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Would you like to inspect the original subtitles? These are the user uploaded subtitles that are being translated: 1 00:00:01,069 --> 00:00:02,402 It is an idea 2 00:00:02,404 --> 00:00:07,140 that has spawned hatred, war, and genocide. 3 00:00:07,142 --> 00:00:10,911 It is one of the most polarizing questions 4 00:00:10,913 --> 00:00:13,613 we could ever ask. 5 00:00:13,615 --> 00:00:17,217 Do different races not just look different? 6 00:00:17,219 --> 00:00:20,487 Are they fundamentally different? 7 00:00:20,489 --> 00:00:25,559 Will a future race of advanced humans look back 8 00:00:25,561 --> 00:00:29,363 and see all of us as a vastly inferior breed? 9 00:00:30,665 --> 00:00:33,967 Could there be a superior race? 10 00:00:39,941 --> 00:00:45,278 Space, time, life itself. 11 00:00:47,348 --> 00:00:51,852 The secrets of the cosmos lie through the wormhole. 12 00:00:51,854 --> 00:00:55,854 Through the Wormhole 03x02 Is There a Superior Race? Original Air Date on June 6, 2012 13 00:00:55,879 --> 00:00:59,879 == sync, corrected by elderman == 14 00:01:04,832 --> 00:01:07,300 Speak of racial differences, 15 00:01:07,302 --> 00:01:10,771 and you're bound to inflame passions. 16 00:01:10,773 --> 00:01:12,672 Bosnian and Serb. 17 00:01:12,674 --> 00:01:15,242 Japanese and Korean. 18 00:01:15,244 --> 00:01:17,077 Black and White. 19 00:01:17,079 --> 00:01:19,413 The belief that one group's germ line 20 00:01:19,415 --> 00:01:20,881 is superior to another's 21 00:01:20,883 --> 00:01:23,650 has haunted history for thousands of years. 22 00:01:23,652 --> 00:01:28,255 But now we're in the age of DNA technology. 23 00:01:28,257 --> 00:01:32,659 We can track down minute differences 24 00:01:32,661 --> 00:01:34,728 in these chemical strands 25 00:01:34,730 --> 00:01:37,831 and perhaps discover whether they make Africans 26 00:01:37,833 --> 00:01:40,634 not just look different from Indians, 27 00:01:40,636 --> 00:01:43,603 but also think differently. 28 00:01:43,605 --> 00:01:48,942 Science has long been misused to try and prop up bigotry, 29 00:01:48,944 --> 00:01:51,912 but daring to ask how we might be different 30 00:01:51,914 --> 00:01:53,713 is important. 31 00:01:53,715 --> 00:01:56,016 Because the answers could tell us 32 00:01:56,018 --> 00:01:59,719 where the entire human species is headed. 33 00:02:03,491 --> 00:02:07,627 I grew up in an all-black neighborhood in Mississippi. 34 00:02:09,330 --> 00:02:14,668 I never thought of myself as better or worse than anyone. 35 00:02:14,670 --> 00:02:16,203 But all around town, 36 00:02:16,205 --> 00:02:20,574 there were signs that other people did. 37 00:02:23,811 --> 00:02:28,548 Dr. Martin Luther King Jr. had a dream of racial equality. 38 00:02:28,550 --> 00:02:30,117 And in the last 50 years, 39 00:02:30,119 --> 00:02:32,419 we've taken some steps 40 00:02:32,421 --> 00:02:35,422 toward the colorblind world he imagined. 41 00:02:35,424 --> 00:02:39,860 But scientists are still trying to understand what race means, 42 00:02:39,862 --> 00:02:44,231 or if it has any scientific meaning at all. 43 00:02:44,233 --> 00:02:47,868 Is race only skin deep? 44 00:02:47,870 --> 00:02:51,571 Or is there something internal, invisible, 45 00:02:51,573 --> 00:02:54,875 that sets the races apart? 46 00:02:54,877 --> 00:02:58,678 Evolutionary biologist Andy Brower 47 00:02:58,680 --> 00:03:01,982 thinks we can understand what the word "race" means 48 00:03:01,984 --> 00:03:04,417 by looking at another species, 49 00:03:04,419 --> 00:03:07,787 one he feels he was born to study. 50 00:03:07,789 --> 00:03:11,625 Both my parents worked on butterflies for their PhDs 51 00:03:11,627 --> 00:03:13,293 back in the '50s. 52 00:03:14,747 --> 00:03:18,784 So I just became fascinated by that at 5 years old, 53 00:03:18,809 --> 00:03:21,993 and I've had a little butterfly collection as a kid. 54 00:03:22,449 --> 00:03:25,047 Definitely in my DNA, right from the start. 55 00:03:25,732 --> 00:03:28,554 Andy studies Heliconius butterflies. 56 00:03:29,322 --> 00:03:31,073 He has followed their fluttering wings 57 00:03:31,098 --> 00:03:33,549 all over the Western Hemisphere. 58 00:03:33,876 --> 00:03:37,669 As much as he is enchanted by their elaborate wing markings, 59 00:03:37,694 --> 00:03:41,629 he knows that their beauty is only superficial. 60 00:03:42,019 --> 00:03:43,656 They're poisonous butterflies, 61 00:03:43,657 --> 00:03:46,051 and they have mimetic wing patterns 62 00:03:46,053 --> 00:03:49,589 so that they are advertising the fact that they taste bad 63 00:03:49,689 --> 00:03:52,957 to potential predators, birds, usually. 64 00:03:52,959 --> 00:03:56,193 So that the more butterflies exhibit a common color pattern, 65 00:03:56,195 --> 00:03:58,929 the easier it is for the birds to recognize that, 66 00:03:58,931 --> 00:04:01,232 "Okay, there's one of those red and yellow things. 67 00:04:01,234 --> 00:04:03,200 They taste bad. I'm leaving those alone." 68 00:04:03,202 --> 00:04:05,402 But Heliconius butterflies 69 00:04:05,404 --> 00:04:08,038 do not look the same everywhere. 70 00:04:08,040 --> 00:04:10,007 A group in one region of South America 71 00:04:10,009 --> 00:04:11,976 has completely different wing patterns 72 00:04:11,978 --> 00:04:15,479 from another group that lives just across a river 73 00:04:15,481 --> 00:04:19,416 or another on the other side of a mountain. 74 00:04:19,418 --> 00:04:23,087 This is a box of butterflies that are all the same species. 75 00:04:23,089 --> 00:04:26,223 In French Guiana, a red band is on the fore wing 76 00:04:26,225 --> 00:04:28,726 and the hind wing is basically black. 77 00:04:28,728 --> 00:04:29,960 And then, further south, 78 00:04:29,962 --> 00:04:33,430 you have red rays and the yellow areas. 79 00:04:33,432 --> 00:04:35,366 These two rows in the middle here, 80 00:04:35,368 --> 00:04:36,734 the colors are different. 81 00:04:36,736 --> 00:04:38,435 The wing pattern differences 82 00:04:38,437 --> 00:04:40,571 are probably driven by which colors and patterns 83 00:04:40,573 --> 00:04:44,038 stand out most clearly to the local bird population. 84 00:04:44,331 --> 00:04:45,897 But these different-looking varieties -- 85 00:04:46,820 --> 00:04:48,478 you could call them races. 86 00:04:48,887 --> 00:04:52,547 Appear to have identical inner biologies. 87 00:04:52,915 --> 00:04:54,522 They smell the same, 88 00:04:54,547 --> 00:04:56,957 they recognize each other as being potential mates. 89 00:04:56,982 --> 00:04:59,411 And so they produce hybrid offspring. 90 00:04:59,810 --> 00:05:01,638 Hybrid offspring are perfectly fine. 91 00:05:01,663 --> 00:05:03,317 There, there viable and healthy. 92 00:05:03,342 --> 00:05:05,993 They can, their fertile, so they can lay their own eggs. 93 00:05:06,409 --> 00:05:09,034 These butterflies all have the same life-span 94 00:05:09,059 --> 00:05:12,271 and the same adaptive poison to ward off predators. 95 00:05:12,641 --> 00:05:17,179 The differences appear to be only skin deep. 96 00:05:18,114 --> 00:05:20,504 It is the same for humans. 97 00:05:21,074 --> 00:05:25,167 Race poses no biological barriers to mating, 98 00:05:25,503 --> 00:05:30,206 and our life-spans are all very similar, 99 00:05:30,208 --> 00:05:33,176 no matter what our ethnic background. 100 00:05:33,178 --> 00:05:37,113 Are people, like Heliconius butterflies, 101 00:05:37,115 --> 00:05:40,750 all the same beneath our different-colored skins? 