1 00:00:03,080 --> 00:00:05,920 Speaker 1: Welcome to Stuff to Blow Your Mind from how Stuff 2 00:00:05,920 --> 00:00:15,360 Speaker 1: Works dot com. Hey, welcome to Stuff to Blow your Mind. 3 00:00:15,480 --> 00:00:18,040 Speaker 1: My name is Robert lamp and I'm Joe McCormick. And 4 00:00:18,079 --> 00:00:22,239 Speaker 1: today we're gonna be looking at understanding a little bit 5 00:00:22,320 --> 00:00:26,800 Speaker 1: of the gaps in our knowledge and our metacognition. And 6 00:00:26,960 --> 00:00:28,960 Speaker 1: it's going to be the first part of a two 7 00:00:29,000 --> 00:00:33,520 Speaker 1: part episode on the illusion of explanatory depth. So if 8 00:00:33,520 --> 00:00:36,000 Speaker 1: you like this one, you should also definitely come back 9 00:00:36,000 --> 00:00:38,400 Speaker 1: for the next episode we released next time, which will 10 00:00:38,440 --> 00:00:40,120 Speaker 1: be a follow up to what we're going to talk 11 00:00:40,159 --> 00:00:44,199 Speaker 1: about today, illusion of explanatory depth. So to put that 12 00:00:44,240 --> 00:00:48,640 Speaker 1: in simpler terms, we're talking about a situation where you 13 00:00:48,680 --> 00:00:52,279 Speaker 1: think you know how something works, you think you have 14 00:00:52,479 --> 00:00:56,360 Speaker 1: a working knowledge of the thing, but in reality you don't. Yeah, 15 00:00:56,400 --> 00:00:59,720 Speaker 1: and we've talked about the gaps between the feeling of 16 00:00:59,760 --> 00:01:02,840 Speaker 1: no wing and the actual knowing before this came up 17 00:01:02,840 --> 00:01:04,480 Speaker 1: in the episode we did about the tip of the 18 00:01:04,520 --> 00:01:07,600 Speaker 1: tongue state. You remember that the sense that you know 19 00:01:07,880 --> 00:01:12,080 Speaker 1: something is not necessarily coterminous with actually being able to 20 00:01:12,160 --> 00:01:15,399 Speaker 1: produce that piece of knowledge from memory. There's a gap 21 00:01:15,440 --> 00:01:18,240 Speaker 1: in your mind. So you think you know the name 22 00:01:18,560 --> 00:01:21,680 Speaker 1: of the actor who played Thaiwan Lanister on Game of Thrones. 23 00:01:21,760 --> 00:01:23,920 Speaker 1: Do you Robert Oh, no, I can't. He has that 24 00:01:23,959 --> 00:01:26,839 Speaker 1: weird name that I can never know, Thaiwan. Yeah, wait, 25 00:01:26,880 --> 00:01:28,680 Speaker 1: which one is Taiwan? No, I'm thinking of Jamie. I 26 00:01:28,720 --> 00:01:31,080 Speaker 1: can never remember Jamie's name. What about Thaiwan? Come on, 27 00:01:31,120 --> 00:01:34,400 Speaker 1: he's an alien? Three? Okay, Well you got it. You 28 00:01:34,440 --> 00:01:36,400 Speaker 1: didn't You didn't have that gap. Then some people might 29 00:01:36,480 --> 00:01:38,479 Speaker 1: there was a gap in there somewhere. I did feel 30 00:01:38,520 --> 00:01:41,440 Speaker 1: a gap. If if you're familiar with Game of Thrones 31 00:01:41,480 --> 00:01:43,880 Speaker 1: out there you were, like some of you were probably thinking, oh, 32 00:01:44,000 --> 00:01:46,319 Speaker 1: I know that name, what is it? What is it? 33 00:01:46,319 --> 00:01:50,440 Speaker 1: It was Charles Dance. Okay. The other possible um gap 34 00:01:50,480 --> 00:01:52,600 Speaker 1: there is you hear Taiwan? And then you were is 35 00:01:52,640 --> 00:01:56,040 Speaker 1: a Tyrian? Is it Thaiwan? More names? Well? I picked 36 00:01:57,160 --> 00:02:00,120 Speaker 1: Character actors often fall into this category. The character know 37 00:02:00,160 --> 00:02:02,640 Speaker 1: the actors you've seen in tons of movies throughout the years. 38 00:02:02,680 --> 00:02:05,480 Speaker 1: They become that tip of the tongue name where you 39 00:02:05,520 --> 00:02:07,760 Speaker 1: know the face. You know some movies they've been in. 40 00:02:07,840 --> 00:02:09,880 Speaker 1: You know you know the name, but you don't know 41 00:02:09,960 --> 00:02:12,280 Speaker 1: the name. At the moment. It's this that guy, Oh, 42 00:02:12,320 --> 00:02:14,640 Speaker 1: what's that guy's name? Yeah, And so there's this gap, 43 00:02:14,720 --> 00:02:17,680 Speaker 1: there's this feeling of knowing, and there's the gap between 44 00:02:17,720 --> 00:02:21,200 Speaker 1: the feeling of knowing and the actual knowing itself. But 45 00:02:21,320 --> 00:02:23,920 Speaker 1: the interesting thing is that this gap can be applied 46 00:02:24,200 --> 00:02:26,960 Speaker 1: to other realms of knowledge. It's not just in trying 47 00:02:26,960 --> 00:02:29,840 Speaker 1: to come up with the name for a thing, for example, 48 00:02:29,919 --> 00:02:33,000 Speaker 1: in a quint essentially how stuff works move I think 49 00:02:33,080 --> 00:02:35,640 Speaker 1: we should look at the domain of knowledge that covers 50 00:02:36,040 --> 00:02:42,200 Speaker 1: understanding how things happen, or really in really understanding how 51 00:02:42,280 --> 00:02:46,600 Speaker 1: things work in causal relationships, because of course we live 52 00:02:46,600 --> 00:02:50,320 Speaker 1: in a world of systems. The system is always trying 53 00:02:50,360 --> 00:02:54,040 Speaker 1: to get you down. But but there are causal systems 54 00:02:54,040 --> 00:02:57,920 Speaker 1: all around us, machines, the coffee maker in the office, 55 00:02:57,960 --> 00:03:01,800 Speaker 1: the computer you're working on, and ammals, animals or systems 56 00:03:01,800 --> 00:03:05,520 Speaker 1: of causal relationships. There are natural cycles, like you know, 57 00:03:05,600 --> 00:03:09,440 Speaker 1: the nitrogen cycle or the water cycle. Those are causal systems. 58 00:03:09,480 --> 00:03:15,520 Speaker 1: And then other natural phenomenon uh, tides, rainbows, I don't know, 59 00:03:16,120 --> 00:03:19,760 Speaker 1: pooping a all natural phenomenon. Well, these are all things 60 00:03:19,840 --> 00:03:21,560 Speaker 1: that I mean too. We have to mention, of course, 61 00:03:21,560 --> 00:03:24,680 Speaker 1: the famous quote other C. Clark, right, that any sufficiently 62 00:03:24,680 --> 00:03:27,880 Speaker 1: advanced technology is indistinguishable from magic. But you could pretty 63 00:03:27,960 --> 00:03:31,200 Speaker 1: much say that about like any system, Uh that if 64 00:03:31,240 --> 00:03:33,799 Speaker 1: if you if it's if it's it's it's if it's 65 00:03:33,800 --> 00:03:37,920 Speaker 1: advanced enough and complex enough, and and most systems are U. 66 00:03:39,520 --> 00:03:41,760 Speaker 1: It can it can seem magical in the fact that 67 00:03:41,800 --> 00:03:45,400 Speaker 1: the sun rises in the morning. Um, there's a magic 68 00:03:45,440 --> 00:03:47,680 Speaker 1: to that. We we've we've we've observed it his magic 69 00:03:47,720 --> 00:03:50,080 Speaker 1: and felt it is magic since the time. Out of 70 00:03:50,080 --> 00:03:53,120 Speaker 1: mind we sometimes are even though we have the the 71 00:03:53,160 --> 00:03:57,280 Speaker 1: actual scientific explanation for what's happening, you still also have 72 00:03:57,520 --> 00:04:02,680 Speaker 1: this magical version of the event, uh pared right beside 73 00:04:02,720 --> 00:04:04,920 Speaker 1: it on on the shelf in your mind. Oh totally. 74 00:04:05,000 --> 00:04:08,120 Speaker 1: I mean, we have strong intuitions to give to give 75 00:04:08,280 --> 00:04:12,880 Speaker 1: magical or kind of fuzzy causal relationships. And and it's 76 00:04:12,880 --> 00:04:16,520 Speaker 1: funny because one way of interpreting the idea of magic 77 00:04:16,640 --> 00:04:21,160 Speaker 1: or the supernatural is it's just causal anddeterminacy, right, Like, 78 00:04:21,240 --> 00:04:23,560 Speaker 1: what do you mean when you say something happened by 79 00:04:23,600 --> 00:04:27,040 Speaker 1: magic or something happened with the supernatural cause, it just 80 00:04:27,160 --> 00:04:30,599 Speaker 1: means that the cause. Essentially you're saying, well, the cause 81 00:04:30,680 --> 00:04:34,440 Speaker 1: isn't clear. It's just kind of like getting vague about 82 00:04:34,520 --> 00:04:36,800 Speaker 1: what it means to be a cause I like this. 83 00:04:36,880 --> 00:04:40,800 Speaker 1: You know, my my son who's almost five. He we 84 00:04:41,080 --> 00:04:45,119 Speaker 1: try to explain how things work to him, as one should, 85 00:04:45,800 --> 00:04:48,120 Speaker 1: but he also has this concept of magic. It's very 86 00:04:48,160 --> 00:04:50,440 Speaker 1: loose concept. So the other day he had a new 87 00:04:50,800 --> 00:04:53,200 Speaker 1: helium balloon and it was one of those uh those 88 00:04:53,240 --> 00:04:57,240 Speaker 1: fancy shiny ones that that you get. What's the material? 89 00:04:58,120 --> 00:05:00,479 Speaker 1: My large, my large? So it was a mile balloons, 90 00:05:00,480 --> 00:05:02,599 Speaker 1: so it last, it was lasting longer. He's used to 91 00:05:02,600 --> 00:05:04,920 Speaker 1: getting these cheap balloons and they the helium goes down 92 00:05:04,920 --> 00:05:07,120 Speaker 1: and they're on the floor, but this one was floating 93 00:05:07,120 --> 00:05:09,320 Speaker 1: the next day and he said, hey, that my balloon 94 00:05:09,360 --> 00:05:13,160 Speaker 1: is still floating. Is this is it magic helium? Um? 95 00:05:13,200 --> 00:05:15,920 Speaker 1: Which I think was maybe like his definition of magic 96 00:05:15,960 --> 00:05:17,600 Speaker 1: is more in line with what you just said. There's 97 00:05:17,640 --> 00:05:20,400 Speaker 1: a there's a mystery there. Uh like he knows that 98 00:05:20,480 --> 00:05:24,440 Speaker 1: this helium is not behaving like like like normal helium. 99 00:05:24,480 --> 00:05:27,160 Speaker 1: That's that he's encountered and he has no other explanation 100 00:05:27,240 --> 00:05:29,719 Speaker 1: for it. Yeah. But yeah, so you don't have to 101 00:05:29,760 --> 00:05:32,600 Speaker 1: at that point explain how the magic does what it does. 102 00:05:32,680 --> 00:05:34,919 Speaker 1: If you did, it would sort of stop being magic. 103 00:05:36,120 --> 00:05:39,200 Speaker 1: But Yeah. So so there are these systems all around us. 104 00:05:39,240 --> 00:05:41,919 Speaker 1: We we sort of naturally feel like they're magic, but 105 00:05:41,960 --> 00:05:45,640 Speaker 1: we can come to understand the causal processes that that 106 00:05:46,000 --> 00:05:48,800 Speaker 1: that sustained them and that make them work. But as 107 00:05:48,800 --> 00:05:51,800 Speaker 1: we've said, understanding and the feeling of understanding are actually 108 00:05:51,839 --> 00:05:55,479 Speaker 1: separate things. And whenever you've got two different binary variables 109 00:05:55,480 --> 00:05:57,279 Speaker 1: like this, I think it's interesting to try to make 110 00:05:57,320 --> 00:05:59,520 Speaker 1: that the grid table, you know, where you've got one 111 00:05:59,600 --> 00:06:02,800 Speaker 1: binary area on a column and one binary on a row. 112 00:06:02,960 --> 00:06:06,080 Speaker 1: So you can think of things that we understand and 113 00:06:06,120 --> 00:06:08,200 Speaker 1: that we don't understand, and then you can think of 114 00:06:08,279 --> 00:06:10,960 Speaker 1: things that you feel like you understand or that you 115 00:06:11,040 --> 00:06:13,400 Speaker 1: don't feel like you understand. So there are things that 116 00:06:13,440 --> 00:06:16,040 Speaker 1: we understand and we feel like that we understand them 117 00:06:16,040 --> 00:06:19,000 Speaker 1: like a hammer. Yes, you think you get it, you 118 00:06:19,120 --> 00:06:22,360 Speaker 1: really do get it. Yeah, there's there's some very simple 119 00:06:22,360 --> 00:06:25,600 Speaker 1: physics involved here. There's a there's a there's a definite 120 00:06:25,920 --> 00:06:30,440 Speaker 1: causal um process going on. Yeah. Then there's maybe how 121 00:06:30,520 --> 00:06:34,920 Speaker 1: microprocessor engineering works. That's one where you probably don't understand 122 00:06:34,920 --> 00:06:37,720 Speaker 1: it and you probably feel like you don't understand it. Right. 123 00:06:37,800 --> 00:06:39,839 Speaker 1: This is one of those where you have a problem 124 00:06:39,839 --> 00:06:41,960 Speaker 1: with your computer and you just you tell your tech 125 00:06:42,800 --> 00:06:45,880 Speaker 1: tech guy or gal, you say, it's all magic to me. 126 00:06:46,440 --> 00:06:48,200 Speaker 1: I don't know how this works. Can you help me 127 00:06:48,279 --> 00:06:50,600 Speaker 1: fix this problem? Right? So, those are the ones where 128 00:06:50,640 --> 00:06:53,360 Speaker 1: are understanding and our feelings are basically in agreement. But 129 00:06:53,400 --> 00:06:55,720 Speaker 1: what about the other two boxes? What about things that 130 00:06:55,760 --> 00:07:00,279 Speaker 1: you understand but you don't feel like you understand can 131 00:07:00,279 --> 00:07:03,560 Speaker 1: actually happen sometimes, and I think it's often the starting 132 00:07:03,600 --> 00:07:06,839 Speaker 1: place of a Socratic dialogue or if you ever you know, 133 00:07:06,880 --> 00:07:10,440 Speaker 1: the Socratic teaching method is where instead of telling students 134 00:07:10,440 --> 00:07:13,320 Speaker 1: what to believe, you ask them questions and sort of 135 00:07:13,400 --> 00:07:17,160 Speaker 1: lead them to understand that they already knew the answer, 136 00:07:17,400 --> 00:07:20,360 Speaker 1: but they just didn't know how to articulate it. And 137 00:07:20,400 --> 00:07:23,560 Speaker 1: so in that case, the child already understands, they just 138 00:07:23,600 --> 00:07:26,440 Speaker 1: didn't know how to put the answer with the question 139 00:07:26,520 --> 00:07:30,040 Speaker 1: in context. But then there's the other box, the things 140 00:07:30,080 --> 00:07:34,160 Speaker 1: you feel like you understand but you don't actually understand. 141 00:07:34,680 --> 00:07:36,600 Speaker 1: And the research we're going to talk about today is 142 00:07:36,680 --> 00:07:40,600 Speaker 1: addressing how there is tons of stuff in this box. 143 00:07:41,040 --> 00:07:45,000 Speaker 1: This box box is filled to the brim. Uh toilets 144 00:07:45,000 --> 00:07:47,400 Speaker 1: are probably in this box for you? What do you? 145 00:07:47,440 --> 00:07:49,160 Speaker 1: What do you think? Unless you're a plumber, or you've 146 00:07:49,200 --> 00:07:51,600 Speaker 1: really done some work on your toilet. I bet toilets 147 00:07:51,680 --> 00:07:55,760 Speaker 1: or in this box. Yeah, I mean they're they're fairly complicated, 148 00:07:55,880 --> 00:07:58,560 Speaker 1: a little little mechanisms, despite the fact that they maybe 149 00:07:58,560 --> 00:08:02,360 Speaker 1: haven't buying large advanced as much as they should, because 150 00:08:02,360 --> 00:08:04,400 Speaker 1: it's kind of one of those technologies that we tend 151 00:08:04,400 --> 00:08:06,000 Speaker 1: to think, all right, it's good enough, and we don't 152 00:08:06,000 --> 00:08:08,119 Speaker 1: want to we don't want to put too much extra 153 00:08:08,200 --> 00:08:12,200 Speaker 1: thought into into its design and function. Yeah, here's another one. 154 00:08:12,240 --> 00:08:14,960 Speaker 1: How How what about mirrors? Mirrors is a great one, 155 00:08:15,520 --> 00:08:17,360 Speaker 1: and I love this example. I think I've brought it 156 00:08:17,440 --> 00:08:20,080 Speaker 1: up before, but yeah, I think it's a perfect example 157 00:08:20,080 --> 00:08:22,840 Speaker 1: of an everyday object that we take mostly for granted, 158 00:08:23,240 --> 00:08:26,880 Speaker 1: but it is ultimately this insane, freaky mystery in our lives. 159 00:08:27,680 --> 00:08:29,240 Speaker 1: I mean, really, it's amazing that we don't just run 160 00:08:29,240 --> 00:08:34,200 Speaker 1: around constantly smashing them like maniacs. I think you, like me, 161 00:08:34,679 --> 00:08:38,520 Speaker 1: love a good creepy mirror story, like a haunted mirror. 