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At least since the Industrial Revolution began in the 1700s, improvements in technology have changed the nature of work and destroyed some types of jobs in the process. In 1900, 41 percent of Americans worked in agriculture; by 2000, it was only 2 percent. Likewise, the proportion of Americans employed in manufacturing has dropped from 30 percent in the post–World War II years to around 10 percent today—partly because of increasing automation, especially during the 1980s.
“The sustained interest in blockchain jobs is perhaps a sign that job seekers believe non-financial companies will pursue blockchain applications, even if financial companies see cryptocurrencies as a fad,” the company writes in the report.
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Snag is an online employment website specializing in the hourly marketplace. Founded in 2000 with offices in Washington, D.C., Richmond, Virginia, Charleston, South Carolina, and Oakland, California, Snag has been named to Fortune Magazine’s “Great Place to Work” Best Small & Medium Workplaces list for eight consecutive years. Snag has also been named to Washingtonian’s “Great Places to Work” and Deloitte’s “Fast 500”, a ranking of the fastest growing technology, media, telecommunications, life sciences and clean technology companies in North America.
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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.
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.
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Perhaps the most damning piece of evidence, according to Brynjolfsson, is a chart that only an economist could love. In economics, productivity—the amount of economic value created for a given unit of input, such as an hour of labor—is a crucial indicator of growth and wealth creation. It is a measure of progress. On the chart Brynjolfsson likes to show, separate lines represent productivity and total employment in the United States. For years after World War II, the two lines closely tracked each other, with increases in jobs corresponding to increases in productivity. The pattern is clear: as businesses generated more value from their workers, the country as a whole became richer, which fueled more economic activity and created even more jobs. Then, beginning in 2000, the lines diverge; productivity continues to rise robustly, but employment suddenly wilts. By 2011, a significant gap appears between the two lines, showing economic growth with no parallel increase in job creation. Brynjolfsson and McAfee call it the “great decoupling.” And Brynjolfsson says he is confident that technology is behind both the healthy growth in productivity and the weak growth in jobs.
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It’s hard not to instantly like Baxter, in part because it seems so eager to please. The “eyebrows” on its display rise quizzically when it’s puzzled; its arms submissively and gently retreat when bumped. Asked about the claim that such advanced industrial robots could eliminate jobs, Brooks answers simply that he doesn’t see it that way. Robots, he says, can be to factory workers as electric drills are to construction workers: “It makes them more productive and efficient, but it doesn’t take jobs.”
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Take the bright-orange Kiva robot, a boon to fledgling e-commerce companies. Created and sold by Kiva Systems, a startup that was founded in 2002 and bought by Amazon for $775 million in 2012, the robots are designed to scurry across large warehouses, fetching racks of ordered goods and delivering the products to humans who package the orders. In Kiva’s large demonstration warehouse and assembly facility at its headquarters outside Boston, fleets of robots move about with seemingly endless energy: some newly assembled machines perform tests to prove they’re ready to be shipped to customers around the world, while others wait to demonstrate to a visitor how they can almost instantly respond to an electronic order and bring the desired product to a worker’s station.
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Over the past few years, it has become conventional wisdom that dramatic advances in robotics and artificial intelligence have put us on the path to a jobless future. We are living in the midst of a “second machine age,” to quote the title of the influential book by MIT researchers Erik Brynjolfsson and Andrew McAfee, in which routine work of all kinds—in manufacturing, sales, bookkeeping, food prep—is being automated at a steady clip, and even complex analytical jobs will be superseded before long. A widely cited 2013 study by researchers at the University of Oxford, for instance, found that nearly half of all jobs in the US were at risk of being fully automated over the next 20 years. The endgame, we’re told, is inevitable: The robots are on the march, and human labor is in retreat.
Manual work seems to shorten one’s lifespan. High rank (a higher position at the pecking order) has a positive effect. Professions that cause anxiety have a direct negative impact on health and lifespan. Some data is more complex to interpret due to the various reasons of long life expectancy; thus skilled professionals, employees with secure jobs and low anxiety occupants may live a long life for variant reasons. The more positive characteristics one’s job is, the more likely he or she will have a longer lifespan. Gender, country, and actual (what statistics reveal, not what people believe) danger are also notable parameters.
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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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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Imagine you’re the pilot of an old Cessna. You’re flying in bad weather, you can’t see the horizon, and a frantic, disoriented passenger is yelling that you’re headed straight for the ground. What do you do? No question: You trust your instruments—your altimeter, your compass, and your artificial horizon—to give you your actual bearings, and keep flying.
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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.
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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McAfee, associate director of the MIT Center for Digital Business at the Sloan School of Management, speaks rapidly and with a certain awe as he describes advances such as Google’s driverless car. Still, despite his obvious enthusiasm for the technologies, he doesn’t see the recently vanished jobs coming back. The pressure on employment and the resulting inequality will only get worse, he suggests, as digital technologies—fueled with “enough computing power, data, and geeks”—continue their exponential advances over the next several decades. “I would like to be wrong,” he says, “but when all these science-fiction technologies are deployed, what will we need all the people for?”
Despite the system’s remarkable ability to make sense of all that data, it’s still early days for Dr. Watson. While it has rudimentary abilities to “learn” from specific patterns and evaluate different possibilities, it is far from having the type of judgment and intuition a physician often needs. But IBM has also announced it will begin selling Watson’s services to customer-support call centers, which rarely require human judgment that’s quite so sophisticated. IBM says companies will rent an updated version of Watson for use as a “customer service agent” that responds to questions from consumers; it has already signed on several banks. Automation is nothing new in call centers, of course, but Watson’s improved capacity for natural-language processing and its ability to tap into a large amount of data suggest that this system could speak plainly with callers, offering them specific advice on even technical and complex questions. It’s easy to see it replacing many human holdouts in its new field.
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None of this is to say that automation and AI aren’t having an important impact on the economy. But that impact is far more nuanced and limited than the doomsday forecasts suggest. A rigorous study of the impact of robots in manufacturing, agriculture, and utilities across 17 countries, for instance, found that robots did reduce the hours of lower-skilled workers—but they didn’t decrease the total hours worked by humans, and they actually boosted wages. In other words, automation may affect the kind of work humans do, but at the moment, it’s hard to see that it’s leading to a world without work. McAfee, in fact, says of his earlier public statements, “If I had to do it over again, I would put more emphasis on the way technology leads to structural changes in the economy, and less on jobs, jobs, jobs. The central phenomenon is not net job loss. It’s the shift in the kinds of jobs that are available.”
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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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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.
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The talking bot can supposedly identify joy, sadness, anger, and surprise and determine whether a person is in a good or bad mood—abilities that Pepper’s engineers figured would make “him” an ideal personal assistant or salesperson. And sure enough, there are more than 10,000 Peppers now at work in SoftBank stores, Pizza Huts, cruise ships, homes, and elsewhere.
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Alas, the future this study envisions seems to be very far off. To be sure, the fact that fears about automation have been proved false in the past doesn’t mean they will continue to be so in the future, and all of those long-foretold positive feedback loops exponential growth may abruptly kick in someday. But it isn’t easy to see how we’ll get there from here anytime soon, given how little companies are investing in new technology and how slowly the economy is growing. In that sense, the problem we’re facing isn’t that the robots are coming. It’s that they aren’t.