1 00:00:03,040 --> 00:00:05,840 Speaker 1: Welcome to Stuff to Blow your Mind from how stuff 2 00:00:05,880 --> 00:00:15,000 Speaker 1: Works dot com. Hey, welcome to Stuff to Blow your Mind. 3 00:00:15,040 --> 00:00:17,680 Speaker 1: And my name is Robert Lamb, I'm Christian and I'm 4 00:00:17,760 --> 00:00:19,880 Speaker 1: Joe McCormick. And hey, this is part two of our 5 00:00:20,400 --> 00:00:24,279 Speaker 1: seventeen Ignobles series. That's right. If you haven't listened to 6 00:00:24,280 --> 00:00:26,680 Speaker 1: the first one, I recommend that you go back at 7 00:00:26,720 --> 00:00:29,200 Speaker 1: least listen to the first twenty minutes because we set 8 00:00:29,280 --> 00:00:32,640 Speaker 1: up the stage for what ignobells are, how we've covered 9 00:00:32,680 --> 00:00:35,720 Speaker 1: them in the past before, and what we're doing here today. 10 00:00:35,920 --> 00:00:39,280 Speaker 1: This is really a continuation of us observing the prizes. 11 00:00:39,560 --> 00:00:44,000 Speaker 1: That being said, if there was ever a multipart episode 12 00:00:44,159 --> 00:00:45,959 Speaker 1: that you could just drop in at any point, it's 13 00:00:46,040 --> 00:00:48,959 Speaker 1: this one. This is a bag yeah, because because basically 14 00:00:49,000 --> 00:00:50,919 Speaker 1: we're just taking the ten different winners for the two 15 00:00:50,960 --> 00:00:54,080 Speaker 1: thousand seventeen Ignoble prizes, we divvy them up and we're 16 00:00:54,160 --> 00:00:57,080 Speaker 1: each like taking the lead on a different study discussing 17 00:00:57,400 --> 00:01:00,200 Speaker 1: why it's cool, why it's funny, and exactly what the signs. 18 00:01:00,520 --> 00:01:04,200 Speaker 1: In the last episode, we talked about liquid cats, cave bugs, 19 00:01:04,280 --> 00:01:08,319 Speaker 1: and digury do therapy, along with weird coffee mugs, and 20 00:01:08,360 --> 00:01:11,520 Speaker 1: now we're gonna get into even weirder stuff. Okay, So 21 00:01:11,600 --> 00:01:14,080 Speaker 1: the first prize we're going to discuss today is the 22 00:01:15,040 --> 00:01:19,319 Speaker 1: Economics Prize, ordered to Matthew Rocklough and Nancy Greer quote 23 00:01:19,319 --> 00:01:22,559 Speaker 1: for their experiments to see how contact with a live 24 00:01:22,600 --> 00:01:27,280 Speaker 1: crocodile affects a person's willingness to gamble. Okay, this sounds 25 00:01:27,319 --> 00:01:29,039 Speaker 1: like something out of a out of a James Bond 26 00:01:29,080 --> 00:01:32,319 Speaker 1: film right here. I'm imagining that this is like, I 27 00:01:32,319 --> 00:01:34,920 Speaker 1: don't know, based in Louisiana or Florida or something where 28 00:01:35,120 --> 00:01:37,920 Speaker 1: live crocodiles are a common sighting and then you may 29 00:01:38,000 --> 00:01:42,600 Speaker 1: go gambling it. Based in Australia, you can gamble and 30 00:01:42,760 --> 00:01:47,199 Speaker 1: you can handle saltwater crocodile. Right, Yeah, So the paper 31 00:01:47,240 --> 00:01:49,920 Speaker 1: is called never Smile at a crocodile. Betting on electronic 32 00:01:50,000 --> 00:01:54,640 Speaker 1: gaming machines is intensified by reptile induced arousal. Actually, there, 33 00:01:54,720 --> 00:01:57,080 Speaker 1: we should put an asterisk on the statement in that 34 00:01:57,120 --> 00:02:00,720 Speaker 1: title there, because that that's partially true depending on what 35 00:02:00,840 --> 00:02:03,120 Speaker 1: kind of gambler you are and some other things about you. 36 00:02:03,600 --> 00:02:06,040 Speaker 1: It was published in the Journal of Gambling Studies in 37 00:02:07,480 --> 00:02:11,080 Speaker 1: and so there are a lot of slot machines studies. 38 00:02:11,120 --> 00:02:14,560 Speaker 1: That the whole episode that right, and I think we 39 00:02:14,560 --> 00:02:16,519 Speaker 1: could do more. Robert and I have talked about doing 40 00:02:16,560 --> 00:02:20,799 Speaker 1: episodes entirely on rat slot machine studies or I mean, 41 00:02:20,960 --> 00:02:23,239 Speaker 1: there's just tons of research on slot machines, and there's 42 00:02:23,280 --> 00:02:26,440 Speaker 1: a reason for the slot machines or as the literature 43 00:02:26,440 --> 00:02:29,959 Speaker 1: refers to them, electronic gaming machines or e g m s. 44 00:02:31,120 --> 00:02:35,959 Speaker 1: They're kind of a perfect predator. They're like brilliantly designed 45 00:02:35,960 --> 00:02:40,120 Speaker 1: to exploit vulnerabilities in human psychology and risk management behavior, 46 00:02:40,240 --> 00:02:42,120 Speaker 1: gambling with e g m s tends to produce this 47 00:02:42,240 --> 00:02:45,280 Speaker 1: state of what's known as autonomic arousal. You and I 48 00:02:45,320 --> 00:02:49,080 Speaker 1: would just probably call this excitement, you know, physiological sensation 49 00:02:49,160 --> 00:02:51,440 Speaker 1: of excitement in the body that the brain tends to 50 00:02:51,560 --> 00:02:55,120 Speaker 1: interpret sometimes in the case of gambling, interprets as a 51 00:02:55,200 --> 00:02:58,520 Speaker 1: lucky streak, which keeps you gambling, and it leads to 52 00:02:58,560 --> 00:03:01,720 Speaker 1: this vicious cycle where it's more and more arousing and 53 00:03:01,760 --> 00:03:04,080 Speaker 1: you just keep wanting to bet more and more money. 54 00:03:04,120 --> 00:03:09,400 Speaker 1: Autonomic arousal not to be confused with reptile induced arousal. Well, no, 55 00:03:09,600 --> 00:03:12,880 Speaker 1: I mean, reptiles could create a state of aucomic arousal, 56 00:03:12,960 --> 00:03:15,160 Speaker 1: but yeah, not one and the same thing one could 57 00:03:15,280 --> 00:03:18,560 Speaker 1: lead to the other. So I think e g M 58 00:03:18,600 --> 00:03:20,480 Speaker 1: s are an interesting thing to study, and this kind 59 00:03:20,480 --> 00:03:24,160 Speaker 1: of research really matters because they fit into a similar category. 60 00:03:24,280 --> 00:03:28,000 Speaker 1: Uh that that I would put social media interface design 61 00:03:28,080 --> 00:03:32,640 Speaker 1: in this this successful technology design that is actually better 62 00:03:32,760 --> 00:03:35,800 Speaker 1: at its job than is good for us. What do 63 00:03:35,840 --> 00:03:38,440 Speaker 1: y'all think about that? With like social media interfaces that 64 00:03:38,640 --> 00:03:42,080 Speaker 1: I would say, it's a great success story in terms 65 00:03:42,080 --> 00:03:47,040 Speaker 1: of designing technology. But success doesn't necessarily mean morally good 66 00:03:47,160 --> 00:03:50,480 Speaker 1: or good for our lives. Well, I think we When 67 00:03:50,480 --> 00:03:52,360 Speaker 1: I think of a slot machine, I instantly think of 68 00:03:52,480 --> 00:03:54,880 Speaker 1: like somebody that's kind of shackled there to the machine 69 00:03:54,960 --> 00:03:57,920 Speaker 1: and they're just pushing buttons, uh, And there's this idea 70 00:03:58,000 --> 00:04:00,000 Speaker 1: that it's going to pay off for them, and then 71 00:04:00,000 --> 00:04:01,920 Speaker 1: maybe it does pay off a little bit, and then 72 00:04:01,920 --> 00:04:05,960 Speaker 1: they keep going. And with with social media, you do 73 00:04:06,000 --> 00:04:08,360 Speaker 1: see a some more situation. Someone has their phone out, 74 00:04:08,520 --> 00:04:11,360 Speaker 1: they're constantly checking this feed or that feed, this social 75 00:04:11,360 --> 00:04:14,880 Speaker 1: media appor that or another. And the win in this case, 76 00:04:14,920 --> 00:04:18,680 Speaker 1: I guess would be somebody contacting them directly or some 77 00:04:18,760 --> 00:04:21,360 Speaker 1: sort of response. Howbody like that I get on my 78 00:04:22,080 --> 00:04:24,080 Speaker 1: or you might even you might even have a real win. 79 00:04:24,200 --> 00:04:26,600 Speaker 1: You could have a meaningful interaction with somebody you care 80 00:04:26,640 --> 00:04:29,480 Speaker 1: about on social media, or you might come across an 81 00:04:29,480 --> 00:04:31,919 Speaker 1: interesting article that you're glad you read. Those are the 82 00:04:31,960 --> 00:04:35,440 Speaker 1: little winds, but maybe it just keeps you playing. After that, 83 00:04:35,520 --> 00:04:39,240 Speaker 1: we're speaking more little on our is social media making 84 00:04:39,320 --> 00:04:41,600 Speaker 1: us crazy? Episode from last year? And I think, yeah, 85 00:04:41,680 --> 00:04:47,279 Speaker 1: if I remember correctly, the literature basically assumes and they're 86 00:04:47,320 --> 00:04:49,800 Speaker 1: still looking into this of course that like the same 87 00:04:50,040 --> 00:04:52,200 Speaker 1: parts of our brain that are lit up by gambling 88 00:04:52,279 --> 00:04:54,159 Speaker 1: or lit up by social media. I think I think 89 00:04:54,160 --> 00:04:57,719 Speaker 1: that's a highly successful and correct analogy. Uh so for 90 00:04:57,800 --> 00:05:01,080 Speaker 1: social media interfaces that the job they're trying to achieve 91 00:05:01,160 --> 00:05:04,640 Speaker 1: generally is maximizing time on site. They want to keep 92 00:05:04,720 --> 00:05:07,400 Speaker 1: you on that platform as long as possible and keep 93 00:05:07,440 --> 00:05:09,800 Speaker 1: you looking at stuff and clicking on ads and all that. 94 00:05:10,040 --> 00:05:12,520 Speaker 1: Is that why we do those hour long Facebook lives 95 00:05:12,520 --> 00:05:15,160 Speaker 1: every Friday? I don't, Well, that's why Facebook wants us 96 00:05:15,160 --> 00:05:18,160 Speaker 1: doing those things. Yeah, I don't know what our reason is. 97 00:05:18,200 --> 00:05:21,440 Speaker 1: Maybe we're just slaves to the machine. But you didn't 98 00:05:21,440 --> 00:05:25,240 Speaker 1: know that. Basically, Yeah, the machine says you need to 99 00:05:25,240 --> 00:05:28,159 Speaker 1: do this, and we basically turned it around and said, Okay, 100 00:05:28,160 --> 00:05:31,280 Speaker 1: we'll do it, but if we're gonna do right, we'll 101 00:05:31,360 --> 00:05:34,200 Speaker 1: change it from the inside. Sure, yeah, that's what we're doing. 