All language subtitles for In the Age

NARRATOR: Tonight--

The race to become an A.I.superpower is on...

NARRATOR: The politics ofartificial intelligence...

There will bea Chinese tech sector

and there will bea 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 productivitythrough automation,

jobs go away.

I believe about 50% of jobswill be somewhat

or extremely threatened by A.I.in the next 15 years or so.

NARRATOR: A.I. and corporatesurveillance...

We thought that we weresearching Google.

We had no idea that Googlewas searching us.

NARRATOR: And the threatto democracy.

China is on its wayto building

a total surveillance state.

NARRATOR: Tonight on"Frontline"...

It has pervaded so manyelements of everyday life.

How do we make it transparentand accountable?

NARRATOR:..."In the Age of A.I."

NARRATOR: This is the world'smost complex board game.

There are more possible movesin the game of Go

than there are atomsin 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 startof a new industrial age.

It was 2016, in Seoul,South Korea.

Can machines overtakehuman intelligence?

A breakthrough moment when theworld champion

of the Asian board game Gotakes on an A.I. program

developed by Google.

(speaking Korean):

In countries whereit'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 learnstrategy.

It has an almost spiritualcomponent.

You know, if you talkto South Koreans, right,

and Lee Sedol is the world'sgreatest Go player,

he's a national heroin South Korea.

They were sure that Lee Sedolwould beat AlphaGo hands down.

NARRATOR: Google's AlphaGowas a computer program that,

starting with the rules of Go

and a databaseof historical games,

had been designedto teach itself.

I was one of the commentatorsat the Lee Sedol games.

And yes, it was watched by tensof millions of people.

(man speaking Korean)

NARRATOR: ThroughoutSoutheast Asia,

this was seen asa sports spectacle

with national pride at stake.

Wow, that was a player guess.

NARRATOR: But much morewas in play.

This was the public unveiling

of a form of artificialintelligence

called deep learning,

that mimics the neural networksof the human brain.

So what happens with machinelearning,

or artificial intelligence--initially with AlphaGo--

is that the machine is fedall 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 followinginstructions,

it's figuring out its owninstructions--

it comes up with moves thathumans hadn't thought of before.

So, it studies games that humanshave played, it knows the rules,

and then it comes upwith 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 thathumans could not fathom,

but yet it ended up beingbrilliant

and woke people up to say,

"Wow, after thousandsof years of playing,

we never thought about makinga move like that."

Oh, he resigned.

It looks like... Lee Sedol hasjust resigned, actually.

Yeah!Yes.

NARRATOR: In the end, thescientists watched

their algorithms win fourof the games.

Lee Sedol took one.

What happened with Go,first and foremost,

was a huge victory for deep mindand for A.I., right?

It wasn't that the computersbeat the humans,

it was that, you know, one typeof intelligence beat another.

NARRATOR: Artificialintelligence had proven

it could marshal a vast amountof data,

beyond anything any humancould handle,

and use it to teach itself howto predict an outcome.

The commercial implicationswere enormous.

While AlphaGo is a,is a toy game,

but its success and its wakingeveryone up, I think,

is, is going to be rememberedas the pivotal moment

where A.I. became mature

and everybody jumpedon the bandwagon.

NARRATOR: This is about theconsequences of that defeat.

(man speaking local language)

How the A.I. algorithms areushering in a new age

of great potential andprosperity,

but an age that will also deepeninequality, challenge democracy,

and divide the worldinto two A.I. superpowers.

Tonight, five stories about howartificial intelligence

is changing our world.

China has decided to chasethe A.I. future.

The difference betweenthe internet mindset

and the A.I. mindset...

NARRATOR: A future made andembraced by a new generation.

Well, it's hard not to feelthe kind of immense energy,

and also the obvious factof the demographics.

They're mostly very youngerpeople,

so that this clearly istechnology which is being

generated by a whole newgeneration.

NARRATOR: Orville Schellis one of

America's foremostChina scholars.

(speaking Mandarin)

NARRATOR: He first came here45 years ago.

When I, when I first camehere, in 1975,

Chairman Mao was still alive,

the Cultural Revolutionwas coming on,

and there wasn't a single whiffof anything

of what you see here.

It was unimaginable.

In fact, in those years,one very much thought,

"This is the way China is, thisis the way it's going to be."

And the fact that it has gonethrough

so many different changes sinceis quite extraordinary.

(man giving instructions)

NARRATOR: This extraordinaryprogress goes back

to that game of Go.

I think that the governmentrecognized

that this was a sort of criticalthing for the future,

and, "We need to catch upin this," that, you know,

"We cannot have a foreigncompany showing us up

at our own game.

And this is going to besomething that is going to be

critically importantin the future."

So, you know, we called it theSputnik moment for,

for the Chinese government--

the Chinese government kind ofwoke up.

(translated): As we often sayin China,

"The beginning is the mostdifficult part."

NARRATOR: In 2017, Xi Jinpingannounced

the government's bold new plans

to an audienceof foreign diplomats.

China would catch up with theU.S. in artificial intelligence

by 2025 and lead the worldby 2030.

(translated): ...andintensified cooperation

in frontier areas such asdigital economy,

artificial intelligence,nanotechnology,

and accounting computing.

NARRATOR: Today, China leadsthe world in e-commerce.

Drones deliver to ruralvillages.

And a society that bypassedcredit cards

now shops in storeswithout cashiers,

where the currencyis facial recognition.

No country has ever movedthat fast.

And in a short two-and-a-halfyears,

China's A.I. implementationreally went from minimal amount

to probably about17 or 18 unicorns,

that is billion-dollarcompanies, in A.I. today.

And that, that progress is,is hard to believe.

NARRATOR: The progress waspowered by a new generation

of ambitious young techs pouringout of Chinese universities,

competing with each otherfor new ideas,

and financed by a new cadre ofChinese venture capitalists.

This is Sinovation,

created by U.S.-educated A.I.scientist and businessman

Kai-Fu Lee.

These unicorns-- we've gotone, two, three, four, five,

six, in the general A.I. area.

And unicorn means abillion-dollar company,

a company whose valuationor market capitalization

is at $1 billion or higher.

I think we put two unicornsto show $5 billion or higher.

NARRATOR: Kai-Fu Lee was bornin Taiwan.

His parents sent himto high school in Tennessee.

His PhD thesisat Carnegie Mellon

was on computer speechrecognition,

which took him to Apple.

Well, reality is a stepcloser 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 thisto Make Write 2.

Casper, paste.

Casper, 72-point italic outline.

NARRATOR: He would move on toMicrosoft research in Asia

and became the headof Google China.

Ten years ago, he startedSinovation in Beijing,

and began looking for promisingstartups and A.I. talent.

So, the Chineseentrepreneurial companies

started as copycats.

But over the last 15 years,China has developed its own form

of entrepreneurship, and thatentrepreneurship is described

as tenacious, very fast,winner-take-all,

and incredible work ethic.

I would say these few thousandChinese top entrepreneurs,

they could take on anyentrepreneur

anywhere in the world.

NARRATOR: Entrepreneurs likeCao Xudong,

the 33-year-old C.E.O. ofa new startup called Momenta.

This is a ring road aroundBeijing.

The car is driving itself.

You see, another cutting,another cutting-in.

Another cut-in, yeah, yeah.

NARRATOR: Cao has no doubtabout the inevitability

of autonomous vehicles.

Just like AlphaGo can beatthe human player in, in Go,

I think the machine willdefinitely surpass

the human driver, in the end.

NARRATOR: Recently, therehave been cautions

about how soon autonomousvehicles will be deployed,

but Cao and his team areconfident

they're in for the long haul.

U.S. will be the firstto deploy,

but China may be the firstto 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 infrastructureefforts--

for example, building a new citythe size of Chicago

with autonomous driving enabled,

and also a new highway that hassensors built in

to help autonomous vehiclebe safer.

NARRATOR: Their earlyinvestors included

Mercedes-Benz.

I feel very lucky and veryinspiring

and very exciting that we'reliving in this era.

NARRATOR: Life in China islargely conducted

on smartphones.

A billion people use WeChat,the equivalent of Facebook,

Messenger, and PayPal,and much more,

combined into just onesuper-app.

And there are many more.

China is the best placefor A.I. implementation today,

because the vast amount of datathat's available in China.

China has a lot more users thanany other country,

three to four times more thanthe U.S.

There are 50 times more mobilepayments than the U.S.

There are ten times more fooddeliveries,

which serve as data to learnmore about user behavior

than the U.S.

300 times more shared bicyclerides,

and each shared bicycle ridehas all kinds of sensors

submitting data up to the cloud.

We're talking about maybe tentimes more data than the U.S.,

and A.I. is basically run ondata and fueled by data.

The more data, the betterthe A.I. works,

more importantly than howbrilliant 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 allthat data

means that the deep-learningalgorithm can quickly predict

behavior, like thecreditworthiness of someone

wanting a short-term loan.

