0:00:02.000,0:00:04.000 I want to start my talk today with two observations 0:00:04.000,0:00:06.000 about the human species. 0:00:06.000,0:00:09.000 The first observation is something that you might think is quite obvious, 0:00:09.000,0:00:11.000 and that's that our species, Homo sapiens, 0:00:11.000,0:00:13.000 is actually really, really smart -- 0:00:13.000,0:00:15.000 like, ridiculously smart -- 0:00:15.000,0:00:17.000 like you're all doing things 0:00:17.000,0:00:20.000 that no other species on the planet does right now. 0:00:20.000,0:00:22.000 And this is, of course, 0:00:22.000,0:00:24.000 not the first time you've probably recognized this. 0:00:24.000,0:00:27.000 Of course, in addition to being smart, we're also an extremely vain species. 0:00:27.000,0:00:30.000 So we like pointing out the fact that we're smart. 0:00:30.000,0:00:32.000 You know, so I could turn to pretty much any sage 0:00:32.000,0:00:34.000 from Shakespeare to Stephen Colbert 0:00:34.000,0:00:36.000 to point out things like the fact that 0:00:36.000,0:00:38.000 we're noble in reason and infinite in faculties 0:00:38.000,0:00:40.000 and just kind of awesome-er than anything else on the planet 0:00:40.000,0:00:43.000 when it comes to all things cerebral. 0:00:43.000,0:00:45.000 But of course, there's a second observation about the human species 0:00:45.000,0:00:47.000 that I want to focus on a little bit more, 0:00:47.000,0:00:49.000 and that's the fact that 0:00:49.000,0:00:52.000 even though we're actually really smart, sometimes uniquely smart, 0:00:52.000,0:00:55.000 we can also be incredibly, incredibly dumb 0:00:55.000,0:00:58.000 when it comes to some aspects of our decision making. 0:00:58.000,0:01:00.000 Now I'm seeing lots of smirks out there. 0:01:00.000,0:01:02.000 Don't worry, I'm not going to call anyone in particular out 0:01:02.000,0:01:04.000 on any aspects of your own mistakes. 0:01:04.000,0:01:06.000 But of course, just in the last two years 0:01:06.000,0:01:09.000 we see these unprecedented examples of human ineptitude. 0:01:09.000,0:01:12.000 And we've watched as the tools we uniquely make 0:01:12.000,0:01:14.000 to pull the resources out of our environment 0:01:14.000,0:01:16.000 kind of just blow up in our face. 0:01:16.000,0:01:18.000 We've watched the financial markets that we uniquely create -- 0:01:18.000,0:01:21.000 these markets that were supposed to be foolproof -- 0:01:21.000,0:01:23.000 we've watched them kind of collapse before our eyes. 0:01:23.000,0:01:25.000 But both of these two embarrassing examples, I think, 0:01:25.000,0:01:28.000 don't highlight what I think is most embarrassing 0:01:28.000,0:01:30.000 about the mistakes that humans make, 0:01:30.000,0:01:33.000 which is that we'd like to think that the mistakes we make 0:01:33.000,0:01:35.000 are really just the result of a couple bad apples 0:01:35.000,0:01:38.000 or a couple really sort of FAIL Blog-worthy decisions. 0:01:38.000,0:01:41.000 But it turns out, what social scientists are actually learning 0:01:41.000,0:01:44.000 is that most of us, when put in certain contexts, 0:01:44.000,0:01:47.000 will actually make very specific mistakes. 0:01:47.000,0:01:49.000 The errors we make are actually predictable. 0:01:49.000,0:01:51.000 We make them again and again. 0:01:51.000,0:01:53.000 And they're actually immune to lots of evidence. 0:01:53.000,0:01:55.000 When we get negative feedback, 0:01:55.000,0:01:58.000 we still, the next time we're face with a certain context, 0:01:58.000,0:02:00.000 tend to make the same errors. 0:02:00.000,0:02:02.000 And so this has been a real puzzle to me 0:02:02.000,0:02:04.000 as a sort of scholar of human nature. 0:02:04.000,0:02:06.000 What I'm most curious about is, 0:02:06.000,0:02:09.000 how is a species that's as smart as we are 0:02:09.000,0:02:11.000 capable of such bad 0:02:11.000,0:02:13.000 and such consistent errors all the time? 0:02:13.000,0:02:16.000 You know, we're the smartest thing out there, why can't we figure this out? 0:02:16.000,0:02:19.000 In some sense, where do our mistakes really come from? 0:02:19.000,0:02:22.000 And having thought about this a little bit, I see a couple different possibilities. 0:02:22.000,0:02:25.000 One possibility is, in some sense, it's not really our fault. 0:02:25.000,0:02:27.000 Because we're a smart species, 0:02:27.000,0:02:29.000 we can actually create all kinds of environments 0:02:29.000,0:02:31.000 that are super, super complicated, 0:02:31.000,0:02:34.000 sometimes too complicated for us to even actually understand, 0:02:34.000,0:02:36.000 even though we've actually created them. 0:02:36.000,0:02:38.000 We create financial markets that are super complex. 