>> narrator: tonight-- >> the race to become an ai superper is on... >> narrator: the politicicof artificial intelligence... >> there will be a chinese tech sector and there will be a amican tech sector. >> narrator: the new tech war. >> the more data, the better the ai works. so in the age of ai, 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.>> believe about 5 5 of jobs will be somewhat or extremely threatened by ain the next 15 years or so. >> narrator: ai and corporate rveillance... >> we thought that we were searching g ogle. we had n nidea that google was searching us.ea

>> narrator: and t tt to democracy. >> china is on its way to building a total surveillance state. >> narrator: tight on frontline-- >> it has pervaded so ny emem of everyday life. how do we make it transparent and accountable? >> narrator: "in the age of ai". >> froroline is made possible by contributions to your pb station from viewers like you. thank you. major support is provided by the john d. and catherine t. macarthur foundation, coitted to building a more just, verdant e ford foundation:. working with visionaries on the frontlines of social change worldwid additional support is provid by the abrams foundation, committed to excellence in journalism. the park foundation, dedicated to heightening pububc awareness s critical issues. the john and helen glessner family trust. ppororng trustworthy journalism that informs and inspires. and by thejo frontlinnalism fund, with major support from jon and jo ann hagler.ad

antitial support from tom m air and lucy caldwell-stair. major support for frontline and, "in thage of ai" is provided by the corporation for public broadcasting. ♪ most complex board game. world's 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 ow

industrial age.. ♪ it was 2016, in seoul, south korea.s >> can machiovertake humante lligence? a brkthrough moment when the world champion of the asian board game go takekeon an a.i. program developed d google. >> (speaking korean): >> in countries where it'slaery popu like china and japan go is not t st a game, right?, it's, like, how you learnn it has an almost spiri componen you know, if you talk to south reans, right, and lee sedol is the world's greatest south korea. a national hero in

they were sure that lee sedol would beat alphago hands dn. ♪ >> narrator: google's alphago was computer program that, and a database ohioricalof go games, had been designed to teach itself. ta i was one of the commenrs g at the lee sedoles. ansyes, it was watched by t of millions of people. (man speaking korean) >> narrator: throughoutas southeast asia, thiseen as a sports spectac with national pride at stake. >> wow, that was a player gus. w>> narrator: but much mo in play. this was the public unveilingl of a form of artific intelligence called deep learning, that mimics the neural networks of the human brain. ma>> so what happens with ine learning, or artificial intelligence-- initially with alphago-- is that the mache is fed all kinds of go games, and then it studies them, lear

from them, and figures out its own moves. and because it's aa.i. systst-- it's not just following instructions, it's figuring out its own instructions-- it comes ith moves that humans hadn't't'tught of before.ve so, it studies gameseshat humani have playeknows the rules, and then it comes up with creative moves. (woman speaking korean) (speaking korean): th >> that's a very's a very surprisi 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 p ing brilliant and woke people up to say, "wow, afr thousands of years oea playing, we never thought about making a move like that." >> oh, he resigned. itooks like... lee sedol h just resigned, actually. >> yh!

>> yes. >> narrator: in the end, the scientists watched their algorithms win four of the gas. lee sedol took one. >> what happened with go, firsto anmost, was a huge victory for deep mind and for a.i., right? it wasn't that the computers beat the humans, it wathat, you know, one type of telligence beat another. >> narrator: artificial ininlligence had proven it could marshal a vast amount of data, handle, and ususit to teachould itself how to predict an outcome. the commercial implications were enormous. >> while alphago is a, is a a y gamemebut its success and its waking everyone up, i ink, is, is going to be rememred as the pivotal moment where a.i. became mature and everybody jumped on the bandwagon. ♪ s >> narrator: tis 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 wiwi also deepen and the world into twoemocracyi a.i. superpowers. tonight,ive stories about how artificial intelligence is changing our world. ♪ china a s 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 veryounger people, so that this clearly is technology which is being generated by a whole new neration. >> arrator: orville schell is one of america's foremost china scholars. >> (speaking mandarin) >> narrator: he first came her 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 whan you see here. it was unimaginabl ry much thought, "this is the way china is, this is the way it's goingngo be." and the fact that it has gone through so many different chans since is quite extraordinary. (man giving instructions) >> narrator: t ts 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 foreignow company g us up at our own gaga. and this is going to be something that is gogog to be critalal 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 e u.s. in artificial intelligence by 2025 and lead the world by 2030. >> (translated): ...and intensified cooperation in frtier areas such as digit economy, artificial intelligence, nanotechnology, and accounting computing.pu ♪ >> nartor: today, china leads

the world in e-commerce. drones deliver to rural villes. and a society that bypassed credit cards now shops in stores without cashiers, where the currency i ifacial recognition. that fast.try has ever moved and in a short two-and-a-half years, china's a.i.ea implementationy went from minimal amount to probably about 17 or 18 unicorns, that is billion-doararompanies, in a.i. todayay and that, that progress is, is hard to believe. >> narrator: the progrgrs was powered by a new generatatn ofch ambitious young 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, eated by

u.s.-educated a.i. scientist and businessman kai-fu lee. >> these unicorns-- we've gotth one, twoe, four, five, six, in e general a.i. area. and unicorn means a billion-dollar company, a company whose e luation or market capitalization is at $1 billion or higher. tothink we put two unicorn 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 acarnegie mellon was on computer speech recognition, which took him to apple. >> well, reality is a step closer to science ction, with apple computers' new developed program... >> narrator: and at 31, an early measure of fame. >> kai-fu lee, the inventor of applpls speechecognition technology. c >> caspey this to make write 2. casper, paste. casper, 72-point italic outlinel

>> narrator: he move on to microsoft research in asia and became the head of gooe china. ten years ago, he started sinovation in beijing, andegan looking for promising startupsen and a.i. tal >> s s the chinese entrepreneurial companies started asasopycats. but over the last 15 years, china has developed its own form of entrepreneurship, and tt entrepreneurship is described aa tenacious, very winner-take-all, andet incredible worc. i would say these, a few thousand chinese top entrepreneurs, they could take the world.repreneur anywhere in >> narrator: entrepreneurs like cao dong, th-y-yr-oldst c.e.o. of a new artup called momenta. beijing.a ring road around e car driving itself.

