http://www.slate.com
In the early days of artificial intelligence research, it was commonplace for the well-educated academics in the field to (mistakenly) think that being “intelligent” meant being good at things that other well-educated academic researchers struggled at, like playing chess. We now know, however, that it's far harder to get robots to do things that come naturally to us (like identify objects and pick them up) than it is to get them to prove logical theorems or find patterns in huge volumes of data—things we humans struggle at. This and other counter-intuitive trends in AI and research on the nature of human intelligence have discouraged researchers from trying to predict which jobs will be automated, but a provocative new study by Carl Frey and Michael Osborne at Oxford University tries to do just that, and their findings are alarming.
In “The Future of Employment: How Susceptible Are Jobs to
Computerisation?,” Frey and Osborne estimate that 47 percent of U.S.
jobs are “at risk” of being automated in the next 20 years. This does
not mean that they necessarily will be automated (despite the way the study has been portrayed in some media outlets)—rather, the authors argue, it is plausible
over the next two decades that existing and foreseeable AI technologies
could be used to cost-effectively automate those jobs out of existence.
Machines may not (and probably won't) do the jobs the same way as
people, however—just remember the last time you used an automated
check-out system at a grocery store. There’s a difference between
machines doing something cheaply and doing it well. Frey and Osborne
took into account the possibility of such “task simplification” in their
analysis.
Which jobs are most at risk? According to The Jetsons,
we should expect robots to clean our houses and do other working-class
occupations that educated elites have historically looked down upon as
“unskilled.” But anyone who has done such a job, or has watched an
episode of Undercover Boss
and seen highly-paid CEOs fumble while trying to carry out the
demanding minimum wage jobs usually performed by their underlings, knows
that there is no such thing as unskilled labor anymore (if there ever
was), especially if you are comparing humans and machines in the same
breath. The gap between humans and current AI is vastly greater than the
differences between humans.
Frey and Osborne focus on “engineering bottlenecks” in AI and
robotics, and compare these stumbling points with the requirements of
jobs in order to determine which are most and least likely to be
vulnerable to automation. The biggest bottlenecks are perception and
manipulation, creative intelligence, and social intelligence, all of
which computers struggle mightily at (but Rosie the Robot excelled at,
by the way). While the trend in recent decades has been towards a
hollowing out of “middle-skill” jobs and an increase in low-paying
service sector jobs and high-paying, highly educated jobs, Frey and
Osborne expect that automation in the future will mainly substitute for
“low-skill and low-wage” jobs.
So who, specifically, should be worried? They write:
Our model predicts that most workers in transportation and logistics occupations, together with the bulk of office and administrative support workers, and labour in production occupations, are at risk. These findings are consistent with recent technological developments documented in the literature. More surprisingly, we find that a substantial share of employment in service occupations, where most US job growth has occurred over the past decades (Autor and Dorn, 2013), are highly susceptible to computerisation.
This may turn out to be correct, though I'd note two reservations I have. First, the model uses (in part) the notoriously unreliable
subjective estimates of AI researchers to assign values to whether
tasks can be automated or not, and second, it uses lists of job
requirements, that the authors acknowledge are not written to assess
whether a job can be easily automated. Indeed, job ads don't list things
that are universal (or nearly so) across humans, such as rudimentary
social intelligence, language understanding, and commonsense. As AI
researcher Ernest Davis points out, there has been “only very limited progress” in equipping robots with commonsense reasoning skills.
What do the authors predict will happen to those whose jobs are
automated out of existence? “Our findings thus imply that as technology
races ahead, low-skill workers will reallocate to tasks that are
non-susceptible to computerisation–i.e., tasks requiring
creative and social intelligence. For workers to win the race, however,
they will have to acquire creative and social skills.” Besides Undercover Boss, one could also consult Mike Rose's excellent book The Mind at Work: Valuing the Intelligence of the American Worker in order to lay to rest the notion that low wageworkers lack creative and social skills.
Still, Frey and Osborne are pointing toward a quite urgent and
important issue: how we can best structure our education system and
ensure ready access to retraining services so that everyone has a fair
shot at thriving in the labor market of the future. And as Matthew
Yglesias of Slate notes in his overview of Tyler Cowen's latest book on related issues, Average Is Over,
various policy changes could enable more equitable social outcomes from
the spread of intelligent machines we can expect this century.
However, let's keep in mind that technology does not proceed
autonomously, detached from any human influence. It is our tax dollars
that fund most of the basic research underlying automation technologies,
humans are designing these systems, and consumers have at least some
say in how well automated service technologies fare in the market. I can
imagine, for example, that “made (or served) by humans” could be the
“organic” or “fair trade” of the future. If we as a society collectively
vote with our wallets for good customer service by real people, the
future may just look different from the often gloomy predictions of
science fiction. After all, if there's one thing humans will always be
better at than machines, it's being human.
Miles Brundage is a Ph.D. student in Human and Social Dimensions of Science and Technology at Arizona State University.
Miles Brundage is a Ph.D. student in Human and Social Dimensions of Science and Technology at Arizona State University.
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