WEBVTT 00:00:00.111 --> 00:00:02.271 - [Colin] We have a saying in neuroscience sometimes: 00:00:02.271 --> 00:00:04.383 "Don't ask the person, ask the brain," 00:00:04.383 --> 00:00:06.484 because the brain activity may be something 00:00:06.484 --> 00:00:09.256 that's less than fully conscious. 00:00:09.678 --> 00:00:11.795 ♪ [music] ♪ 00:00:18.815 --> 00:00:20.850 My research is about behavioral economics 00:00:20.850 --> 00:00:22.105 and neuroeconomics. 00:00:22.105 --> 00:00:23.490 And behavioral economics 00:00:23.490 --> 00:00:26.828 is using ideas from psychology and other social sciences 00:00:26.828 --> 00:00:28.799 to make economics a little bit more lifelike 00:00:28.799 --> 00:00:31.310 and fit human behavior. 00:00:31.310 --> 00:00:33.761 The neuroeconomics part is that we actually try to see 00:00:33.761 --> 00:00:35.211 what's happening in the brain 00:00:35.211 --> 00:00:37.300 when people are making economic decisions. 00:00:37.300 --> 00:00:40.270 Hypothetical bias is a term for when you ask somebody 00:00:40.270 --> 00:00:41.748 whether they're going to do something, 00:00:41.748 --> 00:00:43.147 but there's no actual consequences, 00:00:43.147 --> 00:00:45.042 like a lot of surveys: "Are you going to vote?" 00:00:45.042 --> 00:00:47.061 "Will you buy this new product we have?" 00:00:47.621 --> 00:00:50.397 You tend to get a kind of upward "yes" bias. 00:00:50.397 --> 00:00:52.793 People are more likely to say, "Yeah, I'd think I'd buy it" 00:00:52.793 --> 00:00:54.239 or "Oh, yeah, I'm planning to vote." 00:00:54.239 --> 00:00:56.131 The hypothetical bias can be pretty high, 00:00:56.131 --> 00:00:57.881 and it can be also retrospective. 00:00:57.881 --> 00:00:59.529 So if you ask people did they vote, 00:00:59.529 --> 00:01:02.862 70% say yes and really the answer was 45%. 00:01:03.206 --> 00:01:05.097 One application is in things like marketing. 00:01:05.097 --> 00:01:07.913 A lot of new products fail, and one reason they fail 00:01:07.913 --> 00:01:09.631 is because when they test marketed, 00:01:09.631 --> 00:01:11.414 a lot of people said, "Yes, I'd buy it," 00:01:11.414 --> 00:01:12.630 who weren't going to buy it. 00:01:12.630 --> 00:01:14.247 One thing that people have been chasing 00:01:14.247 --> 00:01:16.861 in different fields in economics and psychology is 00:01:16.861 --> 00:01:20.303 how could we measure the size of this bias and adjust for it? 00:01:20.303 --> 00:01:23.102 So that if 70% of the people say they're going to buy a new product, 00:01:23.102 --> 00:01:25.683 we know that the real number is 45%. 00:01:29.619 --> 00:01:32.742 We did a couple of studies using brain imaging to say 00:01:32.742 --> 00:01:34.773 is there a kind of signature in the brain 00:01:34.773 --> 00:01:37.026 of when somebody says, "Yes, I would buy it," 00:01:37.026 --> 00:01:39.461 but when they really have to choose, they say no. 00:01:39.461 --> 00:01:41.442 So we showed them pictures of different goods, 00:01:41.442 --> 00:01:43.601 and the first part of the experiment, we asked them, 00:01:43.601 --> 00:01:46.655 "Would you pay $27 for this backpack, yes or no?" -- 00:01:46.655 --> 00:01:47.908 that's the hypothetical part. 00:01:47.908 --> 00:01:50.671 And then we kind of surprised them, when they come out of the scanner, 00:01:50.671 --> 00:01:52.071 and we say to them, "Oh, by the way, 00:01:52.071 --> 00:01:54.816 now we're going to actually have you decide to spend money, 00:01:54.816 --> 00:01:56.746 so we're going to give you $50." 00:01:56.746 --> 00:01:59.118 If you want to buy the backpack for $27, 00:01:59.118 --> 00:02:00.693 we're going to take it out of your 50, 00:02:00.693 --> 00:02:02.560 so that now they have to make real decisions. 