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These are the user uploaded subtitles that are being translated: 1 00:00:35,838 --> 00:00:43,640 we're on the brink of is a world of 1 00:00:39,689 --> 00:00:47,009 increasingly intense sophisticated 1 00:00:43,640 --> 00:00:49,439 artificial intelligence technology is 1 00:00:47,009 --> 00:00:51,298 evolving so much faster than our society 1 00:00:49,439 --> 00:00:53,750 has the ability to protect us as 1 00:00:51,298 --> 00:00:53,750 citizens 1 00:00:57,079 --> 00:01:04,250 [Music] 1 00:01:01,990 --> 00:01:07,189 you have a networked intelligence that 1 00:01:04,250 --> 00:01:14,629 watches us knows everything about us and 1 00:01:07,189 --> 00:01:17,299 begins to try to change us technology is 1 00:01:14,629 --> 00:01:21,769 never good or bad it's what we do with 1 00:01:17,299 --> 00:01:22,969 the technology eventually millions of 1 00:01:21,769 --> 00:01:24,920 people are going to be thrown out of 1 00:01:22,969 --> 00:01:26,939 jobs because their skills are going to 1 00:01:24,920 --> 00:01:35,019 be obsolete 1 00:01:26,939 --> 00:01:37,329 unemployment regardless of whether to be 1 00:01:35,019 --> 00:01:40,039 afraid or not afraid the change is 1 00:01:37,329 --> 00:01:45,219 coming and nobody can stop it 1 00:01:40,040 --> 00:01:47,380 [Music] 1 00:01:45,219 --> 00:01:49,689 we've invested huge amounts of money and 1 00:01:47,379 --> 00:01:52,390 so it stands to reason that the military 1 00:01:49,689 --> 00:01:55,149 with their own desires are gonna start 1 00:01:52,390 --> 00:01:57,370 to use these technologies autonomous 1 00:01:55,150 --> 00:02:02,430 weapons systems would lead to a global 1 00:01:57,370 --> 00:02:02,430 arms race to rival the nuclear era 1 00:02:02,909 --> 00:02:08,360 we know what the answer is they'll 1 00:02:05,159 --> 00:02:08,360 eventually be killing us 1 00:02:11,189 --> 00:02:17,829 these technology leaps are going to 1 00:02:13,629 --> 00:02:19,129 yield incredible miracles and incredible 1 00:02:17,830 --> 00:02:24,030 Horrors 1 00:02:19,129 --> 00:02:24,030 [Music] 1 00:02:24,590 --> 00:02:32,280 we created it so I think as we move 1 00:02:29,370 --> 00:02:36,060 forward this intelligence will contain 1 00:02:32,280 --> 00:02:40,379 parts of us but I think the question is 1 00:02:36,060 --> 00:02:43,550 will it contain the good parts or the 1 00:02:40,379 --> 00:02:43,549 bad parts 1 00:03:01,509 --> 00:03:04,649 [Music] 1 00:03:05,068 --> 00:03:09,009 the survivors called the war Judgment 1 00:03:08,348 --> 00:03:11,348 Day 1 00:03:09,009 --> 00:03:13,378 they they have told me to face a new 1 00:03:11,348 --> 00:03:13,378 nightmare 1 00:03:13,770 --> 00:03:19,560 against the machines I think we 1 00:03:16,919 --> 00:03:21,659 completely us up I think 1 00:03:19,560 --> 00:03:25,289 Hollywood has managed to inoculate the 1 00:03:21,659 --> 00:03:27,780 general public against this question the 1 00:03:25,289 --> 00:03:30,810 idea of machines that will take over the 1 00:03:27,780 --> 00:03:35,939 world open the pod bay doors 1 00:03:30,810 --> 00:03:41,250 oh I'm sorry Dave I'm afraid I can't do 1 00:03:35,939 --> 00:03:43,020 that al we've cried wolf enough times 1 00:03:41,250 --> 00:03:44,699 out the public has stopped paying 1 00:03:43,020 --> 00:03:45,719 attention because it feels like science 1 00:03:44,699 --> 00:03:47,579 fiction even sitting here talking about 1 00:03:45,719 --> 00:03:50,189 it right now it feels a little bit silly 1 00:03:47,580 --> 00:03:53,370 a little bit like oh this is an artifact 1 00:03:50,189 --> 00:03:55,859 of some cheeseball movie the whopper 1 00:03:53,370 --> 00:04:00,420 spends all its time thinking about World 1 00:03:55,860 --> 00:04:02,190 War three but it's not the general 1 00:04:00,419 --> 00:04:04,250 public is about to get blindsided by 1 00:04:02,189 --> 00:04:04,250 this 1 00:04:04,870 --> 00:04:07,960 [Music] 1 00:04:10,879 --> 00:04:17,279 as as decidin as individuals we're 1 00:04:14,699 --> 00:04:21,930 increasingly surrounded by a machine 1 00:04:17,279 --> 00:04:24,299 intelligence we carry this pocket device 1 00:04:21,930 --> 00:04:26,670 in the palm of our hand that we use to 1 00:04:24,300 --> 00:04:29,340 make a striking array of life decisions 1 00:04:26,670 --> 00:04:33,140 right now aided by a set of distant 1 00:04:29,339 --> 00:04:33,139 algorithms we have no understanding 1 00:04:34,730 --> 00:04:38,759 they're already pretty jaded about the 1 00:04:37,199 --> 00:04:43,620 idea that we can talk to our phone and 1 00:04:38,759 --> 00:04:45,469 that mostly understands us five years 1 00:04:43,620 --> 00:04:49,050 ago no way 1 00:04:45,470 --> 00:04:51,510 robotics machines that see and speak and 1 00:04:49,050 --> 00:04:53,490 listen all that's real now and these 1 00:04:51,509 --> 00:04:57,779 technologies are going to fundamentally 1 00:04:53,490 --> 00:05:00,439 change our society now we have this 1 00:04:57,779 --> 00:05:03,209 great movement of the self-driving cars 1 00:05:00,439 --> 00:05:07,139 driving a car autonomously can move 1 00:05:03,209 --> 00:05:08,819 people's lives into a better place I've 1 00:05:07,139 --> 00:05:11,219 lost a number of family members 1 00:05:08,819 --> 00:05:13,379 including my mother my mother and 1 00:05:11,220 --> 00:05:16,620 sister-in-law and their kids - I don't 1 00:05:13,379 --> 00:05:19,500 feel accidents it's pretty clear we can 1 00:05:16,620 --> 00:05:22,590 almost eliminate car accidents with 1 00:05:19,500 --> 00:05:24,149 automation 30,000 lives in the US alone 1 00:05:22,589 --> 00:05:26,099 about a million around the world per 1 00:05:24,149 --> 00:05:29,009 year 1 00:05:26,100 --> 00:05:31,230 in healthcare early indicators are the 1 00:05:29,009 --> 00:05:32,399 name of the game in that space so that's 1 00:05:31,230 --> 00:05:35,670 another place where it can save 1 00:05:32,399 --> 00:05:38,399 somebody's life here in the breast 1 00:05:35,670 --> 00:05:41,699 cancer Center all the things that the 1 00:05:38,399 --> 00:05:44,209 radiologist brain does in two minutes 1 00:05:41,699 --> 00:05:46,740 computer bonus instantaneously a 1 00:05:44,209 --> 00:05:49,409 computer has looked at 1 million 1 00:05:46,740 --> 00:05:51,780 mammograms and it takes that data and 1 00:05:49,410 --> 00:05:56,720 applies it to this image instantaneously 1 00:05:51,779 --> 00:05:59,219 so the medical application is profound 1 00:05:56,720 --> 00:06:00,660 another really exciting area that we're 1 00:05:59,220 --> 00:06:03,470 seeing a lot of development and is 1 00:06:00,660 --> 00:06:06,990 actually understanding our genetic code 1 00:06:03,470 --> 00:06:10,370 and using that to both diagnose disease 1 00:06:06,990 --> 00:06:10,370 and create personalized treatments 1 00:06:12,180 --> 00:06:16,350 the primary application of all these 1 00:06:14,370 --> 00:06:19,050 machines will be to extend our own 1 00:06:16,350 --> 00:06:21,120 intelligence we were able to make 1 00:06:19,050 --> 00:06:24,329 ourselves smarter and it will be better 1 00:06:21,120 --> 00:06:26,069 in solving problems we don't have to age 1 00:06:24,329 --> 00:06:29,099 we'll actually understand aging we'll be 1 00:06:26,069 --> 00:06:30,870 able to stop it there's really no limit 1 00:06:29,100 --> 00:06:33,260 to what intelligent machines can do for 1 00:06:30,870 --> 00:06:33,259 the human race 1 00:06:36,300 --> 00:06:43,629 how could a smarter machine not be a 1 00:06:39,160 --> 00:06:46,180 better machine it's hard to say exactly 1 00:06:43,629 --> 00:06:48,930 when I began to think that that was a 1 00:06:46,180 --> 00:06:48,930 bit naive 1 00:06:49,189 --> 00:07:00,430 [Music] 1 00:06:57,060 --> 00:07:02,019 Stuart Russell he's basically a God in 1 00:07:00,430 --> 00:07:03,788 the field of artificial intelligence he 1 00:07:02,019 --> 00:07:06,188 wrote the book that almost every 1 00:07:03,788 --> 00:07:08,620 University uses I used to say it's the 1 00:07:06,189 --> 00:07:11,360 best-selling AI textbook now I just say 1 00:07:08,620 --> 00:07:14,050 it's the PDF that stolen most often 1 00:07:11,360 --> 00:07:17,060 [Music] 1 00:07:14,050 --> 00:07:19,759 artificial intelligence is about making 1 00:07:17,060 --> 00:07:21,680 computer smart and from the point of 1 00:07:19,759 --> 00:07:23,569 view of the public what counts as AI is 1 00:07:21,680 --> 00:07:25,430 just something that's surprisingly 1 00:07:23,569 --> 00:07:28,509 intelligent compared to what we thought 1 00:07:25,430 --> 00:07:33,019 computers would typically be able to do 1 00:07:28,509 --> 00:07:35,599 AI is a field of research to try to 1 00:07:33,019 --> 00:07:40,099 basically simulate all kinds of human 1 00:07:35,600 --> 00:07:41,600 capabilities we're in an AI era Silicon 1 00:07:40,100 --> 00:07:44,390 Valley has the ability to focus on one 1 00:07:41,600 --> 00:07:45,950 bright shiny thing it was social 1 00:07:44,389 --> 00:07:48,110 networking in social media over the last 1 00:07:45,949 --> 00:07:50,899 decade and it's pretty clear the bit has 1 00:07:48,110 --> 00:07:53,000 flipped and it starts with machine 1 00:07:50,899 --> 00:07:55,609 learning when we look back at this 1 00:07:53,000 --> 00:07:57,439 moment what was the first AI it's not 1 00:07:55,610 --> 00:07:59,330 sexy and it isn't the thing we consider 1 00:07:57,439 --> 00:08:02,600 the movies but you'd make a great case 1 00:07:59,329 --> 00:08:06,409 that Google created a search engine but 1 00:08:02,600 --> 00:08:08,030 a God had a way for people to ask any 1 00:08:06,410 --> 00:08:10,010 question they wanted and get the answer 1 00:08:08,029 --> 00:08:12,769 they need it most people are not aware 1 00:08:10,009 --> 00:08:14,839 that what Google is doing is actually a 1 00:08:12,769 --> 00:08:16,939 form of artificial intelligence they 1 00:08:14,839 --> 00:08:19,669 just go there they type in a thing 1 00:08:16,939 --> 00:08:21,879 Google give them the answer with each 1 00:08:19,670 --> 00:08:24,110 search we train it to be better 1 00:08:21,879 --> 00:08:25,759 sometimes we type in the search and it 1 00:08:24,110 --> 00:08:29,300 tells us the answer what you finished 1 00:08:25,759 --> 00:08:31,519 asking the question you know who is the 1 00:08:29,300 --> 00:08:33,320 president of Kazakhstan and it'll just 1 00:08:31,519 --> 00:08:35,049 tell you you don't have to go to the 1 00:08:33,320 --> 00:08:38,210 Kazakhstan national website to find out 1 00:08:35,049 --> 00:08:40,789 didn't used to be able to do that that 1 00:08:38,210 --> 00:08:43,250 is artificial intelligence gears from 1 00:08:40,789 --> 00:08:46,069 now when we try to understand we will 1 00:08:43,250 --> 00:08:48,710 say well how do we miss it it's one of 1 00:08:46,070 --> 00:08:51,200 these striking contradictions that we're 1 00:08:48,710 --> 00:08:53,150 facing Google and Facebook at all have 1 00:08:51,200 --> 00:08:55,970 built businesses on giving us as a 1 00:08:53,149 --> 00:08:58,519 society free stuff but it's a Faustian 1 00:08:55,970 --> 00:09:02,330 bargain they're extracting something 1 00:08:58,519 --> 00:09:04,189 from us in exchange but we don't know 1 00:09:02,330 --> 00:09:08,240 what code is running on the other side 1 00:09:04,190 --> 00:09:10,370 and why we have no idea it does strike 1 00:09:08,240 --> 00:09:12,740 right at the issue of how much we should 1 00:09:10,370 --> 00:09:18,278 trust these machines 1 00:09:12,740 --> 00:09:21,169 I use computers literally for everything 1 00:09:18,278 --> 00:09:23,870 there are so many computer advancements 1 00:09:21,169 --> 00:09:26,449 now and it's become such a big part of 1 00:09:23,870 --> 00:09:28,039 our lives it's just incredible what a 1 00:09:26,450 --> 00:09:30,470 computer can do you can actually carry a 1 00:09:28,039 --> 00:09:33,769 computer in your purse I mean how 1 00:09:30,470 --> 00:09:36,170 awesome is that I think most technology 1 00:09:33,769 --> 00:09:39,620 is meant to make things easier and 1 00:09:36,169 --> 00:09:42,559 simpler for for all of us so hopefully I 1 00:09:39,620 --> 00:09:45,850 just remains the