>> narrator: tonight-- >> the race to become an ai >> narrator: the polits of artificial intelligence... c >> there will be anese tech sector and there will be a american tech sector. >> narrator: the new tech war. >> the more data, the tter the ai works. so in the age of ai, where data the new oil, china is the new saudi arabia.ur >> narrator: thee of work... >> when i increase productivity through automation. jobs go away. will be somewhat or exy jobs threatened by ai in the next 15 years or so. >> narrator: ai and corporate surveillance... >> we thought that we were searching google. we had no idea that google was

searching us. >> narrator: and the threat to democracy. >> china is on its way to state.ng a total surveillance >> narrator: tonight on frontline-- >> it has pervaded so many elements of everyday life. how do we make it transparent >> narrator: "in the age of ai". >> frontline is made possible by contributions to your pbs station from viewers like you. thank you. major support is provided by the john d. and catherine t.fo macarthudation, committed to building a more just, verdant and peaceful world. the ford foundation:rk g with visionaries on the frontlines of social change worldwide.di onal support is provided by the abrams foundation, committed to excellence in. journali the park foundion, dedicated to heightening public awarens of critical issues. the john and helen glessner family trust. supporting trustworthy journalism that informs and inspires. and by t frontline journalism fund, with major support from jon and

jo ann hagler. and additional support fromr tom std lucy caldwell-stair. major support for frontline and, "in the age of ai" is provided by the corporation for public badcasting. ♪ >> narrator: this is the world'o complex board game. there are more possible moves in the game of go than there are t atoms universe. legend has it that in 2300 bce, emperor yao devised it to teach s son discipline, concentration, and balance. this ancient chinese game would

industrial age.t of a new ♪ it was 2016, in seoul, sth korea. >> can machines overtake human intelligence? a breakthrough moment when the wod champion of the asian board me go takes on an a.i. program developed by google. >> (speakingorean): un >> in coies where it's very popular, like china and japan and, and south korea, to them, go is not just a game, right? it's, like, how you learn strategy. it has an almost spiritual component. k you know, if you tto south koreans, right, and lee sedol is the world's greatest go player, he's a national hero i south korea.re

they were hat lee sedol would beat alphago hands down. ♪ >> narrator: google's alphago was a computer program that, starting with the rules of goa antabase of historical games, had been designed to. teach itse >> i was one of the commentators at the lee sedol games. and yes, it was watched by tens of millions of people. (man speaking korean) >> narrator: throughout southeast asia, this was seen a orts spectacle with national pride at stake. >> wow, th was a player guess. >> narrator: but much more was in play. this was the public unveiling of a form of artificialce intelligalled deep learning, that mimics the t neural networks human brain. >> so what happens with machine learning, or aificial intelligence-- initially with t alphago-- t the machine is fed all kinds of go games, and then it studies them, learns

from them, and figures out its own moves. and because it's an a.i. system--t's not just following instructions, it's figuring out its own instructions-- it comes up with moves that humans hadn't thought of before. so, it studiesames that humans have played, it knows the rules, and thent comes up with creative moves. (woman speaking korean) (speaking korean): >> that's a very, that's a very surprising move. >> i thought it was a mistake. >> narrator: game two, move 37. >> that move 37 was a move that humans could not fathom, but yee ed up being brilliant and woke people up to say, "wow, after thousands of years of plting, we never thought ab making a move like that." gn >> oh, he re. it looks like... lee sedol has just resigne actually. >> yeah!

>> yes. >> narrator: in the end, theat scientistsed their algorithms win four of the games. lee sedol took one. >> what happened with go, first and foremost, was a hugean victory for deep minfor a.i., right? it wasn't that the computers h beat tans, it was that, you know, one type of intelligence beat another. >> narrator: artificial intelligence had proven it could marshal a vast amount data, beyond anything any human could handle, anusit to teach itself how to predict an outcome. the commercial implications were enormous. >> while alphago is a, is a toy game, but its success and its waki everyone up, i think, is, is going to be remembered as the pivol moment where a.i. became mature and everybody jumped on the bandwagon. ♪ >> narrator: this is about the consequencesf that defeat.

(man speaking local language) how the a.i. algorithms arene ushering iw age of great potential and prosperity, but an age that will also deepen inequality, challenge democracy, and divide the world into two a.i. superpowers. tonight, five stories about how artificial intelligence is changing our world. ♪ china has decided to chase the a.i. future. >> the difference beeen the internet mindset and the a.i. mindset... nd narrator: a future made >> well, it's hard noteltion. the kind of immense energy, andc also the obviousof the

demographics. ey e mostly very younger people, so that this clearly is technology which is being generated by a whole new generation. >> narrator: orville schell is one of america's foremost china scholars. >> (speaking mandarin) >> narrator: he first came here 45 years ago. >> when i, when i first came here, in 1975, chairman mao was still alive, the culturalon revolution was cominand there wasn't a single whiff of anything of what you see here. fact, in those years, one very much thought, "this is the way china is, this is the and the fact that it he through so many different changes since is quite extraordinary. (man giving instructions) >> narrar: this extraordinary progress goes back to that game of go.

>> i think that the government recognized that this was a sorti ofcal thing for the future, and, "we need to catch up in this," that, you know, "we cannot have a foreign company showing us up at our own game. and this is going to be somethinthat is going to be critically important in the future." so, you know, we called it the sputnik moment for, for the chinese government-- the chinese government kind of woke up. >> (translated): as we often say in china, "the beginning is the" most difficult par >> narrator: in 2017, xi jinping announced the government's boldu new plans to aence of foreign diplomats.d china wotch up with the u.s. in artificial intelligence by 2025 and lead the world by 2030. >> (translated): .and intensified cooperation in frontierreas such as digital economy, artificial inlligence, nanotechnology, and accounting computing. ♪ >> narrator: today, china leads

the world in e-commerce. drones deliver to rural villages. and a society that bypassed credit cards now shops in stores without cashiers, where the currency is facial recognition. >> no country has ever moved that fast. and in a sho two-and-a-half years, china's a.i. implementation really went from minimal amount to probably about 17 or 18 unicorns, that is billion-dollar companies, in a.i. tod. and that, that progress is, is hard to believe. >> narrator: the progress was powered by a new generation of ambitious young techs pouring out of chinese universities, competing with each other for new ideas, and financed by a new cadre of chinese venture capitalists. this is sinovation, created by

u.s.-educated a.i. scientist and businessman kai-fu lee. >> these unicorns-- we've got one, two, three, four, five, six, in the general a.i. area. and unicorn means a billion-dollar company, a company whose valuation or market capitalization is at $1 billion or higher. i think we put two unicorns to show $5 billion or higher. >> narrator: kai-fu lee was born in twan. his parents sent him to high school in tennessee.hi phd thesis at carnegie mellon was on computer speech m cognition, which took hi apple. >> well, reality is a stepos to science fiction, with apple computers' new developed program...ra >> nr: and at 31, an early measure of fame. >> kai-fu lee, the inventor of apple's speech-recognition technology >> casper, copy this to make writ2. casper, paste.

casper, 72-point italic outline. >> narrator: he would move on to microsoft research in asia and t beca head of google china. ten years ago, he startedon sinovan beijing, and began looking for promising startups and a.i. talent. >> so, the chinese entrepreneurial companies started as copycats. but over the last 15 years,it china has developeown form of entrepreneurship, and thatne entrepship is described as tenacious, very fast, winner-take-all, and incredible work ethic. i would say these, few thousand chinese top entrepreneurs, they could take reon any entrepreneur anywn the world. >> narrator: entrepreneurs like cao xudong, the 33-year-old c.e.o. of a new startup called momenta. this is a ring road around beijing.

the car is driving itself. ♪ >> you see, another cutting, another cutting-in. >> another cut-in, yeah, yeah. >> narrator: cao has no doubt about the inevitability of autonomous vehicles. >> just like alphago can beat the human player in, in go, ich think the maine will h definitely surpass tan driver, in the end. >> narrator: recently, there have been cautions about how soon autonomous vehicles will be are confident they're theteam long haul. >> u.s. will be the firsto deploy, but china may be the first to popularize. it is 50-50 right now. u.s. is ahead in technology. china has a larger marke and the chinese government i helping with infrastructure efforts, for example, buildingci

a ne the size of chicago with autonomous driving enabled, and also a new highway that has sensors built in to help v autonomoicle be safer. >> narrator: their earlycl investors ed mercedes-benz. >> i feel very lucky and vy inspiring and very exciting that we're living in this era ♪ >> narrator: life in china is largely conducted on smartphones. a billion people use wechat, the equivalent of facebook, messenger, and paypal, and much more, combined into just one super-app. and there are many more. >> china is the best place for a.i. implementation today, because the vast amount of data that's available in china. china has a lot more users than any other country,hree to four times more than the u.s. there are times more mobile payments than the u.s.

