What History Tells Us About the Accelerating AI Revolution
What
History Tells Us About the Accelerating AI Revolution
3d rendering robot learning or machine learning with education hud interface PHOTO: GETTY IMAGES/ISTOCKPHOTO
By Irving Wladawsky-Berger May 22, 2020 1:40 pm ET
A few weeks before our lives were turned upside down by Covid-19,
I read Technology
at Work v4.0,
the fourth report in the Technology
at Work Series developed
by Citigroup in collaboration with Oxford University. The report includes an
excellent chapter on What History Tells Us About the Coming AI Revolution by
Oxford professor Carl
Benedikt Frey based
on his 2019 book The
Technology Trap.
Recent AI advances have “sparked much excitement… yet
despite this, most ordinary people don’t feel particularly optimistic about the
future,” wrote Mr. Frey. For example, a 2017
Pew Research survey found that three quarters of Americans
expressed serious concerns about AI and automation, and just over a third
believe that their children will be better off financially than they were.
But, in fact, serious
concerns about the
impact of technology are part of a historical pattern. “Many of the
trends we see today, such as the disappearance of middle-income jobs, stagnant
wages and growing inequality were also features of the Industrial Revolution,”
he writes.
“We are at the brink of a technological revolution that promises
not just to fundamentally alter the structure of our economy, but also to
reshape the social fabric more broadly. History tells us anxiety tends to
accompany rapid technological change, especially when technology takes the form
of capital which threatens people’s jobs.”
As the Covid-19 pandemic looks to likely
accelerate the
rate and pace of technological change, what can we learn from the Industrial
Revolution that can help us better face our emerging AI revolution? Let
me summarize some of Mr. Frey’s key points.
Over the past two centuries we’ve
learned that there’s
a significant
time lag, between the broad
acceptance of major new transformative technologies and their long-term
economic and productivity growth. This is particularly the case for
General Purpose Technologies like the steam engine, electricity or computers,
which have the potential to radically reshape entire economies and societal
norms.
The life cycle of such historically
transformative technologies consists
of two phases: investments and harvesting. In
their initial phase, transformative technologies require massive complementary investments,
such as business process redesign, co-invention of new products and business
models, and the re-skilling of the workforce. The more transformative the
technologies, the longer it takes them to reach the harvesting phase
when they’re widely embraced by companies and industries across the economy.
The time lags between the investment and harvesting phases are
typically quite long. Mr. Frey cites several historical examples. While James Watt’s steam engine ushered the
Industrial Revolution in the 1780s, “British factories were for the most part
powered by water up until the 1840.”
Similarly, productivity growth did not increase until 40 years
after the introduction of electric power in the early 1880s.
Computers followed a similar pattern. While first deployed
in business in the ’50s and ’60s, computers were too bulky, expensive and
difficult to program to have any meaningful impact on jobs, wages and
productivity. As was the case with factory electrification, companies had
to rethink their overall operations to take full advantage of the new digital
technologies.
“Productivity growth has slowed since 2005, but seen through the
lens of history it is not all that puzzling,” noted Mr. Frey.
Despite the recent hype, we’re still in the early
stages of AI’s
deployment. In their early stages, the extensive investments required to
embrace a GPT like AI will generally reduce productivity growth. For example, a
recent Brookings Institution report estimated that between 2014 and
2017 investments in autonomous vehicles amounted to roughly $80 billion with
almost no returns, lowering labor productivity by 0.1 percent per year over
this period.
Mr. Frey wrote that “the short run consequences of rapid technological
change can be devastating for working people, especially when technology takes
the form of capital which substitutes for labor.” In the long run, the
Industrial Revolution led to a rising standard of living, improved health, and
many other benefits. “Yet in the short run, the lives of working people
got nastier, more brutish, and shorter. And what economists regard as ‘the
short run’ was a lifetime, for some,” given that it generally takes decades to
realize the benefits of transformative technologies.
A 2017 McKinsey study concluded that while a growing
technology-based economy will create a significant number of new occupations,
as has been the case in the past, “the transitions will be very challenging -
matching or even exceeding the scale of shifts out of agriculture and
manufacturing we have seen in the past.”
The US and other industrial economies have seen a remarkable rise
in the polarization of job opportunities and wage inequality by educational attainment, with
the earnings of the most-educated increasing, and the earnings of the
least-educated falling in real terms. Since the 1980s, the earnings of those
with a four year college degree have risen by 40% to 60%, while the earnings of
those with a high school education or less have fallen among men and barely
changed among women.
“Historically, the way people have adjusted to technological
change is by acquiring new skills… During the twentieth century, the expansion
of education was critical to helping people adjust to the accelerating pace of
change,” he writes. “And those skills must be regularly updated as technology
progresses. When upskilling is lagging behind, entire social groups might end
up being excluded from the growth engine.”
Irving Wladawsky-Berger worked at IBM from 1970 to 2007, and has
been a strategic adviser to Citigroup, HBO and Mastercard and a visiting
professor at Imperial College. He's been affiliated with MIT since 2005, and is
a regular contributor to CIO Jour.
Comments
Post a Comment