1 00:00:15,436 --> 00:00:21,316 Speaker 1: Pushkin. Hello, Happiness Lab listeners. We are currently hard at 2 00:00:21,316 --> 00:00:24,436 Speaker 1: work on season three, which will be airing sometime later 3 00:00:24,436 --> 00:00:27,076 Speaker 1: this summer. But while you're waiting, we wanted to share 4 00:00:27,156 --> 00:00:30,636 Speaker 1: something special, an episode of one of my favorite podcasts. 5 00:00:31,156 --> 00:00:34,876 Speaker 1: Hidden Brain, is a weekly podcast hosted by Shankar Vendantem. 6 00:00:34,996 --> 00:00:37,956 Speaker 1: Much like The Happiness Lab, Hidden Brain explores the science 7 00:00:37,996 --> 00:00:40,956 Speaker 1: of human behavior and how we can understand our behavioral 8 00:00:41,036 --> 00:00:44,716 Speaker 1: quirks in order to make better decisions. The show shines 9 00:00:44,756 --> 00:00:47,636 Speaker 1: a spotlight on ideas that help us to better understand 10 00:00:47,676 --> 00:00:51,156 Speaker 1: ourselves and the world around us. You'll get a podcast 11 00:00:51,196 --> 00:00:55,116 Speaker 1: that's guided by empathy, kindness, and great storytelling. And so 12 00:00:55,196 --> 00:00:57,316 Speaker 1: today I want to share an episode of Hidden Brain. 13 00:00:57,796 --> 00:01:00,356 Speaker 1: It's one that I'm quite partial too, because the main 14 00:01:00,396 --> 00:01:03,596 Speaker 1: guest on the episode is me. But this time I'm 15 00:01:03,636 --> 00:01:07,076 Speaker 1: not talking about the science of happiness. Instead, I joined 16 00:01:07,116 --> 00:01:10,356 Speaker 1: Schankar to talk about some of my other search studies 17 00:01:10,396 --> 00:01:14,276 Speaker 1: on the evolutionary origin of our economic biases. Shanka and 18 00:01:14,316 --> 00:01:16,756 Speaker 1: I explore the question of why we make such bad 19 00:01:16,796 --> 00:01:19,156 Speaker 1: decisions when it comes to money, and you'll get to 20 00:01:19,156 --> 00:01:21,316 Speaker 1: hear about some experiments I did back in the day 21 00:01:21,476 --> 00:01:24,596 Speaker 1: with monkeys. We'll look at what monkey's choices can tell 22 00:01:24,676 --> 00:01:27,476 Speaker 1: us about human behavior. It was such a fun conversation 23 00:01:27,676 --> 00:01:29,796 Speaker 1: I wanted to share it with you, so I hope 24 00:01:29,796 --> 00:01:34,556 Speaker 1: you'll enjoy it. Here's my episode on Hidden Brain. This 25 00:01:34,676 --> 00:01:37,876 Speaker 1: is Hidden Brain. I'm shankar Vedantem. Many of the most 26 00:01:38,036 --> 00:01:42,756 Speaker 1: iconic characters and children's stories are talking animals. What yep, gag? 27 00:01:45,316 --> 00:01:54,716 Speaker 1: Just keep swimming, Just keep swimming, Just keep as children, 28 00:01:54,996 --> 00:01:57,476 Speaker 1: we love to imagine that animals think as we think 29 00:01:57,716 --> 00:02:00,676 Speaker 1: and do as we do. We continue to love animal 30 00:02:00,796 --> 00:02:03,996 Speaker 1: videos as we get older. If you need evidence, look 31 00:02:03,996 --> 00:02:07,436 Speaker 1: at YouTube. Maybe you're responsible for one of the twenty 32 00:02:07,476 --> 00:02:10,756 Speaker 1: two million views of this video. It's like to open 33 00:02:10,836 --> 00:02:15,716 Speaker 1: wide s. One monkey lies flat with its mouth wide open. 34 00:02:16,156 --> 00:02:19,436 Speaker 1: A second monkey hunches over the first, peering into its mouth. 35 00:02:20,236 --> 00:02:23,676 Speaker 1: It's pretty typical stuff for monkeys. Animals groom each other 36 00:02:23,716 --> 00:02:27,236 Speaker 1: all the time, But this video went viral for one 37 00:02:27,716 --> 00:02:31,396 Speaker 1: very clear reason. The human voiceovers. Are you going anywhere 38 00:02:31,516 --> 00:02:35,076 Speaker 1: nice on your holidays? Yeah? Yeah, don't try and talk. 39 00:02:35,076 --> 00:02:37,956 Speaker 1: One of my hands are in your mouth. The voices 40 00:02:38,076 --> 00:02:40,916 Speaker 1: turn an ordinary occurrence in the animal world into a 41 00:02:40,956 --> 00:02:44,916 Speaker 1: conversation between a dentist and a patient. Except this dentist 42 00:02:44,996 --> 00:02:47,956 Speaker 1: office is in a tree, and both doctor and patient 43 00:02:48,236 --> 00:02:51,156 Speaker 1: are monkeys. Do a fill in here actually at the back? 44 00:02:51,796 --> 00:02:55,356 Speaker 1: Is it mainly bananas? You eat, won't? I won't tell 45 00:02:55,356 --> 00:02:57,436 Speaker 1: you again, sir, Please don't transpate when I'm working inside 46 00:02:57,436 --> 00:03:00,396 Speaker 1: your mouth. This is just one part of the viral video. 47 00:03:00,796 --> 00:03:05,236 Speaker 1: There are pelicans that look like they're laughing, a squirrel 48 00:03:05,316 --> 00:03:11,236 Speaker 1: that's beatboxing two hours, that complain they've had too much cough. 49 00:03:11,316 --> 00:03:13,276 Speaker 1: I can't blink anymore, and I can hear my heart 50 00:03:13,316 --> 00:03:19,516 Speaker 1: bates in my ears. I don't get it. The joke 51 00:03:19,596 --> 00:03:21,996 Speaker 1: here is that only humans are supposed to do stuff 52 00:03:22,036 --> 00:03:26,156 Speaker 1: like this. Although we love anthropomorphized animals, we don't actually 53 00:03:26,196 --> 00:03:29,196 Speaker 1: believe that other creatures think like us, care about the 54 00:03:29,276 --> 00:03:31,636 Speaker 1: things we care about, or act the way we do. 55 00:03:32,276 --> 00:03:36,676 Speaker 1: When animals behave like people, we find it hilarious. In 56 00:03:36,756 --> 00:03:40,436 Speaker 1: recent years, scientists have begun to actively ask is what 57 00:03:40,516 --> 00:03:44,036 Speaker 1: happens in our minds really that different from what happens 58 00:03:44,036 --> 00:03:47,316 Speaker 1: in the minds of other animals. Researchers working with non 59 00:03:47,436 --> 00:03:50,916 Speaker 1: human primates are finding areas of connection as well as 60 00:03:50,916 --> 00:03:57,596 Speaker 1: important areas of difference. This week on Hidden Brain, what 61 00:03:57,756 --> 00:04:06,676 Speaker 1: other animals can teach us about us the most anxious 62 00:04:06,716 --> 00:04:13,876 Speaker 1: need to smell your breath. Oh oh, that is rank. 63 00:04:14,076 --> 00:04:58,796 Speaker 1: I think gonna lie down. Yale University psychologist Laurie Santos 64 00:04:59,156 --> 00:05:01,876 Speaker 1: has a long commute between her home in Connecticut and 65 00:05:01,956 --> 00:05:05,476 Speaker 1: her lab. It's so far that it takes three forms 66 00:05:05,476 --> 00:05:07,876 Speaker 1: of transportation and the better part of a day to 67 00:05:07,916 --> 00:05:10,916 Speaker 1: get there. But there's no need to feel sorry for her. 68 00:05:11,476 --> 00:05:17,676 Speaker 1: Laurie's lab is a Caribbean island, Cayo Santiago. It's this 69 00:05:17,796 --> 00:05:20,396 Speaker 1: beautiful island right off the southeast coast of Puerto Rico. 70 00:05:21,116 --> 00:05:23,876 Speaker 1: To get there, she flies to San Juan, drives about 71 00:05:23,916 --> 00:05:26,636 Speaker 1: an hour to the small town of Punta Santiago, and 72 00:05:26,716 --> 00:05:29,636 Speaker 1: then hops in a motor boat. Not long after she 73 00:05:29,716 --> 00:05:33,716 Speaker 1: arrives on the dock, she's surrounded by monkeys. The sandy 74 00:05:33,716 --> 00:05:37,636 Speaker 1: colored creatures are everywhere, some lounging around, others jumping off 75 00:05:37,636 --> 00:05:41,276 Speaker 1: a tall branch into the water below. About a thousand 76 00:05:41,596 --> 00:05:45,116 Speaker 1: free ranging reesus monkeys live on this island, and they're 77 00:05:45,116 --> 00:05:47,516 Speaker 1: monkeys that have been used in research for the last 78 00:05:47,636 --> 00:05:50,636 Speaker 1: like eighty years, and so they're incredibly habituated to humans, 79 00:05:50,996 --> 00:05:53,196 Speaker 1: which means we can go down there and test monkeys 80 00:05:53,276 --> 00:05:56,516 Speaker 1: in this natural setting, much like we would test human subjects. 81 00:05:56,756 --> 00:05:58,516 Speaker 1: So you and your team simply walk out onto the 82 00:05:58,516 --> 00:06:01,556 Speaker 1: island with your clipboards looking for ESUS monkeys to study. 83 00:06:01,996 --> 00:06:03,956 Speaker 1: That's exactly right, and we kind of, you know, find 84 00:06:03,996 --> 00:06:05,796 Speaker 1: ones that look kind of bored and like they might 85 00:06:05,796 --> 00:06:07,676 Speaker 1: be willing to do something, and we PLoP down and 86 00:06:07,756 --> 00:06:10,076 Speaker 1: run studies with them. How do you get the animals 87 00:06:10,076 --> 00:06:12,396 Speaker 1: to sit still and take part in the experiment? Would 88 00:06:12,476 --> 00:06:15,156 Speaker 1: why would they want to sign up? Well, they're naturally 89 00:06:15,236 --> 00:06:18,156 Speaker 1: curious animals, you know, and usually many of the studies involved, 90 00:06:18,356 --> 00:06:20,876 Speaker 1: you know, showing the monkeys something really interesting or something 91 00:06:20,916 --> 00:06:23,596 Speaker 1: really unexpected. It's kind of like a little roving you know, 92 00:06:23,676 --> 00:06:25,716 Speaker 1: theater show that shows up. We know when they're sitting 93 00:06:25,716 --> 00:06:27,156 Speaker 1: there eating and they're like, okay, you know what are 94 00:06:27,156 --> 00:06:29,356 Speaker 1: you going to show me? Not all the monkeys sit there, 95 00:06:29,356 --> 00:06:30,876 Speaker 1: you know, So we definitely get some who kind of 96 00:06:30,996 --> 00:06:32,556 Speaker 1: walk away and don't want to deal with us, but 97 00:06:32,836 --> 00:06:38,236 Speaker 1: many are interested enough to stick around. Laurie Santos has 98 00:06:38,236 --> 00:06:40,556 Speaker 1: spent most of her career trying to capture the attention 99 00:06:40,596 --> 00:06:45,356 Speaker 1: of monkeys. Not because she's especially excited about monkeys. She 100 00:06:45,396 --> 00:06:47,596 Speaker 1: didn't come to this work after a childhood of being 101 00:06:47,596 --> 00:06:52,916 Speaker 1: obsessed with curious George no Laurie is fascinated by humans. 102 00:06:53,156 --> 00:06:55,276 Speaker 1: There's no way to study what makes humans special. If 103 00:06:55,276 --> 00:06:57,676 Speaker 1: you only study humans, you actually have to turn to 104 00:06:57,716 --> 00:07:00,716 Speaker 1: all the other critters in the animal kingdom. Monkeys are 105 00:07:00,716 --> 00:07:03,236 Speaker 1: a really important population because they can tell us the 106 00:07:03,316 --> 00:07:05,956 Speaker 1: kinds of things that are unique to the human species. 107 00:07:07,076 --> 00:07:10,636 Speaker 1: You can get very valuable information comparing monkey minds with 108 00:07:10,756 --> 00:07:14,596 Speaker 1: human minds. Doing this can help us distinguish between things 109 00:07:14,596 --> 00:07:17,636 Speaker 1: in our heads that are the product of nature from 110 00:07:17,676 --> 00:07:20,356 Speaker 1: things in our heads that are the product of nature. 111 00:07:20,996 --> 00:07:22,756 Speaker 1: You know, we have lots of human culture, we have 112 00:07:22,796 --> 00:07:25,116 Speaker 1: lots of human teaching. You know, if we're really looking 113 00:07:25,116 --> 00:07:27,476 Speaker 1: for the pure things that the human mind has and 114 00:07:27,556 --> 00:07:30,476 Speaker 1: the absence of those different processes, it's not great to 115 00:07:30,516 --> 00:07:33,876 Speaker 1: study adult humans. Now. Presumably it would be easier if 116 00:07:33,916 --> 00:07:36,636 Speaker 1: you could actually study human ancestors, if you could go 117 00:07:36,676 --> 00:07:39,716 Speaker 1: back and look at you know, human beings who lived 118 00:07:39,876 --> 00:07:42,556 Speaker 1: several hundred thousand years ago, but they're not around any more. 119 00:07:42,556 --> 00:07:45,116 Speaker 1: To round research experiments are Yeah, that's the joke, you know. 120 00:07:45,436 --> 00:07:47,676 Speaker 1: You know, we com undergrad study pools to see if 121 00:07:47,676 --> 00:07:50,756 Speaker 1: there are Neanderthals or Homo erectus, and they're not there. 