1 00:00:00,240 --> 00:00:04,680 Speaker 1: From UFOs to psychic powers and government conspiracies. History is 2 00:00:04,760 --> 00:00:09,080 Speaker 1: riddled with unexplained events. You can turn back now or 3 00:00:09,200 --> 00:00:12,079 Speaker 1: learn the stuff they don't want you to know. A 4 00:00:12,200 --> 00:00:25,639 Speaker 1: production of I Heart Radio. Hello, welcome back to the show. 5 00:00:25,760 --> 00:00:28,200 Speaker 1: My name is Matt, my name is all. They called 6 00:00:28,200 --> 00:00:31,080 Speaker 1: me Ben. We're joined as always with our super producer 7 00:00:31,160 --> 00:00:35,639 Speaker 1: Alexis code named dot Holiday Jackson. Most importantly, you are you. 8 00:00:35,640 --> 00:00:38,519 Speaker 1: You are here, and that makes this the stuff they 9 00:00:38,600 --> 00:00:41,600 Speaker 1: don't want you to know. It's the top of the week, 10 00:00:41,640 --> 00:00:45,400 Speaker 1: which means it is time for more strange news. And 11 00:00:45,600 --> 00:00:49,600 Speaker 1: as we always say in our Strange News segment, a 12 00:00:49,720 --> 00:00:52,560 Speaker 1: lot of stuff has happened, a lot of crazy things. 13 00:00:53,280 --> 00:00:56,760 Speaker 1: Some of them are not getting reported widely in the news. 14 00:00:56,800 --> 00:00:59,600 Speaker 1: Some of them are but deserve a deeper dig. And 15 00:00:59,640 --> 00:01:05,800 Speaker 1: then some of them are. Some of them are interconnected webs. Right, 16 00:01:05,880 --> 00:01:08,040 Speaker 1: you're it's like you're pulling up Let me just do 17 00:01:08,120 --> 00:01:11,800 Speaker 1: some tortures, mixed metaphors. It's like assimilar. It's it's as 18 00:01:11,840 --> 00:01:15,240 Speaker 1: if you are pulling up the tip of an iceberg 19 00:01:15,280 --> 00:01:17,160 Speaker 1: to see that there is not only an iceberg, but 20 00:01:17,160 --> 00:01:19,679 Speaker 1: at the bottom of the iceberg there's this web that's 21 00:01:19,680 --> 00:01:22,640 Speaker 1: connected to all these other icebergs across the world. You're like, 22 00:01:22,720 --> 00:01:25,640 Speaker 1: holy smokes, we only have so much time to talk 23 00:01:25,680 --> 00:01:31,000 Speaker 1: about this. Uh so, and how did get water resistant? Right? Yeah, yeah, 24 00:01:31,280 --> 00:01:34,360 Speaker 1: there are a lot of questions. That's that's the takeaway here. 25 00:01:35,000 --> 00:01:39,560 Speaker 1: But there's something that I think is interesting context of 26 00:01:39,720 --> 00:01:44,120 Speaker 1: for our segment today. You know, earlier we talked a 27 00:01:44,160 --> 00:01:47,480 Speaker 1: little bit about deep fakes, while we talked in depth 28 00:01:47,520 --> 00:01:51,720 Speaker 1: about deep fakes, and we were unfortunately prescient in some 29 00:01:51,880 --> 00:01:56,760 Speaker 1: of our ideas about how these would be implemented further, 30 00:01:57,280 --> 00:02:00,240 Speaker 1: not just in audio, but in video as well. And 31 00:02:00,360 --> 00:02:03,040 Speaker 1: now we're starting to see some more of the rubber 32 00:02:03,200 --> 00:02:07,160 Speaker 1: hit the road in a very public way, and full disclosure, 33 00:02:07,320 --> 00:02:11,640 Speaker 1: this is something that has potential to impact our own 34 00:02:11,680 --> 00:02:15,000 Speaker 1: industry in the future as well. But for a lot 35 00:02:15,000 --> 00:02:17,959 Speaker 1: of people, the first time they heard about this very 36 00:02:18,000 --> 00:02:23,200 Speaker 1: specific kind of mad science was just a few days ago, 37 00:02:23,320 --> 00:02:26,120 Speaker 1: I believe right now, Yeah, it's true. Um, it's a 38 00:02:26,120 --> 00:02:32,320 Speaker 1: new documentary about the beloved traveler World traveler, UM chef 39 00:02:32,600 --> 00:02:36,920 Speaker 1: you know wrecontour Anthony Bourdain m who you know tragically 40 00:02:36,919 --> 00:02:39,000 Speaker 1: took his own life. I don't think it hit a 41 00:02:39,040 --> 00:02:41,320 Speaker 1: lot of people very very hard because he just kind 42 00:02:41,360 --> 00:02:44,880 Speaker 1: of really represented that kind of lust for life that 43 00:02:44,960 --> 00:02:48,440 Speaker 1: I think many people kind of strive for. Um. You know, 44 00:02:48,680 --> 00:02:50,959 Speaker 1: in parts of Known, one of his series on his 45 00:02:51,040 --> 00:02:53,400 Speaker 1: many series UM where he would you know, go and 46 00:02:53,440 --> 00:02:55,480 Speaker 1: travel the world and really just kind of hang out 47 00:02:55,480 --> 00:02:57,600 Speaker 1: with the people, you know, and eat the food, the 48 00:02:57,639 --> 00:03:00,000 Speaker 1: native food, and just really and I just seem like 49 00:03:00,000 --> 00:03:02,160 Speaker 1: a really lovely guy. And it just goes to show that, 50 00:03:02,720 --> 00:03:05,919 Speaker 1: you know, mental health is not someone's mental health is 51 00:03:05,919 --> 00:03:08,200 Speaker 1: not always a parent. You know, if they can seem 52 00:03:08,280 --> 00:03:10,440 Speaker 1: very happy and they can seem like they're living their 53 00:03:10,440 --> 00:03:12,520 Speaker 1: best life, but then you know, there can also be 54 00:03:12,880 --> 00:03:15,880 Speaker 1: a kind of demons underneath the surface, and it certainly 55 00:03:15,880 --> 00:03:18,720 Speaker 1: turned out to be the case with Bourdain. Um. But 56 00:03:18,800 --> 00:03:23,760 Speaker 1: this is about ethics in uh. In filmmaking, you know, 57 00:03:23,880 --> 00:03:27,200 Speaker 1: we certainly see things like in The Irishman, for example, 58 00:03:27,240 --> 00:03:30,280 Speaker 1: Scorsese film. I mean they made Joe Pesci and Robert 59 00:03:30,240 --> 00:03:32,639 Speaker 1: de Niro, you know, look younger. I kind of thought 60 00:03:32,680 --> 00:03:34,079 Speaker 1: it took me out of the movie a little bit, 61 00:03:34,200 --> 00:03:36,000 Speaker 1: sort of felt like a cut scene in the video game. 62 00:03:36,040 --> 00:03:38,440 Speaker 1: But you know, people still seem to really love that movie. 63 00:03:38,960 --> 00:03:41,920 Speaker 1: Or you know, let's say bringing back Carrie Fisher, for example, 64 00:03:42,000 --> 00:03:44,480 Speaker 1: in some of the Star Wars sequels, the more recent 65 00:03:44,520 --> 00:03:48,520 Speaker 1: Star Wars sequels after she passed. Um, you could argue 66 00:03:48,560 --> 00:03:52,040 Speaker 1: that's a little weird. It's like like a Tupac hologram 67 00:03:52,040 --> 00:03:54,800 Speaker 1: at Coachella or something. Uh, if it's done with the 68 00:03:54,880 --> 00:03:59,400 Speaker 1: approval of the estate and it's you know, something like 69 00:03:59,400 --> 00:04:02,040 Speaker 1: like like fiction, that seems pretty harmless, I guess. But 70 00:04:02,400 --> 00:04:05,680 Speaker 1: what happens you take this idea of deep fakes and 71 00:04:05,720 --> 00:04:08,680 Speaker 1: again the ones I just described are pretty obvious, like 72 00:04:08,760 --> 00:04:11,920 Speaker 1: you know, that's not really Carrie Fisher. As much as 73 00:04:12,000 --> 00:04:14,320 Speaker 1: they try, you know, it's still kind of looks like 74 00:04:14,360 --> 00:04:16,240 Speaker 1: a video game cut scene. I'm sure it'll get better. 75 00:04:16,279 --> 00:04:17,799 Speaker 1: But you know, as what you know, with the Internet, 76 00:04:17,839 --> 00:04:19,919 Speaker 1: like I mean, these deep fakes have really started to 77 00:04:20,320 --> 00:04:24,280 Speaker 1: pop up that absolutely could fool you, you know, and 78 00:04:25,560 --> 00:04:30,240 Speaker 1: have the potential to ruin lives if someone uses them 79 00:04:30,279 --> 00:04:33,640 Speaker 1: you nefariously. And it's really caused a lot of news 80 00:04:33,640 --> 00:04:37,320 Speaker 1: agencies and publications, etcetera to really start to have, you know, 81 00:04:37,360 --> 00:04:40,960 Speaker 1: kind of ethical conversations around this stuff. Um. So obviously 82 00:04:41,000 --> 00:04:44,400 Speaker 1: a documentary film is intended to be entertaining, But what 83 00:04:44,520 --> 00:04:47,120 Speaker 1: happens when you take the voice of of a man 84 00:04:47,240 --> 00:04:51,479 Speaker 1: who is beloved as as Anthony Ordaine was and recreate it, 85 00:04:51,800 --> 00:04:55,640 Speaker 1: um using artificial intelligence, by feeding it uh dozens and 86 00:04:55,680 --> 00:04:58,600 Speaker 1: dozens of hours of available recordings. Obviously, we're in an 87 00:04:58,640 --> 00:05:01,600 Speaker 1: era where there are a lot of archival recordings of 88 00:05:01,720 --> 00:05:04,480 Speaker 1: just about everything. And if you're someone that's as a 89 00:05:04,520 --> 00:05:07,120 Speaker 1: bunch of a public figure as Anthony Bourdaine, UM, it's 90 00:05:07,240 --> 00:05:10,520 Speaker 1: gonna be you know, tenfold that what it would be 91 00:05:10,560 --> 00:05:13,479 Speaker 1: for you know, folks like us. Well, it's kind of 92 00:05:13,480 --> 00:05:16,159 Speaker 1: interesting when you think about podcastings. We obviously have a 93 00:05:16,240 --> 00:05:19,160 Speaker 1: lot of our audio of ourselves out there on the internet, 94 00:05:19,440 --> 00:05:24,479 Speaker 1: uh for people to potentially mine and create AI clones 95 00:05:24,520 --> 00:05:26,760 Speaker 1: of us if they so wished. And that's exactly what 96 00:05:26,800 --> 00:05:31,159 Speaker 1: this filmmaker Morgan Neville did. Um. Morgan Neville is like 97 00:05:31,320 --> 00:05:35,360 Speaker 1: probably one of the most high profile kind of like 98 00:05:35,440 --> 00:05:42,000 Speaker 1: bespoke documentary filmmakers in working right now. UMA documentary filmmakers 99 00:05:42,080 --> 00:05:45,400 Speaker 1: like you know you you had you know, you're Errol Morris, 100 00:05:45,560 --> 00:05:47,920 Speaker 1: you know who made some some very high profile ones 101 00:05:47,960 --> 00:05:51,400 Speaker 1: that did very very well. You had, um, some like 102 00:05:51,600 --> 00:05:54,240 Speaker 1: by Werner Herzog, like Grizzly Man that did really really 103 00:05:54,320 --> 00:05:56,560 Speaker 1: well and we're very high profile. And then of course 104 00:05:56,600 --> 00:05:59,279 Speaker 1: you have the big, biggest one kind of the intel 105 00:05:59,320 --> 00:06:02,040 Speaker 1: bell in terms of like popularity of a documentary is, 106 00:06:02,040 --> 00:06:05,240 Speaker 1: which was Michael Moore and like Farenheit nine eleven, Bowling 107 00:06:05,240 --> 00:06:08,920 Speaker 1: for Columbine before that, and Roger and Me. But um so, 108 00:06:08,960 --> 00:06:11,200 Speaker 1: this guy's kind of following in the footsteps of those 109 00:06:11,200 --> 00:06:14,359 Speaker 1: folks for sure in that documentary filmmaking certainly can be 110 00:06:14,360 --> 00:06:16,440 Speaker 1: a little bit more niche. But when you get to 111 00:06:16,440 --> 00:06:18,880 Speaker 1: the level that this guy is and you're making a 112 00:06:18,920 --> 00:06:23,520 Speaker 1: documentary about someone as beloved as Anthony Bourdaine, I would 113 00:06:23,560 --> 00:06:26,680 Speaker 1: think that he would expect some pushback from literally reconstructing 114 00:06:26,720 --> 00:06:30,719 Speaker 1: Anthony Bourdine's voice. Uh to have it seemed like he 115 00:06:30,960 --> 00:06:34,840 Speaker 1: read what you could argue almost sounds like a suicide note. 116 00:06:35,360 --> 00:06:37,080 Speaker 1: That's not what it is. I believe it was a 117 00:06:37,120 --> 00:06:41,080 Speaker 1: text or an email, some some text exchange with his friend, 118 00:06:41,440 --> 00:06:44,080 Speaker 1: the artist David cho who I think is also a 119 00:06:44,080 --> 00:06:46,760 Speaker 1: really interesting character