1 00:00:03,280 --> 00:00:05,880 Hello and welcome to the Behavioral Design Podcast. 2 00:00:05,960 --> 00:00:08,680 This season we're diving into the intersection of behavioral 3 00:00:08,680 --> 00:00:11,080 science and AI. We want to make sense of the 4 00:00:11,080 --> 00:00:14,080 state of AI, from understanding how humans interact with 5 00:00:14,080 --> 00:00:17,520 intelligent systems to using AI to do behavioral design itself. 6 00:00:17,720 --> 00:00:21,280 I'm Aline Holsworth, a health tech advisor specializing in AI 7 00:00:21,280 --> 00:00:23,880 and product design. Over the past 15 years, I've 8 00:00:23,880 --> 00:00:26,720 been crafting human centered products with behavioral science 9 00:00:26,720 --> 00:00:29,160 at the core. At Apple, I LED Behavioral 10 00:00:29,160 --> 00:00:32,119 Science for Health AI, designing and launching AI powered 11 00:00:32,119 --> 00:00:34,440 features to help users reach their health goals. 12 00:00:35,160 --> 00:00:37,160 And I'm Samuel Sultzer, your second Co host. 13 00:00:37,400 --> 00:00:40,600 I'm a behavioral strategist specializing in hybrid formation 14 00:00:40,600 --> 00:00:43,200 and designing products that drive long term baby change. 15 00:00:43,640 --> 00:00:46,880 I work with leading tech organizations integrating AI to 16 00:00:46,880 --> 00:00:48,240 scale behavioral design for good. 17 00:00:48,800 --> 00:00:52,200 And I'm also the founder of Baby Bites, a dedicated community on 18 00:00:52,440 --> 00:00:56,240 behavioral science and AI. Quick word on Nuance Behavior 19 00:00:56,240 --> 00:00:59,640 where we help organizations build impactful digital products 20 00:00:59,640 --> 00:01:02,640 using behavioral design. We only take on a few clients at 21 00:01:02,640 --> 00:01:05,200 a time to ensure the highest level of quality for our 22 00:01:05,200 --> 00:01:07,400 tailored evidence based solutions. 23 00:01:08,280 --> 00:01:11,080 If you'd like to become one of our special projects, e-mail us 24 00:01:11,120 --> 00:01:14,760 at hello@nuancebehavior.com or we could call directly on our 25 00:01:14,760 --> 00:01:35,440 website, nuancebehavior.com. Hey, I don't see a voting 26 00:01:35,440 --> 00:01:37,480 sticker. Have you voted? 27 00:01:38,680 --> 00:01:40,880 Well, yes, actually I have already voted. 28 00:01:41,040 --> 00:01:43,880 I voted early. We have this wonderful thing in 29 00:01:43,880 --> 00:01:47,920 Durham called early voting. There are, there are many, many 30 00:01:47,920 --> 00:01:51,400 advantages to it. You can go at any time of day. 31 00:01:51,440 --> 00:01:54,960 And like one of many, many places, it's flexible. 32 00:01:54,960 --> 00:01:57,720 It's, it's like really the ideal way to vote. 33 00:01:57,720 --> 00:02:00,160 There's no lines. Whereas if you if you vote on 34 00:02:00,400 --> 00:02:04,000 actual Election Day, you can only go to a very specific place 35 00:02:04,000 --> 00:02:07,520 with all the like very specific things and often have to wait 36 00:02:07,840 --> 00:02:09,120 for a very long time time to vote. 37 00:02:09,160 --> 00:02:11,680 So highly recommend early voting. 38 00:02:12,760 --> 00:02:13,760 Nice. That's awesome. 39 00:02:14,240 --> 00:02:18,280 And I had a voting experience this year with voting for the EU 40 00:02:18,280 --> 00:02:21,600 elections. And I feel like for me, every 41 00:02:21,600 --> 00:02:24,800 time I vote, I feel like good about democracy, like I feel. 42 00:02:25,880 --> 00:02:27,400 Like. It's like positive reinforcement 43 00:02:27,400 --> 00:02:31,400 because you know you go to place, people are friendly. 44 00:02:31,400 --> 00:02:34,160 So friendly, yeah. Everyone is friendly and you 45 00:02:34,160 --> 00:02:37,360 kind of feel like you leave there feeling like you've done 46 00:02:37,360 --> 00:02:39,800 something good as well, and you've done your part and you, 47 00:02:40,160 --> 00:02:43,000 yeah, you feel thankful. Yeah, that you, you get that, 48 00:02:43,040 --> 00:02:48,040 that voter's high after. No, I agree. 49 00:02:48,040 --> 00:02:52,280 I mean, there are really very few situations in life nowadays 50 00:02:52,280 --> 00:02:55,040 where you can go and do something, you know, fairly 51 00:02:55,040 --> 00:02:59,800 simple and get like 6 thank you's and like smiles the whole 52 00:02:59,800 --> 00:03:02,160 time and just all of this positive reinforcement. 53 00:03:02,440 --> 00:03:05,240 It's wonderful. And then you even get a sticker 54 00:03:05,240 --> 00:03:07,720 at the end. Yeah, I didn't get a sticker. 55 00:03:07,720 --> 00:03:09,840 I got, I think a cookie maybe or something. 56 00:03:09,840 --> 00:03:11,880 I I got something, but I didn't get a sticker. 57 00:03:11,960 --> 00:03:13,400 But. But I'm glad you did and I'm 58 00:03:13,400 --> 00:03:15,080 glad you voted. And that sets us up for 59 00:03:15,080 --> 00:03:18,200 obviously this episode and also next episode, we're going to 60 00:03:18,200 --> 00:03:22,120 cover a lot of thoughts on how behavioral science can help us 61 00:03:22,120 --> 00:03:26,120 think better about misinformation, elections and 62 00:03:26,120 --> 00:03:29,040 everything in between. Also with kind of AI as a big 63 00:03:29,040 --> 00:03:31,600 influence as well, potentially. Yeah. 64 00:03:31,600 --> 00:03:36,200 And, and overall, we obviously have this big theme of 65 00:03:36,200 --> 00:03:40,960 misinformation, especially looking from this side of the 66 00:03:40,960 --> 00:03:45,200 Atlantic observing the American election, there seems to be this 67 00:03:45,840 --> 00:03:48,600 cloud and worry around misinformation and, and what are 68 00:03:48,600 --> 00:03:52,360 things we can trust and what can we trust when it comes to the 69 00:03:52,440 --> 00:03:57,680 news leading up to the election? And we've heard about cats and 70 00:03:57,680 --> 00:04:01,120 dogs being consumed in some places where I've heard a lot of 71 00:04:01,120 --> 00:04:04,680 different things. But I don't know from my 72 00:04:04,680 --> 00:04:07,960 perspective, I obviously see it from a different angle than you. 73 00:04:08,200 --> 00:04:12,120 So what has been your experience so far when it comes to 74 00:04:12,200 --> 00:04:15,080 encountering misinformation? In this election. 75 00:04:15,760 --> 00:04:18,040 Yeah. Well, so first, I think the 76 00:04:18,040 --> 00:04:22,760 Haitians eating cats and dogs is maybe one of the more comical 77 00:04:23,040 --> 00:04:26,600 form of misinformation. But a lot of the misinformation 78 00:04:26,600 --> 00:04:29,440 that's proliferating increasingly in advance of the 79 00:04:29,480 --> 00:04:32,960 election is less innocuous than that. 80 00:04:33,000 --> 00:04:36,120 And it's really what I would categorize as disinformation, 81 00:04:36,120 --> 00:04:40,840 which is intentional. It's misinformation, but really 82 00:04:40,840 --> 00:04:45,240 intentionally trying to deceive people from mail in ballots 83 00:04:45,240 --> 00:04:49,480 being destroyed in Pennsylvania and then encouraging or 84 00:04:49,480 --> 00:04:53,480 facilitating non citizens to vote in California. 85 00:04:54,080 --> 00:04:57,440 These are all examples of disinformation that's already 86 00:04:57,440 --> 00:05:01,560 spreading that has been very clearly and unilaterally 87 00:05:01,560 --> 00:05:05,320 debunked. But because it's sensational and 88 00:05:05,320 --> 00:05:10,640 because it casts doubt on the election results, it's juicy 89 00:05:10,640 --> 00:05:14,640 enough that people are extremely motivated to spread it. 90 00:05:14,960 --> 00:05:21,160 And the big fear is that this disinformation will not only 91 00:05:21,160 --> 00:05:26,080 have an impact on the election itself, but on whatever happens 92 00:05:26,120 --> 00:05:28,120 after the election. Right. 93 00:05:28,320 --> 00:05:32,640 And yeah, maybe Eileen, do you want to introduce our fantastic 94 00:05:33,160 --> 00:05:37,040 guest at this important time? Yes, I would love to. 95 00:05:37,080 --> 00:05:40,960 We were so lucky to have Gordon Pennycook on the show. 96 00:05:41,280 --> 00:05:45,720 He is a psych professor at Cornell, and he studies where we 97 00:05:45,720 --> 00:05:49,680 go wrong in reasoning. And these reasoning errors show 98 00:05:49,680 --> 00:05:53,400 up in all sorts of domains, from climate change to health issues 99 00:05:53,400 --> 00:05:56,440 to politics, like we'll talk about today. 100 00:05:57,040 --> 00:06:02,680 And one fun fact about Gordon. He won the very humorous and 101 00:06:02,720 --> 00:06:06,640 highly esteemed IG Nobel Peace Prize for his work on pseudo 102 00:06:06,640 --> 00:06:10,960 profound bullshit. This is one of my favorite 103 00:06:11,960 --> 00:06:14,800 prizes in all of social science. It's actually, it's not just 104 00:06:14,800 --> 00:06:18,080 social science, but many social scientists have been awarded the 105 00:06:18,120 --> 00:06:20,920 IG Nobel. And it's also one of my favorite 106 00:06:20,920 --> 00:06:22,760 papers that has won the IG Nobel. 107 00:06:22,760 --> 00:06:26,600 So if you're not familiar, the the IG Nobel is this celebration 108 00:06:26,600 --> 00:06:30,160 of research that quote UN quote first makes people laugh and 109 00:06:30,160 --> 00:06:33,360 then makes them think. And he has some very interesting 110 00:06:33,360 --> 00:06:36,440 research on pseudo profound bullshit, which is what he calls 111 00:06:36,440 --> 00:06:39,760 seemingly impressive assertions that are presented as true and 112 00:06:39,760 --> 00:06:41,920 meaningful but are actually vacuous. 113 00:06:42,240 --> 00:06:46,560 And you can see this in many of the quotes that come from Deepak 114 00:06:46,560 --> 00:06:49,200 Chopra. But it's some examples are 115 00:06:49,240 --> 00:06:53,680 something like hidden meaning transforms unparalleled abstract 116 00:06:53,680 --> 00:07:03,160 beauty, which like has the the syntax of being a statement that 117 00:07:03,280 --> 00:07:07,240 could be true and makes sense, but actually is complete 118 00:07:07,720 --> 00:07:10,640 nonsense, even though it's it like comes off as something that 119 00:07:10,640 --> 00:07:15,200 could be real. Gordon has also done a great 120 00:07:15,200 --> 00:07:18,600 deal of research on misinformation, which is exactly 121 00:07:18,600 --> 00:07:23,000 why we invited him here today. And, you know, given that it's 122 00:07:23,080 --> 00:07:27,200 election week and the first thing that comes to mind when 123 00:07:27,200 --> 00:07:30,920 you think of elections, at least in the US, is misinformation and 124 00:07:30,920 --> 00:07:33,000 disinformation. I'm not sure what that says 125 00:07:33,360 --> 00:07:36,920 exactly about the state of society, but these two do seem 126 00:07:37,320 --> 00:07:42,400 to come hand in hand. And so as a result, who would we 127 00:07:42,400 --> 00:07:45,160 be if we weren't tackling this head on? 128 00:07:45,560 --> 00:07:46,960 Yeah. And like, to be fair, I think 129 00:07:47,040 --> 00:07:49,480 it's not only true for the US, but I think in every election 130 00:07:49,760 --> 00:07:51,680 that happened this year, there's been a lot of elections in the 131 00:07:51,680 --> 00:07:54,600 world. And even last year, it's 132 00:07:54,600 --> 00:07:57,520 definitely always, always a part of the conversation. 