0:02:38.000,0:02:41.000 We create mortgage terms that we can't actually deal with. 0:02:41.000,0:02:44.000 And of course, if we are put in environments where we can't deal with it, 0:02:44.000,0:02:46.000 in some sense makes sense that we actually 0:02:46.000,0:02:48.000 might mess certain things up. 0:02:48.000,0:02:50.000 If this was the case, we'd have a really easy solution 0:02:50.000,0:02:52.000 to the problem of human error. 0:02:52.000,0:02:54.000 We'd actually just say, okay, let's figure out 0:02:54.000,0:02:56.000 the kinds of technologies we can't deal with, 0:02:56.000,0:02:58.000 the kinds of environments that are bad -- 0:02:58.000,0:03:00.000 get rid of those, design things better, 0:03:00.000,0:03:02.000 and we should be the noble species 0:03:02.000,0:03:04.000 that we expect ourselves to be. 0:03:04.000,0:03:07.000 But there's another possibility that I find a little bit more worrying, 0:03:07.000,0:03:10.000 which is, maybe it's not our environments that are messed up. 0:03:10.000,0:03:13.000 Maybe it's actually us that's designed badly. 0:03:13.000,0:03:15.000 This is a hint that I've gotten 0:03:15.000,0:03:18.000 from watching the ways that social scientists have learned about human errors. 0:03:18.000,0:03:21.000 And what we see is that people tend to keep making errors 0:03:21.000,0:03:24.000 exactly the same way, over and over again. 0:03:24.000,0:03:26.000 It feels like we might almost just be built 0:03:26.000,0:03:28.000 to make errors in certain ways. 0:03:28.000,0:03:31.000 This is a possibility that I worry a little bit more about, 0:03:31.000,0:03:33.000 because, if it's us that's messed up, 0:03:33.000,0:03:35.000 it's not actually clear how we go about dealing with it. 0:03:35.000,0:03:38.000 We might just have to accept the fact that we're error prone 0:03:38.000,0:03:40.000 and try to design things around it. 0:03:40.000,0:03:43.000 So this is the question my students and I wanted to get at. 0:03:43.000,0:03:46.000 How can we tell the difference between possibility one and possibility two? 0:03:46.000,0:03:48.000 What we need is a population 0:03:48.000,0:03:50.000 that's basically smart, can make lots of decisions, 0:03:50.000,0:03:52.000 but doesn't have access to any of the systems we have, 0:03:52.000,0:03:54.000 any of the things that might mess us up -- 0:03:54.000,0:03:56.000 no human technology, human culture, 0:03:56.000,0:03:58.000 maybe even not human language. 0:03:58.000,0:04:00.000 And so this is why we turned to these guys here. 0:04:00.000,0:04:03.000 These are one of the guys I work with. This is a brown capuchin monkey. 0:04:03.000,0:04:05.000 These guys are New World primates, 0:04:05.000,0:04:07.000 which means they broke off from the human branch 0:04:07.000,0:04:09.000 about 35 million years ago. 0:04:09.000,0:04:11.000 This means that your great, great, great great, great, great -- 0:04:11.000,0:04:13.000 with about five million "greats" in there -- 0:04:13.000,0:04:15.000 grandmother was probably the same great, great, great, great 0:04:15.000,0:04:17.000 grandmother with five million "greats" in there 0:04:17.000,0:04:19.000 as Holly up here. 0:04:19.000,0:04:22.000 You know, so you can take comfort in the fact that this guy up here is a really really distant, 0:04:22.000,0:04:24.000 but albeit evolutionary, relative. 0:04:24.000,0:04:26.000 The good news about Holly though is that 0:04:26.000,0:04:29.000 she doesn't actually have the same kinds of technologies we do. 0:04:29.000,0:04:32.000 You know, she's a smart, very cut creature, a primate as well, 0:04:32.000,0:04:34.000 but she lacks all the stuff we think might be messing us up. 0:04:34.000,0:04:36.000 So she's the perfect test case. 0:04:36.000,0:04:39.000 What if we put Holly into the same context as humans? 0:04:39.000,0:04:41.000 Does she make the same mistakes as us? 0:04:41.000,0:04:43.000 Does she not learn from them? And so on. 0:04:43.000,0:04:45.000 And so this is the kind of thing we decided to do. 0:04:45.000,0:04:47.000 My students and I got very excited about this a few years ago. 0:04:47.000,0:04:49.000 We said, all right, let's, you know, throw so problems at Holly, 0:04:49.000,0:04:51.000 see if she messes these things up. 0:04:51.000,0:04:54.000 First problem is just, well, where should we start? 0:04:54.000,0:04:56.000 Because, you know, it's great for us, but bad for humans. 