1 00:00:00,280 --> 00:00:01,760 Speaker 1: If you want to support there Are No Girls on 2 00:00:01,800 --> 00:00:04,960 Speaker 1: the Internet, please check out our patreon. There you can 3 00:00:05,000 --> 00:00:08,080 Speaker 1: get ad free bonus content. Just go to patreon dot 4 00:00:08,080 --> 00:00:10,039 Speaker 1: com slash tangoti and thanks so much. 5 00:00:13,760 --> 00:00:17,480 Speaker 2: We have these people who are very socially isolated and 6 00:00:17,680 --> 00:00:21,480 Speaker 2: have difficulty relating to other people. Think trying to design 7 00:00:21,600 --> 00:00:24,119 Speaker 2: or trying to dream up what society is going to 8 00:00:24,160 --> 00:00:25,560 Speaker 2: look like for everybody else. 9 00:00:31,080 --> 00:00:32,800 Speaker 1: There Are No Girls on the Internet. As a production 10 00:00:32,880 --> 00:00:40,360 Speaker 1: of iHeartRadio and Unbossed Creative, I'm Bridge Todd and this 11 00:00:40,479 --> 00:00:45,159 Speaker 1: is There Are No Girls on the Internet. Back in 12 00:00:45,200 --> 00:00:50,040 Speaker 1: twenty ten, technology felt exciting. It was when we first 13 00:00:50,120 --> 00:00:54,560 Speaker 1: got the old school, non Facebook affiliated Instagram app remember 14 00:00:54,640 --> 00:00:55,520 Speaker 1: the Sienna filter. 15 00:00:56,200 --> 00:00:57,120 Speaker 3: Ough, I loved it. 16 00:00:58,320 --> 00:01:02,520 Speaker 1: We were talking about commercial space the very first iPad debuted. 17 00:01:03,000 --> 00:01:06,240 Speaker 1: The vibe seemed to be that Silicon Valley geniuses were 18 00:01:06,280 --> 00:01:08,920 Speaker 1: bestowing gifts to us in the form of new technology, 19 00:01:09,360 --> 00:01:11,360 Speaker 1: and our job was to be in awe of these 20 00:01:11,440 --> 00:01:14,039 Speaker 1: gifts and to say thank you. So there was a 21 00:01:14,080 --> 00:01:17,039 Speaker 1: lot of optimism around technology and it was easy to 22 00:01:17,040 --> 00:01:19,600 Speaker 1: think about it as being an unquestionable force for good. 23 00:01:20,000 --> 00:01:22,560 Speaker 1: And maybe that's why when you look back at that time, 24 00:01:22,800 --> 00:01:25,760 Speaker 1: there weren't a lot of critical questions about technology and 25 00:01:25,800 --> 00:01:27,959 Speaker 1: the people who make it and whether or not that 26 00:01:28,080 --> 00:01:31,480 Speaker 1: technology was actually contributing to a better future, one that 27 00:01:31,520 --> 00:01:35,160 Speaker 1: we'd actually want. That's a dynamic that Paris Marx says 28 00:01:35,200 --> 00:01:37,560 Speaker 1: has led to tech leaders getting really used to being 29 00:01:37,560 --> 00:01:40,720 Speaker 1: able to do whatever they want, and Paris is trying 30 00:01:40,720 --> 00:01:41,440 Speaker 1: to course correct. 31 00:01:41,720 --> 00:01:44,320 Speaker 2: I'm Paris Marx, I host the Tech Won't Save Us podcast. 32 00:01:44,800 --> 00:01:47,039 Speaker 1: Tech Won't Save Us starts from the premise that we 33 00:01:47,120 --> 00:01:50,040 Speaker 1: all need to be questioned in technology and Silicon Valley 34 00:01:50,120 --> 00:01:53,840 Speaker 1: tech billionaires about what kind of futures they're actually contributing to. 35 00:01:54,560 --> 00:01:57,240 Speaker 1: And when it comes to conversations around things like AI 36 00:01:57,720 --> 00:02:01,600 Speaker 1: and its potential to change the world, Paras says, we're 37 00:02:01,640 --> 00:02:04,680 Speaker 1: at risk of kind of mirroring the same dynamic that 38 00:02:04,720 --> 00:02:07,720 Speaker 1: happened in the twenty tens, letting the people who build 39 00:02:07,760 --> 00:02:09,520 Speaker 1: the technology set the terms. 40 00:02:10,840 --> 00:02:13,440 Speaker 2: Into the early twenty tens and stuff like that, Like 41 00:02:13,560 --> 00:02:17,680 Speaker 2: it was very positive around tech and what tech was doing, 42 00:02:17,800 --> 00:02:20,120 Speaker 2: and like all these startups that were forming and how 43 00:02:20,120 --> 00:02:23,839 Speaker 2: these big companies were like growing, and this was going 44 00:02:23,919 --> 00:02:26,239 Speaker 2: to be the way that you know, we were going 45 00:02:26,280 --> 00:02:29,280 Speaker 2: to have prosperity again. Because this tech industry was going 46 00:02:29,320 --> 00:02:31,519 Speaker 2: to like drive a ton of job creation and blah 47 00:02:31,600 --> 00:02:34,800 Speaker 2: blah blah, and so there was a real desire not 48 00:02:35,120 --> 00:02:37,760 Speaker 2: to kind of look at the potential consequences, to not 49 00:02:38,080 --> 00:02:40,960 Speaker 2: look at the downsides of this industry and these business models. 50 00:02:41,240 --> 00:02:43,720 Speaker 2: And now I feel like part of kind of, you know, 51 00:02:43,760 --> 00:02:46,520 Speaker 2: we have seen a more critical view in the past 52 00:02:46,600 --> 00:02:49,640 Speaker 2: number of years, especially since twenty eighteen, and I feel 53 00:02:49,639 --> 00:02:51,200 Speaker 2: like part of that is not just kind of like 54 00:02:52,720 --> 00:02:54,800 Speaker 2: you know, waking up to what is actually happening, but 55 00:02:54,880 --> 00:02:58,680 Speaker 2: also reckoning with the consequences of not you know, looking 56 00:02:58,680 --> 00:03:01,560 Speaker 2: at the potential downsides of the companies through those years, 57 00:03:01,560 --> 00:03:05,560 Speaker 2: through the early twenty ten you know period, And now 58 00:03:05,560 --> 00:03:07,400 Speaker 2: we're kind of trying to catch up and trying to 59 00:03:07,440 --> 00:03:09,680 Speaker 2: be like, whoa, what have we unleashed unto the world. 60 00:03:10,040 --> 00:03:12,720 Speaker 2: And now there's a real kind of desire to you know, 61 00:03:12,840 --> 00:03:15,400 Speaker 2: not just criticize the Elon Musks and Jeff bezos Is 62 00:03:15,440 --> 00:03:17,920 Speaker 2: of the world, but to say, like, we really bought 63 00:03:17,960 --> 00:03:19,959 Speaker 2: into a lot of this stuff that Silicon Valley was 64 00:03:20,000 --> 00:03:22,520 Speaker 2: selling us around how all we need is kind of 65 00:03:22,639 --> 00:03:26,120 Speaker 2: new innovative technologies created by Google and Facebook and whatever, 66 00:03:26,360 --> 00:03:28,000 Speaker 2: and that's going to make the world a better place, 67 00:03:28,160 --> 00:03:30,120 Speaker 2: and we can see that that didn't work out, and 68 00:03:30,160 --> 00:03:32,440 Speaker 2: so now we need to actually think a lot more 69 00:03:32,440 --> 00:03:34,880 Speaker 2: critically about what these tech companies are telling us, but 70 00:03:34,960 --> 00:03:37,560 Speaker 2: also how we address these really serious problems that do 71 00:03:37,640 --> 00:03:40,240 Speaker 2: exist in society and aren't going to be solved from 72 00:03:40,520 --> 00:03:41,800 Speaker 2: a shiny new technology. 73 00:03:42,280 --> 00:03:44,680 Speaker 1: What do you think some of those consequences of not 74 00:03:44,840 --> 00:03:47,560 Speaker 1: asking those questions during that time and technology, What do 75 00:03:47,560 --> 00:03:49,040 Speaker 1: you think some of those consequences have been? 76 00:03:50,000 --> 00:03:53,000 Speaker 2: Oh, there are a ton, right, like the easy ones. 77 00:03:53,040 --> 00:03:55,280 Speaker 2: The point too, that like the mainstream would know about 78 00:03:55,400 --> 00:03:57,920 Speaker 2: is like, you know, the social media platforms and like 79 00:03:57,960 --> 00:03:59,720 Speaker 2: all they've done, and like we love to kind of 80 00:03:59,760 --> 00:04:03,040 Speaker 2: hate Facebook, and I'm totally on board for hating Facebook, right, Like, 81 00:04:03,120 --> 00:04:06,360 Speaker 2: don't get me wrong, but I think that it's much 82 00:04:06,400 --> 00:04:08,800 Speaker 2: bigger than that, right, Like, sure, we had the Cambridge 83 00:04:08,840 --> 00:04:11,920 Speaker 2: Analytica like leaks and the scandal around that, and like, 84 00:04:12,280 --> 00:04:14,960 Speaker 2: you know, I think that that was kind of misconstrued 85 00:04:15,120 --> 00:04:18,200 Speaker 2: a bit as saying, like, h it was because Facebook 86 00:04:18,240 --> 00:04:21,799 Speaker 2: like manipulated the populations of the UK and the US 87 00:04:21,880 --> 00:04:24,039 Speaker 2: and all this stuff that we had this really terrible 88 00:04:24,360 --> 00:04:26,560 Speaker 2: turn in our politics. And I don't think that that's 89 00:04:26,560 --> 00:04:29,479 Speaker 2: actually accurate. I think it's a misreading of what actually happened. 90 00:04:30,560 --> 00:04:33,440 Speaker 2: And like, I think that there are just things happening 91 00:04:33,480 --> 00:04:37,040 Speaker 2: in our politics for reasons that are not technological, you know, 92 00:04:37,080 --> 00:04:39,680 Speaker 2: that are kind of affecting what people are doing, which 93 00:04:39,720 --> 00:04:43,200 Speaker 2: is really unfortunate. But I think that like much more fundamentally, 94 00:04:43,240 --> 00:04:45,800 Speaker 2: and I think the piece that we tend to ignore 95 00:04:45,839 --> 00:04:49,520 Speaker 2: a lot more is what this actually meant for workers 96 00:04:49,560 --> 00:04:52,360 Speaker 2: as well. Right, Like, obviously, we had this massive boom 97 00:04:52,520 --> 00:04:55,560 Speaker 2: in tech workers and people working in the tech industry 98 00:04:55,560 --> 00:04:58,080 Speaker 2: that were making good salaries and like doing these startups 99 00:04:58,080 --> 00:05:00,279 Speaker 2: and all this kind of stuff, and the media like 100 00:05:00,360 --> 00:05:03,600 Speaker 2: very interested in that story, right in how there were 101 00:05:03,600 --> 00:05:05,520 Speaker 2: these workers who were making all this money, they had 102 00:05:05,520 --> 00:05:08,120 Speaker 2: great benefits when they went to their jobs, like free 103 00:05:08,480 --> 00:05:10,400 Speaker 2: lunch and gyms and I don't know all the other 104 00:05:10,440 --> 00:05:14,360 Speaker 2: stuff that tech workers get. But then, like the tech 105 00:05:14,400 --> 00:05:20,360 Speaker 2: industry was also very like, very clearly involved in affecting 106 00:05:20,600 --> 00:05:24,680 Speaker 2: and attacking like the rights of workers in many different industries, 107 00:05:24,800 --> 00:05:28,039 Speaker 2: not just in the United States or in other Western countries, 108 00:05:28,080 --> 00:05:30,240 Speaker 2: but like around the world as well, Right, And I 109 00:05:30,279 --> 00:05:33,480 Speaker 2: feel like we have not really kind of grappled with 110 00:05:33,520 --> 00:05:36,480 Speaker 2: that as much through the gig economy and of course 111 00:05:36,520 --> 00:05:38,880 Speaker 2: the Ubers of the world and things like that, you know, 112 00:05:39,040 --> 00:05:42,480 Speaker 2: explicitly attacking the regulations on the taxi industry and ensuring 113 00:05:42,480 --> 00:05:45,760 Speaker 2: that this profession gets turned into this kind of unregulated 114 00:05:45,800 --> 00:05:50,040 Speaker 2: contractor model where these people are like completely subjected to 115 00:05:50,680 --> 00:05:54,120 Speaker 2: the rules of like Uber and the rules of these 116 00:05:54,120 --> 00:05:57,360 Speaker 2: gig companies. But then also like much more than that, 117 00:05:57,600 --> 00:06:00,440 Speaker 2: you know, you think about Amazon rolling out out rhythmic 118 00:06:00,480 --> 00:06:04,359 Speaker 2: management across its warehouses and turning warehouse work from like 119 00:06:04,400 --> 00:06:07,159 Speaker 2: a unionized industry where people could make good money to 120 00:06:07,600 --> 00:06:10,800 Speaker 2: like basically your equivalent of a minimum wage job or 121 00:06:10,880 --> 00:06:12,960 Speaker 2: just a little bit above minimum wage. Right, that's kind 122 00:06:12,960 --> 00:06:15,880 Speaker 2: of like the standard if you're in a community. Right, 123 00:06:15,920 --> 00:06:18,080 Speaker 2: it's the new kind of Walmart is working at the 124 00:06:18,120 --> 00:06:21,320 Speaker 2: Amazon warehouse and this really changes, like, you know, then 125 00:06:21,360 --> 00:06:24,240 Speaker 2: you also have the like one of the things that 126 00:06:24,279 --> 00:06:27,080 Speaker 2: I think is pernicious here actually is that, like through 127 00:06:27,120 --> 00:06:29,360 Speaker 2: the mid twenty tens, we had this narrative that automation 128 00:06:29,440 --> 00:06:31,400 Speaker 2: and AI we're going to wipe out all these jobs, right, 129 00:06:31,440 --> 00:06:33,840 Speaker 2: and we're kind of seeing repeats of that right now 130 00:06:33,880 --> 00:06:37,480 Speaker 2: with the whole generative AI boom. But like that moment, 131 00:06:37,520 --> 00:06:39,440 Speaker 2: we have all this these narratives around it and we're like, 132 00:06:39,440 --> 00:06:41,240 Speaker 2: oh my god, the robots are going to take our jobs. 133 00:06:41,279 --> 00:06:43,760 Speaker 2: But actually what happens is the tech companies like deploy 134 00:06:43,839 --> 00:06:46,760 Speaker 2: all these technologies to like decimate the labor rights of 135 00:06:46,800 --> 00:06:49,919 Speaker 2: people across the economy, and we just kind of ignore 136 00:06:49,960 --> 00:06:51,920 Speaker 2: that picture of it. But I think that's much more 137 00:06:52,040 --> 00:06:54,280 Speaker 2: consequential and I think we should be paying more attention 138 00:06:54,320 --> 00:06:54,600 Speaker 2: to it. 139 00:06:54,920 --> 00:06:57,480 Speaker 1: You have a great piece about this called tech Giants 140 00:06:57,520 --> 00:07:00,920 Speaker 1: are building a dystopia of desperate workers and social isolation, 141 00:07:01,520 --> 00:07:03,840 Speaker 1: where you write tech companies like Amazon and Uber are 142 00:07:03,839 --> 00:07:07,040 Speaker 1: creating a society divided between the served and their servants, 143 00:07:07,240 --> 00:07:10,520 Speaker 1: where the friction of in person interaction is eliminated. That 144 00:07:10,600 --> 00:07:13,560 Speaker 1: friction is the stuff of social connection. A world without 145 00:07:13,560 --> 00:07:16,400 Speaker 1: it is nightmarish. And I've talked about this a lot 146 00:07:16,400 --> 00:07:18,440 Speaker 1: on the podcast, and it's not something that I feel 147 00:07:18,480 --> 00:07:21,920 Speaker 1: great about talking about. Which is that during the pandemic, 148 00:07:22,400 --> 00:07:24,880 Speaker 1: which was so hard for all of us, I definitely 149 00:07:25,080 --> 00:07:27,440 Speaker 1: got I mean I've used. 150 00:07:27,200 --> 00:07:28,080 Speaker 3: The word addiction. 