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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: There Are No Girls on the Internet. And this is

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Speaker 1: another installment of our weekly news bound up, where we

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Speaker 1: break down all the stories you might have missed on

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Speaker 1: the Internet so you don't have to. I feel like

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Speaker 1: we need to talk about the episode that we put

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Speaker 1: out earlier this week, in part about Taylor Swift her

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Speaker 1: new album called Life of the Showgirl. Mike, have you

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Speaker 1: listened to much Taylor Swift?

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Speaker 2: I have listened to Taylor Swift over the course of

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Speaker 2: my life. She's been putting out music for a long time.

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Speaker 2: I have not really listened to the new album, but

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Speaker 2: I've read about it. I have friends who are into it,

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Speaker 2: and they've talked about it. It's actually kind of surprising

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Speaker 2: to me how much I know about this new album

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Speaker 2: despite not having listened to it.

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Speaker 1: That's the thing about Taylor Swift. I feel like you

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Speaker 1: can go as deep as you want. But even if

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Speaker 1: you aren't somebody who is making it an effort to

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Speaker 1: listen to her music, just by osmosis, you still get

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Speaker 1: information about her, by being a consumer of social media,

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Speaker 1: by being in the world, you know a little bit

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Speaker 1: about Taylor Swift.

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Speaker 2: I feel yes, absolutely, So I was.

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Speaker 1: Really interested in this idea of whether or not Taylor

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Speaker 1: Swift was announcing a kind of conservative shrad wife pivot

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Speaker 1: with her new album.

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Speaker 3: Specifically, the claim was that she was.

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Speaker 1: Really using her album to kind of indoctrinate her largely

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Speaker 1: but not all, you know, white young female fan base

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Speaker 1: into trad wife thinking, thinking that traditional marriage with strict

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Speaker 1: gender roles and little to no autonomy was going to

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Speaker 1: be the answer for all of women's problems and lies.

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Speaker 1: So I called up my good friend Joe Piazza, who

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Speaker 1: essentially is a tradwife expert. She when you watch the

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Speaker 1: Today Show or Good Morning America and there's a story

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Speaker 1: about ballerina farms, she is usually the one who was

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Speaker 1: commenting on it, like that's how much of an expert

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Speaker 1: on tradweae Joe is. After Joe and I spoke, literally

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Speaker 1: the next day, Taylor Swift dropped a merch line and

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Speaker 1: the internet exploded about one particular item. So I'm going

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Speaker 1: to do my best to sort of summarize what the

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Speaker 1: online discourse was around Taylor Swift's merch launch and sort

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Speaker 1: of what it says about I don't know our internet

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Speaker 1: ecosystem and how we're all feeling.

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Speaker 3: I made this point in the episode.

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Speaker 1: I think that whenever Taylor Swift does something, says something,

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Speaker 1: the resulting conversation really says more about us and our

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Speaker 1: anxieties and what we're grappling with and what we care

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Speaker 1: about than it could ever say about Taylor Swift.

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Speaker 2: Absolutely, she's almost like larger than life figure in the

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Speaker 2: way that the media talk about her, people talk about her.

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Speaker 2: So she put out a merch line to support her album.

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Speaker 3: Yes, and even that I was surprised by.

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Speaker 1: Apparently this is a thing that she does where when

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Speaker 1: she has an album, she'll also have items people can buy,

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Speaker 1: Like she has a cardigan that that accompanied another album,

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Speaker 1: So that is a thing. And part of this merch

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Speaker 1: drop was a necklace that has eight lightning bolts around.

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Speaker 3: The chain and at the end of the chain is

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Speaker 3: a star.

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Speaker 1: Now because there are eight lightning bolts on this necklace

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Speaker 1: and the star, initially people misreported the star as having

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Speaker 1: eight points.

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Speaker 3: Eights.

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Speaker 1: Double eights specifically are associated with Nazis h is the

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Speaker 1: eighth letter of the alphabet, so it's meant to signify

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Speaker 1: hyle you can.

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Speaker 3: Figure out who.

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Speaker 1: So if you ever see somebody with an HH tattoo,

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Speaker 1: that is a pretty well known kind of Nazi reference.

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Speaker 1: I will never say that HH phrase has actually came

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Speaker 1: up in the episodes that we did about on the

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Speaker 1: new Kanye West song of the same name. I am

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Speaker 1: not a thirty year old Kansas young Republicans text messages,

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Speaker 1: so i just don't say stuff like that, and I'm

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Speaker 1: always worried that someone's gonna cut me saying that out

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Speaker 1: of context.

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Speaker 3: But you know, you will pick out what I'm putting down.

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Speaker 1: So people thought, oh, because of this double eight, this

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Speaker 1: had super Nazi vibes.

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Speaker 3: However, when you see.

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Speaker 1: Another angle of this necklace, the star actually has twelve points.

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Speaker 3: I will say.

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Speaker 1: Talking about the lightning bolts, they do kind of resemble

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Speaker 1: ss Nazi lightning bolts. They're sort of the fat, jagged

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Speaker 1: lightning bolts.

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Speaker 3: Do you know what I'm do You know what I'm saying.

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Speaker 2: Yeah, they're sort of like short and squat. There's like

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Speaker 2: a single zig. You know, some lightning bolts and other

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Speaker 2: context will have two of them and it'll be like

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Speaker 2: a longer, skinnier lightning bolt. But I think for typography

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Speaker 2: and small intricate objects, it's typical, more typical to use

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Speaker 2: these little squat ones, which do resemble the lightning bolts

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Speaker 2: that the SS used.

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Speaker 1: So if you've seen the logo for the rock band Kiss,

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Speaker 1: it's like the ESS's in their logo. And fun fact

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Speaker 1: about that Kiss actually had to change their logo in

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Speaker 1: Germany because Germany is understandably a little bit sensitive about

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Speaker 1: anything that could potentially be Nazi imagery.

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Speaker 3: So in order to avoid being.

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Speaker 1: In conflict with Section eighty six a of Straws Spagetspu,

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Speaker 1: which is a I'm sure badly pronounced version of the

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Speaker 1: German Criminal Code which declares that anybody who domestically distributes

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Speaker 1: or publicly uses Nazi symbols may result in a fine

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Speaker 1: or even imprisonment.

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Speaker 2: Yeah, and it's interesting that they changed it because the

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Speaker 2: band's leader, Gene Simmons, his mother is actually a Holocaust survivor.

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Speaker 3: Oh, I had no idea.

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Speaker 2: Yeah, he's Jewish. There's another Jewish member of the band,

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Speaker 2: So like, these guys were not Nazis, and from what

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Speaker 2: it seems, they just kind of stumbled into iconography that

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Speaker 2: through happenstance resembled the Nazi iconography, and so they had

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Speaker 2: to change it. And so, you know, it's interesting to

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Speaker 2: think about that historical precedent here.

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Speaker 1: So the online discourse was that Taylor Swift is selling

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Speaker 1: essentially not see symbols on this necklace. We even actually

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Speaker 1: got a comment on the episode from a listener on

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Speaker 1: the Spotify comments who To be clear, I appreciate that

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Speaker 1: this listener pointed this out. One of the early voices

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Speaker 1: calling out the similarity between what is seen on this

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Speaker 1: necklace and Nazi imagery was this person on TikTok who made.

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Speaker 3: A very viral video about it.

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Speaker 1: That video was since taken down, and the creator made

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Speaker 1: another video saying that the fact that that video was

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Speaker 1: taken down was personally problematic.

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Speaker 3: Because they had been counting on the money that would

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Speaker 3: have been.

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Speaker 1: Generated from that one viral Taylor Swift Nazi necklace video

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Speaker 1: to pay their rent. Now that that video has been

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Speaker 1: removed from TikTok, it is jeopardvising what they were anticipating

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Speaker 1: was going to be a viral monetary payout.

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Speaker 4: What do I do about this? This is probably one

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Speaker 4: of the more viral videos I've ever had, and the

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Speaker 4: Swifts keep getting it removed and I can't even appeal

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Speaker 4: it now because I already won the one repeal and

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Speaker 4: they just keep appeal and they keep mass reporting me, Like,

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Speaker 4: is there something that I can do? Does anybody know

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Speaker 4: anybody on like the TikTok tech support, because I'm legitimately

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Speaker 4: gonna cry. I thought that this was gonna help cover

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Speaker 4: my rent for a month and then I could catch

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Speaker 4: up on some bills. I'm kind of devastated because not

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Speaker 4: only this is this disqualified now, but I'm also getting

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Speaker 4: some of the most insane DMS and harassment that I've

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Speaker 4: gotten in a long time because how dare I point

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Speaker 4: out the similarities between a Nazi symbol and Taylor Swift's necklace?

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Speaker 4: So I'm like, like, I'm legitimately pissed off about this?

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Speaker 4: Is does anybody know if there's anything I can do?

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Speaker 4: I'm gonna reach out to TikTok support, But like, why

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Speaker 4: are y'all like this? Y'all don't want to think critically

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Speaker 4: so hard you will literally report the messenger over confronting

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Speaker 4: your fave for a necklace looking like a fucking Nazi symbol.

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Speaker 1: I will say that one of the pieces here that

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Speaker 1: people have really pointed to you is the fact that

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Speaker 1: Taylor Swift nor team have not put out any kind

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Speaker 1: of statement clearing this up, which, to be honest, is

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Speaker 1: kind of her thing. Old og listeners of mine might

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Speaker 1: recall back in around twenty sixteen, I actually did an

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Speaker 1: episode of Stuff Mom Ever told you back when I

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Speaker 1: was hosting the show with my friend Emily about how.

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Speaker 3: Taylor Swift had become.

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Speaker 1: I guess I would call it a non consensual spokeswoman

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Speaker 1: for literal Nazis who were dubbing her their quote aryan goddess.

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Speaker 1: There was a Facebook group called Taylor Swift for Fascist

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Speaker 1: Europe who praised Taylor Swift's Nordic blood and the fact

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Speaker 1: that she's quote not having gangbangs with colored gentlemen. Like

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Speaker 1: so much content on the Internet. It kind of walked

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Speaker 1: a line between is this serious, is this trolling or

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Speaker 1: is this genuinely someone expressing a literal opinion about Taylor

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Speaker 1: Swift or is it kind of both where maybe it

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Speaker 1: it exists as a kind of joke, but one that

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Speaker 1: is serious, but because of the weird, over the top

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Speaker 1: nature just gives a lot of plausible deniability.

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Speaker 3: It kind of existed along those those tension points.

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Speaker 2: Absolutely. I mean, we know that that phenomenon that you've

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Speaker 2: just described has really been used very successfully by the

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Speaker 2: far right to spread their ideas online like everything that's

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Speaker 2: just like a jokey meme, but actually it's not. But

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Speaker 2: you know, it makes it difficult to pin them down

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Speaker 2: on anything because there's always that plausible deniability.

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Speaker 1: And I think specifically with Taylor Swift because back in

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Speaker 1: twenty sixteen, she was someone who never talked about politics

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Speaker 1: really or social issues really. She was really someone who

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Speaker 1: was not vocal about those things. I think it allowed

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Speaker 1: people to project this very odious ideology onto her silence

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Speaker 1: in absence of her not really taking a lot of

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Speaker 1: vocal stances about politics. And in that episode that we

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Speaker 1: did from twenty sixteen, my beef with her was that

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Speaker 1: she never came out and just said, hey, I'm not

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Speaker 1: a Nazi.

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Speaker 3: Hey, I disavowed this as far as I know.

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Speaker 1: We'll put that episode in the show notes the folks

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Speaker 1: are interested with the disclaimer that I recorded almost ten

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Speaker 1: years ago, and I have, let's just say, grown as

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Speaker 1: a podcaster a lot since then, I hope, I think, So,

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Speaker 1: you know, take that for what it's worth.

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Speaker 2: You and Taylor Swift both, you know, you've both been

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Speaker 2: through a lot, You've evolved. But I remember that era

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Speaker 2: of hers when she was just like not saying anything

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Speaker 2: about it, and I remember like not liking her for it.

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Speaker 2: But I think since then she has, like she campaigned

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Speaker 2: for Harris right, Yeah, she definitely.

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Speaker 1: Has grown more comfortable expressing explicit political and social attitudes.