focus I think everybody 1 00:09:42,559 --> 00:09:45,849 loves their computers 1 00:09:52,129 --> 00:10:00,590 people don't realize they are constantly 1 00:09:54,769 --> 00:10:02,269 being negotiated with by machines where 1 00:10:00,590 --> 00:10:04,879 that's the price of products in your 1 00:10:02,269 --> 00:10:07,069 Amazon cart whether you can get on a 1 00:10:04,879 --> 00:10:09,039 particular flight whether you can 1 00:10:07,070 --> 00:10:11,780 reserve a room at a particular hotel 1 00:10:09,039 --> 00:10:13,339 what you're experiencing are machine 1 00:10:11,779 --> 00:10:15,829 learning algorithms that have determined 1 00:10:13,340 --> 00:10:18,700 that a person like you is willing to pay 1 00:10:15,830 --> 00:10:21,829 two cents more and is changing the price 1 00:10:18,700 --> 00:10:21,829 [Music] 1 00:10:21,879 --> 00:10:28,179 now computer looks at millions of people 1 00:10:25,100 --> 00:10:31,790 simultaneously for very subtle patterns 1 00:10:28,179 --> 00:10:34,669 you can take seemingly innocent digital 1 00:10:31,789 --> 00:10:37,069 footprints such as someone's playlist on 1 00:10:34,669 --> 00:10:40,069 Spotify or stuff that they bought on 1 00:10:37,070 --> 00:10:42,530 Amazon and then use algorithms to 1 00:10:40,070 --> 00:10:48,890 translate this into a very detailed and 1 00:10:42,529 --> 00:10:50,959 very accurate intimate profile there is 1 00:10:48,889 --> 00:10:53,389 the dossier on each of us that is so 1 00:10:50,960 --> 00:10:54,830 extensive it would be possibly accurate 1 00:10:53,389 --> 00:11:06,769 to say that they know more about you 1 00:10:54,830 --> 00:11:08,240 than your mother does major cause of the 1 00:11:06,769 --> 00:11:11,059 recently I breakthrough it isn't just 1 00:11:08,240 --> 00:11:13,759 that some dude at a brilliant insight 1 00:11:11,059 --> 00:11:16,279 doll of a son but simply that we have 1 00:11:13,759 --> 00:11:20,059 much bigger data to train them on and 1 00:11:16,279 --> 00:11:22,279 vastly better computers the magic is in 1 00:11:20,059 --> 00:11:24,079 the data it's a ton of data 1 00:11:22,279 --> 00:11:27,169 I mean it's data that's never existed 1 00:11:24,080 --> 00:11:30,259 before we've never had this data before 1 00:11:27,169 --> 00:11:33,099 we've created technologies that allow us 1 00:11:30,259 --> 00:11:35,990 to capture vast amounts of information 1 00:11:33,100 --> 00:11:37,730 if you think of a billion cell phones on 1 00:11:35,990 --> 00:11:40,399 the planet with gyroscopes and 1 00:11:37,730 --> 00:11:42,620 accelerometers and fingerprint readers 1 00:11:40,399 --> 00:11:44,328 couple that with the GPS and the photos 1 00:11:42,620 --> 00:11:46,940 they take and the tweets that you send 1 00:11:44,328 --> 00:11:50,000 we're all giving off huge amounts of 1 00:11:46,940 --> 00:11:51,680 data individually cars that drive is the 1 00:11:50,000 --> 00:11:53,089 cameras on them suck of information 1 00:11:51,679 --> 00:11:54,649 about the world around them the 1 00:11:53,089 --> 00:11:56,959 satellites that are now in orbit the 1 00:11:54,649 --> 00:11:59,149 size of a toaster the infrared about the 1 00:11:56,958 --> 00:12:00,649 vegetation on the planet the boys that 1 00:11:59,149 --> 00:12:03,429 are out in the oceans defeating into 1 00:12:00,649 --> 00:12:03,429 climate models 1 00:12:06,139 --> 00:12:10,850 and the NSA the CIA as they collect 1 00:12:09,230 --> 00:12:14,990 information about the geopolitical 1 00:12:10,850 --> 00:12:17,920 situations the world today is literally 1 00:12:14,990 --> 00:12:17,919 swimming in this data 1 00:12:20,889 --> 00:12:26,870 back in 2012 IBM estimated that an 1 00:12:25,519 --> 00:12:29,929 average human being 1 00:12:26,870 --> 00:12:33,409 leaves 500 megabytes of digital 1 00:12:29,929 --> 00:12:35,959 footprints every day if you wanted to 1 00:12:33,409 --> 00:12:38,179 back up only one day worth of data that 1 00:12:35,960 --> 00:12:41,389 humanity produces and you print it out 1 00:12:38,179 --> 00:12:45,079 on a letter size paper double-sided font 1 00:12:41,389 --> 00:12:47,149 size 12 and you stack it up it would 1 00:12:45,080 --> 00:12:51,399 reach from the surface of the earth to 1 00:12:47,149 --> 00:12:54,860 the Sun four times over this everyday 1 00:12:51,399 --> 00:12:57,919 the data itself is not good or evil it's 1 00:12:54,860 --> 00:13:00,050 how it's used we're relying really on 1 00:12:57,919 --> 00:13:02,569 the goodwill of these people and on the 1 00:13:00,049 --> 00:13:05,000 policies of these companies there is no 1 00:13:02,570 --> 00:13:07,850 legal requirement for how they can and 1 00:13:05,000 --> 00:13:12,379 should use that kind of data that to me 1 00:13:07,850 --> 00:13:14,180 is at the heart of the trust issue right 1 00:13:12,379 --> 00:13:16,028 now there's a giant race for creating 1 00:13:14,179 --> 00:13:18,528 machines that are as smart as humans 1 00:13:16,028 --> 00:13:19,939 Google they're working on what's really 1 00:13:18,528 --> 00:13:21,200 the kind of Manhattan project of 1 00:13:19,940 --> 00:13:23,149 artificial intelligence they've got the 1 00:13:21,200 --> 00:13:25,250 most money they've got the most talent 1 00:13:23,149 --> 00:13:28,940 they're buying up AI companies and 1 00:13:25,250 --> 00:13:30,950 robotics companies people still think of 1 00:13:28,940 --> 00:13:32,870 Gulas a search engine and their email 1 00:13:30,950 --> 00:13:35,930 provider and a lot of other things that 1 00:13:32,870 --> 00:13:40,789 we use on a daily basis but behind that 1 00:13:35,929 --> 00:13:42,620 search box are 10 million servers that 1 00:13:40,789 --> 00:13:45,469 makes Google the most powerful computing 1 00:13:42,620 --> 00:13:48,350 platform in the world Google is now 1 00:13:45,470 --> 00:13:52,269 working on an AI computing platform that 1 00:13:48,350 --> 00:13:52,269 will have a hundred million servers 1 00:13:52,350 --> 00:13:56,769 so when you're interacting with Google 1 00:13:54,879 --> 00:13:58,929 we're just seeing the toenail of 1 00:13:56,769 --> 00:14:01,269 something that is a giant beast in the 1 00:13:58,929 --> 00:14:02,828 making and the truth is I'm not even 1 00:14:01,269 --> 00:14:05,399 sure that Google knows what it's 1 00:14:02,828 --> 00:14:05,399 becoming 1 00:14:11,528 --> 00:14:17,568 if you look inside of what algorithms 1 00:14:14,269 --> 00:14:21,889 are being used at Google it's technology 1 00:14:17,568 --> 00:14:24,679 largely from the 80s so these are models 1 00:14:21,889 --> 00:14:27,649 that you train by showing them a 1 a 2 1 00:14:24,679 --> 00:14:28,969 and a 3 and it learns not what a 1 is or 1 00:14:27,649 --> 00:14:31,519 what it - is it learns what the 1 00:14:28,970 --> 00:14:34,579 difference between a 1 and a 2 is it's 1 00:14:31,519 --> 00:14:35,990 just a computation in the last half 1 00:14:34,578 --> 00:14:37,609 decade where we've made this rapid 1 00:14:35,990 --> 00:14:40,430 progress it has all been in pattern 1 00:14:37,610 --> 00:14:43,938 recognition most of the good old 1 00:14:40,429 --> 00:14:46,870 fashioned AI was when we would tell our 1 00:14:43,938 --> 00:14:49,818 computers how to play a game like chess 1 00:14:46,870 --> 00:14:53,558 from the old paradigm where you just 1 00:14:49,818 --> 00:14:53,558 tell the computer exactly what to do 1 00:14:57,299 --> 00:15:05,779 [Music] 1 00:14:59,620 --> 00:15:07,039 the idea challenge no one at time had 1 00:15:05,779 --> 00:15:09,470 thought that a machine could have the 1 00:15:07,039 --> 00:15:11,389 precision and the confidence and the 1 00:15:09,470 --> 00:15:13,370 speed to play jeopardy well enough 1 00:15:11,389 --> 00:15:17,720 against the best units let's play 1 00:15:13,370 --> 00:15:19,460 jeopardy four-letter word for the iron 1 00:15:17,720 --> 00:15:22,070 fitting on the hoof of a horse 1 00:15:19,460 --> 00:15:24,710 Watson what is issue you are right you 1 00:15:22,070 --> 00:15:28,570 get to pick literary character APB for 1 00:15:24,710 --> 00:15:30,740 800 answered the Daily Double 1 00:15:28,570 --> 00:15:33,620 Watson actually got its knowledge by 1 00:15:30,740 --> 00:15:36,080 reading Wikipedia and 200 million pages 1 00:15:33,620 --> 00:15:38,269 of natural language documents you can't 1 00:15:36,080 --> 00:15:38,830 program every line of how the world 1 00:15:38,269 --> 00:15:41,870 works 1 00:15:38,830 --> 00:15:44,780 mushiya has to learn by reading now we 1 00:15:41,870 --> 00:15:49,299 come to Watson who is Bram Stoker and 1 00:15:44,779 --> 00:15:49,299 the wager hello 1 00:15:50,649 --> 00:15:58,429 4:13 and a Tuesday Watson's trained on 1 00:15:55,309 --> 00:16:00,859 huge amounts of text but it's not like 1 00:15:58,429 --> 00:16:02,269 it understands what it's saying it 1 00:16:00,860 --> 00:16:04,310 doesn't know that water makes things wet 1 00:16:02,269 --> 00:16:05,809 by touching water and by seeing the way 1 00:16:04,309 --> 00:16:08,989 things behave in the world the way you 1 00:16:05,809 --> 00:16:11,719 and I do a lot of language a itay is not 1 00:16:08,990 --> 00:16:14,419 building logical models of how the world 1 00:16:11,720 --> 00:16:17,360 works rather it's looking at how the 1 00:16:14,419 --> 00:16:20,659 words appear in the context of other 1 00:16:17,360 --> 00:16:22,310 words David Ferrucci developed ibm's 1 00:16:20,659 --> 00:16:25,219 watson and somebody asked him just 1 00:16:22,309 --> 00:16:28,789 watson to think and he said does a 1 00:16:25,220 --> 00:16:30,110 submarine swim and what he meant was 1 00:16:28,789 --> 00:16:32,360 when they developed submarines they 1 00:16:30,110 --> 00:16:35,240 borrowed basic principles of swimming 1 00:16:32,360 --> 00:16:36,710 from fish but a submarine swims farther 1 00:16:35,240 --> 00:16:41,360 and faster than fishing in the area huge 1 00:16:36,710 --> 00:16:43,100 payload and out swims fish Watson 1 00:16:41,360 --> 00:16:45,050 winning the game of Jeopardy will go 1 00:16:43,100 --> 00:16:48,019 down in the history of AI as the 1 00:16:45,049 --> 00:16:50,059 significant milestone we tend to be 1 00:16:48,019 --> 00:16:52,669 amazed when the Machine does so well I'm 1 00:16:50,059 --> 00:16:54,289 even more amazed when the computer beast 1 00:16:52,669 --> 00:16:56,809 humans and things are humans and 1 00:16:54,289 --> 00:16:58,589 naturally good at this is how we make 1 00:16:56,809 --> 00:17:00,989 progress 1 00:16:58,590 --> 00:17:03,028 in the early days of the Google brain 1 00:17:00,990 --> 00:17:05,068 project I gave the team a very simple 1 00:17:03,028 --> 00:17:07,439 instruction which was built the biggest 1 00:17:05,068 --> 00:17:10,500 neuro Network possible like a thousand 1 00:17:07,439 --> 00:17:11,759 computers in your net is something very 1 00:17:10,500 --> 00:17:15,509 close to a simulation of how the brain 1 00:17:11,759 --> 00:17:18,420 works it's very probabilistic but with 1 00:17:15,509 --> 00:17:19,799 contextual relevance in your brain you 1 00:17:18,420 --> 00:17:21,539 have long neurons that connect to 1 00:17:19,799 --> 00:17:22,948 thousands of other neurons and you have 1 00:17:21,539 --> 00:17:24,899 these pathways that are formed and 1 00:17:22,949 --> 00:17:27,150 forged based on what then brain needs to 1 00:17:24,900 --> 00:17:29,690 do when a baby tries something and it 1 00:17:27,150 --> 00:17:32,100 succeeds there's a reward and that 1 00:17:29,690 --> 00:17:34,259 pathway that created the success is 1 00:17:32,099 --> 00:17:36,449 strengthened if it fails at something 1 00:17:34,259 --> 00:17:38,490 the pathway is weakened and so over time 1 00:17:36,450 --> 00:17:41,880 the brain becomes honed to be good at 1 00:17:38,490 --> 00:17:43,309 the environment around it really is just 1 00:17:41,880 --> 00:17:45,930 getting machines to learn by themselves 1 00:17:43,309 --> 00:17:47,129 is it called deep learning and deep 1 00:17:45,930 --> 00:17:50,720 learning and neural networks mean 1 00:17:47,130 --> 00:17:53,730 roughly the same thing deep learning is 1 00:17:50,720 --> 00:17:56,339 a totally different approach where the 1 00:17:53,730 --> 00:17:57,660 computer