job automation

The Origins of the Urban Crisis

by Sugrue, Thomas J.

4.2 Black Workers in Selected Detroit-Area Steel Plants, 1965 4.3 Black Enrollment in Apprenticeship Programs in Detroit, 1957–1966 5.1 Automation-Related Job Loss at Detroit-Area Ford Plants, 1951–1953 5.2 Decline in Manufacturing Employment in Detroit, 1947–1977 5.3 Percentage of Men between Ages

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improve working conditions, reduce hours, and improve workplace safety. It was simply “a better way to do the job.”16 Certainly automated production replaced some of the more dangerous and onerous factory jobs. At Ford, automation eliminated “mankilling,” a task that demanded high speed and involved tremendous risk. “Mankilling” required a worker to remove

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quench tank, all within several seconds. In Ford’s stamping plants, new machines loaded and unloaded presses, another relatively slow, unsafe, and physically demanding job before automation. Here automation offered real benefits to workers.17 5.2. When Ford introduced automated assembly lines in its newly opened Lima, Ohio plant in 1954, it

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1953 and 1955, when Ford announced the construction of new engine production facilities at Brookpark Village, Ohio, and in Lima, Ohio.23 The effects of automation on job opportunities in communities like Detroit were a well-guarded corporate secret. Responding to labor union criticism of automation, employers downplayed the possibility of significant

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job loss. When Ford began automating and decentralizing the Rouge plant, John Bugas, Ford’s vice president for industrial relations, told workers that they had nothing to fear. “I

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employees in the Rouge operations resulting from the building of new facilities will be substantial.” Ford labor relations official Manton Cummins dismissed claims that automation led to job loss as a union-led “scare campaign.” Yet the only detailed statistics on automation and its effects on employment, a UAW-sponsored study of

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campaigns, industry publications like Automation magazine argued that automation reduced labor costs, but by the mid-1950s, they seldom raised labor as a rationale, because automation’s effect on jobs had become a sensitive political issue. Instead, the magazine’s editors went on the defensive against charges that

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automation led to job loss. In February 1960, for example, the magazine noted that “lest anyone be deluded into thinking of [the Plymouth Detroit assembly plant] as a workerless

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there would be “no direct way I can imagine to avoid by private means the dislocations that come from technological obsolescence.”26 TABLE 5.1 Automation-Related Job Loss at Detroit-Area Ford Plants, 1951–1953 General Motors Vice President Louis Seaton was even more sanguine than Ford, but more disingenuous. He

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that the number of auto industry jobs nationwide would fall because of automation. Some economists argued that over the long run, the introduction of automated processes would increase jobs nationwide. Aggregate employment statistics, however, masked profound local variation. Local economies in places like Detroit reeled from the consequences of automation-caused plant

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workers. Labor leaders also became staunch advocates of government funding for education and retraining programs to prepare workers for new automated jobs. Contract provisions guaranteed that workers who lost their jobs because of automation would be protected by seniority and transferred to other jobs. Their programs offered remedies for the symptoms of automation, rather

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: Labor and Taxes Automation was not the only force contributing to job loss in Detroit. Smaller firms that did not automate production or suffer automation-related job losses still fled the city in increasing numbers in the 1950s. Labor relations were especially important in motivating firms to relocate outside of Detroit, or

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industries. Thus they were less likely to have accumulated enough seniority to protect their jobs. And because blacks were concentrated in unskilled, dangerous jobs—precisely those affected by automation—they often found that their job classifications had been eliminated altogether.67 By the early 1960s, observers noted that a seemingly permanent class

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and to federal courtrooms. In February 1950, James Simmons, a worker in the Plastics Department at the Rouge, warned that the introduction of automated machinery would put jobs at risk. Simmons saw changes in the Rouge as “part of a pattern that calls for taking these jobs to new unorganized sections of

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cause of unemployment in Detroit. Social service and employment agencies in the city turned their energies toward what they perceived as a growing gap between automated jobs and workers who were so inadequately trained or educated that they could not qualify for those jobs. Black agencies were especially concerned about the effect

