e. the ‘technological unemployment’ predicted by Wassily Leontief in 197931 may be turning into a reality. If this turns out to be the case, the income equalization which can serve the narrow purposes of the modern secular stagnationist will need to become an essential ingredient of policy in the future. Workers displaced by machines will need to be guaranteed a replacement income.

…

Basingstoke and London: Macmillan, pp. 81–114. Lenin, V. I. (1970 (1917)), Imperialism, the Highest Stage of Capitalism. In: V. I. Lenin, Selected Works (I). Moscow: Progress Publishers, pp. 667–768. Leontief, W. (1952), Machines and man. Scientific American, 187 (3), pp. 150–60. Leontief, W. (1979), Is technological unemployment inevitable? Challenge, 22 (4), pp. 48–50. Lindbeck, A. (1976), Stabilization Policy in Open Economies with Endogenous Politicians. Seminar Paper 54, Institute for International Economic Studies, University of Stockholm. List, F. (1909 (1841)), The National System of Political Economy. London: Longman, Green & Co.

Big Three in Economics: Adam Smith, Karl Marx, and John Maynard Keynes
by Mark Skousen
Published 22 Dec 2006

By faith, I mean a certain degree of confidence that, left to their own devices, individuals acting in their own self-interest will generate a positive outcome. Faith represents a level of predictability of the future: Will an unfettered economy recover on its own from a recession? Will eliminating tariffs between two countries increase trade and jobs between them? Will decontrol-ling oil prices eliminate the energy crisis? Will technological unemployment in one industry lead to new employment in another? Will a competitive environment eventually break down monopolistic power in a particular market? Individuals have differing levels of confidence in the marketplace to respond positively to change or crisis. Some have full faith that all will work out for the better.

Revolution at Point Zero: Housework, Reproduction, and Feminist Struggle
by Silvia Federici
Published 4 Oct 2012

Today our choices are more defined because we can measure what we have achieved and see more clearly the limits and possibilities of the strategies adopted in the past. For example, can we still campaign for “equal pay for equal work” when wage differentials are being introduced even in what have traditionally been the strongholds of male working class power? Or can we afford to be confused as to “who is the enemy,” when the attack on male workers, by technological unemployment and wage cuts, is used to contain our demands as well? And can we believe that liberation begins with “getting a job and joining the union,” when the jobs we get are at the minimum wage and the unions only seem capable of bargaining over the terms of our defeat? When the women’s movement started in the late ‘60s we believed it was up to us women to turn the world upside down.

Prediction Machines: The Simple Economics of Artificial Intelligence
by Ajay Agrawal , Joshua Gans and Avi Goldfarb
Published 16 Apr 2018

Thus, people unsurprisingly took notice when, in December 2016, he wrote: “The automation of factories has already decimated jobs in traditional manufacturing, and the rise of artificial intelligence is likely to extend this job destruction deep into the middle classes, with only the most caring, creative or supervisory roles remaining.”3 Several studies had already tallied up potential job destruction due to automation, and this time it wasn’t just physical labor but also cognitive functions previously believed immune to such forces.4 After all, horses fell behind in horsepower, not brainpower. As economists, we’ve heard these claims before. But while the specter of technological unemployment has loomed since the Luddites destroyed textile frames centuries ago, unemployment rates have been remarkably low. Business managers may be concerned about shedding jobs by adopting technologies like AI; however, we can take some comfort in the fact that farming jobs started to disappear over one hundred years ago, without corresponding long-term mass unemployment.

Tomorrow's Capitalist: My Search for the Soul of Business
by Alan Murray
Published 15 Dec 2022

Mankind had successfully moved from farmer to factory worker, and from factory worker to knowledge worker. But if machines took over knowledge work, what then? In their important 2013 study, “The Future of Employment: How Susceptible Are Jobs to Computerisation?,” Oxford professors Carl Benedikt Frey and Michael A. Osborne began by noting that “concern over technological unemployment is hardly a recent phenomenon. Throughout history, the process of creative destruction, following technological inventions, has created enormous wealth, but also undesired disruptions.”10 They tell an amusing anecdote about William Lee, who invented the stocking frame knitting machine in 1589 as a replacement for hand knitting.

Automate This: How Algorithms Came to Rule Our World
by Christopher Steiner
Published 29 Aug 2012

McAfee, wrote, “Many workers, in short, are losing the race against the machine.”3 The median worker, the average white-collar accountant, the MIT pair warn, should prepare to be replaced. Academics have made such predictions before. When machines began taking over manufacturing tasks in the 1920s and 1930s, John Maynard Keynes sounded the alarm for a “new disease” he termed “technological unemployment,” which happens when jobs can’t be replaced as fast as they’re eliminated by automation.4 Keynes’s warning was blown off as hyperbolic when it didn’t prove out. But perhaps his theory was simply ninety years early. Since the end of the recession in June 2009, according to Brynjolfsson and McAfee, corporations have spent 26 percent more on technology and software but haven’t raised their payrolls at all.

