>> rose: welcome to the program. tonight, artificial intelligence, early in 2016, i visited the a.i. and robotics lab at carnegie mellon in pittsburgh for a piece at aired on "60 minutes." this evening, i bring you my full conversation with andrew moore, dean of school of computer science at carnegie. >> a lot of the biggest advances in artificial intelligence in the last 20 years have actually been inspired by looking at what goes on in the brain. often, the brain really reacts to mistakes. if you do something that doesn't work out, stuff in the brain says, well, i'm not going to do that next time, i'm going to try something else. a lot of our machine learning algorithms do the same thing. >> rose: all about artificial intelligence when we continue.

>> rose: funding for "charlie rose" has been provided by the following: >> and by bloomberg, a provider of multimedia news and information services worldwide. captioning sponsored by rose communications from our studios in new york city, this is charlie rose. >> rose: what is artificial intelligence? >> so it is what we're all doing when we make machines do things which we usually ascribe to human intelligence. so it is all about taking the things which we thought were brilliant things that only went along inside our brains and make computers do them instead. we often break up artificial

intelligence into two subsets of work. many of the a.i. researchers here are working on autonomy, which is having a machine survive by themselves and figure out things by themselves when humans can't help them. many of the other folks here work on cognitive assistance, which is all about machines helping humans be smarter. >> rose: when people think about artificial intelligence, they're thinking about trair trying to get at human intelligence and even to do it better. >> yes. >> rose: what's the barometer, though, to measure the progress in a.i.? >> my favorite barometer is how much does the boring part of my life get done for me by machines. 100 years ago, people said if a machine can multiply two numbers together, it's artificial intelligence. we are growing up where we don't regard that as particularly intelligent. 20 years ago, it was beating

humans at chess. nowadays it's things like really acting like a human in your language dialogue between the computer and the human. so the barometer keeps changing, if you like. it's always the thing which we humans think that we're unique at, automating it and finding out if we can get computers to do it instead. >> rose: are there similarities between how a.i. systems learn and how our brain learns? >> yes. a lot of the biggest advances in artificial intelligence in the last 20 years have actually been inspired by looking at what goes on in the brain. often, the brain really reacts to mistakes. if you do something, it doesn't work out, the brain says, well, i'm not doing that next time, i'm going to try something else. a lot of our machine learning algorithms do the same thing. >> rose: such as touching something hot, recoiling from it

and, therefore, learning not to put your hand there? >> yes. the reflex action is a good one. there are much more mundane things. like, if you say to a search engine, i want to buy a chevy tahoe, and the search engine shows you a vacation in lake tahoe, they're not going to click. there is going to be evidence you're not particularly satisfied. so the search engine will change itself a little bit and after a few hours of making the same mistake, it will correct that. >> rose: that's a good system of how a.i. systems learn and the brain learns and the differences therein. >> yes. >> rose: what are the differences between a.i. learning and brain learning? >> one of the things is computers have got really, really good memories. we're much fuzzier in your memories. so when the computer scientists working on a.i. try to build intelligent systems, they do kind of cheat by taking advantage of all this memory. for example, to be good at end

games in chess, humans study, learn all the principles. computers think just once about of every single possible end game, record all the possible situations they could be in, memorize what they'll do in each situation. >> rose: and can recall it instantly? >> yes. so to some extent, i would say that's an approach to a.i. which is cheating because it is absolutely nothing like what humans do, but it's very effective. >> rose: is that how watson beat kasparov? >> part of it. it turns out, to memorize every single possibility in chess would take hundreds of years on a fast computer. >> rose: you got a grant here from the federal government to study the brain, for a million-dollar grant to study the brain? >> that's right. >> rose: what are you looking to learn about the brain that will fuel what you are doing here in your research? >> so one of the big ones is how does the visual system work.

