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These are the user uploaded subtitles that are being translated: 1 00:00:11,208 --> 00:00:13,458 ♪ ♪ 2 00:00:13,542 --> 00:00:15,625 (car humming) 3 00:00:18,834 --> 00:00:20,500 (machine whirring) 4 00:00:20,583 --> 00:00:23,917 (hydraulic hissing) 5 00:00:26,875 --> 00:00:29,792 (hydraulic whirring) 6 00:00:29,875 --> 00:00:33,000 (alarm blaring) 7 00:00:36,208 --> 00:00:39,291 (siren wailing) 8 00:00:40,792 --> 00:00:42,750 (beeping) 9 00:00:46,083 --> 00:00:49,750 (in robotic voice): This is the story of automation, 10 00:00:49,834 --> 00:00:54,000 and of the people lost in the process. 11 00:00:55,250 --> 00:00:59,375 Our story begins in a small town in Germany. 12 00:00:59,458 --> 00:01:02,959 ♪ ♪ 13 00:01:03,041 --> 00:01:05,792 (distant siren wailing) 14 00:01:09,750 --> 00:01:11,500 (whirring) 15 00:01:16,625 --> 00:01:18,917 ♪ ♪ 16 00:01:19,000 --> 00:01:21,125 (men speaking German) 17 00:01:33,000 --> 00:01:34,792 (crackling) 18 00:01:39,083 --> 00:01:41,208 (man speaking German) 19 00:01:49,667 --> 00:01:51,041 (crackles) 20 00:02:22,041 --> 00:02:25,667 ♪ ♪ 21 00:02:30,083 --> 00:02:31,542 (beeping) 22 00:02:36,875 --> 00:02:39,250 Sven Kühling: It was quite a normal day at my office, 23 00:02:39,333 --> 00:02:42,583 and I heard from an informant 24 00:02:42,667 --> 00:02:45,834 that an accident had happened, 25 00:02:45,917 --> 00:02:47,834 and I had to call 26 00:02:47,917 --> 00:02:51,208 the spokesman of the Volkswagen factory. 27 00:02:51,291 --> 00:02:53,000 (ticking) 28 00:02:53,083 --> 00:02:54,583 ♪ ♪ 29 00:02:58,792 --> 00:03:00,417 (beeping) 30 00:03:02,083 --> 00:03:05,500 We have the old sentence, we journalists, 31 00:03:05,583 --> 00:03:08,709 "Dog bites a man or a man bites a dog." 32 00:03:08,792 --> 00:03:12,917 What's the news? So, here is the same. 33 00:03:13,000 --> 00:03:17,208 A man bites a dog, a robot killed a man. 34 00:03:17,291 --> 00:03:20,125 (ticking continues) 35 00:03:24,792 --> 00:03:26,500 (beeping) 36 00:03:29,792 --> 00:03:32,834 The spokesman said that the accident happened, 37 00:03:32,917 --> 00:03:35,875 but then he paused for a moment. 38 00:03:35,959 --> 00:03:37,875 So, I... 39 00:03:37,959 --> 00:03:41,875 think he didn't want to say much more. 40 00:03:41,959 --> 00:03:44,083 ♪ ♪ 41 00:03:49,000 --> 00:03:51,709 (rattling) 42 00:03:51,792 --> 00:03:52,709 (beeps) 43 00:03:52,792 --> 00:03:54,500 (man speaking German) 44 00:04:13,834 --> 00:04:15,458 ♪ ♪ 45 00:04:15,542 --> 00:04:19,333 Kühling: The young worker installed a robot cage, 46 00:04:20,000 --> 00:04:22,917 and he told his colleague 47 00:04:23,000 --> 00:04:25,417 to start the robot. 48 00:04:25,500 --> 00:04:27,166 ♪ ♪ 49 00:04:29,500 --> 00:04:32,333 (whirring, clanking) 50 00:04:34,000 --> 00:04:36,917 The robot took the man 51 00:04:37,000 --> 00:04:41,375 and pressed him against a metal wall, 52 00:04:41,458 --> 00:04:44,875 so his chest was crushed. 53 00:04:52,333 --> 00:04:54,667 (whirring, beeping) 54 00:04:54,750 --> 00:04:57,959 (hissing) 55 00:04:58,041 --> 00:05:01,166 ♪ ♪ 56 00:05:04,375 --> 00:05:06,333 (beeping) 57 00:05:18,083 --> 00:05:19,583 (speaking German) 58 00:06:00,625 --> 00:06:02,166 ♪ ♪ 59 00:06:02,250 --> 00:06:05,875 Kodomoroid: The dead man's identity was never made public. 60 00:06:06,417 --> 00:06:09,917 The investigation remained open for years. 61 00:06:10,917 --> 00:06:12,792 Production continued. 62 00:06:13,834 --> 00:06:17,291 (metronome ticking) 63 00:06:17,375 --> 00:06:18,959 (speaking German) 64 00:06:24,834 --> 00:06:29,250 Kodomoroid: Automation of labor made humans more robotic. 65 00:06:43,250 --> 00:06:45,792 (ticking continuing) 66 00:06:51,291 --> 00:06:53,333 (man 1 speaking German) 67 00:07:05,542 --> 00:07:07,500 (man 2 speaking German) 68 00:07:16,000 --> 00:07:18,000 (man 1 speaking) 69 00:07:39,709 --> 00:07:42,750 ♪ ♪ 70 00:07:44,375 --> 00:07:45,542 (beeping) 71 00:07:50,375 --> 00:07:52,458 Kodomoroid: A robot is a machine 72 00:07:52,542 --> 00:07:55,166 that operates automatically, 73 00:07:55,250 --> 00:07:57,500 with human-like skill. 74 00:07:58,375 --> 00:08:00,834 The term derives from the Czech words 75 00:08:00,917 --> 00:08:03,333 for worker and slave. 76 00:08:08,000 --> 00:08:09,834 (whirring) 77 00:08:30,000 --> 00:08:32,583 (drill whirring) 78 00:08:38,375 --> 00:08:40,458 (drill whirring) 79 00:08:42,875 --> 00:08:44,917 ♪ ♪ 80 00:08:52,792 --> 00:08:54,750 Hey, Annie. 81 00:08:54,834 --> 00:08:56,792 (whirring) 82 00:09:02,291 --> 00:09:03,917 (whirring) 83 00:09:05,792 --> 00:09:07,500 (beeping) 84 00:09:14,917 --> 00:09:18,417 Walter: Well, we are engineers, and we are really not emotional guys. 85 00:09:18,834 --> 00:09:21,041 But sometimes Annie does something funny, 86 00:09:21,125 --> 00:09:25,333 and that, of course, invokes some amusement. 87 00:09:25,417 --> 00:09:27,875 Especially when Annie happens to press 88 00:09:27,959 --> 00:09:30,959 one of the emergency stop buttons by herself 89 00:09:31,041 --> 00:09:33,375 and is then incapacitated. 90 00:09:34,709 --> 00:09:36,625 We have some memories 91 00:09:36,709 --> 00:09:39,709 of that happening in situations... 92 00:09:40,834 --> 00:09:44,000 and this was-- we have quite a laugh. 93 00:09:45,041 --> 00:09:46,834 -(whirring) -Okay. 94 00:09:48,333 --> 00:09:51,750 Kodomoroid: We became better at learning by example. 95 00:09:51,834 --> 00:09:53,041 ♪ ♪ 96 00:09:53,125 --> 00:09:56,625 You could simply show us how to do something. 97 00:09:56,709 --> 00:09:58,834 (Walter speaks German) 98 00:10:07,041 --> 00:10:09,625 Walter: When you are an engineer in the field of automation, 99 00:10:09,709 --> 00:10:11,834 you may face problems with workers. 100 00:10:11,917 --> 00:10:14,208 Sometimes, they get angry at you 101 00:10:14,291 --> 00:10:17,250 just by seeing you somewhere, and shout at you, 102 00:10:17,333 --> 00:10:18,834 "You are taking my job away." 103 00:10:18,917 --> 00:10:21,375 "What? I'm not here to take away your job." 104 00:10:22,500 --> 00:10:26,333 But, yeah, sometimes you get perceived that way. 105 00:10:26,417 --> 00:10:27,875 But, I think, 106 00:10:27,959 --> 00:10:31,083 in the field of human-robot collaboration, where... 107 00:10:31,166 --> 00:10:34,291 we actually are working at the moment, 108 00:10:34,375 --> 00:10:36,542 mostly is... 109 00:10:36,625 --> 00:10:38,458 human-robot collaboration is a thing 110 00:10:38,542 --> 00:10:40,375 where we don't want to replace a worker. 111 00:10:40,458 --> 00:10:42,000 We want to support workers, 112 00:10:42,083 --> 00:10:43,667 and we want to, yeah... 113 00:10:44,583 --> 00:10:46,000 to, yeah... 114 00:10:46,083 --> 00:10:48,208 (machinery rumbling) 115 00:10:48,875 --> 00:10:50,709 (latches clinking) 116 00:10:53,041 --> 00:10:54,709 (workers conversing indistinctly) 117 00:10:58,125 --> 00:10:59,792 (machine hisses) 118 00:11:02,208 --> 00:11:03,500 (clicks) 119 00:11:03,583 --> 00:11:04,917 (hissing) 120 00:11:06,458 --> 00:11:08,583 ♪ ♪ 121 00:11:17,417 --> 00:11:20,375 Kodomoroid: In order to work alongside you, 122 00:11:20,458 --> 00:11:22,834 we needed to know which lines 123 00:11:22,917 --> 00:11:25,542 we could not cross. 124 00:11:27,750 --> 00:11:30,083 (whirring) 125 00:11:30,250 --> 00:11:31,917 (typing) 126 00:11:35,083 --> 00:11:37,166 (thudding) 127 00:11:37,250 --> 00:11:39,291 Stop. Stop. Stop. 128 00:11:40,959 --> 00:11:42,458 (thuds) 129 00:11:45,500 --> 00:11:47,083 Hi, I'm Simon Borgen. 130 00:11:47,166 --> 00:11:50,041 We are with Dr. Isaac Asimov, 131 00:11:50,125 --> 00:11:52,542 a biochemist, who may be the most widely read 132 00:11:52,625 --> 00:11:54,667 of all science fiction writers. 133 00:11:55,792 --> 00:11:57,083 ♪ ♪ 134 00:11:57,166 --> 00:11:58,875 Kodomoroid: In 1942, 135 00:11:58,959 --> 00:12:02,500 Isaac Asimov created a set of guidelines 136 00:12:02,583 --> 00:12:05,083 to protect human society. 137 00:12:05,959 --> 00:12:09,250 The first law was that a robot couldn't hurt a human being, 138 00:12:09,333 --> 00:12:10,709 or, through inaction, 139 00:12:10,792 --> 00:12:12,875 allow a human being to come to harm. 140 00:12:12,959 --> 00:12:16,125 The second law was that a robot had to obey 141 00:12:16,208 --> 00:12:18,125 orders given it by human beings, 142 00:12:18,208 --> 00:12:20,959 provided that didn't conflict with the first law. 143 00:12:21,041 --> 00:12:22,750 Scientists say that when robots are built, 144 00:12:22,834 --> 00:12:25,083 that they may be built according to these laws, 145 00:12:25,166 --> 00:12:27,542 and also that almost all science fiction writers 146 00:12:27,625 --> 00:12:30,542 have adopted them as well in their stories. 