102 00:05:34,240 --> 00:05:37,359 Speaker 1: We're changing the machine. Man. But the electronic gaming machines, 103 00:05:37,440 --> 00:05:39,920 Speaker 1: I would put them in the same category. But instead 104 00:05:40,040 --> 00:05:42,520 Speaker 1: what they're seeking is not maximizing time on site, but 105 00:05:42,600 --> 00:05:47,040 Speaker 1: maximizing time on machine. Because when they maximize time on machine, 106 00:05:47,200 --> 00:05:51,400 Speaker 1: this tends toward infinity of losses for the player. It 107 00:05:51,520 --> 00:05:56,240 Speaker 1: leads to playing two extinctions industry term. Basically, the machine 108 00:05:56,320 --> 00:05:58,640 Speaker 1: getting all your cash and then making you come back 109 00:05:58,680 --> 00:06:01,200 Speaker 1: to play again when you've got more are draining the 110 00:06:01,279 --> 00:06:05,040 Speaker 1: host dry of its precious blood. So unless you want 111 00:06:05,080 --> 00:06:08,119 Speaker 1: to make gambling illegal or something, one of the best 112 00:06:08,120 --> 00:06:12,680 Speaker 1: defenses against this type of machine is for independent researchers 113 00:06:12,720 --> 00:06:15,720 Speaker 1: to study the psychology of gaming, basically to understand how 114 00:06:15,760 --> 00:06:18,760 Speaker 1: these machines exploit our brains, so we can build up 115 00:06:18,800 --> 00:06:22,920 Speaker 1: defense behaviors that people could employ independently to resist the machines, 116 00:06:23,000 --> 00:06:25,960 Speaker 1: or maybe so you could impose regulations on what types 117 00:06:26,000 --> 00:06:28,880 Speaker 1: of things these machines can do. Well, like what one 118 00:06:28,920 --> 00:06:31,760 Speaker 1: of the issues that we got into before was what 119 00:06:31,880 --> 00:06:34,120 Speaker 1: happens when a machine is speaking to you in a 120 00:06:34,200 --> 00:06:39,039 Speaker 1: human voice or using other kind of anthropomorphic forms, like 121 00:06:39,160 --> 00:06:41,800 Speaker 1: if if you were to pass a lot and says, look, 122 00:06:41,839 --> 00:06:43,640 Speaker 1: you can have slot machines, but they can't look like 123 00:06:43,680 --> 00:06:47,080 Speaker 1: beautiful women. They can't look like cartoon characters. That's they 124 00:06:47,080 --> 00:06:49,840 Speaker 1: can't be a cowboy that says, howdy, partner, put coins 125 00:06:49,880 --> 00:06:53,760 Speaker 1: in me. And that is actually a meaningful thing because 126 00:06:54,000 --> 00:06:56,479 Speaker 1: studies have shown that you might spend more money in 127 00:06:56,520 --> 00:06:59,479 Speaker 1: a slot machine that seems more humanoid and less mechanical. 128 00:06:59,720 --> 00:07:02,240 Speaker 1: So the tons of studies like this, there's just a 129 00:07:02,279 --> 00:07:06,760 Speaker 1: prolific slot machine research. This is one example that is 130 00:07:06,839 --> 00:07:09,320 Speaker 1: maybe the weirdest one I've ever come across, but I 131 00:07:09,360 --> 00:07:12,560 Speaker 1: like it. So Rock Lofting Career decided to study this 132 00:07:12,680 --> 00:07:15,720 Speaker 1: strange condition. What happens when you have the opportunity to 133 00:07:15,800 --> 00:07:18,840 Speaker 1: gamble on an e g M after you've just held 134 00:07:18,840 --> 00:07:23,560 Speaker 1: a saltwater crocodile. The so the subjects are tourists at 135 00:07:23,600 --> 00:07:29,080 Speaker 1: the Kurana Saltwater Crocodile Farm in Kowonga, Queensland, Australia. It 136 00:07:29,160 --> 00:07:31,840 Speaker 1: was a hundred and three subjects, forty one of them female, 137 00:07:32,360 --> 00:07:35,520 Speaker 1: uh ages eighteen to sixty six. And here's the experiment 138 00:07:36,440 --> 00:07:39,880 Speaker 1: under two different conditions. Subjects would be given money. They'll 139 00:07:39,880 --> 00:07:42,320 Speaker 1: give you twenty bucks, and then they ask you to 140 00:07:42,480 --> 00:07:45,680 Speaker 1: play a laptop simulated e g M sort of a 141 00:07:45,720 --> 00:07:48,880 Speaker 1: slot machine simulator written in visual basic on a laptop 142 00:07:48,960 --> 00:07:52,000 Speaker 1: computer where you would get to gamble with the money 143 00:07:52,040 --> 00:07:55,480 Speaker 1: they just gave you. And the two different conditions were this, 144 00:07:56,000 --> 00:07:57,880 Speaker 1: you could either play this game or right before you 145 00:07:57,920 --> 00:08:01,760 Speaker 1: walk into the crocodile farm or right after you have 146 00:08:01,880 --> 00:08:05,240 Speaker 1: cradled a one meter long saltwater crocodile in your hands. 147 00:08:05,720 --> 00:08:08,320 Speaker 1: So there are some independent variables going into this. Right 148 00:08:08,360 --> 00:08:11,280 Speaker 1: you've got obviously the control condition and the test condition 149 00:08:11,360 --> 00:08:13,880 Speaker 1: did you just walk in or have you handled a crocodile, 150 00:08:13,960 --> 00:08:16,720 Speaker 1: and so that is supposed to correspond to your level 151 00:08:16,720 --> 00:08:20,040 Speaker 1: of arousal. They did a galvanic skin conductance test to 152 00:08:20,040 --> 00:08:22,200 Speaker 1: to sort of check this and say, okay, we're people 153 00:08:22,240 --> 00:08:25,640 Speaker 1: actually showing physiological signs of arousal, and they determined yeah, 154 00:08:25,680 --> 00:08:29,920 Speaker 1: people who held crocodiles were physiologically aroused. But the other 155 00:08:29,960 --> 00:08:33,480 Speaker 1: independent variables would be problem gaming status, like do do 156 00:08:33,559 --> 00:08:35,880 Speaker 1: you have any of the risk factors for being a 157 00:08:35,920 --> 00:08:40,920 Speaker 1: problem gambler or affective state? Are you having negative feelings 158 00:08:41,040 --> 00:08:43,520 Speaker 1: right now, and so they'd established that by a questionnaire 159 00:08:44,040 --> 00:08:46,360 Speaker 1: UH that they administer at the time of the test, 160 00:08:46,480 --> 00:08:49,400 Speaker 1: like are you having emotions that we'd usually classify as 161 00:08:49,400 --> 00:08:53,559 Speaker 1: negative affect or positive affect? And then the deependit variables. 162 00:08:53,600 --> 00:08:55,680 Speaker 1: This is what they were seeing. Was was coming out 163 00:08:55,720 --> 00:08:58,440 Speaker 1: from those variables was bet size, how much you bet, 164 00:08:58,760 --> 00:09:02,040 Speaker 1: speed of betting, how asty bet, and final payouts like 165 00:09:02,080 --> 00:09:04,079 Speaker 1: what what's your your bottom line at the end of 166 00:09:04,120 --> 00:09:07,559 Speaker 1: the game. And the results they found where that compared 167 00:09:07,600 --> 00:09:10,920 Speaker 1: to people in the control group, holding a crocodile could 168 00:09:10,960 --> 00:09:14,559 Speaker 1: affect problem gamblers in a couple of different ways. If 169 00:09:14,600 --> 00:09:19,240 Speaker 1: you held a crocodile and had negative emotions, you actually 170 00:09:19,240 --> 00:09:22,520 Speaker 1: placed lower than average bets on the e g M. 171 00:09:22,960 --> 00:09:25,880 Speaker 1: So if you're somebody who's at risk for problem gambling, 172 00:09:26,280 --> 00:09:28,679 Speaker 1: they hand you a crocodile and you don't like it 173 00:09:28,760 --> 00:09:32,400 Speaker 1: and you have negative emotions, you'll actually it will tamp 174 00:09:32,480 --> 00:09:35,839 Speaker 1: down your problem gambling behaviors. You're less likely to spend 175 00:09:35,840 --> 00:09:39,280 Speaker 1: more interesting But if you are a problem gambler or 176 00:09:39,320 --> 00:09:42,240 Speaker 1: have these you know, risk factors for problem gambling, and 177 00:09:42,280 --> 00:09:45,240 Speaker 1: you hold a crocodile and you don't have negative feelings 178 00:09:45,280 --> 00:09:48,800 Speaker 1: about it, you actually place much higher than average bets 179 00:09:48,840 --> 00:09:51,720 Speaker 1: on the e g M. That's what I imagined would happen, 180 00:09:51,760 --> 00:09:54,720 Speaker 1: That there's some kind of like I held this dangerous 181 00:09:54,760 --> 00:09:57,720 Speaker 1: animal and everything turned out okay, so now I'm willing 182 00:09:57,760 --> 00:10:02,199 Speaker 1: to take more risks. Well, So here's how the researchers 183 00:10:02,240 --> 00:10:04,240 Speaker 1: interpreted it. I'll see what you guys think about this. 184 00:10:04,480 --> 00:10:06,520 Speaker 1: The way they interpreted it is that they're going on 185 00:10:06,520 --> 00:10:10,000 Speaker 1: what's known as the two factor model of effective states. 186 00:10:10,160 --> 00:10:13,120 Speaker 1: So the way they think affective states tend to happen 187 00:10:13,240 --> 00:10:17,200 Speaker 1: is that we first of all experience physiological arousal, like 188 00:10:17,280 --> 00:10:20,480 Speaker 1: there are feelings in the body that tell you something 189 00:10:20,760 --> 00:10:24,760 Speaker 1: of emotional significance is happening, and then secondary to that, 190 00:10:24,840 --> 00:10:28,240 Speaker 1: you cognitively think about it and give it some kind 191 00:10:28,240 --> 00:10:31,640 Speaker 1: of meaning or significance or cause. So what would happen, 192 00:10:31,760 --> 00:10:35,320 Speaker 1: say if, um, you suddenly a car is driving head 193 00:10:35,360 --> 00:10:37,400 Speaker 1: on at you in the highways. First you have the 194 00:10:37,440 --> 00:10:40,880 Speaker 1: feelings in your body there's some kind of arousal, and 195 00:10:40,920 --> 00:10:43,720 Speaker 1: then you use your sense data and your thoughts to 196 00:10:43,760 --> 00:10:46,360 Speaker 1: kind of say, okay, here's why that's happening. I'm afraid 197 00:10:46,440 --> 00:10:49,480 Speaker 1: because a car is coming at me um. And so 198 00:10:50,160 --> 00:10:53,560 Speaker 1: what that means, though, is that the feelings of arousal 199 00:10:53,559 --> 00:10:57,480 Speaker 1: in the body are not necessarily linked to their actual causes. 