1 00:00:00,280 --> 00:00:04,720 Speaker 1: From UFOs to psychic powers and government conspiracies. History is 2 00:00:04,840 --> 00:00:09,119 Speaker 1: riddled with unexplained events. You can turn back now or 3 00:00:09,240 --> 00:00:12,200 Speaker 1: learn the stuff they don't want you to know. A 4 00:00:12,280 --> 00:00:13,960 Speaker 1: production of iHeartRadio. 5 00:00:24,200 --> 00:00:26,560 Speaker 2: Hello, welcome back to the show. My name is Matt, 6 00:00:26,760 --> 00:00:27,600 Speaker 2: my name is Nol. 7 00:00:27,960 --> 00:00:30,600 Speaker 3: They called me Ben. We're joined as always with our 8 00:00:30,680 --> 00:00:36,240 Speaker 3: super producer Alexis codenamed Dot Holliday Jackson. Most importantly, you 9 00:00:36,320 --> 00:00:40,680 Speaker 3: are here. That makes this the stuff they don't want 10 00:00:40,760 --> 00:00:45,839 Speaker 3: you to know. Common misconception about doing a podcast or 11 00:00:45,880 --> 00:00:48,320 Speaker 3: a show like this is the idea that people should 12 00:00:48,360 --> 00:00:51,440 Speaker 3: be good at speaking. We're okay at it, But the 13 00:00:51,479 --> 00:00:55,160 Speaker 3: more important skill in any show of this nature is 14 00:00:55,200 --> 00:00:58,840 Speaker 3: to listen. And that is why this is one of 15 00:00:58,880 --> 00:01:01,000 Speaker 3: our favorite time times. 16 00:01:00,760 --> 00:01:01,640 Speaker 4: Of the week. 17 00:01:02,320 --> 00:01:06,400 Speaker 3: This is our weekly listener male segment where we get 18 00:01:06,440 --> 00:01:09,559 Speaker 3: to hang out with the best part of the show, 19 00:01:09,640 --> 00:01:14,600 Speaker 3: which is you, specifically you and your fellow conspiracy realist. 20 00:01:15,080 --> 00:01:20,559 Speaker 3: Today we are going to learn, We're going to get 21 00:01:20,600 --> 00:01:25,520 Speaker 3: corrected with some assumptions about things like Madlib. We're going 22 00:01:25,560 --> 00:01:32,080 Speaker 3: to have a conversation about important and dangerous misdiagnoses in 23 00:01:32,160 --> 00:01:36,360 Speaker 3: the world of medicine and behavior. We're going to talk 24 00:01:36,560 --> 00:01:40,640 Speaker 3: about folklore in a way that we hope fascinates everyone 25 00:01:40,800 --> 00:01:45,640 Speaker 3: tuning in. And before we do any of that, we 26 00:01:45,920 --> 00:01:48,960 Speaker 3: have to talk about at least a little bit of 27 00:01:49,000 --> 00:01:53,600 Speaker 3: the amazing correspondence we got in response to our story 28 00:01:53,880 --> 00:01:57,560 Speaker 3: from that on Skyborg, not Cyborg. 29 00:01:57,600 --> 00:02:04,640 Speaker 5: Skyborg, not Skynet, not the Borg, not Skyrim, somehow portmanteau 30 00:02:04,720 --> 00:02:09,120 Speaker 5: of all of those things, and thematic mish mash at 31 00:02:09,200 --> 00:02:11,720 Speaker 5: least two of them. Let's let you guess which one 32 00:02:11,960 --> 00:02:13,600 Speaker 5: is non included. It has to do with an arrow 33 00:02:13,639 --> 00:02:19,160 Speaker 5: in the knee. But yeah, Skyborg, the least malevolent, soundingly 34 00:02:19,280 --> 00:02:24,760 Speaker 5: named piece of military technology I could possibly imagine. Yeah, Skyborg, Matt, 35 00:02:24,880 --> 00:02:30,600 Speaker 5: you brought that piece of strange news, terrifying news, dystopian news. 36 00:02:31,000 --> 00:02:33,000 Speaker 4: Last week or the week before, I can't remember. 37 00:02:33,919 --> 00:02:37,120 Speaker 5: But yeah, there's not a whole lot out there about it, 38 00:02:37,160 --> 00:02:39,359 Speaker 5: which is really interesting. Like I was trying to read 39 00:02:39,440 --> 00:02:40,959 Speaker 5: up on it and look up some and there's a 40 00:02:41,000 --> 00:02:45,679 Speaker 5: lot of like kind of almost marketing type videos for it. 41 00:02:45,680 --> 00:02:49,359 Speaker 5: It seems like it's weird, like the promotion that's being 42 00:02:49,400 --> 00:02:54,640 Speaker 5: done very militaristically styled marketing videos. But you know, just 43 00:02:54,680 --> 00:02:59,000 Speaker 5: to refresher, it is an AI type of drone, at 44 00:02:59,080 --> 00:03:01,359 Speaker 5: least this version that we talked about that you talked 45 00:03:01,360 --> 00:03:04,800 Speaker 5: about MAP is access more of a wingman sort of 46 00:03:04,840 --> 00:03:07,720 Speaker 5: like it hangs it. It's your buddy, you know, I've 47 00:03:07,720 --> 00:03:10,480 Speaker 5: been I think you mentioned Goose is his name? Goose? 48 00:03:11,160 --> 00:03:13,720 Speaker 4: Was heither the wingman from UH or the Iceman? 49 00:03:13,800 --> 00:03:16,360 Speaker 5: I don't remember the Actually, God, I've never seen Top 50 00:03:16,360 --> 00:03:17,800 Speaker 5: Gun nor Top Gun Maverick. 51 00:03:18,080 --> 00:03:20,880 Speaker 3: It's like a class. It's like any American classic. You 52 00:03:20,919 --> 00:03:23,360 Speaker 3: don't have to have actually seen it to understand the 53 00:03:23,440 --> 00:03:26,840 Speaker 3: story because got it. The memes alone tell you the narrative. 54 00:03:26,919 --> 00:03:30,920 Speaker 3: But yeah, man, it's spooky, right, like the marketing there is. 55 00:03:31,760 --> 00:03:32,639 Speaker 4: What what was that? 56 00:03:32,720 --> 00:03:35,119 Speaker 3: What was that story we talked about? Okay, so there 57 00:03:35,200 --> 00:03:38,320 Speaker 3: was a successful test, but it's not public what the 58 00:03:38,400 --> 00:03:40,960 Speaker 3: test was about or why it was successful. 59 00:03:41,120 --> 00:03:41,280 Speaker 4: Right. 60 00:03:42,000 --> 00:03:47,200 Speaker 2: Yeah, the system that is Skyborg functioned, right, That's that's 61 00:03:47,240 --> 00:03:51,640 Speaker 2: what the test was. The sensors in the sky Wingman 62 00:03:51,880 --> 00:03:54,040 Speaker 2: thing that is the R two D two that is 63 00:03:54,120 --> 00:03:55,240 Speaker 2: Skyborg worked. 64 00:03:55,640 --> 00:03:57,040 Speaker 4: That's what we know. Tight. 65 00:03:57,360 --> 00:03:59,880 Speaker 5: Yeah, all that stuff. And then we we already had 66 00:03:59,880 --> 00:04:03,120 Speaker 5: this part of the conversation where we sort of freaked 67 00:04:03,120 --> 00:04:05,920 Speaker 5: out a little bit and made you know, low key 68 00:04:06,120 --> 00:04:08,240 Speaker 5: kind of jokes about the thing, but really, at the 69 00:04:08,320 --> 00:04:12,200 Speaker 5: end of the day, it is terrifying because of just 70 00:04:12,280 --> 00:04:14,480 Speaker 5: the fact that AI is now being seen as like 71 00:04:14,520 --> 00:04:17,600 Speaker 5: a solution for just about everything. And I actually I 72 00:04:17,640 --> 00:04:19,640 Speaker 5: found a really cool podcast today. I'm going to get 73 00:04:19,640 --> 00:04:21,840 Speaker 5: to the listener mail, but I found a really cool 74 00:04:21,880 --> 00:04:25,800 Speaker 5: podcast today. Seems like more people should be listening to it. 75 00:04:25,800 --> 00:04:32,679 Speaker 5: It's called AI with AI. The AI stands for Andy Ilachinsky, 76 00:04:33,200 --> 00:04:35,760 Speaker 5: who I don't know his work. I just found it today, 77 00:04:35,839 --> 00:04:37,320 Speaker 5: but it seems like him that he and his co 78 00:04:37,400 --> 00:04:41,680 Speaker 5: host David Broyles, who's that name rings a bell? Why 79 00:04:41,720 --> 00:04:44,080 Speaker 5: does that name ring a bell? Are very very well 80 00:04:44,160 --> 00:04:46,000 Speaker 5: versed in AI, and they're up to date and all 81 00:04:46,040 --> 00:04:50,560 Speaker 5: the latest stuff. And they point out that like algorithms 82 00:04:50,600 --> 00:04:53,719 Speaker 5: in AI become this like du joure kind of solution, 83 00:04:54,120 --> 00:04:57,000 Speaker 5: and that there are some problems where an algorithm or 84 00:04:57,040 --> 00:05:00,320 Speaker 5: AI is not the solution. It's just not appropriate, you know, 85 00:05:00,400 --> 00:05:03,520 Speaker 5: and and specifically when it comes to the military. But 86 00:05:03,920 --> 00:05:06,040 Speaker 5: that's a conversation for another day, But do check. 87 00:05:05,880 --> 00:05:07,039 Speaker 4: Out AI with AI. 88 00:05:08,000 --> 00:05:12,719 Speaker 5: The email that we got today actually comes from a 89 00:05:12,880 --> 00:05:17,240 Speaker 5: listener who would like to go by the name Fast Mickey, 90 00:05:17,360 --> 00:05:20,960 Speaker 5: which sounds like a top gun character as well. And 91 00:05:21,000 --> 00:05:23,000 Speaker 5: this is what Fastnickey had to say. 92 00:05:23,600 --> 00:05:24,560 Speaker 2: Hey, guys, I have been loving. 