The Economics of Belonging: A Radical Plan to Win Back the Left Behind and Achieve Prosperity for All
by Martin Sandbu
Published 15 Jun 2020

In the other, the only way to keep up with the competition is to invest in machines to replace humans for the same tasks. It is easy to see how both types of market economy can threaten to leave some people behind—the first by maintaining a large population of low-paid labour, the second because of technological unemployment. Yet those who fear for the left behind are too often focused on the second. One of the biggest failures of many Western economies has been to encourage a labour market of the first kind out of fear of the consequences of the second. But the societies that have been most successful at protecting the economy of belonging—the European Nordics—have actively prevented the use of low-paid labour and instead embraced automation.

The Refusal of Work: The Theory and Practice of Resistance to Work
by David Frayne
Published 15 Nov 2015

Marx’s mixed views on technology foreshadowed a central premise in what some writers would later call the ‘end of work’ argument, which is based on the assumption that advances in production technologies are gradually eliminating the need for human labour (Rifkin, 2000). Within the existing structures of capitalist society, the displacement of workers by mechanisation and productivity growth is obviously a grave cause for concern. It leads to forced unemployment (often called ‘technological unemployment’), spelling poverty and social exclusion for thousands of people. However, the elimination of human labour by developments in production technology has also been celebrated by the ‘end of work’ authors, because it opens up the theoretical possibility of a huge expansion of free-time. There have been many versions of this core idea.

A Brief History of Motion: From the Wheel, to the Car, to What Comes Next
by Tom Standage
Published 16 Aug 2021

“Trauma Surgery and Traffic Policy in Germany in the 1930s: A Case Study in the Coevolution of Modern Surgery and Society.” Bulletin of the History of Medicine, vol. 80, no. 1 (Spring 2006): 73–94. Schlosser, E. Fast Food Nation: What the All-American Meal is Doing to the World. London: Penguin, 2007. Schwantes, C. A. “The West Adapts the Automobile: Technology, Unemployment, and the Jitney Phenomenon of 1914–1917.” Western Historical Quarterly, vol. 16, no. 3 (July 1985): 307–326. Shelton, T. “Automobile Utopias and Traditional Urban Infrastructure: Visions of the Coming Conflict, 1925–1940.” Traditional Dwellings and Settlements Review, vol. 22, no. 2 (Spring 2011): 63–76.

Road to Nowhere: What Silicon Valley Gets Wrong About the Future of Transportation
by Paris Marx
Published 4 Jul 2022

Part I: Quantifying the Impact of Major Sectors in 2005,” Atmospheric Environment 79, 2013. 23 Sovacool, “Energy Injustice and Nordic Electric Mobility,” p. 211. 24 Riofrancos, “What Green Costs.” 4. Uber’s Assault on Cities and Labor 1 Carlos A. Schwantes, “The West Adapts the Automobile: Technology, Unemployment, and the Jitney Phenomenon of 1914–1917,” Western Historical Quarterly 16:3, 1985, p. 314. 2 Ross D. Eckert and George W. Hilton, “The Jitneys,” Journal of Law and Economics 15:2, 1972, p. 296. 3 Ibid. 4 Travis Kalanick, “Uber’s Plan to Get More People into Fewer Cars,” TED, February 2016, Ted.com. 5 “Fireside Chat with Travis Kalanick and Marc Benioff,” Sales-force, September 2015, Salesforce.com. 6 Sam Harnett, “Words Matter: How Tech Media Helped Write Gig Companies into Existence,” in Beyond the Algorithm: Qualitative Insights for Gig Work Regulation, ed.

Two Nations, Indivisible: A History of Inequality in America: A History of Inequality in America
by Jamie Bronstein
Published 29 Oct 2016

On the other hand, she advocated for black state directors of black NYA activities (although she tolerated the payment of disproportionately low salaries).39 Like McLeod Bethune, the New Deal adjusted to the South’s ongoing commitment to white supremacy. BEYOND THE NEW DEAL The New Deal was an experiment in the use of government tools to solve economic problems, but Roosevelt encountered pressure from more radical suggestions for redistribution of income. Some who called for change pointed to technological unemployment; in the modern economy, some lost jobs were just not coming back, as the tractor could do a job faster than the hoe. Others argued that economic growth was hindered by lack of economic distribution.40 For example, the philosopher John Dewey headed the People’s Lobby, one of many groups to argue that the Great Depression had been caused by underconsumption as workers could not afford to purchase consumer goods.

