1 00:00:00,400 --> 00:00:02,800 Speaker 1: I'll get a team. Welcome to another installing the You Project. 2 00:00:02,800 --> 00:00:09,240 Speaker 1: Tiffany An Cook's joining me, the newly matched up cook 3 00:00:09,240 --> 00:00:12,360 Speaker 1: who's in a relationship like a grown up. Just quickly 4 00:00:12,400 --> 00:00:14,960 Speaker 1: before we go to the good professor, how are you 5 00:00:15,040 --> 00:00:17,479 Speaker 1: now that you've publicly been ouded by me? Are you 6 00:00:17,560 --> 00:00:20,400 Speaker 1: all right? Have you? If you're stringing a few words together? 7 00:00:20,480 --> 00:00:23,759 Speaker 2: Now? A big twenty four hours half, it's been a 8 00:00:23,760 --> 00:00:24,840 Speaker 2: big twenty four hours. 9 00:00:25,640 --> 00:00:27,639 Speaker 1: Oh, look at you like a grown up in a 10 00:00:27,720 --> 00:00:30,920 Speaker 1: relationship with another grown up. That's a big step for you. 11 00:00:31,960 --> 00:00:34,320 Speaker 2: It's a very big step. If only Stacy knew what 12 00:00:34,360 --> 00:00:35,400 Speaker 2: a big step it was. 13 00:00:36,040 --> 00:00:39,800 Speaker 1: You might have to well, doctor Stacy. Professor Stacy is 14 00:00:39,840 --> 00:00:42,599 Speaker 1: here and she's a clinical psychologist, and if anyone need 15 00:00:42,680 --> 00:00:47,000 Speaker 1: one needs one, it could be you, Professor Stacy would 16 00:00:47,040 --> 00:00:48,720 Speaker 1: welcome to the You Project. How are you? 17 00:00:49,960 --> 00:00:52,120 Speaker 2: I'm great, it's great to be here. 18 00:00:52,800 --> 00:00:55,320 Speaker 1: Yeah, well, we're very happy to meet you and have 19 00:00:55,360 --> 00:00:58,600 Speaker 1: a chat with you. Just to fill you in. Tiffany 20 00:00:58,600 --> 00:01:01,840 Speaker 1: An Cook, my able assistant over there. It is just 21 00:01:02,920 --> 00:01:07,880 Speaker 1: after rejecting all men and all possibilities of a relationship. 22 00:01:07,920 --> 00:01:15,000 Speaker 1: But oh, a decade, if a decade more, She's fallen 23 00:01:15,040 --> 00:01:20,679 Speaker 1: in love unexpectedly, and she's fallen in love and she 24 00:01:20,840 --> 00:01:23,679 Speaker 1: met the person she's fallen in love with on this 25 00:01:24,000 --> 00:01:27,520 Speaker 1: very podcast. So that is hilarious. So it's been a 26 00:01:27,640 --> 00:01:36,440 Speaker 1: groundbreaking few days here at the U Project. I feel like, yeah, yeah, 27 00:01:36,480 --> 00:01:38,280 Speaker 1: So anyway, you didn't need to know that, but I 28 00:01:38,280 --> 00:01:43,280 Speaker 1: thought i'd give you context. Tell us, tell my listeners, 29 00:01:43,400 --> 00:01:48,000 Speaker 1: our listeners, and where you are? Where do we find 30 00:01:48,040 --> 00:01:50,600 Speaker 1: you on this fine? What's a morning here in Australia, 31 00:01:50,640 --> 00:01:52,200 Speaker 1: but I think it's evening over there. 32 00:01:53,720 --> 00:01:56,440 Speaker 2: I'm in Los Angeles and it's about one o'clock in 33 00:01:56,480 --> 00:01:56,960 Speaker 2: the afternoon. 34 00:01:57,000 --> 00:01:59,920 Speaker 1: Okay, good yup. Now, can you, rather than me read, 35 00:02:00,360 --> 00:02:04,240 Speaker 1: rather than may colnkily read some bio off the interwebs, 36 00:02:04,280 --> 00:02:06,600 Speaker 1: can you tell my audience a bit about you, who 37 00:02:06,640 --> 00:02:08,480 Speaker 1: you are, what you do, just in terms of your 38 00:02:08,520 --> 00:02:14,040 Speaker 1: current work and obsession? Do we say obsessional, fascination or curiosity. 39 00:02:14,080 --> 00:02:16,720 Speaker 1: I'm sure it's an insection of all three. 40 00:02:17,000 --> 00:02:20,359 Speaker 2: Yeah, no, that's I think that's accurate. So I'm a professor. 41 00:02:20,600 --> 00:02:24,519 Speaker 2: I teach psychology and neuroscience at Scripts College in Claremont, 42 00:02:25,880 --> 00:02:28,120 Speaker 2: and you know, for a good ten years I've worked 43 00:02:28,160 --> 00:02:31,799 Speaker 2: one day a week at an elder abuse forensic center 44 00:02:32,919 --> 00:02:37,560 Speaker 2: and as a psychologist doing assessments, working out in the field, 45 00:02:37,720 --> 00:02:41,680 Speaker 2: working with law enforcement, and I just was seeing over 46 00:02:41,919 --> 00:02:47,160 Speaker 2: and over again scam victims for aud victims, and trying 47 00:02:47,200 --> 00:02:50,120 Speaker 2: to make sense of that. As a psychologist, I started, 48 00:02:50,680 --> 00:02:55,280 Speaker 2: I shifted my program of research from decision making generally 49 00:02:55,560 --> 00:03:01,560 Speaker 2: you know, older people, to trying to understand this phenomenon. 50 00:03:01,800 --> 00:03:05,480 Speaker 2: So I really have been kind of obsessed with it, 51 00:03:05,680 --> 00:03:10,640 Speaker 2: better understanding the psychology why people are vulnerable, what the 52 00:03:10,760 --> 00:03:13,720 Speaker 2: process is once they're kind of on the hook, how 53 00:03:13,760 --> 00:03:18,680 Speaker 2: it impacts them, and the like. And I end up 54 00:03:18,680 --> 00:03:22,800 Speaker 2: testifying in court and I think about this a lot. 55 00:03:23,720 --> 00:03:27,480 Speaker 1: I'm sure you do. Now. I know there's been probably 56 00:03:27,520 --> 00:03:32,000 Speaker 1: a million revelations, not literally but metaphorically, a million revelations 57 00:03:32,000 --> 00:03:35,440 Speaker 1: and kind of light bulb moments for you tell us 58 00:03:35,480 --> 00:03:39,320 Speaker 1: about something that's kind of really got your attention or 59 00:03:39,400 --> 00:03:43,920 Speaker 1: really maybe even surprised you coming out of your research 60 00:03:44,000 --> 00:03:46,119 Speaker 1: and you're kind of diving into this. 61 00:03:48,160 --> 00:03:52,760 Speaker 2: Something that's continued to interest me is the process by 62 00:03:52,760 --> 00:03:56,080 Speaker 2: which a scammer can take someone who's you know, maybe 63 00:03:56,120 --> 00:04:01,000 Speaker 2: a little lonely, maybe a little depressed, maybe you know, 64 00:04:01,200 --> 00:04:05,280 Speaker 2: has some vulnerability and take them to a point where 65 00:04:05,320 --> 00:04:08,280 Speaker 2: if you were to meet them, you would be sure 66 00:04:08,320 --> 00:04:09,240 Speaker 2: they were delusional. 67 00:04:10,000 --> 00:04:11,520 Speaker 1: Yeah right, you know. 68 00:04:11,680 --> 00:04:15,320 Speaker 2: So I have a case right now where the family 69 00:04:15,440 --> 00:04:19,760 Speaker 2: is like, please help us keep our family member from 70 00:04:19,760 --> 00:04:23,400 Speaker 2: getting on a plane and flying to Ghana right right, 71 00:04:24,120 --> 00:04:27,920 Speaker 2: Like there's there's so much evidence it's a scam. It's 72 00:04:27,960 --> 00:04:31,320 Speaker 2: so risky and this is. 73 00:04:32,920 --> 00:04:33,160 Speaker 1: Sorry. 74 00:04:34,040 --> 00:04:37,200 Speaker 2: Isn't a person that has some mental health history per se? 75 00:04:37,440 --> 00:04:43,880 Speaker 1: Right? M Like we've we've heard of I mean, we 76 00:04:43,960 --> 00:04:46,120 Speaker 1: see that play out over here as well. Of course 77 00:04:46,160 --> 00:04:51,440 Speaker 1: it happens everywhere, but where somebody in inverted commas forms 78 00:04:51,480 --> 00:04:56,479 Speaker 1: a relationship with a person and the person's oh no, no, 79 00:04:56,600 --> 00:04:59,640 Speaker 1: I know there are scams, but he's not that. You know, 80 00:05:00,080 --> 00:05:02,159 Speaker 1: he's not that or she's not that, and this is 81 00:05:02,240 --> 00:05:04,600 Speaker 1: different and I know that that happens, but that's not 82 00:05:04,640 --> 00:05:08,240 Speaker 1: what's happening here. And their year we've spoken, I've seen 83 00:05:08,279 --> 00:05:11,599 Speaker 1: photos of their family or I've seen you know, and 84 00:05:11,680 --> 00:05:14,320 Speaker 1: he or she sent me this and that, and I 85 00:05:14,400 --> 00:05:17,040 Speaker 1: know you're worried, but you don't. It's like they are 86 00:05:17,160 --> 00:05:20,800 Speaker 1: fully down the rabbit hole, aren't they. They totally in 87 00:05:20,839 --> 00:05:25,080 Speaker 1: their mind. It's almost like their family becomes the enemy 88 00:05:26,200 --> 00:05:29,400 Speaker 1: and who are trying to derail their happiness. 89 00:05:29,480 --> 00:05:34,320 Speaker 2: Right, Oh, that's absolutely right. Yeah, yeah, and the scammers 90 00:05:34,360 --> 00:05:37,040 Speaker 2: are so good about putting that wedge in. You know, 91 00:05:37,160 --> 00:05:40,840 Speaker 2: it's the victim and the family using these tactics to 92 00:05:40,920 --> 00:05:42,920 Speaker 2: keep pushing them away. Yeah, exactly. 