3. BY ARTHUR MACEWAN
September/October 2016
Dear Dr. Dollar:
What’s the story with artificial intelligence and jobs? Wil l the
appli-
cation of robotics to production really lead to massive
unemployment?
—Anonymous, via email
In the late 1970s, my early years at the University of
Massachusetts Boston (UMB), the Department of Economics
had two secretaries. When I retired,
in 2008, the number of faculty members and students in the
department had in-
creased, but there was only one secretary. All the faculty
members had their own
computers, with which they did much of the work that
secretaries had previously
done.
I would guess that over those thirty years, the number of
departmental secre-
taries and other secretaries in the university declined by as
many as 100, replaced
by information technology—what has now become the
foundation of artificial in-
telligence. As I started writing this column, however, I looked
on the university’s
web site and counted about 100 people with jobs in various
parts of the Information
Technology Department. Neither this department nor those jobs
existed in my early
years at UMB. The advance in technology that eliminated so
many secretaries also
created as many jobs as it eliminated—perhaps more.
4. My little example parallels the larger and more widely cited
changes on U.S.
farms in the 20th century—a century when the diesel engine,
artificial fertilizers,
and other products of industry reduced the percentage of the
labor force working on
farms from 40% to 2%. No massive unemployment resulted
(though a lot of horses,
mules, and oxen did lose their jobs). The great expansion of
urban industrial produc-
tion along with the growth of the service sector created
employment that balanced
the displacement of workers on the farms.
Other cases are cited in debates over the impact of artificial
intelligence, ex-
amples ranging from handloom weavers’ resistance to new
machinery in the early
stages of the Industrial Revolution to a widespread concern
about “automation” in
the 1960s. Generally, however, the new technologies, while
displacing workers in
some realms of production, also raised productivity and
economic growth. There
has, as a result, been increased demand for old products and
demand for new prod-
ucts, creating more and different jobs.
Historically, it seems, each time prophecies foretold massive
unemployment re-
sulting from major technological innovations, they turned out to
be wrong. Indeed,
often the same forces that threatened existing jobs created new
jobs. The transitions
were traumatic and harmful for the people losing their jobs, but
7. are arguing that
artificial intelligence—sophisticated robotics—is different from
past technological
shifts, will replace human labor of virtually all types, and could
generate massive
unemployment. Are things really different this time? Just
because someone, once
again, walks around with a sign saying, “The world is about
end,” doesn’t mean the
world really isn’t about to end!
In much of modern history, the substitution of machines for
people has in-
volved physical labor. That was the case with handloom
weavers in the early 19th
century and is a phenomenon we all take for granted when we
observe heavy ma-
chinery, instead of hand labor, on construction sites. Even as
robotics entered indus-
try, as on automobile assembly lines, the robots were doing
tasks that had previously
been done with human physical labor.
“Robotics” today, however, involves much more than the
operation of tradi-
tional robots, the machines that simulate human physical labor.
Robots now are
rapidly approaching the ability, if they do not already have it, to
learn from expe-
rience, respond to changes in situations, compare, compute,
read, hear, smell, and
make extremely rapid adjustments (“decisions”) in their
actions—which can include
everything from moving boxes to parsing data. In part, these
capabilities are results
of the extreme progress in the speed and memory capacity of
8. computers.
They are also the result of the emergence of “Cloud Robotics”
and “Deep Learn-
ing.” In Cloud Robotics, each robot gathers information and
experiences from other
robots via “the cloud” and thus learns more and does so more
quickly. Deep Learning
involves a set of software that is designed to simulate the
human neocortex, the part of
the brain where thinking takes place. The software (also often
cloud-based) recognizes
patterns—sounds, images, and other data—and, in effect, learns.
While individual robots—like traditional machines—are often
designed for
special tasks, the basic robot capabilities are applicable to a
broad variety of activi-
ties. Thus, as they are developed to the point of practical
application, they can be
brought into a wide variety of activities during the same period.
Moreover, accord-
ing to those who believe “this time is different,” that period of
transition is close at
hand and could be very short. The disruption of human labor
across the economy
would happen virtually all at once, so adjustments would be
difficult—thus, the
specter of massive unemployment.