The Age of Stagnation: Why Perpetual Growth Is Unattainable and the Global Economy Is in Peril
by Satyajit Das
Published 9 Feb 2016

China frequently uses workers from home on foreign projects, to take advantage of lower costs and avoid the employment conditions of the host country. Conflicts, sometimes violent, with the local workforce are common. Workers, irrespective of profession and skill, now face what John Maynard Keynes termed technological unemployment. The process was championed as reducing low-skilled monotonous jobs and increasing employment mobility, as well as providing greater employment and lifestyle choices. Economists lauded the new knowledge/bioengineered/clean and green (delete as required) economy. The displaced workers would become highly educated and skilled, finding new, intellectually challenging and highly paid jobs.

Noam Chomsky: A Life of Dissent
by Robert F. Barsky
Published 2 Feb 1997

Rev. of Language and Information, by Zellig Harris. Times Literary Supplement 23-29 Dec. 1988: 1430. Mattick, Paul. "Two Men in a BoatNot to Speak of the 8 Points." Living Marxism 6.1 (1941): 24-79. Melman, Seymour. Interview with the author. 26 July 1994. Noble, David. Progress without People: New Technology, Unemployment, and the Message of Resistance. Toronto: Between the Lines, 1995. Norris, Christopher. Uncritical Theory: Postmodernism, Intellectuals and the Gulf War. London: Lawrence, 1992. file:///D|/export3/www.netlibrary.com/nlreader/nlreader.dll@bookid=9296&filename=page_234.html (1 of 2) [4/16/2007 3:21:57 PM] Document Orwell, George.

Everything for Everyone: The Radical Tradition That Is Shaping the Next Economy
by Nathan Schneider
Published 10 Sep 2018

Kathi Weeks, The Problem with Work: Feminism, Marxism, Antiwork Politics, and Postwork Imaginaries (Duke University Press, 2011); Andy Stern and Lee Kravitz, Raising the Floor: How a Universal Basic Income Can Renew Our Economy and Rebuild the American Dream (PublicAffairs, 2016). 20. “Black Cooperatives and the Fight for Economic Democracy,” session at the Left Forum at the John Jay College of Criminal Justice (May 31, 2015); see also Marina Gorbis’s calls for “universal basic assets” rather than merely income. 21. On technological unemployment, see a summary in James Surowiecki, “Robopocalypse Not,” Wired (September 2017); on employment and inequality, see (among many other studies) Michael Förster and Horacio Levy, United States: Tackling High Inequalities, Creating Opportunities for All (OECD, 2014); on workplace surveillance, see Esther Kaplan, “The Spy Who Fired Me,” Harper’s (March 2015); on human computerization, see Brett M.

The Fourth Age: Smart Robots, Conscious Computers, and the Future of Humanity
by Byron Reese
Published 23 Apr 2018

To get there, the “this time is different” assumption will need to be ironclad. We will get to that in a moment. ASSUMPTION 2: Too many jobs will be destroyed too quickly. The “jobs will be destroyed too quickly” argument is an old one as well. In 1930, the economist John Maynard Keynes voiced it by saying, “We are being afflicted with a new disease . . . technological unemployment. This means unemployment due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour.” In 1978, New Scientist repeated the concern: The relationship between technology and employment opportunities most commonly considered and discussed is, of course the tendency for technology to be labour-saving and thus eliminate employment opportunities—if not actual jobs.

Possible Minds: Twenty-Five Ways of Looking at AI
by John Brockman
Published 19 Feb 2019

The message, in other words, does not adequately convey the stakes of the game. Wiener primarily warned of the social risks—risks stemming from careless integration of machine-generated decisions with governance processes and misuse (by humans) of such automated decision making. Likewise, the current “serious” debate about AI risks focuses mostly on things like technological unemployment or biases in machine learning. While such discussions can be valuable and address pressing short-term problems, they are also stunningly parochial. I’m reminded of Yudkowsky’s quip in a blog post: “[A]sking about the effect of machine superintelligence on the conventional human labor market is like asking how US-Chinese trade patterns would be affected by the Moon crashing into the Earth.

The Revenge of Analog: Real Things and Why They Matter
by David Sax
Published 8 Nov 2016

“There is no economic law that says that everyone, or even most people, automatically benefit from technological progress,” wrote economists Erik Brynjolfsson and Andrew McAfee in their groundbreaking 2012 book Race Against the Machine, which highlighted the growing gap between technological progress and job creation. “The threat of technological unemployment is real.” Brynjolfsson and McAfee are not technophobes gripped by a fear of progress. They point to previous disruptions in labor during the technological leaps of the industrial and mechanized ages, and show how these eventually led to greater middle-class wealth and job creation, as productivity increased.

