Speaker 1: How do the algorithms that were surrounded with shape our lives?
Speaker 1: Why does a journalist begin to write differently once metrics
Speaker 1: are introduced? What is algorithmic capture? Has clickbait always existed?
Speaker 1: What did that look like before the Internet? How could
Speaker 1: even vegan content creators go in for rage bait? What
Speaker 1: does any of this have to do with why someone
Speaker 1: would insist on cooking pasta in the bathtub? Or the
Speaker 1: nineteenth century actress Sarah Bernhardt or one weird trick or
Speaker 1: Oxford English Dictionary's word of the year. Join me today
Speaker 1: with sociologist Angel Christen as we talk about how algorithms
Speaker 1: invisibly sculpt human behavior. Welcome to Intercosmos with me David Eagleman.
Speaker 1: I'm a neuroscientist and an author at Stanford An. These episodes,
Speaker 1: we sail deeply into our three pound universe to understand
Speaker 1: why and how our lives look the way they do.
Speaker 1: Every brain is trying to navigate itself through a very
Speaker 1: social world, and it's always unconsciously making predictions to figure
Speaker 1: things out like what should I pay attention to or
Speaker 1: what is worth my time?
Speaker 2: What should I care about?
Speaker 1: And for essentially the entirety of human history, those signals
Speaker 1: came from other humans.
Speaker 2: You read a lot.
Speaker 1: Of information from the expressions on their faces like a
Speaker 1: raised eyebrow. You hear things in the tone of people's voices.
Speaker 1: You modify your behavior if you are getting signals of
Speaker 1: approof or disapproval, not just from your parents, but more
Speaker 1: generally from your tribe. Our brains have worked with these
Speaker 1: sorts of signals for millions of years. You're looking for
Speaker 1: a nod of approval, or people laugh at what you say,
Speaker 1: or they scowl at it or whatever. But now imagine
Speaker 1: replacing all that with numbers. Now you've got a dashboard
Speaker 1: and a counter that ticks upward, and you've got a
Speaker 1: graph that rises or falls, and it's all in real time,
Speaker 1: and you have a notification that says three four hundred
Speaker 1: people watched this or twelve people watched this. So, all
Speaker 1: of a sudden, in this past nanosecond of human evolution,
Speaker 1: we are suddenly in an era when the signals that
Speaker 1: guide our behavior are not primarily human faces, but instead metrics.
Speaker 1: You've got numbers and rankings, you've got dashboards, and it's
Speaker 1: based on algorithms that you can't really see. And these
Speaker 1: algorithms decide what appears in front of us and what disappears.
Speaker 1: And here's the wild part. When those signals change, we change,
Speaker 1: often unconsciously. Writers will change what they write based on
Speaker 1: the feedback. Creators will change what they're about based on
Speaker 1: the feedback. Sometimes there are subtle ways this happens, like
Speaker 1: someone tweaks the headline, or they make a video shorter,
Speaker 1: or they spend more time thinking about a stronger hook.
Speaker 1: But pretty quickly, entire professions can reorganize themselves around these
Speaker 1: invisible feedback systems. So what happens now that algorithms are
Speaker 1: the primary environment that we're swimming in. What happens to
Speaker 1: professional values, what happens to identity? Just think about one
Speaker 1: example of this. One of the brand new words that
Speaker 1: we all witness the birth of a couple decades ago
Speaker 1: was clickbait. As you presumably know, this is one of
Speaker 1: those provocative headlines like you'll never believe what happens next,
Speaker 1: and this gets you to go down some rabbit hole
Speaker 1: that you didn't intend to go down. But now clickbait
Speaker 1: has evolved into Oxford English Dictionaries word of the.
Speaker 2: Year last year, which is rage bait.
Speaker 1: This is the next evolutionary step in the attention economy.
Speaker 1: Rage bait is all about shouting something, some statement that's
Speaker 1: so inflammatory or so absurd that your nervous system lights
Speaker 1: up before your more thoughtful neural networks even get their
Speaker 1: shoes on. So you feel a surge of whatever anger
Speaker 1: or discuss or disbelief, and before you're consciously aware of it,
Speaker 1: your fingers are clicking and you're commenting, you're sharing, you're
Speaker 1: stitching a video, you're firing back at someone in the
Speaker 1: comment section.
Speaker 2: You're all worked up.
Speaker 1: But from the algorithm's point of view, engagement is engagement,
Speaker 1: and in a system that measures success by interaction, provoking
Speaker 1: emotion is a very effective strategy. So I'm fascinated with
Speaker 1: what all this means for us as a society. And
Speaker 1: I knew there was no one better to call for
Speaker 1: this than Onzel. Christen Angel is a sociologist who has
Speaker 1: spent years embedded inside newsrooms, inside influencer culture, inside the
Speaker 1: worlds where algorithms and analytics shape what people produce and
Speaker 1: how they see themselves on shell studies, incentives, and how
Speaker 1: our digital infrastructures are reshaping the social fabric around us.
Speaker 1: So I'm so pleased to sit down with her today
Speaker 1: to talk about what happens when human brains live inside
Speaker 1: algorithmic systems and how those systems are shaping our behavior. So, Angel,
Speaker 1: you study algorithms and their social impact on people, tell
Speaker 1: us about that.
Speaker 3: For the past ten years, I've been looking at how
Speaker 3: algorithmic technologies are playing an increasingly important role in people's
Speaker 3: lives and in their work. So now the thing is,
Speaker 3: I'm a sociologist by training, so I really care about
Speaker 3: people's identities, their work practices, how they communicate and relate
Speaker 3: to others, and all of that has been completely transformed
Speaker 3: with digital technologies and the computational procedure sustaining them. Everything
Speaker 3: we do now is mediated through computational procedures one way
Speaker 3: or another, thanks to mobile devices on the one hand
Speaker 3: and computers on the other.
Speaker 2: So let's take a specific example.
Speaker 1: So you got interested some years ago in how journalists
Speaker 1: were writing their articles and what kind of things they
Speaker 1: chose to write, and how that changed once these with
Speaker 1: the metrics got introduced.
Speaker 4: Yeah, so that was so interesting. At first.
Speaker 3: I came to kind of study journalism because I was, like,
Speaker 3: you know, with the Internet and kind of online advertising,
Speaker 3: the business models of the news are changing right in
Speaker 3: Big Park because online advertising move to social media platforms
Speaker 3: and Google, and so they had news websites had less
Speaker 3: money and newspapers had less money, and so I was
Speaker 3: kind of broadly interested in that and like, what does
Speaker 3: that mean for the future of the news. And I
Speaker 3: did what I always do. I'm an ethnographer, which means
Speaker 3: that I go spend time with people. I interview them,
Speaker 3: I have lunch with them, I observe how they work.
Speaker 3: I become kind of part of the furniture at the office.
Speaker 3: It's like a yeah, she's here again, you know, just
Speaker 3: observing us another day. And what I realized at that
Speaker 3: point is that in the different newsrooms that I was studying,
Speaker 3: some of them were in New York, some of them
Speaker 3: were in Paris, lists kept on looking at these specific
Speaker 3: software programs that they were kind of obsessed with. And
Speaker 3: so what were the software programs? They were web analytics,
Speaker 3: software programs that were providing detailed, real time data about
Speaker 3: what readers were doing on the website. Right, So it
Speaker 3: was giving kind of social media metrics like how many
Speaker 3: readers were coming from Facebook, from Twitter, etc. It was
Speaker 3: telling people how many people had read the articles they
Speaker 3: had published, right, was it ten people, twenty people, one
Speaker 3: hundred thousand, ten hundred thousand, a million, right, So, giving
Speaker 3: that it was ranking all the articles in terms of
Speaker 3: their popularity on the website and on social media, and
Speaker 3: it was also telling journalists how long readers were spending
Speaker 3: on average on any given article, which, by the way,
Speaker 3: is not a good metric in the sense that like
Speaker 3: it's almost always in the range of like six to
Speaker 3: fifteen seconds is the average time that readers spent on
Speaker 3: any news article. Right, Yeah, not fun for journalists, definitely.
Speaker 3: They preferred to ignore that one. And so what I
Speaker 3: realized is that journalists kept on talking about that. So
Speaker 3: that was the early two thousand tents, right. People didn't
Speaker 3: really know. I mean, the internet was still pretty new, right,
Speaker 3: and social media was even newer. But journalists were just like, wow,
Speaker 3: look like that article is so popular. It's just like it's,
Speaker 3: you know, such a hit, everybody's clicking on it. Well
Speaker 3: as this article hmmm, disappointing. I spent two weeks reporting
Speaker 3: this and no one's clicking on it. And so they
Speaker 3: kept on discussing this and making jokes about it, talking
Speaker 3: about it and kind of more and more using this
Speaker 3: data to make sense of what it meant to be
Speaker 3: a good journalist.
