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Would you like to inspect the original subtitles? These are the user uploaded subtitles that are being translated: 1 00:00:01,321 --> 00:00:03,656 Morgan: If you think you see everyone as equal, 2 00:00:03,657 --> 00:00:05,626 you're kidding yourself. 3 00:00:05,627 --> 00:00:07,660 We all have biases. 4 00:00:07,661 --> 00:00:09,030 [ Sighs ] 5 00:00:11,032 --> 00:00:13,568 And no matter how open-minded... 6 00:00:15,170 --> 00:00:17,804 We think we are... 7 00:00:17,805 --> 00:00:20,573 Morgan: Stereotypes color our judgment of others. 8 00:00:20,574 --> 00:00:21,676 [ Gun cocks ] 9 00:00:24,512 --> 00:00:26,547 ...and can lead us badly astray. 10 00:00:28,716 --> 00:00:33,120 We live in a society fractured by race, religion, 11 00:00:33,121 --> 00:00:34,955 even our favorite sports teams. 12 00:00:34,956 --> 00:00:36,324 [ Baseball bat cracks ] 13 00:00:36,325 --> 00:00:38,291 Man: Going, going, gone! 14 00:00:38,292 --> 00:00:39,993 Yes! Yes! 15 00:00:39,994 --> 00:00:44,664 Morgan: We divide ourselves into rival tribes. 16 00:00:44,665 --> 00:00:47,667 The political divide between us grows deeper 17 00:00:47,668 --> 00:00:50,471 with every passing year. 18 00:00:50,472 --> 00:00:53,874 When did hate become hard-wired into our brains? 19 00:00:53,875 --> 00:00:56,843 We live in two different americas, one for the rich... 20 00:00:56,844 --> 00:01:02,048 Are we all born to discriminate against our fellow humans? 21 00:01:02,049 --> 00:01:04,987 Are we all bigots? 22 00:01:08,755 --> 00:01:13,094 Space, time, life itself. 23 00:01:15,496 --> 00:01:20,400 The secrets of the cosmos lie through the wormhole. 24 00:01:20,401 --> 00:01:23,403 -- Captions by vitac -- www.Vitac.Com 25 00:01:23,404 --> 00:01:26,441 captions paid for by discovery communications 26 00:01:33,421 --> 00:01:37,724 Have you ever thought about who you instinctively trust 27 00:01:37,725 --> 00:01:40,362 and who you instinctively fear? 28 00:01:42,764 --> 00:01:47,334 Someone's walking toward you down a dark alley... 29 00:01:47,335 --> 00:01:50,239 [ Metallic click ] Holding something in his hand. 30 00:01:53,876 --> 00:01:57,946 Now, I think of myself as an open-minded person. 31 00:01:57,947 --> 00:02:00,815 But scientists tell me I'm kidding myself 32 00:02:00,816 --> 00:02:03,185 and so are you. 33 00:02:03,186 --> 00:02:06,453 We all look at the world with prejudice, 34 00:02:06,454 --> 00:02:10,524 and when you have only a split second to decide, 35 00:02:10,525 --> 00:02:14,329 your own snap judgments may shock you. 36 00:02:18,801 --> 00:02:22,870 Josh Correll grew up solving puzzles for fun, 37 00:02:22,871 --> 00:02:25,307 but now, as a psychologist, 38 00:02:25,308 --> 00:02:28,909 he's trying to solve the puzzle of racism. 39 00:02:28,910 --> 00:02:32,546 And his work is a matter of life and death. 40 00:02:32,547 --> 00:02:37,351 Correll: So, my research was originally inspired by Amadou Diallo. 41 00:02:37,352 --> 00:02:41,154 He came home, went back outside to sit on his front porch, 42 00:02:41,155 --> 00:02:42,856 basically, the stoop of the apartment building. 43 00:02:42,857 --> 00:02:44,159 [ Vehicle approaches, stops ] 44 00:02:44,160 --> 00:02:46,862 Morgan: It was the early hours of February 4, 1999. 45 00:02:46,863 --> 00:02:48,095 [ Car doors open ] 46 00:02:48,096 --> 00:02:51,231 Four New York police officers approached him. 47 00:02:51,232 --> 00:02:54,000 Diallo reached for his wallet 48 00:02:54,001 --> 00:02:56,337 when one of the officers shouted, 49 00:02:56,338 --> 00:02:58,206 "gun! He's got a gun!" 50 00:02:58,207 --> 00:03:05,080 [ Gunfire ] 51 00:03:05,081 --> 00:03:10,118 They fired 41 rounds, killing him at the scene. 52 00:03:10,119 --> 00:03:13,255 The police officers were acquitted of all charges, 53 00:03:13,256 --> 00:03:15,390 sparking a heated national debate. 54 00:03:15,391 --> 00:03:16,590 [ Crowd chanting indistinctly ] 55 00:03:16,591 --> 00:03:19,659 It was a tragedy that has since repeated itself 56 00:03:19,660 --> 00:03:23,098 in the death of Michael Brown in Ferguson, Missouri, 57 00:03:23,099 --> 00:03:26,767 the death of Tamir Rice in Cleveland, Ohio, 58 00:03:26,768 --> 00:03:30,671 the death of John Crawford in Beavercreek, Ohio. 59 00:03:30,672 --> 00:03:33,540 And so, that presented a puzzle. 60 00:03:33,541 --> 00:03:35,376 That presented a question. 61 00:03:35,377 --> 00:03:38,278 How can we determine whether or not race was actually 62 00:03:38,279 --> 00:03:40,082 what drove the officers to shoot? 63 00:03:42,851 --> 00:03:44,518 Some of them will be armed. 64 00:03:44,519 --> 00:03:47,755 Morgan: Josh is about to run an experiment with live ammunition 65 00:03:47,756 --> 00:03:50,993 and with participants who are not policemen. 66 00:03:52,261 --> 00:03:54,928 He asks his white test subject 67 00:03:54,929 --> 00:03:59,200 to treat the simulation as if it is real life. 68 00:03:59,201 --> 00:04:04,005 A potentially lethal person is about to confront him, 69 00:04:04,006 --> 00:04:08,244 and he will have less than one second to make a decision. 70 00:04:10,478 --> 00:04:12,580 There's time pressure. They have to react quickly. 71 00:04:12,581 --> 00:04:14,447 And we can look and see 72 00:04:14,448 --> 00:04:16,483 whether when we change the race of the suspect 73 00:04:16,484 --> 00:04:18,853 from black to white or white to black, 74 00:04:18,854 --> 00:04:20,856 does that influence a person's behavior. 75 00:04:20,857 --> 00:04:26,127 Morgan: The subject will see a scene appear on a screen downrange. 76 00:04:26,128 --> 00:04:29,796 Then, a white man will appear holding either a gun 77 00:04:29,797 --> 00:04:31,332 or a cellphone 78 00:04:31,333 --> 00:04:38,306 or it will be a black man with a gun or a cellphone. 79 00:04:38,307 --> 00:04:42,310 The image of the man is only up for one second. 80 00:04:42,311 --> 00:04:44,344 Time to decide. 81 00:04:44,345 --> 00:04:46,882 Shoot or hold fire? 82 00:04:48,016 --> 00:04:51,351 Mistake the gun for a phone and die. 83 00:04:51,352 --> 00:04:56,191 Mistake the phone for a gun and kill an innocent person. 84 00:04:59,026 --> 00:04:59,961 [ Gun cocks ] 85 00:05:01,996 --> 00:05:04,565 So, what we want to look at is, in that situation 86 00:05:04,566 --> 00:05:06,834 where there's not good, clear information 87 00:05:06,835 --> 00:05:08,503 where people have to respond quickly, 88 00:05:08,504 --> 00:05:10,972 did they use race to inform their decisions? 89 00:05:11,939 --> 00:05:16,144 Morgan: The simulation cycles through dozens of confrontations 90 00:05:16,145 --> 00:05:19,615 equally split between white and black male subjects. 91 00:05:22,050 --> 00:05:24,252 Josh records how long it takes subjects 92 00:05:24,253 --> 00:05:25,986 to make a decision 93 00:05:25,987 --> 00:05:28,822 and whether or not they kill an innocent person 94 00:05:28,823 --> 00:05:30,390 or die themselves. 95 00:05:30,391 --> 00:05:31,959 It's worth noting that, in this game, 96 00:05:31,960 --> 00:05:33,260 people are pretty good. 97 00:05:33,261 --> 00:05:34,863 They don't make a ton of mistakes. 98 00:05:36,064 --> 00:05:38,266 10%, 15% of the time, they make a mistake. 99 00:05:39,468 --> 00:05:40,969 But when we look at those mistakes, 100 00:05:40,970 --> 00:05:42,570 we see racial bias in the errors. 101 00:05:42,571 --> 00:05:44,472 [ Gunshot ] 102 00:05:44,473 --> 00:05:46,308 So they're faster to shoot the armed target 103 00:05:46,309 --> 00:05:47,710 if he's black rather than white. 104 00:05:49,078 --> 00:05:50,210 [ Gunshot ] 105 00:05:50,211 --> 00:05:51,613 When the target's got a cellphone, 106 00:05:51,614 --> 00:05:53,414 they're much more likely to make that decision 107 00:05:53,415 --> 00:05:55,718 to shoot an innocent target when he's black... 