1 00:00:00,095 --> 00:00:02,460 The following content is provided under a Creative 2 00:00:02,460 --> 00:00:03,870 Commons license. 3 00:00:03,870 --> 00:00:06,910 Your support will help MIT OpenCourseWare continue to 4 00:00:06,910 --> 00:00:10,560 offer high-quality educational resources for free. 5 00:00:10,560 --> 00:00:13,460 To make a donation or view additional materials from 6 00:00:13,460 --> 00:00:17,390 hundreds of MIT courses, visit MIT OpenCourseWare at 7 00:00:17,390 --> 00:00:18,640 ocw.mit.edu. 8 00:00:27,090 --> 00:00:28,340 PROFESSOR: Good afternoon. 9 00:00:30,990 --> 00:00:32,229 Good afternoon. 10 00:00:32,229 --> 00:00:34,730 I want to remind you that a week from today 11 00:00:34,730 --> 00:00:36,130 is the second exam. 12 00:00:36,130 --> 00:00:38,630 The format is identical to what you had, 50 multiple 13 00:00:38,630 --> 00:00:42,940 choice questions; 30 from the book, Chapters 5 to 7; 20 from 14 00:00:42,940 --> 00:00:44,595 Sacks and the lectures; short answers. 15 00:00:48,990 --> 00:00:53,980 So talking about tests, why do we have tests? 16 00:00:53,980 --> 00:00:55,330 You live in a world of tests. 17 00:00:58,140 --> 00:01:03,760 Everything from SATs to, on your horizons, maybe GREs or 18 00:01:03,760 --> 00:01:06,310 MCATs or LSATs. 19 00:01:06,310 --> 00:01:10,850 So why do people have tests, besides making it miserable to 20 00:01:10,850 --> 00:01:13,460 be under 30? 21 00:01:13,460 --> 00:01:16,320 It's the revenge of the older people. 22 00:01:16,320 --> 00:01:17,570 Why do people have tests? 23 00:01:25,140 --> 00:01:25,410 Yeah? 24 00:01:25,410 --> 00:01:25,590 AUDIENCE: [INAUDIBLE]. 25 00:01:25,590 --> 00:01:28,590 PROFESSOR: One of them is just verify 26 00:01:28,590 --> 00:01:29,250 that you know something. 27 00:01:29,250 --> 00:01:34,400 And people will call it sort of have you learned stuff? 28 00:01:34,400 --> 00:01:37,120 And the test is meant to be an estimate of 29 00:01:37,120 --> 00:01:39,240 what have you learned? 30 00:01:39,240 --> 00:01:42,770 But a second form of testing, what people sometimes will 31 00:01:42,770 --> 00:01:45,640 call high-stakes tests in a slightly different way, are 32 00:01:45,640 --> 00:01:49,500 ones about selection and prediction, which sometimes 33 00:01:49,500 --> 00:01:52,040 involve achievement or aptitude, things 34 00:01:52,040 --> 00:01:53,970 like SATs or GREs. 35 00:01:53,970 --> 00:01:58,060 So achievements are meant to be estimates of what you know, 36 00:01:58,060 --> 00:02:00,640 advanced placement tests, how much math you know or physics. 37 00:02:00,640 --> 00:02:02,510 Content in a given area. 38 00:02:02,510 --> 00:02:05,950 And sort of a broader sense of aptitude, SATs or GREs. 39 00:02:05,950 --> 00:02:07,630 Now, one thing that's different about today's 40 00:02:07,630 --> 00:02:09,729 lecture on intelligence, it'll be a little similar when we do 41 00:02:09,729 --> 00:02:13,830 personalities, up until now, to a first approximation, most 42 00:02:13,830 --> 00:02:16,430 of the time we've talked about what we view as general 43 00:02:16,430 --> 00:02:19,900 principles of the human mind and brain across everybody. 44 00:02:19,900 --> 00:02:22,200 How vision works across everybody, memory across 45 00:02:22,200 --> 00:02:25,010 everybody, thinking across everybody. 46 00:02:25,010 --> 00:02:26,630 And now, we're switching to a domain. 47 00:02:26,630 --> 00:02:29,390 And it doesn't have to be this way, but this is the way the 48 00:02:29,390 --> 00:02:32,370 world has done it, where we emphasized 49 00:02:32,370 --> 00:02:34,640 differences between people. 50 00:02:34,640 --> 00:02:37,620 So when people take tests, it's not to see that everybody 51 00:02:37,620 --> 00:02:38,670 took the test. 52 00:02:38,670 --> 00:02:41,570 What they're going to do is, you get an A, or a B, or a C, 53 00:02:41,570 --> 00:02:45,440 or you get a high SAT or a medium SAT, and schools use 54 00:02:45,440 --> 00:02:50,260 the differences to think about you. 55 00:02:50,260 --> 00:02:54,340 And so one question is, from an empirical sense, are these 56 00:02:54,340 --> 00:02:55,910 tests pretty good at predicting things? 57 00:02:55,910 --> 00:02:58,990 And the answer is they're decent. 58 00:02:58,990 --> 00:03:00,940 They're not terrific. 59 00:03:00,940 --> 00:03:07,100 So the tests survive, like SATs or GREs, because there's 60 00:03:07,100 --> 00:03:09,850 correlations between these kinds of tests before you get 61 00:03:09,850 --> 00:03:13,090 to graduate school for example, and how faculty rates 62 00:03:13,090 --> 00:03:16,260 students or how productive people are in terms of 63 00:03:16,260 --> 00:03:19,170 research or as a graduate student in this case, or the 64 00:03:19,170 --> 00:03:21,220 GPAs, or things like that. 65 00:03:21,220 --> 00:03:25,020 And the correlations are about 0.3 to 0.4. 66 00:03:25,020 --> 00:03:27,390 To give you an intuitive sense, the correlations 67 00:03:27,390 --> 00:03:29,990 between sex and height, whether you're a man or a 68 00:03:29,990 --> 00:03:31,620 woman and height, is about 0.4. 69 00:03:31,620 --> 00:03:34,100 So of course lots of women are taller than lots of men. 70 00:03:34,100 --> 00:03:36,000 On average, men are taller than women. 71 00:03:36,000 --> 00:03:38,190 It's a 0.4 correlation. 72 00:03:38,190 --> 00:03:41,240 So this is in that range. 73 00:03:41,240 --> 00:03:44,900 So tests are pretty good predictors. 74 00:03:44,900 --> 00:03:47,020 Everybody says that for things like predicting college 75 00:03:47,020 --> 00:03:50,190 performance or graduate school performance, a combination of 76 00:03:50,190 --> 00:03:52,990 tests and grades are better. 77 00:03:52,990 --> 00:03:56,860 The difference is grades take a lot of years to produce. 78 00:03:56,860 --> 00:04:00,680 Tests are one traumatic outing. 79 00:04:00,680 --> 00:04:06,370 So tests are just a part of our life 80 00:04:06,370 --> 00:04:09,460 in selection processes. 81 00:04:09,460 --> 00:04:11,260 So now what is intelligence? 82 00:04:11,260 --> 00:04:13,780 And it's a loaded word. 83 00:04:13,780 --> 00:04:15,240 I mean memory is kind of a neutral word. 84 00:04:15,240 --> 00:04:16,680 Attention is a neutral word. 85 00:04:16,680 --> 00:04:18,120 Intelligence is a loaded word. 86 00:04:18,120 --> 00:04:22,490 I mean nobody wants to be low on intelligence. 87 00:04:22,490 --> 00:04:25,670 And so psychologists have come out of this way. 88 00:04:25,670 --> 00:04:27,620 But it's kind of funny, because there's not going to 89 00:04:27,620 --> 00:04:29,610 be a really deep definition. 90 00:04:29,610 --> 00:04:31,890 Maybe it's a lot of different things and how they average up 91 00:04:31,890 --> 00:04:33,070 or something like that. 92 00:04:33,070 --> 00:04:34,850 But people have said well, it's something about the 93 00:04:34,850 --> 00:04:37,440 ability to solve problems, to understand and learn complex 94 00:04:37,440 --> 00:04:41,390 material, to adapt to the environment, mental quickness. 95 00:04:41,390 --> 00:04:43,790 Those are all senses you might have of something that you 96 00:04:43,790 --> 00:04:46,360 think of as intelligence in a person. 97 00:04:46,360 --> 00:04:50,280 But whether they're one thing, many things, it's very hard to 98 00:04:50,280 --> 00:04:51,040 pull that out. 99 00:04:51,040 --> 00:04:53,680 And we don't know too much about that really. 100 00:04:53,680 --> 00:04:55,970 And also I want remind you of something we talked about, but 101 00:04:55,970 --> 00:04:57,860 it's especially important in this field. 102 00:04:57,860 --> 00:05:00,810 We talked about an experiment versus correlations. 103 00:05:00,810 --> 00:05:03,190 An experiment, you have to have a dependent measure, 104 00:05:03,190 --> 00:05:03,930 something you measure. 105 00:05:03,930 --> 00:05:06,170 But critically and uniquely, you have an independent 106 00:05:06,170 --> 00:05:08,720 variable, something that you vary. 107 00:05:08,720 --> 00:05:11,010 That's what makes a study an experiment, as opposed to a 108 00:05:11,010 --> 00:05:12,320 correlation. 109 00:05:12,320 --> 00:05:15,800 So studies of intelligence of every kind are almost always 110 00:05:15,800 --> 00:05:19,140 correlational and almost never experimental. 111 00:05:19,140 --> 00:05:21,360 That means they're always subject to lots of 112 00:05:21,360 --> 00:05:23,830 interpretation and many factors in the world. 113 00:05:23,830 --> 00:05:27,290 And that's very important to keep in mind. 114 00:05:27,290 --> 00:05:30,730 And again, they tend to focus on variation in people, rather 115 00:05:30,730 --> 00:05:34,275 than what is intelligence itself. 116 00:05:34,275 --> 00:05:37,060 And again, here's another correlation 117 00:05:37,060 --> 00:05:40,050 of height and weight. 118 00:05:40,050 --> 00:05:43,200 That's a stronger correlation. 119 00:05:43,200 --> 00:05:45,040 So where did intelligence start with? 120 00:05:45,040 --> 00:05:46,600 It's a fascinating story. 121 00:05:46,600 --> 00:05:48,930 And by the way, let me tell you the SAT story, on the 122 00:05:48,930 --> 00:05:50,680 sidebar, for a moment. 123 00:05:50,680 --> 00:05:55,060 So SATs, nowadays do people, some people get ready a lot 124 00:05:55,060 --> 00:05:57,300 for SATs by courses you take and things like that? 125 00:05:57,300 --> 00:05:59,570 I read about that. 126 00:05:59,570 --> 00:06:02,450 When I took it, people weren't that organized. 127 00:06:02,450 --> 00:06:04,165 But getting into college wasn't that competitive. 128 00:06:07,010 --> 00:06:11,250 And the original goals of SATs was what, do you know? 129 00:06:11,250 --> 00:06:12,610 It's really interesting. 130 00:06:12,610 --> 00:06:15,480 Because it ends up being the thing, they say well, because 131 00:06:15,480 --> 00:06:18,260 people who are maybe under more supported circumstances, 132 00:06:18,260 --> 00:06:21,150 more financially advantageous circumstances, get more help 133 00:06:21,150 --> 00:06:22,600 to get ready for the SAT. 134 00:06:22,600 --> 00:06:25,770 Those things might amplify SAT differences in a way that's 135 00:06:25,770 --> 00:06:27,490 not really about the person to start with. 136 00:06:27,490 --> 00:06:30,480 The original goal of the SATs was to have a national test 137 00:06:30,480 --> 00:06:33,700 that was fair for everybody, so that schools like Harvard, 138 00:06:33,700 --> 00:06:35,870 for example, that tended to admit the same kind of 139 00:06:35,870 --> 00:06:37,180 students from the same small set of 140 00:06:37,180 --> 00:06:38,440 schools in the Northeast. 141 00:06:38,440 --> 00:06:40,860 So now, we have a test for everybody across the country. 142 00:06:40,860 --> 00:06:43,960 And we can admit people on their merit, rather than on 143 00:06:43,960 --> 00:06:45,610 small, social connectivity networks. 144 00:06:45,610 --> 00:06:46,560 Does that make sense? 145 00:06:46,560 --> 00:06:48,990 And yet, SATs are now viewed as a suspicious 146 00:06:48,990 --> 00:06:49,710 tool in that regard. 147 00:06:49,710 --> 00:06:51,610 It was originally meant to be democratizing. 148 00:06:51,610 --> 00:06:54,650 It's like everybody in the country takes the same test. 149 00:06:54,650 --> 00:06:58,346 It's not whether you have a connection through a network, 150 00:06:58,346 --> 00:06:59,770 to our university. 151 00:06:59,770 --> 00:07:01,460 IQs have the same story. 152 00:07:01,460 --> 00:07:04,720 For good reasons, and we'll talk about that, IQ tests and 153 00:07:04,720 --> 00:07:08,870 interpretations of IQ don't have a good history. 154 00:07:08,870 --> 00:07:11,760 But the original goal was pretty reasonable. 155 00:07:11,760 --> 00:07:16,440 So in France in 1904, they began universal elementary 156 00:07:16,440 --> 00:07:19,510 education, that every child goes to class. 157 00:07:19,510 --> 00:07:21,920 And Alfred Binet, a physician, wanted an objective way to 158 00:07:21,920 --> 00:07:24,135 identify children who needed extra help. 159 00:07:24,135 --> 00:07:25,590 A perfectly good idea. 160 00:07:25,590 --> 00:07:26,790 A child comes to school. 161 00:07:26,790 --> 00:07:28,300 Some children are ready to go. 162 00:07:28,300 --> 00:07:31,520 Some children need a lot of extra help because they have a 163 00:07:31,520 --> 00:07:32,600 difficulty. 164 00:07:32,600 --> 00:07:36,200 So he developed a set of tests where he probed many different 165 00:07:36,200 --> 00:07:39,640 abilities, like copying a drawing, repeating digits, 166 00:07:39,640 --> 00:07:41,680 recognizing coins, explaining why a statement 167 00:07:41,680 --> 00:07:42,700 did not make sense. 168 00:07:42,700 --> 00:07:45,230 They wanted to probe different little areas of abilities, so 169 00:07:45,230 --> 00:07:48,110 if a child is terrible at something, or two things, the 170 00:07:48,110 --> 00:07:51,540 teacher knows this child needs some extra help to get going. 171 00:07:51,540 --> 00:07:54,480 So that's a good use of testing, I think by 172 00:07:54,480 --> 00:07:55,880 everybody's criterion. 173 00:07:55,880 --> 00:08:00,990 But then testing sort of took off, IQ testing. 174 00:08:00,990 --> 00:08:03,280 IQ stands for intelligence quotient. 175 00:08:03,280 --> 00:08:05,360 It's a test to give typical children. 176 00:08:05,360 --> 00:08:08,470 They give it often for the most commonly used IQ tests, 177 00:08:08,470 --> 00:08:09,580 at many different ages. 178 00:08:09,580 --> 00:08:11,930 They'll test a large number of individuals. 179 00:08:11,930 --> 00:08:14,550 And they'll compare what nowadays what they think of as 180 00:08:14,550 --> 00:08:17,430 your mental age to your chronological age. 181 00:08:17,430 --> 00:08:19,950 So your chronological age is how long you've lived. 182 00:08:19,950 --> 00:08:23,390 And your mental age is how well you score on a test. 183 00:08:23,390 --> 00:08:26,780 The most famous IQ test, the most widely used, takes about 184 00:08:26,780 --> 00:08:27,950 two hours of testing. 185 00:08:27,950 --> 00:08:30,040 It comes from David Wechsler, the Wechsler Adult 186 00:08:30,040 --> 00:08:30,870 Intelligence Scale. 187 00:08:30,870 --> 00:08:32,780 One for children. 188 00:08:32,780 --> 00:08:34,630 And within that test, what's within that test? 189 00:08:34,630 --> 00:08:37,909 Because when people talk about tests I think, whatever kind 190 00:08:37,909 --> 00:08:41,270 of test it is, it can only about as good as the test 191 00:08:41,270 --> 00:08:44,740 design itself, to the extent that it's any good. 192 00:08:44,740 --> 00:08:46,930 A ridiculous test is a ridiculous test, even if 193 00:08:46,930 --> 00:08:49,440 society gives it to you. 194 00:08:49,440 --> 00:08:51,470 But tests can be better than that. 195 00:08:51,470 --> 00:08:56,160 So what is inside the most widely used IQ tests, 196 00:08:56,160 --> 00:08:57,860 especially in clinical environments? 197 00:08:57,860 --> 00:08:59,380 So let's talk about one of them. 198 00:08:59,380 --> 00:09:00,790 It has a bunch of little tests. 199 00:09:00,790 --> 00:09:01,810 One is vocabulary. 200 00:09:01,810 --> 00:09:04,900 They ask you to define words, similarities. 201 00:09:04,900 --> 00:09:06,560 They'll ask you a series of questions, like how are an 202 00:09:06,560 --> 00:09:08,710 airplane and a car alike? 203 00:09:08,710 --> 00:09:11,250 Very simple arithmetic operations. 204 00:09:11,250 --> 00:09:13,980 Digit spans, how many digits can you remember. 205 00:09:13,980 --> 00:09:16,110 Information, they'll give you a series of questions, like 206 00:09:16,110 --> 00:09:17,990 who was Martin Luther King, Jr.? 207 00:09:17,990 --> 00:09:20,700 Comprehension, they'll ask you things about the world, like 208 00:09:20,700 --> 00:09:22,880 why are there taxes and things like that. 209 00:09:22,880 --> 00:09:24,030 And you give an answer. 210 00:09:24,030 --> 00:09:25,830 Somebody scribbles down when you say. 211 00:09:25,830 --> 00:09:27,090 And they score you. 212 00:09:27,090 --> 00:09:28,050 You get two points or one point. 213 00:09:28,050 --> 00:09:29,080 We'll talk about that. 214 00:09:29,080 --> 00:09:30,700 And then they add up these scores in the subtests. 215 00:09:33,540 --> 00:09:35,710 So in the nonverbal verbal tests or the performance 216 00:09:35,710 --> 00:09:38,610 tests, they'll show you a picture with a thing missing. 