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. How long? Not long.
“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” (Basic Books). “Or could someone become proficient by repeating the tasks you’ve already completed, in the way that a student might take practice tests to prepare for an exam? If so, then there’s a good chance that an algorithm may someday be able to learn to do much, or all, of your job.”
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.” (“Even the work of software engineers may soon largely be computerisable,” the study observed. )
[Techies always add that last parenthetical like they say they understand piracy because “Some of my best friends are musicians….]
As recently as twenty years ago, Google didn’t exist, and as recently as thirty years ago it couldn’t have existed, since the Web didn’t exist. At the close of the third quarter of 2016, Google was valued at almost five hundred and fifty billion dollars and ranked as the world’s second-largest publicly traded company, by market capitalization. (The first was Apple.)
Google offers a vivid illustration of how new technologies create new opportunities. Two computer-science students at Stanford go looking for a research project, and the result, within two decades, is worth more than the G.D.P. of a country like Norway or Austria. But Google also illustrates how, in the age of automation, new wealth can be created without creating new jobs. Google employs about sixty thousand workers. General Motors, which has a tenth of the market capitalization, employs two hundred and fifteen thousand people. And this is G.M. post-[IBM’s] Watson. In the late nineteen-seventies, the carmaker’s workforce numbered more than eight hundred thousand.
How much technology has contributed to the widening income gap in the U.S. is a matter of debate; some economists treat it as just one factor, others treat it as the determining factor. In either case, the trend line is ominous.