108 00:05:58,420 --> 00:05:59,321 Rather than white. 109 00:06:02,357 --> 00:06:06,226 Morgan: Josh has run this experiment on thousands of people. 110 00:06:06,227 --> 00:06:10,964 On average, white subjects are quicker to shoot the black male 111 00:06:10,965 --> 00:06:17,171 and are 30% to 40% more likely to mistake his phone for a gun. 112 00:06:17,172 --> 00:06:19,841 When Josh performs this experiment 113 00:06:19,842 --> 00:06:22,142 with law-enforcement officers, 114 00:06:22,143 --> 00:06:24,678 he finds that their expert training 115 00:06:24,679 --> 00:06:28,849 significantly reduced the occurrence of fatal mistakes. 116 00:06:28,850 --> 00:06:31,786 But no matter what their background or training, 117 00:06:31,787 --> 00:06:37,293 most participants are quicker to shoot at a black target. 118 00:06:38,694 --> 00:06:39,827 Does this mean 119 00:06:39,828 --> 00:06:43,330 that white Americans are inherently bigoted? 120 00:06:43,331 --> 00:06:47,902 An utterly shocking trend with Josh's black participants 121 00:06:47,903 --> 00:06:51,607 suggests that it's much more complicated than that. 122 00:07:01,316 --> 00:07:02,285 [ Gunshot ] 123 00:07:03,953 --> 00:07:08,623 We see that black participants show the same anti-black bias 124 00:07:08,624 --> 00:07:10,126 that white participants do. 125 00:07:10,992 --> 00:07:12,293 Actually when we test 126 00:07:12,294 --> 00:07:14,729 to see if there is a difference in the two groups, 127 00:07:14,730 --> 00:07:16,729 white participants versus black participants, 128 00:07:16,730 --> 00:07:18,767 they are not statistically different from each other. 129 00:07:21,237 --> 00:07:22,205 [ Gunshot ] 130 00:07:23,872 --> 00:07:26,339 So, we think this represents 131 00:07:26,340 --> 00:07:28,877 an awareness of a cultural stereotype, 132 00:07:28,878 --> 00:07:32,447 not that our participants believe necessarily 133 00:07:32,448 --> 00:07:34,882 that black men are more dangerous than white men. 134 00:07:34,883 --> 00:07:36,017 [ Gun cocks ] 135 00:07:36,018 --> 00:07:38,853 But by virtue of the movies that they watch, 136 00:07:38,854 --> 00:07:41,223 the music that they listen to, news reports, 137 00:07:41,224 --> 00:07:42,322 they're getting the idea 138 00:07:42,323 --> 00:07:44,892 that "black male" goes with "violent." 139 00:07:44,893 --> 00:07:46,327 [ Siren wails ] 140 00:07:46,328 --> 00:07:49,430 The group and the idea are linked together in their brains 141 00:07:49,431 --> 00:07:52,101 whether they agree with that stereotype or not. 142 00:07:53,634 --> 00:07:57,205 Why would we make life-and-death decisions 143 00:07:57,206 --> 00:08:01,241 based on stereotypes we don't even believe? 144 00:08:01,242 --> 00:08:02,310 I've always thought 145 00:08:02,311 --> 00:08:05,346 we could overcome these bigoted ideas. 146 00:08:05,347 --> 00:08:10,284 But one neuroscientist says it's not that simple. 147 00:08:10,285 --> 00:08:15,491 Racist stereotypes hijack our subconscious minds. 148 00:08:17,693 --> 00:08:19,928 Neuroscientist Jon Freeman believes 149 00:08:19,929 --> 00:08:24,164 that we all carry around stereotypes in our subconscious. 150 00:08:24,165 --> 00:08:28,435 In fact, the instant you see another person's face, 151 00:08:28,436 --> 00:08:32,606 your brain first perceives them as a stereotype of their race, 152 00:08:32,607 --> 00:08:36,044 gender, or sexual orientation. 153 00:08:36,045 --> 00:08:39,646 So when you first lay eyes on a young Asian student, 154 00:08:39,647 --> 00:08:42,550 she might register as... 155 00:08:43,617 --> 00:08:46,554 The stereotypical Asian overachiever... 156 00:08:47,789 --> 00:08:50,691 But only for an instant. 157 00:08:50,692 --> 00:08:52,894 The way we make snap judgments about others is 158 00:08:52,895 --> 00:08:55,462 nowhere near politically correct. 159 00:08:55,463 --> 00:08:57,765 Whether you like it or not, 160 00:08:57,766 --> 00:09:00,333 a well-groomed man may first trigger 161 00:09:00,334 --> 00:09:03,103 a stale stereotype in your subconscious mind... 162 00:09:03,104 --> 00:09:05,874 [ Whistle blows, upbeat music plays ] 163 00:09:05,875 --> 00:09:09,510 Until your conscious mind corrects you. 164 00:09:09,511 --> 00:09:11,946 Jon wants to understand precisely 165 00:09:11,947 --> 00:09:15,116 why first impressions conjure up clich?s. 166 00:09:15,117 --> 00:09:18,986 Woman: Excuse me. Jon? 167 00:09:18,987 --> 00:09:20,756 I'm a docile white girl. 168 00:09:21,689 --> 00:09:24,859 And he wants to learn if there's a way for us 169 00:09:24,860 --> 00:09:27,895 to see through these clich?s. 170 00:09:27,896 --> 00:09:29,496 Jon: It takes hundreds of milliseconds 171 00:09:29,497 --> 00:09:32,466 for that judgment to sort of crystallize and form, 172 00:09:32,467 --> 00:09:34,568 and a lot happens during that process. 173 00:09:34,569 --> 00:09:36,136 And we are only beginning to understand 174 00:09:36,137 --> 00:09:38,338 what the implications of that might be. 175 00:09:38,339 --> 00:09:41,609 Jon uses brain scanners to determine exactly 176 00:09:41,610 --> 00:09:43,144 what is going on in the brain 177 00:09:43,145 --> 00:09:46,280 during the first fraction of a second of perception, 178 00:09:46,281 --> 00:09:48,616 long before we are consciously aware 179 00:09:48,617 --> 00:09:50,086 of what we're looking at. 180 00:09:51,152 --> 00:09:53,688 The brain is like an office, 181 00:09:53,689 --> 00:09:57,957 where two key desks handle most of the face-analyzing workload, 182 00:09:57,958 --> 00:10:00,195 the fusiform face area... 183 00:10:02,463 --> 00:10:05,699 And the orbitofrontal cortex. 184 00:10:05,700 --> 00:10:09,370 When a visual signal arrives, 185 00:10:09,371 --> 00:10:12,606 they both get to work simultaneously to process it 186 00:10:12,607 --> 00:10:15,242 in their own specialized ways. 187 00:10:15,243 --> 00:10:17,111 Jon: The fusiform face area is 188 00:10:17,112 --> 00:10:19,947 involved in taking visual information 189 00:10:19,948 --> 00:10:21,750 and forming a coherent representation 190 00:10:21,751 --> 00:10:24,318 of the identity and, say, the gender 191 00:10:24,319 --> 00:10:25,688 and the race of the face. 192 00:10:28,290 --> 00:10:31,693 Morgan: But across the way, the orbitofrontal cortex is 193 00:10:31,694 --> 00:10:34,895 focused on associating that face with all the knowledge it has 194 00:10:34,896 --> 00:10:36,198 about the world. 195 00:10:37,399 --> 00:10:40,067 Jon: The orbitofrontal cortex is retrieving 196 00:10:40,068 --> 00:10:43,438 all of the associations spontaneously without awareness. 197 00:10:43,439 --> 00:10:45,973 Morgan: When it sees a black man's face, 198 00:10:45,974 --> 00:10:48,610 the orbitofrontal cortex quickly looks up 199 00:10:48,611 --> 00:10:52,047 all the general information the brain has about black men, 200 00:10:52,048 --> 00:10:59,220 including many stereotypes, and alters the visual signal. 201 00:10:59,221 --> 00:11:02,456 So, some brain regions can sort of convince other brain regions 202 00:11:02,457 --> 00:11:04,792 to be in line with them. 203 00:11:04,793 --> 00:11:07,863 Morgan: Because of this, stereotypes can hijack 204 00:11:07,864 --> 00:11:09,864 the signal from our eyes... 205 00:11:10,833 --> 00:11:15,035 And change what we perceive. 206 00:11:15,036 --> 00:11:16,603 When test subjects look 207 00:11:16,604 --> 00:11:19,240 at a black male with a neutral expression, 208 00:11:19,241 --> 00:11:21,842 their brains immediately light up 209 00:11:21,843 --> 00:11:24,611 as if they are perceiving anger. 