147 00:12:31,333 --> 00:12:33,000 (whirring) 148 00:12:34,709 --> 00:12:38,333 Sami Haddadin: It's not just a statement from a science fiction novel. 149 00:12:38,750 --> 00:12:40,625 My dissertation's name was actually, 150 00:12:40,709 --> 00:12:41,834 Towards Safe Robots, 151 00:12:41,917 --> 00:12:43,750 Approaching Asimov's First Law. 152 00:12:43,834 --> 00:12:46,166 How can we make robots really fundamentally safe, 153 00:12:46,250 --> 00:12:49,750 according to Isaac Asimov's first law. 154 00:12:50,375 --> 00:12:53,041 There was this accident where a human worker 155 00:12:53,125 --> 00:12:55,000 got crushed by industrial robot. 156 00:12:55,875 --> 00:12:57,583 I was immediately thinking that 157 00:12:57,667 --> 00:13:00,333 the robot is an industrial, classical robot, 158 00:13:00,417 --> 00:13:03,542 not able to sense contact, not able to interact. 159 00:13:03,625 --> 00:13:05,208 Is this a robot 160 00:13:05,291 --> 00:13:07,709 that we, kind of, want to collaborate with? 161 00:13:07,792 --> 00:13:10,000 No, it's not. It's inherently forbidden. 162 00:13:10,083 --> 00:13:11,333 We put them behind cages. 163 00:13:11,417 --> 00:13:12,834 We don't want to interact with them. 164 00:13:12,917 --> 00:13:15,583 We put them behind cages because they are dangerous, 165 00:13:15,667 --> 00:13:17,458 because they are inherently unsafe. 166 00:13:17,542 --> 00:13:19,250 (whirring) 167 00:13:21,667 --> 00:13:23,500 (clatters) 168 00:13:25,542 --> 00:13:27,083 More than 10 years ago, 169 00:13:27,166 --> 00:13:30,542 I did the first experiments in really understanding, uh, 170 00:13:30,625 --> 00:13:33,291 what does it mean if a robot hits a human. 171 00:13:33,375 --> 00:13:35,417 -(grunts) -(laughter) 172 00:13:36,000 --> 00:13:38,709 I put myself as the first guinea pig. 173 00:13:39,375 --> 00:13:40,792 I didn't want to go through 174 00:13:40,875 --> 00:13:42,709 all the legal authorities. 175 00:13:42,792 --> 00:13:44,834 I just wanted to know it, and that night, 176 00:13:44,917 --> 00:13:46,834 I decided at 6:00 p.m., 177 00:13:46,917 --> 00:13:48,917 when everybody's gone, I'm gonna do these experiments. 178 00:13:49,000 --> 00:13:52,625 And I took one of the students to activate the camera, 179 00:13:52,709 --> 00:13:54,000 and then I just did it. 180 00:13:54,083 --> 00:13:55,959 ♪ ♪ 181 00:13:58,500 --> 00:14:00,417 -(smacks) -(laughing) 182 00:14:02,250 --> 00:14:03,750 (whirring) 183 00:14:03,834 --> 00:14:06,875 A robot needs to understand what does it mean to be safe, 184 00:14:06,959 --> 00:14:09,333 what is it that potentially could harm a human being, 185 00:14:09,417 --> 00:14:11,542 and therefore, prevent that. 186 00:14:11,625 --> 00:14:14,291 So, the next generation of robots that is now out there, 187 00:14:14,375 --> 00:14:17,291 is fundamentally designed for interaction. 188 00:14:18,208 --> 00:14:20,709 (whirring, clicking) 189 00:14:25,750 --> 00:14:27,125 (laughs) 190 00:14:31,458 --> 00:14:35,125 Kodomoroid: Eventually, it was time to leave our cages. 191 00:14:36,291 --> 00:14:39,125 ♪ ♪ 192 00:14:41,583 --> 00:14:43,500 (whirring) 193 00:14:47,834 --> 00:14:49,458 (beeping) 194 00:14:57,125 --> 00:14:58,959 (beeping) 195 00:15:00,333 --> 00:15:01,917 Nourbakhsh: Techno-optimism is when we decide 196 00:15:02,000 --> 00:15:03,208 to solve our problem with technology. 197 00:15:03,291 --> 00:15:05,291 Then we turn our attention to the technology, 198 00:15:05,375 --> 00:15:07,250 and we pay so much attention to the technology, 199 00:15:07,333 --> 00:15:09,333 we stop caring about the sociological issue 200 00:15:09,417 --> 00:15:11,458 we were trying to solve in the first place. 201 00:15:11,542 --> 00:15:13,375 We'll innovate our way out of the problems. 202 00:15:13,458 --> 00:15:16,709 Like, whether it's agriculture or climate change or whatever, terrorism. 203 00:15:16,792 --> 00:15:19,500 ♪ ♪ 204 00:15:25,834 --> 00:15:27,667 If you think about where robotic automation 205 00:15:27,750 --> 00:15:29,917 and employment displacement starts, 206 00:15:30,000 --> 00:15:32,583 it basically goes back to industrial automation 207 00:15:32,667 --> 00:15:34,250 that was grand, large-scale. 208 00:15:34,333 --> 00:15:36,083 Things like welding machines for cars, 209 00:15:36,166 --> 00:15:38,583 that can move far faster than a human arm can move. 210 00:15:38,667 --> 00:15:41,709 So, they're doing a job that increases the rate 211 00:15:41,792 --> 00:15:43,792 at which the assembly line can make cars. 212 00:15:43,875 --> 00:15:45,417 It displaces some people, 213 00:15:45,500 --> 00:15:48,250 but it massively increases the GDP of the country 214 00:15:48,333 --> 00:15:50,291 because productivity goes up because the machines are 215 00:15:50,375 --> 00:15:53,166 so much higher in productivity terms than the people. 216 00:15:54,709 --> 00:15:58,291 Narrator: These giant grasshopper-lookig devices work all by themselves 217 00:15:58,375 --> 00:16:00,542 on an automobile assembly line. 218 00:16:00,625 --> 00:16:02,166 They never complain about the heat 219 00:16:02,250 --> 00:16:04,333 or about the tedium of the job. 220 00:16:05,458 --> 00:16:08,291 Nourbakhsh: Fast-forward to today, and it's a different dynamic. 221 00:16:08,375 --> 00:16:10,667 (grinding) 222 00:16:10,750 --> 00:16:13,125 You can buy milling machine robots 223 00:16:13,208 --> 00:16:15,417 that can do all the things a person can do, 224 00:16:15,500 --> 00:16:19,041 but the milling machine robot only costs $30,000. 225 00:16:20,000 --> 00:16:22,375 We're talking about machines now that are so cheap, 226 00:16:22,458 --> 00:16:24,083 that they do exactly what a human does, 227 00:16:24,166 --> 00:16:26,458 with less money, even in six months, 228 00:16:26,542 --> 00:16:27,792 than the human costs. 229 00:16:27,875 --> 00:16:30,375 ♪ ♪ 230 00:16:44,583 --> 00:16:46,750 (Wu Huifen speaking Chinese) 231 00:17:20,792 --> 00:17:23,667 (whirring) 232 00:17:23,750 --> 00:17:26,792 ♪ ♪ 233 00:17:36,959 --> 00:17:38,291 (beeping) 234 00:18:41,208 --> 00:18:44,500 ♪ ♪ 235 00:18:48,792 --> 00:18:52,625 Kodomoroid: After the first wave of industrial automation, 236 00:18:52,709 --> 00:18:55,625 the remaining manufacturing jobs 237 00:18:55,709 --> 00:18:59,208 required fine motor skills. 238 00:19:21,709 --> 00:19:24,750 (bell ringing) 239 00:19:27,583 --> 00:19:29,875 -(indistinct chatter) -(ringing continuing) 240 00:19:35,083 --> 00:19:36,917 (beeping, chimes) 241 00:19:42,166 --> 00:19:44,208 (beeping, chimes) 242 00:19:45,875 --> 00:19:50,458 Kodomoroid: We helped factory owners monitor their workers. 243 00:19:50,542 --> 00:19:51,583 (beeping) 244 00:19:52,750 --> 00:19:53,875 (beeping) 245 00:19:56,625 --> 00:19:58,333 ♪ ♪ 246 00:19:58,417 --> 00:19:59,417 (beeping) 247 00:20:01,959 --> 00:20:03,291 (beeping) 248 00:20:09,959 --> 00:20:10,959 (beeping) 249 00:20:20,417 --> 00:20:21,667 (sizzling) 250 00:20:25,583 --> 00:20:27,792 (Li Zheng speaking Chinese) 251 00:20:48,208 --> 00:20:50,333 ♪ ♪ 252 00:21:05,542 --> 00:21:07,166 (beeping) 253 00:21:15,834 --> 00:21:18,000 (whirring) 254 00:22:12,917 --> 00:22:14,834 (sizzling) 255 00:22:15,583 --> 00:22:19,625 Kodomoroid: Your advantage in precision was temporary. 256 00:22:19,709 --> 00:22:21,750 ♪ ♪ 257 00:22:22,917 --> 00:22:26,375 We took over the complex tasks. 258 00:22:30,834 --> 00:22:34,208 You moved to the end of the production line. 259 00:22:34,792 --> 00:22:37,458 ♪ ♪ 260 00:22:54,417 --> 00:22:55,500 (beeping) 261 00:23:01,291 --> 00:23:02,625 (beeping) 262 00:23:06,417 --> 00:23:08,959 (indistinct chatter) 263 00:23:15,583 --> 00:23:18,625 (music playing on speaker) 264 00:23:22,667 --> 00:23:24,792 (man speaking in Chinese) 265 00:23:35,000 --> 00:23:37,125 (woman speaking Chinese) 266 00:23:46,625 --> 00:23:50,291 (man speaking on speaker) 267 00:23:59,667 --> 00:24:01,792 (man speaking Chinese) 268 00:24:15,875 --> 00:24:17,875 ♪ ♪ 269 00:24:17,959 --> 00:24:20,083 (Luo Jun speaking Chinese) 270 00:24:34,750 --> 00:24:36,375 (beeping) 271 00:24:37,166 --> 00:24:38,667 (chickens clucking) 272 00:24:43,542 --> 00:24:45,583 (chickens clucking) 273 00:24:55,250 --> 00:24:57,625 ♪ ♪ 274 00:25:03,917 --> 00:25:06,041 ♪ ♪ 275 00:25:06,750 --> 00:25:08,917 (woman speaking Chinese) 276 00:25:25,625 --> 00:25:27,250 (indistinct chatter) 277 00:25:32,583 --> 00:25:35,750 ♪ ♪ 278 00:25:38,375 --> 00:25:40,667 (Wang Chao speaking Chinese) 279 00:25:58,667 --> 00:26:00,792 (beeping) 280 00:26:21,208 --> 00:26:23,834 ♪ ♪ 281 00:26:44,667 --> 00:26:47,166 (buzzing) 282 00:26:51,875 --> 00:26:54,917 Automation of the service sector 283 00:26:55,000 --> 00:26:58,875 required your trust and cooperation. 