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These are the user uploaded subtitles that are being translated: 1 00:00:00,080 --> 00:00:05,759 warm welcome to the Royal Palace and the 2 00:00:02,600 --> 00:00:09,240 badot library here you will find over 3 00:00:05,759 --> 00:00:12,000 100,000 books a collection that used to 4 00:00:09,240 --> 00:00:15,000 belong to previous kings and queens of 5 00:00:12,000 --> 00:00:17,480 the House of badot offering a glimpse 6 00:00:15,000 --> 00:00:20,480 into their history and 7 00:00:17,480 --> 00:00:23,720 interests however today we're here to 8 00:00:20,480 --> 00:00:26,960 listen to our esteemed Nobel laurates to 9 00:00:23,720 --> 00:00:30,800 their insights their expertise and their 10 00:00:26,960 --> 00:00:34,120 invaluable contributions to science and 11 00:00:30,800 --> 00:00:37,320 economics once again a very warm welcome 12 00:00:34,120 --> 00:00:39,120 to the Royal Palace in this program 13 00:00:37,320 --> 00:00:41,879 we'll be looking at the potential and 14 00:00:39,120 --> 00:00:44,079 pitfalls of artificial intelligence why 15 00:00:41,879 --> 00:00:46,280 some countries are richer than others 16 00:00:44,079 --> 00:00:48,650 and what a worm tells us about the 17 00:00:46,280 --> 00:00:51,829 origins of life 18 00:00:48,650 --> 00:00:51,829 [Applause] 19 00:00:58,950 --> 00:01:08,199 [Music] 20 00:01:08,210 --> 00:01:11,400 [Applause] 21 00:01:08,800 --> 00:01:13,320 [Music] 22 00:01:11,400 --> 00:01:15,960 your Royal Highness thank you for that 23 00:01:13,320 --> 00:01:19,119 very warm welcome to your palace here in 24 00:01:15,960 --> 00:01:20,960 Stockholm and uh Nobel laurates this is 25 00:01:19,119 --> 00:01:23,360 the first time that some of you have 26 00:01:20,960 --> 00:01:25,119 been brought together in discussion on 27 00:01:23,360 --> 00:01:27,040 um television and we're also joined by 28 00:01:25,119 --> 00:01:30,680 some of your family and friends as well 29 00:01:27,040 --> 00:01:32,560 as students from here in Stockholm um 30 00:01:30,680 --> 00:01:34,880 before we start let's just give them a 31 00:01:32,560 --> 00:01:38,200 really big round of applause renewed 32 00:01:34,880 --> 00:01:38,200 congratulations to all of 33 00:01:48,240 --> 00:01:52,960 you I guess you're all getting very used 34 00:01:50,759 --> 00:01:56,680 to the sound of Applause now aren't you 35 00:01:52,960 --> 00:02:00,439 so tell me um how has winning the Nobel 36 00:01:56,680 --> 00:02:01,520 Prize changed your life uh who shall I 37 00:02:00,439 --> 00:02:04,039 start with 38 00:02:01,520 --> 00:02:05,560 Gary well the level of attention is 39 00:02:04,039 --> 00:02:09,239 something that's a 40 00:02:05,560 --> 00:02:11,360 THX what it ever was for other Awards 41 00:02:09,239 --> 00:02:15,280 it's you know the Nobel is a it's a 42 00:02:11,360 --> 00:02:17,160 brand and it's 120 something years of 43 00:02:15,280 --> 00:02:20,840 History to 44 00:02:17,160 --> 00:02:23,000 completely uh mesmerizing Daron one of 45 00:02:20,840 --> 00:02:25,560 the uh economists what about you how's 46 00:02:23,000 --> 00:02:27,760 it changed your life I mean I'm here 47 00:02:25,560 --> 00:02:29,920 well being in Stockholm for one week in 48 00:02:27,760 --> 00:02:32,560 December that's a life-changing event 49 00:02:29,920 --> 00:02:35,519 but I am amazingly grateful and happy 50 00:02:32,560 --> 00:02:37,080 honored and I'll take it as it comes 51 00:02:35,519 --> 00:02:38,920 your diary is going to be super full 52 00:02:37,080 --> 00:02:41,879 from now on you're going to be running 53 00:02:38,920 --> 00:02:44,760 around from lecture to lecture and guest 54 00:02:41,879 --> 00:02:47,720 appearances so Professor Jeffrey Hinton 55 00:02:44,760 --> 00:02:49,920 what about you um yeah it makes an 56 00:02:47,720 --> 00:02:52,800 amazing change I get huge amounts of 57 00:02:49,920 --> 00:02:54,400 email asking me to do things um I 58 00:02:52,800 --> 00:02:57,080 luckily have an assistant who deals with 59 00:02:54,400 --> 00:03:00,319 most of it um I get stopped for selfies 60 00:02:57,080 --> 00:03:02,440 in the street which is um it's very 61 00:03:00,319 --> 00:03:04,200 annoying but if it went away I'd be 62 00:03:02,440 --> 00:03:05,480 disappointed but also you've been 63 00:03:04,200 --> 00:03:07,200 teaching for many years at the 64 00:03:05,480 --> 00:03:09,200 University of Toronto and you said after 65 00:03:07,200 --> 00:03:11,400 you won the Nobel Prize They At Last 66 00:03:09,200 --> 00:03:13,560 gave you an office yes they didn't think 67 00:03:11,400 --> 00:03:17,879 I was worth an office before 68 00:03:13,560 --> 00:03:19,799 that James um I've noticed that people 69 00:03:17,879 --> 00:03:21,480 take what I say much more seriously I've 70 00:03:19,799 --> 00:03:23,319 always proceeded on the assumption that 71 00:03:21,480 --> 00:03:25,799 no one was ever actually listening to 72 00:03:23,319 --> 00:03:28,040 anything I said so now I have to really 73 00:03:25,799 --> 00:03:29,599 choose my words carefully yeah and does 74 00:03:28,040 --> 00:03:31,000 that extend to your family members as 75 00:03:29,599 --> 00:03:34,200 well or do they listen to what you say 76 00:03:31,000 --> 00:03:37,599 now um I'd have to think about that 77 00:03:34,200 --> 00:03:39,280 one David Baker uh well actually a 78 00:03:37,599 --> 00:03:41,560 highlight has really been this week and 79 00:03:39,280 --> 00:03:43,959 having all my my family and and 80 00:03:41,560 --> 00:03:47,080 colleagues here it's been a great 81 00:03:43,959 --> 00:03:50,560 celebration and um yeah I've had to give 82 00:03:47,080 --> 00:03:52,439 up email which has been positive um and 83 00:03:50,560 --> 00:03:55,319 I've learned to completely avoid selfies 84 00:03:52,439 --> 00:03:58,040 so um but uh on the whole it's been very 85 00:03:55,319 --> 00:03:59,959 exciting and you don't travel light do 86 00:03:58,040 --> 00:04:01,680 you if I could put it that way just 87 00:03:59,959 --> 00:04:04,519 remind me how many people have you come 88 00:04:01,680 --> 00:04:06,159 with to Stockholm uh 185 I think that 89 00:04:04,519 --> 00:04:08,280 must be a record I'm going to have to 90 00:04:06,159 --> 00:04:09,680 check but I'm pretty sure that must be a 91 00:04:08,280 --> 00:04:13,239 record well it's quite a party you're 92 00:04:09,680 --> 00:04:14,720 going to have and uh sir Demis hassabis 93 00:04:13,239 --> 00:04:17,040 um well of course it's been an honor of 94 00:04:14,720 --> 00:04:19,479 a lifetime and um to tell you the truth 95 00:04:17,040 --> 00:04:21,440 it hasn't really sunk in yet so uh maybe 96 00:04:19,479 --> 00:04:23,560 I'll do that over the Christmas holidays 97 00:04:21,440 --> 00:04:25,880 um but it's also you know an amazing 98 00:04:23,560 --> 00:04:27,520 platform to talk about your subject more 99 00:04:25,880 --> 00:04:29,800 widely and have to think about that 100 00:04:27,520 --> 00:04:31,639 responsibility in the coming years mhm 101 00:04:29,800 --> 00:04:33,280 okay let's turn now to the awards that 102 00:04:31,639 --> 00:04:35,400 were made this year and let's start with 103 00:04:33,280 --> 00:04:39,759 the physics prize and here's a brief 104 00:04:35,400 --> 00:04:42,800 summary of the research behind that 105 00:04:39,759 --> 00:04:44,960 prize this year's physics prize rewards 106 00:04:42,800 --> 00:04:47,919 research that laid the foundations for 107 00:04:44,960 --> 00:04:51,479 the development of AI enabling machine 108 00:04:47,919 --> 00:04:53,880 learning with artificial neural networks 109 00:04:51,479 --> 00:04:57,360 John hopfield created a structure that 110 00:04:53,880 --> 00:05:00,240 can store and reconstruct information 111 00:04:57,360 --> 00:05:02,479 Jeffrey Hinton built on his ideas and 112 00:05:00,240 --> 00:05:05,360 made it possible to create completely 113 00:05:02,479 --> 00:05:09,479 new content with the help of AI 114 00:05:05,360 --> 00:05:12,039 so-called generative AI this opens up 115 00:05:09,479 --> 00:05:14,320 numerous potential areas of use for 116 00:05:12,039 --> 00:05:16,759 instance by providing techniques for 117 00:05:14,320 --> 00:05:20,120 calculating and predicting the 118 00:05:16,759 --> 00:05:22,520 properties of molecules and materials 119 00:05:20,120 --> 00:05:24,840 their research has also prompted 120 00:05:22,520 --> 00:05:27,680 extensive discussion of the ethics 121 00:05:24,840 --> 00:05:30,919 around how the technology is developed 122 00:05:27,680 --> 00:05:30,919 and used 123 00:05:33,000 --> 00:05:40,360 so Jeffrey Hinton you actually wanted to 124 00:05:36,440 --> 00:05:43,240 find out how the human brain works so 125 00:05:40,360 --> 00:05:45,319 how does it work we still don't know 126 00:05:43,240 --> 00:05:47,840 we've made lots of efforts to figure out 127 00:05:45,319 --> 00:05:49,560 how the brain figures out how to change 128 00:05:47,840 --> 00:05:52,240 the strength of connections between two 129 00:05:49,560 --> 00:05:54,319 neurons we've learned a lot from these 130 00:05:52,240 --> 00:05:56,360 big systems that we've built which is if 131 00:05:54,319 --> 00:05:57,840 you could find any way to know whether 132 00:05:56,360 --> 00:05:59,919 you should increase or decrease the 133 00:05:57,840 --> 00:06:01,800 strength and then you just did did that 134 00:05:59,919 --> 00:06:03,840 for all of the connections all 100 135 00:06:01,800 --> 00:06:05,440 trillion connections and you just kept 136 00:06:03,840 --> 00:06:07,160 doing that with lots of examples 137 00:06:05,440 --> 00:06:09,280 slightly increasing or decreasing the 138 00:06:07,160 --> 00:06:12,360 strength then you would get fantastic 139 00:06:09,280 --> 00:06:14,199 systems like gb4 these big chatbots 140 00:06:12,360 --> 00:06:16,440 learn thousands of times more than any 141 00:06:14,199 --> 00:06:18,319 one person so they can compress all of 142 00:06:16,440 --> 00:06:20,599 human knowledge into only a trillion 143 00:06:18,319 --> 00:06:23,199 connections and we have a 100 trillion 144 00:06:20,599 --> 00:06:26,280 connections and none of us know much but 145 00:06:23,199 --> 00:06:28,360 that's but that's interesting he says 146 00:06:26,280 --> 00:06:32,280 speak for yourself but anyway he does 147 00:06:28,360 --> 00:06:35,199 know a lot actually but compared with 148 00:06:32,280 --> 00:06:37,960 gbt so it make you you make it sound 149 00:06:35,199 --> 00:06:39,919 though as if this is the best computer 150 00:06:37,960 --> 00:06:42,160 and it's never been bettered we don't 151 00:06:39,919 --> 00:06:44,680 quite know how it works and yet you also 152 00:06:42,160 --> 00:06:47,039 say that artificial intelligence 153 00:06:44,680 --> 00:06:50,039 artificial neuron networks could 154 00:06:47,039 --> 00:06:52,639 outsmart humans oh I think we've been 155 00:06:50,039 --> 00:06:54,319 bettered already if you look at gbd4 it 156 00:06:52,639 --> 00:06:55,800 knows much more than any one person it's 157 00:06:54,319 --> 00:06:57,960 like a not very good expert at 158 00:06:55,800 --> 00:06:59,800 everything um so it's got much more 159 00:06:57,960 --> 00:07:02,000 knowledge in far fewer connections and 160 00:06:59,800 --> 00:07:03,680 we've been bettered in that sense do you 161 00:07:02,000 --> 00:07:04,800 agree with that Miss well look I think 162 00:07:03,680 --> 00:07:07,160 so I mean just going back to your 163 00:07:04,800 --> 00:07:08,960 initial question um originally in with 164 00:07:07,160 --> 00:07:10,919 with the with the field of AI there's a 165 00:07:08,960 --> 00:07:12,440 lot