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Speaker 1: If you have your own story of being in a

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Speaker 1: cult or a high control group.

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Speaker 2: Or if you've had experience with manipulation or abusive power

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Speaker 2: that you'd like to share.

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Speaker 1: Leave us a message on our hotline number at three

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Speaker 1: four seven eight six trust.

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Speaker 2: That's three four seven eight six eight seven eight seven eight,

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Speaker 2: or shoot.

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Speaker 1: Us an email at trust Me pod at gmail dot com.

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Speaker 3: Trust me, trust me.

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Speaker 1: I'm like a swat person.

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Speaker 2: I've never lived.

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Speaker 1: To you, never a live.

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Speaker 2: If you think that one person has all the answers,

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Speaker 2: don't welcome to trust Me. The podcast about cult, extreme

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Speaker 2: belief and manipulation from two troll dolls who actually experienced it.

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Speaker 2: I'm Lo La Blanc and I'm Megan Elizabeth. Today our

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Speaker 2: guest is Chris Baale. He's a professor of sociology and

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Speaker 2: public policy at Duke University, where he directs the Polarization

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Speaker 2: Lab and studies political tribalism, extremism, and social psychology using

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Speaker 2: computational social science. That is a mouthful. He'll talk to

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Speaker 2: us about this idea of the echo chamber and why

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Speaker 2: it doesn't work the way we think it does, how

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Speaker 2: our needs for identity and community factor into extremism, and

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Speaker 2: how there aren't as many extreme thinkers as the Internet

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Speaker 2: makes us think.

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Speaker 1: We'll get into what the online trolls he met are

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Speaker 1: like in real life, and they're not crazy. How our

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Speaker 1: attraction to narcissists is part of the problem, what a

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Speaker 1: better social media could look like, and lots more.

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Speaker 2: Indeed, lots of food for thought in this one. Before

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Speaker 2: we dive in, Megan, I would like to know what's

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Speaker 2: the cultiest things happened to you?

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Speaker 1: Okay, I'm really stuck on the Raja versus Kim Kardashian

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Speaker 1: urama that's going on right now, and I really don't know.

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Speaker 1: I mean, the more you look into it, the more

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Speaker 1: confused I kind of get. But from what I can gather,

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Speaker 1: Raja is saying, Kim Kardashian and her mother helped sell

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Speaker 1: the tape. Her mom actually picked which tape she thought

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Speaker 1: made Kim look the best.

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Speaker 2: That's true.

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Speaker 1: That is so creepy, so creepy, and I think it

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Speaker 1: is true. I'm sorry I do. But what happened is

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Speaker 1: Christian Or just went on the James Gordon Show and

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Speaker 1: took a lie detector test to say no, I didn't

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Speaker 1: do that. But then ray Ja is saying, but that

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Speaker 1: guy doing the lie detector is a is a fraud.

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Speaker 1: And then I looked it up and it is like

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Speaker 1: he gets he's a paid performer. He has all these

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Speaker 1: lawsuits against him, he has accreditation. Yeah, so for what

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Speaker 1: for for like not for not doing it right or

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Speaker 1: for you know, like I said, I would really need

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Speaker 1: to study this to make a strong strong point on it.

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Speaker 1: But it is this very cult of Kardashian versus like

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Speaker 1: fake doctors versus all of the bullshit, and I'm very

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Speaker 1: curious into what is what's gonna happen.

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Speaker 2: Well, also, can we talk about the fact that light

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Speaker 2: detector tests are like not real?

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Speaker 1: Yeah, like they're not real to begin with.

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Speaker 2: Yeah, Like it measures how much like anxiety you're feeling

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Speaker 2: in a given moment, which is a very easy thing

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Speaker 2: to cheat or be wrong, fake or whatever. I mean,

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Speaker 2: that's this isn't like a reliable science. So the idea

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Speaker 2: that we're presenting it at all as though it's a

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Speaker 2: reliable science is so silly.

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Speaker 1: Yeah.

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Speaker 2: I mean, granted, James Corden is you know, a comedy.

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Speaker 1: Show, great for sure, but I feel like ray J

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Speaker 1: has been you know, he's been pretty ruined by this

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Speaker 1: scandal and they got a lot from it, and I

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Speaker 1: feel kind of bad for him. But again, like I said,

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Speaker 1: I this could be an Amber heard Johnny Depp kind

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Speaker 1: of thing where people have spent their whole entire day studying.

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Speaker 1: And I'm way wrong and I don't know, but from

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Speaker 1: where I'm sitting, I'm like, that was shitty.

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Speaker 2: There's a compelling case being made. I don't know ray

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Speaker 2: j I don't know his character, I don't know the Kardashians,

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Speaker 2: but there it is interesting that they've never I was reading,

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Speaker 2: they've never outright said that it was stolen or against

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Speaker 2: their will. Like they've never literally said that, which you'd

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Speaker 2: think you would say if it were stolen the way

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Speaker 2: Pamela Anderson's tape was stolen. Right, So that's interesting either way.

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Speaker 2: If I have a sex daye. But I'm not showing

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Speaker 2: that shit to my mom.

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Speaker 1: No, And if my mom was like, let me watch it,

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Speaker 1: I'd be like, you're insane. Yeah, anyhow, what about you?

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Speaker 1: What's the cult dance thing that happened to you this week?

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Speaker 2: Okay, we're going to take a tonal shift here. Right.

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Speaker 2: My dog died. Oh no, my dog died a week

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Speaker 2: ago today. Maybe little Rambo died, and it's just I'm

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Speaker 2: not even I don't even know exactly if this is culty,

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Speaker 2: but I'm going to try to tight end because I

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Speaker 2: think it's just sort of interesting. I so he was

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Speaker 2: almost sixteen, and he has been ill in various ways

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Speaker 2: for like years, like multiple medications. It's just like a

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Speaker 2: lot of work taking care of him. And I love

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Speaker 2: him so fucking much. And I was like in my

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Speaker 2: head when I lost him, it was going to ruin

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Speaker 2: my life. It was going to just absolutely destroy me,

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Speaker 2: and I wasn't gonna be able to handle it, probably

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Speaker 2: because like when he would first get sick, I like,

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Speaker 2: you know, it was like the pandemic or I had

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Speaker 2: just gotten out of a breakup or whatever, and I

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Speaker 2: was like, I can't lose him. I can't lose them.

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Speaker 2: I can't lose him. And now I think it's his

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Speaker 2: little gift to me. If I were a magical thinker,

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Speaker 2: I would say, it's this little gift to me that

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Speaker 2: he waited until I'm in a relationship and my partner

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Speaker 2: lives with me now and I feel a lot more

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Speaker 2: like just capable of handling it to the point where

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Speaker 2: I'm There have been moments where I'm like, is it

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Speaker 2: wrong that I'm it's okay? Like should I not be

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Speaker 2: this okay? Like I'm obviously sobbing, Like every day I

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Speaker 2: have a crying fit because I see you a little

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Speaker 2: empty bed. But you were he was he.

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Speaker 1: Took so much medicine every morning, he was so much better.

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Speaker 1: You loved him and you knew he had to go.

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Speaker 2: Yeah, I mean it was sudden, but it was also

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Speaker 2: so not sudden, you know, And like, yeah, I think

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Speaker 2: I'm mentally prepared for it to be this life alteringly

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Speaker 2: horrible thing for so long that when it actually happened,

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Speaker 2: I was like, oh, I can handle this. That's weird,

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Speaker 2: can actually handle this.

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Speaker 1: It's interesting. My dad's dad actually died last week and

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Speaker 1: we went to go get Mexican food after and he

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Speaker 1: was like, I feel bad. I feel kind of good

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Speaker 1: right now, Like I'm okay. I don't know. I think

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Speaker 1: it's just because he just is like happy that he's

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Speaker 1: out of pain.

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Speaker 2: I don't you know, well, I think there really is.

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Speaker 2: We don't really realize how much stress is just sort

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Speaker 2: of lingering in the background on us all the time

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Speaker 2: when something or someone that we love is sick and

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Speaker 2: like just not doing well and we're sort of always

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Speaker 2: anticipating that's going to happen. Of course, I've heard so

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Speaker 2: many people say when their dog finally died or their

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Speaker 2: mom final or whatever, like it's still like devastating. Everyone

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Speaker 2: has a totally different.

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Speaker 1: Reaction, and it can be way worse than of course.

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Speaker 2: Of course, it can be so much worse. And I

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Speaker 2: know so many people for whom it was but for me,

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Speaker 2: and I'm saying this now, but like watching a week,

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Speaker 2: I'm like, I can't handle it, you know, But it

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Speaker 2: is interesting to see, like, oh, my worst fear happened,

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Speaker 2: and I'm gonna be okay. I love that, which makes

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Speaker 2: me think, like, Okay, there's probably a lot of other

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Speaker 2: bad things that will happen, and that I like, I

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Speaker 2: will be okay even if I'm not as okay as

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Speaker 2: I am right now. And it just it does destroy me,

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Speaker 2: like I don't I will lose my mind when my

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Speaker 2: mom dies. I like can't, I can't even think about it.

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Speaker 2: But it also gives me a little bit more confidence

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Speaker 2: that I'm like, okay, I can weather these storms that

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Speaker 2: life is going to.

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Speaker 1: Hit me with.

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Speaker 2: Yeah, and all tied into cults by saying we can

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Speaker 2: all get through anything.

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Speaker 1: I mean, I think leaving them it feels like it's

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Speaker 1: going to destroy you. It feels like there's no way

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Speaker 1: you could possibly do it. It feels like all of

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Speaker 1: those things are just leaving bad situations or bad relationships. Like,

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Speaker 1: once you actually do it, once it's not lingering on

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Speaker 1: and hanging on by this sad little thread, it feels better. Yeah.

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Speaker 2: I've actually read about, you know, on OCD forums and

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Speaker 2: stuff too, people being like I was so obsessed all

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Speaker 2: like the thing that they would fixate on was someone

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Speaker 2: that they love dying, and then it finally happened and

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Speaker 2: they were like, it's not as bad as it was

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Speaker 2: in my head, Like it's horrible I miss.

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Speaker 1: Them, but it's not as bad.

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Speaker 2: Yeah yeah, yeah, but understand Yeah. Again, this is not

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Speaker 2: everyone's experience, but it's just interesting to observe in myself.

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Speaker 2: And also sometimes I'm like, am I a bad person?

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Speaker 2: But you know, am I a bad person? Again?

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Speaker 1: No?

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Speaker 2: Thank you, you're welcome. Okay, all right, let's begin this

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Speaker 2: intermational Charles welcome, Chris bail To trust me.

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Speaker 3: Hey, thanks for having me.

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Speaker 2: Thank you for being here. So you are the author

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Speaker 2: of a book called Breaking the social media prism, how

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Speaker 2: to make our platforms less polarizing. You're a Duke professor

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Speaker 2: and director of the Polarization Lab, and we have so

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Speaker 2: much to talk to you about. Okay, so you're a

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Speaker 2: computational social scientist. What does that mean?

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Speaker 3: It's sort of interesting, like, you know, a lot of

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Speaker 3: times when we want to study people, historically we've only

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Speaker 3: had you know, maybe a thousand data points. You know,

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Speaker 3: you could talk to one hundred people, you could just

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Speaker 3: survey of a thousand people. But now, thanks to things

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Speaker 3: like Twitter, Instagram, TikTok, whatever, you know, we are sort

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Speaker 3: of awash with data. And so in my field, there's

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Speaker 3: been this huge movement to try to develop creative new

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Speaker 3: ways to use those new types of data to study

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Speaker 3: kind of all sorts of different human behavior, often using

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Speaker 3: stuff like AI and other kinds of machine learning.

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Speaker 2: And you have been studying basically social media extremism. How

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Speaker 2: would you kind of summarize it?

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Speaker 3: Yeah, I'd like to say I've seen it all. I mean,

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Speaker 3: I've been studying this stuff for like fifteen years. So

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Speaker 3: you know, I go way back to this thing called MySpace,

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Speaker 3: which you know, nobody under thirty knows about. But you know,

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Speaker 3: once upon a time, there was there were there were

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Speaker 3: platforms before Facebook. And you know, I've been studying political extremism,

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Speaker 3: especially all sorts of extremism, anti Muslim extremism and more

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Speaker 3: recently sort of US politics and started inspired extremism for

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Speaker 3: about fifteen years.

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Speaker 2: Incredible, Okay. We all tend to think that social media

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Speaker 2: foster's extremism because of information silos, and that we're just

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Speaker 2: not getting exposed to the perspective of the other side.

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Speaker 2: And if we got exposed to the perspective of the

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Speaker 2: other side more that we would all become more moderate.

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Speaker 2: And it's it's an information problem, right. Your research has

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Speaker 2: found that to not be true. Can you tell us

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Speaker 2: about that?

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Speaker 3: Yeah, so this was really surprising. You know, I sort

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Speaker 3: of thought this was the most promising explanation of what

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Speaker 3: ails us. You know, like you said, we're all disconnected

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Speaker 3: from each other, We're not listening to each other. You know,

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Speaker 3: surely these evil corporations have created these structures echo chambers,

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Speaker 3: filter bubbles, whatever you want to call them, that prevent

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Speaker 3: us from just simply understanding each other. And you know,

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Speaker 3: that seemed doubly true three or four years ago, when

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Speaker 3: you know, we were witnessing, you know, unprecedented events, sudden

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Speaker 3: shifts in the political environment, like the election of Trump

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Speaker 3: or in Britain, you know, the Brexit referendum. Things we

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Speaker 3: didn't really think were going to happen, and all of

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Speaker 3: a sudden happened, and it seemed really plausible that the

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Speaker 3: reason a lot of us were surprised by these things

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Speaker 3: is because we simply weren't exposed to like the palpable

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Speaker 3: enthusiasm of Trump supporters, or you know, the strong support

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Speaker 3: for leaving Europe in Britain. And so, you know, for years,

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Speaker 3: I thought, you know, as someone who's interested in social

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Speaker 3: media and wants to create some positive change, what we

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Speaker 3: should really do is get people out of these echo chambers.

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Speaker 3: And so about four or five years ago, we designed

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Speaker 3: this really large study to try to take people out

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Speaker 3: of their echo chambers and discover that probably wasn't a

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Speaker 3: very good idea.

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Speaker 1: That is so crazy, I mean not shocking. So what exactly.

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Speaker 3: Happened, Yeah, and it was shocking to us too. So,

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Speaker 3: you know, we paid about twelve hundred people who used

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Speaker 3: Twitter in the US to take a survey about their

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Speaker 3: political views. So we asked them about all sorts of stuff,

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Speaker 3: climate change, racial discrimination, size of government, and then we

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Speaker 3: offered half of them additional money to follow a bot

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Speaker 3: on Twitter that they were told would tweet twenty five

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Speaker 3: or messages to date. We didn't tell them what it

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Speaker 3: was going to tweet, but we told them, you know,

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Speaker 3: you can make more money if you fall on account. Gradually,

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Speaker 3: over the month long study period, we began to increase

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Speaker 3: the number of tweets that that account made that were

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Speaker 3: from the opposing political party. So if you're a Democrat,

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Speaker 3: you started to see more tweets from Republicans. And these

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Speaker 3: were like officials, journalists, you know, social media influencers, all

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Speaker 3: sorts of different people who comprise the echo chamber. And

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Speaker 3: then at the end of the month, we resurveyed everybody,

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Speaker 3: thinking that our neat little experiment would have increased moderation,

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Speaker 3: maybe it just a little bit among everybody who sort

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Speaker 3: of was asked to step outside the echo chamber by

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Speaker 3: following these spots, And instead what we found was nobody

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Speaker 3: became more moderate, or almost nobody became more moderate, and

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Speaker 3: the vast majority of people actually became a little bit

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Speaker 3: more polarized. So if you were, you know, conservative before

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Speaker 3: you came, you became more conservative after you followed our democratic.

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Speaker 1: Bought It's like a double it's like an identity double down.

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Speaker 3: That is a yeah, fun, that's a nice way of

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Speaker 3: putting it.

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Speaker 1: Yeah.

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Speaker 2: Interesting. This really is in line with what we talk

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Speaker 2: about a lot well in some ways. In other ways

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Speaker 2: it completely contradicts what we talk about because we really

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Speaker 2: believed in the echo chamber. But in other ways, when

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Speaker 2: it comes to Colt's an extreme belief, what we consistently

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Speaker 2: hear from experts, what we consistently have seen is that

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Speaker 2: when basically when you presented with an attack on your

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Speaker 2: belief system and it is connected to your identity, people

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Speaker 2: double down on that belief system instead of like listening

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Speaker 2: to the facts. And that's why, like attacking people with

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Speaker 2: extreme belief with facts never works, because it just makes

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Speaker 2: them be like, oh, you're trying to like fuck with

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Speaker 2: my identity, and no one's fucking with my identity. The

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Speaker 2: separate question, was there any accounting for like the way

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Speaker 2: that they were receiving the tweets knowing it was from

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Speaker 2: this bot. Did that impact anything?

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Speaker 3: Yeah? So you know, obviously we would be worried if

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Speaker 3: people knew what we were trying to do because in

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Speaker 3: an experiment like this, you are aware that they're being studied,

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Speaker 3: they may either try to exhibit the kind of behavior

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Speaker 3: that they think you want them to exhibit. So in

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Speaker 3: this case, you know, maybe people would be more moderate, right,

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Speaker 3: or maybe they'd be pissed off and be like, hey,

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Speaker 3: you know you do professors, this was not cool. Why

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Speaker 3: did you make me, you know, follow a bot that

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Speaker 3: that tweets all the stuff I don't like? And so

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Speaker 3: I'm going to pretend to be marestream than I really am.

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Speaker 3: That will getting like too much into the weeds. There's

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Speaker 3: some tricks that we social scientists use to try to

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Speaker 3: discourage that type of behavior. So one that we do,

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Speaker 3: for example, is we disguise the purpose of the bot.

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Speaker 3: So the first few days they're just tweeting like beautiful landscapes,

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Speaker 3: you know, like super anodyne stuff, and then gradually we

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Speaker 3: turn up the the the dial of sort of political content,

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Speaker 3: and then it's not branded as like a bot that

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Speaker 3: you see as like, hey, this is an evil bot

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Speaker 3: trying to influence you. It's just a bot that's retweeting people.

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Speaker 3: So you're just seeing like, you know, our bot retweeted

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Speaker 3: you know, Ted Cruz Alexandria Casio quortees, it's not like,

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Speaker 3: you know, evil Russian bod is trying to change your mind.

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Speaker 3: And then lastly, when we pick up the data points,

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Speaker 3: and this is probably the most important point. When we

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Speaker 3: survey people, we send them surveys designed to look like

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Speaker 3: they come from a different group of researchers, and then

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Speaker 3: we measure how much their minds change before and after

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Speaker 3: the two surveys that seem to come from different sets

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Speaker 3: of researchers. So unless people could remember sort of exactly

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Speaker 3: how they responded to the first one and connect our

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Speaker 3: invitation to follow the bot to the surveys that we

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Speaker 3: were asking them to complete, we don't think it's likely

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Speaker 3: that they were simply sort of responding in this sort

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Speaker 3: of expressive way saying, you know, I don't like your study,

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Speaker 3: or I'm trying to do what I think you want

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Speaker 3: me to do.

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Speaker 2: Right, right?

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Speaker 1: Right?

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Speaker 2: Ye? Can you talk to us about the main reasons

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Speaker 2: that people use social media?

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Speaker 3: Yeah? Sure, And you know, I think this really gets

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Speaker 3: to the heart of the issue. You know, when we

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Speaker 3: hear people talk about the echo chamber, the idea is

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Speaker 3: that there's some kind of like democratic ideal which underpins

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Speaker 3: all of our interaction in these public spaces. Right that

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Speaker 3: a place like Twitter in its ideal form should be

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Speaker 3: a competition of ideas. Right that we should all just

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Speaker 3: go out and like I put my idea out about

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Speaker 3: how to fix inflation. Okay, I could pick a less

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Speaker 3: boring topic, let's say climate change, and then you tell

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Speaker 3: me yours, and then like we meet somewhere in the

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Speaker 3: middle middle through some like you know, reason deliberation, where

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Speaker 3: our facts kind of compete with each other for merit. Right,

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Speaker 3: that does not describe the typical motivation of most social

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Speaker 3: media users I've studied over the years. You know, social

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Speaker 3: media for me is all about status. It's about heightening

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Speaker 3: the things we do that make us human. So if

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Speaker 3: we want to take a big step back and think

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Speaker 3: about what's weird about humans, for my money, it's that

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Speaker 3: we care so much about what other people think about us.

