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 Lights in the Tunnel

by Martin Ford  · 28 May 2011  · 261pp  · 10,785 words

if it is, what are the implications for our economy? In this book, we are going to explore what increasing technological advancement, and in particular job automation, could mean to the economies of developed countries like the United States and also to the world economy as a whole. To do this, we

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Automation Comes to the Tunnel Now that we have a working simulation of the mass market, let’s go ahead and perform our experiment with job automation. To keep things simple, let’s first focus on the issue of jobs being taken over completely by machines or computers and leave the question

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the jobs held by many of the average lights. As this happens, the impacted lights grow dimmer and in many cases disappear completely. The automation process affects jobs throughout the world. In developed countries, the people who lose their jobs will usually continue to receive income, at least for a time,

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gradually evaporating into the new emptiness of the tunnel. A Reality Check Clearly, our simulation did not turn out well. Perhaps our initial assumption about jobs being automated was wrong. But, again, let’s leave that for the next chapter. In the meantime, we might wonder if we have made a

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nation. Here, long before the new light of advanced technology first began to shine, men had discovered a far more primitive and perverse form of job automation. The injustice and moral outrage associated with slavery rightly attracts nearly all of our attention. For this reason, most of us don’t have occasion

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worker could be.] Summarizing Both our tunnel simulation and our examination of the Southern slave economy seem to support the idea that once full automation penetrates the job market to a substantial degree, an economy driven by mass-market production must ultimately go into decline. The reason for this is simply

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and shareholders increased. These were the brighter lights in the tunnel that initially became stronger. However, as nearly all businesses in the tunnel continued to automate jobs, at some point the decrease in the number of potential customers began to outweigh the advantages gained from automation. Once this happened, businesses were forced

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the incredible increase in our ability to compute. We can also certainly expect that this dramatically expanded computational capacity will be focused increasingly on automating our jobs. Later in this chapter, we’ll look in more detail at several specific advancing technologies and how they might impact the job market and

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education seem to make a very strong case that the average worker—and perhaps many above-average workers—are in clear danger of having their jobs automated. Next, let’s look at some trends and specific technologies that show exactly how this is likely to happen. Offshoring and Drive-Through Banking

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millions of workers displaced from traditional jobs is pure fantasy. What are the implications for our economy if a large fraction of these traditional jobs are ultimately automated away? Automated checkout lanes are currently in use at a number of retail stores. We can be sure that in the future, these will become

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In spite of the radiologist’s training requirement of at least thirteen additional years beyond high school, it is conceptually quite easy to envision this job being automated. The primary focus of the job is to analyze and evaluate visual images. Furthermore, the parameters of each image are highly defined since they

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“software” job, I don’t mean that a person who has the job necessarily works with or programs software. I simply mean that automation of the job potentially requires only sufficiently advanced software. In other words, someone with a software job could eventually be replaced by a computer similar to the

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. This trend will only grow, and as I have pointed out previously, where offshoring appears, automation is often likely to eventually follow. The automation of software jobs is tied closely to the field of artificial intelligence. When most of us think about artificial intelligence, we are quickly sidetracked into the world

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jobs (or knowledge worker jobs) are typically high paying jobs. This creates a very strong incentive for businesses to offshore and, when possible, automate these jobs. Another point we can make is that there is really no relationship between how much training is required for a human being, and how difficult

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future, automation will fall heavily on knowledge workers and in particular on highly paid workers. In cases where technology is not yet sufficient to automate the job, offshoring is likely to be pursued as a interim solution. Given this reality, it may be that the simulation we performed in Chapter 1

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be rapid penetration of these practices into businesses of all sizes. As we saw with the radiologist and the lawyer, once significant portions of jobs can be automated, the number of workers employed will immediately begin to fall. The U.S. Small Business Administration estimates that businesses with fewer than 500

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“Hardware” Jobs and Robotics A “hardware” job is a job that requires some investment in mechanical or robotic technologies in order for the job to be automated. The automation of hardware jobs started long before the computer revolution. Machines used on assembly lines, farm equipment, and heavy earth moving equipment are all technologies