162 00:08:39,280 --> 00:08:42,280 Speaker 1: What's the Stephen King won the Representage? The Representage fabrical 163 00:08:42,360 --> 00:08:45,599 Speaker 1: short stories one of his best, in my opinion. Uh, 164 00:08:45,000 --> 00:08:48,200 Speaker 1: and there are tons of them, Lovecraft wrote one Clark 165 00:08:48,240 --> 00:08:51,760 Speaker 1: Ashton Smith wrote one, you could probably fill an entire 166 00:08:51,800 --> 00:08:53,920 Speaker 1: book with just creepy mirror stories, and then I would 167 00:08:53,960 --> 00:08:56,079 Speaker 1: buy said book. But wait a minute. Of course, we 168 00:08:56,160 --> 00:08:59,720 Speaker 1: understand how a mirror works. That's easy. It's just uh, well, 169 00:08:59,800 --> 00:09:04,440 Speaker 1: like the light goes in and then it comes back. Right. Well, yeah, 170 00:09:04,679 --> 00:09:07,560 Speaker 1: we think we we have we have it under wraps, right, 171 00:09:08,160 --> 00:09:09,959 Speaker 1: because we encounter them all the time and we have 172 00:09:10,080 --> 00:09:15,040 Speaker 1: this sort of ubiquitous environmental knowledge of them. But when 173 00:09:15,040 --> 00:09:17,480 Speaker 1: we're put to the test the office seems to be 174 00:09:17,679 --> 00:09:21,120 Speaker 1: uh the case. We we don't really understand how they work. 175 00:09:21,160 --> 00:09:23,400 Speaker 1: And and I think this is why we have all 176 00:09:23,400 --> 00:09:27,000 Speaker 1: these fictional tales about weird creepy mirrors, because we need 177 00:09:27,040 --> 00:09:31,240 Speaker 1: that that cultural release valve, that psychic release valve for 178 00:09:31,280 --> 00:09:34,880 Speaker 1: our uneasiness about them. But in terms of just proving 179 00:09:34,880 --> 00:09:38,120 Speaker 1: this out, there was a two thousand five psychological study 180 00:09:38,120 --> 00:09:40,400 Speaker 1: from the University of Liverpool and they looked into this 181 00:09:40,440 --> 00:09:43,760 Speaker 1: and they asked participants in the study to consider a 182 00:09:44,080 --> 00:09:47,079 Speaker 1: draped mirror, so it's, you know, like a haunted mirror 183 00:09:47,080 --> 00:09:49,000 Speaker 1: that's been covered up to keep monsters from coming out 184 00:09:49,000 --> 00:09:51,480 Speaker 1: of it, and they had to predict at which points 185 00:09:51,559 --> 00:09:53,880 Speaker 1: in the room. They would be able to see themselves 186 00:09:54,480 --> 00:09:57,400 Speaker 1: if the mirror in the mirror, if the mirror was uncovered. Okay, 187 00:09:57,440 --> 00:10:00,120 Speaker 1: so if you really had a solid understanding of what 188 00:10:00,160 --> 00:10:02,640 Speaker 1: a mirror, how a mirror works, you should be able 189 00:10:02,640 --> 00:10:05,520 Speaker 1: to predict how you can use it. And they weren't 190 00:10:05,520 --> 00:10:08,160 Speaker 1: able to to do that. They weren't. They weren't able 191 00:10:08,160 --> 00:10:10,000 Speaker 1: to Another thing they couldn't do is they weren't able 192 00:10:10,040 --> 00:10:12,760 Speaker 1: to grasp the fact that your reflection in the mirror 193 00:10:12,840 --> 00:10:16,559 Speaker 1: is always half your size, because the mirror is always 194 00:10:16,600 --> 00:10:20,000 Speaker 1: halfway between the viewer and the viewers reflection. So they'd 195 00:10:20,000 --> 00:10:22,240 Speaker 1: be asked to say, well, they'd be asked how big 196 00:10:22,320 --> 00:10:25,000 Speaker 1: is your your head in that reflection, and they would 197 00:10:25,120 --> 00:10:27,120 Speaker 1: assume that it was the same size as their own head. 198 00:10:27,920 --> 00:10:30,120 Speaker 1: So I would have assumed, yeah, I mean I wouldn't. 199 00:10:30,120 --> 00:10:32,360 Speaker 1: I really had to read the that sentence a couple 200 00:10:32,400 --> 00:10:35,520 Speaker 1: of times. Towie, oh, yeah, there is the mirror is 201 00:10:35,559 --> 00:10:40,480 Speaker 1: halfway between me and the spectral doppelganger with that that 202 00:10:40,559 --> 00:10:45,120 Speaker 1: has his his hair parted on the opposite side. Um 203 00:10:45,240 --> 00:10:47,680 Speaker 1: the But the study basically revealed that we we tend 204 00:10:47,720 --> 00:10:51,680 Speaker 1: to assume the size of the reflection. We tend to 205 00:10:51,800 --> 00:10:54,800 Speaker 1: assume that we know exactly how the angles work for 206 00:10:54,840 --> 00:10:59,440 Speaker 1: the reflection. Uh, we're terrible determining what will be seen 207 00:10:59,480 --> 00:11:02,000 Speaker 1: in a mirror based on the observer's vantage point. And 208 00:11:02,440 --> 00:11:04,719 Speaker 1: a major example of this is the Venus effect that 209 00:11:04,760 --> 00:11:07,840 Speaker 1: we see in so many paintings. Venus. Okay, so you 210 00:11:07,840 --> 00:11:10,880 Speaker 1: have Venus in the painting. Venus is looking at her 211 00:11:10,880 --> 00:11:14,040 Speaker 1: face in a mirror, and we're looking at the painting 212 00:11:14,240 --> 00:11:17,640 Speaker 1: and we see Venus's face. But if she's looking at 213 00:11:17,640 --> 00:11:20,360 Speaker 1: her face in the mirror, how does that work. It's 214 00:11:20,400 --> 00:11:22,200 Speaker 1: It's like, next time you're watching a TV show or 215 00:11:22,200 --> 00:11:25,240 Speaker 1: a movie and there's a scene with a mirror over analysis, 216 00:11:25,679 --> 00:11:28,600 Speaker 1: really think about where's the camera, where's the camera? What 217 00:11:28,640 --> 00:11:31,839 Speaker 1: are they looking at it? It really begins to open 218 00:11:31,920 --> 00:11:34,320 Speaker 1: up your eyes to the fact that it said, Wow, 219 00:11:34,360 --> 00:11:38,240 Speaker 1: I I was completely hoodwinked by this, and maybe I 220 00:11:38,280 --> 00:11:42,080 Speaker 1: don't have the firmest idea of the optical scenario going 221 00:11:42,120 --> 00:11:45,560 Speaker 1: on here. Uh. Slightly related, Also, anytime you're watching a 222 00:11:45,600 --> 00:11:48,040 Speaker 1: movie where there's a mirror on the lid of a 223 00:11:48,120 --> 00:11:51,480 Speaker 1: medicine cabinet and the person opens the medicine cabinet and 224 00:11:51,520 --> 00:11:54,640 Speaker 1: then shuts it be prepared to see another face in 225 00:11:54,679 --> 00:11:57,120 Speaker 1: the mirror behind the person when they shut the lid. 226 00:11:57,520 --> 00:12:00,319 Speaker 1: It happens every time. You know. One more, just very 227 00:12:00,400 --> 00:12:03,520 Speaker 1: quick optical example is just site itself. I think we've 228 00:12:03,520 --> 00:12:06,520 Speaker 1: touched on this that the idea that site is something 229 00:12:06,559 --> 00:12:10,440 Speaker 1: that leaves our eyes. Oh yeah, it's like laser vision. Uh. 230 00:12:10,480 --> 00:12:12,480 Speaker 1: This is one of those things like I talked about earlier, 231 00:12:12,480 --> 00:12:15,320 Speaker 1: where we have this magical unrealistic idea of how it works. 232 00:12:15,920 --> 00:12:18,920 Speaker 1: And even if you have the the realistic idea of 233 00:12:18,960 --> 00:12:21,360 Speaker 1: how it works, the idea of that light is entering 234 00:12:21,360 --> 00:12:24,760 Speaker 1: your eyes, you still you still end up thinking about 235 00:12:24,800 --> 00:12:28,400 Speaker 1: the world in terms of the the fictional scenario. I 236 00:12:28,400 --> 00:12:30,360 Speaker 1: think that's sort of a different gap because I think 237 00:12:30,400 --> 00:12:33,719 Speaker 1: most people do know really they know that the light 238 00:12:33,840 --> 00:12:36,160 Speaker 1: is entering the eyes, that nothing, nothing's going out. But 239 00:12:36,200 --> 00:12:39,280 Speaker 1: you're talking there about the difference between what what we 240 00:12:39,360 --> 00:12:44,080 Speaker 1: know and what we feel, and I think that where 241 00:12:44,080 --> 00:12:47,800 Speaker 1: those two converge, there's room for a lot of confusion. 242 00:12:48,120 --> 00:12:50,960 Speaker 1: I think that's absolutely right. Well, I think so today 243 00:12:51,000 --> 00:12:53,680 Speaker 1: we're going to look at the one big original study 244 00:12:54,240 --> 00:12:57,640 Speaker 1: in the illusion of explanatory depth, and then in the 245 00:12:57,679 --> 00:13:00,600 Speaker 1: next episode we're gonna look at some some takeaways and 246 00:13:00,640 --> 00:13:03,480 Speaker 1: some applications from it. But so I guess we should 247 00:13:03,520 --> 00:13:06,199 Speaker 1: get into the study itself, right, Yeah, do you want 248 00:13:06,200 --> 00:13:07,920 Speaker 1: to take a quick break before we get into it. 249 00:13:08,559 --> 00:13:10,400 Speaker 1: I want to take a quick break, Joe, and then 250 00:13:10,400 --> 00:13:17,880 Speaker 1: when we come back, let's get into this study. All right, 251 00:13:17,920 --> 00:13:21,800 Speaker 1: we're back, all right. So this landmark study is called 252 00:13:21,920 --> 00:13:26,920 Speaker 1: The Misunderstood Limits of Folk Science, an Illusion of Explanatory Depth, 253 00:13:27,200 --> 00:13:31,120 Speaker 1: published in Cognitive Science in two thousand two by Frank 254 00:13:31,200 --> 00:13:36,520 Speaker 1: Kyle and Leonard Rosenblit. And so they start by discussing 255 00:13:36,559 --> 00:13:39,920 Speaker 1: the idea of folk theories. Have you ever heard this 256 00:13:40,000 --> 00:13:44,040 Speaker 1: concept before, Robert folk theories or folk science. Yeah, this 257 00:13:44,120 --> 00:13:47,520 Speaker 1: is just kind of the It was like folk medicine, right, 258 00:13:47,559 --> 00:13:50,760 Speaker 1: It's not necessarily there's not necessarily any science to it. 259 00:13:50,760 --> 00:13:54,800 Speaker 1: It's just kind of the the the general understanding of 260 00:13:54,800 --> 00:13:57,280 Speaker 1: how something works or how it's supposed to work. Yeah, 261 00:13:57,280 --> 00:13:59,600 Speaker 1: it's what we come up with when our methods are 262 00:13:59,600 --> 00:14:02,480 Speaker 1: not Garris. Essentially, it's what we all do sort of 263 00:14:02,480 --> 00:14:06,040 Speaker 1: intuitively all the time. And so they say, you know, 264 00:14:06,080 --> 00:14:09,280 Speaker 1: sort of a theory can be defined as a system 265 00:14:09,320 --> 00:14:13,480 Speaker 1: of ideas that are designed to explain something observed. The 266 00:14:13,480 --> 00:14:16,800 Speaker 1: theory gives an explanation, and theories are a totally common 267 00:14:16,800 --> 00:14:19,600 Speaker 1: feature of science and of everyday life. You know, we 268 00:14:19,600 --> 00:14:21,480 Speaker 1: we use theories all the time. They might not be 269 00:14:21,600 --> 00:14:25,360 Speaker 1: good or correct theories, but we're constantly having theories about 270 00:14:25,480 --> 00:14:28,560 Speaker 1: the explanation of the workings of objects and systems. A 271 00:14:28,680 --> 00:14:32,120 Speaker 1: great example of this is that blue blood in your veins. 272 00:14:33,120 --> 00:14:35,680 Speaker 1: Oh yeah, do you have an explanation for that? Well, 273 00:14:35,720 --> 00:14:39,120 Speaker 1: there's the Well, it's because it's deprived of oxygen, right, 274 00:14:39,360 --> 00:14:41,680 Speaker 1: and that why it turns blue. That's not correct, is it. No, 275 00:14:41,800 --> 00:14:43,480 Speaker 1: it's not correct, but it's It's one of those that 276 00:14:43,600 --> 00:14:46,880 Speaker 1: is often thrown out there sometimes but very intelligent people. 277 00:14:46,880 --> 00:14:49,000 Speaker 1: It's I you know, I don't mean to to mention 278 00:14:49,000 --> 00:14:52,040 Speaker 1: any of these is an example of intellectual failing, but 279 00:14:52,080 --> 00:14:56,320 Speaker 1: they just they pick up esteem. They're passed around, and 280 00:14:56,760 --> 00:14:59,040 Speaker 1: it's easy to go through life thinking that they're true. No, 281 00:14:59,240 --> 00:15:01,160 Speaker 1: and that that can to another thing. We should say. 282 00:15:01,200 --> 00:15:03,760 Speaker 1: This episode is going to be all about our cognitive 283 00:15:03,800 --> 00:15:07,640 Speaker 1: limitations and failures and overconfidence in what we know. But 284 00:15:07,800 --> 00:15:10,680 Speaker 1: this isn't to say that people are stupid or you know, 285 00:15:10,880 --> 00:15:13,280 Speaker 1: we're not accusing the people featured in the studies or 286 00:15:13,320 --> 00:15:16,600 Speaker 1: people in general of being dumb. It's just good to 287 00:15:16,760 --> 00:15:20,440 Speaker 1: reckon with what the mistakes human brains usually make. Our 288 00:15:20,880 --> 00:15:25,840 Speaker 1: human brains make mistakes continually, and uh, I mean, the 289 00:15:25,840 --> 00:15:28,360 Speaker 1: best you can do is be aware of the limitations. 290 00:15:28,400 --> 00:15:30,880 Speaker 1: But one of the things about these folk theories is 291 00:15:30,920 --> 00:15:34,400 Speaker 1: that they often feel like they explain more than they 292 00:15:34,440 --> 00:15:36,960 Speaker 1: actually do. And take the blue blood in the vein 293 00:15:37,320 --> 00:15:40,880 Speaker 1: that that seems intuitive. What if somebody you believe that, Okay, 294 00:15:40,960 --> 00:15:43,080 Speaker 1: I'm looking at my veins in their blue and it's 295 00:15:43,080 --> 00:15:45,720 Speaker 1: because the blood turns blue. What if somebody asked you 296 00:15:46,240 --> 00:15:51,840 Speaker 1: to write down an explanation of how that happens. Then 297 00:15:51,880 --> 00:15:54,000 Speaker 1: you'd start being like, well, wait, so I'm trying to 298 00:15:54,000 --> 00:15:56,480 Speaker 1: write the steps down, so the blood is deprived of 299 00:15:56,520 --> 00:16:00,840 Speaker 1: oxygen and turns blue, how does that happen? Don't You'd 300 00:16:00,840 --> 00:16:04,640 Speaker 1: start encountering gaps in your knowledge. And the authors of 301 00:16:04,680 --> 00:16:07,480 Speaker 1: the study right about this, they say, quote, we frequently 302 00:16:07,520 --> 00:16:10,760 Speaker 1: discovered that the theory that seems crystal clear and complete 303 00:16:10,760 --> 00:16:15,080 Speaker 1: in our head suddenly develops gaping holes and inconsistencies when 304 00:16:15,080 --> 00:16:18,120 Speaker 1: we try to set it down on paper. Uh, intuitively, 305 00:16:18,200 --> 00:16:20,600 Speaker 1: I think that's they're exactly correct about that. I've had 306 00:16:20,600 --> 00:16:23,600 Speaker 1: this experience plenty of times, or not even on paper. 307 00:16:23,640 --> 00:16:25,920 Speaker 1: I bet Robert, I bet you've had this experience too. 308 00:16:25,920 --> 00:16:29,680 Speaker 1: I know I have. Here in the podcast studio. In 309 00:16:29,720 --> 00:16:32,800 Speaker 1: the middle of a podcast, maybe a tangent comes up 310 00:16:32,800 --> 00:16:35,480 Speaker 1: where you briefly want to explain how something works that's 311 00:16:35,520 --> 00:16:38,120 Speaker 1: not central to your research, and you think you do, 312 00:16:38,280 --> 00:16:40,920 Speaker 1: so you just start talking, and you get a sentence 313 00:16:41,000 --> 00:16:43,440 Speaker 1: or two in and you wait. You're like, oh, wait 314 00:16:43,480 --> 00:16:47,080 Speaker 1: a minute. I thought I understood that when I started talking, 315 00:16:47,120 --> 00:16:49,800 Speaker 1: But now that I'm saying the words, I don't actually 316 00:16:49,840 --> 00:16:52,800 Speaker 1: know how this works. And you have to stop and 317 00:16:52,840 --> 00:16:55,520 Speaker 1: figure out, Okay, what am I gonna do now? Yeah? Yeah, 318 00:16:55,760 --> 00:16:57,800 Speaker 1: you have to make that decision. Do I do I 319 00:16:57,840 --> 00:17:00,520 Speaker 1: own up to the fact that I that I really 320 00:17:00,560 --> 00:17:02,560 Speaker 1: don't know what I'm talking about. I'm gonna make everybody 321 00:17:02,560 --> 00:17:05,480 Speaker 1: wait while I read about this for fifteen minutes. Or 322 00:17:05,560 --> 00:17:08,560 Speaker 1: do I just plow ahead and somehow easyl my way 323 00:17:08,560 --> 00:17:11,480 Speaker 1: out of it. Um. I think where I encountered this 324 00:17:11,520 --> 00:17:15,040 Speaker 1: a lot is is in the preparation for a podcast episode. 325 00:17:15,560 --> 00:17:18,200 Speaker 1: My wife will ask me what we're recording on this week, 326 00:17:18,560 --> 00:17:20,679 Speaker 1: and I'll say, oh, recording on such and side, and 327 00:17:20,720 --> 00:17:22,760 Speaker 1: she's like, oh, really, what's what's that about? Give me 328 00:17:22,800 --> 00:17:25,320 Speaker 1: the elevator pitch and and then I'll start to explain it, 329 00:17:25,359 --> 00:17:27,760 Speaker 1: and then I'll realize, oh, you know, it's you know, 330 00:17:27,840 --> 00:17:32,119 Speaker 1: A plus VEH equals C, except I can't adequately describe 331 00:17:32,359 --> 00:17:35,280 Speaker 1: step B in the scenario. It made sense in your 332 00:17:35,320 --> 00:17:38,440 Speaker 1: head until you started trying to use words, and then 333 00:17:38,600 --> 00:17:41,359 Speaker 1: that's where the that's where it became problematic. And what 334 00:17:41,440 --> 00:17:44,040 Speaker 1: it reveals is that, in fact, it didn't actually make 335 00:17:44,119 --> 00:17:46,560 Speaker 1: sense in my head. It just felt like it did. 336 00:17:46,680 --> 00:17:48,720 Speaker 1: And it's useful to it for us because then you know, oh, well, 337 00:17:48,760 --> 00:17:51,600 Speaker 1: that's that's what I don't understand. That's what I need. 338 00:17:51,640 --> 00:17:54,239 Speaker 1: That needs to make sense to me truly, because if 339 00:17:54,240 --> 00:17:55,800 Speaker 1: it doesn't truly make sense to me, it's not going 340 00:17:55,880 --> 00:17:58,520 Speaker 1: to make sense to the listener. Right. Okay, So folk 341 00:17:58,640 --> 00:18:02,080 Speaker 1: theories in contrast us too scientific theories, where you've got 342 00:18:02,119 --> 00:18:05,199 Speaker 1: scientists trying to constantly hunt down the gaping holes and 343 00:18:05,240 --> 00:18:10,160 Speaker 1: inconsistencies in their theories and fix them. With folk theories, uh, 344 00:18:10,359 --> 00:18:13,240 Speaker 1: the explanatory systems are sort of produced in the minds 345 00:18:13,280 --> 00:18:17,199 Speaker 1: of lay people by non rigorous processes. And uh so, 346 00:18:17,240 --> 00:18:19,919 Speaker 1: if you're not a telecommunications engineer, you probably have some 347 00:18:20,000 --> 00:18:23,120 Speaker 1: kind of folk theory about how your cell phone works. Right, 348 00:18:23,160 --> 00:18:26,639 Speaker 1: You've got some basic skeletal idea of well, there's a 349 00:18:26,720 --> 00:18:29,639 Speaker 1: signal in the phone. Maybe you know, it's electromagnetic radiation 350 00:18:29,760 --> 00:18:33,560 Speaker 1: that goes from the phone from the antenna part maybe 351 00:18:33,720 --> 00:18:36,040 Speaker 1: or the antenna is hidden inside now, But it goes 352 00:18:36,080 --> 00:18:38,600 Speaker 1: from part of the phone to a tower. Does it 353 00:18:38,640 --> 00:18:40,520 Speaker 1: go to a satellite, I don't know. If it goes 354 00:18:40,560 --> 00:18:42,760 Speaker 1: to the cloud, that's a big one. And I and 355 00:18:42,800 --> 00:18:46,840 Speaker 1: I've been guilty of this too, not really stopping to realize, 356 00:18:46,840 --> 00:18:48,960 Speaker 1: oh wait, the cloud, Like I know that there's not 357 00:18:49,080 --> 00:18:54,439 Speaker 1: an invisible wonder Woman's airplane type computing system floating in 358 00:18:54,480 --> 00:18:59,000 Speaker 1: the sky. And yet somehow I fall back on that idea, 359 00:18:59,560 --> 00:19:02,600 Speaker 1: just perhaps just out of like I out of a 360 00:19:02,680 --> 00:19:07,880 Speaker 1: lack of desire to understand um the details and our 361 00:19:07,880 --> 00:19:12,040 Speaker 1: telecommunication system. But but yeah, I find myself at least 362 00:19:12,040 --> 00:19:14,960 Speaker 1: putting it up, putting the non realists, the unrealistic version 363 00:19:15,000 --> 00:19:19,840 Speaker 1: up on the shelf with a more realistic expectation of technology. Yeah, 364 00:19:19,880 --> 00:19:22,879 Speaker 1: and yet nevertheless, you sort of think you understand how 365 00:19:22,920 --> 00:19:25,160 Speaker 1: a cell phone works right at a basic level, at 366 00:19:25,160 --> 00:19:27,359 Speaker 1: a basic level, and and then you start, oh no. 367 00:19:28,080 --> 00:19:30,160 Speaker 1: But so the authors of the study, they're they're talking 368 00:19:30,200 --> 00:19:33,520 Speaker 1: about the problems with the way people hold them. So 369 00:19:33,720 --> 00:19:37,920 Speaker 1: they say, quote first, they are novice scientists. People people 370 00:19:37,960 --> 00:19:41,359 Speaker 1: in general are novice scientists. Their knowledge of most phenomena 371 00:19:41,600 --> 00:19:44,600 Speaker 1: is not very deep. We have shallow understandings. But then 372 00:19:44,640 --> 00:19:49,320 Speaker 1: they also say, quote second, their novice epistemologists, meaning people 373 00:19:49,320 --> 00:19:54,399 Speaker 1: who study how knowledge is generated, how we know things, uh, continuing, 374 00:19:54,600 --> 00:19:58,080 Speaker 1: their sense of the properties of knowledge itself, including how 375 00:19:58,119 --> 00:20:01,600 Speaker 1: it is stored, is poor and potentially misleading. So we 376 00:20:01,680 --> 00:20:04,520 Speaker 1: have both an incomplete understanding of how many things work, 377 00:20:04,720 --> 00:20:07,359 Speaker 1: but we also fail to recognize that we have an 378 00:20:07,359 --> 00:20:11,240 Speaker 1: incomplete understanding, uh, exhibited by the fact that when we 379 00:20:11,280 --> 00:20:13,320 Speaker 1: get put on the spot where we're sort of caught 380 00:20:13,320 --> 00:20:16,080 Speaker 1: off guard, we're like, oh, wait, I thought I understood that, 381 00:20:16,119 --> 00:20:19,600 Speaker 1: but now I'm realizing maybe I didn't. UM. So their 382 00:20:19,640 --> 00:20:23,800 Speaker 1: central thesis in this paper is quote we argue here 383 00:20:23,840 --> 00:20:28,080 Speaker 1: that people's limited knowledge and they're misleading. Intuitive epistemology combined 384 00:20:28,119 --> 00:20:32,080 Speaker 1: to create an illusion of explanatory depth or io e ed. 385 00:20:32,960 --> 00:20:37,880 Speaker 1: Most people feel they understand the world in far greater detail, coherence, 386 00:20:37,960 --> 00:20:42,520 Speaker 1: and depth than they actually do. Um Also, they say 387 00:20:42,520 --> 00:20:45,960 Speaker 1: that we're more overconfident about our understanding of some types 388 00:20:46,000 --> 00:20:50,000 Speaker 1: of knowledge than others. Specifically, are our knowledge dealing with 389 00:20:50,160 --> 00:20:53,639 Speaker 1: explanations for how things work that that is that is 390 00:20:53,680 --> 00:20:56,800 Speaker 1: to be singled out. So to test these ideas, the 391 00:20:56,880 --> 00:21:00,720 Speaker 1: authors performed a big series of studies. They're actually twelve 392 00:21:00,800 --> 00:21:04,760 Speaker 1: different studies inside this this massive paper, UH, to measure 393 00:21:04,760 --> 00:21:09,600 Speaker 1: people's level of confidence in their understanding compared with what 394 00:21:09,680 --> 00:21:12,920 Speaker 1: their actual level of understanding is as measured by their 395 00:21:12,920 --> 00:21:18,120 Speaker 1: confidence after they've had some calibration, and then then UH, 396 00:21:18,160 --> 00:21:22,240 Speaker 1: comparing that within various different domains of knowledge, meaning just 397 00:21:22,359 --> 00:21:26,320 Speaker 1: different types of knowing things do you know facts about geography, 398 00:21:26,440 --> 00:21:29,120 Speaker 1: or do you know the narratives of movie plots, or 399 00:21:29,359 --> 00:21:34,000 Speaker 1: do you know how a toilet works. So there have 400 00:21:34,040 --> 00:21:36,399 Speaker 1: been a lot of previous studies about overconfidence, and one 401 00:21:36,440 --> 00:21:39,760 Speaker 1: of the things that's important to establish is that a 402 00:21:39,800 --> 00:21:43,720 Speaker 1: lot of previous research has sort of focused on general knowledge, 403 00:21:43,920 --> 00:21:48,040 Speaker 1: that people might be overconfident about knowledge in general. And 404 00:21:48,080 --> 00:21:51,440 Speaker 1: the authors are not into this idea. That they don't 405 00:21:51,480 --> 00:21:54,439 Speaker 1: like the idea of general knowledge. Instead, they like the 406 00:21:54,480 --> 00:21:58,320 Speaker 1: idea of breaking out knowledge into these different categories, because, 407 00:21:58,359 --> 00:22:01,040 Speaker 1: as they will end up showing in their research, the 408 00:22:01,160 --> 00:22:05,399 Speaker 1: brain estimates its own knowledge in different categories in with 409 00:22:05,480 --> 00:22:08,639 Speaker 1: different levels of accuracy. Yeah. I think we all, most 410 00:22:08,760 --> 00:22:11,760 Speaker 1: healthy individuals realize that they know a lot about some 411 00:22:11,800 --> 00:22:16,960 Speaker 1: things maybe, but certainly little or nothing about other topics. Correct, right, 412 00:22:17,320 --> 00:22:21,080 Speaker 1: and especially uh, not just topics, but different types of 413 00:22:21,119 --> 00:22:24,240 Speaker 1: things to know. Like, you might be way more if 414 00:22:24,280 --> 00:22:29,639 Speaker 1: I ask you, um, Robert, what is the capital of England? 415 00:22:30,240 --> 00:22:32,760 Speaker 1: Before you answer, tell me how confident are you that 416 00:22:32,800 --> 00:22:34,560 Speaker 1: you know the right answer? On a scale of one 417 00:22:34,600 --> 00:22:38,199 Speaker 1: to ten, I would say a ten, Okay, what's the 418 00:22:38,240 --> 00:22:42,159 Speaker 1: capital London? Okay, you're right there, you go. Okay, but 419 00:22:42,320 --> 00:22:45,080 Speaker 1: tell me how confident are you that you can explain 420 00:22:45,119 --> 00:22:49,840 Speaker 1: how a lightsaber works? Well? Uh, not not very because 421 00:22:49,880 --> 00:22:53,840 Speaker 1: that's a it's essentially a magical device. Yeah, I forgot 422 00:22:54,040 --> 00:22:57,240 Speaker 1: and uh and and I also don't I actually I 423 00:22:57,320 --> 00:23:00,240 Speaker 1: think I rewrote the intro page for how lightsabers were 424 00:23:00,400 --> 00:23:02,840 Speaker 1: on how stuff works dot com. Yeah, so I have 425 00:23:02,960 --> 00:23:06,560 Speaker 1: actually worked with the an article, an article that explains 426 00:23:06,640 --> 00:23:10,000 Speaker 1: how it supposedly works, but I don't recall it at all. 427 00:23:10,680 --> 00:23:12,880 Speaker 1: Do you think working on that article would have made 428 00:23:12,880 --> 00:23:16,080 Speaker 1: you more or less confident in your own understanding. I 429 00:23:16,080 --> 00:23:18,600 Speaker 1: think if I had actually worked on the meat of it. 430 00:23:18,960 --> 00:23:20,840 Speaker 1: But that's an article. I think I just brewsed up 431 00:23:20,880 --> 00:23:23,879 Speaker 1: the landing page. I just sexed it up a little. 432 00:23:23,960 --> 00:23:26,080 Speaker 1: Did Tracy Wilson write that one? No, I think it 433 00:23:26,119 --> 00:23:30,439 Speaker 1: was an older piece. Well, anyway, let's go onto the study. 434 00:23:30,720 --> 00:23:34,359 Speaker 1: So study number one out of this. First thing they 435 00:23:34,359 --> 00:23:37,680 Speaker 1: wanted to do was document the illusion of explanatory depth. 436 00:23:37,760 --> 00:23:39,960 Speaker 1: If this thing exists, let's see if we can get 437 00:23:39,960 --> 00:23:42,120 Speaker 1: some evidence that it is there. So they got sixteen 438 00:23:42,119 --> 00:23:45,920 Speaker 1: graduate students from various departments at Yale and these are 439 00:23:45,920 --> 00:23:49,480 Speaker 1: the participants that this was done by professors at Yale University, 440 00:23:49,560 --> 00:23:52,359 Speaker 1: so there's a lot of Yale's in this. And the 441 00:23:52,880 --> 00:23:55,040 Speaker 1: test dealt with their ability to explain how a bunch 442 00:23:55,080 --> 00:23:58,320 Speaker 1: of devices work. So participants were given instructions on how 443 00:23:58,400 --> 00:24:02,240 Speaker 1: to rate their level of explanatory knowledge of a device 444 00:24:02,280 --> 00:24:05,080 Speaker 1: on a scale of one to seven with the help 445 00:24:05,080 --> 00:24:08,520 Speaker 1: of a couple of examples GPS system and a crossbow. 446 00:24:08,920 --> 00:24:12,159 Speaker 1: So with the example of a crossbow, basically a seven 447 00:24:12,200 --> 00:24:14,480 Speaker 1: means you know all the parts and you know how 448 00:24:14,520 --> 00:24:16,960 Speaker 1: all of them work together to make the device work. 449 00:24:17,040 --> 00:24:20,080 Speaker 1: You know all the causal relationships. You could you could 450 00:24:20,080 --> 00:24:22,760 Speaker 1: almost build the thing yourself if you had all the parts. 451 00:24:23,359 --> 00:24:27,120 Speaker 1: Um A one means you you basically don't know anything 452 00:24:27,160 --> 00:24:29,240 Speaker 1: more than what it looks like and what it does. 453 00:24:29,359 --> 00:24:31,480 Speaker 1: You don't know what the parts are, how the parts 454 00:24:31,480 --> 00:24:34,919 Speaker 1: work together. It's almost magic to you. Okay. Then the 455 00:24:34,960 --> 00:24:38,119 Speaker 1: participants were given a list of forty eight objects and 456 00:24:38,160 --> 00:24:41,240 Speaker 1: asked to rate their level of understanding of how the 457 00:24:41,280 --> 00:24:44,160 Speaker 1: object works. So you just go down this list, uh 458 00:24:44,240 --> 00:24:48,119 Speaker 1: you know, uh l C D screen, car, battery, a zipper, 459 00:24:48,280 --> 00:24:53,560 Speaker 1: a spiedometer, piano, key, can opener, hydroelectric turbine, flush toilet, 460 00:24:53,880 --> 00:24:57,919 Speaker 1: cylinder lock, helicopter, quartz watch, sewing machine, And you're supposed 461 00:24:57,920 --> 00:25:00,000 Speaker 1: to give the number on the scale of one to seven. 462 00:25:00,040 --> 00:25:02,240 Speaker 1: Then how well do you understand what all the parts are, 463 00:25:02,400 --> 00:25:05,200 Speaker 1: how they work together? How well do how well do 464 00:25:05,240 --> 00:25:07,480 Speaker 1: you understand how it works? And just to use a 465 00:25:07,480 --> 00:25:10,320 Speaker 1: little terminology because it will recur throughout throughout all the 466 00:25:10,320 --> 00:25:13,200 Speaker 1: different studies here. This first rating is known as T one. 467 00:25:13,359 --> 00:25:15,880 Speaker 1: This thing they give on the first questions their own 468 00:25:15,880 --> 00:25:19,040 Speaker 1: self rating of their explanatory knowledge of each item. Is 469 00:25:19,119 --> 00:25:21,680 Speaker 1: T one. And then in the next phase, the students 470 00:25:22,119 --> 00:25:25,600 Speaker 1: are asked to write a detailed explanation for half of 471 00:25:25,640 --> 00:25:28,399 Speaker 1: the of some of these items in the test category, 472 00:25:29,000 --> 00:25:32,040 Speaker 1: to explain in detail how a sewing machine works. So 473 00:25:32,240 --> 00:25:35,359 Speaker 1: you rated maybe a four on how well you know 474 00:25:35,400 --> 00:25:37,520 Speaker 1: how a sewing machine works? Now we need you to 475 00:25:37,600 --> 00:25:40,879 Speaker 1: explain it step by step in in words, And then 476 00:25:40,920 --> 00:25:43,359 Speaker 1: they wrote that detailed explanation. Then they were asked to 477 00:25:43,520 --> 00:25:47,160 Speaker 1: rate their initial understanding again. So now that you've written 478 00:25:47,160 --> 00:25:51,520 Speaker 1: that explanation, how well did you understand it to begin with? Uh? 479 00:25:51,560 --> 00:25:54,200 Speaker 1: Then they were given and that that rating is T 480 00:25:54,200 --> 00:25:58,920 Speaker 1: two uh. Then they're given a diagnostic question. For example, 481 00:25:59,400 --> 00:26:01,280 Speaker 1: if one of the items they had to explain was 482 00:26:01,320 --> 00:26:04,639 Speaker 1: a cylinder lock, the diagnostic question might be do you 483 00:26:04,640 --> 00:26:08,000 Speaker 1: know how to pick a cylinder lock? And this question 484 00:26:08,080 --> 00:26:10,720 Speaker 1: is designed to force the person to think even more 485 00:26:10,800 --> 00:26:13,080 Speaker 1: about what the parts are and how they work together. 486 00:26:13,400 --> 00:26:15,960 Speaker 1: And then after the diagnostic question, they're asked to rate 487 00:26:16,000 --> 00:26:19,320 Speaker 1: their initial understanding yet again how well did you understand 488 00:26:19,359 --> 00:26:22,800 Speaker 1: it to begin with? And then finally the participants got 489 00:26:22,800 --> 00:26:26,600 Speaker 1: to read a brief explanation written by an expert of 490 00:26:26,720 --> 00:26:30,280 Speaker 1: how these items worked that they explained. And these expert 491 00:26:30,320 --> 00:26:33,320 Speaker 1: explanations came from a cd ROM titled The Way Things 492 00:26:33,320 --> 00:26:35,719 Speaker 1: Worked two point oh. I was hoping they'd use some 493 00:26:35,800 --> 00:26:40,040 Speaker 1: vintage how stuff Works articles. No, no, alas it was 494 00:26:40,080 --> 00:26:43,200 Speaker 1: two thousand two. How staff Works existed then, but we 495 00:26:43,200 --> 00:26:47,000 Speaker 1: were not here anyway. After reading these expert explanations, they 496 00:26:47,040 --> 00:26:50,879 Speaker 1: had to rate again how well they had initially understood 497 00:26:50,880 --> 00:26:53,680 Speaker 1: the device, and then how well they understood it now 498 00:26:53,800 --> 00:26:57,960 Speaker 1: after having read the explanation. So what are the results? 499 00:26:58,000 --> 00:27:00,399 Speaker 1: What does this graph look like? You start with your 500 00:27:00,440 --> 00:27:03,480 Speaker 1: initial guests, and then you get adjusted by having had 501 00:27:03,520 --> 00:27:07,760 Speaker 1: to make an explanation, answer a diagnostic question, and then 502 00:27:07,800 --> 00:27:10,600 Speaker 1: read an expert's explanation. Well, the graph forms a kind 503 00:27:10,600 --> 00:27:14,600 Speaker 1: of U shape or an inverted bell shape, where initially 504 00:27:14,640 --> 00:27:18,000 Speaker 1: the students rate their level of understanding really high or 505 00:27:18,359 --> 00:27:21,560 Speaker 1: relatively high. Not necessarily really high, but it's like, yeah, 506 00:27:21,920 --> 00:27:24,359 Speaker 1: you know, I give it a four. I I understand 507 00:27:24,400 --> 00:27:28,480 Speaker 1: pretty well how a cylinder lock works. Then then they 508 00:27:28,480 --> 00:27:31,879 Speaker 1: have to give the explanation and the ratings drop off significantly. 509 00:27:32,480 --> 00:27:34,840 Speaker 1: Now note that this is not somebody coming in from 510 00:27:34,840 --> 00:27:37,840 Speaker 1: the outside and telling them their explanation is wrong. This 511 00:27:37,920 --> 00:27:41,560 Speaker 1: is their own self evaluation after having had to do 512 00:27:41,640 --> 00:27:45,360 Speaker 1: nothing but just put their own ideas into words. Then 513 00:27:45,359 --> 00:27:48,359 Speaker 1: it continued to drop again after the diagnostic question, and 514 00:27:48,359 --> 00:27:52,440 Speaker 1: then finally shot back up again after reading the experts explanation. No, 515 00:27:52,640 --> 00:27:55,520 Speaker 1: no surprise. If you read somebody telling you how it works, 516 00:27:55,560 --> 00:27:57,639 Speaker 1: now you understand how it works. So it's a perfect 517 00:27:57,680 --> 00:28:00,320 Speaker 1: story arc. It's kind of like a most to kung 518 00:28:00,359 --> 00:28:03,520 Speaker 1: fu movies, right where you have the the the young 519 00:28:03,640 --> 00:28:06,679 Speaker 1: student who is overconfident and then his uh, his, he 520 00:28:06,720 --> 00:28:10,080 Speaker 1: gets his his rear end handed to him by the villain, 521 00:28:10,520 --> 00:28:12,879 Speaker 1: and then he has to learn, he has to accept 522 00:28:12,920 --> 00:28:15,000 Speaker 1: what he doesn't know, and then he has to to 523 00:28:15,080 --> 00:28:17,760 Speaker 1: learn the craft from a from a master, and then 524 00:28:17,840 --> 00:28:20,840 Speaker 1: in the end he can defeat the villain. It's a 525 00:28:20,880 --> 00:28:26,240 Speaker 1: kind of a cry kid situation. Yeah. I think that's 526 00:28:26,240 --> 00:28:30,920 Speaker 1: interesting how how our our narratives play on this this 527 00:28:31,440 --> 00:28:34,480 Speaker 1: fact about us. It almost suggests that somehow we might 528 00:28:34,600 --> 00:28:38,800 Speaker 1: intuitively be somewhat aware of the illusion of explanatory depth. 529 00:28:39,520 --> 00:28:42,520 Speaker 1: But so anyway, looking at this graph, so you know 530 00:28:42,640 --> 00:28:45,080 Speaker 1: that there were drops from T one to T two, 531 00:28:45,440 --> 00:28:48,000 Speaker 1: and then again slightly from T two to T three, 532 00:28:48,640 --> 00:28:51,280 Speaker 1: and then pretty much no drop from T three to 533 00:28:51,400 --> 00:28:54,560 Speaker 1: T four, and then a large increase from T four 534 00:28:54,640 --> 00:28:57,040 Speaker 1: to T five. So one of the things is the 535 00:28:57,040 --> 00:29:01,000 Speaker 1: pattern rules out the idea that confidence is dropping merely 536 00:29:01,040 --> 00:29:04,320 Speaker 1: because of the elapsing of time in the experiment. Right, 537 00:29:04,360 --> 00:29:07,200 Speaker 1: It's not just people are steadily going lower. You know 538 00:29:07,360 --> 00:29:10,560 Speaker 1: that there they eventually stopped lowering their own score, and 539 00:29:10,560 --> 00:29:13,520 Speaker 1: then it comes back up after they read the expert's explanation. 