Treasury Secretary Mnuchin says AI taking US jobs is '50-100 more years' away — but it's already beginning to happen

Steven Mnuchin.
Yuri
Gripas/Reuters

On Friday, US Treasury Secretary Steven Mnuchin
answered a slew of questions in an interview with Axios’ Mike
Allen about the global economy and US labor market, including
about the threat of artificial intelligence (AI) affecting
American jobs.

Mnuchin is not overly worried. Concerns about AI and jobs
are so far way “it’s not even on our radar
screen… 50-100 more years” away, he said,
according to Axios.

“I’m not worried at all” about robots displacing humans in the
near future, he said, before adding, “In fact, I’m optimistic.”

However, studies have estimated that AI could affect jobs much
sooner than that. And, crucially, technological advancements
will likely not only be impacting the manufacturing
sector.

In
a paper published in 2013, Oxford University’s Carl
Benedikt Frey and Michael A. Osborne looked at which current jobs
are susceptible to technological innovations such as machine
learning, and estimated the probability that the 702 different
occupations they looked at will be computerized.

Notably, they did not estimate the number of jobs that
will actually be automated, but rather a given
occupation’s “potential job automatability” over an
unspecified number of years.

They found that about 47% of total US employment is in the high
risk category, which the team defined as jobs they expect could
be automated “relatively soon, perhaps over the next decade or
two.”

They discuss the model and its results in greater detail
(emphasis ours):

“Our model predicts that most workers in transportation
and logistical occupations, together with the bulk of office and
administrative support workers, and labor in production
occupations, are at risk. These finds 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
computerization. Additional support for this finding is
provided by the recent growth in the market for service robots
(MGI, 2013) and the gradually diminishment of the comparative
advantage of human labor in tasks involving mobility and
dexterity (Robotics-VO, 2013).”

Osborne and Frey included a chart in their paper showing the
probability of computerization for a given job versus the number
of people employed in that job:

Michael
Osborne and Carl Benedikt Frey/Oxford University

High-skill jobs under the categories of “management, business,
and financial,” “healthcare practitioners and technical,” and
“computer, engineering, and science” saw lower likelihoods of
automation, while “service,” “sales and related,” “transportation
and material moving,” and “office and administrative support”
have higher probabilities.

One particularly notable thing here, as the authors write in the
above paragraph, is many of the jobs that are highly susceptible
to computerization are in the services sector, which has seen the
most job growth over the past few decades as the US has
transitioned from a
manufacturing-based economy to a services-based one.

In other words, although the recent political cycle has focused
primarily on manufacturing and construction jobs — and, indeed,
those are susceptible to being automated away, according to Frey
and Osbourne — this study suggests that they are not the only
jobs “at risk.” To take it a step further, this suggests
manufacturing jobs are not the only jobs economists, politicians,
and policymakers should be focusing on.

For a clearer but less detailed look, a Morgan Stanley team
led by Elga Bartsche put together a chart
last year using select data from Frey and Osborne, showing
the probability of some of the more popular service sector
jobs becoming automatable.

As you can see below, within the services sector, jobs that
requiring high-level analytical thinking and problem solving
(physicians or surgeons),
originality and/or performance (musicians and
singers), and even highly unpredictable personal interactions
(elementary school teachers) have lower probabilities of becoming
automated. 

On the other hand, low-skill services sector jobs such as
receptionists, paralegals, and even taxi drivers, are more likely
to be automated.

Morgan
Stanley

Already we are seeing some of this happen in real-time. As
an example of a low-skill service sector job getting automated,
we can look at Panera Bread, a fast-casual restaurant chain,
which has started
replacing human cashiers with kiosks. Moreover,
Uber is testing self-driving cars. 

In their paper, Frey and Osborne cite the example of
computerization entering legal services. They write,
“specifically, law firms now rely on computers that can scan
thousands of legal briefs and precedents to assist in pre-trial
research.”

Of course, the effects of technological advancements on
the US labor market aren’t all negative. For example, with
computerization entering legal services and taking care of the
more mindless, repetitive work, a legal team can allocate
resources and people to other tasks and hire more people with
different skill sets. And so, in a sense, the team as a whole
works with the computer as opposed to against it
for a net-advantage.

But the question of what will happen to folks who will lose their
jobs to automation remains.

Looking ahead, the authors write in their conclusion:

“Finally, we provide evidence that wages and educational
attainment exhibit a strong negative relationship with the
probability of computerization. We note that this finding implies
a discontinuity between the 19th, 20th and the 21st
century in the impact of capital deepening on the relative
demand for skilled labour. While nineteenth century manufacturing
technologies largely substituted for skilled labour through the
simplification of tasks, the Computer Revolution of the twentieth
century caused a hollowing-out of middle-income jobs.

Our model predicts a truncation in the current trend towards
labor market polarization, with computerization being principally
confined to low-skill and low-wage occupations. Our
findings thus imply that as technology races ahead, low-skill
workers will reallocate to tasks that are non-susceptible to
computerization – i.e., tasks requiring creative and social
intelligence. For workers to win the race, however, they will
have to acquire creative and social skills.”

In other words, they write that low-skill workers would
theoretically have to re-adjust to find jobs that require
creative and social intelligence skills.

However, as we have seen with the US’ transition
from manufacturing
to services, re-adjusting sometimes takes time
as some
workers benefit significantly
more than others.