All language subtitles for iHuman 2019.WEBRip.x264-ION10.english

af Afrikaans
sq Albanian
am Amharic
ar Arabic
hy Armenian
az Azerbaijani
eu Basque
be Belarusian
bn Bengali
bs Bosnian
bg Bulgarian
ca Catalan
ceb Cebuano
ny Chichewa
zh-CN Chinese (Simplified)
zh-TW Chinese (Traditional)
co Corsican
hr Croatian
cs Czech
da Danish
nl Dutch
en English
eo Esperanto
et Estonian
tl Filipino
fi Finnish
fr French
fy Frisian
gl Galician
ka Georgian
de German
el Greek
gu Gujarati
ht Haitian Creole
ha Hausa
haw Hawaiian
iw Hebrew
hi Hindi
hmn Hmong
hu Hungarian
is Icelandic
ig Igbo
id Indonesian
ga Irish
it Italian
ja Japanese
jw Javanese
kn Kannada
kk Kazakh
km Khmer
ko Korean
ku Kurdish (Kurmanji)
ky Kyrgyz
lo Lao
la Latin
lv Latvian
lt Lithuanian
lb Luxembourgish
mk Macedonian
mg Malagasy
ms Malay
ml Malayalam
mt Maltese
mi Maori
mr Marathi
mn Mongolian
my Myanmar (Burmese)
ne Nepali
no Norwegian
ps Pashto
fa Persian
pl Polish
pt Portuguese
pa Punjabi
ro Romanian
ru Russian
sm Samoan
gd Scots Gaelic
sr Serbian
st Sesotho
sn Shona
sd Sindhi
si Sinhala
sk Slovak
sl Slovenian
so Somali
es Spanish Download
su Sundanese
sw Swahili
sv Swedish
tg Tajik
ta Tamil
te Telugu
th Thai
tr Turkish
uk Ukrainian
ur Urdu
uz Uzbek
vi Vietnamese
cy Welsh
xh Xhosa
yi Yiddish
yo Yoruba
zu Zulu
or Odia (Oriya)
rw Kinyarwanda
tk Turkmen
tt Tatar
ug Uyghur
Would you like to inspect the original subtitles? These are the user uploaded subtitles that are being translated: 1 00:00:25,020 --> 00:00:28,000 - Intelligence is the ability to understand. 2 00:00:28,000 --> 00:00:30,220 We passed on what we know to machines. 3 00:00:30,220 --> 00:00:31,760 - The rise of artificial intelligence 4 00:00:31,760 --> 00:00:34,210 is happening fast, but some fear the new technology 5 00:00:34,210 --> 00:00:36,960 might have more problems than anticipated. 6 00:00:36,960 --> 00:00:38,510 - We will not control it. 7 00:01:37,720 --> 00:01:40,290 - Artificially intelligent algorithms are here, 8 00:01:40,290 --> 00:01:41,930 but this is only the beginning. 9 00:01:51,380 --> 00:01:54,850 - In the age of AI, data is the new oil. 10 00:01:57,180 --> 00:01:59,230 - Today, Amazon, Google and Facebook 11 00:01:59,230 --> 00:02:01,440 are richer and more powerful than any companies 12 00:02:01,440 --> 00:02:03,840 that have ever existed throughout human history. 13 00:02:05,000 --> 00:02:08,690 - A handful of people working at a handful of technology companies 14 00:02:08,690 --> 00:02:11,360 steer what a billion people are thinking today. 15 00:02:12,710 --> 00:02:16,840 - This technology is changing: What does it mean to be human? 16 00:03:11,870 --> 00:03:16,340 - Artificial intelligence is simply non-biological intelligence. 17 00:03:17,310 --> 00:03:20,910 And intelligence itself is simply the ability to accomplish goals. 18 00:03:23,440 --> 00:03:26,030 I'm convinced that AI will ultimately be either 19 00:03:26,030 --> 00:03:29,780 the best thing ever to happen to humanity, or the worst thing ever to happen. 20 00:03:31,240 --> 00:03:34,930 We can use it to solve all of today's and tomorrow's 21 00:03:34,930 --> 00:03:40,620 greatest problems; cure diseases, deal with climate change, 22 00:03:40,780 --> 00:03:42,840 lift everybody out of poverty. 23 00:03:44,380 --> 00:03:47,460 But, we could use exactly the same technology 24 00:03:47,460 --> 00:03:51,780 to create a brutal global dictatorship with unprecedented 25 00:03:51,780 --> 00:03:54,600 surveillance and inequality and suffering. 26 00:03:56,230 --> 00:03:59,260 That's why this is the most important conversation of our time. 27 00:04:04,380 --> 00:04:07,590 - Artificial intelligence is everywhere 28 00:04:08,450 --> 00:04:11,500 because we now have thinking machines. 29 00:04:12,420 --> 00:04:15,840 If you go on social media or online, 30 00:04:15,840 --> 00:04:20,290 there's an artificial intelligence engine that decides what to recommend. 31 00:04:21,290 --> 00:04:25,400 If you go on Facebook and you're just scrolling through your friends' posts,- 32 00:04:25,400 --> 00:04:29,100 there's an AI engine that's picking which one to show you first 33 00:04:29,100 --> 00:04:30,840 - and which one to bury. 34 00:04:30,840 --> 00:04:34,190 If you try to get insurance, there is an AI engine 35 00:04:34,190 --> 00:04:36,270 trying to figure out how risky you are. 36 00:04:37,170 --> 00:04:40,710 And if you apply for a job, it's quite possible 37 00:04:40,710 --> 00:04:43,430 that an AI engine looks at the resume. 38 00:04:51,350 --> 00:04:53,500 - We are made of data. 39 00:04:54,240 --> 00:04:59,520 Every one of us is made of data -in terms of how we behave, 40 00:04:59,770 --> 00:05:03,000 how we talk, how we love, what we do every day. 41 00:05:05,410 --> 00:05:09,120 So, computer scientists are developing deep learning 42 00:05:09,120 --> 00:05:14,120 algorithms that can learn to identify, classify, 43 00:05:14,570 --> 00:05:18,680 and predict patterns within massive amounts of data. 44 00:05:31,390 --> 00:05:35,190 We are facing a form of precision surveillance, 45 00:05:35,190 --> 00:05:38,750 you could call it algorithmic surveillance, 46 00:05:38,750 --> 00:05:41,810 and it means that you cannot go unrecognized. 47 00:05:43,120 --> 00:05:46,110 You are always under the watch of algorithms. 48 00:05:51,070 --> 00:05:54,380 - Almost all the AI development on the planet today 49 00:05:54,380 --> 00:05:57,050 is done by a handful of big technology companies 50 00:05:57,050 --> 00:05:58,770 or by a few large governments. 51 00:06:01,930 --> 00:06:06,170 If we look at what AI is mostly being developed for, 52 00:06:06,170 --> 00:06:11,170 I would say it's killing, spying, and brainwashing. 53 00:06:11,570 --> 00:06:13,730 So, I mean, we have military AI, 54 00:06:13,730 --> 00:06:16,850 we have a whole surveillance apparatus being built 55 00:06:16,850 --> 00:06:19,060 using AI by major governments, 56 00:06:19,060 --> 00:06:21,730 and we have an advertising industry which is oriented 57 00:06:21,730 --> 00:06:25,870 toward recognizing what ads to try to sell to someone. 58 00:06:29,080 --> 00:06:32,090 - We humans have come to a fork in the road now. 59 00:06:33,530 --> 00:06:36,670 The AI we have today is very narrow. 60 00:06:37,820 --> 00:06:40,550 The holy grail of AI research ever since the beginning 61 00:06:40,550 --> 00:06:43,300 is to make AI that can do everything better than us, 62 00:06:44,660 --> 00:06:46,280 and we've basically built a God. 63 00:06:47,640 --> 00:06:49,930 It's going to revolutionize life as we know it. 64 00:06:53,040 --> 00:06:55,760 It's incredibly important to take a step back 65 00:06:55,760 --> 00:06:57,660 and think carefully about this. 66 00:06:59,380 --> 00:07:01,510 What sort of society do we want? 67 00:07:04,760 --> 00:07:07,430 - So, we're in this historic transformation. 68 00:07:08,890 --> 00:07:11,260 Like we're raising this new creature. 69 00:07:11,260 --> 00:07:14,230 We have a new offspring of sorts. 70 00:07:16,120 --> 00:07:19,630 But just like actual offspring, 71 00:07:19,630 --> 00:07:22,990 you don't get to control everything it's going to do. 72 00:07:57,000 --> 00:08:00,300 We are living at this privileged moment where, 73 00:08:00,300 --> 00:08:05,270 for the first time, we will see probably that AI 74 00:08:05,270 --> 00:08:08,860 is really going to outcompete humans in many, many, 75 00:08:08,860 --> 00:08:10,460 if not all, important fields. 76 00:08:14,300 --> 00:08:16,450 - Everything is going to change. 77 00:08:16,450 --> 00:08:19,520 A new form of life is emerging. 78 00:08:45,000 --> 00:08:50,900 When I was a boy, I thought, how can I maximize my impact? 79 00:08:52,050 --> 00:08:56,270 And then it was clear that I have to build something 80 00:08:56,270 --> 00:09:00,050 that learns to become smarter than myself, 81 00:09:00,050 --> 00:09:01,680 such that I can retire, 82 00:09:01,680 --> 00:09:04,480 and the smarter thing can further self-improve 83 00:09:04,480 --> 00:09:06,950 and solve all the problems that I cannot solve. 84 00:09:11,180 --> 00:09:14,520 Multiplying that tiny little bit of creativity 85 00:09:14,520 --> 00:09:16,370 that I have into infinity, 86 00:09:18,270 --> 00:09:20,780 and that's what has been driving me since then. 87 00:09:39,220 --> 00:09:40,680 How am I trying to build 88 00:09:40,680 --> 00:09:43,320 a general purpose artificial intelligence? 89 00:09:45,540 --> 00:09:49,690 If you want to be intelligent, you have to recognize speech, 90 00:09:49,690 --> 00:09:54,550 video and handwriting, and faces, and all kinds of things, 91 00:09:54,550 --> 00:09:57,550 and there we have made a lot of progress. 92 00:09:59,290 --> 00:10:02,010 See, LSTM, neural networks, 93 00:10:02,010 --> 00:10:05,890 which we developed in our labs in Munich and in Switzerland, 94 00:10:05,890 --> 00:10:10,460 and it's now used for speech recognition and translation, 95 00:10:10,460 --> 00:10:12,640 and video recognition. 96 00:10:12,640 --> 00:10:16,660 They are now in everybody's smartphone, almost one billion 97 00:10:16,660 --> 00:10:20,660 iPhones and in over two billion Android phones. 98 00:10:21,990 --> 00:10:26,990 So, we are generating all kinds of useful by-products 99 00:10:27,490 --> 00:10:29,040 on the way to the general goal. 100 00:10:40,000 --> 00:10:44,990 The main goal, some Artificial General Intelligence, 101 00:10:44,990 --> 00:10:51,400 an AGI that can learn to improve the learning algorithm itself. 102 00:10:52,960 --> 00:10:56,940 So, it basically can learn to improve the way it learns 103 00:10:56,940 --> 00:11:00,940 and it can also recursively improve the way it learns, 104 00:11:00,940 --> 00:11:04,460 the way it learns without any limitations except for 105 00:11:04,460 --> 00:11:07,970 the basic fundamental limitations of computability. 106 00:11:14,590 --> 00:11:17,880 One of my favorite robots is this one here. 107 00:11:17,880 --> 00:11:21,380 We use this robot for our studies of artificial curiosity. 108 00:11:22,640 --> 00:11:27,620 Where we are trying to teach this robot to teach itself. 109 00:11:32,870 --> 00:11:33,960 What is a baby doing? 110 00:11:33,960 --> 00:11:37,820 A baby is curiously exploring its world. 111 00:11:39,970 --> 00:11:42,210 That's how he learns how gravity works 112 00:11:42,210 --> 00:11:45,130 and how certain things topple, and so on. 113 00:11:46,700 --> 00:11:49,980 And as it learns to ask questions about the world, 114 00:11:49,980 --> 00:11:52,640 and as it learns to answer these questions, 115 00:11:52,640 --> 00:11:55,500 it becomes a more and more general problem solver. 116 00:11:56,540 --> 00:11:59,160 And so, our artificial systems are also learning 117 00:11:59,160 --> 00:12:03,320 to ask all kinds of questions, not just slavishly 118 00:12:03,320 --> 00:12:07,010 try to answer the questions given to them by humans. 119 00:12:10,880 --> 00:12:14,920 You have to give AI the freedom to invent its own tasks. 120 00:12:17,830 --> 00:12:20,610 If you don't do that, it's not going to become very smart. 