Do you trust this computer? | Elon Musk recommended | Doc:02
On. The brink of is, a world, of increasingly. Intense. Sophisticated. Artificial. Intelligence. Technology. Is evolving so much faster than, our society, has the ability, to protect, us as citizens. You. Have a networked intelligence that watches us knows. Everything about us and, begins, to try to change us. Technology. Is never good or bad it's what we do with the technology. Eventually. Millions. Of people are going to be thrown out of jobs because their skills are going to be obsolete. Unemployment. Regardless. Of whether to be afraid or not afraid the. Change is coming, and nobody can stop him. We've, invested huge amounts of money and so it stands to reason that the military, with, their own desires, are, gonna start to use these technologies. Autonomous. Weapons systems, would lead to a global arms race to, rival, the nuclear, era. So you know what the answer is they'll. Eventually be killing us. These. Technology. Leaps are gonna yield incredible. Miracles, and. Incredible. Horrors. We. Created it. So. I think as we move forward this, intelligence. Will, contain parts of us. But. I think the question is will. It contain the good parts. Or. The bad parts. The. Survivors, called the war Judgment. Day, they. Lived only to face a new nightmare. Against. The machines. I, think. We completely. Us up I think. Hollywood has managed to inoculate the, general public against, this. Question, the. Idea of a machines that will take, over the world. Open. The pod bay doors, oh, I'm. Sorry. Dave I'm. Afraid I can't, do that. Al. We've. Cried wolf enough times out the public has stopped paying attention because, it feels like science fiction even sitting here talking about it right now it feels a little bit silly a little bit like oh this, is an artifact, of some. Cheeseball, movie the whopper, spends, all its time thinking. About World, War three, but. It's not. The. General public it is about to get blindsided, by this. As. Is, decided as individuals, we're increasingly. Surrounded. By a machine intelligence. We. Carry this pocket, device, in, the palm of our hand that we use to make a striking. Array of life decisions, right now aided. By a set of distant, algorithms, we have no understanding. It's. Already pretty jaded about the idea that we can talk to our phone and that mostly. Understands, us. Years. Ago no, way. Robotics. Machines, that see and, speak, and listen all that's real now and these, technologies are. Going to fundamentally change our society. Now. We have this great movement, of the self-driving cars. Driving. A car autonomously. Can move people's, lives into a better place. I've. Lost a number of family members including my mother my, mother and sister-in-law and their kids to, automobile, accidents, it's. Pretty clear we, can almost eliminate, car. Accidents, with automation. 30,000. Lives in the US alone, about a million around the world per year. In, healthcare early, indicators, are the name of the game in that space so. That's another place where it can save somebody's life. Here. In the breast cancer Center all the things that the. Radiologist brain does in, two. Minutes, the computer goes instantaneously. A computer. Has looked at 1, billion mammograms. And it takes that data and applies, it to this image instantaneously. So. The medical application, is profound. Another. Really exciting area that we're seeing a lot of development, and is actually. Understanding, our genetic, code and. Using that to both, diagnose, disease and create personalized, treatments. The. Primary application, of all these machines will, be to extend our own intelligence. We. Were able to make ourselves smarter and, it, will be better at solving problems. Because. I'll have to age will actually have to stay on Aging we'll be able to stop it. There's. Really no limit to what intelligent, machines can do for the human race. How. Could a smarter, machine not be a better machine. It's. Hard to say exactly when, I began, to think that that was a bit naive. Stuart. Russell he's basically, a God in the field of artificial intelligence he, wrote the book that, almost every University uses, I used. To say it's the best-selling AI. Textbook, now I just say it's the PDF that stolen most often. Artificial. Intelligence, is, about making computer smart and from. The point of view of the public what, counts as AI is just, something that's surprisingly. Intelligent compared, to what we thought computers. Would typically be able to do. AI. Is. A field, of research to. Try to basically, simulate. All kinds, of human capabilities.
We're. In an AI era. Silicon. Valley has the ability to focus on one bright, shiny thing it, was social, networking in social media over the last decade, and it's pretty clear the bit has flipped and, it starts, with. Machine learning when. We look back at this moment what was the first AI it's. Not sexy, and it isn't the thing we consider the movies but you'd make a great case that Google. Created. A search engine but a God had a, way. For people to ask any. Question they wanted and get the answer they need it most. People are not aware that what, Google is doing is, actually a form of artificial intelligence they. Just go, there they type in a thing Google, gives them the answer, with. Each search we. Train it to be better sometimes. We type in the search and it tells us the answer what you finished, asking the question. You. Know who is the president. Of Kazakhstan and, it'll just tell you you. Don't have to go to the Kazakhstan, national website to find out didn't. Used to be able to do that, that. Is artificial, intelligence, years. From now when we try to understand, we. Will say well how do we miss it it's. One of these striking. Contradictions. That we're facing Google, and Facebook at all have built businesses on, giving us as a society free, stuff but. It's a Faustian, bargain they're. Extracting. Something, from us in exchange. But. We don't know what, code is running on the other side and why we have no idea. It. Does strike right at the issue of how much we should trust, machines I. Use. Computers. Literally. For everything. There's. So many computer, advancements. Now and, it's. Become such a big part of our lives it's just incredible. What a computer can do you can actually carry a computer in your purse I mean. How awesome, is that, I think. Most technology, is, meant. To make things easier and simpler for for, all of us so. Hopefully. I just remains the focus I think. Everybody, loves, their computers. People. Don't realize they, are constantly, being negotiated. With, by. Machines. Whether. That's the price of products in your Amazon cart whether. You can get on a particular, flight whether. You can reserve a room at a particular hotel, what. You're experiencing. Our machine, learning algorithms, that have determined that a person, like you is willing to pay two cents more and is changing the price. Now. Computer, looks at millions. Of people simultaneously, for, very, subtle, patterns. You. Can take seemingly. Innocent. Digital, footprints, such as someone's. Playlist, on Spotify or. Stuff, that they bought on Amazon, and then. Use algorithms, to translate. This into a very detailed and very accurate, intimate. Profile. There. Is video CA on each of us that is so extensive, it would, be possibly, accurate, to say that they know more about you than your, mother does. Major. Cause, of the recently I breakthrough, it isn't just that some dude. Had a brilliant insight. All, of a sudden but, simply, that we have much bigger data, to train them on and vastly. Better computers. The. Magic is in the data it's. A ton of data, I mean, it's data that's never existed before we've never had this data before. We've. Created, technologies. That allow us to capture vast. Amounts, of information, if. You think of a billion, cell phones on the planet with gyroscopes, and accelerometers. Fingerprint. Readers couple, that with the GPS, and the photos they take and the tweets that you send we're. All giving off huge. Amounts of data individually. Cars. That drive as the cameras, on them suck up information about the world around them the satellites, that are now in orbit the size of a toaster, the infrared about, the vegetation, on the planet the boys that are out in the oceans defeating into climate models.