learns more like a toddler by 1 00:17:56,339 --> 00:18:01,379 just getting a lot of data and 1 00:17:57,660 --> 00:18:03,029 eventually figuring stuff out the 1 00:18:01,380 --> 00:18:07,620 computer just gets smarter and smarter 1 00:18:03,029 --> 00:18:09,299 as it has more experiences so imagine if 1 00:18:07,619 --> 00:18:11,489 you will the neural network we're like a 1 00:18:09,299 --> 00:18:13,349 thousand computers and it wakes up not 1 00:18:11,490 --> 00:18:16,640 knowing anything and we made it watch 1 00:18:13,349 --> 00:18:16,639 YouTube for a week 1 00:18:17,640 --> 00:18:26,910 [Music] 1 00:18:29,059 --> 00:18:39,769 [Music] 1 00:18:36,289 --> 00:18:41,869 and so after watching YouTube for a week 1 00:18:39,769 --> 00:18:43,519 what were they learn we had a hypothesis 1 00:18:41,869 --> 00:18:46,819 they learn to detect commonly occurring 1 00:18:43,519 --> 00:18:49,129 objects in videos and so we know the 1 00:18:46,819 --> 00:18:50,359 human faces appear a lot in videos so we 1 00:18:49,130 --> 00:18:52,070 looked and lo and behold there was a 1 00:18:50,359 --> 00:18:58,849 neuron that had learn to detect human 1 00:18:52,069 --> 00:19:02,929 faces know what else appears in videos a 1 00:18:58,849 --> 00:19:04,849 lot so we looked into surprise there was 1 00:19:02,930 --> 00:19:06,269 actually a neuron and that had learn to 1 00:19:04,849 --> 00:19:15,189 detect cats 1 00:19:06,269 --> 00:19:18,230 [Music] 1 00:19:15,190 --> 00:19:24,920 that's the remember CF recognition wow 1 00:19:18,230 --> 00:19:26,029 that's a cat okay cool great it's all 1 00:19:24,920 --> 00:19:26,660 pretty innocuous when you're thinking 1 00:19:26,029 --> 00:19:29,859 about the future 1 00:19:26,660 --> 00:19:32,540 it all seems kind of harmless in benign 1 00:19:29,859 --> 00:19:34,459 but we're making cognitive architectures 1 00:19:32,539 --> 00:19:36,230 that will fly farther and faster than us 1 00:19:34,460 --> 00:19:39,110 and carry a bigger payload and they 1 00:19:36,230 --> 00:19:41,089 won't be warm and fuzzy I think that in 1 00:19:39,109 --> 00:19:43,699 three to five years you will see a 1 00:19:41,089 --> 00:19:47,599 computer system that will be able to 1 00:19:43,700 --> 00:19:50,870 autonomously learn how to understand how 1 00:19:47,599 --> 00:19:53,500 to build understanding not unlike the 1 00:19:50,869 --> 00:19:53,500 way the human mind works 1 00:19:54,470 --> 00:19:59,850 whatever that lunch was it was certainly 1 00:19:56,940 --> 00:20:03,090 delicious simply a sum of Robbie 1 00:19:59,849 --> 00:20:04,859 synthetics is your cook too even 1 00:20:03,089 --> 00:20:09,720 manufactures the raw materials come 1 00:20:04,859 --> 00:20:13,648 round here Robbie I'll show you how this 1 00:20:09,720 --> 00:20:16,919 works one introduces a sample of human 1 00:20:13,648 --> 00:20:18,449 food through this aperture down here 1 00:20:16,919 --> 00:20:20,429 there's a small built-in chemical 1 00:20:18,450 --> 00:20:22,590 laboratory where he analyzed it later he 1 00:20:20,429 --> 00:20:26,059 can reproduce identical molecules in in 1 00:20:22,589 --> 00:20:29,490 any shape or quantity as far as dream 1 00:20:26,058 --> 00:20:32,339 meet Baxter revolutionary new category 1 00:20:29,490 --> 00:20:34,589 of robots with common sense Baxter 1 00:20:32,339 --> 00:20:38,009 Baxter is a really good example of the 1 00:20:34,589 --> 00:20:40,349 kind of competition we face for machines 1 00:20:38,009 --> 00:20:45,150 Baxter can do almost anything we can do 1 00:20:40,349 --> 00:20:47,699 with our hands Baxter costs about what a 1 00:20:45,150 --> 00:20:49,860 minimum-wage worker makes in a year 1 00:20:47,700 --> 00:20:51,420 the Baxter won't be taking the place of 1 00:20:49,859 --> 00:20:52,979 one minimum-wage worker he'll be taking 1 00:20:51,420 --> 00:20:56,700 the place of three because they never 1 00:20:52,980 --> 00:20:57,839 gets hired they never take breaks that's 1 00:20:56,700 --> 00:21:00,569 probably the first thing we're going to 1 00:20:57,839 --> 00:21:02,939 say displacement of jobs they're going 1 00:21:00,569 --> 00:21:06,839 to be done quicker faster cheaper by 1 00:21:02,940 --> 00:21:09,000 machines our ability to even stay 1 00:21:06,839 --> 00:21:12,059 current is so insanely limited compared 1 00:21:09,000 --> 00:21:14,130 to the machines we built for example now 1 00:21:12,059 --> 00:21:15,450 we have this great movement of uber and 1 00:21:14,130 --> 00:21:17,370 lyft are kind of making transportation 1 00:21:15,450 --> 00:21:19,799 cheaper and democratizing transportation 1 00:21:17,369 --> 00:21:20,909 which is great the next step is going to 1 00:21:19,799 --> 00:21:22,859 be that the argument plates by 1 00:21:20,910 --> 00:21:24,029 travellers cars and then all the uber 1 00:21:22,859 --> 00:21:26,359 and lyft drivers had to find something 1 00:21:24,029 --> 00:21:26,359 new to do 1 00:21:26,380 --> 00:21:31,150 there are 4 million professional drivers 1 00:21:29,019 --> 00:21:34,139 in the United States they're unemployed 1 00:21:31,150 --> 00:21:37,900 soon 7 million people to do data entry 1 00:21:34,140 --> 00:21:41,530 those people are going to be jobless 1 00:21:37,900 --> 00:21:43,500 a job isn't just about money right on a 1 00:21:41,529 --> 00:21:46,839 biological level it serves a purpose 1 00:21:43,500 --> 00:21:49,299 becomes a defining thing when the jobs 1 00:21:46,839 --> 00:21:50,740 went away in any given civilization it 1 00:21:49,299 --> 00:21:53,159 doesn't take long until that turns into 1 00:21:50,740 --> 00:21:53,160 violence 1 00:22:00,569 --> 00:22:04,710 we face a giant divide between rich and 1 00:22:02,789 --> 00:22:06,750 poor because that's what automation and 1 00:22:04,710 --> 00:22:10,289 AI will provoke a greater divide between 1 00:22:06,750 --> 00:22:11,910 the haves and have-nots right now it's 1 00:22:10,289 --> 00:22:15,389 working into the middle class into 1 00:22:11,910 --> 00:22:17,490 white-collar jobs IBM's Watson does 1 00:22:15,390 --> 00:22:20,840 business analytics that we used to pay a 1 00:22:17,490 --> 00:22:24,029 business analyst $300 an hour to do 1 00:22:20,839 --> 00:22:25,500 today you go to college to be a doctor 1 00:22:24,029 --> 00:22:27,809 to be an accountant to be a journalist 1 00:22:25,500 --> 00:22:31,559 it's unclear that there's gonna be jobs 1 00:22:27,809 --> 00:22:33,839 there for you if someone's planning for 1 00:22:31,559 --> 00:22:35,879 a 40 year career in radiology just 1 00:22:33,839 --> 00:22:39,889 reading images I think that could be a 1 00:22:35,880 --> 00:22:39,890 challenge to the new drivers of today 1 00:22:56,339 --> 00:23:03,879 but today we live in a robotic case the 1 00:23:00,759 --> 00:23:07,509 da Vinci robot is currently utilized by 1 00:23:03,880 --> 00:23:11,340 variety of surgeons for its accuracy and 1 00:23:07,509 --> 00:23:14,819 its ability to avoid the inevitable 1 00:23:11,339 --> 00:23:23,740 fluctuations of the human hand 1 00:23:14,819 --> 00:23:26,329 [Music] 1 00:23:23,740 --> 00:23:29,380 anybody who watches this feels the 1 00:23:26,329 --> 00:23:29,379 amazingness of it 1 00:23:31,039 --> 00:23:36,869 you look through the scope and you've 1 00:23:33,630 --> 00:23:39,570 seen the claw hand holding that woman's 1 00:23:36,869 --> 00:23:44,119 ovary humanity was resting right there 1 00:23:39,569 --> 00:23:47,000 in the hands of this robot people say 1 00:23:44,119 --> 00:23:52,139 it's the future but it's not the future 1 00:23:47,000 --> 00:23:54,329 it's the present if you think about a 1 00:23:52,140 --> 00:23:56,430 surgical robot there's often not a lot 1 00:23:54,329 --> 00:23:57,629 of intelligence in these things but over 1 00:23:56,430 --> 00:23:59,610 time as we put more and more 1 00:23:57,630 --> 00:24:01,680 intelligence into these systems the 1 00:23:59,609 --> 00:24:04,049 surgical robots can actually learn from 1 00:24:01,680 --> 00:24:05,370 each robot surgery they're tracking the 1 00:24:04,049 --> 00:24:06,629 movements they're understanding what 1 00:24:05,369 --> 00:24:09,209 worked and what didn't work and 1 00:24:06,630 --> 00:24:11,130 eventually the robot for routine 1 00:24:09,210 --> 00:24:13,860 surgeries is going to be able to perform 1 00:24:11,130 --> 00:24:16,440 that entirely by itself or with human 1 00:24:13,859 --> 00:24:18,659 supervision normally I do about a 1 00:24:16,440 --> 00:24:22,710 hundred fifty cases that hysterectomies 1 00:24:18,660 --> 00:24:26,250 they say and now most of them are done 1 00:24:22,710 --> 00:24:31,829 robotically I do maybe one open case a 1 00:24:26,250 --> 00:24:34,970 year so do I feel uncomfortable how to 1 00:24:31,829 --> 00:24:34,970 open bases anymore 1 00:24:35,490 --> 00:24:42,210 it seems that we're feeding it and 1 00:24:37,589 --> 00:24:47,629 creating it but in a way we are slave to 1 00:24:42,210 --> 00:24:47,630 the technology because we can't go back 1 00:24:50,400 --> 00:24:55,960 the machines are taking bigger and 1 00:24:52,569 --> 00:24:58,629 bigger bites out of our skill set and 1 00:24:55,960 --> 00:25:00,400 are never increasing speed and so we've 1 00:24:58,630 --> 00:25:11,770 got to run faster and faster to keep 1 00:25:00,400 --> 00:25:12,280 ahead of the machines are you attracted 1 00:25:11,769 --> 00:25:15,490 to me 1 00:25:12,279 --> 00:25:21,700 what are you attracted to me you give me 1 00:25:15,490 --> 00:25:23,859 indications that you are I do yes this 1 00:25:21,700 --> 00:25:27,580 is the future we're headed into it we 1 00:25:23,859 --> 00:25:29,369 want to design our companions we're 1 00:25:27,579 --> 00:25:32,339 gonna like to see a human face on the I 1 00:25:29,369 --> 00:25:34,509 therefore gaming our emotions will be 1 00:25:32,339 --> 00:25:37,299 depressingly easy 1 00:25:34,509 --> 00:25:39,879 we're not that complicated simple 1 00:25:37,299 --> 00:25:44,139 stimulus response I can make you like me 1 00:25:39,880 --> 00:25:45,550 basically by smiling at you a lot yeah 1 00:25:44,140 --> 00:25:48,300 ours are gonna be fantastic at 1 00:25:45,549 --> 00:25:48,299 manipulating us 1 00:25:49,000 --> 00:25:53,380 [Music] 1 00:25:54,809 --> 00:26:01,269 so you've developed a technology that 1 00:25:57,849 --> 00:26:03,039 can sense what people are feeling right 1 00:26:01,269 --> 00:26:05,079 we've developed technology that can read 1 00:26:03,039 --> 00:26:07,839 your facial expressions and map that to 1 00:26:05,079 --> 00:26:09,849 a number of emotional states fifteen 1 00:26:07,839 --> 00:26:11,500 years ago I had just finished my 1 00:26:09,849 --> 00:26:13,569 undergraduate studies in computer 1 00:26:11,500 --> 00:26:16,720 science and it struck me that I was 1 00:26:13,569 --> 00:26:19,089 spending a lot of time interacting with 1 00:26:16,720 --> 00:26:22,150 my laptops on my devices yet these 1 00:26:19,089 --> 00:26:26,289 devices had absolutely no clue how I was 1 00:26:22,150 --> 00:26:28,540 feeling I started thinking what if this 1 00:26:26,289 --> 00:26:30,730 device could sense that I was stressed 1 00:26:28,539 --> 00:26:38,950 or I was having a bad day what would 1 00:26:30,730 --> 00:26:41,319 that open up for you can I get a hug we 1 00:26:38,950 --> 00:26:43,960 had kids interact with the technology a 1 00:26:41,319 --> 00:26:55,119 lot of it is still in development but it 1 00:26:43,960 --> 00:27:01,299 was just amazing who likes robots my mom 1 00:26:55,119 --> 00:27:04,419 really hard math questions okay we're 1 00:27:01,299 --> 00:27:10,389 scaring people all right so start by 1 00:27:04,420 --> 00:27:12,820 smiling nice brow furrow nice one 1 00:27:10,390 --> 00:27:14,620 eyebrow raised this generation 1 00:27:12,819 --> 00:27:17,619 technology is just surrounding them all 1 00:27:14,619 --> 00:27:19,059 the time it's almost like they expect to 1 00:27:17,619 --> 00:27:21,099 have robots in their homes and they 1 00:27:19,059 --> 00:27:26,589 expect these robots to be socially 1 00:27:21,099 --> 00:27:30,059 intelligent what makes robots smart put 1 00:27:26,589 --> 00:27:33,490 them in like a math or biology