of inspiration taken from 166 00:07:10,919 --> 00:07:14,360 architectures of the brain including 167 00:07:12,440 --> 00:07:16,479 neur networks and an algorithm called 168 00:07:14,360 --> 00:07:18,560 reinforcement learning um then we've 169 00:07:16,479 --> 00:07:20,240 gone into a kind of engineering phase 170 00:07:18,560 --> 00:07:22,160 now where we're scaling these systems up 171 00:07:20,240 --> 00:07:24,400 to massive size all of these large 172 00:07:22,160 --> 00:07:26,400 Foundation models or language models uh 173 00:07:24,400 --> 00:07:28,000 and there's many leading models now and 174 00:07:26,400 --> 00:07:29,919 I think we'll we'll end up in the next 175 00:07:28,000 --> 00:07:32,639 phase where we'll start using these AI 176 00:07:29,919 --> 00:07:34,560 models to analyze our own brains and to 177 00:07:32,639 --> 00:07:36,960 help with Neuroscience as one of the 178 00:07:34,560 --> 00:07:38,280 sciences that AI helps with so actually 179 00:07:36,960 --> 00:07:41,319 I think it's going of come sort of Full 180 00:07:38,280 --> 00:07:44,159 Circle neurosciences sort of inspired 181 00:07:41,319 --> 00:07:46,199 modern Ai and then AI will come back and 182 00:07:44,159 --> 00:07:48,240 um help us I think understand what's 183 00:07:46,199 --> 00:07:50,560 special about the brain will machine 184 00:07:48,240 --> 00:07:52,039 intelligence outsmart humans I mean what 185 00:07:50,560 --> 00:07:53,440 what kind of time frame are you talking 186 00:07:52,039 --> 00:07:56,199 about are you saying it's already 187 00:07:53,440 --> 00:07:57,479 happened so in terms of the amount of 188 00:07:56,199 --> 00:07:59,639 knowledge you can have in one system 189 00:07:57,479 --> 00:08:01,720 it's clearly already happened right GB 190 00:07:59,639 --> 00:08:03,479 knows much more than any human yeah and 191 00:08:01,720 --> 00:08:06,080 it it does make stuff up but it still 192 00:08:03,479 --> 00:08:08,759 knows a lot yeah um in terms of the 193 00:08:06,080 --> 00:08:11,560 timing I think all the leading experts I 194 00:08:08,759 --> 00:08:12,960 know people like Demis um they believe 195 00:08:11,560 --> 00:08:14,440 it's going to happen they believe these 196 00:08:12,960 --> 00:08:17,080 machines are going to get smarter than 197 00:08:14,440 --> 00:08:18,680 people at general intelligence and they 198 00:08:17,080 --> 00:08:20,120 just differ in how long they think 199 00:08:18,680 --> 00:08:22,039 that's going to take well we're going to 200 00:08:20,120 --> 00:08:24,280 start being bossed around by machines 201 00:08:22,039 --> 00:08:27,000 and robots is that what your suggestion 202 00:08:24,280 --> 00:08:28,879 well that's the question um can you have 203 00:08:27,000 --> 00:08:30,720 things more intelligent than you and you 204 00:08:28,879 --> 00:08:32,000 still staying control once they're more 205 00:08:30,720 --> 00:08:33,800 intelligent than us will they be the 206 00:08:32,000 --> 00:08:35,719 bosses or will we still be the bosses 207 00:08:33,800 --> 00:08:38,159 and what do you think I think we need to 208 00:08:35,719 --> 00:08:40,000 do a lot of research right now on how we 209 00:08:38,159 --> 00:08:42,399 Remain the bosses you didn't actually 210 00:08:40,000 --> 00:08:44,880 answer that question dearis do you think 211 00:08:42,399 --> 00:08:47,279 that machine intelligence could outsmart 212 00:08:44,880 --> 00:08:49,480 outwits to the extent that actually they 213 00:08:47,279 --> 00:08:51,519 start ruling the roost no well look I 214 00:08:49,480 --> 00:08:53,519 think for now so I disagree with with 215 00:08:51,519 --> 00:08:55,880 with with Jeff on the fact that today's 216 00:08:53,519 --> 00:08:57,519 systems are still not that good they're 217 00:08:55,880 --> 00:08:59,640 impressive they can talk to us and other 218 00:08:57,519 --> 00:09:01,200 things they acquire a lot of knowledge 219 00:08:59,640 --> 00:09:02,560 um but they're pretty weak at a lot of 220 00:09:01,200 --> 00:09:06,399 things they're not very good at planning 221 00:09:02,560 --> 00:09:07,880 yet or reasoning um or uh imagining and 222 00:09:06,399 --> 00:09:09,600 you know creativity those kinds of 223 00:09:07,880 --> 00:09:11,880 things but they they are going to get 224 00:09:09,600 --> 00:09:14,880 better rapidly so it depends now on how 225 00:09:11,880 --> 00:09:17,079 we design those systems and how we um 226 00:09:14,880 --> 00:09:18,440 decide to sort of as a society deploy 227 00:09:17,079 --> 00:09:20,200 those systems and build those systems 228 00:09:18,440 --> 00:09:22,320 all right so we'll look at what we do 229 00:09:20,200 --> 00:09:25,040 about it but gentlemen this is a very 230 00:09:22,320 --> 00:09:27,040 big fundamental question Gary and then 231 00:09:25,040 --> 00:09:30,560 you yeah I think you're overrating 232 00:09:27,040 --> 00:09:34,279 humans in this so we make up a lot of 233 00:09:30,560 --> 00:09:36,760 untruths as well and uh there's so many 234 00:09:34,279 --> 00:09:39,040 examples of false ideas that get 235 00:09:36,760 --> 00:09:41,800 propagated and and it's getting worse of 236 00:09:39,040 --> 00:09:46,120 course with social networks so the 237 00:09:41,800 --> 00:09:49,399 standards for AI to do well it is it's 238 00:09:46,120 --> 00:09:54,839 pretty low you humanity is way 239 00:09:49,399 --> 00:09:56,680 overrated right okay dve humans I I'll 240 00:09:54,839 --> 00:09:58,279 I'll take a contrarian view here um you 241 00:09:56,680 --> 00:10:00,040 know humans since the really the 242 00:09:58,279 --> 00:10:02,079 beginning of civilization have have 243 00:10:00,040 --> 00:10:04,040 created things that are um better at 244 00:10:02,079 --> 00:10:06,760 them than in almost every domain you 245 00:10:04,040 --> 00:10:09,800 know cars can go infinitely faster 246 00:10:06,760 --> 00:10:11,519 planes can fly humans can't um you know 247 00:10:09,800 --> 00:10:14,040 for a long time we've had computers that 248 00:10:11,519 --> 00:10:16,200 can do calculations that humans can't do 249 00:10:14,040 --> 00:10:18,519 um Demis has developed you know programs 250 00:10:16,200 --> 00:10:20,079 that solve go and chess so we're very 251 00:10:18,519 --> 00:10:22,440 comfortable I think with machines being 252 00:10:20,079 --> 00:10:25,920 able to do things that we can't do chat 253 00:10:22,440 --> 00:10:27,440 GP you know gp4 um has much more 254 00:10:25,920 --> 00:10:28,720 knowledge than any human being I think 255 00:10:27,440 --> 00:10:30,519 we just take this kind of thing in 256 00:10:28,720 --> 00:10:32,920 stride I don't think we worry about 257 00:10:30,519 --> 00:10:35,120 losing control so I guess that's the key 258 00:10:32,920 --> 00:10:37,120 issue that we know that computers can do 259 00:10:35,120 --> 00:10:39,440 a lot that we can't but it's question of 260 00:10:37,120 --> 00:10:41,480 control I mean planes fly but it's the 261 00:10:39,440 --> 00:10:44,200 human pilot who's in the cockpit 262 00:10:41,480 --> 00:10:47,639 assisted by technology obviously and we 263 00:10:44,200 --> 00:10:50,200 still drive cars yeah um what about you 264 00:10:47,639 --> 00:10:51,399 two The Economist where do you stand on 265 00:10:50,200 --> 00:10:53,040 this question I'll take the opposite 266 00:10:51,399 --> 00:10:55,560 position to Gary I think humans are 267 00:10:53,040 --> 00:11:00,040 incredibly underrated right 268 00:10:55,560 --> 00:11:03,600 now human adaptability fluidity 269 00:11:00,040 --> 00:11:06,639 creativity but also Community I think 270 00:11:03,600 --> 00:11:09,000 humans are just amazing social animals 271 00:11:06,639 --> 00:11:11,760 we learn as collectives and as 272 00:11:09,000 --> 00:11:14,800 collectives we are able to do a huge 273 00:11:11,760 --> 00:11:17,600 number of things in very quick 274 00:11:14,800 --> 00:11:20,160 succession so I would worry about those 275 00:11:17,600 --> 00:11:24,000 people controlling AI before AI itself 276 00:11:20,160 --> 00:11:26,560 turning on us humankind's greatest enemy 277 00:11:24,000 --> 00:11:29,920 is humankind the sort of do evils that 278 00:11:26,560 --> 00:11:33,800 we see in Popular Science fic who think 279 00:11:29,920 --> 00:11:36,519 they're doing good I wouldn't put those 280 00:11:33,800 --> 00:11:38,120 past doing huge damage yeah I would 281 00:11:36,519 --> 00:11:39,720 agree I mean as the tools get more 282 00:11:38,120 --> 00:11:41,519 powerful I think the worry is not the 283 00:11:39,720 --> 00:11:44,680 machines themselves but people using the 284 00:11:41,519 --> 00:11:46,720 tools misinformation autonomous military 285 00:11:44,680 --> 00:11:49,000 weapons all kinds of things humans have 286 00:11:46,720 --> 00:11:51,000 a great track record of inventing things 287 00:11:49,000 --> 00:11:52,800 you know that jeopardize the human race 288 00:11:51,000 --> 00:11:55,800 such as nuclear weapons I mean just 289 00:11:52,800 --> 00:11:58,120 think about how close we've been to 290 00:11:55,800 --> 00:11:59,800 obliterating the planet with the Cuba 291 00:11:58,120 --> 00:12:02,000 Cuban Missile Crisis 292 00:11:59,800 --> 00:12:03,920 and you know so so we've done it already 293 00:12:02,000 --> 00:12:06,160 we can do it again in a different form 294 00:12:03,920 --> 00:12:07,839 or you know with a diff so so so I guess 295 00:12:06,160 --> 00:12:09,639 I would I would like to ask Demis you 296 00:12:07,839 --> 00:12:11,279 know I I I take the point of view 297 00:12:09,639 --> 00:12:13,040 everyone's saying yes we need to 298 00:12:11,279 --> 00:12:14,920 regulate we need to but who has the 299 00:12:13,040 --> 00:12:17,440 incentive to do that I don't you know 300 00:12:14,920 --> 00:12:19,079 like it's one thing to say that but but 301 00:12:17,440 --> 00:12:20,920 I I suspect the politicians and the 302 00:12:19,079 --> 00:12:22,519 governments they're just playing catchup 303 00:12:20,920 --> 00:12:24,480 that you know the thing is moving faster 304 00:12:22,519 --> 00:12:26,040 than they can get their hands on and who 305 00:12:24,480 --> 00:12:27,920 in the private sector they just want to 306 00:12:26,040 --> 00:12:30,199 make money and get this stuff out there 307 00:12:27,920 --> 00:12:31,959 and so where where are the incentives to 308 00:12:30,199 --> 00:12:34,399 actually do something about that yeah 309 00:12:31,959 --> 00:12:36,160 well look I mean there's obviously the 310 00:12:34,399 --> 00:12:37,800 reason that many of us are working on AI 311 00:12:36,160 --> 00:12:39,680 is because we want to bring to bear all 312 00:12:37,800 --> 00:12:42,279 of the incredible benefits that can 313 00:12:39,680 --> 00:12:44,199 happen with AI from in medicine but also 314 00:12:42,279 --> 00:12:45,519 productivity and so on but I agree with 315 00:12:44,199 --> 00:12:48,440 you there is a going to be a kind of 316 00:12:45,519 --> 00:12:49,720 coordination problem where um I think 317 00:12:48,440 --> 00:12:51,199 there has to be some form of 318 00:12:49,720 --> 00:12:53,360 international cooperation on these 319 00:12:51,199 --> 00:12:55,399 issues I think we've got a few years to 320 00:12:53,360 --> 00:12:58,600 get our act together on that and I think 321 00:12:55,399 --> 00:13:00,839 leading researchers and leading um labs 322 00:12:58,600 --> 00:13:02,519 in industry and Academia need to come 323 00:13:00,839 --> 00:13:04,560 together to kind of demand that sort of 324 00:13:02,519 --> 00:13:06,920 cooperation as we get closer to 325 00:13:04,560 --> 00:13:08,920 artificial general intelligence um and 326 00:13:06,920 --> 00:13:11,199 have more