And The, NSA the. CI is they collect information about, the geopolitical, situations. The. World today is literally swimming in this data. Back. In 2012. IBM. Estimated. That an average human being leaves, 500. Megabytes, of digital. Footprints, every, day if. You wanted, to back up only, one day worth of data that humanity, produces, and you, print it out on a letter size paper, double-sided. Font. Size 12 and, you, stack, it up it, would reach from the surface of the earth to the Sun. Four. Times over this. Every day. The data itself is not good or evil, it's how it's used we're. Relying really. On the goodwill of these people and on the policies. Of these companies there. Is no legal requirement for. How they can and should use that kind, of data that to. Me is at the heart of the trust issue. Right. Now there's a giant race for creating machines, that are as smart as humans Google. They're working, on what's really the kind of Manhattan Project of artificial intelligence they've, got the most money they've, got the most talent, they're, buying up AI companies, and robotics, companies. People. Still, think of Google is a search engine and their email provider and, a lot of other things that we use on a daily basis but. Behind, that search box are. 10, million servers. That. Makes Google the most powerful, computing, platform, in the world Google. Is now working on an AI computing. Platform, that will have a hundred, million servers. So. When you're interacting with Google we're just seeing the toenail, of something that is a giant, beast in the making and the. Truth is I'm not even sure that Google knows what it's becoming. If. You look inside of what algorithms, are being used at Google it's. Technology, largely, from the 80s. So. These are models that you train by showing them a 1 a 2 and a 3 and it, learns not what a 1 is or what a 2 is it learns what the difference, between a 1 and a 2 is it's. Just a computation. In. The last half, decade where we've made this rapid progress it has all been in pattern recognition. Most. Of the good old fashioned, AI, was. When we would tell our computers, how to play a game like chess, from.
The Old paradigm. Where you just held a computer exactly what to do. The. IBM, challenge. No. One at time had, thought that a machine could have the precision and, the confidence, and the speed to, play jeopardy well enough against the best units let's, play jeopardy. Four. Letter word for the iron fitting, on the hoof of a horse Watson. What is shoe you are right you get to pick literary. Character, APB, for 800, and, so for Daily Double. Watson. Actually got its knowledge by reading Wikipedia and. 200, million pages of natural language documents, you can't program every. Line of how the world works, mushiya. Has to learn by reading now. We come to Watson, who, is Bram Stoker. And. Hello. 41:13. And a to date. Watson's. Trained on huge, amounts of text, but. It's not like it, understands, what it's saying it. Doesn't know that water makes things wet by touching water and by seeing the way things behave in the world the way you and I do a lot. Of language, a itay is not building, logical. Models of how the world works rather, it's looking, at how, the words, appear. In the context, of other words. David. Ferrucci developed, IBM's Watson and somebody asked him this, Watson to think and he. Said does a submarine, swim. And. What he meant was when they developed submarines they borrowed basic principles, of swimming. From fish, but. A submarine, swims farther and faster than fishing Canaria huge payload without swims fish. Watson. Winning the game of Jeopardy will, go down in the history of AI as the significant, milestone. We. Tend to be amazed when the Machine does so well I'm even, more amazed when, the computer, beast humans and things that humans are naturally, good at this. Is how we make progress. In, the early days of the, Google brain project I gave the team a very simple, instruction, which was built, the biggest neuro Network possible, early, 2000, computers. In. Your net is something very close to a simulation of how the brain works it's. Very probabilistic. But, with. Contextual, relevance, in, your, brain you have long neurons that connect to thousands, of other neurons and you have these pathways that are formed and forged based on what the brain needs to do when. A baby tries, something and it succeeds there's a reward and, that, pathway. That created, the success is strengthened, if, it fails at something the, pathway is weakened and so over time the brain becomes honed to be good at the environment, around it. Really. It's just getting machines to learn by themselves is, it called deep learning and deep learning and neural networks mean roughly the same thing. Deep. Learning is, a. Totally, different approach where. The computer learns more like a toddler, by. Just getting a lot of data and eventually. Figuring. Stuff out, the. Computer just gets smarter, and smarter as it. Has more experiences. Let's. Imagine if you will the neural network you know like a thousand computers, and the, weights are not knowing anything and we, made it watch YouTube, for, a week. And. So. After watching YouTube for a week what were they learn we, had a hypothesis, they'll learn to detect commonly occurring objects, in videos. And so we. Know the human faces appear a lot in videos so we looked and lo and behold there was a neuron that had learn to detect human faces. Know. What else appears in videos. A lot. So. We looked and saw surprise there was actually a neuron, and that had learn to detect cats I.