93 00:05:24,440 --> 00:05:27,360 Speaker 5: Our recent episodes, but there was one listener mail that 94 00:05:27,480 --> 00:05:30,920 Speaker 5: I thought I'd like to respond to, specifically the skyboard 95 00:05:30,920 --> 00:05:32,719 Speaker 5: because that's how you have to say. Was listening to 96 00:05:32,760 --> 00:05:36,200 Speaker 5: another podcast about AI, I know, right, and on that 97 00:05:36,240 --> 00:05:37,880 Speaker 5: show the interview we dropped a reel. 98 00:05:38,320 --> 00:05:40,760 Speaker 4: Well that's us comment. 99 00:05:41,720 --> 00:05:43,320 Speaker 5: He wanted to get rid of the idea that we 100 00:05:43,480 --> 00:05:46,520 Speaker 5: humans would have any hope against AI in any real sense. 101 00:05:46,839 --> 00:05:50,360 Speaker 5: The example he gave was in an airborne dogfight as 102 00:05:50,440 --> 00:05:53,560 Speaker 5: a meat machine. I'm sure you're aware that we operate 103 00:05:53,600 --> 00:05:58,400 Speaker 5: at a thirty millisecond lag plus or minus. Once we 104 00:05:58,440 --> 00:06:01,640 Speaker 5: see something, the signal goes along our visual cortex, then 105 00:06:01,680 --> 00:06:04,240 Speaker 5: gets processed to evaluate it, and we decide what to 106 00:06:04,279 --> 00:06:07,000 Speaker 5: do about it. Given even the fact that we can 107 00:06:07,040 --> 00:06:10,080 Speaker 5: preemptively do things, there is still a lag. 108 00:06:10,000 --> 00:06:12,560 Speaker 2: And there's hey, just to pause there before you even 109 00:06:12,640 --> 00:06:16,000 Speaker 2: keep going. There's also the lag of once it hits 110 00:06:16,040 --> 00:06:18,280 Speaker 2: you the equipment, you're yeah, because then you've got to 111 00:06:18,320 --> 00:06:21,040 Speaker 2: send a signal back down to your arms to take 112 00:06:21,120 --> 00:06:21,520 Speaker 2: that move. 113 00:06:22,600 --> 00:06:24,560 Speaker 5: For sure, the round trip and then also, yeah, there's 114 00:06:24,600 --> 00:06:27,200 Speaker 5: also lag. You know, there's lag in video game controllers. 115 00:06:27,200 --> 00:06:29,599 Speaker 5: There's a lag of anything, So we add that into it. 116 00:06:29,800 --> 00:06:33,039 Speaker 5: I mean, we are inherently kind of handicapped compared to 117 00:06:33,440 --> 00:06:36,240 Speaker 5: as he's about to get to the AI or you know, 118 00:06:36,960 --> 00:06:41,440 Speaker 5: robots operating using machine learning. Given the fact that we 119 00:06:41,440 --> 00:06:43,960 Speaker 5: can preemptively do things, there is still a lag. The AI, 120 00:06:44,000 --> 00:06:46,040 Speaker 5: on the other hand, is operating it basically zero lag. 121 00:06:46,120 --> 00:06:48,400 Speaker 5: Within that time would have come up with tens of 122 00:06:48,480 --> 00:06:51,760 Speaker 5: thousands of firing solutions. There wouldn't be a dogfight. We 123 00:06:51,800 --> 00:06:54,720 Speaker 5: would be shot out of the sky immediately, even with 124 00:06:54,800 --> 00:06:58,240 Speaker 5: Tom Cruise in the pilot seat. Call me fast, Mickey 125 00:06:58,680 --> 00:07:02,640 Speaker 5: and cheers, well, cheers to you, fast Miki. And yeah, 126 00:07:02,680 --> 00:07:08,560 Speaker 5: I mean, you know, that's one thing that is inherently troubling. 127 00:07:08,640 --> 00:07:11,440 Speaker 5: I suppose maybe not troubling, and maybe it's maybe it's 128 00:07:11,520 --> 00:07:16,000 Speaker 5: it's it's what people want. But the fact that machines 129 00:07:16,120 --> 00:07:18,800 Speaker 5: and you know, AI for example, or whatever you want 130 00:07:18,800 --> 00:07:20,040 Speaker 5: to call it, I know, the AI tends to be 131 00:07:20,040 --> 00:07:21,760 Speaker 5: a bit of a misnomer in the way they use it. 132 00:07:21,880 --> 00:07:24,800 Speaker 5: I do, I do as well, I completely do as well. 133 00:07:24,920 --> 00:07:26,520 Speaker 5: It just seems to be a catch all term. It's 134 00:07:26,520 --> 00:07:29,360 Speaker 5: sort of become a pop cultural reference point. So it's 135 00:07:29,360 --> 00:07:31,520 Speaker 5: a little hard to have the conversation without throwing it 136 00:07:31,560 --> 00:07:33,600 Speaker 5: in there. But I think it's also important to remind 137 00:07:33,640 --> 00:07:37,600 Speaker 5: people without being condescending jerk at parties, that it is 138 00:07:37,680 --> 00:07:41,560 Speaker 5: more machine learning or language modeling and things like that. 139 00:07:41,880 --> 00:07:47,160 Speaker 5: But this ability for these machines to learn is vast. 140 00:07:47,320 --> 00:07:50,680 Speaker 5: It's like Keanu Reeves knowing kung fu vast, you know, 141 00:07:51,080 --> 00:07:54,600 Speaker 5: like a machine algorithm, you know, or a whatever you 142 00:07:54,600 --> 00:07:57,320 Speaker 5: want to call it, let's just call it machine learning 143 00:07:57,720 --> 00:08:03,320 Speaker 5: situation can basically ingest the entire Internet, you know, in 144 00:08:03,560 --> 00:08:05,440 Speaker 5: the span of what it would take us to like 145 00:08:05,600 --> 00:08:09,680 Speaker 5: read a chapter in a book. Again, it all depends 146 00:08:09,720 --> 00:08:12,600 Speaker 5: on processing speed and cloud computing or whatever you want 147 00:08:12,600 --> 00:08:16,440 Speaker 5: to call it, like combined computing or whatever. There's lots 148 00:08:16,480 --> 00:08:18,680 Speaker 5: of different scenarios, but that would change, you know, the 149 00:08:18,720 --> 00:08:21,200 Speaker 5: speed of calculation or whatever. But in general, wouldn't you 150 00:08:21,200 --> 00:08:23,960 Speaker 5: guys agree that that's the case. They're like computers can 151 00:08:24,720 --> 00:08:28,320 Speaker 5: ingest much larger pieces, much larger amounts of information than 152 00:08:28,320 --> 00:08:31,200 Speaker 5: we possibly can, and come to a series of conclusions 153 00:08:31,240 --> 00:08:33,120 Speaker 5: and then act much more quickly than we can. 154 00:08:33,160 --> 00:08:37,440 Speaker 2: That's why deep learning models work, right, That's why they're 155 00:08:37,440 --> 00:08:39,800 Speaker 2: so astonishing and revolutionary. 156 00:08:40,000 --> 00:08:40,400 Speaker 4: Yeah. 157 00:08:40,400 --> 00:08:45,559 Speaker 5: Absolutely, Yeah, And maybe this isn't like the aha moment 158 00:08:45,600 --> 00:08:46,880 Speaker 5: of all this. I think this is something that probably 159 00:08:47,000 --> 00:08:48,600 Speaker 5: was always at the back of all of our minds 160 00:08:48,679 --> 00:08:51,679 Speaker 5: around these things and around any conversation around this kind 161 00:08:51,720 --> 00:08:56,040 Speaker 5: of stuff. But it's true, like the precision of this 162 00:08:56,320 --> 00:08:58,480 Speaker 5: would there would be But again, isn't that sort of 163 00:08:58,960 --> 00:09:01,760 Speaker 5: don't we sort of want it take the fight out 164 00:09:01,840 --> 00:09:04,280 Speaker 5: of war that we want to just make it like 165 00:09:04,679 --> 00:09:08,240 Speaker 5: an instantaneous result, you know, That's that's how we want 166 00:09:08,280 --> 00:09:10,640 Speaker 5: to be able to you know, we want we want 167 00:09:10,640 --> 00:09:14,120 Speaker 5: war to be as clean and as precise as possible. 168 00:09:14,120 --> 00:09:16,040 Speaker 5: We know that can't always work out with drones which 169 00:09:16,040 --> 00:09:18,520 Speaker 5: who were being which were being operated by humans, you know, 170 00:09:18,679 --> 00:09:21,400 Speaker 5: much like a video game, but that still involves a 171 00:09:21,440 --> 00:09:24,400 Speaker 5: lot of human error, even though you can still perhaps 172 00:09:24,520 --> 00:09:26,840 Speaker 5: cut down the kind of collateral damage you would with 173 00:09:26,920 --> 00:09:33,480 Speaker 5: a larger scale ground conflict. But this AI making decisions again, 174 00:09:33,800 --> 00:09:35,880 Speaker 5: the way they're putting it out there, it's in tandem 175 00:09:36,000 --> 00:09:41,160 Speaker 5: with a human sort of minder, but like, ultimately it 176 00:09:41,240 --> 00:09:44,880 Speaker 5: is making those calculations, right, Like Matt I know that 177 00:09:44,880 --> 00:09:46,520 Speaker 5: you probably did the deepest dive into this. Is that 178 00:09:46,559 --> 00:09:49,520 Speaker 5: your understanding, like, is it always have to ask permission? 