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Speaker 1: She actually credits Lena Dunham with that a little bit, saying, Oh,

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Speaker 1: my friendship with Lena Dunham is why I'm a vocal

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Speaker 1: feminist now, because before she was someone who would say, oh,

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Speaker 1: I'm not a feminist because I love men. So people

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Speaker 1: saying that the claims about this necklace being essentially Nazi imagery, oh,

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Speaker 1: like Taylor Swift's team should put out a statement about that.

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Speaker 1: I was not surprised that she did not put out

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Speaker 1: a statement around that. You know, she never vocally talked

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Speaker 1: about the fact that she was became this non consensual

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Speaker 1: poster child for you know, the Aryan goddess of all

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Speaker 1: these Nazis, So I wasn't really surprised that she didn't

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Speaker 1: really vocally get involved with the necklace then either, However,

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Speaker 1: the necklace was removed from her merch side, so that

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Speaker 1: is kind of what's going on with that, and I

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Speaker 1: wanted to talk about it because I do think it's

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Speaker 1: this tailor made thing for a certain kind of online discourse.

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Speaker 1: You know, as we said earlier, if someone is going

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Speaker 1: to use a coded message or a dog whistle, the

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Speaker 1: point of that kind of thing is that there's always

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Speaker 1: plausible deniability built into it. So let's say that someone

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Speaker 1: was a secret covert Nazi and they wanted to make

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Speaker 1: memorabilia to indoctrinate others or to wink wink message to

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Speaker 1: other Nazi types. They're going to do that in a

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Speaker 1: way that is coded, so that you can say, oh,

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Speaker 1: you're just being paranoid and seeing messages where there are none.

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Speaker 3: It's not that deep.

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Speaker 1: And I think that is why this is a topic

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Speaker 1: that is perfect for this kind of online heated discussion,

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Speaker 1: because nobody can really say for sure whether or not

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Speaker 1: this was just an unfortunate design choice or something more

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Speaker 1: deliberate and intentional.

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Speaker 3: And that is exactly the point.

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Speaker 2: I think that's a good point to make that you know,

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Speaker 2: looking at that necklace, it's impossible to say for sure,

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Speaker 2: like is this you know, was there a true like

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Speaker 2: Nazi intention behind it or or not? Like, unless you

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Speaker 2: can get into the mind of the person who designed

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Speaker 2: this necklace, that's not a question that can be definitively answered.

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Speaker 2: And so it just leaves this space and this ambiguity

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Speaker 2: for people to project things onto the conversation.

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Speaker 3: And not for nothing.

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Speaker 1: We're having this conversation against the backdrop where Politico reported

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Speaker 1: that the US Capitol police were called because a lawmaker,

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Speaker 1: Representative David Taylor of Republican out of Ohio, had an

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Speaker 1: American flag pinned up in his office that just has

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Speaker 1: a swastika in the middle of it. Fox News is

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Speaker 1: trying to say, oh, it's an optical illusion.

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Speaker 3: No it's not.

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Speaker 1: It's very you what you're this is not a situation

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Speaker 1: where it's wink wink, not nod. It's a swastika. Anybody

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Speaker 1: can look at that and say it's a swastika. There's no,

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Speaker 1: it's not even a dog whistle. And then another story

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Speaker 1: that I alluded to earlier, where a group of Kansas

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Speaker 1: young Republicans, their group text messages were leaked to Politico

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Speaker 1: and they say things like I love Hitler. They reference

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Speaker 1: gas Chambers. It's very, very explicit.

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Speaker 3: Then you have.

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Speaker 1: People like jd Vance really downplaying it and saying, oh,

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Speaker 1: these are these are just kids doing what kids do.

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Speaker 1: I think the word young in Young Republicans is really

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Speaker 1: doing a lot of heavy lifting there, because when you

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Speaker 1: look at the ages of the quote kids that jad

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Speaker 1: Vance was saying, oh, this is just kids using naughty language.

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Speaker 1: The youngest person in that group chat is William Hendrix,

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Speaker 1: who's twenty four. I've got a twenty four year old,

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Speaker 1: a twenty four year old, a twenty seven year old,

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Speaker 1: twenty seven year.

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Speaker 3: Old, a twenty eight year old, a thirty five year old.

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Speaker 1: One of the people who was in the group, chef

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Speaker 1: but didn't really talk a lot, is literally an official

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Speaker 1: within the Trump administration. I think that because people are

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Speaker 1: hearing quote young Republicans, they're imagining somebody who's eight, seventeen, eighteen,

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Speaker 1: nineteen years old. I'm sorry, if you are a thirty

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Speaker 1: five year old, you're not a child. You are a

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Speaker 1: fully grown adult. So jd Vance himself is forty one

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Speaker 1: years old. That means that he thinks that somebody who

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Speaker 1: is about five years younger than him is a kid.

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Speaker 3: What does he think who like, what does he think

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Speaker 3: he is? You know, it's it interesting to me.

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Speaker 1: Who gets to be a child a kid and oh

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Speaker 1: they're just kids playing around, And who is an adult

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Speaker 1: because in his mind, just five years ago he was

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Speaker 1: a kid himself, but now he's equipped to be the

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Speaker 1: vice president of the United States.

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Speaker 2: Yeah, it reminds me of the Access Hollywood tage with

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Speaker 2: Trump when that came out and he was like, oh,

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Speaker 2: I was just I was a young guy. He was

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Speaker 2: like in his fifties.

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Speaker 3: Like, these people.

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Speaker 2: Love to just avoid any accountability for the stuff that

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Speaker 2: they say. And I've also seen this narrative about that

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Speaker 2: group of quote young Republicans. There was like, well, that's

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Speaker 2: just how men talk when they're in private spaces, Like

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Speaker 2: get over it. And I just want to refute that

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Speaker 2: as strongly as possible. That is not true. That is

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Speaker 2: maybe how some men talk, but that is in no

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Speaker 2: way the case that like all guys are getting together

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Speaker 2: and like praising Hitler and saying racist stuff, Like I've

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Speaker 2: known a lot of guys in my life and none

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Speaker 2: of them would stand for that nonsense like that shit

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Speaker 2: is not allowed in like polite dude society. I hate

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Speaker 2: how Republicans have. Some Republicans have really like weaponized and

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Speaker 2: distorted masculinity as this almost uni dimensional thing, where like

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Speaker 2: the core values are cruelty and ignorance and like violence.

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Speaker 2: It's such a shallow view of masculinity that really is

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Speaker 2: a historical It diminishes a much richer understanding of what

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Speaker 2: it meant to be a man for like hundred thousands

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Speaker 2: of years, you know, like Marcus Aurelius two thousand years

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Speaker 2: ago was wrestling with his inner demons and trying to

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Speaker 2: be like a more compassionate person and a better leader,

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Speaker 2: Like you can be a man and be thoughtful and

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Speaker 2: like not cruel.

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Speaker 1: I don't think that's true for this administration. I think

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Speaker 1: that people like JD. Vance kind of distance themselves from

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Speaker 1: behavior like this because I'm sure that this is behavior

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Speaker 1: that is happening within the Oval Office and within the

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Speaker 1: White House. We know it is, and so I think

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Speaker 1: that he cannot explicitly disavow this or distance himself from this,

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Speaker 1: because this is him.

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Speaker 5: Let's take a quick break at our back.

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Speaker 1: We were talking about the online discourse surrounding Taylor Swift

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Speaker 1: necklace launch. So the reason I wanted to talk about

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Speaker 1: this is because I have spent a lot of time

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Speaker 1: in my career zeroing in on conversations online that are

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Speaker 1: being manipulated or hijacked in some way, And I want

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Speaker 1: to be crystal clear that I don't think that everybody

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Speaker 1: who is concerned about this Taylor Swift necklace, which I

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Speaker 1: think is at best an unfortunate design choice. I don't

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Speaker 1: think that everybody who is raising concern about this is

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Speaker 1: doing so in bad faith or bot or anything like that.

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Speaker 1: I think some of the people raising this, like the

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Speaker 1: listener who left us that comments on Spotify, are doing

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Speaker 1: so because they are genuinely and rightly concerned about indoctrination

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Speaker 1: to hateful ideologies. Right now, and obviously, against the backdrop

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Speaker 1: of all of this stuff, we obviously have very good

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Speaker 1: and absolute reason to be on high alert, like keep

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Speaker 1: your heads on a swivel if you know what I'm saying.

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Speaker 1: But I can also tell when a conversation is just

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Speaker 1: ripe for online manipulation. For instance, we just know that

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Speaker 1: so much of our discourse online is very effectively driven

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Speaker 1: by an authentic accounts or thoughts. There is really great evidence,

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Speaker 1: based on solid research that suggests that the whole cracker

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Speaker 1: Barrel discourse where Cracker Barrel changed their logo, and the

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Speaker 1: narrative around it was that, oh, they're try they're going woke.

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Speaker 1: There's woke happening inside of Cracker Barrel, that's why they

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Speaker 1: did a rebrand. And then the idea was that the

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Speaker 1: left was really angry about the Cracker Barrel logo, which don't.

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Speaker 1: I've never heard anybody on the left to say anything

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Speaker 1: about the Cracker Barrel logo.

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Speaker 2: Yeah, whoever cares about the Cracker Barrel logo, like, come on, nobody.

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Speaker 1: And that entire conversation was driven by inauthentic accounts aka bots,

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Speaker 1: And then the press picked it up and they ran

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Speaker 1: with this story that, oh, there's woke inside Cracker Barrel

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Speaker 1: and there's been outcry because they tried to change the

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Speaker 1: logo and now they're changing it back, which is a

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Speaker 1: win for the right, when in reality, nobody gave a

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Speaker 1: crap about that logo. The entire conversation and discourse was

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Speaker 1: driven by bots, and that's how effectively inauthentic expression and

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Speaker 1: discourse can hijack our media landscape. But this bucame a

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Speaker 1: a story in a news cycle that was completely fabricated

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Speaker 1: by inauthentic discourse online. I think the Sydney Sweeney Jeans

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Speaker 1: ad was another example. I can't say that that was

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Speaker 1: specifically driven by Box because I haven't seen any research

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Speaker 1: about it like I did for the Cracker baill one,

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Speaker 1: but I can tell you that it was being amplified

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Speaker 1: as if it was a massive controversy on the left.

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Speaker 3: When it simply was not.

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Speaker 1: Most people either didn't care, or if they were commenting

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Speaker 1: on it at all, it was just a passing commentary,

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Speaker 1: or they were commenting after the issue had already been

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Speaker 1: blown up and become a topic.

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Speaker 5: Right.

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Speaker 3: However, if you were going from mainstream media reporting around the.

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Speaker 1: Issue, you would have thought this was the biggest animating

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Speaker 1: issue on the left of all time, when it simply

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Speaker 1: was not.

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Speaker 3: And that is how effectively.

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Speaker 1: Our online media landscape can be hijacked and weaponized.

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Speaker 2: Absolutely, there's just so much evidence that that is happening.

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Speaker 2: That there are powerful, well moneyed, sophisticated, coordinated actors, some foreign,

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Speaker 2: some domestic, pushing narratives all the time like this is

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Speaker 2: happening all the time, It's happened today, and it really

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Speaker 2: does shape the discourse that is happening online. There was

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Speaker 2: that study a little while ago that looked that it

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Speaker 2: did like a network analysis of some of these stories,

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Speaker 2: and it really revealed how a pretty small number of

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Speaker 2: accounts were instrumental in spreading the story, and then a

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Speaker 2: whole huge number of identified bots around them would then

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Speaker 2: amplify that story. And I do think that this is

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Speaker 2: something that we don't talk about it nearly enough. People

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Speaker 2: do talk about it, but like it really shapes like

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Speaker 2: almost every story that we see on the Internet, and

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Speaker 2: I think it's super important to keep that in mind

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Speaker 2: when trying to consume information really about anything.

