0:00:00.111,0:00:02.271 - [Colin] We have a saying [br]in neuroscience sometimes: 0:00:02.271,0:00:04.383 "Don't ask the person,[br]ask the brain," 0:00:04.383,0:00:06.484 because the brain activity[br]may be something 0:00:06.484,0:00:09.256 that's less than fully conscious. 0:00:09.678,0:00:11.795 ♪ [music] ♪ 0:00:18.815,0:00:20.850 My research is about[br]behavioral economics 0:00:20.850,0:00:22.105 and neuroeconomics. 0:00:22.105,0:00:23.490 And behavioral economics 0:00:23.490,0:00:26.828 is using ideas from psychology[br]and other social sciences 0:00:26.828,0:00:28.799 to make economics[br]a little bit more lifelike 0:00:28.799,0:00:31.310 and fit human behavior. 0:00:31.310,0:00:33.761 The neuroeconomics part [br]is that we actually try to see 0:00:33.761,0:00:35.211 what's happening in the brain 0:00:35.211,0:00:37.300 when people are making [br]economic decisions. 0:00:37.300,0:00:40.270 Hypothetical bias is a term [br]for when you ask somebody 0:00:40.270,0:00:41.748 whether they're going[br]to do something, 0:00:41.748,0:00:43.147 but there's no actual consequences, 0:00:43.147,0:00:45.042 like a lot of surveys:[br]"Are you going to vote?" 0:00:45.042,0:00:47.061 "Will you buy [br]this new product we have?" 0:00:47.621,0:00:50.397 You tend to get a kind [br]of upward "yes" bias. 0:00:50.397,0:00:52.793 People are more likely to say,[br]"Yeah, I'd think I'd buy it" 0:00:52.793,0:00:54.239 or "Oh, yeah,[br]I'm planning to vote." 0:00:54.239,0:00:56.131 The hypothetical bias[br]can be pretty high, 0:00:56.131,0:00:57.881 and it can be also retrospective. 0:00:57.881,0:00:59.529 So if you ask people did they vote, 0:00:59.529,0:01:02.862 70% say yes and really [br]the answer was 45%. 0:01:03.206,0:01:05.097 One application is [br]in things like marketing. 0:01:05.097,0:01:07.913 A lot of new products fail,[br]and one reason they fail 0:01:07.913,0:01:09.631 is because when [br]they test marketed, 0:01:09.631,0:01:11.414 a lot of people said, [br]"Yes, I'd buy it," 0:01:11.414,0:01:12.630 who weren't going to buy it. 0:01:12.630,0:01:14.247 One thing that people [br]have been chasing 0:01:14.247,0:01:16.861 in different fields in economics[br]and psychology is 0:01:16.861,0:01:20.303 how could we measure the size [br]of this bias and adjust for it? 0:01:20.303,0:01:23.102 So that if 70% of the people say[br]they're going to buy a new product, 0:01:23.102,0:01:25.683 we know that [br]the real number is 45%. 0:01:29.619,0:01:32.742 We did a couple of studies[br]using brain imaging to say 0:01:32.742,0:01:34.773 is there a kind[br]of signature in the brain 0:01:34.773,0:01:37.026 of when somebody says, [br]"Yes, I would buy it," 0:01:37.026,0:01:39.461 but when they really have [br]to choose, they say no. 0:01:39.461,0:01:41.442 So we showed them pictures[br]of different goods, 0:01:41.442,0:01:43.601 and the first part [br]of the experiment, we asked them, 0:01:43.601,0:01:46.655 "Would you pay $27 [br]for this backpack, yes or no?" -- 0:01:46.655,0:01:47.948 that's the hypothetical part. 0:01:47.948,0:01:50.671 And then we kind of surprised them[br]when they come out of the scanner, 0:01:50.671,0:01:52.071 and we say to them,[br]"Oh, by the way, 0:01:52.071,0:01:54.816 now we're going to actually[br]have you decide to spend money, 0:01:54.816,0:01:56.746 so we're going to give you $50." 0:01:56.746,0:01:59.118 If you want to buy[br]the backpack for $27, 0:01:59.118,0:02:00.693 we're going to take it[br]out of your 50, 0:02:00.693,0:02:02.560 so that now they have[br]to make real decisions. 