What Jobs Will the Robots Take?
Nearly half of American jobs today could be automated in "a decade or two," according to new research. The question is: Which half?
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It
is an invisible force that goes by many names. Computerization.
Automation. Artificial intelligence. Technology. Innovation. And,
everyone's favorite, ROBOTS.
Whatever name you prefer, some form of it has been stoking
progress and killing jobs—from seamstresses to paralegals—for
centuries. But this time is different: Nearly half of American jobs today could be automated in "a decade or two," according to a new paper by Carl Benedikt Frey and Michael A. Osborne, discussed recently in The Economist. The question is: Which half?
Another way of posing the same question is: Where do
machines work better than people? Tractors are more powerful than
farmers. Robotic arms are stronger and more tireless than assembly-line
workers. But in the past 30 years, software and robots have thrived at
replacing a particular kind of occupation: the average-wage,
middle-skill, routine-heavy worker, especially in manufacturing and
office admin.
Indeed, Frey and Osborne project that the next wave of
computer progress will continue to shred human work where it already
has: manufacturing, administrative support, retail,
and transportation. Most remaining factory jobs are "likely to diminish
over the next decades," they write. Cashiers, counter clerks, and
telemarketers are similarly endangered. On the far right side of this
graph, you can see the industry breakdown of the 47 percent of jobs they
consider at "high risk."
And, for the nitty-gritty breakdown, here's a chart of the ten jobs with a 99-percent
likelihood of being replaced by machines and software. They are mostly
routine-based jobs (telemarketing, sewing) and work that can be solved
by smart algorithms (tax preparation, data entry keyers, and insurance
underwriters). At the bottom, I've also listed the dozen jobs they
consider least likely to be automated. Health care workers, people entrusted with our safety, and management positions dominate the list.
If you wanted to use this graph as a guide to the future of automation, your upshot would be: Machines are better at rules and routines; people are better at directing and diagnosing. But it doesn't have to stay that way.
The Next Big Thing
Predicting the future typically means extrapolating the
past. It often fails to anticipate breakthroughs. But it's precisely
those unpredictable breakthroughs in computing that could have the
biggest impact on the workforce.
For example, imagine somebody in 2004 forecasting the next
ten years in mobile technology. In 2004, three years before the
introduction of the iPhone, the best-selling mobile device, the Nokia
2600, looked like this:
Many extrapolations of phones from the early 2000s were just "the same thing, but smaller." It
hasn't turned out that way at all: Smartphones are hardly phones, and
they're bigger than the Nokia 2600. If you think wearable technology or
the "Internet of Things" seem kind of stupid today, well, fine. But
remember that ten years ago, the future of mobile appeared to be a
minuscule cordless landline phone with Tetris, and now smartphones sales are about to overtake computers. Breakthroughs can be fast.
We might be on the edge of a breakthrough moment in
robotics and artificial intelligence. Although the past 30 years have
hollowed out the middle, high- and low-skill jobs have actually
increased, as if protected from the invading armies of robots by their
own moats. Higher-skill workers have been protected by a kind of
social-intelligence moat. Computers are historically good at executing
routines, but they're bad at finding patterns, communicating with
people, and making decisions, which is what managers are paid to do.
This is why some people think managers are, for the moment, one of the
largest categories immune to the rushing wave of AI.
Meanwhile, lower-skill workers have been protected by the
Moravec moat. Hans Moravec was a futurist who pointed out that machine
technology mimicked a savant infant: Machines could do long math
equations instantly and beat anybody in chess, but they can't answer a
simple question or walk up a flight of stairs. As a result, menial work
done by people without much education (like home health care workers, or
fast-food attendants) have been spared, too.
But perhaps we've hit an inflection point. As Erik Brynjolfsson and Andrew McAfee pointed out in their book Race Against the Machine (and in their new book The Second Machine Age),
robots are finally crossing these moats by moving and thinking like
people. Amazon has bought robots to work its warehouses. Narrative
Science can write earnings summaries that are indistinguishable from
wire reports. We can say to our phones I'm lost, help and our phones can tell us how to get home.
Computers that can drive cars, in particular, were never
supposed to happen. Even ten years ago, many engineers said it was
impossible. Navigating a crowded street isn't mindlessly routine. It
needs a deft combination of spacial awareness, soft focus, and constant
anticipation--skills that are quintessentially human. But I don't need
to tell you about Google's self-driving cars, because they're one of the
most over-covered stories in tech today.
And that's the most remarkable thing: In a decade, the idea of computers driving cars went from impossible to boring.
The Human Half
In the 19th century, new manufacturing technology replaced
what was then skilled labor. Somebody writing about the future of
innovation then might have said skilled labor is doomed. In the second
half of the 20th century, however, software technology took the place of
median-salaried office work, which economists like David Autor have
called the "hollowing out" of the middle-skilled workforce.
The first wave showed that machines are better at
assembling things. The second showed that machines are better at
organization things. Now data analytics and self-driving cars suggest
they might be better at pattern-recognition and driving. So what are we better at?
If you go back to the two graphs in this piece to locate
the safest industries and jobs, they're dominated by managers,
health-care workers, and a super-category that encompasses education,
media, and community service. One conclusion to draw from this is that
humans are, and will always be, superior at working with, and caring
for, other humans. In this light, automation doesn't make the world
worse. Far from it: It creates new opportunities for human ingenuity.
But robots are already creeping into diagnostics and surgeries.
Schools are already experimenting with software that replaces teaching
hours. The fact that some industries have been safe from automation for
the last three decades doesn't guarantee that they'll be safe for the
next one. As Frey and Osborne write in their conclusion:
While computerization has been historically confined to routine tasks involving explicit rule-based activities, algorithms for big data are now rapidly entering domains reliant upon pattern recognition and can readily substitute for labour in a wide range of non-routine cognitive tasks. In addition, advanced robots are gaining enhanced senses and dexterity, allowing them to perform a broader scope of manual tasks. This is likely to change the nature of work across industries and occupations.It would be anxious enough if we knew exactly which jobs are next in line for automation. The truth is scarier. We don't really have a clue.
Derek Thompson is a senior editor at The Atlantic, where he oversees the Business Channel.
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