Here is our application.

And customer can choose how manymoney they want to borrow

and how long they wantto borrow,

and they can inputtheir datas here.

And after, after that, you canjust borrow very quickly.

NARRATOR: The C.E.O. shows ushow quickly you can get a loan.

It is, it has done.

NARRATOR: It takes an averageof eight seconds.

It has passed to banks.Wow.

NARRATOR:In the eight seconds,

the algorithm has assessed5,000 personal features

from all your data.

5,000 features that isrelated with the delinquency,

when maybe the banks only usefew, maybe, maybe ten features

when they are doingtheir risk amendment.

NARRATOR: Processing millionsof transactions,

it'll dig up features that wouldnever be apparent

to a human loan officer,like how confidently you type

your loan application,or, surprisingly,

if you keep your cell phonebattery charged.

It's very interesting, thebattery of the phone

is related with theirdelinquency rate.

Someone who has much morelower battery,

they get much more dangerousthan others.

It's probably unfathomableto an American

how a country can dramaticallyevolve itself

from a copycat laggard to,all of a sudden,

to nearly as good as the U.S. intechnology.

NARRATOR: Like thisfacial-recognition startup

he invested in.

Megvii was started by threeyoung graduates in 2011.

It's now a world leader in usingA.I. to identify people.

It's pretty fast.

For example,on the mobile device,

we have timed thefacial-recognition speed.

It's actually lessthan 100 milliseconds.

So, that's very, very fast.

So 0.1 second that we can, wewill be able to recognize you,

even on a mobile device.

NARRATOR: The company claimsthe system is better

than any human at identifyingpeople 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 toreally take facial recognition

to commercial quality.

NARRATOR: That's why inBeijing today,

you can pay for your KFCwith a smile.

You know, it's not sosurprising,

we've seen Chinese companiescatching up to the U.S.

in technology for a long time.

And so, if particular effortand attention is paid

in a specific sector,it's not so surprising

that they would surpassthe rest of the world.

And facial recognition is one ofthe, really the first places

we've seen that start to happen.

NARRATOR: It's a technologyprized by the government,

like this program in Shenzhento discourage jaywalking.

Offenders are shamed in public--and with facial recognition,

can be instantly fined.

Critics warn that the governmentand some private companies

have been building a nationaldatabase

from dozens of experimentalsocial-credit programs.

The government wants tointegrate

all these individual behaviors,or corporations' records,

into some kind of metrics andcompute out a single number

or set of number associatedwith a individual,

a citizen, and using that,to implement a incentive

or punishment system.

NARRATOR: A highsocial-credit number

can be rewarded with discountson bus fares.

A low number can leadto a travel ban.

Some say it's very popularwith a Chinese public

that wants to punishbad behavior.

Others see a future that rewardsparty loyalty

and silences criticism.

Right now, there is no finalsystem being implemented.

And from those experiments, wealready see that the possibility

of what this social-creditsystem can do to individual.

It's very powerful--Orwellian-like--

and it's extremely troublesomein terms of civil liberty.

NARRATOR: Every eveningin Shanghai,

ever-present cameras record thecrowds

as they surge down to the Bund,

the promenade along the banksof the Huangpu River.

Once the great trading houses ofEurope 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 takein a spectacle

that reflects China'sremarkable progress.

(spectators gasp)

And illuminates the greatpolitical paradox of capitalism

taken rootin the communist state.

People have called itmarket Leninism,

authoritarian capitalism.

We are watching a kindof a Petri dish

in which an experiment of, youknow, extraordinary importance

to the world isbeing carried out.

Whether you can combine thesethings

and get somethingthat's more powerful,

that's coherent,that's durable in the world.

Whether you can bring togethera one-party state

with an innovative sector,both economically

and technologically innovative,

and that's something we thoughtcould not coexist.

NARRATOR:As China reinvents itself,

it has set its sightson leading the world

in artificial intelligenceby 2030.

But that means taking on theworld's most innovative

A.I. culture.

On an interstatein the U.S. Southwest,

artificial intelligence is atwork solving the problem

that's become emblematicof the new age,

replacing a human driver.

This is the company's C.E.O.,24-year-old Alex Rodrigues.

The more things we buildsuccessfully,

the less people ask questions

about how old you are when youhave working trucks.

NARRATOR: And this is whathe's built.

Commercial goods are beingdriven 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 pucksinto the scoring area.

So I, I did competitive roboticsstarting when I was 11,

and I took it very, veryseriously.

To, to give you a sense, I wonthe Robotics World Championships

for the first timewhen I was 13.

I've been to worlds seven times

between the ages of 13and 20-ish.

I eventually founded a team,

did a lot of work at avery high competitive level.

Things looking pretty good.

NARRATOR: This was aprototype of sorts,

from which he has built hismulti-million-dollar company.

I hadn't built a robot in awhile, wanted to get back to it,

and felt that this was by farthe most exciting piece

of robotics technology that wasup and coming.

A lot of people told us wewouldn't be able to build it.

But knew roughly the techniquesthat you would use.

And I was pretty confident thatif you put them together,

you would get somethingthat worked.

Took the summer off, built in myparents' garage a golf cart

that could drive itself.

NARRATOR: That golf cartgot the attention

of Silicon Valley,and the first of several rounds

of venture capital.

He formed a team and thendecided the business opportunity

was in self-driving trucks.

He says there's alsoa human benefit.

If we can build a truckthat's ten times safer

than a human driver, then notmuch else actually matters.

When we talk to regulators,especially,

everyone agrees that the onlyway 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 heardthe statistic,

more than 90% of all crashes

have a human driveras the cause.

So if you want to solvetraffic fatalities,

which, in my opinion, are thesingle biggest tragedy

that happens year after yearin the United States,

this is the only solution.

NARRATOR:It's an ambitious goal,

but only possible becauseof the recent breakthroughs

in deep learning.

Artificial intelligence isone of those key pieces

that has made it possible nowto do driverless vehicles

where it wasn't possibleten years ago,

particularly in the abilityto 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 basicvisual tasks,

like seeing a pictureof a person

and knowing that it's a person.

And we've made gigantic strideswith artificial intelligence

in being able to see andunderstanding tasks,

and that's obviously fundamentalto being able to understand

the world around youwith the sensors that,

that you have available.

NARRATOR: That's now possible

because of the algorithmswritten by Yoshua Bengio

and a small group of scientists.

There are many aspectsof the world

which we can't explainwith words.

And that part of our knowledgeis actually

probably the majority of it.

So, like, the stuff we cancommunicate verbally

is the tip of the iceberg.

And so to get at the bottom ofthe iceberg, the solution was,

the computers have to acquirethat knowledge by themselves

from data, from examples.

Just like children learn,most not from their teachers,

but from interactingwith the world,

and playing around, and, andtrying things

and seeing what worksand what doesn't work.

NARRATOR: This is an earlydemonstration.

In 2013, deep-mind scientistsset a machine-learning program

on the Atari video gameBreakout.

The computer was only toldthe goal-- to win the game.

After 100 games, it learned touse the bat at the bottom

to hit the ball and breakthe bricks at the top.

After 300, it could do thatbetter than a human player.

After 500 games, it came up witha creative way to win the game--

by digging a tunnel on the side

and sending the ballaround the top

to break many brickswith one hit.

That was deep learning.

That's the A.I. program basedon learning,

really, that has beenso successful

in the last few years and has...

It wasn't clear ten years agothat it would work,

but it has completely changedthe map

and is now used in almostevery sector of society.

Even the best and brightestamong us,

we just don't have enoughcompute power

inside of our heads.

NARRATOR: Amy Webb is aprofessor at N.Y.U.

and founder of the Future TodayInstitute.

As A.I. progresses, the greatpromise is that they...

they, these, these machines,alongside of us,

are able to think and imagineand see things

in ways that we never havebefore,

which means that maybe we havesome kind of new,

weird, seemingly implausiblesolution to climate change.

Maybe we have some radicallydifferent approach

to dealing withincurable cancers.

The real practical and wonderfulpromise is that machines help us

be more creative, and,using that creativity,

we get to terrific solutions.

NARRATOR: Solutions thatcould come unexpectedly

to urgent problems.

It's going to changethe face of breast cancer.

Right now, 40,000 womenin the U.S. alone

die from breast cancerevery single year.

NARRATOR: Dr. Connie Lehmanis head

of the breast imaging center

at Massachusetts GeneralHospital in Boston.

We've become so complacentabout it,

we almost don't think it canreally be changed.

We, we somehow think we shouldput all of our energy

into chemotherapiesto save women

with metastatic breast cancer,

and yet, you know, when we findit early, we cure it,

and we cure it without havingthe ravages to the body

when we diagnose it late.

This shows the progression of asmall, small spot from one year

to the next,and then to the diagnosis

of the small cancer here.

