All language subtitles for IHuman.2019.720p.WEBRip.x264.AAC-[YTS.MX]

af Afrikaans
sq Albanian
am Amharic
ar Arabic
hy Armenian
az Azerbaijani
eu Basque
be Belarusian
bn Bengali
bs Bosnian
bg Bulgarian Download
ca Catalan
ceb Cebuano
ny Chichewa
zh-CN Chinese (Simplified)
zh-TW Chinese (Traditional)
co Corsican
hr Croatian
cs Czech
da Danish
nl Dutch Download
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 Download
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 00:00:02,000 --> 00:00:07,000 Downloaded from YTS.MX 2 00:00:08,000 --> 00:00:13,000 Official YIFY movies site: YTS.MX 3 00:00:25,020 --> 00:00:28,000 - Intelligence is the ability to understand. 4 00:00:28,000 --> 00:00:30,220 We passed on what we know to machines. 5 00:00:30,220 --> 00:00:31,760 - The rise of artificial intelligence 6 00:00:31,760 --> 00:00:34,210 is happening fast, but some fear the new technology 7 00:00:34,210 --> 00:00:36,960 might have more problems than anticipated. 8 00:00:36,960 --> 00:00:38,510 - We will not control it. 9 00:01:37,720 --> 00:01:40,290 - Artificially intelligent algorithms are here, 10 00:01:40,290 --> 00:01:41,930 but this is only the beginning. 11 00:01:51,380 --> 00:01:54,850 - In the age of AI, data is the new oil. 12 00:01:57,180 --> 00:01:59,230 - Today, Amazon, Google and Facebook 13 00:01:59,230 --> 00:02:01,440 are richer and more powerful than any companies 14 00:02:01,440 --> 00:02:03,840 that have ever existed throughout human history. 15 00:02:05,000 --> 00:02:08,690 - A handful of people working at a handful of technology companies 16 00:02:08,690 --> 00:02:11,360 steer what a billion people are thinking today. 17 00:02:12,710 --> 00:02:16,840 - This technology is changing: What does it mean to be human? 18 00:03:11,870 --> 00:03:16,340 - Artificial intelligence is simply non-biological intelligence. 19 00:03:17,310 --> 00:03:20,910 And intelligence itself is simply the ability to accomplish goals. 20 00:03:23,440 --> 00:03:26,030 I'm convinced that AI will ultimately be either 21 00:03:26,030 --> 00:03:29,780 the best thing ever to happen to humanity, or the worst thing ever to happen. 22 00:03:31,240 --> 00:03:34,930 We can use it to solve all of today's and tomorrow's 23 00:03:34,930 --> 00:03:40,620 greatest problems; cure diseases, deal with climate change, 24 00:03:40,780 --> 00:03:42,840 lift everybody out of poverty. 25 00:03:44,380 --> 00:03:47,460 But, we could use exactly the same technology 26 00:03:47,460 --> 00:03:51,780 to create a brutal global dictatorship with unprecedented 27 00:03:51,780 --> 00:03:54,600 surveillance and inequality and suffering. 28 00:03:56,230 --> 00:03:59,260 That's why this is the most important conversation of our time. 29 00:04:04,380 --> 00:04:07,590 - Artificial intelligence is everywhere 30 00:04:08,450 --> 00:04:11,500 because we now have thinking machines. 31 00:04:12,420 --> 00:04:15,840 If you go on social media or online, 32 00:04:15,840 --> 00:04:20,290 there's an artificial intelligence engine that decides what to recommend. 33 00:04:21,290 --> 00:04:25,400 If you go on Facebook and you're just scrolling through your friends' posts,- 34 00:04:25,400 --> 00:04:29,100 there's an AI engine that's picking which one to show you first 35 00:04:29,100 --> 00:04:30,840 - and which one to bury. 36 00:04:30,840 --> 00:04:34,190 If you try to get insurance, there is an AI engine 37 00:04:34,190 --> 00:04:36,270 trying to figure out how risky you are. 38 00:04:37,170 --> 00:04:40,710 And if you apply for a job, it's quite possible 39 00:04:40,710 --> 00:04:43,430 that an AI engine looks at the resume. 40 00:04:51,350 --> 00:04:53,500 - We are made of data. 41 00:04:54,240 --> 00:04:59,520 Every one of us is made of data -in terms of how we behave, 42 00:04:59,770 --> 00:05:03,000 how we talk, how we love, what we do every day. 43 00:05:05,410 --> 00:05:09,120 So, computer scientists are developing deep learning 44 00:05:09,120 --> 00:05:14,120 algorithms that can learn to identify, classify, 45 00:05:14,570 --> 00:05:18,680 and predict patterns within massive amounts of data. 46 00:05:31,390 --> 00:05:35,190 We are facing a form of precision surveillance, 47 00:05:35,190 --> 00:05:38,750 you could call it algorithmic surveillance, 48 00:05:38,750 --> 00:05:41,810 and it means that you cannot go unrecognized. 49 00:05:43,120 --> 00:05:46,110 You are always under the watch of algorithms. 50 00:05:51,070 --> 00:05:54,380 - Almost all the AI development on the planet today 51 00:05:54,380 --> 00:05:57,050 is done by a handful of big technology companies 52 00:05:57,050 --> 00:05:58,770 or by a few large governments. 53 00:06:01,930 --> 00:06:06,170 If we look at what AI is mostly being developed for, 54 00:06:06,170 --> 00:06:11,170 I would say it's killing, spying, and brainwashing. 55 00:06:11,570 --> 00:06:13,730 So, I mean, we have military AI, 56 00:06:13,730 --> 00:06:16,850 we have a whole surveillance apparatus being built 57 00:06:16,850 --> 00:06:19,060 using AI by major governments, 58 00:06:19,060 --> 00:06:21,730 and we have an advertising industry which is oriented 59 00:06:21,730 --> 00:06:25,870 toward recognizing what ads to try to sell to someone. 60 00:06:29,080 --> 00:06:32,090 - We humans have come to a fork in the road now. 61 00:06:33,530 --> 00:06:36,670 The AI we have today is very narrow. 62 00:06:37,820 --> 00:06:40,550 The holy grail of AI research ever since the beginning 63 00:06:40,550 --> 00:06:43,300 is to make AI that can do everything better than us, 64 00:06:44,660 --> 00:06:46,280 and we've basically built a God. 65 00:06:47,640 --> 00:06:49,930 It's going to revolutionize life as we know it. 66 00:06:53,040 --> 00:06:55,760 It's incredibly important to take a step back 67 00:06:55,760 --> 00:06:57,660 and think carefully about this. 68 00:06:59,380 --> 00:07:01,510 What sort of society do we want? 69 00:07:04,760 --> 00:07:07,430 - So, we're in this historic transformation. 70 00:07:08,890 --> 00:07:11,260 Like we're raising this new creature. 71 00:07:11,260 --> 00:07:14,230 We have a new offspring of sorts. 72 00:07:16,120 --> 00:07:19,630 But just like actual offspring, 73 00:07:19,630 --> 00:07:22,990 you don't get to control everything it's going to do. 74 00:07:57,000 --> 00:08:00,300 We are living at this privileged moment where, 75 00:08:00,300 --> 00:08:05,270 for the first time, we will see probably that AI 76 00:08:05,270 --> 00:08:08,860 is really going to outcompete humans in many, many, 77 00:08:08,860 --> 00:08:10,460 if not all, important fields. 78 00:08:14,300 --> 00:08:16,450 - Everything is going to change. 79 00:08:16,450 --> 00:08:19,520 A new form of life is emerging. 80 00:08:45,000 --> 00:08:50,900 When I was a boy, I thought, how can I maximize my impact? 81 00:08:52,050 --> 00:08:56,270 And then it was clear that I have to build something 82 00:08:56,270 --> 00:09:00,050 that learns to become smarter than myself, 83 00:09:00,050 --> 00:09:01,680 such that I can retire, 84 00:09:01,680 --> 00:09:04,480 and the smarter thing can further self-improve 85 00:09:04,480 --> 00:09:06,950 and solve all the problems that I cannot solve. 86 00:09:11,180 --> 00:09:14,520 Multiplying that tiny little bit of creativity 87 00:09:14,520 --> 00:09:16,370 that I have into infinity, 88 00:09:18,270 --> 00:09:20,780 and that's what has been driving me since then. 89 00:09:39,220 --> 00:09:40,680 How am I trying to build 90 00:09:40,680 --> 00:09:43,320 a general purpose artificial intelligence? 91 00:09:45,540 --> 00:09:49,690 If you want to be intelligent, you have to recognize speech, 92 00:09:49,690 --> 00:09:54,550 video and handwriting, and faces, and all kinds of things, 93 00:09:54,550 --> 00:09:57,550 and there we have made a lot of progress. 94 00:09:59,290 --> 00:10:02,010 See, LSTM, neural networks, 95 00:10:02,010 --> 00:10:05,890 which we developed in our labs in Munich and in Switzerland, 96 00:10:05,890 --> 00:10:10,460 and it's now used for speech recognition and translation, 97 00:10:10,460 --> 00:10:12,640 and video recognition. 98 00:10:12,640 --> 00:10:16,660 They are now in everybody's smartphone, almost one billion 99 00:10:16,660 --> 00:10:20,660 iPhones and in over two billion Android phones. 100 00:10:21,990 --> 00:10:26,990 So, we are generating all kinds of useful by-products 101 00:10:27,490 --> 00:10:29,040 on the way to the general goal. 102 00:10:40,000 --> 00:10:44,990 The main goal, some Artificial General Intelligence, 103 00:10:44,990 --> 00:10:51,400 an AGI that can learn to improve the learning algorithm itself. 104 00:10:52,960 --> 00:10:56,940 So, it basically can learn to improve the way it learns 105 00:10:56,940 --> 00:11:00,940 and it can also recursively improve the way it learns, 106 00:11:00,940 --> 00:11:04,460 the way it learns without any limitations except for 107 00:11:04,460 --> 00:11:07,970 the basic fundamental limitations of computability. 108 00:11:14,590 --> 00:11:17,880 One of my favorite robots is this one here. 109 00:11:17,880 --> 00:11:21,380 We use this robot for our studies of artificial curiosity. 110 00:11:22,640 --> 00:11:27,620 Where we are trying to teach this robot to teach itself. 111 00:11:32,870 --> 00:11:33,960 What is a baby doing? 112 00:11:33,960 --> 00:11:37,820 A baby is curiously exploring its world. 113 00:11:39,970 --> 00:11:42,210 That's how he learns how gravity works 114 00:11:42,210 --> 00:11:45,130 and how certain things topple, and so on. 115 00:11:46,700 --> 00:11:49,980 And as it learns to ask questions about the world, 116 00:11:49,980 --> 00:11:52,640 and as it learns to answer these questions, 117 00:11:52,640 --> 00:11:55,500 it becomes a more and more general problem solver. 118 00:11:56,540 --> 00:11:59,160 And so, our artificial systems are also learning 119 00:11:59,160 --> 00:12:03,320 to ask all kinds of questions, not just slavishly 120 00:12:03,320 --> 00:12:07,010 try to answer the questions given to them by humans. 121 00:12:10,880 --> 00:12:14,920 You have to give AI the freedom to invent its own tasks. 122 00:12:17,830 --> 00:12:20,610 If you don't do that, it's not going to become very smart. 123 00:12:22,160 --> 00:12:26,780 On the other hand, it's really hard to predict what they are going to do. 124 00:12:49,560 --> 00:12:52,910 - I feel that technology is a force of nature. 125 00:12:55,420 --> 00:13:00,020 I feel like there is a lot of similarity between technology and biological evolution. 126 00:13:08,850 --> 00:13:10,140 Playing God. 127 00:13:13,470 --> 00:13:16,500 Scientists have been accused of playing God for a while, 128 00:13:17,960 --> 00:13:22,410 - but there is a real sense in which we are creating something 129 00:13:23,380 --> 00:13:26,250 very different from anything we've created so far. 130 00:13:49,790 --> 00:13:53,250 I was interested in the concept of AI from a relatively early age. 131 00:13:55,080 --> 00:13:58,420 At some point, I got especially interested in machine learning. 