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Speaker 3: You know, we we sort of over centuries have developed

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Speaker 3: these like ways of monitoring our social environm mints preclues

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Speaker 3: about what other people think about us. You know, as

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Speaker 3: soon as I come on your podcast, like I'm looking

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Speaker 3: to see if your heads are nodding, if you're falling

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Speaker 3: asleep if you're getting ready to throw tomatoes at me, right,

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Speaker 3: and and through that, like I can sort of like

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Speaker 3: change how I behave. I'm sort of like constantly experimenting

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Speaker 3: on my identity in order to see what what works.

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Speaker 1: I mean, I guess that's not surprising seeing that we're

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Speaker 1: social animals and like wolf packs and all of those things.

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Speaker 1: But now we're advancing so fast to be able to

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Speaker 1: share it on scales that we're not comprehending. Really you're nodding,

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Speaker 1: But is that making sense at all?

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Speaker 3: Yeah? Now, you know, if we think about what social

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Speaker 3: media does differently, right, it does two really important things.

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Speaker 3: I think. The first is that you know, we have

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Speaker 3: a much broader range of identities that we can present

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Speaker 3: to people. You know, so like, you know, if you

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Speaker 3: never meet someone in person, you know, you could pretend

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Speaker 3: to be a professional basketball player or like, you know,

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Speaker 3: a great break answer like I am neither.

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Speaker 2: Right, But if we were on.

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Speaker 3: News alert, you know. But you know, if we were

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Speaker 3: on Twitter and I was an anonymous acount, right, I

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Speaker 3: can be whoever I want to be, so I can

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Speaker 3: kind of experiment with a broader range of identities. And

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Speaker 3: then second, I have sort of built into most platforms

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Speaker 3: technology to monitor what other people are thinking of me

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Speaker 3: with unprecedented speed. So, for example, like as soon as

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Speaker 3: I post something right, I get that. You know that

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Speaker 3: immediate response or more often non response. If your experience

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Speaker 3: is like most people. You know, not everybody has a

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Speaker 3: podcast as famous as yours. You know, a lot of

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Speaker 3: podcasts get ignored, a lot of same thing, a lot

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Speaker 3: of social media posts get ignored. But we have this

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Speaker 3: way of sort of getting real time feedback about what

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Speaker 3: huge numbers of people think of us. And of course

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Speaker 3: that information is very often wrong, and that's part of

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Speaker 3: the big problem here, but it's something that you know

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Speaker 3: to the extent that our brains q in on any

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Speaker 3: hints about how to fit in. This is one of

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Speaker 3: the key things that social media has changed about how

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Speaker 3: we act and behave I think.

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Speaker 2: So basically, the internet gives us more room to create

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Speaker 2: an identity that we didn't have. We are all looking

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Speaker 2: to belong always. That's just like programmed into us. It's

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Speaker 2: part of how we exist in the world as human beings.

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Speaker 2: But now it's not just like your chess club that

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Speaker 2: you join, or your local fucking sports team or whatever.

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Speaker 2: We have all of these options, and we can kind

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Speaker 2: of test in real time, like is this my identity?

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Speaker 2: Do I belong here? Are these my people? Or is

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Speaker 2: it over here? Is this going to be the thing

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Speaker 2: that gets me engagement? Does that broader range of options

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Speaker 2: and like real time feedback make people more likely to

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Speaker 2: become extreme in their identities?

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Speaker 3: I think so our research definitely suggests this is going on.

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Speaker 3: So I'll tell you a story. You know. One of

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Speaker 3: the weird things about our research is that we do

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Speaker 3: this like you know, data science style analysis of hundreds

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Speaker 3: of millions of tweets. We also actually talk to people.

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Speaker 3: Thought of it, right, And when we begin to talk

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Speaker 3: to people and like sort of compare how they present

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Speaker 3: themselves online and off, this sort of stuff just lit

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Speaker 3: up as one of the key parts of the story here. So,

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Speaker 3: for example, one of the people we studied, this guy

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Speaker 3: that I call Ray in my book to protect his

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Speaker 3: his confidentiality. You know, it's like the nicest person you'll

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Speaker 3: ever meet, just like super civil, polite, funny, you know,

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Speaker 3: like easy to talk to. You know, goes out of

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Speaker 3: his way to say like how he never gets in arguments,

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Speaker 3: stays away from politics, this, that, and the other right.

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Speaker 3: And then when we go to look up his persona online,

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Speaker 3: which we could do through linking, like our sophisticated kind

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Speaker 3: of data science techniques, we discover that Ray is the

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Speaker 3: biggest roll on the Internet. Like I'm saying that as

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Speaker 3: someone who studied these folks for like fifteen years, and

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Speaker 3: like each night he was undergoing this doctor Jekyl into

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Speaker 3: Mister Hyde style transformation, where you know, despite seeming like

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Speaker 3: a mildly right leaning guy, he turns into like the

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Speaker 3: biggest maga warrior, you know, one of the biggest maga

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Speaker 3: warriors I've ever seen, you know, tweeting, you know, every night,

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Speaker 3: you know, multiple photoshop memes about Nancy Pelosi, Obama or whoever. So, yeah,

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Speaker 3: I mean a lot of the trolls among us, we

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Speaker 3: think are sort of hiding in plain sight. Because of

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Speaker 3: this unprecedented flexibility, you know, we can find ways to

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Speaker 3: fit in in different different places that we never would

435
00:21:29,359 --> 00:21:30,080
Speaker 3: have found before.

436
00:21:30,440 --> 00:21:32,240
Speaker 1: Yeah, and you can have no power in your real

437
00:21:32,280 --> 00:21:34,720
Speaker 1: life and have a lot of power on the Internet,

438
00:21:35,000 --> 00:21:35,600
Speaker 1: which is.

439
00:21:35,800 --> 00:21:38,520
Speaker 3: Oh yeah, wild well yeah, and especially you know, so

440
00:21:38,640 --> 00:21:41,159
Speaker 3: in the case of this guy Ray, one of the

441
00:21:41,160 --> 00:21:43,200
Speaker 3: things that stood out to us and we took another

442
00:21:43,200 --> 00:21:45,080
Speaker 3: step back and say, like, well, what's his deal, Like,

443
00:21:45,119 --> 00:21:48,240
Speaker 3: why would you spend six hours at night when you,

444
00:21:48,240 --> 00:21:50,679
Speaker 3: you know, seem like a nice guy or whatever. And

445
00:21:50,720 --> 00:21:55,040
Speaker 3: what we realized is like Ray was like absolutely isolated

446
00:21:55,080 --> 00:21:58,640
Speaker 3: in his life. You know, he was unmarried, he lived

447
00:21:58,680 --> 00:22:01,920
Speaker 3: with his mom, He was a Republican man who lived

448
00:22:01,920 --> 00:22:03,920
Speaker 3: in a very liberal city and worked in a very

449
00:22:03,960 --> 00:22:07,800
Speaker 3: liberal profession. Interesting, he had very few friends. Right, and

450
00:22:07,920 --> 00:22:10,840
Speaker 3: all of a sudden, like social media becomes sort of

451
00:22:10,880 --> 00:22:13,639
Speaker 3: a refuge for someone like this. Right, you find your community,

452
00:22:13,680 --> 00:22:16,600
Speaker 3: you find your people, and you find instant validation. Now

453
00:22:16,640 --> 00:22:19,879
Speaker 3: that validation might be coming from other social outcasts, but

454
00:22:20,119 --> 00:22:25,480
Speaker 3: it shows you how isolated and how removed from society

455
00:22:25,560 --> 00:22:28,679
Speaker 3: so many people can feel, and how internet communities can

456
00:22:28,680 --> 00:22:30,760
Speaker 3: really give them a sense of belonging, even if it

457
00:22:30,800 --> 00:22:33,320
Speaker 3: seems less meaningful to the rest of us, it can

458
00:22:33,400 --> 00:22:35,640
Speaker 3: be a central part of these folks identity.

459
00:22:35,920 --> 00:22:38,720
Speaker 2: Oh absolutely, I mean it's very much the same as

460
00:22:38,880 --> 00:22:42,840
Speaker 2: with people who join cults. They are often I don't

461
00:22:42,840 --> 00:22:44,520
Speaker 2: want to say all the time, because sometimes people just

462
00:22:44,600 --> 00:22:46,920
Speaker 2: join because they get preyed upon, and that's a whole

463
00:22:46,920 --> 00:22:49,480
Speaker 2: other story, but often it's people who are really in

464
00:22:49,560 --> 00:22:52,960
Speaker 2: need of community, in need of belonging, feeling isolated, or

465
00:22:53,000 --> 00:22:56,080
Speaker 2: going through some sort of life change, And that just

466
00:22:56,080 --> 00:22:58,439
Speaker 2: seems to be the case with kind of everything that

467
00:22:58,480 --> 00:23:01,000
Speaker 2: people build their identities around. I mean, we've had on

468
00:23:01,200 --> 00:23:04,840
Speaker 2: like a former one direction Stan and you know, people

469
00:23:04,840 --> 00:23:07,399
Speaker 2: who become very identified with their political beliefs. It starts

470
00:23:07,400 --> 00:23:11,120
Speaker 2: with like this need that is not being met, and

471
00:23:11,160 --> 00:23:16,400
Speaker 2: suddenly this community online is meeting that need or offline

472
00:23:16,600 --> 00:23:17,640
Speaker 2: in a commune somewhere.

473
00:23:18,400 --> 00:23:20,399
Speaker 1: And I really like the point you make too, that

474
00:23:20,480 --> 00:23:22,800
Speaker 1: it's not that you can go on and just say

475
00:23:22,840 --> 00:23:27,680
Speaker 1: something super quote unquote normal or moderate and find your group.

476
00:23:27,840 --> 00:23:30,399
Speaker 1: Nobody gives a shit if you say anything like that.

477
00:23:30,440 --> 00:23:33,159
Speaker 1: It's the extremists that are getting the hits, that are

478
00:23:33,160 --> 00:23:36,840
Speaker 1: getting the the like acceptance at the end of the day.

479
00:23:37,119 --> 00:23:38,119
Speaker 2: Tell us why that is.

480
00:23:38,600 --> 00:23:40,919
Speaker 3: Yeah. So this is why I called my book Breaking

481
00:23:40,920 --> 00:23:43,399
Speaker 3: the Social Media Prism, because I think instead of thinking

482
00:23:43,400 --> 00:23:46,480
Speaker 3: about echo chambers, or instead of thinking about social media

483
00:23:46,480 --> 00:23:48,240
Speaker 3: as a giant kind of echo chamber, we should really

484
00:23:48,240 --> 00:23:50,399
Speaker 3: think of it more like a prism. So if you

485
00:23:50,440 --> 00:23:52,800
Speaker 3: think about it, you know, if so much of what

486
00:23:52,880 --> 00:23:55,240
Speaker 3: guides our behavior is what we think other people think

487
00:23:55,280 --> 00:23:58,520
Speaker 3: of us. It really really matters who we are looking

488
00:23:58,560 --> 00:24:00,800
Speaker 3: at and who we think are looking at us. And

489
00:24:00,840 --> 00:24:04,480
Speaker 3: we want to use social media, often intentionally or unintentionally,

490
00:24:04,520 --> 00:24:05,600
Speaker 3: and a lot of the time, by the way, I

491
00:24:05,600 --> 00:24:07,840
Speaker 3: think it's unintentional. We want to use it as a

492
00:24:07,920 --> 00:24:09,920
Speaker 3: kind of mirror to say, like who am I, you know,

493
00:24:09,960 --> 00:24:12,600
Speaker 3: Like where do I fit in? You know? Can I

494
00:24:12,720 --> 00:24:15,640
Speaker 3: see my place in society a little bit more neatly

495
00:24:16,040 --> 00:24:18,960
Speaker 3: if I can look at society sort of in its entirety, right,

496
00:24:19,000 --> 00:24:21,639
Speaker 3: that's our sort of instinct. But of course that's not

497
00:24:21,680 --> 00:24:25,320
Speaker 3: what social media is. It's not like an accurate representation

498
00:24:25,440 --> 00:24:28,360
Speaker 3: of what the world thinks of you. It's a heavily

499
00:24:28,400 --> 00:24:32,600
Speaker 3: filtered sort of prism like experience where you're seeing mostly

500
00:24:33,119 --> 00:24:37,200
Speaker 3: a small group of people with pretty radical views generating

501
00:24:37,240 --> 00:24:40,360
Speaker 3: most of the content. And so for someone who's sort

502
00:24:40,400 --> 00:24:44,280
Speaker 3: of you know, isolated and dabbling in extremism, I think

503
00:24:44,320 --> 00:24:49,000
Speaker 3: pretty clearly, pretty quickly, they can come to confuse extremism

504
00:24:49,040 --> 00:24:51,199
Speaker 3: with sort of more normal views. I mean, you know,

505
00:24:51,560 --> 00:24:55,200
Speaker 3: we've known about this type of tendency for fifty sixty years,

506
00:24:55,240 --> 00:24:58,320
Speaker 3: going back to you know, the false consensus effect, where

507
00:24:58,400 --> 00:25:01,760
Speaker 3: people in extremist communities tend to think that because everybody

508
00:25:01,760 --> 00:25:04,080
Speaker 3: else in their community shares their view, it's not an

509
00:25:04,080 --> 00:25:07,200
Speaker 3: extreme view, right, And so I think that social media

510
00:25:07,240 --> 00:25:08,280
Speaker 3: has just sort of accelerated.

511
00:25:08,280 --> 00:25:13,320
Speaker 2: Then what percentage of the population do extreme voices represents

512
00:25:13,480 --> 00:25:14,600
Speaker 2: on social media?

513
00:25:14,800 --> 00:25:17,000
Speaker 3: This is really shocking. So if we go back to

514
00:25:17,400 --> 00:25:20,760
Speaker 3: twenty eighteen twenty nineteen, the Pew Research Center did a

515
00:25:20,760 --> 00:25:24,280
Speaker 3: really interesting study where they tried to look at who

516
00:25:24,320 --> 00:25:28,080
Speaker 3: tweets about politics and how much they tweet about politics,

517
00:25:28,280 --> 00:25:32,000
Speaker 3: and basically what they found is that six percent of

518
00:25:32,080 --> 00:25:36,840
Speaker 3: Twitter users generate seventy six percent of all tweets about politics,

519
00:25:37,440 --> 00:25:41,240
Speaker 3: and that six percent of people tend to overwhelmingly be

520
00:25:41,560 --> 00:25:45,240
Speaker 3: either very conservative or very liberal. And so if you

521
00:25:45,720 --> 00:25:50,040
Speaker 3: wade into a political discussion on Twitter, the likelihood that

522
00:25:50,080 --> 00:25:53,760
Speaker 3: it will be dominated by extremists is extremely high. And

523
00:25:53,800 --> 00:25:56,760
Speaker 3: the challenge then, right, is if we then can't see

524
00:25:56,760 --> 00:25:59,040
Speaker 3: this prism like effect, right, and we just assume, oh,

525
00:25:59,119 --> 00:26:02,639
Speaker 3: everybody's total really crazy, right, when it's easy to do that.

526
00:26:02,680 --> 00:26:04,880
Speaker 3: If you've been watching social media over the last three years,

527
00:26:04,960 --> 00:26:07,560
Speaker 3: especially through COVID, especially as we've been more isolated from

528
00:26:07,560 --> 00:26:11,240
Speaker 3: each other, this prism like power really starts to become

529
00:26:11,240 --> 00:26:13,640
Speaker 3: a self fulfilling prophecy. And that's where I think we're

530
00:26:13,880 --> 00:26:16,600
Speaker 3: really starting to see things go off the rails.

531
00:26:18,560 --> 00:26:21,240
Speaker 2: I feel like it's a common belief that most people

532
00:26:21,320 --> 00:26:24,399
Speaker 2: are actually pretty moderate, and Twitter is, you know, just

533
00:26:24,440 --> 00:26:26,920
Speaker 2: the most extreme of us. Is it because of the

534
00:26:27,000 --> 00:26:30,399
Speaker 2: algorithm that moderate voices are not the ones rising to

535
00:26:30,440 --> 00:26:33,120
Speaker 2: the top, or is it sort of self selection or both?

536
00:26:33,320 --> 00:26:35,520
Speaker 3: Probably a little from Colum A, a little from Colin B.

537
00:26:36,080 --> 00:26:37,560
Speaker 3: You know, certainly it's self selection.

538
00:26:37,640 --> 00:26:37,720
Speaker 1: Right.

539
00:26:37,760 --> 00:26:41,240
Speaker 3: We already talked about why extremists would kind of be,

540
00:26:41,560 --> 00:26:45,200
Speaker 3: you know, captivated by social media. What we haven't talked

541
00:26:45,240 --> 00:26:48,360
Speaker 3: about is why moderate people have nothing to gain from

542
00:26:48,400 --> 00:26:52,280
Speaker 3: social media, right. I mean, if I am a moderate

543
00:26:52,320 --> 00:26:57,919
Speaker 3: conservative who has, let's say, concerns about voter fraud claims, right,

544
00:26:57,960 --> 00:26:59,760
Speaker 3: and maybe I don't believe them, right, or maybe I

545
00:26:59,760 --> 00:27:02,919
Speaker 3: think they are being exaggerated, right, I have virtually no

546
00:27:03,040 --> 00:27:06,120
Speaker 3: incentive to log onto Twitter and say, hey, guys, because

547
00:27:06,119 --> 00:27:10,639
Speaker 3: it's mostly guys, probably right, like, well, you know this

548
00:27:10,640 --> 00:27:12,920
Speaker 3: this is stupid. You're all being stupid. Right. No, I

549
00:27:12,960 --> 00:27:15,639
Speaker 3: would never do that, right, I would. I would fear

550
00:27:15,720 --> 00:27:21,119
Speaker 3: the social sanctioning involved from the merits. Yeah, no joke, right, yeah,

551
00:27:21,119 --> 00:27:24,200
Speaker 3: like literally death threat right. So, so, you know, one

552
00:27:24,240 --> 00:27:25,760
Speaker 3: of the things we discovered in the course of our

553
00:27:25,760 --> 00:27:29,040
Speaker 3: research is like, there are so many reasons why people

554
00:27:29,040 --> 00:27:32,159
Speaker 3: are afraid to post, especially in a public place like Twitter.

555
00:27:33,080 --> 00:27:35,480
Speaker 3: They may worry about losing their job. They might worry

556
00:27:35,520 --> 00:27:38,640
Speaker 3: about like their aunt at Thanksgiving, they might worry about

557
00:27:38,640 --> 00:27:40,719
Speaker 3: their kids. You know, we're just talking about death threats.

558
00:27:40,760 --> 00:27:43,000
Speaker 3: But you know, the number of people who get death

559
00:27:43,040 --> 00:27:47,160
Speaker 3: threats on Twitter is staggering. In fact, recent survey suggests

560
00:27:47,160 --> 00:27:50,720
Speaker 3: the number one reason people get harassed online is for

561
00:27:50,760 --> 00:27:53,760
Speaker 3: sharing their political views, and many of those people's you know,

562
00:27:53,880 --> 00:27:57,040
Speaker 3: children are visible in their timeline or wherever, and we

563
00:27:57,119 --> 00:28:01,360
Speaker 3: have stories of research response in our book who had

564
00:28:01,400 --> 00:28:03,959
Speaker 3: their children threatened multiple times. I mean it's you know,

565
00:28:04,359 --> 00:28:06,600
Speaker 3: what's the point like that, with that level of risk,

566
00:28:06,720 --> 00:28:09,159
Speaker 3: it makes sense that a lot of the most moderate

567
00:28:09,200 --> 00:28:10,880
Speaker 3: folks would would disengage.

568
00:28:11,240 --> 00:28:15,879
Speaker 2: Yeah, even me. I mean, like, I'm a pretty liberal person,

569
00:28:15,920 --> 00:28:18,080
Speaker 2: but there are certain areas in which I'm a little

570
00:28:18,080 --> 00:28:22,040
Speaker 2: bit more moderate, and I don't voice those because I

571
00:28:22,520 --> 00:28:27,080
Speaker 2: know that it won't resonate with my audience on there,

572
00:28:27,119 --> 00:28:29,080
Speaker 2: and I want to fight that instinct, but it is

573
00:28:29,359 --> 00:28:32,120
Speaker 2: the internet is a terrifying place, like you can get

574
00:28:32,119 --> 00:28:36,320
Speaker 2: ostracized so quickly into such an extreme degree. And I

575
00:28:36,359 --> 00:28:38,280
Speaker 2: just want to point out that, yes, you can get

576
00:28:38,320 --> 00:28:42,240
Speaker 2: death death threats of your conservative you know, posting about

577
00:28:42,280 --> 00:28:44,360
Speaker 2: a more moderate view you have, but as a liberal,

578
00:28:44,400 --> 00:28:48,280
Speaker 2: you also can very much be crucified for not sharing

579
00:28:48,320 --> 00:28:51,520
Speaker 2: the sort of belief that you're supposed to share, you know.