0:02:02.560,0:02:05.034 And then we study [br]in the brain imaging, 0:02:05.034,0:02:07.926 could we tell what areas [br]were saying yes, 0:02:07.926,0:02:09.966 but actually would later say no, 0:02:09.966,0:02:12.911 compared to the areas that said,[br]"Yes, I think I'll buy it," 0:02:12.911,0:02:14.452 and, yes, they really did buy it. 0:02:14.452,0:02:17.219 And we found both[br]more activity in certain regions 0:02:17.219,0:02:18.927 associated with valuation 0:02:18.927,0:02:20.843 and then activity[br]in different regions, 0:02:20.843,0:02:22.126 which were somewhat predictive 0:02:22.126,0:02:25.290 of when a yes was going to turn[br]into, "Well, not really." 0:02:28.821,0:02:30.868 In some other studies [br]on hypothetical bias, 0:02:30.868,0:02:33.068 we used eye tracking, [br]which is a computerized way 0:02:33.068,0:02:35.467 of seeing what you're looking at[br]for how long. 0:02:35.467,0:02:37.249 It also measures pupil dilation. 0:02:37.249,0:02:39.679 When you're aroused [br]by something that you like 0:02:39.679,0:02:42.546 or possibly you're scared,[br]the pupil dilates a little bit. 0:02:42.546,0:02:44.107 So we used that method 0:02:44.107,0:02:46.217 and then another method[br]using mouse movements. 0:02:46.217,0:02:48.005 And so we found [br]that the mouse tracking 0:02:48.005,0:02:50.337 and the eye tracking[br]actually could give us an idea 0:02:50.337,0:02:52.974 of when people would say, "Yes, [br]I'm going to buy this product," 0:02:52.974,0:02:55.282 but then they really didn't[br]when they had skin in the game 0:02:55.282,0:02:56.498 and had to buy it. 0:02:56.498,0:03:00.933 The quicker a person moves a mouse[br]to a box to click on something, 0:03:00.933,0:03:02.284 the more they like it. 0:03:02.284,0:03:05.190 It's like a fast trajectory,[br]"I really like this." 0:03:05.190,0:03:08.500 A slow meandering trajectory is, [br]"Well, I don't know. I'm not sure." 0:03:08.500,0:03:12.457 The motor activity in the mouse is[br]actually an index in economic value 0:03:12.457,0:03:15.542 as well as some other things,[br]like indecision. 0:03:19.701,0:03:21.650 We live in a kind of golden age[br]of social science 0:03:21.650,0:03:24.303 in which we can measure things[br]in lots and lots of different ways. 0:03:24.303,0:03:25.819 So one thing we've just begun 0:03:25.819,0:03:28.181 that I think is going [br]to be really, really fun 0:03:28.181,0:03:32.728 is in order to study habit[br]and a bunch of other things, 0:03:32.728,0:03:34.371 we bought a smart vending machine, 0:03:34.371,0:03:35.831 and a smart vending machine 0:03:35.831,0:03:37.620 is basically a vending[br]machine in the back 0:03:37.620,0:03:39.217 and a giant iPad in the front. 0:03:39.217,0:03:42.285 So you could program the iPad[br]to show whatever you want. 0:03:42.285,0:03:43.998 For example, if somebody[br]buys habitually, 0:03:43.998,0:03:46.451 and you raise the price[br]by a few percent, 0:03:46.451,0:03:47.524 do they just ignore that 0:03:47.524,0:03:49.381 because they're not [br]even looking at the price? 0:03:49.381,0:03:51.539 Eventually, we'd like also[br]to be able to use 0:03:51.539,0:03:53.508 webcams or cameras to record, 0:03:53.508,0:03:55.516 so when I say somebody[br]is not looking at the price, 0:03:55.516,0:03:57.537 I really mean they are[br]not looking at the price 0:03:57.537,0:04:00.285 because the camera looked[br]at where their eyes were looking. 0:04:00.285,0:04:02.418 - [Narrator] Want to see [br]more economists in the wild? 0:04:02.418,0:04:04.176 Check out our playlist. 0:04:04.176,0:04:05.228 Are you a teacher? 0:04:05.228,0:04:07.868 Here's some related material [br]for your classroom. 0:04:07.868,0:04:09.641 ♪ [music] ♪