102 00:05:41,919 --> 00:05:43,612 In the year 2000, 103 00:05:43,613 --> 00:05:46,414 when President Clinton announced the completion 104 00:05:46,416 --> 00:05:48,082 of the Human Genome Project, 105 00:05:48,084 --> 00:05:50,585 the answer appeared to be yes. 106 00:05:50,587 --> 00:05:51,786 And in genetic terms, 107 00:05:51,788 --> 00:05:53,888 all human beings, regardless of race, 108 00:05:53,890 --> 00:05:56,924 are more than 99.9% the same. 109 00:05:56,926 --> 00:05:59,594 Another decade of genetic study 110 00:05:59,596 --> 00:06:04,165 has lowered that number somewhat to 99.5%. 111 00:06:04,167 --> 00:06:07,135 No matter who you are or where you come from, 112 00:06:07,137 --> 00:06:13,674 a mere 0.5% of your genetic code is unique to you. 113 00:06:13,676 --> 00:06:19,881 What kinds of racial differences could like in that 0.5%? 114 00:06:19,883 --> 00:06:21,883 Perhaps plenty. 115 00:06:21,885 --> 00:06:26,854 Human and chimpanzee genomes only differ by about 3%. 116 00:06:26,856 --> 00:06:28,489 That difference is enough 117 00:06:28,491 --> 00:06:33,494 to make our brains radically bigger and smarter. 118 00:06:37,366 --> 00:06:40,701 John Hawks is a leading paleoanthropologist 119 00:06:40,703 --> 00:06:43,504 at the University of Wisconsin-Madison. 120 00:06:43,506 --> 00:06:46,474 He studies the bones of ancient humans, 121 00:06:46,476 --> 00:06:48,509 tracking how we have changed 122 00:06:48,511 --> 00:06:50,645 since our evolutionary line split off 123 00:06:50,647 --> 00:06:54,982 from that of the chimp's about 6 million years ago. 124 00:06:54,984 --> 00:06:58,553 When we look at a real brief thumbnail of our evolution, 125 00:06:58,555 --> 00:07:00,054 we started out as apes 126 00:07:00,056 --> 00:07:01,923 and became upright-walking people 127 00:07:01,925 --> 00:07:04,058 and then evolved stone-tool manufacture 128 00:07:04,060 --> 00:07:05,426 and bigger brains. 129 00:07:05,428 --> 00:07:08,596 And those are big events that took millions of years. 130 00:07:08,598 --> 00:07:11,032 But most of my work in the last few years 131 00:07:11,034 --> 00:07:14,368 has been focused on the very recent part of our evolution -- 132 00:07:14,370 --> 00:07:16,437 our time since we left Africa 133 00:07:16,439 --> 00:07:19,440 and evolved into the people we are today. 134 00:07:21,843 --> 00:07:23,544 Scientists now agree 135 00:07:23,546 --> 00:07:25,413 the development of separate races 136 00:07:25,415 --> 00:07:27,949 began around 50,000 years ago, 137 00:07:27,951 --> 00:07:31,319 when modern humans migrated out of Africa. 138 00:07:31,321 --> 00:07:34,889 There dark-skinned pigmentation was and remains 139 00:07:34,891 --> 00:07:38,793 a protective force against ultraviolet rays. 140 00:07:38,795 --> 00:07:41,762 But as humans moved further north, 141 00:07:41,764 --> 00:07:44,832 dark skin blocked too much sunlight 142 00:07:44,834 --> 00:07:47,868 and reduced the natural production of vitamin D 143 00:07:47,870 --> 00:07:49,537 in our deep skin layers. 144 00:07:49,539 --> 00:07:54,442 Lighter-skinned people fared better in Europe and China. 145 00:07:54,444 --> 00:07:55,977 For those who migrated 146 00:07:55,979 --> 00:07:58,512 to South America and Southern India, 147 00:07:58,514 --> 00:08:02,783 darker skin once again protected them from the sun. 148 00:08:02,785 --> 00:08:04,552 But John's research is showing 149 00:08:04,554 --> 00:08:07,822 that these now-isolated ethnicities 150 00:08:07,824 --> 00:08:11,325 continued to evolve over the ensuing millennia 151 00:08:11,327 --> 00:08:13,728 and that distinctions between racial groups 152 00:08:13,730 --> 00:08:16,397 do go deeper than our skin. 153 00:08:16,399 --> 00:08:18,733 When I study archaeological samples 154 00:08:18,735 --> 00:08:21,502 of skulls that have come out of the ground 155 00:08:21,504 --> 00:08:24,905 from 5,000 years ago, from 10,000 years ago, 156 00:08:24,907 --> 00:08:29,076 we can see many of the changes unfolding in those samples 157 00:08:29,078 --> 00:08:32,446 as we go forward in time. 158 00:08:32,448 --> 00:08:34,148 Brain size changed. 159 00:08:34,150 --> 00:08:35,916 Teeth changed. 160 00:08:35,918 --> 00:08:37,985 And then there are some kinds of changes 161 00:08:37,987 --> 00:08:40,354 that are distinct to different regions. 162 00:08:40,356 --> 00:08:41,889 So, there are characteristics 163 00:08:41,891 --> 00:08:43,791 that we can point at in the skull 164 00:08:43,793 --> 00:08:47,695 that now characterize Asians versus Europeans. 165 00:08:47,697 --> 00:08:50,031 John thinks racial differences 166 00:08:50,033 --> 00:08:53,301 run much deeper than our bones. 167 00:08:53,303 --> 00:08:57,371 He believes almost every aspect of our biology changed 168 00:08:57,373 --> 00:09:00,007 as humans migrated around the world, 169 00:09:00,009 --> 00:09:02,376 even the way our brains work. 170 00:09:03,401 --> 00:09:03,401 ++++++++++++++++++++++++++++++ 171 00:09:05,175 --> 00:09:07,609 What separates one race from another? 172 00:09:08,719 --> 00:09:10,219 In the 50,000 years 173 00:09:10,221 --> 00:09:14,490 since small groups of people began migrating out of Africa, 174 00:09:14,492 --> 00:09:18,160 we've developed plenty of physical differences. 175 00:09:18,162 --> 00:09:22,064 But what invisible difference might there be? 176 00:09:22,066 --> 00:09:27,803 Just how far apart has our DNA drifted? 177 00:09:36,746 --> 00:09:39,615 Paleoanthropologist John Hawks 178 00:09:39,617 --> 00:09:43,018 is tracking changes in our genes over the past millennia. 179 00:09:44,354 --> 00:09:47,957 And he's discovered something unsettling. 180 00:09:47,959 --> 00:09:51,694 Our DNA loves to gamble. 181 00:09:56,633 --> 00:10:00,269 So, when we look at the way that DNA changes, 182 00:10:00,271 --> 00:10:03,606 it's sort of like our genes are addicted to gambling. 183 00:10:03,608 --> 00:10:06,809 It's got four possible base pairs -- A, C, G, and T. 184 00:10:06,811 --> 00:10:09,845 And here we've got, well, four colors of chips. 185 00:10:09,847 --> 00:10:12,348 This is like a DNA sequence, 186 00:10:12,350 --> 00:10:15,250 except your DNA would be enormously longer. 187 00:10:18,188 --> 00:10:21,757 The way that evolution works on these gene sequences... 188 00:10:21,759 --> 00:10:25,861 As this gene sequence is reproducing itself, 189 00:10:25,863 --> 00:10:29,698 one base pair may get swapped out 190 00:10:29,700 --> 00:10:33,535 and a different one put in its place. 191 00:10:33,537 --> 00:10:37,272 As we lay out many individuals' DNA next to each other, 192 00:10:37,274 --> 00:10:40,209 those individuals are gonna be different from each other 193 00:10:40,211 --> 00:10:41,210 at random places. 194 00:10:41,212 --> 00:10:43,145 When a mutation happens, 195 00:10:43,147 --> 00:10:45,414 that can cause an enormous problem. 196 00:10:45,416 --> 00:10:47,316 Or it could be an enormous advantage. 197 00:10:47,318 --> 00:10:49,852 Between every generation, 198 00:10:49,854 --> 00:10:54,056 DNA makes about 60 of these random changes to its sequence. 199 00:10:54,058 --> 00:10:56,191 Sometimes, it hits the jackpot. 200 00:10:56,193 --> 00:10:58,594 Sometimes, it goes bust. 201 00:10:58,596 --> 00:11:02,264 Most of the time, these mutations do nothing at all. 202 00:11:02,266 --> 00:11:05,167 But all the changes that don't kill us 203 00:11:05,169 --> 00:11:07,670 are handed down to the next generation, 204 00:11:07,672 --> 00:11:10,039 living on like molecular fossils. 