121 00:12:22,160 --> 00:12:26,780 On the other hand, it's really hard to predict what they are going to do. 122 00:12:49,560 --> 00:12:52,910 - I feel that technology is a force of nature. 123 00:12:55,420 --> 00:13:00,020 I feel like there is a lot of similarity between technology and biological evolution. 124 00:13:08,850 --> 00:13:10,140 Playing God. 125 00:13:13,470 --> 00:13:16,500 Scientists have been accused of playing God for a while, 126 00:13:17,960 --> 00:13:22,410 - but there is a real sense in which we are creating something 127 00:13:23,380 --> 00:13:26,250 very different from anything we've created so far. 128 00:13:49,790 --> 00:13:53,250 I was interested in the concept of AI from a relatively early age. 129 00:13:55,080 --> 00:13:58,420 At some point, I got especially interested in machine learning. 130 00:14:01,690 --> 00:14:03,520 What is experience? 131 00:14:03,520 --> 00:14:04,710 What is learning? 132 00:14:04,710 --> 00:14:05,720 What is thinking? 133 00:14:06,890 --> 00:14:08,150 How does the brain work? 134 00:14:10,140 --> 00:14:11,940 These questions are philosophical, 135 00:14:11,940 --> 00:14:15,190 but it looks like we can come up with algorithms that 136 00:14:15,190 --> 00:14:18,530 both do useful things and help us answer these questions. 137 00:14:20,000 --> 00:14:22,250 Like it's almost like applied philosophy. 138 00:14:48,060 --> 00:14:51,410 Artificial General Intelligence, AGI. 139 00:14:52,610 --> 00:14:57,210 A computer system that can do any job or any task 140 00:14:57,210 --> 00:15:00,380 that a human does, but only better. 141 00:15:13,180 --> 00:15:15,810 Yeah, I mean, we definitely will be able to create 142 00:15:17,340 --> 00:15:20,150 completely autonomous beings with their own goals. 143 00:15:24,060 --> 00:15:25,630 And it will be very important, 144 00:15:25,630 --> 00:15:30,440 especially as these beings become much smarter than humans, 145 00:15:30,440 --> 00:15:34,720 it's going to be important to have these beings, 146 00:15:36,220 --> 00:15:39,330 that the goals of these beings be aligned with our goals. 147 00:15:42,600 --> 00:15:45,340 That's what we're trying to do at OpenAI. 148 00:15:45,340 --> 00:15:49,700 Be at the forefront of research and steer the research, 149 00:15:49,700 --> 00:15:53,940 steer their initial conditions so to maximize the chance 150 00:15:53,940 --> 00:15:56,100 that the future will be good for humans. 151 00:16:11,660 --> 00:16:14,370 Now, AI is a great thing because AI will solve 152 00:16:14,370 --> 00:16:16,440 all the problems that we have today. 153 00:16:19,080 --> 00:16:22,580 It will solve employment, it will solve disease, 154 00:16:24,670 --> 00:16:26,560 it will solve poverty, 155 00:16:29,000 --> 00:16:31,360 but it will also create new problems. 156 00:16:34,580 --> 00:16:36,320 I think that... 157 00:16:40,490 --> 00:16:43,120 The problem of fake news is going to be a thousand, 158 00:16:43,120 --> 00:16:44,360 a million times worse. 159 00:16:46,440 --> 00:16:48,820 Cyberattacks will become much more extreme. 160 00:16:50,640 --> 00:16:53,470 You will have totally automated AI weapons. 161 00:16:56,100 --> 00:16:59,980 I think AI has the potential to create infinitely stable dictatorships. 162 00:17:05,820 --> 00:17:08,850 You're gonna see dramatically more intelligent systems 163 00:17:08,850 --> 00:17:12,620 in 10 or 15 years from now, and I think it's highly likely 164 00:17:12,620 --> 00:17:17,120 that those systems will have completely astronomical impact on society. 165 00:17:19,480 --> 00:17:21,160 Will humans actually benefit? 166 00:17:22,860 --> 00:17:24,860 And who will benefit, who will not? 167 00:17:44,560 --> 00:17:47,660 - In 2012, IBM estimated that 168 00:17:47,660 --> 00:17:52,090 an average person is generating 500 megabytes 169 00:17:52,090 --> 00:17:55,110 of digital footprints every single day. 170 00:17:55,110 --> 00:17:57,390 Imagine that you wanted to back-up one day worth 171 00:17:57,390 --> 00:18:01,260 of data that humanity is leaving behind, on paper. 172 00:18:01,260 --> 00:18:04,370 How tall will be the stack of paper that contains 173 00:18:04,370 --> 00:18:07,820 just one day worth of data that humanity is producing? 174 00:18:09,610 --> 00:18:12,670 It's like from the earth to the sun, four times over. 175 00:18:14,550 --> 00:18:20,340 In 2025, we'll be generating 62 gigabytes of data 176 00:18:20,640 --> 00:18:22,380 per person, per day. 177 00:18:36,970 --> 00:18:42,380 We're leaving a ton of digital footprints while going through our lives. 178 00:18:44,790 --> 00:18:49,380 They provide computer algorithms with a fairly good idea about who we are, 179 00:18:49,380 --> 00:18:52,280 what we want, what we are doing. 180 00:18:56,020 --> 00:18:59,320 In my work, I looked at different types of digital footprints. 181 00:18:59,320 --> 00:19:02,650 I looked at Facebook likes, I looked at language, 182 00:19:02,650 --> 00:19:06,890 credit card records, web browsing histories, search records. 183 00:19:07,740 --> 00:19:12,010 and each time I found that if you get enough of this data, 184 00:19:12,010 --> 00:19:14,370 you can accurately predict future behavior 185 00:19:14,370 --> 00:19:17,560 and reveal important intimate traits. 186 00:19:19,140 --> 00:19:21,270 This can be used in great ways, 187 00:19:21,270 --> 00:19:24,670 but it can also be used to manipulate people. 188 00:19:29,910 --> 00:19:33,880 Facebook is delivering daily information 189 00:19:33,880 --> 00:19:36,460 to two billion people or more. 190 00:19:38,750 --> 00:19:42,840 If you slightly change the functioning of the Facebook engine, 191 00:19:42,840 --> 00:19:46,500 you can move the opinions and hence, 192 00:19:46,500 --> 00:19:49,870 the votes of millions of people. 193 00:19:50,720 --> 00:19:52,680 - Brexit! - When do we want it? 194 00:19:52,720 --> 00:19:54,140 - Now! 195 00:19:56,070 --> 00:19:58,690 - A politician wouldn't be able to figure out 196 00:19:58,690 --> 00:20:02,830 which message each one of his or her voters would like, 197 00:20:02,830 --> 00:20:06,010 but a computer can see what political message 198 00:20:06,010 --> 00:20:08,920 would be particularly convincing for you. 199 00:20:11,320 --> 00:20:12,640 - Ladies and gentlemen, 200 00:20:12,640 --> 00:20:16,170 it's my privilege to speak to you today about the power 201 00:20:16,170 --> 00:20:20,430 of big data and psychographics in the electoral process. 202 00:20:20,430 --> 00:20:22,360 - Data from Cambridge Analytica 203 00:20:22,360 --> 00:20:25,070 secretly harvested the personal information 204 00:20:25,070 --> 00:20:28,320 of 50 million unsuspecting Facebook users. 205 00:20:28,320 --> 00:20:31,690 USA! 206 00:20:31,690 --> 00:20:35,500 - The data firm hired by Donald Trump's presidential election campaign 207 00:20:35,870 --> 00:20:41,080 used secretly obtained information to directly target potential American voters. 208 00:20:41,080 --> 00:20:42,940 - With that, they say they can predict 209 00:20:42,940 --> 00:20:46,760 the personality of every single adult in the United States. 210 00:20:47,470 --> 00:20:49,460 - Tonight we're hearing from Cambridge Analytica 211 00:20:49,460 --> 00:20:51,650 whistleblower, Christopher Wiley. 212 00:20:51,650 --> 00:20:54,990 - What we worked on was data harvesting programs 213 00:20:54,990 --> 00:20:59,200 where we would pull data and run that data through algorithms that could profile 214 00:20:59,200 --> 00:21:01,930 their personality traits and other psychological attributes 215 00:21:01,930 --> 00:21:06,580 to exploit mental vulnerabilities that our algorithms showed that they had. 216 00:21:15,500 --> 00:21:17,570 - Cambridge Analytica mentioned once 217 00:21:17,570 --> 00:21:20,460 or said that their models were based on my work, 218 00:21:22,510 --> 00:21:25,140 but Cambridge Analytica is just one of the hundreds 219 00:21:25,140 --> 00:21:30,040 of companies that are using such methods to target voters. 220 00:21:32,130 --> 00:21:35,760 You know, I would be asked questions by journalists such as, 221 00:21:35,760 --> 00:21:37,220 "So how do you feel about 222 00:21:38,810 --> 00:21:41,990 "electing Trump and supporting Brexit?" 223 00:21:41,990 --> 00:21:43,940 How do you answer to such question? 224 00:21:45,400 --> 00:21:51,740 I guess that I have to deal with being blamed for all of it. 225 00:22:07,700 --> 00:22:12,480 - How tech started was as a democratizing force, 226 00:22:12,480 --> 00:22:15,110 as a force for good, as an ability for humans 227 00:22:15,110 --> 00:22:17,900 to interact with each other without gatekeepers. 228 00:22:20,210 --> 00:22:25,110 There's never been a bigger experiment in communications for the human race. 229 00:22:26,330 --> 00:22:29,060 What happens when everybody gets to have their say? 230 00:22:29,780 --> 00:22:31,850 You would assume that it would be for the better, 231 00:22:31,850 --> 00:22:34,540 that there would be more democracy, there would be more discussion, 232 00:22:34,540 --> 00:22:37,660 there would be more tolerance, but what's happened is that 233 00:22:37,660 --> 00:22:39,720 these systems have been hijacked. 234 00:22:41,300 --> 00:22:43,860 - We stand for connecting every person. 235 00:22:44,960 --> 00:22:46,620 For a global community. 236 00:22:47,780 --> 00:22:50,500 - One company, Facebook, is responsible 237 00:22:50,500 --> 00:22:53,540 for the communications of a lot of the human race. 238 00:22:55,650 --> 00:22:57,360 Same thing with Google. 239 00:22:57,360 --> 00:23:00,540 Everything you want know about the world comes from them. 240 00:23:01,540 --> 00:23:05,120 This is global information economy 241 00:23:05,120 --> 00:23:07,830 that is controlled by a small group of people. 242 00:23:14,400 --> 00:23:17,920 - The world's richest companies are all technology companies. 243 00:23:18,770 --> 00:23:24,500 Google, Apple, Microsoft, Amazon, Facebook. 244 00:23:25,880 --> 00:23:29,040 It's staggering how, 245 00:23:29,040 --> 00:23:31,770 in probably just 10 years, 246 00:23:31,770 --> 00:23:34,810 that the entire corporate power structure 247 00:23:34,810 --> 00:23:39,460 are basically in the business of trading electrons. 248 00:23:41,240 --> 00:23:47,060 These little bits and bytes are really the new currency. 249 00:23:53,560 --> 00:23:55,800 - The way that data is monetized 250 00:23:55,800 --> 00:23:58,820 is happening all around us, even if it's invisible to us. 251 00:24:00,960 --> 00:24:04,280 Google has every amount of information available. 252 00:24:04,280 --> 00:24:07,110 They track people by their GPS location. 253 00:24:07,110 --> 00:24:10,080 They know exactly what your search history has been. 254 00:24:10,080 --> 00:24:12,850 They know your political preferences. 255 00:24:12,850 --> 00:24:14,840 Your search history alone can tell you 256 00:24:14,840 --> 00:24:17,570 everything about an individual from their health problems 257 00:24:17,570 --> 00:24:19,480 to their sexual preferences. 258 00:24:19,480 --> 00:24:21,880 So, Google's reach is unlimited. 259 00:24:28,750 --> 00:24:31,620 - So we've seen Google and Facebook 260 00:24:31,620 --> 00:24:34,150 rise into these large surveillance machines 261 00:24:35,040 --> 00:24:38,200 and they're both actually ad brokers. 