1 00:00:10,720 --> 00:00:14,080 Speaker 1: Hello, and welcome to another episode of the All Lots Podcast. 2 00:00:14,200 --> 00:00:15,560 Speaker 1: I'm Tracy Alloway. 3 00:00:15,240 --> 00:00:16,400 Speaker 2: And I'm Joe Whysenthal. 4 00:00:16,680 --> 00:00:18,960 Speaker 1: Joe, I'm kind of nervous about this episode. 5 00:00:19,600 --> 00:00:20,880 Speaker 2: I am too. 6 00:00:21,560 --> 00:00:25,320 Speaker 3: About fifteen minutes ago, the same thought flashed through my mind, 7 00:00:25,600 --> 00:00:27,760 Speaker 3: I too, am a little nervous about this episode. 8 00:00:27,920 --> 00:00:31,480 Speaker 1: Believe it or not, we do some preparation for our episodes, 9 00:00:31,480 --> 00:00:34,519 Speaker 1: although maybe it doesn't always show this particular episode, I 10 00:00:34,560 --> 00:00:38,760 Speaker 1: haven't done a lot of reading into this topic, and 11 00:00:39,080 --> 00:00:43,720 Speaker 1: I'm really hoping the guest doesn't notice. But I think 12 00:00:43,760 --> 00:00:46,440 Speaker 1: my chances are very low because we are literally going 13 00:00:46,479 --> 00:00:50,360 Speaker 1: to be speaking to someone whose whole career is about 14 00:00:50,479 --> 00:00:51,960 Speaker 1: basically spotting lies. 15 00:00:52,200 --> 00:00:54,279 Speaker 3: I mean that's essential. Like in the business world, if 16 00:00:54,280 --> 00:00:56,960 Speaker 3: you really think about it, you know, companies come on 17 00:00:57,000 --> 00:01:00,960 Speaker 3: their calls. I think they don't typically lie per se. 18 00:01:01,200 --> 00:01:03,280 Speaker 3: I don't think executives lie that much, but you know, 19 00:01:03,360 --> 00:01:05,520 Speaker 3: they shade the truth. They highlight some things, they don't 20 00:01:05,560 --> 00:01:07,480 Speaker 3: highlight the other things. I feel like it would be 21 00:01:07,480 --> 00:01:11,120 Speaker 3: a pretty good skill to have in life to just 22 00:01:11,240 --> 00:01:14,480 Speaker 3: generally and especially in business, to just generally know whether 23 00:01:14,600 --> 00:01:15,920 Speaker 3: someone is being honest with you or not. 24 00:01:16,120 --> 00:01:18,680 Speaker 1: Absolutely, it feels like a sort of module they should 25 00:01:18,680 --> 00:01:20,720 Speaker 1: have at Wharton if you're doing a business degree in 26 00:01:20,720 --> 00:01:21,360 Speaker 1: an MBA. 27 00:01:21,800 --> 00:01:24,360 Speaker 2: That I've never seen in an MBA program. 28 00:01:24,440 --> 00:01:26,679 Speaker 1: Well, the person we're going to be speaking to actually 29 00:01:26,720 --> 00:01:30,840 Speaker 1: came to us via Brad Jacobs. You might remember him 30 00:01:30,959 --> 00:01:33,400 Speaker 1: from the episode in which he was talking about his 31 00:01:33,640 --> 00:01:39,120 Speaker 1: latest acquisition and the new part of his logistics empire. 32 00:01:39,280 --> 00:01:42,000 Speaker 1: And he's written a new book and we were reading 33 00:01:42,040 --> 00:01:44,000 Speaker 1: it and one of the things that we thought was 34 00:01:44,040 --> 00:01:46,880 Speaker 1: really interesting was there was a mention that he was 35 00:01:47,000 --> 00:01:51,640 Speaker 1: working with a man called Dick or Phil Houston, an 36 00:01:51,640 --> 00:01:55,880 Speaker 1: ex CIA person who was basically a polygraph examiner for 37 00:01:55,920 --> 00:02:00,320 Speaker 1: a long time, and Brad and Phil were working together 38 00:02:00,760 --> 00:02:04,680 Speaker 1: as part of the due diligence process for Brad's many, many, 39 00:02:04,720 --> 00:02:08,960 Speaker 1: many serial acquisitions. So the idea was he might go 40 00:02:09,080 --> 00:02:12,320 Speaker 1: in and buy a company and then Phil would interview 41 00:02:12,440 --> 00:02:15,160 Speaker 1: some of the senior execs and basically try to see 42 00:02:15,360 --> 00:02:17,480 Speaker 1: whether or not what they were saying about the company 43 00:02:17,639 --> 00:02:18,160 Speaker 1: was true. 44 00:02:18,400 --> 00:02:20,959 Speaker 3: Right, you know, speak of nice skills to have. There's 45 00:02:20,960 --> 00:02:24,560 Speaker 3: always that information asymmetry, whether you're just an investor or 46 00:02:24,600 --> 00:02:27,200 Speaker 3: whether you're buying out a whole company, and you know, 47 00:02:27,280 --> 00:02:29,120 Speaker 3: the seller is always going to know more. Sort of 48 00:02:29,160 --> 00:02:32,520 Speaker 3: classic problem in economics. But if you knew the result 49 00:02:32,560 --> 00:02:34,400 Speaker 3: of an answer is going to be one hundred percent true, 50 00:02:34,720 --> 00:02:35,800 Speaker 3: then that would be pretty great. 51 00:02:35,880 --> 00:02:37,080 Speaker 2: So that would be nice. 52 00:02:37,400 --> 00:02:40,160 Speaker 1: What's that TV show with the Girl who Can Spot 53 00:02:40,200 --> 00:02:40,520 Speaker 1: a Love? 54 00:02:40,639 --> 00:02:43,720 Speaker 2: Oh? Oh, poker face? Poker face pretty? 55 00:02:43,840 --> 00:02:45,920 Speaker 3: Yes, it's pretty. It's kind of entertaining. It's kind of 56 00:02:45,919 --> 00:02:47,040 Speaker 3: like it's it's fun. 57 00:02:47,280 --> 00:02:49,560 Speaker 1: It's a fun It does seem like a useful scar too. 58 00:02:49,600 --> 00:02:50,120 Speaker 2: Yeah. 59 00:02:50,240 --> 00:02:52,920 Speaker 1: By the way, another reason I'm slightly terrified of this 60 00:02:53,040 --> 00:02:57,440 Speaker 1: episode is I used to know an XCIA person who 61 00:02:57,520 --> 00:03:00,360 Speaker 1: then went into another profession. I don't want to give 62 00:03:00,360 --> 00:03:02,519 Speaker 1: too much way, but it was finance related, so I 63 00:03:02,600 --> 00:03:05,320 Speaker 1: used to speak to him about financial things. And I 64 00:03:05,360 --> 00:03:10,120 Speaker 1: remember I met him once for lunch after a particularly 65 00:03:10,560 --> 00:03:13,960 Speaker 1: terrible mourning where something really really bad had happened in 66 00:03:14,000 --> 00:03:16,760 Speaker 1: my professional life. And I sat down and I was like, Hi, 67 00:03:16,880 --> 00:03:18,840 Speaker 1: how are you. How's it going? I can't wait to 68 00:03:18,840 --> 00:03:21,400 Speaker 1: have lunch. We're going to talk about capital markets or whatever. 69 00:03:21,800 --> 00:03:24,959 Speaker 1: And he immediately leaned forward and was like, Tracy, tell 70 00:03:25,000 --> 00:03:28,600 Speaker 1: me what's wrong. Something bad happened. And I asked him 71 00:03:28,600 --> 00:03:30,280 Speaker 1: how he knew, and he was like, oh, you got 72 00:03:30,280 --> 00:03:32,600 Speaker 1: this like little crease in the middle of your forehead. 73 00:03:32,639 --> 00:03:34,720 Speaker 1: And this wasn't you know, this was like a casual 74 00:03:35,080 --> 00:03:37,720 Speaker 1: source meeting. This wasn't someone I knew really really well, 75 00:03:37,880 --> 00:03:41,800 Speaker 1: but he knew he knew that I was upset. Anyway, 76 00:03:41,920 --> 00:03:44,320 Speaker 1: So on that note, very very pleased to say that 77 00:03:44,360 --> 00:03:47,480 Speaker 1: we are going to be speaking to Phil Houston. He 78 00:03:47,800 --> 00:03:51,320 Speaker 1: is a career CIA officer and also the author of 79 00:03:51,400 --> 00:03:55,760 Speaker 1: the book Spy the Lie. Former CIA officers teach you 80 00:03:55,920 --> 00:03:59,160 Speaker 1: how to detect deception, so we're going to learn how 81 00:03:59,160 --> 00:04:01,720 Speaker 1: to spot the bi Phil, thank you so much for 82 00:04:01,840 --> 00:04:02,760 Speaker 1: joining all thoughts. 83 00:04:03,080 --> 00:04:04,800 Speaker 4: Tracy, thanks a ton for having me. 84 00:04:05,400 --> 00:04:08,000 Speaker 1: So just to begin with, how do you become a 85 00:04:08,080 --> 00:04:11,040 Speaker 1: lie detection expert? What is this career path? 86 00:04:11,680 --> 00:04:16,960 Speaker 4: When I joined the agency fairly early on, I was 87 00:04:18,000 --> 00:04:22,200 Speaker 4: called over to the head of polygraph in the agency 88 00:04:22,320 --> 00:04:25,359 Speaker 4: and they had spotted the fact that I had developed 89 00:04:25,360 --> 00:04:30,119 Speaker 4: a lot of information doing background investigations and they thought 90 00:04:30,160 --> 00:04:34,040 Speaker 4: that I would be a very good candidate for such 91 00:04:34,040 --> 00:04:34,640 Speaker 4: a position. 92 00:04:34,960 --> 00:04:38,080 Speaker 3: There's so much to get into. Tracy mentioned that we 93 00:04:38,279 --> 00:04:41,200 Speaker 3: came across you talking to former guest Brad Jacobs, who 94 00:04:41,200 --> 00:04:43,560 Speaker 3: you apparently have worked with a lot. How do you 95 00:04:43,920 --> 00:04:47,839 Speaker 3: deploy LIE detection skills in the corporate context. 