132 00:14:01,690 --> 00:14:03,520 What is experience? 133 00:14:03,520 --> 00:14:04,710 What is learning? 134 00:14:04,710 --> 00:14:05,720 What is thinking? 135 00:14:06,890 --> 00:14:08,150 How does the brain work? 136 00:14:10,140 --> 00:14:11,940 These questions are philosophical, 137 00:14:11,940 --> 00:14:15,190 but it looks like we can come up with algorithms that 138 00:14:15,190 --> 00:14:18,530 both do useful things and help us answer these questions. 139 00:14:20,000 --> 00:14:22,250 Like it's almost like applied philosophy. 140 00:14:48,060 --> 00:14:51,410 Artificial General Intelligence, AGI. 141 00:14:52,610 --> 00:14:57,210 A computer system that can do any job or any task 142 00:14:57,210 --> 00:15:00,380 that a human does, but only better. 143 00:15:13,180 --> 00:15:15,810 Yeah, I mean, we definitely will be able to create 144 00:15:17,340 --> 00:15:20,150 completely autonomous beings with their own goals. 145 00:15:24,060 --> 00:15:25,630 And it will be very important, 146 00:15:25,630 --> 00:15:30,440 especially as these beings become much smarter than humans, 147 00:15:30,440 --> 00:15:34,720 it's going to be important to have these beings, 148 00:15:36,220 --> 00:15:39,330 that the goals of these beings be aligned with our goals. 149 00:15:42,600 --> 00:15:45,340 That's what we're trying to do at OpenAI. 150 00:15:45,340 --> 00:15:49,700 Be at the forefront of research and steer the research, 151 00:15:49,700 --> 00:15:53,940 steer their initial conditions so to maximize the chance 152 00:15:53,940 --> 00:15:56,100 that the future will be good for humans. 153 00:16:11,660 --> 00:16:14,370 Now, AI is a great thing because AI will solve 154 00:16:14,370 --> 00:16:16,440 all the problems that we have today. 155 00:16:19,080 --> 00:16:22,580 It will solve employment, it will solve disease, 156 00:16:24,670 --> 00:16:26,560 it will solve poverty, 157 00:16:29,000 --> 00:16:31,360 but it will also create new problems. 158 00:16:34,580 --> 00:16:36,320 I think that... 159 00:16:40,490 --> 00:16:43,120 The problem of fake news is going to be a thousand, 160 00:16:43,120 --> 00:16:44,360 a million times worse. 161 00:16:46,440 --> 00:16:48,820 Cyberattacks will become much more extreme. 162 00:16:50,640 --> 00:16:53,470 You will have totally automated AI weapons. 163 00:16:56,100 --> 00:16:59,980 I think AI has the potential to create infinitely stable dictatorships. 164 00:17:05,820 --> 00:17:08,850 You're gonna see dramatically more intelligent systems 165 00:17:08,850 --> 00:17:12,620 in 10 or 15 years from now, and I think it's highly likely 166 00:17:12,620 --> 00:17:17,120 that those systems will have completely astronomical impact on society. 167 00:17:19,480 --> 00:17:21,160 Will humans actually benefit? 168 00:17:22,860 --> 00:17:24,860 And who will benefit, who will not? 169 00:17:44,560 --> 00:17:47,660 - In 2012, IBM estimated that 170 00:17:47,660 --> 00:17:52,090 an average person is generating 500 megabytes 171 00:17:52,090 --> 00:17:55,110 of digital footprints every single day. 172 00:17:55,110 --> 00:17:57,390 Imagine that you wanted to back-up one day worth 173 00:17:57,390 --> 00:18:01,260 of data that humanity is leaving behind, on paper. 174 00:18:01,260 --> 00:18:04,370 How tall will be the stack of paper that contains 175 00:18:04,370 --> 00:18:07,820 just one day worth of data that humanity is producing? 176 00:18:09,610 --> 00:18:12,670 It's like from the earth to the sun, four times over. 177 00:18:14,550 --> 00:18:20,340 In 2025, we'll be generating 62 gigabytes of data 178 00:18:20,640 --> 00:18:22,380 per person, per day. 179 00:18:36,970 --> 00:18:42,380 We're leaving a ton of digital footprints while going through our lives. 180 00:18:44,790 --> 00:18:49,380 They provide computer algorithms with a fairly good idea about who we are, 181 00:18:49,380 --> 00:18:52,280 what we want, what we are doing. 182 00:18:56,020 --> 00:18:59,320 In my work, I looked at different types of digital footprints. 183 00:18:59,320 --> 00:19:02,650 I looked at Facebook likes, I looked at language, 184 00:19:02,650 --> 00:19:06,890 credit card records, web browsing histories, search records. 185 00:19:07,740 --> 00:19:12,010 and each time I found that if you get enough of this data, 186 00:19:12,010 --> 00:19:14,370 you can accurately predict future behavior 187 00:19:14,370 --> 00:19:17,560 and reveal important intimate traits. 188 00:19:19,140 --> 00:19:21,270 This can be used in great ways, 189 00:19:21,270 --> 00:19:24,670 but it can also be used to manipulate people. 190 00:19:29,910 --> 00:19:33,880 Facebook is delivering daily information 191 00:19:33,880 --> 00:19:36,460 to two billion people or more. 192 00:19:38,750 --> 00:19:42,840 If you slightly change the functioning of the Facebook engine, 193 00:19:42,840 --> 00:19:46,500 you can move the opinions and hence, 194 00:19:46,500 --> 00:19:49,870 the votes of millions of people. 195 00:19:50,720 --> 00:19:52,680 - Brexit! - When do we want it? 196 00:19:52,720 --> 00:19:54,140 - Now! 197 00:19:56,070 --> 00:19:58,690 - A politician wouldn't be able to figure out 198 00:19:58,690 --> 00:20:02,830 which message each one of his or her voters would like, 199 00:20:02,830 --> 00:20:06,010 but a computer can see what political message 200 00:20:06,010 --> 00:20:08,920 would be particularly convincing for you. 201 00:20:11,320 --> 00:20:12,640 - Ladies and gentlemen, 202 00:20:12,640 --> 00:20:16,170 it's my privilege to speak to you today about the power 203 00:20:16,170 --> 00:20:20,430 of big data and psychographics in the electoral process. 204 00:20:20,430 --> 00:20:22,360 - Data from Cambridge Analytica 205 00:20:22,360 --> 00:20:25,070 secretly harvested the personal information 206 00:20:25,070 --> 00:20:28,320 of 50 million unsuspecting Facebook users. 207 00:20:28,320 --> 00:20:31,690 USA! 208 00:20:31,690 --> 00:20:35,500 - The data firm hired by Donald Trump's presidential election campaign 209 00:20:35,870 --> 00:20:41,080 used secretly obtained information to directly target potential American voters. 210 00:20:41,080 --> 00:20:42,940 - With that, they say they can predict 211 00:20:42,940 --> 00:20:46,760 the personality of every single adult in the United States. 212 00:20:47,470 --> 00:20:49,460 - Tonight we're hearing from Cambridge Analytica 213 00:20:49,460 --> 00:20:51,650 whistleblower, Christopher Wiley. 214 00:20:51,650 --> 00:20:54,990 - What we worked on was data harvesting programs 215 00:20:54,990 --> 00:20:59,200 where we would pull data and run that data through algorithms that could profile 216 00:20:59,200 --> 00:21:01,930 their personality traits and other psychological attributes 217 00:21:01,930 --> 00:21:06,580 to exploit mental vulnerabilities that our algorithms showed that they had. 218 00:21:15,500 --> 00:21:17,570 - Cambridge Analytica mentioned once 219 00:21:17,570 --> 00:21:20,460 or said that their models were based on my work, 220 00:21:22,510 --> 00:21:25,140 but Cambridge Analytica is just one of the hundreds 221 00:21:25,140 --> 00:21:30,040 of companies that are using such methods to target voters. 222 00:21:32,130 --> 00:21:35,760 You know, I would be asked questions by journalists such as, 223 00:21:35,760 --> 00:21:37,220 "So how do you feel about 224 00:21:38,810 --> 00:21:41,990 "electing Trump and supporting Brexit?" 225 00:21:41,990 --> 00:21:43,940 How do you answer to such question? 226 00:21:45,400 --> 00:21:51,740 I guess that I have to deal with being blamed for all of it. 227 00:22:07,700 --> 00:22:12,480 - How tech started was as a democratizing force, 228 00:22:12,480 --> 00:22:15,110 as a force for good, as an ability for humans 229 00:22:15,110 --> 00:22:17,900 to interact with each other without gatekeepers. 230 00:22:20,210 --> 00:22:25,110 There's never been a bigger experiment in communications for the human race. 231 00:22:26,330 --> 00:22:29,060 What happens when everybody gets to have their say? 232 00:22:29,780 --> 00:22:31,850 You would assume that it would be for the better, 233 00:22:31,850 --> 00:22:34,540 that there would be more democracy, there would be more discussion, 234 00:22:34,540 --> 00:22:37,660 there would be more tolerance, but what's happened is that 235 00:22:37,660 --> 00:22:39,720 these systems have been hijacked. 236 00:22:41,300 --> 00:22:43,860 - We stand for connecting every person. 237 00:22:44,960 --> 00:22:46,620 For a global community. 238 00:22:47,780 --> 00:22:50,500 - One company, Facebook, is responsible 239 00:22:50,500 --> 00:22:53,540 for the communications of a lot of the human race. 240 00:22:55,650 --> 00:22:57,360 Same thing with Google. 241 00:22:57,360 --> 00:23:00,540 Everything you want know about the world comes from them. 242 00:23:01,540 --> 00:23:05,120 This is global information economy 243 00:23:05,120 --> 00:23:07,830 that is controlled by a small group of people. 244 00:23:14,400 --> 00:23:17,920 - The world's richest companies are all technology companies. 245 00:23:18,770 --> 00:23:24,500 Google, Apple, Microsoft, Amazon, Facebook. 246 00:23:25,880 --> 00:23:29,040 It's staggering how, 247 00:23:29,040 --> 00:23:31,770 in probably just 10 years, 248 00:23:31,770 --> 00:23:34,810 that the entire corporate power structure 249 00:23:34,810 --> 00:23:39,460 are basically in the business of trading electrons. 250 00:23:41,240 --> 00:23:47,060 These little bits and bytes are really the new currency. 251 00:23:53,560 --> 00:23:55,800 - The way that data is monetized 252 00:23:55,800 --> 00:23:58,820 is happening all around us, even if it's invisible to us. 253 00:24:00,960 --> 00:24:04,280 Google has every amount of information available. 254 00:24:04,280 --> 00:24:07,110 They track people by their GPS location. 255 00:24:07,110 --> 00:24:10,080 They know exactly what your search history has been. 256 00:24:10,080 --> 00:24:12,850 They know your political preferences. 257 00:24:12,850 --> 00:24:14,840 Your search history alone can tell you 258 00:24:14,840 --> 00:24:17,570 everything about an individual from their health problems 259 00:24:17,570 --> 00:24:19,480 to their sexual preferences. 260 00:24:19,480 --> 00:24:21,880 So, Google's reach is unlimited. 261 00:24:28,750 --> 00:24:31,620 - So we've seen Google and Facebook 262 00:24:31,620 --> 00:24:34,150 rise into these large surveillance machines 263 00:24:35,040 --> 00:24:38,200 and they're both actually ad brokers. 264 00:24:38,200 --> 00:24:42,040 It sounds really mundane, but they're high tech ad brokers. 265 00:24:42,910 --> 00:24:46,080 And the reason they're so profitable is that they're using 266 00:24:46,080 --> 00:24:49,750 artificial intelligence to process all this data about you, 267 00:24:51,560 --> 00:24:54,660 and then to match you with the advertiser 268 00:24:54,660 --> 00:24:59,660 that wants to reach people like you, - for whatever message. 