1 00:00:05,040 --> 00:00:09,120 Speaker 1: How do the algorithms that were surrounded with shape our lives? 2 00:00:09,520 --> 00:00:13,160 Speaker 1: Why does a journalist begin to write differently once metrics 3 00:00:13,240 --> 00:00:19,720 Speaker 1: are introduced? What is algorithmic capture? Has clickbait always existed? 4 00:00:20,079 --> 00:00:22,880 Speaker 1: What did that look like before the Internet? How could 5 00:00:22,920 --> 00:00:28,000 Speaker 1: even vegan content creators go in for rage bait? What 6 00:00:28,080 --> 00:00:30,080 Speaker 1: does any of this have to do with why someone 7 00:00:30,360 --> 00:00:34,040 Speaker 1: would insist on cooking pasta in the bathtub? Or the 8 00:00:34,159 --> 00:00:39,440 Speaker 1: nineteenth century actress Sarah Bernhardt or one weird trick or 9 00:00:40,040 --> 00:00:43,880 Speaker 1: Oxford English Dictionary's word of the year. Join me today 10 00:00:43,920 --> 00:00:48,280 Speaker 1: with sociologist Angel Christen as we talk about how algorithms 11 00:00:48,479 --> 00:00:56,960 Speaker 1: invisibly sculpt human behavior. Welcome to Intercosmos with me David Eagleman. 12 00:00:57,080 --> 00:01:00,800 Speaker 1: I'm a neuroscientist and an author at Stanford An. These episodes, 13 00:01:00,840 --> 00:01:04,520 Speaker 1: we sail deeply into our three pound universe to understand 14 00:01:04,640 --> 00:01:07,520 Speaker 1: why and how our lives look the way they do. 15 00:01:24,720 --> 00:01:27,880 Speaker 1: Every brain is trying to navigate itself through a very 16 00:01:28,000 --> 00:01:33,280 Speaker 1: social world, and it's always unconsciously making predictions to figure 17 00:01:33,319 --> 00:01:36,040 Speaker 1: things out like what should I pay attention to or 18 00:01:36,080 --> 00:01:37,679 Speaker 1: what is worth my time? 19 00:01:38,040 --> 00:01:39,320 Speaker 2: What should I care about? 20 00:01:40,040 --> 00:01:44,039 Speaker 1: And for essentially the entirety of human history, those signals 21 00:01:44,040 --> 00:01:46,479 Speaker 1: came from other humans. 22 00:01:46,560 --> 00:01:47,680 Speaker 2: You read a lot. 23 00:01:47,520 --> 00:01:50,760 Speaker 1: Of information from the expressions on their faces like a 24 00:01:51,280 --> 00:01:55,720 Speaker 1: raised eyebrow. You hear things in the tone of people's voices. 25 00:01:55,800 --> 00:01:59,560 Speaker 1: You modify your behavior if you are getting signals of 26 00:01:59,600 --> 00:02:03,160 Speaker 1: approof or disapproval, not just from your parents, but more 27 00:02:03,320 --> 00:02:07,320 Speaker 1: generally from your tribe. Our brains have worked with these 28 00:02:07,360 --> 00:02:11,160 Speaker 1: sorts of signals for millions of years. You're looking for 29 00:02:11,560 --> 00:02:15,119 Speaker 1: a nod of approval, or people laugh at what you say, 30 00:02:15,200 --> 00:02:19,760 Speaker 1: or they scowl at it or whatever. But now imagine 31 00:02:19,840 --> 00:02:25,239 Speaker 1: replacing all that with numbers. Now you've got a dashboard 32 00:02:25,600 --> 00:02:28,320 Speaker 1: and a counter that ticks upward, and you've got a 33 00:02:28,440 --> 00:02:32,160 Speaker 1: graph that rises or falls, and it's all in real time, 34 00:02:32,520 --> 00:02:36,600 Speaker 1: and you have a notification that says three four hundred 35 00:02:36,639 --> 00:02:41,799 Speaker 1: people watched this or twelve people watched this. So, all 36 00:02:41,800 --> 00:02:45,560 Speaker 1: of a sudden, in this past nanosecond of human evolution, 37 00:02:46,120 --> 00:02:50,000 Speaker 1: we are suddenly in an era when the signals that 38 00:02:50,200 --> 00:02:56,320 Speaker 1: guide our behavior are not primarily human faces, but instead metrics. 39 00:02:56,360 --> 00:03:00,600 Speaker 1: You've got numbers and rankings, you've got dashboards, and it's 40 00:03:00,720 --> 00:03:05,160 Speaker 1: based on algorithms that you can't really see. And these 41 00:03:05,200 --> 00:03:09,200 Speaker 1: algorithms decide what appears in front of us and what disappears. 42 00:03:09,680 --> 00:03:14,359 Speaker 1: And here's the wild part. When those signals change, we change, 43 00:03:14,560 --> 00:03:19,600 Speaker 1: often unconsciously. Writers will change what they write based on 44 00:03:19,639 --> 00:03:23,720 Speaker 1: the feedback. Creators will change what they're about based on 45 00:03:23,760 --> 00:03:27,840 Speaker 1: the feedback. Sometimes there are subtle ways this happens, like 46 00:03:28,120 --> 00:03:31,239 Speaker 1: someone tweaks the headline, or they make a video shorter, 47 00:03:31,480 --> 00:03:35,200 Speaker 1: or they spend more time thinking about a stronger hook. 48 00:03:35,520 --> 00:03:41,840 Speaker 1: But pretty quickly, entire professions can reorganize themselves around these 49 00:03:41,960 --> 00:03:47,080 Speaker 1: invisible feedback systems. So what happens now that algorithms are 50 00:03:47,120 --> 00:03:50,720 Speaker 1: the primary environment that we're swimming in. What happens to 51 00:03:51,160 --> 00:03:55,520 Speaker 1: professional values, what happens to identity? Just think about one 52 00:03:55,600 --> 00:03:58,560 Speaker 1: example of this. One of the brand new words that 53 00:03:58,600 --> 00:04:01,200 Speaker 1: we all witness the birth of a couple decades ago 54 00:04:01,480 --> 00:04:04,880 Speaker 1: was clickbait. As you presumably know, this is one of 55 00:04:04,920 --> 00:04:09,560 Speaker 1: those provocative headlines like you'll never believe what happens next, 56 00:04:09,760 --> 00:04:12,520 Speaker 1: and this gets you to go down some rabbit hole 57 00:04:12,560 --> 00:04:16,240 Speaker 1: that you didn't intend to go down. But now clickbait 58 00:04:16,560 --> 00:04:21,000 Speaker 1: has evolved into Oxford English Dictionaries word of the. 59 00:04:21,080 --> 00:04:23,960 Speaker 2: Year last year, which is rage bait. 60 00:04:24,480 --> 00:04:28,000 Speaker 1: This is the next evolutionary step in the attention economy. 61 00:04:28,520 --> 00:04:32,640 Speaker 1: Rage bait is all about shouting something, some statement that's 62 00:04:32,680 --> 00:04:38,200 Speaker 1: so inflammatory or so absurd that your nervous system lights 63 00:04:38,279 --> 00:04:42,280 Speaker 1: up before your more thoughtful neural networks even get their 64 00:04:42,320 --> 00:04:46,440 Speaker 1: shoes on. So you feel a surge of whatever anger 65 00:04:46,600 --> 00:04:50,720 Speaker 1: or discuss or disbelief, and before you're consciously aware of it, 66 00:04:50,960 --> 00:04:54,880 Speaker 1: your fingers are clicking and you're commenting, you're sharing, you're 67 00:04:55,200 --> 00:04:58,279 Speaker 1: stitching a video, you're firing back at someone in the 68 00:04:58,440 --> 00:04:59,200 Speaker 1: comment section. 69 00:05:00,120 --> 00:05:01,000 Speaker 2: You're all worked up. 70 00:05:01,240 --> 00:05:05,560 Speaker 1: But from the algorithm's point of view, engagement is engagement, 71 00:05:05,839 --> 00:05:11,000 Speaker 1: and in a system that measures success by interaction, provoking 72 00:05:11,080 --> 00:05:16,000 Speaker 1: emotion is a very effective strategy. So I'm fascinated with 73 00:05:16,040 --> 00:05:18,800 Speaker 1: what all this means for us as a society. And 74 00:05:18,839 --> 00:05:21,040 Speaker 1: I knew there was no one better to call for 75 00:05:21,080 --> 00:05:25,120 Speaker 1: this than Onzel. Christen Angel is a sociologist who has 76 00:05:25,120 --> 00:05:31,760 Speaker 1: spent years embedded inside newsrooms, inside influencer culture, inside the 77 00:05:31,800 --> 00:05:36,920 Speaker 1: worlds where algorithms and analytics shape what people produce and 78 00:05:36,960 --> 00:05:41,600 Speaker 1: how they see themselves on shell studies, incentives, and how 79 00:05:41,680 --> 00:05:46,320 Speaker 1: our digital infrastructures are reshaping the social fabric around us. 80 00:05:46,400 --> 00:05:48,800 Speaker 1: So I'm so pleased to sit down with her today 81 00:05:48,960 --> 00:05:53,560 Speaker 1: to talk about what happens when human brains live inside 82 00:05:53,720 --> 00:06:03,400 Speaker 1: algorithmic systems and how those systems are shaping our behavior. So, Angel, 83 00:06:03,520 --> 00:06:08,760 Speaker 1: you study algorithms and their social impact on people, tell 84 00:06:08,800 --> 00:06:09,360 Speaker 1: us about that. 85 00:06:09,839 --> 00:06:13,640 Speaker 3: For the past ten years, I've been looking at how 86 00:06:13,680 --> 00:06:17,640 Speaker 3: algorithmic technologies are playing an increasingly important role in people's 87 00:06:17,640 --> 00:06:20,000 Speaker 3: lives and in their work. So now the thing is, 88 00:06:20,000 --> 00:06:22,920 Speaker 3: I'm a sociologist by training, so I really care about 89 00:06:23,000 --> 00:06:27,919 Speaker 3: people's identities, their work practices, how they communicate and relate 90 00:06:28,200 --> 00:06:32,160 Speaker 3: to others, and all of that has been completely transformed 91 00:06:32,480 --> 00:06:37,000 Speaker 3: with digital technologies and the computational procedure sustaining them. Everything 92 00:06:37,080 --> 00:06:41,760 Speaker 3: we do now is mediated through computational procedures one way 93 00:06:41,839 --> 00:06:45,400 Speaker 3: or another, thanks to mobile devices on the one hand 94 00:06:45,440 --> 00:06:46,880 Speaker 3: and computers on the other. 95 00:06:47,360 --> 00:06:49,240 Speaker 2: So let's take a specific example. 96 00:06:49,320 --> 00:06:53,479 Speaker 1: So you got interested some years ago in how journalists 97 00:06:53,480 --> 00:06:56,039 Speaker 1: were writing their articles and what kind of things they 98 00:06:56,200 --> 00:07:00,159 Speaker 1: chose to write, and how that changed once these with 99 00:07:00,320 --> 00:07:01,920 Speaker 1: the metrics got introduced. 100 00:07:02,560 --> 00:07:05,440 Speaker 4: Yeah, so that was so interesting. At first. 101 00:07:05,480 --> 00:07:08,240 Speaker 3: I came to kind of study journalism because I was, like, 102 00:07:08,320 --> 00:07:12,600 Speaker 3: you know, with the Internet and kind of online advertising, 103 00:07:12,800 --> 00:07:16,520 Speaker 3: the business models of the news are changing right in 104 00:07:16,560 --> 00:07:20,120 Speaker 3: Big Park because online advertising move to social media platforms 105 00:07:20,200 --> 00:07:23,440 Speaker 3: and Google, and so they had news websites had less 106 00:07:23,440 --> 00:07:25,440 Speaker 3: money and newspapers had less money, and so I was 107 00:07:25,520 --> 00:07:28,120 Speaker 3: kind of broadly interested in that and like, what does 108 00:07:28,160 --> 00:07:30,960 Speaker 3: that mean for the future of the news. And I 109 00:07:31,040 --> 00:07:34,360 Speaker 3: did what I always do. I'm an ethnographer, which means 110 00:07:34,400 --> 00:07:39,000 Speaker 3: that I go spend time with people. I interview them, 111 00:07:39,520 --> 00:07:42,640 Speaker 3: I have lunch with them, I observe how they work. 112 00:07:43,000 --> 00:07:45,440 Speaker 3: I become kind of part of the furniture at the office. 113 00:07:45,480 --> 00:07:47,800 Speaker 3: It's like a yeah, she's here again, you know, just 114 00:07:47,920 --> 00:07:51,280 Speaker 3: observing us another day. And what I realized at that 115 00:07:51,440 --> 00:07:55,240 Speaker 3: point is that in the different newsrooms that I was studying, 116 00:07:55,840 --> 00:07:58,000 Speaker 3: some of them were in New York, some of them 117 00:07:58,000 --> 00:08:03,320 Speaker 3: were in Paris, lists kept on looking at these specific 118 00:08:03,400 --> 00:08:07,360 Speaker 3: software programs that they were kind of obsessed with. And 119 00:08:07,400 --> 00:08:11,080 Speaker 3: so what were the software programs? They were web analytics, 120 00:08:11,080 --> 00:08:16,640 Speaker 3: software programs that were providing detailed, real time data about 121 00:08:16,760 --> 00:08:20,480 Speaker 3: what readers were doing on the website. Right, So it 122 00:08:20,600 --> 00:08:23,320 Speaker 3: was giving kind of social media metrics like how many 123 00:08:23,360 --> 00:08:27,160 Speaker 3: readers were coming from Facebook, from Twitter, etc. It was 124 00:08:27,240 --> 00:08:30,600 Speaker 3: telling people how many people had read the articles they 125 00:08:30,600 --> 00:08:34,600 Speaker 3: had published, right, was it ten people, twenty people, one 126 00:08:34,679 --> 00:08:38,240 Speaker 3: hundred thousand, ten hundred thousand, a million, right, So, giving 127 00:08:38,320 --> 00:08:41,720 Speaker 3: that it was ranking all the articles in terms of 128 00:08:41,760 --> 00:08:45,880 Speaker 3: their popularity on the website and on social media, and 129 00:08:45,920 --> 00:08:50,400 Speaker 3: it was also telling journalists how long readers were spending 130 00:08:50,480 --> 00:08:54,200 Speaker 3: on average on any given article, which, by the way, 131 00:08:54,320 --> 00:08:57,320 Speaker 3: is not a good metric in the sense that like 132 00:08:57,400 --> 00:09:00,480 Speaker 3: it's almost always in the range of like six to 133 00:09:00,480 --> 00:09:04,720 Speaker 3: fifteen seconds is the average time that readers spent on 134 00:09:04,800 --> 00:09:09,600 Speaker 3: any news article. Right, Yeah, not fun for journalists, definitely. 135 00:09:09,640 --> 00:09:12,560 Speaker 3: They preferred to ignore that one. And so what I 136 00:09:12,600 --> 00:09:16,240 Speaker 3: realized is that journalists kept on talking about that. So 137 00:09:16,240 --> 00:09:19,720 Speaker 3: that was the early two thousand tents, right. People didn't 138 00:09:19,760 --> 00:09:23,400 Speaker 3: really know. I mean, the internet was still pretty new, right, 139 00:09:23,480 --> 00:09:27,560 Speaker 3: and social media was even newer. But journalists were just like, wow, 140 00:09:27,720 --> 00:09:32,280 Speaker 3: look like that article is so popular. It's just like it's, 141 00:09:32,320 --> 00:09:35,320 Speaker 3: you know, such a hit, everybody's clicking on it. Well 142 00:09:35,320 --> 00:09:40,120 Speaker 3: as this article hmmm, disappointing. I spent two weeks reporting 143 00:09:40,200 --> 00:09:42,880 Speaker 3: this and no one's clicking on it. And so they 144 00:09:43,000 --> 00:09:46,760 Speaker 3: kept on discussing this and making jokes about it, talking 145 00:09:46,800 --> 00:09:50,640 Speaker 3: about it and kind of more and more using this 146 00:09:50,920 --> 00:09:53,560 Speaker 3: data to make sense of what it meant to be 147 00:09:53,720 --> 00:09:54,800 Speaker 3: a good journalist. 