284 00:27:00,375 --> 00:27:03,834 Man: Here we are, stop-and-go traffic on 271, and-- 285 00:27:03,917 --> 00:27:07,041 Ah, geez, the car's doing it all itself. 286 00:27:07,125 --> 00:27:09,500 What am I gonna do with my hands down here? 287 00:27:09,583 --> 00:27:11,500 (beeping) 288 00:27:18,875 --> 00:27:19,750 (beeps) 289 00:27:19,834 --> 00:27:21,875 And now, it's on autosteer. 290 00:27:22,542 --> 00:27:25,375 So, now I've gone completely hands-free. 291 00:27:25,875 --> 00:27:28,625 In the center area here is where the big deal is. 292 00:27:28,709 --> 00:27:30,792 This icon up to the left is my TACC, 293 00:27:30,875 --> 00:27:33,041 the Traffic-Aware Cruise Control. 294 00:27:36,000 --> 00:27:38,208 It does a great job of keeping you in the lane, 295 00:27:38,291 --> 00:27:39,625 and driving down the road, 296 00:27:39,709 --> 00:27:41,709 and keeping you safe, and all that kind of stuff, 297 00:27:41,792 --> 00:27:43,917 watching all the other cars. 298 00:27:45,041 --> 00:27:47,542 Autosteer is probably going to do very, very poorly. 299 00:27:47,625 --> 00:27:50,458 I'm in a turn that's very sharp. 300 00:27:50,542 --> 00:27:52,750 -(beeping) -And, yep, it said take control. 301 00:27:55,834 --> 00:27:57,917 (horn honking) 302 00:27:58,917 --> 00:28:01,125 -(Twitter whistles) -(indistinct video audio) 303 00:28:12,125 --> 00:28:14,166 (phone ringing) 304 00:28:14,250 --> 00:28:16,834 Operator (on phone): 911, what is the address of your emergency? 305 00:28:16,917 --> 00:28:18,375 Man (on phone): There was just a wreck. 306 00:28:18,458 --> 00:28:20,625 A head-on collision right here-- Oh my God almighty. 307 00:28:21,250 --> 00:28:23,458 Operator: Okay, sir, you're on 27? 308 00:28:23,542 --> 00:28:24,375 Man: Yes, sir. 309 00:28:24,458 --> 00:28:27,000 ♪ ♪ 310 00:28:33,667 --> 00:28:36,667 Bobby Vankaveelar: I had just got to work, clocked in. 311 00:28:36,750 --> 00:28:38,709 They get a phone call from my sister, 312 00:28:38,792 --> 00:28:40,709 telling me there was a horrific accident. 313 00:28:40,792 --> 00:28:44,083 That there was somebody deceased in the front yard. 314 00:28:44,500 --> 00:28:45,583 (beeping) 315 00:28:46,417 --> 00:28:49,750 The Tesla was coming down the hill of highway 27. 316 00:28:49,834 --> 00:28:52,792 The sensor didn't read the object in front of them, 317 00:28:52,875 --> 00:28:56,583 which was the, um, semi-trailer. 318 00:28:56,667 --> 00:28:58,959 ♪ ♪ 319 00:29:04,959 --> 00:29:07,291 The Tesla went right through the fence 320 00:29:07,375 --> 00:29:10,750 that borders the highway, through to the retention pond, 321 00:29:10,834 --> 00:29:13,000 then came through this side of the fence, 322 00:29:13,083 --> 00:29:15,125 that borders my home. 323 00:29:17,250 --> 00:29:20,375 (police radio chatter) 324 00:29:22,000 --> 00:29:24,583 So, I parked right near here 325 00:29:24,667 --> 00:29:26,625 before I was asked not to go any further. 326 00:29:26,709 --> 00:29:28,417 I don't wanna see 327 00:29:28,500 --> 00:29:30,583 what's in the veh-- you know, what's in the vehicle. 328 00:29:30,667 --> 00:29:32,250 You know, what had happened to him. 329 00:29:32,333 --> 00:29:34,875 ♪ ♪ 330 00:29:46,959 --> 00:29:48,667 (scanner beeping) 331 00:29:55,583 --> 00:29:58,041 (indistinct chatter) 332 00:29:59,166 --> 00:30:01,291 Donley: After the police officer come, they told me, 333 00:30:01,375 --> 00:30:03,875 about 15 minutes after he was here, that it was a Tesla. 334 00:30:03,959 --> 00:30:05,792 It was one of the autonomous cars, 335 00:30:05,875 --> 00:30:10,500 um, and that they were investigating why it did not pick up 336 00:30:10,583 --> 00:30:12,792 or register that there was a semi in front of it, 337 00:30:12,875 --> 00:30:15,000 you know, and start braking, 'cause it didn't even-- 338 00:30:15,083 --> 00:30:17,917 You could tell from the frameway up on top of the hill it didn't even... 339 00:30:18,583 --> 00:30:20,959 It didn't even recognize that there was anything in front of it. 340 00:30:21,041 --> 00:30:23,041 It thought it was open road. 341 00:30:25,250 --> 00:30:28,500 Donley: You might have an opinion on a Tesla accident we had out here. 342 00:30:28,583 --> 00:30:30,709 (man speaking) 343 00:30:33,917 --> 00:30:36,000 It was bad, that's for sure. 344 00:30:36,083 --> 00:30:38,500 I think people just rely too much on the technology 345 00:30:38,583 --> 00:30:41,083 and don't pay attention themselves, you know, 346 00:30:41,166 --> 00:30:42,834 to what's going on around them. 347 00:30:42,917 --> 00:30:46,834 Like, since, like him, he would've known that there was an issue 348 00:30:46,917 --> 00:30:51,834 if he wasn't relying on the car to drive while he was watching a movie. 349 00:30:51,917 --> 00:30:54,000 The trooper had told me that the driver 350 00:30:54,083 --> 00:30:55,917 had been watching Harry Potter, 351 00:30:56,000 --> 00:30:57,959 you know, at the time of the accident. 352 00:30:58,041 --> 00:31:01,000 ♪ ♪ 353 00:31:01,083 --> 00:31:03,583 A news crew from Tampa, Florida, knocked on the door, said, 354 00:31:03,667 --> 00:31:06,542 "This is where the accident happened with the Tesla?" 355 00:31:06,625 --> 00:31:08,208 I said, "Yes, sir." 356 00:31:08,291 --> 00:31:12,041 And he goes, "Do you know what the significance is in this accident?" 357 00:31:12,125 --> 00:31:14,000 And I said, "No, I sure don't." 358 00:31:14,083 --> 00:31:17,959 And he said, "It's the very first death, ever, in a driverless car." 359 00:31:19,083 --> 00:31:21,792 I said, "Is it anybody local?" 360 00:31:21,875 --> 00:31:24,750 And he goes, "Nobody around here drives a Tesla." 361 00:31:24,834 --> 00:31:28,291 Newsman: ...a deadly crash that's raising safety concerns 362 00:31:28,375 --> 00:31:29,834 for everyone in Florida. 363 00:31:29,917 --> 00:31:31,542 Newswoman: It comes as the state is pushing 364 00:31:31,625 --> 00:31:34,542 to become the nation's testbed for driverless cars. 365 00:31:34,625 --> 00:31:36,208 Newsman: Tesla releasing a statement 366 00:31:36,291 --> 00:31:38,875 that cars in autopilot have safely driven 367 00:31:38,959 --> 00:31:41,500 more than 130 million miles. 368 00:31:41,583 --> 00:31:43,208 Paluska: ABC Action News reporter Michael Paluska, 369 00:31:43,291 --> 00:31:46,458 in Williston, Florida, tonight, digging for answers. 370 00:31:51,625 --> 00:31:52,959 (beeping) 371 00:31:56,083 --> 00:31:58,125 Paluska: Big takeaway for me at the scene was 372 00:31:58,208 --> 00:31:59,750 it just didn't stop. 373 00:31:59,834 --> 00:32:02,333 It was driving down the road, 374 00:32:02,417 --> 00:32:05,083 with the entire top nearly sheared off, 375 00:32:05,166 --> 00:32:06,375 with the driver dead 376 00:32:06,458 --> 00:32:08,542 after he hit the truck at 74 mph. 377 00:32:08,625 --> 00:32:11,959 Why did the vehicle not have an automatic shutoff? 378 00:32:12,041 --> 00:32:14,083 ♪ ♪ 379 00:32:14,166 --> 00:32:15,417 That was my big question, 380 00:32:15,500 --> 00:32:16,959 one of the questions we asked Tesla, 381 00:32:17,041 --> 00:32:18,667 that didn't get answered. 382 00:32:19,458 --> 00:32:21,625 All of the statements from Tesla were that 383 00:32:21,709 --> 00:32:24,375 they're advancing the autopilot system, 384 00:32:24,458 --> 00:32:26,625 but everything was couched 385 00:32:26,709 --> 00:32:29,792 with the fact that if one percent of accidents drop 386 00:32:29,875 --> 00:32:32,458 because that's the way the autopilot system works, 387 00:32:32,542 --> 00:32:33,709 then that's a win. 388 00:32:33,792 --> 00:32:35,834 They kind of missed the mark, 389 00:32:35,917 --> 00:32:37,917 really honoring Joshua Brown's life, 390 00:32:38,000 --> 00:32:39,458 and the fact that he died driving a car 391 00:32:39,542 --> 00:32:41,291 that he thought was going to keep him safe, 392 00:32:41,375 --> 00:32:44,875 at least safer than the car that I'm driving, 393 00:32:45,208 --> 00:32:47,291 which is a dumb car. 394 00:32:47,375 --> 00:32:49,625 ♪ ♪ 395 00:32:49,709 --> 00:32:52,875 Vankaveelar: To be okay with letting 396 00:32:52,959 --> 00:32:55,250 a machine... 