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These are the user uploaded subtitles that are being translated: 1 00:00:30,000 --> 00:00:33,500 Correction and synchronisation: Mazrim Taim 2 00:00:35,078 --> 00:00:41,302 What we're on the brink of is a world of increasingly intense, 3 00:00:41,345 --> 00:00:45,219 sophisticated artificial intelligence. 4 00:00:45,262 --> 00:00:48,396 Technology is evolving so much faster than our society 5 00:00:48,439 --> 00:00:51,181 has the ability to protect us as citizens. 6 00:00:51,486 --> 00:00:55,707 The robots are coming, and they will destroy our livelihoods. 7 00:01:01,887 --> 00:01:04,238 You have a networked intelligence that watches us, 8 00:01:04,281 --> 00:01:08,590 knows everything about us, and begins to try to change us. 9 00:01:08,633 --> 00:01:12,768 Twitter has become the world's number-one news site. 10 00:01:12,811 --> 00:01:15,205 Technology is never good or bad. 11 00:01:15,249 --> 00:01:18,948 It's what we do with the technology. 12 00:01:18,991 --> 00:01:22,734 Eventually, millions of people are gonna be thrown out of jobs 13 00:01:22,778 --> 00:01:25,737 because their skills are going to be obsolete. 14 00:01:25,781 --> 00:01:27,435 Mass unemployment... 15 00:01:27,478 --> 00:01:31,727 greater inequalities, even social unrest. 16 00:01:32,570 --> 00:01:35,530 Regardless of whether to be afraid or not afraid, 17 00:01:35,573 --> 00:01:38,185 the change is coming, and nobody can stop it. 18 00:01:44,582 --> 00:01:48,146 We've invested huge amounts of money, and so it stands to reason 19 00:01:48,148 --> 00:01:50,893 that the military, with their own desires, 20 00:01:50,936 --> 00:01:53,330 are gonna start to use these technologies. 21 00:01:53,374 --> 00:01:57,552 Autonomous weapons systems could lead to a global arms race 22 00:01:57,595 --> 00:02:00,032 to rival the Nuclear Era. 23 00:02:02,339 --> 00:02:05,429 We know what the answer is. They'll eventually be killing us. 24 00:02:10,826 --> 00:02:15,874 These technology leaps are gonna yield incredible miracles 25 00:02:15,918 --> 00:02:18,181 and incredible horrors. 26 00:02:24,274 --> 00:02:29,323 We created it, so I think, as we move forward, 27 00:02:29,366 --> 00:02:33,762 this intelligence will contain parts of us. 28 00:02:33,805 --> 00:02:35,981 And I think the question is: 29 00:02:36,025 --> 00:02:39,463 Will it contain the good parts... 30 00:02:39,507 --> 00:02:41,378 or the bad parts? 31 00:03:04,836 --> 00:03:08,840 The survivors called the war "Judgment Day." 32 00:03:08,884 --> 00:03:12,583 They lived only to face a new nightmare: 33 00:03:12,627 --> 00:03:14,319 The war against the machines. 34 00:03:15,456 --> 00:03:18,023 I think we've completely fucked this up. 35 00:03:18,067 --> 00:03:21,549 I think Hollywood has managed to inoculate the general public 36 00:03:21,592 --> 00:03:24,247 against this question. 37 00:03:24,291 --> 00:03:28,251 The idea of machines that will take over the world. 38 00:03:28,295 --> 00:03:30,645 Open the pod bay doors, HAL. 39 00:03:30,688 --> 00:03:33,561 I'm sorry, Dave. 40 00:03:33,604 --> 00:03:35,911 I'm afraid I can't do that. 41 00:03:37,434 --> 00:03:38,696 HAL? 42 00:03:38,740 --> 00:03:40,437 We've cried wolf enough times... 43 00:03:40,481 --> 00:03:42,483 ...that the public has stopped paying attention, 44 00:03:42,484 --> 00:03:44,120 because it feels like science fiction. 45 00:03:44,121 --> 00:03:46,001 Even sitting here talking about it right now, 46 00:03:46,002 --> 00:03:48,301 it feels a little bit silly, a little bit like, 47 00:03:48,302 --> 00:03:51,697 "Oh, this is an artifact of some cheeseball movie." 48 00:03:51,709 --> 00:03:56,584 The WOPR spends all its time thinking about World War III. 49 00:03:56,627 --> 00:03:59,064 But it's not. 50 00:03:59,108 --> 00:04:02,111 The general public is about to get blindsided by this. 51 00:04:11,555 --> 00:04:13,514 As a society and as individuals, 52 00:04:13,557 --> 00:04:18,954 we're increasingly surrounded by machine intelligence. 53 00:04:18,997 --> 00:04:22,653 We carry this pocket device in the palm of our hand 54 00:04:22,697 --> 00:04:24,829 that we use to make a striking array 55 00:04:24,873 --> 00:04:26,831 of life decisions right now, 56 00:04:26,875 --> 00:04:29,007 aided by a set of distant algorithms 57 00:04:29,051 --> 00:04:30,748 that we have no understanding. 58 00:04:34,186 --> 00:04:36,537 We're already pretty jaded about the idea 59 00:04:36,580 --> 00:04:37,929 that we can talk to our phone, 60 00:04:37,973 --> 00:04:40,062 and it mostly understands us. 61 00:04:40,105 --> 00:04:42,456 I found quite a number of action films. 62 00:04:42,499 --> 00:04:44,327 Five years ago -- no way. 63 00:04:44,371 --> 00:04:47,678 Robotics. Machines that see and speak... 64 00:04:47,722 --> 00:04:48,897 ...and listen. 65 00:04:48,940 --> 00:04:50,202 All that's real now. 66 00:04:50,246 --> 00:04:51,639 And these technologies 67 00:04:51,682 --> 00:04:54,886 are gonna fundamentally change our society. 68 00:04:55,730 --> 00:05:00,212 Now we have this great movement of self-driving cars. 69 00:05:00,256 --> 00:05:01,953 Driving a car autonomously 70 00:05:01,997 --> 00:05:05,688 can move people's lives into a better place. 71 00:05:06,131 --> 00:05:09,570 I've lost a number of family members, including my mother, 72 00:05:09,613 --> 00:05:11,876 my brother and sister-in-law and their kids, 73 00:05:11,920 --> 00:05:14,009 to automobile accidents. 74 00:05:14,052 --> 00:05:18,405 It's pretty clear we could almost eliminate car accidents 75 00:05:18,448 --> 00:05:20,102 with automation. 76 00:05:20,145 --> 00:05:21,843 30,000 lives in the U.S. alone. 77 00:05:21,886 --> 00:05:24,955 About a million around the world per year. 78 00:05:25,499 --> 00:05:27,501 In healthcare, early indicators 79 00:05:27,544 --> 00:05:29,503 are the name of the game in that space, 80 00:05:29,546 --> 00:05:33,158 so that's another place where it can save somebody's life. 81 00:05:33,202 --> 00:05:35,726 Here in the breast-cancer center, 82 00:05:35,770 --> 00:05:38,381 all the things that the radiologist's brain 83 00:05:38,425 --> 00:05:43,386 does in two minutes, the computer does instantaneously. 84 00:05:43,430 --> 00:05:47,303 The computer has looked at 1 billion mammograms, 85 00:05:47,347 --> 00:05:49,261 and it takes that data and applies it 86 00:05:49,305 --> 00:05:51,438 to this image instantaneously, 87 00:05:51,481 --> 00:05:54,441 so the medical application is profound. 88 00:05:56,399 --> 00:05:59,402 Another really exciting area that we're seeing a lot of development in 89 00:05:59,446 --> 00:06:03,275 is actually understanding our genetic code 90 00:06:03,319 --> 00:06:06,104 and using that to both diagnose disease 91 00:06:06,148 --> 00:06:07,758 and create personalized treatments. 92 00:06:11,675 --> 00:06:14,112 The primary application of all these machines 93 00:06:14,156 --> 00:06:17,246 will be to extend our own intelligence. 94 00:06:17,289 --> 00:06:19,422 We'll be able to make ourselves smarter, 95 00:06:19,466 --> 00:06:22,543 and we'll be better at solving problems. 96 00:06:22,586 --> 00:06:25,075 We don't have to age. We'll actually understand aging. 97 00:06:25,076 --> 00:06:27,126 We'll be able to stop it. 98 00:06:27,169 --> 00:06:29,519 There's really no limit to what intelligent machines 99 00:06:29,563 --> 00:06:30,868 can do for the human race. 100 00:06:36,308 --> 00:06:39,399 How could a smarter machine not be a better machine? 101 00:06:42,053 --> 00:06:44,708 It's hard to say exactly when I began to think 102 00:06:44,752 --> 00:06:46,971 that that was a bit naive. 103 00:06:56,503 --> 00:07:00,898 Stuart Russell, he's basically a god in the field of artificial intelligence. 104 00:07:00,942 --> 00:07:04,380 He wrote the book that almost every university uses. 105 00:07:04,424 --> 00:07:06,948 I used to say it's the best-selling AI textbook. 106 00:07:06,991 --> 00:07:10,255 Now I just say "It's the PDF that's stolen most often." 107 00:07:13,694 --> 00:07:17,306 Artificial intelligence is about making computers smart, 108 00:07:17,349 --> 00:07:19,830 and from the point of view of the public, 109 00:07:19,874 --> 00:07:21,484 what counts as AI is just something 110 00:07:21,528 --> 00:07:23,268 that's surprisingly intelligent 111 00:07:23,312 --> 00:07:25,488 compared to what we thought computers 112 00:07:25,532 --> 00:07:28,004 would typically be able to do. 113 00:07:28,448 --> 00:07:33,801 AI is a field of research to try to basically simulate 114 00:07:33,844 --> 00:07:36,717 all kinds of human capabilities. 115 00:07:36,760 --> 00:07:38,719 We're in the AI era. 116 00:07:38,762 --> 00:07:40,503 Silicon Valley has the ability to focus 117 00:07:40,547 --> 00:07:42,462 on one bright, shiny thing. 118 00:07:42,505 --> 00:07:45,508 It was social networking and social media over the last decade, 119 00:07:45,552 --> 00:07:48,119 and it's pretty clear that the bit has flipped. 120 00:07:48,163 --> 00:07:50,557 And it starts with machine learning. 121 00:07:50,600 --> 00:07:54,343 When we look back at this moment, what was the first AI? 122 00:07:54,386 --> 00:07:57,389 It's not sexy, and it isn't the thing we could see at the movies, 123 00:07:57,433 --> 00:08:00,741 but you'd make a great case that Google created, 124 00:08:00,784 --> 00:08:03,395 not a search engine, but a godhead. 125 00:08:03,439 --> 00:08:06,486 A way for people to ask any question they wanted 126 00:08:06,529 --> 00:08:08,270 and get the answer they needed. 127 00:08:08,313 --> 00:08:11,273 Most people are not aware that what Google is doing 128 00:08:11,316 --> 00:08:13,710 is actually a form of artificial intelligence. 129 00:08:13,754 --> 00:08:16,234 They just go there, they type in a thing. 130 00:08:16,278 --> 00:08:18,323 Google gives them the answer. 131 00:08:18,367 --> 00:08:21,444 With each search, we train it to be better. 132 00:08:21,445 --> 00:08:24,108 Sometimes we're typing a search, and it tell us the answer 133 00:08:24,109 --> 00:08:27,434 before you've finished asking the question. 134 00:08:27,463 --> 00:08:29,944 You know, who is the president of Kazakhstan? 135 00:08:29,987 --> 00:08:31,685 And it'll just tell you. 136 00:08:31,728 --> 00:08:34,818 You don't have to go to the Kazakhstan national website to find out. 137 00:08:34,862 --> 00:08:37,081 You didn't used to be able to do that. 138 00:08:37,125 --> 00:08:39,475 That is artificial intelligence. 139 00:08:39,519 --> 00:08:42,783 Years from now when we try to understand, we will say, 140 00:08:42,826 --> 00:08:44,567 "How did we miss it?" 141 00:08:44,611 --> 00:08:48,484 It's one of the striking contradictions that we're facing. 142 00:08:48,528 --> 00:08:52,053 Google and Facebook, et al, have built businesses on giving us, 143 00:08:52,096 --> 00:08:54,185 as a society, free stuff. 144 00:08:54,229 --> 00:08:56,013 But it's a Faustian bargain. 145 00:08:56,057 --> 00:09:00,017 They're extracting something from us in exchange, 146 00:09:00,061 --> 00:09:01,628 but we don't know 147 00:09:01,671 --> 00:09:03,760 what code is running on the other side and why. 148 00:09:03,804 --> 00:09:05,846 We have no idea. 149 00:09:06,589 --> 00:09:08,591 It does strike right at the issue 150 00:09:08,635 --> 00:09:11,028 of how much we should trust these machines. 151 00:09:14,162 --> 00:09:18,166 I use computers literally for everything. 152 00:09:18,209 --> 00:09:21,386 There are so many computer advancements now, 153 00:09:21,430 --> 00:09:23,824 and it's become such a big part of our lives. 