179 00:09:50,280 --> 00:09:53,400 Speaker 5: Is it presenting the human companion with options and then 180 00:09:53,400 --> 00:09:55,000 Speaker 5: the human companion gets to decide. 181 00:09:55,400 --> 00:09:59,960 Speaker 2: My understanding is that it's sensors. It's sensor operations. Basically, 182 00:10:00,000 --> 00:10:02,839 Speaker 2: I don't know if you, I don't know how you 183 00:10:02,840 --> 00:10:05,880 Speaker 2: would put it. It's giving you a better understanding of 184 00:10:05,920 --> 00:10:09,680 Speaker 2: the battlefield while you're operating as a pilot. That's my 185 00:10:09,880 --> 00:10:14,200 Speaker 2: understanding of what Skyborg does. Right when I was researching it, 186 00:10:14,200 --> 00:10:16,680 Speaker 2: there were no weapons systems on board any of the 187 00:10:16,679 --> 00:10:20,280 Speaker 2: Skyborg drones that were flying as wingmen. But that seems 188 00:10:20,320 --> 00:10:22,600 Speaker 2: a bit strange to me that that would be the case. 189 00:10:23,200 --> 00:10:26,120 Speaker 2: I highly doubt that's the final form. I don't know, 190 00:10:26,120 --> 00:10:26,559 Speaker 2: what do you think? 191 00:10:26,600 --> 00:10:26,840 Speaker 4: Ben? 192 00:10:27,120 --> 00:10:31,320 Speaker 3: Of course, going back to our earlier example, when the 193 00:10:32,240 --> 00:10:36,880 Speaker 3: Robodog first came out, first went public, we predicted there 194 00:10:36,920 --> 00:10:40,199 Speaker 3: would be a weapon or armament of some sort attached 195 00:10:40,240 --> 00:10:44,080 Speaker 3: to it. From what I understand speaking with people, and 196 00:10:44,160 --> 00:10:47,400 Speaker 3: this is publicly available knowledge. I'm not spilling any old 197 00:10:47,440 --> 00:10:50,679 Speaker 3: beans here or any new beans. These are all old beans. 198 00:10:51,280 --> 00:10:55,360 Speaker 3: Skyborg is meant to maintain what is called combat mass. 199 00:10:55,880 --> 00:10:58,600 Speaker 3: So it is like your buddy, your eyes in the sky, 200 00:10:58,840 --> 00:11:02,320 Speaker 3: you know. And and I also don't think it's in 201 00:11:02,360 --> 00:11:06,320 Speaker 3: any way condescending to object to the term AI. That's like, 202 00:11:07,040 --> 00:11:10,360 Speaker 3: I think this is not generalized. AI is what people 203 00:11:10,400 --> 00:11:13,920 Speaker 3: need to understand. And what fast Mickey, what you're saying 204 00:11:14,280 --> 00:11:18,240 Speaker 3: that's so amazing is the idea of that response time 205 00:11:18,760 --> 00:11:23,400 Speaker 3: like this could save human lives, save pilot lives, save 206 00:11:23,440 --> 00:11:26,720 Speaker 3: the lives of people on the ground. That part is true. 207 00:11:26,920 --> 00:11:29,400 Speaker 3: And I feel like Skyboard is going to be a 208 00:11:29,400 --> 00:11:33,800 Speaker 3: harbinger or already is a harbinger of new things that 209 00:11:33,920 --> 00:11:37,080 Speaker 3: are on the way a multi your excellent point about 210 00:11:37,080 --> 00:11:41,120 Speaker 3: the concept of reducing the horrors of war. 211 00:11:41,920 --> 00:11:43,720 Speaker 4: There is a world where. 212 00:11:43,559 --> 00:11:47,440 Speaker 3: Technology like this could could make that a reality. The 213 00:11:47,559 --> 00:11:52,640 Speaker 3: question is will it do so? How will it be leveraged? Right? Like, 214 00:11:52,720 --> 00:11:57,480 Speaker 3: how will what will the future of war look like? 215 00:11:58,160 --> 00:12:00,760 Speaker 3: War has been an ugly shadow that has followed the 216 00:12:00,840 --> 00:12:06,920 Speaker 3: human species all its days and nights. Will war follow 217 00:12:07,600 --> 00:12:10,640 Speaker 3: non human minds as well? To your point, I think 218 00:12:10,679 --> 00:12:13,640 Speaker 3: it's a big philosophical question and no one knows the 219 00:12:13,679 --> 00:12:14,280 Speaker 3: answer yet. 220 00:12:14,720 --> 00:12:16,200 Speaker 5: That's right, And I think a lot of this too, 221 00:12:16,760 --> 00:12:20,200 Speaker 5: is the fear around it sort of based on the 222 00:12:20,240 --> 00:12:24,800 Speaker 5: idea of the machine going rogue and not having some 223 00:12:24,920 --> 00:12:28,200 Speaker 5: kind of parameter lock to like some you know, a 224 00:12:28,240 --> 00:12:31,120 Speaker 5: decision that a superior could make, or the idea of 225 00:12:31,160 --> 00:12:34,960 Speaker 5: like experiencing the singularity and then no longer feeling the 226 00:12:35,000 --> 00:12:36,920 Speaker 5: need to do what it's told. I mean, that's sort 227 00:12:36,920 --> 00:12:40,319 Speaker 5: of the old, you know, Frankenstein's Monster kind of trope, like. 228 00:12:40,360 --> 00:12:42,160 Speaker 4: What do we created? What have we done? 229 00:12:43,679 --> 00:12:46,280 Speaker 5: But it's too late to go back? But that I think, 230 00:12:46,320 --> 00:12:48,680 Speaker 5: you know, I'm realizing too, and I'm sure you guys 231 00:12:48,679 --> 00:12:51,880 Speaker 5: have run across this. There is a lot of philosophical 232 00:12:52,240 --> 00:12:57,280 Speaker 5: conversation centered around AI and around the existential threat that 233 00:12:57,400 --> 00:13:00,920 Speaker 5: many in the you know, philosophical community or even scientific 234 00:13:00,960 --> 00:13:05,160 Speaker 5: community see as what the threat that this poses. And 235 00:13:05,200 --> 00:13:08,160 Speaker 5: it's just like another example of like trying out a 236 00:13:08,280 --> 00:13:10,400 Speaker 5: drug that we haven't fully tested yet and then we 237 00:13:10,400 --> 00:13:14,440 Speaker 5: don't really understand, and putting it in a situation where 238 00:13:14,520 --> 00:13:17,480 Speaker 5: if it does go wrong, it's gonna be the worst 239 00:13:17,520 --> 00:13:21,920 Speaker 5: possible version of going wrong, and that I yield my time. 240 00:13:23,120 --> 00:13:25,400 Speaker 2: I would just point out another piece of mail we 241 00:13:25,440 --> 00:13:31,280 Speaker 2: got in concerning Skyborg from El Signor Gatto Don Gatto. 242 00:13:31,559 --> 00:13:35,440 Speaker 2: I can't remember, guys, Uh who was it? It was 243 00:13:35,720 --> 00:13:42,600 Speaker 2: Senor Don Gatto. Then this person pointed us to something 244 00:13:42,640 --> 00:13:47,440 Speaker 2: from the Drive that was talking about a simulation where 245 00:13:48,640 --> 00:13:53,760 Speaker 2: drone wingmen turned on their human pilot because according to 246 00:13:54,280 --> 00:13:58,920 Speaker 2: this story, the drones decided that in order to accomplish 247 00:13:59,000 --> 00:14:01,640 Speaker 2: their mission, they had to take out the human pilot. 248 00:14:03,520 --> 00:14:07,320 Speaker 2: But again, it's weird because according to the original person 249 00:14:08,240 --> 00:14:12,280 Speaker 2: whose words this article was based on has retracted what 250 00:14:12,320 --> 00:14:15,840 Speaker 2: they've said, and I guess said in the future. Oh no, 251 00:14:16,040 --> 00:14:19,600 Speaker 2: it was just a thought experiment. That whole thing like 252 00:14:19,760 --> 00:14:22,840 Speaker 2: that was real. Yeah, yeah, yeah, that's my fault. 253 00:14:24,200 --> 00:14:27,280 Speaker 4: Right, because you don't want to spook people on that. 254 00:14:27,520 --> 00:14:33,880 Speaker 3: Yeah, well, consciousness objectively is nothing more than a thought experiment, right, 255 00:14:34,800 --> 00:14:40,120 Speaker 3: That's so unhelpful. But uh but yeah, Noel, with fast 256 00:14:40,160 --> 00:14:45,760 Speaker 3: Mickey's comment here, which is scientifically accurate, there's sure no 257 00:14:45,840 --> 00:14:49,840 Speaker 3: getting around it. It's inarguable. What do you what do 258 00:14:49,880 --> 00:14:52,360 Speaker 3: you think, Matt as well, what what do you guys think? 259 00:14:52,480 --> 00:14:56,200 Speaker 3: Is this definitely going to roll out? I believe the 260 00:14:56,240 --> 00:14:59,400 Speaker 3: last time we talked about this, the big aim of 261 00:14:59,520 --> 00:15:04,040 Speaker 3: the a defense contractor creating this stuff was to get 262 00:15:04,040 --> 00:15:06,960 Speaker 3: a hold of the Congressional wallet. Do we think that's 263 00:15:07,000 --> 00:15:07,600 Speaker 3: gonna happen? 