Beyond Automation

Automation has traditionally displaced workers, forcing them onto higher ground that machines have not yet claimed. If we reframe the use of machines as augmentation, human work can flourish and accomplish what was never before possible. Some knowledge workers will step up to even higher levels of cognition; others will step aside and draw on forms of intelligence that machines lack. After hearing of a recent Oxford University study on advancing automation and its potential to displace workers, Yuh-Mei Hutt, of Tallahassee, Florida, wrote, “The idea that half of today’s jobs may vanish has changed my view of my children’s future.” Hutt was reacting not only as a mother; she heads a business and occasionally blogs about emerging technologies. That’s especially true now that automation is coming to knowledge work, in the form of artificial intelligence. What if we were to reframe the situation? What if, rather than asking the traditional question-What tasks currently performed by humans will soon be done more cheaply and rapidly by machines?-we ask a new one: What new feats might people achieve if they had better thinking machines to assist them? Instead of seeing work as a zero-sum game with machines taking an ever greater share, we might see growing possibilities for employment. The two of us have been looking at cases in which knowledge workers collaborate with machines to do things that neither could do well on their own. Aiming for increased automation promises cost savings but limits us to thinking within the parameters of work that is being accomplished today. Augmentation, in contrast, means starting with what humans do today and figuring out how that work could be deepened rather than diminished by a greater use of machines. We propose a change in mindset, on the part of both workers and providers of work, that will lead to different outcomes-a change from pursuing automation to promoting augmentation. Knowledge workers will come to see smart machines as partners and collaborators in creative problem solving. In essence this is the same advice that has always been offered and taken as automation has encroached on human work: Let the machine do the things that are beneath you, and take the opportunity to engage with higher-order concerns. Orbitz needs “People who can go really deep in their particular area of expertise,” he says, “And also go really broad and have that kind of curiosity about the overall organization and how their particular piece of the pie fits into it.” That’s good guidance for any knowledge worker who wants to step up: Start thinking more synthetically-in the old sense of that term. Stepping forward means bringing about machines’ next level of encroachment, but it involves work that is itself highly augmented by software. For augmentation to work, employers must be convinced that the combination of humans and computers is better than either working alone.

Keywords: [“work”,”machine”,”people”]

Our Automated Future

What business will want to hire a messy, complex carbon-based life form when a software tweak can get the job done just as well? How long will it be before you, too, lose your job to a computer? This question is taken up by a number of recent books, with titles that read like variations on a theme: “The Industries of the Future,” “The Future of the Professions,” “Inventing the Future.” Although the authors of these works are employed in disparate fields-law, finance, political theory-they arrive at more or less the same conclusion. “Could another person learn to do your job by studying a detailed record of everything you’ve done in the past?” Martin Ford, a software developer, asks early on in “Rise of the Robots: Technology and the Threat of a Jobless Future”. Later, Ford notes, “A computer doesn’t need to replicate the entire spectrum of your intellectual capability in order to displace you from your job; it only needs to do the specific things you are paid to do.” He cites a 2013 study by researchers at Oxford, which concluded that nearly half of all occupations in the United States are “Potentially automatable,” perhaps within “a decade or two.” What if it doesn’t? What if the jobs of the future are also potentially automatable? Jobs can then be arranged into four boxes: manual routine, manual nonroutine, and so on. Jobs on an assembly line fall into the manual-routine box, jobs in home health care into the manual-nonroutine box. The highest-paid jobs are clustered in the last box; managing a hedge fund, litigating a bankruptcy, and producing a TV show are all cognitive and nonroutine. Manual, nonroutine jobs tend to be among the lowest paid-emptying bedpans, bussing tables, cleaning hotel rooms. Routine jobs on the factory floor or in payroll or accounting departments tend to fall in between. It’s these middle-class jobs that robots have the easiest time laying their grippers on. The argument, made by both Bernie Sanders and Donald Trump, was that these deals have shafted middle-class workers by encouraging companies to move jobs to countries like China and Mexico, where wages are lower. According to Brynjolfsson and McAfee, such talk misses the point: trying to save jobs by tearing up trade deals is like applying leeches to a head wound. “These are precisely the tasks that are easiest to automate.” Off-shoring jobs, they argue, is often just a “Way station” on the road to eliminating them entirely. Jerry Kaplan proposes that the federal government create a 401(k)-like account for every ten-year-old in the U.S. Those who ultimately do find jobs could contribute some of their earnings to the accounts; those who don’t could perform volunteer work in return for government contributions.

Keywords: [“job”,”machine”,”new”]