humans are still ridiculously good at actually understanding everything around them. i don't think they're good at fencing. high resolution cameras are wonderful for fencing what's around them. but that i can pay attention to you and not the light moving around you, that the brain does for me. i don't have to think about it. watching what happens in the neurons in the brain helps understand that. >> rose: the interesting i think to me is people think about sight as a function of the eyes. it's a function of the brain. >> yes. >> rose: to a large degree. yes. that's right. well, we're learning a lot. it's interesting how much useful computation happens about here, more happens here, more happens way back here. so biology built a system where computing and sensing is together. we're engineers, so often we break it up into different

modules. >> rose: how intelligent is artificial intelligence today as we sit here in your lab? >> it can do things which, 20 years ago, we thought you had to be a professional, highly-trained human to do. interestingly, it can't do some things which a one-year-old infant can do. >> rose: give me an example of both. what would be something that a highly-trained professional can do and, today, through artificial intelligence, we can duplicate? >> okay. >> rose: the best example. okay. you're a great lawyer, very busy. you ask your assistant, hey, go and find everything else this judge ruled on for this lawsuit and see if we've got a chance of finding the matches. the assistant goes off and does it, that can be automated and seems like very high intelligence work for any training. >> rose: but you can duplicate that now? >> yes. and that's amazing because it's much more creative than something like playing chess.

you're really having to make good judgments. >> rose: so that would be useful for me to know everything you've said about artificial intelligence and i could go back and look at it and it would give me a sense of how you have responded and where your curiosity is but do it at such a rapid speed. >> exactly, yes. and it is very much those kinds of questions which involve real judgment in how you're going to summarize an answer. if i say to you what do you think of washington, d.c., it is not any good for you to give me a massive list of everything you know about washington, d.c. you have to summarize it. so getting the computers to summarize usefully. >> rose: has that been around for a while? >> it's better every year. this is the race between google, microsoft and facebook. they're trying to get their systems to do better than the other in answering these general questions. >> rose: when you say that, listing these great companies, would they all classify that as

artificial intelligence or is it simply as trying to be on the frontier of computer technology and the digital revolution? >> all four of those companies come to place like carnegie mellon and m.i.t. begging us to give them artificial intelligence researchers. the biggest game is a.i. people, yes. >> rose: what's the most surprising thing today that even the capacity to do it amazes you in terms of the velocity of change? >> so here's a couple of big surprises. we've worked so hard in robotics that almost every aspect of being able to understand the world, getting robots to act safely, move swiftly, but they still cannot reliably pick up a cup of coffee. >> rose: they can't do that. simple things where we use our hands -- >> rose: why is it so hard to do that? >> honestly, we're not quite sure. we've tried various kinds of

grippers and claws to do this, but human dexterity still blows us away, and our current understanding is our fingers and hands are amazing instruments with sensing all over them so that, as your hand is coming in to grip something, it's doing lots of computation, is this going to slip, fall, am i doing it right, and we robottists need to get our act together for that kind of thing because that's painfully slow. >> rose: how far away are you from the capacity to do that? >> it's one of the big unknown things. i estimate 50/50 chance we'll be good at it in five years. >> rose: five years. yes. >> rose: on the other hand, there are things that the human brain can do that are not even close. >> yes is that an -- yes. >> rose: and that has to do with emotions, consciousness, what else? what's a better example?

>> i think we have absolutely no idea about making a system which just makes its own decisions about what i want to do in the world. everything we build at the moment is basically a fancy calculator. it's something where we say your purpose is to do it and do it well. this thing that we humans do where we take responsibility for every aspect of our lives and make decisions for exac what weo every day, that kind of level of autonomy is not something i'm seeing in the industry anywhere at the moment. my gut tells me we're about 1935 in aeronautics. we have diesel engines, able to do really cool things, but over the horizon, there are concepts like supersonic flight and the possibility of moving -- affecting masses of ordinary people's lives. so we're very confident. you know, there is industries employing hundreds of thousands

of engineers building intelligent systems, but we can see that these glimpses over the horizon of what happens when we've got our real acts together in terms of understanding what humans want and being able to give answers to that. >> rose: i want to go back to the fact that you said apple, google, i assume amazon, i assume any company heavily into technology and has products, therefore, knows the benefit of knowing more and more about how to input artificial intelligence into those products so they can do more things. >> yes. >> rose: do they -- and when they come here to talk to you about students and what they need, what is it they say to you is important for them? what are they looking for in talent? >> the big one is -- here's one