580
00:28:51,640 --> 00:28:54,680
Speaker 3: Oh yeah, yeah, absolutely, you know. And it's interesting when

581
00:28:54,680 --> 00:28:57,760
Speaker 3: we do experiments where we sort of pretend like people

582
00:28:57,920 --> 00:29:01,360
Speaker 3: are interacting with people from the other side and simulated settings,

583
00:29:01,800 --> 00:29:04,240
Speaker 3: what we see is people are actually much more likely

584
00:29:04,320 --> 00:29:06,840
Speaker 3: sometimes to share their their views with people from the

585
00:29:06,880 --> 00:29:09,360
Speaker 3: other party than their own than their own party. You know.

586
00:29:09,440 --> 00:29:12,200
Speaker 3: So if you are if you tell Republicans that they're

587
00:29:12,240 --> 00:29:15,360
Speaker 3: about to enter a chat with Democrats about voter fraud,

588
00:29:15,400 --> 00:29:17,160
Speaker 3: you know, they'll go right out and say, hey, you

589
00:29:17,160 --> 00:29:19,920
Speaker 3: guys are right. But if you tell them that they're

590
00:29:19,920 --> 00:29:22,280
Speaker 3: about to enter a conversation with some people who they

591
00:29:22,280 --> 00:29:26,040
Speaker 3: think are are Republicans, they're not gonna They're not.

592
00:29:27,080 --> 00:29:33,200
Speaker 2: That's so interesting. Wow, Okay, yeah, I mean I don't

593
00:29:33,200 --> 00:29:35,080
Speaker 2: want to skip to the end, but it just makes

594
00:29:35,080 --> 00:29:37,640
Speaker 2: me so curious about how to sort of change the

595
00:29:37,640 --> 00:29:39,560
Speaker 2: culture of that. But we'll get to that in a second.

596
00:29:40,280 --> 00:29:41,960
Speaker 1: It's just set up a world where no one can

597
00:29:42,000 --> 00:29:45,280
Speaker 1: be normal. Yeah, we all look insane to each other.

598
00:29:46,160 --> 00:29:49,440
Speaker 3: Yeah, I mean yeah, And I think you know your

599
00:29:49,440 --> 00:29:51,440
Speaker 3: other question is about the algorithm, you know, And that's

600
00:29:51,480 --> 00:29:53,920
Speaker 3: another one of these ideas floating around out there that's

601
00:29:53,960 --> 00:29:56,320
Speaker 3: got a lot of traction. Right. If it's not echo chambers,

602
00:29:56,360 --> 00:29:59,000
Speaker 3: then sure, it's these algorithms which are sort of designed

603
00:29:59,080 --> 00:30:02,360
Speaker 3: to reward extremely and are radicalizing people in their in

604
00:30:02,400 --> 00:30:06,040
Speaker 3: their mom's basement. Right, super compelling story. And again like

605
00:30:06,160 --> 00:30:08,920
Speaker 3: one that I, as someone who's been working on this

606
00:30:09,000 --> 00:30:12,040
Speaker 3: wrong time, found seductive. Right, it makes a lot of sense.

607
00:30:12,120 --> 00:30:15,840
Speaker 3: Like these are large corporations, maybe they're profiting off our outrage.

608
00:30:15,920 --> 00:30:18,680
Speaker 3: You know. The interesting thing, though, is when we start

609
00:30:18,720 --> 00:30:22,360
Speaker 3: to put these ideas to scrutiny with like hard data.

610
00:30:22,480 --> 00:30:25,600
Speaker 3: For example, a recent study looked at one hundred and

611
00:30:25,680 --> 00:30:28,840
Speaker 3: thirty million YouTube viewing sessions of you know, hundreds and

612
00:30:28,920 --> 00:30:32,320
Speaker 3: hundreds and hundreds of thousands of people looking for evidence

613
00:30:32,440 --> 00:30:36,000
Speaker 3: of the proverbial rabbit hole you know, where we watch

614
00:30:36,120 --> 00:30:39,840
Speaker 3: you know, some some sort of like super non political thing,

615
00:30:39,880 --> 00:30:41,800
Speaker 3: and then before we know it, you know, we're like

616
00:30:42,280 --> 00:30:46,680
Speaker 3: captivated by Jordan Peterson, God forbid or whatever right now.

617
00:30:47,400 --> 00:30:49,360
Speaker 3: So I, you know, I would have thought, well, probably

618
00:30:49,400 --> 00:30:51,640
Speaker 3: that happens to like, I don't know, five or ten

619
00:30:51,640 --> 00:30:55,520
Speaker 3: percent of people based on what you read in our

620
00:30:55,640 --> 00:30:59,960
Speaker 3: Times or or wherever. Right this research team couldn't find

621
00:31:00,120 --> 00:31:03,040
Speaker 3: any evidence that people were going down round the holes. So, like,

622
00:31:03,080 --> 00:31:06,040
Speaker 3: we have one story, a really powerful story from a

623
00:31:06,080 --> 00:31:08,480
Speaker 3: New York Times article, and one that you know, it

624
00:31:08,560 --> 00:31:11,120
Speaker 3: is compelling, but we don't have a lot of hard

625
00:31:11,200 --> 00:31:14,120
Speaker 3: data to support the idea that that social media is

626
00:31:14,200 --> 00:31:16,520
Speaker 3: radicalizing us. But what I think, you know, the bigger

627
00:31:16,600 --> 00:31:20,400
Speaker 3: issue here is not just that social media is optimized

628
00:31:20,440 --> 00:31:22,440
Speaker 3: for outrage. It is right to the extent that we

629
00:31:22,480 --> 00:31:24,960
Speaker 3: say something outrageous, we're going to get more comments, We

630
00:31:25,000 --> 00:31:27,440
Speaker 3: get more comments than our posts are going to appear

631
00:31:27,480 --> 00:31:29,560
Speaker 3: earlier in the news feed. Like we've known that for

632
00:31:29,600 --> 00:31:32,040
Speaker 3: a long time. Yeah, but that's not how it has

633
00:31:32,120 --> 00:31:35,240
Speaker 3: to be, you know. That's just like our platforms are

634
00:31:35,280 --> 00:31:38,080
Speaker 3: optimized for advertising, right, We're all supposed to go viral.

635
00:31:38,160 --> 00:31:39,840
Speaker 3: That's the whole point. That's the whole point of social

636
00:31:39,880 --> 00:31:41,520
Speaker 3: media and if if we want to get back to

637
00:31:41,600 --> 00:31:44,520
Speaker 3: like the guts of social media, and what I'm really

638
00:31:44,560 --> 00:31:46,560
Speaker 3: passionate about is saying, like why does it have to

639
00:31:46,600 --> 00:31:49,200
Speaker 3: be that way? And you know, there's the graveyard of

640
00:31:49,200 --> 00:31:51,600
Speaker 3: like serve of romantic ideas about social media is pretty

641
00:31:51,600 --> 00:31:55,320
Speaker 3: well populated, right, Like, sure it should be like social

642
00:31:55,360 --> 00:31:57,920
Speaker 3: media should be better, it should help humanity, blah blah blah.

643
00:31:58,000 --> 00:32:00,800
Speaker 3: I'm not naive about this stuff, but even some simple

644
00:32:00,880 --> 00:32:05,080
Speaker 3: tweaks to the way that algorithms sort our content I

645
00:32:05,120 --> 00:32:08,120
Speaker 3: think could have really far reaching consequences. So imagine if

646
00:32:08,240 --> 00:32:13,120
Speaker 3: instead of amplifying the divisive content, algorithms promoted stuff that

647
00:32:13,240 --> 00:32:16,800
Speaker 3: lots of different types of people like you know, so like,

648
00:32:17,360 --> 00:32:20,560
Speaker 3: instead of like me getting really angry about something Ted

649
00:32:20,640 --> 00:32:24,479
Speaker 3: Cruz said yesterday, I can see something that like, you know,

650
00:32:24,920 --> 00:32:29,920
Speaker 3: both Liz Cheney and Alexandrio Casio Cartes and George Bush

651
00:32:30,120 --> 00:32:36,200
Speaker 3: are all excited about. Right. That sounds pretty weird, But

652
00:32:36,200 --> 00:32:38,240
Speaker 3: at this point, right, it doesn't even have to be politics.

653
00:32:38,320 --> 00:32:40,960
Speaker 3: Yeah it could. It could kind of pull us back

654
00:32:41,000 --> 00:32:45,360
Speaker 3: towards consensus instead of rewarding disensus. And you know, these

655
00:32:45,360 --> 00:32:47,080
Speaker 3: are things social media companies could.

656
00:32:46,880 --> 00:32:50,440
Speaker 2: Do tomorrow totally. I mean, so I'm someone who gets

657
00:32:50,480 --> 00:32:53,160
Speaker 2: really really panicky about climate change and really upset that

658
00:32:53,200 --> 00:32:54,959
Speaker 2: we're not doing enough, and I've been fucking mad at

659
00:32:55,000 --> 00:32:58,520
Speaker 2: Joe Mansion for months, and the other day he you know,

660
00:32:58,720 --> 00:33:03,000
Speaker 2: finally relented and not what's the word that I want whatever,

661
00:33:03,040 --> 00:33:05,680
Speaker 2: He finally came through and agreed to this bill that

662
00:33:05,720 --> 00:33:09,800
Speaker 2: he's been blocking for a really long time. My Twitter

663
00:33:09,840 --> 00:33:14,440
Speaker 2: feed was silent on that it had been fucked Joe Mansion,

664
00:33:14,480 --> 00:33:17,360
Speaker 2: Fuck Joe Mansion, Fuck Joe Mansion. And then suddenly it's like, wait,

665
00:33:17,400 --> 00:33:19,520
Speaker 2: but this is a good like we found consensus, Like

666
00:33:19,600 --> 00:33:21,640
Speaker 2: we agree, this is good, Like someone we were mad

667
00:33:21,640 --> 00:33:23,640
Speaker 2: at has done a good thing, and it's just like

668
00:33:23,680 --> 00:33:26,560
Speaker 2: there's it's just not interesting enough to people. And other

669
00:33:26,600 --> 00:33:31,000
Speaker 2: bills also that have gotten past, you know by reaching

670
00:33:31,040 --> 00:33:33,080
Speaker 2: across the aisle or whatever, like they just don't get

671
00:33:33,120 --> 00:33:35,120
Speaker 2: as much attention, right, And you know.

672
00:33:35,160 --> 00:33:37,920
Speaker 3: Let's think about that prism like effect again for one second.

673
00:33:37,960 --> 00:33:40,680
Speaker 3: Let's pretend we're Kristen Cinema, where everybody, you know, who

674
00:33:40,680 --> 00:33:43,280
Speaker 3: everybody's kind of trained on right now because she's next

675
00:33:43,280 --> 00:33:46,160
Speaker 3: to sort of you know, vocalize whether she supports this

676
00:33:46,240 --> 00:33:49,920
Speaker 3: climate change legislation we're talking about, and she's watching, you know,

677
00:33:49,960 --> 00:33:53,440
Speaker 3: she's watching that. She's she's seeing that Joe Manchin is

678
00:33:53,480 --> 00:33:58,080
Speaker 3: getting absolutely no approbation for making this move right. So,

679
00:33:58,480 --> 00:34:02,200
Speaker 3: you know, it's sort of like, you know, back in

680
00:34:02,320 --> 00:34:04,680
Speaker 3: like the nineties or even like earlier in the eighties,

681
00:34:04,720 --> 00:34:06,760
Speaker 3: like people used to talk about voting with your wallet,

682
00:34:07,160 --> 00:34:08,640
Speaker 3: you know, like if you don't like a company, you

683
00:34:08,640 --> 00:34:11,680
Speaker 3: don't buy their products, or you know, support small businesses. Whatever.

684
00:34:11,680 --> 00:34:14,319
Speaker 3: It is like we're all voting with our like buttons now,

685
00:34:14,760 --> 00:34:17,960
Speaker 3: and it's not something people realize. You know, people think

686
00:34:18,040 --> 00:34:20,400
Speaker 3: of like I'm going to log into Twitter or whatever. Haha,

687
00:34:20,400 --> 00:34:22,960
Speaker 3: that's funny, and like that. You know, this guy's being

688
00:34:22,960 --> 00:34:25,919
Speaker 3: a jerk whatever, I'm gonna yell at him. We don't

689
00:34:26,000 --> 00:34:28,960
Speaker 3: understand that all of these actions are being kind of

690
00:34:28,960 --> 00:34:32,040
Speaker 3: analyzed and aggregated in ways that kind of create meaning

691
00:34:32,080 --> 00:34:35,600
Speaker 3: for other people. In fact, a staggering number of people

692
00:34:35,760 --> 00:34:38,960
Speaker 3: don't even know that their actions are observable by others

693
00:34:39,000 --> 00:34:41,560
Speaker 3: on Twitter, something like twenty five percent of Twitter users

694
00:34:41,560 --> 00:34:43,680
Speaker 3: don't know that. So when you put all these things together,

695
00:34:43,800 --> 00:34:46,880
Speaker 3: it's it's really kind of amazing. Because we think of

696
00:34:47,000 --> 00:34:49,040
Speaker 3: social media sort of like an escape or something we

697
00:34:49,120 --> 00:34:52,640
Speaker 3: used to distract ourselves, but really we're sending each other signals,

698
00:34:52,640 --> 00:34:57,080
Speaker 3: and that lack of signal is arguably even more powerful

699
00:34:57,120 --> 00:34:59,279
Speaker 3: than the negative signals we're all seen. Because again, if

700
00:34:59,280 --> 00:35:01,240
Speaker 3: we think back to those moderates who are worried about

701
00:35:01,880 --> 00:35:05,200
Speaker 3: death threats and their kids and losing their job, right,

702
00:35:05,520 --> 00:35:08,160
Speaker 3: and now they're seeing the people who make that sort

703
00:35:08,200 --> 00:35:13,040
Speaker 3: of arguably bold or risky step to move out of

704
00:35:13,080 --> 00:35:15,799
Speaker 3: step with where they've been, and they're saying and they're

705
00:35:15,840 --> 00:35:18,120
Speaker 3: not even getting any any love for that, right, So

706
00:35:18,160 --> 00:35:20,879
Speaker 3: why should I? And I think that's that's a big problem.

707
00:35:20,960 --> 00:35:23,120
Speaker 3: We all have to become I think a little bit

708
00:35:23,120 --> 00:35:25,719
Speaker 3: more reflective as social media users and realize that, yeah,

709
00:35:25,719 --> 00:35:28,759
Speaker 3: we're voting with our we're voting with our filmbs now right.

710
00:35:29,480 --> 00:35:33,759
Speaker 2: I mean, I wish it didn't matter to make politicians

711
00:35:33,840 --> 00:35:38,440
Speaker 2: feel good about like they're going to get affirmation from

712
00:35:38,560 --> 00:35:41,520
Speaker 2: the people for the decision that I may. But unfortunately,

713
00:35:41,560 --> 00:35:43,759
Speaker 2: we are all human and we are all operating from

714
00:35:43,760 --> 00:35:45,719
Speaker 2: an emotional place, whether we want to admit that or not.

715
00:35:45,800 --> 00:35:49,440
Speaker 2: And I don't think politicians are exempt from that, although

716
00:35:49,480 --> 00:35:52,520
Speaker 2: I wish that they were so it's a combination. So

717
00:35:52,520 --> 00:35:55,240
Speaker 2: there could be algorithm tweaks, but also our own behavior

718
00:35:55,280 --> 00:35:59,160
Speaker 2: and being more mindful about how we vote with our likes,

719
00:35:59,200 --> 00:36:00,120
Speaker 2: so to speak.

720
00:36:00,400 --> 00:36:02,799
Speaker 3: Exactly, you know, like the thing like I would love

721
00:36:02,840 --> 00:36:05,760
Speaker 3: to tell you that after you know, researching this stuff

722
00:36:05,760 --> 00:36:08,680
Speaker 3: for fifteen years, spending a lot of time, you know,

723
00:36:08,840 --> 00:36:11,879
Speaker 3: deep inside social media companies seeing how they work, that

724
00:36:12,000 --> 00:36:14,880
Speaker 3: there is just this sort of magic dial that like

725
00:36:15,000 --> 00:36:17,600
Speaker 3: turns down all the all the bullshit, you know, that

726
00:36:17,719 --> 00:36:20,800
Speaker 3: just turns down all the toxicity. It just doesn't exist.

727
00:36:20,920 --> 00:36:23,200
Speaker 3: You know, all of the very best invent you know,

728
00:36:23,320 --> 00:36:27,120
Speaker 3: interventions that we talk about like oh, Facebook should do

729
00:36:27,160 --> 00:36:30,800
Speaker 3: better with content moderation, TikTok should do better with fake users,

730
00:36:30,840 --> 00:36:33,920
Speaker 3: whatever it is, right, these are kind of like games

731
00:36:33,920 --> 00:36:36,279
Speaker 3: of whack a mole. And you know, at the end

732
00:36:36,280 --> 00:36:38,320
Speaker 3: of the day, if you want to create a scalable

733
00:36:38,320 --> 00:36:41,160
Speaker 3: effect that would actually change social media, it's going to

734
00:36:41,280 --> 00:36:44,480
Speaker 3: have to actually involve the supply side problem, the sort

735
00:36:44,480 --> 00:36:48,360
Speaker 3: of seemingly unending supply of vitriol that social media users

736
00:36:48,400 --> 00:36:51,719
Speaker 3: have for each other. You know, one way that some

737
00:36:51,800 --> 00:36:53,920
Speaker 3: of our research we were talking earlier about that research

738
00:36:53,960 --> 00:36:56,640
Speaker 3: we did where we paid people to uh, to follow

739
00:36:56,719 --> 00:37:00,560
Speaker 3: bots from the other side, and then you're times did

740
00:37:00,560 --> 00:37:04,319
Speaker 3: a wonderful up at the calumnist Michelle Goldberg, who's like

741
00:37:04,400 --> 00:37:07,400
Speaker 3: super smart, you know, she read our study and she

742
00:37:07,440 --> 00:37:10,320
Speaker 3: says to me so basically like we were never meant

743
00:37:10,320 --> 00:37:13,560
Speaker 3: to see so many other people, And I was like, wow, yeah,

744
00:37:13,680 --> 00:37:16,160
Speaker 3: you just you just said it much better than I could.

745
00:37:16,480 --> 00:37:17,960
Speaker 3: You know. One of the one of the weird things

746
00:37:17,960 --> 00:37:20,040
Speaker 3: about social media is that allows us to connect with

747
00:37:20,120 --> 00:37:22,480
Speaker 3: more people than we're probably supposed to. When we see

748
00:37:22,840 --> 00:37:27,839
Speaker 3: more vividly, how what an angry country we are, you know. So,

749
00:37:27,840 --> 00:37:29,960
Speaker 3: so this interesting question everybody wants to say, you know,

750
00:37:29,960 --> 00:37:33,120
Speaker 3: it's social media faltered. It's not social media's fault. It's

751
00:37:33,160 --> 00:37:35,600
Speaker 3: really the wrong question, because you know, we were polarized

752
00:37:35,640 --> 00:37:38,200
Speaker 3: before social media will continue to be polarized no matter

753
00:37:38,200 --> 00:37:41,840
Speaker 3: where we go from here. But the solution has to

754
00:37:41,880 --> 00:37:43,799
Speaker 3: be too pronged. It can't just be the Yes, the

755
00:37:43,800 --> 00:37:46,479
Speaker 3: platforms deserve a ton of blame. I would never try

756
00:37:46,480 --> 00:37:50,239
Speaker 3: to minimize that, but you know, social media users themselves

757
00:37:50,480 --> 00:37:53,399
Speaker 3: also deserve a hefty amount of the blame too.

758
00:37:55,560 --> 00:37:58,799
Speaker 2: So if extremism isn't happening the way we thought it,

759
00:37:58,920 --> 00:38:01,279
Speaker 2: was like going down these you two rabbit holes, which

760
00:38:01,360 --> 00:38:05,880
Speaker 2: I have anecdotally heard, is how many people you know

761
00:38:06,120 --> 00:38:09,720
Speaker 2: became into sort of more extreme figures on the internet.