210 00:11:24,612 --> 00:11:26,947 And even though they don't realize it, 211 00:11:26,948 --> 00:11:30,018 when they look at a white female with a blank gaze, 212 00:11:30,019 --> 00:11:34,454 their brain's instant reaction is to perceive happiness. 213 00:11:34,455 --> 00:11:39,492 These stereotypes take place in all of the brains Jon studied, 214 00:11:39,493 --> 00:11:44,030 no matter their gender, race, or sexual orientation. 215 00:11:44,031 --> 00:11:47,266 These prejudiced thoughts are quickly snuffed out 216 00:11:47,267 --> 00:11:48,803 by the conscious mind, 217 00:11:48,804 --> 00:11:51,472 but that doesn't mean that they're harmless. 218 00:11:51,473 --> 00:11:54,141 Those stereotypes can actually wind up impacting behavior. 219 00:11:54,142 --> 00:11:55,443 So, for example, 220 00:11:55,444 --> 00:11:59,380 if individuals unconsciously see African-American faces 221 00:11:59,381 --> 00:12:02,183 as being slightly more angry than they are, 222 00:12:02,184 --> 00:12:05,586 that's probably going to impact how much they approach 223 00:12:05,587 --> 00:12:08,621 or avoid that individual at a spontaneous level. 224 00:12:08,622 --> 00:12:13,059 Morgan: If we recognize that we are all prone to these biases, 225 00:12:13,060 --> 00:12:14,162 maybe we can compensate... 226 00:12:14,163 --> 00:12:15,130 [ Gunshot ] 227 00:12:15,664 --> 00:12:18,698 ...and avoid unintended acts of prejudice. 228 00:12:18,699 --> 00:12:23,069 But one biologist is attempting to go one step further 229 00:12:23,070 --> 00:12:25,073 to manipulate animal minds... 230 00:12:27,075 --> 00:12:29,144 And override their bigotry. 231 00:12:30,821 --> 00:12:36,158 A stereotype is the brain's way of saving time. 232 00:12:36,159 --> 00:12:39,228 It looks at people or objects 233 00:12:39,229 --> 00:12:43,733 and makes quick decisions about them. 234 00:12:43,734 --> 00:12:47,836 Who'd want to eat this disgusting thing? 235 00:12:47,837 --> 00:12:51,576 But these mental shortcuts can lead us astray. 236 00:12:55,244 --> 00:12:57,113 Mmm. 237 00:12:57,114 --> 00:12:59,349 Delicious. 238 00:12:59,350 --> 00:13:02,185 Can we look beyond appearances 239 00:13:02,186 --> 00:13:04,855 and see people for who they really are? 240 00:13:10,427 --> 00:13:12,494 Neuroscientist Peggy Mason knows 241 00:13:12,495 --> 00:13:14,464 that getting through her daily routine 242 00:13:14,465 --> 00:13:20,836 requires looking at everything as a stereotype. 243 00:13:20,837 --> 00:13:23,372 A basket of freshly plucked vegetables is 244 00:13:23,373 --> 00:13:25,708 a vegetable basket. 245 00:13:25,709 --> 00:13:29,378 Vegetable baskets contain vegetables. 246 00:13:29,379 --> 00:13:32,315 don't they? 247 00:13:32,316 --> 00:13:34,749 Mason: We make expectations about everything, 248 00:13:34,750 --> 00:13:36,953 and they smooth the way. 249 00:13:36,954 --> 00:13:38,387 They're shortcuts. 250 00:13:38,388 --> 00:13:41,558 They make our life happen much faster and much more easily. 251 00:13:44,695 --> 00:13:46,597 Morgan: Without the ability to stereotype, 252 00:13:46,598 --> 00:13:49,431 everything we do would take enormous mental effort 253 00:13:49,432 --> 00:13:52,835 to understand. 254 00:13:52,836 --> 00:13:54,871 We could take nothing for granted. 255 00:13:59,243 --> 00:14:01,978 We have relied on stereotyping for eons 256 00:14:01,979 --> 00:14:05,580 to quickly tell our tribe from outsiders. 257 00:14:05,581 --> 00:14:08,551 For all the hurt that stereotyping causes, 258 00:14:08,552 --> 00:14:12,687 it's fundamental to how our brains work. 259 00:14:12,688 --> 00:14:15,758 So, we're more likely to help those closest to us, 260 00:14:15,759 --> 00:14:17,359 and for complete strangers 261 00:14:17,360 --> 00:14:19,862 that we've never even seen the likes of, 262 00:14:19,863 --> 00:14:22,297 we're not so likely to help them. 263 00:14:22,298 --> 00:14:24,700 Morgan: Peggy wanted to see if there might be a way 264 00:14:24,701 --> 00:14:28,336 to get the brain to overcome these biases. 265 00:14:28,337 --> 00:14:32,108 I think that we humans act in part 266 00:14:32,109 --> 00:14:35,878 due to our shared mammalian biology, 267 00:14:35,879 --> 00:14:39,381 and I think that we can increase social cohesion 268 00:14:39,382 --> 00:14:41,452 in modern society amongst humans. 269 00:14:43,854 --> 00:14:47,223 Morgan: She began with a mammal that has a simpler brain than ours... 270 00:14:47,224 --> 00:14:48,257 [ Rat squeaking ] 271 00:14:48,258 --> 00:14:50,694 Mason: Hey, little guys. How you doing? 272 00:14:50,695 --> 00:14:52,427 You're okay, little buddy. 273 00:14:52,428 --> 00:14:55,397 Morgan: ...The rat, a creature who typically 274 00:14:55,398 --> 00:14:59,536 only aids members of its own strain. 275 00:14:59,537 --> 00:15:01,170 Peggy's experiment involves 276 00:15:01,171 --> 00:15:04,440 temporarily trapping a rat in a plastic tube. 277 00:15:04,441 --> 00:15:06,410 The tube has just one way out, 278 00:15:06,411 --> 00:15:10,814 through a door that can only be opened by another rat. 279 00:15:10,815 --> 00:15:13,449 When another rat from the same strain is added 280 00:15:13,450 --> 00:15:15,551 to the chamber, it's not long 281 00:15:15,552 --> 00:15:20,723 before he works out how to free his imprisoned fellow tribesman. 282 00:15:20,724 --> 00:15:25,328 Mason: These are all albino rats of the sprague dawley stock. 283 00:15:25,329 --> 00:15:28,564 And so, while they are not identical 284 00:15:28,565 --> 00:15:30,633 and they've never met each other, 285 00:15:30,634 --> 00:15:34,903 they also might look like the fifth cousin twice removed. 286 00:15:34,904 --> 00:15:38,208 Morgan: If the rat looks familiar, the other rat helps. 287 00:15:38,209 --> 00:15:40,410 But then Peggy repeats the experiment 288 00:15:40,411 --> 00:15:43,179 with rats of unrelated strains. 289 00:15:43,180 --> 00:15:45,980 Now it's a black capped rat in the tube, 290 00:15:45,981 --> 00:15:49,951 and an albino rat has the option to free him. 291 00:15:49,952 --> 00:15:52,253 Mason: They've never met a black capped rat before. 292 00:15:52,254 --> 00:15:53,822 They don't open for them. 293 00:15:53,823 --> 00:15:55,258 They have no affiliative bond, 294 00:15:55,259 --> 00:15:57,060 and therefore they do not act prosocially 295 00:15:57,061 --> 00:16:02,665 towards these very strange-looking type of rats. 296 00:16:02,666 --> 00:16:05,501 Morgan: But can a rat ever change its ways? 297 00:16:05,502 --> 00:16:09,370 To find out, Peggy exposes a white rat 298 00:16:09,371 --> 00:16:11,040 to a black capped rat. 299 00:16:11,041 --> 00:16:13,309 Mason: We took albino rats. 300 00:16:13,310 --> 00:16:15,344 We housed them with black capped rats 301 00:16:15,345 --> 00:16:16,811 for two weeks. 302 00:16:16,812 --> 00:16:20,648 Then we rehoused them with an albino rat 303 00:16:20,649 --> 00:16:23,553 so they've known one black capped rat. 304 00:16:24,721 --> 00:16:28,157 Morgan: Does this experience make the albino empathetic 305 00:16:28,158 --> 00:16:30,528 to all black capped rats? 306 00:16:32,562 --> 00:16:35,263 To find out, she places him in the arena 307 00:16:35,264 --> 00:16:38,868 with a trapped black capped rat that he's never met before. 308 00:16:38,869 --> 00:16:40,738 [ Rat squeaking ] 309 00:16:49,278 --> 00:16:54,117 The albino rat breaks through the color line. 310 00:16:54,118 --> 00:16:57,753 Mason: What that suggested was that just having a bond 311 00:16:57,754 --> 00:17:01,790 to one black capped rat would allow an albino rat 312 00:17:01,791 --> 00:17:05,128 to generalize all the black capped rats. 313 00:17:05,129 --> 00:17:07,830 They've known one. They've lived with one. 314 00:17:07,831 --> 00:17:09,698 Now they get tested with strangers. 