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best available technologies and processes. If it does not do so, it will not survive. History has shown that job automation very often involves pushing a significant portion of the job onto the customer. Automation in the customer service area is really self-service. This has been the case with ATMs, automated checkout isles

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sector and on the overall economy. Robotics and Offshoring As we’ve shown, “software” jobs are highly subject to offshoring and potentially also to automation. Those “Hardware” jobs that require significant hand-eye coordination in a varied environment are currently very difficult to fully automate. But what about offshoring? Can a hardware

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, and the worker will no longer add value. Long before that extremity is reached, however, there must come a tipping point at which job losses from automation begin to overwhelm any positive impact on employment from lower prices and increased consumer demand. In light of unprecedented, geometrically advancing computer technology, the

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technical fields—will desperately, and quite understandably, attempt to protect their livelihoods. We can expect substantial pressure on government to somehow restrict technological progress and job automation. It is possible that there will be a significant, last-ditch resurgence in the power of organized labor. Workers in jobs and industries that are

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of globalization on the job market has received most of the attention, I think most economists would be likely to agree that advancing technology and job automation have played a far more significant role. Although factors such as stagnating wages for average workers would seem to provide support for the theory that

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greatly assist in job creation. Offshoring and Factory Migration In Chapter 2 we saw that offshoring is often really just the leading edge of automation. When a job is offshored, a new consumer is created in a developing nation—at least temporarily. However, from the point of view of consumers in

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focused on insuring that as much of this technology as possible gets transferred to native businesses. Automation is not just about saving money by eliminating jobs. Automation conveys benefits far beyond that: it makes more precise and reliable manufacturing possible.* Machines can simply do things better, faster and with more precision

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the shoulders of American and European consumers. And as we have noted again and again in this book, those Western consumers all depend on jobs. If automation begins to dramatically impact employment in China, while at the same time demand dwindles in the West—and certainly if the catastrophic event described

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in fact due to machine automation rather than globalization, and that China, in spite of its low wage workforce, lost nearly two million textile jobs to improving automation technology between 1995 and 2002.42 *[ Cotton farming in poor countries, of course, remains highly labor intensive. However, this should not be used

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if the overall economy were approaching this tipping point, beyond which industries would no longer be labor intensive enough to absorb workers who lost their jobs to automation? We would probably expect to see gradually rising unemployment, stagnating wages and significant increases in productivity (output per hour of labor) as industries

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will be far more dire if the trends projected in this book come into play. If in addition to these demographic realities, broad-based automation of jobs unfolds simultaneously, the entire payroll tax-based system seems very likely to fall apart. As we saw in the previous section, capital intensive industries

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continue to pay the normal business income tax. Consider some of the advantages of this system: Since payroll taxes would be eliminated, the incentive to automate jobs or move them overseas would immediately be reduced. Likewise, the prospect of hiring a new worker would immediately become more attractive. A business that did

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choose to automate or offshore jobs would not be able to avoid contributing to the social programs that support the population. The demographic, or “baby boom,” issue would be

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people who forecast the future either cannot imagine, or are not willing to consider, a world in which human workers become increasingly superfluous. Economy-wide automation of jobs is not a technological impossibility; it is a psychological impossibility.* *[ It’s always very dangerous to use the word “impossible” where technology is concerned

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pointed out the threat from automation. In his 1995 book, The End of Work,49 Jeremy Rifkin gives many examples of the social impact that job automation has already had and speculates that, in the future, it may lead to social disintegration, dramatic rises in crime, civil unrest and possibly even

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be essential to have a plan. In the next chapter, we will fast forward to a point in the future where the trend toward widespread job automation has become clear. Once this happens, there will really be no choice except to come up with some modifications to our system so that the

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creation, which will then lead to strong consumer demand. The problem with that way of thinking, of course, is that, in an increasingly automated economy, the job creation will not occur. Consumers will have little opportunity to participate in the production process as workers and will lose access to the wages

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to the consumers of the business’s products or services in the form of lower prices. Therefore, the government can recapture the wages from the automated job with some combination of two types of taxes. First, higher business taxes, capital gains taxes and more progressive income taxes on wealthy individuals can be