into himself and you know, another kind 120 00:06:46,800 --> 00:06:51,720 Speaker 1: of weirdo psychedelic traveler. Um but basically was saying something 121 00:06:51,720 --> 00:06:55,839 Speaker 1: to the effect of like, I'm successful, you're successful, but 122 00:06:55,960 --> 00:06:59,440 Speaker 1: my life is now and how are you happy? Kind 123 00:06:59,440 --> 00:07:02,400 Speaker 1: of like looking first of advice, you know, um, And 124 00:07:02,680 --> 00:07:05,480 Speaker 1: the idea I think behind this film was that it 125 00:07:05,520 --> 00:07:08,440 Speaker 1: was constructed from audio recording, so it's like almost like 126 00:07:08,480 --> 00:07:11,200 Speaker 1: the whole idea of the the I guess the gimmick, 127 00:07:11,360 --> 00:07:13,080 Speaker 1: for lack of a better word, is that it's Anthony 128 00:07:13,120 --> 00:07:15,800 Speaker 1: Bourdain telling his story in his own voice, you know, 129 00:07:15,920 --> 00:07:18,280 Speaker 1: pulled from different audio books and all the sources that 130 00:07:18,320 --> 00:07:20,760 Speaker 1: I just mentioned, but there is this one line that 131 00:07:20,760 --> 00:07:23,160 Speaker 1: that the filmmaker felt was really important that he didn't 132 00:07:23,200 --> 00:07:26,560 Speaker 1: have him saying. So it's like the next level, kind 133 00:07:26,600 --> 00:07:28,200 Speaker 1: of powered up version of what they do in the 134 00:07:28,840 --> 00:07:31,480 Speaker 1: reality television a loot which is called franken biting, where 135 00:07:31,480 --> 00:07:34,200 Speaker 1: they take clips of audio that things that people have 136 00:07:34,280 --> 00:07:36,960 Speaker 1: said and with a cutaway so you don't see their 137 00:07:37,000 --> 00:07:39,360 Speaker 1: mouth moving. They sort of stitched together and use a 138 00:07:39,360 --> 00:07:41,400 Speaker 1: little what they call it an audio editing cross fades 139 00:07:41,440 --> 00:07:43,880 Speaker 1: so you don't hear any clicks or hiccups between the words, 140 00:07:44,400 --> 00:07:47,240 Speaker 1: and you can be pretty convincing with that. But this 141 00:07:47,320 --> 00:07:52,720 Speaker 1: isn't that. This is literally feeding this AI software that 142 00:07:52,720 --> 00:07:55,840 Speaker 1: that the filmmaker hooked up with dozens of hours of 143 00:07:55,880 --> 00:07:58,880 Speaker 1: these recordings and then using I imagine some sort of 144 00:07:58,880 --> 00:08:02,960 Speaker 1: interface to type in these words, and I imagine there's 145 00:08:02,960 --> 00:08:05,400 Speaker 1: a there's a graphical user of situation where you can 146 00:08:05,760 --> 00:08:09,400 Speaker 1: adjust the cadence and all that. Um. But it's getting 147 00:08:09,440 --> 00:08:12,600 Speaker 1: a lot of backlash. It's almost like exclusively the conversation 148 00:08:12,600 --> 00:08:16,240 Speaker 1: around what is apparently otherwise you know, pretty good film, Ben, 149 00:08:16,280 --> 00:08:18,120 Speaker 1: you saw it. I haven't seen it yet, I have 150 00:08:18,240 --> 00:08:21,720 Speaker 1: planned to. But um, overall, what did you think of 151 00:08:21,720 --> 00:08:25,600 Speaker 1: the film? And did you know this did tidbit going in? 152 00:08:25,920 --> 00:08:28,280 Speaker 1: I did not know this tidbit going in. I don't 153 00:08:28,280 --> 00:08:31,200 Speaker 1: want to trick everyone to listening to it like a 154 00:08:31,280 --> 00:08:35,480 Speaker 1: painful film review. But for people who are like me, 155 00:08:36,000 --> 00:08:40,240 Speaker 1: a fan of the man's work, his legacy, his excellent writing, 156 00:08:40,800 --> 00:08:43,240 Speaker 1: which I don't think he gets enough credit for, then 157 00:08:43,320 --> 00:08:48,000 Speaker 1: this is um. This can be pretty controversial in terms 158 00:08:48,160 --> 00:08:53,599 Speaker 1: of its lack of objectivity. It is very much presenting 159 00:08:53,840 --> 00:08:59,360 Speaker 1: a narrative regarding the circumstances leading up to his suicide, 160 00:08:59,480 --> 00:09:05,400 Speaker 1: especially relationship with Asia Argento. And when I learned that 161 00:09:05,720 --> 00:09:09,679 Speaker 1: the When when I learned first that AI have been 162 00:09:09,800 --> 00:09:14,040 Speaker 1: used to reconstruct the voice, I was pretty appalled. And 163 00:09:14,080 --> 00:09:18,200 Speaker 1: then secondly, like a lot of people you know. Originally, 164 00:09:18,720 --> 00:09:22,800 Speaker 1: the filmmaker said that the estate had agreed that this 165 00:09:22,800 --> 00:09:26,360 Speaker 1: would be okay to do, because these were words that 166 00:09:26,480 --> 00:09:30,839 Speaker 1: Bourdain specifically wrote himself. So it's not like they had 167 00:09:31,360 --> 00:09:33,560 Speaker 1: you know, it's not like they used the AI to say, 168 00:09:33,720 --> 00:09:36,800 Speaker 1: have him say, at what better time to try a 169 00:09:36,800 --> 00:09:39,839 Speaker 1: whopper from Burger King or something like that, though they 170 00:09:39,880 --> 00:09:43,280 Speaker 1: totally could. And I argue that's the problem. It's it's 171 00:09:43,320 --> 00:09:46,720 Speaker 1: the ethical question of like how would First the estate 172 00:09:46,800 --> 00:09:49,280 Speaker 1: came forward at least the widow, as I believe you mentioned, 173 00:09:49,280 --> 00:09:52,160 Speaker 1: and said I definitely didn't say I was okay with this, 174 00:09:52,320 --> 00:09:57,280 Speaker 1: and then other people came forward and said, based on 175 00:09:57,480 --> 00:10:01,360 Speaker 1: you know, me knowing Tony in his lifetime, he would 176 00:10:01,360 --> 00:10:03,400 Speaker 1: have been repulsed by this. But I think one of 177 00:10:03,400 --> 00:10:07,600 Speaker 1: the biggest issues here not just you know, whether or 178 00:10:07,600 --> 00:10:11,080 Speaker 1: not the estate or the person having their voice stolen 179 00:10:11,160 --> 00:10:13,679 Speaker 1: or recreated however you want to put it. Aside from 180 00:10:13,720 --> 00:10:18,319 Speaker 1: that issue, one of the biggest concerns is ethical disclosure 181 00:10:18,440 --> 00:10:21,079 Speaker 1: to your audience. You know what I mean, Like what 182 00:10:21,200 --> 00:10:23,600 Speaker 1: if what if you're listening to stuff they don't want 183 00:10:23,640 --> 00:10:27,280 Speaker 1: you to know and you found out that um, Matt 184 00:10:27,520 --> 00:10:30,920 Speaker 1: Noel or me or all of us have been dead 185 00:10:31,360 --> 00:10:35,160 Speaker 1: since two thousand and seventeen, and what you're hearing is 186 00:10:35,200 --> 00:10:39,080 Speaker 1: just something written by somebody else in our voices. That's 187 00:10:39,120 --> 00:10:41,560 Speaker 1: not a possibility yet, but it's on the way. Yeah, 188 00:10:41,640 --> 00:10:44,800 Speaker 1: well it's not far from a possibility. I mean, we 189 00:10:44,800 --> 00:10:49,600 Speaker 1: we've all um through working in this field and looking 190 00:10:49,640 --> 00:10:51,560 Speaker 1: into stories like this, I think we know that this 191 00:10:51,640 --> 00:10:54,280 Speaker 1: technology definitely exists. I mean, I think there was even 192 00:10:54,320 --> 00:10:57,320 Speaker 1: a there's some kind of Adobe summit, you know, Adobe, 193 00:10:57,360 --> 00:10:59,439 Speaker 1: the company that makes Photoshop and Illustrated and all that, 194 00:10:59,720 --> 00:11:03,040 Speaker 1: and a demonstrated some kind of software that was essentially 195 00:11:03,040 --> 00:11:06,560 Speaker 1: described as like Photoshop for your voice, and you know, 196 00:11:06,600 --> 00:11:09,439 Speaker 1: in feeding it just a couple of sentences, it could 197 00:11:09,520 --> 00:11:13,720 Speaker 1: get a pretty pretty convincing, um clone of of a voice, 198 00:11:14,040 --> 00:11:17,120 Speaker 1: kind of right before the audience's eyes. So with audio, 199 00:11:17,200 --> 00:11:20,800 Speaker 1: it's even weirder, right because especially with podcasters and you know, 200 00:11:20,840 --> 00:11:23,920 Speaker 1: people people like us, and um, the fact that now 201 00:11:23,960 --> 00:11:27,400 Speaker 1: there is so much audio only content. Uh so you 202 00:11:27,440 --> 00:11:29,719 Speaker 1: don't have to have it be convincing and match up 203 00:11:29,720 --> 00:11:31,720 Speaker 1: with a face. I mean, I mean you could argue 204 00:11:31,760 --> 00:11:33,960 Speaker 1: that that, like, it's gonna be harder to sell if 205 00:11:34,000 --> 00:11:36,480 Speaker 1: it's just someone's voice. But you know, what if you 206 00:11:36,520 --> 00:11:40,000 Speaker 1: manufacture someone's voice saying something or really awful, really offensive, 207 00:11:40,120 --> 00:11:43,640 Speaker 1: or like cancel worthy or something. Yeah, for instance, let's 208 00:11:43,679 --> 00:11:47,839 Speaker 1: take it to a further extent, what if you have 209 00:11:48,160 --> 00:11:51,120 Speaker 1: what what if someone does a deep fake or an 210 00:11:51,120 --> 00:11:55,200 Speaker 1: AI model of the presidents of the United States, whoever 211 00:11:55,280 --> 00:11:58,520 Speaker 1: that is at the time, and then they broadcast across 212 00:11:58,559 --> 00:12:02,920 Speaker 1: the world or in rival country a statement saying we're 213 00:12:03,000 --> 00:12:06,880 Speaker 1: dropping the bombs right like we are engaging in a 214 00:12:07,120 --> 00:12:10,800 Speaker 1: preemptive nuclear strike. That's the stuff of science fiction and 215 00:12:10,840 --> 00:12:15,319 Speaker 1: thrillers right now. But the technology is now there such 216 00:12:15,400 --> 00:12:19,520 Speaker 1: that pretty soon you'll need an AI program to tell 217 00:12:19,559 --> 00:12:21,840 Speaker 1: you that's not the real voice, and that might not 218 00:12:21,960 --> 00:12:24,800 Speaker 1: even be enough. Like this could put people in very 219 00:12:24,960 --> 00:12:29,760 Speaker 1: very dangerous situations very quickly. It's it's deeper than documentaries 220 00:12:29,760 --> 00:12:32,640 Speaker 1: and podcast for sure. Yeah, guys, I want to take 221 00:12:32,760 --> 00:12:36,040 Speaker 1: the stance of the director or maybe a producer or 222 00:12:36,080 --> 00:12:39,480 Speaker 1: someone on this documentary just for a second to imagine 223 00:12:40,559 --> 00:12:44,880 Speaker 1: maybe the devil's advocate position, Because when you're creating something 224 00:12:44,960 --> 00:12:49,000 Speaker 1: like this, you're if you're going to show footage of 225 00:12:49,000 --> 00:12:51,240 Speaker 1: the email that was in question right now, all that 226 00:12:51,320 --> 00:12:52,800 Speaker 1: that's what I think that that's what it was an 227 00:12:52,800 --> 00:12:56,840 Speaker 1: email that was on screen. It's just forty five seconds 228 00:12:56,840 --> 00:12:59,600 Speaker 1: of audio, I believe. Well, there's three different clips throughout 229 00:12:59,600 --> 00:13:01,559 Speaker 1: the movie. This is just the most kind of poignant 230 00:13:01,840 --> 00:13:05,479 Speaker 1: or pointed one because it literally kind of is almost 231 00:13:05,520 --> 00:13:08,800 Speaker 1: it's like the last communication that he did. I think 232 00:13:08,800 --> 00:13:11,640 Speaker 1: there were three other instances, none of which it seemed 233 00:13:11,679 --> 00:13:13,640 Speaker 1: to have robbed people up quite as much. I mean, honestly, 234 00:13:13,679 --> 00:13:15,079 Speaker 1: it's the whole concept that rowing people up, but I 235 00:13:15,080 --> 00:13:19,440 Speaker 1: think specifically it's this very private moment um that they 236 00:13:19,600 --> 00:13:22,560 Speaker 1: you know, manufactured him saying, even though you know they 237 00:13:22,559 --> 00:13:26,480 Speaker 1: obviously are his words. So there there's another ethical issue 238 00:13:26,480 --> 00:13:29,400 Speaker 1: like is it okay because it's his words? I just 239 00:13:29,440 --> 00:13:33,080 Speaker 1: want to clarify that's forty five seconds total, all three instances, 240 00:13:33,080 --> 00:13:37,040 Speaker 1: so it's all three, got it okay? So in the 241 00:13:37,240 --> 00:13:39,360 Speaker 1: I'm just gonna go to that one moment and I'm 242 00:13:39,400 --> 00:13:43,240 Speaker 1: imagining it laid out in you know, premiere or something, 243 00:13:43,320 --> 00:13:46,640 Speaker 1: and I've got the video of this email. I want 244 00:13:46,679 --> 00:13:49,800 Speaker 1: the audience to know the contents of that email. So 245 00:13:49,840 --> 00:13:53,400 Speaker 1: I'm gonna highlight it with voiceover, probably because really your 246 00:13:53,400 --> 00:13:58,240 Speaker 1: options are you you know, say something about this email. 