NARRATOR: This is whathappened when a woman

who had been diagnosedwith breast cancer

started to ask questions

about why it couldn't have beendiagnosed earlier.

It really brings a lot ofanxiety,

and you're asking the questions,you know,

"Am I going to survive?

What's going to happento my son?"

And I start askingother questions.

NARRATOR: She was used toasking questions.

At M.I.T.'sartificial-intelligence lab,

Professor Regina Barzilay usesdeep learning

to teach the computer tounderstand language,

as well as read text and data.

I was really surprisedthat the very basic question

that I ask my physicians,

which were really excellentphysicians here at MGH,

they couldn't give me answersthat I was looking for.

NARRATOR: She was convincedthat if you analyze enough data,

from mammogramsto diagnostic notes,

the computer could predictearly-stage conditions.

If we fast-forward from 2012to '13 to 2014,

we then see when Reginawas diagnosed,

because of this spot on hermammogram.

Is it possible, with moreelegant computer applications,

that we might have identifiedthis spot the year before,

or even back here?

So, those are standardprediction problems

in machine learning-- there isnothing special about them.

And to my big surprise,none of the technologies

that we are developingat M.I.T.,

even in the most simple form,doesn't penetrate the hospital.

NARRATOR: Regina and Conniebegan the slow process

of getting access to thousandsof mammograms and records

from MGH's breast-imagingprogram.

So, our first foray was justto take all of the patients

we had at MGH duringa period of time,

who had had breast surgeryfor a certain type

of high-risk lesion.

And we found that most of themdidn't really need the surgery.

They didn't have cancer.

But about ten percentdid have cancer.

With Regina's techniquesin deep learning

and machine learning, we wereable to predict the women

that truly needed the surgeryand separate out

those that really could avoidthe unnecessary surgery.

What machine can do, it cantake hundreds of thousands

of images where the outcomeis known

and learn, based on how, youknow, pixels are distributed,

what are the very uniquepatterns that correlate highly

with future occurrenceof the disease.

So, instead of using humancapacity

to kind of recognize pattern,formalize pattern--

which is inherently limitedby our cognitive capacity

and how much we can seeand remember--

we're providing machine with alot of data

and make it learnthis prediction.

So, we are using technologynot only to be better

at assessing the breast density,

but to get more to the point ofwhat we're trying to predict.

"Does this woman havea cancer now,

and will she develop a cancerin five years? "

And that's, again, wherethe artificial intelligence,

machine and deep learning canreally help us

and our patients.

NARRATOR: In the age of A.I.,

the algorithms are transportingus into a universe

of vast potential andtransforming almost every aspect

of human endeavor andexperience.

Andrew McAfee is a researchscientist at M.I.T.

who co-authored"The Second Machine Age."

The great compliment that asongwriter gives another one is,

"Gosh, I wish I had writtenthat one."

The great compliment a geekgives another one is,

"Wow, I wish I had drawnthat graph."

So, I wish I had drawnthis graph.

NARRATOR:The graph uses a formula

to show human development andgrowth since 2000 BCE.

The state of humancivilization

is not very advanced, and it'snot getting better

very quickly at all,and this is true for thousands

and thousands of years.

When we, when we formed empiresand empires got overturned,

when we tried democracy,when we invented zero

and mathematics and fundamentaldiscoveries about the universe,

big deal.

It just, the numbers don'tchange very much.

What's weird is that the numberschange essentially in the blink

of an eye at one point in time.

And it goes from reallyhorizontal, unchanging,

uninteresting, to, holy Toledo,crazy vertical.

And then the question is,what on Earth happened

to cause that change?

And the answeris the Industrial Revolution.

There were other things thathappened,

but really what fundamentallyhappened is

we overcame the limitationsof our muscle power.

Something equally interesting ishappening right now.

We are overcoming thelimitations of our minds.

We're not getting rid of them,

we're not making themunnecessary,

but, holy cow, can we leveragethem and amplify them now.

You have to be a huge pessimist

not to find that profoundlygood news.

I really do think the worldhas entered a new era.

Artificial intelligence holds somuch promise,

but it's going to reshape everyaspect of the economy,

so many aspects of our lives.

Because A.I. is a little bitlike electricity.

Everybody's going to use it.

Every company is going to beincorporating A.I.,

integrating it intowhat they do,

governments are going to beusing it,

nonprofit organizations aregoing to be using it.

It's going to create all kindsof benefits

in ways large and small,and challenges for us, as well.

NARRATOR: The challenges,the benefits--

the autonomous truckrepresents both

as it maneuversinto the marketplace.

The engineers are confidentthat, in spite of questions

about when this will happen,

they can get it working safelysooner

than most people realize.

I think that you will see thefirst vehicles operating

with no one inside them movingfreight in the next few years,

and then you're going to seethat 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 aFortune 500 company

as a client, shipping appliancesacross the Southwest.

He says the sales pitchis straightforward.

They spend hundreds ofmillions of dollars a year

shipping parts aroundthe country.

We can bring that cost in half.

And they're really excited to beable to start working with us,

both because of the potential,

the potential savings fromdeploying self-driving,

and also because of all theoperational efficiencies

that they see, the biggest onebeing able to operate

24 hours a day.

So, right now, human drivers arelimited to 11 hours

by federal law,and a driverless truck

obviously wouldn't havethat limitation.

NARRATOR: The idea of adriverless truck comes up often

in discussions about artificialintelligence.

Steve Viscelli is a sociologistwho drove a truck

while researching his book "TheBig Rig" about the industry.

This is one of the mostremarkable stories

in, in U.S. labor history,I think,

is, you know, the decline of,of unionized trucking.

The industry was deregulatedin 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 truckdriver will earn

a little over $40,000 a year.

And I think it'san important part

of the automation story, right?

Why are they so afraid ofautomation?

Because we've had four decadesof rising inequality in wages.

And if anybody is going to takeit on the chin

from automationin the trucking industry,

the, the first in line is goingto 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 sonCharlie.

This is Daddy, me,Daddy, and Mommy.

NARRATOR: But Daddy's nothere.

Shawn Cumbee's truck has brokendown 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 everymonth,

so that's $300 a month.

You still have to doall the maintenance.

We had a motor blow out, right?

$13,000. Right?

I know, I mean, I choke up alittle just thinking about it,

because it was...

And it was 13,000, and we wereoff 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 stopin Tennessee,

Shawn has been sidelinedwaiting for a new part.

The garage owner is letting himstay in the truck to save money.

Hi, baby.

(on phone): Hey, how's itgoing?

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 longtime ago,

when I was probably11, 12 years old, probably,

he said, "The world meets nobodyhalfway.

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 thatsince it was told to me.

So, if you're down for a weekin a truck,

you still have to pay yourbills.

I have enough money in mychecking account at all times

to pay a month's worth of bills.

That does not include my food.

That doesn't include field tripsfor my son's school.

My son and I just went to ouryearly doctor appointment.

I took, I took money out of myson's piggy bank to pay for it,

because it's not...it's not scheduled in.

It's, it's not something thatyou can, you know, afford.

I mean, like, when...

(sighs): Sorry.

It's okay.

Have you guys ever talked aboutself-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 theyever have a truck

that can drive itself."

It's kind of interesting whenyou think about it, you know,

they're putting all this newtechnology into things,

but, you know,it's still man-made.

And man, you know,does make mistakes.

I really don't see it beinga problem with the industry,

'cause, one, you still got tohave a driver in it,

because I don't see itdoing city.

I don't see it doing,you know, main things.

I don't see it backing intoa 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 aboutthe automation of trucks.

How near of a future is it?

Yeah, self-driving, um...

So, some, you know, somecompanies are already operating.

Embark, for instance, is onethat has been doing

driverless truckson the interstate.

And what's called exit-to-exitself-driving.

And they're currently runningreal freight.

Really?Yeah, on I-10.

(on P.A.): Shower guest 100,your shower is now ready.

NARRATOR: Over time, it hasbecome harder and harder

for veteran independent driverslike the Cumbees

to make a living.

They've been replaced byyounger,

less experienced drivers.

So, the, the truckingindustry's $740 billion a year,

and, again, in, in manyof 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 jobsin the foreseeable future

that could be automated to somesignificant extent.

(groans)

NARRATOR: The A.I. futurewas built with great optimism

out here in the West.

In 2018, many of the peoplewho invented it

gathered in San Francisco tocelebrate the 25th anniversary

of the industry magazine.

Howdy, welcome to WIRED25.

NARRATOR: It is acelebration, for sure,

but there's also a growing senseof caution

and even skepticism.

We're having a really goodweekend here.

NARRATOR: Nick Thompson iseditor-in-chief of "Wired."

When it started,it was very much a magazine

about what's coming and why youshould be excited about it.

Optimism was the definingfeature 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 someof the big issues,

and let's look at some of themcritically,

and let's look at the wayalgorithms 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 moreof a observer

of technological change.

So, um, before we start...

