To be sure, Autor says, computer technologies are changing the types of jobs available, and those changes “are not always for the good.” At least since the 1980s, he says, computers have increasingly taken over such tasks as bookkeeping, clerical work, and repetitive production jobs in manufacturing—all of which typically provided middle-class pay. At the same time, higher-paying jobs requiring creativity and problem-solving skills, often aided by computers, have proliferated. So have low-skill jobs: demand has increased for restaurant workers, janitors, home health aides, and others doing service work that is nearly impossible to automate. The result, says Autor, has been a “polarization” of the workforce and a “hollowing out” of the middle class—something that has been happening in numerous industrialized countries for the last several decades. But “that is very different from saying technology is affecting the total number of jobs,” he adds. “Jobs can change a lot without there being huge changes in employment rates.”
So if the data doesn’t show any evidence that robots are taking over, why are so many people even outside Silicon Valley convinced it’s happening? In the US, at least, it’s partly due to the coincidence of two widely observed trends. Between 2000 and 2009, 6 million US manufacturing jobs disappeared, and wage growth across the economy stagnated. In that same period, industrial robots were becoming more widespread, the internet seemed to be transforming everything, and AI became really useful for the first time. So it seemed logical to connect these phenomena: Robots had killed the good-­paying manufacturing job, and they were coming for the rest of us next.
The phrase “don’t quit your day job” is a humorous response to a poor or mediocre performance not up to professional caliber. The phrase implies that the performer is not talented enough in that activity to be able to make a career out of it.
New technologies are “encroaching into human skills in a way that is completely unprecedented,” McAfee says, and many middle-class jobs are right in the bull’s-eye; even relatively high-skill work in education, medicine, and law is affected. “The middle seems to be going away,” he adds. “The top and bottom are clearly getting farther apart.” While technology might be only one factor, says McAfee, it has been an “underappreciated” one, and it is likely to become increasingly significant.
The machines created at Kiva and Rethink have been cleverly designed and built to work with people, taking over the tasks that the humans often don’t want to do or aren’t especially good at. They are specifically designed to enhance these workers’ productivity. And it’s hard to see how even these increasingly sophisticated robots will replace humans in most manufacturing and industrial jobs anytime soon. But clerical and some professional jobs could be more vulnerable. That’s because the marriage of artificial intelligence and big data is beginning to give machines a more humanlike ability to reason and to solve many new types of problems.
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Still, Katz doesn’t dismiss the notion that there is something different about today’s digital technologies—something that could affect an even broader range of work. The question, he says, is whether economic history will serve as a useful guide. Will the job disruptions caused by technology be temporary as the workforce adapts, or will we see a science-fiction scenario in which automated processes and robots with superhuman skills take over a broad swath of human tasks? Though Katz expects the historical pattern to hold, it is “genuinely a question,” he says. “If technology disrupts enough, who knows what will happen?”
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An activity that requires a person’s mental or physical effort is work (as in “a day’s work”). If a person is trained for a certain type of job, they may have a profession. Typically, a job would be a subset of someone’s career. The two may differ in that one usually retires from their career, versus resignation or termination from a job.
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The contention that automation and digital technologies are partly responsible for today’s lack of jobs has obviously touched a raw nerve for many worried about their own employment. But this is only one consequence of what ­Brynjolfsson and McAfee see as a broader trend. The rapid acceleration of technological progress, they say, has greatly widened the gap between economic winners and losers—the income inequalities that many economists have worried about for decades. Digital technologies tend to favor “superstars,” they point out. For example, someone who creates a computer program to automate tax preparation might earn millions or billions of dollars while eliminating the need for countless accountants.
In a less anxious world, Pepper might come across as a cute technological novelty. But for many pundits and prognosticators, he’s a sign of something much more grave: the growing obsolescence of human workers. (Images of the doe-eyed Pepper have accompanied numerous articles with variations on the headline “robots are coming for your job.”)

“We were lucky and steadily rising productivity raised all boats for much of the 20th century,” he says. “Many people, especially economists, jumped to the conclusion that was just the way the world worked. I used to say that if we took care of productivity, everything else would take care of itself; it was the single most important economic statistic. But that’s no longer true.” He adds, “It’s one of the dirty secrets of economics: technology progress does grow the economy and create wealth, but there is no economic law that says everyone will benefit.” In other words, in the race against the machine, some are likely to win while many others lose.
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Given his calm and reasoned academic demeanor, it is easy to miss just how provocative Erik Brynjolfsson’s contention really is. ­Brynjolfsson, a professor at the MIT Sloan School of Management, and his collaborator and coauthor Andrew McAfee have been arguing for the last year and a half that impressive advances in computer technology—from improved industrial robotics to automated translation services—are largely behind the sluggish employment growth of the last 10 to 15 years. Even more ominous for workers, the MIT academics foresee dismal prospects for many types of jobs as these powerful new technologies are increasingly adopted not only in manufacturing, clerical, and retail work but in professions such as law, financial services, education, and medicine.