262 00:24:38,200 --> 00:24:42,040 It sounds really mundane, but they're high tech ad brokers. 263 00:24:42,910 --> 00:24:46,080 And the reason they're so profitable is that they're using 264 00:24:46,080 --> 00:24:49,750 artificial intelligence to process all this data about you, 265 00:24:51,560 --> 00:24:54,660 and then to match you with the advertiser 266 00:24:54,660 --> 00:24:59,660 that wants to reach people like you, - for whatever message. 267 00:25:03,000 --> 00:25:07,880 - One of the problems with technology is that it's been developed to be addictive. 268 00:25:07,880 --> 00:25:09,910 The way these companies design these things 269 00:25:09,910 --> 00:25:12,010 is in order to pull you in and engage you. 270 00:25:13,180 --> 00:25:16,820 They want to become essentially a slot machine of attention. 271 00:25:18,600 --> 00:25:21,770 So you're always paying attention, you're always jacked into the matrix, 272 00:25:21,770 --> 00:25:23,520 you're always checking. 273 00:25:26,580 --> 00:25:30,450 - When somebody controls what you read, they also control what you think. 274 00:25:32,180 --> 00:25:34,610 You get more of what you've seen before and liked before, 275 00:25:34,610 --> 00:25:37,890 because this gives more traffic and that gives more ads, 276 00:25:39,410 --> 00:25:43,160 but it also locks you into your echo chamber. 277 00:25:43,160 --> 00:25:46,350 And this is what leads to this polarization that we see today. 278 00:25:46,460 --> 00:25:49,300 Jair Bolsonaro! 279 00:25:49,970 --> 00:25:52,590 - Jair Bolsonaro, Brazil's right-wing 280 00:25:52,590 --> 00:25:56,000 populist candidate sometimes likened to Donald Trump, 281 00:25:56,000 --> 00:25:58,640 winning the presidency Sunday night in that country's 282 00:25:58,640 --> 00:26:01,840 most polarizing election in decades. 283 00:26:01,840 --> 00:26:02,840 - Bolsonaro! 284 00:26:04,160 --> 00:26:09,550 - What we are seeing around the world is upheaval and polarization and conflict 285 00:26:10,770 --> 00:26:15,000 that is partially pushed by algorithms 286 00:26:15,000 --> 00:26:19,070 that's figured out that political extremes, 287 00:26:19,070 --> 00:26:22,180 tribalism, and sort of shouting for your team, 288 00:26:22,180 --> 00:26:25,290 and feeling good about it, is engaging. 289 00:26:30,420 --> 00:26:33,150 - Social media may be adding to the attention 290 00:26:33,150 --> 00:26:35,490 to hate crimes around the globe. 291 00:26:35,490 --> 00:26:38,120 - It's about how people can become radicalized 292 00:26:38,120 --> 00:26:41,740 by living in the fever swamps of the Internet. 293 00:26:41,740 --> 00:26:45,960 - So is this a key moment for the tech giants? Are they now prepared to take responsibility 294 00:26:45,960 --> 00:26:48,840 as publishers for what they share with the world? 295 00:26:49,790 --> 00:26:52,750 - If you deploy a powerful potent technology 296 00:26:52,750 --> 00:26:56,670 at scale, and if you're talking about Google and Facebook, 297 00:26:56,670 --> 00:26:59,530 you're deploying things at scale of billions. 298 00:26:59,530 --> 00:27:02,770 If your artificial intelligence is pushing polarization, 299 00:27:02,770 --> 00:27:05,090 you have global upheaval potentially. 300 00:27:05,720 --> 00:27:09,240 White lives matter! 301 00:27:09,320 --> 00:27:13,620 Black lives matter! 302 00:28:00,620 --> 00:28:04,040 - Artificial General Intelligence, AGI. 303 00:28:06,350 --> 00:28:08,320 Imagine your smartest friend, 304 00:28:09,600 --> 00:28:11,950 with 1,000 friends, just as smart, 305 00:28:14,680 --> 00:28:17,580 and then run them at a 1,000 times faster than real time. 306 00:28:17,580 --> 00:28:19,940 So it means that in every day of our time, 307 00:28:19,940 --> 00:28:22,510 they will do three years of thinking. 308 00:28:22,510 --> 00:28:25,520 Can you imagine how much you could do 309 00:28:26,580 --> 00:28:31,480 if, for every day, you could do three years' worth of work? 310 00:28:52,440 --> 00:28:55,720 It wouldn't be an unfair comparison to say 311 00:28:55,720 --> 00:28:59,780 that what we have right now is even more exciting than 312 00:28:59,780 --> 00:29:02,510 the quantum physicists of the early 20th century. 313 00:29:02,510 --> 00:29:04,240 They discovered nuclear power. 314 00:29:05,740 --> 00:29:08,380 I feel extremely lucky to be taking part in this. 315 00:29:15,310 --> 00:29:18,820 Many machine learning experts, who are very knowledgeable and experienced, 316 00:29:18,820 --> 00:29:20,820 have a lot of skepticism about AGI. 317 00:29:22,350 --> 00:29:25,900 About when it would happen, and about whether it could happen at all. 318 00:29:31,460 --> 00:29:35,740 But right now, this is something that just not that many people have realized yet. 319 00:29:36,500 --> 00:29:41,240 That the speed of computers, for neural networks, for AI, 320 00:29:41,240 --> 00:29:45,240 are going to become maybe 100,000 times faster 321 00:29:45,240 --> 00:29:46,980 in a small number of years. 322 00:29:49,330 --> 00:29:52,100 The entire hardware industry for a long time 323 00:29:52,100 --> 00:29:54,660 didn't really know what to do next, 324 00:29:55,660 --> 00:30:00,900 but with artificial neural networks, now that they actually work, 325 00:30:00,900 --> 00:30:03,420 you have a reason to build huge computers. 326 00:30:04,530 --> 00:30:06,930 You can build a brain in silicon, it's possible. 327 00:30:14,450 --> 00:30:18,710 The very first AGIs will be basically very, 328 00:30:18,710 --> 00:30:22,850 very large data centers packed with specialized 329 00:30:22,850 --> 00:30:25,660 neural network processors working in parallel. 330 00:30:28,070 --> 00:30:30,920 Compact, hot, power hungry package, 331 00:30:32,140 --> 00:30:35,540 consuming like 10 million homes' worth of energy. 332 00:30:54,140 --> 00:30:55,640 A roast beef sandwich. 333 00:30:55,640 --> 00:30:58,290 Yeah, something slightly different. 334 00:30:58,290 --> 00:30:59,200 Just this once. 335 00:31:04,060 --> 00:31:06,260 Even the very first AGIs 336 00:31:06,260 --> 00:31:09,060 will be dramatically more capable than humans. 337 00:31:10,970 --> 00:31:14,730 Humans will no longer be economically useful for nearly any task. 338 00:31:16,200 --> 00:31:17,880 Why would you want to hire a human, 339 00:31:17,880 --> 00:31:21,980 if you could just get a computer that's going to do it much better and much more cheaply? 340 00:31:28,900 --> 00:31:31,020 AGI is going to be like, without question, 341 00:31:31,880 --> 00:31:34,660 the most important technology in the history 342 00:31:34,660 --> 00:31:36,600 of the planet by a huge margin. 343 00:31:39,410 --> 00:31:42,550 It's going to be bigger than electricity, nuclear, 344 00:31:42,550 --> 00:31:44,140 and the Internet combined. 345 00:31:45,740 --> 00:31:47,620 In fact, you could say that the whole purpose 346 00:31:47,620 --> 00:31:49,660 of all human science, the purpose of computer science, 347 00:31:49,660 --> 00:31:52,550 the End Game, this is the End Game, to build this. 348 00:31:52,550 --> 00:31:54,130 And it's going to be built. 349 00:31:54,130 --> 00:31:56,000 It's going to be a new life form. 350 00:31:56,000 --> 00:31:57,090 It's going to be... 351 00:31:59,190 --> 00:32:00,740 It's going to make us obsolete. 352 00:32:22,070 --> 00:32:24,520 - European manufacturers know the Americans 353 00:32:24,520 --> 00:32:27,460 have invested heavily in the necessary hardware. 354 00:32:27,460 --> 00:32:29,780 - Step into a brave new world of power, 355 00:32:29,780 --> 00:32:31,630 performance and productivity. 356 00:32:32,360 --> 00:32:35,480 - All of the images you are about to see on the large screen 357 00:32:35,480 --> 00:32:39,030 will be generated by what's in that Macintosh. 358 00:32:39,760 --> 00:32:42,210 - It's my honor and privilege to introduce to you 359 00:32:42,210 --> 00:32:44,700 the Windows 95 Development Team. 360 00:32:45,640 --> 00:32:49,040 - Human physical labor has been mostly obsolete for 361 00:32:49,040 --> 00:32:50,620 getting on for a century. 362 00:32:51,390 --> 00:32:55,300 Routine human mental labor is rapidly becoming obsolete 363 00:32:55,300 --> 00:32:58,980 and that's why we're seeing a lot of the middle class jobs disappearing. 364 00:33:01,010 --> 00:33:02,340 - Every once in a while, 365 00:33:02,340 --> 00:33:06,370 a revolutionary product comes along that changes everything. 366 00:33:06,370 --> 00:33:09,190 Today, Apple is reinventing the phone. 367 00:33:20,730 --> 00:33:24,270 - Machine intelligence is already all around us. 368 00:33:24,270 --> 00:33:27,620 The list of things that we humans can do better than machines 369 00:33:27,620 --> 00:33:29,600 is actually shrinking pretty fast. 370 00:33:35,730 --> 00:33:37,400 - Driverless cars are great. 371 00:33:37,400 --> 00:33:40,010 They probably will reduce accidents. 372 00:33:40,010 --> 00:33:43,670 Except, alongside with that, in the United States, 373 00:33:43,670 --> 00:33:46,410 you're going to lose 10 million jobs. 374 00:33:46,480 --> 00:33:49,980 What are you going to do with 10 million unemployed people? 375 00:33:54,900 --> 00:33:58,660 - The risk for social conflict and tensions, 376 00:33:58,660 --> 00:34:02,080 if you exacerbate inequalities, is very, very high. 377 00:34:11,560 --> 00:34:13,870 - AGI can, by definition, 378 00:34:13,870 --> 00:34:16,700 do all jobs better than we can do. 379 00:34:16,700 --> 00:34:18,610 People who are saying, "There will always be jobs 380 00:34:18,610 --> 00:34:21,120 "that humans can do better than machines," are simply 381 00:34:21,120 --> 00:34:24,180 betting against science and saying there will never be AGI. 382 00:34:30,860 --> 00:34:33,630 - What we are seeing now is like a train hurtling 383 00:34:33,630 --> 00:34:37,880 down a dark tunnel at breakneck speed and it looks like 384 00:34:37,880 --> 00:34:39,660 we're sleeping at the wheel. 385 00:35:29,170 --> 00:35:34,710 - A large fraction of the digital footprints we're leaving behind are digital images. 386 00:35:35,690 --> 00:35:39,340 And specifically, what's really interesting to me as a psychologist 387 00:35:39,340 --> 00:35:41,470 are digital images of our faces. 388 00:35:44,500 --> 00:35:47,260 Here you can see the difference in the facial outline 389 00:35:47,260 --> 00:35:50,130 of an average gay and an average straight face. 390 00:35:50,130 --> 00:35:52,660 And you can see that straight men 391 00:35:52,660 --> 00:35:55,380 have slightly broader jaws. 392 00:35:55,680 --> 00:36:00,580 Gay women have slightly larger jaws, compared with straight women. 393 00:36:02,510 --> 00:36:05,670 Computer algorithms can reveal our political views 394 00:36:05,670 --> 00:36:08,280 or sexual orientation, or intelligence, 395 00:36:08,280 --> 00:36:11,120 just based on the picture of our faces. 396 00:36:12,070 --> 00:36:16,760 Even a human brain can distinguish between gay and straight men with some accuracy. 397 00:36:16,920 --> 00:36:21,700 Now it turns out that the computer can do it with much higher accuracy. 