133 00:07:57,880 --> 00:08:03,200 And yeah, as I said, we had AI think a really important and 134 00:08:03,880 --> 00:08:06,320 valuable discussion when it comes to understanding 135 00:08:06,320 --> 00:08:09,320 misinformation from kind of behavioral science perspective, 136 00:08:09,720 --> 00:08:12,600 but in a very fun way. I will say we had a really good 137 00:08:12,600 --> 00:08:17,560 conversation and Gordon shared with us a way for us to break 138 00:08:17,560 --> 00:08:22,360 down misinformation. It's a big topic, but I think he 139 00:08:22,360 --> 00:08:25,400 did a great job of helping us make sense of it in a way. 140 00:08:25,760 --> 00:08:28,040 What we know about misinformation, how to think 141 00:08:28,040 --> 00:08:34,679 about it, and how we can kind of also think about the causes and 142 00:08:34,679 --> 00:08:36,440 ways to measure it and many things. 143 00:08:36,440 --> 00:08:37,799 That is interesting. From a behavioral science 144 00:08:37,799 --> 00:08:41,520 perspective, so we cover. That given the system as well, 145 00:08:41,520 --> 00:08:43,400 we naturally also cover quite a bit on. 146 00:08:43,799 --> 00:08:46,360 A is part. To what degree AI play a role in 147 00:08:46,680 --> 00:08:50,120 amplifying and creating misinformation and how to think 148 00:08:50,120 --> 00:08:54,000 about that as well? But yeah, so if you're 149 00:08:54,000 --> 00:08:56,720 interested to learn what makes misinformation so enticing and 150 00:08:56,720 --> 00:09:01,240 spread worthy, and also AI's. Role in all of this Listen to 151 00:09:01,240 --> 00:09:13,240 this episode with Gordon pennycook happens to. 152 00:09:16,360 --> 00:09:16,920 Murgatroyd. Wow. 153 00:09:18,360 --> 00:09:21,360 Perhaps, say, welcome Gordon to the Behavioral, the same 154 00:09:21,360 --> 00:09:23,880 podcast. Thank you, happy to be here. 155 00:09:25,160 --> 00:09:27,320 Yeah, you don't sound very happy. 156 00:09:27,440 --> 00:09:30,520 Sound very happy to be here. Well, it's 9:30 in the morning, 157 00:09:30,520 --> 00:09:33,360 I mean. That is not that early. 158 00:09:34,080 --> 00:09:38,560 Because that is, that's true. My kids go to school at 8:00 and 159 00:09:38,560 --> 00:09:40,760 I, I'm, they say goodbye to me when I'm in bed still. 160 00:09:40,760 --> 00:09:43,480 So I yeah. Yeah. 161 00:09:43,600 --> 00:09:45,760 Yeah. Well, we're very happy, yeah. 162 00:09:46,200 --> 00:09:49,000 We are excited to have you here. I'm so excited. 163 00:09:49,000 --> 00:09:52,280 This is great, Oh my God. That's better. 164 00:09:52,960 --> 00:09:58,280 And yeah, we obviously wanted to talk to you because it's been a 165 00:09:58,280 --> 00:10:01,680 lot of elections already this year, but then the Big 1 is 166 00:10:01,840 --> 00:10:04,880 coming up. And leading up to this has been 167 00:10:05,280 --> 00:10:09,400 increasingly, I think, questions about how well we understand the 168 00:10:09,400 --> 00:10:12,240 role of misinformation, especially in this day and age 169 00:10:12,240 --> 00:10:17,880 where AI is having a big role. And so we really want to get 170 00:10:17,880 --> 00:10:19,760 your help to make sense of all of this. 171 00:10:19,920 --> 00:10:24,600 And I guess to start, it would be really interesting to maybe 172 00:10:24,600 --> 00:10:26,560 set the scene a little bit. Yeah, that's good. 173 00:10:26,560 --> 00:10:30,040 No, maybe I can give it like a an even broader kind of like 174 00:10:30,040 --> 00:10:32,880 historical thing. Like I started doing research on 175 00:10:33,600 --> 00:10:37,560 misinformation in the 2016 election because fake news was 176 00:10:37,560 --> 00:10:40,560 this big thing and that and that was a particular case where 177 00:10:41,200 --> 00:10:43,120 people, it was like there was a bunch of stories about 178 00:10:43,120 --> 00:10:46,880 Macedonian teenagers and like just people trying to make a 179 00:10:46,880 --> 00:10:48,160 buck. They'd just make a website that 180 00:10:48,160 --> 00:10:50,640 looks like a news website, make up a bunch of stuff. 181 00:10:51,120 --> 00:10:54,920 And then that would be like make go viral on Facebook and they'd 182 00:10:54,920 --> 00:10:58,800 make a few bucks off that. And so that was the kind of 183 00:10:58,840 --> 00:11:01,320 initial sort of thing that we were investigating. 184 00:11:01,960 --> 00:11:04,720 And misinformation has kind of evolved since then. 185 00:11:04,880 --> 00:11:07,440 You know, I mean, misinformation has been around since 186 00:11:07,440 --> 00:11:09,480 information has been around, like it's just false things. 187 00:11:10,680 --> 00:11:15,440 But there's this, like, unique class of Internet stuff, social 188 00:11:15,440 --> 00:11:19,000 media falsehoods and so on. And then as the kind of like 189 00:11:19,000 --> 00:11:22,880 bots on social media we got became more advanced, I mean, 190 00:11:22,880 --> 00:11:26,000 most of they were pushing misinformation that people are 191 00:11:26,000 --> 00:11:27,520 making. It wasn't like, yeah, it was 192 00:11:27,520 --> 00:11:29,440 magnifying it. They were just like, a lot of 193 00:11:29,440 --> 00:11:32,280 the, it was inauthentic kind of engagement on social media that 194 00:11:32,280 --> 00:11:35,800 was helping things go viral. But I mean, a lot of the time it 195 00:11:35,800 --> 00:11:38,600 was purely just people. People were getting their 196 00:11:38,600 --> 00:11:41,920 attention grabbed by some insane headline, and then it was just 197 00:11:41,920 --> 00:11:45,120 kind of getting spread. But then we like when Trump was 198 00:11:45,120 --> 00:11:49,680 the president, it became kind of apparent that there might be 199 00:11:49,680 --> 00:11:53,560 bigger problems. And that's misinformation coming 200 00:11:53,560 --> 00:11:57,400 directly from political elites in some cases. 201 00:11:57,400 --> 00:12:00,880 Like these things work together because I mean, it's just we 202 00:12:00,880 --> 00:12:06,000 happened again in the in the debate with Kamala Harris, which 203 00:12:06,000 --> 00:12:07,560 was like eating the cats and the dogs. 204 00:12:07,680 --> 00:12:11,480 That was a kind of misinformation that came into 205 00:12:11,840 --> 00:12:16,000 Trump's sphere and then he tells everyone, millions of people 206 00:12:16,000 --> 00:12:18,400 about this thing, and not that many people would have seen it 207 00:12:18,680 --> 00:12:19,840 if it was just a fake news headline. 208 00:12:19,840 --> 00:12:21,960 But then it became a gigantic thing. 209 00:12:21,960 --> 00:12:25,560 And then it has a certain level of credibility to people who are 210 00:12:25,560 --> 00:12:28,840 following Donald Trump that that maybe they would have dismissed 211 00:12:28,840 --> 00:12:29,480 otherwise. Yeah. 212 00:12:29,680 --> 00:12:32,240 Yeah, exactly. And I mean, one is just like 213 00:12:32,960 --> 00:12:35,640 getting in front of as many people as you can, if you have 214 00:12:35,640 --> 00:12:38,800 that size of a platform, but then also adding credibility and 215 00:12:38,800 --> 00:12:40,560 people kind of accept what he says and so on. 216 00:12:40,920 --> 00:12:42,760 So there's and there's more dynamic, there's different 217 00:12:42,760 --> 00:12:44,160 dynamics to that. And so it became a more 218 00:12:44,160 --> 00:12:47,320 difficult problem. And then you enter in AI as a 219 00:12:47,320 --> 00:12:51,040 way to kind of like make things easier for the creator side, 220 00:12:52,120 --> 00:12:53,800 like, you know, building misinformation kind of that 221 00:12:53,800 --> 00:12:55,600 scale. Now, at the same time, I should 222 00:12:55,600 --> 00:12:58,760 say, though, it's not difficult to make up crap. 223 00:12:59,440 --> 00:13:01,800 It's not, it's not, it's actually pretty trivial for 224 00:13:01,800 --> 00:13:04,480 people to just make up stories. And a lot of time it's not even 225 00:13:04,480 --> 00:13:06,520 like that. It's like some kernel of 226 00:13:06,520 --> 00:13:08,760 something becomes it's like a rumors. 227 00:13:08,880 --> 00:13:12,720 I'll give one explicit example. The people have heard the story 228 00:13:12,720 --> 00:13:17,880 about like in schools, teens are identifying as cats and there's 229 00:13:17,880 --> 00:13:19,840 litter boxes in bathrooms or whatever. 230 00:13:20,280 --> 00:13:21,800 And like the furries, are these the furries? 231 00:13:21,800 --> 00:13:24,000 Yeah, well, I mean, but they I mean it's because it's like it's 232 00:13:24,000 --> 00:13:27,080 like anti trans kind of trope. People think it's furries, but 233 00:13:27,080 --> 00:13:28,480 people think furries are trans people. 234 00:13:28,480 --> 00:13:32,200 But it has nothing to do with one or the other, of course. 235 00:13:32,200 --> 00:13:34,280 And so they just think so they think that they're identifying 236 00:13:34,280 --> 00:13:36,560 as cats because you could you could identify as anything now 237 00:13:37,080 --> 00:13:37,960 and blah, blah, blah, blah, blah. 238 00:13:38,880 --> 00:13:41,640 But that rumor came out of like, I think there was actually was 239 00:13:41,640 --> 00:13:45,040 Kitty litter in a school, but it was because of shooter scenario. 240 00:13:45,360 --> 00:13:48,720 But there was no one obviously like pretending to be a cat and 241 00:13:48,920 --> 00:13:50,400 using the Kitty litter in the bathroom. 242 00:13:50,400 --> 00:13:53,000 I'm sorry that is lost. I mean what? 243 00:13:53,320 --> 00:13:55,960 Why do you need Kitty litter for an active shooter situation? 244 00:13:56,160 --> 00:13:58,040 Well, you might be stuck in the room for a long time. 245 00:14:00,280 --> 00:14:05,160 Oh, my uncle who is a literal a teacher in Canada told her he's 246 00:14:05,160 --> 00:14:07,520 like, I heard a story about their kind of kid leaders. 247 00:14:07,520 --> 00:14:09,680 And I'm like Shane, there's no who's. 248 00:14:09,720 --> 00:14:11,960 And by the way, I was, there's a here's a little story. 