540 00:29:15,000 --> 00:29:17,520 Speaker 1: So so that basically you have to confront what you 541 00:29:17,600 --> 00:29:21,440 Speaker 1: don't know in order to learn, yes, exactly. And the 542 00:29:21,520 --> 00:29:24,560 Speaker 1: interesting thing is that if they're they they sort of 543 00:29:24,680 --> 00:29:27,640 Speaker 1: rate themselves lower, but then they don't keep dropping, You're 544 00:29:27,640 --> 00:29:30,800 Speaker 1: not in free fall. Maybe that suggests that they're adjusting 545 00:29:30,960 --> 00:29:34,720 Speaker 1: more toward real accuracy in their judgment of how much 546 00:29:34,760 --> 00:29:37,840 Speaker 1: they knew. There's also an interesting note that they have 547 00:29:37,920 --> 00:29:40,280 Speaker 1: though this is not quantified data, but this is just 548 00:29:40,360 --> 00:29:43,640 Speaker 1: sort of a subjective report from the debriefing afterwards. You know, 549 00:29:43,680 --> 00:29:46,160 Speaker 1: they talked to the people who were in the experiments, 550 00:29:46,440 --> 00:29:50,920 Speaker 1: and many participants subjectively said they were surprised and felt 551 00:29:51,000 --> 00:29:54,160 Speaker 1: humbled by how much less they knew than they had 552 00:29:54,160 --> 00:29:58,560 Speaker 1: originally assumed. But also, and this is really interesting, even 553 00:29:58,640 --> 00:30:02,560 Speaker 1: with this new humility. Some of the participants showed that 554 00:30:02,600 --> 00:30:05,920 Speaker 1: they were still susceptible to the illusion of explanatory depth, 555 00:30:06,000 --> 00:30:08,760 Speaker 1: because here's what they said. If only I had gotten 556 00:30:08,760 --> 00:30:11,720 Speaker 1: the cylinder lock instead of the flush toilet or whatever, 557 00:30:12,240 --> 00:30:15,240 Speaker 1: then I would have done better overall. So if only 558 00:30:15,280 --> 00:30:18,520 Speaker 1: I'd gotten these other devices instead of the ones I had, 559 00:30:18,880 --> 00:30:23,160 Speaker 1: And the experimenters say, this judgment seems unlikely to be true, 560 00:30:23,200 --> 00:30:26,080 Speaker 1: given that the average level of performance on the two 561 00:30:26,400 --> 00:30:31,600 Speaker 1: different device sets used in the test was pretty much identical. Okay, 562 00:30:31,680 --> 00:30:33,959 Speaker 1: so it to use the kung fu advantage. It's like 563 00:30:34,000 --> 00:30:38,200 Speaker 1: the the young foolish hero enters into combat with the 564 00:30:38,280 --> 00:30:42,200 Speaker 1: villain and is defeated in a sword fight. Uh, and 565 00:30:42,240 --> 00:30:45,080 Speaker 1: then afterwards he's like like, oh my goodness, Yeah, I 566 00:30:45,400 --> 00:30:47,200 Speaker 1: really didn't know how to fight with a so hard. 567 00:30:47,200 --> 00:30:50,040 Speaker 1: After all. If only he had fought me in judo 568 00:30:50,680 --> 00:30:53,160 Speaker 1: right then, then I truly I would have taken him 569 00:30:53,160 --> 00:30:55,800 Speaker 1: out like that. But what if this guy everybody else 570 00:30:55,840 --> 00:30:58,680 Speaker 1: said that about judo, and this guy has defeated everybody 571 00:30:58,680 --> 00:31:01,600 Speaker 1: in Judo also, Yeah, I mean, if if he's wrong 572 00:31:01,640 --> 00:31:04,520 Speaker 1: about this thing, then it could he is it true 573 00:31:04,560 --> 00:31:06,840 Speaker 1: that he's right about everything else? I would doubt it. 574 00:31:07,000 --> 00:31:11,120 Speaker 1: Well it is if he's very special. Maybe he's very special. 575 00:31:11,360 --> 00:31:14,000 Speaker 1: But but yeah, it shows this um you can still 576 00:31:14,040 --> 00:31:16,600 Speaker 1: you still have the blinders on, like you've been humbled 577 00:31:16,760 --> 00:31:19,880 Speaker 1: on this one category, but you're still susceptible to the 578 00:31:19,960 --> 00:31:24,360 Speaker 1: to the illusion of understanding in all other aspects of life. Yeah, 579 00:31:24,400 --> 00:31:26,680 Speaker 1: if only I'd had the toilet, then I would have 580 00:31:26,680 --> 00:31:31,160 Speaker 1: been golden. Okay, anyway, so established here. But this is 581 00:31:31,200 --> 00:31:34,680 Speaker 1: a pretty small sample sixteen grad students, also Yale grad students. 582 00:31:34,680 --> 00:31:37,840 Speaker 1: That's pretty rarefied group to draw from. So we need 583 00:31:37,880 --> 00:31:40,000 Speaker 1: to do some more experiments of the same type to 584 00:31:40,040 --> 00:31:43,520 Speaker 1: try to replicate the results. So they did another one. 585 00:31:43,600 --> 00:31:46,960 Speaker 1: Study number two, they repeat the same experiment, same conditions, 586 00:31:47,000 --> 00:31:49,600 Speaker 1: with a larger, younger sample, a group of thirty three 587 00:31:49,680 --> 00:31:53,560 Speaker 1: Yale undergrads. Undergrads from the same school were picked because, 588 00:31:53,560 --> 00:31:57,240 Speaker 1: in the words of the author's quote, conceivably graduate study 589 00:31:57,320 --> 00:32:00,400 Speaker 1: leads to an intellectual arrogance, and the allude should of 590 00:32:00,400 --> 00:32:04,160 Speaker 1: explanatory competence might be less in undergraduates who are still 591 00:32:04,200 --> 00:32:09,080 Speaker 1: awed by what they do not know. There were there 592 00:32:09,080 --> 00:32:10,800 Speaker 1: were some parts of the study where the writing was 593 00:32:10,840 --> 00:32:14,680 Speaker 1: a little cheeky. I appreciated it. But the thing is 594 00:32:14,920 --> 00:32:19,560 Speaker 1: it replicated basically got very similar results, producing the same 595 00:32:19,640 --> 00:32:23,200 Speaker 1: pattern with respect to the responses over time. Uh. They 596 00:32:23,240 --> 00:32:26,960 Speaker 1: initially rated their own understanding higher than after they had 597 00:32:27,000 --> 00:32:30,520 Speaker 1: to explain it, not got knocked down, uh, and then 598 00:32:30,680 --> 00:32:33,719 Speaker 1: down by the diagnostic question, and then up again at 599 00:32:33,720 --> 00:32:35,560 Speaker 1: the end after they got to read what the expert 600 00:32:35,600 --> 00:32:38,200 Speaker 1: had to say. But one thing that's interesting about the 601 00:32:38,240 --> 00:32:40,960 Speaker 1: undergrads is that the effect was actually just a little 602 00:32:40,960 --> 00:32:44,840 Speaker 1: bit not significantly, not statistically significantly, but a little bit 603 00:32:44,920 --> 00:32:48,760 Speaker 1: stronger with undergrads than with graduate students. So the uh, 604 00:32:49,480 --> 00:32:52,800 Speaker 1: the the graduate student arrogance theory, we can say is 605 00:32:52,840 --> 00:32:57,120 Speaker 1: probably disproved by this. The the undergrads actually did a 606 00:32:57,200 --> 00:33:00,720 Speaker 1: little worse in over over confidence about their understand I 607 00:33:00,960 --> 00:33:05,880 Speaker 1: can certainly remember being a weirdly overconfident undergraduate, for sure, 608 00:33:07,000 --> 00:33:09,480 Speaker 1: I think we all can. Man, wasn't that a great 609 00:33:09,480 --> 00:33:12,880 Speaker 1: time when you knew everything about everything? You know? I 610 00:33:12,920 --> 00:33:15,400 Speaker 1: do remember the kind of the trajectory of sort of 611 00:33:16,240 --> 00:33:19,680 Speaker 1: in particular, I remember going into some religious studies classes 612 00:33:20,120 --> 00:33:25,840 Speaker 1: with certain ideas about the values of certain religions over others, 613 00:33:25,920 --> 00:33:29,400 Speaker 1: and how religion kind of worked, and and uh, and 614 00:33:29,440 --> 00:33:31,600 Speaker 1: it was just completely foolhardy. And then I was opened 615 00:33:31,680 --> 00:33:34,920 Speaker 1: up to do some some generally basic ideas and religious 616 00:33:34,920 --> 00:33:38,560 Speaker 1: studies and you know the importance of world views and 617 00:33:38,600 --> 00:33:41,680 Speaker 1: how the similarity between systems, the history of these different 618 00:33:41,680 --> 00:33:44,880 Speaker 1: religious systems and uh and and I do remember there 619 00:33:44,880 --> 00:33:48,080 Speaker 1: being like this, this resistance to it at first, giving 620 00:33:48,120 --> 00:33:51,800 Speaker 1: in realizing I didn't know anything, and then a real 621 00:33:51,840 --> 00:33:53,960 Speaker 1: excitement they built up from there and really there's you know, 622 00:33:54,000 --> 00:33:57,680 Speaker 1: continued my entire life. And that's something I always trying 623 00:33:57,720 --> 00:34:00,720 Speaker 1: to keep in mind on our show because sometimes we 624 00:34:00,760 --> 00:34:05,840 Speaker 1: do encounter listeners who have uh an adverse reaction to 625 00:34:06,560 --> 00:34:10,400 Speaker 1: studies that we talk about or different different takes on topics, 626 00:34:10,560 --> 00:34:13,640 Speaker 1: and I always remind myself that, well that to put 627 00:34:13,640 --> 00:34:16,200 Speaker 1: it in terms of our study here, that not quite 628 00:34:16,239 --> 00:34:19,480 Speaker 1: free fall, but that descent that occurs doesn't feel good. 629 00:34:19,520 --> 00:34:22,560 Speaker 1: It doesn't feel it can it can feel It's a 630 00:34:22,600 --> 00:34:26,120 Speaker 1: fearful situation at times and humbling. It's humbling, and it's 631 00:34:26,160 --> 00:34:30,080 Speaker 1: in the process of being humbled. Is is not necessarily enjoyable. 632 00:34:30,360 --> 00:34:32,640 Speaker 1: It's like being beaten by the villain and a karate 633 00:34:32,719 --> 00:34:35,400 Speaker 1: movie and the first the first act, but the true 634 00:34:35,440 --> 00:34:38,200 Speaker 1: wise person seeks to be constantly humbled by what they 635 00:34:38,239 --> 00:34:42,000 Speaker 1: don't know. I agree, I am humbled weekend, week out 636 00:34:42,000 --> 00:34:44,160 Speaker 1: by the things I don't know. Oh so, how wise 637 00:34:44,200 --> 00:34:47,200 Speaker 1: are you then, Robert, Well, that that's the thing. I 638 00:34:48,040 --> 00:34:50,640 Speaker 1: admit that I am not the you know, the wisest 639 00:34:51,120 --> 00:34:53,960 Speaker 1: guy in the room, but I am. I'm willing to 640 00:34:54,000 --> 00:34:55,480 Speaker 1: admit that there's a lot there, a lot of things 641 00:34:55,520 --> 00:34:59,239 Speaker 1: I don't know, and I'm continually hungry to to fill 642 00:34:59,239 --> 00:35:03,120 Speaker 1: in those gaps, as we should all be, sir um. Okay, 643 00:35:03,160 --> 00:35:06,080 Speaker 1: So back to the study. So we've looked at one 644 00:35:06,120 --> 00:35:09,200 Speaker 1: sample and then a larger sample of undergrads. Maybe we 645 00:35:09,239 --> 00:35:12,680 Speaker 1: need to look at a different university. Maybe Yale students 646 00:35:12,680 --> 00:35:16,120 Speaker 1: are just generally more arrogant about their own understanding. So 647 00:35:16,160 --> 00:35:18,400 Speaker 1: they figured they should try this at a different university. 648 00:35:18,719 --> 00:35:22,239 Speaker 1: Sixteen students from a regional, less selective state university were 649 00:35:22,280 --> 00:35:25,000 Speaker 1: given the exact same experiment UH and they judged the 650 00:35:25,040 --> 00:35:28,000 Speaker 1: selectivity by comparing the students s A T scores. The 651 00:35:28,000 --> 00:35:30,680 Speaker 1: students at the Southern University had an average of five 652 00:35:31,040 --> 00:35:33,640 Speaker 1: and forty points less on their combined math and verbal 653 00:35:34,280 --> 00:35:37,279 Speaker 1: and the result was The pattern of the pattern of 654 00:35:37,320 --> 00:35:40,120 Speaker 1: results was very similar to the first two studies, a 655 00:35:40,160 --> 00:35:43,960 Speaker 1: steep drop off in confidence after being asked to explain 656 00:35:44,120 --> 00:35:47,279 Speaker 1: what you thought you knew, and then rising confidence and 657 00:35:47,320 --> 00:35:50,680 Speaker 1: new understanding after reading the expert explanation. In fact, though 658 00:35:50,680 --> 00:35:53,640 Speaker 1: the overall pattern was similar between the Yale students and 659 00:35:53,640 --> 00:35:56,160 Speaker 1: the students from this other university, the students at the 660 00:35:56,280 --> 00:36:00,480 Speaker 1: less selective university actually showed a slightly stronger illustion of 661 00:36:00,480 --> 00:36:03,840 Speaker 1: explanatory depth effect uh, mostly due to the fact that 662 00:36:03,880 --> 00:36:07,480 Speaker 1: their initial ratings of knowledge were about a point higher 663 00:36:07,960 --> 00:36:11,000 Speaker 1: than those of the Yale students, and so the results 664 00:36:11,160 --> 00:36:13,960 Speaker 1: results of the first two studies were basically replicated. But 665 00:36:14,000 --> 00:36:16,879 Speaker 1: basically you could you could rule out various different interpretations 666 00:36:16,880 --> 00:36:19,600 Speaker 1: of what this means. Yeah, I mean again, because we're 667 00:36:19,640 --> 00:36:21,480 Speaker 1: all susceptible to this. I think we should trying not 668 00:36:21,480 --> 00:36:25,319 Speaker 1: to put judgment, you know, moral judgments on people's I know, 669 00:36:25,400 --> 00:36:28,080 Speaker 1: I said arrogant a minute ago, because I think the 670 00:36:28,120 --> 00:36:29,960 Speaker 1: authors were being a little bit cheeky when they were 671 00:36:29,960 --> 00:36:34,759 Speaker 1: talking about grad Yale graduate arrogant um. But yeah, it's 672 00:36:34,800 --> 00:36:38,120 Speaker 1: not that you're a bad person if you overestimate how 673 00:36:38,200 --> 00:36:42,879 Speaker 1: well you understand the workings of a toilet we've all 674 00:36:42,920 --> 00:36:45,600 Speaker 1: been there. Yeah, especially if you have attempt to fix one. 675 00:36:45,760 --> 00:36:48,480 Speaker 1: That's generally where the humbling comes. Where if something breaks 676 00:36:48,480 --> 00:36:50,800 Speaker 1: in the house and I think, oh, well, maybe I 677 00:36:50,880 --> 00:36:53,280 Speaker 1: can fix that. Of course I've got an Ikea toolkit, 678 00:36:54,440 --> 00:36:56,560 Speaker 1: let me add it. And then it's you know, hours 679 00:36:56,640 --> 00:36:58,799 Speaker 1: later you realize I'm in over my head. I need 680 00:36:58,800 --> 00:37:01,239 Speaker 1: to actually call an expert. But you don't want to 681 00:37:01,280 --> 00:37:06,840 Speaker 1: admit defeat, right, Okay, So next study studying number four, Well, 682 00:37:07,000 --> 00:37:10,680 Speaker 1: maybe a strange selection of devices is driving the effect. Right, 683 00:37:10,680 --> 00:37:14,480 Speaker 1: they're asking people about certain things cylinder lock, helicopter, toilet, 684 00:37:14,520 --> 00:37:18,399 Speaker 1: all that stuff. What if it's just particularly strong for 685 00:37:18,600 --> 00:37:22,320 Speaker 1: cylinder locks and toilets and helicopters. What if this effect 686 00:37:22,320 --> 00:37:24,680 Speaker 1: wouldn't show up is strongly for other devices. So they 687 00:37:24,719 --> 00:37:28,080 Speaker 1: did the same experiment again, got thirty two undergrads, what 688 00:37:28,200 --> 00:37:32,160 Speaker 1: with many more options for devices. Uh, to explain in 689 00:37:32,200 --> 00:37:34,839 Speaker 1: the experiment and to keep the experiment time under one hour, 690 00:37:35,760 --> 00:37:38,399 Speaker 1: the last couple of ratings T four and T five 691 00:37:38,440 --> 00:37:41,040 Speaker 1: were taken off, so participants only did the first three 692 00:37:41,120 --> 00:37:44,960 Speaker 1: ratings and the results where the different devices didn't change anything, 693 00:37:45,040 --> 00:37:47,759 Speaker 1: the results were the same, So it seems to be 694 00:37:47,920 --> 00:37:50,799 Speaker 1: robust across all different types of machines that you would 695 00:37:50,800 --> 00:37:54,759 Speaker 1: need to explain the workings of. People generally overestimate their 696 00:37:54,840 --> 00:37:58,960 Speaker 1: understanding of them, and then the explanation makes them realize 697 00:37:59,000 --> 00:38:02,719 Speaker 1: that they overestimate aided. So next study, well, what if 698 00:38:02,760 --> 00:38:05,200 Speaker 1: the subjects are just being cautious? This is something I 699 00:38:05,239 --> 00:38:07,399 Speaker 1: thought about when I was sort of running through this 700 00:38:07,600 --> 00:38:10,080 Speaker 1: uh with with Rachel on the way to work today. 701 00:38:10,080 --> 00:38:12,320 Speaker 1: I was like, how well would you think you understand 702 00:38:12,680 --> 00:38:15,640 Speaker 1: how you know A can open our works or something? 703 00:38:16,120 --> 00:38:19,879 Speaker 1: And we discovered that we would tend to just rate 704 00:38:19,880 --> 00:38:23,640 Speaker 1: ourselves very low, maybe because we've been primed with the 705 00:38:23,680 --> 00:38:26,600 Speaker 1: fact that there isn't an illusion of explanatory depth. So 706 00:38:26,640 --> 00:38:29,360 Speaker 1: I'm just gonna I'm gonna start with a two to 707 00:38:29,480 --> 00:38:32,200 Speaker 1: be safe. Yeah, because if you're asking me, hey, do 708 00:38:32,239 --> 00:38:34,320 Speaker 1: you know how do you know how it can opener works? 