762
00:38:10,320 --> 00:38:16,040
Speaker 2: How would you describe the process of people becoming radicalized.

763
00:38:16,640 --> 00:38:18,480
Speaker 3: I think it's sort of like, you know, how like

764
00:38:18,880 --> 00:38:21,120
Speaker 3: was it battleships have like sonar, you know, where like

765
00:38:21,160 --> 00:38:22,759
Speaker 3: you send out a ping and then you see if

766
00:38:22,760 --> 00:38:24,839
Speaker 3: it hits something, and then if it comes back, then

767
00:38:24,880 --> 00:38:27,399
Speaker 3: you know that there's something out there. Right. I think

768
00:38:27,400 --> 00:38:29,160
Speaker 3: a lot of social media users we were talking about

769
00:38:29,200 --> 00:38:32,480
Speaker 3: like why do people use social media earlier? And I

770
00:38:32,520 --> 00:38:36,160
Speaker 3: think like if you imagine yourself as someone who's socially isolated,

771
00:38:36,400 --> 00:38:40,640
Speaker 3: separated from the world, maybe just bored whatever it is,

772
00:38:40,680 --> 00:38:43,000
Speaker 3: and you're just sort of sending out these sonar signals

773
00:38:43,040 --> 00:38:46,160
Speaker 3: on social media, and I think you really quickly learn,

774
00:38:46,600 --> 00:38:50,959
Speaker 3: you know, that you can get attention for pathological behavior, right.

775
00:38:51,440 --> 00:38:53,360
Speaker 3: And we have a lot of stories in our research

776
00:38:53,440 --> 00:38:55,839
Speaker 3: of people who are like, you know, like I'll give

777
00:38:55,840 --> 00:38:59,080
Speaker 3: you an example, like a woman who like voted for Obama.

778
00:38:59,560 --> 00:39:02,719
Speaker 3: You know, it's like a moderate Democrat that's really liked

779
00:39:02,719 --> 00:39:08,120
Speaker 3: Obama and then got sort of upset about Trayvon Martin

780
00:39:08,440 --> 00:39:10,960
Speaker 3: when when Obama you know, sort of was critical of

781
00:39:11,000 --> 00:39:13,319
Speaker 3: the police, she had a family member of his police

782
00:39:13,360 --> 00:39:16,120
Speaker 3: officer got really mad and starts saying, you know, a

783
00:39:16,120 --> 00:39:19,040
Speaker 3: few sort of mild criticisms of Obama online, and like,

784
00:39:19,160 --> 00:39:22,760
Speaker 3: pretty soon this woman is like blowing up on Twitter

785
00:39:22,800 --> 00:39:25,960
Speaker 3: because you know, she's like she's a Democrat who's criticizing Obama,

786
00:39:26,000 --> 00:39:29,359
Speaker 3: which all of a sudden like opens up her audience massively, right,

787
00:39:30,239 --> 00:39:32,680
Speaker 3: and two or three years later she's gotten Maga in

788
00:39:32,719 --> 00:39:35,200
Speaker 3: her Twitter bio, And like, you know, I think that

789
00:39:35,360 --> 00:39:37,880
Speaker 3: sort of exemplifies the path of a lot of people, right,

790
00:39:37,920 --> 00:39:40,480
Speaker 3: if it's if it's about belonging and finding you know,

791
00:39:40,520 --> 00:39:44,239
Speaker 3: your people, like you know, you're going to become the

792
00:39:44,640 --> 00:39:48,279
Speaker 3: people the person that other people reward, and unfortunately, too

793
00:39:48,320 --> 00:39:51,040
Speaker 3: often that's a that's a pretty extreme identity.

794
00:39:51,200 --> 00:39:52,680
Speaker 1: Well and like you said, I mean, we used to

795
00:39:52,719 --> 00:39:55,920
Speaker 1: know twenty people and now it's infinite people. So our

796
00:39:55,920 --> 00:39:58,440
Speaker 1: brain has no idea how to make all those people

797
00:39:58,680 --> 00:40:01,520
Speaker 1: happy or yeah.

798
00:40:01,040 --> 00:40:03,279
Speaker 3: Exactly exactly, And you know, like this cuts to the

799
00:40:03,280 --> 00:40:04,759
Speaker 3: core of it for me. You know, if we look

800
00:40:04,800 --> 00:40:08,120
Speaker 3: at like anthropologists who for you know, centuries have studied

801
00:40:08,160 --> 00:40:11,160
Speaker 3: the limitations of the human brain and like early societies

802
00:40:11,200 --> 00:40:14,200
Speaker 3: and stuff like that, And there's a there's an estimate

803
00:40:14,280 --> 00:40:17,839
Speaker 3: that we can all only maintain relationships with like one

804
00:40:17,920 --> 00:40:21,000
Speaker 3: hundred and fifty people max. So maybe it's maybe it's less,

805
00:40:21,000 --> 00:40:23,120
Speaker 3: maybe it is twenty for like a real connection.

806
00:40:23,160 --> 00:40:24,879
Speaker 1: Now that your son's more correct.

807
00:40:25,920 --> 00:40:27,760
Speaker 3: Like for me personally, it's probably like five.

808
00:40:27,840 --> 00:40:31,279
Speaker 1: Yeah, maybe I've just got no.

809
00:40:33,320 --> 00:40:36,320
Speaker 3: Anyhow. Anyhow, let's say it's one fifty. Right. The point

810
00:40:36,360 --> 00:40:40,040
Speaker 3: of Facebook is to connect people, Like the point of

811
00:40:40,480 --> 00:40:44,080
Speaker 3: Instagram is to connect people, right, Like, the whole point

812
00:40:44,160 --> 00:40:46,920
Speaker 3: is connection. What if you know, we've thought for years

813
00:40:46,920 --> 00:40:49,640
Speaker 3: connection is a good thing. And certainly, like there's plenty

814
00:40:49,680 --> 00:40:52,319
Speaker 3: of great examples, right like I would never see cat

815
00:40:52,360 --> 00:40:55,520
Speaker 3: lawyer if it weren't for you know, Twitter, right, like

816
00:40:55,560 --> 00:40:56,800
Speaker 3: the thought of it, Right, I don't know how I

817
00:40:56,800 --> 00:41:02,360
Speaker 3: would live. But with you know that same you know privilege,

818
00:41:02,400 --> 00:41:05,799
Speaker 3: I guess comes you know this, this overwhelming you know

819
00:41:06,000 --> 00:41:09,400
Speaker 3: amount of information, And it's not at all clear to

820
00:41:09,440 --> 00:41:11,840
Speaker 3: me that being able to connect with anyone anywhere is

821
00:41:11,880 --> 00:41:14,200
Speaker 3: actually a good thing for us. And yet if we

822
00:41:14,200 --> 00:41:16,560
Speaker 3: look at the guts of social media, that is the

823
00:41:16,719 --> 00:41:20,200
Speaker 3: principle which guides almost every platform that you should be

824
00:41:20,239 --> 00:41:23,080
Speaker 3: allowed to connect with as many people as possible and

825
00:41:23,200 --> 00:41:25,640
Speaker 3: reach as many people as possible, and your goal should

826
00:41:25,640 --> 00:41:28,480
Speaker 3: always be to influence as many people as possible. Right,

827
00:41:28,800 --> 00:41:30,120
Speaker 3: that's that's sort of weird.

828
00:41:30,640 --> 00:41:33,320
Speaker 2: Yeah, I mean, on the one hand, it's it's amazing

829
00:41:33,360 --> 00:41:36,280
Speaker 2: that you can find your communities of like other people

830
00:41:36,280 --> 00:41:38,799
Speaker 2: who I'm hiking with my cat.

831
00:41:38,880 --> 00:41:41,040
Speaker 1: Oh that's a better one, okay, yeah.

832
00:41:41,160 --> 00:41:41,359
Speaker 3: Yeah.

833
00:41:41,480 --> 00:41:45,120
Speaker 2: Like for me, I got my my OCD diagnosis, I

834
00:41:45,160 --> 00:41:47,120
Speaker 2: was like, oh, that's normal, that's normal, that's normal, and

835
00:41:47,200 --> 00:41:49,680
Speaker 2: like that became integrated into my identity. Like this stuff

836
00:41:49,760 --> 00:41:52,839
Speaker 2: is is important in so many ways because we've been

837
00:41:52,920 --> 00:41:56,000
Speaker 2: isolated in our experiences and now we don't have to be.

838
00:41:56,120 --> 00:41:59,560
Speaker 2: But also when you have infinite communities available to you,

839
00:42:00,520 --> 00:42:02,200
Speaker 2: like exactly not all of them, and you.

840
00:42:02,160 --> 00:42:04,000
Speaker 1: Don't want any of them to get mad at.

841
00:42:03,880 --> 00:42:07,760
Speaker 3: You, exactly exactly right, it's exhausting, Right, it's exhausting.

842
00:42:07,840 --> 00:42:08,960
Speaker 1: Yeah, it's impossible.

843
00:42:09,800 --> 00:42:12,000
Speaker 3: And by the way, like you know, like I don't

844
00:42:12,040 --> 00:42:13,920
Speaker 3: know a lot of people who start down this line

845
00:42:13,960 --> 00:42:15,960
Speaker 3: of reasoning. We'll say things and that's why we need

846
00:42:16,000 --> 00:42:20,440
Speaker 3: to all get off social media and blah blah blah. Yeah, yeah,

847
00:42:20,719 --> 00:42:22,960
Speaker 3: And you know, when I talk to my duke students,

848
00:42:23,040 --> 00:42:25,719
Speaker 3: like I often when I teach class on social media,

849
00:42:25,760 --> 00:42:27,440
Speaker 3: like one of the first things I do is like,

850
00:42:27,560 --> 00:42:30,080
Speaker 3: you know, like pull out a piece of paper and

851
00:42:30,120 --> 00:42:33,000
Speaker 3: write down, like your ten first thoughts about social media,

852
00:42:33,000 --> 00:42:35,800
Speaker 3: like things that happen, you know, recently, And then I

853
00:42:35,800 --> 00:42:37,480
Speaker 3: ask students like how many of them are positive and

854
00:42:37,520 --> 00:42:39,840
Speaker 3: how many of them are negative? And you know, like

855
00:42:39,880 --> 00:42:41,560
Speaker 3: I think a lot of older folks would think, like

856
00:42:41,920 --> 00:42:43,440
Speaker 3: eight or nine of the ten things are going to

857
00:42:43,480 --> 00:42:46,160
Speaker 3: be negative. Like sure enough, like eight or nine of

858
00:42:46,200 --> 00:42:48,279
Speaker 3: the ten things are positive for a lot of for

859
00:42:48,360 --> 00:42:50,360
Speaker 3: a lot of people, for a lot of young people especially,

860
00:42:50,360 --> 00:42:53,840
Speaker 3: And they recognized and have learned to navigate social media

861
00:42:53,840 --> 00:42:57,560
Speaker 3: and make it useful. But more importantly, it's it's part

862
00:42:57,600 --> 00:42:58,919
Speaker 3: of their lives. It's part of our lives.

863
00:42:59,000 --> 00:42:59,080
Speaker 1: Right.

864
00:42:59,120 --> 00:43:02,040
Speaker 3: We're not gonna like retreat to some kind of cabin

865
00:43:02,040 --> 00:43:05,360
Speaker 3: in the woods and communicate with each other via carrier pigeon, right, Like,

866
00:43:05,440 --> 00:43:07,279
Speaker 3: it's just not going to happen, Like we are so

867
00:43:07,400 --> 00:43:10,440
Speaker 3: embedded in this world. Yeah, that the suggestion that we

868
00:43:10,480 --> 00:43:13,360
Speaker 3: can all just like waltz back into nature or somehow

869
00:43:13,400 --> 00:43:17,000
Speaker 3: return to like our neanderthal like you know selves is

870
00:43:17,080 --> 00:43:19,960
Speaker 3: just so naive and it's just how to step with

871
00:43:20,560 --> 00:43:23,439
Speaker 3: what people and especially like younger people want and need.

872
00:43:23,560 --> 00:43:27,160
Speaker 3: So for me, like the danger of that argument, it's

873
00:43:27,200 --> 00:43:30,240
Speaker 3: not just that it's naive, but it actually makes social

874
00:43:30,280 --> 00:43:32,560
Speaker 3: media more toxic. So if you're the type of person

875
00:43:32,719 --> 00:43:35,120
Speaker 3: who is repulsed by what's going on in social media

876
00:43:35,200 --> 00:43:37,759
Speaker 3: and you largely you know, remove yourself, that's like a

877
00:43:38,200 --> 00:43:41,000
Speaker 3: perfectly sensible thing to do for you. But what are

878
00:43:41,000 --> 00:43:44,120
Speaker 3: the consequences for everybody else? If the thoughtful, well intentioned

879
00:43:44,160 --> 00:43:48,080
Speaker 3: people are all leaving, right, it means that the extremists

880
00:43:48,120 --> 00:43:52,120
Speaker 3: and other you know, sort of loudmouthed people will We'll

881
00:43:52,160 --> 00:43:53,240
Speaker 3: just gain more real estate.

882
00:43:53,440 --> 00:43:55,640
Speaker 2: This is what I say to people when they try

883
00:43:55,680 --> 00:43:58,879
Speaker 2: to get out of jury duty, like you, we need

884
00:43:58,960 --> 00:44:00,799
Speaker 2: you don't. Why are the more people trying to get

885
00:44:00,800 --> 00:44:01,480
Speaker 2: out of duriy dude?

886
00:44:02,200 --> 00:44:02,799
Speaker 1: Yeah?

887
00:44:02,920 --> 00:44:06,760
Speaker 2: Or like or not have kids? Not that everyone should

888
00:44:06,760 --> 00:44:09,399
Speaker 2: have kis, everyone should make own decisions. But but yeah,

889
00:44:09,440 --> 00:44:11,960
Speaker 2: I mean, but if modern people are on social media

890
00:44:12,040 --> 00:44:14,759
Speaker 2: and we're not contributing anyway, like, what good is it doing?

891
00:44:14,800 --> 00:44:16,840
Speaker 2: Do we need to be more vocal?

892
00:44:17,160 --> 00:44:19,080
Speaker 3: Yeah? And you know the other thing is like one

893
00:44:19,120 --> 00:44:20,880
Speaker 3: thing I often hear, you know, we were talking about

894
00:44:20,880 --> 00:44:23,880
Speaker 3: politicians earlier, right, like you know, you know, people like

895
00:44:23,960 --> 00:44:27,759
Speaker 3: Joe Manchin, right, Like, that is not most people, right,

896
00:44:27,880 --> 00:44:32,520
Speaker 3: Most people are you know, much much less polarized than

897
00:44:32,520 --> 00:44:34,719
Speaker 3: our elected officials are. Right. So when I hear people

898
00:44:34,719 --> 00:44:37,439
Speaker 3: say like where are the moderates or where are you know,

899
00:44:37,680 --> 00:44:41,000
Speaker 3: where's the middle? It's a perfectly reasonable thing to say.

900
00:44:41,080 --> 00:44:43,400
Speaker 3: If you've just spent a half hour scrolling through Twitter

901
00:44:43,920 --> 00:44:46,160
Speaker 3: and you've seen you know, oh my god, like this

902
00:44:46,200 --> 00:44:49,080
Speaker 3: person's angry, that person's angry. Their arguments are so far apart,

903
00:44:49,160 --> 00:44:50,680
Speaker 3: like how are we ever going to sell something like

904
00:44:50,680 --> 00:44:53,439
Speaker 3: climate change? Right? Then, if you go to talk to people,

905
00:44:54,320 --> 00:44:58,759
Speaker 3: survey people, you find, yes, we disagree about a lot

906
00:44:58,800 --> 00:45:00,759
Speaker 3: of stuff, Like I don't want to minimize that, Like

907
00:45:00,800 --> 00:45:04,600
Speaker 3: we do disagree about some pretty important issues, very important

908
00:45:04,600 --> 00:45:08,600
Speaker 3: issues even but like a majority of Americans wants to compromise.

909
00:45:09,200 --> 00:45:10,759
Speaker 3: You know, you may say, they might not know what

910
00:45:10,800 --> 00:45:12,600
Speaker 3: that means or how they're going to get there, but

911
00:45:12,640 --> 00:45:14,560
Speaker 3: they want it. If you look at a lot of

912
00:45:14,560 --> 00:45:18,640
Speaker 3: different areas from like you know, handgun background checks to

913
00:45:19,360 --> 00:45:22,680
Speaker 3: you know, supports for support for you know, new new

914
00:45:23,560 --> 00:45:27,120
Speaker 3: you know, climate change initiatives that have sort of tax

915
00:45:27,160 --> 00:45:30,200
Speaker 3: incentives for new businesses. Like there are so many areas

916
00:45:30,200 --> 00:45:33,680
Speaker 3: where people actually agree, the politicians make it seem like,

917
00:45:33,840 --> 00:45:36,040
Speaker 3: you know, it's a bridge too far. And the problem

918
00:45:36,120 --> 00:45:38,080
Speaker 3: with social media is, you know, we're all focused on

919
00:45:38,120 --> 00:45:41,240
Speaker 3: these sort of celebrities who are among the most extreme

920
00:45:41,320 --> 00:45:44,040
Speaker 3: parts of the continuum, and so we can really start

921
00:45:44,080 --> 00:45:46,200
Speaker 3: to feel like the middle has just completely fallen out.

922
00:45:47,000 --> 00:45:48,640
Speaker 2: So I was going to ask you what is false

923
00:45:48,680 --> 00:45:53,640
Speaker 2: polarization and that's basically what you're describing right now, right, Yeah.

924
00:45:53,480 --> 00:45:55,040
Speaker 3: It's super interesting. I mean this is something that was

925
00:45:55,080 --> 00:45:58,000
Speaker 3: around before social media. So if you you know, back

926
00:45:58,040 --> 00:46:02,000
Speaker 3: in like the nineteen eighties, even you know, folks at

927
00:46:02,040 --> 00:46:06,320
Speaker 3: like Arvard and Princeton, we're studying, you know, what people

928
00:46:06,480 --> 00:46:09,600
Speaker 3: thought and then what they thought the other side thought

929
00:46:09,640 --> 00:46:12,600
Speaker 3: about an issue. So for example, I might ask you,

930
00:46:12,600 --> 00:46:16,440
Speaker 3: you know, what do you think about, you know, a

931
00:46:16,480 --> 00:46:19,960
Speaker 3: woman's right to choose? Right, And then you know, now

932
00:46:19,960 --> 00:46:21,880
Speaker 3: that I know you're you're a liberal, I'll say, what

933
00:46:21,920 --> 00:46:25,279
Speaker 3: do you think most conservatives think about a women's right

934
00:46:25,320 --> 00:46:28,640
Speaker 3: to choose? And you may say, you know, you're you're

935
00:46:28,760 --> 00:46:31,960
Speaker 3: you're by and large people are going to way exaggerate

936
00:46:32,200 --> 00:46:37,160
Speaker 3: how extreme the other side is and underestimate how ideological

937
00:46:37,239 --> 00:46:40,640
Speaker 3: their own side is. And what's there's a few problems

938
00:46:40,680 --> 00:46:43,120
Speaker 3: with that one is right, we we it's sort of tragic.

939
00:46:43,160 --> 00:46:45,600
Speaker 3: We don't realize we have a lot more to agree

940
00:46:45,600 --> 00:46:48,359
Speaker 3: about than than than we thought we did. But also

941
00:46:48,400 --> 00:46:51,920
Speaker 3: it makes everybody feel more polarized because everybody thinks that

942
00:46:52,000 --> 00:46:55,480
Speaker 3: of the other side. So you know, just like you know, you,

943
00:46:55,520 --> 00:46:58,560
Speaker 3: as a liberal person might be exaggerating the extremity of

944
00:46:58,600 --> 00:47:00,840
Speaker 3: a conservatives, the conservatives are doing it right back to you,

945
00:47:01,320 --> 00:47:03,360
Speaker 3: and both of you begin to feel more and more

946
00:47:03,760 --> 00:47:04,600
Speaker 3: like it's hopeless.

947
00:47:04,880 --> 00:47:07,680
Speaker 1: Are you conducting these surveys in person? Is that what

948
00:47:07,880 --> 00:47:11,319
Speaker 1: changes the the energy around it.