Speaker 2: Yeah.
Speaker 1: So first, what was the difference before if you you
Speaker 1: were a newspaper writer, let's say twenty years before that,
Speaker 1: how did you get feedback?
Speaker 4: Yeah, so that's the really interesting thing.
Speaker 3: So what's really fun there, and that's you know, the
Speaker 3: great point of being in academia is that other people
Speaker 3: have studied print newsrooms in the eighties and nineties, right,
Speaker 3: so they have all of these historical material about how
Speaker 3: print newsrooms used to work. Now, the print newsrooms, the
Speaker 3: way it used to work was two characteristics. First, journalists
Speaker 3: and editors did not care much about the audience, right,
Speaker 3: And they didn't care mostly because they thought that what
Speaker 3: mattered more was the opinion of their peers and superiors.
Speaker 3: So there was this kind of strong professional identities that
Speaker 3: what was really important was what other journalists were thinking
Speaker 3: about you, both in new newsroom and in other newsrooms. Right,
Speaker 3: because journalists always tried to move between one newsroom and
Speaker 3: the next.
Speaker 4: So let's say you had the New York Times.
Speaker 3: You also care about what people at the Washington Post
Speaker 3: think about your work, because if they like it, perhaps
Speaker 3: they'll offer your job later on that kind of stuff,
Speaker 3: and then what your.
Speaker 4: Hierarchical superiors total of your work.
Speaker 3: So your editors in chief basically, right, and if your
Speaker 3: editor in chief was saying like, wow, this is a
Speaker 3: great article, well done, that was that you know, that
Speaker 3: was kind of the best things that could happen to
Speaker 3: you on any given day. Now, they were receiving letters
Speaker 3: from the audience, right. So letters to the editor are
Speaker 3: like kind of a long established tradition, most newspapers have them,
Speaker 3: but there are all of these like historical studies showing
Speaker 3: that journalists mostly disregarded these letters and they're like, oh yeah,
Speaker 3: people are crazy, they're understand those crazy stuff. They don't
Speaker 3: understand how journalism works, right, So a very different kind
Speaker 3: of relationship where really what the audience was actually doing
Speaker 3: and what it wanted wasn't very well understood or kind
Speaker 3: of paid attention to. The second aspect, there was also
Speaker 3: that with newspapers there were lots of surveys obviously, because
Speaker 3: you had marketing departments and you had like kind of
Speaker 3: commercial the commercial side of publications, right, and they cared
Speaker 3: about the audience because that's how depending on you know,
Speaker 3: readership figures. That's how they were able to charge for
Speaker 3: more expensive advertising space, right, And so that's what revenues
Speaker 3: depended on. So the marketing departments were doing surveys. But
Speaker 3: what's interesting about these surveys is that you know, in
Speaker 3: the eighteen and nineties, they only asked like, well, do
Speaker 3: you like the newspaper and people would say yeah, But
Speaker 3: they didn't have super granular data about well, which section
Speaker 3: exactly do you read the most People would say like, well,
Speaker 3: based on memory, I tend to read more of the lifestyle.
Speaker 3: Say but you know, I really care about international news too, Right,
Speaker 3: So people they were relying on this kind of post
Speaker 3: hoc memories and recollections of what readers were doing, and
Speaker 3: they didn't really know in detail which articles and which
Speaker 3: topics they cared the most. Now comes the Internet and
Speaker 3: comes web analytics and the kind of software programs and
Speaker 3: algorithms kind of displaying with dashboards what these analytics look
Speaker 3: like to journalists and editors. Suddenly they realize that no
Speaker 3: one's clicking on international news. Very few people click on
Speaker 3: political news unless it involves some kind of scandal or
Speaker 3: sex or celebrities. Right, that people care a lot about
Speaker 3: lifestyle news. They have a lot about celebrity news. They
Speaker 3: care not at all about culture and the arts. That's
Speaker 3: not really what people click on, right, And so suddenly
Speaker 3: they have this kind of like almost tsunami of data
Speaker 3: telling them what people are actually clicking on.
Speaker 4: And that's kind of a cognitive.
Speaker 3: Revolution for journalists, right, because suddenly they're just like, wait,
Speaker 3: what should we do? Should we only do tabloid news
Speaker 3: because that's what readers want?
Speaker 4: Or is our jobs something else?
Speaker 1: And you know, it's interesting because from a behavioral economics perspective,
Speaker 1: even if you ask readers in a very granular fashion
Speaker 1: what they wanted and so on, they don't necessarily know that.
Speaker 1: Consciously they might think I'm the kind of person who
Speaker 1: clicks on international news, even though they don't. Okay, So
Speaker 1: there's this notion of algorithmic capture, which is that let's
Speaker 1: say you're a writer, you start chasing the numbers and
Speaker 1: you end up doing what the algorithm wants. Now, one
Speaker 1: might say, okay, but maybe there was something like editorial capture.
Speaker 1: The editor who's seen or to you, who really admired
Speaker 1: you end up doing what he or she wanted.
Speaker 2: The problem is that the algorithm is.
Speaker 1: More opaque, right, and it changes, it's fungible.
Speaker 2: So tell us how you see that?
Speaker 3: Yeah, So that's fascinating because that's exactly what I observed
Speaker 3: in newsrooms, and that's what my book Metrics at Work
Speaker 3: Journalism is a contested meaning of algorithms is basically all
Speaker 3: about right. So what I find kind of due to
Speaker 3: that kind of again that wave of granular data that
Speaker 3: kind of enter newsrooms, and you know often it entered
Speaker 3: newsrooms with the best intentions, right, which was that editors,
Speaker 3: journalists and the companies that were that were usually for
Speaker 3: profit companies that were providing these kind of dashboards and
Speaker 3: software programs. We're like, listen, it's a question of democratization.
Speaker 3: We want to give journalists the knowledge of what like
Speaker 3: their audiences are actually engaging with so that they can
Speaker 3: survive in the digital age, right, so that they can
Speaker 3: drive in the digital age. So that was the impulse,
Speaker 3: a good one, right. But then what you see is
Speaker 3: that once that data is available, you get exactly the
Speaker 3: kind of algorithm captures that you find, right, And there
Speaker 3: is this.
Speaker 4: Like push towards clickbait.
Speaker 3: It's just like it's and it happens at many different
Speaker 3: levels individually it happens because journalists, like all communicators, and
Speaker 3: I include academics in that, they want to be read.
Speaker 3: What's the point of being a journalist if no one
Speaker 3: reads your stuff, you know what I mean? That's kind
Speaker 3: of an existential question. And so to me, it makes
Speaker 3: perfect sense that you would be like, well, I'm going
Speaker 3: to do everything in my power so that you know,
Speaker 3: my articles find the audience, right, and if that means
Speaker 3: putting a slightly more clickbaita title, so be it.
Speaker 1: And clickbaity is things like here's one weird thing you
Speaker 1: can do, and so what else.
Speaker 2: Do you see?
Speaker 3: Yeah, so at the time, Okay, so that's going to
Speaker 3: be a bit dated now because again this was you know,
Speaker 3: the bright days of the early twenty tents, right, but
Speaker 3: the big things where yeah, this one wheel trick you know,
Speaker 3: you'll never believe. You know, what happened next was shocking listicles.
Speaker 3: We're a big thing, right, like the ten best restaurants
Speaker 3: in San Francisco, you know kind of stuff. Slide shows too, right,
Speaker 3: because at the time, a lot of newsrooms were still
Speaker 3: counting page views, and so a slide show with ten
Speaker 3: pages counted as ten phage views. I know, it's really
Speaker 3: kind of a cheap trick, so kind of things like that, right,
Speaker 3: And you could see these formats becoming widely popular across
Speaker 3: newsrooms because newsrooms are also all watching each other and
Speaker 3: seeing especially at the time, it was Busfeed and the
Speaker 3: Huffington posts using these kind of more clickbaity tactics and
Speaker 3: getting the traffic numbers that were coming with from it,
Speaker 3: especially on Facebook and Twitter, and everybody was like, oh, okay,
Speaker 3: we've got to do this, right, So then a couple
Speaker 3: of things kind of happen. So first one, which is
Speaker 3: exactly what you said, is that you know, social media
Speaker 3: traffic and social media algorithms are fiical. They have gotten
Speaker 3: only morephical since, right, But they're opaque, so no one
Speaker 3: really understands what's getting recommended. And you know, platforms have
Speaker 3: given some modicum of information, but they also don't want
Speaker 3: users to gain the system, so they're not given that
Speaker 3: much information.