709 00:38:34,800 --> 00:38:36,960 Speaker 1: I would think you're trying to trick me, right, And 710 00:38:37,000 --> 00:38:39,960 Speaker 1: so maybe maybe the experiment is doing the same thing 711 00:38:40,480 --> 00:38:43,640 Speaker 1: in that once the experience. As the experiment goes on, 712 00:38:43,760 --> 00:38:46,920 Speaker 1: people are just becoming more cautious. They're being put on 713 00:38:47,120 --> 00:38:51,560 Speaker 1: guard and regardless of the actual accuracy of their original 714 00:38:51,600 --> 00:38:54,360 Speaker 1: explanatory depths. Does that make sense, Like they're not adjusting 715 00:38:54,760 --> 00:38:58,439 Speaker 1: toward how well they actually understand things, they're maybe they're 716 00:38:58,440 --> 00:39:02,640 Speaker 1: just adjusting towards call and just lower in general and 717 00:39:02,760 --> 00:39:06,120 Speaker 1: so um. Some students were recruited to subjectively, so they 718 00:39:06,160 --> 00:39:10,000 Speaker 1: basically they did the same study again, the same test, 719 00:39:10,360 --> 00:39:13,080 Speaker 1: you know, hadding people make the assessments. But then they 720 00:39:13,120 --> 00:39:17,480 Speaker 1: also got some people to subjectively rate the explanations written 721 00:39:17,640 --> 00:39:21,040 Speaker 1: by the original people in the study. And some really 722 00:39:21,040 --> 00:39:24,200 Speaker 1: complicated statistical analysis was required on this one, but the 723 00:39:24,200 --> 00:39:27,480 Speaker 1: basic result was that, according to the independent raiders who 724 00:39:27,520 --> 00:39:32,000 Speaker 1: read people's explanations and rated them on the scale, the 725 00:39:32,040 --> 00:39:35,839 Speaker 1: participants initially overestimated their level of understanding, and then their 726 00:39:35,880 --> 00:39:40,319 Speaker 1: confidence ratings became more accurate when they dropped after being 727 00:39:40,360 --> 00:39:42,600 Speaker 1: asked to give the explanation on the and on the 728 00:39:42,640 --> 00:39:45,560 Speaker 1: calibration question. So this seems to rule out the idea 729 00:39:45,600 --> 00:39:48,960 Speaker 1: that people are just becoming more timid or more modest 730 00:39:49,040 --> 00:39:51,960 Speaker 1: or cautious as the ratings go on through the test. 731 00:39:52,280 --> 00:39:55,000 Speaker 1: According to some independent judges who come in and said, 732 00:39:55,080 --> 00:39:58,040 Speaker 1: oh wow, this explanation of a can opener is a 733 00:39:58,120 --> 00:40:04,440 Speaker 1: two um. According to these people, the participants are actually 734 00:40:04,640 --> 00:40:08,080 Speaker 1: becoming more accurate as the test goes on, that they're 735 00:40:08,080 --> 00:40:11,879 Speaker 1: getting closer to how good their understanding was for real. 736 00:40:12,840 --> 00:40:15,239 Speaker 1: Here's another thing related to the priming I was just 737 00:40:15,320 --> 00:40:19,320 Speaker 1: talking about studying number six. Can you destroy the effect 738 00:40:19,560 --> 00:40:22,360 Speaker 1: just by warning people that they're going to have to 739 00:40:22,400 --> 00:40:25,040 Speaker 1: give an explanation for how some of the items work. 740 00:40:25,800 --> 00:40:27,880 Speaker 1: So think about it this way, Robert. You know, I 741 00:40:27,920 --> 00:40:30,440 Speaker 1: ask you, um, on a scale of one to seven, 742 00:40:30,520 --> 00:40:33,400 Speaker 1: how well do you understand how a toilet works? And 743 00:40:33,520 --> 00:40:38,640 Speaker 1: be prepared to explain your answer. Yeah. Another example of 744 00:40:38,680 --> 00:40:41,080 Speaker 1: this would be when someone asks you, hey, have you 745 00:40:41,080 --> 00:40:44,080 Speaker 1: ever seen such and such movie? Your answer might be 746 00:40:44,120 --> 00:40:46,759 Speaker 1: different if you know that the follow up is tell 747 00:40:46,800 --> 00:40:49,920 Speaker 1: me the breakdown of the plot. Yeah, because because that 748 00:40:50,000 --> 00:40:51,960 Speaker 1: I've had that happened before and says, hey, you know 749 00:40:52,000 --> 00:40:54,359 Speaker 1: such and such movie? And sometimes you interpret that as 750 00:40:54,680 --> 00:40:57,279 Speaker 1: do I know of that movie? Did I see the 751 00:40:57,280 --> 00:41:00,400 Speaker 1: trailer for it once? Uh? Did I watch it twenty 752 00:41:00,440 --> 00:41:04,800 Speaker 1: years ago? Yes? Yes? Maybe, But then if you actually 753 00:41:04,840 --> 00:41:08,920 Speaker 1: have to prove that you know this film, that's sometimes 754 00:41:08,920 --> 00:41:11,759 Speaker 1: a different can of worms, right, Yeah, So it could 755 00:41:11,760 --> 00:41:14,759 Speaker 1: put you on guard. And so the question is if 756 00:41:14,760 --> 00:41:18,080 Speaker 1: the illusion of explanatory depth effect is real. What we 757 00:41:18,080 --> 00:41:21,759 Speaker 1: would expect is that maybe maybe warning people this way 758 00:41:22,400 --> 00:41:24,880 Speaker 1: might reduce the effect, elimit a little bit, but it 759 00:41:24,880 --> 00:41:29,680 Speaker 1: shouldn't eliminate it. It shouldn't make it completely go away. Right. Um? 760 00:41:29,880 --> 00:41:33,319 Speaker 1: So with thirty one undergrads again, uh, they did the 761 00:41:33,320 --> 00:41:36,960 Speaker 1: exact same test, except they added a paragraph warning the 762 00:41:37,000 --> 00:41:38,759 Speaker 1: subjects that they were going to have to give a 763 00:41:38,800 --> 00:41:43,560 Speaker 1: written explanation and answer a diagnostic question. So what happened here? Well, 764 00:41:43,600 --> 00:41:47,000 Speaker 1: the results on this one were pretty odd. The same 765 00:41:47,120 --> 00:41:50,640 Speaker 1: pattern presented itself in that the first ratings they gave 766 00:41:50,640 --> 00:41:53,560 Speaker 1: were higher, and then they dropped after being asked to 767 00:41:53,560 --> 00:41:56,600 Speaker 1: write an explanation, and then again after the diagnostic question, 768 00:41:56,920 --> 00:42:00,360 Speaker 1: but the magnitude of the effect was reduced, so the 769 00:42:00,440 --> 00:42:04,760 Speaker 1: drop off was much less. Um, there's still a difference 770 00:42:04,760 --> 00:42:07,400 Speaker 1: between the initial and the later ratings. But the odd 771 00:42:07,400 --> 00:42:10,640 Speaker 1: part is it wasn't because the subjects who were warned 772 00:42:10,800 --> 00:42:14,759 Speaker 1: initially rated their understanding any lower. That's what you would expect, right, 773 00:42:14,760 --> 00:42:17,880 Speaker 1: you'd expect that if you've been warned, your first rating 774 00:42:17,880 --> 00:42:20,359 Speaker 1: would be more cautious, Right Yeah, I mean, if someone 775 00:42:20,440 --> 00:42:22,839 Speaker 1: warns you, whatever you say, someone's going to call you 776 00:42:23,000 --> 00:42:26,520 Speaker 1: on it. So don't. Don't b S is because you 777 00:42:26,520 --> 00:42:28,680 Speaker 1: you will be you'll be corrected, you'll have to have 778 00:42:28,760 --> 00:42:32,280 Speaker 1: to prove your answer. Yeah, but that's not what happened here. Instead, 779 00:42:32,320 --> 00:42:35,799 Speaker 1: they were no less confident in their initial understanding. It 780 00:42:35,880 --> 00:42:41,080 Speaker 1: was because their later self ratings were higher. And that's 781 00:42:41,120 --> 00:42:44,560 Speaker 1: kind of weird, right, So this seems to reveal that 782 00:42:44,680 --> 00:42:46,600 Speaker 1: it's it's not just a it's not it's certainly not 783 00:42:46,719 --> 00:42:50,480 Speaker 1: a conscious matter of I really thinking, Oh, I really 784 00:42:50,520 --> 00:42:52,800 Speaker 1: don't understand how toilets work, but I don't want anybody 785 00:42:52,840 --> 00:42:55,640 Speaker 1: to know, so I'll just tell them I understand. Could 786 00:42:55,680 --> 00:42:57,520 Speaker 1: I mean it? Could? I mean? Maybe that's what's going 787 00:42:57,560 --> 00:43:00,840 Speaker 1: on the author's right quote. One path stability is that 788 00:43:00,920 --> 00:43:05,240 Speaker 1: the new instruction changed the way participants used the rating scales. 789 00:43:05,840 --> 00:43:09,560 Speaker 1: For example, hearing the explicit instructions may have caused participants 790 00:43:09,560 --> 00:43:13,480 Speaker 1: to try to be more consistent with their subsequent ratings 791 00:43:13,520 --> 00:43:17,680 Speaker 1: because they had less justification for being surprised at their 792 00:43:17,719 --> 00:43:22,200 Speaker 1: poor performance. Basically like being it's like you were warned. 793 00:43:22,280 --> 00:43:25,719 Speaker 1: What excuse did you have for overcome for being overconfident 794 00:43:25,800 --> 00:43:28,600 Speaker 1: in how much you knew UM and the fact that 795 00:43:28,640 --> 00:43:30,400 Speaker 1: you were warned? Maybe I don't know, it makes you 796 00:43:30,440 --> 00:43:33,840 Speaker 1: more embarrassed that you were overconfident, and thus you're less 797 00:43:33,840 --> 00:43:38,160 Speaker 1: likely to admit how overconfident you were initially. I don't 798 00:43:38,160 --> 00:43:41,440 Speaker 1: know that that's a that's an odd result here, so 799 00:43:41,520 --> 00:43:44,640 Speaker 1: that's worth keeping in mind. But at this point the 800 00:43:44,640 --> 00:43:50,120 Speaker 1: study considers the initial effect basically satisfactorily satisfactorily replicated for 801 00:43:50,200 --> 00:43:53,160 Speaker 1: how we understand the mechanical workings of devices, and then 802 00:43:53,160 --> 00:43:56,040 Speaker 1: it's gonna move on to other things, other types of 803 00:43:56,080 --> 00:44:00,000 Speaker 1: knowledge and what the researchers called different domains of knowledge. 804 00:44:00,200 --> 00:44:02,879 Speaker 1: Does the same illusion of knowledge hold true for things 805 00:44:03,400 --> 00:44:07,920 Speaker 1: other than next like explanations of causally complex phenomenon like 806 00:44:08,120 --> 00:44:10,880 Speaker 1: how a machine works, how a device works. Does it 807 00:44:10,960 --> 00:44:15,120 Speaker 1: exist for facts? Does it exist for narratives for procedures? 808 00:44:15,400 --> 00:44:18,520 Speaker 1: Can it be lumped in with general over confidence effects? 809 00:44:18,760 --> 00:44:22,439 Speaker 1: Or is the illusion of explanatory depth its own thing? 810 00:44:23,120 --> 00:44:24,880 Speaker 1: So maybe we should take a quick break and then 811 00:44:24,880 --> 00:44:27,320 Speaker 1: when we come back we will get into the rest 812 00:44:27,360 --> 00:44:35,600 Speaker 1: of this study. All right, we're back, So study number seven. 813 00:44:35,880 --> 00:44:37,640 Speaker 1: One of the things is what if people are just 814 00:44:37,719 --> 00:44:41,200 Speaker 1: generally overconfident about what they know, regardless of the type 815 00:44:41,200 --> 00:44:43,400 Speaker 1: of knowledge. What if it's not just explaining things. What 816 00:44:43,480 --> 00:44:47,120 Speaker 1: if everybody's overconfident about all their knowledge. Yeah, I could 817 00:44:47,120 --> 00:44:49,479 Speaker 1: see it being sort of like the scenario in which 818 00:44:49,520 --> 00:44:53,000 Speaker 1: the brain just sort of convinces you that you have 819 00:44:53,040 --> 00:44:55,320 Speaker 1: an answer to a question just so you don't have 820 00:44:55,360 --> 00:44:58,279 Speaker 1: to worry about Because the brain is ultimately an economic system, 821 00:44:58,320 --> 00:45:01,080 Speaker 1: it can't it doesn't need a waste reas sources. So 822 00:45:01,160 --> 00:45:04,600 Speaker 1: it's it's I've read, for instance, the individuals who have 823 00:45:04,680 --> 00:45:07,439 Speaker 1: been quizzed on where they were and what they were 824 00:45:07,440 --> 00:45:11,720 Speaker 1: doing during the September eleventh attacks. People have very specific answers, 825 00:45:11,719 --> 00:45:14,120 Speaker 1: so saying I was wearing a blue shirt, was eating 826 00:45:14,640 --> 00:45:19,960 Speaker 1: hunting nut cheerios, but that in many cases what seems 827 00:45:19,960 --> 00:45:23,600 Speaker 1: to be happening is you're in this state of fight, 828 00:45:23,760 --> 00:45:27,839 Speaker 1: fight or flight. Really uh, there's you're not sure how 829 00:45:27,840 --> 00:45:31,680 Speaker 1: you're gonna survive on some level, and your brain just 830 00:45:31,680 --> 00:45:33,799 Speaker 1: goes ahead and makes up an answer for you. Because 831 00:45:33,800 --> 00:45:35,200 Speaker 1: if to say they don't worry about it was a 832 00:45:35,200 --> 00:45:37,560 Speaker 1: blue shirt, why don't you worry about your shirt that 833 00:45:37,719 --> 00:45:41,000 Speaker 1: there's this awful catastrophic event taking place. Don't worry about 834 00:45:41,000 --> 00:45:43,120 Speaker 1: the cereal bam, I'll just check something off. Don't don't 835 00:45:43,160 --> 00:45:45,640 Speaker 1: even don't even fret. Yeah, I've I've heard about this too, 836 00:45:45,880 --> 00:45:51,239 Speaker 1: like memory confabulation in these like momentary memories, you know, 837 00:45:51,280 --> 00:45:55,279 Speaker 1: the flash bold memories from some big event in your past. Yeah. 838 00:45:55,320 --> 00:45:57,440 Speaker 1: So it's like, if I go into the bathroom and 839 00:45:57,880 --> 00:45:59,480 Speaker 1: on some level one thing, do I know how a 840 00:45:59,560 --> 00:46:01,600 Speaker 1: toilet works? My brain is kind of saying, yeah, you 841 00:46:01,600 --> 00:46:03,920 Speaker 1: know how toilet works, use the restroom, and then you 842 00:46:03,960 --> 00:46:06,560 Speaker 1: flush it obviously. Yeah, don't worry. You've got other things 843 00:46:06,600 --> 00:46:09,000 Speaker 1: to do. Stop worrying about the toilet. Okay, So let's 844 00:46:09,040 --> 00:46:12,759 Speaker 1: test some basic geography here. So specifically, what they did 845 00:46:12,920 --> 00:46:16,200 Speaker 1: was naming the capitals of countries around the world. Experiment 846 00:46:16,280 --> 00:46:18,520 Speaker 1: Ers that came up with a list of forty eight countries, 847 00:46:18,719 --> 00:46:21,600 Speaker 1: and they split it roughly in thirds between countries where 848 00:46:21,640 --> 00:46:24,480 Speaker 1: it's easy to know the capital, or where at least 849 00:46:24,520 --> 00:46:27,920 Speaker 1: where you would expect American students to easily guess the capital. 850 00:46:28,200 --> 00:46:31,279 Speaker 1: How about England. We hit that one already, you know, 851 00:46:31,440 --> 00:46:35,399 Speaker 1: man genius here. Uh, then the ones where they were 852 00:46:35,440 --> 00:46:38,680 Speaker 1: moderate likely moderately likely to know the capital, and then 853 00:46:38,680 --> 00:46:40,759 Speaker 1: the ones where they were very unlikely to know. So 854 00:46:40,880 --> 00:46:44,640 Speaker 1: split into thirds. Uh, Robert, what's the capital of Brazil. Oh, 855 00:46:44,719 --> 00:46:49,200 Speaker 1: this one, it's like Brazilia, but my Portuguese is not good. 856 00:46:49,440 --> 00:46:51,759 Speaker 1: You are correct. I was hoping i'd trick you into 857 00:46:51,760 --> 00:46:55,439 Speaker 1: saying Rio de jann Arrow. Well, this is You would 858 00:46:55,440 --> 00:46:58,239 Speaker 1: have caught me with various states for sure, because yeah, 859 00:46:58,280 --> 00:47:00,720 Speaker 1: you think of the what's the most thing this city 860 00:47:00,800 --> 00:47:03,640 Speaker 1: from that country or US state, and then you assume 861 00:47:03,719 --> 00:47:07,439 Speaker 1: that's the capital. If I recall correctly, the Brazilia Rio 862 00:47:07,600 --> 00:47:11,200 Speaker 1: de Janeiro confusion is actually a major plot point in 863 00:47:11,280 --> 00:47:14,239 Speaker 1: one of the I Know what you did last summer sequels, 864 00:47:14,719 --> 00:47:19,640 Speaker 1: which I am here publicly admitting that I've seen. But 865 00:47:19,680 --> 00:47:24,640 Speaker 1: then also, here's a hard one. What's the capital of Tajikstan. Yeah, 866 00:47:24,680 --> 00:47:27,400 Speaker 1: that one. That one is one that I I probably 867 00:47:27,440 --> 00:47:29,279 Speaker 1: should have a leg up on that one because I 868 00:47:29,280 --> 00:47:32,359 Speaker 1: took because I remember taking a course in college about 869 00:47:32,640 --> 00:47:37,279 Speaker 1: former Soviet states in that region. Yeah, I'm drawn up 870 00:47:37,320 --> 00:47:39,600 Speaker 1: complete blank on that one. I think it used to 871 00:47:39,680 --> 00:47:43,719 Speaker 1: be called Stalinabad, but now it's a ducham Bay Okay. 872 00:47:44,080 --> 00:47:47,799 Speaker 1: But yeah, anyway, so participants fifty two college undergraduates, um 873 00:47:48,080 --> 00:47:50,560 Speaker 1: and they were first shown a list of all the countries. 874 00:47:50,600 --> 00:47:52,200 Speaker 1: So here all the countries you're gonna have to know 875 00:47:52,239 --> 00:47:55,000 Speaker 1: the capitals of go down and rate them on the 876 00:47:55,040 --> 00:47:58,080 Speaker 1: seventh same seven point scale. Rate your confidence in how 877 00:47:58,120 --> 00:48:00,280 Speaker 1: well do you know the capital of all these countries? Reason? 878 00:48:00,760 --> 00:48:03,319 Speaker 1: And then they're asked to actually list the names of 879 00:48:03,360 --> 00:48:05,719 Speaker 1: capitals for half the countries and then asked to re 880 00:48:05,920 --> 00:48:08,920 Speaker 1: rate their knowledge. So essentially it's the same thing, except 881 00:48:09,000 --> 00:48:11,640 Speaker 1: instead of giving an explanation of how something works, you're 882 00:48:11,680 --> 00:48:14,640 Speaker 1: just listing the capital. Then they're told the real names 883 00:48:14,680 --> 00:48:16,880 Speaker 1: of the capitals and asked to re rate their knowledge. 884 00:48:16,920 --> 00:48:19,600 Speaker 1: So what are the results here, Well compared to a 885 00:48:19,680 --> 00:48:23,080 Speaker 1: combined group from studies one through four, and the authors 886 00:48:23,120 --> 00:48:26,479 Speaker 1: justify combining them into one group in their discussion. Uh, 887 00:48:26,560 --> 00:48:28,799 Speaker 1: the students who were tested on the facts showed a 888 00:48:28,920 --> 00:48:32,640 Speaker 1: different pattern in the same direction, but with less magnitude. 889 00:48:32,719 --> 00:48:36,959 Speaker 1: So confidence dropped off significantly between the first and second rating, 890 00:48:37,040 --> 00:48:40,359 Speaker 1: So after people had to answer the questions, they were 891 00:48:40,440 --> 00:48:44,160 Speaker 1: less confident, But UH, it stayed almost the same for 892 00:48:44,200 --> 00:48:46,360 Speaker 1: the final rating. And though the drop off from T 893 00:48:46,480 --> 00:48:50,720 Speaker 1: one to T two is statistically significant, UH, it's significantly 894 00:48:50,840 --> 00:48:54,680 Speaker 1: smaller than the drop off in explanation. So essentially, with facts, 895 00:48:55,440 --> 00:48:58,040 Speaker 1: we're seeing a pattern that's going in the same direction, 896 00:48:58,080 --> 00:49:01,120 Speaker 1: but it's just much smaller. The line graph shows a 897 00:49:01,160 --> 00:49:03,960 Speaker 1: slight decrease, but it's closer to being flat than the 898 00:49:04,000 --> 00:49:07,600 Speaker 1: graph line for the device explanations. So we've got some 899 00:49:07,840 --> 00:49:10,920 Speaker 1: overconfidence with capitals, and I think we've all got to 900 00:49:10,960 --> 00:49:13,799 Speaker 1: be that way given our schooling. Right, How how many 901 00:49:13,800 --> 00:49:16,120 Speaker 1: capitals did you have to learn in school? Why why 902 00:49:16,120 --> 00:49:19,360 Speaker 1: do they do capitals? You know? I remember I remember 903 00:49:19,400 --> 00:49:22,000 Speaker 1: exercises where we had to of course remember the states 904 00:49:22,000 --> 00:49:24,560 Speaker 1: and their capitals, but I also remember just a lot 905 00:49:24,600 --> 00:49:30,279 Speaker 1: of geography quizzes that had no substance to them, like 906 00:49:30,320 --> 00:49:33,960 Speaker 1: you'd have to you'd have to memorize all the nations 907 00:49:33,960 --> 00:49:37,080 Speaker 1: of Africa, and yes, some of the some of the 908 00:49:37,160 --> 00:49:39,719 Speaker 1: nations you were learning about, you know, every everyone's learning 909 00:49:39,760 --> 00:49:43,000 Speaker 1: about Egypt, everyone's learning something about South Africa. But then 910 00:49:43,000 --> 00:49:46,839 Speaker 1: there are all these other African states. You're not even 911 00:49:46,960 --> 00:49:49,919 Speaker 1: asked to know anything about them, just except for their name, 912 00:49:50,000 --> 00:49:53,600 Speaker 1: and so they're useless facts because there's no substance behind it. Yeah, 913 00:49:53,600 --> 00:49:55,680 Speaker 1: I feel like it would be much more useful if 914 00:49:55,800 --> 00:49:58,520 Speaker 1: if you're doing that instead of learning capitals, to learn 915 00:49:58,680 --> 00:50:03,360 Speaker 1: like primary language is main ethnic groups and main exports, 916 00:50:04,880 --> 00:50:06,600 Speaker 1: but I guess there's only so much time in a day. 917 00:50:06,920 --> 00:50:09,040 Speaker 1: Then again, I guess I won't complain when I I 918 00:50:09,080 --> 00:50:11,080 Speaker 1: don't know. It's good being able to produce a capital. 