Still. Remember see recognition. Wow, that's a cat okay cool great. It's. All pretty innocuous when you're thinking about the future, it, all seems kind of harmless in benign. But. We're making cognitive, architectures, that will fly, farther and faster than us and carry a bigger payload, and they, won't be warm and fuzzy I think. That in three to five years you will see a computer system that will. Be able to autonomously. Learn. How. To understand. How to build understanding. Not. Unlike the way the human mind works. Whatever. That lunch was it was certainly delicious. Simply. A sum, of Robbie synthetics, is, your cook to even. Manufactures, the raw materials, come round, here Robbie. I'll. Show. You how this worked. One. Introduced, is a sample, of human food through this aperture. Down. Here there's a small built-in chemical. Laboratory, where he analyzed, it later he can reproduce identical. Molecules in in any shape or quantity a spiced. Cream. Meat. Baxter, revolutionary. New category, of robots, with common sense Baxter. Baxter, is a really, good example of the kind of competition we face for machines. Baxter. Can do almost anything we can do with, our hands. Baxter. Costs about what a minimum-wage. Worker makes in a year but. Baxter won't be taking the place of one minimum-wage worker he'll be taking the place of three because they, never gets hired they never take breaks. That's. Probably the first thing we're going to say, displacement. Of jobs they're. Going to be done quicker faster cheaper, by, machines. Our. Ability to even stay current is so insanely, limited, compared, to the machines we built. For. Example now we have this great movement, of uber and lyft are kind of making transportation cheaper, and democratizing, transportation, which is great the. Next step is going to be that the argument fades by travellers cars and then, all the uber and lyft drivers had to find something new so -. There. Are four, million professional, drivers, in the United States they're. Unemployed soon. 7. Million people to do data entry those. People are going to be jobless. A job. Isn't just about money, right. On a biological, level it serves a purpose becomes. A defining, thing when. The jobs went away in, any given civilization, it doesn't take long until that turns into violence. We. Face a giant divide between rich and poor because that's what automation. And AI will provoke or a greater divide between the haves and have-nots. Right. Now it's working into the middle class into white-collar, jobs. IBM's. Watson does. Business analytics, that we used, to pay of business, analysts $300, an hour to do. Today. You come at a college to, be a doctor to be an accountant, to be a journalist, it's, unclear that there's gonna be jobs there, for you. If. Someone's planning for a 40 year career in radiology. Just reading images, I think that could be a challenge to the new drivers of today. But, today we do a robotic, case. The. Da Vinci robot. Is currently, utilized by, variety. Of surgeons for, its accuracy. And its ability to avoid. The inevitable. Fluctuations. Of the human hand. Anybody. Who watches this feels, the amazingness, of it. You. Look through the scope and you seen the, claw, hand, holding. That woman's ovary, humanity. Was resting, right there, in the hands of this robot. People. Say it's. The future but it's not the future, it's. The present. If. You think about a surgical robot there's, often not a lot of intelligence in these things but over, time as we put more and more intelligence, into these systems the, surgical robots can actually learn from each robot, surgery, they're tracking the movements, they're understanding, what worked and what didn't work and eventually. The robot for routine, surgeries, is going to be able to perform, that entirely, by itself or. With human supervision. Normally. I do about 150 cases of hysterectomies. Let's say and, now. Most. Of them are done robotically. I do. Maybe one open case a, year so. Do I feel uncomfortable. Because. I had. To open bases anymore. It. Seems that we're feeding it and creating it but in. A way we. Are slave, to. The technology. Because. We. Can't go back. The. Machines are taking bigger and bigger bites out of. Our, skill set that are never increasing, speed, and. So we've got to run faster, and faster to keep her here to the machines. Are. You attracted, to me what, are you attracted, to me it. Gives me indications, that you are I. Do. Yes. This. Is the future we're headed aim to it we, want to design our. Companions. We're. Gonna like to see a human face on the I therefore, gaming. Our emotions, will be depressingly. Easy. We're. Not that complicated. Simple. Stimulus response I, can. Make you like me basically by smiling at you a lot. Yeah. Ours are gonna be fantastic of. Manipulating, us. So. You've developed a technology, that, can, sense, what people are feeling right.