0:04:56.000,0:04:58.000 We make a lot of mistakes in a lot of different contexts. 0:04:58.000,0:05:00.000 You know, where are we actually going to start with this? 0:05:00.000,0:05:03.000 And because we started this work around the time of the financial collapse, 0:05:03.000,0:05:05.000 around the time when foreclosures were hitting the news, 0:05:05.000,0:05:07.000 we said, hhmm, maybe we should 0:05:07.000,0:05:09.000 actually start in the financial domain. 0:05:09.000,0:05:12.000 Maybe we should look at monkey's economic decisions 0:05:12.000,0:05:15.000 and try to see if they do the same kinds of dumb things that we do. 0:05:15.000,0:05:17.000 Of course, that's when we hit a sort second problem -- 0:05:17.000,0:05:19.000 a little bit more methodological -- 0:05:19.000,0:05:21.000 which is that, maybe you guys don't know, 0:05:21.000,0:05:24.000 but monkeys don't actually use money. I know, you haven't met them. 0:05:24.000,0:05:26.000 But this is why, you know, they're not in the queue behind you 0:05:26.000,0:05:29.000 at the grocery store or the ATM -- you know, they don't do this stuff. 0:05:29.000,0:05:32.000 So now we faced, you know, a little bit of a problem here. 0:05:32.000,0:05:34.000 How are we actually going to ask monkeys about money 0:05:34.000,0:05:36.000 if they don't actually use it? 0:05:36.000,0:05:38.000 So we said, well, maybe we should just, actually just suck it up 0:05:38.000,0:05:40.000 and teach monkeys how to use money. 0:05:40.000,0:05:42.000 So that's just what we did. 0:05:42.000,0:05:45.000 What you're looking at over here is actually the first unit that I know of 0:05:45.000,0:05:47.000 of non-human currency. 0:05:47.000,0:05:49.000 We weren't very creative at the time we started these studies, 0:05:49.000,0:05:51.000 so we just called it a token. 0:05:51.000,0:05:54.000 But this is the unit of currency that we've taught our monkeys at Yale 0:05:54.000,0:05:56.000 to actually use with humans, 0:05:56.000,0:05:59.000 to actually buy different pieces of food. 0:05:59.000,0:06:01.000 It doesn't look like much -- in fact, it isn't like much. 0:06:01.000,0:06:03.000 Like most of our money, it's just a piece of metal. 0:06:03.000,0:06:06.000 As those of you who've taken currencies home from your trip know, 0:06:06.000,0:06:08.000 once you get home, it's actually pretty useless. 0:06:08.000,0:06:10.000 It was useless to the monkeys at first 0:06:10.000,0:06:12.000 before they realized what they could do with it. 0:06:12.000,0:06:14.000 When we first gave it to them in their enclosures, 0:06:14.000,0:06:16.000 they actually kind of picked them up, looked at them. 0:06:16.000,0:06:18.000 They were these kind of weird things. 0:06:18.000,0:06:20.000 But very quickly, the monkeys realized 0:06:20.000,0:06:22.000 that they could actually hand these tokens over 0:06:22.000,0:06:25.000 to different humans in the lab for some food. 0:06:25.000,0:06:27.000 And so you see one of our monkeys, Mayday, up here doing this. 0:06:27.000,0:06:30.000 This is A and B are kind of the points where she's sort of a little bit 0:06:30.000,0:06:32.000 curious about these things -- doesn't know. 0:06:32.000,0:06:34.000 There's this waiting hand from a human experimenter, 0:06:34.000,0:06:37.000 and Mayday quickly figures out, apparently the human wants this. 0:06:37.000,0:06:39.000 Hands it over, and then gets some food. 0:06:39.000,0:06:41.000 It turns out not just Mayday, all of our monkeys get good 0:06:41.000,0:06:43.000 at trading tokens with human salesman. 0:06:43.000,0:06:45.000 So here's just a quick video of what this looks like. 0:06:45.000,0:06:48.000 Here's Mayday. She's going to be trading a token for some food 0:06:48.000,0:06:51.000 and waiting happily and getting her food. 0:06:51.000,0:06:53.000 Here's Felix, I think. He's our alpha male; he's a kind of big guy. 0:06:53.000,0:06:56.000 But he too waits patiently, gets his food and goes on. 0:06:56.000,0:06:58.000 So the monkeys get really good at this. 0:06:58.000,0:07:01.000 They're surprisingly good at this with very little training. 0:07:01.000,0:07:03.000 We just allowed them to pick this up on their own. 0:07:03.000,0:07:05.000 The question is: is this anything like human money? 0:07:05.000,0:07:07.000 Is this a market at all, 0:07:07.000,0:07:09.000 or did we just do a weird psychologist's trick 0:07:09.000,0:07:11.000 by getting monkeys to do something, 0:07:11.000,0:07:13.000 looking smart, but not really being smart. 