1 00:00:00,240 --> 00:00:04,680 Speaker 1: From UFOs to psychic powers and government conspiracies. History is 2 00:00:04,760 --> 00:00:09,080 Speaker 1: riddled with unexplained events. You can turn back now or 3 00:00:09,200 --> 00:00:12,079 Speaker 1: learn the stuff they don't want you to know. A 4 00:00:12,200 --> 00:00:25,560 Speaker 1: production of I Heart Radio. Hello, welcome back to the show. 5 00:00:25,640 --> 00:00:28,280 Speaker 1: My name is Matt, my name is Noel. They call 6 00:00:28,400 --> 00:00:30,520 Speaker 1: me Bed, and we are joined as always with our 7 00:00:30,600 --> 00:00:35,360 Speaker 1: super producer Paul Mission Control Decades. Most importantly, you are you, 8 00:00:35,360 --> 00:00:38,360 Speaker 1: You are here, and that makes this the stuff they 9 00:00:38,479 --> 00:00:42,720 Speaker 1: don't want you to know history. That's part of where 10 00:00:42,760 --> 00:00:45,680 Speaker 1: we're going today, folks. Despite what some of us may 11 00:00:45,720 --> 00:00:49,479 Speaker 1: experience in grade school, history is much more than a 12 00:00:49,680 --> 00:00:54,240 Speaker 1: collection of isolated statistics and out of context facts printed 13 00:00:54,240 --> 00:00:58,160 Speaker 1: in dusty classroom tomes. History is both powerful and at 14 00:00:58,240 --> 00:01:02,800 Speaker 1: times controversial. The story of human civilization, in particular, is 15 00:01:02,960 --> 00:01:06,759 Speaker 1: full to the brim of stories that people in power 16 00:01:06,959 --> 00:01:10,040 Speaker 1: sometimes would rather be forgotten, as well as stories that 17 00:01:10,080 --> 00:01:13,040 Speaker 1: can empower us with a new understanding of the present. 18 00:01:13,319 --> 00:01:16,880 Speaker 1: In today's interview, we're diving into the power of history, 19 00:01:17,200 --> 00:01:22,199 Speaker 1: and we're diving into the consequences of sometimes bad decisions 20 00:01:22,480 --> 00:01:26,000 Speaker 1: as well as the literal cautionary tales it can teach us. 21 00:01:26,120 --> 00:01:29,679 Speaker 1: And we're not setting off on this journey alone. Please 22 00:01:29,760 --> 00:01:34,320 Speaker 1: join us and welcoming the economist, journalist, broadcaster, and author. 23 00:01:34,560 --> 00:01:38,920 Speaker 1: Tim Harford, the creator of the Cautionary Tales podcast, Thanks 24 00:01:38,920 --> 00:01:41,679 Speaker 1: so much for joining us today, Tim, Oh, I'm so 25 00:01:41,800 --> 00:01:44,560 Speaker 1: pleased to be on the show. Thank you. Ben. So 26 00:01:45,000 --> 00:01:46,720 Speaker 1: you've got a podcast to that too, right, you know 27 00:01:46,760 --> 00:01:49,360 Speaker 1: you're you're an old school and a new school media 28 00:01:49,400 --> 00:01:51,800 Speaker 1: specialist there, right, Yeah, I've I've done it all. I'm 29 00:01:51,920 --> 00:01:56,360 Speaker 1: I mean, I'm done it all. Just on that note, 30 00:01:56,960 --> 00:01:59,600 Speaker 1: I have to bring this up to him. I was 31 00:01:59,640 --> 00:02:02,880 Speaker 1: looking act just through your work and I realized I had. 32 00:02:03,120 --> 00:02:05,520 Speaker 1: I've been watching you on television for quite a while. 33 00:02:05,520 --> 00:02:08,440 Speaker 1: I think we all have. UM. Specifically, I looked back 34 00:02:08,480 --> 00:02:11,919 Speaker 1: at an episode of the Colbert Rapport. Uh there's actually 35 00:02:11,960 --> 00:02:14,359 Speaker 1: I'm sure there's more than one. Maybe they're the only 36 00:02:14,400 --> 00:02:17,400 Speaker 1: one that I saw and vividly remembered was when you 37 00:02:17,440 --> 00:02:20,679 Speaker 1: were you were discussing a book that had recently come out, 38 00:02:20,760 --> 00:02:24,600 Speaker 1: The Logic of Life, and uh, my goodness, that was wonderful. 39 00:02:24,760 --> 00:02:27,520 Speaker 1: Thank you for doing that. It was there was an 40 00:02:27,560 --> 00:02:32,400 Speaker 1: incredible experience that colbet he I there was a joke 41 00:02:32,919 --> 00:02:38,360 Speaker 1: in that exchange about um, well, maybe I shouldn't. I 42 00:02:38,360 --> 00:02:40,440 Speaker 1: don't know how adult the audience is, so maybe I 43 00:02:40,480 --> 00:02:42,480 Speaker 1: shouldn't go into all the details. The joke was slightly 44 00:02:42,480 --> 00:02:47,760 Speaker 1: excuted joke about Pepsi and coke and I had I 45 00:02:47,800 --> 00:02:50,800 Speaker 1: had worked on that book for two years, and Colberts 46 00:02:51,080 --> 00:02:54,760 Speaker 1: and did not the joke, which in retrospect is obvious 47 00:02:55,320 --> 00:02:59,120 Speaker 1: about today's teenagers being the Pepsi generation and what they 48 00:02:59,160 --> 00:03:01,360 Speaker 1: like to get up to. The joke did not occur 49 00:03:01,400 --> 00:03:04,600 Speaker 1: to me. It's it occurred to to Stephen in about 50 00:03:04,639 --> 00:03:07,120 Speaker 1: three seconds. I mean, he's um, he's very very good 51 00:03:07,120 --> 00:03:10,280 Speaker 1: at what he does. He's also he's super nice backstage, 52 00:03:10,320 --> 00:03:12,079 Speaker 1: he was so nice. He came into the green room 53 00:03:12,280 --> 00:03:13,840 Speaker 1: and he talked it all through and he's like, have 54 00:03:13,880 --> 00:03:15,160 Speaker 1: you ever seen the show? Do you know what the 55 00:03:15,200 --> 00:03:17,720 Speaker 1: show's about? And I'm going to be in character. My 56 00:03:17,800 --> 00:03:21,040 Speaker 1: character is a total idiot. My character hasn't made your book. 57 00:03:21,360 --> 00:03:23,840 Speaker 1: My character doesn't doesn't understand anything. I was like, Oh, 58 00:03:23,840 --> 00:03:26,040 Speaker 1: that's that's so kind of him. And then he got 59 00:03:26,080 --> 00:03:29,320 Speaker 1: into character later and he walked past my dressing room 60 00:03:29,400 --> 00:03:33,320 Speaker 1: and he yells out, I'm going to tell you apart Wow, 61 00:03:33,360 --> 00:03:35,440 Speaker 1: Like the guys, he's in the zone. Now this is 62 00:03:35,480 --> 00:03:38,160 Speaker 1: how it all works behind the scenes. Yeah, you gotta 63 00:03:38,200 --> 00:03:40,560 Speaker 1: wonder if that took a toll on him eventually, and 64 00:03:40,600 --> 00:03:42,960 Speaker 1: that's why he kind of decided to pivot away from 65 00:03:42,960 --> 00:03:46,480 Speaker 1: doing that character, which it was a wonderful period in 66 00:03:46,520 --> 00:03:48,120 Speaker 1: his career. But I'm kind of glad that he's just 67 00:03:48,400 --> 00:03:51,000 Speaker 1: himself now. He's such a thoughtful guy and a devout, 68 00:03:51,200 --> 00:03:54,840 Speaker 1: a devoutly religious man, which is interesting considering the types 69 00:03:54,880 --> 00:03:57,800 Speaker 1: of conversations that that we're having today as well, And 70 00:03:57,800 --> 00:04:01,880 Speaker 1: and Dungeons and Dragons fan as Well's right, Yeah, I 71 00:04:01,920 --> 00:04:03,880 Speaker 1: mean he's he's one of the gang. There. There's a 72 00:04:03,880 --> 00:04:06,280 Speaker 1: couch entails abou Dungeons Dragons, which we can discuss if 73 00:04:06,280 --> 00:04:09,520 Speaker 1: you like. Yes, the whole reason of bringing that up 74 00:04:09,600 --> 00:04:12,440 Speaker 1: is because that that appearance was in two thousand eight 75 00:04:12,680 --> 00:04:16,200 Speaker 1: and far before that and up and to that point 76 00:04:16,200 --> 00:04:19,720 Speaker 1: and up until today. One of your main at least 77 00:04:19,720 --> 00:04:23,320 Speaker 1: in my mind, one of your main studies is in 78 00:04:23,440 --> 00:04:26,599 Speaker 1: logic itself and how we think, in critical thinking, and 79 00:04:26,640 --> 00:04:30,240 Speaker 1: the way we look at things and how we analyze them. 80 00:04:30,360 --> 00:04:32,560 Speaker 1: And I just want to say thank you for doing that, 81 00:04:32,600 --> 00:04:35,000 Speaker 1: first of all, because we need it very very much now. 82 00:04:35,080 --> 00:04:38,360 Speaker 1: And then and before and always we need that. And 83 00:04:38,440 --> 00:04:42,599 Speaker 1: how has that pursuit of logic, and how has that 84 00:04:42,680 --> 00:04:45,839 Speaker 1: affected your own work in choosing what to cover next. 85 00:04:46,839 --> 00:04:49,600 Speaker 1: It's it's a good question. It's taken me on quite 86 00:04:49,600 --> 00:04:52,880 Speaker 1: a journey because I began I studied philosophy, and I 87 00:04:52,920 --> 00:04:57,159 Speaker 1: studied formal logic, and I studied economics, and as a journalist. 88 00:04:57,480 --> 00:05:00,360 Speaker 1: At first I was covering economics, and I deers in 89 00:05:00,400 --> 00:05:04,280 Speaker 1: economics and the free economics kind of stuff, and also 90 00:05:04,760 --> 00:05:07,520 Speaker 1: statistics and the way people think about numbers and the 91 00:05:07,520 --> 00:05:09,960 Speaker 1: way numbers are used as weapons, and the way numbers 92 00:05:09,960 --> 00:05:12,560 Speaker 1: are used to sell things, to sell political ideas, to 93 00:05:12,600 --> 00:05:16,920 Speaker 1: sell your soft drinks, whatever it is. And over time 94 00:05:17,080 --> 00:05:21,279 Speaker 1: I came to realize that the way that we process 95 00:05:22,400 --> 00:05:28,440 Speaker 1: these apparent facts is not often logical. It's emotional, and 96 00:05:28,480 --> 00:05:30,760 Speaker 1: it's not because people are done, it's because they're human. 97 00:05:31,839 --> 00:05:34,880 Speaker 1: And I got more and more interested in the things 98 00:05:34,920 --> 00:05:37,880 Speaker 1: that we get wrong, in the way that we persuade ourselves, 99 00:05:38,000 --> 00:05:41,520 Speaker 1: or things that aren't necessarily true. And so I had 100 00:05:41,560 --> 00:05:46,560 Speaker 1: this journey on studying from studying logic, studying rationality, studying 101 00:05:46,640 --> 00:05:50,680 Speaker 1: statistical reasoning, to study studying the you know, we've kind 102 00:05:50,680 --> 00:05:53,200 Speaker 1: of meat sacks that we are trying to understand all 103 00:05:53,279 --> 00:05:55,640 Speaker 1: these things, and I think you need a bit of both. 104 00:05:55,720 --> 00:05:57,760 Speaker 1: You've got to understand the world. You You want to 105 00:05:57,839 --> 00:05:59,839 Speaker 1: understand the rational side, but you need to understand the 106 00:06:00,000 --> 00:06:01,880 Speaker 1: ootional side as well. The reason I brought up the 107 00:06:01,880 --> 00:06:04,640 Speaker 1: core beer thing in him being devoutly religious, Um, you know, 108 00:06:04,680 --> 00:06:07,600 Speaker 1: when thinking about logic and this kind of stuff, is 109 00:06:07,600 --> 00:06:11,240 Speaker 1: obviously an incredibly intelligent man. They're obviously very intelligent people 110 00:06:11,480 --> 00:06:14,240 Speaker 1: that are very much like yourself, focused on statistics and 111 00:06:14,320 --> 00:06:16,520 Speaker 1: logic and all of this kind of thing and rational thought, 112 00:06:16,640 --> 00:06:18,960 Speaker 1: who are devoutly religious. Is there a place for that 113 00:06:19,120 --> 00:06:22,400 Speaker 1: in your studies that you found or is it sort 114 00:06:22,400 --> 00:06:25,480 Speaker 1: of Do you see it as a form of self delusion? Well, 115 00:06:25,520 --> 00:06:28,000 Speaker 1: I'm not a religious person myself, but I certainly wouldn't 116 00:06:28,279 --> 00:06:30,360 Speaker 1: see it as self delusion. I mean, my my wife 117 00:06:30,480 --> 00:06:33,839 Speaker 1: is religious, and I don't certainly. I think my wife 118 00:06:33,880 --> 00:06:38,080 Speaker 1: is a person of extreme taste and good judgment in 119 00:06:38,160 --> 00:06:44,440 Speaker 1: all things. So yeah, I'm struck by how there's a 120 00:06:44,440 --> 00:06:48,960 Speaker 1: particular group who say that they're logical and say that 121 00:06:48,960 --> 00:06:51,719 Speaker 1: they're rational about this issue and then seem to get 122 00:06:51,760 --> 00:06:54,719 Speaker 1: really up in everyone's faces about it, and after I'm 123 00:06:54,800 --> 00:06:57,799 Speaker 1: not sure that we need to argue so much about 124 00:06:57,839 --> 00:07:01,560 Speaker 1: this particular subject. I think it's possible to unders to 125 00:07:01,920 --> 00:07:04,720 Speaker 1: disagree with someone in a friendly way, to still treat 126 00:07:04,760 --> 00:07:07,640 Speaker 1: them as human, to still treat them as thoughtful, and 127 00:07:07,680 --> 00:07:10,400 Speaker 1: to be curious about their views. Um, you don't have 128 00:07:10,400 --> 00:07:12,120 Speaker 1: to agree with them, but you don't have to just 129 00:07:12,440 --> 00:07:15,560 Speaker 1: constantly be chipping away at them either. Yeah, and you 130 00:07:15,600 --> 00:07:18,840 Speaker 1: know this is something that I see as a common 131 00:07:18,960 --> 00:07:22,960 Speaker 1: through line in your work, Tim. I will admit that 132 00:07:23,160 --> 00:07:27,320 Speaker 1: when I was researching this interview that we're doing today, 133 00:07:27,920 --> 00:07:31,840 Speaker 1: I had a moment of epiphany similar to what Matt described, 134 00:07:32,000 --> 00:07:34,960 Speaker 1: where I said, Oh, it's it's that Tim. I've been 135 00:07:35,000 --> 00:07:39,239 Speaker 1: reading I have, I have his books, and uh, I 136 00:07:39,280 --> 00:07:45,760 Speaker 1: love this through line of exploring empathy as well as economics. 