Skepticism
People under thirty may take much of what is happening with
information technol-
ogy (including artificial intelligence) for granted, but those of
us who are older find
11. tr
ib
ut
e.
many, many jobs will be replaced. But as with historical
experience, the expansion
of productivity and the increase of average income will tend to
generate rising de-
mand, which will be met with both new products and more of
the old ones; new
jobs will open up and absorb the labor force. (But hang on to
that phrase “aver-
age income.”)
Real Problems
Even if my skepticism is warranted, the advent of the era of
artificial intelligence will
create real problems, perhaps worse than in earlier eras. Most
obvious, even when
society in general (on average) gains, there are always losers
from economic change.
Workers who get replaced by robots may not be the ones who
find jobs in new or
expanding activity elsewhere. And, as has been the case for
workers who lost their
jobs in the Great Recession, those who succeed in finding new
jobs often do so only
with lower wages.
Beyond the wage issue, the introduction of new machinery—
traditional ma-
chines or robots—often affects the nature and, importantly, the
12. speed of work. The
mechanized assembly line is the classic example, but
computers—and, we can as-
sume, robotics more generally—allow for more thorough
monitoring and control of
the activity of human workers. The handloom weavers who
opposed the introduc-
tion of machines in the early 19th century were resisting the
speed-up brought by
the machines as well as the elimination of jobs. (The Luddite
movement of North-
west England, while derided for incidents of smashing
machines, was a reaction to
real threats to their lives.)
More broadly, there is the question of how artificial intelligence
will affect the
distribution of income. However intelligent robots may be, they
are still machines
which, like slaves, have owners (whether owners of physical
hardware, patents on the
machines, or copyrights on the software). Will the owners be
able to reap the lion’s
share of the gains that come with the rising productivity of this
major innovation?
In the context of the extremely high degree of inequality that
now exists as artificial
intelligence is coming online, there is good reason for concern.
As has been the case with the information technology
innovations that have al-
ready taken place—Microsoft, Apple, Google, and Facebook
leap to mind—highly
educated or specially skilled (or just lucky) workers are likely
to share some of the
gains from artificial intelligence. But with the great inequalities
14. D
o not copy or distribute.
Co
py
ri
gh
t E
co
no
m
ic
A
ff
ai
rs
B
ur
ea
u,
In
c.
D
o
15. no
t c
op
y
or
d
is
tr
ib
ut
e.
Over the long run, technological improvements that generate
greater productivity
have yielded some widely shared benefits. In the United States
and other high-income
countries, workers’ real incomes have risen substantially since
the dawn of the Indus-
trial Revolution. Moreover, a significant part of the gains for
workers has come in the
form of an increase in leisure time. Rising productivity from
artificial intelligence
holds out the possibility, in spite of the trends of recent
decades, for a shift away from
consumerism towards a resumption of the long-term trend
toward more leisure—and,
I would venture, more pleasant lives.
Yet, even as economic growth over the past 200 years has meant
absolute gains for
working people, some groups have fared much better than
16. others. Moreover, even with
absolute gains, relative gains have been limited. With some
periods of exception, great
inequalities have persisted, and those inequalities weigh heavily
against the absolute rises
in real wages and leisure. (And in some parts of the last two
centuries—the last few de-
cades in particular—gains for working people have followed
from rising productivity
and economic growth.)
So even though I’m skeptical that artificial intelligence will
generate massive
unemployment, I fear that it may reinforce, and perhaps
increase, economic in-
equality. q
Sources: David H. Autor, “Whey Are There Still So Many Jobs?
The History and Future of
Workplace Automation,” Journal of Economic Perspectives,
Summer 2015; Johan Mokyr, Chris
Vickers and Nicolas L. Ziebarth, “The History of Technological
Anxiety and the Future of
Economic Growth: Is This Time Different?” Journal of
Economic Perspectives, Summer 2015; Gill
A. Pratt, “Is a Cambrian Explosion Coming for Robotics?”
Journal of Economic Perspectives,
Summer 2015; The Economist, Special Report on Artificial
Intelligence, “The Return of the
Machinery Question,” June 15, 2016 (economist.com); Robert
D. Hof, “Deep Learning,” MIT
Technology Review, 2016 (technologyreview.com); Andrew
Figura and David Ratner, “The Labor
Share of Income and Equilibrium Unemployment, Accessible
Data,” FEDS Notes, June 8, 2015
(federalreserve.gov).