96 00:04:48,040 --> 00:04:51,200 Speaker 4: Well, we use them in every single day. It's not 97 00:04:51,560 --> 00:04:56,880 Speaker 4: just in a regimen of due diligence protocol. We're looking 98 00:04:57,120 --> 00:05:02,120 Speaker 4: day in and day out. It's continuous of value, especially 99 00:05:02,160 --> 00:05:07,320 Speaker 4: with new companies that Brad acquires, because we never know 100 00:05:08,160 --> 00:05:11,640 Speaker 4: if we've missed something in the due diligence process, so 101 00:05:11,880 --> 00:05:16,360 Speaker 4: we're always paying attention. And Brad has been highly trained 102 00:05:16,400 --> 00:05:20,640 Speaker 4: now by us and my team in the lie detection 103 00:05:20,839 --> 00:05:23,839 Speaker 4: model that I developed when I was at the agency. 104 00:05:24,640 --> 00:05:28,080 Speaker 1: What kind of things are you looking out for specifically? 105 00:05:28,120 --> 00:05:30,800 Speaker 1: So you know, if Brad says he wants to buy 106 00:05:30,800 --> 00:05:33,560 Speaker 1: a company, I'm sure he gets lots of information like 107 00:05:33,680 --> 00:05:37,640 Speaker 1: printed information as part of the due diligence process, and 108 00:05:37,680 --> 00:05:41,600 Speaker 1: then he has interviews with senior executives. What type of 109 00:05:41,680 --> 00:05:43,480 Speaker 1: questions would you be asking them. 110 00:05:43,880 --> 00:05:48,360 Speaker 4: There are multiple areas of probing that we do. Number 111 00:05:48,400 --> 00:05:53,000 Speaker 4: one is first and foremost, is are there any problems 112 00:05:53,200 --> 00:05:57,840 Speaker 4: or circumstances associated with the acquisition that are not a 113 00:05:57,880 --> 00:06:01,520 Speaker 4: matter of record that no vera one has come forth 114 00:06:01,600 --> 00:06:04,560 Speaker 4: and said, hey, this is a problem or might be 115 00:06:04,640 --> 00:06:09,520 Speaker 4: a problem going forward. And so to gather that information 116 00:06:10,279 --> 00:06:13,599 Speaker 4: Usually the first encounter is with a management meeting, where 117 00:06:13,600 --> 00:06:19,600 Speaker 4: we sit down in front of management and ask them questions. Now, granted, 118 00:06:20,360 --> 00:06:24,800 Speaker 4: the topics are fairly traditional, but the way that we 119 00:06:25,000 --> 00:06:31,480 Speaker 4: word questions sometimes are very different. For example, on the 120 00:06:31,560 --> 00:06:35,919 Speaker 4: really key issues, we rarely will ask a did you 121 00:06:36,360 --> 00:06:39,359 Speaker 4: or do you so? For example, we won't say do 122 00:06:39,400 --> 00:06:42,360 Speaker 4: you have any concerns in this area? We use what 123 00:06:42,400 --> 00:06:47,280 Speaker 4: we call presumptive questions. And a presumptive question might sound 124 00:06:47,320 --> 00:06:50,680 Speaker 4: simply like what concerns do you have in this area? 125 00:06:51,240 --> 00:06:55,640 Speaker 4: It presumes that there's potential for a concern. The beauty 126 00:06:55,680 --> 00:06:59,400 Speaker 4: of that type of a question is that if a 127 00:06:59,520 --> 00:07:03,520 Speaker 4: person is telling the truth, it's still a very easy 128 00:07:03,560 --> 00:07:08,200 Speaker 4: and fair question to answer. However, if a person is 129 00:07:08,320 --> 00:07:13,880 Speaker 4: concealing something and we ask it presumptively, it generally and 130 00:07:14,040 --> 00:07:18,679 Speaker 4: often plants what we call a mind virus. The mind 131 00:07:18,800 --> 00:07:22,360 Speaker 4: virus is that thing that we've all been victims of. 132 00:07:22,960 --> 00:07:25,400 Speaker 4: It's when you know, somebody walks in the door in 133 00:07:25,480 --> 00:07:28,360 Speaker 4: the morning and their coworker comes running up and says, 134 00:07:28,760 --> 00:07:30,880 Speaker 4: you know, Joe, the boss wants to see you, and 135 00:07:30,920 --> 00:07:34,640 Speaker 4: you say, well, what's that about, and you know, they say, 136 00:07:34,680 --> 00:07:37,920 Speaker 4: I don't know but but right away and as Joe's 137 00:07:37,920 --> 00:07:40,960 Speaker 4: walking down there, is he likely thinking more, Geez is 138 00:07:41,040 --> 00:07:42,360 Speaker 4: going to be a great day, I'm going to get 139 00:07:42,360 --> 00:07:45,440 Speaker 4: a bonus, I'm going to get a promotion. Or does 140 00:07:45,480 --> 00:07:49,800 Speaker 4: he immediately start thinking what's wrong? Or is there a problem? 141 00:07:49,880 --> 00:07:53,640 Speaker 4: And if it is, then he's inventorying mentally what the 142 00:07:53,720 --> 00:07:56,680 Speaker 4: problems might be and how he's going to deal with that. 143 00:07:56,680 --> 00:08:02,880 Speaker 4: That mind virus triggers if someone's lying, it often triggers 144 00:08:03,000 --> 00:08:09,840 Speaker 4: the exhibition of deceptive behaviors, both verbal and nonverbal behaviors. 145 00:08:10,240 --> 00:08:13,400 Speaker 3: I already love this conversation so much, but let's continue 146 00:08:13,520 --> 00:08:16,960 Speaker 3: to pursue. I imagine that when you're doing due diligence 147 00:08:17,000 --> 00:08:20,040 Speaker 3: on a company, you know it's the unknown unknowns, it's 148 00:08:20,040 --> 00:08:21,560 Speaker 3: the things that aren't written down. But you don't even 149 00:08:21,560 --> 00:08:24,000 Speaker 3: know the right question to ask because it's not written down. 150 00:08:24,600 --> 00:08:28,080 Speaker 3: But as you say the presumptive approach, talk to us 151 00:08:28,120 --> 00:08:32,560 Speaker 3: about like, okay, take the example further with a question 152 00:08:32,760 --> 00:08:35,400 Speaker 3: like that, what are the types of responses that would 153 00:08:35,400 --> 00:08:38,880 Speaker 3: say trigger warning lights of either it's verbally or physically, 154 00:08:39,160 --> 00:08:39,840 Speaker 3: this looks. 155 00:08:39,640 --> 00:08:40,240 Speaker 2: Like a lie? 156 00:08:40,559 --> 00:08:44,520 Speaker 3: Like what might be gleaned in the response and to 157 00:08:44,559 --> 00:08:45,680 Speaker 3: such a question, sure. 158 00:08:46,080 --> 00:08:49,200 Speaker 4: In working with Brad, we've had all kinds of when 159 00:08:49,280 --> 00:08:53,240 Speaker 4: people are lying, all kinds of crazy responses. We've had 160 00:08:53,640 --> 00:08:56,920 Speaker 4: responses where we've said or made just simply the statement 161 00:08:57,000 --> 00:09:00,079 Speaker 4: listen in describing our diligence, we are also going to to, 162 00:09:00,200 --> 00:09:02,079 Speaker 4: you know, come in and take a look at your accounting, 163 00:09:02,640 --> 00:09:05,560 Speaker 4: and the person immediately says, oh, there's no need to 164 00:09:05,600 --> 00:09:08,280 Speaker 4: do that. And you'd think that they would realize how 165 00:09:08,320 --> 00:09:12,760 Speaker 4: obvious that that dodge is the spot, But at the 166 00:09:12,880 --> 00:09:16,199 Speaker 4: moment they're on the spot and they need it out, 167 00:09:16,320 --> 00:09:19,680 Speaker 4: and so they're not realizing the kinds of responses they give. 168 00:09:20,120 --> 00:09:23,000 Speaker 4: They'll also say, well, why do you need to go there? 169 00:09:23,160 --> 00:09:25,680 Speaker 4: Or why are you asking that? Or how much do 170 00:09:25,720 --> 00:09:29,199 Speaker 4: you need to know? Or here's what I can tell you. 171 00:09:30,040 --> 00:09:33,160 Speaker 4: And that's an interesting statement we hear and we listen for, 172 00:09:33,640 --> 00:09:37,719 Speaker 4: because if you think of the literal interpretation of that 173 00:09:37,920 --> 00:09:41,400 Speaker 4: statement here's what I can tell you, it immediately in 174 00:09:41,440 --> 00:09:44,480 Speaker 4: our world conjures up. What can't you tell us? 175 00:09:45,640 --> 00:09:49,319 Speaker 1: Do people try to deflect? Having interviewed many people on 176 00:09:49,320 --> 00:09:53,400 Speaker 1: this podcast, the most problematic response that we tend to get, 177 00:09:53,440 --> 00:09:57,079 Speaker 1: hopefully not outright lies at least not often, but you 178 00:09:57,120 --> 00:09:59,240 Speaker 1: ask a question and someone will say, oh, that's very 179 00:09:59,320 --> 00:10:02,640 Speaker 1: very interesting. Now let me talk about this entirely different 180 00:10:02,800 --> 00:10:05,080 Speaker 1: point that has nothing to do with what you just asked. 181 00:10:05,400 --> 00:10:09,319 Speaker 4: That could be a product of their media training, but 182 00:10:09,920 --> 00:10:14,960 Speaker 4: it also could be if it's accompanied by other deceptive behaviors. 