205 00:11:10,041 --> 00:11:13,575 And these fossils give John a way to calculate 206 00:11:13,577 --> 00:11:16,311 how old any particular gene is. 207 00:11:16,313 --> 00:11:18,981 The longer it has been around, 208 00:11:18,983 --> 00:11:22,651 the more random mutations would have collected around it. 209 00:11:22,653 --> 00:11:25,688 The part that's functionally important stays the same, 210 00:11:25,690 --> 00:11:28,357 but as you go farther and farther away from that part, 211 00:11:28,359 --> 00:11:30,225 it's more likely to have 212 00:11:30,227 --> 00:11:32,928 swapped up with another sequence. 213 00:11:32,930 --> 00:11:37,066 It's the length of that part that hasn't been swapped 214 00:11:37,068 --> 00:11:38,267 that gives us an idea 215 00:11:38,269 --> 00:11:40,369 of how long it's been around in the population. 216 00:11:40,371 --> 00:11:42,905 Because the longer the gene has been around, 217 00:11:42,907 --> 00:11:46,008 the more likely it is that we'll have these random changes. 218 00:11:46,010 --> 00:11:47,609 When John and his colleagues 219 00:11:47,611 --> 00:11:50,312 used this gene-dating technique 220 00:11:50,314 --> 00:11:54,516 in populations native to Europe, Asia, and Africa, 221 00:11:54,518 --> 00:11:56,585 they were in for a big surprise. 222 00:11:56,587 --> 00:12:00,289 Many genes were much younger than they'd expected. 223 00:12:00,291 --> 00:12:03,158 What we discovered was that lots of them 224 00:12:03,160 --> 00:12:06,095 showed evidence of really fast adaptive changes. 225 00:12:06,097 --> 00:12:08,997 We're talking about 2,000 places 226 00:12:08,999 --> 00:12:12,367 that, in one part of the world or another, 227 00:12:12,369 --> 00:12:15,304 have undergone really recent adaptation. 228 00:12:15,306 --> 00:12:18,273 We were pretty surprised to find that the number was so large. 229 00:12:18,275 --> 00:12:20,142 John had expected to find 230 00:12:20,144 --> 00:12:23,345 that just a fraction of a percent of human genes 231 00:12:23,347 --> 00:12:25,881 would show signs of recent mutation. 232 00:12:25,883 --> 00:12:30,219 But instead, he discovered that about 7% of our genes 233 00:12:30,221 --> 00:12:32,321 have mutated to new forms 234 00:12:32,323 --> 00:12:34,890 in the last 10,000 to 20,000 years. 235 00:12:34,892 --> 00:12:39,762 Some of these genes are only found in certain racial groups. 236 00:12:39,764 --> 00:12:43,532 These mutations are not just related to skin color 237 00:12:43,534 --> 00:12:45,734 and physical appearance. 238 00:12:45,736 --> 00:12:48,337 The changes go far deeper. 239 00:12:48,339 --> 00:12:50,973 Probably the most obvious examples 240 00:12:50,975 --> 00:12:53,976 are the examples where there's a disease that's new 241 00:12:53,978 --> 00:12:57,579 that some people have developed resistance strategies to. 242 00:12:57,581 --> 00:12:59,414 So, malaria, for example, 243 00:12:59,416 --> 00:13:02,284 is a disease that has been around for about 5,000 years 244 00:13:02,286 --> 00:13:03,986 as a human pathogen. 245 00:13:03,988 --> 00:13:07,890 Over that time, populations in South Asia, in Africa, 246 00:13:07,892 --> 00:13:12,127 have developed new adaptations to this particular disease. 247 00:13:12,129 --> 00:13:14,763 But John suspects there is another force 248 00:13:14,765 --> 00:13:16,665 driving these genetic changes -- 249 00:13:16,667 --> 00:13:19,101 our civilization. 250 00:13:19,103 --> 00:13:20,969 It is an idea that puts him at odds 251 00:13:20,971 --> 00:13:23,539 with most evolutionary scientists, 252 00:13:23,541 --> 00:13:26,241 including the father of them all -- 253 00:13:26,243 --> 00:13:27,943 Charles Darwin. 254 00:13:27,945 --> 00:13:32,147 Darwin talked about the hostile forces of nature, 255 00:13:32,149 --> 00:13:36,485 the sun beating down on us, the cold of the winter, 256 00:13:36,487 --> 00:13:39,087 and these would change us, 257 00:13:39,089 --> 00:13:42,057 because we had to adapt to those environments. 258 00:13:42,059 --> 00:13:45,027 And in human evolution, we could invent things. 259 00:13:45,029 --> 00:13:48,831 We could change our behavior and our culture to insulate us, 260 00:13:48,833 --> 00:13:50,799 to buffer us from those things. 261 00:13:50,801 --> 00:13:54,536 And so the idea was that humans didn't have to change biology 262 00:13:54,538 --> 00:13:56,939 in order to adapt to new places. 263 00:13:59,008 --> 00:14:02,678 Charles Darwin's argument was 264 00:14:02,680 --> 00:14:05,414 that farming, houses, clothes, 265 00:14:05,416 --> 00:14:07,983 should stop our genes from changing and evolving, 266 00:14:07,985 --> 00:14:11,620 because we began protecting ourselves from our environments. 267 00:14:11,622 --> 00:14:14,857 But John's research shows 268 00:14:14,859 --> 00:14:18,327 that the different ways groups of humans chose to live 269 00:14:18,329 --> 00:14:20,796 in different parts of the world 270 00:14:20,798 --> 00:14:23,465 could actually have driven genetic changes. 271 00:14:23,467 --> 00:14:24,967 Probably the best example 272 00:14:24,969 --> 00:14:28,470 of how culture has influenced our evolution is milk drinking. 273 00:14:28,472 --> 00:14:31,707 Now, it's not normal for adult mammals 274 00:14:31,709 --> 00:14:33,709 to have access to milk. 275 00:14:33,711 --> 00:14:36,378 If you think about a bull trying to get milk 276 00:14:36,380 --> 00:14:38,046 up from underneath the cow's udder... 277 00:14:39,183 --> 00:14:40,983 ...it just doesn't work in nature. 278 00:14:42,753 --> 00:14:45,053 There have been many populations 279 00:14:45,055 --> 00:14:47,756 that have adopted dairy animals of different kinds. 280 00:14:47,758 --> 00:14:51,226 Five of them have developed new mutations 281 00:14:51,228 --> 00:14:53,362 that give them, as adults, 282 00:14:53,364 --> 00:14:56,465 the ability to digest the sugar in this milk. 283 00:14:56,467 --> 00:14:59,568 In northern Europe, this is a really common mutation. 284 00:14:59,570 --> 00:15:02,504 But if you go to come parts of the world, like China, 285 00:15:02,506 --> 00:15:05,574 it's very rare for people to be able to drink milk. 286 00:15:07,111 --> 00:15:10,445 But in fact, it's the ability to digest this milk, 287 00:15:10,447 --> 00:15:13,215 the lactase persistence, as we call it, 288 00:15:13,217 --> 00:15:15,784 which is the weird, mutant version of this. 289 00:15:15,786 --> 00:15:18,053 And it's all happened in populations 290 00:15:18,055 --> 00:15:20,389 because they've changed their culture. 291 00:15:20,391 --> 00:15:22,291 Just as the climates 292 00:15:22,293 --> 00:15:24,927 where different ethnic groups lived varied, 293 00:15:24,929 --> 00:15:27,863 so did the rules and habits of their societies. 294 00:15:27,865 --> 00:15:31,066 And their DNA was forced to adapt. 295 00:15:31,068 --> 00:15:33,001 If you're a human, 296 00:15:33,003 --> 00:15:36,505 you have to survive and deal with other people every day 297 00:15:36,507 --> 00:15:37,940 in order to reproduce. 298 00:15:37,942 --> 00:15:41,376 And that makes culture your environment. 299 00:15:41,378 --> 00:15:43,946 Genetic adaptations 300 00:15:43,948 --> 00:15:47,115 may even have altered the way our brains work. 301 00:15:47,117 --> 00:15:48,951 John and his colleagues 302 00:15:48,953 --> 00:15:51,887 have discovered around 100 mutations 303 00:15:51,889 --> 00:15:53,989 in genes controlling brain chemistry 304 00:15:53,991 --> 00:15:55,223 that have taken place 305 00:15:55,225 --> 00:15:58,360 since humanity migrated from Africa. 306 00:15:58,362 --> 00:16:03,832 One of them, a genetic variant called DRD4, 307 00:16:03,834 --> 00:16:08,370 may even have triggered that migration in the first place. 