The Price of Everything: And the Hidden Logic of Value
by Eduardo Porter
Published 4 Jan 2011

surplus survival Sweden, Swedes culture in The Pirate Bay and Swift, Jonathan Taiwan Tanzania, Tanzanians taxes energy faith and income taxicab drivers, tipping of Tea Party tea prices technology Digital Rights Management (DRM) information innovation and stocks ultrasound see also computers telenovelas telephone calls Televisa television advertising on television sets Templeton, Brad Tenenbaum, Joel Tennessee terrorism Texas, happiness in textile mills Tha Carter III (album) Thailand Thatcher, Margaret Theory of Economic Growth, The (Lewis) Theory of the Leisure Class (Veblen) The Pirate Bay tickets: airline for events time faith and free Times of India Time Warner tipping Titanic, lifeboats on TiVo tobacco see also smoking Togo trade barriers to traffic accidents Transportation Department, U.S. Trobriand Islands Truman, Harry trust faith and Turkey Turkmenistan twins, happiness of Ultimatum Game ultrasound technology unemployment United Airlines United Auto Workers United Kingdom United Nations United States carbon emissions of copyright in culture in divorce in drug abuse in free lunch in gas prices in happiness in health care in housing in illegal immigration to immigrant behavior in income and wages in life expectancy in music in 9/11 compensation in out-of-wedlock births in pharmaceutical industry in politics in polygamy in religion in safety issues in sex in sex ratios in slavery in speed limits in women’s work in work hours in vaccines value of women’s work Varian, Hal Veblen, Thorstein Veja Venables-Vernon, George, the second Baron Vernon vending machines versioning video recorders, digital Vietnam Vogue VoIP technology voting, voters wages executive faith and in Indonesia in London minimum of sports and pop stars time and of women see also income waiters, waitresses Waldfogel, Joel Wall Street Walmart Warner Bros.

Only Humans Need Apply: Winners and Losers in the Age of Smart Machines
by Thomas H. Davenport and Julia Kirby
Published 23 May 2016

It’s important to be clear that the Depression was the result of a massive failure of the financial system and not due to the automation of work that was proceeding apace in the nation’s factories. Still, the potential threat to jobs that automation also posed had certainly been noted. John Maynard Keynes, most famously, diagnosed in his 1930 essay “Economic Possibilities for Our Grandchildren” what he called a “new disease” in the world’s largest economies. He called it “technological unemployment” and explained that it was “due to our discovery of means of economizing the use of labor outrunning the pace at which we can find new uses for labor.” And a clever YouTube video, “No Humans Need Apply,” points out that it wouldn’t be that difficult for automation to lead to the same levels of unemployment—about 25 percent in the United States—found in the Depression.

Forward: Notes on the Future of Our Democracy
by Andrew Yang
Published 15 Nov 2021

It’s an honor and privilege to consider you friends and supporters. I hope you have the chance to meet each other in the days to come. I’m running for President as a Democrat in 2020 because I believe we must start having honest conversations about and formulate real solutions to the growing impact of technological unemployment/automation that has already displaced millions of Americans and will soon affect millions more. The elimination of 4 million manufacturing jobs in Ohio, Michigan, Pennsylvania, Wisconsin and other midwestern states gave us Donald Trump. The displacement of retail workers, truck drivers, fast food workers, call center workers, etc. will strain our society beyond repair.

Ghost Work: How to Stop Silicon Valley From Building a New Global Underclass
by Mary L. Gray and Siddharth Suri
Published 6 May 2019

Identifiers: LCCN 2018042557 (print) | LCCN 2018044155 (ebook) | ISBN 9781328566287 (ebook) | ISBN 9781328566249 (hardcover) | ISBN 9780358120575 (int. ed.) Subjects: LCSH: Labor supply—Effect of automation on. | Automation—Economic aspects. | Artificial intelligence—Economic aspects. | Technological unemployment. Classification: LCC HD6331 (ebook) | LCC HD6331 .G826 2019 (print) | DDC 331.1—dc23 LC record available at https://lccn.loc.gov/2018042557 Cover design by Mark R. Robinson Cover image © WIN-Initiative / Getty Images Gray photograph © Adrianne Mathiowetz Photography Suri photograph © Peter Hurley v1.0419 For Ila and George —M.L.G.

The AI Economy: Work, Wealth and Welfare in the Robot Age
by Roger Bootle
Published 4 Sep 2019

The employment of human labor definitely is taxed, not just through the imposition of income taxes on employees but also through employment taxes, such as National Insurance in the UK and social security taxes in other countries, on both employees and employers. Without a corresponding tax on robots and AI, the argument runs, the tax system is being far from neutral. It is actually encouraging the substitution of robots and AI for human labor.11 Accordingly, the tax system could be worsening the problems of technological unemployment, depressed wages, and increased inequality. Even if you do not buy the mass impoverishment case, which I don’t, the implication would still be diminished income for society as a result of a distorted allocation of resources. But what is neutral and not neutral in the tax system depends critically upon whether you regard the robots and AI systems that may replace human workers as “artificial workers” or items of capital investment.