217 00:09:38,610 --> 00:09:39,430 Have you did that a kid? 218 00:09:39,430 --> 00:09:40,650 I love those things. 219 00:09:40,650 --> 00:09:43,270 What's missing in the picture and stuff like that. 220 00:09:43,270 --> 00:09:45,460 Blocks, they'll have you rearrange them into various 221 00:09:45,460 --> 00:09:46,790 geometric design. 222 00:09:46,790 --> 00:09:49,820 Picture arrangement, you'll get cartoon panels and you 223 00:09:49,820 --> 00:09:52,080 have to put them in the correct order to tell a story. 224 00:09:52,080 --> 00:09:53,960 And they measure how accurately and quickly you do 225 00:09:53,960 --> 00:09:55,040 these things. 226 00:09:55,040 --> 00:09:57,130 There's nothing amazing about any of these things. 227 00:09:57,130 --> 00:09:59,100 They're probing a variety of little 228 00:09:59,100 --> 00:10:02,060 abilities that you have. 229 00:10:02,060 --> 00:10:04,720 And again, they will take the mental age and chronological 230 00:10:04,720 --> 00:10:06,580 age, divide it, multiply it by 100. 231 00:10:06,580 --> 00:10:09,750 And they'll standardize it, so that 100 is the population 232 00:10:09,750 --> 00:10:11,040 mean in the United States. 233 00:10:11,040 --> 00:10:13,150 Other countries do these things, as well. 234 00:10:13,150 --> 00:10:15,050 Is that OK? 235 00:10:15,050 --> 00:10:17,490 So I mean a test can only be as possibly good as the 236 00:10:17,490 --> 00:10:18,440 content of it. 237 00:10:18,440 --> 00:10:20,490 And what it measures or doesn't measure depends on the 238 00:10:20,490 --> 00:10:24,320 specific conflict of it. 239 00:10:24,320 --> 00:10:26,450 They'll scale the scores out, so you get a normal 240 00:10:26,450 --> 00:10:29,220 distribution, with a peak in the middle. 241 00:10:29,220 --> 00:10:30,800 The raw score is the number you get. 242 00:10:30,800 --> 00:10:33,030 The standardized one is adjusted for your age. 243 00:10:33,030 --> 00:10:34,820 And it's a pretty important concept, because we'll come 244 00:10:34,820 --> 00:10:36,010 back to this in a moment. 245 00:10:36,010 --> 00:10:37,810 The raw score is your actual score. 246 00:10:37,810 --> 00:10:39,970 But then they adjust it for your age. 247 00:10:39,970 --> 00:10:43,080 Because you don't expect a five-year-old to do as well as 248 00:10:43,080 --> 00:10:49,540 a 15-year-old, to do as well as peak 18 to 23-year-olds. 249 00:10:49,540 --> 00:10:51,870 And then bad things happen as you get older. 250 00:10:51,870 --> 00:10:54,460 I'll tell you a bit of them about that too. 251 00:10:54,460 --> 00:10:56,950 2/3 of the people are at plus or minus 1 standard deviation. 252 00:10:56,950 --> 00:10:58,600 They set it for that. 253 00:10:58,600 --> 00:11:01,260 More than two standard deviations up or down, are 254 00:11:01,260 --> 00:11:04,600 about 5% on either end of the distribution of scores. 255 00:11:04,600 --> 00:11:06,020 And they norm it by age. 256 00:11:06,020 --> 00:11:09,690 Again, you don't expect a six-year-old to do something. 257 00:11:09,690 --> 00:11:10,860 But you get some funny things. 258 00:11:10,860 --> 00:11:12,460 Not that you have to worry about this in detail. 259 00:11:12,460 --> 00:11:14,380 But it gives you a sense. 260 00:11:14,380 --> 00:11:18,820 So imagine you're a five-year-old and you take the 261 00:11:18,820 --> 00:11:21,140 test, on the last day you're a five-year-old. 262 00:11:21,140 --> 00:11:23,045 Or imagine you have your birthday today and 263 00:11:23,045 --> 00:11:24,400 you're six years old. 264 00:11:24,400 --> 00:11:28,120 By moving from five to six, from Wednesday to Thursday, 265 00:11:28,120 --> 00:11:31,410 you've moved up a year for the scoring. 266 00:11:31,410 --> 00:11:33,410 Because they go by year, not by day. 267 00:11:33,410 --> 00:11:36,940 So if you would have scored 120 on the IQ test yesterday, 268 00:11:36,940 --> 00:11:38,890 when they say what should you have scored for a 269 00:11:38,890 --> 00:11:41,630 five-year-old, the very same test, the next day, 270 00:11:41,630 --> 00:11:43,590 you would score 100. 271 00:11:43,590 --> 00:11:45,910 Now, that's the extreme case. 272 00:11:45,910 --> 00:11:47,290 But you understand what happens, right? 273 00:11:47,290 --> 00:11:49,130 Because here's how well you did. 274 00:11:49,130 --> 00:11:50,440 That might have been pretty good. 275 00:11:50,440 --> 00:11:53,950 120 is above the average for a five-year-old. 276 00:11:53,950 --> 00:11:57,190 But the next day, if you're a six-year-old, now for a 277 00:11:57,190 --> 00:11:59,140 six-year-old, it's just average. 278 00:11:59,140 --> 00:12:02,850 So age has a big effect on these things. 279 00:12:02,850 --> 00:12:06,810 Here's something sad for aging, but good for you. 280 00:12:06,810 --> 00:12:08,850 Be smart now. 281 00:12:08,850 --> 00:12:11,920 A 40-year-old who scores average 282 00:12:11,920 --> 00:12:16,280 would be a real undergrad. 283 00:12:16,280 --> 00:12:18,560 If I score like you-- 284 00:12:18,560 --> 00:12:19,560 no, let me rephrase this. 285 00:12:19,560 --> 00:12:22,830 If you were compared to a 40-year-old, you would have 286 00:12:22,830 --> 00:12:25,320 100 IQ, you would have a 230 IQ. 287 00:12:25,320 --> 00:12:28,310 Because age knocks down the score as well. 288 00:12:28,310 --> 00:12:30,230 So things go up and then things go 289 00:12:30,230 --> 00:12:33,210 down, in this problem. 290 00:12:33,210 --> 00:12:36,670 And usually they think of a score below 70 as clinically 291 00:12:36,670 --> 00:12:38,850 concerning. 292 00:12:38,850 --> 00:12:41,400 And the top 2%, you get to join Mensa and do whatever 293 00:12:41,400 --> 00:12:42,130 Mensa people do. 294 00:12:42,130 --> 00:12:44,310 Which I don't know exactly, but it sounds interesting. 295 00:12:46,950 --> 00:12:49,710 An important thing about tests of any kind, are two huge 296 00:12:49,710 --> 00:12:51,220 concepts, reliability and validity. 297 00:12:51,220 --> 00:12:53,690 So reliability refers to the idea that if you were tested 298 00:12:53,690 --> 00:12:56,900 more than once, you would get the same score. 299 00:12:56,900 --> 00:12:58,650 The better IQ tests work a fair bit to 300 00:12:58,650 --> 00:13:00,360 try to achieve that. 301 00:13:00,360 --> 00:13:03,190 Validity is the deeper question. 302 00:13:03,190 --> 00:13:05,360 Does the test validly measure what it's supposed to measure? 303 00:13:05,360 --> 00:13:08,180 So if we had you flip a coin and said that's your IQ, you'd 304 00:13:08,180 --> 00:13:09,830 say, that's ridiculous. 305 00:13:09,830 --> 00:13:11,210 That's not a valid test. 306 00:13:11,210 --> 00:13:13,090 We could measure your height. 307 00:13:13,090 --> 00:13:14,830 That would be extremely reliable measure. 308 00:13:14,830 --> 00:13:16,390 You'll have the same height today as tomorrow, if we did a 309 00:13:16,390 --> 00:13:17,340 decent job. 310 00:13:17,340 --> 00:13:20,350 That wouldn't be a valid measure of anything about any 311 00:13:20,350 --> 00:13:22,580 mental ability, never mind something like intelligence. 312 00:13:22,580 --> 00:13:25,050 So those are two important concepts in 313 00:13:25,050 --> 00:13:27,620 testing, but very different. 314 00:13:27,620 --> 00:13:30,300 Now, why do people think IQ tests are interesting, besides 315 00:13:30,300 --> 00:13:33,330 just this weird curiosity about intelligence? 316 00:13:33,330 --> 00:13:36,450 Because IQ tests correlate with GPA in high school and 317 00:13:36,450 --> 00:13:39,910 college, job success, salary, stable marriages, staying out 318 00:13:39,910 --> 00:13:42,340 of jail, and how long you live. 319 00:13:42,340 --> 00:13:43,380 Again, it's a correlation. 320 00:13:43,380 --> 00:13:45,645 It could be many different things. 321 00:13:45,645 --> 00:13:48,250 The thing I want to talk you out of is the idea that if you 322 00:13:48,250 --> 00:13:52,985 have a 200 IQ today, you've got something stored up that 323 00:13:52,985 --> 00:13:54,590 will fend off disease. 324 00:13:54,590 --> 00:13:56,850 It's not that, necessarily. 325 00:13:56,850 --> 00:13:59,290 It's that there's lots of things in your life that got 326 00:13:59,290 --> 00:14:00,600 you to that score. 327 00:14:00,600 --> 00:14:02,710 And all those things are likely to persist in your 328 00:14:02,710 --> 00:14:07,250 life: good health, support of education, interest maybe in 329 00:14:07,250 --> 00:14:09,230 taking on challenging tasks. 330 00:14:09,230 --> 00:14:10,110 You had those before. 331 00:14:10,110 --> 00:14:11,400 You had them while you took the test. 332 00:14:11,400 --> 00:14:14,440 You continue to have them after. 333 00:14:14,440 --> 00:14:16,660 Another way to think about it though, which is both a plus 334 00:14:16,660 --> 00:14:19,390 and minus, depending on how you look at it, IQ scores 335 00:14:19,390 --> 00:14:21,670 account for approximately 25% of the 336 00:14:21,670 --> 00:14:23,260 variation on these things. 337 00:14:23,260 --> 00:14:24,220 So that's not huge. 338 00:14:24,220 --> 00:14:27,020 That means there's many, many, many other factors, besides 339 00:14:27,020 --> 00:14:28,890 whatever IQ is capturing. 340 00:14:28,890 --> 00:14:31,250 But it's about as big a chunk as you can get for a couple 341 00:14:31,250 --> 00:14:32,300 hours of testing. 342 00:14:32,300 --> 00:14:35,290 And we know that other things like personality, variation, 343 00:14:35,290 --> 00:14:38,210 education, culture, all those things blend in on how a 344 00:14:38,210 --> 00:14:40,775 person will do on all these outcomes. 345 00:14:43,630 --> 00:14:44,720 So I'm going to go back and forth. 346 00:14:44,720 --> 00:14:45,850 Because on the one hand, we say there's a lot of stuff 347 00:14:45,850 --> 00:14:46,210 besides IQ. 348 00:14:46,210 --> 00:14:48,010 But IQ has some interestingness, otherwise 349 00:14:48,010 --> 00:14:49,040 nobody would talk about it. 350 00:14:49,040 --> 00:14:50,260 And it would just disappear from the world. 351 00:14:50,260 --> 00:14:55,790 So on average, on average, what does 15 IQ points mean? 352 00:14:55,790 --> 00:14:58,640 So on average, a person with 100 IQ in the US will go to 353 00:14:58,640 --> 00:15:00,660 high school and a year or two in a community college. 354 00:15:00,660 --> 00:15:04,560 On average, these are averages over huge variety of people. 355 00:15:04,560 --> 00:15:07,120 You get 15 more IQ points, and on average, you're likely to 356 00:15:07,120 --> 00:15:09,630 finish college and have a white collar job. 357 00:15:09,630 --> 00:15:11,890 Have 15 fewer points, and you're not likely to complete 358 00:15:11,890 --> 00:15:12,700 high school. 359 00:15:12,700 --> 00:15:14,570 And you'd have to have a job that doesn't require 360 00:15:14,570 --> 00:15:16,270 educational background. 361 00:15:16,270 --> 00:15:20,870 So 15 point on averages correlate with things. 362 00:15:20,870 --> 00:15:24,450 Here's another one, because everybody in the end is a 363 00:15:24,450 --> 00:15:25,930 little bit curious. 364 00:15:25,930 --> 00:15:28,680 In your own life, how much of what you're good at or not 365 00:15:28,680 --> 00:15:32,210 good at, of any of us, comes from our genes, from our 366 00:15:32,210 --> 00:15:32,970 environment? 367 00:15:32,970 --> 00:15:34,790 Where does that come from? 368 00:15:34,790 --> 00:15:37,930 What are the things that support us or limit us? 369 00:15:37,930 --> 00:15:42,970 So here's one study that took women from the same family. 370 00:15:42,970 --> 00:15:45,800 So they're all sisters from the same family. 371 00:15:45,800 --> 00:15:48,690 They're trying to control a little bit of the genetics, 372 00:15:48,690 --> 00:15:50,220 because they share genes within the family. 373 00:15:50,220 --> 00:15:51,280 They're not twins. 374 00:15:51,280 --> 00:15:53,360 And definitely shared environment. 375 00:15:53,360 --> 00:15:55,760 They're in the same household. 376 00:15:55,760 --> 00:15:59,320 And within those families, they look at the IQ scores. 377 00:15:59,320 --> 00:16:02,580 So here's the average group, above average, well above 378 00:16:02,580 --> 00:16:05,760 average, a little below average, a lot below average. 379 00:16:05,760 --> 00:16:09,330 And they say that in these women, all coming from the 380 00:16:09,330 --> 00:16:13,120 same household, here's their average income and here's the 381 00:16:13,120 --> 00:16:17,500 average rate of illegitimate births, which is one measure 382 00:16:17,500 --> 00:16:21,540 that people think is kind of a social, on average not a 383 00:16:21,540 --> 00:16:23,500 desired outcome, to have a child without a family 384 00:16:23,500 --> 00:16:23,990 supporting. 385 00:16:23,990 --> 00:16:26,180 It's not going to help a person succeed in the world to 386 00:16:26,180 --> 00:16:28,570 be a single mother. 387 00:16:28,570 --> 00:16:32,370 And so you can see, the salary pretty much moves with the IQ 388 00:16:32,370 --> 00:16:33,320 on average. 389 00:16:33,320 --> 00:16:36,890 And the rate of illegitimate births pretty much 390 00:16:36,890 --> 00:16:38,620 moves with that too. 391 00:16:38,620 --> 00:16:41,730 So again, it's an average. 392 00:16:41,730 --> 00:16:44,510 But there's some relationship between these things. 393 00:16:44,510 --> 00:16:49,980 Now, if you pick up the newspaper today and read about 394 00:16:49,980 --> 00:16:55,110 nuclear disasters in Japan and problems in the Middle East 395 00:16:55,110 --> 00:16:57,750 and other things like that, you would say, it's hard to 396 00:16:57,750 --> 00:16:59,880 say the world is getting smarter. 397 00:16:59,880 --> 00:17:02,010 But you may or may not be surprised to hear of the 398 00:17:02,010 --> 00:17:02,940 so-called Flynn effect. 399 00:17:02,940 --> 00:17:05,450 This was kind of a surprise when it was discovered, which 400 00:17:05,450 --> 00:17:06,430 is basically this. 401 00:17:06,430 --> 00:17:09,369 IQ scores, where they're measured, go up around the 402 00:17:09,369 --> 00:17:10,400 world all the time. 403 00:17:10,400 --> 00:17:14,089 By IQ test scores, it's as if the world is getting smarter 404 00:17:14,089 --> 00:17:17,859 all the time, which is kind of an optimistic thing. 405 00:17:17,859 --> 00:17:20,240 Whether it's getting wiser is a good question. 406 00:17:20,240 --> 00:17:23,030 But by IQ score, smarter all the time. 407 00:17:23,030 --> 00:17:26,630 So that's hidden for many years, because every few years 408 00:17:26,630 --> 00:17:29,320 these tests get renormed for the groups. 409 00:17:29,320 --> 00:17:30,670 Does that makes sense? 410 00:17:30,670 --> 00:17:33,210 So they're given again and 100 is the average. 411 00:17:33,210 --> 00:17:35,310 And they're given again and 100 is the average. 412 00:17:35,310 --> 00:17:38,040 But if they ignore this averaging and just say, across 413 00:17:38,040 --> 00:17:39,970 these tests that only change a little bit, some of them only 414 00:17:39,970 --> 00:17:42,760 change a little bit, if we just take the scores, look at 415 00:17:42,760 --> 00:17:45,606 1930, 1940. 416 00:17:45,606 --> 00:17:48,770 And it just keeps going up. 417 00:17:48,770 --> 00:17:51,340 So Flynn is the person who discovered that the world is 418 00:17:51,340 --> 00:17:54,320 getting smarter by raw IQ tests. 419 00:17:56,970 --> 00:17:59,640 And one of tests they use, I'll show you an example of 420 00:17:59,640 --> 00:18:01,420 this, it's another widely used test called Raven's 421 00:18:01,420 --> 00:18:03,510 Progressive Matrices, IQs go up about three 422 00:18:03,510 --> 00:18:05,770 points every 10 years. 423 00:18:05,770 --> 00:18:10,160 So that if you were born in 1930, a person would have an 424 00:18:10,160 --> 00:18:15,490 IQ of 100, their child 108, and their grandchild, 120, 425 00:18:15,490 --> 00:18:16,810 with a standard deviation higher. 426 00:18:16,810 --> 00:18:20,590 So it's like smarter, smarter, smarter. 427 00:18:20,590 --> 00:18:24,860 I don't recommend to go home and tell your parents that any 428 00:18:24,860 --> 00:18:26,610 debate you have with them is pointless, because you're 429 00:18:26,610 --> 00:18:29,390 smarter than they are. 430 00:18:29,390 --> 00:18:32,180 But if push comes to shove, you can look up the Flynn 431 00:18:32,180 --> 00:18:34,760 effect and have a discussion about that. 432 00:18:34,760 --> 00:18:39,240 So somebody who has an IQ today, just flip it around. 