>> NARRATOR: Tonight--
>> The race to become an A.I.
superpower is on...
>> NARRATOR: The politics of
artificial intelligence...
>> There will be
a Chinese tech sector
and there will be
a American tech sector.
>> NARRATOR: The new tech war.
>> The more data,
the better the A.I. works.
So in the age of A.I.,
where data is the new oil,
China is the new Saudi Arabia.
>> NARRATOR:
The future of work...
>> When I increase productivity
through automation,
jobs go away.
>> I believe about 50% of jobs
will be somewhat
or extremely threatened by A.I.
in the next 15 years or so.
>> NARRATOR: A.I. and corporate
surveillance...
>> We thought that we were
searching Google.
We had no idea that Google
was searching us.
>> NARRATOR: And the threat
to democracy.
>> China is on its way
to building
a total surveillance state.
>> NARRATOR: Tonight on
"Frontline"...
>> It has pervaded so many
elements of everyday life.
How do we make it transparent
and accountable?
>> NARRATOR:
..."In the Age of A.I."
♪ ♪
♪ ♪
>> NARRATOR: This is the world's
most complex board game.
There are more possible moves
in the game of Go
than there are atoms
in the universe.
Legend has it that in 2300 BCE,
Emperor Yao devised it
to teach his son discipline,
concentration, and balance.
And, over 4,000 years later,
this ancient Chinese game
would signal the start
of a new industrial age.
♪ ♪
It was 2016, in Seoul,
South Korea.
>> Can machines overtake
human intelligence?
A breakthrough moment when the
world champion
of the Asian board game Go
takes on an A.I. program
developed by Google.
>> (speaking Korean):
>> In countries where
it's very popular,
like China and Japan and,
and South Korea, to them,
Go is not just a game, right?
It's, like, how you learn
strategy.
It has an almost spiritual
component.
You know, if you talk
to South Koreans, right,
and Lee Sedol is the world's
greatest Go player,
he's a national hero
in South Korea.
They were sure that Lee Sedol
would beat AlphaGo hands down.
♪ ♪
>> NARRATOR: Google's AlphaGo
was a computer program that,
starting with the rules of Go
and a database
of historical games,
had been designed
to teach itself.
>> I was one of the commentators
at the Lee Sedol games.
And yes, it was watched by tens
of millions of people.
(man speaking Korean)
>> NARRATOR: Throughout
Southeast Asia,
this was seen as
a sports spectacle
with national pride at stake.
>> Wow, that was a player guess.
>> NARRATOR: But much more
was in play.
This was the public unveiling
of a form of artificial
intelligence
called deep learning,
that mimics the neural networks
of the human brain.
>> So what happens with machine
learning,
or artificial intelligence--
initially with AlphaGo--
is that the machine is fed
all kinds of Go games,
and then it studies them,
learns from them,
and figures out its own moves.
And because it's an A.I.
system--
it's not just following
instructions,
it's figuring out its own
instructions--
it comes up with moves that
humans hadn't thought of before.
So, it studies games that humans
have played, it knows the rules,
and then it comes up
with creative moves.
(woman speaking Korean)
(speaking Korean):
>> That's a very...
that's a very surprising move.
>> I thought it was a mistake.
>> NARRATOR: Game two, move 37.
>> That move 37 was a move that
humans could not fathom,
but yet it ended up being
brilliant
and woke people up to say,
"Wow, after thousands
of years of playing,
we never thought about making
a move like that."
>> Oh, he resigned.
It looks like... Lee Sedol has
just resigned, actually.
>> Yeah!
>> Yes.
>> NARRATOR: In the end, the
scientists watched
their algorithms win four
of the games.
Lee Sedol took one.
>> What happened with Go,
first and foremost,
was a huge victory for deep mind
and for A.I., right?
It wasn't that the computers
beat the humans,
it was that, you know, one type
of intelligence beat another.
>> NARRATOR: Artificial
intelligence had proven
it could marshal a vast amount
of data,
beyond anything any human
could handle,
and use it to teach itself how
to predict an outcome.
The commercial implications
were enormous.
>> While AlphaGo is a,
is a toy game,
but its success and its waking
everyone up, I think,
is, is going to be remembered
as the pivotal moment
where A.I. became mature
and everybody jumped
on the bandwagon.
♪ ♪
>> NARRATOR: This is about the
consequences of that defeat.
(man speaking local language)
How the A.I. algorithms are
ushering in a new age
of great potential and
prosperity,
but an age that will also deepen
inequality, challenge democracy,
and divide the world
into two A.I. superpowers.
Tonight, five stories about how
artificial intelligence
is changing our world.
♪ ♪
China has decided to chase
the A.I. future.
>> The difference between
the internet mindset
and the A.I. mindset...
>> NARRATOR: A future made and
embraced by a new generation.
>> Well, it's hard not to feel
the kind of immense energy,
and also the obvious fact
of the demographics.
They're mostly very younger
people,
so that this clearly is
technology which is being
generated by a whole new
generation.
>> NARRATOR: Orville Schell
is one of
America's foremost
China scholars.
>> (speaking Mandarin)
>> NARRATOR: He first came here
45 years ago.
>> When I, when I first came
here, in 1975,
Chairman Mao was still alive,
the Cultural Revolution
was coming on,
and there wasn't a single whiff
of anything
of what you see here.
It was unimaginable.
In fact, in those years,
one very much thought,
"This is the way China is, this
is the way it's going to be."
And the fact that it has gone
through
so many different changes since
is quite extraordinary.
(man giving instructions)
>> NARRATOR: This extraordinary
progress goes back
to that game of Go.
>> I think that the government
recognized
that this was a sort of critical
thing for the future,
and, "We need to catch up
in this," that, you know,
"We cannot have a foreign
company showing us up
at our own game.
And this is going to be
something that is going to be
critically important
in the future."
So, you know, we called it the
Sputnik moment for,
for the Chinese government--
the Chinese government kind of
woke up.
>> (translated): As we often say
in China,
"The beginning is the most
difficult part."
>> NARRATOR: In 2017, Xi Jinping
announced
the government's bold new plans
to an audience
of foreign diplomats.
China would catch up with the
U.S. in artificial intelligence
by 2025 and lead the world
by 2030.
>> (translated): ...and
intensified cooperation
in frontier areas such as
digital economy,
artificial intelligence,
nanotechnology,
and accounting computing.
♪ ♪
>> NARRATOR: Today, China leads
the world in e-commerce.
Drones deliver to rural
villages.
And a society that bypassed
credit cards
now shops in stores
without cashiers,
where the currency
is facial recognition.
>> No country has ever moved
that fast.
And in a short two-and-a-half
years,
China's A.I. implementation
really went from minimal amount
to probably about
17 or 18 unicorns,
that is billion-dollar
companies, in A.I. today.
And that, that progress is,
is hard to believe.
>> NARRATOR: The progress was
powered by a new generation
of ambitious young techs pouring
out of Chinese universities,
competing with each other
for new ideas,
and financed by a new cadre of
Chinese venture capitalists.
This is Sinovation,
created by U.S.-educated A.I.
scientist and businessman
Kai-Fu Lee.
>> These unicorns-- we've got
one, two, three, four, five,
six, in the general A.I. area.
And unicorn means a
billion-dollar company,
a company whose valuation
or market capitalization
is at $1 billion or higher.
I think we put two unicorns
to show $5 billion or higher.
>> NARRATOR: Kai-Fu Lee was born
in Taiwan.
His parents sent him
to high school in Tennessee.
His PhD thesis
at Carnegie Mellon
was on computer speech
recognition,
which took him to Apple.
>> Well, reality is a step
closer to science fiction,
with Apple Computers'
new developed program...
>> NARRATOR: And at 31,
an early measure of fame.
>> Kai-Fu Lee,
the inventor of Apple's
speech-recognition technology.
>> Casper, copy this
to Make Write 2.
Casper, paste.
Casper, 72-point italic outline.
>> NARRATOR: He would move on to
Microsoft research in Asia
and became the head
of Google China.
Ten years ago, he started
Sinovation in Beijing,
and began looking for promising
startups and A.I. talent.
>> So, the Chinese
entrepreneurial companies
started as copycats.
But over the last 15 years,
China has developed its own form
of entrepreneurship, and that
entrepreneurship is described
as tenacious, very fast,
winner-take-all,
and incredible work ethic.
I would say these few thousand
Chinese top entrepreneurs,
they could take on any
entrepreneur
anywhere in the world.
>> NARRATOR: Entrepreneurs like
Cao Xudong,
the 33-year-old C.E.O. of
a new startup called Momenta.
This is a ring road around
Beijing.
The car is driving itself.
♪ ♪
>> You see, another cutting,
another cutting-in.
>> Another cut-in, yeah, yeah.
>> NARRATOR: Cao has no doubt
about the inevitability
of autonomous vehicles.
>> Just like AlphaGo can beat
the human player in, in Go,
I think the machine will
definitely surpass
the human driver, in the end.
>> NARRATOR: Recently, there
have been cautions
about how soon autonomous
vehicles will be deployed,
but Cao and his team are
confident
they're in for the long haul.
>> U.S. will be the first
to deploy,
but China may be the first
to popularize.
It is 50-50 right now.
U.S. is ahead in technology.
China has a larger market,
and the Chinese government
is helping with infrastructure
efforts--
for example, building a new city
the size of Chicago
with autonomous driving enabled,
and also a new highway that has
sensors built in
to help autonomous vehicle
be safer.
>> NARRATOR: Their early
investors included
Mercedes-Benz.
>> I feel very lucky and very
inspiring
and very exciting that we're
living in this era.
♪ ♪
>> NARRATOR: Life in China is
largely conducted
on smartphones.
A billion people use WeChat,
the equivalent of Facebook,
Messenger, and PayPal,
and much more,
combined into just one
super-app.
And there are many more.
>> China is the best place
for A.I. implementation today,
because the vast amount of data
that's available in China.
China has a lot more users than
any other country,
three to four times more than
the U.S.
There are 50 times more mobile
payments than the U.S.
There are ten times more food
deliveries,
which serve as data to learn
more about user behavior
than the U.S.
300 times more shared bicycle
rides,
and each shared bicycle ride
has all kinds of sensors
submitting data up to the cloud.
We're talking about maybe ten
times more data than the U.S.,
and A.I. is basically run on
data and fueled by data.
The more data, the better
the A.I. works,
more importantly than how
brilliant the researcher is
working on the problem.
