1 00:00:00,880 --> 00:00:03,480 Speaker 1: Hey, everyone, it's me Joshuam. For this week's select I've 2 00:00:03,560 --> 00:00:08,680 Speaker 1: chosen our January twenty sixteen episode on futurology. It's one 3 00:00:08,680 --> 00:00:10,520 Speaker 1: of those topics that has a name that makes it 4 00:00:10,560 --> 00:00:13,240 Speaker 1: sound way cooler and far out than it actually is. 5 00:00:13,600 --> 00:00:16,799 Speaker 1: But happily we found that when you dig into it, 6 00:00:16,920 --> 00:00:20,680 Speaker 1: even the blandest parts of futurology are super interesting. Still, 7 00:00:21,200 --> 00:00:22,279 Speaker 1: I hope you like this one. 8 00:00:22,320 --> 00:00:33,880 Speaker 2: Guys, welcome to Stuff you Should Know, a production of iHeartRadio. 9 00:00:37,040 --> 00:00:39,600 Speaker 3: Hey, and welcome to the podcast. I'm Josh Clark. 10 00:00:39,640 --> 00:00:43,760 Speaker 1: There's Charles w Chuck Bryant and Jerry's here, and it's 11 00:00:43,800 --> 00:00:48,120 Speaker 1: stuff you should know from the future, but not really. 12 00:00:49,840 --> 00:00:54,840 Speaker 3: How you doing, I'm fine, Well, good, that's good. I 13 00:00:54,920 --> 00:00:57,120 Speaker 3: enjoyed this topic. I thought it was kind of neat. Yeah, 14 00:00:57,200 --> 00:00:59,360 Speaker 3: it was. It was funny. 15 00:01:00,000 --> 00:01:06,400 Speaker 1: When you're reading about futurology and futurelogists aka futurists, you 16 00:01:06,840 --> 00:01:10,399 Speaker 1: tend to want to make it like more than it 17 00:01:10,480 --> 00:01:13,319 Speaker 1: actually is, and when you look into the topic it 18 00:01:13,400 --> 00:01:15,760 Speaker 1: keeps having to be beaten down just because of the 19 00:01:15,840 --> 00:01:16,360 Speaker 1: name alone. 20 00:01:16,480 --> 00:01:18,880 Speaker 3: Yeah, you sound like a little bit like a wackad 21 00:01:18,920 --> 00:01:21,679 Speaker 3: do A whack could do, say you're a futurist, a seer. 22 00:01:21,959 --> 00:01:25,679 Speaker 1: Yeah, and you know, sometimes they're thinking about they're using 23 00:01:25,760 --> 00:01:32,120 Speaker 1: these these really neat techniques to predict the future. They're 24 00:01:32,120 --> 00:01:37,280 Speaker 1: talking about some really mundane stuff, Yeah, boring stuff, economic forecasts, 25 00:01:37,319 --> 00:01:39,840 Speaker 1: things like that, how much oil will be left in 26 00:01:39,920 --> 00:01:41,840 Speaker 1: thirty years, that kind of thing. But then on the 27 00:01:41,920 --> 00:01:44,280 Speaker 1: other hand, if you're a futurerologist, you may also be 28 00:01:44,360 --> 00:01:47,440 Speaker 1: tasked with figuring out what technology we're going to be 29 00:01:47,560 --> 00:01:52,800 Speaker 1: using in thirty years, or you know, what color the 30 00:01:52,840 --> 00:01:55,000 Speaker 1: shiny jumpsuits we're all going to wear will be. 31 00:01:55,160 --> 00:01:57,280 Speaker 3: That kind of stuff. Yeah. I think one of my 32 00:01:57,280 --> 00:02:02,320 Speaker 3: favorite things is to look at past future predictions. Yeah, 33 00:02:02,320 --> 00:02:05,840 Speaker 3: it's fun. Yeah, there's nothing that'll make someone look less 34 00:02:06,280 --> 00:02:09,919 Speaker 3: knowledgeable than going back to what they thought the future 35 00:02:09,919 --> 00:02:12,160 Speaker 3: would look like in the year two thousand, right, like 36 00:02:12,200 --> 00:02:15,200 Speaker 3: back in the nineteen thirties or forties or sometimes some 37 00:02:15,240 --> 00:02:18,359 Speaker 3: of those things happen. Yeah, and then it's amazing. Yeah, 38 00:02:18,480 --> 00:02:21,040 Speaker 3: that's like wow, you know, because something to this. 39 00:02:21,240 --> 00:02:24,160 Speaker 1: These guys are like really really dead on. And I 40 00:02:24,200 --> 00:02:27,160 Speaker 1: was reading an article I think it was in Harvard 41 00:02:27,240 --> 00:02:31,480 Speaker 1: Business Review, and it was a post by Paul Sappho, 42 00:02:32,320 --> 00:02:37,320 Speaker 1: who runs a venture capital firm I believe called discern. Yeah, 43 00:02:37,480 --> 00:02:41,440 Speaker 1: and Paul Sefa was saying like he was trying to 44 00:02:41,600 --> 00:02:50,600 Speaker 1: get across that sci fi authors and future ologists their 45 00:02:50,760 --> 00:02:54,680 Speaker 1: paths overlap quite a bit, but really there's pretty big distinctions. 46 00:02:54,720 --> 00:02:57,800 Speaker 1: And even in this article they got lumped in together. Yeah, 47 00:02:57,880 --> 00:03:03,799 Speaker 1: because sci fi writers do definitely use futurology techniques. But 48 00:03:04,000 --> 00:03:07,000 Speaker 1: Paul Cefo was saying like, yeah, but a real futureologist 49 00:03:07,280 --> 00:03:08,360 Speaker 1: you have to use logic. 50 00:03:09,560 --> 00:03:10,519 Speaker 3: If you're a sci fi. 51 00:03:10,400 --> 00:03:12,320 Speaker 1: Writer, you can just use your imagination, you don't have 52 00:03:12,360 --> 00:03:14,680 Speaker 1: to back it up with anything. Yes, you're a creature ologist. 53 00:03:14,760 --> 00:03:17,840 Speaker 1: You have to use logic that makes sense to whoever's 54 00:03:18,440 --> 00:03:19,400 Speaker 1: hearing your prediction. 55 00:03:19,760 --> 00:03:22,320 Speaker 3: Yeah, And I think that's one reason why some sci 56 00:03:22,360 --> 00:03:26,680 Speaker 3: fi writers have been right on the nose with some 57 00:03:26,800 --> 00:03:32,000 Speaker 3: future predictions, because they're not hampered by logic and they 58 00:03:32,000 --> 00:03:36,840 Speaker 3: can just free form, you know. Yeah, but then it's 59 00:03:36,880 --> 00:03:39,200 Speaker 3: just a lucky guess. No, I don't think so. I 60 00:03:39,240 --> 00:03:41,600 Speaker 3: think they're still applying a lot of the same rules 61 00:03:41,640 --> 00:03:46,000 Speaker 3: of future ology. Yeah, but they're just not bound by 62 00:03:46,680 --> 00:03:50,600 Speaker 3: you know, the laws of well not the laws, but 63 00:03:50,840 --> 00:03:54,360 Speaker 3: you know, the laws of logic. Yeah, exactly. I'm with you. 64 00:03:54,560 --> 00:03:56,760 Speaker 1: But that's the best science fiction though, I think, is 65 00:03:57,360 --> 00:04:02,600 Speaker 1: something that logically makes sense. Yeah, because then it's just fantasy. Yeah, 66 00:04:02,640 --> 00:04:03,080 Speaker 1: that's true. 67 00:04:03,680 --> 00:04:12,200 Speaker 3: So futurology is recognizing and assessing potential future events. I 68 00:04:12,240 --> 00:04:14,400 Speaker 3: could have sworn Jonathan Strickland wrote this, by the way, 69 00:04:14,400 --> 00:04:17,720 Speaker 3: it ready, but it was not. No, it's very Strickland esk. 70 00:04:18,000 --> 00:04:22,400 Speaker 3: Nicholas Gerbis. Yeah, that's Strickland's alter ego. I wonder if 71 00:04:22,440 --> 00:04:26,680 Speaker 3: it is. I've never met this, Nicholas Gerbis. But the 72 00:04:26,760 --> 00:04:28,880 Speaker 3: point Gerbus makes, which I think is good as it's 73 00:04:29,160 --> 00:04:31,880 Speaker 3: a product of our times in many cases, like depending 74 00:04:31,880 --> 00:04:36,599 Speaker 3: on where we are as a society, and like he 75 00:04:36,680 --> 00:04:39,039 Speaker 3: makes a great point. During the Civil War there probably 76 00:04:39,080 --> 00:04:41,400 Speaker 3: weren't a lot of like rosy predictions for the future 77 00:04:41,600 --> 00:04:44,480 Speaker 3: American Civil War, sure, but in the Gilded Age people 78 00:04:44,480 --> 00:04:48,480 Speaker 3: a lot more optimistic, optimistic, so they may have you know, 79 00:04:48,520 --> 00:04:50,640 Speaker 3: it's a whole different deal like during the Cold War, 80 00:04:50,839 --> 00:04:54,880 Speaker 3: for instance, right, a lot of paranoia, a lot of cynicism. 81 00:04:54,920 --> 00:04:58,560 Speaker 3: Probably not going to be a rosy outlook for the future, right, 82 00:04:58,760 --> 00:05:01,640 Speaker 3: like during the Gilded Age when it was rosier. Yeah, 83 00:05:01,680 --> 00:05:03,280 Speaker 3: way more optimistic than the Cold. 84 00:05:03,040 --> 00:05:06,080 Speaker 1: War, which is kind of ironic because the Gilded Age 85 00:05:06,120 --> 00:05:09,400 Speaker 1: didn't have anything to be optimistic about. They were just pretending, 86 00:05:09,600 --> 00:05:15,320 Speaker 1: hence the name. Yeah, the thing is what you've just said, though, 87 00:05:15,400 --> 00:05:19,400 Speaker 1: is is kind of an argument against futurology because one 88 00:05:19,440 --> 00:05:21,560 Speaker 1: of the big critiques of it is that a futureologist, 89 00:05:22,000 --> 00:05:25,040 Speaker 1: they're not doing anything. Even if you're commenting on the 90 00:05:25,080 --> 00:05:29,960 Speaker 1: past or the future, you're still really commenting about your present, 91 00:05:30,160 --> 00:05:32,799 Speaker 1: your contemporary time, because that's what you. 92 00:05:32,839 --> 00:05:33,640 Speaker 3: Or recent past. 93 00:05:33,839 --> 00:05:37,400 Speaker 1: Sure, yeah, that's what you what you've lived through and experienced. 