151 00:07:28,440 --> 00:07:32,960 Speaker 1: I got addicted to buying quick crap on Amazon that 152 00:07:33,000 --> 00:07:36,080 Speaker 1: I didn't need to give myself a quick serotonin boost 153 00:07:36,080 --> 00:07:37,880 Speaker 1: because I was miserable, just like everybody else. 154 00:07:38,200 --> 00:07:40,080 Speaker 3: I got addicted to not. 155 00:07:40,160 --> 00:07:44,320 Speaker 1: Cooking and ordering Uber eats, And when I had to 156 00:07:44,400 --> 00:07:46,400 Speaker 1: take a step back and look at what I was 157 00:07:46,400 --> 00:07:49,960 Speaker 1: contributing to personally me bridget, it was really hard. It 158 00:07:50,000 --> 00:07:53,280 Speaker 1: was hard to see not only that I had been 159 00:07:53,320 --> 00:07:57,000 Speaker 1: so easily conditioned into not thinking about the person who 160 00:07:57,080 --> 00:07:58,720 Speaker 1: was bringing me my Uber eats, the person who was 161 00:07:58,800 --> 00:08:01,200 Speaker 1: leaving whatever I did, what ever dumb thing I just 162 00:08:01,240 --> 00:08:05,160 Speaker 1: bought on Amazon during a pandemic to my apartment, but 163 00:08:05,360 --> 00:08:09,200 Speaker 1: also conditioning meat to think, when I want food, I 164 00:08:09,200 --> 00:08:11,360 Speaker 1: certainly don't have to, you know, cook it myself. But 165 00:08:11,480 --> 00:08:12,880 Speaker 1: I don't even have to go to the I don't 166 00:08:12,880 --> 00:08:15,640 Speaker 1: even have to call my local pizza place down the 167 00:08:15,640 --> 00:08:17,920 Speaker 1: street and have a conversation with the person who owns it. 168 00:08:18,320 --> 00:08:19,480 Speaker 3: That's I don't have to do that. 169 00:08:19,560 --> 00:08:24,120 Speaker 1: And I wonder how did technology trick us into thinking 170 00:08:24,160 --> 00:08:25,960 Speaker 1: that all of these things that are part of the 171 00:08:26,000 --> 00:08:28,720 Speaker 1: fabric of life in a society you don't need and 172 00:08:28,720 --> 00:08:31,160 Speaker 1: in fact, your life would be better without it. Like 173 00:08:31,200 --> 00:08:33,280 Speaker 1: I enjoy cooking dinner, why is it that I now 174 00:08:33,320 --> 00:08:35,400 Speaker 1: am like, oh, like uber eats, is better when this 175 00:08:35,480 --> 00:08:37,400 Speaker 1: is something that used to be something that like brought 176 00:08:37,440 --> 00:08:39,679 Speaker 1: me a little bit of joy and calm in my life, you. 177 00:08:39,600 --> 00:08:42,679 Speaker 2: Know, absolutely, And you know, I think that there are 178 00:08:42,679 --> 00:08:45,679 Speaker 2: so many people who are like in that position, and 179 00:08:46,040 --> 00:08:48,760 Speaker 2: you know, like I think that on one hand, there 180 00:08:48,800 --> 00:08:51,520 Speaker 2: is kind of like the individual responsibility piece of it, 181 00:08:51,600 --> 00:08:53,600 Speaker 2: of like should we be using this and should we 182 00:08:53,679 --> 00:08:55,840 Speaker 2: be kind of contributing to this, But then on the 183 00:08:55,840 --> 00:08:57,679 Speaker 2: other hand, you also have to think about how like 184 00:08:58,000 --> 00:09:01,679 Speaker 2: these are ultimately like much large kind of structural problems, 185 00:09:01,920 --> 00:09:05,760 Speaker 2: and whether we you know, participate in them or not, 186 00:09:06,600 --> 00:09:09,959 Speaker 2: it's not really going to necessarily change like the bigger picture, 187 00:09:10,120 --> 00:09:12,320 Speaker 2: like if one of us opts out, and you know, 188 00:09:12,480 --> 00:09:15,840 Speaker 2: personally I do still opt out, Like I don't use Uber, 189 00:09:15,920 --> 00:09:18,560 Speaker 2: I don't use any of the food delivery services anything 190 00:09:18,640 --> 00:09:21,200 Speaker 2: like that, very rarely use Amazon unless I have to. 191 00:09:21,640 --> 00:09:24,720 Speaker 2: But you know, I know that ultimately, like that's not 192 00:09:24,760 --> 00:09:30,000 Speaker 2: going to take down Jeff Bezos and Amazon. Right, But yeah, right, 193 00:09:31,040 --> 00:09:33,320 Speaker 2: but I think to your bigger point, like you know 194 00:09:33,880 --> 00:09:36,240 Speaker 2: what you say is very true, right, the tech companies 195 00:09:36,240 --> 00:09:38,920 Speaker 2: have essentially tried to convince us, and in many cases 196 00:09:38,960 --> 00:09:42,520 Speaker 2: have successfully done so. To convince us that like things 197 00:09:42,559 --> 00:09:46,520 Speaker 2: that are like regular average aspects of life are actually 198 00:09:46,520 --> 00:09:48,679 Speaker 2: inconvenient and we need to like get rid of them, right, 199 00:09:49,120 --> 00:09:51,920 Speaker 2: And the goal of that, from their perspective is that 200 00:09:52,200 --> 00:09:55,560 Speaker 2: if they can kind of insert themselves between like more 201 00:09:55,559 --> 00:09:58,240 Speaker 2: of our interactions, more of what kind of like the 202 00:09:58,559 --> 00:10:00,800 Speaker 2: transactions that we make in our lives, and that is 203 00:10:00,880 --> 00:10:04,280 Speaker 2: better for them and their business models. Right If if we, 204 00:10:04,440 --> 00:10:06,760 Speaker 2: if Amazon or Uber can like stick itself in the 205 00:10:06,840 --> 00:10:09,080 Speaker 2: middle of more of the transactions that we do, if 206 00:10:09,120 --> 00:10:11,720 Speaker 2: they ensure that like instead of going to the shop, 207 00:10:11,720 --> 00:10:13,720 Speaker 2: instead of talking to someone, that we use one of 208 00:10:13,720 --> 00:10:15,880 Speaker 2: their apps, then that is great for their kind of 209 00:10:15,920 --> 00:10:18,679 Speaker 2: business model because they get to have like a piece 210 00:10:18,679 --> 00:10:21,240 Speaker 2: of that transaction, right, And so this is like the 211 00:10:21,320 --> 00:10:24,480 Speaker 2: whole incentive behind it. And I remember, like all the 212 00:10:24,480 --> 00:10:27,200 Speaker 2: way back in I think it was twenty fourteen, maybe 213 00:10:27,200 --> 00:10:30,439 Speaker 2: it was twenty fifteen, Lauren Smiley, you know who writes 214 00:10:30,440 --> 00:10:33,240 Speaker 2: for Wired now, But she wrote this piece called the 215 00:10:33,280 --> 00:10:36,600 Speaker 2: shut in Economy where she was like outside of of 216 00:10:36,640 --> 00:10:38,640 Speaker 2: Oakland for a while, and then she moved back in 217 00:10:38,760 --> 00:10:40,760 Speaker 2: and all of a sudden it was like people were 218 00:10:42,320 --> 00:10:44,000 Speaker 2: or maybe she moved into San Francisco. It was like 219 00:10:44,040 --> 00:10:45,559 Speaker 2: you know, it was in the Bay Area somewhere, and 220 00:10:45,880 --> 00:10:47,640 Speaker 2: she saw that, like, there are all these people now 221 00:10:47,679 --> 00:10:49,840 Speaker 2: that all of a sudden were like, you know, home 222 00:10:49,880 --> 00:10:51,160 Speaker 2: a lot or at work a lot, and they were 223 00:10:51,200 --> 00:10:53,240 Speaker 2: getting a lot of things delivered and like contracting a 224 00:10:53,280 --> 00:10:55,559 Speaker 2: lot of services because the gig economy is just kind 225 00:10:55,559 --> 00:10:58,600 Speaker 2: of booming in that in that period, right, And she 226 00:10:58,840 --> 00:11:00,720 Speaker 2: was like, what is going on here, Like this is 227 00:11:00,720 --> 00:11:02,680 Speaker 2: really weird, this is not really good. You can see 228 00:11:02,679 --> 00:11:06,000 Speaker 2: the distinction between the served and the servants basically very 229 00:11:06,040 --> 00:11:08,840 Speaker 2: clearly in this model. And sure, it allows a few 230 00:11:08,880 --> 00:11:11,840 Speaker 2: more people to become the served, but that means you 231 00:11:11,880 --> 00:11:14,319 Speaker 2: need a whole bigger kind of population of servants to 232 00:11:14,720 --> 00:11:17,880 Speaker 2: serve them effectively. And what we saw during the pandemic 233 00:11:18,000 --> 00:11:20,840 Speaker 2: was really like an expansion of this model where many 234 00:11:20,880 --> 00:11:23,400 Speaker 2: more people became the people who were kind of like 235 00:11:23,440 --> 00:11:26,679 Speaker 2: relying on gig services and e commerce websites and all 236 00:11:26,679 --> 00:11:29,160 Speaker 2: this stuff to get everything delivered to them so they 237 00:11:29,200 --> 00:11:31,520 Speaker 2: could stay home and kind of isolate. But then you 238 00:11:31,559 --> 00:11:34,600 Speaker 2: also needed this whole population that for a while we 239 00:11:34,600 --> 00:11:38,440 Speaker 2: were calling essential workers, you know, to deliver all this 240 00:11:38,440 --> 00:11:40,400 Speaker 2: stuff and do all this work for the people who 241 00:11:40,400 --> 00:11:42,760 Speaker 2: were staying home and working from home and all this stuff, 242 00:11:43,520 --> 00:11:46,040 Speaker 2: and like we've just kind of like moved on from 243 00:11:46,080 --> 00:11:48,080 Speaker 2: that moment and not really thought about the kind of 244 00:11:48,160 --> 00:11:52,320 Speaker 2: larger implications of that. And like, I do think that 245 00:11:52,360 --> 00:11:54,560 Speaker 2: there were consequences and there were some shifts that happened 246 00:11:54,640 --> 00:11:57,240 Speaker 2: during the pandemic with those whole labor models. But I 247 00:11:57,240 --> 00:11:58,760 Speaker 2: think that part of what we see right now with 248 00:11:58,800 --> 00:12:01,320 Speaker 2: like the big whole generative I push is again like 249 00:12:01,679 --> 00:12:04,160 Speaker 2: this this kind of return of this narrative that oh 250 00:12:04,200 --> 00:12:06,360 Speaker 2: my god, like the AIS are going to take away 251 00:12:06,400 --> 00:12:08,920 Speaker 2: all the jobs, when actually, like what we're much more 252 00:12:09,040 --> 00:12:13,280 Speaker 2: likely to see is like the continuation of tech companies 253 00:12:13,559 --> 00:12:16,719 Speaker 2: like kind of using technology against workers to further kind 254 00:12:16,760 --> 00:12:20,200 Speaker 2: of you know, create more precarious employment and things like that. 255 00:12:20,280 --> 00:12:22,520 Speaker 2: And I think that is like what a lot of 256 00:12:22,520 --> 00:12:24,920 Speaker 2: the media narratives don't suggest, but I think that's much 257 00:12:25,000 --> 00:12:27,640 Speaker 2: more likely to be what we what comes out of it. 258 00:12:27,760 --> 00:12:29,440 Speaker 2: And if we're not paying attention to it now, then 259 00:12:29,520 --> 00:12:31,319 Speaker 2: it's going to be much more difficult to like stop 260 00:12:31,360 --> 00:12:34,360 Speaker 2: that happening because we're too focused on like you know, 261 00:12:34,480 --> 00:12:37,920 Speaker 2: agi and digital minds and all this like sci fi bullshit, 262 00:12:38,000 --> 00:12:38,360 Speaker 2: Oh my. 263 00:12:38,320 --> 00:12:41,720 Speaker 1: God, like something. Actually I actually heard this on your podcast. 264 00:12:41,800 --> 00:12:44,000 Speaker 1: I forget who the guest was, but I do think 265 00:12:44,040 --> 00:12:48,240 Speaker 1: that there's this overton window thing happening where the they like, 266 00:12:48,280 --> 00:12:50,960 Speaker 1: there was a time where if I told you that 267 00:12:51,640 --> 00:12:56,000 Speaker 1: in between you and your mental health care professional would 268 00:12:56,040 --> 00:12:59,160 Speaker 1: be a skizy tech company, you would be like, what 269 00:12:59,160 --> 00:13:02,280 Speaker 1: the fuck? Of course, And now that is commonplace with 270 00:13:02,400 --> 00:13:04,640 Speaker 1: services like Betterhelp, right, And so I think that you're 271 00:13:04,679 --> 00:13:08,640 Speaker 1: so right that tech leaders want to be the wedge 272 00:13:08,679 --> 00:13:12,440 Speaker 1: between us and you know, the business of being a human, 273 00:13:12,760 --> 00:13:16,040 Speaker 1: and we're going to become more and more okay with 274 00:13:16,160 --> 00:13:18,800 Speaker 1: the different things that they're okay, Like I don't want 275 00:13:18,880 --> 00:13:21,320 Speaker 1: Jeff Bezos in the middle of my healthcare, right, I 276 00:13:21,400 --> 00:13:23,480 Speaker 1: use one medical and that is exactly what the fuck 277 00:13:23,520 --> 00:13:26,079 Speaker 1: is happening right now, right, Like, I'm not really comfortable 278 00:13:26,080 --> 00:13:28,840 Speaker 1: with like these very intimate things about my body and 279 00:13:28,880 --> 00:13:32,400 Speaker 1: my health there being a Jeff Bezos interference. And I 280 00:13:32,400 --> 00:13:35,560 Speaker 1: think that sort of without us really paying attention and 281 00:13:35,600 --> 00:13:39,360 Speaker 1: really thinking about it more and more intimate spaces, it 282 00:13:39,400 --> 00:13:41,960 Speaker 1: has become commonplace to think that a tech leader would 283 00:13:42,000 --> 00:13:44,360 Speaker 1: be in the middle of your ability. 284 00:13:43,960 --> 00:13:47,120 Speaker 3: To like talk to your healthcare professional or whatever. Does 285 00:13:47,160 --> 00:13:47,680 Speaker 3: that make sense? 286 00:13:48,280 --> 00:13:50,840 Speaker 2: Yeah, Like, and I think that you really clearly see 287 00:13:50,840 --> 00:13:55,720 Speaker 2: that during the pandemic, right, because you know, lockdown orders happen. 288 00:13:55,840 --> 00:13:58,320 Speaker 2: You know, there's an expectation that we lock down or 289 00:13:58,360 --> 00:14:00,800 Speaker 2: at least that like we physical this since from one another, 290 00:14:00,840 --> 00:14:02,839 Speaker 2: we don't see as many people, so we're spending more 291 00:14:02,840 --> 00:14:05,880 Speaker 2: time at home, We're using our devices more, we're watching 292 00:14:05,920 --> 00:14:08,280 Speaker 2: more things on streaming services, as you say, we're using 293 00:14:08,280 --> 00:14:10,839 Speaker 2: more of these services to get food and get other 294 00:14:10,880 --> 00:14:13,560 Speaker 2: things delivered to us. And what we see, like over 295 00:14:13,880 --> 00:14:15,520 Speaker 2: the course of like the first year or two of 296 00:14:15,559 --> 00:14:18,320 Speaker 2: the pandemic, is that like the profits and the revenues 297 00:14:18,320 --> 00:14:20,720 Speaker 2: of all these companies absolutely sore, right, And so it 298 00:14:20,760 --> 00:14:22,520 Speaker 2: shows you that the more that we kind of use 299 00:14:22,560 --> 00:14:25,160 Speaker 2: their services, the more that we look at our screens, 300 00:14:25,440 --> 00:14:27,720 Speaker 2: the better that is for them. And they're incentivized to 301 00:14:27,880 --> 00:14:32,160 Speaker 2: ensure that we spend more time as possible, like engaging 302 00:14:32,160 --> 00:14:34,640 Speaker 2: with their services kind of in front of our screens, 303 00:14:34,640 --> 00:14:36,440 Speaker 2: all these sorts of things. And I would say, like 304 00:14:36,480 --> 00:14:39,160 Speaker 2: that's exactly what the metaverse push was, right, like, how 305 00:14:39,160 --> 00:14:40,840 Speaker 2: can we get you in front of a screen much 306 00:14:40,840 --> 00:14:42,840 Speaker 2: more like the smart glasses all that stuff. The idea 307 00:14:42,880 --> 00:14:44,840 Speaker 2: is just like you need to look at screens more, 308 00:14:45,000 --> 00:14:46,720 Speaker 2: and it's like I don't actually want to do that. 309 00:14:46,880 --> 00:14:49,480 Speaker 2: But I think on your point about healthcare is interesting 310 00:14:49,520 --> 00:14:51,160 Speaker 2: as well, because I've been thinking about it a lot 311 00:14:51,240 --> 00:14:55,080 Speaker 2: lately because I'm in Canada, right, and so our healthcare 312 00:14:55,120 --> 00:14:57,360 Speaker 2: system is a little bit different, and I have like 313 00:14:57,440 --> 00:14:59,680 Speaker 2: even bigger concerns where like, you know, at least in 314 00:14:59,720 --> 00:15:02,000 Speaker 2: the state, it's like the healthcare system is already private 315 00:15:02,040 --> 00:15:04,520 Speaker 2: and so like to a certain degree, you're shifting from 316 00:15:04,520 --> 00:15:07,600 Speaker 2: like one private provider to another. But like, I think 317 00:15:07,640 --> 00:15:10,760 Speaker 2: it's really kind of worrying to see the potential like 318 00:15:11,160 --> 00:15:14,200 Speaker 2: encroachment and the further encroachment of like private companies on 319 00:15:14,240 --> 00:15:19,240 Speaker 2: public healthcare systems, and especially like how technology and digital 320 00:15:19,240 --> 00:15:22,280 Speaker 2: technology provides a means for that to happen, because the 321 00:15:22,400 --> 00:15:25,240 Speaker 2: argument is like, oh, this is like new technology. It 322 00:15:25,280 --> 00:15:27,200 Speaker 2: can't be done by the public sector, so you need 323 00:15:27,240 --> 00:15:29,560 Speaker 2: to contract it from the private sector and bring it 324 00:15:29,560 --> 00:15:32,600 Speaker 2: into your public healthcare system. And then like you know, 325 00:15:33,480 --> 00:15:35,840 Speaker 2: we could say that that's not going to make any difference, 326 00:15:35,840 --> 00:15:37,520 Speaker 2: but really, like it's kind of what I call like 327 00:15:37,560 --> 00:15:40,440 Speaker 2: a sly privatization that's happening there, and it does start 328 00:15:40,480 --> 00:15:42,720 Speaker 2: to change the logics of like what is actually happening 329 00:15:42,800 --> 00:15:45,240 Speaker 2: in the system, And it's not just a Canadian problem, 330 00:15:45,240 --> 00:15:47,120 Speaker 2: Like you know, we see these things happening in the 331 00:15:47,200 --> 00:15:49,480 Speaker 2: UK where there's a big push to privatize, and other 332 00:15:49,520 --> 00:15:52,040 Speaker 2: countries where I've talked to people, So yeah, you know 333 00:15:52,240 --> 00:15:54,480 Speaker 2: a bit of a different perspective there. But those are 334 00:15:54,520 --> 00:15:57,440 Speaker 2: things that I worry about too, even just beyond like 335 00:15:57,480 --> 00:16:00,160 Speaker 2: the general encroachment into healthcare that these companies are. 336 00:16:00,200 --> 00:16:16,720 Speaker 4: Or do it. Let's take a quick break at our back. 337 00:16:18,960 --> 00:16:20,880 Speaker 1: What do you picture when you think of having a 338 00:16:20,920 --> 00:16:24,960 Speaker 1: full and fulfilled life. It probably looks something like engaging 339 00:16:25,000 --> 00:16:28,520 Speaker 1: with your friends and family and having fulfilling life experiences. 