122 00:07:51,076 --> 00:07:53,836 Speaker 1: It'd be fantastic to study them. But but honestly, for 123 00:07:53,956 --> 00:07:55,956 Speaker 1: many of the things that we've been studying, you know, 124 00:07:55,996 --> 00:07:59,036 Speaker 1: these basic aspects of social cognition, or these basic aspects 125 00:07:59,036 --> 00:08:02,316 Speaker 1: of decision making, these are capacities that are old enough 126 00:08:02,396 --> 00:08:04,596 Speaker 1: that you might expect them to be shared with our 127 00:08:04,596 --> 00:08:07,396 Speaker 1: common ancestor with reciss monkeys, say, and so in some 128 00:08:07,436 --> 00:08:10,596 Speaker 1: ways for the particular cognitive aacities were studying. You know, 129 00:08:10,636 --> 00:08:13,356 Speaker 1: it's good to kind of rewind the evolutionary tape as 130 00:08:13,356 --> 00:08:16,356 Speaker 1: it were as far back as we can. I want 131 00:08:16,356 --> 00:08:18,956 Speaker 1: to get your experiments in a moment. But just being 132 00:08:18,996 --> 00:08:22,316 Speaker 1: on this island has apparently revealed all kinds of similarities 133 00:08:22,356 --> 00:08:26,116 Speaker 1: between humans and other animals. One problem you've had to 134 00:08:26,156 --> 00:08:29,436 Speaker 1: guard against on the island is unethical behavior. Tell me 135 00:08:29,516 --> 00:08:34,236 Speaker 1: about the monkey thieves that you've encountered on Kio Santiago. Well, 136 00:08:34,516 --> 00:08:36,316 Speaker 1: you know, it's kind of sad to admit that you're 137 00:08:36,316 --> 00:08:38,876 Speaker 1: getting ripped off by monkeys, but it happens more than 138 00:08:38,916 --> 00:08:41,996 Speaker 1: you'd think on the island. You know, they're wily creatures 139 00:08:41,996 --> 00:08:45,356 Speaker 1: who are often pretty hungry, and humans have backpacks filled 140 00:08:45,356 --> 00:08:48,396 Speaker 1: with things like lunches and delicious fruit objects for studies 141 00:08:48,396 --> 00:08:51,196 Speaker 1: and so on. And one of the big inspirations for 142 00:08:51,436 --> 00:08:52,796 Speaker 1: some of the work we were trying to do on 143 00:08:53,156 --> 00:08:55,596 Speaker 1: deception and kind of how monkeys think about other minds 144 00:08:55,996 --> 00:08:58,156 Speaker 1: came from this active theft on behalf of one of 145 00:08:58,156 --> 00:09:00,996 Speaker 1: the monkeys. We were running a study about number where 146 00:09:00,996 --> 00:09:04,436 Speaker 1: we were showing monkeys different numbers of objects, and there 147 00:09:04,516 --> 00:09:06,316 Speaker 1: was one research day that we actually had to go 148 00:09:06,396 --> 00:09:09,716 Speaker 1: home from the island early because the monkey had ripped 149 00:09:09,716 --> 00:09:12,236 Speaker 1: off all of the fruit we were using to display 150 00:09:12,276 --> 00:09:14,316 Speaker 1: the numbers in the study. And I think it was 151 00:09:14,356 --> 00:09:16,396 Speaker 1: really on that boat ride home that I started thinking, 152 00:09:16,476 --> 00:09:18,636 Speaker 1: you know, they're they're doing this in a successful way. 153 00:09:18,716 --> 00:09:21,276 Speaker 1: You know, it's not just that we're we're done researchers 154 00:09:21,276 --> 00:09:24,076 Speaker 1: and they can outsmart us. They're specifically trying to steal 155 00:09:24,116 --> 00:09:26,316 Speaker 1: from us when we're not aware of what they're doing, 156 00:09:26,596 --> 00:09:28,396 Speaker 1: or maybe even when we have a false belief about 157 00:09:28,396 --> 00:09:30,436 Speaker 1: what they're doing. And so it really launched this line 158 00:09:30,436 --> 00:09:32,236 Speaker 1: of research to be like, Okay, how are they thinking 159 00:09:32,236 --> 00:09:34,436 Speaker 1: about that problem? You know that they're duping us in 160 00:09:34,756 --> 00:09:37,276 Speaker 1: you know, what are the representations they're using to solve 161 00:09:37,276 --> 00:09:40,036 Speaker 1: this task. And is it true that they are not 162 00:09:40,116 --> 00:09:42,756 Speaker 1: just simply stealing, but in some ways going after the 163 00:09:42,796 --> 00:09:45,916 Speaker 1: easiest targets, in some ways what criminologists might call a 164 00:09:46,036 --> 00:09:48,916 Speaker 1: rational model of crime. Yeah, in lots of ways. In fact, 165 00:09:48,956 --> 00:09:50,636 Speaker 1: we set this up as a study. This was work 166 00:09:50,676 --> 00:09:53,756 Speaker 1: early work that I did with John Flambum. We basically 167 00:09:53,796 --> 00:09:56,356 Speaker 1: set up an experiment where we gave monkeys the opportunity 168 00:09:56,396 --> 00:10:00,436 Speaker 1: to steal rationally. What we did was we had them experienced. 169 00:10:00,476 --> 00:10:02,716 Speaker 1: They're kind of walking around and they see two people 170 00:10:02,756 --> 00:10:04,476 Speaker 1: who are standing in front of a grape, which is 171 00:10:04,476 --> 00:10:06,996 Speaker 1: a tasty piece of food for monkeys. One of those 172 00:10:07,116 --> 00:10:08,916 Speaker 1: people is kind of looking at the grapes. If you 173 00:10:08,916 --> 00:10:11,196 Speaker 1: try to steal it, he'd probably stop you, whereas the 174 00:10:11,196 --> 00:10:13,676 Speaker 1: other person is not paying attention, either because he's turned 175 00:10:13,716 --> 00:10:15,756 Speaker 1: around or he has a barrier in front of his 176 00:10:15,796 --> 00:10:18,356 Speaker 1: face and so on. And we just gave monkeys one trial, 177 00:10:18,596 --> 00:10:20,796 Speaker 1: and what we found is that even on that first trial, 178 00:10:20,996 --> 00:10:23,756 Speaker 1: monkeys selectively stole from the person who couldn't see them. 179 00:10:24,076 --> 00:10:27,156 Speaker 1: In other words, they're rationally calculating, you know, whether or 180 00:10:27,196 --> 00:10:29,916 Speaker 1: not someone could detect that they're they're about to do 181 00:10:29,956 --> 00:10:34,316 Speaker 1: something dastardly. That's fascinating, And you've done some experiments revealings, 182 00:10:34,356 --> 00:10:38,356 Speaker 1: I'm fairly sophisticated things that the monkeys are doing, including 183 00:10:38,436 --> 00:10:41,756 Speaker 1: things involving basic math. Can you tell me about some 184 00:10:41,796 --> 00:10:44,636 Speaker 1: of the experiments where you've tested whether the monkeys have 185 00:10:45,076 --> 00:10:48,996 Speaker 1: an ability to count a very simple counting for example. Yeah. 186 00:10:48,996 --> 00:10:50,996 Speaker 1: So this is some early work that was done at 187 00:10:50,996 --> 00:10:53,556 Speaker 1: the field site back when I was an undergraduate actually, 188 00:10:54,236 --> 00:10:56,276 Speaker 1: and it was studies that we're really trying to see 189 00:10:56,276 --> 00:10:59,316 Speaker 1: whether or not monkeys shared the basic capacities that that 190 00:10:59,716 --> 00:11:02,076 Speaker 1: human infants seemed to have. This is work by Karen 191 00:11:02,076 --> 00:11:04,436 Speaker 1: Wynn and her colleagues at Yale. She found that even 192 00:11:04,476 --> 00:11:07,196 Speaker 1: by about six months of age, babies can track the 193 00:11:07,316 --> 00:11:12,076 Speaker 1: outcomes of arithmetic events. Here's mickey. So if babyc one 194 00:11:12,116 --> 00:11:14,156 Speaker 1: object added to a box, and that box is covered 195 00:11:14,236 --> 00:11:18,316 Speaker 1: up and up goes the screen, and the second object 196 00:11:18,396 --> 00:11:21,436 Speaker 1: is put in and who is this, they seem to 197 00:11:21,476 --> 00:11:24,556 Speaker 1: expect exactly two objects will be in the box. Watch 198 00:11:24,596 --> 00:11:27,796 Speaker 1: the screen, and they seem to be surprised when the 199 00:11:27,836 --> 00:11:30,556 Speaker 1: box is open to reveal only one object or three objects. 200 00:11:31,276 --> 00:11:33,116 Speaker 1: And so we can do the same kinds of studies 201 00:11:33,556 --> 00:11:35,676 Speaker 1: out in the field with the monkeys. We literally set 202 00:11:35,756 --> 00:11:38,636 Speaker 1: up a little magical box for the monkeys. We've come 203 00:11:38,676 --> 00:11:40,596 Speaker 1: to put on a little monkey magician hats and head 204 00:11:40,636 --> 00:11:43,396 Speaker 1: out and then show the magic tricks. That the magic 205 00:11:43,476 --> 00:11:46,036 Speaker 1: isn't all that exciting. You know, we're putting one or 206 00:11:46,076 --> 00:11:48,636 Speaker 1: two eggplants into a box and revealing different outcomes. I 207 00:11:48,676 --> 00:11:51,556 Speaker 1: can give you my magician's secrets if you need them, 208 00:11:51,716 --> 00:11:54,636 Speaker 1: But basically what we found is that monkeys show exactly 209 00:11:54,636 --> 00:11:57,156 Speaker 1: the same performance on these studies as human infants. In 210 00:11:57,196 --> 00:12:00,476 Speaker 1: other words, they expect the outcome of one plus one 211 00:12:00,556 --> 00:12:03,116 Speaker 1: to be exactly two, and they're surprised if they see 212 00:12:03,596 --> 00:12:06,396 Speaker 1: three or one. And in some ways, it's interesting the 213 00:12:06,436 --> 00:12:09,436 Speaker 1: connection you're making between studying monkeys and studying infants, because 214 00:12:09,436 --> 00:12:11,156 Speaker 1: in some ways they both tell us. When you study 215 00:12:11,196 --> 00:12:15,556 Speaker 1: a child, a small child, an infant, and you see 216 00:12:15,596 --> 00:12:18,556 Speaker 1: this kind of rudimentary maths skills, it actually tells you 217 00:12:18,556 --> 00:12:20,276 Speaker 1: you don't actually have to go to school to learn 218 00:12:20,316 --> 00:12:23,476 Speaker 1: that basic math. Some of that is actually potentially programmed 219 00:12:23,476 --> 00:12:26,836 Speaker 1: into how the brain operates. That's right. It's yet another 220 00:12:26,876 --> 00:12:29,356 Speaker 1: way of kind of removing all the training and teaching 221 00:12:29,396 --> 00:12:31,796 Speaker 1: and cultural learning that we humans have. If you turn 222 00:12:31,876 --> 00:12:34,436 Speaker 1: to human infants, what you find is capacities that are 223 00:12:34,476 --> 00:12:37,636 Speaker 1: there in the absence of experience, right in the absence 224 00:12:37,636 --> 00:12:42,596 Speaker 1: of very little experience. These studies suggest that there are 225 00:12:42,636 --> 00:12:46,276 Speaker 1: more similarities than we imagine between humans and other animals. 226 00:12:46,956 --> 00:12:50,476 Speaker 1: They challenge our assumption that the human mind is unique. 227 00:12:51,036 --> 00:12:54,516 Speaker 1: For example, Laurie says, one longstanding belief was that non 228 00:12:54,636 --> 00:12:58,596 Speaker 1: human primates were bad at thinking about other animals perspectives. 