148 00:09:55,640 --> 00:09:56,000 Speaker 2: Yeah. 149 00:09:56,160 --> 00:10:00,040 Speaker 1: So first, what was the difference before if you you 150 00:10:00,120 --> 00:10:03,880 Speaker 1: were a newspaper writer, let's say twenty years before that, 151 00:10:04,040 --> 00:10:05,239 Speaker 1: how did you get feedback? 152 00:10:05,360 --> 00:10:07,400 Speaker 4: Yeah, so that's the really interesting thing. 153 00:10:07,520 --> 00:10:09,720 Speaker 3: So what's really fun there, and that's you know, the 154 00:10:09,760 --> 00:10:12,199 Speaker 3: great point of being in academia is that other people 155 00:10:12,240 --> 00:10:15,440 Speaker 3: have studied print newsrooms in the eighties and nineties, right, 156 00:10:15,480 --> 00:10:18,480 Speaker 3: so they have all of these historical material about how 157 00:10:18,520 --> 00:10:21,760 Speaker 3: print newsrooms used to work. Now, the print newsrooms, the 158 00:10:21,760 --> 00:10:25,960 Speaker 3: way it used to work was two characteristics. First, journalists 159 00:10:26,000 --> 00:10:29,440 Speaker 3: and editors did not care much about the audience, right, 160 00:10:29,840 --> 00:10:33,080 Speaker 3: And they didn't care mostly because they thought that what 161 00:10:33,240 --> 00:10:38,080 Speaker 3: mattered more was the opinion of their peers and superiors. 162 00:10:38,120 --> 00:10:42,240 Speaker 3: So there was this kind of strong professional identities that 163 00:10:42,559 --> 00:10:47,120 Speaker 3: what was really important was what other journalists were thinking 164 00:10:47,160 --> 00:10:51,480 Speaker 3: about you, both in new newsroom and in other newsrooms. Right, 165 00:10:51,520 --> 00:10:54,520 Speaker 3: because journalists always tried to move between one newsroom and 166 00:10:54,600 --> 00:10:54,800 Speaker 3: the next. 167 00:10:54,840 --> 00:10:56,280 Speaker 4: So let's say you had the New York Times. 168 00:10:56,480 --> 00:10:58,720 Speaker 3: You also care about what people at the Washington Post 169 00:10:58,760 --> 00:11:00,640 Speaker 3: think about your work, because if they like it, perhaps 170 00:11:00,640 --> 00:11:03,000 Speaker 3: they'll offer your job later on that kind of stuff, 171 00:11:03,640 --> 00:11:04,680 Speaker 3: and then what your. 172 00:11:04,640 --> 00:11:06,680 Speaker 4: Hierarchical superiors total of your work. 173 00:11:06,720 --> 00:11:09,600 Speaker 3: So your editors in chief basically, right, and if your 174 00:11:09,679 --> 00:11:12,360 Speaker 3: editor in chief was saying like, wow, this is a 175 00:11:12,400 --> 00:11:15,640 Speaker 3: great article, well done, that was that you know, that 176 00:11:15,840 --> 00:11:18,480 Speaker 3: was kind of the best things that could happen to 177 00:11:18,600 --> 00:11:23,000 Speaker 3: you on any given day. Now, they were receiving letters 178 00:11:23,040 --> 00:11:26,360 Speaker 3: from the audience, right. So letters to the editor are 179 00:11:26,400 --> 00:11:29,760 Speaker 3: like kind of a long established tradition, most newspapers have them, 180 00:11:30,320 --> 00:11:34,080 Speaker 3: but there are all of these like historical studies showing 181 00:11:34,160 --> 00:11:37,880 Speaker 3: that journalists mostly disregarded these letters and they're like, oh yeah, 182 00:11:37,880 --> 00:11:40,960 Speaker 3: people are crazy, they're understand those crazy stuff. They don't 183 00:11:41,000 --> 00:11:45,840 Speaker 3: understand how journalism works, right, So a very different kind 184 00:11:45,840 --> 00:11:51,120 Speaker 3: of relationship where really what the audience was actually doing 185 00:11:51,280 --> 00:11:55,640 Speaker 3: and what it wanted wasn't very well understood or kind 186 00:11:55,640 --> 00:11:59,120 Speaker 3: of paid attention to. The second aspect, there was also 187 00:11:59,160 --> 00:12:03,439 Speaker 3: that with newspapers there were lots of surveys obviously, because 188 00:12:03,440 --> 00:12:05,920 Speaker 3: you had marketing departments and you had like kind of 189 00:12:06,000 --> 00:12:09,240 Speaker 3: commercial the commercial side of publications, right, and they cared 190 00:12:09,320 --> 00:12:12,840 Speaker 3: about the audience because that's how depending on you know, 191 00:12:12,920 --> 00:12:16,360 Speaker 3: readership figures. That's how they were able to charge for 192 00:12:17,080 --> 00:12:21,520 Speaker 3: more expensive advertising space, right, And so that's what revenues 193 00:12:21,559 --> 00:12:25,840 Speaker 3: depended on. So the marketing departments were doing surveys. But 194 00:12:25,880 --> 00:12:28,319 Speaker 3: what's interesting about these surveys is that you know, in 195 00:12:28,360 --> 00:12:31,600 Speaker 3: the eighteen and nineties, they only asked like, well, do 196 00:12:31,679 --> 00:12:34,920 Speaker 3: you like the newspaper and people would say yeah, But 197 00:12:35,000 --> 00:12:38,920 Speaker 3: they didn't have super granular data about well, which section 198 00:12:39,080 --> 00:12:41,800 Speaker 3: exactly do you read the most People would say like, well, 199 00:12:41,880 --> 00:12:44,959 Speaker 3: based on memory, I tend to read more of the lifestyle. 200 00:12:45,200 --> 00:12:48,480 Speaker 3: Say but you know, I really care about international news too, Right, 201 00:12:48,559 --> 00:12:51,040 Speaker 3: So people they were relying on this kind of post 202 00:12:51,080 --> 00:12:54,760 Speaker 3: hoc memories and recollections of what readers were doing, and 203 00:12:54,800 --> 00:12:58,760 Speaker 3: they didn't really know in detail which articles and which 204 00:12:58,800 --> 00:13:02,000 Speaker 3: topics they cared the most. Now comes the Internet and 205 00:13:02,080 --> 00:13:04,840 Speaker 3: comes web analytics and the kind of software programs and 206 00:13:04,880 --> 00:13:08,720 Speaker 3: algorithms kind of displaying with dashboards what these analytics look 207 00:13:08,840 --> 00:13:14,000 Speaker 3: like to journalists and editors. Suddenly they realize that no 208 00:13:14,040 --> 00:13:19,280 Speaker 3: one's clicking on international news. Very few people click on 209 00:13:19,480 --> 00:13:24,160 Speaker 3: political news unless it involves some kind of scandal or 210 00:13:24,240 --> 00:13:28,760 Speaker 3: sex or celebrities. Right, that people care a lot about 211 00:13:29,080 --> 00:13:33,319 Speaker 3: lifestyle news. They have a lot about celebrity news. They 212 00:13:33,360 --> 00:13:36,440 Speaker 3: care not at all about culture and the arts. That's 213 00:13:36,559 --> 00:13:39,560 Speaker 3: not really what people click on, right, And so suddenly 214 00:13:39,760 --> 00:13:43,520 Speaker 3: they have this kind of like almost tsunami of data 215 00:13:43,679 --> 00:13:46,360 Speaker 3: telling them what people are actually clicking on. 216 00:13:46,679 --> 00:13:49,360 Speaker 4: And that's kind of a cognitive. 217 00:13:48,880 --> 00:13:52,600 Speaker 3: Revolution for journalists, right, because suddenly they're just like, wait, 218 00:13:52,800 --> 00:13:55,880 Speaker 3: what should we do? Should we only do tabloid news 219 00:13:56,320 --> 00:13:57,760 Speaker 3: because that's what readers want? 220 00:13:58,760 --> 00:14:00,320 Speaker 4: Or is our jobs something else? 221 00:14:01,080 --> 00:14:05,640 Speaker 1: And you know, it's interesting because from a behavioral economics perspective, 222 00:14:06,040 --> 00:14:09,440 Speaker 1: even if you ask readers in a very granular fashion 223 00:14:09,559 --> 00:14:12,000 Speaker 1: what they wanted and so on, they don't necessarily know that. 224 00:14:12,080 --> 00:14:14,400 Speaker 1: Consciously they might think I'm the kind of person who 225 00:14:14,400 --> 00:14:17,640 Speaker 1: clicks on international news, even though they don't. Okay, So 226 00:14:17,679 --> 00:14:21,040 Speaker 1: there's this notion of algorithmic capture, which is that let's 227 00:14:21,040 --> 00:14:24,080 Speaker 1: say you're a writer, you start chasing the numbers and 228 00:14:24,120 --> 00:14:27,680 Speaker 1: you end up doing what the algorithm wants. Now, one 229 00:14:27,800 --> 00:14:32,680 Speaker 1: might say, okay, but maybe there was something like editorial capture. 230 00:14:32,520 --> 00:14:34,960 Speaker 1: The editor who's seen or to you, who really admired 231 00:14:35,000 --> 00:14:36,880 Speaker 1: you end up doing what he or she wanted. 232 00:14:37,400 --> 00:14:39,400 Speaker 2: The problem is that the algorithm is. 233 00:14:39,280 --> 00:14:43,239 Speaker 1: More opaque, right, and it changes, it's fungible. 234 00:14:43,680 --> 00:14:44,760 Speaker 2: So tell us how you see that? 235 00:14:44,920 --> 00:14:48,520 Speaker 3: Yeah, So that's fascinating because that's exactly what I observed 236 00:14:48,520 --> 00:14:51,640 Speaker 3: in newsrooms, and that's what my book Metrics at Work 237 00:14:52,000 --> 00:14:55,920 Speaker 3: Journalism is a contested meaning of algorithms is basically all 238 00:14:55,960 --> 00:14:59,320 Speaker 3: about right. So what I find kind of due to 239 00:14:59,480 --> 00:15:02,640 Speaker 3: that kind of again that wave of granular data that 240 00:15:02,760 --> 00:15:05,560 Speaker 3: kind of enter newsrooms, and you know often it entered 241 00:15:05,560 --> 00:15:09,440 Speaker 3: newsrooms with the best intentions, right, which was that editors, 242 00:15:10,200 --> 00:15:13,720 Speaker 3: journalists and the companies that were that were usually for 243 00:15:13,840 --> 00:15:17,280 Speaker 3: profit companies that were providing these kind of dashboards and 244 00:15:17,360 --> 00:15:22,040 Speaker 3: software programs. We're like, listen, it's a question of democratization. 245 00:15:22,680 --> 00:15:26,280 Speaker 3: We want to give journalists the knowledge of what like 246 00:15:26,400 --> 00:15:30,560 Speaker 3: their audiences are actually engaging with so that they can 247 00:15:30,640 --> 00:15:33,240 Speaker 3: survive in the digital age, right, so that they can 248 00:15:33,320 --> 00:15:36,240 Speaker 3: drive in the digital age. So that was the impulse, 249 00:15:36,280 --> 00:15:39,520 Speaker 3: a good one, right. But then what you see is 250 00:15:39,520 --> 00:15:43,320 Speaker 3: that once that data is available, you get exactly the 251 00:15:43,400 --> 00:15:46,720 Speaker 3: kind of algorithm captures that you find, right, And there 252 00:15:46,760 --> 00:15:47,080 Speaker 3: is this. 253 00:15:47,200 --> 00:15:49,000 Speaker 4: Like push towards clickbait. 254 00:15:49,800 --> 00:15:52,800 Speaker 3: It's just like it's and it happens at many different 255 00:15:52,880 --> 00:15:58,320 Speaker 3: levels individually it happens because journalists, like all communicators, and 256 00:15:58,320 --> 00:16:01,520 Speaker 3: I include academics in that, they want to be read. 257 00:16:01,960 --> 00:16:04,040 Speaker 3: What's the point of being a journalist if no one 258 00:16:04,120 --> 00:16:06,280 Speaker 3: reads your stuff, you know what I mean? That's kind 259 00:16:06,280 --> 00:16:09,000 Speaker 3: of an existential question. And so to me, it makes 260 00:16:09,040 --> 00:16:11,040 Speaker 3: perfect sense that you would be like, well, I'm going 261 00:16:11,120 --> 00:16:14,040 Speaker 3: to do everything in my power so that you know, 262 00:16:14,240 --> 00:16:17,920 Speaker 3: my articles find the audience, right, and if that means 263 00:16:17,960 --> 00:16:21,320 Speaker 3: putting a slightly more clickbaita title, so be it. 264 00:16:21,840 --> 00:16:24,920 Speaker 1: And clickbaity is things like here's one weird thing you 265 00:16:24,960 --> 00:16:26,440 Speaker 1: can do, and so what else. 266 00:16:26,280 --> 00:16:27,040 Speaker 2: Do you see? 267 00:16:27,240 --> 00:16:29,280 Speaker 3: Yeah, so at the time, Okay, so that's going to 268 00:16:29,320 --> 00:16:31,760 Speaker 3: be a bit dated now because again this was you know, 269 00:16:31,840 --> 00:16:34,320 Speaker 3: the bright days of the early twenty tents, right, but 270 00:16:34,400 --> 00:16:37,680 Speaker 3: the big things where yeah, this one wheel trick you know, 271 00:16:38,240 --> 00:16:44,800 Speaker 3: you'll never believe. You know, what happened next was shocking listicles. 272 00:16:44,960 --> 00:16:48,480 Speaker 3: We're a big thing, right, like the ten best restaurants 273 00:16:48,520 --> 00:16:53,880 Speaker 3: in San Francisco, you know kind of stuff. Slide shows too, right, 274 00:16:54,040 --> 00:16:58,200 Speaker 3: because at the time, a lot of newsrooms were still 275 00:16:58,240 --> 00:17:01,280 Speaker 3: counting page views, and so a slide show with ten 276 00:17:01,520 --> 00:17:04,600 Speaker 3: pages counted as ten phage views. I know, it's really 277 00:17:04,680 --> 00:17:07,800 Speaker 3: kind of a cheap trick, so kind of things like that, right, 278 00:17:07,840 --> 00:17:12,040 Speaker 3: And you could see these formats becoming widely popular across 279 00:17:12,119 --> 00:17:16,480 Speaker 3: newsrooms because newsrooms are also all watching each other and 280 00:17:16,560 --> 00:17:19,679 Speaker 3: seeing especially at the time, it was Busfeed and the 281 00:17:19,760 --> 00:17:23,399 Speaker 3: Huffington posts using these kind of more clickbaity tactics and 282 00:17:23,440 --> 00:17:25,840 Speaker 3: getting the traffic numbers that were coming with from it, 283 00:17:26,440 --> 00:17:29,840 Speaker 3: especially on Facebook and Twitter, and everybody was like, oh, okay, 284 00:17:29,960 --> 00:17:32,800 Speaker 3: we've got to do this, right, So then a couple 285 00:17:32,800 --> 00:17:35,280 Speaker 3: of things kind of happen. So first one, which is 286 00:17:35,359 --> 00:17:39,080 Speaker 3: exactly what you said, is that you know, social media 287 00:17:39,160 --> 00:17:44,600 Speaker 3: traffic and social media algorithms are fiical. They have gotten 288 00:17:44,720 --> 00:17:49,680 Speaker 3: only morephical since, right, But they're opaque, so no one 289 00:17:49,760 --> 00:17:53,359 Speaker 3: really understands what's getting recommended. And you know, platforms have 290 00:17:53,480 --> 00:17:56,920 Speaker 3: given some modicum of information, but they also don't want 291 00:17:57,000 --> 00:18:00,119 Speaker 3: users to gain the system, so they're not given that 292 00:18:00,240 --> 00:18:01,320 Speaker 3: much information. 293 00:18:01,560 --> 00:18:01,720 Speaker 4: Right. 