137 00:07:45,880 --> 00:07:50,040 Speaker 1: And I was wondering if we could ask some some 138 00:07:50,120 --> 00:07:54,160 Speaker 1: kind of dumb questions on my end about economics. Uh. 139 00:07:54,360 --> 00:07:56,120 Speaker 1: I was going to say, there are no dumb questions, 140 00:07:56,120 --> 00:07:58,320 Speaker 1: but I should wait until I've heard the questions before 141 00:07:58,360 --> 00:08:00,960 Speaker 1: I say that I shouldn't. But you know, go right ahead. 142 00:08:01,560 --> 00:08:06,080 Speaker 1: I'm leaning into your long history as a columnist fielding 143 00:08:06,160 --> 00:08:10,920 Speaker 1: questions from the public. And what one thing that I 144 00:08:11,000 --> 00:08:14,360 Speaker 1: wanted to start with is the idea that economics have 145 00:08:14,400 --> 00:08:18,720 Speaker 1: occasionally been called, you know, the dismal science. What, in 146 00:08:18,760 --> 00:08:23,920 Speaker 1: your mind are some of the common misconceptions about economics 147 00:08:23,960 --> 00:08:27,120 Speaker 1: and statistics in in the public. I mean that that 148 00:08:27,200 --> 00:08:29,640 Speaker 1: dismal science thing is a good place to start, because 149 00:08:29,640 --> 00:08:34,240 Speaker 1: the person who accused economics of being the dismal science, 150 00:08:34,679 --> 00:08:38,600 Speaker 1: the dismal science was a guy called Thomas Carlyle, who 151 00:08:38,920 --> 00:08:43,560 Speaker 1: was very upset that so many economists were abolitionists. Wanted 152 00:08:43,600 --> 00:08:46,360 Speaker 1: to get rid of the slave trade, and they felt 153 00:08:46,360 --> 00:08:49,320 Speaker 1: that if you wanted someone to work, you should agree 154 00:08:50,040 --> 00:08:52,880 Speaker 1: a contract and pay them a wage to which they agree, 155 00:08:53,000 --> 00:08:54,400 Speaker 1: and that's what you do. If you want someone to 156 00:08:54,440 --> 00:08:56,560 Speaker 1: work for them, you don't treat them as property, you 157 00:08:56,559 --> 00:09:00,200 Speaker 1: don't oppress them. And Carlisle was like, oh, no, you 158 00:09:00,200 --> 00:09:03,800 Speaker 1: don't understand kind of humanity is so diverse. There are 159 00:09:03,800 --> 00:09:05,920 Speaker 1: people who are supposed to be masters, and there are 160 00:09:05,920 --> 00:09:08,199 Speaker 1: people who are supposed to be enslaved, and economists just 161 00:09:08,240 --> 00:09:12,200 Speaker 1: don't understand this about the diversity of human beings. He's 162 00:09:12,240 --> 00:09:15,240 Speaker 1: the guy who called us the dismal science. So guilty 163 00:09:15,240 --> 00:09:17,120 Speaker 1: has charged I'm happy to be dismal if I think 164 00:09:17,120 --> 00:09:20,800 Speaker 1: that basically all all humans are fundamentally equal. So that's 165 00:09:20,840 --> 00:09:23,079 Speaker 1: one thing, and then people people call us dismal science, 166 00:09:23,120 --> 00:09:25,800 Speaker 1: they very often don't know where that comes from. Another 167 00:09:25,840 --> 00:09:29,800 Speaker 1: thing that I think people get wrong if they think 168 00:09:29,840 --> 00:09:33,800 Speaker 1: that economics is basically the study of money. I think 169 00:09:33,880 --> 00:09:37,040 Speaker 1: actually economists don't think much about money, and you could 170 00:09:37,040 --> 00:09:40,400 Speaker 1: accuse them of not thinking enough about money and and 171 00:09:40,520 --> 00:09:42,640 Speaker 1: kind of treating it as though was this it's a 172 00:09:42,679 --> 00:09:45,280 Speaker 1: detail that doesn't really matter. What we're interested in is 173 00:09:45,320 --> 00:09:48,800 Speaker 1: in the real flow of goods and services and the 174 00:09:48,840 --> 00:09:51,240 Speaker 1: decisions that people make every day and how they spend 175 00:09:51,240 --> 00:09:53,520 Speaker 1: their lives and how they spend their time and how 176 00:09:53,559 --> 00:09:56,360 Speaker 1: they reason. Maybe we should think a bit more about money. 177 00:09:56,480 --> 00:10:00,120 Speaker 1: But that's the thing people think that economics is is 178 00:10:00,160 --> 00:10:03,040 Speaker 1: about money, And actually economics is kind of about everything 179 00:10:03,360 --> 00:10:05,920 Speaker 1: except money. If that sounds a bit weird, but I 180 00:10:05,960 --> 00:10:09,640 Speaker 1: think it's defensible well, And the the economic argument against 181 00:10:09,679 --> 00:10:12,319 Speaker 1: slavery wasn't necessarily even taking a political stance. It was 182 00:10:12,400 --> 00:10:15,800 Speaker 1: mortgaged about logistics and like how things would function better 183 00:10:16,120 --> 00:10:18,880 Speaker 1: like as a society if we, you know, moved towards 184 00:10:18,920 --> 00:10:21,720 Speaker 1: this model. I think there would be higher quality work, 185 00:10:21,840 --> 00:10:23,480 Speaker 1: there would be less strife. It would just be a 186 00:10:23,520 --> 00:10:26,480 Speaker 1: better situation. Is that correct? Yeah, well, I'm not I'm 187 00:10:26,480 --> 00:10:28,120 Speaker 1: not an expert in the history of it, but I 188 00:10:28,160 --> 00:10:30,319 Speaker 1: know that one of the people who was most prominent 189 00:10:30,320 --> 00:10:32,360 Speaker 1: was John Stuart Mill, who was both one of the 190 00:10:32,360 --> 00:10:34,440 Speaker 1: greatest economists who have ever lived and also one of 191 00:10:34,440 --> 00:10:38,439 Speaker 1: the greatest moral philosophers. So I I would be fairly 192 00:10:38,440 --> 00:10:41,679 Speaker 1: confident that he would be taking both the political moral 193 00:10:41,720 --> 00:10:44,160 Speaker 1: angle and also the practical angle. He would do both. 194 00:10:45,000 --> 00:10:48,079 Speaker 1: I want to follow up with the question on with 195 00:10:48,200 --> 00:10:52,440 Speaker 1: the question on misconceptions in the world of statistics. You know, 196 00:10:52,760 --> 00:10:57,120 Speaker 1: you said something that really tickled me right before recording 197 00:10:57,160 --> 00:11:01,760 Speaker 1: to him where we were talking about our tech details, 198 00:11:02,040 --> 00:11:04,280 Speaker 1: and he said, you know, I I study how things 199 00:11:04,320 --> 00:11:08,840 Speaker 1: go wrong, so I'm prepared for the stuff and when 200 00:11:08,880 --> 00:11:12,679 Speaker 1: we're talking about misconceptions and how things go wrong, something 201 00:11:12,679 --> 00:11:16,200 Speaker 1: that I believe everyone in our audience has encountered hinges 202 00:11:16,360 --> 00:11:20,360 Speaker 1: on statistics, especially when sort of cherry picked presented by 203 00:11:20,440 --> 00:11:25,000 Speaker 1: politicians and pundits, usually to attempt to support their point 204 00:11:25,160 --> 00:11:29,080 Speaker 1: right a quick glance at a kind of lazy, simple, 205 00:11:29,160 --> 00:11:33,640 Speaker 1: colorful infographic and then move on right, What can the 206 00:11:33,720 --> 00:11:38,800 Speaker 1: average person do to understand whether or not a statistic 207 00:11:39,400 --> 00:11:43,200 Speaker 1: is legitimate? So I wrote an entire book about this, 208 00:11:43,520 --> 00:11:45,920 Speaker 1: and I'm going to give you the secret to that book, 209 00:11:45,960 --> 00:11:47,880 Speaker 1: so you don't need to buy it, although I do 210 00:11:48,000 --> 00:11:50,439 Speaker 1: recommend that you do buy it. It's called The Data Detective. 211 00:11:51,120 --> 00:11:54,800 Speaker 1: And uh and yeah, I recommend the book. But but 212 00:11:54,840 --> 00:11:56,599 Speaker 1: then I would, wouldn't I? But let me try and 213 00:11:56,640 --> 00:12:01,040 Speaker 1: give you the okay. So the three part approach to 214 00:12:01,120 --> 00:12:03,400 Speaker 1: making sense of a number that you see, it's the 215 00:12:03,480 --> 00:12:08,400 Speaker 1: three cs. Calm, context, curiosity. So the first he is calm. 216 00:12:08,600 --> 00:12:11,760 Speaker 1: Most of the statistics that we see are drawn to 217 00:12:11,760 --> 00:12:16,440 Speaker 1: our attention on social media or regular media because they 218 00:12:16,640 --> 00:12:22,240 Speaker 1: elicit an emotional reaction. They're meant to make you upset, afraid, angry, 219 00:12:22,720 --> 00:12:27,120 Speaker 1: amused at some other person is being stupid, dumbfounded at 220 00:12:27,160 --> 00:12:29,800 Speaker 1: the mendacity of politicians? Was something. It's supposed to elicit 221 00:12:29,800 --> 00:12:32,839 Speaker 1: an emotional reaction, That's why you're seeing it. So the 222 00:12:32,920 --> 00:12:35,480 Speaker 1: very first things, just be calm. Notice what is my 223 00:12:35,520 --> 00:12:38,520 Speaker 1: emotional reaction? Is it denial? I can't possibly be true? 224 00:12:39,200 --> 00:12:41,679 Speaker 1: Is it? Oh? Yes, this just proves I'm right. Let 225 00:12:41,679 --> 00:12:43,240 Speaker 1: me just go and tell my friend, who are is 226 00:12:43,320 --> 00:12:47,960 Speaker 1: arguing about this with? Just notice that reaction counter three. 227 00:12:48,240 --> 00:12:50,640 Speaker 1: Then you then you move on so that the second 228 00:12:50,640 --> 00:12:53,480 Speaker 1: thing is context, and that's just to ask some basic 229 00:12:53,559 --> 00:12:57,000 Speaker 1: facts about the statistic that you're being shown. The most 230 00:12:57,000 --> 00:13:00,960 Speaker 1: basic of all is what is the definite issue? What 231 00:13:01,200 --> 00:13:03,760 Speaker 1: is the way that this thing is being measured or 232 00:13:03,760 --> 00:13:05,959 Speaker 1: what is being measured? So let's say, for example, you're 233 00:13:05,960 --> 00:13:10,559 Speaker 1: having an argument about I don't know immigration, well, immigration 234 00:13:10,600 --> 00:13:12,559 Speaker 1: is a is a subject that you know, people get 235 00:13:12,640 --> 00:13:15,040 Speaker 1: very excited about, they feel very emotional about on one 236 00:13:15,080 --> 00:13:17,959 Speaker 1: side or the other. But how is it being measured? 237 00:13:18,000 --> 00:13:20,560 Speaker 1: Like are we talking about illegal immigration? Are we talking 238 00:13:20,559 --> 00:13:23,960 Speaker 1: about people kind of illicitly crossing the border? Are we 239 00:13:24,040 --> 00:13:28,200 Speaker 1: talking about people with green cards? Are we or are 240 00:13:28,240 --> 00:13:30,480 Speaker 1: we are we actually not really talking about immigration at all? 241 00:13:30,480 --> 00:13:33,760 Speaker 1: We're talking about people of different ethnicities. What is it 242 00:13:33,800 --> 00:13:36,640 Speaker 1: that we're talking about? So get the context, and that 243 00:13:36,679 --> 00:13:38,959 Speaker 1: can also mean is the number going up or down? Whatever? 244 00:13:39,040 --> 00:13:40,480 Speaker 1: Could also is it a big number? Is it a 245 00:13:40,480 --> 00:13:42,800 Speaker 1: small number? Can I compare it to something that makes 246 00:13:42,800 --> 00:13:46,319 Speaker 1: it makes sense? So first, see was calm, second see 247 00:13:46,400 --> 00:13:51,000 Speaker 1: was context, and the third really encompasses everything, which is curiosity. 248 00:13:51,080 --> 00:13:54,280 Speaker 1: So you treat all this information as Hey, I don't 249 00:13:54,360 --> 00:13:57,599 Speaker 1: know everything about the world. There are gaps in my knowledge. 250 00:13:58,440 --> 00:14:02,040 Speaker 1: Is this filling a cap Is this answering a question? 251 00:14:02,080 --> 00:14:05,679 Speaker 1: If it doesn't answer a question, well, you know, dig deeper, 252 00:14:05,960 --> 00:14:10,560 Speaker 1: go another click, ask around, get some more context, and 253 00:14:10,559 --> 00:14:15,640 Speaker 1: and view these statistics as a way of making your 254 00:14:15,640 --> 00:14:19,880 Speaker 1: ignorance smaller, rather that which sounds obvious like, of course 255 00:14:19,920 --> 00:14:22,520 Speaker 1: a fact informs you, it fills in a gap in 256 00:14:22,560 --> 00:14:24,400 Speaker 1: your knowledge. But that's not how we treat facts. We 257 00:14:24,480 --> 00:14:27,520 Speaker 1: treat facts as weapons. We treat them as ah, I 258 00:14:27,560 --> 00:14:29,720 Speaker 1: can use this to win an argument. That's how so 259 00:14:29,840 --> 00:14:33,240 Speaker 1: much of what we see as processed so treated instead 260 00:14:33,360 --> 00:14:37,320 Speaker 1: in a curious frame of mind, calm, context, curiosity, And 261 00:14:37,400 --> 00:14:39,680 Speaker 1: now you don't have to buy the data is a detective, 262 00:14:39,720 --> 00:14:42,400 Speaker 1: but maybe you should. Yeah, yeah, yeah, I'm going to 263 00:14:43,080 --> 00:14:46,920 Speaker 1: uh for sure. Um. I wish that Sir Arthur Conan 264 00:14:47,000 --> 00:14:49,560 Speaker 1: Doyle could have purchased the data detective while he was 265 00:14:49,560 --> 00:14:52,000 Speaker 1: still around. I want to bring this back to the 266 00:14:52,040 --> 00:14:56,880 Speaker 1: Fourth Sea, which is Cautionary Tales, that is, in a 267 00:14:56,960 --> 00:15:00,960 Speaker 1: specific episode there there we listen to you in preparation 268 00:15:01,000 --> 00:15:05,800 Speaker 1: for this interview. It's on a curious case of images 269 00:15:05,880 --> 00:15:12,480 Speaker 1: of fairies, of photographs specifically plates um and how these 270 00:15:12,480 --> 00:15:15,960 Speaker 1: photographs taken I guess the first photograph ever taken by 271 00:15:16,040 --> 00:15:19,920 Speaker 1: an amateur photographer, and how it fooled Sir Arthur Conan Doyle. 