of the things the companies are always telling me they need. not people who understand math but really like solving actual problems people are facing right now. so i very rarely have someone come in and tell me i need someone in expert of some technical aspect. they will say i need someone who is going to build me a system to give me an early warning if the crops look diseased in ecuador. >> rose: so that's artificial intelligence using sensors and everything else. >> that's right. but the best people in this industry right now are the ones trying to solve big problems through a.i., not just building a.i. for its own sake. >> rose: if you look to where a.i. may go, everyone talks about a personal assistant. you have a daughter? >> yep. >> rose: what's the world of a.i. going to make for her ten years from now? >> so here's the fun way of

looking at it -- look at celebrities, they walk around with a team of people with clip boards managing everything like let's get the car ready, make sure we have the right kind of drink for you, let's make sure you have time with your friends. so we will have technology sort of matching all this up for us, so you won't be dialing for an uber when you walk out. >> rose: it will be automatically happening. >> it will be ready. >> rose: because they will know what i like, where i am, where i have to be and want to go. >> that's right. so this idea we have very fancy concierges helping us in our lives will be fun. the important things are someone slips and falls late at night, a meter that helps them immediately. >> rose: a.i. will know this person has fallen. >> yes, exactly. so we will have machines, if we want with it, we will have machines looking out for us to

make sure that we're okay. >> rose: that's pretty close by, isn't it? is that near? at that soon? >> it's already here in that many people have sensors on them, if they have a fall, that will be sensed and the hospital will be called. what comes next, though, is if i am actually finding it harder and harder to walk upstairs every day and i don't evennote, maybe my system will call my physician who will help figure out what's happening to me. >> rose: what's interesting about this, think about the idea of all these assistants that are working for these celebrities, they're going to be out of a job. what's going to happen to them? >> that is something which we spend a remarkable amount of time talking about and, of course, we look back to the days where agriculture was a majorly intensive world. i don't think we feel bad it's not requiring hundreds of people to bring in crops in the field anymore. what we are conscious about is causing disruption while things change.

so nowadays a great career is wedding planner. that's an interesting job. that's fun. it would have seemed ludicrous ordinary people were having professional wedding planners working for them even 50 years ago. why do we have that now? because the rest of tech following enabled the more grungy pieces of work to get automated. this is the patent which you see coming up. one of my kids loves doing video game reviews, and that was a job, if you like, which would never have existed in the past. >> rose: when you build artificial intelligence to beat a game, watson beating kasparov, the results we've seen with go, is this an intelligence we've seen focused on one thing? if it, for lack of a better word, an idiot is savant? >> yes, tease things are total

idiots in that only a very smart go player is good at playing go. when we research a game it's often because they're a very clear example of a specific kind of mental event. chess and go are both games where you the humans see the whole board, you've got time to think about what your next move is and no one's hiding anything. one of the places where a.i. has gotten interesting recently in games is poker. poker is an example of a different kind of mental activity where you're playing a game but some of the things you do are not making the most sense. >> rose: they're not mathematical. or maybe they are. >> they're super mathematical but not what some would call rational. when i play poker, sometimes -- >> rose: read my eyes and face? >> -- read your face. two aspects. one party is assessing the other people. another party is deliberately

misleading. a computer playing chess always does what it thinks is a best thing. a good computer playing poker occasionally will deliberately make mistakes or trying to mislead its opponents in various ways. so when you see people using a.i. for games, it's actually to look at different aspects of intelligence. first one was problem solving. things with poker and other games of gambling are negotiation and deception and these other aspects. >> rose: can you give artificial intelligence judgment? >> you can give artificial intelligence a goal. you can say, we want you to do this, and while you're doing it, you're never allowed to do that. and then you can ask a computer to figure out what is the right way to accomplish that. >> rose: there is, as you know in many graduate schools, especially in terms of geopolitical strategy, there is

a lot of role playing. how does artificial intelligence fit in that? if russia invades a country, the u.s. should do what? >> so for those things, one of the most important things a.i. can do is it teaches us what we must never reveal. so, for example, it actually has to be the case that some of our actions are unpredictable. if you're playing poker and you always bluff, you're playing poker and you never bluff, both are disasters. you will get taken to the cleaners. sometimes you bluff, sometimes not. same in policy and the international games. it cannot be the case that the other stakeholders out there know your strategy in advance. one of the post interesting things for us a.i. folks is we're actually having to program a.i.s which are deliberately not being predictable in the way they deal with these things. for example, if you're fighting