294 00:18:02,320 --> 00:18:07,000 Speaker 3: Then, social media platforms also made sudden changes over the 295 00:18:07,119 --> 00:18:12,320 Speaker 3: years that really hurt newsrooms. For example, Facebook, at some 296 00:18:12,440 --> 00:18:16,119 Speaker 3: point in the mid twenty tens decided that it was 297 00:18:16,160 --> 00:18:22,200 Speaker 3: going to stop prioritizing posts and articles from news organizations 298 00:18:22,240 --> 00:18:28,280 Speaker 3: and instead promote relatively more organic content, namely content coming 299 00:18:28,280 --> 00:18:32,240 Speaker 3: from individuals, and that's where influencers started driving. 300 00:18:32,280 --> 00:18:33,840 Speaker 4: But that's for a bit later. 301 00:18:34,040 --> 00:18:36,399 Speaker 3: But so from one day to the next, basically you 302 00:18:36,480 --> 00:18:39,720 Speaker 3: had like all news websites because traffic was like that, 303 00:18:40,119 --> 00:18:43,439 Speaker 3: just like going way kind of further down, just because 304 00:18:43,480 --> 00:18:47,000 Speaker 3: in one change in the Facebook algorithm that cut traffic 305 00:18:47,080 --> 00:18:50,160 Speaker 3: can of in half for many newsrooms. Right, So it's 306 00:18:50,200 --> 00:18:53,600 Speaker 3: fickle and things are changing, and what works well as 307 00:18:53,600 --> 00:18:57,119 Speaker 3: a recipe for traffic at one point stops working, and 308 00:18:57,160 --> 00:18:59,280 Speaker 3: everybody's kind of in the dark and trying to figure 309 00:18:59,280 --> 00:19:02,040 Speaker 3: out what happens. So that's kind of the first problem. 310 00:19:02,440 --> 00:19:05,440 Speaker 3: The second problem is that, you know, journalists, we're also 311 00:19:05,480 --> 00:19:11,160 Speaker 3: thinking really hard about wait, like, if we follow what 312 00:19:11,240 --> 00:19:16,840 Speaker 3: the algorithms want, we're only going to do tablauid news right, 313 00:19:17,320 --> 00:19:21,520 Speaker 3: namely against sex, kndle celebrities that like, you know, it 314 00:19:21,640 --> 00:19:23,920 Speaker 3: always people are always going to click more on that, 315 00:19:24,080 --> 00:19:27,480 Speaker 3: you know, but this is not what our role is. 316 00:19:27,680 --> 00:19:30,320 Speaker 4: At the end of the day. We became journalists because 317 00:19:30,359 --> 00:19:30,960 Speaker 4: we care. 318 00:19:30,840 --> 00:19:37,919 Speaker 3: About democracy, holding the state and the powerful accountable, about 319 00:19:38,000 --> 00:19:42,959 Speaker 3: covering kind of longer stories, more complex stories, right, And 320 00:19:43,000 --> 00:19:46,120 Speaker 3: so what I kind of observed during kind of all 321 00:19:46,160 --> 00:19:50,080 Speaker 3: the time I spent in newsrooms is that basically journalists 322 00:19:50,119 --> 00:19:55,440 Speaker 3: were torn between these different definitions of what their professional 323 00:19:55,480 --> 00:19:58,400 Speaker 3: identity was about. On the one hand, they were like, well, 324 00:19:58,440 --> 00:20:01,920 Speaker 3: we're professional communicating, so we want our stuff to be read, 325 00:20:02,280 --> 00:20:05,119 Speaker 3: and so if clickbait has to happen, we will do 326 00:20:05,240 --> 00:20:08,680 Speaker 3: it because it's important we want to reach our audience. 327 00:20:08,840 --> 00:20:11,159 Speaker 3: But on the other hand, they were also saying, well, 328 00:20:11,840 --> 00:20:16,360 Speaker 3: we care about sharing important things that will make our 329 00:20:16,440 --> 00:20:20,920 Speaker 3: readers more enlightened citizens of the world. And so they 330 00:20:20,920 --> 00:20:24,280 Speaker 3: were kind of always torn between these two kind of 331 00:20:24,320 --> 00:20:27,760 Speaker 3: definitions and kind of moving back and forth. And what 332 00:20:27,920 --> 00:20:31,800 Speaker 3: was fascinating that they would often do like funny little 333 00:20:31,840 --> 00:20:36,119 Speaker 3: accounting things where they would do like, Okay, so I 334 00:20:36,200 --> 00:20:39,679 Speaker 3: really want to write this article about say, you know 335 00:20:39,680 --> 00:20:43,520 Speaker 3: again international news Ukraine, let's say, right, because I really 336 00:20:43,560 --> 00:20:46,199 Speaker 3: think it's important and I think our readers need to 337 00:20:46,240 --> 00:20:48,679 Speaker 3: know about this. But I know that people are not 338 00:20:48,720 --> 00:20:51,320 Speaker 3: going to click a lot right, So to make up 339 00:20:51,400 --> 00:20:54,760 Speaker 3: for it, I'm also going to write an article on't 340 00:20:54,800 --> 00:20:58,800 Speaker 3: say Rhianna right, and that's going to boost my traffic numbers, 341 00:20:59,000 --> 00:21:03,160 Speaker 3: And that way I've kind of subsidized my Ukraine article 342 00:21:03,400 --> 00:21:06,639 Speaker 3: with the Rhanna article in terms of traffic, So they 343 00:21:06,640 --> 00:21:10,280 Speaker 3: would do like all of these little deals with themselves 344 00:21:10,640 --> 00:21:27,440 Speaker 3: to try to optimize both sets of kind of constraints. 345 00:21:29,080 --> 00:21:32,359 Speaker 1: What was the equivalent of clickbait back in the day 346 00:21:32,560 --> 00:21:36,239 Speaker 1: of newspapers, because there was what's called yellow journalism. I mean, 347 00:21:36,280 --> 00:21:38,080 Speaker 1: there must have been ways that people are trying to 348 00:21:38,080 --> 00:21:40,280 Speaker 1: get readers, and of course there were tabloid presses. 349 00:21:40,440 --> 00:21:43,800 Speaker 3: Yeah, absolutely, so there were many equivalents, and so that's 350 00:21:43,800 --> 00:21:48,480 Speaker 3: the same clickbait has always existed in many ways. So 351 00:21:48,600 --> 00:21:51,520 Speaker 3: at the time, let's see, there was a lot of 352 00:21:52,760 --> 00:21:56,960 Speaker 3: kind of as you say, yellow journalism, so extremely outrageous, 353 00:21:57,240 --> 00:22:03,120 Speaker 3: like inflammatory, kind of aggressive headlines, you know, really kind 354 00:22:03,119 --> 00:22:09,280 Speaker 3: of emphasizing kind of hatred right or like kind of xenophobia, bigotry, 355 00:22:09,520 --> 00:22:11,560 Speaker 3: like you know, things like that have always existed in 356 00:22:11,600 --> 00:22:14,760 Speaker 3: many newspapers over the past two centuries have really indulged 357 00:22:14,760 --> 00:22:18,320 Speaker 3: in that because again it's like stokes kind of patriotic 358 00:22:18,440 --> 00:22:21,119 Speaker 3: sentiments for example, and people are like, yeah, like you know, 359 00:22:21,520 --> 00:22:25,919 Speaker 3: I'm gonna buy this newspaper. So that's kind of one aspect. Definitely, 360 00:22:25,960 --> 00:22:29,840 Speaker 3: coverage of stars and celebrities, for example, at the time 361 00:22:30,000 --> 00:22:33,439 Speaker 3: Sarah Bernhardt, you know, in the late nineteenth century was 362 00:22:33,480 --> 00:22:38,720 Speaker 3: like the idol. All kind of teenage women were doing clippings, 363 00:22:38,920 --> 00:22:43,359 Speaker 3: newspaper clippings of the actress Sarah Bernhart, that was the thing, 364 00:22:43,400 --> 00:22:46,640 Speaker 3: and so newspapers would always put lots of pictures of her, 365 00:22:47,080 --> 00:22:49,320 Speaker 3: so that like the news that teenage girls would do 366 00:22:49,359 --> 00:22:51,760 Speaker 3: the clippings, you know, so they would force their parents 367 00:22:51,800 --> 00:22:54,439 Speaker 3: to buy the newspapers so that they could do that. 368 00:22:55,359 --> 00:23:00,359 Speaker 3: Same with lifestyle and kind of beauty advice, same things. 369 00:23:00,359 --> 00:23:04,440 Speaker 3: That's always been very popular, cooking recipes, things like that, 370 00:23:04,600 --> 00:23:06,920 Speaker 3: you know what I mean. So it's not new, it's 371 00:23:07,040 --> 00:23:10,760 Speaker 3: just the shape it takes and the specific tricks that 372 00:23:11,000 --> 00:23:14,640 Speaker 3: people use to capture the attention changes with the medium, 373 00:23:15,040 --> 00:23:18,879 Speaker 3: you know what I mean, from print to broadcast to digital. 374 00:23:19,280 --> 00:23:23,800 Speaker 3: But again I think it's a change in degree, not 375 00:23:23,840 --> 00:23:25,800 Speaker 3: really a changing kind, if that makes sense. 376 00:23:26,000 --> 00:23:28,000 Speaker 1: So when you published your book in twenty twenty, you 377 00:23:28,080 --> 00:23:30,600 Speaker 1: were interested in this issue about clickbait and how people 378 00:23:30,600 --> 00:23:35,120 Speaker 1: are getting sucked into this whirlpool of that. Now we're 379 00:23:35,119 --> 00:23:39,200 Speaker 1: in twenty twenty six. So last year Oxford English Dictionary's 380 00:23:39,280 --> 00:23:42,720 Speaker 1: word of the Year was rage bait, which is close 381 00:23:42,760 --> 00:23:45,040 Speaker 1: cousins to clickbait tell us about rage bait. 382 00:23:45,760 --> 00:23:49,199 Speaker 3: So rage bait I think of as a kind of 383 00:23:49,359 --> 00:23:52,600 Speaker 3: like vengeful cousin of clickbait. 384 00:23:52,680 --> 00:23:54,520 Speaker 4: Right, well, clickbait was. 385 00:23:54,520 --> 00:23:58,439 Speaker 3: Still kind of light. You will never believe what happens next. 386 00:23:58,720 --> 00:24:05,080 Speaker 3: You will be shocked ten weird tricks to whatever do something, 387 00:24:05,240 --> 00:24:10,119 Speaker 3: you know. Rage bait is more about provoking you into 388 00:24:10,320 --> 00:24:14,560 Speaker 3: kind of negative, kind of arousal, right, negative emotions such 389 00:24:14,640 --> 00:24:21,440 Speaker 3: as anger, fear, hatred, again, not things that are radically new, 390 00:24:21,560 --> 00:24:25,160 Speaker 3: but really kind of pushing on that. The typical example 391 00:24:25,200 --> 00:24:28,280 Speaker 3: of rage bait is going to be an influencer or 392 00:24:28,280 --> 00:24:34,800 Speaker 3: someone on the internet just stating something outrageous, right, or 393 00:24:34,920 --> 00:24:39,919 Speaker 3: doing something outrageous but with complete confidence and innocence and 394 00:24:39,960 --> 00:24:41,120 Speaker 3: not seeming. 395 00:24:40,760 --> 00:24:41,800 Speaker 4: To see the problem. 396 00:24:42,200 --> 00:24:44,919 Speaker 3: Right. So there are a number of examples of that. 397 00:24:44,960 --> 00:24:46,800 Speaker 3: I mean, one of the ones that I like are 398 00:24:46,840 --> 00:24:52,639 Speaker 3: like these weird cooking videos, but where they cook things like, 399 00:24:52,720 --> 00:24:55,879 Speaker 3: for example, like in the bathroom using. 400 00:24:55,640 --> 00:24:58,159 Speaker 4: The baths stub and doing like this is really. 401 00:24:57,920 --> 00:25:00,720 Speaker 3: The most efficient way to cook pasta, things like that, 402 00:25:00,920 --> 00:25:03,960 Speaker 3: and like kind of really going going fully in you 403 00:25:03,960 --> 00:25:06,040 Speaker 3: know what I mean, and not acknowledging how weird it 404 00:25:06,119 --> 00:25:08,280 Speaker 3: is to try to cook pasta in the bastub or 405 00:25:08,280 --> 00:25:12,040 Speaker 3: whatever it is, or you know, I mean, there are 406 00:25:12,040 --> 00:25:15,560 Speaker 3: lots of examples. And what's really interesting about this type 407 00:25:15,600 --> 00:25:22,280 Speaker 3: of content is that it's typically produced by content creators 408 00:25:22,400 --> 00:25:28,280 Speaker 3: who know very well that it's going to infuriate people, right, 409 00:25:28,320 --> 00:25:30,679 Speaker 3: it's going to make them mad. But because it's going 410 00:25:30,760 --> 00:25:33,359 Speaker 3: to make them mad, they're gonna engage with the content. 411 00:25:33,400 --> 00:25:36,640 Speaker 3: They're gonna watch it, they're gonna comment on it, they're 412 00:25:36,680 --> 00:25:40,280 Speaker 3: gonna share it, all kind of basically yelling insults, you 413 00:25:40,320 --> 00:25:42,040 Speaker 3: know what I mean, and saying like how dare you? 414 00:25:42,200 --> 00:25:44,720 Speaker 3: How could you use? This is so gross? I can't 415 00:25:44,720 --> 00:25:45,960 Speaker 3: believe you. 416 00:25:46,240 --> 00:25:48,800 Speaker 4: Are you a troll? Why are you saying this? How 417 00:25:48,800 --> 00:25:49,480 Speaker 4: can you say this? 418 00:25:50,200 --> 00:25:55,280 Speaker 3: But all of this obviously translates into revenues and engagement 419 00:25:55,480 --> 00:25:57,840 Speaker 3: on social media platforms, and so that's very much a 420 00:25:57,960 --> 00:26:00,720 Speaker 3: deliberate kind of content productions. 421 00:26:01,000 --> 00:26:04,479 Speaker 1: When you think about rage bait, what percentage of that 422 00:26:04,640 --> 00:26:07,240 Speaker 1: is political versus I hadn't thought about the cooking past 423 00:26:07,320 --> 00:26:07,960 Speaker 1: of the bathtub. 424 00:26:08,960 --> 00:26:09,920 Speaker 4: That's a good question. 425 00:26:10,400 --> 00:26:11,320 Speaker 2: When I think about it. 426 00:26:11,359 --> 00:26:16,240 Speaker 1: I think people saying things politically that are very inflammatory. 427 00:26:16,040 --> 00:26:18,719 Speaker 2: But you I'm glad to see you have a broader 428 00:26:18,800 --> 00:26:19,919 Speaker 2: view of rage based. 429 00:26:19,640 --> 00:26:21,200 Speaker 4: I definitely have a broader view. 430 00:26:21,320 --> 00:26:23,840 Speaker 3: I mean I think so, I think it's a continuum, right, 431 00:26:23,920 --> 00:26:26,200 Speaker 3: always think about it is that it's really a spectrum 432 00:26:26,600 --> 00:26:30,160 Speaker 3: from you know what psychologist called kind of high arousal 433 00:26:30,440 --> 00:26:36,680 Speaker 3: negative content. Right, So that's going to be anything inflammatory, incendiary, 434 00:26:37,440 --> 00:26:40,800 Speaker 3: shocking in a negative way. Right, wh It just makes 435 00:26:40,840 --> 00:26:44,560 Speaker 3: you kind of freeze and it kind of bypasses whichever 436 00:26:44,800 --> 00:26:47,840 Speaker 3: defenses you may have, and you're just like, this is 437 00:26:48,240 --> 00:26:49,480 Speaker 3: serious and bad. 438 00:26:49,600 --> 00:26:50,880 Speaker 4: I need to pay attention. 