♪ ot >> you see, anher cutting, another cutting-in. >> another cut-in, yeah, yeah. >> narrator: caoas no dot about the inevitability ofeh autonomousles.no thn player in, in go, in beatma think the e chine will definitely surpass the human e iver, in t. narrar: recently, the have been cautions about how soon autonomous vehicles will ba deployed, buand his team are confident they're in for the long haul. >> u.s. . ll be the first to deploy, but china may be the firsto 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 irastructure efforts, for example, building

a new city the size ofhicago with autonomous driving enabled, and also new highway that has sensors built in to help autonomous vehicle be safer. >> narrar:heir early investors included mercedes-benz. >> i feel very lucky and very inspiring and ry exciting that we're living inin this era. ♪ >> narrator: life in china is i largely conducted on a billion people use w the equivalent of facebook, messenger, and paypal, and much more, combined into just one super-app. and there are many more.s >> chinae best place for a.i.mplementation today, because the vast amount of data that's available in china. china has a lot more users than any other cocotry, three to four times morehan the u.s. there are 50 times more mobile payments than the u.s.

there are ten times more food deliveries, , ich serve as data behavior than the u.s.er 300 times more shared bicycle rides, and each shared bicycle ride has all kinds of sensorssit sung data up to the cloud. we're talking about maybe ten .stimes more data than the 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 rerearcher is working on the problem. so, in the age of a.i.i.wheref the new saudi arabia.china is >> 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. ca >> here is our appon. and customer can choose howny oney they want to borrow

and how long they want to borrow, and they can input their datas here. and ter, after tha you can just borrow very quickly. >> narrator: the c.e.o. shows us how quickly you can get a loan. >> it is, , has done. >> narrator: it takes anverage of eight seconds. >> it has passed to banks. >> wow. >> narrator: in the eight seconds, the aorithm h h assessed 5,000 personal features from all youdata. >> 5 500 features that is related with the delinquen, when maybe the banks onluse few, maybe, maybe ten features when they are doing their risk g amendment. >> narrator: processing millions of transactions, it'll dig up features that would never bere ap to a human loan officer, like how confidently you type your loan application,

or, surprisingly, if you keep k 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 ttery, they get much moree >> 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. >> narrarar: like this facial-recognition startup he invested in. megvii was started by three young graduatein 2011. it's now a world leader in using a.i. to identify people.e.in >> 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 0.1ecd that we can, we will be able to recognize you, even a mobile device. >> narrator: the company claimss the system is better than any e human at identifying peo its database. and r those who aren't, it c n describe them. like our director-- what he's wearing, and a good guess at h h age, missing it by only a few months. >> we are the firsonto really take facial recognition to commercial quality. >> narrator:r:hat's why in beijing today, you can pay for your kfc with a smile. >> you know, it's not so surprising, we've se chinese companies catching up to the u.s. in technology for a long time. and so, if particular effort and attention is paiaiin aic specector, it's not so surprising that they would surpass the rest of the world. i and facial recognitione of the, really the first places we've seen that start to happen.

>> narrator: it's a technology prized by the government, like th program in shenzhen to discourage jaywalking. offenderare shamed in public-- and with faciarecognition, can bebenstantlyined critics warn that the gornment and some private companies have been building a nationalalro databasedozens of experimental social-credit programs. >> the government wants to integrate all these individual behaviors, or corporations' records, into so kind of metrics and compute out a singl numbert of number associated with a individual, a citizen, a using that, to implement a incentive or punishment stem. >> narrator: a high social-cdit number can be rewarded witdiscounts on bus fares. a lolonumber can lead to a travel ban.

some say it't'very popularne with ase public that wants to punish bad behavior. othehe see a future that rewards rty loyalty and silences criticism. >> right now, there is no final system being inglemented. and from thosexperiments, we already see that the possibility of what this social-credit systememan do to individual.an orn-like-- and it's-ll extremely troublesome in terms of civil liberty. >> narrator: every evening in shanghai, , er-present cameras record the crowds as they surge along g e banks of thepuomene 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 n mao's but now, in the age ofom people ce here to take in a spectacle that reflects china's remarkable progress. (spectators gasp) and illuminates the grea political paradox of capitalism taken root in e communist state. >> people have called it market leninism, authoritarian capitalism. we are watching a kind of a petri dish in which anex riment 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 e world. whether you can bring togeer a one-party state with an innovative sector, both economically and technologically

innovative, and that something we thought could not coexist. >> narrator: as china reinvents itse, it h set its sights on leadidi t t world i i artificial intelgence by 2030. but that means taking on the world's most innovative a.i. culture. ♪ an interstate in the u.s. ininlligence is at work solv 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

plsuccessfully, the less p ask questions about how old you are when you have working. truc he's built.and this is what commercial goods are being driven from california to arizona on interstate 10. theris 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 robotic starting whes 11, and i took it very, very seriously. 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-i i eventually founded a team, did a t of work at a very high competitive level. things looking pretty good.r: >> narrahis was a prototype of sorts, fromomhich he has built hisi- mullion-dollar company.ar

>> i hadn't built a robot in a while, wanted to get back to it, and felt that th was by far the most exciting piece of robotics technology that was up and coming.a t of people told us we wouldn't be able to build it. but knew roughly the techniquesu thatould use. and i was pretty confident that if you put them together, you would get someing 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 thfirst of several rounds of venture capital. he formed a team and then decided e business opportunity was in self-driving trucks. he says therers 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,pe ally, everyone agrees that the only way that we're going to is to use self-driving.'vtive,

and so, i'm sure yheard the statistic, more than 90% of all crashes have a han driver as t cause. so if you want to solve traffic fatalitieseswhich, in my opinion, are the single biggest tragedy that happens year aftert year in the united states, this is the only solution. >> narrator:r:t's an aitious goal, but only possible because of the recent brbrkthroughs in deep learning. >> artificicl intells one of those key pieces that has made it possible now to do driverless vehicles where it wasn't possible ten years ago, particularlyn the ability to see and understand scenes. a lot of people don't know this, but it's remarkably hard forco uters, until very, very recently, to do even the most basic visual tasks, like sing a picture of a person and knowing that it's a person. and we've made gigantic strides with artificial intelligence inb bein to see and understanding tasks, and that's obviously fundamental to being able to undersnd the world

around you with the sensors that, thatatou have available. >> narrator: that's now possible because of the algorithms wririen by yoshua bengio a a a small gro o o 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 atathe bottom of the iceberg, the solution was, the computers have to acquire that knowledge by themselvlv from data, from examples. just like children learn, moster not from their tea but d playing around, and, andworld, 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 vid 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 e ll and break the bricks at the top. after 300, it could do that better than a human player. after 500 games, it came up witr tive 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 ccessful in the last few years and has... you know, it wasn't clear tenag yearthat it would work, but it has completely changed the map anis now used ininin almost every sector of society. >> even the best and brightest among us, we just don't have enough compute powernside of our heads.

>> narrator: amy webb is a unprofessor at n.y.u. and r of the future today institute. >> as a.i. progresses, thet gromise is that they... ongside of us,s,re able tos, 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 clclate change. h maybe e some radically different apoach to dealing with incurable cancers. the real practical and wonderfu prom that machines help us more creative, and, using at creativity, we get to terrific solutions. >> narrator: solutions that could come unexpectedly to urgent problem >> it's going to change the face of breast cancer.