93 00:05:42,920 --> 00:05:47,159 Speaker 1: And what's the underlying psychology there is that just I'm 94 00:05:47,240 --> 00:05:50,760 Speaker 1: super lonely. Someone's giving me attention, someone's giving me affection 95 00:05:51,640 --> 00:05:55,719 Speaker 1: or albeit manufactured, but to me, the experience is real. 96 00:05:56,839 --> 00:05:59,480 Speaker 1: Is that that feeling that some kind of void. 97 00:06:01,120 --> 00:06:04,800 Speaker 2: So if we're if we're talking about like a romance scam, uh, 98 00:06:05,080 --> 00:06:08,400 Speaker 2: you know, there's there's not a lot of literature suggesting 99 00:06:08,640 --> 00:06:15,400 Speaker 2: a prototype. It's it's usually something more like wanting a relationship, 100 00:06:15,920 --> 00:06:19,240 Speaker 2: you know, maybe telling people you know, I think I'm ready, 101 00:06:19,360 --> 00:06:23,000 Speaker 2: I'm ready to meet the one, yes, you know, like Tiffany, 102 00:06:23,720 --> 00:06:31,680 Speaker 2: and and then putting themselves on dating sites, right, which 103 00:06:31,720 --> 00:06:34,840 Speaker 2: is totally a legitimate step you know, to take when 104 00:06:34,880 --> 00:06:38,600 Speaker 2: you're ready to have a relationship, and then not very 105 00:06:38,640 --> 00:06:43,200 Speaker 2: good at disserting red flags right away. So you know, 106 00:06:43,320 --> 00:06:45,680 Speaker 2: some red flags or if you're like a guy in 107 00:06:45,720 --> 00:06:49,159 Speaker 2: your fifties and the woman is thirty or younger and 108 00:06:49,320 --> 00:06:53,360 Speaker 2: very attractive. That's I'm sorry to say, that's probably a 109 00:06:53,360 --> 00:06:53,920 Speaker 2: red flag. 110 00:06:54,640 --> 00:06:57,359 Speaker 1: Oh my god, I wish I had it. Why didn't 111 00:06:57,400 --> 00:07:05,200 Speaker 1: we do this yesterday? That's yes, yeah, I get it. Tiffy, 112 00:07:05,200 --> 00:07:09,280 Speaker 1: you sure that you're tiff You sure that your bloke's not? AI? 113 00:07:09,560 --> 00:07:12,480 Speaker 1: Is sure he's not? Have you actually met him in person? 114 00:07:13,360 --> 00:07:15,320 Speaker 2: I think I might be I might have been scammed. 115 00:07:16,120 --> 00:07:18,320 Speaker 1: You could have been scammed. Maybe the guy that you 116 00:07:18,440 --> 00:07:22,720 Speaker 1: met is a bloody a cyborg is a biological kind 117 00:07:22,720 --> 00:07:29,000 Speaker 1: of technological interface. That's just very convincing. Sorry, prof speaking 118 00:07:29,040 --> 00:07:34,440 Speaker 1: of AI. Professor that the scammers must be rubbing their 119 00:07:34,560 --> 00:07:38,920 Speaker 1: hands together with the rapid evolution of what can be 120 00:07:38,960 --> 00:07:39,600 Speaker 1: done now with. 121 00:07:39,600 --> 00:07:45,480 Speaker 2: AI, Yeah, it's it's a great tool for them. Sadly, 122 00:07:46,160 --> 00:07:48,960 Speaker 2: you know, he used to be like, if you were 123 00:07:49,000 --> 00:07:52,160 Speaker 2: talking to a bond, you could tell like within a 124 00:07:52,200 --> 00:07:57,880 Speaker 2: few exchanges, right, I mean pretty recently, yes, And now 125 00:07:58,080 --> 00:08:00,840 Speaker 2: like if you're doing like a cuss to more service, 126 00:08:00,960 --> 00:08:05,160 Speaker 2: like the tenor of the voice, it's much more. If 127 00:08:05,200 --> 00:08:07,720 Speaker 2: you like, if you're speaking to a bot, it can 128 00:08:07,800 --> 00:08:11,600 Speaker 2: take my experience, many more exchanges before you're like, oh 129 00:08:11,680 --> 00:08:16,160 Speaker 2: my god, this isn't even a person. Yes, yes, you know, 130 00:08:16,200 --> 00:08:20,280 Speaker 2: they've cracked down on the spelling mistakes and the bad grammar. 131 00:08:20,960 --> 00:08:27,680 Speaker 2: The messaging, the communication is much better. And yeah, I 132 00:08:27,680 --> 00:08:33,840 Speaker 2: mean it's just every way to target youse social media, texting, email, phones, 133 00:08:34,080 --> 00:08:35,040 Speaker 2: either using AI. 134 00:08:36,880 --> 00:08:40,440 Speaker 1: It's so funny you firstly, do you use I mean yourself, 135 00:08:40,480 --> 00:08:42,920 Speaker 1: do you use II data Day? Do you use whatever 136 00:08:43,000 --> 00:08:47,320 Speaker 1: che apt or Claude or any of those, either professionally 137 00:08:47,400 --> 00:08:47,920 Speaker 1: or personally. 138 00:08:48,760 --> 00:08:51,200 Speaker 2: You know, I've just started playing with it myself. Honestly, 139 00:08:51,640 --> 00:08:53,640 Speaker 2: I was a little weary of it as a professor, 140 00:08:53,720 --> 00:08:56,360 Speaker 2: but I'm curious about it too. 141 00:08:57,240 --> 00:09:02,920 Speaker 1: Yeah, it's sometimes okay, So this morning, so it's what 142 00:09:03,040 --> 00:09:06,559 Speaker 1: is It's eight point fifteen here, and I was walking 143 00:09:06,600 --> 00:09:09,480 Speaker 1: to the cafe, which is a six minute walk, and 144 00:09:09,520 --> 00:09:14,600 Speaker 1: I jumped in to chat GPT, just in audio mode, 145 00:09:14,600 --> 00:09:18,679 Speaker 1: and I said, tell me about professor Stacy Would and 146 00:09:18,720 --> 00:09:20,720 Speaker 1: it just started telling me about you. I'm like cool, 147 00:09:20,760 --> 00:09:22,760 Speaker 1: And then I asked a few questions and it gave 148 00:09:22,800 --> 00:09:25,360 Speaker 1: me some answers about you, and like what is her 149 00:09:25,400 --> 00:09:29,120 Speaker 1: main focus of her research? And like I'd already I'd 150 00:09:29,360 --> 00:09:31,840 Speaker 1: already looked at you yesterday and done a little bit 151 00:09:31,840 --> 00:09:35,640 Speaker 1: of reading and researching, but just as a and it's 152 00:09:35,679 --> 00:09:40,600 Speaker 1: it's so interesting where I'm like, and I go, if 153 00:09:40,640 --> 00:09:44,400 Speaker 1: you were interviewing and I don't have any interview questions 154 00:09:44,400 --> 00:09:46,520 Speaker 1: in front of me, clearly I just ramble on. I said, 155 00:09:46,520 --> 00:09:49,400 Speaker 1: but if you're interviewing Stacy, what would you ask her? 156 00:09:49,400 --> 00:09:52,200 Speaker 1: And it just goes this bang bang bang, and it's 157 00:09:52,360 --> 00:09:55,760 Speaker 1: like there's no delay and the questions are great, and 158 00:09:55,800 --> 00:10:00,360 Speaker 1: it's specific to you, and you know, while oh, you're 159 00:10:00,440 --> 00:10:02,800 Speaker 1: not nobody, of course, it's not like you have a 160 00:10:02,840 --> 00:10:06,600 Speaker 1: world famous profile, right, you know what I mean. And 161 00:10:06,640 --> 00:10:09,280 Speaker 1: it's just it knows all about you, and it's like, well, 162 00:10:09,320 --> 00:10:11,320 Speaker 1: she's this, and she's that, and she works here and 163 00:10:11,320 --> 00:10:14,800 Speaker 1: she's a professor of this and she's a clinical psychology 164 00:10:14,800 --> 00:10:18,280 Speaker 1: and I'm like, oh my this it is It is 165 00:10:18,400 --> 00:10:21,880 Speaker 1: hard to resist in that use the right way. I 166 00:10:21,960 --> 00:10:24,840 Speaker 1: underline that it's a very helpful resource. 167 00:10:26,480 --> 00:10:30,960 Speaker 2: Yeah, well, that's of course chilling. And I did a 168 00:10:30,960 --> 00:10:33,000 Speaker 2: similar thing about you this morning when I went for 169 00:10:33,040 --> 00:10:38,040 Speaker 2: a walk. No, I didn't use it, but that's a 170 00:10:38,080 --> 00:10:41,080 Speaker 2: great idea. I just listened to some snippets from some 171 00:10:41,080 --> 00:10:44,120 Speaker 2: of your Paws podcast to just get a sense of 172 00:10:44,160 --> 00:10:48,280 Speaker 2: your style and your you know the topics that are covered, 173 00:10:48,559 --> 00:10:50,840 Speaker 2: but your waste seems a lot more efficient. 174 00:10:51,760 --> 00:10:53,800 Speaker 1: TIF did you hear that I have a style? Did 175 00:10:53,840 --> 00:11:03,439 Speaker 1: you hear that I'm a not style? I have a style? 