We've Developed technology, that can read your facial expressions, and map that to a number of emotional, states, fifteen. Years ago I, had just finished my undergraduate. Studies, in computer science and it struck me that I was spending a lot, of time, interacting. With my laptops on my devices yet, these devices, had absolutely, no clue how. I was feeling I. Started. Thinking what if this device could sense that, I was stressed or I was having a bad day what, would that open up. For. You can. I get a hug. We. Had kids interact, with the technology a lot, of it is still in development but. It was just amazing. Who likes robots. Ask. My mom really, hard math questions. Okay. We're. Scaring, people, all. Right so start by smiling. Nice. Brow. Furrow. Nice. One eyebrow raised this. Generation, technology. Is just surrounding, them all the time. It's. Almost like they expect to have robots in their homes and they expect, these robots to be socially intelligent. What. Makes robots, smart. Put. Them in like a math, or biology class. I, think. You would have to train, all. Right let's, walk over here. So. If you smile and you raise your eyebrows it's gonna run over to you. But. If you look angry it's gonna run away. We're. Trading computers, to read and recognize emotions. And. The response so far has been really amazing people are integrating, this into health apps meditation. Apps robots. Cars. We're. Gonna see how this unfolds. Robots. Can contain, AI but. The robot is the physical, instantiation and, the artificial intelligence is the brain and so, brains can exist purely in software based systems they, don't need to have a physical form, robots. Can exist without any artificial intelligence, we have a lot of dumb robots out there, but. A dumb robot can be a smart, robot overnight, given, the right software, given, the right sensors. We. Can't help but impute. Motive into inanimate objects, we do it with machines we'll. Treat them like children we'll, treat them like surrogates. And. We'll. Pay the price. You. Get welcome to that yeah. My. Purpose is to have more, human-like robot, which has the human right the intention, desire.
The. Name, of the robot is Erica. Erica. Is the most advanced. Humanoid. Robot, in the world I think, Erica. And I can gaze at your face. Only. To our. Properties. And be pretty with the conversational partners, especially for. The Averys, and young children's, handicapped. People's, ideas, when. We talk to the robot we don't fear the social, barriers social, pressures. And. Finally. Everybody. Except. The, Android. As just. Our friend we're partners. We. Have implemented, a simple desire, and, she wanted to be a well, recognized, and she wanted to arrest. If. A robot could have an intention there's Oreos the robot can understand, other, people's. Intention, desires. That. Is tied relationships. With people and that means they like each other. That. Means well. I'm not sure and to, rub each other. We, build about official intelligence, and the very first thing we want to do is replicate us. I think. The, key point will, come when, all the major senses. Are, replicated. Sight. Touch. Smell. When. We replicate, our senses, is that when it becomes alive. So. Many of our machines are being built to understand, us. But. What happens with an anthropomorphic creature, discovers, that they can adjust their loyalty. Adjust, their courage. Adjust, their avarice adjust they're cutting. The. Average person they, don't see killer robots going down the streets they're like what are you talking about. Man. We. Want to make sure that we don't have killer robots going down the street. Once. They're going down the street it is too late. The. Thing that worries, me right now that keeps me awake is. The. Development, of autonomous weapons. Up. To now people, have expressed unease, about drones. Which. Are remotely piloted aircraft. If. You take a drones camera feed it into the AI system it's. A very easy step from, here to. Fully, autonomous, weapons that choose their own targets, release. Their own missiles. The. Expected, lifespan of a human being in, that kind of battling environment, will be measured in seconds. At. One point drones, or, science fiction and now. They've become the, normal, thing and war. There's. Over 10,000. In the US military inventory. Alone, but. They're not just a u.s. phenomenon there's, more than 80 countries that operate, them. It. Stands to reason that people. Making some of the most important, and difficult decisions in the world are, gonna start to use and implement artificial. Intelligence. The. Air Force just designed a four hundred billion dollar jet program to put pilots, in the sky and, a. $500. AI, designed.
By, A couple of graduate students as being, the best human pilots with. A relatively, simple algorithm. I. Know. I will have as big an impact on, the military as, the. Combustion engine had. At the turn of the century that, will, literally touch everything, that the military does from. Driverless. Convoys, delivering. Logistical, supplies to. Unmanned. Drones delivering, medical. Aid to, computational. Propaganda. Try and win the hearts and minds of the population, and so. It stands to reason that, whoever. Has, the best day I will, probably achieve dominance on this planet. At. Some point in the early 21st century all of mankind. Was united in. Celebration we. Marveled. At our own magnificence as, we gave birth, to a. In artificial intelligence a singular, consciousness that spawned an entire race, of machines. We. Don't know who struck first us, or them but. We know that it was us that scorched, the sky. There's. A long history of science fiction not just predicting, the future but, shaping, the future. Arthur. Conan Doyle riding. Before World, War one honor the danger of how, submarines. Might. Be used to carry out civilian. Blockades. At. The time he's writing this fiction the. Royal Navy made. Fun of Arthur, Conan Doyle for this absurd, idea, that, submarines, could be useful in, war. One. Of the things we've seen in history is that our attitude. Towards, technology but. Also ethics. A very context. Dependent, for example the submarine, nations. Like Great, Britain and even the I states found it horrifying, to use the submarine, in. Fact. The German use of the submarine to carry out attacks was, the reason why the United, States joined, World War one. But. Move the timeline forward. The United States, of America, was, suddenly and, deliberately. Attacked by, the Empire, of, Japan, five. Hours, after Pearl Harbor, the. Order goes out to, commit, unrestricted. Submarine warfare, against. Japan. So. Arthur, Conan Doyle turned out to be right. That's. The the great old line about science fiction it's, a lie that tells the truth fellow. Executives, it, gives me great pleasure to introduce you to the future of law, enforcement, edie 209. This. Isn't just a question of science fiction this, is about. What's next about what's happening right now. The. Role of intelligent. Systems is growing very rapidly in, warfare. Everyone. Is pushing in the unmanned, realm. Today. Secretary. Of Defense is very very clear we will not create fully autonomous, attacking, vehicles, not. Everyone, is going to hold themselves to that same set of values and when, China and Russia and start deploying, autonomous. Vehicles. That can attack and kill. What's. The move that we're gonna make. You. Can't say well we're going to use at homeless weapons for our our military dominance but no one else is. Going to use them if, you make these weapons they're, going to be used to attack, human.