315 00:17:09,699 --> 00:17:10,766 And lo and behold, 316 00:17:10,767 --> 00:17:13,368 they're perfectly helpful to the strangers. 317 00:17:13,369 --> 00:17:17,439 So that was really exceptional to me 318 00:17:17,440 --> 00:17:21,644 because it showed that experience was so powerful. 319 00:17:21,645 --> 00:17:23,614 Morgan: It may not be as hard as you think 320 00:17:23,615 --> 00:17:26,080 for a bigot to have a change of heart. 321 00:17:26,081 --> 00:17:28,518 If any of us has a positive experience 322 00:17:28,519 --> 00:17:31,121 with someone from a different racial group, 323 00:17:31,122 --> 00:17:34,657 biology has the power to make us feel empathy 324 00:17:34,658 --> 00:17:36,891 for a stranger from that group. 325 00:17:36,892 --> 00:17:41,930 In fact, Peggy believes that empathy is a primal instinct 326 00:17:41,931 --> 00:17:43,299 for all mammals. 327 00:17:43,300 --> 00:17:48,437 What rats tell us is that we have a mammalian inheritance 328 00:17:48,438 --> 00:17:53,775 which makes us want to help another in distress. 329 00:17:53,776 --> 00:17:56,579 But the amazing thing that we learn from the rats is 330 00:17:56,580 --> 00:18:00,081 that what the rats need to do is to have an experience 331 00:18:00,082 --> 00:18:01,817 with a different type of rat, 332 00:18:01,818 --> 00:18:05,989 and then that rat can be part of their ingroup, too. 333 00:18:05,990 --> 00:18:11,360 And that's really an amazing and hopeful message, I think. 334 00:18:11,361 --> 00:18:15,764 Empathy has enormous power. 335 00:18:15,765 --> 00:18:19,167 Images of Nelson Mandela behind bars 336 00:18:19,168 --> 00:18:24,139 evoked such compassion from people of all races 337 00:18:24,140 --> 00:18:29,278 that they helped end apartheid in South Africa. 338 00:18:29,279 --> 00:18:33,549 But there's another darker side to the human mind, 339 00:18:33,550 --> 00:18:35,884 one that allows us to take pleasure 340 00:18:35,885 --> 00:18:39,054 in the pain of others 341 00:18:39,055 --> 00:18:43,693 and could make us addicted to bigotry. 342 00:18:45,821 --> 00:18:50,591 Bigotry is as old as human society. 343 00:18:50,592 --> 00:18:56,464 We persecute people of different skin color, 344 00:18:56,465 --> 00:19:01,102 of different religion. 345 00:19:01,103 --> 00:19:06,241 We discriminate between men and women. 346 00:19:06,242 --> 00:19:10,811 But bigotry isn't just about the circumstances of your birth. 347 00:19:10,812 --> 00:19:15,650 Even fans of rival sports teams can learn to hate one another 348 00:19:15,651 --> 00:19:19,054 with all the venom of a bigot. 349 00:19:20,022 --> 00:19:23,758 Harvard psychologist Mina cikara has been thinking 350 00:19:23,759 --> 00:19:28,897 about how human beings move from individuals, to groups 351 00:19:28,898 --> 00:19:31,399 to bitter, violent rivals. 352 00:19:31,400 --> 00:19:34,302 Imagine a group of perfect strangers. 353 00:19:34,303 --> 00:19:39,206 It takes very little for them to form devout tribal alliances. 354 00:19:39,207 --> 00:19:41,842 Well, one of the most amazing things about humans is 355 00:19:41,843 --> 00:19:43,611 how readily they form groups. 356 00:19:43,612 --> 00:19:46,313 In fact, psychological research has shown 357 00:19:46,314 --> 00:19:48,349 that you can randomly assign people 358 00:19:48,350 --> 00:19:50,284 to red team or blue team, 359 00:19:50,285 --> 00:19:52,521 and that's enough to make them show 360 00:19:52,522 --> 00:19:54,321 what we call ingroup bias. 361 00:19:54,322 --> 00:19:57,693 They prefer their ingroup, they treat them better, 362 00:19:57,694 --> 00:20:00,162 they devote more resources to them, 363 00:20:00,163 --> 00:20:02,899 and, in general, it's just a part of human nature. 364 00:20:07,369 --> 00:20:09,670 Morgan: Since the dawn of humanity, 365 00:20:09,671 --> 00:20:14,643 we have needed the support of others to thrive and survive. 366 00:20:14,644 --> 00:20:17,613 So when two groups come into direct competition, 367 00:20:17,614 --> 00:20:21,383 no matter arbitrarily those groups were formed, 368 00:20:21,384 --> 00:20:24,453 the individuals will put the needs of the group 369 00:20:24,454 --> 00:20:26,221 above themselves. 370 00:20:26,222 --> 00:20:29,192 A line is drawn in the sand. 371 00:20:36,032 --> 00:20:37,666 Out. Nice job. 372 00:20:37,667 --> 00:20:39,967 "Out"? What... give me a break. 373 00:20:39,968 --> 00:20:44,272 All-out violence needs only a little provocation. 374 00:20:44,273 --> 00:20:45,674 You were out. 375 00:20:45,675 --> 00:20:46,875 [ Scoffs ] 376 00:20:46,876 --> 00:20:49,511 A dose of escalation... 377 00:20:49,512 --> 00:20:51,112 And both sides will... 378 00:20:51,113 --> 00:20:52,214 [ All shouting indistinctly ] 379 00:20:52,215 --> 00:20:53,481 Charge. 380 00:20:53,482 --> 00:20:55,483 [ Shouting continues ] 381 00:20:55,484 --> 00:20:57,484 [ Upbeat music plays ] 382 00:20:57,485 --> 00:20:59,522 [ Crashing, thumping ] 383 00:21:01,956 --> 00:21:06,628 In general, people are adverse to treating other people badly. 384 00:21:06,629 --> 00:21:08,997 But that's the thing about competition. 385 00:21:08,998 --> 00:21:10,732 Being a good ingroup member 386 00:21:10,733 --> 00:21:12,466 means being a jerk to the out group. 387 00:21:12,467 --> 00:21:13,768 Aah! 388 00:21:13,769 --> 00:21:16,072 It's not just that you want your own team to do well. 389 00:21:16,073 --> 00:21:18,939 It's that you have to make sure that the other team doesn't. 390 00:21:18,940 --> 00:21:20,009 Aaaaaah! 391 00:21:20,010 --> 00:21:21,476 Aaaah! 392 00:21:21,477 --> 00:21:24,445 Morgan: Mina wants to know why this desire 393 00:21:24,446 --> 00:21:27,782 to persecute the other overrides our better judgment. 394 00:21:27,783 --> 00:21:29,285 Aaaaah! 395 00:21:32,921 --> 00:21:37,091 These two are a couple of stand-up guys. 396 00:21:37,092 --> 00:21:40,595 They certainly would never beat each other into a pulp... 397 00:21:40,596 --> 00:21:42,098 Unless it's game day. 398 00:21:43,032 --> 00:21:46,667 Today Mina is going to scan their brains 399 00:21:46,668 --> 00:21:49,437 as they watch their rival team suffer. 400 00:21:49,438 --> 00:21:50,704 So, what we did was we recruited 401 00:21:50,705 --> 00:21:53,841 18 die-hard Red Sox and Yankees fans. 402 00:21:53,842 --> 00:21:57,312 And the idea was we wanted people to watch plays 403 00:21:57,313 --> 00:22:00,214 where their rivals did poorly against another third team, 404 00:22:00,215 --> 00:22:00,982 the orioles. 405 00:22:00,983 --> 00:22:01,849 [ Crowd cheering ] 406 00:22:01,850 --> 00:22:04,019 The Red Sox fan watches a video 407 00:22:04,020 --> 00:22:07,188 where Alex Rodriguez of the Yankees is pelted 408 00:22:07,189 --> 00:22:09,357 by a 100-mile-per-hour fast ball. 409 00:22:09,358 --> 00:22:10,559 [ Baseball thuds, crowd groans ] 410 00:22:10,560 --> 00:22:13,762 Man: Ooh! That's gonna leave a mark. 411 00:22:13,763 --> 00:22:17,366 Morgan: The Yankees fan gets to enjoy an embarrassing mistake 412 00:22:17,367 --> 00:22:21,537 that cost the Red Sox three runs in a single play. 413 00:22:21,538 --> 00:22:23,538 [ Baseball bat cracks, crowd groans ] 414 00:22:23,539 --> 00:22:26,308 Man: What a disaster. 415 00:22:26,309 --> 00:22:30,345 Ooh, how embarrassing for the Red Sox. 416 00:22:30,346 --> 00:22:31,646 Morgan: Mina discovered 417 00:22:31,647 --> 00:22:35,215 that this feeling of pleasure at our rival's pain, 418 00:22:35,216 --> 00:22:38,387 what the Germans call schadenfreude, 419 00:22:38,388 --> 00:22:42,256 is something our brains learn to crave. 420 00:22:42,257 --> 00:22:44,859 When participants watch their rivals fail, 421 00:22:44,860 --> 00:22:46,561 what we saw that there was activations 422 00:22:46,562 --> 00:22:48,730 of the region called the ventral striatum. 