340 00:16:29,480 --> 00:16:32,360 Speaker 1: But if you ask some of the most influential tech leaders, 341 00:16:32,720 --> 00:16:35,160 Speaker 1: the people trying to shape what our futures will look like, 342 00:16:35,840 --> 00:16:38,520 Speaker 1: their vision of a full and fulfilled life might look 343 00:16:38,840 --> 00:16:41,840 Speaker 1: very different from whatever it is you're picturing. It might 344 00:16:41,880 --> 00:16:45,520 Speaker 1: look like more time spent on screens and more technology 345 00:16:45,600 --> 00:16:48,400 Speaker 1: encroaching on more and more aspects of our lives, from 346 00:16:48,440 --> 00:16:50,760 Speaker 1: the food we eat to how we get our medical care. 347 00:16:52,040 --> 00:16:55,400 Speaker 4: All those times you went late at night and eight 348 00:16:55,520 --> 00:16:56,560 Speaker 4: things you shouldn't have eaten. 349 00:16:56,960 --> 00:16:59,720 Speaker 2: That was a secret moment you had with your refrigerator. 350 00:17:01,720 --> 00:17:06,400 Speaker 1: That's popular podcaster, engineer and AI researcher Lex Friedman, who 351 00:17:06,400 --> 00:17:09,920 Speaker 1: has described wanting the ability to share late night meaningful 352 00:17:09,960 --> 00:17:13,560 Speaker 1: moments with his smart refrigerator. But what if I want 353 00:17:13,560 --> 00:17:16,560 Speaker 1: a future where I'm sharing meaningful moments with my partner 354 00:17:16,640 --> 00:17:20,560 Speaker 1: or my best friend, not a robot screen in my refrigerator. 355 00:17:21,080 --> 00:17:23,240 Speaker 1: What if the future that they want and the future 356 00:17:23,240 --> 00:17:26,280 Speaker 1: that I want for myself are two very different things. 357 00:17:27,400 --> 00:17:31,240 Speaker 1: I don't necessarily think that it's good to be encouraged 358 00:17:31,280 --> 00:17:33,399 Speaker 1: to spend more of my time in front of a 359 00:17:33,440 --> 00:17:35,800 Speaker 1: screen looking at a screen, like I want to be 360 00:17:35,840 --> 00:17:38,200 Speaker 1: in the meat space. I want to be having actual 361 00:17:38,240 --> 00:17:42,440 Speaker 1: connections with humans irl. Obviously it's a place of privilege, 362 00:17:42,480 --> 00:17:45,240 Speaker 1: like not everybody can can do that easily. I'm like, 363 00:17:45,359 --> 00:17:47,720 Speaker 1: very lucky that that is my experience in the world. 364 00:17:48,000 --> 00:17:51,760 Speaker 1: But sometimes when I would probably have said that most 365 00:17:51,800 --> 00:17:54,800 Speaker 1: people who have the ability to get out into the world, 366 00:17:55,080 --> 00:17:56,920 Speaker 1: they want that they see that as a good thing, 367 00:17:56,960 --> 00:17:59,119 Speaker 1: as a part of life. That I hear people like 368 00:17:59,200 --> 00:18:01,800 Speaker 1: Lex Friedman or something elon Musk talk, and I don't 369 00:18:01,800 --> 00:18:02,520 Speaker 1: think we're all on. 370 00:18:02,480 --> 00:18:03,240 Speaker 3: The same page. 371 00:18:03,320 --> 00:18:06,400 Speaker 1: I think that some of these people who are hugely 372 00:18:06,440 --> 00:18:11,480 Speaker 1: influential in technology, for them, how can I put this, 373 00:18:11,720 --> 00:18:15,359 Speaker 1: for them, spending more and more time, the idea of 374 00:18:15,400 --> 00:18:17,760 Speaker 1: spending more and more time in front of screens with technology, 375 00:18:17,800 --> 00:18:22,080 Speaker 1: sort of immersing yourself around technology as a human is 376 00:18:22,240 --> 00:18:25,200 Speaker 1: good and thus they are leading this, leading us into 377 00:18:25,200 --> 00:18:27,600 Speaker 1: this future where that is more and more commonplace. And 378 00:18:28,160 --> 00:18:30,879 Speaker 1: because of the way I think, partly because of the 379 00:18:30,880 --> 00:18:33,919 Speaker 1: way that like tech press sometimes covers these people, we 380 00:18:34,000 --> 00:18:36,040 Speaker 1: don't stop and think, like, well, is this the person 381 00:18:36,080 --> 00:18:38,200 Speaker 1: that we want designing the future? This person who has 382 00:18:38,320 --> 00:18:42,960 Speaker 1: like describing a very weird relationship with their robot, vacuum 383 00:18:43,080 --> 00:18:45,320 Speaker 1: or whatever, that there's not a relationship that I want 384 00:18:45,320 --> 00:18:47,160 Speaker 1: to have, But this is the person who is put 385 00:18:47,200 --> 00:18:49,440 Speaker 1: in charge of designing the future of how I will 386 00:18:49,880 --> 00:18:51,720 Speaker 1: relate with technology, do you know what I mean? 387 00:18:52,280 --> 00:18:55,520 Speaker 2: Absolutely? Absolutely, And like I think, I think there's so 388 00:18:55,560 --> 00:18:58,840 Speaker 2: many things like to explore there basically, but I think, 389 00:18:58,960 --> 00:19:01,639 Speaker 2: like on a large I think I would say that, 390 00:19:01,760 --> 00:19:06,080 Speaker 2: like I I wonder to what degree like the views 391 00:19:06,080 --> 00:19:08,560 Speaker 2: and perspectives of these people at the top of the 392 00:19:08,600 --> 00:19:12,280 Speaker 2: tech industry are actually kind of like you know, reflective 393 00:19:12,359 --> 00:19:15,600 Speaker 2: of wider desires among like the average public, and I 394 00:19:15,640 --> 00:19:18,600 Speaker 2: would say it's actually quite limited. Like I think that 395 00:19:18,720 --> 00:19:21,560 Speaker 2: people are definitely like excited by the idea of humans 396 00:19:21,600 --> 00:19:24,560 Speaker 2: doing more in space, and people generally like the idea 397 00:19:24,680 --> 00:19:27,520 Speaker 2: of like electric cars, and sure there's some conservatives who 398 00:19:27,520 --> 00:19:29,520 Speaker 2: don't like that, but like you know, in general, like 399 00:19:29,560 --> 00:19:32,680 Speaker 2: I think these broad ideas are things that people find appealing. 400 00:19:32,880 --> 00:19:34,600 Speaker 2: But I think that if you dig into like the 401 00:19:34,680 --> 00:19:39,080 Speaker 2: more kind of niche, the more kind of specific viewpoints 402 00:19:39,160 --> 00:19:41,800 Speaker 2: of these influential tech leaders, I think that you'll quickly 403 00:19:41,840 --> 00:19:44,280 Speaker 2: find that if people knew more about them, they would 404 00:19:44,280 --> 00:19:48,640 Speaker 2: think that it was really weird and like really separate 405 00:19:48,760 --> 00:19:51,880 Speaker 2: from what most people think like a good life actually 406 00:19:51,920 --> 00:19:54,600 Speaker 2: looks like. And I think, like, you know, maybe this 407 00:19:54,640 --> 00:19:56,720 Speaker 2: is a bit stereotypical, but I think a bit of 408 00:19:56,760 --> 00:19:59,359 Speaker 2: that is related to how a lot of these people 409 00:19:59,440 --> 00:20:02,120 Speaker 2: in the tech and who are successful in this particular 410 00:20:02,119 --> 00:20:06,399 Speaker 2: industry do seem to be like socially stunted in many ways. 411 00:20:06,440 --> 00:20:08,760 Speaker 2: If you look at the Zuckerbergs, the Elon Musks, like 412 00:20:09,119 --> 00:20:11,119 Speaker 2: you know, Lex Friedman. Of course you mentioned like a 413 00:20:11,119 --> 00:20:13,560 Speaker 2: lot of these people do seem to have difficulty with 414 00:20:13,680 --> 00:20:17,240 Speaker 2: like social relationships, and I'm not going to like diagnose 415 00:20:17,240 --> 00:20:20,479 Speaker 2: them on this podcast, but I think that also shapes 416 00:20:20,520 --> 00:20:23,200 Speaker 2: the way that they think society should be set up 417 00:20:23,280 --> 00:20:25,879 Speaker 2: and like what the future should look like. And so 418 00:20:26,320 --> 00:20:28,959 Speaker 2: we have these people who are like very kind of 419 00:20:29,160 --> 00:20:33,360 Speaker 2: socially isolated and have difficulty relating to other people then 420 00:20:33,480 --> 00:20:36,280 Speaker 2: kind of trying to design or trying to dream up, 421 00:20:36,520 --> 00:20:39,240 Speaker 2: like what society is going to look like for everybody else, 422 00:20:39,280 --> 00:20:43,120 Speaker 2: and that naturally shapes how they think that that society 423 00:20:43,119 --> 00:20:45,240 Speaker 2: should look and how we should all interact with one 424 00:20:45,240 --> 00:20:47,840 Speaker 2: another in the future, when most of us don't have 425 00:20:47,920 --> 00:20:51,440 Speaker 2: that issue and would like to spend more time kind 426 00:20:51,440 --> 00:20:53,639 Speaker 2: of getting to know other people. And of course we 427 00:20:53,760 --> 00:20:57,000 Speaker 2: know right now that you know, there's plenty of talk 428 00:20:57,040 --> 00:21:00,479 Speaker 2: about it, there's kind of like a loneliness crisis in 429 00:21:00,800 --> 00:21:03,920 Speaker 2: you know, I would say, like the Western world probably broadly, 430 00:21:05,040 --> 00:21:07,679 Speaker 2: and like I think that that is linked one to 431 00:21:07,760 --> 00:21:10,280 Speaker 2: our grater reliance on technology, but I would like go 432 00:21:10,400 --> 00:21:12,520 Speaker 2: back much further and say that it's also a result 433 00:21:12,560 --> 00:21:15,320 Speaker 2: of the way that we've designed our communities to be like, 434 00:21:15,640 --> 00:21:18,280 Speaker 2: you know, very suburban in many cases, so you're really 435 00:21:18,800 --> 00:21:20,920 Speaker 2: distanced from a lot of the people that you might 436 00:21:20,960 --> 00:21:23,280 Speaker 2: care about, and it becomes more difficult to actually reach 437 00:21:23,320 --> 00:21:25,919 Speaker 2: them because of transportation all these sorts of things. So like, 438 00:21:25,960 --> 00:21:27,959 Speaker 2: I think that's rooted in like, you know, much more 439 00:21:28,040 --> 00:21:31,400 Speaker 2: kind of like physical geographical problems. And then the tech 440 00:21:31,400 --> 00:21:33,960 Speaker 2: industry because of this is how it works. It responds 441 00:21:34,000 --> 00:21:36,920 Speaker 2: that by saying, not, maybe we should rethink the way 442 00:21:36,920 --> 00:21:38,840 Speaker 2: that our communities are set up so that we can 443 00:21:38,960 --> 00:21:42,840 Speaker 2: encourage like, you know, people to live closer together, for 444 00:21:42,960 --> 00:21:45,879 Speaker 2: us to like fund public social spaces where people can 445 00:21:45,920 --> 00:21:48,800 Speaker 2: come together and you know, they don't need to you know, 446 00:21:48,880 --> 00:21:52,760 Speaker 2: pay to go somewhere to do something. But also beyond that, 447 00:21:52,800 --> 00:21:55,800 Speaker 2: they would say, like instead of proposing those things that 448 00:21:55,800 --> 00:21:57,720 Speaker 2: that might actually address the issue, they would say, you 449 00:21:57,720 --> 00:21:59,960 Speaker 2: know what we need to actually make people more social 450 00:22:00,080 --> 00:22:02,879 Speaker 2: or make people interact with one another more, is actually 451 00:22:02,920 --> 00:22:04,960 Speaker 2: a new technology that will enable them to do that, 452 00:22:05,000 --> 00:22:07,960 Speaker 2: where whether it's like Facebook and how that is kind 453 00:22:07,960 --> 00:22:10,879 Speaker 2: of imagined to connect the world, or like the metaverse, 454 00:22:10,920 --> 00:22:13,760 Speaker 2: because now we don't need to go spend time with 455 00:22:13,840 --> 00:22:16,240 Speaker 2: people in person. We can just put on a VR 456 00:22:16,280 --> 00:22:18,520 Speaker 2: headset and we can put on these other technologies on 457 00:22:18,560 --> 00:22:20,439 Speaker 2: our hands and on our bodies. That allows us to 458 00:22:20,440 --> 00:22:23,520 Speaker 2: feel a physical presence in a virtual environment. And like 459 00:22:23,840 --> 00:22:26,159 Speaker 2: great for all the tech companies because they're constantly tracking us, 460 00:22:26,200 --> 00:22:27,840 Speaker 2: they're getting all the data on us, they're showing us 461 00:22:27,880 --> 00:22:30,000 Speaker 2: ads all the time. We're in this virtual world that 462 00:22:30,040 --> 00:22:32,720 Speaker 2: they completely control. But I think it's like a terrible 463 00:22:32,760 --> 00:22:34,560 Speaker 2: idea of what a future would look like if we 464 00:22:34,600 --> 00:22:37,120 Speaker 2: actually like moved in that direction instead of just saying, hey, 465 00:22:37,320 --> 00:22:39,080 Speaker 2: maybe we should make it easier for you to see 466 00:22:39,080 --> 00:22:42,120 Speaker 2: the people that you care about and get away from 467 00:22:42,119 --> 00:22:44,200 Speaker 2: the technology that these companies want you to be looking 468 00:22:44,240 --> 00:22:44,960 Speaker 2: at all the time. 469 00:22:45,320 --> 00:22:50,119 Speaker 1: And I think there is a fundamental fuckery happening with 470 00:22:50,440 --> 00:22:54,400 Speaker 1: us as regular people and the people who make technology 471 00:22:54,400 --> 00:22:56,520 Speaker 1: and make money from us regular people. I think there 472 00:22:56,600 --> 00:23:01,359 Speaker 1: is a fundamental fucked up relationship that we really need 473 00:23:01,359 --> 00:23:03,720 Speaker 1: to question, like and I think part of it is 474 00:23:03,720 --> 00:23:05,639 Speaker 1: that tech leaders have been able to convince us, the 475 00:23:06,040 --> 00:23:09,000 Speaker 1: regular people, quote unquote, that we're not smart enough to 476 00:23:09,080 --> 00:23:13,280 Speaker 1: understand it. These people are geniuses. They went to Harvard Honey, like, 477 00:23:13,359 --> 00:23:16,120 Speaker 1: they know how to code. You'll never even be able 478 00:23:16,119 --> 00:23:19,400 Speaker 1: to figure it out. So this technology that is already 479 00:23:19,440 --> 00:23:21,960 Speaker 1: impacting so much of your life shaping your day to 480 00:23:22,080 --> 00:23:25,800 Speaker 1: day that is like a meshed with your daily experiences. 481 00:23:26,200 --> 00:23:28,000 Speaker 1: You don't even need to ask questions about it, right, 482 00:23:28,080 --> 00:23:31,359 Speaker 1: Like you don't even get to who are you tech? 483 00:23:31,440 --> 00:23:31,840 Speaker 3: Question? 484 00:23:32,240 --> 00:23:34,200 Speaker 1: These tech leaders who are so smart you don't even 485 00:23:34,320 --> 00:23:37,320 Speaker 1: understand how what do you think needs to be done 486 00:23:37,359 --> 00:23:39,600 Speaker 1: to Really I believe we need to shift that relationship 487 00:23:39,680 --> 00:23:40,440 Speaker 1: like massively. 488 00:23:40,760 --> 00:23:41,880 Speaker 3: Do you think that's possible? 489 00:23:41,880 --> 00:23:44,440 Speaker 1: Because none of this technology you would exist without us, 490 00:23:44,720 --> 00:23:46,840 Speaker 1: yet you wouldn't know that from the way that, I 491 00:23:46,880 --> 00:23:51,280 Speaker 1: feel like tech leaders continue to expand upon this like 492 00:23:51,320 --> 00:23:53,760 Speaker 1: fucked up relationship between quote regular people. 