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Speaker 1: There Are No Girls on the Internet, as a production

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Speaker 1: of iHeartRadio and Unbossed Creative. I'm Bridget Todd and this

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Speaker 1: is There Are No Girls on the Internet. Welcome to

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Speaker 1: another episode of There No Girls on the Internet, where

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Speaker 1: weeks before the intersection of social media, technology and identity.

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Speaker 1: This is another iteration of our weekly news roundup where

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Speaker 1: we talked through the stories that you might have seen

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Speaker 1: on the Internet so you don't have to. I am

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Speaker 1: so thrilled, so welcome back to the show. Friend of

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Speaker 1: the show, I think maybe the are our longest running guests.

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Speaker 1: Like you know how Steve Martin was the most he

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Speaker 1: hosted SNL the most. I think you're the Steve Martin

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Speaker 1: of There No Girls on the Internet. Oh my god,

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Speaker 1: what a claim to fame. It's an honor and a privilege.

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Speaker 1: We are so thrilled to be joined by Abby Richards,

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Speaker 1: prolific TikTok user, misinformation expert, media matters analyst. How do

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Speaker 1: you describe yourself these days? You're a woman who were

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Speaker 1: many hats.

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Speaker 2: Yeah, I think I described myself as a woman who

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Speaker 2: wears many hats. I'm still going with like misinformation researcher

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Speaker 2: and content creator as like blanket, you know, just covers

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Speaker 2: all the bases.

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Speaker 1: Yeah, there's a lot more to Abby. She has multitudes. Abby.

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Speaker 1: The last time that we saw each other, I think

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Speaker 1: was in Ireland a question mark. Yeah, it was in Dublin. Dublin,

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Speaker 1: that's right. We were there with Mozilla. And one of

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Speaker 1: the folks that you and I were lucky enough to

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Speaker 1: spend some time with and really get to know when

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Speaker 1: we were in Ireland was Chris Smalls. We've talked about

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Speaker 1: Chris Small's on the show before. He is one of

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Speaker 1: my personal heroes. You might know him best as one

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Speaker 1: of the main leaders in the fight to unionize Amazon workers.

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Speaker 1: He was the co founder and the former president of

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Speaker 1: the Amazon Labor Union, which was the very first ever

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Speaker 1: unionized Amazon worker coalition recognized by the National Labor Relations Board.

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Speaker 1: When we first got on, we were talking about the

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Speaker 1: fact that Chris was part of this Freedom Wotilla coalition,

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Speaker 1: which is a great last roots international collective that has

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Speaker 1: really been trying to get aid to folks in Gaza.

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Speaker 1: They were intercepted by the IDF, they boarded their their

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Speaker 1: vessel and you know, I'm sure that nobody was having

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Speaker 1: a great time once that happened, But all the reporting

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Speaker 1: I saw was that Chris was being uniquely targeted, and

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Speaker 1: I have to imagine that has something to do with

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Speaker 1: him being I think the only black man as part

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Speaker 1: of that coalition. Yeah, he was the only black activist

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Speaker 1: on board.

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Speaker 2: And he was reportedly like kicked in the head and

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Speaker 2: like had like they were like beating at his like

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Speaker 2: knees and legs. It was like seven uniformed, big people

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Speaker 2: in uniforms that were assaulting him. And reportedly then when

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Speaker 2: his lawyers went to go like meet with him, they

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Speaker 2: had like six like special police guards on him, and

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Speaker 2: then his conditions like when he was being held were terrible,

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Speaker 2: I think as without their activists. But it did seem

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Speaker 2: like he was specific targeted and it was really really

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Speaker 2: concerning for us who are like his friends and want

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Speaker 2: to make sure.

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Speaker 1: That he's safe. Yeah, and it sounds like he might

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Speaker 1: have actually been released quite recently, Do I have that right?

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Speaker 2: Yeah, So he's in as far as I'm aware at

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Speaker 2: the time of recording, I think he's like in Jordan,

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Speaker 2: like boarding a plane or maybe even like on the

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Speaker 2: plane right now and is expected to land tomorrow morning,

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Speaker 2: which like thank god, I'm really glad that he's he's

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Speaker 2: made it out. Sounds like conditions were terrible. They were

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Speaker 2: saying that they were like that infested with bed bugs

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Speaker 2: and overheated, really unclean, overpacked, and also that the activists

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Speaker 2: like we're on like day five of their like a

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Speaker 2: hunger strike. So it just the conditions were terrible and

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Speaker 2: it sounded absolutely miserable. But he posted a video i think,

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Speaker 2: at an airport like ready to leave, and seemed in

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Speaker 2: good spirits, which is nice.

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Speaker 1: And it's a good reminder of something that we get

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Speaker 1: into sometimes, which is that these issues, at least from

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Speaker 1: my perspective, are very much all connected. But back that

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Speaker 1: Chris Mall's was the you know, co founder of the

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Speaker 1: first Amazon labor union, I don't think is unrelated to

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Speaker 1: what's happening with Palestine. Like I think these are all

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Speaker 1: tech issues, they're all justice issues, they're all race issues.

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Speaker 1: The fact that a black activist would be uniquely targeted

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Speaker 1: by IDF when coming to provide aid and coming to

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Speaker 1: advocate for the cause, I think all of these issues

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Speaker 1: are connected in ways that sometimes can be difficult to see.

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Speaker 1: But I think that what happened with Chris really does

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Speaker 1: demonstrate that, and so I think a lot of folks

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Speaker 1: might think, like, oh, well, what does this issue have

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Speaker 1: to do with technology? Why would you be talking about

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Speaker 1: this in a tech podcast. I see it as very

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Speaker 1: as very linked the fact that someone would see what's

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Speaker 1: happening with Palestine and have the orientation of, like, well,

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Speaker 1: the same kind of forces of injustice that are at

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Speaker 1: play with big tech companies like Amazon are certainly at

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Speaker 1: play here. Yeah.

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Speaker 2: I mean, I think that is connected on so many

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Speaker 2: different angles. There's like the you know, technological colonialism of

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Speaker 2: it all, but there's also like the social media activism

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Speaker 2: of it of like how he even got there was

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Speaker 2: from a place of like knowing how to utilize social

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Speaker 2: media to get eyes on Gaza. Because it's not like

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Speaker 2: the Freedom flotilla was bringing like tremendous amounts of aid

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Speaker 2: in I think like they're they were very aware as

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Speaker 2: with the first round of it too, that like they

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Speaker 2: would likely get boarded and taken into custody and that

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Speaker 2: the aid wasn't going to get through. But it's like

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Speaker 2: a it's activism in that performance of like letting themselves

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Speaker 2: get arrested, right, A lot of activism revolves around that

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Speaker 2: and using social media to get that many eyes on it, right,

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Speaker 2: the types of activists that were on that boat.

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Speaker 1: That is such a technological issue.

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Speaker 2: It of course it is, And those things are so

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Speaker 2: connected and intersecting, and I think that they're really interesting

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Speaker 2: that we have to like account for that in you know,

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Speaker 2: twenty first century resistance efforts.

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Speaker 1: Absolutely well, Chris, if you are listening, our hearts are

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Speaker 1: with you, We're thinking about you. We love you. Yeah,

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Speaker 1: good vibe, so proud. Okay. So I want to talk

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Speaker 1: about something that I know you probably have lots of

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Speaker 1: thoughts about, and that is TikTok adding footnotes. Did you

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Speaker 1: see this this new kind of like program they're rolling

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Speaker 1: out that'll like let a select group of TikTokers add

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Speaker 1: context and background information to some videos on the app.

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Speaker 2: I saw, yeah, I saw. I saw the article like

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Speaker 2: saying that they were planning to unroll it. I would

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Speaker 2: like to be in that first group, please you?

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Speaker 1: Yeah, you would be let me, Mike you. I can't

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Speaker 1: think of somebody who uses the platform in a better

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Speaker 1: way to call out some of the misinformation that is there,

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Speaker 1: Like I there's nobody really doing it the way that

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Speaker 1: you're doing it. And what I love about your work

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Speaker 1: is how you're able to, like you use the platform.

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Speaker 1: You're a prolific user of the platform, but you also

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Speaker 1: critique the way that misinformation is able to spread on

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Speaker 1: that platform. And so it's not like you're someone who

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Speaker 1: is only raw rah. This platform that I've built up

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Speaker 1: can do no wrong. You just come at it from

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Speaker 1: such a such a place of transparency going on. Thank you.

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Speaker 1: I mean, like I am, I am a TikTok and enjoyer.

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Speaker 2: There are things I really enjoy about that aut but

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Speaker 2: also there are things that like infuriate me, and I

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Speaker 2: think that we can hold space for you know, two

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Speaker 2: things to exist at the same time, where like I

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Speaker 2: have found great, great joy there and also I have

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Speaker 2: been like lied to prolifically. So yeah, I think that

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Speaker 2: the community notes function that they're going to try, and

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Speaker 2: add I'm actually pretty in favor of it, as long

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Speaker 2: as it's not also replacing other fact checking, which it

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Speaker 2: sounds like it isn't.

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Speaker 1: So it's similar to the way that community notes functions

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Speaker 1: on X. But notably TikTok has says they are not

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Speaker 1: going to abandon in house back checking X and META.

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Speaker 1: When they rolled out community notes. That was all they

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Speaker 1: were going to be doing, and it really really did

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Speaker 1: seem like a way to all fload that burden from

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Speaker 1: paid staff at these companies and just put the burden

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Speaker 1: on you users, right, And so I think that you're

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Speaker 1: exactly right. The fact that TikTok is saying, hey, this

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Speaker 1: is not going to be replacing our in house backcheckers.

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Speaker 1: We're going to continue to have that too, I think

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Speaker 1: is really a key difference. And why to me, I'm

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Speaker 1: not like opposed to this. Yeah, no, I'm not opposed.

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Speaker 2: And I also think that it's kind of community oriented,

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Speaker 2: which I like. I like that there can be like

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Speaker 2: discussions around the accuracy of something like I'm very interested

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Speaker 2: in that. Again, it doesn't replace like journalists and fact checkers,

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Speaker 2: so as long as like it's just like an added

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Speaker 2: thing of like I think this is ai. I can

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Speaker 2: recognize what this bunny disappeared on a trampoline.

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Speaker 1: But bunny. So the bunny it got me. I sent

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Speaker 1: that to somebody, and then I had to send a

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Speaker 1: follow up when I saw the piece and four for

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Speaker 1: media and well that got a lot of people, That

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Speaker 1: got millions of people. So the piece, so the piece

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Speaker 1: and four for media breaking down this viral TikTok that

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Speaker 1: purported to be backyard ring cam security footage on a

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Speaker 1: bunch of bunnies adorably jumping out a trampoline. They were

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Speaker 1: so cute. It was so cute. And the reason why

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Speaker 1: it got me was because ring camera footage is always blurry,

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Speaker 1: so you're not I think that you're not trained to

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Speaker 1: be thinking is this real or is this not? You're

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Speaker 1: just expecting to see some low res video, and I

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Speaker 1: think that's easier to like slip AI into that. Yeah,

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Speaker 1: I think the blurry footage also with there's been a

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Speaker 1: few of those videos of like animals jumping on a

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Speaker 1: trampoline at night, and it's always at night because if

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Speaker 1: it were during the day, I think it would be

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Speaker 1: a lot more obvious.

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Speaker 2: But that like nighttime ring ring footage, it's just easier

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Speaker 2: for it to look a little shitty.

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Speaker 1: Yes, And when it comes to missing disinformation in the

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Speaker 1: way that it spreads in video form, it usually adheres

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Speaker 1: to some sort of worldview that you hold, And I

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Speaker 1: have the worldview that when night falls, animals are doing

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Speaker 1: all kinds of cute things and wouldn't it be great

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Speaker 1: if we could see them? And so I was like, Oh,

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Speaker 1: I I want to believe. I want to believe in

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Speaker 1: a world that bunnies are jumping on a trampoline at

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Speaker 1: night in a coordinated way when we're all asleep.

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Speaker 2: That's the ideology that I want to have. My core

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Speaker 2: belief is that when I go to sleep, bunnies get together.

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Speaker 1: It just jump fundrey of belief. Bunny nighttime mischief.

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Speaker 3: Yeah.

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Speaker 1: Yeah, So this is something interesting about community notes. So

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Speaker 1: I like the fact that TikTok is not replacing their

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Speaker 1: in house fact checking with community notes. But when platforms

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Speaker 1: like x are using community community notes only as fact checking,

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Speaker 1: the studies on whether or not that and that alone

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Speaker 1: is an effective way of handling incorrect information is a

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Speaker 1: little bit mixed. There's a really good analysis in Tech

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Speaker 1: Policy Press written by not A Jude, a PhD. Researcher

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Speaker 1: within the Digital Media Research Center at the Queensland University

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Speaker 1: of Technology, and doctor Adriana Matrimos Fernandez, Associate professor at

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Speaker 1: the University College a Dublin. They found that studies on

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Speaker 1: the effective of community notes are mixed. For example, there

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Speaker 1: is a debate about whether or not the tool reduces

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Speaker 1: or heightens engagement with misleading posts. Notes are also slow,

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Speaker 1: and the public sees less than twelve point five percent

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Speaker 1: of all submitted notes. Partisanship often motivates volunteers to participate,

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Speaker 1: and the system struggles to fact check divisive issues from

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Speaker 1: influential counts and hard to verify claims that include, for example, sarcasm.

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Speaker 1: These challenges call into question whether or not prioritizing consensus

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Speaker 1: and moderation systems designed to address miss and disinformation is

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Speaker 1: a desirable or worthy aim. And I found that to

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Speaker 1: be so interesting because you know, on a platform like X,

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Speaker 1: where that really is the only thing that anybody is

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Speaker 1: doing to prevent the spread of false information, you really

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Speaker 1: see how it might not be something that's genuinely affected

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Speaker 1: at keeping incress information off the platform on TikTok. I

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Speaker 1: like the idea of it being something where it's where

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Speaker 1: context is added or you know, background information or sort

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Speaker 1: of like let me put this in context for you,

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Speaker 1: as opposed to being like yes it is true or

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Speaker 1: no it is not true. I almost wonder if that

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Speaker 1: false binary of true versus not true. But it's like

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Speaker 1: it's just not working on platforms like X when that's

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Speaker 1: the only thing they have.

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Speaker 2: I think there's so many other context on TikTok where

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Speaker 2: context would be so helpful. I mean the amount of

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Speaker 2: times that like I'm fully lost trying to find the

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Speaker 2: original video that someone is like mocking and has like

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Speaker 2: done a play on, or like I'm completely lost and

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Speaker 2: don't have context on like what this like discourse I've

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Speaker 2: stumbled into is, or or what account posted about it first,

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Speaker 2: and like what their user name is? Like it it's

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Speaker 2: so confusing, and like just given the nature of TikTok,

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Speaker 2: you get dropped into like these conversations on your for

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Speaker 2: you page and you're like, I don't know what's happening.

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Speaker 2: So I think, like, yeah, focusing on context and adding

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Speaker 2: that is I think that that can actually be like

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Speaker 2: a beautiful thing for community. I'm interested to see how

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Speaker 2: it plays out. I certainly don't think it can replace

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Speaker 2: fact checking at all ever, And I don't think it

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Speaker 2: can replace true like content moderation. And I certainly worry

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Speaker 2: about companies who just like don't want to deal with

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Speaker 2: content moderation so they just like kind of give that

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Speaker 2: burden to users and they're like, you figure out what's

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Speaker 2: real exactly.

