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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 Bridgett and this is

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Speaker 1: there Are No Girls on the Internet.

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Speaker 2: Yeah, this is just like the banter between Chris Prett

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Speaker 2: and Mark Wahlberg on the Hello app.

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Speaker 1: The Hallow app is wild to me. So it is

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Speaker 1: a prayer app where celebrities like Mark Wahlberg, like Chris

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Speaker 1: Pratt is the newest one this week, Gwen Stefani are

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Speaker 1: basically howking. It is a prayer app for Catholics. I

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Speaker 1: knew about Gwen Stefani because I had seen that a

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Speaker 1: while ago. I did not know about Mark Wahlberg, although

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Speaker 1: that totally tracks. Is he also a celebrity affiliated with

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Speaker 1: this Catholic prayer app?

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Speaker 2: He's in there. Yeah, he's actually a major investor and partner.

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Speaker 1: Oh that makes so much sense. I was actually watching

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Speaker 1: for some reason him on the View on Wednesday morning,

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Speaker 1: which was ash Wednesday. Obviously he had to book an

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Speaker 1: interview to talk about any random thing, just to show

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Speaker 1: off his ashes. I went to Catholic school. I have

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Speaker 1: had my fair share of ash Wednesday ashes smudged on

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Speaker 1: my forehead back when I would get it. It would just

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Speaker 1: be like a little smudge that would be gone. You

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Speaker 1: would get it during Mass, it would be gone by lunchtime.

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Speaker 1: Mark Wahlberg's ashes look like somebody put grease paint on

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Speaker 1: his forehead. I think that they're doing the ashes more

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Speaker 1: intense so that notable Catholics can go on TV and

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Speaker 1: have their faith be this big, large badge on their forehead.

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Speaker 1: I think he booked an interview to talk about any

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Speaker 1: random thing just so that he would have an opportunity

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Speaker 1: to show off these ashes. So yeah, not surprising that

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Speaker 1: Mark Wahlberg is pulling out the big guns to promote

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Speaker 1: the Hallow app.

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Speaker 2: I was curious, so I created an account logged in

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Speaker 2: UH and it was a pretty long on board. He

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Speaker 2: asked me a bunch of questions about myself, had a

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Speaker 2: couple choice quotes from various saints and disciples UH, and

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Speaker 2: then it asked and invited me to select the What

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Speaker 2: was a celebrity guides that I wanted to hear from

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Speaker 2: Mark Wahlberg was like top left guide to choose? Did

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Speaker 2: you use him number one position? Of course?

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Speaker 1: I did.

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Speaker 2: I mean I knew you would be interested and want

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Speaker 2: me to report back about your boyfriend.

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Speaker 1: Oh, shut up. I was a kid. Okay, listeners, Mike

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Speaker 1: is teasing me because he knows a shameful secret of mine,

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Speaker 1: which I will reveal. But please don't tell anybody. This

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Speaker 1: is just between me, Mike, Joey who edits this? And

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Speaker 1: I guess whoever is listening, which is that when I

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Speaker 1: when I was young, I had such the hots for

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Speaker 1: Mark Wahlberg. I had a Marky Mark. You might be

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Speaker 1: too young to know this. Mark Wahlberg used to be

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Speaker 1: Marky Mark with the Funky Bunch that was his group,

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Speaker 1: which was awful. But I had one of his Calvin

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Speaker 1: Klein posters on my wall when I was a kid.

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Speaker 1: I used to write him letters. I was so obsessed

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Speaker 1: with her. I thought he was so hot. This is

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Speaker 1: when I was a child, by the way, so not

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Speaker 1: currently not now.

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Speaker 2: I know exactly the poster that you're talking about. I

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Speaker 2: feel like I knew a lot of girls who had

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Speaker 2: that poster on their walls.

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Speaker 1: There was a movie that Mark Wahlberg was in that

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Speaker 1: it's called Fear. There is a specific scene from the

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Speaker 1: movie Fear that let's just say it really made an

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Speaker 1: impression on me when I saw it. When I was

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Speaker 1: like eleven and I what can I say, I have

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Speaker 1: terrible taste. What can I say? But I guess it

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Speaker 1: doesn't surprise me now. Like Mark Wahlberg is a scumbag

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Speaker 1: for so many reasons, we could talk so much about

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Speaker 1: all the of the scumbag stuff. I know that he

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Speaker 1: is a famous Catholic. Hallo. This app, this faith based

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Speaker 1: prayer app for Catholics. Fun fact funded by Trump supporting

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Speaker 1: evil gay billionaire Peter Tiel and also JD Vance are

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Speaker 1: backers of this app. Here is how them described it.

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Speaker 1: Though prayer is famously free, the app is a subscription

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Speaker 1: based service that charges seventy dollars per year for an

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Speaker 1: annual plan or eleven dollars a month for a monthly option.

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Speaker 1: That is a lot of money to pray. The better

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Speaker 1: they better have some some primo voice talent on there

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Speaker 1: for those prices.

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Speaker 2: Yeah, and I had to buy the subscription to get

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Speaker 2: in there, which I did immediately cancel. But it was

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Speaker 2: going to be you know, I think sixty nine to

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Speaker 2: ninety nine for the year was what they were going

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Speaker 2: to build me if I didn't cancel, which is it's

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Speaker 2: a lot to pray. I don't know how much of

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Speaker 2: that makes its way to God.

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Speaker 1: How much of it makes its way to God, how

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Speaker 1: much of it makes its way to Mark Wahlberg, Chris Pratt,

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Speaker 1: and Gwen Stefani. Even on the Catholic subreddit on Reddit,

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Speaker 1: a place where Catholics gather, people are very skeptical this

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Speaker 1: app that is charging that amount of money just to pray,

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Speaker 1: And basically they're also kind of skeptical about what they

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Speaker 1: call these influential Catholics being used as a marketing opportunity.

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Speaker 1: The general consensus over there is the whole thing just

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Speaker 1: feels like turning people's legitimate faith into a cash grab.

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Speaker 1: And Mashable reports that the CEO, Alex Jones, no, not

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Speaker 1: that Alex Jones, a different Alex Jones, is on the

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Speaker 1: record saying that they're courting famous religious celebrities, so that

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Speaker 1: is part of their thing. They've done partnerships with Wahlberg,

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Speaker 1: as you said, Chris Pratt. Newly this week he released

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Speaker 1: a video about this app Hollywood Icon Mario Lopez, which

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Speaker 1: again I don't know that I should say that I

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Speaker 1: am shocked to hear some of these names, but the

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Speaker 1: founder says that he's doing this as a way to

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Speaker 1: reach fallen away Catholics or those who are not particularly

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Speaker 1: religious on the social media platforms they frequent most they're

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Speaker 1: just incredible Christians, They're great people of faith. Joes said

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Speaker 1: that actually is interesting to me that they're not going

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Speaker 1: after people who might consider themselves as like deeply religious.

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Speaker 1: They're just you know, you're just scrolling social media and

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Speaker 1: you have a particular fondness for Mark Wahlberg. Unfortunately, like me,

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Speaker 1: you might say, oh, what is this app? Maybe I'll

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Speaker 1: pay one hundred dollars a year to pray. One of

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Speaker 1: the other celebrities they talked about reaching out to work

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Speaker 1: with is Kevin James, Paul Blart mall Cop, my man

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Speaker 1: Mike's boyfriend.

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Speaker 2: Yeah, but I can see how that might pull me in.

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Speaker 2: I had never considered Paul Blart mall CoP's views about

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Speaker 2: theology and the divine. You know, I might be curious

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Speaker 2: to hear what he had to say, but I probably

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Speaker 2: wouldn't pay for it, you know, Like, I do feel

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Speaker 2: like there's something a little suss about putting up a

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Speaker 2: paywall between people and the divine, right like, and it

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Speaker 2: just seems like a bit of a red flo Oh.

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Speaker 1: Jesus notably loved a pay wall. You know. That was

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Speaker 1: one of his famous sayings in the Bible, is that'll

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Speaker 1: be eleven dollars a month, please, right.

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Speaker 2: Yeah, yeah, That's why he went into the temple and

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Speaker 2: the money changers and was like, make sure you have

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Speaker 2: a good system for only allowing people with money to

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Speaker 2: get in here, because we don't want those riff rafts.

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Speaker 1: Make sure this whole thing is backed by Peter Thiel's capital.

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Speaker 1: That's that is that is in the Bible. So when

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Speaker 1: Gwen Stefani last year was hawking this app, one of

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Speaker 1: my favorite people are not that I know this person,

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Speaker 1: but one of my favorite parasocial podcasters. Matt Bernstein from

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Speaker 1: the podcast A little Bit Fruity pointed out that the

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Speaker 1: app is not just prayers. They also have I guess

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Speaker 1: I would describe them as almost sort of mean prayers

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Speaker 1: specifically targeted at people who have gotten abortions. These prayers

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Speaker 1: are read by people like anti abortion activist Lila Rose.

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Speaker 1: One of the prayers is, Jesus, we pray for every

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Speaker 1: woman who is considering abortion in an especial way for

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Speaker 1: those who are pregnant from acts of rape or incest

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Speaker 1: by every woman, know the goodness gift and beauty of

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Speaker 1: her own life and so be able to receive the

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Speaker 1: gift of her child's life. What I find interesting about

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Speaker 1: this is that Alex Jones, the CEO of the app,

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Speaker 1: was like, oh, we're not even targeting people who are religious.

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Speaker 1: This is just like content. It's It's interesting to me

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Speaker 1: how when convenient this is able to sort of be

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Speaker 1: couched as non political, not even necessarily overtly religious. Then

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Speaker 1: you get into the app and it's like these abortion

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Speaker 1: having women to just have the baby? Am I right? People?

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Speaker 2: Yeah? Funny how they always just like kind of sneak

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Speaker 2: that in this is.

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Speaker 1: Me revealing how Pollyanna I am. I'm a little bit.

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Speaker 1: I was a little bit surprised about Gwen Stevanni on

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Speaker 1: this one, based purely on the girl Power songs that

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Speaker 1: she was making when I was in sixth grade. I

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Speaker 1: think maybe adulthood is about is like learning who people

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Speaker 1: actually are. You know, when you're a kid, you decide

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Speaker 1: who somebody is, you project who they are, and then

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Speaker 1: you're like, oh, this is who they actually are. I

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Speaker 1: also remember, not that long ago. I don't know if

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Speaker 1: this is true or not, but reading that Gwen Stefani

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Speaker 1: had put out a holiday album that was available to

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Speaker 1: buy exclusively at Cracker Barrel.

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Speaker 2: Which I feel said a lot that was true, but

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Speaker 2: I don't remember being a holiday album. I guess it

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Speaker 2: wasn't her solo album. But she's featured on Blake Shelton's

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Speaker 2: twenty sixteen album If I'm Honest, which was sold at

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Speaker 2: Cracker Barrel locations.