308 00:16:08,372 --> 00:16:09,738 It's linked to ADHD, 309 00:16:09,740 --> 00:16:12,708 because when we study patients who have ADHD, 310 00:16:12,710 --> 00:16:15,877 they have a greater chance of having this gene. 311 00:16:15,879 --> 00:16:17,346 One possible reason is 312 00:16:17,348 --> 00:16:19,982 that it made people more likely to move. 313 00:16:19,984 --> 00:16:23,418 The DRD4 mutation is most commonly found 314 00:16:23,420 --> 00:16:27,055 in populations that live outside of Africa. 315 00:16:27,057 --> 00:16:30,459 It appeared around 50,000 years ago. 316 00:16:30,461 --> 00:16:33,128 It has been called "the migration gene," 317 00:16:33,130 --> 00:16:35,931 because traits like rapidly shifting focus 318 00:16:35,933 --> 00:16:37,566 and quick movements 319 00:16:37,568 --> 00:16:42,070 could have been very useful when our ancestors were on the move. 320 00:16:42,072 --> 00:16:45,774 Even though short attention now appears less useful 321 00:16:45,776 --> 00:16:48,410 in our modern, sedentary society. 322 00:16:48,412 --> 00:16:51,747 DRD4 is the best example of a gene 323 00:16:51,749 --> 00:16:54,216 that is clearly recently selected 324 00:16:54,218 --> 00:16:56,084 and has behavioral impacts. 325 00:16:56,086 --> 00:16:57,819 It affects the brain in some way. 326 00:16:57,821 --> 00:16:59,187 But there are others. 327 00:16:59,189 --> 00:17:00,856 And we don't know what they do, 328 00:17:00,858 --> 00:17:03,592 but we can say that they're expressed in the brain, 329 00:17:03,594 --> 00:17:07,162 they're related to our behavior in some way, potentially. 330 00:17:07,164 --> 00:17:09,231 But we don't know what those changes are for. 331 00:17:09,233 --> 00:17:13,769 The notion that genetic changes affecting the brain 332 00:17:13,771 --> 00:17:15,203 might actually underpin 333 00:17:15,205 --> 00:17:17,639 the spread of humanity across the globe 334 00:17:17,641 --> 00:17:20,275 leads to an unsettling question. 335 00:17:20,277 --> 00:17:22,978 Might some races have evolved 336 00:17:22,980 --> 00:17:26,281 to become more intelligent than others? 337 00:17:26,283 --> 00:17:29,751 It is a highly divisive notion, 338 00:17:29,753 --> 00:17:32,954 but some scientists are probing the issue, 339 00:17:32,956 --> 00:17:37,359 and their conclusions have triggered outrage. 340 00:17:38,884 --> 00:17:38,884 ++++++++++++++++++++++++++++++ 341 00:17:39,830 --> 00:17:42,132 Race. 342 00:17:42,134 --> 00:17:45,869 It is a word that stirs powerful emotions. 343 00:17:45,871 --> 00:17:47,270 Some scientists think 344 00:17:47,272 --> 00:17:50,340 the genetic differences between us are so small 345 00:17:50,342 --> 00:17:53,610 that the word "race" doesn't even make sense. 346 00:17:53,612 --> 00:17:57,947 But understanding how evolution has shaped the races 347 00:17:57,949 --> 00:17:59,849 and continues to do so 348 00:17:59,851 --> 00:18:02,786 is of great scientific importance. 349 00:18:05,022 --> 00:18:08,725 The trait that sets humans apart from all other species 350 00:18:08,727 --> 00:18:12,228 is our incredibly complex brain. 351 00:18:12,230 --> 00:18:15,965 But could the brains of different races be different? 352 00:18:15,967 --> 00:18:20,003 Could they have different intelligences? 353 00:18:20,005 --> 00:18:23,273 Renowned psychologist Stanley Coren 354 00:18:23,275 --> 00:18:26,976 has spent years studying intelligence differences -- 355 00:18:26,978 --> 00:18:29,679 not among different races of people, 356 00:18:29,681 --> 00:18:33,283 but in different breeds of dogs. 357 00:18:33,285 --> 00:18:35,852 Dogs are a marvel of genetic engineering, 358 00:18:35,854 --> 00:18:38,655 simply because we've kept the breeds separate. 359 00:18:38,657 --> 00:18:45,528 You know, my grandparents were Latvia, Lithuania, Russia, 360 00:18:45,530 --> 00:18:47,597 but I take a golden retriever, 361 00:18:47,599 --> 00:18:50,934 and his granddaddy was a purebred golden retriever, 362 00:18:50,936 --> 00:18:54,104 and his great-granddaddy was, and so on and so forth. 363 00:18:54,106 --> 00:18:56,206 So, there's less noise in the genome. 364 00:18:56,208 --> 00:18:59,976 For at least 14,000 years, 365 00:18:59,978 --> 00:19:03,747 humans have systematically shaped the evolution of dogs, 366 00:19:03,749 --> 00:19:06,549 changing them to fit our needs. 367 00:19:06,551 --> 00:19:09,385 Stanley has measured the intelligence 368 00:19:09,387 --> 00:19:11,187 of more than 100 breeds. 369 00:19:11,189 --> 00:19:15,525 So, we can get dogs which, because of their breeding, 370 00:19:15,527 --> 00:19:18,561 differ in terms of their intelligence. 371 00:19:18,563 --> 00:19:21,431 If you take a young child below 18 months of age 372 00:19:21,433 --> 00:19:23,566 and you put a towel over his head, 373 00:19:23,568 --> 00:19:25,668 he thinks that the world has gone away, 374 00:19:25,670 --> 00:19:26,736 and he sits there. 375 00:19:26,738 --> 00:19:29,506 So, if Montana has a mental ability 376 00:19:29,508 --> 00:19:31,641 beyond an 18-month-old human, 377 00:19:31,643 --> 00:19:33,743 Montana should throw the towel off of his head 378 00:19:33,745 --> 00:19:34,878 very quickly. 379 00:19:34,880 --> 00:19:36,813 Are you ready, Montana? Go. 380 00:19:42,219 --> 00:19:45,555 Stanley's test results have convinced him 381 00:19:45,557 --> 00:19:49,092 that there are big differences in canine intelligence 382 00:19:49,094 --> 00:19:51,594 from breed to breed. 383 00:19:51,596 --> 00:19:53,363 Where has the world gone? 384 00:19:53,365 --> 00:19:56,332 Okay, what a good dog. 385 00:19:56,334 --> 00:19:58,802 And then I've got a beagle. 386 00:19:58,804 --> 00:20:02,338 And his job is to amuse my grandchildren. 387 00:20:02,340 --> 00:20:04,941 As dog intelligence goes, 388 00:20:04,943 --> 00:20:07,143 beagles are seven from the bottom. 389 00:20:07,145 --> 00:20:10,046 So, this bench that I'm sitting on right now 390 00:20:10,048 --> 00:20:12,081 is more trainable than a beagle. 391 00:20:12,083 --> 00:20:15,051 The top dogs in terms of intelligence 392 00:20:15,053 --> 00:20:18,621 are the Border Collie, followed by the poodle. 393 00:20:18,623 --> 00:20:20,957 Some people say, "the poodle? That's a froufrou dog." 394 00:20:20,959 --> 00:20:23,660 No, the poodle is a retriever, okay? 395 00:20:23,662 --> 00:20:26,696 And he didn't ask for that silly haircut. 396 00:20:26,698 --> 00:20:30,266 If some breeds of dogs are smarter than others, 397 00:20:30,268 --> 00:20:31,768 why could that not be true 398 00:20:31,770 --> 00:20:35,038 for the animals at the other end of the leash? 399 00:20:35,040 --> 00:20:40,243 University of Delaware sociologist Linda Gottfredson 400 00:20:40,245 --> 00:20:43,112 has been analyzing I.Q. test scores 401 00:20:43,114 --> 00:20:45,048 for the past two decades. 402 00:20:45,050 --> 00:20:50,119 She claims they reveal a subtle but measurable link 403 00:20:50,121 --> 00:20:54,057 between intelligence, genetics, and race. 404 00:20:54,059 --> 00:20:57,427 For very complex traits like intelligence, 405 00:20:57,429 --> 00:21:00,330 many genes have small effect, 406 00:21:00,332 --> 00:21:03,433 may push a person this way or that. 407 00:21:03,435 --> 00:21:07,937 And they're really, really hard to find. 408 00:21:07,939 --> 00:21:10,306 Individual I.Q.s 409 00:21:10,308 --> 00:21:14,644 are as diverse as the grains of sand on a beach. 410 00:21:14,646 --> 00:21:18,848 But Linda believes there are patterns in this noise, 411 00:21:18,850 --> 00:21:22,719 patterns that depend on our genes. 412 00:21:22,721 --> 00:21:24,821 As any parent knows, 413 00:21:24,823 --> 00:21:26,389 brothers and sisters look different. 414 00:21:26,391 --> 00:21:28,925 They often have different personalities, 415 00:21:28,927 --> 00:21:32,161 and they often have different levels of intelligence. 