0:07:13.000,0:07:16.000 And so we said, well, what would the monkeys spontaneously do 0:07:16.000,0:07:19.000 if this was really their currency, if they were really using it like money? 0:07:19.000,0:07:21.000 Well, you might actually imagine them 0:07:21.000,0:07:23.000 to do all the kinds of smart things 0:07:23.000,0:07:26.000 that humans do when they start exchanging money with each other. 0:07:26.000,0:07:29.000 You might have them start paying attention to price, 0:07:29.000,0:07:31.000 paying attention to how much they buy -- 0:07:31.000,0:07:34.000 sort of keeping track of their monkey token, as it were. 0:07:34.000,0:07:36.000 Do the monkeys do anything like this? 0:07:36.000,0:07:39.000 And so our monkey marketplace was born. 0:07:39.000,0:07:41.000 The way this works is that 0:07:41.000,0:07:44.000 our monkeys normally live in a kind of big zoo social enclosure. 0:07:44.000,0:07:46.000 When they get a hankering for some treats, 0:07:46.000,0:07:48.000 we actually allowed them a way out 0:07:48.000,0:07:50.000 into a little smaller enclosure where they could enter the market. 0:07:50.000,0:07:52.000 Upon entering the market -- 0:07:52.000,0:07:54.000 it was actually a much more fun market for the monkeys than most human markets 0:07:54.000,0:07:57.000 because, as the monkeys entered the door of the market, 0:07:57.000,0:07:59.000 a human would give them a big wallet full of tokens 0:07:59.000,0:08:01.000 so they could actually trade the tokens 0:08:01.000,0:08:03.000 with one of these two guys here -- 0:08:03.000,0:08:05.000 two different possible human salesmen 0:08:05.000,0:08:07.000 that they could actually buy stuff from. 0:08:07.000,0:08:09.000 The salesmen were students from my lab. 0:08:09.000,0:08:11.000 They dressed differently; they were different people. 0:08:11.000,0:08:14.000 And over time, they did basically the same thing 0:08:14.000,0:08:16.000 so the monkeys could learn, you know, 0:08:16.000,0:08:19.000 who sold what at what price -- you know, who was reliable, who wasn't, and so on. 0:08:19.000,0:08:21.000 And you can see that each of the experimenters 0:08:21.000,0:08:24.000 is actually holding up a little, yellow food dish. 0:08:24.000,0:08:26.000 and that's what the monkey can for a single token. 0:08:26.000,0:08:28.000 So everything costs one token, 0:08:28.000,0:08:30.000 but as you can see, sometimes tokens buy more than others, 0:08:30.000,0:08:32.000 sometimes more grapes than others. 0:08:32.000,0:08:35.000 So I'll show you a quick video of what this marketplace actually looks like. 0:08:35.000,0:08:38.000 Here's a monkey-eye-view. Monkeys are shorter, so it's a little short. 0:08:38.000,0:08:40.000 But here's Honey. 0:08:40.000,0:08:42.000 She's waiting for the market to open a little impatiently. 0:08:42.000,0:08:45.000 All of a sudden the market opens. Here's her choice: one grapes or two grapes. 0:08:45.000,0:08:47.000 You can see Honey, very good market economist, 0:08:47.000,0:08:50.000 goes with the guy who gives more. 0:08:50.000,0:08:52.000 She could teach our financial advisers a few things or two. 0:08:52.000,0:08:54.000 So not just Honey, 0:08:54.000,0:08:57.000 most of the monkeys went with guys who had more. 0:08:57.000,0:08:59.000 Most of the monkeys went with guys who had better food. 0:08:59.000,0:09:02.000 When we introduced sales, we saw the monkeys paid attention to that. 0:09:02.000,0:09:05.000 They really cared about their monkey token dollar. 0:09:05.000,0:09:08.000 The more surprising thing was that when we collaborated with economists 0:09:08.000,0:09:11.000 to actually look at the monkeys' data using economic tools, 0:09:11.000,0:09:14.000 they basically matched, not just qualitatively, 0:09:14.000,0:09:16.000 but quantitatively with what we saw 0:09:16.000,0:09:18.000 humans doing in a real market. 0:09:18.000,0:09:20.000 So much so that, if you saw the monkeys' numbers, 0:09:20.000,0:09:23.000 you couldn't tell whether they came from a monkey or a human in the same market. 0:09:23.000,0:09:25.000 And what we'd really thought we'd done 0:09:25.000,0:09:27.000 is like we'd actually introduced something 0:09:27.000,0:09:29.000 that, at least for the monkeys and us, 0:09:29.000,0:09:31.000 works like a real financial currency. 0:09:31.000,0:09:34.000 Question is: do the monkeys start messing up in the same ways we do? 0:09:34.000,0:09:37.000 Well, we already saw anecdotally a couple of signs that they might. 