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Speaker 1: Blake Shelton is her husband. What is this Cracker Barrel

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Speaker 1: collab couple a CCC.

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Speaker 2: This is back before Cracker Barrel went woke too, so

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Speaker 2: it was acceptable for them to be there pre logo.

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Speaker 1: Change Cracker Barrel. You know. So I'm I'm a little

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Speaker 1: disappointed to find that when Stefani is missed up and

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Speaker 1: mixed up in this, I shouldn't be. But you know,

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Speaker 1: she was somebody who I liked as a youth quite

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Speaker 1: a bit. But Chris Pratt, nobody is surprised this week

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Speaker 1: to find that Chris Pratt made an ad for this

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Speaker 1: prayer app. You know, I was really having a big

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Speaker 1: think about it about what it is about Chris Pratt,

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Speaker 1: Why it is that I that not just me, but

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Speaker 1: like people dislike him. Also, I do love that our

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Speaker 1: super producer Joey. Their last name is Pat. The first

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Speaker 1: time that Joey and I spoke, I was like, oh,

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Speaker 1: Joey Pratt, and they were like, actually, it's a Pat. Actually,

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Speaker 1: my whole social media vibe is Pat, not Pratt to

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Speaker 1: distinguish from Chris Pratt, which I respect immensely, But that's

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Speaker 1: how much people don't want to be associated with Chris Pratt.

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Speaker 1: And I don't know, I was thinking, what the deal is.

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Speaker 1: Obviously Chris Pratt really hangs out a lot with RFK,

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Speaker 1: so it was in this sort of like Maha universe.

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Speaker 1: So there were definitely reasons to not like him and

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Speaker 1: not trust him. But for me, it is not even

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Speaker 1: necessarily really his politics or his ideology that I find

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Speaker 1: so annoying. One. I feel that he disarmed us when

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Speaker 1: he was on Parks and Recreation he was sort of goofy,

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Speaker 1: lovable Andy Dwyer. People liked him. He was generally inoffensive.

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Speaker 1: Then after that role, remember he got jacked. His whole

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Speaker 1: thing was like, oh, hey, I'm Chris Pratt and I'm jacked. Now.

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Speaker 1: I feel that there's something that happens there where it

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Speaker 1: just there's like an ego thing that happens there when

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Speaker 1: you go from being lovable and goofy to them being

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Speaker 1: jacked that you've really got to keep an eye on

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Speaker 1: with man, I'll just put it that way.

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Speaker 2: Yes, we saw Jim from the Office do the same

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Speaker 2: thing right where he rose to start him as kind

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Speaker 2: of like a gentle, sweet every man, but apparently lurking

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Speaker 2: within was like a desire to be the lead of

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Speaker 2: an action movie.

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Speaker 1: Don't even get me started. Aren't his movies this is

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Speaker 1: I'm speaking off the cuffs, so I don't know, and

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Speaker 1: I actually would love to be educated on this. Aren't

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Speaker 1: his movies basically just propaganda for US imperialism and the

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Speaker 1: war machine. Basically, you've got Jim Helper in those in

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Speaker 1: those movies. Is he also doing the Jim Helper where

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Speaker 1: he looks at the camera and mix that little plast

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Speaker 1: smile like, oh, on my work in imperialism? What are

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Speaker 1: you gonna do? Do you know what I'm talking about?

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Speaker 2: Well, wearing body armor? Yeah, that would be pretty good.

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Speaker 1: So the thing with Chris Pratt is that I feel

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Speaker 1: that he does this thing that I can't stand where Okay,

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Speaker 1: we get it. You are religious, you are Catholic. You

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Speaker 1: don't want to be too open about your politics, but

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Speaker 1: your politics are very clear. I don't think anybody is confused.

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Speaker 1: I'm not confused. You align yourself with kind of conservative

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Speaker 1: or tradition no values, but you're also in Hollywood. Fine,

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Speaker 1: got it, totally fine. The thing that gets me is

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Speaker 1: I have to be a victim about it, right. It

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Speaker 1: can't just be yes, I align myself with all of

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Speaker 1: these traditional conservative values, da da dah. I also need

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Speaker 1: to be talking about it as if I'm a victim

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Speaker 1: for these stances. That's what I don't like. And also

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Speaker 1: I don't like how he is everywhere, Like he is

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Speaker 1: really overrepresented in media when you compare to the actual

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Speaker 1: talent and charisma and the kind of roles that he gets. Like,

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Speaker 1: I don't understand why he is everywhere, But could you

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Speaker 1: other than the Avengers or whatever, could you name a

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Speaker 1: role or a movie that he's in right now that

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Speaker 1: he's in and like really crushing?

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Speaker 2: I mean I couldn't, but I don't know anything about movies.

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Speaker 2: It was notable when I selected him in the Hallow

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Speaker 2: app as a guide that I wanted to hear from

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Speaker 2: that they did not Parks and rec They listed Guardians

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Speaker 2: with the Galaxy and some other movie that I didn't

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Speaker 2: know but probably should, but it seemed like a notable omission.

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Speaker 3: Yeah.

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Speaker 1: I just feel like, if you are an actor and

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Speaker 1: you're not really that charismatic, and you're not really that talented,

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Speaker 1: and you're not really getting like great role after a

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Speaker 1: great role after a great role, why do I have

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Speaker 1: to be hearing about you so much? Why do I

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Speaker 1: have to know so much about your faith? You know,

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Speaker 1: there are plenty of entertainers of performers that I don't

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Speaker 1: personally like, but if I'm like, oh, well, they're in

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Speaker 1: the conversation. I'll give you a great example. Sidney Sweeney.

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Speaker 1: I don't personally enjoy her work. I did really like

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Speaker 1: her in the movie Reality, which if you've not seen

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Speaker 1: that on HBO, she actual does a great job, but

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Speaker 1: that she was great in Euphoria, but that was a

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Speaker 1: pretty minimal role. She is someone that I'll say I

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Speaker 1: don't like that I'm hearing from her often, but also

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Speaker 1: like she's in the conversation. She is in a lot

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Speaker 1: of movies. I'll concede that she is being interest reviewed

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Speaker 1: a ton because she is like in the conversation. I

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Speaker 1: don't have to like it, but there she is, I'll

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Speaker 1: tolerate it. I don't get the deal with Chris Prett.

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Speaker 1: I don't get why I'm hearing about him constantly. I

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Speaker 1: think I might cut this, but this just so that

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Speaker 1: you are aware of how I feel about Chris Prett.

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Speaker 2: Sure well, I mean I think we could put marky

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Speaker 2: Mark in that same category.

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Speaker 1: H don't make me I hate. Oh you know, I

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Speaker 1: do know, I do know. Listen, Mark Wahlberg, he is

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Speaker 1: a scumbag. He has a history of violence toward minoritized

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Speaker 1: people from his youth. Look it up. It's like horrifying.

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Speaker 1: I hate, I hate, and cannot help how much I

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Speaker 1: was obsessed with him when I was young. He stars

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Speaker 1: in my favorite movie of all time, Boogie Nights. I

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Speaker 1: don't know, I don't. We do hear about it. We

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Speaker 1: do hear from him too much. I will say that

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Speaker 1: we do hear from him a lot compared to It's

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Speaker 1: not commiserate with his at with the actual like his

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Speaker 1: the print that he picks up at a Hollywood I

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Speaker 1: guess I'll put it that way. Does that make sense?

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Speaker 2: It does make sense. And if you want to compare

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Speaker 2: acting skill, I mean, I guess he's he's been he's

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Speaker 2: he's a pretty good actor. But in the reading that

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Speaker 2: him and Chris were doing in the Hallow app he

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Speaker 2: was really phoning it in. Like it was clear that

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Speaker 2: Chris was giving it his all. Mark was definitely reading

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Speaker 2: from a script. I think he was doing like a

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Speaker 2: like a big batch of clips that were going to

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Speaker 2: be used for a bunch of things. You know, Like

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Speaker 2: they were not in conversation, they were recording separately, was

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Speaker 2: being edited together. He was really phoning that one in.

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Speaker 1: You can hear the note like is that good enough?

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Speaker 1: God is Love? Is that good? I was trying to

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Speaker 1: do a Boston accent because he's from Boston. Yeah. But

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Speaker 1: a fact about Mark Wahlberg, so you know that I

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Speaker 1: think pt Anderson's Bookie Nights is the best movie of

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Speaker 1: all time. It's a masterpiece. Mark Wahlberg basically never brings

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Speaker 1: up that he was in that movie. He has said

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Speaker 1: in interviews that he regrets doing Boogie Nights and said

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Speaker 1: that he actually has prayed to God for forgiveness for

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Speaker 1: having done Boogie Knights. Now, mind you, this is somebody

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Speaker 1: who went to prison for a hate crime when they

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Speaker 1: were young. I hope that he also asked for forgiveness

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Speaker 1: for that behavior. But because it's like a movie that

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Speaker 1: is about sex and a boxroous behavior comma, things that

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Speaker 1: Mark Wahlberg in real life is definitely associated with. He's not.

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Speaker 1: I don't know why. He's like a like makes it

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Speaker 1: seem like he's above these things. He certainly is not.

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Speaker 1: But imagine being part of a masterpiece and distancing yourself

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Speaker 1: from it. I don't even know why, because it's like

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Speaker 1: not Christian enough or whatever.

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Speaker 3: I mean.

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Speaker 2: I guess he does like a lot of Disney stuff, right,

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Speaker 2: So maybe maybe he's trying to protect the Wahlberg brand

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Speaker 2: for the Sanita Disney audience. Yeah, I don't know. Because

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Speaker 2: Booge Nights is an excellent movie. If I was in it,

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Speaker 2: i'd tell people.

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Speaker 1: Oh it mean, I never shut up about it.

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Speaker 2: You weren't even in it, and you never shut up

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Speaker 2: about it.

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Speaker 1: I wasn't even in it. Don't get me heard on

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Speaker 1: Boogie Knights. Fun fact about Boogie Knights. It has the

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Speaker 1: best DVD commentary of any DVD commentary because I love it.

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Speaker 1: I live for a DVD commentary. You know this the

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Speaker 1: best DVD commentary I've ever heard. Pet Anderson definitely in

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Speaker 1: my opinion, sounds like he had been doing some partying

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Speaker 1: while recording that DVD commentary. Let's put it that way.

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Speaker 1: They don't make DVD commentaries like that anymore.

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Speaker 4: If you have the DVD, if you've seen this, if

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Speaker 4: you're one of the handful of people that know what

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Speaker 4: I'm talking about, there are a few specific moments where

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Speaker 4: were like, wow, just a different time in the entertainment industry.

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Speaker 1: I guess on that DVD commentary. Anyway, I've really got

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Speaker 1: off track here.