Populations, In, large numbers. Autonomous, weapons that by. Their nature weapons, of mass destruction because it doesn't need a human being to guide it or carry it you, don't need it one person. To. You know write a little program. It's. Just captures, the. Complexity. Of this field it, is cool it is important. It is amazing. It. Is also frightening. And, it's. All about trust. It's. An open letter about artificial, intelligence signed, by some of the biggest names in science, what do they want ban. The use of autonomous, weapons the author stated, quote autonomous. Weapons, have been described, as the third revolution, in warfare thousand. Artificial, intelligence specialists calling for a global ban on killer, robots, this. Open letter basically. Says that we should redefine the goal of the, field of artificial intelligence away, from just creating, pure undirected. Intelligence. Towards. Creating beneficial, intelligence, the development, of AI is not going to stop it is going to continue and get better if the international. Community is in putting certain, controls, on this people will develop things, that, can do anything the letter says that we are years, not, decades away, from these weapons being deployed so we had six thousands, in countries of, that letter including, many of the major figures in the field. I'm. Getting, a lot of visits from high-ranking. Officials, who wish to emphasize that. American, malaria dominance, is very important, and, autonomous. Weapons may be part, of the, Defense Department's, plan. That's. Very very scary because a value, system of military developers. Of technology is not the same as the value system of the human race. Out. Of the concerns about the possibility, that this technology, might be a threat, to human existence a number. Of the technologists. Have funded, the future of life Institute to, try to grapple with these problems. All. Of these guys are secretive. And so it's interesting to me to see them at you know all together. Everything. We have is, a result of our intelligence, it's not the result of our big scary teeth or our. Large. Claws or our enormous muscles it's because we're actually relatively. Intelligent and. Among my generation, we're, all having what we call holy, cow or something wholly something else moments, because, we, see that the technology is accelerating faster, than. We expected. Remember. Sitting around the, table there with some, of the bests and the smartest minds in the world and what. Really, struck me was maybe. The human brain is not able to fully. Grasp the, complexity, of the world that we're confronted, with as. It's. Currently constructed the, road that AI is following heads off a cliff and we. Need to change the direction that. We're going so, that we don't take the human race off, the cliff. Google. Acquired deep mind several, years ago. Do. You mind operates as a semi independent subsidiary, of Google. The. Thing that makes deep, mind unique, is that deep mind is absolutely, focused on creating, digital. Super, intelligence, an. AI that is vastly smarter, than any. Here on earth and ultimately. Smarter than all humans, on earth combined this. Is from the deep mind, reinforcement. Learning system, basically. Wakes, up like. A newborn baby and is shown the screen of an Atari video game and then. Has to learn to play the video game. It. Knows nothing about, objects. About, motion about, time. It. Only knows that there's an image on the screen and there's a score. So. If your baby. Woke, up the day it was born and by later afternoon was. Playing 40.
Different Atari, video games at a superhuman, level, you. Would be terrified, you, would say my baby is possessed, send, it back, the. Deep line system can win at any game. It. Can already beat all the original Atari games. It. Is superhuman it plays the games at SuperSpeed in less, than a minute. Deep. Mine turned to another challenge, and the challenge was the game of Go which, people, have generally argued, has been beyond the power of computers to play with the best human go players. First. A challenge to european, go, champion. Then. They challenged, a korean go champion. And. They. Were able to win in both times and kind, of striking passionate. Here. Media articles in new york times years ago talking about how go would, take a hundred years, for, us to solve, people. Said well you know but that's still just a board. Poker. Is, an art poker involves, reading people poker involves lying bluffing. It's not an exact thing that will never be you know a computer, you can't do that they. Took the best poker players in the world and took. Seven days for. The computer to start demolishing. The humans. So. The best poker player in the world's best go player in the world and the pattern here is that AI might. Take a little while to wrap, its tentacles, around a new skill but. When it does when it gets it it. Is, unstoppable. Beep, mines AI has administrator. Level access, to Google's servers. To. Optimize, energy usage, at the data centers. However. This, could, be an unintentional. Trojan, horse eat, mine has to have complete control of the data centers so with a little software, update, that a I could take complete control of the whole Google system which, means they can do anything they. Can look at all your data you do anything. We're. Rapidly headed towards digital super intelligence, that far exceeds any human I think it's very obvious, the. Problem is we don't make suddenly hit, human level intelligence and, say okay let's stop research. It's. Gonna go beyond human level intelligence and, do what's called super intelligence, and that's anything smarter, than us. AI. At, the superhuman, level if we succeed without will be by far the most powerful. Invention. We've, ever made and the last dimension we ever have to make. And if, we create AI that's smarter than us we. Have to be open, to the possibility, that we, might actually lose control, to them. Let's. Say you give it some objective, like you're in cancer and then you discover that the, way it chooses to go about that is actually in conflict with a lot of other things you care about. Ai doesn't have to be evil to destroy humanity. If. AI has a goal and humanity, just happens to be in the way it. Will destroy him at the humanity as a matter of course without even thinking about it no hard feelings it's. Just like if we're building a road and an, anthill happens to be in the way we. Don't hate ants we're. Just building a road and so. Goodbye anthill. It's, tempting, to dismiss these concerns, because, it's, like something that might happen and a few decades or 100 years so. Why worry. But. If you go back to September 11th, 1933. Ernest, Rutherford who, is the most well, known nuclear physicist, of his time said. That the possibility, of ever extracting. Useful amounts of energy from the transmutation, of atoms as he called it was moonshine. The. Next morning Leo Szilard, who is much younger physicist, read, this and got really annoyed and figured. Out how, to make a nuclear chain reaction, just a few months later. We. Have spent more than two, billion dollars, on, the greatest scientific. Gamble, in history. So. When people say that oh this is so far off in the future we don't have to worry about it we, might only be three, four breakthroughs, of that magnitude, that, will get us from here to super, intelligent, machines. If. It's gonna take 20 years to figure out how, the, keep AI beneficial, then, we should start today. Not. At the last second when some, dudes. Drinking, Red Bull decide to flip the switch and test the thing.