So, in the age of A.I.,
where data is the new oil,
China is the new Saudi Arabia.
>> NARRATOR: And access to all
that data
means that the deep-learning
algorithm can quickly predict
behavior, like the
creditworthiness of someone
wanting a short-term loan.
>> Here is our application.
And customer can choose how many
money they want to borrow
and how long they want
to borrow,
and they can input
their datas here.
And after, after that, you can
just borrow very quickly.
>> NARRATOR: The C.E.O. shows us
how quickly you can get a loan.
>> It is, it has done.
>> NARRATOR: It takes an average
of eight seconds.
>> It has passed to banks.
>> Wow.
>> NARRATOR:
In the eight seconds,
the algorithm has assessed
5,000 personal features
from all your data.
>> 5,000 features that is
related with the delinquency,
when maybe the banks only use
few, maybe, maybe ten features
when they are doing
their risk amendment.
>> NARRATOR: Processing millions
of transactions,
it'll dig up features that would
never be apparent
to a human loan officer,
like how confidently you type
your loan application,
or, surprisingly,
if you keep your cell phone
battery charged.
>> It's very interesting, the
battery of the phone
is related with their
delinquency rate.
Someone who has much more
lower battery,
they get much more dangerous
than others.
>> It's probably unfathomable
to an American
how a country can dramatically
evolve itself
from a copycat laggard to,
all of a sudden,
to nearly as good as the U.S. in
technology.
>> NARRATOR: Like this
facial-recognition startup
he invested in.
Megvii was started by three
young graduates in 2011.
It's now a world leader in using
A.I. to identify people.
>> It's pretty fast.
For example,
on the mobile device,
we have timed the
facial-recognition speed.
It's actually less
than 100 milliseconds.
So, that's very, very fast.
So 0.1 second that we can, we
will be able to recognize you,
even on a mobile device.
>> NARRATOR: The company claims
the system is better
than any human at identifying
people in its database.
And for those who aren't,
it can describe them.
Like our director--
what he's wearing,
and a good guess at his age,
missing it by only a few months.
>> We are the first one to
really take facial recognition
to commercial quality.
>> NARRATOR: That's why in
Beijing today,
you can pay for your KFC
with a smile.
>> You know, it's not so
surprising,
we've seen Chinese companies
catching up to the U.S.
in technology for a long time.
And so, if particular effort
and attention is paid
in a specific sector,
it's not so surprising
that they would surpass
the rest of the world.
And facial recognition is one of
the, really the first places
we've seen that start to happen.
>> NARRATOR: It's a technology
prized by the government,
like this program in Shenzhen
to discourage jaywalking.
Offenders are shamed in public--
and with facial recognition,
can be instantly fined.
Critics warn that the government
and some private companies
have been building a national
database
from dozens of experimental
social-credit programs.
>> The government wants to
integrate
all these individual behaviors,
or corporations' records,
into some kind of metrics and
compute out a single number
or set of number associated
with a individual,
a citizen, and using that,
to implement a incentive
or punishment system.
>> NARRATOR: A high
social-credit number
can be rewarded with discounts
on bus fares.
A low number can lead
to a travel ban.
Some say it's very popular
with a Chinese public
that wants to punish
bad behavior.
Others see a future that rewards
party loyalty
and silences criticism.
>> Right now, there is no final
system being implemented.
And from those experiments, we
already see that the possibility
of what this social-credit
system can do to individual.
It's very powerful--
Orwellian-like--
and it's extremely troublesome
in terms of civil liberty.
>> NARRATOR: Every evening
in Shanghai,
ever-present cameras record the
crowds
as they surge down to the Bund,
the promenade along the banks
of the Huangpu River.
Once the great trading houses of
Europe came here to do business
with the Middle Kingdom.
In the last century,
they were all shut down
by Mao's revolution.
But now, in the age of A.I.,
people come here to take
in a spectacle
that reflects China's
remarkable progress.
(spectators gasp)
And illuminates the great
political paradox of capitalism
taken root
in the communist state.
>> People have called it
market Leninism,
authoritarian capitalism.
We are watching a kind
of a Petri dish
in which an experiment of, you
know, extraordinary importance
to the world is
being carried out.
Whether you can combine these
things
and get something
that's more powerful,
that's coherent,
that's durable in the world.
Whether you can bring together
a one-party state
with an innovative sector,
both economically
and technologically innovative,
and that's something we thought
could not coexist.
>> NARRATOR:
As China reinvents itself,
it has set its sights
on leading the world
in artificial intelligence
by 2030.
But that means taking on the
world's most innovative
A.I. culture.
♪ ♪
On an interstate
in the U.S. Southwest,
artificial intelligence is at
work solving the problem
that's become emblematic
of the new age,
replacing a human driver.
♪ ♪
This is the company's C.E.O.,
24-year-old Alex Rodrigues.
>> The more things we build
successfully,
the less people ask questions
about how old you are when you
have working trucks.
>> NARRATOR: And this is what
he's built.
Commercial goods are being
driven from California
to Arizona on Interstate 10.
There is a driver in the cab,
but he's not driving.
It's a path set by a C.E.O.
with an unusual CV.
>> Are we ready, Henry?
The aim is to score these pucks
into the scoring area.
So I, I did competitive robotics
starting when I was 11,
and I took it very, very
seriously.
To, to give you a sense, I won
the Robotics World Championships
for the first time
when I was 13.
I've been to worlds seven times
between the ages of 13
and 20-ish.
I eventually founded a team,
did a lot of work at a
very high competitive level.
Things looking pretty good.
>> NARRATOR: This was a
prototype of sorts,
from which he has built his
multi-million-dollar company.
>> I hadn't built a robot in a
while, wanted to get back to it,
and felt that this was by far
the most exciting piece
of robotics technology that was
up and coming.
A lot of people told us we
wouldn't be able to build it.
But knew roughly the techniques
that you would use.
And I was pretty confident that
if you put them together,
you would get something
that worked.
Took the summer off, built in my
parents' garage a golf cart
that could drive itself.
>> NARRATOR: That golf cart
got the attention
of Silicon Valley,
and the first of several rounds
of venture capital.
He formed a team and then
decided the business opportunity
was in self-driving trucks.
He says there's also
a human benefit.
>> If we can build a truck
that's ten times safer
than a human driver, then not
much else actually matters.
When we talk to regulators,
especially,
everyone agrees that the only
way that we're going to get
to zero highway deaths,
which is everyone's objective,
is to use self-driving.
And so, I'm sure you've heard
the statistic,
more than 90% of all crashes
have a human driver
as the cause.
So if you want to solve
traffic fatalities,
which, in my opinion, are the
single biggest tragedy
that happens year after year
in the United States,
this is the only solution.
>> NARRATOR:
It's an ambitious goal,
but only possible because
of the recent breakthroughs
in deep learning.
>> Artificial intelligence is
one of those key pieces
that has made it possible now
to do driverless vehicles
where it wasn't possible
ten years ago,
particularly in the ability
to see and understand scenes.
A lot of people don't know this,
but it's remarkably hard
for computers,
until very, very recently,
to do even the most basic
visual tasks,
like seeing a picture
of a person
and knowing that it's a person.
And we've made gigantic strides
with artificial intelligence
in being able to see and
understanding tasks,
and that's obviously fundamental
to being able to understand
the world around you
with the sensors that,
that you have available.
>> NARRATOR: That's now possible
because of the algorithms
written by Yoshua Bengio
and a small group of scientists.
>> There are many aspects
of the world
which we can't explain
with words.
And that part of our knowledge
is actually
probably the majority of it.
So, like, the stuff we can
communicate verbally
is the tip of the iceberg.
And so to get at the bottom of
the iceberg, the solution was,
the computers have to acquire
that knowledge by themselves
from data, from examples.
Just like children learn,
most not from their teachers,
but from interacting
with the world,
and playing around, and, and
trying things
and seeing what works
and what doesn't work.
>> NARRATOR: This is an early
demonstration.
In 2013, deep-mind scientists
set a machine-learning program
on the Atari video game
Breakout.
The computer was only told
the goal-- to win the game.
After 100 games, it learned to
use the bat at the bottom
to hit the ball and break
the bricks at the top.
After 300, it could do that
better than a human player.
After 500 games, it came up with
a creative way to win the game--
by digging a tunnel on the side
and sending the ball
around the top
to break many bricks
with one hit.
That was deep learning.
>> That's the A.I. program based
on learning,
really, that has been
so successful
in the last few years and has...
It wasn't clear ten years ago
that it would work,
but it has completely changed
the map
and is now used in almost
every sector of society.
>> Even the best and brightest
among us,
we just don't have enough
compute power
inside of our heads.
>> NARRATOR: Amy Webb is a
professor at N.Y.U.
and founder of the Future Today
Institute.
>> As A.I. progresses, the great
promise is that they...
they, these, these machines,
alongside of us,
are able to think and imagine
and see things
in ways that we never have
before,
which means that maybe we have
some kind of new,
weird, seemingly implausible
solution to climate change.
Maybe we have some radically
different approach
to dealing with
incurable cancers.
The real practical and wonderful
promise is that machines help us
be more creative, and,
using that creativity,
we get to terrific solutions.
>> NARRATOR: Solutions that
could come unexpectedly
to urgent problems.
>> It's going to change
the face of breast cancer.
Right now, 40,000 women
in the U.S. alone
die from breast cancer
every single year.
>> NARRATOR: Dr. Connie Lehman
is head
of the breast imaging center
at Massachusetts General
Hospital in Boston.
>> We've become so complacent
about it,
we almost don't think it can
really be changed.
We, we somehow think we should
put all of our energy
into chemotherapies
to save women
with metastatic breast cancer,
and yet, you know, when we find
it early, we cure it,
and we cure it without having
the ravages to the body
when we diagnose it late.
This shows the progression of a
small, small spot from one year
to the next,
and then to the diagnosis
of the small cancer here.
>> NARRATOR: This is what
happened when a woman
who had been diagnosed
with breast cancer
started to ask questions
about why it couldn't have been
diagnosed earlier.
>> It really brings a lot of
anxiety,
and you're asking the questions,
you know,
"Am I going to survive?
What's going to happen
to my son?"
And I start asking
other questions.
>> NARRATOR: She was used to
asking questions.
At M.I.T.'s
artificial-intelligence lab,
Professor Regina Barzilay uses
deep learning
to teach the computer to
understand language,
as well as read text and data.