there arten times more food deliveries, which serve as data to lea more about user behavior than the u.s. 300 times more shared bicycle b rides, and each sharycle ride has all kinds of sensors submitting data up to the cloud. we're talking about maybe ten times more data than the u.s., and a.i. is basically run on data and fueled by data. the more data, the bter the a.i. works, more importantly thanow brilliant the researcher is working on the problem. data is the new oil, china is the new saudi arabia. >> narrator: and access to all that data means that the deep-learning algorithm can quickly edict behavior, like the creditworthiness of someone wanting a short-term loan. >> here is our application. and customer can choose how many money they want to borrow

and how long they want to borrow, and they can input their datas here. and after, after that, you can just borrow very quickly. >> narrator: the c.e.o. shows u how quickly you t a loan. >> it is, it has done.to >> nar it takes an average of eight seconds. >> it has passed to banks. >> wow. >> narrator: in the eight seconds, t algorithm has asseed 5,000 personal featur from all your data. >> 5,000 features that is related with the delinquency, when maybe the banks only use few, maybe, maybe ten featureswk amendment. >> narrator: processing millions of transactions, it'll dig up features that uld never be apparent to a human loan officer, like how confidently you type your loan application,

or, surprisingly, if you keeptt your cell phone baery charged. >> it's very interesting, the battery of the phone is related with their delinquency rate.mu someone who ha more lower battery, they get much more dangerous than others. >> it's probably unfathomable to an american how a country canse dramatically evolve from a copycat laggard to, all of a suddhe, to nearly as good as t u.s. in technology. >> narrator: like this facial-recognition startup he invested in. megvii was started by three young graduates in 2011. it's now a world leader in using a.i. to idtify people. >> it's pretty fast. r example, on the mobile device, we have timed the facial-recognition speed it's actually less than 100 milliseconds.

so, that's very, very fast. so 0.1 second that we can, we will be able to recognize e yon on a mobile device. >> narrator: the company claims the system is better than any human at identifying people inda itbase. and for those who aren't, it can describe them.wh like our director- he's wearing, and a good guess at his age, missing it by only a few months. >> we are the first one tofa really takal recogniti to commercial quality. >> narrator: that's why in beijing today, you can pay for your kfc with a smil >> you know, it's not sori sung, we've seen chinese companies catching up to the u.s. in technology for a long time. p and so, ticular effort and attention is paid in a specific sector, it's not sosi surp that they would surpass the rest of the world. and facial recognition is one of the, reallthe first places we've seen that start to happen.

>> narrator: it'a technology prized by the governnt, like this program in shenzhen to offenders are shamed in public-- instantly fined.s ognition, can criticrn that the government and some private companies have been buiing a national database from dozens of experimental social-creditms prog >> the government wants to integrate all these individual behaviors, or corporations' records, into some kind of metrics and compute out a single number or set of number associated wita individual, a citizen, and using that, to implement a incentive or punishment system. >> narrator: a high social-credit number can be rewarded with discounts on bus fares. a low number can lead to a

travel ban. some say it's ve popular with a chinese public that wants to punish bad behavior. others see a future that rewards party loyalty and silees criticism.th >> right now, e is no final system being implemented. and from those experiments, we already see that the possibility of what this social-credit syst can do to individual. it's very powerful-- orwellian-like-- and it's mstremely troublesome in t of civil liberty. >> narrator: every evening inre shanghai, evernt cameras record the crowds as they surged down to the bu, the promenade along the banks of the huangpu river. once the great trading houses of europe came here to do business with the middle kingdom.

in the last century, they were all shut down by mao's revolution. but now, in the age of a.i., people come here to take in a spectacle that reflects china'sp remarkabgress. (spectators gasp) and illuminates the great political paradox of capitalisma n root in the communist state. >> people have called it market leninism, authoritarian capitalism. we are watching a kind of a petri dish in which an experiment of, you know,ce extraordinary importo the world is being cried out. whether you can combine these things and get something that's more powerful, that's coherent, that'surable in the world.yo whethecan bring together a innovative sector, botn economically and technologicalli

inno, and that's something we thought could notoexist. >> narrator: as cha reinvents itself, it has set its sights on leading the world in ar0.ficial intelligence by 2 but that means taking on the world's most innovative a.i. culture. ♪ on an interstate in the u.s. southwest, artificial intelligence is at work solving the problem that's become emblematic of thnew age, replacing a human driver. ♪ i thisthe company's c.e.o., 24-year-old alex rodrigues. >> the more things we build

successfully, the less people ask questions about how old you are when you have rking trucks. >> narrator: and this is what he's built. commercial goods are being driven from california to arizona on interstate 10. but he's not driving.the cab, it's a path set by a c.e. with an unusual cv. the aim is to score the pucks into the scoring area. so i, i did competitive robotics starting when i was 11, and i took it very, very seriously. e, to, to give you a se won the robotics world championships for the first time when i was 13. i've been to worlds seven times betwn the ages of 13 and 20-ish. i eventually founded a team, did a lot of work at a very high competitive level. things looking pretty good. >> narrator: this was a prototype of sor, from which he has built his

multi-million-dollar company. >> i hadn't built a robot in a while, wanted to get back to it lt that this was by far the most exciting piece of robotics technology that was up. and comi a lot of people told us we wouldn't be able to build it. but knew roughly the techniques that you would use. and i was pretty confident that if you put them togetherwoyou d get something that worked. took the summer off, built in my parents' garage a golf cart that could drive itself. >> narrator: that golf cart got the attention of siliconva ey, and the first of several rounds of venture capital. he formed a team and then decided the business opportuni was in self-driving trucks. he says there's also a human benefit. >> iwe can build a truck that's ten times safer than a human driver, then not much else actually matters. when we talk to regulators, especially, everyone agrees that the only way that we're going to get to zero highway deaths, which is everyone's objective, is to use self-driving.

and so, i'm su you've heard the statistic, more than 90% of all crashes have a human drivers he cause. so if you want to solve traffic fatalities, which, in my opinion, are the single biggesth traged happens year after year in the united states, this is the only solution.ra >> narr: it's an ambitious goal, but only possible because of the recent breakthroughs in deep learning. >> artificial intelligence is one of those key pieces at has made it possible now to do sn't possible ten years ago, particularly in the ability to see and understand scenes. owa lot of people don't kn this, but it's remarkably hard for computers, until very, very recently, to do even the most basic visual tasks, like seeing a picture of a person and knowing that it's a person. and we've de gigantic strides with artificial intelligence in being able to see and understandintasks, and that's obviously fundamental to being

able to understand the world around you with the nsors that, that you have available. >> narrator: that's now possible because of the algorithms written by yoshua bengio and a small group of scientists. world which we can't explain the with words. and that part of our knowledgeab is actually pr the majority of it. so, like, thstuff we can communicate verbally is the tip of t iceberg. m and so to get at the bot the iceberg, the solution was, the computers have to acquire that knowledge by themselves from data, from examples. just like children learn, most not from their teachers, but from interacting with the world, and playing around, and, and trying things and seeing what works and what doesn't work. >> nrator: this is an early demonstration. in 2013, deep-mind scientists set a machine-learning program on the atari video game

breakout. the computer was only told the goal-- to win the game. after 100 games, it learned to use the bat at the bottom to hit the ball and break the brickat the top. after 300, it could dohat better than a human player. after 500 games, it came up with a creative way to win the ga-- by digging a tunnel on the siden and sethe ball around the top to break many bricks with one hit.ar that was deep ng. >> that's the a.i. program based on learning, really, that has been so successful in the last few years and has... you know, it wasn't clear ten years ago that it would work, the map and is now used inged almo every sector of society >> even the best and brightestus among us, wedon't have enough compute power inside of our heads.