information about what that 327 00:13:08,920 --> 00:13:14,199 might look like but I'm I'm I'm a big 328 00:13:11,199 --> 00:13:15,880 believer in human Ingenuity and um as 329 00:13:14,199 --> 00:13:18,040 David says you know we're unbelievably 330 00:13:15,880 --> 00:13:19,560 adaptive as a species and you know look 331 00:13:18,040 --> 00:13:21,279 at our modern technology we already use 332 00:13:19,560 --> 00:13:22,760 today that we sort of seamlessly the 333 00:13:21,279 --> 00:13:25,040 younger generation just seamlessly 334 00:13:22,760 --> 00:13:26,440 adapts to and takes as a given and I 335 00:13:25,040 --> 00:13:29,680 think that's also happened with these 336 00:13:26,440 --> 00:13:31,279 chat Bots which you know 25 years ago we 337 00:13:29,680 --> 00:13:33,040 would have been amazed those of us in 338 00:13:31,279 --> 00:13:34,760 this in the area of AI if you were to 339 00:13:33,040 --> 00:13:37,720 transport the Technologies back we have 340 00:13:34,760 --> 00:13:39,519 today back then um and yet we've all um 341 00:13:37,720 --> 00:13:41,800 Society seems to have sort of seamlessly 342 00:13:39,519 --> 00:13:43,560 adapted to that as well Jeffrey Hinton 343 00:13:41,800 --> 00:13:45,399 do you see that happening you've raised 344 00:13:43,560 --> 00:13:48,560 the alarm Bells about humans becoming 345 00:13:45,399 --> 00:13:50,040 subservient in a way to to machines um 346 00:13:48,560 --> 00:13:52,160 do you think that there's enough of a 347 00:13:50,040 --> 00:13:56,199 debate at an international level do we 348 00:13:52,160 --> 00:13:58,040 need more Ethics in science to debate 349 00:13:56,199 --> 00:14:00,759 these kind of issues do you see that 350 00:13:58,040 --> 00:14:03,160 happening so to distinguish two kinds of 351 00:14:00,759 --> 00:14:04,720 risks from AI one is relatively 352 00:14:03,160 --> 00:14:08,199 shortterm and that's to do with Bad 353 00:14:04,720 --> 00:14:09,759 actors and that's much more urgent um 354 00:14:08,199 --> 00:14:11,560 that were that's going to be obvious 355 00:14:09,759 --> 00:14:12,800 with lethal autonomous weapons which all 356 00:14:11,560 --> 00:14:15,240 the big defense departments are 357 00:14:12,800 --> 00:14:17,440 developing and they have no intention of 358 00:14:15,240 --> 00:14:20,240 not doing it the European regulations on 359 00:14:17,440 --> 00:14:22,680 AI say none of these regulations apply 360 00:14:20,240 --> 00:14:25,000 to military uses of AI so they clearly 361 00:14:22,680 --> 00:14:26,560 intend to go ahead with all that and 362 00:14:25,000 --> 00:14:30,120 there's many other short-term risks like 363 00:14:26,560 --> 00:14:32,639 cyber crime um generating bad path 364 00:14:30,120 --> 00:14:34,680 fake videos surveillance all of those 365 00:14:32,639 --> 00:14:36,720 short-term risks are very serious and we 366 00:14:34,680 --> 00:14:37,839 need to take them seriously and it's 367 00:14:36,720 --> 00:14:39,720 going to be very hard to get 368 00:14:37,839 --> 00:14:41,639 collaboration on those then the 369 00:14:39,720 --> 00:14:43,320 long-term risk that these things will 370 00:14:41,639 --> 00:14:45,440 get more intelligent than us and they'll 371 00:14:43,320 --> 00:14:47,120 be agents they'll act in the world and 372 00:14:45,440 --> 00:14:48,920 they'll decide that they can achieve 373 00:14:47,120 --> 00:14:50,160 their goals better which we gave them 374 00:14:48,920 --> 00:14:51,480 the goals and they can achieve them 375 00:14:50,160 --> 00:14:55,079 better if they just brush us aside and 376 00:14:51,480 --> 00:14:56,959 get on with it um that particular risk 377 00:14:55,079 --> 00:14:59,040 the existential threat is a place where 378 00:14:56,959 --> 00:15:00,839 people will cooperate and that's because 379 00:14:59,040 --> 00:15:03,800 because we're all in the same boat 380 00:15:00,839 --> 00:15:06,079 nobody wants these AIS to take over from 381 00:15:03,800 --> 00:15:08,279 people and so the Chinese Communist 382 00:15:06,079 --> 00:15:09,639 party doesn't want AI to be in control 383 00:15:08,279 --> 00:15:11,440 it wants the Chinese Communist party to 384 00:15:09,639 --> 00:15:14,680 be in control you know for somebody 385 00:15:11,440 --> 00:15:16,680 who's described as the Godfather of AI 386 00:15:14,680 --> 00:15:19,360 you sound quite a bit down on it in so 387 00:15:16,680 --> 00:15:21,519 many ways well it's potentially very 388 00:15:19,360 --> 00:15:23,639 dangerous it's potentially very good and 389 00:15:21,519 --> 00:15:25,399 potentially very dangerous and I you 390 00:15:23,639 --> 00:15:28,120 know I think we should be making a huge 391 00:15:25,399 --> 00:15:30,399 effort now into making sure we can get 392 00:15:28,120 --> 00:15:32,759 the good aspects of of it without the 393 00:15:30,399 --> 00:15:35,680 bad possibilities and it's not going to 394 00:15:32,759 --> 00:15:37,319 happen automatically like he says well 395 00:15:35,680 --> 00:15:38,839 we've got some students in the audience 396 00:15:37,319 --> 00:15:41,199 here and I know that some of them want 397 00:15:38,839 --> 00:15:44,319 to pose a question to you Lau prashan 398 00:15:41,199 --> 00:15:47,319 yadava from the kth AI Society your 399 00:15:44,319 --> 00:15:50,199 question please I'd like to know in what 400 00:15:47,319 --> 00:15:52,440 ways AI can be put to use uh in bringing 401 00:15:50,199 --> 00:15:54,519 truly democratic values and bringing 402 00:15:52,440 --> 00:15:58,639 economic equalities to the 403 00:15:54,519 --> 00:16:01,399 world so in what way can AI promote 404 00:15:58,639 --> 00:16:04,680 democ Ry and equality in the world who's 405 00:16:01,399 --> 00:16:04,680 going to answer that 406 00:16:04,800 --> 00:16:10,240 one I can start off I mean I I think um 407 00:16:08,880 --> 00:16:12,399 as we've discussed actually for most of 408 00:16:10,240 --> 00:16:16,240 the conversation you I think powerful 409 00:16:12,399 --> 00:16:18,319 Technologies in of themselves are um 410 00:16:16,240 --> 00:16:20,959 kind of like neutral they could go good 411 00:16:18,319 --> 00:16:22,959 or bad depending on what we as society 412 00:16:20,959 --> 00:16:24,720 decide to do with them and I think AI is 413 00:16:22,959 --> 00:16:26,160 just the latest example of that in that 414 00:16:24,720 --> 00:16:28,240 case maybe it's going to be the most 415 00:16:26,160 --> 00:16:30,199 powerful thing and most important that 416 00:16:28,240 --> 00:16:31,680 we get right but it's also on the 417 00:16:30,199 --> 00:16:33,040 optimistic end I think it's one of the 418 00:16:31,680 --> 00:16:34,800 challenges it's the only challenge I can 419 00:16:33,040 --> 00:16:37,480 think of that could be useful to address 420 00:16:34,800 --> 00:16:40,560 the other challenges if we get it right 421 00:16:37,480 --> 00:16:41,759 so um so that's the key um I don't know 422 00:16:40,560 --> 00:16:43,040 you know democracy and other things 423 00:16:41,759 --> 00:16:44,680 that's better out scope maybe it's for 424 00:16:43,040 --> 00:16:46,759 the economist to talk about well I'll 425 00:16:44,680 --> 00:16:48,839 I'll just say I think AI is an 426 00:16:46,759 --> 00:16:53,120 informational tool and it would be most 427 00:16:48,839 --> 00:16:56,319 useful and most uh enriching for us in 428 00:16:53,120 --> 00:16:58,560 every respect if it's useful reliable 429 00:16:56,319 --> 00:17:00,399 and enabling information for everybody 430 00:16:58,560 --> 00:17:02,480 not just for somebody sitting at top to 431 00:17:00,399 --> 00:17:04,199 manipulate others but enabling for 432 00:17:02,480 --> 00:17:06,079 Citizens for example enabling for 433 00:17:04,199 --> 00:17:08,679 workers of different skills to do their 434 00:17:06,079 --> 00:17:11,240 tasks all of those are aspects of 435 00:17:08,679 --> 00:17:13,520 democratization but we still have a long 436 00:17:11,240 --> 00:17:15,679 way to go for that sort of tool to be 437 00:17:13,520 --> 00:17:17,720 available in a widespread way and not be 438 00:17:15,679 --> 00:17:20,400 manipulable let's go for another 439 00:17:17,720 --> 00:17:23,199 question now from our audience Al karini 440 00:17:20,400 --> 00:17:25,880 papasu from the Stockholm School of 441 00:17:23,199 --> 00:17:28,120 Economics your question please uh hello 442 00:17:25,880 --> 00:17:31,440 thank you uh my question regards how do 443 00:17:28,120 --> 00:17:34,200 you think philosophy and science coexist 444 00:17:31,440 --> 00:17:36,640 um we have a very deep need for more 445 00:17:34,200 --> 00:17:38,240 philosophy and great endon perhaps 446 00:17:36,640 --> 00:17:40,480 There's an opportunity for some new 447 00:17:38,240 --> 00:17:42,679 great philosophers to appear um to help 448 00:17:40,480 --> 00:17:45,120 us through the next phase of 449 00:17:42,679 --> 00:17:46,960 technological development um in my view 450 00:17:45,120 --> 00:17:49,880 that that is going to require depending 451 00:17:46,960 --> 00:17:51,720 on your definition of philosophy um some 452 00:17:49,880 --> 00:17:53,720 uh uh deep thinking and and wider 453 00:17:51,720 --> 00:17:55,919 Thinking Beyond the technology itself 454 00:17:53,720 --> 00:17:59,600 yeah absolutely I think actually one of 455 00:17:55,919 --> 00:18:03,039 the things with the advances in AI 456 00:17:59,600 --> 00:18:04,720 we will need to understand much better 457 00:18:03,039 --> 00:18:07,080 what makes us conscious what makes us 458 00:18:04,720 --> 00:18:11,159 human there might be some stumbling 459 00:18:07,080 --> 00:18:13,600 blocks that will make us delve deeper 460 00:18:11,159 --> 00:18:15,919 into some of these questions but even if 461 00:18:13,600 --> 00:18:19,440 advances in AI are very fast we will 462 00:18:15,919 --> 00:18:21,559 need to question our own existence and 463 00:18:19,440 --> 00:18:24,080 what makes that more meaningful 464 00:18:21,559 --> 00:18:25,679 certainly we need ethics but the kind of 465 00:18:24,080 --> 00:18:27,760 philosophy we don't need I think is 466 00:18:25,679 --> 00:18:30,120 philosophers talking about Consciousness 467 00:18:27,760 --> 00:18:31,720 and sentience and subjective experience 468 00:18:30,120 --> 00:18:34,200 I think understanding those is a 469 00:18:31,720 --> 00:18:36,679 scientific problem and we'll be better 470 00:18:34,200 --> 00:18:36,679 off without 471 00:18:36,799 --> 00:18:41,840 philosophers anybody else on this no all 472 00:18:39,679 --> 00:18:44,400 right thank you very much but let's turn 473 00:18:41,840 --> 00:18:47,240 now to um some of the work that has 474 00:18:44,400 --> 00:18:49,440 contributed to the award for the 475 00:18:47,240 --> 00:18:52,240 chemistry prize this year for Demis 476 00:18:49,440 --> 00:18:54,200 cabis David Baker along with John jumper 477 00:18:52,240 --> 00:18:57,960 and let's just get a brief idea of the 478 00:18:54,200 --> 00:19:00,039 research that led to the chemistry Nobel 479 00:18:57,960 --> 00:19:02,559 Prize award 480 00:19:00,039 --> 00:19:04,919 the ability to figure out quickly what 481 00:19:02,559 --> 00:19:07,600 proteins look like and to create 482 00:19:04,919 --> 00:19:09,919 proteins of your own has fundamentally 483 00:19:07,600 --> 00:19:13,640 changed the development of chemistry 484 00:19:09,919 --> 00:19:17,320 biology and medical science by creating 485 00:19:13,640 --> 00:19:20,280 the AI program Alpha fold 2 this year's 486 00:19:17,320 --> 00:19:22,880 chemistry laurates Demis hassabis and 487 00:19:20,280 --> 00:19:25,600 John jumper have made it possible to 488 00:19:22,880 --> 00:19:27,919 calculate the