423 00:22:48,731 --> 00:22:51,400 The way that this region purportedly works is 424 00:22:51,401 --> 00:22:54,336 that it basically tags positive information, 425 00:22:54,337 --> 00:22:57,539 rewarding events, so that people then can say, 426 00:22:57,540 --> 00:23:00,908 "oh, I should come back to this in order to get pleasure again." 427 00:23:00,909 --> 00:23:05,813 Morgan: The ventral striatum is at the core of many addictions. 428 00:23:05,814 --> 00:23:08,182 When a smoker sees a cigarette, 429 00:23:08,183 --> 00:23:11,720 their ventral striatum reminds them of its pleasures. 430 00:23:11,721 --> 00:23:15,524 And just as a cigarette a day can soon become a pack a day, 431 00:23:15,525 --> 00:23:17,692 couldn't seeing your rival suffer 432 00:23:17,693 --> 00:23:20,462 make you want to see it happen more and more? 433 00:23:20,463 --> 00:23:21,997 Cikara: So, the question then is 434 00:23:21,998 --> 00:23:24,765 whether or not watching your rival suffer misfortune 435 00:23:24,766 --> 00:23:26,801 makes you then more likely to endorse harm 436 00:23:26,802 --> 00:23:28,803 or actually do harm to the rival team 437 00:23:28,804 --> 00:23:30,772 and affiliated individuals. 438 00:23:30,773 --> 00:23:32,942 Well, we have evidence to suggest that it does. 439 00:23:34,275 --> 00:23:36,211 Morgan: What troubles Mina is 440 00:23:36,212 --> 00:23:38,515 that this line of group-oriented thinking 441 00:23:38,516 --> 00:23:41,281 extends beyond sports teams. 442 00:23:41,282 --> 00:23:44,485 In fact, we see everybody belonging 443 00:23:44,486 --> 00:23:47,422 to one of four social categories. 444 00:23:47,423 --> 00:23:50,024 The first time you meet a new person or a group, 445 00:23:50,025 --> 00:23:52,026 there are two questions you need answered right away. 446 00:23:52,027 --> 00:23:53,727 The first is "friend or foe," 447 00:23:53,728 --> 00:23:55,797 and the second is, "how capable are they 448 00:23:55,798 --> 00:23:58,666 of enacting their intentions toward me, good or ill?" 449 00:23:58,667 --> 00:24:01,636 Morgan: First, there are the friendly groups. 450 00:24:01,637 --> 00:24:04,005 Bright, young kids and doctors, for example, 451 00:24:04,006 --> 00:24:06,442 we usually see as competent. 452 00:24:06,443 --> 00:24:10,445 Less capable friendly groups, like the elderly and infirm, 453 00:24:10,446 --> 00:24:12,914 usually invoke pity. 454 00:24:12,915 --> 00:24:15,584 Drug addicts or teenage Internet bullies, 455 00:24:15,585 --> 00:24:17,919 we categorize as foe. 456 00:24:17,920 --> 00:24:20,422 But these groups aren't competent enough 457 00:24:20,423 --> 00:24:22,991 to spend much energy hating. 458 00:24:22,992 --> 00:24:27,928 It's the people seen both as foe and highly competent 459 00:24:27,929 --> 00:24:31,099 who stir the strong urges toward bigotry. 460 00:24:31,100 --> 00:24:34,903 This includes investment bankers but also groups like asians 461 00:24:34,904 --> 00:24:38,308 or professional women in domains where men generally dominate. 462 00:24:39,975 --> 00:24:42,109 Morgan: Mina studied hundreds of subjects 463 00:24:42,110 --> 00:24:46,580 who report feeling pleasure when members of these groups suffer. 464 00:24:46,581 --> 00:24:48,649 Cikara: When you ask them who they're most likely to harm, 465 00:24:48,650 --> 00:24:51,252 to just hurt, not actually kill, 466 00:24:51,253 --> 00:24:53,588 they're most willing to harm these competent groups 467 00:24:53,589 --> 00:24:56,457 that are competitive with our own interests. 468 00:24:56,458 --> 00:24:58,893 So what's really interesting about these groups is 469 00:24:58,894 --> 00:25:00,695 that, in times of social stability, 470 00:25:00,696 --> 00:25:02,696 people go along to get along with them 471 00:25:02,697 --> 00:25:04,666 because they control resources. 472 00:25:04,667 --> 00:25:07,403 But they're also the first ones to get scapegoated 473 00:25:07,404 --> 00:25:09,705 when social relations become unstable. 474 00:25:10,821 --> 00:25:12,624 Morgan: Being part of a group is 475 00:25:12,625 --> 00:25:15,326 an unavoidable part of being human. 476 00:25:15,327 --> 00:25:18,328 But groupism does more than just block 477 00:25:18,329 --> 00:25:20,731 our natural empathy for others. 478 00:25:20,732 --> 00:25:23,867 When it involves a political agenda, 479 00:25:23,868 --> 00:25:26,937 groupism may actually hack our brains 480 00:25:26,938 --> 00:25:29,807 into perceiving a false reality. 481 00:25:29,808 --> 00:25:32,609 Do you see the world as it really is 482 00:25:32,610 --> 00:25:37,116 or how your political party wants you to see it? 483 00:25:38,821 --> 00:25:40,989 We're a tribal species, 484 00:25:40,990 --> 00:25:43,660 and we all want to be in the winning tribe. 485 00:25:45,228 --> 00:25:49,163 But surely humanity can aspire to rise above this, 486 00:25:49,164 --> 00:25:52,534 to bridge the divide between us. 487 00:25:52,535 --> 00:25:55,304 Democracy was founded in the principle of equality, 488 00:25:55,305 --> 00:25:58,739 that we could reach across the aisle and compromise. 489 00:25:58,740 --> 00:26:00,643 But with every passing year, 490 00:26:00,644 --> 00:26:02,544 political parties seem to be getting 491 00:26:02,545 --> 00:26:05,314 more and more divided. 492 00:26:05,315 --> 00:26:09,485 Maybe it's because conservatives are bigoted 493 00:26:09,486 --> 00:26:12,587 against liberals. 494 00:26:12,588 --> 00:26:14,790 I think you have it backward. 495 00:26:19,729 --> 00:26:22,631 Darren Schreiber is an American political scientist 496 00:26:22,632 --> 00:26:25,800 now working in exeter, u.K. 497 00:26:25,801 --> 00:26:27,402 If there's one thing he's learned 498 00:26:27,403 --> 00:26:29,604 from moving across the pond, 499 00:26:29,605 --> 00:26:32,172 it's that no matter where you go, 500 00:26:32,173 --> 00:26:37,113 liberals and conservatives are not from the same planet. 501 00:26:37,114 --> 00:26:38,813 Do you see yourself as being more liberal 502 00:26:38,814 --> 00:26:39,882 or more conservative? 503 00:26:39,883 --> 00:26:41,350 Definitely more conservative. 504 00:26:41,351 --> 00:26:42,950 I'd see myself more liberal. 505 00:26:42,951 --> 00:26:44,752 Military intervention in the middle east... 506 00:26:44,753 --> 00:26:45,754 How do you feel about that? 507 00:26:45,755 --> 00:26:47,156 I think it's absolutely fundamental. 508 00:26:47,157 --> 00:26:50,325 Each country should be allowed to determine their own future. 509 00:26:50,326 --> 00:26:52,294 What do you think about immigration policy? 510 00:26:52,295 --> 00:26:53,862 The borders need to be slightly more closed. 511 00:26:53,863 --> 00:26:55,599 We should have an open-border policy. 512 00:26:55,600 --> 00:27:00,102 Liberals and conservatives rarely see eye to eye. 513 00:27:00,103 --> 00:27:04,472 Could it be that they have different brains? 514 00:27:04,473 --> 00:27:07,575 Darren decided he would try to uncover the truth 515 00:27:07,576 --> 00:27:10,945 by using an mri brain scanner to see 516 00:27:10,946 --> 00:27:14,016 how the brains of liberals and conservatives handled 517 00:27:14,017 --> 00:27:17,818 decision-making in a simple gambling game. 518 00:27:17,819 --> 00:27:22,156 Today, Darren and his students are re-creating that experiment 519 00:27:22,157 --> 00:27:24,692 but without the mri. 520 00:27:24,693 --> 00:27:29,632 Each test subject is given ?1... About a buck and a half. 521 00:27:29,633 --> 00:27:33,134 They can keep the money, or they can gamble with it. 522 00:27:33,135 --> 00:27:35,569 There's a chance to double the winnings 523 00:27:35,570 --> 00:27:38,707 but also a risk of losing it all. 524 00:27:38,708 --> 00:27:41,209 Do you want to keep that ?1, or do you want to take a risk 525 00:27:41,210 --> 00:27:43,412 at potentially winning or losing ?2? 