0:09:37.000,0:09:39.000 One thing we never saw in the monkey marketplace 0:09:39.000,0:09:41.000 was any evidence of saving -- 0:09:41.000,0:09:43.000 you know, just like our own species. 0:09:43.000,0:09:45.000 The monkeys entered the market, spent their entire budget 0:09:45.000,0:09:47.000 and then went back to everyone else. 0:09:47.000,0:09:49.000 The other thing we also spontaneously saw, 0:09:49.000,0:09:51.000 embarrassingly enough, 0:09:51.000,0:09:53.000 is spontaneous evidence of larceny. 0:09:53.000,0:09:56.000 The monkeys would rip-off the tokens at every available opportunity -- 0:09:56.000,0:09:58.000 from each other, often from us -- 0:09:58.000,0:10:00.000 you know, things we didn't necessarily think we were introducing, 0:10:00.000,0:10:02.000 but things we spontaneously saw. 0:10:02.000,0:10:04.000 So we said, this looks bad. 0:10:04.000,0:10:06.000 Can we actually see if the monkeys 0:10:06.000,0:10:09.000 are doing exactly the same dumb things as humans do? 0:10:09.000,0:10:11.000 One possibility is just kind of let 0:10:11.000,0:10:13.000 the monkey financial system play out, 0:10:13.000,0:10:15.000 you know, see if they start calling us for bailouts in a few years. 0:10:15.000,0:10:17.000 We were a little impatient so we wanted 0:10:17.000,0:10:19.000 to sort of speed things up a bit. 0:10:19.000,0:10:21.000 So we said, let's actually give the monkeys 0:10:21.000,0:10:23.000 the same kinds of problems 0:10:23.000,0:10:25.000 that humans tend to get wrong 0:10:25.000,0:10:27.000 in certain kinds of economic challenges, 0:10:27.000,0:10:29.000 or certain kinds of economic experiments. 0:10:29.000,0:10:32.000 And so, since the best way to see how people go wrong 0:10:32.000,0:10:34.000 is to actually do it yourself, 0:10:34.000,0:10:36.000 I'm going to give you guys a quick experiment 0:10:36.000,0:10:38.000 to sort of watch your own financial intuitions in action. 0:10:38.000,0:10:40.000 So imagine that right now 0:10:40.000,0:10:42.000 I handed each and every one of you 0:10:42.000,0:10:45.000 a thousand U.S. dollars -- so 10 crisp hundred dollar bills. 0:10:45.000,0:10:47.000 Take these, put it in your wallet 0:10:47.000,0:10:49.000 and spend a second thinking about what you're going to do with it. 0:10:49.000,0:10:51.000 Because it's yours now; you can buy whatever you want. 0:10:51.000,0:10:53.000 Donate it, take it, and so on. 0:10:53.000,0:10:56.000 Sounds great, but you get one more choice to earn a little bit more money. 0:10:56.000,0:10:59.000 And here's your choice: you can either be risky, 0:10:59.000,0:11:01.000 in which case I'm going to flip one of these monkey tokens. 0:11:01.000,0:11:03.000 If it comes up heads, you're going to get a thousand dollars more. 0:11:03.000,0:11:05.000 If it comes up tails, you get nothing. 0:11:05.000,0:11:08.000 So it's a chance to get more, but it's pretty risky. 0:11:08.000,0:11:11.000 Your other option is a bit safe. Your just going to get some money for sure. 0:11:11.000,0:11:13.000 I'm just going to give you 500 bucks. 0:11:13.000,0:11:16.000 You can stick it in your wallet and use it immediately. 0:11:16.000,0:11:18.000 So see what your intuition is here. 0:11:18.000,0:11:21.000 Most people actually go with the play-it-safe option. 0:11:21.000,0:11:24.000 Most people say, why should I be risky when I can get 1,500 dollars for sure? 0:11:24.000,0:11:26.000 This seems like a good bet. I'm going to go with that. 0:11:26.000,0:11:28.000 You might say, eh, that's not really irrational. 0:11:28.000,0:11:30.000 People are a little risk-averse. So what? 0:11:30.000,0:11:32.000 Well, the "so what?" comes when start thinking 0:11:32.000,0:11:34.000 about the same problem 0:11:34.000,0:11:36.000 set up just a little bit differently. 0:11:36.000,0:11:38.000 So now imagine that I give each and every one of you 0:11:38.000,0:11:41.000 2,000 dollars -- 20 crisp hundred dollar bills. 0:11:41.000,0:11:43.000 Now you can buy double to stuff you were going to get before. 0:11:43.000,0:11:45.000 Think about how you'd feel sticking it in your wallet. 0:11:45.000,0:11:47.000 And now imagine that I have you make another choice 0:11:47.000,0:11:49.000 But this time, it's a little bit worse. 0:11:49.000,0:11:52.000 Now, you're going to be deciding how you're going to lose money, 0:11:52.000,0:11:54.000 but you're going to get the same choice. 0:11:54.000,0:11:56.000 You can either take a risky loss -- 0:11:56.000,0:11:59.000 so I'll flip a coin. If it comes up heads, you're going to actually lose a lot. 0:11:59.000,0:12:02.000 If it comes up tails, you lose nothing, you're fine, get to keep the whole thing -- 0:12:02.000,0:12:05.000 or you could play it safe, which means you have to reach back into your wallet 0:12:05.000,0:12:08.000 and give me five of those $100 bills, for certain. 