spam email, when we build a.i.s to notice if an email is likely to be spam, those a.i.s themselves are being pretty clever about not acting in a way which tips off the spam email writers so the writers can make more effective spam. >> rose: but what in the most essential way is the challenge of creating human intelligence? what is it that is the great impediment to progress? >> well, i want to be clear about something. i don't think many of us are interested in trying to duplicate human intelligence. it's called artificial intelligence. >> rose: for a reason. the artificial is there for a reason. what we're often trying to do here is save lives or increase safety and comfort by having computers which react very quickly to emergencies or spot patterns no human could to make us safer and more comfort snoobl

and that could be essential to medical research, medical treatment? >> exactly. >> rose: because you can sense that in somebody's makeup. >> yes. >> rose: it's an insight into what they might have and supercomputers and artificial intelligence can do that analysis faster than anything. >> exactly right. it's a very interesting thing going on at the moment in cancer treatment is using computers to spot patterns as to which kind of people are going to be affected successfully by which kind of treatment, and the computers are noticing all kinds of little things going on in the battleground none of us humans ever -- in the background that none of us humans ever do. >> rose: what about

consciousness? >> consciousness is nothing any of us engineers know about. it is a complete mystery to me as a human and i would not know where to start to do a technological version of that. >> rose: i want to go through the list to ask if ma scenes would ever be able to do this. >> sure. >> rose: create original works of art. >> yes. >> rose: explain how that will happen. >> this has actually been around for a while. i can actually have a robot which throws a can of paint across a floor. >> rose: and call it art. yes. if, on the other hand, you wanted to have a computer program produce imagery which the critics love, i do also think that is quite possible, even know, and if we did a blind touring test of computer art versus human art, maybe not now, maybe five, ten years from now, a blind test you will not be able to see the difference. >> rose: what's a blind

touring test is this. >> great question. so how do you know if a computer is acting like a human? you put either computer or human behind a wall talking to you through text messaging, and we find out if you can tell if it's a human or a computer. >> rose: and if you can't, then it passes the touring test? >> yes, and that is one of the old sort of benchmarks for whether a.i. has reached human intelligence. these days we don't talk about it very often because that looks fairly easy to do. >> rose: okay, but you're telling me that you can sit on this kind of a curtain, and on the other side of the curtain is a supercomputer having the qualities of artificial intelligence, and by the text messages it sends, you cannot tell whether it's a human brain or an artificial intelligence? >> that is the touring test is to do this.

and for the moment, there has not been a convincing victory for the computer at the touring test. but it is not one of the harder things to imagine. >> rose: no one has ever had a successful test to pass the touring test. will they? >> i think so. it's very hard. >> rose: i think so? yes. like i say, i'm really confident that, within 20 years, convincingly, we will pass the touring test. but by the time it happens, it will just be like chess or calculating large multiplication tables. people will say, sure, but the computer doing that is not real intelligence. >> rose: completing my list of chores and things machines may be able to do, i think this is easy, household chores. >> that one's harder, actually. i much prefer to be given the

task of doing original works of art than household chores. as i mentioned earlier, picking stuff up in a mess, picking up a floppy object like a piece of clothing and folding it, i know it seems pun dane, but we -- mundane but we humans are geniuses at that, and the robots we build are still pretty crappy. the robot are pretty crummy when it comes to these very everyday acts of manipulation. it's going to happen, but you will have autonomous trucks driving on the freeway at 80 miles an hour before you have a robot to clean up after your kid and fold their clothes. >> rose: is it going to make us face this question, what the hell are we going to do with all our free time? >> we are going to face a question like that, but i want to warn you that this would be the same question that agriculture laborers were asking

in 1880. we don't quite know what happened. >> rose: it's been a question to come frequently in economic history. >> yes, and every time it comes up, we like to believe we're the special case, we're the really the ones who are the end of it all, but so far that hasn't happened. we do have one important choice -- suppose we all had a system that means we could do a better job at each of our jobs but only have to work 30 hours a week, would you take it? that's one way that we could actually spend the benefits that we get from a.i. we could be working 30-hour weeks instead of in the united states 60-hour weeks and share the benefit that way. or we could say half of you keep working 60-hour weeks, the rest of you, you're unemployed, and that sounds to me like a worse future. >> rose: this will be a tough question, how we handle the job market implications of artificial intelligence.