>>arrator:my webb is a professor at n.y.u. and founder of the future today institute. >> as a.i. progresses, the great promise is that they... they, these, these machines, alongside of us, are able to think and imagine and see things in ways that we never have befor which means that maybe we have some kind of new, weird, seemingly implausible solution to climate change. maybe we have some radically different approach to dealing with incurable cancers. the real practical andonderful promise is that machines help us be more creati, and, using that creativity, we get to terrific solutions. >> nrator: solutions that could come unexpectedly to urgent problems. >> it's going to change the

ce of breast cancer. right now, 40,000 women in the u.s. alone die from breastry cancer eingle year. >> narrator: dr. connie lehman is head of the breast imaging center at massachusetts general hospital in boston >> we've become so complacent about it, we almost don't thinkc really be changed. we, we somehow think we should put all of our energy into chemotherapies to save women with metastatic breast cancer, and yet, you know, when we findy it ewe cure it, and we cure it without having the vages to the body when w 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.ha >> narrator: this is happened when a woman who had been diagnosed with breast cancer started to ask questions about why it couldt have been diagnosed earlier. >> it really brings a lot of anxiety, and you're asking the questions, you know, "am i gog to survive?

what's going to happen to my son?" and i start asking other questions. >> narrator: she was used to asking questions. at m.i.t.'sli artificial-intnce lab, professor regina barzilay useseep learning to teach the computer to understand language, as well as read text and data. >> i was really rprised that the very basic question that i ask my physicians,hich were really excellent physicians here at mgh, they couldn't give me answers that i was looking for. >> narrator: she was convinced that if you analyze enough data, from mammograms to diagnostic notes, the computer could predict early-stage conditions. >> if we fast-forward from 2012 to '13 to 2014, we then see whei rena was diagnosed, because of this spot on her mammogram. is it possible, with more elegant computer applications,

that we might have identified this spot the year before, or even back re? >> so, those are standard prediction problems in machine learning-- there is nothing special about them. and to my big surprise, none of the technologies that we are developing at m.i.t., even in the most simple form, doesn't penetrate the hospital. >> narrator: regina and connie began the slow process of gettinaccess to thousands of mammograms and records from mgh's breast-imaging program. >> so, our first foray was just toake all of the patients had at mgh during a period of time, who had had breast surgery for a certain type of high-risk lesi. and we found that most of them didn't really need the surgery. they didn't ve cancer.bu about ten percent did have cancer. with regina's techniques in deep learning and machine learning, we were able to predict the women that truly

needed the surgery and separate out those that really could avoid thunnecessary surgery. >> what machine can do, itanof take hundredhousands of images where the outcome is known and learn, based on how, you know, pixels are distributed, what are the very unique patterns that correlate highly with future occurrence of the disease. so, instead of using human t capacikind of recognize pattern, formalize pattern-- which is inherently limited by our cognitive capacity and how much we can see and rember-- we're providing machine with a lot of data and make it learn this prediction. >> so, we e using technology sessing the breast density, but to get more to the point of what we're trying to predict. "does this woman have a cancer now, and will she develop a cancer in five years?"

and that's, again, where the artificial intelligence, machine and deep learning can really help us and our patients.to >> narr: in the age of a.i.,th the algorims are transrting us into a iverse of vast tential and transforming almost every aspect of human endeavor and experience. andrew mcafee is a research scientist at m.i.t. who co-authored "the second machine age." >> the gat compliment that a g songwrites another one is, "gosh, i wish i had written that one." the great compliment a gk gives another one is, "wow, i wish i had drawn that graph." so, i wish i had drawn this graph. >> narrator: the graph uses a formula to show human development and growth since b 20. >> the state of human civilization is not veryad nced, and it's not getting better very quickly at all, ands this is true for tds and thousands of years. and empires got overturned, when we tried democracy, when we z

invento and mathematics and fundamental discoveries about the universe, big deal. it just, the numbers don't change very much. what's weird is that the numbers change essentially in the blink of an eye at one point in time.t anoes from really horizontal, unchanging, uninteresting, to, holy toledo, crazy vertical. d en the question is, what on earth happened to cause that change? and the answer is the industrial ere were other things that happened, but really what fundamentally happened is, weit overcame the lions of our muscle power. something equally interesting is happening right now. we are overcoming the limitations of our minds. we're not getting rid of them, we're not making them unnecessary, but, holy cow, can we leverage them and amplify them now. you have to be a hugpessimist not to find that profoundly good news. >> i really do think the world has entered a new era.fi aral intelligence holds so much promise, but it's going to

reshape every aspect of the economy, so many aspects of our lives. because a.i. is a little bitli electricity. everybody's going to use it. every company is going to be incorporating a.i., integrating it into what they do, governments are going to be using it, nonprofit organizations are going be using it. it's going to create all kindsit of benin ways large and small, and challenges for us, as well. >> narrator: the challenges, the benefits-- the autonomous truck represents both as it maneuvers into the marketplace. the engineers nfident that, in spite of questions about when this will happen, they can get it workinsafely sooner than most people realize. >> i think that you will see the first vehicles operating with no one inside them ving freight in the next few years, and then expanding to more freiat more geographies, more weather over time asas that capability builds up.

we're talking, like, less than half a decade. >> narrator: he already has a fortune 500 company as a client, shipping appliances across the southwest. raightforward.les pitch is >> they spend hundreds of llions of dollars a year shipping parts around the country. we can bring that cost half. and they're really excited to be able to start working with us, bothecause of the potential, the potential savings from deploying self-driving, and also because of all the operational efficiencies that they see, the biggest one being able to operate 24 hours a day. so, right now, human drivers are limited to 11 hours by federal law, and a driverless truck obviously wouldn't have that limitation. ♪ >> narrator: the idea of a driverless truck comes up often in discussions about aificial intelligence. steve viscelli is a sociologist

who drove a truck while researching his book "the big rig" about the industry. >> this is one of the most remarkable stories in, in u.s. ow, the decline of, of, is, you unionized trucking.eg the industry was dated in 1980, and at that time, you know, truck drivers were earning the equivalent of over $100,000 in today's dollars. and today the typical truck driver will earn a little over $40,000 a year. and i think it's an imrtant part of the automation story, right? why are they so afraid of automation? because we've had four decades of rising inequaty in wages. and if anybody is going to take it on the chin from automation in the trucking industry, the, the first in line is going to be the driver, without a doub >> 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.e >> to meet you, too, thanks. >> come on in. >> narrator: and their son charlie. >> this is daddy, me, daddy, and mommy. >> narrator: but daddy's not awn cumbee's truck has broken down in tennessee. hope, who drove a truck herself, knows the business well. >> we made $150,000, right, in a year. that sounds great, right? that's, like, good money.00 we paid 00 in fuel, okay? so, right there, now made $50,000. but i didn't really, because,t you know, you oil change every month, so that's $300 a month. you still have tdo all the maintenance. we had a motor blow out, right? $13,0. right? i know, i mean, i choke up a little just thinking about it, because it was...

and it was 13,000, and we were off work for two weeks. so, by t of the year, with that $150,000, by the end of the year, we'd made about 20... about $22,000. >> narrator: in a truck stop in tennessee, shawn has been sidelined waiting for a new part. the garage owner is letting him stay in the truck save money. >> hi, baby. >> (on phone): hey, how' itgoing? >> it's going. chunky-butt! >> hi, daddy!y- >> hi, chubutt. what're you doing? >> (talking inaudibly) >> believe ior not, i do it i mean, you know, it'se blood. third-generation driver. and my granddaddy told me a long time ago, when i was probably 11, 12 years old, probably, he said, "the world meets nobody halfway. nobody." he said, "if you want it, you have to earn it." and that's what i do every day. i live by that creed. and i've lived by that since

it was told to me. >> s if you're down for a we in a truck, you still have to pay your bills. i have enough money in my checking account at all times to pay a month's worth of bills. at doesn't include field trips for my son's school. my son and i just went to our yearly doctor appointment. i took, i took money out of my son's piggy bank to pay for it, because it's not... it's not scheduled in. it's, it's not something that you can, you know, afford. i mean, like, when... (sighs): sorry. >> it's okay. ♪ al have you guys everd about self-driving trucks? is he... >> (laughing): so, kind of. um, i asked him once, you know. and he laughed so hard. he said, "no way will they ever have a truck that can drive itself."

>> it's kind of interesting when you think about it, you know, they're putting l this new technology into things, but, you know, it's still man-made. anman, you know, does make mistakes. i really don't see it being a problem with the industry, 'cause, one, you still got to have a driver in it, because i don't see it doing city. i don't seit doing, you know, main things. i don't see it backing into a dock. i don't see the automation part, you know, doing... maybe the box-trailer side, yoknow, i can see that, but not stuff like i do. so, i ain't really worried abouc the automation of . >> how near of a future is it? ..>> yeah, self-driving, u so, some, you know, some companies are already operating. embark, for instance, is one that has been doing driverless trucks on the interstate. and what's called exit-to-exitvi self-d. and they're currently running real freight. >> really? >> yeah, on i-10. ♪ >> (on p.a.): shower guest 100,

your shower is now ready.ve >> narrator: or time, it has become harder anharder for veteran independent drivers like the cumbees to make a living. they've been replaced by younger, less experienced drivers. >> so, the, the trucking industry's $740 billion a year, operations, labor's a y of these of that cost. w,by my estimate, i, you k think we're in the range of 300,000 or so jobs in the foreseeable future that coul be automated to some significant extent. ♪ >> (groans) ♪ >> narrator: the a.i. future was built with great optimism out re in the west. in 2018, many of the people who invented it gathered in san

francisco to celebrate the 25th anniversary of the industry magazine. >> howdy, welcome to wired25. >> narrator: it is a celebration, for sure, but there's also a growing sense of caution and even skepticism. >> we're having a really good weekend here. >> nartor: nick thompson is editor-in-chief of "wired."rt >> when it s, it was very much a magazine about what'snd cominghy you should be excited about it. optimism was the defining feature of "wired" for many, many years. s or, as ogan used to be, "change is good." and er time, it shifted a little bit. and now it's more, "we love some of the big issues, andat let's look at some of them critically, and let's look at thgway algorithms are chang the way we behave, for good and for ill."e so, ole nature of "wired" has gone from a champion of t technological chanmore