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Speaker 2: Yeah, let's bring it back around the Hallow app.

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Speaker 1: Well, fun fact about the hallow app is that it

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Speaker 1: was actually banned from EU markets a few months ago.

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Speaker 1: Many suspected that the reason that regulators shut it down

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Speaker 1: in the EU was due to data privacy concerns and

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Speaker 1: things like sensitive data being used for ad targeting, including

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Speaker 1: religious affiliation, which all that stuff is obviously highly regulated

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Speaker 1: under the EU's Digital Services Act. Yeah, just like Jesus

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Speaker 1: intended for your deepest, most intimate religious thoughts and connections

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Speaker 1: being used to target you to sell you more crap.

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Speaker 2: Yeah, totally fine here in the US though, like, no problem,

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Speaker 2: go for it, make that money, target target on religious ideology,

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Speaker 2: whatever you want.

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Speaker 3: To do.

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Speaker 1: Have at it, Have at it, y'all in the US,

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Speaker 1: fucking live free.

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Speaker 3: Let's take a quick break at our.

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Speaker 1: Back speaking of stuff that should be cracked down on

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Speaker 1: in the US but weirdly is not. Let's talk about

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Speaker 1: GROC because for four media has this new report that

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Speaker 1: GROC is being used to uncover private information about porn performers.

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Speaker 1: So we talked about how GROC was being used to

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Speaker 1: undress women and minors according to the European Commission, in

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Speaker 1: ways that are illegal. That's not me saying that, that's

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Speaker 1: them saying that. Well, it just gets worse from there,

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Speaker 1: because porn performer Siri Doll basically is spent over a

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Speaker 1: decade and locked in lots of money trying to protect

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Speaker 1: her legal identity from the Internet, and GROC basically just

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Speaker 1: destroyed that. When a user on X tagged GROC asking

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Speaker 1: oh who is this person in this clip, GROC wasn't

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Speaker 1: just like, oh, here is Siri Doll, Here is this

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Speaker 1: porn performer's like performance identity. GROC volunteered Siri Doll's full

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Speaker 1: legal name and birthday. Mind you, this person was not

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Speaker 1: asking for this information. The user just asked, who is

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Speaker 1: this performer? Because they wanted to find more of this

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Speaker 1: performer's work public facing work. So what you might have

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Speaker 1: expected is for Groc to generate this person's stage name. No no,

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Speaker 1: no no. What was actually generated was their full legal

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Speaker 1: name and birthday, which happens to be information that this

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Speaker 1: performer has been trying to keep from the Internet for

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Speaker 1: many years. As soon as this happened, harassers started opening

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Speaker 1: Facebook accounts in her real name, porn leak site started

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Speaker 1: posting her content using her legal name instead of her

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Speaker 1: stage name, and people started asking Groc for her car,

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Speaker 1: her address, and her location. Scary stuff. And what makes

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Speaker 1: this particularly kind of scary and painful is the collateral

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Speaker 1: damage because she says that the reason why she is

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Speaker 1: trying to guard her legal name is to protect her family,

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Speaker 1: which you know, it's probably no surprise to anybody that

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Speaker 1: it is common practice for harassers to find somebody's parents'

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Speaker 1: phone numbers and call them or email somebody's family and friends.

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Speaker 1: And so now she has to warn her family and

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Speaker 1: put all of these defensive plans in place. Thanks to

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Speaker 1: Ex's chatbot volunteering this information about her unprompted, it is

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Speaker 1: ostensibly against X's own terms of service which explicitly prohibit doxing,

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Speaker 1: calling it a serious safety risk. But here it is

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Speaker 1: Ex's own chatbot, Groc, actually volunteering this information about somebody.

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Speaker 2: That is really scary, Uh, Like, how terrible for this performer.

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Speaker 2: And you have to wonder, how does Groc know her

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Speaker 2: name and her birthday? Is it just that good at

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Speaker 2: facial recognition? It is like what percentage of Americans would

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Speaker 2: Groc be able to identify? It's kind of a scary

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Speaker 2: thing to think about.

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Speaker 1: Yeah, And I think it fits into a broader pattern

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Speaker 1: of GROCK related abuses and harms, which we're going to

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Speaker 1: continue talking about both in this episode and just generally

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Speaker 1: as long as I'm fucking alive and I'll have a

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Speaker 1: beating heart, I'm going to continue talking about it because

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Speaker 1: I genuinely cannot believe that not more is being done

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Speaker 1: in the United States. Federally, nothing is being done, zero nothing.

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Speaker 1: We have a collection of state attorneys generals trying to

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Speaker 1: do something, but there is no federal regulating body in

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Speaker 1: the United States that is taking any action whatsoever against this.

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Speaker 1: And mind you, we're talking about sex against miners here,

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Speaker 1: we're talking about like crimes against kids, regulators from other

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Speaker 1: countries are stepping in because federally in the United States,

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Speaker 1: essentially nothing is being done. And as the four four

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Speaker 1: piece really points out well, in all the debate about

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Speaker 1: Internet safety and all these conversations that we have about

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Speaker 1: the need to regulate and sense or the internet to

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Speaker 1: protect kids, it is worth asking who is actually being

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Speaker 1: protected and who keeps being left exposed to harm. I

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Speaker 1: think stories like this one really illustrate what's going on here.

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Speaker 2: Totally agree, and I think something that is becoming clear

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Speaker 2: over this past year is that the types of answers

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Speaker 2: to those questions who's being protected and who's being harmed

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Speaker 2: I think are really changing. You Know, over the years

432
00:24:53,000 --> 00:24:56,600
Speaker 2: as we've been doing the show, we've talked about categories

433
00:24:56,640 --> 00:24:59,680
Speaker 2: of people who were not being protected.

434
00:24:59,720 --> 00:24:59,800
Speaker 1: Right.

435
00:25:00,160 --> 00:25:04,480
Speaker 2: We talk about the ways in which black women face

436
00:25:06,280 --> 00:25:12,439
Speaker 2: multiple threats challenges, you know, are disproportionately harmed by a

437
00:25:12,480 --> 00:25:17,359
Speaker 2: lot of the abuses that happen online. We talk about

438
00:25:17,359 --> 00:25:23,840
Speaker 2: how trans people are being disproportionately and unfairly targeted. And

439
00:25:23,880 --> 00:25:26,040
Speaker 2: so we're used to talking about categories of people who

440
00:25:26,040 --> 00:25:29,800
Speaker 2: are left out, but with the Trump administration, it really

441
00:25:29,840 --> 00:25:33,760
Speaker 2: feels like it's specific people who are being protected.

442
00:25:33,840 --> 00:25:33,959
Speaker 1: Right.

443
00:25:34,040 --> 00:25:36,320
Speaker 2: You can look at Elon Musky. He's a big supporter

444
00:25:36,440 --> 00:25:42,199
Speaker 2: of Trump, he's donating to Republicans. I don't know, but

445
00:25:42,240 --> 00:25:45,480
Speaker 2: I truly suspect and believe that a big part of

446
00:25:45,480 --> 00:25:48,359
Speaker 2: the reason of the administration is not doing anything about

447
00:25:48,400 --> 00:25:51,920
Speaker 2: any of these egregious crimes that his platform is doing

448
00:25:52,200 --> 00:25:54,000
Speaker 2: is because he's like part of their crew.

449
00:25:54,359 --> 00:25:54,560
Speaker 1: You know.

450
00:25:54,640 --> 00:25:57,919
Speaker 2: We can look at the Epstein files for other examples

451
00:25:58,280 --> 00:26:04,120
Speaker 2: where it is. It's not even like categories of people anymore.

452
00:26:04,160 --> 00:26:10,400
Speaker 2: It's specific people who are in power protecting themselves, and

453
00:26:11,040 --> 00:26:15,600
Speaker 2: everybody else can just you know, get bed pretty much.

454
00:26:15,680 --> 00:26:19,919
Speaker 1: That's really how it feels. Four or four also reported

455
00:26:20,040 --> 00:26:23,920
Speaker 1: on a site called camgirl Finder, which has been quietly

456
00:26:23,960 --> 00:26:28,160
Speaker 1: operating for years, that uses facial recognition technology to let

457
00:26:28,160 --> 00:26:31,280
Speaker 1: anybody search a database of over two billion phases straight

458
00:26:31,320 --> 00:26:35,080
Speaker 1: from adult streaming platforms. The premise and the threat is

459
00:26:35,200 --> 00:26:37,840
Speaker 1: very obvious. You just take a photo of a woman

460
00:26:38,000 --> 00:26:42,360
Speaker 1: from her personal Instagram or social media, upload it and

461
00:26:42,480 --> 00:26:44,920
Speaker 1: you can use that to find out if she does

462
00:26:44,960 --> 00:26:48,840
Speaker 1: sex work and if so where four or four tested

463
00:26:48,880 --> 00:26:53,720
Speaker 1: this and it actually works. Results will show a person's username,

464
00:26:54,080 --> 00:26:57,400
Speaker 1: the probability of a face match when they were last online,

465
00:26:57,480 --> 00:27:01,240
Speaker 1: and links to other profiles across platform. The site will

466
00:27:01,280 --> 00:27:03,960
Speaker 1: even sell you all of the images it has of

467
00:27:04,000 --> 00:27:07,760
Speaker 1: a given person for one dollar. This database includes women

468
00:27:07,800 --> 00:27:11,639
Speaker 1: who stopped streaming or doing cam work years ago, meaning

469
00:27:11,800 --> 00:27:15,560
Speaker 1: there is really no expiration date on the exposure risk.