416 00:21:32,163 --> 00:21:35,798 The average difference between siblings 417 00:21:35,800 --> 00:21:38,468 is 12 I.Q. points. 418 00:21:38,470 --> 00:21:41,905 If you compare to random people walking on the beach, 419 00:21:41,907 --> 00:21:45,375 you might ask, "Well, how different are those people?" 420 00:21:45,377 --> 00:21:50,213 On the average, strangers differ by 17 I.Q. points. 421 00:21:50,215 --> 00:21:54,050 So, you see that biological brothers and sisters 422 00:21:54,052 --> 00:21:57,020 are 2/3 as different on the average 423 00:21:57,022 --> 00:21:59,889 as random strangers on the street. 424 00:21:59,891 --> 00:22:04,627 The genes of strangers vary more than those of siblings, 425 00:22:04,629 --> 00:22:09,198 and Linda argues this is why their I.Q.s vary more. 426 00:22:09,200 --> 00:22:11,701 Her interpretation of this data 427 00:22:11,703 --> 00:22:13,803 has led her to a controversial notion, 428 00:22:13,805 --> 00:22:16,372 that the genetic differences between races 429 00:22:16,374 --> 00:22:17,907 might lead to differences 430 00:22:17,909 --> 00:22:22,011 in the average intelligence of those races. 431 00:22:22,013 --> 00:22:23,913 I guess there would be 432 00:22:23,915 --> 00:22:26,382 two rules about human diversity. 433 00:22:26,384 --> 00:22:32,455 One is that there's lots of variation 434 00:22:32,457 --> 00:22:34,223 within all groups, 435 00:22:34,225 --> 00:22:39,595 but there's also a gradation between the groups 436 00:22:39,597 --> 00:22:42,932 so that there are recurring 437 00:22:42,934 --> 00:22:46,102 and sometimes large average differences 438 00:22:46,104 --> 00:22:48,037 between racial ethnic groups. 439 00:22:48,039 --> 00:22:51,040 I.Q. scores in any group of people 440 00:22:51,042 --> 00:22:53,309 are spread across a bell curve 441 00:22:53,311 --> 00:22:58,548 ranging from a score of about 70 to about 130. 442 00:22:58,550 --> 00:23:01,351 There are outliers on either end, 443 00:23:01,353 --> 00:23:05,088 but most people are clustered around an average. 444 00:23:05,090 --> 00:23:08,825 There are differences between racial ethnic groups 445 00:23:08,827 --> 00:23:12,261 on the average in I.Q. 446 00:23:12,263 --> 00:23:17,100 The average white I.Q. is arbitrarily set at 100. 447 00:23:17,102 --> 00:23:21,504 Blacks in the United States and in many other western countries 448 00:23:21,506 --> 00:23:23,740 average 85. 449 00:23:23,742 --> 00:23:27,677 Hispanics -- the average would be about 80. 450 00:23:27,679 --> 00:23:31,214 Native Americans around that level. 451 00:23:31,216 --> 00:23:35,852 And then Japanese and Chinese Americans 452 00:23:35,854 --> 00:23:38,054 above the white average. 453 00:23:38,056 --> 00:23:43,326 And then Ashkenazi Jews probably around 110, 115. 454 00:23:43,328 --> 00:23:47,363 Linda's research has made her a scientific outcast. 455 00:23:47,365 --> 00:23:52,969 She's even been called a racist, a claim she denies. 456 00:23:52,971 --> 00:23:56,139 Her critics argue that I.Q. tests results 457 00:23:56,141 --> 00:23:59,509 are heavily skewed by socioeconomic factors. 458 00:23:59,511 --> 00:24:03,079 Childhood nutrition and access to healthcare 459 00:24:03,081 --> 00:24:06,215 can vary widely between different racial groups. 460 00:24:06,217 --> 00:24:08,518 If you live in a good neighborhood 461 00:24:08,520 --> 00:24:10,119 with well-funded schools, 462 00:24:10,121 --> 00:24:12,388 you are more likely to be accustomed 463 00:24:12,390 --> 00:24:14,857 to the academic setting of an I.Q. test. 464 00:24:14,859 --> 00:24:16,859 And if you live in those neighborhoods, 465 00:24:16,861 --> 00:24:20,296 you are more likely to be Asian or White. 466 00:24:20,298 --> 00:24:22,065 There are also concerns 467 00:24:22,067 --> 00:24:25,935 over whether the test questions have a cultural bias, 468 00:24:25,937 --> 00:24:27,537 a bias reflected by the fact 469 00:24:27,539 --> 00:24:32,642 that it's the white I.Q. average that's set to 100. 470 00:24:32,644 --> 00:24:36,546 Is one race smarter than another? 471 00:24:36,548 --> 00:24:39,849 Depends on what you mean by smart. 472 00:24:39,851 --> 00:24:41,517 Could I.Q. scores predict 473 00:24:41,519 --> 00:24:44,153 the greatness of an artist like Picasso 474 00:24:44,155 --> 00:24:47,423 or of a political leader like Gandhi? 475 00:24:47,425 --> 00:24:50,893 I.Q. is a narrow obsession. 476 00:24:50,895 --> 00:24:53,796 No two people think the same way, 477 00:24:53,798 --> 00:24:56,132 regardless of their race. 478 00:24:56,134 --> 00:24:58,468 So, here's a new question. 479 00:24:58,470 --> 00:25:02,505 If the brains of the races are similar now, 480 00:25:02,507 --> 00:25:04,841 will that always be true? 481 00:25:04,843 --> 00:25:07,243 We are still evolving. 482 00:25:07,245 --> 00:25:10,079 Could our brains one day become as different 483 00:25:10,081 --> 00:25:13,816 as those of Border Collies and beagles? 484 00:25:15,841 --> 00:25:15,841 ++++++++++++++++++++++++++++++ 485 00:25:17,710 --> 00:25:21,713 Evolution has given human beings one incredible asset -- 486 00:25:22,722 --> 00:25:25,556 the remarkable network of nerve cells 487 00:25:25,558 --> 00:25:28,292 buzzing around inside our heads. 488 00:25:28,294 --> 00:25:31,829 The growth of these three pounds of soft tissue 489 00:25:31,831 --> 00:25:33,998 catapulted human intelligence 490 00:25:34,000 --> 00:25:37,001 to a level far above the other species. 491 00:25:37,003 --> 00:25:40,104 How much further can it grow? 492 00:25:40,106 --> 00:25:43,407 Will we eventually evolve into a superior race 493 00:25:43,409 --> 00:25:46,644 of super-intelligent humans? 494 00:25:56,521 --> 00:25:58,522 Neuroscience Professor Simon Laughlin 495 00:25:58,524 --> 00:26:02,693 from the University of Cambridge studies brain power. 496 00:26:02,695 --> 00:26:04,428 He tests the limits 497 00:26:04,430 --> 00:26:07,865 of what brains and their nerve cells can do, 498 00:26:07,867 --> 00:26:11,302 all the while watching how much fuel they guzzle. 499 00:26:11,304 --> 00:26:13,671 So, I'm interested in what the physical limits 500 00:26:13,673 --> 00:26:15,239 to the performance of brains are 501 00:26:15,241 --> 00:26:19,610 and in what determines the processing power of brains. 502 00:26:19,612 --> 00:26:22,813 Simon has developed a unique way to see 503 00:26:22,815 --> 00:26:26,383 just how much information living brains are processing 504 00:26:26,385 --> 00:26:29,086 while simultaneously keeping track 505 00:26:29,088 --> 00:26:31,622 of how much energy they are using. 506 00:26:31,624 --> 00:26:34,124 His window into the human brain 507 00:26:34,126 --> 00:26:38,529 is through the bulbous eyes of flies. 508 00:26:38,531 --> 00:26:40,297 They're a simpler system, 509 00:26:40,299 --> 00:26:42,433 so it's like looking at a pocket calculator 510 00:26:42,435 --> 00:26:44,868 before you work up to actually trying to understand 511 00:26:44,870 --> 00:26:46,503 a really big computer. 512 00:26:46,505 --> 00:26:49,573 The basic principles by which the fly's brain operates 513 00:26:49,575 --> 00:26:50,808 is the same as ours, 514 00:26:50,810 --> 00:26:53,444 but they're much easier to work with, 515 00:26:53,446 --> 00:26:56,447 and we have a much more complete understanding of what they do. 516 00:26:56,449 --> 00:27:00,884 Simon's ability to measure the performance of fly brains 517 00:27:00,886 --> 00:27:06,323 is all thanks to this insect's most bothersome characteristic. 518 00:27:08,294 --> 00:27:10,594 Anybody who's tried to swat a fly knows 519 00:27:10,596 --> 00:27:12,763 that they're very good at detecting movement. 