264 00:15:07,760 --> 00:15:10,680 Speaker 5: Oh well, usually seems. I mean it's definitely being touted 265 00:15:10,680 --> 00:15:14,280 Speaker 5: that way. What's the company Craytos You're right, yes, yeah, yeah, 266 00:15:14,360 --> 00:15:17,400 Speaker 5: I mean I think hence the marketing kind of materials. 267 00:15:17,600 --> 00:15:20,760 Speaker 5: It does feel like whatever new stuff like this. 268 00:15:20,800 --> 00:15:21,400 Speaker 4: I mean, it wasn't. 269 00:15:21,400 --> 00:15:24,560 Speaker 5: The news, Matt was that they tested it on an 270 00:15:24,560 --> 00:15:27,680 Speaker 5: airfield and then it was quote unquote successful. I believe 271 00:15:27,720 --> 00:15:30,000 Speaker 5: that's right, whether whether that was your story or there 272 00:15:30,080 --> 00:15:32,200 Speaker 5: or something that happened more recently. There was, like the 273 00:15:32,440 --> 00:15:34,480 Speaker 5: guys on that AI on AI podcast that I was 274 00:15:34,480 --> 00:15:37,280 Speaker 5: talking about, they mentioned there was a test at some 275 00:15:37,480 --> 00:15:43,680 Speaker 5: military facility that was categorized as a success, and you know, Cratos. 276 00:15:43,240 --> 00:15:44,760 Speaker 4: Is coming out and saying like, yeah, we did that. 277 00:15:44,760 --> 00:15:48,200 Speaker 5: That's us hoping to be perhaps in the era of 278 00:15:48,680 --> 00:15:50,440 Speaker 5: this type of thing, the next Lockheed. 279 00:15:50,600 --> 00:15:54,200 Speaker 2: You know, yeah, this is definitely military contractor one oh 280 00:15:54,240 --> 00:15:57,320 Speaker 2: one man put it out there and give the government 281 00:15:57,400 --> 00:16:00,600 Speaker 2: some real juicy to sink their teeth into them just 282 00:16:00,760 --> 00:16:03,440 Speaker 2: enough and be like, oh, look we tested our drones. 283 00:16:03,680 --> 00:16:07,120 Speaker 2: It seems to be working, but we need more funding. 284 00:16:08,920 --> 00:16:10,480 Speaker 5: And they always you can always tell them, they'll get 285 00:16:10,520 --> 00:16:12,240 Speaker 5: excited because their voices get really high pitched. 286 00:16:12,560 --> 00:16:14,560 Speaker 2: Yeah, yeah, yeah, yeah. 287 00:16:15,120 --> 00:16:17,880 Speaker 5: But it's it's it's true, and you know, there really 288 00:16:17,960 --> 00:16:19,360 Speaker 5: isn't a whole hell of a lot more to add 289 00:16:19,400 --> 00:16:23,160 Speaker 5: to it, other than I really do appreciate the idea 290 00:16:23,240 --> 00:16:25,480 Speaker 5: that I mentioned that those guys on the podcast said 291 00:16:25,960 --> 00:16:29,400 Speaker 5: that the algorithm or AI or machine learning or whatever, 292 00:16:29,840 --> 00:16:33,480 Speaker 5: it's so in vogue right now, but it is inherently 293 00:16:33,560 --> 00:16:35,360 Speaker 5: probably a bad. 294 00:16:35,160 --> 00:16:36,720 Speaker 4: Solution for a lot of things. 295 00:16:37,200 --> 00:16:40,480 Speaker 5: And yet I think there's blinders on, you know, an 296 00:16:40,600 --> 00:16:44,880 Speaker 5: entertainment in the military, in all sectors. It's the shiny 297 00:16:44,920 --> 00:16:48,480 Speaker 5: new thing, and if we're not careful, it's gonna bite 298 00:16:48,520 --> 00:16:50,720 Speaker 5: us in the ass or like blow up our houses. 299 00:16:51,120 --> 00:16:53,400 Speaker 2: And what you're talking about, I don't know what you 300 00:16:53,440 --> 00:16:55,560 Speaker 2: all they're talking about. Everything's going to happen in the 301 00:16:55,560 --> 00:16:56,920 Speaker 2: metaverse from now on. 302 00:16:57,040 --> 00:16:58,680 Speaker 4: That's what I know, all. 303 00:16:58,640 --> 00:17:03,680 Speaker 3: Right, Mark, Hey, what if this universe not necessarily our 304 00:17:03,720 --> 00:17:06,800 Speaker 3: own as we record this. What if this universe where 305 00:17:06,840 --> 00:17:10,920 Speaker 3: our fellow conspiracy realists are listening in. What if this 306 00:17:11,320 --> 00:17:14,320 Speaker 3: is just its own, unique, one off thing. What if 307 00:17:14,320 --> 00:17:18,040 Speaker 3: every universe is an n FT and the world, the 308 00:17:18,080 --> 00:17:20,199 Speaker 3: reality as we know It is just a series of 309 00:17:20,240 --> 00:17:24,840 Speaker 3: cascading n fts, just a series of bathing apes all 310 00:17:24,880 --> 00:17:25,400 Speaker 3: the way down. 311 00:17:25,800 --> 00:17:30,919 Speaker 2: You know what NFT stands for nice sing try Oh. 312 00:17:30,800 --> 00:17:34,440 Speaker 3: I was gonna say, no fun triceratops accurate. 313 00:17:34,520 --> 00:17:36,959 Speaker 5: It's a lot of fun, fun jokes that can make 314 00:17:37,000 --> 00:17:40,200 Speaker 5: with the one. Are people even still interested in n fts? 315 00:17:40,240 --> 00:17:42,320 Speaker 4: Then the bottom just drop out of that whole grift. 316 00:17:42,720 --> 00:17:48,240 Speaker 3: I think the people who put money into it are desperately. 317 00:17:49,600 --> 00:17:51,080 Speaker 4: By abs. 318 00:17:53,280 --> 00:17:56,080 Speaker 5: Yeah, go and crying about your cartoon, you know, while 319 00:17:56,080 --> 00:17:59,800 Speaker 5: we're getting blown up by sky robots and all that 320 00:18:00,160 --> 00:18:05,160 Speaker 5: note of joyous positivity. Let's take a break. First of all, 321 00:18:05,520 --> 00:18:11,080 Speaker 5: thanks again to Mattie fast Hands. That's you, Matt, but 322 00:18:11,240 --> 00:18:14,399 Speaker 5: also to fast Nickey. We're gonna take a break here, 323 00:18:14,400 --> 00:18:16,600 Speaker 5: a word from our sponsor, and then come back with 324 00:18:16,800 --> 00:18:17,879 Speaker 5: more messages from you. 325 00:18:24,640 --> 00:18:27,440 Speaker 3: And we have returned. We're going to take a spoonful 326 00:18:27,640 --> 00:18:31,160 Speaker 3: of sugar approach here. So we're going to talk about 327 00:18:31,280 --> 00:18:37,080 Speaker 3: something quite serious that likely affects many of us tuning 328 00:18:37,200 --> 00:18:40,080 Speaker 3: in this evening in one way or another. Whether or 329 00:18:40,119 --> 00:18:42,639 Speaker 3: not it's you directly, it may be someone you know. 330 00:18:43,520 --> 00:18:45,840 Speaker 3: Here's our letter. Oh, and then we'll follow it with 331 00:18:45,960 --> 00:18:50,199 Speaker 3: something hilarious from our friends very far down South our 332 00:18:50,240 --> 00:18:52,760 Speaker 3: first letter. Hi, my name is VI, and I was 333 00:18:52,800 --> 00:18:55,800 Speaker 3: wondering if you guys could possibly talk about the missing 334 00:18:56,000 --> 00:19:00,960 Speaker 3: generation of autism in women. How autism is commonly only 335 00:19:01,080 --> 00:19:05,520 Speaker 3: seen as a male issue until recently. I can't remember 336 00:19:05,640 --> 00:19:09,520 Speaker 3: the exact percentage, but I believed ninety percent of women 337 00:19:09,720 --> 00:19:14,560 Speaker 3: in the nineteen nineties never were properly diagnosed with autism 338 00:19:15,000 --> 00:19:19,160 Speaker 3: because it was only studied in boys. V continues, I'm 339 00:19:19,200 --> 00:19:21,840 Speaker 3: a twenty six year old Puerto Rican woman, and I 340 00:19:22,119 --> 00:19:26,040 Speaker 3: just realized I'm autistic. I spent my whole life wondering 341 00:19:26,200 --> 00:19:30,960 Speaker 3: why I felt so alien compared to other people. It's 342 00:19:31,040 --> 00:19:34,840 Speaker 3: bittersweet realizing this. I started to realize it because I 343 00:19:34,920 --> 00:19:38,119 Speaker 3: see the traits of my children. I was selective mute 344 00:19:38,240 --> 00:19:41,719 Speaker 3: as a child and had no social skills. I had 345 00:19:41,760 --> 00:19:44,840 Speaker 3: to repeat kindergarten due to having to do play therapy 346 00:19:45,040 --> 00:19:49,680 Speaker 3: and speech therapy. But yet still they missed my diagnosis 347 00:19:50,040 --> 00:19:54,680 Speaker 3: simply because I'm a girl. I'm interested in your opinion 348 00:19:54,760 --> 00:19:58,879 Speaker 3: on this. Also, there's a theory that psychologists believe that 349 00:19:59,040 --> 00:20:05,160 Speaker 3: borderline person disorder or BPD is actually female presentation of autism. 