0:12:08.000,0:12:11.000 And I'm seeing a lot of furrowed brows out there. 0:12:11.000,0:12:13.000 So maybe you're having the same intuitions 0:12:13.000,0:12:15.000 as the subjects that were actually tested in this, 0:12:15.000,0:12:17.000 which is when presented with these options, 0:12:17.000,0:12:19.000 people don't choose to play it safe. 0:12:19.000,0:12:21.000 They actually tend to go a little risky. 0:12:21.000,0:12:24.000 The reason this is irrational is that we've given people in both situations 0:12:24.000,0:12:26.000 the same choice. 0:12:26.000,0:12:29.000 It's a 50/50 shot of a thousand or 2,000, 0:12:29.000,0:12:31.000 or just 1,500 dollars with certainty. 0:12:31.000,0:12:34.000 But people's intuitions about how much risk to take 0:12:34.000,0:12:36.000 varies depending on where they started with. 0:12:36.000,0:12:38.000 So what's going on? 0:12:38.000,0:12:40.000 Well, it turns out that this seems to be the result 0:12:40.000,0:12:43.000 of at least two biases that we have at the psychological level. 0:12:43.000,0:12:46.000 One is that we have a really hard time thinking in absolute terms. 0:12:46.000,0:12:48.000 You really have to do work to figure out, 0:12:48.000,0:12:50.000 well, one option's a thousand, 2,000; 0:12:50.000,0:12:52.000 one is 1,500. 0:12:52.000,0:12:55.000 Instead, we find it very easy to think in very relative terms 0:12:55.000,0:12:58.000 as options change from one time to another. 0:12:58.000,0:13:01.000 So we think of things as, "Oh, I'm going to get more," or "Oh, I'm going to get less." 0:13:01.000,0:13:03.000 This is all well and good, except that 0:13:03.000,0:13:05.000 changes in different directions 0:13:05.000,0:13:07.000 actually effect whether or not we think 0:13:07.000,0:13:09.000 options are good or not. 0:13:09.000,0:13:11.000 And this leads to the second bias, 0:13:11.000,0:13:13.000 which economists have called loss aversion. 0:13:13.000,0:13:16.000 The idea is that we really hate it when things go into the red. 0:13:16.000,0:13:18.000 We really hate it when we have to lose out on some money. 0:13:18.000,0:13:20.000 And this means that sometimes we'll actually 0:13:20.000,0:13:22.000 switch our preferences to avoid this. 0:13:22.000,0:13:24.000 What you saw in that last scenario is that 0:13:24.000,0:13:26.000 subjects get risky 0:13:26.000,0:13:29.000 because they want the small shot that there won't be any loss. 0:13:29.000,0:13:31.000 That means when we're in a risk mindset -- 0:13:31.000,0:13:33.000 excuse me, when we're in a loss mindset, 0:13:33.000,0:13:35.000 we actually become more risky, 0:13:35.000,0:13:37.000 which can actually be really worrying. 0:13:37.000,0:13:40.000 These kinds of things play out in lots of bad ways in humans. 0:13:40.000,0:13:43.000 They're why stock investors hold onto losing stocks longer -- 0:13:43.000,0:13:45.000 because they're evaluating them in relative terms. 0:13:45.000,0:13:47.000 They're why people in the housing market refused to sell their house -- 0:13:47.000,0:13:49.000 because they don't want to sell at a loss. 0:13:49.000,0:13:51.000 The question we were interested in 0:13:51.000,0:13:53.000 is whether the monkeys show the same biases. 0:13:53.000,0:13:56.000 If we set up those same scenarios in our little monkey market, 0:13:56.000,0:13:58.000 would they do the same thing as people? 0:13:58.000,0:14:00.000 And so this is what we did, we gave the monkeys choices 0:14:00.000,0:14:03.000 between guys who were safe -- they did the same thing every time -- 0:14:03.000,0:14:05.000 or guys who were risky -- 0:14:05.000,0:14:07.000 they did things differently half the time. 0:14:07.000,0:14:09.000 And then we gave them options that were bonuses -- 0:14:09.000,0:14:11.000 like you guys did in the first scenario -- 0:14:11.000,0:14:13.000 so they actually have a chance more, 0:14:13.000,0:14:16.000 or pieces where they were experiencing losses -- 0:14:16.000,0:14:18.000 they actually thought they were going to get more than they really got. 0:14:18.000,0:14:20.000 And so this is what this looks like. 0:14:20.000,0:14:22.000 We introduced the monkeys to two new monkey salesmen. 0:14:22.000,0:14:24.000 The guy on the left and right both start with one piece of grape, 0:14:24.000,0:14:26.000 so it looks pretty good. 0:14:26.000,0:14:28.000 But they're going to give the monkeys bonuses. 