247 00:13:58,360 --> 00:14:00,520 Speaker 1: Then you put it up as text on the screen 248 00:14:00,640 --> 00:14:03,280 Speaker 1: so your audience can read it in the moment, you know, 249 00:14:03,360 --> 00:14:05,600 Speaker 1: let it play for amount of time that you anticipate 250 00:14:05,640 --> 00:14:08,480 Speaker 1: the audience can read it, and then it goes away. 251 00:14:08,640 --> 00:14:13,200 Speaker 1: Or you have a narrator somebody whoever that person is 252 00:14:13,240 --> 00:14:15,880 Speaker 1: going to be read those words while they're on the screen. 253 00:14:17,000 --> 00:14:19,480 Speaker 1: So in this case, if you're going to go that route, 254 00:14:19,480 --> 00:14:23,080 Speaker 1: it can be some you know, somebody who's been narrating 255 00:14:23,200 --> 00:14:26,640 Speaker 1: with you for the entire documentary, or just some random 256 00:14:26,680 --> 00:14:31,640 Speaker 1: person that's going to only read Anthony Bourdain's words, or 257 00:14:32,400 --> 00:14:35,640 Speaker 1: in this case, because the technology is available, actually have 258 00:14:35,840 --> 00:14:39,960 Speaker 1: Anthony Bourdain read the words he wrote to me. I 259 00:14:40,000 --> 00:14:45,040 Speaker 1: can imagine that being very desirable, if only for emotional 260 00:14:45,080 --> 00:14:49,000 Speaker 1: impact right of that moment of seeing that, you know, 261 00:14:49,160 --> 00:14:53,440 Speaker 1: perhaps a downtrodden person saying something that we're there at 262 00:14:54,120 --> 00:14:57,520 Speaker 1: possibly one of their lowest moments. That's very intriguing to me. 263 00:14:58,320 --> 00:15:00,480 Speaker 1: But everything that you guys have already pointed, know, not 264 00:15:00,600 --> 00:15:03,760 Speaker 1: letting your audience know, not getting permission from the estate 265 00:15:03,880 --> 00:15:07,280 Speaker 1: to use it, I mean it does seem incredibly uh 266 00:15:07,600 --> 00:15:10,080 Speaker 1: made in bad taste, A decision made in bad taste. 267 00:15:10,160 --> 00:15:13,440 Speaker 1: I think it's absolutely desirable from a creative standpoint. I mean, 268 00:15:13,840 --> 00:15:15,720 Speaker 1: when you hear the filmmaker talking about it, that's how 269 00:15:15,720 --> 00:15:18,560 Speaker 1: he frames it. He kind of doesn't do himself too 270 00:15:18,560 --> 00:15:21,640 Speaker 1: many favors because he talks pretty flippantly and dismissively of 271 00:15:21,720 --> 00:15:24,560 Speaker 1: almost as though he feels like people getting riled up 272 00:15:24,560 --> 00:15:27,600 Speaker 1: about this is like ridiculous. And he it was even 273 00:15:27,640 --> 00:15:30,800 Speaker 1: maybe before the the out the kind of outcry or whatever, 274 00:15:30,840 --> 00:15:33,400 Speaker 1: but like he, you know, says something like, we can 275 00:15:33,440 --> 00:15:35,760 Speaker 1: have an ethical panel. We can have a panel on 276 00:15:35,920 --> 00:15:39,240 Speaker 1: documentary ethics later, har har harror, and you know, as 277 00:15:39,320 --> 00:15:40,560 Speaker 1: one of the articles I read, I think in the 278 00:15:40,600 --> 00:15:43,040 Speaker 1: New York Times pointed out that the critics didn't want 279 00:15:43,040 --> 00:15:45,320 Speaker 1: to wait till later because a lot of the critics 280 00:15:45,360 --> 00:15:47,560 Speaker 1: didn't know going in either, and so then a lot 281 00:15:47,600 --> 00:15:51,000 Speaker 1: of them had almost amend their reviews and express their 282 00:15:51,240 --> 00:15:54,320 Speaker 1: discussed with this technique. I'm with you, Matt, though, I 283 00:15:54,360 --> 00:15:56,720 Speaker 1: see the creative que especially since it's like a very 284 00:15:56,800 --> 00:15:59,520 Speaker 1: uniform technique that he's doing. Where again, he went to 285 00:15:59,640 --> 00:16:02,840 Speaker 1: great lengths to mind all this stuff. Yeah, so it 286 00:16:02,880 --> 00:16:05,520 Speaker 1: could be largely in his his voice. Ben, you've seen 287 00:16:05,520 --> 00:16:07,240 Speaker 1: it is that accurate, like it is kind of largely 288 00:16:07,520 --> 00:16:09,920 Speaker 1: narrated by him, based on you know, pulling from all 289 00:16:09,920 --> 00:16:13,560 Speaker 1: these sources. Yes, so it's I don't want to tell 290 00:16:13,640 --> 00:16:16,760 Speaker 1: people what to think. I did enjoy watching it, uh, 291 00:16:16,800 --> 00:16:22,920 Speaker 1: and I largely agree with their depiction of Bourdain. However, 292 00:16:23,520 --> 00:16:25,840 Speaker 1: I do want to say, you know, the big sticking 293 00:16:25,840 --> 00:16:29,240 Speaker 1: point here is the permission of the estate. If the 294 00:16:29,480 --> 00:16:33,680 Speaker 1: estate gave the permission, then it seems pretty ethical. But 295 00:16:34,360 --> 00:16:38,440 Speaker 1: if we're playing Devil's advocate, let's also acknowledge we've had 296 00:16:38,640 --> 00:16:44,400 Speaker 1: voice actors do countless, countless recordings of other people, you 297 00:16:44,440 --> 00:16:47,960 Speaker 1: know what I mean, like the Founding Fathers right, Uh, 298 00:16:48,160 --> 00:16:51,680 Speaker 1: spoiler alert, that's not Jefferson that you hear on those 299 00:16:51,720 --> 00:16:55,480 Speaker 1: History Channel documentaries. That's some other two or in the 300 00:16:55,480 --> 00:17:01,720 Speaker 1: Hall of Presidents at Disney. No, I think that is him. Okay, No, 301 00:17:01,800 --> 00:17:03,720 Speaker 1: it's a really it's a really good point. I mean, hell, 302 00:17:03,840 --> 00:17:07,239 Speaker 1: I just did a voice reenactment for a podcast of 303 00:17:07,240 --> 00:17:12,520 Speaker 1: ours where I pretend to be this ufologist. You know, um, 304 00:17:13,119 --> 00:17:16,919 Speaker 1: I we've all done I think narrations or recreations of 305 00:17:17,000 --> 00:17:20,400 Speaker 1: like courtroom scenes, or we've contributed uh, you know, we've 306 00:17:20,400 --> 00:17:23,800 Speaker 1: contributed re enactment voiceovers. You know that, but they are 307 00:17:24,040 --> 00:17:26,960 Speaker 1: saying the words of other people. UM. It's interesting. I 308 00:17:27,000 --> 00:17:30,440 Speaker 1: think people are getting caught up in the creepy AI 309 00:17:30,680 --> 00:17:35,800 Speaker 1: future of it all rather than necessarily thinking about if 310 00:17:35,840 --> 00:17:39,679 Speaker 1: he really did anything wrong per se. I mean the 311 00:17:39,720 --> 00:17:44,600 Speaker 1: fact that that Bourdain's widow tweeted out emphatically he didn't 312 00:17:44,640 --> 00:17:48,240 Speaker 1: ask me. He claimed to have asked her, and the 313 00:17:48,280 --> 00:17:51,840 Speaker 1: executive his literary agent. So I guess whomever has is 314 00:17:51,880 --> 00:17:57,320 Speaker 1: the executor of his uh literary estate his life rights right. Um, 315 00:17:57,480 --> 00:18:01,520 Speaker 1: he and his his wife were in the process of 316 00:18:01,520 --> 00:18:03,920 Speaker 1: getting divorced, it just hadn't been finalized. I'm not I'm 317 00:18:03,960 --> 00:18:06,239 Speaker 1: not saying that matters necessarily. I just mean maybe she 318 00:18:06,359 --> 00:18:09,760 Speaker 1: was not no longer it was the executor in that way. 319 00:18:10,000 --> 00:18:13,879 Speaker 1: So maybe her making this very kind of pointed you know, 320 00:18:14,280 --> 00:18:17,520 Speaker 1: all caps tweet certainly set some people off, but maybe 321 00:18:17,520 --> 00:18:20,480 Speaker 1: he did actually clear with the proper channels quote unquote. 322 00:18:20,760 --> 00:18:22,720 Speaker 1: I just want to point out the voice over NOL 323 00:18:22,840 --> 00:18:26,760 Speaker 1: is referring to. In those instances, we always say and 324 00:18:26,840 --> 00:18:29,879 Speaker 1: the following is read by a voice actor, or you know, 325 00:18:30,080 --> 00:18:32,479 Speaker 1: here are the words of so and so read by 326 00:18:32,520 --> 00:18:35,480 Speaker 1: a voice actor, and very clear. I think I'm in 327 00:18:35,520 --> 00:18:38,920 Speaker 1: there too. That's strange arrivals, right, great, check it out. 328 00:18:39,119 --> 00:18:41,919 Speaker 1: It is. We had Toby Ball on the show on 329 00:18:41,960 --> 00:18:45,240 Speaker 1: the last season. Maybe you've got time is weird, um, 330 00:18:45,280 --> 00:18:48,760 Speaker 1: but I don't know, like it's an interesting one. I 331 00:18:48,760 --> 00:18:50,320 Speaker 1: think people are getting been in a shape for the 332 00:18:50,320 --> 00:18:52,919 Speaker 1: wrong reasons a little bit. But I do think the 333 00:18:52,920 --> 00:18:56,480 Speaker 1: future of this tech is very troubling. Agreed. That's that's 334 00:18:56,480 --> 00:18:58,600 Speaker 1: all I've got to say about that. I think it's 335 00:18:58,640 --> 00:19:02,840 Speaker 1: a time time for a quick sponsor break and h 336 00:19:02,920 --> 00:19:11,960 Speaker 1: and I'm back with some more strange news and we're 337 00:19:12,000 --> 00:19:15,280 Speaker 1: back now candidly everyone, I had a bit of a 338 00:19:15,280 --> 00:19:17,639 Speaker 1: tough time finding a story that I felt met the 339 00:19:17,800 --> 00:19:21,080 Speaker 1: stuff they don't want you to know criteria. So I'm 340 00:19:21,080 --> 00:19:23,200 Speaker 1: going to rattle off a couple of quick headlines. We're 341 00:19:23,200 --> 00:19:25,479 Speaker 1: gonna go super fast, then we'll jump to the one 342 00:19:25,520 --> 00:19:30,760 Speaker 1: I chose for this week. Cool. Yes, say, First of all, 343 00:19:31,359 --> 00:19:36,440 Speaker 1: Bismarcki has left us. He had what we needed, and 344 00:19:36,840 --> 00:19:40,560 Speaker 1: it was advice about people who are less than forthcoming 345 00:19:40,640 --> 00:19:45,000 Speaker 1: about their relationship status. Very talented individual. That is seriously 346 00:19:45,080 --> 00:19:47,639 Speaker 1: kind of a sad thing that hit all of us. 347 00:19:47,720 --> 00:19:51,639 Speaker 1: Huge influence on hip hop. Um. You know, I know 348 00:19:51,960 --> 00:19:57,480 Speaker 1: that grief is something people encounter in their own ways, right, 349 00:19:57,640 --> 00:20:00,639 Speaker 1: Probably the best description of grief is that it's waiting 350 00:20:00,680 --> 00:20:04,120 Speaker 1: for a telephone that never rings, right, Um, if we're 351 00:20:04,119 --> 00:20:08,000 Speaker 1: being poetic about it. But when we see the passage 352 00:20:08,160 --> 00:20:12,440 Speaker 1: of musicians and celebrities, you know, sometimes you might see 353 00:20:12,480 --> 00:20:15,399 Speaker 1: something that seems like a smartass meme, you know, a 354 00:20:15,400 --> 00:20:19,399 Speaker 1: hot take tweet, right