shape of proteins and 489 00:19:25,600 --> 00:19:29,880 thereby understand how the building 490 00:19:27,919 --> 00:19:32,320 block of life Life 491 00:19:29,880 --> 00:19:34,640 Works the second half of this year's 492 00:19:32,320 --> 00:19:37,200 award goes to David Baker for what's 493 00:19:34,640 --> 00:19:40,480 been described as the almost impossible 494 00:19:37,200 --> 00:19:43,640 feat of building entirely new kinds of 495 00:19:40,480 --> 00:19:47,520 proteins useful not least for producing 496 00:19:43,640 --> 00:19:50,760 what could block the SARS Cove 2 virus 497 00:19:47,520 --> 00:19:52,799 making new proteins can simply open up 498 00:19:50,760 --> 00:19:55,120 whole new 499 00:19:52,799 --> 00:19:57,720 worlds so let's start with you David 500 00:19:55,120 --> 00:19:59,159 Baker you've been applauded for creating 501 00:19:57,720 --> 00:20:00,679 these new 502 00:19:59,159 --> 00:20:02,559 proteins and actually you didn't even 503 00:20:00,679 --> 00:20:04,360 want to become a scientist in the first 504 00:20:02,559 --> 00:20:06,600 place so it's quite amazing that You' 505 00:20:04,360 --> 00:20:09,080 now got this Nobel Prize but just tell 506 00:20:06,600 --> 00:20:12,240 us what kind of um applications 507 00:20:09,080 --> 00:20:14,280 implications do you think your work has 508 00:20:12,240 --> 00:20:16,320 uh led to or could lead to yeah I think 509 00:20:14,280 --> 00:20:18,480 following up on our previous discussion 510 00:20:16,320 --> 00:20:21,440 um I think I can really talk about the 511 00:20:18,480 --> 00:20:24,720 the really real power of AI to do good 512 00:20:21,440 --> 00:20:26,280 so um some of the proteins in nature uh 513 00:20:24,720 --> 00:20:28,280 solve all the problems that came up 514 00:20:26,280 --> 00:20:29,840 during Evolution and we face all kinds 515 00:20:28,280 --> 00:20:31,280 of new problems in the world today you 516 00:20:29,840 --> 00:20:33,320 know we live longer so neur 517 00:20:31,280 --> 00:20:35,360 neurodegenerative diseases are important 518 00:20:33,320 --> 00:20:37,880 we heating up and pling the planet and 519 00:20:35,360 --> 00:20:41,080 these are really existential problems 520 00:20:37,880 --> 00:20:43,159 and uh now um you know maybe with 521 00:20:41,080 --> 00:20:44,960 Evolution another 100 million years 522 00:20:43,159 --> 00:20:46,799 proteins would evolve that would help 523 00:20:44,960 --> 00:20:49,120 address these but with protein design we 524 00:20:46,799 --> 00:20:51,480 can now design proteins to uh try and 525 00:20:49,120 --> 00:20:53,240 deal with these today and so we're 526 00:20:51,480 --> 00:20:55,480 designing proteins completely new 527 00:20:53,240 --> 00:20:57,080 proteins to do things ranging from 528 00:20:55,480 --> 00:21:00,280 breaking down plastic that's been 529 00:20:57,080 --> 00:21:02,360 released into the environment to um uh 530 00:21:00,280 --> 00:21:05,400 combating neurod degenerative disease 531 00:21:02,360 --> 00:21:07,559 and and cancer and de sis of course 532 00:21:05,400 --> 00:21:09,440 you're well known for being a co-founder 533 00:21:07,559 --> 00:21:11,840 of Deep Mind the machine Learning 534 00:21:09,440 --> 00:21:15,080 Company and uh I mean you're a 535 00:21:11,840 --> 00:21:18,039 chess uh Champion you're a child prodigy 536 00:21:15,080 --> 00:21:19,760 really um you know making video games 537 00:21:18,039 --> 00:21:21,919 when you're only in your team so here 538 00:21:19,760 --> 00:21:24,880 you are you've got a Nobel Prize under 539 00:21:21,919 --> 00:21:27,440 your belt as well um but you've already 540 00:21:24,880 --> 00:21:29,400 actually started using the research that 541 00:21:27,440 --> 00:21:31,039 for which you were awarded the prize 542 00:21:29,400 --> 00:21:33,480 along with John jumper that's right so 543 00:21:31,039 --> 00:21:35,440 we we are with our own collaborations um 544 00:21:33,480 --> 00:21:37,120 uh we've been uh working with uh 545 00:21:35,440 --> 00:21:41,039 institutes like the drugs for neglected 546 00:21:37,120 --> 00:21:43,520 diseases part of the who uh and uh 547 00:21:41,039 --> 00:21:45,640 indeed because if you reduce the cost of 548 00:21:43,520 --> 00:21:48,120 of understanding what these proteins do 549 00:21:45,640 --> 00:21:50,240 you can go straight to drug design um 550 00:21:48,120 --> 00:21:51,360 that can help uh with a lot of the 551 00:21:50,240 --> 00:21:53,159 diseases that affect the poorer 552 00:21:51,360 --> 00:21:55,200 countries of the world where big farmer 553 00:21:53,159 --> 00:21:57,840 won't go because there isn't a return to 554 00:21:55,200 --> 00:21:59,480 be made so but in fact it affects uh you 555 00:21:57,840 --> 00:22:02,279 know a larger part of the of the world's 556 00:21:59,480 --> 00:22:03,559 population so um I think these these 557 00:22:02,279 --> 00:22:05,640 Technologies actually going back to our 558 00:22:03,559 --> 00:22:07,480 earlier conversation will help a lot of 559 00:22:05,640 --> 00:22:10,320 the poorer parts of the world by making 560 00:22:07,480 --> 00:22:11,679 the cost of Discovery so much um so much 561 00:22:10,320 --> 00:22:14,120 lower you know that it's within the 562 00:22:11,679 --> 00:22:16,120 scope then of Nos and nonprofits anybody 563 00:22:14,120 --> 00:22:19,000 else want to chip in on this I mean I 564 00:22:16,120 --> 00:22:22,120 mean obviously I think this is just an 565 00:22:19,000 --> 00:22:25,880 amazing opportunity for science anything 566 00:22:22,120 --> 00:22:27,799 we can use to improve the scientific 567 00:22:25,880 --> 00:22:30,279 process can have can have not 568 00:22:27,799 --> 00:22:33,919 necessarily will have have can have 569 00:22:30,279 --> 00:22:36,200 great benefits but that doesn't change 570 00:22:33,919 --> 00:22:38,600 some of the tenor of the earlier 571 00:22:36,200 --> 00:22:41,480 conversation great tools also still 572 00:22:38,600 --> 00:22:44,080 create great risks Fritz harber you know 573 00:22:41,480 --> 00:22:46,520 a Nobel Prize winner for work on which 574 00:22:44,080 --> 00:22:50,000 we depend every day with uh synthetic 575 00:22:46,520 --> 00:22:52,640 fertilizers you know also made chemical 576 00:22:50,000 --> 00:22:55,440 weapons for the German Army in World War 577 00:22:52,640 --> 00:22:57,279 one and directly causing the deaths of 578 00:22:55,440 --> 00:22:59,039 hundreds of thousands of people so the 579 00:22:57,279 --> 00:23:01,279 responsibility of scientist with 580 00:22:59,039 --> 00:23:03,840 powerful tools is no 581 00:23:01,279 --> 00:23:06,520 less we're seeing skepticism in all 582 00:23:03,840 --> 00:23:09,000 sorts of positions of power now aren't 583 00:23:06,520 --> 00:23:10,799 we um all over the world is is that 584 00:23:09,000 --> 00:23:12,919 something that worries you that policy 585 00:23:10,799 --> 00:23:16,240 makers don't perhaps understand the full 586 00:23:12,919 --> 00:23:19,360 complexity of science be climate science 587 00:23:16,240 --> 00:23:22,000 or or you know other difficult 588 00:23:19,360 --> 00:23:24,240 issues well I would say it's also part 589 00:23:22,000 --> 00:23:25,480 of our responsibility that we have to 590 00:23:24,240 --> 00:23:29,960 work 591 00:23:25,480 --> 00:23:33,120 harder in getting people to trust 592 00:23:29,960 --> 00:23:35,240 science I think there is much greater 593 00:23:33,120 --> 00:23:38,039 skepticism about 594 00:23:35,240 --> 00:23:40,520 science and I don't know I don't think 595 00:23:38,039 --> 00:23:42,520 anybody knows exactly why but it is part 596 00:23:40,520 --> 00:23:45,960 of the general polarization but it's 597 00:23:42,520 --> 00:23:48,159 also probably the way that we are not 598 00:23:45,960 --> 00:23:50,120 properly communicating the uncertainties 599 00:23:48,159 --> 00:23:51,679 in science the disagreements in science 600 00:23:50,120 --> 00:23:54,320 what we are sure and what we are not 601 00:23:51,679 --> 00:23:58,960 sure so I think we do have a lot more 602 00:23:54,320 --> 00:24:01,600 responsibilities in building the 603 00:23:58,960 --> 00:24:03,799 Public's trust in the knowledge that's 604 00:24:01,600 --> 00:24:06,440 usable in order for that knowledge to be 605 00:24:03,799 --> 00:24:08,400 seamlessly applicable to good things 606 00:24:06,440 --> 00:24:10,799 Demis and then maybe Gary yeah yeah I 607 00:24:08,400 --> 00:24:12,960 think um I I agree with that and uh I 608 00:24:10,799 --> 00:24:16,360 think in the in just in the realm of AI 609 00:24:12,960 --> 00:24:18,440 I feel like um one of the benefits of uh 610 00:24:16,360 --> 00:24:20,000 the sort of chatbot era is AI is much 611 00:24:18,440 --> 00:24:21,720 more than just chatbots you know it's 612 00:24:20,000 --> 00:24:23,039 scientific tools and other things and 613 00:24:21,720 --> 00:24:25,039 and but that it has brought it to the 614 00:24:23,039 --> 00:24:26,520 Public's Consciousness and also made 615 00:24:25,039 --> 00:24:27,799 governments more aware of it and sort of 616 00:24:26,520 --> 00:24:29,559 brought it out of the realm of Science 617 00:24:27,799 --> 00:24:30,919 Fiction and I think that's good because 618 00:24:29,559 --> 00:24:33,559 I think in the last couple of years I've 619 00:24:30,919 --> 00:24:36,600 seen a lot more convening of government 620 00:24:33,559 --> 00:24:39,200 Civil Society um academic institutes to 621 00:24:36,600 --> 00:24:40,720 discuss the broader uh issues beyond the 622 00:24:39,200 --> 00:24:42,279 Technologies which I totally agree with 623 00:24:40,720 --> 00:24:44,000 by the way including things like what 624 00:24:42,279 --> 00:24:46,480 new institutes do we need how do do we 625 00:24:44,000 --> 00:24:49,279 distribute the the benefits of this uh 626 00:24:46,480 --> 00:24:51,720 uh widely um that's a societal problem 627 00:24:49,279 --> 00:24:53,640 it's not a technal technological problem 628 00:24:51,720 --> 00:24:55,480 and um we need to have a broad debate 629 00:24:53,640 --> 00:24:57,440 about that and we've started seeing that 630 00:24:55,480 --> 00:24:59,799 we've had a couple of um Global safety 631 00:24:57,440 --> 00:25:02,080 Summits about a one in the UK one in 632 00:24:59,799 --> 00:25:03,399 South Korea next one's in France um and 633 00:25:02,080 --> 00:25:06,200 I think we need actually a higher 634 00:25:03,399 --> 00:25:08,559 intensity and more rapid discussion 635 00:25:06,200 --> 00:25:11,919 around those issues Gary do you want to 636 00:25:08,559 --> 00:25:14,080 come in here yeah I the engine of 637 00:25:11,919 --> 00:25:17,159 Western economies in terms of the 638 00:25:14,080 --> 00:25:19,960 revolution in the last 50 years has been 639 00:25:17,159 --> 00:25:21,640 technology and and uh science and 640 00:25:19,960 --> 00:25:26,679 Silicon Valley and that sort of thing in 641 00:25:21,640 --> 00:25:30,200 terms of and and um if you wanted to if 642 00:25:26,679 --> 00:25:32,120 you're an enemy of the West you want to 643 00:25:30,200 --> 00:25:34,840 destabilize that and so I think this 644 00:25:32,120 --> 00:25:37,480 whole Social Network I don't trust 645 00:25:34,840 --> 00:25:39,880 technology I don't trust any of the 646 00:25:37,480 --> 00:25:41,559 Enterprises I don't think that's evolved 647 00:25:39,880 --> 00:25:46,320 naturally I think that's been 648 00:25:41,559 --> 00:25:49,440 manipulated by bad agents and uh we have 649 00:25:46,320 --> 00:25:52,919 to be aware of that which bad agents I I 650 00:25:49,440 --> 00:25:55,799 think it's Russia and Iran I I don't 651 00:25:52,919 --> 00:25:59,440 think it's stupid to say that