200 00:10:58,000 --> 00:11:00,360 Speaker 1: It's just something that we sort of figure you're out 201 00:11:00,440 --> 00:11:04,360 Speaker 1: secondary to having the feeling. And so the way that 202 00:11:04,440 --> 00:11:06,880 Speaker 1: might work in a gambler is if you do something 203 00:11:07,000 --> 00:11:12,080 Speaker 1: dangerous or something arousing, like holding a dangerous reptile, you 204 00:11:12,120 --> 00:11:14,800 Speaker 1: can you get this physiological sense of arousal. But the 205 00:11:14,880 --> 00:11:19,360 Speaker 1: gambler who doesn't have fear emotions really about that animal 206 00:11:19,520 --> 00:11:22,560 Speaker 1: or any other kind of negative emotions, can just interpret 207 00:11:22,679 --> 00:11:26,360 Speaker 1: that free floating arousal as a lucky streak. So it's like, 208 00:11:26,400 --> 00:11:29,760 Speaker 1: I'm pumped up by what just happened, and I'm that 209 00:11:29,800 --> 00:11:32,640 Speaker 1: means I'm good to go. Let's gamble. I'm I just 210 00:11:32,679 --> 00:11:35,160 Speaker 1: had the crocodile. I'm ready to drop some cash. Yeah, 211 00:11:35,160 --> 00:11:38,560 Speaker 1: it's content content free arousal that you can interpret in 212 00:11:38,679 --> 00:11:41,600 Speaker 1: any schema you want. And for the problem gambler, that 213 00:11:41,640 --> 00:11:44,680 Speaker 1: schema may very well be the feeling of luckiness or 214 00:11:44,720 --> 00:11:46,840 Speaker 1: the feeling of being on a roll. So I gotta 215 00:11:46,920 --> 00:11:50,280 Speaker 1: ask you, then, how well do you think Kenny Rogers 216 00:11:50,559 --> 00:11:54,520 Speaker 1: the gambler would do based on his crocodile experience was it. 217 00:11:54,600 --> 00:11:56,840 Speaker 1: Maybe here's the thing he maybe he was talking about 218 00:11:56,960 --> 00:11:58,959 Speaker 1: a crocodile. You've got to know when to hold the 219 00:11:59,000 --> 00:12:01,800 Speaker 1: crocodile and when to run. See, that would actually be 220 00:12:01,840 --> 00:12:06,319 Speaker 1: more specific. I've got issues with Kenny Rogers the Gambler 221 00:12:06,360 --> 00:12:10,040 Speaker 1: who doesn't because I think it fits into this category 222 00:12:10,200 --> 00:12:15,160 Speaker 1: of advice that is not actually specific enough to matter. There. 223 00:12:15,200 --> 00:12:17,319 Speaker 1: There's tons of advice like that out in the world. 224 00:12:17,360 --> 00:12:20,120 Speaker 1: You'll read these, you know, inspirational quotes. People have whole 225 00:12:20,160 --> 00:12:22,920 Speaker 1: books like this where they offer advice, but the advice 226 00:12:22,960 --> 00:12:26,880 Speaker 1: is actually completely generic. It's essentially like telling somebody you 227 00:12:26,920 --> 00:12:29,200 Speaker 1: should figure out what the right thing to do is. 228 00:12:29,280 --> 00:12:31,520 Speaker 1: It's like a fortune cookie. Yeah, and so in the 229 00:12:31,679 --> 00:12:33,439 Speaker 1: in the song, it's you've got to know when to 230 00:12:33,520 --> 00:12:35,720 Speaker 1: hold them, no, when to fold them. That's not advice. 231 00:12:35,760 --> 00:12:38,520 Speaker 1: Advice would be telling me what to judge that on, 232 00:12:38,720 --> 00:12:41,679 Speaker 1: Like how should I know when to hold them? Uh, 233 00:12:41,960 --> 00:12:44,640 Speaker 1: this is completely an aside. But if you want some fun, 234 00:12:44,880 --> 00:12:47,520 Speaker 1: look up the video of him performing that song on 235 00:12:47,559 --> 00:12:50,360 Speaker 1: The Muppet Show in the eighties. Now he does he 236 00:12:50,400 --> 00:12:52,439 Speaker 1: does give us some advice. You never count your money. 237 00:12:52,760 --> 00:12:54,680 Speaker 1: I want you sitting at the table that Okay, I'll 238 00:12:54,679 --> 00:12:57,120 Speaker 1: give him that. That is specific advice. I'll take that. 239 00:12:57,240 --> 00:12:58,640 Speaker 1: But you've got to know when to hold them, no 240 00:12:58,679 --> 00:13:01,720 Speaker 1: one to fold them. That's not advice, that's just generic 241 00:13:01,800 --> 00:13:04,719 Speaker 1: fortune teller stuff. But anyway, I wanted to come back 242 00:13:04,720 --> 00:13:06,880 Speaker 1: to the study because there are some masterisks we should 243 00:13:06,880 --> 00:13:09,320 Speaker 1: put on this. Number one is I want to clarify 244 00:13:09,440 --> 00:13:12,760 Speaker 1: that this only seemed to be the case for problem gamblers, 245 00:13:13,120 --> 00:13:16,200 Speaker 1: So like holding the crocodile, just for normal people who 246 00:13:16,200 --> 00:13:18,640 Speaker 1: do who did not have these risk factors for being 247 00:13:18,679 --> 00:13:23,640 Speaker 1: a problem gambler, did not seem to intensify betting, and uh, 248 00:13:23,840 --> 00:13:26,440 Speaker 1: like these would be people for whom gambling is not 249 00:13:26,520 --> 00:13:30,320 Speaker 1: a novel experience, but maybe holding a crocodile is, whereas 250 00:13:30,360 --> 00:13:34,679 Speaker 1: from for me, holding a crocodile is the novel experience, 251 00:13:34,760 --> 00:13:38,280 Speaker 1: as is using a slot machine. Right, so you you 252 00:13:38,360 --> 00:13:41,800 Speaker 1: probably would not place higher bets or or have intensified 253 00:13:41,840 --> 00:13:45,840 Speaker 1: gambling or reward seeking behaviors after holding a crocodile, or likewise, 254 00:13:45,840 --> 00:13:48,040 Speaker 1: somebody who had a strict rule like, yeah, I play 255 00:13:48,120 --> 00:13:49,960 Speaker 1: the slot machines when I go to the casino, but 256 00:13:50,000 --> 00:13:52,800 Speaker 1: I only spend five dollars and once that's gone. I'm done, 257 00:13:52,840 --> 00:13:55,120 Speaker 1: and I never break that rule. Right. Yeah, So people 258 00:13:55,120 --> 00:13:57,959 Speaker 1: who don't exhibit these behaviors, this doesn't apply to them. 259 00:13:58,000 --> 00:14:00,320 Speaker 1: It does seem to apply to people who are risk 260 00:14:00,400 --> 00:14:03,520 Speaker 1: for problem gambling. But there is a limitation to the study. 261 00:14:03,600 --> 00:14:06,120 Speaker 1: Essentially that they did not have a lot of people 262 00:14:06,200 --> 00:14:09,640 Speaker 1: in their sample group who showed problem gambling behaviors or 263 00:14:09,880 --> 00:14:12,440 Speaker 1: or risk factors. So one thing would be that they 264 00:14:12,440 --> 00:14:15,400 Speaker 1: should probably try to replicate this to have more confidence 265 00:14:15,440 --> 00:14:18,400 Speaker 1: in the in the result with a larger sample group 266 00:14:18,480 --> 00:14:20,880 Speaker 1: that has more problem gamblers, and it just to make 267 00:14:20,880 --> 00:14:23,320 Speaker 1: sure that they're getting a real effect and this isn't 268 00:14:23,320 --> 00:14:25,960 Speaker 1: just noise. Now. Remember also, the thing is that even 269 00:14:26,000 --> 00:14:28,600 Speaker 1: among the problem gamblers, it was only when you don't 270 00:14:28,680 --> 00:14:32,000 Speaker 1: have any negative moods or negative feelings about holding the 271 00:14:32,040 --> 00:14:35,080 Speaker 1: crocodile that it leads to these intensified behaviors. If you 272 00:14:35,120 --> 00:14:38,360 Speaker 1: have these negative moods, you report it actually kind of 273 00:14:38,360 --> 00:14:41,720 Speaker 1: seems to moderate your gambling behavior. And so that sets 274 00:14:41,760 --> 00:14:43,280 Speaker 1: up this quote I want to read from the paper. 275 00:14:43,360 --> 00:14:47,960 Speaker 1: Quote in some low intensity negative moods, such as boredom 276 00:14:48,080 --> 00:14:52,920 Speaker 1: or mild anxiety, contribute to large bets among at risk players. 277 00:14:53,200 --> 00:14:58,600 Speaker 1: Whereas high autonomic arousal without negative moods also produces relatively 278 00:14:58,680 --> 00:15:03,000 Speaker 1: large wagers. Taken together, the results suggest that betting among 279 00:15:03,120 --> 00:15:06,520 Speaker 1: at risk players may be motivated both by attempts to 280 00:15:06,560 --> 00:15:12,240 Speaker 1: alleviate low arousal dysphoric moods and by high arousal induced 281 00:15:12,320 --> 00:15:16,320 Speaker 1: positive expectations of winning money. Yeah, totally. This lines up 282 00:15:16,320 --> 00:15:18,400 Speaker 1: with the social media thing as well. I think, yeah, 283 00:15:18,480 --> 00:15:20,720 Speaker 1: that makes sense. So it's like when you when you're 284 00:15:20,720 --> 00:15:23,680 Speaker 1: a problem gambler and you participate in these gambling behaviors, 285 00:15:23,680 --> 00:15:26,800 Speaker 1: it seems you may be trying to counteract basically like 286 00:15:27,160 --> 00:15:33,680 Speaker 1: low level unpleasantness and seeking high arousal, high reward pleas 287 00:15:34,120 --> 00:15:37,120 Speaker 1: you know, high high pleasure interactions. Right, But if you're 288 00:15:37,160 --> 00:15:41,000 Speaker 1: like absolutely in the pits emotionally, you're probably not going 289 00:15:41,040 --> 00:15:43,720 Speaker 1: to be likely to gamble as much as that the 290 00:15:43,800 --> 00:15:46,000 Speaker 1: person who's just sort of low level and happy, right, 291 00:15:46,040 --> 00:15:48,440 Speaker 1: a little bit anxious, a little bit bored, that's the 292 00:15:48,480 --> 00:15:51,880 Speaker 1: target show. Yeah, So what's the what what's the overall 293 00:15:51,920 --> 00:15:54,400 Speaker 1: takeaway from this? Is there any kind of crocodile based 294 00:15:54,440 --> 00:15:58,280 Speaker 1: regulation that might be employed to help problem gambling? Well, 295 00:15:58,280 --> 00:16:01,480 Speaker 1: I wouldn't say crocodile based. I mean, I think it. 296 00:16:01,520 --> 00:16:04,440 Speaker 1: Studies like this actually do matter, like that, this is 297 00:16:04,440 --> 00:16:06,400 Speaker 1: the kind of thing that can help us understand the 298 00:16:06,440 --> 00:16:09,960 Speaker 1: psychological states that lead to problem gambling and can help 299 00:16:10,040 --> 00:16:13,360 Speaker 1: people either individually can help people