269 00:25:03,000 --> 00:25:07,880 - One of the problems with technology is that it's been developed to be addictive. 270 00:25:07,880 --> 00:25:09,910 The way these companies design these things 271 00:25:09,910 --> 00:25:12,010 is in order to pull you in and engage you. 272 00:25:13,180 --> 00:25:16,820 They want to become essentially a slot machine of attention. 273 00:25:18,600 --> 00:25:21,770 So you're always paying attention, you're always jacked into the matrix, 274 00:25:21,770 --> 00:25:23,520 you're always checking. 275 00:25:26,580 --> 00:25:30,450 - When somebody controls what you read, they also control what you think. 276 00:25:32,180 --> 00:25:34,610 You get more of what you've seen before and liked before, 277 00:25:34,610 --> 00:25:37,890 because this gives more traffic and that gives more ads, 278 00:25:39,410 --> 00:25:43,160 but it also locks you into your echo chamber. 279 00:25:43,160 --> 00:25:46,350 And this is what leads to this polarization that we see today. 280 00:25:46,460 --> 00:25:49,300 Jair Bolsonaro! 281 00:25:49,970 --> 00:25:52,590 - Jair Bolsonaro, Brazil's right-wing 282 00:25:52,590 --> 00:25:56,000 populist candidate sometimes likened to Donald Trump, 283 00:25:56,000 --> 00:25:58,640 winning the presidency Sunday night in that country's 284 00:25:58,640 --> 00:26:01,840 most polarizing election in decades. 285 00:26:01,840 --> 00:26:02,840 - Bolsonaro! 286 00:26:04,160 --> 00:26:09,550 - What we are seeing around the world is upheaval and polarization and conflict 287 00:26:10,770 --> 00:26:15,000 that is partially pushed by algorithms 288 00:26:15,000 --> 00:26:19,070 that's figured out that political extremes, 289 00:26:19,070 --> 00:26:22,180 tribalism, and sort of shouting for your team, 290 00:26:22,180 --> 00:26:25,290 and feeling good about it, is engaging. 291 00:26:30,420 --> 00:26:33,150 - Social media may be adding to the attention 292 00:26:33,150 --> 00:26:35,490 to hate crimes around the globe. 293 00:26:35,490 --> 00:26:38,120 - It's about how people can become radicalized 294 00:26:38,120 --> 00:26:41,740 by living in the fever swamps of the Internet. 295 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 296 00:26:45,960 --> 00:26:48,840 as publishers for what they share with the world? 297 00:26:49,790 --> 00:26:52,750 - If you deploy a powerful potent technology 298 00:26:52,750 --> 00:26:56,670 at scale, and if you're talking about Google and Facebook, 299 00:26:56,670 --> 00:26:59,530 you're deploying things at scale of billions. 300 00:26:59,530 --> 00:27:02,770 If your artificial intelligence is pushing polarization, 301 00:27:02,770 --> 00:27:05,090 you have global upheaval potentially. 302 00:27:05,720 --> 00:27:09,240 White lives matter! 303 00:27:09,320 --> 00:27:13,620 Black lives matter! 304 00:28:00,620 --> 00:28:04,040 - Artificial General Intelligence, AGI. 305 00:28:06,350 --> 00:28:08,320 Imagine your smartest friend, 306 00:28:09,600 --> 00:28:11,950 with 1,000 friends, just as smart, 307 00:28:14,680 --> 00:28:17,580 and then run them at a 1,000 times faster than real time. 308 00:28:17,580 --> 00:28:19,940 So it means that in every day of our time, 309 00:28:19,940 --> 00:28:22,510 they will do three years of thinking. 310 00:28:22,510 --> 00:28:25,520 Can you imagine how much you could do 311 00:28:26,580 --> 00:28:31,480 if, for every day, you could do three years' worth of work? 312 00:28:52,440 --> 00:28:55,720 It wouldn't be an unfair comparison to say 313 00:28:55,720 --> 00:28:59,780 that what we have right now is even more exciting than 314 00:28:59,780 --> 00:29:02,510 the quantum physicists of the early 20th century. 315 00:29:02,510 --> 00:29:04,240 They discovered nuclear power. 316 00:29:05,740 --> 00:29:08,380 I feel extremely lucky to be taking part in this. 317 00:29:15,310 --> 00:29:18,820 Many machine learning experts, who are very knowledgeable and experienced, 318 00:29:18,820 --> 00:29:20,820 have a lot of skepticism about AGI. 319 00:29:22,350 --> 00:29:25,900 About when it would happen, and about whether it could happen at all. 320 00:29:31,460 --> 00:29:35,740 But right now, this is something that just not that many people have realized yet. 321 00:29:36,500 --> 00:29:41,240 That the speed of computers, for neural networks, for AI, 322 00:29:41,240 --> 00:29:45,240 are going to become maybe 100,000 times faster 323 00:29:45,240 --> 00:29:46,980 in a small number of years. 324 00:29:49,330 --> 00:29:52,100 The entire hardware industry for a long time 325 00:29:52,100 --> 00:29:54,660 didn't really know what to do next, 326 00:29:55,660 --> 00:30:00,900 but with artificial neural networks, now that they actually work, 327 00:30:00,900 --> 00:30:03,420 you have a reason to build huge computers. 328 00:30:04,530 --> 00:30:06,930 You can build a brain in silicon, it's possible. 329 00:30:14,450 --> 00:30:18,710 The very first AGIs will be basically very, 330 00:30:18,710 --> 00:30:22,850 very large data centers packed with specialized 331 00:30:22,850 --> 00:30:25,660 neural network processors working in parallel. 332 00:30:28,070 --> 00:30:30,920 Compact, hot, power hungry package, 333 00:30:32,140 --> 00:30:35,540 consuming like 10 million homes' worth of energy. 334 00:30:54,140 --> 00:30:55,640 A roast beef sandwich. 335 00:30:55,640 --> 00:30:58,290 Yeah, something slightly different. 336 00:30:58,290 --> 00:30:59,200 Just this once. 337 00:31:04,060 --> 00:31:06,260 Even the very first AGIs 338 00:31:06,260 --> 00:31:09,060 will be dramatically more capable than humans. 339 00:31:10,970 --> 00:31:14,730 Humans will no longer be economically useful for nearly any task. 340 00:31:16,200 --> 00:31:17,880 Why would you want to hire a human, 341 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? 342 00:31:28,900 --> 00:31:31,020 AGI is going to be like, without question, 343 00:31:31,880 --> 00:31:34,660 the most important technology in the history 344 00:31:34,660 --> 00:31:36,600 of the planet by a huge margin. 345 00:31:39,410 --> 00:31:42,550 It's going to be bigger than electricity, nuclear, 346 00:31:42,550 --> 00:31:44,140 and the Internet combined. 347 00:31:45,740 --> 00:31:47,620 In fact, you could say that the whole purpose 348 00:31:47,620 --> 00:31:49,660 of all human science, the purpose of computer science, 349 00:31:49,660 --> 00:31:52,550 the End Game, this is the End Game, to build this. 350 00:31:52,550 --> 00:31:54,130 And it's going to be built. 351 00:31:54,130 --> 00:31:56,000 It's going to be a new life form. 352 00:31:56,000 --> 00:31:57,090 It's going to be... 353 00:31:59,190 --> 00:32:00,740 It's going to make us obsolete. 354 00:32:22,070 --> 00:32:24,520 - European manufacturers know the Americans 355 00:32:24,520 --> 00:32:27,460 have invested heavily in the necessary hardware. 356 00:32:27,460 --> 00:32:29,780 - Step into a brave new world of power, 357 00:32:29,780 --> 00:32:31,630 performance and productivity. 358 00:32:32,360 --> 00:32:35,480 - All of the images you are about to see on the large screen 359 00:32:35,480 --> 00:32:39,030 will be generated by what's in that Macintosh. 360 00:32:39,760 --> 00:32:42,210 - It's my honor and privilege to introduce to you 361 00:32:42,210 --> 00:32:44,700 the Windows 95 Development Team. 362 00:32:45,640 --> 00:32:49,040 - Human physical labor has been mostly obsolete for 363 00:32:49,040 --> 00:32:50,620 getting on for a century. 364 00:32:51,390 --> 00:32:55,300 Routine human mental labor is rapidly becoming obsolete 365 00:32:55,300 --> 00:32:58,980 and that's why we're seeing a lot of the middle class jobs disappearing. 366 00:33:01,010 --> 00:33:02,340 - Every once in a while, 367 00:33:02,340 --> 00:33:06,370 a revolutionary product comes along that changes everything. 368 00:33:06,370 --> 00:33:09,190 Today, Apple is reinventing the phone. 369 00:33:20,730 --> 00:33:24,270 - Machine intelligence is already all around us. 370 00:33:24,270 --> 00:33:27,620 The list of things that we humans can do better than machines 371 00:33:27,620 --> 00:33:29,600 is actually shrinking pretty fast. 372 00:33:35,730 --> 00:33:37,400 - Driverless cars are great. 373 00:33:37,400 --> 00:33:40,010 They probably will reduce accidents. 374 00:33:40,010 --> 00:33:43,670 Except, alongside with that, in the United States, 375 00:33:43,670 --> 00:33:46,410 you're going to lose 10 million jobs. 376 00:33:46,480 --> 00:33:49,980 What are you going to do with 10 million unemployed people? 377 00:33:54,900 --> 00:33:58,660 - The risk for social conflict and tensions, 378 00:33:58,660 --> 00:34:02,080 if you exacerbate inequalities, is very, very high. 379 00:34:11,560 --> 00:34:13,870 - AGI can, by definition, 380 00:34:13,870 --> 00:34:16,700 do all jobs better than we can do. 381 00:34:16,700 --> 00:34:18,610 People who are saying, "Oh, there will always be jobs 382 00:34:18,610 --> 00:34:21,120 "that humans can do better than machines," are simply 383 00:34:21,120 --> 00:34:24,180 betting against science and saying there will never be AGI. 384 00:34:30,860 --> 00:34:33,630 - What we are seeing now is like a train hurtling 385 00:34:33,630 --> 00:34:37,880 down a dark tunnel at breakneck speed and it looks like 386 00:34:37,880 --> 00:34:39,660 we're sleeping at the wheel. 387 00:35:29,170 --> 00:35:34,710 - A large fraction of the digital footprints we're leaving behind are digital images. 388 00:35:35,690 --> 00:35:39,340 And specifically, what's really interesting to me as a psychologist 389 00:35:39,340 --> 00:35:41,470 are digital images of our faces. 390 00:35:44,500 --> 00:35:47,260 Here you can see the difference in the facial outline 391 00:35:47,260 --> 00:35:50,130 of an average gay and an average straight face. 392 00:35:50,130 --> 00:35:52,660 And you can see that straight men 393 00:35:52,660 --> 00:35:55,380 have slightly broader jaws. 394 00:35:55,680 --> 00:36:00,580 Gay women have slightly larger jaws, compared with straight women. 395 00:36:02,510 --> 00:36:05,670 Computer algorithms can reveal our political views 396 00:36:05,670 --> 00:36:08,280 or sexual orientation, or intelligence, 397 00:36:08,280 --> 00:36:11,120 just based on the picture of our faces. 398 00:36:12,070 --> 00:36:16,760 Even a human brain can distinguish between gay and straight men with some accuracy. 399 00:36:16,920 --> 00:36:21,700 Now it turns out that the computer can do it with much higher accuracy. 400 00:36:21,700 --> 00:36:25,200 What you're seeing here is an accuracy of 401 00:36:25,200 --> 00:36:29,410 off-the-shelf facial recognition software. 402 00:36:29,410 --> 00:36:31,640 This is terrible news 403 00:36:31,640 --> 00:36:34,320 for gay men and women all around the world. 404 00:36:34,320 --> 00:36:35,680 And not only gay men and women, 405 00:36:35,680 --> 00:36:38,300 because the same algorithms can be used to detect other 406 00:36:38,300 --> 00:36:42,350 intimate traits, think being a member of the opposition, 407 00:36:42,350 --> 00:36:45,090 or being a liberal, or being an atheist. 