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of automation on black job prospects. The Detroit Urban League (DUL) ran the most important black employment agency in the city. From its founding in 1916 through the 1940s

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men held positions as unskilled laborers; three decades later, a mere one in twelve held unskilled jobs. This decline was primarily a consequence of automation: manufacturers eliminated unskilled jobs throughout the period (see Chapter 5). The fraction of blacks employed in the service sector also fell significantly in the postwar period. More

Surviving AI: The Promise and Peril of Artificial Intelligence

by Calum Chace  · 28 Jul 2015  · 144pp  · 43,356 words

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

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analysis to make us more efficient and more effective. But this improvement means change, and change is usually uncomfortable. There are concerns that it is automating our jobs out of existence, and that this will increase rapidly in the coming few years. There are concerns that AI is de-humanising war, and

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people and policy makers with an even bigger concern than digital disruption. It may render most of us unemployed, and indeed unemployable, because our jobs have been automated. Automation Automation has been a feature of human civilisation since at least the early industrial revolution. In the 15th century, Dutch workers threw their shoes into

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individual who was dismissed from a particular job, there was generally the chance to retrain, or find new work elsewhere. The idea that each job lost to automation equates to a person rendered permanently unemployed is known as the Luddite Fallacy. This is unfair to the Luddites, who weren’t advancing a

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were simply protesting about the very real danger of starvation in the short term. It is also not true that Maynard Keynes argued that automation would destroy jobs any time soon. The essay quoted above goes on to say, “But this is only a temporary phase of maladjustment. All this means in

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daily bread, leisure is a longed-for sweet – until they get it.” This time it’s different? Some people argue that soon, people automated out of a job may not find new employment, thanks to the rapid advances in machine learning, and the availability of increasingly powerful and increasingly portable computers. MIT

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job churn or economic singularity If computers steal our old jobs, perhaps we can invent lots of new ones? In the past, people whose jobs were automated turned their hands to more value-adding activity, and the net result was higher overall productivity. The children of people who did back-breaking farm

The Means of Prediction: How AI Really Works (And Who Benefits)

by Maximilian Kasy  · 15 Jan 2025  · 209pp  · 63,332 words

might often be quite thin. Office computers might have increased the marginal productivity of high-wage workers, but they also automated away jobs of certain administrative staff. Knitting machines might have automated away the jobs of highly trained artisans, but they increased demand for workers with less training. How should we evaluate such technological

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Prize in Economic Sciences), Larry Katz, and others, technological change has systematically favored workers with higher levels of education, increasing their marginal productivity, while automating away the jobs of workers with lower levels of education, decreasing their marginal productivity. This has led to a widening gap of wages across education groups, and

Mattering: The Secret to Building a Life of Deep Connection and Purpose

by Jennifer Breheny Wallace  · 13 Jan 2026  · 206pp  · 68,830 words

downturn that worsened in the 1990s when environmental protections led to widespread mill closures and high unemployment rates. In the 1990s and 2000s, when manufacturing jobs were automated and offshored, millions of jobs were lost, leaving entire regions struggling with economic decline that persists today. In the early to mid 2010s, coalmining

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, 194 practicing, 126–27 to self, 137–38 teaching, 135–36 work and, 183 Augsburger, David W., 136 Authentic Connections Groups, 76 authentic relationships, 76 automation, job losses from, 165 bailing, 127 Baldwin, James, 74 Banana Cabaret comedy club, 205 Barbershop Books, 222 barbershops, 222–24 Barry-Wehmiller, 194–95 Bates Trucking

AI Superpowers: China, Silicon Valley, and the New World Order

by Kai-Fu Lee  · 14 Sep 2018  · 307pp  · 88,180 words

answers, trying to peer into the future with a mixture of childlike wonder and grown-up worries. We want to know what AI automation will mean for our jobs and for our sense of purpose. We want to know which people and countries will benefit from this tremendous technology. We wonder whether