94 00:05:37,720 --> 00:05:42,920 Speaker 1: That's all you can really reflect on. And futurology seeks 95 00:05:42,960 --> 00:05:43,960 Speaker 1: to go beyond that. 96 00:05:44,600 --> 00:05:46,520 Speaker 3: Well, yeah, that makes sense. So if you like, look 97 00:05:46,560 --> 00:05:49,679 Speaker 3: at this thing that is happening now or just happened, 98 00:05:50,240 --> 00:05:52,960 Speaker 3: then what is going to be happening in that thing 99 00:05:53,120 --> 00:05:56,839 Speaker 3: in ten years? And it's a lot of times based 100 00:05:56,880 --> 00:06:00,600 Speaker 3: on how the direction it's currently going. Yes, okay, so. 101 00:06:02,080 --> 00:06:04,440 Speaker 1: Gerbis makes a pretty good It gives you a good 102 00:06:04,440 --> 00:06:07,760 Speaker 1: example that the cell phone grew out of the telegraph, 103 00:06:08,160 --> 00:06:11,240 Speaker 1: which ultimately is related further. 104 00:06:10,960 --> 00:06:12,320 Speaker 3: Back to the smoke signal. 105 00:06:12,920 --> 00:06:15,560 Speaker 1: Sure, right, yeah, but if you were a future all 106 00:06:15,680 --> 00:06:18,360 Speaker 1: just hanging out around somebody who was sending smoke signals. 107 00:06:19,279 --> 00:06:22,600 Speaker 3: Would you be able to predict the cell phone? Probably 108 00:06:22,640 --> 00:06:26,919 Speaker 3: not or not? Could you predict the impact of the 109 00:06:26,920 --> 00:06:31,599 Speaker 3: automobile or the highway system? Right? Maybe? But would you 110 00:06:31,600 --> 00:06:35,560 Speaker 3: predict that people would have sex in the back seat 111 00:06:35,600 --> 00:06:38,600 Speaker 3: of a car because it provides a little well, I 112 00:06:38,640 --> 00:06:41,880 Speaker 3: don't think they did. Or urban sprawl? Yeah? Could you 113 00:06:41,880 --> 00:06:47,040 Speaker 3: predict exurbs and edge cities just because the highways got built? 114 00:06:47,120 --> 00:06:48,680 Speaker 1: Yeah, and not a lot of people did, even though 115 00:06:48,720 --> 00:06:51,440 Speaker 1: a lot of people said there's going to be horseless 116 00:06:51,440 --> 00:06:54,520 Speaker 1: carriages one day, and it's going they're going to change 117 00:06:54,560 --> 00:06:56,479 Speaker 1: things big time. People are going to be able to 118 00:06:56,480 --> 00:06:59,479 Speaker 1: move around a lot more. Yeah, But that doesn't mean 119 00:06:59,480 --> 00:07:04,159 Speaker 1: that everybody saw every result of the automobile. It was 120 00:07:04,160 --> 00:07:09,320 Speaker 1: a game changer, yeah, is what you could agreed. So 121 00:07:10,360 --> 00:07:12,240 Speaker 1: what we're saying here, And if it sounds a little 122 00:07:12,280 --> 00:07:16,320 Speaker 1: weird that we're at once supporting and criticizing futurology, that's 123 00:07:16,360 --> 00:07:19,280 Speaker 1: basically the fun thing to do when you talk about 124 00:07:19,280 --> 00:07:24,200 Speaker 1: futurology is to criticize it and be awed by it 125 00:07:24,280 --> 00:07:27,400 Speaker 1: because a lot of times they really are super right. 126 00:07:27,760 --> 00:07:32,600 Speaker 3: That's right. Futurology has been around for a long time. 127 00:07:33,560 --> 00:07:36,760 Speaker 3: I mean, since people were writing fiction, there were people 128 00:07:36,800 --> 00:07:42,920 Speaker 3: predicting the future, right, but as far as things didn't 129 00:07:42,960 --> 00:07:46,520 Speaker 3: really get going as far as being meaningful until after 130 00:07:46,760 --> 00:07:52,520 Speaker 3: World War Two, when the US started developing technological forecasting. Basically, 131 00:07:52,600 --> 00:07:55,800 Speaker 3: like it was really important to try and see where 132 00:07:55,840 --> 00:07:59,160 Speaker 3: things were going militarily, right, because it was super expensive 133 00:07:59,480 --> 00:08:02,920 Speaker 3: to develop new technologies. It could take a long time. 134 00:08:03,440 --> 00:08:05,960 Speaker 3: So they started thinking, hey, we need to get some 135 00:08:05,960 --> 00:08:09,200 Speaker 3: people on board that can kind of hopefully predict where 136 00:08:09,200 --> 00:08:11,000 Speaker 3: we're headed here so we can make the right decisions. 137 00:08:11,160 --> 00:08:13,160 Speaker 1: Yeah, because if it takes a really long time, like 138 00:08:13,200 --> 00:08:15,880 Speaker 1: you said, to develop a weapon, by the time you 139 00:08:15,960 --> 00:08:19,480 Speaker 1: have that weapon in deployed in the field, you're going 140 00:08:19,560 --> 00:08:22,640 Speaker 1: to need to know it's not already obsolete. The only 141 00:08:22,680 --> 00:08:25,000 Speaker 1: way to do that is to predict what kind of 142 00:08:25,000 --> 00:08:27,440 Speaker 1: warfare you're going to be engaged in. Because this is 143 00:08:27,480 --> 00:08:29,040 Speaker 1: a time like at the end of World War two, 144 00:08:29,320 --> 00:08:31,320 Speaker 1: so many inventions came out of World War one and 145 00:08:31,360 --> 00:08:35,000 Speaker 1: two war machine inventions that things were changing so quickly 146 00:08:35,280 --> 00:08:38,080 Speaker 1: that there was actually you can kind of put modern 147 00:08:38,320 --> 00:08:41,680 Speaker 1: futureology into the lap of one guy, an Air Force 148 00:08:41,760 --> 00:08:46,120 Speaker 1: general named hap Arnold, who saw that things were changing 149 00:08:46,160 --> 00:08:50,280 Speaker 1: so fast that his Air Force needed to basically predict 150 00:08:50,280 --> 00:08:52,520 Speaker 1: the future and see what direction it needed to go. 151 00:08:53,000 --> 00:08:55,080 Speaker 1: So he looked around and he started tapping people to 152 00:08:55,160 --> 00:08:57,040 Speaker 1: do that. One of the first people he tapped is 153 00:08:57,200 --> 00:09:02,280 Speaker 1: a scientist anautical engineer named Theodore von Carmon. 154 00:09:03,120 --> 00:09:05,880 Speaker 3: Yes, he was a super smart dude, and he led 155 00:09:05,920 --> 00:09:09,320 Speaker 3: a team that did predict a lot of stuff like 156 00:09:09,480 --> 00:09:13,640 Speaker 3: drones and as far as you know, the military using drones, 157 00:09:13,720 --> 00:09:17,000 Speaker 3: not your uncle who flies it around the neighborhood, just 158 00:09:17,000 --> 00:09:21,720 Speaker 3: a film stuff. He predicted the rise of Brookstone, target 159 00:09:21,720 --> 00:09:26,880 Speaker 3: seeking missiles, supersonic aircraft, and even the atom bomb. 160 00:09:27,160 --> 00:09:30,000 Speaker 1: All of this was in one report. Yeah, to hap 161 00:09:30,080 --> 00:09:33,120 Speaker 1: Arnold like, this is like and this guy knocked it 162 00:09:33,280 --> 00:09:36,760 Speaker 1: out of the park. But he and his group were 163 00:09:36,920 --> 00:09:40,520 Speaker 1: very much limited to small academic and military circles. Like 164 00:09:40,559 --> 00:09:42,840 Speaker 1: the general public wasn't aware that this was going on, 165 00:09:43,360 --> 00:09:49,360 Speaker 1: but his group. Von Carmon's group so accurately foresaw the 166 00:09:49,440 --> 00:09:54,960 Speaker 1: direction that modern warfare was going that you can also 167 00:09:55,200 --> 00:09:57,880 Speaker 1: very easily make the case that no, he basically created 168 00:09:57,880 --> 00:10:00,000 Speaker 1: a roadmap to the future that the Air Force follows. 169 00:10:00,480 --> 00:10:04,240 Speaker 1: So is his prophecies were self fulfilling? Yeah, because he 170 00:10:04,320 --> 00:10:07,280 Speaker 1: said go this way, and the Air Force went that way, yeah, 171 00:10:07,320 --> 00:10:08,800 Speaker 1: and created all this stuff. 172 00:10:09,080 --> 00:10:15,160 Speaker 3: Yeah, and then the military and well, the Brand Corporation specifically, 173 00:10:15,520 --> 00:10:17,880 Speaker 3: it grew out of the US Air Force and Douglas Aircraft. 