and uh 652 00:25:55,799 --> 00:26:01,279 politics yeah they're not not looking in 653 00:25:59,440 --> 00:26:03,640 our best interests I think there's other 654 00:26:01,279 --> 00:26:05,240 bad agents too I probably the energy 655 00:26:03,640 --> 00:26:07,520 industry would like you not to believe 656 00:26:05,240 --> 00:26:09,600 in climate change just like the tobacco 657 00:26:07,520 --> 00:26:11,240 industry knew very well that cigarettes 658 00:26:09,600 --> 00:26:13,360 cause cancer but they hid that fact for 659 00:26:11,240 --> 00:26:14,960 a long time you know if we cannot trust 660 00:26:13,360 --> 00:26:16,840 the energy companies we cannot trust 661 00:26:14,960 --> 00:26:18,880 pharmaceutical companies tobacco 662 00:26:16,840 --> 00:26:20,720 companies can we trust the tech 663 00:26:18,880 --> 00:26:23,760 companies which are extremely 664 00:26:20,720 --> 00:26:24,559 concentrated and if AI is so important 665 00:26:23,760 --> 00:26:27,679 what 666 00:26:24,559 --> 00:26:30,559 about uh the power of tech companies I 667 00:26:27,679 --> 00:26:33,039 don't know why ask me I don't work for a 668 00:26:30,559 --> 00:26:34,880 tech so you have an objective opinion no 669 00:26:33,039 --> 00:26:37,159 no but that's that's one aspect of the 670 00:26:34,880 --> 00:26:39,600 risks of AI that we didn't talk 671 00:26:37,159 --> 00:26:40,960 about okay well but just to take a more 672 00:26:39,600 --> 00:26:43,440 positive point of view again I mean 673 00:26:40,960 --> 00:26:45,559 despite the skepticism of about science 674 00:26:43,440 --> 00:26:48,279 and certainly um you don't have to look 675 00:26:45,559 --> 00:26:50,320 far in the US it should be pointed out 676 00:26:48,279 --> 00:26:52,919 that it was the response to covid with 677 00:26:50,320 --> 00:26:55,399 the MRNA vaccines was truly miraculous 678 00:26:52,919 --> 00:26:58,480 it was a technology that really had not 679 00:26:55,399 --> 00:27:00,200 been proven at at all and in very little 680 00:26:58,480 --> 00:27:02,480 time because it was it was this thing 681 00:27:00,200 --> 00:27:05,120 about having a common enemy and and a 682 00:27:02,480 --> 00:27:07,080 threat um you know we were able to 683 00:27:05,120 --> 00:27:09,200 mobilize very quickly try something 684 00:27:07,080 --> 00:27:11,760 really completely new and bring it to 685 00:27:09,200 --> 00:27:15,039 the point where it uh did a huge amount 686 00:27:11,760 --> 00:27:17,320 of good so um uh so there there reasons 687 00:27:15,039 --> 00:27:20,360 to be optimistic that were other threats 688 00:27:17,320 --> 00:27:22,960 to appear that uh a lot of the silliness 689 00:27:20,360 --> 00:27:24,640 would sort of filter out and um the 690 00:27:22,960 --> 00:27:28,440 correct actions would be taken and the 691 00:27:24,640 --> 00:27:30,240 Skeptics died okay well on that positive 692 00:27:28,440 --> 00:27:33,039 not let's just pause there for a moment 693 00:27:30,240 --> 00:27:35,399 and let's turn to the economics Nobel 694 00:27:33,039 --> 00:27:36,370 Prize and let's see why the award was 695 00:27:35,399 --> 00:27:37,840 made this 696 00:27:36,370 --> 00:27:40,960 [Music] 697 00:27:37,840 --> 00:27:43,880 year this year's prize in economics 698 00:27:40,960 --> 00:27:47,440 touches on historical injustices and 699 00:27:43,880 --> 00:27:49,720 cruelties as well as current events too 700 00:27:47,440 --> 00:27:51,919 the question of how economic development 701 00:27:49,720 --> 00:27:54,840 is connected to individual rights 702 00:27:51,919 --> 00:27:57,279 equality and decent political 703 00:27:54,840 --> 00:28:00,360 leaders when large parts of the world 704 00:27:57,279 --> 00:28:04,360 were colonized by European powers their 705 00:28:00,360 --> 00:28:07,039 approaches varied derone asoglu Simon 706 00:28:04,360 --> 00:28:09,960 Johnson and James Robinson have shown 707 00:28:07,039 --> 00:28:12,600 that Prosperity Rose in places where the 708 00:28:09,960 --> 00:28:15,720 colonial authorities built functioning 709 00:28:12,600 --> 00:28:18,440 social institutions rather than simply 710 00:28:15,720 --> 00:28:21,480 exploiting the locals and their 711 00:28:18,440 --> 00:28:24,159 resources but no growth or improvements 712 00:28:21,480 --> 00:28:27,200 in lifestyle were created in societies 713 00:28:24,159 --> 00:28:28,799 where democracy and legal certainties 714 00:28:27,200 --> 00:28:31,679 were lacking 715 00:28:28,799 --> 00:28:34,559 the laur's research also helps us 716 00:28:31,679 --> 00:28:37,720 understand why this is the case and 717 00:28:34,559 --> 00:28:39,570 could contribute to reducing income gaps 718 00:28:37,720 --> 00:28:41,919 between 719 00:28:39,570 --> 00:28:45,399 [Music] 720 00:28:41,919 --> 00:28:47,000 nations so Daron when you're both 721 00:28:45,399 --> 00:28:48,840 talking about the importance of 722 00:28:47,000 --> 00:28:50,840 democratic institutions what kind of 723 00:28:48,840 --> 00:28:56,200 Institutions are you talking 724 00:28:50,840 --> 00:28:58,480 about the uh label that we Simon Jim and 725 00:28:56,200 --> 00:29:01,399 I use as inclusive Institution ions 726 00:28:58,480 --> 00:29:04,960 meaning institutions that distribute 727 00:29:01,399 --> 00:29:07,519 political power and economic power and 728 00:29:04,960 --> 00:29:09,919 opportunity broadly in society and that 729 00:29:07,519 --> 00:29:11,519 requires certain political institutions 730 00:29:09,919 --> 00:29:13,799 that provide voice to people so that 731 00:29:11,519 --> 00:29:16,559 they can participate their views are 732 00:29:13,799 --> 00:29:18,480 expressed and also constraints on the 733 00:29:16,559 --> 00:29:19,679 exercise of that power so you just 734 00:29:18,480 --> 00:29:22,399 talking about really the checks and 735 00:29:19,679 --> 00:29:24,799 balances we see in you know set down in 736 00:29:22,399 --> 00:29:28,240 constitutions like a an independent 737 00:29:24,799 --> 00:29:30,000 legislature a free Judiciary freedom of 738 00:29:28,240 --> 00:29:31,960 speech with you know a me the media 739 00:29:30,000 --> 00:29:35,080 being able to operate as it absolutely 740 00:29:31,960 --> 00:29:37,720 absolutely but that's not enough partly 741 00:29:35,080 --> 00:29:41,200 because what you write in a constitution 742 00:29:37,720 --> 00:29:43,120 is not going to get enforced unless 743 00:29:41,200 --> 00:29:45,840 there is a general empowerment of the 744 00:29:43,120 --> 00:29:49,559 people so Constitutions are sometimes 745 00:29:45,840 --> 00:29:52,880 changed just like shirts and uh it 746 00:29:49,559 --> 00:29:56,360 doesn't mean anything unless it becomes 747 00:29:52,880 --> 00:29:58,480 enforced but you have also seen um 748 00:29:56,360 --> 00:30:00,720 countries Prosper economically which 749 00:29:58,480 --> 00:30:02,919 have been governed by fairly 750 00:30:00,720 --> 00:30:05,640 authoritarian governments haven't you I 751 00:30:02,919 --> 00:30:08,320 mean often we talk about Lee kuu in 752 00:30:05,640 --> 00:30:10,120 Singapore or Mah Muhammad in Malaysia 753 00:30:08,320 --> 00:30:12,279 for instance yeah I think that's not the 754 00:30:10,120 --> 00:30:14,200 general pattern I mean so there are 755 00:30:12,279 --> 00:30:16,120 examples like that of course but for 756 00:30:14,200 --> 00:30:18,240 every example like that there's far more 757 00:30:16,120 --> 00:30:20,440 examples of autocratic societies that 758 00:30:18,240 --> 00:30:23,320 have not flourished economically you 759 00:30:20,440 --> 00:30:25,519 know if if you can create inclusive 760 00:30:23,320 --> 00:30:27,600 Economic Institutions even under a 761 00:30:25,519 --> 00:30:29,919 politically kind of autocratic Society 762 00:30:27,600 --> 00:30:31,600 you can flourish economically at least 763 00:30:29,919 --> 00:30:34,039 transitorily you know that's what 764 00:30:31,600 --> 00:30:36,080 happened in China you know starting in 765 00:30:34,039 --> 00:30:37,960 the late 1970s it was the movement 766 00:30:36,080 --> 00:30:39,960 towards a much more inclusive economy 767 00:30:37,960 --> 00:30:42,000 giving people the right to make 768 00:30:39,960 --> 00:30:44,440 decisions making them residual claimants 769 00:30:42,000 --> 00:30:46,080 on their own efforts and you know so so 770 00:30:44,440 --> 00:30:48,039 that that's what generated economic 771 00:30:46,080 --> 00:30:50,159 growth but our our view is that you know 772 00:30:48,039 --> 00:30:53,159 you can't sustain an economy like that 773 00:30:50,159 --> 00:30:56,320 under a autocratic political system it 774 00:30:53,159 --> 00:30:58,519 can be there for a transitory period but 775 00:30:56,320 --> 00:31:00,679 it's not sustainable a lot of research 776 00:30:58,519 --> 00:31:03,080 is based on countries which have been 777 00:31:00,679 --> 00:31:04,559 colonized and um there's been a lot of 778 00:31:03,080 --> 00:31:06,880 debate of course particularly in the 779 00:31:04,559 --> 00:31:10,080 United Kingdom because of the historical 780 00:31:06,880 --> 00:31:12,080 you know Great British Empire and um 781 00:31:10,080 --> 00:31:13,559 whether it was good or bad for the 782 00:31:12,080 --> 00:31:15,639 countries that were colonized 783 00:31:13,559 --> 00:31:18,080 practically all of Africa but you say 784 00:31:15,639 --> 00:31:21,760 that colonization often brought about a 785 00:31:18,080 --> 00:31:24,399 reversal in economic fortunes of the 786 00:31:21,760 --> 00:31:25,919 colonized people so just unpack for us 787 00:31:24,399 --> 00:31:29,200 why you say that because it sounds like 788 00:31:25,919 --> 00:31:31,840 you're saying colonization was bad for 789 00:31:29,200 --> 00:31:34,120 the people I I think colonization was a 790 00:31:31,840 --> 00:31:37,639 disaster AB absolutely but of course it 791 00:31:34,120 --> 00:31:39,159 did create prosperous Societies in parts 792 00:31:37,639 --> 00:31:41,360 of the world in North America and 793 00:31:39,159 --> 00:31:43,480 australasia but for the indigenous 794 00:31:41,360 --> 00:31:46,600 people it was a catastrophe you know 795 00:31:43,480 --> 00:31:48,880 diseases wiped out 90% of the population 796 00:31:46,600 --> 00:31:50,919 of the Americas people were exploited 797 00:31:48,880 --> 00:31:52,960 they had their lands and livelihoods 798 00:31:50,919 --> 00:31:56,120 destroyed their communities destroyed I 799 00:31:52,960 --> 00:31:58,120 mean absolutely yes so so so I don't you 800 00:31:56,120 --> 00:31:59,840 know so I don't think there's much to 801 00:31:58,120 --> 00:32:02,159 about that in my view I think this 802 00:31:59,840 --> 00:32:03,760 notion of reversal you know the Americas 803 00:32:02,159 --> 00:32:06,240 is very clear in the Americas you know 804 00:32:03,760 --> 00:32:07,880 at the time 5 you go back 500 years 805 00:32:06,240 --> 00:32:09,919 where were the prosperous parts of the 806 00:32:07,880 --> 00:32:13,919 Americas Central America the Central 807 00:32:09,919 --> 00:32:16,519 Valley of Mexico andian the Inca Empire 808 00:32:13,919 --> 00:32:18,600 you know the mexicas the valley of Waka 809 00:32:16,519 --> 00:32:21,120 you know there you had you had writing 810 00:32:18,600 --> 00:32:23,559 you had political complexity you had 811 00:32:21,120 --> 00:32:25,399 economic organization sophistication 812 00:32:23,559 --> 00:32:28,360 whatever the southern cone of Latin 813 00:32:25,399 --> 00:32:30,519 America North America far behind 814 00:32:28,360 --> 00:32:33,000 you know and then this gets completely 815 00:32:30,519 --> 00:32:35,000 reversed during the colonial period and 816 