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. A pair of researchers at Oxford University kicked things off in 2013 with a paper making a dire prediction: 47 percent of U.S. jobs could be automated within the next decade or two. The paper’s authors, Carl Benedikt Frey and Michael A. Osborne, began by asking machine-learning experts to

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probability model to find what percentage of jobs were at “high risk” (i.e., at least 70 percent of the tasks associated with the job could be automated). As noted, they found that in the United States only 9 percent of workers fell in the high-risk category. Applying that same model

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professional background. Many of the preceding studies were done by economists, whereas I am a technologist and early-stage investor. In predicting what jobs were at risk of automation, economists looked at what tasks a person completed while going about their job and asked whether a machine would be able to complete

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of the world.” This prediction is based on the makeup of China’s workforce, as well as a gut-level intuition about what kinds of jobs become automated. Over one-quarter of Chinese workers are still on farms, with another quarter involved in industrial production. That compares with less than 2 percent

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the recent history of automation. Looking back at the last hundred years of economic evolution, blue-collar workers and farmhands have faced the steepest job losses from physical automation. Industrial and agricultural tools (think forklifts and tractors) greatly increased the productivity of each manual laborer, reducing demand for workers in these sectors

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THE ALGORITHMS AND RISE OF THE ROBOTS This hard reality about algorithms and robots will have profound effects on the sequence of AI-induced job losses. The physical automation of the past century largely hurt blue-collar workers, but the coming decades of intelligent automation will hit white-collar workers first. The

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strike on cognitive labor, robotics’ assault on manual labor is closer to trench warfare. Over the long term, I believe the number of jobs at risk of automation will be similar for China and the United States. American education’s greater emphasis on creativity and interpersonal skills may give it an employment

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work for top performers or low-paying jobs in tough industries. The risk of replacement cited in the earlier figures reflects this. The most difficult jobs to automate—those in the top-right corner of the “Safe Zone”—include both ends of the income spectrum: CEOs and healthcare aides, venture capitalists and

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. In this envisioned world of fluid retraining, unemployed insurance brokers can use online education platforms like Coursera to become software programmers. And when that job becomes automated, they can use those same tools to retrain for a new position that remains out of reach for AI, perhaps as an algorithm engineer or

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build up. Uncertainty over the pace and path of automation makes things even more difficult. Even AI experts have difficulty predicting exactly which jobs will be subject to automation in the coming years. Can we really expect a typical worker choosing a retraining program to accurately predict which jobs will be safe

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’t hold. Blindly pursuing profits without any thought to social impact won’t just be morally dubious; it will be downright dangerous. Fink referenced automation and job retraining multiple times in his letter. As an investor with interests spanning the full breadth of the global economy, he sees that dealing with AI

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.com/research/report/artificial-intelligence-trends-2018/. a dire prediction: Carl Benedikt Frey and Michael A. Osborne, “The Future of Employment: How Susceptible Are Jobs to Automation,” Oxford Martin Programme on Technology and Employment, September 17, 2013, https://www.oxfordmartin.ox.ac.uk/downloads/academic/future-of-employment.pdf. just 9 percent

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of jobs: Melanie Arntz, Terry Gregory, and Ulrich Zierahn, “The Risk of Automation for Jobs in OECD Countries: A Comparative Analysis,” OECD Social, Employment, and Migration Working Papers, no. 189, May 14, 2016, http://dx.doi.org/10.1787

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/5jlz9h56dvq7-en. 38 percent of jobs: Richard Berriman and John Hawksworth, “Will Robots Steal Our Jobs? The Potential Impact of Automation on the UK and Other Major Economies,” PwC, March 2017, https://www.pwc.co.uk/economic-services/ukeo/pwcukeo-section-4-automation-march

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inequality in, 170–72, 200 internet ecosystem of, 24–28, 40, 43–44, 46, 49–50. See also China’s alternate internet universe jobs at risk of automation in, 159–60 low-cost exports and, 146 medical diagnosis in, 114 privacy protection in, 124, 125 reemergence of, 180–81 scarcity mentality, 27