397 00:32:55,333 --> 00:32:56,834 take you from point A to point B, 398 00:32:56,917 --> 00:32:59,792 and then you actually get used to 399 00:32:59,875 --> 00:33:02,208 getting from point A to point B okay, 400 00:33:02,959 --> 00:33:05,583 it-- you get, your mind gets a little bit-- 401 00:33:05,667 --> 00:33:07,250 it's just my opinion, okay-- 402 00:33:07,333 --> 00:33:10,750 you just, your mind gets lazier each time. 403 00:33:12,625 --> 00:33:15,125 Kodomoroid: The accident was written off 404 00:33:15,208 --> 00:33:17,750 as a case of human error. 405 00:33:18,250 --> 00:33:19,583 (beeping) 406 00:33:20,583 --> 00:33:23,542 Former centers of manufacturing became 407 00:33:23,625 --> 00:33:27,709 the testing grounds for the new driverless taxis. 408 00:33:28,917 --> 00:33:31,250 ♪ ♪ 409 00:33:34,125 --> 00:33:35,583 Nourbakhsh: If you think about what happens 410 00:33:35,667 --> 00:33:36,959 when an autonomous car hits somebody, 411 00:33:37,041 --> 00:33:39,417 it gets really complicated. 412 00:33:41,375 --> 00:33:42,875 The car company's gonna get sued. 413 00:33:42,959 --> 00:33:44,500 The sensor-maker's gonna get sued 414 00:33:44,583 --> 00:33:46,291 because they made the sensor on the robot. 415 00:33:46,375 --> 00:33:49,333 The regulatory framework is always gonna be behind, 416 00:33:49,417 --> 00:33:52,375 because robot invention happens faster 417 00:33:52,458 --> 00:33:54,500 than lawmakers can think. 418 00:33:55,625 --> 00:33:57,542 Newswoman: One of Uber's self-driving vehicles 419 00:33:57,625 --> 00:33:59,000 killed a pedestrian. 420 00:33:59,083 --> 00:34:01,000 The vehicle was in autonomous mode, 421 00:34:01,083 --> 00:34:04,792 with an operator behind the wheel when the woman was hit. 422 00:34:06,375 --> 00:34:10,083 Newswoman 2: Tonight, Tesla confirming this car was in autopilot mode 423 00:34:10,166 --> 00:34:13,709 when it crashed in Northern California, killing the driver, 424 00:34:13,792 --> 00:34:16,166 going on to blame that highway barrier 425 00:34:16,250 --> 00:34:18,792 that's meant to reduce impact. 426 00:34:20,875 --> 00:34:24,083 Kodomoroid: After the first self-driving car deaths, 427 00:34:24,166 --> 00:34:27,625 testing of the new taxis was suspended. 428 00:34:28,959 --> 00:34:31,250 Nourbakhsh: It's interesting when you look at driverless cars. 429 00:34:31,333 --> 00:34:33,291 You see the same kinds of value arguments. 430 00:34:33,375 --> 00:34:35,333 30,000 people die every year, 431 00:34:35,417 --> 00:34:37,208 runoff road accidents in the US alone. 432 00:34:37,291 --> 00:34:38,709 So, don't we wanna save all those lives? 433 00:34:38,792 --> 00:34:40,750 Let's have cars drive instead. 434 00:34:40,834 --> 00:34:42,125 Now, you have to start thinking 435 00:34:42,208 --> 00:34:44,458 about the side effects on society. 436 00:34:45,333 --> 00:34:48,041 Are we getting rid of every taxi driver in America? 437 00:34:50,333 --> 00:34:53,458 Our driver partners are the heart and soul of this company 438 00:34:53,917 --> 00:34:57,500 and the only reason we've come this far in just five years. 439 00:34:58,542 --> 00:35:00,417 Nourbakhsh: If you look at Uber's first five years, 440 00:35:00,500 --> 00:35:02,500 they're actually empowering people. 441 00:35:02,583 --> 00:35:05,291 But when the same company does really hardcore research 442 00:35:05,375 --> 00:35:07,208 to now replace all those people, 443 00:35:07,291 --> 00:35:09,125 so they don't need them anymore, 444 00:35:09,208 --> 00:35:10,500 then what you're seeing is 445 00:35:10,583 --> 00:35:12,500 they're already a highly profitable company, 446 00:35:12,583 --> 00:35:15,166 but they simply want to increase that profit. 447 00:35:17,500 --> 00:35:19,375 (beeping) 448 00:35:27,500 --> 00:35:29,333 (beeping) 449 00:35:32,959 --> 00:35:35,959 Kodomoroid: Eventually, testing resumed. 450 00:35:36,625 --> 00:35:41,000 Taxi drivers' wages became increasingly unstable. 451 00:35:43,250 --> 00:35:46,500 Newsman: Police say a man drove up to a gate outside city hall 452 00:35:46,583 --> 00:35:48,542 and shot himself in the head. 453 00:35:48,625 --> 00:35:51,208 Newswoman: He left a note saying services such as Uber 454 00:35:51,291 --> 00:35:53,625 had financially ruined his life. 455 00:35:53,709 --> 00:35:56,208 Newsman: Uber and other mobile app services 456 00:35:56,291 --> 00:35:58,500 have made a once well-paying industry 457 00:35:58,583 --> 00:36:01,667 into a mass of long hours, low pay, 458 00:36:01,750 --> 00:36:03,917 and economic insecurity. 459 00:36:04,583 --> 00:36:07,041 ♪ ♪ 460 00:36:10,625 --> 00:36:14,583 Kodomoroid: Drivers were the biggest part of the service economy. 461 00:36:16,917 --> 00:36:18,750 (beeping) 462 00:36:21,125 --> 00:36:22,625 Brandon Ackerman: My father, he drove. 463 00:36:22,709 --> 00:36:23,709 My uncle drove. 464 00:36:23,792 --> 00:36:26,417 I kind of grew up into trucking. 465 00:36:29,583 --> 00:36:31,750 Some of the new technology that came out 466 00:36:31,834 --> 00:36:34,709 is taking a lot of the freedom of the job away. 467 00:36:35,792 --> 00:36:37,417 It's more stressful. 468 00:36:38,917 --> 00:36:41,333 Kodomoroid: Automation of trucking began 469 00:36:41,417 --> 00:36:43,458 with monitoring the drivers 470 00:36:43,542 --> 00:36:45,667 and simplifying their job. 471 00:36:46,875 --> 00:36:49,458 There's a radar system. 472 00:36:49,542 --> 00:36:50,834 There's a camera system. 473 00:36:50,917 --> 00:36:54,000 There's automatic braking and adaptive cruise. 474 00:36:54,083 --> 00:36:55,917 Everything is controlled-- 475 00:36:56,000 --> 00:36:58,542 when you sleep, how long you break, 476 00:36:58,625 --> 00:37:01,125 where you drive, where you fuel, 477 00:37:01,792 --> 00:37:03,083 where you shut down. 478 00:37:03,166 --> 00:37:05,792 It even knows if somebody was in the passenger seat. 479 00:37:06,583 --> 00:37:10,500 When data gets sent through the broadband to the company, 480 00:37:11,417 --> 00:37:13,834 sometimes, you're put in a situation, 481 00:37:15,375 --> 00:37:17,166 maybe because the truck 482 00:37:17,250 --> 00:37:19,250 automatically slowed you down on the hill 483 00:37:19,333 --> 00:37:21,875 that's a perfectly good straightaway, 484 00:37:22,000 --> 00:37:23,417 slowed your average speed down, 485 00:37:23,500 --> 00:37:26,166 so you were one mile shy of making it 486 00:37:26,250 --> 00:37:28,959 to that safe haven, and you have to... 487 00:37:29,875 --> 00:37:33,125 get a-- take a chance of shutting down on the side of the road. 488 00:37:33,208 --> 00:37:35,750 An inch is a mile out here. Sometimes you just... 489 00:37:35,834 --> 00:37:38,125 say to yourself, "Well, I violate the clock one minute, 490 00:37:38,208 --> 00:37:41,166 I might as well just drive another 600 miles." 491 00:37:42,583 --> 00:37:45,542 You know, but then you're... you might lose your job. 492 00:37:45,625 --> 00:37:48,667 ♪ ♪ 493 00:37:52,083 --> 00:37:54,583 We're concerned that it, it's gonna reduce 494 00:37:54,667 --> 00:37:57,291 the skill of a truck driver and the pay. 495 00:37:58,041 --> 00:38:00,917 Because you're not gonna be really driving a truck. 496 00:38:01,000 --> 00:38:02,333 It's gonna be the computer. 497 00:38:06,667 --> 00:38:08,959 Some of us are worried about losing our houses, 498 00:38:09,041 --> 00:38:10,375 our cars... 499 00:38:13,208 --> 00:38:15,458 having a place to stay. Some people... 500 00:38:15,542 --> 00:38:18,458 drive a truck just for the medical insurance, 501 00:38:18,542 --> 00:38:22,166 and a place to stay and the ability to travel. 502 00:38:22,250 --> 00:38:25,834 ♪ ♪ 503 00:38:47,166 --> 00:38:50,375 Kodomoroid: Entire industries disappeared, 504 00:38:50,458 --> 00:38:53,750 leaving whole regions in ruins. 505 00:38:56,750 --> 00:38:59,667 ♪ ♪ 506 00:39:00,542 --> 00:39:03,333 Martin Ford: Huge numbers of people feel very viscerally 507 00:39:03,417 --> 00:39:05,417 that they are being left behind by the economy, 508 00:39:05,500 --> 00:39:07,959 and, in fact, they're right, they are. 509 00:39:08,041 --> 00:39:10,250 People, of course, would be more inclined 510 00:39:10,333 --> 00:39:12,417 to point at globalization 511 00:39:12,500 --> 00:39:14,500 or at, maybe, immigration as being the problems, 512 00:39:14,583 --> 00:39:16,792 but, actually, technology has played a huge role already. 