526 00:27:43,413 --> 00:27:44,813 I will risk ?2. 527 00:27:44,814 --> 00:27:47,214 All right, so open up the envelope 528 00:27:47,215 --> 00:27:48,684 and see what you get. 529 00:27:50,452 --> 00:27:51,652 I've won ?2. 530 00:27:51,653 --> 00:27:52,755 Good. All right. 531 00:27:52,756 --> 00:27:54,021 So here's ?2. 532 00:27:54,022 --> 00:27:55,423 Do you want to keep the ?1, 533 00:27:55,424 --> 00:27:57,425 or do you want to risk potentially winning 534 00:27:57,426 --> 00:27:58,727 or losing ?2? 535 00:27:58,728 --> 00:28:01,331 I think I'll take a risk at winning ?2. 536 00:28:01,332 --> 00:28:02,298 Okay. 537 00:28:03,200 --> 00:28:04,098 I've won ?2. 538 00:28:04,099 --> 00:28:05,432 Whoo-hoo. Congratulations. 539 00:28:05,433 --> 00:28:07,536 So, here's your ?2. 540 00:28:07,537 --> 00:28:08,702 [ Laughing ] I've lost ?1. 541 00:28:08,703 --> 00:28:10,005 You've lost. All right. 542 00:28:10,006 --> 00:28:12,108 Well, you have to give me ?4 now. 543 00:28:12,109 --> 00:28:13,442 Thanks, Sophie. 544 00:28:14,544 --> 00:28:17,013 Darren doesn't care who wins or loses. 545 00:28:17,014 --> 00:28:20,149 His only interest is in how their brains deal 546 00:28:20,150 --> 00:28:22,816 with taking gambling risks, 547 00:28:22,817 --> 00:28:26,221 an act that has no intrinsic political slant. 548 00:28:26,222 --> 00:28:30,793 But to his surprise, liberals and conservatives processed risk 549 00:28:30,794 --> 00:28:33,930 with wildly different regions of their brains. 550 00:28:35,897 --> 00:28:39,367 Conservative brains consistently use the amygdala 551 00:28:39,368 --> 00:28:42,770 to make the decisions to risk everything. 552 00:28:42,771 --> 00:28:45,606 This region is associated with gut feeling 553 00:28:45,607 --> 00:28:48,009 and fight-or-flight responses. 554 00:28:48,010 --> 00:28:50,112 Red brains experienced risk 555 00:28:50,113 --> 00:28:53,150 as a threat with a potential reward. 556 00:28:55,050 --> 00:28:59,287 Liberal brains consistently use the insula when gambling, 557 00:28:59,288 --> 00:29:00,823 a region associated 558 00:29:00,824 --> 00:29:03,392 with perception of one's own feelings. 559 00:29:03,393 --> 00:29:08,563 Blue brains experienced risk as a problem to be solved. 560 00:29:08,564 --> 00:29:12,902 Both brains end up at similar conclusions about taking risks, 561 00:29:12,903 --> 00:29:17,471 but their brains experience it differently. 562 00:29:17,472 --> 00:29:21,043 What it tells us is that being a political liberal 563 00:29:21,044 --> 00:29:23,612 or a political conservative influences 564 00:29:23,613 --> 00:29:25,780 everything that we see, 565 00:29:25,781 --> 00:29:27,882 that we see the world in really different ways, 566 00:29:27,883 --> 00:29:30,818 we use different mental tools when we're processing 567 00:29:30,819 --> 00:29:32,520 even basic things like gambling 568 00:29:32,521 --> 00:29:35,524 that appear to have nothing to do with politics. 569 00:29:35,525 --> 00:29:36,826 And that just blew our minds. 570 00:29:37,559 --> 00:29:39,595 Morgan: So, why is this? 571 00:29:39,596 --> 00:29:41,796 Are we born with our future politics 572 00:29:41,797 --> 00:29:45,700 already fixed in the structure of our brains? 573 00:29:45,701 --> 00:29:47,102 We're unsure about this, 574 00:29:47,103 --> 00:29:48,836 and I actually have a study where we're gonna be looking 575 00:29:48,837 --> 00:29:51,672 to see with a data set that has studied children 576 00:29:51,673 --> 00:29:53,408 from age 4 to 20, 577 00:29:53,409 --> 00:29:55,210 the differences in people's brains 578 00:29:55,211 --> 00:29:57,479 and do they change over time. 579 00:29:57,480 --> 00:29:59,716 But what we know right now is that people, 580 00:29:59,717 --> 00:30:01,216 when they're around 20, 581 00:30:01,217 --> 00:30:03,820 seem to have different sizes of amygdala and insula 582 00:30:03,821 --> 00:30:06,954 depending on whether they're liberals or conservatives. 583 00:30:06,955 --> 00:30:09,923 Morgan: Darren expects that, by the time we are 20, 584 00:30:09,924 --> 00:30:11,692 most of us will have solidified 585 00:30:11,693 --> 00:30:14,895 the color of our political brain. 586 00:30:14,896 --> 00:30:16,664 The possibility of Harmony 587 00:30:16,665 --> 00:30:18,866 between liberals and conservatives is 588 00:30:18,867 --> 00:30:22,002 therefore unlikely. 589 00:30:22,003 --> 00:30:24,605 Politicians and politically active citizens cannot 590 00:30:24,606 --> 00:30:27,843 truly see things from the other side. 591 00:30:27,844 --> 00:30:31,145 Their brains won't let them. 592 00:30:31,146 --> 00:30:35,284 Our intense partisanship is probably here to stay. 593 00:30:37,019 --> 00:30:39,688 But there may be a way to reshape our brains 594 00:30:39,689 --> 00:30:44,325 to Cherish the greater good of all mankind 595 00:30:44,326 --> 00:30:48,997 and open our minds and hearts to one another 596 00:30:48,998 --> 00:30:51,766 if we all play 597 00:30:51,767 --> 00:30:55,437 ultra-violent video games. 598 00:30:55,438 --> 00:30:57,538 [ Gunfire ] 599 00:30:57,539 --> 00:30:58,874 [ Gun cocks ] 600 00:31:01,821 --> 00:31:04,890 The world is full of hate. 601 00:31:04,891 --> 00:31:08,493 Eliminating bigotry seems hopeless. 602 00:31:08,494 --> 00:31:11,130 But there may be a way... 603 00:31:11,131 --> 00:31:17,670 Pure, unadulterated violence in an alternate reality. 604 00:31:18,771 --> 00:31:20,072 [ Gunfire ] Man: Aah! 605 00:31:20,073 --> 00:31:22,809 Professor Matthew grizzard has spent a lot of time 606 00:31:22,810 --> 00:31:24,610 playing video games. 607 00:31:24,611 --> 00:31:25,678 [ Gunfire ] 608 00:31:25,679 --> 00:31:27,746 But as a communications researcher, 609 00:31:27,747 --> 00:31:32,751 these mediated realities are more than just entertainment. 610 00:31:32,752 --> 00:31:34,151 [ Gunfire ] 611 00:31:34,152 --> 00:31:36,053 We don't necessarily distinguish very much 612 00:31:36,054 --> 00:31:40,659 between mediated reality and real reality. 613 00:31:40,660 --> 00:31:42,026 We see visual elements. 614 00:31:42,027 --> 00:31:45,097 We hear things, auditory elements. 615 00:31:45,098 --> 00:31:47,232 And our bodies respond to those elements 616 00:31:47,233 --> 00:31:48,766 as if they were real. 617 00:31:48,767 --> 00:31:50,901 Morgan: Immersed in a game, 618 00:31:50,902 --> 00:31:53,104 Matthew can feel his pulse pounding 619 00:31:53,105 --> 00:31:56,909 and his stomach churning from the intensity of the experience. 620 00:31:56,910 --> 00:31:58,310 [ Gunfire ] 621 00:31:58,311 --> 00:32:04,016 But one day, a level in a game downright disturbed him. 622 00:32:07,186 --> 00:32:10,188 Grizzard: So, I'm in an elevator. 623 00:32:10,189 --> 00:32:11,657 And I'm looking around, 624 00:32:11,658 --> 00:32:15,462 and there's a lot of armed men in military fatigues with me. 625 00:32:17,729 --> 00:32:19,397 At that point, elevator doors open. 626 00:32:19,398 --> 00:32:20,766 [ Elevator bell dings ] 627 00:32:23,736 --> 00:32:26,405 And we step out into what appears to be a crowded airport. 628 00:32:26,406 --> 00:32:29,142 [ Intercom chatter, [ Indistinct conversations ] 629 00:32:29,143 --> 00:32:31,409 And at that point, the order is given, 630 00:32:31,410 --> 00:32:35,080 and we raise our guns to point at innocent civilians 631 00:32:35,081 --> 00:32:37,047 surrounding this airport. 632 00:32:37,048 --> 00:32:40,118 [ Gun cocks ] 633 00:32:40,119 --> 00:32:41,753 And then, we start firing. 634 00:32:41,754 --> 00:32:43,622 [ Gunfire, people screaming ] 635 00:32:51,831 --> 00:32:53,233 [ People moaning, sobbing ] 636 00:32:56,436 --> 00:32:57,703 Morgan: Matthew felt guilty 637 00:32:57,704 --> 00:33:01,907 for murdering so many innocent pixels. 