493 00:23:54,760 --> 00:23:58,000 Speaker 2: Yeah. Absolutely, It's like they are kind of like, you 494 00:23:58,040 --> 00:24:01,080 Speaker 2: know that they are kind of gifted with this superior intelligence, 495 00:24:01,080 --> 00:24:03,560 Speaker 2: and they're looking down at us and saying, we're gifting 496 00:24:03,600 --> 00:24:06,080 Speaker 2: you with this knowledge. You know, just use it properly, right. 497 00:24:06,320 --> 00:24:08,399 Speaker 2: And I think that you also see that reflected in 498 00:24:08,440 --> 00:24:13,000 Speaker 2: like the discourse around how government understands technology and whether 499 00:24:13,040 --> 00:24:16,640 Speaker 2: government can regulate technology, And every single time that there's 500 00:24:16,720 --> 00:24:19,440 Speaker 2: like a new technology or we're discussing tech policy or 501 00:24:19,480 --> 00:24:22,600 Speaker 2: something like that, like one of the narratives that we 502 00:24:22,640 --> 00:24:25,920 Speaker 2: constantly hear is, uh, you know, the political leaders don't 503 00:24:25,960 --> 00:24:28,399 Speaker 2: get it they're too old like whatever it is, so 504 00:24:28,880 --> 00:24:31,600 Speaker 2: they can't respond to this, they can't do anything about it. 505 00:24:31,640 --> 00:24:34,359 Speaker 2: And inherently, like within that narrative is you know, we 506 00:24:34,520 --> 00:24:38,000 Speaker 2: just need to trust like the tech leaders to regulate themselves, 507 00:24:38,040 --> 00:24:40,600 Speaker 2: to like be ethical. If we just put a bit 508 00:24:40,640 --> 00:24:43,639 Speaker 2: more pressure on them, then they'll be better, right, you know, 509 00:24:43,800 --> 00:24:46,720 Speaker 2: don't be evil the old Google slogan, when we know 510 00:24:46,760 --> 00:24:48,240 Speaker 2: that they're very evil. 511 00:24:47,960 --> 00:24:50,520 Speaker 3: Actually killing technology. 512 00:24:50,960 --> 00:24:53,600 Speaker 2: Yeah, like that, don't talk about that, you. 513 00:24:53,560 --> 00:24:55,760 Speaker 3: Know, we don't talk about the death tech. 514 00:24:56,200 --> 00:24:59,240 Speaker 2: Yeah. Yeah, they're just making nice search engines that talk 515 00:24:59,280 --> 00:25:02,240 Speaker 2: to us. Now. It's very nice, it's very beautiful. I 516 00:25:02,240 --> 00:25:05,880 Speaker 2: think ultimately, like shifting our perspective on these things is essential, right, 517 00:25:06,040 --> 00:25:08,560 Speaker 2: And I think that we're in this moment where, you know, 518 00:25:08,760 --> 00:25:11,280 Speaker 2: as I was saying earlier, like during the early part 519 00:25:11,320 --> 00:25:13,679 Speaker 2: of the twenty tens, the mid twenty tens, like you know, 520 00:25:13,720 --> 00:25:16,679 Speaker 2: we were kind of generally, you know, we as a 521 00:25:16,760 --> 00:25:19,719 Speaker 2: general we kind of like infatuated with the tech industry, right, 522 00:25:19,760 --> 00:25:21,879 Speaker 2: they could do no wrong. All the reporting was like 523 00:25:22,000 --> 00:25:24,320 Speaker 2: these great companies who are doing so many great things 524 00:25:24,320 --> 00:25:26,760 Speaker 2: for us. Then near the end of the twenty tens 525 00:25:26,800 --> 00:25:28,960 Speaker 2: and kind of through the early twenty twenties, we have 526 00:25:29,040 --> 00:25:31,760 Speaker 2: this shift where all of a sudden, you know, we're 527 00:25:31,800 --> 00:25:34,879 Speaker 2: recognizing that maybe we shouldn't have been so positive, so 528 00:25:35,200 --> 00:25:37,960 Speaker 2: kind of uncritical of what they were doing, and there's 529 00:25:38,000 --> 00:25:40,880 Speaker 2: a broader kind of recognition that these companies do need 530 00:25:40,920 --> 00:25:45,199 Speaker 2: more kind of critical you know, critical analysis, critical insight, 531 00:25:45,320 --> 00:25:47,760 Speaker 2: We need to actually be looking at what they're what 532 00:25:47,800 --> 00:25:52,000 Speaker 2: they're doing, right. And I think that that's important because 533 00:25:52,440 --> 00:25:54,680 Speaker 2: I think that, on one hand, like it does kind 534 00:25:54,720 --> 00:25:56,600 Speaker 2: of bring the public along, and it does kind of 535 00:25:56,600 --> 00:25:59,040 Speaker 2: tell the public like, you know, maybe all that we 536 00:25:59,040 --> 00:26:01,199 Speaker 2: were saying before and all that it was cracked up 537 00:26:01,240 --> 00:26:03,960 Speaker 2: to be, and actually these tech companies deserve more scrutiny. 538 00:26:04,840 --> 00:26:07,040 Speaker 2: But I think it also kind of what you see 539 00:26:07,080 --> 00:26:10,399 Speaker 2: in that moment as well, is that the people in 540 00:26:10,520 --> 00:26:13,440 Speaker 2: charge of the tech industry were used to being treated 541 00:26:13,840 --> 00:26:16,439 Speaker 2: like these kind of godlike figures, Like these kind of 542 00:26:16,720 --> 00:26:19,159 Speaker 2: figures who were you know, giving us all this intelligence, 543 00:26:19,160 --> 00:26:21,520 Speaker 2: who we kind of worshiped, you know, like if you 544 00:26:21,600 --> 00:26:23,520 Speaker 2: think of like how Steve Jobs used to be seen 545 00:26:23,560 --> 00:26:26,200 Speaker 2: and he was handing us down our iPods and our 546 00:26:26,480 --> 00:26:29,359 Speaker 2: things like that, right, like he was worshiped, right, it 547 00:26:29,400 --> 00:26:31,520 Speaker 2: was it was basically like a like a religion. And 548 00:26:31,600 --> 00:26:34,520 Speaker 2: I find it interesting if you look at the like 549 00:26:34,600 --> 00:26:37,440 Speaker 2: auditorium that Apple has created on their Apple campus. Now, 550 00:26:37,560 --> 00:26:39,800 Speaker 2: like to me, if you look at it, like it 551 00:26:39,840 --> 00:26:41,919 Speaker 2: has the vibes of a church kind of and like 552 00:26:41,960 --> 00:26:43,920 Speaker 2: pews and all this sort of like this is how 553 00:26:43,920 --> 00:26:45,760 Speaker 2: I feel when I look at it. Right, But anyway, 554 00:26:46,119 --> 00:26:50,119 Speaker 2: this is this is not the point. But if you 555 00:26:50,160 --> 00:26:52,840 Speaker 2: look at what happened as the press became more critical, 556 00:26:52,880 --> 00:26:55,000 Speaker 2: and as the public became more critical, and as the 557 00:26:55,040 --> 00:26:58,040 Speaker 2: government became more critical of the tech industry, all of 558 00:26:58,080 --> 00:27:00,400 Speaker 2: a sudden, you have these tech leaders who are used 559 00:27:00,400 --> 00:27:04,240 Speaker 2: to being worshiped start to shift how they are responding, right, 560 00:27:04,320 --> 00:27:07,160 Speaker 2: and all of a sudden, they are feeling like victimized. 561 00:27:07,320 --> 00:27:10,320 Speaker 2: You know, they are kind of all powerful, they're billionaires, 562 00:27:10,320 --> 00:27:11,960 Speaker 2: they're some of the richest people in the world, but 563 00:27:12,000 --> 00:27:14,480 Speaker 2: they are treating themselves like victims because all of a sudden, 564 00:27:14,520 --> 00:27:17,600 Speaker 2: we're not worshiping everything that they do and just thinking that, 565 00:27:17,920 --> 00:27:19,520 Speaker 2: you know, everything that they do is positive. 566 00:27:20,160 --> 00:27:23,919 Speaker 1: Back in twenty twenty, Silicon Valley billionaire and venture capitalists 567 00:27:23,920 --> 00:27:27,560 Speaker 1: Mark Andresen published an essay called It's Time to Build, 568 00:27:28,200 --> 00:27:31,200 Speaker 1: encouraging Silicon Valley tech leaders to be more involved in 569 00:27:31,320 --> 00:27:34,440 Speaker 1: building and shaping America. We've already seen more and more 570 00:27:34,480 --> 00:27:37,640 Speaker 1: tech leaders getting involved in politics and government. But when 571 00:27:37,720 --> 00:27:40,800 Speaker 1: these people who have the power to exert such control 572 00:27:40,880 --> 00:27:44,800 Speaker 1: over our futures embrace ideologies that are harmful, like long 573 00:27:44,880 --> 00:27:49,200 Speaker 1: termism to pro natalism, an ideology embraced by Elon Musk 574 00:27:49,320 --> 00:27:52,280 Speaker 1: that posits that all the really wealthy tech people should 575 00:27:52,320 --> 00:27:54,960 Speaker 1: be having lots and lots of kids to pass down 576 00:27:55,000 --> 00:27:59,320 Speaker 1: their superior genes and repopulate the earth with their super babies. 577 00:28:00,080 --> 00:28:02,000 Speaker 1: It's kind of hard to imagine that it'll be a 578 00:28:02,040 --> 00:28:04,119 Speaker 1: future that's better for all of us. 579 00:28:04,440 --> 00:28:09,080 Speaker 2: We've seen that kind of slowly become clearer in recent years, 580 00:28:09,080 --> 00:28:11,840 Speaker 2: where you have people like Mark Andrieson kind of pushing 581 00:28:11,880 --> 00:28:14,040 Speaker 2: back on this, you know, releasing in twenty twenty that 582 00:28:14,080 --> 00:28:16,520 Speaker 2: it's time to build essay where he's really saying like, 583 00:28:16,840 --> 00:28:18,919 Speaker 2: Silicon Valley needs to be more forceful and needs to 584 00:28:18,920 --> 00:28:23,199 Speaker 2: be involved in like much more of society, kind of 585 00:28:23,359 --> 00:28:26,760 Speaker 2: you know, ensuring that they are shaping society in the 586 00:28:26,800 --> 00:28:29,000 Speaker 2: way that they think it should operate. But then you 587 00:28:29,040 --> 00:28:31,920 Speaker 2: also see, like you know, people like David Sachs getting 588 00:28:31,920 --> 00:28:34,679 Speaker 2: more involved in politics, you know, donating more. Obviously you 589 00:28:34,680 --> 00:28:37,000 Speaker 2: have Peter Tiel, but he's been at it much longer 590 00:28:37,040 --> 00:28:38,920 Speaker 2: than that. He has a kind of a larger project. 591 00:28:39,760 --> 00:28:42,800 Speaker 2: And obviously more recently you see Elon Musk becoming much 592 00:28:42,800 --> 00:28:45,200 Speaker 2: more open about his politics. But this is indicative of 593 00:28:45,240 --> 00:28:48,960 Speaker 2: a broader shift that we're seeing in the Valley away 594 00:28:49,080 --> 00:28:51,719 Speaker 2: from kind of, you know, these people being seen as 595 00:28:51,800 --> 00:28:55,520 Speaker 2: like liberal Democrats or whatever, toward the recognition that you know, 596 00:28:55,560 --> 00:28:58,160 Speaker 2: these are powerful capitalists at the head of an industry, 597 00:28:58,600 --> 00:29:01,600 Speaker 2: and now instead of being more they are being challenged 598 00:29:01,600 --> 00:29:03,840 Speaker 2: and their position is being challenged, and they want to 599 00:29:03,960 --> 00:29:07,720 Speaker 2: ensure that everyone understands that they actually deserve the position 600 00:29:07,800 --> 00:29:10,200 Speaker 2: that they're in. They didn't just get it because they 601 00:29:10,280 --> 00:29:12,560 Speaker 2: happened to be in the right place at the right 602 00:29:12,600 --> 00:29:15,040 Speaker 2: time when this massive industry was taking off and there 603 00:29:15,080 --> 00:29:18,200 Speaker 2: was a dot com boom, and they their startup was 604 00:29:18,240 --> 00:29:20,560 Speaker 2: one of the ones that rode the wave, and that 605 00:29:20,680 --> 00:29:23,000 Speaker 2: kind of gave them allowed them to like luck in 606 00:29:23,280 --> 00:29:26,120 Speaker 2: and use their already privileged positions to then kind of 607 00:29:26,120 --> 00:29:28,280 Speaker 2: take off to this new level. Right, And so I 608 00:29:28,320 --> 00:29:30,880 Speaker 2: think that is why we see, especially in the past 609 00:29:30,880 --> 00:29:35,120 Speaker 2: few years, them embracing these particular ideologies that are all 610 00:29:35,120 --> 00:29:38,600 Speaker 2: around kind of ensuring that the public believes that they 611 00:29:38,640 --> 00:29:40,640 Speaker 2: deserve the position that they're in, that they deserve the 612 00:29:40,680 --> 00:29:42,680 Speaker 2: wealth that they're in. And you know, when I say that, 613 00:29:42,720 --> 00:29:45,840 Speaker 2: I mean things like effective altruism, which I say is 614 00:29:45,840 --> 00:29:49,200 Speaker 2: basically the notion that like, you know, there's nothing wrong 615 00:29:49,240 --> 00:29:52,480 Speaker 2: with philanthropy, with there's nothing wrong with philanthropy, there's nothing 616 00:29:52,520 --> 00:29:55,560 Speaker 2: wrong with rich people. And how we actually solve our 617 00:29:55,600 --> 00:29:58,400 Speaker 2: problems is not by challenging rich people and taxing them more, 618 00:29:58,520 --> 00:30:01,240 Speaker 2: but ensuring they spend their billion of dollars more effectively 619 00:30:01,280 --> 00:30:06,320 Speaker 2: to address problems, or like long termism that says, you know, actually, yeah, 620 00:30:06,440 --> 00:30:09,200 Speaker 2: sure we face these problems right now in society, but 621 00:30:09,720 --> 00:30:11,160 Speaker 2: you know, we need to be thinking on a much 622 00:30:11,200 --> 00:30:14,800 Speaker 2: longer time horizon. And you regular people, the you know, 623 00:30:14,880 --> 00:30:17,000 Speaker 2: the means and yous and the listeners of this podcast 624 00:30:17,000 --> 00:30:20,120 Speaker 2: in the world, we are too kind of involved and 625 00:30:20,400 --> 00:30:22,960 Speaker 2: to thinking our thinking too much about the day to 626 00:30:23,040 --> 00:30:25,160 Speaker 2: day and how we're going to pay our bills and 627 00:30:25,200 --> 00:30:27,480 Speaker 2: on all these sorts of things. So we can't think 628 00:30:27,520 --> 00:30:30,000 Speaker 2: on these time horizons. So we need these wealthy people 629 00:30:30,040 --> 00:30:31,760 Speaker 2: like the Elon Musks of the world and the Jeff 630 00:30:31,760 --> 00:30:34,160 Speaker 2: bezos Is of the world to do that work for us, 631 00:30:34,160 --> 00:30:35,880 Speaker 2: So they need to be up there and thinking about 632 00:30:35,920 --> 00:30:39,440 Speaker 2: space colonization and all this bullshit, right. And then of 633 00:30:39,480 --> 00:30:41,160 Speaker 2: course the other piece of this, I would say, is 634 00:30:41,200 --> 00:30:44,600 Speaker 2: like the pronatalism that we're seeing as well, which is like, 635 00:30:44,720 --> 00:30:47,200 Speaker 2: you know, really kind of bringing the eugenics thinking back 636 00:30:47,200 --> 00:30:49,720 Speaker 2: into this eugenics thinking that has always been around in 637 00:30:50,200 --> 00:30:53,480 Speaker 2: tech circles and in Silicon Valley. You know, Stanford University 638 00:30:53,720 --> 00:30:56,960 Speaker 2: was kind of a hotbed of eugenics thinking and kind 639 00:30:57,000 --> 00:30:59,560 Speaker 2: of you know, reviving this put a fresh putting a 640 00:30:59,560 --> 00:31:02,320 Speaker 2: fresh goal on it, so that there is kind of 641 00:31:02,640 --> 00:31:06,280 Speaker 2: a new revival and a new justification for thinking about, 642 00:31:06,600 --> 00:31:10,840 Speaker 2: you know, genetics, for thinking about genes, for thinking about 643 00:31:10,920 --> 00:31:14,880 Speaker 2: kind of you know, Elon Musk really thinks that because 644 00:31:14,920 --> 00:31:17,840 Speaker 2: he is incredibly wealthy, that means as well that he's 645 00:31:17,880 --> 00:31:21,200 Speaker 2: incredibly smart, right, and that the smarts that he has 646 00:31:21,280 --> 00:31:24,600 Speaker 2: need to be passed on to future generations, to his kids, 647 00:31:24,920 --> 00:31:27,840 Speaker 2: because then, you know, if not, the world kind of 648 00:31:27,920 --> 00:31:30,840 Speaker 2: risks having all these low IQ people going around like 649 00:31:31,040 --> 00:31:33,760 Speaker 2: it's just wild thinking. But it shows you, how, you know, 650 00:31:33,840 --> 00:31:37,800 Speaker 2: in many different ways. They are invested in ensuring that 651 00:31:38,320 --> 00:31:41,360 Speaker 2: they keep their power, that they maintain their position, and 652 00:31:41,400 --> 00:31:45,400 Speaker 2: that we regular people are not challenging them, and kind 653 00:31:45,400 --> 00:31:48,040 Speaker 2: of the wealth and the power that they've accumulated over 654 00:31:48,080 --> 00:31:49,040 Speaker 2: the past few decades. 