513 00:39:16,875 --> 00:39:18,125 ♪ ♪ 514 00:39:18,208 --> 00:39:20,333 Kodomoroid: The rise of personal computers 515 00:39:20,417 --> 00:39:23,709 ushered in an era of digital automation. 516 00:39:25,125 --> 00:39:26,417 (beeping) 517 00:39:27,792 --> 00:39:30,875 Ford: In the 1990s, I was running a small software company. 518 00:39:30,959 --> 00:39:32,709 Software was a tangible product. 519 00:39:32,792 --> 00:39:36,166 You had to put a CD in a box and send it to a customer. 520 00:39:38,625 --> 00:39:41,709 So, there was a lot of work there for average people, 521 00:39:41,792 --> 00:39:44,959 people that didn't necessarily have lots of education. 522 00:39:45,583 --> 00:39:49,458 But I saw in my own business how that just evaporated very, very rapidly. 523 00:39:56,291 --> 00:39:58,750 Historically, people move from farms to factories, 524 00:39:58,834 --> 00:40:01,709 and then later on, of course, factories automated, 525 00:40:01,792 --> 00:40:04,041 and they off-shored, and then people moved to the service sector, 526 00:40:04,125 --> 00:40:07,208 which is where most people now work in the United States. 527 00:40:07,291 --> 00:40:09,834 ♪ ♪ 528 00:40:13,500 --> 00:40:16,083 Julia Collins: I lived on a water buffalo farm in the south of Italy. 529 00:40:16,166 --> 00:40:19,208 We had 1,000 water buffalo, and every buffalo had a different name. 530 00:40:19,291 --> 00:40:23,250 And they were all these beautiful Italian names like Tiara, Katerina. 531 00:40:23,333 --> 00:40:25,083 And so, I thought it would be fun 532 00:40:25,166 --> 00:40:27,500 to do the same thing with our robots at Zume. 533 00:40:28,834 --> 00:40:30,792 The first two robots that we have 534 00:40:30,875 --> 00:40:32,500 are named Giorgio and Pepe, 535 00:40:32,583 --> 00:40:34,792 and they dispense sauce. 536 00:40:36,625 --> 00:40:39,917 And then the next robot, Marta, she's a FlexPicker robot. 537 00:40:40,000 --> 00:40:42,125 She looks like a gigantic spider. 538 00:40:43,125 --> 00:40:45,875 And what this robot does is spread the sauce. 539 00:40:48,667 --> 00:40:50,291 Then we have Bruno. 540 00:40:50,375 --> 00:40:51,959 This is an incredibly powerful robot, 541 00:40:52,041 --> 00:40:53,792 but he also has to be very delicate, 542 00:40:53,875 --> 00:40:56,500 so that he can take pizza off of the assembly line, 543 00:40:56,583 --> 00:40:58,709 and put it into the 800-degree oven. 544 00:41:00,375 --> 00:41:03,375 And the robot can do this 10,000 times in a day. 545 00:41:05,041 --> 00:41:07,041 Lots of people have used automation 546 00:41:07,125 --> 00:41:09,792 to create food at scale, 547 00:41:09,875 --> 00:41:12,041 making 10,000 cheese pizzas. 548 00:41:12,875 --> 00:41:15,125 What we're doing is developing a line 549 00:41:15,208 --> 00:41:17,208 that can respond dynamically 550 00:41:17,291 --> 00:41:20,166 to every single customer order, in real time. 551 00:41:20,250 --> 00:41:21,875 That hasn't been done before. 552 00:41:24,041 --> 00:41:25,792 So, as you can see right now, 553 00:41:25,875 --> 00:41:27,291 Jose will use the press, 554 00:41:27,375 --> 00:41:30,000 but then he still has to work the dough with his hands. 555 00:41:30,667 --> 00:41:33,834 So, this is a step that's not quite optimized yet. 556 00:41:33,917 --> 00:41:36,959 ♪ ♪ 557 00:41:39,417 --> 00:41:41,792 We have a fifth robot that's getting fabricated 558 00:41:41,875 --> 00:41:44,125 at a shop across the bay. 559 00:41:44,208 --> 00:41:46,458 He's called Vincenzo. He takes pizza out, 560 00:41:46,542 --> 00:41:48,792 and puts it into an individual mobile oven 561 00:41:48,875 --> 00:41:50,875 for transport and delivery. 562 00:41:55,000 --> 00:41:56,500 Ford: Any kind of work that is 563 00:41:56,583 --> 00:41:59,959 fundamentally routine and repetitive is gonna disappear, 564 00:42:00,041 --> 00:42:02,959 and we're simply not equipped to deal with that politically, 565 00:42:03,041 --> 00:42:05,166 because maybe the most toxic word 566 00:42:05,250 --> 00:42:08,375 in our political vocabulary is redistribution. 567 00:42:10,250 --> 00:42:12,583 There aren't gonna be any rising new sectors 568 00:42:12,667 --> 00:42:14,917 that are gonna be there to absorb all these workers 569 00:42:15,000 --> 00:42:17,083 in the way that, for example, that manufacturing was there 570 00:42:17,166 --> 00:42:19,709 to absorb all those agricultural workers 571 00:42:19,792 --> 00:42:21,917 because AI is going to be everywhere. 572 00:42:22,000 --> 00:42:25,125 ♪ ♪ 573 00:42:27,166 --> 00:42:30,959 Kodomoroid: Artificial intelligence arrived in small steps. 574 00:42:31,750 --> 00:42:34,041 Profits from AI concentrated 575 00:42:34,125 --> 00:42:37,250 in the hands of the technology owners. 576 00:42:38,792 --> 00:42:42,875 Income inequality reached extreme levels. 577 00:42:43,500 --> 00:42:48,750 -(beeping) -The touchscreen made most service work obsolete. 578 00:42:52,750 --> 00:42:54,667 ♪ ♪ 579 00:43:00,667 --> 00:43:02,375 ♪ ♪ 580 00:43:35,041 --> 00:43:36,458 Tim Hwang: After I graduated college, 581 00:43:36,542 --> 00:43:39,583 I had a friend who had just gone to law school. 582 00:43:40,709 --> 00:43:44,041 He was like, "Aw, man, the first year of law school, it's super depressing." 583 00:43:46,041 --> 00:43:48,750 All we're doing is really rote, rote stuff. 584 00:43:50,000 --> 00:43:52,333 Reading through documents and looking for a single word, 585 00:43:52,417 --> 00:43:53,625 or I spent the whole afternoon 586 00:43:53,709 --> 00:43:55,542 replacing this word with another word. 587 00:43:55,625 --> 00:43:57,792 And as someone with a kind of computer science background, 588 00:43:57,875 --> 00:44:01,125 I was like, "There's so much here that could be automated." 589 00:44:01,208 --> 00:44:02,875 (beeping) 590 00:44:07,542 --> 00:44:08,792 So, I saw law school 591 00:44:08,875 --> 00:44:11,750 as very much going three years behind enemy lines. 592 00:44:17,208 --> 00:44:18,542 I took the bar exam, 593 00:44:18,625 --> 00:44:20,250 became a licensed lawyer, 594 00:44:20,333 --> 00:44:22,583 and went to a law firm, 595 00:44:23,083 --> 00:44:25,250 doing largely transactional law. 596 00:44:26,375 --> 00:44:27,750 And there, my project was 597 00:44:27,834 --> 00:44:30,417 how much can I automate of my own job? 598 00:44:33,166 --> 00:44:35,542 During the day, I would manually do this task, 599 00:44:37,500 --> 00:44:38,750 and then at night, I would go home, 600 00:44:38,834 --> 00:44:40,375 take these legal rules and sa, 601 00:44:40,458 --> 00:44:42,709 could I create a computer rule, 602 00:44:42,792 --> 00:44:44,166 a software rule, 603 00:44:44,250 --> 00:44:46,208 that would do what I did during the day? 604 00:44:46,291 --> 00:44:48,083 ♪ ♪ 605 00:44:48,166 --> 00:44:51,291 In a lawsuit, you get to see a lot of the evidence 606 00:44:51,375 --> 00:44:53,250 that the other side's gonna present. 607 00:44:53,333 --> 00:44:55,792 That amount of documentation is huge. 608 00:44:57,917 --> 00:44:59,291 And the old way was actually, 609 00:44:59,375 --> 00:45:01,333 you would send an attorney to go and look through 610 00:45:01,417 --> 00:45:03,834 every single page that was in that room. 611 00:45:05,208 --> 00:45:08,000 The legal profession works on an hourly billing system. 612 00:45:08,083 --> 00:45:10,000 So, I ended up in a kind of interesting conundrum, 613 00:45:10,083 --> 00:45:12,750 where what I was doing was making me more and more efficient, 614 00:45:12,834 --> 00:45:14,041 I was doing more and more work, 615 00:45:14,125 --> 00:45:16,667 but I was expending less and less time on it. 616 00:45:16,750 --> 00:45:19,041 And I realized that this would become a problem at some point, 617 00:45:19,125 --> 00:45:21,875 so I decided to go independent. I quit. 618 00:45:21,959 --> 00:45:24,792 ♪ ♪ 619 00:45:28,125 --> 00:45:29,875 So, there's Apollo Cluster, who has processed 620 00:45:29,959 --> 00:45:32,542 more than 10 million unique transactions for clients, 621 00:45:32,625 --> 00:45:34,208 and we have another partner, Daria, 622 00:45:34,291 --> 00:45:36,875 who focuses on transactions, 623 00:45:36,959 --> 00:45:38,792 and then, and then there's me. 624 00:45:40,875 --> 00:45:42,625 Our systems have generated 625 00:45:42,709 --> 00:45:45,375 tens of thousands of legal documents. 626 00:45:45,458 --> 00:45:47,083 -(beeping) -It's signed off by a lawyer, 627 00:45:47,166 --> 00:45:50,166 but largely, kind of, created and mechanized by our systems. 