>> it is interesting that, now, at places like carnegie mellon, the students, part of what they learn are thinking about these questions. you're no longer thinking just about the technology, you are thinking about the sideline implications. >> rose: do the kids who come here to study artificial intelligence at carnegie mellon, i mean, is there a basic core course of computer science, or what is the core course they're studying? >> when they are at high school, we feed them to have loved math. math is the center of all a.i. once they come to a place like carnegie mellon, they learn about algorithms, which is how a computer is organized, how they're going to solve tasks. then they study things like computer vision and machine learning and all these disciplines which really are about replacing different parts of the human brain. >> rose: at what age did your daughter learn to code?

>> at ten, she was able to code which i thought was pretty respectable. >> rose: did she do that on her own or because you encouraged her to do it? >> that's a very common thing. she is sur rounded by friends and family who are all geeks and, so, she becomes a geek herself. >> rose: like father, like daughter? >> yep. >> rose: are we facing what many might call a fourth industrial revolution? >> i think it is -- >> rose: or is it here? it is happening. i think we're in the first few years of it. ever since things like travel agents became irrelevant because it's easier to do with a computer now for all of us, that is when it started, and we're now getting into full swing. i think it will be 2020 that we see that, wow, whole areas of what we used to think as what only people could do can now be

done better with having computers help them. >> rose: is this part of the sharing economy? >> the sharing economy is an interesting side aspect of a.i. it's where you're getting groups of people together to solve problems by -- i've got to have another go at this. let me describe it more clearly. the sharing economy is a way in which people can do what they are really good at. so if i'm really good at writing, and you're really good at planning, we make sure that you do what you're good at and i do what i'm good at and then we will win. so i think the computers help organize us so the right people are doing the right things. >> rose: and sharing in the way uber provides a way to take someone somewhere. >> yes. >> rose: what can be the

companies in the industries and sectors that are disrupted most by artificial intelligence? >> the ones which are really coming up in my mind are what we might have originally called white-collar work, like the legal profession and some parts of the medical profession with extremely high training and expertise. so these are ones where computers are actually able to make some of these judgment calls. a doctor facing lots of contradictory information actually figuring out what the problem is or a lawyer who has to sift through a vast familiar of information to find the actual solution to a difficult problem, that i can also make. interestingly, something like a nurse or a teacher whose real job is understanding the people that they're interacting with all the time, that i find much harder to auto mate. i don't see those disappearing for a decade. >> rose: artificial

intelligence is changing life as we know it. >> yes. >> rose: obvious. yes. >> rose: and when you sit around and you blue-sky this, so ten, 15, 25 years from now -- just take 25 years from now, we're in 2016, right before 2050, where do you think artificial intelligence will be? >> i hope that the world will be a much safer place. >> rose: safer? safer. when disasters happen, there will be fleets of robotic devices coming in to render aid, very first triage to get people to safety. remote vehicles to pick up severely injured folks, large pieces of heavy equipment coming in to move things that are in the way. you can imagine a world in

which, just like now, we've learned how to build houses to protect us from the elements, we're actually using machines to give a far greater protection, then for the 50% of the plant currently living their life in fear almost every year of what's going to happen to them, they may have a more secure and pleasant life. >> rose: you can't stop technology. >> that's right. and if we the united states said, well, we're not going to do this, then we could just sit on our hands and let europe and asia do it. we're not going to want to do that. that is not what the united states is all about. >> rose: so who stops us? our collective will stops us? or is it a legislative function? is it some ethics board that decides here but no further? >> the place that we need legislative help is to answer some uncomfortable questions

which we will need answers in order to save lives. for example, when you're programming an autonomous vehicle, a car to minimize casualties in an accident, who decides whether that car should be protecting the driver or the person that's being crashed into? i don't want the engineers to decide that. i don't need to decide that. >> rose: do you want congress to decide that? >> i know it sounds impossible, but i want congress to decide that. >> rose: yeah. what worries you the most about this forward progress of artificial intelligence? >> i worry that it's very stressful for people to live through times of change, and this is a time of change, and it is going to cause great anxiety, and all the economic theories and experience we have saying that disruption occurs, people get new jobs and life goes on,