righ 40,000 women in the u.s. alone die from breast cancer every single year.. >> narrator: dr. connie lehmanre is head of thet imaging center at massachusetts general hospital in boston. >> we've become so complact about it, almost don't think it can really be changed. we, we somehow think we should put all of our energy intopi chchothe tsave women with metastatic breast cancer,w, and yet, you khen we find it ear, 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 diagsis of the small cancer here. >> narrator: this is what happened when a woman who had been diagnosed with h east cancer started to ask questions about why it couldn't have beenb diagnosed earlier. >> it really brings a lot ofou anxiety, ande asking the questions, you know, "am i going to survivi?en what's going to hao my

son?" and i start asking other ququtions. >> narrator: she was used to asking questions. at m m.t.'s artificial-intelligence lab, professor regina barzilay uses deep learning to teach the computer to understand language, as well as read text andata. >> i was really surprised that the ry basic question that i ask my physicians, which were really excellent physicians here at mgh, thehecouldn't give me answers that i was looking for. >> narrator: she was convincnc that if you analyze enough data, from mammograms toam diagnostic notes, the computeric could prearly-stage conditions. >> if we fast-forwararfrom 2012 to '1313o 2014, we then see when regina was diagnos, because of this spot on herammogram. m is it possible, wie elegant computer applications,

that we might haha identified this spot the year before, or even back here? >> so, those are standard prediction problems in machine learning-- tre inothing spial abouthem. of the technologies that we are developing at m.i.t., even inim the moste form, doesn't penetrate the hospital. nn narrator: regina and coie began the slow process of getting access to thousands of mammograms and records from ammgh's breast-imaging pro j >o, our first foray wt to take all of the patients we hahaat mgh during a period of time, who had had breast surgery for a certain type of d we found that most of them didn't really need the surgery.y idn't have cancer. but about ten percn t did have cancer.a' with regtechniques in deep learning and mache learning, we were able to predict the women that truly

needed the surgery and separate out t ososthat really could avoid the unnecessary surgery. >> what mache 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 correlatecc highly with futurerence of the disease.d so, inst using human capacity to kind of recognize pattern, formalize pattern-- which is inherently limited byba our cognitive capaci how much we can see and remember-- we're providing machine e th a this prediction.ke it learar >> so, we are using technology noonly to be better at asseseing the breast densityet but to get more to the point of what we're trying to prect. now, and will she develop acer cancer in five years?"

and that's, again, where thege artificial intele, machine and deep learning can really help us and our patients. >> narrator: in the age a.i., the algorithms are transpoing us into a universe of vast potential and ansforming almost every aspect of human endeavor and expxpience. andrew mcafee is a researchat scientis.i.t. who co-authored "the second machine agag" t great compliment that a songwriter gives another one is, "gosh, i wish i had written thah one.e. the great compliment a geekhe gives anone is, "wow, i wish i had drawn that graph."" so, i wish i had drawn this aph. >> narrator: the graph uses a formulto show human developmpmt and growth since 2000 bce. >> the state of human civilization is not very advanced, and '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 empis got overturned, when we tried democracy, when we

invented zero and mathatics about the universe, bi.ries it just, t numbers don't change very much. what's weird is that the numberi change essly in the blink of an eye at one point in time. and it goes from rlly horizontal, unchanging, crazy vertical.to, holy toledo, and then the queion is, what on earth happened to cau that change? and the answer is the instrial revolution. there were other things that happened, but really what fundamentally happed is, we overcame the limitations of our muscle power. somethinequally interesting is happing right now. we are overcoming the we're not getting rid m, we're not making them we leverage them and alify, can them now. u have to be a huge pessimistro not to find thatundly good news. >> i really do think the worer has entered a ne artificial intelligence holds so much promise, but it's going to reshape every aspect of the

economy, so many aspngts of f r 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., integratingt governments are going to be using it, nonprofit organitions are going to be ing 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 nefits-- the autonomous truck represents both as it maneuvers into the marketplace. the engineers are confident about when this will htions they can get it working safely sooner than st 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,mo geographies, more weather ilds up.e as, as that capability we're talking, like, less than

half a dece. >> narrator: he already has a fortune 500 company as a clientshipping appliances across the southwest. s s thsales pitch is straightforward. >> they spend hundreds of millions of dollars a yeard shipping parts a ae country. we can bring that cost d they're really excited to be able to start working with us, both because of the potential, the potential savings from deploying self-driving, andau also b of all the operational efficiencies that they see, the biggest one being able to operate 24 hours a day. so, right now, human drivers ari lid to 11 hours by federal law, and a driverless truck obvivisly 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" abo thehendustry. >> this is one of the most remarkable stories in, in u.s. labor history, i think, isisyou know, the decline of, of unionized trucking. the industry was deregulated in 1980, and at that time, you know, truck drivers were earning theqeqvalent 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 >> narrator: f his research, viscelli tracked down truckers

and their families, like shawnve and hope cumbee of bon, michigan. >> hi. >> hey, hope, i'm steve viscelli. >> hi, steve, nice to meet you. >> great to meet youtoo, thanks. >> come on in. >>arrator: and their son charlie. >> this is daddy, me, daddy, and moy. >> narrator: but daddy's not here. shawn cumbee'sruck has broken down in tennessee.o hope, ove a truck herself, knows the business well. >> we made $150,000, right, in a year. th sounds great, rht? that's, like, good money. we paid $100,000 in fuel, okay? so, right there, now i made but i didn't really, b, 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, , choke a e it was... thinkiki about it,ca

and it was 13,000, and we were off work for two weeks. so, by the end of the ye, with that $150,000, by the end of the year, we'd made about 20... about $22,000.ra >> nr: in a truck stop in tennessee, shawn has been sidelined waiting for a new part. the garage owner is lettinthhim stay in the truck to save money. >> hi,aby. >> (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 itca e i love it. i mean, you know, it's'sn the blood. third-generati dririr. and my grandndddy told me a long time ago, when i was probably 11, 12 years old, probably, he sa, "the world meets nobody halfway. nobody." he said, "if you want it, you i have to ea" 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'rereown for a week in a truck, you still have to pay your bills.mo i have enougy in my choking account at all times to pay a month's worth of bills. that does not inclcle my foooo that doesn'tnclude field trips for my son's school. my son and i just wento ourap yearly doctointment. i took, i took money out of mygg son's baba to pay for it, because it's not... it's not scheduled in. it's, it's not something that you can, you know, aff.d. i an, like, when... (sighs): sor. >> it's okay. ♪ have you guys ever talked about self-driving trucks? is he... >> (laughi): so, kind of. um, i i ked 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 abouit, you know, they're putting all this new technology into things, but, you know, it's still man-mad and man, you know, does make mistakes. i really don't see it being a problem with the industry, 'cause, one, you sll 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. o i don't see it backing i dock. i n't see the automation part, you know, dog... maybe the box-trailer side, you know, i can see thth, but not stuff like i do. so, i ain't really worried about the automation of trucks. >>ow near of a future is i >> yeah, self-driving, um... so, someyou know, some companies s e already operating. embark, for instance, is one that has been doing driverless trucks on the interstate. and what called exit-to-exit self-driring. and they're cuently running real freight. >> really? >> yeah, on i-10. ♪ >> (on p.a.): shower guest 100, your shower is now ready.