154 00:09:23,867 --> 00:09:26,174 It's just incredible what a computer can do. 155 00:09:26,217 --> 00:09:29,090 You can actually carry a computer in your purse. 156 00:09:29,133 --> 00:09:31,571 I mean, how awesome is that? 157 00:09:31,614 --> 00:09:35,052 I think most technology is meant to make things easier 158 00:09:35,096 --> 00:09:37,315 and simpler for all of us, 159 00:09:37,359 --> 00:09:40,362 so hopefully that just remains the focus. 160 00:09:40,405 --> 00:09:43,147 I think everybody loves their computers. 161 00:09:51,721 --> 00:09:53,810 People don't realize they are constantly 162 00:09:53,854 --> 00:09:59,076 being negotiated with by machines; 163 00:09:59,120 --> 00:10:02,993 whether that's the price of products in your Amazon cart, 164 00:10:03,037 --> 00:10:05,517 whether you can get on a particular flight, 165 00:10:05,561 --> 00:10:08,912 whether you can reserve a room at a particular hotel. 166 00:10:08,956 --> 00:10:11,959 What you're experiencing are machine-learning algorithms 167 00:10:12,002 --> 00:10:14,265 that have determined that a person like you 168 00:10:14,309 --> 00:10:17,791 is willing to pay 2 cents more and is changing the price. 169 00:10:21,795 --> 00:10:24,014 Now, a computer looks at millions of people 170 00:10:24,058 --> 00:10:28,105 simultaneously for very subtle patterns. 171 00:10:28,149 --> 00:10:31,369 You can take seemingly innocent digital footprints, 172 00:10:31,413 --> 00:10:34,677 such as someone's playlist on Spotify, 173 00:10:34,721 --> 00:10:37,201 or stuff that they bought on Amazon, 174 00:10:37,245 --> 00:10:40,291 and then use algorithms to translate this 175 00:10:40,335 --> 00:10:44,513 into a very detailed and a very accurate, intimate profile. 176 00:10:47,603 --> 00:10:50,911 There is a dossier on each of us that is so extensive 177 00:10:50,954 --> 00:10:52,695 it would be possibly accurate to say 178 00:10:52,739 --> 00:10:55,698 that they know more about you than your mother does. 179 00:11:04,098 --> 00:11:06,883 The major cause of the recent AI breakthrough 180 00:11:06,927 --> 00:11:08,580 isn't just that some dude 181 00:11:08,624 --> 00:11:11,583 had a brilliant insight all of a sudden, 182 00:11:11,627 --> 00:11:14,325 but simply that we have much bigger data 183 00:11:14,369 --> 00:11:18,242 to train them on and vastly better computers. 184 00:11:18,286 --> 00:11:19,940 The magic is in the data. 185 00:11:19,983 --> 00:11:21,463 It's a ton of data. 186 00:11:21,506 --> 00:11:23,726 I mean, it's data that's never existed before. 187 00:11:23,770 --> 00:11:26,686 We've never had this data before. 188 00:11:26,729 --> 00:11:30,733 We've created technologies that allow us to capture 189 00:11:30,777 --> 00:11:33,040 vast amounts of information. 190 00:11:33,083 --> 00:11:35,738 If you think of a billion cellphones on the planet 191 00:11:35,782 --> 00:11:38,393 with gyroscopes and accelerometers 192 00:11:38,436 --> 00:11:39,786 and fingerprint readers... 193 00:11:39,829 --> 00:11:42,005 couple that with the GPS and the photos they take 194 00:11:42,049 --> 00:11:43,964 and the tweets that you send, 195 00:11:44,007 --> 00:11:47,750 we're all giving off huge amounts of data individually. 196 00:11:47,794 --> 00:11:50,274 Cars that drive as the cameras on them suck up information 197 00:11:50,318 --> 00:11:52,059 about the world around them. 198 00:11:52,102 --> 00:11:54,844 The satellites that are now in orbit the size of a toaster. 199 00:11:54,888 --> 00:11:57,629 The infrared about the vegetation on the planet. 200 00:11:57,673 --> 00:12:01,024 The buoys that are out in the oceans to feed into the climate models. 201 00:12:05,072 --> 00:12:08,902 And the NSA, the CIA, as they collect information 202 00:12:08,945 --> 00:12:12,644 about the geopolitical situations. 203 00:12:12,688 --> 00:12:15,604 The world today is literally swimming in this data. 204 00:12:20,609 --> 00:12:22,480 Back in 2012, 205 00:12:22,524 --> 00:12:25,875 IBM estimated that an average human being 206 00:12:25,919 --> 00:12:31,098 leaves 500 megabytes of digital footprints every day. 207 00:12:31,141 --> 00:12:34,841 If you wanted to back up on the one day worth of data 208 00:12:34,884 --> 00:12:36,494 that humanity produces 209 00:12:36,538 --> 00:12:39,062 and imprint it out on a letter-sized paper, 210 00:12:39,106 --> 00:12:43,806 double-sided, font size 12, and you stack it up, 211 00:12:43,850 --> 00:12:46,113 it would reach from the surface of the Earth 212 00:12:46,156 --> 00:12:49,116 to the sun four times over. 213 00:12:49,159 --> 00:12:51,292 That's every day. 214 00:12:51,335 --> 00:12:53,816 The data itself is not good or evil. 215 00:12:53,860 --> 00:12:55,470 It's how it's used. 216 00:12:55,513 --> 00:12:58,342 We're relying, really, on the goodwill of these people 217 00:12:58,386 --> 00:13:01,171 and on the policies of these companies. 218 00:13:01,215 --> 00:13:03,870 There is no legal requirement for how they can 219 00:13:03,913 --> 00:13:06,307 and should use that kind of data. 220 00:13:06,350 --> 00:13:09,266 That, to me, is at the heart of the trust issue. 221 00:13:11,007 --> 00:13:13,793 Right now there's a giant race for creating machines 222 00:13:13,836 --> 00:13:15,751 that are as smart as humans. 223 00:13:15,795 --> 00:13:18,071 Google -- They're working on what's really the kind of 224 00:13:18,072 --> 00:13:20,074 Manhattan Project of artificial intelligence. 225 00:13:20,075 --> 00:13:22,686 They've got the most money. They've got the most talent. 226 00:13:22,714 --> 00:13:27,067 They're buying up AI companies and robotics companies. 227 00:13:27,110 --> 00:13:29,069 People still think of Google as a search engine 228 00:13:29,112 --> 00:13:30,722 and their e-mail provider 229 00:13:30,766 --> 00:13:33,943 and a lot of other things that we use on a daily basis, 230 00:13:33,987 --> 00:13:39,383 but behind that search box are 10 million servers. 231 00:13:39,427 --> 00:13:43,910 That makes Google the most powerful computing platform in the world. 232 00:13:43,953 --> 00:13:47,217 Google is now working on an AI computing platform 233 00:13:47,261 --> 00:13:50,133 that will have 100 million servers. 234 00:13:52,179 --> 00:13:53,963 So when you're interacting with Google, 235 00:13:54,007 --> 00:13:56,052 we're just seeing the toenail of something 236 00:13:56,096 --> 00:13:58,881 that is a giant beast in the making. 237 00:13:58,925 --> 00:14:00,622 And the truth is, I'm not even sure 238 00:14:00,665 --> 00:14:02,798 that Google knows what it's becoming. 239 00:14:11,546 --> 00:14:15,811 If you look inside of what algorithms are being used at Google, 240 00:14:15,855 --> 00:14:20,076 it's technology largely from the '80s. 241 00:14:20,120 --> 00:14:23,863 So these are models that you train by showing them a 1, a 2, 242 00:14:23,906 --> 00:14:27,344 and a 3, and it learns not what a 1 is or what a 2 is -- 243 00:14:27,388 --> 00:14:30,434 It learns what the difference between a 1 and a 2 is. 244 00:14:30,478 --> 00:14:32,436 It's just a computation. 245 00:14:32,480 --> 00:14:35,396 In the last half decade, where we've made this rapid progress, 246 00:14:35,439 --> 00:14:38,268 it has all been in pattern recognition. 247 00:14:38,312 --> 00:14:41,184 Most of the good, old-fashioned AI 248 00:14:41,228 --> 00:14:44,057 was when we would tell our computers 249 00:14:44,100 --> 00:14:46,798 how to play a game like chess... 250 00:14:46,842 --> 00:14:49,584 from the old paradigm where you just tell the computer 251 00:14:49,627 --> 00:14:51,895 exactly what to do. 252 00:14:54,502 --> 00:14:57,505 This is "Jeopardy!" 253 00:14:59,420 --> 00:15:02,510 "The IBM Challenge"! 254 00:15:02,553 --> 00:15:05,730 No one at the time had thought that a machine 255 00:15:05,774 --> 00:15:08,298 could have the precision and the confidence 256 00:15:08,342 --> 00:15:11,475 and the speed to play "Jeopardy!" well enough against the best humans. 257 00:15:11,519 --> 00:15:14,609 Let's play "Jeopardy!" 258 00:15:18,569 --> 00:15:20,354 What is "shoe"? 259 00:15:20,397 --> 00:15:21,877 You are right. You get to pick. 260 00:15:21,921 --> 00:15:24,836 Literary Character APB for $800. 261 00:15:24,880 --> 00:15:28,014 Answer -- the Daily Double. 262 00:15:28,057 --> 00:15:31,539 Watson actually got its knowledge by reading Wikipedia 263 00:15:31,582 --> 00:15:34,672 and 200 million pages of natural-language documents. 264 00:15:34,716 --> 00:15:36,674 You can't program every line 265 00:15:36,718 --> 00:15:38,502 of how the world works. 266 00:15:38,546 --> 00:15:40,722 The machine has to learn by reading. 267 00:15:40,765 --> 00:15:42,202 Now we come to Watson. 268 00:15:42,245 --> 00:15:43,986 "Who is Bram Stoker?" 269 00:15:44,030 --> 00:15:45,988 And the wager? 270 00:15:46,032 --> 00:15:49,165 Hello! $17,973. 271 00:15:49,209 --> 00:15:50,993 $41,413. 272 00:15:51,037 --> 00:15:53,343 And a two-day total of $77-- 273 00:15:53,387 --> 00:15:56,694 Watson's trained on huge amounts of text, 274 00:15:56,738 --> 00:15:59,628 but it's not like it understands what it's saying. 275 00:15:59,671 --> 00:16:02,309 It doesn't know that water makes things wet by touching water 276 00:16:02,352 --> 00:16:04,441 and by seeing the way things behave in the world 277 00:16:04,485 --> 00:16:06,182 the way you and I do. 278 00:16:06,226 --> 00:16:10,143 A lot of language AI today is not building logical models 279 00:16:10,186 --> 00:16:11,622 of how the world works. 280 00:16:11,666 --> 00:16:15,365 Rather, it's looking at how the words appear 281 00:16:15,409 --> 00:16:18,238 in the context of other words. 282 00:16:18,281 --> 00:16:20,196 David Ferrucci developed IBM's Watson, 283 00:16:20,240 --> 00:16:23,547 and somebody asked him, "Does Watson think?" 284 00:16:23,591 --> 00:16:26,660 And he said, "Does a submarine swim?" 285 00:16:26,903 --> 00:16:29,331 And what they meant was, when they developed submarines, 286 00:16:29,332 --> 00:16:32,949 they borrowed basic principles of swimming from fish. 287 00:16:33,035 --> 00:16:36,525 But a submarine swims farther and faster than fish and can carry a huge payload. 288 00:16:36,569 --> 00:16:39,411 It out-swims fish. 289 00:16:39,955 --> 00:16:43,741 Watson winning the game of "Jeopardy!" will go down in the history of AI 290 00:16:43,785 --> 00:16:46,370 as a significant milestone. 291 00:16:46,614 --> 00:16:49,269 We tend to be amazed when the machine does so well. 292 00:16:49,312 --> 00:16:52,663 I'm even more amazed when the computer beats humans at things 293 00:16:52,707 --> 00:16:55,188 that humans are naturally good at. 294 00:16:55,231 --> 00:16:58,060 This is how we make progress. 295 00:16:58,104 --> 00:17:00,671 In the early days of the Google Brain project, 296 00:17:00,715 --> 00:17:02,804 I gave the team a very simple instruction, 297 00:17:02,847 --> 00:17:05,807 which was, "Build the biggest neural network possible, 298 00:17:05,850 --> 00:17:08,157 like 1,000 computers." 299 00:17:08,201 --> 00:17:12,161 A neural net is something very close to a simulation of how the brain works. 300 00:17:12,205 --> 00:17:16,818 It's very probabilistic, but with contextual relevance. 301 00:17:16,819 --> 00:17:18,456 In your brain, you have long neurons 302 00:17:18,457 --> 00:17:20,372 that connect to thousands of other neurons, 303 00:17:20,373 --> 00:17:22,592 and you have these pathways that are formed and forged 304 00:17:22,593 --> 00:17:24,769 based on what the brain needs to do. 305 00:17:24,782 --> 00:17:28,960 When a baby tries something and it succeeds, there's a reward, 306 00:17:29,004 --> 00:17:32,312 and that pathway that created the success is strengthened. 