Working out

Okay, what really happens down the road to all our jobs?welcomeWe know that automation replaces many human jobs and generates many others, and that artificial intelligence will accelerate this creative destruction. Historically, the default view among business and technology leaders, supported mostly by hand-waving, is that this unstoppable march will bring a wealth of new jobs, if only the masses somehow can receive proper technological education.

It’s hard to assess the recent historical record on job loss versus gain, although today’s New York Times offers an interesting take. And while we can easily spot job losses, new jobs created by machines, “almost by definition, are harder to imagine,” as MIT economist Erik Brynjolfsson pointed out in a session at the American Association for the Advancement of Science (AAAS) annual meeting in Boston on Saturday.

But in the past couple of years the public discussion has grown more worried, with one dark perspective on implications well described in a poorly titled essay by Rutgers historian James Livingston.

At the AAAS session, Harvard computer scientist David Parkes presented some relevant thoughts from the 100 Year Study on Artificial Intelligence project. Here are a few quotes from the study’s report on AI and real life in 2030, published last September:

  • “AI will gradually invade almost all employment sectors, requiring a shift away from human labor that computers are able to take over.”
  • “To date, digital technologies have been affecting workers more in the skilled middle, such as travel agents, rather than the very lowest-skilled or highest skilled work. On the other hand, the spectrum of tasks that digital systems can do is evolving as AI systems improve, which is likely to gradually increase the scope of what is considered routine. AI is also creeping into high end of the spectrum, including professional services not historically performed by machines.”
  • “A spectrum of effects will emerge, ranging from small amounts of replacement or augmentation to complete replacement. For example, although most of a lawyer’s job is not yet automated, AI applied to legal information extraction and topic modeling has automated parts of first-year lawyers’ jobs. In the not too distant future, a diverse array of job-holders, from radiologists to truck drivers to gardeners, may be affected.”
  • “As labor becomes a less important factor in production as compared to owning intellectual capital, a majority of citizens may find the value of their labor insufficient to pay for a socially acceptable standard of living. These changes will require a political, rather than a purely economic, response concerning what kind of social safety nets should be in place to protect people from large, structural shifts in the economy. Absent mitigating policies, the beneficiaries of these shifts may be a small group at the upper stratum of the society.”
  • “Longer term, the current social safety net may need to evolve into better social services for everyone, such as healthcare and education, or a guaranteed basic income. Indeed, countries such as Switzerland and Finland have actively considered such measures. AI may be thought of as a radically different mechanism of wealth creation in which everyone should be entitled to a portion of the world’s AI-produced treasure.”

At another packed AAAS session, Alta Charo, professor of law and bioethics at the University of Wisconsin at Madison, gave a masterful quick summary of the history and findings of the report on human genome editing from the National Academy of Science. Released last week, this report’s recommendations drew plenty of public attention—far more than last fall’s AI in 2030 report, although AI will have much greater impact in the next decade or two or three.