949
00:47:12,640 --> 00:47:15,000
Speaker 3: We did our interviews by phone, but even by phone,

950
00:47:15,080 --> 00:47:17,160
Speaker 3: right you know, you see these dynamics, I mean, certainly

951
00:47:17,160 --> 00:47:19,480
Speaker 3: in person it gets even more real. You know, Like

952
00:47:19,520 --> 00:47:22,520
Speaker 3: there's some really interesting efforts in other countries, for example,

953
00:47:22,640 --> 00:47:25,640
Speaker 3: to use to conduct like, you know it just kind

954
00:47:25,640 --> 00:47:28,720
Speaker 3: of in person meetings. In Germany, there's a really interesting

955
00:47:28,760 --> 00:47:31,480
Speaker 3: effort to bring like influencers together to to sort of

956
00:47:31,520 --> 00:47:35,360
Speaker 3: guess each other's political beliefs and then predictably they're really wrong,

957
00:47:35,520 --> 00:47:36,920
Speaker 3: and then they you know, they have this kind of

958
00:47:36,920 --> 00:47:39,279
Speaker 3: warm moment where they're like, oh, we're not so we're

959
00:47:39,320 --> 00:47:43,080
Speaker 3: not a part right, So you know, there's there's stuff

960
00:47:43,120 --> 00:47:46,000
Speaker 3: like that, and you know, certainly, I think there's a

961
00:47:46,040 --> 00:47:48,480
Speaker 3: ton of evidence that getting together in person. In fact,

962
00:47:48,520 --> 00:47:52,279
Speaker 3: in one study from University of Pennsylvania indicates that a

963
00:47:52,320 --> 00:47:56,080
Speaker 3: simple fifteen minute conversation between a Republican and a Democrat

964
00:47:56,280 --> 00:48:00,600
Speaker 3: in a library can move our pains of each other

965
00:48:00,600 --> 00:48:03,239
Speaker 3: by about fifteen percentage points one hundred point scale, which

966
00:48:03,280 --> 00:48:06,279
Speaker 3: is a huge effect, especially in such polarized times. So

967
00:48:06,640 --> 00:48:09,279
Speaker 3: absolutely getting together in person is great. But hey, let's

968
00:48:09,320 --> 00:48:11,839
Speaker 3: face it, like that's not happening very much anymore, right,

969
00:48:11,920 --> 00:48:15,720
Speaker 3: not only because Republicans and Democrats increasingly live in different

970
00:48:15,800 --> 00:48:18,880
Speaker 3: zip codes, but also like through COVID and whatever norms

971
00:48:18,880 --> 00:48:21,399
Speaker 3: have been established through COVID, like we just don't hang

972
00:48:21,400 --> 00:48:25,320
Speaker 3: out with unusual people or you know, new people very often,

973
00:48:26,400 --> 00:48:29,399
Speaker 3: and increasingly social media is becoming the place where all

974
00:48:29,440 --> 00:48:33,080
Speaker 3: of those conversations are moving and that's probably not a

975
00:48:33,120 --> 00:48:33,480
Speaker 3: great thing.

976
00:48:33,880 --> 00:48:36,720
Speaker 2: Well, that's so interesting to me because it is about

977
00:48:36,880 --> 00:48:40,440
Speaker 2: exposure to the perspective of the other side, But it's

978
00:48:40,480 --> 00:48:44,160
Speaker 2: about the exposure to their humanity and complexity and not

979
00:48:44,280 --> 00:48:47,920
Speaker 2: just exposure to like some of the more extreme things.

980
00:48:47,880 --> 00:48:52,959
Speaker 1: Words on a screen with an exclamation point. Yeah, yeah, yeah.

981
00:48:53,000 --> 00:48:56,600
Speaker 2: So I feel like the common idea about it that like, oh,

982
00:48:56,640 --> 00:48:58,759
Speaker 2: we just need to talk more like is sort of

983
00:48:58,840 --> 00:49:02,040
Speaker 2: true in a way, but the Internet just sort of

984
00:49:02,680 --> 00:49:05,440
Speaker 2: puts up a wall and makes that much more difficult

985
00:49:05,440 --> 00:49:07,480
Speaker 2: to actually do, right.

986
00:49:07,320 --> 00:49:09,200
Speaker 3: Yeah, And like you said, you know, it's it's all

987
00:49:09,200 --> 00:49:11,719
Speaker 3: about these things called identities, right like that we all

988
00:49:11,840 --> 00:49:14,120
Speaker 3: we all care as soon as we have an identity,

989
00:49:14,239 --> 00:49:16,239
Speaker 3: you know, we have like our marching orders, right Like,

990
00:49:16,400 --> 00:49:19,120
Speaker 3: I am a Democrat, I'm supposed to think this about Republicans.

991
00:49:19,120 --> 00:49:20,840
Speaker 3: I'm a Republican. I supposed to think about you know,

992
00:49:20,840 --> 00:49:23,200
Speaker 3: the sort of thing about democrats. One of the things

993
00:49:23,280 --> 00:49:25,640
Speaker 3: we wanted to do in our research is ask the question,

994
00:49:25,719 --> 00:49:28,680
Speaker 3: like what if you could take identity out of the equation.

995
00:49:29,680 --> 00:49:32,120
Speaker 3: And so what we did is we created our own

996
00:49:32,160 --> 00:49:34,520
Speaker 3: social media platform. And we did this because we wanted

997
00:49:34,520 --> 00:49:36,320
Speaker 3: to do all sorts of new studies, but one of

998
00:49:36,360 --> 00:49:38,320
Speaker 3: the first ones we wanted to do is to see,

999
00:49:38,360 --> 00:49:43,880
Speaker 3: like what about anonymous conversation Now you may hear that

1000
00:49:43,920 --> 00:49:46,960
Speaker 3: and say, like Chris, you're crazy. Like most of the

1001
00:49:47,000 --> 00:49:50,200
Speaker 3: most vile you know, discussion on the Internet is anonymous. Like,

1002
00:49:50,600 --> 00:49:52,799
Speaker 3: you know, people who are anonymous will say things they

1003
00:49:52,800 --> 00:49:55,040
Speaker 3: would never say in real life. Right, we've all seen that,

1004
00:49:55,080 --> 00:49:56,920
Speaker 3: we've all all experienced it. You know, those are the

1005
00:49:56,920 --> 00:49:59,840
Speaker 3: ones giving us death threats primarily, Right. But in the

1006
00:50:00,000 --> 00:50:04,640
Speaker 3: other hand, anonymous conversation has some underappreciated features, Like let's

1007
00:50:04,640 --> 00:50:07,439
Speaker 3: go back to that Republican, that modern Republican who maybe

1008
00:50:07,480 --> 00:50:11,319
Speaker 3: has concerns about, you know, whether voter fraud actually happened. Right,

1009
00:50:12,280 --> 00:50:15,440
Speaker 3: if we enter a public space where we wear you know,

1010
00:50:15,719 --> 00:50:18,040
Speaker 3: our team's name on our sleeves, which we basically do

1011
00:50:18,120 --> 00:50:21,160
Speaker 3: on a place like Twitter, right, we're not gonna we're

1012
00:50:21,160 --> 00:50:22,920
Speaker 3: just not going to talk about that. Right, But if

1013
00:50:22,960 --> 00:50:25,680
Speaker 3: we enter an anonymous forum, you know, where we're free

1014
00:50:25,760 --> 00:50:28,480
Speaker 3: from peer pressure, you know, we might be much more

1015
00:50:28,600 --> 00:50:33,640
Speaker 3: likely to explore unusual or unpopular ideas on our side.

1016
00:50:33,800 --> 00:50:36,560
Speaker 3: And you know, surprisingly, at least it was sprisened to me.

1017
00:50:36,800 --> 00:50:38,640
Speaker 3: That's what we found. So when we put a really

1018
00:50:38,719 --> 00:50:42,280
Speaker 3: large group of Republicans and Democrats in this anonymous chat platform,

1019
00:50:42,400 --> 00:50:45,920
Speaker 3: it really could have gone wrong, right, We could imagine

1020
00:50:46,000 --> 00:50:49,279
Speaker 3: people could have really ripped into each other, and a

1021
00:50:49,280 --> 00:50:51,120
Speaker 3: few people did so much, so much that we had

1022
00:50:51,120 --> 00:50:54,200
Speaker 3: to shut one or two conversations down, But the overwhelming

1023
00:50:54,239 --> 00:50:59,520
Speaker 3: majority of people actually had you know, remarkably productive conversations.

1024
00:50:59,560 --> 00:50:59,640
Speaker 2: You know.

1025
00:50:59,760 --> 00:51:03,800
Speaker 3: Yeah, you know, you know, a mother of two from

1026
00:51:04,080 --> 00:51:09,799
Speaker 3: inner city talking to a you know, deeply republican you know,

1027
00:51:09,960 --> 00:51:13,800
Speaker 3: AK forty seven owner in North Dakota about gun violence,

1028
00:51:13,840 --> 00:51:17,000
Speaker 3: and they're finding common ground in this you know, brief

1029
00:51:17,160 --> 00:51:20,280
Speaker 3: anonymous conversation online. And if they ever had that conversation

1030
00:51:20,360 --> 00:51:24,839
Speaker 3: imperfect in person, it probably would go profoundly differently, right,

1031
00:51:24,840 --> 00:51:28,320
Speaker 3: as soon as they saw each other's race, class, political ideology, whatever,

1032
00:51:28,800 --> 00:51:31,920
Speaker 3: they would instantly sort of retreat into their predictable partisan

1033
00:51:31,920 --> 00:51:34,080
Speaker 3: positions and they would never even have a conversation. So,

1034
00:51:34,760 --> 00:51:38,000
Speaker 3: you know, figuring out ways that we can de emphasize identity,

1035
00:51:38,040 --> 00:51:39,719
Speaker 3: I think is important, or maybe even to try to

1036
00:51:39,719 --> 00:51:42,680
Speaker 3: create some new identities, you know, where there can be

1037
00:51:42,760 --> 00:51:46,839
Speaker 3: common ground. Easier said than done, obviously, but you know,

1038
00:51:47,040 --> 00:51:49,200
Speaker 3: it does seem that if we can sort of tone

1039
00:51:49,239 --> 00:51:52,200
Speaker 3: down that instinct to protect our side and sort of

1040
00:51:52,200 --> 00:51:55,600
Speaker 3: attack the other side, that's probably a key part of

1041
00:51:55,760 --> 00:51:57,640
Speaker 3: the solution, Right.

1042
00:51:57,520 --> 00:52:00,960
Speaker 2: I can't that sounds like an incredible platform, But also

1043
00:52:01,040 --> 00:52:02,719
Speaker 2: I can see why it wouldn't be there wouldn't be

1044
00:52:02,719 --> 00:52:05,240
Speaker 2: as much incentive to join it because we just really

1045
00:52:05,280 --> 00:52:10,319
Speaker 2: are driven to seek status and seek belonging and like,

1046
00:52:10,360 --> 00:52:13,640
Speaker 2: without that, then why why even go on there? Like

1047
00:52:13,719 --> 00:52:17,640
Speaker 2: not that many people are interested in like just good discourse.

1048
00:52:17,520 --> 00:52:19,880
Speaker 3: Right, Yeah, And that's the challenge, right, Like, so I

1049
00:52:19,920 --> 00:52:21,920
Speaker 3: agree with you, Like, it's not as if there's this

1050
00:52:22,040 --> 00:52:24,920
Speaker 3: like untapped you know, majority that wants to go talk

1051
00:52:24,960 --> 00:52:27,760
Speaker 3: about politics in an anonymous place. That I totally agree.

1052
00:52:27,960 --> 00:52:30,439
Speaker 3: But it's also the case that most people everywhere don't

1053
00:52:30,440 --> 00:52:32,160
Speaker 3: want to talk about politics. If we look at like

1054
00:52:32,680 --> 00:52:35,080
Speaker 3: large scale surveys, right, most people try to avoid talking

1055
00:52:35,080 --> 00:52:37,319
Speaker 3: about politics. It's usually only a small group of people

1056
00:52:37,360 --> 00:52:40,640
Speaker 3: who really care a lot, and those people, for better

1057
00:52:40,719 --> 00:52:42,319
Speaker 3: or worse, have a lot of influence. You know. So

1058
00:52:42,360 --> 00:52:44,480
Speaker 3: you might say, like, yeah, well, not everybody's on Twitter,

1059
00:52:44,920 --> 00:52:48,279
Speaker 3: but if Twitter can start you know, a protest or

1060
00:52:48,400 --> 00:52:51,520
Speaker 3: you know, violent insurrection, then we probably should care about

1061
00:52:51,520 --> 00:52:54,239
Speaker 3: Twitter and what's happening on Twitter. Right, So you know,

1062
00:52:54,560 --> 00:52:56,279
Speaker 3: it's not as if I think you can do one

1063
00:52:56,320 --> 00:53:00,480
Speaker 3: thing that like say, changes Facebook and then like everything changed, right.

1064
00:53:00,600 --> 00:53:03,240
Speaker 3: I think increasingly we're seeing the splintering of social media,

1065
00:53:03,600 --> 00:53:06,480
Speaker 3: and I think there are places that could be created

1066
00:53:07,040 --> 00:53:10,239
Speaker 3: that would appeal to a smaller number of people. But

1067
00:53:10,320 --> 00:53:13,719
Speaker 3: if we could move, you know, disincentivize them to you know,

1068
00:53:13,880 --> 00:53:16,480
Speaker 3: ruin Twitter for the rest of us, and you know,

1069
00:53:16,640 --> 00:53:20,440
Speaker 3: move their their conversation about inflation over to this enomous

1070
00:53:20,680 --> 00:53:24,040
Speaker 3: platform right now bore us to death. You know, maybe

1071
00:53:24,040 --> 00:53:26,400
Speaker 3: that'd be better for everybody. It's an interesting argument.

1072
00:53:28,400 --> 00:53:30,359
Speaker 2: I do hear so many people talking about like we're

1073
00:53:30,360 --> 00:53:32,319
Speaker 2: all we're just going to get off of social media

1074
00:53:32,360 --> 00:53:33,920
Speaker 2: and go live on a commune. And I think the

1075
00:53:33,960 --> 00:53:35,640
Speaker 2: majority of people are not going to do that, but

1076
00:53:35,760 --> 00:53:39,160
Speaker 2: a small subsect of people will do that.

1077
00:53:39,440 --> 00:53:40,920
Speaker 1: Yeah, they'll probably.

1078
00:53:41,000 --> 00:53:44,080
Speaker 2: End up in communes in cults because we need we

1079
00:53:44,120 --> 00:53:45,920
Speaker 2: need identity young when we're.

1080
00:53:47,640 --> 00:53:48,399
Speaker 3: Yeah, you're right.

1081
00:53:48,560 --> 00:53:51,479
Speaker 2: I feel like the talk like commune talk is coming

1082
00:53:51,560 --> 00:53:53,279
Speaker 2: up more and more and more, and I'm like, you guys,

1083
00:53:53,360 --> 00:53:56,000
Speaker 2: you know it's the same thing. It's just like yeah,

1084
00:53:56,080 --> 00:54:00,640
Speaker 2: in person in a couple of years, Yeah, why why

1085
00:54:00,640 --> 00:54:02,399
Speaker 2: I must we need community like this?

1086
00:54:02,760 --> 00:54:05,319
Speaker 1: I don't know if this is a very inconvenient. Yeah,

1087
00:54:05,320 --> 00:54:08,600
Speaker 1: it is right. I would like to stop needing identity

1088
00:54:08,680 --> 00:54:12,799
Speaker 1: and community very badly. But you know, it's almost like

1089
00:54:13,520 --> 00:54:17,319
Speaker 1: we need to combat narcissism because they're the ones who

1090
00:54:17,400 --> 00:54:20,840
Speaker 1: are online saying. I'm not saying they're all narcissists, that

1091
00:54:20,880 --> 00:54:23,640
Speaker 1: everybody on Twitter with the following is a narcissist, but

1092
00:54:23,719 --> 00:54:27,399
Speaker 1: there is this way of behave Okay, there's this way

1093
00:54:27,440 --> 00:54:32,480
Speaker 1: of behaving that we center around as human beings, and

1094
00:54:32,640 --> 00:54:35,880
Speaker 1: it's almost like we have to figure out how to

1095
00:54:36,040 --> 00:54:39,920
Speaker 1: stop circling around narcissists because it just keeps happening because.

1096
00:54:39,719 --> 00:54:42,279
Speaker 2: We're drawn to people who make really loud statements with

1097
00:54:42,440 --> 00:54:43,440
Speaker 2: lots of confidence.

1098
00:54:43,480 --> 00:54:46,080
Speaker 1: So you can be the craziest cult leader on the planet.

1099
00:54:46,120 --> 00:54:48,240
Speaker 1: But if you're like, I think they know what they're doing,

1100
00:54:48,320 --> 00:54:51,080
Speaker 1: so I'm just gonna like go along with it. You know,

1101
00:54:51,360 --> 00:54:53,240
Speaker 1: is there any parallel there?

1102
00:54:53,760 --> 00:54:55,680
Speaker 3: Well, I think like it's just it's again, it's this

1103
00:54:55,760 --> 00:54:57,920
Speaker 3: question of where we're going. You know, like I feel

1104
00:54:57,920 --> 00:55:00,480
Speaker 3: like we're on sort of a rudderless shit with so media.

1105
00:55:00,640 --> 00:55:03,399
Speaker 3: You know, like nobody steps back and says like, hey,

1106
00:55:03,520 --> 00:55:06,200
Speaker 3: this isn't working too well. What could we do differently?

1107
00:55:06,400 --> 00:55:06,600
Speaker 2: You know.

1108
00:55:06,640 --> 00:55:09,120
Speaker 3: Instead it's like, hey, given that we have a bunch

1109
00:55:09,120 --> 00:55:11,399
Speaker 3: of narcissists ruin it for the rest of us, how

1110
00:55:11,400 --> 00:55:13,920
Speaker 3: can we maybe convince them to be a little less awful? Right?

1111
00:55:13,960 --> 00:55:15,879
Speaker 3: That's sort of the tone of our conversation right now

1112
00:55:16,160 --> 00:55:18,160
Speaker 3: in the companies, that's the tone of the conversation. In

1113
00:55:18,280 --> 00:55:20,759
Speaker 3: policy regulation, that's the tone of the conversation right like

1114
00:55:20,760 --> 00:55:24,160
Speaker 3: should there be more content moderation? Should there not? And

1115
00:55:24,560 --> 00:55:27,040
Speaker 3: the problem for me is just like we never step

1116
00:55:27,120 --> 00:55:29,960
Speaker 3: back and ask, like what is the purpose of social media?

1117
00:55:30,080 --> 00:55:31,800
Speaker 3: You know, I love the question that you asked me

1118
00:55:31,840 --> 00:55:33,960
Speaker 3: at the beginning of this interview, which is why do

1119
00:55:34,040 --> 00:55:35,160
Speaker 3: people use social media?

1120
00:55:35,239 --> 00:55:35,399
Speaker 2: Right?

1121
00:55:35,960 --> 00:55:37,799
Speaker 3: And I think if you ask most people like they

1122
00:55:37,840 --> 00:55:39,719
Speaker 3: can't even articulate it, right. It's just a thing that

1123
00:55:39,760 --> 00:55:42,600
Speaker 3: we do. It's like you know, taking a shower at

1124
00:55:42,600 --> 00:55:44,400
Speaker 3: this point, it's like, you know, I got to check Twitter?

1125
00:55:44,480 --> 00:55:47,120
Speaker 3: Right or It's not like it very rarely is it

1126
00:55:47,200 --> 00:55:49,919
Speaker 3: like this willful thing where we're like, oh, I'm going

1127
00:55:49,960 --> 00:55:52,120
Speaker 3: to go, you know, have a laugh on Twitter? Like

1128
00:55:52,160 --> 00:55:54,000
Speaker 3: it's it's just sort of like these things in our

1129
00:55:54,040 --> 00:55:56,040
Speaker 3: pockets are like constantly there for us to check, and

1130
00:55:56,080 --> 00:55:59,560
Speaker 3: they bother us if we don't, right, But you know,

1131
00:55:59,800 --> 00:56:02,680
Speaker 3: we have this sort of like rudderless experience on social

1132
00:56:02,719 --> 00:56:04,520
Speaker 3: media where it's like, what are we even doing? You know?

1133
00:56:04,560 --> 00:56:09,120
Speaker 3: There there is no purpose to Facebook, no purpose Twitter, right.

1134
00:56:09,160 --> 00:56:11,040
Speaker 2: To look up birthdays when I don't remember that?