439 00:26:51,080 --> 00:26:55,000 Speaker 3: Right, It's almost like an embodied response, right that just 440 00:26:55,080 --> 00:26:59,159 Speaker 3: like shotcuts kind of a lot of the usual ways 441 00:26:59,160 --> 00:27:02,360 Speaker 3: we have of interaction acting with media. So that's kind 442 00:27:02,400 --> 00:27:07,280 Speaker 3: of one way. And then like rage bait, I think 443 00:27:07,280 --> 00:27:09,840 Speaker 3: it's a bit of a wider kind of type of 444 00:27:09,880 --> 00:27:14,680 Speaker 3: content because it also involves other kind of emotions such 445 00:27:14,720 --> 00:27:20,280 Speaker 3: as like again discussed weirdness, like you know, a wider 446 00:27:20,720 --> 00:27:25,760 Speaker 3: set of reactions that are also negative but are not 447 00:27:25,840 --> 00:27:28,000 Speaker 3: necessarily about politics specifically. 448 00:27:29,240 --> 00:27:33,439 Speaker 1: Now, does it make sense for anyone on social media 449 00:27:33,520 --> 00:27:35,480 Speaker 1: to do clickbait and rage bait? 450 00:27:35,560 --> 00:27:35,720 Speaker 2: Is it? 451 00:27:35,800 --> 00:27:40,320 Speaker 1: Is it sensible? Or are we all sinking into a morass? 452 00:27:40,640 --> 00:27:42,600 Speaker 4: This is such an excellent question. 453 00:27:42,800 --> 00:27:47,400 Speaker 3: So it depends on the time and frame you're looking at. 454 00:27:47,560 --> 00:27:51,439 Speaker 3: And again, to some extent, you know, this is a 455 00:27:51,520 --> 00:27:55,000 Speaker 3: question that most kind of content creators have to deal 456 00:27:55,040 --> 00:27:58,680 Speaker 3: with at this point, and it also kind of resembles 457 00:27:58,680 --> 00:28:01,239 Speaker 3: the questions that newsrooms at the time had to deal with, 458 00:28:01,280 --> 00:28:02,440 Speaker 3: but in a bit of a different way. 459 00:28:02,480 --> 00:28:04,240 Speaker 4: So let me walk through that. 460 00:28:04,920 --> 00:28:09,800 Speaker 3: So for content creators, it depends on how you monetize 461 00:28:10,320 --> 00:28:15,960 Speaker 3: your online production, right, if you monetize it through platform payments, 462 00:28:16,200 --> 00:28:20,160 Speaker 3: so things like the YouTube Partner program, right where if 463 00:28:20,160 --> 00:28:22,280 Speaker 3: you qualify you have to have a channel that's kind 464 00:28:22,280 --> 00:28:25,680 Speaker 3: of big enough, but if you do qualify, you can 465 00:28:25,720 --> 00:28:28,879 Speaker 3: get fifty five percent of the advertising revenues that your 466 00:28:28,960 --> 00:28:34,320 Speaker 3: videos gather. Right, So in that case, basically your revenues 467 00:28:34,359 --> 00:28:37,960 Speaker 3: are going to depend on how many views you get 468 00:28:38,000 --> 00:28:41,000 Speaker 3: and watch time, right Obviously, that's that's going to be 469 00:28:41,360 --> 00:28:46,560 Speaker 3: the main thing. So in that case, rage bait in 470 00:28:46,640 --> 00:28:50,920 Speaker 3: the short term amazing, right, because you're going to provoke 471 00:28:51,040 --> 00:28:55,320 Speaker 3: people into watching you hook them in with something truly 472 00:28:55,560 --> 00:28:58,720 Speaker 3: kind of atrocious, you know, or really kind of hair 473 00:28:58,800 --> 00:29:02,120 Speaker 3: raising kind of kind of stuff that like makes it 474 00:29:02,200 --> 00:29:04,800 Speaker 3: so that like you can't look away. Literally, it's like 475 00:29:04,840 --> 00:29:06,560 Speaker 3: looking at a car crash, you know what I mean. 476 00:29:06,600 --> 00:29:08,560 Speaker 3: You you kind of have to watch it just to 477 00:29:08,600 --> 00:29:11,720 Speaker 3: see what's gonna happen next and which kind of insane 478 00:29:11,760 --> 00:29:13,840 Speaker 3: things they are gonna be saying next, And then you 479 00:29:13,920 --> 00:29:18,520 Speaker 3: keep on engaging true comments and sharing, et cetera, making 480 00:29:18,600 --> 00:29:22,240 Speaker 3: them the video even more popular because that's what recommendation 481 00:29:22,320 --> 00:29:24,479 Speaker 3: algorithms are gonna pick up on. They're gonna look at 482 00:29:24,480 --> 00:29:27,400 Speaker 3: all of these engagement signals right, and they're gonna promote 483 00:29:27,440 --> 00:29:30,400 Speaker 3: it more widely, making it go viral. So all of 484 00:29:30,440 --> 00:29:33,080 Speaker 3: this is great for watch time. All of this is 485 00:29:33,120 --> 00:29:36,760 Speaker 3: great for platform payments in the short term. Now the 486 00:29:36,880 --> 00:29:41,240 Speaker 3: question is can you make a living for several years 487 00:29:41,600 --> 00:29:44,280 Speaker 3: based on that type of content? And that's where it 488 00:29:44,320 --> 00:29:47,400 Speaker 3: becomes a bit more complicated, because you see, you can 489 00:29:47,440 --> 00:29:50,320 Speaker 3: shock people once, you can shock people twice, you can 490 00:29:50,360 --> 00:29:53,680 Speaker 3: shock people three times. But then well, likely they're just 491 00:29:53,760 --> 00:29:56,360 Speaker 3: gonna stop watching because gonna be like, oh, well that's 492 00:29:56,440 --> 00:29:59,880 Speaker 3: that person doing the shocking thing again. But you know, avoi, 493 00:30:00,640 --> 00:30:02,480 Speaker 3: I'm not going to click and I'm not going to 494 00:30:02,480 --> 00:30:05,560 Speaker 3: give them that attention. So what I've seen kind of 495 00:30:05,600 --> 00:30:09,880 Speaker 3: in my world is that often What happens is that 496 00:30:10,400 --> 00:30:16,360 Speaker 3: over time, influencers or content creators move from only relying 497 00:30:16,640 --> 00:30:20,120 Speaker 3: on platform payments and views and watch time as a 498 00:30:20,120 --> 00:30:24,280 Speaker 3: way to kind of really make a living to becoming 499 00:30:24,440 --> 00:30:29,760 Speaker 3: more either what I call gurus, so trying to really 500 00:30:29,840 --> 00:30:37,000 Speaker 3: monetize their audience directly through especially donations subscriptions, and so 501 00:30:37,120 --> 00:30:40,719 Speaker 3: that entails a slightly different way of relating to the 502 00:30:40,760 --> 00:30:43,960 Speaker 3: audience and producing content where it's not so much rage 503 00:30:44,040 --> 00:30:47,360 Speaker 3: baits and kind of this kind of negative shocking engagement, 504 00:30:47,760 --> 00:30:52,640 Speaker 3: but it's more framing things as it's us against them, right, 505 00:30:53,560 --> 00:30:57,760 Speaker 3: So basically saying I'm speaking truth to power, I'm saying 506 00:30:57,840 --> 00:31:01,200 Speaker 3: things like it is, and you following me because you 507 00:31:01,400 --> 00:31:04,680 Speaker 3: like that I'm uncensored. You like that I'm saying things 508 00:31:04,800 --> 00:31:07,160 Speaker 3: is the way they should be said. And so if 509 00:31:07,200 --> 00:31:11,040 Speaker 3: you want to support my mission, please subscribe to my channel, 510 00:31:11,720 --> 00:31:15,120 Speaker 3: give me a donation, subscribe to my Patreon, and kind 511 00:31:15,120 --> 00:31:18,280 Speaker 3: of support me financially. But it's a bit of a 512 00:31:18,320 --> 00:31:20,440 Speaker 3: different thing than the rage base, you see what I mean, 513 00:31:20,480 --> 00:31:23,240 Speaker 3: because it's more about loyalty at that point. 514 00:31:23,600 --> 00:31:25,560 Speaker 2: Yeah, now you've studied that. 515 00:31:25,600 --> 00:31:28,760 Speaker 1: You spend a lot of time studying influencers or content 516 00:31:28,840 --> 00:31:31,480 Speaker 1: creators And am I correct that you see there's a 517 00:31:31,520 --> 00:31:33,959 Speaker 1: lot of anxiety in that population. 518 00:31:34,360 --> 00:31:35,120 Speaker 4: Absolutely. 519 00:31:35,240 --> 00:31:39,240 Speaker 3: So that was kind of my next project after journalists. 520 00:31:39,360 --> 00:31:42,840 Speaker 3: And you know the thing with journalists is that they 521 00:31:42,960 --> 00:31:45,200 Speaker 3: themselves could see the writing on the wall and they 522 00:31:45,200 --> 00:31:50,280 Speaker 3: were like, oh, we are all going to become influencers basically, 523 00:31:50,880 --> 00:31:53,000 Speaker 3: and you know, it's something that newsrooms have been doing 524 00:31:53,040 --> 00:31:56,120 Speaker 3: ever since. Basically they show more and more video content 525 00:31:56,360 --> 00:31:59,280 Speaker 3: can of on their homepages, and they send kind of 526 00:31:59,360 --> 00:32:03,880 Speaker 3: journalists to have more like journalist slash influencer profiles in 527 00:32:03,960 --> 00:32:09,680 Speaker 3: order to try to reach young audiences on TikTok for example. Right, So, anyway, 528 00:32:09,760 --> 00:32:12,800 Speaker 3: so just like, oh, so what about content creators? So 529 00:32:12,840 --> 00:32:17,840 Speaker 3: I spent six years studying content creators and doing interviews 530 00:32:17,880 --> 00:32:21,720 Speaker 3: with them, observing them as they were shooting videos and 531 00:32:21,840 --> 00:32:27,960 Speaker 3: kind of producing them, doing interviews with brands, with platform employees, 532 00:32:28,000 --> 00:32:32,520 Speaker 3: and just trying to understand the careers of influencers, right, 533 00:32:32,560 --> 00:32:34,680 Speaker 3: and like, how do you make money as a content 534 00:32:34,760 --> 00:32:37,840 Speaker 3: creator and more importantly, how do you keep on making 535 00:32:37,880 --> 00:32:40,360 Speaker 3: money over time? Because it's one thing to make money 536 00:32:40,360 --> 00:32:42,920 Speaker 3: for one year, it's another thing to make money and 537 00:32:42,920 --> 00:32:47,120 Speaker 3: make a living and sustain yourself for five, seven, ten years, 538 00:32:47,280 --> 00:32:50,400 Speaker 3: and so yeah, what I found basically is this big, 539 00:32:50,560 --> 00:32:53,760 Speaker 3: like one of my first findings, is this big disconnect 540 00:32:53,760 --> 00:32:58,800 Speaker 3: between what people imagine being a content creator is like 541 00:32:59,240 --> 00:33:03,280 Speaker 3: and what the real reality of social media labor looks like. 542 00:33:03,440 --> 00:33:07,920 Speaker 3: So almost everybody at this point thinks that being a 543 00:33:07,920 --> 00:33:12,160 Speaker 3: content creator sounds like the most fun job in the world. 544 00:33:12,920 --> 00:33:16,120 Speaker 3: In a recent survey from twenty twenty three, more than 545 00:33:16,160 --> 00:33:19,360 Speaker 3: fifty percent of Americans said that they would like to 546 00:33:19,400 --> 00:33:24,080 Speaker 3: become content creators. So this is a massive kind of 547 00:33:24,320 --> 00:33:27,520 Speaker 3: pull on the collective imagination. Right, We're all like, oh 548 00:33:27,560 --> 00:33:30,480 Speaker 3: my gosh, they're having so much fun. They get to 549 00:33:30,520 --> 00:33:33,320 Speaker 3: follow their passions, they get to have an amazing life, 550 00:33:33,320 --> 00:33:36,000 Speaker 3: to talk about what they care about. They kind of 551 00:33:36,040 --> 00:33:38,920 Speaker 3: look great, right, They're just having so much fun. They're 552 00:33:38,920 --> 00:33:41,120 Speaker 3: hanging out with their friends. I want to do that, 553 00:33:41,280 --> 00:33:44,880 Speaker 3: and I want to have the money, the glory, the fame, 554 00:33:45,200 --> 00:33:48,760 Speaker 3: the luxurious lifestyle that comes with it. And so what 555 00:33:48,800 --> 00:33:51,760 Speaker 3: you see is more and more people entering into social 556 00:33:51,760 --> 00:33:55,400 Speaker 3: media creation and trying to become an entrepreneur right and 557 00:33:55,440 --> 00:33:57,400 Speaker 3: saying I want to be my own boss, I want 558 00:33:57,440 --> 00:33:59,840 Speaker 3: to be a content creator, and I want to follow 559 00:34:00,040 --> 00:34:02,480 Speaker 3: and of my passion took about the topics I'm truly 560 00:34:02,480 --> 00:34:06,520 Speaker 3: interested in, and that my day job is not recognizing. Okay, 561 00:34:06,760 --> 00:34:10,160 Speaker 3: so big pool, a big funnel that kind of brings 562 00:34:10,200 --> 00:34:12,880 Speaker 3: in lots and lots of people to social media creation. 563 00:34:14,040 --> 00:34:17,560 Speaker 3: What happens, though, is that it turns out making a 564 00:34:17,600 --> 00:34:21,640 Speaker 3: living as a content creator is very hard. And why 565 00:34:21,719 --> 00:34:24,439 Speaker 3: is it very hard? Well, mostly again because of social 566 00:34:24,520 --> 00:34:28,319 Speaker 3: media algorithms and the fact that it's really hard to 567 00:34:28,400 --> 00:34:32,799 Speaker 3: figure out what people want to watch and what platforms 568 00:34:32,800 --> 00:34:36,600 Speaker 3: are rewarding in terms of content, right, and what's getting promoted, 569 00:34:37,080 --> 00:34:41,560 Speaker 3: especially true recommendation algorithms and true feed algorithms that kind 570 00:34:41,600 --> 00:34:43,799 Speaker 3: of gonna, you know, are going to present you with 571 00:34:43,960 --> 00:34:46,759 Speaker 3: the most kind of viral and popular videos of the day. 572 00:34:47,239 --> 00:34:50,120 Speaker 3: And so for content creators, what that means is that 573 00:34:50,280 --> 00:34:53,640 Speaker 3: very often they're like, oh, well, you know, I'm going 574 00:34:53,719 --> 00:34:55,799 Speaker 3: to try, right, And so they try. And let's say 575 00:34:55,840 --> 00:34:58,080 Speaker 3: they get a bit of success at the beginning, right, 576 00:34:58,120 --> 00:35:00,440 Speaker 3: and they have a couple of videos that go viral, 577 00:35:00,920 --> 00:35:03,480 Speaker 3: and let's say they start kind of getting some followers, 578 00:35:03,480 --> 00:35:05,960 Speaker 3: and so that looks pretty good, right, And let's say 579 00:35:06,000 --> 00:35:08,239 Speaker 3: is they have brands that start coming to you and 580 00:35:08,280 --> 00:35:10,160 Speaker 3: are like, oh, do you want to work with us, Like, 581 00:35:10,360 --> 00:35:14,200 Speaker 3: we'll send you sunglasses, you know, and eventually a little 582 00:35:14,239 --> 00:35:17,480 Speaker 3: bit of payment. But soon what happens is that, you know, 583 00:35:17,560 --> 00:35:22,279 Speaker 3: creators realize that it's a twenty four to seven kind 584 00:35:22,280 --> 00:35:25,680 Speaker 3: of job in the sense of in order for some 585 00:35:25,719 --> 00:35:28,960 Speaker 3: of your videos to go viral, in order for your 586 00:35:29,080 --> 00:35:32,319 Speaker 3: number of subscribers and followers to kind of keep increasing, 587 00:35:32,360 --> 00:35:34,600 Speaker 3: which is what brands want to see. They want to 588 00:35:34,640 --> 00:35:37,480 Speaker 3: be associated with accounts that are going up, not with 589 00:35:37,560 --> 00:35:40,600 Speaker 3: accounts that are going down in terms of audience measurements. 