But
this is clearly an issue which educationists need to start thinking
about and creating responses/positions, before the school managements / education systems eagerly welcome such possibilities, that the Google's of
the world will offer.... of control of teaching-learning. Overall, a
political response will be required to regulate/direct these
technological trends.
Comments, feedback welcome.
Guru
Source -
https://www.nytimes.com/2017/06/24/opinion/sunday/artificial-intelligence-economic-inequality.html?action=click&pgtype=Homepage&version=Moth-Visible&moduleDetail=inside-nyt-region-1&module=inside-nyt-region®ion=inside-nyt-region&WT.nav=inside-nyt-regionBy KAI-FU LEEJUNE 24, 2017
BEIJING — What worries you about the coming world of artificial intelligence?
Too
often the answer to this question resembles the plot of a sci-fi
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 common-sense 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.
---
Kai-Fu Lee is the chairman and chief
executive of Sinovation Ventures, a venture capital firm, and the
president of its Artificial Intelligence Institute.