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Speaker 1: Yeah, none of this would be a replacement for expert

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Speaker 1: factcheckers who know what they're doing, who are trained to

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Speaker 1: address things, and particularly like culturally informed content moderators, because

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Speaker 1: so much of the content moderation like it's just if

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Speaker 1: people aren't culturally informed, it can be very difficult to

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Speaker 1: know what people are talking about. I mean, you're you're

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Speaker 1: so right about TikTok. It's a platform that it's really

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Speaker 1: difficult to follow drama on TikTok because god, you're like,

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Speaker 1: I'm out of the loop, Like, but who said what?

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Speaker 1: What started it? I can never keep up?

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Speaker 2: And then like somebody will just post a user name

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Speaker 2: that's like scrambled, and then you get like to like

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Speaker 2: that person's old videos and you're going through and it's

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Speaker 2: just it's a lot of it's a lot of investigative

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Speaker 2: work to try and understand drama you've gotten like dropped

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Speaker 2: into the middle of due to your algorithm. And there's

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Speaker 2: like a lot of the times where I look at

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Speaker 2: something and I like just have to make a decision

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Speaker 2: of just like I have to let this go.

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Speaker 1: I don't like I can't invest any more of my

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Speaker 1: time to try to figure out who started this random dispute. Yeah,

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Speaker 1: I understand that the wordal community is having discourse and

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Speaker 1: that they're fighting, but like, I need to not put

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Speaker 1: any energy into understanding why. Ooh, I actually would be

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Speaker 1: interested to know what the wordal community is up in

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Speaker 1: arms about. They were that was a while ago, but

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Speaker 1: like there was some beef in the word community. I

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Speaker 1: honestly felt like it was kind of manufactured for attention.

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Speaker 3: But that was just me. Let's take a quick break

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Speaker 3: at our back.

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Speaker 1: Okay, Well, speaking of TikTok I have, this is like

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Speaker 1: not something I mean. I'll just say like, I try

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Speaker 1: very hard to not focus on what the Trump administration

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Speaker 1: is doing unless I absolutely have to, and so I

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Speaker 1: blocked all of their social accounts because they're all abhorrent.

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Speaker 1: But when I peeked back in, I was surprised to

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Speaker 1: see that, you know, the TikTok viral baby hold my

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Speaker 1: Hand Nelson Beatza Debt to Holiday, So everybody was on

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Speaker 1: that meme. They were using that song from the Jet

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Speaker 1: to Holiday commercial to illustrate, you know, things vacation's gone

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Speaker 1: awry or things bad happening while they're on trips. While

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Speaker 1: the White House got in on that, they posted on

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Speaker 1: X videos of handcuffed allegedly undocumented people being escorted by

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Speaker 1: blurred out ICE enforcement of fit onto a Global X flight,

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Speaker 1: which is like an airline provider abused by ICE with

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Speaker 1: that viral TikTok sound, and the post is captioned when

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Speaker 1: X books you will one way jet to holiday to deportation.

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Speaker 1: Nothing beats it. Yeah, I just think we I know

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Speaker 1: there's a lot of other horrible stuff in the world,

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Speaker 1: but I do think that we should be talking about

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Speaker 1: how a borring the official comms channels out of this

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Speaker 1: administration have gotten. I remember earlier they were doing the

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Speaker 1: studio Ghiblie like AI generated cartoons. They made one of

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Speaker 1: a woman being deported, like a cartoon version of her crying,

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Speaker 1: and I just feel like they are putting out stuff

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Speaker 1: even for their base. You have to be a depraved

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Speaker 1: sicko to want to see this kind of thing. You

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Speaker 1: have to be like a depraved person to get enjoyment

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Speaker 1: out of this. And it really reminds me of like

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Speaker 1: our country's history with things like lynchings, right, like big

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Speaker 1: public displays, big spectacles being made out of the suffering

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Speaker 1: of others. And I just think like in the scheme

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Speaker 1: of things that might not be that big of a deal.

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Speaker 1: But the way that the administration uses their official comms

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Speaker 1: channels to signal to the most depraved members of their

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Speaker 1: base just really I mean it cannot be overstated.

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Speaker 2: Yeah, No, that meme was like truly sick kidding, Like

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Speaker 2: I felt that in my stomach.

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Speaker 1: I mean same with like the they have like the deportation.

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Speaker 2: Asmr oh too, And it very much is an instance

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Speaker 2: of like the cruelty is the point, right, Like they're

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Speaker 2: trying to be as cruel as possible because they know

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Speaker 2: that it creates media attention.

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Speaker 1: They know it works people up.

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Speaker 2: So it's also just about I think triggering the left

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Speaker 2: to some extent, doing things that they know will make

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Speaker 2: the left upset. And I think it's also partially about desensitization.

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Speaker 2: So like the more you're like eye sockets are assaulted

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Speaker 2: with abhorrent content like that, you just get used to it,

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Speaker 2: You get desensitized to it, and I think it encourages

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Speaker 2: people to like emotionally shut down. It's absolutely bonkers propaganda,

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Speaker 2: but it does seem to be working for them and

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Speaker 2: getting the attention that they crave.

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Speaker 1: Yeah, I think you're so right about the purpose of

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Speaker 1: this kind of content, because I do think it's about

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Speaker 1: you could. I mean, this is why I have these

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Speaker 1: channels all blocked, because you can only see this stuff

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Speaker 1: so much. You can only engage with this so much

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Speaker 1: until you're either it just either you're you become desensitized

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Speaker 1: to it, as you said, or you simply can't go

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Speaker 1: about your day. I mean, Elaine Walterroth had this great

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Speaker 1: TikTok where she was like, the experience of scrolling social

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Speaker 1: media right now is horrible, tragedy, horrible, despicable comms coming

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Speaker 1: out of an official White House channel and then somebody's

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Speaker 1: makeup tutorial. And I don't irmly believe that this is

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Speaker 1: not an environment that we were as humans meant to

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Speaker 1: be in. This is very It's like, oh, no, we

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Speaker 1: should not have this is just should not be normal.

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Speaker 2: No, our brains were not meant to be assaulted with

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Speaker 2: this much like horrendous content and then simultaneously sold as

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Speaker 2: many things to consume as we possibly can. And that's

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Speaker 2: what going on social media like really feels like right

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Speaker 2: now is just like.

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Speaker 1: Horrible thing, horrible thing, by this horrible thing, horrible thing,

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Speaker 1: purchase this and like it's really bleak. And I think

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Speaker 1: that there are people who like see that and recognize it,

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Speaker 1: like that's the emotional experience that like a lot of

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Speaker 1: us are having and are happy to add on to

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Speaker 1: it and try to like emotionally wear us out and

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Speaker 1: wear us down. Yeah, and I think the fact that

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Speaker 1: they're picking these things that are symbols of joy might

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Speaker 1: might be too strong. But the the Studio Ghiblie cartoons,

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Speaker 1: like those cartoons are all about celebrating nature and love

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Speaker 1: and innocence, Like they're very kind of pure and you

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Speaker 1: know they're they're they're for me. They are a symbol

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Speaker 1: of joy. So then seeing that perverted and seeing that

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Speaker 1: taken to illustrate cruelty, I think is as a as

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Speaker 1: a definite like intentional choice.

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Speaker 2: Can we talk about how they did the Jet Too

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Speaker 2: Holiday meme wrong? Though, Like that bothers me because the

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Speaker 2: whole point of the Jets to Holidays that it's supposed

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Speaker 2: to be something going terribly wrong.

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Speaker 1: And yeah, and they are like, oh, we love this,

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Speaker 1: so look at us deporting so well, and it's almost

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Speaker 1: like they almost.

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Speaker 2: Kind of got themselves with the fact that they don't

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Speaker 2: know how the meme works and they just used a

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Speaker 2: trending audio. But like the whole point of that meme

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Speaker 2: is that like fun upbeat audio with like something going

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Speaker 2: just like demonstrably like wrong.

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Speaker 1: Like, yes, they they've kind of misunderstood them, like what

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Speaker 1: makes it a meme? What make it funny? And in

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Speaker 1: a roundabout way, they're kind of saying these deportations are

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Speaker 1: something that have gone wrong. But I know that's not

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Speaker 1: what they want to say. No, that's not what they want.

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Speaker 2: What they want is just like cruelty and supremacy and

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Speaker 2: to like trigger I think they want to like trigger

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Speaker 2: the left and then on the right. They want to

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Speaker 2: trigger feelings in superiority and like give people that kind

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Speaker 2: of like emotional hit of other people's cruelty.

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Speaker 1: Yeah. The person who sings the song is Jess glim.

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Speaker 1: The song is called hold My Hand, and she actually

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Speaker 1: posted a statement on Instagram basically saying that she was

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Speaker 1: horrified to see the White House using her song in

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Speaker 1: this way, even though she was happy to see it

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Speaker 1: take off on TikTok. Initially, she wrote this post honestly

404
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Speaker 1: makes me sick. My music is about love, unity and

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Speaker 1: spreading positivity, never about division or hate. And then the

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Speaker 1: voiceover artist, the one that's saying nothing beats a jet

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Speaker 1: Blue Holiday said what can be done about the White

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Speaker 1: House using jet to Sound and my voice over to

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Speaker 1: promote their nasty agenda? And I do feel like it.

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Speaker 1: I mean it sucks, Like I can't imagine what it

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Speaker 1: must feel like to have the White House take your

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Speaker 1: work and your words and use it to promote something

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Speaker 1: in this way, especially after kind of celebrating that that

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Speaker 1: this jet to Holiday ad that you made people did

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Speaker 1: find joy and sort of recontextualizing it, Like I don't know,

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Speaker 1: I just it's like the White House like we can

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Speaker 1: we cannot have any small moment of joy or or

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Speaker 1: wonder without them being like, how can we pervert this

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Speaker 1: but make it awful? It's so annoying, like let us

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Speaker 1: have fun, let us like enjoy things, but no, like

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Speaker 1: let's like they just come in here and completely ruin

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Speaker 1: the vibes and.

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Speaker 2: It's not like this is like the first artist that

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Speaker 2: this has happened to. It was like, wasn't a Olivia

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Speaker 2: Rodrigo had a song?

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Speaker 1: Oh my god? Which song was it?

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Speaker 3: Was it?

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Speaker 1: Deja vus?

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Speaker 2: That yeah, the Trump administration used as an audio and

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Speaker 2: she was just like take this down or like never

431
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Speaker 2: use my audio again, Like don't use my sound and

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Speaker 2: they deleted her comments, so then she just like removed

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Speaker 2: the sound off of TikTok.

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Speaker 1: I think yeah, And I mean it also says a

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Speaker 1: lot that they have to steal from artists and use

436
00:23:19,359 --> 00:23:23,719
Speaker 1: their voices and their work without permission up because who

437
00:23:23,760 --> 00:23:25,560
Speaker 1: would want to be associated with this? Like they they're

438
00:23:25,600 --> 00:23:27,600
Speaker 1: not able to like it's not like, I mean, part

439
00:23:27,600 --> 00:23:30,199
Speaker 1: of me wonders like why not just work with the

440
00:23:30,440 --> 00:23:33,239
Speaker 1: artists who voluntarily would would sign on for this kind

441
00:23:33,280 --> 00:23:34,800
Speaker 1: of thing. It's telling that it's like, you don't want

442
00:23:34,800 --> 00:23:37,359
Speaker 1: it to be kid rock doing the soundtrack, somebody who

443
00:23:37,440 --> 00:23:39,520
Speaker 1: probably would jump at that chance. No, it has to

444
00:23:39,520 --> 00:23:40,919
Speaker 1: be somebody who doesn't want.

445
00:23:40,760 --> 00:23:43,159
Speaker 2: To be associated with you, Bridget, Bridget, you know, they

446
00:23:43,160 --> 00:23:46,119
Speaker 2: don't have good artists on their side. You know the

447
00:23:46,160 --> 00:23:49,320
Speaker 2: answer to this. They don't have good artists. They have

448
00:23:49,400 --> 00:23:50,440
Speaker 2: to steal ours.

449
00:23:50,560 --> 00:23:54,160
Speaker 1: They have to. They're not making like what the Carrie

450
00:23:54,200 --> 00:23:57,240
Speaker 1: Underwood's going to produce the really top audio right now,

451
00:23:57,320 --> 00:24:00,679
Speaker 1: Like that's what they're working with. Oh my god, this

452
00:24:00,760 --> 00:24:03,120
Speaker 1: is such a throwback that Carrie Underwood thing. I found

453
00:24:03,119 --> 00:24:05,720
Speaker 1: that to be that was like something out of out

454
00:24:05,720 --> 00:24:08,919
Speaker 1: of Veep, where Carrie Underwood. For folks who don't know,

455
00:24:08,960 --> 00:24:11,240
Speaker 1: this is a little bit of my personal Roman Empire

456
00:24:11,600 --> 00:24:14,760
Speaker 1: signed on to perform with the inauguration. Really shouldn't have

457
00:24:15,240 --> 00:24:18,120
Speaker 1: when she signed up. When she went to perform her

458
00:24:18,320 --> 00:24:20,800
Speaker 1: there was a problem with her stage and her performance

459
00:24:20,840 --> 00:24:23,560
Speaker 1: ended up being really yanky, and she was panned, and

460
00:24:24,000 --> 00:24:25,560
Speaker 1: it just was one of those things where it's like, dang,

461
00:24:26,119 --> 00:24:27,600
Speaker 1: don't you wish you would never got mixed up with

462
00:24:27,640 --> 00:24:29,840
Speaker 1: these people? What a bad choice.

463
00:24:29,920 --> 00:24:32,439
Speaker 2: It's oh my god. We always forget how incompetent they

464
00:24:32,440 --> 00:24:35,400
Speaker 2: are too. They're incoonfident and they don't have any good

465
00:24:35,480 --> 00:24:37,960
Speaker 2: artists on their side, and that sucks, and I do

466
00:24:38,000 --> 00:24:38,880
Speaker 2: feel bad for them.

467
00:24:39,119 --> 00:24:40,520
Speaker 1: I do absolutely.

468
00:24:44,280 --> 00:24:57,280
Speaker 3: Let's take a quick break at her back.

469
00:25:02,040 --> 00:25:04,720
Speaker 1: Okay, so we have to talk about what is going

470
00:25:04,760 --> 00:25:08,440
Speaker 1: on at Substack. I don't have a Substack. I for

471
00:25:08,480 --> 00:25:10,480
Speaker 1: the longest time was like, oh, I should get a substack.