of a observer of technological change. >> so, um, before we start... >> narrator: there are 25 speakers, all named as icons of the last 25 years of technological progress. >> so, why is apple so secretive? >> (chuckling) >> narrator: jony ive, who designed apple's iphone. >> it would be bizarre not to be.ti >> there's this qu of, like, what are we doing heren this life, in this reality? >> narrator: jaron lanier, who pioneered virtual reality. and jeff bezos, the founder of amazon. rt>> amazon was a garage s. now it's a very large company. two kids in a dorm... >> narrator: his message is, "all will be well in the new world." >> i guess, first of all, i remain incredibly optimist about technology, and technologies always are two-sided. but that's not new. that's always been the case.an and we will figure it out. the last thing we would ever want to do is stop the pgress of new technologies, even when

they are dual-use. >> narrator: but, says thompson, beneath the surface, there's aem worry most of on't like to talk about. >> there are some people in tsilicon valley who beliet, "you just have to trust the technology. throughout history, there's been a complicad relationship between humans and machines, we've always worried about maches, and it's always been fine. and we don't know how a.i. will change the labor force, but it so, that argument exists. there's another argument, which is what i think most of theme beliep down, which is, 're going to have labor-force disruption like we've never seen and if that happens, will they blame us?" >> narrator: there is, however, one of the wired25 icons willing to take on the issue. onstage, kai-fu lee dispenses with one common fear. >> well, i think there are so many myths out there. i think one, one myth is that

because a.i. is so good at a single task, that one day we'll wake up, and we'll all be enslaved or forced to plug our brains to the a.i. but it is nowhere close to displacing humans. >> nrator: but in interviews around the event and beyond, he takes a decidedly contrarian position on a.i. and job loss. a >> t. giants want to paint the rosier picture becausey they're happking money. so, i think they prefer not to i believe about 50% ofwillde. be somewhat or extrely threatened by a.i. in the next 15 years or so. >> narrator: kai-fu lee also makes a great al of money from a.i. s whatarates 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 ink, based on these 40 investments, most of them arehu not impactinn jobs. they're creating value, making high margins, inventing a new model. but i could list seven or eight that would lead to a very clear displacement of human jobs.r: >> narratoe says that a.i. is coming, whether we like it or not. anhe wants to warn society about at he sees as inevitable. you have a view which i think is different than many others, which is that a.i. is not going to take blue-collar jobs so quickly, but is actuly going to take white-collar jobs. >> yeah. well, both will happen. a.i. will be, at the same time, white-collar jobs, and-collar, great symbiotic tool for doctors, lawyers, and you, for example. but the white-collar jobs are easier to take, because they're a pure quantitative analytal process. let's say reporters, traders,

telemarketing, telesales, customer service... >> analysts? >> analysts, yes, these can all be replaced just by a software. to do blue-collar, some ofhe work requires, you know, hand-eye coordination, things that machines are not yet good enou to do. >> today, there are many people who are ringing arm, "oh, my god, what are we going to do? half the jobs are going away." i believthat's true, but here's the missing fact. i've done the research on this, and if you go back 20, 30, or a 40 yea, you will find that 50% of the jobs that people performed back then are gone today. al you know, where arthe telephone operators, bowling-pin setters, elevator operators? you used to have seas of secretaries in corporations that have now been eliminated-- travel agents. you can just go through fieldte field after field. that same pattern has recurred many times throughout history, with each new wave of

automation. >> but i would argue that history is only trustable if it is multiple repetitions of similar events, not once-in-a-blue-moon occurrence. soover the history of many tech inventions, most are smallh gs. only maybe three are at the magnitude of a.i. revolution-- the steam, steam engine, electricity, and theomputer revolution. i'd say everything else is too smal and the reason i think it might be something brand-new is that our cognitive process in doing a job in its significant entirety, and it can do it dramatically better. >> narrator: this argument about job loss in the age of a.i. was ignited six years ago amid the gargoyles and spires

of oxford university. two researchers had been poring through u.s. labor statistics, identifying jobs that could be vulnerable to a.i. automation. >> well, vulnerable to automation, in the context that we discussed five years ago now, essentially meant that those jobs are potentially automatable over an unspified number of years. and the figure we came up with was 47%. >> narrator: 47%. the world in headlinesewsd bulletins. but authors carl frey andos michaerne offered a caution. they can't predict how manyos jobs will be or how t frey believes that there are lessons in history. >> and what worries me the most is that there is actually one episode that loo quite familiar to today, which is the british industrial revolution, where wages didn't grow for nine

decades, and a lot of people actually saw living standards decle as technology progressed. ♪ >> narrator: saginaw, michigan, knows about decline in living standards. harry cripps, anuto worker and a local union president, has witnessed what 40 ars of automation can do to a town. >> you know, we're one of the cities in the country that, i think we were left behind in this recovery. and i just... i don't know how we get on the bandwagon now. r: >> narratonce, this was the u.a.w. hall for one local union. now, with falling membership, it's shared by five locals. >> rudy didn't get his shift. >> narrator: this day, it's the nter for a christmas food drive. even in a growth economy, unemployment here is near

six percent. poverty in sinaw is over 30%. to >> our f has about 1.9 million square feet. backn the '70s, that 1.9 million square feet had about 7,500 u.a.w. automive workers making middle-class wage with decent benefs and able to send their kids to college and do all the things that the middle-class family should be able to do. our factory today, with automaon, would probably be about 700 united auto workers. that's a dramatic change. u lot on brothers used to work there, buddy. >> the trw plant, that wase. unfortun >> delphi... looks like they're starting to tear it down now. wow. automations is, is definitely taking away a lot of jobs. y cars, i don't know how they buy sandwiches, i don't know how they go to the grocery store. they definitely don't pay taxes, which serves the infrastructure. and the police and the firemen,

and anybody else that supports the city is gone, 'cause there's no tax base. robots don't pay taxes. >> narrator: the average personal incomin saginaw is $16,000 a year. >> a lot of the families that i work with he in the community, both parentsre working. they're working two jobs. mainly, it's the wages, youak know, people notg a decent wage to be able to support a family. n like, backe day, my dad even worked at the plant. my mom stad home, raised the children. and that give us the opportunity to put food on the table, and things of that nature. and, and them times are gone. >> if you look at this graph of what's been happening to america since the end of world war ii, you see line for our productivity, and our productivity gets better over time. ca it used to be th that our pay, our income, would increase in lockstep with those productivity increases.

the weird part about this graph is how the income has decoupled, is not going up thsame way that productivity is anymore. >> nrator: as automation has taken over, workers are either laid off or left with less-skilled jobs for less pay, while productivity goes up. >> there are still plenty of factories in america. we are a manufacturing powerhouse, but if you go walk arou an american factory, yo do not see long lines of people doing repetitive, manual labor. you see a whole lot of automation. if you go upstairs in that factory and look at the payrolln department, you seor two people looking into a screen all day. so, the activity is still there, but the number of jobs is very, ry low, because of automation and tech progress. now, dealing with that challenge, and figuring out what the next generation of the american middle class should be doing, is a really imptant challenge, because i am pretty confident that we are never again going to have this large, stable, prosperous middln

class doing rowork. ♪ >> narrator: evidence of how a.i. is likelyo bring accelerated change to the u.s. workforce can be found not far from saginaw. this is the u.s. headquarters for one of the world's largest builders of industrial robots, a japanese-owned company called fanuc botics. >> we've been producing robots for well over 35 years. and you can imagine, over the c years, they'nged quite a bit. we're utilizing the artificial intelligence to really make the robots easier to use and be able to handle a broader spectrum of opportunities.ug we see agrowth potential in robotics. and we see that growth pottial as being, really, there's 90% of the market left. >> narrator: the industry says optimistically that withhat growth, they can create more jobs. >> even if there were five people on a job, and we reduced that down to two people, a

because omated some level of it, we might produce twowe times more parts thaid before, because we automated it. so now, there might be the need for two more fork-truck drivers, or two more quality-inspection personnel. so, although we reduce some ofop the , we grow in other areas as we produce more things. >> when i increase productivity through automation, i lose jobs. jobs go aw. and i don't care what the robot manufacturers say, you aren't replacing those ten production people, that that rot is now doing that job, with ten peopleu you can incrse pivity to a level to stay competitive with the global market-- that's what they're trying to do. ♪ >> narrator: in the popular telling, blame for widespread job lo has been aimed overseas, at what's called offshoring. >> we want to keep our factories here, we want to keep our manufacturing here

we don't want them moving too china,xico, to japan, to india, to vietnam. >> narrator: but it turns outf moste job loss isn't because of offshoring.n >> there's bfshoring. and i think offshoring is responsible for maybe 20% of the jobs that have been lost. i would say most of the jobs that have been lost, despite what most ericans thinks, was due to automation or productivity growth. >> narrator: mike hicks is an economist at ball state university in muncie, indiana. he and sociologist emily wornell haveeen documenting employme trends in middle america. hicks says thaautomation has been a mostly silent job killer lowering the stand living. >> so, in the last 15 years, the standard of living has dropped by 15, ten to 15 percent. so, that's unusual in a developed world. a one-yearecline is a recession. a 15-year decline gives an entirely different sense about