272 00:15:20,320 --> 00:15:21,960 Speaker 1: So could you just tell us a bit of the story, 273 00:15:22,000 --> 00:15:24,960 Speaker 1: maybe the condensed version that we can get into what 274 00:15:24,960 --> 00:15:28,960 Speaker 1: what occurred? Because of belief in this situation, I find 275 00:15:28,960 --> 00:15:31,680 Speaker 1: the story just completely enchanting. And by the way, this 276 00:15:31,760 --> 00:15:35,800 Speaker 1: is a classic way that we approach for cautionary tales. 277 00:15:35,840 --> 00:15:38,640 Speaker 1: So so I tell a story, we have actors, we 278 00:15:38,720 --> 00:15:43,240 Speaker 1: have music, really put in, putting the work to give 279 00:15:43,240 --> 00:15:46,920 Speaker 1: people really immersive storytelling experience, and then we try to 280 00:15:47,000 --> 00:15:49,920 Speaker 1: draw lessons from the story, like what went wrong? What 281 00:15:50,000 --> 00:15:53,440 Speaker 1: was the mistake? Are we making that same mistake ourselves? 282 00:15:53,880 --> 00:15:57,760 Speaker 1: In this particular case, the story is of arthuricon and Doyle, 283 00:15:58,560 --> 00:16:01,120 Speaker 1: the creator of Sherlock Holmes, one of the most famous 284 00:16:01,160 --> 00:16:04,320 Speaker 1: men in the world at the time. This is about 285 00:16:04,320 --> 00:16:08,400 Speaker 1: a hundred years ago, going public, publishing a book, publishing 286 00:16:08,400 --> 00:16:13,000 Speaker 1: these huge cover stories saying we found these photos of fairies. 287 00:16:14,200 --> 00:16:18,880 Speaker 1: Fair is a real mind blown and he sort of recognized, well, 288 00:16:18,920 --> 00:16:20,480 Speaker 1: you know, maybe it could be a hoax, but of 289 00:16:20,480 --> 00:16:22,400 Speaker 1: course it's not a hoax, and he found all these 290 00:16:22,440 --> 00:16:24,560 Speaker 1: ways to dismiss the evidence that it was a hoax. 291 00:16:24,880 --> 00:16:26,880 Speaker 1: And the photos you can look them up on the 292 00:16:26,880 --> 00:16:30,680 Speaker 1: internet very easily. That they're called the Cottingly Fairies, Cottingly 293 00:16:30,760 --> 00:16:33,280 Speaker 1: being a suburb of Bradford in the north of England. 294 00:16:34,160 --> 00:16:38,360 Speaker 1: Very charming black and white photos. Got these girls. One 295 00:16:38,360 --> 00:16:40,280 Speaker 1: of them looks about nine years old, and other ones 296 00:16:40,280 --> 00:16:43,600 Speaker 1: a little older, and then these fairies in the foreground, 297 00:16:44,360 --> 00:16:47,160 Speaker 1: and they kind of look a little bit like maybe 298 00:16:47,200 --> 00:16:50,040 Speaker 1: they were cut out of a picture book, which probably 299 00:16:50,120 --> 00:16:55,040 Speaker 1: they in fact were. And and yet Sir Arthur convinced 300 00:16:55,120 --> 00:16:59,000 Speaker 1: himself that a nine year old girl can't fake photos. 301 00:16:59,840 --> 00:17:02,240 Speaker 1: He he really wanted to believe. And there's a couple 302 00:17:02,280 --> 00:17:04,720 Speaker 1: of different things going on there. One was his own 303 00:17:04,800 --> 00:17:08,200 Speaker 1: family history. He was he had been bereaved several times, 304 00:17:08,200 --> 00:17:10,240 Speaker 1: he had lost his son, he had lost his brother, 305 00:17:10,640 --> 00:17:12,639 Speaker 1: his wife, and his mother. He was very close to 306 00:17:12,680 --> 00:17:15,240 Speaker 1: his mother, and he really wanted to believe there's something 307 00:17:15,240 --> 00:17:18,119 Speaker 1: out there, there's something more than just what we can 308 00:17:18,160 --> 00:17:20,439 Speaker 1: see and touch ourselves. So he was very open to 309 00:17:20,480 --> 00:17:23,760 Speaker 1: spiritualist beliefs. He was hungry for that there was also 310 00:17:23,800 --> 00:17:28,560 Speaker 1: a history in his family of taking fairies seriously. His 311 00:17:28,800 --> 00:17:32,760 Speaker 1: father was confined to a mental asylum and he used 312 00:17:32,800 --> 00:17:35,920 Speaker 1: to draw pictures of fairies, and right, I have known 313 00:17:36,000 --> 00:17:39,280 Speaker 1: such a creature, So you really there's this real longing 314 00:17:39,320 --> 00:17:42,399 Speaker 1: to believe. But the other thing was that Arthur was 315 00:17:42,400 --> 00:17:46,480 Speaker 1: actually a very good photographer himself. His first ever published 316 00:17:46,520 --> 00:17:49,680 Speaker 1: work was not The Sign of for or The Hound 317 00:17:49,720 --> 00:17:51,719 Speaker 1: of Basketball is one of these great Shollock home stories. 318 00:17:52,440 --> 00:17:55,040 Speaker 1: It was a piece in the British Journal of Photography. 319 00:17:55,280 --> 00:17:58,199 Speaker 1: So so Arthur knew that photographs could be faked. He 320 00:17:58,320 --> 00:18:00,760 Speaker 1: just didn't want to believe that these ones swhere. And 321 00:18:00,880 --> 00:18:03,200 Speaker 1: what he basically told himself is, I know how hard 322 00:18:03,240 --> 00:18:05,560 Speaker 1: it is to take a photograph. I know how hard 323 00:18:05,600 --> 00:18:08,240 Speaker 1: it is to fake a photograph, and I don't think 324 00:18:08,560 --> 00:18:10,840 Speaker 1: a nine year old girl can do it. And that's 325 00:18:10,840 --> 00:18:12,760 Speaker 1: why he just put his whole reputation on the line 326 00:18:12,800 --> 00:18:14,680 Speaker 1: and he made a total fool of himself. I mean, 327 00:18:14,680 --> 00:18:17,520 Speaker 1: it's so fascinating, especially since this is a man whose 328 00:18:17,560 --> 00:18:21,879 Speaker 1: life's work it's all about detective work and finding clues 329 00:18:21,960 --> 00:18:25,639 Speaker 1: and using logic and reason to get to a realistic 330 00:18:25,720 --> 00:18:28,359 Speaker 1: solution to a puzzle. Um, and he threw all that 331 00:18:28,400 --> 00:18:30,760 Speaker 1: out the window in favor of belief. I think there's 332 00:18:30,760 --> 00:18:32,960 Speaker 1: the cautionary tale right there. If this can happen to him, 333 00:18:32,960 --> 00:18:34,919 Speaker 1: that can happen to any of us. Yes, if you 334 00:18:34,960 --> 00:18:37,720 Speaker 1: want to believe it enough, you can find a way 335 00:18:37,720 --> 00:18:41,800 Speaker 1: to believe. There's there's another cautionary tale, rather darker, but 336 00:18:41,960 --> 00:18:46,520 Speaker 1: it's very very similar, of an art forger who fools 337 00:18:46,560 --> 00:18:48,679 Speaker 1: the greatest art critic in the world. And it's the 338 00:18:48,800 --> 00:18:51,920 Speaker 1: same basic story. A guy who really he knows more 339 00:18:51,920 --> 00:18:56,000 Speaker 1: than anybody else about the works of Vermeir, and that's 340 00:18:56,000 --> 00:18:58,280 Speaker 1: why he wants so badly to believe he's just found 341 00:18:58,280 --> 00:19:03,040 Speaker 1: a Vermeir. And that one involves Nazis and sex workers 342 00:19:03,080 --> 00:19:05,480 Speaker 1: and kind of all kinds of weird stuff. So it's 343 00:19:05,600 --> 00:19:08,560 Speaker 1: it's a little less family friendly, but same fundamental story. 344 00:19:09,080 --> 00:19:13,080 Speaker 1: The the leading expert uses their own expertise to kind 345 00:19:13,080 --> 00:19:16,360 Speaker 1: of unravel themselves and to to fool themselves. I love 346 00:19:16,400 --> 00:19:19,040 Speaker 1: that you can apply something like that to other stories, 347 00:19:19,119 --> 00:19:21,800 Speaker 1: right something that you find in cautionary tales as a 348 00:19:21,840 --> 00:19:24,960 Speaker 1: listener a larger story and then apply it to other things. 349 00:19:25,240 --> 00:19:27,600 Speaker 1: I want to just go quickly back to kind of 350 00:19:27,640 --> 00:19:31,080 Speaker 1: the origin of the fairy photograph and how it began, 351 00:19:31,119 --> 00:19:34,800 Speaker 1: because I believe in the episode that you've got it's 352 00:19:34,840 --> 00:19:36,960 Speaker 1: not necessarily a statement, but it was an interview that 353 00:19:37,040 --> 00:19:39,280 Speaker 1: was given at some point by one of the children, 354 00:19:39,920 --> 00:19:42,479 Speaker 1: either Francis Griffith's or Elsie, right. I think it might 355 00:19:42,520 --> 00:19:46,600 Speaker 1: have been Elsie who gave the interview, and she spoke 356 00:19:46,640 --> 00:19:49,200 Speaker 1: of why it even occurred in the first place and 357 00:19:49,240 --> 00:19:54,800 Speaker 1: how this entire huge scenario was generated. All you know, 358 00:19:55,000 --> 00:19:56,399 Speaker 1: one of the most famous men, as you said in 359 00:19:56,400 --> 00:20:00,440 Speaker 1: the world writing about it. Um, it all started as 360 00:20:00,480 --> 00:20:05,880 Speaker 1: an attempt to help a child who was what could 361 00:20:05,880 --> 00:20:07,760 Speaker 1: you tell this in that story, The child was getting 362 00:20:07,760 --> 00:20:10,359 Speaker 1: in trouble for something or getting chastise for something, and 363 00:20:10,840 --> 00:20:12,600 Speaker 1: she wanted to help and that's all she wanted to 364 00:20:12,640 --> 00:20:14,600 Speaker 1: help out. Yeah, Because because one of the things we 365 00:20:14,640 --> 00:20:16,800 Speaker 1: do in caution tales is is not is there's often 366 00:20:16,800 --> 00:20:18,719 Speaker 1: more than one side of the story. So we were 367 00:20:18,720 --> 00:20:22,600 Speaker 1: trying to ask not only how did Sir Arthur fool himself, 368 00:20:22,880 --> 00:20:26,880 Speaker 1: but also why did these girls do this and why 369 00:20:26,920 --> 00:20:30,080 Speaker 1: didn't they own up for it? Turns out sixty five 370 00:20:30,160 --> 00:20:32,960 Speaker 1: years they kept the secret for sixty five years and 371 00:20:33,240 --> 00:20:37,080 Speaker 1: Francis and Elsie were initially motivated because Francis, who was nine, 372 00:20:37,800 --> 00:20:41,000 Speaker 1: got into trouble with her mother. She slipped in the stream, 373 00:20:41,320 --> 00:20:44,800 Speaker 1: she got her clothes wet. Her mother was yelling at her, 374 00:20:45,040 --> 00:20:47,440 Speaker 1: and she said, well, I was playing with the fairies. 375 00:20:47,480 --> 00:20:49,760 Speaker 1: That's why I slipped, and her mother sent her to 376 00:20:49,800 --> 00:20:52,080 Speaker 1: her room because not only did she get her clothes wet, 377 00:20:52,160 --> 00:20:55,480 Speaker 1: but she also told a lie about the fairies. And Elsie, 378 00:20:55,560 --> 00:20:58,480 Speaker 1: who is her cousin who lives with her, who's older, 379 00:20:59,359 --> 00:21:03,960 Speaker 1: she's a teenage jay. She was outraged. She's growing ups 380 00:21:03,960 --> 00:21:07,199 Speaker 1: are always making up stupid stuff. They're always telling us 381 00:21:07,240 --> 00:21:10,080 Speaker 1: these fantastical lies. You know, you can think of your 382 00:21:10,080 --> 00:21:14,320 Speaker 1: own examples. And why should Elsie, why should Francis get 383 00:21:14,320 --> 00:21:17,000 Speaker 1: into such trouble for doing the same thing. So she 384 00:21:17,000 --> 00:21:20,919 Speaker 1: said to Francis, don't worry. We'll borrow my father's camera. 