307 00:17:32,355 --> 00:17:34,662 If it fails at something, the pathway is weakened, 308 00:17:34,705 --> 00:17:36,794 and so, over time, the brain becomes honed 309 00:17:36,838 --> 00:17:40,120 to be good at the environment around it. 310 00:17:40,363 --> 00:17:43,279 Really, it's just getting machines to learn by themselves. 311 00:17:43,323 --> 00:17:45,538 This is called "deep learning," and "deep learning" 312 00:17:45,539 --> 00:17:48,834 and "neural networks" mean roughly the same thing. 313 00:17:48,835 --> 00:17:52,391 Deep learning is a totally different approach 314 00:17:52,419 --> 00:17:55,161 where the computer learns more like a toddler, 315 00:17:55,204 --> 00:17:56,466 by just getting a lot of data 316 00:17:56,510 --> 00:18:00,340 and eventually figuring stuff out. 317 00:18:00,383 --> 00:18:03,125 The computer just gets smarter and smarter 318 00:18:03,169 --> 00:18:05,997 as it has more experiences. 319 00:18:06,041 --> 00:18:09,697 Imagine, if you will, a neural network, you know, like 1,000 computers. 320 00:18:09,740 --> 00:18:11,438 And it wakes up not knowing anything. 321 00:18:11,481 --> 00:18:14,093 And we made it watch YouTube for a week. 322 00:18:25,408 --> 00:18:28,194 Charlie! That really hurt! 323 00:18:36,245 --> 00:18:38,508 And so, after watching YouTube for a week, 324 00:18:38,552 --> 00:18:39,988 what would it learn? 325 00:18:40,031 --> 00:18:42,103 We had a hypothesis that it would learn to detect 326 00:18:42,146 --> 00:18:44,384 commonly occurring objects in videos. 327 00:18:44,427 --> 00:18:47,517 And so, we know that human faces appear a lot in videos, 328 00:18:47,561 --> 00:18:49,302 so we looked, and, lo and behold, 329 00:18:49,345 --> 00:18:52,008 there was a neuron that had learned to detect human faces. 330 00:18:52,052 --> 00:18:55,865 Leave Britney alone! 331 00:18:56,309 --> 00:18:58,354 Well, what else appears in videos a lot? 332 00:19:00,095 --> 00:19:01,792 So, we looked, and to our surprise, 333 00:19:01,836 --> 00:19:05,082 there was actually a neuron that had learned to detect cats. 334 00:19:14,892 --> 00:19:17,068 I still remember seeing recognition. 335 00:19:17,112 --> 00:19:20,071 "Wow, that's a cat. Okay, cool. Great." 336 00:19:23,162 --> 00:19:26,295 It's all pretty innocuous when you're thinking about the future. 337 00:19:26,339 --> 00:19:29,733 It all seems kind of harmless and benign. 338 00:19:29,777 --> 00:19:33,520 But we're making cognitive architectures that will fly farther and faster than us 339 00:19:33,563 --> 00:19:37,437 and carry a bigger payload, and they won't be warm and fuzzy. 340 00:19:37,480 --> 00:19:41,702 I think that, in three to five years, you will see a computer system 341 00:19:41,745 --> 00:19:45,401 that will be able to autonomously learn 342 00:19:45,445 --> 00:19:49,013 how to understand, how to build understanding, 343 00:19:49,057 --> 00:19:51,364 not unlike the way the human mind works. 344 00:19:53,931 --> 00:19:56,891 Whatever that lunch was, it was certainly delicious. 345 00:19:56,934 --> 00:19:59,807 Simply some of Robby's synthetics. 346 00:19:59,850 --> 00:20:01,635 He's your cook, too? 347 00:20:01,678 --> 00:20:04,551 Even manufactures the raw materials. 348 00:20:04,594 --> 00:20:06,944 Come around here, Robby. 349 00:20:06,988 --> 00:20:09,773 I'll show you how this works. 350 00:20:11,122 --> 00:20:13,342 One introduces a sample of human food 351 00:20:13,386 --> 00:20:15,344 through this aperture. 352 00:20:15,388 --> 00:20:17,738 Down here there's a small built-in chemical laboratory, 353 00:20:17,781 --> 00:20:19,218 where he analyzes it. 354 00:20:19,261 --> 00:20:21,263 Later, he can reproduce identical molecules 355 00:20:21,307 --> 00:20:22,482 in any shape or quantity. 356 00:20:22,525 --> 00:20:24,614 Why, it's a housewife's dream. 357 00:20:24,958 --> 00:20:26,834 Meet Baxter, 358 00:20:26,877 --> 00:20:30,490 revolutionary new category of robots, with common sense. 359 00:20:30,533 --> 00:20:31,839 Baxter... 360 00:20:31,882 --> 00:20:33,449 Baxter is a really good example 361 00:20:33,493 --> 00:20:36,887 of the kind of competition we face from machines. 362 00:20:36,931 --> 00:20:42,676 Baxter can do almost anything we can do with our hands. 363 00:20:42,719 --> 00:20:45,722 Baxter costs about what a minimum-wage worker 364 00:20:45,766 --> 00:20:47,507 makes in a year. 365 00:20:47,550 --> 00:20:50,318 But Baxter won't be taking the place of one minimum-wage worker -- 366 00:20:50,319 --> 00:20:51,930 He'll be taking the place of three, 367 00:20:51,931 --> 00:20:55,531 because they never get tired, they never take breaks. 368 00:20:55,558 --> 00:20:57,865 That's probably the first thing we're gonna see -- 369 00:20:57,908 --> 00:20:59,475 displacement of jobs. 370 00:20:59,519 --> 00:21:04,088 They're gonna be done quicker, faster, cheaper by machines. 371 00:21:04,132 --> 00:21:07,657 Our ability to even stay current is so insanely limited 372 00:21:07,701 --> 00:21:10,138 compared to the machines we build. 373 00:21:10,181 --> 00:21:13,446 For example, now we have this great movement of Uber and Lyft 374 00:21:13,489 --> 00:21:16,505 kind of making transportation cheaper and democratizing transportation, 375 00:21:16,506 --> 00:21:17,768 which is great. 376 00:21:17,769 --> 00:21:21,189 The next step is gonna be that they're all gonna be replaced by driverless cars 377 00:21:21,192 --> 00:21:25,936 and then all the Uber and Lyft drivers have to find something new to do. 378 00:21:25,980 --> 00:21:29,723 There are 4 million professional drivers in the United States. 379 00:21:29,766 --> 00:21:31,638 They're unemployed soon. 380 00:21:31,681 --> 00:21:34,075 7 million people that do data entry. 381 00:21:34,118 --> 00:21:37,339 Those people are gonna be jobless. 382 00:21:37,383 --> 00:21:40,342 A job isn't just about money, right? 383 00:21:40,386 --> 00:21:42,605 On a biological level, it serves a purpose. 384 00:21:42,649 --> 00:21:45,391 It becomes a defining thing. 385 00:21:45,434 --> 00:21:48,350 When the jobs went away in any given civilization, 386 00:21:48,394 --> 00:21:50,987 it doesn't take long until that turns into violence. 387 00:21:59,622 --> 00:22:02,016 We face a giant divide between rich and poor, 388 00:22:02,059 --> 00:22:05,019 because that's what automation and AI will provoke -- 389 00:22:05,062 --> 00:22:08,588 a greater divide between the haves and the have-nots. 390 00:22:08,631 --> 00:22:10,807 Right now, it's working into the middle class, 391 00:22:10,851 --> 00:22:12,896 into white-collar jobs. 392 00:22:12,940 --> 00:22:15,334 IBM's Watson does business analytics 393 00:22:15,377 --> 00:22:20,600 that we used to pay a business analyst $300 an hour to do. 394 00:22:20,643 --> 00:22:23,037 Today, you're going to college to be a doctor, 395 00:22:23,080 --> 00:22:25,082 to be an accountant, to be a journalist. 396 00:22:25,126 --> 00:22:28,608 It's unclear that there's gonna be jobs there for you. 397 00:22:28,651 --> 00:22:32,612 If someone's planning for a 40-year career in radiology, 398 00:22:32,655 --> 00:22:34,222 just reading images, 399 00:22:34,265 --> 00:22:37,120 I think that could be a challenge to the new graduates of today. 400 00:22:58,507 --> 00:23:02,729 The da Vinci robot is currently utilized 401 00:23:02,772 --> 00:23:07,516 by a variety of surgeons for its accuracy and its ability 402 00:23:07,560 --> 00:23:12,303 to avoid the inevitable fluctuations of the human hand. 403 00:23:23,402 --> 00:23:28,494 Anybody who watches this feels the amazingness of it. 404 00:23:30,931 --> 00:23:34,674 You look through the scope, and you're seeing the claw hand 405 00:23:34,717 --> 00:23:36,893 holding that woman's ovary. 406 00:23:36,937 --> 00:23:42,638 Humanity was resting right here in the hands of this robot. 407 00:23:42,682 --> 00:23:46,947 People say it's the future, but it's not the future -- 408 00:23:46,990 --> 00:23:50,516 It's the present. 409 00:23:50,559 --> 00:23:52,474 If you think about a surgical robot, 410 00:23:52,475 --> 00:23:54,894 there's often not a lot of intelligence in these things, 411 00:23:54,895 --> 00:23:58,567 but over time, as we put more and more intelligence into these systems, 412 00:23:58,611 --> 00:24:02,281 the surgical robots can actually learn from each robot surgery. 413 00:24:02,284 --> 00:24:04,581 They're tracking the movements, they're understanding 414 00:24:04,582 --> 00:24:06,423 what worked and what didn't work. 415 00:24:06,424 --> 00:24:09,023 And eventually, the robot for routine surgeries 416 00:24:09,024 --> 00:24:12,362 is going to be able to perform that entirely by itself... 417 00:24:12,363 --> 00:24:14,056 or with human supervision. 418 00:24:35,038 --> 00:24:37,214 It seems that we're feeding it and creating it, 419 00:24:37,258 --> 00:24:42,785 but, in a way, we are a slave to the technology, 420 00:24:42,829 --> 00:24:45,701 because we can't go back. 421 00:24:50,053 --> 00:24:52,882 The machines are taking bigger and bigger bites 422 00:24:52,926 --> 00:24:57,147 out of our skill set at an ever-increasing speed. 423 00:24:57,191 --> 00:24:59,236 And so we've got to run faster and faster 424 00:24:59,280 --> 00:25:00,890 to keep ahead of the machines. 425 00:25:02,675 --> 00:25:04,677 How do I look? 426 00:25:04,720 --> 00:25:06,374 Good. 427 00:25:10,030 --> 00:25:11,553 Are you attracted to me? 428 00:25:11,597 --> 00:25:14,251 What? - Are you attracted to me? 429 00:25:14,295 --> 00:25:17,777 You give me indications that you are. 430 00:25:17,820 --> 00:25:20,562 I do? - Yes. 431 00:25:20,606 --> 00:25:22,608 This is the future we're headed into. 432 00:25:22,651 --> 00:25:26,046 We want to design our companions. 433 00:25:26,089 --> 00:25:29,266 We're gonna like to see a human face on AI. 434 00:25:29,310 --> 00:25:33,967 Therefore, gaming our emotions will be depressingly easy. 435 00:25:34,010 --> 00:25:35,272 We're not that complicated. 436 00:25:35,316 --> 00:25:38,101 We're simple. Stimulus-response. 437 00:25:38,145 --> 00:25:42,763 I can make you like me basically by smiling at you a lot. 438 00:25:43,106 --> 00:25:45,974 AI's are gonna be fantastic at manipulating us. 439 00:25:54,683 --> 00:25:56,946 So, you've developed a technology 440 00:25:56,990 --> 00:26:00,036 that can sense what people are feeling. 441 00:26:00,080 --> 00:26:03,387 Right. We've developed technology that can read your facial expressions 442 00:26:03,431 --> 00:26:06,521 and map that to a number of emotional states. 443 00:26:06,565 --> 00:26:08,697 15 years ago, I had just finished 444 00:26:08,741 --> 00:26:11,482 my undergraduate studies in computer science, 445 00:26:11,526 --> 00:26:15,008 and it struck me that I was spending a lot of time 446 00:26:15,051 --> 00:26:17,793 interacting with my laptops and my devices, 447 00:26:17,837 --> 00:26:23,582 yet these devices had absolutely no clue how I was feeling. 448 00:26:23,625 --> 00:26:26,802 I started thinking, "What if this device could sense 449 00:26:26,846 --> 00:26:29,326 that I was stressed or I was having a bad day? 450 00:26:29,370 --> 00:26:31,067 What would that open up?" 451 00:26:32,721 --> 00:26:34,418 Hi, first-graders! 452 00:26:34,462 --> 00:26:35,855 How are you? 453 00:26:35,898 --> 00:26:37,813 Can I get a hug? 454 00:26:37,857 --> 00:26:40,773 We had kids interact with the technology. 455 00:26:40,816 --> 00:26:44,472 A lot of it is still in development, but it was just amazing. 456 00:26:44,515 --> 00:26:46,648 Who likes robots? - Me! 457 00:26:46,692 --> 00:26:48,911 Who wants to have a robot in their house? 