433 00:18:39,240 --> 00:18:41,360 If you have a 100, your grandparent would 434 00:18:41,360 --> 00:18:44,176 have a IQ of 82. 435 00:18:44,176 --> 00:18:46,400 By this reasoning, people in 1900 would have 436 00:18:46,400 --> 00:18:47,650 a mean IQ of 70. 437 00:18:50,330 --> 00:18:52,580 And nobody knows why it's going up all over the world. 438 00:18:52,580 --> 00:18:54,010 There's all kinds of ideas about maybe 439 00:18:54,010 --> 00:18:55,650 nutrition is going up. 440 00:18:55,650 --> 00:18:57,950 Maybe reasoning abilities are being pushed. 441 00:18:57,950 --> 00:18:59,350 Maybe educational things. 442 00:18:59,350 --> 00:19:01,730 I mean it's impossible scientifically to know why, 443 00:19:01,730 --> 00:19:05,450 because it's happening in such a global, giant scale. 444 00:19:05,450 --> 00:19:08,410 But some people have said, the tests don't go up uniformly 445 00:19:08,410 --> 00:19:09,120 across the tests. 446 00:19:09,120 --> 00:19:12,320 Which gives us a hint about the way the world is changing 447 00:19:12,320 --> 00:19:15,840 and how intelligence tests in some way become a barometer of 448 00:19:15,840 --> 00:19:17,200 what mental abilities are 449 00:19:17,200 --> 00:19:20,710 increasingly prized by societies. 450 00:19:20,710 --> 00:19:23,670 So there's relatively small gains across years in 451 00:19:23,670 --> 00:19:26,950 vocabulary or general knowledge or arithmetic. 452 00:19:26,950 --> 00:19:29,530 Where there are large gains are what you might call 453 00:19:29,530 --> 00:19:32,850 abstract thinking tasks, like similarities. 454 00:19:32,850 --> 00:19:34,730 So let's focus on that for a moment. 455 00:19:34,730 --> 00:19:36,670 So a similarities question might be like this. 456 00:19:36,670 --> 00:19:39,810 In what way are dogs and rabbits alike? 457 00:19:39,810 --> 00:19:43,870 If you answer both mammals, you get two points. 458 00:19:43,870 --> 00:19:46,090 That's the best you can do. 459 00:19:46,090 --> 00:19:48,870 And that's what we would call an abstract or taxonomic one. 460 00:19:48,870 --> 00:19:51,140 You're abstracting across the two things. 461 00:19:51,140 --> 00:19:53,190 Or you could give an answer like, you use 462 00:19:53,190 --> 00:19:55,660 dogs to hunt rabbits. 463 00:19:55,660 --> 00:19:57,150 That's not a wrong answer. 464 00:19:57,150 --> 00:20:00,090 That's considered a one-point answer. 465 00:20:00,090 --> 00:20:01,920 You kind of seem to know what a dog is, you kind of seem to 466 00:20:01,920 --> 00:20:02,410 know a rabbit. 467 00:20:02,410 --> 00:20:05,120 But you didn't give the best answer by this test criterion. 468 00:20:05,120 --> 00:20:07,250 Because it's a functional description of these things, 469 00:20:07,250 --> 00:20:09,980 not a abstract, conceptual one. 470 00:20:09,980 --> 00:20:13,210 So let's think about different societies, besides the Western 471 00:20:13,210 --> 00:20:16,500 industrialized one that we represent mostly. 472 00:20:16,500 --> 00:20:22,250 In Liberia, they ask people to sort baskets of food, tools, 473 00:20:22,250 --> 00:20:24,710 containers, and clothing. 474 00:20:24,710 --> 00:20:28,330 So most of us, Western educated in a very broad 475 00:20:28,330 --> 00:20:31,350 sense, would put the things of food together, the things of 476 00:20:31,350 --> 00:20:32,000 tools together. 477 00:20:32,000 --> 00:20:34,100 Those are the abstract categories. 478 00:20:34,100 --> 00:20:36,370 The people from this tribe put them in terms 479 00:20:36,370 --> 00:20:37,300 of functional pairings. 480 00:20:37,300 --> 00:20:39,870 They put the potato next to the knife they use to peel the 481 00:20:39,870 --> 00:20:42,250 potato, right? 482 00:20:42,250 --> 00:20:44,250 And here's the fun thing in this study. 483 00:20:44,250 --> 00:20:47,040 They said, what would a fool do with this? 484 00:20:47,040 --> 00:20:49,720 And they said oh, well, a fool would put all the food things 485 00:20:49,720 --> 00:20:51,610 together and all the utensils together. 486 00:20:51,610 --> 00:20:54,060 But that's pointless to do that, because what are you 487 00:20:54,060 --> 00:20:55,310 going to do with all the food things over here, when the 488 00:20:55,310 --> 00:20:56,500 utensils are over here. 489 00:20:56,500 --> 00:20:57,330 You understand? 490 00:20:57,330 --> 00:20:59,500 It's what our society emphasizes as a 491 00:20:59,500 --> 00:21:01,830 useful way of thinking. 492 00:21:01,830 --> 00:21:05,540 So it could be arbitrary. 493 00:21:05,540 --> 00:21:08,460 But it's not arbitrarily rewarded and prized in the 494 00:21:08,460 --> 00:21:14,000 world of education, that we live in here. 495 00:21:14,000 --> 00:21:17,970 So intelligence tests attach value at a specific time and 496 00:21:17,970 --> 00:21:18,700 specific test. 497 00:21:18,700 --> 00:21:21,180 Scores are changing over time. 498 00:21:21,180 --> 00:21:24,230 Different cultures are valuing different things. 499 00:21:24,230 --> 00:21:25,480 It's constantly renormed. 500 00:21:28,200 --> 00:21:30,340 And because of that, here's another example of how the 501 00:21:30,340 --> 00:21:31,110 renorming is. 502 00:21:31,110 --> 00:21:34,360 It used to be for some number of years, that 70 was used as 503 00:21:34,360 --> 00:21:37,080 a cut-off for estimates of, broadly speaking, mental 504 00:21:37,080 --> 00:21:38,120 retardation. 505 00:21:38,120 --> 00:21:41,040 And why that matters is that a person for example would get 506 00:21:41,040 --> 00:21:45,140 certain kinds of medical services provided to them. 507 00:21:45,140 --> 00:21:48,530 When a new version of the WISC, of the Wechsler test, 508 00:21:48,530 --> 00:21:51,980 came out in 1991, so a renormed version, so that 509 00:21:51,980 --> 00:21:56,360 means the scores are going up, if every state in the country 510 00:21:56,360 --> 00:21:58,970 had simultaneously used that new test when it came out, 511 00:21:58,970 --> 00:22:01,110 which they didn't quite, but if they had, the number of 512 00:22:01,110 --> 00:22:04,440 people rated as retarded, diagnosed as retarded, would 513 00:22:04,440 --> 00:22:06,630 have doubled in a single day. 514 00:22:06,630 --> 00:22:09,560 Because the norms aren't pushing the numbers up. 515 00:22:09,560 --> 00:22:10,220 OK? 516 00:22:10,220 --> 00:22:13,620 So the number of people scoring very poorly would have 517 00:22:13,620 --> 00:22:16,710 doubled in a single day because of the renorming. 518 00:22:19,320 --> 00:22:21,730 It's very important to realize that all these things, what's 519 00:22:21,730 --> 00:22:25,270 really in the test, what's valued by a sort of society or 520 00:22:25,270 --> 00:22:28,030 culture, and the norming things are really influencing 521 00:22:28,030 --> 00:22:29,855 a lot of how you get to these numbers. 522 00:22:33,110 --> 00:22:37,540 So ideas about intelligence, roughly in this field, have 523 00:22:37,540 --> 00:22:39,040 come out of what people call 524 00:22:39,040 --> 00:22:40,900 psychometric analysis of subtests. 525 00:22:40,900 --> 00:22:42,850 They give you the scatter of tests. 526 00:22:42,850 --> 00:22:45,780 And the thing that struck many people is how for a given 527 00:22:45,780 --> 00:22:48,570 individual, there's correlations among the tests. 528 00:22:48,570 --> 00:22:52,280 A person who does well on one test, tends to do well on 529 00:22:52,280 --> 00:22:55,270 another test, and tends to do well on a third test. 530 00:22:55,270 --> 00:23:00,590 And a researcher named Spearman gave this correlation 531 00:23:00,590 --> 00:23:03,730 among tests, the letter "g," the name g, to stand for 532 00:23:03,730 --> 00:23:07,660 general intelligence, and "s" for specific intelligence. 533 00:23:07,660 --> 00:23:10,445 And since then, many people have said well really is there 534 00:23:10,445 --> 00:23:12,680 one broad sense of intelligence, are there 535 00:23:12,680 --> 00:23:15,060 multiple separate kinds of intelligence? 536 00:23:15,060 --> 00:23:16,370 And people debate that in the field. 537 00:23:16,370 --> 00:23:19,240 And probably somewhat the answer is it depends what 538 00:23:19,240 --> 00:23:21,630 you're measuring for and the purpose of the measurement. 539 00:23:21,630 --> 00:23:24,130 But a good one to look at, because it's very clear, is 540 00:23:24,130 --> 00:23:27,600 the difference between fluid and crystallized intelligence. 541 00:23:27,600 --> 00:23:29,810 So fluid intelligence is what we think of as 542 00:23:29,810 --> 00:23:31,290 novel problem solving. 543 00:23:31,290 --> 00:23:32,440 You have a situation you were never in 544 00:23:32,440 --> 00:23:34,640 before, what do you do? 545 00:23:34,640 --> 00:23:36,930 Crystallized intelligence are facts you know, 546 00:23:36,930 --> 00:23:40,250 information you know. 547 00:23:40,250 --> 00:23:43,120 So here's the conceptual idea that maybe general 548 00:23:43,120 --> 00:23:45,470 intelligence is a thing. 549 00:23:45,470 --> 00:23:48,250 And then it shows up on different tests, with the 550 00:23:48,250 --> 00:23:49,680 different specific intelligences. 551 00:23:49,680 --> 00:23:51,090 That's like maybe verbal or arithmetic. 552 00:23:54,230 --> 00:23:58,710 But let me show you the fluid and crystallized one. 553 00:23:58,710 --> 00:24:01,060 So the fluid one we said were first mental processes that 554 00:24:01,060 --> 00:24:02,840 apply for a novel situation. 555 00:24:02,840 --> 00:24:06,110 And that declines a lot with age and adulthood. 556 00:24:06,110 --> 00:24:10,090 So these lines going down here, I'm about here and 557 00:24:10,090 --> 00:24:11,150 you're about here. 558 00:24:11,150 --> 00:24:14,930 Who should be grading who in this course, you might ask? 559 00:24:14,930 --> 00:24:17,980 The only reason that I get to grade you is because these 560 00:24:17,980 --> 00:24:19,190 lines keep going up here. 561 00:24:19,190 --> 00:24:21,970 This is how many facts you know. 562 00:24:21,970 --> 00:24:25,150 So the plus of living longer is that you get 563 00:24:25,150 --> 00:24:27,510 to know more stuff. 564 00:24:27,510 --> 00:24:30,170 The risk of living longer is you don't use it as flexibly 565 00:24:30,170 --> 00:24:32,410 under novel situations. 566 00:24:32,410 --> 00:24:34,100 So a pretty strong distinction, at least with 567 00:24:34,100 --> 00:24:37,040 aging, between so-called fluid intelligence and crystallized 568 00:24:37,040 --> 00:24:38,140 intelligence. 569 00:24:38,140 --> 00:24:40,990 Here's another study of exactly the same thing. 570 00:24:40,990 --> 00:24:44,960 It's a striking ski slope of decline in fluid intelligence. 571 00:24:44,960 --> 00:24:50,840 Look at this, ernt, from 20 to 80, it just goes down 572 00:24:50,840 --> 00:24:52,650 relentlessly. 573 00:24:52,650 --> 00:24:54,680 But when it comes to crystallized intelligence, 574 00:24:54,680 --> 00:24:57,810 things like vocabulary, that kind of hangs in there, until 575 00:24:57,810 --> 00:25:00,530 you have some big health problem. 576 00:25:00,530 --> 00:25:01,740 So at least those two kinds seem to 577 00:25:01,740 --> 00:25:05,210 have a different basis. 578 00:25:05,210 --> 00:25:08,110 And people have thought about different ways to think about 579 00:25:08,110 --> 00:25:08,770 intelligence. 580 00:25:08,770 --> 00:25:11,030 And I'll just tell you that in general you get positive 581 00:25:11,030 --> 00:25:12,340 correlations among the tests. 582 00:25:12,340 --> 00:25:14,650 And so often people think about this general 583 00:25:14,650 --> 00:25:15,280 intelligence. 584 00:25:15,280 --> 00:25:16,990 The correlation among the tests is 585 00:25:16,990 --> 00:25:18,240 the best single predictor. 586 00:25:20,670 --> 00:25:23,560 Now, there's lots of responses to ideas about intelligence. 587 00:25:23,560 --> 00:25:26,980 One of them is the study of emotional intelligence. 588 00:25:26,980 --> 00:25:28,410 Peter Salovey is the researcher 589 00:25:28,410 --> 00:25:30,240 most involved in that. 590 00:25:30,240 --> 00:25:31,850 And we know this in everyday life. 591 00:25:31,850 --> 00:25:36,730 We know smart people, what we might call book smart people, 592 00:25:36,730 --> 00:25:40,070 who seem unwise in how they relate to people, how they 593 00:25:40,070 --> 00:25:43,360 perceive emotions, how they facilitate thought with 594 00:25:43,360 --> 00:25:45,930 emotion, how they understand or manage their emotions, how 595 00:25:45,930 --> 00:25:47,470 they relate to other people. 596 00:25:47,470 --> 00:25:52,530 And so it's common sense to think of that as something 597 00:25:52,530 --> 00:25:53,950 that varies across people. 598 00:25:53,950 --> 00:25:56,210 It's very hard to measure that. 599 00:25:56,210 --> 00:25:59,400 I mean, part of the tyranny of tests is what can be measured, 600 00:25:59,400 --> 00:26:00,120 gets measured. 601 00:26:00,120 --> 00:26:01,900 What's hard to measure, is hard to measure. 602 00:26:01,900 --> 00:26:05,640 It's very hard to measure, in a laboratory, in an hour, a 603 00:26:05,640 --> 00:26:06,900 person's emotional intelligence. 604 00:26:06,900 --> 00:26:07,770 People have tried. 605 00:26:07,770 --> 00:26:10,020 It's just hard to do. 606 00:26:10,020 --> 00:26:12,310 Here's another area that's gotten a lot of attention, 607 00:26:12,310 --> 00:26:14,560 from Howard Gardner at Harvard. 608 00:26:14,560 --> 00:26:17,320 Kind of fighting back against this idea of a single form of 609 00:26:17,320 --> 00:26:19,880 intelligence as captured by g, the idea of multiple 610 00:26:19,880 --> 00:26:21,050 intelligences. 611 00:26:21,050 --> 00:26:23,760 And looking at things, the associations in patients and 612 00:26:23,760 --> 00:26:24,840 development. 613 00:26:24,840 --> 00:26:27,380 That we can talk about linguistic intelligence, 614 00:26:27,380 --> 00:26:30,540 spatial intelligence, music intelligence, bodily 615 00:26:30,540 --> 00:26:31,140 intelligence. 616 00:26:31,140 --> 00:26:33,180 Great athletes have great bodily intelligence. 617 00:26:33,180 --> 00:26:35,430 Intrapersonal or interpersonal, it's kind of 618 00:26:35,430 --> 00:26:36,710 like emotional. 619 00:26:36,710 --> 00:26:38,020 Existential. 620 00:26:38,020 --> 00:26:39,250 So he said, there's all these different kinds of 621 00:26:39,250 --> 00:26:40,720 intelligence. 622 00:26:40,720 --> 00:26:43,030 And each person is a profile of these. 623 00:26:43,030 --> 00:26:45,340 You can be really strong in one, and medium in another, 624 00:26:45,340 --> 00:26:47,210 and not so strong in another. 625 00:26:47,210 --> 00:26:49,700 The problem with this whole approach is, yes, it's true 626 00:26:49,700 --> 00:26:51,520 that people have a huge variety of 627 00:26:51,520 --> 00:26:52,640 facets of their humanity. 628 00:26:52,640 --> 00:26:55,480 This whole course, I feel like every lecture we do, we just 629 00:26:55,480 --> 00:26:57,070 turn a person a little bit to study another 630 00:26:57,070 --> 00:26:59,440 facet of their humanity. 631 00:26:59,440 --> 00:27:03,600 But it's hard as heck to measure interpersonal 632 00:27:03,600 --> 00:27:05,880 intelligence or naturalistic intelligence. 633 00:27:05,880 --> 00:27:07,670 Now, maybe somebody will figure out how to do that. 634 00:27:07,670 --> 00:27:10,300 It's just hard to measure those things, even if it feels 635 00:27:10,300 --> 00:27:13,430 like something conceptually that's there. 636 00:27:13,430 --> 00:27:17,130 So this idea, which has had a lot of resonance to people not 637 00:27:17,130 --> 00:27:20,580 liking very simple-minded ideas of intelligence, very 638 00:27:20,580 --> 00:27:23,610 unitary ones, it's still not gained much traction in 639 00:27:23,610 --> 00:27:24,860 practical use. 640 00:27:27,060 --> 00:27:29,165 So let me talk a bit about some of the things that people 641 00:27:29,165 --> 00:27:31,240 have said, well, if we talk about this intelligence, what 642 00:27:31,240 --> 00:27:33,590 might be some mental mechanisms or neural 643 00:27:33,590 --> 00:27:36,400 mechanisms that support or underlie it. 644 00:27:36,400 --> 00:27:39,110 So some things that go with it are mental speed. 645 00:27:39,110 --> 00:27:42,410 And you know this, kind of quickness of thought. 