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, 3, 11 traffic accidents in, 101 U.S. competition with. See China and U.S., competition between China and U.S., competition between, 81–103 automation and jobs at risk, 165–67, 168 autonomous AI and, 130–31, 134–36 business AI and, 111–12, 116, 136 China’s advantages in, 14

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and, 106 deep-learning breakthroughs and, 4–5 general purpose technologies (GPTs), 148–55 global economic inequality, 146, 168–70, 172 intelligent vs. physical automation, 167–68 job loss, two kinds of, 162–63 job losses, bottom line, 164–65 job loss studies, 157–61 jobs and inequality crisis, 145–47 machine

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X, 117 iron rice bowl, 67 Italy, 85, 191–92 J Japan, 20, 229 Jesuits, 29 JingChi, 135 Jinri Toutiao. See Toutiao (news platform) job displacement by automation, 160, 162, 204. See also under economy and AI Jobs, Steve, 26, 32, 33, 226 jobs, threat to. See risk-of-replacement graphs; unemployment

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’s hands-off approach, 18, 229 great decoupling and, 150, 202 inequality within, 170–72, 199–200 inheritance of technological skillsets in, 33 jobs at risk of automation in, 157–60, 164 mobile payments in, compared to China, 75–77 privacy protection in, 125 self-driving cars in, 133 spending on research

Work in the Future The Automation Revolution-Palgrave MacMillan (2019)

by Robert Skidelsky Nan Craig  · 15 Mar 2020

person services, notably healthcare, care work and so on. How many of these jobs will be created? Why should their number equal the total of jobs automated? For creative industries, a winner-takes-all projection is quite common. Top artists get top pay and ordinary ones get nothing, or almost nothing. The

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that the adoption of the technology itself will in return be mediated, in part, by those attitudes. James Bessen describes the ways in which automation has changed jobs, and in what ways this is likely to continue or develop. He argues that specific jobs or categories of work rarely become obsolete in

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their entirety—rather, they evolve as technology becomes available to automate particular elements of the work. In deciding whether automation creates or destroys jobs, the decisive factor is demand rather than technology. 1 Introduction 5 What are the advantages of technology? Often people say, ‘It is obvious

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a route to a superior ‘post-work’ society (Gorz 1985). Such concerns and hopes have resurfaced in the present, due to predictions of mass job losses via automation (see Spencer 2018). The evolution of machine learning and artificial intelligence, it is claimed, will allow for the replacement of human workers across myriad

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rather than complete automation. Second, partial automation can lead to increases in employment in affected industries as well as decreases. Third, even if automation does not destroy jobs on the net, it will still be highly disruptive because people need to learn new jobs and skills in order to remain employed. First

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, it is important to distinguish between automating a task and automating a job. Jobs involve many different tasks, often very diverse skills. Because of that, it is relatively rare that a job will be completely automated. For instance, I looked at the number of detailed occupations listed in the 1950

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of technological obsolescence, when the industry was replaced. There is no longer ‘telegraph operators’ listed as a category. Only one occupation was completely automated, and that was the job of elevator operator. Now we are seeing machine learning, where we have all these capabilities, where machines can do better than humans on

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truck drivers and warehouse workers are going to be completely automated. Given that most of the automation is partial, we need to recognise that automation can create jobs and, in some cases, will. Even in the affected industries, jobs can increase. Look, for example, at the US textile industry (Bessen 2015, 2019

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). We are accustomed to associating automation with terrible job losses in industries such as textiles and that has been the experience of the last several decades, but it was not the case earlier

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look at the employment of production workers in cotton textiles, the nineteenth century and well into the twentieth century saw a high rate of automation accompanied by rapid job growth. This is an interesting puzzle. What changed here? Demand changed. Because of automation, less labour was required to produce a yard of