the prospects of a community. and so that is common from the canadian border to the gulf of mexico in the middle swath of the united states. >> this is something we're gonna do for you guys. these were left over from our suggestion drive that we did, and we're going to give them each two.is >> that awesome. >> i mean, that is going to go a long ways, right? i mean, that'll really help that family out during thlidays. >> yes, well, with the kids home from school, the families have goree meals a day that the to put on the table. so, it's going to make a big difference. so, thank you, guys. >> you're welcome. >> this is wonderful. >> let them know merry christmas behalf of us here at th local, okay? >> absolutely, you guys are just, just amazing, thank you. and please, tell, tell all theul workers how gratef these families will be. >> we will. >> i mean, this is not a small problem. i the neso great. and i can tell you that it's all ras, it's all income class that you might think someone might be from. but i can tell you that when you see it, and you deliver this

typef gift to somebody who i in need, just the gratitude that they show you is incredible. >> we actually know that people are at greater risk of mortality for over 20 years after they lose their job due to, due to no fault of their own, so something like automation or offshoring. they're at higher risk for d cardiovasculease, they're d suicide.risk for depression tergenerational impacts, we likely-- children of p whoe more have lost their job due to automation-- are more likely to repeat a grade, they're more likely to drop out of school, they're more likely to be hespended from school, and have lower educational attainment over their entire lifetimes. >> it's the future of this, not the past, that scares me. because i think we're in the early decades of what is a multi-decade adjustment period. ♪

>> narrator: theorld is being re-imagined. this is a surmarket. robots, guided by a.i., pack evything from soap powder cantaloupes for online consumers. machines that pick groceries, machines that can also read reports, learn routines, and comprehend are reaching deep into factories, stores, and offices. at a college in goshen, indiana, a group of local business and political leaders come together mpto try to understand thet of a.i. and the new machines. of work at a washington think tank. >> how many people have gone into a fast-food restaurant and anyone, yes?ordering? panera, for instance, is doing this. cashier was my first job, and in, in, where i live, in washington, dc, it's actually the number-one occupation for the greater dc region. there are millions of people who

work in cashier positions. this is not a futuristic challenge, this is something that's hapning sooner than we think. in the popular discussions about robots and automation and work, almost every image is of a man on a factory floor or a truck driver. and yet, in r data, when we looked, women disproportionately hold the jobs that today aret highest risk of automation. and that's not rlly being talked about, and that's in part because women are over- represented in some of these marginalized occupations, like a cashier or a fast-food worker. and alson a large numbers in clerical jobs in offices-- hr departments, payroll, finance, s lot of thaore routine processing information, p processier, transferring data. that has huge potential for automation. a.i. is gonna do some of that, software, robots are gonna do some of that.

so how many people are still working as switchboard operators? probably none in this country. >> narrator: the workplace of ree future will demand dif skills, and gaining them, says molly kinder, will depend on w can afford them. >> i mean it's not a goodd situation in the uniates. there's been some excellent research that says that halff americans couldn't afford a 00 unexpected expense. and if you want to get to a $1,000, there's even less. so imagine you're going to go out without a month's pay, two months' pay, a yea imagine you want to put savings toward a course to, to redevelop your career. people can afford to take time off of work. they don't have a cushion, soac thisof economic stability, married with the disruptions in people's careers, is a really toxic mi >> (blowing whistle) >> narrator: the new machines will penetrate every sector of the economy: from insunce companies to human resource departments; from law firms to the trading floors of wall

street. >> wall street's going tough it, but every industry is going through it. every company is looking at all of the disruptive technogies, could be robotics or drones or and whatever it is, every company's using everything that's developed, everything that's disruptive, in thinking about, "how do i apply that to my business to make myself more efficit?" and what efficiency means is, mostly, "how do i do this with fewer workers?" and i do think that when we loot ome of the studies about opportunity in this country, and the inequality of opportunity, the likelihood that you n't be able to advance from where your parents were, i think that's, that's, is very serious and gets to the heart of the way we like to think of america as the landy of opportu >> narrator: inequality has been rising in america. it used to be the top 1% of earners-- here in red-- owned a

relatively small ption of the country's wealth. middle and lower earners-- in blue-- had the largest share. then, 15 years ago, the lines crossed. and inequality has been ineasing ever since. >> there's many factors that arn drivinuality today, and unfortunately, artificial intelligence-- without being thoughtful about it-- is a driver for increased inequality because it's a form of automation, and automaon is the substitution of capital for labor. and when you do that, e people with the capital win., so karl marx was rig's a struggle between capital and labor,nd with artificial intelligence, we're putting our finger on the scale on the sidee of capital, and hoish to distribute the benefits, theec omic benefits, that that will create is going to be a major moral considation for society over the next several decades.

>> this is really an outgrowth o of the increasing gahavesot and have- the wealthy getting wealthier, the poor geing poorer. it may not be specifically related to a.i., but as... but a.i. will exacerbate that. and that, i think, will tear the society apart, because the rich will have just too much, and those who are have-nots will have perhaps very little way of digging themselves out of the hole. and with a.i. making its impact, it, it'll be worse, i think. ♪ (crowd cheering and applauding) >> (speaking on p.a.) i'm here today for one main reason. y to say tha to ohio.

(cro) cheering and applauding >> i think the trump vote was a protes i mean that for whatever reason, whatever the hot button was that, you know, that really hit home with these americans whore voted for him it was a protest vote. they didn't like the direction things were going. (crowd booing and shouting) i'm scared. i'm nna be quite honest with you, i worry about the future of not just ts country, but the, the entire globe. if we continue to gon an automated system, what are we gonna do? now i've got a group of people t top that are making all the money and i don't have anybody in the middle that can support a family so do we have to go to the poine wherrash to come back? and in this case, the automation's already gonna be there, so i don't know how you come back. i'm really worried abo where this, where this leads us in the future.

♪ >> narrator: the future is largely being shap by a few hugely successful tech companies. they're nstantly buying up successful smaller companies and recruiting talent. between the u.s. and china, they employ a great majority of thea. leadin researchers and scientists. in the course of amassing sucho power, they've acome among the richest companies in the world. >> a.i. really is the ultimate tool of wealth creation. think about the massive data that, you know, facebook has on user preferences, and how it can very smartly target an ad that geu might buy something an a much bigger cut that a smaller

company couldn't do. same with google, same with amazon. so it's... a.i. is a set of tools that helps you maximize ab ctive function, and that objective function initially will simply be, make more money. >> narrator: and it is how these compans make that money, and how their algorithms reach deeper and deeper into our work, our daily lives, and our democracy, that makes many people increasingly uncomfortable. pedro domingos wrote theook "the master algorithm." >>verywhere you go, you generate a cloud of data. that you do is producia.erything and then there are computers looking at that data that are learning, and these computersng are essentially tro serve you better. they're trying to personalize things to you. they're trying to adapt the world to you. so on the one hand, this is great, because theorld will get adapted to you without you

even having to explicitly adapt it. there's also a danger, because the entities in the companies that aren control of those algorithms don't necessarily have the same goals as you, and this is where i think people need to be aware that, what's t going on, y can have more control over it. >> you know, we came into this new world thinng that we were users of social media.s it didn't occur toat social media was actually using us. we thought that we were searching google. we had no idea that google was searching us. >> narrator: shoshana zuboff is a harvsiness school professor emerita. in 1988, she wrote a definitive book called "in the age of the smart machine."fo the last seven years, she has worked on a new book, makino the case that we hav entered a new phase of thels economy, which she c "surveillance capitalism." >> so, famously,ndustrial c

capitaliimed nature. innocent rivers, and meadows, a and forest so forth, for the market dynamic to be reborn as real estate, as land that could be sold and purchased. industrial capitalism claimed work for the market dynamic to reborn, to be reborn as labor that could be sold and purchased. now, here cos surveillance capitalism, following this pattern, but with a dark and sttling twist. claims is private, humtalism experience.e, privuman experience is claimed as a free source of raw mateal, fabricated into predictions of human behavior. and it turns out that there are a lot of businesses that really want to know what we will dono >> narrator: like most

people, alastair mactaggart had know ideabout this new surveillance business until one evening in 2015. >> i had a conversation with a fellow who's an engineer, and i st talking to him one night at a, you know, a dinner,i at a cocparty. and i... there had been something in the press that day about privacy in the paper, and i remember asking him-- herk for google-- "what's the big deal about all, why are people so worked up about it?" and thought it was gonna be one of those conversations, like, with, you know, if you ever ask an airline lot, "should i be worried about flying?", and they say, "oh, the e airport, you know, in theng to car." horrified if you knew chbe we knew about you." and i remember that kind ofin stucy head, because it was nowhat i expected. >> narrator: that question would change his life. a successful california real estate developer, mactaggart w business model. the

>> what i've learned since ise that their entsiness is learning as much about you as they can. everything about your thoughts, and your desires, and your dreams, and who your friends are, and what you're thinking, what your private thoughts are.t and wit, 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. ♪ en doing her own research.ff had >> you know, i'd been reading and reading and reading. from patents, to transcripts of earnings calls, research reports. and, you know, just literallyan everything, for yearyears and years. >> narrator: her studies included the early days of google, started in 1998 by two young stanford grad students, sergey brin and larry page. o the beginning, they had clear business model. their unofficial motto was "don't be evil."