472
00:25:10,480 --> 00:25:12,080
Speaker 1: I should get a Substack, and then I'm kind of gone,

473
00:25:12,119 --> 00:25:15,360
Speaker 1: I don't have one. We talked about this before. Back

474
00:25:15,400 --> 00:25:19,440
Speaker 1: in twenty twenty four, Substack agreed to remove Nazi content

475
00:25:19,600 --> 00:25:22,760
Speaker 1: after hundreds of writers, including Casey Newton, who runs this

476
00:25:22,960 --> 00:25:26,520
Speaker 1: very prominent tech publication, platform or on substack. They all

477
00:25:26,560 --> 00:25:29,440
Speaker 1: signed an open letter threatened to quit the platform if

478
00:25:29,440 --> 00:25:32,840
Speaker 1: the platform did not remove Nazi content. The Atlantic reported

479
00:25:32,880 --> 00:25:36,400
Speaker 1: that prominent white supremacists, people like Richard Spencer were using

480
00:25:36,400 --> 00:25:39,120
Speaker 1: the platform to earn money. Spencer was likely at least

481
00:25:39,160 --> 00:25:41,960
Speaker 1: making nine thousand dollars a year and potentially more than

482
00:25:41,960 --> 00:25:45,000
Speaker 1: that from his substack, and because substack got a cut,

483
00:25:45,000 --> 00:25:49,720
Speaker 1: they got ten percent. Essentially, substack is profiting from white

484
00:25:49,760 --> 00:25:54,440
Speaker 1: supremacists who are on their platform. So Substack back in

485
00:25:54,480 --> 00:25:56,919
Speaker 1: twenty twenty four was like, Okay, we'll do something, and

486
00:25:57,359 --> 00:26:00,000
Speaker 1: I guess the problem has not been solved because Taylor

487
00:26:00,040 --> 00:26:03,760
Speaker 1: the Rens reported that substack sent a pushed notification promoting

488
00:26:03,800 --> 00:26:07,840
Speaker 1: a Nazi publication on the platform to an unidentified number

489
00:26:07,880 --> 00:26:12,160
Speaker 1: of their users. I don't use the term Nazi publication lightly.

490
00:26:12,640 --> 00:26:17,200
Speaker 1: The blog literally included a swastika icon, So that's like

491
00:26:18,000 --> 00:26:20,560
Speaker 1: pretty cut and dry. I feel pretty confident saying this

492
00:26:20,640 --> 00:26:22,200
Speaker 1: is a Nazi public They were definitely.

493
00:26:22,480 --> 00:26:26,400
Speaker 2: I think they self identified as a National Socialist public exactly.

494
00:26:26,640 --> 00:26:29,440
Speaker 1: This is not something where I'm just throwing the word

495
00:26:29,520 --> 00:26:32,280
Speaker 1: around like they would probably agree that that's how they

496
00:26:32,359 --> 00:26:36,480
Speaker 1: would They would self identify Yeah, and so substack apologized.

497
00:26:36,600 --> 00:26:39,240
Speaker 1: They said, we discovered an error that caused some people

498
00:26:39,240 --> 00:26:42,159
Speaker 1: to receive pushed notifications they never should have received. In

499
00:26:42,200 --> 00:26:45,720
Speaker 1: some cases, these notifications were extremely offensive and disturbing. Y'll say,

500
00:26:46,320 --> 00:26:48,520
Speaker 1: this was a serious error, and we apologize for the

501
00:26:48,560 --> 00:26:51,640
Speaker 1: distressed cause. We have taken the relevant system offline, diagnosed

502
00:26:51,640 --> 00:26:54,080
Speaker 1: the issue, and are making changes to ensure it does

503
00:26:54,160 --> 00:26:58,720
Speaker 1: not happen again. So I feel like, for as bad

504
00:26:59,040 --> 00:27:02,200
Speaker 1: as it is to send a push notification that includes

505
00:27:02,240 --> 00:27:04,560
Speaker 1: a swastika telling people to check out this nazi blog,

506
00:27:04,840 --> 00:27:07,240
Speaker 1: that that statement, to me is like throw that in

507
00:27:07,280 --> 00:27:09,879
Speaker 1: a garbage It doesn't mean anything. Ours Technica spoke to

508
00:27:10,119 --> 00:27:13,119
Speaker 1: Joshua fish Or Birch, a terrorism analyst at a nonprofit

509
00:27:13,359 --> 00:27:17,280
Speaker 1: and geo the Counter Extremism Project who's been monitoring substack

510
00:27:18,040 --> 00:27:21,919
Speaker 1: and their role in helping far right movements spread propaganda online.

511
00:27:22,160 --> 00:27:24,840
Speaker 1: He makes a very good point that what should be

512
00:27:24,880 --> 00:27:29,560
Speaker 1: happening now is more transparency and then outlining exactly what

513
00:27:29,760 --> 00:27:33,160
Speaker 1: happened and exactly what steps substack is taking to prevent

514
00:27:33,160 --> 00:27:36,080
Speaker 1: it from happening again. Just saying oopsie, we sent you

515
00:27:36,119 --> 00:27:39,480
Speaker 1: a swastika is really not good enough. When you consider

516
00:27:39,800 --> 00:27:43,040
Speaker 1: how big of a of a fuck up that is.

517
00:27:43,320 --> 00:27:46,280
Speaker 2: Yeah, No, that's like a really big fuck up and

518
00:27:46,600 --> 00:27:50,359
Speaker 2: being like, oh, like that system has been diagnosed, what

519
00:27:50,400 --> 00:27:53,440
Speaker 2: do you mean? Yes, what do you mean? Can you

520
00:27:53,520 --> 00:27:55,520
Speaker 2: tell me more about what that system was?

521
00:27:55,600 --> 00:27:57,720
Speaker 1: Like? How did that even get scooped up there?

522
00:27:57,760 --> 00:28:00,680
Speaker 2: Like I go, when we say transparency, we don't mean

523
00:28:00,800 --> 00:28:04,359
Speaker 2: like a two sentenced statement from your company. We say like,

524
00:28:04,400 --> 00:28:08,080
Speaker 2: we mean like like true accountability, like what rent wrong here?

525
00:28:08,880 --> 00:28:10,639
Speaker 2: And like how can you explain it to us so

526
00:28:10,680 --> 00:28:13,320
Speaker 2: that we understand and can have faith that like you're

527
00:28:13,359 --> 00:28:15,520
Speaker 2: taking actions and like steps to make sure it doesn't

528
00:28:15,520 --> 00:28:18,720
Speaker 2: go wrong again? But like that's I don't feel like

529
00:28:18,720 --> 00:28:20,600
Speaker 2: we're getting real transparency here.

530
00:28:20,880 --> 00:28:23,639
Speaker 1: No, absolutely not. And Fish or Birch he made a

531
00:28:23,680 --> 00:28:26,760
Speaker 1: really good point that all of these like far right

532
00:28:27,720 --> 00:28:32,080
Speaker 1: nazi extremist types have gotten the impression that their content

533
00:28:32,200 --> 00:28:35,000
Speaker 1: is far less likely to be removed from substack, and

534
00:28:35,040 --> 00:28:39,040
Speaker 1: they're not wrong. And importantly, they see substack as quote

535
00:28:39,040 --> 00:28:43,200
Speaker 1: a legitimizing tool for sharing content, specifically because the substack brand,

536
00:28:43,920 --> 00:28:46,840
Speaker 1: which is widely used by independent journalists and top influencers

537
00:28:46,960 --> 00:28:50,280
Speaker 1: and sherish content creators, can help them convey the image

538
00:28:50,280 --> 00:28:52,080
Speaker 1: of a thought leader. And so I thought that was

539
00:28:52,120 --> 00:28:55,440
Speaker 1: such an important point. That it's not just that substack

540
00:28:55,600 --> 00:28:58,560
Speaker 1: is hosting this kind of content, which that is a problem,

541
00:28:58,720 --> 00:29:01,239
Speaker 1: it's also that the people who make this kind of

542
00:29:01,280 --> 00:29:05,920
Speaker 1: content rightly understand that me being on substack next to

543
00:29:06,360 --> 00:29:10,000
Speaker 1: all of these important influencers and content creators legitimizes whatever

544
00:29:10,040 --> 00:29:11,600
Speaker 1: it is I have to say. So it's not just

545
00:29:11,640 --> 00:29:14,040
Speaker 1: that it's being taken down. It's that I'm hobnobbing with

546
00:29:14,080 --> 00:29:17,120
Speaker 1: all these other important voices. So it seems like my

547
00:29:17,240 --> 00:29:18,360
Speaker 1: voice is important too.

548
00:29:19,120 --> 00:29:23,400
Speaker 2: Yeah, it like just it lends them legitimacy exactly. It's yeah,

549
00:29:23,440 --> 00:29:28,080
Speaker 2: And hasn't substack like talked about how they don't want

550
00:29:28,120 --> 00:29:30,320
Speaker 2: to take that content down because they don't want to

551
00:29:30,360 --> 00:29:33,720
Speaker 2: like overly sense like sensor that content and they believe

552
00:29:33,720 --> 00:29:34,800
Speaker 2: that like it'll just.

553
00:29:34,800 --> 00:29:36,760
Speaker 1: Go into the shadows, Like, am I right? That's like

554
00:29:36,800 --> 00:29:40,440
Speaker 1: also that is part of their Like that's just also

555
00:29:40,600 --> 00:29:43,160
Speaker 1: we I would so much rather that content be in

556
00:29:43,200 --> 00:29:47,640
Speaker 1: the shadows than on substack next to you know, legitimate journalists,

557
00:29:47,800 --> 00:29:52,200
Speaker 1: like actual high quality substacks. Uh, Like it's okay for

558
00:29:52,360 --> 00:29:54,840
Speaker 1: bad things to be in the shadows where we can't

559
00:29:54,840 --> 00:29:56,960
Speaker 1: see them. Actually that's where bad things like should be

560
00:29:57,080 --> 00:29:59,720
Speaker 1: and should stay. I'm okay with that, and I think

561
00:29:59,760 --> 00:30:03,200
Speaker 1: that's that's that's such a good point. And you know,

562
00:30:03,640 --> 00:30:05,720
Speaker 1: it's one of those things where I do think that,

563
00:30:05,960 --> 00:30:09,160
Speaker 1: like so many prominent journalists who are doing their own

564
00:30:09,200 --> 00:30:11,880
Speaker 1: thing and like have their own you know, media outlets

565
00:30:12,200 --> 00:30:16,360
Speaker 1: are on substack. And it goes back to that old

566
00:30:16,400 --> 00:30:18,760
Speaker 1: adage about a Nazi bar, right, Like, if you're hanging

567
00:30:18,800 --> 00:30:20,920
Speaker 1: out a naziabar, what point are people gonna start thinking

568
00:30:20,920 --> 00:30:23,760
Speaker 1: that you're the Nazi. I think that if substack doesn't

569
00:30:23,800 --> 00:30:27,600
Speaker 1: do something, I think people who are who are prominent

570
00:30:27,640 --> 00:30:29,920
Speaker 1: on the platform who don't want to be associated with

571
00:30:29,920 --> 00:30:32,160
Speaker 1: this kind of thing and don't like don't want this

572
00:30:32,200 --> 00:30:33,600
Speaker 1: thing to be out of the shadows they want. They

573
00:30:33,920 --> 00:30:35,920
Speaker 1: don't want it to be like next to their piece

574
00:30:36,000 --> 00:30:39,240
Speaker 1: or something, I think they might be having to make

575
00:30:39,280 --> 00:30:42,400
Speaker 1: some changes. Angry Black Lady Amani Gandhy, who is a

576
00:30:42,480 --> 00:30:44,920
Speaker 1: journalist and a lawyer who I follow online. She wrote

577
00:30:44,920 --> 00:30:47,800
Speaker 1: on Blue Sky that basically it sounds like substack is

578
00:30:48,600 --> 00:30:52,280
Speaker 1: unsustainable and that people either have to move now or

579
00:30:52,440 --> 00:30:55,160
Speaker 1: move in shame later. Those are really the only two

580
00:30:55,160 --> 00:30:56,560
Speaker 1: options at this point, And I thought that was such

581
00:30:56,560 --> 00:30:59,720
Speaker 1: a good point of like, at a certain point people

582
00:30:59,800 --> 00:31:01,760
Speaker 1: might have to decide, I don't want to be on

583
00:31:01,800 --> 00:31:05,240
Speaker 1: a platform like this, and won't it be embarrassing to

584
00:31:05,320 --> 00:31:08,560
Speaker 1: have to do that in shame after you've been like, Oh,

585
00:31:08,560 --> 00:31:09,840
Speaker 1: they're gonna fix the problem.

586
00:31:11,000 --> 00:31:14,080
Speaker 2: But also at the same time, it puts like creators

587
00:31:14,160 --> 00:31:18,280
Speaker 2: of that content in such a shitty position where like

588
00:31:18,560 --> 00:31:24,080
Speaker 2: they need that like hosting service and their audience uses it,

589
00:31:24,120 --> 00:31:26,920
Speaker 2: and it's not like the audience is that good at

590
00:31:26,960 --> 00:31:30,680
Speaker 2: following people off platform onto different platforms, and so like

591
00:31:30,680 --> 00:31:34,000
Speaker 2: if they're financially dependent on substack and they've gone independent

592
00:31:34,080 --> 00:31:37,000
Speaker 2: and they like rely on it, then like it's a

593
00:31:37,040 --> 00:31:40,080
Speaker 2: big ask to be like, can you not use this

594
00:31:40,160 --> 00:31:43,120
Speaker 2: platform that you rely on and that you can't really

595
00:31:43,440 --> 00:31:48,760
Speaker 2: transfer your audience to anywhere else because you don't like

596
00:31:48,880 --> 00:31:51,600
Speaker 2: other content that's being hosted here. Like it's it's really hard.

597
00:31:51,640 --> 00:31:54,360
Speaker 2: It puts them in a really yeah, between a rock

598
00:31:54,400 --> 00:31:56,280
Speaker 2: and a hard place. That's a really good point.

599
00:31:56,320 --> 00:31:59,680
Speaker 1: They're really doing a disservice to the people that use

600
00:31:59,720 --> 00:32:02,200
Speaker 1: their but they have to be thinking about this at all.

601
00:32:02,240 --> 00:32:04,320
Speaker 1: And I get a lot of people who are on subseck.

602
00:32:04,440 --> 00:32:07,440
Speaker 1: Like the state of journalism and media, everyone I know

603
00:32:07,800 --> 00:32:10,560
Speaker 1: has either been laid off or wakes up being worried

604
00:32:10,560 --> 00:32:12,400
Speaker 1: about being laid off. And the people who are laid

605
00:32:12,400 --> 00:32:15,120
Speaker 1: off often use platforms like subsec to do their own

606
00:32:15,160 --> 00:32:17,240
Speaker 1: thing while they figure out what's next. But I think

607
00:32:18,040 --> 00:32:20,280
Speaker 1: they I think SUBSEC is putting a lot of people

608
00:32:20,640 --> 00:32:24,600
Speaker 1: who are already oftentimes operating from a place of precarity,

609
00:32:24,760 --> 00:32:27,480
Speaker 1: not oft not always, but often, I think that they

610
00:32:27,520 --> 00:32:30,680
Speaker 1: are putting this on them in a way that is

611
00:32:30,720 --> 00:32:31,800
Speaker 1: I don't think is acceptable.

612
00:32:32,600 --> 00:32:35,040
Speaker 2: No, I mean, that's what happens on every platform where

613
00:32:35,080 --> 00:32:38,400
Speaker 2: like they refuse to engage in and content moderation because

614
00:32:38,400 --> 00:32:40,760
Speaker 2: like arguably I do the same thing on TikTok where

615
00:32:40,760 --> 00:32:43,040
Speaker 2: like I'm forced to be on TikTok at like to

616
00:32:43,280 --> 00:32:46,720
Speaker 2: to reach my audience who I can't transfer over anywhere else.