176 00:11:05,480 --> 00:11:08,720 Speaker 1: So I might be wrong in assuming this. Well, actually 177 00:11:08,760 --> 00:11:10,640 Speaker 1: I know the answer to this because I did hear 178 00:11:10,679 --> 00:11:13,599 Speaker 1: you in an interview. But I would have assumed that 179 00:11:14,400 --> 00:11:19,680 Speaker 1: older people got scammed the most. But that's not always true. 180 00:11:21,240 --> 00:11:24,120 Speaker 2: Yeah, correct, I would say when I was starting doing 181 00:11:24,160 --> 00:11:27,400 Speaker 2: this work like ten years ago, it was definitely true, 182 00:11:28,160 --> 00:11:31,920 Speaker 2: and the kind of federal statistics in the US were 183 00:11:31,960 --> 00:11:35,160 Speaker 2: bearing it out. And then after twenty sixteen, twenty seventeen, 184 00:11:36,160 --> 00:11:40,199 Speaker 2: you know, the social media you know, it's not a coincident. Yeah, 185 00:11:40,240 --> 00:11:43,880 Speaker 2: it's like the scammers, don't They like older people because 186 00:11:43,880 --> 00:11:47,400 Speaker 2: they tend to have more money, so they're targeted more. 187 00:11:48,040 --> 00:11:50,560 Speaker 2: But they're happy to scam younger people. And it was 188 00:11:50,600 --> 00:11:55,120 Speaker 2: easier to reach people, you know, on social media, and 189 00:11:56,360 --> 00:11:59,200 Speaker 2: so the scams look a little different. You know, younger 190 00:11:59,200 --> 00:12:03,240 Speaker 2: adults tend to be more like us, like a shopping scam, Yes, 191 00:12:04,200 --> 00:12:07,560 Speaker 2: investment scams. Have you heard the term pig butchering? 192 00:12:08,520 --> 00:12:10,160 Speaker 1: No, no, tell us about that. 193 00:12:11,320 --> 00:12:15,280 Speaker 2: It's a horrible scam, but it is a crypto scam 194 00:12:15,679 --> 00:12:18,959 Speaker 2: where you're approached maybe on LinkedIn or some job board 195 00:12:19,080 --> 00:12:23,800 Speaker 2: or some kind of legitimate site, and you know, befriended 196 00:12:24,040 --> 00:12:27,280 Speaker 2: and then it's not necessarily even a romance. It's more like, 197 00:12:27,880 --> 00:12:30,360 Speaker 2: you know, we have an investment group, and you can 198 00:12:30,400 --> 00:12:33,680 Speaker 2: see our gains, and they start to like share, you know, 199 00:12:34,320 --> 00:12:37,959 Speaker 2: screenshots of the money they're making, and they help that 200 00:12:38,120 --> 00:12:40,960 Speaker 2: victims set up like a fake wallet. It looks real, 201 00:12:41,040 --> 00:12:44,480 Speaker 2: it looks like coinbase, it's very sophisticated or it's similar, 202 00:12:45,559 --> 00:12:49,240 Speaker 2: and they show them getting gains and when the scammers 203 00:12:49,280 --> 00:12:53,520 Speaker 2: think they've gotten everything they can, they just disappear. Yeah, 204 00:12:53,559 --> 00:12:57,520 Speaker 2: and they but once once it's fat enough and if 205 00:12:57,520 --> 00:13:00,040 Speaker 2: you try to get money out, it's like, oh, you 206 00:13:00,080 --> 00:13:01,720 Speaker 2: have so many capital gains, you have to pay this 207 00:13:01,800 --> 00:13:04,520 Speaker 2: taxes first before we can release it. And then they 208 00:13:04,559 --> 00:13:09,000 Speaker 2: get more money. So that is more like people that 209 00:13:09,040 --> 00:13:12,160 Speaker 2: are younger, like probably like thirties, forties, fifties, because they 210 00:13:13,040 --> 00:13:17,040 Speaker 2: have to have money, but also they're interested in crypto 211 00:13:17,080 --> 00:13:21,280 Speaker 2: and they're online a lot, so the scammers have adapted 212 00:13:21,360 --> 00:13:25,400 Speaker 2: to target you know, they'll target teenagers and gaming, you know, 213 00:13:25,960 --> 00:13:32,240 Speaker 2: discord type approaches. They are, they're everywhere, so they just 214 00:13:32,440 --> 00:13:35,640 Speaker 2: curate the scam based on the demographics they're targeting. 215 00:13:35,679 --> 00:13:39,840 Speaker 1: Now, so I know there's no single like with anything, 216 00:13:39,880 --> 00:13:44,760 Speaker 1: there's no single intervention or pill or solution. But but 217 00:13:45,200 --> 00:13:48,880 Speaker 1: what the what's on the table as things that can 218 00:13:48,960 --> 00:13:53,480 Speaker 1: help us, that protect ourselves, will protect people that we love. 219 00:13:54,800 --> 00:14:00,319 Speaker 2: So for older people, like if you have parents, adult 220 00:14:00,360 --> 00:14:06,800 Speaker 2: children and parents having some conversations about safeguards here in 221 00:14:06,840 --> 00:14:08,920 Speaker 2: the US, you can be added as like a trusted 222 00:14:08,960 --> 00:14:13,480 Speaker 2: other to bank accounts, not not with control, but just 223 00:14:13,640 --> 00:14:17,080 Speaker 2: being able to you know, agreeing ahead of time to 224 00:14:17,120 --> 00:14:22,360 Speaker 2: be alerted of suspicious transactions. So that's yeah, And it's 225 00:14:22,400 --> 00:14:25,600 Speaker 2: again it's not when the we were talking about, when 226 00:14:25,640 --> 00:14:28,040 Speaker 2: the person's in the throes of it, it's it's almost 227 00:14:28,080 --> 00:14:31,520 Speaker 2: impossible to get them to agree to have that kind 228 00:14:31,520 --> 00:14:33,800 Speaker 2: of help. But if you can get to them, you know, 229 00:14:33,800 --> 00:14:36,840 Speaker 2: if you just have a conversation and say, look, let's 230 00:14:38,040 --> 00:14:41,040 Speaker 2: let's talk about this and put some safeguards in place. 231 00:14:42,040 --> 00:14:46,680 Speaker 2: I think structural changes, like I'd love to see big platforms, 232 00:14:46,720 --> 00:14:53,000 Speaker 2: meta et cetera, indeed crack down more on on scammers 233 00:14:53,360 --> 00:14:58,880 Speaker 2: or improve their algorithms for detecting scams. I think it's 234 00:14:58,920 --> 00:15:02,400 Speaker 2: it's hard for the human brain now to discern legitimate 235 00:15:02,440 --> 00:15:09,040 Speaker 2: from illegitimate messaging. Yeah, so that would be another kind 236 00:15:09,080 --> 00:15:13,240 Speaker 2: of structural recommendation. It is happening in the UK. They 237 00:15:13,280 --> 00:15:15,800 Speaker 2: are they are moving, They have moved forward with some 238 00:15:17,040 --> 00:15:21,120 Speaker 2: legislation around that. In the US there's been more of 239 00:15:21,200 --> 00:15:23,800 Speaker 2: a focus on trying to get the banks to be 240 00:15:23,800 --> 00:15:32,200 Speaker 2: better at identifying suspicious transactions. Yes, at the individual level, 241 00:15:32,280 --> 00:15:36,360 Speaker 2: you know, like you know kids in school financial literacy, 242 00:15:36,520 --> 00:15:38,760 Speaker 2: you could have some add some scam literacy to that. 243 00:15:40,120 --> 00:15:45,400 Speaker 1: Yeah. My parents are eighty six and uh, her mum 244 00:15:45,480 --> 00:15:49,560 Speaker 1: rings me every day with something she's like. And yesterday 245 00:15:49,600 --> 00:15:54,760 Speaker 1: it was like her phone wanted to update something and 246 00:15:54,800 --> 00:15:57,720 Speaker 1: I'm like, what are the what does it say? And 247 00:15:57,760 --> 00:16:00,680 Speaker 1: she says it says update now or lighter And I said, well, 248 00:16:00,680 --> 00:16:03,640 Speaker 1: that's probably fine, I said, but just press later and 249 00:16:04,920 --> 00:16:06,840 Speaker 1: I'll see. I'm seeing her in a couple of days, 250 00:16:06,880 --> 00:16:08,920 Speaker 1: I said, when I get there, old, I'll have a 251 00:16:08,920 --> 00:16:10,560 Speaker 1: look at and I'll do what needs to be done. 252 00:16:10,560 --> 00:16:16,800 Speaker 1: But it's like, in a way, I'm glad they're technically 253 00:16:16,920 --> 00:16:21,360 Speaker 1: or technologically inept because they don't have social media, They 254 00:16:21,480 --> 00:16:26,480 Speaker 1: don't really have email, they don't know all of their 255 00:16:26,520 --> 00:16:30,680 Speaker 1: banking and everything is done by me or more accurately, Melissa, 256 00:16:30,680 --> 00:16:34,880 Speaker 1: who the other highly efficient person who runs my life. 257 00:16:35,000 --> 00:16:37,200 Speaker 1: So they don't you know, they wouldn't know how to 258 00:16:37,240 --> 00:16:41,720 Speaker 1: take money out online or buy anything online, and so 259 00:16:41,800 --> 00:16:45,520 Speaker 1: they really don't get presented with other than the odd 260 00:16:45,560 --> 00:16:49,480 Speaker 1: thing on my mum's phone, which she you know, she 261 00:16:49,560 --> 00:16:51,920 Speaker 1: genuinely doesn't. I just go if anything comes, I go. 262 00:16:52,000 --> 00:16:55,520 Speaker 1: If somebody rings you and you don't know the person 263 00:16:56,280 --> 00:16:58,920 Speaker 1: and they're telling you you need to do something, I 264 00:16:58,960 --> 00:17:02,480 Speaker 1: go just hang up, you know, or at the very 265 00:17:02,520 --> 00:17:04,840 Speaker 1: least and then ring me, and I'll ring that whoever 266 00:17:04,880 --> 00:17:08,159 Speaker 1: that alleged person is, you know. So it's it's I 267 00:17:08,160 --> 00:17:13,639 Speaker 1: think sometimes, you know, even though it's almost becoming impossible 268 00:17:13,760 --> 00:17:17,240 Speaker 1: not to have your toe in technology and the internet 269 00:17:17,320 --> 00:17:20,240 Speaker 1: in twenty twenty five, of course, but for you know, 270 00:17:20,320 --> 00:17:23,600 Speaker 1: for people who are really really kind of advanced in years, 271 00:17:23,680 --> 00:17:26,520 Speaker 1: like my mum and dad, it's almost too late to 272 00:17:26,640 --> 00:17:28,960 Speaker 1: open the door and try and educate them because they 273 00:17:29,119 --> 00:17:32,000 Speaker 1: just don't well, my mum and dad anyway, they don't 274 00:17:32,000 --> 00:17:35,560 Speaker 1: even understand the language. It's just overwhelming for them, you know. 275 00:17:37,240 --> 00:17:42,000 Speaker 2: Yeah, so you know, fortunately they have you. Yes, yeah, So, 276 00:17:42,080 --> 00:17:45,479 Speaker 2: let's comfort with technology can be a risk factor for 277 00:17:45,560 --> 00:17:47,360 Speaker 2: those that don't have a safeguard. 