470
00:27:15,640 --> 00:27:19,760
Speaker 1: So if you did streaming or cam work once years ago,

471
00:27:20,760 --> 00:27:23,720
Speaker 1: it can still be used to find you across the internet,

472
00:27:23,760 --> 00:27:27,359
Speaker 1: and it will still allow whoever to buy your image

473
00:27:27,800 --> 00:27:30,320
Speaker 1: now four or four talk to the creator of this

474
00:27:30,440 --> 00:27:35,160
Speaker 1: site about privacy concerns, and their point is basically like, hey,

475
00:27:35,200 --> 00:27:38,240
Speaker 1: if you stream publicly, you are a public figure. Deal

476
00:27:38,280 --> 00:27:41,760
Speaker 1: with it. He compared people who do sex work to

477
00:27:42,040 --> 00:27:47,120
Speaker 1: politicians or YouTubers, never really talked about what I think

478
00:27:47,200 --> 00:27:50,640
Speaker 1: is like the obvious difference, which is that people who

479
00:27:50,680 --> 00:27:54,200
Speaker 1: perform in adult content might want to keep their actual

480
00:27:54,520 --> 00:27:58,960
Speaker 1: legal names and identities separate from their personal lives for

481
00:27:59,440 --> 00:28:03,080
Speaker 1: safety because people are creeps. You know you don't. It

482
00:28:03,080 --> 00:28:06,199
Speaker 1: doesn't take a genius to imagine why it might not

483
00:28:06,320 --> 00:28:10,200
Speaker 1: be good to have your actual legal identity and family

484
00:28:10,400 --> 00:28:13,040
Speaker 1: and name attached to the work that you do professionally

485
00:28:13,119 --> 00:28:16,880
Speaker 1: because it's not safe for you. So there is an

486
00:28:16,920 --> 00:28:21,520
Speaker 1: opt out option, but that option only works if the

487
00:28:21,560 --> 00:28:24,720
Speaker 1: women know the site exists in the first place. And

488
00:28:24,760 --> 00:28:27,439
Speaker 1: I wanted to sort of put these two stories, the

489
00:28:27,480 --> 00:28:32,080
Speaker 1: one about Siri Doll having her real name be exposed

490
00:28:32,240 --> 00:28:35,359
Speaker 1: on X and this story. I wanted to sort of

491
00:28:35,359 --> 00:28:37,520
Speaker 1: put them in conversation with each other, because I do

492
00:28:37,560 --> 00:28:41,280
Speaker 1: think that they're sort of the same accelerating problem. That

493
00:28:41,760 --> 00:28:45,640
Speaker 1: these tools can be used to very easily, cheaply and

494
00:28:45,720 --> 00:28:49,960
Speaker 1: quickly strip away the separation that a sex worker might

495
00:28:50,000 --> 00:28:53,600
Speaker 1: put between their personal and their professional identity, and that

496
00:28:53,680 --> 00:28:59,400
Speaker 1: has real meaningful consequences for their safety, for their lives,

497
00:28:59,520 --> 00:29:04,200
Speaker 1: for their families. And I think it's really two stories

498
00:29:04,320 --> 00:29:07,360
Speaker 1: about the same thing. That we have a tech infrastructure

499
00:29:07,520 --> 00:29:12,040
Speaker 1: that treats people's safety and privacy as like a public

500
00:29:12,160 --> 00:29:16,120
Speaker 1: resource to be dismantled, not a right to be protected,

501
00:29:16,120 --> 00:29:20,880
Speaker 1: and that it's kind of fun or a fun challenge

502
00:29:20,960 --> 00:29:26,840
Speaker 1: to dismantle and erase whatever boundary somebody might have put

503
00:29:26,880 --> 00:29:29,640
Speaker 1: up between their personal and their professional lives. It's kind

504
00:29:29,640 --> 00:29:32,840
Speaker 1: of a quote fun challenge to see how you can

505
00:29:33,240 --> 00:29:35,680
Speaker 1: trample those And I think it just goes back to

506
00:29:35,720 --> 00:29:37,400
Speaker 1: something that we talk about on the show all the time.

507
00:29:37,400 --> 00:29:41,760
Speaker 1: It's just how much of the Internet is about exploiting

508
00:29:42,360 --> 00:29:45,840
Speaker 1: and consuming women. And I think the fact that these

509
00:29:45,880 --> 00:29:49,040
Speaker 1: folks are targeting women who do sex work is not

510
00:29:49,160 --> 00:29:52,959
Speaker 1: a coincidence, because you know, it's not enough that you

511
00:29:53,000 --> 00:29:58,040
Speaker 1: could pay to have access to these performers' professional work

512
00:29:58,840 --> 00:30:00,480
Speaker 1: and call that the end of it. It's like, no,

513
00:30:01,360 --> 00:30:04,480
Speaker 1: I cannot have them control the means by which they

514
00:30:05,600 --> 00:30:08,440
Speaker 1: present themselves to the world, and to me, I need

515
00:30:08,480 --> 00:30:10,719
Speaker 1: to be in control of that. Like, it's very much

516
00:30:10,760 --> 00:30:12,120
Speaker 1: about control.

517
00:30:11,640 --> 00:30:15,520
Speaker 2: To me and profit, right, Like they're charging a dollar

518
00:30:15,600 --> 00:30:17,440
Speaker 2: for these images that they have stolen.

519
00:30:17,840 --> 00:30:22,240
Speaker 1: Yeah, And I also I don't think that it works that, oh,

520
00:30:22,920 --> 00:30:28,000
Speaker 1: the information is public, so anything goes. There are plenty

521
00:30:28,000 --> 00:30:31,440
Speaker 1: of like if I started an only Fans tomorrow that

522
00:30:31,640 --> 00:30:35,360
Speaker 1: is technically public, but OnlyFans still has rules that you

523
00:30:35,400 --> 00:30:38,920
Speaker 1: can't screenshot and share elsewhere because it's my ip right

524
00:30:39,000 --> 00:30:42,760
Speaker 1: Like that, I feel like we have this logic, particularly

525
00:30:42,800 --> 00:30:47,400
Speaker 1: when it comes to women and our bodies, particularly when

526
00:30:47,520 --> 00:30:51,440
Speaker 1: women have found a way to have agency and economic

527
00:30:51,520 --> 00:30:54,080
Speaker 1: control over how they want to use their own bodies,

528
00:30:54,240 --> 00:30:56,280
Speaker 1: that says like, oh, well, if it's public, it belongs

529
00:30:56,320 --> 00:31:01,000
Speaker 1: to everybody, right, I have the right to quote expose

530
00:31:01,200 --> 00:31:04,680
Speaker 1: or unmask this person as if they're doing something that

531
00:31:05,120 --> 00:31:07,480
Speaker 1: means that they don't have a right to privacy anymore.

532
00:31:07,480 --> 00:31:12,760
Speaker 1: It's a very toxic, exploitative dynamics that I think is

533
00:31:12,960 --> 00:31:15,920
Speaker 1: baked into so much of our culture and not even

534
00:31:16,040 --> 00:31:19,520
Speaker 1: really a tech problem, necessarily a cultural.

535
00:31:19,080 --> 00:31:25,560
Speaker 2: Rot problem totally. And this camgirl Finder is like specifically

536
00:31:25,600 --> 00:31:29,000
Speaker 2: built for this purpose, right, Like there's there's not as

537
00:31:29,000 --> 00:31:31,280
Speaker 2: far as I get de there's not a legitimate use

538
00:31:31,320 --> 00:31:34,440
Speaker 2: of this tool, and people are have just found a

539
00:31:34,480 --> 00:31:39,720
Speaker 2: way to use it for this nefarious purpose, Like this

540
00:31:39,800 --> 00:31:45,080
Speaker 2: is it. This is the sole reason that the creators

541
00:31:45,160 --> 00:31:49,600
Speaker 2: of this app built it, which is just really gross.

542
00:31:50,040 --> 00:31:53,560
Speaker 1: Yeah, and I'm just so sick of it because it

543
00:31:53,680 --> 00:31:56,880
Speaker 1: just doesn't feel, as you were saying, it doesn't feel

544
00:31:56,920 --> 00:32:00,080
Speaker 1: that we have a system that is invested.

545
00:31:59,720 --> 00:32:00,680
Speaker 3: Means flee in.

546
00:32:02,360 --> 00:32:05,200
Speaker 1: Whether or not people get hurt. The creator of cam

547
00:32:05,280 --> 00:32:07,920
Speaker 1: Girl Finder says that if privacy is a concern, this

548
00:32:08,040 --> 00:32:10,000
Speaker 1: kind of job is not for you and gets to

549
00:32:10,120 --> 00:32:15,600
Speaker 1: dictate how and who shows up to this work, as

550
00:32:15,640 --> 00:32:19,320
Speaker 1: opposed to the performer dictating how they show up to

551
00:32:19,360 --> 00:32:22,960
Speaker 1: that work. Right. Elon Musk's platform has a terms of

552
00:32:23,040 --> 00:32:28,120
Speaker 1: service that explicitly bans docsing but also has a chatbot

553
00:32:28,360 --> 00:32:33,920
Speaker 1: that it volunteers people's private personal information that they don't

554
00:32:33,920 --> 00:32:36,520
Speaker 1: want on the Internet. And I just feel that until

555
00:32:36,560 --> 00:32:39,440
Speaker 1: we have some sort of real accountability, and right now

556
00:32:39,480 --> 00:32:42,440
Speaker 1: in the United States we don't really have that, the

557
00:32:42,520 --> 00:32:46,000
Speaker 1: burden is going to continue falling on women. Right It's

558
00:32:46,120 --> 00:32:49,200
Speaker 1: our responsibility to opt out of this website that's some

559
00:32:49,320 --> 00:32:53,760
Speaker 1: creep design. It's our responsibility to report, to warn families,

560
00:32:53,800 --> 00:32:57,040
Speaker 1: to spend all of this money like this porn performer

561
00:32:57,120 --> 00:33:01,520
Speaker 1: did on data removal services that can undo in like

562
00:33:01,640 --> 00:33:04,520
Speaker 1: one single reply. I'm just really sick of that. I'm

563
00:33:04,520 --> 00:33:08,440
Speaker 1: sick of living in a world where we are made

564
00:33:08,520 --> 00:33:14,200
Speaker 1: to shoulder this burden. As bad as I find all

565
00:33:14,240 --> 00:33:17,479
Speaker 1: of this, I do think the tides are turning because,

566
00:33:18,160 --> 00:33:21,640
Speaker 1: you know, as we talked about on x GROC was

567
00:33:21,680 --> 00:33:24,960
Speaker 1: being you to generate what the European Commission deemed illegal

568
00:33:25,000 --> 00:33:27,200
Speaker 1: images of women and miners that are rate of six

569
00:33:27,240 --> 00:33:32,840
Speaker 1: thousand requests per hour. While no US federal agency or

570
00:33:32,880 --> 00:33:38,240
Speaker 1: body did anything at all about this, other countries were

571
00:33:38,360 --> 00:33:41,720
Speaker 1: and are taking it more seriously. UK Prime Minister Keir

572
00:33:41,800 --> 00:33:45,640
Speaker 1: Starmer is calling non consensual intimate images both real and

573
00:33:45,680 --> 00:33:49,600
Speaker 1: AI generated a national emergency, and as actually backing that

574
00:33:49,760 --> 00:33:53,000
Speaker 1: up with new legislation. So under proposed amendments to the

575
00:33:53,040 --> 00:33:56,920
Speaker 1: Crime and Policing build tech companies like x would have

576
00:33:57,240 --> 00:34:00,400
Speaker 1: just forty eight hours to remove deep sake news and

577
00:34:00,440 --> 00:34:04,719
Speaker 1: revenge porn after those images have been flagged, or they

578
00:34:04,720 --> 00:34:07,800
Speaker 1: would face fines up to ten percent of their global

579
00:34:07,880 --> 00:34:11,600
Speaker 1: revenue or an outright block in the UK. Talking to

580
00:34:11,640 --> 00:34:15,000
Speaker 1: The Guardian, Starmer said the burden of tackling abuse must

581
00:34:15,040 --> 00:34:18,200
Speaker 1: no longer fall on victims. It must fall on perpetrators

582
00:34:18,239 --> 00:34:21,399
Speaker 1: and on the companies that enable harm. So I have

583
00:34:21,760 --> 00:34:25,440
Speaker 1: a lot of gripes about Starmar's government, but in this

584
00:34:25,640 --> 00:34:28,960
Speaker 1: case I really think that that is well said. The

585
00:34:29,120 --> 00:34:32,760
Speaker 1: idea that we need to stop flaming victims, stop putting

586
00:34:32,800 --> 00:34:36,920
Speaker 1: the onus and the responsibility on people who are targeted,

587
00:34:37,400 --> 00:34:40,839
Speaker 1: and move that onus and responsibility to tech companies and

588
00:34:40,880 --> 00:34:43,360
Speaker 1: tech platforms is one of the core reasons that I

589
00:34:43,440 --> 00:34:46,040
Speaker 1: started this podcast. The Prime Minister went on to say

590
00:34:46,040 --> 00:34:49,640
Speaker 1: that institutional misogyny being quote woven into the fabric of

591
00:34:49,680 --> 00:34:53,640
Speaker 1: our institutions means the problem has not been taken seriously enough.