174 00:10:17,920 --> 00:10:21,240 Speaker 3: In the mid forties. They said, well, having one person 175 00:10:21,360 --> 00:10:24,080 Speaker 3: to say these things is great, but what we need 176 00:10:24,160 --> 00:10:27,959 Speaker 3: is a team and a consensus among this team. So 177 00:10:28,040 --> 00:10:30,839 Speaker 3: they kind of, well, not kind of. They very much 178 00:10:31,200 --> 00:10:35,720 Speaker 3: patented a technique they called the Delphi technique d E. 179 00:10:35,840 --> 00:10:39,440 Speaker 3: L Phi, and that is basically a technique where they're 180 00:10:39,440 --> 00:10:43,720 Speaker 3: trying to get agreed on consensus from a number of people. 181 00:10:44,040 --> 00:10:50,080 Speaker 1: So there's this very famous story about how the Navy, 182 00:10:50,120 --> 00:10:53,360 Speaker 1: I think lost a submarine, a nuclear submarine, or the 183 00:10:53,440 --> 00:10:55,559 Speaker 1: Russians had lost a submarine something like that. There was 184 00:10:55,600 --> 00:10:58,600 Speaker 1: a loss sub that they wanted to find and they 185 00:10:58,640 --> 00:11:01,880 Speaker 1: had no idea where it was. So the Navy polled 186 00:11:02,240 --> 00:11:06,600 Speaker 1: all these different different experts and all these different fields 187 00:11:06,600 --> 00:11:13,280 Speaker 1: that might have something to do with nuclear submarines, whether aeronautics, 188 00:11:14,280 --> 00:11:17,880 Speaker 1: people from Noah, all these people right, and ask them 189 00:11:18,040 --> 00:11:20,640 Speaker 1: where do you think the sub is? And no one 190 00:11:21,080 --> 00:11:24,360 Speaker 1: hit it on the nose. But why when they basically 191 00:11:24,520 --> 00:11:30,840 Speaker 1: used statistical distribution of these various opinions guesses of professionals. 192 00:11:31,200 --> 00:11:34,440 Speaker 1: It led them right to that sub And that's what 193 00:11:34,480 --> 00:11:38,400 Speaker 1: the Delphi technique does too. It takes opinions of experts 194 00:11:38,400 --> 00:11:40,880 Speaker 1: in various fields and says, what do you think of this? 195 00:11:41,320 --> 00:11:45,120 Speaker 1: And everybody sends in a questionnaire and anonymously, and there's 196 00:11:45,160 --> 00:11:48,160 Speaker 1: no group meeting, so the group doesn't bow to pressure, 197 00:11:48,440 --> 00:11:52,400 Speaker 1: no leaders emerge. They're giving their unvarnished opinion. And then 198 00:11:52,520 --> 00:11:56,960 Speaker 1: after those opinions come in, they take that information and 199 00:11:57,040 --> 00:11:58,839 Speaker 1: send it out again. So it goes in rounds and 200 00:11:58,920 --> 00:12:02,320 Speaker 1: rounds and rounds until they finally come to a group 201 00:12:02,440 --> 00:12:05,559 Speaker 1: consensus that in the future, we're all going to be 202 00:12:05,600 --> 00:12:08,479 Speaker 1: wearing metallic blue jumpsuits. 203 00:12:08,720 --> 00:12:11,120 Speaker 3: Yeah. And what they're doing is generating what's known as 204 00:12:11,160 --> 00:12:15,839 Speaker 3: a scenario. And a guy named Herman Khan Kahn worked 205 00:12:15,840 --> 00:12:19,120 Speaker 3: with Rand in the nineteen fifties and he's the one 206 00:12:19,160 --> 00:12:21,800 Speaker 3: that kind of coined the term scenario as it applies 207 00:12:22,360 --> 00:12:26,400 Speaker 3: to futurology. A pretty good definition I found was a 208 00:12:26,520 --> 00:12:30,400 Speaker 3: scenario is a detailed portrait of a plausible future world, 209 00:12:30,960 --> 00:12:33,640 Speaker 3: one sufficiently vivid that a planner can clearly see and 210 00:12:33,679 --> 00:12:37,800 Speaker 3: comprehend the problems, challenges, and opportunities that such an environment 211 00:12:37,800 --> 00:12:43,880 Speaker 3: would present. So it's you know, it's saying, in the future, 212 00:12:43,920 --> 00:12:46,360 Speaker 3: we're going to have a scenario where there are going 213 00:12:46,400 --> 00:12:49,400 Speaker 3: to be robots in every house hold. Yeah. And one 214 00:12:49,440 --> 00:12:52,120 Speaker 3: of the biggest ways that they work on scenarios is 215 00:12:52,760 --> 00:12:55,959 Speaker 3: with something called back casting, which is starting at the end, 216 00:12:56,040 --> 00:12:58,400 Speaker 3: which is you got a robot in every house, and 217 00:12:58,440 --> 00:13:01,320 Speaker 3: then go backwards to how you got there? Yeah, how 218 00:13:01,320 --> 00:13:03,360 Speaker 3: you got there? Really? Yeah makes sense? 219 00:13:03,440 --> 00:13:06,160 Speaker 1: Yeah, and a scenario that's a pretty cool scenario. They 220 00:13:06,160 --> 00:13:09,760 Speaker 1: can also be as mundane as running a fire drill 221 00:13:10,679 --> 00:13:13,640 Speaker 1: where you're envisioning the fire broke out in the high 222 00:13:13,679 --> 00:13:16,920 Speaker 1: school gym, right, and so everybody needs to get out. 223 00:13:17,000 --> 00:13:19,679 Speaker 1: That's a that's a scenario. It's as simple as that. Yeah. There. 224 00:13:20,960 --> 00:13:24,320 Speaker 1: The weather forecasts are economic forecasts that are run through 225 00:13:24,360 --> 00:13:29,000 Speaker 1: computer algorithms. The computer algorithms, the model, the process that 226 00:13:29,040 --> 00:13:31,920 Speaker 1: it's going through is the scenario, and it spits out 227 00:13:31,960 --> 00:13:32,959 Speaker 1: a possible prediction. 228 00:13:33,040 --> 00:13:37,040 Speaker 3: It's almost like an effect then, cause right, yeah, you know, yeah, 229 00:13:37,080 --> 00:13:40,600 Speaker 3: excellently put thank you. So Herman Kahn worked with rand 230 00:13:40,640 --> 00:13:42,920 Speaker 3: and and he did you look him up at all? Oh? 231 00:13:43,000 --> 00:13:46,040 Speaker 1: Yeah, he's one of the inspirations for Doctor Strangelove. Yeah, 232 00:13:46,160 --> 00:13:48,480 Speaker 1: he was described as a super genius. 233 00:13:48,760 --> 00:13:51,600 Speaker 3: Yeah, he was super smart, and he he kind of 234 00:13:51,800 --> 00:13:53,480 Speaker 3: was a bit of a celebrity at the time. He 235 00:13:53,520 --> 00:13:57,640 Speaker 3: wrote a book in nineteen sixty one called on Thermonuclear 236 00:13:57,720 --> 00:14:00,720 Speaker 3: War and then went on to forum left ran to 237 00:14:00,760 --> 00:14:03,840 Speaker 3: from the Hudson Institute, where he basically was like, we're 238 00:14:03,880 --> 00:14:08,679 Speaker 3: a group that is going to forecast the future. So 239 00:14:08,920 --> 00:14:11,560 Speaker 3: he became it was like super popular book. Yeah, and 240 00:14:11,559 --> 00:14:14,040 Speaker 3: he spawned a lot of other books, similar books. 241 00:14:14,120 --> 00:14:16,800 Speaker 1: We need to take a break, but we're getting We'll 242 00:14:16,840 --> 00:14:34,760 Speaker 1: get right back to this in a second. So, Chuck, 243 00:14:34,800 --> 00:14:37,880 Speaker 1: you were just talking about Herman Kahn being the super 244 00:14:37,880 --> 00:14:40,640 Speaker 1: genius who is something of a celebrity. I read that 245 00:14:40,640 --> 00:14:43,840 Speaker 1: Timothy Leary animated that he had taken acid with him. 246 00:14:44,600 --> 00:14:45,160 Speaker 3: I believe it. 247 00:14:45,240 --> 00:14:48,240 Speaker 1: He was a part of the inspiration for Doctor Strange Love. 248 00:14:48,440 --> 00:14:53,520 Speaker 1: And this book that he wrote called the Year two 249 00:14:53,560 --> 00:14:57,040 Speaker 1: thousand a Framework for Speculation on the next thirty three years. 250 00:14:58,120 --> 00:15:04,080 Speaker 1: It basically established this outlook that America and capitalism could 251 00:15:04,120 --> 00:15:11,640 Speaker 1: do anything thanks to basically technological inventiveness. 252 00:15:12,000 --> 00:15:14,960 Speaker 3: Yeah, here's a let's hear some of these There was 253 00:15:15,000 --> 00:15:19,160 Speaker 3: a list in that book, one hundred technical innovations very 254 00:15:19,280 --> 00:15:22,440 Speaker 3: likely in the last third of the twentieth century, one 255 00:15:22,520 --> 00:15:28,760 Speaker 3: hundred some of the first ten multiple applications of lasers, boom, 256 00:15:30,320 --> 00:15:35,640 Speaker 3: high strength structural materials nailed it, wouldn't you think, Hellois 257 00:15:36,560 --> 00:15:41,920 Speaker 3: new or improved materials for equipment and appliances. That's easy. Yeah, 258 00:15:42,000 --> 00:15:42,680 Speaker 3: anyone can. 259 00:15:42,560 --> 00:15:44,920 Speaker 1: Say that, sure should be better material and predict that 260 00:15:45,040 --> 00:15:46,960 Speaker 1: now for twenty fifty. 