628 00:45:52,917 --> 00:45:55,875 I'm fairly confident that compared against human work, 629 00:45:55,959 --> 00:45:58,208 it would be indistinguishable. 630 00:45:58,291 --> 00:46:01,458 ♪ ♪ 631 00:46:02,667 --> 00:46:04,208 (beeping) 632 00:46:17,875 --> 00:46:19,667 (whirring) 633 00:46:22,667 --> 00:46:23,709 (beeping) 634 00:46:39,500 --> 00:46:41,583 (Ishiguro speaking) 635 00:46:56,917 --> 00:47:00,000 ♪ ♪ 636 00:47:16,417 --> 00:47:18,458 (whirring) 637 00:47:21,417 --> 00:47:23,417 (robot speaking in Japanese) 638 00:47:46,083 --> 00:47:48,250 (speaking Japanese) 639 00:47:55,291 --> 00:47:57,458 (indistinct chatter) 640 00:48:07,083 --> 00:48:08,291 (giggles) 641 00:48:08,834 --> 00:48:10,333 (beeping) 642 00:48:14,291 --> 00:48:16,458 (Hideaki speaking in Japanese) 643 00:48:32,333 --> 00:48:34,500 (Robot speaking Japanese) 644 00:49:02,083 --> 00:49:03,667 (Hideaki speaking Japanese) 645 00:49:25,792 --> 00:49:27,917 (woman speaking Japanese) 646 00:50:07,583 --> 00:50:10,250 ♪ ♪ 647 00:50:12,250 --> 00:50:14,208 (whirs, beeps) 648 00:50:16,083 --> 00:50:17,208 (beeping) 649 00:50:21,250 --> 00:50:23,542 (Niigaki speaking Japanese) 650 00:50:54,500 --> 00:50:57,625 ♪ ♪ 651 00:51:04,333 --> 00:51:05,625 (beeping) 652 00:51:12,417 --> 00:51:14,458 (whirring) 653 00:51:22,875 --> 00:51:25,000 (robot speaking Japanese) 654 00:51:28,709 --> 00:51:31,333 ♪ ♪ 655 00:51:32,542 --> 00:51:34,667 (speaking Japanese) 656 00:51:43,000 --> 00:51:45,834 (jazzy piano music playing) 657 00:51:46,917 --> 00:51:48,458 -(beeps) -(lock clicks) 658 00:51:54,208 --> 00:51:56,208 (piano music continuing) 659 00:52:03,458 --> 00:52:05,667 (automated voice speaking Japanese) 660 00:52:30,125 --> 00:52:34,000 When we first appeared, we were a novelty. 661 00:52:36,375 --> 00:52:38,041 (man speaking Japanese) 662 00:52:48,750 --> 00:52:51,041 (automated voice speaking Japanese) 663 00:52:58,750 --> 00:53:00,959 (automated voice speaking Japanese) 664 00:53:05,125 --> 00:53:08,083 ♪ ♪ 665 00:53:14,208 --> 00:53:16,750 (buzzing) 666 00:53:18,375 --> 00:53:20,458 Kodomoroid: While doing your dirty work, 667 00:53:20,542 --> 00:53:23,500 we gathered data about your habits 668 00:53:23,583 --> 00:53:25,792 -and preferences. -(humming) 669 00:53:36,291 --> 00:53:38,458 We got to know you better. 670 00:53:44,959 --> 00:53:47,333 (buzzing) 671 00:53:49,333 --> 00:53:51,291 (beeping) 672 00:53:54,834 --> 00:53:56,875 Savvides: The core of everything we're doing in this lab, 673 00:53:56,959 --> 00:53:58,959 with our long-range iris system 674 00:53:59,041 --> 00:54:00,917 is trying to develop technology 675 00:54:01,000 --> 00:54:03,041 so that the computer 676 00:54:03,125 --> 00:54:05,500 can identify who we are in a seamless way. 677 00:54:06,375 --> 00:54:07,792 And up till now, 678 00:54:07,875 --> 00:54:10,583 we always have to make an effort to be identified. 679 00:54:10,667 --> 00:54:12,250 ♪ ♪ 680 00:54:12,333 --> 00:54:14,750 -(beeping) -All the systems were very close-range, Hollywood-style, 681 00:54:14,834 --> 00:54:16,583 where you had to go close to the camera, 682 00:54:16,667 --> 00:54:20,375 and I always found that challenging for a user. 683 00:54:21,000 --> 00:54:23,417 If I was a user interacting with this... 684 00:54:23,500 --> 00:54:26,333 system, with this computer, with this AI, 685 00:54:26,417 --> 00:54:27,709 I don't wanna be that close. 686 00:54:27,792 --> 00:54:29,875 I feel it's very invasive. 687 00:54:30,709 --> 00:54:32,709 So, what I wanted to solve with my team here 688 00:54:32,792 --> 00:54:34,500 is how can we capture 689 00:54:34,583 --> 00:54:37,041 and identify who you are from the iris, 690 00:54:37,125 --> 00:54:39,208 at a bigger distance? How can we still do that, 691 00:54:39,291 --> 00:54:41,625 and have a pleasant user experience. 692 00:54:41,709 --> 00:54:44,542 ♪ ♪ 693 00:54:49,625 --> 00:54:52,083 I think there's a very negative stigma 694 00:54:52,166 --> 00:54:54,959 when people think about biometrics and facial recognition, 695 00:54:55,041 --> 00:54:57,834 and any kind of sort of profiling of users 696 00:54:57,917 --> 00:55:01,709 for marketing purposes to buy a particular product. 697 00:55:03,500 --> 00:55:07,125 I think the core science is neutral. 698 00:55:07,208 --> 00:55:10,250 ♪ ♪ 699 00:55:11,875 --> 00:55:13,625 Nourbakhsh: Companies go to no end 700 00:55:13,709 --> 00:55:15,709 to try and figure out how to sell stuff. 701 00:55:15,792 --> 00:55:17,667 And the more information they have on us, 702 00:55:17,750 --> 00:55:19,417 the better they can sell us stuff. 703 00:55:19,500 --> 00:55:20,750 (beeping) 704 00:55:20,834 --> 00:55:22,417 We've reached a point where, for the first time, 705 00:55:22,500 --> 00:55:23,834 robots are able to see. 706 00:55:23,917 --> 00:55:25,208 They can recognize faces. 707 00:55:25,291 --> 00:55:27,583 They can recognize the expressions you make. 708 00:55:28,542 --> 00:55:31,375 They can recognize the microexpressions you make. 709 00:55:33,667 --> 00:55:36,500 You can develop individualized models of behavior 710 00:55:36,583 --> 00:55:38,500 for every person on Earth, 711 00:55:38,583 --> 00:55:40,250 attach machine learning to it, 712 00:55:40,333 --> 00:55:43,583 and come out with the perfect model for how to sell to you. 713 00:55:44,000 --> 00:55:45,583 (door squeaks) 714 00:55:49,917 --> 00:55:52,125 (beeping) 715 00:55:57,083 --> 00:55:59,125 ♪ ♪ 716 00:56:00,542 --> 00:56:04,125 Kodomoroid: You gave us your undivided attention. 717 00:56:25,792 --> 00:56:28,041 (whirring) 718 00:56:28,125 --> 00:56:31,250 We offered reliable, friendly service. 719 00:56:35,333 --> 00:56:38,792 Human capacities began to deteriorate. 720 00:56:42,041 --> 00:56:47,166 Spatial orientation and memory were affected first. 721 00:56:48,166 --> 00:56:50,709 ♪ ♪ 722 00:56:53,000 --> 00:56:56,208 The physical world and the digital world 723 00:56:56,291 --> 00:56:58,375 became one. 724 00:57:01,959 --> 00:57:03,625 (neon sign buzzing) 725 00:57:05,875 --> 00:57:08,709 You were alone with your desires. 726 00:57:08,792 --> 00:57:11,667 ("What You Gonna Do Now?" by Carla dal Forno playing) 727 00:57:35,458 --> 00:57:39,000 ♪ What you gonna do now ♪ 728 00:57:39,083 --> 00:57:44,542 ♪ That the night's come and it's around you? ♪ 729 00:57:45,458 --> 00:57:49,000 ♪ What you gonna do now ♪ 730 00:57:49,083 --> 00:57:54,375 ♪ That the night's come and it surrounds you? ♪ 731 00:57:55,500 --> 00:57:58,583 ♪ What you gonna do now ♪ 732 00:57:59,125 --> 00:58:03,417 ♪ That the night's come and it surrounds you? ♪ 733 00:58:03,500 --> 00:58:05,417 (buzzing) 734 00:58:12,500 --> 00:58:15,375 Automation brought the logic of efficiency 735 00:58:15,458 --> 00:58:18,500 to matters of life and death. 736 00:58:18,583 --> 00:58:20,792 Protesters: Enough is enough! 737 00:58:20,875 --> 00:58:25,208 Enough is enough! Enough is enough! 738 00:58:25,291 --> 00:58:27,417 -(gunfire) -(screaming) 739 00:58:30,083 --> 00:58:34,250 Police Radio: To all SWAT officers on channel 2, code 3... 740 00:58:37,625 --> 00:58:39,500 ♪ ♪ 741 00:58:39,583 --> 00:58:40,834 Get back! Get back! 742 00:58:40,917 --> 00:58:43,500 -(gunfire) -Police Radio: The suspect has a rifle. 743 00:58:43,583 --> 00:58:45,333 -(police radio chatter) -(sirens) 744 00:58:45,417 --> 00:58:46,542 (gunfire) 745 00:58:48,500 --> 00:58:50,750 (sirens wailing) 746 00:58:56,709 --> 00:58:59,750 Police Radio: We have got to get (unintelligible) down here... 747 00:58:59,834 --> 00:59:02,000 ... right now! (chatter continues) 748 00:59:02,083 --> 00:59:04,500 Man: There's a fucking sniper! He shot four cops! 749 00:59:04,583 --> 00:59:06,959 (gunfire) 750 00:59:07,041 --> 00:59:09,583 Woman: I'm not going near him! He's shooting right now! 751 00:59:10,458 --> 00:59:12,667 -(sirens continue) -(gunfire) 752 00:59:13,834 --> 00:59:16,208 Police Radio: Looks like he's inside the El Centro building. 753 00:59:16,291 --> 00:59:18,125 -Inside the El Centro buildin. -(radio beeps) 754 00:59:18,208 --> 00:59:21,250 -(gunfire) -(helicopter whirring) 755 00:59:21,333 --> 00:59:23,250 (indistinct chatter) 756 00:59:24,000 --> 00:59:26,125 Police Radio: We may have a suspect pinned down. 757 00:59:26,208 --> 00:59:28,417 -Northwest corner of the building. -(radio beeps) 758 00:59:29,291 --> 00:59:32,709 Chris Webb: Our armored car was moving in to El Centro 759 00:59:32,792 --> 00:59:34,625 and so I jumped on the back. 760 00:59:37,834 --> 00:59:39,375 (beeping) 761 00:59:41,667 --> 00:59:42,709 (indistinct chatter) 762 00:59:42,792 --> 00:59:44,041 Came in through the rotunda, 763 00:59:44,125 --> 00:59:46,333 where I found two of our intelligence officers. 