590 00:35:40,719 --> 00:35:42,799 Speaker 4: Right, you have to. 591 00:35:42,840 --> 00:35:46,960 Speaker 3: Post videos all the time because most of these videos 592 00:35:47,000 --> 00:35:50,040 Speaker 3: will not go viral, most of them will not find 593 00:35:50,040 --> 00:35:53,080 Speaker 3: their audience, right. But you are kind of a production 594 00:35:53,280 --> 00:35:56,080 Speaker 3: company of one person, and so that means that you 595 00:35:56,160 --> 00:35:57,319 Speaker 3: have to post every day. 596 00:35:57,560 --> 00:35:58,759 Speaker 4: And so again, what. 597 00:35:58,719 --> 00:36:02,839 Speaker 3: I see in my interviews is creator saying I made 598 00:36:02,840 --> 00:36:07,120 Speaker 3: myself sick. I try to post every day, twice a day, 599 00:36:07,600 --> 00:36:09,919 Speaker 3: just to keep that rhythm. I was on my own 600 00:36:10,120 --> 00:36:13,200 Speaker 3: in my bedroom and it just became too much. I 601 00:36:13,280 --> 00:36:15,239 Speaker 3: just couldn't deal with it. So that's the first thing. 602 00:36:15,440 --> 00:36:18,120 Speaker 3: It's a relentless rhysm. It's a rhythm that would be 603 00:36:18,239 --> 00:36:22,200 Speaker 3: very hard for a TV network or like a newsroom 604 00:36:22,320 --> 00:36:24,760 Speaker 3: to kind of keep doing. And we're talking here about 605 00:36:24,760 --> 00:36:27,399 Speaker 3: people who are alone. They're like a company of one 606 00:36:27,840 --> 00:36:31,360 Speaker 3: in their bedroom, right and just pushing themselves and saying, like, 607 00:36:31,440 --> 00:36:33,319 Speaker 3: you know, I'm an entrepreneur, I. 608 00:36:33,320 --> 00:36:35,520 Speaker 4: Have to make it work, right. So that's the first thing. 609 00:36:36,239 --> 00:36:38,759 Speaker 3: The second thing that happens is that as they get 610 00:36:38,880 --> 00:36:42,440 Speaker 3: kind of more popular and the size of their following 611 00:36:42,640 --> 00:36:47,680 Speaker 3: kind of increases, most of them start receiving hate comments, 612 00:36:47,800 --> 00:36:50,640 Speaker 3: right and start kind of facing the darker side of 613 00:36:50,680 --> 00:36:53,600 Speaker 3: the internet. So at first they're like, oh, I love 614 00:36:53,640 --> 00:36:56,879 Speaker 3: my community, I love my followers. We share the same 615 00:36:56,920 --> 00:37:00,880 Speaker 3: passion for X topic, right, regardless whether the topic is 616 00:37:00,880 --> 00:37:04,839 Speaker 3: like beauty or K pop or you know, DYI kind 617 00:37:04,880 --> 00:37:09,800 Speaker 3: of you know, reroof your house. I mean, it doesn't matter. 618 00:37:09,840 --> 00:37:11,880 Speaker 3: And they're just like, yeah, there are such good people, 619 00:37:12,440 --> 00:37:15,080 Speaker 3: you know, We've become really close. I love them, they 620 00:37:15,080 --> 00:37:17,919 Speaker 3: love me. We really get each other in this deep, 621 00:37:18,000 --> 00:37:18,839 Speaker 3: authentic way. 622 00:37:18,960 --> 00:37:19,200 Speaker 4: Right. 623 00:37:19,840 --> 00:37:22,640 Speaker 3: But as your fame grows and as you start to 624 00:37:22,640 --> 00:37:26,560 Speaker 3: make more and more money from social media production, suddenly 625 00:37:26,880 --> 00:37:31,080 Speaker 3: something switches in the relationship with your followers. Namely, is 626 00:37:31,080 --> 00:37:33,600 Speaker 3: that First, you can't keep track of all of them, 627 00:37:33,840 --> 00:37:37,839 Speaker 3: so it becomes more of a faceless mass of people, right, 628 00:37:38,120 --> 00:37:40,839 Speaker 3: and you know still a few of them from the beginnings, right, 629 00:37:40,920 --> 00:37:43,640 Speaker 3: but most of them have just become numbers. That's the 630 00:37:43,640 --> 00:37:48,960 Speaker 3: first thing. And second, negative feedback starts coming in. Typically, 631 00:37:49,400 --> 00:37:53,040 Speaker 3: you're gonna get kind of hate comments, you're gonna get destreats, 632 00:37:53,440 --> 00:37:57,120 Speaker 3: You're gonna get themeaning comments about your physical appearance or 633 00:37:57,120 --> 00:37:59,560 Speaker 3: your mental health or whatever it is that you know 634 00:38:00,040 --> 00:38:02,959 Speaker 3: comes up in your videos. You're going to get stockers, 635 00:38:03,120 --> 00:38:06,360 Speaker 3: right who show up kind of in your hometown and 636 00:38:07,000 --> 00:38:09,759 Speaker 3: perhaps show up at your doorstep. And suddenly you're just 637 00:38:09,880 --> 00:38:13,600 Speaker 3: like wait, like wow, this is really taking a toll 638 00:38:13,640 --> 00:38:16,400 Speaker 3: on me, because day after day you get both the 639 00:38:16,440 --> 00:38:19,120 Speaker 3: good parts of the Internet and of that kind of 640 00:38:19,120 --> 00:38:22,760 Speaker 3: public presence, but also the negative parts and the relentless 641 00:38:22,840 --> 00:38:28,120 Speaker 3: like trolling, harassing, insulting, and everything that comes with it, 642 00:38:28,320 --> 00:38:31,360 Speaker 3: and that takes such a heavy toll on the mental 643 00:38:31,400 --> 00:38:32,440 Speaker 3: health of creators. 644 00:38:32,760 --> 00:38:35,640 Speaker 4: That together with the pressure to publish all the time. 645 00:38:50,600 --> 00:38:53,440 Speaker 1: And from your point of view, the change in the algorithms. 646 00:38:53,480 --> 00:38:55,759 Speaker 1: I'm seeing this on X all the time lately, that 647 00:38:56,160 --> 00:38:58,799 Speaker 1: creators are complaining, Hey, I was doing so well and 648 00:38:58,800 --> 00:39:01,760 Speaker 1: they just change the algorithm. Now suddenly I'm getting shadow 649 00:39:01,800 --> 00:39:03,560 Speaker 1: band or whatever term they're using for it. 650 00:39:03,880 --> 00:39:06,640 Speaker 3: Yeah, so I have a whole thing about that. I mean, 651 00:39:06,719 --> 00:39:10,480 Speaker 3: so basically, creators talk about the algorithm kind of all 652 00:39:10,520 --> 00:39:12,759 Speaker 3: the time, and it's really interesting because it's always the 653 00:39:12,920 --> 00:39:17,600 Speaker 3: algorithm singular. It's not like all the computational procedures of 654 00:39:17,680 --> 00:39:20,480 Speaker 3: social media platforms, of which are many, right, because you 655 00:39:20,560 --> 00:39:27,000 Speaker 3: have feed algorithms, you have recommendation algorithms, you have demonetization algorithms. 656 00:39:27,040 --> 00:39:32,080 Speaker 3: So these are basically algorithms that if your video is 657 00:39:32,120 --> 00:39:36,680 Speaker 3: deemed to be not family friendly or edgy, or going 658 00:39:36,880 --> 00:39:39,160 Speaker 3: kind of being kind of a bit too close to 659 00:39:39,400 --> 00:39:42,200 Speaker 3: kind of the edge of community guidelines in a range 660 00:39:42,200 --> 00:39:45,120 Speaker 3: of way, you're going to get demonetized, which means that 661 00:39:45,200 --> 00:39:49,320 Speaker 3: you won't get any money from the ads getting served 662 00:39:49,600 --> 00:39:52,799 Speaker 3: on the videos. Right, So basically for content creators that 663 00:39:52,880 --> 00:39:54,839 Speaker 3: means that they're not making money from that video, which 664 00:39:54,880 --> 00:39:57,440 Speaker 3: is a big problem for them. And so that's like 665 00:39:57,480 --> 00:40:02,040 Speaker 3: demonetization algorithms. And then you content moderation algorithms that are 666 00:40:02,120 --> 00:40:05,040 Speaker 3: you know, along the same lines, but with more serious 667 00:40:05,040 --> 00:40:07,960 Speaker 3: sanctions such as getting banned, for example, from a given 668 00:40:07,960 --> 00:40:11,360 Speaker 3: platform because your content goes against the community guidelines of 669 00:40:11,400 --> 00:40:14,520 Speaker 3: the platform. All of these algorithms are kind of changing 670 00:40:14,600 --> 00:40:17,799 Speaker 3: all the time they are opake. There is no announcement 671 00:40:17,880 --> 00:40:21,719 Speaker 3: of what's happening, right, and so creators are always kind 672 00:40:21,760 --> 00:40:24,360 Speaker 3: of like basically putting their finger in the air and 673 00:40:24,400 --> 00:40:28,560 Speaker 3: trying to see what does the algorithm want at any 674 00:40:28,600 --> 00:40:32,759 Speaker 3: given point in time, right, and trying to intuit what 675 00:40:32,840 --> 00:40:35,759 Speaker 3: the algorithm is looking for. And so that's already kind 676 00:40:35,800 --> 00:40:38,640 Speaker 3: of quite a thing there. But then what I kind 677 00:40:38,640 --> 00:40:41,319 Speaker 3: of argue kind of in my book is that in 678 00:40:41,360 --> 00:40:47,879 Speaker 3: a way, the algorithm becomes a shortcut for a more 679 00:40:47,960 --> 00:40:53,640 Speaker 3: complex set of actors that you know, influencers and content 680 00:40:53,680 --> 00:40:57,319 Speaker 3: creators prefer not to think too closely about. So one 681 00:40:57,360 --> 00:41:01,600 Speaker 3: things that content creators do is that they pomorphize the algorithm. 682 00:41:01,680 --> 00:41:04,640 Speaker 3: So they keep on saying the algorithm is stupid, the 683 00:41:04,719 --> 00:41:08,440 Speaker 3: algorithm is silly, the algorithm doesn't like me, or the 684 00:41:08,520 --> 00:41:12,320 Speaker 3: algorithm really likes them. They got really friendly and close 685 00:41:12,440 --> 00:41:14,560 Speaker 3: with the algorithm, right. So all of these ways of 686 00:41:14,640 --> 00:41:20,080 Speaker 3: projecting human characteristics onto computational procedures that are obviously and 687 00:41:20,080 --> 00:41:21,799 Speaker 3: to the best of our knowledge at this point like 688 00:41:21,920 --> 00:41:23,800 Speaker 3: not sentient, you know what I mean, they do not 689 00:41:23,920 --> 00:41:28,160 Speaker 3: have emotions. But what I argue is that this kind 690 00:41:28,160 --> 00:41:32,880 Speaker 3: of process of anthropomorphism is really because so who is 691 00:41:32,920 --> 00:41:39,160 Speaker 3: behind the algorithm? Social media companies, right, the alphabets, the meta, 692 00:41:39,960 --> 00:41:45,680 Speaker 3: the tiktoks of the world right by dense Now who 693 00:41:45,719 --> 00:41:47,200 Speaker 3: else is behind the algorithm? 694 00:41:47,760 --> 00:41:48,400 Speaker 4: The audience? 695 00:41:49,040 --> 00:41:51,640 Speaker 3: Right, I mean basically the algorithm just picking up on 696 00:41:51,719 --> 00:41:56,759 Speaker 3: audience signals and now the algorithm, you know, for creators, 697 00:41:56,920 --> 00:42:00,480 Speaker 3: blaming the algorithm for everything that goes wrong is a 698 00:42:00,520 --> 00:42:04,480 Speaker 3: way to avoid blaming social media companies, which very often 699 00:42:04,520 --> 00:42:08,080 Speaker 3: as the one paying them through partner programs, right, and 700 00:42:08,280 --> 00:42:12,239 Speaker 3: audiences which also as the one supporting them through their 701 00:42:12,239 --> 00:42:13,480 Speaker 3: clicks and their engagement. 702 00:42:13,600 --> 00:42:13,839 Speaker 4: Right. 703 00:42:14,080 --> 00:42:17,680 Speaker 3: So the algorithm is kind of a convenient scapegoat. And 704 00:42:17,719 --> 00:42:20,920 Speaker 3: again not to say is that it's not unpredictable, opaque, 705 00:42:20,920 --> 00:42:22,640 Speaker 3: and all of these things, But it's kind of a 706 00:42:22,680 --> 00:42:26,960 Speaker 3: convenient kind of scapegoat for these broader kind of forces 707 00:42:26,960 --> 00:42:30,719 Speaker 3: that really are responsible for the fortunes or lack of 708 00:42:30,760 --> 00:42:32,520 Speaker 3: fortunes of content creators. 709 00:42:33,120 --> 00:42:34,759 Speaker 1: By the way, just from a neuroscience point of view, 710 00:42:34,800 --> 00:42:36,880 Speaker 1: we always have to do this with systems that are 711 00:42:36,920 --> 00:42:41,239 Speaker 1: sufficiently complex, we reduce them to a person because that's 712 00:42:41,280 --> 00:42:43,239 Speaker 1: what we're evolved to do, is understand other people. 713 00:42:43,320 --> 00:42:46,280 Speaker 2: Yeah, try exactly, Yeah, yeah, exactly, So it's no surprise 714 00:42:46,360 --> 00:42:47,080 Speaker 2: that people do that. 715 00:42:47,920 --> 00:42:50,640 Speaker 1: I want to return to rage bait for a moment 716 00:42:50,719 --> 00:42:52,920 Speaker 1: because one of the things I've been so interested in, 717 00:42:53,000 --> 00:42:54,800 Speaker 1: and this is on a lot of my podcast, is 718 00:42:54,840 --> 00:42:57,040 Speaker 1: about polarization and in groups and out groups and so on. 719 00:42:57,200 --> 00:43:00,279 Speaker 1: And one thing that's hard not to notice is what 720 00:43:00,320 --> 00:43:04,040 Speaker 1: I've been calling lately the fringe amplification effect, which is 721 00:43:05,360 --> 00:43:08,560 Speaker 1: somebody on one side of the political spectrum makes a 722 00:43:08,680 --> 00:43:12,160 Speaker 1: totally rage baby video that's just so extreme in their 723 00:43:12,200 --> 00:43:15,320 Speaker 1: political view on it, and then the other side says, 724 00:43:15,760 --> 00:43:19,200 Speaker 1: look what the other side is doing, and they stitch 725 00:43:19,280 --> 00:43:21,240 Speaker 1: in that video and everyone. 726 00:43:20,920 --> 00:43:21,920 Speaker 2: Gets to see that. 727 00:43:22,080 --> 00:43:25,360 Speaker 1: So the videos that you know, one side gets to 728 00:43:25,400 --> 00:43:28,520 Speaker 1: see of the other is the most extreme. Yeah, and 729 00:43:28,520 --> 00:43:31,279 Speaker 1: that seems to be a real problem because that's driving polarization. 730 00:43:31,400 --> 00:43:33,240 Speaker 4: But again, so I completely agree. 731 00:43:33,280 --> 00:43:35,200 Speaker 3: I mean, I think so the way I kind of 732 00:43:35,280 --> 00:43:39,000 Speaker 3: analyze this that all of these stems from the economic 733 00:43:39,040 --> 00:43:42,719 Speaker 3: incentives of content creators. And so again we think a 734 00:43:42,760 --> 00:43:45,839 Speaker 3: lot of it in terms of like political polarizations, right, 735 00:43:45,920 --> 00:43:51,319 Speaker 3: and kind of deeply held beliefs, right about politics, all 736 00:43:51,360 --> 00:43:54,080 Speaker 3: about religion, all about immigration, you know, you name it. 737 00:43:54,600 --> 00:43:56,239 Speaker 3: But I guess I mean, I guess I'm a bit 738 00:43:56,280 --> 00:43:58,360 Speaker 3: more cynical kind of in a way. And that's like 739 00:43:58,400 --> 00:44:02,520 Speaker 3: the sociologist in me. I'm like, sure. But that's also 740 00:44:02,560 --> 00:44:07,120 Speaker 3: because platforms have put in place economic incentives that basically 741 00:44:07,200 --> 00:44:11,280 Speaker 3: encourage content creators to produce this kind of polarizing content. 