>> I was really surprised
that the very basic question
that I ask my physicians,
which were really excellent
physicians here at MGH,
they couldn't give me answers
that I was looking for.
>> NARRATOR: She was convinced
that if you analyze enough data,
from mammograms
to diagnostic notes,
the computer could predict
early-stage conditions.
>> If we fast-forward from 2012
to '13 to 2014,
we then see when Regina
was diagnosed,
because of this spot on her
mammogram.
Is it possible, with more
elegant computer applications,
that we might have identified
this spot the year before,
or even back here?
>> So, those are standard
prediction problems
in machine learning-- there is
nothing special about them.
And to my big surprise,
none of the technologies
that we are developing
at M.I.T.,
even in the most simple form,
doesn't penetrate the hospital.
>> NARRATOR: Regina and Connie
began the slow process
of getting access to thousands
of mammograms and records
from MGH's breast-imaging
program.
>> So, our first foray was just
to take all of the patients
we had at MGH during
a period of time,
who had had breast surgery
for a certain type
of high-risk lesion.
And we found that most of them
didn't really need the surgery.
They didn't have cancer.
But about ten percent
did have cancer.
With Regina's techniques
in deep learning
and machine learning, we were
able to predict the women
that truly needed the surgery
and separate out
those that really could avoid
the unnecessary surgery.
>> What machine can do, it can
take hundreds of thousands
of images where the outcome
is known
and learn, based on how, you
know, pixels are distributed,
what are the very unique
patterns that correlate highly
with future occurrence
of the disease.
So, instead of using human
capacity
to kind of recognize pattern,
formalize pattern--
which is inherently limited
by our cognitive capacity
and how much we can see
and remember--
we're providing machine with a
lot of data
and make it learn
this prediction.
>> So, we are using technology
not only to be better
at assessing the breast density,
but to get more to the point of
what we're trying to predict.
"Does this woman have
a cancer now,
and will she develop a cancer
in five years? "
And that's, again, where
the artificial intelligence,
machine and deep learning can
really help us
and our patients.
>> NARRATOR: In the age of A.I.,
the algorithms are transporting
us into a universe
of vast potential and
transforming almost every aspect
of human endeavor and
experience.
Andrew McAfee is a research
scientist at M.I.T.
who co-authored
"The Second Machine Age."
>> The great compliment that a
songwriter gives another one is,
"Gosh, I wish I had written
that one."
The great compliment a geek
gives another one is,
"Wow, I wish I had drawn
that graph."
So, I wish I had drawn
this graph.
>> NARRATOR:
The graph uses a formula
to show human development and
growth since 2000 BCE.
>> The state of human
civilization
is not very advanced, and it's
not getting better
very quickly at all,
and this is true for thousands
and thousands of years.
When we, when we formed empires
and empires got overturned,
when we tried democracy,
when we invented zero
and mathematics and fundamental
discoveries about the universe,
big deal.
It just, the numbers don't
change very much.
What's weird is that the numbers
change essentially in the blink
of an eye at one point in time.
And it goes from really
horizontal, unchanging,
uninteresting, to, holy Toledo,
crazy vertical.
And then the question is,
what on Earth happened
to cause that change?
And the answer
is the Industrial Revolution.
There were other things that
happened,
but really what fundamentally
happened is
we overcame the limitations
of our muscle power.
Something equally interesting is
happening right now.
We are overcoming the
limitations of our minds.
We're not getting rid of them,
we're not making them
unnecessary,
but, holy cow, can we leverage
them and amplify them now.
You have to be a huge pessimist
not to find that profoundly
good news.
>> I really do think the world
has entered a new era.
Artificial intelligence holds so
much promise,
but it's going to reshape every
aspect of the economy,
so many aspects of our lives.
Because A.I. is a little bit
like electricity.
Everybody's going to use it.
Every company is going to be
incorporating A.I.,
integrating it into
what they do,
governments are going to be
using it,
nonprofit organizations are
going to be using it.
It's going to create all kinds
of benefits
in ways large and small,
and challenges for us, as well.
>> NARRATOR: The challenges,
the benefits--
the autonomous truck
represents both
as it maneuvers
into the marketplace.
The engineers are confident
that, in spite of questions
about when this will happen,
they can get it working safely
sooner
than most people realize.
>> I think that you will see the
first vehicles operating
with no one inside them moving
freight in the next few years,
and then you're going to see
that expanding to more freight,
more geographies,
more weather over time as,
as that capability builds up.
We're talking, like,
less than half a decade.
>> NARRATOR: He already has a
Fortune 500 company
as a client, shipping appliances
across the Southwest.
He says the sales pitch
is straightforward.
>> They spend hundreds of
millions of dollars a year
shipping parts around
the country.
We can bring that cost in half.
And they're really excited to be
able to start working with us,
both because of the potential,
the potential savings from
deploying self-driving,
and also because of all the
operational efficiencies
that they see, the biggest one
being able to operate
24 hours a day.
So, right now, human drivers are
limited to 11 hours
by federal law,
and a driverless truck
obviously wouldn't have
that limitation.
♪ ♪
>> NARRATOR: The idea of a
driverless truck comes up often
in discussions about artificial
intelligence.
Steve Viscelli is a sociologist
who drove a truck
while researching his book "The
Big Rig" about the industry.
>> This is one of the most
remarkable stories
in, in U.S. labor history,
I think,
is, you know, the decline of,
of unionized trucking.
The industry was deregulated
in 1980,
and at that time, you know,
truck drivers were earning
the equivalent of over
$100,000 in today's dollars.
And today the typical truck
driver will earn
a little over $40,000 a year.
And I think it's
an important part
of the automation story, right?
Why are they so afraid of
automation?
Because we've had four decades
of rising inequality in wages.
And if anybody is going to take
it on the chin
from automation
in the trucking industry,
the, the first in line is going
to be the driver,
without a doubt.
>> NARRATOR: For his research,
Viscelli tracked down truckers
and their families,
like Shawn and Hope Cumbee
of Beaverton, Michigan.
>> Hi.
>> Hey, Hope,
I'm Steve Viscelli.
>> Hi, Steve, nice to meet you.
Come on in.
>> Great to meet you, too,
thanks.
>> NARRATOR: And their son
Charlie.
>> This is Daddy, me,
Daddy, and Mommy.
>> NARRATOR: But Daddy's not
here.
Shawn Cumbee's truck has broken
down in Tennessee.
Hope, who drove a truck herself,
knows the business well.
>> We made $150,000, right,
in a year.
That sounds great, right?
That's, like, good money.
We paid $100,000 in fuel, okay?
So, right there,
now I made $50,000.
But I didn't really, because,
you know,
you get an oil change every
month,
so that's $300 a month.
You still have to do
all the maintenance.
We had a motor blow out, right?
$13,000. Right?
I know, I mean, I choke up a
little just thinking about it,
because it was...
And it was 13,000, and we were
off work for two weeks.
So, by the end of the year,
with that $150,000,
by the end of the year,
we'd made about 20...
About $22,000.
>> NARRATOR: In a truck stop
in Tennessee,
Shawn has been sidelined
waiting for a new part.
The garage owner is letting him
stay in the truck to save money.
>> Hi, baby.
>> (on phone): Hey, how's it
going?
>> It's going.
Chunky-butt!
>> Hi, Daddy!
>> Hi, Chunky-butt.
What're you doing?
>> (talking inaudibly)
>> Believe it or not,
I do it because I love it.
I mean, you know,
it's in the blood.
Third-generation driver.
And my granddaddy told me a long
time ago,
when I was probably
11, 12 years old, probably,
he said, "The world meets nobody
halfway.
Nobody."
He said, "If you want it,
you have to earn it."
And that's what I do every day.
I live by that creed.
And I've lived by that
since it was told to me.
>> So, if you're down for a week
in a truck,
you still have to pay your
bills.
I have enough money in my
checking account at all times
to pay a month's worth of bills.
That does not include my food.
That doesn't include field trips
for my son's school.
My son and I just went to our
yearly doctor appointment.
I took, I took money out of my
son's piggy bank to pay for it,
because it's not...
it's not scheduled in.
It's, it's not something that
you can, you know, afford.
I mean, like, when...
(sighs): Sorry.
>> It's okay.
♪ ♪
Have you guys ever talked about
self-driving trucks?
Is he...
>> (laughing): So, kind of.
Um, I asked him once, you know.
And he laughed so hard.
He said, "No way will they
ever have a truck
that can drive itself."
>> It's kind of interesting when
you think about it, you know,
they're putting all this new
technology into things,
but, you know,
it's still man-made.
And man, you know,
does make mistakes.
I really don't see it being
a problem with the industry,
'cause, one, you still got to
have a driver in it,
because I don't see it
doing city.
I don't see it doing,
you know, main things.
I don't see it backing into
a dock.
I don't see the automation part,
you know, doing...
maybe the box-trailer side,
you know, I can see that,
but not stuff like I do.
So, I ain't really worried about
the automation of trucks.
>> How near of a future is it?
>> Yeah, self-driving, um...
So, some, you know, some
companies are already operating.
Embark, for instance, is one
that has been doing
driverless trucks
on the interstate.
And what's called exit-to-exit
self-driving.
And they're currently running
real freight.
>> Really?
>> Yeah, on I-10.
♪ ♪
>> (on P.A.): Shower guest 100,
your shower is now ready.
>> NARRATOR: Over time, it has
become harder and harder
for veteran independent drivers
like the Cumbees
to make a living.
They've been replaced by
younger,
less experienced drivers.
>> So, the, the trucking
industry's $740 billion a year,
and, again, in, in many
of these operations,
labor's a third of that cost.
By my estimate, I, you know,
I think we're in the range
of 300,000 or so jobs
in the foreseeable future
that could be automated to some
significant extent.
♪ ♪
>> (groans)
♪ ♪
>> NARRATOR: The A.I. future
was built with great optimism
out here in the West.
In 2018, many of the people
who invented it
gathered in San Francisco to
celebrate the 25th anniversary
of the industry magazine.
>> Howdy, welcome to WIRED25.
>> NARRATOR: It is a
celebration, for sure,
but there's also a growing sense
of caution
and even skepticism.
>> We're having a really good
weekend here.
>> NARRATOR: Nick Thompson is
editor-in-chief of "Wired."
>> When it started,
it was very much a magazine
about what's coming and why you
should be excited about it.
Optimism was the defining
feature of "Wired"
for many, many years.