261 00:15:48,680 --> 00:15:53,920 Speaker 3: Longer range, longer range weather forecasting, more reliable weather forecasting. 262 00:15:54,200 --> 00:15:55,640 Speaker 3: I don't know about that one. I think that was 263 00:15:55,640 --> 00:15:58,800 Speaker 3: a miss. How about this here here are a few 264 00:15:58,880 --> 00:16:03,440 Speaker 3: of the other ones. New techniques for cheap and reliable 265 00:16:03,480 --> 00:16:07,200 Speaker 3: birth control for sure. Yeah, the pill. I don't know 266 00:16:07,240 --> 00:16:10,440 Speaker 3: if the pill is around, we should do A whole 267 00:16:10,440 --> 00:16:12,160 Speaker 3: thing may have been the same year because it came 268 00:16:12,200 --> 00:16:13,560 Speaker 3: out in sixty seven, was it. 269 00:16:13,720 --> 00:16:17,360 Speaker 1: Yeah, well, this book came out in sixty seven, right, right? 270 00:16:17,680 --> 00:16:21,880 Speaker 3: A widespread use of nuclear reactors for power duh. Improved 271 00:16:21,920 --> 00:16:25,800 Speaker 3: capability to change sex of a children or adult gender reassignment, 272 00:16:25,880 --> 00:16:31,320 Speaker 3: Pervasive business use of computers. Yeah, they're all over. Personal pagers. Yeah, 273 00:16:31,400 --> 00:16:34,520 Speaker 3: they came and went, and then one of the other 274 00:16:34,520 --> 00:16:37,600 Speaker 3: ones was home computers to run households and communicate with 275 00:16:37,640 --> 00:16:39,960 Speaker 3: the outside world. Yeah, the Internet of Things. Yeah. 276 00:16:40,040 --> 00:16:43,480 Speaker 1: They also predicted the rise of the credit economy. Oh 277 00:16:43,560 --> 00:16:47,160 Speaker 1: really Yeah, that we currently are in interesting yeah. So, 278 00:16:47,640 --> 00:16:51,760 Speaker 1: and that was just like a list, like a sidebar basically, yeah, 279 00:16:51,760 --> 00:16:54,320 Speaker 1: in the book, in this book, but the whole idea 280 00:16:54,400 --> 00:16:58,200 Speaker 1: that America and capitalism in the West could invent its 281 00:16:58,240 --> 00:17:00,800 Speaker 1: way out of any problem. Will we possibly ran across 282 00:17:00,840 --> 00:17:04,560 Speaker 1: in the future was the premise or the position of 283 00:17:04,600 --> 00:17:10,200 Speaker 1: this book, and it caused an enormous furor in academic circles, 284 00:17:10,280 --> 00:17:13,640 Speaker 1: and not just academic circles, because this book was one 285 00:17:13,680 --> 00:17:15,640 Speaker 1: of the first to introduce to the public that there 286 00:17:15,640 --> 00:17:19,440 Speaker 1: were such things as think tanks like Randy and that 287 00:17:19,520 --> 00:17:22,160 Speaker 1: Club of Rome. Yeah, and that these people were sitting 288 00:17:22,200 --> 00:17:25,840 Speaker 1: there thinking about the future and we're writing books about it, 289 00:17:25,880 --> 00:17:28,159 Speaker 1: and it kind of became a hip thing. But the 290 00:17:28,160 --> 00:17:33,359 Speaker 1: Club of Rome was basically diametrically opposed to the outlook 291 00:17:33,520 --> 00:17:36,800 Speaker 1: that Herman Kahn had. And the Club of Rome was 292 00:17:36,840 --> 00:17:41,200 Speaker 1: a business consortium that conspiracy theorists say is basically the seat. 293 00:17:41,040 --> 00:17:42,080 Speaker 3: Of the new world order. 294 00:17:42,400 --> 00:17:45,960 Speaker 1: They're still around, they are, And the Club of Rome 295 00:17:46,000 --> 00:17:49,280 Speaker 1: basically said No, we are establishing the gloom and doom 296 00:17:49,359 --> 00:17:53,840 Speaker 1: camp that there's such thing as resource depletion overpopulation and 297 00:17:54,000 --> 00:17:55,240 Speaker 1: we are basically doomed. 298 00:17:55,800 --> 00:17:58,160 Speaker 3: Yeah. I mean we've covered this a lot on the show. 299 00:17:58,160 --> 00:18:01,000 Speaker 3: Different people that have made wild predictions about we're going 300 00:18:01,040 --> 00:18:03,920 Speaker 3: to run out of this by this year. Thomas Malthus, Yeah, 301 00:18:04,080 --> 00:18:06,879 Speaker 3: very Malthusian. One of the books that came out of 302 00:18:06,880 --> 00:18:09,560 Speaker 3: the Club of Rome in nineteen seventy two was called 303 00:18:09,560 --> 00:18:14,560 Speaker 3: Limits to Growth by Danella H. Meadows, Dennis Meadows, Jurgen Randers, 304 00:18:14,560 --> 00:18:18,120 Speaker 3: and William Barn's at MIT and they had a very 305 00:18:18,680 --> 00:18:23,320 Speaker 3: dire apocalyptic outlook of the future, as did a lot 306 00:18:23,320 --> 00:18:26,320 Speaker 3: of other people at the time, and a lot of 307 00:18:26,359 --> 00:18:30,280 Speaker 3: these were way off base. A lot of these dire predictions, right, 308 00:18:30,359 --> 00:18:32,879 Speaker 3: you know, which happened over and over again. Yeah, and so. 309 00:18:33,480 --> 00:18:37,000 Speaker 1: On the Club of Rome's website they defend the Limits 310 00:18:37,040 --> 00:18:40,760 Speaker 1: to Growth. No, not the Limits to Growth, the yeah, 311 00:18:40,800 --> 00:18:44,840 Speaker 1: the Limits to Growth book, basically saying that it's often 312 00:18:45,680 --> 00:18:50,960 Speaker 1: miscited as predicting the collapse of civilization due to renewable 313 00:18:51,000 --> 00:18:54,800 Speaker 1: resource over use, right, and it doesn't do that. But 314 00:18:54,880 --> 00:18:57,879 Speaker 1: they did use these same kind of techniques that Herman 315 00:18:57,960 --> 00:19:01,240 Speaker 1: Kahn and some of his other colleagues. We're coming up 316 00:19:01,240 --> 00:19:09,560 Speaker 1: with by by taking population information, food production data, industrial production, pollution, 317 00:19:09,680 --> 00:19:13,280 Speaker 1: and non renewable resource consumption and then running scenarios through 318 00:19:13,280 --> 00:19:17,399 Speaker 1: this model that they built using computers and coming up 319 00:19:17,440 --> 00:19:21,400 Speaker 1: with the scenarios they came up with were kind of grim. 320 00:19:21,720 --> 00:19:23,960 Speaker 1: The thing is is, even though they missed the mark, 321 00:19:24,480 --> 00:19:31,520 Speaker 1: they still helped establish a very young idea that you 322 00:19:31,560 --> 00:19:34,359 Speaker 1: can't just throw your McDonald's styrofoam on the ground, You 323 00:19:34,440 --> 00:19:38,040 Speaker 1: can't drive a car that gets two miles per gallon, like, 324 00:19:38,080 --> 00:19:42,760 Speaker 1: we can't live like everything is just forever abundant, that 325 00:19:42,760 --> 00:19:44,280 Speaker 1: there's no such thing as scarcity. 326 00:19:45,160 --> 00:19:47,680 Speaker 3: Yeah, it's a double edged sword though, Like I totally agree. 327 00:19:47,720 --> 00:19:50,080 Speaker 3: But then it also when you're wrong about these things, 328 00:19:50,520 --> 00:19:53,360 Speaker 3: it gives Cynex something to point to to say, well, see, 329 00:19:53,480 --> 00:19:55,919 Speaker 3: we didn't run out of oil in the early nineteen 330 00:19:56,000 --> 00:19:57,960 Speaker 3: eighties like you said we would, and we don't do 331 00:19:57,960 --> 00:19:59,080 Speaker 3: anything about it. Yeah. 332 00:19:59,160 --> 00:20:02,280 Speaker 1: I mean, man, that is a great point. It's a 333 00:20:02,359 --> 00:20:05,400 Speaker 1: very great point. But at the same time, what you're 334 00:20:05,400 --> 00:20:08,600 Speaker 1: seeing here between the limits to growth and the year 335 00:20:08,600 --> 00:20:14,160 Speaker 1: two thousand, we still see this today with climate change. 336 00:20:14,440 --> 00:20:17,560 Speaker 1: You know, it's like, let's do something about climate change. 