Extreme Economies: Survival, Failure, Future – Lessons From the World’s Limits
by Richard Davies
Published 4 Sep 2019

CHAPTER 8: TALLINN NOTES Wassily Leontief The quote at the start of the chapter on p. 263 is from an essay, ‘Machines and Man’, written by Harvard economist Wassily Leontief for an issue of Scientific American devoted to automatic control of machines – see Leontief (1952). The two fears from technology: unemployment and division On the risk that technological progress will lead to mass unemployment, see Keynes (1930) and Leontief (1952), and for a survey of the history of these kinds of concerns, see Mokyr et al. (2015). The prediction of 30 per cent automation – 44 per cent for the low skilled – is from PwC (2018); see also Muro et al. (2019) for a Brookings Institution report on the US.

Bullshit Jobs: A Theory
by David Graeber
Published 14 May 2018

on the political ramifications of bullshitization and consequent decline of productivity in the caring sector as it relates to the possibility of a revolt of the caring classes Since at least the Great Depression, we’ve been hearing warnings that automation was or was about to be throwing millions out of work—Keynes at the time coined the term “technological unemployment,” and many assumed the mass unemployment of the 1930s was just a sign of things to come—and while this might make it seem such claims have always been somewhat alarmist, what this book suggests is that the opposite was the case. They were entirely accurate. Automation did, in fact, lead to mass unemployment.

Rise of the Machines: A Cybernetic History
by Thomas Rid
Published 27 Jun 2016

Dechert (Notre Dame, IN: University of Notre Dame Press, 1966), 98–99. 71.John Diebold, “Goals to Match Our Means,” in Dechert, Social Impact of Cybernetics, 4. 72.Curtis Gerald, Computers and the Art of Computation (Reading, MA: Addison-Wesley, 1972), 319. 73.“Automation: Jobs Change, Clamor Dies,” Chicago Tribune, October 26, 1969, B8. 74.Gregory R. Woirol, The Technological Unemployment and Structural Unemployment Debates (Westport, CT: Greenwood, 1996), 78. 75.David Fouquet, “Automation Held Threat to US Value Code,” Washington Post, May 12, 1964, A24. 76.Diebold, Beyond Automation, 10. 77.Fouquet, “Automation Held Threat.” 78.Diebold, Automation, 170. 79.Diebold, Beyond Automation, 206. 80.Kahn left Rand before publishing The Year 2000. 81.Herman Kahn and Anthony Wiener, The Year 2000: A Framework for Speculation on the Next Thirty-Three Years (London: Macmillan, 1967), 350. 4.

Digital Apollo: Human and Machine in Spaceflight
by David A. Mindell
Published 3 Apr 2008

Bilstein, Roger E., and Frank Walter Anderson. Orders of Magnitude: A History of the NACA and NASA, 1915–1990. NASA History Series. SP-4406. Washington, D.C.: Office of Management, Scientific and Technical Information Division, NASA, 1989. Bix, Amy Sue. Inventing Ourselves Out of Jobs?: America’s Debate over Technological Unemployment, 1929–1981. Baltimore: Johns Hopkins University Press, 2000. 314 Bibliography Black, Harold. ‘‘Stabilized Feedback Amplifiers.’’ Bell System Technical Journal 13 ( January 1934): 1–18. Blackburn, A. W. ‘‘Flight Testing Stability Augmentation Systems for High Performance Fighters.’’ SETP Quarterly Review 6, no. 1 (Summer 1957): 2.

Between Human and Machine: Feedback, Control, and Computing Before Cybernetics
by David A. Mindell
Published 10 Oct 2002

Am sober, intelligent, strictly attentive to business, never ask for time off, do not talk back, am not affected by bill of fare or poor cooking, in fact do not eat at all. Wages wanted, only 54 cents per day for 24 hours service. [Signed] Sperry Gyro Pilot. 9 “Helmsman regarded the course recorder as a kind of mechanical company spy,” Fortune magazine reported, “and the marine gyropilot as a wicked device meant to send them into technological unemployment.” 10 As Stuart Bennett noted in his study of instruments in the process industries, feedback devices were accompanied not only by claims of improved accuracy but also by social questions about obedience and reliability. 11 These advertisements portrayed the human steersman as a weak link in the system.