Speaker 4: Right.
Speaker 3: Then, social media platforms also made sudden changes over the
Speaker 3: years that really hurt newsrooms. For example, Facebook, at some
Speaker 3: point in the mid twenty tens decided that it was
Speaker 3: going to stop prioritizing posts and articles from news organizations
Speaker 3: and instead promote relatively more organic content, namely content coming
Speaker 3: from individuals, and that's where influencers started driving.
Speaker 4: But that's for a bit later.
Speaker 3: But so from one day to the next, basically you
Speaker 3: had like all news websites because traffic was like that,
Speaker 3: just like going way kind of further down, just because
Speaker 3: in one change in the Facebook algorithm that cut traffic
Speaker 3: can of in half for many newsrooms. Right, So it's
Speaker 3: fickle and things are changing, and what works well as
Speaker 3: a recipe for traffic at one point stops working, and
Speaker 3: everybody's kind of in the dark and trying to figure
Speaker 3: out what happens. So that's kind of the first problem.
Speaker 3: The second problem is that, you know, journalists, we're also
Speaker 3: thinking really hard about wait, like, if we follow what
Speaker 3: the algorithms want, we're only going to do tablauid news right,
Speaker 3: namely against sex, kndle celebrities that like, you know, it
Speaker 3: always people are always going to click more on that,
Speaker 3: you know, but this is not what our role is.
Speaker 4: At the end of the day. We became journalists because
Speaker 4: we care.
Speaker 3: About democracy, holding the state and the powerful accountable, about
Speaker 3: covering kind of longer stories, more complex stories, right, And
Speaker 3: so what I kind of observed during kind of all
Speaker 3: the time I spent in newsrooms is that basically journalists
Speaker 3: were torn between these different definitions of what their professional
Speaker 3: identity was about. On the one hand, they were like, well,
Speaker 3: we're professional communicating, so we want our stuff to be read,
Speaker 3: and so if clickbait has to happen, we will do
Speaker 3: it because it's important we want to reach our audience.
Speaker 3: But on the other hand, they were also saying, well,
Speaker 3: we care about sharing important things that will make our
Speaker 3: readers more enlightened citizens of the world. And so they
Speaker 3: were kind of always torn between these two kind of
Speaker 3: definitions and kind of moving back and forth. And what
Speaker 3: was fascinating that they would often do like funny little
Speaker 3: accounting things where they would do like, Okay, so I
Speaker 3: really want to write this article about say, you know
Speaker 3: again international news Ukraine, let's say, right, because I really
Speaker 3: think it's important and I think our readers need to
Speaker 3: know about this. But I know that people are not
Speaker 3: going to click a lot right, So to make up
Speaker 3: for it, I'm also going to write an article on't
Speaker 3: say Rhianna right, and that's going to boost my traffic numbers,
Speaker 3: And that way I've kind of subsidized my Ukraine article
Speaker 3: with the Rhanna article in terms of traffic, So they
Speaker 3: would do like all of these little deals with themselves
Speaker 3: to try to optimize both sets of kind of constraints.
Speaker 1: What was the equivalent of clickbait back in the day
Speaker 1: of newspapers, because there was what's called yellow journalism. I mean,
Speaker 1: there must have been ways that people are trying to
Speaker 1: get readers, and of course there were tabloid presses.
Speaker 3: Yeah, absolutely, so there were many equivalents, and so that's
Speaker 3: the same clickbait has always existed in many ways. So
Speaker 3: at the time, let's see, there was a lot of
Speaker 3: kind of as you say, yellow journalism, so extremely outrageous,
Speaker 3: like inflammatory, kind of aggressive headlines, you know, really kind
Speaker 3: of emphasizing kind of hatred right or like kind of xenophobia, bigotry,
Speaker 3: like you know, things like that have always existed in
Speaker 3: many newspapers over the past two centuries have really indulged
Speaker 3: in that because again it's like stokes kind of patriotic
Speaker 3: sentiments for example, and people are like, yeah, like you know,
Speaker 3: I'm gonna buy this newspaper. So that's kind of one aspect. Definitely,
Speaker 3: coverage of stars and celebrities, for example, at the time
Speaker 3: Sarah Bernhardt, you know, in the late nineteenth century was
Speaker 3: like the idol. All kind of teenage women were doing clippings,
Speaker 3: newspaper clippings of the actress Sarah Bernhart, that was the thing,
Speaker 3: and so newspapers would always put lots of pictures of her,
Speaker 3: so that like the news that teenage girls would do
Speaker 3: the clippings, you know, so they would force their parents
Speaker 3: to buy the newspapers so that they could do that.
Speaker 3: Same with lifestyle and kind of beauty advice, same things.
Speaker 3: That's always been very popular, cooking recipes, things like that,
Speaker 3: you know what I mean. So it's not new, it's
Speaker 3: just the shape it takes and the specific tricks that
Speaker 3: people use to capture the attention changes with the medium,
Speaker 3: you know what I mean, from print to broadcast to digital.
Speaker 3: But again I think it's a change in degree, not
Speaker 3: really a changing kind, if that makes sense.
Speaker 1: So when you published your book in twenty twenty, you
Speaker 1: were interested in this issue about clickbait and how people
Speaker 1: are getting sucked into this whirlpool of that. Now we're
Speaker 1: in twenty twenty six. So last year Oxford English Dictionary's
Speaker 1: word of the Year was rage bait, which is close
Speaker 1: cousins to clickbait tell us about rage bait.
Speaker 3: So rage bait I think of as a kind of
Speaker 3: like vengeful cousin of clickbait.
Speaker 4: Right, well, clickbait was.
Speaker 3: Still kind of light. You will never believe what happens next.
Speaker 3: You will be shocked ten weird tricks to whatever do something,
Speaker 3: you know. Rage bait is more about provoking you into
Speaker 3: kind of negative, kind of arousal, right, negative emotions such
Speaker 3: as anger, fear, hatred, again, not things that are radically new,
Speaker 3: but really kind of pushing on that. The typical example
Speaker 3: of rage bait is going to be an influencer or
Speaker 3: someone on the internet just stating something outrageous, right, or
Speaker 3: doing something outrageous but with complete confidence and innocence and
Speaker 3: not seeming.
Speaker 4: To see the problem.
Speaker 3: Right. So there are a number of examples of that.
Speaker 3: I mean, one of the ones that I like are
Speaker 3: like these weird cooking videos, but where they cook things like,
Speaker 3: for example, like in the bathroom using.
Speaker 4: The baths stub and doing like this is really.
Speaker 3: The most efficient way to cook pasta, things like that,
Speaker 3: and like kind of really going going fully in you
Speaker 3: know what I mean, and not acknowledging how weird it
Speaker 3: is to try to cook pasta in the bastub or
Speaker 3: whatever it is, or you know, I mean, there are
Speaker 3: lots of examples. And what's really interesting about this type
Speaker 3: of content is that it's typically produced by content creators
Speaker 3: who know very well that it's going to infuriate people, right,
Speaker 3: it's going to make them mad. But because it's going
Speaker 3: to make them mad, they're gonna engage with the content.
Speaker 3: They're gonna watch it, they're gonna comment on it, they're
Speaker 3: gonna share it, all kind of basically yelling insults, you
Speaker 3: know what I mean, and saying like how dare you?
Speaker 3: How could you use? This is so gross? I can't
Speaker 3: believe you.
Speaker 4: Are you a troll? Why are you saying this? How
Speaker 4: can you say this?
Speaker 3: But all of this obviously translates into revenues and engagement
Speaker 3: on social media platforms, and so that's very much a
Speaker 3: deliberate kind of content productions.
Speaker 1: When you think about rage bait, what percentage of that
Speaker 1: is political versus I hadn't thought about the cooking past
Speaker 1: of the bathtub.
Speaker 4: That's a good question.
Speaker 2: When I think about it.
Speaker 1: I think people saying things politically that are very inflammatory.
Speaker 2: But you I'm glad to see you have a broader
Speaker 2: view of rage based.
Speaker 4: I definitely have a broader view.
Speaker 3: I mean I think so, I think it's a continuum, right,
Speaker 3: always think about it is that it's really a spectrum
Speaker 3: from you know what psychologist called kind of high arousal
Speaker 3: negative content. Right, So that's going to be anything inflammatory, incendiary,
Speaker 3: shocking in a negative way. Right, wh It just makes
Speaker 3: you kind of freeze and it kind of bypasses whichever
Speaker 3: defenses you may have, and you're just like, this is
Speaker 3: serious and bad.
Speaker 4: I need to pay attention.