337 00:20:17,640 --> 00:20:19,560 Speaker 1: The other people say, no, we can invent our way 338 00:20:19,600 --> 00:20:21,280 Speaker 1: out of it. And besides, if we do something about 339 00:20:21,280 --> 00:20:24,399 Speaker 1: climate change, it's going to mess with the economy. And 340 00:20:24,440 --> 00:20:27,160 Speaker 1: these people are saying, forget about the economy. We are 341 00:20:27,200 --> 00:20:27,840 Speaker 1: all going to. 342 00:20:27,800 --> 00:20:30,320 Speaker 3: Die, yeah, or not necessarily forget about the economy. But 343 00:20:30,320 --> 00:20:33,919 Speaker 3: maybe you can do both, right, you know, yeah, you know. 344 00:20:34,000 --> 00:20:36,320 Speaker 3: My whole deal with that has always been just like 345 00:20:36,840 --> 00:20:37,760 Speaker 3: why take that risk? 346 00:20:38,600 --> 00:20:41,520 Speaker 1: Well, who we humans aren't very good at like preparing 347 00:20:41,560 --> 00:20:44,119 Speaker 1: for future risk, which is I think one of the 348 00:20:44,119 --> 00:20:48,320 Speaker 1: reasons why future ologists are so revered and odd but 349 00:20:48,400 --> 00:20:51,920 Speaker 1: also mocked and scorned, because they're doing something that's almost 350 00:20:52,200 --> 00:20:55,119 Speaker 1: almost flies in the face of human nature. 351 00:20:55,200 --> 00:20:57,879 Speaker 3: Yeah, you're really putting yourself out there when you predict 352 00:20:57,920 --> 00:20:58,600 Speaker 3: some of this stuff. 353 00:21:00,200 --> 00:21:02,080 Speaker 1: One other episode that that just reminded me of the 354 00:21:02,119 --> 00:21:03,120 Speaker 1: ten thousand year clock. 355 00:21:03,200 --> 00:21:06,320 Speaker 3: Oh yeah, yeah, that was a great one. Yeah. So 356 00:21:07,160 --> 00:21:10,480 Speaker 3: the military, the United States military obviously has used it 357 00:21:10,520 --> 00:21:15,480 Speaker 3: for years. Then beginning when was this in the sixties 358 00:21:15,560 --> 00:21:17,879 Speaker 3: or seventies, that business got into it. 359 00:21:18,000 --> 00:21:21,320 Speaker 1: So in nineteen seventy two, I think Royal Dutch Shell 360 00:21:22,400 --> 00:21:24,800 Speaker 1: heard somebody at the top heard that there wasn't going 361 00:21:24,880 --> 00:21:27,240 Speaker 1: to be any oil in by nineteen eighty five, and 362 00:21:27,280 --> 00:21:28,840 Speaker 1: they went w Yeah. 363 00:21:28,960 --> 00:21:32,000 Speaker 3: Businesses basically said, wait a minute, there are people that 364 00:21:32,080 --> 00:21:36,280 Speaker 3: can actually use models to determine what the future might 365 00:21:36,320 --> 00:21:39,639 Speaker 3: look like, right, how can we use that to make money? Well, 366 00:21:39,680 --> 00:21:42,119 Speaker 3: let's throw money at them and find out exactly. 367 00:21:42,400 --> 00:21:46,800 Speaker 1: A couple of other places too that were nascent think 368 00:21:46,840 --> 00:21:50,840 Speaker 1: tanks like RAND was the Stanford Research Institute Futures Group 369 00:21:50,880 --> 00:21:55,919 Speaker 1: in the California Institute of Technology early like kind of 370 00:21:56,040 --> 00:22:01,320 Speaker 1: think tank breeding grounds of smart people walking around thinking 371 00:22:01,359 --> 00:22:01,960 Speaker 1: about the future. 372 00:22:02,160 --> 00:22:03,120 Speaker 3: But that wasn't enough. 373 00:22:03,760 --> 00:22:06,400 Speaker 1: You can't just say this is what I think it's 374 00:22:06,440 --> 00:22:08,840 Speaker 1: going to be like, you have to back it up 375 00:22:09,040 --> 00:22:10,560 Speaker 1: and we'll talk about how they back it up right 376 00:22:10,600 --> 00:22:23,080 Speaker 1: after this. 377 00:22:27,080 --> 00:22:27,919 Speaker 3: How do they back it up? 378 00:22:29,440 --> 00:22:32,040 Speaker 1: Well, they use different techniques. If you're a futurist or 379 00:22:32,080 --> 00:22:35,000 Speaker 1: a future ologist, you're going to be using techniques that 380 00:22:35,680 --> 00:22:38,560 Speaker 1: are pretty recognizable. But the way you put them together 381 00:22:39,000 --> 00:22:42,240 Speaker 1: and the things you sort out is what's going to 382 00:22:42,240 --> 00:22:45,199 Speaker 1: make you successful or not successful. Right, So you like 383 00:22:45,320 --> 00:22:46,760 Speaker 1: brainstorm ideas. 384 00:22:46,440 --> 00:22:48,879 Speaker 3: Yeah, that's probably where you start. Yeah, it's just like 385 00:22:49,160 --> 00:22:50,480 Speaker 3: blue Sky Territory as. 386 00:22:50,359 --> 00:22:55,080 Speaker 1: They say, yeah, you imagine things using scenarios or games, 387 00:22:55,200 --> 00:22:56,520 Speaker 1: apparently game theory. 388 00:22:56,640 --> 00:22:58,040 Speaker 3: But we got to do that at some point. 389 00:22:58,280 --> 00:23:01,760 Speaker 1: Yeah, I've been avoiding it cano so like we's a 390 00:23:01,800 --> 00:23:04,440 Speaker 1: mind bender. We could mess it up really bad, Yeah, 391 00:23:04,480 --> 00:23:11,200 Speaker 1: but we'll do it. That changed the futurism feel tremendously 392 00:23:11,320 --> 00:23:13,359 Speaker 1: when they came up with game theory, because it's a 393 00:23:13,400 --> 00:23:16,359 Speaker 1: pretty good way of predicting how people will work. And 394 00:23:16,400 --> 00:23:20,960 Speaker 1: that's one of the big confounding factors is you can 395 00:23:21,000 --> 00:23:23,520 Speaker 1: predict something, follow every single one of these steps that 396 00:23:23,520 --> 00:23:27,080 Speaker 1: we're talking about right now, and then people will just 397 00:23:27,720 --> 00:23:30,280 Speaker 1: cut to the left all of a sudden, and your 398 00:23:30,359 --> 00:23:33,879 Speaker 1: prediction just fell to the wayside because humanity went this 399 00:23:33,920 --> 00:23:34,600 Speaker 1: way real quick. 400 00:23:34,720 --> 00:23:38,480 Speaker 3: Yeah. Or somebody invented a game changer, a game changing 401 00:23:38,520 --> 00:23:42,160 Speaker 3: product or innovation, Yeah, that nobody saw coming. Yeah. What's 402 00:23:42,160 --> 00:23:46,160 Speaker 3: that called disruptive technology? Is it? Yeah? That's a good 403 00:23:46,280 --> 00:23:49,959 Speaker 3: I like that, not a bad band name. Oh, I 404 00:23:50,000 --> 00:23:50,960 Speaker 3: wonder if it's out there. 405 00:23:51,040 --> 00:23:54,320 Speaker 1: If so, it's made of like Silicon Valley rich guys. 406 00:23:54,359 --> 00:23:56,160 Speaker 3: Yeah, this is like my sideband. Right. 407 00:23:57,520 --> 00:24:00,760 Speaker 1: Do you want to gather professional opinions using say the 408 00:24:00,760 --> 00:24:05,479 Speaker 1: Delphi technique? Yeah, you want to do historical analysis current 409 00:24:05,520 --> 00:24:08,639 Speaker 1: trends are very huge and can help you as well. 410 00:24:09,000 --> 00:24:10,719 Speaker 1: And then like you were saying, I think you call 411 00:24:10,760 --> 00:24:12,080 Speaker 1: it back masking. 412 00:24:13,280 --> 00:24:19,919 Speaker 3: No, that's turn me on dead man right from the bets. 413 00:24:20,000 --> 00:24:21,880 Speaker 1: Yeah, that's what they do. They listen to the beatles 414 00:24:21,920 --> 00:24:27,000 Speaker 1: backwards where what it was it. It's not back masking, 415 00:24:27,040 --> 00:24:30,040 Speaker 1: I know, but where they where you envision the future 416 00:24:30,480 --> 00:24:33,720 Speaker 1: and then you work your way backward from it. When 417 00:24:33,720 --> 00:24:36,639 Speaker 1: you do this, you do all this stuff together and 418 00:24:36,760 --> 00:24:41,000 Speaker 1: again back casting, backcasting, and when you're when you're using 419 00:24:41,040 --> 00:24:44,600 Speaker 1: this along with computer algorithms that can model like the 420 00:24:44,680 --> 00:24:48,720 Speaker 1: economy or the weather, oil consumption or something like that, 421 00:24:49,160 --> 00:24:51,959 Speaker 1: you can come up with something that you could rightly 422 00:24:52,000 --> 00:24:55,119 Speaker 1: say is a prediction or a forecast for the future 423 00:24:55,280 --> 00:24:58,960 Speaker 1: where we're going to be. That's right again, though, just 424 00:24:59,119 --> 00:25:05,080 Speaker 1: things happen, Like for example, Herman Kahn did not predict 425 00:25:03,800 --> 00:25:08,480 Speaker 1: the oil crisis that came the year after he wrote 426 00:25:08,880 --> 00:25:13,200 Speaker 1: another famous book. Yeah, in nineteen seventy two, he wrote 427 00:25:13,359 --> 00:25:16,000 Speaker 1: a response, I think to limits the growth and just 428 00:25:16,080 --> 00:25:18,040 Speaker 1: totally missed the oil crisis. 429 00:25:18,119 --> 00:25:21,360 Speaker 3: Man. But how could he predict that? Because the oil crisis. 