385 00:21:21,359 --> 00:21:24,760 Speaker 1: We're going to go down the back and we will 386 00:21:24,800 --> 00:21:27,800 Speaker 1: take photographs of the fairis. And that's what they did, 387 00:21:28,640 --> 00:21:32,560 Speaker 1: and of course they were they were fake. Francis always 388 00:21:32,560 --> 00:21:35,879 Speaker 1: said she really did see fairies, but she admitted that 389 00:21:35,920 --> 00:21:39,159 Speaker 1: the photographs were faked. Elsie, I think never believed in fairies, 390 00:21:39,920 --> 00:21:42,480 Speaker 1: but she believed in her artistic ability. She believed in 391 00:21:42,480 --> 00:21:45,359 Speaker 1: her ability as a photographer and as an artist, and 392 00:21:45,400 --> 00:21:47,200 Speaker 1: so it was partly a matter of pride. Once she 393 00:21:47,240 --> 00:21:52,119 Speaker 1: had started, she she wanted to continue, and things escalated, 394 00:21:52,160 --> 00:21:54,960 Speaker 1: so her father didn't believe her. Her mother was kind 395 00:21:54,960 --> 00:21:58,200 Speaker 1: of curious. Her mother mentioned the photographs. At this meeting 396 00:21:58,240 --> 00:22:02,439 Speaker 1: of local spiritualists. Word got out to a very senior piritualist, 397 00:22:02,440 --> 00:22:06,560 Speaker 1: a man called Edward Gardner. Edward Gardner told Doyle Doyle 398 00:22:06,600 --> 00:22:09,040 Speaker 1: got hold of the photographs. Doyle is, as I mentioned, 399 00:22:09,119 --> 00:22:11,840 Speaker 1: one of the most famous men in the world. And 400 00:22:11,880 --> 00:22:18,000 Speaker 1: at each stage, Elsie is thinking, probably should own up, 401 00:22:18,320 --> 00:22:21,080 Speaker 1: but that would be bad, past that would be bad, 402 00:22:21,119 --> 00:22:23,159 Speaker 1: and it just escalated and escalated and escalated, and it 403 00:22:23,280 --> 00:22:25,320 Speaker 1: just got too far. In the end, she realizes she 404 00:22:25,320 --> 00:22:28,840 Speaker 1: would just humiliate these men, and so not for the 405 00:22:28,880 --> 00:22:32,280 Speaker 1: first time, this young woman keeps quiet because she doesn't 406 00:22:32,320 --> 00:22:34,960 Speaker 1: want to offend the egos of these older men. You know, 407 00:22:35,080 --> 00:22:37,800 Speaker 1: this is something that really stands out to me about 408 00:22:37,960 --> 00:22:42,080 Speaker 1: Cautionary Tales. I don't want to spoil too much, but 409 00:22:42,560 --> 00:22:45,639 Speaker 1: one thing that really stood out in every episode, and 410 00:22:45,680 --> 00:22:49,760 Speaker 1: in The Mummies Curse in particular, is the structure, the 411 00:22:49,840 --> 00:22:54,280 Speaker 1: way that we explore this story of the Mummy's Curse 412 00:22:54,400 --> 00:22:58,760 Speaker 1: right in depth, and we go through all of the 413 00:22:59,440 --> 00:23:02,720 Speaker 1: all of the anecdotes and all of the embellishments that 414 00:23:02,800 --> 00:23:07,040 Speaker 1: accrete to the core legend over time, and then towards 415 00:23:07,080 --> 00:23:12,119 Speaker 1: the turn of the narrative we learn about selection bias. 416 00:23:12,200 --> 00:23:15,840 Speaker 1: So in a very a very real way to cautionary 417 00:23:15,880 --> 00:23:20,760 Speaker 1: tales seems to me a masterclass in teaching people how 418 00:23:20,840 --> 00:23:24,679 Speaker 1: to think. So I'm quite curious to learn when you 419 00:23:24,960 --> 00:23:29,000 Speaker 1: first said about making this show, did you start with 420 00:23:29,280 --> 00:23:33,560 Speaker 1: perhaps a list of concepts who wanted to impart or 421 00:23:33,840 --> 00:23:36,800 Speaker 1: was it more um, did it start the other way? 422 00:23:37,000 --> 00:23:41,000 Speaker 1: Did you start with these stories a Mummy's Curse, a 423 00:23:41,040 --> 00:23:45,800 Speaker 1: whistleblower and then say what what can we find? What 424 00:23:45,960 --> 00:23:50,000 Speaker 1: is our teachable concept in these stories? I'm just interested there, Well, 425 00:23:50,280 --> 00:23:51,880 Speaker 1: thank you bad. I mean, that is what we're trying 426 00:23:51,880 --> 00:23:56,240 Speaker 1: to do with and where we are trying to ensnare 427 00:23:56,280 --> 00:23:58,520 Speaker 1: people with the stories, to draw them in, get them 428 00:23:58,520 --> 00:24:01,159 Speaker 1: fascinated by what whats what's gonna happen? How is this 429 00:24:01,240 --> 00:24:03,920 Speaker 1: going to work out? And then while we've got them, 430 00:24:04,240 --> 00:24:06,760 Speaker 1: then we suddenly whack them over the head with some 431 00:24:06,800 --> 00:24:10,119 Speaker 1: social science or something, and really tell people something that 432 00:24:10,119 --> 00:24:12,800 Speaker 1: hopefully they didn't know or they hadn't thought of in 433 00:24:12,840 --> 00:24:15,000 Speaker 1: a way that they'll remember with the music and with 434 00:24:15,080 --> 00:24:17,800 Speaker 1: the acting and so on. So to answer your question, 435 00:24:18,160 --> 00:24:19,880 Speaker 1: do I start with the story or do I start 436 00:24:19,920 --> 00:24:24,280 Speaker 1: with the concept? A bit of both at first, so 437 00:24:24,520 --> 00:24:26,119 Speaker 1: you'd find a concept you would think it would be 438 00:24:26,119 --> 00:24:30,520 Speaker 1: great to find um and a really nice example of 439 00:24:30,800 --> 00:24:34,320 Speaker 1: I don't know, plan continuation bias. The plan continuation biases, 440 00:24:34,359 --> 00:24:37,760 Speaker 1: like when you have a plan and a little something 441 00:24:37,800 --> 00:24:39,320 Speaker 1: goes wrong makes it a bit more difficult, but you 442 00:24:39,359 --> 00:24:41,120 Speaker 1: kind of stick to it and something goes something else 443 00:24:41,119 --> 00:24:43,000 Speaker 1: goes wrong, and something else goes wrong, And we've all 444 00:24:43,000 --> 00:24:45,280 Speaker 1: had this way, like we've got some you know, we're 445 00:24:45,320 --> 00:24:47,800 Speaker 1: going to meet some friends, or we go to a 446 00:24:47,800 --> 00:24:51,240 Speaker 1: business meeting or something, and gradually more and more obstacles 447 00:24:51,760 --> 00:24:55,360 Speaker 1: accumulate and the plan gets ever more complicated and difficult, 448 00:24:56,359 --> 00:24:58,960 Speaker 1: but because it's happening bit by bit, you never take 449 00:24:59,000 --> 00:25:00,200 Speaker 1: that step back and go, hang on, this is a 450 00:25:00,280 --> 00:25:04,560 Speaker 1: ridiculous absurd I need a different plan. So sometimes you 451 00:25:04,600 --> 00:25:08,840 Speaker 1: have the concept. Sometimes you've got the story and you think, well, 452 00:25:08,880 --> 00:25:10,960 Speaker 1: this is a great story, but what's the what's the 453 00:25:11,000 --> 00:25:14,240 Speaker 1: psychological concept to illustrate, And often there's more than one, 454 00:25:14,960 --> 00:25:18,440 Speaker 1: and then you can choose. More Recently, we've now done 455 00:25:18,480 --> 00:25:22,720 Speaker 1: oh goodness, me probably getting on for I'm not sure, 456 00:25:22,720 --> 00:25:25,399 Speaker 1: maybe forty cautionary tales, and we're now we're releasing new 457 00:25:25,400 --> 00:25:30,359 Speaker 1: caution details every two weeks. Now. It's more story driven now, 458 00:25:31,600 --> 00:25:34,119 Speaker 1: because I find that that's that that gets you a 459 00:25:34,119 --> 00:25:38,040 Speaker 1: better result. It's easier to research um. And once you 460 00:25:38,119 --> 00:25:41,480 Speaker 1: have that library of psychological concept, if you have a 461 00:25:41,520 --> 00:25:43,800 Speaker 1: story of something going wrong, you can figure out why. 462 00:25:43,880 --> 00:25:46,359 Speaker 1: You can figure out a reason why to discuss. But 463 00:25:46,480 --> 00:25:49,800 Speaker 1: every now and then I still bump into some really 464 00:25:49,840 --> 00:25:53,800 Speaker 1: really cute psychological idea and I think, wow, I'm going 465 00:25:53,880 --> 00:25:56,439 Speaker 1: to wait until the story comes along that I can 466 00:25:56,480 --> 00:25:58,720 Speaker 1: hang that idea on because it's really nice. It will 467 00:25:58,760 --> 00:26:00,399 Speaker 1: be surprised to how easy it is to just like 468 00:26:00,880 --> 00:26:03,760 Speaker 1: research the idea and how many stories you will find 469 00:26:03,840 --> 00:26:06,840 Speaker 1: just by like a simple Google search of some concept 470 00:26:06,960 --> 00:26:10,080 Speaker 1: or some you know, psychological you know, construct or whatever, 471 00:26:10,119 --> 00:26:11,679 Speaker 1: and then they'll be you know, the Internet is a 472 00:26:11,680 --> 00:26:15,760 Speaker 1: beautiful place and things like Reddit are wonderful hunting grounds 473 00:26:15,760 --> 00:26:18,760 Speaker 1: for these kinds of tales. It really is. And sometimes 474 00:26:18,800 --> 00:26:21,640 Speaker 1: you'll find them mentioned in an academic article for example, 475 00:26:21,760 --> 00:26:24,560 Speaker 1: as you know, an example, and you'll look into it 476 00:26:24,840 --> 00:26:28,360 Speaker 1: and one of two things happens. Either you find that 477 00:26:28,800 --> 00:26:31,560 Speaker 1: actually the story is just an urban myth it never happened, 478 00:26:31,680 --> 00:26:34,679 Speaker 1: or they've got all kinds of important details wrong. The 479 00:26:34,720 --> 00:26:36,560 Speaker 1: other thing that sometimes happens, and that's when it gets 480 00:26:36,560 --> 00:26:39,879 Speaker 1: really fun, is where you go, oh, wow, you guys 481 00:26:40,000 --> 00:26:43,119 Speaker 1: totally buried the lead. There's so much to this story. 482 00:26:43,200 --> 00:26:46,760 Speaker 1: It's so fascinating. I can't believe that you just kind 483 00:26:46,760 --> 00:26:50,320 Speaker 1: of threw it away into sentences, because I can. I 484 00:26:50,359 --> 00:26:52,640 Speaker 1: can keep people entertained for forty minutes with this because 485 00:26:52,640 --> 00:26:57,560 Speaker 1: there's it's just so much detail, so amazing, so many twists. Yes, 486 00:26:58,200 --> 00:27:00,800 Speaker 1: and I would urge everyone to listen to especially I 487 00:27:00,800 --> 00:27:05,040 Speaker 1: think the Conningly Fairy story really is extremely strong, especially 488 00:27:05,040 --> 00:27:08,399 Speaker 1: when it comes to applying lessons we learned within that episode. 489 00:27:08,400 --> 00:27:11,680 Speaker 1: Two other things. I keep thinking about the snowballing lie 490 00:27:12,359 --> 00:27:15,320 Speaker 1: that that's at the heart of that story, and how 491 00:27:15,440 --> 00:27:18,840 Speaker 1: you can apply that to something like an alien abduction 492 00:27:18,920 --> 00:27:22,320 Speaker 1: story that maybe was told to one person or two 493 00:27:22,320 --> 00:27:25,080 Speaker 1: people for a very specific reason to you know, get 494 00:27:25,119 --> 00:27:27,840 Speaker 1: out of one situation or another as you're saying, like 495 00:27:28,080 --> 00:27:31,880 Speaker 1: this one tiny thing to escape consequences of whatever action, 496 00:27:32,400 --> 00:27:35,480 Speaker 1: and then it you can't tell the truth because it's 497 00:27:35,520 --> 00:27:38,720 Speaker 1: become too big. Um. And I just wonder if I 498 00:27:38,760 --> 00:27:40,960 Speaker 1: think there, I think there's so many concepts within the 499 00:27:41,000 --> 00:27:44,880 Speaker 1: world of conspiracy theories in particular, that we can take 500 00:27:44,920 --> 00:27:48,680 Speaker 1: that and apply it to Yeah. I mean, I'm currently 501 00:27:49,280 --> 00:27:53,160 Speaker 1: very interested in in urban myths and which of them 502 00:27:53,680 --> 00:27:57,800 Speaker 1: have something really important at the heart of them, and 503 00:27:57,840 --> 00:28:00,960 Speaker 1: which are in fact is completely allusiveate. So I don't 504 00:28:00,960 --> 00:28:03,200 Speaker 1: want to do too many spoilers because I'm still researching 505 00:28:03,200 --> 00:28:07,320 Speaker 1: the story, but I'm looking into the poisoned candy myth. 506 00:28:08,520 --> 00:28:13,000 Speaker 1: The Halloween parents are told, you know, some child will 507 00:28:13,119 --> 00:28:17,359 Speaker 1: die tonight in America because a stranger has poisoned their candy. 508 00:28:17,440 --> 00:28:22,119 Speaker 1: That will happen, and that is almost completely false, but 509 00:28:22,200 --> 00:28:28,600 Speaker 1: it's not quite false. And the exception to that is 510 00:28:28,600 --> 00:28:30,879 Speaker 1: actually one of the most horrendous things I've ever researched 511 00:28:31,080 --> 00:28:34,240 Speaker 1: in my life for cautionary tales. But even then, it's 512 00:28:34,280 --> 00:28:36,399 Speaker 1: not the story that people think it is. And the 513 00:28:36,480 --> 00:28:37,879 Speaker 1: deeper you go and the more you look at it, 514 00:28:37,920 --> 00:28:41,920 Speaker 1: the more you realize people just people misunderstood when when 515 00:28:41,920 --> 00:28:44,400 Speaker 1: this story hit about this was a child who died. 516 00:28:45,240 --> 00:28:48,000 Speaker 1: When this story hit the headlines, everybody thought they knew 517 00:28:48,120 --> 00:28:52,040 Speaker 1: what they were looking at. And actually, wait a week 518 00:28:52,400 --> 00:28:54,960 Speaker 1: and the truth comes out. But in a week's time, 519 00:28:54,960 --> 00:28:58,080 Speaker 1: no one's paying any attention. And it's it's surprising that 520 00:28:58,080 --> 00:28:59,920 Speaker 1: that's a very similar actually to the dungeons and drag 521 00:29:00,440 --> 00:29:03,680 Speaker 1: cautionary tales, the story that everyone told and everyone told, 522 00:29:03,720 --> 00:29:07,160 Speaker 1: and everyone told. It turns out there's absolutely nothing to 523 00:29:07,160 --> 00:29:11,680 Speaker 1: do with what really happened at all. But people remember 524 00:29:11,760 --> 00:29:13,760 Speaker 1: the fake story and they don't sit around for the 525 00:29:13,800 --> 00:29:16,840 Speaker 1: reality because the reality is never as fun. Let's pause 526 00:29:16,880 --> 00:29:19,720 Speaker 1: here for a word from our sponsor, and we'll return 527 00:29:19,840 --> 00:29:29,760 Speaker 1: with more from Tim Harford. And we're back with Tim Harford. 