NARRATOR: Thereare 25 speakers,

all named as iconsof the last 25 years

of technological progress.

So, why is Apple sosecretive?

(chuckling)

NARRATOR: Jony Ive, whodesigned Apple's iPhone.

It would be bizarrenot to be.

There's this question of,like,

what are we doing here in thislife, in this reality?

NARRATOR: Jaron Lanier, whopioneered 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 wellin the new world."

I guess, first of all, Iremain incredibly optimistic

about technology,

and technologies alwaysare 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 everwant 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 themdon't like to talk about.

There are some people inSilicon Valley who believe that,

"You just have to trustthe technology.

Throughout history, there's beena complicated relationship

between humans and machines,

we've always worried aboutmachines,

and it's always been fine.

And we don't know how A.I. willchange the labor force,

but it will be okay."

So, that argument exists.

There's another argument,

which is what I think most ofthem believe deep down,

which is, "This is different.

We're going to have labor-forcedisruption

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 dispenseswith one common fear.

Well, I think there are somany myths out there.

I think one, one myth is that

because A.I. is so good at asingle task,

that one day we'll wake up, andwe'll all be enslaved

or forced to plug our brainsto the A.I.

But it is nowhere closeto displacing humans.

NARRATOR: But in interviewsaround the event and beyond,

he takes a decidedly contrarianposition on A.I. and job loss.

The A.I. giants want to paintthe rosier picture

because they're happilymaking money.

So, I think they prefer not totalk about the negative side.

I believe about 50% of jobswill be

somewhat or extremelythreatened by A.I.

in the next 15 years or so.

NARRATOR: Kai-Fu Lee alsomakes a great deal

of money from A.I.

What separates him from most ofhis colleagues

is that he's frankabout its downside.

Yes, yes, we, we've madeabout 40 investments in A.I.

I think, based on these 40investments,

most of them are not impactinghuman 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 cleardisplacement 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 asinevitable.

You have a view which I thinkis different than many others,

which is that A.I. is not goingto take blue-collar jobs

so quickly, but is actuallygoing 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 bea great symbiotic tool

for doctors, lawyers, and you,for example.

But the white-collar jobs areeasier to take,

because they're a purequantitative analytical process.

Let's say reporters, traders,telemarketing,

telesales, customer service...

Analysts?

Analysts, yes, these can allbe replaced just by a software.

To do blue-collar, some of thework requires, you know,

hand-eye coordination, thingsthat machines are not yet

good enough to do.

Today, there are many peoplewho are ringing the alarm,

"Oh, my God, what are we goingto do?

Half the jobs are going away."

I believe that's true, buthere's the missing fact.

I've done the research on this,and if you go back 20, 30,

or 40 years ago, you will findthat 50% of the jobs

that people performed back thenare gone today.

You know, where are all thetelephone operators,

bowling-pin setters,elevator operators?

You used to have seas ofsecretaries in corporations

that have now been eliminated--travel agents.

You can just go through fieldafter field after field.

That same pattern has recurredmany times throughout history,

with each new waveof automation.

But I would argue thathistory is only trustable

if it is multiple repetitionsof similar events,

not once-in-a-blue-moonoccurrence.

So, over the history of manytech inventions,

most are small things.

Only maybe three are at themagnitude of A.I. revolution--

the steam, steam engine,electricity,

and the computer revolution.

I'd say everything elseis too small.

And the reason I think it mightbe something brand-new

is that A.I. is fundamentallyreplacing our cognitive process

in doing a job in itssignificant entirety,

and it can do it dramaticallybetter.

NARRATOR: This argumentabout job loss

in the age of A.I. was ignitedsix years ago

amid the gargoyles and spiresof Oxford University.

Two researchers had been poringthrough U.S. labor statistics,

identifying jobs that could bevulnerable to A.I. automation.

Well, vulnerable toautomation,

in the context that we discussedfive years ago now,

essentially meant that thosejobs are potentially automatable

over an unspecified number ofyears.

And the figure we came up withwas 47%.

NARRATOR: 47%.

That number quickly traveledthe world in headlines

and news bulletins.

But authors Carl Freyand Michael Osborne

offered a caution.

They can't predict how many jobswill be lost, or how quickly.

But Frey believes that there arelessons in history.

And what worries me the mostis that there is actually

one episode that looks quitefamiliar to today,

which is the BritishIndustrial Revolution,

where wages didn't growfor nine decades,

and a lot of people actuallysaw living standards decline

as technology progressed.

NARRATOR: Saginaw, Michigan,knows about decline

in living standards.

Harry Cripps, an auto workerand a local union president,

has witnessed what 40 years ofautomation can do to a town.

You know, we're one of thecities in the country that,

I think we were left behind inthis recovery.

And I just... I don't know howwe get on the bandwagon now.

NARRATOR: Once, this was theU.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 nearsix percent.

Poverty in Saginaw is over 30%.

Our factory has about1.9 million square feet.

Back in the '70s, that 1.9million square feet

had about 7,500 U.A.W.automotive workers

making middle-class wage withdecent benefits

and able to send their kids tocollege and do all the things

that the middle-class familyshould be able to do.

Our factory today, withautomation,

would probably be about700 United Auto Workers.

That's a dramatic change.

Lot of union brothers usedto work there, buddy.

The TRW plant, that wasunfortunate.

Delphi... looks like they'restarting to tear it down now.

Wow.

Automations is, is definitelytaking away a lot of jobs.

Robots, I don't know how theybuy cars,

I don't know howthey buy sandwiches,

I don't know how they go to thegrocery store.

They definitely don't pay taxes,which serves the infrastructure.

So, you don't have the sheriffsand the police and the firemen,

and anybody else that supportsthe city is gone,

'cause there's no tax base.

Robots don't pay taxes.

NARRATOR: The averagepersonal income in Saginaw

is $16,000 a year.

A lot of the families that Iwork 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 wageto be able to support a family.

Like, back in the day, my dadeven worked at the plant.

My mom stayed home,raised the children.

And that give us the opportunityto put food on the table,

and things of that nature.

And, and them times are gone.

If you look at this graph ofwhat's been happening

to America since the endof World War II,

you see a line for ourproductivity,

and our productivitygets better over time.

It used to be the casethat our pay, our income,

would increase in lockstep withthose productivity increases.

The weird part about this graphis how the income has decoupled,

is not going up the same waythat productivity is anymore.

NARRATOR: As automation hastaken over,

workers are either laid off orleft with less-skilled jobs

for less pay,while productivity goes up.

There are still plentyof factories in America.

We are a manufacturingpowerhouse,

but if you go walk aroundan American factory,

you do not see long linesof people

doing repetitive manual labor.

You see a whole lotof automation.

If you go upstairs in thatfactory

and look at the payrolldepartment,

you see one or two peoplelooking into a screen all day.

So, the activity is still there,

but the number of jobsis very, very low,

because of automationand tech progress.

Now, dealing withthat challenge,

and figuring out whatthe next generation

of the American middle classshould be doing,

is a really important challenge,

because I am pretty confidentthat we are never again

going to have this large,stable, prosperous

middle class doing routine work.

NARRATOR: Evidence of howA.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 largestbuilders of industrial robots,

a Japanese-owned company calledFanuc Robotics.

We've been producing robotsfor well over 35 years.

And you can imagine,over the years,

they've changed quite a bit.

We're utilizing the artificialintelligence

to really make the robotseasier to use

and be able to handle a broaderspectrum of opportunities.

We see a huge growth potentialin robotics.

And we see that growth potentialas being, really,

there's 90% of the market left.

NARRATOR: The industry saysoptimistically

that with that growth,they can create more jobs.

Even if there were fivepeople on a job,

and we reduced that down to twopeople,

because we automatedsome level of it,

we might produce two times moreparts than we did before,

because we automated it.

So now, there might be the needfor two more fork-truck drivers,

or two more quality-inspectionpersonnel.

So, although we reducesome of the people,

we grow in other areas as weproduce more things.

When I increase productivitythrough automation, I lose jobs.

Jobs go away.

And I don't care what the robotmanufacturers say,

you aren't replacing those tenproduction people

that that robot is now doingthat job, with ten people.

You can increase productivity toa level to stay competitive

with the global market-- that'swhat they're trying to do.

NARRATOR:In the popular telling,

blame for widespread job losshas been aimed overseas,

at what's called offshoring.

We want to keepour factories here,

we want to keepour manufacturing here.

We don't want them movingto China, to Mexico, to Japan,

to India, to Vietnam.

NARRATOR: But it turns outmost of the job loss

isn't because of offshoring.

There's been offshoring.

And I think offshoring isresponsible for maybe 20%

of the jobs that have been lost.

I would say most of the jobsthat have been lost,

despite what most Americansthinks, was due to automation

or productivity growth.

NARRATOR:Mike Hicks is an economist

at Ball State Universityin Muncie, Indiana.

He and sociologist Emily Wornellhave been documenting

employment trendsin Middle America.