458 00:26:48,955 --> 00:26:51,479 What would you use a robot for, Jack? 459 00:26:51,522 --> 00:26:56,353 I would use it to ask my mom very hard math questions. 460 00:26:56,397 --> 00:26:58,181 Okay. What about you, Theo? 461 00:26:58,225 --> 00:27:02,272 I would use it for scaring people. 462 00:27:02,316 --> 00:27:04,666 All right. So, start by smiling. 463 00:27:04,710 --> 00:27:06,625 Nice. 464 00:27:06,668 --> 00:27:09,018 Brow furrow. 465 00:27:09,062 --> 00:27:10,890 Nice one. Eyebrow raise. 466 00:27:10,933 --> 00:27:15,068 This generation, technology is just surrounding them all the time. 467 00:27:15,111 --> 00:27:17,853 It's almost like they expect to have robots in their homes, 468 00:27:17,897 --> 00:27:22,336 and they expect these robots to be socially intelligent. 469 00:27:22,379 --> 00:27:25,252 What makes robots smart? 470 00:27:25,295 --> 00:27:29,648 Put them in, like, a math or biology class. 471 00:27:29,691 --> 00:27:32,259 I think you would have to train it. 472 00:27:32,302 --> 00:27:35,218 All right. Let's walk over here. 473 00:27:35,262 --> 00:27:37,394 So, if you smile and you raise your eyebrows, 474 00:27:37,438 --> 00:27:39,005 it's gonna run over to you. 475 00:27:39,048 --> 00:27:40,833 It's coming over! It's coming over! Look. 476 00:27:43,183 --> 00:27:45,272 But if you look angry, it's gonna run away. 477 00:27:46,534 --> 00:27:48,797 -Awesome! -Oh, that was good. 478 00:27:48,841 --> 00:27:52,366 We're training computers to read and recognize emotions. 479 00:27:52,409 --> 00:27:53,846 Ready? Set? Go! 480 00:27:53,889 --> 00:27:57,414 And the response so far has been really amazing. 481 00:27:57,458 --> 00:27:59,590 People are integrating this into health apps, 482 00:27:59,634 --> 00:28:03,865 meditation apps, robots, cars. 483 00:28:04,508 --> 00:28:06,728 We're gonna see how this unfolds. 484 00:28:09,470 --> 00:28:11,602 Robots can contain AI, 485 00:28:11,646 --> 00:28:14,388 but the robot is just a physical instantiation, 486 00:28:14,431 --> 00:28:16,782 and the artificial intelligence is the brain. 487 00:28:16,825 --> 00:28:19,872 And so brains can exist purely in software-based systems. 488 00:28:19,915 --> 00:28:22,483 They don't need to have a physical form. 489 00:28:22,526 --> 00:28:25,094 Robots can exist without any artificial intelligence. 490 00:28:25,138 --> 00:28:28,097 We have a lot of dumb robots out there. 491 00:28:28,141 --> 00:28:31,753 But a dumb robot can be a smart robot overnight, 492 00:28:31,797 --> 00:28:34,103 given the right software, given the right sensors. 493 00:28:34,147 --> 00:28:38,629 We can't help but impute motive into inanimate objects. 494 00:28:38,673 --> 00:28:41,502 We do it with machines. We'll treat them like children. 495 00:28:41,545 --> 00:28:43,330 We'll treat them like surrogates. 496 00:28:43,373 --> 00:28:45,027 Goodbye! 497 00:28:45,071 --> 00:28:48,204 And we'll pay the price. 498 00:29:08,616 --> 00:29:10,792 Okay, welcome to the ATR. 499 00:29:18,000 --> 00:29:20,800 My purpose is to have a more human-like robot 500 00:29:20,801 --> 00:29:24,001 which has human-like intentions and desires. 501 00:29:36,000 --> 00:29:38,400 The name of the robot is Erica. 502 00:29:39,501 --> 00:29:43,901 Erica is the most advanced human-like robot in the world, I think. 503 00:29:44,202 --> 00:29:47,202 Erica can gaze at your face. 504 00:29:51,528 --> 00:29:52,791 Konnichiwa. 505 00:29:53,592 --> 00:29:57,092 Robots can be pretty good as conversation partners, 506 00:29:57,093 --> 00:30:00,493 especially for the elderly and younger children, 507 00:30:00,494 --> 00:30:02,494 handicapped people. 508 00:30:03,094 --> 00:30:06,294 When we talk to the robot we don't fear the social barriers, 509 00:30:06,295 --> 00:30:08,095 social pressures. 510 00:30:08,396 --> 00:30:15,796 Finally everybody accepts the android as just our friend or partner. 511 00:30:15,997 --> 00:30:18,997 We have implemented simple desires. 512 00:30:18,998 --> 00:30:22,798 She wanted to be well recognized and she wanted to go rest. 513 00:30:29,299 --> 00:30:32,299 If a robot could have intentions and desires, 514 00:30:32,300 --> 00:30:36,300 the robot can understand other people's intentions and desires. 515 00:30:44,300 --> 00:30:47,100 That is tied to relationships with people 516 00:30:47,101 --> 00:30:49,201 and that means they like eachother. 517 00:30:50,302 --> 00:30:53,302 That means, well, I'm not sure, to rub eachother. 518 00:30:56,985 --> 00:30:58,682 We build artificial intelligence, 519 00:30:58,726 --> 00:31:01,948 and the very first thing we want to do is replicate us. 520 00:31:02,991 --> 00:31:05,341 I think the key point will come 521 00:31:05,385 --> 00:31:08,858 when all the major senses are replicated. 522 00:31:09,302 --> 00:31:11,130 Sight... 523 00:31:11,173 --> 00:31:12,871 touch... 524 00:31:12,914 --> 00:31:14,611 smell. 525 00:31:14,655 --> 00:31:17,919 When we replicate our senses, is that when it becomes alive? 526 00:31:27,624 --> 00:31:31,019 So many of our machines are being built to understand us. 527 00:31:32,847 --> 00:31:35,005 But what happens when an anthropomorphic creature 528 00:31:35,006 --> 00:31:37,474 discovers that they can adjust their loyalty, 529 00:31:37,475 --> 00:31:40,043 adjust their courage, adjust their avarice, 530 00:31:40,072 --> 00:31:42,291 adjust their cunning? 531 00:31:44,859 --> 00:31:48,645 The average person, they don't see killer robots going down the streets. 532 00:31:48,689 --> 00:31:50,996 They're like, "What are you talking about?" 533 00:31:51,039 --> 00:31:56,245 Man, we want to make sure that we don't have killer robots going down the street. 534 00:31:57,089 --> 00:31:59,439 Once they're going down the street, it is too late. 535 00:32:05,053 --> 00:32:08,578 The thing that worries me right now, that keeps me awake, 536 00:32:08,622 --> 00:32:11,842 is the development of autonomous weapons. 537 00:32:27,815 --> 00:32:32,733 Up to now, people have expressed unease about drones, 538 00:32:32,776 --> 00:32:35,127 which are remotely piloted aircraft. 539 00:32:39,827 --> 00:32:43,309 If you take a drone's camera and feed it into the AI system, 540 00:32:43,352 --> 00:32:47,443 it's a very easy step from here to fully autonomous weapons 541 00:32:47,487 --> 00:32:50,881 that choose their own targets and release their own missiles. 542 00:33:12,729 --> 00:33:15,080 The expected life-span of a human being 543 00:33:15,123 --> 00:33:19,420 in that kind of battle environment would be measured in seconds. 544 00:33:20,563 --> 00:33:23,740 At one point, drones were science fiction, 545 00:33:23,784 --> 00:33:28,832 and now they've become the normal thing in war. 546 00:33:28,876 --> 00:33:33,402 There's over 10,000 in U.S. military inventory alone. 547 00:33:33,446 --> 00:33:35,274 But they're not just a U.S. phenomena. 548 00:33:35,317 --> 00:33:39,060 There's more than 80 countries that operate them. 549 00:33:39,104 --> 00:33:41,932 It stands to reason that people making some 550 00:33:41,976 --> 00:33:44,587 of the most important and difficult decisions in the world 551 00:33:44,631 --> 00:33:46,328 are gonna start to use and implement 552 00:33:46,372 --> 00:33:48,591 artificial intelligence. 553 00:33:50,767 --> 00:33:53,596 The Air Force just designed a $400-billion jet program 554 00:33:53,640 --> 00:33:55,555 to put pilots in the sky, 555 00:33:55,598 --> 00:34:01,300 and a $500 AI, designed by a couple of graduate students, 556 00:34:01,343 --> 00:34:03,432 is beating the best human pilots 557 00:34:03,476 --> 00:34:05,782 with a relatively simple algorithm. 558 00:34:09,438 --> 00:34:13,399 AI will have as big an impact on the military 559 00:34:13,442 --> 00:34:17,490 as the combustion engine had at the turn of the century. 560 00:34:17,533 --> 00:34:21,233 It will literally touch everything that the military does, 561 00:34:21,276 --> 00:34:25,324 from driverless convoys delivering logistical supplies, 562 00:34:25,367 --> 00:34:27,021 to unmanned drones 563 00:34:27,065 --> 00:34:30,764 delivering medical aid, to computational propaganda, 564 00:34:30,807 --> 00:34:34,246 trying to win the hearts and minds of a population. 565 00:34:34,289 --> 00:34:38,337 And so it stands to reason that whoever has the best AI 566 00:34:38,380 --> 00:34:41,688 will probably achieve dominance on this planet. 567 00:34:45,561 --> 00:34:47,650 At some point in the early 21st century, 568 00:34:47,694 --> 00:34:51,219 all of mankind was united in celebration. 569 00:34:51,263 --> 00:34:53,830 We marveled at our own magnificence 570 00:34:53,874 --> 00:34:56,833 as we gave birth to AI. 571 00:34:56,877 --> 00:34:58,966 AI? 572 00:34:59,009 --> 00:35:00,489 You mean artificial intelligence? 573 00:35:00,533 --> 00:35:01,751 A singular consciousness 574 00:35:01,795 --> 00:35:05,886 that spawned an entire race of machines. 575 00:35:05,929 --> 00:35:09,716 We don't know who struck first -- us or them, 576 00:35:09,759 --> 00:35:12,980 but we know that it was us that scorched the sky. 577 00:35:14,677 --> 00:35:16,766 There's a long history of science fiction, 578 00:35:16,810 --> 00:35:19,987 not just predicting the future, but shaping the future. 579 00:35:26,863 --> 00:35:30,389 Arthur Conan Doyle writing before World War I 580 00:35:30,432 --> 00:35:34,393 on the danger of how submarines might be used 581 00:35:34,436 --> 00:35:38,048 to carry out civilian blockades. 582 00:35:38,092 --> 00:35:40,399 At the time he's writing this fiction, 583 00:35:40,442 --> 00:35:43,402 the Royal Navy made fun of Arthur Conan Doyle 584 00:35:43,445 --> 00:35:45,230 for this absurd idea 585 00:35:45,273 --> 00:35:47,623 that submarines could be useful in war. 586 00:35:53,455 --> 00:35:55,370 One of the things we've seen in history 587 00:35:55,414 --> 00:35:58,243 is that our attitude towards technology, 588 00:35:58,286 --> 00:36:01,942 but also ethics, are very context-dependent. 589 00:36:01,985 --> 00:36:03,726 For example, the submarine... 590 00:36:03,770 --> 00:36:06,468 nations like Great Britain and even the United States 591 00:36:06,512 --> 00:36:09,863 found it horrifying to use the submarine. 592 00:36:09,906 --> 00:36:13,214 In fact, the German use of the submarine to carry out attacks 593 00:36:13,258 --> 00:36:18,480 was the reason why the United States joined World War I. 594 00:36:18,524 --> 00:36:20,613 But move the timeline forward. 595 00:36:20,656 --> 00:36:23,529 The United States of America was suddenly 596 00:36:23,572 --> 00:36:28,403 and deliberately attacked by the empire of Japan. 597 00:36:28,447 --> 00:36:32,190 Five hours after Pearl Harbor, the order goes out 598 00:36:32,233 --> 00:36:36,498 to commit unrestricted submarine warfare against Japan. 599 00:36:39,936 --> 00:36:43,589 So Arthur Conan Doyle turned out to be right. 600 00:36:44,332 --> 00:36:46,856 That's the great old line about science fiction -- 601 00:36:46,900 --> 00:36:48,336 It's a lie that tells the truth. 602 00:36:48,380 --> 00:36:51,470 Fellow executives, it gives me great pleasure 603 00:36:51,513 --> 00:36:54,821 to introduce you to the future of law enforcement... 604 00:36:54,864 --> 00:36:56,562 ED-209. 605 00:37:03,656 --> 00:37:05,919 This isn't just a question of science fiction. 606 00:37:05,962 --> 00:37:09,488 This is about what's next, about what's happening right now. 607 00:37:13,970 --> 00:37:19,324 The role of intelligent systems is growing very rapidly in warfare. 608 00:37:19,367 --> 00:37:22,152 Everyone is pushing in the unmanned realm. 