528 00:29:30,560 --> 00:29:35,360 Speaker 1: Let's turn the page here to uh the idea of conspiracies, 529 00:29:35,400 --> 00:29:39,719 Speaker 1: conspiracy theory, the idea of that grain of truth and 530 00:29:39,760 --> 00:29:44,920 Speaker 1: that sort of uh, cumulative pearl of bs and malarkey 531 00:29:45,000 --> 00:29:47,920 Speaker 1: that people kind that people love. We love it so much, right, 532 00:29:48,200 --> 00:29:51,840 Speaker 1: it's cognitive. Oh, mommy, I want to spend some time 533 00:29:51,880 --> 00:29:56,640 Speaker 1: exploring an article you wrote for the Atlantic in what 534 00:29:56,760 --> 00:30:02,240 Speaker 1: conspiracy theorists don't believe. And I was profoundly into this 535 00:30:02,520 --> 00:30:05,520 Speaker 1: and realized that we were all very much on the 536 00:30:05,560 --> 00:30:10,760 Speaker 1: same page when I saw this examination, this very empathetic 537 00:30:10,800 --> 00:30:14,680 Speaker 1: examination of how we can talk our loved ones back 538 00:30:14,760 --> 00:30:18,680 Speaker 1: from that cognitive brink In there too, you you draw 539 00:30:18,760 --> 00:30:22,080 Speaker 1: a distinction that a lot of people don't think about 540 00:30:22,160 --> 00:30:26,640 Speaker 1: as often as they perhaps should, a distinction between excessive 541 00:30:26,720 --> 00:30:30,560 Speaker 1: doubt and excessive belief. Could you tell us a little 542 00:30:30,680 --> 00:30:34,240 Speaker 1: more about the distinction here? Also, folks, you can read 543 00:30:34,240 --> 00:30:36,600 Speaker 1: the article in full right now, but listen to the 544 00:30:36,600 --> 00:30:42,160 Speaker 1: rest of the episode. So this started to interest me 545 00:30:42,280 --> 00:30:46,280 Speaker 1: as I was working on the Data Detective, because everybody 546 00:30:46,440 --> 00:30:49,760 Speaker 1: I spoke to was was like, Oh, you're writing a 547 00:30:49,760 --> 00:30:51,960 Speaker 1: book about statistics. That's great. I mean, it's not really 548 00:30:51,960 --> 00:30:53,880 Speaker 1: a book about statistics. It's a book about how to 549 00:30:53,920 --> 00:30:56,920 Speaker 1: think clearly, and statistics are a tool to help you. 550 00:30:57,440 --> 00:31:00,880 Speaker 1: But as people thought I was writing this book about statistics, 551 00:31:01,080 --> 00:31:04,360 Speaker 1: they kept saying, Oh, that's great. You're going to tell 552 00:31:04,400 --> 00:31:08,880 Speaker 1: people that they shouldn't believe all these fake statistics. And 553 00:31:08,880 --> 00:31:10,840 Speaker 1: I was like, yeah, that is partly what I'm going 554 00:31:10,880 --> 00:31:15,560 Speaker 1: to say. But if you just sit there disbelieving everything 555 00:31:16,160 --> 00:31:20,520 Speaker 1: you think it's all fake. Then where do you end up? 556 00:31:20,680 --> 00:31:23,120 Speaker 1: You end up in a very weird place. It feels 557 00:31:23,680 --> 00:31:26,640 Speaker 1: kind of smart and kind of savvy to you know, 558 00:31:26,680 --> 00:31:28,600 Speaker 1: not believe what you're told here and not believe the 559 00:31:28,640 --> 00:31:31,520 Speaker 1: spin here, or to say, oh, that's just the kind 560 00:31:31,520 --> 00:31:34,160 Speaker 1: of the mainstream media or whatever. It feels smart, but 561 00:31:34,240 --> 00:31:37,000 Speaker 1: it can take you to some strange places. And when 562 00:31:37,040 --> 00:31:43,880 Speaker 1: I looked at what was happening with, for example, the 563 00:31:43,680 --> 00:31:48,600 Speaker 1: you know, the Capital riots, the mainstream narrative about about 564 00:31:48,640 --> 00:31:52,840 Speaker 1: the people who invaded the capital was these are people 565 00:31:52,840 --> 00:31:56,960 Speaker 1: who believe all kinds of crazy stuff that's not true. Well, 566 00:31:57,000 --> 00:31:59,320 Speaker 1: you could characterize them in that way, but I thought 567 00:31:59,320 --> 00:32:03,160 Speaker 1: it was much more or it helped me much more understand. 568 00:32:03,560 --> 00:32:07,400 Speaker 1: These are people who have decided to disbelieve all kinds 569 00:32:07,440 --> 00:32:11,000 Speaker 1: of things. They've disbelieved what the New York Times is 570 00:32:11,040 --> 00:32:15,200 Speaker 1: telling them, they disbelieve what CNN is telling them, disbelieve 571 00:32:15,240 --> 00:32:18,880 Speaker 1: what the judiciary are telling them. They disbelieve what at 572 00:32:18,920 --> 00:32:23,400 Speaker 1: the time mainstream Republican politicians were telling them. Although many 573 00:32:23,400 --> 00:32:25,960 Speaker 1: of those politicians have changed their views, this is this 574 00:32:26,000 --> 00:32:29,120 Speaker 1: is a group of people who don't trust anything. They 575 00:32:29,160 --> 00:32:32,280 Speaker 1: don't believe any of these things Now then it then 576 00:32:32,280 --> 00:32:34,959 Speaker 1: gets you too well, and they believe some other stuff. 577 00:32:35,560 --> 00:32:38,560 Speaker 1: But much more important to understand the disbelief, to understand 578 00:32:38,600 --> 00:32:43,560 Speaker 1: that the distrust, than to focus on what these people 579 00:32:43,680 --> 00:32:46,080 Speaker 1: ended up believing well and and and what kind of 580 00:32:46,120 --> 00:32:49,680 Speaker 1: power and influences that take to so that level of 581 00:32:49,720 --> 00:32:52,960 Speaker 1: disbelief to say, believe me when I say, do not 582 00:32:53,160 --> 00:32:57,560 Speaker 1: believe there's other you know that I have differentiated from 583 00:32:57,640 --> 00:32:59,760 Speaker 1: my word. You know, what I'm saying is the truth 584 00:32:59,800 --> 00:33:02,880 Speaker 1: and they're saying is not. And it creates this kind 585 00:33:02,920 --> 00:33:06,840 Speaker 1: of us versus them mentality that if you let it 586 00:33:06,880 --> 00:33:10,800 Speaker 1: go too far unchecked, it can erupt into violence in 587 00:33:10,840 --> 00:33:14,080 Speaker 1: the streets. Um And it does go unchecked, because that's 588 00:33:14,080 --> 00:33:15,920 Speaker 1: sort of what it's designed to do, isn't it. It's 589 00:33:15,960 --> 00:33:20,800 Speaker 1: designed it's like the weaponized rhetorical version of all those 590 00:33:20,800 --> 00:33:23,320 Speaker 1: clickbata articles that are designed to make you a little upset. 591 00:33:23,760 --> 00:33:26,440 Speaker 1: This is designed to make you act out. You know. 592 00:33:26,600 --> 00:33:29,080 Speaker 1: This is sort of the culmination of all that other stuff, right, 593 00:33:29,360 --> 00:33:32,160 Speaker 1: And it goes back a long way. So the use 594 00:33:32,200 --> 00:33:35,680 Speaker 1: of disbelief as a weapon goes back well, at least 595 00:33:35,680 --> 00:33:38,800 Speaker 1: to the cigarette industry. So I described this in in 596 00:33:39,360 --> 00:33:43,080 Speaker 1: the data detective, the evidence comes out cigarettes are very dangerous, 597 00:33:43,640 --> 00:33:46,200 Speaker 1: dramatically increased risk of lung cancer, and new evidence starts 598 00:33:46,240 --> 00:33:48,520 Speaker 1: coming in and heart disease and all kinds of other stuff. 599 00:33:49,480 --> 00:33:51,560 Speaker 1: That's what the science is starting to show. But it's 600 00:33:51,600 --> 00:33:54,120 Speaker 1: early days because we don't have great evidence. But that's 601 00:33:54,160 --> 00:33:58,760 Speaker 1: what it's looking like. What's the response of the cigarette companies. Well, 602 00:33:58,800 --> 00:34:03,040 Speaker 1: they could say, don't believe this stuff. You know, it's 603 00:34:03,040 --> 00:34:08,160 Speaker 1: it's untrue. Trust us. We are giving you safe products, 604 00:34:08,520 --> 00:34:10,200 Speaker 1: you know, have we ever let you down? And they 605 00:34:10,200 --> 00:34:15,400 Speaker 1: realized that's not gonna work. Instead they just work on doubt. Well, yeah, 606 00:34:15,600 --> 00:34:18,239 Speaker 1: isn't it interesting These scientists they haven't quite got their 607 00:34:18,280 --> 00:34:20,920 Speaker 1: story all lined up, have they. They disagree about some 608 00:34:20,960 --> 00:34:23,560 Speaker 1: interesting stuff, Like these people are saying this thing, these 609 00:34:23,560 --> 00:34:26,319 Speaker 1: people are saying this other thing. Shouldn't we do some 610 00:34:26,360 --> 00:34:29,239 Speaker 1: more research, shouldn't we shouldn't we dig a bit deeper? 611 00:34:29,239 --> 00:34:31,480 Speaker 1: Shouldn't we wait until the full facts are out? And 612 00:34:31,520 --> 00:34:33,960 Speaker 1: of course all those things they sound really reasonable, and 613 00:34:34,000 --> 00:34:37,560 Speaker 1: in fact they kind of are really reasonable, except you 614 00:34:37,600 --> 00:34:41,800 Speaker 1: take them to the extreme conclusion, and the extreme conclusion 615 00:34:41,840 --> 00:34:45,080 Speaker 1: is no one knows anything about anything, and therefore keep 616 00:34:45,120 --> 00:34:49,560 Speaker 1: smoking that's and it's incredibly effective, and it's been so 617 00:34:49,640 --> 00:34:55,000 Speaker 1: interesting to see that strategy weaponized and continued in the 618 00:34:55,040 --> 00:34:59,120 Speaker 1: modern world and so many different people trying to sell 619 00:34:59,160 --> 00:35:02,960 Speaker 1: so many different ideas, is political ideologists, whatever, they'll focus 620 00:35:03,040 --> 00:35:06,120 Speaker 1: first on doubt. Can you believe what you're being told? 621 00:35:07,000 --> 00:35:09,480 Speaker 1: Can you can you believe what the mainstream media are 622 00:35:09,520 --> 00:35:12,560 Speaker 1: telling you? And it's it's effective partly because well, you know, 623 00:35:12,719 --> 00:35:15,000 Speaker 1: sometimes you shouldn't believe what you're told. Sometimes you shouldn't 624 00:35:15,000 --> 00:35:18,160 Speaker 1: believe the mainstream media, but it can if you overdo 625 00:35:18,239 --> 00:35:20,360 Speaker 1: it. It It gets you to a very sort of corrosive place. 626 00:35:20,560 --> 00:35:22,880 Speaker 1: But also, like I mean, the nature of research is 627 00:35:23,160 --> 00:35:26,360 Speaker 1: you know, disagreement. The nature of research is this scientist 628 00:35:26,400 --> 00:35:28,239 Speaker 1: says this, this scientist is this. It takes a year 629 00:35:28,360 --> 00:35:31,120 Speaker 1: sometimes to prove out, you know, which parts are actually 630 00:35:31,280 --> 00:35:33,400 Speaker 1: the truth. And it's the same with the media. And 631 00:35:33,440 --> 00:35:37,000 Speaker 1: now we're in this super cluttered space that's very confusing 632 00:35:37,080 --> 00:35:40,560 Speaker 1: and difficult. It's it's easier to just disbelieve than it 633 00:35:40,680 --> 00:35:43,320 Speaker 1: is to pick out the right pieces over time yourself. 634 00:35:43,360 --> 00:35:46,279 Speaker 1: I think the motto of the Royal Society, one of 635 00:35:46,320 --> 00:35:49,320 Speaker 1: the oldest scientific societists in the world, is nullius in 636 00:35:49,440 --> 00:35:54,719 Speaker 1: wherever take nobody's word for it, just you need to 637 00:35:54,760 --> 00:35:57,439 Speaker 1: prove to your own satisfaction, and that is of course 638 00:35:57,440 --> 00:36:01,880 Speaker 1: how science works. UM. But you can't go through the 639 00:36:01,920 --> 00:36:05,640 Speaker 1: world basically saying I'm not going to believe anything anybody 640 00:36:05,680 --> 00:36:08,480 Speaker 1: tells me about anything at all until I personally can 641 00:36:08,600 --> 00:36:11,960 Speaker 1: verify it. You can't function like that. It works for 642 00:36:12,040 --> 00:36:17,360 Speaker 1: scientists in the science that they're investigating, UM, it can't 643 00:36:17,360 --> 00:36:20,399 Speaker 1: be a universal strategy for life. You have to pick 644 00:36:20,440 --> 00:36:24,080 Speaker 1: your battles. What am I going to focus more curiosity on? 645 00:36:24,080 --> 00:36:26,359 Speaker 1: What am I going to pay more attention to? And 646 00:36:26,360 --> 00:36:28,360 Speaker 1: when am I just going to pick somebody that I 647 00:36:28,400 --> 00:36:33,120 Speaker 1: will believe? And that is so beautifully put. I think 648 00:36:33,160 --> 00:36:37,280 Speaker 1: this is an exploration that has to be continuing journey 649 00:36:37,320 --> 00:36:40,879 Speaker 1: for people, especially when you're not a scientist, and when 650 00:36:40,880 --> 00:36:44,840 Speaker 1: you live in an age of endless inundation right of 651 00:36:44,960 --> 00:36:49,799 Speaker 1: information that grabs your attention and tells you again to 652 00:36:49,880 --> 00:36:54,000 Speaker 1: get angry or to have an emotional reaction. Um, it's 653 00:36:54,080 --> 00:36:57,800 Speaker 1: quite as successful strategy as as you've established both in 654 00:36:57,840 --> 00:37:02,120 Speaker 1: the Data Detective and in other work. But before we 655 00:37:02,160 --> 00:37:05,560 Speaker 1: move on from from the world of conspiracy term, I 656 00:37:05,640 --> 00:37:07,200 Speaker 1: have to ask you, and I know there's a little 657 00:37:07,239 --> 00:37:10,920 Speaker 1: bit of a silly question. Do you have a favorite 658 00:37:10,960 --> 00:37:14,400 Speaker 1: conspiracy theory, by which I mean not one you necessarily believe, 659 00:37:14,800 --> 00:37:19,160 Speaker 1: but one that one that just is fascinating to you. Well, 660 00:37:20,080 --> 00:37:21,920 Speaker 1: here's one. I'm not even sure you'll have heard of 661 00:37:21,960 --> 00:37:26,120 Speaker 1: this conspiracy theory, although I know you guys have heard 662 00:37:26,120 --> 00:37:31,200 Speaker 1: a lot Brendall sham Forest. Okay, So do you remember 663 00:37:32,760 --> 00:37:39,239 Speaker 1: the reported sex attacks in Cologne in I think New 664 00:37:39,320 --> 00:37:45,920 Speaker 1: Year's Eve beginning of UM, there were a lot of 665 00:37:46,040 --> 00:37:53,720 Speaker 1: media reports that men of North African heritage we're roaming 666 00:37:53,760 --> 00:37:57,879 Speaker 1: around the center of Cologne and just attacking women, uh, 667 00:37:57,960 --> 00:38:00,759 Speaker 1: sexually assaulting women, and it's got a lot of attention. 