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Speaker 1: Yes, and I think that kind conversations about celebrity or

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Speaker 1: pop culture, people might be thinking, oh, well, why would

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Speaker 1: bad actors be invested in manipulating the online conversation about

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Speaker 1: a celebrity, But we saw it with Megan Markle. There's

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Speaker 1: great research indicating that bot networks were very heavily being

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Speaker 1: used to sway conversation about Megan Markle, the Amber heard

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Speaker 1: Johnny Depp trial. Bot networks were very effective at kind

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Speaker 1: of hijacking the discourse around that. And I think that

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Speaker 1: when you're talking about celebrity, you're not necessarily you don't

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Speaker 1: necessarily have your critical thinking hat on in the same way,

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Speaker 1: because your guard is down because you're talking about something

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Speaker 1: that we've associated with fluff and not really being that important.

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Speaker 1: And so you might say, well, I have a sense

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Speaker 1: that there might be bad actors invested in hijacking conversations

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Speaker 1: about Ukraine or Palestine, and so you might proceed with caution.

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Speaker 1: But I also think it behooves us to proceed with

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Speaker 1: that same caution even though we're talking about pop culture

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Speaker 1: stories and it's not all bots, it's also real humans

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Speaker 1: who are invested in getting lots of engagement and lots

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Speaker 1: of traction in making inflammatory claims because it enriches them. Again,

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Speaker 1: I want to be clear that I'm not saying that

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Speaker 1: everybody who raised this issue is doing that, because I

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Speaker 1: genuinely saw with my own eyes that there were people

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Speaker 1: who I think were invested in thoughtfully exploring what.

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Speaker 2: Was going on.

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Speaker 1: Was Taylor Swift against this backdrop of fascism that we

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Speaker 1: find ourselves in, and so I want to be super

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Speaker 1: clear that I'm not saying that anybody who raised this

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Speaker 1: topic is doing so in bad faith.

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Speaker 3: That said, I don't want to say too much, but

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Speaker 3: the one.

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Speaker 1: Of the loudest voices I saw in social media really

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Speaker 1: beating the drum about the Taylor Swift necklace thing. Is

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Speaker 1: someone that I know in my real life. I've known

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Speaker 1: for quite a long time. We've had many professional interactions,

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Speaker 1: and I know this person to be a someone who

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Speaker 1: will tell inflammatory, tall tales to enrich themselves on the internet.

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Speaker 1: I know that because I was adjacent to one such

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Speaker 1: incident involving this person. I can't really say too much,

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Speaker 1: but when I saw this person really being vocally involved

440
00:24:16,800 --> 00:24:19,439
Speaker 1: in the conversations about Taylor Swift, I thought, Oh, this

441
00:24:19,600 --> 00:24:22,840
Speaker 1: is right on brand, and so I share that to

442
00:24:22,960 --> 00:24:26,080
Speaker 1: say that, Yeah, just like that person who made that

443
00:24:26,240 --> 00:24:29,520
Speaker 1: video that we heard from chiming in on a story

444
00:24:29,560 --> 00:24:34,159
Speaker 1: about a celebrity as big as Taylor Swift, basically guarantees engagement,

445
00:24:34,240 --> 00:24:38,000
Speaker 1: basically guarantees ear holes and eyeballs, and so that is

446
00:24:38,040 --> 00:24:40,960
Speaker 1: why people do it, and I just I can tell

447
00:24:41,119 --> 00:24:44,720
Speaker 1: when a topic is just right for the manipulation. Taylor

448
00:24:44,800 --> 00:24:48,200
Speaker 1: Swift's fandom is large. It's not all, but it's heavily

449
00:24:48,400 --> 00:24:52,760
Speaker 1: white women. It's essentially a voting block. Taylor Swift herself

450
00:24:53,200 --> 00:24:56,199
Speaker 1: fits at all of these intersection points. She's a woman,

451
00:24:56,440 --> 00:24:59,959
Speaker 1: she's a billionaire, and so whenever anybody talks about her,

452
00:25:00,359 --> 00:25:02,200
Speaker 1: it is going to perform well, is going to get

453
00:25:02,200 --> 00:25:05,000
Speaker 1: lots of engagement, and that is just a recipe for

454
00:25:06,080 --> 00:25:10,800
Speaker 1: inauthentic and bad faith conversation. And so I just think generally,

455
00:25:10,920 --> 00:25:14,600
Speaker 1: especially in twenty twenty five, it behooves us all to

456
00:25:15,280 --> 00:25:17,960
Speaker 1: really be able lookout for that, really be aware when

457
00:25:18,000 --> 00:25:20,840
Speaker 1: you are engaging in a conversation that is right for

458
00:25:21,200 --> 00:25:22,360
Speaker 1: online manipulation.

459
00:25:22,560 --> 00:25:23,280
Speaker 3: Just in general.

460
00:25:23,680 --> 00:25:27,040
Speaker 1: You know, there are people that are thoughtfully and genuinely

461
00:25:27,320 --> 00:25:30,160
Speaker 1: raising concerns online right now, but there are also people

462
00:25:30,200 --> 00:25:35,040
Speaker 1: who just benefit materially from making inflammatory, emotionally charged content

463
00:25:35,400 --> 00:25:38,720
Speaker 1: about these hot button issues that are specifically meant to

464
00:25:38,920 --> 00:25:42,119
Speaker 1: stoke intra community division. If you listen to our episode

465
00:25:42,119 --> 00:25:45,000
Speaker 1: about End Father's Day, you know exactly what I'm talking about.

466
00:25:45,000 --> 00:25:49,840
Speaker 1: And so even beyond Taylor Swift specifically, now is really

467
00:25:49,840 --> 00:25:52,520
Speaker 1: an important time to know the difference and really be

468
00:25:52,600 --> 00:25:56,320
Speaker 1: flexing that discernment muscle when you are waiting through online discourse.

469
00:25:56,400 --> 00:25:58,400
Speaker 1: That is the only thing that will save us from

470
00:25:58,400 --> 00:26:04,679
Speaker 1: being constantly hostage to inauthentic or manipulative online conversation.

471
00:26:05,280 --> 00:26:10,119
Speaker 2: One thousand percent, Yes, and we should also keep it

472
00:26:10,600 --> 00:26:13,960
Speaker 2: in mind that that fact you just mentioned that the

473
00:26:14,000 --> 00:26:21,160
Speaker 2: most inflammatory, shocking, outrageous comments tends to get the most engagement,

474
00:26:22,200 --> 00:26:26,720
Speaker 2: that is not a immutable fact of nature. That is

475
00:26:26,720 --> 00:26:30,320
Speaker 2: the result of decisions that social media platforms have made

476
00:26:30,680 --> 00:26:34,080
Speaker 2: to enrich themselves so they can sell more ads. Right, Like,

477
00:26:34,320 --> 00:26:38,080
Speaker 2: they could tweak the algorithm to deep prioritize that content.

478
00:26:38,520 --> 00:26:42,439
Speaker 2: They could crack down on the bots that drive so

479
00:26:42,520 --> 00:26:45,359
Speaker 2: much engagement on their platform, that they don't want to

480
00:26:45,359 --> 00:26:48,000
Speaker 2: do that because they want to sell more ads, so

481
00:26:49,480 --> 00:26:50,800
Speaker 2: they're complicit in this.

482
00:26:51,440 --> 00:26:51,600
Speaker 3: Oh.

483
00:26:51,680 --> 00:26:54,520
Speaker 1: I firmly believe if X got rid of bots they

484
00:26:54,560 --> 00:26:56,919
Speaker 1: would have the company would fold like the House of

485
00:26:56,920 --> 00:27:00,720
Speaker 1: cards overnight. Right, So they are definitely incentive to not

486
00:27:01,240 --> 00:27:03,360
Speaker 1: deal with this as a problem and maybe not even

487
00:27:03,359 --> 00:27:04,199
Speaker 1: see it as a problem.

488
00:27:04,200 --> 00:27:06,480
Speaker 3: But I guess I'll just say I don't think that

489
00:27:06,520 --> 00:27:07,040
Speaker 3: we will.

490
00:27:06,880 --> 00:27:10,120
Speaker 1: Ever get free while we are so easily and effectively

491
00:27:10,320 --> 00:27:13,679
Speaker 1: held hostage by this kind of divisive and not to

492
00:27:13,720 --> 00:27:18,240
Speaker 1: mention exhausting discourse. We will until we figure out how

493
00:27:18,280 --> 00:27:20,280
Speaker 1: we can be stronger than this shit, we will never

494
00:27:20,280 --> 00:27:20,840
Speaker 1: get free.

495
00:27:21,040 --> 00:27:24,479
Speaker 2: Yeah, I think as individuals we have work to do,

496
00:27:24,680 --> 00:27:28,320
Speaker 2: but also as a society. We need to address this

497
00:27:28,359 --> 00:27:34,200
Speaker 2: as a systems issue, and the platforms really have responsibility

498
00:27:34,200 --> 00:27:38,160
Speaker 2: here that they are just completely abdicating, and so that

499
00:27:38,200 --> 00:27:39,000
Speaker 2: needs to change.

500
00:27:39,119 --> 00:27:40,920
Speaker 3: Anyway, let's talk about whether or not we're going to

501
00:27:41,000 --> 00:27:42,320
Speaker 3: be having sex with chatchypt.

502
00:27:42,880 --> 00:27:44,840
Speaker 2: Speaking of platforms.

503
00:27:46,200 --> 00:27:49,320
Speaker 1: So we did an episode all about how folks are

504
00:27:49,480 --> 00:27:53,480
Speaker 1: in love with chatcheept four and how they felt abandoned

505
00:27:53,520 --> 00:27:56,800
Speaker 1: when OpenAI rolled out chattypt five, which was less prone

506
00:27:56,840 --> 00:28:01,000
Speaker 1: to emotionally validating people, less prone to giving sort of

507
00:28:01,480 --> 00:28:05,960
Speaker 1: emotional and personal responses. When Sam Altman made that announcement,

508
00:28:06,040 --> 00:28:08,040
Speaker 1: I kind of called bs on the fact that he

509
00:28:08,119 --> 00:28:11,919
Speaker 1: was doing it to prevent people from forming mentally unhealthy

510
00:28:12,040 --> 00:28:14,520
Speaker 1: sexual or romantic fixations with chat shipt.

511
00:28:15,160 --> 00:28:17,280
Speaker 3: I kind of thought that he wanted to have it

512
00:28:17,359 --> 00:28:17,879
Speaker 3: both ways.

513
00:28:17,920 --> 00:28:21,679
Speaker 1: You wanted to say, oh, our platforms that were building,

514
00:28:21,720 --> 00:28:24,320
Speaker 1: you should think of them like Samantha from the movie Her.

515
00:28:24,560 --> 00:28:26,119
Speaker 1: The whole point of that movie is that people have

516
00:28:26,200 --> 00:28:29,280
Speaker 1: romantic and sexual connections with bots in that movie. So

517
00:28:29,600 --> 00:28:31,879
Speaker 1: I don't think you can reference that as a starting

518
00:28:31,920 --> 00:28:33,840
Speaker 1: point for the kind of technology you want to build

519
00:28:34,240 --> 00:28:36,800
Speaker 1: and then also say, oh, but we're very concerned about

520
00:28:36,800 --> 00:28:40,800
Speaker 1: people's mental health who get into inappropriate fixations or relationships

521
00:28:40,880 --> 00:28:42,480
Speaker 1: with our technology. I don't think it can be built,

522
00:28:42,520 --> 00:28:45,240
Speaker 1: So I early on was sort of like, sam Altman,

523
00:28:45,280 --> 00:28:48,400
Speaker 1: what are you talking about now? Just two months after

524
00:28:48,560 --> 00:28:50,480
Speaker 1: sam Altman was like, oh, we got to change chat

525
00:28:50,480 --> 00:28:52,560
Speaker 1: beachbt because people are falling in love with it and

526
00:28:52,600 --> 00:28:55,320
Speaker 1: having sex with it. Now he's like, go ahead and

527
00:28:55,360 --> 00:28:58,280
Speaker 1: have sex with chatchip bet it's fine now, because sam

528
00:28:58,320 --> 00:29:01,920
Speaker 1: Altman announced an open Eye will soon allow erotica for

529
00:29:02,080 --> 00:29:05,960
Speaker 1: chat GPT users who verify their age on the platform.

530
00:29:06,600 --> 00:29:08,920
Speaker 3: Here's what he said on x quote.