609 00:37:26,418 --> 00:37:28,898 Today, the Secretary of Defense is very, very clear -- 610 00:37:28,942 --> 00:37:32,337 We will not create fully autonomous attacking vehicles. 611 00:37:32,380 --> 00:37:34,643 Not everyone is gonna hold themselves 612 00:37:34,687 --> 00:37:36,515 to that same set of values. 613 00:37:36,558 --> 00:37:40,693 And when China and Russia start deploying autonomous vehicles 614 00:37:40,736 --> 00:37:45,611 that can attack and kill, what's the move that we're gonna make? 615 00:37:50,006 --> 00:37:51,617 You can't say, "Well, we're gonna use 616 00:37:51,660 --> 00:37:53,967 autonomous weapons for our military dominance, 617 00:37:54,010 --> 00:37:56,796 but no one else is gonna use them." 618 00:37:56,839 --> 00:38:00,495 If you make these weapons, they're gonna be used to attack 619 00:38:00,539 --> 00:38:03,324 human populations in large numbers. 620 00:38:12,551 --> 00:38:14,596 Autonomous weapons are, by their nature, 621 00:38:14,640 --> 00:38:16,468 weapons of mass destruction, 622 00:38:16,511 --> 00:38:19,862 because it doesn't need a human being to guide it or carry it. 623 00:38:19,906 --> 00:38:22,517 You only need one person, to, you know, 624 00:38:22,561 --> 00:38:25,781 write a little program. 625 00:38:25,825 --> 00:38:30,220 It just captures the complexity of this field. 626 00:38:30,264 --> 00:38:32,571 It is cool. It is important. 627 00:38:32,614 --> 00:38:34,573 It is amazing. 628 00:38:34,616 --> 00:38:37,053 It is also frightening. 629 00:38:37,097 --> 00:38:38,968 And it's all about trust. 630 00:38:42,102 --> 00:38:44,583 It's an open letter about artificial intelligence, 631 00:38:44,626 --> 00:38:47,063 signed by some of the biggest names in science. 632 00:38:47,107 --> 00:38:48,413 What do they want? 633 00:38:48,456 --> 00:38:50,763 Ban the use of autonomous weapons. 634 00:38:50,806 --> 00:38:52,373 The author stated, 635 00:38:52,417 --> 00:38:54,375 "Autonomous weapons have been described 636 00:38:54,419 --> 00:38:56,595 as the third revolution in warfare." 637 00:38:56,638 --> 00:38:58,853 ...thousand artificial-intelligence specialists 638 00:38:58,855 --> 00:39:01,875 calling for a global ban on killer robots. 639 00:39:01,876 --> 00:39:04,357 This open letter basically says 640 00:39:04,385 --> 00:39:07,954 that we should redefine the goal of the field of artificial intelligence 641 00:39:07,997 --> 00:39:11,610 away from just creating pure, undirected intelligence, 642 00:39:11,653 --> 00:39:13,655 towards creating beneficial intelligence. 643 00:39:13,699 --> 00:39:16,092 The development of AI is not going to stop. 644 00:39:16,136 --> 00:39:18,094 It is going to continue and get better. 645 00:39:18,138 --> 00:39:19,835 If the international community 646 00:39:19,879 --> 00:39:21,968 isn't putting certain controls on this, 647 00:39:22,011 --> 00:39:24,666 people will develop things that can do anything. 648 00:39:24,710 --> 00:39:27,365 The letter says that we are years, not decades, 649 00:39:27,408 --> 00:39:30,106 away from these weapons being deployed. So first of all... 650 00:39:30,150 --> 00:39:32,413 We had 6,000 signatories of that letter, 651 00:39:32,457 --> 00:39:35,155 including many of the major figures in the field. 652 00:39:37,026 --> 00:39:39,942 I'm getting a lot of visits from high-ranking officials 653 00:39:39,986 --> 00:39:42,989 who wish to emphasize that American military dominance 654 00:39:43,032 --> 00:39:45,731 is very important, and autonomous weapons 655 00:39:45,774 --> 00:39:50,083 may be part of the Defense Department's plan. 656 00:39:50,126 --> 00:39:52,433 That's very, very scary, because a value system 657 00:39:52,477 --> 00:39:54,479 of military developers of technology 658 00:39:54,522 --> 00:39:57,307 is not the same as a value system of the human race. 659 00:40:00,789 --> 00:40:02,922 Out of the concerns about the possibility 660 00:40:02,965 --> 00:40:06,665 that this technology might be a threat to human existence, 661 00:40:06,708 --> 00:40:08,144 a number of the technologists 662 00:40:08,188 --> 00:40:09,972 have funded the Future of Life Institute 663 00:40:10,016 --> 00:40:12,192 to try to grapple with these problems. 664 00:40:13,193 --> 00:40:14,847 All of these guys are secretive, 665 00:40:14,890 --> 00:40:16,805 and so it's interesting to me to see them, 666 00:40:16,849 --> 00:40:19,735 you know, all together. 667 00:40:20,679 --> 00:40:24,030 Everything we have is a result of our intelligence. 668 00:40:24,073 --> 00:40:26,641 It's not the result of our big, scary teeth 669 00:40:26,685 --> 00:40:29,470 or our large claws or our enormous muscles. 670 00:40:29,514 --> 00:40:32,473 It's because we're actually relatively intelligent. 671 00:40:32,517 --> 00:40:35,520 And among my generation, we're all having 672 00:40:35,563 --> 00:40:37,086 what we call "holy cow," 673 00:40:37,130 --> 00:40:39,045 or "holy something else" moments, 674 00:40:39,088 --> 00:40:41,003 because we see that the technology 675 00:40:41,047 --> 00:40:44,180 is accelerating faster than we expected. 676 00:40:44,224 --> 00:40:46,705 I remember sitting around the table there 677 00:40:46,748 --> 00:40:50,099 with some of the best and the smartest minds in the world, 678 00:40:50,143 --> 00:40:52,058 and what really struck me was, 679 00:40:52,101 --> 00:40:56,149 maybe the human brain is not able to fully grasp 680 00:40:56,192 --> 00:40:58,673 the complexity of the world that we're confronted with. 681 00:40:58,717 --> 00:41:01,415 As it's currently constructed, 682 00:41:01,459 --> 00:41:04,766 the road that AI is following heads off a cliff, 683 00:41:04,810 --> 00:41:07,595 and we need to change the direction that we're going 684 00:41:07,639 --> 00:41:10,729 so that we don't take the human race off the cliff. 685 00:41:13,558 --> 00:41:17,126 Google acquired DeepMind several years ago. 686 00:41:17,170 --> 00:41:22,088 DeepMind operates as a semi-independent subsidiary of Google. 687 00:41:22,131 --> 00:41:24,960 The thing that makes DeepMind unique 688 00:41:25,004 --> 00:41:26,919 is that DeepMind is absolutely focused 689 00:41:26,962 --> 00:41:30,313 on creating digital superintelligence -- 690 00:41:30,357 --> 00:41:34,056 an AI that is vastly smarter than any human on Earth 691 00:41:34,100 --> 00:41:36,624 and ultimately smarter than all humans on Earth combined. 692 00:41:36,668 --> 00:41:40,715 This is from the DeepMind reinforcement learning system. 693 00:41:40,759 --> 00:41:43,544 Basically wakes up like a newborn baby 694 00:41:43,588 --> 00:41:46,852 and is shown the screen of an Atari video game 695 00:41:46,895 --> 00:41:50,508 and then has to learn to play the video game. 696 00:41:50,551 --> 00:41:55,600 It knows nothing about objects, about motion, about time. 697 00:41:57,602 --> 00:41:59,604 It only knows that there's an image on the screen 698 00:41:59,647 --> 00:42:02,563 and there's a score. 699 00:42:02,607 --> 00:42:06,436 So, if your baby woke up the day it was born 700 00:42:06,480 --> 00:42:08,090 and, by late afternoon, 701 00:42:08,134 --> 00:42:11,093 was playing 40 different Atari video games 702 00:42:11,137 --> 00:42:15,315 at a superhuman level, you would be terrified. 703 00:42:15,358 --> 00:42:19,101 You would say, "My baby is possessed. Send it back." 704 00:42:19,145 --> 00:42:23,584 The DeepMind system can win at any game. 705 00:42:23,628 --> 00:42:27,588 It can already beat all the original Atari games. 706 00:42:27,632 --> 00:42:29,155 It is superhuman. 707 00:42:29,198 --> 00:42:31,636 It plays the games at superspeed in less than a minute. 708 00:42:37,076 --> 00:42:38,643 DeepMind turned to another challenge, 709 00:42:38,686 --> 00:42:40,558 and the challenge was the game of Go, 710 00:42:40,601 --> 00:42:42,603 which people have generally argued 711 00:42:42,647 --> 00:42:45,084 has been beyond the power of computers 712 00:42:45,127 --> 00:42:48,304 to play with the best human Go players. 713 00:42:48,348 --> 00:42:51,264 First, they challenged a European Go champion. 714 00:42:53,222 --> 00:42:55,834 Then they challenged a Korean Go champion. 715 00:42:55,877 --> 00:42:57,836 Please start the game. 716 00:42:57,879 --> 00:42:59,838 And they were able to win both times 717 00:42:59,881 --> 00:43:02,797 in kind of striking fashion. 718 00:43:02,841 --> 00:43:05,017 You were reading articles in New York Times years ago 719 00:43:05,060 --> 00:43:09,761 talking about how Go would take 100 years for us to solve. 720 00:43:09,804 --> 00:43:13,460 People said, "Well, you know, but that's still just a board. 721 00:43:13,503 --> 00:43:15,027 Poker is an art. 722 00:43:15,070 --> 00:43:16,419 Poker involves reading people. 723 00:43:16,463 --> 00:43:18,073 Poker involves lying and bluffing. 724 00:43:18,117 --> 00:43:19,553 It's not an exact thing. 725 00:43:19,597 --> 00:43:21,381 That will never be, you know, a computer. 726 00:43:21,424 --> 00:43:22,861 You can't do that." 727 00:43:22,904 --> 00:43:24,932 They took the best poker players in the world, 728 00:43:25,176 --> 00:43:30,520 and it took seven days for the computer to start demolishing the humans. 729 00:43:30,564 --> 00:43:32,461 So it's the best poker player in the world, 730 00:43:32,462 --> 00:43:35,012 it's the best Go player in the world, and the pattern here 731 00:43:35,013 --> 00:43:37,454 is that AI might take a little while 732 00:43:37,484 --> 00:43:40,443 to wrap its tentacles around a new skill, 733 00:43:40,487 --> 00:43:44,883 but when it does, when it gets it, it is unstoppable. 734 00:43:52,020 --> 00:43:55,110 DeepMind's AI has administrator-level access 735 00:43:55,154 --> 00:43:57,156 to Google's servers 736 00:43:57,199 --> 00:44:00,768 to optimize energy usage at the data centers. 737 00:44:00,812 --> 00:44:04,816 However, this could be an unintentional Trojan horse. 738 00:44:04,859 --> 00:44:07,253 DeepMind has to have complete control of the data centers, 739 00:44:07,296 --> 00:44:08,950 so with a little software update, 740 00:44:08,994 --> 00:44:10,691 that AI could take complete control 741 00:44:10,735 --> 00:44:12,214 of the whole Google system, 742 00:44:12,258 --> 00:44:13,607 which means they can do anything. 743 00:44:13,651 --> 00:44:16,131 They could look at all your data. They could do anything. 744 00:44:20,135 --> 00:44:23,051 We're rapidly heading towards digital superintelligence 745 00:44:23,095 --> 00:44:24,313 that far exceeds any human. 746 00:44:24,357 --> 00:44:26,402 I think it's very obvious. 747 00:44:26,446 --> 00:44:29,710 The problem is, we're not gonna suddenly hit human-level intelligence 748 00:44:29,754 --> 00:44:33,105 and say, "Okay, let's stop research." 749 00:44:33,148 --> 00:44:35,015 It's gonna go beyond human-level intelligence 750 00:44:35,016 --> 00:44:39,459 into what's called "superintelligence," and that's anything smarter than us. 751 00:44:39,502 --> 00:44:42,810 AI at the superhuman level, if we succeed with that, will be 752 00:44:42,854 --> 00:44:46,553 by far the most powerful invention we've ever made 753 00:44:46,596 --> 00:44:50,296 and the last invention we ever have to make. 754 00:44:50,339 --> 00:44:53,168 And if we create AI that's smarter than us, 755 00:44:53,212 --> 00:44:54,735 we have to be open to the possibility 756 00:44:54,779 --> 00:44:57,520 that we might actually lose control to them. 757 00:45:00,785 --> 00:45:02,612 Let's say you give it some objective, 758 00:45:02,656 --> 00:45:04,745 like curing cancer, and then you discover 759 00:45:04,789 --> 00:45:06,965 that the way it chooses to go about that 760 00:45:07,008 --> 00:45:08,444 is actually in conflict 761 00:45:08,488 --> 00:45:11,705 with a lot of other things you care about. 