592
00:34:54,160 --> 00:34:57,920
Speaker 1: Too often misogyny is excused, minimized, or ignored, the arguments

593
00:34:57,920 --> 00:35:01,200
Speaker 1: of women are dismissed as exaggerated or one off that

594
00:35:01,280 --> 00:35:05,840
Speaker 1: culture creates permission, Starmer wrote, So under these new rules,

595
00:35:06,360 --> 00:35:09,560
Speaker 1: victims and survivors could report images once, either to the

596
00:35:09,600 --> 00:35:13,000
Speaker 1: platform or to the media regulator in the UK OFFCOM

597
00:35:13,320 --> 00:35:17,800
Speaker 1: and that would trigger removal requests across multiple platforms simultaneously.

598
00:35:18,680 --> 00:35:21,719
Speaker 1: OFFCOME is also being asked to explore digital water marking

599
00:35:21,800 --> 00:35:25,000
Speaker 1: so that abusive images can be automatically detected every time

600
00:35:25,000 --> 00:35:30,320
Speaker 1: that's they're reposted. Creating or sharing non consensual digital images

601
00:35:30,320 --> 00:35:34,080
Speaker 1: would become a quote priority offense under the Online Safety Act,

602
00:35:34,320 --> 00:35:37,240
Speaker 1: putting it in the same category as child abuse material

603
00:35:37,440 --> 00:35:41,160
Speaker 1: or terrorism. OFFCOM would then be responsible for enforcing the

604
00:35:41,200 --> 00:35:44,040
Speaker 1: ban on the images, with the aim to remove that

605
00:35:44,200 --> 00:35:47,520
Speaker 1: burden or onus from the person targeted to need to

606
00:35:47,560 --> 00:35:50,560
Speaker 1: report the same image potentially thousands of times as it

607
00:35:50,640 --> 00:35:52,960
Speaker 1: just keeps continually getting reposted. And that was one of

608
00:35:52,960 --> 00:35:54,719
Speaker 1: the points that I made when talking about what was

609
00:35:54,760 --> 00:35:57,719
Speaker 1: happening with GROC here in the state, is that we

610
00:35:57,800 --> 00:36:01,480
Speaker 1: actually do have legislation to take a down Act, which

611
00:36:01,480 --> 00:36:04,440
Speaker 1: Ostensibly you might be thinking, well, why is that not

612
00:36:04,520 --> 00:36:07,160
Speaker 1: being triggered? And one of the reasons is is that

613
00:36:07,560 --> 00:36:12,320
Speaker 1: the person targeted has to make a complaint before anything happens,

614
00:36:12,320 --> 00:36:16,200
Speaker 1: and so if nobody makes that complaint, nothing happens, and

615
00:36:16,239 --> 00:36:18,720
Speaker 1: that really the burden really is on the person targeted

616
00:36:18,760 --> 00:36:20,479
Speaker 1: to do something to have it taken down.

617
00:36:20,640 --> 00:36:24,960
Speaker 2: So is forty eight hours feasible? Are companies going to

618
00:36:25,000 --> 00:36:27,520
Speaker 2: be able to do this even if they want to

619
00:36:27,520 --> 00:36:28,600
Speaker 2: comply with this new rule?

620
00:36:28,760 --> 00:36:31,239
Speaker 1: That is a great question. The Guardian spoke to the

621
00:36:31,320 --> 00:36:34,520
Speaker 1: Institute for Strategic Dialogue, which I should say I did

622
00:36:34,560 --> 00:36:36,520
Speaker 1: a bunch of work with in my former job. They

623
00:36:36,600 --> 00:36:40,480
Speaker 1: spoke to Ann Crannon, who researches online misogyny for ISD,

624
00:36:40,600 --> 00:36:44,400
Speaker 1: who said, I think that forty eight hours is certainly possible,

625
00:36:44,440 --> 00:36:46,960
Speaker 1: to be honest with you, The problem is it may

626
00:36:47,000 --> 00:36:50,759
Speaker 1: not necessarily incentivize a quicker response rate from companies, but

627
00:36:50,880 --> 00:36:53,600
Speaker 1: forty eight hours is longer than the timeframe for the

628
00:36:53,640 --> 00:36:56,600
Speaker 1: removal of other types of content, such as terrorist content

629
00:36:56,680 --> 00:37:00,440
Speaker 1: in the EU. She added that there are already existing

630
00:37:00,440 --> 00:37:03,960
Speaker 1: initiatives to use hash matching to protect victims of intimate abuse,

631
00:37:04,320 --> 00:37:07,360
Speaker 1: although it can be challenging to get different tech platforms

632
00:37:07,400 --> 00:37:10,840
Speaker 1: to coordinate among themselves so that an abusive video uploaded

633
00:37:10,920 --> 00:37:15,520
Speaker 1: to say, Facebook, for example, is automatically then detected on Reddit.

634
00:37:16,440 --> 00:37:19,000
Speaker 1: She's really careful to talk about the ways that hash

635
00:37:19,040 --> 00:37:25,360
Speaker 1: matching is not perfect technology and can be circumvented. Terrorist groups,

636
00:37:25,360 --> 00:37:29,279
Speaker 1: for example, often add small alterations to videos that have

637
00:37:29,320 --> 00:37:32,239
Speaker 1: already been hashed as terroristic content, or like they'll add

638
00:37:32,239 --> 00:37:35,799
Speaker 1: an emoji, and that will then make them unrecognizable to

639
00:37:35,840 --> 00:37:39,960
Speaker 1: hatchmashing systems. It's also the problem of AI tools and

640
00:37:40,040 --> 00:37:43,480
Speaker 1: AI deep things, so just make everything worse, allowing non

641
00:37:43,480 --> 00:37:47,160
Speaker 1: consensual intimate images and other content to be altered really

642
00:37:47,239 --> 00:37:50,920
Speaker 1: quickly and then spread across different pockets of the Internet,

643
00:37:51,120 --> 00:37:53,960
Speaker 1: which makes it a lot easier to evade attempts to

644
00:37:54,000 --> 00:37:56,759
Speaker 1: detect it quickly with tools like hashmashing.

645
00:37:57,320 --> 00:38:00,400
Speaker 2: I really think that that is a big part of

646
00:38:00,440 --> 00:38:04,800
Speaker 2: why it seems like things are becoming so bad so rapidly.

647
00:38:04,920 --> 00:38:10,360
Speaker 2: Is is just just AI allowing these pre existing structural

648
00:38:10,400 --> 00:38:14,040
Speaker 2: harms to happen so much faster, on such a wider scale,

649
00:38:14,160 --> 00:38:15,799
Speaker 2: so quickly, exactly.

650
00:38:15,880 --> 00:38:17,879
Speaker 1: And then you add to that the fact that you've

651
00:38:17,920 --> 00:38:22,080
Speaker 1: got platforms that are private or encrypted like Signal or WhatsApp,

652
00:38:22,080 --> 00:38:25,640
Speaker 1: where content is able to be traded and passed around

653
00:38:25,719 --> 00:38:27,799
Speaker 1: in ways that are harder to get a sense of.

654
00:38:28,320 --> 00:38:31,640
Speaker 1: And then the fact that you've got rogue websites or

655
00:38:31,680 --> 00:38:35,520
Speaker 1: fringe platforms that fall outside of the reach of legislation

656
00:38:35,680 --> 00:38:39,840
Speaker 1: like the Online Safety Act. They're just it's just tough,

657
00:38:39,880 --> 00:38:42,920
Speaker 1: and I think that a lot of what people like

658
00:38:43,040 --> 00:38:46,480
Speaker 1: me and advocates have been warning about it's here, you know,

659
00:38:46,560 --> 00:38:49,160
Speaker 1: this is what happened. This is what that looks like

660
00:38:49,280 --> 00:38:52,359
Speaker 1: when you have a climate where platforms are not being

661
00:38:52,440 --> 00:38:55,160
Speaker 1: held accountable. This is what it looks like. The people

662
00:38:55,160 --> 00:38:58,840
Speaker 1: who are harmed are women and young people, and the

663
00:38:58,840 --> 00:39:01,400
Speaker 1: people who get to just do whatever they want are

664
00:39:01,440 --> 00:39:04,160
Speaker 1: billionaires like Elon Musk who are getting rich off of it.

665
00:39:04,280 --> 00:39:11,080
Speaker 1: So I really think you're right. More after a quick break,

666
00:39:22,400 --> 00:39:27,800
Speaker 1: let's get right back into it. So, speaking of stuff

667
00:39:27,800 --> 00:39:31,120
Speaker 1: that I hate on the Internet, I have to quickly

668
00:39:31,360 --> 00:39:35,800
Speaker 1: talk about this frankly absurd. It would almost be funny

669
00:39:35,840 --> 00:39:40,600
Speaker 1: if it wasn't so enraging. Insight into how DOGE decided

670
00:39:41,200 --> 00:39:45,760
Speaker 1: what humanities programs were DEI and thus needed to be cut,

671
00:39:46,719 --> 00:39:51,360
Speaker 1: and it was being done by two totally unqualified bros

672
00:39:51,760 --> 00:39:57,440
Speaker 1: who literally just asked chat GPT. This is one of

673
00:39:57,480 --> 00:40:00,800
Speaker 1: those stories created in a lab to make me angry

674
00:40:00,840 --> 00:40:05,920
Speaker 1: and piss me off. Mission accomplished. Now bear in mind

675
00:40:06,320 --> 00:40:09,960
Speaker 1: that we are talking about federal grants that were already

676
00:40:10,000 --> 00:40:16,120
Speaker 1: approved after the full rigorous application and review process. So

677
00:40:16,719 --> 00:40:21,160
Speaker 1: if you're doing some interesting, important work in the humanities,

678
00:40:21,719 --> 00:40:25,480
Speaker 1: you write a vigorous grant application, it's submitted to the

679
00:40:25,480 --> 00:40:28,680
Speaker 1: federal government, the federal government. It's no joke. I've done

680
00:40:28,719 --> 00:40:30,799
Speaker 1: it and I've never gotten one of these grants. It

681
00:40:30,880 --> 00:40:33,320
Speaker 1: is no joke. It takes a long time. They really

682
00:40:33,520 --> 00:40:38,200
Speaker 1: there's very rigorous. Your application is approved, the money is approved.