229 00:12:58,796 --> 00:13:02,116 Speaker 1: Even our closest living relative, chimpanzees, had failed on really 230 00:13:02,116 --> 00:13:05,396 Speaker 1: simple tasks where a humans trying to get the chimpanzee 231 00:13:05,396 --> 00:13:07,956 Speaker 1: to look for food in one particular location, and there's 232 00:13:07,956 --> 00:13:09,956 Speaker 1: a bunch of cups that are turned over, and the 233 00:13:10,036 --> 00:13:12,996 Speaker 1: human would point at one of these overturned cups. And 234 00:13:13,036 --> 00:13:15,196 Speaker 1: what the research showed is that primates were really bad 235 00:13:15,236 --> 00:13:18,116 Speaker 1: at this task. They didn't seem to realize that pointing 236 00:13:18,596 --> 00:13:21,396 Speaker 1: meant some information that a human was trying to communicate 237 00:13:21,396 --> 00:13:23,436 Speaker 1: with you, And this really led to the view that 238 00:13:23,476 --> 00:13:26,756 Speaker 1: primates were bad at understanding others perspectives. They didn't seem 239 00:13:26,836 --> 00:13:30,436 Speaker 1: to know what other individuals knew, and that that that 240 00:13:30,716 --> 00:13:33,396 Speaker 1: line of research kind of it didn't really settle well 241 00:13:33,396 --> 00:13:35,116 Speaker 1: with a lot of the people who are watching primates 242 00:13:35,116 --> 00:13:37,276 Speaker 1: in the field, you know, like, you know, it's bad 243 00:13:37,276 --> 00:13:38,996 Speaker 1: to be reading this paper that you know primates don't 244 00:13:39,076 --> 00:13:41,396 Speaker 1: understand other people's perpective when you're getting ripped off every 245 00:13:41,476 --> 00:13:43,516 Speaker 1: day on this island and have to go home early, 246 00:13:44,036 --> 00:13:45,756 Speaker 1: and so, you know, So that was what launched a 247 00:13:45,796 --> 00:13:48,676 Speaker 1: lot of our studies and other studies by researchers like 248 00:13:48,836 --> 00:13:51,076 Speaker 1: Brian Hare and colleagues trying to look at, you know, 249 00:13:51,116 --> 00:13:53,956 Speaker 1: what are the basic capacities primate non human primates have 250 00:13:54,716 --> 00:13:58,636 Speaker 1: for understanding like what other people's perspectives are. And as 251 00:13:58,676 --> 00:14:00,716 Speaker 1: part of these studies, we've developed all kinds of different 252 00:14:00,756 --> 00:14:03,636 Speaker 1: things to test whether monkeys share our understanding of what 253 00:14:03,676 --> 00:14:06,476 Speaker 1: others perceive, what others here, and what others know. And 254 00:14:06,556 --> 00:14:08,516 Speaker 1: all of those studies by and large seemed to be 255 00:14:08,596 --> 00:14:11,436 Speaker 1: showing that nonhuman primates are pretty good at that they 256 00:14:11,476 --> 00:14:14,596 Speaker 1: seem to know something about someone else's perspective. Can you 257 00:14:14,596 --> 00:14:16,756 Speaker 1: give me one or two examples of what these studies 258 00:14:16,796 --> 00:14:19,356 Speaker 1: are and what they find. Yeah. One of the studies 259 00:14:19,436 --> 00:14:21,876 Speaker 1: was again built off a study that had been done 260 00:14:21,876 --> 00:14:24,756 Speaker 1: in human infants. This was a study looking at whether 261 00:14:24,836 --> 00:14:27,516 Speaker 1: or not human infants predict that a person will reach 262 00:14:27,676 --> 00:14:30,836 Speaker 1: where she knows an object is. So imagine the following scenario. 263 00:14:30,916 --> 00:14:34,356 Speaker 1: You're watching somebody who seems to really like a particular object. 264 00:14:34,356 --> 00:14:36,476 Speaker 1: There's a toy that they're really interested in, and that 265 00:14:36,516 --> 00:14:39,156 Speaker 1: toy rolls over and falls into one of two boxes. 266 00:14:39,436 --> 00:14:41,356 Speaker 1: Question is where do you expect that person to reach. 267 00:14:41,796 --> 00:14:43,836 Speaker 1: You probably expect her to reach in the box where 268 00:14:43,876 --> 00:14:45,596 Speaker 1: she knows it to be. You know, people reach for 269 00:14:45,636 --> 00:14:47,796 Speaker 1: things where they think they are, and that's what the 270 00:14:47,836 --> 00:14:50,596 Speaker 1: research found with babies. Babies are surprised if that person 271 00:14:50,716 --> 00:14:53,476 Speaker 1: who saw a toy roll into one box reaches into 272 00:14:53,516 --> 00:14:55,996 Speaker 1: a different box to look for the toy. We just 273 00:14:56,076 --> 00:14:59,196 Speaker 1: imported that same study for monkeys. We had monkeys watch 274 00:14:59,196 --> 00:15:02,516 Speaker 1: as a human looked longingly at a delicious apple, and 275 00:15:02,556 --> 00:15:05,636 Speaker 1: then they saw that apple move into a particular box, 276 00:15:05,756 --> 00:15:07,916 Speaker 1: and we showed that the monkeys are surprised if when 277 00:15:08,236 --> 00:15:10,836 Speaker 1: a person sees an apple move into a box, they 278 00:15:10,916 --> 00:15:13,436 Speaker 1: look to the opposite location. They kind of expect a 279 00:15:13,516 --> 00:15:15,916 Speaker 1: person to reach for something where they know it's going 280 00:15:15,956 --> 00:15:24,076 Speaker 1: to be. When we come back more from Laurie's experiments 281 00:15:24,156 --> 00:15:26,676 Speaker 1: and what they may tell us about the human mind, 282 00:15:44,756 --> 00:15:48,916 Speaker 1: During the summer, psychologist Laurie Santos takes her research outdoors, 283 00:15:49,716 --> 00:15:53,436 Speaker 1: under palm trees and sunshine. She studies Reesus monkeys on 284 00:15:53,476 --> 00:15:57,196 Speaker 1: the island of Caio Santiago, but that's only one setting 285 00:15:57,196 --> 00:16:00,796 Speaker 1: for her research. For a decade, she also studied monkeys 286 00:16:00,876 --> 00:16:04,316 Speaker 1: at a lab she built at Yale University. Unlike the 287 00:16:04,356 --> 00:16:08,556 Speaker 1: Reesus monkeys in Puerto Rico, the monkeys at Yale were capuchin's. 288 00:16:09,156 --> 00:16:11,836 Speaker 1: We mostly chose different species because in some ways capuchins 289 00:16:11,876 --> 00:16:15,476 Speaker 1: are very easy to kind of house socially in captivity, 290 00:16:15,516 --> 00:16:16,716 Speaker 1: so you can have them in kind of a big 291 00:16:16,796 --> 00:16:19,476 Speaker 1: zoo enclosure and they're very comfortable, and that was one 292 00:16:19,516 --> 00:16:22,036 Speaker 1: of the reasons we picked that species. A second reason 293 00:16:22,156 --> 00:16:24,076 Speaker 1: was that with the capuchins, we wanted to look at 294 00:16:24,276 --> 00:16:26,836 Speaker 1: a set of different questions. We did work on what 295 00:16:26,836 --> 00:16:29,396 Speaker 1: they knew about others perspectives, but we also wanted to 296 00:16:29,396 --> 00:16:32,276 Speaker 1: look at their decision making strategies, and there was lots 297 00:16:32,276 --> 00:16:35,036 Speaker 1: of work showing that capuchins were really good at kind 298 00:16:35,076 --> 00:16:37,916 Speaker 1: of making decisions and using tools, but in particular that 299 00:16:37,956 --> 00:16:40,036 Speaker 1: they were good at a method that we really wanted 300 00:16:40,036 --> 00:16:43,076 Speaker 1: to use, which was a method involving token trading where 301 00:16:43,116 --> 00:16:46,276 Speaker 1: monkeys could pay us for different goods and services. There 302 00:16:46,316 --> 00:16:48,356 Speaker 1: was lots of work suggesting that capuchins might be good 303 00:16:48,356 --> 00:16:50,396 Speaker 1: at that, and we thought that might be an interesting 304 00:16:50,436 --> 00:16:53,836 Speaker 1: avenue to start looking at some of monkeys economic decision making. 305 00:16:54,796 --> 00:16:59,396 Speaker 1: Laurie created what she called a monkey marketplace. She wanted 306 00:16:59,436 --> 00:17:02,756 Speaker 1: to teach monkeys to use money. I mean, when we 307 00:17:02,796 --> 00:17:05,116 Speaker 1: first started talking about these studies, you know, to friends 308 00:17:05,116 --> 00:17:06,956 Speaker 1: and stuff, they're like, you're going to teach monkeys to 309 00:17:07,036 --> 00:17:10,276 Speaker 1: use money? You like, it sounds crazy, but in fact 310 00:17:10,356 --> 00:17:12,716 Speaker 1: it's pretty It's pretty simple to get the monkeys to 311 00:17:12,756 --> 00:17:16,276 Speaker 1: do this kind of trading. They're naturally really curious critters, 312 00:17:16,316 --> 00:17:18,596 Speaker 1: and so at the start we just put inside their 313 00:17:18,676 --> 00:17:21,596 Speaker 1: enclosure little metal tokens. They kind of looked like, you know, 314 00:17:21,636 --> 00:17:24,916 Speaker 1: little fake pieces of money, and the kuchins would naturally 315 00:17:24,956 --> 00:17:26,836 Speaker 1: pick these up, but they kind of, you know, didn't 316 00:17:26,836 --> 00:17:29,076 Speaker 1: have any use for them, and they quickly realized that 317 00:17:29,076 --> 00:17:31,756 Speaker 1: if they handed them back to a human experimenter, we'd 318 00:17:31,756 --> 00:17:33,956 Speaker 1: give the monkeys back a piece of food for the tokens. 319 00:17:33,956 --> 00:17:35,756 Speaker 1: So it's kind of like a token for a piece 320 00:17:35,796 --> 00:17:38,316 Speaker 1: of food sort of exchange. And what was surprising is 321 00:17:38,316 --> 00:17:41,076 Speaker 1: that the monkeys picked this up incredibly quickly, you know, 322 00:17:41,116 --> 00:17:43,476 Speaker 1: within just a few exposures they realized like, oh wait, 323 00:17:43,476 --> 00:17:45,836 Speaker 1: I give tokens for food, got it. And then once 324 00:17:45,836 --> 00:17:47,956 Speaker 1: we had them doing that, we could ask all kinds 325 00:17:47,956 --> 00:17:50,676 Speaker 1: of economic questions about what they knew about real markets. 326 00:17:51,116 --> 00:17:54,396 Speaker 1: Once the monkeys learned the tokens with currency, they began 327 00:17:54,476 --> 00:17:57,156 Speaker 1: hunting for bargains. The first thing we did was give 328 00:17:57,196 --> 00:18:00,156 Speaker 1: them opportunities to find good deals, and that meant giving 329 00:18:00,196 --> 00:18:03,716 Speaker 1: them a choice between different goods offered at different prices. 330 00:18:04,276 --> 00:18:06,636 Speaker 1: So the monkey marketplace was when the monkeys, you know, 331 00:18:06,716 --> 00:18:09,116 Speaker 1: they came in for testing from their big social enclosure 332 00:18:09,236 --> 00:18:11,556 Speaker 1: and entered a little smaller enclosure where they had access 333 00:18:11,556 --> 00:18:14,276 Speaker 1: to a few of these tokens, and then monkeys had 334 00:18:14,276 --> 00:18:17,316 Speaker 1: a choice between two experimenters who sold different goods at 335 00:18:17,316 --> 00:18:19,876 Speaker 1: different prices. You know, so someone might be selling a 336 00:18:19,956 --> 00:18:22,156 Speaker 1: grape for one token and someone might be selling, say 337 00:18:22,196 --> 00:18:24,796 Speaker 1: a cucumber from one token. And the question was whether 338 00:18:24,836 --> 00:18:27,636 Speaker 1: the monkeys maximized their their food dollar as it were, 339 00:18:27,716 --> 00:18:30,316 Speaker 1: you know, did they shop rationally given the amount to 340 00:18:30,316 --> 00:18:32,116 Speaker 1: food that they were getting and the kind of food. 341 00:18:32,556 --> 00:18:35,076 Speaker 1: And the amazing thing that we've found is that the 342 00:18:35,156 --> 00:18:39,396 Speaker 1: monkeys seemed to be relatively rational in this market. That is, 343 00:18:39,436 --> 00:18:42,476 Speaker 1: they seemed to substitute rationally. They bought more food with 344 00:18:42,476 --> 00:18:45,116 Speaker 1: their token dollar, and they seem to prefer shopping for 345 00:18:45,196 --> 00:18:48,236 Speaker 1: foods that they liked better. Did they actually, you think, 346 00:18:48,396 --> 00:18:51,556 Speaker 1: enjoy the process of shopping? I mean humans, as you know, 347 00:18:51,636 --> 00:18:53,756 Speaker 1: sort of lots of humans actually enjoy the process of 348 00:18:53,756 --> 00:18:56,276 Speaker 1: going to a store and buying things. What was there 349 00:18:56,476 --> 00:18:58,396 Speaker 1: a pleasure in sort of doing this, because, of course, 350 00:18:58,396 --> 00:19:00,236 Speaker 1: what the monkeys were doing here is not just simply 351 00:19:00,476 --> 00:19:02,956 Speaker 1: I'm part of an experiment where I press you know, 352 00:19:02,996 --> 00:19:05,276 Speaker 1: I press a lever and I get some food. In 353 00:19:05,316 --> 00:19:07,356 Speaker 1: this case, you actually can choose. I can go to 354 00:19:07,396 --> 00:19:09,716 Speaker 1: Personnai or I can go to person BI have choices, 355 00:19:10,076 --> 00:19:13,316 Speaker 1: I have autonomy as a consumer. Yeah, it's hard. I 356 00:19:13,316 --> 00:19:15,756 Speaker 1: mean we didn't have a direct empirical measure of pleasure. 