520 00:27:12,765 --> 00:27:16,467 And to do that, they have to be able to respond 521 00:27:16,469 --> 00:27:19,670 to very rapid and fast changes in light. 522 00:27:19,672 --> 00:27:22,272 In fact, detecting light 523 00:27:22,274 --> 00:27:25,476 is most of what a fly's brain does. 524 00:27:25,478 --> 00:27:29,613 Simon's lab is stocked with two species -- 525 00:27:29,615 --> 00:27:32,483 the blowfly, with large, bulging eyes, 526 00:27:32,485 --> 00:27:37,321 and the diminutive fruit fly, whose eyes are much smaller. 527 00:27:37,323 --> 00:27:40,424 He and his team fit microelectrodes 528 00:27:40,426 --> 00:27:42,693 into the fly's nerve cells, 529 00:27:42,695 --> 00:27:45,863 then they expose them to a flickering light 530 00:27:45,865 --> 00:27:49,933 to record their processing power. 531 00:27:49,935 --> 00:27:52,369 So, the cell responds to the light 532 00:27:52,371 --> 00:27:54,872 by changing its membrane potential. 533 00:27:54,874 --> 00:27:56,874 And then we can process those signals 534 00:27:56,876 --> 00:28:00,377 to work out how much information they contain. 535 00:28:00,379 --> 00:28:02,946 Simon discovered that while the fruit fly 536 00:28:02,948 --> 00:28:06,283 is able to see some of the changes in light, 537 00:28:06,285 --> 00:28:10,587 the blowfly picks up on even the most minute flicker. 538 00:28:10,589 --> 00:28:12,523 The blowfly's bulbous eyeballs 539 00:28:12,525 --> 00:28:16,026 spew out a huge quantity of neural data, 540 00:28:16,028 --> 00:28:20,030 enough to fill up a one-gigabyte memory stick 541 00:28:20,032 --> 00:28:21,465 every minute. 542 00:28:21,467 --> 00:28:24,968 But there's a downside for the blowfly. 543 00:28:24,970 --> 00:28:26,503 So, the blowfly picks up 544 00:28:26,505 --> 00:28:30,007 about five times as many bits per second as the fruit fly, 545 00:28:30,009 --> 00:28:33,010 but because it has a much higher performance, 546 00:28:33,012 --> 00:28:34,311 those bits of information, 547 00:28:34,313 --> 00:28:37,881 each bit costs it about 10 times more energy. 548 00:28:37,883 --> 00:28:41,385 Information is very expensive for a fly. 549 00:28:49,961 --> 00:28:53,831 So, we have a sports car that has a very high top speed. 550 00:28:53,833 --> 00:28:55,999 It has a very high performance. 551 00:28:56,001 --> 00:28:59,269 But also, it has a very heavy fuel consumption. 552 00:28:59,271 --> 00:29:00,838 It uses a lot of energy. 553 00:29:00,840 --> 00:29:03,173 So, as we're idling along now in Cambridge, 554 00:29:03,175 --> 00:29:05,709 we're not using any of our performance at all. 555 00:29:13,652 --> 00:29:16,086 This little car here has a lot lower performance 556 00:29:16,088 --> 00:29:17,187 than this sports car, 557 00:29:17,189 --> 00:29:18,722 but it's much more economical. 558 00:29:18,724 --> 00:29:21,225 It uses much less energy to go a given distance. 559 00:29:21,227 --> 00:29:23,627 So, you pay a high price for high performance, 560 00:29:23,629 --> 00:29:25,028 just like neurons. 561 00:29:25,030 --> 00:29:27,397 The powerhouse brain of a human being 562 00:29:27,399 --> 00:29:31,235 is even less fuel efficient than that of the blowfly. 563 00:29:31,237 --> 00:29:34,171 And this is why Simon is almost certain 564 00:29:34,173 --> 00:29:37,908 that the human brain has reached its limit. 565 00:29:37,910 --> 00:29:40,844 So, if the blowfly is this sports car, 566 00:29:40,846 --> 00:29:45,148 then the human brain, with it's vastly superior performance, 567 00:29:45,150 --> 00:29:47,384 is like a space rocket. 568 00:29:47,386 --> 00:29:51,522 Huge amounts of energy being used to process information. 569 00:29:51,524 --> 00:29:55,259 The human brain is only 2% of our body mass, 570 00:29:55,261 --> 00:30:00,197 but it consumes 20% of our oxygen when we are at rest. 571 00:30:00,199 --> 00:30:03,800 The smarter we get, the higher the energy cost. 572 00:30:03,802 --> 00:30:06,837 If we wanted to have a brain that was 10% better, 573 00:30:06,839 --> 00:30:09,973 we might have to have one that was actually 20% bigger. 574 00:30:09,975 --> 00:30:14,244 Then it would make increasingly large demands on the body. 575 00:30:15,447 --> 00:30:17,014 If the human brain got bigger, 576 00:30:17,016 --> 00:30:20,884 it would be more difficult to give birth to children. 577 00:30:20,886 --> 00:30:23,921 And if you wanted to make it much bigger, 578 00:30:23,923 --> 00:30:25,556 when the child was born, 579 00:30:25,558 --> 00:30:28,759 the brain would have to be less well-developed than it is now. 580 00:30:28,761 --> 00:30:32,329 So, infancy and childhood would last longer. 581 00:30:33,966 --> 00:30:37,834 Our brain has evolved to strike some sort of balance 582 00:30:37,836 --> 00:30:41,371 between the cost of processing the information, 583 00:30:41,373 --> 00:30:42,906 which is very high, 584 00:30:42,908 --> 00:30:45,742 and the amount of information we actually need to process. 585 00:30:45,744 --> 00:30:50,847 But there may still be a way for us to become smarter. 586 00:30:50,849 --> 00:30:54,017 If we take matters into our own hands, 587 00:30:54,019 --> 00:30:58,488 we may build a superior human race. 588 00:30:58,490 --> 00:31:02,125 And only some of us will be part of it. 589 00:31:02,150 --> 00:31:02,150 ++++++++++++++++++++++++++++++ 590 00:31:05,461 --> 00:31:07,395 All of modern humanity 591 00:31:07,397 --> 00:31:11,866 can trace its ancestry back to a small group of people 592 00:31:11,868 --> 00:31:15,837 living in East Africa about 50,000 years ago. 593 00:31:15,839 --> 00:31:19,074 We all looked very similar back then. 594 00:31:19,076 --> 00:31:20,508 Over the millennia, 595 00:31:20,510 --> 00:31:23,111 we've adapted to our local climates 596 00:31:23,113 --> 00:31:26,815 and become the rainbow of people we are today. 597 00:31:26,817 --> 00:31:29,651 But evolution hasn't stopped. 598 00:31:29,653 --> 00:31:32,487 Where are we headed? 599 00:31:32,489 --> 00:31:35,423 Could a future race of superior humans... 600 00:31:35,425 --> 00:31:39,027 Look like this? 601 00:31:41,997 --> 00:31:45,500 Peter Ward is a paleontologist 602 00:31:45,502 --> 00:31:49,237 at the University of Washington in Seattle. 603 00:31:49,239 --> 00:31:51,840 He finds evolution everywhere he looks, 604 00:31:51,842 --> 00:31:55,410 even inside a fish market. 605 00:31:55,412 --> 00:31:58,213 Well, we got two really standard wonderful food fish 606 00:31:58,215 --> 00:31:59,681 in the Northwest. 607 00:31:59,683 --> 00:32:02,917 We've got this nice big halibut and these beautiful salmon. 608 00:32:02,919 --> 00:32:04,919 If we look at the fossil record, actually, 609 00:32:04,921 --> 00:32:06,654 these are way more primitive. 610 00:32:06,656 --> 00:32:08,823 These guys were here first and, in fact, 611 00:32:08,825 --> 00:32:12,560 far more fish look like this -- that beautiful fusiform shape -- 612 00:32:12,562 --> 00:32:14,596 than this rather ugly thing. 613 00:32:14,598 --> 00:32:17,098 It's been squished down and flattened. 614 00:32:17,100 --> 00:32:20,268 It's like taking a salmon, rolling it on its side, 615 00:32:20,270 --> 00:32:21,870 bringing an eye over, 616 00:32:21,872 --> 00:32:25,540 and living forever with that totally rotated shape. 617 00:32:25,542 --> 00:32:27,809 This guy lives on the bottom, 618 00:32:27,811 --> 00:32:31,379 and this is a superb adaptation for where it lives. 619 00:32:31,381 --> 00:32:35,884 From the salmon, evolution created the halibut. 620 00:32:35,886 --> 00:32:40,822 What, Peter wonders, might it do to humans? 