249 00:14:12,320 --> 00:14:15,560 I was my parents were janitors in addition to other things, but 250 00:14:15,560 --> 00:14:18,480 I so after school, my after school's chores were to clean 251 00:14:18,480 --> 00:14:22,080 the high school. And if a kid, you know, use the 252 00:14:22,080 --> 00:14:24,280 Kitty litter box, there's like they're not going to clean it. 253 00:14:24,280 --> 00:14:26,040 Like that's just not, you know what I mean? 254 00:14:26,120 --> 00:14:29,560 That's it's not in the cards. So anyways, that's but so like 255 00:14:29,560 --> 00:14:32,760 you don't really need AI to make up stuff like that, but it does. 256 00:14:33,120 --> 00:14:35,040 But you can. It does help scale things, and 257 00:14:35,040 --> 00:14:35,760 then it's. Easier. 258 00:14:35,760 --> 00:14:37,000 To scale things. Yeah, exactly. 259 00:14:37,240 --> 00:14:40,360 It's not difficult, but it but it does make it easier to make 260 00:14:40,360 --> 00:14:43,160 much much more of it. Yeah, exactly. 261 00:14:43,800 --> 00:14:45,080 Yeah. And I'm interested in that 262 00:14:45,080 --> 00:14:47,400 sense, like, do you in your research or how you think about 263 00:14:47,400 --> 00:14:50,840 this, is that a way that this is in some way separate in terms 264 00:14:50,840 --> 00:14:53,560 like we have some things, as mentioned, there's been, you 265 00:14:53,560 --> 00:14:56,560 know, various types of falsehoods and gossip and 266 00:14:56,560 --> 00:14:59,800 propaganda in various ways where the objective has been to kind 267 00:14:59,800 --> 00:15:01,280 of shape a narrative in some ways. 268 00:15:01,280 --> 00:15:05,720 And and we've recently seen some like popular kind of more maybe 269 00:15:05,720 --> 00:15:08,600 right wing pundits that has come out that they've been sponsored 270 00:15:08,600 --> 00:15:12,320 by Russian television to to push certain things. 271 00:15:12,320 --> 00:15:16,800 And so that it is kind of like this type of misinformation that 272 00:15:17,120 --> 00:15:18,960 in some ways maybe has been around, but still obviously 273 00:15:18,960 --> 00:15:22,720 still amplified with, you know, Internet existing today. 274 00:15:23,040 --> 00:15:25,840 But then you have this maybe in some ways new wave of 275 00:15:25,840 --> 00:15:30,080 misinformation that is purely used, accelerated and spewed by 276 00:15:30,320 --> 00:15:35,960 used artificial means, like some form of bots or some form of LLM 277 00:15:36,240 --> 00:15:38,240 models that are kind of used for for some of this. 278 00:15:38,600 --> 00:15:40,880 Is that something that's actively separated or how would 279 00:15:40,880 --> 00:15:43,080 you categorize misinformation in this way? 280 00:15:43,080 --> 00:15:45,840 It's. Not separated by us. 281 00:15:46,440 --> 00:15:48,160 I don't know, maybe some people are trying to do that. 282 00:15:48,160 --> 00:15:51,560 I think it would be very hard to know which was which. 283 00:15:52,360 --> 00:15:56,320 And we actually don't generally because I'm a psychologist, we 284 00:15:56,320 --> 00:15:58,840 don't spend a lot of time speculating about the source of 285 00:15:58,840 --> 00:16:00,720 it because it could who knows really. 286 00:16:00,720 --> 00:16:06,800 And ultimately, and I think actually the, the funding of the 287 00:16:07,200 --> 00:16:12,800 influencers by Russian, like by, by Russian interests is a great 288 00:16:12,800 --> 00:16:15,520 example because they didn't tell them to do anything. 289 00:16:15,520 --> 00:16:17,200 They're just funding them. They're like, they're already 290 00:16:17,200 --> 00:16:20,320 saying what we want them to say. So they don't need AI. 291 00:16:20,320 --> 00:16:22,440 They don't need they just, we're just giving them money to keep 292 00:16:22,440 --> 00:16:24,280 doing what they're doing because they've already adopted the 293 00:16:24,280 --> 00:16:26,960 narrative. And so like, I mean, so it's a 294 00:16:26,960 --> 00:16:30,040 case study in the sense that if you think about there's enough 295 00:16:30,040 --> 00:16:33,800 stuff out there already to drop on if you want to push false 296 00:16:33,800 --> 00:16:36,480 narratives. And then, you know, you can see 297 00:16:36,480 --> 00:16:38,800 how AI would help with it, but it's certainly not necessary. 298 00:16:38,800 --> 00:16:41,360 And like we had the same. So I don't think that the scope 299 00:16:41,360 --> 00:16:43,920 of the problem has really changed that much since AI has 300 00:16:43,920 --> 00:16:46,880 come around. It's probably made the lives of 301 00:16:46,880 --> 00:16:49,000 people who are trying to actively disinform people a 302 00:16:49,000 --> 00:16:51,880 little bit easier perhaps. But like, I don't think it's 303 00:16:51,880 --> 00:16:56,640 really improving the falsehoods or like making them more more 304 00:16:56,640 --> 00:16:58,440 catchy or whatever. I think it's just that was 305 00:16:58,440 --> 00:17:00,520 already there, people already pretty good at that. 306 00:17:00,960 --> 00:17:04,400 So that is, is I think a really good way to frame it. 307 00:17:04,440 --> 00:17:09,119 And so then looking on still technological side of how things 308 00:17:09,119 --> 00:17:12,240 have evolved, we you kind of mentioned the 2016 election 309 00:17:12,240 --> 00:17:15,040 where there was talk, I think there was Cambridge Analytica 310 00:17:15,040 --> 00:17:17,200 was kind of like one of the main things that was talked around. 311 00:17:17,880 --> 00:17:23,000 I want to stop on Cambridge Analytica because this, I think, 312 00:17:23,000 --> 00:17:26,839 is fake news in itself. I don't know, Gordon, how how 313 00:17:26,839 --> 00:17:29,680 familiar you are with what actually happened with Cambridge 314 00:17:29,680 --> 00:17:31,160 Analytica. Sure, yeah. 315 00:17:31,160 --> 00:17:33,600 People thought that they were really targeting people, but 316 00:17:33,600 --> 00:17:36,120 they weren't. It was, you know, they thought 317 00:17:36,320 --> 00:17:39,280 they thought that it was like they had some secret sauce that 318 00:17:39,280 --> 00:17:41,920 was really doing persuasion. But it. 319 00:17:41,920 --> 00:17:46,480 Yeah, and, and I think a lot of us bought into that as well. 320 00:17:46,760 --> 00:17:50,080 I, I certainly did. I used this as a, as a case 321 00:17:50,080 --> 00:17:53,320 study to, to test out your debunk bot, which we're going to 322 00:17:53,320 --> 00:17:56,840 talk about in another episode. But you know, I, I was actually, 323 00:17:57,240 --> 00:18:03,040 you know, fairly unsure, at least not 100% certain that what 324 00:18:03,040 --> 00:18:07,480 happened around this was, you know, certainly a lot of 325 00:18:07,680 --> 00:18:12,000 accounts on Facebook were mishandled and information was 326 00:18:12,360 --> 00:18:15,760 stolen or whatever you want to call it without consent. 327 00:18:16,080 --> 00:18:18,680 But in terms of what was done with that information, I think 328 00:18:18,680 --> 00:18:25,400 there's this huge misconception, let's just say, about how what 329 00:18:25,400 --> 00:18:29,400 actually happened and then how much that actually affected the 330 00:18:29,400 --> 00:18:32,600 election. So you might ask someone, you 331 00:18:32,600 --> 00:18:34,960 know, why? Why did the election tilt in 332 00:18:34,960 --> 00:18:37,400 favor of Donald Trump? And someone could reasonably 333 00:18:37,400 --> 00:18:40,000 say, oh, you know, that psychological targeting that 334 00:18:40,000 --> 00:18:44,280 happened through through Cambridge Analytica's data 335 00:18:44,280 --> 00:18:46,880 problem. Yeah, and it probably was. 336 00:18:46,960 --> 00:18:49,320 I mean, people say the same thing with fake news as well. 337 00:18:49,840 --> 00:18:52,520 I mean, they're, so they're did that did the fake news sway the 338 00:18:52,520 --> 00:18:53,880 election? Was it Cambridge Political 339 00:18:54,280 --> 00:18:57,160 people are looking for reasons. I mean, at the time, you can see 340 00:18:57,160 --> 00:18:59,240 we were looking for reasons to explain this thing that we could 341 00:18:59,240 --> 00:19:03,640 not explain as like, liberal intellectuals, I guess, you 342 00:19:03,640 --> 00:19:05,080 know, or like this doesn't make sense. 343 00:19:05,200 --> 00:19:07,480 It turns out people actually like Trump and they had 344 00:19:07,480 --> 00:19:09,040 different political opinions, you know what I mean? 345 00:19:09,040 --> 00:19:10,200 So. And the polling was wrong and 346 00:19:10,200 --> 00:19:11,640 they weren't listening to the. They weren't answering the 347 00:19:11,640 --> 00:19:13,120 polls. So that was basically what it 348 00:19:13,120 --> 00:19:16,280 was. So you, all of our little 349 00:19:16,280 --> 00:19:18,520 explanations that we developed immediately after the election 350 00:19:18,840 --> 00:19:20,160 were. Yeah. 351 00:19:21,040 --> 00:19:23,840 I guess this for me raises another question, which is how 352 00:19:23,840 --> 00:19:28,800 do you quantify the impact of misinformation on something like 353 00:19:28,800 --> 00:19:31,080 an election? Can we in any reasonable way 354 00:19:31,080 --> 00:19:33,840 actually do that? Yeah, probably not. 355 00:19:33,840 --> 00:19:37,040 I mean, it's, I don't know, You can't, I can't quantify it on 356 00:19:37,320 --> 00:19:39,680 the like, what people actually believe, you know what I mean? 357 00:19:39,680 --> 00:19:41,800 Like how do you know this? Behavior. 358 00:19:41,960 --> 00:19:43,640 Yeah, we want to. We what we really want to 359 00:19:43,640 --> 00:19:46,080 understand is what influences voting behavior. 