>> right from the start, the founders, larry page and sergey brin, they had been very public about their antipathy toward advertising. advertising would distort the internet and it would distort and disfigure the, the purity of any search engine, including their own. >> once in love with e-commerced wall street has turnts back on the dotcoms. >> narrator: then came the dos.om crash of the early 20 >> ...has left hundreds of unprofitable internet companies begging for love and money. >> narrator: while google hadbe rapidlme the default search engine for tens of millions of users, their investors were preuring them to make more money. without a new business model,fo thders knew that the young company was in dger. >> in this state of emergency,

the founders decided, "we'veo simply gotnd a way to save this company." and so, parallel to this wereve another set of dises, where it turns out that whenever we search or whenever we browse, we're leaving behind traces-- digital aces-- of our behavior. ys, were called digitalin these exhaust. >> narrator: they realized how valuable this data could be by applying machine learning algorithms to predict users' interests. >> what happened was, they decided to turn to those data logs in a systematic way, and to begin to use these surplus data as a way to come up within fine-g predictions of what a user wouldlick on, what kind of aa user would click on.

and inside google, they started seeing these revenues pile up at a startling rate. they realized that they had to keep it secret.ey idn't want anyone to know how much money they were making, or how they were making it. because users had no idea that these tra-behavioral data that told so much about them, you t know, was just ore, and now it was being used to predict their future. >> narrator: when gole's i.p.o. took place just a few years later, the company had a market capitalization of around $2billion. google's stock was now as vaable 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 i

revenue lireased by 3,590%. formation, and search, and how people consume it. >> narrator: by 2010, the c.e.o. of google, eric schmidt, would tell "the atlantic" magazine... >> ...is, we don't need you to type at all. because we know where you are, with your peission, we know where you've been, with your permission.or we canor less guess what you're thinking about. (audience laughing) now,s that over the line? >> narrator: eric schmidt and google declined to be interviewed for this program. google's new business model for predicting users' profiles had migrated to other companies, particularly facebook. roger mcnamee was an early investor and adviser to facebook. he's now a critic, and wrote a book about the company. he ss he's concerned about h widely companies like facebook and google have been casti the net r data.

>> and then they realized, "wait a minute, ere's all this data in the economy we don't have." so they went to credit card processors, and credit rating services, and said, "we want to buy your data." they go to health and wellness apps and say, "h, you got women's menstrual cycles? why are they doing tha." they're doing that because behavioral prediction is aut taking uncertainty out of life. advertising and marketing are all about uncertainty-- you never really know who's going to buy your product. until now. we have to recognize that we gave technology a place in our lives that it had not rned. that essentially, because technology always made things better in the '50s, '60s, '70s, '80s, and '90s, we developed a sense of inevitability that it we developed a trust, and ther. industry earned good will thatok

facend google have cashed in. >> narrator: the model is simply this: provide a free service-- like facebook-- and in exchangeo yollect the data of the millions who use it. ♪ and every sliver of information is valuable. >> it's not just what you post, it's that you post. it's not just that you make plans to see your friends later. it's whether you say, "i'll see you later," or, "i'll see you at 6:45." it's not just that you talk about the things that you have to do today. it's whetherou simply rattle them on in a, in a rambling paragraph, or list them as buet points. all of these tiny signals are the behavioral surplus thats tuout to have immense predictive value.

>> narrator: in 2010, facebook experimented with a.i.'s predictive powers in what they called a "social contagion" experiment. they wanted to see if, through online messaging, they couldeh influence real-worldior. the aim was to get more people to the polls ithe 2010 midterm elections. >> cleveland, i need you to keep on fighting. i need you to keep on believing. >> narrator: they offered 61 million users an "i voted" button together with faces of friends who had voted. a subset of users received just the button.la in the end, theyed to have nudged 340,000 people to vote. they would conduct other "massive contagion" experiments. among them, one showing that by adjusting their feeds, they could make users happy or sad. >> when they went to write up

these findings, they boasted out two things. one was, "oh, my goodness. now we know that we can use cues in the online environment toan real-world behavior. that's big news." the second thing that they understood, and they celebrated, was that, "we can do this in a way that bypasses the users' awareness." >> private corporations have built a corporate surveillance state without our awareness or permission. and the systems necessary to make it work are getting a lot better, specifically with what are known as internet of thingsp smariances, you know, powered by the alexa voice recognition system, or the google home system. >> okay, google, play thern g playlist. >> okay, playing morning playlist. ♪

>> okay, google, play music in all rooms. ♪ l >> and those wt the surveillance in places we've oms, kitchens, bedrooms.ving 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. impre the user experience. >> alexa, turn on the fan. (fan clicks on) >> okay.r: >> narraeanwhile, they are researching and applying for patents to expand their reachto inomes and lives. >> alexa, take a video. (camera chirps) >> the more and more that you use spoken interfaces-- so smart speakers-- they're being trained not just to recognize who you are, but they're staing to take baselines and comparing changes over time. so does your cadence increase or decrease?

are you snzing while you're talking? is your voice a little wobbly? the purpose of doing this is to understand more about you in real time. so that a system could make inferences, perhaps, like, do you have a cold? are you in a manic phase? are you feeling depressed? so that is an extraordinary amount of information that can be gleaned by you simply wakin up and asking your smart speaker, "what's the weather today?" >> alexa, what's the weather for tonight? >> currently, in pasadena, it's 58 degrees with cloudy skies. >> inside it is, then. dinner! >> the point is that this is the same micro-behavioral targeting that is directed toward individuals based on intimate, detailed understanding of personalities. so this is precisely what

cambridge analytica did, simply pivoting from the advertisers to the political outcomes. >> narrator: the cambridgean analytica dal of 2018 engulfed facebook, forcing mark ezuckerberg to appear bef congress to explain how the data of up to 87 million fabook users had been harvested by a political consulting company based in the u.k. the purpose was to tget and manipulate voters in the 2016 presidential campaign, as well as the brexit referendum.ri cae analytica had been largely funded by conservative hedge fund billionaire robert mercer. >> and now we know that any billionaire with enough money, who can buy the data, buy the machine intelligencepa lities, buy the skilled data scientists, you know, they too can commaner the public,ct

and innd infiltrate and heupend our democracy with surveillance capitalism uses every single day >> we di't take a broad enough view of our responsibility, and that was a big mistake. and it was my mistake, and i'm sorry. >> narrator: zuckerberg has apologized for numerousy, violations of privnd his company was recently fined $5er billion by the f trade he has said facebook will now make data protection a priority, and the company has suspended tens of thousands of third-party apps from its platform as a result of an internal investigation. >> you know, i wish i could say th, after cambridge analyti we've learned our lesson and that everything will be much i better after that, b afraid the opposite is true.

in some ways, cambridge analytica was using tools that were ten years old. it was really, in me ways, old-school, first-wave data science. what we're looking at now, withr t tools and machine learning, is that the ability for manipulation, both in terms of elections and opinions, but more broadly, just how information travels,hat is a much bigger problem, and certainly much more serioused than what we fith cambridge analytica. >> narrator: a.i. pioneer yoshu bengio as concerns about how his algorithms are being used.a. >> so the is. are tools. and they will serve the people who control those tools. go those people's interest against the, the values of democracy, then democracy is in so i believe that scie who contribute to science, when e at science can or will h

impact on society, those scientists have a responsibility. it's a little bit like the physicists of, around the secon world war, who r to tell the governments, "wait, nuclear power can be dangerous and nuclear war can be rlly, really destructive." and today, the equivalent of a physicist of the '40s and '50s and '60s are, are the computer scientists who are doing machine learning and a.i. ♪ >> narrator: one person who wanted to do something about the dangers was not a computer scientist, but an ordinary citizen. alastair mactaggart was alarmed. >> voting is, for me, the most alarming one. if less than 100,000 votespa ted the last two candidates in the last presidential election, in three states... >> narrator: he began a solitary caaign. >> we're talking about convincing a relatively tinyon