Speaker 3: Right, It's almost like an embodied response, right that just
Speaker 3: like shotcuts kind of a lot of the usual ways
Speaker 3: we have of interaction acting with media. So that's kind
Speaker 3: of one way. And then like rage bait, I think
Speaker 3: it's a bit of a wider kind of type of
Speaker 3: content because it also involves other kind of emotions such
Speaker 3: as like again discussed weirdness, like you know, a wider
Speaker 3: set of reactions that are also negative but are not
Speaker 3: necessarily about politics specifically.
Speaker 1: Now, does it make sense for anyone on social media
Speaker 1: to do clickbait and rage bait?
Speaker 2: Is it?
Speaker 1: Is it sensible? Or are we all sinking into a morass?
Speaker 4: This is such an excellent question.
Speaker 3: So it depends on the time and frame you're looking at.
Speaker 3: And again, to some extent, you know, this is a
Speaker 3: question that most kind of content creators have to deal
Speaker 3: with at this point, and it also kind of resembles
Speaker 3: the questions that newsrooms at the time had to deal with,
Speaker 3: but in a bit of a different way.
Speaker 4: So let me walk through that.
Speaker 3: So for content creators, it depends on how you monetize
Speaker 3: your online production, right, if you monetize it through platform payments,
Speaker 3: so things like the YouTube Partner program, right where if
Speaker 3: you qualify you have to have a channel that's kind
Speaker 3: of big enough, but if you do qualify, you can
Speaker 3: get fifty five percent of the advertising revenues that your
Speaker 3: videos gather. Right, So in that case, basically your revenues
Speaker 3: are going to depend on how many views you get
Speaker 3: and watch time, right Obviously, that's that's going to be
Speaker 3: the main thing. So in that case, rage bait in
Speaker 3: the short term amazing, right, because you're going to provoke
Speaker 3: people into watching you hook them in with something truly
Speaker 3: kind of atrocious, you know, or really kind of hair
Speaker 3: raising kind of kind of stuff that like makes it
Speaker 3: so that like you can't look away. Literally, it's like
Speaker 3: looking at a car crash, you know what I mean.
Speaker 3: You you kind of have to watch it just to
Speaker 3: see what's gonna happen next and which kind of insane
Speaker 3: things they are gonna be saying next, And then you
Speaker 3: keep on engaging true comments and sharing, et cetera, making
Speaker 3: them the video even more popular because that's what recommendation
Speaker 3: algorithms are gonna pick up on. They're gonna look at
Speaker 3: all of these engagement signals right, and they're gonna promote
Speaker 3: it more widely, making it go viral. So all of
Speaker 3: this is great for watch time. All of this is
Speaker 3: great for platform payments in the short term. Now the
Speaker 3: question is can you make a living for several years
Speaker 3: based on that type of content? And that's where it
Speaker 3: becomes a bit more complicated, because you see, you can
Speaker 3: shock people once, you can shock people twice, you can
Speaker 3: shock people three times. But then well, likely they're just
Speaker 3: gonna stop watching because gonna be like, oh, well that's
Speaker 3: that person doing the shocking thing again. But you know, avoi,
Speaker 3: I'm not going to click and I'm not going to
Speaker 3: give them that attention. So what I've seen kind of
Speaker 3: in my world is that often What happens is that
Speaker 3: over time, influencers or content creators move from only relying
Speaker 3: on platform payments and views and watch time as a
Speaker 3: way to kind of really make a living to becoming
Speaker 3: more either what I call gurus, so trying to really
Speaker 3: monetize their audience directly through especially donations subscriptions, and so
Speaker 3: that entails a slightly different way of relating to the
Speaker 3: audience and producing content where it's not so much rage
Speaker 3: baits and kind of this kind of negative shocking engagement,
Speaker 3: but it's more framing things as it's us against them, right,
Speaker 3: So basically saying I'm speaking truth to power, I'm saying
Speaker 3: things like it is, and you following me because you
Speaker 3: like that I'm uncensored. You like that I'm saying things
Speaker 3: is the way they should be said. And so if
Speaker 3: you want to support my mission, please subscribe to my channel,
Speaker 3: give me a donation, subscribe to my Patreon, and kind
Speaker 3: of support me financially. But it's a bit of a
Speaker 3: different thing than the rage base, you see what I mean,
Speaker 3: because it's more about loyalty at that point.
Speaker 2: Yeah, now you've studied that.
Speaker 1: You spend a lot of time studying influencers or content
Speaker 1: creators And am I correct that you see there's a
Speaker 1: lot of anxiety in that population.
Speaker 4: Absolutely.
Speaker 3: So that was kind of my next project after journalists.
Speaker 3: And you know the thing with journalists is that they
Speaker 3: themselves could see the writing on the wall and they
Speaker 3: were like, oh, we are all going to become influencers basically,
Speaker 3: and you know, it's something that newsrooms have been doing
Speaker 3: ever since. Basically they show more and more video content
Speaker 3: can of on their homepages, and they send kind of
Speaker 3: journalists to have more like journalist slash influencer profiles in
Speaker 3: order to try to reach young audiences on TikTok for example. Right, So, anyway,
Speaker 3: so just like, oh, so what about content creators? So
Speaker 3: I spent six years studying content creators and doing interviews
Speaker 3: with them, observing them as they were shooting videos and
Speaker 3: kind of producing them, doing interviews with brands, with platform employees,
Speaker 3: and just trying to understand the careers of influencers, right,
Speaker 3: and like, how do you make money as a content
Speaker 3: creator and more importantly, how do you keep on making
Speaker 3: money over time? Because it's one thing to make money
Speaker 3: for one year, it's another thing to make money and
Speaker 3: make a living and sustain yourself for five, seven, ten years,
Speaker 3: and so yeah, what I found basically is this big,
Speaker 3: like one of my first findings, is this big disconnect
Speaker 3: between what people imagine being a content creator is like
Speaker 3: and what the real reality of social media labor looks like.
Speaker 3: So almost everybody at this point thinks that being a
Speaker 3: content creator sounds like the most fun job in the world.
Speaker 3: In a recent survey from twenty twenty three, more than
Speaker 3: fifty percent of Americans said that they would like to
Speaker 3: become content creators. So this is a massive kind of
Speaker 3: pull on the collective imagination. Right, We're all like, oh
Speaker 3: my gosh, they're having so much fun. They get to
Speaker 3: follow their passions, they get to have an amazing life,
Speaker 3: to talk about what they care about. They kind of
Speaker 3: look great, right, They're just having so much fun. They're
Speaker 3: hanging out with their friends. I want to do that,
Speaker 3: and I want to have the money, the glory, the fame,
Speaker 3: the luxurious lifestyle that comes with it. And so what
Speaker 3: you see is more and more people entering into social
Speaker 3: media creation and trying to become an entrepreneur right and
Speaker 3: saying I want to be my own boss, I want
Speaker 3: to be a content creator, and I want to follow
Speaker 3: and of my passion took about the topics I'm truly
Speaker 3: interested in, and that my day job is not recognizing. Okay,
Speaker 3: so big pool, a big funnel that kind of brings
Speaker 3: in lots and lots of people to social media creation.
Speaker 3: What happens, though, is that it turns out making a
Speaker 3: living as a content creator is very hard. And why
Speaker 3: is it very hard? Well, mostly again because of social
Speaker 3: media algorithms and the fact that it's really hard to
Speaker 3: figure out what people want to watch and what platforms
Speaker 3: are rewarding in terms of content, right, and what's getting promoted,
Speaker 3: especially true recommendation algorithms and true feed algorithms that kind
Speaker 3: of gonna, you know, are going to present you with
Speaker 3: the most kind of viral and popular videos of the day.
Speaker 3: And so for content creators, what that means is that
Speaker 3: very often they're like, oh, well, you know, I'm going
Speaker 3: to try, right, And so they try. And let's say
Speaker 3: they get a bit of success at the beginning, right,
Speaker 3: and they have a couple of videos that go viral,
Speaker 3: and let's say they start kind of getting some followers,
Speaker 3: and so that looks pretty good, right, And let's say
Speaker 3: is they have brands that start coming to you and
Speaker 3: are like, oh, do you want to work with us, Like,
Speaker 3: we'll send you sunglasses, you know, and eventually a little
Speaker 3: bit of payment. But soon what happens is that, you know,
Speaker 3: creators realize that it's a twenty four to seven kind
Speaker 3: of job in the sense of in order for some
Speaker 3: of your videos to go viral, in order for your
Speaker 3: number of subscribers and followers to kind of keep increasing,
Speaker 3: which is what brands want to see. They want to
Speaker 3: be associated with accounts that are going up, not with
Speaker 3: accounts that are going down in terms of audience measurements.