The peculiar thing about this historical moment is that we’re afraid of two contradictory futures at once. On the one hand, we’re told that robots are coming for our jobs and that their superior productivity will transform industry after industry. If that happens, economic growth will soar and society as a whole will be vastly richer than it is today. But at the same time, we’re told that we’re in an era of secular stagnation, stuck with an economy that’s doomed to slow growth and stagnant wages. In this world, we need to worry about how we’re going to support an aging population and pay for rising health costs, because we’re not going to be much richer in the future than we are today. Both of these futures are possible. But they can’t both come true. Fretting about both the rise of the robots and about secular stagnation doesn’t make any sense. Yet that’s precisely what many intelligent people are doing.
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Workers often talk of “getting a job”, or “having a job”. This conceptual metaphor of a “job” as a possession has led to its use in slogans such as “money for jobs, not bombs”. Similar conceptions are that of “land” as a possession (real estate) or intellectual rights as a possession (intellectual property).
IBM likes to call it cognitive computing. Essentially, Watson uses artificial-­intelligence techniques, advanced natural-language processing and analytics, and massive amounts of data drawn from sources specific to a given application (in the case of health care, that means medical journals, textbooks, and information collected from the physicians or hospitals using the system). Thanks to these innovative techniques and huge amounts of computing power, it can quickly come up with “advice”—for example, the most recent and relevant information to guide a doctor’s diagnosis and treatment decisions.
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But are these new technologies really responsible for a decade of lackluster job growth? Many labor economists say the data are, at best, far from conclusive. Several other plausible explanations, including events related to global trade and the financial crises of the early and late 2000s, could account for the relative slowness of job creation since the turn of the century. “No one really knows,” says Richard Freeman, a labor economist at Harvard University. That’s because it’s very difficult to “extricate” the effects of technology from other macroeconomic effects, he says. But he’s skeptical that technology would change a wide range of business sectors fast enough to explain recent job numbers.
This anxiety about automation is understandable in light of the hair-raising progress that tech companies have made lately in robotics and artificial intelligence, which is now capable of, among other things, defeating Go masters, outbluffing champs in Texas Hold’em, and safely driving a car. And the notion that we’re on the verge of a radical leap forward in the scale and scope of automation certainly jibes with the pervasive feeling in Silicon Valley that we’re living in a time of unprecedented, accelerating innovation. Some tech leaders, including Y Combinator’s Sam Altman and Tesla’s Elon Musk, are so sure this jobless future is imminent—and, perhaps, so wary of torches and pitchforks—that they’re busy contemplating how to build a social safety net for a world with less work. Hence the sudden enthusiasm in Silicon Valley for a so-called universal basic income, a stipend that would be paid automatically to every citizen, so that people can have something to live on after their jobs are gone.
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What’s more, even if today’s digital technologies are holding down job creation, history suggests that it is most likely a temporary, albeit painful, shock; as workers adjust their skills and entrepreneurs create opportunities based on the new technologies, the number of jobs will rebound. That, at least, has always been the pattern. The question, then, is whether today’s computing technologies will be different, creating long-term involuntary unemployment.
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Despite the labor-saving potential of the robots, Mick Mountz, Kiva’s founder and CEO, says he doubts the machines have put many people out of work or will do so in the future. For one thing, he says, most of Kiva’s customers are e-commerce retailers, some of them growing so rapidly they can’t hire people fast enough. By making distribution operations cheaper and more efficient, the robotic technology has helped many of these retailers survive and even expand. Before founding Kiva, Mountz worked at Webvan, an online grocery delivery company that was one of the 1990s dot-com era’s most infamous flameouts. He likes to show the numbers demonstrating that Webvan was doomed from the start; a $100 order cost the company $120 to ship. Mountz’s point is clear: something as mundane as the cost of materials handling can consign a new business to an early death. Automation can solve that problem.
Though advances like these suggest how some aspects of work could be subject to automation, they also illustrate that humans still excel at certain tasks—for example, packaging various items together. Many of the traditional problems in robotics—such as how to teach a machine to recognize an object as, say, a chair—remain largely intractable and are especially difficult to solve when the robots are free to move about a relatively unstructured environment like a factory or office.
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That robots, automation, and software can replace people might seem obvious to anyone who’s worked in automotive manufacturing or as a travel agent. But Brynjolfsson and McAfee’s claim is more troubling and controversial. They believe that rapid technological change has been destroying jobs faster than it is creating them, contributing to the stagnation of median income and the growth of inequality in the United States. And, they suspect, something similar is happening in other technologically advanced countries.
While many people do hold a full-time occupation, “day job” specifically refers to those who hold the position solely to pay living expenses so they can pursue, through low paying entry work, the job they really want (which may also be during the day). The phrase strongly implies that the day job would be quit, if only the real vocation paid a living wage.
McAfee points to both retail and transportation as areas where automation is likely to have a major impact. Yet even in those industries, the job-loss numbers are less scary than many headlines suggest. Goldman Sachs just released a report predicting that autonomous cars could ultimately eat away 300,000 driving jobs a year. But that won’t happen, the firm argues, for another 25 years, which is more than enough time for the economy to adapt. A recent study by the Organization for Economic Cooperation and Development, meanwhile, predicts that 9 percent of jobs across 21 different countries are under serious threat from automation. That’s a significant number, but not an apocalyptic one.
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