617
00:32:48,040 --> 00:32:50,480
Speaker 2: And it's also on a platform that is like you know,

618
00:32:50,880 --> 00:32:54,120
Speaker 2: consumed with like misinformation and like a lot of you know,

619
00:32:54,240 --> 00:32:56,440
Speaker 2: like I just published about all like the racist AI

620
00:32:56,560 --> 00:33:00,479
Speaker 2: generated content and I'm forced to like live there, and

621
00:33:00,520 --> 00:33:04,479
Speaker 2: it's it's not fair to me. I don't think it's fair. Uh,

622
00:33:04,880 --> 00:33:07,000
Speaker 2: I mean, I think that the platform in general would

623
00:33:07,000 --> 00:33:08,760
Speaker 2: be a lot better if it focused instead on like

624
00:33:08,800 --> 00:33:13,120
Speaker 2: creators who made like original, high quality content, but that's

625
00:33:13,640 --> 00:33:16,920
Speaker 2: not where they want to invest all of their operations.

626
00:33:17,440 --> 00:33:19,200
Speaker 1: You know, the last time that you and I spoke

627
00:33:19,280 --> 00:33:22,600
Speaker 1: on the podcast, we were talking about a potential TikTok

628
00:33:22,640 --> 00:33:26,320
Speaker 1: ban in the United States. If TikTok was banned, what,

629
00:33:26,720 --> 00:33:29,640
Speaker 1: like what would that look like for your voice and

630
00:33:29,680 --> 00:33:30,920
Speaker 1: your platform.

631
00:33:31,520 --> 00:33:34,880
Speaker 2: I mean, on one hand, I would lose like, you know,

632
00:33:34,920 --> 00:33:39,200
Speaker 2: half a million followers, which is is like brutal. But

633
00:33:39,320 --> 00:33:42,280
Speaker 2: on the other hand, my TikTok reach right now is terrible,

634
00:33:42,840 --> 00:33:44,240
Speaker 2: absolutely horrendous.

635
00:33:45,080 --> 00:33:51,520
Speaker 1: Uh, Like I barely can reach like a tenth of

636
00:33:51,600 --> 00:33:55,280
Speaker 1: those followers, like I just have. I never have guaranteed.

637
00:33:54,800 --> 00:33:56,920
Speaker 2: Access to the people who did choose to opt into

638
00:33:56,960 --> 00:34:01,040
Speaker 2: my content and like routinely them in the comments being

639
00:34:01,080 --> 00:34:03,080
Speaker 2: like I haven't seen you on my fore page in

640
00:34:03,200 --> 00:34:07,960
Speaker 2: years or like whatever. And I feel like on TikTok,

641
00:34:08,040 --> 00:34:10,960
Speaker 2: especially right now, my content is just being flooded out

642
00:34:11,000 --> 00:34:14,640
Speaker 2: with ads instead. I mean, the place is just becoming

643
00:34:14,680 --> 00:34:19,880
Speaker 2: like a glorified Amazon. I got eleven sponsored posts in

644
00:34:19,920 --> 00:34:23,920
Speaker 2: a row like last month between like TikTok shop ads

645
00:34:23,920 --> 00:34:25,040
Speaker 2: and like actual ads.

646
00:34:25,320 --> 00:34:26,960
Speaker 1: I got eleven in a row.

647
00:34:27,040 --> 00:34:29,840
Speaker 2: I screen recorded at eleven in a row. It was

648
00:34:30,080 --> 00:34:34,680
Speaker 2: crazy and like it's barely usable. I mean, I loved

649
00:34:34,760 --> 00:34:35,719
Speaker 2: TikTok for a time.

650
00:34:36,080 --> 00:34:39,520
Speaker 1: I stopped using it precisely because of the just the

651
00:34:39,600 --> 00:34:44,040
Speaker 1: deluge of ads. And I don't mind ads that much

652
00:34:44,080 --> 00:34:49,560
Speaker 1: in my content. However, there was there is something particularly

653
00:34:53,680 --> 00:35:00,000
Speaker 1: the user generated TikTok shop ads alongside the regular ad

654
00:35:00,760 --> 00:35:04,880
Speaker 1: There's something about that that just feels dystopian. You know,

655
00:35:05,560 --> 00:35:08,319
Speaker 1: you've probably seen this sting on there where it will

656
00:35:08,360 --> 00:35:12,000
Speaker 1: be someone who says they're going through a horrible trauma

657
00:35:12,400 --> 00:35:15,360
Speaker 1: and it's like, can you just let this video play

658
00:35:15,480 --> 00:35:18,399
Speaker 1: for seven seconds or so that I can get get

659
00:35:18,480 --> 00:35:20,640
Speaker 1: on the button so that I can pay my bills

660
00:35:20,760 --> 00:35:25,480
Speaker 1: or whatever. Yeah, I'm very sympathetic to people who need

661
00:35:25,560 --> 00:35:29,839
Speaker 1: to use platforms like TikTok to raise money to get

662
00:35:29,840 --> 00:35:33,920
Speaker 1: themselves out of tough situations. But it just it just

663
00:35:33,920 --> 00:35:37,439
Speaker 1: makes me sad. It just doesn't feel good to show

664
00:35:37,560 --> 00:35:41,000
Speaker 1: up on a platform where this is feeling more and

665
00:35:41,040 --> 00:35:43,400
Speaker 1: more like the norm and less and less like a

666
00:35:43,600 --> 00:35:46,160
Speaker 1: like an unusual experience, you know what I'm saying.

667
00:35:46,400 --> 00:35:50,280
Speaker 2: Yeah, It's almost like we now are not just consuming

668
00:35:50,320 --> 00:35:53,480
Speaker 2: the ads, but we also produce ads for ourselves to

669
00:35:53,600 --> 00:35:58,160
Speaker 2: consume alongside other content of people just being like I

670
00:35:58,239 --> 00:36:01,000
Speaker 2: need money so badly and you have to sit there

671
00:36:01,040 --> 00:36:04,440
Speaker 2: and be like, my attention is currency. I have to

672
00:36:04,600 --> 00:36:07,720
Speaker 2: pay you in attention so that you can pay rent.

673
00:36:07,800 --> 00:36:11,400
Speaker 2: And it's just it's so dystopian and it feels like

674
00:36:11,440 --> 00:36:15,200
Speaker 2: it never ends, and it's it's brutal because I remember

675
00:36:15,239 --> 00:36:17,920
Speaker 2: a time where TikTok was fun and not flooded with dads,

676
00:36:18,400 --> 00:36:21,040
Speaker 2: and now I go on there and it just feels

677
00:36:21,280 --> 00:36:23,080
Speaker 2: like I'm reminded of what.

678
00:36:23,120 --> 00:36:26,840
Speaker 1: Like a capitalist dystopia we live in. Oh my god.

679
00:36:26,960 --> 00:36:30,719
Speaker 1: I was seeing this song on TikTok everywhere and I

680
00:36:30,760 --> 00:36:32,480
Speaker 1: was like, Oh, it's weird that this song I've never

681
00:36:32,480 --> 00:36:34,000
Speaker 1: heard of by an artist I have never heard of

682
00:36:34,040 --> 00:36:36,560
Speaker 1: and don't know at all, is in all these tiktoks

683
00:36:36,560 --> 00:36:39,440
Speaker 1: at the same time. And it turned out that you

684
00:36:39,520 --> 00:36:42,000
Speaker 1: probably know this. I learned this for the first time,

685
00:36:42,400 --> 00:36:45,280
Speaker 1: that TikTok had a program where you could get paid

686
00:36:45,400 --> 00:36:48,640
Speaker 1: to use artists' songs because they're trying to promote the

687
00:36:48,680 --> 00:36:51,080
Speaker 1: songs with like, oh, if you get x views on

688
00:36:51,120 --> 00:36:53,680
Speaker 1: this song, you might get a payout, and I realized

689
00:36:54,160 --> 00:36:57,680
Speaker 1: is nothing organic anymore? No, people like like, if I

690
00:36:57,840 --> 00:37:01,440
Speaker 1: like a song, I'll use that song on social media.

691
00:37:01,640 --> 00:37:04,680
Speaker 1: But the idea that someone would be being paid to

692
00:37:05,800 --> 00:37:09,319
Speaker 1: amplify a song just so that it becomes an earworm, yeah,

693
00:37:09,360 --> 00:37:11,200
Speaker 1: I guess it's just what you're saying. It's it's just

694
00:37:11,239 --> 00:37:16,040
Speaker 1: so clearly an attention economy where they're just trying to

695
00:37:17,400 --> 00:37:20,879
Speaker 1: get whatever value they can of me, my eyeball's paying

696
00:37:20,920 --> 00:37:23,040
Speaker 1: attention to something for a couple of seconds, and it's

697
00:37:23,040 --> 00:37:25,719
Speaker 1: like like they're not asking did anybody actually like the song?

698
00:37:25,800 --> 00:37:28,480
Speaker 1: That anybody would anybody have actually organically used this song

699
00:37:28,520 --> 00:37:30,040
Speaker 1: and their content. No, they were just trying to get

700
00:37:30,040 --> 00:37:32,200
Speaker 1: a couple a couple of cents, Okay.

701
00:37:32,040 --> 00:37:35,120
Speaker 2: Yeah, now it really the moment that broke me was

702
00:37:35,160 --> 00:37:37,600
Speaker 2: one time I had an influencer tell me that they

703
00:37:37,600 --> 00:37:42,799
Speaker 2: were paid by jo Josiah's team to talk about her negatively.

704
00:37:43,040 --> 00:37:45,840
Speaker 1: I absolutely believe this because something's going on with Jojo

705
00:37:45,920 --> 00:37:48,839
Speaker 1: Siwa and I never it's always there's only something going

706
00:37:48,880 --> 00:37:51,359
Speaker 1: on with her, and I absolutely believe I believe her.

707
00:37:51,440 --> 00:37:52,800
Speaker 1: I believe that influenceder No.

708
00:37:52,880 --> 00:37:54,680
Speaker 2: I mean, the influencer showed me the video like I

709
00:37:54,719 --> 00:37:58,040
Speaker 2: saw it and like told me about like the money

710
00:37:58,080 --> 00:38:00,719
Speaker 2: they took, uh, and that like their team was very

711
00:38:00,760 --> 00:38:04,160
Speaker 2: much just like say whatever you've got to say, like anything,

712
00:38:04,719 --> 00:38:08,400
Speaker 2: anything you want to say. And yeah, I really do

713
00:38:08,560 --> 00:38:11,880
Speaker 2: believe that like very little is organic at these points,

714
00:38:11,920 --> 00:38:14,759
Speaker 2: and just so much of it is just like discourse

715
00:38:14,880 --> 00:38:17,080
Speaker 2: all the way down and at the end of the day,

716
00:38:17,120 --> 00:38:18,839
Speaker 2: it's just like meaningless distraction.

717
00:38:19,680 --> 00:38:22,440
Speaker 1: Oh my gosh, I mean I might even cut this,

718
00:38:22,560 --> 00:38:25,800
Speaker 1: But when my producer was putting together the different stories

719
00:38:25,800 --> 00:38:28,360
Speaker 1: that we might talk about, one of the potential things

720
00:38:28,520 --> 00:38:32,640
Speaker 1: was the Sydney Sweeney controversy around the American and Eagle

721
00:38:32,840 --> 00:38:35,319
Speaker 1: Jeans ad. That's like, oh, I have great genes. And

722
00:38:35,719 --> 00:38:37,600
Speaker 1: the only thing I have to say about that is

723
00:38:37,640 --> 00:38:41,200
Speaker 1: that it just demonstrated to me how annoying discourse is

724
00:38:41,239 --> 00:38:45,400
Speaker 1: on the Internet, because it's just it's just a very

725
00:38:45,560 --> 00:38:51,680
Speaker 1: It just became clear how easily our attention is captured

726
00:38:51,880 --> 00:38:53,960
Speaker 1: and how easily we're all sort of played in a

727
00:38:54,040 --> 00:38:57,360
Speaker 1: kind of way that you know, I think that company

728
00:38:57,440 --> 00:38:59,080
Speaker 1: was like, oh, this is going to be a controversial

729
00:38:59,080 --> 00:39:01,440
Speaker 1: ad that he gets people talking. I think that one

730
00:39:01,440 --> 00:39:05,280
Speaker 1: of the executives from American Eagle posted on LinkedIn basically

731
00:39:05,320 --> 00:39:08,480
Speaker 1: saying that, oh, Sidney Sweeney really wanted to, you know,

732
00:39:09,920 --> 00:39:12,200
Speaker 1: make this something everybody was talking about. And I just

733
00:39:12,560 --> 00:39:14,759
Speaker 1: just it just I'm just so sick of feeling like

734
00:39:15,560 --> 00:39:19,279
Speaker 1: we are all so reactive and that our attention is

735
00:39:19,320 --> 00:39:23,000
Speaker 1: just so easily gamified. And they're not wrong, right, like,

736
00:39:23,000 --> 00:39:24,960
Speaker 1: like that's not incorrect, it's very effective.

737
00:39:25,320 --> 00:39:27,400
Speaker 2: It's so effective, and it like distracts us from like

738
00:39:27,520 --> 00:39:32,239
Speaker 2: actual real problems, with like surface level representations of those problems.

739
00:39:32,840 --> 00:39:37,520
Speaker 2: Like did you read Charlie Rosel's piece in I think

740
00:39:37,520 --> 00:39:38,280
Speaker 2: it was The Atlantic?

741
00:39:38,400 --> 00:39:39,040
Speaker 1: I sure did.

742
00:39:39,239 --> 00:39:42,399
Speaker 2: Sidney Speed I literally copied and pasted his last because

743
00:39:42,560 --> 00:39:44,120
Speaker 2: I was like, if we talk about this, I need

744
00:39:44,120 --> 00:39:46,680
Speaker 2: to read to you this last paragraph because like it

745
00:39:46,800 --> 00:39:49,360
Speaker 2: had some place like stuff on discourse that can.

746
00:39:49,239 --> 00:39:51,520
Speaker 1: I just read it? Oh my god, hit us with it. Okay.

747
00:39:51,840 --> 00:39:56,200
Speaker 2: Discourse suggests a process that feels productive, maybe even democratic,

748
00:39:56,440 --> 00:39:58,759
Speaker 2: but there's nothing productive about the end result of our

749
00:39:58,840 --> 00:40:03,120
Speaker 2: information environment. What we're consuming isn't discourse. It's algorithmic grist

750
00:40:03,239 --> 00:40:05,759
Speaker 2: for the mills that power the platforms. We've uploaded our

751
00:40:05,760 --> 00:40:08,759
Speaker 2: conversations onto the Grist is made of all our very

752
00:40:08,800 --> 00:40:12,239
Speaker 2: real political and cultural anxieties ground down until they start

753
00:40:12,280 --> 00:40:14,879
Speaker 2: to feel meaningless. The only thing that matters is that

754
00:40:14,920 --> 00:40:18,920
Speaker 2: the machine keeps running, the wheel keeps turning, leaving everybody

755
00:40:19,000 --> 00:40:21,360
Speaker 2: feeling like they've won and lost at the same time.

756
00:40:22,320 --> 00:40:25,560
Speaker 1: That is exactly how it feels. That is that literally

757
00:40:25,920 --> 00:40:28,560
Speaker 1: that like sums it up exactly.