Speaker 4: Right, you have to.
Speaker 3: Post videos all the time because most of these videos
Speaker 3: will not go viral, most of them will not find
Speaker 3: their audience, right. But you are kind of a production
Speaker 3: company of one person, and so that means that you
Speaker 3: have to post every day.
Speaker 4: And so again, what.
Speaker 3: I see in my interviews is creator saying I made
Speaker 3: myself sick. I try to post every day, twice a day,
Speaker 3: just to keep that rhythm. I was on my own
Speaker 3: in my bedroom and it just became too much. I
Speaker 3: just couldn't deal with it. So that's the first thing.
Speaker 3: It's a relentless rhysm. It's a rhythm that would be
Speaker 3: very hard for a TV network or like a newsroom
Speaker 3: to kind of keep doing. And we're talking here about
Speaker 3: people who are alone. They're like a company of one
Speaker 3: in their bedroom, right and just pushing themselves and saying, like,
Speaker 3: you know, I'm an entrepreneur, I.
Speaker 4: Have to make it work, right. So that's the first thing.
Speaker 3: The second thing that happens is that as they get
Speaker 3: kind of more popular and the size of their following
Speaker 3: kind of increases, most of them start receiving hate comments,
Speaker 3: right and start kind of facing the darker side of
Speaker 3: the internet. So at first they're like, oh, I love
Speaker 3: my community, I love my followers. We share the same
Speaker 3: passion for X topic, right, regardless whether the topic is
Speaker 3: like beauty or K pop or you know, DYI kind
Speaker 3: of you know, reroof your house. I mean, it doesn't matter.
Speaker 3: And they're just like, yeah, there are such good people,
Speaker 3: you know, We've become really close. I love them, they
Speaker 3: love me. We really get each other in this deep,
Speaker 3: authentic way.
Speaker 4: Right.
Speaker 3: But as your fame grows and as you start to
Speaker 3: make more and more money from social media production, suddenly
Speaker 3: something switches in the relationship with your followers. Namely, is
Speaker 3: that First, you can't keep track of all of them,
Speaker 3: so it becomes more of a faceless mass of people, right,
Speaker 3: and you know still a few of them from the beginnings, right,
Speaker 3: but most of them have just become numbers. That's the
Speaker 3: first thing. And second, negative feedback starts coming in. Typically,
Speaker 3: you're gonna get kind of hate comments, you're gonna get destreats,
Speaker 3: You're gonna get themeaning comments about your physical appearance or
Speaker 3: your mental health or whatever it is that you know
Speaker 3: comes up in your videos. You're going to get stockers,
Speaker 3: right who show up kind of in your hometown and
Speaker 3: perhaps show up at your doorstep. And suddenly you're just
Speaker 3: like wait, like wow, this is really taking a toll
Speaker 3: on me, because day after day you get both the
Speaker 3: good parts of the Internet and of that kind of
Speaker 3: public presence, but also the negative parts and the relentless
Speaker 3: like trolling, harassing, insulting, and everything that comes with it,
Speaker 3: and that takes such a heavy toll on the mental
Speaker 3: health of creators.
Speaker 4: That together with the pressure to publish all the time.
Speaker 1: And from your point of view, the change in the algorithms.
Speaker 1: I'm seeing this on X all the time lately, that
Speaker 1: creators are complaining, Hey, I was doing so well and
Speaker 1: they just change the algorithm. Now suddenly I'm getting shadow
Speaker 1: band or whatever term they're using for it.
Speaker 3: Yeah, so I have a whole thing about that. I mean,
Speaker 3: so basically, creators talk about the algorithm kind of all
Speaker 3: the time, and it's really interesting because it's always the
Speaker 3: algorithm singular. It's not like all the computational procedures of
Speaker 3: social media platforms, of which are many, right, because you
Speaker 3: have feed algorithms, you have recommendation algorithms, you have demonetization algorithms.
Speaker 3: So these are basically algorithms that if your video is
Speaker 3: deemed to be not family friendly or edgy, or going
Speaker 3: kind of being kind of a bit too close to
Speaker 3: kind of the edge of community guidelines in a range
Speaker 3: of way, you're going to get demonetized, which means that
Speaker 3: you won't get any money from the ads getting served
Speaker 3: on the videos. Right, So basically for content creators that
Speaker 3: means that they're not making money from that video, which
Speaker 3: is a big problem for them. And so that's like
Speaker 3: demonetization algorithms. And then you content moderation algorithms that are
Speaker 3: you know, along the same lines, but with more serious
Speaker 3: sanctions such as getting banned, for example, from a given
Speaker 3: platform because your content goes against the community guidelines of
Speaker 3: the platform. All of these algorithms are kind of changing
Speaker 3: all the time they are opake. There is no announcement
Speaker 3: of what's happening, right, and so creators are always kind
Speaker 3: of like basically putting their finger in the air and
Speaker 3: trying to see what does the algorithm want at any
Speaker 3: given point in time, right, and trying to intuit what
Speaker 3: the algorithm is looking for. And so that's already kind
Speaker 3: of quite a thing there. But then what I kind
Speaker 3: of argue kind of in my book is that in
Speaker 3: a way, the algorithm becomes a shortcut for a more
Speaker 3: complex set of actors that you know, influencers and content
Speaker 3: creators prefer not to think too closely about. So one
Speaker 3: things that content creators do is that they pomorphize the algorithm.
Speaker 3: So they keep on saying the algorithm is stupid, the
Speaker 3: algorithm is silly, the algorithm doesn't like me, or the
Speaker 3: algorithm really likes them. They got really friendly and close
Speaker 3: with the algorithm, right. So all of these ways of
Speaker 3: projecting human characteristics onto computational procedures that are obviously and
Speaker 3: to the best of our knowledge at this point like
Speaker 3: not sentient, you know what I mean, they do not
Speaker 3: have emotions. But what I argue is that this kind
Speaker 3: of process of anthropomorphism is really because so who is
Speaker 3: behind the algorithm? Social media companies, right, the alphabets, the meta,
Speaker 3: the tiktoks of the world right by dense Now who
Speaker 3: else is behind the algorithm?
Speaker 4: The audience?
Speaker 3: Right, I mean basically the algorithm just picking up on
Speaker 3: audience signals and now the algorithm, you know, for creators,
Speaker 3: blaming the algorithm for everything that goes wrong is a
Speaker 3: way to avoid blaming social media companies, which very often
Speaker 3: as the one paying them through partner programs, right, and
Speaker 3: audiences which also as the one supporting them through their
Speaker 3: clicks and their engagement.
Speaker 4: Right.
Speaker 3: So the algorithm is kind of a convenient scapegoat. And
Speaker 3: again not to say is that it's not unpredictable, opaque,
Speaker 3: and all of these things, But it's kind of a
Speaker 3: convenient kind of scapegoat for these broader kind of forces
Speaker 3: that really are responsible for the fortunes or lack of
Speaker 3: fortunes of content creators.
Speaker 1: By the way, just from a neuroscience point of view,
Speaker 1: we always have to do this with systems that are
Speaker 1: sufficiently complex, we reduce them to a person because that's
Speaker 1: what we're evolved to do, is understand other people.
Speaker 2: Yeah, try exactly, Yeah, yeah, exactly, So it's no surprise
Speaker 2: that people do that.
Speaker 1: I want to return to rage bait for a moment
Speaker 1: because one of the things I've been so interested in,
Speaker 1: and this is on a lot of my podcast, is
Speaker 1: about polarization and in groups and out groups and so on.
Speaker 1: And one thing that's hard not to notice is what
Speaker 1: I've been calling lately the fringe amplification effect, which is
Speaker 1: somebody on one side of the political spectrum makes a
Speaker 1: totally rage baby video that's just so extreme in their
Speaker 1: political view on it, and then the other side says,
Speaker 1: look what the other side is doing, and they stitch
Speaker 1: in that video and everyone.
Speaker 2: Gets to see that.
Speaker 1: So the videos that you know, one side gets to
Speaker 1: see of the other is the most extreme. Yeah, and
Speaker 1: that seems to be a real problem because that's driving polarization.
Speaker 4: But again, so I completely agree.
Speaker 3: I mean, I think so the way I kind of
Speaker 3: analyze this that all of these stems from the economic
Speaker 3: incentives of content creators. And so again we think a
Speaker 3: lot of it in terms of like political polarizations, right,
Speaker 3: and kind of deeply held beliefs, right about politics, all
Speaker 3: about religion, all about immigration, you know, you name it.