183 00:10:15,480 --> 00:10:17,559 Speaker 4: And if we talk a little bit later about the 184 00:10:18,440 --> 00:10:23,200 Speaker 4: model for detecting deception, clusters are an important component of 185 00:10:23,200 --> 00:10:26,960 Speaker 4: that model. So more than just one deceptive behavior in 186 00:10:27,000 --> 00:10:30,640 Speaker 4: response to a stimulus, meaning a question or a statement, 187 00:10:31,320 --> 00:10:36,000 Speaker 4: that's what gets our attention. And so when they start 188 00:10:36,040 --> 00:10:40,600 Speaker 4: that deflection, deceptive people know that they can't just sit 189 00:10:40,679 --> 00:10:43,320 Speaker 4: there like the proverbial bump on a log and say nothing. 190 00:10:43,360 --> 00:10:46,880 Speaker 4: They have to say something. And so what they often 191 00:10:47,040 --> 00:10:49,679 Speaker 4: do is we'll try to lead us as stray by 192 00:10:49,720 --> 00:10:52,840 Speaker 4: talking about something they can comfortably talk about that you 193 00:10:53,240 --> 00:10:56,480 Speaker 4: might be interested to you and perhaps even a suage. 194 00:10:56,880 --> 00:10:59,079 Speaker 4: You know, what concerns they think you might have. 195 00:11:00,160 --> 00:11:03,920 Speaker 1: Are lies in the business world different or do they 196 00:11:04,080 --> 00:11:09,480 Speaker 1: exhibit different qualities to lies outside of the business world. 197 00:11:09,480 --> 00:11:14,320 Speaker 1: So I guess in criminal activity or maybe in intelligence gathering, 198 00:11:14,440 --> 00:11:17,000 Speaker 1: going back to your career at the CIA, are there 199 00:11:17,080 --> 00:11:19,599 Speaker 1: differences in the way those lies benifest. 200 00:11:19,920 --> 00:11:25,760 Speaker 4: The primary difference is tracy are the topics, but in reality, 201 00:11:26,240 --> 00:11:31,680 Speaker 4: the lying the behaviors remain the same. They're intrinsic to 202 00:11:31,760 --> 00:11:36,920 Speaker 4: human nature, and we have a very specific list of 203 00:11:37,000 --> 00:11:42,160 Speaker 4: behaviors that we are looking for. The biggest problem in 204 00:11:42,240 --> 00:11:46,559 Speaker 4: spotting lies if people are not trained, is when they 205 00:11:46,600 --> 00:11:51,319 Speaker 4: see something odd that happens, or something different or uncomfortable, 206 00:11:51,880 --> 00:11:55,680 Speaker 4: their instincts may kick in, but they might not recognize 207 00:11:55,760 --> 00:12:00,280 Speaker 4: what's going on, and they're only guessing at that point 208 00:12:00,320 --> 00:12:02,280 Speaker 4: as to whether they've just heard a line or not. 209 00:12:17,720 --> 00:12:19,840 Speaker 3: Why do we back up and talk about the framework 210 00:12:19,920 --> 00:12:22,360 Speaker 3: or the model that you first developed at the CIA. 211 00:12:22,440 --> 00:12:25,640 Speaker 3: I imagined that over the years it's been refined more 212 00:12:25,679 --> 00:12:27,960 Speaker 3: examples and you get better and better at applying it. 213 00:12:28,160 --> 00:12:29,960 Speaker 3: Why don't you just sort of just bring us back to, like, 214 00:12:30,160 --> 00:12:32,840 Speaker 3: what are the core, like underpinnings of your approach. 215 00:12:33,280 --> 00:12:39,360 Speaker 4: The core is that we have codified the behaviors, so 216 00:12:39,520 --> 00:12:43,000 Speaker 4: meaning that we've picked the behaviors that we know through 217 00:12:43,080 --> 00:12:47,839 Speaker 4: research and anecdotal evidence are the most reliable indicators. What 218 00:12:47,880 --> 00:12:51,000 Speaker 4: we learned in the early days is that many of 219 00:12:51,040 --> 00:12:55,760 Speaker 4: the traditional behaviors that we thought were good were not 220 00:12:56,720 --> 00:13:01,439 Speaker 4: and for example, take an eye contact for exams. Eye 221 00:13:01,440 --> 00:13:06,360 Speaker 4: contact is not nearly as reliable as people would think 222 00:13:06,400 --> 00:13:08,080 Speaker 4: it to be. Fact. 223 00:13:08,200 --> 00:13:10,520 Speaker 2: Yeah, now, both me and Tracy a big relief on that. 224 00:13:11,000 --> 00:13:15,120 Speaker 4: Yeah yeah. Eye contact can be very different, especially in 225 00:13:15,160 --> 00:13:19,840 Speaker 4: different cultures, in different regions. I'm here in New York City. 226 00:13:20,840 --> 00:13:22,840 Speaker 4: You know, if I were to walk down the street, 227 00:13:22,880 --> 00:13:25,320 Speaker 4: you know and smiling and saying hi to people and 228 00:13:25,360 --> 00:13:28,680 Speaker 4: so forth, that wouldn't look very good, right, or it 229 00:13:28,679 --> 00:13:31,120 Speaker 4: probably wouldn't go over very well. But in the little 230 00:13:31,160 --> 00:13:33,880 Speaker 4: town where I live in the reverse would be true. 231 00:13:33,920 --> 00:13:36,000 Speaker 4: If I if I didn't smile, or if I didn't 232 00:13:36,040 --> 00:13:39,480 Speaker 4: you know, nod, or even you know, verbally greet someone, 233 00:13:40,040 --> 00:13:43,360 Speaker 4: they'll walk away with a different opinion. And so the 234 00:13:43,480 --> 00:13:48,040 Speaker 4: eye contact piece is just simply not as reliable as 235 00:13:48,080 --> 00:13:50,839 Speaker 4: we need it to be. The anecdotal evidence in our 236 00:13:50,880 --> 00:13:54,880 Speaker 4: world uh supports that, as as well as some major 237 00:13:54,920 --> 00:13:58,040 Speaker 4: research studies. Two in particular, one in the US and 238 00:13:58,080 --> 00:14:03,200 Speaker 4: one in London, strongly suggests that the deceptive person often 239 00:14:03,280 --> 00:14:07,160 Speaker 4: has better eye contact than the truthful person does, highly 240 00:14:07,320 --> 00:14:08,760 Speaker 4: likely because they're forcing it. 241 00:14:10,040 --> 00:14:10,280 Speaker 2: You know. 242 00:14:10,400 --> 00:14:14,200 Speaker 1: Earlier I was using the term bs and lie sort 243 00:14:14,240 --> 00:14:17,800 Speaker 1: of interchangeably, but they're not exactly the same thing. And 244 00:14:17,840 --> 00:14:20,840 Speaker 1: in the business world, one thing that tends to happen 245 00:14:21,120 --> 00:14:25,920 Speaker 1: is you have people telling a good story about their business, 246 00:14:26,080 --> 00:14:29,240 Speaker 1: and the story, you know, it might even be true. 247 00:14:29,320 --> 00:14:35,240 Speaker 1: That might be the way particularly ambitious executive sees things unfolding. 248 00:14:35,800 --> 00:14:37,520 Speaker 1: I guess what I'm getting at is, how do you 249 00:14:37,560 --> 00:14:41,720 Speaker 1: tell the difference between an outright lie saying something fraudulent 250 00:14:42,040 --> 00:14:45,880 Speaker 1: about their business versus someone who's like trying to sell 251 00:14:46,080 --> 00:14:49,800 Speaker 1: the optimistic best case scenario story. 252 00:14:50,040 --> 00:14:52,440 Speaker 4: Okay, first of all, let me go back to the 253 00:14:52,440 --> 00:14:57,760 Speaker 4: model itself. In the model, we're monitoring both their verbal 254 00:14:57,840 --> 00:15:01,680 Speaker 4: behavior or what's commonly been refined to a body language, 255 00:15:02,040 --> 00:15:07,920 Speaker 4: and we're also monitoring their nonverbal behavior. What I said earlier, 256 00:15:07,920 --> 00:15:10,560 Speaker 4: we're monitoring their verbal behavior is what they say. The 257 00:15:10,680 --> 00:15:15,000 Speaker 4: nonverbal is obviously what they don't say. And those both happened, 258 00:15:15,200 --> 00:15:20,080 Speaker 4: you know, often simultaneously or or in conjunction with a 259 00:15:20,120 --> 00:15:25,040 Speaker 4: single response to a particular stimulus, and we're picking up 260 00:15:25,160 --> 00:15:28,040 Speaker 4: on both of those. Now, what are we picking up? 261 00:15:28,600 --> 00:15:32,520 Speaker 4: All of the behaviors that we use fit into five 262 00:15:32,760 --> 00:15:39,160 Speaker 4: psychological buckets. The first bucket is the evasion bucket. Okay, 263 00:15:39,280 --> 00:15:42,600 Speaker 4: these are These are behaviors such as, you know, failing 264 00:15:42,640 --> 00:15:47,280 Speaker 4: to answer the question or qualifying the question. They're not 265 00:15:47,400 --> 00:15:50,840 Speaker 4: giving you some or all of what you want from them. 266 00:15:51,440 --> 00:15:55,680 Speaker 4: The second one is this persuasion bucket. And this is 267 00:15:55,720 --> 00:15:58,400 Speaker 4: kind of tracy where you were leading to if I 268 00:15:58,600 --> 00:16:01,920 Speaker 4: if I heard you correctly, where someone's trying to tell 269 00:16:01,960 --> 00:16:05,960 Speaker 4: you something positive or good because they can't tell you 270 00:16:06,040 --> 00:16:09,320 Speaker 4: the truth because the truth has consequences to it, so 271 00:16:09,360 --> 00:16:14,040 Speaker 4: they start using convincing statements, Oh, we would never do that. 272 00:16:14,160 --> 00:16:17,520 Speaker 4: We're a great company, we've been around forever, We've got 273 00:16:17,520 --> 00:16:21,200 Speaker 4: the best team in the industry. And they're trying to 274 00:16:21,360 --> 00:16:25,240 Speaker 4: convince you that you don't have to worry about, you know, 275 00:16:25,280 --> 00:16:28,720 Speaker 4: whatever it is or whatever topic that you surface to them. 276 00:16:29,080 --> 00:16:33,720 Speaker 4: The third behavior is aggression behavior, sometimes referred to as 277 00:16:33,760 --> 00:16:39,720 Speaker 4: attack behavior. Sometimes it's very visibly or visible, other times 278 00:16:39,760 --> 00:16:42,480 Speaker 4: it's more nuanced. So for example, you ask someone a 279 00:16:42,560 --> 00:16:46,800 Speaker 4: question and they say why are you asking that? And 280 00:16:47,040 --> 00:16:49,720 Speaker 4: or sometimes they say why are you asking me that? 281 00:16:50,200 --> 00:16:54,520 Speaker 4: You guys always ask these things. I've gone from you know, 282 00:16:54,560 --> 00:16:57,160 Speaker 4: to five different banks today, and it seems like every 283 00:16:57,240 --> 00:17:01,040 Speaker 4: single person has this has fixated on this issue, and 284 00:17:01,080 --> 00:17:04,359 Speaker 4: so forth. They're trying to get you to back off. 285 00:17:05,280 --> 00:17:08,840 Speaker 4: The fourth behavior is what we call manipulation. This is 286 00:17:08,920 --> 00:17:13,800 Speaker 4: where they're manipulating the circumstances of the interaction to their favor. 287 00:17:14,240 --> 00:17:17,240 Speaker 4: A good example of that is when you ask them 288 00:17:17,280 --> 00:17:22,720 Speaker 4: a question and they repeat your question. Now, you might say, well, geez, 289 00:17:22,720 --> 00:17:25,640 Speaker 4: what value does that bring to them? Well, the value 290 00:17:25,960 --> 00:17:30,720 Speaker 4: is that we think about ten times faster than we talk, 291 00:17:31,320 --> 00:17:34,760 Speaker 4: So in that second or two to repeat the question 292 00:17:35,359 --> 00:17:40,240 Speaker 4: could equate to twenty seconds of material to say or 293 00:17:40,359 --> 00:17:43,919 Speaker 4: strategy to pursue, and that's how they stay up with it. 294 00:17:44,119 --> 00:17:46,359 Speaker 1: That was good media training, right. If you need to 295 00:17:46,359 --> 00:17:48,960 Speaker 1: buy yourself a little bit of time to formulate the 296 00:17:48,960 --> 00:17:51,240 Speaker 1: thoughts in your head, you repeat the question or say 297 00:17:51,280 --> 00:17:55,600 Speaker 1: something nonscript what a great point, Joe, thank you so 298 00:17:55,720 --> 00:17:56,760 Speaker 1: much for bringing that up. 299 00:17:57,119 --> 00:18:00,720 Speaker 4: A non answer statement is another one in the manipulation bucket, 300 00:18:01,000 --> 00:18:05,159 Speaker 4: and for the same purposes, it's buying time. The fifth 301 00:18:05,160 --> 00:18:09,720 Speaker 4: and final bucket is the reaction bucket, and this is 302 00:18:09,760 --> 00:18:15,280 Speaker 4: again the body language when people respond either as a 303 00:18:15,320 --> 00:18:19,239 Speaker 4: result of the fight, flight or freeze response, or there 304 00:18:19,240 --> 00:18:22,040 Speaker 4: are a couple of other things that aren't caused necessarily 305 00:18:22,080 --> 00:18:26,040 Speaker 4: by that response. For example, something we call a verbal 306 00:18:26,160 --> 00:18:30,880 Speaker 4: nonverbal disconnect, where you ask someone a question and they're 307 00:18:30,920 --> 00:18:34,520 Speaker 4: saying no, I wouldn't do that, and at the same 308 00:18:34,600 --> 00:18:38,040 Speaker 4: time they're nodding their head yes in response to the question. 309 00:18:38,119 --> 00:18:40,720 Speaker 4: You see that kind of thing. But the other big one, 310 00:18:41,160 --> 00:18:45,120 Speaker 4: two big ones in the reaction bucket are when people 311 00:18:45,760 --> 00:18:49,200 Speaker 4: have anchor point movements in response to something you ask 312 00:18:49,280 --> 00:18:52,400 Speaker 4: them or see them. I remember, early in the early 313 00:18:52,480 --> 00:18:55,359 Speaker 4: days when I first started working in the investment world 314 00:18:55,800 --> 00:18:58,479 Speaker 4: at a hedge fund, and I was sitting there with 315 00:18:58,560 --> 00:19:02,760 Speaker 4: the hedge fund manager interviewing a management team, and I 316 00:19:02,840 --> 00:19:07,000 Speaker 4: remember he asked someone a very direct question about what 317 00:19:07,480 --> 00:19:10,760 Speaker 4: the street was saying was a problem, and the moment 318 00:19:10,800 --> 00:19:14,520 Speaker 4: he started answering the question, he reached across the table 319 00:19:14,560 --> 00:19:19,480 Speaker 4: and started making huge sweeping gestures on the table. And 320 00:19:19,640 --> 00:19:23,919 Speaker 4: we call those grooming gestures or anchor point movements. And 321 00:19:23,960 --> 00:19:27,200 Speaker 4: it can be as simple as a swivel in the chair, 322 00:19:27,600 --> 00:19:31,600 Speaker 4: a leaning forward after answering, or in the midstore or 323 00:19:31,640 --> 00:19:34,719 Speaker 4: in preparation for answering your question leaning backwards. 324 00:19:35,920 --> 00:19:38,200 Speaker 3: In the case of the sweeping of the table that 325 00:19:38,320 --> 00:19:42,919 Speaker 3: they has, what is the respondent doing there implicitly or 326 00:19:42,960 --> 00:19:45,800 Speaker 3: why is that what makes that a tell or a edwy. 327 00:19:46,040 --> 00:19:49,280 Speaker 4: From a psychological standpoint, what he's doing is cleaning up 328 00:19:49,320 --> 00:19:53,359 Speaker 4: the surroundings. He in his mind, is making life better 329 00:19:53,440 --> 00:19:56,960 Speaker 4: at that moment, because right now life's terrible because he 330 00:19:56,960 --> 00:20:00,960 Speaker 4: doesn't have a great answer to the question. And that example, 331 00:20:01,000 --> 00:20:03,400 Speaker 4: by the way, the company went under a few weeks 332 00:20:03,480 --> 00:20:08,440 Speaker 4: later for the exact issue that he was doing. That's sweeping. Now, 333 00:20:08,600 --> 00:20:12,800 Speaker 4: we don't rely on any one of these behaviors in 334 00:20:12,840 --> 00:20:15,960 Speaker 4: response to the question. We're looking for a cluster two 335 00:20:16,080 --> 00:20:21,080 Speaker 4: or more deceptive indicators will tell us immediately that we 336 00:20:21,200 --> 00:20:24,960 Speaker 4: have more work to do. More work simply means not 337 00:20:25,080 --> 00:20:28,199 Speaker 4: that we're leaping to judgment, but that we're going to 338 00:20:28,240 --> 00:20:31,960 Speaker 4: ask more questions, We're going to follow up, or we're 339 00:20:31,960 --> 00:20:34,680 Speaker 4: going to talk to somebody else once they leave whatever, 340 00:20:34,880 --> 00:20:38,720 Speaker 4: or do research whatever. More work means. But the beauty 341 00:20:38,720 --> 00:20:42,679 Speaker 4: of it is is that we don't get snookered, so 342 00:20:42,800 --> 00:20:43,320 Speaker 4: to speak. 343 00:20:44,080 --> 00:20:47,960 Speaker 1: How often do you get false positives where you're interviewing 344 00:20:47,960 --> 00:20:51,159 Speaker 1: someone and you think this person is lying or there 345 00:20:51,200 --> 00:20:53,840 Speaker 1: are some bread flags here to suggest that maybe he's 346 00:20:53,840 --> 00:20:56,600 Speaker 1: not being one hundred percent truthful, and then you go 347 00:20:56,680 --> 00:20:59,960 Speaker 1: out you do additional info gathering as you were just describe, 348 00:21:00,280 --> 00:21:02,840 Speaker 1: and you find out, actually, maybe he's just a weird 349 00:21:02,880 --> 00:21:05,200 Speaker 1: guy or socially awkward or something like that. 350 00:21:05,280 --> 00:21:07,160 Speaker 2: Sure, Sure, he just likes to straighten up the table. 