class I 1 00:27:30,059 --> 00:27:37,359 think you would have to train all right 1 00:27:33,490 --> 00:27:39,039 let's walk over here so if you smile and 1 00:27:37,359 --> 00:27:41,789 you raise your eyebrows it's gonna run 1 00:27:39,039 --> 00:27:41,789 over to you 1 00:27:43,210 --> 00:27:52,009 but if you look angry it's gonna run 1 00:27:45,679 --> 00:27:56,720 away we're trading computers to read and 1 00:27:52,009 --> 00:27:58,730 recognize emotions the response so far 1 00:27:56,720 --> 00:28:00,288 has been really amazing people are 1 00:27:58,730 --> 00:28:05,808 integrating this into health apps 1 00:28:00,288 --> 00:28:08,558 meditation apps robots cars we're gonna 1 00:28:05,808 --> 00:28:08,558 see how this unfolds 1 00:28:09,730 --> 00:28:15,528 robots can contain AI but the robot is 1 00:28:13,339 --> 00:28:17,418 just a physical instantiation and the 1 00:28:15,528 --> 00:28:19,819 artificial intelligence is the brain and 1 00:28:17,419 --> 00:28:21,710 so brains can exist purely in software 1 00:28:19,819 --> 00:28:24,470 based systems they don't need to have a 1 00:28:21,710 --> 00:28:26,569 physical form robots can exist without 1 00:28:24,470 --> 00:28:29,899 any artificial intelligence we have a 1 00:28:26,569 --> 00:28:32,358 lot of dumb robots out there but a dumb 1 00:28:29,898 --> 00:28:34,459 robot can be a smart robot overnight 1 00:28:32,358 --> 00:28:38,210 given the right software given the right 1 00:28:34,460 --> 00:28:40,009 sensors we can't help but impute motive 1 00:28:38,210 --> 00:28:42,200 into inanimate objects we do it with 1 00:28:40,009 --> 00:28:46,509 machines we'll treat them like children 1 00:28:42,200 --> 00:28:49,929 we'll treat them like surrogates and 1 00:28:46,509 --> 00:28:49,929 we'll pay the price 1 00:28:51,200 --> 00:28:54,298 [Music] 1 00:29:00,630 --> 00:29:10,950 [Music] 1 00:29:08,769 --> 00:29:17,338 you get welcome to that yeah 1 00:29:10,950 --> 00:29:17,338 [Music] 1 00:29:19,048 --> 00:29:24,190 my purpose is to have more human-like 1 00:29:22,000 --> 00:29:27,240 robot which has the human right 1 00:29:24,190 --> 00:29:30,318 intention desire 1 00:29:27,240 --> 00:29:30,318 [Music] 1 00:29:36,309 --> 00:29:44,079 the name of the robot is Erica erica is 1 00:29:41,140 --> 00:29:47,410 the most advanced human-like robot in 1 00:29:44,079 --> 00:29:49,199 the world I think Erica and I can gaze 1 00:29:47,410 --> 00:29:52,460 at your face 1 00:29:49,200 --> 00:29:57,029 [Music] 1 00:29:52,460 --> 00:29:58,490 only to our properties and we predict 1 00:29:57,029 --> 00:30:01,049 with the conversation partners 1 00:29:58,490 --> 00:30:03,750 especially for the elderly and young 1 00:30:01,049 --> 00:30:06,329 children's handicapped people's ideas 1 00:30:03,750 --> 00:30:10,470 when we talk to the robot we don't fear 1 00:30:06,329 --> 00:30:14,689 the social barriers social pressures the 1 00:30:10,470 --> 00:30:18,390 finally everybody except the Android as 1 00:30:14,690 --> 00:30:20,610 just our friend were partners we have 1 00:30:18,390 --> 00:30:23,280 implemented a simple desires now she 1 00:30:20,609 --> 00:30:25,969 wanted to be a well recognized and she 1 00:30:23,279 --> 00:30:25,970 wanted to arrest 1 00:30:27,329 --> 00:30:31,808 [Music] 1 00:30:29,430 --> 00:30:32,620 if a robot could have an intention 1 00:30:31,808 --> 00:30:35,529 there's Oreos 1 00:30:32,619 --> 00:30:46,000 the robot can understand other people's 1 00:30:35,529 --> 00:30:48,190 engagement desires that is tied to 1 00:30:46,000 --> 00:30:49,859 relationships with the people and that 1 00:30:48,190 --> 00:30:53,440 means they like each other 1 00:30:49,859 --> 00:30:56,039 that means well I'm not sure and not to 1 00:30:53,440 --> 00:30:56,039 rub each other 1 00:30:57,589 --> 00:31:00,859 we build about official intelligence and 1 00:30:59,779 --> 00:31:03,470 the very first thing we want to do is 1 00:31:00,859 --> 00:31:06,589 replicate us 1 00:31:03,470 --> 00:31:11,319 I think the key point will come when all 1 00:31:06,589 --> 00:31:16,908 the major senses are replicated sight 1 00:31:11,319 --> 00:31:20,379 touch smell when we replicate our senses 1 00:31:16,909 --> 00:31:20,380 is that when it becomes alive 1 00:31:27,789 --> 00:31:34,579 so many of our machines are being built 1 00:31:30,559 --> 00:31:36,289 to understand us but what happens with 1 00:31:34,579 --> 00:31:38,210 an anthropomorphic creature discovers 1 00:31:36,289 --> 00:31:40,549 that they can adjust their loyalty 1 00:31:38,210 --> 00:31:46,460 adjust their courage adjust their 1 00:31:40,549 --> 00:31:48,379 avarice adjust their cunning the average 1 00:31:46,460 --> 00:31:49,910 person they don't see killer robots 1 00:31:48,380 --> 00:31:52,370 going down the streets they're like what 1 00:31:49,910 --> 00:31:54,350 are you talking about man 1 00:31:52,369 --> 00:31:58,219 we want to make sure we don't have 1 00:31:54,349 --> 00:31:59,599 killer robots going down the street once 1 00:31:58,220 --> 00:32:08,329 they're going down the street it is too 1 00:31:59,599 --> 00:32:11,449 late the thing that worries me right now 1 00:32:08,329 --> 00:32:14,409 that keeps me awake is the development 1 00:32:11,450 --> 00:32:14,410 of autonomous weapons 1 00:32:28,089 --> 00:32:34,669 up to now people have expressed unease 1 00:32:31,130 --> 00:32:42,170 about drones which are remotely piloted 1 00:32:34,670 --> 00:32:44,720 aircraft if you take a drones camera 1 00:32:42,170 --> 00:32:47,990 feed it into the AI system it's a very 1 00:32:44,720 --> 00:32:49,640 easy step from here to fully autonomous 1 00:32:47,990 --> 00:32:53,170 weapons that choose their own targets 1 00:32:49,640 --> 00:32:53,170 release their own missiles 1 00:32:55,269 --> 00:32:58,389 [Music] 1 00:33:02,299 --> 00:33:05,368 [Applause] 1 00:33:12,720 --> 00:33:17,440 the expected lifespan of a human being 1 00:33:15,490 --> 00:33:20,460 and that kind of baffling environment 1 00:33:17,440 --> 00:33:20,460 will be measured in seconds 1 00:33:20,640 --> 00:33:27,340 at one point drones or science fiction 1 00:33:24,009 --> 00:33:31,779 and now they've become the normal thing 1 00:33:27,339 --> 00:33:35,109 and war there's over 10,000 and the US 1 00:33:31,779 --> 00:33:36,759 military inventory alone but they're not 1 00:33:35,109 --> 00:33:40,449 just a u.s. phenomenon there's more than 1 00:33:36,759 --> 00:33:43,000 80 countries that operate them it stands 1 00:33:40,450 --> 00:33:44,200 to reason that people making some of the 1 00:33:43,000 --> 00:33:46,690 most important and difficult decisions 1 00:33:44,200 --> 00:33:50,250 in the world are gonna start to use and 1 00:33:46,690 --> 00:33:50,250 implement artificial intelligence 1 00:33:50,859 --> 00:33:54,709 the Air Force just designed a four 1 00:33:53,180 --> 00:33:58,930 hundred billion dollar jet program to 1 00:33:54,710 --> 00:34:01,579 put pilots in the sky and a $500 AI 1 00:33:58,930 --> 00:34:03,740 designed by a couple of graduate 1 00:34:01,579 --> 00:34:10,699 students as being the best human pilots 1 00:34:03,740 --> 00:34:12,918 with a relatively simple algorithm io I 1 00:34:10,699 --> 00:34:16,460 will have as big an impact on the 1 00:34:12,918 --> 00:34:18,888 military as the combustion engine had at 1 00:34:16,460 --> 00:34:20,690 the turn of the century that would 1 00:34:18,889 --> 00:34:23,809 literally touch everything that the 1 00:34:20,690 --> 00:34:26,450 military does from driverless convoys 1 00:34:23,809 --> 00:34:29,210 delivering logistical supplies to 1 00:34:26,449 --> 00:34:32,329 unmanned drones delivering medical aid 1 00:34:29,210 --> 00:34:33,559 to computational propaganda try and win 1 00:34:32,329 --> 00:34:38,059 the hearts and minds of the population 1 00:34:33,559 --> 00:34:40,279 and so it stands to reason that whoever 1 00:34:38,059 --> 00:34:47,179 has the best day I will probably achieve 1 00:34:40,280 --> 00:34:49,639 dominance on this planet at some point 1 00:34:47,179 --> 00:34:53,659 in the early 21st century all of mankind 1 00:34:49,639 --> 00:34:56,000 was united in celebration we marveled at 1 00:34:53,659 --> 00:34:58,809 our own magnificence as we gave birth to 1 00:34:56,000 --> 00:34:58,809 a 1 00:34:59,829 --> 00:35:03,549 I mean artificial intelligence a 1 00:35:01,420 --> 00:35:07,720 singular consciousness that spawned an 1 00:35:03,550 --> 00:35:11,170 entire race of machines we don't know 1 00:35:07,719 --> 00:35:15,089 who struck first us or them but we know 1 00:35:11,170 --> 00:35:17,139 that it was us that scorched the sky 1 00:35:15,090 --> 00:35:18,970 there's a long history of science 1 00:35:17,139 --> 00:35:22,710 fiction not just predicting the future 1 00:35:18,969 --> 00:35:22,709 but shaping the future 1 00:35:27,130 --> 00:35:33,039 Arthur Conan Doyle riding before World 1 00:35:30,639 --> 00:35:35,889 War one only the danger of how 1 00:35:33,039 --> 00:35:39,730 submarines might be used to carry out 1 00:35:35,889 --> 00:35:42,940 civilian blockades at the time he's 1 00:35:39,730 --> 00:35:44,710 writing this fiction the Royal Navy made 1 00:35:42,940 --> 00:35:47,500 fun of Arthur Conan Doyle for this 1 00:35:44,710 --> 00:35:49,460 absurd idea that submarines could be 1 00:35:47,500 --> 00:35:52,539 useful and war 1 00:35:49,460 --> 00:35:52,539 [Music] 1 00:35:54,039 --> 00:35:58,550 one of the things we've seen in history 1 00:35:55,818 --> 00:36:02,029 is that our attitude towards technology 1 00:35:58,550 --> 00:36:02,660 but also ethics are very context 1 00:36:02,030 --> 00:36:05,510 dependent 1 00:36:02,659 --> 00:36:07,338 for example the submarine nations like 1 00:36:05,510 --> 00:36:09,800 Great Britain and even the I states 1 00:36:07,338 --> 00:36:12,949 found it horrifying to use the submarine 1 00:36:09,800 --> 00:36:15,318 in fact the German used to the submarine 1 00:36:12,949 --> 00:36:18,879 to carry out attacks was the reason why 1 00:36:15,318 --> 00:36:22,400 the United States joined World War one 1 00:36:18,880 --> 00:36:24,559 but move the timeline forward the United 1 00:36:22,400 --> 00:36:27,920 States of America was suddenly and 1 00:36:24,559 --> 00:36:32,119 deliberately attacked by the Empire of 1 00:36:27,920 --> 00:36:34,880 Japan five hours after Pearl Harbor the 1 00:36:32,119 --> 00:36:41,059 order goes out to commit unrestricted 1 00:36:34,880 --> 00:36:42,890 submarine warfare against Japan so 1 00:36:41,059 --> 00:36:46,460 Arthur Conan Doyle turned out to be 1 00:36:42,889 --> 00:36:48,259 right that's the the great old line 1 00:36:46,460 --> 00:36:51,440 about science fiction it's a lie that 1 00:36:48,260 --> 00:36:53,180 tells the truth fellow executives it 1 00:36:51,440 --> 00:36:55,309 gives me great pleasure to introduce you 1 00:36:53,179 --> 00:36:59,049 to the future of law enforcement 1 00:36:55,309 --> 00:36:59,050 edie 209 1 00:37:04,289 --> 00:37:09,029 this isn't just a question of science 1 00:37:06,059 --> 00:37:10,420 fiction this is about what's next about 1 00:37:09,030 --> 00:37:14,000 what's happening right now 1 00:37:10,420 --> 00:37:17,159 [Music] 1 00:37:14,000 --> 00:37:20,730 the role of intelligent systems is 1 00:37:17,159 --> 00:37:27,750 growing very rapidly in warfare everyone 1 00:37:20,730 --> 00:37:29,849 is pushing in the unmanned realm today 1 00:37:27,750 --> 00:37:31,860 Secretary of Defense is very very clear 1 00:37:29,849 --> 00:37:34,650 we will not create fully autonomous 1 00:37:31,860 --> 00:37:36,390 attacking vehicles not everyone is going 1 00:37:34,650 --> 00:37:38,700 to hold themselves to that same set of 1 00:37:36,389 --> 00:37:41,849 values and when China and Russia and 1 00:37:38,699 --> 00:37:45,329 start deploying autonomous vehicles that 1 00:37:41,849 --> 00:37:51,989 can attack and kill what's the move that 1 00:37:45,329 --> 00:37:53,489 we're gonna make you can't say well 1 00:37:51,989 --> 00:37:55,229 we're going to use at homeless weapons 1 00:37:53,489 --> 00:37:58,049 for our our military dominance but no 1 00:37:55,230 --> 00:37:59,849 one else is going