655 00:31:49,560 --> 00:31:54,080 Speaker 1: It's terrifying. It also kind of I mean, it's that's 656 00:31:54,080 --> 00:31:56,680 Speaker 1: completely anti science, right, like it doesn't work that way 657 00:31:57,160 --> 00:32:00,160 Speaker 1: if you are if you are wealthy and like you 658 00:32:00,160 --> 00:32:02,479 Speaker 1: think of yourself as like a smart person, you're not 659 00:32:02,520 --> 00:32:05,600 Speaker 1: necessarily it's antimplely anti science. But you're going to pass 660 00:32:05,680 --> 00:32:08,120 Speaker 1: that down genetically to your kids, so you better have 661 00:32:08,160 --> 00:32:09,640 Speaker 1: a million kids. 662 00:32:09,640 --> 00:32:10,760 Speaker 3: It's what's funny to me that. 663 00:32:10,720 --> 00:32:13,800 Speaker 1: These it's such a fallacy because it's both like I 664 00:32:13,840 --> 00:32:17,320 Speaker 1: am so brilliant and you know, so good at business, 665 00:32:17,320 --> 00:32:21,600 Speaker 1: blah blah blah, so I'm going to utilize this completely 666 00:32:21,880 --> 00:32:25,920 Speaker 1: nonsensical anti science way of supreading that. 667 00:32:25,960 --> 00:32:27,840 Speaker 3: It's like, well, whoa, whoa. They both can't be true. 668 00:32:27,880 --> 00:32:31,720 Speaker 1: Either you're really smart or you're like falling for something 669 00:32:31,720 --> 00:32:33,880 Speaker 1: that's completely flies in the face. 670 00:32:33,600 --> 00:32:36,240 Speaker 3: Of how genetics work at a very basic level. 671 00:32:37,280 --> 00:32:40,600 Speaker 2: Oh no, absolutely, And like you very clearly see it 672 00:32:40,720 --> 00:32:43,200 Speaker 2: reflected in like everything that they're talking about right. And 673 00:32:43,400 --> 00:32:45,400 Speaker 2: I do think it's funny because like, on the one hand, 674 00:32:45,440 --> 00:32:48,680 Speaker 2: they present themselves as these like brilliant engineers who like 675 00:32:48,800 --> 00:32:51,440 Speaker 2: understand everything, and like, you know, the whole thing about 676 00:32:51,480 --> 00:32:54,200 Speaker 2: these Silicon Valley founders is that, like you know, going 677 00:32:54,240 --> 00:32:56,600 Speaker 2: back to like the PayPal mafia days and stuff like that, 678 00:32:56,760 --> 00:33:00,239 Speaker 2: is like they really believed that they had this kind 679 00:33:00,280 --> 00:33:05,440 Speaker 2: of inherent knowledge, this knowledge that allowed them not just 680 00:33:05,480 --> 00:33:09,080 Speaker 2: to understand technology, but to move into any industry that 681 00:33:09,120 --> 00:33:12,960 Speaker 2: they thought was ripe for kind of technological disruption and 682 00:33:13,760 --> 00:33:16,320 Speaker 2: disrupt it basically. Right, you know, Elon Musk can go 683 00:33:16,360 --> 00:33:19,360 Speaker 2: into banking and cars and space and Twitter and whatever, 684 00:33:19,680 --> 00:33:23,040 Speaker 2: and because he is just the smartest person in the world, 685 00:33:23,080 --> 00:33:25,560 Speaker 2: he will know exactly what needs to happen for all 686 00:33:25,600 --> 00:33:28,000 Speaker 2: of these sectors to be transformed and made better by 687 00:33:28,000 --> 00:33:30,440 Speaker 2: the tech industry. And I think what we've actually seen, 688 00:33:30,560 --> 00:33:32,360 Speaker 2: like if we actually look at the impact of the 689 00:33:32,360 --> 00:33:34,840 Speaker 2: tech industry is that in some cases, yes, they have 690 00:33:34,960 --> 00:33:38,320 Speaker 2: made things more efficient if they have kind of organized 691 00:33:38,360 --> 00:33:41,080 Speaker 2: things properly. Like if you look at as much as 692 00:33:41,120 --> 00:33:44,640 Speaker 2: I hate Amazon, like it's supply chain and logistics system 693 00:33:44,760 --> 00:33:48,000 Speaker 2: does seem to be like, you know, quite an impressive 694 00:33:48,000 --> 00:33:50,440 Speaker 2: feat that it has put together. Right, there's a whole 695 00:33:50,440 --> 00:33:52,840 Speaker 2: load of exploitation that it's built on, and like all 696 00:33:52,840 --> 00:33:55,200 Speaker 2: that kind of stuff, Like let's not forget that, but 697 00:33:55,600 --> 00:33:58,120 Speaker 2: you know, it has kind of effectively put this system 698 00:33:58,160 --> 00:34:00,560 Speaker 2: together that like I would love to see transferred over 699 00:34:00,600 --> 00:34:02,120 Speaker 2: to the post office or something like that. 700 00:34:02,240 --> 00:34:04,600 Speaker 1: It's amazing what you could accomplish when you're like grinding 701 00:34:04,640 --> 00:34:07,160 Speaker 1: the bones of workers exactly exactly. 702 00:34:07,440 --> 00:34:09,680 Speaker 2: But then on the other hand, is like you'll have 703 00:34:09,800 --> 00:34:12,520 Speaker 2: a company like Uber, which promotes itself as like this 704 00:34:12,600 --> 00:34:16,160 Speaker 2: efficient transportation company because it's using all this technology to 705 00:34:16,320 --> 00:34:19,960 Speaker 2: like design the routes and the patterns and whatever of 706 00:34:20,280 --> 00:34:22,920 Speaker 2: how all these vehicles go. But you know, if you 707 00:34:22,960 --> 00:34:26,440 Speaker 2: look at listen to people who actually understand transportation, like 708 00:34:26,520 --> 00:34:29,360 Speaker 2: Hubert Horn, a transportation consultant who's been kind of writing 709 00:34:29,360 --> 00:34:32,520 Speaker 2: critically about Uber for years, you understand that actually their 710 00:34:32,560 --> 00:34:35,480 Speaker 2: model is like less efficient than the model that existed 711 00:34:35,520 --> 00:34:40,160 Speaker 2: before because they have lost like all of these you know, 712 00:34:40,239 --> 00:34:42,960 Speaker 2: ways of organizing the business that are actually more efficient 713 00:34:43,000 --> 00:34:45,120 Speaker 2: in that they don't have a fleet of cars. Everyone 714 00:34:45,160 --> 00:34:46,879 Speaker 2: has to own their own car and do their own 715 00:34:46,880 --> 00:34:49,480 Speaker 2: maintenance and buy their own insurance, and that's much less 716 00:34:49,480 --> 00:34:52,920 Speaker 2: efficient than what existed before. And because you have this 717 00:34:53,080 --> 00:34:57,400 Speaker 2: kind of global company that has these massive, expensive headquarters 718 00:34:57,440 --> 00:34:59,919 Speaker 2: and these like well paid executives and these high paid 719 00:35:00,080 --> 00:35:03,000 Speaker 2: tech workers and all this kind of stuff like working 720 00:35:03,080 --> 00:35:05,839 Speaker 2: on all these things, actually the cost of running that 721 00:35:05,880 --> 00:35:09,120 Speaker 2: business is higher than like a regular taxi company that 722 00:35:09,239 --> 00:35:11,759 Speaker 2: just like had a small office in a city and 723 00:35:11,840 --> 00:35:14,120 Speaker 2: like a few dispatchers and stuff like that, and like 724 00:35:14,440 --> 00:35:16,200 Speaker 2: you know, they kind of managed it and worked it out, 725 00:35:17,080 --> 00:35:18,880 Speaker 2: so so you know, and I think that there are 726 00:35:18,880 --> 00:35:21,960 Speaker 2: actually many other examples like that, where like we think 727 00:35:22,000 --> 00:35:24,400 Speaker 2: that because of the narrative around the tech industry that 728 00:35:24,440 --> 00:35:26,879 Speaker 2: oh my god, they've revolutionized all these things, they've made 729 00:35:26,880 --> 00:35:29,360 Speaker 2: everything better, But actually they've just put like the gloss 730 00:35:29,360 --> 00:35:32,640 Speaker 2: of digital tech over something that already existed and tell 731 00:35:32,719 --> 00:35:34,319 Speaker 2: us that it's better. And we kind of believe it 732 00:35:34,360 --> 00:35:36,560 Speaker 2: because this is the narrative that we have about technology. 733 00:35:36,880 --> 00:35:38,680 Speaker 2: But that isn't necessarily the case. 734 00:35:39,120 --> 00:35:41,240 Speaker 1: Yeah, And I'm so glad that folks like you exist 735 00:35:41,280 --> 00:35:43,640 Speaker 1: who are out there really trying to shift shift that 736 00:35:43,719 --> 00:35:46,480 Speaker 1: narrative and like pump the brakes and say wait a minute, 737 00:35:46,520 --> 00:35:49,480 Speaker 1: like is this actually better? Is this actually more efficient 738 00:35:49,560 --> 00:35:53,040 Speaker 1: or are we just so used to these confident men, 739 00:35:54,040 --> 00:35:55,960 Speaker 1: you know, telling us that it's better at us just 740 00:35:55,960 --> 00:35:57,919 Speaker 1: sort of believing it. Like, I think a big part 741 00:35:57,960 --> 00:36:01,080 Speaker 1: of it it's also just good old fashion hubris that 742 00:36:01,200 --> 00:36:04,680 Speaker 1: if I'm really good at building rockets, of course I 743 00:36:04,719 --> 00:36:08,680 Speaker 1: would be good at figuring out, you know, content moderation, 744 00:36:08,840 --> 00:36:11,800 Speaker 1: which is this incredibly complex thing that like people debate 745 00:36:11,800 --> 00:36:14,000 Speaker 1: all the time about how to do it right. I'm 746 00:36:14,160 --> 00:36:17,280 Speaker 1: I built a rocket, right, Like, I'm a pretty good podcaster. 747 00:36:18,239 --> 00:36:20,520 Speaker 1: That doesn't mean that I would be a good president 748 00:36:20,680 --> 00:36:23,239 Speaker 1: or that I could solve you know, uh uh, like. 749 00:36:23,480 --> 00:36:27,760 Speaker 3: Homelessness or something like. It's incredibly it's hubris. 750 00:36:27,880 --> 00:36:30,880 Speaker 1: But it's also it's so like narrow minded that you 751 00:36:30,960 --> 00:36:34,960 Speaker 1: think that because you maybe are smart in one sphere, 752 00:36:35,040 --> 00:36:37,200 Speaker 1: that that is always going to translate over because of 753 00:36:37,280 --> 00:36:39,640 Speaker 1: something particular and innate to who you are. 754 00:36:39,719 --> 00:36:41,600 Speaker 3: It's so it's I just really hate it. 755 00:36:42,400 --> 00:36:44,319 Speaker 2: Yeah, oh yeah, And I think it tells you a 756 00:36:44,360 --> 00:36:47,000 Speaker 2: ton about like who these people are and how they 757 00:36:47,000 --> 00:36:50,040 Speaker 2: think about themselves, that they do think that just because 758 00:36:50,040 --> 00:36:52,960 Speaker 2: they're successful in one arena, that they can naturally kind 759 00:36:53,000 --> 00:36:56,239 Speaker 2: of move that success into many others. Just because they 760 00:36:56,239 --> 00:36:58,319 Speaker 2: are like, you know, they've been graced with this like 761 00:36:58,360 --> 00:37:02,000 Speaker 2: an inherent intelligence. And you know, the tech industry for 762 00:37:02,080 --> 00:37:05,240 Speaker 2: whatever reason, is like can just do everything and whatever, 763 00:37:05,960 --> 00:37:07,839 Speaker 2: and you know, they also kind of like apply this 764 00:37:07,920 --> 00:37:11,239 Speaker 2: kind of software mindset to everything to the physical world 765 00:37:11,320 --> 00:37:13,839 Speaker 2: even when it doesn't doesn't work out. And so, you know, 766 00:37:13,880 --> 00:37:16,320 Speaker 2: I think that one of the things that's been refreshing 767 00:37:16,360 --> 00:37:18,920 Speaker 2: over the past few years is to see kind of 768 00:37:19,000 --> 00:37:23,000 Speaker 2: a greater awareness around you know, these people and their 769 00:37:23,000 --> 00:37:26,279 Speaker 2: flaws and how they're not kind of like messiahs and 770 00:37:26,560 --> 00:37:28,640 Speaker 2: great people who are like making the world better, but 771 00:37:28,680 --> 00:37:32,360 Speaker 2: actually like you know, exploiters who you know, are making 772 00:37:32,400 --> 00:37:35,759 Speaker 2: massive profits off of a ton of workers, workers who 773 00:37:35,760 --> 00:37:39,480 Speaker 2: they're trying to like hide behind, you know, the kind 774 00:37:39,520 --> 00:37:43,759 Speaker 2: of veil of technology, but actually you know, they are 775 00:37:44,080 --> 00:37:46,920 Speaker 2: creating these systems that are built on exploitation. And like 776 00:37:47,000 --> 00:37:50,799 Speaker 2: generative AI of course is another version of this. You know, 777 00:37:51,120 --> 00:37:53,440 Speaker 2: even though it's presented as just being like all the 778 00:37:53,520 --> 00:37:56,600 Speaker 2: tech technology and computers like doing all this magical stuff, 779 00:37:56,840 --> 00:37:59,080 Speaker 2: there's there's always kind of workers below it that like 780 00:37:59,120 --> 00:38:01,640 Speaker 2: we like to ignore. And so I think one of 781 00:38:01,680 --> 00:38:04,400 Speaker 2: the things that's been positive is seeing people wake up 782 00:38:04,440 --> 00:38:06,880 Speaker 2: a bit more, and certainly not everyone has, certainly, like 783 00:38:07,080 --> 00:38:09,000 Speaker 2: you know, I would like more people to have done so, 784 00:38:09,160 --> 00:38:11,239 Speaker 2: But I still think it's positive to see us moving 785 00:38:11,280 --> 00:38:13,520 Speaker 2: in this direction. To see that like as soon as 786 00:38:13,560 --> 00:38:17,799 Speaker 2: new technologies are announced and kind of unveiled and rolled 787 00:38:17,800 --> 00:38:21,000 Speaker 2: out now that you know, very quickly, there's a discussion 788 00:38:21,040 --> 00:38:23,680 Speaker 2: around you know, does this make sense? Should we be 789 00:38:23,719 --> 00:38:25,920 Speaker 2: regulating it? Like what are we doing about this? Like 790 00:38:25,960 --> 00:38:29,040 Speaker 2: we see whitchat GBT, or we saw about the metaverse, 791 00:38:29,080 --> 00:38:31,799 Speaker 2: like people just quickly ridiculing it as soon as Mark 792 00:38:31,880 --> 00:38:34,600 Speaker 2: Zuckerberg rolled it out, And like, I think that's a 793 00:38:34,640 --> 00:38:37,399 Speaker 2: really positive like change, because I wonder if we would 794 00:38:37,440 --> 00:38:40,440 Speaker 2: have saw that like a decade or so ago. And also, 795 00:38:40,560 --> 00:38:43,560 Speaker 2: like you know, how Crypto was. Sure you had a 796 00:38:43,560 --> 00:38:45,719 Speaker 2: lot of people who were like really invested in it 797 00:38:45,760 --> 00:38:48,120 Speaker 2: and really believe that crypto is the future and whatever, 798 00:38:48,320 --> 00:38:50,880 Speaker 2: but you also had this really strong community who was saying, like, 799 00:38:50,960 --> 00:38:53,440 Speaker 2: hold up, this does not make any sense. This is 800 00:38:53,520 --> 00:38:57,040 Speaker 2: just spammy, exploitative Ponzi schemes, and we can't allow this 801 00:38:57,120 --> 00:38:59,120 Speaker 2: to go anywhere. And I think that we've seen like 802 00:38:59,200 --> 00:39:03,200 Speaker 2: the you know, the kind of the steam kind of 803 00:39:03,239 --> 00:39:06,520 Speaker 2: has come out of that bubble right like it has collapsedure, 804 00:39:06,560 --> 00:39:08,759 Speaker 2: they're not all gone, but I think that these things 805 00:39:08,760 --> 00:39:10,680 Speaker 2: are like positive and they give me some hope that 806 00:39:10,760 --> 00:39:13,320 Speaker 2: like we're at least sort of going in the right direction, 807 00:39:13,719 --> 00:39:15,719 Speaker 2: and we just need to keep kind of you know, 808 00:39:15,800 --> 00:39:18,719 Speaker 2: keeping up the good fight to ensure that as you know, 809 00:39:18,800 --> 00:39:21,080 Speaker 2: the tech industry keeps kind of pushing these new waves 810 00:39:21,080 --> 00:39:23,520 Speaker 2: of hype that you know, there are critics who are 811 00:39:23,520 --> 00:39:26,000 Speaker 2: around who are looking at what's happening and saying, like, 812 00:39:26,320 --> 00:39:28,719 Speaker 2: hold up just a minute. What these people say are 813 00:39:28,760 --> 00:39:32,440 Speaker 2: saying like makes absolutely no sense, and we need to 814 00:39:32,440 --> 00:39:35,120 Speaker 2: be looking not at like the pr and the marketing 815 00:39:35,160 --> 00:39:38,080 Speaker 2: lines that these companies and you know, the executives like 816 00:39:38,080 --> 00:39:40,279 Speaker 2: Sam Altman want us to be thinking about and looking 817 00:39:40,320 --> 00:39:44,080 Speaker 2: at and talking talking about, but to actually look at 818 00:39:44,120 --> 00:39:47,319 Speaker 2: the real impacts, to like be informed by history and 819 00:39:47,440 --> 00:39:49,400 Speaker 2: how these things have worked out in the past, because 820 00:39:49,440 --> 00:39:53,720 Speaker 2: the tech industry loves to ignore history and to actually 821 00:39:53,719 --> 00:39:56,280 Speaker 2: try to like get some lessons about what might happen 822 00:39:56,600 --> 00:40:00,359 Speaker 2: so that we can respond like proactively, instead of being 823 00:40:00,440 --> 00:40:02,960 Speaker 2: a few years down the line and realizing, like, man, 824 00:40:03,000 --> 00:40:04,600 Speaker 2: we've let this go a bit too far. It might 825 00:40:04,640 --> 00:40:06,719 Speaker 2: be impossible to roll it back at this point, right, 826 00:40:07,280 --> 00:40:09,040 Speaker 2: So yeah, I take some hope from those things. 