398 00:36:21,700 --> 00:36:25,200 What you're seeing here is an accuracy of 399 00:36:25,200 --> 00:36:29,410 off-the-shelf facial recognition software. 400 00:36:29,410 --> 00:36:31,640 This is terrible news 401 00:36:31,640 --> 00:36:34,320 for gay men and women all around the world. 402 00:36:34,320 --> 00:36:35,680 And not only gay men and women, 403 00:36:35,680 --> 00:36:38,300 because the same algorithms can be used to detect other 404 00:36:38,300 --> 00:36:42,350 intimate traits, think being a member of the opposition, 405 00:36:42,350 --> 00:36:45,090 or being a liberal, or being an atheist. 406 00:36:46,850 --> 00:36:50,070 Being an atheist is also punishable by death 407 00:36:50,070 --> 00:36:52,610 in Saudi Arabia, for instance. 408 00:36:59,780 --> 00:37:04,440 My mission as an academic is to warn people about the dangers of algorithms 409 00:37:04,440 --> 00:37:08,290 being able to reveal our intimate traits. 410 00:37:09,780 --> 00:37:14,060 The problem is that when people receive bad news, 411 00:37:14,060 --> 00:37:16,260 they very often choose to dismiss them. 412 00:37:17,810 --> 00:37:22,250 Well, it's a bit scary when you start receiving death threats from one day to another, 413 00:37:22,250 --> 00:37:24,830 and I've received quite a few death threats, - 414 00:37:25,910 --> 00:37:30,870 -but as a scientist, I have to basically show what is possible. 415 00:37:33,590 --> 00:37:36,900 So what I'm really interested in now is to try to see 416 00:37:36,900 --> 00:37:41,080 whether we can predict other traits from people's faces. 417 00:37:46,270 --> 00:37:48,580 Now, if you can detect depression from a face, 418 00:37:48,580 --> 00:37:53,580 or suicidal thoughts, maybe a CCTV system 419 00:37:53,690 --> 00:37:56,970 on the train station can save some lives. 420 00:37:59,130 --> 00:38:03,830 What if we could predict that someone is more prone to commit a crime? 421 00:38:04,960 --> 00:38:07,150 You probably had a school counselor, 422 00:38:07,150 --> 00:38:10,380 a psychologist hired there to identify children 423 00:38:10,380 --> 00:38:14,830 that potentially may have some behavioral problems. 424 00:38:17,330 --> 00:38:20,080 So now imagine if you could predict with high accuracy 425 00:38:20,080 --> 00:38:22,590 that someone is likely to commit a crime in the future 426 00:38:22,590 --> 00:38:24,780 from the language use, from the face, 427 00:38:24,780 --> 00:38:27,580 from the facial expressions, from the likes on Facebook. 428 00:38:32,310 --> 00:38:35,210 I'm not developing new methods, I'm just describing 429 00:38:35,210 --> 00:38:38,890 something or testing something in an academic environment. 430 00:38:40,590 --> 00:38:42,790 But there obviously is a chance that, 431 00:38:42,790 --> 00:38:47,790 while warning people against risks of new technologies, 432 00:38:47,960 --> 00:38:50,560 I may also give some people new ideas. 433 00:39:11,140 --> 00:39:13,830 - We haven't yet seen the future in terms of 434 00:39:13,830 --> 00:39:18,780 the ways in which the new data-driven society 435 00:39:18,780 --> 00:39:21,380 is going to really evolve. 436 00:39:23,540 --> 00:39:26,740 The tech companies want to get every possible bit 437 00:39:26,740 --> 00:39:30,170 of information that they can collect on everyone 438 00:39:30,170 --> 00:39:31,690 to facilitate business. 439 00:39:33,470 --> 00:39:37,090 The police and the military want to do the same thing 440 00:39:37,090 --> 00:39:38,830 to facilitate security. 441 00:39:41,960 --> 00:39:46,440 The interests that the two have in common are immense, 442 00:39:46,440 --> 00:39:51,220 and so the extent of collaboration between what you might 443 00:39:51,220 --> 00:39:56,820 call the Military-Tech Complex is growing dramatically. 444 00:40:00,400 --> 00:40:03,010 - The CIA, for a very long time, 445 00:40:03,010 --> 00:40:06,120 has maintained a close connection with Silicon Valley. 446 00:40:07,110 --> 00:40:10,270 Their venture capital firm known as In-Q-Tel, 447 00:40:10,270 --> 00:40:13,870 makes seed investments to start-up companies developing 448 00:40:13,870 --> 00:40:17,490 breakthrough technology that the CIA hopes to deploy. 449 00:40:18,660 --> 00:40:22,100 Palantir, the big data analytics firm, 450 00:40:22,100 --> 00:40:25,100 one of their first seed investments was from In-Q-Tel. 451 00:40:28,950 --> 00:40:31,780 - In-Q-Tel has struck gold in Palantir 452 00:40:31,780 --> 00:40:35,990 in helping to create a private vendor 453 00:40:35,990 --> 00:40:40,850 that has intelligence and artificial intelligence 454 00:40:40,850 --> 00:40:44,460 capabilities that the government can't even compete with. 455 00:40:46,370 --> 00:40:48,720 - Good evening, I'm Peter Thiel. 456 00:40:49,740 --> 00:40:54,210 I'm not a politician, but neither is Donald Trump. 457 00:40:54,210 --> 00:40:58,620 He is a builder and it's time to rebuild America. 458 00:41:01,280 --> 00:41:03,940 - Peter Thiel, the founder of Palantir, 459 00:41:03,940 --> 00:41:06,680 was a Donald Trump transition advisor 460 00:41:06,680 --> 00:41:09,180 and a close friend and donor. 461 00:41:11,080 --> 00:41:13,700 Trump was elected largely on the promise 462 00:41:13,700 --> 00:41:17,560 to deport millions of immigrants. 463 00:41:17,560 --> 00:41:22,240 The only way you can do that is with a lot of intelligence 464 00:41:22,240 --> 00:41:25,010 and that's where Palantir comes in. 465 00:41:28,680 --> 00:41:33,340 They ingest huge troves of data, which include, 466 00:41:33,340 --> 00:41:37,370 where you live, where you work, who you know, 467 00:41:37,370 --> 00:41:40,930 who your neighbors are, who your family is, 468 00:41:40,930 --> 00:41:44,480 where you have visited, where you stay, 469 00:41:44,480 --> 00:41:46,320 your social media profile. 470 00:41:49,250 --> 00:41:53,240 Palantir gets all of that and is remarkably good 471 00:41:53,240 --> 00:41:58,240 at structuring it in a way that helps law enforcement, 472 00:41:58,460 --> 00:42:02,450 immigration authorities or intelligence agencies 473 00:42:02,450 --> 00:42:06,210 of any kind, track you, find you, 474 00:42:06,210 --> 00:42:09,550 and learn everything there is to know about you. 475 00:42:48,430 --> 00:42:51,040 - We're putting AI in charge now of evermore 476 00:42:51,040 --> 00:42:53,860 important decisions that affect people's lives. 477 00:42:54,810 --> 00:42:58,050 Old-school AI used to have its intelligence programmed in 478 00:42:58,050 --> 00:43:01,420 by humans who understood how it worked, but today, 479 00:43:01,420 --> 00:43:04,080 powerful AI systems have just learned for themselves, 480 00:43:04,080 --> 00:43:07,480 and we have no clue really how they work, 481 00:43:07,480 --> 00:43:09,680 which makes it really hard to trust them. 482 00:43:14,270 --> 00:43:17,820 - This isn't some futuristic technology, this is now. 483 00:43:19,470 --> 00:43:23,220 AI might help determine where a fire department 484 00:43:23,220 --> 00:43:25,900 is built in a community or where a school is built. 485 00:43:25,900 --> 00:43:28,380 It might decide whether you get bail, 486 00:43:28,380 --> 00:43:30,680 or whether you stay in jail. 487 00:43:30,680 --> 00:43:32,930 It might decide where the police are going to be. 488 00:43:32,930 --> 00:43:37,140 It might decide whether you're going to be under additional police scrutiny. 489 00:43:43,340 --> 00:43:46,140 - It's popular now in the US to do predictive policing. 490 00:43:46,980 --> 00:43:50,900 So what they do is they use an algorithm to figure out where crime will be, 491 00:43:51,760 --> 00:43:55,240 - and they use that to tell where we should send police officers. 492 00:43:56,430 --> 00:43:59,420 So that's based on a measurement of crime rate. 493 00:44:00,640 --> 00:44:02,330 So we know that there is bias. 494 00:44:02,330 --> 00:44:05,090 Black people and Hispanic people are pulled over, 495 00:44:05,090 --> 00:44:07,180 and stopped by the police officers more frequently 496 00:44:07,180 --> 00:44:09,820 than white people are, so we have this biased data going in, 497 00:44:09,820 --> 00:44:11,820 and then what happens is you use that to say, 498 00:44:11,820 --> 00:44:13,640 "Here's where the cops should go." 499 00:44:13,640 --> 00:44:17,320 Well, the cops go to those neighborhoods, and guess what they do, they arrest people. 500 00:44:17,680 --> 00:44:21,160 And then it feeds back biased data into the system, 501 00:44:21,160 --> 00:44:23,060 and that's called a feedback loop. 502 00:44:35,990 --> 00:44:40,650 - Predictive policing leads at the extremes 503 00:44:41,590 --> 00:44:45,910 to experts saying, "Show me your baby, 504 00:44:45,910 --> 00:44:48,860 "and I will tell you whether she's going to be a criminal." 505 00:44:51,300 --> 00:44:55,780 Now that we can predict it, we're going to then surveil 506 00:44:55,780 --> 00:45:01,100 those kids much more closely and we're going to jump on them 507 00:45:01,100 --> 00:45:03,700 at the first sign of a problem. 508 00:45:03,700 --> 00:45:06,700 And that's going to make for more effective policing. 509 00:45:07,000 --> 00:45:11,250 It does, but it's going to make for a really grim society 510 00:45:11,250 --> 00:45:16,250 and it's reinforcing dramatically existing injustices. 511 00:45:22,960 --> 00:45:27,810 - Imagine a world in which networks of CCTV cameras, 512 00:45:27,810 --> 00:45:30,930 drone surveillance cameras, have sophisticated 513 00:45:30,930 --> 00:45:34,440 face recognition technologies and are connected 514 00:45:34,440 --> 00:45:37,020 to other government surveillance databases. 515 00:45:38,080 --> 00:45:41,190 We will have the technology in place to have 516 00:45:41,190 --> 00:45:45,690 all of our movements comprehensively tracked and recorded. 517 00:45:47,680 --> 00:45:50,330 What that also means is that we will have 518 00:45:50,330 --> 00:45:52,940 created a surveillance time machine 519 00:45:52,940 --> 00:45:56,620 that will allow governments and powerful corporations 520 00:45:56,620 --> 00:45:58,710 to essentially hit rewind on our lives. 521 00:45:58,710 --> 00:46:01,780 We might not be under any suspicion now 522 00:46:01,780 --> 00:46:03,860 and five years from now, they might want to know 523 00:46:03,860 --> 00:46:08,100 more about us, and can then recreate granularly 524 00:46:08,100 --> 00:46:10,260 everything we've done, everyone we've seen, 525 00:46:10,260 --> 00:46:13,050 everyone we've been around over that entire period. 526 00:46:15,820 --> 00:46:19,320 That's an extraordinary amount of power 527 00:46:19,320 --> 00:46:21,660 for us to seed to anyone. 528 00:46:22,910 --> 00:46:25,370 And it's a world that I think has been difficult 529 00:46:25,370 --> 00:46:29,180 for people to imagine, but we've already built 530 00:46:29,180 --> 00:46:31,660 the architecture to enable that. 531 00:47:07,140 --> 00:47:10,290 - I'm a political reporter and I'm very interested 532 00:47:10,290 --> 00:47:14,670 in the ways powerful industries use their political power 533 00:47:14,670 --> 00:47:17,180 to influence the public policy process. 