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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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.”
A warehouse equipped with Kiva robots can handle up to four times as many orders as a similar unautomated warehouse, where workers might spend as much as 70 percent of their time walking about to retrieve goods. (Coincidentally or not, Amazon bought Kiva soon after a press report revealed that workers at one of the retailer’s giant warehouses often walked more than 10 miles a day.)
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In December of last year, Indeed also provided CoinDesk with data regarding blockchain jobs posted. The report indicated that the number of blockchain jobs posted in the U.S. had increased by 207 percent since 2016, and by 631 percent since November 2015.
Moonlighting is the practice of holding an additional job or jobs, often at night, in addition to one’s main job, usually to earn extra income. A person who moonlights may have little time left for sleep or leisure activities.
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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Brynjolfsson and McAfee are not Luddites. Indeed, they are sometimes accused of being too optimistic about the extent and speed of recent digital advances. Brynjolfsson says they began writing Race Against the Machine, the 2011 book in which they laid out much of their argument, because they wanted to explain the economic benefits of these new technologies (Brynjolfsson spent much of the 1990s sniffing out evidence that information technology was boosting rates of productivity). But it became clear to them that the same technologies making many jobs safer, easier, and more productive were also reducing the demand for many types of human workers.
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It’s a startling assertion because it threatens the faith that many economists place in technological progress. Brynjolfsson and McAfee still believe that technology boosts productivity and makes societies wealthier, but they think that it can also have a dark side: technological progress is eliminating the need for many types of jobs and leaving the typical worker worse off than before. ­Brynjolfsson can point to a second chart indicating that median income is failing to rise even as the gross domestic product soars. “It’s the great paradox of our era,” he says. “Productivity is at record levels, innovation has never been faster, and yet at the same time, we have a falling median income and we have fewer jobs. People are falling behind because technology is advancing so fast and our skills and organizations aren’t keeping up.”
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Techniques using vast amounts of computational power have gone a long way toward helping robots understand their surroundings, but John Leonard, a professor of engineering at MIT and a member of its Computer Science and Artificial Intelligence Laboratory (CSAIL), says many familiar difficulties remain. “Part of me sees accelerating progress; the other part of me sees the same old problems,” he says. “I see how hard it is to do anything with robots. The big challenge is uncertainty.” In other words, people are still far better at dealing with changes in their environment and reacting to unexpected events.
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.”
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.
One of the friendlier, more flexible robots meant to work with humans is Rethink’s Baxter. The creation of Rodney Brooks, the company’s founder, Baxter needs minimal training to perform simple tasks like picking up objects and moving them to a box. It’s meant for use in relatively small manufacturing facilities where conventional industrial robots would cost too much and pose too much danger to workers. The idea, says Brooks, is to have the robots take care of dull, repetitive jobs that no one wants to do.
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In the tony northern suburbs of New York City, IBM Research is pushing super-smart computing into the realms of such professions as medicine, finance, and customer service. IBM’s efforts have resulted in Watson, a computer system best known for beating human champions on the game show Jeopardy! in 2011. That version of Watson now sits in a corner of a large data center at the research facility in Yorktown Heights, marked with a glowing plaque commemorating its glory days. Meanwhile, researchers there are already testing new generations of Watson in medicine, where the technology could help physicians diagnose diseases like cancer, evaluate patients, and prescribe treatments.
Getting a first job is an important rite of passage in many cultures. The youth may start by doing household work, odd jobs, or working for a family business. In many countries, school children get summer jobs during the longer summer vacation. Students enrolled in higher education can apply for internships or coops to further enhance the probability of securing an entry level job upon graduation.
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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Snag is an online employment website specializing in the hourly marketplace.[1] Founded in 2000 with offices in Washington, D.C., Richmond, Virginia, Charleston, South Carolina, and Oakland, California,[2] 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.[3]
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