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extensive analysis and probably through computer simulation of the economy. Obviously, any real world taxes that we implement in order to recapture the income from automated jobs will end up doing so in an imperfect way. We also know that government tends to be inefficient and wasteful. However, that does not change

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. It is likely that in the future, we may see a mix of direct incentive-based income streams and traditional full or part-time jobs. As automation advances, the remaining traditional jobs are likely to be those that require uniquely human attributes. In the future, we will continue to need social

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for new ventures, we have to somehow insure that the average consumers in our population have access to reliable income streams even as traditional jobs are increasing automated away. Consider the business model of an Internet company like Google. Google relies on revenue from online advertisements that are highly targeted. The

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danger is going occur when the service sector automates, and direct foreign competition is less of an issue in that arena. In the long run, job automation will clearly be a worldwide phenomenon. No country will escape its impact, and this includes developing nations with low wages. As I pointed out in

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automated economy. Over time, the incentive-based income streams provided by the government would increase, and the amount of traditional work performed would decrease. As job automation increases and the wages paid by businesses fall, the special taxes that have been put in place would need to be gradually increased to recapture

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We can then see how our transitional strategy might work. * * * * * We are back in our tunnel. Very gradually, just as before, we begin to automate the jobs held by many of the average lights. As this happens, the impacted lights grow dimmer and in many cases disappear completely. Now, however, we notice

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permeates the tunnel gradually shifts from white to green, we can also sense that it is once again increasing in overall intensity. Even as jobs are relentlessly automated away, the logic of the free market has been successfully leveraged to once again drive sustained prosperity. Chapter 5 THE GREEN LIGHT In

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labor intensive and ultimately reach a “tipping point.” Beyond this point, the economy will no longer be able to absorb the workers who lose jobs due to automation: businesses will instead invest primarily in more machines. I have also argued that this process will be relentless, and if it is not

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worker jobs. Software is typically more flexible and has a lower up front cost than expensive mechanical automation. As I noted in Chapter 2, automation of these jobs, together with offshoring, may mean diminishing prospects for knowledge works and college graduates in general. Machines may take over most unskilled labor, but

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are we now? Four Possible Cases” later in the Appendix for more on this. In the future, wages/income may be very low because of job automation, but technology will also make everything plentiful and cheap—so low income won’t matter This is an idea that is often expressed in conjunction

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is likely to threaten routine jobs. So it won’t arrive in time to solve the problem in any case. *[ It is perhaps conceivable that job automation may someday lead to somewhat lower housing costs because it could result in a lot of empty office towers and commercial buildings. Those buildings might

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Significant effort is likely to be put into machine learning technology, so that automation algorithms can be easily taught to perform a variety of jobs. Because automating the jobs of relatively unskilled workers often requires high capital investment in mechanically complex machines, it may well be office and knowledge workers who

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

The Globotics Upheaval: Globalisation, Robotics and the Future of Work

by Richard Baldwin  · 10 Jan 2019  · 301pp  · 89,076 words

—those who work in offices rather than farms and factories. These people are unprepared. Until recently, most white-collar, service-sector, and professional jobs were shielded from automation by humans’ cogitative monopoly. Computers couldn’t think, so jobs that required any type of thinking—be it teaching nuclear physics, arranging flowers, or

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see a stay-calm-and-carry-on attitude. Backlash Bedfellows The Trump and Brexit voters who drove the 2016 backlash know all about the job-displacing impact of automation and globalization. For decades, they, their families, and their communities have been competing with robots at home, and China abroad. They are still

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news is that once we make it past the upheaval, the world will be a much nicer place. A MORE HUMAN, MORE LOCAL FUTURE Automation and globalization displaced jobs in the nineteenth and twentieth centuries. Human creativity—being boundless—invented “needs” that we did not even know we needed. That’s why

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legendary ex-CEO of General Electric, Jack Welch might say.5 The upshot of this new type of thinking computer is that automation is now affecting office jobs, not just factory jobs as in the past. The same digitech is also making it easy for foreign-based workers to perform tasks in our

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parts for machines that could be churned out with higher accuracy and lower costs. This sort of innovation cut both ways when it came to jobs. Automation and Jobs—the Push and Pull Effects Mechanization meant that the same pile of work could be done with fewer workers, but the cost savings