683
00:40:39,080 --> 00:40:43,439
Speaker 1: It just takes two bozos using chat GBT to say up,

684
00:40:44,880 --> 00:40:49,280
Speaker 1: we're taking it back. So these grants were terminated by

685
00:40:49,320 --> 00:40:54,640
Speaker 1: these two random, inexperienced doged bros based on whether or

686
00:40:54,719 --> 00:40:57,840
Speaker 1: not chat GPT could explain in under one hundred and

687
00:40:57,920 --> 00:41:03,680
Speaker 1: twenty characters that they were quote related to DEI. We

688
00:41:03,840 --> 00:41:06,400
Speaker 1: know this thanks to a newly released complaint from the

689
00:41:06,440 --> 00:41:11,120
Speaker 1: author's guild against the government, which reveals how DOGE actually

690
00:41:11,160 --> 00:41:15,320
Speaker 1: decided which National Endowments for the Humanities grants to kill

691
00:41:15,760 --> 00:41:20,280
Speaker 1: after those grants had already been a worden so TECT reports.

692
00:41:20,719 --> 00:41:25,799
Speaker 1: Two young DOGE operatives, Nate Cavanaugh Comma, a college dropout

693
00:41:26,040 --> 00:41:30,320
Speaker 1: Love That Little ad Tector Great Detail, and Justin Fox,

694
00:41:30,480 --> 00:41:34,200
Speaker 1: a junior private equity associate, were given access to the

695
00:41:34,320 --> 00:41:37,840
Speaker 1: National Endowment for the Humanities and tasked with cutting grants.

696
00:41:38,040 --> 00:41:41,840
Speaker 1: Their method box built a keyword detection list with words

697
00:41:41,880 --> 00:41:47,960
Speaker 1: like lgbthugh, tribal, BIPOC, and immigrants. Notably absent were words

698
00:41:48,040 --> 00:41:52,800
Speaker 1: like white, Caucasian, or heterosexual. Then they fed the grant

699
00:41:52,840 --> 00:41:56,839
Speaker 1: descriptions into chat GBT, asking whether or not they were

700
00:41:56,920 --> 00:42:01,040
Speaker 1: quote related to DEI, requiring answer under one hundred and

701
00:42:01,040 --> 00:42:05,799
Speaker 1: twenty characters. Side note they couldn't even read more like

702
00:42:06,239 --> 00:42:09,799
Speaker 1: one hundred and twenty characters is so few characters.

703
00:42:10,400 --> 00:42:13,319
Speaker 2: So I'm guessing that there's a field like when you

704
00:42:13,320 --> 00:42:16,320
Speaker 2: submit for one of these grants, because I've never applied

705
00:42:16,320 --> 00:42:18,799
Speaker 2: for a National Endlment for the Humanities grant, but I've

706
00:42:18,840 --> 00:42:22,160
Speaker 2: applied to other federal agencies, and you know, it's a

707
00:42:22,200 --> 00:42:25,120
Speaker 2: whole automated system with different fields where you have to

708
00:42:25,120 --> 00:42:27,719
Speaker 2: pay stuff in, And I'm guessing that there was like

709
00:42:29,400 --> 00:42:32,120
Speaker 2: a description field that was limited to one hundred and

710
00:42:32,120 --> 00:42:36,200
Speaker 2: twenty characters, which is just the absolute shortest you could imagine.

711
00:42:36,400 --> 00:42:40,920
Speaker 2: That's that's what like ten words, maybe fifteen words.

712
00:42:40,600 --> 00:42:41,799
Speaker 1: It's like a sentence.

713
00:42:42,320 --> 00:42:45,160
Speaker 2: So I have two bodes to pick with this methodology,

714
00:42:45,160 --> 00:42:49,320
Speaker 2: which is like so stupid, but it's like extra extra

715
00:42:49,400 --> 00:42:53,400
Speaker 2: stupid for two reasons. One, they created a list of

716
00:42:53,440 --> 00:42:57,200
Speaker 2: words and then needed chat gpt to tell them whether

717
00:42:57,600 --> 00:43:00,800
Speaker 2: one of those words was present in a text string,

718
00:43:01,200 --> 00:43:03,919
Speaker 2: Like you don't need chat shept for that, So that's

719
00:43:03,960 --> 00:43:06,919
Speaker 2: one thing. And then the second is, yeah, why would

720
00:43:06,960 --> 00:43:10,960
Speaker 2: they use the shortest what I assume has to be

721
00:43:11,000 --> 00:43:13,560
Speaker 2: the shortest field, this one hundred and twenty character description.

722
00:43:15,600 --> 00:43:18,360
Speaker 2: Why not use the abstract which was probably you know,

723
00:43:18,400 --> 00:43:24,360
Speaker 2: maybe like five hundred characters or something. Just really dumb

724
00:43:24,440 --> 00:43:26,960
Speaker 2: execution of a dumb strategy.

725
00:43:27,239 --> 00:43:30,960
Speaker 1: Well, I think it's on it. It's purposeful, right, because

726
00:43:31,360 --> 00:43:34,640
Speaker 1: then you would actually have to consider the merit of

727
00:43:34,719 --> 00:43:37,400
Speaker 1: these grants, and they don't want to consider the merit

728
00:43:37,400 --> 00:43:39,920
Speaker 1: of these grants. They want to cut the grants. And

729
00:43:39,960 --> 00:43:42,800
Speaker 1: so if you did it that way, you might actually

730
00:43:42,840 --> 00:43:45,960
Speaker 1: get a clear or full picture of what these the

731
00:43:45,960 --> 00:43:48,440
Speaker 1: purpose of these grants and the merit of these grants.

732
00:43:48,680 --> 00:43:51,440
Speaker 1: They're not interested in that, And so I think it

733
00:43:51,560 --> 00:43:55,560
Speaker 1: being so stupid and sloppy and blunt is the point.

734
00:43:55,800 --> 00:43:59,080
Speaker 1: They probably put their stupidest assholes on it on purpose.

735
00:44:00,880 --> 00:44:05,680
Speaker 2: Yeah, these were probably like the dumbest guys on Team Doze. Yes,

736
00:44:05,920 --> 00:44:08,399
Speaker 2: they're like, oh, yeah, we want you to match some

737
00:44:08,560 --> 00:44:11,560
Speaker 2: text strings. See if you can figure out how to

738
00:44:11,560 --> 00:44:13,120
Speaker 2: do it with an LM.

739
00:44:13,320 --> 00:44:16,080
Speaker 1: Like the like, the stupidity is the point, I think.

740
00:44:16,520 --> 00:44:19,400
Speaker 1: And so the grants that were flagged by CHATCHBT were

741
00:44:19,440 --> 00:44:22,600
Speaker 1: then canceled, even though the grants were already awarded. Experts

742
00:44:22,680 --> 00:44:25,719
Speaker 1: at any age who could have provided any kind of

743
00:44:25,760 --> 00:44:30,040
Speaker 1: context were blocked from pushing back the acting director, whose

744
00:44:30,040 --> 00:44:34,799
Speaker 1: signature appeared on one four hundred termination emails sent from

745
00:44:34,800 --> 00:44:35,560
Speaker 1: a private server.

746
00:44:36,440 --> 00:44:39,279
Speaker 2: You know, you would really expect an email like this

747
00:44:39,400 --> 00:44:43,400
Speaker 2: coming from an agency director to come from an official

748
00:44:43,440 --> 00:44:47,400
Speaker 2: agency server. In fact, I'm pretty sure there are laws

749
00:44:47,560 --> 00:44:53,879
Speaker 2: requiring that for like records retention reasons. So just one

750
00:44:53,960 --> 00:44:59,000
Speaker 2: more dumb piece of the execution here, sending it from

751
00:44:59,000 --> 00:44:59,760
Speaker 2: a private server.

752
00:45:00,120 --> 00:45:04,640
Speaker 1: Well, that acting any h head later admitted they had

753
00:45:04,680 --> 00:45:08,600
Speaker 1: no idea which grants were cut and why. Basically, I

754
00:45:08,640 --> 00:45:12,600
Speaker 1: don't know, couldn't even tell you. Among the grant casualties

755
00:45:12,640 --> 00:45:16,520
Speaker 1: were grants on the Colfax massacre that happened in eighteen

756
00:45:16,640 --> 00:45:20,239
Speaker 1: seventy three in Colfax, Louisiana. We're in a group of

757
00:45:20,640 --> 00:45:23,000
Speaker 1: sixty two to one hundred and fifty three black men

758
00:45:23,080 --> 00:45:26,520
Speaker 1: were murdered while surrendering to a mob of former Confederate

759
00:45:26,600 --> 00:45:30,360
Speaker 1: soldiers and members of the KKK Jewish women slave labor

760
00:45:30,400 --> 00:45:33,680
Speaker 1: and during the Holocaust, Native American boarding schools, and the

761
00:45:33,719 --> 00:45:36,680
Speaker 1: women pilots of World War Two who were denied entry

762
00:45:36,719 --> 00:45:39,920
Speaker 1: because of their race. So this discovery came through a

763
00:45:40,000 --> 00:45:44,240
Speaker 1: lawsuit by the Authors Guild, and the details are as

764
00:45:44,480 --> 00:45:48,239
Speaker 1: bad as you would imagine. Just like two guys with

765
00:45:48,400 --> 00:45:54,360
Speaker 1: absolutely no humanities experience, and this culture war key list

766
00:45:54,440 --> 00:45:59,560
Speaker 1: that somebody cooked up asking CHADJBT to make funding decisions

767
00:45:59,760 --> 00:46:04,200
Speaker 1: that actual experts had spent months reviewing. And again this

768
00:46:04,360 --> 00:46:07,799
Speaker 1: money had already been awarded, So taking away money that

769
00:46:07,840 --> 00:46:10,960
Speaker 1: had already already been they'd gone through this regorous process

770
00:46:11,080 --> 00:46:12,439
Speaker 1: that had already been dolled out.