534 00:47:21,000 --> 00:47:24,420 The large tech companies and their lobbyists get together 535 00:47:24,420 --> 00:47:27,530 behind closed doors and are able to craft policies 536 00:47:27,530 --> 00:47:29,340 that we all have to live under. 537 00:47:30,790 --> 00:47:35,780 That's true for surveillance policies, for policies in terms of data collection, 538 00:47:35,780 --> 00:47:40,540 but also increasingly important when it comes to military and foreign policy. 539 00:47:43,930 --> 00:47:50,220 Starting in 2016, the Defense Department formed the Defense Innovation Board. 540 00:47:50,220 --> 00:47:54,010 That's a special body created to bring top tech executives 541 00:47:54,010 --> 00:47:56,420 into closer contact with the military. 542 00:47:59,140 --> 00:48:01,750 Eric Schmidt, former chairman of Alphabet, 543 00:48:01,750 --> 00:48:03,380 the parent company of Google, 544 00:48:03,380 --> 00:48:07,240 became the chairman of the Defense Innovation Board, 545 00:48:07,240 --> 00:48:09,930 and one of their first priorities was to say, 546 00:48:09,930 --> 00:48:13,850 "We need more artificial intelligence integrated into the military." 547 00:48:15,930 --> 00:48:19,190 - I've worked with a group of volunteers over the 548 00:48:19,190 --> 00:48:22,150 last couple of years to take a look at innovation in the 549 00:48:22,150 --> 00:48:26,780 overall military, and my summary conclusion is that we have 550 00:48:26,780 --> 00:48:30,460 fantastic people who are trapped in a very bad system. 551 00:48:33,290 --> 00:48:35,700 - From the Department of Defense's perspective, 552 00:48:35,700 --> 00:48:37,700 where I really started to get interested in it 553 00:48:37,700 --> 00:48:40,980 was when we started thinking about Unmanned Systems and 554 00:48:40,980 --> 00:48:45,980 how robotic and unmanned systems would start to change war. 555 00:48:46,160 --> 00:48:50,320 The smarter you made the Unmanned Systems and robots, 556 00:48:50,320 --> 00:48:53,570 the more powerful you might be able to make your military. 557 00:48:55,540 --> 00:48:57,240 - Under Secretary of Defense, 558 00:48:57,240 --> 00:49:00,420 Robert Work put together a major memo known as 559 00:49:00,420 --> 00:49:03,680 the Algorithmic Warfare Cross-Functional Team, 560 00:49:03,680 --> 00:49:05,540 better known as Project Maven. 561 00:49:07,830 --> 00:49:10,760 Eric Schmidt gave a number of speeches and media appearances 562 00:49:10,760 --> 00:49:14,310 where he said this effort was designed to increase fuel 563 00:49:14,310 --> 00:49:18,240 efficiency in the Air Force, to help with the logistics, 564 00:49:18,240 --> 00:49:21,300 but behind closed doors there was another parallel effort. 565 00:49:26,710 --> 00:49:29,760 Late in 2017 as part of Project Maven, 566 00:49:29,760 --> 00:49:33,710 Google, Eric Schmidt's firm, was tasked to secretly work 567 00:49:33,710 --> 00:49:36,100 on another part of Project Maven, 568 00:49:36,100 --> 00:49:41,480 and that was to take the vast volumes of image data vacuumed up 569 00:49:41,480 --> 00:49:47,060 by drones operating in Iraq and Afghanistan and to teach an AI 570 00:49:47,060 --> 00:49:49,690 to quickly identify targets on the battlefield. 571 00:49:52,600 --> 00:49:58,470 - We have a sensor and the sensor can do full motion video of an entire city. 572 00:49:58,470 --> 00:50:01,690 And we would have three seven-person teams working 573 00:50:01,690 --> 00:50:06,360 constantly and they could process 15% of the information. 574 00:50:06,360 --> 00:50:08,950 The other 85% of the information was just left 575 00:50:08,950 --> 00:50:14,040 on the cutting room floor, so we said, "Hey, AI and machine learning 576 00:50:14,040 --> 00:50:17,810 "would help us process 100% of the information." 577 00:50:25,380 --> 00:50:28,760 - Google has long had the motto, "Don't be evil." 578 00:50:28,760 --> 00:50:30,630 They have created a public image 579 00:50:30,630 --> 00:50:35,080 that they are devoted to public transparency. 580 00:50:35,080 --> 00:50:39,200 But for Google to slowly transform into a defense contractor, 581 00:50:39,200 --> 00:50:41,720 they maintained the utmost secrecy. 582 00:50:41,720 --> 00:50:45,280 And you had Google entering into this contract with most of the employees, 583 00:50:45,280 --> 00:50:49,020 even employees who were working on the program completely left in the dark. 584 00:51:01,840 --> 00:51:05,050 - Usually within Google, anyone in the company 585 00:51:05,050 --> 00:51:08,100 is allowed to know about any other project that's happening 586 00:51:08,100 --> 00:51:09,800 in some other part of the company. 587 00:51:11,180 --> 00:51:14,300 With Project Maven, the fact that it was kept secret, 588 00:51:14,300 --> 00:51:18,740 I think was alarming to people because that's not the norm at Google. 589 00:51:20,620 --> 00:51:22,940 - When this story was first revealed, 590 00:51:22,940 --> 00:51:25,540 it set off a firestorm within Google. 591 00:51:25,540 --> 00:51:28,420 You had a number of employees quitting in protests, 592 00:51:28,420 --> 00:51:31,900 others signing a petition objecting to this work. 593 00:51:34,130 --> 00:51:37,680 - You have to really say, "I don't want to be part of this anymore." 594 00:51:38,820 --> 00:51:41,750 There are companies called defense contractors 595 00:51:41,750 --> 00:51:45,830 and Google should just not be one of those companies 596 00:51:45,830 --> 00:51:50,040 because people need to trust Google for Google to work. 597 00:51:52,070 --> 00:51:55,710 - Good morning and welcome to Google I/O. 598 00:51:57,310 --> 00:52:00,160 - We've seen emails that show that Google simply 599 00:52:00,160 --> 00:52:03,350 continued to mislead their employees that the drone 600 00:52:03,350 --> 00:52:07,390 targeting program was only a minor effort that could at most 601 00:52:07,390 --> 00:52:11,170 be worth $9 million to the firm, which is drops in the bucket 602 00:52:11,170 --> 00:52:13,540 for a gigantic company like Google. 603 00:52:14,400 --> 00:52:17,300 But from internal emails that we obtained, 604 00:52:17,300 --> 00:52:21,530 Google was expecting Project Maven would ramp up to as much 605 00:52:21,530 --> 00:52:26,530 as $250 million, and that this entire effort would provide 606 00:52:26,630 --> 00:52:29,900 Google with Special Defense Department certification to make 607 00:52:29,900 --> 00:52:32,660 them available for even bigger defense contracts, 608 00:52:32,660 --> 00:52:34,980 some worth as much as $10 billion. 609 00:52:45,710 --> 00:52:49,750 The pressure for Google to compete for military contracts 610 00:52:49,750 --> 00:52:53,780 has come at a time when its competitors are also shifting their culture. 611 00:52:55,850 --> 00:53:00,070 Amazon, similarly pitching the military and law enforcement. 612 00:53:00,070 --> 00:53:02,280 IBM and other leading firms, 613 00:53:02,280 --> 00:53:04,890 they're pitching law enforcement and military. 614 00:53:05,840 --> 00:53:09,420 To stay competitive, Google has slowly transformed. 615 00:53:15,150 --> 00:53:18,910 - The Defense Science Board said of all of the 616 00:53:18,910 --> 00:53:22,170 technological advances that are happening right now, 617 00:53:22,170 --> 00:53:26,780 the single most important thing was artificial intelligence 618 00:53:26,780 --> 00:53:30,780 and the autonomous operations that it would lead. 619 00:53:30,780 --> 00:53:32,330 Are we investing enough? 620 00:53:37,810 --> 00:53:41,220 - Once we develop what are known as 621 00:53:41,220 --> 00:53:45,820 autonomous lethal weapons, in other words, 622 00:53:45,820 --> 00:53:51,510 weapons that are not controlled at all, they are genuinely autonomous, 623 00:53:51,510 --> 00:53:54,000 you've only got to get a president who says, 624 00:53:54,000 --> 00:53:56,410 "The hell with international law, we've got these weapons. 625 00:53:56,410 --> 00:53:58,560 "We're going to do what we want with them." 626 00:54:02,540 --> 00:54:03,960 - We're very close. 627 00:54:03,960 --> 00:54:06,340 When you have the hardware already set up 628 00:54:06,340 --> 00:54:10,360 and all you have to do is flip a switch to make it fully autonomous, 629 00:54:10,360 --> 00:54:13,240 what is it there that's stopping you from doing that? 630 00:54:14,670 --> 00:54:19,080 There's something really to be feared in war at machine speed. 631 00:54:19,930 --> 00:54:24,370 What if you're a machine and you've run millions and millions of different war scenarios 632 00:54:24,370 --> 00:54:28,060 and you have a team of drones and you've delegated control to half of them, 633 00:54:28,060 --> 00:54:30,790 and you're collaborating in real time? 634 00:54:30,790 --> 00:54:35,600 What happens when that swarm of drones is tasked with engaging a city? 635 00:54:37,490 --> 00:54:39,870 How will they take over that city? 636 00:54:39,870 --> 00:54:42,760 The answer is we won't know until it happens. 637 00:54:50,020 --> 00:54:53,910 - We do not want an AI system to decide 638 00:54:53,910 --> 00:54:56,180 what human it would attack, 639 00:54:56,180 --> 00:54:59,500 but we're going up against authoritarian competitors. 640 00:54:59,500 --> 00:55:02,450 So in my view, an authoritarian regime 641 00:55:02,450 --> 00:55:05,710 will have less problem delegating authority 642 00:55:05,710 --> 00:55:08,460 to a machine to make lethal decisions. 643 00:55:09,410 --> 00:55:12,660 So how that plays out remains to be seen. 644 00:55:37,270 --> 00:55:41,020 - Almost the gift of AI now is that it will force us 645 00:55:41,020 --> 00:55:44,410 collectively to think through at a very basic level, 646 00:55:44,410 --> 00:55:46,310 what does it mean to be human? 647 00:55:48,620 --> 00:55:50,510 What do I do as a human better 648 00:55:50,510 --> 00:55:52,970 than a certain super smart machine can do? 649 00:55:56,300 --> 00:56:01,000 First, we create our technology and then it recreates us. 650 00:56:01,000 --> 00:56:05,630 We need to make sure that we don't miss some of the things 651 00:56:05,630 --> 00:56:07,520 that make us so beautiful human. 652 00:56:11,840 --> 00:56:14,380 - Once we build intelligent machines, 653 00:56:14,380 --> 00:56:16,920 the philosophical vocabulary we have available to think 654 00:56:16,920 --> 00:56:20,680 about ourselves as human increasingly fails us. 655 00:56:23,160 --> 00:56:25,950 If I ask you to write up a list of all the terms you have 656 00:56:25,950 --> 00:56:28,960 available to describe yourself as human, 657 00:56:28,960 --> 00:56:31,100 there are not so many terms. 658 00:56:31,100 --> 00:56:38,140 Culture, history, sociality, maybe politics, civilization, 659 00:56:38,820 --> 00:56:45,090 subjectivity, all of these terms ground in two positions 660 00:56:45,670 --> 00:56:48,020 that humans are more than mere animals 661 00:56:49,000 --> 00:56:52,200 and that humans are more than mere machines. 662 00:56:55,140 --> 00:56:59,290 But if machines truly think there is a large set 663 00:56:59,290 --> 00:57:03,520 of key philosophical questions in which what is at stake is: 664 00:57:04,880 --> 00:57:09,080 Who are we? What is our place in the world? What is the world? How is it structured? 