Speaker 3: But I guess I mean, I guess I'm a bit
Speaker 3: more cynical kind of in a way. And that's like
Speaker 3: the sociologist in me. I'm like, sure. But that's also
Speaker 3: because platforms have put in place economic incentives that basically
Speaker 3: encourage content creators to produce this kind of polarizing content.
Speaker 3: Again because of like the logic of engagement. So if
Speaker 3: you want people to engage with your content, the tendency
Speaker 3: and I've seen that in my interviews over and over
Speaker 3: and over again. Creators start by saying, Okay, I have
Speaker 3: one example. One of my case studies was vegan creators. Okay,
Speaker 3: you'll tell me vigan creators.
Speaker 4: How nice.
Speaker 3: Right, They're going to be talking about plant based eating.
Speaker 3: It's good for the planet, it's good for the animals,
Speaker 3: it's good for your health, you know, with kind of
Speaker 3: some precautions around it. So what could go wrong? How
Speaker 3: could that lead to polarization?
Speaker 4: Well, it turns out that, you know, almost.
Speaker 3: All the creators I talked about were like, well, okay,
Speaker 3: so there are a couple of really outrageous personalities that
Speaker 3: are extremely rage baity within the vegan kind of influencer world,
Speaker 3: and that basically just like attack other creators and other
Speaker 3: kind of people for how they are doing veganism wrong, right,
Speaker 3: so extremely kind of contentious, kind of like you're doing
Speaker 3: it wrong, this is not the right way of being
Speaker 3: kind of a vegan. What they also see is like
Speaker 3: the rise of extremely restrictive diets that become more and
Speaker 3: more niche, so typically FRUITIVL diets where you only eat fruits,
Speaker 3: or raw vegan diets where you only eat row fruits
Speaker 3: and veggies, or you know, things like that that become
Speaker 3: like increasingly niche and kind of extreme right. And what
Speaker 3: like all of my content creators were saying is that,
Speaker 3: And often I will add, the creators that are the
Speaker 3: most kind of outrageous also start kind of verging into
Speaker 3: conspiracy theories Q and non you know at the time
Speaker 3: Pizza Gates, I mean, you know, things where it's like,
Speaker 3: you know, really blaming the system for everything that goes
Speaker 3: wrong and saying like, oh, you should live off grid
Speaker 3: and be kind of on this extremely restrictive kind of
Speaker 3: vegan diet and everything kind of going together. And what
Speaker 3: like my you know, my more moderate interview is were saying,
Speaker 3: is like, listen, what you realize is that as soon
Speaker 3: as I start covering or reacting or responding or stitching
Speaker 3: one of these more extreme influencers and what they say,
Speaker 3: my number of views and my watch time go way
Speaker 3: up because basically everybody wants to read that, Zaka, You're
Speaker 3: going to take down that outrageous influenza. Yes, please, like
Speaker 3: you know, I'm going to watch it. And so what
Speaker 3: they were saying my more moderate kind of you know,
Speaker 3: vegan creators, is that it's really a slippery slope towards
Speaker 3: more aggressive, more incendiary, more extreme kind of content. And
Speaker 3: even if you start kind of somewhere in the middle,
Speaker 3: after months and months of producing videos and seeing what
Speaker 3: performs well with the algorithm and audiences and kind of
Speaker 3: you know, social media platforms, you kind of go more
Speaker 3: towards polarized content. It's just kind of what the system
Speaker 3: is designed to kind of reward you for. And so,
Speaker 3: you know, we've had social media now for ten to
Speaker 3: fifteen years, and what you see is this kind of
Speaker 3: war of all against all. But that's in part because
Speaker 3: of these economic incentives you know.
Speaker 2: Let me ask you this.
Speaker 1: So in the world of let's say, stand up comedy,
Speaker 1: young comedians find that if they do a lot of cussing,
Speaker 1: that gets them a lot of attention. But then you
Speaker 1: have comedians like let's say Jerry Seinfeld who never cussed
Speaker 1: and just kept slow and steady and did did his
Speaker 1: thing without blue material and got really successful. What is
Speaker 1: is there an equivalent in the algorithmic world.
Speaker 3: So it's really interesting because that's that's a very good point, right,
Speaker 3: And I mean I think that in general, you have
Speaker 3: this moderating force a bit like my journalist at the time,
Speaker 3: you know what I mean that even as some of
Speaker 3: them are going the road of clickbait, there was also
Speaker 3: a significant kind of pushback, you know, saying this is
Speaker 3: not who we are, you know, and this is not
Speaker 3: what we care about. And at the end of the day,
Speaker 3: I became a journalist for different reasons, not to cover
Speaker 3: like you know, X scandal, like this kind of tableauid
Speaker 3: manner day after day with influences. What I do find,
Speaker 3: and it is kind of interesting because it's you know,
Speaker 3: slightly different, is that there is a moderating force, but
Speaker 3: it's not a neutral one. The moderating force is brands
Speaker 3: and sponsored content. So, as an influencer, how do you
Speaker 3: make money? Either you do platform.
Speaker 4: Payments, right, and you receive money.
Speaker 3: Directly from meta or YouTube or TikTok based on the
Speaker 3: number of views and the watch times that your videos get.
Speaker 3: Oh the kind of actually the main way which influencers
Speaker 3: make money is by contracting with brands to promote whatever
Speaker 3: the brand is doing and kind of promoting it kind
Speaker 3: of in their videos, in their posts to their followers. Now,
Speaker 3: what's interesting about that? And you know, for anyone who
Speaker 3: kind of knows a bit about advertising, it's not that surprising.
Speaker 3: But brands hate polarization, They hate scandals because they want
Speaker 3: to appeal to the wider possible customer base that's out there,
Speaker 3: and they do not want to be associated with things
Speaker 3: that could raise red flags among their customers or for
Speaker 3: that matter, amongst their boards or you know kind of
Speaker 3: financial kind of stakeholders.
Speaker 4: Right.
Speaker 3: And so what I find is that over time you
Speaker 3: kind of see two different profiles of content creators that emerge.
Speaker 3: You have the ones who really depend on virality, and
Speaker 3: they are gonna go more and more extreme. It's really
Speaker 3: hard to fight against that. Again, there are some exceptions,
Speaker 3: but it's just really hard to fight against it because
Speaker 3: everything pushes you in that direction. It's like not nuge
Speaker 3: after nudge. But you have a second category where they
Speaker 3: go mostly towards branded content, right, and for people who
Speaker 3: go more the route of sponsored content and working with brands,
Speaker 3: actually avoiding any whiff of you know, scandal, harassment, polarization,
Speaker 3: anything and of outrageous is really important because otherwise brands
Speaker 3: are gonna stop working with them and they're gonna lose revenues.
Speaker 3: So you do have these different polls there.
Speaker 1: So is that enough of a force that we can
Speaker 1: have hope that we won't just sink completely into clickbait
Speaker 1: rage bait world? Or are there things that social media
Speaker 1: companies can do, slash should do, slash might do someday
Speaker 1: that would change this?
Speaker 4: This is an excellent question.
Speaker 3: So I think brands in themselves are not enough for
Speaker 3: two reasons. First, because you know, especially over the past
Speaker 3: year and a half, brands themselves have become politically polarized. Right,
Speaker 3: So you have big companies taking sides on one side
Speaker 3: or the other, and especially I mean I'm thinking on
Speaker 3: the kind of conservative side. The number of brands have
Speaker 3: aligned with you know, extremely misogenistic, anti immigrant and violent
Speaker 3: forms of content on social media and actually take pride
Speaker 3: in it because they're like, these are going to be
Speaker 3: our markets, right.
Speaker 2: Like, which brands can so right now.
Speaker 3: Actually I forget them, and I remember there is a
Speaker 3: coffee brand that's like specifically marketed like you know, far right,
Speaker 3: and they're basically like, yeah, the more extreme the better.
Speaker 4: This is where we want to advertise.
Speaker 3: This is the audience we want to get, and so
Speaker 3: they're kind of finding a bit of a niche market there.
Speaker 1: I mean, presumably there's brands on the lab Yeah.
Speaker 3: Definitely obviously like brands on the left to our costco right,
Speaker 3: like also kind of becoming more aligned with kind of
Speaker 3: you know, liberal kind of attitudes kind of in recent years,
Speaker 3: so you know, you do have you do see kind
Speaker 3: of that the transformations of politics, in part with social media,
Speaker 3: are also affecting brick and mortar kind of companies, right
Speaker 3: that themselves kind of end up having to pick aside
Speaker 3: a bit more. So that's not so good, right in
Speaker 3: terms of reducing polarization. If anything, it might be that
Speaker 3: like this is the future we're moving towards.
Speaker 4: So that's the first thing, become.
Speaker 2: Part of your identity to drink this coffee.