646 00:27:42,410 --> 00:27:44,910 OK, not even big thoughts, just quickness feels like it 647 00:27:44,910 --> 00:27:46,860 helps a person solve problems. 648 00:27:46,860 --> 00:27:49,000 So for example there's a moderately high correlation 649 00:27:49,000 --> 00:27:52,250 between IQ, complicated tests, of all those tests, and how 650 00:27:52,250 --> 00:27:55,390 quickly you push a button when the light comes on. 651 00:27:55,390 --> 00:27:59,360 Now, we never say, wow, Sally or Fred is really smart. 652 00:27:59,360 --> 00:28:00,950 They can push a button when the light 653 00:28:00,950 --> 00:28:03,090 comes on really fast. 654 00:28:03,090 --> 00:28:04,890 Let's go to them and get the answers for the problem set. 655 00:28:07,490 --> 00:28:10,540 But that would go with the idea that simply being fast is 656 00:28:10,540 --> 00:28:13,560 kind of a useful thing for acting on the world. 657 00:28:13,560 --> 00:28:16,090 Or how quickly people decide whether two lengths, two 658 00:28:16,090 --> 00:28:18,040 lines, are the same length or a different length. 659 00:28:18,040 --> 00:28:20,810 Very simple thing, just speed. 660 00:28:20,810 --> 00:28:23,110 And another idea is working memory capacity. 661 00:28:23,110 --> 00:28:25,790 How much information you can hold in your head at any one 662 00:28:25,790 --> 00:28:28,000 time that's relevant to the problem or 663 00:28:28,000 --> 00:28:29,510 task in front of you. 664 00:28:29,510 --> 00:28:31,220 So people have tried to explore these in certain ways. 665 00:28:31,220 --> 00:28:32,950 And I'm going to talk to you about a couple of brain 666 00:28:32,950 --> 00:28:34,970 studies that have tried to look at this. 667 00:28:34,970 --> 00:28:38,730 So again, we talked last time about frontal cortex and 668 00:28:38,730 --> 00:28:39,430 different parts of it. 669 00:28:39,430 --> 00:28:41,340 And especially the dorsal-lateral prefrontal 670 00:28:41,340 --> 00:28:44,680 cortex is involved in thinking. 671 00:28:44,680 --> 00:28:48,670 And so people have taken tasks and said, what happens when 672 00:28:48,670 --> 00:28:49,720 you think about them? 673 00:28:49,720 --> 00:28:53,190 So here's one, an easy item on the so-called Cattell 674 00:28:53,190 --> 00:28:54,710 Culture-Fair Test. 675 00:28:54,710 --> 00:28:57,920 So which of these things goes into here. 676 00:28:57,920 --> 00:28:59,170 There's harder ones. 677 00:29:01,910 --> 00:29:06,350 Or here's a slightly adapted version of the Raven's 678 00:29:06,350 --> 00:29:07,160 Progressive Matrices. 679 00:29:07,160 --> 00:29:08,290 I'll let you think about that for a moment. 680 00:29:08,290 --> 00:29:09,980 I don't remember which it is. 681 00:29:09,980 --> 00:29:13,170 So you're told here's some rows and columns. 682 00:29:13,170 --> 00:29:17,380 One of these eight answers logically fits in here. 683 00:29:17,380 --> 00:29:21,100 And it's your job to figure out which one. 684 00:29:21,100 --> 00:29:22,630 Let's see. 685 00:29:22,630 --> 00:29:24,890 How do we like-- 686 00:29:24,890 --> 00:29:25,170 three. 687 00:29:25,170 --> 00:29:27,935 I like three too. 688 00:29:27,935 --> 00:29:29,330 Does that three seem OK? 689 00:29:32,110 --> 00:29:35,560 This is a medium-hard item on this kind of a test. 690 00:29:35,560 --> 00:29:39,290 And then they do these kind of map of results. 691 00:29:39,290 --> 00:29:41,060 This is what's fun about the Raven's test, the 692 00:29:41,060 --> 00:29:41,630 item you just saw. 693 00:29:41,630 --> 00:29:43,950 Which is they sort of looked at lots of other tests, so 694 00:29:43,950 --> 00:29:47,710 specifically spatial tests, specifically verbal tests, 695 00:29:47,710 --> 00:29:49,720 specifically math tests. 696 00:29:49,720 --> 00:29:53,530 And they said if we have to give you one test only, one 697 00:29:53,530 --> 00:29:57,400 test only, what test would best predict your performance 698 00:29:57,400 --> 00:29:59,410 on all the other tests? 699 00:29:59,410 --> 00:30:03,130 And the answer is Raven's or IQ tests like that. 700 00:30:03,130 --> 00:30:05,500 So of course if I give you a math test, that better 701 00:30:05,500 --> 00:30:06,810 predicts your math performance. 702 00:30:06,810 --> 00:30:08,760 If I give you a verbal test, that better predicts your 703 00:30:08,760 --> 00:30:09,680 verbal performance. 704 00:30:09,680 --> 00:30:11,890 If I gave you a spatial test, that better predicts your 705 00:30:11,890 --> 00:30:13,520 special performance. 706 00:30:13,520 --> 00:30:15,550 But if I want to give you one test that gives me the best 707 00:30:15,550 --> 00:30:18,820 prediction of your performance on other tests, it's things 708 00:30:18,820 --> 00:30:21,530 like these IQ tests that do that. 709 00:30:21,530 --> 00:30:24,380 And that's just empirical. 710 00:30:24,380 --> 00:30:26,240 That's not arguing about values or what 711 00:30:26,240 --> 00:30:27,460 intelligence is. 712 00:30:27,460 --> 00:30:29,760 A lot of people who work in this field, they don't even 713 00:30:29,760 --> 00:30:31,080 care about these arguments. 714 00:30:31,080 --> 00:30:34,370 They just say, I just want a test that predicts. 715 00:30:34,370 --> 00:30:37,020 It's your job, if you wanted to figure out why it is. 716 00:30:37,020 --> 00:30:39,330 It's the genes, environment, education, whatever. 717 00:30:39,330 --> 00:30:42,100 I just want a test that predicts. 718 00:30:42,100 --> 00:30:44,290 So from that perspective, these tests 719 00:30:44,290 --> 00:30:47,540 have a strong history. 720 00:30:47,540 --> 00:30:48,830 And what turns on in the brain when you solve 721 00:30:48,830 --> 00:30:49,700 this kind of a task. 722 00:30:49,700 --> 00:30:52,245 Well, the frontal cortex a lot. 723 00:30:52,245 --> 00:30:52,830 The parietal cortex. 724 00:30:52,830 --> 00:30:54,200 But especially, frontal cortex. 725 00:30:54,200 --> 00:30:57,280 So it goes with our idea that thinking is very much tied to 726 00:30:57,280 --> 00:30:58,990 prefrontal cortical function. 727 00:30:58,990 --> 00:31:02,440 Here's another example of a study that said, let's compare 728 00:31:02,440 --> 00:31:04,680 what happens in the brain when you have test items that are 729 00:31:04,680 --> 00:31:09,190 hard, which is the outlier one here, that require a lot of g, 730 00:31:09,190 --> 00:31:12,060 or items that are easy, that require very little g. 731 00:31:12,060 --> 00:31:14,990 Will up here in the brain, what happens when you turn on 732 00:31:14,990 --> 00:31:16,610 your g, so to speak? 733 00:31:16,610 --> 00:31:19,730 And again, the prominent areas tend to be, for both spatial 734 00:31:19,730 --> 00:31:21,365 and verbal, prefrontal cortex. 735 00:31:24,610 --> 00:31:26,350 One more. 736 00:31:26,350 --> 00:31:28,500 the n-back task, we use that a lot. 737 00:31:28,500 --> 00:31:30,520 Where your job is, letters come on. 738 00:31:30,520 --> 00:31:33,180 And in this one, one-back, you say, what do I see a letter 739 00:31:33,180 --> 00:31:35,380 that's the same letter as the one before? 740 00:31:35,380 --> 00:31:36,810 So, for example-- 741 00:31:36,810 --> 00:31:37,910 two-back, sorry. 742 00:31:37,910 --> 00:31:40,970 So you see, R, R, M, X, this is two-back, because an M 743 00:31:40,970 --> 00:31:42,210 occurred two items ago. 744 00:31:42,210 --> 00:31:43,370 Three-backs are really hard. 745 00:31:43,370 --> 00:31:44,970 Because the letters are going, boom, boom, boom, boom. 746 00:31:44,970 --> 00:31:47,490 And what's hard about it is, the letter in front of you, 747 00:31:47,490 --> 00:31:49,780 you have to say does it match the one I saw three letters 748 00:31:49,780 --> 00:31:51,910 previously, plus remember that, because it's going to be 749 00:31:51,910 --> 00:31:54,270 the target for the one that comes three after. 750 00:31:54,270 --> 00:31:55,070 It's hard. 751 00:31:55,070 --> 00:31:55,910 I can tell you it's hard. 752 00:31:55,910 --> 00:31:56,720 You can be smart. 753 00:31:56,720 --> 00:31:58,500 It's pretty hard. 754 00:31:58,500 --> 00:32:02,660 And for this task in general, the harder it gets, the more 755 00:32:02,660 --> 00:32:06,580 you turn on the dorsal-lateral prefrontal cortex. 756 00:32:06,580 --> 00:32:08,965 And so they did this test with students in Washington St. 757 00:32:08,965 --> 00:32:12,670 Louis, Louis, related it to performance on the Raven's. 758 00:32:12,670 --> 00:32:16,790 And sure enough in the brain, it's again prefrontal cortex. 759 00:32:16,790 --> 00:32:20,430 So a bunch of studies have found all these tests involve 760 00:32:20,430 --> 00:32:21,290 a fair bit of the brain. 761 00:32:21,290 --> 00:32:24,623 But they seem to really draw upon the capacities that you 762 00:32:24,623 --> 00:32:27,450 and I have in prefrontal cortex. 763 00:32:27,450 --> 00:32:30,930 And one more note, in brain imaging when we talk about 764 00:32:30,930 --> 00:32:33,100 things, sometimes it's better to have more activation and 765 00:32:33,100 --> 00:32:34,570 sometimes less activation. 766 00:32:34,570 --> 00:32:36,830 And you have to know the behavior to know that. 767 00:32:36,830 --> 00:32:39,660 So whenever you see somebody saying oh, this person, this 768 00:32:39,660 --> 00:32:41,960 group, or whatever, had more brain activity or less brain 769 00:32:41,960 --> 00:32:44,920 activity, you don't know until you know the rest of the 770 00:32:44,920 --> 00:32:47,440 behavior, whether more is good or bad. 771 00:32:47,440 --> 00:32:49,680 Sometimes when people get really good at something, they 772 00:32:49,680 --> 00:32:52,880 use less of their brain, because they can do it so 773 00:32:52,880 --> 00:32:54,240 efficiently. 774 00:32:54,240 --> 00:32:57,560 So here's an example of people with lower and higher IQ doing 775 00:32:57,560 --> 00:32:58,370 an n-back task. 776 00:32:58,370 --> 00:33:01,440 And you can see that the people with lower IQ have much 777 00:33:01,440 --> 00:33:04,460 more activation than the people with higher IQ. 778 00:33:04,460 --> 00:33:07,150 It's as if these people have to use all their brain 779 00:33:07,150 --> 00:33:08,950 resources to accomplish this. 780 00:33:08,950 --> 00:33:10,910 And these people only have to use some. 781 00:33:10,910 --> 00:33:12,160 It's as if it were that. 782 00:33:14,600 --> 00:33:18,890 So here comes one of the classic topics of 783 00:33:18,890 --> 00:33:20,140 the fate of a human. 784 00:33:20,140 --> 00:33:22,380 How much is your genes at birth and how much is the 785 00:33:22,380 --> 00:33:24,230 environment that you're in. 786 00:33:24,230 --> 00:33:26,610 And if we were really to understand that in a deep, 787 00:33:26,610 --> 00:33:29,120 deep scientific way, we would know the genes are related to 788 00:33:29,120 --> 00:33:32,630 intelligence; the experiential factors in the world, family, 789 00:33:32,630 --> 00:33:37,910 education, emotional support, and so on; how they interact. 790 00:33:37,910 --> 00:33:39,860 All those things, we know practically nothing about. 791 00:33:39,860 --> 00:33:41,230 I'll show you one tiny example. 792 00:33:41,230 --> 00:33:42,750 We know practically nothing about them in 793 00:33:42,750 --> 00:33:44,270 any depth at all. 794 00:33:44,270 --> 00:33:48,010 So we mostly end up using twin studies to make the best 795 00:33:48,010 --> 00:33:49,710 estimates we can. 796 00:33:49,710 --> 00:33:51,410 Which doesn't tell you what the factors are. 797 00:33:51,410 --> 00:33:54,710 It just tells you how much is a twin who is identical more 798 00:33:54,710 --> 00:33:56,740 or less like a twin who is fraternal. 799 00:33:56,740 --> 00:33:59,340 OK, we'll come back to that. 800 00:33:59,340 --> 00:34:01,750 But I do want to tell you sort of an exciting direction 801 00:34:01,750 --> 00:34:04,950 that's slightly getting at the genetic story of this. 802 00:34:04,950 --> 00:34:06,570 So you may know, many of you more 803 00:34:06,570 --> 00:34:08,810 than I do, about genetics. 804 00:34:08,810 --> 00:34:11,350 But single nucleotide polymorphisms are DNA 805 00:34:11,350 --> 00:34:12,800 variations. 806 00:34:12,800 --> 00:34:15,860 These occur relatively commonly. 807 00:34:15,860 --> 00:34:17,699 They're estimated to make up about 90% of 808 00:34:17,699 --> 00:34:19,260 human genetic variation. 809 00:34:19,260 --> 00:34:21,250 And they're constant from generation to generation. 810 00:34:21,250 --> 00:34:24,250 So people have studied a few of these variations among 811 00:34:24,250 --> 00:34:26,860 people and related them to performance. 812 00:34:26,860 --> 00:34:29,290 So let me remind you of something from last lecture, 813 00:34:29,290 --> 00:34:32,210 the Wisconsin Card Sorting Task. 814 00:34:32,210 --> 00:34:36,250 Where you sorted these cards mysteriously and we said that 815 00:34:36,250 --> 00:34:39,239 if you have a frontal lesion, you do poorly on this task. 816 00:34:39,239 --> 00:34:43,460 You get stuck with one kind of problem solving or habit, 817 00:34:43,460 --> 00:34:47,650 answer even when it's wrong, in a new circumstance. 818 00:34:47,650 --> 00:34:51,270 So what people have done is look at one particular gene 819 00:34:51,270 --> 00:34:56,830 that's related to this enzyme that modulates dopamine 820 00:34:56,830 --> 00:34:59,290 function in the prefrontal cortex. 821 00:34:59,290 --> 00:35:02,205 So it's a risk factor for schizophrenia. 822 00:35:02,205 --> 00:35:05,710 It metabolizes dopamine in prefrontal cortex. 823 00:35:05,710 --> 00:35:11,350 We vary with which version of this gene we have. 824 00:35:11,350 --> 00:35:13,570 And here's the performance on the card sorting task. 825 00:35:13,570 --> 00:35:14,730 And let me pick these. 826 00:35:14,730 --> 00:35:16,060 These are healthy people. 827 00:35:16,060 --> 00:35:19,550 If you have this version of the gene or this pairing or 828 00:35:19,550 --> 00:35:23,240 this pairing, your card sorting task is going up. 829 00:35:23,240 --> 00:35:25,620 So this is kind of amazing that we're close to that, 830 00:35:25,620 --> 00:35:26,860 where a single gene is varying. 831 00:35:26,860 --> 00:35:28,110 Now, the score doesn't go up a lot. 832 00:35:28,110 --> 00:35:29,960 It accounts a small percent of the variance. 833 00:35:29,960 --> 00:35:33,890 But it's one gene having an identifiable correlation with 834 00:35:33,890 --> 00:35:37,580 performance on a demanding task. 835 00:35:37,580 --> 00:35:39,160 And you can do this n-back kind of task 836 00:35:39,160 --> 00:35:40,450 we just talked about. 837 00:35:40,450 --> 00:35:42,470 And then you can look in the brain as people are performing 838 00:35:42,470 --> 00:35:46,360 this, divided by which version of this gene they have. 839 00:35:46,360 --> 00:35:52,060 And what you get is more activation in the people with 840 00:35:52,060 --> 00:35:56,750 this complement, than this complement. 841 00:35:56,750 --> 00:35:58,690 Sort of consistent with the idea they're working harder. 842 00:35:58,690 --> 00:36:01,200 There's the same group of people who are performing less 843 00:36:01,200 --> 00:36:02,710 well in the card sorting task. 844 00:36:02,710 --> 00:36:05,210 So there are some genes that have been identified that are 845 00:36:05,210 --> 00:36:07,930 associated with what we may call broadly, intelligence. 846 00:36:07,930 --> 00:36:11,030 But that one gene only accounts for a tiny bit of the 847 00:36:11,030 --> 00:36:13,430 overall score on these kinds of things. 848 00:36:13,430 --> 00:36:15,840 And we don't know much more about it than that. 849 00:36:15,840 --> 00:36:18,170 So how do people even begin to think 850 00:36:18,170 --> 00:36:19,910 about nature and nurture? 851 00:36:19,910 --> 00:36:21,520 And I like to think about this in two ways. 852 00:36:21,520 --> 00:36:23,830 One way is narrowly IQ tests, because there's been so much 853 00:36:23,830 --> 00:36:24,840 work in that area. 854 00:36:24,840 --> 00:36:27,340 But it's the deep question of how do we get 855 00:36:27,340 --> 00:36:29,260 to be who we are? 856 00:36:29,260 --> 00:36:31,900 So again, they mostly look at twin studies, so-called 857 00:36:31,900 --> 00:36:35,100 behavioral genetics, and estimated heritability, how 858 00:36:35,100 --> 00:36:38,302 much of variation is due to genetics. 859 00:36:38,302 --> 00:36:39,810 And I'll come back to this height thing. 