that says like, si million people 355 00:20:19,440 --> 00:20:22,119 Speaker 1: are starving on the planet, and why are we you know, 356 00:20:22,200 --> 00:20:24,719 Speaker 1: why are you been out of shape about one person 357 00:20:24,760 --> 00:20:26,760 Speaker 1: passing way? But I think that's an unfair way to 358 00:20:26,800 --> 00:20:31,239 Speaker 1: look at it. Every human life is valuably replaceable. So um, 359 00:20:31,400 --> 00:20:34,880 Speaker 1: I'm grateful to uh, to Markis and all his work. 360 00:20:35,280 --> 00:20:37,600 Speaker 1: He did a really great guest vocal on one of 361 00:20:37,640 --> 00:20:41,360 Speaker 1: my favorite albums of the last I think probably ten 362 00:20:41,440 --> 00:20:45,840 Speaker 1: years or more, The Avalanches Wildflower. He did a very fun, 363 00:20:46,160 --> 00:20:50,639 Speaker 1: jokey song called the Noisy Eater. Um. He talks about 364 00:20:50,680 --> 00:20:53,760 Speaker 1: you know, eating his Captain crunch and cereal and you know, 365 00:20:54,680 --> 00:20:56,760 Speaker 1: poured the milk, made sure it was cold. It's like 366 00:20:56,800 --> 00:21:01,560 Speaker 1: really just cool, fun, goofy, classic bismarckie uh. And it's 367 00:21:01,600 --> 00:21:03,800 Speaker 1: a joy to listen to. And it also like matches 368 00:21:03,800 --> 00:21:07,760 Speaker 1: it up with the kids singing Come Together by the Beatles. Uh, 369 00:21:07,800 --> 00:21:09,400 Speaker 1: it's sped up kind of. It's a really cool track 370 00:21:09,440 --> 00:21:11,320 Speaker 1: if you haven't heard it, Yeah, it is cool. And 371 00:21:11,359 --> 00:21:13,840 Speaker 1: another genuinely said moment where you lose another person who 372 00:21:13,840 --> 00:21:17,280 Speaker 1: was highly influential in the music space. There was a 373 00:21:17,640 --> 00:21:23,160 Speaker 1: I'm gonna say the word been fun Olympic story. Uh. 374 00:21:23,200 --> 00:21:26,280 Speaker 1: It was aside from all the stuff coming out about 375 00:21:26,320 --> 00:21:29,800 Speaker 1: the growing list of participants who are testing positive not 376 00:21:29,920 --> 00:21:32,119 Speaker 1: for I think you made this joke, Ben, not for 377 00:21:32,240 --> 00:21:35,720 Speaker 1: p E d S, but for COVID. Um, there's a 378 00:21:35,840 --> 00:21:39,240 Speaker 1: rumor going around about the cardboard beds in the Olympic 379 00:21:39,359 --> 00:21:44,119 Speaker 1: village and how they're meant to prevent uh how did 380 00:21:44,160 --> 00:21:49,000 Speaker 1: I put it here cardio based bed related activities. Um. 381 00:21:49,880 --> 00:21:52,679 Speaker 1: But but it was proven to be just a rumor, 382 00:21:52,720 --> 00:21:55,600 Speaker 1: at least according to NBC New York and several other 383 00:21:55,640 --> 00:21:58,280 Speaker 1: outlets and The New York Times. Yeah, I got it 384 00:21:58,400 --> 00:22:02,159 Speaker 1: got debunked. But I'm glad it got debunked because it 385 00:22:02,200 --> 00:22:05,560 Speaker 1: means that people are at least not as naive as 386 00:22:05,560 --> 00:22:08,760 Speaker 1: they appeared in that initial story. Just talking with Doc 387 00:22:08,800 --> 00:22:11,840 Speaker 1: about this off air first reaction and I saw this 388 00:22:12,000 --> 00:22:16,520 Speaker 1: was Okay, you're telling me that the literally the most 389 00:22:16,720 --> 00:22:20,800 Speaker 1: physically in shape people on the planet, who also happened 390 00:22:20,800 --> 00:22:25,080 Speaker 1: to be the most psychologically driven people on the planet 391 00:22:25,240 --> 00:22:27,800 Speaker 1: are gonna want are gonna gonna want to have sex 392 00:22:28,119 --> 00:22:30,359 Speaker 1: because it is like a sex party at the Olympic village. 393 00:22:30,359 --> 00:22:32,160 Speaker 1: They're gonna want to have sex, and they're gonna stop 394 00:22:32,160 --> 00:22:34,320 Speaker 1: and go and go and do all. The bed doesn't 395 00:22:34,359 --> 00:22:40,360 Speaker 1: work really, really, someone who can like and someone who 396 00:22:40,400 --> 00:22:45,480 Speaker 1: is genuinely Captain America level of physical prowess is gonna 397 00:22:45,560 --> 00:22:48,199 Speaker 1: be like, I don't know how to have sex if 398 00:22:48,200 --> 00:22:50,560 Speaker 1: we're not on a bet. They know about the helicopter. 399 00:22:50,720 --> 00:22:54,520 Speaker 1: You don't need a bed for that. Uh so sorry, 400 00:22:55,080 --> 00:22:59,040 Speaker 1: keep it literally A reference from my old band was 401 00:22:59,080 --> 00:23:02,359 Speaker 1: an inside joke for just the lines of scissors guys. Okay, 402 00:23:02,520 --> 00:23:07,600 Speaker 1: sorry sorry, Um, yes, but you're correct. I think that's absurd. 403 00:23:07,920 --> 00:23:12,679 Speaker 1: But also, um, it is b y o P this 404 00:23:12,760 --> 00:23:15,640 Speaker 1: year bring your own prophylactic because they are giving out 405 00:23:15,840 --> 00:23:20,040 Speaker 1: many fewer condoms than normal at an Olympics, Like I was, 406 00:23:20,200 --> 00:23:23,880 Speaker 1: just fewer. They're not giving out Okay, so are they're 407 00:23:23,920 --> 00:23:28,520 Speaker 1: like condom quotas or condom rations. I think I think 408 00:23:28,600 --> 00:23:31,359 Speaker 1: last year's four and fifty thousand. Now it's a hundred 409 00:23:31,359 --> 00:23:35,439 Speaker 1: and sixty thousand or something like that. But I just 410 00:23:35,480 --> 00:23:38,760 Speaker 1: have this picture of every like there's a line and 411 00:23:38,800 --> 00:23:42,280 Speaker 1: it's all these athletes across the world. There's someone saying, Okay, 412 00:23:42,680 --> 00:23:50,520 Speaker 1: everybody gets three choose wisely that'd be great. Yes, hopefully 413 00:23:50,560 --> 00:23:54,800 Speaker 1: everyone stays safe at the Olympics in all the ways. Uh, 414 00:23:54,840 --> 00:23:57,880 Speaker 1: there were some chemical fears that came out because at 415 00:23:57,920 --> 00:24:01,680 Speaker 1: a six Flags water park in Texas, dozens of people 416 00:24:01,840 --> 00:24:04,879 Speaker 1: got super sick and nobody really understood why. And it 417 00:24:04,880 --> 00:24:07,200 Speaker 1: turns out there were some chemicals that shouldn't have been 418 00:24:07,240 --> 00:24:10,119 Speaker 1: in one of the what let's call them features of 419 00:24:10,160 --> 00:24:12,720 Speaker 1: the water park. Just you know, as we're going back 420 00:24:12,760 --> 00:24:16,200 Speaker 1: out there, just be aware that everything is still terrible 421 00:24:16,240 --> 00:24:18,959 Speaker 1: to some extent. So you can't even be safe at 422 00:24:19,000 --> 00:24:22,240 Speaker 1: the water park. I mean you're certainly never safe from 423 00:24:22,240 --> 00:24:24,879 Speaker 1: little kids. P at the word people that COVID or 424 00:24:24,960 --> 00:24:32,080 Speaker 1: no would never dip a toe into a wave pool parts. Well, 425 00:24:32,119 --> 00:24:34,360 Speaker 1: so that was a thing blah blah blah that happened. 426 00:24:34,800 --> 00:24:41,119 Speaker 1: Careful of carbon monoxide when you're using uh, generators, specifically 427 00:24:41,119 --> 00:24:45,280 Speaker 1: gas powered ones when you're at music festivals. And Russia 428 00:24:45,359 --> 00:24:48,199 Speaker 1: tested a missile and so did the US, and the 429 00:24:48,240 --> 00:24:52,840 Speaker 1: Cold Ore is still happening. Okay, So the major story 430 00:24:52,960 --> 00:24:58,120 Speaker 1: is that the country of India looks to be planning 431 00:24:58,359 --> 00:25:03,640 Speaker 1: at least on implementing some form of population control via 432 00:25:04,160 --> 00:25:07,840 Speaker 1: something that China implemented a while ago, attempting to reduce 433 00:25:07,960 --> 00:25:12,720 Speaker 1: the number of children individual families have, and they're doing 434 00:25:12,760 --> 00:25:18,520 Speaker 1: this with incentives. Interestingly enough, it feels almost like, uh, 435 00:25:18,600 --> 00:25:20,959 Speaker 1: I don't know, some kind of new credit card system 436 00:25:21,000 --> 00:25:23,920 Speaker 1: where you're going to get points for only having two 437 00:25:24,000 --> 00:25:30,040 Speaker 1: kids or for getting one of one of your partners sterilized. Uh. 438 00:25:30,080 --> 00:25:32,760 Speaker 1: At some point it sounds like very strange stuff. But 439 00:25:32,840 --> 00:25:36,080 Speaker 1: it's policies that are being put forth to solve a 440 00:25:36,160 --> 00:25:39,560 Speaker 1: perceived problem. Right, So let's talk about it. I'm gonna 441 00:25:39,560 --> 00:25:44,440 Speaker 1: be reading from Insider and India dot Com. I would 442 00:25:44,480 --> 00:25:49,000 Speaker 1: highly recommend the India dot Com article. It has a 443 00:25:49,040 --> 00:25:52,600 Speaker 1: pretty great set of two lists. One of them is 444 00:25:52,680 --> 00:25:55,880 Speaker 1: what you need to know about the population policy that's 445 00:25:55,880 --> 00:25:59,520 Speaker 1: being proposed, as well as the incentives and subsidies that 446 00:25:59,600 --> 00:26:04,960 Speaker 1: are being offered for voluntary sterilization Oh boy, sounds weird 447 00:26:05,000 --> 00:26:09,320 Speaker 1: to even stay right. At least it's not involuntary sterilization. 448 00:26:09,359 --> 00:26:14,280 Speaker 1: At least, it's not like state mandated sterilization. Its correct, 449 00:26:15,359 --> 00:26:19,239 Speaker 1: completely correct. Now, these policies are being put forth in 450 00:26:19,480 --> 00:26:24,439 Speaker 1: two of the states within India, Uttar Pradesh as well 451 00:26:24,480 --> 00:26:29,840 Speaker 1: as a PSALM, which is in northeastern India. Now, these 452 00:26:29,920 --> 00:26:35,240 Speaker 1: haven't been adopted necessarily, if that makes sense. These are proposals. 453 00:26:35,320 --> 00:26:38,000 Speaker 1: At least from my understanding, these are proposals and they're 454 00:26:38,040 --> 00:26:41,800 Speaker 1: gonna they they want them to run until from now until. 455 00:26:43,480 --> 00:26:46,800 Speaker 1: That's the concept here. These proposals were put forth on 456 00:26:46,920 --> 00:26:52,160 Speaker 1: July eleven, which is a World Population Day. Yeah, population, 457 00:26:52,240 --> 00:26:56,320 Speaker 1: let's let's control it. There are some issues here. The 458 00:26:56,400 --> 00:27:00,399 Speaker 1: experts at the u N and uni SEF estimate that 459 00:27:00,440 --> 00:27:03,960 Speaker 1: around twenty five million children are born every year in India. 460 00:27:04,680 --> 00:27:07,840 Speaker 1: That accounts for a fifth of the world's annual births 461 00:27:07,840 --> 00:27:12,720 Speaker 1: according to Insider, and essentially India in these two particular 462 00:27:12,800 --> 00:27:16,399 Speaker 1: states are attempting just to reduce the number of people 463 00:27:16,800 --> 00:27:20,679 Speaker 1: entering into the the economic system, the system of you know, 464 00:27:21,560 --> 00:27:23,639 Speaker 1: the things we've talked about on this show before. For 465 00:27:23,680 --> 00:27:28,160 Speaker 1: each person there comes certain costs for state or country, 466 00:27:28,760 --> 00:27:34,480 Speaker 1: local municipality, as well as for the family itself. Weird 467 00:27:34,560 --> 00:27:38,000 Speaker 1: to conceptualize, but let's talk about some of the things 468 00:27:38,160 --> 00:27:42,280 Speaker 1: that they want to implement. First. They want to increase 469 00:27:42,600 --> 00:27:47,240 Speaker 1: the accessibility of contraceptive measures, things that would be offered 470 00:27:47,240 --> 00:27:50,560 Speaker 1: in the family planning program that exists there in several states. 