351 00:21:07,320 --> 00:21:14,160 Speaker 4: Yeah, very meticulous individual. More often than not not likely 352 00:21:14,240 --> 00:21:16,240 Speaker 4: to see. But if we're going to see one, it's 353 00:21:16,359 --> 00:21:19,720 Speaker 4: likely going to be in a situation where we're dealing 354 00:21:19,800 --> 00:21:24,880 Speaker 4: with multiple issues. So, for example, for Bradford years, we've 355 00:21:24,920 --> 00:21:28,080 Speaker 4: done a ton of employment pre employment screening, especially for 356 00:21:28,160 --> 00:21:32,359 Speaker 4: the senior executives, and there may be more than one 357 00:21:32,520 --> 00:21:35,560 Speaker 4: lie or more than one problem that they're worried about, 358 00:21:35,720 --> 00:21:40,280 Speaker 4: but because of something called psychological set, it means that 359 00:21:40,400 --> 00:21:45,840 Speaker 4: they have a fixation or fear on one particular area 360 00:21:45,880 --> 00:21:49,120 Speaker 4: of deception and they're not nearly as worried as much 361 00:21:49,119 --> 00:21:53,240 Speaker 4: about the other areas, And so most of their behavior 362 00:21:53,320 --> 00:21:57,400 Speaker 4: comes out on that particular issue that they're worried about, 363 00:21:58,040 --> 00:22:01,320 Speaker 4: and as a result, we may miss you know, which 364 00:22:01,320 --> 00:22:05,280 Speaker 4: would be a false negative. But if our bias has 365 00:22:05,440 --> 00:22:08,240 Speaker 4: the pitchfork effect, in other words, we're thinking, oh, that 366 00:22:08,320 --> 00:22:11,200 Speaker 4: this guy's not telling the truth about anything, then we're 367 00:22:11,240 --> 00:22:14,960 Speaker 4: starting to see false positives, and it happens I. 368 00:22:14,920 --> 00:22:17,960 Speaker 3: Mean, I know you mentioned that eye contact is not 369 00:22:18,359 --> 00:22:22,199 Speaker 3: as robust as maybe people imagine in popular belief. But 370 00:22:22,280 --> 00:22:24,720 Speaker 3: I'm curiously in a world where more and more is 371 00:22:24,760 --> 00:22:29,560 Speaker 3: done zoom digitally, et cetera. Have you had to update 372 00:22:29,640 --> 00:22:32,119 Speaker 3: your tactics at all our approach? Can you talk a 373 00:22:32,160 --> 00:22:35,080 Speaker 3: little bit about lie detection in the pre and post 374 00:22:35,400 --> 00:22:35,840 Speaker 3: zoom era. 375 00:22:36,119 --> 00:22:40,240 Speaker 4: Sure. We always, if we can, want to be doing 376 00:22:40,280 --> 00:22:44,080 Speaker 4: the interaction in person and in particular when we're there, 377 00:22:44,640 --> 00:22:48,280 Speaker 4: whether we can do it overtly or even covertly, we 378 00:22:48,359 --> 00:22:52,040 Speaker 4: want to head to toe observance of them as we're 379 00:22:52,040 --> 00:22:55,600 Speaker 4: talking to them, because the behavior can leak out anywhere. 380 00:22:55,920 --> 00:22:59,560 Speaker 4: For example, you know, we know that the feet are 381 00:22:59,600 --> 00:23:03,000 Speaker 4: always an anchor point, and if the fight or flight 382 00:23:03,040 --> 00:23:06,639 Speaker 4: response kicks in, it will often go to the feet first, 383 00:23:06,720 --> 00:23:11,120 Speaker 4: because that's our primary anchor point in life, and that's 384 00:23:11,160 --> 00:23:13,840 Speaker 4: what gets us out of trouble, that's the escape mode 385 00:23:13,880 --> 00:23:16,760 Speaker 4: and so forth. So we want to be able to 386 00:23:16,760 --> 00:23:21,159 Speaker 4: see those In the zoom we lose a lot. We 387 00:23:21,320 --> 00:23:25,040 Speaker 4: lose at least fifty percent of the reaction bucket, and 388 00:23:25,119 --> 00:23:28,320 Speaker 4: so we rely very heavily then or more heavily even 389 00:23:28,680 --> 00:23:32,359 Speaker 4: on the other four buckets, because those are all almost 390 00:23:32,359 --> 00:23:35,480 Speaker 4: completely related to the verbal activity. 391 00:23:36,080 --> 00:23:39,080 Speaker 1: What about eye contact in zoom, because I will admit 392 00:23:39,119 --> 00:23:42,000 Speaker 1: I have a hard time focusing my eyes on zoom calls, 393 00:23:42,040 --> 00:23:44,159 Speaker 1: partially because I don't want to look at the screen 394 00:23:44,320 --> 00:23:47,200 Speaker 1: and see myself when I'm talking. It's just very awkward, 395 00:23:47,400 --> 00:23:49,200 Speaker 1: so I sort of look off in the distance. 396 00:23:49,240 --> 00:23:52,840 Speaker 4: Does that mean anything, No, Tracy, there are people that 397 00:23:52,880 --> 00:23:57,080 Speaker 4: will tell you the opposite, But our research and again 398 00:23:57,119 --> 00:24:00,280 Speaker 4: the anecdotal evidence, and a lot of your taxpayers he 399 00:24:00,640 --> 00:24:03,880 Speaker 4: has gone to, you know, to invalidate some of that. 400 00:24:04,480 --> 00:24:07,439 Speaker 4: When you're on zoom, one of the biggest problems you 401 00:24:07,560 --> 00:24:10,840 Speaker 4: have both as the interviewer, if you're the person asking 402 00:24:10,880 --> 00:24:14,240 Speaker 4: the questions, or you know, if it's just a conversation, 403 00:24:14,840 --> 00:24:17,560 Speaker 4: one or the other is likely to experience what we 404 00:24:17,600 --> 00:24:22,440 Speaker 4: call mental drift, where when you're sitting there, you have 405 00:24:22,720 --> 00:24:27,639 Speaker 4: all kinds of distractors that are drawing your attention, whether 406 00:24:27,680 --> 00:24:30,600 Speaker 4: it's an email that pops up or a dialogue box 407 00:24:30,640 --> 00:24:33,919 Speaker 4: that pops up, whatever the case may be, or someone 408 00:24:34,000 --> 00:24:37,679 Speaker 4: sticks their head in the door or a sound outside 409 00:24:37,760 --> 00:24:42,600 Speaker 4: or whatever. It's so easy to become distracted, and it 410 00:24:42,760 --> 00:24:44,919 Speaker 4: happens a lot and so we have to be very 411 00:24:44,920 --> 00:24:49,080 Speaker 4: careful with, you know, using eye contact as a lie behavior, 412 00:24:49,160 --> 00:24:49,840 Speaker 4: so to speak. 413 00:24:50,080 --> 00:24:53,080 Speaker 3: So in the CIA context, obviously a lot of people 414 00:24:53,119 --> 00:24:55,880 Speaker 3: engaged in intelligence gathering, it's good to. 415 00:24:55,880 --> 00:24:57,280 Speaker 2: Know if someone is being honest or not. 416 00:24:57,480 --> 00:24:59,560 Speaker 3: But I also have to imagine that in the CIA 417 00:24:59,680 --> 00:25:02,199 Speaker 3: content there are a handful of people for whom the 418 00:25:02,240 --> 00:25:05,400 Speaker 3: ability to lie is actually a valuable skill, including save 419 00:25:05,440 --> 00:25:08,880 Speaker 3: people who are going undercover in some situation which case 420 00:25:08,960 --> 00:25:10,159 Speaker 3: deception is actually. 421 00:25:09,920 --> 00:25:10,560 Speaker 2: Part of the job. 422 00:25:10,920 --> 00:25:13,200 Speaker 3: Can we learn to be better liars? Can we learn 423 00:25:13,280 --> 00:25:16,760 Speaker 3: to identify our own leaks and tells and behaviors and 424 00:25:16,800 --> 00:25:20,800 Speaker 3: sweeps and anchors and pivots so that we come off 425 00:25:20,840 --> 00:25:23,160 Speaker 3: more trustworthy than we should be in some situations. 426 00:25:23,680 --> 00:25:28,960 Speaker 4: Most of the time, when people try to avoid light detection, 427 00:25:29,640 --> 00:25:33,280 Speaker 4: they're doing two things. Number one is they're trying not 428 00:25:33,440 --> 00:25:38,600 Speaker 4: to do things that everyone believes is obviously a deceptive behavior. 429 00:25:39,440 --> 00:25:43,959 Speaker 4: The second is they try to do things that and 430 00:25:44,000 --> 00:25:48,680 Speaker 4: focus on things that mask or carve out the other 431 00:25:48,800 --> 00:25:52,439 Speaker 4: behaviors that sound better, so to speak. And we know 432 00:25:52,560 --> 00:25:57,440 Speaker 4: that because once we develop this methodology in the CI 433 00:25:57,560 --> 00:26:01,520 Speaker 4: was the principal developer of both the model and the training, 434 00:26:02,119 --> 00:26:06,960 Speaker 4: we started training federal law enforcement, and they loved the 435 00:26:07,040 --> 00:26:10,480 Speaker 4: training we in fact did years ago before Homeland Security 436 00:26:10,960 --> 00:26:15,240 Speaker 4: with the US Customs down at the southern California border. 437 00:26:15,720 --> 00:26:17,480 Speaker 4: We did a lot of training for them, and they 438 00:26:17,600 --> 00:26:20,480 Speaker 4: actually did a study, a little mini study, to see 439 00:26:20,960 --> 00:26:25,040 Speaker 4: how well this worked, and it showed that their agents 440 00:26:25,119 --> 00:26:30,000 Speaker 4: were much much more better skilled at spotting who has 441 00:26:30,040 --> 00:26:32,439 Speaker 4: the contraband versus who doesn't. 442 00:26:47,760 --> 00:26:50,040 Speaker 1: I mentioned in the intro that we hadn't done much 443 00:26:50,080 --> 00:26:53,080 Speaker 1: prep for this particular conversation. That was in fact a lie, 444 00:26:53,119 --> 00:26:54,880 Speaker 1: because I've done a little bit of prep. But one 445 00:26:54,880 --> 00:26:56,720 Speaker 1: of the things I saw that I thought was really 446 00:26:56,760 --> 00:27:00,719 Speaker 1: interesting was a bit where you were talking about cognitive 447 00:27:01,040 --> 00:27:05,280 Speaker 1: dissonance and how that feeds into asking the right questions 448 00:27:05,480 --> 00:27:10,480 Speaker 1: or interrogation techniques. And you are basically suggesting that someone 449 00:27:10,840 --> 00:27:15,320 Speaker 1: who is lying or misrepresenting the facts is dealing with 450 00:27:15,400 --> 00:27:18,400 Speaker 1: cognitive dissonance because more likely than not, they still think 451 00:27:18,440 --> 00:27:21,560 Speaker 1: of themselves as a good person even though they've done 452 00:27:21,760 --> 00:27:25,399 Speaker 1: or are doing a bad thing. And so the idea 453 