758
00:40:28,320 --> 00:40:32,600
Speaker 2: Literally, Like that's exactly it, and like it's just so

759
00:40:33,760 --> 00:40:37,160
Speaker 2: mindless and it's about these real things, like they are

760
00:40:37,239 --> 00:40:40,439
Speaker 2: these very real political and cultural anxieties, and yet it's

761
00:40:40,680 --> 00:40:42,480
Speaker 2: just a hamster.

762
00:40:42,120 --> 00:40:45,879
Speaker 1: Wheel where it takes us nowhere at all. Yeah, And

763
00:40:46,960 --> 00:40:49,880
Speaker 1: I mean I checked back in on the discourse around

764
00:40:50,040 --> 00:40:53,920
Speaker 1: the ad and it was like liberals turn on Sydney

765
00:40:54,000 --> 00:40:57,200
Speaker 1: Sweeney because they hate hot women, and it's like, who

766
00:40:57,239 --> 00:40:59,520
Speaker 1: hates hot people? No, Like, I just really love you

767
00:40:59,520 --> 00:41:02,360
Speaker 1: hot women. Yeah, I like talking about.

768
00:41:04,160 --> 00:41:05,719
Speaker 2: I will speak for the left and be like I

769
00:41:05,800 --> 00:41:08,319
Speaker 2: love hot women. And they're like they hate they hate

770
00:41:08,400 --> 00:41:10,400
Speaker 2: her boobs, and I'm like, no, I love her boobs.

771
00:41:10,760 --> 00:41:13,320
Speaker 1: And also like, what's I don't think we need to

772
00:41:13,360 --> 00:41:15,840
Speaker 1: act like good looking women with big boobs are in

773
00:41:15,920 --> 00:41:17,399
Speaker 1: a pressed class, you know what I mean?

774
00:41:18,160 --> 00:41:18,560
Speaker 3: They don't.

775
00:41:18,640 --> 00:41:22,400
Speaker 1: They don't understand the plight the flight of a hot

776
00:41:22,520 --> 00:41:26,879
Speaker 1: blonde with big tits Fridgid, We don't know the struggle, yes,

777
00:41:29,880 --> 00:41:33,560
Speaker 1: but yeah, it's just just something about that particular story

778
00:41:33,640 --> 00:41:37,440
Speaker 1: I found very exhausting, and I think that piece really

779
00:41:37,440 --> 00:41:40,400
Speaker 1: sums it up that it it feels like a hamster

780
00:41:40,520 --> 00:41:44,319
Speaker 1: wheel where we kind of get near, like you're right

781
00:41:44,360 --> 00:41:47,880
Speaker 1: that there are real anxieties, real political and social anxieties

782
00:41:48,280 --> 00:41:51,239
Speaker 1: that they kind of represent, but then we're not actually

783
00:41:51,320 --> 00:41:53,879
Speaker 1: having a substantive conversation. It just feels like when you

784
00:41:53,920 --> 00:41:55,760
Speaker 1: eat a bunch of junk food, a bunch of McDonald's,

785
00:41:55,760 --> 00:41:57,920
Speaker 1: and then you feel good for a minute, but then

786
00:41:57,960 --> 00:41:59,960
Speaker 1: you're hungry again later because you didn't get any nourish.

787
00:42:00,040 --> 00:42:02,799
Speaker 1: But I don't. I feel like the discourse is not

788
00:42:02,960 --> 00:42:06,080
Speaker 1: nourishing me. It's only it's like making me feel empty.

789
00:42:06,320 --> 00:42:09,680
Speaker 2: Yeah, it's yeah, it reminds me of the discourse around

790
00:42:10,520 --> 00:42:14,680
Speaker 2: Sabrina Carpenter's album. It was exact same thing of just

791
00:42:14,760 --> 00:42:18,320
Speaker 2: like this is so meaningless and it truly doesn't matter,

792
00:42:18,520 --> 00:42:23,000
Speaker 2: and it's not really like representative of all of feminism.

793
00:42:22,560 --> 00:42:25,319
Speaker 1: Or like all of all women, and like we.

794
00:42:25,320 --> 00:42:28,759
Speaker 2: Project so much meaning onto things, and I think it

795
00:42:28,800 --> 00:42:32,960
Speaker 2: represents like our feelings of like lack of control, and

796
00:42:33,600 --> 00:42:37,200
Speaker 2: it just, oh my god, that discourse drove me absolutely insane.

797
00:42:37,440 --> 00:42:40,560
Speaker 2: They were like, she's setting the feminist movement back, or like,

798
00:42:40,600 --> 00:42:42,719
Speaker 2: you know, she's like a feminist icon, and it's just like,

799
00:42:42,760 --> 00:42:43,960
Speaker 2: I think she's just horny.

800
00:42:44,719 --> 00:42:47,200
Speaker 1: Yeah, I think it's so random. Have you ever seen

801
00:42:47,239 --> 00:42:50,560
Speaker 1: the movie This is Vital Tap? No, So it's it's

802
00:42:50,560 --> 00:42:53,160
Speaker 1: such a classic. I'm like outing myself with a big

803
00:42:53,200 --> 00:42:57,320
Speaker 1: nerd here. But it's a satirical movie about a rock band.

804
00:42:57,800 --> 00:43:01,080
Speaker 1: It's like a mockumentary. And they put out an album

805
00:43:01,160 --> 00:43:04,200
Speaker 1: cover where it's a woman sniffing a glove.

806
00:43:04,880 --> 00:43:09,520
Speaker 4: She's put a greased, naked woman on all fours with

807
00:43:09,600 --> 00:43:12,920
Speaker 4: a dog collar around her neck and a leash and

808
00:43:12,960 --> 00:43:16,560
Speaker 4: a man's arm extended out up to here, holding on

809
00:43:16,640 --> 00:43:19,799
Speaker 4: to the leash and pushing a black glove in her

810
00:43:19,880 --> 00:43:22,920
Speaker 4: face to sniff it. You don't find that offensive, you

811
00:43:22,960 --> 00:43:24,960
Speaker 4: don't find that sexy.

812
00:43:25,360 --> 00:43:27,960
Speaker 3: That's nineteen eighty two. Get out of the sixties.

813
00:43:28,000 --> 00:43:29,680
Speaker 1: We don't have this mentality anymore.

814
00:43:30,480 --> 00:43:32,799
Speaker 4: They wanted to do. I don't care what they want

815
00:43:32,800 --> 00:43:33,120
Speaker 4: to believe.

816
00:43:33,360 --> 00:43:35,200
Speaker 1: When I first saw that to Breena Carpenter album, I

817
00:43:35,239 --> 00:43:38,799
Speaker 1: was like, Oh, is this a no mushmild a really

818
00:43:38,920 --> 00:43:42,160
Speaker 1: niche of mad a niche. This is a joke for

819
00:43:42,320 --> 00:43:45,840
Speaker 1: just me specifically. That's so funny.

820
00:43:45,960 --> 00:43:48,520
Speaker 2: I also think this is just like this is like

821
00:43:48,600 --> 00:43:51,040
Speaker 2: new research that just came out from media matters, but

822
00:43:51,200 --> 00:43:54,400
Speaker 2: is like interesting with the Sydney Sweeney stuff they just

823
00:43:54,440 --> 00:43:58,440
Speaker 2: published that Like since Monday, Fox News spent eighty five

824
00:43:58,520 --> 00:44:02,960
Speaker 2: minutes talking about Sydney's and three minutes talking about Epstein.

825
00:44:03,160 --> 00:44:06,799
Speaker 1: Certainly Sidney Sweeney's new American eagle gene that is more

826
00:44:06,840 --> 00:44:11,440
Speaker 1: important has more like bigger impacts for the country.

827
00:44:11,560 --> 00:44:15,120
Speaker 2: No, And it's like it just feels so representative of

828
00:44:15,160 --> 00:44:19,600
Speaker 2: like how our own like discourse cycle that like we

829
00:44:19,880 --> 00:44:23,319
Speaker 2: feel like is somehow scratching an itch of our like

830
00:44:23,400 --> 00:44:27,719
Speaker 2: political issues actually just becomes a tool to distract us

831
00:44:27,760 --> 00:44:33,200
Speaker 2: from like real political power and how it's manipulated. Like

832
00:44:33,760 --> 00:44:37,279
Speaker 2: it just it feels so representative of that phenomenon.

833
00:44:37,560 --> 00:44:38,080
Speaker 1: Definitely.

834
00:44:38,440 --> 00:44:42,360
Speaker 3: Oh more, after a.

835
00:44:42,360 --> 00:44:59,560
Speaker 1: Quick break, let's get right back into it. LinkedIn is

836
00:45:00,040 --> 00:45:04,399
Speaker 1: viiantly stripping their explicit protections for trans and non white

837
00:45:04,480 --> 00:45:08,400
Speaker 1: users from its English language hate speech rules. The changes,

838
00:45:08,440 --> 00:45:12,040
Speaker 1: which were flagged by the nonprofit Open Terms Archive and

839
00:45:12,080 --> 00:45:15,640
Speaker 1: then independently confirmed by the advocate involved, edits to LinkedIn's

840
00:45:15,640 --> 00:45:19,480
Speaker 1: professional community policies, specifically the hateful and Derogatory content and

841
00:45:19,480 --> 00:45:24,200
Speaker 1: harassment and Abusive Content sections in both references to protections

842
00:45:24,200 --> 00:45:26,560
Speaker 1: for trans people and people of color were either weakened

843
00:45:26,640 --> 00:45:30,160
Speaker 1: or removed entirely. This is something that is I have

844
00:45:30,160 --> 00:45:32,040
Speaker 1: a b in my bonnet about it because it was

845
00:45:32,400 --> 00:45:34,760
Speaker 1: work that I worked on when I was at Ultra Violet,

846
00:45:34,840 --> 00:45:37,000
Speaker 1: like getting platforms like I will say TikTok was one

847
00:45:37,040 --> 00:45:38,560
Speaker 1: of the first platforms to be like, oh, of course

848
00:45:38,560 --> 00:45:41,600
Speaker 1: we will add dead naming and misgendering to our hateful

849
00:45:41,600 --> 00:45:42,240
Speaker 1: conduct policies.

850
00:45:42,320 --> 00:45:42,480
Speaker 3: Yeah.

851
00:45:42,520 --> 00:45:45,920
Speaker 1: Great. But when Elon Musk bought Twitter, one of his

852
00:45:46,000 --> 00:45:50,840
Speaker 1: first acts was removing twitters at dead naming and misgendering

853
00:45:50,880 --> 00:45:55,239
Speaker 1: policy from their hate speech policy. And I remember thinking, oh, well,

854
00:45:55,320 --> 00:45:58,840
Speaker 1: I think that platforms are going to be watching to

855
00:45:58,880 --> 00:46:01,120
Speaker 1: see if he is able to do this without much

856
00:46:01,120 --> 00:46:04,440
Speaker 1: fanfare and without much pushback. People did push back against it.

857
00:46:04,440 --> 00:46:06,400
Speaker 1: It's not like nobody said anything, but I think the

858
00:46:06,400 --> 00:46:08,480
Speaker 1: fact that he was able to just like unilaterally make

859
00:46:08,520 --> 00:46:11,720
Speaker 1: that choice, and you know, people kept using the platform.

860
00:46:11,760 --> 00:46:14,000
Speaker 1: At that point, I think signaled to a lot of

861
00:46:14,040 --> 00:46:17,120
Speaker 1: other platforms that it was okay to roll back these

862
00:46:17,200 --> 00:46:20,719
Speaker 1: kinds of policies. So when Trump got an office in January,

863
00:46:21,400 --> 00:46:23,839
Speaker 1: like Meta did the same thing, YouTube did the same thing.

864
00:46:24,200 --> 00:46:28,719
Speaker 1: And I do think you know, platforms, they see how

865
00:46:28,800 --> 00:46:31,960
Speaker 1: other CEOs behave, they see what other things that other

866
00:46:32,000 --> 00:46:34,200
Speaker 1: platforms can get away with, and I think it informs

867
00:46:34,200 --> 00:46:35,799
Speaker 1: what they think they can get away with. So I

868
00:46:35,800 --> 00:46:38,560
Speaker 1: do really think that in part we have Elon Musk

869
00:46:38,600 --> 00:46:42,120
Speaker 1: to sort of blame for LinkedIn of all places feeling

870
00:46:42,160 --> 00:46:45,279
Speaker 1: as if it's fine for them to stop or to

871
00:46:45,400 --> 00:46:48,880
Speaker 1: roll back these these policies to add protections for trans

872
00:46:48,920 --> 00:46:50,040
Speaker 1: folks and people of color.

873
00:46:50,400 --> 00:46:54,120
Speaker 2: I think in general, like there's group think when it

874
00:46:54,160 --> 00:46:59,640
Speaker 2: comes to stuff like you know, content moderation policies on platforms,

875
00:47:00,040 --> 00:47:02,359
Speaker 2: and they are kind of all looking at each other

876
00:47:02,560 --> 00:47:06,160
Speaker 2: because like, I don't want to moderate. It's it's like

877
00:47:06,920 --> 00:47:10,320
Speaker 2: time intensive, it's money intensive, it requires the hire people

878
00:47:10,440 --> 00:47:12,920
Speaker 2: to do that work. Like the less moderation that they

879
00:47:12,960 --> 00:47:15,920
Speaker 2: have to do, like, the more cost effective it is

880
00:47:15,920 --> 00:47:16,239
Speaker 2: for them.

881
00:47:16,280 --> 00:47:18,000
Speaker 1: So I think that they're always going to look for

882
00:47:18,120 --> 00:47:20,440
Speaker 1: where they can trim that and just like not.

883
00:47:20,560 --> 00:47:26,560
Speaker 2: Have to worry about it. It's it's I don't understand it.

884
00:47:26,600 --> 00:47:29,319
Speaker 2: I don't understand why you would just like not care

885
00:47:29,560 --> 00:47:33,200
Speaker 2: if your platform becomes like a toxic wasteland. I really

886
00:47:33,200 --> 00:47:37,000
Speaker 2: can't wrap my head around it, especially a platform like LinkedIn.

887
00:47:37,239 --> 00:47:41,319
Speaker 1: Yeah, so it's for it's really meant to be for professionals,

888
00:47:41,400 --> 00:47:44,040
Speaker 1: job seekers, that kind of thing. I think, not giving

889
00:47:44,760 --> 00:47:48,040
Speaker 1: trans folks and folks of color an equal playing field

890
00:47:48,200 --> 00:47:51,160
Speaker 1: in a digital arena that it's all about job seeking,

891
00:47:51,239 --> 00:47:55,239
Speaker 1: it's just not. It's it's it feels especially cruel, especially

892
00:47:55,280 --> 00:47:57,279
Speaker 1: as more and more people are getting laid off that

893
00:47:57,600 --> 00:48:01,080
Speaker 1: are that nobody it seems like nobody's hiring right now.

894
00:48:01,120 --> 00:48:06,040
Speaker 1: It just feels like an extra added burden that fist

895
00:48:06,120 --> 00:48:10,000
Speaker 1: people and not non black people are not asked to

896
00:48:10,280 --> 00:48:11,719
Speaker 1: deal with. If you if you can't show up to

897
00:48:11,760 --> 00:48:14,759
Speaker 1: a platform that it's all about talking about professional accomplishments

898
00:48:14,760 --> 00:48:17,560
Speaker 1: and professional thought leader and find thought leadership and like

899
00:48:17,640 --> 00:48:20,120
Speaker 1: finding a job, if you can't show up there without

900
00:48:20,440 --> 00:48:23,440
Speaker 1: being dead named and misgendered, I just think it really

901
00:48:24,040 --> 00:48:27,040
Speaker 1: it's it's a it's a clear way where these platforms

902
00:48:27,080 --> 00:48:30,200
Speaker 1: are not equitable and people are not having equitable experiences

903
00:48:30,239 --> 00:48:30,560
Speaker 1: on them.