408 00:36:46,850 --> 00:36:50,070 Being an atheist is also punishable by death 409 00:36:50,070 --> 00:36:52,610 in Saudi Arabia, for instance. 410 00:36:59,780 --> 00:37:04,440 My mission as an academic is to warn people about the dangers of algorithms 411 00:37:04,440 --> 00:37:08,290 being able to reveal our intimate traits. 412 00:37:09,780 --> 00:37:14,060 The problem is that when people receive bad news, 413 00:37:14,060 --> 00:37:16,260 they very often choose to dismiss them. 414 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, 415 00:37:22,250 --> 00:37:24,830 and I've received quite a few death threats, - 416 00:37:25,910 --> 00:37:30,870 -but as a scientist, I have to basically show what is possible. 417 00:37:33,590 --> 00:37:36,900 So what I'm really interested in now is to try to see 418 00:37:36,900 --> 00:37:41,080 whether we can predict other traits from people's faces. 419 00:37:46,270 --> 00:37:48,580 Now, if you can detect depression from a face, 420 00:37:48,580 --> 00:37:53,580 or suicidal thoughts, maybe a CCTV system 421 00:37:53,690 --> 00:37:56,970 on the train station can save some lives. 422 00:37:59,130 --> 00:38:03,830 What if we could predict that someone is more prone to commit a crime? 423 00:38:04,960 --> 00:38:07,150 You probably had a school counselor, 424 00:38:07,150 --> 00:38:10,380 a psychologist hired there to identify children 425 00:38:10,380 --> 00:38:14,830 that potentially may have some behavioral problems. 426 00:38:17,330 --> 00:38:20,080 So now imagine if you could predict with high accuracy 427 00:38:20,080 --> 00:38:22,590 that someone is likely to commit a crime in the future 428 00:38:22,590 --> 00:38:24,780 from the language use, from the face, 429 00:38:24,780 --> 00:38:27,580 from the facial expressions, from the likes on Facebook. 430 00:38:32,310 --> 00:38:35,210 I'm not developing new methods, I'm just describing 431 00:38:35,210 --> 00:38:38,890 something or testing something in an academic environment. 432 00:38:40,590 --> 00:38:42,790 But there obviously is a chance that, 433 00:38:42,790 --> 00:38:47,790 while warning people against risks of new technologies, 434 00:38:47,960 --> 00:38:50,560 I may also give some people new ideas. 435 00:39:11,140 --> 00:39:13,830 - We haven't yet seen the future in terms of 436 00:39:13,830 --> 00:39:18,780 the ways in which the new data-driven society 437 00:39:18,780 --> 00:39:21,380 is going to really evolve. 438 00:39:23,540 --> 00:39:26,740 The tech companies want to get every possible bit 439 00:39:26,740 --> 00:39:30,170 of information that they can collect on everyone 440 00:39:30,170 --> 00:39:31,690 to facilitate business. 441 00:39:33,470 --> 00:39:37,090 The police and the military want to do the same thing 442 00:39:37,090 --> 00:39:38,830 to facilitate security. 443 00:39:41,960 --> 00:39:46,440 The interests that the two have in common are immense, 444 00:39:46,440 --> 00:39:51,220 and so the extent of collaboration between what you might 445 00:39:51,220 --> 00:39:56,820 call the Military-Tech Complex is growing dramatically. 446 00:40:00,400 --> 00:40:03,010 - The CIA, for a very long time, 447 00:40:03,010 --> 00:40:06,120 has maintained a close connection with Silicon Valley. 448 00:40:07,110 --> 00:40:10,270 Their venture capital firm known as In-Q-Tel, 449 00:40:10,270 --> 00:40:13,870 makes seed investments to start-up companies developing 450 00:40:13,870 --> 00:40:17,490 breakthrough technology that the CIA hopes to deploy. 451 00:40:18,660 --> 00:40:22,100 Palantir, the big data analytics firm, 452 00:40:22,100 --> 00:40:25,100 one of their first seed investments was from In-Q-Tel. 453 00:40:28,950 --> 00:40:31,780 - In-Q-Tel has struck gold in Palantir 454 00:40:31,780 --> 00:40:35,990 in helping to create a private vendor 455 00:40:35,990 --> 00:40:40,850 that has intelligence and artificial intelligence 456 00:40:40,850 --> 00:40:44,460 capabilities that the government can't even compete with. 457 00:40:46,370 --> 00:40:48,720 - Good evening, I'm Peter Thiel. 458 00:40:49,740 --> 00:40:54,210 I'm not a politician, but neither is Donald Trump. 459 00:40:54,210 --> 00:40:58,620 He is a builder and it's time to rebuild America. 460 00:41:01,280 --> 00:41:03,940 - Peter Thiel, the founder of Palantir, 461 00:41:03,940 --> 00:41:06,680 was a Donald Trump transition advisor 462 00:41:06,680 --> 00:41:09,180 and a close friend and donor. 463 00:41:11,080 --> 00:41:13,700 Trump was elected largely on the promise 464 00:41:13,700 --> 00:41:17,560 to deport millions of immigrants. 465 00:41:17,560 --> 00:41:22,240 The only way you can do that is with a lot of intelligence 466 00:41:22,240 --> 00:41:25,010 and that's where Palantir comes in. 467 00:41:28,680 --> 00:41:33,340 They ingest huge troves of data, which include, 468 00:41:33,340 --> 00:41:37,370 where you live, where you work, who you know, 469 00:41:37,370 --> 00:41:40,930 who your neighbors are, who your family is, 470 00:41:40,930 --> 00:41:44,480 where you have visited, where you stay, 471 00:41:44,480 --> 00:41:46,320 your social media profile. 472 00:41:49,250 --> 00:41:53,240 Palantir gets all of that and is remarkably good 473 00:41:53,240 --> 00:41:58,240 at structuring it in a way that helps law enforcement, 474 00:41:58,460 --> 00:42:02,450 immigration authorities or intelligence agencies 475 00:42:02,450 --> 00:42:06,210 of any kind, track you, find you, 476 00:42:06,210 --> 00:42:09,550 and learn everything there is to know about you. 477 00:42:48,430 --> 00:42:51,040 - We're putting AI in charge now of evermore 478 00:42:51,040 --> 00:42:53,860 important decisions that affect people's lives. 479 00:42:54,810 --> 00:42:58,050 Old-school AI used to have its intelligence programmed in 480 00:42:58,050 --> 00:43:01,420 by humans who understood how it worked, but today, 481 00:43:01,420 --> 00:43:04,080 powerful AI systems have just learned for themselves, 482 00:43:04,080 --> 00:43:07,480 and we have no clue really how they work, 483 00:43:07,480 --> 00:43:09,680 which makes it really hard to trust them. 484 00:43:14,270 --> 00:43:17,820 - This isn't some futuristic technology, this is now. 485 00:43:19,470 --> 00:43:23,220 AI might help determine where a fire department 486 00:43:23,220 --> 00:43:25,900 is built in a community or where a school is built. 487 00:43:25,900 --> 00:43:28,380 It might decide whether you get bail, 488 00:43:28,380 --> 00:43:30,680 or whether you stay in jail. 489 00:43:30,680 --> 00:43:32,930 It might decide where the police are going to be. 490 00:43:32,930 --> 00:43:37,140 It might decide whether you're going to be under additional police scrutiny. 491 00:43:43,340 --> 00:43:46,140 - It's popular now in the US to do predictive policing. 492 00:43:46,980 --> 00:43:50,900 So what they do is they use an algorithm to figure out where crime will be, 493 00:43:51,760 --> 00:43:55,240 - and they use that to tell where we should send police officers. 494 00:43:56,430 --> 00:43:59,420 So that's based on a measurement of crime rate. 495 00:44:00,640 --> 00:44:02,330 So we know that there is bias. 496 00:44:02,330 --> 00:44:05,090 Black people and Hispanic people are pulled over, 497 00:44:05,090 --> 00:44:07,180 and stopped by the police officers more frequently 498 00:44:07,180 --> 00:44:09,820 than white people are, so we have this biased data going in, 499 00:44:09,820 --> 00:44:11,820 and then what happens is you use that to say, 500 00:44:11,820 --> 00:44:13,640 "Oh, here's where the cops should go." 501 00:44:13,640 --> 00:44:17,320 Well, the cops go to those neighborhoods, and guess what they do, they arrest people. 502 00:44:17,680 --> 00:44:21,160 And then it feeds back biased data into the system, 503 00:44:21,160 --> 00:44:23,060 and that's called a feedback loop. 504 00:44:35,990 --> 00:44:40,650 - Predictive policing leads at the extremes 505 00:44:41,590 --> 00:44:45,910 to experts saying, "Show me your baby, 506 00:44:45,910 --> 00:44:48,860 "and I will tell you whether she's going to be a criminal." 507 00:44:51,300 --> 00:44:55,780 Now that we can predict it, we're going to then surveil 508 00:44:55,780 --> 00:45:01,100 those kids much more closely and we're going to jump on them 509 00:45:01,100 --> 00:45:03,700 at the first sign of a problem. 510 00:45:03,700 --> 00:45:06,700 And that's going to make for more effective policing. 511 00:45:07,000 --> 00:45:11,250 It does, but it's going to make for a really grim society 512 00:45:11,250 --> 00:45:16,250 and it's reinforcing dramatically existing injustices. 513 00:45:22,960 --> 00:45:27,810 - Imagine a world in which networks of CCTV cameras, 514 00:45:27,810 --> 00:45:30,930 drone surveillance cameras, have sophisticated 515 00:45:30,930 --> 00:45:34,440 face recognition technologies and are connected 516 00:45:34,440 --> 00:45:37,020 to other government surveillance databases. 517 00:45:38,080 --> 00:45:41,190 We will have the technology in place to have 518 00:45:41,190 --> 00:45:45,690 all of our movements comprehensively tracked and recorded. 519 00:45:47,680 --> 00:45:50,330 What that also means is that we will have 520 00:45:50,330 --> 00:45:52,940 created a surveillance time machine 521 00:45:52,940 --> 00:45:56,620 that will allow governments and powerful corporations 522 00:45:56,620 --> 00:45:58,710 to essentially hit rewind on our lives. 523 00:45:58,710 --> 00:46:01,780 We might not be under any suspicion now 524 00:46:01,780 --> 00:46:03,860 and five years from now, they might want to know 525 00:46:03,860 --> 00:46:08,100 more about us, and can then recreate granularly 526 00:46:08,100 --> 00:46:10,260 everything we've done, everyone we've seen, 527 00:46:10,260 --> 00:46:13,050 everyone we've been around over that entire period. 528 00:46:15,820 --> 00:46:19,320 That's an extraordinary amount of power 529 00:46:19,320 --> 00:46:21,660 for us to seed to anyone. 530 00:46:22,910 --> 00:46:25,370 And it's a world that I think has been difficult 531 00:46:25,370 --> 00:46:29,180 for people to imagine, but we've already built 532 00:46:29,180 --> 00:46:31,660 the architecture to enable that. 533 00:47:07,140 --> 00:47:10,290 - I'm a political reporter and I'm very interested 534 00:47:10,290 --> 00:47:14,670 in the ways powerful industries use their political power 535 00:47:14,670 --> 00:47:17,180 to influence the public policy process. 536 00:47:21,000 --> 00:47:24,420 The large tech companies and their lobbyists get together 537 00:47:24,420 --> 00:47:27,530 behind closed doors and are able to craft policies 538 00:47:27,530 --> 00:47:29,340 that we all have to live under. 539 00:47:30,790 --> 00:47:35,780 That's true for surveillance policies, for policies in terms of data collection, 540 00:47:35,780 --> 00:47:40,540 but also increasingly important when it comes to military and foreign policy. 