278 00:17:48,040 --> 00:17:49,280 Speaker 1: Yeah. 279 00:17:49,840 --> 00:17:56,240 Speaker 2: A really popular scam was impersonation of Microsoft. So they 280 00:17:56,240 --> 00:17:59,080 Speaker 2: were sort of online but you know, maybe Facebook and 281 00:17:59,080 --> 00:18:03,520 Speaker 2: some emailing, and it would be like a pop up 282 00:18:03,560 --> 00:18:08,320 Speaker 2: that says your computer is compromised, call this number. Yeah, right, 283 00:18:08,880 --> 00:18:11,640 Speaker 2: and then from there they you know, coach them through 284 00:18:11,800 --> 00:18:17,119 Speaker 2: all of these you know, confusing steps to fix their computer, move, 285 00:18:17,880 --> 00:18:22,080 Speaker 2: you know, transfer accounts, and they actually can gain control 286 00:18:22,119 --> 00:18:26,400 Speaker 2: of the computer if the person follows all the steps. Yeah. Really, 287 00:18:27,920 --> 00:18:30,719 Speaker 2: but yeah, that's right. I mean so, but also younger, 288 00:18:30,800 --> 00:18:33,600 Speaker 2: younger adults who are constantly online have more exposure. 289 00:18:35,320 --> 00:18:37,560 Speaker 1: And also some of these people, now, like I've heard 290 00:18:38,119 --> 00:18:43,880 Speaker 1: I heard you do an interview on some American show anyway, 291 00:18:44,760 --> 00:18:47,119 Speaker 1: Dione chatted to you for about six or seven minutes. 292 00:18:47,160 --> 00:18:50,320 Speaker 1: You were part of a but that we're talking about 293 00:18:50,440 --> 00:18:57,119 Speaker 1: how articulate and smooth and charismatic and like some of 294 00:18:57,160 --> 00:19:02,919 Speaker 1: these scammers sound absolutely jit like. It doesn't sound like 295 00:19:03,000 --> 00:19:07,040 Speaker 1: some educated, uneducated bum sitting in his mum's basement just 296 00:19:07,080 --> 00:19:10,479 Speaker 1: trying to trying to scam. It sounds like you're actually 297 00:19:10,520 --> 00:19:14,920 Speaker 1: talking to an employee of an organization who's very polished 298 00:19:15,000 --> 00:19:21,679 Speaker 1: and very capable. So no wonder people who are not 299 00:19:22,000 --> 00:19:25,440 Speaker 1: experienced or aware gets scammed because very convincing. 300 00:19:26,720 --> 00:19:29,560 Speaker 2: Yeah, and you know, kind of two points here. The 301 00:19:29,960 --> 00:19:33,560 Speaker 2: first step is to put you into that more emotional, 302 00:19:34,160 --> 00:19:39,040 Speaker 2: non deliberative mental state, Right, you're not at your best 303 00:19:39,200 --> 00:19:44,920 Speaker 2: in terms of I think deliberative reasoning. And then all 304 00:19:44,960 --> 00:19:47,680 Speaker 2: the queueing or talking about it's really it's out of hand, 305 00:19:47,880 --> 00:19:50,240 Speaker 2: like it's one of I was going to say one 306 00:19:50,280 --> 00:19:53,679 Speaker 2: of my favorite scams, but one of the most impressive 307 00:19:53,680 --> 00:20:00,200 Speaker 2: scams i've I've researched was targeting psychologists. Oh wow, yeah, yeah, 308 00:20:00,200 --> 00:20:02,480 Speaker 2: And a reporter reached out to me and I looked 309 00:20:02,520 --> 00:20:04,320 Speaker 2: into a little bit and we did a little peace 310 00:20:04,359 --> 00:20:07,119 Speaker 2: on it. And then I had like a former student 311 00:20:07,200 --> 00:20:10,520 Speaker 2: contact me and say, you know, I heard you and 312 00:20:10,720 --> 00:20:15,560 Speaker 2: this actually happened to me who came out HD wow, 313 00:20:15,600 --> 00:20:20,919 Speaker 2: and they the scam was that they had missed a 314 00:20:21,040 --> 00:20:23,520 Speaker 2: summons and they were at risk of losing their license. 315 00:20:24,800 --> 00:20:26,879 Speaker 2: And you know, you're you're getting a PhD. You know 316 00:20:26,920 --> 00:20:30,520 Speaker 2: how hard it is, right, It's like you would you 317 00:20:30,560 --> 00:20:32,680 Speaker 2: would freak out right, and you know, I'd just been 318 00:20:32,720 --> 00:20:35,560 Speaker 2: working for five years to get this degree. What do 319 00:20:35,640 --> 00:20:36,360 Speaker 2: I have to do? 320 00:20:37,080 --> 00:20:37,439 Speaker 1: Yeah? 321 00:20:37,520 --> 00:20:43,120 Speaker 2: And she said it was so realistic that like her, 322 00:20:43,240 --> 00:20:45,600 Speaker 2: her husband or family members were in law enforcement. You 323 00:20:45,640 --> 00:20:48,639 Speaker 2: could hear the sounds of the station and it sounded 324 00:20:48,680 --> 00:20:51,119 Speaker 2: like just like when our family members were at work 325 00:20:51,600 --> 00:20:55,480 Speaker 2: the background. Yes, yes, they're that good. 326 00:20:56,720 --> 00:21:03,119 Speaker 1: I've thought this through Melissa, who works with me. She 327 00:21:03,240 --> 00:21:06,480 Speaker 1: got one of my papers and put it into I 328 00:21:06,520 --> 00:21:08,840 Speaker 1: don't even know what the AI is, but put it 329 00:21:08,880 --> 00:21:16,160 Speaker 1: into this AI program. And the program turns my academic 330 00:21:17,320 --> 00:21:20,959 Speaker 1: hard to understand, hard to read, highly confusing, you know, 331 00:21:21,760 --> 00:21:25,919 Speaker 1: psychoacademic jargon for the average person, and it turns it 332 00:21:25,960 --> 00:21:28,840 Speaker 1: into a podcast between a male in Inverted Commas and 333 00:21:28,880 --> 00:21:33,400 Speaker 1: a female in Inverted Comma's co host co hosts. So 334 00:21:33,480 --> 00:21:36,199 Speaker 1: these two people have a chat about my paper in 335 00:21:36,200 --> 00:21:38,800 Speaker 1: this research coming out of Australia, in this research team 336 00:21:38,800 --> 00:21:42,080 Speaker 1: and all of this, and it just turns my paper 337 00:21:42,200 --> 00:21:48,960 Speaker 1: into an interesting conversation about this research that anyone can understand. 338 00:21:49,359 --> 00:21:52,160 Speaker 1: And it goes for twenty one minutes. And I said 339 00:21:52,200 --> 00:21:54,120 Speaker 1: it to like twenty of my friends to go here, 340 00:21:54,160 --> 00:21:57,479 Speaker 1: this will help you understand my research and they're like, 341 00:21:58,000 --> 00:22:00,960 Speaker 1: what did you send me that two years ago. I'm like, yeah, 342 00:22:01,080 --> 00:22:05,200 Speaker 1: it's just the stuff that it can produce now and 343 00:22:05,880 --> 00:22:09,400 Speaker 1: you know, explain what can be confusing or complicated concepts 344 00:22:09,520 --> 00:22:14,000 Speaker 1: or ideas in a very It wasn't perfect, by the way, 345 00:22:14,400 --> 00:22:16,800 Speaker 1: but it was it was very good. It was I mean, 346 00:22:16,880 --> 00:22:20,719 Speaker 1: considering it turns it out in a few minutes. It's 347 00:22:21,280 --> 00:22:24,520 Speaker 1: it's as we say in Australia, it's bloody unbelievable what 348 00:22:24,560 --> 00:22:26,919 Speaker 1: they can produce now, Like what can happen? 