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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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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] 96621

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