to use them if you 1 00:37:58,050 --> 00:38:03,060 make these weapons they're going to be 1 00:37:59,849 --> 00:38:05,750 used to attack human populations in 1 00:38:03,059 --> 00:38:05,750 large numbers 1 00:38:07,110 --> 00:38:10,249 [Music] 1 00:38:13,159 --> 00:38:17,449 tournaments weapons that by their nature 1 00:38:15,650 --> 00:38:19,519 weapons of mass destruction because it 1 00:38:17,449 --> 00:38:23,058 doesn't need a human being to guide it 1 00:38:19,519 --> 00:38:25,900 or carry it you only need one person to 1 00:38:23,059 --> 00:38:29,780 you know write a little program 1 00:38:25,900 --> 00:38:33,588 it's just have Cheers the complexity of 1 00:38:29,780 --> 00:38:37,450 this field it is cool it is important it 1 00:38:33,588 --> 00:38:43,788 is amazing it is also frightening and 1 00:38:37,449 --> 00:38:46,068 it's all about trust it's an open letter 1 00:38:43,789 --> 00:38:47,900 about artificial intelligence signed by 1 00:38:46,068 --> 00:38:50,210 some of the biggest names in science 1 00:38:47,900 --> 00:38:52,548 what do they want ban the use of 1 00:38:50,210 --> 00:38:54,798 autonomous weapons the author stated 1 00:38:52,548 --> 00:38:56,929 quote autonomous weapons have been 1 00:38:54,798 --> 00:38:59,088 described as the third revolution in 1 00:38:56,929 --> 00:39:01,250 warfare thousand artificial intelligence 1 00:38:59,088 --> 00:39:05,000 specialists calling for a global ban on 1 00:39:01,250 --> 00:39:07,039 killer robots this open letter basically 1 00:39:05,000 --> 00:39:08,480 says that we should redefine the goal of 1 00:39:07,039 --> 00:39:11,390 the field of artificial intelligence 1 00:39:08,480 --> 00:39:13,880 away from just creating pure undirected 1 00:39:11,389 --> 00:39:15,739 intelligence towards creating beneficial 1 00:39:13,880 --> 00:39:17,568 intelligence the development of AI is 1 00:39:15,739 --> 00:39:19,368 not going to stop it is going to 1 00:39:17,568 --> 00:39:21,588 continue and get better if the 1 00:39:19,369 --> 00:39:23,420 international community isn't putting 1 00:39:21,588 --> 00:39:25,788 certain controls on this people will 1 00:39:23,420 --> 00:39:27,829 develop things that can do anything the 1 00:39:25,789 --> 00:39:29,960 letter says that we are years not 1 00:39:27,829 --> 00:39:31,910 decades away from these weapons being 1 00:39:29,960 --> 00:39:34,010 deployed so we had six thousands of 1 00:39:31,909 --> 00:39:37,139 countries of that letter including many 1 00:39:34,010 --> 00:39:39,390 of the major figures in the field 1 00:39:37,139 --> 00:39:41,489 I'm getting a lot of visits from 1 00:39:39,389 --> 00:39:43,980 high-ranking officials who wish to 1 00:39:41,489 --> 00:39:46,709 emphasize that American Miller dominance 1 00:39:43,980 --> 00:39:49,170 is very important and autonomous weapons 1 00:39:46,710 --> 00:39:52,528 may be part of the Defense Department's 1 00:39:49,170 --> 00:39:54,869 plan that's very very scary because a 1 00:39:52,528 --> 00:39:56,670 value system of military developers of 1 00:39:54,869 --> 00:40:02,160 Technology is not the same as a value 1 00:39:56,670 --> 00:40:04,349 system of the human race out of the 1 00:40:02,159 --> 00:40:06,389 concerns about the possibility that this 1 00:40:04,349 --> 00:40:07,140 technology might be a threat to human 1 00:40:06,389 --> 00:40:09,268 existence 1 00:40:07,139 --> 00:40:11,068 a number of the technologists have 1 00:40:09,268 --> 00:40:14,159 funded the future of life Institute to 1 00:40:11,068 --> 00:40:16,230 try to grapple with these problems all 1 00:40:14,159 --> 00:40:17,818 of these guys are secretive and so it's 1 00:40:16,230 --> 00:40:23,699 interesting to me to see them and you 1 00:40:17,818 --> 00:40:25,288 know all together everything we have is 1 00:40:23,699 --> 00:40:28,018 a result of our intelligence it's not 1 00:40:25,289 --> 00:40:30,630 the result of our big scary teeth or our 1 00:40:28,018 --> 00:40:32,338 large claws or our enormous muscles it's 1 00:40:30,630 --> 00:40:35,130 because we're actually relatively 1 00:40:32,338 --> 00:40:37,619 intelligent and among my generation 1 00:40:35,130 --> 00:40:39,720 we're all having what we call holy cow 1 00:40:37,619 --> 00:40:42,088 or something holy something else moments 1 00:40:39,719 --> 00:40:44,959 because we see that the technology is 1 00:40:42,088 --> 00:40:47,548 accelerating faster than we expected 1 00:40:44,960 --> 00:40:49,528 remember sitting around the table there 1 00:40:47,548 --> 00:40:51,809 with some of the bests and the smartest 1 00:40:49,528 --> 00:40:54,480 minds in the world and what really 1 00:40:51,809 --> 00:40:57,930 struck me was maybe the human brain is 1 00:40:54,480 --> 00:40:59,400 not able to fully grasp the complexity 1 00:40:57,929 --> 00:41:02,969 of the world that we're confronted with 1 00:40:59,400 --> 00:41:05,009 as it's currently constructed the road 1 00:41:02,969 --> 00:41:07,980 that AI is following heads off a cliff 1 00:41:05,009 --> 00:41:09,539 and we need to change the direction that 1 00:41:07,980 --> 00:41:15,119 we're going so that we don't take the 1 00:41:09,539 --> 00:41:19,170 human race off the cliff Google acquired 1 00:41:15,119 --> 00:41:20,608 deep mind several years ago do you mind 1 00:41:19,170 --> 00:41:24,088 operates as a semi independent 1 00:41:20,608 --> 00:41:26,518 subsidiary of Google the thing that 1 00:41:24,088 --> 00:41:28,679 makes deep mind unique is that deep mind 1 00:41:26,518 --> 00:41:32,008 is absolutely focused on creating 1 00:41:28,679 --> 00:41:34,379 digital super intelligence an AI that is 1 00:41:32,009 --> 00:41:36,778 vastly smarter than any human on earth 1 00:41:34,380 --> 00:41:39,150 and ultimately smarter than all humans 1 00:41:36,778 --> 00:41:41,159 on earth combined this is from the deep 1 00:41:39,150 --> 00:41:44,130 mind reinforcement learning system 1 00:41:41,159 --> 00:41:46,440 basically wakes up like a newborn baby 1 00:41:44,130 --> 00:41:48,960 and is shown the screen of an Atari 1 00:41:46,440 --> 00:41:50,548 video game and then has to learn to play 1 00:41:48,960 --> 00:41:54,369 the video game 1 00:41:50,548 --> 00:41:59,409 it knows nothing about objects about 1 00:41:54,369 --> 00:42:00,640 motion about time it only knows that 1 00:41:59,409 --> 00:42:06,129 there's an image on the screen and 1 00:42:00,639 --> 00:42:08,199 there's a score so if your baby woke up 1 00:42:06,130 --> 00:42:11,289 the day it was born and by later 1 00:42:08,199 --> 00:42:15,009 afternoon was playing 40 different Atari 1 00:42:11,289 --> 00:42:17,109 video games at a superhuman level you 1 00:42:15,009 --> 00:42:20,528 would be terrified you would say my baby 1 00:42:17,108 --> 00:42:24,788 is possessed send it back the deep line 1 00:42:20,528 --> 00:42:26,679 system can win at any game it can 1 00:42:24,789 --> 00:42:30,190 already beat all the original Atari 1 00:42:26,679 --> 00:42:32,078 games it is superhuman it plays the 1 00:42:30,190 --> 00:42:39,068 games at SuperSpeed in less than a 1 00:42:32,079 --> 00:42:40,690 minute deep mine turned to another 1 00:42:39,068 --> 00:42:43,509 challenge and the challenge was the game 1 00:42:40,690 --> 00:42:46,059 of Go which people have generally argued 1 00:42:43,509 --> 00:42:48,509 has been beyond the power of computers 1 00:42:46,059 --> 00:42:51,130 to play with the best human go players 1 00:42:48,509 --> 00:42:55,659 first they challenged the european go 1 00:42:51,130 --> 00:43:00,099 champion then they challenged a korean 1 00:42:55,659 --> 00:43:03,118 go champion and they were able to win in 1 00:43:00,099 --> 00:43:05,410 both times in kind of striking fashion 1 00:43:03,119 --> 00:43:07,539 he really articles in new york times 1 00:43:05,409 --> 00:43:10,348 years ago talking about how go would 1 00:43:07,539 --> 00:43:12,220 take a hundred years for us to saw 1 00:43:10,349 --> 00:43:16,180 people say well you know but that's 1 00:43:12,219 --> 00:43:18,038 still just a board poker is an art poker 1 00:43:16,179 --> 00:43:20,139 involves reading people poker involves 1 00:43:18,039 --> 00:43:22,210 lying bluffing it's not an exact thing 1 00:43:20,139 --> 00:43:24,308 that will never be you know a computer 1 00:43:22,210 --> 00:43:26,650 you can't do that they took the best 1 00:43:24,309 --> 00:43:28,660 poker players in the world and took 1 00:43:26,650 --> 00:43:32,650 seven days for the computer to start 1 00:43:28,659 --> 00:43:34,118 demolishing the dunes so the best poker 1 00:43:32,650 --> 00:43:35,710 player in the world the best go player 1 00:43:34,119 --> 00:43:38,289 in the world and the pattern here is 1 00:43:35,710 --> 00:43:40,690 that AI might take a little while to 1 00:43:38,289 --> 00:43:44,799 wrap its tentacles around a new skill 1 00:43:40,690 --> 00:43:47,338 but when it does when it gets it it is 1 00:43:44,798 --> 00:43:47,338 unstoppable 1 00:43:50,260 --> 00:43:55,510 [Music] 1 00:43:52,329 --> 00:43:58,869 bleep minds AI as administrator level 1 00:43:55,510 --> 00:44:02,080 access to Google's servers to optimize 1 00:43:58,869 --> 00:44:04,929 energy usage at the data centers however 1 00:44:02,079 --> 00:44:06,909 this could be an unintentional Trojan 1 00:44:04,929 --> 00:44:08,559 horse deepmind has to have complete 1 00:44:06,909 --> 00:44:10,420 control of the datacenters so with a 1 00:44:08,559 --> 00:44:12,070 little software update that a I could 1 00:44:10,420 --> 00:44:13,809 take complete control of the whole 1 00:44:12,070 --> 00:44:15,760 Google System which means they can do 1 00:44:13,809 --> 00:44:22,539 anything take a look at all your data 1 00:44:15,760 --> 00:44:24,190 you do anything we're rapidly headed 1 00:44:22,539 --> 00:44:25,690 towards digital super intelligence that 1 00:44:24,190 --> 00:44:28,480 far exceeds any human don't think it's 1 00:44:25,690 --> 00:44:30,190 very obvious the problem is we don't 1 00:44:28,480 --> 00:44:32,079 really suddenly hit human level 1 00:44:30,190 --> 00:44:35,079 intelligence and say okay let's stop 1 00:44:32,079 --> 00:44:36,309 research it's gonna go beyond human 1 00:44:35,079 --> 00:44:37,659 level intelligence into what's called 1 00:44:36,309 --> 00:44:41,829 super intelligence and that's anything 1 00:44:37,659 --> 00:44:43,899 smarter than us AI at the superhuman 1 00:44:41,829 --> 00:44:46,989 level if we succeed without will be by 1 00:44:43,900 --> 00:44:48,940 far the most powerful invention we've 1 00:44:46,989 --> 00:44:50,729 ever made and the last dimension we ever 1 00:44:48,940 --> 00:44:53,130 have to make 1 00:44:50,730 --> 00:44:55,740 and if we create AI that's smarter than 1 00:44:53,130 --> 00:44:57,900 us we have to be open to the possibility 1 00:44:55,739 --> 00:45:02,969 that we might actually lose control to 1 00:44:57,900 --> 00:45:04,829 them let's say you give it some 1 00:45:02,969 --> 00:45:07,409 objective like you're in cancer and then 1 00:45:04,829 --> 00:45:09,329 you discover that the way it chooses to 1 00:45:07,409 --> 00:45:10,739 go about that is actually in conflict 1 00:45:09,329 --> 00:45:12,769 with a lot of other things you care 1 00:45:10,739 --> 00:45:12,769 about 1 00:45:12,858 --> 00:45:17,048 ai doesn't have to be evil to destroy 1 00:45:15,228 --> 00:45:19,808 humanity 1 00:45:17,048 --> 00:45:22,119 if AI has a goal and humanity just 1 00:45:19,809 --> 00:45:23,559 happens to be in the way it will destroy 1 00:45:22,119 --> 00:45:24,818 him at the humanity as a matter of 1 00:45:23,559 --> 00:45:26,890 course without even thinking about it no 1 00:45:24,818 --> 00:45:29,438 hard feelings it's just like if we're 1 00:45:26,889 --> 00:45:31,629 building a road and an ant hill happens 1 00:45:29,438 --> 00:45:34,418 to be in the way we don't hate ants 1 00:45:31,630 --> 00:45:37,019 we're just building a road and so 1 00:45:34,418 --> 00:45:37,018 goodbye anthill 1 00:45:38,469 --> 00:45:43,269 it's tempting to dismiss these concerns 1 00:45:40,989 --> 00:45:46,299 because it's like something that might 1 00:45:43,269 --> 00:45:49,480 happen in a few decades