We. Have five, years I think. Digital, super intelligence will happen in my lifetime. One. Hard percent. What, this happens it will be surrounded, by a bunch of people, who are really, just excited about the technology. They. Want to see it succeed but, they're not anticipating, that they can get out of control oh. My. God I trust, my computer, so much that's, an amazing question I don't trust my computer if it's on I take it off, like, even with off I still think it's all like you know like you really cannot just like the webcams, you don't know like someone, might turn it up don't know like I don't, trust my computer, like, in my phone every, time they ask me, we, send your information to, happen, every, time I so. Trust. My phone okay. So part, of it is yes I do trust it because it's. Really it'll be really hard to get through the day and the way I was set up without, computers. Trust. Is such a human, experience. I have. A patient coming in with, intracranial. Aneurysm. They. Want to look in my eyes and know that they, can trust this person with their life I'm. Not, horribly. Concerned. About. Anything. Good. Part of that is because I have confidence in you. This, procedure we're doing today 20. Years ago was. Essentially, impossible. We. Just didn't have the materials, in the technologies. That. Corner. Could. It be any more difficult my god. So. The coil is barely. In there right now it's. Just a feather holding, it in, its. Nervous time. We're. Just in purgatory, intellectual. Humanistic. Purgatory, an. AI might, know exactly what to do here. We. Got the coil into the aneurysm but it wasn't in tremendously. Well that I knew that it would stay so with. A maybe, 20%, risk of a very bad situation I, elected. To just bring her back. Because. Of my relationship with her and knowing the difficulties, of coming in and having the procedure I consider. Things when I should only consider the safest, possible route, to, achieve success. But. I had to stand there for 10 minutes agonizing, about it the. Computer feels nothing the. Computer, just does what it's supposed, to do, better and better. I. Want. To be AI in this case. But. Can. A I be, compassionate. I. Mean. It's everybody's, question, about AI. We. Are the sole. Embodiment. Of humanity, and it's. A stretch for us to accept, that a machine can, be compassionate, and loving in, that, way. Part. Of me doesn't believe in magic but. Part of me has faith that there is something beyond, the sum of the parts if, there is at least a oneness in our shared. Ancestry. Our shared biology, our shared history. Some. Connection, there beyond, machine. So, then you have the other side of that is does the computer, know it's conscious or can it be conscious or does it care, does. It need to be conscious. Does. It need to be aware. I. Do. Not think that a robot could ever be conscious. Unless. They programmed it that way, conscious. No. No. No I. Mean. I think a robot could be programmed to be conscious, how they program to do everything else. That's. Another big part of our official intelligence, is to make them a conscious, and make them feel.
Back. In 2005. We started trying, to build, machines. With self-awareness. This. Robot to, begin with didn't know what it was. All. He knew is that it needed to do something like walk. Through. Trial and error and figure out how to walk, using. Its imagination, and then, it walked away. And. Then. We did something very cruel we, chopped off a leg and watched what happened. At, the beginning it, didn't quite know what had, happened. But. Over, by the period of a day and then began to limp. And. Then. A year ago we. Were training an AI system for, a live demonstration. We. Wanted to show how we wave all these objects. In front of the camera under the AI can recognize, that the objects. And. So we're preparing this demo and we, had an aside screen this ability to watch what, certain. Neurons were responding. To and. Suddenly. We noticed that one of the neurons was tracking, faces. It was tracking, our faces as we were moving around. Now. The spooky. Thing about this is that we never trained the system to, recognize human, faces, and. Yet. Somehow. And, learn to do that. Even. Though these robots are very simple, we can see there's something else going on there it's. Not just program. So. This is just the beginning, I. Often. Think about that beach in Kitty Hawk. The. 1903. Flight, by Orville, and Wilbur Wright. As. A kind of a canvas claim it's more than iron and it gets off the ground for what a minute and 20 seconds and it's windy day, if. We're touching back down again. And. It. Was just around, 65. Summers, or so after. That moment. That. You have a 747. Taking, off from JFK. With. A major concern of Somali airplane might being whether. Or not their salt free diet meal. Is going to be coming to them or not with. A whole infrastructure, with travel, agents, and tower. Control, and it's all casual and it's all part of the world. Right. Now as far as we've come with, machines, and thinking solve problems, you, brought Kitty Hawk now we're in the wind we. Have our are tattered canvas, planes up in the air. But. What happens in sixty five summers or so we. Will have machines, that are behind you control. Should. We worry about that. I'm. Not. Sure, it's going to help. Nobody. Has any idea today. What it means for a robot to be conscious. There. Is no such thing. There. Are a lot of smart people and I have a great deal of respect for them but. The truth is machines. Are natural, Psychopaths, fear. Came back into the market and down eight hundred nearly a thousand in a heartbeat, made it is classic capitulation, there are some people were proposing, it was some kind of fat-finger error take. The flash crash of 2010 in. A matter of minutes. A trillion, dollars in value was, lost in stock market the Dow dropped nearly a thousand. Points in a half hour so. What. Went wrong. By. That point in time more. Than 60% of, all the trades that took place on stock exchange we're. Actually being initiated by. Computers. The, short story of what happened in the flash crash is that algorithms. Responded, to algorithms, and it, compounded, upon itself over and over and over again the, matter of minutes at, one point the market fell as if down, a well, there. Is no