Speaker 3: I'll go to that supermarket, right, So that's kind of
Speaker 3: that's kind of one one way, So that's not perfect.
Speaker 3: The second thing with brands is that you know, again
Speaker 3: brands hate politics in general, right, most brands hate politics.
Speaker 3: And do we want content creators who i are incredibly
Speaker 3: incendiary and politicized or are not politicized at all, you
Speaker 3: know what I mean? You also probably want a healthy
Speaker 3: middle of people who are voicing kind of political questions
Speaker 3: and concerns and kind of hashing it out kind of
Speaker 3: on social media in a respectful and civic way. But
Speaker 3: this is not what brands want. Most brands again, do
Speaker 3: not really want that. So it's not perfect. I think
Speaker 3: for me, you know, thinking about what could be done,
Speaker 3: it's a complicated thing. And as often, you know, social
Speaker 3: scientists are very good at kind of diagnosing what's going wrong,
Speaker 3: but less good as saying like and this is what
Speaker 3: we should do now. But I am kind of mildly
Speaker 3: optimistic about subscription systems.
Speaker 4: I mean, you know, I'm thinking.
Speaker 3: Of substack, for example, where you know, a lot of
Speaker 3: content creators, a lot of writers, have kind of gone
Speaker 3: so low right and created newsletters on substanles and monetizing
Speaker 3: that true kind of annual subscriptions. What I like about
Speaker 3: that is that these kinds of annual subscriptions do not
Speaker 3: create exactly the same kind of incentives as clickbait, right,
Speaker 3: because you have your loyal audience and you want to
Speaker 3: keep on delivering quality content for them, right, And so
Speaker 3: again it's a bit more like traditional newspapers and memberships.
Speaker 3: It's like you kind of have a sense of who
Speaker 3: your loyal audience is and you're trying to do the
Speaker 3: best you can for them.
Speaker 4: And so I see that as like, you know, one
Speaker 4: way in.
Speaker 3: Which the incentives are a bit different, But then it
Speaker 3: also raises lots of questions.
Speaker 1: So I think it's a really good point about substack.
Speaker 1: But not knowing the numbers of the time ahead, I
Speaker 1: have to imagine that substack is so much smaller than
Speaker 1: say TikTok or Instagram. What do you see if you're
Speaker 1: thinking five ten years out about the future of this.
Speaker 1: Presumably short form media is going to stay around. I
Speaker 1: think people love the choice involved in it.
Speaker 2: Is anything going to change in some meaningful way?
Speaker 3: So one of the big changes that has happened over
Speaker 3: the past ten years and which I think is going
Speaker 3: to continue. And it's a fascinating change because it's one
Speaker 3: that social media companies never talk about, is that average
Speaker 3: people have stopped sharing on social media, normal regular users.
Speaker 3: The bets that may Facebook successful, right, which was like
Speaker 3: you were going to connect with your friends and share like,
Speaker 3: you know, pictures of you, like whatever, going to the
Speaker 3: coffee shop or like having kind of a moment of
Speaker 3: you know, going skiing. The average, like the percentage of
Speaker 3: kind of overall content that comes from people who are
Speaker 3: not professional producers has gone from like, you know, eighty
Speaker 3: percent to like less than five percent over the past
Speaker 3: ten year. It's something on which like it's really hard
Speaker 3: to find data because social media companies do not publicize
Speaker 3: that because again, part of their appeal is like, oh,
Speaker 3: you may once in a while you are going to
Speaker 3: see content from your friends, right, And that's kind of
Speaker 3: that was the whole goal of social media platforms in
Speaker 3: the beginning, right. But this is not what you see
Speaker 3: on social media now. What you see is professionally produce
Speaker 3: content by kind of influencers and creators who make a
Speaker 3: living from their production.
Speaker 1: It's like cable television where you have lots of production companies,
Speaker 1: lots of channels, and and they've gotten quite good. I mean,
Speaker 1: the content is extraordinary. I wonder if they'll have to
Speaker 1: change the name social media at some point because it's not.
Speaker 3: Really that that's exactly the point, right. So I think
Speaker 3: that if you look at the ten years like to come, right,
Speaker 3: you're going to see this decline of like just friends content,
Speaker 3: organic you know, non monetized content is going to keep
Speaker 3: on declining because you know, who to share a poorly
Speaker 3: shot picture of themselves when you have the Kardashians kind
Speaker 3: of next to you, or for that matter, like all
Speaker 3: content producers who are doing quality, high quality videos and
Speaker 3: posts rights, I mean, you should, just you don't really
Speaker 3: want to do that, and it doesn't feel like the
Speaker 3: space for it either. So that my question is like, well,
Speaker 3: are people going to stay on social media or you know,
Speaker 3: are the way in which they interact with social media
Speaker 3: going to be the same if it's all professional content
Speaker 3: producers ten years from now? And I guess I do
Speaker 3: think that things are going to have to change when
Speaker 3: we get closer to exactly what you are talking about,
Speaker 3: which is more of a cable television system, except that
Speaker 3: you have like, you know, five hundred million channels, you
Speaker 3: know what I mean, not thirty.
Speaker 2: And you have the option and you have the option
Speaker 2: to swipe right.
Speaker 3: But I do think that for platforms, once that's kind
Speaker 3: of clarifying, and once people kind of understand that, you know,
Speaker 3: we're not in the world that Facebook created circa like
Speaker 3: two thousand and you know ten, we're already in the
Speaker 3: world that's closer to cable television, where you get, like again,
Speaker 3: this infinite kind of array of professional production on an
Speaker 3: infinite array of topics. I do think that things will
Speaker 3: get clearer, you know what I mean, Or that both
Speaker 3: the economic incentives, the algorithmic infrastructure, and the expectations of
Speaker 3: the audience are going to change, But I don't exactly
Speaker 3: know in which directions.
Speaker 1: Yeah, we're really just in the adolescence of all these platforms.
Speaker 1: This is so new, and I'm really interested in what's
Speaker 1: happening with politics. I mean, it's clear that we're very
Speaker 1: polarized now. I do want to say so you and
Speaker 1: I are both very interesting in how algorithms play a
Speaker 1: role in that. I do want to say that people
Speaker 1: have always been polarized, and if you just look at
Speaker 1: let's say last century twentieth century, the polarization was so
Speaker 1: extreme that hundreds of millions of people were killed by
Speaker 1: their neighbors, whether that's Nazi Germany or the Chinese and
Speaker 1: Russian Communist revolutions, or Rwanda with the Tutsi against the Hutu,
Speaker 1: or in Cambodi with Paul pot What. It doesn't mean
Speaker 1: people always are very prone to get polarized. So I
Speaker 1: don't think it can be blamed on social media. But
Speaker 1: I am hopeful that if we sort of get out
Speaker 1: of our hormonal adolescence with these platforms, we can at
Speaker 1: least calm things down a little bit.
Speaker 2: What are your thoughts on that?
Speaker 3: I agree, I mean, I think polarization. You know, I
Speaker 3: think for the past twenty years there has been and
Speaker 3: I mean pre dating social media, there has been this worry,
Speaker 3: right that polarization is increasing, and I agree with that. Historically,
Speaker 3: it's a bit of a myopic view, right in the
Speaker 3: sense that again, this very long history and as you
Speaker 3: as you were saying, extremely deadly of kind of people
Speaker 3: hating each other with such faults that it led to
Speaker 3: actual civil war or kind of revolutions, et cetera.
Speaker 4: So that's kind of point number one.
Speaker 3: I agree also that social media is not the only culprits.
Speaker 4: There is no doubt about that.
Speaker 3: There are a number of other forces at stake, including
Speaker 3: a big kind of macro economic and socio demographic transformations
Speaker 3: in the United States among other places. But you know,
Speaker 3: in many countries that everybody is just kind of grappling with,
Speaker 3: right and with the role of technology in society. And
Speaker 3: I also think that social media really doesn't help, right
Speaker 3: in the sense of, like, again, it's not like it's
Speaker 3: not the only culprit, it's not the only cause, but
Speaker 3: it is enough to kind of tilt, you know, the
Speaker 3: thing from a three, four to six, seven.
Speaker 4: You know, on the scale of zero to ten.