Or, as our slogan used to be,
"Change Is Good."
And over time,
it shifted a little bit.
And now it's more,
"We love technology,
but let's look at some
of the big issues,
and let's look at some of them
critically,
and let's look at the way
algorithms are changing
the way we behave,
for good and for ill."
So, the whole nature of "Wired"
has gone from a champion
of technological change to more
of a observer
of technological change.
>> So, um, before we start...
>> NARRATOR: There
are 25 speakers,
all named as icons
of the last 25 years
of technological progress.
>> So, why is Apple so
secretive?
>> (chuckling)
>> NARRATOR: Jony Ive, who
designed Apple's iPhone.
>> It would be bizarre
not to be.
>> There's this question of,
like,
what are we doing here in this
life, in this reality?
>> NARRATOR: Jaron Lanier, who
pioneered virtual reality.
And Jeff Bezos,
the founder of Amazon.
>> Amazon was a garage startup.
Now it's a very large company.
Two kids in a dorm...
>> NARRATOR: His message is,
"All will be well
in the new world."
>> I guess, first of all, I
remain incredibly optimistic
about technology,
and technologies always
are two-sided.
But that's not new.
That's always been the case.
And, and we will figure it out.
The last thing we would ever
want to do is stop the progress
of new technologies,
even when they are dual-use.
>> NARRATOR: But, says Thompson,
beneath the surface,
there's a worry most of them
don't like to talk about.
>> There are some people in
Silicon Valley who believe that,
"You just have to trust
the technology.
Throughout history, there's been
a complicated relationship
between humans and machines,
we've always worried about
machines,
and it's always been fine.
And we don't know how A.I. will
change the labor force,
but it will be okay."
So, that argument exists.
There's another argument,
which is what I think most of
them believe deep down,
which is, "This is different.
We're going to have labor-force
disruption
like we've never seen before.
And if that happens,
will they blame us?"
>> NARRATOR: There is, however,
one of the WIRED25 icons
willing to take on the issue.
Onstage, Kai-Fu Lee dispenses
with one common fear.
>> Well, I think there are so
many myths out there.
I think one, one myth is that
because A.I. is so good at a
single task,
that one day we'll wake up, and
we'll all be enslaved
or forced to plug our brains
to the A.I.
But it is nowhere close
to displacing humans.
>> NARRATOR: But in interviews
around the event and beyond,
he takes a decidedly contrarian
position on A.I. and job loss.
>> The A.I. giants want to paint
the rosier picture
because they're happily
making money.
So, I think they prefer not to
talk about the negative side.
I believe about 50% of jobs
will be
somewhat or extremely
threatened by A.I.
in the next 15 years or so.
>> NARRATOR: Kai-Fu Lee also
makes a great deal
of money from A.I.
What separates him from most of
his colleagues
is that he's frank
about its downside.
>> Yes, yes, we, we've made
about 40 investments in A.I.
I think, based on these 40
investments,
most of them are not impacting
human jobs.
They're creating value,
making high margins,
inventing a new model.
But I could list seven or eight
that would lead to a very clear
displacement of human jobs.
>> NARRATOR: He says that A.I.
is coming,
whether we like it or not.
And he wants to warn society
about what he sees as
inevitable.
>> You have a view which I think
is different than many others,
which is that A.I. is not going
to take blue-collar jobs
so quickly, but is actually
going to take white-collar jobs.
>> Yeah.
Well, both will happen.
A.I. will be, at the same time,
a replacement for blue-collar,
white-collar jobs, and be
a great symbiotic tool
for doctors, lawyers, and you,
for example.
But the white-collar jobs are
easier to take,
because they're a pure
quantitative analytical process.
Let's say reporters, traders,
telemarketing,
telesales, customer service...
>> Analysts?
>> Analysts, yes, these can all
be replaced just by a software.
To do blue-collar, some of the
work requires, you know,
hand-eye coordination, things
that machines are not yet
good enough to do.
>> Today, there are many people
who are ringing the alarm,
"Oh, my God, what are we going
to do?
Half the jobs are going away."
I believe that's true, but
here's the missing fact.
I've done the research on this,
and if you go back 20, 30,
or 40 years ago, you will find
that 50% of the jobs
that people performed back then
are gone today.
You know, where are all the
telephone operators,
bowling-pin setters,
elevator operators?
You used to have seas of
secretaries in corporations
that have now been eliminated--
travel agents.
You can just go through field
after field after field.
That same pattern has recurred
many times throughout history,
with each new wave
of automation.
>> But I would argue that
history is only trustable
if it is multiple repetitions
of similar events,
not once-in-a-blue-moon
occurrence.
So, over the history of many
tech inventions,
most are small things.
Only maybe three are at the
magnitude of A.I. revolution--
the steam, steam engine,
electricity,
and the computer revolution.
I'd say everything else
is too small.
And the reason I think it might
be something brand-new
is that A.I. is fundamentally
replacing our cognitive process
in doing a job in its
significant entirety,
and it can do it dramatically
better.
>> NARRATOR: This argument
about job loss
in the age of A.I. was ignited
six years ago
amid the gargoyles and spires
of Oxford University.
Two researchers had been poring
through U.S. labor statistics,
identifying jobs that could be
vulnerable to A.I. automation.
>> Well, vulnerable to
automation,
in the context that we discussed
five years ago now,
essentially meant that those
jobs are potentially automatable
over an unspecified number of
years.
And the figure we came up with
was 47%.
>> NARRATOR: 47%.
That number quickly traveled
the world in headlines
and news bulletins.
But authors Carl Frey
and Michael Osborne
offered a caution.
They can't predict how many jobs
will be lost, or how quickly.
But Frey believes that there are
lessons in history.
>> And what worries me the most
is that there is actually
one episode that looks quite
familiar to today,
which is the British
Industrial Revolution,
where wages didn't grow
for nine decades,
and a lot of people actually
saw living standards decline
as technology progressed.
♪ ♪
>> NARRATOR: Saginaw, Michigan,
knows about decline
in living standards.
Harry Cripps, an auto worker
and a local union president,
has witnessed what 40 years of
automation can do to a town.
>> You know, we're one of the
cities in the country that,
I think we were left behind in
this recovery.
And I just... I don't know how
we get on the bandwagon now.
>> NARRATOR: Once, this was the
U.A.W. hall
for one local union.
Now, with falling membership,
it's shared by five locals.
>> Rudy didn't get his shift.
>> NARRATOR: This day,
it's the center
for a Christmas food drive.
Even in a growth economy,
unemployment here is near
six percent.
Poverty in Saginaw is over 30%.
>> Our factory has about
1.9 million square feet.
Back in the '70s, that 1.9
million square feet
had about 7,500 U.A.W.
automotive workers
making middle-class wage with
decent benefits
and able to send their kids to
college and do all the things
that the middle-class family
should be able to do.
Our factory today, with
automation,
would probably be about
700 United Auto Workers.
That's a dramatic change.
Lot of union brothers used
to work there, buddy.
>> The TRW plant, that was
unfortunate.
>> Delphi... looks like they're
starting to tear it down now.
Wow.
Automations is, is definitely
taking away a lot of jobs.
Robots, I don't know how they
buy cars,
I don't know how
they buy sandwiches,
I don't know how they go to the
grocery store.
They definitely don't pay taxes,
which serves the infrastructure.
So, you don't have the sheriffs
and the police and the firemen,
and anybody else that supports
the city is gone,
'cause there's no tax base.
Robots don't pay taxes.
>> NARRATOR: The average
personal income in Saginaw
is $16,000 a year.
>> A lot of the families that I
work with here in the community,
both parents are working.
They're working two jobs.
Mainly, it's the wages,
you know,
people not making a decent wage
to be able to support a family.
Like, back in the day, my dad
even worked at the plant.
My mom stayed home,
raised the children.
And that give us the opportunity
to put food on the table,
and things of that nature.
And, and them times are gone.
>> If you look at this graph of
what's been happening
to America since the end
of World War II,
you see a line for our
productivity,
and our productivity
gets better over time.
It used to be the case
that our pay, our income,
would increase in lockstep with
those productivity increases.
The weird part about this graph
is how the income has decoupled,
is not going up the same way
that productivity is anymore.
>> NARRATOR: As automation has
taken over,
workers are either laid off or
left with less-skilled jobs
for less pay,
while productivity goes up.
>> There are still plenty
of factories in America.
We are a manufacturing
powerhouse,
but if you go walk around
an American factory,
you do not see long lines
of people
doing repetitive manual labor.
You see a whole lot
of automation.
If you go upstairs in that
factory
and look at the payroll
department,
you see one or two people
looking into a screen all day.
So, the activity is still there,
but the number of jobs
is very, very low,
because of automation
and tech progress.
Now, dealing with
that challenge,
and figuring out what
the next generation
of the American middle class
should be doing,
is a really important challenge,
because I am pretty confident
that we are never again
going to have this large,
stable, prosperous
middle class doing routine work.
♪ ♪
>> NARRATOR: Evidence of how
A.I. is likely to bring
accelerated change to the U.S.
workforce can be found
not far from Saginaw.
This is the U.S. headquarters
for one of the world's largest
builders of industrial robots,
a Japanese-owned company called
Fanuc Robotics.
>> We've been producing robots
for well over 35 years.
And you can imagine,
over the years,
they've changed quite a bit.
We're utilizing the artificial
intelligence
to really make the robots
easier to use
and be able to handle a broader
spectrum of opportunities.
We see a huge growth potential
in robotics.
And we see that growth potential
as being, really,
there's 90% of the market left.
>> NARRATOR: The industry says
optimistically
that with that growth,
they can create more jobs.
>> Even if there were five
people on a job,
and we reduced that down to two
people,
because we automated
some level of it,
we might produce two times more
parts than we did before,
because we automated it.
So now, there might be the need
for two more fork-truck drivers,
or two more quality-inspection
personnel.
So, although we reduce
some of the people,
we grow in other areas as we
produce more things.
>> When I increase productivity
through automation, I lose jobs.
Jobs go away.
And I don't care what the robot
manufacturers say,
you aren't replacing those ten
production people
that that robot is now doing
that job, with ten people.
You can increase productivity to
a level to stay competitive
with the global market-- that's
what they're trying to do.
♪ ♪
>> NARRATOR:
In the popular telling,
blame for widespread job loss
has been aimed overseas,
at what's called offshoring.
>> We want to keep
our factories here,
we want to keep
our manufacturing here.