742 00:44:11,400 --> 00:44:15,879 Speaker 3: Again because of like the logic of engagement. So if 743 00:44:15,920 --> 00:44:19,360 Speaker 3: you want people to engage with your content, the tendency 744 00:44:19,440 --> 00:44:21,960 Speaker 3: and I've seen that in my interviews over and over 745 00:44:22,040 --> 00:44:25,560 Speaker 3: and over again. Creators start by saying, Okay, I have 746 00:44:25,600 --> 00:44:29,920 Speaker 3: one example. One of my case studies was vegan creators. Okay, 747 00:44:30,040 --> 00:44:31,520 Speaker 3: you'll tell me vigan creators. 748 00:44:31,920 --> 00:44:32,480 Speaker 4: How nice. 749 00:44:32,960 --> 00:44:35,880 Speaker 3: Right, They're going to be talking about plant based eating. 750 00:44:36,480 --> 00:44:39,960 Speaker 3: It's good for the planet, it's good for the animals, 751 00:44:40,239 --> 00:44:43,239 Speaker 3: it's good for your health, you know, with kind of 752 00:44:43,280 --> 00:44:47,120 Speaker 3: some precautions around it. So what could go wrong? How 753 00:44:47,160 --> 00:44:48,680 Speaker 3: could that lead to polarization? 754 00:44:49,239 --> 00:44:52,040 Speaker 4: Well, it turns out that, you know, almost. 755 00:44:51,600 --> 00:44:54,520 Speaker 3: All the creators I talked about were like, well, okay, 756 00:44:54,520 --> 00:44:58,080 Speaker 3: so there are a couple of really outrageous personalities that 757 00:44:58,120 --> 00:45:04,520 Speaker 3: are extremely rage baity within the vegan kind of influencer world, 758 00:45:04,640 --> 00:45:09,120 Speaker 3: and that basically just like attack other creators and other 759 00:45:09,480 --> 00:45:13,200 Speaker 3: kind of people for how they are doing veganism wrong, right, 760 00:45:13,320 --> 00:45:17,399 Speaker 3: so extremely kind of contentious, kind of like you're doing 761 00:45:17,400 --> 00:45:19,799 Speaker 3: it wrong, this is not the right way of being 762 00:45:19,880 --> 00:45:23,200 Speaker 3: kind of a vegan. What they also see is like 763 00:45:23,320 --> 00:45:27,560 Speaker 3: the rise of extremely restrictive diets that become more and 764 00:45:27,680 --> 00:45:32,560 Speaker 3: more niche, so typically FRUITIVL diets where you only eat fruits, 765 00:45:32,719 --> 00:45:36,960 Speaker 3: or raw vegan diets where you only eat row fruits 766 00:45:36,960 --> 00:45:39,520 Speaker 3: and veggies, or you know, things like that that become 767 00:45:39,640 --> 00:45:43,160 Speaker 3: like increasingly niche and kind of extreme right. And what 768 00:45:43,360 --> 00:45:46,160 Speaker 3: like all of my content creators were saying is that, 769 00:45:46,440 --> 00:45:50,160 Speaker 3: And often I will add, the creators that are the 770 00:45:50,200 --> 00:45:54,200 Speaker 3: most kind of outrageous also start kind of verging into 771 00:45:55,120 --> 00:46:00,680 Speaker 3: conspiracy theories Q and non you know at the time 772 00:46:00,719 --> 00:46:03,239 Speaker 3: Pizza Gates, I mean, you know, things where it's like, 773 00:46:03,280 --> 00:46:06,719 Speaker 3: you know, really blaming the system for everything that goes 774 00:46:06,760 --> 00:46:09,000 Speaker 3: wrong and saying like, oh, you should live off grid 775 00:46:09,480 --> 00:46:12,160 Speaker 3: and be kind of on this extremely restrictive kind of 776 00:46:12,200 --> 00:46:16,000 Speaker 3: vegan diet and everything kind of going together. And what 777 00:46:16,320 --> 00:46:19,880 Speaker 3: like my you know, my more moderate interview is were saying, 778 00:46:19,960 --> 00:46:23,759 Speaker 3: is like, listen, what you realize is that as soon 779 00:46:23,920 --> 00:46:28,640 Speaker 3: as I start covering or reacting or responding or stitching 780 00:46:29,040 --> 00:46:32,359 Speaker 3: one of these more extreme influencers and what they say, 781 00:46:33,000 --> 00:46:36,440 Speaker 3: my number of views and my watch time go way 782 00:46:36,719 --> 00:46:41,040 Speaker 3: up because basically everybody wants to read that, Zaka, You're 783 00:46:41,080 --> 00:46:44,960 Speaker 3: going to take down that outrageous influenza. Yes, please, like 784 00:46:45,040 --> 00:46:47,120 Speaker 3: you know, I'm going to watch it. And so what 785 00:46:47,239 --> 00:46:50,040 Speaker 3: they were saying my more moderate kind of you know, 786 00:46:50,120 --> 00:46:54,280 Speaker 3: vegan creators, is that it's really a slippery slope towards 787 00:46:54,360 --> 00:46:59,840 Speaker 3: more aggressive, more incendiary, more extreme kind of content. And 788 00:47:00,040 --> 00:47:02,120 Speaker 3: even if you start kind of somewhere in the middle, 789 00:47:02,800 --> 00:47:06,400 Speaker 3: after months and months of producing videos and seeing what 790 00:47:06,520 --> 00:47:10,960 Speaker 3: performs well with the algorithm and audiences and kind of 791 00:47:11,040 --> 00:47:14,279 Speaker 3: you know, social media platforms, you kind of go more 792 00:47:14,320 --> 00:47:18,000 Speaker 3: towards polarized content. It's just kind of what the system 793 00:47:18,080 --> 00:47:21,600 Speaker 3: is designed to kind of reward you for. And so, 794 00:47:22,000 --> 00:47:24,319 Speaker 3: you know, we've had social media now for ten to 795 00:47:24,400 --> 00:47:27,279 Speaker 3: fifteen years, and what you see is this kind of 796 00:47:27,320 --> 00:47:30,040 Speaker 3: war of all against all. But that's in part because 797 00:47:30,080 --> 00:47:32,040 Speaker 3: of these economic incentives you know. 798 00:47:32,680 --> 00:47:33,360 Speaker 2: Let me ask you this. 799 00:47:33,560 --> 00:47:36,080 Speaker 1: So in the world of let's say, stand up comedy, 800 00:47:36,880 --> 00:47:39,760 Speaker 1: young comedians find that if they do a lot of cussing, 801 00:47:39,880 --> 00:47:42,160 Speaker 1: that gets them a lot of attention. But then you 802 00:47:42,200 --> 00:47:45,120 Speaker 1: have comedians like let's say Jerry Seinfeld who never cussed 803 00:47:45,680 --> 00:47:49,359 Speaker 1: and just kept slow and steady and did did his 804 00:47:49,400 --> 00:47:53,400 Speaker 1: thing without blue material and got really successful. What is 805 00:47:53,400 --> 00:47:55,760 Speaker 1: is there an equivalent in the algorithmic world. 806 00:47:56,040 --> 00:48:00,160 Speaker 3: So it's really interesting because that's that's a very good point, right, 807 00:48:00,239 --> 00:48:02,480 Speaker 3: And I mean I think that in general, you have 808 00:48:02,560 --> 00:48:05,160 Speaker 3: this moderating force a bit like my journalist at the time, 809 00:48:05,239 --> 00:48:07,400 Speaker 3: you know what I mean that even as some of 810 00:48:07,440 --> 00:48:10,760 Speaker 3: them are going the road of clickbait, there was also 811 00:48:10,880 --> 00:48:13,719 Speaker 3: a significant kind of pushback, you know, saying this is 812 00:48:13,760 --> 00:48:16,680 Speaker 3: not who we are, you know, and this is not 813 00:48:16,719 --> 00:48:18,520 Speaker 3: what we care about. And at the end of the day, 814 00:48:18,840 --> 00:48:21,720 Speaker 3: I became a journalist for different reasons, not to cover 815 00:48:22,040 --> 00:48:25,120 Speaker 3: like you know, X scandal, like this kind of tableauid 816 00:48:25,160 --> 00:48:30,360 Speaker 3: manner day after day with influences. What I do find, 817 00:48:30,400 --> 00:48:32,680 Speaker 3: and it is kind of interesting because it's you know, 818 00:48:32,960 --> 00:48:36,680 Speaker 3: slightly different, is that there is a moderating force, but 819 00:48:36,800 --> 00:48:40,960 Speaker 3: it's not a neutral one. The moderating force is brands 820 00:48:41,239 --> 00:48:45,000 Speaker 3: and sponsored content. So, as an influencer, how do you 821 00:48:45,040 --> 00:48:47,520 Speaker 3: make money? Either you do platform. 822 00:48:47,200 --> 00:48:49,279 Speaker 4: Payments, right, and you receive money. 823 00:48:49,000 --> 00:48:54,120 Speaker 3: Directly from meta or YouTube or TikTok based on the 824 00:48:54,239 --> 00:48:56,880 Speaker 3: number of views and the watch times that your videos get. 825 00:48:57,480 --> 00:49:00,759 Speaker 3: Oh the kind of actually the main way which influencers 826 00:49:00,800 --> 00:49:06,400 Speaker 3: make money is by contracting with brands to promote whatever 827 00:49:07,080 --> 00:49:10,200 Speaker 3: the brand is doing and kind of promoting it kind 828 00:49:10,200 --> 00:49:14,399 Speaker 3: of in their videos, in their posts to their followers. Now, 829 00:49:14,480 --> 00:49:17,759 Speaker 3: what's interesting about that? And you know, for anyone who 830 00:49:17,880 --> 00:49:21,160 Speaker 3: kind of knows a bit about advertising, it's not that surprising. 831 00:49:21,280 --> 00:49:29,239 Speaker 3: But brands hate polarization, They hate scandals because they want 832 00:49:29,280 --> 00:49:33,680 Speaker 3: to appeal to the wider possible customer base that's out there, 833 00:49:34,080 --> 00:49:37,720 Speaker 3: and they do not want to be associated with things 834 00:49:37,760 --> 00:49:41,680 Speaker 3: that could raise red flags among their customers or for 835 00:49:41,800 --> 00:49:45,239 Speaker 3: that matter, amongst their boards or you know kind of 836 00:49:45,280 --> 00:49:47,280 Speaker 3: financial kind of stakeholders. 837 00:49:47,360 --> 00:49:47,600 Speaker 4: Right. 838 00:49:48,360 --> 00:49:51,360 Speaker 3: And so what I find is that over time you 839 00:49:51,480 --> 00:49:56,360 Speaker 3: kind of see two different profiles of content creators that emerge. 840 00:49:56,400 --> 00:49:59,840 Speaker 3: You have the ones who really depend on virality, and 841 00:50:00,040 --> 00:50:02,200 Speaker 3: they are gonna go more and more extreme. It's really 842 00:50:02,200 --> 00:50:05,480 Speaker 3: hard to fight against that. Again, there are some exceptions, 843 00:50:06,160 --> 00:50:10,320 Speaker 3: but it's just really hard to fight against it because 844 00:50:10,360 --> 00:50:14,359 Speaker 3: everything pushes you in that direction. It's like not nuge 845 00:50:14,360 --> 00:50:17,960 Speaker 3: after nudge. But you have a second category where they 846 00:50:18,000 --> 00:50:22,640 Speaker 3: go mostly towards branded content, right, and for people who 847 00:50:22,640 --> 00:50:26,320 Speaker 3: go more the route of sponsored content and working with brands, 848 00:50:26,680 --> 00:50:35,400 Speaker 3: actually avoiding any whiff of you know, scandal, harassment, polarization, 849 00:50:35,880 --> 00:50:39,800 Speaker 3: anything and of outrageous is really important because otherwise brands 850 00:50:39,840 --> 00:50:42,680 Speaker 3: are gonna stop working with them and they're gonna lose revenues. 851 00:50:42,920 --> 00:50:45,000 Speaker 3: So you do have these different polls there. 852 00:50:45,719 --> 00:50:48,239 Speaker 1: So is that enough of a force that we can 853 00:50:48,320 --> 00:50:52,760 Speaker 1: have hope that we won't just sink completely into clickbait 854 00:50:52,880 --> 00:50:56,520 Speaker 1: rage bait world? Or are there things that social media 855 00:50:56,560 --> 00:51:00,200 Speaker 1: companies can do, slash should do, slash might do someday 856 00:51:00,760 --> 00:51:02,200 Speaker 1: that would change this? 857 00:51:02,200 --> 00:51:03,560 Speaker 4: This is an excellent question. 858 00:51:03,800 --> 00:51:10,960 Speaker 3: So I think brands in themselves are not enough for 859 00:51:11,040 --> 00:51:16,440 Speaker 3: two reasons. First, because you know, especially over the past 860 00:51:16,520 --> 00:51:21,399 Speaker 3: year and a half, brands themselves have become politically polarized. Right, 861 00:51:21,520 --> 00:51:25,719 Speaker 3: So you have big companies taking sides on one side 862 00:51:25,800 --> 00:51:28,680 Speaker 3: or the other, and especially I mean I'm thinking on 863 00:51:28,760 --> 00:51:31,360 Speaker 3: the kind of conservative side. The number of brands have 864 00:51:31,440 --> 00:51:37,000 Speaker 3: aligned with you know, extremely misogenistic, anti immigrant and violent 865 00:51:37,560 --> 00:51:40,359 Speaker 3: forms of content on social media and actually take pride 866 00:51:40,400 --> 00:51:42,080 Speaker 3: in it because they're like, these are going to be 867 00:51:42,120 --> 00:51:43,480 Speaker 3: our markets, right. 868 00:51:43,640 --> 00:51:45,680 Speaker 2: Like, which brands can so right now. 869 00:51:45,640 --> 00:51:47,640 Speaker 3: Actually I forget them, and I remember there is a 870 00:51:47,640 --> 00:51:51,359 Speaker 3: coffee brand that's like specifically marketed like you know, far right, 871 00:51:51,960 --> 00:51:55,680 Speaker 3: and they're basically like, yeah, the more extreme the better. 872 00:51:56,200 --> 00:51:57,920 Speaker 4: This is where we want to advertise. 873 00:51:57,960 --> 00:51:59,600 Speaker 3: This is the audience we want to get, and so 874 00:51:59,600 --> 00:52:01,680 Speaker 3: they're kind of finding a bit of a niche market there. 875 00:52:01,800 --> 00:52:05,560 Speaker 1: I mean, presumably there's brands on the lab Yeah. 876 00:52:05,040 --> 00:52:08,200 Speaker 3: Definitely obviously like brands on the left to our costco right, 877 00:52:08,360 --> 00:52:11,160 Speaker 3: like also kind of becoming more aligned with kind of 878 00:52:11,960 --> 00:52:15,400 Speaker 3: you know, liberal kind of attitudes kind of in recent years, 879 00:52:15,400 --> 00:52:17,520 Speaker 3: so you know, you do have you do see kind 880 00:52:17,520 --> 00:52:21,480 Speaker 3: of that the transformations of politics, in part with social media, 881 00:52:21,800 --> 00:52:25,600 Speaker 3: are also affecting brick and mortar kind of companies, right 882 00:52:25,680 --> 00:52:28,520 Speaker 3: that themselves kind of end up having to pick aside 883 00:52:28,520 --> 00:52:30,799 Speaker 3: a bit more. So that's not so good, right in 884 00:52:30,880 --> 00:52:34,000 Speaker 3: terms of reducing polarization. If anything, it might be that 885 00:52:34,120 --> 00:52:35,920 Speaker 3: like this is the future we're moving towards. 886 00:52:35,960 --> 00:52:37,360 Speaker 4: So that's the first thing, become. 887 00:52:37,160 --> 00:52:39,600 Speaker 2: Part of your identity to drink this coffee. 888 00:52:39,880 --> 00:52:42,719 Speaker 3: I'll go to that supermarket, right, So that's kind of 889 00:52:43,200 --> 00:52:47,440 Speaker 3: that's kind of one one way, So that's not perfect. 