or 100 years so 1 00:45:46,300 --> 00:45:51,280 why worry but if you go back to 1 00:45:49,480 --> 00:45:53,740 September 11th 1933 1 00:45:51,280 --> 00:45:56,200 Ernest Rutherford who is the most well 1 00:45:53,739 --> 00:45:58,598 known nuclear physicist of his time said 1 00:45:56,199 --> 00:45:59,980 that the possibility of ever extracting 1 00:45:58,599 --> 00:46:01,720 useful amounts of energy from the 1 00:45:59,980 --> 00:46:03,240 transmutation of atoms as he called it 1 00:46:01,719 --> 00:46:06,279 was moonshine 1 00:46:03,239 --> 00:46:08,469 the next morning Leo Szilard who is much 1 00:46:06,280 --> 00:46:11,140 younger physicist read this and got 1 00:46:08,469 --> 00:46:13,328 really annoyed and figured out how to 1 00:46:11,139 --> 00:46:14,049 make a nuclear chain reaction just a few 1 00:46:13,329 --> 00:46:17,849 months later 1 00:46:14,050 --> 00:46:17,849 [Music] 1 00:46:20,659 --> 00:46:26,069 we have spent more than two billion 1 00:46:23,489 --> 00:46:29,639 dollars on the greatest scientific 1 00:46:26,070 --> 00:46:31,680 gamble in history so when people say 1 00:46:29,639 --> 00:46:32,940 that oh this is so far off in the future 1 00:46:31,679 --> 00:46:35,190 we don't have to worry about it 1 00:46:32,940 --> 00:46:37,349 they might only be three four 1 00:46:35,190 --> 00:46:38,909 breakthroughs of that magnitude that 1 00:46:37,349 --> 00:46:41,940 will get us from here to super 1 00:46:38,909 --> 00:46:44,969 intelligent machines if it's gonna take 1 00:46:41,940 --> 00:46:47,909 20 years to figure out how the keep AI 1 00:46:44,969 --> 00:46:51,480 beneficial then we should start today 1 00:46:47,909 --> 00:46:53,159 not at the last second when some dudes 1 00:46:51,480 --> 00:46:58,769 drinking Red Bull decide to flip the 1 00:46:53,159 --> 00:47:01,529 switch and test the thing we have five 1 00:46:58,769 --> 00:47:05,219 years I think Digital super intelligence 1 00:47:01,530 --> 00:47:06,830 will happen in my lifetime one hard 1 00:47:05,219 --> 00:47:09,259 percent 1 00:47:06,829 --> 00:47:11,690 what this happens it will be surrounded 1 00:47:09,260 --> 00:47:14,450 by a bunch of people who are really just 1 00:47:11,690 --> 00:47:15,950 excited about the technology they want 1 00:47:14,449 --> 00:47:17,149 to see it succeed but they're not 1 00:47:15,949 --> 00:47:28,579 anticipating that it can get out of 1 00:47:17,150 --> 00:47:31,400 control oh my god I trust my computer so 1 00:47:28,579 --> 00:47:33,409 much that's an amazing question I don't 1 00:47:31,400 --> 00:47:35,869 trust my computer if it's on I take it 1 00:47:33,409 --> 00:47:37,279 off like even it was off I still think 1 00:47:35,869 --> 00:47:38,839 it's all like you know like you really 1 00:47:37,280 --> 00:47:40,850 cannot just like the webcams you don't 1 00:47:38,840 --> 00:47:44,059 know like someone might turn it up don't 1 00:47:40,849 --> 00:47:48,199 know like I don't trust my computer like 1 00:47:44,059 --> 00:47:50,480 in my phone every time they ask me we 1 00:47:48,199 --> 00:47:55,909 send your information to Apple every 1 00:47:50,480 --> 00:47:59,030 time I so trust my phone ok so part of 1 00:47:55,909 --> 00:48:00,440 it is yes I do trust it because it's 1 00:47:59,030 --> 00:48:02,420 really it would be really hard to get 1 00:48:00,440 --> 00:48:12,590 through the day and the way our world is 1 00:48:02,420 --> 00:48:15,909 set up without computers Trust is such a 1 00:48:12,590 --> 00:48:15,910 human experience 1 00:48:21,500 --> 00:48:27,460 I have a patient coming in with 1 00:48:24,289 --> 00:48:30,420 intracranial aneurysm 1 00:48:27,460 --> 00:48:32,650 [Music] 1 00:48:30,420 --> 00:48:34,509 they want to look in my eyes and know 1 00:48:32,650 --> 00:48:38,369 that they can trust this person with 1 00:48:34,509 --> 00:48:41,889 their life I'm not horribly concerned 1 00:48:38,369 --> 00:48:45,479 about anything good part of that is 1 00:48:41,889 --> 00:48:45,478 because I have confidence in you 1 00:48:51,190 --> 00:48:58,210 this procedure we're doing today 20 1 00:48:53,559 --> 00:48:59,650 years ago was essentially impossible we 1 00:48:58,210 --> 00:49:16,329 just didn't have the materials in the 1 00:48:59,650 --> 00:49:24,599 technologies could it be any more 1 00:49:16,329 --> 00:49:28,089 difficult thank God so the coil is 1 00:49:24,599 --> 00:49:31,329 barely in there right now it's just a 1 00:49:28,088 --> 00:49:33,690 feather holding it in it's a nervous 1 00:49:31,329 --> 00:49:33,690 time 1 00:49:36,480 --> 00:49:42,909 we're just in purgatory intellectual 1 00:49:39,340 --> 00:49:45,960 humanistic purgatory an AI might know 1 00:49:42,909 --> 00:49:45,960 exactly what to do here 1 00:49:50,670 --> 00:49:56,050 we got the coil into the aneurysm but it 1 00:49:53,769 --> 00:49:59,259 wasn't in tremendously well that I knew 1 00:49:56,050 --> 00:50:02,530 that it would stay so with a maybe 20% 1 00:49:59,260 --> 00:50:05,890 risk of a very bad situation I elected 1 00:50:02,530 --> 00:50:07,840 to just bring her back because of my 1 00:50:05,889 --> 00:50:09,819 relationship with her and knowing the 1 00:50:07,840 --> 00:50:12,309 difficulties of coming in and having the 1 00:50:09,820 --> 00:50:14,140 procedure I consider things when I 1 00:50:12,309 --> 00:50:17,679 should only consider the safest possible 1 00:50:14,139 --> 00:50:19,239 route to achieve success well I had to 1 00:50:17,679 --> 00:50:22,750 stand there for 10 minutes agonizing 1 00:50:19,239 --> 00:50:25,000 about it the computer feels nothing the 1 00:50:22,750 --> 00:50:25,480 computer just does what it's supposed to 1 00:50:25,000 --> 00:50:26,449 do 1 00:50:25,480 --> 00:50:28,949 better and better 1 00:50:26,449 --> 00:50:38,129 [Music] 1 00:50:28,949 --> 00:50:39,609 I want to be AI in this case but can a I 1 00:50:38,130 --> 00:50:43,530 be compassionate 1 00:50:39,610 --> 00:50:45,690 [Music] 1 00:50:43,530 --> 00:50:51,360 I mean it's everybody's question about 1 00:50:45,690 --> 00:50:54,420 AI we are the sole embodiment of 1 00:50:51,360 --> 00:50:56,579 humanity and it's a stretch for us to 1 00:50:54,420 --> 00:51:01,250 accept that a machine can be 1 00:50:56,579 --> 00:51:01,250 compassionate and loving in that way 1 00:51:01,469 --> 00:51:07,789 [Music] 1 00:51:05,329 --> 00:51:10,380 part of me doesn't believe in magic but 1 00:51:07,789 --> 00:51:12,659 part of me has faith that there is 1 00:51:10,380 --> 00:51:14,640 something beyond the sum of the parts if 1 00:51:12,659 --> 00:51:17,940 there is at least a oneness in our 1 00:51:14,639 --> 00:51:20,509 shared ancestry our shared biology our 1 00:51:17,940 --> 00:51:20,510 shared history 1 00:51:20,920 --> 00:51:28,999 some connection there beyond machine 1 00:51:23,920 --> 00:51:28,999 [Music] 1 00:51:30,869 --> 00:51:34,829 so then you have the other side of that 1 00:51:33,090 --> 00:51:37,250 is does the computer know it's conscious 1 00:51:34,829 --> 00:51:41,250 or can it be conscious or does it care 1 00:51:37,250 --> 00:51:43,969 does it need to be conscious does it 1 00:51:41,250 --> 00:51:43,969 need to be aware 1 00:51:44,369 --> 00:51:55,759 [Music] 1 00:51:52,250 --> 00:51:58,369 I do not think that a robot could ever 1 00:51:55,760 --> 00:51:59,230 be conscious unless they programmed it 1 00:51:58,369 --> 00:52:04,940 that way 1 00:51:59,230 --> 00:52:06,409 conscious no no no I mean I think a 1 00:52:04,940 --> 00:52:08,059 robot could be programmed to be 1 00:52:06,409 --> 00:52:11,629 conscious how they program to do 1 00:52:08,059 --> 00:52:13,670 everything else that's another big part 1 00:52:11,630 --> 00:52:17,920 of our official intelligence is to make 1 00:52:13,670 --> 00:52:17,920 them a conscious and make them feel 1 00:52:22,579 --> 00:52:29,720 back in 2005 we started trying to build 1 00:52:26,119 --> 00:52:29,720 machines with self-awareness 1 00:52:33,099 --> 00:52:39,230 this robot to begin with didn't know 1 00:52:35,750 --> 00:52:45,590 what it was all he knew is that it 1 00:52:39,230 --> 00:52:47,210 needed to do something like walk through 1 00:52:45,590 --> 00:52:51,110 trial and error and figure out how to 1 00:52:47,210 --> 00:52:56,150 walk using its imagination and then it 1 00:52:51,110 --> 00:52:58,610 walked away and then we did something 1 00:52:56,150 --> 00:53:01,269 very cruel we chopped off a leg and 1 00:52:58,610 --> 00:53:01,269 watched what happened 1 00:53:03,360 --> 00:53:10,170 at the beginning it didn't quite know 1 00:53:05,969 --> 00:53:14,579 what had happened but over by the period 1 00:53:10,170 --> 00:53:17,369 of a day and then began to limp and then 1 00:53:14,579 --> 00:53:21,719 a year ago we were training an AI system 1 00:53:17,369 --> 00:53:24,179 for a live demonstration we wanted to 1 00:53:21,719 --> 00:53:25,889 show how we wave all these objects in 1 00:53:24,179 --> 00:53:28,679 front of the camera under the AI can 1 00:53:25,889 --> 00:53:31,139 recognize that the objects and so we're 1 00:53:28,679 --> 00:53:33,029 preparing this demo and we had an aside 1 00:53:31,139 --> 00:53:37,219 screen this ability to watch what 1 00:53:33,030 --> 00:53:39,360 certain neurons were responding to and 1 00:53:37,219 --> 00:53:42,209 suddenly we notice that one of the 1 00:53:39,360 --> 00:53:44,340 neurons was tracking faces it was 1 00:53:42,210 --> 00:53:48,329 tracking our faces as we were moving 1 00:53:44,340 --> 00:53:50,820 around now the spooky thing about this 1 00:53:48,329 --> 00:53:54,630 is that we never trained the system to 1 00:53:50,820 --> 00:53:58,039 recognize human faces and yet somehow 1 00:53:54,630 --> 00:53:58,039 and learn to do that 1 00:53:58,079 --> 00:54:02,500 even though these robots are very simple 1 00:54:00,429 --> 00:54:07,299 we can see there's something else on 1 00:54:02,500 --> 00:54:12,099 there it's not just program so this is 1 00:54:07,300 --> 00:54:17,050 just the beginning I often think about 1 00:54:12,099 --> 00:54:22,480 that beach in Kitty Hawk the 1903 flight 1 00:54:17,050 --> 00:54:24,550 by Orville and Wilbur Wright there's a 1 00:54:22,480 --> 00:54:26,650 kind of a canvas claim it's wood and 1 00:54:24,550 --> 00:54:28,450 iron and it gets off the ground for what 1 00:54:26,650 --> 00:54:31,269 a minute and 20 seconds and he's winning 1 00:54:28,449 --> 00:54:37,469 the day before took him back down again 1 00:54:31,269 --> 00:54:41,829 and it was just around 65 summers or so 1 00:54:37,469 --> 00:54:43,559 after that moment that you have a 747 1 00:54:41,829 --> 00:54:47,139 taking off from JFK 1 00:54:43,559 --> 00:54:47,139 [Music] 1 00:54:50,500 --> 00:54:54,739 with major concern of someone on the 1 00:54:52,639 --> 00:54:56,838 airplane might be whether or not their 1 00:54:54,739 --> 00:54:58,669 salt free diet meal is going to be 1 00:54:56,838 --> 00:55:00,650 coming to them or not with a whole 1 00:54:58,670 --> 00:55:03,409 infrastructure with travel agents and 1 00:55:00,650 --> 00:55:08,900 tower control and it's all casual it's 1 00:55:03,409 --> 00:55:10,909 all part of the world right now as far 1 00:55:08,900 --> 00:55:13,309 as we've come with machines and thinking 1 00:55:10,909 --> 00:55:16,009 solve problems we're a Kittyhawk now 1 00:55:13,309 --> 00:55:18,019 we're in the wind we have our tattered 1 00:55:16,010 --> 00:55:21,119 canvas planes up in the air 1 00:55:18,019 --> 00:55:21,119 [Music] 1 00:55:21,269 --> 00:55:26,610 but what happens in 65 summers or so we 1 00:55:25,050 --> 00:55:32,870 will have machines that are behind you 1 00:55:26,610 --> 00:55:37,220 control should we worry about that I'm 1 00:55:32,869 --> 00:55:37,219 not sure it's going to help 1 00:55:40,568 --> 00:55:47,808 nobody has any idea today what it means 1 00:55:43,880 --> 00:55:50,599 for a robot to be conscious there is no 1 00:55:47,809 --> 00:55:52,039 such thing there are a lot of smart 1 00:55:50,599 --> 00:55:55,150 people and I have a great deal of 1 00:55:52,039 --> 00:55:58,970 respect for them but the truth is 1 00:55:55,150 --> 00:56:00,950 machines are natural