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the nineteenth-century equivalent of today’s unionized workers holding secure jobs with good pay and benefits. What they objected to was the way that automation allowed jobs that were traditionally reserved for qualified craftsmen to go to low-skill, low-wage workers—often young children. It just seemed outrageously unfair. It

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into deindustrialization. The results were dramatic. NEW TECHNOLOGY PRODUCES A NEW ECONOMIC TRANSFORMATION The impact of the ICT impulse was first felt though the automation of industrial jobs. Computer-controlled machines rapidly displaced workers, especially in the auto industry, and especially those involved in welding, painting, and specific pick-and-place tasks

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victory over the best human player. But machine learning is not just fun and games. Computer scientist are pushing beyond headline-grabbing game playing to job-grabbing automation. Before machines crossed the second continental divide with machine learning, computers were not very good at office work. They couldn’t read handwriting, recognize

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speak of the “robot apocalypse,” but RPA will be a key part of the Globotics Transformation. It’s worth a closer look. RPAs are automating white-collar jobs in a very direct way. The Low-End Competition: RPA “They mimic a human. They do exactly what a human does. If you watch

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properly introduced to AI software robots and having learned about what they are capable of, we now get to the question about white-collar automation. How many jobs will go? In fact, a number of researchers have developed estimates of how many jobs will be displaced. Think of these estimates as dogs

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is something that society clearly needs. HOW MANY JOBS WILL AI DISPLACE? Many studies have tried to estimate the total impact of recent, AI-linked automation on jobs. These are essential reading but far from infallible. They are, after all, talking about the future, which means they are making it up—making

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next few years, the number of jobs displaced by white-collar robots will be somewhere between big and enormous. “Big” means one in every ten jobs is automated; “enormous” dials that up to six out of ten. The granddaddy of these studies was done way back in 2013 by two Oxford professors

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to 60 percent (due in part to the fact that white-collar robots have gotten so much better).8 These rather startling numbers refer to jobs that could be automated. But how many actually will be? A recent study by the consulting firm, Forrester, suggest that 16 percent of all US

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jobs will be displaced by automation in the next ten years.9 That is one out of every six jobs. The professions hardest hit are forecast to be those that employ

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, indeed, the only alternative to employing AI would be to ignore the data (as is often the case even today). “People who worry about job losses to automation tend to overlook the unprecedented data explosion businesses are experiencing, now accelerating out of knowledge workers’ control and demanding automation to deal with it

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a curious feature of digital products—they are often free. There are many striking differences between the mechanical automation that marked factory and farm jobs and the electronic automation that is hitting the service sector today. One is the price. Since it is almost costless on the margin to run white-collar

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people to look after the robots and do more human chores like management, accounting, human resource management, and the like. A third way AI automation is creating jobs in rich nations is by reshoring back-office jobs that had been offshored to countries like India. The idea of replacing high-cost workers

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practice. That explains why it is insightful to turn to actual practice, namely service-sector occupations where robots are displacing workers today. REALITY CHECK—JOBS BEING AUTOMATED TODAY The world is a complicated place, so it helps to figure out what matters and what doesn’t. It may well be that AI

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of all is the twenty-two million office workers. Many of them do things that AI can replace easily. Office Work Automated RPA is automating away many jobs in which workers are basically processing information and sending it on down an information assembly line. It is hard to estimate how many of

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The second biggest category of US jobs shown in Figure 6.1 is “sales and related occupations” with 14.5 million US workers. Automation of “Walking Worker” Service Jobs Automation in the service sector is not limited to software robots replacing brain workers. It is also coming to what we might call

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, but the intent is absolutely clear. They are direct substitutes for humans. Machine learning has also been applied to physical jobs outside of factories. Construction Jobs Automated—SAM the Bricklaying Robot For people with a strong back but not much education, construction is one of the best jobs on offer. But this

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jobs, which often pay minimum wage. Almost one in eleven US workers are involved in food preparation and food serving: thirteen million jobs. Food Preparation Jobs Being Automated McDonald’s and other big US chains like Chili’s Grill & Bar, Applebee’s, and Panera Bread are automating some tasks—taking some of