668 00:38:00,960 --> 00:38:03,880 Speaker 1: People are horrified. Obviously, people are horrified. There's this whip 669 00:38:04,200 --> 00:38:10,080 Speaker 1: for UM people who are kind of liberal. There was 670 00:38:10,160 --> 00:38:13,759 Speaker 1: this weird kind of tug of war because you want 671 00:38:13,800 --> 00:38:17,400 Speaker 1: to take sexual assault on women extremely seriously, but also 672 00:38:17,440 --> 00:38:21,000 Speaker 1: you're very suspicious of reports of people with brown skin 673 00:38:21,120 --> 00:38:23,480 Speaker 1: doing bad things. That feels like it's not politically correct. 674 00:38:23,520 --> 00:38:25,600 Speaker 1: So people didn't know what to believe. There's a lot 675 00:38:25,600 --> 00:38:27,759 Speaker 1: of confusion, there's a lot of angst. It was a 676 00:38:27,880 --> 00:38:31,560 Speaker 1: very weird story and then it just kind of every 677 00:38:31,600 --> 00:38:33,680 Speaker 1: wanting to forget about it. I never really saw any 678 00:38:33,680 --> 00:38:38,640 Speaker 1: follow up reporting. So that's the that's the story. The 679 00:38:38,719 --> 00:38:45,520 Speaker 1: conspiracy theory is that the that was in some respects 680 00:38:46,640 --> 00:38:50,440 Speaker 1: Russian disinformation. I have no evidence that that was Russian 681 00:38:50,600 --> 00:38:56,440 Speaker 1: disinformation other than one person who has had some experience 682 00:38:56,440 --> 00:39:01,399 Speaker 1: of Russian disinformation wants talk to me. Wandered about that 683 00:39:02,160 --> 00:39:04,840 Speaker 1: because it was so strange, It came from nowhere, It 684 00:39:04,960 --> 00:39:07,080 Speaker 1: was very sensitive in its timing. It was before the 685 00:39:07,080 --> 00:39:11,719 Speaker 1: Brexit referendum in the UK and I believe before an 686 00:39:11,719 --> 00:39:16,120 Speaker 1: important election in Germany. It was you know, court got 687 00:39:16,360 --> 00:39:20,359 Speaker 1: all this attention. It just seemed odd, like, what does 688 00:39:20,400 --> 00:39:23,360 Speaker 1: that happen? That seems strange, and there's never seems to 689 00:39:23,400 --> 00:39:25,399 Speaker 1: have happened ever before. It never seems to have happened 690 00:39:25,400 --> 00:39:28,759 Speaker 1: ever ever again, So then there was the conspiracy theory 691 00:39:28,840 --> 00:39:33,719 Speaker 1: is that somehow the Kremlin paid some young men to 692 00:39:33,840 --> 00:39:36,160 Speaker 1: do some stuff. I mean not saying that this didn't happen, 693 00:39:36,239 --> 00:39:39,279 Speaker 1: but this was in some way organized. Now that is 694 00:39:39,320 --> 00:39:42,120 Speaker 1: a conspiracy theory that I find why the Kremlin and 695 00:39:42,120 --> 00:39:44,520 Speaker 1: not the right wing government like like of of Britain 696 00:39:44,719 --> 00:39:46,520 Speaker 1: seems more like it would be a way of pushing 697 00:39:46,520 --> 00:39:49,000 Speaker 1: the England for the English kind of narrative, like like, 698 00:39:49,040 --> 00:39:51,840 Speaker 1: what's the why would the Kremlin have been involved? Like 699 00:39:53,280 --> 00:39:56,040 Speaker 1: I mean, I mean, Cologne is in Germany, So the 700 00:39:56,760 --> 00:39:59,719 Speaker 1: for a British faction to get involved, would you would 701 00:39:59,760 --> 00:40:02,360 Speaker 1: you would thought they'd arranged for it to happen in um, 702 00:40:02,440 --> 00:40:05,880 Speaker 1: I know, Luton instead some some British city rather than 703 00:40:06,000 --> 00:40:09,719 Speaker 1: German city. Also, I just have more belief in the 704 00:40:09,800 --> 00:40:13,080 Speaker 1: Kremlin's ability to organized this kind of thing that I 705 00:40:13,200 --> 00:40:17,040 Speaker 1: do in any British politicians ability. But let me just 706 00:40:17,080 --> 00:40:22,000 Speaker 1: to be serious, I don't believe this conspiracy theory. And 707 00:40:22,080 --> 00:40:24,800 Speaker 1: yet it's I'm not the kind of person who normally 708 00:40:24,800 --> 00:40:27,359 Speaker 1: does believe in conspiracy theories. I tend to just go, oh, 709 00:40:27,400 --> 00:40:30,120 Speaker 1: you know, that's a really kind of compelling story, but 710 00:40:31,000 --> 00:40:35,000 Speaker 1: surely not. But this is one that I can't I 711 00:40:35,000 --> 00:40:37,720 Speaker 1: can't get out of my head. But I've seen no evidence, 712 00:40:37,920 --> 00:40:40,640 Speaker 1: and so I think I have to say that the 713 00:40:40,680 --> 00:40:44,880 Speaker 1: most plausible explanation probably is that the kind of horrible 714 00:40:44,920 --> 00:40:48,040 Speaker 1: thing that was reported just happened, and it was fairly spontaneous, 715 00:40:48,560 --> 00:40:51,200 Speaker 1: and thank goodness, it doesn't usually happen. Okay, we'll take 716 00:40:51,200 --> 00:40:52,880 Speaker 1: a quick pause and hear a word from one of 717 00:40:52,880 --> 00:41:02,280 Speaker 1: our sponsors, and then we'll be back with more from Tim. 718 00:41:02,320 --> 00:41:06,239 Speaker 1: And we're back. Tim. I want to just take again, 719 00:41:06,280 --> 00:41:08,279 Speaker 1: take some of the same logic that you have going 720 00:41:08,320 --> 00:41:10,600 Speaker 1: on there and apply it to something that we've all 721 00:41:10,640 --> 00:41:13,400 Speaker 1: been dealing with for gosh, it's going to be three 722 00:41:13,480 --> 00:41:17,840 Speaker 1: years now, it's over three years um, the reaction, the 723 00:41:17,880 --> 00:41:23,759 Speaker 1: public reaction to a mandated vaccination. You know, we get 724 00:41:23,800 --> 00:41:26,120 Speaker 1: a ton of emails and voicemails and listeners calling in 725 00:41:26,160 --> 00:41:27,960 Speaker 1: and giving us their opinions and how they feel and 726 00:41:28,000 --> 00:41:31,920 Speaker 1: why they will or won't get vaccinated, and their fears 727 00:41:32,040 --> 00:41:34,520 Speaker 1: or their complete lack of fear when it comes to 728 00:41:34,560 --> 00:41:37,799 Speaker 1: a pandemic. What have you seen or how have you 729 00:41:38,040 --> 00:41:44,640 Speaker 1: maybe analyzed the public reaction to a mandated vaccination, especially 730 00:41:44,640 --> 00:41:48,839 Speaker 1: in your podcast how to Vaccinate the World, Yeah, the World, 731 00:41:48,880 --> 00:41:52,080 Speaker 1: which I did for for the BBC, and we did 732 00:41:52,120 --> 00:41:56,279 Speaker 1: that weekly for several months, starting with the announcement of 733 00:41:56,360 --> 00:42:00,320 Speaker 1: the first the FISA trial results. So when it first 734 00:42:00,360 --> 00:42:04,080 Speaker 1: became clear that there there might well be a vaccine approved, 735 00:42:04,280 --> 00:42:07,080 Speaker 1: and it looked it looked pretty good, but it was 736 00:42:07,080 --> 00:42:09,160 Speaker 1: all very early day. So how would you know who 737 00:42:09,200 --> 00:42:11,359 Speaker 1: would take this and how would it work and how 738 00:42:11,400 --> 00:42:13,719 Speaker 1: safe would it be and how would it be manufactured 739 00:42:13,719 --> 00:42:15,560 Speaker 1: and how quickly could we get this into what people's 740 00:42:15,640 --> 00:42:18,640 Speaker 1: arms and etcetera. So all of those issues we discussed 741 00:42:19,040 --> 00:42:20,920 Speaker 1: UM and it was such a privilege. I just met 742 00:42:20,960 --> 00:42:24,719 Speaker 1: so many people who really thought so deeply about the subject. 743 00:42:25,880 --> 00:42:29,960 Speaker 1: So mandated vaccination. I find it interesting that that's the 744 00:42:30,200 --> 00:42:35,000 Speaker 1: way that you introduced the topic because in the UK 745 00:42:35,719 --> 00:42:40,919 Speaker 1: the vaccine isn't mandatory, and I've crossed borders a few 746 00:42:40,960 --> 00:42:46,720 Speaker 1: times recently, flown to various other European countries and mostly 747 00:42:46,960 --> 00:42:49,120 Speaker 1: it's easier to cross the border if you can show 748 00:42:49,160 --> 00:42:52,799 Speaker 1: proof of vaccination. But it's not mandatory. You know, you 749 00:42:52,960 --> 00:42:55,160 Speaker 1: have to show negative tests and so on, which is 750 00:42:55,480 --> 00:42:57,279 Speaker 1: just more of a hassle. It's super easy to show 751 00:42:57,320 --> 00:43:01,520 Speaker 1: you've that you've been vaccinated. And absolutely, I'm sorry for 752 00:43:01,560 --> 00:43:05,880 Speaker 1: even putting it that way. I think that's the perhaps 753 00:43:05,920 --> 00:43:09,120 Speaker 1: the perception that is out there that exists and the 754 00:43:09,120 --> 00:43:12,440 Speaker 1: way it's spoken about, especially in UM you know, on 755 00:43:12,560 --> 00:43:15,720 Speaker 1: places like read it and in places where uh maybe 756 00:43:15,719 --> 00:43:18,920 Speaker 1: fears about the vaccine are discussed. Yeah, so it's but 757 00:43:18,960 --> 00:43:20,840 Speaker 1: it is interesting and you know, there is a school 758 00:43:20,840 --> 00:43:22,640 Speaker 1: of thought that says, on it, you should. You should. 759 00:43:23,160 --> 00:43:27,239 Speaker 1: It's a public health issue. It's like drink driving. You know, 760 00:43:27,400 --> 00:43:30,080 Speaker 1: you're not allowed to wander around unvaccinated, just like you're 761 00:43:30,080 --> 00:43:31,920 Speaker 1: not allowed to get in your car if you've been drinking. 762 00:43:31,960 --> 00:43:36,680 Speaker 1: I mean, there's an argument, but it doesn't seem just purely. 763 00:43:36,719 --> 00:43:38,080 Speaker 1: I mean, who cares what I think. But it doesn't 764 00:43:38,080 --> 00:43:42,799 Speaker 1: seem necessary. Right. The vaccine seems very effective at protecting 765 00:43:42,800 --> 00:43:47,360 Speaker 1: you from harm. It doesn't seem as effective as we 766 00:43:47,440 --> 00:43:52,120 Speaker 1: hoped at preventing transmission. And therefore, you know, there's a 767 00:43:52,160 --> 00:43:54,399 Speaker 1: strong case that it's an individual decision. I mean, there's 768 00:43:54,400 --> 00:43:57,080 Speaker 1: always got to be a presumption of an individual decision anyway. 769 00:43:57,080 --> 00:44:00,440 Speaker 1: You would always you want really good ever before you 770 00:44:00,440 --> 00:44:04,040 Speaker 1: mandated anything at all about anything. But you know, the 771 00:44:04,120 --> 00:44:06,440 Speaker 1: vaccine protects you, it probably doesn't protect other people as 772 00:44:06,520 --> 00:44:10,280 Speaker 1: much as we hoped. So it's not like the smallpox vaccine. 773 00:44:10,320 --> 00:44:12,760 Speaker 1: Was the smallpox vaccine, You're like, hey, do we actually 774 00:44:12,800 --> 00:44:16,839 Speaker 1: could eradicate this disease forever? We just need to make 775 00:44:16,880 --> 00:44:20,200 Speaker 1: sure that everybody who is anywhere close to being exposed 776 00:44:20,200 --> 00:44:24,480 Speaker 1: to smallpox has that has the vaccine, then you might say, well, 777 00:44:24,920 --> 00:44:28,120 Speaker 1: maybe maybe there's a reason to to mandate. But for 778 00:44:28,360 --> 00:44:31,560 Speaker 1: covid um, it's stuff that it's something that people have 779 00:44:31,560 --> 00:44:34,480 Speaker 1: talked about a lot. But even in China, where they 780 00:44:34,520 --> 00:44:36,719 Speaker 1: have a problem because they don't have enough up there there, 781 00:44:36,760 --> 00:44:39,879 Speaker 1: elderly population is not very well vaccinated. They everyone who's 782 00:44:39,920 --> 00:44:44,040 Speaker 1: young who is probably not at serious risk from covid 783 00:44:45,040 --> 00:44:48,120 Speaker 1: unless they're very unlucky, they're all vaccinated. The elderly people 784 00:44:48,120 --> 00:44:50,800 Speaker 1: are not vaccinated. You would have thought the Chinese government 785 00:44:51,080 --> 00:44:53,600 Speaker 1: would get around to mandating it, But even the Chinese, 786 00:44:54,400 --> 00:44:58,920 Speaker 1: unless I've missed something, have not mandated it. So so 787 00:44:59,040 --> 00:45:01,680 Speaker 1: what interests me more is this question of well, first 788 00:45:01,680 --> 00:45:03,600 Speaker 1: of all, what evidence can we gather, how safe is 789 00:45:03,640 --> 00:45:06,640 Speaker 1: the vaccine, how effect how effective is the vaccine? And 790 00:45:06,680 --> 00:45:09,440 Speaker 1: then how do we how do we have conversations about 791 00:45:09,520 --> 00:45:14,839 Speaker 1: it um and talking to people who who thought think 792 00:45:14,880 --> 00:45:16,960 Speaker 1: about this a lot. The first thing to recognize is 793 00:45:17,000 --> 00:45:19,520 Speaker 1: people are hesitant about having the vaccine for lots and 794 00:45:19,560 --> 00:45:22,080 Speaker 1: lots of different reasons. So for some people it's a 795 00:45:22,120 --> 00:45:27,200 Speaker 1: religious objection. For some people it's that there's fear of needles, 796 00:45:27,239 --> 00:45:29,520 Speaker 1: like they want it, but they really it's really scared 797 00:45:29,560 --> 00:45:34,120 Speaker 1: of the needle. Some people think that it's a pharmaceutical conspiracy, 798 00:45:34,520 --> 00:45:38,279 Speaker 1: the vaccine is not safe. Um. Some people just want 799 00:45:38,280 --> 00:45:42,160 Speaker 1: to wait for more data. People just have different kinds 800 00:45:42,160 --> 00:45:46,560 Speaker 1: of objection, and so to lump everybody together as anti 801 00:45:46,600 --> 00:45:50,960 Speaker 1: vaxes or vaccine hesitant or whatever, these labels never really help. 802 00:45:51,600 --> 00:45:55,160 Speaker 1: And if you're if you have a loved one and 803 00:45:55,320 --> 00:45:59,000 Speaker 1: you would like them to get vaccinated, UM, then the 804 00:45:59,040 --> 00:46:01,600 Speaker 1: conversation you need to have with them has got to 805 00:46:01,640 --> 00:46:04,440 Speaker 1: involve a lot of listening to what are the what 806 00:46:04,480 --> 00:46:06,920 Speaker 1: are their reasons for? I mean, this is not just true. 807 00:46:06,920 --> 00:46:10,279 Speaker 1: A vaccinations is true anybody, anybody you disagree with. If 808 00:46:10,320 --> 00:46:13,640 Speaker 1: you disagree with someone, ask a couple of questions and 809 00:46:13,680 --> 00:46:16,719 Speaker 1: then shut up and just let them explain themselves to you. 810 00:46:17,000 --> 00:46:19,319 Speaker 1: But shouldn't it be a simpler conversation kind of like 811 00:46:19,320 --> 00:46:21,880 Speaker 1: how you're describing it a very matter of factly, and 812 00:46:21,960 --> 00:46:24,840 Speaker 1: yet it's not um And do you think that's because 813 00:46:24,880 --> 00:46:27,319 Speaker 1: of how it's been used as a talking point and 814 00:46:27,400 --> 00:46:30,920 Speaker 1: kind of politicized the point of weaponization to create this 815 00:46:31,080 --> 00:46:32,920 Speaker 1: discord in the same ways that we've kind of been 816 00:46:32,920 --> 00:46:35,839 Speaker 1: talking about throughout the episode. Yeah, that doesn't help. There's 817 00:46:35,960 --> 00:46:40,360 Speaker 1: a really interesting essay by Dan Kahan, who's a psychologist 818 00:46:40,400 --> 00:46:43,600 Speaker 1: and law professor at Yale, and he studies two different vaccines. 