350 00:20:05,520 --> 00:20:09,720 Speaker 3: That was misdiagnosed. Let me know your opinion first off, V, 351 00:20:09,880 --> 00:20:13,359 Speaker 3: I can assure you from experience that people who have 352 00:20:13,440 --> 00:20:16,680 Speaker 3: to repeat kindergarten can go on to live wonderful and 353 00:20:16,960 --> 00:20:21,840 Speaker 3: fulfilling lives. I'm speaking from firsthand experience. I didn't make it. 354 00:20:22,720 --> 00:20:25,320 Speaker 3: I didn't make it through kindergarten on my first run 355 00:20:25,400 --> 00:20:29,680 Speaker 3: through due to lack of social skills. What do you 356 00:20:29,720 --> 00:20:32,800 Speaker 3: guys think about that? I know autism and the autism 357 00:20:32,880 --> 00:20:35,800 Speaker 3: spectrum can be a very sensitive subject for people, and 358 00:20:35,920 --> 00:20:38,800 Speaker 3: something science is still trying to grock to get its 359 00:20:38,800 --> 00:20:39,359 Speaker 3: head around. 360 00:20:39,720 --> 00:20:42,800 Speaker 4: Remember that email we got the other week from a 361 00:20:42,880 --> 00:20:45,840 Speaker 4: lovely listener who told us about their son and their 362 00:20:45,880 --> 00:20:49,280 Speaker 4: public school experience and how they were neurodiversion but the 363 00:20:49,280 --> 00:20:52,720 Speaker 4: school didn't quite know how to categorize them, and then they. 364 00:20:52,440 --> 00:20:54,280 Speaker 5: Slapped them with some label that was sort of like 365 00:20:54,440 --> 00:20:56,479 Speaker 5: it's a thing, but we don't quite know, and then 366 00:20:56,600 --> 00:20:59,720 Speaker 5: that even eventually was replaced with another term. Forgive me 367 00:20:59,800 --> 00:21:04,160 Speaker 5: for from forgetting the exact terms, but the point is, yes, definitely, 368 00:21:04,240 --> 00:21:05,240 Speaker 5: I mean it's hard. 369 00:21:05,080 --> 00:21:09,040 Speaker 4: To pin down. Schools don't know what to do with it. 370 00:21:09,160 --> 00:21:12,399 Speaker 5: It seems like childhood psychology is something of a black 371 00:21:12,480 --> 00:21:15,320 Speaker 5: box in many cases, and a lot of you know, 372 00:21:15,480 --> 00:21:19,960 Speaker 5: cases of autism fly under the radar in whatever gender. 373 00:21:20,200 --> 00:21:22,080 Speaker 4: And it doesn't surprise me to. 374 00:21:22,520 --> 00:21:26,240 Speaker 5: Note that the idea of women being underdiagnosed to such 375 00:21:26,320 --> 00:21:28,399 Speaker 5: I wouldn't have thought maybe it's such an alarming degree, 376 00:21:29,920 --> 00:21:31,720 Speaker 5: but it does not surprise me. 377 00:21:32,400 --> 00:21:32,560 Speaker 3: You know. 378 00:21:32,800 --> 00:21:34,399 Speaker 4: It just seems like there's sort of. 379 00:21:34,400 --> 00:21:39,000 Speaker 5: A Grin and Barrett mentality, and it's difficult to really 380 00:21:39,160 --> 00:21:40,920 Speaker 5: understand the fallout from that. 381 00:21:41,359 --> 00:21:47,080 Speaker 2: I've never heard that concept that borderline personality disorder is 382 00:21:47,400 --> 00:21:52,240 Speaker 2: actually an autism diagnosis. I've never heard that at all ever, 383 00:21:52,720 --> 00:21:57,480 Speaker 2: not once, But it seems interesting. There's such a history 384 00:21:57,640 --> 00:22:01,760 Speaker 2: of misdiagnosing women in this country with things, or you know, 385 00:22:02,320 --> 00:22:07,280 Speaker 2: falsely diagnosing them with something that isn't real at all. So, yeah, 386 00:22:07,880 --> 00:22:11,639 Speaker 2: there's muddy waters here. I was looking at what is 387 00:22:11,720 --> 00:22:16,040 Speaker 2: this PubMed This is the National Library of Medicine something 388 00:22:16,080 --> 00:22:19,800 Speaker 2: in here and it's from February twenty twenty two. The 389 00:22:19,920 --> 00:22:22,360 Speaker 2: title of it is Finding the True Number of Females 390 00:22:22,440 --> 00:22:26,199 Speaker 2: with Autistic Spectrum Disorder by Estimating the biases and initial 391 00:22:26,320 --> 00:22:32,960 Speaker 2: recognition and Clinical Diagnosis by Robert mccrosson. Seems pretty legit. 392 00:22:34,240 --> 00:22:36,879 Speaker 3: The first thing you should know V is that you 393 00:22:37,160 --> 00:22:42,920 Speaker 3: are by no means isolated in this situation. There's quite 394 00:22:42,960 --> 00:22:46,119 Speaker 3: a bit of scholarship evaluating this, and there's there's a 395 00:22:46,400 --> 00:22:50,720 Speaker 3: really okay, clearly I'm a bit biased obviously, but there's 396 00:22:51,440 --> 00:22:55,480 Speaker 3: a great episode from our buddies Josh and Chuck over 397 00:22:55,680 --> 00:23:00,920 Speaker 3: at Stuff you Should Know about BPD orderline personality disorder. 398 00:23:02,080 --> 00:23:05,399 Speaker 3: The title is the worst disorder or not a disorder 399 00:23:05,600 --> 00:23:10,240 Speaker 3: at all. Highly recommend check that out for anybody wondering 400 00:23:10,520 --> 00:23:15,880 Speaker 3: what borderline personality disorder is. It is typically understood as 401 00:23:16,880 --> 00:23:20,520 Speaker 3: it's called a mental illness currently that severely impacts a 402 00:23:20,600 --> 00:23:27,920 Speaker 3: person's ability to manage their emotions. Shadows of medical mistakes 403 00:23:28,240 --> 00:23:33,480 Speaker 3: in the past, right, like the idea that hilarity or 404 00:23:33,640 --> 00:23:39,160 Speaker 3: being hilarious is one's ability to quote unquote not control 405 00:23:39,320 --> 00:23:46,679 Speaker 3: their emotions. It is thankfully acknowledged now that Western medicine 406 00:23:47,160 --> 00:23:54,240 Speaker 3: has done a terrible job addressing the concerns and the 407 00:23:54,359 --> 00:23:59,520 Speaker 3: health Basically, anybody who's not a certain demographic of dude, 408 00:24:00,040 --> 00:24:01,720 Speaker 3: you know what I mean. We all know the ugly 409 00:24:01,840 --> 00:24:04,960 Speaker 3: story of how guynecology became a thing. We all know 410 00:24:05,080 --> 00:24:08,440 Speaker 3: the ugly story of lobotomies. I assume, let us not 411 00:24:08,560 --> 00:24:14,600 Speaker 3: forget the human species is the same primate that beat 412 00:24:14,680 --> 00:24:16,960 Speaker 3: the shit out of the first guy who was like, hey, 413 00:24:17,080 --> 00:24:20,960 Speaker 3: maybe wash your hands, sam Olweiss. And he didn't even 414 00:24:21,000 --> 00:24:23,440 Speaker 3: say he didn't even ask everybody to wash their hands. 415 00:24:23,640 --> 00:24:27,040 Speaker 3: He asked surgeons to maybe wash their hands before they 416 00:24:27,119 --> 00:24:29,760 Speaker 3: put their hands inside of people. And they were like, 417 00:24:29,920 --> 00:24:33,480 Speaker 3: this guy's crazy, lock them up. You may be interested 418 00:24:33,520 --> 00:24:36,560 Speaker 3: to find Vee. I was certainly interested to see that. 419 00:24:37,040 --> 00:24:40,960 Speaker 3: To your point, Matt, there is a lot of newer 420 00:24:41,119 --> 00:24:45,800 Speaker 3: scholarship on this, and it does appear that for one 421 00:24:45,920 --> 00:24:49,240 Speaker 3: reason or another. Again, none of us are medical professionals. 422 00:24:49,680 --> 00:24:53,679 Speaker 3: For one reason or another, there has been an intense, 423 00:24:54,359 --> 00:25:02,480 Speaker 3: traceable and intergenerational tendency to miss diagon knows autism, spectrum 424 00:25:02,720 --> 00:25:08,880 Speaker 3: or neurodivergence in women and female identifying humans. And it's 425 00:25:08,880 --> 00:25:12,080 Speaker 3: a greedious because that affects people's lives, like Noll to 426 00:25:12,160 --> 00:25:16,520 Speaker 3: your point, to our excellent listener's point earlier a few 427 00:25:16,560 --> 00:25:21,680 Speaker 3: weeks ago regarding how a one size fits all education 428 00:25:21,920 --> 00:25:27,359 Speaker 3: system does not fit every growing mind, we see the 429 00:25:27,480 --> 00:25:32,159 Speaker 3: same thing here, you know, and I cannot help, but 430 00:25:32,840 --> 00:25:35,280 Speaker 3: knowing just a little bit of history we do know. 431 00:25:35,560 --> 00:25:39,480 Speaker 3: I cannot help but imagine there were a ton of 432 00:25:40,160 --> 00:25:44,679 Speaker 3: innocent people, but the best of intentions, who were unjustly 433 00:25:44,840 --> 00:25:49,440 Speaker 3: told that they were quote unquote acting crazy. Right, and 434 00:25:50,240 --> 00:25:53,720 Speaker 3: it's a gregious it continues. I found some statistics I 435 00:25:53,800 --> 00:25:57,600 Speaker 3: want to shout out the Gersh Autism Center. In March 436 00:25:58,119 --> 00:26:01,879 Speaker 3: of this year, March fifteenth, they had a They had 437 00:26:01,920 --> 00:26:07,679 Speaker 3: a grate and sobering collection of statistics. They say the following. 