541 00:47:43,930 --> 00:47:50,220 Starting in 2016, the Defense Department formed the Defense Innovation Board. 542 00:47:50,220 --> 00:47:54,010 That's a special body created to bring top tech executives 543 00:47:54,010 --> 00:47:56,420 into closer contact with the military. 544 00:47:59,140 --> 00:48:01,750 Eric Schmidt, former chairman of Alphabet, 545 00:48:01,750 --> 00:48:03,380 the parent company of Google, 546 00:48:03,380 --> 00:48:07,240 became the chairman of the Defense Innovation Board, 547 00:48:07,240 --> 00:48:09,930 and one of their first priorities was to say, 548 00:48:09,930 --> 00:48:13,850 "We need more artificial intelligence integrated into the military." 549 00:48:15,930 --> 00:48:19,190 - I've worked with a group of volunteers over the 550 00:48:19,190 --> 00:48:22,150 last couple of years to take a look at innovation in the 551 00:48:22,150 --> 00:48:26,780 overall military, and my summary conclusion is that we have 552 00:48:26,780 --> 00:48:30,460 fantastic people who are trapped in a very bad system. 553 00:48:33,290 --> 00:48:35,700 - From the Department of Defense's perspective, 554 00:48:35,700 --> 00:48:37,700 where I really started to get interested in it 555 00:48:37,700 --> 00:48:40,980 was when we started thinking about Unmanned Systems and 556 00:48:40,980 --> 00:48:45,980 how robotic and unmanned systems would start to change war. 557 00:48:46,160 --> 00:48:50,320 The smarter you made the Unmanned Systems and robots, 558 00:48:50,320 --> 00:48:53,570 the more powerful you might be able to make your military. 559 00:48:55,540 --> 00:48:57,240 - Under Secretary of Defense, 560 00:48:57,240 --> 00:49:00,420 Robert Work put together a major memo known as 561 00:49:00,420 --> 00:49:03,680 the Algorithmic Warfare Cross-Functional Team, 562 00:49:03,680 --> 00:49:05,540 better known as Project Maven. 563 00:49:07,830 --> 00:49:10,760 Eric Schmidt gave a number of speeches and media appearances 564 00:49:10,760 --> 00:49:14,310 where he said this effort was designed to increase fuel 565 00:49:14,310 --> 00:49:18,240 efficiency in the Air Force, to help with the logistics, 566 00:49:18,240 --> 00:49:21,300 but behind closed doors there was another parallel effort. 567 00:49:26,710 --> 00:49:29,760 Late in 2017 as part of Project Maven, 568 00:49:29,760 --> 00:49:33,710 Google, Eric Schmidt's firm, was tasked to secretly work 569 00:49:33,710 --> 00:49:36,100 on another part of Project Maven, 570 00:49:36,100 --> 00:49:41,480 and that was to take the vast volumes of image data vacuumed up 571 00:49:41,480 --> 00:49:47,060 by drones operating in Iraq and Afghanistan and to teach an AI 572 00:49:47,060 --> 00:49:49,690 to quickly identify targets on the battlefield. 573 00:49:52,600 --> 00:49:58,470 - We have a sensor and the sensor can do full motion video of an entire city. 574 00:49:58,470 --> 00:50:01,690 And we would have three seven-person teams working 575 00:50:01,690 --> 00:50:06,360 constantly and they could process 15% of the information. 576 00:50:06,360 --> 00:50:08,950 The other 85% of the information was just left 577 00:50:08,950 --> 00:50:14,040 on the cutting room floor, so we said, "Hey, AI and machine learning 578 00:50:14,040 --> 00:50:17,810 "would help us process 100% of the information." 579 00:50:25,380 --> 00:50:28,760 - Google has long had the motto, "Don't be evil." 580 00:50:28,760 --> 00:50:30,630 They have created a public image 581 00:50:30,630 --> 00:50:35,080 that they are devoted to public transparency. 582 00:50:35,080 --> 00:50:39,200 But for Google to slowly transform into a defense contractor, 583 00:50:39,200 --> 00:50:41,720 they maintained the utmost secrecy. 584 00:50:41,720 --> 00:50:45,280 And you had Google entering into this contract with most of the employees, 585 00:50:45,280 --> 00:50:49,020 even employees who were working on the program completely left in the dark. 586 00:51:01,840 --> 00:51:05,050 - Usually within Google, anyone in the company 587 00:51:05,050 --> 00:51:08,100 is allowed to know about any other project that's happening 588 00:51:08,100 --> 00:51:09,800 in some other part of the company. 589 00:51:11,180 --> 00:51:14,300 With Project Maven, the fact that it was kept secret, 590 00:51:14,300 --> 00:51:18,740 I think was alarming to people because that's not the norm at Google. 591 00:51:20,620 --> 00:51:22,940 - When this story was first revealed, 592 00:51:22,940 --> 00:51:25,540 it set off a firestorm within Google. 593 00:51:25,540 --> 00:51:28,420 You had a number of employees quitting in protests, 594 00:51:28,420 --> 00:51:31,900 others signing a petition objecting to this work. 595 00:51:34,130 --> 00:51:37,680 - You have to really say, "I don't want to be part of this anymore." 596 00:51:38,820 --> 00:51:41,750 There are companies called defense contractors 597 00:51:41,750 --> 00:51:45,830 and Google should just not be one of those companies 598 00:51:45,830 --> 00:51:50,040 because people need to trust Google for Google to work. 599 00:51:52,070 --> 00:51:55,710 - Good morning and welcome to Google I/O. 600 00:51:57,310 --> 00:52:00,160 - We've seen emails that show that Google simply 601 00:52:00,160 --> 00:52:03,350 continued to mislead their employees that the drone 602 00:52:03,350 --> 00:52:07,390 targeting program was only a minor effort that could at most 603 00:52:07,390 --> 00:52:11,170 be worth $9 million to the firm, which is drops in the bucket 604 00:52:11,170 --> 00:52:13,540 for a gigantic company like Google. 605 00:52:14,400 --> 00:52:17,300 But from internal emails that we obtained, 606 00:52:17,300 --> 00:52:21,530 Google was expecting Project Maven would ramp up to as much 607 00:52:21,530 --> 00:52:26,530 as $250 million, and that this entire effort would provide 608 00:52:26,630 --> 00:52:29,900 Google with Special Defense Department certification to make 609 00:52:29,900 --> 00:52:32,660 them available for even bigger defense contracts, 610 00:52:32,660 --> 00:52:34,980 some worth as much as $10 billion. 611 00:52:45,710 --> 00:52:49,750 The pressure for Google to compete for military contracts 612 00:52:49,750 --> 00:52:53,780 has come at a time when its competitors are also shifting their culture. 613 00:52:55,850 --> 00:53:00,070 Amazon, similarly pitching the military and law enforcement. 614 00:53:00,070 --> 00:53:02,280 IBM and other leading firms, 615 00:53:02,280 --> 00:53:04,890 they're pitching law enforcement and military. 616 00:53:05,840 --> 00:53:09,420 To stay competitive, Google has slowly transformed. 617 00:53:15,150 --> 00:53:18,910 - The Defense Science Board said of all of the 618 00:53:18,910 --> 00:53:22,170 technological advances that are happening right now, 619 00:53:22,170 --> 00:53:26,780 the single most important thing was artificial intelligence 620 00:53:26,780 --> 00:53:30,780 and the autonomous operations that it would lead. 621 00:53:30,780 --> 00:53:32,330 Are we investing enough? 622 00:53:37,810 --> 00:53:41,220 - Once we develop what are known as 623 00:53:41,220 --> 00:53:45,820 autonomous lethal weapons, in other words, 624 00:53:45,820 --> 00:53:51,510 weapons that are not controlled at all, they are genuinely autonomous, 625 00:53:51,510 --> 00:53:54,000 you've only got to get a president who says, 626 00:53:54,000 --> 00:53:56,410 "The hell with international law, we've got these weapons. 627 00:53:56,410 --> 00:53:58,560 "We're going to do what we want with them." 628 00:54:02,540 --> 00:54:03,960 - We're very close. 629 00:54:03,960 --> 00:54:06,340 When you have the hardware already set up 630 00:54:06,340 --> 00:54:10,360 and all you have to do is flip a switch to make it fully autonomous, 631 00:54:10,360 --> 00:54:13,240 what is it there that's stopping you from doing that? 632 00:54:14,670 --> 00:54:19,080 There's something really to be feared in war at machine speed. 633 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 634 00:54:24,370 --> 00:54:28,060 and you have a team of drones and you've delegated control to half of them, 635 00:54:28,060 --> 00:54:30,790 and you're collaborating in real time? 636 00:54:30,790 --> 00:54:35,600 What happens when that swarm of drones is tasked with engaging a city? 637 00:54:37,490 --> 00:54:39,870 How will they take over that city? 638 00:54:39,870 --> 00:54:42,760 The answer is we won't know until it happens. 639 00:54:50,020 --> 00:54:53,910 - We do not want an AI system to decide 640 00:54:53,910 --> 00:54:56,180 what human it would attack, 641 00:54:56,180 --> 00:54:59,500 but we're going up against authoritarian competitors. 642 00:54:59,500 --> 00:55:02,450 So in my view, an authoritarian regime 643 00:55:02,450 --> 00:55:05,710 will have less problem delegating authority 644 00:55:05,710 --> 00:55:08,460 to a machine to make lethal decisions. 645 00:55:09,410 --> 00:55:12,660 So how that plays out remains to be seen. 646 00:55:37,270 --> 00:55:41,020 - Almost the gift of AI now is that it will force us 647 00:55:41,020 --> 00:55:44,410 collectively to think through at a very basic level, 648 00:55:44,410 --> 00:55:46,310 what does it mean to be human? 649 00:55:48,620 --> 00:55:50,510 What do I do as a human better 650 00:55:50,510 --> 00:55:52,970 than a certain super smart machine can do? 651 00:55:56,300 --> 00:56:01,000 First, we create our technology and then it recreates us. 652 00:56:01,000 --> 00:56:05,630 We need to make sure that we don't miss some of the things 653 00:56:05,630 --> 00:56:07,520 that make us so beautiful human. 654 00:56:11,840 --> 00:56:14,380 - Once we build intelligent machines, 655 00:56:14,380 --> 00:56:16,920 the philosophical vocabulary we have available to think 656 00:56:16,920 --> 00:56:20,680 about ourselves as human increasingly fails us. 657 00:56:23,160 --> 00:56:25,950 If I ask you to write up a list of all the terms you have 658 00:56:25,950 --> 00:56:28,960 available to describe yourself as human, 659 00:56:28,960 --> 00:56:31,100 there are not so many terms. 660 00:56:31,100 --> 00:56:38,140 Culture, history, sociality, maybe politics, civilization, 661 00:56:38,820 --> 00:56:45,090 subjectivity, all of these terms ground in two positions 662 00:56:45,670 --> 00:56:48,020 that humans are more than mere animals 663 00:56:49,000 --> 00:56:52,200 and that humans are more than mere machines. 664 00:56:55,140 --> 00:56:59,290 But if machines truly think there is a large set 665 00:56:59,290 --> 00:57:03,520 of key philosophical questions in which what is at stake is: 666 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? 667 00:57:09,080 --> 00:57:12,190 Do the categories that we have relied on 668 00:57:12,190 --> 00:57:14,510 - Do they still work? Were they wrong? 669 00:57:19,500 --> 00:57:22,220 - Many people think of intelligence as something mysterious 670 00:57:22,220 --> 00:57:26,190 that can only exist inside of biological organisms, like us, 671 00:57:26,190 --> 00:57:29,260 but intelligence is all about information processing. 