fracf the voters in a very... in a handful of statesnd to either come outote or stay home. and remember, these companies know everybody intimely. they know who's a racist, who's a misogynist, who's a homophobe, who's a conspiracy theorist. they know the lazy people and the gullible people.ss they have aco the greatest trove of personal information that's ever been assembled. dthey have the world's bea scientists. and they have essentially a frictionle way of communicating with you. this is power. >> narrator: mactaggart started a signature drive for a california ballot initiative,ns for a law to give ers control of their digital data. s in all, he wound $4 effort to rein in the hs in an of silicon valley. google, facebook, at&t, and comcast all opposed his initiative. >> i'll tell you, i was scared. fear. fear of oking like a world- class idiot. the market cap of all the firms

arrayed against me were, was over $6 trillion. >> narrator: he needed 500,000 signatures to get his initiave on the ballot. he got well over 600,000. polls showed 80% approval for a privacy w. that made the politicians in sacramento pay attention. so mactaggart decided that because he was holding a strong hand, it was worth negotiati with them. >> and if ab75 passes by tomorrow and is signed into law by the governor we will widraw the initiative. our deadline to do so is tomorrow at five. >> narrator: at the very last moment, a new law was rushed to the floor of the state house. >> everyone take their seats please. mr. secretary, please call the roll. >> the voting starts. >> alan, i. >> and the first guy, i think, was a republican, and he voted for it. and everybodhad said the republicans won't vote for it because it has this private right of action, where

consumers can sue. and the guy in the senate, he i, roth. me. i, skinner. i, stern. i, stone >> you can see down below, and everyone wt green, and then it passed unanimously. >> "i's" 36, "no" zero, the measure passes. immediate transmittal to the... >> so i was blown away. never forget.yea day i will so in january, nex, you as a california resident will company and say, "whatyouny collected on me in the last 12 years... 12 months? what of my personal informationh do ye?" that's the first right. it's right of... we call that the right to know.s the seconde right to say no. and that's the right to go to any company and click a button on any page where they're collecting your information, and inrmation."t sell my more importantly, we require that they honor what's called a third-party opt-out. you will click once in your browser, "don't sell my information," and it will then

send the signal to every single websat you visit: "don't sell this person's information." and that's gonna have a huge impact on the spread oyour information across the internet. >> narrator: the tech companies had been publicly caious, but privately alarmed about regulation. then one tech giant came on board in support of mactaggart's effort >> i find the reaction among other tech companies to, at this point, be pretty much all over the place. some people are saying, "you're right to raise this. these are good ideas." some people say, "we're not sure these are good ideas, but you're right to raise it," and some people are saying, "we don't want regulatio" and so, you know, we have conversations with people wheret we put that the auto industry is better because there are safety standards. pharmaceuticals, even food products, all of these industries are better becauseic the puas confidence in the products, in part because of a mixture of responsible companies

and responsible regulation. r big tech have been workingts the corridors in washington.g they're lookr a more lenient national privacy standard, one that could perhaps override the california law and others like it. but while hearings are held, and anti-trust legislation threatened, the problem is that a.i. has already spread so far into our lives and work. >> well, it's in healthcare, it's in education, it's in i criminal justice, itthe experience of shopping as you walk down the street. it has pervaded so many elements of everyday life, and in a way that, in many cases, ismp tely opaque to people. while we can see a phone and look at it and we know thatso there' a.i. technology behind it, many of us don't know that wn we go for a jobw intervd we sit down and we have a conversation, that we're expressions are being analyzedro by hiring companies.

or that if you're in the criminal justice system, that there are risk assessment algorithms that are decidingyo "risk number," which could determine whether or not you receive bail or not. these are systems which, in many cases, are hidden in the back end of our sort of social institutions. and so, one of the big challenges we have is, how do we make that more apparent? w how ma it transparent? and how do we make it accountable? >> for a very long time, we have felt like as humans, aser ans, we have full agency in determining our own futures-- what we read, what we see, we're in charge. what cambridge analytica taught us, and what facebook continues to teach us, is that we don't have agency. we're not in charge. this is machines that are tomating some of our skills, but have made decisions about who... who we are.

and they're using that information to tell others the story of us. ♪ >> nrator: in china, in the age of a.i., there's no doubt about who is in charge. in an authoritarian state, social stability is the watchword of t government. (whistle blowing) and artificial intelligence has increased itability to scan the country for signs of unrest. (whistle blowing) it's been projected that over 600 million cameras will be deployed by 2020. here, they may be used to discourageaywalking. but they also serve to remind people that the state is watching.

>> and now, there is a project called sharp eyes, which is putting camera on every majorhe street andorner of every village in china-- meaning everywhere. matching with the most advanced artificial intelgence algorithm, which they can actually use this data, real-time data, to pick up a face or pick up a action. ♪ >> narrator: frequent security expos feature companies like megviind its facial- recognition technology. they show off cameras with a.i. that can track cars, and identify individuals by face, or just by the way they walk. >> the place is just filled with these screens where you can see the computers are actually reading people's faces and trying to digest that data, d basically track and identify who each person is.'s and ncredible to see so many, because just two or three years ago, we hardly saw that

ki of thing. so, a big part of it is government spending. and so the technology's really a taken of a lot of companies have started to sort of glom onto this idea that this is the future. >> china is on its way tour building a totalillance state.nd >> narrator:his is the test lab for the surveillance state.re in the far northwest of china, ithe autonomous region of xinjiang. of the 25 million people who live here, almost half are a muslim turkic speaking people called the uighurs. (people shouting) in 2009, tensions with local han chinese led to protests and then riots in the capital, urumqi. (people shouting, guns firing) (people shouting) as the conflict has grown, the authorities have brought in more police, and deployed extensive

surveillance technology. that data feeds an a.i. systemt that the governmaims can predict individuals prone to "terrorism" and detect those in need of "re-education" in scores of recently built camps. it is a campaign that has alarmehuman rights groups. >> chinese authorities are, without any legal basis, arbitrarily detaining up to a million turkic muslims simply on the basis of their identity. but even outside the facilities in which these people are being held, most of the populationed there is being subjeo extraordinary levels of high-tech surveillance such that almost no aspect of life anymore, you know, takes placets e the state's line of sight. and so the kinds of behavior that's now being monored-- you know, which language do you speak at home, whether you're talkinto your relatives in other countries, how often you pray-- that informion isow

being hoovered up and used to decide whether people should be subjected to political re-education ithese camps. >> narrator: there have been reports of torture and deaths in the camps.an for uighurs on the outside, xinjiang has already been deribed as an "open-air prison." l>> trying to have a norme as a uighur is impossible both inside and outside of china. just imagine, while you're o your way to work, police subject you to scan your i.d., forcing you to lift your cn, while machines take your photo and wait... you wait until you findn out if youo. imagine police take your phone and run data sn, and force you install compulsory software anallowing your phone calld messag to be monitored. >> narrator: nury turkel, a lawyer and a prominent uighur activist, addresses a demonstration in washington,c.

many among the uighur diaspora have lost all contact with their families back home. turkel warns that this dystopian deployment of new technology is a demonstration project for authoritarian regimes around the world. >> they have a bar codes in somebody's home doors to identify what kind of citizen that he is. what we're talking about is a collective punishment of anic etroup. not only that, the chinese government has been promoting its methods, its technology, it is... to other countries, namely pakistan, venezuela, sudan, and others to utilize, to squelch evpolitical resentment or t a political upheaval in their various societies. ♪ >> narrator: china has a grand scheme to spread its technology

and influence around the world.d launn 2013, it started along the old silk road out ofan xinjiangnow goes far beyond. it called "the belt and ro initiative." >> so effectively what the belt and road is is china's attempt to, via spending and investment, projecits influence all over the world. and we've seen, you know, massive infrastructure projects going in in places like pakistan, in, in venezuela, in ecuador, in bolivia-- you know, all over the world, argentina, in america's backyard, in africa. africa's been a huge place. and what the belt and ro ultimaly does is, it attempts to kind of create a political leverage for the chinese erspending campaign all ovhe globe. >> narrator: like xi jinping's 2018 visit to senegal, where chinese contractors had just built a new stadium, arranged loanfor a new infrastructure development, and, said the foreign minist, there would

be help "maintaining social stability." >> as china cos 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 theseie we've started to see it already in terms of surveillance systems. not the kind of high-level a.i. stuff yet, but, you know, lower- level, camera-based, you know, manual sort of observation-type things all over. you know, you see it in cambodia, you see it in ecdor, you see it in venezuela. and what they do is, they sell a , m, sell some other stuffd they say, "you know, by the wayh we can give you e camera systems and, for your emergency response. and it'll cost you $300 million, and we'll build a ton of ameras, and we'll build y kind of, you know, a main center where you have police who cane watch thmeras." and that's going in all over the world already. ♪ >>here are 58 countries th are starting to plug in to china's vision of artificial intelligence.wh h means effectively that

china is in the process of raising a bamboo curtain. one that does not need to... one that is sort of all-en mpassing, that has shared resources, sharedte telecommunications s, shared infrastructure, shared digital systems-- even shared mobile-phone technologies-- that is, that is quickly gng up all around the world to the exclusion of us in the west. >> well,ne of the things i worry about the most is that the world is gonna split in two, and th there will be a chinese tech sector and there will be an american tech sector.tr and cos will effectively get to choose which one they want.'l be kind of like the cold war, where you decide, "oh, are we gonna align with the soviet w union or agonna align with the united states?" and the third world gets to choose this or that. and that's not a world that's good for anybody. >> the markets in asia and the u.s. fling sharply on news that a top chinese executivees has been ad in canada.