430 00:25:20,960 --> 00:25:24,160 Speaker 1: Came out of the OPEC oil embargo that was punishment 431 00:25:24,200 --> 00:25:26,960 Speaker 1: for the US's being involved in the Yam Kipper War. 432 00:25:27,400 --> 00:25:29,480 Speaker 3: So you couldn't see that coming. No, and that's the 433 00:25:29,560 --> 00:25:34,600 Speaker 3: big problem with futurology. Yes, exactly, our own US government 434 00:25:34,640 --> 00:25:37,679 Speaker 3: has been wrong. The US Department of Interior announced twice 435 00:25:37,760 --> 00:25:40,400 Speaker 3: in nineteen thirty nine and then in nineteen fifty one 436 00:25:40,840 --> 00:25:44,080 Speaker 3: that we only had thirteen years of oil left. Yeah, 437 00:25:44,400 --> 00:25:47,040 Speaker 3: so weird that both times it was thirteen years. 438 00:25:47,600 --> 00:25:49,639 Speaker 1: They don't like to bother people, so they wait until 439 00:25:49,640 --> 00:25:53,920 Speaker 1: there's thirteen years left, and they sound it's. 440 00:25:52,840 --> 00:25:54,080 Speaker 3: Just such a specific number. 441 00:25:54,160 --> 00:25:54,240 Speaker 2: It. 442 00:25:56,200 --> 00:25:58,919 Speaker 3: What else, Well, we've talked about Moore's law before. That 443 00:25:58,960 --> 00:26:03,320 Speaker 3: has aged a little better than some other futurology predictions 444 00:26:03,320 --> 00:26:07,840 Speaker 3: because it has been revised over the years, which is 445 00:26:07,920 --> 00:26:10,479 Speaker 3: sort of a cheat a little bit. But still, what 446 00:26:10,520 --> 00:26:11,719 Speaker 3: I really meant was this right. 447 00:26:12,359 --> 00:26:14,680 Speaker 1: I think he went from eighteen months to two years 448 00:26:14,760 --> 00:26:17,680 Speaker 1: or something like that. But what's funny is Gerbis stakes 449 00:26:17,680 --> 00:26:21,240 Speaker 1: his position in this article. He's saying, like the limits 450 00:26:21,280 --> 00:26:23,440 Speaker 1: to Growth and the other Club of Rome stuff, they 451 00:26:23,480 --> 00:26:28,840 Speaker 1: missed the mark because they predicted catastrophe, and Moore's law 452 00:26:29,480 --> 00:26:35,160 Speaker 1: predicts technological innovation, so it's successful. So yeah, clearly Gerbis 453 00:26:35,240 --> 00:26:38,680 Speaker 1: agrees with the Herman Khan group rather than the Club 454 00:26:38,680 --> 00:26:39,440 Speaker 1: of Rome group. 455 00:26:39,760 --> 00:26:40,639 Speaker 3: I don't think it's subtle. 456 00:26:40,720 --> 00:26:43,600 Speaker 1: I think you can't just say, like the Gloom and 457 00:26:43,640 --> 00:26:47,240 Speaker 1: Doom camp has just been completely eradicated or proven wrong. 458 00:26:47,359 --> 00:26:49,800 Speaker 3: Agreed, you know, yeah, Moore's law. I don't eve think 459 00:26:49,800 --> 00:26:53,439 Speaker 3: we said specifically. It predicts the number of transistors on 460 00:26:53,480 --> 00:26:57,160 Speaker 3: integrated circuits and computers doubles every two years, right, And 461 00:26:57,200 --> 00:26:59,640 Speaker 3: like we said, it's been updated and it's been pretty consistent. 462 00:27:00,280 --> 00:27:04,720 Speaker 1: And so with Herman Khan's popularity, and then the big 463 00:27:04,840 --> 00:27:11,199 Speaker 1: high profile book publishing argument that he got in with 464 00:27:11,240 --> 00:27:13,439 Speaker 1: the Club of Rome that led to like a spade 465 00:27:13,520 --> 00:27:15,240 Speaker 1: of other futureology books that I. 466 00:27:15,560 --> 00:27:17,600 Speaker 3: Remember it being a big deal when I was a kid. 467 00:27:17,600 --> 00:27:20,760 Speaker 3: I remember a lot of people talking about the near 468 00:27:20,840 --> 00:27:22,119 Speaker 3: and far future. 469 00:27:22,000 --> 00:27:24,199 Speaker 1: The one that I ran across in this article that 470 00:27:24,440 --> 00:27:27,400 Speaker 1: I had heard of, but I didn't know anything about Alvin. 471 00:27:27,119 --> 00:27:29,800 Speaker 3: Toffler's Future Shock. I remember that. 472 00:27:29,880 --> 00:27:32,760 Speaker 1: I think, did you read it? N The cover I 473 00:27:32,800 --> 00:27:35,760 Speaker 1: guarantee would just give you a nostalgia. I'm really but 474 00:27:35,840 --> 00:27:37,679 Speaker 1: it came out in nineteen seventy and it predicts a 475 00:27:37,720 --> 00:27:42,439 Speaker 1: future where too much rapid change technological change and advancement. 476 00:27:43,040 --> 00:27:46,199 Speaker 1: It happens too quickly, and people get all sorts of 477 00:27:46,359 --> 00:27:52,520 Speaker 1: stressed and just worn out and basically have all manner 478 00:27:52,560 --> 00:27:56,159 Speaker 1: of terrible reactions to it. And I'm like, oh, well, 479 00:27:56,560 --> 00:27:58,720 Speaker 1: I predicted twenty fifteen. 480 00:27:59,000 --> 00:28:02,120 Speaker 3: So like a person's emotions couldn't handle. 481 00:28:02,520 --> 00:28:07,320 Speaker 1: Yeah, we're just overwhelmed, okay, through too much rapid technological 482 00:28:07,320 --> 00:28:09,280 Speaker 1: innovation happens too quick. 483 00:28:09,400 --> 00:28:10,480 Speaker 3: Do you think we're overwhelmed? 484 00:28:11,000 --> 00:28:13,600 Speaker 1: Like I get stressed out by like say social media 485 00:28:13,760 --> 00:28:14,520 Speaker 1: or something like that. 486 00:28:14,600 --> 00:28:16,639 Speaker 3: Yeah. I wonder if it's like people of a certain 487 00:28:16,680 --> 00:28:18,640 Speaker 3: age maybe Yeah. 488 00:28:18,720 --> 00:28:20,600 Speaker 1: I would guess if you're born into it, you're used 489 00:28:20,600 --> 00:28:23,800 Speaker 1: to it, So it would probably more likely apply to 490 00:28:23,880 --> 00:28:26,800 Speaker 1: a transition population, like. 491 00:28:26,840 --> 00:28:30,080 Speaker 3: Right, a transitional generation? Is that what we are? Don't 492 00:28:30,080 --> 00:28:32,119 Speaker 3: you get stressed by social media? Don't you get like 493 00:28:32,280 --> 00:28:35,439 Speaker 3: just tense and uh yeah, I mean I kind of 494 00:28:35,480 --> 00:28:36,040 Speaker 3: just hate. 495 00:28:35,800 --> 00:28:39,800 Speaker 1: It or having like having information, all this information and 496 00:28:39,840 --> 00:28:43,920 Speaker 1: all of it's just so thin ye, content wise or 497 00:28:44,640 --> 00:28:47,920 Speaker 1: value wise, but there's tons of it. Yeah, and it's 498 00:28:47,960 --> 00:28:49,080 Speaker 1: always coming at you. 499 00:28:49,320 --> 00:28:51,960 Speaker 3: Ye. Always wears me out. It wears me out. I 500 00:28:52,000 --> 00:28:56,920 Speaker 3: got the future, shock, chuck, you got the Jimmy legs yeah, no, 501 00:28:57,040 --> 00:29:00,840 Speaker 3: I totally agree. I'm like that. I just want to 502 00:29:00,920 --> 00:29:07,480 Speaker 3: shut it all down, just sh everybody. Not podcasts though, right, yes, 503 00:29:08,480 --> 00:29:11,360 Speaker 3: that should live on. So we talked about science fiction 504 00:29:11,400 --> 00:29:14,960 Speaker 3: writers and how they are easily off the hook because 505 00:29:14,960 --> 00:29:17,360 Speaker 3: they're just writers, right, They're not supposed to predict the future, 506 00:29:18,400 --> 00:29:20,920 Speaker 3: but they have been. You can't dismiss it because they've 507 00:29:20,920 --> 00:29:23,080 Speaker 3: been on the money or close to it a lot 508 00:29:23,120 --> 00:29:25,200 Speaker 3: over the years. Yeah, because, like we said, they're not 509 00:29:25,240 --> 00:29:30,160 Speaker 3: hampered by the rational laws of today. They can just 510 00:29:30,240 --> 00:29:33,480 Speaker 3: say whatever they want and if they're wrong, it's like, hey, dude, 511 00:29:33,480 --> 00:29:37,480 Speaker 3: I'm just writing stuff. Yes, this is fiction, right, But 512 00:29:38,160 --> 00:29:42,360 Speaker 3: a few of the highlights. Jules Verne mid nineteenth century 513 00:29:42,400 --> 00:29:46,080 Speaker 3: predicted going to the Moon in a spacecraft. 514 00:29:46,360 --> 00:29:49,560 Speaker 1: Not only that, so he predicted it would be shot 515 00:29:49,600 --> 00:29:53,880 Speaker 1: out of a cannon basically yeah, but done. But the 516 00:29:53,960 --> 00:29:57,960 Speaker 1: thing that he really got though, was that he placed 517 00:29:58,320 --> 00:30:01,440 Speaker 1: the moon shot in Florida. Yeah, like one hundred and 518 00:30:01,480 --> 00:30:04,200 Speaker 1: thirty seven miles from Cape Canaveral, where they do launch 519 00:30:04,400 --> 00:30:06,640 Speaker 1: rockets to the Moon. Not bad now, and for the 520 00:30:06,640 --> 00:30:09,240 Speaker 1: same reason too, Like that was it's close to the equator. 