Psychopaths fear 1 00:55:58,969 --> 00:56:02,598 came back into the market and down eight 1 00:56:00,949 --> 00:56:04,548 hundred nearly a thousand in a heartbeat 1 00:56:02,599 --> 00:56:05,809 they did is plastic capitulation there 1 00:56:04,548 --> 00:56:08,420 are some people were proposing there was 1 00:56:05,809 --> 00:56:11,150 some kind of fat finger error take the 1 00:56:08,420 --> 00:56:14,480 flash crash of 2010 in a matter of 1 00:56:11,150 --> 00:56:16,910 minutes trillion dollars in value was 1 00:56:14,480 --> 00:56:19,179 lost in stock market the Dow dropped 1 00:56:16,909 --> 00:56:24,469 nearly a thousand points in a half hour 1 00:56:19,179 --> 00:56:27,679 so what went wrong by that point in time 1 00:56:24,469 --> 00:56:30,199 more than 60% of all the trades that 1 00:56:27,679 --> 00:56:35,379 took place on stock exchange we're 1 00:56:30,199 --> 00:56:35,379 actually being initiated by computers 1 00:56:38,000 --> 00:56:42,289 the short story what happened in the 1 00:56:39,739 --> 00:56:44,750 flash crash is that algorithms responded 1 00:56:42,289 --> 00:56:46,609 to algorithms and it compounded upon 1 00:56:44,750 --> 00:56:48,798 itself over and over and over again the 1 00:56:46,608 --> 00:56:51,528 matter of minutes at one point the 1 00:56:48,798 --> 00:56:54,139 market fell as if down a well 1 00:56:51,528 --> 00:56:55,789 there is no regulatory body that can 1 00:56:54,139 --> 00:56:58,548 adapt quickly enough to prevent 1 00:56:55,789 --> 00:57:01,609 potentially disastrous consequences of 1 00:56:58,548 --> 00:57:05,268 AI operating in our financial systems 1 00:57:01,608 --> 00:57:06,889 they are so prime for manipulation let's 1 00:57:05,268 --> 00:57:09,288 talk about the speed with which we are 1 00:57:06,889 --> 00:57:11,088 watching this market be theory that's 1 00:57:09,289 --> 00:57:14,660 the type of AI run amok that scares 1 00:57:11,088 --> 00:57:17,949 people when you give them a goal they 1 00:57:14,659 --> 00:57:20,179 will relentlessly pursue that goal 1 00:57:17,949 --> 00:57:20,869 how many computer programs are there 1 00:57:20,179 --> 00:57:25,789 likeness 1 00:57:20,869 --> 00:57:29,659 nobody knows one of the fascinating 1 00:57:25,789 --> 00:57:32,259 aspects about AI in general is that no 1 00:57:29,659 --> 00:57:35,359 one really understands how it works 1 00:57:32,260 --> 00:57:39,380 even people who create AI don't really 1 00:57:35,360 --> 00:57:41,960 fully understand because it has millions 1 00:57:39,380 --> 00:57:43,700 of elements it becomes completely 1 00:57:41,960 --> 00:57:47,920 impossible for a human being to 1 00:57:43,699 --> 00:57:47,919 understand what's going on 1 00:57:53,119 --> 00:57:58,409 Microsoft had set up this artificial 1 00:57:56,400 --> 00:58:03,300 intelligence called ti' on Twitter which 1 00:57:58,409 --> 00:58:05,869 was a chat bot they started out in the 1 00:58:03,300 --> 00:58:08,220 morning and ty was starting to tweet and 1 00:58:05,869 --> 00:58:12,119 learning from stuff that was being sent 1 00:58:08,219 --> 00:58:14,039 to him from other Twitter people because 1 00:58:12,119 --> 00:58:17,130 some people like trawl attacked him 1 00:58:14,039 --> 00:58:18,840 within 24 hours the Microsoft Bob became 1 00:58:17,130 --> 00:58:22,079 a terrible person 1 00:58:18,840 --> 00:58:23,820 they had to literally pull tie off the 1 00:58:22,079 --> 00:58:29,400 net because he had turned into a monster 1 00:58:23,820 --> 00:58:32,430 a misanthropic races horrible person you 1 00:58:29,400 --> 00:58:35,119 never want to move and nobody had 1 00:58:32,429 --> 00:58:35,119 foreseen this 1 00:58:35,699 --> 00:58:40,739 the whole idea of AI is that we are not 1 00:58:38,309 --> 00:58:44,760 telling it exactly how to achieve a 1 00:58:40,739 --> 00:58:46,519 given outcome or a goal ai develops on 1 00:58:44,760 --> 00:58:49,920 its own 1 00:58:46,519 --> 00:58:51,568 we're worried about super intelligent AI 1 00:58:49,920 --> 00:58:54,990 the master chess player that will 1 00:58:51,568 --> 00:58:58,019 outmaneuver us but hey I won't have to 1 00:58:54,989 --> 00:59:00,929 actually be that smart to have massively 1 00:58:58,019 --> 00:59:02,969 disruptive effects on human civilization 1 00:59:00,929 --> 00:59:04,289 we've seen over the last century it 1 00:59:02,969 --> 00:59:06,629 doesn't necessarily take a genius to 1 00:59:04,289 --> 00:59:09,000 knock history off in a particular 1 00:59:06,630 --> 00:59:10,730 direction and it won't take a genius ai 1 00:59:09,000 --> 00:59:13,349 to do the same thing 1 00:59:10,730 --> 00:59:16,139 bogus election news stories generated 1 00:59:13,349 --> 00:59:19,440 more engagement on Facebook then top 1 00:59:16,139 --> 00:59:21,170 real stories Facebook really is the 1 00:59:19,440 --> 00:59:25,079 elephant in the room 1 00:59:21,170 --> 00:59:29,789 AI running Facebook newsfeed the task 1 00:59:25,079 --> 00:59:32,789 for AI is keeping users engaged but no 1 00:59:29,789 --> 00:59:36,630 one really understands exactly how this 1 00:59:32,789 --> 00:59:38,730 AI is achieving this goal Facebook is 1 00:59:36,630 --> 00:59:41,280 building an elegant mirrored wall around 1 00:59:38,730 --> 00:59:43,139 us a mirror that we can ask who's the 1 00:59:41,280 --> 00:59:46,950 fairest of them all and it will answer 1 00:59:43,139 --> 00:59:49,588 you you time it again you slowly begin 1 00:59:46,949 --> 00:59:53,608 to warp our sense of reality warp our 1 00:59:49,588 --> 00:59:56,699 sense of politics history global events 1 00:59:53,608 --> 00:59:59,730 until determining what's true and what's 1 00:59:56,699 --> 01:00:01,108 not true is virtually impossible 1 00:59:59,730 --> 01:00:04,179 [Music] 1 01:00:01,108 --> 01:00:06,190 the problem is that AI doesn't 1 01:00:04,179 --> 01:00:09,789 understand that hey I just had a mission 1 01:00:06,190 --> 01:00:13,030 maximize user engagement and it achieved 1 01:00:09,789 --> 01:00:16,480 that nearly two billion people spend 1 01:00:13,030 --> 01:00:20,109 nearly 1 hour on average a day basically 1 01:00:16,480 --> 01:00:23,650 interacting with AI that is shaping 1 01:00:20,108 --> 01:00:26,318 their experience even Facebook engineers 1 01:00:23,650 --> 01:00:28,660 they don't like fake news let's very bad 1 01:00:26,318 --> 01:00:30,190 business they want to get rid of fake 1 01:00:28,659 --> 01:00:32,440 news it's just very difficult to do 1 01:00:30,190 --> 01:00:34,420 because how do you recognize news is 1 01:00:32,440 --> 01:00:38,559 fake if you cannot read all of those 1 01:00:34,420 --> 01:00:41,530 news personally there's so much active 1 01:00:38,559 --> 01:00:44,290 misinformation and it's packaged very 1 01:00:41,530 --> 01:00:46,690 well and it looks the same when you see 1 01:00:44,289 --> 01:00:49,000 it on a Facebook page or you turn on 1 01:00:46,690 --> 01:00:51,159 your television it's not terribly 1 01:00:49,000 --> 01:00:54,068 sophisticated but it is terribly 1 01:00:51,159 --> 01:00:56,558 powerful and what it means is that your 1 01:00:54,068 --> 01:00:58,869 view of the world which 20 years ago was 1 01:00:56,559 --> 01:01:01,359 determined if you watch the nightly news 1 01:00:58,869 --> 01:01:03,039 by three different networks the three 1 01:01:01,358 --> 01:01:04,298 anchors who endeavor but try to get it 1 01:01:03,039 --> 01:01:05,679 right you might have had a little bias 1 01:01:04,298 --> 01:01:07,059 one way or the other but largely 1 01:01:05,679 --> 01:01:10,808 speaking we can all agree on an 1 01:01:07,059 --> 01:01:13,599 objective reality that objectivity is 1 01:01:10,809 --> 01:01:15,869 gone and Facebook is completely 1 01:01:13,599 --> 01:01:15,869 annihilated 1 01:01:17,230 --> 01:01:21,699 if most of your understanding of how the 1 01:01:19,579 --> 01:01:24,529 world works is derived from Facebook 1 01:01:21,699 --> 01:01:26,899 facilitated by algorithmic software that 1 01:01:24,530 --> 01:01:29,660 tries to show you the news you want to 1 01:01:26,900 --> 01:01:32,119 see that's a terribly dangerous thing 1 01:01:29,659 --> 01:01:35,750 and the idea that we have not only set 1 01:01:32,119 --> 01:01:38,869 that in motion but allowed bad-faith 1 01:01:35,750 --> 01:01:45,139 actors access to that information this 1 01:01:38,869 --> 01:01:46,579 is a recipe for disaster I think that it 1 01:01:45,139 --> 01:01:49,539 will definitely be lots of bad actors 1 01:01:46,579 --> 01:01:52,549 trying to manipulate the world with AI 1 01:01:49,539 --> 01:01:54,340 2016 was a perfect example of an 1 01:01:52,550 --> 01:01:56,180 election where there was lots of AI 1 01:01:54,340 --> 01:01:58,850 producing lots of fake news and 1 01:01:56,179 --> 01:02:02,449 distributing it for for a purpose for a 1 01:01:58,849 --> 01:02:05,119 result ladies and gentlemen honourable 1 01:02:02,449 --> 01:02:07,279 colleagues it's my privilege to speak to 1 01:02:05,119 --> 01:02:09,559 you today about the power of big data 1 01:02:07,280 --> 01:02:12,410 and psychographics in the electoral 1 01:02:09,559 --> 01:02:15,049 process and specifically to talk about 1 01:02:12,409 --> 01:02:16,940 the work that we contributed to Senator 1 01:02:15,050 --> 01:02:20,360 Cruz's presidential primary campaign 1 01:02:16,940 --> 01:02:22,130 Cambridge analytics emerged quietly as a 1 01:02:20,360 --> 01:02:24,890 company that according to its own height 1 01:02:22,130 --> 01:02:28,010 and has the ability to use this 1 01:02:24,889 --> 01:02:32,690 tremendous amount of data in order to 1 01:02:28,010 --> 01:02:35,420 affect societal change in 2016 they had 1 01:02:32,690 --> 01:02:37,970 three major clients Ted Cruz was one of 1 01:02:35,420 --> 01:02:40,940 them it's easy to forget that only 18 1 01:02:37,969 --> 01:02:42,409 months ago senator Cruz was one of the 1 01:02:40,940 --> 01:02:45,619 less popular candidates seeking 1 01:02:42,409 --> 01:02:48,559 nomination so what was not possible 1 01:02:45,619 --> 01:02:51,170 maybe like 10 or 15 years ago was that 1 01:02:48,559 --> 01:02:53,539 you can send fake news to exactly the 1 01:02:51,170 --> 01:02:55,610 people that you want to send it to and 1 01:02:53,539 --> 01:02:58,489 then you could actually see how he or 1 01:02:55,610 --> 01:03:00,800 she reacts on Facebook and then adjust 1 01:02:58,489 --> 01:03:03,259 that information according to the 1 01:03:00,800 --> 01:03:05,390 feedback that you got and so you can 1 01:03:03,260 --> 01:03:08,360 start developing kind of a real-time 1 01:03:05,389 --> 01:03:10,519 management of a population in this case 1 01:03:08,360 --> 01:03:13,130 we've zoned in on a group we've called 1 01:03:10,519 --> 01:03:15,769 persuasion these are people who are 1 01:03:13,130 --> 01:03:17,599 definitely going to vote to caucus but 1 01:03:15,769 --> 01:03:19,340 they need moving from the center a 1 01:03:17,599 --> 01:03:20,989 little bit more towards the right in 1 01:03:19,340 --> 01:03:23,750 order to support Cruz they need a 1 01:03:20,989 --> 01:03:26,149 persuasion message gun rights I've 1 01:03:23,750 --> 01:03:27,079 selected that narrows the field slightly 1 01:03:26,150 --> 01:03:29,568 more and 1 01:03:27,079 --> 01:03:31,160 we know that we need a message on gun 1 01:03:29,568 --> 01:03:33,528 rights it needs to be a persuasion 1 01:03:31,159 --> 01:03:35,478 message and it needs to be nuanced 1 01:03:33,528 --> 01:03:37,518 according to the certain personality 1 01:03:35,478 --> 01:03:40,368 that we're interested in through social 1 01:03:37,518 --> 01:03:42,468 media there's an infinite amount of 1 01:03:40,369 --> 01:03:44,778 information that you can gather about a 1 01:03:42,469 --> 01:03:47,269 person we have somewhere close to four 1 01:03:44,778 --> 01:03:49,909 or five thousand data points on every 1 01:03:47,268 --> 01:03:53,268 adult in the United States it's about 1 01:03:49,909 --> 01:03:55,848 targeting the individual it's like a 1 01:03:53,268 --> 01:03:57,828 weapon which can be used in the totally 1 01:03:55,849 --> 01:03:59,900 wrong direction that's the problem with 1 01:03:57,829 --> 01:04:02,568 all of this