860 00:36:39,810 --> 00:36:42,300 But to give you a sense, height is thought to be 90% 861 00:36:42,300 --> 00:36:44,480 inheritable in the US. 862 00:36:44,480 --> 00:36:46,970 Tall parents on average will average will have taller kids. 863 00:36:46,970 --> 00:36:49,030 Less tall parents, less tall kids. 864 00:36:49,030 --> 00:36:51,860 And in twin studies, they contrast monozygotic twins, 865 00:36:51,860 --> 00:36:54,210 twins that are identical or have the same genes, with 866 00:36:54,210 --> 00:36:58,960 dizygotic ones, who share some genes, but not nearly as many. 867 00:36:58,960 --> 00:37:01,250 Of course, they share the same environment a lot. 868 00:37:01,250 --> 00:37:04,000 Have you guys seen the two twins talking to each other 869 00:37:04,000 --> 00:37:06,220 video on YouTube? 870 00:37:06,220 --> 00:37:07,530 If you haven't seen it, it's kind of fun. 871 00:37:07,530 --> 00:37:09,270 The two twins are babbling. 872 00:37:09,270 --> 00:37:11,930 But they're so demonstrative, it's as if they were talking 873 00:37:11,930 --> 00:37:12,810 to each other in babble. 874 00:37:12,810 --> 00:37:13,913 It's kind of fun, if you haven't see it. 875 00:37:13,913 --> 00:37:15,163 It's very cute. 876 00:37:18,390 --> 00:37:20,850 Here is it again. 877 00:37:20,850 --> 00:37:25,390 The fraternal twins and here's the identical twins, before 878 00:37:25,390 --> 00:37:27,160 they're born. 879 00:37:27,160 --> 00:37:30,220 This has been studied a fair bit. 880 00:37:30,220 --> 00:37:34,690 Here's the correlations between IQ scores and people 881 00:37:34,690 --> 00:37:35,510 of varying relations. 882 00:37:35,510 --> 00:37:37,340 So let's work down that list. 883 00:37:37,340 --> 00:37:39,160 Unrelated persons, reared together. 884 00:37:39,160 --> 00:37:41,350 So perhaps an adopted person and his or 885 00:37:41,350 --> 00:37:42,750 her sibling or something. 886 00:37:42,750 --> 00:37:45,730 They're correlated at about what, 0.2. 887 00:37:45,730 --> 00:37:48,030 Foster parent and child, it goes up a little bit. 888 00:37:48,030 --> 00:37:49,830 Parent and child living together, so that's a 889 00:37:49,830 --> 00:37:52,170 biological parent and child living together, that goes up 890 00:37:52,170 --> 00:37:53,010 a fair bit. 891 00:37:53,010 --> 00:37:55,110 Brother and sister reared apart, back down. 892 00:37:55,110 --> 00:37:56,400 Brother and sister reared together. 893 00:37:56,400 --> 00:38:00,940 So you could look at this as kind of shared genes. 894 00:38:00,940 --> 00:38:02,920 And this might be something like environment. 895 00:38:02,920 --> 00:38:03,510 Does make sense? 896 00:38:03,510 --> 00:38:04,950 Intuitively. 897 00:38:04,950 --> 00:38:07,640 That's assuming there's no interaction between genes and 898 00:38:07,640 --> 00:38:09,760 the environment, which we know must happen. 899 00:38:09,760 --> 00:38:12,470 So when I do this I'm treating them as if they were additive 900 00:38:12,470 --> 00:38:13,990 and independent. 901 00:38:13,990 --> 00:38:16,260 Everything we know about genes and the environment are 902 00:38:16,260 --> 00:38:18,010 tremendously interactive. 903 00:38:18,010 --> 00:38:19,760 We just don't have insight into that in any 904 00:38:19,760 --> 00:38:22,850 deep way, in humans. 905 00:38:22,850 --> 00:38:24,220 Here's the really stunning one. 906 00:38:24,220 --> 00:38:28,430 Identical twins reared apart, 70.7 correlation. 907 00:38:28,430 --> 00:38:30,640 Identical twins reared apart. 908 00:38:30,640 --> 00:38:33,570 That suggests a huge influence of genes. 909 00:38:36,170 --> 00:38:39,750 Identical twins reared together, 90.9. 910 00:38:39,750 --> 00:38:41,830 So this is the finding that stunned people. 911 00:38:41,830 --> 00:38:45,020 So look at identical twins reared apart. 912 00:38:45,020 --> 00:38:48,670 They're much more like each other than a brother and 913 00:38:48,670 --> 00:38:51,490 sister reared together, who share all the same environment 914 00:38:51,490 --> 00:38:54,410 of education, parental support, and other things. 915 00:38:54,410 --> 00:38:57,070 So I'm going to come back to this. 916 00:38:57,070 --> 00:39:00,190 But as best people can estimate, and these might be 917 00:39:00,190 --> 00:39:02,540 radically replaced as we deepen our understanding of 918 00:39:02,540 --> 00:39:05,460 the actual genes and the actual environmental factors, 919 00:39:05,460 --> 00:39:07,370 but people are estimating it's about half 920 00:39:07,370 --> 00:39:10,150 and half for IQ tests. 921 00:39:10,150 --> 00:39:13,210 And we discussed the bit of arbitrariness in that. 922 00:39:13,210 --> 00:39:14,600 So about half and half. 923 00:39:14,600 --> 00:39:16,370 Let me show you a couple of environmental influences that 924 00:39:16,370 --> 00:39:17,960 have been identified. 925 00:39:17,960 --> 00:39:23,160 And the first two, one suspects has to do on average 926 00:39:23,160 --> 00:39:25,470 with something about the healthiness of the environment 927 00:39:25,470 --> 00:39:26,920 the child was born into. 928 00:39:26,920 --> 00:39:31,830 The third one is kind of fun just to talk about because you 929 00:39:31,830 --> 00:39:34,950 may wonder if you have a sibling or no sibling, what 930 00:39:34,950 --> 00:39:37,120 does it mean that you were first born, or second born, or 931 00:39:37,120 --> 00:39:38,960 third born, at least statistically. 932 00:39:38,960 --> 00:39:40,300 So let's do the first two. 933 00:39:40,300 --> 00:39:44,570 Here's breast feeding, 3,000 people were followed from 934 00:39:44,570 --> 00:39:46,720 birth to young adulthood, who had breast feeding, for at 935 00:39:46,720 --> 00:39:48,670 least six months, correlated with a five to 936 00:39:48,670 --> 00:39:50,590 seven point IQ gain. 937 00:39:50,590 --> 00:39:53,820 So we said, 15 points really seems to mean something in 938 00:39:53,820 --> 00:39:54,740 educational outcome. 939 00:39:54,740 --> 00:39:56,610 So 5 to 7 is half of that. 940 00:39:56,610 --> 00:39:59,560 So that's something. 941 00:39:59,560 --> 00:40:00,580 So let's talk about this for a minute. 942 00:40:00,580 --> 00:40:04,890 You could say, and I can tell you as a parent who fairly 943 00:40:04,890 --> 00:40:09,130 recently had children, all the mothers in the US that I know 944 00:40:09,130 --> 00:40:10,480 were going like, I've got to breast feed and 945 00:40:10,480 --> 00:40:13,420 get my kid to MIT. 946 00:40:13,420 --> 00:40:15,250 Two more months of breast feeding and this kid could go 947 00:40:15,250 --> 00:40:18,200 all the way to tenured faculty. 948 00:40:18,200 --> 00:40:21,380 I can tell you there's a lot of pressure on mothers, if you 949 00:40:21,380 --> 00:40:22,600 don't know this. 950 00:40:22,600 --> 00:40:23,900 Not my mother. 951 00:40:23,900 --> 00:40:27,110 But now mothers hear, do this for your kid, do this for your 952 00:40:27,110 --> 00:40:30,570 kid, do this for your kid, because of results like these. 953 00:40:30,570 --> 00:40:33,810 So one possibility is there's something in breast milk. 954 00:40:33,810 --> 00:40:35,000 That would be the direct mechanism 955 00:40:35,000 --> 00:40:36,620 that's making kids smarter. 956 00:40:36,620 --> 00:40:38,580 Give me another possibility that has nothing to do with 957 00:40:38,580 --> 00:40:39,220 the breast milk? 958 00:40:39,220 --> 00:40:39,580 Yeah? 959 00:40:39,580 --> 00:40:42,940 AUDIENCE: Maybe mothers who breast feed, also tend to be 960 00:40:42,940 --> 00:40:44,380 mothers who are more nurturing to their children. 961 00:40:44,380 --> 00:40:45,640 PROFESSOR: It could be more nurturing to 962 00:40:45,640 --> 00:40:46,780 children in many ways. 963 00:40:46,780 --> 00:40:50,050 They could be mothers who can stay home and spend some time 964 00:40:50,050 --> 00:40:52,480 with the children versus being under very pressured economic 965 00:40:52,480 --> 00:40:54,910 circumstances that prohibit that. 966 00:40:54,910 --> 00:40:56,420 It could be a lot of things. 967 00:40:56,420 --> 00:40:57,300 Does that make sense? 968 00:40:57,300 --> 00:40:57,950 We don't know. 969 00:40:57,950 --> 00:41:00,720 Nobody has shown yet that it is the breast milk that goes 970 00:41:00,720 --> 00:41:03,870 into your brain and pushes up your brain, in any sense. 971 00:41:03,870 --> 00:41:05,330 It's just a correlation. 972 00:41:05,330 --> 00:41:08,750 And of course, if you're a parent, I'll do the breast 973 00:41:08,750 --> 00:41:11,180 feeding and let the scientists figure it out in the future. 974 00:41:11,180 --> 00:41:12,240 Here's another one. 975 00:41:12,240 --> 00:41:14,200 There's the birth weight. 976 00:41:14,200 --> 00:41:15,440 So again, you could say the same thing. 977 00:41:15,440 --> 00:41:19,160 I mean certainly having very low birth weight is a big risk 978 00:41:19,160 --> 00:41:20,680 factor for lots of things. 979 00:41:20,680 --> 00:41:24,240 But birth weight again goes with many factors in the 980 00:41:24,240 --> 00:41:26,230 environment that are supportive for a healthy 981 00:41:26,230 --> 00:41:28,070 pregnancy versus not. 982 00:41:28,070 --> 00:41:29,510 So it doesn't mean that it's the birth weight. 983 00:41:29,510 --> 00:41:31,640 It could be all the other things that were in the 984 00:41:31,640 --> 00:41:35,280 environment during the pregnancy, at birth, and 985 00:41:35,280 --> 00:41:38,580 continue, on average, in the environment of that child, 986 00:41:38,580 --> 00:41:40,740 throughout their childhood and young education. 987 00:41:40,740 --> 00:41:41,840 Does that make sense? 988 00:41:41,840 --> 00:41:44,280 If they're born in a very unsupportive medical 989 00:41:44,280 --> 00:41:47,370 environment, they might have a low birth weight. 990 00:41:47,370 --> 00:41:49,380 And unless their parents win the lottery or something, 991 00:41:49,380 --> 00:41:51,840 they're likely to be in a difficult environment for all 992 00:41:51,840 --> 00:41:55,500 their educational years to come. 993 00:41:55,500 --> 00:41:58,320 So people have tried to make clear, because it's so easy to 994 00:41:58,320 --> 00:42:00,430 get into sort of little mental traps on genes versus 995 00:42:00,430 --> 00:42:02,330 environment, how genetic diversity affects 996 00:42:02,330 --> 00:42:03,670 heritability. 997 00:42:03,670 --> 00:42:05,000 So there's a couple different ways to do it. 998 00:42:05,000 --> 00:42:05,890 Let's do this one. 999 00:42:05,890 --> 00:42:09,160 So imagine you had cloned tomato plants. 1000 00:42:09,160 --> 00:42:12,520 That means they all have the exact same genes in this 1001 00:42:12,520 --> 00:42:13,790 hypothetical example. 1002 00:42:13,790 --> 00:42:17,020 But somebody has poor soil, somebody has good soil. 1003 00:42:17,020 --> 00:42:19,130 Well, you'll get big differences. 1004 00:42:19,130 --> 00:42:21,470 And the heritability will be zero. 1005 00:42:21,470 --> 00:42:23,880 Environment can have huge influences. 1006 00:42:23,880 --> 00:42:28,160 But if you have genetically diverse plants, then you're 1007 00:42:28,160 --> 00:42:29,210 going to have an interaction. 1008 00:42:29,210 --> 00:42:32,200 So some plants will do OK, even in poor soil. 1009 00:42:32,200 --> 00:42:35,110 Some plants will do most spectacularly in good soil and 1010 00:42:35,110 --> 00:42:36,090 less spectacularly alike. 1011 00:42:36,090 --> 00:42:38,120 Environment by genes' interactions. 1012 00:42:38,120 --> 00:42:39,660 And you can see this in so many different ways. 1013 00:42:39,660 --> 00:42:40,430 So here's one example. 1014 00:42:40,430 --> 00:42:43,730 So we said height is 90% heritable within a society. 1015 00:42:43,730 --> 00:42:47,440 But Japanese men in the US, or people with Japanese extract, 1016 00:42:47,440 --> 00:42:50,600 are three inches taller than people in Japan. 1017 00:42:50,600 --> 00:42:53,630 So they still have whatever Japanese genes are. 1018 00:42:53,630 --> 00:42:54,470 They have Japanese genes. 1019 00:42:54,470 --> 00:42:57,240 But they're in the US getting the US diet of McDonald's. 1020 00:42:57,240 --> 00:43:00,000 And it's pushing them up three inches. 1021 00:43:03,450 --> 00:43:04,660 Height is heritable. 1022 00:43:04,660 --> 00:43:06,980 But environment is a big part of the story. 1023 00:43:06,980 --> 00:43:09,370 So it's just both. 1024 00:43:09,370 --> 00:43:12,560 Now, here's a fun study. 1025 00:43:12,560 --> 00:43:16,930 And a reason that if you're a younger sibling and you 1026 00:43:16,930 --> 00:43:19,420 desperately want two IQ points, you might knock off 1027 00:43:19,420 --> 00:43:20,570 your older sibling. 1028 00:43:20,570 --> 00:43:21,700 I don't recommend this. 1029 00:43:21,700 --> 00:43:23,310 This is tongue-in-cheek. 1030 00:43:23,310 --> 00:43:25,580 But it's kind of fun study, just thinking about birth 1031 00:43:25,580 --> 00:43:27,160 order more in a fun way. 1032 00:43:27,160 --> 00:43:28,520 Well, look at the whole thing, we're talking 1033 00:43:28,520 --> 00:43:29,950 about from 99 to 104. 1034 00:43:29,950 --> 00:43:32,520 So it's five points we're talking there. 1035 00:43:32,520 --> 00:43:35,410 But in some countries, they sort of test everybody going 1036 00:43:35,410 --> 00:43:37,180 into the military. 1037 00:43:37,180 --> 00:43:39,730 And I think this was done in Denmark. 1038 00:43:39,730 --> 00:43:40,980 And what they said is. 1039 00:43:43,900 --> 00:43:45,510 These are all children. 1040 00:43:45,510 --> 00:43:46,910 These are the IQ scores. 1041 00:43:46,910 --> 00:43:50,130 And these are the IQ scores that you would have. 1042 00:43:50,130 --> 00:43:52,040 But what happens if your older sibling has 1043 00:43:52,040 --> 00:43:54,246 passed away, sadly. 1044 00:43:54,246 --> 00:43:56,250 You get those points. 1045 00:43:56,250 --> 00:43:58,770 And here's a person who has an older sibling. 1046 00:43:58,770 --> 00:44:00,010 And the older sibling passed away. 1047 00:44:00,010 --> 00:44:01,460 And they moved up those points. 1048 00:44:01,460 --> 00:44:03,970 That is, if you're a younger sibling, you have a few lower 1049 00:44:03,970 --> 00:44:07,230 IQ points, on average. 1050 00:44:07,230 --> 00:44:09,410 But kind of strikingly, if your older sibling passes 1051 00:44:09,410 --> 00:44:13,110 away, sadly; you seem to get those IQ points as you move up 1052 00:44:13,110 --> 00:44:14,580 the birth order. 1053 00:44:14,580 --> 00:44:15,840 Yeah? 1054 00:44:15,840 --> 00:44:17,620 AUDIENCE: Is this if they pass away before birth, or --? 1055 00:44:17,620 --> 00:44:18,280 PROFESSOR: Yes. 1056 00:44:18,280 --> 00:44:19,700 Yeah, when they're young. 1057 00:44:19,700 --> 00:44:20,880 It's too late. 1058 00:44:20,880 --> 00:44:21,520 Sorry. 1059 00:44:21,520 --> 00:44:25,550 For all you in here, too late. 1060 00:44:25,550 --> 00:44:27,420 It's only a couple points also. 1061 00:44:27,420 --> 00:44:29,060 But this got into Science, because people are always 1062 00:44:29,060 --> 00:44:30,070 wondering about-- 1063 00:44:30,070 --> 00:44:32,490 there's been a huge curiosity about birth order 1064 00:44:32,490 --> 00:44:33,740 consequences. 1065 00:44:41,670 --> 00:44:44,200 But let's talk a little bit about birth order again. 1066 00:44:44,200 --> 00:44:46,340 Because there's a second really interesting point. 1067 00:44:46,340 --> 00:44:48,720 So here's Raven's score. 1068 00:44:48,720 --> 00:44:52,440 And here is if you're a lone child, the second of two 1069 00:44:52,440 --> 00:44:55,590 children, the third of three, the fourth of four, the eighth 1070 00:44:55,590 --> 00:44:56,860 of eight, to ninth of nine. 1071 00:44:56,860 --> 00:44:58,300 You can see the scores keep going down. 1072 00:44:58,300 --> 00:45:00,920 It's not dramatic, but larger families. 1073 00:45:00,920 --> 00:45:04,350 And you can have a million ideas about why that would be. 1074 00:45:04,350 --> 00:45:06,770 About why it is the larger your family and the further 1075 00:45:06,770 --> 00:45:09,810 you're down on the list, you lose a few IQ points for every 1076 00:45:09,810 --> 00:45:11,560 sibling who's older. 1077 00:45:11,560 --> 00:45:17,190 So here's one idea from Robert Zajonc, who's a very creative 1078 00:45:17,190 --> 00:45:17,820 psychologist. 1079 00:45:17,820 --> 00:45:18,960 We're not sure that it's right. 1080 00:45:18,960 --> 00:45:21,390 But I think it's really fun to think about. 