762 00:45:12,448 --> 00:45:16,496 AI doesn't have to be evil to destroy humanity. 763 00:45:16,539 --> 00:45:20,674 If AI has a goal, and humanity just happens to be in the way, 764 00:45:20,718 --> 00:45:22,894 it will destroy humanity as a matter of course, 765 00:45:22,937 --> 00:45:25,113 without even thinking about it. No hard feelings. 766 00:45:25,157 --> 00:45:27,072 It's just like if we're building a road 767 00:45:27,115 --> 00:45:29,770 and an anthill happens to be in the way... 768 00:45:29,814 --> 00:45:31,467 We don't hate ants. 769 00:45:31,511 --> 00:45:33,165 We're just building a road. 770 00:45:33,208 --> 00:45:34,857 And so goodbye, anthill. 771 00:45:37,996 --> 00:45:40,172 It's tempting to dismiss these concerns, 772 00:45:40,215 --> 00:45:42,783 'cause it's, like, something that might happen 773 00:45:42,827 --> 00:45:47,396 in a few decades or 100 years, so why worry? 774 00:45:47,440 --> 00:45:50,704 But if you go back to September 11, 1933, 775 00:45:50,748 --> 00:45:54,795 Ernest Rutherford, who was the most well-known nuclear physicist of his time, 776 00:45:54,839 --> 00:45:58,668 said that the possibility of ever extracting useful amounts of energy 777 00:45:58,712 --> 00:46:00,801 from the transmutation of atoms, as he called it, 778 00:46:00,845 --> 00:46:03,151 was moonshine. 779 00:46:03,195 --> 00:46:06,502 The next morning, Leo Szilard, who was a much younger physicist, 780 00:46:06,546 --> 00:46:09,984 read this and got really annoyed and figured out 781 00:46:10,028 --> 00:46:11,943 how to make a nuclear chain reaction 782 00:46:11,986 --> 00:46:13,379 just a few months later. 783 00:46:20,603 --> 00:46:23,693 We have spent more than $2 billion 784 00:46:23,737 --> 00:46:27,523 on the greatest scientific gamble in history. 785 00:46:27,567 --> 00:46:30,222 So when people say that, "Oh, this is so far off 786 00:46:30,265 --> 00:46:32,528 in the future, we don't have to worry about it," 787 00:46:32,572 --> 00:46:36,271 it might only be three, four breakthroughs of that magnitude 788 00:46:36,315 --> 00:46:40,275 that will get us from here to superintelligent machines. 789 00:46:40,319 --> 00:46:42,974 If it's gonna take 20 years to figure out 790 00:46:43,017 --> 00:46:45,237 how to keep AI beneficial, 791 00:46:45,280 --> 00:46:48,849 then we should start today, not at the last second 792 00:46:48,893 --> 00:46:51,460 when some dudes drinking Red Bull 793 00:46:51,504 --> 00:46:53,832 decide to flip the switch and test the thing. 794 00:46:56,814 --> 00:46:58,859 We have five years. 795 00:46:58,903 --> 00:47:03,764 I think digital superintelligence will happen in my lifetime. 796 00:47:03,908 --> 00:47:05,735 100%. 797 00:47:05,779 --> 00:47:07,215 When this happens, 798 00:47:07,259 --> 00:47:09,696 it will be surrounded by a bunch of people 799 00:47:09,739 --> 00:47:13,091 who are really just excited about the technology. 800 00:47:13,134 --> 00:47:15,571 They want to see it succeed, but they're not anticipating 801 00:47:15,615 --> 00:47:16,964 that it can get out of control. 802 00:47:25,494 --> 00:47:28,584 Oh, my God, I trust my computer so much. 803 00:47:28,628 --> 00:47:30,195 That's an amazing question. 804 00:47:30,238 --> 00:47:31,457 I don't trust my computer. 805 00:47:31,500 --> 00:47:32,937 If it's on, I take it off. 806 00:47:32,980 --> 00:47:34,242 Like, even when it's off, 807 00:47:34,286 --> 00:47:35,896 I still think it's on. Like, you know? 808 00:47:35,897 --> 00:47:37,694 Like, you really cannot tru-- Like, the webcams, 809 00:47:37,695 --> 00:47:39,625 you don't know if, like, someone might turn it... 810 00:47:39,639 --> 00:47:41,249 You don't know, like. 811 00:47:41,293 --> 00:47:42,903 I don't trust my computer. 812 00:47:42,947 --> 00:47:46,907 Like, in my phone, every time they ask me 813 00:47:46,951 --> 00:47:49,475 "Can we send your information to Apple?" 814 00:47:49,518 --> 00:47:50,998 every time, I... 815 00:47:51,042 --> 00:47:53,087 So, I don't trust my phone. 816 00:47:53,131 --> 00:47:56,743 Okay. So, part of it is, yes, I do trust it, 817 00:47:56,786 --> 00:48:00,660 because it would be really hard to get through the day 818 00:48:00,703 --> 00:48:04,011 in the way our world is set up without computers. 819 00:48:10,975 --> 00:48:13,368 Trust is such a human experience. 820 00:48:21,289 --> 00:48:25,119 I have a patient coming in with an intracranial aneurysm. 821 00:48:30,037 --> 00:48:31,691 They want to look in my eyes and know 822 00:48:31,734 --> 00:48:34,955 that they can trust this person with their life. 823 00:48:34,999 --> 00:48:39,129 I'm not horribly concerned about anything. 824 00:48:39,138 --> 00:48:40,204 Good. 825 00:48:40,206 --> 00:48:42,920 Part of that is because I have confidence in you. 826 00:48:50,753 --> 00:48:57,151 This procedure we're doing today, 20 years ago was essentially impossible. 827 00:48:57,195 --> 00:49:00,328 We just didn't have the materials and the technologies. 828 00:49:22,698 --> 00:49:26,485 So, the coil is barely in there right now. 829 00:49:26,528 --> 00:49:29,923 It's just a feather holding it in. 830 00:49:29,967 --> 00:49:32,012 It's nervous time. 831 00:49:36,190 --> 00:49:40,673 We're just in purgatory, intellectual, humanistic purgatory, 832 00:49:40,716 --> 00:49:43,632 and AI might know exactly what to do here. 833 00:49:50,639 --> 00:49:52,554 We've got the coil into the aneurysm. 834 00:49:52,598 --> 00:49:54,556 But it wasn't in tremendously well 835 00:49:54,600 --> 00:49:56,428 that I knew that it would stay, 836 00:49:56,471 --> 00:50:01,041 so with a maybe 20% risk of a very bad situation, 837 00:50:01,085 --> 00:50:04,436 I elected to just bring her back. 838 00:50:04,479 --> 00:50:05,959 Because of my relationship with her 839 00:50:06,003 --> 00:50:08,222 and knowing the difficulties of coming in 840 00:50:08,266 --> 00:50:11,051 and having the procedure, I consider things, 841 00:50:11,095 --> 00:50:14,272 when I should only consider the safest possible route 842 00:50:14,315 --> 00:50:16,361 to achieve success. 843 00:50:16,404 --> 00:50:19,755 But I had to stand there for 10 minutes agonizing about it. 844 00:50:19,799 --> 00:50:21,757 The computer feels nothing. 845 00:50:21,801 --> 00:50:24,760 The computer just does what it's supposed to do, 846 00:50:24,804 --> 00:50:26,284 better and better. 847 00:50:30,331 --> 00:50:32,551 I want to be AI in this case. 848 00:50:35,945 --> 00:50:38,861 But can AI be compassionate? 849 00:50:43,083 --> 00:50:47,827 I mean, it's everybody's question about AI. 850 00:50:47,870 --> 00:50:51,961 We are the sole embodiment of humanity, 851 00:50:52,005 --> 00:50:55,269 and it's a stretch for us to accept that a machine 852 00:50:55,313 --> 00:50:58,794 can be compassionate and loving in that way. 853 00:51:05,149 --> 00:51:07,281 Part of me doesn't believe in magic, 854 00:51:07,325 --> 00:51:09,805 but part of me has faith that there is something 855 00:51:09,849 --> 00:51:11,546 beyond the sum of the parts, 856 00:51:11,590 --> 00:51:15,637 that there is at least a oneness in our shared ancestry, 857 00:51:15,681 --> 00:51:19,738 our shared biology, our shared history. 858 00:51:20,381 --> 00:51:23,210 Some connection there beyond machine. 859 00:51:30,348 --> 00:51:32,567 So, then, you have the other side of that, is, 860 00:51:32,611 --> 00:51:37,137 does the computer know it's conscious, or can it be conscious, or does it care? 861 00:51:37,181 --> 00:51:40,009 Does it need to be conscious? 862 00:51:40,053 --> 00:51:42,011 Does it need to be aware? 863 00:51:52,892 --> 00:51:56,417 I do not think that a robot could ever be conscious. 864 00:51:56,461 --> 00:51:58,376 Unless they programmed it that way. 865 00:51:58,419 --> 00:52:00,639 Conscious? No. 866 00:52:00,682 --> 00:52:03,163 No. 867 00:52:03,207 --> 00:52:06,035 I mean, think a robot could be programmed to be conscious. 868 00:52:06,079 --> 00:52:09,648 How are they programmed to do everything else? 869 00:52:09,691 --> 00:52:12,390 That's another big part of artificial intelligence, 870 00:52:12,433 --> 00:52:15,741 is to make them conscious and make them feel. 871 00:52:22,443 --> 00:52:27,709 Back in 2005, we started trying to build machines with self-awareness. 872 00:52:33,106 --> 00:52:37,284 This robot, to begin with, didn't know what it was. 873 00:52:37,328 --> 00:52:40,244 All it knew was that it needed to do something like walk. 874 00:52:44,117 --> 00:52:45,597 Through trial and error, 875 00:52:45,640 --> 00:52:49,731 it figured out how to walk using its imagination, 876 00:52:49,775 --> 00:52:54,040 and then it walked away. 877 00:52:54,083 --> 00:52:56,390 And then we did something very cruel. 878 00:52:56,434 --> 00:52:58,653 We chopped off a leg and watched what happened. 879 00:53:03,049 --> 00:53:07,749 At the beginning, it didn't quite know what had happened. 880 00:53:07,793 --> 00:53:13,233 But over about a period of a day, it then began to limp. 881 00:53:13,277 --> 00:53:16,845 And then, a year ago, we were training an AI system 882 00:53:16,889 --> 00:53:20,240 for a live demonstration. 883 00:53:20,284 --> 00:53:24,113 We wanted to show how we wave all these objects in front of the camera 884 00:53:24,157 --> 00:53:27,334 and the AI could recognize the objects. 885 00:53:27,378 --> 00:53:29,031 And so, we're preparing this demo, 886 00:53:29,075 --> 00:53:31,251 and we had on a side screen this ability 887 00:53:31,295 --> 00:53:36,778 to watch what certain neurons were responding to. 888 00:53:36,822 --> 00:53:41,087 And suddenly we noticed that one of the neurons was tracking faces. 889 00:53:41,130 --> 00:53:45,483 It was tracking our faces as we were moving around. 890 00:53:45,526 --> 00:53:48,616 Now, the spooky thing about this is that we never trained 891 00:53:48,660 --> 00:53:52,490 the system to recognize human faces, 892 00:53:52,533 --> 00:53:55,710 and yet, somehow, it learned to do that. 893 00:53:57,973 --> 00:53:59,784 Even though these robots are very simple, 894 00:53:59,785 --> 00:54:02,658 we can see there's something else going on there. 895 00:54:02,659 --> 00:54:05,867 It's not just programming. 896 00:54:05,894 --> 00:54:08,462 So, this is just the beginning. 897 00:54:10,377 --> 00:54:14,294 I often think about that beach in Kitty Hawk. 898 00:54:14,338 --> 00:54:18,255 The 1903 flight by Orville and Wilbur Wright. 899 00:54:21,214 --> 00:54:24,289 It was kind of a canvas plane, and it's wood and iron, 900 00:54:24,291 --> 00:54:26,928 and it gets off the ground for, what, a minute and 20 seconds, 901 00:54:26,929 --> 00:54:31,006 on this windy day before touching back down again. 902 00:54:33,270 --> 00:54:37,143 And it was just around 65 summers or so 903 00:54:37,186 --> 00:54:43,149 after that moment that you have a 747 taking off from JFK... 904 00:54:50,099 --> 00:54:52,184 ...where a major concern of someone on the airplane 905 00:54:52,185 --> 00:54:55,380 might be whether or not their salt-free diet meal 906 00:54:55,381 --> 00:54:56,917 is gonna be coming to them or not. 907 00:54:56,945 --> 00:55:01,385 We have a whole infrastructure, with travel agents and tower control, 908 00:55:01,428 --> 00:55:03,778 and it's all casual, and it's all part of the world. 