349 00:22:29,600 --> 00:22:33,560 Speaker 2: Yeah, I agree, Like you know, I have to be 350 00:22:33,760 --> 00:22:36,760 Speaker 2: looking for students like are they plagiarizing? Are they using 351 00:22:36,800 --> 00:22:39,879 Speaker 2: ai I to have a suspicious paragraph? And before it 352 00:22:39,880 --> 00:22:43,200 Speaker 2: would be kind of clumsy, yes, and now I'm like, oh, 353 00:22:43,280 --> 00:22:44,680 Speaker 2: it's much harder to tell. 354 00:22:45,520 --> 00:22:49,560 Speaker 1: Yeah, And I think I think that's like I'm at 355 00:22:49,640 --> 00:22:53,600 Speaker 1: Monash University in Melbourne here in Australia, and I think 356 00:22:53,680 --> 00:22:56,720 Speaker 1: every you know, Melbourne University, University of New South Wales, 357 00:22:57,119 --> 00:23:00,600 Speaker 1: Monash where I'm at Deacon, all of the bigger universities 358 00:23:00,640 --> 00:23:03,399 Speaker 1: in Australia, they're all trying to figure out how to 359 00:23:03,440 --> 00:23:05,639 Speaker 1: deal with it. And I'm sure every union in the 360 00:23:05,680 --> 00:23:10,520 Speaker 1: States is the same because it's it's evolving so fast. 361 00:23:10,760 --> 00:23:12,600 Speaker 1: And I might get in trouble for saying this, but 362 00:23:14,000 --> 00:23:15,760 Speaker 1: you know, I kind of feel like some of the 363 00:23:15,840 --> 00:23:18,840 Speaker 1: decision makers at a higher level in my university anyway, 364 00:23:19,440 --> 00:23:21,960 Speaker 1: they're in their fifties and sixties and they're trying to 365 00:23:22,040 --> 00:23:25,320 Speaker 1: navigate this space that they don't understand nearly as well 366 00:23:25,760 --> 00:23:30,560 Speaker 1: as the students, you know, because all the students are 367 00:23:30,800 --> 00:23:35,200 Speaker 1: so good in this space. And you know, I'm kind 368 00:23:35,200 --> 00:23:37,760 Speaker 1: of a hybrid because I'm an old guy but I'm 369 00:23:37,760 --> 00:23:41,680 Speaker 1: also a student. But I think, yeah, trying to navigate 370 00:23:41,680 --> 00:23:44,439 Speaker 1: this over the next year or two, so people are 371 00:23:44,520 --> 00:23:48,359 Speaker 1: not coming, people are not getting a PhD in four weeks. 372 00:23:48,840 --> 00:23:52,960 Speaker 1: Tongue in cheek, but you know, it's like the stuff 373 00:23:53,000 --> 00:23:55,200 Speaker 1: that it can produce in a short amount of time, 374 00:23:55,680 --> 00:24:00,399 Speaker 1: which is almost indistinguishable between you know, like an actual 375 00:24:01,000 --> 00:24:04,119 Speaker 1: paper that's taken and research that stayed. Like my lit review, 376 00:24:04,160 --> 00:24:06,879 Speaker 1: as you would know, my systematic lit review from start 377 00:24:06,920 --> 00:24:09,720 Speaker 1: to finish. It took me two and a half years 378 00:24:09,760 --> 00:24:13,679 Speaker 1: to produce that paper, Like two and half years for 379 00:24:13,800 --> 00:24:18,960 Speaker 1: one paper, and it's like that could take half a 380 00:24:19,040 --> 00:24:23,399 Speaker 1: day or an hour using AI that's terrifying to me. 381 00:24:24,720 --> 00:24:26,480 Speaker 2: Yeah, and as you were saying, like, it's not bad 382 00:24:26,480 --> 00:24:30,119 Speaker 2: at getting like some big themes to make all the 383 00:24:30,200 --> 00:24:33,600 Speaker 2: connections or you know, do that correct Mullar level of 384 00:24:33,640 --> 00:24:35,480 Speaker 2: work that we have to do, you know, in terms 385 00:24:35,520 --> 00:24:39,680 Speaker 2: of the methodology. But yeah, it is, it is skilled. 386 00:24:40,960 --> 00:24:44,480 Speaker 1: We've we've got this thing that's just happened here prof 387 00:24:44,680 --> 00:24:51,119 Speaker 1: in Australia where they've banned social media nationally for kids 388 00:24:51,240 --> 00:24:52,960 Speaker 1: under sixteen. Have you heard about that? 389 00:24:53,480 --> 00:24:54,320 Speaker 2: No? No, I had? 390 00:24:54,480 --> 00:24:57,240 Speaker 1: Yeah, yeah, yeah so that When did that come in? 391 00:24:57,280 --> 00:24:58,520 Speaker 1: Tip a couple of days ago? 392 00:24:59,320 --> 00:25:01,720 Speaker 2: I think, so, yeah, yeah. 393 00:25:01,040 --> 00:25:05,080 Speaker 1: So it's what are we it's Thursday here, Yeah, it 394 00:25:05,119 --> 00:25:07,439 Speaker 1: came in I don't know, like two or three days ago. 395 00:25:07,920 --> 00:25:13,560 Speaker 1: And so children under sixteen in Australia no social media 396 00:25:13,640 --> 00:25:20,480 Speaker 1: access and it's it hasn't gone down. Well, let's say 397 00:25:20,520 --> 00:25:25,960 Speaker 1: that it hasn't been well received. How do they implement 398 00:25:26,040 --> 00:25:32,119 Speaker 1: that or how do they enforce it? They the kids 399 00:25:32,119 --> 00:25:34,199 Speaker 1: have got to jump through tif you're probably better at 400 00:25:34,240 --> 00:25:36,679 Speaker 1: answering this, but they've got to jump through all of 401 00:25:36,720 --> 00:25:40,640 Speaker 1: these hoops. There's got to be because they're I think 402 00:25:40,680 --> 00:25:42,639 Speaker 1: their day to birth and they're all that is that 403 00:25:42,720 --> 00:25:44,880 Speaker 1: in there, Tiff. I don't know how do they. 404 00:25:44,840 --> 00:25:47,639 Speaker 2: Enflange how I've got no idea how it works, to 405 00:25:47,640 --> 00:25:48,400 Speaker 2: be honest. 406 00:25:48,880 --> 00:25:51,720 Speaker 1: Yeah, but they've got there's a whole lot of stuff 407 00:25:51,760 --> 00:25:54,720 Speaker 1: in place, and even a lot of parents I should 408 00:25:54,800 --> 00:25:58,280 Speaker 1: just go I don't know. Prop But the answer is, 409 00:25:58,680 --> 00:26:01,199 Speaker 1: or part of the issue, is that a lot of 410 00:26:01,280 --> 00:26:04,520 Speaker 1: parents some parents love it. I'd say sixty seventy percent 411 00:26:04,560 --> 00:26:08,120 Speaker 1: of their parents like it because they think social media 412 00:26:08,240 --> 00:26:12,280 Speaker 1: is doing harm to their kids or potentially, but there's probably, 413 00:26:12,680 --> 00:26:14,879 Speaker 1: I don't know, probably about a third of parents just 414 00:26:15,040 --> 00:26:18,480 Speaker 1: aren't for it at all. So this has been dominating 415 00:26:18,640 --> 00:26:22,280 Speaker 1: kind of you know, headlines and discussion for the last 416 00:26:22,280 --> 00:26:27,280 Speaker 1: few days here in Australia. So but already apparently kids 417 00:26:27,280 --> 00:26:29,159 Speaker 1: are finding a way to get around it. So I 418 00:26:29,200 --> 00:26:31,160 Speaker 1: don't know if it's going to be something that sticks, 419 00:26:31,160 --> 00:26:32,879 Speaker 1: but we'll see. 420 00:26:33,320 --> 00:26:39,640 Speaker 2: Yeah, it's an interesting experiment. Hard to see the downsides. Yeah, 421 00:26:39,640 --> 00:26:44,000 Speaker 2: but you know, in California, in the last couple of years, 422 00:26:44,040 --> 00:26:48,040 Speaker 2: they banned cell phones during the school day, right, and 423 00:26:48,840 --> 00:26:52,200 Speaker 2: as a parent of three kids, my youngest was still 424 00:26:52,200 --> 00:26:54,480 Speaker 2: in high school, I thought that was fantastic. 425 00:26:55,119 --> 00:26:58,040 Speaker 1: Yeah, yeah, yeah, I don't think it's the worst thing. 426 00:26:58,119 --> 00:27:01,399 Speaker 1: That's that's for sure. I don't. I mean, it's a bittersweet, 427 00:27:01,440 --> 00:27:03,920 Speaker 1: I think, because phones and that kind of tech can 428 00:27:03,960 --> 00:27:09,640 Speaker 1: be used the right way amazingly helpful and practical resources. 429 00:27:09,640 --> 00:27:12,520 Speaker 1: But on the other hand, you know, the opposite of 430 00:27:12,560 --> 00:27:17,199 Speaker 1: all of that. What's what's got your interest at the 431 00:27:17,240 --> 00:27:20,280 Speaker 1: moment looking forward? Is there something new on the horizon 432 00:27:20,320 --> 00:27:24,600 Speaker 1: for you, some new area of fraud or some other 433 00:27:24,720 --> 00:27:28,280 Speaker 1: topic that's fascinating you. 434 00:27:28,560 --> 00:27:34,280 Speaker 2: Something I've been thinking about recently has been comparing the 435 00:27:35,080 --> 00:27:39,240 Speaker 2: thinking and belief structures of individuals with conspiracy theories. 436 00:27:40,000 --> 00:27:41,680 Speaker 1: Yeah, to some of my. 437 00:27:41,800 --> 00:27:48,160 Speaker 2: Chronic compliance scam victims, you know, yeah, just like how 438 00:27:48,160 --> 00:27:53,160 Speaker 2: it's reinforced, how it gets developed. You know, what kind 439 00:27:53,160 --> 00:27:57,600 Speaker 2: of psychological interventions could you even use. Yes, you're different 440 00:27:57,640 --> 00:28:02,919 Speaker 2: stages of development too to help you know, scam victims, 441 00:28:03,640 --> 00:28:07,320 Speaker 2: you're deep programmed to some degree. So I've been reading 442 00:28:07,359 --> 00:28:11,320 Speaker 2: a little bit more about conspiracy theories and the type 443 00:28:11,359 --> 00:28:14,720 Speaker 2: of cognitive errors that individuals that tend to get into, 444 00:28:15,200 --> 00:28:19,960 Speaker 2: you know, kind of deep conspiracy territory tend to show. 445 00:28:21,440 --> 00:28:25,520 Speaker 1: Are there any trites that predispose people to be more 446 00:28:25,600 --> 00:28:33,720 Speaker 1: susceptible to scams or conspiracy theories that that could be 447 00:28:33,800 --> 00:28:36,560 Speaker 1: problematic for them. 448 00:28:36,680 --> 00:28:40,440 Speaker 2: Well, well, one area of work that's pretty I think, 449 00:28:40,440 --> 00:28:45,400 Speaker 2: pretty interesting is Gordon Pennycook is a social psychologist that's 450 00:28:45,400 --> 00:28:51,760 Speaker 2: been studying this phenomenon where people endorse pseudo profound statements. 