665 00:57:09,080 --> 00:57:12,190 Do the categories that we have relied on 666 00:57:12,190 --> 00:57:14,510 - Do they still work? Were they wrong? 667 00:57:19,500 --> 00:57:22,220 - Many people think of intelligence as something mysterious 668 00:57:22,220 --> 00:57:26,190 that can only exist inside of biological organisms, like us, 669 00:57:26,190 --> 00:57:29,260 but intelligence is all about information processing. 670 00:57:30,280 --> 00:57:32,230 It doesn't matter whether the intelligence is processed 671 00:57:32,230 --> 00:57:35,940 by carbon atoms inside of cells and brains, and people, 672 00:57:35,940 --> 00:57:38,020 or by silicon atoms in computers. 673 00:57:40,700 --> 00:57:43,320 Part of the success of AI recently has come 674 00:57:43,320 --> 00:57:47,540 from stealing great ideas from evolution. 675 00:57:47,540 --> 00:57:49,320 We noticed that the brain, for example, 676 00:57:49,320 --> 00:57:52,920 has all these neurons inside connected in complicated ways. 677 00:57:52,920 --> 00:57:55,660 So we stole that idea and abstracted it 678 00:57:55,660 --> 00:57:58,350 into artificial neural networks in computers, 679 00:57:59,330 --> 00:58:02,800 and that's what has revolutionized machine intelligence. 680 00:58:07,690 --> 00:58:10,300 If we one day get Artificial General Intelligence, 681 00:58:10,300 --> 00:58:14,330 then by definition, AI can also do better the job of AI 682 00:58:14,330 --> 00:58:18,930 programming and that means that further progress in making 683 00:58:18,930 --> 00:58:22,950 AI will be dominated not by human programmers, but by AI. 684 00:58:25,450 --> 00:58:29,090 Recursively self-improving AI could leave human intelligence 685 00:58:29,090 --> 00:58:32,990 far behind, creating super intelligence. 686 00:58:34,970 --> 00:58:37,970 It's gonna be the last invention we ever need to make, 687 00:58:37,970 --> 00:58:40,520 because it can then invent everything else 688 00:58:40,520 --> 00:58:42,010 much faster than we could. 689 00:59:54,040 --> 00:59:59,040 - There is a future that we all need to talk about. 690 00:59:59,110 --> 01:00:02,430 Some of the fundamental questions about the future 691 01:00:02,430 --> 01:00:06,280 of artificial intelligence, not just where it's going, 692 01:00:06,280 --> 01:00:09,630 but what it means for society to go there. 693 01:00:10,930 --> 01:00:14,620 It is not what computers can do, 694 01:00:14,620 --> 01:00:17,590 but what computers should do. 695 01:00:17,590 --> 01:00:22,210 As the generation of people that is bringing AI to the future, 696 01:00:22,210 --> 01:00:27,690 we are the generation that will answer this question first and foremost. 697 01:00:34,570 --> 01:00:37,380 - We haven't created the human-level thinking machine yet, 698 01:00:37,380 --> 01:00:39,410 but we get closer and closer. 699 01:00:41,100 --> 01:00:44,780 Maybe we'll get to human-level AI in five years from now 700 01:00:44,780 --> 01:00:47,410 or maybe it'll take 50 or 100 years from now. 701 01:00:47,660 --> 01:00:51,540 It almost doesn't matter. Like these are all really, really soon, 702 01:00:51,540 --> 01:00:56,060 in terms of the overall history of humanity. 703 01:01:01,200 --> 01:01:02,180 Very nice. 704 01:01:15,750 --> 01:01:19,350 So, the AI field is extremely international. 705 01:01:19,350 --> 01:01:23,790 China is up and coming and it's starting to rival the US, 706 01:01:23,790 --> 01:01:26,940 Europe and Japan in terms of putting a lot 707 01:01:26,940 --> 01:01:29,770 of processing power behind AI 708 01:01:29,770 --> 01:01:33,120 and gathering a lot of data to help AI learn. 709 01:01:35,960 --> 01:01:40,540 We have a young generation of Chinese researchers now. 710 01:01:40,540 --> 01:01:43,910 Nobody knows where the next revolution is going to come from. 711 01:01:50,120 --> 01:01:54,290 - China always wanted to become the superpower in the world. 712 01:01:56,120 --> 01:01:59,410 The Chinese government thinks AI gave them the chance to become 713 01:01:59,410 --> 01:02:03,940 one of the most advanced technology wise, business wise. 714 01:02:04,190 --> 01:02:07,780 So the Chinese government look at this as a huge opportunity. 715 01:02:09,140 --> 01:02:13,670 Like they've raised a flag and said, "That's a good field. 716 01:02:13,670 --> 01:02:16,300 "The companies should jump into it." 717 01:02:16,300 --> 01:02:18,300 Then China's commercial world and companies say, 718 01:02:18,300 --> 01:02:20,800 "Okay, the government raised a flag, that's good. 719 01:02:20,800 --> 01:02:22,500 "Let's put the money into it." 720 01:02:23,900 --> 01:02:28,090 Chinese tech giants, like Baidu, like Tencent and like AliBaba, 721 01:02:28,090 --> 01:02:31,800 they put a lot of the investment into the AI field. 722 01:02:33,410 --> 01:02:36,740 So we see that China's AI development is booming. 723 01:02:43,430 --> 01:02:47,370 - In China, everybody has Alipay and WeChat pay, 724 01:02:47,370 --> 01:02:49,500 so mobile payment is everywhere. 725 01:02:50,850 --> 01:02:54,850 And with that, they can do a lot of AI analysis 726 01:02:54,850 --> 01:02:59,340 to know like your spending habits, your credit rating. 727 01:03:01,150 --> 01:03:06,100 Face recognition technology is widely adopted in China, 728 01:03:06,100 --> 01:03:08,200 in airports and train stations. 729 01:03:09,040 --> 01:03:11,570 So, in the future, maybe in just a few months, 730 01:03:11,570 --> 01:03:15,140 you don't need a paper ticket to board a train. 731 01:03:15,140 --> 01:03:15,970 Only your face. 732 01:03:24,620 --> 01:03:29,690 - We generate the world's biggest platform of facial recognition. 733 01:03:31,260 --> 01:03:37,300 We have 300,000 developers using our platform. 734 01:03:38,330 --> 01:03:41,550 A lot of it is selfie camera apps. 735 01:03:41,550 --> 01:03:43,930 It makes you look more beautiful. 736 01:03:46,550 --> 01:03:49,780 There are millions and millions of cameras in the world, 737 01:03:50,760 --> 01:03:54,880 each camera from my point is a data generator. 738 01:03:58,820 --> 01:04:02,810 In a machine's eye, your face will change into the features 739 01:04:02,810 --> 01:04:06,660 and it will turn your face into a paragraph of code. 740 01:04:07,720 --> 01:04:11,980 So we can detect how old you are, if you're male or female, 741 01:04:11,980 --> 01:04:13,440 and your emotions. 742 01:04:16,640 --> 01:04:20,110 Shopping is about what kind of thing you are looking at. 743 01:04:20,110 --> 01:04:25,650 We can track your eyeballs, so if you are focusing on some product, 744 01:04:25,650 --> 01:04:28,690 we can track that so that we can know 745 01:04:28,690 --> 01:04:32,120 which kind of people like which kind of product. 746 01:04:42,450 --> 01:04:45,820 Our mission is to create a platform 747 01:04:45,950 --> 01:04:50,300 that will enable millions of AI developers in China. 748 01:04:51,280 --> 01:04:58,060 We study all the data we can get. 749 01:05:00,440 --> 01:05:04,350 Not just user profiles, 750 01:05:04,350 --> 01:05:08,380 but what you are doing at the moment, 751 01:05:09,460 --> 01:05:12,060 your geographical location. 752 01:05:15,380 --> 01:05:23,580 This platform will be so valuable that we don't even worry about profit now, 753 01:05:23,580 --> 01:05:27,660 because it is definitely there. 754 01:05:29,660 --> 01:05:34,420 China's social credit system is just one of the applications. 755 01:05:45,990 --> 01:05:48,040 - The Chinese government is using multiple 756 01:05:48,040 --> 01:05:50,810 different kinds of technologies, whether it's AI, 757 01:05:50,810 --> 01:05:53,650 whether it's big data platforms, facial recognition, 758 01:05:53,650 --> 01:05:57,030 voice recognition, essentially to monitor 759 01:05:57,030 --> 01:05:58,800 what the population is doing. 760 01:06:01,860 --> 01:06:04,240 I think the Chinese government has made very clear 761 01:06:04,240 --> 01:06:09,240 its intent to gather massive amounts of data about people 762 01:06:09,600 --> 01:06:13,300 to socially engineer a dissent-free society. 763 01:06:16,040 --> 01:06:19,060 The logic behind the Chinese government's 764 01:06:19,060 --> 01:06:23,180 social credit system, it's to take the idea that 765 01:06:23,180 --> 01:06:27,930 whether you are credit worthy for a financial loan 766 01:06:27,930 --> 01:06:31,860 and adding to it a very political dimension to say, 767 01:06:31,860 --> 01:06:34,270 "Are you a trustworthy human being? 768 01:06:36,530 --> 01:06:40,270 "What you've said online, have you ever been critical of the authorities? 769 01:06:40,270 --> 01:06:42,190 "Do you have a criminal record?" 770 01:06:43,720 --> 01:06:47,340 And all that information is packaged up together to rate 771 01:06:47,340 --> 01:06:51,820 you in ways that if you have performed well in their view, 772 01:06:51,820 --> 01:06:56,490 you'll have easier access to certain kinds of state services or benefits. 773 01:06:57,790 --> 01:06:59,710 But if you haven't done very well, 774 01:06:59,710 --> 01:07:02,130 you are going to be penalized or restricted. 775 01:07:05,940 --> 01:07:09,020 There's no way for people to challenge those designations 776 01:07:09,020 --> 01:07:12,100 or, in some cases, even know that they've been put in that category, 777 01:07:12,100 --> 01:07:17,990 and it's not until they try to access some kind of state service or buy a plane ticket, 778 01:07:17,990 --> 01:07:20,460 or get a passport, or enroll their kid in school, 779 01:07:20,460 --> 01:07:23,590 that they come to learn that they've been labeled in this way, 780 01:07:23,590 --> 01:07:27,550 and that there are negative consequences for them as a result. 781 01:07:44,970 --> 01:07:48,660 We've spent the better part of the last one or two years 782 01:07:48,660 --> 01:07:53,180 looking at abuses of surveillance technology across China, 783 01:07:53,180 --> 01:07:56,030 and a lot of that work has taken us to Xinjiang, 784 01:07:57,580 --> 01:08:01,220 the Northwestern region of China that has a more than half 785 01:08:01,220 --> 01:08:05,870 population of Turkic Muslims, Uyghurs, Kazakhs and Hui. 786 01:08:08,430 --> 01:08:10,980 This is a region and a population the Chinese government 787 01:08:10,980 --> 01:08:14,900 has long considered to be politically suspect or disloyal. 788 01:08:17,580 --> 01:08:20,160 We came to find information about what's called 789 01:08:20,160 --> 01:08:23,130 the Integrated Joint Operations Platform, 790 01:08:23,130 --> 01:08:27,190 which is a predictive policing program and that's one 791 01:08:27,190 --> 01:08:30,650 of the programs that has been spitting out lists of names 792 01:08:30,650 --> 01:08:33,560 of people to be subjected to political re-education. 793 01:08:39,090 --> 01:08:42,770 A number of our interviewees for the report we just released 794 01:08:42,770 --> 01:08:46,110 about the political education camps in Xinjiang just 795 01:08:46,110 --> 01:08:50,380 painted an extraordinary portrait of a surveillance state. 796 01:08:53,460 --> 01:08:56,380 A region awash in surveillance cameras 797 01:08:56,380 --> 01:09:00,600 for facial recognition purposes, checkpoints, body scanners, 798 01:09:00,600 --> 01:09:04,030 QR codes outside people's homes. 