00:32:33,000 --> 00:32:36,880 the places that were relatively poor 817 00:32:35,000 --> 00:32:38,799 then become relatively prosperous so 818 00:32:36,880 --> 00:32:41,399 that's there you see the reversal in a 819 00:32:38,799 --> 00:32:43,440 very clear way right I want to bring you 820 00:32:41,399 --> 00:32:45,880 in Demis because your mother is 821 00:32:43,440 --> 00:32:47,960 Singaporean or Singaporean born uh you 822 00:32:45,880 --> 00:32:50,080 brought up in in Britain of course but 823 00:32:47,960 --> 00:32:52,360 um what do you think when you hear about 824 00:32:50,080 --> 00:32:54,200 this kind of thing about democracy and 825 00:32:52,360 --> 00:32:55,360 prosperity and well it's very I mean 826 00:32:54,200 --> 00:32:56,720 it's very interesting obviously I've 827 00:32:55,360 --> 00:32:58,919 heard from my mother the sort of 828 00:32:56,720 --> 00:33:00,240 economic miracle that leanu brought to 829 00:32:58,919 --> 00:33:02,320 Singapore and he's re when you're 830 00:33:00,240 --> 00:33:04,039 rightly revered for that I don't know 831 00:33:02,320 --> 00:33:06,480 obviously this is not my area but it's 832 00:33:04,039 --> 00:33:08,159 it's how do you how do you try and you 833 00:33:06,480 --> 00:33:10,399 know how are these institutions going to 834 00:33:08,159 --> 00:33:12,159 be built in the places where they aren't 835 00:33:10,399 --> 00:33:13,880 um is there external is it going to be 836 00:33:12,159 --> 00:33:15,760 external encouragement or it has to 837 00:33:13,880 --> 00:33:17,240 happen internally or you know how is 838 00:33:15,760 --> 00:33:19,559 that going to or you just have to be 839 00:33:17,240 --> 00:33:21,840 lucky with finding the right leader like 840 00:33:19,559 --> 00:33:23,440 like a Le oneu yeah I mean I think you 841 00:33:21,840 --> 00:33:25,320 know the success stories are all they 842 00:33:23,440 --> 00:33:27,799 all come from within people build the 843 00:33:25,320 --> 00:33:29,600 institutions in their own context I mean 844 00:33:27,799 --> 00:33:31,120 there are you know I think Lewan Yu is a 845 00:33:29,600 --> 00:33:33,159 sort of fascinating person he's not the 846 00:33:31,120 --> 00:33:36,240 only person in the world like that you 847 00:33:33,159 --> 00:33:38,639 know you had seretti karma in in in in 848 00:33:36,240 --> 00:33:41,440 Botswana you know you have other kind of 849 00:33:38,639 --> 00:33:44,039 outstanding leaders but I think on 850 00:33:41,440 --> 00:33:46,480 average you know the evidence suggests 851 00:33:44,039 --> 00:33:48,919 autocratic regimes don't do as well as 852 00:33:46,480 --> 00:33:50,919 Democratic ones and sure you know people 853 00:33:48,919 --> 00:33:53,840 matter individuals matter having good 854 00:33:50,919 --> 00:33:55,200 leader matter where' you find leanu you 855 00:33:53,840 --> 00:33:57,279 know that's what was going to ask you so 856 00:33:55,200 --> 00:33:59,000 then if it has to come from within you 857 00:33:57,279 --> 00:34:01,000 know what so you're pointing out with 858 00:33:59,000 --> 00:34:03,200 your great work like what the issues are 859 00:34:01,000 --> 00:34:05,279 but how other than wait for for the 860 00:34:03,200 --> 00:34:07,559 right you know Mandela or leanu to come 861 00:34:05,279 --> 00:34:09,480 along which is very rare as you say what 862 00:34:07,559 --> 00:34:11,119 else can be done to you know encourage 863 00:34:09,480 --> 00:34:12,599 those institutions to be built yeah but 864 00:34:11,119 --> 00:34:14,679 there's lots of Institutions are built 865 00:34:12,599 --> 00:34:17,240 without famous leaders I think the track 866 00:34:14,679 --> 00:34:18,679 record of external imposition of 867 00:34:17,240 --> 00:34:21,599 Institutions is not very good there are 868 00:34:18,679 --> 00:34:24,839 a few cases where you can point to but 869 00:34:21,599 --> 00:34:27,240 uh but generally institutions are built 870 00:34:24,839 --> 00:34:30,440 organically but there are influences out 871 00:34:27,240 --> 00:34:34,159 there so one of the cases Jim already 872 00:34:30,440 --> 00:34:36,879 hinted that Sama Botswana you know an 873 00:34:34,159 --> 00:34:38,399 amazingly successful democracy in 874 00:34:36,879 --> 00:34:40,200 subsaharan Africa an amazingly 875 00:34:38,399 --> 00:34:43,280 successful country in terms of economic 876 00:34:40,200 --> 00:34:45,879 growth uh very rapid growth on the whole 877 00:34:43,280 --> 00:34:48,200 and it was all existing actually 878 00:34:45,879 --> 00:34:50,399 pre-colonial institutions that were the 879 00:34:48,200 --> 00:34:52,520 basis of more democratic but leadership 880 00:34:50,399 --> 00:34:55,960 there mattered too so you need you need 881 00:34:52,520 --> 00:34:57,720 a combination so I think facilitating 882 00:34:55,960 --> 00:34:59,839 institution building domestically 883 00:34:57,720 --> 00:35:03,079 providing tools for them and getting rid 884 00:34:59,839 --> 00:35:05,680 of our hindrances often you know Western 885 00:35:03,079 --> 00:35:08,480 and Russian powers or sometimes Chinese 886 00:35:05,680 --> 00:35:10,280 Powers interfering in other Count's uh 887 00:35:08,480 --> 00:35:11,960 domestic affairs is not conducive to 888 00:35:10,280 --> 00:35:13,280 better institution building but at the 889 00:35:11,960 --> 00:35:16,040 end of the day institutions are going to 890 00:35:13,280 --> 00:35:18,560 be built bottom up okay so look a major 891 00:35:16,040 --> 00:35:20,599 theme of this year's Nobel prizes has 892 00:35:18,560 --> 00:35:21,920 been artificial intelligence so James 893 00:35:20,599 --> 00:35:26,280 let me ask you then if you think 894 00:35:21,920 --> 00:35:28,280 technology AI could help Africa develop 895 00:35:26,280 --> 00:35:30,320 but Africa has not been benefiting from 896 00:35:28,280 --> 00:35:32,920 all this technology I'm saying it it 897 00:35:30,320 --> 00:35:34,520 could but to do that many things have to 898 00:35:32,920 --> 00:35:36,680 change many things have to change 899 00:35:34,520 --> 00:35:38,680 institutions have to change politics has 900 00:35:36,680 --> 00:35:41,200 to change you know people's trusts all 901 00:35:38,680 --> 00:35:43,560 sorts of things have to change and what 902 00:35:41,200 --> 00:35:46,359 about the impact of technology AI for 903 00:35:43,560 --> 00:35:48,680 instance on Democracy really I am 904 00:35:46,359 --> 00:35:51,119 talking about the impact on jobs to what 905 00:35:48,680 --> 00:35:54,480 extent there'll be displacement of human 906 00:35:51,119 --> 00:35:58,319 activity and jobs by machines yeah I 907 00:35:54,480 --> 00:36:01,359 mean I think that's a huge risk I 908 00:35:58,319 --> 00:36:03,480 believe that humans would have a very 909 00:36:01,359 --> 00:36:06,680 difficult time building their social 910 00:36:03,480 --> 00:36:09,640 systems and communities if they become 911 00:36:06,680 --> 00:36:13,280 majorly sidelined and they feel they 912 00:36:09,640 --> 00:36:15,839 don't have dignity or use or a way to 913 00:36:13,280 --> 00:36:17,160 contribute to the social good from your 914 00:36:15,839 --> 00:36:19,200 perspective I mean there have been a lot 915 00:36:17,160 --> 00:36:21,560 of advances in technology over the last 916 00:36:19,200 --> 00:36:23,640 100 years have have any of them really 917 00:36:21,560 --> 00:36:26,480 cause massive displacement of jobs I 918 00:36:23,640 --> 00:36:28,200 mean already you know there's um a lot 919 00:36:26,480 --> 00:36:29,680 of these Technologies are out there but 920 00:36:28,200 --> 00:36:31,520 have they reduced the number of jobs 921 00:36:29,680 --> 00:36:33,119 yeah yeah there it has happened it has 922 00:36:31,520 --> 00:36:34,839 happened I mean the early phase of the 923 00:36:33,119 --> 00:36:36,960 Industrial Revolution where it was all 924 00:36:34,839 --> 00:36:40,000 lot about automation there were huge 925 00:36:36,960 --> 00:36:42,040 displacements huge wage losses onethird 926 00:36:40,000 --> 00:36:44,240 two you know people's wages within 20 927 00:36:42,040 --> 00:36:46,640 years in real terms fell to for some 928 00:36:44,240 --> 00:36:48,400 people to onethird of it what it was 929 00:36:46,640 --> 00:36:52,240 that's just a tremendous yes but down 930 00:36:48,400 --> 00:36:53,960 then in the end it became better so I 931 00:36:52,240 --> 00:36:55,720 yes so in my view there will be a lot of 932 00:36:53,960 --> 00:36:57,680 disruption like these other like the 933 00:36:55,720 --> 00:37:00,319 Industrial Revolution 934 00:36:57,680 --> 00:37:02,000 90 years it took 90 years I don't think 935 00:37:00,319 --> 00:37:05,440 what we want to put up with but there 936 00:37:02,000 --> 00:37:07,480 could be new classes of jobs I mean most 937 00:37:05,440 --> 00:37:09,079 but those new classes of jobs they're 938 00:37:07,480 --> 00:37:13,000 not automatic so there are like two ways 939 00:37:09,079 --> 00:37:14,560 of thinking uh on this beyond the 940 00:37:13,000 --> 00:37:16,200 artificial general intelligence one is 941 00:37:14,560 --> 00:37:17,839 that you introduce these disruptive 942 00:37:16,200 --> 00:37:19,920 Technologies and the system 943 00:37:17,839 --> 00:37:21,880 automatically adjusts nobody needs to do 944 00:37:19,920 --> 00:37:24,680 anything no policy maker no scientist 945 00:37:21,880 --> 00:37:26,040 nor technologist the system will adjust 946 00:37:24,680 --> 00:37:28,040 I think that just does is is 947 00:37:26,040 --> 00:37:30,160 contradicted by history the way that it 948 00:37:28,040 --> 00:37:32,280 works is that we all have to work in 949 00:37:30,160 --> 00:37:34,400 order to make things better including 950 00:37:32,280 --> 00:37:36,480 technologist so that we actually use the 951 00:37:34,400 --> 00:37:38,440 scientific knowledge to create new tasks 952 00:37:36,480 --> 00:37:40,319 more capabilities for humans rather than 953 00:37:38,440 --> 00:37:41,720 just sidelining them I mean we've seen 954 00:37:40,319 --> 00:37:43,560 used to talk about the lessons of 955 00:37:41,720 --> 00:37:45,880 history but we saw with the printing 956 00:37:43,560 --> 00:37:49,040 press Revolution people who were writing 957 00:37:45,880 --> 00:37:51,720 books were put out of business but then 958 00:37:49,040 --> 00:37:53,800 lots of new jobs were created through 959 00:37:51,720 --> 00:37:56,440 publishing but look at the last 40 years 960 00:37:53,800 --> 00:37:59,560 the US is an extreme case yeah 961 00:37:56,440 --> 00:38:01,640 but roughly speaking I'm exaggerating a 962 00:37:59,560 --> 00:38:03,880 little bit but about half of the US 963 00:38:01,640 --> 00:38:07,000 population those who don't have college 964 00:38:03,880 --> 00:38:11,520 degrees have had almost no growth in 965 00:38:07,000 --> 00:38:15,560 their real incomes until about 2015 from 966 00:38:11,520 --> 00:38:17,119 1980 so no new jobs of import were 967 00:38:15,560 --> 00:38:19,400 created for them there were a lot of new 968 00:38:17,119 --> 00:38:21,560 jobs in the 1990s and 2000s but they 969 00:38:19,400 --> 00:38:23,960 were all for people with postgraduate 970 00:38:21,560 --> 00:38:26,119 degrees and and and specialized 971 00:38:23,960 --> 00:38:28,079 knowledge okay Jeff Hinton do you think 972 00:38:26,119 --> 00:38:30,560 that this increase in product activity 973 00:38:28,079 --> 00:38:33,079 essentially that will come with um 974 00:38:30,560 --> 00:38:35,480 Automation and so on and so forth is is 975 00:38:33,079 --> 00:38:37,359 a good thing for society well it ought 976 00:38:35,480 --> 00:38:41,040 to be right I mean it's crazy we're 