We don't want them moving
to China, to Mexico, to Japan,
to India, to Vietnam.
>> NARRATOR: But it turns out
most of the job loss
isn't because of offshoring.
>> There's been offshoring.
And I think offshoring is
responsible for maybe 20%
of the jobs that have been lost.
I would say most of the jobs
that have been lost,
despite what most Americans
thinks, was due to automation
or productivity growth.
>> NARRATOR:
Mike Hicks is an economist
at Ball State University
in Muncie, Indiana.
He and sociologist Emily Wornell
have been documenting
employment trends
in Middle America.
Hicks says that automation has
been a mostly silent job killer,
lowering the standard of living.
>> So, in the last 15 years, the
standard of living has dropped
by 15, ten to 15 percent.
So, that's unusual
in a developed world.
A one-year decline
is a recession.
A 15-year decline gives
an entirely different sense
about the prospects
of a community.
And so that is common
from the Canadian border
to the Gulf of Mexico
in the middle swath
of the United States.
>> This is something we're gonna
do for you guys.
These were left over from our
suggestion drive that we did,
and we're going to give them
each two.
>> That is awesome.
>> I mean,
that is going to go a long ways,
right?
I mean, that'll really help that
family out during the holidays.
>> Yes, well, with the kids home
from school,
the families have three meals
a day that they got
to put on the table.
So, it's going to make a big
difference.
So, thank you, guys.
>> You're welcome.
>> This is wonderful.
>> Let them know Merry Christmas
on behalf of us here
at the local, okay?
>> Absolutely, you guys are
just, just amazing, thank you.
And please, tell, tell all the
workers how grateful
these families will be.
>> We will.
>> I mean, this is not a small
problem.
The need is so great.
And I can tell you
that it's all races,
it's all income classes
that you might think someone
might be from.
But I can tell you that when you
see it,
and you deliver this type
of gift to somebody
who is in need, just the
gratitude that they show you
is incredible.
>> We actually know that people
are at greater risk of mortality
for over 20 years after they
lose their job due to,
due to no fault of their own, so
something like automation
or offshoring.
They're at higher risk
for cardiovascular disease,
they're at higher risk
for depression and suicide.
But then with the
intergenerational impacts,
we also see their children
are more likely--
children of parents who have
lost their job
due to automation-- are more
likely to repeat a grade,
they're more likely to drop out
of school,
they're more likely to be
suspended from school,
and they have lower educational
attainment
over their entire lifetimes.
>> It's the future of this,
not the past, that scares me.
Because I think we're in the
early decades
of what is a multi-decade
adjustment period.
♪ ♪
>> NARRATOR: The world is being
re-imagined.
This is a supermarket.
Robots, guided by A.I., pack
everything from soap powder
to cantaloupes for online
consumers.
Machines that pick groceries,
machines that can also read
reports, learn routines,
and comprehend are reaching deep
into factories,
stores, and offices.
At a college in Goshen, Indiana,
a group of local business and
political leaders come together
to try to understand the impact
of A.I. and the new machines.
Molly Kinder studies
the future of work
at a Washington think tank.
>> How many people have gone
into a fast-food restaurant
and done a self-ordering?
Anyone, yes?
Panera, for instance,
is doing this.
Cashier was my first job,
and in, in, where I live,
in Washington, DC, it's actually
the number-one occupation
for the greater DC region.
There are millions of people who
work in cashier positions.
This is not a futuristic
challenge,
this is something that's
happening sooner than we think.
In the popular discussions about
robots and automation and work,
almost every image is of a man
on a factory floor
or a truck driver.
And yet, in our data, when we
looked,
women disproportionately hold
the jobs that today
are at highest risk
of automation.
And that's not really being
talked about,
and that's in part because women
are over-represented
in some of these marginalized
occupations,
like a cashier
or a fast-food worker.
And also in a large numbers
in clerical jobs in offices--
HR departments,
payroll, finance,
a lot of that is more routine
processing information,
processing paper,
transferring data.
That has huge potential for
automation.
A.I. is going to do
some of that, software,
robots are going to do
some of that.
So how many people are still
working
as switchboard operators?
Probably none in this country.
>> NARRATOR: The workplace of
the future will demand
different skills, and gaining
them, says Molly Kinder,
will depend on who
can afford them.
>> I mean it's not a good
situation in the United States.
There's been some excellent
research that says
that half of Americans
couldn't afford
a $400 unexpected expense.
And if you want to get to a
$1,000, there's even less.
So imagine you're going to go
out without a month's pay,
two months' pay, a year.
Imagine you want to put savings
toward a course
to, to redevelop your career.
People can't afford to take time
off of work.
They don't have a cushion, so
this lack of economic stability,
married with the disruptions in
people's careers,
is a really toxic mix.
>> (blowing whistle)
>> NARRATOR: The new machines
will penetrate every sector
of the economy:
from insurance companies
to human resource departments;
from law firms to the trading
floors of Wall Street.
>> Wall Street's
going through it,
but every industry is going
through it.
Every company is looking at all
of the disruptive technologies,
could be robotics or drones
or blockchain.
And whatever it is, every
company's using everything
that's developed, everything
that's disruptive,
in thinking about, "How do
I apply that to my business
to make myself more efficient?"
And what efficiency means is,
mostly,
"How do I do this
with fewer workers?"
And I do think that when we look
at some of the studies
about opportunity
in this country,
and the inequality
of opportunity,
the likelihood that you won't be
able to advance
from where your parents were, I
think that's, that's,
is very serious and gets
to the heart of the way
we like to think of America as
the land of opportunity.
>> NARRATOR: Inequality has been
rising in America.
It used to be the top 1%
of earners-- here in red--
owned a relatively small portion
of the country's wealth.
Middle and lower earners--
in blue-- had the largest share.
Then, 15 years ago,
the lines crossed.
And inequality has been
increasing ever since.
>> There's many factors that are
driving inequality today,
and unfortunately,
artificial intelligence--
without being thoughtful
about it--
is a driver for increased
inequality
because it's a form of
automation,
and automation is the
substitution of capital
for labor.
And when you do that,
the people with the capital win.
So Karl Marx was right,
it's a struggle between capital
and labor,
and with artificial
intelligence,
we're putting our finger on the
scale on the side of capital,
and how we wish to distribute
the benefits,
the economic benefits,
that that will create is going
to be a major
moral consideration for society
over the next several decades.
>> This is really an outgrowth
of the increasing gaps
of haves and have-nots--
the wealthy getting wealthier,
the poor getting poorer.
It may not be specifically
related to A.I.,
but as... but A.I. will
exacerbate that.
And that, I think, will tear
the society apart,
because the rich will have just
too much,
and those who are have-nots will
have perhaps very little way
of digging themselves
out of the hole.
And with A.I. making its impact,
it, it'll be worse, I think.
♪ ♪
(crowd cheering and applauding)
>> (speaking on P.A.)
I'm here today for one main
reason.
To say thank you to Ohio.
(crowd cheering and applauding)
>> I think the Trump vote
was a protest.
I mean that for whatever reason,
whatever the hot button was
that, you know,
that really hit home with these
Americans who voted for him
were, it was a protest vote.
They didn't like the direction
things were going.
(crowd booing and shouting)
I'm scared.
I'm gonna be quite honest with
you, I worry about the future
of not just this country,
but the, the entire globe.
If we continue to go in an
automated system,
what are we going to do?
Now I've got a group of people
at the top
that are making all the money
and I don't have anybody
in the middle
that can support a family.
So do we have to go to the point
where we crash to come back?
And in this case,
the automation's already gonna
be there,
so I don't know how
you come back.
I'm really worried
about where this,
where this leads us
in the future.
♪ ♪
>> NARRATOR: The future is
largely being shaped
by a few hugely successful
tech companies.
They're constantly buying up
successful smaller companies
and recruiting talent.
Between the U.S. and China,
they employ a great majority of
the leading A.I. researchers
and scientists.
In the course of amassing
such power,
they've also become among the
richest companies in the world.
>> A.I. really is the ultimate
tool of wealth creation.
Think about the massive data
that, you know, Facebook has
on user preferences, and how
it can very smartly target
an ad that you might buy
something
and get a much bigger cut that
a smaller company couldn't do.
Same with Google,
same with Amazon.
So it's... A.I. is a set of
tools
that helps you maximize an
objective function,
and that objective function
initially will simply be,
make more money.
>> NARRATOR: And it is how these
companies make that money,
and how their algorithms reach
deeper and deeper into our work,
our daily lives,
and our democracy,
that makes many people
increasingly uncomfortable.
Pedro Domingos wrote the book
"The Master Algorithm."
>> Everywhere you go,
you generate a cloud of data.
You're trailing data, everything
that you do is producing data.
And then there are computers
looking at that data
that are learning, and these
computers are essentially
trying to serve you better.
They're trying to personalize
things to you.
They're trying to adapt
the world to you.
So on the one hand,
this is great,
because the world will get
adapted to you
without you even having to
explicitly adapt it.
There's also a danger, because
the entities in the companies
that are in control of those
algorithms
don't necessarily have the same
goals as you,
and this is where I think people
need to be aware that,
what's going on, so they can
have more control over it.
>> You know, we came into this
new world thinking
that we were users
of social media.
It didn't occur to us
that social media
was actually using us.
We thought that we were
searching Google.
We had no idea that Google
was searching us.
>> NARRATOR: Shoshana Zuboff
is a Harvard Business School
professor emerita.
In 1988, she wrote a definitive
book called
"In the Age of
the Smart Machine."
For the last seven years,
she has worked on a new book,
making the case that we have now
entered a new phase
of the economy, which she calls
"surveillance capitalism."
>> So, famously, industrial
capitalism claimed nature.
Innocent rivers, and meadows,
and forests, and so forth,
for the market dynamic to be
reborn as real estate,
as land that could be sold
and purchased.
Industrial capitalism claimed
work for the market dynamic
to reborn, to be reborn as labor
that could be sold
and purchased.
Now, here comes surveillance
capitalism,
following this pattern, but with
a dark and startling twist.
What surveillance capitalism
claims is private,
human experience.
Private, human experience is
claimed as a free source
of raw material, fabricated into
predictions of human behavior.
And it turns out that there are
a lot of businesses
that really want to know what
we will do now, soon, and later.
>> NARRATOR: Like most people,
Alastair Mactaggart
had know idea
about this new surveillance
business,
until one evening in 2015.