357 00:19:15,796 --> 00:19:17,756 Speaker 1: But but they really did seem to like it. You know, 358 00:19:17,796 --> 00:19:20,076 Speaker 1: they would, you know, rush into the enclosure to try 359 00:19:20,076 --> 00:19:21,996 Speaker 1: to do this. And what I loved most is that 360 00:19:22,036 --> 00:19:24,396 Speaker 1: they tended to pay a lot of attention to you know, 361 00:19:24,516 --> 00:19:26,236 Speaker 1: what the different options were. You know, they'd kind of 362 00:19:26,276 --> 00:19:28,316 Speaker 1: go on both sides of the enclosure and look at 363 00:19:28,356 --> 00:19:31,396 Speaker 1: what each experiment was offering very carefully. So they seem 364 00:19:31,436 --> 00:19:35,516 Speaker 1: to be very careful shoppers. I'm wondering whether the monkeys 365 00:19:35,556 --> 00:19:38,356 Speaker 1: ever traded tokens with each other. Did they say, you know, 366 00:19:38,396 --> 00:19:40,396 Speaker 1: I'm going to pay you three tokens for you to 367 00:19:40,436 --> 00:19:43,516 Speaker 1: groom me. Yeah. Well, you know, the remarkable thing is 368 00:19:43,556 --> 00:19:45,196 Speaker 1: that the monkeys never really did that. I mean, to 369 00:19:45,196 --> 00:19:47,276 Speaker 1: be fair, we didn't give them opportunities to do that, 370 00:19:47,356 --> 00:19:49,036 Speaker 1: you know, because they were kind of with the tokens 371 00:19:49,156 --> 00:19:53,116 Speaker 1: mostly by themselves. But but what's striking is it doesn't 372 00:19:53,116 --> 00:19:55,716 Speaker 1: seem like the monkeys maybe need a token economy in 373 00:19:56,036 --> 00:19:58,956 Speaker 1: their own social system. They kind of have an economy 374 00:19:58,996 --> 00:20:01,756 Speaker 1: that works. They have this really strict dominance hierarchy, and 375 00:20:01,796 --> 00:20:04,596 Speaker 1: that determines who gets goods and services. So in other words, 376 00:20:04,596 --> 00:20:06,476 Speaker 1: you know, if you're a low ranking mail and you 377 00:20:06,476 --> 00:20:08,436 Speaker 1: had a big wallet of tokens, if the alpha male 378 00:20:08,476 --> 00:20:10,996 Speaker 1: saw that, you might kind of naturally let them go 379 00:20:11,076 --> 00:20:12,876 Speaker 1: and let him take it, because you know, that's the 380 00:20:12,916 --> 00:20:15,756 Speaker 1: social system you're part of. You know, it's equivalent to 381 00:20:15,796 --> 00:20:18,116 Speaker 1: you know, human systems of you know, back in the 382 00:20:18,196 --> 00:20:20,876 Speaker 1: days of feudalism and these kinds of things where only 383 00:20:20,916 --> 00:20:23,796 Speaker 1: certain individuals are supposed to get access to goods and services. 384 00:20:24,036 --> 00:20:25,916 Speaker 1: So in some ways it kind of taught us that, 385 00:20:25,996 --> 00:20:29,676 Speaker 1: you know, to be a species that uses money, you 386 00:20:29,756 --> 00:20:39,036 Speaker 1: really have to be a relatively egalitarian species. One of 387 00:20:39,076 --> 00:20:41,676 Speaker 1: the next questions Laurie wanted to answer, it gets at 388 00:20:41,716 --> 00:20:45,436 Speaker 1: the heart of how humans make economic decisions. The economics 389 00:20:45,436 --> 00:20:48,396 Speaker 1: has long rested on the idea that humans are rational 390 00:20:48,636 --> 00:20:51,396 Speaker 1: when money is involved, but we now have plenty of 391 00:20:51,436 --> 00:20:56,236 Speaker 1: evidence that this often isn't the case. Humans are amazing species, 392 00:20:56,276 --> 00:20:58,796 Speaker 1: but you know, pick up any article of the economists 393 00:20:58,836 --> 00:21:00,556 Speaker 1: and you figure out that we're not great at money. 394 00:21:00,596 --> 00:21:02,956 Speaker 1: You know, we kind of mess up a lot of times. 395 00:21:02,996 --> 00:21:06,076 Speaker 1: You know, we overpay attention to losses and risk, we 396 00:21:06,116 --> 00:21:09,796 Speaker 1: don't necessarily invest rationally. And researchers have found a set 397 00:21:09,836 --> 00:21:12,876 Speaker 1: of standard cognitive biases that humans show in the markets, 398 00:21:13,516 --> 00:21:15,276 Speaker 1: and so we wanted to use the monkey market to 399 00:21:15,276 --> 00:21:17,556 Speaker 1: see if monkeys are biased in the same way as 400 00:21:17,636 --> 00:21:20,276 Speaker 1: humans are. And to do that, we gave them options 401 00:21:20,316 --> 00:21:23,676 Speaker 1: that objectively gave them similar outcomes, so they would get 402 00:21:23,716 --> 00:21:27,676 Speaker 1: the same amount of food, but those options were framed differently. Basically, 403 00:21:27,676 --> 00:21:31,036 Speaker 1: we're stealing from classic work in human psychology with adult 404 00:21:31,076 --> 00:21:34,396 Speaker 1: participants from people like Danny Koneman and Amos t Verski, 405 00:21:35,156 --> 00:21:38,316 Speaker 1: who gave people problems where things were framed as gains 406 00:21:38,356 --> 00:21:42,516 Speaker 1: or losses. Danny Koneman and Amos to Verski famously found 407 00:21:42,516 --> 00:21:45,076 Speaker 1: that people don't think of gains and losses the same way. 408 00:21:45,916 --> 00:21:47,676 Speaker 1: Let's say I was going to give you ten dollars. 409 00:21:48,156 --> 00:21:50,436 Speaker 1: In one scenario, I tell you I'm going to give 410 00:21:50,476 --> 00:21:55,116 Speaker 1: you fifteen dollars and instead give you ten. In another scenario, 411 00:21:55,476 --> 00:21:57,996 Speaker 1: I tell you I'm going to give you five dollars 412 00:21:58,036 --> 00:22:01,716 Speaker 1: and instead give you ten. In both scenarios, you receive 413 00:22:01,796 --> 00:22:05,956 Speaker 1: the same amount ten dollars, but they feel different. In 414 00:22:05,956 --> 00:22:08,556 Speaker 1: one case, you feel something's being taken away from you, 415 00:22:09,236 --> 00:22:12,556 Speaker 1: in the other, you feel like you got a little extra. 416 00:22:13,596 --> 00:22:16,796 Speaker 1: Laurie wanted to see if monkeys responded the same way, 417 00:22:17,276 --> 00:22:18,996 Speaker 1: and so to do that, we would show monkeys a 418 00:22:19,036 --> 00:22:21,916 Speaker 1: case where ultimately they're going to get, say, two pieces 419 00:22:21,916 --> 00:22:24,636 Speaker 1: of food, but that two pieces of food is framed differently. 420 00:22:24,756 --> 00:22:26,836 Speaker 1: One experiment or just shows two pieces of food and 421 00:22:26,876 --> 00:22:29,196 Speaker 1: the monkeys get too, so that's kind of what they expect, 422 00:22:29,476 --> 00:22:32,276 Speaker 1: whereas another experiment or say shows three pieces of food 423 00:22:32,476 --> 00:22:34,476 Speaker 1: and then the monkey only gets two pieces of food. 424 00:22:34,956 --> 00:22:37,316 Speaker 1: And that second case, you know, you get the same 425 00:22:37,316 --> 00:22:39,476 Speaker 1: amount of food in the end, but it kind of 426 00:22:39,476 --> 00:22:42,196 Speaker 1: feels like you lost something. And what we would find 427 00:22:42,236 --> 00:22:44,556 Speaker 1: and studies like that is that the monkeys seem to 428 00:22:44,596 --> 00:22:47,796 Speaker 1: systematically avoid the loss, even though they were getting the 429 00:22:47,796 --> 00:22:50,036 Speaker 1: same amount of food, They would avoid the guy that 430 00:22:50,076 --> 00:22:52,476 Speaker 1: gave them what felt like a loss. And this is 431 00:22:52,556 --> 00:22:54,676 Speaker 1: exactly what humans seem to do in a lot of 432 00:22:54,756 --> 00:22:58,276 Speaker 1: standard decision making studies. We tend to avoid losses even 433 00:22:58,276 --> 00:23:00,316 Speaker 1: when they're not objectively a loss, even when they're just 434 00:23:00,396 --> 00:23:04,596 Speaker 1: framed that way. And what about the situation where maybe 435 00:23:04,596 --> 00:23:08,036 Speaker 1: someone showed only one item of food, but when the 436 00:23:08,036 --> 00:23:12,236 Speaker 1: monkey paid up potoke, the monkey got too. Yeah, And 437 00:23:12,276 --> 00:23:14,116 Speaker 1: so the monkeys also seemed to pay a little bit 438 00:23:14,116 --> 00:23:17,516 Speaker 1: of attention to gains what looked like gains. In fact, 439 00:23:17,916 --> 00:23:20,476 Speaker 1: what we gave the monkeys a choice between was a 440 00:23:20,516 --> 00:23:23,316 Speaker 1: gain that they would get for sure, so a sure 441 00:23:23,396 --> 00:23:27,436 Speaker 1: gain and a risky gain. Let me give you the 442 00:23:27,436 --> 00:23:29,996 Speaker 1: following problem that was given to humans by comment Versky. 443 00:23:30,276 --> 00:23:31,996 Speaker 1: I'm first going to give you a thousand dollars, which 444 00:23:31,996 --> 00:23:33,876 Speaker 1: seems great, but now you're going to have to figure 445 00:23:33,916 --> 00:23:36,116 Speaker 1: out a way to get more money. On one hand, 446 00:23:36,156 --> 00:23:38,636 Speaker 1: you could just get five hundred extra dollars with certainty, 447 00:23:38,716 --> 00:23:41,116 Speaker 1: so you get fifteen hundred dollars. Or you could take 448 00:23:41,116 --> 00:23:43,076 Speaker 1: a risk. I'm going to flip a coin and if 449 00:23:43,116 --> 00:23:45,396 Speaker 1: it comes up heads, you get another thousand dollars, but 450 00:23:45,516 --> 00:23:48,516 Speaker 1: tails you get nothing. When you pitch this problem to 451 00:23:48,836 --> 00:23:51,796 Speaker 1: most undergraduates, most people pick the safe option. There. They 452 00:23:51,796 --> 00:23:53,556 Speaker 1: want to go with the gain that they get for sure. 453 00:23:54,276 --> 00:23:56,596 Speaker 1: And that's the problem we gave to monkeys. We gave 454 00:23:56,636 --> 00:23:59,276 Speaker 1: them a choice between a sure gain, like they saw 455 00:23:59,356 --> 00:24:00,876 Speaker 1: one piece of food but knew they were going to 456 00:24:00,956 --> 00:24:03,356 Speaker 1: get too, versus a risky option where they saw one 457 00:24:03,356 --> 00:24:04,836 Speaker 1: piece of food and they were always going to get 458 00:24:04,876 --> 00:24:07,356 Speaker 1: that one, but they might get two extra ones in 459 00:24:07,396 --> 00:24:10,396 Speaker 1: a risky way. So the objective was exactly the same. 460 00:24:10,756 --> 00:24:13,356 Speaker 1: All that varied was their risk, And what we found 461 00:24:13,396 --> 00:24:16,236 Speaker 1: was that the monkeys selectively shocked at the person who 462 00:24:16,236 --> 00:24:19,436 Speaker 1: gave them the safe bet. They, like humans, avoided risk 463 00:24:19,836 --> 00:24:22,476 Speaker 1: when they were in a situation that seemed framed like 464 00:24:22,596 --> 00:24:25,396 Speaker 1: a gain. But all that change when we made the 465 00:24:25,436 --> 00:24:30,836 Speaker 1: situation more about losses, and so you can experience this yourself. 466 00:24:30,876 --> 00:24:32,876 Speaker 1: You know. Imagine I'm going to start you with two 467 00:24:32,916 --> 00:24:35,996 Speaker 1: thousand dollars, and your choices are how to lose this money. 