977 00:38:37,359 --> 00:38:42,960 we're talking about um having a huge 978 00:38:41,040 --> 00:38:44,680 increase in productivity so there's 979 00:38:42,960 --> 00:38:46,599 going to be more goods and services for 980 00:38:44,680 --> 00:38:48,839 everybody so everybody ought to be 981 00:38:46,599 --> 00:38:50,599 better off but actually it's going to be 982 00:38:48,839 --> 00:38:52,599 the other way around and it's because we 983 00:38:50,599 --> 00:38:54,599 live in a capitalist society and so 984 00:38:52,599 --> 00:38:56,560 what's going to happen is this huge 985 00:38:54,599 --> 00:38:58,040 increase in productivity is going to 986 00:38:56,560 --> 00:38:59,960 make much more money for the big 987 00:38:58,040 --> 00:39:01,720 companies and the rich and it's going to 988 00:38:59,960 --> 00:39:03,800 increase the gap between the rich and 989 00:39:01,720 --> 00:39:06,200 the people who lose their jobs and as 990 00:39:03,800 --> 00:39:09,079 soon as you increase that Gap you get 991 00:39:06,200 --> 00:39:13,079 fertile ground for fascism and so it's 992 00:39:09,079 --> 00:39:14,599 very scary that um we may be at a point 993 00:39:13,079 --> 00:39:17,359 where we're just making things worse and 994 00:39:14,599 --> 00:39:19,240 worse and it's crazy because we're doing 995 00:39:17,359 --> 00:39:20,800 something that should help everybody and 996 00:39:19,240 --> 00:39:23,760 obviously it will help in healthcare it 997 00:39:20,800 --> 00:39:25,440 help in education but if the profits 998 00:39:23,760 --> 00:39:28,520 just go to the rich that's going to make 999 00:39:25,440 --> 00:39:31,040 Society worse so okay let's look at the 1000 00:39:28,520 --> 00:39:34,520 last award and that's the Nobel Prize 1001 00:39:31,040 --> 00:39:37,960 for medicine or physiology and this is 1002 00:39:34,520 --> 00:39:40,880 why it was awarded this 1003 00:39:37,960 --> 00:39:44,040 year our organs and tissues are made up 1004 00:39:40,880 --> 00:39:47,079 of many varied types of cells they all 1005 00:39:44,040 --> 00:39:48,520 have identical genetic material but 1006 00:39:47,079 --> 00:39:50,640 different 1007 00:39:48,520 --> 00:39:54,160 characteristics this year's medicine 1008 00:39:50,640 --> 00:39:56,319 laurates Gary riffkin and Victor Ambrose 1009 00:39:54,160 --> 00:39:59,720 have shown how a new form of Gene 1010 00:39:56,319 --> 00:40:01,920 regulation microrna is crucial in 1011 00:39:59,720 --> 00:40:05,400 ensuring that the different cells of 1012 00:40:01,920 --> 00:40:08,319 organisms such as muscles or nerve cells 1013 00:40:05,400 --> 00:40:11,720 get the functions they need it's already 1014 00:40:08,319 --> 00:40:14,280 known that abnormal levels of micro RNA 1015 00:40:11,720 --> 00:40:16,920 increase the risk of cancer but the 1016 00:40:14,280 --> 00:40:19,920 laurat research could lead to developing 1017 00:40:16,920 --> 00:40:23,520 new Diagnostics and treatments for 1018 00:40:19,920 --> 00:40:26,319 example it could map how microrna varies 1019 00:40:23,520 --> 00:40:30,440 in different diseases helping unlock 1020 00:40:26,319 --> 00:40:30,440 prognosis for the development of 1021 00:40:31,079 --> 00:40:37,520 diseases so Gary your research was based 1022 00:40:34,680 --> 00:40:39,720 on um looking at mutant strains of the 1023 00:40:37,520 --> 00:40:41,440 round worm um actually it should have 1024 00:40:39,720 --> 00:40:44,800 its own Nobel Prize shouldn't it It's 1025 00:40:41,440 --> 00:40:48,359 featured so much in research that's led 1026 00:40:44,800 --> 00:40:50,920 to Nobel prizes but um just tell us what 1027 00:40:48,359 --> 00:40:55,119 does your work with round worms tell us 1028 00:40:50,920 --> 00:40:58,599 about genetic mutations in humans doing 1029 00:40:55,119 --> 00:41:00,720 genetics is is a form of doing what 1030 00:40:58,599 --> 00:41:04,800 evolution has been doing for 4 billion 1031 00:41:00,720 --> 00:41:07,760 years the our planet is a genetic 1032 00:41:04,800 --> 00:41:11,079 experiment that's has been generating 1033 00:41:07,760 --> 00:41:14,560 diverse life from primitive life over 1034 00:41:11,079 --> 00:41:16,520 four billion years by inducing variation 1035 00:41:14,560 --> 00:41:19,599 to give you the tree of life that goes 1036 00:41:16,520 --> 00:41:23,079 you know to bats and to plants and to 1037 00:41:19,599 --> 00:41:26,040 bacteria and we do that on one organism 1038 00:41:23,079 --> 00:41:28,680 and the reason it works so well is that 1039 00:41:26,040 --> 00:41:32,160 Evolution has evolved a way to generate 1040 00:41:28,680 --> 00:41:34,400 diversity by mutating that's that's what 1041 00:41:32,160 --> 00:41:36,720 all around us you know when you see a a 1042 00:41:34,400 --> 00:41:39,280 green tree it's because 1043 00:41:36,720 --> 00:41:42,000 photosynthesis was developed two billion 1044 00:41:39,280 --> 00:41:45,680 years ago the reason we can breathe 1045 00:41:42,000 --> 00:41:48,720 oxygen is because photosynthesis evolved 1046 00:41:45,680 --> 00:41:50,800 and it wasn't there beforehand and so 1047 00:41:48,720 --> 00:41:52,680 what we're doing is that process and 1048 00:41:50,800 --> 00:41:55,720 that's why it works so well so the 1049 00:41:52,680 --> 00:41:58,520 reason uh the worm has gotten four Nobel 1050 00:41:55,720 --> 00:42:01,960 prizes is that and it's the worm that 1051 00:41:58,520 --> 00:42:04,359 got it so you know we we're just The 1052 00:42:01,960 --> 00:42:07,839 Operators uh is she behave with this 1053 00:42:04,359 --> 00:42:10,640 yeah yeah it's very tiny it's very tiny 1054 00:42:07,839 --> 00:42:14,040 it's a millimeter long it you know it 1055 00:42:10,640 --> 00:42:15,680 has 959 cells that's different from us 1056 00:42:14,040 --> 00:42:18,400 right our not every one of our cells 1057 00:42:15,680 --> 00:42:21,280 does not have a name you know it but 1058 00:42:18,400 --> 00:42:23,520 every cell in a worm has a name and that 1059 00:42:21,280 --> 00:42:27,200 attracted a kind of cohort of people who 1060 00:42:23,520 --> 00:42:29,119 like names names are important and we 1061 00:42:27,200 --> 00:42:31,240 we're thinking about well we can learn a 1062 00:42:29,119 --> 00:42:33,880 lot about how biology works by sort of 1063 00:42:31,240 --> 00:42:35,760 following cells what's their history 1064 00:42:33,880 --> 00:42:38,000 what do they become how much do they 1065 00:42:35,760 --> 00:42:39,800 talk to each other but we figure it out 1066 00:42:38,000 --> 00:42:41,400 by breaking it but it's I mean it's 1067 00:42:39,800 --> 00:42:46,200 extraordinary that a human has about 1068 00:42:41,400 --> 00:42:47,440 20,000 genes and a worm has 20,000 gen 1069 00:42:46,200 --> 00:42:50,319 that's why we really are too 1070 00:42:47,440 --> 00:42:52,480 self-important we're just not you know 1071 00:42:50,319 --> 00:42:55,480 humans are just not that great you know 1072 00:42:52,480 --> 00:42:58,359 we're we're fine I'm happy to be a human 1073 00:42:55,480 --> 00:43:02,119 I don't want to be a worm but you 1074 00:42:58,359 --> 00:43:04,280 know you know a bacteria has 4,000 genes 1075 00:43:02,119 --> 00:43:07,640 that's not very different from 20,000 1076 00:43:04,280 --> 00:43:10,000 I'm sorry right and you know people say 1077 00:43:07,640 --> 00:43:13,480 oh geez if you look for life on other 1078 00:43:10,000 --> 00:43:16,000 planets it's bacteria how boring you got 1079 00:43:13,480 --> 00:43:17,839 it all wrong folks bacteria are totally 1080 00:43:16,000 --> 00:43:19,880 awesome yeah yeah but so what you're 1081 00:43:17,839 --> 00:43:22,440 saying essentially is that mutations 1082 00:43:19,880 --> 00:43:25,240 obviously can be bad because they can 1083 00:43:22,440 --> 00:43:27,359 lead to sorts of genetic um illnesses 1084 00:43:25,240 --> 00:43:29,520 and so on but they're not always bad and 1085 00:43:27,359 --> 00:43:31,720 some are quite actually relatively 1086 00:43:29,520 --> 00:43:34,200 insignificant like you're color blind 1087 00:43:31,720 --> 00:43:36,200 aren't you for instance I mean that's a 1088 00:43:34,200 --> 00:43:39,240 genetic mutation it is and it's a 1089 00:43:36,200 --> 00:43:42,280 debilitating mutation for me be uh in 1090 00:43:39,240 --> 00:43:45,920 the days of black and white um 1091 00:43:42,280 --> 00:43:48,839 publishing I I was King things were fine 1092 00:43:45,920 --> 00:43:52,040 and then everything became color you 1093 00:43:48,839 --> 00:43:55,000 know it it I have to say so like uh our 1094 00:43:52,040 --> 00:43:57,240 little worm I'll go to a seminar and 1095 00:43:55,000 --> 00:43:59,520 people are presenting graphs with red 1096 00:43:57,240 --> 00:44:02,200 green and and I come out going gez that 1097 00:43:59,520 --> 00:44:04,000 was just complete horse what I didn't 1098 00:44:02,200 --> 00:44:07,640 and people said oh it was fantastic you 1099 00:44:04,000 --> 00:44:11,000 didn't see I wrote to Google Maps and 1100 00:44:07,640 --> 00:44:14,160 said you guys you do traffic is red and 1101 00:44:11,000 --> 00:44:17,839 green means things are F I can't see it 1102 00:44:14,160 --> 00:44:20,680 and you're losing 4% of the of the users 1103 00:44:17,839 --> 00:44:20,680 and it's the best 1104 00:44:20,920 --> 00:44:25,680 4% but I mean you actually want did not 1105 00:44:23,480 --> 00:44:27,599 respond you wanted to be an electrical 1106 00:44:25,680 --> 00:44:30,599 engineer originally did 1107 00:44:27,599 --> 00:44:34,280 well yes I did Electronics as a kid cuz 1108 00:44:30,599 --> 00:44:38,280 I loved electronics and I built kits uh 1109 00:44:34,280 --> 00:44:41,000 I built a shortwave radio with a $39 kit 1110 00:44:38,280 --> 00:44:44,400 made with vacuum tubes this is before 1111 00:44:41,000 --> 00:44:45,800 you know transistors but the resistors 1112 00:44:44,400 --> 00:44:48,800 have a color 1113 00:44:45,800 --> 00:44:51,160 code right and so and it tells you how 1114 00:44:48,800 --> 00:44:54,640 many ohms it is and that's how much 1115 00:44:51,160 --> 00:44:56,200 resistance it has and so I didn't know 1116 00:44:54,640 --> 00:44:58,960 it I didn't know I was color blind at 1117 00:44:56,200 --> 00:45:02,040 the time so I put it together and the 1118 00:44:58,960 --> 00:45:03,280 test for how well you are whether it's 1119 00:45:02,040 --> 00:45:07,480 going to work is you turn it on and if 1120 00:45:03,280 --> 00:45:09,440 it doesn't smoke that that's good and my 1121 00:45:07,480 --> 00:45:11,160 electronic assembly didn't pass the 1122 00:45:09,440 --> 00:45:15,000 smoke 1123 00:45:11,160 --> 00:45:18,599 test so um let's go for another question 1124 00:45:15,000 --> 00:45:21,280 now from our audience Jasmin kovitz what 1125 00:45:18,599 --> 00:45:24,040 do you want to ask Professor rkin was 1126 00:45:21,280 --> 00:45:25,960 micro RNA an unexpected Fant or was it a 1127 00:45:24,040 --> 00:45:28,760 part of your hypothesis while conducting 1128 00:45:25,960 --> 00:45:31,559 your research there no hypothesis on 1129 00:45:28,760 --> 00:45:34,119 that no no no no no it was a complete 1130 00:45:31,559 --> 00:45:37,640 surprise and I love 1131 00:45:34,119 --> 00:45:41,520 surprises and really you know that's the 1132 00:45:37,640 --> 00:45:44,720 beauty of doing genetics is that what 1133 00:45:41,520 --> 00:45:47,040 comes out is what teaches you right it's 1134 00:45:44,720 --> 00:45:49,440 and you know you do a mutagenesis you 1135 00:45:47,040 --> 00:45:51,800 get an animal that looks like what you 1136 00:45:49,440 --> 00:45:53,640 were looking for part of the search is 1137 00:45:51,800 --> 00:45:56,319 saying