1081 00:45:21,390 --> 00:45:22,550 So here is this idea. 1082 00:45:22,550 --> 00:45:25,370 He said, I'm going to make up an idea, which is this. 1083 00:45:25,370 --> 00:45:28,216 The first born, maybe he is exposed only to adults. 1084 00:45:28,216 --> 00:45:31,980 The adults are talking to them about the views of the day and 1085 00:45:31,980 --> 00:45:32,570 all kinds of things. 1086 00:45:32,570 --> 00:45:35,330 The second born has two adults, let's say 1087 00:45:35,330 --> 00:45:36,670 in a typical family. 1088 00:45:36,670 --> 00:45:39,650 But also has an older sibling. 1089 00:45:39,650 --> 00:45:41,600 So the intellectual environment will be the 1090 00:45:41,600 --> 00:45:45,440 average of two adults and a little child. 1091 00:45:45,440 --> 00:45:46,430 The next one, and so on. 1092 00:45:46,430 --> 00:45:48,160 So he said, you can do a kind of a formula, 1093 00:45:48,160 --> 00:45:49,330 which is like this. 1094 00:45:49,330 --> 00:45:52,760 Pretend the two parents are each 30 and you're born. 1095 00:45:52,760 --> 00:45:55,050 We'll call your family intellectual stimulating 1096 00:45:55,050 --> 00:45:56,110 environment, 30. 1097 00:45:56,110 --> 00:45:57,890 Because we'll add up the ages and divide by the number of 1098 00:45:57,890 --> 00:45:59,210 people in the family. 1099 00:45:59,210 --> 00:46:00,670 Does that make sense? 1100 00:46:00,670 --> 00:46:04,260 This is not meant to be a real formula, just 1101 00:46:04,260 --> 00:46:06,470 a conceptual plan. 1102 00:46:06,470 --> 00:46:08,570 And then he said, now you have the two parents and you have a 1103 00:46:08,570 --> 00:46:11,550 four-year-old sibling, because you're the second born. 1104 00:46:11,550 --> 00:46:12,980 So now there's four of you. 1105 00:46:12,980 --> 00:46:13,840 We divide by 4. 1106 00:46:13,840 --> 00:46:15,930 And we'll say the average intellectual thing in the 1107 00:46:15,930 --> 00:46:17,770 family is 16. 1108 00:46:17,770 --> 00:46:19,950 By the time the next child comes along, a seven-year-old 1109 00:46:19,950 --> 00:46:22,810 sibling, three-year-old, divide by five, and the 1110 00:46:22,810 --> 00:46:25,190 average intellectual environment is 14. 1111 00:46:25,190 --> 00:46:27,060 Here's the idea. 1112 00:46:27,060 --> 00:46:30,730 On average, it's better for a child to have lots of 1113 00:46:30,730 --> 00:46:33,210 interaction with a parent, that with a little kid. 1114 00:46:33,210 --> 00:46:35,190 Because a parent will stimulate you more than a 1115 00:46:35,190 --> 00:46:38,460 little kid, although a little sibling might be a lot of fun. 1116 00:46:38,460 --> 00:46:42,430 But purely IQ land, two parents talking to you about 1117 00:46:42,430 --> 00:46:47,150 stuff, is a more educational environment than two parents 1118 00:46:47,150 --> 00:46:51,130 plus a sibling who is two years older than you. 1119 00:46:51,130 --> 00:46:52,560 Because the two-year-old can't help. 1120 00:46:52,560 --> 00:46:55,360 No matter how smart he or she is, they can't talk with you 1121 00:46:55,360 --> 00:46:56,270 like an adult. 1122 00:46:56,270 --> 00:46:58,680 This is the thought. 1123 00:46:58,680 --> 00:47:02,460 And now, here's the really fun observation. 1124 00:47:02,460 --> 00:47:04,860 And again, we don't really know if this is exactly right. 1125 00:47:04,860 --> 00:47:08,990 But every year, if you're around issues of education, 1126 00:47:08,990 --> 00:47:11,380 there's test scores that different states have. 1127 00:47:11,380 --> 00:47:13,480 And the test scores go up. 1128 00:47:13,480 --> 00:47:17,690 And you have taken high-tests tests right, in high schools 1129 00:47:17,690 --> 00:47:19,620 and grade schools and stuff. 1130 00:47:19,620 --> 00:47:23,140 If the test scores goes up, everybody goes, oh, reelect us 1131 00:47:23,140 --> 00:47:24,860 because we're awesome administration and our test 1132 00:47:24,860 --> 00:47:25,530 scores are going up. 1133 00:47:25,530 --> 00:47:26,830 We're doing everything right. 1134 00:47:26,830 --> 00:47:30,020 If the test scores go down, they go oh, throw the bums out 1135 00:47:30,020 --> 00:47:30,950 of the administration. 1136 00:47:30,950 --> 00:47:33,410 Their kids are watching too much MTV, turn off that 1137 00:47:33,410 --> 00:47:34,710 computer, and so on. 1138 00:47:34,710 --> 00:47:35,910 Everybody gets the test scores. 1139 00:47:35,910 --> 00:47:39,100 And they figure out who's good and who's bad, parents, 1140 00:47:39,100 --> 00:47:42,200 teachers, school systems, politicians, whatever. 1141 00:47:42,200 --> 00:47:44,030 Zajonc says, and this is kind of an interesting thought. 1142 00:47:44,030 --> 00:47:48,750 He says no, he can predict whether scores will go up or 1143 00:47:48,750 --> 00:47:54,480 down simply by on average in a given year, whether there are 1144 00:47:54,480 --> 00:47:56,950 more first borns, or second borns, or third borns. 1145 00:47:56,950 --> 00:47:59,460 That if he just takes that population average of every 1146 00:47:59,460 --> 00:48:04,260 kid, the moment they're born, he can predict years later 1147 00:48:04,260 --> 00:48:05,800 where the scores go. 1148 00:48:05,800 --> 00:48:08,970 And so here's the scores in Iowa. 1149 00:48:08,970 --> 00:48:10,860 Of the actual scores, they're going up and down. 1150 00:48:10,860 --> 00:48:12,410 So you can imagine, scores are going down. 1151 00:48:12,410 --> 00:48:15,810 Everybody's really upset about kids who don't study, and 1152 00:48:15,810 --> 00:48:18,350 teachers who don't teach, and parents who don't parent. 1153 00:48:18,350 --> 00:48:19,200 Scores are going up. 1154 00:48:19,200 --> 00:48:20,920 And the kids are awesome, the teachers are awesome, the 1155 00:48:20,920 --> 00:48:21,920 parents are awesome. 1156 00:48:21,920 --> 00:48:23,670 Because that's who gets the credit. 1157 00:48:23,670 --> 00:48:25,990 And he's saying, uh-uh. 1158 00:48:25,990 --> 00:48:32,370 This is my prediction here, based simply on for a given 1159 00:48:32,370 --> 00:48:35,220 birth year, the average number of older 1160 00:48:35,220 --> 00:48:37,800 children in your family. 1161 00:48:37,800 --> 00:48:38,550 That's it. 1162 00:48:38,550 --> 00:48:39,720 And look how well that tracks. 1163 00:48:39,720 --> 00:48:41,460 It's unbelievable. 1164 00:48:41,460 --> 00:48:44,680 So it just makes you rethink that so often when we get 1165 00:48:44,680 --> 00:48:49,310 information about society of what's going on, this may be 1166 00:48:49,310 --> 00:48:50,440 right or wrong. 1167 00:48:50,440 --> 00:48:52,460 But we don't really know what's going on. 1168 00:48:52,460 --> 00:48:55,190 There's all kinds of huge things out there in the world 1169 00:48:55,190 --> 00:49:00,220 that aren't the easiest things to blame or give credit to. 1170 00:49:00,220 --> 00:49:03,160 So they're relatively small differences, but they seem to 1171 00:49:03,160 --> 00:49:06,090 track interestingly in the number of siblings you have 1172 00:49:06,090 --> 00:49:08,842 who are older than you. 1173 00:49:08,842 --> 00:49:11,490 And at the same time, this idea of 1174 00:49:11,490 --> 00:49:13,650 parental exposure to language. 1175 00:49:13,650 --> 00:49:17,980 There's this widely cited study from Hart and Risley. 1176 00:49:17,980 --> 00:49:21,890 So they recorded for each month, for 2 and 1/2 years, a 1177 00:49:21,890 --> 00:49:25,240 heroic recording, one full hour of every word spoken at 1178 00:49:25,240 --> 00:49:28,550 home between parents and children in just 42 families. 1179 00:49:28,550 --> 00:49:32,220 But they categorized them as high, medium, or low 1180 00:49:32,220 --> 00:49:33,130 socioeconomically. 1181 00:49:33,130 --> 00:49:34,830 So in terms of income and education. 1182 00:49:34,830 --> 00:49:35,570 OK. 1183 00:49:35,570 --> 00:49:37,730 And they're recording lots and lots of 1184 00:49:37,730 --> 00:49:39,420 conversations verbatim. 1185 00:49:39,420 --> 00:49:42,870 And they code and analyzed every utterance in 1,300 1186 00:49:42,870 --> 00:49:46,140 transcripts of 30,000 pages. 1187 00:49:46,140 --> 00:49:48,680 The reason why this is not done a lot, it's not very 1188 00:49:48,680 --> 00:49:50,350 glamorous work to do. 1189 00:49:50,350 --> 00:49:51,440 You can imagine sitting down there. 1190 00:49:51,440 --> 00:49:55,010 But they're recording lots of conversations at home in 1191 00:49:55,010 --> 00:49:58,880 families who are better off, medium off, or poor. 1192 00:49:58,880 --> 00:50:02,280 And they're looking at what is the conversation like, for an 1193 00:50:02,280 --> 00:50:03,640 hour a day. 1194 00:50:03,640 --> 00:50:05,120 And here's what they find. 1195 00:50:05,120 --> 00:50:07,460 That variation in children's IQ and language abilities 1196 00:50:07,460 --> 00:50:09,020 related to the amount that the parents 1197 00:50:09,020 --> 00:50:10,780 speak to their children. 1198 00:50:10,780 --> 00:50:14,000 And that the academic success by age 8 or 9 or 10 is related 1199 00:50:14,000 --> 00:50:16,860 a lot to speech at 0 to 3. 1200 00:50:16,860 --> 00:50:19,080 Now again, you think causally. 1201 00:50:19,080 --> 00:50:21,780 Because you think, parents are talking to you at 0 and 3. 1202 00:50:21,780 --> 00:50:22,840 And 9 and 10, you're doing 1203 00:50:22,840 --> 00:50:25,330 differential equations, causally. 1204 00:50:25,330 --> 00:50:25,630 No. 1205 00:50:25,630 --> 00:50:28,030 The parents that are talking to you a lot, 0 to 3, are 1206 00:50:28,030 --> 00:50:30,870 talking to you at 4, 5, and 6 a lot, most of the time. 1207 00:50:30,870 --> 00:50:33,420 So if these things are not like, you get an injection, 1208 00:50:33,420 --> 00:50:34,740 you're done. 1209 00:50:34,740 --> 00:50:36,960 Many of the factors that we can measure, continue on 1210 00:50:36,960 --> 00:50:40,570 average, for most people in their environment. 1211 00:50:40,570 --> 00:50:43,960 But it's very impressive how the environment altogether 1212 00:50:43,960 --> 00:50:44,990 influences things. 1213 00:50:44,990 --> 00:50:47,880 By age 3, the cumulative vocabulary is 1,100 words in a 1214 00:50:47,880 --> 00:50:51,480 professional family as a child, 750 in a working class, 1215 00:50:51,480 --> 00:50:53,400 and 500 in a welfare family. 1216 00:50:53,400 --> 00:50:56,870 And welfare families, 600 words per hour, working class 1217 00:50:56,870 --> 00:50:59,800 750, professionals 2,153. 1218 00:50:59,800 --> 00:51:03,580 By age 3, the vocabulary used by children in the high SES 1219 00:51:03,580 --> 00:51:08,270 homes, is larger than the vocabulary used by parents in 1220 00:51:08,270 --> 00:51:09,080 the low SES. 1221 00:51:09,080 --> 00:51:11,210 By age 3, larger vocabulary. 1222 00:51:11,210 --> 00:51:15,600 This is just telling you the incredible cumulative power of 1223 00:51:15,600 --> 00:51:18,120 strong environmental influences. 1224 00:51:18,120 --> 00:51:20,160 Because it's unbelievably multiplicative. 1225 00:51:20,160 --> 00:51:21,635 It's every day, all day long. 1226 00:51:21,635 --> 00:51:24,170 And if you're in an environment that's supportive 1227 00:51:24,170 --> 00:51:26,420 or an environment that's not. 1228 00:51:26,420 --> 00:51:27,630 It's not one shot. 1229 00:51:27,630 --> 00:51:31,840 It's every day, multiply, multiply, multiply. 1230 00:51:31,840 --> 00:51:33,940 300 words more per hour for professional, 1231 00:51:33,940 --> 00:51:34,770 than the welfare family. 1232 00:51:34,770 --> 00:51:35,460 Extrapolate to a year. 1233 00:51:35,460 --> 00:51:37,870 A child in a professional family hears 11 million words, 1234 00:51:37,870 --> 00:51:40,250 versus 3 million in a welfare family. 1235 00:51:40,250 --> 00:51:43,110 And strong correlation with IQ scores by age 9. 1236 00:51:43,110 --> 00:51:46,360 So very huge differences in what children are 1237 00:51:46,360 --> 00:51:47,480 exposed to at home. 1238 00:51:47,480 --> 00:51:49,610 And they correlate highly with these IQ things. 1239 00:51:52,210 --> 00:51:56,440 So the literature is that on average, on average, the IQ 1240 00:51:56,440 --> 00:51:58,830 scores that children have around 9 or 10, correlate 1241 00:51:58,830 --> 00:52:00,160 pretty well with ones they'll have for the 1242 00:52:00,160 --> 00:52:01,750 rest of their lives. 1243 00:52:01,750 --> 00:52:04,560 Before that, it extremely jumps around. 1244 00:52:04,560 --> 00:52:06,090 We don't know why. 1245 00:52:06,090 --> 00:52:07,720 But that's they're finding. 1246 00:52:07,720 --> 00:52:11,360 By the time in 9 or 10, whatever you have, on average 1247 00:52:11,360 --> 00:52:12,640 tends to hang in there. 1248 00:52:12,640 --> 00:52:15,950 If you're 100 at 10, you'll tend to be 100 at 20. 1249 00:52:15,950 --> 00:52:18,090 If you're 120 at 10, you'll tend to be 120 at 20. 1250 00:52:18,090 --> 00:52:20,860 Does that make sense? 1251 00:52:20,860 --> 00:52:22,620 So there's been a lot of interest in evidence about 1252 00:52:22,620 --> 00:52:26,850 whether you can change your IQ as an adult. 1253 00:52:26,850 --> 00:52:29,230 So here's one study that got a lot of attention, because it 1254 00:52:29,230 --> 00:52:31,130 was kind of interesting in that way. 1255 00:52:31,130 --> 00:52:34,530 So they did a complicated task like this. 1256 00:52:34,530 --> 00:52:35,750 This was an n-back task. 1257 00:52:35,750 --> 00:52:38,560 Simultaneously you hear letters and you see little 1258 00:52:38,560 --> 00:52:40,220 spatial locations like this. 1259 00:52:40,220 --> 00:52:44,040 And every time something matched two items ago, you 1260 00:52:44,040 --> 00:52:44,730 would push a button. 1261 00:52:44,730 --> 00:52:45,920 So you're hearing them at the same time. 1262 00:52:45,920 --> 00:52:47,170 And if you hear a letter that was two letters 1263 00:52:47,170 --> 00:52:47,920 ago, you push a button. 1264 00:52:47,920 --> 00:52:49,480 Or same spatial location, you push one. 1265 00:52:49,480 --> 00:52:50,710 It's pretty hard. 1266 00:52:50,710 --> 00:52:52,610 They took 34 adults. 1267 00:52:52,610 --> 00:52:55,590 They trained them from eight to 19 days, 1268 00:52:55,590 --> 00:52:56,480 so less than a month. 1269 00:52:56,480 --> 00:52:57,550 Skipped weekends. 1270 00:52:57,550 --> 00:52:58,450 25 minutes a day. 1271 00:52:58,450 --> 00:53:00,470 It's only half an hour a day. 1272 00:53:00,470 --> 00:53:01,780 They train on this. 1273 00:53:01,780 --> 00:53:05,280 And then they tested them on some of these widely used IQ 1274 00:53:05,280 --> 00:53:07,080 types of measures. 1275 00:53:07,080 --> 00:53:09,940 Here's their performance on the task itself, getting 1276 00:53:09,940 --> 00:53:10,770 better and better. 1277 00:53:10,770 --> 00:53:12,280 OK, that's not surprising. 1278 00:53:12,280 --> 00:53:14,120 And the more they practiced, the higher they got. 1279 00:53:14,120 --> 00:53:16,305 So if you practice really hard at something, you get better 1280 00:53:16,305 --> 00:53:17,980 at doing it. 1281 00:53:17,980 --> 00:53:20,690 That's not the thing they were interested in. 1282 00:53:20,690 --> 00:53:22,380 They were interested in this. 1283 00:53:22,380 --> 00:53:24,170 Here's the IQ scores before they were trained. 1284 00:53:24,170 --> 00:53:25,020 The IQ scores. 1285 00:53:25,020 --> 00:53:26,180 They didn't practice the IQ tests. 1286 00:53:26,180 --> 00:53:27,930 And here's the IQ ones afterwards. 1287 00:53:27,930 --> 00:53:29,670 This is the control group, who did nothing. 1288 00:53:29,670 --> 00:53:31,320 This is the group that did the mental practice. 1289 00:53:31,320 --> 00:53:32,960 And you can see, they pushed up their IQ scores. 1290 00:53:32,960 --> 00:53:33,850 Not a lot. 1291 00:53:33,850 --> 00:53:38,010 But it was only 20 minutes a day for less than a month. 1292 00:53:38,010 --> 00:53:40,010 So these kinds of studies really intrigued 1293 00:53:40,010 --> 00:53:41,810 people in two ways. 1294 00:53:41,810 --> 00:53:43,920 And the more training you got, the more your 1295 00:53:43,920 --> 00:53:44,596 IQ score went up. 1296 00:53:44,596 --> 00:53:46,410 The more weeks you did this. 1297 00:53:46,410 --> 00:53:49,330 Because a), maybe we could push up IQ scores, if that's 1298 00:53:49,330 --> 00:53:50,480 important to push up. 1299 00:53:50,480 --> 00:53:52,240 This is a big decision. 1300 00:53:52,240 --> 00:53:53,790 Even when you're an adult. 