come up with strategies 300 00:16:13,400 --> 00:16:16,640 Speaker 1: to avoid problem gambling behaviors if they know, like, Okay, 301 00:16:16,880 --> 00:16:19,120 Speaker 1: here's the state I'm in when I'm vulnerable. I know 302 00:16:19,160 --> 00:16:22,040 Speaker 1: when I'm in that state, I should, uh, you know, 303 00:16:22,160 --> 00:16:25,120 Speaker 1: not be around electronic gaming machines or something like that. 304 00:16:25,160 --> 00:16:29,040 Speaker 1: Like you can devise behaviors to protect yourself from your 305 00:16:29,080 --> 00:16:33,880 Speaker 1: own impulses, or you could also devise regulations on society, 306 00:16:33,920 --> 00:16:36,600 Speaker 1: like if we find out that in general, people are 307 00:16:36,640 --> 00:16:41,320 Speaker 1: just much more susceptible to electronic gaming machines under certain 308 00:16:41,320 --> 00:16:45,160 Speaker 1: psychological conditions, you could try to keep gaming machines from 309 00:16:45,160 --> 00:16:47,840 Speaker 1: being around in places where you would expect people to 310 00:16:47,920 --> 00:16:51,360 Speaker 1: be in those conditions. Or you end up you end 311 00:16:51,440 --> 00:16:54,200 Speaker 1: up having just like some sort of a B S 312 00:16:54,360 --> 00:16:57,320 Speaker 1: question that pops up on the screen. Uh, please write 313 00:16:57,360 --> 00:16:59,520 Speaker 1: your depression level and if you and if you and 314 00:16:59,560 --> 00:17:02,240 Speaker 1: if you ad it too appropriately, then it won't let 315 00:17:02,240 --> 00:17:03,920 Speaker 1: you play right, And then you do it again and 316 00:17:03,960 --> 00:17:07,040 Speaker 1: you just click the number that's required, like an age gate. 317 00:17:10,119 --> 00:17:12,000 Speaker 1: They have a test in the machine to see if 318 00:17:12,040 --> 00:17:14,600 Speaker 1: you're okay or you having kind of like no, no 319 00:17:14,760 --> 00:17:18,320 Speaker 1: real strong negative emotions, but experiencing high arousal. I don't 320 00:17:18,359 --> 00:17:20,399 Speaker 1: know how you test for that, but but if you 321 00:17:20,440 --> 00:17:22,600 Speaker 1: detect that, it's like you better not gamble right now. 322 00:17:22,680 --> 00:17:24,480 Speaker 1: I mean, if you wanted to do it physiologically, you 323 00:17:24,520 --> 00:17:27,119 Speaker 1: could actually do a galvanic skin conductance test, you know, 324 00:17:27,160 --> 00:17:30,080 Speaker 1: like you could test for arousal with a physical test 325 00:17:30,119 --> 00:17:32,119 Speaker 1: and not a questionnaire. Yeah, I can see that, you like, 326 00:17:32,160 --> 00:17:34,600 Speaker 1: put your arm into a cuff of some sort and test. 327 00:17:34,840 --> 00:17:37,480 Speaker 1: It's like you're too aroused. You can't, can't play right now. 328 00:17:38,280 --> 00:17:39,800 Speaker 1: But then you come back to the again, to the 329 00:17:40,160 --> 00:17:44,120 Speaker 1: the question, how much energy, how much effort, how much 330 00:17:44,160 --> 00:17:48,040 Speaker 1: design are slot machine makers going to be willing to 331 00:17:48,119 --> 00:17:52,480 Speaker 1: put into you know, basically protecting the host organs? Well, 332 00:17:52,520 --> 00:17:54,720 Speaker 1: of course, I mean when we did our last slot 333 00:17:54,760 --> 00:17:57,359 Speaker 1: machine episode, we had somebody right in who worked for 334 00:17:57,400 --> 00:18:00,080 Speaker 1: a gaming design company and they were like, you know, 335 00:18:00,160 --> 00:18:02,320 Speaker 1: I think you you were a little too harsh on us. 336 00:18:02,320 --> 00:18:05,320 Speaker 1: You were a little too negative about slot machines. You know, 337 00:18:05,359 --> 00:18:07,760 Speaker 1: I don't want to demonize them too much, because I 338 00:18:07,800 --> 00:18:10,919 Speaker 1: can understand, like, under plenty of conditions, they might just 339 00:18:10,960 --> 00:18:13,560 Speaker 1: be a fun thing people do, Like if they've got 340 00:18:13,800 --> 00:18:15,960 Speaker 1: certain limits on how much they bet, it might just 341 00:18:16,000 --> 00:18:18,679 Speaker 1: be a cool recreational activity. I don't have a problem 342 00:18:18,680 --> 00:18:22,359 Speaker 1: with that, but I think we should recognize that certain 343 00:18:22,359 --> 00:18:25,320 Speaker 1: people have conditions that make them vulnerable to this and 344 00:18:25,359 --> 00:18:27,720 Speaker 1: that can be incredibly destructive in their lives. Well, I 345 00:18:27,720 --> 00:18:29,119 Speaker 1: think one of the things that we observed in that 346 00:18:29,160 --> 00:18:32,120 Speaker 1: episode is that the origins of the slot machine were 347 00:18:32,200 --> 00:18:36,280 Speaker 1: very mundane and fun. It was about, uh, administering a 348 00:18:36,280 --> 00:18:40,359 Speaker 1: prize in a simple game, not unlike you know, like 349 00:18:40,359 --> 00:18:44,520 Speaker 1: a trivia machine or something in bars today. But the machine, 350 00:18:44,560 --> 00:18:48,919 Speaker 1: as machines do, uh, they they evolved, They took on 351 00:18:49,040 --> 00:18:51,800 Speaker 1: more advanced forms, they were designed to take on more 352 00:18:51,800 --> 00:18:55,760 Speaker 1: advanced forms. They became better and better at at carrying 353 00:18:55,760 --> 00:18:59,080 Speaker 1: out their their key bit of programming, which was, you know, 354 00:18:59,160 --> 00:19:03,000 Speaker 1: drain the sucker of its coin, the original Facebook algorithm. 355 00:19:03,080 --> 00:19:06,040 Speaker 1: Have you guys noticed this trend in video games lately 356 00:19:06,119 --> 00:19:08,399 Speaker 1: when you're in like an immersive world video game, that 357 00:19:08,440 --> 00:19:12,000 Speaker 1: there is almost always a gambling component to it, Like 358 00:19:12,080 --> 00:19:14,800 Speaker 1: if you're in like Skyrim you can gamble. If you're 359 00:19:14,800 --> 00:19:17,760 Speaker 1: in Red Dead Redemption, you can gamble. I'm trying to 360 00:19:17,800 --> 00:19:19,840 Speaker 1: remember what the most recent one. Oh, the Witcher. I 361 00:19:19,880 --> 00:19:22,120 Speaker 1: was playing one of those Witcher games. It's like, everywhere 362 00:19:22,160 --> 00:19:24,200 Speaker 1: you go you can sit down and gamble. I would 363 00:19:24,200 --> 00:19:27,720 Speaker 1: say that the games like that incorporate gambling elements even 364 00:19:27,720 --> 00:19:30,240 Speaker 1: outside of the gaming within the gaming things. So in 365 00:19:30,240 --> 00:19:31,840 Speaker 1: a lot of these games, you can walk up to 366 00:19:31,880 --> 00:19:33,959 Speaker 1: a slot machine and play it, or you can play cards, 367 00:19:34,000 --> 00:19:37,520 Speaker 1: but also when you're in the world, there are variable 368 00:19:37,640 --> 00:19:41,800 Speaker 1: reward payouts where, for example, if your achievements yeah yeah, 369 00:19:41,840 --> 00:19:44,159 Speaker 1: you know, you might kill certain enemies or something, and 370 00:19:44,200 --> 00:19:47,320 Speaker 1: they've got goodies they give you when you loot them, 371 00:19:47,640 --> 00:19:50,240 Speaker 1: and you notice you don't get the same thing every time. 372 00:19:50,560 --> 00:19:54,320 Speaker 1: It's not guaranteed. It's variable payouts, just like a slot machine, 373 00:19:54,680 --> 00:19:57,720 Speaker 1: and the variable payouts are a psychological hack. The variable 374 00:19:57,760 --> 00:19:59,720 Speaker 1: payouts make us think like, oh, it could be really 375 00:19:59,720 --> 00:20:01,600 Speaker 1: big next time. I'm gonna keep doing it. That's what 376 00:20:01,680 --> 00:20:04,480 Speaker 1: leads to grinding and video games. Yeah, yeah, I think 377 00:20:04,560 --> 00:20:08,320 Speaker 1: I wonder though, if there's something about the actual placing 378 00:20:08,440 --> 00:20:13,359 Speaker 1: of gambling into those games that psychologically gets players to 379 00:20:13,359 --> 00:20:16,000 Speaker 1: play longer. Yeah, I think that could very well be. 380 00:20:16,119 --> 00:20:17,520 Speaker 1: All right. On that note, we're going to take a 381 00:20:17,520 --> 00:20:19,600 Speaker 1: break and when we come back, we're going to jump 382 00:20:19,640 --> 00:20:26,840 Speaker 1: into the Cognition prize. Alright, we're back cognition. You say, 383 00:20:26,880 --> 00:20:30,480 Speaker 1: what have we got here? We have a paper titled 384 00:20:30,720 --> 00:20:33,680 Speaker 1: is that Me or My Twin? Lack of self face 385 00:20:33,800 --> 00:20:38,560 Speaker 1: recognition advantage in identical Twins. I saw this and as 386 00:20:38,600 --> 00:20:40,920 Speaker 1: we were doing the research for this yesterday a headline 387 00:20:40,960 --> 00:20:45,399 Speaker 1: popped up that was related to this. Apparently, Uh, you know, 388 00:20:45,560 --> 00:20:48,840 Speaker 1: when your phone does facial recognition as a way to unlock, 389 00:20:49,119 --> 00:20:54,040 Speaker 1: like as as a password, it has trouble with identical twins. Yeah, 390 00:20:54,080 --> 00:20:56,080 Speaker 1: so I wonder if what you're about to reveal to 391 00:20:56,160 --> 00:20:58,840 Speaker 1: us is related in a way. In a way, So, 392 00:20:59,160 --> 00:21:03,040 Speaker 1: this is a paper that came out in and it's 393 00:21:03,080 --> 00:21:06,480 Speaker 1: from a an Italian and Spanish team and it was 394 00:21:06,520 --> 00:21:10,040 Speaker 1: published in p Los one it. Uh, Before we get 395 00:21:10,080 --> 00:21:13,080 Speaker 1: into it, I do want to just touch basically on 396 00:21:13,560 --> 00:21:16,919 Speaker 1: the idea of identical twins. And uh, we've had some 397 00:21:16,960 --> 00:21:18,919 Speaker 1: episodes in the past. I've dealt with twins a little bit, 398 00:21:18,960 --> 00:21:20,439 Speaker 1: but I don't know, like I can't remember we've done 399 00:21:20,480 --> 00:21:22,960 Speaker 1: a deep dive. I know that we have some identical 400 00:21:22,960 --> 00:21:25,359 Speaker 1: twins out there listening to the show. I know that 401 00:21:25,400 --> 00:21:29,600 Speaker 1: we have parents of identical twins, siblings of identical twins, etcetera. 