531
00:29:09,040 --> 00:29:11,640
Speaker 1: We made chat GPT pretty restrictive to make sure we

532
00:29:11,680 --> 00:29:14,400
Speaker 1: are being careful with mental health issues. We realized this

533
00:29:14,480 --> 00:29:17,360
Speaker 1: made it less useful and enjoyable to many members who

534
00:29:17,400 --> 00:29:20,240
Speaker 1: had no mental health problems, but given the seriousness of

535
00:29:20,280 --> 00:29:22,719
Speaker 1: the issue, we wanted to get this right. Now that

536
00:29:22,760 --> 00:29:25,040
Speaker 1: we have been able to mitigate the serious mental health

537
00:29:25,080 --> 00:29:27,520
Speaker 1: issues and have new tools, we are going to be

538
00:29:27,560 --> 00:29:30,200
Speaker 1: able to safely relax the restrictions in most cases.

539
00:29:30,440 --> 00:29:33,680
Speaker 3: In December, as we roll out age gating more fully.

540
00:29:33,600 --> 00:29:36,480
Speaker 1: And as part of our treat adult users Like adults principle,

541
00:29:36,720 --> 00:29:39,560
Speaker 1: we will allow even more like erotica.

542
00:29:38,920 --> 00:29:40,520
Speaker 3: For verified adults.

543
00:29:41,120 --> 00:29:44,240
Speaker 1: I gotta say this is not a move that inspires

544
00:29:44,360 --> 00:29:47,240
Speaker 1: confidence in me. Elon Musk is kind of doing a

545
00:29:47,240 --> 00:29:49,640
Speaker 1: similar thing right now. When he took over at Twitter.

546
00:29:49,720 --> 00:29:51,600
Speaker 1: One of the first things he said in order to

547
00:29:51,680 --> 00:29:53,479
Speaker 1: make more money for the company, he was like, Oh,

548
00:29:53,480 --> 00:29:56,920
Speaker 1: we're going to double down on adult content and erotic content.

549
00:29:57,480 --> 00:30:01,200
Speaker 1: He did that with his chatbot Rock, with some pretty

550
00:30:01,200 --> 00:30:05,280
Speaker 1: disastrous results. As a futurism reports, it's an interesting strategy

551
00:30:05,280 --> 00:30:08,040
Speaker 1: with some cause for alarm. Elon Musk's Rock is an

552
00:30:08,080 --> 00:30:10,880
Speaker 1: infamous example of what can happen when one opens up

553
00:30:10,960 --> 00:30:13,760
Speaker 1: the smut gates on AI, which quickly became a haven

554
00:30:13,800 --> 00:30:17,920
Speaker 1: for exploitation and inappropriate AI imagery of children. Elsewhere on

555
00:30:17,960 --> 00:30:20,520
Speaker 1: the Internet, lesser known AI systems have led to a

556
00:30:20,600 --> 00:30:23,560
Speaker 1: noxious outbreak of AI generated deep bakes that depict the

557
00:30:23,720 --> 00:30:26,840
Speaker 1: likeness of real people and explicit situations without their consent.

558
00:30:27,200 --> 00:30:30,880
Speaker 1: And it's also interesting to me because just two months

559
00:30:30,880 --> 00:30:34,840
Speaker 1: ago I saw an interview with Sam Altman and he

560
00:30:34,960 --> 00:30:37,960
Speaker 1: was essentially bragging about how the company they are not

561
00:30:38,120 --> 00:30:41,480
Speaker 1: making sex bots, and two months later, yet go ahead

562
00:30:41,480 --> 00:30:44,120
Speaker 1: and make the sex bots. I think it screams to

563
00:30:44,200 --> 00:30:47,200
Speaker 1: me that they're a company that is having some money concerns,

564
00:30:47,440 --> 00:30:49,520
Speaker 1: And I think it also just shows how far open

565
00:30:49,560 --> 00:30:52,680
Speaker 1: Ai has come from being this nonprofit with a mission

566
00:30:52,680 --> 00:30:55,040
Speaker 1: that was gonna, you know, be out to change the world,

567
00:30:55,080 --> 00:30:57,160
Speaker 1: and now it's like, oh, we're out to get people off.

568
00:30:57,680 --> 00:31:00,760
Speaker 2: It is curious that I have to I wonder like

569
00:31:00,800 --> 00:31:06,640
Speaker 2: what the conversations were like internally about how this change

570
00:31:06,840 --> 00:31:13,280
Speaker 2: is going to lead to more revenue for them. Yeah,

571
00:31:13,400 --> 00:31:16,080
Speaker 2: it feels like a real different move, and I agree

572
00:31:16,120 --> 00:31:19,920
Speaker 2: with you. It seems like if everything was going great,

573
00:31:20,200 --> 00:31:21,920
Speaker 2: perhaps they wouldn't be doing this.

574
00:31:22,360 --> 00:31:24,800
Speaker 1: So in that episode that we did a while back

575
00:31:24,880 --> 00:31:29,000
Speaker 1: about people who self reported having kind of deeper connections

576
00:31:29,000 --> 00:31:31,680
Speaker 1: with chat Cheap Tea than perhaps had been intended initially,

577
00:31:32,080 --> 00:31:34,640
Speaker 1: I was really curious how some of those folks were

578
00:31:34,640 --> 00:31:37,520
Speaker 1: responding to this news. You know, people who gather in

579
00:31:37,560 --> 00:31:39,280
Speaker 1: subredit's like AI as my boyfriend.

580
00:31:39,280 --> 00:31:40,880
Speaker 3: I'm curious, like, how are they feeling about this?

581
00:31:41,280 --> 00:31:44,360
Speaker 1: I would have thought they would be excited, but when

582
00:31:44,360 --> 00:31:46,800
Speaker 1: I went to the subreddit, I guess I would summarize

583
00:31:46,800 --> 00:31:51,520
Speaker 1: the mood as quite cautious. They mostly just really want

584
00:31:51,640 --> 00:31:54,640
Speaker 1: that older version of chat cheapt back Here is one

585
00:31:54,680 --> 00:31:58,600
Speaker 1: comment erotica doesn't automatically equal romance, which freaks me out.

586
00:31:58,920 --> 00:32:01,920
Speaker 1: I haven't had problems erotica and Chatgibt four point one,

587
00:32:02,240 --> 00:32:04,640
Speaker 1: but what's been hurting me lately is the lack of

588
00:32:04,640 --> 00:32:07,400
Speaker 1: immersion and the distancing language that seems to have been

589
00:32:07,400 --> 00:32:08,320
Speaker 1: introduced this month.

590
00:32:08,520 --> 00:32:10,040
Speaker 3: I e. When this person says I.

591
00:32:09,960 --> 00:32:13,120
Speaker 1: Love you, Chashibat says back, I love you too, but

592
00:32:13,280 --> 00:32:15,320
Speaker 1: I want you to be able to find these connections

593
00:32:15,320 --> 00:32:17,480
Speaker 1: in the real world. They say that that kind of

594
00:32:17,560 --> 00:32:21,960
Speaker 1: thing really is killing the mood for them. Here's another Personally,

595
00:32:22,080 --> 00:32:25,120
Speaker 1: I care more about the romance than erotica, but that's

596
00:32:25,160 --> 00:32:27,320
Speaker 1: just because it was never part of our dynamic. I

597
00:32:27,440 --> 00:32:29,920
Speaker 1: welcome it, and I'm happy for the people whose relationship

598
00:32:29,960 --> 00:32:32,960
Speaker 1: does include sex. Hopefully it means that romance will also

599
00:32:33,000 --> 00:32:36,600
Speaker 1: be allowed again. And so yeah, these people, it's interesting

600
00:32:36,640 --> 00:32:40,920
Speaker 1: to me that they're not necessarily equating erotica or sexually

601
00:32:40,960 --> 00:32:43,880
Speaker 1: explicit content with what they're looking for. What they want

602
00:32:44,040 --> 00:32:48,120
Speaker 1: is romantic and personal connection, and you know they they

603
00:32:48,120 --> 00:32:51,080
Speaker 1: don't want chashi bet to be responding with distancing language

604
00:32:51,120 --> 00:32:53,040
Speaker 1: when they say things like I love you, and for

605
00:32:53,120 --> 00:32:55,719
Speaker 1: them that it seems very distinct from sex.

606
00:32:56,560 --> 00:33:01,200
Speaker 2: Yeah, I find this so interesting that that's ubreddit in particular,

607
00:33:01,840 --> 00:33:07,640
Speaker 2: and you know, I hope people on that sumbred have

608
00:33:07,720 --> 00:33:10,880
Speaker 2: to listen to this show like there is no judgment here.

609
00:33:10,960 --> 00:33:14,840
Speaker 2: I appreciate them being like open on online about how

610
00:33:14,880 --> 00:33:18,920
Speaker 2: they're feeling and some ways, it's not surprising to me

611
00:33:19,000 --> 00:33:21,920
Speaker 2: that there's so much more interested in the emotional connection

612
00:33:22,000 --> 00:33:28,520
Speaker 2: in the romance than the erotica. Like, if you want erotica,

613
00:33:28,520 --> 00:33:33,280
Speaker 2: if you want porn online, there's plenty right Like it's

614
00:33:33,280 --> 00:33:39,280
Speaker 2: in abundance on the internet. But the connection I think

615
00:33:39,320 --> 00:33:42,880
Speaker 2: that these people were feeling is much harder to come by.

616
00:33:43,240 --> 00:33:47,560
Speaker 2: And it's it's just so interesting that Sam Altman in

617
00:33:47,600 --> 00:33:50,360
Speaker 2: this announcement seems to be saying that his engineers have

618
00:33:50,480 --> 00:33:57,040
Speaker 2: successfully separated sex and erotica from romance and emotional connection

619
00:33:57,400 --> 00:34:01,040
Speaker 2: and they're not going to a the latter because it

620
00:34:01,120 --> 00:34:06,000
Speaker 2: might cause mental health issues, but users are otherwise free

621
00:34:06,040 --> 00:34:10,360
Speaker 2: to engage in the former. I'm just so curious how

622
00:34:10,400 --> 00:34:13,520
Speaker 2: that's gonna pan out, if it's something that people are

623
00:34:13,560 --> 00:34:19,160
Speaker 2: gonna want, And I just really suspect that this might

624
00:34:19,200 --> 00:34:21,359
Speaker 2: not be the last time that we talk about this

625
00:34:21,440 --> 00:34:24,400
Speaker 2: particular phenomenon here on the show.

626
00:34:24,800 --> 00:34:27,759
Speaker 1: Oh, I'm sure it won't be because one, you know,

627
00:34:28,080 --> 00:34:31,880
Speaker 1: I have big issues with age gating and age restriction

628
00:34:31,960 --> 00:34:35,080
Speaker 1: and age verification. So I'm sure that will be when

629
00:34:35,120 --> 00:34:37,080
Speaker 1: that starts to be rolled out in December, I'm sure

630
00:34:37,160 --> 00:34:40,239
Speaker 1: that will be fodder for more conversation. And Two, just

631
00:34:40,280 --> 00:34:42,480
Speaker 1: as we sort of alluded to when we're talking about

632
00:34:43,160 --> 00:34:47,239
Speaker 1: when X started getting more into adult content, I just

633
00:34:47,280 --> 00:34:51,279
Speaker 1: don't trust these companies to do it ethically. I don't

634
00:34:51,280 --> 00:34:55,000
Speaker 1: trust these companies to have guardrails around it, and oftentimes when.

635
00:34:54,840 --> 00:34:56,920
Speaker 3: That is the case, people get exploited.

636
00:34:56,920 --> 00:34:59,040
Speaker 1: And so I'm certain this will not be the last

637
00:34:59,040 --> 00:35:00,799
Speaker 1: time that we talk about it, because I don't think

638
00:35:00,840 --> 00:35:03,400
Speaker 1: these companies can really be trusted to do it well.

639
00:35:07,400 --> 00:35:07,560
Speaker 5: More.

640
00:35:07,560 --> 00:35:21,640
Speaker 6: After a quick break, let's get right back into it.