1135
00:56:11,200 --> 00:56:15,200
Speaker 3: Yeah, yeah, now I talk I talked to my under

1136
00:56:15,320 --> 00:56:17,319
Speaker 3: my college students about this a lot, and I'm like,

1137
00:56:17,360 --> 00:56:19,560
Speaker 3: you know, like I said, what's the purpose of Facebook?

1138
00:56:19,560 --> 00:56:21,759
Speaker 3: And it's like, oh, that's where we pretend that we

1139
00:56:21,840 --> 00:56:24,239
Speaker 3: use social media for our parents and grandparents so that

1140
00:56:24,239 --> 00:56:24,760
Speaker 3: they don't.

1141
00:56:24,560 --> 00:56:26,800
Speaker 1: Look us up on TikTok exactly.

1142
00:56:28,000 --> 00:56:30,360
Speaker 3: So like no, but seriously, there's no point, right, And

1143
00:56:30,400 --> 00:56:34,120
Speaker 3: that's a big problem because everything follows from that purpose.

1144
00:56:34,239 --> 00:56:37,920
Speaker 3: Right if the purpose is influencer culture and advertising and

1145
00:56:38,000 --> 00:56:41,160
Speaker 3: viral diffusion, which is pretty much how every platform is

1146
00:56:41,160 --> 00:56:43,239
Speaker 3: set up to promote those things, Like that's what we're

1147
00:56:43,239 --> 00:56:45,359
Speaker 3: going to get. We're going to reward narcissism, We're going

1148
00:56:45,400 --> 00:56:47,920
Speaker 3: to reward extremism, We're going to reward so like, I

1149
00:56:47,920 --> 00:56:49,600
Speaker 3: think it has to sort of step back for a moment,

1150
00:56:49,600 --> 00:56:51,920
Speaker 3: you know, if we all like if we again we're

1151
00:56:51,920 --> 00:56:54,200
Speaker 3: a little more introspective, like what are we hoping to get?

1152
00:56:54,200 --> 00:56:58,520
Speaker 3: Out of social media, I mean, better relationships, more useful

1153
00:56:58,560 --> 00:57:02,719
Speaker 3: information or high quality information, you know, like there's a

1154
00:57:02,800 --> 00:57:04,799
Speaker 3: market there, like the thing that I have, the thing

1155
00:57:04,800 --> 00:57:08,680
Speaker 3: that gives me hope. Like, okay, so I'm pretty pessimistic

1156
00:57:08,760 --> 00:57:10,520
Speaker 3: at times, but like, you know, this is one thing

1157
00:57:10,520 --> 00:57:14,000
Speaker 3: I'm actually sort of optimistic about. Nobody's really happy with

1158
00:57:14,040 --> 00:57:16,280
Speaker 3: social media. Like nobody would say like don't you think

1159
00:57:16,280 --> 00:57:18,480
Speaker 3: Twitter are just doing a great job or Facebook is

1160
00:57:18,520 --> 00:57:21,240
Speaker 3: just you know, like you know that you know, it's

1161
00:57:21,280 --> 00:57:23,880
Speaker 3: it's exactly the opposite, right There's an appetite like can't

1162
00:57:23,880 --> 00:57:25,560
Speaker 3: we do better? Isn't there a way that we can

1163
00:57:25,600 --> 00:57:28,520
Speaker 3: make this better? And instead of kaind of like trying

1164
00:57:28,560 --> 00:57:30,520
Speaker 3: to fix a broken system, I think we just need

1165
00:57:30,560 --> 00:57:32,240
Speaker 3: to step back and say, like, hey, we are early

1166
00:57:32,320 --> 00:57:35,080
Speaker 3: in the story of social media. There are so many

1167
00:57:35,280 --> 00:57:38,480
Speaker 3: other options, and we need creativity. That's what we need

1168
00:57:38,560 --> 00:57:41,800
Speaker 3: right now, not like you know, more hard work or

1169
00:57:41,800 --> 00:57:45,280
Speaker 3: more like we just need ideas. And you know, the

1170
00:57:45,320 --> 00:57:48,280
Speaker 3: one thing that gives me, you know, hope is that

1171
00:57:48,840 --> 00:57:51,640
Speaker 3: this sector is you know, full of creative people, and

1172
00:57:52,520 --> 00:57:55,240
Speaker 3: hopefully people outside of the tech sector will come into

1173
00:57:55,320 --> 00:57:57,720
Speaker 3: and say like, hey, yeah, maybe it's social science that

1174
00:57:57,720 --> 00:57:59,600
Speaker 3: should guide us. Maybe we should use that one hundred

1175
00:57:59,600 --> 00:58:01,760
Speaker 3: and fifty number. Oh, don't foind at me. I don't

1176
00:58:01,760 --> 00:58:06,120
Speaker 3: want that job. Yeah, you know, how do we you know,

1177
00:58:06,160 --> 00:58:08,040
Speaker 3: maybe it's maybe it's we cut down the number of

1178
00:58:08,880 --> 00:58:12,120
Speaker 3: connections we can have. Maybe it's something even more fundamental,

1179
00:58:12,160 --> 00:58:14,200
Speaker 3: like why do we even have news feeds? Like news

1180
00:58:14,240 --> 00:58:16,200
Speaker 3: feeds are weird when you think about it, Like, I'm

1181
00:58:16,200 --> 00:58:19,600
Speaker 3: interacting with bits of information, not people, right, I'm not

1182
00:58:19,680 --> 00:58:21,400
Speaker 3: seeing a group of people like I would if I

1183
00:58:21,440 --> 00:58:23,720
Speaker 3: walked into like a cocktail party or something like that,

1184
00:58:24,000 --> 00:58:27,080
Speaker 3: And so I'm just broad, you know, like, you know,

1185
00:58:27,440 --> 00:58:31,720
Speaker 3: confronted with these like angry messages again and again and again.

1186
00:58:32,120 --> 00:58:34,480
Speaker 3: And that's just a really weird way to interact with

1187
00:58:34,520 --> 00:58:36,960
Speaker 3: the world, you know, Like we see the world as

1188
00:58:37,000 --> 00:58:40,680
Speaker 3: social groups, as communities, as towns, as villages, as social networks, right,

1189
00:58:40,720 --> 00:58:43,120
Speaker 3: Like couldn't we get more creative with the way that

1190
00:58:43,160 --> 00:58:46,560
Speaker 3: social media even just looks let alone, why we build

1191
00:58:46,600 --> 00:58:48,320
Speaker 3: it or how it, you know, to make it a

1192
00:58:48,360 --> 00:58:51,040
Speaker 3: more natural experience? Like these are the types of things

1193
00:58:51,040 --> 00:58:53,800
Speaker 3: that get me excited and that make me think, you know, hey,

1194
00:58:54,000 --> 00:58:55,800
Speaker 3: we're early in the story. We got a long way

1195
00:58:55,840 --> 00:58:58,000
Speaker 3: to go, but that the good news is that means

1196
00:58:58,000 --> 00:58:59,360
Speaker 3: it can only get better from here.

1197
00:59:00,280 --> 00:59:03,240
Speaker 1: So maybe yeah, we just need to swallow. Hey, I'm

1198
00:59:03,240 --> 00:59:05,080
Speaker 1: going to post something. It's going to get no likes

1199
00:59:06,000 --> 00:59:06,840
Speaker 1: because it's moderate.

1200
00:59:06,880 --> 00:59:08,400
Speaker 2: I do it.

1201
00:59:08,080 --> 00:59:10,640
Speaker 1: I do it, so it's not going to get any

1202
00:59:10,640 --> 00:59:11,800
Speaker 1: love and I'm going to look like kind of a

1203
00:59:11,800 --> 00:59:14,520
Speaker 1: loser and that's what life is, okay.

1204
00:59:14,640 --> 00:59:16,520
Speaker 2: Or you do what I do, and you post something

1205
00:59:16,600 --> 00:59:18,240
Speaker 2: about your work and no one likes it, and so

1206
00:59:18,320 --> 00:59:21,760
Speaker 2: then you post a Towerking video immediately after telling people

1207
00:59:21,760 --> 00:59:23,280
Speaker 2: to go look at the previous posts.

1208
00:59:23,320 --> 00:59:27,040
Speaker 3: Brilliant, brilliant, yes, yes, Or maybe you get rid of

1209
00:59:27,080 --> 00:59:28,880
Speaker 3: the like button, you know, like this is an example

1210
00:59:28,920 --> 00:59:32,120
Speaker 3: of a fundamental thing, right, Like, on the one hand,

1211
00:59:32,120 --> 00:59:34,120
Speaker 3: that makes us all nervous because like, then what are

1212
00:59:34,120 --> 00:59:35,880
Speaker 3: we doing? Right, But that's sort of the point, right,

1213
00:59:35,960 --> 00:59:38,760
Speaker 3: Like we're looking for likes because that's the thing that

1214
00:59:39,400 --> 00:59:41,720
Speaker 3: the system is set up to do, right, so, you know,

1215
00:59:41,800 --> 00:59:44,640
Speaker 3: And sure enough, when Instagram took off the like button

1216
00:59:44,680 --> 00:59:46,880
Speaker 3: in a random for random set of users in five

1217
00:59:46,960 --> 00:59:50,000
Speaker 3: or six countries over two or three years, they discovered

1218
00:59:50,000 --> 00:59:53,760
Speaker 3: that it was actually leading to less abusive behavior. Like

1219
00:59:53,800 --> 00:59:57,439
Speaker 3: all sorts of good things. Unfortunately we never read about

1220
00:59:57,480 --> 01:00:00,240
Speaker 3: the details of the study because Facebook and Instagram ever

1221
01:00:00,280 --> 01:00:03,840
Speaker 3: released it. But you know those types of things, you know,

1222
01:00:03,880 --> 01:00:05,480
Speaker 3: like why do we even have a like button? What's

1223
01:00:05,520 --> 01:00:06,280
Speaker 3: the point? You know?

1224
01:00:07,080 --> 01:00:08,840
Speaker 2: It was gone for me, we have it was gone

1225
01:00:08,840 --> 01:00:11,479
Speaker 2: for me to talk for one day, and I was so happy.

1226
01:00:11,520 --> 01:00:14,520
Speaker 2: Didn't mean interrupt you, Sorry, I was so happy that day.

1227
01:00:14,560 --> 01:00:17,280
Speaker 2: I was like, I can post pictures of fucking books

1228
01:00:17,320 --> 01:00:19,720
Speaker 2: and like cabins, and like it doesn't have to be

1229
01:00:19,800 --> 01:00:21,600
Speaker 2: my naked body. This is so cool.

1230
01:00:22,280 --> 01:00:26,320
Speaker 1: Nope, just today mine was like that for a minute.

1231
01:00:26,480 --> 01:00:28,520
Speaker 1: I couldn't see any other people's likes either.

1232
01:00:29,240 --> 01:00:32,240
Speaker 2: Actually the trust me account weirdly had that for what

1233
01:00:32,400 --> 01:00:35,200
Speaker 2: But yeah, again it's gone. So anyways, strange, continuous.

1234
01:00:35,200 --> 01:00:37,880
Speaker 3: Sorry, And I learned something today, which is if I

1235
01:00:37,920 --> 01:00:40,000
Speaker 3: want people to pay attention to sociology, I need to

1236
01:00:40,000 --> 01:00:40,640
Speaker 3: do more talking.

1237
01:00:44,480 --> 01:00:45,640
Speaker 2: Can't wait to see that.

1238
01:00:45,840 --> 01:00:47,439
Speaker 1: Yes, wonderful.

1239
01:00:48,720 --> 01:00:52,760
Speaker 2: Given all of this, In what ways does you know

1240
01:00:52,760 --> 01:00:55,360
Speaker 2: because I originally found you because I was looking for

1241
01:00:55,360 --> 01:00:57,240
Speaker 2: people to talk to about just like this idea of

1242
01:00:57,320 --> 01:00:59,760
Speaker 2: mass manipulation propaganda. We're going to do a whole series

1243
01:00:59,760 --> 01:01:02,520
Speaker 2: on that. In what ways given your research and what

1244
01:01:02,560 --> 01:01:06,840
Speaker 2: you understand about social media and the modern world? Are

1245
01:01:06,840 --> 01:01:08,440
Speaker 2: we vulnerable to manipulation?

1246
01:01:09,200 --> 01:01:12,000
Speaker 3: Really good question and one that we had the opportunity

1247
01:01:12,120 --> 01:01:16,000
Speaker 3: to study in a somewhat unusual way. So we had

1248
01:01:16,040 --> 01:01:18,240
Speaker 3: been studying Twitter users, We had been asking them all

1249
01:01:18,280 --> 01:01:21,000
Speaker 3: sorts of questions about politics and what they think for

1250
01:01:21,360 --> 01:01:24,960
Speaker 3: a few weeks, and about a year and a half later,

1251
01:01:25,280 --> 01:01:28,760
Speaker 3: Twitter released is the first platform ever to do this,

1252
01:01:30,200 --> 01:01:34,600
Speaker 3: a giant trove of tweets and videos and all sorts

1253
01:01:34,600 --> 01:01:37,800
Speaker 3: of other content shared by foreign influence operations, so like

1254
01:01:37,920 --> 01:01:41,560
Speaker 3: the Russia linked Internet Research Agency, but also campaigns in Venezuela,

1255
01:01:41,760 --> 01:01:45,400
Speaker 3: China all over the place. And you know, we've all

1256
01:01:45,480 --> 01:01:47,400
Speaker 3: seen this stuff, right and heard about this stuff, and

1257
01:01:47,440 --> 01:01:50,080
Speaker 3: you see these messages like you know, oh, like you know,

1258
01:01:50,600 --> 01:01:52,920
Speaker 3: you know, fake news spreads all over the place, and

1259
01:01:53,000 --> 01:01:55,400
Speaker 3: like you know, face, you know, fake news is ubiquitous,

1260
01:01:55,400 --> 01:01:58,280
Speaker 3: and these campaigns are all over the place. But one

1261
01:01:58,280 --> 01:02:00,880
Speaker 3: thing is much harder to study, and just studying the

1262
01:02:00,920 --> 01:02:04,080
Speaker 3: spread of these ideas is whether they actually influence people.

1263
01:02:04,720 --> 01:02:06,560
Speaker 3: And you know, it's sort of an interesting thing because

1264
01:02:06,600 --> 01:02:08,800
Speaker 3: we all assume that just because they spread that they

1265
01:02:08,840 --> 01:02:10,480
Speaker 3: influence a lot of people. But it's really hard to

1266
01:02:10,480 --> 01:02:12,440
Speaker 3: study because what you really want to know is what

1267
01:02:12,560 --> 01:02:14,800
Speaker 3: someone thought before they saw the thing, and then what

1268
01:02:14,840 --> 01:02:17,280
Speaker 3: they thought after they saw the thing. But in order

1269
01:02:17,360 --> 01:02:19,600
Speaker 3: to do that, you have to have sort of anticipated

1270
01:02:19,600 --> 01:02:22,200
Speaker 3: that there might be this like evil influence campaign and

1271
01:02:22,240 --> 01:02:24,160
Speaker 3: had a survey ready to do that, right, So it's

1272
01:02:24,200 --> 01:02:26,280
Speaker 3: not often that we get to do that. So when

1273
01:02:26,280 --> 01:02:28,600
Speaker 3: we discovered this opportunity, we're like, great, we're going to

1274
01:02:28,640 --> 01:02:31,360
Speaker 3: figure out, like how impactful are these things? And we

1275
01:02:31,400 --> 01:02:34,160
Speaker 3: looked at the data like ninety different ways, you know,

1276
01:02:34,560 --> 01:02:37,760
Speaker 3: latest machine learning techniques, everything we could throw at it.

1277
01:02:38,360 --> 01:02:41,040
Speaker 3: From everything we analyze, the only thing we can say

1278
01:02:41,120 --> 01:02:46,120
Speaker 3: is that people who interact with, especially these Russia linked accounts,

1279
01:02:46,480 --> 01:02:49,760
Speaker 3: don't seem to change their attitudes or behavior at all.

1280
01:02:50,560 --> 01:02:53,800
Speaker 3: Super surprising, right, because we're supposed to be living in

1281
01:02:53,560 --> 01:02:56,760
Speaker 3: the age of fake news or alternative you know, like

1282
01:02:56,920 --> 01:03:01,600
Speaker 3: alternative reality or whatever. But what we found is not

1283
01:03:01,680 --> 01:03:04,840
Speaker 3: only do most people not change their views, but most

1284
01:03:04,880 --> 01:03:10,480
Speaker 3: people who interact with these types of campaigns are a

1285
01:03:10,720 --> 01:03:14,240
Speaker 3: very small group of very active people who are locked

1286
01:03:14,320 --> 01:03:18,760
Speaker 3: deep inside echo chambers, and so somewhat paradoxically, these campaigns

1287
01:03:18,840 --> 01:03:22,200
Speaker 3: tend to have their deepest effect for a small group

1288
01:03:22,240 --> 01:03:24,320
Speaker 3: of people inside echo chambers, and so they kind of

1289
01:03:24,400 --> 01:03:28,920
Speaker 3: quarantine the misinformation. Those people already have such extreme views

1290
01:03:28,920 --> 01:03:31,000
Speaker 3: that when they when someone tries to change their view,

1291
01:03:31,000 --> 01:03:33,360
Speaker 3: it can't become any more extreme, and so it's sort

1292
01:03:33,360 --> 01:03:36,160
Speaker 3: of this weird, weird effect, you know, you know, so

1293
01:03:36,520 --> 01:03:38,840
Speaker 3: they're there again, you know, just like the echo chamber,

1294
01:03:38,960 --> 01:03:41,400
Speaker 3: the algorithm. It's another like popular idea that I wish

1295
01:03:41,480 --> 01:03:44,040
Speaker 3: was true, Like it would be much easier to say, hey,

1296
01:03:44,440 --> 01:03:47,000
Speaker 3: let's crack down on Russia or whoever it is trying

1297
01:03:47,040 --> 01:03:50,360
Speaker 3: to influence us. But it doesn't seem like that alone

1298
01:03:50,480 --> 01:03:51,560
Speaker 3: is going to solve the problem.

1299
01:03:52,320 --> 01:03:57,160
Speaker 2: Well, that just makes me wonder because I certainly took

1300
01:03:57,200 --> 01:04:01,800
Speaker 2: that at face value, like, oh yeah, Russian by they're influencing.

1301
01:04:01,520 --> 01:04:02,240
Speaker 1: All of us.

1302
01:04:02,840 --> 01:04:06,680
Speaker 2: What about like a personality is like a Tucker Carlson

1303
01:04:07,400 --> 01:04:09,760
Speaker 2: or someone who's like a or Alex Jones, like someone

1304
01:04:09,760 --> 01:04:13,120
Speaker 2: who's sort of a loud figure with a cult following,

1305
01:04:13,160 --> 01:04:17,720
Speaker 2: who's promoting that kind of thing? Do you have Do

1306
01:04:17,760 --> 01:04:18,920
Speaker 2: you have anything to say on that?

1307
01:04:19,800 --> 01:04:23,960
Speaker 3: I think we are profoundly underestimating how important those types

1308
01:04:23,960 --> 01:04:26,960
Speaker 3: of legacy or older media systems are. You know, like

1309
01:04:27,200 --> 01:04:29,880
Speaker 3: you can do you know, all sorts of stuff to

1310
01:04:29,920 --> 01:04:32,480
Speaker 3: try to root out, you know, Russian accounts that might

1311
01:04:32,520 --> 01:04:35,240
Speaker 3: be trying to spread misinformation. But if the president of

1312
01:04:35,240 --> 01:04:38,120
Speaker 3: the United States or if you know, the leader of

1313
01:04:38,160 --> 01:04:41,920
Speaker 3: a major nightly news program is distributing this stuff, like,

1314
01:04:42,120 --> 01:04:44,760
Speaker 3: you know that that's going to go far no matter what. Right.

1315
01:04:44,840 --> 01:04:48,480
Speaker 3: So a lot of the story of polarization again starts

1316
01:04:48,560 --> 01:04:50,760
Speaker 3: before social media, and a lot of it is sort

1317
01:04:50,800 --> 01:04:54,840
Speaker 3: of blamed upon sort of cable news networks like Fox

1318
01:04:54,880 --> 01:04:57,520
Speaker 3: News and sort of without like getting too deep in

1319
01:04:57,600 --> 01:05:00,880
Speaker 3: the history, sort of an interesting story there, Like if

1320
01:05:00,920 --> 01:05:04,560
Speaker 3: we went back to like nineteen seventy five, there would

1321
01:05:04,600 --> 01:05:09,600
Speaker 3: be like three main news networks. It'd be like ABC, NBCCBS,

1322
01:05:09,680 --> 01:05:12,600
Speaker 3: And if one day ABC said something that was like

1323
01:05:12,600 --> 01:05:15,040
Speaker 3: a little too liberal, they might lose some of their

1324
01:05:15,040 --> 01:05:18,440
Speaker 3: conservative audience to NBC or CBS, Right, And so you

1325
01:05:18,480 --> 01:05:21,360
Speaker 3: have the sort of natural incentive for everybody to be centrists.