402 00:21:29,960 --> 00:21:33,359 Speaker 1: For a lot of us, though, our main point of 403 00:21:33,400 --> 00:21:37,080 Speaker 1: reference for identical twins ends up being fiction because how 404 00:21:37,119 --> 00:21:39,880 Speaker 1: many of example, how many examples can you think of of, 405 00:21:39,920 --> 00:21:43,200 Speaker 1: like weird twins or twins with a paranormal link. Yeah, 406 00:21:43,200 --> 00:21:46,080 Speaker 1: it's played up for the uncanny nous. I mean they 407 00:21:46,160 --> 00:21:48,720 Speaker 1: push it to creepy links and things like The Shining 408 00:21:48,840 --> 00:21:52,199 Speaker 1: or Dead Ringers. Yeah. Uh, and I and I say this, 409 00:21:52,520 --> 00:21:55,160 Speaker 1: I mean I have written stories about creepy twins before, 410 00:21:55,760 --> 00:22:00,000 Speaker 1: because they it does become a useful way of examining yourself, 411 00:22:00,040 --> 00:22:03,880 Speaker 1: examining identity, uh, at least if you're out an outside 412 00:22:03,920 --> 00:22:06,680 Speaker 1: or if you're not an identical twin. Likewise, I'm glad 413 00:22:06,680 --> 00:22:09,320 Speaker 1: you mentioned dead Ringers because you also see it used 414 00:22:09,359 --> 00:22:12,320 Speaker 1: over and over again in films. Sometimes it feels like 415 00:22:12,359 --> 00:22:16,000 Speaker 1: just pure actor or director vanity, Like let's have this 416 00:22:16,080 --> 00:22:19,760 Speaker 1: actor play two characters. Why have one James Franco when 417 00:22:19,800 --> 00:22:23,200 Speaker 1: you can have to James Franco is playing slightly different 418 00:22:23,760 --> 00:22:31,120 Speaker 1: James Franco twins. Yeah, yeah, I immediately thought of that. 419 00:22:31,119 --> 00:22:34,400 Speaker 1: That recent movie about the Crab Brothers legend where Tom 420 00:22:34,440 --> 00:22:36,639 Speaker 1: Hardy plays both the oh yeah, he plays he plays 421 00:22:36,640 --> 00:22:41,080 Speaker 1: identical twins. Uh. There was the recent Fargo season they 422 00:22:41,119 --> 00:22:44,160 Speaker 1: had identical twins played by the same actor. It's done 423 00:22:44,200 --> 00:22:47,080 Speaker 1: so many times that you get tired of it after 424 00:22:47,119 --> 00:22:50,280 Speaker 1: a while, unless there's a really compelling reason to have 425 00:22:50,520 --> 00:22:53,560 Speaker 1: identical twins played by single actor. I just got to 426 00:22:53,600 --> 00:22:56,040 Speaker 1: throw in that one of my favorite words in all 427 00:22:56,080 --> 00:23:00,640 Speaker 1: of science is the word for identical twins, the monozygotic twins. Yeah, 428 00:23:00,680 --> 00:23:04,960 Speaker 1: the monosygotic twinka. It is utilized in this paper quite 429 00:23:05,000 --> 00:23:09,600 Speaker 1: a bit now on top of so so basically it 430 00:23:09,640 --> 00:23:11,520 Speaker 1: comes down to the idea that for us non twins, 431 00:23:12,119 --> 00:23:15,840 Speaker 1: identical twins are a way to unravel ourselves. They perplex 432 00:23:15,920 --> 00:23:18,760 Speaker 1: us and they toy with our sense of self perception. 433 00:23:19,440 --> 00:23:21,960 Speaker 1: And as the researchers on this, uh, this paper, this 434 00:23:22,040 --> 00:23:26,000 Speaker 1: two thousand fIF paper point out, science has generally overlooked 435 00:23:26,040 --> 00:23:30,359 Speaker 1: the conundrum of self facial recognition in identical twins. We 436 00:23:30,359 --> 00:23:32,159 Speaker 1: have a lot of twin studies out there, but there 437 00:23:32,160 --> 00:23:34,560 Speaker 1: hasn't been a lot of papers that have looked at. 438 00:23:34,600 --> 00:23:38,520 Speaker 1: What happens when an identical twin looks at a photograph 439 00:23:38,760 --> 00:23:41,480 Speaker 1: or image of representation of their own face. Do they 440 00:23:41,480 --> 00:23:45,840 Speaker 1: experience some kind of cognitive dissonance? Yeah, because consider for 441 00:23:45,840 --> 00:23:47,360 Speaker 1: for the for the rest of us, for those of 442 00:23:47,480 --> 00:23:52,959 Speaker 1: us who are not identical twins. Um, self facial recognition 443 00:23:53,080 --> 00:23:55,480 Speaker 1: is is a major thing, and it may be a 444 00:23:55,520 --> 00:23:59,959 Speaker 1: cognitive prerequisite for theory of mind, our ability to imagine 445 00:24:00,000 --> 00:24:02,119 Speaker 1: the mind state of others. Because just think of all 446 00:24:02,119 --> 00:24:04,560 Speaker 1: the times you've looked in a mirror, you've taken a selfie, 447 00:24:04,640 --> 00:24:06,280 Speaker 1: or if you've looked at a picture of yourself and 448 00:24:06,320 --> 00:24:09,119 Speaker 1: you think, ah, who's that handsome devil? You know? And 449 00:24:09,160 --> 00:24:12,120 Speaker 1: then you answer that question, you you tell yourself who 450 00:24:12,119 --> 00:24:15,200 Speaker 1: that handsome devil is? Yeah? Why why is he making 451 00:24:15,200 --> 00:24:18,320 Speaker 1: a smile like that? What's that twinkle in his eyes? Um, 452 00:24:18,320 --> 00:24:21,280 Speaker 1: it's the evil twin? Well, you know, I'm I'm painting 453 00:24:21,280 --> 00:24:23,960 Speaker 1: in in in shades of vanity here, But there's a 454 00:24:24,000 --> 00:24:27,480 Speaker 1: there's a basic cognitive process that's going on when you 455 00:24:27,520 --> 00:24:30,000 Speaker 1: do that. You are identifying yourself and thinking about who 456 00:24:30,000 --> 00:24:34,119 Speaker 1: you are. Well, I mean people respond in hilarious, obsessive 457 00:24:34,240 --> 00:24:37,840 Speaker 1: ways to their own reflection when you notice it, like, uh, 458 00:24:37,880 --> 00:24:39,719 Speaker 1: you know, there's a reason that a lot of places 459 00:24:39,760 --> 00:24:43,040 Speaker 1: will put mirrors near elevators where people need to wait 460 00:24:43,080 --> 00:24:46,920 Speaker 1: for things. People just time flies. When you're looking in 461 00:24:46,960 --> 00:24:51,000 Speaker 1: a mirror, you can obsessively gaze into this image, right, 462 00:24:51,119 --> 00:24:53,320 Speaker 1: rather than worry about the people that are next to 463 00:24:53,320 --> 00:24:56,320 Speaker 1: you in the elevator. Yeah, and there's a there's a 464 00:24:56,359 --> 00:25:00,720 Speaker 1: similar uh, cognitive process going on when you look at 465 00:25:00,760 --> 00:25:02,879 Speaker 1: any face. You look at a loved one's face, you 466 00:25:02,920 --> 00:25:05,879 Speaker 1: look at a stranger's face. There's still this theory of 467 00:25:05,920 --> 00:25:08,440 Speaker 1: mind exercise that's going on. And what you're saying, who 468 00:25:08,560 --> 00:25:12,000 Speaker 1: is that handsome devil or who is that person with 469 00:25:12,440 --> 00:25:14,400 Speaker 1: you know, some brarow on, you know, whatever the case 470 00:25:14,440 --> 00:25:16,960 Speaker 1: may be, You're looking at the face and you're trying 471 00:25:16,960 --> 00:25:20,439 Speaker 1: to figure out who they are, at least insofar as 472 00:25:20,480 --> 00:25:23,800 Speaker 1: it relates to you. I've had like the opposite experience 473 00:25:23,840 --> 00:25:25,240 Speaker 1: with this, and I don't want to take us too 474 00:25:25,240 --> 00:25:28,399 Speaker 1: far off track, but when I used to ride the train, 475 00:25:29,080 --> 00:25:32,840 Speaker 1: the windows on the train were curved in such a 476 00:25:32,880 --> 00:25:34,840 Speaker 1: way that when you saw your own reflection in it, 477 00:25:34,920 --> 00:25:37,520 Speaker 1: your face was distorted a little bit, and it would 478 00:25:37,560 --> 00:25:40,359 Speaker 1: look like my forehead had ridges or something, or like 479 00:25:40,400 --> 00:25:42,399 Speaker 1: it was just it's kind of like a fun house mirror, 480 00:25:42,480 --> 00:25:45,760 Speaker 1: and I'm yeah, clings, that was exactly what it looked 481 00:25:45,800 --> 00:25:49,040 Speaker 1: like to me. Yeah, and uh, it was fascinating. I 482 00:25:49,080 --> 00:25:51,439 Speaker 1: would sit there and look at it for for the 483 00:25:51,440 --> 00:25:53,840 Speaker 1: whole ride and just kind of wonderment, like what if 484 00:25:53,840 --> 00:25:56,160 Speaker 1: I actually did look like that? You know. So there 485 00:25:56,280 --> 00:26:01,160 Speaker 1: is a weird sort of obsessiveness with our own uh reflection, 486 00:26:01,240 --> 00:26:04,760 Speaker 1: but also like just a slight variation on it. Yeah, 487 00:26:04,840 --> 00:26:06,800 Speaker 1: I mean, I think you see this in in skype 488 00:26:06,800 --> 00:26:11,120 Speaker 1: calls and FaceTime calls where everyone's looking at their own 489 00:26:11,119 --> 00:26:13,679 Speaker 1: picture instead of the camera. Maybe they're looking at other 490 00:26:13,720 --> 00:26:16,120 Speaker 1: people's pictures. I noticed it with my son because he's 491 00:26:16,119 --> 00:26:18,800 Speaker 1: just when I when I put him on FaceTime calls 492 00:26:18,840 --> 00:26:21,960 Speaker 1: with relatives, he's just captivated by the own little, the 493 00:26:21,960 --> 00:26:24,400 Speaker 1: little version of his own face, and he's not even 494 00:26:24,400 --> 00:26:27,160 Speaker 1: thinking about the call, much less someone on the other line. 495 00:26:28,480 --> 00:26:32,639 Speaker 1: And this underlines a basic reality. Our own face grabs 496 00:26:32,640 --> 00:26:36,520 Speaker 1: and retains attention longer than any other face out there, uh, 497 00:26:36,560 --> 00:26:39,359 Speaker 1: you know, loved one, stranger, etcetera. And this, according to 498 00:26:39,400 --> 00:26:43,840 Speaker 1: the researchers, occurs with both upright and inverted faces. So 499 00:26:43,880 --> 00:26:48,200 Speaker 1: we process upright faces faster usually, but we also have 500 00:26:48,280 --> 00:26:52,359 Speaker 1: the similar process that goes on when the face is 501 00:26:52,560 --> 00:26:56,240 Speaker 1: upside down. In fact, our ability to recognize our own 502 00:26:56,280 --> 00:26:59,680 Speaker 1: face holds true even in cases of severe face blindness, 503 00:27:00,040 --> 00:27:04,960 Speaker 1: accept in cases of just really catastrophic neurological or psychiatric disorder. 