The
Real Threat of Artificial Intelligence
By
KAIFU LEE JUNE 24, 2017 BEIJING —
NY
Times Sunday Review
What
worries you about the coming world of artificial intelligence? Too often the
answer to this question resembles the plot of a scifi thriller. People worry
that developments in A.I. will bring about the “singularity” — that point in
history when A.I. surpasses human intelligence, leading to an unimaginable
revolution in human affairs. Or they wonder whether instead of our controlling
artificial intelligence, it will control us, turning us, in effect, into
cyborgs.
These
are interesting issues to contemplate, but they are not pressing. They concern
situations that may not arise for hundreds of years, if ever. At the moment,
there is no known path from our best A.I. tools (like the Google computer
program that recently beat the world’s best player of the game of Go) to
“general” A.I. — self-aware computer programs that can engage in commonsense
reasoning, attain knowledge in multiple domains, feel, express and understand
emotions and so on.
This
doesn’t mean we have nothing to worry about. On the contrary, the A.I. products
that now exist are improving faster than most people realize and promise to
radically transform our world, not always for the better. They are only tools,
not a competing form of intelligence. But they will reshape what work means and
how wealth is created, leading to unprecedented economic inequalities and even
altering the global balance of power. It is imperative that we turn our
attention to these imminent challenges.
What
is artificial intelligence today? Roughly speaking, it’s technology that takes
in huge amounts of information from a specific domain (say, loan repayment
histories) and uses it to make a decision in a specific case (whether to give
an individual a loan) in the service of a specified goal (maximizing profits
for the lender). Think of a spreadsheet on steroids, trained on big data. These
tools can outperform human beings at a given task. This kind of A.I. is
spreading to thousands of domains (not just loans), and as it does, it will
eliminate many jobs. Bank tellers, customer service representatives,
telemarketers, stock and bond traders, even paralegals and radiologists will
gradually be replaced by such software. Over time this technology will come to
control semiautonomous and autonomous hardware like self-driving cars and
robots, displacing factory workers, construction workers, drivers, delivery
workers and many others.
Unlike
the Industrial Revolution and the computer revolution, the A.I. revolution is not
taking certain jobs (artisans, personal assistants who use paper and
typewriters) and replacing them with other jobs (assembly-line workers,
personal assistants conversant with computers). Instead, it is poised to bring
about a wide-scale decimation of jobs — mostly lower-paying jobs, but some
higher-paying ones, too. This transformation will result in enormous profits
for the companies that develop A.I., as well as for the companies that adopt
it.
Imagine how much money a company like Uber would make if it
used only robot drivers. Imagine the profits if Apple could manufacture its
products without human labor. Imagine the gains to a loan company that could
issue 30 million loans a year with virtually no human involvement. (As
it happens, my venture capital firm has invested in just such a loan company.)
We are thus facing two developments that do not sit easily together: enormous
wealth concentrated in relatively few hands and enormous numbers of people out
of work.
What
is to be done? Part of the answer will involve educating or retraining people
in tasks A.I. tools aren’t good at. Artificial intelligence is poorly suited
for jobs involving creativity, planning and “cross-domain” thinking — for
example, the work of a trial lawyer. But these skills are typically required by
high-paying jobs that may be hard to retrain displaced workers to do. More
promising are lower-paying jobs involving the “people skills” that A.I. lacks:
social workers, bartenders, concierges — professions requiring nuanced human
interaction. But here, too, there is a problem: How many bartenders does a
society really need?
The
solution to the problem of mass unemployment, I suspect, will involve “service jobs of love.” These are jobs that A.I. cannot do,
that society needs and that give people a sense of purpose. Examples
include accompanying an older person to visit a doctor, mentoring at an
orphanage and serving as a sponsor at Alcoholics Anonymous — or, potentially
soon, Virtual Reality Anonymous (for those addicted to their parallel lives in
computer-generated simulations). The volunteer service jobs of today, in other
words, may turn into the real jobs of the future. Other volunteer jobs may be
higher-paying and professional, such as compassionate medical service
providers who serve as the “human interface” for A.I. programs that diagnose
cancer.
In
all cases, people will be able to choose to work fewer hours than they do now.
Who will pay for these jobs? Here is where the enormous wealth concentrated in
relatively few hands comes in. It strikes me as unavoidable that large chunks
of the money created by A.I. will have to be transferred to those whose jobs
have been displaced. This seems feasible only through Keynesian policies of
increased government spending, presumably raised through taxation on wealthy
companies. As for what form that social welfare would take, I would argue for a
conditional universal basic income: welfare
offered to those who have a financial need, on the condition they either show
an effort to receive training that would make them employable or commit to a
certain number of hours of “service of love” voluntarism.
To
fund this, tax rates will have to be high. The government will not only have to
subsidize most people’s lives and work; it will also have to compensate for the
loss of individual tax revenue previously collected from employed individuals.
This leads to the final and perhaps most consequential challenge of A.I. The
Keynesian approach I have sketched out may be feasible in the United States and
China, which will have enough successful A.I. businesses to fund welfare
initiatives via taxes.
But
what about other countries? They face two insurmountable problems. First, most of the money being made from artificial
intelligence will go to the United States and China. A.I. is an industry
in which strength begets strength: The more data you have, the better your
product; the better your product, the more data you can collect; the more data
you can collect, the more talent you can attract; the more talent you can
attract, the better your product. It’s a virtuous circle, and the United States
and China have already amassed the talent, market share and data to set it in
motion.
For
example, the Chinese speech-recognition company iFlytek and several Chinese
face-recognition companies such as Megvii and SenseTime have become industry
leaders, as measured by market capitalization. The United States is
spearheading the development of autonomous vehicles, led by companies like
Google, Tesla and Uber. As for the consumer internet market, seven American or
Chinese companies — Google, Facebook, Microsoft, Amazon, Baidu, Alibaba and
Tencent — are making extensive use of A.I. and expanding operations to other
countries, essentially owning those A.I. markets. It
seems American businesses will dominate in developed markets and some
developing markets, while Chinese companies will win in most developing
markets.
The
other challenge for many countries that are not China or the United States is
that their populations are increasing, especially in the developing world.
While a large, growing population can be an economic asset (as in China and
India in recent decades), in the age of A.I. it will be an economic liability
because it will comprise mostly displaced workers, not productive ones. So if
most countries will not be able to tax ultra-profitable A.I. companies to
subsidize their workers, what options will they have? I foresee only one:
Unless they wish to plunge their people into poverty, they will be forced to
negotiate with whichever country supplies most of their A.I. software — China
or the United States — to essentially become that country’s economic dependent,
taking in welfare subsidies in exchange for letting the “parent” nation’s A.I.
companies continue to profit from the dependent country’s users.
Such
economic arrangements would reshape today’s geopolitical alliances. One way or
another, we are going to have to start thinking about how to minimize the
looming A.I. fueled gap between the haves and the have-nots, both within and
between nations. Or to put the matter more optimistically: A.I. is presenting
us with an opportunity to rethink economic inequality on a global scale. These
challenges are too far-ranging in their effects for any nation to isolate
itself from the rest of the world.