451 00:28:52,880 --> 00:28:55,920 Speaker 2: So he developed a scale of statements that really are 452 00:28:55,720 --> 00:29:00,680 Speaker 2: there b s. It's like, uh, the world's spins on 453 00:29:00,800 --> 00:29:03,880 Speaker 2: abstract beauty? Do you think that's around? 454 00:29:08,320 --> 00:29:10,080 Speaker 1: I don't know what, I don't know what it means. 455 00:29:10,440 --> 00:29:13,800 Speaker 1: It might be a nice metaphor yeah, you. 456 00:29:13,680 --> 00:29:15,520 Speaker 2: Know, And so there are kind of statements like that, 457 00:29:15,680 --> 00:29:19,960 Speaker 2: like inspirational statements, and he's found that individuals that have 458 00:29:20,240 --> 00:29:22,920 Speaker 2: endorse these at a high level of saying that that's 459 00:29:23,000 --> 00:29:25,920 Speaker 2: profound are more likely to kind of go along with 460 00:29:26,040 --> 00:29:30,320 Speaker 2: like conspiracy theories in terms of like the tenants or beliefs, 461 00:29:30,320 --> 00:29:33,200 Speaker 2: and then it just they just tend to comply more. 462 00:29:33,080 --> 00:29:35,760 Speaker 1: Cognitive Yeah, yeah, yeah. 463 00:29:35,840 --> 00:29:38,760 Speaker 2: So in my lab we started playing around with the 464 00:29:38,920 --> 00:29:42,800 Speaker 2: scale with fraud victims and propensity to fraud and we're 465 00:29:42,800 --> 00:29:44,160 Speaker 2: seeing similar trends. 466 00:29:46,240 --> 00:29:50,720 Speaker 1: Tell us about some of your work with the police 467 00:29:50,840 --> 00:29:55,840 Speaker 1: and in the justice system and you get involved in 468 00:29:55,880 --> 00:29:58,000 Speaker 1: that as well, Yeah. 469 00:29:58,120 --> 00:30:04,040 Speaker 2: I do and so I, you know, conduct interviews with 470 00:30:04,160 --> 00:30:06,800 Speaker 2: individuals who may have been the victim of a scam. 471 00:30:07,880 --> 00:30:13,240 Speaker 2: And in most cases, you know, those cases end up 472 00:30:13,280 --> 00:30:16,479 Speaker 2: being civil trials, you know, like it could be a 473 00:30:16,520 --> 00:30:20,719 Speaker 2: broker or like some you know, investor or some Ponzi scheme, 474 00:30:21,560 --> 00:30:25,440 Speaker 2: and what the victim really wants is their money back, right, 475 00:30:25,480 --> 00:30:28,760 Speaker 2: So that's that would be a civil litigation here. So 476 00:30:29,120 --> 00:30:32,200 Speaker 2: I would complete an assessment and look at all the 477 00:30:32,200 --> 00:30:38,880 Speaker 2: communication between the scammer and the alleged victim and put 478 00:30:38,920 --> 00:30:42,480 Speaker 2: together reports kind of partly why were they vulnerable, what 479 00:30:42,560 --> 00:30:47,200 Speaker 2: tactics did the scammer use, and how did it impact them? 480 00:30:47,400 --> 00:30:51,000 Speaker 2: You know, what psychological effect did it have on them. 481 00:30:51,520 --> 00:30:54,920 Speaker 2: Criminal cases are more rare, but I do those as well. 482 00:30:55,040 --> 00:30:57,960 Speaker 2: So that would be those tend to be the elderly victims, 483 00:30:59,000 --> 00:31:02,240 Speaker 2: you know, that have been to frauded, the DL bring 484 00:31:02,880 --> 00:31:08,960 Speaker 2: you know, potentially criminal charges against the caregiver, friend, you know, 485 00:31:08,960 --> 00:31:12,160 Speaker 2: a person in their life that took advantage of them. 486 00:31:13,120 --> 00:31:16,040 Speaker 1: I want to ask you a random question which seems unrelated, 487 00:31:16,080 --> 00:31:17,960 Speaker 1: but I think a lot of these people who do this, 488 00:31:19,640 --> 00:31:24,120 Speaker 1: or perpetrate this fraud and create these scams are probably sociopaths. 489 00:31:24,160 --> 00:31:28,440 Speaker 1: But what what is the percentage of the population do 490 00:31:28,520 --> 00:31:34,560 Speaker 1: you think that's sociopathic? Like not necessarily that they want 491 00:31:34,600 --> 00:31:37,280 Speaker 1: to kill anyone or harm people physically, but they just 492 00:31:37,480 --> 00:31:41,160 Speaker 1: don't have a moral compass. They just don't care. They 493 00:31:41,240 --> 00:31:45,200 Speaker 1: just don't have empathy. I feel like it's higher than 494 00:31:45,280 --> 00:31:50,040 Speaker 1: we think. I feel like it's more than one percent. Huron, 495 00:31:50,960 --> 00:31:53,560 Speaker 1: every fourth person I meet is a bit that I. 496 00:31:53,480 --> 00:31:58,080 Speaker 2: Think, and you know, I mean, I guess it's you know, 497 00:31:58,120 --> 00:32:00,240 Speaker 2: I do see a lot of bad behavior if you're 498 00:32:00,280 --> 00:32:06,240 Speaker 2: in my work. I agree. Something maybe people don't know though, 499 00:32:06,400 --> 00:32:09,080 Speaker 2: is for like those third party scammers, the ones you 500 00:32:09,080 --> 00:32:14,080 Speaker 2: don't really ever meet. Yes, that there's been a trend 501 00:32:14,160 --> 00:32:20,200 Speaker 2: towards using trafficked workers to man those scam centers, right 502 00:32:21,120 --> 00:32:24,080 Speaker 2: like in me or Mare and stuff. So I try 503 00:32:24,120 --> 00:32:28,880 Speaker 2: to remember that I used to sort of enjoy trolling scammers, 504 00:32:29,000 --> 00:32:31,920 Speaker 2: like keeping them on the phone or you know, messing 505 00:32:31,960 --> 00:32:34,960 Speaker 2: with them a little bit. But now I'm a little 506 00:32:35,000 --> 00:32:38,560 Speaker 2: more aware that they may be themselves a victim of 507 00:32:38,600 --> 00:32:42,520 Speaker 2: some type. But yeah, it takes a certain personality to 508 00:32:42,560 --> 00:32:47,080 Speaker 2: be willing to take all of someone else's money. 509 00:32:47,560 --> 00:32:52,200 Speaker 1: Yeah, yeah, I think I never thought about the people 510 00:32:52,240 --> 00:32:57,520 Speaker 1: who are making those coals being basically, you know, poppets 511 00:32:57,560 --> 00:33:01,280 Speaker 1: being controlled by somebody else, and then themselves being in 512 00:33:01,280 --> 00:33:06,640 Speaker 1: a way victims or being used. What what do you 513 00:33:06,720 --> 00:33:12,560 Speaker 1: find most fascinating about. I don't know, Like I'm very 514 00:33:12,680 --> 00:33:15,200 Speaker 1: very interested in the way that we perceive and process 515 00:33:15,240 --> 00:33:18,760 Speaker 1: and experience the world, Like there's the thing that's going on, 516 00:33:18,840 --> 00:33:21,440 Speaker 1: and then there's our story about the thing that's going on, 517 00:33:22,840 --> 00:33:26,040 Speaker 1: the way that people, like some people seem to be 518 00:33:26,200 --> 00:33:29,640 Speaker 1: very easily drawn into these things, some people not so much. 519 00:33:29,680 --> 00:33:32,600 Speaker 1: Some people are not very wary. Some people are completely 520 00:33:32,680 --> 00:33:36,520 Speaker 1: paranoid and will never do anything. Is that is that 521 00:33:36,840 --> 00:33:40,000 Speaker 1: a is that a cognitive default setting? Is that just 522 00:33:40,160 --> 00:33:44,640 Speaker 1: how we're wired, or is that something that's like a 523 00:33:44,680 --> 00:33:47,000 Speaker 1: byproduct of where we've been and what we've seen and 524 00:33:47,000 --> 00:33:48,080 Speaker 1: what we've been involved in. 525 00:33:49,960 --> 00:33:51,320 Speaker 2: I think I'm going to ask you just see a 526 00:33:51,360 --> 00:33:52,280 Speaker 2: little bit more about that. 527 00:33:55,360 --> 00:33:58,120 Speaker 1: I feel like some people. I just feel like some 528 00:33:58,160 --> 00:34:04,880 Speaker 1: people are really gullible and vulnerable, and they naturally believe 529 00:34:05,320 --> 00:34:10,160 Speaker 1: like I'm naturally more skeptical. I don't don't like I 530 00:34:10,280 --> 00:34:14,200 Speaker 1: trust people very slowly. That doesn't mean I think everybody's 531 00:34:14,239 --> 00:34:18,160 Speaker 1: a scammer or everybody's bad. I don't think that at all, 532 00:34:18,400 --> 00:34:23,600 Speaker 1: but it just my default setting is defense, like not 533 00:34:24,200 --> 00:34:26,319 Speaker 1: you know, it's like, I'll believe you when I know 534 00:34:26,520 --> 00:34:28,920 Speaker 1: that you're believable, and I'll trust you when I know 535 00:34:29,000 --> 00:34:32,600 Speaker 1: that you're trustworthy. Now, I don't operate on the assumption 536 00:34:32,760 --> 00:34:35,239 Speaker 1: that you're a fraud or that you're a scammer. I 537 00:34:35,280 --> 00:34:38,400 Speaker 1: don't do that at all. But I'm just almost indifferent 538 00:34:38,480 --> 00:34:41,279 Speaker 1: until I find out Whereas I feel like there are 539 00:34:41,320 --> 00:34:44,560 Speaker 1: some some people like I even say to my audiences 540 00:34:45,680 --> 00:34:48,719 Speaker 1: when I'm doing presentations or lecturing or whatever, I don't 541 00:34:48,719 --> 00:34:52,359 Speaker 1: believe me because you like me, just consider what I'm 542 00:34:52,400 --> 00:34:55,239 Speaker 1: saying and then see, if you know, maybe do some 543 00:34:55,280 --> 00:34:57,760 Speaker 1: more investigating or research. I might give you an idea 544 00:34:57,840 --> 00:35:00,560 Speaker 1: or a thought or a construct or a suggestion, but 545 00:35:00,680 --> 00:35:03,400 Speaker 1: rather than just go, Craig told me that, therefore that's true, 546 00:35:04,239 --> 00:35:06,640 Speaker 1: go and kind of find out for yourself. Does that 547 00:35:06,680 --> 00:35:07,200 Speaker 1: make sense? 