890 00:52:47,480 --> 00:52:50,440 Speaker 3: The second thing with brands is that you know, again 891 00:52:50,840 --> 00:52:55,919 Speaker 3: brands hate politics in general, right, most brands hate politics. 892 00:52:55,960 --> 00:53:01,400 Speaker 3: And do we want content creators who i are incredibly 893 00:53:01,400 --> 00:53:08,040 Speaker 3: incendiary and politicized or are not politicized at all, you 894 00:53:08,080 --> 00:53:10,120 Speaker 3: know what I mean? You also probably want a healthy 895 00:53:10,200 --> 00:53:14,759 Speaker 3: middle of people who are voicing kind of political questions 896 00:53:14,800 --> 00:53:17,759 Speaker 3: and concerns and kind of hashing it out kind of 897 00:53:17,800 --> 00:53:20,799 Speaker 3: on social media in a respectful and civic way. But 898 00:53:20,880 --> 00:53:23,400 Speaker 3: this is not what brands want. Most brands again, do 899 00:53:23,520 --> 00:53:27,279 Speaker 3: not really want that. So it's not perfect. I think 900 00:53:27,360 --> 00:53:29,879 Speaker 3: for me, you know, thinking about what could be done, 901 00:53:31,040 --> 00:53:33,440 Speaker 3: it's a complicated thing. And as often, you know, social 902 00:53:33,480 --> 00:53:37,200 Speaker 3: scientists are very good at kind of diagnosing what's going wrong, 903 00:53:37,320 --> 00:53:39,239 Speaker 3: but less good as saying like and this is what 904 00:53:39,280 --> 00:53:42,600 Speaker 3: we should do now. But I am kind of mildly 905 00:53:43,000 --> 00:53:47,319 Speaker 3: optimistic about subscription systems. 906 00:53:47,400 --> 00:53:49,000 Speaker 4: I mean, you know, I'm thinking. 907 00:53:48,680 --> 00:53:52,360 Speaker 3: Of substack, for example, where you know, a lot of 908 00:53:52,400 --> 00:53:55,080 Speaker 3: content creators, a lot of writers, have kind of gone 909 00:53:55,200 --> 00:54:00,960 Speaker 3: so low right and created newsletters on substanles and monetizing 910 00:54:01,040 --> 00:54:05,160 Speaker 3: that true kind of annual subscriptions. What I like about 911 00:54:05,239 --> 00:54:09,319 Speaker 3: that is that these kinds of annual subscriptions do not 912 00:54:09,920 --> 00:54:14,000 Speaker 3: create exactly the same kind of incentives as clickbait, right, 913 00:54:14,040 --> 00:54:18,400 Speaker 3: because you have your loyal audience and you want to 914 00:54:18,520 --> 00:54:23,799 Speaker 3: keep on delivering quality content for them, right, And so 915 00:54:24,600 --> 00:54:28,239 Speaker 3: again it's a bit more like traditional newspapers and memberships. 916 00:54:28,320 --> 00:54:30,640 Speaker 3: It's like you kind of have a sense of who 917 00:54:30,680 --> 00:54:34,200 Speaker 3: your loyal audience is and you're trying to do the 918 00:54:34,239 --> 00:54:35,799 Speaker 3: best you can for them. 919 00:54:36,239 --> 00:54:39,640 Speaker 4: And so I see that as like, you know, one 920 00:54:39,680 --> 00:54:40,239 Speaker 4: way in. 921 00:54:40,160 --> 00:54:42,560 Speaker 3: Which the incentives are a bit different, But then it 922 00:54:42,560 --> 00:54:44,080 Speaker 3: also raises lots of questions. 923 00:54:44,239 --> 00:54:46,360 Speaker 1: So I think it's a really good point about substack. 924 00:54:46,480 --> 00:54:48,560 Speaker 1: But not knowing the numbers of the time ahead, I 925 00:54:48,600 --> 00:54:50,960 Speaker 1: have to imagine that substack is so much smaller than 926 00:54:51,000 --> 00:54:54,120 Speaker 1: say TikTok or Instagram. What do you see if you're 927 00:54:54,200 --> 00:54:58,000 Speaker 1: thinking five ten years out about the future of this. 928 00:54:58,280 --> 00:55:02,160 Speaker 1: Presumably short form media is going to stay around. I 929 00:55:02,200 --> 00:55:05,200 Speaker 1: think people love the choice involved in it. 930 00:55:05,239 --> 00:55:07,759 Speaker 2: Is anything going to change in some meaningful way? 931 00:55:08,280 --> 00:55:11,080 Speaker 3: So one of the big changes that has happened over 932 00:55:11,120 --> 00:55:13,239 Speaker 3: the past ten years and which I think is going 933 00:55:13,280 --> 00:55:17,279 Speaker 3: to continue. And it's a fascinating change because it's one 934 00:55:17,320 --> 00:55:22,840 Speaker 3: that social media companies never talk about, is that average 935 00:55:22,920 --> 00:55:31,359 Speaker 3: people have stopped sharing on social media, normal regular users. 936 00:55:31,360 --> 00:55:34,560 Speaker 3: The bets that may Facebook successful, right, which was like 937 00:55:34,640 --> 00:55:37,319 Speaker 3: you were going to connect with your friends and share like, 938 00:55:37,480 --> 00:55:39,719 Speaker 3: you know, pictures of you, like whatever, going to the 939 00:55:39,760 --> 00:55:43,040 Speaker 3: coffee shop or like having kind of a moment of 940 00:55:43,080 --> 00:55:48,759 Speaker 3: you know, going skiing. The average, like the percentage of 941 00:55:49,000 --> 00:55:52,239 Speaker 3: kind of overall content that comes from people who are 942 00:55:52,280 --> 00:55:56,240 Speaker 3: not professional producers has gone from like, you know, eighty 943 00:55:56,280 --> 00:55:59,680 Speaker 3: percent to like less than five percent over the past 944 00:55:59,680 --> 00:56:02,120 Speaker 3: ten year. It's something on which like it's really hard 945 00:56:02,160 --> 00:56:05,040 Speaker 3: to find data because social media companies do not publicize 946 00:56:05,040 --> 00:56:07,440 Speaker 3: that because again, part of their appeal is like, oh, 947 00:56:07,600 --> 00:56:10,000 Speaker 3: you may once in a while you are going to 948 00:56:10,000 --> 00:56:12,640 Speaker 3: see content from your friends, right, And that's kind of 949 00:56:12,680 --> 00:56:16,960 Speaker 3: that was the whole goal of social media platforms in 950 00:56:17,000 --> 00:56:18,879 Speaker 3: the beginning, right. But this is not what you see 951 00:56:18,880 --> 00:56:21,840 Speaker 3: on social media now. What you see is professionally produce 952 00:56:21,960 --> 00:56:26,200 Speaker 3: content by kind of influencers and creators who make a 953 00:56:26,239 --> 00:56:27,880 Speaker 3: living from their production. 954 00:56:28,880 --> 00:56:32,520 Speaker 1: It's like cable television where you have lots of production companies, 955 00:56:32,719 --> 00:56:37,120 Speaker 1: lots of channels, and and they've gotten quite good. I mean, 956 00:56:37,160 --> 00:56:40,719 Speaker 1: the content is extraordinary. I wonder if they'll have to 957 00:56:40,840 --> 00:56:43,279 Speaker 1: change the name social media at some point because it's not. 958 00:56:43,280 --> 00:56:45,359 Speaker 3: Really that that's exactly the point, right. So I think 959 00:56:45,400 --> 00:56:48,399 Speaker 3: that if you look at the ten years like to come, right, 960 00:56:48,920 --> 00:56:53,440 Speaker 3: you're going to see this decline of like just friends content, 961 00:56:53,680 --> 00:56:57,719 Speaker 3: organic you know, non monetized content is going to keep 962 00:56:57,719 --> 00:57:01,760 Speaker 3: on declining because you know, who to share a poorly 963 00:57:01,840 --> 00:57:06,120 Speaker 3: shot picture of themselves when you have the Kardashians kind 964 00:57:06,120 --> 00:57:08,480 Speaker 3: of next to you, or for that matter, like all 965 00:57:08,600 --> 00:57:12,960 Speaker 3: content producers who are doing quality, high quality videos and 966 00:57:13,200 --> 00:57:16,480 Speaker 3: posts rights, I mean, you should, just you don't really 967 00:57:16,520 --> 00:57:18,120 Speaker 3: want to do that, and it doesn't feel like the 968 00:57:18,160 --> 00:57:22,000 Speaker 3: space for it either. So that my question is like, well, 969 00:57:22,400 --> 00:57:25,840 Speaker 3: are people going to stay on social media or you know, 970 00:57:26,000 --> 00:57:28,360 Speaker 3: are the way in which they interact with social media 971 00:57:28,480 --> 00:57:31,720 Speaker 3: going to be the same if it's all professional content 972 00:57:31,760 --> 00:57:36,240 Speaker 3: producers ten years from now? And I guess I do 973 00:57:36,320 --> 00:57:38,520 Speaker 3: think that things are going to have to change when 974 00:57:38,600 --> 00:57:41,040 Speaker 3: we get closer to exactly what you are talking about, 975 00:57:41,080 --> 00:57:44,640 Speaker 3: which is more of a cable television system, except that 976 00:57:44,680 --> 00:57:48,040 Speaker 3: you have like, you know, five hundred million channels, you 977 00:57:48,080 --> 00:57:50,520 Speaker 3: know what I mean, not thirty. 978 00:57:50,400 --> 00:57:52,640 Speaker 2: And you have the option and you have the option 979 00:57:52,720 --> 00:57:53,440 Speaker 2: to swipe right. 980 00:57:53,600 --> 00:57:57,040 Speaker 3: But I do think that for platforms, once that's kind 981 00:57:57,040 --> 00:58:00,520 Speaker 3: of clarifying, and once people kind of understand that, you know, 982 00:58:00,760 --> 00:58:04,080 Speaker 3: we're not in the world that Facebook created circa like 983 00:58:04,120 --> 00:58:06,960 Speaker 3: two thousand and you know ten, we're already in the 984 00:58:07,000 --> 00:58:10,479 Speaker 3: world that's closer to cable television, where you get, like again, 985 00:58:10,520 --> 00:58:14,840 Speaker 3: this infinite kind of array of professional production on an 986 00:58:14,880 --> 00:58:18,120 Speaker 3: infinite array of topics. I do think that things will 987 00:58:18,160 --> 00:58:21,880 Speaker 3: get clearer, you know what I mean, Or that both 988 00:58:21,920 --> 00:58:27,120 Speaker 3: the economic incentives, the algorithmic infrastructure, and the expectations of 989 00:58:27,160 --> 00:58:30,640 Speaker 3: the audience are going to change, But I don't exactly 990 00:58:30,680 --> 00:58:32,040 Speaker 3: know in which directions. 991 00:58:32,280 --> 00:58:35,160 Speaker 1: Yeah, we're really just in the adolescence of all these platforms. 992 00:58:35,200 --> 00:58:38,560 Speaker 1: This is so new, and I'm really interested in what's 993 00:58:38,560 --> 00:58:41,040 Speaker 1: happening with politics. I mean, it's clear that we're very 994 00:58:41,080 --> 00:58:44,440 Speaker 1: polarized now. I do want to say so you and 995 00:58:44,400 --> 00:58:46,680 Speaker 1: I are both very interesting in how algorithms play a 996 00:58:46,720 --> 00:58:49,560 Speaker 1: role in that. I do want to say that people 997 00:58:49,640 --> 00:58:52,600 Speaker 1: have always been polarized, and if you just look at 998 00:58:52,640 --> 00:58:56,040 Speaker 1: let's say last century twentieth century, the polarization was so 999 00:58:56,240 --> 00:58:59,160 Speaker 1: extreme that hundreds of millions of people were killed by 1000 00:58:59,160 --> 00:59:02,280 Speaker 1: their neighbors, whether that's Nazi Germany or the Chinese and 1001 00:59:02,320 --> 00:59:06,080 Speaker 1: Russian Communist revolutions, or Rwanda with the Tutsi against the Hutu, 1002 00:59:06,200 --> 00:59:08,160 Speaker 1: or in Cambodi with Paul pot What. It doesn't mean 1003 00:59:08,760 --> 00:59:11,760 Speaker 1: people always are very prone to get polarized. So I 1004 00:59:11,760 --> 00:59:15,120 Speaker 1: don't think it can be blamed on social media. But 1005 00:59:15,200 --> 00:59:20,040 Speaker 1: I am hopeful that if we sort of get out 1006 00:59:20,080 --> 00:59:23,880 Speaker 1: of our hormonal adolescence with these platforms, we can at 1007 00:59:23,960 --> 00:59:25,280 Speaker 1: least calm things down a little bit. 1008 00:59:25,320 --> 00:59:26,320 Speaker 2: What are your thoughts on that? 1009 00:59:27,640 --> 00:59:31,320 Speaker 3: I agree, I mean, I think polarization. You know, I 1010 00:59:31,360 --> 00:59:34,160 Speaker 3: think for the past twenty years there has been and 1011 00:59:34,520 --> 00:59:37,480 Speaker 3: I mean pre dating social media, there has been this worry, 1012 00:59:37,680 --> 00:59:41,600 Speaker 3: right that polarization is increasing, and I agree with that. Historically, 1013 00:59:41,760 --> 00:59:45,040 Speaker 3: it's a bit of a myopic view, right in the 1014 00:59:45,080 --> 00:59:47,560 Speaker 3: sense that again, this very long history and as you 1015 00:59:47,840 --> 00:59:51,960 Speaker 3: as you were saying, extremely deadly of kind of people 1016 00:59:52,120 --> 00:59:54,720 Speaker 3: hating each other with such faults that it led to 1017 00:59:55,200 --> 00:59:58,720 Speaker 3: actual civil war or kind of revolutions, et cetera. 1018 00:59:58,880 --> 01:00:01,080 Speaker 4: So that's kind of point number one. 1019 01:00:01,840 --> 01:00:05,640 Speaker 3: I agree also that social media is not the only culprits. 1020 01:00:05,720 --> 01:00:07,280 Speaker 4: There is no doubt about that. 1021 01:00:07,360 --> 01:00:10,520 Speaker 3: There are a number of other forces at stake, including 1022 01:00:11,120 --> 01:00:16,920 Speaker 3: a big kind of macro economic and socio demographic transformations 1023 01:00:16,960 --> 01:00:19,520 Speaker 3: in the United States among other places. But you know, 1024 01:00:19,560 --> 01:00:23,600 Speaker 3: in many countries that everybody is just kind of grappling with, 1025 01:00:23,840 --> 01:00:28,360 Speaker 3: right and with the role of technology in society. And 1026 01:00:28,880 --> 01:00:32,280 Speaker 3: I also think that social media really doesn't help, right 1027 01:00:32,960 --> 01:00:35,160 Speaker 3: in the sense of, like, again, it's not like it's 1028 01:00:35,160 --> 01:00:38,560 Speaker 3: not the only culprit, it's not the only cause, but 1029 01:00:39,080 --> 01:00:41,520 Speaker 3: it is enough to kind of tilt, you know, the 1030 01:00:41,600 --> 01:00:45,680 Speaker 3: thing from a three, four to six, seven. 