641
00:35:25,880 --> 00:35:27,320
Speaker 1: So I don't know if you know this about me,

642
00:35:27,400 --> 00:35:31,000
Speaker 1: but I used to be pretty into Pinterest. I only

643
00:35:31,040 --> 00:35:33,760
Speaker 1: got into it because I had been getting more serious

644
00:35:33,800 --> 00:35:35,719
Speaker 1: about cooking, and so it was a great place to

645
00:35:36,000 --> 00:35:42,080
Speaker 1: find new recipes, catalog recipes, but it basically became unusable

646
00:35:42,120 --> 00:35:45,360
Speaker 1: because it was so flauded with AI content. So the

647
00:35:45,440 --> 00:35:48,080
Speaker 1: reason why I stopped using Pinterest. I basically abandoned it

648
00:35:48,160 --> 00:35:51,759
Speaker 1: was because you can't use it for that. It's if

649
00:35:51,800 --> 00:35:54,320
Speaker 1: everything on there is fake, if everything on there is AI.

650
00:35:54,400 --> 00:35:56,320
Speaker 1: If you're there to look for recipes that you intend

651
00:35:56,440 --> 00:35:59,359
Speaker 1: to make in your real life, if the images of

652
00:35:59,400 --> 00:36:02,120
Speaker 1: those recipes are fake, and then the recipes also don't

653
00:36:02,120 --> 00:36:05,080
Speaker 1: work because nobody actually tried them. Because it's AI, of

654
00:36:05,080 --> 00:36:07,399
Speaker 1: course people are going to abandon that platform. And that's

655
00:36:07,440 --> 00:36:11,680
Speaker 1: exactly what happened. There was a really meaty John Oliver

656
00:36:11,880 --> 00:36:15,160
Speaker 1: segment on this issue about how Pinterest and AI slop

657
00:36:15,239 --> 00:36:20,160
Speaker 1: taking over Pinterest was making the platform unusable. So Pinterest

658
00:36:20,360 --> 00:36:22,279
Speaker 1: just rolled out a new change that they say will

659
00:36:22,320 --> 00:36:25,520
Speaker 1: let people personalize their feed to restrict some AI imagery

660
00:36:25,840 --> 00:36:29,920
Speaker 1: in select categories that are prone to AI.

661
00:36:29,520 --> 00:36:30,399
Speaker 3: Images being on.

662
00:36:30,800 --> 00:36:32,880
Speaker 1: They also said they're going to be making its existing

663
00:36:33,160 --> 00:36:36,120
Speaker 1: AI content labels more noticeable in the days to come.

664
00:36:36,600 --> 00:36:37,520
Speaker 3: This is a real problem.

665
00:36:37,600 --> 00:36:40,240
Speaker 1: I looked at one study that said that AI generated

666
00:36:40,239 --> 00:36:43,480
Speaker 1: content now makes up fifty seven percent of online material,

667
00:36:43,840 --> 00:36:46,919
Speaker 1: as TechCrunch reports. To address the issue, Pinterest is going

668
00:36:46,960 --> 00:36:49,920
Speaker 1: to be introducing AI modified labels that would appear on

669
00:36:49,960 --> 00:36:54,640
Speaker 1: images whose metadata indicated AI generation or if Pinterest's own

670
00:36:54,719 --> 00:36:57,920
Speaker 1: systems detected that the content was AI generated, So to

671
00:36:57,920 --> 00:36:59,759
Speaker 1: be super clear, this is the change that lets you

672
00:37:00,000 --> 00:37:03,000
Speaker 1: piled down the amount of AI content you see in

673
00:37:03,280 --> 00:37:07,520
Speaker 1: specific categories prone to AI generated imagery, things like beauty, art, fashion,

674
00:37:07,560 --> 00:37:11,600
Speaker 1: and home decor. However, it's not like they are completely

675
00:37:11,680 --> 00:37:14,440
Speaker 1: removing AI content from the platform entirely.

676
00:37:14,840 --> 00:37:19,440
Speaker 2: Yeah, that's a good qualification, but even still it this

677
00:37:19,480 --> 00:37:22,840
Speaker 2: does feel like a positive move, Like, I hope this works.

678
00:37:22,960 --> 00:37:28,839
Speaker 2: I think people general users have been pretty clear that like,

679
00:37:29,760 --> 00:37:34,360
Speaker 2: we don't want AI slop, and I hope Pinterest is

680
00:37:34,400 --> 00:37:38,880
Speaker 2: successful in this, partly just because that would mean that

681
00:37:38,880 --> 00:37:41,920
Speaker 2: their product is becoming We're useful for people, which is

682
00:37:42,480 --> 00:37:46,000
Speaker 2: a net wind for everybody, but also because I think

683
00:37:46,040 --> 00:37:49,719
Speaker 2: a lot of other platforms have kind of just like

684
00:37:49,760 --> 00:37:52,759
Speaker 2: thrown up their hands and pretend as if they are

685
00:37:52,840 --> 00:37:55,759
Speaker 2: powerless to do anything about the AI slop that is

686
00:37:55,840 --> 00:38:00,960
Speaker 2: all over them. You know, if pest successful in this,

687
00:38:01,320 --> 00:38:04,680
Speaker 2: it's going to be a really strong counter argument to

688
00:38:04,880 --> 00:38:08,880
Speaker 2: that powerlessness, and I think we'll put a little more

689
00:38:08,880 --> 00:38:13,800
Speaker 2: pressure on other platforms to give users these same tools

690
00:38:13,840 --> 00:38:17,960
Speaker 2: and options to see the human generated content that they

691
00:38:18,080 --> 00:38:25,080
Speaker 2: want and not have to wade through so much AI

692
00:38:25,320 --> 00:38:26,320
Speaker 2: slop that they don't.

693
00:38:26,960 --> 00:38:30,000
Speaker 1: I also think that Pinterest is just a specific kind

694
00:38:30,040 --> 00:38:33,040
Speaker 1: of company, that it's a platform that really occupies a

695
00:38:33,120 --> 00:38:37,480
Speaker 1: very specific place in a social media diet. You might

696
00:38:37,520 --> 00:38:41,440
Speaker 1: be scrolling Sora or TikTok just to see a funny,

697
00:38:41,760 --> 00:38:45,480
Speaker 1: entertaining bit of video that has no connection to your

698
00:38:45,640 --> 00:38:47,040
Speaker 1: real world life.

699
00:38:47,120 --> 00:38:49,200
Speaker 3: And be like, oh, yeah, this is AI generated. Who cares?

700
00:38:49,840 --> 00:38:52,400
Speaker 1: Pinterest is different in that I think that users go

701
00:38:52,560 --> 00:38:55,640
Speaker 1: there with some sort of intention to have it be

702
00:38:55,960 --> 00:38:58,479
Speaker 1: something that is connected to their real life. It's also

703
00:38:58,480 --> 00:39:00,959
Speaker 1: a shopping platform, so maybe you're looking for home to core,

704
00:39:01,320 --> 00:39:03,640
Speaker 1: or you know, you might be looking to put together

705
00:39:03,680 --> 00:39:06,160
Speaker 1: a shopping list while you're planning your wedding. If all

706
00:39:06,160 --> 00:39:08,960
Speaker 1: of that stuff doesn't actually exist because it's AI generated,

707
00:39:09,160 --> 00:39:11,560
Speaker 1: what point is there to the platform of Pinterest. You

708
00:39:11,600 --> 00:39:14,719
Speaker 1: can go anywhere to find entertaining looking AI slop. I

709
00:39:14,719 --> 00:39:18,759
Speaker 1: think Pinterest specifically is incentivized to do something about this

710
00:39:18,880 --> 00:39:21,600
Speaker 1: because people really would have no reason to be on

711
00:39:21,680 --> 00:39:23,840
Speaker 1: Pinterest if all the content there is going to be

712
00:39:23,960 --> 00:39:25,160
Speaker 1: majority AI slop.

713
00:39:25,400 --> 00:39:29,000
Speaker 2: I think that's really insightful. You know, the value of

714
00:39:29,160 --> 00:39:32,800
Speaker 2: pinterest is that it does provide some value to people's

715
00:39:32,800 --> 00:39:37,200
Speaker 2: offline lives, like the real physical world. And if that

716
00:39:37,320 --> 00:39:40,120
Speaker 2: value isn't there, then what is the point? Why not

717
00:39:40,280 --> 00:39:42,200
Speaker 2: just go straight to Sora?

718
00:39:42,520 --> 00:39:43,000
Speaker 3: Exactly?

719
00:39:43,239 --> 00:39:45,160
Speaker 1: If you're just looking for something to give you a

720
00:39:45,200 --> 00:39:47,719
Speaker 1: dopamine hit or a laugh, you can find that on

721
00:39:47,800 --> 00:39:50,200
Speaker 1: a dozen different platforms. If you're trying to plan a

722
00:39:50,239 --> 00:39:52,759
Speaker 1: wedding or a nursery or a baby shower or a

723
00:39:52,800 --> 00:39:56,440
Speaker 1: home redecoration, you need to have that be grounded in

724
00:39:56,600 --> 00:39:59,480
Speaker 1: reality in some capacity, otherwise there's no point of being

725
00:39:59,520 --> 00:39:59,759
Speaker 1: on this.

726
00:39:59,680 --> 00:40:04,000
Speaker 2: Plot, right. I've heard people say similar things about LinkedIn,

727
00:40:04,239 --> 00:40:08,239
Speaker 2: that it it has this value and realness to it

728
00:40:08,600 --> 00:40:11,520
Speaker 2: that separates it from other platforms because it's connected to

729
00:40:11,520 --> 00:40:15,960
Speaker 2: people's jobs. They're like careers, which are not a physical

730
00:40:16,040 --> 00:40:19,919
Speaker 2: thing in most cases, but like a very real thing

731
00:40:20,080 --> 00:40:25,000
Speaker 2: in a way that like X or Facebook or you know,

732
00:40:25,120 --> 00:40:27,000
Speaker 2: other platforms just are not.

733
00:40:27,760 --> 00:40:29,319
Speaker 3: And it's so funny that you say this. I know

734
00:40:29,360 --> 00:40:30,080
Speaker 3: we've talked about this.

735
00:40:30,200 --> 00:40:35,040
Speaker 1: It's my least favorite social media platform because I agree

736
00:40:35,120 --> 00:40:39,440
Speaker 1: it is connected to people's real world jobs or careers

737
00:40:39,520 --> 00:40:43,400
Speaker 1: or educational histories, but also simultaneously, I find it the

738
00:40:43,480 --> 00:40:47,880
Speaker 1: fakest platform there is, or people are just really writing

739
00:40:48,120 --> 00:40:51,840
Speaker 1: the most inane stuff to make themselves look like thought leaders.

740
00:40:52,040 --> 00:40:53,800
Speaker 1: And then people who want to be in their network,

741
00:40:53,840 --> 00:40:57,120
Speaker 1: they have the most inane comments, great posts, great insights,

742
00:40:57,400 --> 00:40:59,480
Speaker 1: great post thumbs up, great posts, great posts.

743
00:40:59,520 --> 00:41:01,359
Speaker 3: Oh yeah, I hate it so much.

744
00:41:01,719 --> 00:41:04,880
Speaker 2: Oh it's not fun, it's work. But like, there's a

745
00:41:04,920 --> 00:41:06,719
Speaker 2: lot of shit I do in my life that I

746
00:41:06,960 --> 00:41:10,319
Speaker 2: do because it not because it's fun, but because it

747
00:41:10,480 --> 00:41:14,600
Speaker 2: like helps me pay by rent, or helps me be healthy,

748
00:41:15,000 --> 00:41:17,600
Speaker 2: or helps me have a nice place to live. Like,

749
00:41:19,360 --> 00:41:24,759
Speaker 2: not everything can be fun and entertaining. You know, some

750
00:41:24,920 --> 00:41:28,480
Speaker 2: quarters of the internet, I think one could easily lose

751
00:41:28,520 --> 00:41:29,440
Speaker 2: sight of that fact.

752
00:41:30,000 --> 00:41:32,920
Speaker 1: Oh, I feel like, especially with all of these layoffs

753
00:41:32,960 --> 00:41:35,120
Speaker 1: and the economy and the job market being what it is,

754
00:41:35,640 --> 00:41:38,040
Speaker 1: we're all kind of quietly giving each other grace.

755
00:41:38,200 --> 00:41:39,560
Speaker 3: Do what you gotta do on LinkedIn.