her name is sabrina meng. she is the cfo of the chineseco telem huawei. t >> narrator: news ofhe dramatic arrest of an important huawei execuve was ostensibly about the company doing business with iran. but it seemed to be more about american distrust of the company's technology. from its headquarters in soutrn china-- designed to look like fanciful european capitals-- huawei is the second- biggest seller of smartphones, and the world leader ibuilding 5g networks, the high-speed backbone for the age of a.i. huawei's c.e.o., a former p ficer in tple's liberation army, was defiant about the american actions. >> (speaking mandarin) (translated): there's no way the u.s. can crush us.hu the world needei because we are more advanced. if the lights go out in the west, the east will still shine.

and if the north goes dark, then there is still the sou. america doesn't represent the world. fears that as huawei ssovernment countries around the world with 5g, the chinese government could have bacdoor access to their equipment. recently, the c.e.o. promised complete transparency into the company's software, but u.s. authorities are not convinced. in >> nothing in chexists free and clear of the party-state. those companies can only exist and prosper at the sufferance of the party. and it's made very explicit that when the party needs them, the either have to respond or they will be dethroned. so this is the challenge with a company like hwei. so huawei, ren zhengfei, thef headawei, he can say, "well, we... we're just a private company and we just... weon't take orders from th

communist party." well, maybe they haven't yet. national intelligence councilhe sees, and what the fbi sees is,y "well, not yet." but when the call comes, everybody knows what the company's response will be. >> narrator: the u.s. commerce blacklisted eight companies for doing business with governme agencies in xinjiang, claiming they are aiding in the nority.onon" of the muslim the companies is megvii. they have strongly objected toth blacklist, saying that it's "a misunderstanding of our company and our tenology." ♪ president xi has increased his authoritarian grip on the country. in 2018, he had the chine

constitution changed so that he could be president for life. >> if you had asked me 20 years ago, "what will happen to china?", i would've said, "well, over time, the great firewall will break down. of course, people will get access to social media, they'll get access to google... eventually, it'll become a much moreemocratic place, with free expression and lots of western values."la and th time i checked, that has not happened. in fact, technoly's become a tool of control. c and na has gone through this amazing period of growth and wealth and openness in certain wa, there has not been the democratic transformation that i thought. and it may turn out that, in ttfact, technology is a beer tool for authoritarian governments than it is for democratic governments. >> nartor: to dominate the world in a.i., president xi is depending on chinese tech to lead the way.wh e companies like baidu,

alibaba, and tencent are growing more powerful and competitive, they're also beginning to have difficulty accessing american technology, and are racing to develop their own. c withtinuing trade war and growing distrust, the longtime argument for engagement stween the two countries been losing ground. >> i've seen more and more of my colleagues move from a position when they thought, "well, if we nes between the two countries s wiwly converge." you know, whether it's in economics, technogy, politics. and the transformation, where they now think they're diverging. so, in other words, the whole idea of engagement is coming under question. and that's cast an entirely different light on technology,

because if you're diverging and you're heading into a world of antagonism-- you know, conflict, possibly, then suddenly, technology is something that you don't want to share. you want to sequester, to o protect yo national interest. and i think the tipping-point moment we are at now, which is what is casting e whole question of things like artificial intelligence and technological innovation into a completely different framework, is that if in fact china and the u.s. are in some way fundamentally antagonistic to each otherthen we're in a completely different world. >> narrator: in the age of a.i., a new reality is emerging.mu that with so much acted investment and intellectual power, the world is already dominated by just two a.i.

superpowers. t thhe premise of a new book written by kai-fu lee. >> hi, i'm kai-fu. you.i, dr. lee, so nice to mee >> really nice to meet you. look at all these dog ears. i love, i love tha >> you like that? >> but i. but i don't like you didn't buy the book, you... youd borrow it. >> i couldn't find it! >> oh, really? >> and, and you... youcoming to my talk? >> of course! >> oh, hi. >> i did my homework, i'm telling you. >> oh, my goodness, thank you.u laurie, can yot this gentleman a book? (people talking in background) >> narrator: in his book and in life, the computer scientist-cum-nture capitalist walks a careful path. criticism of the chinese government is avoided, while capitalist success is celebrated. >>'m studying electrical engineering. >> sure, send me a resume. >> okay, thanks.r: >> narra now, with the rise of the two superpowers, he wants to warn the world of what's coming. y >> a the new leaders? we're pretty close. new leaders,

(laughs) thank you very much. >> thanks. >> narrator: "never," he writes, "has the pottial for human flourishing been higher or the stakes of failure greater." ♪ >> so if one has to say who's ahead, i would say today, china is quickly catching up. china actually began its big push in a.i. only two-and-a-half years ago, when the alphago-lee sedol match became the sputnik moment. >> narrator: he says he believes that the two a.i. superpowers should lead the way and work together to make a.i. a force for good. if we do, we may have a chance of getting it right.ve >> if we do good job in the next 20 years, a.i. will be viewed as an age of enlightenment. our children a their children will see a.i. as serendipity. that a.i. is here to liberate us from having to do routine jobs,

and push us to do what we love, and push us to think what it means to be human. >> narrator: but what if humansw mishandle thisower? kai-fu lee understands the stakes. after all, he invested early in megvii, which is now on the u.s. blacklist. he says he's reduced his stake and doesn't speak for the company. asked about the government using a.i. for social control, he chose his rds carefully. >> um... a.i. is a technology that can be used for good and for evil. so how... how do governments limit themselves in, on the one hand, using this a.i. technology and the database to mainta a safe environment for itsot citizens, but, butncroach on a individual'rights and

privacies? that, i think, is also a tricky issue, i thir, for every country. i think for... i think everyy counll be tempted to use a.i. probably beyond the limits to which that you and i would li the government to use. ♪ >> narrator: emperor yao devised the game of go to teach his son discipline, concentration, and balance. over 4,000 years later, in the age of.i., those words stillon resonate witof its architects. ♪ >> so a.i. can be used in many ways that are very beneficial for societ but the current use of a.i. isn't necessarily aligned with the goals of building a better society, unfortunately.

but, but we could ange that. >> narrator: in 2016, a game of go gave us a glimpse of the future of arficial intelligence. since then, it has become clear that we will need a careful strategy tharness this new and awesome power. >>y, i do think that democr is threatened by the progress of these tools unless we improve our social norms and we increase the collective wisdom t planet level to, to deal with that increased power. i'm hoping that my concerns are not founded, but the stakes are so high that i don't think we should take these concns lightly. thdon't think we can play those possibilities and just... race ahead without thinking

about the potential outcomes. ♪ >> go to pbs.org/frontline for more of the impact of a.i. on jobs. of jobs will be somewhty percent extremely threatened by a.i. ine th 15 years or so. >> and a look at the potential for racial bias in this technology.e >> wed issues with bias, with discrimination, with poor system design, with errors. >> connect to the frontline community on facebook and twitter, and watch anytime on the pbs video app or pbs.org/frontline. >> narrator: the mass detention of migrant children... >> they put me in the cage. i was with around 12 other younger minors. it was like a stadium, but with cages and that's wre they kept l the people. >> narrator: who's profiting? >> isn't there an incentive to detain kids? >> there is a price incentive,ot

but it's detention incentive. >> narrator: and at what cost? >> if is is a deterrence, the price is way too high. >> narrator: frontline and the associated press investigate. >> frontline is made possible by contributions to your pbs ank you.from viewers like you. major support is provided by the john d. and catherine t. macarthur foundation, committed to building a more just, verdant and peaceful world. the ford foundation: working with visionaries on the frtlines of social change worldwide. additional support is provided by the abrams foundation, committed to excellence in journalism. the park foundation, dedicated to heightening publicf awarenesritical issues. the john and helen glessner family trust. supporting trustworthy journalism that informs and inspires. and by the frontline journalism fund, with major support from jon and jo ann hagler. and additional support from tom stair and lucy caldwe-stair.

major support for frontline and, "in the age of ai" is provided by the corporationca for public broing. captioned by media access group at wgbh access.wgbh.org >> for more on this and other "frontline" progra, 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.is rogram is also available on amazon prime video. ♪

re ♪ you'atching pbs. ♪ christiane: can you tell us what ♪ fire before us. ♪ you're the brightest. judy: turning ba t now to the race for white house. ♪ you will lead us through the storms. ♪ robert: the state board of election voted thursday to set up a new election. t rchristiane: it m a veryof emotional day. ♪ i will trust the promise. myamiche: children at the the heart of this story. ♪ safe to shore. ♪ safe to shore.

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