672 00:57:30,280 --> 00:57:32,230 It doesn't matter whether the intelligence is processed 673 00:57:32,230 --> 00:57:35,940 by carbon atoms inside of cells and brains, and people, 674 00:57:35,940 --> 00:57:38,020 or by silicon atoms in computers. 675 00:57:40,700 --> 00:57:43,320 Part of the success of AI recently has come 676 00:57:43,320 --> 00:57:47,540 from stealing great ideas from evolution. 677 00:57:47,540 --> 00:57:49,320 We noticed that the brain, for example, 678 00:57:49,320 --> 00:57:52,920 has all these neurons inside connected in complicated ways. 679 00:57:52,920 --> 00:57:55,660 So we stole that idea and abstracted it 680 00:57:55,660 --> 00:57:58,350 into artificial neural networks in computers, 681 00:57:59,330 --> 00:58:02,800 and that's what has revolutionized machine intelligence. 682 00:58:07,690 --> 00:58:10,300 If we one day get Artificial General Intelligence, 683 00:58:10,300 --> 00:58:14,330 then by definition, AI can also do better the job of AI 684 00:58:14,330 --> 00:58:18,930 programming and that means that further progress in making 685 00:58:18,930 --> 00:58:22,950 AI will be dominated not by human programmers, but by AI. 686 00:58:25,450 --> 00:58:29,090 Recursively self-improving AI could leave human intelligence 687 00:58:29,090 --> 00:58:32,990 far behind, creating super intelligence. 688 00:58:34,970 --> 00:58:37,970 It's gonna be the last invention we ever need to make, 689 00:58:37,970 --> 00:58:40,520 because it can then invent everything else 690 00:58:40,520 --> 00:58:42,010 much faster than we could. 691 00:59:54,040 --> 00:59:59,040 - There is a future that we all need to talk about. 692 00:59:59,110 --> 01:00:02,430 Some of the fundamental questions about the future 693 01:00:02,430 --> 01:00:06,280 of artificial intelligence, not just where it's going, 694 01:00:06,280 --> 01:00:09,630 but what it means for society to go there. 695 01:00:10,930 --> 01:00:14,620 It is not what computers can do, 696 01:00:14,620 --> 01:00:17,590 but what computers should do. 697 01:00:17,590 --> 01:00:22,210 As the generation of people that is bringing AI to the future, 698 01:00:22,210 --> 01:00:27,690 we are the generation that will answer this question first and foremost. 699 01:00:34,570 --> 01:00:37,380 - We haven't created the human-level thinking machine yet, 700 01:00:37,380 --> 01:00:39,410 but we get closer and closer. 701 01:00:41,100 --> 01:00:44,780 Maybe we'll get to human-level AI in five years from now 702 01:00:44,780 --> 01:00:47,410 or maybe it'll take 50 or 100 years from now. 703 01:00:47,660 --> 01:00:51,540 It almost doesn't matter. Like these are all really, really soon, 704 01:00:51,540 --> 01:00:56,060 in terms of the overall history of humanity. 705 01:01:01,200 --> 01:01:02,180 Very nice. 706 01:01:15,750 --> 01:01:19,350 So, the AI field is extremely international. 707 01:01:19,350 --> 01:01:23,790 China is up and coming and it's starting to rival the US, 708 01:01:23,790 --> 01:01:26,940 Europe and Japan in terms of putting a lot 709 01:01:26,940 --> 01:01:29,770 of processing power behind AI 710 01:01:29,770 --> 01:01:33,120 and gathering a lot of data to help AI learn. 711 01:01:35,960 --> 01:01:40,540 We have a young generation of Chinese researchers now. 712 01:01:40,540 --> 01:01:43,910 Nobody knows where the next revolution is going to come from. 713 01:01:50,120 --> 01:01:54,290 - China always wanted to become the superpower in the world. 714 01:01:56,120 --> 01:01:59,410 The Chinese government thinks AI gave them the chance to become 715 01:01:59,410 --> 01:02:03,940 one of the most advanced technology wise, business wise. 716 01:02:04,190 --> 01:02:07,780 So the Chinese government look at this as a huge opportunity. 717 01:02:09,140 --> 01:02:13,670 Like they've raised a flag and said, "That's a good field. 718 01:02:13,670 --> 01:02:16,300 "The companies should jump into it." 719 01:02:16,300 --> 01:02:18,300 Then China's commercial world and companies say, 720 01:02:18,300 --> 01:02:20,800 "Okay, the government raised a flag, that's good. 721 01:02:20,800 --> 01:02:22,500 "Let's put the money into it." 722 01:02:23,900 --> 01:02:28,090 Chinese tech giants, like Baidu, like Tencent and like AliBaba, 723 01:02:28,090 --> 01:02:31,800 they put a lot of the investment into the AI field. 724 01:02:33,410 --> 01:02:36,740 So we see that China's AI development is booming. 725 01:02:43,430 --> 01:02:47,370 - In China, everybody has Alipay and WeChat pay, 726 01:02:47,370 --> 01:02:49,500 so mobile payment is everywhere. 727 01:02:50,850 --> 01:02:54,850 And with that, they can do a lot of AI analysis 728 01:02:54,850 --> 01:02:59,340 to know like your spending habits, your credit rating. 729 01:03:01,150 --> 01:03:06,100 Face recognition technology is widely adopted in China, 730 01:03:06,100 --> 01:03:08,200 in airports and train stations. 731 01:03:09,040 --> 01:03:11,570 So, in the future, maybe in just a few months, 732 01:03:11,570 --> 01:03:15,140 you don't need a paper ticket to board a train. 733 01:03:15,140 --> 01:03:15,970 Only your face. 734 01:03:24,620 --> 01:03:29,690 - We generate the world's biggest platform of facial recognition. 735 01:03:31,260 --> 01:03:37,300 We have 300,000 developers using our platform. 736 01:03:38,330 --> 01:03:41,550 A lot of it is selfie camera apps. 737 01:03:41,550 --> 01:03:43,930 It makes you look more beautiful. 738 01:03:46,550 --> 01:03:49,780 There are millions and millions of cameras in the world, 739 01:03:50,760 --> 01:03:54,880 each camera from my point is a data generator. 740 01:03:58,820 --> 01:04:02,810 In a machine's eye, your face will change into the features 741 01:04:02,810 --> 01:04:06,660 and it will turn your face into a paragraph of code. 742 01:04:07,720 --> 01:04:11,980 So we can detect how old you are, if you're male or female, 743 01:04:11,980 --> 01:04:13,440 and your emotions. 744 01:04:16,640 --> 01:04:20,110 Shopping is about what kind of thing you are looking at. 745 01:04:20,110 --> 01:04:25,650 We can track your eyeballs, so if you are focusing on some product, 746 01:04:25,650 --> 01:04:28,690 we can track that so that we can know 747 01:04:28,690 --> 01:04:32,120 which kind of people like which kind of product. 748 01:04:42,450 --> 01:04:45,820 Our mission is to create a platform 749 01:04:45,950 --> 01:04:50,300 that will enable millions of AI developers in China. 750 01:04:51,280 --> 01:04:58,060 We study all the data we can get. 751 01:05:00,440 --> 01:05:04,350 Not just user profiles, 752 01:05:04,350 --> 01:05:08,380 but what you are doing at the moment, 753 01:05:09,460 --> 01:05:12,060 your geographical location. 754 01:05:15,380 --> 01:05:23,580 This platform will be so valuable that we don't even worry about profit now, 755 01:05:23,580 --> 01:05:27,660 because it is definitely there. 756 01:05:29,660 --> 01:05:34,420 China's social credit system is just one of the applications. 757 01:05:45,990 --> 01:05:48,040 - The Chinese government is using multiple 758 01:05:48,040 --> 01:05:50,810 different kinds of technologies, whether it's AI, 759 01:05:50,810 --> 01:05:53,650 whether it's big data platforms, facial recognition, 760 01:05:53,650 --> 01:05:57,030 voice recognition, essentially to monitor 761 01:05:57,030 --> 01:05:58,800 what the population is doing. 762 01:06:01,860 --> 01:06:04,240 I think the Chinese government has made very clear 763 01:06:04,240 --> 01:06:09,240 its intent to gather massive amounts of data about people 764 01:06:09,600 --> 01:06:13,300 to socially engineer a dissent-free society. 765 01:06:16,040 --> 01:06:19,060 The logic behind the Chinese government's 766 01:06:19,060 --> 01:06:23,180 social credit system, it's to take the idea that 767 01:06:23,180 --> 01:06:27,930 whether you are credit worthy for a financial loan 768 01:06:27,930 --> 01:06:31,860 and adding to it a very political dimension to say, 769 01:06:31,860 --> 01:06:34,270 "Are you a trustworthy human being? 770 01:06:36,530 --> 01:06:40,270 "What you've said online, have you ever been critical of the authorities? 771 01:06:40,270 --> 01:06:42,190 "Do you have a criminal record?" 772 01:06:43,720 --> 01:06:47,340 And all that information is packaged up together to rate 773 01:06:47,340 --> 01:06:51,820 you in ways that if you have performed well in their view, 774 01:06:51,820 --> 01:06:56,490 you'll have easier access to certain kinds of state services or benefits. 775 01:06:57,790 --> 01:06:59,710 But if you haven't done very well, 776 01:06:59,710 --> 01:07:02,130 you are going to be penalized or restricted. 777 01:07:05,940 --> 01:07:09,020 There's no way for people to challenge those designations 778 01:07:09,020 --> 01:07:12,100 or, in some cases, even know that they've been put in that category, 779 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, 780 01:07:17,990 --> 01:07:20,460 or get a passport, or enroll their kid in school, 781 01:07:20,460 --> 01:07:23,590 that they come to learn that they've been labeled in this way, 782 01:07:23,590 --> 01:07:27,550 and that there are negative consequences for them as a result. 783 01:07:44,970 --> 01:07:48,660 We've spent the better part of the last one or two years 784 01:07:48,660 --> 01:07:53,180 looking at abuses of surveillance technology across China, 785 01:07:53,180 --> 01:07:56,030 and a lot of that work has taken us to Xinjiang, 786 01:07:57,580 --> 01:08:01,220 the Northwestern region of China that has a more than half 787 01:08:01,220 --> 01:08:05,870 population of Turkic Muslims, Uyghurs, Kazakhs and Hui. 788 01:08:08,430 --> 01:08:10,980 This is a region and a population the Chinese government 789 01:08:10,980 --> 01:08:14,900 has long considered to be politically suspect or disloyal. 790 01:08:17,580 --> 01:08:20,160 We came to find information about what's called 791 01:08:20,160 --> 01:08:23,130 the Integrated Joint Operations Platform, 792 01:08:23,130 --> 01:08:27,190 which is a predictive policing program and that's one 793 01:08:27,190 --> 01:08:30,650 of the programs that has been spitting out lists of names 794 01:08:30,650 --> 01:08:33,560 of people to be subjected to political re-education. 795 01:08:39,090 --> 01:08:42,770 A number of our interviewees for the report we just released 796 01:08:42,770 --> 01:08:46,110 about the political education camps in Xinjiang just 797 01:08:46,110 --> 01:08:50,380 painted an extraordinary portrait of a surveillance state. 798 01:08:53,460 --> 01:08:56,380 A region awash in surveillance cameras 799 01:08:56,380 --> 01:09:00,600 for facial recognition purposes, checkpoints, body scanners, 800 01:09:00,600 --> 01:09:04,030 QR codes outside people's homes. 