1326
01:05:22,120 --> 01:05:25,040
Speaker 3: Then in like the nineteen eighties, you know, in stations

1327
01:05:25,040 --> 01:05:28,040
Speaker 3: like Fox News, CNN come along and all of a

1328
01:05:28,080 --> 01:05:30,400
Speaker 3: sudden they have the small market share, right, They're not

1329
01:05:30,440 --> 01:05:34,360
Speaker 3: going to knock CBS, NBC, ABC off their pedestals, right,

1330
01:05:34,440 --> 01:05:37,040
Speaker 3: But what they can do is sort of chip away

1331
01:05:37,240 --> 01:05:40,200
Speaker 3: at parts of their audience. And so what cable news

1332
01:05:40,200 --> 01:05:42,919
Speaker 3: networks I think quickly learned is if they take those

1333
01:05:42,960 --> 01:05:46,560
Speaker 3: extreme positions, like everybody who's sort of annoyed by the

1334
01:05:46,720 --> 01:05:49,000
Speaker 3: centrist positions on the left and the right is going

1335
01:05:49,040 --> 01:05:52,400
Speaker 3: to come running towards them. And so throughout the eighties

1336
01:05:52,440 --> 01:05:55,760
Speaker 3: we saw sort of like the centrifuge of media, right,

1337
01:05:55,800 --> 01:05:58,840
Speaker 3: like people really pushed the extremes, and now what we're

1338
01:05:58,920 --> 01:06:01,120
Speaker 3: left with today is sort of that to become normalized.

1339
01:06:01,160 --> 01:06:04,280
Speaker 3: And so you know, certainly if we take the long

1340
01:06:04,360 --> 01:06:07,440
Speaker 3: view again, like long before social media, like the media

1341
01:06:07,560 --> 01:06:10,400
Speaker 3: has been you know, a key driver of not just

1342
01:06:10,480 --> 01:06:14,600
Speaker 3: polarization but also false polarization. So the media talks so

1343
01:06:14,680 --> 01:06:18,240
Speaker 3: much about polarization and how bad everything is, but in reality,

1344
01:06:18,360 --> 01:06:21,960
Speaker 3: the data looked much much better than you'd think after

1345
01:06:22,040 --> 01:06:24,919
Speaker 3: reading you know, ten articles on polarization in the US.

1346
01:06:24,920 --> 01:06:28,840
Speaker 3: So when people are shown in experiments, like social scientists

1347
01:06:28,840 --> 01:06:30,800
Speaker 3: like may have done experiments where you show people like

1348
01:06:30,920 --> 01:06:35,040
Speaker 3: news about polarization and then you need to show and

1349
01:06:35,040 --> 01:06:36,400
Speaker 3: then you don't show it to other people, And what

1350
01:06:36,440 --> 01:06:39,800
Speaker 3: you find is the people who read about polarization, sure enough,

1351
01:06:40,120 --> 01:06:42,240
Speaker 3: they think there's much more polarization than there is. So

1352
01:06:42,280 --> 01:06:44,920
Speaker 3: the media matters at so many levels. And even though

1353
01:06:45,200 --> 01:06:47,640
Speaker 3: social media has democratized things like that, and for every

1354
01:06:47,680 --> 01:06:51,400
Speaker 3: Tucker Carlson, there's like some random teenager who has you know,

1355
01:06:51,520 --> 01:06:54,080
Speaker 3: two hundred thousand Instagram followers and has a lot of influence.

1356
01:06:54,320 --> 01:06:56,080
Speaker 3: Like the fact of the matter is like someone like

1357
01:06:56,120 --> 01:06:58,680
Speaker 3: Tucker Carlson still has a ton of influence.

1358
01:06:59,240 --> 01:07:01,080
Speaker 2: Right, And that's why I'm trying to get Noam choms

1359
01:07:01,120 --> 01:07:07,760
Speaker 2: Kean to talk about manufacturing consent. So basically, it seems

1360
01:07:07,840 --> 01:07:13,320
Speaker 2: like what we we come to social media with like

1361
01:07:13,400 --> 01:07:17,640
Speaker 2: some core things that we identify with already, and social

1362
01:07:17,720 --> 01:07:20,600
Speaker 2: media just sort of amplifies it and makes it a

1363
01:07:20,640 --> 01:07:24,080
Speaker 2: little bit louder and easier to find that community. So

1364
01:07:24,280 --> 01:07:27,840
Speaker 2: different from what I thought, Yeah, it's pretty mindful and.

1365
01:07:27,800 --> 01:07:29,680
Speaker 3: What everybody else thinks, right, Like if we look at like,

1366
01:07:29,840 --> 01:07:32,360
Speaker 3: what's like, you know, one of the themes we've been

1367
01:07:32,400 --> 01:07:34,640
Speaker 3: talking about is like what's the point of social media? Right?

1368
01:07:34,680 --> 01:07:36,880
Speaker 3: And if you look at like someone like Mark Zuckerberg, right,

1369
01:07:37,000 --> 01:07:39,880
Speaker 3: it's very clear that he has like a libertarian view

1370
01:07:39,920 --> 01:07:42,640
Speaker 3: of the universe, Right, like that, like everybody should have

1371
01:07:42,720 --> 01:07:46,120
Speaker 3: their say, you know, the people should figure out what's wrong,

1372
01:07:46,400 --> 01:07:50,000
Speaker 3: you know, like and like that could work if everybody

1373
01:07:50,120 --> 01:07:53,240
Speaker 3: was genuinely interested in having a productive argument right in

1374
01:07:53,280 --> 01:07:56,280
Speaker 3: our in our goal and using social media was seeking truth, right,

1375
01:07:56,280 --> 01:07:58,720
Speaker 3: which is very noble pursuit, you know, Like I wish

1376
01:07:58,760 --> 01:08:01,000
Speaker 3: that that's what we were all doing. But it's not right.

1377
01:08:01,080 --> 01:08:04,840
Speaker 3: It's getting status and so right, right and getting likes.

1378
01:08:04,880 --> 01:08:07,360
Speaker 3: So like if we if we, you know, we have

1379
01:08:07,440 --> 01:08:09,720
Speaker 3: the wrong model. You know, the model is all about like,

1380
01:08:09,800 --> 01:08:11,880
Speaker 3: oh well, yeah, you just need to put the people together.

1381
01:08:12,000 --> 01:08:14,400
Speaker 3: If they just get together, they'll realize things aren't you know,

1382
01:08:14,480 --> 01:08:17,400
Speaker 3: as bad, and like that's that's exactly the opposite of

1383
01:08:17,400 --> 01:08:19,960
Speaker 3: what's going on. Right When you're putting people together, you're

1384
01:08:20,000 --> 01:08:23,000
Speaker 3: sort of launching them deeper into these identity battles because

1385
01:08:23,040 --> 01:08:25,080
Speaker 3: all they care about is taking down the other side

1386
01:08:25,120 --> 01:08:27,200
Speaker 3: to make them feel better about themselves and to get

1387
01:08:27,240 --> 01:08:31,320
Speaker 3: more you know, likes for their own content. So you know, yeah,

1388
01:08:31,360 --> 01:08:33,920
Speaker 3: it's a you know, it really does cut down to

1389
01:08:34,200 --> 01:08:36,920
Speaker 3: the motivation, you know, like nobody really is you know,

1390
01:08:37,200 --> 01:08:39,639
Speaker 3: and and you know a lot of people might say, okay,

1391
01:08:39,680 --> 01:08:42,240
Speaker 3: well yeah, that's all well and good, But I don't

1392
01:08:42,280 --> 01:08:44,479
Speaker 3: care that much about status on social media, right, Like

1393
01:08:44,560 --> 01:08:47,000
Speaker 3: maybe the people listening to this podcast are a little

1394
01:08:47,280 --> 01:08:49,479
Speaker 3: less narcissistic than the three of us, and don't you know,

1395
01:08:49,600 --> 01:08:52,840
Speaker 3: don't care whether they have you know, Twitter followings or whatever, right,

1396
01:08:53,200 --> 01:08:55,800
Speaker 3: And that's fine, Like, that's that's fine, but it doesn't

1397
01:08:55,840 --> 01:08:58,519
Speaker 3: mean that status still isn't driving your behavior, right, Like

1398
01:08:58,640 --> 01:09:01,040
Speaker 3: the reason you avoid so media is because you don't

1399
01:09:01,040 --> 01:09:04,040
Speaker 3: want whatever valued status you have offline, like you know,

1400
01:09:04,080 --> 01:09:07,679
Speaker 3: your relationship with your grandmother or your uncle or whatever,

1401
01:09:08,120 --> 01:09:10,920
Speaker 3: to be corrupted by your online behavior. And so like,

1402
01:09:10,960 --> 01:09:13,479
Speaker 3: no matter what we are, sort of status a tune

1403
01:09:13,520 --> 01:09:17,360
Speaker 3: creatures and social media is is just you know, profoundly

1404
01:09:17,400 --> 01:09:20,760
Speaker 3: distorting the sort of typical social signals we would all

1405
01:09:20,800 --> 01:09:23,679
Speaker 3: give to each other to sort of work our shit

1406
01:09:23,720 --> 01:09:25,880
Speaker 3: out a in a more natural way.

1407
01:09:25,960 --> 01:09:28,639
Speaker 1: Yeah, I keep seeing this thing that is like people

1408
01:09:28,680 --> 01:09:32,080
Speaker 1: posting like cut out people who don't think the same

1409
01:09:32,120 --> 01:09:34,479
Speaker 1: as you. It's not what an I'm.

1410
01:09:34,240 --> 01:09:36,479
Speaker 2: Like, oh my god, what No.

1411
01:09:36,720 --> 01:09:39,000
Speaker 1: We have to keep talking to each other. But I

1412
01:09:39,040 --> 01:09:42,120
Speaker 1: feel like in COVID that became really like popular too

1413
01:09:42,240 --> 01:09:45,519
Speaker 1: because it was just so you know, divisive like you.

1414
01:09:45,520 --> 01:09:49,639
Speaker 2: Will literally kill me with your beliefs. Yeah, we will

1415
01:09:49,680 --> 01:09:51,200
Speaker 2: let you go in a minute. But I just wanted

1416
01:09:51,240 --> 01:09:54,000
Speaker 2: you to give us a few examples that I saw

1417
01:09:54,000 --> 01:09:56,599
Speaker 2: in your book that I thought were super interesting of

1418
01:09:56,920 --> 01:10:00,519
Speaker 2: in group favoritism, and just just one of the things

1419
01:10:00,520 --> 01:10:02,519
Speaker 2: we talk about a lot and that I'm super interested

1420
01:10:02,520 --> 01:10:06,200
Speaker 2: in is well all the different kinds of cognitive bias,

1421
01:10:06,240 --> 01:10:11,040
Speaker 2: but also just how much we think we're in control

1422
01:10:11,280 --> 01:10:14,559
Speaker 2: of what we think and believe and how much it's

1423
01:10:14,600 --> 01:10:17,519
Speaker 2: actually determined by all these other things. And in this case,

1424
01:10:17,560 --> 01:10:19,479
Speaker 2: it would be like the group that we identify with.

1425
01:10:19,520 --> 01:10:21,679
Speaker 2: So can do you have Can you just offhand throw

1426
01:10:21,760 --> 01:10:22,599
Speaker 2: some examples of that?

1427
01:10:23,800 --> 01:10:26,960
Speaker 3: Yeah? Sure, I mean you know, there's like decades of

1428
01:10:27,080 --> 01:10:29,720
Speaker 3: research on this kind of stuff, you know, in group bias,

1429
01:10:29,920 --> 01:10:33,360
Speaker 3: you know, social identity theories sometimes it's called but basically

1430
01:10:33,400 --> 01:10:36,200
Speaker 3: what it means is like, you know, our load stars

1431
01:10:36,320 --> 01:10:39,040
Speaker 3: are our identities, whether we know it or not, to

1432
01:10:39,080 --> 01:10:42,000
Speaker 3: the point where we will do things to promote our

1433
01:10:42,000 --> 01:10:45,200
Speaker 3: own side and denigrate the other side in all sorts

1434
01:10:45,240 --> 01:10:48,559
Speaker 3: of settings, not just like obvious you know, like obviously

1435
01:10:48,600 --> 01:10:51,519
Speaker 3: polorized settings like Twitter, but even if we like make

1436
01:10:51,640 --> 01:10:54,599
Speaker 3: up fake pieces of art and then tell people that

1437
01:10:54,640 --> 01:10:56,880
Speaker 3: they are this type of person who likes this type

1438
01:10:56,920 --> 01:10:58,479
Speaker 3: of art, and you tell someone else they're a different

1439
01:10:58,479 --> 01:11:00,720
Speaker 3: type of person who likes this type of art. They

1440
01:11:00,720 --> 01:11:04,000
Speaker 3: will then develop attitudes just based on these totally arbitrary

1441
01:11:04,160 --> 01:11:07,519
Speaker 3: identities that we might create for people in a lab setting.

1442
01:11:08,240 --> 01:11:10,920
Speaker 3: And so yeah, it's it's absolutely the case that you know,

1443
01:11:11,520 --> 01:11:13,880
Speaker 3: we're guided by our identities. I mean, you know, you know,

1444
01:11:13,960 --> 01:11:16,880
Speaker 3: some people you know, would would take that argument all

1445
01:11:16,880 --> 01:11:20,720
Speaker 3: the way back to you know again Neanderthals and all

1446
01:11:20,720 --> 01:11:22,080
Speaker 3: that kind of stuff. I don't even think we need

1447
01:11:22,120 --> 01:11:24,559
Speaker 3: to go that far back. I think, like, you know,

1448
01:11:25,000 --> 01:11:29,160
Speaker 3: just take a minute and think how many times subconsciously

1449
01:11:29,240 --> 01:11:32,800
Speaker 3: or unconsciously you classify people into like part of us

1450
01:11:32,880 --> 01:11:35,760
Speaker 3: or them in a day. And you know, again, so

1451
01:11:35,960 --> 01:11:39,880
Speaker 3: much of it's subconscious, right, Like you know, I can

1452
01:11:39,920 --> 01:11:44,280
Speaker 3: tell that you know, you guys are nice people and

1453
01:11:44,439 --> 01:11:48,360
Speaker 3: would get along with my friends based on our body

1454
01:11:48,439 --> 01:11:53,600
Speaker 3: language are shared, you know, you know, our like our vocabulary,

1455
01:11:53,640 --> 01:11:56,519
Speaker 3: like all sorts of subtle things. Right. But if you

1456
01:11:56,640 --> 01:11:59,559
Speaker 3: drop me into a place where you know people are

1457
01:11:59,600 --> 01:12:02,400
Speaker 3: very different, right, I'm going to very quickly become attuned

1458
01:12:02,400 --> 01:12:05,360
Speaker 3: to all the things that make us different. We focus on,

1459
01:12:05,479 --> 01:12:08,440
Speaker 3: like our brains are trained to focus on these contrasts.

1460
01:12:09,000 --> 01:12:12,439
Speaker 3: That's what we do. That's that's why you know, you

1461
01:12:12,439 --> 01:12:15,360
Speaker 3: know earlier I said, we're constantly sort of experimenting on

1462
01:12:15,400 --> 01:12:18,599
Speaker 3: our identities, right, we're just sort of constantly updating, like

1463
01:12:18,680 --> 01:12:22,280
Speaker 3: oh that worked, that joke landed, that didn't write. Most

1464
01:12:22,320 --> 01:12:25,400
Speaker 3: of my jokes don't land for me. But like, but

1465
01:12:25,439 --> 01:12:27,360
Speaker 3: you know what I mean, Like, that's that's sort of

1466
01:12:27,680 --> 01:12:30,240
Speaker 3: that's sort of our loadstar. That's like, our our identities

1467
01:12:30,280 --> 01:12:32,240
Speaker 3: are are are what guide us, not just on social

1468
01:12:32,280 --> 01:12:33,519
Speaker 3: media but pretty much everywhere.

1469
01:12:33,520 --> 01:12:38,400
Speaker 1: We need social lobotomies where we're just like that, I

1470
01:12:38,479 --> 01:12:40,920
Speaker 1: think that done.

1471
01:12:41,080 --> 01:12:44,839
Speaker 3: Well done, well done. Let's get Mark Zuckerberg.

1472
01:12:45,120 --> 01:12:48,200
Speaker 1: Yeah, you'd probably love it.

1473
01:12:48,200 --> 01:12:53,960
Speaker 2: It's just another reason to interrogate your initial instincts and

1474
01:12:54,160 --> 01:12:59,720
Speaker 2: perception about other people, because it's like it is adaptive

1475
01:12:59,720 --> 01:13:02,880
Speaker 2: that areans do that, that they just automatically come to these conclusions.

1476
01:13:03,240 --> 01:13:05,639
Speaker 2: But so much of the time it's wrong, and it's

1477
01:13:05,720 --> 01:13:09,000
Speaker 2: just based on familiarity, it's just based on identity, it's

1478
01:13:09,040 --> 01:13:10,880
Speaker 2: just based on all of these other things. And if

1479
01:13:10,920 --> 01:13:13,120
Speaker 2: we were presented with the same information or the same

1480
01:13:13,120 --> 01:13:14,920
Speaker 2: piece of art or whatever it is, and we were

1481
01:13:14,960 --> 01:13:18,439
Speaker 2: told it was from the the outgroup instead of the

1482
01:13:18,439 --> 01:13:22,280
Speaker 2: in group, we would feel very differently about it. And yeah,

1483
01:13:22,680 --> 01:13:25,400
Speaker 2: slow thinking, you know, that's that's what we're promoting here.

1484
01:13:25,560 --> 01:13:27,559
Speaker 3: And that you know, and getting back to like what's

1485
01:13:27,600 --> 01:13:29,800
Speaker 3: messed up about social media is like it's the exact

1486
01:13:29,840 --> 01:13:32,439
Speaker 3: opposite of slow thinking, right, it's process things as quickly

1487
01:13:32,479 --> 01:13:35,000
Speaker 3: as possible, is as many heuristics as you can to like,

1488
01:13:35,240 --> 01:13:37,880
Speaker 3: you know, if I open up Twitter, like half the

1489
01:13:37,920 --> 01:13:40,920
Speaker 3: time I realized, like I had this realization deep into

1490
01:13:41,320 --> 01:13:44,200
Speaker 3: you know, writing this book, Like half the time I

1491
01:13:44,240 --> 01:13:46,000
Speaker 3: spent on Twitter is just sort of like what is

1492
01:13:46,000 --> 01:13:49,360
Speaker 3: everybody so upset about? That's like that's what I'm trying

1493
01:13:49,400 --> 01:13:52,280
Speaker 3: to figure out. Like the first ten minutes of oh

1494
01:13:52,439 --> 01:13:55,040
Speaker 3: so and so said this or whatever, right it And

1495
01:13:55,080 --> 01:13:56,920
Speaker 3: it's almost like you just get caught up. Okay, okay,

1496
01:13:56,960 --> 01:13:59,679
Speaker 3: we're mad now, like but you know my side's mad,

1497
01:14:01,360 --> 01:14:04,360
Speaker 3: and you know, it's sort of like we entered conversations

1498
01:14:04,360 --> 01:14:06,719
Speaker 3: that have been unfolding for hours or even days sometimes

1499
01:14:06,720 --> 01:14:10,040
Speaker 3: before us, rather than like confronting the information objectively, like well,

1500
01:14:10,080 --> 01:14:11,519
Speaker 3: what did this person actually say?

1501
01:14:11,560 --> 01:14:11,640
Speaker 2: What?

1502
01:14:11,720 --> 01:14:13,639
Speaker 3: Did they actually do right now, sometimes we don't even

1503
01:14:13,640 --> 01:14:16,920
Speaker 3: get there until we've already ingested like twenty minutes of hate.