and we progress, the frightening part of that, of course, is, during the disruption, a lot of people are displaced and they will have a harder time than they might have otherwise. >> rose: that's the kind of impact amazon had, isn't it? amazon was the new business model, using technology, all online, and it was disrupting the business of book stores around the world. >> absolutely, yes. it is the story of the technology. it is the story of the united states for the last 200 years. we have constantly found better, more effective ways to do things, but you cannot do that and not think about the consequences to all the people who have been trained to do something, which are now automating. >> rose: this is what intrigues people, this question. you have people like elon musk, you have stephen hawking saying it could spell the end of the human race -- stephen hawking

saying that. elon musk said it's the most existential threat we face. so here are pretty smart guys saying, watch out. do we know what we are creating? >> it is worth being extraordinarily careful about all these things. i will put this up there with yes genetic modification of foo. i know it sounds crazy but if we put things in interstellar space, some extraterrestrials could spot us. these are things to think about. but to make the distinction, what we are building here and in robotics institutions around the world, the equivalent of really smart calculators which solves specific problems. >> rose: okay. is having artificial intelligence that's smarter than you are, is that bad?

>> if i was really worried about that, i would already be really unhappy because i know that there are billions of people smarter than me out there at the moment. we all know that there are many, many smarter people and smarter organizations than us at the moment, so i don't think we are affected by smarter people. rose: let's not use you as an example. >> all right. >> rose: artificial intelligence that could outthink the human population. my question that intrigues me is who controls the artificial intelligence, because we're talking about artificial intelligence being created by engineers, scientists. >> yes. >> rose: but could it go out of control? >> no one knows how we go about building something that frightening. that is not something that our generation of a.i. folks can do. it is well possible that someone 30 or 80 years from now might

start to look at that question. at the moment, though, we have the word artificial and artificial intelligence. i am dreadfully worried about releasing software for economists which turn out to have a very serious bug which means on the leap day all the cars stop on the freeway because they had a bug in their code. that could kill tens of thousands of people. that is a very real question and responsible engineers have got to have responsible ways of validating and proving their systems are safe. >> rose: what's the difference between artificial intelligence and super intelligence? >> artificial intelligence is a real technology just like steel or hired electric power to make our lives safer. super intelligence is an intriguing science fiction

concept like meeting aliens or having nanobots crawling through our veins. >> rose: but i can tell you thing after thing in which science fiction became reality. >> that's absolutely true. plenty of stories do involve the frankenstein story, and we're all concerned about this model of an eager scientist producing some compound which they thought would do good but turns out to do bad. modern engineering, we tell our students you do not release something without testing it. it's illegal to release something safety critical without havin having the detail. >> rose: make sure you understand the consequences and collateral damage. >> yes. when you look at what's happening in a large company or

universities, usually what's happening in a large company is producing complicated pieces of equipment, much more effort goes into testing it. most projects, 10% of the work is inventing things, 90% of the work is testing to find out any scenarios in which it can cause trouble. that is what frightens me is if we a.i. people, you know, are exciting at getting this stuff out there don't test enough and some of our robots, instead of saving lives, inadvertently hurt people. >> rose: that's what keeps you up late at night, that fear. >> yes. >> rose: we haven't tested it, it goes out of control and spreads like wildfire? >> yes. the early days if computerring -- computing in medicine saved millions of lives as we know, but in the early days there were some computer programs which accidentally made pieces of medical equipment go

out of control and actually kill patients. what happened then is the computer scientist realized you have to have very detailed testing procedures. we don't want to make the same mistake with robots. we are smart enough to know we have to test this stuff. i, frankly, know it's not ethical to release autonomous vehicles on the road, for example, right now until we have some governmental standards for safety. >> rose: but it's coming? yeah. >> rose: it's really coming? yeah. >> rose: what about this -- through the power and progress and rapid increase in potential of artificial intelligence, some mad person who happens to have all the smarts in the world takes advantage of all the other learning in the world and programs some robot or some other kind of thing to do

destructive acts, perhaps racial, perhaps antisocial, perhaps terrifying communities. is that a scenario? could that happen? >> it absolutely could. every piece of technology which can improve the human condition can also be used to damage the human condition. iabsolutely believe, unfortunately, though right now there are people in various parts of the world figuring out how to put explosives on to drones, amateurs even who learned how to do this stuff on the internet, and just as we have metical treatments where there have to be controls on disease agents people come out with, we as a society have to understand that technology will be used by evil people as well