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allowed the company to review performance quarterly instead of annually and to cover far more borrowers. The leading investment bank, Goldman-Sachs, has automated many trading desk jobs. In 2000, the company employed six hundred traders in its New York office. Now there are just two traders working with two hundred computer

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Automation, Even the Masters of the Universe Are Threatened,” TechnologyReview.com, February 7, 2017. 35. Quotes from Laura Noonan, “Citi Issues Stark Warning on Automation of Bank Jobs,” Financial Times, June 12, 2018. 7 The Globotics Upheaval Bill Gates is worried that digitech will launch an upheaval. This should worry all of

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frankly those tens of thousands of people doing those jobs now have no idea that there are very serious projects underway that could automate a lot of those jobs.”5 Projecting forward, he says that if a human can perform a mental task in less than a second, it’s likely that

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140 million workers. And in any case, becoming a Googler is just not an option for most of the US hospitality workers whose jobs will be displaced by automation in the next few years. The simple fact is that using digitech to create jobs is not the main focus of today’s

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will face many of the same bad choices that manufacturing workers did in recent years. When it comes to white-collar robots and the automation of service jobs, the basic mismatched-speed point is well captured by a slight twist on the old (pre-DNA testing) Latin saying, “The mother is always

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-like event. The reduction in jobs was the result of a steady “infiltration” of globots into the newsrooms, editing rooms, and broadcast studios. Many jobs were automated, and others were shifted to freelancers—some of whom were based in low-wage nations. The next key driver of upheaval—unfairness—has nothing to

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follows the average trajectory of US workers with his skill level, his future could hold some very dark moments. During the Services Transformation, automation and globalization eliminated good jobs for low education workers. It was the start of what might be called the “wretched ratchet.” Manufacturing employment jagged down with each recession

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$27 billion. On top of that they are well-known to the general public, and some of their companies are involved in the automation of white-collar jobs and online freelancing. Another aspect that will make them targets-for-opportunists is a vague sense that these men (and they all are men

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. 16. “Stick Shift: Autonomous vehicles, Driving Jobs, and the Future of Work”, Center for Global Policy Solution, March 2017. 17. Quoted in “Anxiety about Automation and Jobs: Will We See Anti-Tech Laws?” James Pethokoukis, www.AEI.org (blog). 18. Quotes from Luke Muelhauswer, “What Should We Learn from Past AI Forecasts

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a job where ICT was a helper, not a hurter. Until the digitech revolution took off, especially machine learning, most service-sector and professional jobs were shielded from automation since industrial robots could not speak, listen, read, write, or help around the office in any way. Likewise, competition from foreign service workers

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

Machines of Loving Grace: The Quest for Common Ground Between Humans and Robots

by John Markoff  · 24 Aug 2015  · 413pp  · 119,587 words

has actually added seventy-four million jobs.3 MIT economist David Autor has offered a detailed explanation of the consequences of the current wave of automation. Job destruction is not across the board, he argues, but instead has focused on the routinized tasks performed by those in the middle of the job

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JOBS & MANUFACTURING BACK TO CALIFORNIA! Walking the Fremont factory line, however, it quickly becomes clear that the facility is a testament to highly automated manufacturing rather than creating jobs; there are fewer than ten workers actually handling products on the assembly line producing almost as many panels as hundreds of employees would

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has been a dramatic loss of clerical jobs. However, even within the world of clerical labor there are subtleties that suggest that predictions of automation and job destruction across the board are unlikely to prove valid. The case of bank tellers and the advent of automated teller machines is a particularly good

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a big way but failed, and it failed in its effort to enter the medical imaging business. The new anxiety about AI-based automation and the resulting job loss may eventually prove well founded, but it is just as likely that those who are alarmed have in fact just latched onto the

The Fourth Age: Smart Robots, Conscious Computers, and the Future of Humanity

by Byron Reese  · 23 Apr 2018  · 294pp  · 96,661 words

, and Peter who every day give me new reasons to believe in a better tomorrow PREFACE * * * (Please read. Not the usual blah-blah stuff.) Robots. Jobs. Automation. Artificial intelligence. Conscious computers. Superintelligence. Abundance. A jobless future. “Useless” humans. The end of scarcity. Creative computers. Robot overlords. Unlimited wealth. The end of work