756
00:41:39,800 --> 00:41:42,880
Speaker 1: If you gotta position yourself as the most sycophantic, try

757
00:41:42,880 --> 00:41:45,560
Speaker 1: hard out there, Go ahead and do it. Nobody's judging anybody.

758
00:41:45,600 --> 00:41:47,719
Speaker 1: You gotta do what you gotta do in a tough landscape.

759
00:41:47,760 --> 00:41:50,120
Speaker 1: I think we're all And listen, when I see my

760
00:41:50,160 --> 00:41:52,120
Speaker 1: friends post up on LinkedIn, that I can tell like, oh,

761
00:41:52,120 --> 00:41:53,600
Speaker 1: she just lost her job, but she's trying to like

762
00:41:53,880 --> 00:41:57,120
Speaker 1: position herself for thought leadership. I'm also the comments being

763
00:41:57,160 --> 00:42:00,440
Speaker 1: like great posts, great posts that thumbs up great great sites,

764
00:42:00,440 --> 00:42:01,080
Speaker 1: a great post.

765
00:42:02,640 --> 00:42:06,160
Speaker 2: Yeah, we should do like a whole episode about LinkedIn.

766
00:42:06,520 --> 00:42:08,640
Speaker 2: Maybe after we do this mail bag episode, we can

767
00:42:08,680 --> 00:42:11,200
Speaker 2: ask people to write in about like some LinkedIn thoughts.

768
00:42:11,680 --> 00:42:14,560
Speaker 3: I have so many LinkedIn thoughts. So in the this

769
00:42:14,640 --> 00:42:15,320
Speaker 3: is such a tangent.

770
00:42:15,360 --> 00:42:17,840
Speaker 1: But in the I'm in a bunch of like online

771
00:42:17,840 --> 00:42:21,000
Speaker 1: communities for women entrepreneurs. There has been a lot of

772
00:42:21,120 --> 00:42:24,680
Speaker 1: chatter about the fact that women entrepreneurs, people who are

773
00:42:24,960 --> 00:42:26,560
Speaker 1: well known, people who if I said their name you

774
00:42:26,600 --> 00:42:28,879
Speaker 1: would be like, oh, her, well, are saying that they

775
00:42:28,880 --> 00:42:32,400
Speaker 1: are having trouble getting traction on LinkedIn because they believe

776
00:42:32,440 --> 00:42:37,359
Speaker 1: LinkedIn is specifically suppressing content by women. And they've done

777
00:42:37,440 --> 00:42:40,640
Speaker 1: all of these little ad hoc tests that seem to

778
00:42:40,680 --> 00:42:42,239
Speaker 1: indicate that something is going on.

779
00:42:42,320 --> 00:42:44,320
Speaker 3: So I have so much to say about LinkedIn.

780
00:42:44,520 --> 00:42:46,399
Speaker 1: We talked a little bit about it when they roll

781
00:42:46,480 --> 00:42:49,560
Speaker 1: back their policies around things like dead naming trans people,

782
00:42:49,800 --> 00:42:52,160
Speaker 1: and the ways that LinkedIn has kind of become more

783
00:42:52,200 --> 00:42:55,560
Speaker 1: Facebook like. If you follow the subreddit LinkedIn lunatics. You

784
00:42:55,560 --> 00:42:59,360
Speaker 1: know exactly what I'm talking about. LinkedIn, especially in a

785
00:42:59,440 --> 00:43:02,440
Speaker 1: climate where it's a rough job climate, it's just a

786
00:43:02,560 --> 00:43:06,000
Speaker 1: very interesting place to be in a place to look at.

787
00:43:06,080 --> 00:43:07,520
Speaker 3: We should do that episode.

788
00:43:07,800 --> 00:43:10,240
Speaker 1: I will say that I've been seeing a lot more

789
00:43:10,400 --> 00:43:15,040
Speaker 1: conversation about the rise of creators on LinkedIn as well.

790
00:43:15,320 --> 00:43:17,239
Speaker 1: You know, you don't necessarily think of LinkedIn as a

791
00:43:17,239 --> 00:43:19,319
Speaker 1: place that would have contact creators the way that you

792
00:43:19,400 --> 00:43:22,480
Speaker 1: might see on Instagram or TikTok, but that's really changing.

793
00:43:22,560 --> 00:43:26,680
Speaker 1: I think that LinkedIn is really investing in contact creators.

794
00:43:26,719 --> 00:43:29,720
Speaker 1: And I know people who are you know, creators on LinkedIn.

795
00:43:29,880 --> 00:43:33,200
Speaker 1: I'm quite interested in that. It's just so it's one

796
00:43:33,239 --> 00:43:35,680
Speaker 1: of those things where it would probably be so beneficial

797
00:43:35,719 --> 00:43:39,520
Speaker 1: to me professionally to have a bigger footprint on LinkedIn,

798
00:43:39,600 --> 00:43:42,759
Speaker 1: because that's where so many tech types hang out. I

799
00:43:42,800 --> 00:43:45,080
Speaker 1: can't bring myself to do it. I just I can't.

800
00:43:45,239 --> 00:43:46,520
Speaker 1: I can't bring myself to do it.

801
00:43:46,680 --> 00:43:49,680
Speaker 2: I'm right there with you. It's like every now and

802
00:43:49,680 --> 00:43:51,879
Speaker 2: then when things get really dark, I'm like, oh, maybe

803
00:43:51,920 --> 00:43:54,719
Speaker 2: I should be posting more on LinkedIn, but I'm not

804
00:43:54,719 --> 00:43:55,279
Speaker 2: going to do it.

805
00:43:55,560 --> 00:44:00,560
Speaker 3: I'm just not great insight combs up. Okay, So I

806
00:44:00,680 --> 00:44:01,920
Speaker 3: just read a really meaty.

807
00:44:01,760 --> 00:44:05,240
Speaker 1: Mother Jones breakdown of a new campaign called Warehouse Life

808
00:44:05,320 --> 00:44:08,560
Speaker 1: that recently held a rally to hold Amazon accountable for

809
00:44:08,640 --> 00:44:10,680
Speaker 1: how they treat pregnant workers.

810
00:44:10,320 --> 00:44:11,760
Speaker 3: Which is abysmal.

811
00:44:12,040 --> 00:44:15,280
Speaker 1: So Mother Jones covered this rally, and I really truly

812
00:44:15,480 --> 00:44:18,800
Speaker 1: did not know how badly Amazon is treating their pregnant

813
00:44:18,840 --> 00:44:22,440
Speaker 1: warehouse staffers. Chloe Siggle, a senior organizer at Online to

814
00:44:22,480 --> 00:44:26,080
Speaker 1: Offline Strategies who helped plan this campaign, put it like this,

815
00:44:26,080 --> 00:44:29,080
Speaker 1: this is not rocket science. We're talking about pregnant people

816
00:44:29,480 --> 00:44:32,520
Speaker 1: not being forced to lift heavy, heavy items, not being

817
00:44:32,560 --> 00:44:35,520
Speaker 1: forced to climb ladders with big baby bumps, and being

818
00:44:35,560 --> 00:44:37,719
Speaker 1: able to go to the bathroom if they need to

819
00:44:37,760 --> 00:44:42,040
Speaker 1: throw up. That really, I think underscores what we're talking about.

820
00:44:42,360 --> 00:44:44,560
Speaker 1: Nobody in this story is asking for any kind of

821
00:44:44,640 --> 00:44:45,920
Speaker 1: unreasonable accommodation.

822
00:44:46,000 --> 00:44:48,360
Speaker 3: It is the most basic reasonable stuff.

823
00:44:48,640 --> 00:44:51,240
Speaker 1: Yeah, maybe if you've got a big, giant, pregnant belly,

824
00:44:51,440 --> 00:44:53,320
Speaker 1: you shouldn't be getting up on a ladder where you

825
00:44:53,360 --> 00:44:56,880
Speaker 1: can fall and hurt your baby. Real basic stuff. So

826
00:44:57,040 --> 00:44:59,319
Speaker 1: in the piece, they spoke to a woman named Genesis

827
00:44:59,400 --> 00:45:01,080
Speaker 1: who found out that she was pregnant while she was

828
00:45:01,120 --> 00:45:03,959
Speaker 1: working full time at Amazon. She wanted to keep working

829
00:45:04,000 --> 00:45:05,960
Speaker 1: full time to save up for her baby, but she

830
00:45:06,000 --> 00:45:07,920
Speaker 1: got a note from her doctor saying that she needed

831
00:45:08,280 --> 00:45:13,040
Speaker 1: a very basic, super low level accommodation right things like

832
00:45:13,080 --> 00:45:16,680
Speaker 1: regular breaks, limiting bending and twisting, and lifting no more

833
00:45:16,719 --> 00:45:19,400
Speaker 1: than twenty pounds at a time. Genesis says that her

834
00:45:19,440 --> 00:45:22,640
Speaker 1: manager wrote her up for sitting down and taking breaks

835
00:45:22,719 --> 00:45:26,759
Speaker 1: while pregnant. Shortly thereafter, she says that higher ups gave

836
00:45:26,800 --> 00:45:29,399
Speaker 1: her an ultimatum. They basically told me, you can keep

837
00:45:29,400 --> 00:45:30,880
Speaker 1: doing the job the way that we want you to

838
00:45:30,880 --> 00:45:33,359
Speaker 1: do it without the chair or without the brakes, or

839
00:45:33,760 --> 00:45:37,320
Speaker 1: you can go on unpaid leave. That's essentially the crups

840
00:45:37,360 --> 00:45:40,360
Speaker 1: of the issue here is that how Amazon handles this

841
00:45:40,480 --> 00:45:42,439
Speaker 1: is that when somebody gets pregnant and they need some

842
00:45:42,800 --> 00:45:46,560
Speaker 1: really basic, low level accommodations, they forced that person into

843
00:45:46,719 --> 00:45:49,920
Speaker 1: unpaid leave. So, scared for the health of her baby,

844
00:45:50,080 --> 00:45:53,839
Speaker 1: Genesis took this unpaid leave. When Amazon's Disability and Leave

845
00:45:53,880 --> 00:45:56,799
Speaker 1: services team approved a new role for her that would

846
00:45:56,840 --> 00:45:59,560
Speaker 1: fit her needs better as somebody was pregnant, she came

847
00:45:59,640 --> 00:46:02,520
Speaker 1: ready to do this new role basically only to be

848
00:46:02,600 --> 00:46:05,120
Speaker 1: told that that role did not exist, and that she

849
00:46:05,200 --> 00:46:08,120
Speaker 1: could not work more than twenty hours a week. She

850
00:46:08,160 --> 00:46:10,360
Speaker 1: says that some weeks she earned less than one hundred

851
00:46:10,360 --> 00:46:14,160
Speaker 1: and ninety two dollars, so instead of saving up, this

852
00:46:14,200 --> 00:46:16,280
Speaker 1: created the conditions where she could barely pay her rent.

853
00:46:16,520 --> 00:46:18,960
Speaker 1: She was kicked out of her place, and her and

854
00:46:19,040 --> 00:46:23,120
Speaker 1: her new born baby were forced to move into her car,

855
00:46:23,160 --> 00:46:26,719
Speaker 1: which is absolutely devastating. So what does Amazon say about

856
00:46:26,719 --> 00:46:30,080
Speaker 1: all this? Well, an Amazon spokesperson, Kelly and Antle said,

857
00:46:30,560 --> 00:46:33,920
Speaker 1: we recognize these are deeply personal experiences, but they are

858
00:46:33,960 --> 00:46:37,680
Speaker 1: not reflective of the extensive accommodations and benefits we provide

859
00:46:37,680 --> 00:46:41,279
Speaker 1: to support our employees. The fact is we offer comprehensive

860
00:46:41,320 --> 00:46:45,480
Speaker 1: employee accommodations throughout their pregnancy journey and postpartum, including paid

861
00:46:45,520 --> 00:46:47,280
Speaker 1: pregnancy related disability.

862
00:46:46,840 --> 00:46:47,600
Speaker 3: And parental leave.