1504
01:14:17,040 --> 01:14:19,200
Speaker 3: So of course by the time we get that, we

1505
01:14:19,280 --> 01:14:22,120
Speaker 3: bring all those biases with us. So so yeah, absolutely,

1506
01:14:22,160 --> 01:14:24,320
Speaker 3: And the sort of interesting question is like how do

1507
01:14:24,400 --> 01:14:29,920
Speaker 3: we train ourselves to become aware of those biases? And

1508
01:14:30,200 --> 01:14:33,200
Speaker 3: I here again like, okay, call me an optimist, but like,

1509
01:14:33,280 --> 01:14:35,960
Speaker 3: I think technology has a role. So, like, one of

1510
01:14:35,960 --> 01:14:38,240
Speaker 3: the things I wanted to do with this book was

1511
01:14:38,280 --> 01:14:41,759
Speaker 3: to offer people some sometimes it's called middleware like tools

1512
01:14:41,760 --> 01:14:45,519
Speaker 3: that you can use in tandem with social media to

1513
01:14:45,560 --> 01:14:48,320
Speaker 3: try to change your experience. So, like earlier I was saying,

1514
01:14:48,360 --> 01:14:52,519
Speaker 3: wouldn't it be cool if social media, you know, newsfeed

1515
01:14:52,560 --> 01:14:56,479
Speaker 3: algorithms rewarded content that lots of different people like instead

1516
01:14:56,479 --> 01:14:59,719
Speaker 3: of just what my side likes. Right, So we've created

1517
01:14:59,720 --> 01:15:02,960
Speaker 3: bos that you can follow on Polarization lab dot com

1518
01:15:02,960 --> 01:15:05,439
Speaker 3: that's the name of the lab I lead at Duke,

1519
01:15:05,840 --> 01:15:09,000
Speaker 3: where you know, you can basically insert that content into

1520
01:15:09,040 --> 01:15:12,040
Speaker 3: your feed or you know, if you are sort of

1521
01:15:12,080 --> 01:15:15,240
Speaker 3: falling victim to this prism like distortion of our identities, right,

1522
01:15:15,240 --> 01:15:18,639
Speaker 3: you can actually see what your tweets say about your

1523
01:15:18,640 --> 01:15:21,080
Speaker 3: politics by putting in your your Twitter handle and you'll

1524
01:15:21,120 --> 01:15:23,320
Speaker 3: see like, oh, you know, I think of myself as

1525
01:15:23,479 --> 01:15:25,840
Speaker 3: as a pretty moderate person, but actually I come off

1526
01:15:26,040 --> 01:15:28,360
Speaker 3: as sort of a jerk, you know, or whatever. It is, right,

1527
01:15:28,760 --> 01:15:32,639
Speaker 3: And the goal here isn't like everybody uses this every

1528
01:15:32,680 --> 01:15:35,759
Speaker 3: time they tweet something. It's like little tiny nudges along

1529
01:15:35,800 --> 01:15:38,680
Speaker 3: the way that sort of remind us periodically, and you

1530
01:15:38,720 --> 01:15:40,920
Speaker 3: can imagine in the long term, like some of these

1531
01:15:40,960 --> 01:15:44,240
Speaker 3: could be built into the platforms themselves, Like, hey, you've

1532
01:15:44,320 --> 01:15:47,160
Speaker 3: only read the opinion of your friends on this issue.

1533
01:15:47,240 --> 01:15:49,360
Speaker 3: Maybe you want to check out this this piece that

1534
01:15:49,479 --> 01:15:51,360
Speaker 3: you know none of your friends have read yet. Like

1535
01:15:51,760 --> 01:15:54,080
Speaker 3: the technology is there to do those types of things.

1536
01:15:54,960 --> 01:15:56,840
Speaker 3: What isn't there yet? And where I think the rubber

1537
01:15:56,920 --> 01:15:58,040
Speaker 3: is going to hit the road is how do you

1538
01:15:58,080 --> 01:16:00,720
Speaker 3: make those things markets? And how do you make them monetizable?

1539
01:16:00,720 --> 01:16:03,599
Speaker 3: Because I think you're actually, you know, exactly right earlier

1540
01:16:03,640 --> 01:16:06,000
Speaker 3: when you said, like, yeah, but why would someone do that? Right?

1541
01:16:06,520 --> 01:16:10,200
Speaker 3: We have to be trained to understand the rewards of

1542
01:16:10,360 --> 01:16:13,080
Speaker 3: seeking out different perspectives, and that's not something most of

1543
01:16:13,160 --> 01:16:15,599
Speaker 3: us do, right, Like that's something that's sort of trained

1544
01:16:15,640 --> 01:16:16,160
Speaker 3: out of us.

1545
01:16:16,320 --> 01:16:19,880
Speaker 2: Yeah, absolutely, Thank you so much for talking to us.

1546
01:16:19,880 --> 01:16:22,000
Speaker 2: This has been super, super interesting.

1547
01:16:22,920 --> 01:16:23,799
Speaker 3: Oh it's my pleasure.

1548
01:16:24,120 --> 01:16:25,680
Speaker 2: Yeah, do you want to I mean you did a

1549
01:16:25,680 --> 01:16:28,840
Speaker 2: shout out, But where do people find more information about

1550
01:16:28,880 --> 01:16:30,559
Speaker 2: the Polarization Lab and you in general?

1551
01:16:30,960 --> 01:16:31,200
Speaker 1: Sure?

1552
01:16:31,320 --> 01:16:34,320
Speaker 3: Yeah, you can go to Polarization Lab dot com. You

1553
01:16:34,360 --> 01:16:36,840
Speaker 3: can go to Chris Bail dot net bail. If you

1554
01:16:36,840 --> 01:16:39,000
Speaker 3: want to read about a bunch of our other research

1555
01:16:39,960 --> 01:16:43,320
Speaker 3: or some of the new visions we have for social media,

1556
01:16:43,439 --> 01:16:45,400
Speaker 3: you can check out a recent episode or a recent

1557
01:16:45,400 --> 01:16:49,320
Speaker 3: issue of The New Yorker which profiled some additional research

1558
01:16:49,439 --> 01:16:53,720
Speaker 3: I did, including a Google doc that was designed to

1559
01:16:53,920 --> 01:16:57,160
Speaker 3: try to summarize research on social media for a public

1560
01:16:57,160 --> 01:17:00,320
Speaker 3: audience that can't spend all day reading academic article cools.

1561
01:17:01,720 --> 01:17:04,000
Speaker 3: And you know, if you want to learn more about

1562
01:17:04,400 --> 01:17:07,679
Speaker 3: data science and computational social science, I want I run

1563
01:17:07,760 --> 01:17:10,360
Speaker 3: a free training program where you can train yourself these

1564
01:17:10,400 --> 01:17:14,600
Speaker 3: texting with in these techniques online cool summer institutes, and

1565
01:17:14,720 --> 01:17:16,080
Speaker 3: computational social science.

1566
01:17:16,160 --> 01:17:18,800
Speaker 2: Seriously, Well do yeah?

1567
01:17:19,439 --> 01:17:21,080
Speaker 3: I mean I'm a geek, but I think it's cool.

1568
01:17:21,120 --> 01:17:23,880
Speaker 3: So we'll see if you're if you're listeners like it too.

1569
01:17:23,880 --> 01:17:27,200
Speaker 3: But that's S I C S S dot io. It's

1570
01:17:27,240 --> 01:17:30,000
Speaker 3: completely free and we also run training events all around

1571
01:17:30,000 --> 01:17:30,320
Speaker 3: the world.

1572
01:17:30,439 --> 01:17:34,400
Speaker 2: I'm amazing. Well, thanks so much for joining us, and

1573
01:17:34,640 --> 01:17:37,720
Speaker 2: have yourself a fantastic What time is it where you

1574
01:17:37,760 --> 01:17:38,559
Speaker 2: are evening?

1575
01:17:38,960 --> 01:17:39,080
Speaker 1: Uh?

1576
01:17:39,479 --> 01:17:39,960
Speaker 3: A dinner?

1577
01:17:40,520 --> 01:17:40,680
Speaker 1: Yeah?

1578
01:17:40,680 --> 01:17:42,639
Speaker 3: I thought you're going to say social lobotomy, so.

1579
01:17:44,920 --> 01:17:46,080
Speaker 1: Feel free to quote me on that.

1580
01:17:46,240 --> 01:17:48,320
Speaker 3: You can use that. Well, I'm going to steal that.

1581
01:17:49,000 --> 01:17:49,760
Speaker 1: Thank you so much.

1582
01:17:49,760 --> 01:17:52,479
Speaker 3: Thanks so much for having me. Okay, take care bye, all.

1583
01:17:52,439 --> 01:17:56,720
Speaker 2: Right, Megan, Yes, dearest friend Megan, I don't exactly have

1584
01:17:56,760 --> 01:17:58,559
Speaker 2: a question for you, because I know that you are

1585
01:17:58,600 --> 01:18:00,479
Speaker 2: not an internatural at least I think you're not.

1586
01:18:00,640 --> 01:18:00,960
Speaker 1: I'm not.

1587
01:18:01,120 --> 01:18:02,160
Speaker 2: Would you tell me if you were?

1588
01:18:02,360 --> 01:18:04,920
Speaker 1: Yeah, my trolling is more positive where I'm just like

1589
01:18:04,920 --> 01:18:07,080
Speaker 1: it's perfect. I love it, even if it's crazy.

1590
01:18:07,120 --> 01:18:13,599
Speaker 2: But I have noticed that about you. All right, So

1591
01:18:13,720 --> 01:18:15,679
Speaker 2: I'm just going to read a quote from this book

1592
01:18:15,680 --> 01:18:17,200
Speaker 2: Atomic Habits. Have you read it? No?

1593
01:18:17,320 --> 01:18:19,160
Speaker 1: I haven't, but I saw it on your bedside table.

1594
01:18:19,000 --> 01:18:21,640
Speaker 2: The other day, which is funny because I have not

1595
01:18:21,880 --> 01:18:24,880
Speaker 2: finished reading it and Jack just finished reading it. So

1596
01:18:25,000 --> 01:18:27,320
Speaker 2: Atomic Habits, which again I got like a fourth of

1597
01:18:27,360 --> 01:18:29,679
Speaker 2: the way through. Jack just finished reading. I was reading

1598
01:18:29,720 --> 01:18:31,479
Speaker 2: over his shoulders, so I'm not going to pretend like

1599
01:18:31,520 --> 01:18:33,880
Speaker 2: I'm actually actively reading this book, but I really liked

1600
01:18:33,880 --> 01:18:35,000
Speaker 2: this quote, and I wow.

1601
01:18:34,880 --> 01:18:36,960
Speaker 1: This is literally a picture over someone's shoulder.

1602
01:18:37,040 --> 01:18:41,080
Speaker 2: I thought it was. It was irrelevant, so he quotes

1603
01:18:41,120 --> 01:18:45,439
Speaker 2: this man, Paul Graham. The quote is keep your identity small.

1604
01:18:45,479 --> 01:18:48,240
Speaker 2: And here is what the author of Atomic Habits says.

1605
01:18:48,280 --> 01:18:50,559
Speaker 2: The more you let a single belief define you, the

1606
01:18:50,640 --> 01:18:53,360
Speaker 2: less capable you are of adapting when life challenges you.

1607
01:18:53,520 --> 01:18:55,559
Speaker 2: If you tie everything up and being the point guard

1608
01:18:55,600 --> 01:18:57,519
Speaker 2: or the partner at the firm or whatever else, then

1609
01:18:57,520 --> 01:19:00,000
Speaker 2: the loss of that facet of your life will wreck you.

1610
01:18:59,880 --> 01:19:02,160
Speaker 2: You're a vegan and then develop a health condition that

1611
01:19:02,200 --> 01:19:04,200
Speaker 2: forces you to change your diet, You'll have an identity

1612
01:19:04,240 --> 01:19:06,400
Speaker 2: crisis on your hands. When you cling too tightly to

1613
01:19:06,439 --> 01:19:09,479
Speaker 2: one identity, you become brittle. Lose that one thing, and

1614
01:19:09,560 --> 01:19:11,840
Speaker 2: you lose yourself. For most of my young life, being

1615
01:19:11,840 --> 01:19:14,200
Speaker 2: an athlete was a major part of my identity. After

1616
01:19:14,200 --> 01:19:16,360
Speaker 2: my baseball career, and did I struggle to find myself?

1617
01:19:16,479 --> 01:19:18,559
Speaker 2: When you spend your whole life defining yourself in one

1618
01:19:18,600 --> 01:19:22,360
Speaker 2: way and that disappears, who are you now? I love

1619
01:19:22,560 --> 01:19:26,000
Speaker 2: that and I just think it's relevant. Because obviously identity

1620
01:19:26,040 --> 01:19:29,000
Speaker 2: is something we talk about all the time, but particularly

1621
01:19:29,040 --> 01:19:32,919
Speaker 2: in this episode, it's like so many of these trolls

1622
01:19:32,960 --> 01:19:35,839
Speaker 2: and people who become sort of extreme online are finding

1623
01:19:35,880 --> 01:19:39,000
Speaker 2: their identity in this like one particular place, which is

1624
01:19:39,160 --> 01:19:43,479
Speaker 2: you know, conspiracy theories or you know, patrolling or whatever.

1625
01:19:43,520 --> 01:19:47,120
Speaker 2: It is, like what happens when say Donald Trump leaves

1626
01:19:47,120 --> 01:19:50,920
Speaker 2: that platform, what happens when your four chan is shut

1627
01:19:50,920 --> 01:19:53,519
Speaker 2: down or whatever? You know, Like, what is that really

1628
01:19:53,560 --> 01:19:55,720
Speaker 2: what you want to be building your identity on? And

1629
01:19:55,760 --> 01:19:57,479
Speaker 2: I think that just applies to all of us in general.

1630
01:19:57,560 --> 01:19:59,120
Speaker 2: It's like, do we It's the same thing we talk

1631
01:19:59,160 --> 01:20:01,639
Speaker 2: about all the time, do we want to have all

1632
01:20:01,680 --> 01:20:05,679
Speaker 2: of ourselves coming from one source, from one place, everything

1633
01:20:05,720 --> 01:20:09,040
Speaker 2: that we believe? We you know, we should be what's

1634
01:20:09,040 --> 01:20:10,400
Speaker 2: the word what do we normally say?

1635
01:20:10,479 --> 01:20:12,080
Speaker 1: Multifaceted? Sure?

1636
01:20:12,280 --> 01:20:15,040
Speaker 2: No, we should be like building our identity on multiple

1637
01:20:15,040 --> 01:20:15,439
Speaker 2: things and.

1638
01:20:16,200 --> 01:20:20,400
Speaker 1: One leader, Like multiple people influence you, multiple different people

1639
01:20:21,360 --> 01:20:24,040
Speaker 1: you try to store, you know, just building your life

1640
01:20:24,080 --> 01:20:26,280
Speaker 1: to involve more than one thing in one person.

1641
01:20:26,720 --> 01:20:29,240
Speaker 2: Yeah. Yeah. And he also talks about in the it

1642
01:20:29,280 --> 01:20:32,200
Speaker 2: goes on to talk about like, Okay, maybe you shouldn't

1643
01:20:32,200 --> 01:20:35,439
Speaker 2: have your identity be like, I am a lawyer who's

1644
01:20:35,439 --> 01:20:37,879
Speaker 2: good at lawyering, but maybe you can sort of expand

1645
01:20:37,880 --> 01:20:39,920
Speaker 2: that and broaden that and it can be like I

1646
01:20:39,960 --> 01:20:44,240
Speaker 2: am someone who's extremely organized and I love, you know,

1647
01:20:44,560 --> 01:20:47,000
Speaker 2: getting to the bottom of things, and that is like

1648
01:20:47,080 --> 01:20:49,320
Speaker 2: broadening it. Yeah, yeah, yeah, exactly.

1649
01:20:49,479 --> 01:20:49,839
Speaker 3: Yeah.

1650
01:20:50,080 --> 01:20:53,160
Speaker 1: I've been really impressed with because we live in Los Angeles.

1651
01:20:54,000 --> 01:20:56,880
Speaker 1: I'm a woman who is friends with a lot of

1652
01:20:56,920 --> 01:21:00,240
Speaker 1: other women, and like I just would always hear like, oh,

1653
01:21:00,320 --> 01:21:02,360
Speaker 1: growing all there, it's so hard you lose your beauty

1654
01:21:02,479 --> 01:21:05,360
Speaker 1: or whatever. But even in my friends who are like

1655
01:21:05,360 --> 01:21:08,280
Speaker 1: like much older than me, they're all super like nobody

1656
01:21:08,320 --> 01:21:10,679
Speaker 1: formed their identity around it, and everybody seems really good.

1657
01:21:11,000 --> 01:21:14,439
Speaker 2: I don't know really. Yeah, I mean that's great for

1658
01:21:14,479 --> 01:21:16,160
Speaker 2: me to hear right now, because I feel like I've

1659
01:21:16,160 --> 01:21:19,720
Speaker 2: been having a little bit of a crisis. Yeah, just

1660
01:21:19,760 --> 01:21:21,960
Speaker 2: like you know, you go through I remember I started

1661
01:21:22,000 --> 01:21:24,479
Speaker 2: getting cat cold most women did when I was like

1662
01:21:24,479 --> 01:21:27,439
Speaker 2: thirteen years old. Yeah, so it's weird to like hit

1663
01:21:27,479 --> 01:21:29,639
Speaker 2: a point in your life when you're like, oh, people

1664
01:21:29,680 --> 01:21:32,240
Speaker 2: don't look at me exactly the same way anymore interesting.

1665
01:21:32,920 --> 01:21:33,680
Speaker 1: I get none of that.

1666
01:21:34,000 --> 01:21:36,400
Speaker 2: Like it's like nice because you like don't really want

1667
01:21:36,439 --> 01:21:38,639
Speaker 2: to be cat called. But then on another level, you're like, oh,

1668
01:21:38,720 --> 01:21:42,000
Speaker 2: does this mean I'm no longer as like valid in

1669
01:21:42,040 --> 01:21:44,880
Speaker 2: the world because people don't immediately see me as like

1670
01:21:45,000 --> 01:21:49,240
Speaker 2: the young girl. Yeah, it's the youth. I've been having

1671
01:21:49,320 --> 01:21:52,240
Speaker 2: sort of an interesting relationship with the idea of youth leaving.

1672
01:21:52,280 --> 01:21:54,120
Speaker 2: But I want it. I don't want to be stuck

1673
01:21:54,120 --> 01:21:56,240
Speaker 2: on that at all. Like I think that's dumb. Yeah,

1674
01:21:56,320 --> 01:21:58,720
Speaker 2: I think youth is not. I mean, it's valuable in

1675
01:21:58,760 --> 01:22:00,920
Speaker 2: some ways, but it is certainly not like a defining

1676
01:22:01,000 --> 01:22:01,960
Speaker 2: characteristic career.

1677
01:22:02,280 --> 01:22:02,920
Speaker 1: Right, it's a lot.

1678
01:22:02,960 --> 01:22:07,200
Speaker 2: It's fun anyway, Just a little tanded there and that's it.

1679
01:22:07,400 --> 01:22:09,679
Speaker 1: Yeah, that's it. I love you guys, thanks for spending

1680
01:22:09,680 --> 01:22:11,439
Speaker 1: another week with us. We can't wait to see you

1681
01:22:11,479 --> 01:22:15,280
Speaker 1: again next week. But for now, remember to follow your

1682
01:22:15,280 --> 01:22:17,760
Speaker 1: gut watch up for a flat.

1683
01:22:17,200 --> 01:22:25,759
Speaker 2: And never ever nice. Trust Me is produced by Kirsten Woodward,

1684
01:22:25,880 --> 01:22:27,560
Speaker 2: Gabby Rapp and Steve Delemator.

1685
01:22:27,640 --> 01:22:29,599
Speaker 1: The special thanks to Stacy Para.

1686
01:22:29,520 --> 01:22:31,960
Speaker 2: And our theme song was composed by Holly amber Church.

1687
01:22:32,160 --> 01:22:35,040
Speaker 1: You can find us on Instagram at trust Me Podcast,

1688
01:22:35,200 --> 01:22:38,559
Speaker 1: Twitter at trust Me Cult Pod, or on TikTok at

1689
01:22:38,640 --> 01:22:40,320
Speaker 1: trust Me Cult Podcast.

1690
01:22:40,479 --> 01:22:43,479
Speaker 2: I'm Ula Lola on Instagram and Ola Lola on Twitter.

1691
01:22:43,560 --> 01:22:47,120
Speaker 1: And I am Megan Elizabeth eleven on Instagram and Babraham

1692
01:22:47,280 --> 01:22:48,320
Speaker 1: Hicks on Twitter.

1693
01:22:48,520 --> 01:22:50,800
Speaker 2: Remember to rate and review and spread the word.