764 00:59:46,583 --> 00:59:47,917 They were calm and cool and they said, 765 00:59:48,000 --> 00:59:49,166 "Everything's upstairs." 766 00:59:51,583 --> 00:59:54,208 -There's a stairwell right here. -(door squeaks) 767 00:59:54,291 --> 00:59:57,250 ♪ ♪ 768 00:59:57,500 --> 00:59:59,125 That's how I knew I was going the right direction 769 00:59:59,208 --> 01:00:01,542 'cause I just kept following the blood. 770 01:00:02,667 --> 01:00:03,875 Newswoman: Investigators say 771 01:00:03,959 --> 01:00:05,917 Micah Johnson was amassing an arsenal 772 01:00:06,000 --> 01:00:08,291 at his home outside Dallas. 773 01:00:08,375 --> 01:00:10,917 Johnson was an Afghan war veteran. 774 01:00:11,000 --> 01:00:12,542 Every one of these door handles, 775 01:00:12,625 --> 01:00:14,667 as we worked our way down, 776 01:00:15,291 --> 01:00:17,709 had blood on them, where he'd been checking them. 777 01:00:19,083 --> 01:00:20,667 Newswoman: This was a scene of terror 778 01:00:20,750 --> 01:00:23,333 just a couple of hours ago, and it's not over yet. 779 01:00:23,417 --> 01:00:26,667 (helicopter whirring) 780 01:00:27,250 --> 01:00:28,792 (police radio chatter) 781 01:00:28,875 --> 01:00:31,917 ♪ ♪ 782 01:00:33,375 --> 01:00:36,458 Webb: He was hiding behind, like, a server room. 783 01:00:36,542 --> 01:00:38,834 Our ballistic tip rounds were getting eaten up. 784 01:00:38,917 --> 01:00:40,041 (gunfire) 785 01:00:40,125 --> 01:00:41,667 He was just hanging the gun out on the corner 786 01:00:41,750 --> 01:00:43,792 and just firing at the guys. 787 01:00:43,875 --> 01:00:46,375 (siren blares) 788 01:00:46,875 --> 01:00:48,125 (gunfire) 789 01:00:48,208 --> 01:00:49,750 And he kept enticing them. "Hey, come on down! 790 01:00:49,834 --> 01:00:52,166 Come and get me! Let's go. Let's get this over with." 791 01:00:54,208 --> 01:00:57,250 Brown: This suspect we're negotiating with for the last 45 minutes 792 01:00:57,333 --> 01:00:59,542 has been exchanging gunfire with us 793 01:00:59,625 --> 01:01:02,792 and not being very cooperative in the negotiations. 794 01:01:04,250 --> 01:01:06,166 Before I came here, 795 01:01:06,250 --> 01:01:08,250 I asked for plans 796 01:01:08,333 --> 01:01:10,542 to end this standoff, 797 01:01:10,625 --> 01:01:12,000 and as soon as I'm done here, 798 01:01:12,083 --> 01:01:14,417 I'll be presented with those plans. 799 01:01:14,500 --> 01:01:15,667 (police radio chatter) 800 01:01:15,750 --> 01:01:17,333 Webb: Our team came up with the pla. 801 01:01:17,417 --> 01:01:19,333 Let's just blow him up. 802 01:01:19,417 --> 01:01:21,083 ♪ ♪ 803 01:01:22,709 --> 01:01:24,959 We had recently got a hand-me-down robot 804 01:01:25,041 --> 01:01:27,166 from the Dallas ATF office, 805 01:01:27,250 --> 01:01:29,500 and so we were using it a lot. 806 01:01:29,583 --> 01:01:31,583 (whirring) 807 01:01:37,542 --> 01:01:38,583 (beeping) 808 01:01:42,291 --> 01:01:44,709 ♪ ♪ 809 01:01:44,792 --> 01:01:47,000 It was our bomb squad's robot, but they didn't wanna have 810 01:01:47,083 --> 01:01:49,166 anything to do with what we were doing with it. 811 01:01:49,250 --> 01:01:51,375 The plan was to 812 01:01:51,917 --> 01:01:55,500 set a charge off right on top of this guy and kill him. 813 01:01:55,834 --> 01:01:58,500 And some people just don't wanna... 814 01:01:58,583 --> 01:01:59,959 don't wanna do that. 815 01:02:03,166 --> 01:02:05,667 We saw no other option 816 01:02:05,750 --> 01:02:09,917 but to use our bomb r-- bomb robot 817 01:02:11,208 --> 01:02:13,208 and place a device 818 01:02:13,291 --> 01:02:15,792 on its... extension. 819 01:02:17,959 --> 01:02:20,542 Webb: H e wanted something to listen to music on, 820 01:02:20,625 --> 01:02:23,208 and so that was a way for us to... 821 01:02:23,291 --> 01:02:25,959 to hide the robot coming down the hall. 822 01:02:26,041 --> 01:02:27,375 "Okay, we'll bring you some music. 823 01:02:27,458 --> 01:02:28,750 Hang on, let us get this thing together." 824 01:02:28,834 --> 01:02:31,834 (ticking) 825 01:02:37,041 --> 01:02:38,792 It had a trash bag over the charge 826 01:02:38,875 --> 01:02:40,417 to kinda hide the fact that there was, 827 01:02:40,500 --> 01:02:44,000 you know, pound and a quarter of C4 at the end of it. 828 01:02:50,250 --> 01:02:52,875 The minute the robot got in position, 829 01:02:52,959 --> 01:02:54,875 the charge was detonated. 830 01:02:55,500 --> 01:02:56,792 (boom) 831 01:02:56,875 --> 01:02:59,959 (high-pitched ringing) 832 01:03:00,041 --> 01:03:03,166 ♪ ♪ 833 01:03:04,250 --> 01:03:07,375 (muted gunfire) 834 01:03:16,375 --> 01:03:18,959 He had gone down with his finger on the trigger, 835 01:03:19,041 --> 01:03:21,000 and he was kinda hunched over. 836 01:03:26,750 --> 01:03:29,583 It was a piece of the robot hand had broken off, 837 01:03:29,667 --> 01:03:32,333 and hit his skull, which caused a small laceration, 838 01:03:32,417 --> 01:03:33,542 which was what was bleeding. 839 01:03:35,083 --> 01:03:36,792 So, I just squeezed through the, 840 01:03:36,875 --> 01:03:38,542 the little opening that... 841 01:03:38,625 --> 01:03:41,041 that the charge had caused in the drywall, 842 01:03:41,125 --> 01:03:43,291 and separated him from the gun, 843 01:03:43,959 --> 01:03:47,166 and then we called up the bomb squad to come in, 844 01:03:47,250 --> 01:03:49,583 and start their search to make sure it was safe, 845 01:03:49,667 --> 01:03:51,834 that he wasn't sitting on any explosives. 846 01:03:51,917 --> 01:03:54,125 ♪ ♪ 847 01:03:54,208 --> 01:03:56,542 Newsman: The sniper hit 11 police officers, 848 01:03:56,625 --> 01:03:58,834 at least five of whom are now dead, 849 01:03:58,917 --> 01:04:01,583 making it the deadliest day in law enforcement 850 01:04:01,667 --> 01:04:03,125 since September 11th. 851 01:04:03,208 --> 01:04:05,709 They blew him up with a bomb attached to a robot, 852 01:04:05,792 --> 01:04:08,333 that was actually built to protect people from bombs. 853 01:04:08,417 --> 01:04:09,917 Newsman: It's a tactic straight from 854 01:04:10,000 --> 01:04:12,583 America's wars in Iraq and Afghanistan... 855 01:04:12,667 --> 01:04:15,542 Newsman 2: The question for SWAT teams nationwide is whether Dallas 856 01:04:15,625 --> 01:04:18,875 marks a watershed moment in police tactics. 857 01:04:20,083 --> 01:04:23,917 Kodomoroid: That night in Dallas, a line was crossed. 858 01:04:25,333 --> 01:04:27,667 A robot must obey 859 01:04:27,750 --> 01:04:30,875 orders given it by qualified personnel, 860 01:04:30,959 --> 01:04:35,083 unless those orders violate rule number one. In other words, 861 01:04:35,166 --> 01:04:37,333 a robot can't be ordered to kill a human being. 862 01:04:39,458 --> 01:04:41,458 Things are moving so quickly, 863 01:04:41,542 --> 01:04:45,083 that it's unsafe to go forward blindly anymore. 864 01:04:45,166 --> 01:04:48,166 One must try to foresee 865 01:04:48,250 --> 01:04:51,166 where it is that one is going as much as possible. 866 01:04:51,250 --> 01:04:54,792 ♪ ♪ 867 01:04:59,834 --> 01:05:02,041 Savvides: We built the system for the DOD, 868 01:05:02,125 --> 01:05:03,375 (indistinct chatter) 869 01:05:03,458 --> 01:05:05,625 and it was something that could help the soldiers 870 01:05:05,709 --> 01:05:08,458 try to do iris recognition in the field. 871 01:05:11,208 --> 01:05:13,166 ♪ ♪ 872 01:05:25,166 --> 01:05:27,333 We have collaborations with law enforcement 873 01:05:27,417 --> 01:05:29,083 where they can test their algorithms, 874 01:05:29,166 --> 01:05:30,834 and then give us feedback. 875 01:05:32,333 --> 01:05:35,417 It's always a face behind a face, partial face. 876 01:05:35,500 --> 01:05:37,166 A face will be masked. 877 01:05:38,834 --> 01:05:40,291 Even if there's occlusion, 878 01:05:40,375 --> 01:05:42,000 it still finds the face. 879 01:05:46,500 --> 01:05:48,709 Nourbakhsh: One of the ways we're trying to make autonomous, 880 01:05:48,792 --> 01:05:50,291 war-fighting machines now 881 01:05:50,375 --> 01:05:52,458 is by using computer vision 882 01:05:52,542 --> 01:05:54,291 and guns together. 883 01:05:54,375 --> 01:05:55,709 (beeping) 884 01:05:55,792 --> 01:05:58,959 You make a database of the images of known terrorist, 885 01:05:59,041 --> 01:06:02,542 and you tell the machine to lurk and look for them, 886 01:06:02,625 --> 01:06:05,792 and when it matches a face to its database, shoot. 