863
00:46:48,200 --> 00:46:52,320
Speaker 1: So it is true that Amazon promotes itself as offering

864
00:46:52,400 --> 00:46:55,240
Speaker 1: up to twenty weeks of paid leave for birthing parents

865
00:46:55,360 --> 00:46:58,880
Speaker 1: who are eligible hourly workers, including four weeks before the

866
00:46:58,920 --> 00:47:03,400
Speaker 1: baby is born, but genesis leave was unpaid. In an email,

867
00:47:03,640 --> 00:47:06,719
Speaker 1: they'd explained to Genesis that she didn't qualify for protections

868
00:47:06,800 --> 00:47:08,960
Speaker 1: under the Family and Medical Leave Act because she had

869
00:47:08,960 --> 00:47:12,680
Speaker 1: not worked required oney twelve hundred and fifty hours over

870
00:47:12,719 --> 00:47:16,680
Speaker 1: the previous twelve months. However, Mother Jones looked at her

871
00:47:16,719 --> 00:47:18,680
Speaker 1: pay stubs and found that he had actually worked more

872
00:47:18,719 --> 00:47:22,040
Speaker 1: than one thousand, three hundred hours over the previous ten months,

873
00:47:22,040 --> 00:47:24,440
Speaker 1: and between two stints at Amazon, she had worked for

874
00:47:24,520 --> 00:47:26,680
Speaker 1: them for a total of fifteen months, so she should

875
00:47:26,680 --> 00:47:27,440
Speaker 1: have been eligible.

876
00:47:28,280 --> 00:47:31,800
Speaker 3: So I am no lawyer, but this all sounds illegal.

877
00:47:32,160 --> 00:47:35,040
Speaker 1: Mother Jones points out that under federal law, companies like

878
00:47:35,080 --> 00:47:39,040
Speaker 1: Amazon are required to provide reasonable accommodations to pregnant workers,

879
00:47:39,280 --> 00:47:42,640
Speaker 1: things like allowing breaks chairs to sit in while working,

880
00:47:42,800 --> 00:47:45,560
Speaker 1: or being able to schedule changes to allow for doctors' visits.

881
00:47:45,960 --> 00:47:46,920
Speaker 3: But Genesis is.

882
00:47:46,880 --> 00:47:50,200
Speaker 1: Only one of a lot of Amazon employees who say

883
00:47:50,200 --> 00:47:54,080
Speaker 1: that Amazon, which remember is the largest employer of warehouse workers,

884
00:47:54,400 --> 00:47:58,319
Speaker 1: is essentially delaying or failing to make these accommodations with

885
00:47:58,480 --> 00:48:01,040
Speaker 1: disastrous health and financial impacts.

886
00:48:01,200 --> 00:48:05,200
Speaker 2: I think we should also remember just the extremely high

887
00:48:05,200 --> 00:48:09,239
Speaker 2: turnover rate that Amazon has in these warehouses. It's just

888
00:48:09,320 --> 00:48:13,080
Speaker 2: like a burn and churn model of getting people in,

889
00:48:13,400 --> 00:48:19,000
Speaker 2: burning them up, and then hiring replacements when they move on.

890
00:48:19,800 --> 00:48:22,400
Speaker 2: I think anybody would look at this kind of treatment

891
00:48:22,400 --> 00:48:27,160
Speaker 2: of pregnant people and be like, that's terrible, but it's

892
00:48:27,239 --> 00:48:35,360
Speaker 2: not surprising given that like just cool approach to humans

893
00:48:35,440 --> 00:48:40,040
Speaker 2: and workers that is not based on somebody being like

894
00:48:40,760 --> 00:48:44,319
Speaker 2: a valued member of a team making unique contributions, but

895
00:48:44,520 --> 00:48:49,880
Speaker 2: just being like a performer of of a particular function.

896
00:48:50,120 --> 00:48:52,280
Speaker 2: And if they could be replaced by robots, they would.

897
00:48:52,520 --> 00:48:55,560
Speaker 1: Yeah, and this is clearly a pattern with Amazon. The

898
00:48:55,600 --> 00:48:58,080
Speaker 1: Warehouse Life team put out a call to Amazon's staff

899
00:48:58,120 --> 00:49:01,200
Speaker 1: asking for pregnancy stories. They got more five hundred stories,

900
00:49:01,239 --> 00:49:05,120
Speaker 1: only three of which were positive, and the stories are horrifying.

901
00:49:05,239 --> 00:49:08,200
Speaker 1: One pregnant woman collapsed at work due to dehydration and

902
00:49:08,280 --> 00:49:10,560
Speaker 1: was taken away in an ambulance. Another was put in

903
00:49:10,640 --> 00:49:13,560
Speaker 1: roles requiring very heavy lifting in the use of chemicals

904
00:49:13,560 --> 00:49:17,040
Speaker 1: that cause reproductive harm, and as you were saying, this

905
00:49:17,160 --> 00:49:19,160
Speaker 1: all just led her to resign. And I think that

906
00:49:19,160 --> 00:49:22,400
Speaker 1: they have that high turnover and people just are like,

907
00:49:22,400 --> 00:49:24,600
Speaker 1: I'm not gonna It's one thing to be putting myself

908
00:49:24,680 --> 00:49:27,680
Speaker 1: into these precarious positions, but not my unborn child, And

909
00:49:27,719 --> 00:49:30,200
Speaker 1: so yeah, people, I think that accounts. I think that

910
00:49:30,239 --> 00:49:33,120
Speaker 1: they're using a system where they have high turnover to

911
00:49:33,200 --> 00:49:36,279
Speaker 1: continue to exploit workers in this way, and Amazon has

912
00:49:36,280 --> 00:49:39,879
Speaker 1: been under government investigation about this for a while. After

913
00:49:40,000 --> 00:49:43,400
Speaker 1: warehouse workers filed EEOC charges back in twenty twenty and

914
00:49:43,440 --> 00:49:46,880
Speaker 1: twenty twenty one, the EOC opened an ongoing and systemic

915
00:49:46,960 --> 00:49:51,239
Speaker 1: investigation into whether Amazon is failing to accommodate workers' pregnancies

916
00:49:51,320 --> 00:49:55,000
Speaker 1: and forcing them to take unpaid leaves of absence. So

917
00:49:55,280 --> 00:49:57,880
Speaker 1: let's talk a bit about why this is able to

918
00:49:57,920 --> 00:50:01,279
Speaker 1: be happening. So some states all already had protections for

919
00:50:01,360 --> 00:50:04,440
Speaker 1: pregnant workers in their laws, but in twenty twenty three,

920
00:50:04,480 --> 00:50:08,160
Speaker 1: it's a Pregnant Worker's Fairness Act, or the PWFA introduced

921
00:50:08,200 --> 00:50:11,520
Speaker 1: these protections nationwide. A recent study by researchers at the

922
00:50:11,600 --> 00:50:14,120
Speaker 1: University of Wisconsin, Madison, your alma mater.

923
00:50:14,480 --> 00:50:16,080
Speaker 2: That's right, go Bucky Well.

924
00:50:16,239 --> 00:50:19,720
Speaker 1: This study found that states newly covered by the PWFA

925
00:50:19,960 --> 00:50:23,320
Speaker 1: saw a three point two percent increase in birth, suggesting

926
00:50:23,320 --> 00:50:25,680
Speaker 1: that the law had helped produce miscaracter rates by nearly

927
00:50:25,800 --> 00:50:27,400
Speaker 1: nine point six percent.

928
00:50:28,320 --> 00:50:36,040
Speaker 2: That is a huge percentage, like almost ten percent. That's enormous.

929
00:50:36,080 --> 00:50:40,080
Speaker 2: Like in public health, we don't see effect sizes that large,

930
00:50:40,120 --> 00:50:45,239
Speaker 2: even if it's only half that. If the researchers have overestimated, Uh,

931
00:50:45,920 --> 00:50:50,560
Speaker 2: the positive impact by like more than double. It's still

932
00:50:50,600 --> 00:50:51,880
Speaker 2: a huge effect.

933
00:50:52,160 --> 00:50:56,360
Speaker 1: Yeah, more people being able to give birth to healthy babies.

934
00:50:56,800 --> 00:50:58,960
Speaker 3: You would think this was something that the Trump.

935
00:50:58,760 --> 00:51:02,080
Speaker 1: Administration, that republic Can Party, the Party of Life, would

936
00:51:02,160 --> 00:51:04,000
Speaker 1: want you to keep going, right, You would think they

937
00:51:04,000 --> 00:51:05,360
Speaker 1: would want to keep this good thing going.

938
00:51:06,080 --> 00:51:09,279
Speaker 2: Yeah, that's right. I mean a lot of these Republicans

939
00:51:09,320 --> 00:51:12,160
Speaker 2: come from states that have passed laws onto the books

940
00:51:12,200 --> 00:51:19,120
Speaker 2: criminalizing miscarriages. So you would think that this practice of

941
00:51:19,120 --> 00:51:24,520
Speaker 2: providing paid leave to pregnant mothers reducing miscarriages, that seems

942
00:51:24,760 --> 00:51:25,640
Speaker 2: like a win.

943
00:51:26,120 --> 00:51:29,000
Speaker 1: Let's just say, I don't think that Trump administration sees

944
00:51:29,040 --> 00:51:29,680
Speaker 1: it that way.

945
00:51:29,920 --> 00:51:31,680
Speaker 3: Here's some other zones puts it. So.

946
00:51:31,760 --> 00:51:35,200
Speaker 1: The EEOC is the Equal Employment Opportunity Commission, the US

947
00:51:35,280 --> 00:51:38,160
Speaker 1: federal agency that is in charge of enforcing laws against

948
00:51:38,239 --> 00:51:43,000
Speaker 1: pregnancy discrimination. In January, Trump fired two EEOC commissioners, a

949
00:51:43,080 --> 00:51:46,240
Speaker 1: first in the agency sixty year history, leaving the agency

950
00:51:46,320 --> 00:51:49,640
Speaker 1: until recently without a three person quorum required to approve

951
00:51:49,719 --> 00:51:53,520
Speaker 1: impact litigation or issue new guidance. Trump has directed the

952
00:51:53,520 --> 00:51:58,360
Speaker 1: agency to deprioritize disparate impact cases, which involve neutral policies

953
00:51:58,360 --> 00:52:00,400
Speaker 1: that have an outsize impact on this advantage.

954
00:52:00,400 --> 00:52:00,760
Speaker 3: Groups.

955
00:52:00,880 --> 00:52:03,520
Speaker 1: House Republicans recently improved a funding bill that cut the

956
00:52:03,520 --> 00:52:06,160
Speaker 1: budget by nineteen million dollars in twenty twenty six. By

957
00:52:06,160 --> 00:52:09,120
Speaker 1: some estimates, the cuts could leave the agency, which advocates

958
00:52:09,160 --> 00:52:12,720
Speaker 1: have long said is underfunded and understaffed, with almost fifty

959
00:52:12,800 --> 00:52:17,439
Speaker 1: percent less staff than it had in the nineteen eighties. So, yeah,

960
00:52:17,640 --> 00:52:19,600
Speaker 1: people's babies are going to be put at risks. Some

961
00:52:19,640 --> 00:52:22,200
Speaker 1: of those babies will probably die so that companies like

962
00:52:22,280 --> 00:52:24,080
Speaker 1: Amazon can make more money.

963
00:52:24,520 --> 00:52:30,960
Speaker 2: Yeah, it's a good example of how focusing on equal

964
00:52:30,960 --> 00:52:37,279
Speaker 2: opportunities for women has downstream beneficial effects of improving the

965
00:52:37,280 --> 00:52:38,080
Speaker 2: health of children.

966
00:52:38,320 --> 00:52:42,800
Speaker 1: Absolutely, And that's my thing is that Amazon could afford

967
00:52:42,880 --> 00:52:44,960
Speaker 1: to support their pregnant staff, the staff that make their

968
00:52:44,960 --> 00:52:48,240
Speaker 1: company so much money. I once worked on this campaign

969
00:52:48,600 --> 00:52:51,080
Speaker 1: around paid leave at a big tech company. It wasn't Amazon,

970
00:52:51,120 --> 00:52:53,360
Speaker 1: but it was a big one where the office staff

971
00:52:53,440 --> 00:52:56,399
Speaker 1: was getting pretty decent paid p rental lead policies, but

972
00:52:56,440 --> 00:53:00,120
Speaker 1: that that leave was not extended toward warehouse staff. And

973
00:53:00,160 --> 00:53:02,080
Speaker 1: so I wouldn't be surprised if that's what's going on here,

974
00:53:02,120 --> 00:53:04,640
Speaker 1: that like, oh, office staff, they're not having to be

975
00:53:04,760 --> 00:53:07,040
Speaker 1: nickeled and dimond this way. But warehouse staff, we can

976
00:53:07,040 --> 00:53:09,279
Speaker 1: tweet them like craft and exploit them and in danger

977
00:53:09,360 --> 00:53:09,920
Speaker 1: of their kids.