Hicks says that automation hasbeen a mostly silent job killer,

lowering the standard of living.

So, in the last 15 years, thestandard of living has dropped

by 15, ten to 15 percent.

So, that's unusualin a developed world.

A one-year declineis a recession.

A 15-year decline givesan entirely different sense

about the prospectsof a community.

And so that is commonfrom the Canadian border

to the Gulf of Mexico

in the middle swathof the United States.

This is something we're gonnado for you guys.

These were left over from oursuggestion drive that we did,

and we're going to give themeach two.

That is awesome.I mean,

that is going to go a long ways,right?

I mean, that'll really help thatfamily out during the holidays.

Yes, well, with the kids homefrom school,

the families have three mealsa day that they got

to put on the table.

So, it's going to make a bigdifference.

So, thank you, guys.You're welcome.

This is wonderful.Let them know Merry Christmas

on behalf of us hereat the local, okay?

Absolutely, you guys arejust, just amazing, thank you.

And please, tell, tell all theworkers how grateful

these families will be.We will.

I mean, this is not a smallproblem.

The need is so great.

And I can tell youthat it's all races,

it's all income classes

that you might think someonemight be from.

But I can tell you that when yousee it,

and you deliver this typeof gift to somebody

who is in need, just thegratitude that they show you

is incredible.

We actually know that peopleare at greater risk of mortality

for over 20 years after theylose their job due to,

due to no fault of their own, sosomething like automation

or offshoring.

They're at higher riskfor cardiovascular disease,

they're at higher riskfor depression and suicide.

But then with theintergenerational impacts,

we also see their childrenare more likely--

children of parents who havelost their job

due to automation-- are morelikely to repeat a grade,

they're more likely to drop outof school,

they're more likely to besuspended from school,

and they have lower educationalattainment

over their entire lifetimes.

It's the future of this,not the past, that scares me.

Because I think we're in theearly decades

of what is a multi-decadeadjustment period.

NARRATOR: The world is beingre-imagined.

This is a supermarket.

Robots, guided by A.I., packeverything from soap powder

to cantaloupes for onlineconsumers.

Machines that pick groceries,

machines that can also readreports, learn routines,

and comprehend are reaching deepinto factories,

stores, and offices.

At a college in Goshen, Indiana,

a group of local business andpolitical leaders come together

to try to understand the impactof A.I. and the new machines.

Molly Kinder studiesthe future of work

at a Washington think tank.

How many people have goneinto 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 actuallythe number-one occupation

for the greater DC region.

There are millions of people whowork in cashier positions.

This is not a futuristicchallenge,

this is something that'shappening sooner than we think.

In the popular discussions aboutrobots and automation and work,

almost every image is of a manon a factory floor

or a truck driver.

And yet, in our data, when welooked,

women disproportionately holdthe jobs that today

are at highest riskof automation.

And that's not really beingtalked about,

and that's in part because womenare over-represented

in some of these marginalizedoccupations,

like a cashieror a fast-food worker.

And also in a large numbersin clerical jobs in offices--

HR departments,payroll, finance,

a lot of that is more routineprocessing information,

processing paper,transferring data.

That has huge potential forautomation.

A.I. is going to dosome of that, software,

robots are going to dosome of that.

So how many people are stillworking

as switchboard operators?

Probably none in this country.

NARRATOR: The workplace ofthe future will demand

different skills, and gainingthem, says Molly Kinder,

will depend on whocan afford them.

I mean it's not a goodsituation in the United States.

There's been some excellentresearch that says

that half of Americanscouldn'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 goout without a month's pay,

two months' pay, a year.

Imagine you want to put savingstoward a course

to, to redevelop your career.

People can't afford to take timeoff of work.

They don't have a cushion, sothis lack of economic stability,

married with the disruptions inpeople's careers,

is a really toxic mix.

(blowing whistle)

NARRATOR: The new machineswill penetrate every sector

of the economy:from insurance companies

to human resource departments;

from law firms to the tradingfloors of Wall Street.

Wall Street'sgoing through it,

but every industry is goingthrough it.

Every company is looking at allof the disruptive technologies,

could be robotics or dronesor blockchain.

And whatever it is, everycompany's using everything

that's developed, everythingthat's disruptive,

in thinking about, "How doI apply that to my business

to make myself more efficient?"

And what efficiency means is,mostly,

"How do I do thiswith fewer workers?"

And I do think that when we lookat some of the studies

about opportunityin this country,

and the inequalityof opportunity,

the likelihood that you won't beable to advance

from where your parents were, Ithink that's, that's,

is very serious and getsto the heart of the way

we like to think of America asthe land of opportunity.

NARRATOR: Inequality has beenrising in America.

It used to be the top 1%of earners-- here in red--

owned a relatively small portionof the country's wealth.

Middle and lower earners--in blue-- had the largest share.

Then, 15 years ago,the lines crossed.

And inequality has beenincreasing ever since.

There's many factors that aredriving inequality today,

and unfortunately,artificial intelligence--

without being thoughtfulabout it--

is a driver for increasedinequality

because it's a form ofautomation,

and automation is thesubstitution 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 capitaland labor,

and with artificialintelligence,

we're putting our finger on thescale on the side of capital,

and how we wish to distributethe benefits,

the economic benefits,

that that will create is goingto be a major

moral consideration for societyover the next several decades.

This is really an outgrowthof the increasing gaps

of haves and have-nots--the wealthy getting wealthier,

the poor getting poorer.

It may not be specificallyrelated to A.I.,

but as... but A.I. willexacerbate that.

And that, I think, will tearthe society apart,

because the rich will have justtoo much,

and those who are have-nots willhave perhaps very little way

of digging themselvesout 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 mainreason.

To say thank you to Ohio.

(crowd cheering and applauding)

I think the Trump votewas a protest.

I mean that for whatever reason,

whatever the hot button wasthat, you know,

that really hit home with theseAmericans who voted for him

were, it was a protest vote.

They didn't like the directionthings were going.

(crowd booing and shouting)

I'm scared.

I'm gonna be quite honest withyou, I worry about the future

of not just this country,but the, the entire globe.

If we continue to go in anautomated system,

what are we going to do?

Now I've got a group of peopleat the top

that are making all the moneyand I don't have anybody

in the middlethat can support a family.

So do we have to go to the pointwhere we crash to come back?

And in this case,

the automation's already gonnabe there,

so I don't know howyou come back.

I'm really worriedabout where this,

where this leads usin the future.

NARRATOR: The future islargely being shaped

by a few hugely successfultech companies.

They're constantly buying upsuccessful smaller companies

and recruiting talent.

Between the U.S. and China,

they employ a great majority ofthe leading A.I. researchers

and scientists.

In the course of amassingsuch power,

they've also become among therichest companies in the world.

A.I. really is the ultimatetool of wealth creation.

Think about the massive datathat, you know, Facebook has

on user preferences, and howit can very smartly target

an ad that you might buysomething

and get a much bigger cut thata smaller company couldn't do.

Same with Google,same with Amazon.

So it's... A.I. is a set oftools

that helps you maximize anobjective function,

and that objective functioninitially will simply be,

make more money.

NARRATOR: And it is how thesecompanies make that money,

and how their algorithms reachdeeper and deeper into our work,

our daily lives,and our democracy,

that makes many peopleincreasingly uncomfortable.

Pedro Domingos wrote the book"The Master Algorithm."

Everywhere you go,you generate a cloud of data.

You're trailing data, everythingthat you do is producing data.

And then there are computerslooking at that data

that are learning, and thesecomputers are essentially

trying to serve you better.

They're trying to personalizethings to you.

They're trying to adaptthe world to you.

So on the one hand,this is great,

because the world will getadapted to you

without you even having toexplicitly adapt it.

There's also a danger, becausethe entities in the companies

that are in control of thosealgorithms

don't necessarily have the samegoals as you,

and this is where I think peopleneed to be aware that,

what's going on, so they canhave more control over it.

You know, we came into thisnew world thinking

that we were usersof social media.

It didn't occur to usthat social media

was actually using us.

We thought that we weresearching Google.

We had no idea that Googlewas searching us.

NARRATOR: Shoshana Zuboffis a Harvard Business School

professor emerita.

In 1988, she wrote a definitivebook called

"In the Age ofthe Smart Machine."

For the last seven years,she has worked on a new book,

making the case that we have nowentered a new phase

of the economy, which she calls"surveillance capitalism."

So, famously, industrialcapitalism claimed nature.

Innocent rivers, and meadows,and forests, and so forth,

for the market dynamic to bereborn as real estate,

as land that could be soldand purchased.

Industrial capitalism claimedwork for the market dynamic

to reborn, to be reborn as labor

that could be soldand purchased.

Now, here comes surveillancecapitalism,

following this pattern, but witha dark and startling twist.

What surveillance capitalismclaims is private,

human experience.

Private, human experience isclaimed as a free source

of raw material, fabricated intopredictions of human behavior.