548 00:35:08,480 --> 00:35:13,920 Speaker 2: Yeah? It does. And so you know, I don't know 549 00:35:13,920 --> 00:35:16,239 Speaker 2: that we've been able to measure that. I actually looked 550 00:35:16,239 --> 00:35:19,440 Speaker 2: into gullibility a while back, and there's you know, older 551 00:35:19,520 --> 00:35:23,400 Speaker 2: older adults. Yes, that the older cohorts are more trusting. 552 00:35:24,000 --> 00:35:27,960 Speaker 2: It was like a generational you know value. You know 553 00:35:28,040 --> 00:35:32,719 Speaker 2: that in younger generations are less trusting, people tend to 554 00:35:32,760 --> 00:35:38,440 Speaker 2: be suggestible in areas where they have less knowledge, right, right, 555 00:35:39,800 --> 00:35:43,600 Speaker 2: And so that's the trick. You know, over confidence is 556 00:35:43,600 --> 00:35:47,080 Speaker 2: a trait that we see in our research that predicts 557 00:35:47,239 --> 00:35:52,200 Speaker 2: victimization or complying with our lab based scams. Right, we're 558 00:35:52,200 --> 00:35:56,440 Speaker 2: not actually victimizing people. But so so that's so I 559 00:35:56,440 --> 00:35:58,640 Speaker 2: would say, yeah, I'm probably not going to be able 560 00:35:58,640 --> 00:36:01,319 Speaker 2: to scam you in an inner personal setting then, but 561 00:36:01,560 --> 00:36:05,640 Speaker 2: you know, maybe an investment scam. 562 00:36:05,880 --> 00:36:10,560 Speaker 1: I feel like I feel like ironically scammers have some 563 00:36:10,640 --> 00:36:15,320 Speaker 1: of them seem to have a high level of social 564 00:36:15,320 --> 00:36:18,799 Speaker 1: and emotional intelligence because their ability to build connection and 565 00:36:18,880 --> 00:36:21,640 Speaker 1: rapport and trust, which some of them do really quickly, 566 00:36:22,200 --> 00:36:26,799 Speaker 1: and to metaphorically read the room and know how to 567 00:36:26,920 --> 00:36:29,920 Speaker 1: lead people, know how to build trust, do all those things. 568 00:36:30,760 --> 00:36:34,200 Speaker 1: Like that's a that's a very specific kind of intelligence 569 00:36:34,239 --> 00:36:37,960 Speaker 1: and capacity, you know. So do you think that they 570 00:36:38,040 --> 00:36:40,799 Speaker 1: target emotion more than they do intelligence? 571 00:36:41,600 --> 00:36:42,200 Speaker 2: Absolutely? 572 00:36:44,280 --> 00:36:50,880 Speaker 1: Yeah, yeah, And so so what's the what's the antidote 573 00:36:50,920 --> 00:36:53,279 Speaker 1: to that? I guess it's just again doing what we're doing. 574 00:36:53,320 --> 00:36:55,560 Speaker 1: It's just awareness. It's just talking about it. 575 00:36:55,520 --> 00:37:00,320 Speaker 2: Is it and having that person that trusted us there, 576 00:37:00,760 --> 00:37:05,560 Speaker 2: they can get you back more into that analytic mode. 577 00:37:06,440 --> 00:37:09,960 Speaker 2: I'm sure you've been studying like dual process models. Yeah, 578 00:37:10,280 --> 00:37:12,799 Speaker 2: in terms of decision making, right, so you want to 579 00:37:12,840 --> 00:37:18,040 Speaker 2: be more in that deliberative mode. But they're so they're 580 00:37:18,080 --> 00:37:22,799 Speaker 2: so skilled at like jumping people into that emotional reactive 581 00:37:22,880 --> 00:37:26,600 Speaker 2: mode for those one off scams. You know, most scams 582 00:37:26,640 --> 00:37:33,279 Speaker 2: are one off. You know, you screw up and it's done. Yeah, 583 00:37:33,320 --> 00:37:36,200 Speaker 2: it's actually pretty rare to have these like long cons 584 00:37:36,800 --> 00:37:39,960 Speaker 2: that those are those they happen of course romance scams 585 00:37:40,000 --> 00:37:42,160 Speaker 2: and investment scams, but they're a little less common. 586 00:37:43,440 --> 00:37:46,600 Speaker 1: Do you think that many have asked a few psychologists, 587 00:37:46,920 --> 00:37:52,520 Speaker 1: but do you think people generally think about how they think? Like, 588 00:37:52,600 --> 00:37:55,759 Speaker 1: do you think people have a real well, they have 589 00:37:55,840 --> 00:37:58,920 Speaker 1: any sense of awareness around why do I process the world? 590 00:37:58,920 --> 00:38:00,879 Speaker 1: Do I that I did? Where did they beliefs come from? 591 00:38:00,880 --> 00:38:03,600 Speaker 1: Where do these ideas come? Why do I trust or 592 00:38:03,600 --> 00:38:06,840 Speaker 1: why do I not trust? Like I'm really curious about 593 00:38:06,920 --> 00:38:10,520 Speaker 1: my mind and the way that you know, I create 594 00:38:10,600 --> 00:38:13,480 Speaker 1: my own experiences, and I'm really interested about your mind 595 00:38:13,680 --> 00:38:16,319 Speaker 1: and try to understand your mind, you know, theory of mind, 596 00:38:16,360 --> 00:38:18,920 Speaker 1: so that I can build connection and rapport. But I 597 00:38:18,920 --> 00:38:21,680 Speaker 1: feel like a lot of people have a belief. Perhaps 598 00:38:22,640 --> 00:38:26,879 Speaker 1: they didn't choose that belief, that belief just became part 599 00:38:26,880 --> 00:38:30,080 Speaker 1: of them as a byproduct of being around certain people 600 00:38:30,160 --> 00:38:33,400 Speaker 1: or exposed to certain ideas. But yeah, so I guess 601 00:38:33,400 --> 00:38:36,440 Speaker 1: my long winded question is, do you think that we 602 00:38:37,600 --> 00:38:40,600 Speaker 1: think about how we think enough, or that we understand 603 00:38:40,640 --> 00:38:41,680 Speaker 1: our own mind. 604 00:38:41,840 --> 00:38:47,400 Speaker 2: Enough, you know, in terms of like meta cognition. 605 00:38:48,120 --> 00:38:52,160 Speaker 1: Yeah, yeah, just that metacognitive Why is this my you know, 606 00:38:52,880 --> 00:38:55,440 Speaker 1: like there's the thing that's happening, and then there's my story. 607 00:38:55,520 --> 00:38:57,840 Speaker 1: But I think quite often we don't see the distinction 608 00:38:57,960 --> 00:38:59,239 Speaker 1: between the story and the. 609 00:38:59,160 --> 00:39:05,239 Speaker 2: Real Oh yeah, I agree. I mean I think it's 610 00:39:05,239 --> 00:39:12,680 Speaker 2: definitely there's varying degrees of abilities, and as you probably 611 00:39:12,680 --> 00:39:15,440 Speaker 2: fell into your work, you know, again it relates to confidence. 612 00:39:15,560 --> 00:39:19,520 Speaker 2: Sort of paradoxically, when you're in an area where you 613 00:39:19,920 --> 00:39:25,600 Speaker 2: actually don't have a lot of skill, people may overestimate, yeah, 614 00:39:25,760 --> 00:39:28,799 Speaker 2: the their abilities and insight. And then you know, as 615 00:39:28,840 --> 00:39:33,040 Speaker 2: you become an expert, you actually become more cautious. Yes, yes, 616 00:39:33,040 --> 00:39:36,239 Speaker 2: but saying that this will yeah, this is something I 617 00:39:36,320 --> 00:39:38,160 Speaker 2: can do one hundred percent. You have because you have 618 00:39:38,200 --> 00:39:40,760 Speaker 2: more data, you know, to make a more accurate prediction. 