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coming along. The general takeaway is that demand matters. Repeatedly over the last 200 years we have had various people concerned about the effect of automation on jobs. These predictions have typically not been borne out. That is not a reason to say that predictions today are necessarily wrong. I think the

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about. References Bessen, J. (2015). Learning by Doing: The Real Connection Between Innovation, Wages, and Wealth. Yale University Press. Bessen, J. E. (2016). How Computer Automation Affects Occupations: Technology, Jobs, and Skills. Boston Univ. school of Law, Law and Economics Research Paper, 15–49 Bessen, J. E. (2019 forthcoming

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). Automation and Jobs: When Technology Boosts Employment. Economic Policy. 10 Attitudes to Technology: Part 2 Carl Benedikt Frey I’m going to spend the next 15 minutes of

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a lot of things that require interaction with unstructured environments and irregular objects. For example one of the last things we are likely to automate is the jobs of janitors. In part, we can circumvent some of these bottlenecks by task simplification. For example we didn’t automate the work of laundresses

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electric washing machine, which does an entirely different set of tasks, but still accomplishes the same goal: clean clothing. And similarly, we didn’t automate away the jobs of lamplighters by building robots capable of climbing lamppost. One reason why many commentators u ­ nderestimate 1 Frey and Osborne (2017). 92 C. B

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case. Simplification is mostly how automation happens. As some of you will know, we reached the conclusion that roughly 47 percent of American jobs are exposed to automation in our 2013 paper. Our finding has often been taken to suggest that all of these jobs are going to disappear in a couple

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big data. Now, it has been argued that we shouldn’t worry too much about automation because individual tasks are likely to be automated rather than entire jobs. However, many jobs, like those of elevator operators, lamplighters, switchboard operators, farm labourers, and car washers, just to name a few, have been fully automated

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on paper, the 10 Attitudes to Technology: Part 2 93 i­mplication is not the end of work. One reason is that new jobs and tasks appear as automation progresses. Few of today’s jobs existed in 1750 at the dawn of the Industrial Revolution. And job titles like robot engineer, database

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Caused by Automation. Pew Research Center. Retrieved from http://www.pewresearch.org/fact-tank/2017/10/09/most-americanswould-favor-policies-to-limit-job-and-wage-lossescaused-by-automation/ Part IV Possibilities and Limitations for AI: What Can’t Machines Do? 11 What Computers Will Never Be Able To Do Thomas Tozer

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on. In an age of automation, imagine a company boss announcing that ‘this week’s lucky person is Joan Smith in accounts, because her job has been automated’. The lucky winners in this scenario are then given the option of going on permanent leave with a full salary, continuing to do aspects

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, 1, 4, 53–62, 73, 75 Aubrey, 184 Austria, 68, 196 Authenticity, 116 Authority, 120, 165 Automation restrictions on, 95 speed of, 21, 137 task automation vs job automation, 92, 93, 110, 141 Autonomous cars, 114, 115, 118 Autor, David, 59, 126 Autor Levy Murnane (ALM) hypothesis, 126–128, 131 B Bailey

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Organisation (ILO), 193 Internet of Things, 139, 191 Investment in capital, 114 in skills, 70 J Japan, 117 Jensen, C, 55 Job guarantee, 172 Jobs, Steve, 73 Journalism automation of, 118 clickbait, 118 Juries, algorithmic selection of, 150, 153 K Karstgen, Jack, 196 Kasparov, Garry, 91, 112, 129, 130 207 Katz, Lawrence

Lessons-Learned-in-Software-Testing-A-Context-Driven-Approach

by Anson-QA

costs are probably the most common problem that automated regression test efforts face. Maintenance costs alone should convince you to mistrust the tales that automation will turn your job into a vacation. Lesson 118: Test automation is a software development process Test automation projects often fail because of a lack of discipline

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a nonprogrammer) and someone else isn't certified but can program, don't be surprised if you're not the one who gets the test automation job. Your certification can carry you only so far. On balance, we think the software testing and software quality certification efforts have been beneficial to the