1301 00:53:53,790 --> 00:53:56,650 What if you did more than 20 minutes a day for three weeks. 1302 00:53:56,650 --> 00:54:00,400 And b), maybe we could push up everybody's IQ score, who 1303 00:54:00,400 --> 00:54:02,090 needed help in that, with the right kind of 1304 00:54:02,090 --> 00:54:04,070 training, at any age. 1305 00:54:04,070 --> 00:54:06,880 So a lot of interest in that. 1306 00:54:06,880 --> 00:54:10,720 So let me take a step now to sort of harder topics. 1307 00:54:10,720 --> 00:54:14,730 Now, one of the reasons that intelligence and IQ topics 1308 00:54:14,730 --> 00:54:18,860 have gotten appropriately lots of concern is a terrible 1309 00:54:18,860 --> 00:54:22,930 history of racism and sexism associated with IQ tests and 1310 00:54:22,930 --> 00:54:26,790 the way people use that to argue basically inferiority of 1311 00:54:26,790 --> 00:54:29,250 groups, other than themselves. 1312 00:54:29,250 --> 00:54:32,490 So the US Immigration Act of 1924, the official government 1313 00:54:32,490 --> 00:54:34,800 talked about biologically weak stocks. 1314 00:54:34,800 --> 00:54:38,060 At that time, they were focused or prejudiced against 1315 00:54:38,060 --> 00:54:40,070 Italians and Jews from Europe. 1316 00:54:40,070 --> 00:54:42,540 Different societies, different times, as you know, 1317 00:54:42,540 --> 00:54:47,020 tragically, had biases against different groups in the world. 1318 00:54:47,020 --> 00:54:49,520 Unfortunately, it's part of the world we live in. 1319 00:54:49,520 --> 00:54:52,930 And even though we know now with certainty that we're all 1320 00:54:52,930 --> 00:54:55,660 almost identical genetically in any practical sense across 1321 00:54:55,660 --> 00:55:01,720 racial groups, race remains a powerful social category. 1322 00:55:01,720 --> 00:55:03,645 It's a very complicated topic. 1323 00:55:03,645 --> 00:55:06,530 The experience you've had, is the experience you've had. 1324 00:55:06,530 --> 00:55:09,680 But we know it's a social category. 1325 00:55:09,680 --> 00:55:12,380 People identify to a certain extent with that. 1326 00:55:12,380 --> 00:55:15,060 They recognize other people in that context. 1327 00:55:15,060 --> 00:55:16,780 We'll come back to that later in the course. 1328 00:55:16,780 --> 00:55:19,320 But it's a sort of fact of life that we often think of 1329 00:55:19,320 --> 00:55:21,980 ourselves as belonging to one racial group or another and 1330 00:55:21,980 --> 00:55:26,070 somebody else as belonging to one racial group or another. 1331 00:55:26,070 --> 00:55:28,240 So I'm going to focus on one thing that's both troubled 1332 00:55:28,240 --> 00:55:31,910 people and led to bad things, but has some interesting, 1333 00:55:31,910 --> 00:55:34,070 important aspects to think about. 1334 00:55:34,070 --> 00:55:38,210 So in the US, when people compare African American and 1335 00:55:38,210 --> 00:55:41,840 European American scores, there's a gap of scores that 1336 00:55:41,840 --> 00:55:42,630 grows over time. 1337 00:55:42,630 --> 00:55:45,130 So in infancy, to the extent you can test these kinds of 1338 00:55:45,130 --> 00:55:46,020 things, there's no difference. 1339 00:55:46,020 --> 00:55:50,740 By age 4, on average, people who are European American will 1340 00:55:50,740 --> 00:55:52,160 tend to score about four or five points 1341 00:55:52,160 --> 00:55:53,540 higher on IQ tests. 1342 00:55:53,540 --> 00:55:55,930 And as the goes up, it continues to go up. 1343 00:55:55,930 --> 00:55:57,530 There's a gap on average. 1344 00:55:57,530 --> 00:55:58,320 This is a huge average. 1345 00:55:58,320 --> 00:56:04,370 It's across many people across time, as people get 1346 00:56:04,370 --> 00:56:05,560 older in the US. 1347 00:56:05,560 --> 00:56:10,140 Now, we've strongly believed for many, many reasons 1348 00:56:10,140 --> 00:56:12,400 empirically that this is an environmental influence. 1349 00:56:12,400 --> 00:56:15,040 And here's one example of many pieces of evidence. 1350 00:56:15,040 --> 00:56:18,340 So that children fathered, for example, by Black America GIs 1351 00:56:18,340 --> 00:56:21,260 in Germany, brought up by German mothers, have exactly 1352 00:56:21,260 --> 00:56:23,870 the same IQs as white American GI 1353 00:56:23,870 --> 00:56:24,740 children and German mothers. 1354 00:56:24,740 --> 00:56:28,620 That is, in countries where stereotypes were applied in 1355 00:56:28,620 --> 00:56:32,120 general, partly because there wasn't a history of African 1356 00:56:32,120 --> 00:56:34,650 Americans in Germany at that time, the IQ 1357 00:56:34,650 --> 00:56:35,370 scores are the same. 1358 00:56:35,370 --> 00:56:38,300 So we think it's overwhelmingly evident that 1359 00:56:38,300 --> 00:56:39,480 it's an environmental effect. 1360 00:56:39,480 --> 00:56:43,610 But in the US, there's a lot of relationship between, on 1361 00:56:43,610 --> 00:56:46,630 average, across the entire country, on average, between 1362 00:56:46,630 --> 00:56:48,710 what group you're in and average income. 1363 00:56:48,710 --> 00:56:51,160 So here's the average income a few years ago, depending on 1364 00:56:51,160 --> 00:56:54,160 which group you identified yourself as belonging to. 1365 00:56:54,160 --> 00:56:59,130 So we talked earlier about the relationship between economic 1366 00:56:59,130 --> 00:57:01,880 comfort or stability or support and things like the 1367 00:57:01,880 --> 00:57:05,600 number of words a parent can speak to or it's time to speak 1368 00:57:05,600 --> 00:57:06,310 to their child. 1369 00:57:06,310 --> 00:57:08,310 And the habit seems to correlate with all kinds of 1370 00:57:08,310 --> 00:57:09,730 advantages. 1371 00:57:09,730 --> 00:57:14,270 So here's an incredibly powerful and important idea. 1372 00:57:14,270 --> 00:57:16,865 Claude Steele is a researcher at Stanford, who I knew, who 1373 00:57:16,865 --> 00:57:19,100 has played a big part in this. 1374 00:57:19,100 --> 00:57:20,310 And here's the idea. 1375 00:57:20,310 --> 00:57:22,390 So it's called stereotype threat. 1376 00:57:22,390 --> 00:57:23,980 It applies to all of us. 1377 00:57:23,980 --> 00:57:27,270 But in some ways depending on the world we live in, some of 1378 00:57:27,270 --> 00:57:29,970 us can be more vulnerable than others in certain situations. 1379 00:57:29,970 --> 00:57:31,040 Here's the idea. 1380 00:57:31,040 --> 00:57:32,350 So let me tell you the experiment and then the 1381 00:57:32,350 --> 00:57:33,070 interpretation. 1382 00:57:33,070 --> 00:57:35,490 The experiment is that he'll bring people in and give, 1383 00:57:35,490 --> 00:57:39,390 Claude or his students, black and white participants, 1384 00:57:39,390 --> 00:57:40,400 college students. 1385 00:57:40,400 --> 00:57:41,940 And they say, it's a laboratory experiment. 1386 00:57:41,940 --> 00:57:44,760 And they give them something like an SAT test. 1387 00:57:44,760 --> 00:57:48,140 And the groups perform just the same. 1388 00:57:48,140 --> 00:57:50,920 Stanford students, black and white, perform just the same. 1389 00:57:50,920 --> 00:57:52,330 That's the one group. 1390 00:57:52,330 --> 00:57:55,480 Here comes the next group of black and white students, who 1391 00:57:55,480 --> 00:57:59,670 are told we're going to give you a test of intelligence. 1392 00:57:59,670 --> 00:58:00,710 Now, look what happens. 1393 00:58:00,710 --> 00:58:03,800 The scores of African Americans go down. 1394 00:58:03,800 --> 00:58:05,610 And it doesn't even have to be the phrase "test of 1395 00:58:05,610 --> 00:58:08,530 intelligence," you can have people just tick off, on a 1396 00:58:08,530 --> 00:58:12,480 front page, what racial group they belong to and you get 1397 00:58:12,480 --> 00:58:14,790 almost the same effect. 1398 00:58:14,790 --> 00:58:15,530 So what is this? 1399 00:58:15,530 --> 00:58:18,380 This is understood as stereotype vulnerability. 1400 00:58:18,380 --> 00:58:23,580 That is, tragically in the US there's a stereotype that 1401 00:58:23,580 --> 00:58:26,680 African Americans are not as good 1402 00:58:26,680 --> 00:58:29,890 academically as white Americans. 1403 00:58:29,890 --> 00:58:31,700 It's a pernicious stereotype. 1404 00:58:31,700 --> 00:58:34,400 It's one we can decry morally and say it's a bad thing. 1405 00:58:34,400 --> 00:58:35,990 But it's out there. 1406 00:58:35,990 --> 00:58:38,360 There's another area where African Americans are thought 1407 00:58:38,360 --> 00:58:42,100 of as phenomenal by stereotype, which is sports, 1408 00:58:42,100 --> 00:58:42,760 in this country. 1409 00:58:42,760 --> 00:58:44,010 It's a weird thing. 1410 00:58:49,260 --> 00:58:53,130 The idea is that knowledge of these things, even if this is 1411 00:58:53,130 --> 00:58:56,040 your real performance, once that thought enters your mind 1412 00:58:56,040 --> 00:58:59,380 that I'm doing something that some people say I'm not going 1413 00:58:59,380 --> 00:59:02,820 to do such a good job at, is enough to make you 1414 00:59:02,820 --> 00:59:06,550 underperform compared to your true potential. 1415 00:59:06,550 --> 00:59:09,410 So the other area where this has been studied a lot is 1416 00:59:09,410 --> 00:59:11,040 women and mathematics. 1417 00:59:11,040 --> 00:59:11,980 I think that's disappearing. 1418 00:59:11,980 --> 00:59:16,110 When I grew up, everybody was worried that women weren't 1419 00:59:16,110 --> 00:59:18,160 given as good an academic support as men 1420 00:59:18,160 --> 00:59:19,290 or girls and boys. 1421 00:59:19,290 --> 00:59:21,530 OK, it's reversed. 1422 00:59:21,530 --> 00:59:22,810 In my lifetime, it's reversed. 1423 00:59:22,810 --> 00:59:24,490 Because now, by every criteria, women are 1424 00:59:24,490 --> 00:59:27,040 outperforming men in the US by every criteria, at least 1425 00:59:27,040 --> 00:59:29,470 societally, the number who finish school, your beginning 1426 00:59:29,470 --> 00:59:30,700 salaries, everything. 1427 00:59:30,700 --> 00:59:32,950 So now they're worried that us boys are 1428 00:59:32,950 --> 00:59:34,740 really being left behind. 1429 00:59:34,740 --> 00:59:38,280 So these things change because they're cultural inventions. 1430 00:59:38,280 --> 00:59:39,650 They're cultural inventions. 1431 00:59:39,650 --> 00:59:42,980 And cultural morays change. 1432 00:59:42,980 --> 00:59:46,470 And sometimes in good ways, hopefully. 1433 00:59:46,470 --> 00:59:50,680 So stereotype threat is that other's judgments or one's own 1434 00:59:50,680 --> 00:59:53,930 actions will confirm negative stereotypes about one's group. 1435 00:59:53,930 --> 00:59:56,130 Oh, you should do badly on something or you should do 1436 00:59:56,130 --> 00:59:57,590 well on something. 1437 00:59:57,590 --> 01:00:00,390 So they studied on women on that, old people. 1438 01:00:00,390 --> 01:00:02,380 Athletic ability of course runs the opposite. 1439 01:00:02,380 --> 01:00:03,710 The experiment was kind of fun. 1440 01:00:03,710 --> 01:00:06,330 They had a very athletic African American instructor 1441 01:00:06,330 --> 01:00:08,560 come up and start doing push-ups. 1442 01:00:08,560 --> 01:00:11,420 And all the white guys started to lapse in their push-ups. 1443 01:00:11,420 --> 01:00:13,680 They got tired really fast, compared to an equally 1444 01:00:13,680 --> 01:00:17,510 athletic white trainer who came up to the front. 1445 01:00:17,510 --> 01:00:19,290 Does that make sense? 1446 01:00:19,290 --> 01:00:20,360 Does that make sense? 1447 01:00:20,360 --> 01:00:22,490 It's whatever is the stereotype you have in your 1448 01:00:22,490 --> 01:00:25,793 head, if you say OK, oh, oh, I'm not supposed to do so good 1449 01:00:25,793 --> 01:00:27,160 in this, you underperform. 1450 01:00:27,160 --> 01:00:28,850 Not everybody, all the time of course. 1451 01:00:28,850 --> 01:00:31,260 But enough that we have to be concerned about that. 1452 01:00:31,260 --> 01:00:34,050 More for academic performance probably than push-ups. 1453 01:00:34,050 --> 01:00:36,020 But who knows. 1454 01:00:36,020 --> 01:00:38,730 So here's this achievement gap. 1455 01:00:38,730 --> 01:00:45,540 And different scores between again, at age 13, between 1456 01:00:45,540 --> 01:00:47,830 whites and blacks in the United States, which we know 1457 01:00:47,830 --> 01:00:49,190 shouldn't be there. 1458 01:00:49,190 --> 01:00:50,565 Many factors are in it. 1459 01:00:50,565 --> 01:00:52,590 A huge variation among people, of course. 1460 01:00:52,590 --> 01:00:54,220 These are huge averages. 1461 01:00:54,220 --> 01:00:57,320 But one that everybody wants to get rid of, in a just 1462 01:00:57,320 --> 01:01:01,070 society where everybody has an equal opportunity. 1463 01:01:01,070 --> 01:01:05,440 So here's a result that's so unbelievable, that if it 1464 01:01:05,440 --> 01:01:07,410 weren't for some subsequent results, I wouldn't even show 1465 01:01:07,410 --> 01:01:09,550 it to you, even though it's a well-done experiment. 1466 01:01:09,550 --> 01:01:11,800 But the message of it seems so incredible. 1467 01:01:11,800 --> 01:01:13,330 So here's what they did. 1468 01:01:13,330 --> 01:01:15,200 In this well-controlled study in Science, and there's been 1469 01:01:15,200 --> 01:01:17,850 some follow-ups that have exactly done this. 1470 01:01:17,850 --> 01:01:22,230 So they took African American students and white students. 1471 01:01:22,230 --> 01:01:25,690 And they had them take these various tests. 1472 01:01:25,690 --> 01:01:27,788 But some of them, at the beginning of the year, wrote 1473 01:01:27,788 --> 01:01:28,540 an affirmation. 1474 01:01:28,540 --> 01:01:30,570 They had to choose a value from a list and write an 1475 01:01:30,570 --> 01:01:33,050 in-class essay about why the chosen value is 1476 01:01:33,050 --> 01:01:34,470 important to you. 1477 01:01:34,470 --> 01:01:36,790 The controls chose a value from those same lists and 1478 01:01:36,790 --> 01:01:38,630 wrote an in-class essay about why the value might be 1479 01:01:38,630 --> 01:01:40,340 important for somebody else. 1480 01:01:40,340 --> 01:01:42,710 You're writing a one-time essay about why something 1481 01:01:42,710 --> 01:01:45,370 matters to you or matters to somebody else. 1482 01:01:45,370 --> 01:01:49,380 So obviously what matters to you is more powerful for you. 1483 01:01:49,380 --> 01:01:52,650 And by just doing that, there's a 40% reduction in the 1484 01:01:52,650 --> 01:01:54,480 African American students in the study in 1485 01:01:54,480 --> 01:01:55,370 their achievement gap. 1486 01:01:55,370 --> 01:02:00,570 Their scores went up 40% because they wrote one essay 1487 01:02:00,570 --> 01:02:04,580 at the beginning of the year about why values are important 1488 01:02:04,580 --> 01:02:06,430 to them and related to education. 1489 01:02:06,430 --> 01:02:08,770 One essay did that. 1490 01:02:08,770 --> 01:02:09,970 Unbelievable. 1491 01:02:09,970 --> 01:02:13,870 And just a reminder about how much one's attitude incredibly 1492 01:02:13,870 --> 01:02:16,220 influences your performance. 1493 01:02:16,220 --> 01:02:18,310 You have a range of things you can do it. 1494 01:02:18,310 --> 01:02:21,040 And what gets you to the top of your range that's in you, 1495 01:02:21,040 --> 01:02:23,060 or the bottom of your range, has a lot to do with 1496 01:02:23,060 --> 01:02:25,940 attitudes, that can be moved around by a lot of things. 1497 01:02:25,940 --> 01:02:29,450 One essay overcame a tremendous amount of the 1498 01:02:29,450 --> 01:02:32,680 concerns that on average, African American students have 1499 01:02:32,680 --> 01:02:35,520 about academic achievement. 1500 01:02:35,520 --> 01:02:36,980 And it's not just that. 1501 01:02:36,980 --> 01:02:39,630 So in this course, you only get a couple of tips of things 1502 01:02:39,630 --> 01:02:40,880 that are useful to you for courses. 1503 01:02:40,880 --> 01:02:41,550 Here's one. 1504 01:02:41,550 --> 01:02:43,260 It's the same principle, but it seems 1505 01:02:43,260 --> 01:02:45,560 to apply for everybody. 1506 01:02:45,560 --> 01:02:47,600 So here's the experiment, also published in Science. 1507 01:02:47,600 --> 01:02:49,050 It's really cool. 1508 01:02:49,050 --> 01:02:51,850 So they brought in students. 