619 00:39:42,239 --> 00:39:45,520 Speaker 1: And when when there's something that we believe and we 620 00:39:45,640 --> 00:39:48,000 Speaker 1: want that thing that we believe to be right, that 621 00:39:48,200 --> 00:39:52,760 Speaker 1: almost becomes intertwined with our identity. So when you question 622 00:39:52,920 --> 00:39:57,560 Speaker 1: my belief, you question my identity. So fuck you, do 623 00:39:57,560 --> 00:39:58,319 Speaker 1: you know what I mean? 624 00:39:59,160 --> 00:40:03,480 Speaker 2: Yeah? Right, So when you're so, when you're at that stage, 625 00:40:04,160 --> 00:40:08,160 Speaker 2: there's no there's no you're not looking for evidence that 626 00:40:08,520 --> 00:40:13,560 Speaker 2: is refuting your claim. Yea, and it becomes an existential threat. Yes, 627 00:40:13,600 --> 00:40:18,600 Speaker 2: you know, this relationship that you've staked your entire identity 628 00:40:18,640 --> 00:40:22,680 Speaker 2: and your in future plans on is not real. Yeah, 629 00:40:22,800 --> 00:40:27,440 Speaker 2: that's a horrible narrative. Great, And that's that's what I 630 00:40:27,440 --> 00:40:30,160 Speaker 2: feezed when I go out with law enforcement, Like, would 631 00:40:30,160 --> 00:40:33,560 Speaker 2: you rather believe this person that's calling you telling you 632 00:40:33,600 --> 00:40:37,000 Speaker 2: all of these you know, wonderful things for me, who 633 00:40:37,080 --> 00:40:39,879 Speaker 2: you've met one time, who's saying I'm sorry, This has 634 00:40:39,920 --> 00:40:41,280 Speaker 2: all the hallmarks of the scam. 635 00:40:42,160 --> 00:40:46,040 Speaker 1: Yeah, yeah, yeah. And it's like when when we believe 636 00:40:46,080 --> 00:40:50,319 Speaker 1: something and we want that something to be true, I mean, 637 00:40:50,360 --> 00:40:53,360 Speaker 1: this is no enlightenment for you, But you know that 638 00:40:53,440 --> 00:40:56,000 Speaker 1: whole confirmation bias where well, now all of a sudden, 639 00:40:56,040 --> 00:41:00,839 Speaker 1: I live in this ideological echo chamber, and I I'm 640 00:41:00,840 --> 00:41:04,560 Speaker 1: not open to even thinking about anything else. So I'm 641 00:41:04,600 --> 00:41:08,960 Speaker 1: not teachable. I can't unlearn. And you know, even with 642 00:41:10,400 --> 00:41:13,680 Speaker 1: even with something like religion, where there's hundreds, potentially thousands 643 00:41:13,760 --> 00:41:18,040 Speaker 1: of minor religions anyway, and forget the religious bit for 644 00:41:18,080 --> 00:41:20,799 Speaker 1: the moment, but just the thinking bit where we think, oh, no, 645 00:41:20,920 --> 00:41:24,000 Speaker 1: my religion is the one. So I'm also saying all 646 00:41:24,040 --> 00:41:28,560 Speaker 1: other four thousand minor religions are wrong. We're right. Yet 647 00:41:28,560 --> 00:41:31,600 Speaker 1: every person in every religion essentially thinks the same thing 648 00:41:31,600 --> 00:41:35,399 Speaker 1: about all the other religions, you know, where they all 649 00:41:35,480 --> 00:41:38,840 Speaker 1: live in their own echo chamber of ideology, philosophy, theology, 650 00:41:39,560 --> 00:41:44,160 Speaker 1: thinking that amongst all of these thousands of theological kind 651 00:41:44,239 --> 00:41:48,399 Speaker 1: of echo chambers, that they are the one. And even 652 00:41:48,440 --> 00:41:51,640 Speaker 1: when you think just logically, you go, well, just statistically, 653 00:41:52,520 --> 00:41:56,839 Speaker 1: is there a chance that we're wrong? I mean, because yeah, 654 00:41:56,920 --> 00:42:00,600 Speaker 1: still no, no, there's no chance that we're wrong. Like 655 00:42:00,719 --> 00:42:04,360 Speaker 1: that's that's where our our I don't know, fear or 656 00:42:04,440 --> 00:42:07,280 Speaker 1: insecurity or whatever definitely overwrites logic. 657 00:42:08,600 --> 00:42:11,480 Speaker 2: Yeah, and those police are being reinforced, right, you know, 658 00:42:11,560 --> 00:42:16,279 Speaker 2: in that in that echo chamber community, yes, you know, 659 00:42:16,440 --> 00:42:20,479 Speaker 2: and so and pushing out the other voices. And that's 660 00:42:20,560 --> 00:42:24,080 Speaker 2: you know, similar scammers. We will like look at the 661 00:42:24,120 --> 00:42:28,320 Speaker 2: communication and they might like text their you know victim 662 00:42:28,480 --> 00:42:30,919 Speaker 2: target dozens of times a day. 663 00:42:31,640 --> 00:42:36,000 Speaker 1: Yeah, right right, And that that's so interesting because in 664 00:42:36,040 --> 00:42:39,000 Speaker 1: the mind of the person who's getting those dozens of texts, 665 00:42:40,600 --> 00:42:44,960 Speaker 1: you know, that's one that's real obviously for them. But 666 00:42:45,120 --> 00:42:50,799 Speaker 1: they're they're strategically you know, the the fraudster is just 667 00:42:51,040 --> 00:42:57,319 Speaker 1: building rapport and connection and trust and familiarity until eventually 668 00:42:57,520 --> 00:43:01,319 Speaker 1: there's such a deep emotional connection that the idea that 669 00:43:01,400 --> 00:43:05,000 Speaker 1: this isn't true just that can't exist. 670 00:43:06,239 --> 00:43:08,279 Speaker 2: Yeah, and you know it's not even all that deep, 671 00:43:08,960 --> 00:43:11,600 Speaker 2: you know, it just feel like the most mundane stuff. 672 00:43:11,640 --> 00:43:15,720 Speaker 2: It's probably a bot, you know, like what are you doing? 673 00:43:15,760 --> 00:43:19,520 Speaker 2: What do you have for lunch? Send me a picture 674 00:43:19,640 --> 00:43:23,040 Speaker 2: that sounds really good, you know, if you have a pet, yeah, 675 00:43:23,760 --> 00:43:27,600 Speaker 2: your dog. You know, it's it's mundane stuff, but it's 676 00:43:27,680 --> 00:43:29,880 Speaker 2: just so much of it, you know, it just keeps 677 00:43:29,880 --> 00:43:31,239 Speaker 2: the engaged. 678 00:43:32,760 --> 00:43:34,320 Speaker 1: Have you written a book, prof? 679 00:43:36,880 --> 00:43:40,320 Speaker 2: I have, I have an edited book, but I'm working 680 00:43:40,480 --> 00:43:46,320 Speaker 2: on a current book. It's called played the Psychology of 681 00:43:48,040 --> 00:43:53,720 Speaker 2: Fraud and with my co author Nive Hannik. Yeah, we're 682 00:43:53,760 --> 00:43:56,000 Speaker 2: doing our research and we're in the writing phase of 683 00:43:56,040 --> 00:43:56,760 Speaker 2: that right now. 684 00:43:57,360 --> 00:44:02,080 Speaker 1: Oh amazing, amazing. So I applied the Psychology of Fraud. Well, 685 00:44:02,080 --> 00:44:04,279 Speaker 1: when you get that out, you have to hit us 686 00:44:04,360 --> 00:44:06,000 Speaker 1: up or we'll hit you up. So we can have 687 00:44:06,000 --> 00:44:08,320 Speaker 1: a chat about that and promote it. What's the timeline 688 00:44:08,360 --> 00:44:08,640 Speaker 1: on that? 689 00:44:10,239 --> 00:44:11,120 Speaker 2: Such a good question. 690 00:44:12,239 --> 00:44:16,000 Speaker 1: I'm on, come on, get your shit together, come on. 691 00:44:18,120 --> 00:44:22,759 Speaker 2: Due to my publisher by October, so hopefully i'll the end. 692 00:44:22,640 --> 00:44:27,040 Speaker 1: Of yeah, yeah, yeah, yeah, so maybe maybe end of 693 00:44:27,080 --> 00:44:28,279 Speaker 1: next year release. 694 00:44:28,000 --> 00:44:30,080 Speaker 2: Huh yeah, exactly. 695 00:44:30,200 --> 00:44:31,960 Speaker 1: That'd be good. Now is that going to be Is 696 00:44:31,960 --> 00:44:33,680 Speaker 1: that going to be user friendly or is that going 697 00:44:33,719 --> 00:44:34,800 Speaker 1: to be an academic book? 698 00:44:35,960 --> 00:44:38,680 Speaker 2: No, it's it's definitely going to be user friendly. Lots 699 00:44:38,680 --> 00:44:42,719 Speaker 2: of keys, examples and yah, you know, trying to bring 700 00:44:43,080 --> 00:44:47,200 Speaker 2: some of the science to bearon explaining the phenomenon, but mostly, 701 00:44:47,840 --> 00:44:52,000 Speaker 2: you know, trying to help consumers be better about identifying this. 702 00:44:52,719 --> 00:44:57,719 Speaker 1: Yeahs Now, if my audience wants to find you or 703 00:44:57,760 --> 00:44:59,520 Speaker 1: follow you, do you do you have Oh you do 704 00:44:59,560 --> 00:45:02,120 Speaker 1: have a webs don't you? So can you just remind 705 00:45:02,200 --> 00:45:05,399 Speaker 1: us what that is. You are the web address. 706 00:45:06,040 --> 00:45:09,440 Speaker 2: It's doctor Stacey, would dot com perfect. 707 00:45:09,440 --> 00:45:11,480 Speaker 1: And you want them to connect with you anywhere else? 708 00:45:11,560 --> 00:45:12,520 Speaker 1: Or is that the best place? 709 00:45:13,440 --> 00:45:14,840 Speaker 2: I'd say that's the best place. 710 00:45:15,920 --> 00:45:19,120 Speaker 1: Perfect. All right, Well, we appreciate you. We'll say goodbye 711 00:45:19,200 --> 00:45:21,160 Speaker 1: of here, but thanks for coming to have a chat 712 00:45:21,239 --> 00:45:23,479 Speaker 1: on the you project, and congrats on all you're doing, 713 00:45:23,560 --> 00:45:30,440 Speaker 1: and thanks for helping people get scammed less. Let's hope 714 00:45:30,440 --> 00:45:33,440 Speaker 1: that a few people listening to this might have got 715 00:45:33,480 --> 00:45:37,239 Speaker 1: some insights and maybe a little bit more awareness. 716 00:45:38,239 --> 00:45:42,120 Speaker 2: Yeah, thanks to both of you. I've really enjoyed talking 717 00:45:42,160 --> 00:45:42,400 Speaker 2: with you. 718 00:45:42,880 --> 00:45:45,880 Speaker 1: Yeah, thanks Doc, Thanks TIV, thank you.