regulatory, body that can adapt quickly enough to prevent potentially. Disastrous, consequences. Of AI. Operating. In our financial system they. Are so prime, for. Manipulation, let's, talk about the speed with which we are watching this market be theory that's. The type of AI run amok that scares people when you. Give them a goal they. Will relentlessly, pursue. That goal. How. Many computer programs are there likeness, nobody. Knows. One. Of the fascinating, aspects. About AI, in general, is that no. One really understands. How, it works. Even. People who create, AI don't, really fully understand. Because. It has millions, of elements, it. Becomes, completely, impossible for a human being to understand. What's. Going on. Microsoft. Had, set, up this artificial, intelligence called ti' on Twitter which was a chat bot. They. Started out in the morning and ty was starting, to tweet and, learning. From stuff that was being sent to him from, other Twitter people. Because. Some people like trawl, attacked, him within 24 hours the Microsoft, thought became a terrible. Person. They. Had to literally, pull tie off the net because he had turned into a monster a. Misanthropic. Races. Horrible. Person, you never want to move and. Nobody. Had foreseen, this. The, whole idea of AI is that we are not telling it exactly, how to achieve a, given. Outcome, or, a goal ai, develops, on its own. We're. Worried about super, intelligent, AI, the master, chess player that will outmaneuver, us. But. Hey I won't have to actually be that smart to. Have massively. Disruptive effects. On human.
Civilization, We've, seen over the last century, it doesn't necessarily take genius, to knock history, off in a particular direction and. It won't take a genius ai to, do the same thing. Bogus. Election, news stories generated, more engagement, on Facebook then. Top, real. Stories. Facebook. Really is the elephant in the room. Ai. Running. Facebook, newsfeed the, task for AI is. Keeping. Users engaged, but. No one really understands, exactly how. This, AI is achieving, this goal. Facebook. Is building an elegant, mirrored wall around, us a mirror. That we can ask who's the fairest of them all and it, will answer you you time it again, you. Slowly begin to warp, our sense of reality warp, our sense of. Politics. History, global. Events until. Determining. What's true and what's not true, is, virtually. Impossible. The. Problem is that. AI doesn't understand that hey I just had a mission maximize. User engagement. And it achieved, that, nearly. Two billion people spend. Nearly, 1 hour on, average today basically. Interacting. With AI, that. Is shaping. Their experience. Even. Facebook engineers, they don't like fake news it's. Very bad business they. Want to get rid of fake news it's just very difficult to do because how, do you recognize news is fake if you cannot read all of those news personally, there's, so much. Active. Misinformation, and, it's. Packaged, very well and it looks the same when you see. It on a Facebook, page or you, turn on your television. It's. Not terribly sophisticated, but. It is terribly powerful, and. What it means is that your view of the world which, 20 years ago was determined, if you watch, the nightly news by, three different networks, the, three anchors who endeavor to try to get it right might have had a little bias one way or the other but largely speaking we can all agree on an objective reality. That. Objectivity, is gone and Facebook, is completely. Annihilated. If. Most of your understanding of how the world works is derived, from Facebook. Facilitated. By algorithmic. Software, that tries to show you the news you want to see, that's. A terribly dangerous thing, and the idea that we have not only set. That in motion. But. Allowed bad-faith. Actors, access to that information, this. Is a recipe for disaster I. Think. That it will definitely be lots of bad actors trying to manipulate the world with AI. 2016. Was a perfect example of an election where there was lots of AI producing. Lots of fake news and distributing, it for, for, a purpose, for a result. Ladies. And gentlemen honourable colleagues it's, my privilege to, speak to you today about the. Power of big data and psychographics. In the electoral process and. Specifically. To, talk about the work that we contributed, to Senator, Cruz's presidential. Primary campaign, Cambridge. Analytics emerged. Quietly, as a company, that according to its own height and has the, ability to use. This tremendous, amount of data in. Order to affect, societal. Change, in. 2016. They had three major clients, Ted, Cruz was one of them it's. Easy to forget that only 18 months ago senator. Cruz was one. Of the less popular candidates. Seeking nomination. So. What, was not possible maybe like 10 or 15 years ago was, that you can send, fake news to exactly, the people that you want to send it to and, then you could actually see, how he or, she reacts. On Facebook, and then adjust, that, information. According. To the feedback that you got and. So you can start developing, kind of a real-time management. Of a population, in this. Case we've, zoned in on a group we've called persuasion. These are people who are, definitely going to vote, to caucus but they need moving, from the center a little bit more towards the right in order to support Cruz they need a persuasion, message, gun. Rights I've selected that. Narrows the field slightly, more and now we know that we, a message, on gun, rights it needs to be a persuasion, message, and it needs to be nuanced, according, to the certain, personality. That we're interested in through. Social media there's. An infinite. Amount of information that you can gather about. A person, we have somewhere close to four or five thousand. Data points on every adult in the United States it's. About targeting. The individual. It's. Like a weapon which, can be used in the totally wrong direction that's, the problem with all of this data it's, almost as if we built the bullet before, we built the gun, Ted. Cruz employed. Our data our behavioral. Insights he, started from a base of less, than 5% and, had. A very slow, and steady, but firm. Rise to above. 35%. Making him obviously the, second most threatening contender. In the race now clearly. The Cruz campaign, is over now but.