904
00:48:30,800 --> 00:48:33,440
Speaker 2: Yeah, and like we've known that, and we've known that

905
00:48:33,480 --> 00:48:37,040
Speaker 2: they also aren't very good at enforcing those policies. But

906
00:48:37,200 --> 00:48:39,840
Speaker 2: like watching them get taken away and like take away,

907
00:48:39,920 --> 00:48:42,080
Speaker 2: like even like the pretense that they were going to

908
00:48:42,160 --> 00:48:45,240
Speaker 2: try is just like really sad, and I think speaks

909
00:48:45,239 --> 00:48:49,359
Speaker 2: to like the current political moment and the apathy that

910
00:48:49,400 --> 00:48:55,320
Speaker 2: these companies feel towards like a need to serve historically

911
00:48:55,360 --> 00:48:58,160
Speaker 2: like marginalized groups, Like they don't like they like that

912
00:48:58,320 --> 00:49:00,920
Speaker 2: was very much I think a performance for when it

913
00:49:01,040 --> 00:49:04,440
Speaker 2: was popular, and now that they feel like it's not popular,

914
00:49:04,440 --> 00:49:04,839
Speaker 2: they're not.

915
00:49:04,800 --> 00:49:06,720
Speaker 1: Going to do that performance. Like it was never coming

916
00:49:06,719 --> 00:49:11,400
Speaker 1: from a place of actual, like well meaning desire to help.

917
00:49:11,840 --> 00:49:13,520
Speaker 1: Oh I know it wasn't because they had to be

918
00:49:13,560 --> 00:49:16,960
Speaker 1: cajoled into it. So this can't be real if if

919
00:49:17,040 --> 00:49:18,960
Speaker 1: you it only happens because you were cajoled.

920
00:49:19,280 --> 00:49:23,040
Speaker 2: I just imagine being like I'm gonna build a h

921
00:49:23,840 --> 00:49:28,520
Speaker 2: platform that's for professionals to discuss their professional work and

922
00:49:28,600 --> 00:49:31,759
Speaker 2: I don't care like if people dead name each other,

923
00:49:31,760 --> 00:49:35,000
Speaker 2: Like I hope there's more dead naming on this platform. Yeah, why,

924
00:49:35,280 --> 00:49:38,640
Speaker 2: Like it's it's a professional platform. It makes no sense.

925
00:49:38,920 --> 00:49:40,640
Speaker 1: No, I'm with you, and even the way that they

926
00:49:41,000 --> 00:49:44,080
Speaker 1: dealt with it is really wild. So the Advocate reported

927
00:49:44,120 --> 00:49:46,279
Speaker 1: on this and they got a statement from LinkedIn where

928
00:49:46,280 --> 00:49:50,240
Speaker 1: a spokesperson initially defended the platform stance against identity base abuse,

929
00:49:50,480 --> 00:49:54,759
Speaker 1: asserting quote, we regularly update our policies. Personal tax intimidation

930
00:49:54,920 --> 00:49:58,400
Speaker 1: or hate speech towards anyone based on their identity, including misgendering,

931
00:49:58,719 --> 00:50:00,680
Speaker 1: violates our harassment policy. See it is not a lot

932
00:50:00,760 --> 00:50:04,000
Speaker 1: on our platform. Then less than an hour later, the

933
00:50:04,040 --> 00:50:07,120
Speaker 1: company wrote back to the Advocate and asked to revise

934
00:50:07,160 --> 00:50:11,400
Speaker 1: that statement, removing the phrase hate speech and instead mirroring

935
00:50:11,440 --> 00:50:15,000
Speaker 1: the new policy language saying personal texts or intimidation towards

936
00:50:15,000 --> 00:50:18,239
Speaker 1: anyone based on their identity, including miss gendering, violates our

937
00:50:18,239 --> 00:50:20,600
Speaker 1: harassment policy and it's not allowed on their platform. So

938
00:50:20,640 --> 00:50:23,719
Speaker 1: it's like they can't even keep their own whack policy

939
00:50:23,840 --> 00:50:24,800
Speaker 1: straight internally.

940
00:50:25,280 --> 00:50:27,239
Speaker 2: Well, also, at a certain point, like these words become

941
00:50:27,280 --> 00:50:30,160
Speaker 2: meaningless because like how is that different than hate speech?

942
00:50:30,320 --> 00:50:33,440
Speaker 2: And then also you think about like the fact that,

943
00:50:33,520 --> 00:50:36,279
Speaker 2: like you know, dozens of people were involved in that

944
00:50:36,360 --> 00:50:39,200
Speaker 2: discussion and there's a whole email thread about like is

945
00:50:39,280 --> 00:50:42,680
Speaker 2: hate speech allowed but like discrimination isn't, and.

946
00:50:42,600 --> 00:50:44,759
Speaker 1: Like like what are we doing? Like this?

947
00:50:46,080 --> 00:50:50,600
Speaker 2: It's it's kind of mind boggling and like hard to process,

948
00:50:50,640 --> 00:50:53,239
Speaker 2: but like there are so many people involved, and like

949
00:50:53,320 --> 00:50:56,960
Speaker 2: having those conversations of like are we is hate speech

950
00:50:57,040 --> 00:50:59,640
Speaker 2: not a word that we're not a phrase that we're

951
00:50:59,640 --> 00:51:01,880
Speaker 2: going to be using in our policy anymore?

952
00:51:01,880 --> 00:51:06,040
Speaker 1: And it's just like what is this? What are we doing?

953
00:51:06,360 --> 00:51:10,200
Speaker 1: Why can we have like a group meeting and maybe

954
00:51:10,200 --> 00:51:12,560
Speaker 1: like revise our goals as a species, because like what

955
00:51:12,600 --> 00:51:14,839
Speaker 1: are we? Truly? What are we doing? I think this

956
00:51:15,200 --> 00:51:18,279
Speaker 1: all the time. My last thing I want to talk

957
00:51:18,280 --> 00:51:20,399
Speaker 1: about is an update on a story that we did

958
00:51:20,520 --> 00:51:23,640
Speaker 1: earlier this week, and that is about the tea app.

959
00:51:23,800 --> 00:51:27,200
Speaker 1: Certainly you have heard about this, right, oh, I'm I

960
00:51:27,280 --> 00:51:30,640
Speaker 1: have heard a lot, Yes, I'm very It's very interesting.

961
00:51:30,719 --> 00:51:32,840
Speaker 1: So for folks that don't know, the tea app was

962
00:51:32,880 --> 00:51:36,280
Speaker 1: designed for women to spill tea on men. The creator

963
00:51:36,320 --> 00:51:38,000
Speaker 1: of this app because it was designed to help women

964
00:51:38,080 --> 00:51:40,320
Speaker 1: feel more safe while dating men, so that they could

965
00:51:41,239 --> 00:51:44,400
Speaker 1: share Women could share their experiences with specific men. I

966
00:51:44,400 --> 00:51:46,600
Speaker 1: guess the idea being that if a man was abusive

967
00:51:46,840 --> 00:51:49,400
Speaker 1: or you know, they had a bad experience with a

968
00:51:49,400 --> 00:51:52,560
Speaker 1: man they could they could safely and anonymously share that

969
00:51:52,840 --> 00:51:55,520
Speaker 1: what we know it was not anonymous. For a time,

970
00:51:55,640 --> 00:51:58,440
Speaker 1: that app required women to show there to give copies

971
00:51:58,480 --> 00:52:01,200
Speaker 1: of their driver's licenses to confirm they were women. The

972
00:52:01,239 --> 00:52:04,120
Speaker 1: app eventually scrapped that requirement, but did require women to

973
00:52:04,160 --> 00:52:09,120
Speaker 1: send selfies. Last week, one three hundred driver's license images

974
00:52:09,160 --> 00:52:12,440
Speaker 1: of those women, along with seventy two thousand sealthies of women,

975
00:52:12,800 --> 00:52:16,560
Speaker 1: were all found to be essentially publicly accessible thanks to

976
00:52:16,600 --> 00:52:20,600
Speaker 1: the app's atrocious security practices. So the app said, oh,

977
00:52:20,640 --> 00:52:23,040
Speaker 1: as soon as you submit your license or your selfie,

978
00:52:23,080 --> 00:52:25,719
Speaker 1: we deleted as soon as you're confirmed. Obviously that wasn't

979
00:52:25,719 --> 00:52:28,200
Speaker 1: the case because images of that stuff was all over

980
00:52:28,280 --> 00:52:31,640
Speaker 1: four chan. Additionally, private dms were also left accessible. So

981
00:52:31,680 --> 00:52:35,040
Speaker 1: folks want the deep dive into what happened there, check

982
00:52:35,040 --> 00:52:36,880
Speaker 1: out the episode that we put out about it this week.

983
00:52:37,239 --> 00:52:40,520
Speaker 1: But we have a slight update ooh okay, and that

984
00:52:40,640 --> 00:52:44,880
Speaker 1: is the app, probably unsurprisingly, has been hit with two lawsuits.

985
00:52:45,239 --> 00:52:47,880
Speaker 1: Two lawsuits have been filed in the Northern District of

986
00:52:47,880 --> 00:52:52,400
Speaker 1: California alleging negligence, breach of implied contract, and other claims.

987
00:52:52,640 --> 00:52:55,319
Speaker 1: So one was filed on behalf of Griselda Rays, who

988
00:52:55,360 --> 00:52:57,160
Speaker 1: said that she submitted a photo while signing up for

989
00:52:57,200 --> 00:52:59,560
Speaker 1: the app that was included in the breach. She seeks

990
00:52:59,600 --> 00:53:02,680
Speaker 1: it in junk, requiring Tea to encrypt all data and

991
00:53:02,719 --> 00:53:06,560
Speaker 1: purge private information as well as monetary damages as determined

992
00:53:06,600 --> 00:53:09,280
Speaker 1: by the court. I actually think she has that case.

993
00:53:09,360 --> 00:53:12,680
Speaker 1: Like I the app made it clear as day and

994
00:53:12,719 --> 00:53:15,040
Speaker 1: said we delete your images, and they did it like that.

995
00:53:15,200 --> 00:53:15,840
Speaker 1: They dislied.

996
00:53:16,040 --> 00:53:20,400
Speaker 2: That's wild. It's it's absolutely wild. How negligent that is.

997
00:53:20,719 --> 00:53:22,879
Speaker 1: Yeah, I mean, it almost wasn't fair to call it

998
00:53:23,760 --> 00:53:27,279
Speaker 1: a hack or or like even breach feels a little

999
00:53:27,320 --> 00:53:31,239
Speaker 1: bit strong because these things were essentially publicly accessible, so

1000
00:53:31,280 --> 00:53:33,880
Speaker 1: you can't like to hack information, to hack something, it

1001
00:53:33,880 --> 00:53:36,239
Speaker 1: has to be behind some sort of security protocol. This

1002
00:53:36,400 --> 00:53:38,799
Speaker 1: was not, so it's like you can't even a hack.

1003
00:53:40,120 --> 00:53:42,880
Speaker 1: It was the level to which I mean the analogy

1004
00:53:42,920 --> 00:53:45,759
Speaker 1: that that I spoke to a cybersecurity professional about it.

1005
00:53:45,840 --> 00:53:48,480
Speaker 1: The analogy that they gave me was imagine if your

1006
00:53:48,520 --> 00:53:51,560
Speaker 1: doctor told you that your private health information that they

1007
00:53:51,600 --> 00:53:54,520
Speaker 1: collected was private, but actually they stored it in an

1008
00:53:54,520 --> 00:53:58,360
Speaker 1: open crate in the alley behind the clinic. That is

1009
00:53:58,360 --> 00:54:02,759
Speaker 1: the level of except that this information was Oh.

1010
00:54:02,480 --> 00:54:05,279
Speaker 2: My god, wait, isn't that so the tea app it's

1011
00:54:05,320 --> 00:54:08,680
Speaker 2: all like for women. It's for women to discuss like

1012
00:54:08,800 --> 00:54:13,080
Speaker 2: men and ranging on, you know, their interactions with men.

1013
00:54:13,640 --> 00:54:16,279
Speaker 1: But wasn't it like found and created by a man? Yeah?

1014
00:54:16,360 --> 00:54:20,120
Speaker 1: The creator, businessman and tech capitalist Sean Cook, formerly of Shutterfly,

1015
00:54:20,280 --> 00:54:23,440
Speaker 1: said that he created this app because he like in

1016
00:54:23,480 --> 00:54:25,640
Speaker 1: their marketing. Honestly, it does just sound like marketing to me.

1017
00:54:26,040 --> 00:54:28,319
Speaker 1: In the marketing materials for the app, he said, Oh,

1018
00:54:28,360 --> 00:54:31,759
Speaker 1: I watched my mother date and get catfished and like

1019
00:54:31,760 --> 00:54:33,920
Speaker 1: get mixed up with men who had criminal records. So

1020
00:54:33,960 --> 00:54:36,480
Speaker 1: I wanted an app that would keep women safe and

1021
00:54:36,480 --> 00:54:39,879
Speaker 1: that women could like have safer dating experiences. That may

1022
00:54:40,160 --> 00:54:42,400
Speaker 1: very well be true, And I'm not deny that there

1023
00:54:42,400 --> 00:54:45,319
Speaker 1: are women who maybe use this app to vet a

1024
00:54:45,360 --> 00:54:48,960
Speaker 1: man or to find out information about somebody who genuinely

1025
00:54:49,120 --> 00:54:51,640
Speaker 1: was abusive. I'm not saying that that did not happen

1026
00:54:51,680 --> 00:54:54,160
Speaker 1: on this app. I am saying that when you actually

1027
00:54:54,160 --> 00:54:55,640
Speaker 1: look at the kind of stuff that was posted on

1028
00:54:55,680 --> 00:55:00,040
Speaker 1: the app, it was also women being like, you know this,

1029
00:55:00,000 --> 00:55:02,480
Speaker 1: this guy has a bad vibe or like like saying

1030
00:55:02,520 --> 00:55:05,319
Speaker 1: things that were not necessarily rooted in trying to keep

1031
00:55:05,360 --> 00:55:07,880
Speaker 1: women safe from abuse. And so I think it's interesting

1032
00:55:07,960 --> 00:55:11,919
Speaker 1: that this man who created this app for women got

1033
00:55:11,960 --> 00:55:14,600
Speaker 1: to enjoy talking about how they were all about women's

1034
00:55:14,600 --> 00:55:18,120
Speaker 1: safety while doing something that put those same women so

1035
00:55:18,560 --> 00:55:19,800
Speaker 1: clearly at risk.