360 00:19:46,080 --> 00:19:49,480 What people believe maybe is one thing, not necessarily the same 361 00:19:49,480 --> 00:19:51,840 as who they actually vote for. Sure, yeah. 362 00:19:51,840 --> 00:19:53,600 But yeah, I guess what I was saying was that it's hard to 363 00:19:53,600 --> 00:19:57,320 even pinned down a little of misinformation and what people's 364 00:19:57,320 --> 00:20:00,960 beliefs are and like, whether it's, you know, identity or 365 00:20:00,960 --> 00:20:03,320 cultural negatives or whatever. But it's like, yeah, but 366 00:20:03,320 --> 00:20:08,920 definitely when it comes to the election, this is it's difficult 367 00:20:08,920 --> 00:20:15,440 because and one, respect almost all of like the vast majority of 368 00:20:15,440 --> 00:20:17,600 people who vote, you already know who they're going to vote 369 00:20:17,600 --> 00:20:18,480 for. That's what it's going to be 370 00:20:18,480 --> 00:20:21,200 anyways. And so you have this like weird 371 00:20:21,200 --> 00:20:24,240 situation in the States where there's this. 372 00:20:24,960 --> 00:20:29,640 Small minority in a particular few states who have a gigantic 373 00:20:29,640 --> 00:20:34,080 influence and there's a lot of things that could that's a very 374 00:20:34,080 --> 00:20:37,920 like hard to predict context. And so like small things could 375 00:20:37,920 --> 00:20:40,200 have a big influence or not and I don't know. 376 00:20:40,640 --> 00:20:44,160 And so when it comes to misinformation, it's just, it's 377 00:20:44,520 --> 00:20:47,120 just one of these things where people, one thing that we can 378 00:20:47,120 --> 00:20:51,920 say for sure is that people do are walking around with a huge 379 00:20:51,920 --> 00:20:55,160 amount of like misunderstanding about how the world is. 380 00:20:56,240 --> 00:21:00,720 And that comes from somewhere. And the thing where it comes 381 00:21:00,720 --> 00:21:03,200 from is like misinformation. Now, to the extent with that 382 00:21:03,200 --> 00:21:06,520 comes from the sort of thing that we mean when we say 383 00:21:06,520 --> 00:21:09,960 misinformation, like the social media viral stuff that everyone 384 00:21:09,960 --> 00:21:13,240 kind of worries about or just like simple mistakes or 385 00:21:13,240 --> 00:21:16,000 conversations with neighbors or whatever, you know, it's hard to 386 00:21:16,080 --> 00:21:19,160 really tease that apart. Yeah. 387 00:21:19,200 --> 00:21:24,360 And maybe the way to tease it apart a little bit is if we then 388 00:21:24,360 --> 00:21:29,800 move forward a few years, we have 2020 and we have a strange 389 00:21:30,360 --> 00:21:34,960 year with, you know, COVID and many other things happening 390 00:21:34,960 --> 00:21:39,160 around there as well. But talking about COVID and and 391 00:21:39,160 --> 00:21:43,160 vaccine and misinformation, I know you've you've done research 392 00:21:43,160 --> 00:21:44,840 around that specifically. Yeah. 393 00:21:45,240 --> 00:21:48,480 I mean, I think it's a good example because, like, thinking 394 00:21:48,480 --> 00:21:51,160 about people not getting vaccinated as a consequence of 395 00:21:51,160 --> 00:21:54,000 misinformation. Now, there are lots of reasons 396 00:21:54,000 --> 00:21:58,040 why people don't vaccinate. And they, you know, some of it 397 00:21:58,040 --> 00:22:00,760 like institutional trusts, you know, how much you trust doctors 398 00:22:00,760 --> 00:22:01,960 in the system and all that kind of stuff. 399 00:22:03,240 --> 00:22:05,480 But, I mean, I think there's something to question that the 400 00:22:05,480 --> 00:22:08,440 amount of misinformation spreading had some impact on 401 00:22:08,440 --> 00:22:10,440 people not deciding not to vaccinate. 402 00:22:10,440 --> 00:22:11,560 It's just kind of very obvious, yeah. 403 00:22:12,960 --> 00:22:16,400 It's it's primarily attributed to Joe Rogan, right? 404 00:22:16,760 --> 00:22:20,480 Yeah, I'm not sure primarily, but like, I think what's it 405 00:22:20,480 --> 00:22:21,600 called? Ivermectin? 406 00:22:21,600 --> 00:22:23,200 I mean, we've got to be clear on the. 407 00:22:23,640 --> 00:22:25,320 I don't want to be too politically biased. 408 00:22:25,640 --> 00:22:29,600 You know, people were saying that Joe Rogan was promoting 409 00:22:29,640 --> 00:22:32,480 horse tranquilizer or whatever, which is kind of may be true in 410 00:22:32,480 --> 00:22:35,360 a strict sense, but not true. And like, it's not really like 411 00:22:35,360 --> 00:22:37,120 what it's for for humans, you know what I mean? 412 00:22:37,120 --> 00:22:38,880 So but anyways, so it it goes both ways. 413 00:22:38,880 --> 00:22:42,360 But there's been this kind of growing thing in the research on 414 00:22:42,360 --> 00:22:45,440 misinformation where people are kind of like denying its 415 00:22:45,480 --> 00:22:49,640 importance and consequence. And I think that's kind of just 416 00:22:49,960 --> 00:22:51,120 wrong. I mean, I think that is the 417 00:22:51,120 --> 00:22:53,960 case. We can it's it probably is 418 00:22:53,960 --> 00:22:55,920 overrated in many respects. Like people think it's the most 419 00:22:55,920 --> 00:22:58,920 there was like some like kind of a thing as aun thing or 420 00:22:58,920 --> 00:23:00,960 something where it's like misinformation is the most 421 00:23:00,960 --> 00:23:04,200 important problem. And like, Oh yeah, it's easy to 422 00:23:04,200 --> 00:23:07,360 like make it see it's but it's like proximally speaking, not, 423 00:23:08,080 --> 00:23:12,520 you know, like misinformation flourishes because of the 424 00:23:12,520 --> 00:23:14,880 structure of our fragmented information environment. 425 00:23:15,120 --> 00:23:18,680 That's a much bigger problem. And there's other like but many 426 00:23:18,680 --> 00:23:20,400 other big problems, you know, climate change. 427 00:23:20,400 --> 00:23:22,880 But but it still ultimately is like we want people to have 428 00:23:22,880 --> 00:23:25,920 accurate beliefs about the world and misinformation is just false 429 00:23:25,920 --> 00:23:28,280 things. And so like, just in a strict 430 00:23:28,280 --> 00:23:30,640 sense, like, yeah, that's a huge problem. 431 00:23:30,640 --> 00:23:32,760 We don't, we want, that's the whole point of education. 432 00:23:32,760 --> 00:23:36,600 This is why we have expertise and and This is why we make 433 00:23:36,600 --> 00:23:38,120 podcasts where we teach people things. 434 00:23:38,360 --> 00:23:42,200 It ultimately is all about trying to like, persuade people 435 00:23:42,440 --> 00:23:46,040 to believe things that are on based on good evidence, and 436 00:23:46,040 --> 00:23:48,600 misinformation counteracts that. It's interesting that you put it 437 00:23:48,600 --> 00:23:51,920 next to climate change because, well, for example, if you don't 438 00:23:51,920 --> 00:23:55,640 believe in climate change, then it doesn't like there's nothing 439 00:23:55,640 --> 00:23:59,560 you can even start to do there for getting someone to act. 440 00:23:59,560 --> 00:24:01,840 They're just, you know, it doesn't matter how big the 441 00:24:01,960 --> 00:24:03,880 actual problem of climate change is. 442 00:24:03,880 --> 00:24:05,120 If they don't believe it, they're not going to do 443 00:24:05,120 --> 00:24:06,880 anything. That's that's true. 444 00:24:06,880 --> 00:24:08,600 I think that's so perfect example. 445 00:24:08,680 --> 00:24:12,040 So that is the case. And people often say in papers 446 00:24:12,040 --> 00:24:14,240 about climate change, they'll be like, we really need to kind of 447 00:24:14,240 --> 00:24:16,200 convince people that this is a problem because they're not 448 00:24:16,200 --> 00:24:18,960 going to do anything. But like at the same time, what 449 00:24:18,960 --> 00:24:21,360 are the most effective ways to combat climate change? 450 00:24:21,360 --> 00:24:24,040 It's not the everyday behaviors of citizens. 451 00:24:24,040 --> 00:24:28,680 It's governmental policy and, you know, so those are things 452 00:24:28,680 --> 00:24:31,280 that cannot be influenced by changing an individual's belief. 453 00:24:31,400 --> 00:24:33,760 Then, of course, what people say is, well, if you change what 454 00:24:33,760 --> 00:24:37,040 people believe and then the governments will listen to them, 455 00:24:37,680 --> 00:24:41,000 well, you know that there's there's nothing there that's not 456 00:24:41,000 --> 00:24:43,160 completely wrong, but it's not exactly right either. 457 00:24:43,520 --> 00:24:47,040 So yeah. Pretty difficult indirect route 458 00:24:47,120 --> 00:24:48,360 for sure. Yeah, exactly. 459 00:24:49,640 --> 00:24:51,440 Yeah. And so if I'm going to try to 460 00:24:51,440 --> 00:24:53,320 summarize a little bit where we're come so far. 461 00:24:53,320 --> 00:24:56,400 So we started in some ways where misinformation has been around 462 00:24:56,400 --> 00:25:00,600 forever and it's kind of it's the twin to information. 463 00:25:00,600 --> 00:25:03,520 Like it's kind of hard to avoid in human society. 464 00:25:03,520 --> 00:25:05,400 We're always have to deal with that. 465 00:25:06,800 --> 00:25:11,520 We spoke about how a lot of the current misinformation is 466 00:25:11,680 --> 00:25:15,760 amplified by credibility through certain voices and like certain 467 00:25:15,760 --> 00:25:19,600 people that are kind of spreading this and with help of 468 00:25:19,600 --> 00:25:21,680 obviously technology today, like it's making it easier. 469 00:25:22,360 --> 00:25:25,520 But at the same time, it's it's much of that still comes from 470 00:25:25,520 --> 00:25:27,520 people doing it. Like a lot of people being 471 00:25:27,520 --> 00:25:32,120 involved in, in sharing their maybe false beliefs that we just 472 00:25:32,120 --> 00:25:35,480 use masses and then has some kind of consequences, but that 473 00:25:35,560 --> 00:25:37,720 it's very hard to understand actually what the consequences 474 00:25:37,720 --> 00:25:39,520 are still. Like it's kind of hard to even 475 00:25:39,520 --> 00:25:43,200 with something like vaccine hesitancy or or not taking your 476 00:25:43,200 --> 00:25:47,080 vaccine, it's still hard to really know, like to what degree 477 00:25:47,080 --> 00:25:50,680 people were vaccinated or not because of misinformation on the 478 00:25:50,680 --> 00:25:53,640 sources. Because it's like it's so mixed 479 00:25:53,640 --> 00:25:57,040 in to the fragment of like human experience that we talked to 480 00:25:57,680 --> 00:25:59,720 people on the like in our lives on online. 481 00:25:59,720 --> 00:26:02,760 Like this is very hard to know. Like, OK, this source of 482 00:26:02,760 --> 00:26:06,080 misinformation LED people to to not do this thing. 483 00:26:07,120 --> 00:26:09,760 It's like good summary so far. Anything you would like 484 00:26:09,760 --> 00:26:11,640 underline? That's a great summary. 485 00:26:11,800 --> 00:26:14,120 I think that captures it. We could just use that we don't 486 00:26:14,120 --> 00:26:15,320 need. We could just cut out the first 487 00:26:15,320 --> 00:26:16,640 part. They've got the gist. 488 00:26:17,240 --> 00:26:19,720 Well, that, that's good to hear that sometimes you get it wrong 489 00:26:19,720 --> 00:26:21,160 into summarizing, but that's good. 490 00:26:21,320 --> 00:26:25,520 And and then I do want to kind of build on kind of moving from 491 00:26:26,000 --> 00:26:30,440 COVID in some ways. I would say I've noticed and I 492 00:26:30,440 --> 00:26:32,800 think it's been big part of the discourse is that, you know, I 493 00:26:32,800 --> 00:26:36,960 think in 2022 there was some research that was around X or 494 00:26:36,960 --> 00:26:41,080 Twitter saying that like 2/3 or at least 1/3 of of all accounts 495 00:26:41,080 --> 00:26:43,240 were some form of bots on Twitter. 496 00:26:43,400 --> 00:26:46,600 We saw counties rising first, like more edge cases where 497 00:26:46,600 --> 00:26:48,040 you're like, hey, you could use deepfakes. 