771
00:46:12,800 --> 00:46:18,960
Speaker 2: You know, it's as comically stupid as these two guys'

772
00:46:18,960 --> 00:46:24,080
Speaker 2: execution was. It's the consequences are quite real, right, Like

773
00:46:24,080 --> 00:46:30,719
Speaker 2: those grants were canceled and these important, if uncomfortable histories

774
00:46:32,640 --> 00:46:36,800
Speaker 2: are not being studied or told or whatever the purpose

775
00:46:36,840 --> 00:46:41,759
Speaker 2: of these grants was, right. I think it connects with

776
00:46:41,960 --> 00:46:45,560
Speaker 2: what we talked about last week to save our Signs campaign,

777
00:46:46,560 --> 00:46:51,840
Speaker 2: because this is right in lockstep with the administration's larger

778
00:46:52,480 --> 00:46:58,080
Speaker 2: efforts to erase all of these aspects of American history

779
00:46:58,800 --> 00:47:02,720
Speaker 2: that they don't like, that paint white people in anything

780
00:47:02,760 --> 00:47:07,560
Speaker 2: other than the most flattering picture. They give any sort

781
00:47:07,600 --> 00:47:13,120
Speaker 2: of pause to the idea that America is like the

782
00:47:13,160 --> 00:47:16,960
Speaker 2: best and pure and has never made any mistakes. And

783
00:47:17,000 --> 00:47:22,560
Speaker 2: it's such a dangerous thing to try to do to

784
00:47:22,760 --> 00:47:26,440
Speaker 2: erase that history rather than try to learn from it

785
00:47:26,480 --> 00:47:27,320
Speaker 2: and move forward.

786
00:47:27,840 --> 00:47:30,120
Speaker 1: That is a good reminder. Shout out to one of

787
00:47:30,120 --> 00:47:34,920
Speaker 1: our listeners, Deb. We will put Deb's call to document

788
00:47:35,080 --> 00:47:37,560
Speaker 1: signs that you see for the Save our Science project

789
00:47:37,719 --> 00:47:41,400
Speaker 1: in the show notes. It's very important to preserve our history,

790
00:47:41,440 --> 00:47:45,480
Speaker 1: even the history that is uncomfortable or heaven forbid, paints

791
00:47:45,520 --> 00:47:49,720
Speaker 1: white people and unflattering light despite being absolutely historically accurate

792
00:47:49,760 --> 00:47:53,120
Speaker 1: and truthful. I have a related story, which is that

793
00:47:53,560 --> 00:47:58,160
Speaker 1: the EEOC, the Equal Employment Opportunity Commission, which is the

794
00:47:58,200 --> 00:48:01,920
Speaker 1: federal civil rights agency that is supposed to sort of

795
00:48:02,719 --> 00:48:06,960
Speaker 1: represent workers who have been legitimately discriminated against. Has A

796
00:48:07,000 --> 00:48:11,839
Speaker 1: filed its first DEI related lawsuit of the Trump era,

797
00:48:12,360 --> 00:48:16,040
Speaker 1: and that is against a Coca Cola bottler in New England. So,

798
00:48:16,520 --> 00:48:19,240
Speaker 1: if you listen to this show, we've definitely talked about

799
00:48:19,560 --> 00:48:24,240
Speaker 1: shocking cases of discrimination where people have been genuinely harmed.

800
00:48:25,400 --> 00:48:28,360
Speaker 1: Hold onto your hat. You're not gonna believe it's the

801
00:48:28,520 --> 00:48:31,920
Speaker 1: harm that happened in this case. So this is the allegation.

802
00:48:33,600 --> 00:48:38,600
Speaker 1: Coca Cola hosted a two day networking event for about

803
00:48:38,640 --> 00:48:43,160
Speaker 1: two hundred and fifty female employees at a Connecticut casino.

804
00:48:44,320 --> 00:48:48,680
Speaker 1: Get this, the men were not invited.

805
00:48:49,280 --> 00:48:53,000
Speaker 2: Just perpetuating that girls club smoking cigars.

806
00:48:54,080 --> 00:48:57,160
Speaker 1: For too long, women have had their boot on the

807
00:48:57,160 --> 00:49:00,000
Speaker 1: neck of the white American male worker, and it's high

808
00:49:00,120 --> 00:49:03,040
Speaker 1: time we did something about it. So y'all might remember

809
00:49:03,120 --> 00:49:07,600
Speaker 1: that back in December, the EEOC chair Andrea Lucas posted

810
00:49:07,600 --> 00:49:13,360
Speaker 1: this video really just explicitly asking white men, do you

811
00:49:13,480 --> 00:49:17,400
Speaker 1: feel you have been discriminated against at your job? Let

812
00:49:17,560 --> 00:49:20,799
Speaker 1: us know. We will file a lawsuit. So the kind

813
00:49:20,840 --> 00:49:25,760
Speaker 1: of cases that the EEOC typically takes on involve people

814
00:49:25,800 --> 00:49:31,160
Speaker 1: who have been measurably clearly harmed by their employers because

815
00:49:31,160 --> 00:49:36,160
Speaker 1: of discrimination. Right. We've covered things like pregnant women being

816
00:49:36,239 --> 00:49:40,720
Speaker 1: fired for being pregnant right before giving birth, or nursing

817
00:49:40,800 --> 00:49:43,360
Speaker 1: parents being let go because they need to pump on

818
00:49:43,440 --> 00:49:47,960
Speaker 1: the job, workers with cancer or MS or diabetes who

819
00:49:48,040 --> 00:49:51,640
Speaker 1: lost their jobs and subsequently their health insurance because their

820
00:49:51,680 --> 00:49:54,480
Speaker 1: employer would not make reasonable accommodations.

821
00:49:54,680 --> 00:49:59,120
Speaker 2: They're also the agency that sued Tesla for racial discrimination

822
00:49:59,280 --> 00:50:02,800
Speaker 2: in its factory that was found to be widespread.

823
00:50:03,440 --> 00:50:06,960
Speaker 1: Yeah. They In twenty fifteen, they sued BMW, and BMW

824
00:50:07,040 --> 00:50:09,239
Speaker 1: had to pay back one point six million dollars to

825
00:50:09,320 --> 00:50:12,680
Speaker 1: black workers who were screened out by a background chech

826
00:50:12,760 --> 00:50:18,000
Speaker 1: policy the EEOC successfully argued had a racially disparate impact. Right.

827
00:50:18,040 --> 00:50:22,680
Speaker 1: And so historically this is what the EEOC has been

828
00:50:22,880 --> 00:50:28,080
Speaker 1: used for cases where there has been a clear measurable harm.

829
00:50:28,560 --> 00:50:32,280
Speaker 1: It is not typical for the EEOC to sue because

830
00:50:32,600 --> 00:50:36,400
Speaker 1: men were not invited explicitly to a networking event.

831
00:50:39,960 --> 00:50:54,239
Speaker 3: More. After a quick break, let's get right back into it.

832
00:50:57,520 --> 00:51:01,360
Speaker 1: So this first lawsuit under the Trump administration sort of

833
00:51:01,440 --> 00:51:06,040
Speaker 1: new focus around this is claiming that the diversity focused

834
00:51:06,080 --> 00:51:11,320
Speaker 1: workplace program is itself unlawful. They're also investigating Nike and

835
00:51:11,400 --> 00:51:15,239
Speaker 1: Northwest Mutual for allegedly discriminating against white workers, and of

836
00:51:15,280 --> 00:51:17,480
Speaker 1: course we talked about it on the show, but also

837
00:51:17,800 --> 00:51:22,360
Speaker 1: demanded DEI policy information from about twenty major law firms.

838
00:51:22,680 --> 00:51:26,120
Speaker 1: This Coke case is kind of being seen as a

839
00:51:26,239 --> 00:51:30,040
Speaker 1: test for how far the Trump administration is willing to

840
00:51:30,080 --> 00:51:33,200
Speaker 1: push DEI when it comes to the private sector. We

841
00:51:33,320 --> 00:51:35,840
Speaker 1: talked about this on the show before, but when Trump

842
00:51:35,920 --> 00:51:39,319
Speaker 1: was reelected, a lot of companies just Trump administration did

843
00:51:39,320 --> 00:51:41,520
Speaker 1: not ask them to do this yet, but they just

844
00:51:41,640 --> 00:51:48,320
Speaker 1: immediately pulled their DEI initiatives. Companies like Target. Meanwhile, Costco

845
00:51:48,960 --> 00:51:51,479
Speaker 1: was asked to do the same thing. Costco basically said,

846
00:51:51,600 --> 00:51:54,560
Speaker 1: kick Rock, We'll do what we want. Diversity and inclusion

847
00:51:54,680 --> 00:51:58,320
Speaker 1: is making us money, so we're going to continue making money.

848
00:51:58,640 --> 00:52:01,480
Speaker 1: They are not suffering this kind of economic woes that

849
00:52:01,560 --> 00:52:05,200
Speaker 1: Target is experiencing. I almost wonder how much of this

850
00:52:05,320 --> 00:52:09,520
Speaker 1: is the Trump administration saying, hey, companies, wouldn't it be

851
00:52:09,640 --> 00:52:14,080
Speaker 1: great if you abandoned all the people who are making

852
00:52:14,120 --> 00:52:18,760
Speaker 1: you money by publicly backing away from DEI initiatives. Don't

853
00:52:18,760 --> 00:52:22,400
Speaker 1: you want the opportunity to be as financially and economically

854
00:52:22,480 --> 00:52:25,080
Speaker 1: uncertain as Target right now? Don't you? Don't you look

855
00:52:25,080 --> 00:52:27,680
Speaker 1: at the CEO of Target and think that should be me.

856
00:52:28,160 --> 00:52:29,880
Speaker 1: We'll get in line and do what we say.

857
00:52:30,080 --> 00:52:32,480
Speaker 2: Yeah, it's got to be a pretty tough sell. Which, yeah,

858
00:52:32,520 --> 00:52:34,920
Speaker 2: maybe you're right. Maybe that's why they're just coming out

859
00:52:34,960 --> 00:52:37,520
Speaker 2: and suing these companies to get them to do it,

860
00:52:37,560 --> 00:52:43,239
Speaker 2: because clearly, as Target has learned, it's not a very

861
00:52:43,280 --> 00:52:45,719
Speaker 2: financially rewarding way to go.

862
00:52:45,880 --> 00:52:49,080
Speaker 1: So this employment attorney daphneed Delvo that I follow on

863
00:52:49,120 --> 00:52:52,480
Speaker 1: Threads put it very well. She writes, women hold roughly

864
00:52:52,640 --> 00:52:56,640
Speaker 1: ten percent of fortune, five hundred CEO positions, earn less

865
00:52:56,680 --> 00:52:59,759
Speaker 1: and virtually every occupation, and face a wage penalty for

866
00:52:59,760 --> 00:53:03,759
Speaker 1: having children, while fathers get a bonus. White men are

867
00:53:03,800 --> 00:53:09,600
Speaker 1: not a systematically excluded group. Individual discomfort is not structural discrimination.