00:27:25,440 --> 00:27:28,960 Speaker 1: is to allow them space to sort of deal or 454 00:27:29,000 --> 00:27:33,080 Speaker 1: sort through that cognitive dissonance out loud to you and 455 00:27:33,280 --> 00:27:37,600 Speaker 1: provide a narrative that explains their behavior. Is that a 456 00:27:37,760 --> 00:27:40,520 Speaker 1: useful technique in business as well, like the idea of 457 00:27:40,560 --> 00:27:44,880 Speaker 1: just providing people space to try to walk through their 458 00:27:44,920 --> 00:27:46,679 Speaker 1: mindset at a particular time. 459 00:27:47,400 --> 00:27:51,919 Speaker 4: If you really want them to be truthful with you, your 460 00:27:51,080 --> 00:27:57,200 Speaker 4: demeanor is very important, number one. Number two, you need 461 00:27:57,280 --> 00:28:03,320 Speaker 4: to present yourself as doing your job, whatever your job. 462 00:28:03,359 --> 00:28:06,480 Speaker 4: If you're an investment analyst, you know, for example, if 463 00:28:06,520 --> 00:28:11,600 Speaker 4: you simply you know, present the questions or the opening monologue, 464 00:28:11,680 --> 00:28:14,119 Speaker 4: you know, to the meeting, saying hey, listen, you know, 465 00:28:14,200 --> 00:28:16,439 Speaker 4: let me just say up front, we're really interested in 466 00:28:16,480 --> 00:28:20,280 Speaker 4: you guys, but I really need to ask some direct questions, 467 00:28:20,280 --> 00:28:22,480 Speaker 4: so please if I don't mean to offend you or 468 00:28:22,520 --> 00:28:25,800 Speaker 4: anything of that nature. And then you lower their guard 469 00:28:25,880 --> 00:28:29,760 Speaker 4: a little bit. And it's amazing. Just simply opening up 470 00:28:29,840 --> 00:28:34,800 Speaker 4: the conversation that way and then presenting your question in 471 00:28:34,840 --> 00:28:39,320 Speaker 4: a non threatening manner, you can begin to get people 472 00:28:39,440 --> 00:28:44,520 Speaker 4: to open up. There is another methodology that we use 473 00:28:45,200 --> 00:28:49,160 Speaker 4: if and when we think that someone is lying and 474 00:28:49,200 --> 00:28:52,200 Speaker 4: we have the green light from the client to use 475 00:28:52,240 --> 00:28:57,160 Speaker 4: that methodology, and it is much different than what you 476 00:28:57,200 --> 00:29:02,400 Speaker 4: would think of as interrogation. It's a persuasion technique that 477 00:29:02,560 --> 00:29:06,720 Speaker 4: is enormously effective, and sometimes you get the whole story. 478 00:29:06,760 --> 00:29:09,200 Speaker 4: Most of the time, though you get at least more 479 00:29:09,200 --> 00:29:11,600 Speaker 4: than they'd given up at that particular point. 480 00:29:11,960 --> 00:29:13,960 Speaker 3: Could you explain that a little bit further? What's this 481 00:29:14,080 --> 00:29:14,760 Speaker 3: approach about? 482 00:29:14,920 --> 00:29:18,400 Speaker 4: Sure? I once had a hat in my office It said, 483 00:29:18,440 --> 00:29:23,680 Speaker 4: if your lips are moving, you're lying, okay, And in reality, 484 00:29:24,240 --> 00:29:27,480 Speaker 4: if I think the person's lying, I want to go 485 00:29:27,560 --> 00:29:29,959 Speaker 4: for a period of time where their lips are not moving. 486 00:29:30,600 --> 00:29:33,640 Speaker 4: I want to be the one talking to them, and 487 00:29:33,720 --> 00:29:36,960 Speaker 4: I'm going to be not saying random things. I'm going 488 00:29:37,000 --> 00:29:43,920 Speaker 4: to be using very selective influence techniques that will help 489 00:29:44,040 --> 00:29:48,400 Speaker 4: me make it easier in their mind at that moment 490 00:29:48,960 --> 00:29:54,200 Speaker 4: to fess up. And we've used these techniques on spies, 491 00:29:54,560 --> 00:29:59,520 Speaker 4: on criminals, on double agents. I know I have three 492 00:29:59,600 --> 00:30:03,960 Speaker 4: confess essions from double agents in my career at the agency, 493 00:30:04,120 --> 00:30:07,440 Speaker 4: and to get a confession from a double agent is 494 00:30:08,080 --> 00:30:11,440 Speaker 4: like solving the most major crime you can you know 495 00:30:11,520 --> 00:30:13,440 Speaker 4: you can solve, so to speak, in our world. 496 00:30:13,480 --> 00:30:14,719 Speaker 2: So what does that sound like? 497 00:30:14,720 --> 00:30:14,800 Speaker 4: Like? 498 00:30:14,840 --> 00:30:16,240 Speaker 3: How do you like what are some of the things 499 00:30:16,240 --> 00:30:16,520 Speaker 3: you say? 500 00:30:16,680 --> 00:30:16,880 Speaker 4: Yeah? 501 00:30:16,920 --> 00:30:18,600 Speaker 1: Do they actually admit it? Do they go like, oh 502 00:30:18,640 --> 00:30:20,280 Speaker 1: you got me, I'm a double agent, but. 503 00:30:20,280 --> 00:30:21,960 Speaker 3: Like yeah, and how like what are the things you 504 00:30:22,000 --> 00:30:23,880 Speaker 3: say to like put them in that framework. 505 00:30:23,480 --> 00:30:27,680 Speaker 4: Like that that is is a longer monologue, so to speak, 506 00:30:27,760 --> 00:30:30,320 Speaker 4: if you will. And so you know, if you think 507 00:30:30,360 --> 00:30:33,600 Speaker 4: about the interview and interaction, it's a dialogue. And so 508 00:30:33,640 --> 00:30:36,080 Speaker 4: when we go in the monologue mode, we're in the 509 00:30:36,800 --> 00:30:42,560 Speaker 4: in that direct elicitation mode. And it sounds very low key, 510 00:30:43,240 --> 00:30:46,200 Speaker 4: so different than what you see in the movies where 511 00:30:46,480 --> 00:30:50,240 Speaker 4: somebody starts, you know, the conversation by yelling, you know, 512 00:30:50,280 --> 00:30:53,320 Speaker 4: screaming you better tell me or you know, we're gonna 513 00:30:53,400 --> 00:30:59,200 Speaker 4: and they list a series of consequences. We do the reverse. 514 00:30:59,760 --> 00:31:04,560 Speaker 4: We lower our voice, we start talking. We start telling 515 00:31:04,640 --> 00:31:08,240 Speaker 4: them reasons why people have done this and that we 516 00:31:08,400 --> 00:31:13,360 Speaker 4: understand those reasons. So there are just a lot of 517 00:31:13,520 --> 00:31:17,720 Speaker 4: different categories of things that we can say and do 518 00:31:18,680 --> 00:31:22,479 Speaker 4: that make it easier and over time to talk about it. 519 00:31:22,840 --> 00:31:26,240 Speaker 4: And often it doesn't come out as the big confession. 520 00:31:26,920 --> 00:31:31,360 Speaker 4: It often comes out as an admission about something related 521 00:31:31,400 --> 00:31:35,160 Speaker 4: to it. And then we take that admission and it's 522 00:31:35,240 --> 00:31:38,440 Speaker 4: like a thread or perhaps peeling the onion to use 523 00:31:38,480 --> 00:31:42,800 Speaker 4: another metaphor, and you start just peeling or tugging and 524 00:31:43,160 --> 00:31:46,680 Speaker 4: you begin to get the information. 525 00:31:46,720 --> 00:31:48,960 Speaker 1: That reminds me, actually this is a little bit media 526 00:31:49,120 --> 00:31:52,440 Speaker 1: naval gaisy. But Joe and I have talked about this before, 527 00:31:52,480 --> 00:31:55,360 Speaker 1: but every once in a while we will get comments 528 00:31:55,400 --> 00:31:57,880 Speaker 1: saying like, Oh, I wish you'd pushed back on this 529 00:31:58,000 --> 00:32:00,680 Speaker 1: point a little bit more in the interviewer. Why didn't 530 00:32:00,680 --> 00:32:04,600 Speaker 1: you press them on this particular point. And it feels 531 00:32:04,640 --> 00:32:09,280 Speaker 1: like people have an idea in their heads that like, 532 00:32:09,360 --> 00:32:13,880 Speaker 1: if you just ask the right question enough times, eventually 533 00:32:13,920 --> 00:32:17,520 Speaker 1: you'll get that kind of gotcha moment from the interviewee 534 00:32:17,520 --> 00:32:20,000 Speaker 1: and they'll just throw their hands up and say like, oh, 535 00:32:20,120 --> 00:32:23,080 Speaker 1: you're right, I'm completely wrong, blah blah blah blah. But 536 00:32:23,280 --> 00:32:27,000 Speaker 1: that hardly ever happens in my experience, Like even the 537 00:32:27,040 --> 00:32:31,440 Speaker 1: best interviewers in the world, it's difficult to elicit that 538 00:32:31,480 --> 00:32:35,760 Speaker 1: particular reaction because everyone is so on guard for that 539 00:32:35,880 --> 00:32:39,120 Speaker 1: like major admission. So it's interesting that you sort of 540 00:32:39,200 --> 00:32:42,320 Speaker 1: you go for the smaller admissions that maybe are tangential 541 00:32:42,440 --> 00:32:44,600 Speaker 1: to that, and then try to pull those threats. 