>> narrator: over time, has become harder and harder foa veteindependent drivers like the cumbees to make a living. they've been replaced bys younger, lperienced drivers., >> so, te trucking industry's $740 billion a yearar and, again, in, in many of these operations, labor's a thirdd, of that cost. by my estimate, i, you know, i think we're in the range of 300,000 or so jobs in the seeable future that t uld be automated to some significant extent. ♪ >> (groans) ♪ he >> narrator:.i. future was built with grere optimism m t here in the west. of in 2018, manhe people who invented it gathered in san

2francisco to celebrate th anniversary of the industry >> howdy, welcome to wired25. >> narrator: it is a celeleation, for sure, but there's also a growing sense of caution and even skepticism. >> we're having a real good weekend here. >> narrator: nick thompson is editor-in-chief of "wired." >> when it started, it was ver>r much a magazine about what's coming and why you shod be excited about it. feature of "wid" for many, many years. or, as our slogan used tbe, "change is good." and over time, it shshted 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 naturef "wired" has gone from a champion of technological change to more

of a observer of technological change.or >> so, um, bwe start... >> narrator: there are 25 speakers, all named as icons of the last 25 years of so, why is apple soss. secretive? >> (chuckling) >> narrator: jony ive, who designed apple's iphone. >>t would be bizarre not to be. >> there's this question of, li , what are we doing here in this life, in this reality? w>> narrator: jaron lanie pioneered virtual reality.un and jeff bezos, the r of amazon. >> amazon was a garage startup. two kids in a dorm...ny. >> narrator: his message is,l "all w well in the new world." >> i guess, first of alllli remain incredibly opmistic about technology, and technologies always are two-sided. but that's not new. that's always been thee. and, and we will figure it outul the last thing we ever want to do is stop the progress of new technologies, even whene.

they are dual- >> narrator: but, says thompson, beath the surface, there's 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 historythere's been a complicated relationship utwe've always worried anes, machines, and it's always been fine. and we don't know how a.i. will change the lab forceabbut it will be okay." so, that argument exists. there's another argument, ich is what i think most of them believe deep down, which is, "this is different. we're going to have labor-forcec disruption like we've never seen before. and if that happens, will theyus blam >> narrator: there is, however, one of tow wired25 icons willing to take on the issueue onste, kai-fu lee dispenses with one common fear. i >> well, t there are so many mnyhs 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 tola ding humans. >> narrator: but in interviewsnt around the end beyond, he takes a decidedly contrarian o positia.i. and job loss. >> the a.i. giants want to paint the rosier pture because ey're happily making money. so, i think they prefer t 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 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 creatingalue, making high mgins, inventing a newde but i could list seven or eighta thatould lead ery clear displacement of human jobs. >> narrator: he says that a.i. is coming, whether we like it n. and he wants to warn society about what he sees as inevitable. is different than many others,ha which isa.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,c a replacement for bllar, white-collar jobs, and be a great symbiotic tool f doctors, lawyers, and you, for example. t the white-collar jobs are easier to take, because they're a pure quantitative analytical let's say reporters, t,

telemarking, telesales, customer service... >> analysts?st >> ana 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, wh are we going g do? half the jobs are going away." i believe thth's true, but here's the missing fact. i've de the research on this, oand if you go back 20, 3 40 years ago, you will find that 50% of t jobs that people performed back then are gone today. you know, ere are all thele one operators, bowling-pin setters, elevator erators? you used to have seas of secretaries in corporations that haveveow been eliminated-- travel agents. you can juju go through field after field aftefield. that same pattern has s curred many times throuout history, with each new wave of automation.

>> but i would argue that history is only trustable if it is multiple repetitions of similar events, notn once-in-a-blue-mcurrence. so, over the history of many tech inventions, most are small things. only maybe three are at the magnitude of a.irevolution-- the steam, stete engine, electricity, and the computer revolution. i'd say everythinglse is too small. and the reason i think it might be somethingngrand-new is that a.i. is fundamtally replacing our cognive process in doing a job in its significant entirety, and it can do it dramatically better. >> narrator: this argument a.i. was ignited six years agoyl amid thehear and spires of oxford university.

two researchers had been poring through u.s. labor statistics, identifying jobs that could be lnerable to a.i. automation. >> well, vulnerable to 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%. >>arrator: 47%. that number quicy traveled the world in headlines and news bulletins. f but authors cay and michael osborne offered a caution.ct they can't pow 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 quitear famio today, which is the brish industrial revolutio where wages didn't grow for nine

decades, and a lot of people actually saw living standards decline as technology progssed. ♪ ows about decline in livinggan, standards. harry cripps, an auto worker ano a l union president, has witnessed what 40 years ofma auon can do to a town. >> younow, we're one of the cities in the cocotry that, i this rovery.e left behind in 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 localn. unio now, with falling membership, itit shared by five lols. >> rudy didn't get his shift. t >> narratos 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 sent their kio llege and do all the things that the middle-class family should be able too. automation, would probably be about 700 united auto workers. that a dramatic change. work there, buddy.er >> the trw plant, that was >> delphi... looks like they're arting to tear it down now. wow. automations is, is definitely taking away a lot of jobs. robobo, i don't t ow how they buy cars, i n't know how they buy sandwiches, i don't know how they go to the gcery store.n' they definitely pay taxes, which serves the infrastructure. so, you don't have the sheriffs and the lice and the firemen,

d 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.mi >> a lot of the faes 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, raraed the children. and that give us the opportututy to put food on the table, and o thinthat nature. and, and them times are gone. o if you look at this gra what's been happening to america since the end of world war ii, you see a line for our productivity, and our me.ductivity gets better over it used to be the case that our pay, our income, would increase in lockstep with those productivity increases. the weird part about this grgrhm

is how the ihas decoupled,d, is not going up the same way that produivity is anymore. >> narrator: as automation hass taken n er, worke either laid off or r ft with less-skilledobs for less pay, while productivity goes up. >> there are still plenty of factories in america. 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. automati if you go upstairs in that factory and lolot the payroll department, you see one or two people looking into a screen ale day. so, the actity is still there, but the number of jobs is very, very low, because of automation and tech progress. now, deali with that challenge, and figuring outge what the nexration of the american middle class should be doing, is a really important challenge, because i am pretty confident that we areav never again going tothis largrg stable, prosperous mile

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 fofoone of the w wld's largest builders of industrial robots, a japanese-owned company called fanuc robotics. >> we'e' been producing robots for well over 35 yearsrs and you can imagine, over the year o they've changed quite a bit. we're utilizing the arficialal intelligence to make thth robots easier to use and be able to hane a broader spectrum of opportunities. we see a huge growth pottial in robotic and we see that growth potentia as beially, there's 90% of the market left.nd >> narrator: thetry says optimistically that with that growth, they can create more jo. >> even if there were five people on a job, and we reduced that down to two people, because we automated somlevel

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. w so, althoureduce some of the people, we grow in other areas as we e oduce more things. >hen i increase productivity througtomation, i lose jobs. jobs go away. and i don't care what the robot manufacturers say, you aren't replacing those ten production people, , at that robot is now doing that job, with ten people. you can increase productivity to a level to stay competitive with they're trng to do. that's what ♪ po >> narrator: in the lar telling, blame for widespread job loss has been aimed >> we wantkeep our factories here, we wt to keep our manufacturing here.'t

we want them moving to china, to mexico, to jap, to india, to vinam. >> narrator: but it turns s t most of the job loss i't because of offshoring. >> there's been offshoring. and i think offshoring is jobs that have been lost. of the i would say most of the jobs that havavbeenost, 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 emi 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 by 15, ten to 15 percent.opped so, that's unusual in awo deloped. a one-year decline is a recession. a 15-year decline gives an entirely different sense about the prospects of a community.

and sohat 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 er from our suggestion drive that we did,to and we're go give them each two. >> that is awesome. >> i mean, that is going to go a mean, that'll really help that family out during the holidays.s >> y, well, with the kids home veom school, the families three meals a day that they got to put on the table. so, it's going to make a big. differen so, thank you, guys.om >> you're we >> t ts is wonderful. >> let them know merer christmas on behalf of us here at the local, okatm >> absolutely, you guys arest , 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 smama problem. the need is so great. and i can tell you that it's all races, it's all income classes y thatou might think someone might be from.ll but i can te you that when you y see it, and you deliver this type of gift to somebody who is

in need, just the gratitude thas they show yoncredible. w >> we actually kat people e at greater risk of mortalityr for over 20 years afey lose their job due to, due to fault of their own, so something like automation or offshong. ig they're atr risk for cacaiovascular disease, they're and suicide.sk for depression but then with the intergeneratnal 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, theyre likely to drop out of school, thth'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'r'rin thede early deof what is a multi-decade adjustment period. ♪