The Next Shift: The Fall of Industry and the Rise of Health Care in Rust Belt America
by Gabriel Winant
Published 23 Mar 2021

See also Medicare cost-productivity gap, 46 Cott, Nancy, 83 COVID-19, 263 Cowie, Jefferson, 27 Czap, Mary, 86 Day, Jared, 163 debt: and construction of new hospitals, 167–169, 171, 173, 175, 209, 235; and mergers and acquisitions wave of 1980s, 187, 249, 250; and precarity, 4, 263; and steel industry capital expansion, 38; and steel strike of 1959, 86 debt financing, 167 deindustrialization: and health care, 18, 19, 260; as historical process, 17, 21, 134, 245; and technological unemployment, 185; and welfare state, 181; and working-class community, 99 Denenberg, Herbert, 166 Denominational Ministry Strategy, 190 Department of Health and Human Services (HHS), 223–226 Department of Public Assistance, 127 Detre, Thomas, 245–246, 248 Detroit: and African American kinship networks, 120; in comparison with Pittsburgh, 34, 100, 102, 112, 159, 182; and deindustrialization, 195, 206; and growth of health care and social assistance sector, 5, 6; and New Deal order, 8 diagnostic related groups (DRGs), 226, 227 Dillard, Annie, 38, 40 discipline: and social policy, 11, 15; and collective child-rearing, 121; discipline slips, 43, 54, 62–63; and domesticity, 70–75, 84, 89–96; of the market, 227; in steel workplace, 26, 41, 238, 239 disinvestment, 16, 107, 125, 202, 245 divorce, 195, 214 Dohanic, Pete, 46, 47 domesticity, 64, 73, 77, 78, 80, 96, 116, 222 domestic emigration, 195 domestic violence, 200, 201 domestic work, 90, 116, 152, 179, 223, 232 Donora, 114, 120 Dravo, 34 Dravosburg, 58, 86 dualization of economy, 2.

Computer: A History of the Information Machine
by Martin Campbell-Kelly and Nathan Ensmenger
Published 29 Jul 2013

Commentators have often failed to realize the importance of the CPC, not least because it was called a “calculator” instead of a “computer.” Watson insisted on this terminology because he was concerned that the latter term, which had previously always referred to a human being, would raise the specter of technological unemployment. It was why he had also insisted on calling the Harvard Mark I and the SSEC “calculators.” But the fact remained that, as far as effective scientific-computing products were concerned, IBM had the lead from the very beginning. Thus by 1949 IBM had built up an excellent R&D capability in computers.

Capitalism in America: A History
by Adrian Wooldridge and Alan Greenspan
Published 15 Oct 2018

See also specific decisions FDR and, 248–49, 256–57 “official liberalism” of, 159–60, 163, 166 in 1920s, 193–94 sushi cake, 345 Sutch, Richard, 85 Swan, Joseph, 105 Swarthout, Glendon, 269 Sweden, entitlement reform in, 27, 440–42 Swift, Earl, 286 Swift, Gustavus Franklin, 119 Taft, Robert, 249 Taft, William Howard, 183, 184, 188 Taft-Hartley Act of 1947, 22, 289 Talleyrand, Charles Maurice de, 31 Tarbell, Ida, 124, 129, 176 Tariff Act of 1930, 230–31, 233 tariffs, 7, 31, 65, 191, 230–32, 233, 263, 278, 416 TARP (Troubled Asset Relief Program), 385–86 taxes, 186, 329, 331, 372, 416–17. See also income taxes Taxi Driver (movie), 321 Taylor, Charlie, 108 Taylor, Frederick, 147, 317 Taylor, John, 384 Taylor, Zachary, 267 Tea Party, 406, 415 technological unemployment, 21–22 technology vs. entitlements, 438–39 Tedlow, Richard, 106 telegraph, 55–57, 109, 127 first transatlantic cable, 16, 19, 56–57 telephone, 109–10 Teller, Edward, 284 Tennessee Valley Authority (TVA), 244, 274 Terman, Frederick, 351–52 Terry, Eli, 72 Tesla, 423 Tesla, Nikola, 11 Texas annexation, 5, 40 Texas draught of 1887, 154 textile industry, 49, 69, 71, 214 Thiel, Peter, 423, 439 Thirteenth Amendment, 86 Thomas, Norman, 245 Thompson, Joe, 263 Thomson, J.

WTF?: What's the Future and Why It's Up to Us
by Tim O'Reilly
Published 9 Oct 2017

Sure enough, we are indeed once again hearing the chorus of pessimism and doubt. Automation is going to destroy white-collar jobs in the same way it once destroyed factory jobs. We have an economy that relies on growth, but the age of growth is over. And so on. Keynes presciently gave a name to the heart of our current angst: technological unemployment. He defined it as our inability to find new uses for labor as quickly as we are finding ways to eliminate the need for it. He concluded, “But this is only a temporary phase of maladjustment.” Like Keynes, I remain optimistic. There has already been enormous dislocation, with far more ahead, but if we make the right choices as a society, we will come through it in the end.

