1 00:00:00,111 --> 00:00:02,271 - [Colin] We have a saying in neuroscience sometimes: 2 00:00:02,271 --> 00:00:04,253 "Don't ask the person, ask the brain," 3 00:00:04,253 --> 00:00:07,606 because the brain activity may be something that's less 4 00:00:07,606 --> 00:00:09,256 than fully conscious. 5 00:00:09,678 --> 00:00:11,795 ♪ [music] ♪ 6 00:00:18,925 --> 00:00:22,015 My research is about behavioral economics and neuroeconomics. 7 00:00:22,015 --> 00:00:25,138 And behavioral economics is using ideas from psychology 8 00:00:25,138 --> 00:00:27,739 and other social sciences to make economics 9 00:00:27,739 --> 00:00:31,390 a little bit more lifelike and fit human behavior. 10 00:00:31,493 --> 00:00:33,761 The neuroeconomics part is that we actually try to see 11 00:00:33,761 --> 00:00:35,211 what's happening in the brain 12 00:00:35,211 --> 00:00:37,210 when people are making economic decisions. 13 00:00:37,210 --> 00:00:40,310 Hypothetical bias is a term for when you ask somebody 14 00:00:40,310 --> 00:00:43,127 whether they're going to something, but there's no actual consequences, 15 00:00:43,127 --> 00:00:45,042 like a lot of surveys: "Are you going to vote?" 16 00:00:45,042 --> 00:00:47,061 "Will you buy this new product we have?" 17 00:00:47,621 --> 00:00:50,447 You tend to get a kind of upward "yes" bias. 18 00:00:50,447 --> 00:00:52,933 People are more likely to say, "Yeah, I'd think I'd buy it," 19 00:00:52,933 --> 00:00:54,449 or, "Oh yeah, I'm planning to vote." 20 00:00:54,449 --> 00:00:56,126 The hypothetical bias can be pretty high, 21 00:00:56,131 --> 00:00:57,881 and it can be also retrospective. 22 00:00:57,881 --> 00:00:59,529 So if you ask people did they vote, 23 00:00:59,529 --> 00:01:02,647 70% say yes and really the answer was 45%. 24 00:01:03,297 --> 00:01:05,097 One application is in things like marketing. 25 00:01:05,097 --> 00:01:07,913 A lot of new products fail and one reason they fail 26 00:01:07,913 --> 00:01:09,631 is because when they test market it, 27 00:01:09,631 --> 00:01:11,414 a lot of people said, "Yes, I'd buy it," 28 00:01:11,414 --> 00:01:12,630 who weren't going to buy it. 29 00:01:12,630 --> 00:01:14,247 One thing that people have been chasing 30 00:01:14,247 --> 00:01:16,780 in different fields in economics and psychology is 31 00:01:16,861 --> 00:01:20,044 how can we measure the size of this bias and adjust for it. 32 00:01:20,044 --> 00:01:22,862 So that if 70% of the people say they're going to buy a new product, 33 00:01:22,862 --> 00:01:25,683 we know that the real number is 45%. 34 00:01:29,619 --> 00:01:32,682 We did a couple of studies using brain imaging to say 35 00:01:32,742 --> 00:01:34,960 is there a kind of signature in the brain of when 36 00:01:34,960 --> 00:01:37,026 somebody says, "Yes, I would buy it," 37 00:01:37,026 --> 00:01:39,309 but when they really have to choose, they say no. 38 00:01:39,461 --> 00:01:41,442 So we showed them pictures of different goods, 39 00:01:41,442 --> 00:01:43,601 and the first part of the experiment, we asked them, 40 00:01:43,601 --> 00:01:46,715 "Would you pay $27 for this backpack, yes or no?" 41 00:01:46,715 --> 00:01:49,261 That's the hypothetical part, and then we kind of surprised them 42 00:01:49,261 --> 00:01:51,631 when they come out of the scanner and we say to them, 43 00:01:51,631 --> 00:01:54,042 "Oh by the way, now we're going to actually have you decide 44 00:01:54,042 --> 00:01:56,436 to spend money so we're going to give you $50." 