799 01:09:05,660 --> 01:09:10,690 Yeah, it really is the stuff of dystopian movies that we've all gone to and thought, 800 01:09:10,690 --> 01:09:13,160 "Wow, that would be a creepy world to live in." 801 01:09:13,160 --> 01:09:16,510 Yeah, well, 13 million Turkic Muslims in China 802 01:09:16,510 --> 01:09:18,530 are living in that reality right now. 803 01:09:30,840 --> 01:09:33,060 - The Intercept reports that Google is planning to 804 01:09:33,060 --> 01:09:36,490 launch a censored version of its search engine in China. 805 01:09:36,490 --> 01:09:38,730 - Google's search for new markets leads it 806 01:09:38,730 --> 01:09:42,170 to China, despite Beijing's rules on censorship. 807 01:09:42,170 --> 01:09:44,080 - Tell us more about why you felt it was 808 01:09:44,080 --> 01:09:46,650 your ethical responsibility to resign, 809 01:09:46,650 --> 01:09:51,060 because you talk about being complicit in censorship and oppression, and surveillance. 810 01:09:51,060 --> 01:09:54,220 - There is a Chinese venture company that has to be 811 01:09:54,220 --> 01:09:56,230 set up for Google to operate in China. 812 01:09:56,230 --> 01:09:58,920 And the question is, to what degree did they get to control 813 01:09:58,920 --> 01:10:01,970 the blacklist and to what degree would they have just 814 01:10:01,970 --> 01:10:05,220 unfettered access to surveilling Chinese citizens? 815 01:10:05,220 --> 01:10:07,470 And the fact that Google refuses to respond 816 01:10:07,470 --> 01:10:09,250 to human rights organizations on this, 817 01:10:09,250 --> 01:10:12,060 I think should be extremely disturbing to everyone. 818 01:10:16,640 --> 01:10:21,120 Due to my conviction that dissent is fundamental to functioning democracies 819 01:10:21,120 --> 01:10:25,560 and forced to resign in order to avoid contributing to or profiting from the erosion 820 01:10:25,560 --> 01:10:27,510 of protections for dissidents. 821 01:10:28,560 --> 01:10:30,920 The UN is currently reporting that between 822 01:10:30,920 --> 01:10:34,190 200,000 and one million Uyghurs have been disappeared 823 01:10:34,190 --> 01:10:36,520 into re-education camps. 824 01:10:36,520 --> 01:10:39,290 And there is a serious argument that Google would be complicit 825 01:10:39,290 --> 01:10:42,460 should it launch a surveilled version of search in China. 826 01:10:45,180 --> 01:10:51,380 Dragonfly is a project meant to launch search in China under 827 01:10:51,390 --> 01:10:55,810 Chinese government regulations, which include censoring 828 01:10:55,810 --> 01:10:59,510 sensitive content, basic queries on human rights, 829 01:10:59,510 --> 01:11:03,210 information about political representatives is blocked, 830 01:11:03,210 --> 01:11:07,080 information about student protests is blocked. 831 01:11:07,080 --> 01:11:09,180 And that's one small part of it. 832 01:11:09,180 --> 01:11:12,250 Perhaps a deeper concern is the surveillance side of this. 833 01:11:16,070 --> 01:11:19,580 When I raised the issue with my managers, with my colleagues, 834 01:11:19,580 --> 01:11:23,370 there was a lot of concern, but everyone just said, "I don't know anything." 835 01:11:27,760 --> 01:11:30,200 And then when there was a meeting finally, 836 01:11:30,200 --> 01:11:35,080 there was essentially no addressing the serious concerns associated with it. 837 01:11:37,010 --> 01:11:39,790 So then I filed my formal resignation, 838 01:11:39,790 --> 01:11:42,950 not just to my manager, but I actually distributed it company-wide. 839 01:11:42,950 --> 01:11:45,440 And that's the letter that I was reading from. 840 01:11:50,360 --> 01:11:55,960 Personally, I haven't slept well. I've had pretty horrific headaches, 841 01:11:55,960 --> 01:11:58,520 wake up in the middle of the night just sweating. 842 01:12:00,640 --> 01:12:03,340 With that said, what I found since speaking out 843 01:12:03,340 --> 01:12:07,930 is just how positive the global response to this has been. 844 01:12:10,350 --> 01:12:13,910 Engineers should demand to know what the uses 845 01:12:13,910 --> 01:12:16,280 of their technical contributions are 846 01:12:16,280 --> 01:12:19,340 and to have a seat at the table in those ethical decisions. 847 01:12:27,020 --> 01:12:29,590 Most citizens don't really understand what it means to be 848 01:12:29,590 --> 01:12:32,250 in a very large scale prescriptive technology. 849 01:12:33,720 --> 01:12:36,260 Where someone has already pre-divided the work 850 01:12:36,260 --> 01:12:38,300 and all you know about is your little piece, 851 01:12:38,300 --> 01:12:41,150 and almost certainly you don't understand how it fits in. 852 01:12:44,630 --> 01:12:51,040 So, I think it's worth drawing the analogy to physicists' work on the atomic bomb. 853 01:12:53,840 --> 01:12:56,610 In fact, that's actually the community I came out of. 854 01:12:59,220 --> 01:13:03,460 I wasn't a nuclear scientist by any means, but I was an applied mathematician 855 01:13:04,400 --> 01:13:09,400 and my PhD program was actually funded to train people to work in weapons labs. 856 01:13:12,980 --> 01:13:17,100 One could certainly argue that there is an existential threat 857 01:13:17,820 --> 01:13:22,060 and whoever is leading in AI will lead militarily. 858 01:13:31,420 --> 01:13:34,250 - China fully expects to pass the United States 859 01:13:34,250 --> 01:13:37,480 as the number one economy in the world and it believes that 860 01:13:37,480 --> 01:13:42,450 AI will make that jump more quickly and more dramatically. 861 01:13:43,900 --> 01:13:46,480 And they also see it as being able to leapfrog 862 01:13:46,480 --> 01:13:49,820 the United States in terms of military power. 863 01:13:57,580 --> 01:13:59,600 Their plan is very simple. 864 01:13:59,600 --> 01:14:03,620 We want to catch the United States and these technologies by 2020, 865 01:14:03,620 --> 01:14:07,940 we want to surpass the United States in these technologies by 2025, 866 01:14:07,940 --> 01:14:12,600 and we want to be the world leader in AI and autonomous technologies by 2030. 867 01:14:15,110 --> 01:14:16,850 It is a national plan. 868 01:14:16,850 --> 01:14:21,790 It is backed up by at least $150 billion in investments. 869 01:14:21,790 --> 01:14:25,060 So, this is definitely a race. 870 01:14:50,070 --> 01:14:52,070 - AI is a little bit like fire. 871 01:14:53,360 --> 01:14:56,270 Fire was invented 700,000 years ago, 872 01:14:57,480 --> 01:14:59,820 and it has its pros and cons. 873 01:15:01,960 --> 01:15:06,810 People realized you can use fire to keep warm at night and to cook, 874 01:15:08,520 --> 01:15:14,420 but they also realized that you can kill other people with that. 875 01:15:19,860 --> 01:15:24,300 Fire also has this AI-like quality of growing 876 01:15:24,300 --> 01:15:27,400 in a wildfire without further human ado, 877 01:15:30,530 --> 01:15:35,970 but the advantages outweigh the disadvantages by so much 878 01:15:35,970 --> 01:15:39,760 that we are not going to stop its development. 879 01:15:49,540 --> 01:15:51,180 Europe is waking up. 880 01:15:52,160 --> 01:15:58,390 Lots of companies in Europe are realizing that the next wave of AI 881 01:15:58,730 --> 01:16:01,540 will be much bigger than the current wave. 882 01:16:03,310 --> 01:16:08,000 The next wave of AI will be about robots. 883 01:16:09,810 --> 01:16:15,450 All these machines that make things, that produce stuff, 884 01:16:15,450 --> 01:16:19,370 that build other machines, they are going to become smart. 885 01:16:26,660 --> 01:16:29,950 In the not-so-distant future, we will have robots 886 01:16:29,950 --> 01:16:33,290 that we can teach like we teach kids. 887 01:16:35,640 --> 01:16:38,660 For example, I will talk to a little robot and I will say, 888 01:16:39,970 --> 01:16:42,550 "Look here, robot, look here. 889 01:16:42,550 --> 01:16:44,620 "Let's assemble a smartphone. 890 01:16:44,620 --> 01:16:48,720 "We take this slab of plastic like that and we takes a screwdriver like that, 891 01:16:48,720 --> 01:16:52,310 "and now we screw in everything like this. 892 01:16:52,310 --> 01:16:54,310 "No, no, not like this. 893 01:16:54,310 --> 01:16:57,690 "Like this, look, robot, look, like this." 894 01:16:58,820 --> 01:17:01,890 And he will fail a couple of times but rather quickly, 895 01:17:01,890 --> 01:17:05,860 he will learn to do the same thing much better than I could do it. 896 01:17:06,710 --> 01:17:11,400 And then we stop the learning and we make a million copies, and sell it. 897 01:17:32,410 --> 01:17:35,800 Regulation of AI sounds like an attractive idea, 898 01:17:35,800 --> 01:17:38,210 but I don't think it's possible. 899 01:17:40,250 --> 01:17:42,720 One of the reasons why it won't work is 900 01:17:42,720 --> 01:17:46,360 the sheer curiosity of scientists. 901 01:17:47,260 --> 01:17:49,560 They don't give a damn for regulation. 902 01:17:52,640 --> 01:17:56,740 Military powers won't give a damn for regulations, either. 903 01:17:56,740 --> 01:17:59,020 They will say, "If we, the Americans don't do it, 904 01:17:59,020 --> 01:18:00,720 "then the Chinese will do it." 905 01:18:00,720 --> 01:18:03,150 And the Chinese will say, "If we don't do it, 906 01:18:03,150 --> 01:18:04,810 "then the Russians will do it." 907 01:18:07,700 --> 01:18:10,930 No matter what kind of political regulation is out there, 908 01:18:10,930 --> 01:18:14,660 all these military industrial complexes, 909 01:18:14,660 --> 01:18:17,570 they will almost by definition have to ignore that 910 01:18:18,670 --> 01:18:21,250 because they want to avoid falling behind. 911 01:18:26,030 --> 01:18:27,690 Welcome to Xinhua. 912 01:18:27,690 --> 01:18:30,260 I'm the world's first female AI news anchor developed 913 01:18:30,260 --> 01:18:32,690 jointly by Xinhua and search engine company Sogou. 914 01:18:33,050 --> 01:18:36,310 - A program developed by the company OpenAI can write 915 01:18:36,310 --> 01:18:39,500 coherent and credible stories just like human beings. 916 01:18:39,500 --> 01:18:41,520 - It's one small step for machine, 917 01:18:41,520 --> 01:18:44,330 one giant leap for machine kind. 918 01:18:44,330 --> 01:18:47,170 IBM's newest artificial intelligence system took on 919 01:18:47,170 --> 01:18:51,570 experienced human debaters and won a live debate. 920 01:18:51,570 --> 01:18:54,160 - Computer-generated videos known as deep fakes 921 01:18:54,160 --> 01:18:57,980 are being used to put women's faces on pornographic videos. 922 01:19:02,510 --> 01:19:06,450 - Artificial intelligence evolves at a very crazy pace. 923 01:19:07,970 --> 01:19:10,180 You know, it's like progressing so fast. 924 01:19:10,180 --> 01:19:12,940 In some ways, we're only at the beginning right now. 925 01:19:14,490 --> 01:19:17,620 You have so many potential applications, it's a gold mine. 926 01:19:19,590 --> 01:19:23,450 Since 2012, when deep learning became a big game changer 927 01:19:23,450 --> 01:19:25,370 in the computer vision community, 928 01:19:25,370 --> 01:19:28,730 we were one of the first to actually adopt deep learning 929 01:19:28,730 --> 01:19:31,080 and apply it in the field of computer graphics. 