1036
00:55:20,880 --> 00:55:25,360
Speaker 2: Yeah, no, it's it feels kind of poetic. It's also

1037
00:55:25,480 --> 00:55:29,240
Speaker 2: kind of what I've started to expect from men, especially

1038
00:55:29,320 --> 00:55:35,360
Speaker 2: when they like perform feminism, Like I have pretty like

1039
00:55:35,440 --> 00:55:39,160
Speaker 2: low expectations from them when they like make their whole

1040
00:55:39,960 --> 00:55:45,200
Speaker 2: persona about like protecting women, Like I just think that

1041
00:55:45,320 --> 00:55:48,960
Speaker 2: I need to see them go above and beyond and like, actually,

1042
00:55:49,880 --> 00:55:51,080
Speaker 2: you know, walk that walk.

1043
00:55:52,680 --> 00:55:55,799
Speaker 1: But yeah, the fact that it's like it was that

1044
00:55:56,040 --> 00:56:01,840
Speaker 1: careless and that that easily not even hacked, I guess

1045
00:56:01,960 --> 00:56:06,360
Speaker 1: stumbled upon und crazy and the women, some of the

1046
00:56:06,400 --> 00:56:09,120
Speaker 1: women they so that not only were these women's drivers'

1047
00:56:09,160 --> 00:56:13,240
Speaker 1: licenses which have their addresses on them, posted online, also

1048
00:56:14,120 --> 00:56:17,480
Speaker 1: some of these dms that were that became accessible were

1049
00:56:18,280 --> 00:56:21,759
Speaker 1: very serious in nature. The second lawsuit, which was brought

1050
00:56:21,800 --> 00:56:23,680
Speaker 1: on behalf of an anonymous Jane Doe, says that she

1051
00:56:23,840 --> 00:56:26,239
Speaker 1: joined the tea app because she wanted to anonymously warn

1052
00:56:26,360 --> 00:56:29,120
Speaker 1: other women in her northern California community about a man

1053
00:56:29,120 --> 00:56:32,000
Speaker 1: who sexually assaulted at least two other women. The app

1054
00:56:32,000 --> 00:56:34,840
Speaker 1: promised her that anonymity, and promised her safety, and promised

1055
00:56:34,840 --> 00:56:37,279
Speaker 1: to delete her verifrication data. Te broke every one of

1056
00:56:37,320 --> 00:56:41,040
Speaker 1: those promises. And so that law Shue really demonstrates, like

1057
00:56:41,719 --> 00:56:44,640
Speaker 1: fact that genuinely could put her at an unsafe situation

1058
00:56:44,719 --> 00:56:48,319
Speaker 1: if she is if she is reporting this person attacked me,

1059
00:56:48,560 --> 00:56:53,240
Speaker 1: harmed me. Having her her conversations about that be accessible

1060
00:56:53,280 --> 00:56:55,560
Speaker 1: to anybody who wants to see it is putting her

1061
00:56:55,920 --> 00:56:59,000
Speaker 1: deeply at risk. And so, yeah, this app, like I

1062
00:56:59,640 --> 00:57:01,720
Speaker 1: had a there were going to be lawsuits. I'm actually

1063
00:57:01,719 --> 00:57:04,359
Speaker 1: surprised it was this quick because this just happened last Yeah,

1064
00:57:04,360 --> 00:57:07,759
Speaker 1: but you know it really it really I think these

1065
00:57:07,760 --> 00:57:10,279
Speaker 1: women have a right to some justice here.

1066
00:57:11,080 --> 00:57:14,080
Speaker 2: Yeah, no, one hundred percent. I kind of am interested.

1067
00:57:14,320 --> 00:57:17,480
Speaker 2: I'm very interested to see how this unfolds. I think

1068
00:57:17,520 --> 00:57:20,480
Speaker 2: the whole conversation around it is fascinating. How did they

1069
00:57:20,680 --> 00:57:21,280
Speaker 2: make money?

1070
00:57:21,440 --> 00:57:24,440
Speaker 1: Oh so the app? You got up to five free

1071
00:57:24,480 --> 00:57:27,280
Speaker 1: searches on the app, So how it works. Let's say

1072
00:57:27,280 --> 00:57:28,880
Speaker 1: that I met Joe Blow on the street, and I

1073
00:57:28,920 --> 00:57:30,560
Speaker 1: want to see if anybody's talking about him. I could

1074
00:57:30,560 --> 00:57:32,880
Speaker 1: search him on the app to see, you know, if

1075
00:57:32,880 --> 00:57:37,120
Speaker 1: he appears in any te posts. After those five posts,

1076
00:57:37,680 --> 00:57:40,200
Speaker 1: you then have to buy a paid subscription, which is

1077
00:57:40,200 --> 00:57:43,160
Speaker 1: fifteen dollars a month, or you could share. You could

1078
00:57:43,440 --> 00:57:46,040
Speaker 1: have like five girlfriends sign up and keep using it

1079
00:57:46,080 --> 00:57:48,080
Speaker 1: for free. Okay, so it was gonna be paid, so

1080
00:57:48,080 --> 00:57:49,760
Speaker 1: they weren't doing giving it away for free. And then

1081
00:57:49,800 --> 00:57:54,480
Speaker 1: like selling data. I I mean that I am I'm

1082
00:57:54,480 --> 00:57:56,280
Speaker 1: not willing to say, I'm not able to say that.

1083
00:57:56,800 --> 00:57:59,520
Speaker 1: Would it surprised me? I don't know for sure, Okay,

1084
00:57:59,600 --> 00:58:00,280
Speaker 1: that makes sense.

1085
00:58:01,560 --> 00:58:05,760
Speaker 2: I just think everything about that app is completely fascinating

1086
00:58:05,840 --> 00:58:09,080
Speaker 2: to me, and like the fact that so many women

1087
00:58:09,600 --> 00:58:10,360
Speaker 2: flocked to it.

1088
00:58:10,280 --> 00:58:12,400
Speaker 1: As a place of safety and then more portrayed is interesting.

1089
00:58:12,440 --> 00:58:15,080
Speaker 2: But also like the discourse that was had there, and

1090
00:58:15,120 --> 00:58:19,200
Speaker 2: like what it means for privacy and safety today is interesting.

1091
00:58:19,240 --> 00:58:20,920
Speaker 2: And then the fact that like you know, all of

1092
00:58:20,920 --> 00:58:25,680
Speaker 2: a sudden, thousands and thousands of women are docked is

1093
00:58:26,360 --> 00:58:29,560
Speaker 2: like the fact that we live in that context too,

1094
00:58:29,640 --> 00:58:32,880
Speaker 2: where so suddenly you become essentially like a public figure.

1095
00:58:32,600 --> 00:58:33,840
Speaker 1: Who is getting harassed.

1096
00:58:33,960 --> 00:58:36,800
Speaker 2: Is like I mean, it's it's such a like a

1097
00:58:36,880 --> 00:58:41,400
Speaker 2: rich text for twenty twenty five Society and Technology.

1098
00:58:41,720 --> 00:58:44,400
Speaker 1: I talked about this in the episode, but genuinely, when

1099
00:58:44,440 --> 00:58:46,440
Speaker 1: I first heard about this, I thought, this has to

1100
00:58:46,480 --> 00:58:48,480
Speaker 1: be some kind of a setup. There's no million this

1101
00:58:48,880 --> 00:58:52,480
Speaker 1: I mean, but that was my initial gut feeling was

1102
00:58:52,960 --> 00:58:56,360
Speaker 1: it was such a kind of morality play in a

1103
00:58:56,440 --> 00:58:59,000
Speaker 1: kind of way where it just seemed so on the

1104
00:58:59,040 --> 00:59:02,200
Speaker 1: nose that I thought, this has to be this has

1105
00:59:02,320 --> 00:59:04,360
Speaker 1: there has to be more to this story. I'm I

1106
00:59:04,360 --> 00:59:06,000
Speaker 1: don't know that to be true, but that was my

1107
00:59:06,080 --> 00:59:10,480
Speaker 1: initial just it just felt too just too much of

1108
00:59:10,520 --> 00:59:13,080
Speaker 1: an on the nose gender war story to have to

1109
00:59:13,160 --> 00:59:15,880
Speaker 1: have actually happened the way that it seemed to have happened.

1110
00:59:16,400 --> 00:59:19,440
Speaker 2: Also, there's something to be said to culturally about the

1111
00:59:19,480 --> 00:59:23,040
Speaker 2: way like women engage in sleuthing as a means of

1112
00:59:23,080 --> 00:59:28,400
Speaker 2: like self defense and not almost it almost felt like

1113
00:59:28,440 --> 00:59:33,480
Speaker 2: that on steroids of just like let spring sleuthing into

1114
00:59:33,640 --> 00:59:36,120
Speaker 2: like let's like give it a whole structure, let's give

1115
00:59:36,120 --> 00:59:39,320
Speaker 2: it a system when it's already something that like so

1116
00:59:39,480 --> 00:59:42,959
Speaker 2: many women do in the name of, like I think,

1117
00:59:43,080 --> 00:59:45,520
Speaker 2: really an anxiety and trying to protect themselves.

1118
00:59:45,560 --> 00:59:50,960
Speaker 1: Oh yeah, I think that sleuthing and gossip and whisper networks,

1119
00:59:51,040 --> 00:59:52,960
Speaker 1: I don't want to stigmatize those things, I think. I

1120
00:59:52,960 --> 00:59:55,960
Speaker 1: think those things exist for a reason and they have

1121
00:59:56,160 --> 01:00:00,000
Speaker 1: forever because it's about those are how women keep our

1122
01:00:00,120 --> 01:00:02,600
Speaker 1: self safe. I don't think that there's anything wrong with

1123
01:00:02,720 --> 01:00:05,440
Speaker 1: women sharing information with each other. I think the problem

1124
01:00:05,480 --> 01:00:08,560
Speaker 1: is when this app promises to systematize that in a

1125
01:00:08,600 --> 01:00:14,120
Speaker 1: way that is safe and anonymous, and so cruelly betrays

1126
01:00:14,280 --> 01:00:16,840
Speaker 1: the women who flocked to it thinking that it would

1127
01:00:16,840 --> 01:00:17,880
Speaker 1: be safe and anonymous.

1128
01:00:18,040 --> 01:00:21,400
Speaker 2: Yeah, it's like if a whisper network has that much

1129
01:00:21,480 --> 01:00:25,160
Speaker 2: official structure, Like, at what point is it no longer

1130
01:00:25,480 --> 01:00:31,680
Speaker 2: a whisper network exactly exactly.

1131
01:00:30,320 --> 01:00:31,000
Speaker 1: Like I'm not sure.

1132
01:00:31,160 --> 01:00:33,800
Speaker 2: I am pro whisper network, and I am a huge

1133
01:00:33,840 --> 01:00:37,760
Speaker 2: proponent of gossiping. I think that it is like an

1134
01:00:37,840 --> 01:00:41,000
Speaker 2: evolutionary tactic. I think gossiping is like one of the

1135
01:00:41,040 --> 01:00:42,280
Speaker 2: best things we've ever developed.

1136
01:00:42,320 --> 01:00:43,440
Speaker 1: I love it. Uh.

1137
01:00:43,800 --> 01:00:47,280
Speaker 2: But also if you're gossiping, like with you know, one

1138
01:00:47,320 --> 01:00:51,400
Speaker 2: hundred thousand people, Like is that is that still gossiping?

1139
01:00:51,480 --> 01:00:54,960
Speaker 2: Like is that still protection? Or like I don't know,

1140
01:00:55,040 --> 01:00:58,800
Speaker 2: I I I find it really interesting.

1141
01:00:59,200 --> 01:01:02,400
Speaker 1: Same and you know, one of the reasons why I

1142
01:01:02,440 --> 01:01:06,240
Speaker 1: found the t app breach so concerning was that so

1143
01:01:06,360 --> 01:01:09,560
Speaker 1: much of the Internet is being restricted by age and

1144
01:01:09,680 --> 01:01:13,360
Speaker 1: like age verification sometimes requires a copy of your government ID,

1145
01:01:13,880 --> 01:01:16,560
Speaker 1: and so we already know that platforms that do this

1146
01:01:16,800 --> 01:01:20,400
Speaker 1: have been compromised before. So the version, so a version

1147
01:01:20,440 --> 01:01:22,000
Speaker 1: of what happened to the women with the t APP

1148
01:01:22,560 --> 01:01:25,640
Speaker 1: could happen conceivably when all of us are submitting our

1149
01:01:25,640 --> 01:01:28,400
Speaker 1: IDs to verify that we're old enough to access certain

1150
01:01:28,480 --> 01:01:31,680
Speaker 1: pockets of the Internet. And it's already happening in some

1151
01:01:31,760 --> 01:01:34,720
Speaker 1: places like the UK. So on Wednesday, Spotify said that

1152
01:01:34,760 --> 01:01:36,280
Speaker 1: they were going to be rolling out the use of

1153
01:01:36,480 --> 01:01:39,160
Speaker 1: yod which is a smartphone app that uses face scanning

1154
01:01:39,200 --> 01:01:41,720
Speaker 1: to estimate a person's age. If you appeared to be

1155
01:01:41,880 --> 01:01:44,800
Speaker 1: under age, then you need to submit your government ID

1156
01:01:45,080 --> 01:01:48,600
Speaker 1: in order to not be age restricted on Spotify and

1157
01:01:48,920 --> 01:01:51,400
Speaker 1: also YouTube announced this week that it was rolling out

1158
01:01:51,400 --> 01:01:56,040
Speaker 1: technology that was going to use AI to quote interpret

1159
01:01:56,120 --> 01:01:59,680
Speaker 1: a variety of signals based on the kinds of videos

1160
01:01:59,680 --> 01:02:02,240
Speaker 1: that so one sorches for and watches and the longevity

1161
01:02:02,280 --> 01:02:04,520
Speaker 1: of their account to determine if they are under eighteen,

1162
01:02:04,600 --> 01:02:08,480
Speaker 1: So if their AI senses that you're because of your

1163
01:02:08,520 --> 01:02:10,960
Speaker 1: viewing habits that you might be under eighteen. You will

1164
01:02:10,960 --> 01:02:14,240
Speaker 1: then have to submit your government ID to bypass automatic

1165
01:02:14,280 --> 01:02:16,760
Speaker 1: age restrictions. And so the fact that this is becoming

1166
01:02:16,800 --> 01:02:20,240
Speaker 1: more commonplace really concerns me. Yeah, that's gonna be a

1167
01:02:20,280 --> 01:02:20,760
Speaker 1: problem for me.

1168
01:02:20,800 --> 01:02:24,640
Speaker 2: On YouTube, I've been watching so many clips from zombies

1169
01:02:24,880 --> 01:02:29,440
Speaker 2: for They're gonna be like, why is this child also

1170
01:02:29,520 --> 01:02:31,440
Speaker 2: watching so many the ussays?

1171
01:02:32,080 --> 01:02:32,360
Speaker 3: I think.

1172
01:02:32,720 --> 01:02:36,360
Speaker 1: I think about my my sister in law, who when

1173
01:02:36,400 --> 01:02:38,520
Speaker 1: I look on her YouTube it's one hundred percent blue,

1174
01:02:38,600 --> 01:02:41,080
Speaker 1: it's one hundred percent because they've got toddlers. Yeah, or

1175
01:02:41,200 --> 01:02:42,720
Speaker 1: you know, she's got great taste.

1176
01:02:42,600 --> 01:02:42,680
Speaker 3: Ye.