Speaker 3: And what I find is that it's not only polarization,
Speaker 3: it's also this kind of like twenty four to seven
Speaker 3: news reism, which you know, if you look at that
Speaker 3: kind of the timeline of kind of news production. Again,
Speaker 3: it's a longer history, right in a way it started
Speaker 3: with cable television, right that we're broadcasting twenty four to seven,
Speaker 3: you know, so it has a longer history. But certainly
Speaker 3: the reactivity of social media the fact that you can
Speaker 3: post a video just right when it's happening, the fact
Speaker 3: that you can live stream. All of these development just
Speaker 3: means that the ReSm of kind of news, kind of
Speaker 3: circulation and reaction and reaction to the reaction has just
Speaker 3: accelerated so much. And you see that it has definitely
Speaker 3: changed politics as well. I mean, political life used to
Speaker 3: be pretty subdued kind of business. Like the reasm, for example,
Speaker 3: of Congress is a very slow ReSm, as is the
Speaker 3: judicial ReSm. You know, the time for the Supreme Court
Speaker 3: to make decisions a long time ago that was taking
Speaker 3: like literally years, you know, and now we're just like
Speaker 3: kind of in this you know, puff puff puff, kind
Speaker 3: of every second there is a new kind of thing
Speaker 3: that is even more shocking than the previous one.
Speaker 4: And that you know, you can't help but kind of
Speaker 4: see that.
Speaker 3: It is correlated with the affordances of social media platforms. Right,
Speaker 3: and so the question then is are we gonna are
Speaker 3: we gonna move towards kind of a more stable kind
Speaker 3: of reason. Well, as you said, it's like, I think
Speaker 3: the parallel with adolescence is really interesting that right now
Speaker 3: it's like everything's running really high, you know, what I mean,
Speaker 3: and everything's gonna kind of came down a bit. And
Speaker 3: I think that for that we need to turn to
Speaker 3: kind of technology companies and just say, like, what are
Speaker 3: the incentives that you've created for people to post, right,
Speaker 3: and what are the guard rails that you're putting in place.
Speaker 3: And again this is not to blame social media companies,
Speaker 3: because it's really hard business. Like hundreds of millions billions
Speaker 3: of people are interacting with this algorithmic structure, right, and
Speaker 3: trying to kind of, you know, adjust things for that
Speaker 3: scale of kind of people. It's just incredibly hard. And
Speaker 3: so they are also on a learning curve, just like
Speaker 3: the rest of us are. So they're trying in some
Speaker 3: cases to do the right thing. In other cases, they're
Speaker 3: also making decisions that are kind of irresponsible, right For example,
Speaker 3: you know, getting rid of content moderation guidelines, I mean
Speaker 3: you kind of know that that's going to encourage like
Speaker 3: much more kind of heinous, hateful behavior. Again because that
Speaker 3: not necessarily because creators believe in that heinous and hateful content,
Speaker 3: but because that's what's going to capture the engagement and
Speaker 3: attention of online audiences. And so I do think that
Speaker 3: social media platforms at this point are at a bit
Speaker 3: of a crossroad in terms of, like, so you have
Speaker 3: become the key infrastructures for kind of media and communication,
Speaker 3: what are you going to do. Are you going to
Speaker 3: keep on chasing engagement at all costs right potentially kind
Speaker 3: of destroying everything in your wake, or are you going
Speaker 3: to start looking at the long term satisfaction? The long
Speaker 3: term kind of benefits a long term outview of what
Speaker 3: you can do for your customers. And I really think
Speaker 3: it's kind of a short term, long term kind of
Speaker 3: trade offs that's happening right now, and I really hope
Speaker 3: that the long term considerations are going to gain traction.
Speaker 1: I love that, And I feel like social media companies
Speaker 1: don't necessarily have the economic incentive to do that unless
Speaker 1: one can stand out by saying we're going to take
Speaker 1: less advertiser revenue for the purpose of making a better
Speaker 1: community here.
Speaker 2: And I think they can really stand that that way.
Speaker 4: I agree.
Speaker 3: I mean, I think a couple of things that are
Speaker 3: pretty obvious. I mean another one and again, and I mean,
Speaker 3: I know that it's not necessarily a popular recommendation, but
Speaker 3: we kind of got used to getting stuff for free.
Speaker 3: Audiences Also, have to change, We all have to change,
Speaker 3: and we kind of have to be willing to pay
Speaker 3: for access to social media platforms because you see, if
Speaker 3: we all had kind of subscriptions, well, that would kind
Speaker 3: of reduce the part of advertising right in the kind
Speaker 3: of overall revenues of social media companies, So they wouldn't
Speaker 3: be chasing engagement metrics in quite the same way, so
Speaker 3: they wouldn't be putting quite the same incentives in place
Speaker 3: for content creators, and so everything would look a bit different.
Speaker 4: You know what I mean.
Speaker 3: So part of this is also due to the advertising
Speaker 3: only or advertising mostly revenue structures of social media companies.
Speaker 3: And I do think that all of us, as customers,
Speaker 3: as audiences, as participants, we also have kind of a
Speaker 3: role to play in saying, like, you know, we should
Speaker 3: would be willing to pay for this service. And again,
Speaker 3: it raises lots of questions about access democratization.
Speaker 4: You know, there are lots of it.
Speaker 3: It's not an easy debate to have, but I think
Speaker 3: it's a debate for us having because a lot of
Speaker 3: what's going wrong right now comes from this original I mean,
Speaker 3: I don't want to call it an original sin, but
Speaker 3: this original deal right that advertising was going to be
Speaker 3: funding social media period. Yeah, and that is not the
Speaker 3: healthiest way to kind of make a living as a company.
Speaker 1: That was my conversation with Angel Christen, and what we
Speaker 1: talked about today was this notion of algorithmic capture, which
Speaker 1: is the gradual reshaping of behavior in response to opaque
Speaker 1: systems that reward certain choices and ignore others. If you
Speaker 1: zoom out far enough, you can see that we are
Speaker 1: living inside a huge experiment. Billions of brains, billions of
Speaker 1: feedback loops, billions of tiny reinforcements happening every second. And
Speaker 1: in this environment, some headline performs well, or some video
Speaker 1: sparks outrage and multiplies. Maybe a creator feels the uplift
Speaker 1: of attention. Maybe a newsroom watches a dashboard climb or
Speaker 1: stall out, and gradually everybody's behavior adapts. So, as we
Speaker 1: heard from Anzell, she studies journalists who entered the field
Speaker 1: with a sense of civic mission, or content creators who
Speaker 1: began with passion for a topic or a community. And
Speaker 1: by the way, this is just as true with lots
Speaker 1: of professions. Maybe a musician who enters wanting to create
Speaker 1: something really new, and then the metrics arrive and suddenly
Speaker 1: they're dealing with the gravitational pull of the algorithm. I
Speaker 1: just want to zoom out for one second. As you'll
Speaker 1: know if you've listened to a lot of these episodes.
Speaker 1: Lea's pointing out that polarization predates social media by millions
Speaker 1: of years, and obviously, any cursory reading of history will
Speaker 1: tell you that outrage predates the Internet. Newspapers in the
Speaker 1: nineteenth century, for example, they ran inflammatory headlines. This was
Speaker 1: known as yellow journalism, and this all thrived long before
Speaker 1: Wi Fi. Human attention has always been drawn to scandal
Speaker 1: and spectacle and celebrity, but the scale of the quantification
Speaker 1: of today's systems do introduce a new texture to public life.
Speaker 1: Everything accelerates, the incentives intensify, and presumably the emotional temperature rises.
Speaker 1: But I do want to say, as a techno optimist,
Speaker 1: that nothing here is inevitable. Incentives can be redesigned, Revenue
Speaker 1: models can and will evolve, Platforms can make different trade offs,
Speaker 1: audiences can decide what there willing to pay for, and
Speaker 1: creators can choose which signals they respond to. None of
Speaker 1: this is simple, but it is important to realize that
Speaker 1: we are in the earliest chapters of a story about
Speaker 1: how human psychology interfaces with computational systems. We are in
Speaker 1: the infancy phase of a technology that now functions as infrastructure.
Speaker 1: So the next time you feel outrage when you're scrolling around,
Speaker 1: or you see a headline that's engineered to hook you,
Speaker 1: or you watch numbers tick upwards somewhere on a screen,
Speaker 1: just pause for a second to ask yourself, what behavior
Speaker 1: of mine is getting reinforced, what is being trained? How
Speaker 1: do I want to participate in the system a little
Speaker 1: more thoughtfully? Understanding the machinery just gives you a little
Speaker 1: more agency inside of it, and that might be one
Speaker 1: of the most important skills for living in this second quarter.
Speaker 2: Of the twenty first century.
Speaker 1: Go to Eagleman dot com slash podcast for more information
Speaker 1: and to find further reading. Join the weekly discussions on
Speaker 1: my substack, and check out and subscribe to Inner Cosmos
Speaker 1: on YouTube for videos of each episode and to leave
Speaker 1: comments until next time. I'm David Eagleman, and this is
Speaker 1: Inner Cosmos.