0:14:28.000,0:14:30.000 The guy on the left is a safe bonus. 0:14:30.000,0:14:33.000 All the time, he adds one, to give the monkeys two. 0:14:33.000,0:14:35.000 The guy on the right is actually a risky bonus. 0:14:35.000,0:14:38.000 Sometimes the monkeys get no bonus -- so this is a bonus of zero. 0:14:38.000,0:14:41.000 Sometimes the monkeys get two extra. 0:14:41.000,0:14:43.000 For a big bonus, now they get three. 0:14:43.000,0:14:45.000 But this is the same choice you guys just faced. 0:14:45.000,0:14:48.000 Do the monkeys actually want to play it safe 0:14:48.000,0:14:50.000 and then go with the guy who's going to do the same thing on every trial, 0:14:50.000,0:14:52.000 or do they want to be risky 0:14:52.000,0:14:54.000 and try to get a risky, but big, bonus, 0:14:54.000,0:14:56.000 but risk the possibility of getting no bonus. 0:14:56.000,0:14:58.000 People here played it safe. 0:14:58.000,0:15:00.000 Turns out, the monkeys play it safe too. 0:15:00.000,0:15:02.000 Qualitatively and quantitatively, 0:15:02.000,0:15:04.000 they choose exactly the same way as people, 0:15:04.000,0:15:06.000 when tested in the same thing. 0:15:06.000,0:15:08.000 You might say, well, maybe the monkeys just don't like risk. 0:15:08.000,0:15:10.000 Maybe we should see how they do with losses. 0:15:10.000,0:15:12.000 And so we ran a second version of this. 0:15:12.000,0:15:14.000 Now, the monkeys meet two guys 0:15:14.000,0:15:16.000 who aren't giving them bonuses; 0:15:16.000,0:15:18.000 they're actually giving them less than they expect. 0:15:18.000,0:15:20.000 So they look like they're starting out with a big amount. 0:15:20.000,0:15:22.000 These are three grapes; the monkey's really psyched for this. 0:15:22.000,0:15:25.000 But now they learn these guys are going to give them less than they expect. 0:15:25.000,0:15:27.000 They guy on the left is a safe loss. 0:15:27.000,0:15:30.000 Every single time, he's going to take one of these away 0:15:30.000,0:15:32.000 and give the monkeys just two. 0:15:32.000,0:15:34.000 the guy on the right is the risky loss. 0:15:34.000,0:15:37.000 Sometimes he gives no loss, so the monkeys are really psyched, 0:15:37.000,0:15:39.000 but sometimes he actually gives a big loss, 0:15:39.000,0:15:41.000 taking away two to give the monkeys only one. 0:15:41.000,0:15:43.000 And so what do the monkeys do? 0:15:43.000,0:15:45.000 Again, same choice; they can play it safe 0:15:45.000,0:15:48.000 for always getting two grapes every single time, 0:15:48.000,0:15:51.000 or they can take a risky bet and choose between one and three. 0:15:51.000,0:15:54.000 The remarkable thing to us is that, when you give monkeys this choice, 0:15:54.000,0:15:56.000 they do the same irrational thing that people do. 0:15:56.000,0:15:58.000 They actually become more risky 0:15:58.000,0:16:01.000 depending on how the experimenters started. 0:16:01.000,0:16:03.000 This is crazy because it suggests that the monkeys too 0:16:03.000,0:16:05.000 are evaluating things in relative terms 0:16:05.000,0:16:08.000 and actually treating losses differently than they treat gains. 0:16:08.000,0:16:10.000 So what does all of this mean? 0:16:10.000,0:16:12.000 Well, what we've shown is that, first of all, 0:16:12.000,0:16:14.000 we can actually give the monkeys a financial currency, 0:16:14.000,0:16:16.000 and they do very similar things with it. 0:16:16.000,0:16:18.000 They do some of the smart things we do, 0:16:18.000,0:16:20.000 some of the kind of not so nice things we do, 0:16:20.000,0:16:22.000 like steal it and so on. 0:16:22.000,0:16:24.000 But they also do some of the irrational things we do. 0:16:24.000,0:16:26.000 They systematically get things wrong 0:16:26.000,0:16:28.000 and in the same ways that we do. 0:16:28.000,0:16:30.000 This is the first take-home message of the Talk, 0:16:30.000,0:16:32.000 which is that if you saw the beginning of this and you thought, 0:16:32.000,0:16:34.000 oh, I'm totally going to go home and hire a capuchin monkey financial adviser. 0:16:34.000,0:16:36.000 They're way cuter than the one at ... you know -- 0:16:36.000,0:16:38.000 Don't do that; they're probably going to be just as dumb 0:16:38.000,0:16:41.000 as the human one you already have. 0:16:41.000,0:16:43.000 So, you know, a little bad -- Sorry, sorry, sorry. 0:16:43.000,0:16:45.000 A little bad for monkey investors. 