498 00:26:48,040 --> 00:26:51,160 Like deepfakes is kind of the thing you could kind of copy 499 00:26:51,160 --> 00:26:55,080 someone's voice or or face and that can be used in various 500 00:26:55,080 --> 00:26:56,160 ways. But it was kind of like little 501 00:26:56,160 --> 00:26:59,760 edge cases and, and more like, hey, be wary as soon it's going 502 00:26:59,760 --> 00:27:02,280 to happen. And then I think it was around 503 00:27:02,280 --> 00:27:05,000 last year that was in Slovakia. They had some form of election 504 00:27:05,000 --> 00:27:07,520 deep fake thing around, especially with audio I believe 505 00:27:07,880 --> 00:27:10,960 where there was some basing up to the election, there was some 506 00:27:11,240 --> 00:27:15,920 basically deep fake audio that was spread that had some form of 507 00:27:16,680 --> 00:27:19,560 impact in terms of least fact checkers were scrambling to make 508 00:27:19,560 --> 00:27:22,080 sense of these fake recordings and how to make sense of it. 509 00:27:22,800 --> 00:27:26,840 Yeah, they they had the Slovakian Liberal Party leader 510 00:27:27,040 --> 00:27:31,880 talking about vote rigging and I think it was raising the price 511 00:27:31,880 --> 00:27:34,920 of beer. Oh geez, of all the that's the 512 00:27:34,920 --> 00:27:39,240 last, That's the final straw. Yeah, we cannot tolerate this. 513 00:27:40,160 --> 00:27:41,880 Yeah. So we're moving into, you know, 514 00:27:41,880 --> 00:27:46,320 the area now 2024 where it feels a little more real when it comes 515 00:27:46,320 --> 00:27:50,080 to this either. We have also, not only are these 516 00:27:50,080 --> 00:27:53,480 bots more like very simple bots that you just jump around and 517 00:27:53,480 --> 00:27:57,080 maybe use retweets or post some very generic things, but they're 518 00:27:57,080 --> 00:28:00,440 actually powered sometimes by large language models where they 519 00:28:00,440 --> 00:28:03,520 can actually have some form of level conversations online and 520 00:28:03,760 --> 00:28:08,840 and they can actually engage with people in some form of 521 00:28:09,080 --> 00:28:12,840 shack communities and and so on. Maybe the last thing I'll say as 522 00:28:12,840 --> 00:28:16,680 an example is recently I've seen this like people being worried 523 00:28:16,680 --> 00:28:21,080 about what we see on images online because someone googled 524 00:28:21,080 --> 00:28:25,000 baby Peacock and they realized that of the 20 images on Google 525 00:28:25,240 --> 00:28:28,120 there was a baby Peacock, only three of them were actually real 526 00:28:28,120 --> 00:28:30,600 baby Peacocks. And all of them else was like AI 527 00:28:31,120 --> 00:28:35,760 generated images. So I think more and more of this 528 00:28:35,760 --> 00:28:39,560 fear is sweeping out now. It's like, OK, where are we 529 00:28:39,560 --> 00:28:44,240 right now when it comes to this kind of technological influence 530 00:28:44,240 --> 00:28:48,480 on misinformation and so on. So you you alluded a little bit 531 00:28:48,480 --> 00:28:54,320 to that already in terms of we're not maybe going in orders 532 00:28:54,320 --> 00:28:56,360 of magnitudes away from where we're before. 533 00:28:56,360 --> 00:28:59,640 Like we're still, we're existing and ordering a pretty, pretty 534 00:29:00,360 --> 00:29:04,240 misinformation high levels. But yeah, how do you make sense 535 00:29:04,240 --> 00:29:07,080 of the current technology global advancements? 536 00:29:07,240 --> 00:29:08,800 Yeah. I mean, I think what the real 537 00:29:08,800 --> 00:29:13,880 concern is essentially is like inauthentic behavior, like what 538 00:29:13,880 --> 00:29:17,880 you in a, in a kind of like a democratic society, we can have 539 00:29:17,880 --> 00:29:21,520 differences of opinion and like people get things wrong and 540 00:29:21,600 --> 00:29:24,280 whatever, and we can learn from each other and all that kind of 541 00:29:24,280 --> 00:29:27,040 stuff. But when people are acting 542 00:29:27,040 --> 00:29:30,360 inauthentically, then it kind of like disrupts the system. 543 00:29:30,360 --> 00:29:34,680 And what that, what that means is like the obvious case that 544 00:29:34,680 --> 00:29:37,760 you're talking about is like literally it's a bot and it's 545 00:29:37,760 --> 00:29:39,200 not really a person. You think it's a person. 546 00:29:39,200 --> 00:29:42,520 And so like you're taking that to mean that there's all these 547 00:29:42,520 --> 00:29:44,400 people are supporting this cause, but actually it's a bunch 548 00:29:44,400 --> 00:29:46,720 of Russian bots and it's not actual Americans or whatever. 549 00:29:47,840 --> 00:29:51,960 Or it's like this is someone talking, but it's actually not 550 00:29:51,960 --> 00:29:53,720 them talking. It's an AI or this is a picture 551 00:29:53,720 --> 00:29:54,880 of something. I think it's not actually that. 552 00:29:55,920 --> 00:29:59,320 But there's also like, I mean, those are all concerns, but of 553 00:29:59,320 --> 00:30:01,320 course, like inauthentic behaviors. 554 00:30:01,320 --> 00:30:07,880 Also people who are influencers who are not generating authentic 555 00:30:07,880 --> 00:30:11,200 opinions, they're trying to just say what they think will get 556 00:30:11,200 --> 00:30:14,200 them the clicks and the likes and the, and the views and the 557 00:30:14,200 --> 00:30:17,040 listens and so on. That's also an authentic 558 00:30:17,040 --> 00:30:18,360 behavior. And So what you end up as a 559 00:30:18,360 --> 00:30:22,720 distorted kind of reality that people are entering online and 560 00:30:23,200 --> 00:30:26,600 which of course leads offline where it's like, it's hard to 561 00:30:26,600 --> 00:30:30,160 know what's going on. Misinformation makes that worse. 562 00:30:30,160 --> 00:30:32,040 But also like it's not just about truth and falsehood. 563 00:30:32,040 --> 00:30:35,880 It's just about like what, how do we know what other people are 564 00:30:35,880 --> 00:30:37,840 like, what's what's actually happening in the country? 565 00:30:38,160 --> 00:30:41,600 And so like our understanding of like in, in the context of like, 566 00:30:41,600 --> 00:30:45,840 you know, given the election of like our political others is 567 00:30:45,840 --> 00:30:48,760 like way off. People have really, really do 568 00:30:48,760 --> 00:30:52,240 not, they totally think that like people on the other side of 569 00:30:52,240 --> 00:30:54,040 the aisle are way more extreme than they actually are. 570 00:30:55,200 --> 00:30:58,080 There was actually a paper that was published recently where, 571 00:30:58,600 --> 00:31:03,200 you know, people think the like way more people are responsible 572 00:31:03,200 --> 00:31:06,680 for trolling than actually are. It's a tiny fraction of people 573 00:31:06,680 --> 00:31:10,760 actually engage in kind of like actual users engage in what you 574 00:31:10,760 --> 00:31:12,960 might call like an authentic, an authentic sort of behavior. 575 00:31:13,680 --> 00:31:17,960 But the, our sense of it is that like 40% of people actually do. 576 00:31:17,960 --> 00:31:20,160 It was actually 3% or something. I can't remember what the actual 577 00:31:20,320 --> 00:31:22,160 status. So we, our perception of reality 578 00:31:22,160 --> 00:31:23,680 is being really distorted by all these things. 579 00:31:24,320 --> 00:31:27,560 And then you enter in, these things are just essentially made 580 00:31:27,560 --> 00:31:29,640 to be inauthentic. Yeah, it's not going to make it 581 00:31:29,640 --> 00:31:31,360 better, that's for sure. It's a it's an issue. 582 00:31:32,120 --> 00:31:35,960 So, so I'm familiar with this research about believing that 583 00:31:35,960 --> 00:31:38,040 others are much more extreme than they really are. 584 00:31:38,040 --> 00:31:44,080 I actually, I feel very strongly the opposite feeling in in my 585 00:31:44,080 --> 00:31:48,160 own experience, which is that I tend to think that other people 586 00:31:48,160 --> 00:31:52,120 think like me, even if they're, you know, not like me. 587 00:31:52,480 --> 00:31:56,480 And I extend my own belief system to the Republicans of the 588 00:31:56,480 --> 00:32:00,800 world as well. And so when I think about, you 589 00:32:00,840 --> 00:32:04,840 know, the tightness of the race, for example, in the 2024 590 00:32:04,840 --> 00:32:09,240 election, and I think, oh, about half the country is going to 591 00:32:09,240 --> 00:32:12,400 vote for Donald Trump, that is so inconsistent with my beliefs 592 00:32:12,400 --> 00:32:16,760 about what other people could possibly even be capable of. 593 00:32:17,480 --> 00:32:20,920 And my liberal bias is very, very strong here. 594 00:32:21,920 --> 00:32:25,720 But, you know, and part of it, I'm sure, could be living 595 00:32:25,720 --> 00:32:29,800 physically in a little liberal bubble myself where I mostly 596 00:32:29,800 --> 00:32:33,000 interact with other people that are very similar to me. 597 00:32:33,560 --> 00:32:39,160 But for me, I am shocked to think about anyone voting for 598 00:32:39,160 --> 00:32:41,760 Donald Trump. I think both of those things 599 00:32:41,760 --> 00:32:45,360 will be true at once. So like you're kind of 600 00:32:45,360 --> 00:32:51,720 intuitive, like sense of you would assume that everyone's 601 00:32:51,720 --> 00:32:54,040 more similar to you than they actually are because you have 602 00:32:54,040 --> 00:32:55,920 to, you know, you live through your own perspective. 603 00:32:56,920 --> 00:33:02,840 If I ask you, OK, then like think about a Republican and how 604 00:33:02,840 --> 00:33:06,480 extreme they are or whatever. Now you think, OK, wait, I think 605 00:33:06,480 --> 00:33:08,320 they're similar to me. But then you look and see that 606 00:33:08,320 --> 00:33:10,160 they're supporting Donald Trump. And so you make some sort of 607 00:33:10,160 --> 00:33:12,960 inference of it must be that, oh, they actually must be like 608 00:33:12,960 --> 00:33:15,760 way more extreme or like not different. 609 00:33:15,960 --> 00:33:17,520 So like you take. So then you make an inference 610 00:33:17,520 --> 00:33:19,240 that they're like, now you overcorrect essentially. 611 00:33:19,920 --> 00:33:22,480 I'll give you I'll give you like another kind of like related 612 00:33:22,480 --> 00:33:24,160 examples of this. And this relates to conspiracy 613 00:33:24,160 --> 00:33:27,080 beliefs. So like people there's this like 614 00:33:27,080 --> 00:33:29,480 common thing for conspiracy believers where they think about 615 00:33:29,480 --> 00:33:33,140 the people to, you know, accept mainstream narratives, quote UN 616 00:33:33,140 --> 00:33:35,720 quote as like sheeple. You know, they're like there's 617 00:33:35,720 --> 00:33:36,920 going along, they're conformists. 