504 00:27:05,160 --> 00:27:07,199 Speaker 1: Another fun word the term there, I guess would be 505 00:27:07,240 --> 00:27:11,920 Speaker 1: auto prosopagnosia. Prosopagnosia is face blindness. Yes, so even in 506 00:27:12,200 --> 00:27:15,480 Speaker 1: cases of severe face blindness, again, your own face is 507 00:27:15,520 --> 00:27:19,160 Speaker 1: still going to um have a special place in uh 508 00:27:19,200 --> 00:27:23,359 Speaker 1: in in facial recognition. Okay, but there is a So 509 00:27:23,400 --> 00:27:26,080 Speaker 1: what we're getting at here is with the twins in particular, 510 00:27:26,760 --> 00:27:30,639 Speaker 1: they lack the ability to recognize their own face. And 511 00:27:30,640 --> 00:27:34,080 Speaker 1: these these twins that have a similar face to them, well, 512 00:27:34,119 --> 00:27:36,080 Speaker 1: I mean basically it comes comes down to the fact 513 00:27:36,080 --> 00:27:39,879 Speaker 1: that it's going to mess with this system because the 514 00:27:40,080 --> 00:27:43,000 Speaker 1: basic fact here is that if you have an identical twin, 515 00:27:43,520 --> 00:27:47,000 Speaker 1: then looking at your own face, looking at a representation 516 00:27:47,040 --> 00:27:50,520 Speaker 1: of your own face, it's not instantly going to be 517 00:27:50,880 --> 00:27:54,199 Speaker 1: your face. It could be your twins face. And and 518 00:27:54,240 --> 00:27:57,080 Speaker 1: so we're looking at this to see like what's different 519 00:27:57,080 --> 00:27:59,320 Speaker 1: without identical twins, and then what this reveals about our 520 00:27:59,320 --> 00:28:03,040 Speaker 1: own about everyone else's facial recognition process. Now, there are 521 00:28:03,040 --> 00:28:06,120 Speaker 1: a few other factors you have to take into account, so, uh, 522 00:28:06,240 --> 00:28:11,040 Speaker 1: self face processing is a right hemisphere um exercise, and 523 00:28:11,080 --> 00:28:16,200 Speaker 1: it's impaired in individuals with schizotypal traits. Also, extroverts, who 524 00:28:16,280 --> 00:28:19,680 Speaker 1: typically have better social skills, they recognize a higher number 525 00:28:19,680 --> 00:28:24,320 Speaker 1: of faces than introverts. Lower face recognition is associated with 526 00:28:24,400 --> 00:28:29,040 Speaker 1: increased social phobia. So in all of this, personality plays 527 00:28:29,040 --> 00:28:31,920 Speaker 1: a role in facial recognition as well, twin or not. 528 00:28:32,200 --> 00:28:34,960 Speaker 1: So this is good because it gives me a reason 529 00:28:35,080 --> 00:28:37,199 Speaker 1: to explain to my wife why I mix up like 530 00:28:37,240 --> 00:28:39,880 Speaker 1: actors and actresses all the time, because she's like, you 531 00:28:39,960 --> 00:28:43,080 Speaker 1: just think everybody looks alike, and well, no, it's because 532 00:28:43,120 --> 00:28:47,040 Speaker 1: actually I have lower face recognition because of my increased 533 00:28:47,080 --> 00:28:52,480 Speaker 1: social phobia. So, given all of of what we've discussed 534 00:28:52,520 --> 00:28:57,480 Speaker 1: so far, uh monosa gottic twins they pose an interesting 535 00:28:57,680 --> 00:29:01,240 Speaker 1: exception to the uniqueness of the self face because again, 536 00:29:02,240 --> 00:29:04,920 Speaker 1: when we see a representation of our own face, we 537 00:29:04,960 --> 00:29:08,000 Speaker 1: instantly know who that is. There's no room for doubt, 538 00:29:08,280 --> 00:29:10,640 Speaker 1: and the idea here with an identical twin, there's going 539 00:29:10,680 --> 00:29:15,280 Speaker 1: to be at least a little room for doubt, you know. Granted, 540 00:29:15,320 --> 00:29:18,400 Speaker 1: if one has an evil goatee or something, it's gonna 541 00:29:18,520 --> 00:29:20,719 Speaker 1: throw things out the window a bit. But for the 542 00:29:20,760 --> 00:29:23,600 Speaker 1: most part, uh, this is this is interesting to look 543 00:29:23,600 --> 00:29:25,800 Speaker 1: at because it turns things on its on there on 544 00:29:25,840 --> 00:29:30,200 Speaker 1: its head a little bit. So. Past predictions have been 545 00:29:30,200 --> 00:29:33,120 Speaker 1: made related to this that twins might have trouble with 546 00:29:33,160 --> 00:29:37,840 Speaker 1: self identification as they identify more as a duo. Also, 547 00:29:37,920 --> 00:29:42,040 Speaker 1: identical twins might sometimes mistake photos of their twin or 548 00:29:42,080 --> 00:29:44,560 Speaker 1: their self. That's been the previous thinking on this. Also, 549 00:29:44,640 --> 00:29:47,440 Speaker 1: another past study indicated that while humans can you usually 550 00:29:47,440 --> 00:29:50,360 Speaker 1: identify themselves in a mirror by age two, uh, you, 551 00:29:50,880 --> 00:29:54,120 Speaker 1: there have been cases where two year old twins discriminate 552 00:29:54,160 --> 00:29:56,640 Speaker 1: their own faces from the face of their co twins 553 00:29:56,720 --> 00:29:59,440 Speaker 1: only of exposed to the facial stimuli for a longer 554 00:29:59,480 --> 00:30:03,240 Speaker 1: period of time, So there might be a delay at least. 555 00:30:03,600 --> 00:30:06,200 Speaker 1: And studies have looked at young twins and their ability 556 00:30:06,200 --> 00:30:09,360 Speaker 1: to work out these faces. But prior to this study, 557 00:30:09,360 --> 00:30:11,200 Speaker 1: no one had really looked at the ability of adult 558 00:30:11,200 --> 00:30:14,360 Speaker 1: twins to tell their faces apart. Okay, so what do 559 00:30:14,440 --> 00:30:17,800 Speaker 1: we find out all right. Well, basically, the the overall 560 00:30:17,840 --> 00:30:20,240 Speaker 1: aim of the paper, according to them is quote in 561 00:30:20,280 --> 00:30:23,520 Speaker 1: the light of these premises, the main objective of the 562 00:30:23,520 --> 00:30:27,520 Speaker 1: present study was to examine at both configural that's based 563 00:30:27,520 --> 00:30:30,840 Speaker 1: on the whole face and featural that's based on details 564 00:30:30,840 --> 00:30:34,760 Speaker 1: of the face processing levels, whether despite their physical similarity, 565 00:30:34,800 --> 00:30:38,000 Speaker 1: twins would be better at recognizing their own face compared 566 00:30:38,080 --> 00:30:40,680 Speaker 1: to their co twin faces. So what they did is 567 00:30:40,760 --> 00:30:44,600 Speaker 1: they presented groups of twins with upright and inverted images 568 00:30:44,680 --> 00:30:47,320 Speaker 1: of their faces, those of a twin and a control 569 00:30:47,440 --> 00:30:50,719 Speaker 1: image of a non twin, so just some other person. 570 00:30:51,560 --> 00:30:56,840 Speaker 1: They used tin monosygonic right handed gender balanced healthy twin 571 00:30:56,960 --> 00:31:00,360 Speaker 1: couples that's the exact wording from the paper, and tin 572 00:31:00,560 --> 00:31:05,960 Speaker 1: right handed gender balanced healthy controls all white Caucasians in Rome, 573 00:31:06,120 --> 00:31:09,080 Speaker 1: where they where the study was held, and the control 574 00:31:09,160 --> 00:31:12,680 Speaker 1: participants the non twins. Using the study for balance, they 575 00:31:12,680 --> 00:31:16,480 Speaker 1: were matched with sex matched close friends or relatives, all 576 00:31:16,520 --> 00:31:18,560 Speaker 1: people they've known at least three years, so there'd be 577 00:31:18,640 --> 00:31:22,280 Speaker 1: a level of familiarity. This resulted in two days of tests. 578 00:31:22,360 --> 00:31:25,280 Speaker 1: First they did personality tests, then they did the facial tests, 579 00:31:25,640 --> 00:31:28,720 Speaker 1: and these were the results. Identical twins they said, seem 580 00:31:28,800 --> 00:31:32,920 Speaker 1: to lack the self identification advantage. However, the absence of 581 00:31:32,960 --> 00:31:36,840 Speaker 1: the self advantage depends on how much the twins report 582 00:31:36,920 --> 00:31:39,880 Speaker 1: that they physically resemble each other. Okay, so adult twins 583 00:31:40,320 --> 00:31:43,840 Speaker 1: can't pick themselves out of a lineup as easily as 584 00:31:43,880 --> 00:31:48,560 Speaker 1: most adults can, but this is mitigated by whether they 585 00:31:48,600 --> 00:31:52,160 Speaker 1: look all that much like their identical twin. Right, Yeah, 586 00:31:52,280 --> 00:31:54,200 Speaker 1: I want to drive home that it is. We're not 587 00:31:54,360 --> 00:31:57,040 Speaker 1: saying that twins can't tell each other apart in there, 588 00:31:57,560 --> 00:32:02,320 Speaker 1: but that there is not basically not as easily. It 589 00:32:02,360 --> 00:32:05,360 Speaker 1: also depends on their anxious and avoid an attachment style. 590 00:32:05,480 --> 00:32:08,520 Speaker 1: And they found out that quote self and co twin 591 00:32:08,600 --> 00:32:12,920 Speaker 1: faces share very similar featural, configural and matching processes, but 592 00:32:13,080 --> 00:32:16,560 Speaker 1: differ with respect to the higher order stages of face processing. 