542 00:32:44,840 --> 00:32:48,600 Speaker 4: In some cases yes, in some cases no, we're reading 543 00:32:48,680 --> 00:32:51,960 Speaker 4: them very closely as we're talking to them. If we 544 00:32:52,160 --> 00:32:56,840 Speaker 4: think that they're prone to confessing the you know, yes 545 00:32:56,920 --> 00:32:59,880 Speaker 4: I killed them, or yes I we cook the books, 546 00:33:00,120 --> 00:33:03,280 Speaker 4: or yes we did this, then we'll go for that. 547 00:33:03,920 --> 00:33:07,480 Speaker 4: But if it's clear that they're being cagey and they're 548 00:33:07,520 --> 00:33:11,160 Speaker 4: trying to dance around the issues and so forth, then 549 00:33:11,240 --> 00:33:16,360 Speaker 4: we'll go for much smaller chunks of information. And it's 550 00:33:16,440 --> 00:33:20,240 Speaker 4: very effective. And keep in mind the more questions you 551 00:33:20,520 --> 00:33:23,320 Speaker 4: ask someone a human being. But we know from the 552 00:33:23,320 --> 00:33:30,320 Speaker 4: behavioralist is that every time a person lies, their resistance doubles. 553 00:33:30,920 --> 00:33:33,880 Speaker 4: So if you were keeping score and you were lying 554 00:33:34,000 --> 00:33:36,920 Speaker 4: to me and I said, Tracy, did you do it? 555 00:33:37,480 --> 00:33:40,880 Speaker 4: And you say no, you get two points for your answer, 556 00:33:40,920 --> 00:33:43,480 Speaker 4: but I only get one for my question. And then 557 00:33:43,520 --> 00:33:46,560 Speaker 4: I ask it again in some other other way, and 558 00:33:46,600 --> 00:33:48,600 Speaker 4: now the score is four to two, and then eight 559 00:33:48,640 --> 00:33:50,360 Speaker 4: to three, and so on and so forth. 560 00:33:51,000 --> 00:33:52,760 Speaker 1: I'm sort of building up a wall. 561 00:33:52,560 --> 00:33:57,000 Speaker 4: I guess exactly. That's a great analogy, you're great metaphor. 562 00:33:56,760 --> 00:33:57,600 Speaker 2: Does everyone lie? 563 00:33:58,840 --> 00:34:02,480 Speaker 4: The research set as that in the western world, meaning 564 00:34:02,520 --> 00:34:06,680 Speaker 4: in the in the Western hemisphere, that the average person 565 00:34:06,840 --> 00:34:11,560 Speaker 4: lies at least ten times every day. Now, now they 566 00:34:11,640 --> 00:34:15,920 Speaker 4: include in those lies, you know, in the metrics for 567 00:34:16,000 --> 00:34:19,319 Speaker 4: that research, they include what we call you know, the 568 00:34:19,360 --> 00:34:22,200 Speaker 4: white lies. I like to call them the smart lies. 569 00:34:22,280 --> 00:34:25,200 Speaker 4: If I go home from this trip and my wife 570 00:34:25,200 --> 00:34:28,240 Speaker 4: has a new hairdo and I and my immediate thought 571 00:34:28,360 --> 00:34:30,920 Speaker 4: is yikes, and she goes, hey, honey, how do you 572 00:34:31,000 --> 00:34:33,600 Speaker 4: like my you know, my hairdew, I'm definitely not going 573 00:34:33,680 --> 00:34:37,480 Speaker 4: to say yikes, but I'm going to try to soften 574 00:34:37,560 --> 00:34:41,040 Speaker 4: the blow, you know, at a minimum. And if I 575 00:34:41,080 --> 00:34:43,880 Speaker 4: can get away with all, that's nice. And then you 576 00:34:43,880 --> 00:34:47,279 Speaker 4: know she'll she'll pick up on something. She worked for 577 00:34:47,320 --> 00:34:48,200 Speaker 4: the agency as. 578 00:34:48,040 --> 00:34:51,360 Speaker 2: Well, So it's got to be Yeah, that's so easy. 579 00:34:51,400 --> 00:34:52,920 Speaker 4: It's a two hit short. You're going to be very 580 00:34:53,000 --> 00:34:53,640 Speaker 4: very careful. 581 00:34:53,920 --> 00:34:57,759 Speaker 1: Wow, communication in your household must be both excellent and 582 00:34:57,840 --> 00:35:01,160 Speaker 1: at times fraud but phil At times. You have been 583 00:35:01,200 --> 00:35:04,960 Speaker 1: described as the human polygraph. I think, can we play 584 00:35:05,040 --> 00:35:06,800 Speaker 1: a little game, a little live spotting? 585 00:35:08,160 --> 00:35:11,160 Speaker 4: You can, but I will tell you up front that 586 00:35:11,560 --> 00:35:17,400 Speaker 4: what causes deceptive behaviors is the fear of detection, and 587 00:35:17,480 --> 00:35:21,800 Speaker 4: so parler games, it's difficult, if not impossible, to spot 588 00:35:21,840 --> 00:35:25,120 Speaker 4: the deception because the person doesn't have any fear. The 589 00:35:26,120 --> 00:35:29,040 Speaker 4: game is and they know and they know how the 590 00:35:29,080 --> 00:35:29,960 Speaker 4: path to win it. 591 00:35:30,640 --> 00:35:31,960 Speaker 1: Oh, maybe it's not a good idea. 592 00:35:32,000 --> 00:35:33,560 Speaker 3: Though, I want to know what your lie was going 593 00:35:33,600 --> 00:35:35,680 Speaker 3: to be, Tracy, I'll give it a shot as well. 594 00:35:35,719 --> 00:35:39,279 Speaker 1: And okay, all right, Three things. Number One, I went 595 00:35:39,320 --> 00:35:42,120 Speaker 1: on vacation to Brazil and it is my favorite place 596 00:35:42,120 --> 00:35:45,880 Speaker 1: in the world. Number two, I have a corky named Pablo. 597 00:35:46,239 --> 00:35:50,320 Speaker 1: He just turned four. Number three, I want saying karaoke 598 00:35:50,719 --> 00:35:51,960 Speaker 1: with sir Ian McKellen. 599 00:35:53,200 --> 00:35:54,560 Speaker 2: I think I know the answer. 600 00:35:54,680 --> 00:35:56,400 Speaker 1: I think you might know something because I just like 601 00:35:56,400 --> 00:35:59,200 Speaker 1: of enough, like you're. 602 00:35:58,960 --> 00:36:04,360 Speaker 4: You're you're exhibiting almost zero deceptive behavior. So I if 603 00:36:04,400 --> 00:36:06,560 Speaker 4: I were forced, I would have picked number one. 604 00:36:06,920 --> 00:36:10,040 Speaker 3: Oh that's right, that's right, that's right. That was there 605 00:36:10,120 --> 00:36:11,120 Speaker 3: something at all in the way. 606 00:36:11,160 --> 00:36:15,200 Speaker 4: She said that absolutely, she she went to the persuasion bucket. 607 00:36:15,520 --> 00:36:19,000 Speaker 4: To the others, she didn't there was nothing persuasively. 608 00:36:19,000 --> 00:36:20,160 Speaker 3: Wait, what did she say? 609 00:36:20,640 --> 00:36:21,279 Speaker 2: How did she phrase? 610 00:36:21,480 --> 00:36:23,720 Speaker 4: She said? That was? She says, I went on vacation 611 00:36:23,880 --> 00:36:28,040 Speaker 4: to Brazil and that's my favorite place in the whole world. 612 00:36:27,800 --> 00:36:31,200 Speaker 1: I emphasized it, and I don't normally emphasize words. 613 00:36:31,840 --> 00:36:34,000 Speaker 3: That's really good. That was really good because like I 614 00:36:34,080 --> 00:36:36,080 Speaker 3: knew it because I had heard you talk about karaoke 615 00:36:36,160 --> 00:36:38,240 Speaker 3: and I know your dog, so I just knew it, Brazil, 616 00:36:38,239 --> 00:36:41,719 Speaker 3: but I did not pick up on your embellishment of 617 00:36:41,800 --> 00:36:42,239 Speaker 3: that fact. 618 00:36:42,360 --> 00:36:45,320 Speaker 1: So this is I swear, this is such a frightening 619 00:36:45,400 --> 00:36:47,760 Speaker 1: episode for people who talk for a living. 620 00:36:48,560 --> 00:36:51,480 Speaker 3: Do polygraphs work. You mentioned you're the human polygraph but 621 00:36:51,520 --> 00:36:53,960 Speaker 3: where do we stand the conventional wisdom on actual. 622 00:36:53,760 --> 00:36:58,160 Speaker 4: Polygraphs in the in the hands of a well trained polygrapher, 623 00:36:58,760 --> 00:36:59,839 Speaker 4: they're incredible. 624 00:37:00,120 --> 00:37:03,480 Speaker 1: Oh really, yeah, Maybe just to boil it all down, 625 00:37:03,680 --> 00:37:08,120 Speaker 1: what is your top tip for spotting lies in the 626 00:37:08,160 --> 00:37:08,880 Speaker 1: business world? 627 00:37:09,680 --> 00:37:14,480 Speaker 4: At a minimum, pay attention to the evasion bucket. So 628 00:37:14,680 --> 00:37:18,640 Speaker 4: whether it's in a pre employment interview you're doing, whether 629 00:37:18,719 --> 00:37:22,200 Speaker 4: it's in an m and A situation, whether it's in 630 00:37:22,200 --> 00:37:27,840 Speaker 4: an employee malfeason situation, if they don't answer your question, 631 00:37:28,760 --> 00:37:32,640 Speaker 4: and if they don't answer it entirely, don't think of 632 00:37:32,680 --> 00:37:36,280 Speaker 4: yourself as a human light detector, but take that as 633 00:37:36,560 --> 00:37:41,000 Speaker 4: a catalyst for doing more work. I give you a 634 00:37:41,000 --> 00:37:45,960 Speaker 4: great example. I remember interviewing a very senior executive candidate 635 00:37:46,400 --> 00:37:51,320 Speaker 4: at a Fortune two hundred company, and they love this guy. 636 00:37:51,440 --> 00:37:54,920 Speaker 4: Everybody had interviewed him, they loved him. And when I 637 00:37:55,040 --> 00:37:58,560 Speaker 4: interviewed him after the one hour interview, I walked back 638 00:37:58,600 --> 00:38:01,120 Speaker 4: out into the CEO's office. They said what did you think? 