>> I had a conversation with a
fellow who's an engineer,
and I was just talking to him
one night at a,
you know, a dinner,
at a cocktail party.
And I... there had been
something in the press that day
about privacy in the paper,
and I remember asking him--
he worked for Google-- "What's
the big deal about all,
why are people so worked up
about it?"
And I thought it was gonna be
one of those conversations,
like, with, you know, if you
ever ask an airline pilot,
"Should I be worried about
flying?"
and they say,
"Oh, the most dangerous part
is coming to the airport,
you know, in the car."
And he said, "Oh, you'd be
horrified
if you knew how much we knew
about you."
And I remember that kind of
stuck in my head,
because it was not
what I expected.
>> NARRATOR: That question
would change his life.
A successful California real
estate developer,
Mactaggart began researching
the new business model.
>> What I've learned since is
that their entire business
is learning as much about you
as they can.
Everything about your thoughts,
and your desires,
and your dreams,
and who your friends are,
and what you're thinking, what
your private thoughts are.
And with that,
that's true power.
And so, I think...
I didn't know that at the time.
That their entire business
is basically mining
the data of your life.
♪ ♪
>> NARRATOR: Shoshana Zuboff had
been doing her own research.
>> You know, I'd been reading
and reading and reading.
From patents, to transcripts
of earnings calls,
research reports.
And, you know,
just literally everything,
for years and years and years.
>> NARRATOR: Her studies
included the early days
of Google, started in 1998
by two young Stanford grad
students,
Sergey Brin and Larry Page.
In the beginning, they had no
clear business model.
Their unofficial motto was,
"Don't Be Evil."
>> Right from the start,
the founders,
Larry Page and Sergey Brin,
they had been very public
about their antipathy
toward advertising.
Advertising would distort
the internet
and it would distort and
disfigure the, the purity
of any search engine,
including their own.
>> Once in love with e-commerce,
Wall Street has turned its back
on the dotcoms.
>> NARRATOR: Then came the
dotcom crash of the early 2000s.
>> ...has left hundreds of
unprofitable internet companies
begging for love and money.
>> NARRATOR: While Google had
rapidly become the default
search engine for tens of
millions of users,
their investors were pressuring
them to make more money.
Without a new business model,
the founders knew that the young
company was in danger.
>> In this state of emergency,
the founders decided,
"We've simply got to find a way
to save this company."
And so, parallel to this were
another set of discoveries,
where it turns out that whenever
we search or whenever we browse,
we're leaving behind traces--
digital traces--
of our behavior.
And those traces,
back in these days,
were called digital exhaust.
>> NARRATOR: They realized how
valuable this data could be
by applying machine learning
algorithms
to predict users' interests.
>> What happened was,
they decided to turn
to those data logs
in a systematic way,
and to begin to use these
surplus data
as a way to come up with
fine-grained predictions
of what a user would click on,
what kind of ad
a user would click on.
And inside Google, they started
seeing these revenues
pile up at a startling rate.
They realized that they had to
keep it secret.
They didn't want anyone to know
how much money they were making,
or how they were making it.
Because users had no idea that
these extra-behavioral data
that told so much about them,
you know, was just out there,
and now it was being used
to predict their future.
>> NARRATOR: When Google's
I.P.O. took place
just a few years later,
the company had a market
capitalization
of around $23 billion.
Google's stock was now as
valuable as General Motors.
♪ ♪
>> And it was only when Google
went public in 2004
that the numbers were released.
And it's at that point that we
learn that between the year 2000
and the year 2004, Google's
revenue line increased
by 3,590%.
>> Let's talk a little about
information, and search,
and how people consume it.
>> NARRATOR: By 2010, the C.E.O.
of Google, Eric Schmidt,
would tell "The Atlantic"
magazine...
>> ...is, we don't need you to
type at all.
Because we know where you are,
with your permission,
we know where you've been,
with your permission.
We can more or less guess what
you're thinking about.
(audience laughing)
Now, is that over the line?
>> NARRATOR: Eric Schmidt
and Google declined
to be interviewed
for this program.
Google's new business model for
predicting users' profiles
had migrated to other companies,
particularly Facebook.
Roger McNamee was an early
investor
and adviser to Facebook.
He's now a critic, and wrote
a book about the company.
He says he's concerned about how
widely companies like Facebook
and Google have been casting
the net for data.
>> And then they realized,
"Wait a minute,
there's all this data in
the economy we don't have."
So they went to credit card
processors,
and credit rating services,
and said, "We want
to buy your data."
They go to health and wellness
apps and say,
"Hey, you got women's
menstrual cycles?
We want all that stuff."
Why are they doing that?
They're doing that because
behavioral prediction
is about taking uncertainty
out of life.
Advertising and marketing
are all about uncertainty--
you never really know who's
going to buy your product.
Until now.
We have to recognize that we
gave technology a place
in our lives
that it had not earned.
That essentially, because
technology always made things
better in the '50s, '60s, '70s,
'80s, and '90s,
we developed a sense of
inevitability
that it will always make things
better.
We developed a trust, and the
industry earned good will
that Facebook and Google have
cashed in.
>> NARRATOR: The model is simply
this: provide a free service--
like Facebook-- and in exchange,
you collect the data
of the millions who use it.
♪ ♪
And every sliver of information
is valuable.
>> It's not just what you post,
it's that you post.
It's not just that you make
plans to see your friends later.
It's whether you say,
"I'll see you later,"
or, "I'll see you at 6:45."
It's not just that you talk
about the things
that you have to do today.
It's whether you simply rattle
them on in a,
in a rambling paragraph,
or list them as bullet points.
All of these tiny signals are
the behavioral surplus
that turns out to have immense
predictive value.
>> NARRATOR: In 2010, Facebook
experimented
with A.I.'s predictive powers
in what they called
a "social contagion" experiment.
They wanted to see if, through
online messaging,
they could influence real-world
behavior.
The aim was to get more people
to the polls
in the 2010 midterm elections.
>> Cleveland, I need you to keep
on fighting.
I need you to keep on believing.
>> NARRATOR: They offered
61 million users
an "I voted" button together
with faces of friends
who had voted.
A subset of users received
just the button.
In the end, they claimed to have
nudged 340,000 people to vote.
They would conduct other
"massive contagion" experiments.
Among them, one showing that by
adjusting their feeds,
they could make users
happy or sad.
>> When they went to write up
these findings,
they boasted about two things.
One was, "Oh, my goodness.
Now we know that we can use cues
in the online environment
to change real-world behavior.
That's big news."
The second thing that they
understood, and they celebrated,
was that, "We can do this in a
way that bypasses
the users' awareness."
>> Private corporations have
built a corporate surveillance
state without our awareness
or permission.
And the systems necessary to
make it work
are getting a lot better,
specifically with what are known
as internet of things,
smart appliances, you know,
powered by the Alexa voice
recognition system,
or the Google Home system.
>> Okay, Google,
play the morning playlist.
>> Okay, playing morning
playlist.
♪ ♪
>> Okay, Google,
play music in all rooms.
♪ ♪
>> And those will put the
surveillance in places
we've never had it before--
living rooms, kitchens,
bedrooms.
And I find all of that
terrifying.
>> Okay, Google, I'm listening.
>> NARRATOR: The companies say
they're not using the data
to target ads, but helping A.I.
improve the user experience.
>> Alexa, turn on the fan.
(fan clicks on)
>> Okay.
>> NARRATOR: Meanwhile, they are
researching
and applying for patents
to expand their reach
into homes and lives.
>> Alexa, take a video.
(camera chirps)
>> The more and more that you
use spoken interfaces--
so smart speakers-- they're
being trained
not just to recognize
who you are,
but they're starting to take
baselines
and comparing changes over time.
So does your cadence increase
or decrease?
Are you sneezing
while you're talking?
Is your voice a little wobbly?
The purpose of doing this is
to understand
more about you in real time.
So that a system could make
inferences, perhaps,
like, do you have a cold?
Are you in a manic phase?
Are you feeling depressed?
So that is an extraordinary
amount of information
that can be gleaned by you
simply waking up
and asking your smart speaker,
"What's the weather today?"
>> Alexa, what's the weather
for tonight?
>> Currently, in Pasadena, it's
58 degrees with cloudy skies.
>> Inside it is, then.
Dinner!
>> The point is that this
is the same
micro-behavioral targeting that
is directed
toward individuals based on
intimate, detailed understanding
of personalities.
So this is precisely what
Cambridge Analytica did,
simply pivoting from
the advertisers
to the political outcomes.
>> NARRATOR: The Cambridge
Analytica scandal of 2018
engulfed Facebook, forcing
Mark Zuckerberg to appear
before Congress to explain how
the data
of up to 87 million Facebook
users had been harvested
by a political consulting
company based in the U.K.
The purpose was to target
and manipulate voters
in the 2016 presidential
campaign,
as well as the Brexit
referendum.
Cambridge Analytica had been
largely funded
by conservative hedge fund
billionaire Robert Mercer.
>> And now we know that any
billionaire with enough money,
who can buy the data,
buy the machine intelligence
capabilities,
buy the skilled data scientists,
you know, they too can
commandeer the public,
and infect and infiltrate and
upend our democracy
with the same methodologies that
surveillance capitalism
uses every single day.
>> We didn't take a broad enough
view of our responsibility,
and that was a big mistake.
And it was my mistake,
and I'm sorry.
>> NARRATOR:
Zuckerberg has apologized
for numerous violations of
privacy,
and his company was recently
fined $5 billion
by the Federal Trade Commission.
He has said Facebook will now
make data protection a priority,
and the company has suspended
tens of thousands
of third-party apps from its
platform
as a result of an internal
investigation.
>> You know, I wish I could say
that after Cambridge Analytica,
we've learned our lesson and
that everything will be much
better after that, but I'm
afraid the opposite is true.
In some ways, Cambridge
Analytica was using tools
that were ten years old.
It was really, in some ways,
old-school,
first-wave data science.
What we're looking at now,
with current tools
and machine learning, is that
the ability for manipulation,
both in terms of elections
and opinions,
but more broadly,
just how information travels,
That is a much bigger problem,
and certainly much more serious
than what we faced
with Cambridge Analytica.
>> NARRATOR: A.I. pioneer Yoshua
Bengio also has concerns
about how his algorithms
are being used.
>> So the A.I.s are tools.
And they will serve the people
who control those tools.
If those people's interests go
against the, the values
of democracy, then democracy is
in danger.