as good people. >> rose: just think about the horror. we already have people who are terrorists who are willing to die for their cause, and, so, they're willing to blow themselves up. think about how much larger that potential would be, you know, if you could multiply that and somehow get inside of -- you know, and do things on such a large scale? >> so i am worried about all kind of active terrorism which can happen now. >> rose: that's my point. and there are many folks using tools from artificial intelligence and machine learning to help quickly react or even prevent these kinds of disasters. so, for example, after the boston marathon bombings, there was very limited visual information about possible suspects, but it was possible

then to use computer vision, automatic methods to sift through all the information from all the videography around at the time to help quickly determine the potential suspects. so while i agree that there is a real danger of people using robots for evil, the solution for us to sit on our hands and say we nee don't need to do robt work, we need to use robots to help people. >> rose: how about used by the military? the ability to use anything autonomous to advance into places tha that seem too dangers to do otherwise. >> in the last 40 years cruise missiles have been using artificial intelligence to route

themselves efficiently. >> rose: and drones, too. yes. so understanding the world for surveilling and getting a sense of where there are dangers, a.i.'s been in use for more than a decade in these kinds of areas. the military is also investing in experimental robotics, not just flying drones but ground-based drones, water-based robots and underwater robots to do surveilling when it's too dangerous for people. >> rose: i have to believe the military is doing this. they need protection. they want to know what the other person is doing it so they've got to figure out how they'd do it if they were doing it and then you have to figure out what the antidote is to it. >> yes. one thing noticed during the wars to have the last decade is the u.s. soldiers asked friends from home to send them remote control vehicles because they actually felt safer piloting a toy vehicle into an area in

order to see what was going on. >> rose: because of land mines. >> yeah. and this was just hobbiest folks in the military. so there is plenty of these things happening as government programs to use small robots to protect the lives of troops. >> rose: the interesting thing -- and i may be wrong about this -- the interesting thing, it seems to me, is this is not just what nation states are doing, this is what a role range of -- a whole range of people who are very smart who are operating computers, accessing the internet or creating software, and that's creating a whole range of people to do a whole range of things. >> yes, and one of the -- when you look at the world this way, it's the countries or the

organizations which have got the trained, marked people who are the ones to prosper in this situation. so i would not like to be a country who had very few mathematicians because that would indicate that the technical people are eventually -- >> rose: does china have a lot more math metations than we do? >> for people, more mathematicians. >> can't put this on math and science, then. >> that's right. >> rose: and computer science, especially. >> yes. so if i'm looking what the natural resources are for a successful country in the 21s 21st century, it is the number of math-trained branles. it is not the amount of oil. >> rose: could i make this even more precise that, as we look at the contest, it's not a zero-sum game, among nations, those that have the most capable and proficient and innovative

use of artificial intelligence are going to be in a commanding place? >> yes, absolutely. you see this even now. it is more groups of smart people who start the $100 billion companies. i really do profoundly believe that the united states, which has led for the last 60 or 70 years in technology, still can lead here, and i want it to, because i want us to build the auto mated planet that respects human life and values. you mentioned earlier the question of where does the military go to find these brilliant people? they go to places like silicon valley. the main thing we think about now is the care and feeding of young tech geniuses. the reason places are going to

places like silicon valley is the young tech geniuses want to live in cool places. the reason pittsburgh is cool now, we're getting an influx. >> rose: and the same way palo alto and a few places like that. >> exactly. if you want to build up a great a.i. workforce, you need to have an environment where people can explore crazy ideas. >> rose: is it in our national interest to share? >> if you want to get your idea out there and used by billions of people, your best bet is to do a startup if the united states with viral marketing which gets the whole world using it. so in that sense, yes, everyone wants the rest of the world the share what they're doing. there is trade secrets and military secrets at the same time, and one of the things you learn in either of these environments is you come across some great technical idea, you're not going to hold on to it forever. you better use it right now because someone else will come up with the idea or the

technology will change and completely wipe away that advantage. >> rose: you know both as a former vice president of google, you know as -- you know the business side as well as the scientific side, is it reasonable to expect somebody like google to want to be as secretive as possible about this because the competition is so intense? >> does make sense to protect new technology, usually it is by keeping it secret rather than patenting it these days. >> rose: that's the model these days, keep it secret, don't patent it? >> correct. here's the fascinating thing about the game at the moment. remember, getting the a.i. experts is the most important thing, so you have to have them be happy and motivated. telling someone to come work for you, to do something which, like your parents are never going to see or know about, is not motivating.