>> narrator: the world is being re-imagined. this is a supermarke robots, guided ba.i., pack everything from soap pder to nsumers.pes for online ck machines that pi groceries, machines that can also read reports, learn routines, and comprehend are reaching deep into factories, stores, and offices. at a college in goshen, indianab a group of lociness an political leaders come together to try to understand the impact of a.i. ananthe new machines. molly kinder studies the future of work at a washingen think >> how many people have gone into a fast-food restaurant and done a self-ordering? anyone, yes? panera, foinstance, is doing this.wa cashiemy first job, andd in, in, where i live, in washington, dc, it's actually the number-one occupation for the greater dc region. lethere are millions of peho

work in cashier positions. this is not a futuristichi chlenge,is something that's happeng sooner than we think. in the popular discussions about robots a automation and work, almost every image is of a man o on a factory floa truck driver. and yet, in our data, when we looked, women disprortionately hold the jobs that today are at highest risk of automation.hi and that's not really beingd talked about, at's in part because women are over- marginalizupationslike ahese o cashier or a fast-food worker. and also in a large numbers in clerical jobs in offices-- hr departments, payroll, financnc a lot of that is more routine processing information, prpressing paper, transferring data. that has huge potential for h automamaon. software, robots are gof that, some of that. so how many peanle are stillg

work switctcoard operators? probably none in this country.ra >> nr: the workplace of the future will demand different skills, and gaining them, says molly kinder, will depend on who can ford them.it >> i mea not a good situation in the united states. there's been some excellent research that says that half of americans couldn't afford a $40e uned expense. and d you want to get to a $1,000, there's even less.ma sone you're going to go out without a a nth's pay, two months' pay, a year. imagine you want to put savings toward a course to, to redevelop your c ceer. peopop can't'tfford to take titi off of work. they don't have a cushion, so this lack of e enomistability, married with the disruptions in people's careers, is a really toxic mix. >> (blowing whistle) >> narrator: the new machines wi penetrate every sector of the economy: from insurance companies to human resource departments; from m w firms to the trading floors of wall

street. >> wall street's going through goit, but every industry ig through it. every company is looking at all of the disruptive technologies, co robotics or drones or blockckcin. and whatever it is, every company's using everything that's developed, everything that's disruptive, in thinking t about, "how do i apply t 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 likekehood that you won't be o advance from where your parents were, i think that's, that's, is very rious and gets to think of america asandlike of opportututy. >> nartor: inequality has been rising in america. it used to be the top 1% ofer ea- here in red-- owned a relatively small portion of the

countrs wealth. middle and lower earners-- in blue-- had the largest share. then, 15 years ago, the lines crossed.as and inequalityeen increasing ever since. >> there's many factors that are driving inequality today, and unfortunately, artrticialig intece-- without being driver for increased inequality because it's a form of automation, and automation is the susutitution 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 capapalnd labor, and with artificial intelligence, we're putting our fieng on the scale on the s of capital, and how we wish to distribute the benefitit the economic benefs, 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 gettg wealthier, the poor getting poorer. related to a.i., but aally but a.i. will exacerbate that.d at, i think, will tear the society apart, because the rich ndwill have just too mucuc those who are have-nots willps have perery little way of digging themselves out of the hole. and with a.i. making its impacte it, it'lorse, i think. ♪ (crowd cheering and applauding) >> (speaking on p.a.) i'm here tay for one main reason. to say thank you to ohio. (crowd cheering and applplding)

>> i think the t tmp vote was a protest. i mean that for whatever reason, whatever the hot button wasat that, you know, eally hihi home with these americans who voted for him were, it was a protest vo. they didn't like t t 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 wedo gonn now i've got a group of people at the top that armaking all the money and i don't have anybody in the middle that can support a fafaly. so do we have to go to the point where we crash to comeack? 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 huly successful tech companies. they're constantly buying up successful smaller companies and recruiting talen between the u.s. and china, them employ a greority of the leading a.i. researchers and ientists. in the coursof a assing such power, they've also become among the richest companies in the wowod.al >> a.i. is the ultimate tool of wealth creation. think about the massive data that, you knkn, facebook has on user preferences, and how it can very smartly target an ad that you might buy sobuthing and get a much bigger cut that a smaller company couldn't do.an

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 i objective functitially will simply be, make more money. >> narrator: and it is how these companies make that t ney, and how their algorithms reach deeper and deeper into our work ily lives, and our democracy, that makes manyre people iingly uncomfortable. pedro domingos wrote the book "the master algorithm." >> everywhere you go, you generate a cloud of data.ra you'reing data, everything that you do is producing data. looking at that data that are learning, and these computers are essentially trying to o rve you better. they're trying to rsonalize things to you. they're trying to adapt the world to you. so on the one nd, this is great, because the world will get adapteteto you without you

even having to expliciy adapt it. there's also a danger, because the entities in the compmpies that are in control of those algorithms don't necessarily have the same goals as you, and this is where i think people w neededo be aware that'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.t we thought t were searching google. we had no idea that t ogle w searching us. >> narrator: shoshana zuboff is a harvard business schl professor emerita. in 1988, she wrote a definitivee book c"in the age of the smart machine." for the last sev years, she has worked on a new book, making the case that we have now h entered a new phase of the economy, which she calls "surveillance capitalism." >> so, famously, industrial capitalism claimed natur

innocent rivers, and meadows, and forests, and so forth, for the market dynamic to be reborn as reaeaestate, as land that could be sold and purchased. industrial capitalism claimed work for the market namic to reborn, to be reborn as labor that could be sold and purchased. pitatasm, following thisance pattern, but with a dark and startling twist. what surveillance capitalism claims is private, human experience. private, human expernce is claimed as a free source of raw material, fabricated into prictions of human behavio and it turns out that there are a lot of businesses that really want to know what we will do now, soon, a later.