909 00:55:07,086 --> 00:55:09,523 Right now, as far as we've come with machines 910 00:55:09,567 --> 00:55:12,134 that think and solve problems, we're at Kitty Hawk now. 911 00:55:12,178 --> 00:55:13,745 We're in the wind. 912 00:55:13,788 --> 00:55:17,052 We have our tattered-canvas planes up in the air. 913 00:55:20,926 --> 00:55:23,885 But what happens in 65 summers or so? 914 00:55:23,929 --> 00:55:27,889 We will have machines that are beyond human control. 915 00:55:27,933 --> 00:55:30,457 Should we worry about that? 916 00:55:32,633 --> 00:55:34,853 I'm not sure it's going to help. 917 00:55:40,337 --> 00:55:44,036 Nobody has any idea today what it means for a robot 918 00:55:44,079 --> 00:55:46,430 to be conscious. 919 00:55:46,473 --> 00:55:48,649 There is no such thing. 920 00:55:48,693 --> 00:55:50,172 There are a lot of smart people, 921 00:55:50,216 --> 00:55:53,088 and I have a great deal of respect for them, 922 00:55:53,132 --> 00:55:57,528 but the truth is, machines are natural psychopaths. 923 00:55:57,571 --> 00:55:59,225 Fear came back into the market. 924 00:55:59,268 --> 00:56:01,706 Went down 800, nearly 1,000, in a heartbeat. 925 00:56:01,749 --> 00:56:03,360 I mean, it is classic capitulation. 926 00:56:03,403 --> 00:56:07,146 There are some people who are proposing it was some kind of fat-finger error. 927 00:56:07,189 --> 00:56:09,583 Take the Flash Crash of 2010. 928 00:56:09,627 --> 00:56:13,413 In a matter of minutes, $1 trillion in value 929 00:56:13,457 --> 00:56:15,415 was lost in the stock market. 930 00:56:15,459 --> 00:56:18,984 The Dow dropped nearly 1,000 points in a half-hour. 931 00:56:19,027 --> 00:56:22,553 So, what went wrong? 932 00:56:22,596 --> 00:56:26,644 By that point in time, more than 60% of all the trades 933 00:56:26,687 --> 00:56:29,124 that took place on the stock exchange 934 00:56:29,168 --> 00:56:32,693 were actually being initiated by computers. 935 00:56:32,737 --> 00:56:35,783 Panic selling on the way down, and all of a sudden it stopped on a dime. 936 00:56:35,827 --> 00:56:37,611 This is all happening in real time, folks. 937 00:56:37,612 --> 00:56:39,883 The short story of what happened in the Flash Crash 938 00:56:39,884 --> 00:56:42,513 is that algorithms responded to algorithms, 939 00:56:42,514 --> 00:56:45,430 and it compounded upon itself over and over and over again 940 00:56:45,431 --> 00:56:47,041 in a matter of minutes. 941 00:56:47,055 --> 00:56:50,972 At one point, the market fell as if down a well. 942 00:56:51,016 --> 00:56:54,323 There is no regulatory body that can adapt quickly enough 943 00:56:54,367 --> 00:56:57,979 to prevent potentially disastrous consequences 944 00:56:58,023 --> 00:57:01,243 of AI operating in our financial systems. 945 00:57:01,287 --> 00:57:03,898 They are so prime for manipulation. 946 00:57:03,942 --> 00:57:05,639 Let's talk about the speed with which 947 00:57:05,683 --> 00:57:08,076 we are watching this market deteriorate. 948 00:57:08,120 --> 00:57:11,602 That's the type of AI-run-amuck that scares people. 949 00:57:11,645 --> 00:57:13,560 When you give them a goal, 950 00:57:13,604 --> 00:57:17,225 they will relentlessly pursue that goal. 951 00:57:17,869 --> 00:57:20,393 How many computer programs are there like this? 952 00:57:20,437 --> 00:57:22,683 Nobody knows. 953 00:57:23,527 --> 00:57:27,444 One of the fascinating aspects about AI in general 954 00:57:27,487 --> 00:57:31,970 is that no one really understands how it works. 955 00:57:32,013 --> 00:57:36,975 Even the people who create AI don't really fully understand. 956 00:57:37,018 --> 00:57:41,675 Because it has millions of elements, it becomes completely impossible 957 00:57:41,719 --> 00:57:45,113 for a human being to understand what's going on. 958 00:57:52,556 --> 00:57:56,037 Microsoft had set up this artificial intelligence 959 00:57:56,081 --> 00:57:59,127 called Tay on Twitter, which was a chatbot. 960 00:58:00,912 --> 00:58:02,696 They started out in the morning, 961 00:58:02,740 --> 00:58:06,526 and Tay was starting to tweet and learning from stuff 962 00:58:06,570 --> 00:58:10,835 that was being sent to him from other Twitter people. 963 00:58:10,878 --> 00:58:13,272 Because some people, like trolls, attacked him, 964 00:58:13,315 --> 00:58:18,582 within 24 hours, the Microsoft bot became a terrible person. 965 00:58:18,625 --> 00:58:21,367 They had to literally pull Tay off the Net 966 00:58:21,410 --> 00:58:24,718 because he had turned into a monster. 967 00:58:24,762 --> 00:58:30,550 A misanthropic, racist, horrible person you'd never want to meet. 968 00:58:30,594 --> 00:58:32,857 And nobody had foreseen this. 969 00:58:35,337 --> 00:58:38,602 The whole idea of AI is that we are not telling it exactly 970 00:58:38,645 --> 00:58:42,780 how to achieve a given outcome or a goal. 971 00:58:42,823 --> 00:58:46,435 AI develops on its own. 972 00:58:46,479 --> 00:58:48,829 We're worried about superintelligent AI, 973 00:58:48,873 --> 00:58:52,790 the master chess player that will outmaneuver us, 974 00:58:52,833 --> 00:58:55,923 but AI won't have to actually be that smart 975 00:58:55,967 --> 00:59:00,145 to have massively disruptive effects on human civilization. 976 00:59:00,188 --> 00:59:01,886 We've seen over the last century 977 00:59:01,929 --> 00:59:05,150 it doesn't necessarily take a genius to knock history off 978 00:59:05,193 --> 00:59:06,804 in a particular direction, 979 00:59:06,847 --> 00:59:09,589 and it won't take a genius AI to do the same thing. 980 00:59:09,633 --> 00:59:13,158 Bogus election news stories generated more engagement 981 00:59:13,201 --> 00:59:17,075 on Facebook than top real stories. 982 00:59:17,118 --> 00:59:21,079 Facebook really is the elephant in the room. 983 00:59:21,122 --> 00:59:23,777 AI running Facebook news feed -- 984 00:59:23,821 --> 00:59:28,347 The task for AI is keeping users engaged, 985 00:59:28,390 --> 00:59:29,827 but no one really understands 986 00:59:29,870 --> 00:59:34,832 exactly how this AI is achieving this goal. 987 00:59:34,875 --> 00:59:38,792 Facebook is building an elegant mirrored wall around us. 988 00:59:38,836 --> 00:59:41,665 A mirror that we can ask, "Who's the fairest of them all?" 989 00:59:41,708 --> 00:59:45,016 and it will answer, "You, you," time and again 990 00:59:45,059 --> 00:59:48,193 and slowly begin to warp our sense of reality, 991 00:59:48,236 --> 00:59:53,502 warp our sense of politics, history, global events, 992 00:59:53,546 --> 00:59:57,028 until determining what's true and what's not true, 993 00:59:57,071 --> 00:59:58,943 is virtually impossible. 994 01:00:01,032 --> 01:00:03,861 The problem is that AI doesn't understand that. 995 01:00:03,904 --> 01:00:08,039 AI just had a mission -- maximize user engagement, 996 01:00:08,082 --> 01:00:10,041 and it achieved that. 997 01:00:10,084 --> 01:00:13,653 Nearly 2 billion people spend nearly one hour 998 01:00:13,697 --> 01:00:17,831 on average a day basically interacting with AI 999 01:00:17,875 --> 01:00:21,530 that is shaping their experience. 1000 01:00:21,574 --> 01:00:24,664 Even Facebook engineers, they don't like fake news. 1001 01:00:24,708 --> 01:00:28,015 It's very bad business. They want to get rid of fake news. 1002 01:00:28,059 --> 01:00:32,324 It's just very difficult to do because, how do you recognize news as fake 1003 01:00:32,367 --> 01:00:34,456 if you cannot read all of those news personally? 1004 01:00:34,500 --> 01:00:39,418 There's so much active misinformation 1005 01:00:39,461 --> 01:00:41,115 and it's packaged very well, 1006 01:00:41,159 --> 01:00:44,553 and it looks the same when you see it on a Facebook page 1007 01:00:44,597 --> 01:00:47,426 or you turn on your television. 1008 01:00:47,469 --> 01:00:51,691 It's not terribly sophisticated, but it is terribly powerful. 1009 01:00:51,735 --> 01:00:54,346 And what it means is that your view of the world, 1010 01:00:54,389 --> 01:00:56,435 which, 20 years ago, was determined, 1011 01:00:56,478 --> 01:01:00,004 if you watched the nightly news, by three different networks, 1012 01:01:00,047 --> 01:01:02,528 the three anchors who endeavored to try to get it right. 1013 01:01:02,529 --> 01:01:04,583 Might have had a little bias one way or the other, 1014 01:01:04,584 --> 01:01:08,273 but, largely speaking, we could all agree on an objective reality. 1015 01:01:08,316 --> 01:01:10,754 Well, that objectivity is gone, 1016 01:01:10,797 --> 01:01:13,757 and Facebook has completely annihilated it. 1017 01:01:17,108 --> 01:01:20,807 If most of your understanding of how the world works is derived from Facebook, 1018 01:01:20,851 --> 01:01:23,418 facilitated by algorithmic software 1019 01:01:23,462 --> 01:01:27,118 that tries to show you the news you want to see, 1020 01:01:27,161 --> 01:01:28,815 that's a terribly dangerous thing. 1021 01:01:28,859 --> 01:01:33,080 And the idea that we have not only set that in motion, 1022 01:01:33,124 --> 01:01:37,258 but allowed bad-faith actors access to that information... 1023 01:01:37,302 --> 01:01:39,565 I mean, this is a recipe for disaster. 1024 01:01:43,177 --> 01:01:45,876 I think that there will definitely be lots of bad actors 1025 01:01:45,919 --> 01:01:48,922 trying to manipulate the world with AI. 1026 01:01:48,966 --> 01:01:52,143 2016 was a perfect example of an election 1027 01:01:52,186 --> 01:01:55,015 where there was lots of AI producing lots of fake news 1028 01:01:55,059 --> 01:01:58,323 and distributing it for a purpose, for a result. 1029 01:01:59,890 --> 01:02:02,283 Ladies and gentlemen, honorable colleagues... 1030 01:02:02,327 --> 01:02:04,546 it's my privilege to speak to you today 1031 01:02:04,590 --> 01:02:07,985 about the power of big data and psychographics 1032 01:02:08,028 --> 01:02:09,682 in the electoral process 1033 01:02:09,726 --> 01:02:12,206 and, specifically, to talk about the work 1034 01:02:12,250 --> 01:02:14,513 that we contributed to Senator Cruz's 1035 01:02:14,556 --> 01:02:16,558 presidential primary campaign. 1036 01:02:16,602 --> 01:02:19,910 Cambridge Analytica emerged quietly as a company 1037 01:02:19,953 --> 01:02:21,563 that, according to its own hype, 1038 01:02:21,607 --> 01:02:26,307 has the ability to use this tremendous amount of data 1039 01:02:26,351 --> 01:02:30,137 in order to effect societal change. 1040 01:02:30,181 --> 01:02:33,358 In 2016, they had three major clients. 1041 01:02:33,401 --> 01:02:34,794 Ted Cruz was one of them. 1042 01:02:34,838 --> 01:02:37,884 It's easy to forget that, only 18 months ago, 1043 01:02:37,928 --> 01:02:42,846 Senator Cruz was one of the less popular candidates seeking nomination. 1044 01:02:42,889 --> 01:02:47,241 So, what was not possible maybe, like, 10 or 15 years ago, 1045 01:02:47,285 --> 01:02:49,374 was that you can send fake news 1046 01:02:49,417 --> 01:02:52,420 to exactly the people that you want to send it to. 1047 01:02:52,464 --> 01:02:56,685 And then you could actually see how he or she reacts on Facebook 1048 01:02:56,729 --> 01:02:58,905 and then adjust that information 1049 01:02:58,949 --> 01:03:01,778 according to the feedback that you got. 1050 01:03:01,821 --> 01:03:03,257 So you can start developing 1051 01:03:03,301 --> 01:03:06,130 kind of a real-time management of a population. 1052 01:03:06,173 --> 01:03:10,699 In this case, we've zoned in on a group we've called "Persuasion." 1053 01:03:10,743 --> 01:03:13,746 These are people who are definitely going to vote, 1054 01:03:13,790 --> 01:03:16,705 to caucus, but they need moving from the center 1055 01:03:16,749 --> 01:03:18,490 a little bit more towards the right. 1056 01:03:18,533 --> 01:03:19,708 in order to support Cruz. 1057 01:03:19,752 --> 01:03:22,059 They need a persuasion message. 