what am I going to look for 1138 00:45:53,640 --> 00:45:59,359 that's the the art of it how did your 1139 00:45:56,319 --> 00:46:00,839 research with Victor Ambrose's um go 1140 00:45:59,359 --> 00:46:03,599 down when you first published it in the 1141 00:46:00,839 --> 00:46:06,319 early 1990s it was in a little little 1142 00:46:03,599 --> 00:46:08,280 corner of biology this worm and there 1143 00:46:06,319 --> 00:46:11,240 was a sense when you would deliver a 1144 00:46:08,280 --> 00:46:13,040 paper to go to give a talk about it that 1145 00:46:11,240 --> 00:46:15,400 well it's a worm who cares you know and 1146 00:46:13,040 --> 00:46:18,359 it's a weird little animal until it we 1147 00:46:15,400 --> 00:46:22,040 discovered that it was in human genome 1148 00:46:18,359 --> 00:46:24,559 and then many other genomes and it's 1149 00:46:22,040 --> 00:46:26,960 been embraced and it what was 1150 00:46:24,559 --> 00:46:28,960 especially sort of empowering to it was 1151 00:46:26,960 --> 00:46:31,240 was it it intersected with RNA 1152 00:46:28,960 --> 00:46:34,160 interference which is an antiviral 1153 00:46:31,240 --> 00:46:36,640 response and people really care now of 1154 00:46:34,160 --> 00:46:39,440 course about antiviral responses of 1155 00:46:36,640 --> 00:46:41,040 course I mean how did you all find doing 1156 00:46:39,440 --> 00:46:43,520 your research I mean just listening to 1157 00:46:41,040 --> 00:46:46,079 what Gary is saying did you encounter 1158 00:46:43,520 --> 00:46:49,559 setbacks can you define particular 1159 00:46:46,079 --> 00:46:52,680 moments when your research really felt 1160 00:46:49,559 --> 00:46:54,960 that you you were on a winning streak 1161 00:46:52,680 --> 00:46:57,440 did people discourage you from what you 1162 00:46:54,960 --> 00:47:01,720 were doing all of the above 1163 00:46:57,440 --> 00:47:05,359 really I mean you know Academia is 1164 00:47:01,720 --> 00:47:09,400 really hard at some level you know you 1165 00:47:05,359 --> 00:47:12,000 work sometimes three years on a project 1166 00:47:09,400 --> 00:47:16,000 and then somebody anonymously destroys 1167 00:47:12,000 --> 00:47:18,960 it so that's very very difficult to get 1168 00:47:16,000 --> 00:47:21,160 used to so I do a lot of coaching with 1169 00:47:18,960 --> 00:47:22,960 my graduate students to get them ready 1170 00:47:21,160 --> 00:47:26,319 for that but on the other hand I found 1171 00:47:22,960 --> 00:47:28,800 Academia to be quite open-minded as well 1172 00:47:26,319 --> 00:47:31,119 you know when 1173 00:47:28,800 --> 00:47:33,480 Jim Simon Johnson and I for example 1174 00:47:31,119 --> 00:47:36,119 started doing our work you know I think 1175 00:47:33,480 --> 00:47:38,599 there was not much of the sort in 1176 00:47:36,119 --> 00:47:40,359 economics and people could have said no 1177 00:47:38,599 --> 00:47:42,440 this is not economics and some people 1178 00:47:40,359 --> 00:47:44,000 did and people could have said this is 1179 00:47:42,440 --> 00:47:45,520 crazy and some people did but there were 1180 00:47:44,000 --> 00:47:47,920 a lot of people who were open-minded 1181 00:47:45,520 --> 00:47:50,800 especially young researchers you know 1182 00:47:47,920 --> 00:47:54,119 they're hungry for new angles so I found 1183 00:47:50,800 --> 00:47:56,839 Academia to be quite open-minded as well 1184 00:47:54,119 --> 00:47:58,920 but a tough Place D Salis David I think 1185 00:47:56,839 --> 00:48:01,839 I think you've both said that research 1186 00:47:58,920 --> 00:48:05,079 in proteins is kind of seen as at the 1187 00:48:01,839 --> 00:48:08,400 time being on The Lunatic Fringe of uh 1188 00:48:05,079 --> 00:48:10,319 science um I mean how how did you cope 1189 00:48:08,400 --> 00:48:12,040 with that kind of perception that you 1190 00:48:10,319 --> 00:48:14,319 were doing something that was a bit out 1191 00:48:12,040 --> 00:48:15,920 there well I think when um when we 1192 00:48:14,319 --> 00:48:17,559 started trying to design proteins 1193 00:48:15,920 --> 00:48:19,720 everyone thought it was a crazy way to 1194 00:48:17,559 --> 00:48:21,200 try and solve hard problems the only 1195 00:48:19,720 --> 00:48:23,000 proteins we knew at the time were the 1196 00:48:21,200 --> 00:48:24,720 ones that came down through you know 1197 00:48:23,000 --> 00:48:26,599 through Evolution the ones in us and in 1198 00:48:24,720 --> 00:48:28,200 all living things so the idea that you 1199 00:48:26,599 --> 00:48:30,960 could make completely new ones and that 1200 00:48:28,200 --> 00:48:34,280 they could they could do new things was 1201 00:48:30,960 --> 00:48:36,480 was really seen as um you know Lunatic 1202 00:48:34,280 --> 00:48:37,880 Fringe as you said but um I think the 1203 00:48:36,480 --> 00:48:40,760 way you deal with that is you you work 1204 00:48:37,880 --> 00:48:42,359 on the problem and you make progress and 1205 00:48:40,760 --> 00:48:44,839 uh you know now it's gotten to the point 1206 00:48:42,359 --> 00:48:46,200 where um every other day there's another 1207 00:48:44,839 --> 00:48:47,920 company saying they're joining the 1208 00:48:46,200 --> 00:48:49,760 protein design Revolution and they're 1209 00:48:47,920 --> 00:48:51,599 going to be solving so you can go from 1210 00:48:49,760 --> 00:48:53,559 The Lunatic Fringe to the mainstream 1211 00:48:51,599 --> 00:48:55,839 faster than you might expect utterly 1212 00:48:53,559 --> 00:48:58,640 Vindicated weren't you I mean yeah it's 1213 00:48:55,839 --> 00:49:00,559 very right similar with you know I think 1214 00:48:58,640 --> 00:49:01,960 if you're fascinated enough and 1215 00:49:00,559 --> 00:49:03,280 passionate enough about the area you're 1216 00:49:01,960 --> 00:49:05,720 going to you know I was going to do it 1217 00:49:03,280 --> 00:49:06,760 no matter what you know and and actually 1218 00:49:05,720 --> 00:49:08,520 um I can't think of anything more 1219 00:49:06,760 --> 00:49:10,720 interesting to work on than than in the 1220 00:49:08,520 --> 00:49:12,400 nature of intelligence and and and 1221 00:49:10,720 --> 00:49:14,640 computation of you know computational 1222 00:49:12,400 --> 00:49:17,640 principles underpinning that and when we 1223 00:49:14,640 --> 00:49:19,319 started like Deep Mind in 2010 um nobody 1224 00:49:17,640 --> 00:49:22,160 was working on AI pretty much there was 1225 00:49:19,319 --> 00:49:25,960 some Yes except for very few people very 1226 00:49:22,160 --> 00:49:28,440 few fored people in in in in um in 1227 00:49:25,960 --> 00:49:30,480 Academia and uh and then now fast 1228 00:49:28,440 --> 00:49:31,920 forward 15 years which is not very much 1229 00:49:30,480 --> 00:49:33,359 time and obviously the whole world's 1230 00:49:31,920 --> 00:49:35,640 talking about it and certainly in 1231 00:49:33,359 --> 00:49:38,200 Industry no one was doing that in 2010 1232 00:49:35,640 --> 00:49:39,680 but we I we already foresaw um building 1233 00:49:38,200 --> 00:49:42,160 on you know the great work of people 1234 00:49:39,680 --> 00:49:43,839 like Professor Hinton that um uh this 1235 00:49:42,160 --> 00:49:45,319 would be one of the most consequential 1236 00:49:43,839 --> 00:49:46,960 transformative Technologies in the world 1237 00:49:45,319 --> 00:49:48,480 if it could be done and if it's that you 1238 00:49:46,960 --> 00:49:50,760 see something like that then it's worth 1239 00:49:48,480 --> 00:49:52,319 doing in its you know in of itself I 1240 00:49:50,760 --> 00:49:54,520 mean you Professor Hinton along with 1241 00:49:52,319 --> 00:49:58,200 your co-recipient of the physics Nobel 1242 00:49:54,520 --> 00:50:00,559 Prize professor John hopfield who is 91 1243 00:49:58,200 --> 00:50:03,920 a real Pioneer in this field of 1244 00:50:00,559 --> 00:50:06,000 Technology also I mean do does this what 1245 00:50:03,920 --> 00:50:08,799 you've just heard here resonate with you 1246 00:50:06,000 --> 00:50:10,599 that work that at one stage was seen as 1247 00:50:08,799 --> 00:50:12,880 being on The Lunatic Fringe and then 1248 00:50:10,599 --> 00:50:17,440 here you are years later 1249 00:50:12,880 --> 00:50:19,079 Vindicated uh yes so um people students 1250 00:50:17,440 --> 00:50:20,960 would apply to my department to work 1251 00:50:19,079 --> 00:50:22,720 with me and other professors in my 1252 00:50:20,960 --> 00:50:23,920 department would say oh if you work with 1253 00:50:22,720 --> 00:50:25,079 Hinton that's the end of your career 1254 00:50:23,920 --> 00:50:27,400 this stuff is 1255 00:50:25,079 --> 00:50:30,760 rubbish how did that make you feel I 1256 00:50:27,400 --> 00:50:33,760 mean did you still you luckily at the 1257 00:50:30,760 --> 00:50:33,760 time I didn't know about 1258 00:50:35,079 --> 00:50:40,559 it time I think for another question 1259 00:50:37,400 --> 00:50:43,760 from our audience and Mano dinakaran 1260 00:50:40,559 --> 00:50:45,079 from The kolinska Institute wants to ask 1261 00:50:43,760 --> 00:50:48,079 this what's your question thank you 1262 00:50:45,079 --> 00:50:50,760 Laurette um science is all about being 1263 00:50:48,079 --> 00:50:53,359 motivated when things don't go the way 1264 00:50:50,760 --> 00:50:55,880 we expect them to so what kept you all 1265 00:50:53,359 --> 00:50:57,760 motivated when things didn't go the way 1266 00:50:55,880 --> 00:51:00,200 you expected in times of hardship and 1267 00:50:57,760 --> 00:51:03,280 helped you adapt who'd like to pick it 1268 00:51:00,200 --> 00:51:05,400 up there that's that's the best bit that 1269 00:51:03,280 --> 00:51:07,359 when it doesn't when what you expected 1270 00:51:05,400 --> 00:51:08,520 to happen doesn't happen and then you 1271 00:51:07,359 --> 00:51:10,319 you really learn that's when you really 1272 00:51:08,520 --> 00:51:12,960 learn something I mean so that's the 1273 00:51:10,319 --> 00:51:15,880 best bit it's really crushing for the 1274 00:51:12,960 --> 00:51:18,720 first couple of days and then you then 1275 00:51:15,880 --> 00:51:20,520 you then then you like oh then oh now I 1276 00:51:18,720 --> 00:51:22,359 learned something that's like I didn't 1277 00:51:20,520 --> 00:51:24,359 understand that there is ascertainment 1278 00:51:22,359 --> 00:51:27,599 bias here cuz you have the people who've 1279 00:51:24,359 --> 00:51:30,000 gotten winning hands in the in the poker 1280 00:51:27,599 --> 00:51:33,160 game of life you 1281 00:51:30,000 --> 00:51:35,559 know right well gentlemen thanks to all 1282 00:51:33,160 --> 00:51:37,760 of you and renewed congratulations on 1283 00:51:35,559 --> 00:51:39,920 your Nobel prizes that saw from this 1284 00:51:37,760 --> 00:51:41,680 year's Nobel mindes from the Royal 1285 00:51:39,920 --> 00:51:43,720 Palace in Stockholm it's been a 1286 00:51:41,680 --> 00:51:46,040 privilege having this discussion with 1287 00:51:43,720 --> 00:51:47,839 you thank you to their Royal highnesses 1288 00:51:46,040 --> 00:51:49,680 the Crown Princess Victoria and Prince 1289 00:51:47,839 --> 00:51:51,799 Daniel for being with us of course 1290 00:51:49,680 --> 00:51:54,040 everybody else in the audience and you 1291 00:51:51,799 --> 00:51:56,240 also at home for watching from me Zay 1292 00:51:54,040 --> 00:51:59,880 abuwi and the rest of the Nobel Minds 1293 00:51:56,240 --> 00:51:59,880 team goodbye 1294 00:52:01,020 --> 00:52:10,810 [Applause] 1295 00:52:05,450 --> 00:52:13,910 [Music] 1296 00:52:10,810 --> 00:52:19,470 [Applause] 1297 00:52:13,910 --> 00:52:22,540 [Music] 1298 00:52:19,470 --> 00:52:22,540 [Applause]99258

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