And it turns out that there area lot of businesses

that really want to know whatwe will do now, soon, and later.

NARRATOR: Like most people,

Alastair Mactaggarthad know idea

about this new surveillancebusiness,

until one evening in 2015.

I had a conversation with afellow who's an engineer,

and I was just talking to himone night at a,

you know, a dinner,at a cocktail party.

And I... there had beensomething in the press that day

about privacy in the paper,and I remember asking him--

he worked for Google-- "What'sthe big deal about all,

why are people so worked upabout it?"

And I thought it was gonna beone of those conversations,

like, with, you know, if youever ask an airline pilot,

"Should I be worried aboutflying?"

and they say,"Oh, the most dangerous part

is coming to the airport,you know, in the car."

And he said, "Oh, you'd behorrified

if you knew how much we knewabout you."

And I remember that kind ofstuck in my head,

because it was notwhat I expected.

NARRATOR: That questionwould change his life.

A successful California realestate developer,

Mactaggart began researchingthe new business model.

What I've learned since isthat their entire business

is learning as much about youas they can.

Everything about your thoughts,and your desires,

and your dreams,and who your friends are,

and what you're thinking, whatyour 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 businessis basically mining

the data of your life.

NARRATOR: Shoshana Zuboff hadbeen doing her own research.

You know, I'd been readingand reading and reading.

From patents, to transcriptsof earnings calls,

research reports.

And, you know,just literally everything,

for years and years and years.

NARRATOR: Her studiesincluded the early days

of Google, started in 1998

by two young Stanford gradstudents,

Sergey Brin and Larry Page.

In the beginning, they had noclear 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 antipathytoward advertising.

Advertising would distortthe internet

and it would distort anddisfigure the, the purity

of any search engine,including their own.

Once in love with e-commerce,

Wall Street has turned its backon the dotcoms.

NARRATOR: Then came thedotcom crash of the early 2000s.

...has left hundreds ofunprofitable internet companies

begging for love and money.

NARRATOR: While Google hadrapidly become the default

search engine for tens ofmillions of users,

their investors were pressuringthem to make more money.

Without a new business model,

the founders knew that the youngcompany was in danger.

In this state of emergency,the founders decided,

"We've simply got to find a wayto save this company."

And so, parallel to this wereanother set of discoveries,

where it turns out that wheneverwe 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 howvaluable this data could be

by applying machine learningalgorithms

to predict users' interests.

What happened was,they decided to turn

to those data logsin a systematic way,

and to begin to use thesesurplus data

as a way to come up withfine-grained predictions

of what a user would click on,what kind of ad

a user would click on.

And inside Google, they startedseeing these revenues

pile up at a startling rate.

They realized that they had tokeep it secret.

They didn't want anyone to knowhow much money they were making,

or how they were making it.

Because users had no idea thatthese extra-behavioral data

that told so much about them,you know, was just out there,

and now it was being usedto predict their future.

NARRATOR: When Google'sI.P.O. took place

just a few years later,

the company had a marketcapitalization

of around $23 billion.

Google's stock was now asvaluable as General Motors.

And it was only when Googlewent public in 2004

that the numbers were released.

And it's at that point that welearn that between the year 2000

and the year 2004, Google'srevenue line increased

by 3,590%.

Let's talk a little aboutinformation, 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 totype 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 whatyou're thinking about.

(audience laughing)Now, is that over the line?

NARRATOR: Eric Schmidtand Google declined

to be interviewedfor this program.

Google's new business model forpredicting users' profiles

had migrated to other companies,particularly Facebook.

Roger McNamee was an earlyinvestor

and adviser to Facebook.

He's now a critic, and wrotea book about the company.

He says he's concerned about howwidely companies like Facebook

and Google have been castingthe net for data.

And then they realized,"Wait a minute,

there's all this data inthe economy we don't have."

So they went to credit cardprocessors,

and credit rating services,

and said, "We wantto buy your data."

They go to health and wellnessapps and say,

"Hey, you got women'smenstrual cycles?

We want all that stuff."

Why are they doing that?

They're doing that becausebehavioral prediction

is about taking uncertaintyout of life.

Advertising and marketingare all about uncertainty--

you never really know who'sgoing to buy your product.

Until now.

We have to recognize that wegave technology a place

in our livesthat it had not earned.

That essentially, becausetechnology always made things

better in the '50s, '60s, '70s,'80s, and '90s,

we developed a sense ofinevitability

that it will always make thingsbetter.

We developed a trust, and theindustry earned good will

that Facebook and Google havecashed in.

NARRATOR: The model is simplythis: provide a free service--

like Facebook-- and in exchange,you collect the data

of the millions who use it.

And every sliver of informationis valuable.

It's not just what you post,it's that you post.

It's not just that you makeplans 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 talkabout the things

that you have to do today.

It's whether you simply rattlethem on in a,

in a rambling paragraph,or list them as bullet points.

All of these tiny signals arethe behavioral surplus

that turns out to have immensepredictive value.

NARRATOR: In 2010, Facebookexperimented

with A.I.'s predictive powersin what they called

a "social contagion" experiment.

They wanted to see if, throughonline messaging,

they could influence real-worldbehavior.

The aim was to get more peopleto the polls

in the 2010 midterm elections.

Cleveland, I need you to keepon fighting.

I need you to keep on believing.

NARRATOR: They offered61 million users

an "I voted" button togetherwith faces of friends

who had voted.

A subset of users receivedjust the button.

In the end, they claimed to havenudged 340,000 people to vote.

They would conduct other"massive contagion" experiments.

Among them, one showing that byadjusting their feeds,

they could make usershappy or sad.

When they went to write upthese findings,

they boasted about two things.

One was, "Oh, my goodness.

Now we know that we can use cuesin the online environment

to change real-world behavior.

That's big news."

The second thing that theyunderstood, and they celebrated,

was that, "We can do this in away that bypasses

the users' awareness."

Private corporations havebuilt a corporate surveillance

state without our awarenessor permission.

And the systems necessary tomake it work

are getting a lot better,specifically with what are known

as internet of things,smart appliances, you know,

powered by the Alexa voicerecognition system,

or the Google Home system.

Okay, Google,play the morning playlist.

Okay, playing morningplaylist.

Okay, Google,play music in all rooms.

And those will put thesurveillance in places

we've never had it before--

living rooms, kitchens,bedrooms.

And I find all of thatterrifying.

Okay, Google, I'm listening.

NARRATOR: The companies saythey'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 areresearching

and applying for patents

to expand their reachinto homes and lives.

Alexa, take a video.

(camera chirps)

The more and more that youuse spoken interfaces--

so smart speakers-- they'rebeing trained

not just to recognizewho you are,

but they're starting to takebaselines

and comparing changes over time.

So does your cadence increaseor decrease?

Are you sneezingwhile you're talking?

Is your voice a little wobbly?

The purpose of doing this isto understand

more about you in real time.

So that a system could makeinferences, perhaps,

like, do you have a cold?

Are you in a manic phase?

Are you feeling depressed?

So that is an extraordinaryamount of information

that can be gleaned by yousimply waking up

and asking your smart speaker,"What's the weather today?"

Alexa, what's the weatherfor tonight?

Currently, in Pasadena, it's58 degrees with cloudy skies.

Inside it is, then.

Dinner!

The point is that thisis the same

micro-behavioral targeting thatis directed

toward individuals based onintimate, detailed understanding

of personalities.

So this is precisely whatCambridge Analytica did,

simply pivoting fromthe advertisers

to the political outcomes.

NARRATOR: The CambridgeAnalytica scandal of 2018

engulfed Facebook, forcingMark Zuckerberg to appear

before Congress to explain howthe data

of up to 87 million Facebookusers had been harvested

by a political consultingcompany based in the U.K.

The purpose was to targetand manipulate voters

in the 2016 presidentialcampaign,

as well as the Brexitreferendum.

Cambridge Analytica had beenlargely funded

by conservative hedge fundbillionaire Robert Mercer.

And now we know that anybillionaire with enough money,

who can buy the data,

buy the machine intelligencecapabilities,

buy the skilled data scientists,

you know, they too cancommandeer the public,

and infect and infiltrate andupend our democracy

with the same methodologies thatsurveillance capitalism

uses every single day.

We didn't take a broad enoughview 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 ofprivacy,

and his company was recentlyfined $5 billion

by the Federal Trade Commission.

He has said Facebook will nowmake data protection a priority,

and the company has suspendedtens of thousands

of third-party apps from itsplatform

as a result of an internalinvestigation.

You know, I wish I could saythat after Cambridge Analytica,

we've learned our lesson andthat everything will be much

better after that, but I'mafraid the opposite is true.

In some ways, CambridgeAnalytica 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 thatthe ability for manipulation,

both in terms of electionsand opinions,

but more broadly,just how information travels,

That is a much bigger problem,

and certainly much more seriousthan what we faced

with Cambridge Analytica.