621 00:32:40,824 --> 00:32:44,392 It is tempting to believe that nature has a master plan 622 00:32:44,394 --> 00:32:48,897 to evolve us into fitter, smarter, more attractive beings. 623 00:32:48,899 --> 00:32:52,734 But nature doesn't work that way. 624 00:32:52,736 --> 00:32:56,671 Our best traits and our worst traits 625 00:32:56,673 --> 00:33:00,241 are chosen for us quite randomly. 626 00:33:00,243 --> 00:33:02,610 Albert Einstein most famously said, 627 00:33:02,612 --> 00:33:05,413 "God does not play dice with the universe." 628 00:33:05,415 --> 00:33:07,515 Well, maybe he was right in physics, 629 00:33:07,517 --> 00:33:10,451 but in evolution, there's a whole lot of dice playing. 630 00:33:10,453 --> 00:33:13,655 Here's my evolutionary dice -- die. 631 00:33:13,657 --> 00:33:17,826 This is A, T, G, and C -- the genetic code. 632 00:33:17,828 --> 00:33:19,928 When they combine together, 633 00:33:19,930 --> 00:33:22,630 they tell an organism what traits it's gonna have. 634 00:33:22,632 --> 00:33:24,265 And much of that combination 635 00:33:24,267 --> 00:33:26,367 comes together in random fashion. 636 00:33:26,369 --> 00:33:29,671 So if I throw this evolutionary die, 637 00:33:29,673 --> 00:33:33,675 I'm gonna be stuck with this particular gene, 638 00:33:33,677 --> 00:33:37,679 and that gene might take me up any one of these four roads. 639 00:33:37,681 --> 00:33:40,448 Three of those roads might kill you almost instantly. 640 00:33:40,450 --> 00:33:44,552 One of them might be towards a really superior organism. 641 00:33:46,789 --> 00:33:50,291 If Peter wants to make his way across town 642 00:33:50,293 --> 00:33:51,993 to a high-end restaurant 643 00:33:51,995 --> 00:33:55,129 using the rules of DNA navigation, 644 00:33:55,131 --> 00:33:59,701 he will have to rely on the random roll of a die. 645 00:34:02,872 --> 00:34:05,039 One turn could get him closer. 646 00:34:07,042 --> 00:34:09,978 The next could turn him back toward where he started. 647 00:34:09,980 --> 00:34:13,882 There's no telling when or if he will ever make it. 648 00:34:13,884 --> 00:34:16,484 Evolution is a random process 649 00:34:16,486 --> 00:34:19,721 that usually leads to genetic dead ends. 650 00:34:19,723 --> 00:34:21,022 Ugh! 651 00:34:22,191 --> 00:34:25,193 But what if Peter could escape the randomness 652 00:34:25,195 --> 00:34:27,195 of natural selection? 653 00:34:27,197 --> 00:34:30,064 Up until we became a technical species, 654 00:34:30,066 --> 00:34:32,567 we were, like every other species, 655 00:34:32,569 --> 00:34:34,302 at mercy to the randomness 656 00:34:34,304 --> 00:34:37,639 and to, really, the nastiness of evolution. 657 00:34:37,641 --> 00:34:39,540 The next stage of human evolution 658 00:34:39,542 --> 00:34:41,342 is going to be we humans 659 00:34:41,344 --> 00:34:45,280 tinkering right into the genome itself. 660 00:34:46,682 --> 00:34:50,785 Not only can we change people in their lifetime, 661 00:34:50,787 --> 00:34:54,722 but we'll be able to change their very DNA 662 00:34:54,724 --> 00:34:56,524 so that they and their changes 663 00:34:56,526 --> 00:34:58,993 get passed on to the next generation. 664 00:34:58,995 --> 00:35:01,863 With this type of directed evolution, 665 00:35:01,865 --> 00:35:05,133 Peter does not have to blindly depend on chance 666 00:35:05,135 --> 00:35:08,269 to get him where he wants to go. 667 00:35:10,673 --> 00:35:12,740 Waterfront Seafood Grill. 668 00:35:18,847 --> 00:35:20,682 Genetic technology 669 00:35:20,684 --> 00:35:23,851 could take you on a direct route from "A" to "B", 670 00:35:23,853 --> 00:35:25,853 as long as you can pay for the ride. 671 00:35:25,855 --> 00:35:28,156 Peter believes that once humans 672 00:35:28,158 --> 00:35:30,692 start pursuing unnatural selection, 673 00:35:30,694 --> 00:35:33,928 we will diverge into two separate races -- 674 00:35:33,930 --> 00:35:37,332 those who are left rolling the evolutionary dice 675 00:35:37,334 --> 00:35:42,036 and those who can afford to design their own genome. 676 00:35:42,038 --> 00:35:44,839 All right. Thank you much. 677 00:35:44,841 --> 00:35:47,141 Halibut. Thanks. 678 00:35:47,143 --> 00:35:50,144 I could see a point where once the differences 679 00:35:50,146 --> 00:35:51,813 we engineer into ourselves 680 00:35:51,815 --> 00:35:54,315 are so different from what you find 681 00:35:54,317 --> 00:35:56,317 in the wild, stock humans 682 00:35:56,319 --> 00:35:59,220 versus the genetically engineered humans, 683 00:35:59,222 --> 00:36:01,055 there will be a divergence. 684 00:36:01,057 --> 00:36:03,291 If you had children that bred 685 00:36:03,293 --> 00:36:04,926 with other children with these enhancements, 686 00:36:04,928 --> 00:36:06,327 it keeps going. 687 00:36:06,329 --> 00:36:09,263 You're gonna see a social drifting apart. 688 00:36:09,265 --> 00:36:11,099 And speciation happens 689 00:36:11,101 --> 00:36:15,770 when gene pools separate -- populations separate. 690 00:36:15,772 --> 00:36:18,873 It is a grim vision of the future -- 691 00:36:18,875 --> 00:36:21,075 a global gated community 692 00:36:21,077 --> 00:36:25,213 of super-rich, long-lived human 2.0's 693 00:36:25,215 --> 00:36:27,882 hogging all the resources... 694 00:36:27,884 --> 00:36:31,586 And a completely separate species of people 695 00:36:31,588 --> 00:36:33,821 who can barely survive. 696 00:36:33,823 --> 00:36:35,723 But another technological course 697 00:36:35,725 --> 00:36:38,826 is driving us in a different direction. 698 00:36:40,362 --> 00:36:43,664 The next big leap toward creating a superior human race 699 00:36:43,666 --> 00:36:46,267 may come from us putting aside our differences 700 00:36:46,269 --> 00:36:49,804 and putting our heads together. 701 00:36:49,229 --> 00:36:49,229 ++++++++++++++++++++++++++++++ 702 00:36:52,051 --> 00:36:54,986 Earth is already a crowded place. 703 00:36:54,988 --> 00:36:56,888 And by the end of this century, 704 00:36:56,890 --> 00:37:01,192 the human population will probably reach 11 billion. 705 00:37:01,194 --> 00:37:05,330 We'll be packed in as tightly as bees in a hive. 706 00:37:05,332 --> 00:37:07,899 That prospect has inspired some scientists 707 00:37:07,901 --> 00:37:10,868 to envision a new evolution of mankind. 708 00:37:10,870 --> 00:37:13,972 Just as insect colonies share the workload, 709 00:37:13,974 --> 00:37:18,109 perhaps we can learn to harness the power of multiple brains 710 00:37:18,111 --> 00:37:23,047 and create a vastly superior global hive mind. 711 00:37:26,018 --> 00:37:29,087 "Sandy" Pentland is the head of the Human Dynamics Lab 712 00:37:29,089 --> 00:37:30,488 at M.I.T. 713 00:37:30,490 --> 00:37:33,224 He's a pioneer of a new field of research -- 714 00:37:33,226 --> 00:37:36,027 computational social science. 715 00:37:36,029 --> 00:37:37,862 Sandy believes humanity 716 00:37:37,864 --> 00:37:41,332 is about to become a smarter, superior species -- 717 00:37:41,334 --> 00:37:43,201 not because we're going to evolve 718 00:37:43,203 --> 00:37:45,336 at the individual level, 719 00:37:45,338 --> 00:37:48,606 but through a transformation in the way we work together. 720 00:37:48,608 --> 00:37:50,475 So, human organizations 721 00:37:50,477 --> 00:37:53,077 are a little bit like an information machine. 722 00:37:53,079 --> 00:37:55,213 The gears not only have to fit together, 723 00:37:55,215 --> 00:37:56,814 but they have to be synchronized 724 00:37:56,816 --> 00:38:00,084 so that they work together rather than against each other. 