So I believe that scientists
who contribute to science,
when that science can or will
have an impact on society,
those scientists have a
responsibility.
It's a little bit like the
physicists of,
around the Second World War,
who rose up to tell
the governments,
"Wait, nuclear power
can be dangerous
and nuclear war can be really,
really destructive."
And today, the equivalent of a
physicist of the '40s and '50s
and '60s are,
are the computer scientists
who are doing machine learning
and A.I.
♪ ♪
>> NARRATOR: One person who
wanted to do something
about the dangers was not
a computer scientist,
but an ordinary citizen.
Alastair Mactaggart was alarmed.
>> Voting is, for me,
the most alarming one.
If less than 100,000 votes
separated
the last two candidates in the
last presidential election,
in three states...
>> NARRATOR: He began a solitary
campaign.
>> We're talking about
convincing a relatively tiny
fraction of the voters
in a very...
in a handful of states
to either come out and vote
or stay home.
And remember, these companies
know everybody intimately.
They know who's a racist,
who's a misogynist,
who's a homophobe,
who's a conspiracy theorist.
They know the lazy people and
the gullible people.
They have access to the greatest
trove of personal information
that's ever been assembled.
They have the world's best data
scientists.
And they have essentially
a frictionless way
of communicating with you.
This is power.
>> NARRATOR: Mactaggart started
a signature drive
for a California ballot
initiative,
for a law to give consumers
control of their digital data.
In all, he would spend
$4 million of his own money
in an effort to rein in the
goliaths of Silicon Valley.
Google, Facebook, AT&T,
and Comcast
all opposed his initiative.
>> I'll tell you, I was scared.
Fear.
Fear of looking like
a world-class idiot.
The market cap of all the firms
arrayed against me were,
was over $6 trillion.
>> NARRATOR: He needed 500,000
signatures
to get his initiative
on the ballot.
He got well over 600,000.
Polls showed 80% approval
for a privacy law.
That made the politicians in
Sacramento pay attention.
So Mactaggart decided that
because he was holding
a strong hand, it was worth
negotiating with them.
>> And if AB-375 passes
by tomorrow
and is signed into law
by the governor,
we will withdraw the initiative.
Our deadline to do so is
tomorrow at 5:00.
>> NARRATOR:
At the very last moment,
a new law was rushed to the
floor of the state house.
>> Everyone take their seats,
please.
Mr. Secretary,
please call the roll.
>> The voting starts.
>> Alan, aye.
>> And the first guy,
I think, was a Republican,
and he voted for it.
And everybody had said the
Republicans won't vote for it
because it has this private
right of action,
where consumers can sue.
And the guy in the Senate,
he calls the name.
>> Aye, Roth.
Aye, Skinner.
Aye, Stern.
Aye, Stone.
>> You can see down below,
and everyone went green,
and then it passed unanimously.
>> Ayes 36; No zero,
the measure passes.
Immediate transmittal to the...
>> So I was blown away.
It was, it was a day I will
never forget.
So in January, next year,
you as a California resident
will have the right to go to any
company and say,
"What have you collected on me
in the last 12 years...
12 months?
What of my personal information
do you have?"
So that's the first right.
It's right of... we call that
the right to know.
The second is the right
to say no.
And that's the right to go to
any company and click a button,
on any page where they're
collecting your information,
and say, "Do not sell
my information."
More importantly, we require
that they honor
what's called a third-party
opt-out.
You will click once
in your browser,
"Don't sell my information,"
and it will then send the signal
to every single website
that you visit: "Don't sell
this person's information."
And that's gonna have a huge
impact on the spread
of your information
across the internet.
>> NARRATOR: The tech companies
had been publicly cautious,
but privately alarmed
about regulation.
Then one tech giant came on
board in support
of Mactaggart's efforts.
>> I find the reaction among
other tech companies to,
at this point, be pretty much
all over the place.
Some people are saying,
"You're right to raise this.
These are good ideas."
Some people say, "We're not sure
these are good ideas,
but you're right to raise it,"
and some people are saying,
"We don't want regulation."
And so, you know, we have
conversations with people
where we point out that the auto
industry is better
because there are
safety standards.
Pharmaceuticals,
even food products,
all of these industries are
better because the public
has confidence in the products,
in part because of a mixture
of responsible companies
and responsible regulation.
>> NARRATOR: But the lobbyists
for big tech have been working
the corridors in Washington.
They're looking for
a more lenient
national privacy standard,
one that could perhaps override
the California law
and others like it.
But while hearings are held,
and anti-trust legislation
threatened,
the problem is that A.I.
has already spread so far
into our lives and work.
>> Well, it's in healthcare,
it's in education,
it's in criminal justice,
it's in the experience
of shopping as you walk down
the street.
It has pervaded so many elements
of everyday life,
and in a way that, in many
cases, is completely opaque
to people.
While we can see a phone and
look at it and we know that
there's some A.I. technology
behind it,
many of us don't know that when
we go for a job interview
and we sit down
and we have a conversation,
that we're being filmed, and
that our micro expressions
are being analyzed
by hiring companies.
Or that if you're in the
criminal justice system,
that there are risk assessment
algorithms
that are deciding
your "risk number,"
which could determine whether
or not you receive bail or not.
These are systems which, in many
cases, are hidden
in the back end of our sort
of social institutions.
And so, one of the big
challenges we have is,
how do we make that more
apparent?
How do we make it transparent?
And how do we make it
accountable?
>> For a very long time,
we have felt like as humans,
as Americans,
we have full agency
in determining our own futures--
what we read, what we see,
we're in charge.
What Cambridge Analytica taught
us,
and what Facebook continues
to teach us,
is that we don't have agency.
We're not in charge.
This is machines that are
automating some of our skills,
but have made decisions about
who...
Who we are.
And they're using that
information to tell others
the story of us.
♪ ♪
>> NARRATOR: In China,
in the age of A.I.,
there's no doubt
about who is in charge.
In an authoritarian state,
social stability
is the watchword
of the government.
(whistle blowing)
And artificial intelligence has
increased its ability to scan
the country for signs of unrest.
(whistle blowing)
It's been projected that over
600 million cameras
will be deployed by 2020.
Here, they may be used to
discourage jaywalking.
But they also serve to remind
people
that the state is watching.
>> And now, there is a project
called Sharp Eyes,
which is putting camera
on every major street
and the corner of every village
in China-- meaning everywhere.
Matching with the most advanced
artificial intelligence
algorithm, which they can
actually use this data,
real-time data, to pick up
a face or pick up a action.
♪ ♪
>> NARRATOR: Frequent security
expos feature companies
like Megvii and its facial-
recognition technology.
They show off cameras with A.I.
that can track cars,
and identify individuals
by face,
or just by the way they walk.
>> The place is just filled with
these screens where you can see
the computers are actually
reading people's faces
and trying to digest that data,
and basically track
and identify who each person is.
And it's incredible to see so
many,
because just two
or three years ago,
we hardly saw
that kind of thing.
So, a big part of it is
government spending.
And so the technology's really
taken off,
and a lot of companies have
started to sort of glom onto
this idea that this
is the future.
>> China is on its way
to building
a total surveillance state.
>> NARRATOR: And this is the
test lab
for the surveillance state.
Here, in the far northwest of
China,
is the autonomous region
of Xinjiang.
Of the 25 million people
who live here,
almost half are a Muslim Turkic
speaking people
called the Uighurs.
(people shouting)
In 2009, tensions with local
Han Chinese led to protests
and then riots in the capital,
Urumqi.
(people shouting, guns firing)
(people shouting)
As the conflict has grown,
the authorities have brought in
more police,
and deployed extensive
surveillance technology.
That data feeds an A.I. system
that the government claims
can predict individuals prone
to "terrorism"
and detect those in need of
"re-education"
in scores of recently
built camps.
It is a campaign that has
alarmed human rights groups.
>> Chinese authorities are,
without any legal basis,
arbitrarily detaining up
to a million Turkic Muslims
simply on the basis
of their identity.
But even outside the facilities
in which these people
are being held, most of the
population there
is being subjected to
extraordinary levels
of high-tech surveillance such
that almost no aspect of life
anymore, you know, takes place
outside
the state's line of sight.
And so the kinds of behavior
that's now being monitored--
you know, which language do you
speak at home,
whether you're talking to your
relatives
in other countries,
how often you pray--
that information is now being
hoovered up
and used to decide whether
people should be subjected
to political re-education
in these camps.
>> NARRATOR: There have been
reports of torture
and deaths in the camps.
And for Uighurs on the outside,
Xinjiang has already been
described
as an "open-air prison."
>> Trying to have a normal life
as a Uighur
is impossible both inside
and outside of China.
Just imagine, while you're on
your way to work,
police subject you to scan
your I.D.,
forcing you to lift your chin,
while machines take your photo
and wait... you wait until you
find out if you can go.
Imagine police take your phone
and run data scan,
and force you to install
compulsory software
allowing your phone calls and
messages to be monitored.
>> NARRATOR: Nury Turkel, a
lawyer and a prominent
Uighur activist, addresses a
demonstration in Washington, DC.
Many among the Uighur diaspora
have lost all contact
with their families back home.
Turkel warns that this dystopian
deployment of new technology
is a demonstration project
for authoritarian regimes
around the world.
>> They have a bar codes in
somebody's home doors
to identify what kind of citizen
that he is.
What we're talking about is a
collective punishment
of an ethnic group.
Not only that, the Chinese
government has been promoting
its methods, its technology,
it is...
to other countries, namely
Pakistan, Venezuela, Sudan,
and others to utilize, to
squelch political resentment
or prevent a political upheaval
in their various societies.
♪ ♪
>> NARRATOR: China has a grand
scheme to spread its technology
and influence around the world.
Launched in 2013, it started
along the old Silk Road
out of Xinjiang,
and now goes far beyond.
It's called "the Belt and Road
Initiative."
>> So effectively
what the Belt and Road
is is China's attempt to,
via spending and investment,
project its influence
all over the world.
And we've seen, you know,
massive infrastructure projects
going in in places like
Pakistan, in, in Venezuela,
in Ecuador, in Bolivia--
you know, all over the world,
Argentina,
in America's backyard,
in Africa.
Africa's been a huge place.
And what the Belt and Road
ultimately does is, it attempts
to kind of create a political
leverage
for the Chinese spending
campaign all over the globe.