00:02:02.560 --> 00:02:05.034 And then we study in the brain imaging, 00:02:05.034 --> 00:02:07.926 could we tell what areas were saying yes, 00:02:07.926 --> 00:02:09.966 but actually would later say no, 00:02:09.966 --> 00:02:12.911 compared to the areas that said, "Yes, I think I'll buy it," 00:02:12.911 --> 00:02:14.452 and, yes, they really did buy it. 00:02:14.452 --> 00:02:17.219 And we found both more activity in certain regions 00:02:17.219 --> 00:02:18.927 associated with valuation 00:02:18.927 --> 00:02:20.843 and then activity in different regions, 00:02:20.843 --> 00:02:22.126 which were somewhat predictive 00:02:22.126 --> 00:02:25.290 of when a yes was going to turn into, "Well, not really." 00:02:28.821 --> 00:02:30.868 In some other studies on hypothetical bias, 00:02:30.868 --> 00:02:33.068 we used eye tracking, which is a computerized way 00:02:33.068 --> 00:02:35.467 of seeing what you're looking at for how long. 00:02:35.467 --> 00:02:37.249 It also measures pupil dilation. 00:02:37.249 --> 00:02:39.679 When you're aroused by something that you like 00:02:39.679 --> 00:02:42.546 or possibly you're scared, the pupil dilates a little bit. 00:02:42.546 --> 00:02:44.107 So we used that method 00:02:44.107 --> 00:02:46.217 and then another method using mouse movements. 00:02:46.217 --> 00:02:48.005 And so we found that the mouse tracking 00:02:48.005 --> 00:02:50.337 and the eye tracking actually could give us an idea 00:02:50.337 --> 00:02:52.974 of when people would say, "Yes, I'm going to buy this product," 00:02:52.974 --> 00:02:55.282 but then they really didn't when they had skin in the game 00:02:55.282 --> 00:02:56.498 and had to buy it. 00:02:56.498 --> 00:03:00.933 The quicker a person moves a mouse to a box to click on something, 00:03:00.933 --> 00:03:02.284 the more they like it. 00:03:02.284 --> 00:03:05.190 It's like a fast trajectory, "I really like this." 00:03:05.190 --> 00:03:08.500 A slow meandering trajectory is, "Well, I don't know. I'm not sure." 00:03:08.500 --> 00:03:12.457 The motor activity in the mouse is actually an index in economic value 00:03:12.457 --> 00:03:15.542 as well as some other things, like indecision. 00:03:19.701 --> 00:03:21.650 We live in a kind of golden age of social science 00:03:21.650 --> 00:03:24.303 in which we can measure things in lots and lots of different ways. 00:03:24.303 --> 00:03:25.819 So one thing we've just begun 00:03:25.819 --> 00:03:28.181 that I think is going to be really, really fun 00:03:28.181 --> 00:03:32.728 is in order to study habit and a bunch of other things, 00:03:32.728 --> 00:03:34.371 we bought a smart vending machine, 00:03:34.371 --> 00:03:35.831 and a smart vending machine 00:03:35.831 --> 00:03:37.620 is basically a vending machine in the back 00:03:37.620 --> 00:03:39.217 and a giant iPad in the front. 00:03:39.217 --> 00:03:42.285 So you could program the iPad to show whatever you want. 00:03:42.285 --> 00:03:43.998 For example, if somebody buys habitually, 00:03:43.998 --> 00:03:46.451 and you raise the price by a few percent, 00:03:46.451 --> 00:03:47.524 do they just ignore that 00:03:47.524 --> 00:03:49.381 because they're not even looking at the price? 00:03:49.381 --> 00:03:51.539 Eventually, we'd like also to be able to use 00:03:51.539 --> 00:03:53.508 webcams or cameras to record, 00:03:53.508 --> 00:03:55.516 so when I say somebody is not looking at the price, 00:03:55.516 --> 00:03:57.537 I really mean they are not looking at the price 00:03:57.537 --> 00:04:00.285 because the camera looked at where their eyes were looking. 00:04:00.285 --> 00:04:02.418 - [Narrator] Want to see more economists in the wild? 00:04:02.418 --> 00:04:04.176 Check out our playlist. 00:04:04.176 --> 00:04:05.228 Are you a teacher? 00:04:05.228 --> 00:04:07.868 Here's some related material for your classroom. 00:04:07.868 --> 00:04:09.641 ♪ [music] ♪