638 00:33:01,908 --> 00:33:06,277 But as a social psychologist, he knows that guilt is a feeling 639 00:33:06,278 --> 00:33:10,082 that can profoundly change our behavior. 640 00:33:10,083 --> 00:33:11,617 Grizzard: We wanted to see if this guilt 641 00:33:11,618 --> 00:33:13,251 that was elicited from virtual environments 642 00:33:13,252 --> 00:33:16,055 could cause people to think more about real-world morality 643 00:33:16,056 --> 00:33:18,723 and could actually increase their moral sensitivity 644 00:33:18,724 --> 00:33:20,159 to real-world issues. 645 00:33:21,393 --> 00:33:24,361 Morgan: Media pundits often accuse violent video games 646 00:33:24,362 --> 00:33:27,666 of destroying the morality of our youth. 647 00:33:27,667 --> 00:33:29,735 Is that really true? 648 00:33:29,736 --> 00:33:33,237 Matthew has a series of test subjects play a game 649 00:33:33,238 --> 00:33:37,176 where they can hurt simulated human beings. 650 00:33:37,177 --> 00:33:39,378 So, Matthew gives the order 651 00:33:39,379 --> 00:33:44,282 to commit blatant crimes against humanity. 652 00:33:44,283 --> 00:33:47,052 So, we set up a situation where people are gonna play 653 00:33:47,053 --> 00:33:48,719 a violent first-person shooter 654 00:33:48,720 --> 00:33:51,156 where they're engaging in terrorist behaviors, 655 00:33:51,157 --> 00:33:53,192 where they're committing genocides 656 00:33:53,193 --> 00:33:55,026 and they're killing innocent civilians, 657 00:33:55,027 --> 00:33:57,294 they're bombing areas, they're gauging in things 658 00:33:57,295 --> 00:34:01,332 that would be considered morally reprehensible in the real world. 659 00:34:01,333 --> 00:34:03,134 Morgan: Matthew's subjects surrender 660 00:34:03,135 --> 00:34:07,504 to the alternative reality of the game. 661 00:34:07,505 --> 00:34:08,505 [ Gun cocks ] 662 00:34:08,506 --> 00:34:10,107 Inside their minds... 663 00:34:10,108 --> 00:34:11,210 [ Gun cocks ] 664 00:34:11,211 --> 00:34:13,446 They are living through the experience 665 00:34:13,447 --> 00:34:15,214 of being a mass murder. 666 00:34:17,583 --> 00:34:19,951 The game is guilt-inducing... [ Gun cocks ] 667 00:34:19,952 --> 00:34:21,787 To say the least. 668 00:34:26,291 --> 00:34:29,428 So we also had a control group because we wanted to see 669 00:34:29,429 --> 00:34:31,362 and distinguish video-game-induced guilt 670 00:34:31,363 --> 00:34:33,598 from real-world guilt. 671 00:34:33,599 --> 00:34:36,268 So we had individuals remember a situation 672 00:34:36,269 --> 00:34:38,937 in which they felt particularly guilty. 673 00:34:38,938 --> 00:34:42,975 Morgan: Writing this out is emotionally taxing. 674 00:34:42,976 --> 00:34:45,009 It brings back painful memories, 675 00:34:45,010 --> 00:34:48,212 perhaps of the time they cheated on a lover 676 00:34:48,213 --> 00:34:51,516 or lied and got someone else in trouble 677 00:34:51,517 --> 00:34:55,187 or sabotaged a friend for selfish gain. 678 00:34:55,188 --> 00:35:00,658 In every case, real people were really hurt. 679 00:35:00,659 --> 00:35:04,830 Matthew compared this group to the murder-simulator group. 680 00:35:06,599 --> 00:35:09,634 So, our findings showed that individuals recalling 681 00:35:09,635 --> 00:35:13,638 a real-world guilty experience actually felt more guilt 682 00:35:13,639 --> 00:35:15,708 but that guilt solicited by video game 683 00:35:15,709 --> 00:35:19,712 was positively associated with increased moral sensitivity. 684 00:35:19,713 --> 00:35:22,580 Morgan: Committing virtual mass murder 685 00:35:22,581 --> 00:35:26,016 gave his subjects a stronger sense of morality. 686 00:35:26,017 --> 00:35:27,051 [ Gun cocks ] 687 00:35:27,052 --> 00:35:28,752 It's a surprising result, 688 00:35:28,753 --> 00:35:32,123 but Matthew thinks he knows why it's the case. 689 00:35:32,124 --> 00:35:36,962 The players violated their own personal sense of fairness. 690 00:35:36,963 --> 00:35:40,765 They cannot right the wrongs they have committed, 691 00:35:40,766 --> 00:35:44,569 so they atone with a subconscious desire 692 00:35:44,570 --> 00:35:47,172 to be a better person. 693 00:35:47,173 --> 00:35:49,741 I think that's the real power of video games. 694 00:35:49,742 --> 00:35:52,043 You can think of them as kind of moral sandboxes, 695 00:35:52,044 --> 00:35:55,346 as areas where we can explore different aspects of morality 696 00:35:55,347 --> 00:35:57,181 or even take viewpoints that are opposed 697 00:35:57,182 --> 00:35:59,417 to our very core of morality. 698 00:35:59,418 --> 00:36:02,420 Morgan: But it's hard to imagine everyone agreeing 699 00:36:02,421 --> 00:36:06,056 to play guilt-inducting video games. 700 00:36:06,057 --> 00:36:09,094 And there will always be sociopaths 701 00:36:09,095 --> 00:36:11,362 whose bigotry spreads through society 702 00:36:11,363 --> 00:36:12,763 like a deadly virus. 703 00:36:12,764 --> 00:36:17,902 Could it be that we're just too tolerant of intolerance? 704 00:36:17,903 --> 00:36:21,874 What would really happen if we cut off the worst offenders? 705 00:36:23,276 --> 00:36:24,644 Could we ever do it? 706 00:36:29,881 --> 00:36:32,683 In the past century, 707 00:36:32,684 --> 00:36:36,754 we've broken down a lot of walls that divided us. 708 00:36:36,755 --> 00:36:40,824 More social groups have been accepted into the mainstream. 709 00:36:40,825 --> 00:36:45,062 Segregation and prejudice are no longer the laws of the land. 710 00:36:45,063 --> 00:36:47,498 But there are still those who think they're superior 711 00:36:47,499 --> 00:36:52,337 because of their skin color, their age, or their gender. 712 00:36:52,338 --> 00:36:54,906 There may be a way to deal 713 00:36:54,907 --> 00:36:56,977 with these bigots and their bigotry... 714 00:36:59,144 --> 00:37:01,246 Build walls around them. 715 00:37:04,483 --> 00:37:08,652 Sociologist and physician Nicholas christakis is taking 716 00:37:08,653 --> 00:37:12,190 a bird's eye view of human society. 717 00:37:12,191 --> 00:37:13,757 From his perspective, 718 00:37:13,758 --> 00:37:16,728 when bigots flourish in a social network, 719 00:37:16,729 --> 00:37:19,665 it is partly the fault of the group itself. 720 00:37:19,666 --> 00:37:22,132 Christakis: So we're embedded in these networks. 721 00:37:22,133 --> 00:37:23,801 How we act in the world is affected 722 00:37:23,802 --> 00:37:26,069 by how the people we know act 723 00:37:26,070 --> 00:37:28,574 but also even by how people we don't know act 724 00:37:28,575 --> 00:37:30,174 as things ripple through the network 725 00:37:30,175 --> 00:37:32,345 and come to affect us. 726 00:37:33,021 --> 00:37:36,323 Morgan: Nicholas and long-time collaborator James Fowler are 727 00:37:36,324 --> 00:37:39,825 studying how social connections change the behavior 728 00:37:39,826 --> 00:37:42,928 of the group as a whole. 729 00:37:42,929 --> 00:37:45,298 Christakis: When you add these ties between people, 730 00:37:45,299 --> 00:37:48,433 the particular number of ties, the particular pattern of ties 731 00:37:48,434 --> 00:37:50,336 then confers on the group 732 00:37:50,337 --> 00:37:53,674 properties it didn't necessarily have before. 733 00:37:53,675 --> 00:37:56,609 Morgan: Patterns and wiring matter. 734 00:37:56,610 --> 00:37:58,310 Think of the Internet. 735 00:37:58,311 --> 00:38:01,147 It's a highly dynamic network of computers. 736 00:38:01,148 --> 00:38:03,183 If one area goes down, 737 00:38:03,184 --> 00:38:06,252 the data simply move around the blockage. 738 00:38:06,253 --> 00:38:09,923 But the electrical grid is more vulnerable. 739 00:38:09,924 --> 00:38:14,061 One bad node can damage all of its neighboring connections... 