468 00:24:36,316 --> 00:24:38,556 Speaker 1: One option is that you can lose it with certainty, 469 00:24:38,676 --> 00:24:41,716 Speaker 1: so I just take five hundred dollars away. But another 470 00:24:41,756 --> 00:24:43,676 Speaker 1: option is that you can take a risk. I'm going 471 00:24:43,716 --> 00:24:45,836 Speaker 1: to flip a coin. If it comes up heads, that's bad. 472 00:24:45,876 --> 00:24:48,956 Speaker 1: You lose a thousand dollars. Tails you lose nothing. And 473 00:24:48,996 --> 00:24:51,836 Speaker 1: so objectively the amounts are the same. On average, you'll 474 00:24:51,836 --> 00:24:55,396 Speaker 1: get fifteen hundred dollars. But in practice, now that loss 475 00:24:55,436 --> 00:24:58,476 Speaker 1: seems kind of yucky. Most people actually, when given that choice, 476 00:24:58,756 --> 00:25:01,316 Speaker 1: avoid the loss. And what we found when we gave 477 00:25:01,316 --> 00:25:05,636 Speaker 1: the monkeys qualitatively similar economic situations is that they also 478 00:25:05,716 --> 00:25:09,036 Speaker 1: avoided the loss. And that's what's irrational. They're switching their 479 00:25:09,236 --> 00:25:13,396 Speaker 1: choice about risk depending on how a problem is arbitrarily framed. 480 00:25:14,156 --> 00:25:16,716 Speaker 1: In otherwise, they took the safe option when it was 481 00:25:16,756 --> 00:25:19,436 Speaker 1: framed as a gain, they took the risky option when 482 00:25:19,476 --> 00:25:21,676 Speaker 1: it was framed as a loss. That's exactly right, And 483 00:25:21,716 --> 00:25:24,636 Speaker 1: what's surprising is that's exactly the same bias that we 484 00:25:24,716 --> 00:25:27,636 Speaker 1: see in housing markets. That's the exact same bias that 485 00:25:27,676 --> 00:25:30,556 Speaker 1: we see on the golf course. People actually put differently 486 00:25:31,116 --> 00:25:32,716 Speaker 1: when they're putting and they know they're going to go 487 00:25:32,756 --> 00:25:36,076 Speaker 1: overpar versus underpar. It seems to be a basic bias 488 00:25:36,116 --> 00:25:38,596 Speaker 1: we have and how we as humans frame the world. 489 00:25:38,916 --> 00:25:40,876 Speaker 1: And what this study showed was that monkeys seem to 490 00:25:40,916 --> 00:25:44,716 Speaker 1: have exactly that same bias. So researchers like Danny Kaneman 491 00:25:44,756 --> 00:25:47,836 Speaker 1: have also studied something called the endowment effect. What is 492 00:25:47,836 --> 00:25:49,716 Speaker 1: the endowment effect and do we see the same thing 493 00:25:49,796 --> 00:25:53,196 Speaker 1: among monkeys. Yeah, the endowment effect is a bias where 494 00:25:53,196 --> 00:25:56,316 Speaker 1: we overvalue things that we own. You know, that old 495 00:25:56,356 --> 00:25:57,916 Speaker 1: couch that you've had in your house. You know, if 496 00:25:57,956 --> 00:26:00,276 Speaker 1: somebody were to offer you some money on ebate, they 497 00:26:00,356 --> 00:26:02,556 Speaker 1: might think it's kind of, you know, a little ratty, 498 00:26:02,876 --> 00:26:05,636 Speaker 1: but you think, because you own it, it's amazing. This 499 00:26:05,676 --> 00:26:07,876 Speaker 1: is a bias we see playing out all different parts 500 00:26:07,916 --> 00:26:10,636 Speaker 1: of the market in h cultures, and we wanted to 501 00:26:10,636 --> 00:26:13,396 Speaker 1: see whether monkeys had that bias too. What we basically 502 00:26:13,396 --> 00:26:16,076 Speaker 1: did was to give monkeys different food items, so now 503 00:26:16,076 --> 00:26:18,716 Speaker 1: they're trading foods rather than tokens, and we wanted to 504 00:26:18,716 --> 00:26:21,076 Speaker 1: see whether monkeys would give up their piece of food 505 00:26:21,396 --> 00:26:24,116 Speaker 1: for an equivalent piece of food. And what we found 506 00:26:24,156 --> 00:26:26,036 Speaker 1: was that they didn't seem to want to do that, 507 00:26:26,396 --> 00:26:28,476 Speaker 1: even when we upped the anties such that the food 508 00:26:28,476 --> 00:26:31,236 Speaker 1: we were giving them was many many, many times as 509 00:26:31,316 --> 00:26:34,516 Speaker 1: valuable as the food that they had. At one level, 510 00:26:34,556 --> 00:26:36,236 Speaker 1: we were so interested in seeing if we could get 511 00:26:36,236 --> 00:26:39,076 Speaker 1: the monkeys to trade back their food that we offered 512 00:26:39,076 --> 00:26:41,396 Speaker 1: them in contrast to like a small piece of grape 513 00:26:41,836 --> 00:26:44,156 Speaker 1: what we called the fluff taco, which is a fruit 514 00:26:44,236 --> 00:26:46,836 Speaker 1: roll up filled with marshmallow fluff. It's about the sweetest 515 00:26:46,876 --> 00:26:48,596 Speaker 1: thing you can offer a monkey and a small go 516 00:26:49,116 --> 00:26:51,956 Speaker 1: And even in that case, they still wouldn't trade their 517 00:26:52,156 --> 00:26:54,196 Speaker 1: piece of food that they were endowed with for a 518 00:26:54,236 --> 00:26:58,476 Speaker 1: different piece of food. So humans and Kipuchin monkeys shared 519 00:26:58,476 --> 00:27:02,076 Speaker 1: a common ancestor tens of millions of years ago. What 520 00:27:02,116 --> 00:27:04,156 Speaker 1: does it tell us that we see loss of version 521 00:27:04,356 --> 00:27:07,196 Speaker 1: or the endowment effect in monkeys as well as humans. 522 00:27:07,716 --> 00:27:09,836 Speaker 1: I mean, I think it tells us that whatever cognitive 523 00:27:09,876 --> 00:27:12,236 Speaker 1: strategies we're using, you know, when we go to the 524 00:27:12,276 --> 00:27:15,756 Speaker 1: grocery store to buy our food, those mechanisms aren't just 525 00:27:15,876 --> 00:27:19,556 Speaker 1: mechanisms that are built for using money. Like those mechanisms 526 00:27:19,556 --> 00:27:23,676 Speaker 1: are mechanisms that we've been using to frame decisions for millennia. Right, 527 00:27:23,716 --> 00:27:26,556 Speaker 1: The mechanisms that we use when we're making quick purchases 528 00:27:26,556 --> 00:27:29,316 Speaker 1: online are the same as the mechanisms monkeys must be 529 00:27:29,396 --> 00:27:31,916 Speaker 1: using when they're foraging and so on. So I think 530 00:27:31,916 --> 00:27:34,316 Speaker 1: it tells us that the strategies we're using are really 531 00:27:34,356 --> 00:27:37,196 Speaker 1: really old, and that gives us some hints about what 532 00:27:37,236 --> 00:27:39,676 Speaker 1: those strategies might be for and whether or not we 533 00:27:39,676 --> 00:27:48,956 Speaker 1: should really consider them irrational. I was going to ask 534 00:27:48,956 --> 00:27:50,596 Speaker 1: you that question. I mean, we think of these as 535 00:27:50,636 --> 00:27:53,316 Speaker 1: being examples of bias or error, but the fact that 536 00:27:53,356 --> 00:27:56,516 Speaker 1: they're really ancient suggest that perhaps they played a useful 537 00:27:56,596 --> 00:27:59,996 Speaker 1: role at least in our evolutionary past, if not the present. Yeah, 538 00:28:00,036 --> 00:28:01,916 Speaker 1: I mean, you'd think if they were that harmful, they 539 00:28:01,956 --> 00:28:03,956 Speaker 1: would have been selected out. You know, monkeys who use 540 00:28:04,316 --> 00:28:06,716 Speaker 1: loss of version versus some other bias you know, might 541 00:28:06,756 --> 00:28:09,036 Speaker 1: not do as well, kind of you know, real monkey mark. 542 00:28:09,156 --> 00:28:11,876 Speaker 1: It's out there in the evolutionary world. I think that's 543 00:28:11,876 --> 00:28:14,156 Speaker 1: one possibility. I think, you know, when you think about 544 00:28:14,156 --> 00:28:16,596 Speaker 1: what could a bias like that be useful for, it 545 00:28:16,636 --> 00:28:19,036 Speaker 1: turns out that it's hard to think in objective terms 546 00:28:19,036 --> 00:28:22,276 Speaker 1: in the world. Sometimes there's a strategy where you think relative, 547 00:28:22,356 --> 00:28:25,156 Speaker 1: like relative to someone else's option, a relative to a 548 00:28:25,156 --> 00:28:28,436 Speaker 1: reference point. Those strategies can be better. So imagine the 549 00:28:28,476 --> 00:28:31,476 Speaker 1: following scenario. You're you're instantly a Kapuchin monkey, and you 550 00:28:31,516 --> 00:28:33,356 Speaker 1: have to figure out how much food to get today. 551 00:28:33,596 --> 00:28:35,716 Speaker 1: You know, you're forging for nuts. How many nuts should 552 00:28:35,716 --> 00:28:37,956 Speaker 1: you go for and when should you stop? You know, 553 00:28:37,996 --> 00:28:40,476 Speaker 1: it's a hard problem. But if you see that I'm 554 00:28:40,556 --> 00:28:43,236 Speaker 1: walking around with three nuts and Joe Monkey's walking around 555 00:28:43,236 --> 00:28:45,476 Speaker 1: with three nuts, then maybe shooting for three nuts is 556 00:28:45,476 --> 00:28:47,196 Speaker 1: pretty good. Maybe if you only get two, you should 557 00:28:47,196 --> 00:28:49,356 Speaker 1: work a little harder and feel bad. But if you 558 00:28:49,396 --> 00:28:51,436 Speaker 1: get four, I shouldn't You know, you don't need to celebrate. 559 00:28:51,516 --> 00:28:53,636 Speaker 1: That was just good. And so it might be that 560 00:28:53,756 --> 00:28:56,436 Speaker 1: strategies like loss a version, where you really are comparing 561 00:28:56,476 --> 00:28:59,356 Speaker 1: against other people and then you have mechanisms to motivate 562 00:28:59,396 --> 00:29:01,676 Speaker 1: you not to go under what other people have, those 563 00:29:01,756 --> 00:29:04,036 Speaker 1: might have been more useful than we think. It's just 564 00:29:04,076 --> 00:29:05,996 Speaker 1: when we throw them into stock markets that they kind 565 00:29:05,996 --> 00:29:09,676 Speaker 1: of look a little quirky, you know. We had Heath Pain, 566 00:29:09,956 --> 00:29:14,036 Speaker 1: the psychologist on Hidden Brain, recently talking about how inequality 567 00:29:14,116 --> 00:29:17,316 Speaker 1: works in the psychology of inequality, and in some ways 568 00:29:17,636 --> 00:29:20,796 Speaker 1: you and others have found that monkeys exhibit some of 569 00:29:20,836 --> 00:29:23,716 Speaker 1: the same behavior. They pay very very close attention, as 570 00:29:23,716 --> 00:29:26,076 Speaker 1: in the analogy you just gave me, to what other 571 00:29:26,116 --> 00:29:29,596 Speaker 1: monkeys have and whether what they have in relative terms 572 00:29:29,956 --> 00:29:32,836 Speaker 1: is fair. I think that's right. I mean, there's some 573 00:29:32,876 --> 00:29:36,116 Speaker 1: classic work by their researchers, Sarah Brosnon and Franz to all. 574 00:29:36,436 --> 00:29:38,516 Speaker 1: They find that monkeys don't just pay attention to what 575 00:29:38,556 --> 00:29:40,676 Speaker 1: other individuals have when they feel like they're getting a 576 00:29:40,756 --> 00:29:43,156 Speaker 1: raw deal. You know, if you're unlikey who's getting kind 577 00:29:43,196 --> 00:29:46,076 Speaker 1: of a yucky cucumber when another monkey's getting a grape, 578 00:29:46,356 --> 00:29:49,116 Speaker 1: you actually reject that offer. So it's not just that 579 00:29:49,556 --> 00:29:52,316 Speaker 1: monkeys sort of experience things like, hey, that's unfair, they 580 00:29:52,356 --> 00:29:54,996 Speaker 1: actually act on it in ways that reduce the number 581 00:29:54,996 --> 00:30:01,876 Speaker 1: of resources they have. When we come back experiments that 582 00:30:01,956 --> 00:30:04,956 Speaker 1: show what other animals do differently than us, and the 583 00:30:05,036 --> 00:30:26,836 Speaker 1: psychological quirks that make us uniquely human. In the eighteen hundreds, 584 00:30:26,956 --> 00:30:30,036 Speaker 1: a British inventor named William Henry Talbot was so caught 585 00:30:30,116 --> 00:30:32,876 Speaker 1: up in his work that he and his wife had 586 00:30:32,916 --> 00:30:36,916 Speaker 1: to delay their honeymoon Eventually they did go, winding their 587 00:30:36,916 --> 00:30:41,436 Speaker 1: way through Europe to Italy. He was mesmerized by Lake Como, 588 00:30:41,716 --> 00:30:45,276 Speaker 1: with its wishbone shape and its backdrop of the Alps. 589 00:30:46,156 --> 00:30:48,796 Speaker 1: He was neither the first nor the last to be 590 00:30:48,956 --> 00:30:50,996 Speaker 1: enchanted by the view. It was even a lake that 591 00:30:51,036 --> 00:30:53,236 Speaker 1: George Lucas used in one of the Star Wars movies 592 00:30:53,316 --> 00:30:57,156 Speaker 1: when Padmi and Anakin were getting together. We used to 593 00:30:57,196 --> 00:30:59,076 Speaker 1: lie out on the sand and let the sun gi 594 00:30:59,236 --> 00:31:02,796 Speaker 1: us and try to guess the names of the birds singing. 