639 00:38:01,200 --> 00:38:04,600 Speaker 4: And I said, well, he's got a lot going for him. 640 00:38:05,080 --> 00:38:08,280 Speaker 4: But the problem I'm concerned about is he's been either 641 00:38:08,440 --> 00:38:13,160 Speaker 4: fired or separated involuntarily from his last five jobs. 642 00:38:13,520 --> 00:38:14,279 Speaker 1: How did you know that? 643 00:38:14,719 --> 00:38:18,640 Speaker 4: Because when I ask him the first time, I asked 644 00:38:18,719 --> 00:38:22,040 Speaker 4: the normal questions, but then I ask a question that 645 00:38:22,200 --> 00:38:26,600 Speaker 4: no one typically asks. So somebody comes in and says, oh, 646 00:38:26,800 --> 00:38:31,080 Speaker 4: we had a restructuring and you know I was thinking 647 00:38:31,120 --> 00:38:34,440 Speaker 4: about maybe changing jobs. So I put up my hand 648 00:38:34,480 --> 00:38:37,279 Speaker 4: and said, I you know, hey, I'll be glad to 649 00:38:37,320 --> 00:38:41,560 Speaker 4: take one of those or whatever and so, and people say, okay, 650 00:38:41,560 --> 00:38:43,080 Speaker 4: that makes sense. We hear a lot of people that 651 00:38:43,200 --> 00:38:47,800 Speaker 4: do that, but they fail to ask the simple question, 652 00:38:48,520 --> 00:38:51,479 Speaker 4: could you have stayed if you wanted to? Wow? 653 00:38:51,640 --> 00:38:54,120 Speaker 3: I just have one more small question, out of curiosity, 654 00:38:54,800 --> 00:38:57,640 Speaker 3: have you or anyone approached you or is there any 655 00:38:57,640 --> 00:39:01,360 Speaker 3: work on AI machine learning of pro just to lie detection? 656 00:39:01,440 --> 00:39:04,680 Speaker 3: If you have all these video of interrogations and texts 657 00:39:04,680 --> 00:39:07,520 Speaker 3: and documents other is there any work being done on 658 00:39:07,560 --> 00:39:08,040 Speaker 3: that approach? 659 00:39:08,160 --> 00:39:10,560 Speaker 4: Joe, I'm so glad you asked. We are working on 660 00:39:10,640 --> 00:39:15,560 Speaker 4: it furiously and we've already had some success and we're 661 00:39:15,600 --> 00:39:16,960 Speaker 4: making great progress. 662 00:39:17,440 --> 00:39:20,120 Speaker 1: Exciting stuff, all right, Phil Houston, thank you so much 663 00:39:20,200 --> 00:39:22,960 Speaker 1: for coming on all thoughts and telling us how to 664 00:39:23,320 --> 00:39:25,120 Speaker 1: spy the lie. I appreciate it. 665 00:39:25,320 --> 00:39:26,839 Speaker 4: Thank you guys. It's been fun. 666 00:39:26,880 --> 00:39:28,480 Speaker 2: That was really fun. Thank you so fun. 667 00:39:28,600 --> 00:39:44,680 Speaker 1: Yeah, it was terrifying and fun. Joe, that was really fun. 668 00:39:45,000 --> 00:39:48,200 Speaker 3: I was super impressed that he caught your lie. I know, 669 00:39:48,360 --> 00:39:50,480 Speaker 3: especially because, as you said, you don't make sense that 670 00:39:50,600 --> 00:39:54,000 Speaker 3: parlor games when the stakes aren't really there, that you're 671 00:39:54,000 --> 00:39:55,560 Speaker 3: not going to have that same response, but that he 672 00:39:55,760 --> 00:39:59,239 Speaker 3: caught that embellishment your first question and flagged it. 673 00:39:59,600 --> 00:40:02,200 Speaker 1: And it's definitely going to make me think about what 674 00:40:02,280 --> 00:40:04,080 Speaker 1: words I'm emphasizing you. 675 00:40:04,920 --> 00:40:08,120 Speaker 3: Didn't mean to like at that point, right, No, Like 676 00:40:08,160 --> 00:40:09,840 Speaker 3: you didn't think I'm going to give a little clue 677 00:40:09,920 --> 00:40:11,600 Speaker 3: here on this one right now. No, I s not 678 00:40:11,800 --> 00:40:14,440 Speaker 3: voluntarily offered up a clue that, like you did not 679 00:40:14,520 --> 00:40:14,960 Speaker 3: intend to. 680 00:40:15,239 --> 00:40:18,160 Speaker 1: Yeah, I mean I tried to make them like fairly neutral. 681 00:40:18,200 --> 00:40:20,520 Speaker 1: Obviously you have to say something, but I was trying 682 00:40:20,560 --> 00:40:23,640 Speaker 1: to make each of them like roughly similar to the others. 683 00:40:23,640 --> 00:40:27,279 Speaker 1: But he absolutely nailed it. No, I thought that entire 684 00:40:27,320 --> 00:40:31,360 Speaker 1: conversation was really interesting, especially given that our day jobs 685 00:40:31,520 --> 00:40:34,640 Speaker 1: is to interview people, and the idea of like, maybe 686 00:40:34,680 --> 00:40:38,520 Speaker 1: you don't seek out the big admission if people are 687 00:40:38,640 --> 00:40:41,680 Speaker 1: cagey or if they're in pr mode and you know 688 00:40:41,719 --> 00:40:43,600 Speaker 1: they have a story that they want to tell, but 689 00:40:43,640 --> 00:40:47,359 Speaker 1: maybe you try to nibble around the edges at smaller admissions. 690 00:40:47,440 --> 00:40:49,640 Speaker 3: Well. And the other thing too is even if we're 691 00:40:49,680 --> 00:40:51,880 Speaker 3: not in our jobs like trying to like, you know, 692 00:40:51,920 --> 00:40:54,520 Speaker 3: most of our interviews aren't like gotcha now views, But 693 00:40:54,600 --> 00:40:58,160 Speaker 3: I think that there's something to be gleaned about question 694 00:40:58,400 --> 00:41:02,200 Speaker 3: structure and what is it that's going to elicit the 695 00:41:02,239 --> 00:41:05,520 Speaker 3: most fruitful answer? And so even in his first example, 696 00:41:05,560 --> 00:41:08,520 Speaker 3: are you concerned about X? It seems like that's the 697 00:41:08,600 --> 00:41:11,160 Speaker 3: question we might ask on a range of things. Are 698 00:41:11,160 --> 00:41:13,239 Speaker 3: you concerned about what AI is going to do to 699 00:41:13,280 --> 00:41:15,880 Speaker 3: your business? Are you're concerned about what the energy transition 700 00:41:16,040 --> 00:41:19,040 Speaker 3: is going to do to your oil company? Versus? Maybe 701 00:41:19,120 --> 00:41:21,640 Speaker 3: we can frame it as what are your biggest concerns 702 00:41:21,680 --> 00:41:23,960 Speaker 3: about how AI will affect your business? What are your 703 00:41:24,040 --> 00:41:26,920 Speaker 3: biggest concerns about the energy transition? Even when we're not 704 00:41:27,000 --> 00:41:29,200 Speaker 3: trying to catch people in a lie, there's probably good 705 00:41:29,280 --> 00:41:32,000 Speaker 3: lessons and hear about higher quality questions. 706 00:41:31,640 --> 00:41:32,120 Speaker 4: Just in general. 707 00:41:32,320 --> 00:41:36,440 Speaker 1: Absolutely also asking the questions that other people haven't asked yet. 708 00:41:36,640 --> 00:41:38,640 Speaker 1: We do try to do that, Like sometimes we ask 709 00:41:38,719 --> 00:41:42,160 Speaker 1: the obvious questions. Yeah, and they're the most interesting ones, 710 00:41:42,200 --> 00:41:44,920 Speaker 1: but no one has asked them before because they seem 711 00:41:45,080 --> 00:41:48,920 Speaker 1: so obvious. Totally, Well, anyway, shall we leave it there? 712 00:41:49,000 --> 00:41:49,719 Speaker 2: Let's leave it there. 713 00:41:49,920 --> 00:41:52,880 Speaker 1: This has been another episode of the Odd Thoughts podcast. 714 00:41:52,960 --> 00:41:56,000 Speaker 1: I'm Tracy Alloway. You can follow me at Tracy Alloway. 715 00:41:56,080 --> 00:41:58,960 Speaker 3: And I'm Joe Wisenthal. You can follow me at the Stalwart. 716 00:41:59,320 --> 00:42:02,719 Speaker 3: Check out the book Spy the Live former CIA officers 717 00:42:02,760 --> 00:42:06,240 Speaker 3: teach you how to detect deception from our guest Phil Houston, 718 00:42:06,320 --> 00:42:10,160 Speaker 3: follow our producers Carmen Rodriguez at Carmen armand Dashel Bennett 719 00:42:10,160 --> 00:42:13,319 Speaker 3: at Dashbot and kil Brooks at Cale Brooks. And thank 720 00:42:13,360 --> 00:42:16,680 Speaker 3: you to our producer Moses ondm and from our Oddlogs content. 721 00:42:16,760 --> 00:42:19,760 Speaker 3: Go to Bloomberg dot com slash odd Lots. Weable blog 722 00:42:19,920 --> 00:42:23,239 Speaker 3: transcription in the newsletter, and check out the Discord chat 723 00:42:23,280 --> 00:42:26,320 Speaker 3: twenty four to seven with fellow listeners Discord dot gg 724 00:42:26,400 --> 00:42:26,960 Speaker 3: slash od. 725 00:42:27,000 --> 00:42:30,120 Speaker 1: Loots and if you enjoy odd Lots, if you want 726 00:42:30,200 --> 00:42:32,640 Speaker 1: Joe and I to tell more lies to each other 727 00:42:32,719 --> 00:42:35,680 Speaker 1: and play parlor games around that, then please leave us 728 00:42:35,719 --> 00:42:39,480 Speaker 1: a positive review on your favorite podcast platform and a 729 00:42:39,560 --> 00:42:43,600 Speaker 1: reminder for Bloomberg subscribers, you can listen to all Oddlots 730 00:42:43,640 --> 00:42:47,680 Speaker 1: episodes ad free if you connect your Bloomberg subscription to 731 00:42:47,880 --> 00:42:49,920 Speaker 1: Apple Podcasts. Thanks for listening 732 00:43:07,080 --> 00:43:07,120 Speaker 4: In