Always Day One: How the Tech Titans Plan to Stay on Top Forever

by Alex Kantrowitz  · 6 Apr 2020  · 260pp  · 67,823 words

software can watch your screen as you work and, with some labeling, automate your tasks. UiPath and its counterparts are on track to automate work across millions of jobs in the coming years, making the chorus of F-yous a bit jarring. Months before the show, I heard rumblings that UiPath had

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robotics floor from above. In the same time Amazon has added the two hundred thousand robots, it’s added three hundred thousand human jobs. Amazon’s push toward automation may not be sending its associates to the unemployment lines, but it is forcing them to navigate constant change, which can be both

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. “Amazon Scraps Secret AI Recruiting Tool That Showed Bias Against Women.” Reuters. Thomson Reuters, October 9, 2018. https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G. J. Robert Oppenheimer: Ratcliffe, Susan. Oxford Essential Quotations. Oxford, UK: Oxford University

Economic Dignity

by Gene Sperling  · 14 Sep 2020  · 667pp  · 149,811 words

significant—estimates of job loss. The OECD estimates that only 9 percent of U.S. jobs are at risk from automation.16 Similarly, analysis by McKinsey & Company found that fewer than 5 percent of jobs could be completely automated.17 My goal is not to litigate which side is right in this ongoing debate

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workers who, through an extensive process, can establish they lost their job due to trade. Yet why should it matter if someone lost their job due to trade, automation, AI, some combination of those factors, or simply changing consumer trends? Our goal should be to help people find a new career, not

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also be more effective if it was available before job loss hit. While regional strategies are critical when there is concentrated geographic job loss, jobs dislocated by automation—such as autonomous cars and trucks—could often be dispersed. A broad UBI to Rise can be helpful to such workers even if their

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not only be looking for every option to help people in the workplace but also be imagining how we can use AI and automation to both create new jobs and better address national challenges. Consider a few ideas. Brynjolfsson often cites Iora Health, winner of MIT’s Inclusive Innovation Challenge—a contest

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people pursue their passions, purpose, and potential. If we prioritize meaningful work, it is also worth considering whether our tax code is actually favoring automation over jobs. Perhaps Bill Gates had not thought through all the policy angles when he floated his much-criticized idea of a “robot tax” in 2017.80

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video, 18:51, November 28, 2016, https://www.youtube.com/watch?v=LCxcnUrokJo. 16. Melanie Arntz, Terry Gregory, and Ulrich Zierahn, “The Risk of Automation for Jobs in OECD Countries: A Comparative Analysis,” OECD Social, Employment, and Migration Working Papers No. 189 (Paris: OECD Publishing, May 14, 2016), https://www.oecd-ilibrary

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Job,” World Economic Forum, September 26, 2016, https://www.weforum.org/agenda/2016/09/why-automation-doesnt-mean-a-robot-is-going-to-take-your-job. 24. “Automation and Anxiety: Will Smarter Machines Cause Mass Unemployment?” Economist, June 23, 2016, https://www.economist.com/special-report/2016/06/23/automation-and-anxiety

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; and James Bessen, “How Computer Automation Affects Occupations: Technology, Jobs, and Skills,” Vox, September 22, 2016, https://voxeu.org/article/how-computer-automation-affects-occupations. 25. “Automation and Anxiety.” 26. “Belgium—Unemployment,” European

Zero to Sold: How to Start, Run, and Sell a Bootstrapped Business

by Arvid Kahl  · 24 Jun 2020  · 461pp  · 106,027 words

people go out of their way not to do a certain job without describing it as a problem at the same time? Where do people “automate” their jobs with tools that, from your perspective, seem inadequate for the task? Where do they build makeshift solutions? The moment you find people organizing data

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to solve a problem as simple as rebooting a computer. This list also shows that the cost of solving a problem can vary wildly. Automating the job may cost a couple of minutes of your developer's time, but creating the new role of the system administrator to deal with these kinds

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