618 00:33:36,920 --> 00:33:39,600 And like really the conspiracy theorists are the actual kind of 619 00:33:39,600 --> 00:33:42,960 critical thinkers, the unique critical free thinkers, they 620 00:33:42,960 --> 00:33:46,280 often say. And So what you might assume 621 00:33:46,280 --> 00:33:50,160 from that is so people who believe conspiracies probably, 622 00:33:50,160 --> 00:33:52,680 like, know that they're on the fringe, right? 623 00:33:52,800 --> 00:33:54,200 And kind of, they kind of want to be there. 624 00:33:54,280 --> 00:33:55,360 And that's the whole point of it. 625 00:33:56,200 --> 00:33:58,520 And like, if you ask them that, they probably would agree to it, 626 00:33:58,600 --> 00:34:00,080 Yeah. That's a feature, not a bug. 627 00:34:00,360 --> 00:34:02,160 Yeah, yeah. But at the same time, we did a 628 00:34:02,160 --> 00:34:05,400 study where we asked people to estimate the percent of people 629 00:34:05,400 --> 00:34:07,320 that agree with them about conspiracies. 630 00:34:07,880 --> 00:34:10,120 OK. And so I'll give an example in. 631 00:34:10,199 --> 00:34:13,520 So for the Sandy Hook false flag conspiracy, it's a ludicrous 632 00:34:13,679 --> 00:34:16,880 extreme conspiracy. 8% of people in our sample thought it was 633 00:34:16,880 --> 00:34:19,159 true that Sandy Hook didn't actually happen. 634 00:34:19,159 --> 00:34:22,560 It was a whole false flag thing, actors and so on. 635 00:34:23,199 --> 00:34:26,159 And so we asked the people to both the people who believe and 636 00:34:26,159 --> 00:34:28,639 don't believe, but we asked them, estimate the percent of 637 00:34:28,639 --> 00:34:29,760 people that you think agree with you. 638 00:34:30,400 --> 00:34:32,760 And so 8% thought it was true. If they're calibrated, they'll 639 00:34:32,760 --> 00:34:39,040 say 8 to 10%, you know, whatever they said 61%, they thought they 640 00:34:39,040 --> 00:34:40,880 were in the majority. They thought that most people 641 00:34:41,360 --> 00:34:42,800 realize that this was a false flag. 642 00:34:43,000 --> 00:34:46,679 So like both at the same time, they're like, yeah, I'm unique, 643 00:34:46,719 --> 00:34:48,120 I'm critical, freethinker, whatever. 644 00:34:48,320 --> 00:34:50,800 But they also kind of think that everyone agrees with them. 645 00:34:51,199 --> 00:34:53,080 And that's even when you're totally on the fringe. 646 00:34:53,080 --> 00:34:56,199 And so you can see how this there's kind of dueling elements 647 00:34:56,199 --> 00:34:58,120 of our psychology that contribute to these issues. 648 00:34:58,720 --> 00:35:01,960 That's great. Yeah, Sam has been calling AI 649 00:35:01,960 --> 00:35:05,040 and and and specifically Gen. AI weird humans. 650 00:35:05,040 --> 00:35:07,480 And to me, this seems like humans are are really the weird 651 00:35:07,480 --> 00:35:09,040 humans. Yeah, exactly. 652 00:35:09,120 --> 00:35:11,840 It's it's a reflection of us. We're like, oh, how weird AI is. 653 00:35:11,840 --> 00:35:14,080 It's like it's just doing, you know, we created. 654 00:35:14,080 --> 00:35:16,480 It right it's. Just it's a little, it's like a 655 00:35:16,480 --> 00:35:18,920 weird little mirror, but it's still us in the mirror. 656 00:35:18,920 --> 00:35:23,000 Yep, Yep. Yeah, no, but that's super 657 00:35:23,000 --> 00:35:26,680 interesting. So I think we've now spoken 658 00:35:26,680 --> 00:35:30,720 quite a bit of, you know, elements to setting the scene in 659 00:35:30,720 --> 00:35:33,480 terms of OK, where are we, what is the role of humans? 660 00:35:33,480 --> 00:35:35,640 We're humans, we're technology and so on. 661 00:35:36,680 --> 00:35:40,160 But used to really make sure we're on the same page in terms 662 00:35:40,160 --> 00:35:44,120 of misinformation. There's a lot of things run 663 00:35:44,120 --> 00:35:47,160 misinformation that I think it's kind of interesting to to talk 664 00:35:47,160 --> 00:35:50,400 about and that idea in terms of I've seen a lot of versions of 665 00:35:50,400 --> 00:35:51,800 this. You know, we talk about a lie 666 00:35:51,800 --> 00:35:54,720 spreading X amount of faster than truth. 667 00:35:55,280 --> 00:35:57,760 I I've come across this thing called Brandolini's law. 668 00:35:57,760 --> 00:35:59,480 Have you come across this idea Brandolini's Law? 669 00:35:59,800 --> 00:36:01,400 Yeah. It's it's much easier to create 670 00:36:01,400 --> 00:36:04,400 bullshit than to refute it. Yeah, yeah, exactly, exactly. 671 00:36:06,360 --> 00:36:08,320 And yeah, I think it's called some like bullshit, the symmetry 672 00:36:08,320 --> 00:36:10,120 principle or something like that as well. 673 00:36:10,240 --> 00:36:12,160 I wrote the 1st paper on the psychology of bullshit. 674 00:36:12,160 --> 00:36:13,960 You don't think I know about the Brandolini's law? 675 00:36:14,120 --> 00:36:15,760 That's a that's a dining criminal. 676 00:36:15,760 --> 00:36:16,320 Thing. Thank you. 677 00:36:16,680 --> 00:36:19,720 Oh my God, how dare you. Even I've got I've got 678 00:36:19,720 --> 00:36:21,320 Frankfurt's own bullshit on my shelf over here. 679 00:36:22,160 --> 00:36:25,240 That's good representing and and sticking up for your territory 680 00:36:25,240 --> 00:36:29,120 there. So yeah, tell us, tell us about 681 00:36:29,120 --> 00:36:32,160 that. Like what is what is true about 682 00:36:32,760 --> 00:36:35,840 how misinformation spreads? Is it true that it spreads X 683 00:36:35,840 --> 00:36:36,600 much faster? Yeah. 684 00:36:36,720 --> 00:36:38,720 Is it 8 times more? I think so. 685 00:36:38,720 --> 00:36:40,720 I think it is true actually. And So what this is an 686 00:36:40,720 --> 00:36:44,000 interesting case study in itself because so there was a paper 687 00:36:44,000 --> 00:36:47,160 published, Deb Roy and and others published this paper in 688 00:36:47,160 --> 00:36:50,120 Science in the kind of early days of misinformation research 689 00:36:50,120 --> 00:36:54,720 or whatever, saying that like misinformation spreads faster 690 00:36:54,720 --> 00:36:57,920 than true information, false spreads faster than true on it 691 00:36:57,920 --> 00:37:00,160 was a Twitter analysis. We were really dubious about 692 00:37:00,160 --> 00:37:03,320 that because it was like most, it was among things that were 693 00:37:03,320 --> 00:37:06,840 fact checked, false things were spread faster than true things. 694 00:37:07,280 --> 00:37:10,080 And so we thought that was a weird kind of category of 695 00:37:10,080 --> 00:37:12,000 things, like the type of true things that are fact checked is 696 00:37:12,000 --> 00:37:13,920 different than just true things in general. 697 00:37:14,760 --> 00:37:16,720 But we've, there's actually been more follow-ups and we've looked 698 00:37:16,720 --> 00:37:19,080 at data ourselves and like it does seem to be the case that 699 00:37:19,520 --> 00:37:24,280 things that are dubious are have a kind of extra bit of our 700 00:37:24,280 --> 00:37:27,200 virality on social media. If you and if you look at all 701 00:37:27,200 --> 00:37:29,920 kind of ways of slicing that, it seems to be kind of generally 702 00:37:29,920 --> 00:37:31,440 the case. And there's a there's a kind of 703 00:37:31,440 --> 00:37:36,240 simple logic to it, which is that if you have freedom to say 704 00:37:36,240 --> 00:37:39,280 whatever you want and you're unconstrained by reality and the 705 00:37:39,280 --> 00:37:41,280 truth, you can say something more interesting. 706 00:37:42,080 --> 00:37:45,000 I mean, This is why we watch movies and TV. 707 00:37:45,280 --> 00:37:47,440 We kind of like say, OK, this is a different world now. 708 00:37:47,840 --> 00:37:50,920 It's OK that we can, you know, they're superheroes or whatever 709 00:37:50,920 --> 00:37:53,160 it is that's interesting. That's what narratives are, you 710 00:37:53,160 --> 00:37:55,880 know? And so it is the case that like, 711 00:37:56,360 --> 00:37:58,600 yeah, in certainly in the context of like kind of news 712 00:37:58,600 --> 00:38:01,840 content, if you want to stretch the truth, it's going to get 713 00:38:01,840 --> 00:38:04,160 more clicks. And like, it's part of that 714 00:38:04,160 --> 00:38:06,760 also, like if you're stretching the truth, then you're probably 715 00:38:06,760 --> 00:38:11,080 also being more willing to really hype up the emotional 716 00:38:11,080 --> 00:38:13,920 language or like, play on people's fears or whatever. 717 00:38:14,280 --> 00:38:17,360 And so, yeah, if you have no scruples, you can you can make a 718 00:38:17,360 --> 00:38:18,680 buck on social media, unfortunately. 719 00:38:21,080 --> 00:38:24,560 It's interesting the, the statement that a lie spreads 8 720 00:38:24,560 --> 00:38:28,680 times faster than the truth to me, I, I feel it doesn't have, 721 00:38:28,680 --> 00:38:30,720 it doesn't have all of those characteristics, right? 722 00:38:31,000 --> 00:38:35,720 It's, there's not as much emotion or creativity to it. 723 00:38:35,720 --> 00:38:38,600 But I, I think it has enough of those elements that it makes me 724 00:38:38,600 --> 00:38:42,160 wonder, is that true? You know, like it kind of feels 725 00:38:42,160 --> 00:38:44,840 like a lie. That's so excessively precise. 726 00:38:45,280 --> 00:38:47,640 It's like there's no way you can estimate that because how? 727 00:38:47,920 --> 00:38:50,280 Because think about what the think about what the claim is 728 00:38:50,280 --> 00:38:52,360 there. You're like, OK, we've done it. 729 00:38:52,800 --> 00:38:56,480 We've captured a representative sent of all true things and all 730 00:38:56,480 --> 00:38:58,400 false things. It's eight times we did it. 731 00:38:58,400 --> 00:38:59,960 Yeah, yeah. We're we're going to shoot them 732 00:38:59,960 --> 00:39:02,440 both out of a rocket and see how quickly they, yeah, they go. 733 00:39:02,680 --> 00:39:05,400 It's also a round Number. It's not like 8.35 times, it's 734 00:39:05,520 --> 00:39:08,720 eight times, Yeah. Anyways, in general, false 735 00:39:08,720 --> 00:39:10,200 things can spread faster than true things. 736 00:39:10,200 --> 00:39:11,560 But it's just, it doesn't mean all false. 737 00:39:11,600 --> 00:39:13,360 It's. And who knows how many times 738 00:39:13,480 --> 00:39:15,120 more is it's. Yeah. 739 00:39:15,520 --> 00:39:18,040 What would you say are some more characteristics of lies? 740 00:39:18,600 --> 00:39:23,160 If you're trying to arm someone to maybe spot misinformation out 741 00:39:23,160 --> 00:39:26,920 there, this sort of false precision might be part of it. 742 00:39:27,120 --> 00:39:30,520 You talked about the the emotional aspect. 743 00:39:30,520 --> 00:39:32,720 What are some other features of misinformation? 