521 00:30:10,280 --> 00:30:12,200 Speaker 3: Oh is that why? That's one of the reasons why. 522 00:30:12,640 --> 00:30:17,040 Speaker 1: Plus Cape Canaveral is largely protected by the Gulf Stream 523 00:30:17,400 --> 00:30:20,880 Speaker 1: from hurricanes. Like as a hurricane comes ashore right before 524 00:30:21,080 --> 00:30:23,760 Speaker 1: it starts to get to Canaveral, it goes. 525 00:30:23,600 --> 00:30:27,720 Speaker 3: Out again right and then hits North Carolina. Interesting that 526 00:30:27,840 --> 00:30:30,120 Speaker 3: that'd be an interesting conversation to have been in on 527 00:30:30,920 --> 00:30:32,920 Speaker 3: Like oh, when they were picking play, like where should 528 00:30:32,920 --> 00:30:35,040 Speaker 3: we launch this? I mean, where should we put all 529 00:30:35,080 --> 00:30:41,000 Speaker 3: of our money in? Right? HG. Wells He predicted tanks. Yeah, 530 00:30:41,040 --> 00:30:42,080 Speaker 3: he was here three. 531 00:30:42,200 --> 00:30:44,480 Speaker 1: Supposedly he was the first guy to really think of 532 00:30:44,560 --> 00:30:45,680 Speaker 1: himself as a futurist. 533 00:30:46,040 --> 00:30:48,360 Speaker 3: He predicted the Adam bomb in nineteen oh eight, aerial 534 00:30:48,360 --> 00:30:54,320 Speaker 3: bombing in nineteen oh eight. What The name robot was 535 00:30:54,360 --> 00:30:57,000 Speaker 3: actually coined by a science fiction writer, a check writer 536 00:30:57,160 --> 00:31:03,840 Speaker 3: named Carl Kopek. In nineteen twenty one, he named robots. 537 00:31:04,240 --> 00:31:08,920 Speaker 1: I think the all time winner, though, is Hugo Gernsbach. 538 00:31:09,080 --> 00:31:12,320 Speaker 1: And Hugo Gernsbach. If you're into science fiction, you recognize 539 00:31:12,360 --> 00:31:15,160 Speaker 1: his first name because he's who the Hugo Award is 540 00:31:15,200 --> 00:31:17,800 Speaker 1: named after. You may also recognize his last name too, 541 00:31:17,840 --> 00:31:21,640 Speaker 1: if you're a Hugo Gernsbach fan. But back in I 542 00:31:21,680 --> 00:31:23,479 Speaker 1: think the nineteen tens. 543 00:31:23,880 --> 00:31:24,760 Speaker 3: Yeah, he was rinning. 544 00:31:24,840 --> 00:31:26,920 Speaker 1: Yeah, he wrote a book called Ralph one two four 545 00:31:27,000 --> 00:31:31,600 Speaker 1: C forty one plus. He predicted everything in this. 546 00:31:32,360 --> 00:31:35,040 Speaker 3: Yeah you know what that means. It's actually a play 547 00:31:35,080 --> 00:31:41,120 Speaker 3: on words one two It means one two for C 548 00:31:41,560 --> 00:31:46,200 Speaker 3: for one another. You get it. Wow. Yeah, that's great. 549 00:31:46,240 --> 00:31:48,840 Speaker 3: One two four C for one and then another is 550 00:31:48,840 --> 00:31:51,920 Speaker 3: the plus sign. Yeah. Yeah that alone, I was sold. Yeah, 551 00:31:52,000 --> 00:31:53,120 Speaker 3: it's like, I love this guy. 552 00:31:53,280 --> 00:31:55,640 Speaker 1: It's just like that Van Halen album. OHU eight one 553 00:31:55,680 --> 00:31:57,520 Speaker 1: two exactly. 554 00:31:58,560 --> 00:32:01,240 Speaker 3: So what is he predicted? He predict did solar power, 555 00:32:01,480 --> 00:32:04,800 Speaker 3: like the realistic use of solar power? Uh huh. He 556 00:32:04,880 --> 00:32:11,560 Speaker 3: predicted plastics, video phones, tape recorders, jukeboxes, loud. 557 00:32:11,280 --> 00:32:18,120 Speaker 1: Speakers, tinfoil, rust, poof steel, synthetic fabrics, all in one book. 558 00:32:18,600 --> 00:32:21,160 Speaker 1: And he's famous in the Hugo Awards named after him 559 00:32:21,200 --> 00:32:24,800 Speaker 1: because he wanted to make science fiction more science based. 560 00:32:24,960 --> 00:32:28,000 Speaker 1: Yeah you know, I'm using that same logic. So he 561 00:32:28,040 --> 00:32:31,840 Speaker 1: would have been a very like almost a father of 562 00:32:31,920 --> 00:32:32,760 Speaker 1: future ology. 563 00:32:33,000 --> 00:32:35,440 Speaker 3: Oh yeah, for sure. You know, here's a few other 564 00:32:35,480 --> 00:32:39,640 Speaker 3: things from that book. This one, to me, I'm surprised 565 00:32:39,640 --> 00:32:42,560 Speaker 3: no one's done this yet. The appetizer, which is at 566 00:32:42,600 --> 00:32:46,600 Speaker 3: a restaurant in an advanced scientifically advanced restaurant will be 567 00:32:46,600 --> 00:32:48,760 Speaker 3: a room that you wait in before you get your 568 00:32:48,800 --> 00:32:52,000 Speaker 3: table that's flooded with gases that make you hungry. Oh yeah, 569 00:32:52,080 --> 00:32:55,560 Speaker 3: not bad. Yeah, just have a seat in the appetizer room, right, 570 00:32:55,720 --> 00:32:56,640 Speaker 3: we'll be ready shortly. 571 00:32:57,840 --> 00:33:00,800 Speaker 1: Just like bloody fingernails, a scratch send in the walls 572 00:33:00,800 --> 00:33:02,760 Speaker 1: as people are trying to get to the other room 573 00:33:02,800 --> 00:33:04,920 Speaker 1: where the food is. 574 00:33:04,080 --> 00:33:09,760 Speaker 3: The telautograph, which is basically a fax machine, the telefat 575 00:33:10,480 --> 00:33:14,800 Speaker 3: which was a picturephone, had a universal translator where they 576 00:33:14,840 --> 00:33:18,440 Speaker 3: translate any language right there in your hand. Yeah, not bad. 577 00:33:19,160 --> 00:33:24,440 Speaker 3: And then this one I love. The Vacation City was 578 00:33:24,560 --> 00:33:28,200 Speaker 3: a suspended city and a domed suspended city twenty thousand 579 00:33:28,200 --> 00:33:31,960 Speaker 3: feet in the air that used a device that nullified gravity. 580 00:33:32,040 --> 00:33:36,920 Speaker 3: And in vacation City, no mechanical devices are permitted because 581 00:33:36,960 --> 00:33:39,600 Speaker 3: it was supposed to be a true escape. That's awesome 582 00:33:39,600 --> 00:33:42,120 Speaker 3: from the mechanized world. Waiting for that one. And this 583 00:33:42,280 --> 00:33:45,239 Speaker 3: was in nineteen eleven. Yeah, he predicted just that there 584 00:33:45,240 --> 00:33:46,640 Speaker 3: would be a need for that. 585 00:33:46,640 --> 00:33:50,760 Speaker 1: That's like that town in West Virginia, Green something, West 586 00:33:50,800 --> 00:33:54,800 Speaker 1: Virginia where the people who have electromagnetic sensitivity. Go because 587 00:33:54,800 --> 00:33:57,800 Speaker 1: you're not allowed to have any electromagnetic stuff. Oh really, 588 00:33:57,880 --> 00:34:00,400 Speaker 1: because there's like a radio telescope whe there's something there 589 00:34:01,560 --> 00:34:02,479 Speaker 1: could be interfered with. 590 00:34:02,680 --> 00:34:06,080 Speaker 3: Yeah, and you could be amish. Can you just be amish? No, 591 00:34:07,400 --> 00:34:09,680 Speaker 3: like I want to be amish. If you're Harrison Ford, 592 00:34:09,680 --> 00:34:15,480 Speaker 3: you could be yeah, or Woody Harrelson. Yeah, right, you 593 00:34:15,560 --> 00:34:17,720 Speaker 3: got anything else? How about these predictions for the future. 594 00:34:17,920 --> 00:34:20,239 Speaker 3: There's a couple in here there kind of funny. Ten 595 00:34:20,280 --> 00:34:24,239 Speaker 3: predictions that missed the mark, and these are real predictions. 596 00:34:24,560 --> 00:34:28,359 Speaker 3: In nineteen sixty seven, US News and World Report said 597 00:34:28,400 --> 00:34:30,880 Speaker 3: that by the end of the century, we will launch 598 00:34:30,920 --> 00:34:34,960 Speaker 3: our freight across the continent with missiles. Like you order 599 00:34:35,040 --> 00:34:37,719 Speaker 3: something from Amazon in New York instead of having a 600 00:34:37,719 --> 00:34:40,360 Speaker 3: fulfillment center nearby, Right, they just put it in a 601 00:34:40,400 --> 00:34:44,560 Speaker 3: missile and shoot it to you. Yeah, didn't happen. No, 602 00:34:44,640 --> 00:34:47,839 Speaker 3: but drones are coming? Are they really? Are they still 603 00:34:47,840 --> 00:34:49,120 Speaker 3: on that? Probably? Okay. 604 00:34:49,440 --> 00:34:53,200 Speaker 1: In nineteen fifty five, a guy named Alex Lewett predicted 605 00:34:53,280 --> 00:34:55,760 Speaker 1: nuclear power vacuum cleaners. 