438 00:26:07,720 --> 00:26:10,760 Speaker 3: I'll just read the quote quote. Since autism was first 439 00:26:10,840 --> 00:26:14,040 Speaker 3: identified in the nineteen forties, boys have been more commonly 440 00:26:14,200 --> 00:26:17,840 Speaker 3: diagnosed than girls. The ratio of males to females with 441 00:26:18,000 --> 00:26:22,600 Speaker 3: autism is generally quoted as four to one, meaning four 442 00:26:22,720 --> 00:26:27,080 Speaker 3: dudes to one do debt, though it is believed the 443 00:26:27,160 --> 00:26:31,080 Speaker 3: true ratio is lower. One research group estimates the actual 444 00:26:31,200 --> 00:26:34,360 Speaker 3: male to female ratio appears to be three to four. 445 00:26:35,080 --> 00:26:39,439 Speaker 3: Flipping the direction, another study found that, get this, eighty 446 00:26:39,600 --> 00:26:45,640 Speaker 3: percent of females remain undiagnosed at age eighteen comma, which 447 00:26:45,680 --> 00:26:49,639 Speaker 3: has serious consequences for their mental health. I mean, I 448 00:26:49,760 --> 00:26:55,920 Speaker 3: know it's not quite a conspiracy. There is hopefully not 449 00:26:56,160 --> 00:27:01,520 Speaker 3: some sort of creepy cabal of Monty Byrne esque scientists, 450 00:27:01,760 --> 00:27:05,680 Speaker 3: you know, steepling their fingers and saying, yes, let's just 451 00:27:05,920 --> 00:27:07,480 Speaker 3: Ruin and Beeble's lives. 452 00:27:07,800 --> 00:27:11,119 Speaker 5: But yeah, but you evoked that image often and I 453 00:27:11,200 --> 00:27:12,760 Speaker 5: appreciate it, so it's always in my head. But I 454 00:27:12,880 --> 00:27:15,160 Speaker 5: swear to God, do you think that's what Elon Musk 455 00:27:15,320 --> 00:27:17,760 Speaker 5: is going for in his photo ops? Because there are 456 00:27:17,960 --> 00:27:21,680 Speaker 5: multiple images of him with his fingers steepled and a 457 00:27:21,720 --> 00:27:24,640 Speaker 5: grumpy look on his face, like like as though he's 458 00:27:24,680 --> 00:27:26,000 Speaker 5: plotting the world's destruction. 459 00:27:26,400 --> 00:27:30,040 Speaker 3: I'm not sure. Maybe it's just again, we recently did 460 00:27:30,080 --> 00:27:33,760 Speaker 3: this thing about billionaires. They live in rarefied air man. 461 00:27:34,440 --> 00:27:38,399 Speaker 3: They do have typically armies of people controlling how their 462 00:27:38,480 --> 00:27:41,760 Speaker 3: public image is presented. So there is a non zero 463 00:27:42,080 --> 00:27:46,440 Speaker 3: chance that those images you're seeing have been greenlit by 464 00:27:46,560 --> 00:27:49,280 Speaker 3: that guy. So maybe that's the way he wants to present. 465 00:27:49,320 --> 00:27:53,919 Speaker 5: That's kind of my thinking as well. Yeah, I don't know, man. 466 00:27:54,000 --> 00:27:56,960 Speaker 5: They don't have a whole lot to add to this one. 467 00:27:57,280 --> 00:27:59,439 Speaker 3: Well, I would like to add some more stuff if 468 00:27:59,480 --> 00:28:02,719 Speaker 3: we go back further, if we go to psychology today, 469 00:28:03,880 --> 00:28:07,720 Speaker 3: I want to shout out Robert T. Muller, PhD, who 470 00:28:08,000 --> 00:28:12,560 Speaker 3: is bringing some more facts to bear about this, this 471 00:28:12,760 --> 00:28:17,879 Speaker 3: danger of misdiagnosis. Doctor Mueller says forty two percent of 472 00:28:18,040 --> 00:28:23,680 Speaker 3: women and girls with autism received at least one misdiagnosis 473 00:28:24,480 --> 00:28:30,399 Speaker 3: before they were correctly diagnosed. And this professor is arguing 474 00:28:30,720 --> 00:28:35,359 Speaker 3: that there's not a clear reason for this misdiagnosis to occur. 475 00:28:36,840 --> 00:28:40,040 Speaker 3: But this, and again there's a sticky subject. This may 476 00:28:40,080 --> 00:28:45,120 Speaker 3: be controversial. This person is arguing that there may be 477 00:28:45,440 --> 00:28:51,520 Speaker 3: some social behavior, some camouflaging or as it's also known, masking, 478 00:28:52,320 --> 00:28:56,880 Speaker 3: that may play a role in this. And this stuff 479 00:28:57,080 --> 00:29:04,280 Speaker 3: does have consequences. There is a ripple effect. We want 480 00:29:04,360 --> 00:29:08,080 Speaker 3: to hear from everybody else if this again, if this 481 00:29:08,160 --> 00:29:10,760 Speaker 3: applies to you, we want to hear about your experiences 482 00:29:11,280 --> 00:29:18,840 Speaker 3: with misdiagnosis, your thoughts on neurodivergence. It's something that society 483 00:29:19,200 --> 00:29:23,720 Speaker 3: is getting its head around together, and it's going to 484 00:29:23,840 --> 00:29:28,040 Speaker 3: take time. It's going to take time and honesty. It's 485 00:29:28,120 --> 00:29:31,560 Speaker 3: probably going to include, let's just be candid here, it's 486 00:29:31,600 --> 00:29:35,560 Speaker 3: going to include some difficult conversations that maybe not everybody 487 00:29:35,920 --> 00:29:40,000 Speaker 3: would like to have, and we want, we welcome you 488 00:29:40,200 --> 00:29:42,520 Speaker 3: to be a part of that. As you know, hopefully 489 00:29:43,080 --> 00:29:45,600 Speaker 3: if you're hearing this. We have your back and we 490 00:29:45,760 --> 00:29:49,400 Speaker 3: want to hear from you. Now. That is a serious thing, 491 00:29:49,960 --> 00:29:52,840 Speaker 3: but we promised you a spoonful of sugar with that. 492 00:29:53,920 --> 00:29:56,680 Speaker 3: Before we go to our next ad break. Here is 493 00:29:56,960 --> 00:30:01,560 Speaker 3: a complaint Matt nol doc Holiday codenamed dot Holiday. We 494 00:30:01,840 --> 00:30:07,120 Speaker 3: got a complaint and a while back, I cannot remember 495 00:30:07,200 --> 00:30:11,760 Speaker 3: how long ago. A while back, we made an offhand 496 00:30:12,120 --> 00:30:15,720 Speaker 3: reference to something called mad lips. 497 00:30:16,320 --> 00:30:17,720 Speaker 4: We all know what mad lips. 498 00:30:17,440 --> 00:30:20,360 Speaker 5: Are, yeah, I mean, I guess I just mainly remember 499 00:30:20,400 --> 00:30:22,479 Speaker 5: it from like road trips and stuff of the kind 500 00:30:22,480 --> 00:30:25,640 Speaker 5: of things they'd sell it, like gas stations or you know, 501 00:30:26,840 --> 00:30:29,240 Speaker 5: the cracker barrel. But I guess people in other country 502 00:30:29,240 --> 00:30:31,120 Speaker 5: probably don't know what the cracker barrel is either. I 503 00:30:31,200 --> 00:30:32,920 Speaker 5: guess that's a pretty American thing. 504 00:30:32,960 --> 00:30:34,360 Speaker 4: But it's just where you fill in the blanks and 505 00:30:34,440 --> 00:30:37,720 Speaker 4: make silly stories, right, Like I can't even do it, 506 00:30:37,840 --> 00:30:44,040 Speaker 4: Banana and my goose all the way to the grocery face, 507 00:30:44,360 --> 00:30:45,440 Speaker 4: you know, right? 508 00:30:46,000 --> 00:30:50,320 Speaker 3: Yeah, yeah, I recently finished listening to your highpot news 509 00:30:50,840 --> 00:30:54,680 Speaker 3: regarding meta tarsals, and I have to admit I'm a 510 00:30:54,720 --> 00:30:59,120 Speaker 3: little perclemped that you didn't fart symphonically, right, like that. 511 00:30:59,360 --> 00:31:02,800 Speaker 3: That would be any phrase in there that sounds weird 512 00:31:03,000 --> 00:31:05,040 Speaker 3: is a blank in the sentence that you write. 513 00:31:05,520 --> 00:31:08,000 Speaker 4: So I'm just supposed to put a certain part of. 514 00:31:08,080 --> 00:31:09,920 Speaker 3: Speech right now at you. 515 00:31:10,760 --> 00:31:11,480 Speaker 5: Yeah, yeah, yeah. 516 00:31:11,480 --> 00:31:13,680 Speaker 4: They'll help you out, they'll help you out. There are 517 00:31:13,800 --> 00:31:16,320 Speaker 4: some guide rails. 518 00:31:16,560 --> 00:31:19,280 Speaker 5: So's it's educational kind of right to that end. Isn't 519 00:31:19,280 --> 00:31:21,480 Speaker 5: it so meant to be to teach you about parts 520 00:31:21,520 --> 00:31:21,960 Speaker 5: of Smooch? 