919 00:50:11,160 --> 00:50:14,399 Speaker 1: You still you still get that third grade rush. Oh yeah, 920 00:50:14,440 --> 00:50:20,000 Speaker 1: I did it, Brazilia. Okay, So next next test study 921 00:50:20,080 --> 00:50:23,120 Speaker 1: number eight. Uh, let's look let's look at a different 922 00:50:23,160 --> 00:50:25,840 Speaker 1: domain of knowledge. So we've looked at we've looked at 923 00:50:25,920 --> 00:50:29,400 Speaker 1: explanations for causal phenomenon with devices, and we've looked at facts. 924 00:50:29,560 --> 00:50:32,920 Speaker 1: What about procedures? So this, uh, this type of knowledge 925 00:50:32,960 --> 00:50:35,719 Speaker 1: in a way is very similar to explaining how devices work. 926 00:50:36,200 --> 00:50:40,440 Speaker 1: It involves explaining how you do something. How do you 927 00:50:40,520 --> 00:50:43,480 Speaker 1: tie a tie? How do you bake chocolate chip cookies 928 00:50:43,520 --> 00:50:46,200 Speaker 1: from scratch? How do you drive from New York to 929 00:50:46,280 --> 00:50:49,839 Speaker 1: New Haven? This makes me think of all the wonderful 930 00:50:49,960 --> 00:50:54,040 Speaker 1: wiki how um explanations out there, often with pictures that 931 00:50:54,200 --> 00:50:57,799 Speaker 1: explain and yet don't explain the thing you looked that. 932 00:50:57,920 --> 00:51:00,480 Speaker 1: Those things are my favorite looking up obscure e how 933 00:51:00,640 --> 00:51:02,600 Speaker 1: articles used to be one of my favorite games on 934 00:51:02,600 --> 00:51:04,960 Speaker 1: the Internet, the best one I ever came across. I 935 00:51:04,960 --> 00:51:07,759 Speaker 1: swear this is true. It was an eHow article because 936 00:51:08,000 --> 00:51:10,320 Speaker 1: I think it doesn't exist anymore. But it was called 937 00:51:10,480 --> 00:51:15,880 Speaker 1: how to pray for Money? Oh really, yeah, for money? 938 00:51:16,200 --> 00:51:18,600 Speaker 1: So it's so it would be like it had instruction 939 00:51:18,760 --> 00:51:22,920 Speaker 1: meal pray asked for money? Well, I think it was. 940 00:51:22,960 --> 00:51:25,560 Speaker 1: Actually it was actually kind of complex because it was 941 00:51:25,600 --> 00:51:28,719 Speaker 1: like recognized that money might not be the most important thing. 942 00:51:29,320 --> 00:51:32,640 Speaker 1: Um that was like step number five. I guess, okay, well, 943 00:51:32,640 --> 00:51:33,879 Speaker 1: these are the kind of things that I guess occur 944 00:51:34,000 --> 00:51:38,359 Speaker 1: when when writing assignments are going out, Um, you know 945 00:51:38,440 --> 00:51:43,280 Speaker 1: lickety split based purely on you know, search engine terms, 946 00:51:43,360 --> 00:51:46,800 Speaker 1: right right, Okay, So this part, so they're going to 947 00:51:46,880 --> 00:51:48,839 Speaker 1: run the same test they've done before, all the same 948 00:51:48,920 --> 00:51:52,359 Speaker 1: rating steps, everything's the same, except instead of explanations, it's 949 00:51:52,360 --> 00:51:54,239 Speaker 1: going to be how do you do this? Here's a 950 00:51:54,280 --> 00:51:57,480 Speaker 1: procedure right down the steps and and what order they 951 00:51:57,480 --> 00:52:01,919 Speaker 1: come in and how they work together. Results are very interesting. Uh, 952 00:52:01,960 --> 00:52:05,680 Speaker 1: this pattern was completely unlike anything we've seen before. So 953 00:52:05,840 --> 00:52:08,640 Speaker 1: instead of the ratings dropping off between T one and 954 00:52:08,680 --> 00:52:11,279 Speaker 1: T two, your first guests and then your adjustment after 955 00:52:11,320 --> 00:52:13,719 Speaker 1: you have to write something, write the answer out, the 956 00:52:13,840 --> 00:52:18,080 Speaker 1: ratings actually showed a slight but statistically non significant increase 957 00:52:18,239 --> 00:52:21,000 Speaker 1: from one to two and so after you have to 958 00:52:21,040 --> 00:52:23,720 Speaker 1: give an account of how to bake chocolate chip cookies, 959 00:52:24,040 --> 00:52:27,480 Speaker 1: you're actually more confident in your knowledge than you were 960 00:52:27,600 --> 00:52:31,919 Speaker 1: before you wrote down the steps. Um, and I thought 961 00:52:31,960 --> 00:52:34,200 Speaker 1: that was interesting, but it also sort of matches. I 962 00:52:34,200 --> 00:52:36,600 Speaker 1: can see how that would be true. Like you think 963 00:52:36,640 --> 00:52:39,560 Speaker 1: you probably know how to do something, then you write 964 00:52:39,600 --> 00:52:42,440 Speaker 1: down the steps to do it, and looking at them 965 00:52:42,480 --> 00:52:44,439 Speaker 1: there you're like, oh, yeah, I was right, I knew, 966 00:52:44,480 --> 00:52:47,200 Speaker 1: And so you're a little more confident. Yeah, especially if 967 00:52:47,200 --> 00:52:50,279 Speaker 1: it's something you've chocolate chip cookies as an example, Like 968 00:52:50,360 --> 00:52:52,920 Speaker 1: so often you're going off a recipe, or at least 969 00:52:53,200 --> 00:52:56,719 Speaker 1: I I'm not being a real baker. So I'm gonna 970 00:52:56,760 --> 00:52:59,440 Speaker 1: look up the recipe and then I'm gonna follow the 971 00:52:59,440 --> 00:53:03,200 Speaker 1: recipe with no intent of memorizing it. And then afterwards 972 00:53:03,200 --> 00:53:05,239 Speaker 1: I may be able to recall those steps and list 973 00:53:05,280 --> 00:53:09,279 Speaker 1: them out and say, all right, that looks accurate. But 974 00:53:09,320 --> 00:53:12,640 Speaker 1: then if I actually take that list and compared to 975 00:53:12,680 --> 00:53:14,960 Speaker 1: the recipe, I'm bound to have left out some like 976 00:53:15,120 --> 00:53:19,440 Speaker 1: key steps well like baking them, like something I don't know, 977 00:53:20,120 --> 00:53:24,040 Speaker 1: like licking the raw egg laden spoon. All on that 978 00:53:24,120 --> 00:53:26,840 Speaker 1: part I got down. Oh yeah, So so the authors 979 00:53:26,880 --> 00:53:30,120 Speaker 1: also report again this is some non quantified information, but 980 00:53:30,239 --> 00:53:34,840 Speaker 1: just some post test debriefing. They report that the students 981 00:53:34,920 --> 00:53:38,120 Speaker 1: didn't show any of the now characteristic surprise and all 982 00:53:38,160 --> 00:53:41,080 Speaker 1: the other stuff, you know. After the test they'd be like, Wow, 983 00:53:41,120 --> 00:53:43,799 Speaker 1: I can't believe how much I didn't know. Instead, they 984 00:53:43,800 --> 00:53:46,640 Speaker 1: seemed perfectly aware of how much or how little they 985 00:53:46,719 --> 00:53:49,680 Speaker 1: knew about how to do things. On the other hand, 986 00:53:49,800 --> 00:53:51,759 Speaker 1: I guess, yeah, I would say, this isn't really all 987 00:53:51,800 --> 00:53:55,319 Speaker 1: that surprising. Our mental process of remembering how to do 988 00:53:55,400 --> 00:53:58,799 Speaker 1: something is very different from our mental process of remembering 989 00:53:59,080 --> 00:54:02,399 Speaker 1: how something x sternal to the self works because when 990 00:54:02,400 --> 00:54:05,360 Speaker 1: you're remembering how to do something, it's usually a first 991 00:54:05,400 --> 00:54:10,719 Speaker 1: person memory. You picture yourself being the thing doing the thing. Yeah, 992 00:54:10,800 --> 00:54:14,799 Speaker 1: often it's like an unlanguaged experience. I've had this this 993 00:54:14,960 --> 00:54:19,080 Speaker 1: experience with Legos recently because because I'm building Legos with 994 00:54:19,120 --> 00:54:21,960 Speaker 1: my son. Haven't built built anything out of Legos since 995 00:54:22,000 --> 00:54:25,200 Speaker 1: I was a kid, and I'm realizing that I'm I'm 996 00:54:25,200 --> 00:54:27,840 Speaker 1: sure there are industry terms for all the different blocks 997 00:54:27,840 --> 00:54:30,960 Speaker 1: and the sizes of blocks, but I do not know 998 00:54:31,000 --> 00:54:35,160 Speaker 1: what those terms are, so I'm and the the of course, 999 00:54:35,160 --> 00:54:39,120 Speaker 1: the instructions are wordless, so I don't have any length 1000 00:54:39,239 --> 00:54:42,000 Speaker 1: or I have very little language to describe the steps 1001 00:54:42,000 --> 00:54:44,560 Speaker 1: that are taking place, but I can, you know, I 1002 00:54:44,600 --> 00:54:46,960 Speaker 1: can picture myself doing it. Yeah, And there there are 1003 00:54:46,960 --> 00:54:49,600 Speaker 1: also plenty of things where there is like something you 1004 00:54:49,640 --> 00:54:51,560 Speaker 1: know how to do through muscle memory that would be 1005 00:54:51,560 --> 00:54:54,319 Speaker 1: difficult to put into words, like could you explain the 1006 00:54:54,400 --> 00:54:57,080 Speaker 1: steps of how to ride a bicycle? Right? Or a 1007 00:54:57,080 --> 00:55:00,680 Speaker 1: big one is is tying a long neck? Hi? Yeah, 1008 00:55:00,840 --> 00:55:02,840 Speaker 1: but like I can I can tie one on myself, 1009 00:55:02,880 --> 00:55:05,399 Speaker 1: I cannot tie one on another person all the time 1010 00:55:05,400 --> 00:55:07,200 Speaker 1: with people where if they're going to tie a tie 1011 00:55:07,239 --> 00:55:10,200 Speaker 1: for someone, they have to wear it themselves. Uh. Well, 1012 00:55:10,239 --> 00:55:13,160 Speaker 1: at least that is interesting and I think that's true 1013 00:55:13,160 --> 00:55:15,600 Speaker 1: in my experience. But it does not seem so much 1014 00:55:15,640 --> 00:55:17,799 Speaker 1: born out in these results. It seems like people are 1015 00:55:18,280 --> 00:55:21,239 Speaker 1: or maybe actually it's not that people were perfect at 1016 00:55:21,280 --> 00:55:24,000 Speaker 1: being able to explain how to do procedures. They were 1017 00:55:24,040 --> 00:55:27,000 Speaker 1: just very accurate in predicting how well they would be 1018 00:55:27,040 --> 00:55:30,840 Speaker 1: able to explain them, because you are you. It's based 1019 00:55:30,880 --> 00:55:33,680 Speaker 1: on an actual memory of doing the thing or trying 1020 00:55:33,719 --> 00:55:37,279 Speaker 1: to do the thing. Yeah. Um so yeah, So next 1021 00:55:37,280 --> 00:55:39,200 Speaker 1: next study, what about a different type of knowledge. We've 1022 00:55:39,239 --> 00:55:42,440 Speaker 1: looked at facts, We've looked at procedures. How about narratives. 1023 00:55:43,320 --> 00:55:46,359 Speaker 1: One of my favorite things to recall is what happened 1024 00:55:46,480 --> 00:55:49,080 Speaker 1: in that part of Big Trouble and Little China after 1025 00:55:49,800 --> 00:55:54,759 Speaker 1: the monster for first Pokes's head. I don't anyway, So yeah, 1026 00:55:54,840 --> 00:55:57,400 Speaker 1: recalling a narrative if if the plot of a narrative 1027 00:55:57,520 --> 00:56:00,759 Speaker 1: is basically realist in terms of genre, you're not talking 1028 00:56:00,760 --> 00:56:04,680 Speaker 1: about el topo or something. There is a causal logic 1029 00:56:04,800 --> 00:56:07,239 Speaker 1: to the events that take place in it, right, in 1030 00:56:07,239 --> 00:56:09,440 Speaker 1: the sense that a narrative, like the plot of a 1031 00:56:09,480 --> 00:56:13,359 Speaker 1: book or a movie, is a kind of machine. It's 1032 00:56:13,360 --> 00:56:17,080 Speaker 1: a structure built out of causal relationships that can be labeled, explained, 1033 00:56:17,080 --> 00:56:20,760 Speaker 1: and summarized. So so let's let's look at the machine 1034 00:56:20,840 --> 00:56:24,399 Speaker 1: of movie plots. Thirty nine students were given a list 1035 00:56:24,400 --> 00:56:28,040 Speaker 1: of twenty popular movies UH, selected to be things college 1036 00:56:28,040 --> 00:56:30,800 Speaker 1: students were likely to have seen. I think Forest Gump 1037 00:56:30,880 --> 00:56:33,640 Speaker 1: was one of them. UH. And they're asked which of 1038 00:56:33,680 --> 00:56:36,160 Speaker 1: the movies they had seen, and then asked to rate 1039 00:56:36,239 --> 00:56:39,520 Speaker 1: their understanding of the plots of five of the movies 1040 00:56:39,560 --> 00:56:42,920 Speaker 1: they'd seen, and then, after their t one first ratings, 1041 00:56:43,239 --> 00:56:46,000 Speaker 1: they had to describe each of those five plots and 1042 00:56:46,000 --> 00:56:49,040 Speaker 1: then rewrite their original understanding, So the same procedure we've 1043 00:56:49,080 --> 00:56:53,839 Speaker 1: seen the whole time, except instead of explaining devices or procedures, 1044 00:56:53,920 --> 00:56:58,000 Speaker 1: it's plots of movies. And then finally they read reviews 1045 00:56:58,040 --> 00:57:01,440 Speaker 1: from a professional movie website, not review summaries of plots 1046 00:57:01,480 --> 00:57:04,880 Speaker 1: from a professional movie review website, and then compared those 1047 00:57:04,920 --> 00:57:07,520 Speaker 1: to what they had and rated again, and the results 1048 00:57:07,520 --> 00:57:09,600 Speaker 1: were that the pattern was closer to the one for 1049 00:57:09,719 --> 00:57:12,480 Speaker 1: procedures than the one for devices. I thought this was 1050 00:57:12,560 --> 00:57:15,400 Speaker 1: interesting because in a narrative, you were recalling a narrative 1051 00:57:15,440 --> 00:57:18,320 Speaker 1: that's not something you had to do with your body. 1052 00:57:18,400 --> 00:57:21,400 Speaker 1: It's so that it's taking that element out, but it's 1053 00:57:21,440 --> 00:57:25,040 Speaker 1: closer to the pattern for procedures. There's no significant drop 1054 00:57:25,040 --> 00:57:27,400 Speaker 1: off from T one to T two. People were pretty 1055 00:57:27,440 --> 00:57:31,240 Speaker 1: accurate at predicting how well they knew narratives. That's interesting 1056 00:57:31,280 --> 00:57:34,560 Speaker 1: because just thinking back on movies I've seen, like you mentioned, 1057 00:57:34,600 --> 00:57:37,040 Speaker 1: Big Trouble a Little China, and I instantly started trying 1058 00:57:37,040 --> 00:57:39,840 Speaker 1: to in my mind sort of piece out of timeline 1059 00:57:39,840 --> 00:57:41,800 Speaker 1: of that movie. And it's a movie I've seen a lot, 1060 00:57:42,520 --> 00:57:44,240 Speaker 1: and and and I have a lot of Love for 1061 00:57:44,520 --> 00:57:48,040 Speaker 1: But there I think there's some definite holes in my 1062 00:57:48,120 --> 00:57:51,080 Speaker 1: attempt to restructure. You know, at what point they go 1063 00:57:51,240 --> 00:57:54,880 Speaker 1: to the to the import export business there, and then 1064 00:57:54,920 --> 00:57:56,560 Speaker 1: they come out, and then they go back in And 1065 00:57:56,600 --> 00:57:59,920 Speaker 1: when did this encounter fall in line? You know, they 1066 00:58:00,120 --> 00:58:02,760 Speaker 1: ran a different study to test different devices just to 1067 00:58:02,760 --> 00:58:05,120 Speaker 1: make sure the device list they had wasn't peculiar. I 1068 00:58:05,160 --> 00:58:07,840 Speaker 1: wonder if they should have run another test with different movies, 1069 00:58:07,880 --> 00:58:11,720 Speaker 1: Like what if the movies they had were unusually perspicuous 1070 00:58:11,760 --> 00:58:14,800 Speaker 1: and clear in terms of plot relationship? Yeah, like say 1071 00:58:14,800 --> 00:58:18,720 Speaker 1: a romantic comedy, say like the movie Amala. Despite the 1072 00:58:18,760 --> 00:58:20,840 Speaker 1: fact that I've seen Big Trouble A Little China far 1073 00:58:20,880 --> 00:58:23,800 Speaker 1: more than I've seen Amlay, I'm far more confident in 1074 00:58:23,840 --> 00:58:28,040 Speaker 1: my ability to to just rattle off the plot points 1075 00:58:28,360 --> 00:58:31,960 Speaker 1: and the basic movement of the narrative for Amlay because 1076 00:58:32,000 --> 00:58:34,520 Speaker 1: it one thing follows from another, Right, it follows a 1077 00:58:34,600 --> 00:58:38,520 Speaker 1: basic Uh, there's a basic blueprint for that sort of film. 1078 00:58:38,760 --> 00:58:41,880 Speaker 1: And I'm not saying Big Trump A Little China doesn't 1079 00:58:41,920 --> 00:58:44,520 Speaker 1: follow a very basic blueprint as well. Now, I think 1080 00:58:44,560 --> 00:58:47,280 Speaker 1: some kind of random things happened in it, you wouldn't 1081 00:58:47,280 --> 00:58:50,080 Speaker 1: necessarily infer from one scene, what's going to happen in 1082 00:58:50,120 --> 00:58:55,440 Speaker 1: the Uh? Yeah? Anyway, So next study, let's look at 1083 00:58:55,480 --> 00:58:58,160 Speaker 1: one more different type of knowledge. So we've looked at 1084 00:58:58,520 --> 00:59:02,600 Speaker 1: explanations for machines, facts about geography, procedures on how to 1085 00:59:02,640 --> 00:59:05,880 Speaker 1: do things, and narratives from movie plots. How about explaining 1086 00:59:05,960 --> 00:59:11,360 Speaker 1: natural phenomenon. Natural phenomena are complex causal systems. In a way, 1087 00:59:11,400 --> 00:59:14,360 Speaker 1: they're very much like devices or like machines, except they're 1088 00:59:14,480 --> 00:59:17,280 Speaker 1: you know, they're not made by humans. But in other senses, 1089 00:59:17,560 --> 00:59:20,760 Speaker 1: they are like that. They have causal relationships, different components 1090 00:59:20,800 --> 00:59:23,480 Speaker 1: that work together, and they in the end they make 1091 00:59:23,600 --> 00:59:28,240 Speaker 1: something happen. Uh. So participants were thirty one Yale undergrads 1092 00:59:28,280 --> 00:59:32,800 Speaker 1: and study was identical to the ones before, except instead 1093 00:59:32,840 --> 00:59:36,800 Speaker 1: of explaining how device works, you explain how tides occur, 1094 00:59:37,160 --> 00:59:41,240 Speaker 1: how why comets have tales, how earthquakes occur, how rainbows 1095 00:59:41,280 --> 00:59:44,360 Speaker 1: are formed, things like that. So, just like in the 1096 00:59:44,400 --> 00:59:48,240 Speaker 1: first four studies, they gave the initial confidence rating, you know, rainbows, Oh, 1097 00:59:48,280 --> 00:59:50,880 Speaker 1: I'm six on rainbows. Then they had to explain how 1098 00:59:50,920 --> 00:59:56,120 Speaker 1: they're formed, YadA YadA, and the results were it's a jackpot. 