606 00:34:57,120 --> 00:35:01,760 Speaker 3: This one I think would be pretty great, dissolving dishes. Yeah, 607 00:35:01,800 --> 00:35:04,400 Speaker 3: and asked what it would be like in the year 608 00:35:04,440 --> 00:35:09,759 Speaker 3: two thousand, a science writer named Valdemire. Come, there's a 609 00:35:09,800 --> 00:35:13,279 Speaker 3: lot of man one, two, three, four five. He's a 610 00:35:13,280 --> 00:35:16,120 Speaker 3: fabulous science writer with the funny name Consonants in a row. 611 00:35:16,920 --> 00:35:21,560 Speaker 3: He said, you would basically, uh, put your plate in 612 00:35:21,719 --> 00:35:23,680 Speaker 3: two hundred and fifty degree water at the end and 613 00:35:23,719 --> 00:35:28,040 Speaker 3: it will just dissolve it. No more dishwashing. Uh. 614 00:35:28,560 --> 00:35:34,000 Speaker 1: Bucky Fuller predicted that Canada would be a subtropical climate 615 00:35:34,120 --> 00:35:35,920 Speaker 1: because we build a dome over it. 616 00:35:37,600 --> 00:35:38,360 Speaker 3: That didn't happen. 617 00:35:38,680 --> 00:35:41,360 Speaker 1: No, it didn't, which is strange because Bucky Fuller was 618 00:35:41,400 --> 00:35:41,919 Speaker 1: pretty sharp. 619 00:35:42,000 --> 00:35:46,960 Speaker 3: Dude. Here's another one. Was he really? Yeah? Buckminster Fuller? 620 00:35:47,040 --> 00:35:48,839 Speaker 3: Oh I didn't pick up on that. 621 00:35:49,120 --> 00:35:54,600 Speaker 1: He's who bucky balls are named after. Really, why I don't. 622 00:35:55,080 --> 00:35:56,600 Speaker 1: He may have invented him. I'm not sure. 623 00:35:57,280 --> 00:35:58,160 Speaker 3: What's the bucky ball. 624 00:35:58,360 --> 00:36:01,319 Speaker 1: It's the those little balls that are magnetic spheres that 625 00:36:01,400 --> 00:36:03,759 Speaker 1: like you, Oh, they'll shape in bucket balls. 626 00:36:03,840 --> 00:36:08,520 Speaker 3: Yeah. Yeah. Here's one. A Scottish geneticist that said in 627 00:36:08,560 --> 00:36:11,920 Speaker 3: the nineteen twenties that in the future, one third of 628 00:36:11,960 --> 00:36:14,800 Speaker 3: the babies would not be born. Oh, only one third 629 00:36:15,320 --> 00:36:17,600 Speaker 3: would be born as a result of pregnancy and the 630 00:36:17,680 --> 00:36:20,799 Speaker 3: other babies would be born in a lab. 631 00:36:20,840 --> 00:36:25,560 Speaker 1: Would they be grown basically exogenesis? Yeah, here's the last one. 632 00:36:25,640 --> 00:36:29,880 Speaker 1: Check you ready. Nineteen seventy five, the Research Institute of America, 633 00:36:29,880 --> 00:36:35,080 Speaker 1: which sounds pretty smart, said that by nineteen seventy five, 634 00:36:35,120 --> 00:36:38,120 Speaker 1: I'm sorry, this is several years before that, we would 635 00:36:38,160 --> 00:36:41,439 Speaker 1: all be driving personal helicopters. 636 00:36:41,800 --> 00:36:42,280 Speaker 3: Yeah. 637 00:36:42,560 --> 00:36:45,040 Speaker 1: Did not pan out, Probably never will. I don't know 638 00:36:45,080 --> 00:36:46,719 Speaker 1: if i'd want a personal helicopter. 639 00:36:48,080 --> 00:36:51,080 Speaker 3: You know. I was for Emily's birthday. I rented a 640 00:36:51,080 --> 00:36:53,680 Speaker 3: cabin in the North Georgia Mountains. Did you take a 641 00:36:53,719 --> 00:36:56,640 Speaker 3: personal helicopter there? No? But I was sitting on the 642 00:36:56,680 --> 00:37:00,160 Speaker 3: deck we all were, and way across the valley on 643 00:37:00,200 --> 00:37:02,960 Speaker 3: the side of a mountain was this huge, huge house. 644 00:37:03,760 --> 00:37:06,360 Speaker 3: And I heard a sound of a helicopter. I was like, 645 00:37:06,600 --> 00:37:08,520 Speaker 3: and I saw a blinking light. I got out the 646 00:37:08,560 --> 00:37:13,239 Speaker 3: binoculars and this dude had a helicopter. Wow. And he 647 00:37:13,320 --> 00:37:16,360 Speaker 3: took it and he flew it down about two miles 648 00:37:16,480 --> 00:37:19,120 Speaker 3: to the lake at the bottom of the valley. And 649 00:37:19,640 --> 00:37:22,520 Speaker 3: I guess he has a lake house and a mountain house, 650 00:37:22,880 --> 00:37:24,879 Speaker 3: and the easiest way to get there is to make 651 00:37:24,920 --> 00:37:28,239 Speaker 3: the four minute helicopter flight. That's crazy. Yeah. Wow, it 652 00:37:28,280 --> 00:37:30,239 Speaker 3: was pretty amazing. Wow, I want to know who that 653 00:37:30,280 --> 00:37:33,040 Speaker 3: guy is? Nut guy could be a lady. Yeah, it 654 00:37:33,080 --> 00:37:36,400 Speaker 3: could be what am I saying? It could be Carly Fiorina. Yeah. 655 00:37:36,560 --> 00:37:41,600 Speaker 1: Is that she's the woman who's running for GOP president candidate? 656 00:37:42,040 --> 00:37:47,200 Speaker 1: Oh right, Fiurina, that's right, gotcha? 657 00:37:47,800 --> 00:37:50,960 Speaker 3: Go ahead? Oh oh sorry, let's see. 658 00:37:51,000 --> 00:37:53,200 Speaker 1: Well, if you want to know more about futurology, you 659 00:37:53,239 --> 00:37:55,239 Speaker 1: can type that word into the search bar at house 660 00:37:55,280 --> 00:37:57,800 Speaker 1: to work dot com. And since Chuck had an anecdote 661 00:37:57,840 --> 00:38:00,000 Speaker 1: about helicopters, it's time for listeners. 662 00:38:03,360 --> 00:38:05,000 Speaker 3: It sort of looked like one of those Magnum p 663 00:38:05,120 --> 00:38:05,680 Speaker 3: I ones too. 664 00:38:05,920 --> 00:38:08,520 Speaker 1: Well, if I did have a personal helicopter, it would 665 00:38:08,560 --> 00:38:09,759 Speaker 1: look an awful lot like that. 666 00:38:09,880 --> 00:38:12,759 Speaker 3: I'm sure what Hey, guys, my name is Shelby. I'm 667 00:38:12,800 --> 00:38:14,759 Speaker 3: honored for you to be reading this. My husband and 668 00:38:14,800 --> 00:38:16,960 Speaker 3: I love your show, and you've solved our dilemma as 669 00:38:16,960 --> 00:38:18,920 Speaker 3: to what to listen to in our car together. I 670 00:38:18,960 --> 00:38:20,319 Speaker 3: want to let you know you did a great job 671 00:38:20,360 --> 00:38:23,320 Speaker 3: on the HIV AIDS podcast. However, I think you missed 672 00:38:23,320 --> 00:38:26,040 Speaker 3: telling a really important story about the AIDS crisis. Just 673 00:38:26,080 --> 00:38:29,120 Speaker 3: before the AIDS crisis broke, a method for treating heemophilia, 674 00:38:29,800 --> 00:38:32,920 Speaker 3: called a clotting factor concentrate was developed. I finally let 675 00:38:32,920 --> 00:38:35,960 Speaker 3: those suffering from the disease live into adulthood and completely 676 00:38:36,040 --> 00:38:39,160 Speaker 3: change the landscape of the disorder. By the time HIV 677 00:38:39,400 --> 00:38:41,920 Speaker 3: was discovered to be a blood born virus, many of 678 00:38:41,920 --> 00:38:44,799 Speaker 3: those suffering from hemophilia already had it, not to mention 679 00:38:44,960 --> 00:38:48,839 Speaker 3: that many also contracted hepatitis. However, the pharmaceutical companies did 680 00:38:48,840 --> 00:38:51,120 Speaker 3: not begin to pasteurize the drug in spite of their 681 00:38:51,160 --> 00:38:54,240 Speaker 3: knowledge that it was spreading HIV until a strong public 682 00:38:54,280 --> 00:38:57,320 Speaker 3: outcry prompted a government intervention. I think the story is 683 00:38:57,320 --> 00:38:59,759 Speaker 3: not told often enough. In the injustice that these individuals 684 00:39:00,160 --> 00:39:03,560 Speaker 3: suffered at the hands of big Pharma is undoubtedly one 685 00:39:03,560 --> 00:39:06,040 Speaker 3: of the greatest our country has seen. Man. There's an 686 00:39:06,080 --> 00:39:09,040 Speaker 3: extremely informative and sad documentary on the topic called Bad 687 00:39:09,080 --> 00:39:13,520 Speaker 3: Blood Colon A cautionary tale. Anyway, that's about it, And 688 00:39:13,560 --> 00:39:18,120 Speaker 3: I'm sorry if I bummed everyone out. That is from Shelby. 689 00:39:18,280 --> 00:39:23,920 Speaker 1: Shelby thank you for not only that illuminating email, yeah, 690 00:39:23,920 --> 00:39:26,000 Speaker 1: but also the documentary recommendation. 691 00:39:26,040 --> 00:39:27,759 Speaker 3: We're always looking for those absolutely. 692 00:39:28,239 --> 00:39:29,680 Speaker 1: If you want to get in touch with us, you 693 00:39:29,719 --> 00:39:32,560 Speaker 1: can send us an email to Stuff podcast at houstuffworks 694 00:39:32,600 --> 00:39:34,680 Speaker 1: dot com and has always tuned us at our home 695 00:39:34,719 --> 00:39:39,360 Speaker 1: on the web. Stuff Youshould Know dot com. 696 00:39:39,480 --> 00:39:42,360 Speaker 2: Stuff you Should Know is a production of iHeartRadio. For 697 00:39:42,440 --> 00:39:46,640 Speaker 2: more podcasts my heart Radio, visit the iHeartRadio app, Apple Podcasts, 698 00:39:46,760 --> 00:39:48,600 Speaker 2: or wherever you listen to your favorite shows.