471 00:27:51,240 --> 00:27:55,159 Speaker 1: And they also want to provide a safe avenue for 472 00:27:55,200 --> 00:27:59,480 Speaker 1: anyone seeking to get an abortion. So, while depending on 473 00:27:59,560 --> 00:28:03,680 Speaker 1: where you and politically, that's such a politicized, uh topic, 474 00:28:04,080 --> 00:28:05,840 Speaker 1: at least here in the United States, and I would 475 00:28:05,840 --> 00:28:09,520 Speaker 1: say the world over, giving the option for a person 476 00:28:09,560 --> 00:28:12,800 Speaker 1: who wants to have an abortion to get an abortion 477 00:28:12,920 --> 00:28:15,399 Speaker 1: is probably a good thing. They're also looking to do 478 00:28:15,440 --> 00:28:18,440 Speaker 1: a little bit of propaganda maybe, I would say. They're 479 00:28:18,440 --> 00:28:22,320 Speaker 1: setting up these things called health clubs in schools and 480 00:28:22,760 --> 00:28:25,720 Speaker 1: the well, the whole point there is to teach kids 481 00:28:26,000 --> 00:28:29,480 Speaker 1: about how to keep the population stable and how to 482 00:28:29,760 --> 00:28:33,639 Speaker 1: reach stabilization through some of these policies. There's other stuff 483 00:28:33,680 --> 00:28:36,199 Speaker 1: here that we can get into. It's a draft of 484 00:28:36,240 --> 00:28:39,440 Speaker 1: a bill right now, and the public is going to 485 00:28:39,520 --> 00:28:43,120 Speaker 1: be giving suggestions until guess what, the day that we 486 00:28:43,160 --> 00:28:46,880 Speaker 1: record this episode, So I guess it's too late, unfortunately, 487 00:28:47,520 --> 00:28:50,560 Speaker 1: not really giving anyone awareness out there in India, just 488 00:28:50,680 --> 00:28:54,120 Speaker 1: letting you know that this is happening, so not to derailists, 489 00:28:54,120 --> 00:28:59,120 Speaker 1: but just to interject very briefly, this is, as you 490 00:28:59,160 --> 00:29:03,920 Speaker 1: can imagine, very controversial in some places. Uh. There have 491 00:29:04,040 --> 00:29:09,880 Speaker 1: been political analysts who find that it is islamophobic. They're 492 00:29:09,960 --> 00:29:15,040 Speaker 1: worried that it is targeting and growing Muslim population. And 493 00:29:15,200 --> 00:29:19,640 Speaker 1: also to the point about incentives, the the opt in, 494 00:29:19,800 --> 00:29:24,720 Speaker 1: opt out organ donation discount for driver's license that we 495 00:29:24,760 --> 00:29:28,720 Speaker 1: always talk about, that is that is a very milk 496 00:29:28,840 --> 00:29:34,240 Speaker 1: toast example of how incentives can push you towards a mandate. 497 00:29:34,400 --> 00:29:37,600 Speaker 1: Just like in Gattaga. Remember it wasn't illegal to have 498 00:29:37,640 --> 00:29:41,160 Speaker 1: a kid who wasn't genetically modified. The insurance was just 499 00:29:41,200 --> 00:29:44,160 Speaker 1: so expensive that their lives would be terrible if they 500 00:29:44,200 --> 00:29:47,600 Speaker 1: were born. So how far do these incentives go, Matt 501 00:29:47,640 --> 00:29:51,520 Speaker 1: in this proposed bill, Well, they go pretty far. I'm 502 00:29:51,520 --> 00:29:54,080 Speaker 1: going to read directly from India dot Com. The title 503 00:29:54,200 --> 00:29:57,720 Speaker 1: is Yogi d to Enough unveils new population policy for 504 00:29:57,960 --> 00:30:02,360 Speaker 1: u P says every community taken care of. Okay, so 505 00:30:02,920 --> 00:30:06,320 Speaker 1: they're saying that parents who choose to limit their family 506 00:30:06,360 --> 00:30:09,640 Speaker 1: to just two children, similar to the policies in China 507 00:30:09,680 --> 00:30:13,120 Speaker 1: the to child policy that have recently been changed altered 508 00:30:13,120 --> 00:30:16,040 Speaker 1: to three I believe, I think, I think that's correct. 509 00:30:16,080 --> 00:30:19,480 Speaker 1: In China. They will essentially be able to get more 510 00:30:19,760 --> 00:30:23,520 Speaker 1: government money for several things housing they call them housing 511 00:30:23,600 --> 00:30:28,640 Speaker 1: schemes UM, as well as contributions from their employers, so 512 00:30:28,760 --> 00:30:32,520 Speaker 1: personal contributions to the individual or the family from the 513 00:30:32,560 --> 00:30:39,000 Speaker 1: employer UM also promotions within wherever they're working, if they're 514 00:30:39,000 --> 00:30:42,000 Speaker 1: working for the government or with the government. There are 515 00:30:42,000 --> 00:30:45,720 Speaker 1: also stuff in there about reducing what you have to 516 00:30:45,760 --> 00:30:50,360 Speaker 1: pay for water, electricity, house taxes, home loans, and other 517 00:30:50,480 --> 00:30:53,600 Speaker 1: stuff that you would need to run a house that contains, 518 00:30:53,800 --> 00:30:57,120 Speaker 1: you know, just two children rather than more than two children. 519 00:30:57,560 --> 00:30:59,960 Speaker 1: And one of the most I don't know, potentially dan 520 00:31:00,000 --> 00:31:04,360 Speaker 1: imaging things within this proposal for a family that ends 521 00:31:04,440 --> 00:31:07,400 Speaker 1: up having more than two children is this last one 522 00:31:07,440 --> 00:31:10,840 Speaker 1: that they list on India dot com. Children of a 523 00:31:10,880 --> 00:31:15,120 Speaker 1: family of two would have free education up to graduation 524 00:31:15,240 --> 00:31:20,400 Speaker 1: level quote scholarship for higher studies in the cases of 525 00:31:20,440 --> 00:31:24,480 Speaker 1: a CURL a female child here according to India dot Com, 526 00:31:24,520 --> 00:31:28,720 Speaker 1: and preference to the single child in government jobs UH 527 00:31:28,760 --> 00:31:31,640 Speaker 1: and other other benefits that couples with a single child 528 00:31:31,640 --> 00:31:35,040 Speaker 1: will receive. So they're they're even benefits for reducing from 529 00:31:35,080 --> 00:31:38,360 Speaker 1: two to one. I don't know, guys, Yeah, there was 530 00:31:38,400 --> 00:31:42,760 Speaker 1: an earlier bill in twenty bill is a little bit 531 00:31:42,840 --> 00:31:47,800 Speaker 1: different because the twenty nineteen bill that was proposed not 532 00:31:48,000 --> 00:31:51,280 Speaker 1: you just described what are called the carrots, right, the incentence, 533 00:31:51,320 --> 00:31:55,720 Speaker 1: the rewards. The Goodies Bill included what would be known 534 00:31:55,760 --> 00:31:59,360 Speaker 1: as the stick, the penalties for couples that did not 535 00:32:00,080 --> 00:32:03,959 Speaker 1: adhere to the proposed to child policy. You wouldn't be 536 00:32:04,120 --> 00:32:09,800 Speaker 1: able to run for office, you wouldn't be able to 537 00:32:09,880 --> 00:32:14,440 Speaker 1: get certain government jobs, or get promoted, or get certain 538 00:32:14,480 --> 00:32:17,600 Speaker 1: government benefits. Like they were coming down hard on people 539 00:32:17,960 --> 00:32:23,400 Speaker 1: and incentives, including the one time cash incentive. Maybe one 540 00:32:23,440 --> 00:32:26,640 Speaker 1: of the one of their best chances of enacting this policy, 541 00:32:26,680 --> 00:32:30,800 Speaker 1: regardless of how you feel about it, because the family 542 00:32:30,840 --> 00:32:35,760 Speaker 1: and the children are such a support network for for people. 543 00:32:36,160 --> 00:32:39,640 Speaker 1: And if you look at the ongoing problem of female 544 00:32:39,720 --> 00:32:43,040 Speaker 1: and fanticide in India, then you'll see why they have 545 00:32:43,240 --> 00:32:47,920 Speaker 1: those um why they have those sexual distinctions right for 546 00:32:48,160 --> 00:32:51,920 Speaker 1: a female child. They say, you know, you get these 547 00:32:51,920 --> 00:32:57,640 Speaker 1: certain benefits because due to poverty and the dowry system, 548 00:32:57,760 --> 00:33:01,480 Speaker 1: and multiple other factors. There are families that have a 549 00:33:01,600 --> 00:33:05,520 Speaker 1: higher than average chance of this like a learning the 550 00:33:05,560 --> 00:33:07,880 Speaker 1: sex of a child and then aborting it if it 551 00:33:08,040 --> 00:33:11,640 Speaker 1: is a if it is biological female. So they're fighting 552 00:33:11,680 --> 00:33:17,160 Speaker 1: against uh, history spanning centuries. So does it sound like 553 00:33:17,280 --> 00:33:19,280 Speaker 1: I don't want to purge them up in? It sounds 554 00:33:19,280 --> 00:33:23,160 Speaker 1: to me like maybe you're almost uh saying that there's 555 00:33:23,160 --> 00:33:27,480 Speaker 1: a little bit of humanitarianism in this policy, like it 556 00:33:27,560 --> 00:33:30,760 Speaker 1: could be much more draconian, but instead it's like, Okay, 557 00:33:30,800 --> 00:33:32,640 Speaker 1: we know we have a population problem, we know we 558 00:33:32,680 --> 00:33:37,479 Speaker 1: have these historical issues with the way female children are treated. 559 00:33:38,080 --> 00:33:39,640 Speaker 1: We have to do something about it. But I think 560 00:33:39,640 --> 00:33:42,040 Speaker 1: maybe they could have gone farther to their credit. I mean, 561 00:33:42,160 --> 00:33:44,760 Speaker 1: it is creepy obviously and not something we think about 562 00:33:44,800 --> 00:33:46,800 Speaker 1: here in the States. But I don't know what are 563 00:33:46,800 --> 00:33:51,320 Speaker 1: your thoughts there been? Well, the question here is also yeah, 564 00:33:51,520 --> 00:33:55,120 Speaker 1: just in terms of human interest, how would you feel 565 00:33:55,280 --> 00:33:57,760 Speaker 1: if you, for anybody not living in India, how would 566 00:33:57,800 --> 00:34:00,320 Speaker 1: you feel if your government told you there was a 567 00:34:00,400 --> 00:34:03,600 Speaker 1: limit on the number of children you could have? Uh? 568 00:34:03,920 --> 00:34:06,880 Speaker 1: What what would your reaction be? And is there an 569 00:34:06,880 --> 00:34:10,080 Speaker 1: official reasoning that would get you on board with it? 570 00:34:10,719 --> 00:34:14,359 Speaker 1: Because I mean, if you imagine, think of it this way. 571 00:34:14,520 --> 00:34:19,400 Speaker 1: The average household size in India is four point eight 572 00:34:20,120 --> 00:34:23,880 Speaker 1: though that doesn't mean necessarily that it's two parents and 573 00:34:23,920 --> 00:34:27,439 Speaker 1: then two point eight kids, but it does it does 574 00:34:27,600 --> 00:34:30,680 Speaker 1: indicate that there, of course, there would be pushed back. 575 00:34:31,200 --> 00:34:36,320 Speaker 1: It's it's a dangerous kind of law to enact, even 576 00:34:36,560 --> 00:34:39,200 Speaker 1: if it has noble intentions, and it can be a 577 00:34:39,200 --> 00:34:42,800 Speaker 1: painful auto enact. The incentives are great, you know, to 578 00:34:42,800 --> 00:34:47,120 Speaker 1: to help people toward that move, but also consider the 579 00:34:47,200 --> 00:34:52,200 Speaker 1: long tail ramifications of China's policy is similar policy. Right, 580 00:34:52,239 --> 00:34:56,920 Speaker 1: the gender divide is crazy there right now in terms 581 00:34:57,000 --> 00:35:01,640 Speaker 1: of the male population being skewed because people wanted a 582 00:35:01,719 --> 00:35:08,680 Speaker 1: male air right. This Uh, it's it's incredibly difficult to 583 00:35:08,800 --> 00:35:11,200 Speaker 1: figure out an equitable way to do this, you know, 584 00:35:11,280 --> 00:35:14,239 Speaker 1: But I think I don't know, Matt. We know the 585 00:35:14,280 --> 00:35:17,480 Speaker 1: inspiration behind this. Well, there are a lot of people 586 00:35:17,520 --> 00:35:20,839 Speaker 1: in India. It is currently, I believe, the second most 587 00:35:20,920 --> 00:35:26,279 Speaker 1: populous country that exists outside of China, and in that 588 00:35:26,400 --> 00:35:29,880 Speaker 1: one state, Uttar Pradesh, there are two and forty million 589 00:35:29,920 --> 00:35:33,880 Speaker 1: people and India overall, at least according to the unis 590 00:35:33,960 --> 00:35:37,840 Speaker 1: F and the u N, it will overtake China as 591 00:35:37,880 --> 00:35:42,799 Speaker 1: the world's most populous country by so you can see that, 592 00:35:43,640 --> 00:35:47,440 Speaker 1: you know, they likely want to reduce those numbers if 593 00:35:47,440 --> 00:35:50,239 Speaker 1: they can, or reduce the trajectory if they can a 594 00:35:50,280 --> 00:35:54,080 Speaker 1: little bit. As we as we said, there are issues, real, 595 00:35:54,200 --> 00:35:58,160 Speaker 1: real issues when you know you increase a population and 596 00:35:58,520 --> 00:36:02,600 Speaker 1: if that is outpaced, seeing your ability as a country, 597 00:36:02,719 --> 00:36:05,040 Speaker 1: as a on a state level, on a local level, 598 00:36:05,080 --> 00:36:07,960 Speaker 1: to feed everybody, to get everybody jobs, to do everything, 599 00:36:08,640 --> 00:36:11,520 Speaker 1: uh that you know each individual family will need. I 600 00:36:11,520 --> 00:36:14,040 Speaker 1: don't know this. It's really messed up though, just thinking 601 00:36:14,040 --> 00:36:17,680 Speaker 1: of having to do this, Like I'm imagining the meetings 602 00:36:17,680 --> 00:36:20,080 Speaker 1: where people are saying, well, we've got to find a solution. 