0:16:45.000,0:16:48.000 But of course, you know, the reason you're laughing is bad for humans too. 0:16:48.000,0:16:51.000 Because we've answered the question we started out with. 0:16:51.000,0:16:53.000 We wanted to know where these kinds of errors came from. 0:16:53.000,0:16:55.000 And we started with the hope that maybe we can 0:16:55.000,0:16:57.000 sort of tweak our financial institutions, 0:16:57.000,0:17:00.000 tweak our technologies to make ourselves better. 0:17:00.000,0:17:03.000 But what we've learn is that these biases might be a deeper part of us than that. 0:17:03.000,0:17:05.000 In fact, they might be due to the very nature 0:17:05.000,0:17:07.000 of our evolutionary history. 0:17:07.000,0:17:09.000 You know, maybe it's not just humans 0:17:09.000,0:17:11.000 at the right side of this chain that's duncey. 0:17:11.000,0:17:13.000 Maybe it's sort of duncey all the way back. 0:17:13.000,0:17:16.000 And this, if we believe the capuchin monkey results, 0:17:16.000,0:17:18.000 means that these duncey strategies 0:17:18.000,0:17:20.000 might be 35 million years old. 0:17:20.000,0:17:22.000 That's a long time for a strategy 0:17:22.000,0:17:25.000 to potentially get changed around -- really, really old. 0:17:25.000,0:17:27.000 What do we know about other old strategies like this? 0:17:27.000,0:17:30.000 Well, one thing we know is that they tend to be really hard to overcome. 0:17:30.000,0:17:32.000 You know, think of our evolutionary predilection 0:17:32.000,0:17:35.000 for eating sweet things, fatty things like cheesecake. 0:17:35.000,0:17:37.000 You can't just shut that off. 0:17:37.000,0:17:40.000 You can't just look at the dessert cart as say, "No, no, no. That looks disgusting to me." 0:17:40.000,0:17:42.000 We're just built differently. 0:17:42.000,0:17:44.000 We're going to perceive it as a good thing to go after. 0:17:44.000,0:17:46.000 My guess is that the same thing is going to be true 0:17:46.000,0:17:48.000 when humans are perceiving 0:17:48.000,0:17:50.000 different financial decisions. 0:17:50.000,0:17:52.000 When you're watching your stocks plummet into the red, 0:17:52.000,0:17:54.000 when you're watching your house price go down, 0:17:54.000,0:17:56.000 you're not going to be able to see that 0:17:56.000,0:17:58.000 in anything but old evolutionary terms. 0:17:58.000,0:18:00.000 This means that the biases 0:18:00.000,0:18:02.000 that lead investors to do badly, 0:18:02.000,0:18:04.000 that lead to the foreclosure crisis 0:18:04.000,0:18:06.000 are going to be really hard to overcome. 0:18:06.000,0:18:08.000 So that's the bad news. The question is: is there any good news? 0:18:08.000,0:18:10.000 I'm supposed to be up here telling you the good news. 0:18:10.000,0:18:12.000 Well, the good news, I think, 0:18:12.000,0:18:14.000 is what I started with at the beginning of the Talk, 0:18:14.000,0:18:16.000 which is that humans are not only smart; 0:18:16.000,0:18:18.000 we're really inspirationally smart 0:18:18.000,0:18:21.000 to the rest of the animals in the biological kingdom. 0:18:21.000,0:18:24.000 We're so good at overcoming our biological limitations -- 0:18:24.000,0:18:26.000 you know, I flew over here in an airplane. 0:18:26.000,0:18:28.000 I didn't have to try to flap my wings. 0:18:28.000,0:18:31.000 I'm wearing contact lenses now so that I can see all of you. 0:18:31.000,0:18:34.000 I don't have to rely on my own near-sightedness. 0:18:34.000,0:18:36.000 We actually have all of these cases 0:18:36.000,0:18:39.000 where we overcome our biological limitations 0:18:39.000,0:18:42.000 through technology and other means, seemingly pretty easily. 0:18:42.000,0:18:45.000 But we have to recognize that we have those limitations. 0:18:45.000,0:18:47.000 And here's the rub. 0:18:47.000,0:18:49.000 It was Camus who once said that, "Man is the only species 0:18:49.000,0:18:52.000 who refuses to be what he really is." 0:18:52.000,0:18:54.000 But the irony is that 0:18:54.000,0:18:56.000 it might only be in recognizing our limitations 0:18:56.000,0:18:58.000 that we can really actually overcome them. 0:18:58.000,0:19:01.000 The hope is that you all will think about your limitations, 0:19:01.000,0:19:04.000 not necessarily as unovercomable, 0:19:04.000,0:19:06.000 but to recognize them, accept them 0:19:06.000,0:19:09.000 and then use the world of design to actually figure them out. 0:19:09.000,0:19:12.000 That might be the only way that we will really be able 0:19:12.000,0:19:14.000 to achieve our own human potential 0:19:14.000,0:19:17.000 and really be the noble species we hope to all be. 0:19:17.000,0:19:19.000 Thank you. 0:19:19.000,0:19:24.000 (Applause)