740 00:38:16,029 --> 00:38:20,033 Or even bring the whole network down. 741 00:38:20,034 --> 00:38:21,901 Nicholas is performing experiments 742 00:38:21,902 --> 00:38:25,071 to see if he can re-engineer human social networks 743 00:38:25,072 --> 00:38:27,339 to be more like the Internet. 744 00:38:27,340 --> 00:38:30,642 His student volunteers form a single social network 745 00:38:30,643 --> 00:38:33,513 divided into four separate groups. 746 00:38:33,514 --> 00:38:38,551 Every student's goal is to make as much money as possible. 747 00:38:38,552 --> 00:38:40,285 Okay, guys, so here's what we're gonna do. 748 00:38:40,286 --> 00:38:42,654 Each of you has a dollar and a pad in front of you. 749 00:38:42,655 --> 00:38:44,991 In a moment, I'm gonna ask you to write "give" or "take." 750 00:38:44,992 --> 00:38:46,560 You can contribute to the collective, 751 00:38:46,561 --> 00:38:48,294 or you can be a parasite and take advantage 752 00:38:48,295 --> 00:38:49,863 of the collective... "Give" or "take." 753 00:38:49,864 --> 00:38:52,165 Then you'll be asked to reveal your choice 754 00:38:52,166 --> 00:38:54,702 and to contribute your dollar or not towards the middle. 755 00:38:54,703 --> 00:38:55,935 I will double the pot, 756 00:38:55,936 --> 00:38:57,370 and then we'll divide the money equally 757 00:38:57,371 --> 00:38:59,339 amongst everyone at every table. 758 00:38:59,340 --> 00:39:00,973 If everybody shares, 759 00:39:00,974 --> 00:39:03,910 everybody makes a good amount of money. 760 00:39:03,911 --> 00:39:07,446 If nobody shares, nobody makes any money. 761 00:39:07,447 --> 00:39:09,083 So, reveal. 762 00:39:10,617 --> 00:39:11,917 All right. You're all givers. 763 00:39:11,918 --> 00:39:14,287 So make your contributions, as well, accordingly. 764 00:39:14,288 --> 00:39:15,388 And so, what we're gonna do is 765 00:39:15,389 --> 00:39:19,625 we're gonna double that and share. 766 00:39:19,626 --> 00:39:22,395 Morgan: At first, most are nice to each other 767 00:39:22,396 --> 00:39:25,031 and share in the rewards. 768 00:39:25,032 --> 00:39:28,401 But a few players choose not to contribute. 769 00:39:28,402 --> 00:39:32,705 When the pot is doubled, they get more than their peers. 770 00:39:32,706 --> 00:39:34,174 In these rounds, 771 00:39:34,175 --> 00:39:37,812 the students cannot change their society's social wiring. 772 00:39:37,813 --> 00:39:39,946 So you're assigned a position in the network, 773 00:39:39,947 --> 00:39:41,848 and you're told, "these are your neighbors. 774 00:39:41,849 --> 00:39:44,551 These are your friends for the next hour. 775 00:39:44,552 --> 00:39:47,086 And you're stuck now interacting with these jerks." 776 00:39:47,087 --> 00:39:49,890 And you don't like it, but all you can do is control 777 00:39:49,891 --> 00:39:54,060 whether you cooperate or defect, whether you share or take. 778 00:39:54,061 --> 00:39:55,696 And what happens after you've been sharing 779 00:39:55,697 --> 00:39:57,131 and some of the people around you are taking is 780 00:39:57,132 --> 00:39:59,633 you say, "I'm not gonna do that anymore," 781 00:39:59,634 --> 00:40:02,067 and you switching to taking, as well. 782 00:40:02,068 --> 00:40:04,537 And sharing disappears from the system. 783 00:40:04,538 --> 00:40:07,073 Cooperation goes away. 784 00:40:07,074 --> 00:40:10,243 And what you find is that you have then a society of takers. 785 00:40:10,244 --> 00:40:14,481 Morgan: But now Nicholas adds one important rule. 786 00:40:14,482 --> 00:40:16,482 After each round, 787 00:40:16,483 --> 00:40:20,419 each student has the option of moving seats. 788 00:40:20,420 --> 00:40:24,457 Now you can cut the ties to the people who are defectors, 789 00:40:24,458 --> 00:40:26,459 the people who are taking advantage of you 790 00:40:26,460 --> 00:40:27,828 and preferentially form ties 791 00:40:27,829 --> 00:40:29,462 to other nice people in the network, 792 00:40:29,463 --> 00:40:30,698 to other cooperators. 793 00:40:30,699 --> 00:40:31,997 And if you do that, 794 00:40:31,998 --> 00:40:35,368 if you make that small change in the social order, 795 00:40:35,369 --> 00:40:39,471 what you find is cooperation flourishes in the system. 796 00:40:39,472 --> 00:40:41,707 Morgan: The selfish people haven't gone away, 797 00:40:41,708 --> 00:40:45,011 but the society that everybody now lives in 798 00:40:45,012 --> 00:40:48,583 has a completely different culture. 799 00:40:49,617 --> 00:40:51,952 Nicholas believes humans and societies are 800 00:40:51,953 --> 00:40:55,488 like groups of carbon atoms. 801 00:40:55,489 --> 00:40:56,790 Arrange them one way, 802 00:40:56,791 --> 00:40:59,524 and you get soft, opaque graphite. 803 00:40:59,525 --> 00:41:03,462 But if you arrange those same atoms just right, 804 00:41:03,463 --> 00:41:08,000 you get strong, clear, sparkling diamond. 805 00:41:08,001 --> 00:41:10,069 And so, these properties of softness and darkness 806 00:41:10,070 --> 00:41:12,640 aren't properties of the carbon atoms. 807 00:41:12,641 --> 00:41:15,975 And it's just like that with our social groups. 808 00:41:15,976 --> 00:41:19,078 The same human beings connected different ways 809 00:41:19,079 --> 00:41:21,348 gives the group different properties. 810 00:41:21,349 --> 00:41:23,283 Some corporations are experimenting 811 00:41:23,284 --> 00:41:26,486 with an open social network architecture. 812 00:41:26,487 --> 00:41:28,354 Employees are free to break bonds 813 00:41:28,355 --> 00:41:31,191 with any other employee they don't work well with 814 00:41:31,192 --> 00:41:33,392 and form new ones. 815 00:41:33,393 --> 00:41:36,062 Could a similar strategy work for our national 816 00:41:36,063 --> 00:41:39,098 or even global society? 817 00:41:39,099 --> 00:41:42,667 If we were all free to move around, 818 00:41:42,668 --> 00:41:44,803 would there be less hate? 819 00:41:44,804 --> 00:41:47,473 Christakis: Network science doesn't offer one prescription. 820 00:41:47,474 --> 00:41:50,377 It's not as if there's one network structure 821 00:41:50,378 --> 00:41:52,578 that's optimal for everything. 822 00:41:52,579 --> 00:41:54,915 What I can tell you is that network structure matters 823 00:41:54,916 --> 00:41:57,785 to lots of problems, and understanding the rules 824 00:41:57,786 --> 00:42:00,252 of social network structure and function gives us 825 00:42:00,253 --> 00:42:03,558 a new set of tools to intervene in the world to make it better. 826 00:42:05,259 --> 00:42:08,261 Morgan: We may not find a solution to bigotry soon, 827 00:42:08,262 --> 00:42:12,066 but science is at last exposing its roots... 828 00:42:13,034 --> 00:42:16,202 Our biased, snap judgments of others, 829 00:42:16,203 --> 00:42:18,537 our innate groupism, 830 00:42:18,538 --> 00:42:21,808 our rigid political filters. 831 00:42:21,809 --> 00:42:26,979 For now, our best tool to fight bigotry lies 832 00:42:26,980 --> 00:42:29,381 within ourselves... 833 00:42:29,382 --> 00:42:32,651 The courage to walk away. 834 00:42:32,652 --> 00:42:36,189 We all have bigotry inside us. 835 00:42:36,190 --> 00:42:40,692 Most of us work hard to suppress our innate prejudices. 836 00:42:40,693 --> 00:42:42,696 But some don't. 837 00:42:42,697 --> 00:42:46,165 And their bigotry is infectious. 838 00:42:46,166 --> 00:42:48,334 The solution to bigotry does not start 839 00:42:48,335 --> 00:42:49,736 with governments and laws. 840 00:42:49,737 --> 00:42:54,374 It starts with understanding and neutralizing its source 841 00:42:54,375 --> 00:42:58,346 and with you and me doing our best to change. 842 00:42:58,396 --> 00:43:02,946 Repair and Synchronization by Easy Subtitles Synchronizer 1.0.0.0 66691

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