1177
01:02:44,760 --> 01:02:47,200
Speaker 1: Blue is a fantastic show and I am going to

1178
01:02:47,480 --> 01:02:51,800
Speaker 1: stand ten toes down on Blue. Yeah we're not no,

1179
01:02:51,800 --> 01:02:55,320
Speaker 1: no shame for liking Blue here. But all this age

1180
01:02:55,400 --> 01:02:58,600
Speaker 1: verification stuff, it's often janky and doesn't work, and there's

1181
01:02:58,600 --> 01:03:00,560
Speaker 1: been lots of studies about like being kind of hit

1182
01:03:00,680 --> 01:03:03,720
Speaker 1: or miss. And I think as we sort of move

1183
01:03:03,760 --> 01:03:05,920
Speaker 1: to a place where more and where the Internet is

1184
01:03:06,320 --> 01:03:08,800
Speaker 1: age restricted and we have we might have to show

1185
01:03:08,800 --> 01:03:11,360
Speaker 1: our government IDs to get it. You know. I think

1186
01:03:11,360 --> 01:03:16,200
Speaker 1: the t APP breach really shows how problematic and concerning

1187
01:03:16,240 --> 01:03:17,840
Speaker 1: that can be because we really don't know that much

1188
01:03:17,840 --> 01:03:20,720
Speaker 1: about these platforms, and like any company can say, oh week,

1189
01:03:20,760 --> 01:03:22,960
Speaker 1: we're going to delete your driver's license picture as soon

1190
01:03:22,960 --> 01:03:25,040
Speaker 1: as you submit it, they don't have to necessarily do that.

1191
01:03:25,240 --> 01:03:28,880
Speaker 2: It's also interesting that, like, truly, the thing that drives

1192
01:03:28,920 --> 01:03:33,440
Speaker 2: all of this is porn. Like it's really interesting to

1193
01:03:33,440 --> 01:03:35,000
Speaker 2: me because it's like, you know, both of us have

1194
01:03:35,080 --> 01:03:38,760
Speaker 2: been deep in this world of like content moderation and

1195
01:03:38,800 --> 01:03:41,640
Speaker 2: people who make anonymous accounts and can get away with

1196
01:03:41,680 --> 01:03:45,600
Speaker 2: posting the most horrendous things and there's no verification, Like

1197
01:03:45,920 --> 01:03:48,720
Speaker 2: you know, part of the reason why you're able to

1198
01:03:48,760 --> 01:03:52,080
Speaker 2: go online and create a hate account and just troll

1199
01:03:52,160 --> 01:03:54,959
Speaker 2: people and make everybody's lives worse is because like you're

1200
01:03:55,000 --> 01:03:58,600
Speaker 2: making that count completely unconnected to a government id right

1201
01:03:58,680 --> 01:04:02,800
Speaker 2: like they like there's that's part of how the Internet

1202
01:04:03,440 --> 01:04:06,840
Speaker 2: has always worked and part of what's made our lives

1203
01:04:06,840 --> 01:04:08,560
Speaker 2: in particular very difficult.

1204
01:04:09,400 --> 01:04:11,760
Speaker 1: But the thing that is.

1205
01:04:11,760 --> 01:04:15,520
Speaker 2: Driving this, it's always porn. It's always porn in sex

1206
01:04:15,640 --> 01:04:18,840
Speaker 2: and like a panic around it rather than like actual

1207
01:04:18,960 --> 01:04:23,800
Speaker 2: like well being conversations. I think it's really interesting.

1208
01:04:23,920 --> 01:04:26,720
Speaker 1: And let's be real, if we actually wanted to keep

1209
01:04:26,840 --> 01:04:28,960
Speaker 1: young people safe and keep them away from things that

1210
01:04:29,160 --> 01:04:32,280
Speaker 1: are harmful. There are a million things we could be

1211
01:04:32,360 --> 01:04:36,320
Speaker 1: doing other than restricting the internet so heavily in the

1212
01:04:36,440 --> 01:04:39,160
Speaker 1: name of keeping children safer. Like, it's interesting to me

1213
01:04:39,840 --> 01:04:42,720
Speaker 1: when we do and when we don't appear to care

1214
01:04:42,840 --> 01:04:45,800
Speaker 1: about the well being of children and keeping them safe.

1215
01:04:45,960 --> 01:04:49,240
Speaker 1: I argue that we are a deeply anti child society,

1216
01:04:49,240 --> 01:04:51,240
Speaker 1: that we don't care about children, We don't care about

1217
01:04:51,280 --> 01:04:54,640
Speaker 1: their safety at all. But then, so what's interesting when

1218
01:04:55,000 --> 01:04:57,480
Speaker 1: we're being told we all have to start showing our

1219
01:04:57,520 --> 01:05:01,320
Speaker 1: IDs to listen to music on Spotify the children, it

1220
01:05:01,480 --> 01:05:05,880
Speaker 1: just immediate red flag, red flag, red flag, red yeah.

1221
01:05:06,320 --> 01:05:09,000
Speaker 2: Of like yeah, or like you know, the sex toy

1222
01:05:09,440 --> 01:05:12,720
Speaker 2: like legislation in Texas of like trying to make sure

1223
01:05:12,760 --> 01:05:14,080
Speaker 2: that you have to if you want to buy a

1224
01:05:14,120 --> 01:05:17,680
Speaker 2: sex toy online, you need to show like a government

1225
01:05:17,720 --> 01:05:19,800
Speaker 2: ID to prove your age. And it's just like, first

1226
01:05:19,800 --> 01:05:25,760
Speaker 2: of all, which children are buying sex toys online? Find

1227
01:05:26,000 --> 01:05:26,760
Speaker 2: me one.

1228
01:05:28,480 --> 01:05:28,760
Speaker 1: Second?

1229
01:05:28,800 --> 01:05:29,160
Speaker 3: Of all?

1230
01:05:29,400 --> 01:05:31,760
Speaker 2: I just I mean, maybe this is a hot I

1231
01:05:31,880 --> 01:05:34,000
Speaker 2: just I don't really care about a kid having a

1232
01:05:34,000 --> 01:05:36,720
Speaker 2: sex toy. If a kid wants to have a sex toy,

1233
01:05:36,720 --> 01:05:39,520
Speaker 2: and do whatever, like they're they're gonna use something to

1234
01:05:39,560 --> 01:05:40,800
Speaker 2: masturbate their children.

1235
01:05:41,240 --> 01:05:44,200
Speaker 1: Well, yeah, I mean that's some So in Australia, they

1236
01:05:44,200 --> 01:05:47,640
Speaker 1: had done this whole study on what on like her

1237
01:05:48,200 --> 01:05:50,000
Speaker 1: respecting the Internet and harm against kids, and one of

1238
01:05:50,000 --> 01:05:52,000
Speaker 1: the things they found was that when you try to

1239
01:05:52,120 --> 01:05:56,520
Speaker 1: keep like sexual content and sexual things away from kids,

1240
01:05:56,960 --> 01:05:59,000
Speaker 1: a lot of times those kids are actually using it

1241
01:05:59,040 --> 01:06:03,280
Speaker 1: for content that they're trying to learn about their bodies

1242
01:06:03,320 --> 01:06:05,919
Speaker 1: and their sexuality and all of that. And so by

1243
01:06:06,280 --> 01:06:09,760
Speaker 1: trying to legislate that kind of stuff away from them,

1244
01:06:09,800 --> 01:06:12,080
Speaker 1: you might actually be harming them because you're creating an

1245
01:06:12,160 --> 01:06:14,120
Speaker 1: environment where it's harder for them to get that education

1246
01:06:14,160 --> 01:06:16,840
Speaker 1: and they will seek it elsewhere. Yes, which I thought

1247
01:06:16,920 --> 01:06:21,080
Speaker 1: was such an interesting perspective and sort of how the

1248
01:06:21,120 --> 01:06:25,080
Speaker 1: way that we've restrict things sometimes actually end up introducing

1249
01:06:25,160 --> 01:06:25,760
Speaker 1: new harms.

1250
01:06:26,000 --> 01:06:28,640
Speaker 2: Yeah, because well, I mean we're doing this and simultaneously

1251
01:06:29,000 --> 01:06:32,040
Speaker 2: not providing sex ed right. Like part of the reason

1252
01:06:32,040 --> 01:06:34,880
Speaker 2: why I think young people might flock to porn is

1253
01:06:34,880 --> 01:06:38,520
Speaker 2: because they're not having those conversations like at home or

1254
01:06:38,560 --> 01:06:42,720
Speaker 2: in school. They don't understand like how sex works, and

1255
01:06:42,920 --> 01:06:46,160
Speaker 2: like they can't make sense of like the feelings that

1256
01:06:46,160 --> 01:06:48,840
Speaker 2: they're experiencing in their body, and they don't have access

1257
01:06:48,880 --> 01:06:51,560
Speaker 2: to that information, so of course they're going to like

1258
01:06:51,680 --> 01:06:53,800
Speaker 2: gravitate towards porn, and then porn is going to like

1259
01:06:53,840 --> 01:06:56,360
Speaker 2: pull you deeper into some sort of Internet rabbit hole

1260
01:06:56,360 --> 01:06:59,360
Speaker 2: because it's like an algorithmically kind of like send you somewhere,

1261
01:07:00,520 --> 01:07:04,560
Speaker 2: but it seems like the real Like if we cared

1262
01:07:04,600 --> 01:07:07,840
Speaker 2: about kids and taking care of them and respected them

1263
01:07:07,960 --> 01:07:12,240
Speaker 2: as like coming into their own sexuality before the age

1264
01:07:12,280 --> 01:07:15,160
Speaker 2: of eighteen, which they are, like they're going through puberty,

1265
01:07:15,520 --> 01:07:18,080
Speaker 2: Like we would make sure to have like resources for

1266
01:07:18,160 --> 01:07:20,919
Speaker 2: them and like teach them about the things that they're experiencing.

1267
01:07:21,080 --> 01:07:22,880
Speaker 2: But instead we're so much more interested like we did

1268
01:07:22,960 --> 01:07:25,080
Speaker 2: just makes us uncomfortable, so we just shut it down.

1269
01:07:25,360 --> 01:07:27,400
Speaker 2: And she'd be like no, we no, like no sex

1270
01:07:27,440 --> 01:07:29,560
Speaker 2: for them, nothing sexual.

1271
01:07:30,000 --> 01:07:33,360
Speaker 1: Yes, nothing sexual for them. And also show your ID

1272
01:07:33,560 --> 01:07:36,240
Speaker 1: when you want to watch something other than bluey I'm huge.

1273
01:07:36,640 --> 01:07:39,600
Speaker 2: But also the second you turn eighteen, you can be

1274
01:07:39,760 --> 01:07:43,480
Speaker 2: in that porn like yes of the day, yeah, the day.

1275
01:07:43,320 --> 01:07:48,640
Speaker 1: You're eighteen, go wild, Abby. It's always such a pleasure

1276
01:07:48,720 --> 01:07:51,400
Speaker 1: talking to you. You bring such a light to these

1277
01:07:51,520 --> 01:07:55,280
Speaker 1: sometimes tough topics. Where can people what are you up to?

1278
01:07:55,520 --> 01:07:57,920
Speaker 1: Where can people keep up with what you're up to?

1279
01:07:58,320 --> 01:08:00,400
Speaker 1: Tell us all the things? What am I too?

1280
01:08:01,360 --> 01:08:05,320
Speaker 2: I'm just back from vacation and like reassessing some kind

1281
01:08:05,320 --> 01:08:07,959
Speaker 2: of bigger projects that I want to do some deep

1282
01:08:08,000 --> 01:08:11,520
Speaker 2: dives in. So we're gonna see where those take me.

1283
01:08:12,360 --> 01:08:14,400
Speaker 2: What I've been up to for the last few months

1284
01:08:14,520 --> 01:08:17,559
Speaker 2: is a big like fascist propaganda series, so doing a

1285
01:08:17,560 --> 01:08:20,240
Speaker 2: lot of breakdowns on different types of fascist propaganda and

1286
01:08:20,320 --> 01:08:23,200
Speaker 2: like how they work and the themes that they typically

1287
01:08:23,520 --> 01:08:28,160
Speaker 2: cover and like use to manipulate people into buying into.

1288
01:08:28,040 --> 01:08:31,920
Speaker 1: The fascist cause. And you can find that work on

1289
01:08:31,960 --> 01:08:36,360
Speaker 1: my TikTok at topology or Instagram or Abby s R.

1290
01:08:37,360 --> 01:08:39,719
Speaker 1: I'm also on YouTube, which I think it's just Abby

1291
01:08:39,800 --> 01:08:43,439
Speaker 1: Richard's uh and you can read my written stuff at

1292
01:08:43,479 --> 01:08:47,240
Speaker 1: medium Matters. Abby is one of my favorite follows on TikTok.

1293
01:08:47,400 --> 01:08:49,960
Speaker 1: It will it Will It Will It will turn your

1294
01:08:49,960 --> 01:08:52,760
Speaker 1: TikTok experience up a notch to follow Abby. Thank you,

1295
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Speaker 1: that's so kind. I love your TikTok videos. I like

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Speaker 1: to see you. I'm I'm from me. I've talked about this.

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Speaker 1: It's like it's like in bare. I am an audio

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Speaker 1: person because I like the idea of being a voice

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Speaker 1: in somebody's ears. And then when you get on video

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Speaker 1: you're like, oh, that's how I look.

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01:09:06,320 --> 01:09:10,360
Speaker 2: He's like, I'm trying, Well, you're a delightful voice in

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Speaker 2: my ears, and you look great on screen.

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Speaker 1: I'll take it. I'm trying to get like you. Oh

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Speaker 1: I want to be like you. I want to be

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Speaker 1: a voice in people's ears. I want to stay a

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Speaker 1: little podcast sounds fun. We got a freaky Friday where

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Speaker 1: I do the short form video content and you do

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Speaker 1: the long form podcast. That sounds so fun. Sign me up. Yeah.

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Speaker 1: Thank you all for listening and hanging out and unpacking

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Speaker 1: these stories. If you want to follow me, you can

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Speaker 1: follow me on Instagram at Bridget Brie and DC, on

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01:09:37,800 --> 01:09:40,320
Speaker 1: TikTok at Bridget Brie and DC, or on YouTube. There

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Speaker 1: are no girls on the internet. Leave us a comment.

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Speaker 1: If you're listening on Spotify, I hope you're over eighteen

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01:09:44,920 --> 01:09:53,840
Speaker 1: and I will talk to you soon. Got a story

1316
01:09:53,880 --> 01:09:55,760
Speaker 1: about an interesting thing in tech, or just want to

1317
01:09:55,760 --> 01:09:58,120
Speaker 1: say hi? You can be just said Hello at tengodi

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Speaker 1: dot com. You can also find transcripts with today's episode

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01:10:00,760 --> 01:10:02,960
Speaker 1: at Tengoiti dot com. There Are No Girls on the

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Speaker 1: Internet was created by me bridget Toad. It's a production

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Speaker 1: of iHeartRadio and Unbossed Creative. Jonathan Strickland is our executive producer.

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01:10:09,760 --> 01:10:13,000
Speaker 1: Tari Harrison is our producer and sound engineer. Michael Almado

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Speaker 1: is our contributing producer. I'm your host, bridget Tood. If

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Speaker 1: you want to help us grow, rate and review us

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01:10:18,360 --> 01:10:22,000
Speaker 1: on Apple Podcasts. For more podcasts from iHeartRadio, check out

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Speaker 1: the iHeartRadio app, Apple podcast or wherever you get your podcasts.