595 00:31:06,196 --> 00:31:10,916 Speaker 1: I don't like sound, its course, and he allegedly didn't 596 00:31:10,956 --> 00:31:15,716 Speaker 1: use any CGI on that scene. William Henry Talbot wanted 597 00:31:15,756 --> 00:31:18,676 Speaker 1: to capture the moment and share it with others, but 598 00:31:18,756 --> 00:31:21,956 Speaker 1: it was the nineteenth century cameras as we know them 599 00:31:22,276 --> 00:31:27,836 Speaker 1: didn't exist. What he had was something called a camera lucida, 600 00:31:27,916 --> 00:31:29,676 Speaker 1: which is like, you know a little device that you 601 00:31:29,716 --> 00:31:31,836 Speaker 1: can use to kind of sketch things. It's kind of 602 00:31:31,836 --> 00:31:34,836 Speaker 1: like the iPhone eleven of his time, and he made 603 00:31:34,836 --> 00:31:38,036 Speaker 1: an amazing sketch. One that's very famous because he was 604 00:31:38,236 --> 00:31:41,436 Speaker 1: very disappointed with his sketch. He allegedly said it was 605 00:31:41,436 --> 00:31:43,476 Speaker 1: a melancholy to behold, which is not what you want 606 00:31:43,476 --> 00:31:47,556 Speaker 1: to say about your honeymoons, and it caused him to 607 00:31:47,596 --> 00:31:50,436 Speaker 1: start thinking about what it would be like, what technology 608 00:31:50,476 --> 00:31:54,036 Speaker 1: could actually let images that he saw in his version 609 00:31:54,076 --> 00:31:56,756 Speaker 1: of a camera to stick on paper, and it led 610 00:31:56,836 --> 00:31:58,876 Speaker 1: him to be one of the first developers of a 611 00:31:58,916 --> 00:32:02,076 Speaker 1: lot of the photo technology that we use in real 612 00:32:02,076 --> 00:32:07,276 Speaker 1: cameras today. William Henry Talbot's pioneering techniques and photography tell 613 00:32:07,356 --> 00:32:11,196 Speaker 1: us something about how humans we have an impulse to 614 00:32:11,236 --> 00:32:13,716 Speaker 1: share with others what is going on in our heads, 615 00:32:14,196 --> 00:32:19,796 Speaker 1: our feelings, our experiences, our perspectives. Laurie things this might 616 00:32:19,836 --> 00:32:22,876 Speaker 1: be an important area of difference with other animals. I 617 00:32:22,876 --> 00:32:25,956 Speaker 1: think even if animals had had photographs, they wouldn't use them. 618 00:32:26,036 --> 00:32:27,756 Speaker 1: You know, if they had their iPhone eleven, they wouldn't 619 00:32:27,756 --> 00:32:30,956 Speaker 1: take pictures. And it's so funny when you realize that, 620 00:32:30,996 --> 00:32:34,076 Speaker 1: because you know, that urge to share stuff is such 621 00:32:34,076 --> 00:32:36,516 Speaker 1: a very human urge. You know, it's one that researchers 622 00:32:36,556 --> 00:32:39,876 Speaker 1: like Mike Thomas Ello and colleagues fine emerges like within 623 00:32:39,956 --> 00:32:42,236 Speaker 1: the first year of life, babies are already starting to 624 00:32:42,276 --> 00:32:44,196 Speaker 1: point at things and trying to get their parents to 625 00:32:44,236 --> 00:32:48,596 Speaker 1: look and so it's a very, very fundamental urge, and remarkably, 626 00:32:48,596 --> 00:32:51,716 Speaker 1: it seems to be one that's unique to humans. And 627 00:32:51,756 --> 00:32:53,756 Speaker 1: you can see this so strikingly when you watch the 628 00:32:53,796 --> 00:32:56,956 Speaker 1: behavior of you know, mother primates and their kids, like 629 00:32:57,316 --> 00:32:59,836 Speaker 1: they just don't tend to show each other stuff, Like 630 00:32:59,876 --> 00:33:02,436 Speaker 1: there's just not like active teaching or even active like 631 00:33:02,476 --> 00:33:04,436 Speaker 1: hey mom, look at this, look at me. They kind 632 00:33:04,436 --> 00:33:08,116 Speaker 1: of just don't care. How do these differences reveal themselves 633 00:33:08,116 --> 00:33:11,436 Speaker 1: and experiments, especially when it comes to certain mistakes that 634 00:33:11,796 --> 00:33:16,916 Speaker 1: perhaps monkeys, chims and dogs don't make that humans do make. Well. 635 00:33:16,916 --> 00:33:19,356 Speaker 1: I think one of the consequences of being a species 636 00:33:19,356 --> 00:33:21,596 Speaker 1: that shares a lot of stuff is that we also 637 00:33:21,636 --> 00:33:24,356 Speaker 1: are probably a species that believes a lot of stuff. 638 00:33:24,596 --> 00:33:26,996 Speaker 1: You know, we want to share because it affects what 639 00:33:27,076 --> 00:33:29,476 Speaker 1: others learn, and that suggests that we might be a 640 00:33:29,476 --> 00:33:32,796 Speaker 1: species that kind of can overlearn based on when we're 641 00:33:32,836 --> 00:33:36,476 Speaker 1: getting information from others. In other words, we really are 642 00:33:36,716 --> 00:33:40,036 Speaker 1: liable to believe the stuff that we're hearing from other individuals, 643 00:33:40,036 --> 00:33:42,436 Speaker 1: you know. That's why the sharing feels so powerful. But 644 00:33:42,556 --> 00:33:44,836 Speaker 1: given that sharing is kind of in beta testing, it 645 00:33:44,956 --> 00:33:47,276 Speaker 1: suggests that the learning might be in beta testing too, 646 00:33:47,756 --> 00:33:49,796 Speaker 1: and so the way that researchers have tried to test 647 00:33:49,876 --> 00:33:52,716 Speaker 1: this is to ask whether or not humans are prone 648 00:33:52,716 --> 00:33:56,476 Speaker 1: to overlearn when they get bad information from others. It's 649 00:33:56,516 --> 00:33:59,596 Speaker 1: a it's a tendency that researchers call over imitation, the 650 00:33:59,676 --> 00:34:03,156 Speaker 1: tendency to imitate too much. And so here's the study. 651 00:34:03,716 --> 00:34:06,596 Speaker 1: You bring human children in chimpanzees into the lab. This 652 00:34:06,716 --> 00:34:08,916 Speaker 1: is work done by Vicki Horner and her colleagues, and 653 00:34:09,156 --> 00:34:11,796 Speaker 1: you give them access to a little puzzle box. In 654 00:34:11,796 --> 00:34:14,036 Speaker 1: some cases, the puzzle box is opaque, it's hard to 655 00:34:14,076 --> 00:34:15,956 Speaker 1: figure out how it opens up. But they get to 656 00:34:15,956 --> 00:34:18,116 Speaker 1: see a human experiment or who helps them, and the 657 00:34:18,196 --> 00:34:21,036 Speaker 1: human are experiment or does all these different actions on 658 00:34:21,076 --> 00:34:22,916 Speaker 1: the box. You have to tap a lever at the 659 00:34:22,956 --> 00:34:25,676 Speaker 1: top and stick a tool in, and it's very, very elaborate. 660 00:34:26,116 --> 00:34:29,196 Speaker 1: What you find is that when kids and chimpanzees see that, 661 00:34:29,556 --> 00:34:32,716 Speaker 1: they copy pretty slavishly everything the human does. And that 662 00:34:32,796 --> 00:34:34,876 Speaker 1: kind of copying makes sense because they don't know how 663 00:34:34,916 --> 00:34:37,516 Speaker 1: to open the box. But in a different condition, all 664 00:34:37,556 --> 00:34:40,996 Speaker 1: that changes. Now you give kids in chimpanzees a transparent 665 00:34:41,076 --> 00:34:44,276 Speaker 1: puzzle box, and because it's transparent, it's really obvious how 666 00:34:44,276 --> 00:34:45,996 Speaker 1: to open it. There's just a door, and you open 667 00:34:46,036 --> 00:34:48,716 Speaker 1: the door. There's nothing else in the box. The subjects 668 00:34:48,756 --> 00:34:52,236 Speaker 1: also get to see this experiment, are painstakingly trying to 669 00:34:52,236 --> 00:34:54,836 Speaker 1: open the box, you know, using all these levers, using 670 00:34:54,876 --> 00:34:57,156 Speaker 1: tools inside it, and so on. But you can see 671 00:34:57,276 --> 00:35:00,276 Speaker 1: those actions aren't doing anything. What you find is that 672 00:35:00,356 --> 00:35:03,556 Speaker 1: the chimpanzees are pretty rational on this task. They completely 673 00:35:03,556 --> 00:35:06,036 Speaker 1: ignore what the human did on the transparent box and 674 00:35:06,076 --> 00:35:09,076 Speaker 1: just solve it in the really easy way. But sadly, 675 00:35:09,276 --> 00:35:12,596 Speaker 1: perhaps for our species, human children don't do that. They 676 00:35:12,676 --> 00:35:16,876 Speaker 1: slavishly follow everything they see the human doing. They overimitate 677 00:35:16,956 --> 00:35:21,316 Speaker 1: these actions, suggesting that when you see another individual doing something, 678 00:35:21,516 --> 00:35:24,956 Speaker 1: especially intentionally, it messes up the way you think about 679 00:35:24,956 --> 00:35:27,036 Speaker 1: the world. In the case of the children, it messes 680 00:35:27,076 --> 00:35:29,596 Speaker 1: up the way they think the box works. There's also 681 00:35:29,636 --> 00:35:32,356 Speaker 1: been some work, i think, looking at a sort of 682 00:35:32,436 --> 00:35:35,116 Speaker 1: child development showing that when children are shown how a 683 00:35:35,156 --> 00:35:38,316 Speaker 1: certain toy works a certain way, they become it's really 684 00:35:38,316 --> 00:35:41,556 Speaker 1: difficult for them to actually explore the toy and actually 685 00:35:41,556 --> 00:35:43,716 Speaker 1: play with it in a different way that they actually believe. Okay, 686 00:35:43,716 --> 00:35:45,676 Speaker 1: now I've been shown this is how the toy works, 687 00:35:45,996 --> 00:35:48,436 Speaker 1: this is how I have to play with it. That's 688 00:35:48,436 --> 00:35:50,796 Speaker 1: exactly right. This is some lovely work by Liz Bonowich 689 00:35:50,796 --> 00:35:53,156 Speaker 1: which is shown that when children are taught something, it 690 00:35:53,236 --> 00:35:55,876 Speaker 1: limits their exploration. So if they're given a puzzle box 691 00:35:55,916 --> 00:35:58,436 Speaker 1: with lots of different knobs and interesting things, and a 692 00:35:58,516 --> 00:36:00,956 Speaker 1: teacher comes and says, hey, here, this is how it works, 693 00:36:01,076 --> 00:36:03,756 Speaker 1: and just presses one of the buttons, when children interact 694 00:36:03,756 --> 00:36:06,236 Speaker 1: with that box, they'll just press that button. Even though 695 00:36:06,276 --> 00:36:08,476 Speaker 1: all these other levers and cool things also make the 696 00:36:08,516 --> 00:36:11,276 Speaker 1: toy do interest stuff. Kids never find it, and so 697 00:36:11,316 --> 00:36:13,756 Speaker 1: it seems like teaching We often think of as this 698 00:36:13,796 --> 00:36:15,756 Speaker 1: wonderful thing, and of course it is, you know, of course, 699 00:36:15,756 --> 00:36:17,796 Speaker 1: this is the way we learn so much about our 700 00:36:17,796 --> 00:36:19,996 Speaker 1: culture and how to do things in the world. But 701 00:36:20,076 --> 00:36:22,076 Speaker 1: there's a downside to it, which is that we don't 702 00:36:22,116 --> 00:36:25,076 Speaker 1: have mechanisms to be critical about the things we're hearing 703 00:36:25,076 --> 00:36:35,196 Speaker 1: from other humans. There's something humans do that's so intuitive 704 00:36:35,556 --> 00:36:38,716 Speaker 1: it's hard to even recognize that we're doing it. We 705 00:36:38,796 --> 00:36:42,556 Speaker 1: can believe one thing I can understand. Another person might 706 00:36:42,636 --> 00:36:46,196 Speaker 1: believe something entirely different. Imagine that you ask a friend 707 00:36:46,236 --> 00:36:48,836 Speaker 1: what day it is. She tells you it's the twenty. 