593 00:32:17,360 --> 00:32:22,080 Speaker 1: So this is a study. Honestly, there's so many studies 594 00:32:22,320 --> 00:32:24,680 Speaker 1: that the Igno Bell covers that I'm like, yeah, that's 595 00:32:24,720 --> 00:32:27,040 Speaker 1: of course that the nobles chose that one or their 596 00:32:27,080 --> 00:32:28,520 Speaker 1: studies that come out and you're like, oh, I can't 597 00:32:28,560 --> 00:32:30,479 Speaker 1: wait till they feature this one. They give this one, 598 00:32:30,480 --> 00:32:33,560 Speaker 1: they need noble prize. I I honestly didn't see what 599 00:32:33,600 --> 00:32:36,880 Speaker 1: was that funny about this one is Yeah, it seems 600 00:32:36,920 --> 00:32:40,120 Speaker 1: like right exactly. I guess maybe it's the idea of 601 00:32:40,200 --> 00:32:43,760 Speaker 1: looking at your own face upside down again, Like if 602 00:32:43,800 --> 00:32:46,440 Speaker 1: we had watched the ceremony this year, I imagine they 603 00:32:46,440 --> 00:32:48,760 Speaker 1: would have done some kind of visual gag or whatever 604 00:32:49,240 --> 00:32:52,200 Speaker 1: you know, related to this specifics. But it doesn't seem 605 00:32:52,240 --> 00:32:54,920 Speaker 1: to have an inherent gag quality to it. There's no 606 00:32:55,000 --> 00:32:58,400 Speaker 1: crocodile being held already using a gambling machine. There's a 607 00:32:58,440 --> 00:33:02,240 Speaker 1: liquid cats. Yeah, so it's I have trouble figuring out. 608 00:33:02,280 --> 00:33:04,920 Speaker 1: I mean, I'm glad they highlighted it. It's a case 609 00:33:04,920 --> 00:33:06,640 Speaker 1: where yeah, it's a cool study and I'm glad more 610 00:33:06,640 --> 00:33:10,200 Speaker 1: eyes are on it because it does it is important. Uh. 611 00:33:10,240 --> 00:33:12,160 Speaker 1: The take home here is again not that twins are 612 00:33:12,200 --> 00:33:15,680 Speaker 1: freaky or anything. Rather, we're looking at a slight tweaking 613 00:33:15,720 --> 00:33:19,200 Speaker 1: of the basic visual, safe self faced recognition, and it 614 00:33:19,240 --> 00:33:21,840 Speaker 1: illuminates what's going on in all of us now. The 615 00:33:21,840 --> 00:33:25,000 Speaker 1: researchers also argue that their findings match up with the 616 00:33:25,160 --> 00:33:29,000 Speaker 1: self referrent phenotype matching theory that we recognize our kin 617 00:33:29,240 --> 00:33:33,479 Speaker 1: by implicitly or explicitly comparing the similarity of other people's 618 00:33:33,480 --> 00:33:36,959 Speaker 1: appearance to our own. So that's another potential takeome from 619 00:33:37,000 --> 00:33:39,240 Speaker 1: the from the study. And again, I know we have 620 00:33:39,320 --> 00:33:42,640 Speaker 1: some identical twins out there, We have parents of identical twins, 621 00:33:42,680 --> 00:33:45,960 Speaker 1: family members and friends of identical twins. We would obviously 622 00:33:46,080 --> 00:33:48,760 Speaker 1: love to hear from all of you about this particular paper, 623 00:33:48,920 --> 00:33:51,200 Speaker 1: and we'd like to hear from evil twins as well. Yeah, 624 00:33:51,280 --> 00:33:53,720 Speaker 1: evil twins jump in. All right, let's take one more break, 625 00:33:53,760 --> 00:33:55,280 Speaker 1: and when we get back, I'm going to talk to 626 00:33:55,280 --> 00:34:02,200 Speaker 1: you guys about big years. Alright, we're back. This potato 627 00:34:02,320 --> 00:34:05,200 Speaker 1: has big ears. Oh that's interesting that you went there. 628 00:34:05,480 --> 00:34:09,080 Speaker 1: So there is actually a variety of slang around the 629 00:34:09,120 --> 00:34:15,440 Speaker 1: world for talking about big ears, whether it's potatoes. Yeah, 630 00:34:15,719 --> 00:34:19,480 Speaker 1: well no, but in the UK, Uh, they are sometimes 631 00:34:19,480 --> 00:34:22,279 Speaker 1: called bat ears. I had not heard that before, or 632 00:34:22,360 --> 00:34:24,760 Speaker 1: wing nut, which I thought wing nut was a completely 633 00:34:24,800 --> 00:34:27,520 Speaker 1: different thing. I assume that this is talking about big 634 00:34:27,520 --> 00:34:31,040 Speaker 1: ears on humans, not on other animals. Yeah, yeah, uh. 635 00:34:31,080 --> 00:34:34,920 Speaker 1: And Hindus seem to find big ears desirable because of 636 00:34:34,960 --> 00:34:39,440 Speaker 1: comparisons to the elephant god Ganesha. The French compare big 637 00:34:39,440 --> 00:34:43,799 Speaker 1: ears to cabbage, Hungarians compare them to donkey ears, and 638 00:34:43,840 --> 00:34:47,280 Speaker 1: the Polish compare them to pig ears. Now, this is interesting. 639 00:34:47,280 --> 00:34:52,600 Speaker 1: The Chinese believe that long ears predict prosperity and longevity. 640 00:34:52,840 --> 00:34:56,160 Speaker 1: And this is the most important to this paper that 641 00:34:56,200 --> 00:34:58,560 Speaker 1: I'm about to present to you and its purposes. I 642 00:34:58,560 --> 00:35:01,600 Speaker 1: also want to say, all of those like statements about 643 00:35:01,719 --> 00:35:03,799 Speaker 1: various societies around the world, I didn't look that up 644 00:35:03,840 --> 00:35:06,200 Speaker 1: that came out of this original paper here. This is 645 00:35:06,520 --> 00:35:09,920 Speaker 1: yet another Ignoble winner. It is the Anatomy Prize winner 646 00:35:10,440 --> 00:35:16,160 Speaker 1: for the article why do you old men have big ears? Oh? Man? 647 00:35:16,400 --> 00:35:19,800 Speaker 1: Because it's true? Right? It turns out it is true, 648 00:35:19,880 --> 00:35:22,560 Speaker 1: but it's this is why it's funny, right. The idea 649 00:35:22,560 --> 00:35:24,520 Speaker 1: is that it's one of these things that we all assume, 650 00:35:25,200 --> 00:35:27,480 Speaker 1: but it does turn out that there's there's some reality 651 00:35:27,520 --> 00:35:29,560 Speaker 1: to it. They've done lots of measurements, so let's get 652 00:35:29,600 --> 00:35:32,640 Speaker 1: into it. I'm trying to picture pig ears and I 653 00:35:32,680 --> 00:35:35,320 Speaker 1: can't what a pig ears look like. Oh, they're they're 654 00:35:35,440 --> 00:35:37,960 Speaker 1: big and flopped. Well, sometimes they're floppy, It depends on 655 00:35:38,000 --> 00:35:40,000 Speaker 1: the pig. Yeah. Oh, they're kind of like dog ear, 656 00:35:40,040 --> 00:35:45,680 Speaker 1: they're kind of like pit bull ears. Yeah yeah. Um. 657 00:35:45,760 --> 00:35:49,000 Speaker 1: So the idea for this paper actually came about this way. 658 00:35:49,480 --> 00:35:53,320 Speaker 1: Nineteen members of the Thames Faculty of the Royal College 659 00:35:53,320 --> 00:35:57,440 Speaker 1: of General Practitioners. We're just sitting around brainstorming and the 660 00:35:57,480 --> 00:35:59,759 Speaker 1: first question that came up to them was why do 661 00:35:59,800 --> 00:36:02,760 Speaker 1: we old men have big ears? And then they realized 662 00:36:02,760 --> 00:36:04,359 Speaker 1: they were like, well, wait a minute, actually, we need 663 00:36:04,400 --> 00:36:07,759 Speaker 1: to confirm that old men's ears are bigger and they 664 00:36:07,800 --> 00:36:10,560 Speaker 1: get bigger in the first place. So this study was 665 00:36:10,640 --> 00:36:14,440 Speaker 1: conducted by Dr James A. Heath Cut and he was 666 00:36:14,480 --> 00:36:17,440 Speaker 1: a general practitioner in Bromley at the time. This is 667 00:36:17,480 --> 00:36:21,480 Speaker 1: in the nineties. The paper was published in So they 668 00:36:21,520 --> 00:36:25,680 Speaker 1: asked routine patients who were coming in for surgery consultations 669 00:36:26,160 --> 00:36:29,319 Speaker 1: if it was okay if they measured their ears as 670 00:36:29,360 --> 00:36:32,120 Speaker 1: part of this research along with it. When the group 671 00:36:32,239 --> 00:36:35,640 Speaker 1: was thirty plus years old, from either sex and from 672 00:36:35,680 --> 00:36:40,080 Speaker 1: any racial group that came in. Interestingly, none refused. Everybody 673 00:36:40,120 --> 00:36:43,879 Speaker 1: was cool, measure my ears. This sounds fun and they 674 00:36:43,920 --> 00:36:47,359 Speaker 1: recorded this along with the patient's age, and at this 675 00:36:47,400 --> 00:36:50,000 Speaker 1: time they got two hundred and six people to participate in. 676 00:36:50,080 --> 00:36:54,520 Speaker 1: The study showed that as these participants got older, their 677 00:36:54,520 --> 00:36:59,160 Speaker 1: ears grew on an average of point to two millimeters 678 00:36:59,160 --> 00:37:03,920 Speaker 1: a year. What the study didn't explain is why ears 679 00:37:04,080 --> 00:37:07,640 Speaker 1: keep growing when the rest of the body stops. That 680 00:37:07,719 --> 00:37:10,160 Speaker 1: seems to be odd, right. The thing about this study 681 00:37:10,280 --> 00:37:12,880 Speaker 1: is it doesn't explain another thing. What if you're a 682 00:37:12,920 --> 00:37:17,160 Speaker 1: taller person and like Robert, Robert is taller than I am. 683 00:37:17,600 --> 00:37:21,640 Speaker 1: Robert's taller than Joe. So what if Robert has longer 684 00:37:21,680 --> 00:37:25,360 Speaker 1: ears simply because he's taller, and then as he gets older? 685 00:37:25,960 --> 00:37:28,640 Speaker 1: You know, so there's some discrepancies that they didn't really 686 00:37:28,640 --> 00:37:32,160 Speaker 1: fill in here with you long legs, big ears, yeah, 687 00:37:32,200 --> 00:37:34,000 Speaker 1: and well, and plus when you get older, you're gonna 688 00:37:34,000 --> 00:37:36,000 Speaker 1: be more stooped over, whereas the ears are not going 689 00:37:36,040 --> 00:37:37,719 Speaker 1: to get stooped over to go. So I could see 690 00:37:37,719 --> 00:37:40,800 Speaker 1: that being the illusion of like, oh, this this old person, 691 00:37:40,880 --> 00:37:43,640 Speaker 1: they're shrinking except for their ears, which there's there's no 692 00:37:43,760 --> 00:37:47,400 Speaker 1: limited sight. Yeah. Uh. And they also didn't answer, for instance, 693 00:37:47,440 --> 00:37:50,520 Speaker 1: like all of the elderly people that they checked their ears, 694 00:37:50,560 --> 00:37:52,520 Speaker 1: they were all English because they're all in this one 695 00:37:52,520 --> 00:37:56,840 Speaker 1: small spot, so they hadn't didn't really replicate it across 696 00:37:56,880 --> 00:38:00,600 Speaker 1: cultures or ethnicities. Right, So this study was actually replicated 697 00:38:00,640 --> 00:38:04,720 Speaker 1: in Japan in nine and they found the same thing. Yes, 698 00:38:04,840 --> 00:38:08,520 Speaker 1: ear length still correlates with age, even when it is 699 00:38:08,600 --> 00:38:13,640 Speaker 1: corrected for height. But still there's all these alternative interpretations 700 00:38:13,640 --> 00:38:17,200 Speaker 1: that remain. So for instance, are people who are young 701 00:38:17,400 --> 