603 00:36:20,160 --> 00:36:22,279 Speaker 1: What does our solution look like? And how do we 604 00:36:22,480 --> 00:36:26,840 Speaker 1: how do we do this without being evil? Um? And 605 00:36:26,880 --> 00:36:29,680 Speaker 1: I guess this is what you come up with. Incentives 606 00:36:29,719 --> 00:36:35,359 Speaker 1: to only have two children or fewer, and bad things 607 00:36:35,360 --> 00:36:38,759 Speaker 1: that happen if you don't do that. Yeah. One activist, 608 00:36:39,239 --> 00:36:43,680 Speaker 1: Kevia Christian said, every time there's population control, it's led 609 00:36:43,719 --> 00:36:47,920 Speaker 1: to violence against women's bodies. Right there isn't There's a 610 00:36:48,000 --> 00:36:56,120 Speaker 1: huge opportunity for corruption for violence. One point to establish 611 00:36:56,239 --> 00:36:59,000 Speaker 1: the issue here and part one of the reasons I 612 00:36:59,160 --> 00:37:02,400 Speaker 1: imagine new people living in the country are concerned about 613 00:37:02,400 --> 00:37:08,000 Speaker 1: this is that femicide became such an acknowledged problem that 614 00:37:08,080 --> 00:37:14,479 Speaker 1: back in nineteen the country of India and what's called 615 00:37:14,560 --> 00:37:18,560 Speaker 1: prenatal sex determination. You know how if you're expecting a child, 616 00:37:18,680 --> 00:37:21,120 Speaker 1: you can go to your doctor and they can, you know, 617 00:37:21,400 --> 00:37:23,640 Speaker 1: do some doctor magic and then they'll be able to 618 00:37:23,680 --> 00:37:26,799 Speaker 1: tell you, you you know what, what they believe the gender is. Uh. 619 00:37:26,840 --> 00:37:28,960 Speaker 1: And you know, some people want to be surprised. Some 620 00:37:29,000 --> 00:37:33,440 Speaker 1: people would rather know in advance. That doesn't happen in India. 621 00:37:33,680 --> 00:37:36,120 Speaker 1: It's crazy. Put yourself in the position of somebody who 622 00:37:36,160 --> 00:37:40,000 Speaker 1: have to think about that if you've had your second child, 623 00:37:40,360 --> 00:37:43,640 Speaker 1: you either have to convince your partner to become sterilized, 624 00:37:43,880 --> 00:37:50,200 Speaker 1: get sterilized yourself or risk real financial problems perhaps, or 625 00:37:51,200 --> 00:37:53,880 Speaker 1: have to get an abortion at some point if you 626 00:37:53,920 --> 00:37:56,800 Speaker 1: do get pregnant again. The choices you would be faced 627 00:37:56,800 --> 00:38:00,399 Speaker 1: with no matter what, if you end up having two 628 00:38:00,480 --> 00:38:04,919 Speaker 1: children right immediately after that, um, none of them look 629 00:38:05,000 --> 00:38:08,839 Speaker 1: that great on paper. So yeah, we'd love to know 630 00:38:09,040 --> 00:38:12,240 Speaker 1: what you think, and especially if you live in India 631 00:38:12,360 --> 00:38:14,480 Speaker 1: or if you're watching this happen, if you lived in 632 00:38:14,560 --> 00:38:16,640 Speaker 1: China under the two child policy. If you've just got 633 00:38:16,719 --> 00:38:19,480 Speaker 1: any insight, we'd love to hear from you, um, but 634 00:38:19,600 --> 00:38:21,800 Speaker 1: for now, we're going to take a quick break. It 635 00:38:21,840 --> 00:38:30,960 Speaker 1: will be right back with more strange news. And we've 636 00:38:31,000 --> 00:38:35,319 Speaker 1: returned question here. Uh, when's the last time you guys 637 00:38:35,320 --> 00:38:38,080 Speaker 1: looked at your smartphones? A couple of seconds, a couple 638 00:38:38,080 --> 00:38:40,680 Speaker 1: of seconds ago, what about you know? Literally just like 639 00:38:40,760 --> 00:38:44,160 Speaker 1: one second ago a commercial break. It pops up as 640 00:38:44,200 --> 00:38:46,000 Speaker 1: we're sitting here recording. I've got it kind of over 641 00:38:46,040 --> 00:38:47,879 Speaker 1: to the right and everyone. So it just lights up 642 00:38:47,920 --> 00:38:50,400 Speaker 1: when an email comes through, and I was like, okay, 643 00:38:51,280 --> 00:38:53,440 Speaker 1: catches your eye, you know, right right right there. It's 644 00:38:53,480 --> 00:38:56,480 Speaker 1: like it's like a beacon. It's always calling to you, yep, 645 00:38:56,600 --> 00:39:01,120 Speaker 1: and it's designed to do so. It's very successful. Pretty 646 00:39:01,200 --> 00:39:05,440 Speaker 1: much any country that has widespread smartphone use, you will 647 00:39:05,480 --> 00:39:09,719 Speaker 1: look increasingly odd not being on your phone. Right, You're like, 648 00:39:09,800 --> 00:39:12,880 Speaker 1: you forget your phone. You go to the airport and 649 00:39:12,960 --> 00:39:15,920 Speaker 1: you're standing in line, not looking at your phone, just 650 00:39:15,960 --> 00:39:19,480 Speaker 1: sort of staring off into space like a psychopath counting 651 00:39:19,480 --> 00:39:22,879 Speaker 1: the number of trash cans. You lunatic, right, It's it's 652 00:39:22,960 --> 00:39:25,799 Speaker 1: unusual now, and I think this is an important thing 653 00:39:25,880 --> 00:39:29,760 Speaker 1: to think about when we look into our last story, 654 00:39:29,960 --> 00:39:33,200 Speaker 1: the iceberg that somehow is also a web because I 655 00:39:33,360 --> 00:39:36,640 Speaker 1: made the worst metaphor ever on air. Uh, it's this. 656 00:39:38,000 --> 00:39:43,160 Speaker 1: It was a massive data leak recently that uncovered human 657 00:39:43,320 --> 00:39:47,359 Speaker 1: rights abuses on an enormous scale. We do not know 658 00:39:47,640 --> 00:39:50,520 Speaker 1: at the time of recording. We do not know how 659 00:39:51,239 --> 00:39:55,040 Speaker 1: widespread this is. We don't know how many people died 660 00:39:55,480 --> 00:39:59,120 Speaker 1: as a result of this, but we will give you 661 00:39:59,239 --> 00:40:03,640 Speaker 1: the ends and out of the story. There's a outfit 662 00:40:03,680 --> 00:40:05,600 Speaker 1: you may not have heard of called n s O 663 00:40:05,880 --> 00:40:10,319 Speaker 1: Group Technologies, which stands for Niv Shalev and Omar. It 664 00:40:10,440 --> 00:40:14,400 Speaker 1: is an Israeli technology firm that created a spyware program 665 00:40:14,440 --> 00:40:20,319 Speaker 1: called vegas Is. Vegas Is is scary because no matter 666 00:40:20,400 --> 00:40:23,040 Speaker 1: how good your security is on your phone, whether you 667 00:40:23,080 --> 00:40:26,080 Speaker 1: have an iPhone or an Android or something else, this 668 00:40:26,120 --> 00:40:31,200 Speaker 1: stuff can be covertly installed without you having to click 669 00:40:31,560 --> 00:40:36,560 Speaker 1: on anything. It enables keystroke monitoring of all communications from 670 00:40:36,600 --> 00:40:40,239 Speaker 1: your phone. It also allows the It also allows the 671 00:40:40,320 --> 00:40:44,880 Speaker 1: user to track phone call content and track location. It 672 00:40:44,960 --> 00:40:50,320 Speaker 1: allows the user to hijack mobile phones, microphone, and camera, 673 00:40:50,719 --> 00:40:55,160 Speaker 1: turning it into a constant surveillance device. This has been rumored. 674 00:40:55,360 --> 00:40:59,040 Speaker 1: Stuff like this has been rumored for since the advent 675 00:40:59,640 --> 00:41:06,319 Speaker 1: of these mobile devices. However, this is absolute proof. This 676 00:41:06,440 --> 00:41:10,280 Speaker 1: affects multiple things. We don't know how far it goes. 677 00:41:11,040 --> 00:41:15,440 Speaker 1: We don't know what exactly tech companies can do to 678 00:41:15,680 --> 00:41:18,560 Speaker 1: stop it. But I'd like to give us just a 679 00:41:18,640 --> 00:41:22,480 Speaker 1: little bit of a timeline as we dive in. So, 680 00:41:22,560 --> 00:41:25,880 Speaker 1: first off, n s O was founded in They've been 681 00:41:25,920 --> 00:41:29,400 Speaker 1: around for more than a decade now, and they claim 682 00:41:29,520 --> 00:41:34,440 Speaker 1: that this technology they're selling is to authorized governments and 683 00:41:34,520 --> 00:41:38,319 Speaker 1: this will help them combat terrorism and organized crime and 684 00:41:38,400 --> 00:41:42,480 Speaker 1: stuff like that. But according to several reports, including a 685 00:41:42,520 --> 00:41:46,440 Speaker 1: piece by Amnesty International, software that was created by an 686 00:41:46,560 --> 00:41:51,080 Speaker 1: ESO was used in attacks against people you wouldn't ordinarily 687 00:41:51,200 --> 00:41:55,720 Speaker 1: consider terrorists, people like journalists who were reported on human 688 00:41:55,800 --> 00:41:59,839 Speaker 1: rights abuses, people like human rights activists who are reported 689 00:42:00,040 --> 00:42:02,960 Speaker 1: on human rights abuses. There's a little bit of a pattern, 690 00:42:03,239 --> 00:42:08,080 Speaker 1: is what we're saying. Uh, there's also evidence that not conclusive, 691 00:42:08,120 --> 00:42:10,759 Speaker 1: but there's evidence that we can trace the use of 692 00:42:10,800 --> 00:42:16,120 Speaker 1: pagases to the murder of specific people such as Jamal Kashagi, 693 00:42:16,200 --> 00:42:22,960 Speaker 1: who was vivisected, dismembered while alive by the Saudi government. Uh, 694 00:42:23,040 --> 00:42:27,120 Speaker 1: the US refused to do anything, and as we record today, UH, 695 00:42:27,200 --> 00:42:31,200 Speaker 1: the Saudi government has experienced no repercussions for the state 696 00:42:31,239 --> 00:42:35,080 Speaker 1: sanctioned murder. Uh. There was another journalist that will get 697 00:42:35,120 --> 00:42:40,200 Speaker 1: to in a moment who also was pretty pretty definitely 698 00:42:41,040 --> 00:42:46,799 Speaker 1: murdered by people using this uh, using this software. And 699 00:42:47,360 --> 00:42:50,160 Speaker 1: this brings us to the first debate. So now that 700 00:42:50,200 --> 00:42:52,080 Speaker 1: we have the now we have the lay of the land, 701 00:42:52,080 --> 00:42:55,359 Speaker 1: I wanted to ask you all, Matt Noel, do you 702 00:42:55,480 --> 00:43:00,359 Speaker 1: think in ESSO should bear any responsibility for these for 703 00:43:00,400 --> 00:43:04,200 Speaker 1: this targeting, for these human rights