>> narrator: like most people, alastair mactataart had know idea abt this new surveillance business, until one evening in 2015.ss >> had a conversation with a fellow who'sn engineer, and i was just talking to him one, night at a, you kndinner, at a cocktail party.y. and i... there had been something in the press that y about privacy in the paper, and i remember asking him-- he worked for google-- "what's the big dede about all, why are u people so workabout it?" and i thought it was gonna be one of those conversations, like, with, you kn, if you ever ask an airline pilot, "should i be worried about flying?", and they say, "oh, tho dangerous part is coming to the e rport, you know, in the car." and he said, "ohyou'd be horrified if you knew how much d i remember that kind of stuck in my head, because it was not what i expected. e >> narrator: that question would change his life. a successful california realop estate dev, mactaggart began researching the

new businessodel. >> what i've learned since is that their entire business is learning as much about you as they can. everything about your thoughts, and yoyo dires, and your dreamsmsand who your friends 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 herwn research. >> you know, i'd been readingad and reading and g. from patents, to transcripts of earnings calls, research reports. and,d,ou know, just literally everything, for years and years and years. >> narrator: her studies included the early days of google, stted in 1998 by two rgey brin and larry page.nts, in the beginning, they had no clear business model. on't be evil."al motto was,

>> right from the start, the founrs, larry page and serge brin, they had been very public about their antipathy toward advertising. advertising would distort the internet and it wod distort and ure the, the purity e, any search engncluding their own. >> once inove with e-commerce, wall s seet 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 googlglhad rapidlbecome the defau search engine for tens of millions of users, their investors were pressuring them to make more money. without a new busine model, the founders knew that the young company was in danger. nc>> in this state of emer

the founders decided, "we've simply got to find a way to save this company." and so, parallel to this were other set of discoveries, where it turns out turt whenevev we search or whenevewe b bwse, wee leaving behind traces- digital traces-- of our behavior. ck and those traces, n these days, were called digital exhaust.he >> narrator: trealized how valuable this data could be by applying machine learningms algoritho predict users' interests.us >> what happened was, they decided to turn to those data d gs in a systematic way, begin to use these surplus data as a way to come up with fine-grained predictionsf whatat a user would click on, what kind of ad a user would click on.

and inside googl they started seeing these revenues pile up at a startling rate. they realized that they had to keep it secret. they didn't want aone to know how much money they were making, or howowhey wewe making it. because users had no idea that these extra-behavioral data that told so much about them, you know, was s st o o there, and now it was being used to predi their future. >> narrator: when google's i.p.o. took place just a few years later, the company had a market capitalizizn of around $23 billion. s googleck 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 linenencreased by

3,590%. >> let's talk a little about ininrmation, and search, and how ople consusu it. >> narrator: by 2010, the c.e.ol of g eric schmidt, would tell "the atlantic" magazine... >> ...is, weon'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? >> narartor: eric schmidt and google declined toe interviewed for this program. google's new business model for predicting users' profiles had migrated to other companies, particularly facebook. roger mcnamee was an e ely investor and adviser to facebook. he's now a critic, and wrote a book about the company. he says he's concerned about how dely companies like facebook and google have been casting the net for data. r >> and then lized, "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." ssey go to health and well apps and say, "hey, you got women's menstrual cycles? we want all that stuff." why are they doing that? they're doing thatecau behavioral prediction is about taki uncertainty out of life advertising and marketing are all about uncertainty-- you never really know o's going to buy your product. until now. weave to recognize that we gave technology a place in our lives thth it had not earned. at essentially, because tenology always made thing better in the '50s, '60s, '70s, '80s, and '90s, we developed a sense of inevitability that t will always make things beer. we developed a trust, and the industry earned good will that

facebook and google have cashed in. >> nrator: the model is simp this: provide a free service-- like facebook-- and in exchange, you collect the data of the millions who use it. ♪ is valuable.iver of information >> 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 late" or, "i'll see you at 6:45." it'sot just that you talk about the things that you have to do day. it's whether you simply rattle them on in a, in a ramblin paragrh, or list them asli bullet points. all these tiny signals are the behavior surplus that turns out to have immense predictive value.

experimented with a.i.'sce predictive powers in wt 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. c veland, i need you to keep on fighting. i need you tkeep on believing. >> narrator: they offered 6161 million ers 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 c "massitagion" experiments. among them, one showing that by adjusting their feeds, they could ke users happy or sapy >> when they went to write up ese findings, they boast

about two things. one was, "oh, my goodness. now we know that we can use cues in the online environment to change real-world havior. that's big news." the second thing thathey undetood, and they celebrate was that, "we can do this s a way that bypasses the users' awareness." >> private corporationhave built a corporate surveillance state without our aweness or permission.d e systems necessary to make it work are getting a lot betterspecifically with what are known as internet of things, smarappliances, you ow, powered by the alexa voice recognition system, or the google home system. >> okay, google, play thee morning playlist. >> okay, playing morning playlist.y, ♪

>> okay, google, plalamusic in all rooms. ♪ >> and those will put ththth surveillance in places we've never had it befefe-- living rooms, kitchen 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, rn on the fan. (fan clicks on)>> kay. >> narrator: meanwhile, they are researching and applplngngor patents to expand their reach into homes and lives. >> alexa, take a video. (cera chirps) >> the more and more that you use spoken interfaces-- so srt speakers-- they're being trained not just to recognize who you are, but they're starting to changes over time. comparing asso does your cadence incor decrease? e 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, rhaps, 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 fo tonight? >> currently, pasadena, it's 58egrees 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 onin mate, detailed understanding ofofersonalities. so this isrecisely what

cambridge analytica did, simplye pivoting from the isers totc the political es. >> narrator: the cambrid analica scandal of 2018 engulfed facebook, forcing mark zuckerberg to appear before cocoress to explain how the data of up to 87 million facebook users had been harvested by a based in the u.k.ing company the purpose was to tget and nipulate voters s the 2016 presential campaign, as well as the bret referendum. largely funded by conservative hedge fund billionaire robert mercer. >> and now we know that any y,llionaire with enough mo who can buy the data, buy e mache intelligence capabilities, buy the skilled data scientists, you know,hey too can commandeer the public,

and infect and infiltratand upend our democracy with the same methodologies thatha survrvllance capitalism uses every single day. >> we didn't take a broad enough view of our responsibility, ands at was a bigke. 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 hasuspended tens of thousands of third-partt apps froplatform 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. ititas really, in some ways, old-school, first-wave data scieiee.wh we're looking at now, with current tools and machine learning, is that the abity of elections and opinions, buts more broadad, just how information travels, that is a much bigger problem, and certainly much more serious than w wt we faced with cambridge analytica. >> narrato a.i. pioneer yoshua bengio also has concernsbout hohohis algorithms are being used. >> so the a.is. are tools. and they will serve the people who control those tools. if those people's interests go against the, the values s democrac then democracy is in daer. who contribute to science, when that science can or will have an

impact on society, those scientists have are onsibility. it's a little bit like the physicists of, around the send world war, who rose up to tell the governments, "wait, nuclear power can be dangerous and nuclear war can be really, really destructive." antoday, the equivalent of ays ist of the '40s and '50s and '60s are, are the computerre scientists whooing machine learning and a.i ♪ >> narrator: one person who wanted to doomething about the dangers was not a computer scientist, but an ordinary citizen. alastair mactaggart t s alarmed. >> voting is, for me, the mostal ming one. if less than 100,000 votes separated the lastwo candidates in the laste 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 h hdfulf states to either come out and vote or stay home. anremember, these companie know everybody intimately. they know who's a racist, who's misogynist, who's a homophobe, who's a conspiracy theorist. they know the lazy people and the gullible people. they have access to the greast trove of personal information that's ever been assembled. they have the world's best data scientists. d they have essentially frnttionless way of communicating with you. this is power. >> narrator: mactaggart started a signature drive for a californrn 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 of silicon valley.the goliaths google, facebook, at&t, and comct all opposed his initiative. >> i'll tell you, i was scared. fear. fear of looking like a world- class idiot.as the market cap oall the firms

arrayed against me were, wastr over $lion. >> narrator: he needed 500,000 signatures to get his initiative got well over 600,000. polls showed 80% approval for a privacy law. that made the politicians inacramento pay attention. so mactaggart decided that because he w holding a strong hand, it was worth negotiating with them. >> and if ab-375 passes by tomorrow and is signed into w by the governor we will withdraw the initiative. our deadline to do so is narrator: at the very last moment, a new law was rushed to the floor r the state house. >> everyone take their seats please.le mr. secretary,e call the roll. v >> ting starts. >> alan, i. t >> a first guy, i think, was a republican, and he voted for it. and everybody had said t t f republicans won't vo it because it has this private right of action, where consumers can sue.