708 00:36:48,876 --> 00:36:53,396 Speaker 1: First you check your calendar and realize it's actually the twentieth. 709 00:36:54,236 --> 00:36:57,716 Speaker 1: You're capable of understanding that it is the twentieth by 710 00:36:57,756 --> 00:37:00,956 Speaker 1: that your friend believes something else. We can constantly think 711 00:37:00,996 --> 00:37:04,756 Speaker 1: about these cases where other people have misinformation, you know, otherwise, 712 00:37:04,796 --> 00:37:06,796 Speaker 1: you know, Romeo and Juliet would make no sense. You know, 713 00:37:06,916 --> 00:37:09,676 Speaker 1: Juliet didn't know that Romeo was alive, and all these 714 00:37:09,676 --> 00:37:11,836 Speaker 1: things that I forget from my high school English class. Right. 715 00:37:12,116 --> 00:37:13,916 Speaker 1: But this is the kind of thing we do all 716 00:37:13,956 --> 00:37:17,236 Speaker 1: the time. We constantly can think about that other people 717 00:37:17,276 --> 00:37:19,756 Speaker 1: have a different belief than us. We can think about 718 00:37:19,836 --> 00:37:22,436 Speaker 1: past us and know that we had different beliefs than 719 00:37:22,476 --> 00:37:25,036 Speaker 1: we do have now. We can think about future us 720 00:37:25,036 --> 00:37:26,796 Speaker 1: and think, you know, I might have a different belief 721 00:37:26,836 --> 00:37:28,956 Speaker 1: when I'm old and gray than when I do now, 722 00:37:29,756 --> 00:37:32,516 Speaker 1: and so is. It seems so easy because it comes 723 00:37:32,516 --> 00:37:35,796 Speaker 1: so fluidly to us, But cognitively this is really tricky. 724 00:37:36,156 --> 00:37:39,196 Speaker 1: It means I have to maintain this like representation, this 725 00:37:39,316 --> 00:37:42,236 Speaker 1: information about the world that I know is really true, 726 00:37:42,636 --> 00:37:44,916 Speaker 1: versus at the same time knowing that somebody else thinks 727 00:37:44,916 --> 00:37:47,196 Speaker 1: something different. It's it's kind of a hard task when 728 00:37:47,236 --> 00:37:49,316 Speaker 1: you think about it. You know, when you think about 729 00:37:49,316 --> 00:37:51,796 Speaker 1: the movies. For example, the movies wouldn't work if we 730 00:37:51,836 --> 00:37:55,316 Speaker 1: didn't have this scale. I'm thinking about the famous shower 731 00:37:55,396 --> 00:37:58,276 Speaker 1: scene in Psycho. You know, as a member of the audience, 732 00:37:58,356 --> 00:38:00,676 Speaker 1: you know that you know the murder is about to 733 00:38:00,756 --> 00:38:02,396 Speaker 1: kill the woman in the shower, but the woman in 734 00:38:02,436 --> 00:38:04,436 Speaker 1: the shower doesn't know this, and of course that that 735 00:38:04,556 --> 00:38:08,036 Speaker 1: increases your fear and anxiety about what's happening, not just 736 00:38:08,076 --> 00:38:09,716 Speaker 1: because you know a motor is about to take place, 737 00:38:09,756 --> 00:38:12,036 Speaker 1: but because you know the victim doesn't know that a 738 00:38:12,116 --> 00:38:14,796 Speaker 1: murder is about to take place. That's exactly right. And 739 00:38:15,196 --> 00:38:18,156 Speaker 1: beyond that, you know, another feature of this ability that 740 00:38:18,196 --> 00:38:19,996 Speaker 1: we have is, you know, it allows us to do 741 00:38:20,076 --> 00:38:22,036 Speaker 1: fiction at all. You know, like you know that there's 742 00:38:22,036 --> 00:38:23,676 Speaker 1: a murder about to take place, but it's not in 743 00:38:23,716 --> 00:38:26,356 Speaker 1: your house, like you can represent that. There's a separation 744 00:38:26,516 --> 00:38:29,396 Speaker 1: between you and what you know in the moment and 745 00:38:29,556 --> 00:38:33,476 Speaker 1: other people's representations, other people's beliefs. So it's a really 746 00:38:33,476 --> 00:38:36,476 Speaker 1: fundamental capacity, and that's one of the reasons that researchers 747 00:38:36,476 --> 00:38:39,276 Speaker 1: have been so interested in whether or not non human 748 00:38:39,316 --> 00:38:41,516 Speaker 1: animals can do this. You know, how do we solve 749 00:38:41,556 --> 00:38:44,716 Speaker 1: this hard computational problem, like do we need language to 750 00:38:44,756 --> 00:38:46,636 Speaker 1: solve it, you know, is this the kind of thing 751 00:38:46,676 --> 00:38:50,476 Speaker 1: other species can look at. Testing this, though, is pretty 752 00:38:50,516 --> 00:38:53,116 Speaker 1: tricky because you have to be able to ask whether 753 00:38:53,196 --> 00:38:55,876 Speaker 1: or not a monkey knows that some other person has 754 00:38:55,876 --> 00:38:59,716 Speaker 1: a false belief, and it's hard because they can't tell you. Luckily, 755 00:38:59,796 --> 00:39:01,836 Speaker 1: we have different tricks we can use to test it, 756 00:39:02,356 --> 00:39:04,236 Speaker 1: and one of those tricks is kind of using the 757 00:39:04,276 --> 00:39:06,156 Speaker 1: same type of study we use to look at what 758 00:39:06,236 --> 00:39:09,356 Speaker 1: monkeys know about other perspectives. These kinds of studies where 759 00:39:09,556 --> 00:39:12,236 Speaker 1: monkeys see people acting in different ways based on what 760 00:39:12,316 --> 00:39:14,516 Speaker 1: they know. But in this case, we can ask how 761 00:39:14,556 --> 00:39:17,676 Speaker 1: monkeys expect people to behave based on their belief. And 762 00:39:17,756 --> 00:39:20,276 Speaker 1: here's the situation. You know, we just use this example 763 00:39:20,316 --> 00:39:23,996 Speaker 1: of me having the false belief about it raining, you know, 764 00:39:23,996 --> 00:39:26,436 Speaker 1: so imagine I think it's raining out in Newhaven. You 765 00:39:26,516 --> 00:39:29,436 Speaker 1: might have certain predictions about my behavior. You might expect 766 00:39:29,476 --> 00:39:31,836 Speaker 1: me to take an umbrella and be surprised, you know, 767 00:39:32,076 --> 00:39:34,036 Speaker 1: if I went out in like, you know, shoes that 768 00:39:34,276 --> 00:39:37,116 Speaker 1: weren't appropriate for the rain. That would surprise you because 769 00:39:37,156 --> 00:39:39,596 Speaker 1: you know something about my belief, even though that belief 770 00:39:39,676 --> 00:39:42,236 Speaker 1: is false. That was basically the logic we used to 771 00:39:42,276 --> 00:39:45,356 Speaker 1: set up a study with monkeys. Monkeys get to watch 772 00:39:45,436 --> 00:39:48,076 Speaker 1: as a person is looking for an object that she 773 00:39:48,156 --> 00:39:50,716 Speaker 1: really wants in the world, and the monkeys get to 774 00:39:51,156 --> 00:39:54,036 Speaker 1: watch this object rolling back and forth between two boxes, 775 00:39:54,076 --> 00:39:56,476 Speaker 1: a left box and a right box. So at this 776 00:39:56,516 --> 00:39:58,396 Speaker 1: point the monkey should be thinking, oh, the person's going 777 00:39:58,396 --> 00:40:00,396 Speaker 1: to reach into the left box. But then all of 778 00:40:00,436 --> 00:40:02,756 Speaker 1: a sudden, the person gets covered up. She's not paying 779 00:40:02,756 --> 00:40:06,276 Speaker 1: attention anymore, and the monkey gets his own private access 780 00:40:06,316 --> 00:40:09,036 Speaker 1: to the fact that the object that the person wants 781 00:40:09,116 --> 00:40:12,316 Speaker 1: then rolls into the right sidebox, so the monkey knows 782 00:40:12,316 --> 00:40:14,556 Speaker 1: where it's really But the question is whether or not 783 00:40:14,636 --> 00:40:18,116 Speaker 1: the monkey recognizes that the person shouldn't know where it is, 784 00:40:18,436 --> 00:40:20,956 Speaker 1: that the person should have a false belief. If the 785 00:40:20,996 --> 00:40:23,836 Speaker 1: monkey gets that, he should be surprised if the person 786 00:40:23,916 --> 00:40:26,396 Speaker 1: reaches to where the object really is because she shouldn't 787 00:40:26,436 --> 00:40:29,356 Speaker 1: know that she should have a false belief. But interestingly, 788 00:40:29,556 --> 00:40:31,796 Speaker 1: that's not what we find. What we find is that 789 00:40:31,836 --> 00:40:34,356 Speaker 1: the monkeys seem to make no prediction in that case. 790 00:40:34,756 --> 00:40:36,836 Speaker 1: And what this tells us, which is so cool, is 791 00:40:36,876 --> 00:40:39,556 Speaker 1: it tells us that the monkey is realized the person's 792 00:40:39,636 --> 00:40:42,876 Speaker 1: perspective is different from their own, but they can't simulate 793 00:40:42,876 --> 00:40:44,876 Speaker 1: what it is. In other words, they know, well, she 794 00:40:44,916 --> 00:40:46,996 Speaker 1: doesn't know what I know. Like that's why they don't 795 00:40:47,036 --> 00:40:48,716 Speaker 1: really have a prediction about where she should act. They 796 00:40:48,756 --> 00:40:51,116 Speaker 1: don't think she should reach for the object, but they 797 00:40:51,156 --> 00:41:01,436 Speaker 1: can't really simulate this other belief. So this is so 798 00:41:01,476 --> 00:41:03,916 Speaker 1: fascinating because when you think about what the monkeys were 799 00:41:03,956 --> 00:41:07,036 Speaker 1: doing on the island in Puerto Rico, and they're basically saying, 800 00:41:07,356 --> 00:41:09,716 Speaker 1: this person has her back to me, so it's going 801 00:41:09,756 --> 00:41:12,436 Speaker 1: to be easier to steal a fruit from this person 802 00:41:12,476 --> 00:41:14,876 Speaker 1: than the person who is facing me. At some level, 803 00:41:14,956 --> 00:41:17,396 Speaker 1: the monkey is able to say, I have a sense 804 00:41:17,436 --> 00:41:20,716 Speaker 1: that the person who's back is toward me knows less 805 00:41:20,716 --> 00:41:23,116 Speaker 1: than the person who is faces toward me. So they 806 00:41:23,116 --> 00:41:26,196 Speaker 1: have some sense of representation of what's happening inside the 807 00:41:26,236 --> 00:41:29,836 Speaker 1: experimenter's mind or the experimenter's knowledge, But that doesn't translate 808 00:41:29,876 --> 00:41:32,716 Speaker 1: in this experiment into what you think about are the 809 00:41:32,756 --> 00:41:35,276 Speaker 1: beliefs of the experiment and what's the distinction between those 810 00:41:35,276 --> 00:41:39,516 Speaker 1: two scenarios. Yeah, the distinction is between a case where 811 00:41:39,516 --> 00:41:42,036 Speaker 1: the monkeys simply think, oh, that person doesn't know anything, 812 00:41:42,676 --> 00:41:46,436 Speaker 1: versus that person has a very specific belief right, and 813 00:41:46,476 --> 00:41:49,076 Speaker 1: when you get back to, you know, the example you used, 814 00:41:49,436 --> 00:41:52,116 Speaker 1: the kind of the shower example, the really scary example, 815 00:41:52,476 --> 00:41:54,396 Speaker 1: the monkeys might have the same intuition and the same 816 00:41:54,396 --> 00:41:56,076 Speaker 1: reaction to that scene that we do. You know, they 817 00:41:56,076 --> 00:41:58,956 Speaker 1: would probably know the person doesn't know that you know, 818 00:41:58,956 --> 00:42:02,716 Speaker 1: a killer is coming. But what they might not be 819 00:42:02,756 --> 00:42:05,556 Speaker 1: able to represent is what the person themselves does believe. 