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side. With respect to robots and automation, the situation is the same. The experts couldn’t be further apart. Some say that all jobs will be lost to automation, or at the very least that we are about to enter a permanent Great Depression in which one part of the workforce will

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is overwhelmingly about their impact on jobs, and therefore we will explore this topic in detail. The question at issue is this: Will automation, on net, eliminate more jobs than the economy will create, or will we remain close to full employment? An incalculable amount of analysis and opinion has been written

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need to broaden the term a bit. Robots, strictly speaking, don’t necessarily need to be embodied or have locomotion. When considering the effects of automation on jobs, this is certainly the case. A machine replacing a beekeeper, tending hives and harvesting honey, is clearly a robot. However, a machine replacing a

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and intuitive judgment; perspiration and inspiration; adherence to rules and judicious application of discretion. He goes on to maintain that using technology to automate some part of a job almost always makes the tasks that the machine cannot do more valuable, because with technology, the value of the entire job goes up

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-hundred-word description of some of the limitations of the study’s methodology. They state that “we make no attempt to estimate how many jobs will actually be automated. The actual extent and pace of computerisation will depend on several additional factors which were left unaccounted for.” So what’s with the

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47 percent figure? What they said is that some tasks within 47 percent of jobs will be automated. Well, there is nothing terribly shocking about that at all. Pretty much every job there is has had tasks within it

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automated. But the job remains. It is just different. For instance, Frey and Osborne give the following jobs a 65 percent or better chance of being computerized: social science

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tasks being computerized are tour guides and carpenters’ helpers. The disconnect is clear: some of what a carpenter’s helper does will get automated, but the carpenter helper job won’t vanish; it will morph, as almost everyone else’s job will, from architect to zoologist. Sure, your iPhone can be a

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up of nations committed to free markets and democracy, released a report in 2016 that directly counters it. In this report, entitled The Risk of Automation for Jobs in OECD Countries, the authors apply a “whole job” methodology and come up with the percent of jobs potentially lost to computerization as 9

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” argument, you won’t be surprised to hear, has been around for a while too. In 1961, Time magazine printed, “What worries many job experts more is that automation may prevent the economy from creating enough new jobs. . . . Today’s new industries have comparatively few jobs for the unskilled or semiskilled, just

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the class of workers whose jobs are being eliminated by automation.” Is this a valid concern today? Will new jobs be slow in coming? I suspect not. In 2016, the World Economic Forum in

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will be spread throughout the wage spectrum. All that being said, there is a widespread concern that automation is destroying jobs at the “bottom” and creating new jobs at the “top.” Automation, this logic goes, may be making new jobs at the top, like geneticist, but is destroying jobs at the bottom like warehouse

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story generally ends well for them. This is how free economies work, and why we have never run out of jobs due to automation. There are not a fixed number of jobs that automation steals one by one, resulting in progressively more unemployment. That simply isn’t how the economy works. There are as

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or possibility three comes to pass, then there will be robot-proof jobs. What will they be? A good method for evaluating any job’s likelihood of being automated is what I call the “training manual test.” Think about a set of instructions needed to do your job, right down to the

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listed some of the kinds of jobs that are less susceptible to automation. If you want a quick test for scoring how likely specific jobs are to be automated, I offer the following. It is ten questions, and the answer to each can be scored from 0 to 10. For every question

Squeezed: Why Our Families Can't Afford America

by Alissa Quart  · 25 Jun 2018  · 320pp  · 90,526 words

office and administrative jobs in health care, advertising, public relations, broadcasting, law, and financial services. (Women’s jobs account for more than five jobs lost due to our automated friends for every job gained.) The National Science Foundation is spending nearly $1 million to research a future of robotic nurses who will

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that UBI could help make sense of the automation of so many middle-class and working-class jobs. It would protect workers who lose their jobs to automation and thus alleviate the impulse to blame themselves or, even worse, point fingers at immigrants and people living below the poverty line. As for

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