1099 00:59:56,200 --> 01:00:00,360 Speaker 1: The results distribution from the explanations of natural phenomen we're 1100 01:00:00,520 --> 01:00:05,280 Speaker 1: very similar to those four devices. They were closest to devices. So, 1101 01:00:05,280 --> 01:00:08,400 Speaker 1: whether it's tides or whether it's toilets, we think we 1102 01:00:08,560 --> 01:00:11,520 Speaker 1: understand how things work, but when we try to explain it, 1103 01:00:11,560 --> 01:00:14,560 Speaker 1: we realize there are lots of gaps in our understanding. 1104 01:00:15,120 --> 01:00:17,880 Speaker 1: So to summarize the results across all these studies we've 1105 01:00:17,920 --> 01:00:21,400 Speaker 1: we've seen that people are significantly overconfident in their understanding 1106 01:00:21,400 --> 01:00:25,520 Speaker 1: of how devices work and how natural phenomena occur, um 1107 01:00:25,560 --> 01:00:29,480 Speaker 1: that asking for an explanation makes this overconfidence apparent and 1108 01:00:29,560 --> 01:00:34,440 Speaker 1: reduces it. People are somewhat overconfident, but less so about 1109 01:00:34,440 --> 01:00:37,760 Speaker 1: their knowledge of facts like capital cities, and people are 1110 01:00:37,800 --> 01:00:41,280 Speaker 1: fairly accurate at judging their own knowledge of procedures, how 1111 01:00:41,280 --> 01:00:44,800 Speaker 1: to do stuff, and narratives what happened in a movie? Now, 1112 01:00:44,840 --> 01:00:47,040 Speaker 1: the big question is this is the thing we haven't 1113 01:00:47,080 --> 01:00:52,200 Speaker 1: gotten to yet. Why? Why? So? What's causing these differences 1114 01:00:52,200 --> 01:00:56,360 Speaker 1: in metacognition across different domains of knowledge? Why are we 1115 01:00:56,440 --> 01:01:00,200 Speaker 1: more overconfident about some types of knowledge than other is? 1116 01:01:00,200 --> 01:01:03,160 Speaker 1: What is it that would make us more confident about 1117 01:01:03,440 --> 01:01:06,560 Speaker 1: knowing how a toilet works than about knowing the plot 1118 01:01:06,560 --> 01:01:09,320 Speaker 1: of Forest Gump. Well, my my initial answer would be 1119 01:01:09,360 --> 01:01:13,760 Speaker 1: that we assume a certain simplicity of its design, Like 1120 01:01:14,280 --> 01:01:18,720 Speaker 1: without even really reminiscing too much on Forest Gump, I'm 1121 01:01:18,760 --> 01:01:22,720 Speaker 1: given the fact that it was a big blockbuster summer movie, 1122 01:01:23,480 --> 01:01:26,520 Speaker 1: I'm assuming it has a pretty simplistic structure. And as 1123 01:01:26,520 --> 01:01:30,320 Speaker 1: for the toilet, I mean it has such a it 1124 01:01:30,360 --> 01:01:33,120 Speaker 1: has such a a low standing in the household when 1125 01:01:33,160 --> 01:01:36,560 Speaker 1: it's functioning that you you just assume it couldn't be 1126 01:01:36,600 --> 01:01:39,600 Speaker 1: that complicated. Why would why would it take high technology 1127 01:01:39,880 --> 01:01:45,840 Speaker 1: to simply dispose of human waste? Yeah, I guess I 1128 01:01:45,840 --> 01:01:48,160 Speaker 1: can see that. I mean, so one of the answers 1129 01:01:48,200 --> 01:01:50,120 Speaker 1: that was given in the piloting they did for this, 1130 01:01:50,240 --> 01:01:51,600 Speaker 1: you know, when they were trying to think, what, what 1131 01:01:51,680 --> 01:01:54,960 Speaker 1: are some good hypotheses that could explain this this difference 1132 01:01:55,200 --> 01:02:00,360 Speaker 1: is complexity of the device, and so the hypothese sees 1133 01:02:00,400 --> 01:02:04,160 Speaker 1: that they ended up wanting to test where how about confusion? 1134 01:02:05,000 --> 01:02:09,640 Speaker 1: They called it confusion of environmental support with internal representation, 1135 01:02:10,000 --> 01:02:13,120 Speaker 1: And what that means is confusion of the fact that 1136 01:02:13,200 --> 01:02:15,800 Speaker 1: you can see the parts and how they work with 1137 01:02:16,000 --> 01:02:18,560 Speaker 1: the idea that you can represent the parts and how 1138 01:02:18,600 --> 01:02:22,120 Speaker 1: they work in your mind. Um. And so what this 1139 01:02:22,160 --> 01:02:27,840 Speaker 1: predicts is devices like bicycles and can openers and stuff 1140 01:02:27,880 --> 01:02:32,240 Speaker 1: that are very clear and perspicuous are the things that 1141 01:02:32,320 --> 01:02:37,080 Speaker 1: were most likely to overestimate our knowledge of the workings 1142 01:02:37,120 --> 01:02:39,360 Speaker 1: of because when we can just look at them and 1143 01:02:39,400 --> 01:02:42,080 Speaker 1: see all the parts, there's no there's no sensation that 1144 01:02:42,160 --> 01:02:46,120 Speaker 1: the workings are being hidden from us. But in your mind, 1145 01:02:46,920 --> 01:02:49,200 Speaker 1: try to draw a picture of a bicycle right now, 1146 01:02:50,680 --> 01:02:53,800 Speaker 1: I think actually, even if you've seen lots of bicycles, 1147 01:02:53,880 --> 01:02:57,280 Speaker 1: chances are you just mentally illustrated a bicycle that could 1148 01:02:57,360 --> 01:03:00,680 Speaker 1: not work. I don't know, I feel I feel a 1149 01:03:00,720 --> 01:03:04,160 Speaker 1: sense of perhaps false confidence here. Well maybe I mean, 1150 01:03:04,200 --> 01:03:07,120 Speaker 1: maybe I'm just because I assembled one on Christmas. Well, 1151 01:03:07,160 --> 01:03:09,400 Speaker 1: if you've if you've actually assembled a bicycle, then you 1152 01:03:09,440 --> 01:03:11,440 Speaker 1: might be in a different category. But I'm willing to 1153 01:03:11,480 --> 01:03:15,160 Speaker 1: accept that I'm completely foolhardy on this. The bicycle might 1154 01:03:15,200 --> 01:03:17,600 Speaker 1: be if you've actually worked on them with your hands, 1155 01:03:17,680 --> 01:03:20,000 Speaker 1: it might be more in the procedures category. But with 1156 01:03:20,040 --> 01:03:24,280 Speaker 1: an ikea tool kits so place. Well, I mean a 1157 01:03:24,320 --> 01:03:26,160 Speaker 1: lot of people we would try to draw try to 1158 01:03:26,200 --> 01:03:29,200 Speaker 1: draw a bicycle, and then they'd have like a you know, 1159 01:03:29,320 --> 01:03:33,520 Speaker 1: like a single bar running from the spokes of both wheels, 1160 01:03:33,800 --> 01:03:36,400 Speaker 1: and that would make it impossible to steer the bicycle 1161 01:03:36,560 --> 01:03:38,960 Speaker 1: and stuff like that, or they'd have, um, you know, 1162 01:03:39,040 --> 01:03:41,520 Speaker 1: the chain running to the front wheel and the back 1163 01:03:41,560 --> 01:03:44,840 Speaker 1: wheel or something like that. Well, it also makes me 1164 01:03:44,880 --> 01:03:46,880 Speaker 1: think that one of the scenarios here is that you 1165 01:03:46,960 --> 01:03:51,040 Speaker 1: feel that one should be able to understand a bicycle. Yes, 1166 01:03:51,280 --> 01:03:53,800 Speaker 1: I'm reminded that's the ease of representation. Yeah, Like I'm 1167 01:03:53,800 --> 01:03:56,000 Speaker 1: reminded of a bid ends in in the Art of 1168 01:03:56,040 --> 01:03:59,120 Speaker 1: Motorcycle Maintenance where uh, it's one of the parts where 1169 01:03:59,120 --> 01:04:02,920 Speaker 1: he's talking about motorcyle Coleman. It's that he says that 1170 01:04:02,960 --> 01:04:06,280 Speaker 1: the motorcycle is a perfect vehicle, a perfect perfect just 1171 01:04:06,320 --> 01:04:09,720 Speaker 1: a perfect system to have control of because it is 1172 01:04:09,760 --> 01:04:12,280 Speaker 1: a it is a complex system, but it's not so 1173 01:04:12,360 --> 01:04:16,240 Speaker 1: complex that a single individual can't master it and care 1174 01:04:16,280 --> 01:04:19,200 Speaker 1: for it. And whereas if you get into progressively more 1175 01:04:19,240 --> 01:04:23,600 Speaker 1: complicated mechanical systems or just systems in general, then it 1176 01:04:23,680 --> 01:04:26,560 Speaker 1: becomes increasingly difficult for one person to be able to 1177 01:04:26,560 --> 01:04:28,360 Speaker 1: have a grasp of it. Can you be the master 1178 01:04:28,520 --> 01:04:31,560 Speaker 1: of your prius? I don't know. I mean, I'm sure 1179 01:04:31,560 --> 01:04:34,080 Speaker 1: there are people that can. I I could not be 1180 01:04:34,120 --> 01:04:36,919 Speaker 1: the master of a motorcycle. I'm and I'm willing to 1181 01:04:36,920 --> 01:04:38,960 Speaker 1: to admit that I probably can't even be the master 1182 01:04:39,040 --> 01:04:42,520 Speaker 1: of my son's bicycle at this point. Well, I bet 1183 01:04:42,600 --> 01:04:44,959 Speaker 1: you're more master than me, now that you've actually used 1184 01:04:44,960 --> 01:04:48,200 Speaker 1: your hands on it. I I know now. I was primed, 1185 01:04:48,320 --> 01:04:50,480 Speaker 1: actually had to think about what's in a bicycle and 1186 01:04:50,520 --> 01:04:53,440 Speaker 1: look it up. But I'm quite confident that if I 1187 01:04:53,480 --> 01:04:55,880 Speaker 1: had just been asked to draw a bicycle and the 1188 01:04:55,920 --> 01:04:58,640 Speaker 1: different parts and what they do, I would not have 1189 01:04:58,720 --> 01:05:01,000 Speaker 1: been able to do it correctually if I hadn't thought 1190 01:05:01,000 --> 01:05:04,720 Speaker 1: about it ahead of time. Okay, another hypothesis. What about 1191 01:05:04,840 --> 01:05:09,200 Speaker 1: confusing higher and lower levels of an analysis. Basically, this 1192 01:05:09,280 --> 01:05:12,600 Speaker 1: just means, uh, if you've got an idea of the 1193 01:05:12,640 --> 01:05:16,560 Speaker 1: causal relationships at a high level, you know the big 1194 01:05:16,640 --> 01:05:20,000 Speaker 1: parts of a machine and basically what the machine does, 1195 01:05:20,480 --> 01:05:23,200 Speaker 1: you assume you have an understanding for the things at 1196 01:05:23,240 --> 01:05:25,240 Speaker 1: the lower level, even if you don't. So you think 1197 01:05:25,240 --> 01:05:28,520 Speaker 1: about car breakes. Car brakes slow the spinning of the 1198 01:05:28,560 --> 01:05:31,800 Speaker 1: wheels by applying friction. I understand how car brakes work, 1199 01:05:32,680 --> 01:05:35,600 Speaker 1: but there there are tons of things involved in the 1200 01:05:35,640 --> 01:05:38,600 Speaker 1: brakes that you've got some kind of hydraulics probably, or 1201 01:05:38,640 --> 01:05:40,720 Speaker 1: you know, fluid or some kind of How how is 1202 01:05:40,760 --> 01:05:44,320 Speaker 1: the pressure applied from the brake pedal to the brakes? 1203 01:05:44,360 --> 01:05:46,959 Speaker 1: What are all the different little gears and connections and parts. 1204 01:05:47,040 --> 01:05:50,080 Speaker 1: There's tons of stuff there that you're not even thinking about. 1205 01:05:50,160 --> 01:05:53,520 Speaker 1: But at the high level you basically know what it does, 1206 01:05:54,040 --> 01:05:56,720 Speaker 1: and so that makes you assume that you know how 1207 01:05:56,760 --> 01:06:00,280 Speaker 1: it works. It's a confusion of the what with the how. Yeah, 1208 01:06:00,360 --> 01:06:04,080 Speaker 1: Like examples that come to mind, like a chainsaw. You 1209 01:06:04,160 --> 01:06:06,560 Speaker 1: know how the cutting occurs, but do you really know 1210 01:06:06,600 --> 01:06:11,160 Speaker 1: how the all the intricacies of the saw itself hydraulic 1211 01:06:11,160 --> 01:06:13,320 Speaker 1: press like the one of the end of terminator. Oh yeah, 1212 01:06:13,640 --> 01:06:17,640 Speaker 1: you know, but it's pretty simple concept. The two pieces 1213 01:06:17,680 --> 01:06:21,040 Speaker 1: come together and flatten the terminator. But there's a lot 1214 01:06:21,080 --> 01:06:24,720 Speaker 1: more involved there with the hydraulic system and everything else. 1215 01:06:24,760 --> 01:06:27,240 Speaker 1: I like, I don't I don't even have a firm 1216 01:06:27,320 --> 01:06:31,640 Speaker 1: enough understanding of that of how how the intense pressure 1217 01:06:31,680 --> 01:06:35,880 Speaker 1: is applied via hydraulics. Yeah, yeah, um that that that's 1218 01:06:35,880 --> 01:06:38,600 Speaker 1: a good one. How about another explanation. What if it's 1219 01:06:39,080 --> 01:06:43,439 Speaker 1: the problem that explanations of of how things work, explanations 1220 01:06:44,000 --> 01:06:48,520 Speaker 1: unlike facts and stuff like that have indeterminate end states, 1221 01:06:48,720 --> 01:06:50,920 Speaker 1: and that if I ask you the capital of a country, 1222 01:06:51,160 --> 01:06:53,240 Speaker 1: how confident are you that you know the capital of 1223 01:06:53,280 --> 01:06:56,120 Speaker 1: a country? Whether or not you're right about the answer, 1224 01:06:56,160 --> 01:06:58,160 Speaker 1: you know what the answer will look like. It will 1225 01:06:58,200 --> 01:07:00,800 Speaker 1: be you know a short word, and you you think 1226 01:07:00,800 --> 01:07:04,959 Speaker 1: you probably know what that word is, um with an explanation. 1227 01:07:05,480 --> 01:07:08,080 Speaker 1: It's just it's very open ended. You know, you don't 1228 01:07:08,120 --> 01:07:11,360 Speaker 1: exactly know what the answer should look like, exactly how 1229 01:07:11,400 --> 01:07:14,360 Speaker 1: detailed is it supposed to be? UM? What you know? 1230 01:07:14,440 --> 01:07:16,320 Speaker 1: What are all the things that would be in it? 1231 01:07:16,320 --> 01:07:19,520 Speaker 1: It's it's it's more amorphous in terms of structure, even 1232 01:07:19,560 --> 01:07:24,040 Speaker 1: if you haven't colored inside the lines yet. And then 1233 01:07:24,040 --> 01:07:29,560 Speaker 1: the final hypothesis is what about rarity of production? We just, Robert, 1234 01:07:29,640 --> 01:07:31,800 Speaker 1: here's one where you and I might be different than 1235 01:07:31,840 --> 01:07:33,680 Speaker 1: a lot of people. Not to say we're better, We're 1236 01:07:33,720 --> 01:07:38,120 Speaker 1: probably worse. But most people don't have to give explanations 1237 01:07:38,160 --> 01:07:41,680 Speaker 1: of how things work very often. But we do often 1238 01:07:41,720 --> 01:07:46,120 Speaker 1: have to give recountings of facts, narratives and uh and 1239 01:07:46,200 --> 01:07:48,600 Speaker 1: about procedures. Right, these are things that are common for 1240 01:07:48,640 --> 01:07:51,120 Speaker 1: everybody to explain, but it's not all that common for 1241 01:07:51,120 --> 01:07:54,680 Speaker 1: people to explain how things work, and this may make 1242 01:07:54,800 --> 01:07:59,400 Speaker 1: us overestimate our performance at it. Yeah, I think that's reasonable. 1243 01:07:59,440 --> 01:08:01,600 Speaker 1: I mean we we are in kind of a privileged 1244 01:08:02,120 --> 01:08:05,840 Speaker 1: situation where we are constantly having to confront the things 1245 01:08:05,880 --> 01:08:09,120 Speaker 1: we don't know and and research them and form form 1246 01:08:09,120 --> 01:08:12,160 Speaker 1: and understanding of ourselves and then share that understanding with 1247 01:08:12,360 --> 01:08:15,720 Speaker 1: listeners or readers or viewers what have you. Yeah, we 1248 01:08:15,800 --> 01:08:19,800 Speaker 1: we we were practiced enough to know how little we know. Hopefully, No, 1249 01:08:20,000 --> 01:08:23,520 Speaker 1: we probably don't know how little we know. We foolishly 1250 01:08:23,600 --> 01:08:26,720 Speaker 1: think we know how little we know. But yeah, we 1251 01:08:26,800 --> 01:08:32,559 Speaker 1: have an illusion of depth of understanding our own ignorance. Uh, 1252 01:08:32,840 --> 01:08:34,959 Speaker 1: hopefully we have a lag up on the on the situation. 1253 01:08:35,080 --> 01:08:38,880 Speaker 1: That's the main hope. Maybe. Well we try, we try, 1254 01:08:39,320 --> 01:08:43,360 Speaker 1: probably fail, but we try, okay, well to examine how 1255 01:08:43,439 --> 01:08:45,840 Speaker 1: these figure. And there are a couple more studies there 1256 01:08:45,840 --> 01:08:48,639 Speaker 1: two more in this uh, in this research. So one 1257 01:08:48,680 --> 01:08:51,719 Speaker 1: of them, study number eleven is what if the difference 1258 01:08:52,000 --> 01:08:54,400 Speaker 1: in the different knowledge types is just that some knowledge 1259 01:08:54,400 --> 01:08:58,120 Speaker 1: types are more socially desirable than others. I thought about that. 1260 01:08:58,120 --> 01:09:00,800 Speaker 1: That's kind of interesting. What if we're more likely to 1261 01:09:00,920 --> 01:09:06,439 Speaker 1: overestimate our knowledge in say, uh devices, because it's much 1262 01:09:06,600 --> 01:09:10,559 Speaker 1: cooler to know how a toilet works, uh, and thus 1263 01:09:10,640 --> 01:09:13,720 Speaker 1: much more socially desirable, And thus we're sort of internally 1264 01:09:13,840 --> 01:09:19,360 Speaker 1: bluffing on the most socially important categories that could be possible. 