819 00:46:43,600 --> 00:46:46,400 Speaker 1: This is all pre COVID, so it's kind of interesting, 820 00:46:46,560 --> 00:46:50,960 Speaker 1: like a time capsule. He studied the hb V and 821 00:46:51,200 --> 00:46:56,600 Speaker 1: HPV vaccines. HPV as heptitis b. HPV is human paploma virus, 822 00:46:56,920 --> 00:47:00,920 Speaker 1: so this is the prevents the virus that can lead 823 00:47:00,960 --> 00:47:05,680 Speaker 1: to cervical cancer. And what he found was these are 824 00:47:05,719 --> 00:47:07,839 Speaker 1: two vaccines that are basically they even kind of sound 825 00:47:07,920 --> 00:47:10,800 Speaker 1: the same. Where HBV you get it. If your doctor 826 00:47:10,880 --> 00:47:13,879 Speaker 1: says you should have the heap BE vaccine, you get 827 00:47:13,920 --> 00:47:15,920 Speaker 1: the heap V vaccine. You just take a cue from 828 00:47:15,920 --> 00:47:21,160 Speaker 1: your physician, whereas the HPV vaccine you take a cue 829 00:47:21,200 --> 00:47:25,359 Speaker 1: from your congressman. But it's a polite, completely political thing. 830 00:47:25,920 --> 00:47:30,040 Speaker 1: And it's partly because it's associated with teenage sexuality. It's 831 00:47:30,960 --> 00:47:35,560 Speaker 1: the virus is sexually transmitted. You're giving this vaccine to teenagers. 832 00:47:35,800 --> 00:47:38,040 Speaker 1: It's kind of a sensitive topic. What does that imply 833 00:47:38,120 --> 00:47:40,400 Speaker 1: about teenagers? Well, I mean, all it really implies is 834 00:47:40,440 --> 00:47:43,600 Speaker 1: that one day most teenagers will have sex one day, 835 00:47:43,680 --> 00:47:45,560 Speaker 1: so you might as well vaccinate them before they start. 836 00:47:45,840 --> 00:47:49,520 Speaker 1: But it's sensitive, and some you know, the companies that 837 00:47:49,520 --> 00:47:51,840 Speaker 1: were making it, we're trying to get it made mandatory, 838 00:47:51,880 --> 00:47:56,799 Speaker 1: which probably backfired, well, definitely backfired. But Dan Kahan's point is, 839 00:47:56,840 --> 00:47:59,759 Speaker 1: these are two vaccines fundamentally in terms of public health. 840 00:47:59,760 --> 00:48:02,160 Speaker 1: It's see the same choice, but one of them is 841 00:48:02,200 --> 00:48:04,680 Speaker 1: politicized and one of them is not. One of them 842 00:48:04,680 --> 00:48:07,360 Speaker 1: you just talk to your doctor and you take professional advice. 843 00:48:07,719 --> 00:48:10,440 Speaker 1: One of them you just you get your cues from 844 00:48:11,120 --> 00:48:13,719 Speaker 1: whether you're whether you vote read or vote blue. And 845 00:48:13,760 --> 00:48:17,320 Speaker 1: this is going back to I think your your earlier 846 00:48:17,480 --> 00:48:21,719 Speaker 1: three step process for statistics. We can apply this to 847 00:48:21,840 --> 00:48:28,280 Speaker 1: so many other things, right, calm context, curiosity, Um, I'm repeating, 848 00:48:28,360 --> 00:48:30,480 Speaker 1: And Matt, I like that you added the fourth seas 849 00:48:30,520 --> 00:48:35,120 Speaker 1: cautionary tales. So what one of my questions then at 850 00:48:35,160 --> 00:48:42,120 Speaker 1: that point becomes a question about um, about historical context 851 00:48:42,760 --> 00:48:47,319 Speaker 1: and the dangers of broad brushes. I greatly appreciate how 852 00:48:47,360 --> 00:48:51,160 Speaker 1: you pointed out the danger of putting everyone in one 853 00:48:51,239 --> 00:48:55,719 Speaker 1: demographic bucket, right, the thought terminating cliche of anti vaxers. 854 00:48:56,120 --> 00:48:58,680 Speaker 1: It's just it's quicker to say it on the evening 855 00:48:58,719 --> 00:49:02,200 Speaker 1: news when you got six minute, it's right. But with 856 00:49:02,480 --> 00:49:07,600 Speaker 1: the idea of historical context. One of the things that 857 00:49:07,640 --> 00:49:11,200 Speaker 1: we've heard often from people in the US and abroad 858 00:49:11,520 --> 00:49:15,000 Speaker 1: regarding their hesitancy to in uh to engage in a 859 00:49:15,080 --> 00:49:20,640 Speaker 1: vaccine program, it's often a matter of historical context. They'll say, well, 860 00:49:20,680 --> 00:49:24,280 Speaker 1: look at the Tuskegee experiments. Right here in the US 861 00:49:24,480 --> 00:49:29,560 Speaker 1: or in Pakistan, people will talk about US intelligence services 862 00:49:30,080 --> 00:49:33,600 Speaker 1: using a vaccination program as cover to hunt down Asama 863 00:49:33,680 --> 00:49:39,040 Speaker 1: bin Laden. How how much weight should people give those 864 00:49:39,440 --> 00:49:46,239 Speaker 1: historical context arguments and is there any sand to those arguments? Well, 865 00:49:46,280 --> 00:49:49,200 Speaker 1: I mean those are I mean that both these both 866 00:49:49,200 --> 00:49:53,000 Speaker 1: of these things happened, and you've got to recognize them. 867 00:49:53,040 --> 00:49:56,400 Speaker 1: And if I was talking to somebody who who was 868 00:49:56,560 --> 00:49:58,799 Speaker 1: using that as a concern and that seemed to be 869 00:49:58,840 --> 00:50:02,480 Speaker 1: a consent, I would just speak curious to ask them, um, 870 00:50:02,760 --> 00:50:04,680 Speaker 1: do do you do you think a similar thing is 871 00:50:04,680 --> 00:50:07,759 Speaker 1: happening with the COVID vaccine. You'll just tell me what, 872 00:50:07,880 --> 00:50:11,160 Speaker 1: Just tell me more about about the connection between the two, 873 00:50:11,719 --> 00:50:14,400 Speaker 1: because you know, the connection to me is not obvious, 874 00:50:14,440 --> 00:50:17,160 Speaker 1: but it might be obvious to them. Same with Tuskege. 875 00:50:17,200 --> 00:50:20,919 Speaker 1: I mean the Tuskegee experiments, I mean, I wouldn't even 876 00:50:21,000 --> 00:50:23,600 Speaker 1: dignify them with the term experiments. And it's just horrendous 877 00:50:23,600 --> 00:50:27,960 Speaker 1: what happened to allow African American men to just develop 878 00:50:28,000 --> 00:50:30,680 Speaker 1: syphilis just so we could see what happened. And that's 879 00:50:31,120 --> 00:50:35,400 Speaker 1: it's astonishing. I mean, it's like kind of what the 880 00:50:35,480 --> 00:50:38,120 Speaker 1: Nazis did. It's really it's a war crime, except there 881 00:50:38,160 --> 00:50:43,080 Speaker 1: was no war. I mean, it's yeah, it's awful, awful, awful, um, 882 00:50:43,120 --> 00:50:45,640 Speaker 1: but I wouldn't know. I would be curious if someone 883 00:50:45,680 --> 00:50:48,800 Speaker 1: brought that up to ask, well, tell tell me about 884 00:50:48,800 --> 00:50:51,439 Speaker 1: the connection. Tell me how you see those two things 885 00:50:51,440 --> 00:50:55,120 Speaker 1: playing out. I personally don't see the connection really, but 886 00:50:55,120 --> 00:50:57,920 Speaker 1: but people might be able to explain to me the connection, 887 00:50:58,640 --> 00:51:00,719 Speaker 1: and then I'd get I'd be smarter, right, because then 888 00:51:00,719 --> 00:51:03,160 Speaker 1: they're telling me they're explaining something to me that I 889 00:51:03,160 --> 00:51:08,040 Speaker 1: don't know. Or maybe this sometimes happens as people talk 890 00:51:08,080 --> 00:51:11,520 Speaker 1: it through, they might go, actually, now you know, now 891 00:51:11,600 --> 00:51:15,080 Speaker 1: I now you ask me to to elaborate. Maybe the 892 00:51:15,080 --> 00:51:18,200 Speaker 1: connection is not so strong. But I wouldn't be wanting 893 00:51:18,200 --> 00:51:19,759 Speaker 1: to use that as a tactic. I think it's got 894 00:51:19,800 --> 00:51:21,880 Speaker 1: to be genuine. You gotta ask the question, not hoping 895 00:51:21,880 --> 00:51:23,799 Speaker 1: I have that they'll talk themselves out of it. Have 896 00:51:23,880 --> 00:51:25,879 Speaker 1: you really seen people do that? I mean, you're giving 897 00:51:25,880 --> 00:51:28,319 Speaker 1: people a lot of credit. I have to say. I 898 00:51:28,400 --> 00:51:31,279 Speaker 1: find so many people dig in deeper the more they 899 00:51:31,560 --> 00:51:34,960 Speaker 1: talk it through. In my experience, yeah, of course, there's 900 00:51:34,960 --> 00:51:38,560 Speaker 1: no magic bullet. It can happen. So by the way, 901 00:51:38,600 --> 00:51:40,719 Speaker 1: I don't know if you guys have spoken to David McCraney, 902 00:51:40,760 --> 00:51:43,400 Speaker 1: the host of the You Are Not So Smart podcast, 903 00:51:43,480 --> 00:51:45,960 Speaker 1: but he has a new book coming very soon that 904 00:51:46,160 --> 00:51:51,840 Speaker 1: really explores this kind of thing and and various field 905 00:51:51,880 --> 00:51:55,200 Speaker 1: experiments and trials where you just get you just have 906 00:51:55,280 --> 00:51:57,839 Speaker 1: a conversation and you ask people to explain themselves because 907 00:51:57,880 --> 00:52:02,280 Speaker 1: in the end, nobody it's persuaded by anybody else of anything. 908 00:52:02,719 --> 00:52:06,360 Speaker 1: People persuade themselves. And if you if you're hoping someone 909 00:52:06,440 --> 00:52:09,560 Speaker 1: might change their mind, you've got to give them room 910 00:52:09,600 --> 00:52:12,720 Speaker 1: to think. And maybe as they're thinking, maybe as they're talking, 911 00:52:12,760 --> 00:52:16,359 Speaker 1: maybe as they're explaining, it's just possible they will change 912 00:52:16,360 --> 00:52:19,120 Speaker 1: their mind. But you're right now, you can't expect that. 913 00:52:19,440 --> 00:52:21,160 Speaker 1: You can't kind of like, oh, all I need to 914 00:52:21,160 --> 00:52:24,799 Speaker 1: do is ask the question and boom they will. They 915 00:52:24,800 --> 00:52:27,560 Speaker 1: will have this conversion. That's that's not how it works. 916 00:52:27,960 --> 00:52:30,640 Speaker 1: That's why it's called the Socratic method and not the 917 00:52:30,680 --> 00:52:34,839 Speaker 1: Socratic solution, right, yea, absolutely, And of course we know 918 00:52:34,880 --> 00:52:39,279 Speaker 1: what they did to Socrates, you know, for this whole 919 00:52:39,320 --> 00:52:43,439 Speaker 1: for the whole vaccine thing. I really do blame British television, Tim, 920 00:52:43,440 --> 00:52:46,440 Speaker 1: I want you to know that, and specifically Dennis Kelly 921 00:52:46,520 --> 00:52:49,600 Speaker 1: and the show Utopia that came out, and I think 922 00:52:49,600 --> 00:52:52,239 Speaker 1: it was like it was early two thousands or mid 923 00:52:52,280 --> 00:52:55,800 Speaker 1: two thousand's, and uh, I blame I blame you completely 924 00:52:55,880 --> 00:53:02,040 Speaker 1: Utopia for making everybody go, oh, vaccines are bad, but 925 00:53:02,760 --> 00:53:04,920 Speaker 1: it is. It is amazing when you have these conversations 926 00:53:04,960 --> 00:53:08,040 Speaker 1: of what people will tell you. I was, I was 927 00:53:08,080 --> 00:53:13,120 Speaker 1: really struck by had a conversation with with an imam. 928 00:53:13,200 --> 00:53:15,280 Speaker 1: But this is for part of how to vaccinate the world. 