abuses. That's tough, man, 704 00:43:04,239 --> 00:43:09,040 Speaker 1: because they built a weapon that they assured everyone would 705 00:43:09,120 --> 00:43:14,880 Speaker 1: only be used by you know, government officials, by intelligence 706 00:43:15,120 --> 00:43:18,200 Speaker 1: agencies about all that kind of stuff. So they said 707 00:43:18,200 --> 00:43:23,000 Speaker 1: about the face scanning software, radar detectors and tasers and 708 00:43:23,080 --> 00:43:25,640 Speaker 1: always you make the thing with the best of intention, 709 00:43:25,680 --> 00:43:27,759 Speaker 1: and you're still responsible for if it finds itself into 710 00:43:27,800 --> 00:43:31,040 Speaker 1: the hands of bad actors. I agree. I'm just saying 711 00:43:31,080 --> 00:43:33,239 Speaker 1: it's not clear cut, right, So it's not I mean, 712 00:43:33,239 --> 00:43:35,160 Speaker 1: I'm not I'm not disagreeing with you. I'm just saying, 713 00:43:35,200 --> 00:43:38,279 Speaker 1: like it's something we see historically that pr line of 714 00:43:38,400 --> 00:43:41,520 Speaker 1: oh we made this only for you know, the use 715 00:43:41,560 --> 00:43:44,600 Speaker 1: by seasoned professionals in X industry with that's not how 716 00:43:44,600 --> 00:43:46,799 Speaker 1: technology works. I mean, you don't always get to keep 717 00:43:46,800 --> 00:43:50,120 Speaker 1: the genie hidden behind paywall or whatever. You know, the 718 00:43:50,239 --> 00:43:53,120 Speaker 1: fire can burn you as easily as it can warm 719 00:43:53,160 --> 00:43:57,640 Speaker 1: you or cook your food, right, and anybody can ride 720 00:43:57,640 --> 00:44:01,920 Speaker 1: in a car. But we have seen, at least my understanding, 721 00:44:01,960 --> 00:44:05,839 Speaker 1: been in several of the cases where someone died even 722 00:44:05,840 --> 00:44:09,360 Speaker 1: though it's unknown if this Pegasus had anything to do 723 00:44:09,400 --> 00:44:12,600 Speaker 1: with their actual death. But there but Pegasus was used 724 00:44:12,600 --> 00:44:15,200 Speaker 1: on several phones, are close to several people like you said, 725 00:44:15,280 --> 00:44:20,120 Speaker 1: Ka Shogi and some other journalists where it appears that 726 00:44:20,200 --> 00:44:24,239 Speaker 1: there was a state actor looking into one of these 727 00:44:24,280 --> 00:44:29,560 Speaker 1: individuals and then they ended up dying. Yeah, exactly. I'd 728 00:44:29,560 --> 00:44:33,759 Speaker 1: like to thank the excellent reporters at the Guardians, specifically 729 00:44:33,840 --> 00:44:38,279 Speaker 1: David peg Paul Lewis, Michael Sophie and Nina Lakhani who 730 00:44:38,440 --> 00:44:44,239 Speaker 1: all collaborated in in breaking this story. What kind of 731 00:44:44,360 --> 00:44:47,759 Speaker 1: terrorists are these governments hunting once they get a hold 732 00:44:47,760 --> 00:44:53,520 Speaker 1: of Pegasus? Oh, you know, people like lawyers, religious figures, academics, 733 00:44:53,760 --> 00:44:59,080 Speaker 1: business people, diplomats, heads of state, senior government officials. That 734 00:44:59,160 --> 00:45:03,799 Speaker 1: doesn't quite sound like isis to me. And this reporting 735 00:45:04,239 --> 00:45:09,040 Speaker 1: is ongoing now, I highly recommend checking out a story 736 00:45:09,080 --> 00:45:14,000 Speaker 1: that broke just yesterday by Paul Lewis over at the Guardian. 737 00:45:14,840 --> 00:45:19,040 Speaker 1: And from what we can see, they're going to continue reporting. 738 00:45:19,080 --> 00:45:22,240 Speaker 1: Pay attention to them because over the next few days 739 00:45:23,120 --> 00:45:27,440 Speaker 1: they'll be revealing identities of specific people have been targeted. 740 00:45:27,760 --> 00:45:33,759 Speaker 1: They're also going to be drilling down into how governments 741 00:45:34,200 --> 00:45:39,959 Speaker 1: rationalized by it on their citizens, how these seemingly innocuous 742 00:45:40,000 --> 00:45:46,520 Speaker 1: processes can become something dangerous. The problem right now is 743 00:45:46,920 --> 00:45:49,600 Speaker 1: if you want to know whether the phone of someone 744 00:45:49,680 --> 00:45:53,600 Speaker 1: whose number appears on the leak was actually targeted by 745 00:45:53,600 --> 00:45:56,400 Speaker 1: a government or whether it was successfully hacked, you'd have 746 00:45:56,480 --> 00:45:58,879 Speaker 1: to get ahold of the phone. You'd have to pull 747 00:45:58,920 --> 00:46:02,920 Speaker 1: a little habeas corp us and do some forensic analysis. 748 00:46:02,960 --> 00:46:05,680 Speaker 1: But the journalists have already found because you know, journalists 749 00:46:05,680 --> 00:46:08,960 Speaker 1: talked to each other, their colleagues, they've already found some 750 00:46:09,120 --> 00:46:14,759 Speaker 1: examples of phones that contain signs of vegass activity. And 751 00:46:14,840 --> 00:46:16,880 Speaker 1: we know that right now this appears to be the 752 00:46:17,080 --> 00:46:23,279 Speaker 1: most extreme kind of counter espionage measure since since the 753 00:46:23,360 --> 00:46:27,720 Speaker 1: days of Edward Snowden. And now we get to the web, 754 00:46:28,280 --> 00:46:32,600 Speaker 1: some web parts, because right as this story broke, the 755 00:46:32,719 --> 00:46:37,920 Speaker 1: United States in the United Kingdom released accusations that China 756 00:46:38,120 --> 00:46:41,799 Speaker 1: was behind a big hack and Microsoft Exchange. This is 757 00:46:41,840 --> 00:46:44,280 Speaker 1: causing some of the more cynical people in the global 758 00:46:44,320 --> 00:46:48,720 Speaker 1: crowd to say, hey, what about the fact basically proven 759 00:46:49,239 --> 00:46:53,080 Speaker 1: this software has been used to kill people, which you 760 00:46:53,200 --> 00:46:57,239 Speaker 1: can't say yet about the Microsoft Exchange hack. So were 761 00:46:57,280 --> 00:47:00,600 Speaker 1: they trying to get people to pay it tension to 762 00:47:00,760 --> 00:47:05,560 Speaker 1: something else? Um? Also, what about what about Julian Osage, 763 00:47:05,840 --> 00:47:08,680 Speaker 1: One of the witnesses in his case, recently said they lied. 764 00:47:09,680 --> 00:47:11,879 Speaker 1: They lied because the main goal is to get him 765 00:47:11,920 --> 00:47:14,040 Speaker 1: extra diet into the U S where he will die 766 00:47:14,040 --> 00:47:17,640 Speaker 1: in prison. A lot of stuff is happening in the 767 00:47:18,239 --> 00:47:21,719 Speaker 1: sphere of technology and espionage now, and I think a 768 00:47:21,800 --> 00:47:25,120 Speaker 1: lot of us, a lot of people need to learn 769 00:47:25,600 --> 00:47:29,799 Speaker 1: more about it. One thing is obvious. While in ESSO 770 00:47:29,960 --> 00:47:33,600 Speaker 1: group may not be aware. Just to be overly fair, 771 00:47:34,480 --> 00:47:38,640 Speaker 1: maybe they aren't aware of what's happening right Maybe there, 772 00:47:38,640 --> 00:47:43,520 Speaker 1: Maybe they're like a an international arms company. As you said, 773 00:47:43,560 --> 00:47:47,400 Speaker 1: Matt sells weapons and then says, oh I didn't know. Wow, 774 00:47:47,520 --> 00:47:58,879 Speaker 1: those missiles explode. That's it's sculpture. Yeah, It's like when 775 00:47:58,880 --> 00:48:00,480 Speaker 1: you go into and you go went to the head 776 00:48:00,520 --> 00:48:03,319 Speaker 1: shop years ago and you had to say, oh, could 777 00:48:03,400 --> 00:48:06,319 Speaker 1: I try out a water pipe? And you would get 778 00:48:06,600 --> 00:48:11,640 Speaker 1: smoking tobacco please you dare you? Yeah, you get kicked 779 00:48:11,640 --> 00:48:13,520 Speaker 1: out if you got if you called it a bong. 780 00:48:13,880 --> 00:48:16,480 Speaker 1: So there's a lot of this idea that it is 781 00:48:16,640 --> 00:48:20,799 Speaker 1: used for national security may be true, but what it's 782 00:48:21,000 --> 00:48:24,800 Speaker 1: looking like right now is that it also is being 783 00:48:24,920 --> 00:48:28,520 Speaker 1: used for a different definition of national security, which is 784 00:48:28,560 --> 00:48:31,680 Speaker 1: to keep a current regime in charge, to enforce a 785 00:48:31,760 --> 00:48:36,319 Speaker 1: status quo up to and including fatal measures. Yeah, keeping that, 786 00:48:36,440 --> 00:48:41,320 Speaker 1: keeping that regime secure, That's what it's all about, um Man. 787 00:48:41,680 --> 00:48:44,120 Speaker 1: Paul Lewis called what is in that article Paul Lewis 788 00:48:44,200 --> 00:48:49,400 Speaker 1: refers to NSO is what developers of weapons of mass 789 00:48:49,400 --> 00:48:52,840 Speaker 1: surveillance or something like that. Little call back to the 790 00:48:52,840 --> 00:48:58,520 Speaker 1: the Bush administration. And this is an on demand service. 791 00:48:58,760 --> 00:49:01,440 Speaker 1: The market for this kind of stuff has blown up. 792 00:49:01,520 --> 00:49:03,680 Speaker 1: It's bigger than an s O. The reason people are 793 00:49:03,680 --> 00:49:06,800 Speaker 1: talking about an s O right now is entirely because 794 00:49:06,800 --> 00:49:09,359 Speaker 1: of this leak. That's the reasons happening in critical way. 795 00:49:09,400 --> 00:49:12,480 Speaker 1: But if you look back through the record, people have 796 00:49:12,560 --> 00:49:15,879 Speaker 1: been raising their hands about the dangers posed by this 797 00:49:15,960 --> 00:49:19,800 Speaker 1: technology and lack of oversight for a quite a while, 798 00:49:19,840 --> 00:49:23,919 Speaker 1: for years. It's just now the surveillance has hit the fan. 799 00:49:24,280 --> 00:49:27,640 Speaker 1: If we want to style in the old cliche, I 800 00:49:27,680 --> 00:49:29,880 Speaker 1: guess if we're going to be fair. An su Oh 801 00:49:29,960 --> 00:49:34,640 Speaker 1: group has responded, and they have they have denied any 802 00:49:34,719 --> 00:49:37,600 Speaker 1: kind of complicity. Of course, they've said, you know, we have, 803 00:49:38,080 --> 00:49:41,600 Speaker 1: we have vetted people. We've not only like vetted our 804 00:49:41,680 --> 00:49:44,760 Speaker 1: state actors that we're selling this too. But the stories 805 00:49:44,800 --> 00:49:48,400 Speaker 1: about this are either exaggerated or they're making false claims, 806 00:49:48,480 --> 00:49:54,040 Speaker 1: wrong assumptions, uncorroborated theories. We see ourselves as a group 807 00:49:54,080 --> 00:49:57,120 Speaker 1: on a life saving mission, right which you know, that 808 00:49:57,120 --> 00:50:00,440 Speaker 1: would be the idea, you could prevent the next terror attack, 809 00:50:00,600 --> 00:50:05,080 Speaker 1: maybe even the next nine eleven before it occurs. That's amazing. 810 00:50:05,200 --> 00:50:08,240 Speaker 1: That is, you are literally saving lives at that point. 811 00:50:08,680 --> 00:50:12,719 Speaker 1: But the question is one of truth. It becomes, as 812 00:50:12,719 --> 00:50:17,480 Speaker 1: you know, it becomes devilishly difficult to prove that your 813 00:50:17,680 --> 00:50:22,640 Speaker 1: actions prevented something that would have happened. You know, like, 814 00:50:22,719 --> 00:50:26,600 Speaker 1: for instance, if you had on a microcosmic level, not 815 00:50:26,680 --> 00:50:30,279 Speaker 1: to get to psychic powery about it, but if you 816 00:50:30,640 --> 00:50:33,000 Speaker 1: what if you had a really terrible dream that one 817 00:50:33,040 --> 00:50:35,160 Speaker 1: of your friends or your family members was going to 818 00:50:35,239 --> 00:50:38,239 Speaker 1: be in a car accident. The next day, you wake up, 819 00:50:38,280 --> 00:50:41,920 Speaker 1: you call them and you say, hey, don't don't drive 820 00:50:41,960 --> 00:50:47,120 Speaker 1: to the uh don't figures of ridiculous, don't drive to 821 00:50:47,160 --> 00:50:50,120 Speaker 1: the Beanie Baby convention, or don't drive to the case 822 00:50:50,160 --> 00:50:52,680 Speaker 1: Ada con because you know, I had a dream you're 823 00:50:52,719 --> 00:50:54,760 Speaker 1: going to get in an accident and they don't drive, 824 00:50:55,120 --> 00:50:57,279 Speaker 1: so they don't get it an accident. Does that mean 825 00:50:57,280 --> 00:51:00,120 Speaker 1: you're psychic? Not really? Yeah? But what if they is 826 00:51:00,160 --> 00:51:02,960 Speaker 1: a carbon monoxide leak at their house and they only 827 00:51:03,320 --> 00:51:06,000 Speaker 1: got affected because they didn't take a drive that day exactly? 