00:38:20,759 Speaker 1: now when they turn old, are they also going to 702 00:38:20,800 --> 00:38:24,160 Speaker 1: see their ears age in the same way. Is ear 703 00:38:24,320 --> 00:38:27,279 Speaker 1: length changing and getting bigger as you get older? Is 704 00:38:27,280 --> 00:38:31,320 Speaker 1: it environmental? And if it's environmental, what could be responsible 705 00:38:31,360 --> 00:38:34,600 Speaker 1: for big years. One of the questions was literally the 706 00:38:34,640 --> 00:38:37,279 Speaker 1: idea that the people who were older at the time 707 00:38:37,280 --> 00:38:39,160 Speaker 1: that they were doing this study, when they were younger, 708 00:38:39,200 --> 00:38:42,200 Speaker 1: it was more common for their parents to box or 709 00:38:42,320 --> 00:38:45,920 Speaker 1: scrub their children's ears, so they thought, well, maybe that 710 00:38:45,960 --> 00:38:48,640 Speaker 1: could have affected it. I mean, my guess on the 711 00:38:48,680 --> 00:38:52,520 Speaker 1: size would just be flesh drooping effects, yeah, or something 712 00:38:52,600 --> 00:38:55,359 Speaker 1: that related to the way the ear grows, like the 713 00:38:55,400 --> 00:38:58,480 Speaker 1: inner um, the inner portions of the ear kind of 714 00:38:58,480 --> 00:39:01,439 Speaker 1: growing out the ear like a tree, like every year 715 00:39:01,480 --> 00:39:03,520 Speaker 1: he gets a new ring. Yeah. I mean, maybe that's 716 00:39:03,520 --> 00:39:08,240 Speaker 1: how aliens will categorize human captives that they alright, measure 717 00:39:08,280 --> 00:39:10,239 Speaker 1: the ears, see how old this one is. But heath 718 00:39:10,280 --> 00:39:12,720 Speaker 1: Cut didn't really account for any of that in his study, 719 00:39:12,800 --> 00:39:16,960 Speaker 1: So I turned to another UH analysis of this. Because 720 00:39:16,960 --> 00:39:19,759 Speaker 1: the study is over twenty years old, I looked at 721 00:39:19,840 --> 00:39:26,200 Speaker 1: Alice Sheryl Caswell's research on this for Improbable Research, so 722 00:39:26,400 --> 00:39:29,239 Speaker 1: the organization that puts out the ignobles. So this is 723 00:39:29,280 --> 00:39:33,160 Speaker 1: where it came about from. So Alice addresses in her paper. 724 00:39:33,239 --> 00:39:37,320 Speaker 1: First of all, the original study is very patriarchal because 725 00:39:37,320 --> 00:39:41,520 Speaker 1: it focuses on men. Now that's only in the title. 726 00:39:41,640 --> 00:39:45,440 Speaker 1: She acknowledges that the Japanese and subsequent German studies confirmed 727 00:39:45,440 --> 00:39:47,840 Speaker 1: that old women have big ears too. But I do 728 00:39:47,880 --> 00:39:50,480 Speaker 1: want to point out that is just poor phrasing of 729 00:39:50,520 --> 00:39:53,879 Speaker 1: the British study. It was clear that they didn't discriminate 730 00:39:53,920 --> 00:39:56,239 Speaker 1: on participants based on gender. I think they were just 731 00:39:56,360 --> 00:40:02,439 Speaker 1: using the old men term jokingly because talking about yeah, 732 00:40:03,120 --> 00:40:06,160 Speaker 1: they had based the entire study on this joke on 733 00:40:06,360 --> 00:40:10,160 Speaker 1: his hook, Yeah exactly. Now, the German study was conducted 734 00:40:10,160 --> 00:40:13,760 Speaker 1: in two thousand and seven, and they used photos instead 735 00:40:13,800 --> 00:40:16,880 Speaker 1: of measuring like real ears. I imagine they must have 736 00:40:16,880 --> 00:40:20,239 Speaker 1: been to scale these photos. They they used photos of 737 00:40:20,480 --> 00:40:23,799 Speaker 1: one thousand, four hundred and forty eight years and they 738 00:40:23,840 --> 00:40:28,399 Speaker 1: measured them in fifteen different ways, and they found that 739 00:40:28,600 --> 00:40:32,680 Speaker 1: female ears show a lesser increase than those of men. 740 00:40:32,840 --> 00:40:35,719 Speaker 1: So so far, across these three studies we've learned that yes, 741 00:40:35,760 --> 00:40:40,120 Speaker 1: people's ears grow as they get older. Yes, women's ears 742 00:40:40,160 --> 00:40:43,640 Speaker 1: also grow along with men's ears, but that it seems like, 743 00:40:43,680 --> 00:40:46,400 Speaker 1: at least in the German study, that female ears have 744 00:40:46,680 --> 00:40:50,640 Speaker 1: lesser increase. So that is really the gist of all 745 00:40:50,680 --> 00:40:53,840 Speaker 1: of these studies. I think they're awarding an older study, 746 00:40:54,000 --> 00:40:56,680 Speaker 1: you know, because Alice came along and was like, hey, 747 00:40:56,680 --> 00:40:59,359 Speaker 1: wait a minute, this deserves a second look. Now, why 748 00:40:59,440 --> 00:41:01,400 Speaker 1: is it funny? Well, because of the whole hook of 749 00:41:01,400 --> 00:41:04,279 Speaker 1: the whole old men have big ears thing, we all 750 00:41:04,320 --> 00:41:07,000 Speaker 1: just assume that to be true. Nobody ever thought you'd 751 00:41:07,040 --> 00:41:09,800 Speaker 1: sit down and actually measure people's ears with a ruler 752 00:41:09,920 --> 00:41:11,920 Speaker 1: or like a what do you call it, like a 753 00:41:11,920 --> 00:41:14,520 Speaker 1: tape measure or something like that. Right, but it does 754 00:41:14,560 --> 00:41:17,839 Speaker 1: seem to be actually important and the reason why there's 755 00:41:17,840 --> 00:41:20,960 Speaker 1: still questions to be answered. We still don't know why 756 00:41:21,239 --> 00:41:24,759 Speaker 1: ears keep going when the rest of the body stops, right, 757 00:41:25,200 --> 00:41:28,360 Speaker 1: and then the gender difference in the rate of growth 758 00:41:28,400 --> 00:41:31,279 Speaker 1: seems like that's it's something important as well, especially in 759 00:41:31,360 --> 00:41:35,600 Speaker 1: terms of just understanding human biology and anatomy. Well, you 760 00:41:35,600 --> 00:41:38,960 Speaker 1: know it also you have to wonder too about ear 761 00:41:39,040 --> 00:41:41,680 Speaker 1: rings and piercings and various you know, which is gonna 762 00:41:41,680 --> 00:41:45,239 Speaker 1: It's gonna vary from culture to culture. But in many 763 00:41:45,280 --> 00:41:49,879 Speaker 1: cases you're going to have more females than males using 764 00:41:49,920 --> 00:41:53,359 Speaker 1: the piercings. And is that going to increase length of 765 00:41:53,360 --> 00:41:55,840 Speaker 1: of low? And I think of about like my friends 766 00:41:56,000 --> 00:41:58,480 Speaker 1: in the punk scene who got like lots of ear 767 00:41:58,560 --> 00:42:01,000 Speaker 1: rings and got like big gage is placed in their 768 00:42:01,040 --> 00:42:04,120 Speaker 1: lobes and how their ears look. Now that could be 769 00:42:04,160 --> 00:42:06,000 Speaker 1: an effect as well. So there you go with some 770 00:42:06,080 --> 00:42:09,960 Speaker 1: environmental possibilities. I don't know about boxing or scrubbing though. Yeah, 771 00:42:10,120 --> 00:42:15,600 Speaker 1: so we're potentially looking though at sort of accidental body 772 00:42:15,640 --> 00:42:19,000 Speaker 1: modification of the human ear, sort of like cultural long 773 00:42:19,120 --> 00:42:23,279 Speaker 1: term modification. Or we're looking at at some sort of 774 00:42:24,280 --> 00:42:29,480 Speaker 1: gender dimorphism of of Homo sapiens where men end up 775 00:42:29,520 --> 00:42:33,080 Speaker 1: having longer ears over time. Yeah, I'm inclined to agree 776 00:42:33,120 --> 00:42:35,440 Speaker 1: with Joe. I mean, I haven't done the research, but 777 00:42:35,520 --> 00:42:37,640 Speaker 1: I would assume that it's similar to like why you 778 00:42:37,680 --> 00:42:40,760 Speaker 1: get bags under your eyes, right, Like over time, the 779 00:42:40,880 --> 00:42:45,839 Speaker 1: um facia underneath your skin just loosens and the you 780 00:42:45,840 --> 00:42:48,399 Speaker 1: know it droops basically, And so I think the ears 781 00:42:48,400 --> 00:42:50,960 Speaker 1: are probably the same, like the cartilage around the ears 782 00:42:51,560 --> 00:42:55,239 Speaker 1: stay I would imagine stays the same, but the other 783 00:42:55,360 --> 00:42:58,680 Speaker 1: stuff starts drooping down. Yeah, all right, so there you 784 00:42:58,760 --> 00:43:03,000 Speaker 1: have it. We've covered this episode the use of saltwater 785 00:43:03,040 --> 00:43:08,760 Speaker 1: crocodiles on problem gamblers. We've looked at facial recognition and twins, 786 00:43:09,080 --> 00:43:12,719 Speaker 1: and then the size of old man ears. So if 787 00:43:12,800 --> 00:43:15,799 Speaker 1: you have any anecdotes or maybe some of your own 788 00:43:15,840 --> 00:43:18,040 Speaker 1: research to share with us on these topics, you can 789 00:43:18,080 --> 00:43:21,040 Speaker 1: find us on Facebook. We're on Twitter, we're on tumbler, 790 00:43:21,320 --> 00:43:25,080 Speaker 1: and we're on Instagram. We've also got our fantastic Facebook 791 00:43:25,080 --> 00:43:28,120 Speaker 1: discussion group. Yeah, the discussion module. You can find it 792 00:43:28,160 --> 00:43:31,440 Speaker 1: on our Facebook page. That's where fans of the show 793 00:43:31,560 --> 00:43:35,400 Speaker 1: hang out, interact, talk about recent episodes, or sometimes share 794 00:43:35,719 --> 00:43:37,799 Speaker 1: potential topics with us. Yeah, and if you want to 795 00:43:37,800 --> 00:43:40,000 Speaker 1: get in touch with us directly, you want to answer 796 00:43:40,040 --> 00:43:42,920 Speaker 1: the question do your ears hang low? Do they wobble 797 00:43:42,960 --> 00:43:45,160 Speaker 1: to and fro? We want to know about that and 798 00:43:45,200 --> 00:43:48,360 Speaker 1: how it relates to this earloab study that Christian has 799 00:43:48,360 --> 00:43:50,719 Speaker 1: been discussing. You can email us at below the Mind 800 00:43:50,800 --> 00:44:02,600 Speaker 1: at how stuff works dot com for more on this 801 00:44:02,760 --> 00:44:05,279 Speaker 1: and thousands of other topics. Does it how stuff works 802 00:44:05,280 --> 00:44:28,520 Speaker 1: dot com