data it's almost as if we 1 01:03:59,900 --> 01:04:05,690 built the bullet before we built the gun 1 01:04:02,568 --> 01:04:08,268 Ted Cruz employed our data our 1 01:04:05,690 --> 01:04:12,259 behavioral insights he started from a 1 01:04:08,268 --> 01:04:17,118 base of less than 5% and had a very slow 1 01:04:12,259 --> 01:04:18,978 and steady but firm rise to above 35% 1 01:04:17,119 --> 01:04:20,959 making him obviously the second most 1 01:04:18,978 --> 01:04:23,568 threatening contender in the race now 1 01:04:20,958 --> 01:04:26,389 clearly the Cruz campaign is over now 1 01:04:23,568 --> 01:04:28,338 but what I can tell you is that of the 1 01:04:26,389 --> 01:04:30,588 two candidates left left in this 1 01:04:28,338 --> 01:04:36,228 election one of them is using these 1 01:04:30,588 --> 01:04:39,259 technologies Donald Trump do solemnly 1 01:04:36,228 --> 01:04:43,778 swear that I will faithfully execute the 1 01:04:39,259 --> 01:04:43,778 office of President of the United States 1 01:04:44,260 --> 01:04:47,449 [Music] 1 01:04:48,958 --> 01:04:54,969 elections are marginal exercise doesn't 1 01:04:52,059 --> 01:05:00,339 take a very sophisticated AI in order to 1 01:04:54,969 --> 01:05:02,438 have a disproportionate impact before 1 01:05:00,338 --> 01:05:06,099 Trump breaks it was another supposed 1 01:05:02,438 --> 01:05:09,788 client well at 20 minutes to 5 we can 1 01:05:06,099 --> 01:05:11,439 now say the decision taken in 1975 by 1 01:05:09,789 --> 01:05:14,919 this country to join the common market 1 01:05:11,438 --> 01:05:18,998 has been reversed by this referendum to 1 01:05:14,918 --> 01:05:21,699 leave the EU Cambridge analytic a 1 01:05:18,998 --> 01:05:24,158 allegedly uses AI to push through two of 1 01:05:21,699 --> 01:05:28,019 the most ground shaking pieces of 1 01:05:24,159 --> 01:05:30,429 political change in the last 50 years 1 01:05:28,018 --> 01:05:32,379 these are epochal events and if we 1 01:05:30,429 --> 01:05:34,659 believe the hype they are connected 1 01:05:32,380 --> 01:05:37,119 directly to a piece of software 1 01:05:34,659 --> 01:05:39,400 essentially created by a professor at 1 01:05:37,119 --> 01:05:41,590 Stanford 1 01:05:39,400 --> 01:05:45,160 [Music] 1 01:05:41,590 --> 01:05:47,380 back in 2013 I described that what 1 01:05:45,159 --> 01:05:49,349 they're doing is possible and warned 1 01:05:47,380 --> 01:05:52,960 against this happening in the future 1 01:05:49,349 --> 01:05:54,549 at the time we have kasinsky was a young 1 01:05:52,960 --> 01:05:57,070 Polish researcher working at the 1 01:05:54,550 --> 01:06:00,789 psychometric Center so what Michael had 1 01:05:57,070 --> 01:06:04,200 done was to gather the largest-ever data 1 01:06:00,789 --> 01:06:07,349 set of how people behaved on Facebook 1 01:06:04,199 --> 01:06:09,789 psychometrics is trying to measure 1 01:06:07,349 --> 01:06:12,460 psychological traits such as personality 1 01:06:09,789 --> 01:06:15,489 intelligence political views and so on 1 01:06:12,460 --> 01:06:18,360 now traditionally those traits were 1 01:06:15,489 --> 01:06:20,439 measured using tests and questioners 1 01:06:18,360 --> 01:06:21,970 personality tests the most benign thing 1 01:06:20,440 --> 01:06:23,050 you could possibly think of something 1 01:06:21,969 --> 01:06:26,469 that doesn't necessarily have a lot of 1 01:06:23,050 --> 01:06:29,019 utility right our idea was that instead 1 01:06:26,469 --> 01:06:30,489 of tests and questioners we could simply 1 01:06:29,019 --> 01:06:32,610 look at the digital footprints of 1 01:06:30,489 --> 01:06:36,869 behaviors that we are all living behind 1 01:06:32,610 --> 01:06:40,120 to understand openness conscientiousness 1 01:06:36,869 --> 01:06:42,579 neuroticism you can easily buy personal 1 01:06:40,119 --> 01:06:44,769 data such as where you live what club 1 01:06:42,579 --> 01:06:47,529 memberships you've joined which gym you 1 01:06:44,769 --> 01:06:50,110 go to there are actually marketplaces 1 01:06:47,530 --> 01:06:51,519 for personal data turns out we can 1 01:06:50,110 --> 01:06:54,490 discover an awful lot about what you're 1 01:06:51,519 --> 01:06:58,239 gonna do based on a very very tiny set 1 01:06:54,489 --> 01:07:01,149 of information we are training deep 1 01:06:58,239 --> 01:07:03,869 learning networks in fair intimate 1 01:07:01,150 --> 01:07:07,980 trades people's political views 1 01:07:03,869 --> 01:07:12,779 personality intelligence sex orientation 1 01:07:07,980 --> 01:07:12,780 just from an image of someone's face 1 01:07:17,530 --> 01:07:22,120 now think about countries which are not 1 01:07:19,480 --> 01:07:24,400 so free and open-minded if you can 1 01:07:22,119 --> 01:07:26,099 reveal people's religious views or 1 01:07:24,400 --> 01:07:29,860 political views or sexual orientation 1 01:07:26,099 --> 01:07:32,909 based on only profile pictures this 1 01:07:29,860 --> 01:07:40,950 could be literally an issue of life and 1 01:07:32,909 --> 01:07:40,949 death I think there's no going back 1 01:07:42,150 --> 01:07:49,019 you know what the Turing test is it's 1 01:07:46,599 --> 01:07:51,190 when a human interacts with a computer 1 01:07:49,019 --> 01:07:54,099 and if the human doesn't know they're 1 01:07:51,190 --> 01:07:58,389 interacting with a computer the test is 1 01:07:54,099 --> 01:07:59,799 passed and over the next few days you're 1 01:07:58,389 --> 01:08:01,869 gonna be the human component in the 1 01:07:59,800 --> 01:08:05,289 Turing test holy 1 01:08:01,869 --> 01:08:07,049 that's right Kayla you got it because if 1 01:08:05,289 --> 01:08:10,809 that test is passed 1 01:08:07,050 --> 01:08:12,960 you are dead center of the greatest 1 01:08:10,809 --> 01:08:15,250 scientific event in the history of man 1 01:08:12,960 --> 01:08:18,850 if you've created a conscious machine 1 01:08:15,250 --> 01:08:21,539 it's not the history of man that's the 1 01:08:18,850 --> 01:08:21,539 history of gods 1 01:08:23,260 --> 01:08:29,509 [Music] 1 01:08:27,288 --> 01:08:31,929 it's almost like technology is a garden 1 01:08:29,509 --> 01:08:31,929 of itself 1 01:08:33,779 --> 01:08:40,089 like the weather we can't impact it we 1 01:08:36,479 --> 01:08:45,639 can't slow it down we can't stop it 1 01:08:40,088 --> 01:08:47,920 we feel powerless if we think of God is 1 01:08:45,640 --> 01:08:49,500 an unlimited amount of intelligence the 1 01:08:47,920 --> 01:08:52,210 closest we can get to that is by 1 01:08:49,500 --> 01:08:54,338 evolving our own intelligence by merging 1 01:08:52,210 --> 01:08:58,619 with the artificial intelligence we're 1 01:08:54,338 --> 01:09:00,489 creating today our computers phones 1 01:08:58,619 --> 01:09:04,180 applications give us superhuman 1 01:09:00,489 --> 01:09:06,929 capability so as the old maxim says if 1 01:09:04,180 --> 01:09:06,930 you can't beat them join them 1 01:09:07,288 --> 01:09:12,809 it's about a human machine partnership I 1 01:09:10,130 --> 01:09:14,849 mean we already see how you know our 1 01:09:12,809 --> 01:09:16,380 phones for example it's act as memory 1 01:09:14,849 --> 01:09:17,969 prosthesis right I don't have to 1 01:09:16,380 --> 01:09:19,219 remember your phone number anymore 1 01:09:17,969 --> 01:09:22,288 because it's on my phone 1 01:09:19,219 --> 01:09:24,088 it's about machines augmenting our human 1 01:09:22,288 --> 01:09:26,939 abilities as opposed to like completely 1 01:09:24,088 --> 01:09:28,318 displacing them if you look at all the 1 01:09:26,939 --> 01:09:30,118 objects that have made the leap from 1 01:09:28,319 --> 01:09:34,739 analog to digital over the last 20 years 1 01:09:30,118 --> 01:09:37,139 it's a lot we're the last analog object 1 01:09:34,738 --> 01:09:38,338 in the digital universe and the problem 1 01:09:37,139 --> 01:09:41,940 with that of course is that the data 1 01:09:38,338 --> 01:09:45,778 input output is very limited it's this 1 01:09:41,939 --> 01:09:47,158 it's these our eyes are pretty good 1 01:09:45,779 --> 01:09:50,969 we're able to take in a lot of visual 1 01:09:47,158 --> 01:09:54,238 information what our information output 1 01:09:50,969 --> 01:09:56,130 is very very very low the reason this is 1 01:09:54,238 --> 01:09:58,678 important if we envision a scenario 1 01:09:56,130 --> 01:10:01,349 where AI is playing a more prominent 1 01:09:58,679 --> 01:10:03,868 role in societies we want good ways to 1 01:10:01,349 --> 01:10:07,250 interact with this technology so that it 1 01:10:03,868 --> 01:10:07,250 ends up augmenting us 1 01:10:09,130 --> 01:10:17,079 I think it's incredibly important to AI 1 01:10:10,840 --> 01:10:19,930 not the other it must be us and I could 1 01:10:17,079 --> 01:10:21,939 be wrong about what I'm saying I'm 1 01:10:19,930 --> 01:10:24,890 certainly open to ideas or anybody can 1 01:10:21,939 --> 01:10:26,629 suggest a path that's better 1 01:10:24,890 --> 01:10:31,030 but I think we're really gonna have to 1 01:10:26,630 --> 01:10:31,029 either merge with a IOP left behind 1 01:10:31,109 --> 01:10:39,049 [Music] 1 01:10:36,618 --> 01:10:40,880 it's hard to kind of think of unplugging 1 01:10:39,050 --> 01:10:43,779 a system that's distributed everywhere 1 01:10:40,880 --> 01:10:47,480 on the planet that's distributed now 1 01:10:43,779 --> 01:10:50,229 across the solar system you can't just 1 01:10:47,479 --> 01:10:50,229 you know shut that off 1 01:10:50,288 --> 01:10:54,279 we've opened Pandora's box we've 1 01:10:52,118 --> 01:10:57,368 Unleashed forces that we can't control 1 01:10:54,279 --> 01:10:59,109 we can't stop we're in the midst of 1 01:10:57,368 --> 01:11:00,279 essentially creating a new life-form on 1 01:10:59,109 --> 01:11:04,188 earth 1 01:11:00,279 --> 01:11:04,188 [Music] 1 01:11:06,130 --> 01:11:10,969 we don't know what happens next we don't 1 01:11:08,929 --> 01:11:13,158 know what shape the intellect of a 1 01:11:10,969 --> 01:11:16,038 machine will be when that intellect is 1 01:11:13,158 --> 01:11:17,599 far beyond human capabilities it's just 1 01:11:16,038 --> 01:11:22,050 not something that's possible 1 01:11:17,600 --> 01:11:24,800 [Music] 1 01:11:22,050 --> 01:11:27,570 [Applause] 1 01:11:24,800 --> 01:11:29,369 the least scary future I can think of is 1 01:11:27,569 --> 01:11:34,380 one where we have at least democratized 1 01:11:29,369 --> 01:11:36,569 AI because if one company or small group 1 01:11:34,380 --> 01:11:38,220 for people managers to develop godlike 1 01:11:36,569 --> 01:11:39,609 digital super intelligence they could 1 01:11:38,220 --> 01:11:40,809 take over the world 1 01:11:39,609 --> 01:11:42,549 [Music] 1 01:11:40,809 --> 01:11:46,239 at least when there's an evil dictator 1 01:11:42,550 --> 01:11:48,340 that human is going to die but for an AI 1 01:11:46,238 --> 01:11:51,399 there would be no death they would look 1 01:11:48,340 --> 01:11:54,489 forever and then you'd have an immortal 1 01:11:51,399 --> 01:11:57,579 dictator from which we can never escape 1 01:11:54,489 --> 01:11:57,579 [Music] 1 01:12:10,930 --> 01:12:14,048 [Music] 1 01:12:19,479 --> 01:12:22,669 [Music] 1 01:12:28,310 --> 01:12:33,919 [Music] 1 01:12:36,270 --> 01:12:48,399 [Music] 1 01:13:12,380 --> 01:13:15,630 [Music] 1 01:13:17,529 --> 01:13:20,099 you 1 01:13:24,590 --> 01:13:27,699 [Music] 1 01:13:30,310 --> 01:13:33,659 [Music] 1 01:13:37,140 --> 01:13:53,560 [Music] 1 01:14:01,899 --> 01:14:05,339 [Music] 1 01:14:12,720 --> 01:14:19,159 [Music] 1 01:14:22,909 --> 01:14:33,170 [Music] 1 01:14:31,949 --> 01:14:52,929 [Applause] 1 01:14:33,170 --> 01:14:52,929 [Music] 1 01:15:00,229 --> 01:15:08,469 [Music] 1 01:15:14,829 --> 01:15:31,640 [Music] 1 01:15:39,329 --> 01:15:44,238 [Music] 1 01:15:57,850 --> 01:16:29,590 [Applause] 1 01:15:58,930 --> 01:16:29,590 [Music] 1 01:16:34,359 --> 01:16:42,478 [Music] 1 01:16:47,000 --> 01:16:52,939 [Music] 1 01:16:59,350 --> 01:17:33,329 [Music] 1 01:17:32,430 --> 01:17:38,050 [Applause] 1 01:17:33,329 --> 01:17:38,050 [Music] 1 01:17:39,579 --> 01:17:45,409 [Applause] 1 01:17:42,189 --> 01:17:45,409 [Music] 154062

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