827 00:40:12,440 --> 00:40:12,600 Speaker 3: More. 828 00:40:12,640 --> 00:40:25,839 Speaker 1: After a quick break, let's get right back into it. 829 00:40:27,400 --> 00:40:31,439 Speaker 1: When Zuckerberg started hyping up the metaverse, everybody pretty much 830 00:40:31,520 --> 00:40:33,719 Speaker 1: just made fun of him until he dropped it. And 831 00:40:33,800 --> 00:40:37,160 Speaker 1: before the crypto crash, it was crypto critics who wouldn't 832 00:40:37,160 --> 00:40:40,600 Speaker 1: stop calling it out as a scam. And now we 833 00:40:40,680 --> 00:40:44,000 Speaker 1: need to be ready to call out AI hype, especially 834 00:40:44,040 --> 00:40:47,960 Speaker 1: when it's hype that just ends up hurting workers. I 835 00:40:48,000 --> 00:40:53,240 Speaker 1: am almost embarrassed to admit this, but I am very confused. 836 00:40:52,760 --> 00:40:54,440 Speaker 3: About I get asked about this a lot. 837 00:40:54,480 --> 00:40:56,440 Speaker 1: I'm always like, oh, I don't know the role that 838 00:40:56,880 --> 00:40:58,759 Speaker 1: generative AI will play in our future. And I think 839 00:40:58,800 --> 00:41:01,040 Speaker 1: part of it is I think that I shouldn't feel 840 00:41:01,040 --> 00:41:03,160 Speaker 1: too bad because I think this is by design. There 841 00:41:03,200 --> 00:41:05,840 Speaker 1: is so much just pr speak that I feel like 842 00:41:05,880 --> 00:41:08,840 Speaker 1: I don't have a good sense of what is actually 843 00:41:08,840 --> 00:41:10,560 Speaker 1: going on. And I listened to the episode that you 844 00:41:10,640 --> 00:41:12,600 Speaker 1: did with Julia Black and she made such a good 845 00:41:12,600 --> 00:41:16,120 Speaker 1: point that when she asked Sam Altman, like straight up, okay, 846 00:41:16,160 --> 00:41:18,879 Speaker 1: so for a like, imagine who you think of as 847 00:41:18,880 --> 00:41:21,600 Speaker 1: like a typical American how will this change? How will 848 00:41:21,640 --> 00:41:24,560 Speaker 1: AI change her life in ten years? And that he 849 00:41:25,120 --> 00:41:27,160 Speaker 1: not only didn't have an answer, that it was like 850 00:41:27,440 --> 00:41:30,400 Speaker 1: he had not thought about the question. And I was like, 851 00:41:30,440 --> 00:41:33,120 Speaker 1: oh God, that's not good. And so I think that 852 00:41:33,160 --> 00:41:36,239 Speaker 1: we hear so much pr speak. We hear so much 853 00:41:36,360 --> 00:41:39,719 Speaker 1: like AI is gonna change everything, It's gonna take all 854 00:41:39,760 --> 00:41:42,000 Speaker 1: of our jobs, and then people saying like, no, that's 855 00:41:42,040 --> 00:41:44,280 Speaker 1: what that's what people who make money off of AI 856 00:41:44,520 --> 00:41:46,080 Speaker 1: want you to be thinking about and want you to 857 00:41:46,120 --> 00:41:47,920 Speaker 1: be repeating and want you to be like making a 858 00:41:47,960 --> 00:41:51,239 Speaker 1: thing like making thatch happen when it like what are 859 00:41:51,280 --> 00:41:53,960 Speaker 1: your thoughts when it comes to generative AI and where 860 00:41:54,160 --> 00:41:57,040 Speaker 1: how it is going to actually impact the lives of 861 00:41:57,080 --> 00:42:01,560 Speaker 1: someone like the you know mother of Ree who you 862 00:42:01,600 --> 00:42:05,120 Speaker 1: know makes add a middle income What do you think 863 00:42:05,320 --> 00:42:06,840 Speaker 1: how is it going to impact our lives? 864 00:42:07,760 --> 00:42:13,440 Speaker 2: Yeah, so I would say I'm definitely skeptical of yeah, 865 00:42:13,840 --> 00:42:16,360 Speaker 2: of like a lot of the narratives that we're hearing, right, 866 00:42:17,280 --> 00:42:20,960 Speaker 2: because yeah, and again like that's just informed by seeing 867 00:42:21,000 --> 00:42:24,480 Speaker 2: how things have worked out in the past, right, by 868 00:42:24,520 --> 00:42:28,600 Speaker 2: seeing that this is an industry that really depends on 869 00:42:29,280 --> 00:42:34,320 Speaker 2: constantly kicking up new hype cycles. In order to keep 870 00:42:34,360 --> 00:42:37,719 Speaker 2: investment flowing, in order to keep people making money, in 871 00:42:37,800 --> 00:42:40,200 Speaker 2: order to keep interest on kind of their industry and 872 00:42:40,239 --> 00:42:43,959 Speaker 2: their products. And what you very clearly saw was that, 873 00:42:44,440 --> 00:42:47,840 Speaker 2: you know, after the crypto collapse and after you know, 874 00:42:47,960 --> 00:42:51,000 Speaker 2: the kind of ridiculing of the metaverse, and after the 875 00:42:51,080 --> 00:42:54,360 Speaker 2: raising of interest rates in particular, the tech industry really 876 00:42:54,400 --> 00:42:57,879 Speaker 2: needed something, right. It really needed you know, a next 877 00:42:57,880 --> 00:43:01,719 Speaker 2: big thing to kind of show to everybody to make 878 00:43:01,719 --> 00:43:03,680 Speaker 2: sure we were all talking about, to make sure it 879 00:43:03,760 --> 00:43:06,719 Speaker 2: stayed relevant, and again to keep money flowing, right, to 880 00:43:06,800 --> 00:43:10,479 Speaker 2: keep money moving through the system. And so generative AI 881 00:43:10,640 --> 00:43:15,680 Speaker 2: has emerged as that thing. And so I look back 882 00:43:15,719 --> 00:43:18,520 Speaker 2: at the mid twenty tens, as we were talking about, 883 00:43:18,560 --> 00:43:21,760 Speaker 2: when there were all of these narratives around how robots 884 00:43:21,760 --> 00:43:23,839 Speaker 2: and AI were going to take all of our jobs, right, 885 00:43:23,920 --> 00:43:26,200 Speaker 2: and millions of people were going to be out of work, 886 00:43:26,280 --> 00:43:28,480 Speaker 2: Like there were studies saying like forty fifty percent of 887 00:43:28,480 --> 00:43:30,720 Speaker 2: people were going to lose their jobs in the coming years, 888 00:43:30,719 --> 00:43:32,480 Speaker 2: all this kind of stuff. There were going to be 889 00:43:32,480 --> 00:43:35,279 Speaker 2: no more truckers because self driving cars were going to 890 00:43:35,280 --> 00:43:36,880 Speaker 2: replace them all. There were going to be no more 891 00:43:36,920 --> 00:43:40,000 Speaker 2: taxi drivers or uber drivers because we're self driving cars 892 00:43:40,000 --> 00:43:42,520 Speaker 2: were going to be everywhere in the next few years, right, 893 00:43:42,840 --> 00:43:45,840 Speaker 2: still waiting for those self driving cars, you know, I 894 00:43:45,880 --> 00:43:47,480 Speaker 2: know there are a few on the streets in San 895 00:43:47,520 --> 00:43:50,080 Speaker 2: Francisco and stuff, but like they're really not a mass 896 00:43:50,120 --> 00:43:53,239 Speaker 2: transportation system. And what we saw durund the pandemic was 897 00:43:53,280 --> 00:43:56,640 Speaker 2: actually we needed some more truck drivers because the whole 898 00:43:56,760 --> 00:43:59,640 Speaker 2: kind of supply chain was a mess. And part of 899 00:43:59,680 --> 00:44:03,799 Speaker 2: the problem there is because truck drivers have had their 900 00:44:03,840 --> 00:44:06,520 Speaker 2: working conditions and their wages so pushed down over recent 901 00:44:06,560 --> 00:44:09,640 Speaker 2: decades that people don't want to join the profession. And 902 00:44:09,680 --> 00:44:12,160 Speaker 2: so it's not because like robots are getting rid of them. 903 00:44:12,200 --> 00:44:14,880 Speaker 2: It's because work the working conditions suck, and we actually 904 00:44:14,960 --> 00:44:18,400 Speaker 2: need more of them. But anyway, that's kind of you know, 905 00:44:18,480 --> 00:44:21,480 Speaker 2: getting away from the point. But so I saw all 906 00:44:21,520 --> 00:44:23,480 Speaker 2: of that, and I saw like all of the narratives 907 00:44:23,520 --> 00:44:25,800 Speaker 2: around that moment and how there was a lot of 908 00:44:25,880 --> 00:44:28,319 Speaker 2: excitement and a lot of belief that like robots were 909 00:44:28,360 --> 00:44:30,960 Speaker 2: going to replace baristas and they were going to replace 910 00:44:31,000 --> 00:44:33,000 Speaker 2: elder care workers and all this was just a few 911 00:44:33,080 --> 00:44:36,080 Speaker 2: years away and never happened. Right, What we actually had 912 00:44:36,400 --> 00:44:39,680 Speaker 2: was technology being deployed in you know, the ways that 913 00:44:39,719 --> 00:44:42,839 Speaker 2: we've been talking about, where it ensured that workers were 914 00:44:42,840 --> 00:44:47,000 Speaker 2: reclassified from employee to contractor, where it ensured that their 915 00:44:47,040 --> 00:44:49,680 Speaker 2: pay was was lessened, where it ensured that they were 916 00:44:49,719 --> 00:44:53,640 Speaker 2: more precarious, where ensured that there was algorithmic management and 917 00:44:53,680 --> 00:44:56,680 Speaker 2: more surveillance of them. These were the actual kind of 918 00:44:56,760 --> 00:45:00,120 Speaker 2: legacies of that period, not destroying jobs and all all 919 00:45:00,120 --> 00:45:02,040 Speaker 2: that kind of stuff, and not making things a whole 920 00:45:02,080 --> 00:45:04,520 Speaker 2: lot more productive. We didn't actually see a whole lot 921 00:45:04,600 --> 00:45:08,920 Speaker 2: of investment in automation through that decade. The scholar economic 922 00:45:09,000 --> 00:45:11,200 Speaker 2: historian Aaron Benanov kind of found that when he went 923 00:45:11,239 --> 00:45:14,600 Speaker 2: and actually looked through the data for that period, what 924 00:45:14,640 --> 00:45:16,839 Speaker 2: we actually saw was, you know, just all of these 925 00:45:16,920 --> 00:45:18,960 Speaker 2: kind of surveillance tech and all this kind of stuff 926 00:45:19,040 --> 00:45:21,480 Speaker 2: used against workers. And so when I see what's going 927 00:45:21,480 --> 00:45:23,520 Speaker 2: on right now, I see the hype cycle I was 928 00:45:23,560 --> 00:45:26,799 Speaker 2: talking about. I see kind of the return of some 929 00:45:26,880 --> 00:45:29,480 Speaker 2: of these narratives from the mid twenty tens. You know, 930 00:45:29,600 --> 00:45:32,040 Speaker 2: open AI released the papers say talking about all the 931 00:45:32,120 --> 00:45:34,399 Speaker 2: jobs that were that were at risk because of CHAT, 932 00:45:34,400 --> 00:45:37,960 Speaker 2: GPT and all this kind of stuff. But that's not 933 00:45:37,960 --> 00:45:40,319 Speaker 2: to say that there aren't real threats that are being 934 00:45:40,360 --> 00:45:45,360 Speaker 2: posed by this technology, where again, it can further disempower labor, 935 00:45:45,600 --> 00:45:47,839 Speaker 2: it can further ensure that they're more precarious, it can 936 00:45:47,880 --> 00:45:50,800 Speaker 2: further push down wages. We're seeing, like you know, the 937 00:45:51,160 --> 00:45:53,200 Speaker 2: front end of that. The most obvious piece of that 938 00:45:53,400 --> 00:45:56,120 Speaker 2: is like the writers and the screen actors who are 939 00:45:56,280 --> 00:45:59,920 Speaker 2: undergoing contract negotiations right now. The writers are even on 940 00:46:00,120 --> 00:46:02,359 Speaker 2: strike and one of the things that they're concerned about 941 00:46:02,480 --> 00:46:05,040 Speaker 2: is how AI can be used in their industries to 942 00:46:05,160 --> 00:46:08,279 Speaker 2: kind of reshape their performances, to change the words to 943 00:46:08,840 --> 00:46:12,840 Speaker 2: kind of generate you know, scripts or generate writing that 944 00:46:12,880 --> 00:46:15,239 Speaker 2: they would have to rewrite, and it would mean that 945 00:46:15,320 --> 00:46:17,200 Speaker 2: there would be less work to do for them, and 946 00:46:17,239 --> 00:46:19,640 Speaker 2: it would also mean that the quality would decline. Like 947 00:46:19,680 --> 00:46:21,759 Speaker 2: I think that those are more of the risks of 948 00:46:21,840 --> 00:46:25,719 Speaker 2: generative AI if we're looking at the potential impacts, and 949 00:46:25,760 --> 00:46:28,959 Speaker 2: I would say that right now, these technologies are also 950 00:46:29,000 --> 00:46:31,040 Speaker 2: being sold to us in such a way where like 951 00:46:31,360 --> 00:46:33,839 Speaker 2: they're going to become ubiquitous in our lives. We're going 952 00:46:33,880 --> 00:46:36,560 Speaker 2: to be using generative AI and chatbots all the time. 953 00:46:36,640 --> 00:46:39,840 Speaker 2: They're going to be like rolled out into everything. This 954 00:46:40,040 --> 00:46:42,040 Speaker 2: is just the new way of the world. I think 955 00:46:42,040 --> 00:46:43,799 Speaker 2: a lot of people are being too quick to like 956 00:46:44,680 --> 00:46:48,839 Speaker 2: accept that as inevitable when I don't think it is. 957 00:46:49,320 --> 00:46:54,080 Speaker 2: Like think about the voice assistance that were rolled out 958 00:46:54,160 --> 00:46:56,359 Speaker 2: in the past, like six or eight years. How many 959 00:46:56,400 --> 00:47:00,200 Speaker 2: people actually use those regularly anymore? I certainly don't, And 960 00:47:00,280 --> 00:47:02,480 Speaker 2: I read a story recently that suggests actually a lot 961 00:47:02,520 --> 00:47:06,160 Speaker 2: of people don't. This is not just anecdotal evidence. So 962 00:47:06,600 --> 00:47:08,040 Speaker 2: you know, I think that there's a lot of things 963 00:47:08,040 --> 00:47:09,920 Speaker 2: that the tech industry rolls out that we think are 964 00:47:10,000 --> 00:47:12,319 Speaker 2: like the next big paradigm, that we think are going 965 00:47:12,360 --> 00:47:15,840 Speaker 2: to revolutionize everything, and it doesn't actually play out as planned. 