725 00:38:00,086 --> 00:38:02,353 So, this desire to synchronize 726 00:38:02,355 --> 00:38:05,523 is something that's very ancient in our species, 727 00:38:05,525 --> 00:38:08,092 and you see it in dance and also in music, 728 00:38:08,094 --> 00:38:10,528 like here with the M.I.T. Logarhythms, 729 00:38:10,530 --> 00:38:12,764 where bass comes in. 730 00:38:12,766 --> 00:38:16,367 Bass: we 731 00:38:16,369 --> 00:38:18,503 And the baritone comes in. 732 00:38:18,505 --> 00:38:21,039 Baritones: are Bass: we 733 00:38:21,041 --> 00:38:22,640 And the tenor. 734 00:38:22,642 --> 00:38:28,713 Tenors: we are Baritones: are Bass: we 735 00:38:28,715 --> 00:38:31,449 and then they meld together into a whole. 736 00:38:31,451 --> 00:38:33,251 We we are 737 00:38:33,253 --> 00:38:35,386 we we are we are 738 00:38:35,388 --> 00:38:37,822 we we are we are 739 00:38:37,824 --> 00:38:40,091 Music like this is an example of something 740 00:38:40,093 --> 00:38:42,794 that's much bigger than just the individuals. 741 00:38:42,796 --> 00:38:46,364 We are 742 00:38:46,366 --> 00:38:49,300 Humans are naturally social creatures. 743 00:38:49,302 --> 00:38:51,302 We developed language and culture 744 00:38:51,304 --> 00:38:54,939 to trade knowledge and share experiences. 745 00:38:54,941 --> 00:38:58,009 Sandy believes that we are about to supercharge 746 00:38:58,011 --> 00:39:00,645 the degree to which we share knowledge, 747 00:39:00,647 --> 00:39:05,717 thanks to a quantum leap in communication technology. 748 00:39:05,719 --> 00:39:08,986 One of the most profound changes has happened in the last decade. 749 00:39:08,988 --> 00:39:10,922 And something that's not well appreciated 750 00:39:10,924 --> 00:39:12,990 is the fact that we all carry around phones, 751 00:39:12,992 --> 00:39:15,359 and these are getting smarter and smarter. 752 00:39:15,361 --> 00:39:16,928 Take traffic, for example. 753 00:39:16,930 --> 00:39:20,798 You can now look on your phone or on your car dashboard 754 00:39:20,800 --> 00:39:24,669 and see how dense the traffic is and get real-time updates. 755 00:39:24,671 --> 00:39:27,472 Technology that lets us share pictures, 756 00:39:27,474 --> 00:39:29,774 share stories in a way we never could 757 00:39:29,776 --> 00:39:31,843 and just turns the clock right up more. 758 00:39:31,845 --> 00:39:33,444 That's all driven by those phones 759 00:39:33,446 --> 00:39:35,213 that people are carrying around. 760 00:39:35,215 --> 00:39:36,647 So, we're being able to make 761 00:39:36,649 --> 00:39:39,917 this sort of unified intelligence. 762 00:39:39,919 --> 00:39:41,619 Handheld smart devices 763 00:39:41,621 --> 00:39:45,022 are getting us to work and think together like never before. 764 00:39:45,024 --> 00:39:47,325 They are merging humanity 765 00:39:47,327 --> 00:39:50,628 into a single interconnected mind 766 00:39:50,630 --> 00:39:52,330 that spans the globe, 767 00:39:52,332 --> 00:39:56,868 capable of feats no single brain could achieve. 768 00:39:56,870 --> 00:39:58,503 In 2009, 769 00:39:58,505 --> 00:40:01,105 the Defense Advanced Research Project Agency 770 00:40:01,107 --> 00:40:04,909 set a challenge designed specifically for hive minds. 771 00:40:04,911 --> 00:40:07,779 It placed 10 red balloons, 772 00:40:07,781 --> 00:40:10,348 each adorned with a special certificate, 773 00:40:10,350 --> 00:40:13,050 at secret locations across the U.S. 774 00:40:13,052 --> 00:40:15,720 It offered a $40,000 prize 775 00:40:15,722 --> 00:40:18,556 to the team that discovered the GPS coordinates 776 00:40:18,558 --> 00:40:21,526 of all 10 balloons the fastest. 777 00:40:21,528 --> 00:40:24,829 Thousands of teams took up the challenge. 778 00:40:24,831 --> 00:40:27,532 Sandy's plan was to engage 779 00:40:27,534 --> 00:40:32,904 a swarm of cell-toting, social-media-connected minds. 780 00:40:32,906 --> 00:40:36,073 And what we did is we leveraged social media 781 00:40:36,075 --> 00:40:37,642 in a very creative way. 782 00:40:37,644 --> 00:40:40,444 So, I wouldn't just give you a prize for finding a balloon. 783 00:40:40,446 --> 00:40:44,215 I'd give you a prize for recruiting people, 784 00:40:44,217 --> 00:40:46,584 one of whom might find the balloon. 785 00:40:46,586 --> 00:40:49,020 So, if they found the balloon, you'd get some, too. 786 00:40:49,022 --> 00:40:52,156 And what this does is it creates a cascade. 787 00:40:52,158 --> 00:40:54,458 Thousands and thousands of people, 788 00:40:54,460 --> 00:40:57,261 all recruiting their friends to look for the balloon 789 00:40:57,263 --> 00:41:00,364 because it's in their interest to do that. 790 00:41:00,366 --> 00:41:03,668 Sandy's method worked incredibly well. 791 00:41:03,670 --> 00:41:07,672 His M.I.T. team bagged photos of all 10 balloons, 792 00:41:07,674 --> 00:41:11,809 uncovered in places like San Francisco's Union Square 793 00:41:11,811 --> 00:41:13,578 and a tennis court in Virginia, 794 00:41:13,580 --> 00:41:16,147 in just nine hours. 795 00:41:16,149 --> 00:41:17,849 They were able to find the balloons 796 00:41:17,851 --> 00:41:19,750 faster than anybody else in the world -- 797 00:41:19,752 --> 00:41:21,652 in fact, in a time 798 00:41:21,654 --> 00:41:24,388 that they generally thought was impossible. 799 00:41:24,390 --> 00:41:28,492 In social species, there's a drive to be social. 800 00:41:28,494 --> 00:41:31,028 If you ask, "What's the number-one thing 801 00:41:31,030 --> 00:41:32,630 that contributes to life satisfaction?" 802 00:41:32,632 --> 00:41:35,333 It's building things with other people. 803 00:41:35,335 --> 00:41:37,768 And what we've done is developed technology 804 00:41:37,770 --> 00:41:40,004 to try and help us do that. 805 00:41:43,041 --> 00:41:46,577 Imagine a sea of humanity with instant awareness of events 806 00:41:46,579 --> 00:41:51,215 taking place over ranges of thousands of miles. 807 00:41:51,217 --> 00:41:53,284 We could trace the source of a viral epidemic 808 00:41:53,286 --> 00:41:56,354 to one apartment block in a matter of hours, 809 00:41:56,356 --> 00:41:59,023 just by seeing who was staying home from work 810 00:41:59,025 --> 00:42:01,359 with their cellphone turned on. 811 00:42:01,361 --> 00:42:04,562 We could solve age-old problems of hunger and poverty 812 00:42:04,564 --> 00:42:07,632 by tracking supply and demand for food 813 00:42:07,634 --> 00:42:09,934 on a minute-to-minute basis. 814 00:42:09,936 --> 00:42:11,769 What you'll see in the future, 815 00:42:11,771 --> 00:42:14,784 where we're able to pool our experience 816 00:42:14,809 --> 00:42:17,622 to make all of our individual experiences better. 817 00:42:20,652 --> 00:42:23,700 So, what is the future of race? 818 00:42:24,758 --> 00:42:28,351 Genetics tells us that there are subtle differences between us. 819 00:42:28,376 --> 00:42:30,560 Both on the inside and the outside. 820 00:42:31,415 --> 00:42:34,064 Those differences emerged as we wandered the Earth 821 00:42:34,089 --> 00:42:37,777 as separate tribes, for more than 50,000 years. 822 00:42:38,444 --> 00:42:42,171 But now, something new is happening in human history. 823 00:42:42,196 --> 00:42:44,887 We don't have room to be separate anymore. 824 00:42:45,520 --> 00:42:49,831 Technology, combined with our deep instinct to work together 825 00:42:50,163 --> 00:42:54,191 is about to push us one giant step forward. 826 00:42:54,297 --> 00:42:57,473 And will create not a superior race, 827 00:42:57,946 --> 00:43:02,166 but a superior species, to which we will all belong. 828 00:43:02,382 --> 00:43:06,382 == sync, corrected by elderman == DHD sync by tagman90 829 00:43:06,432 --> 00:43:10,982 Repair and Synchronization by Easy Subtitles Synchronizer 1.0.0.0 65743

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