820 00:42:05,916 --> 00:42:08,156 Speaker 1: You know, they believe they're safe in the shower, you 821 00:42:08,156 --> 00:42:09,956 Speaker 1: know that nothing's going to happen, that they're going to 822 00:42:10,036 --> 00:42:12,356 Speaker 1: be in their fine Like the monkeys seem to not 823 00:42:12,396 --> 00:42:15,116 Speaker 1: be able to simulate all the things that the person knows, 824 00:42:15,356 --> 00:42:18,516 Speaker 1: but that the monkey himself doesn't know. They know reality 825 00:42:18,636 --> 00:42:20,516 Speaker 1: in the here and now, but they can't kind of 826 00:42:20,516 --> 00:42:23,476 Speaker 1: simulate things that go beyond reality, you know, someone else's 827 00:42:23,516 --> 00:42:26,476 Speaker 1: belief that's not true of reality now or even you know, 828 00:42:26,516 --> 00:42:28,116 Speaker 1: what we're going to think in the future, or what 829 00:42:28,156 --> 00:42:31,596 Speaker 1: we thought in the past, even counterfactual situations, things that 830 00:42:31,636 --> 00:42:33,276 Speaker 1: aren't true in the here and now, but in theory 831 00:42:33,316 --> 00:42:36,196 Speaker 1: could be true. Those aren't situations about the world that 832 00:42:36,196 --> 00:42:38,516 Speaker 1: the monkeys seem to be able to simulate. That's not 833 00:42:38,556 --> 00:42:40,436 Speaker 1: the kind of thing they seem to be able to represent. 834 00:42:40,516 --> 00:42:42,756 Speaker 1: But if you think about how critical that is not 835 00:42:42,836 --> 00:42:45,396 Speaker 1: just to know someone has a different perspective, but to 836 00:42:45,436 --> 00:42:48,396 Speaker 1: know what that perspective is. It really is the crux 837 00:42:48,396 --> 00:42:51,596 Speaker 1: of human cognition in so many ways. So it's fascinating 838 00:42:51,596 --> 00:42:54,596 Speaker 1: that other animals seem not to have this. There's one 839 00:42:54,676 --> 00:42:57,556 Speaker 1: last area of difference I want to explore, which has 840 00:42:57,596 --> 00:43:01,516 Speaker 1: to do with how price shapes the perceptions of humans 841 00:43:01,516 --> 00:43:04,676 Speaker 1: and other animals. How do humans and other animals respond 842 00:43:04,716 --> 00:43:07,916 Speaker 1: when you raise the price of an object. Yeah, well, 843 00:43:07,916 --> 00:43:10,636 Speaker 1: this was another spot where we actually assumed we would 844 00:43:10,636 --> 00:43:13,836 Speaker 1: see similarity between monkeys and humans in this respect, but 845 00:43:14,156 --> 00:43:16,036 Speaker 1: it was one of the few spots in the economic 846 00:43:16,076 --> 00:43:19,356 Speaker 1: domain where we saw these big differences. You know, humans 847 00:43:19,356 --> 00:43:21,396 Speaker 1: have all kinds of theories about price, but one of 848 00:43:21,396 --> 00:43:24,996 Speaker 1: the theories we have is that more expensive things are better. 849 00:43:25,196 --> 00:43:26,676 Speaker 1: You know. This is why you know, when a new 850 00:43:26,716 --> 00:43:29,756 Speaker 1: iPhone comes out, it's often more expensive than the old iPhone, 851 00:43:29,996 --> 00:43:31,836 Speaker 1: and that kind of makes people think it's a lot 852 00:43:31,836 --> 00:43:33,876 Speaker 1: more valuable. You know. It's one of the reasons that 853 00:43:34,116 --> 00:43:36,916 Speaker 1: very very expensive wine people are all excited to try it, 854 00:43:36,956 --> 00:43:40,516 Speaker 1: not necessarily because they know it's necessarily better, but people 855 00:43:40,556 --> 00:43:43,156 Speaker 1: assume it's going to taste better. In fact, there's some 856 00:43:43,236 --> 00:43:46,756 Speaker 1: neuroscience work that you can change the pattern of firing 857 00:43:46,756 --> 00:43:49,556 Speaker 1: in the reward areas of people's brains merely by giving 858 00:43:49,596 --> 00:43:51,676 Speaker 1: them the same wine and lying to them and telling 859 00:43:51,716 --> 00:43:54,036 Speaker 1: them it was more expensive. You know. So this seems 860 00:43:54,036 --> 00:43:56,116 Speaker 1: to be a basic way that we approach price. We 861 00:43:56,156 --> 00:43:59,796 Speaker 1: assume that more expensive things have to be better, and 862 00:43:59,836 --> 00:44:01,436 Speaker 1: so we had this great way to test that in 863 00:44:01,436 --> 00:44:03,796 Speaker 1: our monkey market. We could change the price of goods 864 00:44:04,116 --> 00:44:07,116 Speaker 1: merely by altering the amount of food we gave monkeys. 865 00:44:07,356 --> 00:44:09,396 Speaker 1: You know, so we could give them a really really 866 00:44:09,476 --> 00:44:12,356 Speaker 1: huge piece of one kind of food for their token dollar, 867 00:44:12,356 --> 00:44:14,036 Speaker 1: which would kind of be like you know, getting a 868 00:44:14,036 --> 00:44:16,276 Speaker 1: brand of chocolate that's like really enormous for a dollar, 869 00:44:16,716 --> 00:44:18,676 Speaker 1: Or we could give them a really really tiny piece 870 00:44:18,676 --> 00:44:21,236 Speaker 1: of food, you know, it's like the teeny tiny truffle 871 00:44:21,316 --> 00:44:23,876 Speaker 1: of expensive chocolate that you get for a one dollar, right, 872 00:44:24,596 --> 00:44:26,316 Speaker 1: And so we could train them on this and then 873 00:44:26,556 --> 00:44:29,156 Speaker 1: give them a situation where they got to just decide 874 00:44:29,196 --> 00:44:32,356 Speaker 1: which of those they wanted without having to pay. And 875 00:44:32,396 --> 00:44:34,236 Speaker 1: so that's that's kind of the model. You know, imagine 876 00:44:34,276 --> 00:44:36,756 Speaker 1: you learn, you know, for one dollar you get Brand 877 00:44:36,756 --> 00:44:39,276 Speaker 1: A of chocolate and it's this huge, enormous piece you know, 878 00:44:39,596 --> 00:44:43,196 Speaker 1: probably not that good. And for another dollar, you get 879 00:44:43,236 --> 00:44:46,356 Speaker 1: Brand BE of chocolate and that's a teeny teeny tiny 880 00:44:46,356 --> 00:44:48,956 Speaker 1: piece of chocolate. Now you go to a reception and 881 00:44:49,036 --> 00:44:51,156 Speaker 1: both of those kinds of chocolates are out there, you know, 882 00:44:51,196 --> 00:44:53,316 Speaker 1: sitting for free. You know, which do you go after? 883 00:44:53,716 --> 00:44:55,516 Speaker 1: That was basically what we gave them monkeys. They had 884 00:44:55,516 --> 00:44:58,116 Speaker 1: a free feeding condition where they could grab whatever they wanted, 885 00:44:58,556 --> 00:45:01,316 Speaker 1: and to our surprise, they just didn't seem to care, 886 00:45:01,716 --> 00:45:04,396 Speaker 1: which was shocking because in all our other studies they 887 00:45:04,396 --> 00:45:06,396 Speaker 1: showed us that they cared about price a lot. You know, 888 00:45:06,436 --> 00:45:09,156 Speaker 1: they were these wonderful bargain shoppers, But they did, you 889 00:45:09,276 --> 00:45:11,476 Speaker 1: fall prey to this bias that we show about price. 890 00:45:11,836 --> 00:45:14,756 Speaker 1: They didn't irrationally think that higher priced goods we're going 891 00:45:14,756 --> 00:45:17,236 Speaker 1: to taste better. So in other words, what I'm hearing 892 00:45:17,236 --> 00:45:18,996 Speaker 1: you say is that you could set up a costco 893 00:45:19,076 --> 00:45:20,916 Speaker 1: in the world of monkeys, but probably not a three 894 00:45:20,916 --> 00:45:23,916 Speaker 1: Michelin star restaurant. And that's exactly right, especially a three 895 00:45:23,956 --> 00:45:27,876 Speaker 1: michelin star restaurant that didn't actually have good food. So 896 00:45:28,196 --> 00:45:30,956 Speaker 1: many of the differences you've just identified between humans and 897 00:45:30,996 --> 00:45:33,196 Speaker 1: other animals seem to be connected to the way we 898 00:45:33,276 --> 00:45:36,516 Speaker 1: relate to our social worlds, how we want to share 899 00:45:36,556 --> 00:45:39,756 Speaker 1: ideas with other people, how we intuit what's happening inside 900 00:45:39,756 --> 00:45:43,316 Speaker 1: someone else's mind, how we care intensely about what others 901 00:45:43,356 --> 00:45:46,476 Speaker 1: think of us. It's so interesting that these differences might 902 00:45:46,476 --> 00:45:49,236 Speaker 1: be responsible for some of the best things that humans do, 903 00:45:49,276 --> 00:45:51,716 Speaker 1: but also some of the worst things that humans do. Yeah, 904 00:45:51,876 --> 00:45:53,796 Speaker 1: that's one of the things I find most fascinating about 905 00:45:53,836 --> 00:45:57,196 Speaker 1: these findings is that the things that make us different 906 00:45:57,396 --> 00:46:00,156 Speaker 1: not only allow humans to do some of the smartest 907 00:46:00,196 --> 00:46:03,436 Speaker 1: things we do, you know, set up these five star restaurants, 908 00:46:03,636 --> 00:46:06,916 Speaker 1: you understand, rich fiction and movies, but they also make 909 00:46:06,996 --> 00:46:09,356 Speaker 1: us do some downright dumb stuff, you know. I think 910 00:46:09,356 --> 00:46:12,196 Speaker 1: that the biases we've identified are the same biases that 911 00:46:12,316 --> 00:46:15,636 Speaker 1: result in fake news being spread so easily. They also 912 00:46:15,676 --> 00:46:17,316 Speaker 1: are the same kinds of things that cause us to 913 00:46:17,356 --> 00:46:19,676 Speaker 1: like spend lots of money on stuff that's probably not 914 00:46:19,756 --> 00:46:22,836 Speaker 1: that good, you know. So it's remarkable that the very 915 00:46:22,836 --> 00:46:26,116 Speaker 1: things that make us so special and so smart can also, 916 00:46:26,196 --> 00:46:37,916 Speaker 1: in some contexts make us seem kind of dumb. Laurie 917 00:46:37,956 --> 00:46:40,836 Speaker 1: Santos is a professor of psychology and cognitive science at 918 00:46:40,956 --> 00:46:45,916 Speaker 1: Yale University. She's the host of the podcast The Happiness Lab. Laurie, 919 00:46:46,036 --> 00:46:48,876 Speaker 1: thanks for joining us today on Hidden Brain. Thanks so much. 920 00:46:55,516 --> 00:46:59,236 Speaker 1: Hidden Brain is produced by Hidden Brain Media. Our production 921 00:46:59,276 --> 00:47:04,276 Speaker 1: team includes Bridget McCarthy, Kristin Wong, Laura Quarrel, Ryan Katz, 922 00:47:04,436 --> 00:47:08,836 Speaker 1: Autumn Barnes, and Andrew Chadwick. Tara Boyle is our executive 923 00:47:08,876 --> 00:47:14,236 Speaker 1: produce I'm Hidden Brain's executive editor. Our unsung hero this 924 00:47:14,276 --> 00:47:18,636 Speaker 1: week is Andy Huther. Andy is an audio engineer at NPR. 925 00:47:19,316 --> 00:47:22,036 Speaker 1: When you're as skilled at audio editing as Andy is, 926 00:47:22,476 --> 00:47:25,436 Speaker 1: it's easy to fall prey to the curse of knowledge, 927 00:47:25,876 --> 00:47:29,756 Speaker 1: to forget what it's like to not know something. But 928 00:47:29,876 --> 00:47:33,356 Speaker 1: Andy understands exactly how to explain concepts to people who 929 00:47:33,356 --> 00:47:37,636 Speaker 1: are starting from square one. He's patient and always willing 930 00:47:37,636 --> 00:47:40,836 Speaker 1: to make time to answer questions, which is what makes 931 00:47:40,916 --> 00:47:45,836 Speaker 1: him a true unsung hero. Thanks Andy for more Hidden Brain. 932 00:47:45,996 --> 00:47:49,076 Speaker 1: Be sure to subscribe to one newsletter at news dot 933 00:47:49,116 --> 00:47:52,316 Speaker 1: hidden brain dot org. If you like our show and 934 00:47:52,396 --> 00:47:55,556 Speaker 1: would like to support our work, please go to support 935 00:47:55,876 --> 00:48:00,836 Speaker 1: dot hidden brain dot org. I'm Schanka vedantem See you soon. 936 00:48:05,156 --> 00:48:07,796 Speaker 1: A big thank you to Hidden Brains chanker Vedantem for 937 00:48:07,796 --> 00:48:11,076 Speaker 1: their interesting conversation. If you liked it, you should subscribe 938 00:48:11,116 --> 00:48:14,356 Speaker 1: to Hidden Brain. You can subscribe wherever you get your podcasts, 939 00:48:14,556 --> 00:48:17,476 Speaker 1: or listen and follow the show on Spotify