ed the guy in the senate, calls the name. >> i, roth. i, stern.r. i, stone. >> you can see down below, and passed u unimously., and then it >> "i's" 36, "no" zero, ss the measure . >> so i was blown awayto the... it was, it was a day i will never forget. so in january, nexexyear, you as a california resident will have the right to go to any company and say, "what have youc cod 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. no. second is the right to and that's the right to go to any company and click a button, on any pere they're collecting your information, and say, "do not sell my information."ta more imply, we require d-party opt-out.t.at's called ah you will click once in your browser, "don't sell my information," and it will then

send the signal to every single website that yououis: "don't sell this person's information. and that's gonna havge impact on the spread of your information across the internet >> narrator: the tmpanies had been publicly cautious, but regulation.larmed d out then one tech giant came onrt board in supf mactaggart's efforts. >> i find the reaction among other tech companies to, at this point, be pretty much all over the place. right to raise this.ng, "you're these are goododdeas." some people say, "we're not sure these are good ideas, but you're right to raise it," and some peoplere saying, "we don't't want regulation." and so, you know, we have conversations with people where we point out that thauto industry is bettererecausehe are safety standards. pharmaceuticals, even food products, all of thesebe induries are betteuse the public has confidence in the products, in part because of a mixture ofesponsible companies

and responsible regulation. >> narrator: but the lobbyists for big tech have been working the corridors in washington. they're looking for a morema lenient national privacyrd stanone that could perhaps hers like it.california law and but while hearings are held, and ti-trust legislati threatened, the problem is that ari. has already spread so into our lives and work. well, it's in healthcare,n, criminal jusce, it's in the experience of shopping as you walk down the street. it has pervaded so many elements of eryday life, and in a way that, in many cases, is completely opaque people. while we can see a phone and look at it and we know that there's some a.i. technogy behind it, many of us dodot know that when we go for a job interview and we sit dfoand we hafo 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 assessmental rithms that are deciding your "risk number," which could determine ether or not you recee bail or not. these are systems which, in many cases,re hidden in the back end of our sort of social institutions.he and so, one of tig challenges we have is, how do we make that more apparent? d how do we make itranarart? accoununble? >> for a very long time, we have felt like as hums, as in determining our own futures-- what we read, what we see, we're in charge. auwhat cambridge analyticat teach us, is that we don'tnues have agency. we're not in charge. this is machines that are automating somof our skills, but have made decisions about who... who we are. and they're using that

information to tell others the story y us. ♪ >> narrator: in china, in the age of a.i., there's no doubt about who is in char. in an authoritarian state, social stabity is theso watchword of the government. (whistle blo) and artifial intelligence has increased its ability to sn the country for signs of unrest. (whistle blowing it's been projected that over 600 million cameras will be ployed by 2020.us here, they may b to discourage jaywalking. but they also serve to remind people that the state is watching. p

>> and now, there isject 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 algorithm, which they e actually use this data, face or pick up a action. ♪ >> narrator: frequent security expos feature companies like 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 plala is just filled with these screens where you can see the compute actually readininpeople's faces and trying to digest that data, anda cally track and idenenfy who each person is. and it's incredible toee so many, because just two othree years ago, we hardly saw that

kind of thing. so, a big part of it is d so the technology's really taken off, and a lot of companies have started to sort of glom onto thiidea that this is the future. >> china is on its way to building a totalalurveillance state. >> narrator: and this is the test lab for the surveillance state. here, in the farorthwest of china, is ththautonomous region of xinjiang. of the 25 million people who live h he, almost half are a muslim turkic speaking people called the uighurs. (people shouting in 2009, tensisis with local han chinese led to protests and then riots in the capital, urumqi. (pg)ple shouting, guns firin (people shouting) as the conflict has grown, the c authorities have brought in more police, and deployed extenve

surveillance technology. that da feeds an a.i. system that the government claims can predict individuals prone to"t rorism" and detect those in need of "re-education" i ice scores of ly built camps. it is a campaign that has alarmed human rights groups. thout any legal basis,re, arbitrarily detaining up to ams million turkic musimply on but even outside the facilities in which these people are beinga held, most of the poon 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 sohe kinds of behavior that's now being monitored-- 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 usedo decide whether people should be subjected to polital 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 uigigr is impossible bothut inside andde 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 youin ououif 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, ro wyer and a pminent uighur activist, addresses a demonstration in washington, dc.

many among the uighur diasporaal have lost contact with their families back home. rkel warns that this dystopian dedeoyment of new tetenology isr a demoion project for authoritarian regimes around the world. >> they have a bar codes in somebody's home doors to o identify what kicitizen 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 y,its methods, its technolt is... to other countries, namely pakistan, venezuela, sudan, and others to utilize, to squelch litical resentment or prevent a political upheaval in their various societets. ♪ >> 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 f beyond. it's called "the belt and road initiative."." >> so effectively what the belt to, via spending and ient,empt project its influence all over the world. and we've seen, you know, massive infrastructure projects going in in places likean pakiin, in venezuela, in ecuador, in bolivia-- you know, all over the world, argentina, in america's bkyard, in africa. africa's been a huge place. and what the belt and ro ultimately does is, it attempts to kind of create a political leverage for the chinese spending campaign all over thehe globe. >> narrator: like xi jinping's 2018 visit to senegal, where chinese contctors had just built a new stadium, arranged los for a new infrastrucuc development, and, said the foreign ministry, therwould be help "maintaing 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 osurveillance systems. not the kind of high-level a.i. stuff yet, but, you know, lower- level, cama-based, you know, manual sort of obsvation-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 they say, "you know, by the way, we can ge 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 o ki you know, a main center where you have police who can watch these cameras." and that's going in all over the rld already. ♪ >> there are 5 5countries thato are startingug in to china's vision of artificialen intell. which means effectively that ina is in the process of

raising a bamboo curtain. one that does not need to... one that is sortf all- encompassing, th has shared resources, shared telecommunications systems, shared infrastructe, shared digital systems-- even shared mobile-phone technologies-- that is, that is quickly going up all around the wod totohe exclusion of us in the west. >> well, one of the things i worry about the most is that the wondd is gonna split in two, that there w wl be a chinese tech sector and there will be an erican 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 alignith the soviet union or are we gonna align with the united states?" d the third world gets t t choosehis or that. and that's not a world that's good f anybody. i >> the markeasia and then u.s. falling sharply on news that a top chinese executive has been arrested in canada.

she isfo of the chineseg.he telecom huawei. >> narrator: news of therr dramatic at of an portant about the company doing business with iran. e but it seemed to bmore about american distrust of the company's technology. from its headquarters in ok like fanciful european to capitals-- huawei is the second- biggest seller of smartphones, and thworld leader in building 5g networks, the high-speeig backbone for the age of a.i. officer in the people'ser liberation army, was defiant about the american actions. ranslated): thers 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