>> NARRATOR: Like Xi Jinping's
2018 visit to Senegal,
where Chinese contractors had
just built a new stadium,
arranged loans for a new
infrastructure development,
and, said the Foreign Ministry,
there would be help
"maintaining social stability."
>> As China comes into these
countries and provides
these loans, what you end up
with is Chinese technology
being sold and built out by,
you know, by Chinese companies
in these countries.
We've started to see it already
in terms
of surveillance systems.
Not the kind of high-level A.I.
stuff yet, but, you know,
lower-level, camera-based,
you know,
manual sort of observation-type
things all over.
You know, you see it in
Cambodia, you see it in Ecuador,
you see it in Venezuela.
And what they do is, they sell
a dam, sell some other stuff,
and they say, "You know,
by the way, we can give you
these camera systems and,
for your emergency response.
And it'll cost you $300 million,
and we'll build a ton of
cameras,
and we'll build you a kind of,
you know, a main center
where you have police who can
watch these cameras."
And that's going in all over
the world already.
♪ ♪
>> There are 58 countries that
are starting to plug in
to China's vision of artificial
intelligence.
Which means effectively that
China is in the process
of raising a bamboo curtain.
One that does not need to...
One that is sort of
all-encompassing,
that has shared resources,
shared telecommunications
systems,
shared infrastructure,
shared digital systems--
even shared mobile-phone
technologies--
that is, that is quickly going
up all around the world
to the exclusion of us
in the West.
>> Well, one of the things
I worry about the most
is that the world
is gonna split in two,
and that there will be
a Chinese tech sector
and there will be an
American tech sector.
And countries will effectively
get to choose
which one they want.
It'll be kind of like the Cold
War, where you decide,
"Oh, are we gonna align
with the Soviet Union
or are we gonna align
with the United States?"
And the Third World gets to
choose this or that.
And that's not a world that's
good for anybody.
>> The markets in Asia and the
U.S. falling sharply
on news that a top Chinese
executive
has been arrested in Canada.
Her name is Sabrina Meng.
She is the CFO of the Chinese
telecom Huawei.
>> NARRATOR: News of the
dramatic arrest of an important
Huawei executive was ostensibly
about the company
doing business with Iran.
But it seemed to be more about
American distrust
of the company's technology.
From its headquarters
in southern China--
designed to look like fanciful
European capitals--
Huawei is the second-biggest
seller of smartphones,
and the world leader
in building 5G networks,
the high-speed backbone
for the age of A.I.
Huawei's C.E.O.,
a former officer
in the People's Liberation Army,
was defiant about
the American actions.
>> (speaking Mandarin)
(translated): There's no way
the U.S. can crush us.
The world needs Huawei because
we are more advanced.
If the lights go out in the
West, the East will still shine.
And if the North goes dark,
then there is still the South.
America doesn't represent
the world.
>> NARRATOR: The U.S. government
fears that as Huawei supplies
countries around the world
with 5G,
the Chinese government could
have back-door access
to their equipment.
Recently, the C.E.O. promised
complete transparency
into the company's software,
but U.S. authorities
are not convinced.
>> Nothing in China exists free
and clear of the party-state.
Those companies can only exist
and prosper
at the sufferance of the party.
And it's made very explicit that
when the party needs them,
they either have to respond
or they will be dethroned.
So this is the challenge with a
company like Huawei.
So Huawei, Ren Zhengfei, the
head of Huawei, he can say,
"Well, we... we're just a
private company and we just...
We don't take orders
from the Communist Party."
Well, maybe they haven't yet.
But what the Pentagon sees,
the National Intelligence
Council sees,
and what the FBI sees is,
"Well, maybe not yet."
But when the call comes,
everybody knows what the
company's response will be.
>> NARRATOR: The U.S. Commerce
Department
has recently blacklisted
eight companies
for doing business with
government agencies in Xinjiang,
claiming they are aiding
in the "repression"
of the Muslim minority.
Among the companies is Megvii.
They have strongly objected
to the blacklist,
saying that it's "a
misunderstanding of our company
and our technology."
♪ ♪
President Xi has increased his
authoritarian grip
on the country.
In 2018, he had the Chinese
constitution changed
so that he could be president
for life.
>> If you had asked me
20 years ago,
"What will happen to China?",
I would've said,
"Well, over time, the Great
Firewall will break down.
Of course, people will get
access to social media,
they'll get access to Google...
Eventually, it'll become a much
more democratic place,
with free expression
and lots of Western values."
And the last time I checked,
that has not happened.
In fact, technology's become
a tool of control.
And as China has gone through
this amazing period of growth
and wealth and openness in
certain ways,
there has not been the
democratic transformation
that I thought.
And it may turn out that,
in fact,
technology is a better tool for
authoritarian governments
than it is for democratic
governments.
>> NARRATOR: To dominate
the world in A.I.,
President Xi is depending on
Chinese tech
to lead the way.
While companies like
Baidu, Alibaba,
and Tencent are growing more
powerful and competitive,
they're also beginning to have
difficulty accessing
American technology, and are
racing to develop their own.
With a continuing trade war
and growing distrust,
the longtime argument for
engagement
between the two countries
has been losing ground.
>> I've seen more and more
of my colleagues move
from a position when they
thought,
"Well, if we just keep engaging
China,
the lines between
the two countries
will slowly converge."
You know, whether it's in
economics, technology, politics.
And the transformation,
where they now think
they're diverging.
So, in other words, the whole
idea of engagement
is coming under question.
And that's cast an entirely
different light on technology,
because if you're diverging and
you're heading into a world
of antagonism-- you know,
conflict, possibly,
then suddenly, technology is
something
that you don't want to share.
You want to sequester,
to protect your own national
interest.
And I think the tipping-point
moment we are at now,
which is what is casting
the whole question of things
like artificial intelligence
and technological innovation
into a completely different
framework,
is that if in fact China
and the U.S. are in some way
fundamentally antagonistic
to each other,
then we're in a completely
different world.
>> NARRATOR: In the age of A.I.,
a new reality is emerging.
That with so much accumulated
investment
and intellectual power, the
world is already dominated
by just two A.I. superpowers.
That's the premise of a new book
written by Kai-Fu Lee.
>> Hi, I'm Kai-Fu.
>> Hi, Dr. Lee, so
nice to meet you.
>> Really nice to meet you.
Look at all these dog ears.
I love, I love that.
>> You like that?
>> But I... but I don't like you
didn't buy the book,
you... you borrowed it.
>> I couldn't find it!
>> Oh, really?
>> Yeah!
>> And, and you...
you're coming to my talk?
>> Of course!
>> Oh, hi.
>> I did my homework,
I'm telling you.
>> Oh, my goodness, thank you.
Laurie, can you get this
gentleman a book?
(people talking in background)
>> NARRATOR: In his book
and in life,
the computer
scientist-cum-venture capitalist
walks a careful path.
Criticism of the Chinese
government is avoided,
while capitalist success
is celebrated.
>> I'm studying electrical
engineering.
>> Sure, send me a resume.
>> Okay, thanks.
>> NARRATOR: Now, with the rise
of the two superpowers,
he wants to warn the world
of what's coming.
>> Are you the new leaders?
>> If we're not the new leaders,
we're pretty close.
(laughs)
Thank you very much.
>> Thanks.
>> NARRATOR: "Never," he writes,
"has the potential
for human flourishing been
higher
or the stakes of failure
greater."
♪ ♪
>> So if one has to say who's
ahead, I would say today,
China is quickly catching up.
China actually began
its big push
in A.I. only two-and-a-half
years ago,
when the AlphaGo-Lee Sedol match
became the Sputnik moment.
>> NARRATOR: He says he believes
that the two A.I. superpowers
should lead the way and work
together
to make A.I. a force for good.
If we do, we may have a chance
of getting it right.
>> If we do a very good job
in the next 20 years,
A.I. will be viewed as an age of
enlightenment.
Our children and their children
will see A.I. as serendipity.
That A.I. is here to liberate us
from having to do routine jobs,
and push us to do what we love,
and push us to think what it
means to be human.
>> NARRATOR: But what if humans
mishandle this new power?
Kai-Fu Lee understands
the stakes.
After all, he invested early
in Megvii,
which is now on the U.S.
blacklist.
He says he's reduced his stake
and doesn't speak
for the company.
Asked about the government
using A.I.
for social control,
he chose his words carefully.
>> Um... A.I. is a technology
that can be used
for good and for evil.
So how... how do governments
limit themselves in,
on the one hand,
using this A.I. technology
and the database to maintain
a safe environment
for its citizens, but,
but not encroach
on a individual's rights
and privacies?
That, I think, is also a tricky
issue, I think,
for, for every country.
I think for... I think every
country will be tempted
to use A.I. probably
beyond the limits
to which that you and I would
like the government to use.
♪ ♪
>> NARRATOR: Emperor Yao devised
the game of Go
to teach his son discipline,
concentration, and balance.
Over 4,000 years later,
in the age of A.I.,
those words still resonate with
one of its architects.
♪ ♪
>> So A.I. can be used in many
ways that are very beneficial
for society.
But the current use of A.I.
isn't necessarily aligned
with the goals of building
a better society,
unfortunately.
But, but we could change that.
>> NARRATOR: In 2016, a game of
Go gave us a glimpse
of the future of artificial
intelligence.
Since then, it has become clear
that we will need
a careful strategy to harness
this new and awesome power.
>> I, I do think that democracy
is threatened by the progress
of these tools unless we improve
our social norms
and we increase
the collective wisdom
at the planet level to, to deal
with that increased power.
I'm hoping that my concerns are
not founded,
but the stakes are so high
that I don't think we should
take these concerns lightly.
I don't think we can play with
those possibilities and just...
race ahead without thinking
about the potential outcomes.
♪ ♪
>> Go to pbs.org/frontline for
more of the impact
of A.I. on jobs.
>> I believe about fifty percent
of jobs will be somewhat
or extremely threatened by A.I.
in the next 15 years or so.
>> And a look at the potential
for racial bias
in this technology.
>> We've had issues with bias,
with discrimination,
with poor system design,
with errors.
>> Connect to the "Frontline"
community on Facebook
and Twitter, and watch anytime
on the PBS Video app
or pbs.org/frontline.
♪ ♪
>> For more on this and
other "Frontline" programs,
visit our website
at pbs.org/frontline.
♪ ♪
To order "Frontline's"
"In the Age of A.I." on DVD,
visit ShopPBS or call
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♪ ♪