744 00:39:32,880 --> 00:39:37,240 Let's shrink the category to the like, online viral falsehoods 745 00:39:37,560 --> 00:39:39,720 because that's easier to kind of wrestle with. 746 00:39:39,720 --> 00:39:42,480 But yes, so I mean, So what? Those sorts of things are 747 00:39:42,480 --> 00:39:44,480 common, like using highly emotional language. 748 00:39:44,640 --> 00:39:47,640 But really that's what it's about is there's like an angle, 749 00:39:49,040 --> 00:39:50,960 a narrow way to think about misinformation is like things 750 00:39:50,960 --> 00:39:53,920 strictly speaking being false, which would be like something 751 00:39:53,920 --> 00:39:58,960 like if someone were to claim, oh, 10 million people died due 752 00:39:58,960 --> 00:40:00,280 to COVID. I actually have no idea how many 753 00:40:00,280 --> 00:40:02,080 people I should probably look that up. 754 00:40:02,400 --> 00:40:06,200 But actually it was half that number that was strictly 755 00:40:06,200 --> 00:40:08,560 speaking being false. But like ultimately those 756 00:40:08,840 --> 00:40:12,080 quantities are not really that different for people to 757 00:40:12,120 --> 00:40:14,440 understand. And really the ultimate the, the 758 00:40:14,440 --> 00:40:16,640 kind of like actual kind of just you're getting across. 759 00:40:16,640 --> 00:40:19,880 There is a lot of people. And so it's in a certain sense, 760 00:40:19,880 --> 00:40:22,520 it's kind of true. Yeah, people can't think about 761 00:40:22,520 --> 00:40:23,920 those numbers anyway, so it doesn't really. 762 00:40:24,240 --> 00:40:26,480 Yeah, exactly. So it's just it's a distinction 763 00:40:26,480 --> 00:40:30,200 without a difference. And so like misinformation often 764 00:40:30,200 --> 00:40:32,320 has this kind of quality where it's not just that it's like 765 00:40:32,320 --> 00:40:34,880 strictly speaking is false, but there's misleading that you're 766 00:40:34,880 --> 00:40:37,680 being deflected over here instead of over there. 767 00:40:37,800 --> 00:40:39,560 Haitians are eating their pets, for example. 768 00:40:39,560 --> 00:40:41,840 Yeah, yeah, exactly. Because that what that's about 769 00:40:41,840 --> 00:40:44,440 is like, so there's the specific fact, the claim that like 770 00:40:44,680 --> 00:40:47,560 they're eating the pets, but what's really being communicated 771 00:40:47,560 --> 00:40:48,920 there is that these are dangerous people that are 772 00:40:48,920 --> 00:40:50,360 different than you and and so on. 773 00:40:50,680 --> 00:40:53,520 And that's also false. You know, that's all misleading 774 00:40:53,520 --> 00:40:56,800 like that, you know, exactly. So when when you're kind of 775 00:40:56,800 --> 00:41:00,400 engaging online, you have to think about who is the message 776 00:41:00,400 --> 00:41:03,360 coming from and what are they trying to get from me? 777 00:41:03,360 --> 00:41:06,960 You have to kind of look behind the actual literal facts. 778 00:41:07,040 --> 00:41:08,840 Yeah, what's the point of this message? 779 00:41:09,320 --> 00:41:14,960 1 So 1 issue is that so my oldest brother there is like 780 00:41:14,960 --> 00:41:18,560 kind of down the rabbit hole or he more than in the past than he 781 00:41:18,560 --> 00:41:20,200 is now. But I had conversations about 782 00:41:20,200 --> 00:41:22,160 kind of who he's listening to and what kind of sources he gets 783 00:41:22,520 --> 00:41:24,800 because he thinks all mainstream media is fake news and so on. 784 00:41:25,200 --> 00:41:27,240 And the, you know, the problem with that is that people who are 785 00:41:27,240 --> 00:41:29,120 journalists can actually be fired. 786 00:41:29,160 --> 00:41:30,360 You know what I mean? Like if they would make 787 00:41:30,360 --> 00:41:32,800 something up, there's some mechanism by which they could be 788 00:41:32,800 --> 00:41:34,760 fired. But he likes listening to some 789 00:41:35,160 --> 00:41:38,040 dude on YouTube who like just says a bunch of stuff. 790 00:41:38,480 --> 00:41:40,320 That's OK. What stops this guy from lying 791 00:41:40,320 --> 00:41:42,480 or like saying like that he can't be fired. 792 00:41:42,520 --> 00:41:45,560 In fact, if anything is incentivized to say extreme 793 00:41:45,560 --> 00:41:48,240 things that people will listen to the so they listen to his 794 00:41:48,240 --> 00:41:52,440 videos or watch his videos and he says, yeah, but he doesn't 795 00:41:52,440 --> 00:41:54,160 lie though, So you know what I mean? 796 00:41:55,280 --> 00:41:57,680 But that didn't work. But but I think there's a good 797 00:41:57,680 --> 00:42:00,040 old underlying point you have to think about, like, what is this 798 00:42:00,040 --> 00:42:01,680 person's incentive to mislead me? 799 00:42:02,080 --> 00:42:05,240 And that's that's one way to kind of get around try to figure 800 00:42:05,240 --> 00:42:06,560 out what's true or false on social media. 801 00:42:06,560 --> 00:42:08,520 You got to think about what they're trying to do with the 802 00:42:08,520 --> 00:42:10,280 sources. Yeah, yeah. 803 00:42:10,440 --> 00:42:13,880 And I guess like one specific element we talked a little bit 804 00:42:14,160 --> 00:42:17,400 about that, you know, something that's emotionally arousing or 805 00:42:17,400 --> 00:42:19,560 appealing in some emotional way can have impact. 806 00:42:20,080 --> 00:42:23,960 And a very specific part of that, that honestly, it's always 807 00:42:23,960 --> 00:42:27,000 kind of pisses me off in some ways, is it's funny. 808 00:42:27,560 --> 00:42:30,600 That funny is one of the few things that can like really 809 00:42:30,600 --> 00:42:32,280 amplify a message more than anything. 810 00:42:32,520 --> 00:42:34,640 And I love funny. Like I, I love comedy. 811 00:42:34,640 --> 00:42:38,520 I love watching everything from yeah comedy specials to stand up 812 00:42:38,680 --> 00:42:42,440 to TV shows and and done some improv comedy myself. 813 00:42:42,920 --> 00:42:45,240 That's so ironic given how unfunny you are. 814 00:42:45,480 --> 00:42:49,320 I know it's it's. Wow, way to Crest the man. 815 00:42:49,880 --> 00:42:53,240 Anyway, what is unfortunate though is I feel like fun is 816 00:42:53,240 --> 00:42:57,200 it's kind of taking hostage by like this really bad actors 817 00:42:57,200 --> 00:43:01,000 where you have funny being used. I would say honestly very well 818 00:43:01,000 --> 00:43:02,480 by Trump. Most people are on the same page 819 00:43:02,480 --> 00:43:05,640 in terms of like part of his appeal and why it's hard to also 820 00:43:06,240 --> 00:43:11,600 counteract his bullshit is that he often times veils it in fun 821 00:43:11,760 --> 00:43:15,080 and or funny. Same with, like we mentioned, 822 00:43:15,640 --> 00:43:19,040 the idea that certain people have a lot of sway online and 823 00:43:19,040 --> 00:43:22,040 and can like amplify things. Elon Musk is probably one of 824 00:43:22,040 --> 00:43:23,520 those people. And there's few things that he 825 00:43:23,520 --> 00:43:27,280 loves to retweet as much as funny memes, you know, like a 826 00:43:27,280 --> 00:43:31,320 fun meme, even if it's lie, it's like that doesn't really bother 827 00:43:31,320 --> 00:43:33,040 him. You know, if it's funny, that 828 00:43:33,040 --> 00:43:36,600 kind of takes the box and and I'm just interested to hear your 829 00:43:36,600 --> 00:43:39,160 thoughts on on funny and it's really misinformation. 830 00:43:39,800 --> 00:43:43,600 Well, I mean, people can use it as a excuse essentially, or like 831 00:43:44,040 --> 00:43:46,800 you say something inappropriate, like that was a joke, you know 832 00:43:46,800 --> 00:43:47,960 what I mean? Or like, that's what Musk 833 00:43:47,960 --> 00:43:51,280 basically does on Twitter where he's like, oh, I was just trying 834 00:43:51,280 --> 00:43:54,480 to make people laugh. It just so happens that it was 835 00:43:54,480 --> 00:43:56,680 extremely harmful misinformation or whatever, you know what I 836 00:43:56,680 --> 00:43:58,240 mean? But but I was thinking, I 837 00:43:58,240 --> 00:43:59,360 thought it was funny, You know, if you have to. 838 00:43:59,640 --> 00:44:03,520 So you have to think this is the tension when it comes to comedy, 839 00:44:03,880 --> 00:44:07,280 which is like you have to think about what the consequences of 840 00:44:07,280 --> 00:44:09,840 the jokes are. And so like, I know that 841 00:44:09,840 --> 00:44:14,920 comedians do actually like lament this often, but I saw 842 00:44:14,920 --> 00:44:16,880 Jerry Seinfeld, he said he was wrong about it. 843 00:44:17,360 --> 00:44:20,320 He said what happens is the culture shifts. 844 00:44:20,320 --> 00:44:21,840 You have to know what's funny within the culture. 845 00:44:23,000 --> 00:44:26,200 And so that's I think that's a good way to put it. 846 00:44:26,880 --> 00:44:32,600 So I think one more thing about it too, is The Onion was like 847 00:44:32,680 --> 00:44:34,320 the original kind of fake news site. 848 00:44:35,440 --> 00:44:38,600 Of course, they did it in such a way that it was explicitly and 849 00:44:38,600 --> 00:44:42,520 kind of obviously satirical. What happened was used to be it 850 00:44:42,520 --> 00:44:43,040 used to. Yeah. 851 00:44:43,240 --> 00:44:44,840 And then I was just like reality used. 852 00:44:45,240 --> 00:44:49,080 To be an obvious difference. Yeah, yeah, yeah. 853 00:44:50,080 --> 00:44:52,800 So Facebook was was started clamping down on this kind of 854 00:44:52,800 --> 00:44:55,760 fake news, like where people are, you know, making these 855 00:44:55,760 --> 00:44:57,040 websites and this making things up. 856 00:44:57,480 --> 00:44:59,480 And So what those websites started to do is like, oh, we're 857 00:45:00,000 --> 00:45:03,040 actually we're satire sites, but they weren't promoting the 858 00:45:03,040 --> 00:45:05,320 satirical. And it was like, you could see 859 00:45:05,320 --> 00:45:09,080 that they were like the, the jokes were not, they were 860 00:45:09,080 --> 00:45:11,560 political. It was like really not meant and 861 00:45:11,560 --> 00:45:14,760 also wasn't really funny, unlike the Onion, which is actually 862 00:45:14,760 --> 00:45:16,520 quite funny. You know, you can see that they 863 00:45:16,520 --> 00:45:18,880 were putting effort into the political side, but not the 864 00:45:18,880 --> 00:45:21,040 funny side. And, and someone who knows 865 00:45:21,360 --> 00:45:23,560 comedy knows which, which one you're talking about. 866 00:45:24,560 --> 00:45:27,120 And in terms of like Trump being funny, he's usually funny kind 867 00:45:27,120 --> 00:45:28,240 of incidentally, you know what I mean? 868 00:45:28,240 --> 00:45:30,480 Like he, he doesn't really make jokes. 869 00:45:30,800 --> 00:45:32,800 He just says things that are funny. 