521 00:31:22,440 --> 00:31:26,800 Speaker 3: It's the more wholesome, more educational predecessor to the famous 522 00:31:26,880 --> 00:31:32,440 Speaker 3: grassroots card game Cards against Humanity. So our fellow conspiracy 523 00:31:32,520 --> 00:31:35,320 Speaker 3: realist Savory writes in and says the following, I think 524 00:31:35,360 --> 00:31:38,000 Speaker 3: you guys need to realize that people from all around 525 00:31:38,040 --> 00:31:42,520 Speaker 3: the world listen to a podcast, not just Americans. I 526 00:31:42,720 --> 00:31:45,280 Speaker 3: needed you to explain what mad libs were to me 527 00:31:45,520 --> 00:31:49,120 Speaker 3: because I didn't have a freaking clue. Don't make assumptions, 528 00:31:49,640 --> 00:31:53,160 Speaker 3: makes an arts out of you and me. That just 529 00:31:53,240 --> 00:31:57,200 Speaker 3: made my day because first off, it's true, and then 530 00:31:57,440 --> 00:32:01,280 Speaker 3: second this might be fun. Guys got me thinking what 531 00:32:01,440 --> 00:32:06,080 Speaker 3: are other versions or equivalents of mad lips? Like, do 532 00:32:06,160 --> 00:32:09,680 Speaker 3: you guys know of any of other games that might 533 00:32:09,760 --> 00:32:13,200 Speaker 3: be really familiar to Australians or people in India that 534 00:32:13,320 --> 00:32:14,719 Speaker 3: aren't familiar other places. 535 00:32:14,960 --> 00:32:18,880 Speaker 5: Cards against Humanity is very popular like everywhere, right, I 536 00:32:18,960 --> 00:32:22,880 Speaker 5: assume that one's got crossover appeal. But again, these kinds 537 00:32:22,880 --> 00:32:26,400 Speaker 5: of emails do make me question my like do I 538 00:32:26,520 --> 00:32:29,000 Speaker 5: have a US centric view? I like to think not, 539 00:32:29,240 --> 00:32:32,560 Speaker 5: but the bubble you never know, man, Like have people 540 00:32:32,680 --> 00:32:35,640 Speaker 5: in Australia heard of Cards Against Humanity? I would assume yes, 541 00:32:36,080 --> 00:32:38,560 Speaker 5: if they sell it like at you know, big box 542 00:32:38,640 --> 00:32:41,800 Speaker 5: stores and stuff. But mad libs aren't really a thing anymore. 543 00:32:41,880 --> 00:32:44,120 Speaker 5: I guess they're like they're. 544 00:32:43,960 --> 00:32:46,920 Speaker 3: Like old magazines. I would put them on magazine. 545 00:32:46,560 --> 00:32:50,200 Speaker 4: Level, like, yeah, what what's that one called highlights? 546 00:32:50,560 --> 00:32:50,760 Speaker 5: You know? 547 00:32:52,000 --> 00:32:55,000 Speaker 2: In Canada? I think they're called wacky blanks. 548 00:32:57,320 --> 00:33:01,440 Speaker 4: You have a whole I believe. 549 00:33:03,000 --> 00:33:06,880 Speaker 3: Happy but like magazines like Reader's Digest, which is common 550 00:33:07,000 --> 00:33:10,440 Speaker 3: to us, like common knowledge to a certain demographic of 551 00:33:10,640 --> 00:33:13,920 Speaker 3: the US or a certain generation. But if you went 552 00:33:14,040 --> 00:33:17,120 Speaker 3: on TikTok and said, hey, do you remember Reader's Digest, 553 00:33:17,160 --> 00:33:19,880 Speaker 3: A lot of people wouldn't know it. I do think 554 00:33:19,880 --> 00:33:23,240 Speaker 3: it was an assumption to have that throwaway joke about 555 00:33:23,280 --> 00:33:26,080 Speaker 3: mad libs. And I just wanted to end this part 556 00:33:26,120 --> 00:33:29,840 Speaker 3: of our weekly Listener mail segment by thinking savory, because 557 00:33:29,880 --> 00:33:33,320 Speaker 3: there was an assumption, and people do need to strive 558 00:33:34,200 --> 00:33:38,760 Speaker 3: to get outside of their bubbles of assumption. Some bubbles 559 00:33:39,320 --> 00:33:42,920 Speaker 3: bubble assumptions. It's there somewhere, that portmanteau is out there. 560 00:33:43,160 --> 00:33:43,760 Speaker 4: Oh, it's there. 561 00:33:44,440 --> 00:33:49,240 Speaker 5: I just found a website called wordlibs are actually WordFinder 562 00:33:49,480 --> 00:33:52,280 Speaker 5: dot com, and it's a madlibs generator. 563 00:33:52,360 --> 00:33:55,440 Speaker 3: So give me a color, any color, char truths. 564 00:33:55,560 --> 00:33:56,640 Speaker 4: Sharks, I even spell that. 565 00:33:56,720 --> 00:33:56,840 Speaker 2: Ben. 566 00:33:56,920 --> 00:33:59,160 Speaker 4: Of course you would pick a color that I can't smell. 567 00:34:00,480 --> 00:34:03,760 Speaker 4: Uh blue, fair enough. I can probably figure it out. 568 00:34:04,240 --> 00:34:08,399 Speaker 5: I'll have an adjective, please please hit the random wobbly great, 569 00:34:08,560 --> 00:34:11,000 Speaker 5: I love it, wobbly time. 570 00:34:11,080 --> 00:34:14,440 Speaker 4: I'll give you a time. I'll say noon. Another adjectives. 571 00:34:14,520 --> 00:34:19,359 Speaker 4: Let's just go crazy and say farty and have a place. 572 00:34:19,440 --> 00:34:23,760 Speaker 4: What you got give me a place? I need a place. Bhutan, okay, bhutan. Baby. 573 00:34:24,719 --> 00:34:25,880 Speaker 4: Now we've got a food. 574 00:34:26,040 --> 00:34:28,760 Speaker 5: I'm gonna go with banana because I already said that earlier. 575 00:34:28,960 --> 00:34:33,280 Speaker 5: Another food, y'all, any food will do. Red fish, red fish, 576 00:34:34,080 --> 00:34:36,800 Speaker 5: got it, the deliciousest of fish. 577 00:34:37,000 --> 00:34:38,360 Speaker 4: All right. Now we need a verb. 578 00:34:39,000 --> 00:34:40,480 Speaker 3: You know this is going on for a while. 579 00:34:40,719 --> 00:34:41,560 Speaker 4: It's almost a. 580 00:34:43,280 --> 00:34:43,600 Speaker 5: Sentence. 581 00:34:43,680 --> 00:34:47,560 Speaker 4: I mean maddens were whole stories. Sometimes this is pretty reasonable, 582 00:34:47,640 --> 00:34:48,520 Speaker 4: and I need a verb. 583 00:34:48,800 --> 00:34:49,399 Speaker 3: Oh uh. 584 00:34:50,960 --> 00:34:56,120 Speaker 4: Jump jump, Okay, a noun, let's just go with uh. 585 00:34:56,640 --> 00:35:00,359 Speaker 4: A hot dog. A hot dog is a noun. It's food, 586 00:35:00,440 --> 00:35:02,800 Speaker 4: but it's also now and a number. How about the 587 00:35:02,880 --> 00:35:03,879 Speaker 4: old number of the beast? 588 00:35:04,000 --> 00:35:04,200 Speaker 3: Y'all? 589 00:35:04,280 --> 00:35:09,320 Speaker 5: Y'all co with that, six one hundred and sixty six. 590 00:35:10,120 --> 00:35:14,000 Speaker 5: Go mad Bats are so cool. They are blue, wobbly 591 00:35:14,080 --> 00:35:16,839 Speaker 5: animals which have wings. They like to fly around at noon, 592 00:35:16,880 --> 00:35:19,680 Speaker 5: which makes some people scared of them. But bats are 593 00:35:19,800 --> 00:35:22,440 Speaker 5: farty and they don't want to hurt people. I have 594 00:35:22,560 --> 00:35:25,560 Speaker 5: a bet bat that lives in Bhutad. I like defeeding 595 00:35:25,600 --> 00:35:26,719 Speaker 5: banana and redfish. 596 00:35:26,800 --> 00:35:27,480 Speaker 4: He likes to jump. 597 00:35:27,520 --> 00:35:30,000 Speaker 5: I am his favorite person, but he also likes hot dog. 598 00:35:31,360 --> 00:35:33,560 Speaker 5: I want to convince my parents to get me six 599 00:35:33,680 --> 00:35:37,680 Speaker 5: hundred and sixty six more bats. See that's what a mad. 600 00:35:37,560 --> 00:35:39,200 Speaker 4: Live is, y'all. And it's funny. 601 00:35:39,880 --> 00:35:43,200 Speaker 3: It's silly and funny, and it's something you can play 602 00:35:43,239 --> 00:35:47,600 Speaker 3: along with at home. It'd be fun too to crowdsource 603 00:35:47,760 --> 00:35:50,719 Speaker 3: mad Live. If there was a way to get all 604 00:35:50,960 --> 00:35:54,960 Speaker 3: our fellow conspiracy realists to do that, it would it 605 00:35:55,000 --> 00:35:58,600 Speaker 3: would be like a when oh gosh, what was that country? 606 00:35:59,040 --> 00:36:01,960 Speaker 3: Was it the United King that ask people to suggest 607 00:36:02,040 --> 00:36:05,239 Speaker 3: a name for a new boat and the number one 608 00:36:05,320 --> 00:36:07,120 Speaker 3: answer was body mcboat. 609 00:36:06,840 --> 00:36:09,239 Speaker 4: Body mcbot face, Yeah, body mcbo face. 610 00:36:09,320 --> 00:36:10,160 Speaker 3: Good note, good note. 611 00:36:10,239 --> 00:36:14,239 Speaker 5: And I gotta say, since this listener male came from Australia, 612 00:36:14,520 --> 00:36:17,120 Speaker 5: I know Australia and New Zealand aren't the same, but 613 00:36:17,239 --> 00:36:19,040 Speaker 5: you both kind of call bat's bits. 614 00:36:19,880 --> 00:36:20,560 Speaker 4: Just put that out there. 