801 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, 802 01:09:10,690 --> 01:09:13,160 "Wow, that would be a creepy world to live in." 803 01:09:13,160 --> 01:09:16,510 Yeah, well, 13 million Turkic Muslims in China 804 01:09:16,510 --> 01:09:18,530 are living in that reality right now. 805 01:09:30,840 --> 01:09:33,060 - The Intercept reports that Google is planning to 806 01:09:33,060 --> 01:09:36,490 launch a censored version of its search engine in China. 807 01:09:36,490 --> 01:09:38,730 - Google's search for new markets leads it 808 01:09:38,730 --> 01:09:42,170 to China, despite Beijing's rules on censorship. 809 01:09:42,170 --> 01:09:44,080 - Tell us more about why you felt it was 810 01:09:44,080 --> 01:09:46,650 your ethical responsibility to resign, 811 01:09:46,650 --> 01:09:51,060 because you talk about being complicit in censorship and oppression, and surveillance. 812 01:09:51,060 --> 01:09:54,220 - There is a Chinese venture company that has to be 813 01:09:54,220 --> 01:09:56,230 set up for Google to operate in China. 814 01:09:56,230 --> 01:09:58,920 And the question is, to what degree did they get to control 815 01:09:58,920 --> 01:10:01,970 the blacklist and to what degree would they have just 816 01:10:01,970 --> 01:10:05,220 unfettered access to surveilling Chinese citizens? 817 01:10:05,220 --> 01:10:07,470 And the fact that Google refuses to respond 818 01:10:07,470 --> 01:10:09,250 to human rights organizations on this, 819 01:10:09,250 --> 01:10:12,060 I think should be extremely disturbing to everyone. 820 01:10:16,640 --> 01:10:21,120 Due to my conviction that dissent is fundamental to functioning democracies 821 01:10:21,120 --> 01:10:25,560 and forced to resign in order to avoid contributing to or profiting from the erosion 822 01:10:25,560 --> 01:10:27,510 of protections for dissidents. 823 01:10:28,560 --> 01:10:30,920 The UN is currently reporting that between 824 01:10:30,920 --> 01:10:34,190 200,000 and one million Uyghurs have been disappeared 825 01:10:34,190 --> 01:10:36,520 into re-education camps. 826 01:10:36,520 --> 01:10:39,290 And there is a serious argument that Google would be complicit 827 01:10:39,290 --> 01:10:42,460 should it launch a surveilled version of search in China. 828 01:10:45,180 --> 01:10:51,380 Dragonfly is a project meant to launch search in China under 829 01:10:51,390 --> 01:10:55,810 Chinese government regulations, which include censoring 830 01:10:55,810 --> 01:10:59,510 sensitive content, basic queries on human rights, 831 01:10:59,510 --> 01:11:03,210 information about political representatives is blocked, 832 01:11:03,210 --> 01:11:07,080 information about student protests is blocked. 833 01:11:07,080 --> 01:11:09,180 And that's one small part of it. 834 01:11:09,180 --> 01:11:12,250 Perhaps a deeper concern is the surveillance side of this. 835 01:11:16,070 --> 01:11:19,580 When I raised the issue with my managers, with my colleagues, 836 01:11:19,580 --> 01:11:23,370 there was a lot of concern, but everyone just said, "I don't know anything." 837 01:11:27,760 --> 01:11:30,200 And then when there was a meeting finally, 838 01:11:30,200 --> 01:11:35,080 there was essentially no addressing the serious concerns associated with it. 839 01:11:37,010 --> 01:11:39,790 So then I filed my formal resignation, 840 01:11:39,790 --> 01:11:42,950 not just to my manager, but I actually distributed it company-wide. 841 01:11:42,950 --> 01:11:45,440 And that's the letter that I was reading from. 842 01:11:50,360 --> 01:11:55,960 Personally, I haven't slept well. I've had pretty horrific headaches, 843 01:11:55,960 --> 01:11:58,520 wake up in the middle of the night just sweating. 844 01:12:00,640 --> 01:12:03,340 With that said, what I found since speaking out 845 01:12:03,340 --> 01:12:07,930 is just how positive the global response to this has been. 846 01:12:10,350 --> 01:12:13,910 Engineers should demand to know what the uses 847 01:12:13,910 --> 01:12:16,280 of their technical contributions are 848 01:12:16,280 --> 01:12:19,340 and to have a seat at the table in those ethical decisions. 849 01:12:27,020 --> 01:12:29,590 Most citizens don't really understand what it means to be 850 01:12:29,590 --> 01:12:32,250 in a very large scale prescriptive technology. 851 01:12:33,720 --> 01:12:36,260 Where someone has already pre-divided the work 852 01:12:36,260 --> 01:12:38,300 and all you know about is your little piece, 853 01:12:38,300 --> 01:12:41,150 and almost certainly you don't understand how it fits in. 854 01:12:44,630 --> 01:12:51,040 So, I think it's worth drawing the analogy to physicists' work on the atomic bomb. 855 01:12:53,840 --> 01:12:56,610 In fact, that's actually the community I came out of. 856 01:12:59,220 --> 01:13:03,460 I wasn't a nuclear scientist by any means, but I was an applied mathematician 857 01:13:04,400 --> 01:13:09,400 and my PhD program was actually funded to train people to work in weapons labs. 858 01:13:12,980 --> 01:13:17,100 One could certainly argue that there is an existential threat 859 01:13:17,820 --> 01:13:22,060 and whoever is leading in AI will lead militarily. 860 01:13:31,420 --> 01:13:34,250 - China fully expects to pass the United States 861 01:13:34,250 --> 01:13:37,480 as the number one economy in the world and it believes that 862 01:13:37,480 --> 01:13:42,450 AI will make that jump more quickly and more dramatically. 863 01:13:43,900 --> 01:13:46,480 And they also see it as being able to leapfrog 864 01:13:46,480 --> 01:13:49,820 the United States in terms of military power. 865 01:13:57,580 --> 01:13:59,600 Their plan is very simple. 866 01:13:59,600 --> 01:14:03,620 We want to catch the United States and these technologies by 2020, 867 01:14:03,620 --> 01:14:07,940 we want to surpass the United States in these technologies by 2025, 868 01:14:07,940 --> 01:14:12,600 and we want to be the world leader in AI and autonomous technologies by 2030. 869 01:14:15,110 --> 01:14:16,850 It is a national plan. 870 01:14:16,850 --> 01:14:21,790 It is backed up by at least $150 billion in investments. 871 01:14:21,790 --> 01:14:25,060 So, this is definitely a race. 872 01:14:50,070 --> 01:14:52,070 - AI is a little bit like fire. 873 01:14:53,360 --> 01:14:56,270 Fire was invented 700,000 years ago, 874 01:14:57,480 --> 01:14:59,820 and it has its pros and cons. 875 01:15:01,960 --> 01:15:06,810 People realized you can use fire to keep warm at night and to cook, 876 01:15:08,520 --> 01:15:14,420 but they also realized that you can kill other people with that. 877 01:15:19,860 --> 01:15:24,300 Fire also has this AI-like quality of growing 878 01:15:24,300 --> 01:15:27,400 in a wildfire without further human ado, 879 01:15:30,530 --> 01:15:35,970 but the advantages outweigh the disadvantages by so much 880 01:15:35,970 --> 01:15:39,760 that we are not going to stop its development. 881 01:15:49,540 --> 01:15:51,180 Europe is waking up. 882 01:15:52,160 --> 01:15:58,390 Lots of companies in Europe are realizing that the next wave of AI 883 01:15:58,730 --> 01:16:01,540 will be much bigger than the current wave. 884 01:16:03,310 --> 01:16:08,000 The next wave of AI will be about robots. 885 01:16:09,810 --> 01:16:15,450 All these machines that make things, that produce stuff, 886 01:16:15,450 --> 01:16:19,370 that build other machines, they are going to become smart. 887 01:16:26,660 --> 01:16:29,950 In the not-so-distant future, we will have robots 888 01:16:29,950 --> 01:16:33,290 that we can teach like we teach kids. 889 01:16:35,640 --> 01:16:38,660 For example, I will talk to a little robot and I will say, 890 01:16:39,970 --> 01:16:42,550 "Look here, robot, look here. 891 01:16:42,550 --> 01:16:44,620 "Let's assemble a smartphone. 892 01:16:44,620 --> 01:16:48,720 "We take this slab of plastic like that and we takes a screwdriver like that, 893 01:16:48,720 --> 01:16:52,310 "and now we screw in everything like this. 894 01:16:52,310 --> 01:16:54,310 "No, no, not like this. 895 01:16:54,310 --> 01:16:57,690 "Like this, look, robot, look, like this." 896 01:16:58,820 --> 01:17:01,890 And he will fail a couple of times but rather quickly, 897 01:17:01,890 --> 01:17:05,860 he will learn to do the same thing much better than I could do it. 898 01:17:06,710 --> 01:17:11,400 And then we stop the learning and we make a million copies, and sell it. 899 01:17:32,410 --> 01:17:35,800 Regulation of AI sounds like an attractive idea, 900 01:17:35,800 --> 01:17:38,210 but I don't think it's possible. 901 01:17:40,250 --> 01:17:42,720 One of the reasons why it won't work is 902 01:17:42,720 --> 01:17:46,360 the sheer curiosity of scientists. 903 01:17:47,260 --> 01:17:49,560 They don't give a damn for regulation. 904 01:17:52,640 --> 01:17:56,740 Military powers won't give a damn for regulations, either. 905 01:17:56,740 --> 01:17:59,020 They will say, "If we, the Americans don't do it, 906 01:17:59,020 --> 01:18:00,720 "then the Chinese will do it." 907 01:18:00,720 --> 01:18:03,150 And the Chinese will say, "Oh, if we don't do it, 908 01:18:03,150 --> 01:18:04,810 "then the Russians will do it." 909 01:18:07,700 --> 01:18:10,930 No matter what kind of political regulation is out there, 910 01:18:10,930 --> 01:18:14,660 all these military industrial complexes, 911 01:18:14,660 --> 01:18:17,570 they will almost by definition have to ignore that 912 01:18:18,670 --> 01:18:21,250 because they want to avoid falling behind. 913 01:18:26,030 --> 01:18:27,690 Welcome to Xinhua. 914 01:18:27,690 --> 01:18:30,260 I'm the world's first female AI news anchor developed 915 01:18:30,260 --> 01:18:32,690 jointly by Xinhua and search engine company Sogou. 916 01:18:33,050 --> 01:18:36,310 - A program developed by the company OpenAI can write 917 01:18:36,310 --> 01:18:39,500 coherent and credible stories just like human beings. 918 01:18:39,500 --> 01:18:41,520 - It's one small step for machine, 919 01:18:41,520 --> 01:18:44,330 one giant leap for machine kind. 920 01:18:44,330 --> 01:18:47,170 IBM's newest artificial intelligence system took on 921 01:18:47,170 --> 01:18:51,570 experienced human debaters and won a live debate. 922 01:18:51,570 --> 01:18:54,160 - Computer-generated videos known as deep fakes 923 01:18:54,160 --> 01:18:57,980 are being used to put women's faces on pornographic videos. 924 01:19:02,510 --> 01:19:06,450 - Artificial intelligence evolves at a very crazy pace. 925 01:19:07,970 --> 01:19:10,180 You know, it's like progressing so fast. 926 01:19:10,180 --> 01:19:12,940 In some ways, we're only at the beginning right now. 927 01:19:14,490 --> 01:19:17,620 You have so many potential applications, it's a gold mine. 928 01:19:19,590 --> 01:19:23,450 Since 2012, when deep learning became a big game changer 929 01:19:23,450 --> 01:19:25,370 in the computer vision community, 930 01:19:25,370 --> 01:19:28,730 we were one of the first to actually adopt deep learning 931 01:19:28,730 --> 01:19:31,080 and apply it in the field of computer graphics. 