NARRATOR: A.I. pioneer YoshuaBengio also has concerns

about how his algorithmsare being used.

So the A.I.s are tools.

And they will serve the peoplewho control those tools.

If those people's interests goagainst the, the values

of democracy, then democracy isin danger.

So I believe that scientistswho contribute to science,

when that science can or willhave an impact on society,

those scientists have aresponsibility.

It's a little bit like thephysicists of,

around the Second World War,

who rose up to tellthe governments,

"Wait, nuclear powercan be dangerous

and nuclear war can be really,really destructive."

And today, the equivalent of aphysicist of the '40s and '50s

and '60s are,are the computer scientists

who are doing machine learningand A.I.

NARRATOR: One person whowanted to do something

about the dangers was nota computer scientist,

but an ordinary citizen.

Alastair Mactaggart was alarmed.

Voting is, for me,the most alarming one.

If less than 100,000 votesseparated

the last two candidates in thelast presidential election,

in three states...

NARRATOR: He began a solitarycampaign.

We're talking aboutconvincing a relatively tiny

fraction of the votersin a very...

in a handful of statesto either come out and vote

or stay home.

And remember, these companiesknow 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 andthe gullible people.

They have access to the greatesttrove of personal information

that's ever been assembled.

They have the world's best datascientists.

And they have essentiallya frictionless way

of communicating with you.

This is power.

NARRATOR: Mactaggart starteda signature drive

for a California ballotinitiative,

for a law to give consumerscontrol of their digital data.

In all, he would spend$4 million of his own money

in an effort to rein in thegoliaths of Silicon Valley.

Google, Facebook, AT&T,and Comcast

all opposed his initiative.

I'll tell you, I was scared.Fear.

Fear of looking likea world-class idiot.

The market cap of all the firmsarrayed against me were,

was over $6 trillion.

NARRATOR: He needed 500,000signatures

to get his initiativeon the ballot.

He got well over 600,000.

Polls showed 80% approvalfor a privacy law.

That made the politicians inSacramento pay attention.

So Mactaggart decided thatbecause he was holding

a strong hand, it was worthnegotiating with them.

And if AB-375 passesby tomorrow

and is signed into lawby the governor,

we will withdraw the initiative.

Our deadline to do so istomorrow at 5:00.

NARRATOR:At the very last moment,

a new law was rushed to thefloor 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 theRepublicans won't vote for it

because it has this privateright 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 willnever forget.

So in January, next year,you as a California resident

will have the right to go to anycompany and say,

"What have you collected on mein the last 12 years...

12 months?

What of my personal informationdo you have?"

So that's the first right.

It's right of... we call thatthe right to know.

The second is the rightto say no.

And that's the right to go toany company and click a button,

on any page where they'recollecting your information,

and say, "Do not sellmy information."

More importantly, we requirethat they honor

what's called a third-partyopt-out.

You will click oncein your browser,

"Don't sell my information,"

and it will then send the signalto every single website

that you visit: "Don't sellthis person's information."

And that's gonna have a hugeimpact on the spread

of your informationacross the internet.

NARRATOR: The tech companieshad been publicly cautious,

but privately alarmedabout regulation.

Then one tech giant came onboard in support

of Mactaggart's efforts.

I find the reaction amongother tech companies to,

at this point, be pretty muchall over the place.

Some people are saying,"You're right to raise this.

These are good ideas."

Some people say, "We're not surethese 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 haveconversations with people

where we point out that the autoindustry is better

because there aresafety standards.

Pharmaceuticals,even food products,

all of these industries arebetter because the public

has confidence in the products,

in part because of a mixtureof responsible companies

and responsible regulation.

NARRATOR: But the lobbyistsfor big tech have been working

the corridors in Washington.

They're looking fora more lenient

national privacy standard,one that could perhaps override

the California lawand others like it.

But while hearings are held,

and anti-trust legislationthreatened,

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 downthe street.

It has pervaded so many elementsof everyday life,

and in a way that, in manycases, is completely opaque

to people.

While we can see a phone andlook at it and we know that

there's some A.I. technologybehind it,

many of us don't know that whenwe go for a job interview

and we sit downand we have a conversation,

that we're being filmed, andthat our micro expressions

are being analyzedby hiring companies.

Or that if you're in thecriminal justice system,

that there are risk assessmentalgorithms

that are decidingyour "risk number,"

which could determine whetheror not you receive bail or not.

These are systems which, in manycases, are hidden

in the back end of our sortof social institutions.

And so, one of the bigchallenges we have is,

how do we make that moreapparent?

How do we make it transparent?

And how do we make itaccountable?

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 taughtus,

and what Facebook continuesto teach us,

is that we don't have agency.

We're not in charge.

This is machines that areautomating some of our skills,

but have made decisions aboutwho...

Who we are.

And they're using thatinformation to tell others

the story of us.

NARRATOR: In China,in the age of A.I.,

there's no doubtabout who is in charge.

In an authoritarian state,social stability

is the watchwordof the government.

(whistle blowing)

And artificial intelligence hasincreased its ability to scan

the country for signs of unrest.

(whistle blowing)

It's been projected that over600 million cameras

will be deployed by 2020.

Here, they may be used todiscourage jaywalking.

But they also serve to remindpeople

that the state is watching.

And now, there is a projectcalled Sharp Eyes,

which is putting cameraon every major street

and the corner of every villagein China-- meaning everywhere.

Matching with the most advancedartificial intelligence

algorithm, which they canactually use this data,

real-time data, to pick upa face or pick up a action.

NARRATOR: Frequent securityexpos feature companies

like Megvii and its facial-recognition technology.

They show off cameras with A.I.that can track cars,

and identify individualsby face,

or just by the way they walk.

The place is just filled withthese screens where you can see

the computers are actuallyreading people's faces

and trying to digest that data,and basically track

and identify who each person is.

And it's incredible to see somany,

because just twoor three years ago,

we hardly sawthat kind of thing.

So, a big part of it isgovernment spending.

And so the technology's reallytaken off,

and a lot of companies havestarted to sort of glom onto

this idea that thisis the future.

China is on its wayto building

a total surveillance state.

NARRATOR: And this is thetest lab

for the surveillance state.

Here, in the far northwest ofChina,

is the autonomous regionof Xinjiang.

Of the 25 million peoplewho live here,

almost half are a Muslim Turkicspeaking people

called the Uighurs.

(people shouting)

In 2009, tensions with localHan 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. systemthat the government claims

can predict individuals proneto "terrorism"

and detect those in need of"re-education"

in scores of recentlybuilt camps.

It is a campaign that hasalarmed human rights groups.

Chinese authorities are,without any legal basis,

arbitrarily detaining upto a million Turkic Muslims

simply on the basisof their identity.

But even outside the facilitiesin which these people

are being held, most of thepopulation there

is being subjected toextraordinary levels

of high-tech surveillance suchthat almost no aspect of life

anymore, you know, takes placeoutside

the state's line of sight.

And so the kinds of behaviorthat's now being monitored--

you know, which language do youspeak at home,

whether you're talking to yourrelatives

in other countries,how often you pray--

that information is now beinghoovered up

and used to decide whetherpeople should be subjected

to political re-educationin these camps.

NARRATOR: There have beenreports of torture

and deaths in the camps.

And for Uighurs on the outside,

Xinjiang has already beendescribed

as an "open-air prison."

Trying to have a normal lifeas a Uighur

is impossible both insideand outside of China.

Just imagine, while you're onyour way to work,

police subject you to scanyour I.D.,

forcing you to lift your chin,while machines take your photo

and wait... you wait until youfind out if you can go.

Imagine police take your phoneand run data scan,

and force you to installcompulsory software

allowing your phone calls andmessages to be monitored.

NARRATOR: Nury Turkel, alawyer and a prominent

Uighur activist, addresses ademonstration in Washington, DC.

Many among the Uighur diasporahave lost all contact

with their families back home.

Turkel warns that this dystopiandeployment of new technology

is a demonstration projectfor authoritarian regimes

around the world.

They have a bar codes insomebody's home doors

to identify what kind of citizenthat he is.

What we're talking about is acollective punishment

of an ethnic group.

Not only that, the Chinesegovernment has been promoting

its methods, its technology,it is...

to other countries, namelyPakistan, Venezuela, Sudan,

and others to utilize, tosquelch political resentment

or prevent a political upheavalin their various societies.

NARRATOR: China has a grandscheme to spread its technology

and influence around the world.

Launched in 2013, it startedalong the old Silk Road

out of Xinjiang,and now goes far beyond.

It's called "the Belt and RoadInitiative."

So effectivelywhat the Belt and Road

is is China's attempt to,via spending and investment,

project its influenceall over the world.

And we've seen, you know,massive infrastructure projects

going in in places likePakistan, 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 Roadultimately does is, it attempts

to kind of create a politicalleverage

for the Chinese spendingcampaign all over the globe.