930 01:19:34,640 --> 01:19:39,800 A lot of our research is funded by government, military intelligence agencies. 931 01:19:43,950 --> 01:19:47,840 The way we create these photoreal mappings, 932 01:19:47,840 --> 01:19:50,300 usually the way it works is that we need two subjects, 933 01:19:50,300 --> 01:19:53,740 a source and a target, and I can do a face replacement. 934 01:19:58,880 --> 01:20:03,700 One of the applications is, for example, I want to manipulate someone's face 935 01:20:03,700 --> 01:20:05,450 saying things that he did not. 936 01:20:08,920 --> 01:20:12,140 It can be used for creative things, for funny contents, 937 01:20:12,140 --> 01:20:16,110 but obviously, it can also be used for just simply 938 01:20:16,110 --> 01:20:18,660 manipulate videos and generate fake news. 939 01:20:21,050 --> 01:20:23,340 This can be very dangerous. 940 01:20:24,790 --> 01:20:29,300 If it gets into the wrong hands, it can get out of control very quickly. 941 01:20:33,370 --> 01:20:35,750 - We're entering an era in which our enemies can 942 01:20:35,750 --> 01:20:39,590 make it look like anyone is saying anything at any point in time, 943 01:20:39,590 --> 01:20:41,830 even if they would never say those things. 944 01:20:42,450 --> 01:20:46,970 Moving forward, we need to be more vigilant with what we trust from the Internet. 945 01:20:46,970 --> 01:20:50,710 It may sound basic, but how we move forward 946 01:20:50,710 --> 01:20:55,180 in the age of information is going to be the difference 947 01:20:55,180 --> 01:20:58,160 between whether we survive or whether we become 948 01:20:58,160 --> 01:21:00,270 some kind of fucked up dystopia. 949 01:22:31,070 --> 01:22:37,337 - One criticism that is frequently raised against my work is saying that, 950 01:22:37,337 --> 01:22:43,610 "Hey, you know there were stupid ideas in the past like phrenology or physiognomy.- 951 01:22:45,110 --> 01:22:49,210 - "There were people claiming that you can read a character 952 01:22:49,210 --> 01:22:52,010 "of a person just based on their face." 953 01:22:53,820 --> 01:22:56,050 People would say, "This is rubbish. 954 01:22:56,050 --> 01:23:01,050 "We know it was just thinly veiled racism and superstition." 955 01:23:05,300 --> 01:23:09,650 But the fact that someone made a claim in the past 956 01:23:09,650 --> 01:23:14,650 and tried to support this claim with invalid reasoning, 957 01:23:14,960 --> 01:23:18,970 doesn't automatically invalidate the claim. 958 01:23:23,790 --> 01:23:25,710 Of course, people should have rights 959 01:23:25,710 --> 01:23:31,020 to their privacy when it comes to sexual orientation or political views, 960 01:23:32,310 --> 01:23:35,600 but I'm also afraid that in the current technological environment, 961 01:23:35,600 --> 01:23:38,220 this is essentially impossible. 962 01:23:42,640 --> 01:23:44,910 People should realize there's no going back. 963 01:23:44,910 --> 01:23:48,330 There's no running away from the algorithms. 964 01:23:51,120 --> 01:23:55,670 The sooner we accept the inevitable and inconvenient truth 965 01:23:56,540 --> 01:23:59,430 that privacy is gone, 966 01:24:01,770 --> 01:24:05,380 the sooner we can actually start thinking about 967 01:24:05,380 --> 01:24:07,440 how to make sure that our societies 968 01:24:07,440 --> 01:24:11,660 are ready for the Post-Privacy Age. 969 01:24:35,080 --> 01:24:37,610 - While speaking about facial recognition, 970 01:24:37,610 --> 01:24:43,700 in my deep thoughts, I sometimes get to the very dark era of our history. 971 01:24:45,490 --> 01:24:49,020 When the people had to live in the system, 972 01:24:49,020 --> 01:24:52,660 where some part of the society was accepted 973 01:24:53,680 --> 01:24:56,900 and some part of the society was accused to death. 974 01:25:01,670 --> 01:25:06,180 What would Mengele do to have such an instrument in his hands? 975 01:25:10,740 --> 01:25:14,390 It would be very quick and efficient for selection 976 01:25:18,390 --> 01:25:22,100 and this is the apocalyptic vision. 977 01:26:15,880 --> 01:26:19,870 - So in the near future, the entire story of you 978 01:26:19,870 --> 01:26:25,340 will exist in a vast array of connected databases of faces, 979 01:26:25,750 --> 01:26:28,390 genomes, behaviors and emotion. 980 01:26:30,950 --> 01:26:35,320 So, you will have a digital avatar of yourself online, 981 01:26:35,320 --> 01:26:39,510 which records how well you are doing as a citizen, 982 01:26:39,510 --> 01:26:41,910 what kind of a relationship do you have, 983 01:26:41,910 --> 01:26:45,890 what kind of political orientation and sexual orientation. 984 01:26:50,020 --> 01:26:54,120 Based on all of those data, those algorithms will be able to 985 01:26:54,120 --> 01:26:58,390 manipulate your behavior with an extreme precision, 986 01:26:58,390 --> 01:27:03,890 changing how we think and probably in the future, how we feel. 987 01:27:25,660 --> 01:27:30,510 - The beliefs and desires of the first AGIs will be extremely important. 988 01:27:32,730 --> 01:27:35,180 So, it's important to program them correctly. 989 01:27:36,200 --> 01:27:37,850 I think that if this is not done, 990 01:27:38,810 --> 01:27:44,190 then the nature of evolution of natural selection will favor 991 01:27:44,190 --> 01:27:48,340 those systems, prioritize their own survival above all else. 992 01:27:51,860 --> 01:27:56,660 It's not that it's going to actively hate humans and want to harm them, 993 01:27:58,780 --> 01:28:01,100 but it's just going to be too powerful 994 01:28:01,400 --> 01:28:05,470 and I think a good analogy would be the way humans treat animals. 995 01:28:06,970 --> 01:28:08,200 It's not that we hate animals. 996 01:28:08,260 --> 01:28:11,930 I think humans love animals and have a lot of affection for them, 997 01:28:12,340 --> 01:28:17,610 but when the time comes to build a highway between two cities, 998 01:28:17,610 --> 01:28:20,130 we are not asking the animals for permission. 999 01:28:20,130 --> 01:28:23,340 We just do it because it's important for us. 1000 01:28:24,250 --> 01:28:29,010 And I think by default, that's the kind of relationship that's going to be between us 1001 01:28:29,010 --> 01:28:34,700 and AGIs which are truly autonomous and operating on their own behalf. 1002 01:28:47,190 --> 01:28:51,400 If you have an arms-race dynamics between multiple kings 1003 01:28:51,400 --> 01:28:54,140 trying to build the AGI first, 1004 01:28:54,140 --> 01:28:58,000 they will have less time to make sure that the AGI that they build 1005 01:28:58,970 --> 01:29:00,520 will care deeply for humans. 1006 01:29:03,530 --> 01:29:06,540 Because the way I imagine it is that there is an avalanche, 1007 01:29:06,540 --> 01:29:09,220 there is an avalanche of AGI development. 1008 01:29:09,220 --> 01:29:12,300 Imagine it's a huge unstoppable force. 1009 01:29:15,780 --> 01:29:18,740 And I think it's pretty likely the entire surface of the 1010 01:29:18,740 --> 01:29:22,070 earth would be covered with solar panels and data centers. 1011 01:29:26,230 --> 01:29:28,700 Given these kinds of concerns, 1012 01:29:28,700 --> 01:29:32,830 it will be important that the AGI is somehow built 1013 01:29:32,830 --> 01:29:35,570 as a cooperation with multiple countries. 1014 01:29:38,060 --> 01:29:41,180 The future is going to be good for the AIs, regardless. 1015 01:29:42,130 --> 01:29:45,020 It would be nice if it would be good for humans as well. 1016 01:30:06,750 --> 01:30:10,580 - Is there a lot of responsibility weighing on my shoulders? 1017 01:30:10,580 --> 01:30:11,800 Not really. 1018 01:30:13,420 --> 01:30:16,740 Was there a lot of responsibility on the shoulders 1019 01:30:16,740 --> 01:30:19,100 of the parents of Einstein? 1020 01:30:20,190 --> 01:30:21,780 The parents somehow made him, 1021 01:30:21,780 --> 01:30:25,450 but they had no way of predicting what he would do, 1022 01:30:25,450 --> 01:30:27,300 and how he would change the world. 1023 01:30:28,580 --> 01:30:32,540 And so, you can't really hold them responsible for that. 1024 01:30:57,640 --> 01:31:00,240 So, I'm not a very human-centric person. 1025 01:31:01,840 --> 01:31:05,500 I think I'm a little stepping stone in the evolution 1026 01:31:05,500 --> 01:31:08,060 of the Universe towards higher complexity. 1027 01:31:10,820 --> 01:31:14,860 But it's also clear to me that I'm not the crown of creation 1028 01:31:14,860 --> 01:31:19,320 and that humankind as a whole is not the crown of creation, 1029 01:31:21,140 --> 01:31:26,290 but we are setting the stage for something that is bigger than us that transcends us. 1030 01:31:28,980 --> 01:31:32,780 And then will go out there in a way where humans cannot follow 1031 01:31:32,780 --> 01:31:37,940 and transform the entire Universe, or at least, the reachable Universe. 1032 01:31:41,520 --> 01:31:46,520 So, I find beauty and awe in seeing myself 1033 01:31:46,640 --> 01:31:50,260 as part of this much grander theme. 1034 01:32:14,070 --> 01:32:16,030 - AI is inevitable. 1035 01:32:17,560 --> 01:32:23,370 We need to make sure we have the necessary human regulation 1036 01:32:23,370 --> 01:32:27,940 to prevent the weaponization of artificial intelligence. 1037 01:32:28,690 --> 01:32:32,000 We don't need any more weaponization 1038 01:32:32,000 --> 01:32:33,960 of such a powerful tool. 1039 01:32:37,100 --> 01:32:41,960 - One of the most critical things, I think, is the need for international governance. 1040 01:32:43,920 --> 01:32:46,310 We have an imbalance of power here because now 1041 01:32:46,310 --> 01:32:49,140 we have corporations with more power, might and ability, 1042 01:32:49,140 --> 01:32:51,100 than entire countries. 1043 01:32:51,100 --> 01:32:54,050 How do we make sure that people's voices are getting heard? 1044 01:32:58,030 --> 01:32:59,930 - It can't be a law-free zone. 1045 01:32:59,930 --> 01:33:02,100 It can't be a rights-free zone. 1046 01:33:02,100 --> 01:33:05,870 We can't embrace all of these wonderful new technologies 1047 01:33:05,870 --> 01:33:10,380 for the 21st century without trying to bring with us 1048 01:33:10,380 --> 01:33:15,380 the package of human rights that we fought so hard 1049 01:33:15,640 --> 01:33:19,190 to achieve, and that remains so fragile. 1050 01:33:28,680 --> 01:33:32,180 - AI isn't good and it isn't evil, either. 1051 01:33:32,180 --> 01:33:36,890 It's just going to amplify the desires and goals of whoever controls it. 1052 01:33:36,890 --> 01:33:41,240 And AI today is under the control of a very, very small group of people. 1053 01:33:44,430 --> 01:33:49,260 The most important question that we humans have to ask ourselves at this point in history 1054 01:33:49,260 --> 01:33:51,380 requires no technical knowledge. 1055 01:33:51,590 --> 01:33:57,540 It's the question of what sort of future society do we want to create 1056 01:33:57,540 --> 01:33:59,740 with all this technology we're making? 1057 01:34:01,410 --> 01:34:05,110 What do we want the role of humans to be in this world? 93590

Can't find what you're looking for?
Get subtitles in any language from opensubtitles.com, and translate them here.