966 00:47:16,000 --> 00:47:17,799 Speaker 2: And I think the final point I would make on 967 00:47:17,880 --> 00:47:20,759 Speaker 2: this is that when we look at generative AI, what 968 00:47:20,800 --> 00:47:24,240 Speaker 2: we actually see is that it increases, like the cost structure, 969 00:47:24,280 --> 00:47:26,520 Speaker 2: it increases the cost of doing these things. So if 970 00:47:26,520 --> 00:47:29,400 Speaker 2: you're switching over a search engine from the way it 971 00:47:29,440 --> 00:47:32,160 Speaker 2: works right now to like generative AI and chatbots, the 972 00:47:32,280 --> 00:47:35,360 Speaker 2: cost per search goes up, you know, quite significantly, actually, 973 00:47:35,440 --> 00:47:38,400 Speaker 2: because it uses more computer power, because it's trained on 974 00:47:38,440 --> 00:47:41,680 Speaker 2: these massive models, because it relies on all this centralized 975 00:47:41,760 --> 00:47:45,239 Speaker 2: kind of computation right in these massive data centers that 976 00:47:45,280 --> 00:47:47,759 Speaker 2: these companies own and I think that that's another piece 977 00:47:47,800 --> 00:47:50,440 Speaker 2: of this that maybe there's not enough talk about, because 978 00:47:50,480 --> 00:47:52,439 Speaker 2: certainly you have the sam Altmans of the world going 979 00:47:52,440 --> 00:47:55,080 Speaker 2: out and saying this is going to empower every individual, 980 00:47:55,120 --> 00:47:57,920 Speaker 2: and we're going to have chatbots that are like personalized 981 00:47:57,960 --> 00:48:00,839 Speaker 2: for you and all this kind of stuff. Actually, what 982 00:48:00,880 --> 00:48:03,399 Speaker 2: this technology does is, you know, we've been talking about 983 00:48:03,440 --> 00:48:06,160 Speaker 2: like anti trust and breaking up companies and the issues 984 00:48:06,160 --> 00:48:08,839 Speaker 2: with like monopolization in the tech industry for a few 985 00:48:08,920 --> 00:48:11,360 Speaker 2: years now. What this actually does is like kind of 986 00:48:11,360 --> 00:48:14,479 Speaker 2: cement that power, because you can't really have generative AI 987 00:48:14,960 --> 00:48:18,320 Speaker 2: without scraping all of this data from the web, without 988 00:48:18,360 --> 00:48:21,480 Speaker 2: having this centralized kind of computing infrastructure that only a 989 00:48:21,520 --> 00:48:26,000 Speaker 2: small number of companies globally can actually control. And so 990 00:48:26,080 --> 00:48:28,239 Speaker 2: if we do move in this direction, we're kind of 991 00:48:28,600 --> 00:48:31,320 Speaker 2: building in the power of these large companies in a 992 00:48:31,360 --> 00:48:33,359 Speaker 2: way that we were trying to challenge a few years ago. 993 00:48:33,680 --> 00:48:36,040 Speaker 2: And that suggests to me that they're also kind of 994 00:48:36,080 --> 00:48:38,720 Speaker 2: responding to that fact. You know, there was a story 995 00:48:38,800 --> 00:48:41,440 Speaker 2: just a few months ago about how the tech companies 996 00:48:41,480 --> 00:48:45,799 Speaker 2: had very quite successfully kind of challenged and kind of 997 00:48:45,880 --> 00:48:48,239 Speaker 2: blunted the push for anti trust, and now that the 998 00:48:48,280 --> 00:48:51,200 Speaker 2: Republicans have taken over one of the houses in the 999 00:48:51,200 --> 00:48:54,520 Speaker 2: States that sorry I can't remember which, the Senator of 1000 00:48:54,560 --> 00:48:56,840 Speaker 2: the House or whatever. Anyway, they took over one of 1001 00:48:56,840 --> 00:48:58,520 Speaker 2: those and so now like it's pretty much going to 1002 00:48:58,520 --> 00:49:01,719 Speaker 2: be impossible to get any like anti trust legislation through 1003 00:49:02,239 --> 00:49:05,279 Speaker 2: for the next number of years, I would say. So 1004 00:49:05,320 --> 00:49:08,000 Speaker 2: the tech industry is very concerned about these things as well, 1005 00:49:08,120 --> 00:49:11,440 Speaker 2: very kind of alert to this. So, yeah, those are 1006 00:49:11,480 --> 00:49:13,120 Speaker 2: all my thoughts on Jenner VAI. 1007 00:49:13,840 --> 00:49:14,760 Speaker 3: That's really helpful. 1008 00:49:15,719 --> 00:49:18,640 Speaker 1: And I think it does, like you know, I'm I'm 1009 00:49:18,800 --> 00:49:21,759 Speaker 1: on TikTok a lot, and I do think that it's 1010 00:49:21,880 --> 00:49:24,440 Speaker 1: it really is reflective of like it's a hu it's 1011 00:49:24,440 --> 00:49:25,760 Speaker 1: a it's a little bit of a hustle. 1012 00:49:26,120 --> 00:49:28,960 Speaker 3: And the people who are selling you the hustle have money. 1013 00:49:29,000 --> 00:49:31,040 Speaker 1: There's money to be made, right, And so I see 1014 00:49:31,040 --> 00:49:33,240 Speaker 1: people who are like, oh AI is going to change everything. 1015 00:49:33,440 --> 00:49:36,040 Speaker 1: You're going to need to know how to integrate AI 1016 00:49:36,080 --> 00:49:38,480 Speaker 1: into your work, So better sign up for my course, 1017 00:49:38,560 --> 00:49:41,640 Speaker 1: and I'll tell you like, it's like it's it's it's yeah. 1018 00:49:41,560 --> 00:49:43,520 Speaker 3: Just it just feels like a little bit of a 1019 00:49:43,880 --> 00:49:44,480 Speaker 3: little bit. 1020 00:49:44,320 --> 00:49:47,359 Speaker 2: Of a hustle, and that's the way it's always been right, 1021 00:49:47,480 --> 00:49:49,879 Speaker 2: Like every single time there's a new shift like that. 1022 00:49:49,960 --> 00:49:54,880 Speaker 2: Like I remember when it was popular to like like 1023 00:49:54,920 --> 00:49:57,280 Speaker 2: when Kindle and like self publishing and all that stuff 1024 00:49:57,360 --> 00:49:59,760 Speaker 2: was taking off on Amazon. There were a ton of courses. 1025 00:49:59,760 --> 00:50:01,520 Speaker 2: There were a ton of people trying to sell you, like, 1026 00:50:01,800 --> 00:50:04,160 Speaker 2: you know, the way that you were going to be 1027 00:50:04,239 --> 00:50:06,759 Speaker 2: a successful self published author and all this stuff. And 1028 00:50:06,840 --> 00:50:10,280 Speaker 2: like you know, there's there's all these courses around SEO 1029 00:50:10,440 --> 00:50:13,400 Speaker 2: and search engine option optimization to ensure that your website 1030 00:50:13,520 --> 00:50:14,840 Speaker 2: is going to like get to the top of the 1031 00:50:14,840 --> 00:50:17,439 Speaker 2: search results, and like this is something that happens every 1032 00:50:17,480 --> 00:50:21,200 Speaker 2: single time, and I think it's very indicative of this 1033 00:50:21,360 --> 00:50:25,200 Speaker 2: happening again that like some of the like you know, 1034 00:50:25,280 --> 00:50:28,760 Speaker 2: beyond the kind of pr lines from the sam Altmans 1035 00:50:28,800 --> 00:50:31,239 Speaker 2: and like the real AI boosters that you see the 1036 00:50:31,280 --> 00:50:33,959 Speaker 2: people saying that like you know, it's a massive threat 1037 00:50:34,000 --> 00:50:37,640 Speaker 2: to humanity, using these kind of long term mist arguments 1038 00:50:38,200 --> 00:50:40,520 Speaker 2: against it, saying that you know, they're on the cusp 1039 00:50:40,520 --> 00:50:42,839 Speaker 2: of digital minds. All this stuff is complete bullshit by 1040 00:50:42,840 --> 00:50:46,120 Speaker 2: the way, you know. But the other like big narrative 1041 00:50:46,160 --> 00:50:49,160 Speaker 2: that you see on Twitter and TikTok and like all 1042 00:50:49,160 --> 00:50:51,879 Speaker 2: these other social media platforms is like the hustle bros 1043 00:50:51,920 --> 00:50:54,000 Speaker 2: and the hustle people like going really hard, like the 1044 00:50:54,040 --> 00:50:56,799 Speaker 2: LinkedIn the LinkedIn folks as well, like this is all 1045 00:50:56,800 --> 00:50:58,520 Speaker 2: the stuff you need to know about AI, this is 1046 00:50:58,520 --> 00:51:01,040 Speaker 2: how it's going to improve your workflow, help you writing emails, 1047 00:51:01,080 --> 00:51:03,279 Speaker 2: like all this blah blah blah. Yeah, it's it's a 1048 00:51:03,320 --> 00:51:04,160 Speaker 2: load of bull shit. 1049 00:51:04,840 --> 00:51:08,440 Speaker 1: Have taken over Twitter, Like I almost it's it's just 1050 00:51:08,520 --> 00:51:13,520 Speaker 1: so fucking boring and like I almost miss like I 1051 00:51:13,560 --> 00:51:15,800 Speaker 1: don't know, it's it's just it's just such empty, boring 1052 00:51:15,960 --> 00:51:18,359 Speaker 1: garbage that I can't you can't even like dunk on it. 1053 00:51:18,360 --> 00:51:20,080 Speaker 3: You can't even like all it is. 1054 00:51:20,120 --> 00:51:22,279 Speaker 1: It just like clogs up your feed and where your 1055 00:51:22,320 --> 00:51:24,759 Speaker 1: feed is already like worse than it was five years 1056 00:51:24,760 --> 00:51:26,480 Speaker 1: ago anyway, you know, it's just it's it's so. 1057 00:51:26,560 --> 00:51:30,880 Speaker 2: Boring totally that the whole website is like going downhill 1058 00:51:31,000 --> 00:51:34,319 Speaker 2: and it sucks because like you know that there was 1059 00:51:34,600 --> 00:51:37,120 Speaker 2: such a community there, like it was it was fun 1060 00:51:37,120 --> 00:51:40,200 Speaker 2: to be on Twitter, but like I certainly use it 1061 00:51:40,280 --> 00:51:42,640 Speaker 2: less than I used to. I'm not like off it 1062 00:51:42,760 --> 00:51:46,360 Speaker 2: all together, but especially when you see it like slowly 1063 00:51:46,640 --> 00:51:49,960 Speaker 2: moving in this kind of direction, that Elon Musk is 1064 00:51:50,000 --> 00:51:54,120 Speaker 2: taking it where like I think he's explicitly making decisions 1065 00:51:54,120 --> 00:51:56,160 Speaker 2: to kind of reshape it as more of like a 1066 00:51:56,239 --> 00:51:59,560 Speaker 2: right wing platform, right like parlor failed gab failed thrue 1067 00:51:59,560 --> 00:52:02,399 Speaker 2: socials a joke, Like you know, they they still want 1068 00:52:02,440 --> 00:52:05,200 Speaker 2: to control, like, you know, the the kind of way 1069 00:52:05,239 --> 00:52:07,440 Speaker 2: that we communicate with one another. They still want to 1070 00:52:07,480 --> 00:52:10,520 Speaker 2: control the media. That's long been like part of the rights, 1071 00:52:11,200 --> 00:52:13,920 Speaker 2: you know kind of desire what they want to do. 1072 00:52:14,000 --> 00:52:16,200 Speaker 2: You know, they have Fox News, but they also kind 1073 00:52:16,239 --> 00:52:19,839 Speaker 2: of strongly influence like the liberal media quote unquote as 1074 00:52:19,840 --> 00:52:22,840 Speaker 2: well to kind of pull the narratives in that direction. 1075 00:52:23,760 --> 00:52:25,680 Speaker 2: So obviously they want to do that on social media 1076 00:52:25,719 --> 00:52:28,280 Speaker 2: as well, and have been effectively doing so for many years. 1077 00:52:28,480 --> 00:52:30,600 Speaker 2: We can go back to the reporting on Facebook and 1078 00:52:30,680 --> 00:52:33,680 Speaker 2: like how Zuckerberg was like worried about kind of pissing 1079 00:52:33,680 --> 00:52:35,640 Speaker 2: off the conservatives or making it look like he was 1080 00:52:35,680 --> 00:52:37,920 Speaker 2: taking actions that would go against him even as their 1081 00:52:37,960 --> 00:52:40,680 Speaker 2: pages were like getting the most kind of views and 1082 00:52:40,719 --> 00:52:42,759 Speaker 2: growth and all that stuff. And so now you see 1083 00:52:42,760 --> 00:52:45,560 Speaker 2: like Tucker Carlson starting a Twitter show, like how does 1084 00:52:45,600 --> 00:52:48,640 Speaker 2: that make any sense? We see DeSantis, Like as we're talking, 1085 00:52:48,680 --> 00:52:52,560 Speaker 2: DeSantis is going to like announce his presidential bid this evening, 1086 00:52:53,680 --> 00:52:56,759 Speaker 2: you know, and obviously all these kind of right wing 1087 00:52:56,800 --> 00:53:00,279 Speaker 2: folks just get so much additional traction, or they don't 1088 00:53:00,280 --> 00:53:02,160 Speaker 2: seem to think so, I guess, but you know, they 1089 00:53:02,200 --> 00:53:04,920 Speaker 2: get promoted a lot on Twitter now because of how 1090 00:53:05,040 --> 00:53:07,840 Speaker 2: Musk has changed things around and let all the Nazis 1091 00:53:07,880 --> 00:53:09,880 Speaker 2: back on and all that stuff, like, yeah, it's just 1092 00:53:09,920 --> 00:53:11,680 Speaker 2: a it's a real health site. Like we used to 1093 00:53:11,760 --> 00:53:13,200 Speaker 2: joke it was a health site that like now is 1094 00:53:13,239 --> 00:53:14,040 Speaker 2: really elside. 1095 00:53:14,520 --> 00:53:17,359 Speaker 1: Yeah, I mean, something I've noticed is that people are 1096 00:53:17,400 --> 00:53:19,799 Speaker 1: starting to come around on the fact that Musk has 1097 00:53:19,840 --> 00:53:24,560 Speaker 1: been parroting pretty extremist, far right talking points and it's 1098 00:53:24,560 --> 00:53:25,200 Speaker 1: not a new thing. 1099 00:53:25,239 --> 00:53:26,760 Speaker 3: It's been doing it for kind of a while. 1100 00:53:28,200 --> 00:53:31,520 Speaker 1: Why do you think that is something like even people 1101 00:53:31,520 --> 00:53:36,000 Speaker 1: that I respect in tech press didn't really engage with that, honestly, 1102 00:53:36,080 --> 00:53:38,000 Speaker 1: I feel or like weren't able to get it. There 1103 00:53:38,040 --> 00:53:40,960 Speaker 1: was always this vibe of like, maybe it's just like 1104 00:53:41,000 --> 00:53:44,000 Speaker 1: an edgy thing that he's doing, or it's a like 1105 00:53:44,040 --> 00:53:46,160 Speaker 1: I once read someone saying like, oh, he's trying to 1106 00:53:46,680 --> 00:53:50,960 Speaker 1: save the environment by making buying electric cars, that he 1107 00:53:51,080 --> 00:53:54,640 Speaker 1: makes look more appealing to people on the right to 1108 00:53:54,719 --> 00:53:59,160 Speaker 1: help solve climate injustice, Like what a take Why do 1109 00:53:59,200 --> 00:54:00,759 Speaker 1: you think it was so hard for people to just 1110 00:54:00,840 --> 00:54:03,759 Speaker 1: like take him at his word and like listen to 1111 00:54:03,760 --> 00:54:05,680 Speaker 1: the things that he says and believe them when he 1112 00:54:05,719 --> 00:54:06,960 Speaker 1: says them. 1113 00:54:07,320 --> 00:54:09,960 Speaker 2: Yeah, Like what you're describing is like how far of 1114 00:54:10,000 --> 00:54:13,880 Speaker 2: a stretch some people go to to like justify exactly 1115 00:54:13,880 --> 00:54:15,120 Speaker 2: what he's doing and what he's saying. 1116 00:54:15,239 --> 00:54:15,439 Speaker 3: Right. 