932 01:19:34,640 --> 01:19:39,800 A lot of our research is funded by government, military intelligence agencies. 933 01:19:43,950 --> 01:19:47,840 The way we create these photoreal mappings, 934 01:19:47,840 --> 01:19:50,300 usually the way it works is that we need two subjects, 935 01:19:50,300 --> 01:19:53,740 a source and a target, and I can do a face replacement. 936 01:19:58,880 --> 01:20:03,700 One of the applications is, for example, I want to manipulate someone's face 937 01:20:03,700 --> 01:20:05,450 saying things that he did not. 938 01:20:08,920 --> 01:20:12,140 It can be used for creative things, for funny contents, 939 01:20:12,140 --> 01:20:16,110 but obviously, it can also be used for just simply 940 01:20:16,110 --> 01:20:18,660 manipulate videos and generate fake news. 941 01:20:21,050 --> 01:20:23,340 This can be very dangerous. 942 01:20:24,790 --> 01:20:29,300 If it gets into the wrong hands, it can get out of control very quickly. 943 01:20:33,370 --> 01:20:35,750 - We're entering an era in which our enemies can 944 01:20:35,750 --> 01:20:39,590 make it look like anyone is saying anything at any point in time, 945 01:20:39,590 --> 01:20:41,830 even if they would never say those things. 946 01:20:42,450 --> 01:20:46,970 Moving forward, we need to be more vigilant with what we trust from the Internet. 947 01:20:46,970 --> 01:20:50,710 It may sound basic, but how we move forward 948 01:20:50,710 --> 01:20:55,180 in the age of information is going to be the difference 949 01:20:55,180 --> 01:20:58,160 between whether we survive or whether we become 950 01:20:58,160 --> 01:21:00,270 some kind of fucked up dystopia. 951 01:22:31,070 --> 01:22:37,337 - One criticism that is frequently raised against my work is saying that, 952 01:22:37,337 --> 01:22:43,610 "Hey, you know there were stupid ideas in the past like phrenology or physiognomy.- 953 01:22:45,110 --> 01:22:49,210 - "There were people claiming that you can read a character 954 01:22:49,210 --> 01:22:52,010 "of a person just based on their face." 955 01:22:53,820 --> 01:22:56,050 People would say, "This is rubbish. 956 01:22:56,050 --> 01:23:01,050 "We know it was just thinly veiled racism and superstition." 957 01:23:05,300 --> 01:23:09,650 But the fact that someone made a claim in the past 958 01:23:09,650 --> 01:23:14,650 and tried to support this claim with invalid reasoning, 959 01:23:14,960 --> 01:23:18,970 doesn't automatically invalidate the claim. 960 01:23:23,790 --> 01:23:25,710 Of course, people should have rights 961 01:23:25,710 --> 01:23:31,020 to their privacy when it comes to sexual orientation or political views, 962 01:23:32,310 --> 01:23:35,600 but I'm also afraid that in the current technological environment, 963 01:23:35,600 --> 01:23:38,220 this is essentially impossible. 964 01:23:42,640 --> 01:23:44,910 People should realize there's no going back. 965 01:23:44,910 --> 01:23:48,330 There's no running away from the algorithms. 966 01:23:51,120 --> 01:23:55,670 The sooner we accept the inevitable and inconvenient truth 967 01:23:56,540 --> 01:23:59,430 that privacy is gone, 968 01:24:01,770 --> 01:24:05,380 the sooner we can actually start thinking about 969 01:24:05,380 --> 01:24:07,440 how to make sure that our societies 970 01:24:07,440 --> 01:24:11,660 are ready for the Post-Privacy Age. 971 01:24:35,080 --> 01:24:37,610 - While speaking about facial recognition, 972 01:24:37,610 --> 01:24:43,700 in my deep thoughts, I sometimes get to the very dark era of our history. 973 01:24:45,490 --> 01:24:49,020 When the people had to live in the system, 974 01:24:49,020 --> 01:24:52,660 where some part of the society was accepted 975 01:24:53,680 --> 01:24:56,900 and some part of the society was accused to death. 976 01:25:01,670 --> 01:25:06,180 What would Mengele do to have such an instrument in his hands? 977 01:25:10,740 --> 01:25:14,390 It would be very quick and efficient for selection 978 01:25:18,390 --> 01:25:22,100 and this is the apocalyptic vision. 979 01:26:15,880 --> 01:26:19,870 - So in the near future, the entire story of you 980 01:26:19,870 --> 01:26:25,340 will exist in a vast array of connected databases of faces, 981 01:26:25,750 --> 01:26:28,390 genomes, behaviors and emotion. 982 01:26:30,950 --> 01:26:35,320 So, you will have a digital avatar of yourself online, 983 01:26:35,320 --> 01:26:39,510 which records how well you are doing as a citizen, 984 01:26:39,510 --> 01:26:41,910 what kind of a relationship do you have, 985 01:26:41,910 --> 01:26:45,890 what kind of political orientation and sexual orientation. 986 01:26:50,020 --> 01:26:54,120 Based on all of those data, those algorithms will be able to 987 01:26:54,120 --> 01:26:58,390 manipulate your behavior with an extreme precision, 988 01:26:58,390 --> 01:27:03,890 changing how we think and probably in the future, how we feel. 989 01:27:25,660 --> 01:27:30,510 - The beliefs and desires of the first AGIs will be extremely important. 990 01:27:32,730 --> 01:27:35,180 So, it's important to program them correctly. 991 01:27:36,200 --> 01:27:37,850 I think that if this is not done, 992 01:27:38,810 --> 01:27:44,190 then the nature of evolution of natural selection will favor 993 01:27:44,190 --> 01:27:48,340 those systems, prioritize their own survival above all else. 994 01:27:51,860 --> 01:27:56,660 It's not that it's going to actively hate humans and want to harm them, 995 01:27:58,780 --> 01:28:01,100 but it's just going to be too powerful 996 01:28:01,400 --> 01:28:05,470 and I think a good analogy would be the way humans treat animals. 997 01:28:06,970 --> 01:28:08,200 It's not that we hate animals. 998 01:28:08,260 --> 01:28:11,930 I think humans love animals and have a lot of affection for them, 999 01:28:12,340 --> 01:28:17,610 but when the time comes to build a highway between two cities, 1000 01:28:17,610 --> 01:28:20,130 we are not asking the animals for permission. 1001 01:28:20,130 --> 01:28:23,340 We just do it because it's important for us. 1002 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 1003 01:28:29,010 --> 01:28:34,700 and AGIs which are truly autonomous and operating on their own behalf. 1004 01:28:47,190 --> 01:28:51,400 If you have an arms-race dynamics between multiple kings 1005 01:28:51,400 --> 01:28:54,140 trying to build the AGI first, 1006 01:28:54,140 --> 01:28:58,000 they will have less time to make sure that the AGI that they build 1007 01:28:58,970 --> 01:29:00,520 will care deeply for humans. 1008 01:29:03,530 --> 01:29:06,540 Because the way I imagine it is that there is an avalanche, 1009 01:29:06,540 --> 01:29:09,220 there is an avalanche of AGI development. 1010 01:29:09,220 --> 01:29:12,300 Imagine it's a huge unstoppable force. 1011 01:29:15,780 --> 01:29:18,740 And I think it's pretty likely the entire surface of the 1012 01:29:18,740 --> 01:29:22,070 earth would be covered with solar panels and data centers. 1013 01:29:26,230 --> 01:29:28,700 Given these kinds of concerns, 1014 01:29:28,700 --> 01:29:32,830 it will be important that the AGI is somehow built 1015 01:29:32,830 --> 01:29:35,570 as a cooperation with multiple countries. 1016 01:29:38,060 --> 01:29:41,180 The future is going to be good for the AIs, regardless. 1017 01:29:42,130 --> 01:29:45,020 It would be nice if it would be good for humans as well. 1018 01:30:06,750 --> 01:30:10,580 - Is there a lot of responsibility weighing on my shoulders? 1019 01:30:10,580 --> 01:30:11,800 Not really. 1020 01:30:13,420 --> 01:30:16,740 Was there a lot of responsibility on the shoulders 1021 01:30:16,740 --> 01:30:19,100 of the parents of Einstein? 1022 01:30:20,190 --> 01:30:21,780 The parents somehow made him, 1023 01:30:21,780 --> 01:30:25,450 but they had no way of predicting what he would do, 1024 01:30:25,450 --> 01:30:27,300 and how he would change the world. 1025 01:30:28,580 --> 01:30:32,540 And so, you can't really hold them responsible for that. 1026 01:30:57,640 --> 01:31:00,240 So, I'm not a very human-centric person. 1027 01:31:01,840 --> 01:31:05,500 I think I'm a little stepping stone in the evolution 1028 01:31:05,500 --> 01:31:08,060 of the Universe towards higher complexity. 1029 01:31:10,820 --> 01:31:14,860 But it's also clear to me that I'm not the crown of creation 1030 01:31:14,860 --> 01:31:19,320 and that humankind as a whole is not the crown of creation, 1031 01:31:21,140 --> 01:31:26,290 but we are setting the stage for something that is bigger than us that transcends us. 1032 01:31:28,980 --> 01:31:32,780 And then will go out there in a way where humans cannot follow 1033 01:31:32,780 --> 01:31:37,940 and transform the entire Universe, or at least, the reachable Universe. 1034 01:31:41,520 --> 01:31:46,520 So, I find beauty and awe in seeing myself 1035 01:31:46,640 --> 01:31:50,260 as part of this much grander theme. 1036 01:32:14,070 --> 01:32:16,030 - AI is inevitable. 1037 01:32:17,560 --> 01:32:23,370 We need to make sure we have the necessary human regulation 1038 01:32:23,370 --> 01:32:27,940 to prevent the weaponization of artificial intelligence. 1039 01:32:28,690 --> 01:32:32,000 We don't need any more weaponization 1040 01:32:32,000 --> 01:32:33,960 of such a powerful tool. 1041 01:32:37,100 --> 01:32:41,960 - One of the most critical things, I think, is the need for international governance. 1042 01:32:43,920 --> 01:32:46,310 We have an imbalance of power here because now 1043 01:32:46,310 --> 01:32:49,140 we have corporations with more power, might and ability, 1044 01:32:49,140 --> 01:32:51,100 than entire countries. 1045 01:32:51,100 --> 01:32:54,050 How do we make sure that people's voices are getting heard? 1046 01:32:58,030 --> 01:32:59,930 - It can't be a law-free zone. 1047 01:32:59,930 --> 01:33:02,100 It can't be a rights-free zone. 1048 01:33:02,100 --> 01:33:05,870 We can't embrace all of these wonderful new technologies 1049 01:33:05,870 --> 01:33:10,380 for the 21st century without trying to bring with us 1050 01:33:10,380 --> 01:33:15,380 the package of human rights that we fought so hard 1051 01:33:15,640 --> 01:33:19,190 to achieve, and that remains so fragile. 1052 01:33:28,680 --> 01:33:32,180 - AI isn't good and it isn't evil, either. 1053 01:33:32,180 --> 01:33:36,890 It's just going to amplify the desires and goals of whoever controls it. 1054 01:33:36,890 --> 01:33:41,240 And AI today is under the control of a very, very small group of people. 1055 01:33:44,430 --> 01:33:49,260 The most important question that we humans have to ask ourselves at this point in history 1056 01:33:49,260 --> 01:33:51,380 requires no technical knowledge. 1057 01:33:51,590 --> 01:33:57,540 It's the question of what sort of future society do we want to create 1058 01:33:57,540 --> 01:33:59,740 with all this technology we're making? 1059 01:34:01,410 --> 01:34:05,110 What do we want the role of humans to be in this world? 88726

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