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 thorities are not convinced. >> nothing in china exists free and clear of the party-state.th e coanies can only exist and prosper at the sufferance of e party. and it's made very explicit that when the party needs them, they either h respond or they will be dethroned. so this is the challenge with a company like huauai. so huawei, ren zhengfei, the head ohuawei, , c say, "well, we... w wre just a private company anwe just... we don't t te orders from thth

communist party." ll, maybe they haven't yet. but what theheentagon sees, thet nationalntelligence council sees, and what the fbi sees is, "well, maybe not yet." but when the call comes,er company's response will be. >> narrator: the u.s. commerce department has recently blacklisteeight companies for doing business with government agencies in xinjiang, claiming they are aiding in the "repression" of the muslim minority. amamg the companies is megvii. they have stroroly objected to the blacklist, saying that it's "a misunderstanding of o company and our technology." ♪ president xi has increased his thoritarian grip on the country. in 2018, he had the chinese constitution changed so that he

could be president for life. >> if you had asd me 20 years ago, "what will happen to over time, the great fld, "well, will break down. of course, people will get aclss to social media, they get access to google... eventually, it'll become a much more democratic place, with western values."and lots of and the last time i checked, that has not happened. in fact, technology's become a tool of control. this amazing period of growth and wealth and openness in certain ways, there has not been the democratic transformation that i thought.ou and it may turthat, in fact, technology is a better tool for authoritarian governments than it is for democratic governments. >> narrator: to dominate thehe world in a.i., president xi is depending on chinese tech to lead the way. while companies like baidu, alibaba, and tencent are g gwing

more powerful and competive, theye also beginning to have difficulty accessing american technology, and are racing to develop their own. with a continuing trade r and growing distrust, the longtime argument for engagement between the two countries hasen beosing ground. >> i've seen more and more of my collgues move from aositio when they y ought, "well, if we just keep gaging china, the lines between the two countries will slowly converge."et you know, r it's in economics, technology, politicic and the transformation, where diverging.hinknkhey're so, in other words, the whole i idea of engagemecoming and that's cast an entirely different lighon technology,

because if you're diverging and you're h hding into a world of antagonism-- you know, conflict, possibly, en 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 n n, which is what is casting the whole question of things like artificial intelligence and technological innovation into a completely different framewo, is that if in fact china and the u.s. are in me 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 i power, the woralready dominated by just two a.i.rp suers.

that's the premise of a new book written by k-fu lee. >> hi, i'm kai-fu. >> hi, dr. lee, so nice to meet you. >> really nice to meet you. lookt alalthese dog ears. i love, i love that. >> you like that? >> but i... but i don't like yoy didn'the book, you... you boboowed it. >> i couldn't find it! >> oh, really? >> yeah! >> and, and you... you're cominm toy talk? >> of course! >> oh, hi. >> i did my homework, i'm >> oh, my goodness, thank you. laurie, can you get this gentleman a book? (people talking in background)d) life, the computers book and in scientist-cum-venture a capitalist walksareful path. criticism of the chinese government is avoided, while capitalist success is celebrated. >> i'm studying electrical engineerin >> sure, send me a resume. >> narrator: now, with t of the two superpowers, he wants to warn the world of what's coming. >> are you the new leaders? >> if we're nothe new leaders,

we're pretty close.gh (lau thank yovery much. >> thanks. >> narrator: "never," he writes, "has the potential for humanig flourishing beenr or the stakes of failure greate" ♪ >> so if one has to say who' is quickly catching upay, china china actually began its bigy push in a.i. oo-and-a-half yees ago, when the alphago- sedol match became the sputnik moment. h >> narrator: he sabelieves that the two a.i. superpowers should lead the way and work a together to ma. a force we do, we may have a chance of getting it right. >> if we do a very good d b the next 20 years, a.i. will be viewededs an age of enlighteent. our children and their children will see a.i. as serendipipi. thatat. is here to liberate us om having to do routine jobs,

and push us to do what we love, and push us to think what it means to be human.ha >> narrator: butif humans mishandle this new power?ds kai-fu lee understhe stakes. after all, he invested earlys in megvii, whichw the u.s. blacklist. he says he rededed his stake and doesn't speafor the company. asked about the governnt using a.i. for social control, he chose his wordng carefully. >> um... a.i. is a technology that can be used for good and for evil.er limit themselves in, on thone hand, using this a.i. technology and the database to maintain a e saironment for its citizens, but, but not encroroh on a individual's righ and

privacies? that, i think, is also a tricky issue, i think, for, for every country.i ink for... i think every country will be tempted to usend a.i. probably behe limits to which thahayou and i would like the government to use. ♪ >> narrator: emperor yao devised discipline, concentratndhis son 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 goalof building a better society, unfortunately.

but, but we could change that. >> narrator: in 2016, a game of go gave us a glimpse of the fure of artificial intelligence. since thenenit has become clear that we will need a careful strategy to harness this new and awesome power. >> i, i do think that democracye is threaby the progress ofof these tools unless we improveci our norms and we increase the collective wisdom at the planet le tl to, to deal with that increased power. i'm hoping that my concerns are s not founded, but the staeth so hig i don't think we should take these concerns lightly. i don't think k can play withil those possies and just... race ahead without thinking

about the potential outcomes. ♪ >> go to pbs.org/frontline forim more of the 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 wh bias, with discrimination, with poor system design, with errors.>> onnect to the frontline communy on facebook and twitter, and watch anytime on the pbs video app or pbs.org/frontline. >> narrator: the mass detentione migrant childn... >> they put me in the cage. younger minors.nd 12 other it was like a stadium, but with cages and that's where they kept all the people. >> narrator: who's profiting? >> isn't there an incentive to detain kids?pr >> there is e incentive, but it's not a detention

incentive. >> narrator: and at at cost? >> if this is a deterrence, the price is way too high. >> narrator: frontline and the associated press investigate. >> frontline is made p psible bi cotions to your pbs station from viewers like you. thank you. major suppppt is provided by the john d. anancatherine t. macarthur foundation, committed to building a moreust, verdant and peaceful world. the ford foundation:es working with visionan the frontlines of social changein worldwide.pradditional support d by the abrams foundation, committed to excellence in jonalism. the park foundation, dedicated to heightening public awareness of critical issu. the john and helen glessner family trust.ti supp trustworthy journalism that informs and inspires. and by the frontline e urnalism fund, s with majport from jon and jo ann hagler. and additional support from m stair and lucy caldwell-stair. major support for frontline andf

"in the agi" is provided by the corporation for public broadcasting. captned by memea accessroup at wgbh access.wgbh.org >> 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 1-800-play-pbs. this program is also available on amazon prime video. ♪ ♪

you're watching pbs. ♪ christiane: can you tell us what ♪ fire before us. ♪ you're the brightest. judy: turning back now to the race for the white house. ♪ you will lead us through the storms. ♪ robert: the state board of the race for election votede. thursday to set up a new election. christiane: it must be a very otional day. ♪ i will trust the promise. man: he world changed in the. yamiche: children are at the het of this story. ♪ safe to shore. c ♪ safe to shore.

(singing in foreign language) - we always long for how it used to be when we were growi up. we'd use cardboard for homemade sleds. we were poor, but we didn't know we were poor, you know. - back then people used to visit and we'd play outside, we didn't have such a thing as tv, we ayed outside.