870 00:45:34,400 --> 00:45:37,120 And so that's, you know, that's amusing for people that enjoy 871 00:45:37,160 --> 00:45:39,680 things that are funny. But but I think there's a deeper 872 00:45:39,680 --> 00:45:43,840 problem there, which is like there's conduct you'd expect 873 00:45:43,840 --> 00:45:47,680 from somebody and said that's a position which is like, it's OK 874 00:45:47,680 --> 00:45:49,600 to make jokes, but sometimes you have to be serious or whatever. 875 00:45:49,680 --> 00:45:51,440 I think. And it's actually, it's worse 876 00:45:51,440 --> 00:45:53,920 than it's different than that, which is Trump. 877 00:45:54,120 --> 00:45:58,960 So Trump's the apparent way that he approaches communication is 878 00:45:58,960 --> 00:46:02,720 very different than what you would expect and probably want 879 00:46:02,720 --> 00:46:05,800 from somebody in that sort of position, which is it doesn't 880 00:46:05,800 --> 00:46:08,400 really matter what I'm saying in a strict sense. 881 00:46:08,400 --> 00:46:11,480 I don't like that is the facts don't don't matter. 882 00:46:11,640 --> 00:46:14,560 It's the message that matters. That's what the the example was 883 00:46:14,680 --> 00:46:17,960 somebody pushed back to on. They asked them like, do you 884 00:46:17,960 --> 00:46:21,040 really think that they're eating the cats and the dogs in 885 00:46:21,360 --> 00:46:23,600 Springfield? And he said that was just a 886 00:46:23,600 --> 00:46:26,760 report that I heard. He's like, he's like, it doesn't 887 00:46:26,760 --> 00:46:28,560 he's like for him, it doesn't matter what I believe. 888 00:46:28,560 --> 00:46:31,320 I'm just saying things. I'm just saying things like. 889 00:46:33,400 --> 00:46:35,400 Yeah, that's totally fine. It could be true. 890 00:46:36,040 --> 00:46:38,160 I'll just say it like it doesn't matter if it's true or not. 891 00:46:38,160 --> 00:46:40,400 Like he doesn't. There's no regard for the truth. 892 00:46:40,760 --> 00:46:43,280 And so like whether something's funny that was, that's funny, 893 00:46:43,280 --> 00:46:45,920 I'll say it does it. Will some people be misled by 894 00:46:45,920 --> 00:46:47,680 it? Will it make people like other 895 00:46:47,680 --> 00:46:49,640 people angry? It doesn't matter because like 896 00:46:50,120 --> 00:46:52,520 I, you know, it's just something I want to say. 897 00:46:52,520 --> 00:46:54,280 So I'm going to say whatever it is that I want to say. 898 00:46:54,600 --> 00:46:56,520 And like, that's literally the stream of consciousness thing 899 00:46:56,520 --> 00:46:58,640 that he he does. So there's no filtering on like 900 00:46:58,960 --> 00:47:02,720 whether something is true, obviously, or like whether it 901 00:47:02,720 --> 00:47:03,960 would hurt people or whatever it is. 902 00:47:03,960 --> 00:47:07,480 That's just literally just. And so people, people, what's 903 00:47:07,480 --> 00:47:10,040 interesting is that people take that to mean honesty. 904 00:47:11,040 --> 00:47:12,520 And it's it's honesty in a certain sense. 905 00:47:12,520 --> 00:47:16,040 It's honesty to yourself. Like you're just like, in a 906 00:47:16,040 --> 00:47:17,480 certain sense, like a little kids. 907 00:47:17,480 --> 00:47:19,720 Yeah. The ones that. 908 00:47:19,720 --> 00:47:21,200 Like having any responsibility? Yeah, there's. 909 00:47:21,200 --> 00:47:23,120 No, there's no responsibility. There's no like, there's no 910 00:47:23,120 --> 00:47:24,520 filter in this. It's like everything that comes 911 00:47:24,520 --> 00:47:25,600 in their head comes out of their mouth. 912 00:47:26,000 --> 00:47:28,640 That's one way of being honest. I mean, what we kind of want 913 00:47:28,640 --> 00:47:31,200 honesty is like caring about the truth and getting things right. 914 00:47:31,440 --> 00:47:33,040 That's what is the important part of being honest. 915 00:47:33,040 --> 00:47:35,800 For a president, yeah, yeah. Of the United States. 916 00:47:36,240 --> 00:47:38,400 Or someone who's like a science scientist or like, a 917 00:47:38,400 --> 00:47:39,920 communicator. These are the things that are 918 00:47:39,920 --> 00:47:41,360 important. If you're in the public space 919 00:47:41,560 --> 00:47:44,960 and you have a large audience, being honest and being truthful 920 00:47:44,960 --> 00:47:47,200 is what important, not just being, like, genuine. 921 00:47:47,320 --> 00:47:48,960 You know, doesn't matter who you are. 922 00:47:48,960 --> 00:47:51,280 What matters is that you're doing good in the world. 923 00:47:51,320 --> 00:47:54,760 Yeah. All right, it is time for us to 924 00:47:54,960 --> 00:47:59,560 jump to our quick fire round. This is a game, little game that 925 00:47:59,560 --> 00:48:02,480 we play. It's called to AI or Not to AI, 926 00:48:02,840 --> 00:48:06,080 and we're going to give you a bunch of tasks and you're going 927 00:48:06,080 --> 00:48:10,160 to tell us whether that use case is well suited to AI or not. 928 00:48:10,160 --> 00:48:13,880 OK. All right, So the first one is 929 00:48:13,880 --> 00:48:17,160 about polling to AI or not to AI. 930 00:48:17,400 --> 00:48:22,560 Poll individual AI chat bots that have been trained on US 931 00:48:22,560 --> 00:48:27,560 demographics, past polling data, and representative media diets 932 00:48:27,560 --> 00:48:30,160 in order to predict the outcome of an election. 933 00:48:33,240 --> 00:48:36,720 I think the field says unsure. I'm going to say no because I'm 934 00:48:36,720 --> 00:48:40,880 a psychologist. OK, to AI or not to AI cast most 935 00:48:40,880 --> 00:48:44,040 likely votes for people who can't make it to the polls. 936 00:48:45,760 --> 00:48:50,000 No, no. I mean it's from based on the 937 00:48:50,000 --> 00:48:51,200 other one. Obviously, it's enough. 938 00:48:52,120 --> 00:48:56,800 OK, translate from brash American English to polite 939 00:48:56,800 --> 00:49:01,480 Canadian English. Oh yes, very good. 940 00:49:02,600 --> 00:49:05,880 Great use. We'll see if there's some bias 941 00:49:05,880 --> 00:49:09,080 to filter saying like it started recommending team. 942 00:49:09,080 --> 00:49:10,680 What is it called? Tim horton's. 943 00:49:10,680 --> 00:49:12,480 Tim Horton's. Tim horton's. 944 00:49:12,520 --> 00:49:14,360 Yeah, exactly. You get a copy. 945 00:49:14,720 --> 00:49:17,200 Double double Tim Horton's, which is so much sugar, by the 946 00:49:17,200 --> 00:49:18,240 way. You start getting all these 947 00:49:18,240 --> 00:49:21,240 hockey ads. Yeah, I would be fine. 948 00:49:21,240 --> 00:49:23,920 I would make me more like AI more appealing if it just like 949 00:49:23,920 --> 00:49:26,640 had a tuque on. A tuque is a winter hat, Sorry. 950 00:49:26,920 --> 00:49:28,800 I didn't even know that. It's a winter hat. 951 00:49:29,720 --> 00:49:32,880 OK, what about this? To AI or not to AI create a new 952 00:49:32,880 --> 00:49:39,920 celebrity. No, no, that's what is the Black 953 00:49:39,920 --> 00:49:41,200 Mirror. Yeah, let's just not. 954 00:49:41,680 --> 00:49:43,280 If it sounds like a Black Mirror episode, don't do it. 955 00:49:44,880 --> 00:49:49,160 OK, generate a gullibility profile for every person in the 956 00:49:49,320 --> 00:49:51,760 US. What do you mean by goal ability 957 00:49:51,760 --> 00:49:55,240 profile? How acceptable is that person to 958 00:49:55,600 --> 00:49:58,000 misinformation, for example? That's part. 959 00:49:58,000 --> 00:50:01,560 I think that's something that could be useful and interesting. 960 00:50:05,000 --> 00:50:07,600 Create pseudo profile bullshit memes. 961 00:50:08,000 --> 00:50:13,840 Oh yeah, yes, no question. Very quick. 962 00:50:13,920 --> 00:50:17,560 Did you come across Truth Terminal the the bot that's 963 00:50:17,560 --> 00:50:19,360 called Truth Terminal? No. 964 00:50:20,440 --> 00:50:23,200 OK, Basically it was a controversial AAI bought that 965 00:50:23,200 --> 00:50:26,920 has been able to generate millions in crypto by itself by 966 00:50:26,920 --> 00:50:29,560 creating really really obscene memes online. 967 00:50:30,200 --> 00:50:36,680 Oh, interesting. Spread fake news on social 968 00:50:36,680 --> 00:50:38,960 media. Wait is the answer. 969 00:50:39,080 --> 00:50:43,840 Can it do it or should it do it? Is it a use case well suited to 970 00:50:44,080 --> 00:50:45,280 AI? Sure. 971 00:50:46,520 --> 00:50:50,640 Oh yeah, making things up. OK then this is the big one 972 00:50:50,640 --> 00:50:53,320 then. To AI or not to AI combat the 973 00:50:53,320 --> 00:50:54,720 spread of fake news on social media. 974 00:50:55,440 --> 00:50:59,320 Yeah, yeah, for sure. TuneIn for the next episode. 975 00:51:00,640 --> 00:51:02,760 Perfect. Yes, the battle of the bots. 976 00:51:03,040 --> 00:51:08,200 OK. And that's a wrap. 977 00:51:08,520 --> 00:51:11,200 You've been listening to the Behavioral Design Podcast, 978 00:51:11,640 --> 00:51:14,080 brought to you by Habit Weekly and Nuanced Behavior. 979 00:51:14,440 --> 00:51:17,320 Sam and Aline tell me this season is packed with incredible 980 00:51:17,320 --> 00:51:21,480 insights about behavioral design and AI, so be sure to subscribe 981 00:51:21,480 --> 00:51:23,200 and share the podcast with your friends. 982 00:51:23,440 --> 00:51:25,600 Though you might want to keep it away from your enemies. 983 00:51:26,960 --> 00:51:29,560 In case you haven't noticed, I'm an AI voice. 984 00:51:30,760 --> 00:51:33,520 Yep, pretty crazy. Quite the improvement since last 985 00:51:33,520 --> 00:51:35,520 season's AI outro, don't you think? 986 00:51:36,920 --> 00:51:39,440 And if you'd like to collaborate with us at Nuance Behavior, 987 00:51:39,680 --> 00:51:42,360 where we use behavioral design to craft digital products with 988 00:51:42,360 --> 00:51:46,720 Nuance, e-mail us at hello@nuancebehavior.com or book 989 00:51:46,720 --> 00:51:49,960 a call directly on our website, nuancebehavior.com. 990 00:51:51,400 --> 00:51:54,800 A special thanks to the amazing Dave Pizarro for our show music, 991 00:51:55,040 --> 00:51:57,920 and to Mei Chen Yap and April English for their help in 992 00:51:57,920 --> 00:51:59,800 producing and publishing this episode. 993 00:52:00,400 --> 00:52:03,120 Thanks again for tuning in. We'll be back soon with another 994 00:52:03,120 --> 00:52:06,360 exciting conversation where behavioral design and AI 995 00:52:06,360 --> 00:52:31,360 intersect. Oh. 996 00:53:07,920 --> 00:53:10,280 I still feel burned by that. You said that wasn't funny, but 997 00:53:10,280 --> 00:53:13,640 I'll I'll recover it. You know, it was a joke. 998 00:53:14,880 --> 00:53:18,080 That's like the irony of that. Like that was me trying to be 999 00:53:18,080 --> 00:53:22,720 funny and not being funny. That's that's the deep, deep 1000 00:53:22,720 --> 00:53:23,280 irony.