828 00:51:06,280 --> 00:51:09,760 Speaker 1: But if you accidentally killed them? So right, we start 829 00:51:09,800 --> 00:51:16,000 Speaker 1: to try to unwind the mass of chronology and timelines involved. 830 00:51:16,760 --> 00:51:20,799 Speaker 1: The best argument for an s O S position at 831 00:51:20,800 --> 00:51:26,320 Speaker 1: this point would be proven cases where in an attack 832 00:51:26,360 --> 00:51:30,280 Speaker 1: it's terrorist attack of some sort or an organized crime 833 00:51:30,320 --> 00:51:34,799 Speaker 1: initiative was prevented. But they also claim that they don't 834 00:51:34,880 --> 00:51:40,279 Speaker 1: receive the information that this their customers get due to 835 00:51:40,440 --> 00:51:45,560 Speaker 1: due to privacy concerns. But it looks like the Kashagi 836 00:51:45,680 --> 00:51:51,560 Speaker 1: family was definitely targeted using this software, not only before 837 00:51:51,960 --> 00:51:55,520 Speaker 1: his murder but after his murder, so they kept an 838 00:51:55,520 --> 00:51:59,000 Speaker 1: eye on him. This is per Amnesty International, and this 839 00:51:59,120 --> 00:52:03,160 Speaker 1: is despite repeated denials by the NSO group. So were 840 00:52:03,200 --> 00:52:06,840 Speaker 1: they simply unaware that this was a curry or what? 841 00:52:07,200 --> 00:52:09,080 Speaker 1: You know? What I mean, what are the alternatives? It's 842 00:52:09,080 --> 00:52:11,120 Speaker 1: a good question. You're saying that you think there may 843 00:52:11,160 --> 00:52:15,359 Speaker 1: have been active cover up. There's definitely an active cover 844 00:52:15,440 --> 00:52:18,279 Speaker 1: up at the Kashagi death. The US is participating in it. 845 00:52:19,120 --> 00:52:21,920 Speaker 1: She said. I mean the idea that that they were 846 00:52:21,960 --> 00:52:24,879 Speaker 1: not aware this was going on is very unlikely, right, 847 00:52:25,080 --> 00:52:28,839 Speaker 1: That's what I'm saying. Yeah, I don't know. I think 848 00:52:28,840 --> 00:52:31,719 Speaker 1: it's maybe a tall order to say, like, oh, you 849 00:52:31,800 --> 00:52:34,359 Speaker 1: all knew exactly what you were doing, and you just 850 00:52:35,040 --> 00:52:39,120 Speaker 1: said you're fine with it because the money was good 851 00:52:39,239 --> 00:52:42,480 Speaker 1: enough and you rationalized it. It seems unfair. But it's 852 00:52:42,520 --> 00:52:47,399 Speaker 1: not looking good, you know, because there I would say, 853 00:52:47,440 --> 00:52:50,879 Speaker 1: how much of a how much leeway do you have 854 00:52:51,320 --> 00:52:53,880 Speaker 1: when you say something like that, when you say to 855 00:52:53,960 --> 00:52:59,680 Speaker 1: the missile thing, I designed these, I designed these missiles, 856 00:52:59,800 --> 00:53:02,839 Speaker 1: I sell them to people for their defense. I am 857 00:53:02,880 --> 00:53:06,480 Speaker 1: not in charge of where they get detonated, right, And 858 00:53:06,600 --> 00:53:09,960 Speaker 1: that's something you know, legally, that's something the world has 859 00:53:10,040 --> 00:53:13,640 Speaker 1: kind of agreed on. Now, a firearm manufacturer is not 860 00:53:13,760 --> 00:53:17,680 Speaker 1: held responsible for firearm deaths, and you could go to 861 00:53:17,880 --> 00:53:21,840 Speaker 1: any number of different industries. I think firearms might be 862 00:53:21,840 --> 00:53:25,200 Speaker 1: a little controversial for people. But if you think about 863 00:53:25,280 --> 00:53:28,000 Speaker 1: in this term, in these terms like what if what 864 00:53:28,040 --> 00:53:31,200 Speaker 1: if Facebook sold a surveillance tool and what if people 865 00:53:31,440 --> 00:53:36,719 Speaker 1: began using that to stall, harass, and possibly assaulter murder 866 00:53:37,040 --> 00:53:40,600 Speaker 1: uh their former lovers? Right? Well, that's that's an interesting 867 00:53:40,680 --> 00:53:43,680 Speaker 1: point then, because I think the fire I think the 868 00:53:43,719 --> 00:53:48,520 Speaker 1: firearm uh connection is interesting because firearms kill people when 869 00:53:48,520 --> 00:53:53,120 Speaker 1: they work as advertised other things like other products. If 870 00:53:53,120 --> 00:53:56,000 Speaker 1: a toaster blows up in your house and kills you, 871 00:53:56,040 --> 00:53:58,719 Speaker 1: that toaster company probably would be liable for that. So 872 00:53:58,760 --> 00:54:02,200 Speaker 1: what happens when technologergy that exists for one purpose as 873 00:54:02,239 --> 00:54:05,759 Speaker 1: then co opted and used for a different purpose. Is 874 00:54:05,800 --> 00:54:09,400 Speaker 1: that the responsibility of the company to safeguard against these 875 00:54:09,640 --> 00:54:14,840 Speaker 1: potential negative uses? Uh? You know that's a that's a 876 00:54:14,880 --> 00:54:16,600 Speaker 1: that's a very tough question and not really you know, 877 00:54:16,640 --> 00:54:18,879 Speaker 1: it depends on this situation. There's not really an easy 878 00:54:18,920 --> 00:54:21,279 Speaker 1: answer to that. Obviously, there are safeguards in place to 879 00:54:21,360 --> 00:54:24,440 Speaker 1: keep you know, maybe children from shooting themselves or shooting 880 00:54:24,440 --> 00:54:27,680 Speaker 1: others with safety precautions on guns. But again, when the 881 00:54:27,680 --> 00:54:31,719 Speaker 1: gun is used as intended, it kills people. So in 882 00:54:31,760 --> 00:54:35,640 Speaker 1: this case, again this is an emergence story. In this case, 883 00:54:35,960 --> 00:54:39,880 Speaker 1: it's important to note that we're going to learn more 884 00:54:40,000 --> 00:54:42,279 Speaker 1: very soon. We don't know how far this goes, but 885 00:54:42,680 --> 00:54:47,960 Speaker 1: the Amnesty investigation at as of yesterday identified at least 886 00:54:47,960 --> 00:54:52,359 Speaker 1: a hundred and eighty journalists in twenty different countries who 887 00:54:52,360 --> 00:54:56,359 Speaker 1: have been targeted by this by where between sten and 888 00:54:56,480 --> 00:55:00,600 Speaker 1: July one. And they're including some places that are pretty 889 00:55:00,640 --> 00:55:04,680 Speaker 1: famous for repressing journalists, like Azerbaijan, where if you are 890 00:55:04,719 --> 00:55:09,759 Speaker 1: a journalist Azerbaijan, good luck. I don't know what else 891 00:55:09,800 --> 00:55:17,440 Speaker 1: to say this, this gets Harry very quickly. Uh. And Mexico, Yeah, yeah, 892 00:55:17,480 --> 00:55:22,480 Speaker 1: there's a journalist named Cecilio Panada. Their phone was selected 893 00:55:22,480 --> 00:55:25,560 Speaker 1: for targeting just a few weeks before he was brutally 894 00:55:25,640 --> 00:55:30,800 Speaker 1: murdered in seventeen. Another investigation identified at least twenty five 895 00:55:30,960 --> 00:55:34,799 Speaker 1: Mexican journalists who are targeted over two year period. N 896 00:55:34,960 --> 00:55:38,320 Speaker 1: s O has said, Even if Panda's phone was targeted 897 00:55:38,800 --> 00:55:42,960 Speaker 1: for some reason by state actors in Mexico, data collected 898 00:55:43,000 --> 00:55:46,520 Speaker 1: from his phone didn't contribute to his death, which seems 899 00:55:46,560 --> 00:55:49,640 Speaker 1: like an interesting distinction. They didn't find his phone though, 900 00:55:49,880 --> 00:55:52,480 Speaker 1: so there's like all kinds of stuff in these where 901 00:55:52,880 --> 00:55:55,440 Speaker 1: like you said earlier, if you don't find the phone, 902 00:55:56,160 --> 00:55:59,799 Speaker 1: you can't prove that Pegasus had anything to do with 903 00:56:00,200 --> 00:56:02,600 Speaker 1: locating the phone in the moments leading up to the 904 00:56:02,640 --> 00:56:07,839 Speaker 1: death right. So any state actor can now if they 905 00:56:07,880 --> 00:56:12,000 Speaker 1: have access to Pegasus, can carry out extra judicial killing 906 00:56:12,120 --> 00:56:14,440 Speaker 1: as long as they've removed the cell phone from the 907 00:56:14,480 --> 00:56:19,040 Speaker 1: crime scene. The perfect crime, right. It's terrible, uh, And 908 00:56:19,120 --> 00:56:23,160 Speaker 1: this may be something we explore further in the future 909 00:56:23,440 --> 00:56:27,920 Speaker 1: as the story unfolds. It seems that this sort of 910 00:56:28,000 --> 00:56:33,279 Speaker 1: information warfare master veillance is only set to accelerate in 911 00:56:33,600 --> 00:56:36,279 Speaker 1: not even the years, in the months to come. So 912 00:56:36,360 --> 00:56:39,120 Speaker 1: please be careful out there, folks. Uh. Please let us 913 00:56:39,120 --> 00:56:42,320 Speaker 1: know your stories about MAS surveillance. Please let us know 914 00:56:42,440 --> 00:56:47,760 Speaker 1: your take on AI modeling, on stealing someone's voice, as 915 00:56:47,800 --> 00:56:50,440 Speaker 1: well as all of the other stories we've discussed here, 916 00:56:50,520 --> 00:56:56,319 Speaker 1: including India's proposal for population control. We'd love to hear 917 00:56:56,360 --> 00:56:58,560 Speaker 1: from you. You are the best part of the show, 918 00:56:58,640 --> 00:57:01,600 Speaker 1: fellow conspiracy realists, so do reach out. We try to 919 00:57:01,640 --> 00:57:04,200 Speaker 1: be easy to find online. You can find us online 920 00:57:04,440 --> 00:57:09,160 Speaker 1: that's been said on Twitter, on Facebook, on YouTube, or 921 00:57:09,239 --> 00:57:12,480 Speaker 1: we are Conspiracy Stuff or Conspiracy Stuff Show on Instagram. 922 00:57:12,520 --> 00:57:14,960 Speaker 1: You can also call us on the telephone. Your old 923 00:57:14,960 --> 00:57:18,680 Speaker 1: school number is one eight three three std w y 924 00:57:18,760 --> 00:57:22,120 Speaker 1: t K. You've got three minutes to leave whatever message 925 00:57:22,160 --> 00:57:25,400 Speaker 1: you like. Please give yourself a cool nickname or tell 926 00:57:25,480 --> 00:57:27,200 Speaker 1: us your name however you want to play it. Let 927 00:57:27,240 --> 00:57:29,280 Speaker 1: us know if we can use your message and name 928 00:57:29,480 --> 00:57:32,400 Speaker 1: on the air. If you have too much to say 929 00:57:32,720 --> 00:57:35,040 Speaker 1: in three minutes and you got links and other things 930 00:57:35,080 --> 00:57:37,400 Speaker 1: you want to share with us, we highly recommend you 931 00:57:37,440 --> 00:57:40,880 Speaker 1: send us a good old fashioned email. We are conspiracy 932 00:57:41,040 --> 00:58:02,400 Speaker 1: at iHeart radio dot com. Stuff they don't want you 933 00:58:02,480 --> 00:58:05,080 Speaker 1: to know is a production of I Heart Radio. For 934 00:58:05,160 --> 00:58:07,560 Speaker 1: more podcasts from my heart Radio, visit the I heart 935 00:58:07,600 --> 00:58:10,400 Speaker 1: Radio app, Apple Podcasts, or wherever you listen to your 936 00:58:10,400 --> 00:58:11,120 Speaker 1: favorite shows.