1509 01:02:51,850 --> 01:02:54,020 And they said, look students often are worried about how 1510 01:02:54,020 --> 01:02:56,000 they're going to do in a test, especially if it's an area you 1511 01:02:56,000 --> 01:02:58,440 think you're not so good in. 1512 01:02:58,440 --> 01:03:02,200 So they had them take a test on Gauss's modular arithmetic. 1513 01:03:02,200 --> 01:03:03,030 Here's the pre-test. 1514 01:03:03,030 --> 01:03:04,800 Everybody did about the same. 1515 01:03:04,800 --> 01:03:07,580 Then they said, OK now, they have to create pressure. 1516 01:03:07,580 --> 01:03:10,240 Because of course if you take a test in an experiment, 1517 01:03:10,240 --> 01:03:12,190 that's not pressured, right? 1518 01:03:12,190 --> 01:03:14,240 Pressure is the grade you're going to get, whether it lets 1519 01:03:14,240 --> 01:03:16,420 you into medical school, whether you get to become the 1520 01:03:16,420 --> 01:03:19,400 head of the American Medical Association. 1521 01:03:19,400 --> 01:03:20,590 That's pressure, right? 1522 01:03:20,590 --> 01:03:22,860 So they say oh, here's what we're going to do now. 1523 01:03:22,860 --> 01:03:24,830 We're going to give you another test, everybody 1524 01:03:24,830 --> 01:03:26,000 scoring about the same. 1525 01:03:26,000 --> 01:03:29,030 But you can make a fair bit of money with a partner who's 1526 01:03:29,030 --> 01:03:29,770 down the hall. 1527 01:03:29,770 --> 01:03:31,420 We should tell you that partner has already done a 1528 01:03:31,420 --> 01:03:34,230 really good job on the second version of the test. 1529 01:03:34,230 --> 01:03:36,930 So if you don't do well, you don't get money and the 1530 01:03:36,930 --> 01:03:39,490 partner down the hall doesn't get your money. 1531 01:03:39,490 --> 01:03:41,985 If you do well in the second test you're about to take now, 1532 01:03:41,985 --> 01:03:42,900 then everybody wins. 1533 01:03:42,900 --> 01:03:44,240 So they're trying to make you feel pressured. 1534 01:03:44,240 --> 01:03:45,750 On man, I want to win the money. 1535 01:03:45,750 --> 01:03:47,740 Plus there's a guy down the hall who already did well and 1536 01:03:47,740 --> 01:03:49,430 I'm going to let us down. 1537 01:03:49,430 --> 01:03:50,750 They're trying to make you feel as 1538 01:03:50,750 --> 01:03:51,610 pressured as you might. 1539 01:03:51,610 --> 01:03:54,370 As much as they can in an experiment, like you do in a 1540 01:03:54,370 --> 01:03:56,330 regular test, in a regular course. 1541 01:03:56,330 --> 01:03:58,750 So trying to create pressure and anxiety. 1542 01:03:58,750 --> 01:04:01,130 And then for 10 minutes, the controls just sit there and 1543 01:04:01,130 --> 01:04:01,850 think about it. 1544 01:04:01,850 --> 01:04:03,480 Oh, I hope I don't mess up now. 1545 01:04:03,480 --> 01:04:04,270 The pressure is on. 1546 01:04:04,270 --> 01:04:06,120 I hope I don't meet the person, if I don't do a good 1547 01:04:06,120 --> 01:04:07,845 job, down the hall. 1548 01:04:07,845 --> 01:04:10,530 An expressive group wrote an essay for 10 minutes about 1549 01:04:10,530 --> 01:04:13,676 their thoughts and feelings. 1550 01:04:13,676 --> 01:04:15,030 Oh, I wrote this. 1551 01:04:15,030 --> 01:04:16,980 This is a huge mistake. 1552 01:04:16,980 --> 01:04:21,240 This should be "better." I'll fix it up. 1553 01:04:21,240 --> 01:04:22,350 Better, better, better. 1554 01:04:22,350 --> 01:04:23,860 I did it unrelated, in writing. 1555 01:04:23,860 --> 01:04:25,420 So here's what happens. 1556 01:04:25,420 --> 01:04:28,920 The group that just sat there did nothing. 1557 01:04:28,920 --> 01:04:32,990 Their performance doesn't-- let me get this right. 1558 01:04:32,990 --> 01:04:34,380 The performers that wrote the expressive writing, their 1559 01:04:34,380 --> 01:04:35,690 score goes up. 1560 01:04:35,690 --> 01:04:37,990 Everybody else's scores go down. 1561 01:04:37,990 --> 01:04:40,330 Because here, here's where they're beginning. 1562 01:04:40,330 --> 01:04:42,810 Now, they get pressured. 1563 01:04:42,810 --> 01:04:44,930 And they perform less well. 1564 01:04:44,930 --> 01:04:47,670 They're choking. 1565 01:04:47,670 --> 01:04:49,190 The group that wrote the essay, their 1566 01:04:49,190 --> 01:04:52,040 performance stays up. 1567 01:04:52,040 --> 01:04:56,260 And it's kind of ironic, because a theme of comedy is 1568 01:04:56,260 --> 01:04:59,610 frequently when they tell you, whatever you do, don't tell 1569 01:04:59,610 --> 01:05:00,830 somebody x. 1570 01:05:00,830 --> 01:05:02,030 And then my mistake, you tell x. 1571 01:05:02,030 --> 01:05:04,590 Have you seen that a comedy show? 1572 01:05:04,590 --> 01:05:07,120 So you could have thought, well writing an essay about my 1573 01:05:07,120 --> 01:05:09,880 thoughts and feelings about how much anxiety and pressure 1574 01:05:09,880 --> 01:05:11,910 I feel, is like the worst thing you can do. 1575 01:05:11,910 --> 01:05:13,610 It's like, I don't want face it. 1576 01:05:13,610 --> 01:05:15,530 I'd rather clear my mind. 1577 01:05:15,530 --> 01:05:18,300 But it turns out that when people write this little essay 1578 01:05:18,300 --> 01:05:21,030 about the thoughts and feelings about their anxiety, 1579 01:05:21,030 --> 01:05:24,100 their scores rise. 1580 01:05:24,100 --> 01:05:26,920 And if they don't write that kind of an essay, the scores 1581 01:05:26,920 --> 01:05:29,030 fall, because you've introduced here the stress and 1582 01:05:29,030 --> 01:05:31,780 anxiety that we think is a part of regular testing. 1583 01:05:31,780 --> 01:05:33,280 Does that makes sense? 1584 01:05:33,280 --> 01:05:33,990 I'll fix the slide. 1585 01:05:33,990 --> 01:05:35,480 I'm sorry about the typo. 1586 01:05:35,480 --> 01:05:36,730 Is that OK? 1587 01:05:39,460 --> 01:05:41,130 I'm almost a little afraid to give you advice, because 1588 01:05:41,130 --> 01:05:43,200 somebody will write an essay, do bad on the physics test, 1589 01:05:43,200 --> 01:05:44,690 and say oh, this is terrible. 1590 01:05:44,690 --> 01:05:46,090 I would have gotten a A. 1591 01:05:46,090 --> 01:05:48,790 But it seems like writing a little essay about your 1592 01:05:48,790 --> 01:05:50,900 thoughts and feelings actually pushes scores up. 1593 01:05:50,900 --> 01:05:52,860 I mean that's the scientific evidence. 1594 01:05:52,860 --> 01:05:56,540 But again, it's just a reminder of how powerful 1595 01:05:56,540 --> 01:05:59,440 feelings and attitudes are, whether they're in us or 1596 01:05:59,440 --> 01:06:03,390 visited on us by the world, in how well we perform, within 1597 01:06:03,390 --> 01:06:08,260 the range of performance that are within us to start with. 1598 01:06:08,260 --> 01:06:09,890 I have two more points. 1599 01:06:09,890 --> 01:06:12,440 So we talked a little bit about entity versus growth. 1600 01:06:12,440 --> 01:06:14,700 You know people who believe they're like, I'm only so good 1601 01:06:14,700 --> 01:06:15,560 at something. 1602 01:06:15,560 --> 01:06:17,260 I'm only so good at basketball, I'm only so good 1603 01:06:17,260 --> 01:06:19,220 at math, I'm only so good at programming, I'm only so good 1604 01:06:19,220 --> 01:06:21,700 of writing, or whatever, versus people who say, the 1605 01:06:21,700 --> 01:06:24,400 harder I work, the better I'll get. 1606 01:06:24,400 --> 01:06:27,300 And that pretty much, this work from Carol Dweck, that 1607 01:06:27,300 --> 01:06:30,090 many people tend to go for one thing or the other. 1608 01:06:30,090 --> 01:06:31,720 Is it are we born with talent and that's 1609 01:06:31,720 --> 01:06:33,040 pretty much the deal? 1610 01:06:33,040 --> 01:06:34,620 Or the harder we work, do we get more 1611 01:06:34,620 --> 01:06:36,500 talented at doing something? 1612 01:06:36,500 --> 01:06:37,700 And so this is the kind of questionnaire. 1613 01:06:37,700 --> 01:06:39,280 And these are literally questions, so she gives 1614 01:06:39,280 --> 01:06:42,170 students, you have a certain amount of intelligence and you 1615 01:06:42,170 --> 01:06:43,360 really can't change it. 1616 01:06:43,360 --> 01:06:44,840 I strongly agree. 1617 01:06:44,840 --> 01:06:47,210 That's this trait model. 1618 01:06:47,210 --> 01:06:48,140 Or I disagree. 1619 01:06:48,140 --> 01:06:51,480 The harder I work, the smarter I can be. 1620 01:06:51,480 --> 01:06:54,170 And what she did for example, is give that kind of question 1621 01:06:54,170 --> 01:06:55,800 to students. 1622 01:06:55,800 --> 01:06:58,450 And then follow them in their performance on a math course. 1623 01:06:58,450 --> 01:06:59,950 Here's the ones who believed they could get better. 1624 01:06:59,950 --> 01:07:02,140 Here's the ones who said they only have so much math ability 1625 01:07:02,140 --> 01:07:03,570 and intelligence. 1626 01:07:03,570 --> 01:07:05,050 And look at the ones who thought they could get better, 1627 01:07:05,050 --> 01:07:06,500 got better. 1628 01:07:06,500 --> 01:07:08,830 So that seems like a really good thing to have, is not 1629 01:07:08,830 --> 01:07:10,500 only the positive attitude. 1630 01:07:10,500 --> 01:07:14,540 But a real belief that the harder the work, the smarter 1631 01:07:14,540 --> 01:07:15,790 you'll get. 1632 01:07:18,890 --> 01:07:20,720 Last two slides. 1633 01:07:20,720 --> 01:07:22,300 So finally, finally, finally. 1634 01:07:22,300 --> 01:07:25,220 And we've had a couple of them, but almost none, a 1635 01:07:25,220 --> 01:07:27,800 longitudinal, random assignment study. 1636 01:07:27,800 --> 01:07:30,870 Which doesn't sound hugely exciting, but that's the best 1637 01:07:30,870 --> 01:07:32,400 science we can ever do. 1638 01:07:32,400 --> 01:07:34,160 Randomly assign people to things. 1639 01:07:34,160 --> 01:07:37,200 And then follow them over time to understand how life works. 1640 01:07:37,200 --> 01:07:42,180 So one of the famous studies is, this is Perry Preschool. 1641 01:07:42,180 --> 01:07:46,030 So it followed into adulthood, 123 children from low SES 1642 01:07:46,030 --> 01:07:49,200 environments in Michigan. 1643 01:07:49,200 --> 01:07:51,740 And they were randomly divided, randomly divided. 1644 01:07:51,740 --> 01:07:54,540 And there's no randomness right, in life, mostly. 1645 01:07:54,540 --> 01:07:56,470 You're not randomly given genes. 1646 01:07:56,470 --> 01:07:58,650 You're not randomly put into a household. 1647 01:07:58,650 --> 01:08:01,550 It's always things are super correlated with each other. 1648 01:08:01,550 --> 01:08:02,890 And it's very hard to tease them apart. 1649 01:08:02,890 --> 01:08:05,910 But here they took kids who were from poor families and 1650 01:08:05,910 --> 01:08:07,990 put them randomly into two groups. 1651 01:08:07,990 --> 01:08:10,830 One group is a program group, who received a high-quality 1652 01:08:10,830 --> 01:08:14,080 active learning preschool program and home visits, to be 1653 01:08:14,080 --> 01:08:14,900 supportive as well. 1654 01:08:14,900 --> 01:08:19,130 So they got help at home and help in preschool. 1655 01:08:19,130 --> 01:08:22,010 And a no-program group, who didn't get any of these. 1656 01:08:22,010 --> 01:08:24,960 I can tell you that when you do random assignment studies 1657 01:08:24,960 --> 01:08:29,100 in real life like this, some people argue, I don't agreed 1658 01:08:29,100 --> 01:08:30,399 with this, that it's unethical, because you should 1659 01:08:30,399 --> 01:08:33,450 help everybody all the time. 1660 01:08:33,450 --> 01:08:34,810 But if you don't do this, you never figure 1661 01:08:34,810 --> 01:08:35,630 out what helps people. 1662 01:08:35,630 --> 01:08:38,520 OK It's a little bit of a circular-- 1663 01:08:38,520 --> 01:08:41,520 you can't figure out what really helps people. 1664 01:08:41,520 --> 01:08:43,439 And then in a really rare thing-- so it's random 1665 01:08:43,439 --> 01:08:44,140 assignment. 1666 01:08:44,140 --> 01:08:48,760 They followed them ages 3 to 11, 14 to 15, 19, 27, and 40. 1667 01:08:48,760 --> 01:08:50,290 They follow you through most of your 1668 01:08:50,290 --> 01:08:52,600 childhood and adult life. 1669 01:08:52,600 --> 01:08:55,250 So what happens? 1670 01:08:55,250 --> 01:08:57,600 Here's their IQ scores? 1671 01:08:57,600 --> 01:09:00,160 Here's the program people in red and the 1672 01:09:00,160 --> 01:09:02,000 no-program people in blue. 1673 01:09:02,000 --> 01:09:05,290 And you can see that for a few years, they separate by IQ. 1674 01:09:05,290 --> 01:09:08,340 But by age 7, they're pretty much the same. 1675 01:09:08,340 --> 01:09:11,880 And when these kind of data came out, because of course 1676 01:09:11,880 --> 01:09:13,630 after the preschool, they go back to their 1677 01:09:13,630 --> 01:09:15,330 regular local schools. 1678 01:09:15,330 --> 01:09:17,350 They're pretty much the same schools. 1679 01:09:17,350 --> 01:09:20,660 So people, after that they said, well Head Start is a 1680 01:09:20,660 --> 01:09:24,210 kind of a program to help kids who are poor, get a head start 1681 01:09:24,210 --> 01:09:25,500 in education and support. 1682 01:09:25,500 --> 01:09:26,810 It's no good. 1683 01:09:26,810 --> 01:09:28,770 It doesn't do anything. 1684 01:09:28,770 --> 01:09:31,000 Because once they get back into schools that not very 1685 01:09:31,000 --> 01:09:33,740 supportive, the benefits of the program disappear. 1686 01:09:33,740 --> 01:09:37,120 You didn't do anything for the kid, because unless you fix 1687 01:09:37,120 --> 01:09:40,350 everything in their lives, that one year just doesn't 1688 01:09:40,350 --> 01:09:42,470 make a difference in the long run. 1689 01:09:42,470 --> 01:09:46,080 So everybody said, Head Start programs are just, sadly, a 1690 01:09:46,080 --> 01:09:49,870 waste of resources, because they don't do anything for 1691 01:09:49,870 --> 01:09:51,689 these children over the longer term. 1692 01:09:51,689 --> 01:09:55,350 But here's the remarkable thing. 1693 01:09:55,350 --> 01:09:57,100 They kept following these kids. 1694 01:09:57,100 --> 01:09:58,040 And here's what they found. 1695 01:09:58,040 --> 01:10:02,640 For example, in the number of arrests, 36 had five or more 1696 01:10:02,640 --> 01:10:06,120 arrests in the program group. 1697 01:10:06,120 --> 01:10:08,580 But all the way up to 55, for the no-program group. 1698 01:10:08,580 --> 01:10:10,920 That's a big difference, how often you're arrested. 1699 01:10:10,920 --> 01:10:13,410 That's a big outcome in life. 1700 01:10:13,410 --> 01:10:17,110 Earning $20,000 or more at age 40, program group 60%; 1701 01:10:17,110 --> 01:10:19,180 no-program group, 40%. 1702 01:10:19,180 --> 01:10:21,650 Completed high school, 45% to 65%. 1703 01:10:21,650 --> 01:10:26,850 20% increase in completion of high school, from one year of 1704 01:10:26,850 --> 01:10:28,385 help before kindergarten. 1705 01:10:30,980 --> 01:10:34,230 Basic achievement at age 14, way up. 1706 01:10:34,230 --> 01:10:37,680 Willingness to do homework, way up. 1707 01:10:37,680 --> 01:10:39,940 So what's that's telling us is, IQ is a 1708 01:10:39,940 --> 01:10:40,940 pretty interesting thing. 1709 01:10:40,940 --> 01:10:42,100 And we've talked a lot about it. 1710 01:10:42,100 --> 01:10:44,410 It is an interesting thing. 1711 01:10:44,410 --> 01:10:47,890 But there's something really deep in the ways you can help 1712 01:10:47,890 --> 01:10:51,360 people, that make them succeed in life. 1713 01:10:51,360 --> 01:10:55,390 Not get in trouble, avoid bad things, make money, finish 1714 01:10:55,390 --> 01:10:57,610 school, do your work. 1715 01:10:57,610 --> 01:11:01,750 That one year of school changed these kids for the 1716 01:11:01,750 --> 01:11:04,390 rest of their lives, on average. 1717 01:11:04,390 --> 01:11:08,260 And imagine if you had done two years or five years? 1718 01:11:08,260 --> 01:11:10,730 And IQ in this case doesn't capture it at all. 1719 01:11:10,730 --> 01:11:13,310 There's something else in them that changed, that made them 1720 01:11:13,310 --> 01:11:16,730 more resilient in life and successful in the long run. 1721 01:11:16,730 --> 01:11:20,380 So there's a lot of pieces to who does well and not well in 1722 01:11:20,380 --> 01:11:21,850 ways we wish for everybody. 1723 01:11:21,850 --> 01:11:23,430 And IQ is a piece of that story. 1724 01:11:23,430 --> 01:11:25,450 But there's a lot of pieces. 1725 01:11:25,450 --> 01:11:26,700 So thanks very much.