615 00:36:20,840 --> 00:36:21,840 Speaker 3: We can beats. 616 00:36:22,280 --> 00:36:24,719 Speaker 5: Yeah, it would be fun if a New Zealander or 617 00:36:24,880 --> 00:36:27,640 Speaker 5: an Aussie read this particular mad lab. 618 00:36:28,200 --> 00:36:31,719 Speaker 4: I will not even attempt to do so, but that 619 00:36:31,920 --> 00:36:32,279 Speaker 4: was fun. 620 00:36:32,640 --> 00:36:35,680 Speaker 3: I think it would be even more fun, Savory and 621 00:36:36,080 --> 00:36:38,319 Speaker 3: any of our friends, don Andre. I think it would 622 00:36:38,320 --> 00:36:40,920 Speaker 3: be more fun if you just wrote to us with 623 00:36:41,200 --> 00:36:45,720 Speaker 3: a list of things like verb, noun, description, et cetera, 624 00:36:46,080 --> 00:36:48,600 Speaker 3: have us feed it to you blind black box it. 625 00:36:49,520 --> 00:36:52,959 Speaker 3: Then tell us what the states ended up being. Because again, 626 00:36:53,080 --> 00:36:55,759 Speaker 3: you are the most important part of this show. We're 627 00:36:55,840 --> 00:36:58,360 Speaker 3: gonna pause for a word from our sponsor. Thank you 628 00:36:58,440 --> 00:37:02,640 Speaker 3: to v Thank you too, Savory. We want to hear 629 00:37:02,760 --> 00:37:05,239 Speaker 3: responses of course. One A three three st d w 630 00:37:05,480 --> 00:37:08,480 Speaker 3: y t K conspiracydiheartradio dot com. We're gonna have a 631 00:37:08,520 --> 00:37:18,120 Speaker 3: word from our sponsor, will be right back, and we 632 00:37:18,239 --> 00:37:21,440 Speaker 3: have returned with a bit of a plot twist. We 633 00:37:21,560 --> 00:37:26,120 Speaker 3: were going to examine an amazing piece of correspondence regarding 634 00:37:26,600 --> 00:37:28,840 Speaker 3: the Exorcist files. We got a lot of response from that. 635 00:37:29,520 --> 00:37:32,560 Speaker 3: One in particular that we all loved was from Moshe 636 00:37:33,120 --> 00:37:36,080 Speaker 3: who reached out to us and I don't know you all, 637 00:37:36,719 --> 00:37:39,680 Speaker 3: maybe it's because of what we were about to talk 638 00:37:39,719 --> 00:37:43,720 Speaker 3: about that we had to save this for another evening. 639 00:37:44,120 --> 00:37:46,840 Speaker 4: Ghost in the Machine. Ghost in the Machine. 640 00:37:47,239 --> 00:37:52,239 Speaker 5: Yeah, well that's a good tease, Matt. I know you 641 00:37:52,320 --> 00:37:54,239 Speaker 5: were exalent talking about this, but you're unfortunately having some 642 00:37:54,960 --> 00:37:58,239 Speaker 5: some computery issues that will be resolved in the very 643 00:37:58,320 --> 00:38:00,480 Speaker 5: near term. But we didn't want to leave you out 644 00:38:00,480 --> 00:38:02,440 Speaker 5: of this conversation, especially since it was your you know, 645 00:38:02,600 --> 00:38:03,720 Speaker 5: your pick for today. 646 00:38:03,880 --> 00:38:04,040 Speaker 3: Yeah. 647 00:38:04,080 --> 00:38:07,360 Speaker 2: I've got my twenty thirteen Mac currently sitting on a 648 00:38:07,480 --> 00:38:10,399 Speaker 2: couple of ice packs trying to cool it down because 649 00:38:10,440 --> 00:38:13,040 Speaker 2: it's overheating and it won't allow me to record. We've 650 00:38:13,120 --> 00:38:16,240 Speaker 2: literally had to stop like twenty times while we're recording 651 00:38:16,320 --> 00:38:19,560 Speaker 2: this because my dumb machine. That's my fault of letting 652 00:38:19,600 --> 00:38:21,400 Speaker 2: it live this long. I should have put it down 653 00:38:21,520 --> 00:38:21,919 Speaker 2: years ago. 654 00:38:23,800 --> 00:38:28,319 Speaker 4: I have fault you for that. A robot overlords will 655 00:38:28,520 --> 00:38:30,920 Speaker 4: likely spare you or there at least make you a 656 00:38:31,000 --> 00:38:33,359 Speaker 4: hand servant of some sort of awesome man. 657 00:38:33,440 --> 00:38:35,240 Speaker 3: You're one of my absolute favorites. 658 00:38:35,440 --> 00:38:38,759 Speaker 2: We got this from Mosha, you know, and we picked 659 00:38:38,800 --> 00:38:40,560 Speaker 2: out as soon as it came in because it's just 660 00:38:40,640 --> 00:38:44,040 Speaker 2: a fascinating concept. I think we've talked about just the 661 00:38:44,120 --> 00:38:47,920 Speaker 2: idea that exorcisms occur in other religions. It's not just 662 00:38:48,040 --> 00:38:52,040 Speaker 2: the Catholic Church that has the lock on exercising demons 663 00:38:52,120 --> 00:38:55,759 Speaker 2: and other types of like nefarious creatures that are not human. 664 00:38:56,320 --> 00:38:58,640 Speaker 2: Uh So we will get into this. Maybe we'll read 665 00:38:58,680 --> 00:39:01,120 Speaker 2: it next week and hope flee my computer can come 666 00:39:01,160 --> 00:39:01,640 Speaker 2: in by then. 667 00:39:02,200 --> 00:39:06,560 Speaker 5: Thankfully your computer lived a long and illustrious life like 668 00:39:06,600 --> 00:39:10,480 Speaker 5: alliteration back in the mad Libs world in my head. 669 00:39:10,600 --> 00:39:13,600 Speaker 5: But I'm ten years old, ten years old, Happy birthday, 670 00:39:13,680 --> 00:39:14,560 Speaker 5: Happy death day. 671 00:39:14,760 --> 00:39:16,320 Speaker 4: I'm a pasture for you, laptop. 672 00:39:16,600 --> 00:39:18,759 Speaker 5: But now I feel like we did it proud with 673 00:39:18,880 --> 00:39:21,920 Speaker 5: today's conversation that it did manage to record, and why 674 00:39:22,320 --> 00:39:25,239 Speaker 5: tempt fate. Let's just let's just wrap it up and 675 00:39:25,360 --> 00:39:27,080 Speaker 5: bring this one back for a future episode. 676 00:39:27,080 --> 00:39:29,920 Speaker 3: Of listener now, So thank you of course the v 677 00:39:30,360 --> 00:39:33,880 Speaker 3: Thank you to Savory, Thank you to Fast Mickey. I 678 00:39:34,360 --> 00:39:37,880 Speaker 3: love your name, Mick Mickey, thank you to Musha, and 679 00:39:38,040 --> 00:39:41,000 Speaker 3: thank you to everyone who has written in all these things. 680 00:39:41,040 --> 00:39:43,319 Speaker 3: We cannot wait to hear from you folks. Find us 681 00:39:43,360 --> 00:39:46,800 Speaker 3: on Instagram, find us on TikTok, find us on conspiracy stuff. 682 00:39:47,200 --> 00:39:50,400 Speaker 3: You know the drill by this time, long time listeners. 683 00:39:51,080 --> 00:39:52,920 Speaker 3: If you don't like any of that slow jazz, you 684 00:39:53,000 --> 00:39:56,040 Speaker 3: can always give us a call on your telephonic device. 685 00:39:56,440 --> 00:39:59,560 Speaker 5: Sorry, one eight three three STDWTK is the number to call. 686 00:40:00,080 --> 00:40:02,120 Speaker 5: Leave us a message of the sound of Ben's dull 687 00:40:02,200 --> 00:40:05,560 Speaker 5: sitch tones. You've got three minutes to tell your tale. 688 00:40:06,160 --> 00:40:08,200 Speaker 5: Let us know what to call you, preferably not your 689 00:40:08,280 --> 00:40:10,680 Speaker 5: real name, unless you want to that's fine too. Just 690 00:40:10,760 --> 00:40:12,640 Speaker 5: make sure you let us know and we will call 691 00:40:12,719 --> 00:40:15,200 Speaker 5: you that, and we will respect your anonymity. If that's 692 00:40:15,239 --> 00:40:18,040 Speaker 5: what you prefer as well, We'll do an anonymous We're 693 00:40:18,080 --> 00:40:20,680 Speaker 5: not scared. You might very well find yourself in the 694 00:40:20,719 --> 00:40:22,840 Speaker 5: company of some of the lovely folks that Ben shouted 695 00:40:22,880 --> 00:40:25,000 Speaker 5: out from today's episode. If you don't want to do 696 00:40:25,080 --> 00:40:26,880 Speaker 5: any of that and you want to reach out to 697 00:40:27,000 --> 00:40:29,800 Speaker 5: us using your hands and a keyboard. You can do 698 00:40:29,920 --> 00:40:31,720 Speaker 5: so by sending us a good old fashioned email. 699 00:40:31,800 --> 00:40:53,520 Speaker 2: We are conspiracy at iHeartRadio dot com. Stuff they don't 700 00:40:53,560 --> 00:40:56,440 Speaker 2: want you to know. Is a production of iHeartRadio. For 701 00:40:56,600 --> 00:41:00,680 Speaker 2: more podcasts from iHeartRadio, visit the iHeartRadio app podcasts, or 702 00:41:00,719 --> 00:41:02,480 Speaker 2: wherever you listen to your favorite shows.