45 00:01:56,436 --> 00:01:59,550 If you want to buy the backpack for $27, we're going to take it 46 00:01:59,550 --> 00:02:02,453 out of your 50, so that now they have to make real decisions, 47 00:02:02,560 --> 00:02:04,694 and then we study in the brain imaging, 48 00:02:04,694 --> 00:02:07,776 could we tell what areas were saying yes, 49 00:02:07,776 --> 00:02:11,011 but actually would later say no compared to the areas that said, 50 00:02:11,011 --> 00:02:14,327 "Yes, I think I'll buy it," and, yes, they really did buy it. 51 00:02:14,452 --> 00:02:17,658 And we found both more activity in certain regions associated 52 00:02:17,658 --> 00:02:20,375 with valuation and then activity in different regions, 53 00:02:20,375 --> 00:02:23,507 which were somewhat predictive of when a yes was going to turn 54 00:02:23,507 --> 00:02:25,290 into, "Well, not really." 55 00:02:28,667 --> 00:02:30,748 In some other studies on hypothetical bias, 56 00:02:30,748 --> 00:02:33,068 we used eye tracking, which is a computerized way 57 00:02:33,068 --> 00:02:35,401 of seeing what you're looking at for how long. 58 00:02:35,467 --> 00:02:37,249 It also measures pupil dilation. 59 00:02:37,249 --> 00:02:39,499 When you're aroused by something that you like, 60 00:02:39,499 --> 00:02:42,382 or possibly you're scared, the pupil dilates a little bit. 61 00:02:42,701 --> 00:02:44,871 So we used that method and then another method 62 00:02:44,871 --> 00:02:46,337 using mouse movements. 63 00:02:46,337 --> 00:02:48,005 And so we found that the mouse tracking 64 00:02:48,005 --> 00:02:50,337 and the eye tracking actually could give us an idea 65 00:02:50,337 --> 00:02:52,974 of when people would say, "Yes, I'm going to buy this product," 66 00:02:52,974 --> 00:02:55,282 but then they really didn't when they had skin in the game 67 00:02:55,282 --> 00:02:56,409 and had to buy it. 68 00:02:56,498 --> 00:03:00,283 The quicker a person moves a mouse to a box to click on something, 69 00:03:00,283 --> 00:03:02,040 the more they like it. 70 00:03:02,424 --> 00:03:04,924 It's like a fast trajectory, "I really like this." 71 00:03:05,190 --> 00:03:08,090 A slow meandering trajectory is, "Well, I don't know. I'm not sure." 72 00:03:08,090 --> 00:03:12,457 The motor activity in the mouse is actually an index in economic value 73 00:03:12,457 --> 00:03:15,273 as well as some other things, like indecision. 74 00:03:19,701 --> 00:03:21,624 We live in a kind of golden age of social science 75 00:03:21,650 --> 00:03:24,483 in which we can measure things in lots and lots of different ways. 76 00:03:24,483 --> 00:03:25,819 So one thing we've just begun 77 00:03:25,819 --> 00:03:28,150 that I think it's going to be really, really fun 78 00:03:28,181 --> 00:03:32,448 is in order to study habit and a bunch of other things. 79 00:03:32,448 --> 00:03:35,315 We bought a smart vending machine, and a smart vending machine 80 00:03:35,315 --> 00:03:37,380 is basically a vending machine in the back 81 00:03:37,380 --> 00:03:39,129 and a giant iPad in the front. 82 00:03:39,217 --> 00:03:42,285 So you could program the iPad to show whatever you want. 83 00:03:42,285 --> 00:03:44,850 For example, if somebody buys habitually and you raise the price 84 00:03:44,850 --> 00:03:47,434 by a few percent, do they just ignore that 85 00:03:47,434 --> 00:03:49,299 because they're not even looking at the price? 86 00:03:49,381 --> 00:03:52,560 Eventually, we'd like also to be able to use webcam cameras 87 00:03:52,628 --> 00:03:55,226 to record so when I say somebody is not looking at the price, 88 00:03:55,226 --> 00:03:57,537 I really mean they are not looking at the price 89 00:03:57,537 --> 00:03:59,903 because the camera looked at where their eyes were looking. 90 00:04:00,065 --> 00:04:02,398 - [Narrator] Want to see more economists in the wild? 91 00:04:02,398 --> 00:04:03,764 Check out our playlist. 92 00:04:03,764 --> 00:04:05,148 Are you a teacher? 93 00:04:05,148 --> 00:04:07,628 Here's some related material for your classroom. 94 00:04:07,868 --> 00:04:09,641 ♪ [music] ♪