What I can tell you is that, of the two candidates, left left, in this election one, of them is using, these technologies. Trump. Do, solemnly, swear that, I will faithfully. Execute. The office, of President of. The United States. Elections. Are a marginal, exercise doesn't. Take a very sophisticated AI, in. Order to have. A. Disproportionate. Impact. Before. Trump breaks it was another supposed, client, well, at 20, minutes to 5 we, can now say the decision taken in. 1975. By this country, to join the common market has, been reversed, by, this referendum, to, leave, the, EU. Cambridge. Analytic I allegedly, uses. AI to push through two of the most ground shaking pieces. Of political. Change in, the last. 50 years. These. Are epochal, events and if we believe the hype, they are connected directly to a, piece, of software essentially, created. By a professor at Stanford. Back. In 2013, I, described, that what they're doing is possible, and warned. Against this happening in the future, at. The time we have kasinsky was a young Polish researcher, working at the psychometric, Center. So what mahalo had done was to gather the, largest-ever. Data. Set of how, people behaved on facebook. Psychometrics. Is trying to measure. Psychological. Traits such as personality, intelligence, political. Views and so on now, traditionally. Those traits. Were measured, using tests, and questioners. Personality. Has the most benign thing you could possibly think of something, that doesn't necessarily have a lot of utility right, our. Idea was that instead of tests. And questioners, we could simply look at the digital footprints, of behaviors, that we, are all living behind, to. Understand. Openness. Conscientiousness. Neuroticism. You. Can easily buy, personal data such as where, you live what club memberships, you've joined which gym you go to there. Are actually marketplaces. For personal, data turns. Out we can discover an awful lot about what you're gonna do based, on a very very tiny, set. Of information. We. Are training, deep, learning networks who inferred, intimate. Trades people's. Political views. Personality. Intelligence. Sectarian. Tation, just. From an image, of someone's face. Now, think about countries, which are not so free and open-minded if, you can reveal people's religious. Views or political, views or sexual orientation based. On only profile, pictures. This. Could be literally an issue. Of life, and, death. I. Think. There's no going back. Do. You know what the Turing test is. It's. When a human interacts, with, a computer, and, if, the human doesn't know they're interacting, with a computer. The. Test is passed, and. Over the next few days. You're. Gonna be the human component and the Turing test holy. That's right Kayla you got it, because. If that test is passed. You. Are, dead. Center, of the greatest scientific, event, in the history of man, if. You've created a conscious, machine it's not the history of man. That's. The history of gods. It's, almost like technology is a garden of itself. Like, the weather we can't impact, it we can't slow, it down we can't stop it. We, feel, powerless. If. We think of God it's an unlimited amount of intelligence the closest we can get to that is by evolving. Our own intelligence, by merging with the artificial. Intelligence were creating. Today. Our computers. Phones, applications. Give us superhuman capability. So. As the old maxim says if you can't beat them join them. It's, about a human machine partnership. I mean. We already see how you know our phones for example it's act as memory prosthesis, right I don't have to remember your phone, number anymore because it's on my phone, it's. About machines, augmenting, our human abilities, as opposed, to like completely displacing. Them, if. You look at all the objects, that have made the leap from analog, to digital over, the last 20 years it's. A lot. We're. The last analog, object. In the digital universe and. The problem with that of course is that the data input, output is, very limited it's. This it's these. Our. Eyes are pretty good we're able to take in a lot of visual information. What. Our information, output is very, very very low the. Reason this is important. If we envision a scenario where AI, is playing a more prominent role in societies, we. Want good ways to interact with this technology so, that it, ends up augmenting. Us. I think. It's incredibly important to AI not the other. It. Must be us and. I. Could, be wrong about what I'm saying. I'm. Suddenly open to ideas if anybody, can suggest a path, that's better. But. I think we're really gonna have to either, merge with a IOP left behind. It's. Hard to kind of think of unplugging a system that's distributed everywhere, on the planet, that's. Distributed now, across. The solar system, you. Can't just you know shut that off. We've opened Pandora's box we've Unleashed, forces that we can't control we can't stop.
We're. In the midst of essentially, creating a new life-form on earth. We. Don't know what happens next we don't know what, shape the intellect, of a machine will be when that intellect is far beyond human capabilities, it's. Just not something that's possible. The. Least scary future I can think of is one where we have at least democratized. AI. Because. If one company, or small group for people managers. To develop godlike. Digital, super intelligence, they could take over the world. At, least when there's an evil dictator that, human is going to die but. For an AI there, would be no death they would live forever. And. Then you'd have an immortal dictator, from. Which we can never escape. You.