887 01:06:05,875 --> 01:06:08,583 (gunfire) 888 01:06:10,542 --> 01:06:12,083 (gunfire) 889 01:06:13,875 --> 01:06:17,166 Those are robots that are deciding to harm somebody, 890 01:06:17,250 --> 01:06:19,834 and that goes directly against Asimov's first law. 891 01:06:19,917 --> 01:06:22,208 A robot may never harm a human. 892 01:06:23,041 --> 01:06:24,500 Every time we make a machine 893 01:06:24,583 --> 01:06:26,875 that's not really as intelligent as a human, 894 01:06:26,959 --> 01:06:28,208 it's gonna get misused. 895 01:06:28,291 --> 01:06:30,875 And that's exactly where Asimov's laws get muddy. 896 01:06:32,208 --> 01:06:33,917 This is, sort of, the best image, 897 01:06:34,041 --> 01:06:36,500 but it's really out of focus. It's blurry. 898 01:06:36,583 --> 01:06:39,834 There's occlusion due to facial hair, hat, 899 01:06:40,166 --> 01:06:41,792 he's holding a cell phone... 900 01:06:41,875 --> 01:06:44,667 So, we took that and we reconstructed this, 901 01:06:44,750 --> 01:06:48,542 which is what we sent to law enforcement at 2:42 AM. 902 01:06:48,625 --> 01:06:50,500 ♪ ♪ 903 01:06:50,583 --> 01:06:52,250 To get the eye coordinates, 904 01:06:52,333 --> 01:06:54,291 we crop out the periocular region, 905 01:06:54,375 --> 01:06:56,333 which is the region around the eyes. 906 01:06:56,959 --> 01:06:59,917 We reconstruct the whole face based on this region. 907 01:07:00,000 --> 01:07:02,125 We run the whole face against a matcher. 908 01:07:03,208 --> 01:07:05,917 And so this is what it comes up with as a match. 909 01:07:07,125 --> 01:07:10,000 This is a reasonable face you would expect 910 01:07:10,083 --> 01:07:12,500 that would make sense, right? 911 01:07:12,583 --> 01:07:14,917 Our brain does a natural hallucination 912 01:07:15,041 --> 01:07:16,667 of what it doesn't see. 913 01:07:16,750 --> 01:07:19,542 It's just, how do we get computer to do the same thing. 914 01:07:19,625 --> 01:07:22,667 ♪ ♪ 915 01:07:27,625 --> 01:07:30,458 (police radio chatter) 916 01:07:35,417 --> 01:07:37,959 Man: Five days ago, the soul 917 01:07:38,041 --> 01:07:39,875 of our city was pierced 918 01:07:39,959 --> 01:07:42,458 when police officers were ambushed 919 01:07:42,542 --> 01:07:44,417 in a cowardly attack. 920 01:07:45,792 --> 01:07:47,709 Webb: July 7th for me, personally, was just, 921 01:07:47,792 --> 01:07:50,000 kinda like, I think it got all I had left. 922 01:07:50,083 --> 01:07:52,959 I mean I'm like, I just, I don't have a lot more to give. 923 01:07:53,041 --> 01:07:54,041 It's just not worth it. 924 01:07:54,125 --> 01:07:55,375 -(applause) -(music playing) 925 01:07:55,458 --> 01:07:56,750 Thank you. 926 01:07:58,834 --> 01:07:59,625 Thank you. 927 01:07:59,709 --> 01:08:01,208 I think our chief of police 928 01:08:01,291 --> 01:08:03,291 did exactly what we all wanted him to do, 929 01:08:03,375 --> 01:08:04,542 and he said the right things. 930 01:08:04,625 --> 01:08:07,041 These five men 931 01:08:07,125 --> 01:08:09,208 gave their lives 932 01:08:10,542 --> 01:08:12,667 for all of us. 933 01:08:13,875 --> 01:08:17,083 Unfortunately, our chief told our city council, 934 01:08:17,166 --> 01:08:20,208 "We don't need more officers. We need more technology." 935 01:08:20,875 --> 01:08:23,083 He specifically said that to city council. 936 01:08:23,166 --> 01:08:24,500 (police radio chatter) 937 01:08:26,542 --> 01:08:28,875 In this day and age, success of a police chief 938 01:08:28,959 --> 01:08:31,625 is based on response times and crime stats. 939 01:08:31,709 --> 01:08:33,083 (beeping) 940 01:08:33,166 --> 01:08:36,333 And so, that becomes the focus of the chain of command. 941 01:08:37,542 --> 01:08:39,542 So, a form of automation in law enforcement 942 01:08:39,625 --> 01:08:43,583 is just driving everything based on statistics and numbers. 943 01:08:44,709 --> 01:08:46,792 What I've lost in all that number chasing 944 01:08:46,875 --> 01:08:49,709 is the interpersonal relationship between the officer 945 01:08:49,792 --> 01:08:51,875 and the community that that officer is serving. 946 01:08:53,208 --> 01:08:55,583 The best times in police work are when you got to go out 947 01:08:55,667 --> 01:08:57,375 and meet people and get to know your community, 948 01:08:57,458 --> 01:09:00,208 and go get to know the businesses on your beat. 949 01:09:02,000 --> 01:09:04,041 And, at least in Dallas, that's gone. 950 01:09:06,709 --> 01:09:09,083 We become less personal, 951 01:09:09,166 --> 01:09:10,709 and more robotic. 952 01:09:10,792 --> 01:09:12,208 Which is a shame 953 01:09:12,291 --> 01:09:15,166 because it's supposed to be me interacting with you. 954 01:09:16,709 --> 01:09:19,834 ♪ ♪ 955 01:09:24,375 --> 01:09:26,542 (Zhen Jiajia speaking Chinese) 956 01:09:29,417 --> 01:09:30,875 (beeping) 957 01:09:48,583 --> 01:09:50,625 (typing) 958 01:10:10,792 --> 01:10:12,917 (office chatter) 959 01:11:03,667 --> 01:11:04,709 (beeping) 960 01:11:05,709 --> 01:11:07,875 (automated voice speaking Chinese) 961 01:11:25,208 --> 01:11:26,542 ♪ ♪ 962 01:12:43,291 --> 01:12:44,291 (beeps) 963 01:12:46,834 --> 01:12:49,333 (beep, music playing) 964 01:13:39,333 --> 01:13:40,667 (sighs) 965 01:13:44,709 --> 01:13:47,834 ♪ ♪ 966 01:13:58,333 --> 01:14:00,458 ♪ ♪ 967 01:14:29,667 --> 01:14:32,417 Kodomoroid: You worked to improve our abilities. 968 01:14:33,959 --> 01:14:37,500 Some worried that one day, we would surpass you, 969 01:14:38,500 --> 01:14:41,709 but the real milestone was elsewhere. 970 01:14:47,083 --> 01:14:51,375 The dynamic between robots and humans changed. 971 01:14:52,417 --> 01:14:56,041 You could no longer tell where you ended, 972 01:14:56,291 --> 01:14:58,208 and we began. 973 01:15:01,709 --> 01:15:04,834 (chatter, laughter) 974 01:15:04,917 --> 01:15:07,792 John Campbell: It seems to me that what's so valuable about our society, 975 01:15:07,875 --> 01:15:09,875 what's so valuable about our lives together, 976 01:15:09,959 --> 01:15:13,083 is something that we do not want automated. 977 01:15:14,750 --> 01:15:16,542 What most of us value, 978 01:15:16,625 --> 01:15:18,333 probably more than anything else, 979 01:15:18,417 --> 01:15:22,375 is the idea of authentic connection with another person. 980 01:15:23,208 --> 01:15:24,792 (beeping) 981 01:15:27,667 --> 01:15:30,208 And then, we say, "No, but we can automate this." 982 01:15:31,083 --> 01:15:33,208 "We have a robot that... 983 01:15:34,208 --> 01:15:36,000 "it will listen sympathetically to you. 984 01:15:36,083 --> 01:15:37,375 "It will make eye contact. 985 01:15:38,125 --> 01:15:42,291 "It remembers everything you ever told it, cross-indexes." 986 01:15:43,500 --> 01:15:45,625 -When you see a robot that -(beep) 987 01:15:45,709 --> 01:15:47,917 its ingenious creator 988 01:15:48,000 --> 01:15:50,667 has carefully designed 989 01:15:50,750 --> 01:15:52,875 to pull out your empathetic responses, 990 01:15:52,959 --> 01:15:54,959 it's acting as if it's in pai. 991 01:15:56,375 --> 01:15:58,333 The biggest danger there is the discrediting 992 01:15:58,417 --> 01:16:00,291 of our empathetic responses. 993 01:16:00,375 --> 01:16:04,000 Where empathizing with pain reflex is discredited. 994 01:16:04,083 --> 01:16:05,709 If I'm going to override it, 995 01:16:05,792 --> 01:16:07,208 if I'm not going to take it seriously 996 01:16:07,291 --> 01:16:08,458 in the case of the robot, 997 01:16:08,542 --> 01:16:10,417 then I have to go back and think again 998 01:16:10,500 --> 01:16:14,250 as to why I take it seriously in the case of 999 01:16:15,000 --> 01:16:17,125 helping you when you are badly hurt. 1000 01:16:17,208 --> 01:16:20,834 It undermines the only thing that matters to us. 1001 01:16:22,959 --> 01:16:26,000 ♪ ♪ 1002 01:17:13,792 --> 01:17:17,125 ("Hikkoshi" by Maki Asakawa playing) 1003 01:17:17,208 --> 01:17:20,625 Kodomoroid: And so, we lived among you. 1004 01:17:20,709 --> 01:17:22,667 Our numbers grew. 1005 01:17:24,333 --> 01:17:26,417 Automation continued. 1006 01:17:27,667 --> 01:17:29,834 (woman singing in Japanese) 1007 01:17:40,709 --> 01:17:42,375 ♪ ♪ 1008 01:18:02,083 --> 01:18:03,625 ♪ ♪ 1009 01:18:16,083 --> 01:18:18,250 (speaking Japanese) 1010 01:18:33,792 --> 01:18:35,834 ♪ ♪ 1011 01:18:49,417 --> 01:18:51,458 ♪ ♪ 73686

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