NARRATOR: Like Xi Jinping's2018 visit to Senegal,

where Chinese contractors hadjust built a new stadium,

arranged loans for a newinfrastructure development,

and, said the Foreign Ministry,

there would be help"maintaining social stability."

As China comes into thesecountries and provides

these loans, what you end upwith is Chinese technology

being sold and built out by,you know, by Chinese companies

in these countries.

We've started to see it alreadyin 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-typethings all over.

You know, you see it inCambodia, you see it in Ecuador,

you see it in Venezuela.

And what they do is, they sella 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 ofcameras,

and we'll build you a kind of,you know, a main center

where you have police who canwatch these cameras."

And that's going in all overthe world already.

There are 58 countries thatare starting to plug in

to China's vision of artificialintelligence.

Which means effectively thatChina is in the process

of raising a bamboo curtain.

One that does not need to...

One that is sort ofall-encompassing,

that has shared resources,

shared telecommunicationssystems,

shared infrastructure,shared digital systems--

even shared mobile-phonetechnologies--

that is, that is quickly goingup all around the world

to the exclusion of usin the West.

Well, one of the thingsI worry about the most

is that the worldis gonna split in two,

and that there will bea Chinese tech sector

and there will be anAmerican tech sector.

And countries will effectivelyget to choose

which one they want.

It'll be kind of like the ColdWar, where you decide,

"Oh, are we gonna alignwith the Soviet Union

or are we gonna alignwith the United States?"

And the Third World gets tochoose this or that.

And that's not a world that'sgood for anybody.

The markets in Asia and theU.S. falling sharply

on news that a top Chineseexecutive

has been arrested in Canada.

Her name is Sabrina Meng.

She is the CFO of the Chinesetelecom Huawei.

NARRATOR: News of thedramatic arrest of an important

Huawei executive was ostensiblyabout the company

doing business with Iran.

But it seemed to be more aboutAmerican distrust

of the company's technology.

From its headquartersin southern China--

designed to look like fancifulEuropean capitals--

Huawei is the second-biggestseller of smartphones,

and the world leaderin building 5G networks,

the high-speed backbonefor the age of A.I.

Huawei's C.E.O.,a former officer

in the People's Liberation Army,

was defiant aboutthe American actions.

(speaking Mandarin)

(translated): There's no waythe U.S. can crush us.

The world needs Huawei becausewe are more advanced.

If the lights go out in theWest, the East will still shine.

And if the North goes dark,then there is still the South.

America doesn't representthe world.

NARRATOR: The U.S. governmentfears that as Huawei supplies

countries around the worldwith 5G,

the Chinese government couldhave back-door access

to their equipment.

Recently, the C.E.O. promisedcomplete transparency

into the company's software,

but U.S. authoritiesare not convinced.

Nothing in China exists freeand clear of the party-state.

Those companies can only existand prosper

at the sufferance of the party.

And it's made very explicit thatwhen the party needs them,

they either have to respondor they will be dethroned.

So this is the challenge with acompany like Huawei.

So Huawei, Ren Zhengfei, thehead of Huawei, he can say,

"Well, we... we're just aprivate company and we just...

We don't take ordersfrom the Communist Party."

Well, maybe they haven't yet.

But what the Pentagon sees,

the National IntelligenceCouncil sees,

and what the FBI sees is,"Well, maybe not yet."

But when the call comes,

everybody knows what thecompany's response will be.

NARRATOR: The U.S. CommerceDepartment

has recently blacklistedeight companies

for doing business withgovernment agencies in Xinjiang,

claiming they are aidingin the "repression"

of the Muslim minority.

Among the companies is Megvii.

They have strongly objectedto the blacklist,

saying that it's "amisunderstanding of our company

and our technology."

President Xi has increased hisauthoritarian grip

on the country.

In 2018, he had the Chineseconstitution changed

so that he could be presidentfor life.

If you had asked me20 years ago,

"What will happen to China?",I would've said,

"Well, over time, the GreatFirewall will break down.

Of course, people will getaccess to social media,

they'll get access to Google...

Eventually, it'll become a muchmore democratic place,

with free expressionand lots of Western values."

And the last time I checked,that has not happened.

In fact, technology's becomea tool of control.

And as China has gone throughthis amazing period of growth

and wealth and openness incertain ways,

there has not been thedemocratic transformation

that I thought.

And it may turn out that,in fact,

technology is a better tool forauthoritarian governments

than it is for democraticgovernments.

NARRATOR: To dominatethe world in A.I.,

President Xi is depending onChinese tech

to lead the way.

While companies likeBaidu, Alibaba,

and Tencent are growing morepowerful and competitive,

they're also beginning to havedifficulty accessing

American technology, and areracing to develop their own.

With a continuing trade warand growing distrust,

the longtime argument forengagement

between the two countrieshas been losing ground.

I've seen more and moreof my colleagues move

from a position when theythought,

"Well, if we just keep engagingChina,

the lines betweenthe two countries

will slowly converge."

You know, whether it's ineconomics, technology, politics.

And the transformation,

where they now thinkthey're diverging.

So, in other words, the wholeidea of engagement

is coming under question.

And that's cast an entirelydifferent light on technology,

because if you're diverging andyou're heading into a world

of antagonism-- you know,conflict, possibly,

then suddenly, technology issomething

that you don't want to share.

You want to sequester,

to protect your own nationalinterest.

And I think the tipping-pointmoment we are at now,

which is what is castingthe whole question of things

like artificial intelligenceand technological innovation

into a completely differentframework,

is that if in fact Chinaand the U.S. are in some way

fundamentally antagonisticto each other,

then we're in a completelydifferent world.

NARRATOR: In the age of A.I.,a new reality is emerging.

That with so much accumulatedinvestment

and intellectual power, theworld is already dominated

by just two A.I. superpowers.

That's the premise of a new bookwritten by Kai-Fu Lee.

Hi, I'm Kai-Fu.

Hi, Dr. Lee, sonice 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 youdidn'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 thisgentleman a book?

(people talking in background)

NARRATOR: In his bookand in life,

the computerscientist-cum-venture capitalist

walks a careful path.

Criticism of the Chinesegovernment is avoided,

while capitalist successis celebrated.

I'm studying electricalengineering.

Sure, send me a resume.Okay, thanks.

NARRATOR: Now, with the riseof the two superpowers,

he wants to warn the worldof 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 beenhigher

or the stakes of failuregreater."

So if one has to say who'sahead, I would say today,

China is quickly catching up.

China actually beganits big push

in A.I. only two-and-a-halfyears ago,

when the AlphaGo-Lee Sedol matchbecame the Sputnik moment.

NARRATOR: He says he believesthat the two A.I. superpowers

should lead the way and worktogether

to make A.I. a force for good.

If we do, we may have a chanceof getting it right.

If we do a very good jobin the next 20 years,

A.I. will be viewed as an age ofenlightenment.

Our children and their childrenwill see A.I. as serendipity.

That A.I. is here to liberate usfrom having to do routine jobs,

and push us to do what we love,

and push us to think what itmeans to be human.

NARRATOR: But what if humansmishandle this new power?

Kai-Fu Lee understandsthe stakes.

After all, he invested earlyin Megvii,

which is now on the U.S.blacklist.

He says he's reduced his stakeand doesn't speak

for the company.

Asked about the governmentusing A.I.

for social control,he chose his words carefully.

Um... A.I. is a technologythat can be used

for good and for evil.

So how... how do governmentslimit themselves in,

on the one hand,using this A.I. technology

and the database to maintaina safe environment

for its citizens, but,but not encroach

on a individual's rightsand privacies?

That, I think, is also a trickyissue, I think,

for, for every country.

I think for... I think everycountry will be tempted

to use A.I. probablybeyond the limits

to which that you and I wouldlike the government to use.

NARRATOR: Emperor Yao devisedthe 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 withone of its architects.

So A.I. can be used in manyways that are very beneficial

for society.

But the current use of A.I.isn't necessarily aligned

with the goals of buildinga better society,

unfortunately.

But, but we could change that.

NARRATOR: In 2016, a game ofGo gave us a glimpse

of the future of artificialintelligence.

Since then, it has become clearthat we will need

a careful strategy to harnessthis new and awesome power.

I, I do think that democracyis threatened by the progress

of these tools unless we improveour social norms

and we increasethe collective wisdom

at the planet level to, to dealwith that increased power.

I'm hoping that my concerns arenot founded,

but the stakes are so high

that I don't think we shouldtake these concerns lightly.

I don't think we can play withthose possibilities and just...

race ahead without thinkingabout the potential outcomes.

Go to pbs.org/frontline formore of the impact

of A.I. on jobs.

I believe about fifty percentof jobs will be somewhat

or extremely threatened by A.I.in the next 15 years or so.

And a look at the potentialfor racial bias

in this technology.

We've had issues with bias,with discrimination,

with poor system design,with errors.

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