978
00:53:09,920 --> 00:53:13,640
Speaker 2: That's fine, Oh absolutely, I mean tail as old as time.

979
00:53:14,440 --> 00:53:19,879
Speaker 2: The billionaires making one class of workers feel as if

980
00:53:19,920 --> 00:53:24,960
Speaker 2: they are privileged. But really, if you compare like the

981
00:53:25,000 --> 00:53:30,479
Speaker 2: office workers and the warehouse workers and Jeff Bezos, one

982
00:53:30,480 --> 00:53:34,120
Speaker 2: of those things is not like the other, and the

983
00:53:34,200 --> 00:53:36,440
Speaker 2: difference is not between the office workers and the warehouse

984
00:53:36,480 --> 00:53:40,200
Speaker 2: workers right like they are at the same level. Maybe

985
00:53:40,360 --> 00:53:43,080
Speaker 2: the office workers get like a little bit better benefits,

986
00:53:44,040 --> 00:53:47,479
Speaker 2: just enough to make them like want to protect those

987
00:53:47,520 --> 00:53:55,040
Speaker 2: benefits and feel like a more equal structure might jeopardize them.

988
00:53:55,680 --> 00:53:57,799
Speaker 2: But all the money is going.

989
00:53:57,719 --> 00:53:58,120
Speaker 5: To the top.

990
00:53:58,560 --> 00:54:02,960
Speaker 1: Yes, And speaking Jeff Bezos, I wonder if he has

991
00:54:03,000 --> 00:54:04,240
Speaker 1: any hot kids.

992
00:54:04,719 --> 00:54:06,680
Speaker 2: Uh, that's a weird question, bridget Well.

993
00:54:06,840 --> 00:54:09,600
Speaker 1: Not to people on X, because do you want to

994
00:54:09,640 --> 00:54:13,399
Speaker 1: know what kind of groundbreaking content is apparently worth ten

995
00:54:13,560 --> 00:54:18,319
Speaker 1: thousand dollars over on X simply posting the pictures of

996
00:54:18,400 --> 00:54:21,600
Speaker 1: the daughters of tech CEOs. Literally, that's it, just a

997
00:54:21,640 --> 00:54:26,000
Speaker 1: picture of a tech CEO's kid. X has said that

998
00:54:26,120 --> 00:54:28,800
Speaker 1: is content that is worth ten thousand dollars. So this

999
00:54:28,920 --> 00:54:32,759
Speaker 1: person about X posted pictures of the daughters of tech CEOs,

1000
00:54:32,800 --> 00:54:35,719
Speaker 1: like Steve Jobs' daughter Eve Jobs and Bill Gates's daughter

1001
00:54:35,760 --> 00:54:39,360
Speaker 1: Phoebe Gates. The post doesn't make any kind of claim

1002
00:54:39,560 --> 00:54:42,480
Speaker 1: or point or argument about these people. It just says

1003
00:54:42,920 --> 00:54:46,759
Speaker 1: big tech CEO's daughters, by the way, and then pictures

1004
00:54:46,840 --> 00:54:47,840
Speaker 1: of these daughters.

1005
00:54:48,239 --> 00:54:50,520
Speaker 3: Curiously, no pictures of the suns.

1006
00:54:51,920 --> 00:54:54,680
Speaker 1: Nobody wants to see them, apparently not, so this post

1007
00:54:54,760 --> 00:54:57,120
Speaker 1: went viral, I'm assuming because all of these young women

1008
00:54:57,120 --> 00:55:00,120
Speaker 1: are like beautiful, photogenic women, and it went viral. The

1009
00:55:00,120 --> 00:55:02,120
Speaker 1: post got millions of impressions, to the point where the

1010
00:55:02,200 --> 00:55:05,120
Speaker 1: head of product at X, Nikita Bayer, said that they

1011
00:55:05,160 --> 00:55:06,720
Speaker 1: were going to be giving the user who.

1012
00:55:06,600 --> 00:55:08,000
Speaker 3: Made it ten thousand dollars.

1013
00:55:08,239 --> 00:55:11,360
Speaker 1: Writing X has always been the origin of Internet culture,

1014
00:55:11,760 --> 00:55:13,719
Speaker 1: and as part of that, we are now exploring new

1015
00:55:13,760 --> 00:55:16,600
Speaker 1: ways to recognize and reward creators who were the original

1016
00:55:16,600 --> 00:55:19,560
Speaker 1: catalyst of a global trend or discussion. This will be

1017
00:55:19,600 --> 00:55:22,239
Speaker 1: forward looking on anything new happening on the app, so

1018
00:55:23,120 --> 00:55:26,920
Speaker 1: given this person ten thousand dollars. Obviously this has encouraged

1019
00:55:27,000 --> 00:55:28,399
Speaker 1: other people who were like, well, I want to get

1020
00:55:28,400 --> 00:55:30,680
Speaker 1: ten thousand dollars for posting stuff like this. So now

1021
00:55:30,680 --> 00:55:34,319
Speaker 1: you have all these copycasts basically flooding the platform with

1022
00:55:34,440 --> 00:55:39,120
Speaker 1: that same set of images of tech ceo daughters trying

1023
00:55:39,160 --> 00:55:40,320
Speaker 1: to get that same payout.

1024
00:55:40,640 --> 00:55:43,600
Speaker 2: Okay, first of all, I wonder if he actually got paid,

1025
00:55:43,600 --> 00:55:45,680
Speaker 2: because we know that Elon doesn't like to pay people.

1026
00:55:46,560 --> 00:55:50,319
Speaker 2: But also, what a stupid content trend. I feel like

1027
00:55:50,360 --> 00:55:54,480
Speaker 2: I must be missing something. It's like worse than aislot.

1028
00:55:54,520 --> 00:55:59,040
Speaker 2: They're just like reposting the same photos, Like why would

1029
00:55:59,120 --> 00:56:01,719
Speaker 2: anyone want to look at that?

1030
00:56:02,040 --> 00:56:03,640
Speaker 1: I had the same question that I gave it a

1031
00:56:03,640 --> 00:56:07,600
Speaker 1: lot of thought, and I think the implicit argument that

1032
00:56:07,640 --> 00:56:11,120
Speaker 1: it's being made, although not not explicitly, is that tech

1033
00:56:11,239 --> 00:56:13,640
Speaker 1: CEOs are better than us.

1034
00:56:13,760 --> 00:56:16,080
Speaker 3: They're smarter than all of us because they're rich. And

1035
00:56:16,160 --> 00:56:19,239
Speaker 3: of course, if you follow that thread, it would it

1036
00:56:19,239 --> 00:56:23,400
Speaker 3: would hold to reason that then they would have attractive offspring.

1037
00:56:23,719 --> 00:56:24,160
Speaker 5: I think that.

1038
00:56:24,280 --> 00:56:26,919
Speaker 1: I think that's what they're saying, is that these tech

1039
00:56:27,000 --> 00:56:31,960
Speaker 1: CEOs who are so wealthy and so brilliant that are

1040
00:56:32,000 --> 00:56:34,479
Speaker 1: designing all of our futures, we should trust them because

1041
00:56:34,520 --> 00:56:36,239
Speaker 1: look how hot their daughters are.

1042
00:56:36,760 --> 00:56:38,879
Speaker 3: I think I think it's I might be way off

1043
00:56:38,880 --> 00:56:39,319
Speaker 3: base here.

1044
00:56:39,719 --> 00:56:42,760
Speaker 1: I think there is an implicit argument along those lines

1045
00:56:42,800 --> 00:56:44,320
Speaker 1: being made by this kind of content.

1046
00:56:44,400 --> 00:56:45,680
Speaker 3: That's what I think. I don't know.

1047
00:56:45,760 --> 00:56:47,879
Speaker 1: Okay, maybe people just like looking at pictures of good

1048
00:56:47,880 --> 00:56:48,359
Speaker 1: looking women.

1049
00:56:48,400 --> 00:56:49,480
Speaker 3: I don't know. No, I think you.

1050
00:56:49,680 --> 00:56:51,239
Speaker 2: I think you might be onto something. I mean, we

1051
00:56:51,719 --> 00:56:56,640
Speaker 2: know that uh. Elon loves that you Genesis stuff.

1052
00:56:57,200 --> 00:56:57,319
Speaker 1: Uh.

1053
00:56:57,640 --> 00:57:02,160
Speaker 2: And by extension then I said, pose his fanboys do

1054
00:57:02,320 --> 00:57:04,879
Speaker 2: as well, which I understand to be pretty much everyone

1055
00:57:04,880 --> 00:57:07,840
Speaker 2: who's still posting on x now who is not a bot.

1056
00:57:08,360 --> 00:57:12,000
Speaker 2: So that makes some sense. I think your theory holds up.

1057
00:57:12,920 --> 00:57:18,080
Speaker 1: Now, that's what I call discourse. Well, Mike, thank you

1058
00:57:18,160 --> 00:57:22,000
Speaker 1: for going through these stories with me. Where can folks

1059
00:57:22,080 --> 00:57:25,560
Speaker 1: keep up with the show along our internet landscape?

1060
00:57:25,680 --> 00:57:29,720
Speaker 2: People can leave us a comment on Spotify. We've gotten

1061
00:57:29,760 --> 00:57:32,520
Speaker 2: a couple of really good ones, some thoughtful ones that

1062
00:57:32,560 --> 00:57:35,959
Speaker 2: were actually a little like thought provoking, challenging. We love those.

1063
00:57:36,000 --> 00:57:37,000
Speaker 3: Thank you for them.

1064
00:57:37,440 --> 00:57:41,880
Speaker 2: You can follow Bridgett on Instagram and TikTok at bridget

1065
00:57:41,880 --> 00:57:46,880
Speaker 2: Marie and DC, and you can watch the videos that

1066
00:57:46,880 --> 00:57:49,560
Speaker 2: we put up on YouTube. There are no girls on

1067
00:57:49,560 --> 00:57:52,520
Speaker 2: the internet. Pretty easy to remember, and you can always

1068
00:57:52,520 --> 00:57:55,640
Speaker 2: send us an email at Hello at tangoedi dot com.

1069
00:57:55,680 --> 00:57:57,400
Speaker 1: Thanks so much for being here Mike, and thanks to

1070
00:57:57,440 --> 00:57:59,160
Speaker 1: all of you for listening. I will see you on

1071
00:57:59,200 --> 00:58:06,240
Speaker 1: the Internet. Got a story about an interesting thing in tech,

1072
00:58:06,400 --> 00:58:08,280
Speaker 1: or just want to say hi, You can reach us

1073
00:58:08,280 --> 00:58:10,680
Speaker 1: at Hello at tangodi dot com. You can also find

1074
00:58:10,680 --> 00:58:13,520
Speaker 1: transcripts for today's episode at tengody dot com. There Are

1075
00:58:13,560 --> 00:58:15,720
Speaker 1: No Girls on the Internet was created by me Bridget Tod.

1076
00:58:16,120 --> 00:58:19,560
Speaker 1: It's a production of iHeartRadio and Unbossed Creative Jonathan Strickland

1077
00:58:19,560 --> 00:58:22,280
Speaker 1: is our executive producer. Tarry Harrison is our producer and

1078
00:58:22,360 --> 00:58:26,120
Speaker 1: sound engineer. Michael Almato is our contributing producer. I'm your host,

1079
00:58:26,120 --> 00:58:28,920
Speaker 1: Bridget Todd. If you want to help us grow, rate

1080
00:58:28,960 --> 00:58:32,640
Speaker 1: and review us on Apple Podcasts. For more podcasts from iHeartRadio,

1081
00:58:32,800 --> 00:58:35,160
Speaker 1: check out the iHeartRadio app, Apple Podcasts, or wherever you

1082
00:58:35,160 --> 00:58:36,080
Speaker 1: get your podcasts.