929 00:53:15,440 --> 00:53:20,360 Speaker 1: And so he he a lot of his congregance, uh A, 930 00:53:20,680 --> 00:53:24,719 Speaker 1: young Islamic men go to his mask and he said 931 00:53:24,760 --> 00:53:28,720 Speaker 1: some of them had this belief that the vaccine wasn't hallal, 932 00:53:28,920 --> 00:53:32,960 Speaker 1: so it was religiously forbidden because it contained animal products, 933 00:53:33,239 --> 00:53:36,960 Speaker 1: which it turns out isn't true. But that's a conversation 934 00:53:37,000 --> 00:53:40,000 Speaker 1: that they could have. And others felt that it was 935 00:53:40,120 --> 00:53:42,600 Speaker 1: to take a vaccine was to break your fast. So 936 00:53:42,640 --> 00:53:46,280 Speaker 1: they had the the festival of Ramadan. You're not allowed 937 00:53:46,320 --> 00:53:49,080 Speaker 1: to eat or drink during the daylight hours. You could 938 00:53:49,440 --> 00:53:51,600 Speaker 1: for logistical reasons, you could only get vaccinated during the 939 00:53:51,640 --> 00:53:53,680 Speaker 1: daylight hours. And they felt that was breaking there fast. 940 00:53:53,719 --> 00:53:55,360 Speaker 1: So he would he would talk to them and he 941 00:53:55,400 --> 00:53:58,680 Speaker 1: would explain that in his his opinion as a religious authority, 942 00:53:59,440 --> 00:54:02,600 Speaker 1: it was to be vaccinated. It's okay to receive medical 943 00:54:02,680 --> 00:54:05,640 Speaker 1: it's a medical treatment, and medical treatment is different from 944 00:54:05,640 --> 00:54:08,920 Speaker 1: eating and drinking. But just like, I've never never occurred 945 00:54:08,920 --> 00:54:12,720 Speaker 1: to me that this might be a reason someone would object. 946 00:54:13,160 --> 00:54:15,239 Speaker 1: And then he said something that really stuck with me. 947 00:54:15,560 --> 00:54:19,640 Speaker 1: He said, I tell them that the vaccine is a 948 00:54:19,680 --> 00:54:23,560 Speaker 1: gift from God. God is working through the scientists who 949 00:54:23,560 --> 00:54:26,120 Speaker 1: made this vaccine, and the vaccine is a gift from God. 950 00:54:27,120 --> 00:54:29,279 Speaker 1: And I'm not a religious man. It brought tears to 951 00:54:29,320 --> 00:54:33,000 Speaker 1: my eyes. It was just too to have somebody who 952 00:54:33,000 --> 00:54:38,600 Speaker 1: has a totally different worldview to me thinking about what's 953 00:54:38,600 --> 00:54:42,200 Speaker 1: been done and what's been achieved and expressing it in 954 00:54:42,239 --> 00:54:45,000 Speaker 1: a way that would never have occurred to me. And yeah, 955 00:54:45,120 --> 00:54:47,120 Speaker 1: you only learned this stuff if you if you ask 956 00:54:47,200 --> 00:54:51,040 Speaker 1: the question. But I understand that's that's a very distinct 957 00:54:51,160 --> 00:54:54,320 Speaker 1: point that's being made to a distinct group by someone 958 00:54:54,400 --> 00:54:56,880 Speaker 1: with a basis in faith. And then it's also like 959 00:54:56,920 --> 00:55:00,080 Speaker 1: even a very fascinating and moving co signed the s A. 960 00:55:00,840 --> 00:55:02,880 Speaker 1: This is a way of of having people, you know, 961 00:55:02,960 --> 00:55:06,000 Speaker 1: buy into this, you know, whether it's completely mean. I 962 00:55:06,160 --> 00:55:08,520 Speaker 1: know it seems genuine and to me it truly seems 963 00:55:08,560 --> 00:55:11,279 Speaker 1: like it's coming from a place of genuineness. But where 964 00:55:11,280 --> 00:55:14,040 Speaker 1: does the micro chipping stuff come from? Where does the 965 00:55:14,120 --> 00:55:17,080 Speaker 1: five G stuff come from? Is someone just inventing this 966 00:55:17,160 --> 00:55:19,960 Speaker 1: out of whole cloth and isolation and then spreading it 967 00:55:20,320 --> 00:55:22,160 Speaker 1: a little at a time and it gets picked up 968 00:55:22,200 --> 00:55:26,879 Speaker 1: like a meme like where is that coming from? So yeah, 969 00:55:26,920 --> 00:55:28,640 Speaker 1: I'm not an expert in that, but I did ask 970 00:55:28,680 --> 00:55:31,919 Speaker 1: an expert and she as I said, well, what is 971 00:55:31,920 --> 00:55:36,080 Speaker 1: is it? Do people genuinely believe this? Or is it 972 00:55:36,120 --> 00:55:40,720 Speaker 1: is it disinformation? Um you know, you know, Chinese disinformation, 973 00:55:40,800 --> 00:55:44,640 Speaker 1: Russian disinformation? Or is it is it people trying to 974 00:55:44,680 --> 00:55:47,320 Speaker 1: sell something like they're trying to sell vitamins or whatever, 975 00:55:47,480 --> 00:55:50,839 Speaker 1: some alternative cure. And she said, well, it's all three 976 00:55:51,320 --> 00:55:53,440 Speaker 1: as far as she can work out, there are different. 977 00:55:53,480 --> 00:55:55,880 Speaker 1: There are different sources. There's loads of those are different 978 00:55:55,880 --> 00:55:59,480 Speaker 1: sources of disinformation. Some of it sticks, some of it doesn't. 979 00:56:00,320 --> 00:56:03,160 Speaker 1: It's invented for different reasons, it gets spread for different reasons. 980 00:56:03,640 --> 00:56:06,719 Speaker 1: And I mean that's true of information as well. I mean, no, 981 00:56:06,920 --> 00:56:09,160 Speaker 1: I love the way you put it when you said 982 00:56:09,239 --> 00:56:12,200 Speaker 1: it's a very it's a very specific point in a 983 00:56:12,280 --> 00:56:16,320 Speaker 1: very specific context. But you know that's true of almost everything. 984 00:56:16,520 --> 00:56:21,120 Speaker 1: Everyone believes. It's it's coming from a very specific context. 985 00:56:21,200 --> 00:56:24,320 Speaker 1: And the fact that we put each other in buckets 986 00:56:24,640 --> 00:56:26,719 Speaker 1: are like, oh, they're kind of their red status, their 987 00:56:26,760 --> 00:56:30,799 Speaker 1: blue status, their anti vaxes, their their woke. You put 988 00:56:30,800 --> 00:56:34,880 Speaker 1: people in buckets, you slap the label on them, and 989 00:56:34,960 --> 00:56:37,520 Speaker 1: that's when you stop engaging with them as human beings 990 00:56:37,560 --> 00:56:40,080 Speaker 1: and you stop trying to understand the individual context. And 991 00:56:40,520 --> 00:56:42,680 Speaker 1: we don't just do this to each other, we do 992 00:56:42,719 --> 00:56:45,720 Speaker 1: it to ourselves as well. In certain context, we adopt 993 00:56:45,800 --> 00:56:48,040 Speaker 1: these mentalities and we're like, well, I say the things 994 00:56:48,040 --> 00:56:49,520 Speaker 1: I'm supposed to say, and I believe the things I'm 995 00:56:49,560 --> 00:56:52,760 Speaker 1: supposed to believe, and I perform membership of this tribe. 996 00:56:53,719 --> 00:56:56,480 Speaker 1: None of us are at our best in those circumstances. 997 00:56:56,760 --> 00:56:58,920 Speaker 1: It reminds me of the expression and I'm sure annoys 998 00:56:59,000 --> 00:57:03,040 Speaker 1: you the idea don't let yourself become a statistic, you 999 00:57:03,080 --> 00:57:05,880 Speaker 1: know what I mean? Like, you know, don't be someone 1000 00:57:05,920 --> 00:57:08,120 Speaker 1: that gets killed in a certain situation because you do 1001 00:57:08,200 --> 00:57:10,920 Speaker 1: something stupid. You know. Um, But that's what we're talking 1002 00:57:10,960 --> 00:57:14,200 Speaker 1: about here. We're talking about whittling someone down to like 1003 00:57:14,400 --> 00:57:16,880 Speaker 1: the most basic, easy to understand element. But that's not 1004 00:57:16,920 --> 00:57:19,080 Speaker 1: what statistics are at all. They're much more complex. But 1005 00:57:19,160 --> 00:57:23,160 Speaker 1: I don't know, it's just interesting kind of cognitively dissonant concept, 1006 00:57:23,160 --> 00:57:26,640 Speaker 1: the idea of becoming a statistic. Yeah, and it's it's 1007 00:57:26,640 --> 00:57:28,440 Speaker 1: true though, And this is something i'd say in the 1008 00:57:28,520 --> 00:57:30,640 Speaker 1: data detective that there's just certain things that are easier 1009 00:57:30,640 --> 00:57:32,360 Speaker 1: to measure. And you know, the easiest thing of all 1010 00:57:32,400 --> 00:57:35,040 Speaker 1: to measure is did somebody die or not? I mean 1011 00:57:35,040 --> 00:57:39,919 Speaker 1: there's still some wiggle room. You'd be surprised generally. That's 1012 00:57:39,960 --> 00:57:43,160 Speaker 1: the thing when you're measuring, oh, mental health, or you're 1013 00:57:43,160 --> 00:57:45,560 Speaker 1: measuring injuries, like is it a serious injuries and a 1014 00:57:45,600 --> 00:57:48,000 Speaker 1: minor injuries and not really an injury at all? Did it? 1015 00:57:48,080 --> 00:57:51,680 Speaker 1: Does it? Does it get counted? Deaths get counted? And 1016 00:57:51,800 --> 00:57:56,560 Speaker 1: so there are certain things that they end up absorbing 1017 00:57:56,560 --> 00:58:00,920 Speaker 1: our attention, not just because death is of obviously we 1018 00:58:00,920 --> 00:58:03,720 Speaker 1: should pay attention to death, but also they absorbed our 1019 00:58:03,720 --> 00:58:06,600 Speaker 1: attention because you can count it. And so something like 1020 00:58:06,880 --> 00:58:10,200 Speaker 1: say long COVID you know, side effects of a COVID infection, 1021 00:58:10,240 --> 00:58:15,320 Speaker 1: all side effects of vaccination is much harder to measure. 1022 00:58:15,960 --> 00:58:18,480 Speaker 1: Someone dies, you can measure that. So that's that's an 1023 00:58:18,520 --> 00:58:22,120 Speaker 1: inbuilt bias, and statistics it's always worth I would never 1024 00:58:22,160 --> 00:58:25,120 Speaker 1: dismiss statistics for that reason, but you need to be aware, 1025 00:58:25,600 --> 00:58:28,600 Speaker 1: and you know, I would also add death is the 1026 00:58:28,640 --> 00:58:35,720 Speaker 1: great commonality, right, so that's something everyone, everyone can identify with. Unfortunately, 1027 00:58:35,760 --> 00:58:40,200 Speaker 1: at some point, uh, this this uh has been such 1028 00:58:40,200 --> 00:58:45,280 Speaker 1: a fascinating conversation to my only regret here is that 1029 00:58:45,640 --> 00:58:50,720 Speaker 1: we can't make this a whole series of episodes just yet. 1030 00:58:51,480 --> 00:58:55,760 Speaker 1: But if you would like to learn more, just as 1031 00:58:55,800 --> 00:59:00,480 Speaker 1: Matt Nolan I have about Cautionary Tales, do check out 1032 00:59:00,520 --> 00:59:04,160 Speaker 1: the show available wherever you find your favorite podcast. Uh, 1033 00:59:04,320 --> 00:59:08,680 Speaker 1: take a page from Matt's book and join me being 1034 00:59:08,840 --> 00:59:13,120 Speaker 1: as a fan of The Data Detective along with The 1035 00:59:13,240 --> 00:59:17,600 Speaker 1: Undercover Economist and Messy and How to make the World 1036 00:59:17,680 --> 00:59:21,800 Speaker 1: add Up. Tim Harford Thank you so much for joining 1037 00:59:21,880 --> 00:59:25,800 Speaker 1: us today. Where can people learn more about your work, 1038 00:59:26,160 --> 00:59:30,800 Speaker 1: both in and outside of the things we've discussed. My 1039 00:59:30,920 --> 00:59:35,400 Speaker 1: website is tim Harford dot com. That's not Hartford, Connecticut 1040 00:59:35,440 --> 00:59:38,800 Speaker 1: as no tea in it, in Harvard dot com. And 1041 00:59:38,840 --> 00:59:41,800 Speaker 1: there you've got my articles for the Financial Times. You've 1042 00:59:41,800 --> 00:59:45,280 Speaker 1: got linked to the podcast, links to the books. That's 1043 00:59:45,360 --> 00:59:47,560 Speaker 1: that's the best place I think to find out more. 1044 00:59:48,160 --> 00:59:51,480 Speaker 1: And I would just recommend everyone listen to a specific 1045 00:59:51,520 --> 00:59:54,479 Speaker 1: episode of Cautionary Tales that we kind of mentioned here. 1046 00:59:54,960 --> 00:59:57,840 Speaker 1: It's uh, it's a beautiful story of Howard Carter, a 1047 00:59:57,920 --> 01:00:01,520 Speaker 1: cheeky wound, some spooky all trick and an empathetic count. 1048 01:00:01,680 --> 01:00:05,200 Speaker 1: It's beautiful. It's about the Mummy's curse. And in the meantime, 1049 01:00:05,240 --> 01:00:06,640 Speaker 1: if you want to get in touch with us, you 1050 01:00:06,680 --> 01:00:09,280 Speaker 1: can find us however the internet. We are on the Facebook, 1051 01:00:09,520 --> 01:00:13,040 Speaker 1: the Twitter, all the those, the the YouTube under the 1052 01:00:13,040 --> 01:00:16,680 Speaker 1: handle Conspiracy Stuff on Instagram or Conspiracy Stuff Show. If 1053 01:00:16,680 --> 01:00:18,000 Speaker 1: you don't want to go into the social media, you 1054 01:00:18,040 --> 01:00:19,800 Speaker 1: can also give us a telephone call. We have our 1055 01:00:19,880 --> 01:00:24,360 Speaker 1: very own hotline with an associated voicemail Sure call one 1056 01:00:24,480 --> 01:00:27,640 Speaker 1: eight three three st d W y t K when 1057 01:00:27,680 --> 01:00:30,360 Speaker 1: you call in, give yourself a cool nickname, whatever you 1058 01:00:30,360 --> 01:00:32,720 Speaker 1: want it to be. That's great. You've got three minutes 1059 01:00:32,760 --> 01:00:34,880 Speaker 1: say whatever you'd like. Please include whether or not we 1060 01:00:34,920 --> 01:00:38,040 Speaker 1: can use your name and voice in the show. Thanks 1061 01:00:38,040 --> 01:00:40,120 Speaker 1: so much. If you don't want to call with your voice, 1062 01:00:40,200 --> 01:00:42,360 Speaker 1: you can instead send us a good old fashioned email. 1063 01:00:42,520 --> 01:01:00,400 Speaker 1: We are conspiracy at i heeart radio dot com. M hm, 1064 01:01:04,840 --> 01:01:06,920 Speaker 1: stuff they don't want you to know. Is a production 1065 01:01:06,960 --> 01:01:10,080 Speaker 1: of I Heart Radio. For more podcasts from my heart Radio, 1066 01:01:10,240 --> 01:01:13,040 Speaker 1: visit the i heart Radio app, Apple Podcasts, or wherever 1067 01:01:13,120 --> 01:01:14,440 Speaker 1: you listen to your favorite shows.