1265 01:09:19,400 --> 01:09:22,760 Speaker 1: So twenty four Yale undergrads participated in this. They rate 1266 01:09:22,800 --> 01:09:26,120 Speaker 1: it on a seven point scale how embarrassed they would 1267 01:09:26,120 --> 01:09:28,400 Speaker 1: be if they have to admit if they had to 1268 01:09:28,439 --> 01:09:32,240 Speaker 1: admit they were ignorant about certain things. And the things 1269 01:09:32,720 --> 01:09:35,639 Speaker 1: on the list were pulled from a combined master list 1270 01:09:35,680 --> 01:09:39,080 Speaker 1: of the contents of previous experiments. So you're asked, like 1271 01:09:39,160 --> 01:09:41,680 Speaker 1: four each item, please rate how embarrassed do you think 1272 01:09:41,720 --> 01:09:44,320 Speaker 1: you would be if someone asked you to explain the 1273 01:09:44,360 --> 01:09:46,640 Speaker 1: item and it turned out that you did not have 1274 01:09:46,800 --> 01:09:50,040 Speaker 1: a good understanding or knowledge of that item. So apply 1275 01:09:50,160 --> 01:09:54,120 Speaker 1: what I just said to a flesh toilet, the plot 1276 01:09:54,120 --> 01:09:57,840 Speaker 1: of Forrest Gump, how to tie a bow tie, the 1277 01:09:57,960 --> 01:10:03,360 Speaker 1: capital of England, how rainbows are formed, And the results 1278 01:10:03,400 --> 01:10:06,599 Speaker 1: are that people were the least embarrassed to be ignorant 1279 01:10:06,600 --> 01:10:10,160 Speaker 1: about how devices worked. They were moderately embarrassed to be 1280 01:10:10,200 --> 01:10:13,720 Speaker 1: ignorant about facts, procedures, and natural phenomena, And then this 1281 01:10:13,840 --> 01:10:17,080 Speaker 1: was crazy. They were the most embarrassed to be ignorant 1282 01:10:17,120 --> 01:10:22,439 Speaker 1: about narratives. Interesting because it seems like you would have 1283 01:10:22,479 --> 01:10:25,600 Speaker 1: that that you have the most plausible deniability there I 1284 01:10:25,600 --> 01:10:27,400 Speaker 1: haven't seen it in a while, or I haven't seen it, 1285 01:10:27,600 --> 01:10:31,040 Speaker 1: or I didn't like it all that. I guess for 1286 01:10:31,120 --> 01:10:33,920 Speaker 1: college students, having seen certain movies carries a lot of 1287 01:10:33,960 --> 01:10:38,240 Speaker 1: social cache and don't know it's it's you know anyway. 1288 01:10:38,560 --> 01:10:41,639 Speaker 1: So this response pattern does not show a correlation between 1289 01:10:41,720 --> 01:10:45,360 Speaker 1: overconfidence and a knowledge domain and the social desirability of 1290 01:10:45,360 --> 01:10:47,920 Speaker 1: the knowledge domain. People are not bluffing themselves on the 1291 01:10:48,000 --> 01:10:51,320 Speaker 1: important stuff, or they would be convinced they know way 1292 01:10:51,360 --> 01:10:54,280 Speaker 1: more about what happens in movies than they actually do 1293 01:10:55,479 --> 01:10:59,960 Speaker 1: last study. In this research, so what exactly is correlated 1294 01:11:00,040 --> 01:11:04,000 Speaker 1: with overconfidence? Having established that people are the most overconfident 1295 01:11:04,040 --> 01:11:07,880 Speaker 1: about their understandings of devices and natural phenomenon, ruling out 1296 01:11:07,920 --> 01:11:10,320 Speaker 1: the idea that this is because those domains of knowledge 1297 01:11:10,320 --> 01:11:14,519 Speaker 1: are socially accepted or desirable. Uh, the experimenters, they were 1298 01:11:14,520 --> 01:11:16,840 Speaker 1: trying to measure what are the other factors that are 1299 01:11:16,880 --> 01:11:20,880 Speaker 1: correlated with overconfidence and understanding? So they returned to our 1300 01:11:20,880 --> 01:11:24,320 Speaker 1: old friends, the devices, the cylinder lock, the flush toilet 1301 01:11:24,520 --> 01:11:28,120 Speaker 1: the Grand list from studies one through four. Now, this 1302 01:11:28,200 --> 01:11:32,799 Speaker 1: tested a lot of different correlates, like familiarity with the item, 1303 01:11:32,920 --> 01:11:36,519 Speaker 1: the ratio of visible versus hidden parts, the number of 1304 01:11:36,640 --> 01:11:40,840 Speaker 1: mechanical versus electrical parts, the total number of parts, and 1305 01:11:40,960 --> 01:11:44,000 Speaker 1: the number of parts for which one knows the names. Uh. 1306 01:11:44,040 --> 01:11:46,760 Speaker 1: There was a lot of complicated analysis on this one 1307 01:11:46,800 --> 01:11:49,920 Speaker 1: as well, but in the end the researchers ruled that 1308 01:11:50,000 --> 01:11:54,479 Speaker 1: the visible or two hidden parts ratio explained the most 1309 01:11:54,600 --> 01:11:58,120 Speaker 1: of the variation in over confidence. In other words, a 1310 01:11:58,200 --> 01:12:02,679 Speaker 1: device with visible trans parent mechanisms, in their words, seems 1311 01:12:02,720 --> 01:12:05,280 Speaker 1: to be the most likely to trick you into thinking 1312 01:12:05,320 --> 01:12:08,120 Speaker 1: you understand how it works, when in fact you would 1313 01:12:08,120 --> 01:12:10,880 Speaker 1: discover yourself unable to explain it. So like we were 1314 01:12:10,880 --> 01:12:13,439 Speaker 1: talking about the can open or the bicycle, things that 1315 01:12:13,520 --> 01:12:16,400 Speaker 1: seem very clear and easy to to look at and 1316 01:12:16,479 --> 01:12:19,679 Speaker 1: think you understand are the most likely to make people 1317 01:12:19,800 --> 01:12:23,439 Speaker 1: over confident in their understanding um. They also believe that 1318 01:12:23,479 --> 01:12:27,200 Speaker 1: the results indicate that the quote levels of analysis confusion 1319 01:12:27,360 --> 01:12:31,439 Speaker 1: and the label mechanism confusion may contribute to feelings of knowing, 1320 01:12:31,479 --> 01:12:34,479 Speaker 1: so that means confusing the higher level with the lower 1321 01:12:34,560 --> 01:12:37,639 Speaker 1: level you know knowing confusing what it does with how 1322 01:12:37,680 --> 01:12:40,679 Speaker 1: it does it at the granular level, and then also 1323 01:12:41,320 --> 01:12:44,200 Speaker 1: knowing the names for parts of a thing might make 1324 01:12:44,240 --> 01:12:47,960 Speaker 1: you overconfident in thinking that you know how the thing works. 1325 01:12:48,439 --> 01:12:51,160 Speaker 1: A little knowledge is a dangerous thing, it certainly is. 1326 01:12:51,240 --> 01:12:54,120 Speaker 1: And I can definitely think of this in like biology. 1327 01:12:54,200 --> 01:12:56,920 Speaker 1: Remember in high school when you learn the names of 1328 01:12:56,920 --> 01:12:58,800 Speaker 1: all the parts of the cell. Maybe not high school, 1329 01:12:58,800 --> 01:13:00,720 Speaker 1: I don't know what, but some s class you have 1330 01:13:00,720 --> 01:13:02,720 Speaker 1: in school. If you learn all the parts of the 1331 01:13:02,760 --> 01:13:06,599 Speaker 1: cell in human maybe there's an art project involved. And 1332 01:13:06,640 --> 01:13:08,800 Speaker 1: then you think you know how the cell works. I 1333 01:13:08,800 --> 01:13:11,960 Speaker 1: don't know. You don't know how the cell works? Are 1334 01:13:12,000 --> 01:13:13,800 Speaker 1: you a fool? Yeah? I mean the same can be 1335 01:13:13,800 --> 01:13:15,640 Speaker 1: said of the human body, right, I mean you you 1336 01:13:15,760 --> 01:13:18,960 Speaker 1: you learn all these different anatomical parts, the different organs. 1337 01:13:19,520 --> 01:13:23,360 Speaker 1: But to say you know what a liver is is 1338 01:13:23,400 --> 01:13:25,160 Speaker 1: the different thing than saying you know how the liver 1339 01:13:25,280 --> 01:13:29,400 Speaker 1: works exactly right. So they say in their final discussion, Uh, 1340 01:13:29,600 --> 01:13:32,200 Speaker 1: they're they're thinking about, you know, the explanations for what 1341 01:13:32,360 --> 01:13:35,240 Speaker 1: causes the illusion of explanatory depth, and and they're sort 1342 01:13:35,280 --> 01:13:38,280 Speaker 1: of focusing a lot on this idea of the the 1343 01:13:38,400 --> 01:13:41,120 Speaker 1: environmental support being able to look at an object and 1344 01:13:41,160 --> 01:13:44,880 Speaker 1: see the parts and confusing that for an understanding. And 1345 01:13:45,000 --> 01:13:47,439 Speaker 1: I thought this was a good, good passage, They say, quote, 1346 01:13:47,680 --> 01:13:50,080 Speaker 1: it would be easy to assume that you can derive 1347 01:13:50,200 --> 01:13:53,959 Speaker 1: the same kind of representational support from the mental movie 1348 01:13:54,240 --> 01:13:57,200 Speaker 1: that you could from observing a real phenomenon. So that's 1349 01:13:57,240 --> 01:13:59,040 Speaker 1: like when you play a movie of a thing in 1350 01:13:59,080 --> 01:14:02,880 Speaker 1: your head. Uh. They that you could confuse that with 1351 01:14:03,439 --> 01:14:06,599 Speaker 1: the same level of information that you get from looking 1352 01:14:06,640 --> 01:14:09,600 Speaker 1: at the object working the right quote. Of course, the 1353 01:14:09,640 --> 01:14:12,519 Speaker 1: mental movie is more like Hollywood than it is like 1354 01:14:12,600 --> 01:14:16,800 Speaker 1: real life. It fails to respect reality constraints. When we 1355 01:14:16,880 --> 01:14:20,599 Speaker 1: try to lean on the seductively glossy surface, we find 1356 01:14:20,680 --> 01:14:24,080 Speaker 1: that the facades of our mental films are hollow cardboard. 1357 01:14:24,560 --> 01:14:28,080 Speaker 1: That discovery, the revelation of the shallowness of our mental 1358 01:14:28,200 --> 01:14:34,160 Speaker 1: representations for perceptually salient processes, maybe what causes the surprise 1359 01:14:34,240 --> 01:14:38,439 Speaker 1: and our participants. And that seems very plausible to me. 1360 01:14:38,520 --> 01:14:41,000 Speaker 1: Like you, you try to put together a mental movie 1361 01:14:41,000 --> 01:14:43,479 Speaker 1: of how they can opener works, and you're playing the 1362 01:14:43,520 --> 01:14:46,639 Speaker 1: cartoon in your mind, and because you can do that, 1363 01:14:47,120 --> 01:14:49,160 Speaker 1: you're like, oh, okay, I know how it works. Like 1364 01:14:49,240 --> 01:14:52,080 Speaker 1: I just made the parts work in my mind, so 1365 01:14:52,120 --> 01:14:54,080 Speaker 1: I know what all the parts are and what they do. 1366 01:14:54,640 --> 01:14:57,679 Speaker 1: And it's something. Uh, it's something about this trick where 1367 01:14:57,720 --> 01:15:01,439 Speaker 1: our imagination is less vivid than we think it is. 1368 01:15:02,120 --> 01:15:04,000 Speaker 1: Like I'm picturing it in my head, I can see 1369 01:15:04,000 --> 01:15:06,280 Speaker 1: it in my head, but then you try to explain 1370 01:15:06,320 --> 01:15:08,960 Speaker 1: it and you realize there are blind spots in your 1371 01:15:08,960 --> 01:15:12,760 Speaker 1: own imagination that you do not realize are there. Yeah, 1372 01:15:12,760 --> 01:15:16,360 Speaker 1: our minds kind of tricks, isn't thinking We've filled in 1373 01:15:16,400 --> 01:15:19,759 Speaker 1: all those little gaps. Um, Like I was having similar 1374 01:15:19,760 --> 01:15:23,400 Speaker 1: situation just with Big Trouble a Little China. I feel 1375 01:15:23,439 --> 01:15:26,559 Speaker 1: like my memory of it, when I summon it is 1376 01:15:26,600 --> 01:15:29,879 Speaker 1: more of it, just a flash of images and uh 1377 01:15:29,960 --> 01:15:33,719 Speaker 1: and and probably leaning heavy on just the film score, 1378 01:15:34,400 --> 01:15:37,680 Speaker 1: just all these different ideas, scenes and sounds from the 1379 01:15:37,720 --> 01:15:41,760 Speaker 1: film that I have encapsulated as my memory of the film. 1380 01:15:41,800 --> 01:15:43,519 Speaker 1: I think that's true for a lot of movies with 1381 01:15:43,560 --> 01:15:46,439 Speaker 1: me yea. And yet for some reason, people are generally 1382 01:15:46,479 --> 01:15:48,960 Speaker 1: better at predicting how well they'll be able to describe 1383 01:15:48,960 --> 01:15:51,680 Speaker 1: a narrative, so that that's one of the outliers for me. 1384 01:15:51,720 --> 01:15:54,920 Speaker 1: I'm wondering what that really means. Well, I mean you 1385 01:15:54,960 --> 01:15:58,000 Speaker 1: could could certainly take that apart and say, well, it's 1386 01:15:58,120 --> 01:15:59,360 Speaker 1: a lot of it has to do with the way 1387 01:15:59,400 --> 01:16:01,920 Speaker 1: that we make sense of our lives being narratives when 1388 01:16:01,920 --> 01:16:06,120 Speaker 1: they're really not looking for the story shape in everything 1389 01:16:06,240 --> 01:16:09,920 Speaker 1: from you know, your personal life to current events. It's 1390 01:16:10,960 --> 01:16:13,960 Speaker 1: we're continually bashing our head up against the reality that 1391 01:16:14,040 --> 01:16:17,680 Speaker 1: things do not play out with the economy or the 1392 01:16:17,720 --> 01:16:22,599 Speaker 1: form of a traditional narrative. Well, unless you have anything else, Robert, 1393 01:16:22,600 --> 01:16:24,519 Speaker 1: I think we should wrap up this first part, and 1394 01:16:24,560 --> 01:16:27,080 Speaker 1: then when we return next time, we can look at 1395 01:16:27,080 --> 01:16:29,880 Speaker 1: some of the applications of the fact that we have 1396 01:16:30,000 --> 01:16:34,120 Speaker 1: an illusion of understanding, an illusion of explanatory depth about 1397 01:16:34,120 --> 01:16:36,479 Speaker 1: the world around us. How can this knowledge be brought 1398 01:16:36,520 --> 01:16:39,960 Speaker 1: to bear in various domains of life. Yeah, we'll consider 1399 01:16:40,000 --> 01:16:43,839 Speaker 1: the children, will consider politics. Um, we might even consider 1400 01:16:43,920 --> 01:16:46,439 Speaker 1: zombies a little bit. We'll see. Uh So. One of 1401 01:16:46,439 --> 01:16:48,320 Speaker 1: the one thing though, I do want to to keep 1402 01:16:48,320 --> 01:16:50,800 Speaker 1: in mind about this is that you shouldn't just take 1403 01:16:50,800 --> 01:16:54,120 Speaker 1: this as pessimistic, right, uh Like, oh, we we don't 1404 01:16:54,120 --> 01:16:56,400 Speaker 1: actually understand things as well as we do. How horrible 1405 01:16:57,280 --> 01:16:59,680 Speaker 1: you could be pessimistic. You could say, why do we 1406 01:16:59,760 --> 01:17:02,000 Speaker 1: know so much less about? How things work, then we 1407 01:17:02,040 --> 01:17:04,439 Speaker 1: feel like we do. Or you could look at this 1408 01:17:04,520 --> 01:17:07,599 Speaker 1: in a very optimistic way, and then and instead ask 1409 01:17:07,680 --> 01:17:11,639 Speaker 1: the question, how are we so good at surviving in 1410 01:17:11,720 --> 01:17:15,439 Speaker 1: and traveling through and manipulating the world when our models 1411 01:17:15,439 --> 01:17:20,960 Speaker 1: for understanding causal relationships are so skeletal and bare bones, Like, 1412 01:17:21,160 --> 01:17:25,080 Speaker 1: why are we so good at life compared to how 1413 01:17:25,479 --> 01:17:32,480 Speaker 1: absolutely uh uh sparse are our mental imagery that animates 1414 01:17:32,520 --> 01:17:36,400 Speaker 1: our understanding of the workings of things? Is? Yeah, And 1415 01:17:36,439 --> 01:17:38,840 Speaker 1: I think at two other positive spins. Hey, if I 1416 01:17:38,960 --> 01:17:43,200 Speaker 1: forget details of the plot and the narrative structure of 1417 01:17:43,240 --> 01:17:45,000 Speaker 1: Big Trouble and Little China, that means the next time 1418 01:17:45,040 --> 01:17:47,599 Speaker 1: I see it, a lot of stuff's gonna be new again. 1419 01:17:47,760 --> 01:17:50,439 Speaker 1: Oh and then, and we talked about our own privileged 1420 01:17:50,800 --> 01:17:55,240 Speaker 1: place of continually exploring new topics and and confronting what 1421 01:17:55,320 --> 01:17:57,920 Speaker 1: we don't know and learning more about the world around us. 1422 01:17:58,200 --> 01:18:00,559 Speaker 1: We should also point out, at risk of sounding like 1423 01:18:00,600 --> 01:18:03,880 Speaker 1: I'm pandering uh, that our audience probably is in much 1424 01:18:03,920 --> 01:18:05,920 Speaker 1: the same boat. The mere fact that you listen to 1425 01:18:05,920 --> 01:18:08,800 Speaker 1: stuff to blow your mind, um, that you engage in 1426 01:18:09,160 --> 01:18:15,320 Speaker 1: uh educational infocational uh podcast it just means. It means 1427 01:18:15,360 --> 01:18:18,160 Speaker 1: that you to realize. Hey, Like, for instance, we had 1428 01:18:18,160 --> 01:18:21,040 Speaker 1: to recently had an episode on butter. Some people might say, 1429 01:18:21,120 --> 01:18:22,880 Speaker 1: I know how better works. I'm not gonna listen to that. 1430 01:18:23,200 --> 01:18:25,120 Speaker 1: But people who did listen to it, they realized, well, 1431 01:18:25,120 --> 01:18:27,120 Speaker 1: I think I know how better works. But if they 1432 01:18:27,120 --> 01:18:29,320 Speaker 1: did an episode on it, then I guess there's more 1433 01:18:29,439 --> 01:18:32,080 Speaker 1: to the scenario than I than I than I give 1434 01:18:32,080 --> 01:18:34,760 Speaker 1: it credit. Oh that, I guess there's more. Moment. I 1435 01:18:34,760 --> 01:18:37,800 Speaker 1: feel like it's very central to what we do. Yeah. Uh, 1436 01:18:38,080 --> 01:18:40,680 Speaker 1: but don't let it go to your head. Robert, you 1437 01:18:40,760 --> 01:18:43,200 Speaker 1: and I and you out there listening. We're no better. 1438 01:18:43,360 --> 01:18:47,640 Speaker 1: We're no better. We just we just strive to understand 1439 01:18:47,720 --> 01:18:50,760 Speaker 1: the depths of our ignorance, all right, And if you 1440 01:18:50,800 --> 01:18:53,080 Speaker 1: want to strive to explore the depths of your ignorance, 1441 01:18:53,280 --> 01:18:55,040 Speaker 1: head on over to stuff to Blow your Mind dot com. 1442 01:18:55,040 --> 01:18:58,320 Speaker 1: That's where we find all the podcast episodes, videos, blog post, 1443 01:18:58,520 --> 01:19:00,599 Speaker 1: you name. It leaks out to social media accounts. We're 1444 01:19:00,600 --> 01:19:03,559 Speaker 1: on Facebook, Twitter, Tumbler, et cetera. About the Mothership is 1445 01:19:03,560 --> 01:19:05,519 Speaker 1: Stuff to Blow your Mind dot com. And of course, 1446 01:19:05,600 --> 01:19:07,640 Speaker 1: as always, if you want to email us directly to 1447 01:19:07,640 --> 01:19:10,599 Speaker 1: get in touch about this episode or any other you 1448 01:19:10,640 --> 01:19:13,240 Speaker 1: can hit us up at blow the Mind at how 1449 01:19:13,280 --> 01:19:25,320 Speaker 1: stuff works dot com for more on this and thousands 1450 01:19:25,360 --> 01:19:50,560 Speaker 1: of other topics. Is it how stuff works dot com.