The next phase of automation, relying on AI and AI-powered machines such as
self-driving cars, may be even more disruptive, especially if it is not
accompanied by other types of more human-friendly technologies. This broad
technological platform, with diverse applications and great promise, could
help human productivity and usher in new human tasks and competencies in
education, health care, engineering, manufacturing, and elsewhere. But it
could also worsen job losses and economic disruption if applied exclusively
for automation.
The pandemic has certainly given employers more reasons to look for ways of
substituting machines for workers, and recent evidence suggests they are
doing so (Chernoff and Warman 2020).
Some argue that pervasive automation is the price we pay for prosperity:
new technologies will increase productivity and enrich us, even if they
dislocate some workers and disrupt existing businesses and industries. The
evidence does not support this interpretation.
Despite the bewildering array of new machines and algorithms all around us,
the US economy today generates very low total factor productivity
growth—economists’ headline measure of the productivity performance of an
economy, which gauges how efficiently human and physical capital resources
are being used. In particular, total factor productivity growth has been
much lower over the past 20 years than during the decades after World War
II (Gordon 2017). Even though information and communication technology has
advanced rapidly and is applied in every sector of the economy, industries
that rely more intensively on these technologies have not performed better
in terms of total factor productivity, output, or employment growth
(Acemoglu and others 2014).
The reasons for this recent slow productivity growth are not well
understood. But one contributing factor appears to be that many automation
technologies, such as self-checkout kiosks or automated customer service,
are not generating much total factor productivity growth. Put differently,
rather than bringing productivity dividends, automation has been excessive
because businesses are adopting automation technologies beyond what would
reduce production costs or because these technologies have social costs
because they give rise to lower employment and worker wages. Excessive
automation may also be a cause of the slowdown in productivity growth. This
is because automation decisions are not reducing costs and, even more
important, because a singular focus on automation technologies may be
causing businesses to miss out on productivity gains from new tasks, new
organizational forms, and technological breakthroughs that are more
complementary to humans.
But is automation really excessive? I believe so. First of all, when
employers make decisions about whether to replace workers with machines,
they do not take into account the social disruption caused by the loss of
jobs—especially good ones. This creates a bias toward excessive automation.
Even more important, several factors appear to have fueled automation
beyond socially desirable levels. Particularly important has been the
transformation in the corporate strategies of leading US companies.
American and world technology is shaped by the decisions of a handful of
very large, very successful tech companies that have tiny workforces and a
business model built on automation (Acemoglu and Restrepo 2020). Big Tech
companies including Amazon, Alibaba, Alphabet, Facebook, and Netflix are
responsible for more than $2 of every $3 spent globally on AI (McKinsey
Global Institute 2017). Their vision, centered on the substitution of
algorithms for humans, influences not only their own spending but also what
other companies prioritize and the aspirations and focus of hundreds of
thousands of young students and researchers specializing in computer and
data sciences.
Of course there is nothing wrong with successful companies pursuing their
own vision, but when this becomes the only game in town, we must be on
guard. Past technological successes have more often than not been driven by
a diversity of perspectives and approaches. If we lose this diversity, we
also risk losing our technological edge.
The dominance of a handful of companies over the path of future technology
has been exacerbated as well by dwindling support from the US government
for fundamental research (Gruber and Johnson 2019). In fact, government
policy excessively encourages automation, especially through the tax code.
The US tax system has always treated capital more favorably than labor,
encouraging businesses to substitute machines for workers, even when
workers may be more productive.
My research with Andrea Manera and Pascual Restrepo shows that, over the
past 40 years, labor has paid an effective tax rate of more than 25 percent
via payroll and federal income taxes (Acemoglu, Manera, and Restrepo 2020).
Even 20 years ago, capital was more lightly taxed than labor, with
equipment and software investment facing tax rates of about 15 percent.
This differential has widened with tax cuts on high incomes, the conversion
of many businesses to closely held S corporations that are exempt from
corporate income taxes, and generous depreciation allowances. As a result
of these changes, investments in software and equipment are taxed at rates
of less than 5 percent today, and in some cases corporations can even
derive net subsidies when they invest in capital. This creates a powerful
motive for excessive automation.
A path of future technology centered on automation is not preordained. It
is a consequence of choices by researchers who focus on automation
applications at the expense of other uses of technology and by companies
that build business models on automation and reducing labor costs rather
than on broad-based productivity increases. We can make different choices.
But such a course correction calls for a concerted effort to redirect
technological change, which can happen only if government plays a central
role in the regulation of technology.
Let me be clear that I do not mean government blocking technology or
slowing technological progress. Rather, the government should provide
incentives that tilt the composition of innovation away from an excessive
focus on automation and more toward human-friendly technologies that
produce employment opportunities, especially good jobs, and a more shared
form of economic prosperity. We do not know exactly what the most
transformative human-friendly technologies of the future may be, but many
sectors provide plenty of opportunities. These include education, where AI
can be used for much more adaptive and student-centered teaching combining
new technologies and better-trained teachers; health care, where AI and
digital technologies can empower nurses and technicians to provide more and
better services; and modern manufacturing, where augmented reality and
computer vision can increase human productivity in the production process.
We have also witnessed during the pandemic how new digital technologies,
such as Zoom, have fundamentally broadened human communication and
capabilities.