1031 01:00:46,000 --> 01:00:47,840 Speaker 4: You know, on the scale of zero to ten. 1032 01:00:48,400 --> 01:00:51,160 Speaker 3: And what I find is that it's not only polarization, 1033 01:00:52,200 --> 01:00:55,640 Speaker 3: it's also this kind of like twenty four to seven 1034 01:00:56,400 --> 01:01:00,080 Speaker 3: news reism, which you know, if you look at that 1035 01:01:01,280 --> 01:01:05,280 Speaker 3: kind of the timeline of kind of news production. Again, 1036 01:01:05,480 --> 01:01:08,320 Speaker 3: it's a longer history, right in a way it started 1037 01:01:08,360 --> 01:01:13,400 Speaker 3: with cable television, right that we're broadcasting twenty four to seven, 1038 01:01:14,280 --> 01:01:17,200 Speaker 3: you know, so it has a longer history. But certainly 1039 01:01:17,600 --> 01:01:20,760 Speaker 3: the reactivity of social media the fact that you can 1040 01:01:20,840 --> 01:01:23,760 Speaker 3: post a video just right when it's happening, the fact 1041 01:01:23,800 --> 01:01:26,920 Speaker 3: that you can live stream. All of these development just 1042 01:01:27,000 --> 01:01:30,240 Speaker 3: means that the ReSm of kind of news, kind of 1043 01:01:30,280 --> 01:01:33,720 Speaker 3: circulation and reaction and reaction to the reaction has just 1044 01:01:33,800 --> 01:01:37,320 Speaker 3: accelerated so much. And you see that it has definitely 1045 01:01:37,400 --> 01:01:42,080 Speaker 3: changed politics as well. I mean, political life used to 1046 01:01:42,120 --> 01:01:47,320 Speaker 3: be pretty subdued kind of business. Like the reasm, for example, 1047 01:01:47,400 --> 01:01:51,320 Speaker 3: of Congress is a very slow ReSm, as is the 1048 01:01:51,760 --> 01:01:56,000 Speaker 3: judicial ReSm. You know, the time for the Supreme Court 1049 01:01:56,080 --> 01:01:59,360 Speaker 3: to make decisions a long time ago that was taking 1050 01:01:59,400 --> 01:02:01,920 Speaker 3: like literally years, you know, and now we're just like 1051 01:02:02,000 --> 01:02:04,360 Speaker 3: kind of in this you know, puff puff puff, kind 1052 01:02:04,360 --> 01:02:07,520 Speaker 3: of every second there is a new kind of thing 1053 01:02:08,040 --> 01:02:10,600 Speaker 3: that is even more shocking than the previous one. 1054 01:02:10,480 --> 01:02:13,720 Speaker 4: And that you know, you can't help but kind of 1055 01:02:13,760 --> 01:02:14,240 Speaker 4: see that. 1056 01:02:14,480 --> 01:02:18,520 Speaker 3: It is correlated with the affordances of social media platforms. Right, 1057 01:02:18,560 --> 01:02:20,760 Speaker 3: and so the question then is are we gonna are 1058 01:02:20,760 --> 01:02:23,880 Speaker 3: we gonna move towards kind of a more stable kind 1059 01:02:23,920 --> 01:02:25,520 Speaker 3: of reason. Well, as you said, it's like, I think 1060 01:02:25,520 --> 01:02:28,440 Speaker 3: the parallel with adolescence is really interesting that right now 1061 01:02:28,480 --> 01:02:31,240 Speaker 3: it's like everything's running really high, you know, what I mean, 1062 01:02:31,360 --> 01:02:33,600 Speaker 3: and everything's gonna kind of came down a bit. And 1063 01:02:33,640 --> 01:02:36,040 Speaker 3: I think that for that we need to turn to 1064 01:02:36,280 --> 01:02:39,960 Speaker 3: kind of technology companies and just say, like, what are 1065 01:02:39,960 --> 01:02:45,000 Speaker 3: the incentives that you've created for people to post, right, 1066 01:02:45,560 --> 01:02:48,000 Speaker 3: and what are the guard rails that you're putting in place. 1067 01:02:48,200 --> 01:02:51,480 Speaker 3: And again this is not to blame social media companies, 1068 01:02:51,520 --> 01:02:56,240 Speaker 3: because it's really hard business. Like hundreds of millions billions 1069 01:02:56,280 --> 01:03:01,120 Speaker 3: of people are interacting with this algorithmic structure, right, and 1070 01:03:01,280 --> 01:03:05,680 Speaker 3: trying to kind of, you know, adjust things for that 1071 01:03:05,840 --> 01:03:10,600 Speaker 3: scale of kind of people. It's just incredibly hard. And 1072 01:03:10,640 --> 01:03:13,880 Speaker 3: so they are also on a learning curve, just like 1073 01:03:13,960 --> 01:03:17,920 Speaker 3: the rest of us are. So they're trying in some 1074 01:03:18,000 --> 01:03:21,080 Speaker 3: cases to do the right thing. In other cases, they're 1075 01:03:21,080 --> 01:03:26,560 Speaker 3: also making decisions that are kind of irresponsible, right For example, 1076 01:03:27,160 --> 01:03:30,440 Speaker 3: you know, getting rid of content moderation guidelines, I mean 1077 01:03:30,480 --> 01:03:33,800 Speaker 3: you kind of know that that's going to encourage like 1078 01:03:33,920 --> 01:03:38,560 Speaker 3: much more kind of heinous, hateful behavior. Again because that 1079 01:03:38,920 --> 01:03:43,320 Speaker 3: not necessarily because creators believe in that heinous and hateful content, 1080 01:03:43,360 --> 01:03:46,440 Speaker 3: but because that's what's going to capture the engagement and 1081 01:03:46,480 --> 01:03:49,880 Speaker 3: attention of online audiences. And so I do think that 1082 01:03:49,960 --> 01:03:52,600 Speaker 3: social media platforms at this point are at a bit 1083 01:03:52,640 --> 01:03:56,160 Speaker 3: of a crossroad in terms of, like, so you have 1084 01:03:56,280 --> 01:04:02,320 Speaker 3: become the key infrastructures for kind of media and communication, 1085 01:04:03,600 --> 01:04:05,760 Speaker 3: what are you going to do. Are you going to 1086 01:04:05,880 --> 01:04:11,160 Speaker 3: keep on chasing engagement at all costs right potentially kind 1087 01:04:11,200 --> 01:04:14,280 Speaker 3: of destroying everything in your wake, or are you going 1088 01:04:14,360 --> 01:04:18,720 Speaker 3: to start looking at the long term satisfaction? The long 1089 01:04:18,840 --> 01:04:23,400 Speaker 3: term kind of benefits a long term outview of what 1090 01:04:23,480 --> 01:04:26,880 Speaker 3: you can do for your customers. And I really think 1091 01:04:26,920 --> 01:04:29,680 Speaker 3: it's kind of a short term, long term kind of 1092 01:04:30,680 --> 01:04:33,920 Speaker 3: trade offs that's happening right now, and I really hope 1093 01:04:33,960 --> 01:04:37,160 Speaker 3: that the long term considerations are going to gain traction. 1094 01:04:37,560 --> 01:04:39,840 Speaker 1: I love that, And I feel like social media companies 1095 01:04:39,880 --> 01:04:44,240 Speaker 1: don't necessarily have the economic incentive to do that unless 1096 01:04:44,920 --> 01:04:48,560 Speaker 1: one can stand out by saying we're going to take 1097 01:04:48,760 --> 01:04:53,040 Speaker 1: less advertiser revenue for the purpose of making a better 1098 01:04:53,280 --> 01:04:54,040 Speaker 1: community here. 1099 01:04:54,080 --> 01:04:55,560 Speaker 2: And I think they can really stand that that way. 1100 01:04:55,720 --> 01:04:56,240 Speaker 4: I agree. 1101 01:04:56,280 --> 01:04:58,000 Speaker 3: I mean, I think a couple of things that are 1102 01:04:58,000 --> 01:05:00,640 Speaker 3: pretty obvious. I mean another one and again, and I mean, 1103 01:05:00,720 --> 01:05:04,320 Speaker 3: I know that it's not necessarily a popular recommendation, but 1104 01:05:04,960 --> 01:05:07,600 Speaker 3: we kind of got used to getting stuff for free. 1105 01:05:08,200 --> 01:05:11,480 Speaker 3: Audiences Also, have to change, We all have to change, 1106 01:05:11,720 --> 01:05:13,960 Speaker 3: and we kind of have to be willing to pay 1107 01:05:14,640 --> 01:05:18,160 Speaker 3: for access to social media platforms because you see, if 1108 01:05:18,160 --> 01:05:22,160 Speaker 3: we all had kind of subscriptions, well, that would kind 1109 01:05:22,160 --> 01:05:25,760 Speaker 3: of reduce the part of advertising right in the kind 1110 01:05:25,760 --> 01:05:29,360 Speaker 3: of overall revenues of social media companies, So they wouldn't 1111 01:05:29,360 --> 01:05:33,720 Speaker 3: be chasing engagement metrics in quite the same way, so 1112 01:05:33,760 --> 01:05:36,520 Speaker 3: they wouldn't be putting quite the same incentives in place 1113 01:05:36,560 --> 01:05:40,280 Speaker 3: for content creators, and so everything would look a bit different. 1114 01:05:40,040 --> 01:05:40,800 Speaker 4: You know what I mean. 1115 01:05:41,200 --> 01:05:44,840 Speaker 3: So part of this is also due to the advertising 1116 01:05:44,920 --> 01:05:50,200 Speaker 3: only or advertising mostly revenue structures of social media companies. 1117 01:05:50,400 --> 01:05:53,120 Speaker 3: And I do think that all of us, as customers, 1118 01:05:53,280 --> 01:05:56,520 Speaker 3: as audiences, as participants, we also have kind of a 1119 01:05:56,600 --> 01:05:59,960 Speaker 3: role to play in saying, like, you know, we should 1120 01:06:00,040 --> 01:06:03,560 Speaker 3: would be willing to pay for this service. And again, 1121 01:06:03,840 --> 01:06:07,200 Speaker 3: it raises lots of questions about access democratization. 1122 01:06:07,520 --> 01:06:09,320 Speaker 4: You know, there are lots of it. 1123 01:06:09,320 --> 01:06:11,560 Speaker 3: It's not an easy debate to have, but I think 1124 01:06:11,560 --> 01:06:14,120 Speaker 3: it's a debate for us having because a lot of 1125 01:06:14,120 --> 01:06:18,120 Speaker 3: what's going wrong right now comes from this original I mean, 1126 01:06:18,120 --> 01:06:20,000 Speaker 3: I don't want to call it an original sin, but 1127 01:06:20,080 --> 01:06:24,600 Speaker 3: this original deal right that advertising was going to be 1128 01:06:24,760 --> 01:06:29,520 Speaker 3: funding social media period. Yeah, and that is not the 1129 01:06:29,520 --> 01:06:33,800 Speaker 3: healthiest way to kind of make a living as a company. 1130 01:06:38,280 --> 01:06:41,280 Speaker 1: That was my conversation with Angel Christen, and what we 1131 01:06:41,320 --> 01:06:45,520 Speaker 1: talked about today was this notion of algorithmic capture, which 1132 01:06:45,560 --> 01:06:50,880 Speaker 1: is the gradual reshaping of behavior in response to opaque 1133 01:06:51,160 --> 01:06:55,480 Speaker 1: systems that reward certain choices and ignore others. If you 1134 01:06:55,600 --> 01:06:57,560 Speaker 1: zoom out far enough, you can see that we are 1135 01:06:57,600 --> 01:07:03,640 Speaker 1: living inside a huge experiment. Billions of brains, billions of 1136 01:07:04,040 --> 01:07:08,960 Speaker 1: feedback loops, billions of tiny reinforcements happening every second. And 1137 01:07:09,080 --> 01:07:13,080 Speaker 1: in this environment, some headline performs well, or some video 1138 01:07:13,560 --> 01:07:18,480 Speaker 1: sparks outrage and multiplies. Maybe a creator feels the uplift 1139 01:07:18,520 --> 01:07:23,080 Speaker 1: of attention. Maybe a newsroom watches a dashboard climb or 1140 01:07:23,520 --> 01:07:28,640 Speaker 1: stall out, and gradually everybody's behavior adapts. So, as we 1141 01:07:28,680 --> 01:07:32,480 Speaker 1: heard from Anzell, she studies journalists who entered the field 1142 01:07:32,640 --> 01:07:37,080 Speaker 1: with a sense of civic mission, or content creators who 1143 01:07:37,120 --> 01:07:40,240 Speaker 1: began with passion for a topic or a community. And 1144 01:07:40,240 --> 01:07:42,400 Speaker 1: by the way, this is just as true with lots 1145 01:07:42,440 --> 01:07:46,640 Speaker 1: of professions. Maybe a musician who enters wanting to create 1146 01:07:46,680 --> 01:07:50,440 Speaker 1: something really new, and then the metrics arrive and suddenly 1147 01:07:50,520 --> 01:07:55,080 Speaker 1: they're dealing with the gravitational pull of the algorithm. I 1148 01:07:55,160 --> 01:07:57,360 Speaker 1: just want to zoom out for one second. As you'll 1149 01:07:57,360 --> 01:07:59,480 Speaker 1: know if you've listened to a lot of these episodes. 1150 01:08:00,120 --> 01:08:05,560 Speaker 1: Lea's pointing out that polarization predates social media by millions 1151 01:08:05,600 --> 01:08:09,240 Speaker 1: of years, and obviously, any cursory reading of history will 1152 01:08:09,280 --> 01:08:13,720 Speaker 1: tell you that outrage predates the Internet. Newspapers in the 1153 01:08:13,760 --> 01:08:18,240 Speaker 1: nineteenth century, for example, they ran inflammatory headlines. This was 1154 01:08:18,280 --> 01:08:21,719 Speaker 1: known as yellow journalism, and this all thrived long before 1155 01:08:21,880 --> 01:08:26,320 Speaker 1: Wi Fi. Human attention has always been drawn to scandal 1156 01:08:26,640 --> 01:08:31,800 Speaker 1: and spectacle and celebrity, but the scale of the quantification 1157 01:08:32,040 --> 01:08:36,719 Speaker 1: of today's systems do introduce a new texture to public life. 1158 01:08:37,200 --> 01:08:43,959 Speaker 1: Everything accelerates, the incentives intensify, and presumably the emotional temperature rises. 1159 01:08:44,439 --> 01:08:47,120 Speaker 1: But I do want to say, as a techno optimist, 1160 01:08:47,160 --> 01:08:52,679 Speaker 1: that nothing here is inevitable. Incentives can be redesigned, Revenue 1161 01:08:52,680 --> 01:08:57,360 Speaker 1: models can and will evolve, Platforms can make different trade offs, 1162 01:08:57,760 --> 01:09:01,000 Speaker 1: audiences can decide what there willing to pay for, and 1163 01:09:01,120 --> 01:09:05,000 Speaker 1: creators can choose which signals they respond to. None of 1164 01:09:05,000 --> 01:09:07,280 Speaker 1: this is simple, but it is important to realize that 1165 01:09:07,360 --> 01:09:11,000 Speaker 1: we are in the earliest chapters of a story about 1166 01:09:11,040 --> 01:09:16,360 Speaker 1: how human psychology interfaces with computational systems. We are in 1167 01:09:16,439 --> 01:09:21,680 Speaker 1: the infancy phase of a technology that now functions as infrastructure. 1168 01:09:22,520 --> 01:09:25,840 Speaker 1: So the next time you feel outrage when you're scrolling around, 1169 01:09:25,960 --> 01:09:28,760 Speaker 1: or you see a headline that's engineered to hook you, 1170 01:09:28,960 --> 01:09:32,439 Speaker 1: or you watch numbers tick upwards somewhere on a screen, 1171 01:09:33,240 --> 01:09:36,920 Speaker 1: just pause for a second to ask yourself, what behavior 1172 01:09:37,000 --> 01:09:40,679 Speaker 1: of mine is getting reinforced, what is being trained? How 1173 01:09:40,920 --> 01:09:44,360 Speaker 1: do I want to participate in the system a little 1174 01:09:44,400 --> 01:09:49,439 Speaker 1: more thoughtfully? Understanding the machinery just gives you a little 1175 01:09:49,479 --> 01:09:53,519 Speaker 1: more agency inside of it, and that might be one 1176 01:09:53,520 --> 01:09:58,360 Speaker 1: of the most important skills for living in this second quarter. 1177 01:09:58,320 --> 01:10:00,080 Speaker 2: Of the twenty first century. 1178 01:10:03,280 --> 01:10:06,160 Speaker 1: Go to Eagleman dot com slash podcast for more information 1179 01:10:06,280 --> 01:10:09,519 Speaker 1: and to find further reading. Join the weekly discussions on 1180 01:10:09,560 --> 01:10:13,120 Speaker 1: my substack, and check out and subscribe to Inner Cosmos 1181 01:10:13,160 --> 01:10:15,559 Speaker 1: on YouTube for videos of each episode and to leave 1182 01:10:15,600 --> 01:10:19,160 Speaker 1: comments until next time. I'm David Eagleman, and this is 1183 01:10:19,240 --> 01:10:20,240 Speaker 1: Inner Cosmos.