Superintelligence: Paths, Dangers, Strategies
by Nick Bostrom
Published 3 Jun 2014

Just as many Muslims and Jews shun food prepared in ways they classify as haram or treif, so there might be groups in the future that eschew products whose manufacture involved unsanctioned use of machine intelligence. What hinges on this? To the extent that cheap machine labor can substitute for human labor, human jobs may disappear. Fears about automation and job loss are of course not new. Concerns about technological unemployment have surfaced periodically, at least since the Industrial Revolution; and quite a few professions have in fact gone the way of the English weavers and textile artisans who in the early nineteenth century united under the banner of the folkloric “General Ludd” to fight against the introduction of mechanized looms.

Artificial Intelligence: A Modern Approach
by Stuart Russell and Peter Norvig
Published 14 Jul 2019

In 7th century BCE Greek mythology, a robot named Talos was built by Hephaistos, the Greek god of metallurgy, to protect the island of Crete. The legend is that the sorceress Medea defeated Talos by promising him immortality but then draining his life fluid. Thus, this is the first example of a robot making a mistake in the process of changing its objective function. In 322 BCE, Aristotle anticipated technological unemployment, speculating “If every tool, when ordered, or even of its own accord, could do the work that befits it... then there would be no need either of apprentices for the master workers or of slaves for the lords.” In the 3rd century BCE an actual humanoid robot called the Servant of Philon could pour wine or water into a cup; a series of valves cut off the flow at the right time.

…

The Luddites were not against technology per se; they just wanted the machines to be used by skilled workers paid a good wage to make high-quality goods, rather than by unskilled workers to make poor-quality goods at low wages. The global destruction of jobs in the 1930s led John Maynard Keynes to coin the term technological unemployment. In both cases, and several others, employment levels eventally recovered. The mainstream economic view for most of the 20th century was that technological employment was at most a short-term phenomenon. Increased productivity would always lead to increased wealth and increased demand, and thus net job growth.

…

A., 586, 1114 Tattersall, C., 206, 1114 Tavener, S., 222, 1089 taxi, 60, 61, 403 automated, 75, 228, 403, 1070 taxonomic hierarchy, 41, 335, 357 Taylor, A. D., 638, 1114 Taylor, C., 1030, 1092 Taylor, G., 329, 1114 Taylor, M., 357, 1113 Taylor, P., 900, 1114 Taylor, R., 986, 1104 Taylor, W., 190, 1090 Taylor expansion, 942 TD-GAMMON (backgammon program), 37, 224, 867 technological unemployment, 983, 1049 teddy bear, 1033 Tedrake, R., 986, 1114 Tegmark, M., 838, 1110 Teh, Y. W., 516, 837, 1099, 1108 telephone, 914 telepresence robots, 978 Teller, A., 160, 475, 1106 Teller, E., 160, 475, 1106 Teller, S., 984, 986, 1088, 1114 Tellex, S., 986, 1114 Templeton Foundation, 1037 temporal-difference learning, 844–848, 869 temporal inference, 483–491 temporal invariance, 811 temporal logic, 273 temporal projection, 267 temporal reasoning, 134–142, 255–264, 340–343, 479–517 Tenenbaum, J.

Architects of Intelligence
by Martin Ford
Published 16 Nov 2018

So, they’re saying this, and I didn’t really realize that this was the case before I heard them say it. They say this is something on the scale of electricity, the steam engine, or the electric motor. One thing I’m worried about, and this was before talking to the economists, is the problem of technological unemployment. The idea that technology progresses rapidly and the skills that are required by the new economy are not matched by the skills of the population. A whole proportion of the population suddenly doesn’t have the right skills, and it’s left behind. You would think that as technological progress accelerates, there’d be more and more people left behind, but what the economists say is that the speed at which a piece of technology disseminates in the economy is actually limited by the proportion of people who are not trained to use it.

Slouching Towards Utopia: An Economic History of the Twentieth Century
by J. Bradford Delong
Published 6 Apr 2020

But the upward leap in economic growth after 1870 meant that working classes all over the globe were also becoming richer and richer than their predecessors. That Marx got it wrong is not surprising. The fact is he was a theorist with only one example of industrialization to draw on, Britain. And in Britain, large and visible sections of the working class were worse off in 1840 than in 1790. Technological unemployment was a powerful thing. The construction of dark satanic mills in Lancashire left rural weaving skills useless and populations impoverished. There was a window of time when some of, even much of, Marx’s dark brooding seemed plausible. In 1848 the belief that market capitalism necessarily produced a distribution of income that was unbearable was not reasonable.6 By 1883, when Marx died, such a belief was indefensible.