so to get the best people in your companies and organizations, you actually want to give them the ability of what they're doing. so it is not the case you have long-term secrets about technology anywhere. "we" as people employing a.i. experts, actually part of what we're doing is we tell you you're saving the world, changing the world, and we want you to be part of it. >> rose: and you become heroic and pap lore if -- popular if you do and we know about it. >> yes. >> rose: talk to me about the i.b.m. business model. is it the best one? >> i have real respect for what i.b.m. is doing at the moment, where any of the big internet companies are going directly for bringing a.i. to consumers like u and me, i.b.m. is really focusing its business at the moment about bringing a.i. to the other fortune 500 companies who are going to need it and who

do not have that expertise for themselves. >> rose: but they do they choose this cognitive assistance as the route to go rather than the route that google has chosen? your former employer. >> i'm going to say google and i.b.m. are both going after forms of cognitive assistance. one of them, google's, is all around going out directly to help user user who is using google's ap applications and tag on google apps. i.b.m.'s model is to use it to empower all the other companies, car companies, hospitals, and put a.i. into their systems. they're both viable business models and not in competition. >> rose: there are both ethical problems involved here, clearly. >> yes. >> rose: who should be deciding? is it government? >> one thing for sure, it's not me and it's not engineers. we do need to make some

difficult decisions. for example, we can program a car to act various ways in a collision to save lives. someone has to answer questions like, if the car tried to protect the person inside the car more than the person it's about to hit, that's an ethical question which the country or society probably through the government has to actually come up with before we can put the safety into vehicles. >> rose: speaking of the government, are we at the risk of creating an a.i. arms race? >> there is a technology race in computer science which has been there for decades, and it is going strong at the moment. >> rose: the race has gotten more intensive. >> yes. >> rose: there is more of a feeding frenzy, so to speak? >> yes. >> rose: and is it all behind closed doors? >> no. interestingly, much of the most exciting stuff going on in a.i.

still gets published. there is annual conferences. when something called the american association of artificial intelligence. if you are doing something cool in a.i., the absolute best thing that happens to you is if you get a paper accepted by that conference and you get on the world stage of what's going on -- >> rose: because everybody in the world that has resources and is a competitor in terms of the big deals in america, whether private or public, they want the smart people. it's like an n.f.l. draft? >> it's very much like that. in fact, so much so that at carnegie mellon, we are now planning on sending talent scouts out to high schools and even middle schools to find these people. >> rose: you know what i like about this? we want more people to care about science. we want young people to be as interested in science as they are in becoming a rock star or an n.f.l. star or an n.b.a. star

so that science, because of its consequences, is a place where people know they can do well, do good and be celebrated. >> it's like magic. the thing i tell middle schoolers is the closest thing to getting to go to hogwarts is being able to do robotics and a.i. >> rose: what part of this would you most like to be involved in? i mean, you're here because it's one of the centers for what's happening both in terms of students but in terms of ideas. what excites you the most? what gets you revved up? >> part of the reason i moved from industry to carnegie mellon is that the whole game over the next few decades is won or lost according to talents of the

people building these systems. if they do it well, the year 2014 could be the best year to be alive in the history of the human race. but if we screwed up, it could be pretty disastrous. so right now the thing which motivates me personally is all the 12-year-olds or 15-year-olds around the united states, if they love anything to do with math or programming or computers, they have to take this seriously. they should get involved. so that's why i'm in this business. i have to get them involved. >> rose: it's one pathway to unlock the future of the world. >> yes. >> rose: for for more -- for more about this program and earlier episodes, visit us online at pbs.org and charlierose.com. captioning sponsored by rose communications captioned by media access group at wgbh access.wgbh.org

>> rose: funding for "charlie rose" has been provided by: >> and by bloomberg, a provider of multimedia news and information services worldwide. >> you're watching pbs.

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