1117 00:54:16,520 --> 00:54:20,480 Speaker 2: I think that the key thing here is that for 1118 00:54:20,520 --> 00:54:24,359 Speaker 2: such a long time, Elon Musk was like, you know, 1119 00:54:24,800 --> 00:54:27,680 Speaker 2: he was kind of the tech god. He was the 1120 00:54:27,719 --> 00:54:31,879 Speaker 2: guy who was kind of he was the figure who 1121 00:54:31,920 --> 00:54:34,400 Speaker 2: was kind of held up from the tech industry, especially 1122 00:54:34,440 --> 00:54:37,120 Speaker 2: after the death of jobs, that was like doing all 1123 00:54:37,200 --> 00:54:40,400 Speaker 2: of this wonderful stuff for us. He was investing in 1124 00:54:40,440 --> 00:54:42,360 Speaker 2: the rockets and was going to take us the Mars, 1125 00:54:42,400 --> 00:54:44,279 Speaker 2: and he was building the electric car and was going 1126 00:54:44,320 --> 00:54:46,640 Speaker 2: to save us from climate change and like all this 1127 00:54:46,719 --> 00:54:49,399 Speaker 2: kind of stuff, right, And the media did hold him 1128 00:54:49,480 --> 00:54:52,440 Speaker 2: up as this figure who could really do no wrong 1129 00:54:52,760 --> 00:54:56,120 Speaker 2: and who we really had to like worship as not 1130 00:54:56,320 --> 00:54:59,440 Speaker 2: just like this incredible tech entrepreneur, but as the builder 1131 00:54:59,480 --> 00:55:02,480 Speaker 2: of the future, right, Like he had a vision that 1132 00:55:02,560 --> 00:55:04,840 Speaker 2: nobody else had that you couldn't get from the political 1133 00:55:04,880 --> 00:55:08,400 Speaker 2: system or anything like that. Like he was the future 1134 00:55:08,640 --> 00:55:10,920 Speaker 2: and he was someone that we had to trust. And 1135 00:55:10,960 --> 00:55:13,640 Speaker 2: I think that that has like, even though that has 1136 00:55:13,680 --> 00:55:17,640 Speaker 2: started to shift in recent years, I think that first 1137 00:55:17,680 --> 00:55:19,480 Speaker 2: of all, it took a while for the media to 1138 00:55:19,560 --> 00:55:21,879 Speaker 2: really wake up. I think like even as you did 1139 00:55:21,880 --> 00:55:25,040 Speaker 2: have them publishing more kind of critical stories on Elon Musk, 1140 00:55:25,239 --> 00:55:27,520 Speaker 2: they would still publish the puff pieces as well. Right, 1141 00:55:27,880 --> 00:55:30,400 Speaker 2: you know, even what was it last year, he was 1142 00:55:30,440 --> 00:55:33,160 Speaker 2: still named Times Person of the Year or whatever, Like, 1143 00:55:33,360 --> 00:55:37,200 Speaker 2: even as he was increasingly being engulfed in controversy, there 1144 00:55:37,200 --> 00:55:39,520 Speaker 2: were a ton of stories about the racism and sexism 1145 00:55:39,520 --> 00:55:42,120 Speaker 2: in his factories. You know, there was the story I 1146 00:55:42,160 --> 00:55:45,719 Speaker 2: believe about him like sexually assaulting the flight attendant. I 1147 00:55:45,800 --> 00:55:48,239 Speaker 2: believe that was just before that happened. Like there was 1148 00:55:48,280 --> 00:55:50,040 Speaker 2: all this stuff that was kind of coming out about 1149 00:55:50,080 --> 00:55:52,799 Speaker 2: Elon Musk, and he still got this this title, right, 1150 00:55:53,560 --> 00:55:57,040 Speaker 2: And so I think that like unfortunately, like I think 1151 00:55:57,040 --> 00:55:59,279 Speaker 2: that there's a lot of people who really believe in 1152 00:55:59,400 --> 00:56:01,920 Speaker 2: the cult of and who are not just kind of 1153 00:56:02,000 --> 00:56:05,719 Speaker 2: like personally invested, but also let's be real, they've bought 1154 00:56:05,719 --> 00:56:08,920 Speaker 2: a Tesla or they bought Tesla stock and they're like 1155 00:56:09,000 --> 00:56:11,799 Speaker 2: financially invested in Elon Musk. Because one of the things 1156 00:56:11,840 --> 00:56:14,680 Speaker 2: that is like somewhat unique about Tesla is there's a 1157 00:56:14,680 --> 00:56:17,560 Speaker 2: lot of quote unquote retail investors, people that are not 1158 00:56:17,680 --> 00:56:21,279 Speaker 2: institutional investors who owned Tesla stock, which is a bit 1159 00:56:21,400 --> 00:56:24,480 Speaker 2: less common. Right, It's because Elon Musk has all these 1160 00:56:24,520 --> 00:56:26,640 Speaker 2: fans and they've bought in and they kind of believe 1161 00:56:26,840 --> 00:56:28,960 Speaker 2: what he's doing and where he's going, and they want 1162 00:56:29,000 --> 00:56:31,759 Speaker 2: to follow him. Of course, some people have woken up. 1163 00:56:31,920 --> 00:56:33,839 Speaker 2: But then the other piece of this is there were 1164 00:56:33,960 --> 00:56:36,960 Speaker 2: a lot of you know, kind of people who reported 1165 00:56:37,000 --> 00:56:39,640 Speaker 2: on Elon Musk who got to know Elon Musk because 1166 00:56:39,640 --> 00:56:42,120 Speaker 2: they're access journalists and I won't name names, but maybe 1167 00:56:42,120 --> 00:56:44,520 Speaker 2: you can think about who I'm talking about for a 1168 00:56:44,600 --> 00:56:48,839 Speaker 2: number of years who really helped him to kind of 1169 00:56:49,120 --> 00:56:53,480 Speaker 2: build up the reputation that he had and wanted to 1170 00:56:53,560 --> 00:56:55,840 Speaker 2: ensure that they maintain that connection to him. And I 1171 00:56:55,840 --> 00:56:57,600 Speaker 2: think also kind of some in the way that they 1172 00:56:57,719 --> 00:57:02,319 Speaker 2: presented Elon Musk to the public and didn't want to 1173 00:57:02,400 --> 00:57:07,040 Speaker 2: recognize that not only was it not only is he 1174 00:57:07,160 --> 00:57:10,600 Speaker 2: kind of a bad person, who is you know, ensuring 1175 00:57:10,640 --> 00:57:13,960 Speaker 2: that transphobic talking points, who is ensuring that kind of 1176 00:57:14,120 --> 00:57:16,880 Speaker 2: white nationalist talking points, Like all of this kind of 1177 00:57:17,040 --> 00:57:20,479 Speaker 2: really terrible political stuff is being furthered and that he's 1178 00:57:20,560 --> 00:57:23,320 Speaker 2: like actively sharing it and promoting it and believing it. 1179 00:57:24,240 --> 00:57:28,520 Speaker 2: But also that there how they presented him for so 1180 00:57:28,680 --> 00:57:32,880 Speaker 2: long was also wrong and was not an accurate reflection 1181 00:57:33,160 --> 00:57:35,160 Speaker 2: of who he was and what he was doing and 1182 00:57:35,200 --> 00:57:38,240 Speaker 2: his impact on the world because they created this narrative 1183 00:57:38,240 --> 00:57:41,400 Speaker 2: around him. They created this character of Elon Musk, and 1184 00:57:41,760 --> 00:57:45,880 Speaker 2: he was you know, this was a valuable property that 1185 00:57:45,920 --> 00:57:48,040 Speaker 2: the media had created and kind of sold to the world. 1186 00:57:48,120 --> 00:57:50,120 Speaker 2: It was great for him, that allowed him to get investment. 1187 00:57:50,320 --> 00:57:52,680 Speaker 2: It was also great for them because any time they 1188 00:57:52,680 --> 00:57:55,840 Speaker 2: publish anything on Elon Musk, it gets a ton of views. Right, 1189 00:57:57,160 --> 00:57:59,280 Speaker 2: people love him, people hate him, whatever people want to 1190 00:57:59,320 --> 00:58:01,960 Speaker 2: read about him, And so that was great for the 1191 00:58:02,000 --> 00:58:03,760 Speaker 2: media as well. And that's part of the reason that 1192 00:58:03,800 --> 00:58:05,960 Speaker 2: they that they kind of created this narrative around him, 1193 00:58:06,000 --> 00:58:08,240 Speaker 2: that they created the character of Vila Musk. But if 1194 00:58:08,280 --> 00:58:10,480 Speaker 2: you go back to it the very early days when 1195 00:58:10,520 --> 00:58:14,080 Speaker 2: he is starting zip too, when he's starting x dot com, 1196 00:58:14,280 --> 00:58:16,360 Speaker 2: you can see the stories about how he is a 1197 00:58:16,480 --> 00:58:19,600 Speaker 2: terrible manager who is an asshole to the people who 1198 00:58:19,640 --> 00:58:22,160 Speaker 2: work for him. Right, this is not unknown, This is 1199 00:58:22,280 --> 00:58:24,960 Speaker 2: very clear at that time, and that continues as he 1200 00:58:25,000 --> 00:58:27,560 Speaker 2: starts other businesses as well. And like we see the 1201 00:58:27,600 --> 00:58:30,880 Speaker 2: stories time and again through his history of like who 1202 00:58:30,920 --> 00:58:33,360 Speaker 2: he actually is. But I think that some of these 1203 00:58:33,400 --> 00:58:36,440 Speaker 2: people who worked in the media, who kind of were 1204 00:58:36,480 --> 00:58:39,640 Speaker 2: incentivized to promote him in this way, ensured that that 1205 00:58:39,800 --> 00:58:43,200 Speaker 2: aspect of his personality and who he was was always downplayed, 1206 00:58:43,560 --> 00:58:45,800 Speaker 2: was always kind of hidden from the public, was not 1207 00:58:45,920 --> 00:58:48,800 Speaker 2: part of the persona that was sold to us. And 1208 00:58:48,840 --> 00:58:51,480 Speaker 2: so now there's kind of a reckoning, not just with 1209 00:58:51,520 --> 00:58:53,640 Speaker 2: who he is, because some of these people will say, oh, 1210 00:58:53,640 --> 00:58:55,600 Speaker 2: he's just changed in the past like six months. No, 1211 00:58:55,720 --> 00:58:58,200 Speaker 2: he's always been this person and now he's just being 1212 00:58:58,200 --> 00:59:00,640 Speaker 2: more open about it. And so there's a not just 1213 00:59:00,720 --> 00:59:03,439 Speaker 2: with that, but also like with what we've been told 1214 00:59:03,440 --> 00:59:05,560 Speaker 2: about him for a long time, and some people really 1215 00:59:05,560 --> 00:59:07,400 Speaker 2: don't want to engage with that and don't want to 1216 00:59:08,120 --> 00:59:10,880 Speaker 2: believe that he was always who he is now and 1217 00:59:11,040 --> 00:59:12,920 Speaker 2: is just being more open about it, and want to 1218 00:59:12,920 --> 00:59:15,120 Speaker 2: pretend that this is kind of a break from what 1219 00:59:15,160 --> 00:59:18,400 Speaker 2: they knew before or again is some kind of like 1220 00:59:18,680 --> 00:59:20,960 Speaker 2: you know, three dimensional chess sort of a thing that's 1221 00:59:21,000 --> 00:59:24,200 Speaker 2: going on where he's actually trying to get conservatives on 1222 00:59:24,240 --> 00:59:26,960 Speaker 2: board with climate policy. Like it's just total bullshit, right, 1223 00:59:27,000 --> 00:59:29,040 Speaker 2: But yeah, so that's kind of how I think about that. 1224 00:59:29,560 --> 00:59:32,320 Speaker 1: So I always end all of my interviews with asking 1225 00:59:32,840 --> 00:59:35,720 Speaker 1: when it comes to the future, are you hopeful? Like 1226 00:59:35,760 --> 00:59:37,680 Speaker 1: what is there anything that brings you hope? 1227 00:59:38,000 --> 00:59:41,280 Speaker 2: I would say yes, And I think it's difficult to 1228 00:59:41,400 --> 00:59:44,400 Speaker 2: be hopeful sometimes, like seeing the state of the world, 1229 00:59:44,560 --> 00:59:48,040 Speaker 2: seeing the climate getting worse, seeing like the continued influence 1230 00:59:48,120 --> 00:59:50,400 Speaker 2: of the tech industry and like the worst people in 1231 00:59:50,400 --> 00:59:54,160 Speaker 2: that industry. But I feel like if I didn't have hope, 1232 00:59:54,240 --> 00:59:56,360 Speaker 2: like I would just be like totally depressed and stuff. 1233 00:59:56,400 --> 00:59:58,920 Speaker 2: So even despite the fact that things look bad, I 1234 00:59:58,920 --> 01:00:01,320 Speaker 2: feel like I have to be hopeful. And that's not 1235 01:00:01,360 --> 01:00:03,080 Speaker 2: to say that like there aren't things that do give 1236 01:00:03,120 --> 01:00:05,120 Speaker 2: me hope. I as I was saying, like I feel 1237 01:00:05,120 --> 01:00:08,080 Speaker 2: hopeful seeing kind of people push back against the tech 1238 01:00:08,080 --> 01:00:11,280 Speaker 2: industry and seeing like the broader realization that we have 1239 01:00:11,560 --> 01:00:14,800 Speaker 2: around these people in the industry, around like what they 1240 01:00:14,960 --> 01:00:18,000 Speaker 2: are doing, and the recognition that like you know, they're 1241 01:00:18,040 --> 01:00:21,160 Speaker 2: not who they have been sold to us to be. 1242 01:00:22,280 --> 01:00:25,400 Speaker 2: But then like on top of that, it's also quite 1243 01:00:25,440 --> 01:00:28,200 Speaker 2: inspiring to see, especially in the past number of years, 1244 01:00:29,280 --> 01:00:32,160 Speaker 2: a lot more organizing, not just in the tech industry, 1245 01:00:32,200 --> 01:00:35,720 Speaker 2: but like in the society more broadly, people kind of 1246 01:00:35,720 --> 01:00:38,920 Speaker 2: pushing back against you know, actions of the tech industry, 1247 01:00:39,000 --> 01:00:42,480 Speaker 2: people unionizing, like all these kinds of things I think 1248 01:00:42,520 --> 01:00:46,680 Speaker 2: are really hopeful because they suggest that, you know, maybe 1249 01:00:46,680 --> 01:00:49,640 Speaker 2: we're moving in a direction where people are getting really 1250 01:00:49,680 --> 01:00:52,000 Speaker 2: pissed off with the way that things are and are 1251 01:00:52,040 --> 01:00:55,040 Speaker 2: trying to you know, change those things, are trying to 1252 01:00:55,160 --> 01:00:58,200 Speaker 2: ensure that we don't keep moving in that direction. And 1253 01:00:58,280 --> 01:01:00,360 Speaker 2: of course, you know, I guess the flips of that 1254 01:01:00,440 --> 01:01:03,040 Speaker 2: is that we also see that organizing happening on the 1255 01:01:03,040 --> 01:01:05,840 Speaker 2: other side among the fascists and the white nationalists who 1256 01:01:05,880 --> 01:01:09,439 Speaker 2: are trying to make the world worse. But I think 1257 01:01:09,440 --> 01:01:12,840 Speaker 2: that it's almost like inevitable that in the stage of 1258 01:01:12,880 --> 01:01:14,840 Speaker 2: capitalism that we're in, we're just going to see this 1259 01:01:14,920 --> 01:01:17,680 Speaker 2: kind of polarization. And you know, the goal is to 1260 01:01:17,800 --> 01:01:20,400 Speaker 2: ensure that we have as much energy and power as 1261 01:01:20,800 --> 01:01:22,680 Speaker 2: we can build, like you know, on the left and 1262 01:01:23,120 --> 01:01:27,400 Speaker 2: among people who actually care about like regular people and 1263 01:01:27,480 --> 01:01:30,960 Speaker 2: not just like, you know, all this kind of fascist, 1264 01:01:31,720 --> 01:01:35,720 Speaker 2: racist garbage that we're increasingly seeing to kind of build 1265 01:01:35,800 --> 01:01:37,640 Speaker 2: a better world. So I feel like I feel like 1266 01:01:37,640 --> 01:01:39,360 Speaker 2: that's a bit mixed, but I would say on the whole, 1267 01:01:39,520 --> 01:01:42,920 Speaker 2: I am hopeful that you know, even though things are 1268 01:01:43,480 --> 01:01:46,160 Speaker 2: going bad in some areas, I think that there's a 1269 01:01:46,240 --> 01:01:49,160 Speaker 2: reason to believe that people are willing to fight for 1270 01:01:49,240 --> 01:01:52,600 Speaker 2: something better, and you know, hopefully that continues. 1271 01:01:52,960 --> 01:01:56,240 Speaker 1: Well, your work is a beacon of light in a 1272 01:01:56,320 --> 01:01:59,479 Speaker 1: in what sometimes feels like an ocean of garbage. Where 1273 01:01:59,560 --> 01:02:02,600 Speaker 1: can folk listen to your podcast and all the cool 1274 01:02:03,080 --> 01:02:03,880 Speaker 1: stuff that you're doing. 1275 01:02:04,880 --> 01:02:07,120 Speaker 2: Yeah, thanks so much for inviting me. It was really 1276 01:02:07,360 --> 01:02:11,600 Speaker 2: great to chat. I would say, you know, the podcast 1277 01:02:11,640 --> 01:02:13,120 Speaker 2: is tech won't save us. It's like on all the 1278 01:02:13,200 --> 01:02:16,080 Speaker 2: podcast platforms, wherever you listen, it should be there. I 1279 01:02:16,120 --> 01:02:19,600 Speaker 2: also have a newsletter called Disconnect, which is over on substack. 1280 01:02:19,760 --> 01:02:19,960 Speaker 4: You know. 1281 01:02:20,320 --> 01:02:23,200 Speaker 2: You know people have mixed opinions on that platform. I 1282 01:02:23,200 --> 01:02:25,200 Speaker 2: certainly do as well, but if you want to read it, 1283 01:02:25,200 --> 01:02:28,160 Speaker 2: it's over there. You know, you can follow me on 1284 01:02:28,160 --> 01:02:31,680 Speaker 2: Twitter or maceedon or blue Sky. You know, I post 1285 01:02:31,720 --> 01:02:35,120 Speaker 2: a bit on on those platforms. Still, yeah, I would say, 1286 01:02:35,120 --> 01:02:36,240 Speaker 2: those are the key things. 1287 01:02:36,720 --> 01:02:39,280 Speaker 1: This has been amazing. Is there anything that I did 1288 01:02:39,320 --> 01:02:41,120 Speaker 1: not ask that you want to make sure it gets included? 1289 01:02:42,200 --> 01:02:43,560 Speaker 2: I don't think so. This has been great. 1290 01:02:48,600 --> 01:02:50,600 Speaker 1: Got a story about an interesting thing in tech, or 1291 01:02:50,720 --> 01:02:52,560 Speaker 1: just want to say hi? You can read us at 1292 01:02:52,560 --> 01:02:55,320 Speaker 1: Hello at tangodi dot com. You can also find transcripts 1293 01:02:55,320 --> 01:02:57,720 Speaker 1: for today's episode at TENG Goody dot com. There Are 1294 01:02:57,720 --> 01:02:59,880 Speaker 1: No Girls on the Internet was created by me Bridge Pad. 1295 01:03:00,280 --> 01:03:03,720 Speaker 1: It's a production of iHeartRadio and Unbossed creative. Jonathan Strickland 1296 01:03:03,760 --> 01:03:06,480 Speaker 1: is our executive producer. Tari Harrison is our producer and 1297 01:03:06,520 --> 01:03:10,280 Speaker 1: sound engineer. Michael Almato is our contributing producer. I'm your host, 1298 01:03:10,280 --> 01:03:13,080 Speaker 1: Bridget Todd. If you want to help us grow, rate 1299 01:03:13,160 --> 01:03:13,720 Speaker 1: and review. 1300 01:03:13,560 --> 01:03:14,720 Speaker 4: Us on Apple Podcasts. 1301 01:03:15,360 --> 01:03:18,200 Speaker 1: For more podcasts from iHeartRadio, check out the iHeartRadio app, 1302 01:03:18,200 --> 01:03:30,800 Speaker 1: Apple Podcasts, or wherever you get your podcasts.