The Transhumanist Reader
by Max More and Natasha Vita-More
Published 4 Mar 2013

We have tools right now (symbolic math programs, cad/cam) that release us from most low-level drudgery. Put another way: the work that is truly productive is the domain of a steadily smaller and more elite fraction of humanity. In the coming of the Singularity, we will see the predictions of true technological unemployment finally come true. Another symptom of progress toward the Singularity: ideas themselves should spread ever faster, and even the most radical will quickly become commonplace. And what of the arrival of the Singularity itself? What can be said of its actual appearance? Since it involves an intellectual runaway, it will probably occur faster than any technical revolution seen so far.

Basic Economics
by Thomas Sowell
Published 1 Jan 2000

Ironically, it is in countries with strong job security laws, like Germany, where it is harder to find a new job. Fewer job opportunities in such countries often take the form of fewer hours worked per year, as well as higher unemployment rates and longer periods of unemployment. One form of unemployment that has long stirred political emotions and led to economic fallacies is technological unemployment. Virtually every advance in technological efficiency puts somebody out of work. This is nothing new: By 1830 Barthélemy Thimonnier, a French tailor who had long been obsessed with the idea, had patented and perfected an effective sewing machine. When eighty of his machines were making uniforms for the French army, Paris tailors, alarmed at the threat to their jobs, smashed the machines and drove Thimonnier out of the city.{389} Such reactions were not peculiar to France.

The Age of Surveillance Capitalism
by Shoshana Zuboff
Published 15 Jan 2019

For example, a 2004 white paper from the Kansas City Federal Reserve singles out “voice recognition” as a significant threat to future employment rates: “Advances in voice recognition technology, expert systems, and artificial intelligence may eventually allow computers to handle many customer service jobs and perhaps even routine x-ray screening.” See C. Alan Garner, “Offshoring in the Service Sector: Economic Impact and Policy Issues,” Economic Review 89, no. 3 (2004): 5–37. Frey and Osborne’s much-cited 2013 study of technological unemployment sounded the same theme: “Moreover, a company called SmartAction now provides call computerisation solutions that use ML technology and advanced speech recognition to improve upon conventional interactive voice response systems, realising cost savings of 60 to 80 percent over an outsourced call center consisting of human labour.”

Palo Alto: A History of California, Capitalism, and the World
by Malcolm Harris
Published 14 Feb 2023

The service sector is the choice site for job creation through such super-exploitation because the wages of service workers make up a relatively large share of the final price that consumers pay.13 By cutting the ribbon holding together the suite of labor laws, the lean crabs freed workers to “create demand for their labor at the expense of their incomes.” The result has been, rather than the much-feared plague of technological unemployment, a pandemic of underemployment. It’s a mistake, then, to think of Uber’s carcinized business strategy as driven by its scandal-prone leader, Travis Kalanick, and his bad personality. When author Brad Stone asked Kalanick why the company raised over $10 billion in the previous two years alone, the billionaire’s answer comes off as more resigned than pumped: “If you didn’t do it, it would be a strategic disadvantage, especially when you’re operating globally,” he told Stone.

The Best of Best New SF
by Gardner R. Dozois
Published 1 Jan 2005

Coming up are two new collections, The Periodic Table of SF and Michael Swanwick’s Field Guide to the Mesozoic Megafauna. He’s had stories in our First, Third, Fourth, Seventh and Ninth through Seventeenth annual collections. Swanwick lives in Philadelphia with his wife, Marianne Porter. He has a Web site at http://www.michaelswanwick.com. We’ve been worried about technological unemployment for decades, but, as the bleak little story that follows suggests, now there may be another threat to your job security: dead people. Back from the grave and looking for work. . . . THREE BOY ZOMBIES in matching red jackets bused our table, bringing water, lighting candles, brushing away the crumbs between courses.

Demanding the Impossible: A History of Anarchism
by Peter Marshall
Published 2 Jan 1992

To the objection that some would not want to work without being forced to, he replies that since we give a minimum of food and shelter and medical attention to criminals, why then should we deny it to the lazy and stubborn. He also recognizes that the quality of work is all important in order to make it attractive and he calls for work for the amateur and not the automaton. ‘As social life becomes mature,’ he insists, ‘the social unemployment of machines will become as marked as the present technological unemployment.’39 At the same time, he acknowledges the potential emancipatory effect of technology in alleviating drudgery and increasing personal autonomy. Finally, he proclaims the slogan ‘Socialize creation!’ – creativity should not be the prerogative of a small caste, but the practice of all. Such changes cannot occur without a major shift in consciousness, without a move from a mechanical to an organic ideology.