1058 01:03:22,102 --> 01:03:23,800 "Gun rights," I've selected. 1059 01:03:23,843 --> 01:03:25,802 That narrows the field slightly more. 1060 01:03:25,845 --> 01:03:29,066 And now we know that we need a message on gun rights, 1061 01:03:29,109 --> 01:03:31,111 it needs to be a persuasion message, 1062 01:03:31,155 --> 01:03:34,201 and it needs to be nuanced according to the certain personality 1063 01:03:34,245 --> 01:03:36,029 that we're interested in. 1064 01:03:36,073 --> 01:03:39,946 Through social media, there's an infinite amount of information 1065 01:03:39,990 --> 01:03:42,514 that you can gather about a person. 1066 01:03:42,557 --> 01:03:45,734 We have somewhere close to 4,000 or 5,000 data points 1067 01:03:45,778 --> 01:03:48,563 on every adult in the United States. 1068 01:03:48,607 --> 01:03:51,915 It's about targeting the individual. 1069 01:03:51,958 --> 01:03:55,962 It's like a weapon, which can be used in the totally wrong direction. 1070 01:03:56,006 --> 01:03:58,051 That's the problem with all of this data. 1071 01:03:58,095 --> 01:04:02,229 It's almost as if we built the bullet before we built the gun. 1072 01:04:02,273 --> 01:04:06,407 Ted Cruz employed our data, our behavioral insights. 1073 01:04:06,451 --> 01:04:09,541 He started from a base of less than 5% 1074 01:04:09,584 --> 01:04:15,590 and had a very slow-and-steady- but-firm rise to above 35%, 1075 01:04:15,634 --> 01:04:17,157 making him, obviously, 1076 01:04:17,201 --> 01:04:20,465 the second most threatening contender in the race. 1077 01:04:20,508 --> 01:04:23,120 Now, clearly, the Cruz campaign is over now, 1078 01:04:23,163 --> 01:04:28,168 but what I can tell you is that of the two candidates left in this election, 1079 01:04:28,212 --> 01:04:30,867 one of them is using these technologies. 1080 01:04:32,564 --> 01:04:35,959 I, Donald John Trump, do solemnly swear 1081 01:04:36,002 --> 01:04:38,222 that I will faithfully execute 1082 01:04:38,265 --> 01:04:42,226 the office of President of the United States. 1083 01:04:48,275 --> 01:04:50,234 Elections are a marginal exercise. 1084 01:04:50,277 --> 01:04:53,237 It doesn't take a very sophisticated AI 1085 01:04:53,280 --> 01:04:57,719 in order to have a disproportionate impact. 1086 01:04:57,763 --> 01:05:02,550 Before Trump, Brexit was another supposed client. 1087 01:05:02,594 --> 01:05:04,726 Well, at 20 minutes to 5:00, 1088 01:05:04,770 --> 01:05:08,730 we can now say the decision taken in 1975 1089 01:05:08,774 --> 01:05:10,950 by this country to join the common market 1090 01:05:10,994 --> 01:05:15,999 has been reversed by this referendum to leave the EU. 1091 01:05:16,042 --> 01:05:19,828 Cambridge Analytica allegedly uses AI 1092 01:05:19,872 --> 01:05:23,267 to push through two of the most ground-shaking pieces 1093 01:05:23,310 --> 01:05:27,967 of political change in the last 50 years. 1094 01:05:28,011 --> 01:05:30,709 These are epochal events, and if we believe the hype, 1095 01:05:30,752 --> 01:05:33,755 they are connected directly to a piece of software, 1096 01:05:33,799 --> 01:05:37,194 essentially, created by a professor at Stanford. 1097 01:05:41,459 --> 01:05:45,593 Back in 2013, I described that what they are doing is possible 1098 01:05:45,637 --> 01:05:49,293 and warned against this happening in the future. 1099 01:05:49,336 --> 01:05:51,382 At the time, Michal Kosinski 1100 01:05:51,425 --> 01:05:54,994 was a young Polish researcher working at the Psychometrics Centre. 1101 01:05:55,038 --> 01:06:00,217 So, what Michal had done was to gather the largest-ever data set 1102 01:06:00,260 --> 01:06:03,481 of how people behave on Facebook. 1103 01:06:03,524 --> 01:06:07,789 Psychometrics is trying to measure psychological traits, 1104 01:06:07,833 --> 01:06:09,922 such as personality, intelligence, 1105 01:06:09,966 --> 01:06:11,880 political views, and so on. 1106 01:06:11,924 --> 01:06:15,058 Now, traditionally, those traits were measured 1107 01:06:15,101 --> 01:06:17,712 using tests and questions. 1108 01:06:17,756 --> 01:06:20,715 Personality test, the most benign thing you could possibly think of. 1109 01:06:20,759 --> 01:06:24,197 Something that doesn't necessarily have a lot of utility, right? 1110 01:06:24,241 --> 01:06:27,331 Our idea was that instead of tests and questions, 1111 01:06:27,374 --> 01:06:30,029 we could simply look at the digital footprints of behaviors 1112 01:06:30,073 --> 01:06:32,553 that we are all leaving behind 1113 01:06:32,597 --> 01:06:34,903 to understand openness, 1114 01:06:34,947 --> 01:06:37,732 conscientiousness, neuroticism. 1115 01:06:37,776 --> 01:06:39,560 You can easily buy personal data, 1116 01:06:39,604 --> 01:06:43,129 such as where you live, what club memberships you've tried, 1117 01:06:43,173 --> 01:06:45,044 which gym you go to. 1118 01:06:45,088 --> 01:06:47,873 There are actually marketplaces for personal data. 1119 01:06:47,916 --> 01:06:51,442 It turns out, we can discover an awful lot about what you're gonna do 1120 01:06:51,485 --> 01:06:55,750 based on a very, very tiny set of information. 1121 01:06:55,794 --> 01:06:58,275 We are training deep-learning networks 1122 01:06:58,318 --> 01:07:01,278 to infer intimate traits, 1123 01:07:01,321 --> 01:07:04,759 people's political views, personality, 1124 01:07:04,803 --> 01:07:07,806 intelligence, sexual orientation 1125 01:07:07,849 --> 01:07:10,504 just from an image from someone's face. 1126 01:07:17,076 --> 01:07:20,645 Now think about countries which are not so free and open-minded. 1127 01:07:20,688 --> 01:07:23,300 If you can reveal people's religious views 1128 01:07:23,343 --> 01:07:25,954 or political views or sexual orientation 1129 01:07:25,998 --> 01:07:28,740 based on only profile pictures, 1130 01:07:28,783 --> 01:07:33,310 this could be literally an issue of life and death. 1131 01:07:37,009 --> 01:07:39,751 I think there's no going back. 1132 01:07:42,145 --> 01:07:44,321 Do you know what the Turing test is? 1133 01:07:44,364 --> 01:07:48,977 It's when a human interacts with a computer, 1134 01:07:49,021 --> 01:07:52,546 and if the human doesn't know they're interacting with a computer, 1135 01:07:52,590 --> 01:07:54,126 the test is passed. 1136 01:07:54,170 --> 01:07:57,247 And over the next few days, 1137 01:07:57,290 --> 01:07:59,684 you're gonna be the human component in a Turing test. 1138 01:07:59,727 --> 01:08:02,295 Holy shit. - That's right, Caleb. 1139 01:08:02,339 --> 01:08:04,080 You got it. 1140 01:08:04,123 --> 01:08:06,865 'Cause if that test is passed, 1141 01:08:06,908 --> 01:08:10,825 you are dead center of the greatest scientific event 1142 01:08:10,869 --> 01:08:12,958 in the history of man. 1143 01:08:13,001 --> 01:08:17,615 If you've created a conscious machine, it's not the history of man. 1144 01:08:17,658 --> 01:08:19,356 That's the history of gods. 1145 01:08:26,841 --> 01:08:29,975 It's almost like technology is a god in and of itself. 1146 01:08:33,196 --> 01:08:35,241 Like the weather. We can't impact it. 1147 01:08:35,285 --> 01:08:39,293 We can't slow it down. We can't stop it. 1148 01:08:39,637 --> 01:08:42,849 We feel powerless. 1149 01:08:43,293 --> 01:08:46,687 If we think of God as an unlimited amount of intelligence, 1150 01:08:46,731 --> 01:08:50,474 the closest we can get to that is by evolving our own intelligence 1151 01:08:50,517 --> 01:08:55,566 by merging with the artificial intelligence we're creating. 1152 01:08:55,609 --> 01:08:58,003 Today, our computers, phones, 1153 01:08:58,046 --> 01:09:01,615 applications give us superhuman capability. 1154 01:09:01,659 --> 01:09:04,662 So, as the old maxim says, if you can't beat 'em, join 'em. 1155 01:09:06,968 --> 01:09:09,971 It's about a human-machine partnership. 1156 01:09:10,015 --> 01:09:11,669 I mean, we already see how, you know, 1157 01:09:11,712 --> 01:09:14,933 our phones, for example, act as memory prosthesis, right? 1158 01:09:14,976 --> 01:09:17,196 I don't have to remember your phone number anymore 1159 01:09:17,240 --> 01:09:19,198 'cause it's on my phone. 1160 01:09:19,242 --> 01:09:22,070 It's about machines augmenting our human abilities, 1161 01:09:22,114 --> 01:09:25,248 as opposed to, like, completely displacing them. 1162 01:09:25,249 --> 01:09:27,538 If you look at all the objects that have made the leap 1163 01:09:27,539 --> 01:09:30,237 from analog to digital over the last 20 years... 1164 01:09:30,238 --> 01:09:32,123 it's a lot. 1165 01:09:32,124 --> 01:09:35,388 We're the last analog object in a digital universe. 1166 01:09:35,389 --> 01:09:37,068 And the problem with that, of course, 1167 01:09:37,069 --> 01:09:40,609 is that the data input/output is very limited. 1168 01:09:40,611 --> 01:09:42,613 It's this. It's these. 1169 01:09:42,856 --> 01:09:45,355 Our eyes are pretty good. 1170 01:09:45,398 --> 01:09:48,445 We're able to take in a lot of visual information. 1171 01:09:48,488 --> 01:09:52,536 But our information output is very, very, very low. 1172 01:09:52,579 --> 01:09:55,669 The reason this is important -- If we envision a scenario 1173 01:09:55,713 --> 01:09:59,543 where AI's playing a more prominent role in societies, 1174 01:09:59,586 --> 01:10:02,023 we want good ways to interact with this technology 1175 01:10:02,067 --> 01:10:04,983 so that it ends up augmenting us. 1176 01:10:07,855 --> 01:10:12,295 I think it's incredibly important that AI not be "other." 1177 01:10:12,338 --> 01:10:14,562 It must be us. 1178 01:10:14,906 --> 01:10:18,605 And I could be wrong about what I'm saying. 1179 01:10:18,649 --> 01:10:23,915 I'm certainly open to ideas if anybody can suggest a path that's better. 1180 01:10:23,958 --> 01:10:27,266 But I think we're gonna really have to either merge with AI 1181 01:10:27,310 --> 01:10:29,063 or be left behind. 1182 01:10:36,406 --> 01:10:38,756 It's hard to kind of think of unplugging a system 1183 01:10:38,799 --> 01:10:41,802 that's distributed everywhere on the planet, 1184 01:10:41,846 --> 01:10:45,806 that's distributed now across the solar system. 1185 01:10:45,850 --> 01:10:49,375 You can't just, you know, shut that off. 1186 01:10:49,419 --> 01:10:51,290 We've opened Pandora's box. 1187 01:10:51,334 --> 01:10:55,642 We've unleashed forces that we can't control, we can't stop. 1188 01:10:55,686 --> 01:10:59,516 We're in the midst of essentially creating a new life-form on Earth. 1189 01:11:05,870 --> 01:11:07,611 We don't know what happens next. 1190 01:11:07,654 --> 01:11:10,353 We don't know what shape the intellect of a machine 1191 01:11:10,396 --> 01:11:14,531 will be when that intellect is far beyond human capabilities. 1192 01:11:14,574 --> 01:11:17,360 It's just not something that's possible. 1193 01:11:24,758 --> 01:11:26,976 The least scary future I can think of is one 1194 01:11:26,978 --> 01:11:29,633 where we have at least democratized AI. 1195 01:11:31,548 --> 01:11:34,159 Because if one company or small group of people 1196 01:11:34,202 --> 01:11:37,031 manages to develop godlike digital superintelligence, 1197 01:11:37,075 --> 01:11:39,739 they can take over the world. 1198 01:11:40,383 --> 01:11:44,343 At least when there's an evil dictator, that human is going to die, 1199 01:11:44,387 --> 01:11:46,998 but, for an AI, there would be no death. 1200 01:11:47,041 --> 01:11:49,392 It would live forever. 1201 01:11:49,435 --> 01:11:53,670 And then you have an immortal dictator from which we can never escape. 1202 01:13:33,000 --> 01:13:36,500 Correction and synchronisation: Mazrim Taim 99763

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