868
00:53:09,960 --> 00:53:11,719
Speaker 2: I think that's such a good point to make. That

869
00:53:11,800 --> 00:53:18,360
Speaker 2: the reason the EEOC exists is to address structural discrimination.

870
00:53:18,560 --> 00:53:18,680
Speaker 3: Right.

871
00:53:18,680 --> 00:53:22,200
Speaker 2: It came out of the Civil Rights era as a

872
00:53:22,239 --> 00:53:29,840
Speaker 2: way to address some of these entrenched structural factors and

873
00:53:29,920 --> 00:53:37,200
Speaker 2: forces that were systematically disadvantaging certain groups of people, and

874
00:53:37,360 --> 00:53:40,719
Speaker 2: a lot of those disadvantages still exist. You know, you

875
00:53:40,760 --> 00:53:44,880
Speaker 2: know you just mentioned leadership positions. We could also look

876
00:53:44,880 --> 00:53:48,080
Speaker 2: at wages, right like, there is still a big pay gap.

877
00:53:48,200 --> 00:53:52,960
Speaker 2: That is why the EEOC is supposed to exist to

878
00:53:53,000 --> 00:53:57,759
Speaker 2: eliminate practices that are perpetuating that wage gap. And the

879
00:53:57,800 --> 00:54:02,719
Speaker 2: Trump administration just fundamental acts as if things like the

880
00:54:02,760 --> 00:54:06,640
Speaker 2: wage gap or the leadership gap at the top of

881
00:54:06,920 --> 00:54:11,000
Speaker 2: Fortune five hundred companies doesn't exist, and that the only

882
00:54:11,040 --> 00:54:17,200
Speaker 2: thing that matters is the personal comfort of white men

883
00:54:17,280 --> 00:54:21,360
Speaker 2: working in a Coca Cola factory in Connecticut. It's so

884
00:54:22,600 --> 00:54:25,400
Speaker 2: it's tempting to stay its short sighted, but they know

885
00:54:25,480 --> 00:54:28,880
Speaker 2: exactly what they're doing, right Like they are interested in

886
00:54:28,960 --> 00:54:34,000
Speaker 2: actively perpetuating white supremacy and patriarchy.

887
00:54:34,239 --> 00:54:37,719
Speaker 1: Yes, and that employment attorney, I think she's so right.

888
00:54:38,200 --> 00:54:40,480
Speaker 1: She exactly put it that way. She says, this is

889
00:54:40,480 --> 00:54:43,960
Speaker 1: about discouraging women from gathering, because when women gather, we

890
00:54:44,040 --> 00:54:47,760
Speaker 1: compare notes, we identify patterns, we realize our collective power

891
00:54:48,160 --> 00:54:52,160
Speaker 1: of everything. This administration could have chosen to prosecute wage theft,

892
00:54:52,360 --> 00:54:56,440
Speaker 1: pragnicy discrimination, mass layoffs. They chose this. That tells you

893
00:54:56,520 --> 00:54:59,800
Speaker 1: exactly who they consider a priority and who they consider

894
00:55:00,239 --> 00:55:03,520
Speaker 1: a threat. They're so scared of our stories that they're

895
00:55:03,560 --> 00:55:07,880
Speaker 1: suing to stop them. Heaven from accounting missed some appetizers,

896
00:55:08,040 --> 00:55:10,879
Speaker 1: and that is what the federal government decided was worth

897
00:55:10,920 --> 00:55:15,400
Speaker 1: its litigation power. And it's actually kind of funny because

898
00:55:15,520 --> 00:55:18,959
Speaker 1: I saw this piece in Bloomberg called white Men Learn

899
00:55:19,040 --> 00:55:22,560
Speaker 1: the Hidden Costs of Suing for Discrimination, all about these

900
00:55:22,640 --> 00:55:28,200
Speaker 1: white men who kind of had their grievances, the professional

901
00:55:28,200 --> 00:55:32,280
Speaker 1: grievances nursed by the Trump administration and decided to sue

902
00:55:32,320 --> 00:55:35,839
Speaker 1: their employers for what they felt was discrimination against them

903
00:55:35,880 --> 00:55:40,400
Speaker 1: as white men. They talked to this newscaster named Vaughn

904
00:55:40,840 --> 00:55:43,960
Speaker 1: who said that, you know, he had been a newscaster

905
00:55:44,400 --> 00:55:47,400
Speaker 1: and that when they made when the news outlet made

906
00:55:47,440 --> 00:55:50,360
Speaker 1: their video of all the newscasters, he was not featured

907
00:55:50,400 --> 00:55:53,200
Speaker 1: in it. He didn't get a billboard. And then they

908
00:55:53,200 --> 00:55:57,000
Speaker 1: did a diversity initiative, and then they hired a black newscaster,

909
00:55:57,160 --> 00:56:01,080
Speaker 1: and that black newscaster got a billboard. Now the news

910
00:56:01,120 --> 00:56:03,920
Speaker 1: outlet is quoted as saying, oh no, this person was

911
00:56:04,040 --> 00:56:08,360
Speaker 1: fired for cause for documented performance issues. The article reads,

912
00:56:08,719 --> 00:56:11,759
Speaker 1: if the Trump administration has its way, more suits like

913
00:56:11,840 --> 00:56:14,400
Speaker 1: Vaughn's will come before the courts as the government seeks

914
00:56:14,400 --> 00:56:17,439
Speaker 1: to redress what it sees a discrimination against white men.

915
00:56:17,800 --> 00:56:21,640
Speaker 1: In December, the EEOC urged white men to come forward

916
00:56:21,640 --> 00:56:25,320
Speaker 1: with complaints about their treatment by employers looking to diversify

917
00:56:25,440 --> 00:56:29,560
Speaker 1: their workforces. However, many of the white men doing so

918
00:56:29,880 --> 00:56:33,600
Speaker 1: are confronting the same blunt reality as countless employees of

919
00:56:33,680 --> 00:56:38,000
Speaker 1: other genders, races, or sexual orientations who have stood up

920
00:56:38,040 --> 00:56:42,680
Speaker 1: to corporate hr over perceived wrongdoing. Bringing a lawsuit against

921
00:56:42,719 --> 00:56:47,360
Speaker 1: your employer may well damage your career, and so basically,

922
00:56:48,000 --> 00:56:52,160
Speaker 1: this person Vaughn says that he cannot find a steady,

923
00:56:52,200 --> 00:56:56,000
Speaker 1: stable job that pays what his old job paid after

924
00:56:56,120 --> 00:56:59,680
Speaker 1: suing his former employer, and you know, he's in a

925
00:56:59,719 --> 00:57:02,560
Speaker 1: sick sees now and like it's a lot harder to

926
00:57:02,600 --> 00:57:04,920
Speaker 1: find employment. And having this, he says he does not

927
00:57:05,000 --> 00:57:08,480
Speaker 1: regret doing the lawsuit, but the lawsuit is part of,

928
00:57:08,680 --> 00:57:12,720
Speaker 1: he says, why he is having trouble replacing that work.

929
00:57:12,760 --> 00:57:17,200
Speaker 1: And basically, these white men who are suing their employers

930
00:57:17,480 --> 00:57:20,880
Speaker 1: are finding out the hard way what women and queer

931
00:57:20,880 --> 00:57:24,480
Speaker 1: folks and trans folks and pupil of color and pregnant

932
00:57:24,480 --> 00:57:29,720
Speaker 1: people and other minoritized populations have been known that standing

933
00:57:29,800 --> 00:57:33,840
Speaker 1: up for yourself and suing can hurt your career. Now

934
00:57:33,960 --> 00:57:37,360
Speaker 1: it is complicated because I do think that just across

935
00:57:37,400 --> 00:57:40,320
Speaker 1: the board, we need better protections for people who speak

936
00:57:40,400 --> 00:57:43,960
Speaker 1: up around real workplace harm and people who blow the

937
00:57:43,960 --> 00:57:47,120
Speaker 1: whistle on things like abuse and discrimination. But it's like

938
00:57:47,200 --> 00:57:50,280
Speaker 1: these guys want to play the part of being a

939
00:57:50,400 --> 00:57:55,560
Speaker 1: marginalized oppressed class without actually having realized that, oh, being

940
00:57:55,600 --> 00:58:01,200
Speaker 1: a marginalized oppressed person comes with real economics advantages that

941
00:58:01,280 --> 00:58:03,800
Speaker 1: we've known about for a really long time. Women and

942
00:58:03,800 --> 00:58:06,720
Speaker 1: people who sue their employers for discrimination, they have talked

943
00:58:06,720 --> 00:58:10,200
Speaker 1: about this kind of thing. But these white men are like, oh,

944
00:58:10,320 --> 00:58:13,240
Speaker 1: I want to say I'm the victim without having to

945
00:58:13,280 --> 00:58:17,200
Speaker 1: incur the actual real costs that we know that victims

946
00:58:17,280 --> 00:58:21,080
Speaker 1: just have to eat when they speak up. But that said,

947
00:58:22,160 --> 00:58:24,440
Speaker 1: in my opinion, that is not what is going on

948
00:58:24,520 --> 00:58:28,520
Speaker 1: with these cases, because the piece points out rightly, men

949
00:58:28,600 --> 00:58:32,160
Speaker 1: still make up ninety percent of chief executive officers at

950
00:58:32,240 --> 00:58:34,640
Speaker 1: S and P five hundred companies, as well as about

951
00:58:34,640 --> 00:58:37,840
Speaker 1: three quarters of all C suite employees, and the proportion

952
00:58:37,960 --> 00:58:40,680
Speaker 1: of black men or women who have held the top

953
00:58:40,800 --> 00:58:44,920
Speaker 1: job is extremely small, currently hovering at about one percent,

954
00:58:45,400 --> 00:58:47,400
Speaker 1: and these white men were like, h we were like

955
00:58:47,440 --> 00:58:50,800
Speaker 1: that one percent too, because equal right. If I don't

956
00:58:50,800 --> 00:58:54,160
Speaker 1: get that one percent as well, that's discrimination against me.

957
00:58:54,360 --> 00:58:58,240
Speaker 2: Actually, actually I heard they have mini keiches at that mixer.

958
00:58:58,680 --> 00:59:00,240
Speaker 2: I don't get any MANI keishes.

959
00:59:00,880 --> 00:59:05,120
Speaker 1: Yeah, like you missed the happy hour, dude, calm down.

960
00:59:05,800 --> 00:59:08,400
Speaker 1: The article also talked to this guy who sued Meta

961
00:59:08,520 --> 00:59:12,240
Speaker 1: because Meta, at the time had an apprenticeship program for

962
00:59:12,520 --> 00:59:16,640
Speaker 1: minority applicants and that ever since he sued Meta, he

963
00:59:16,680 --> 00:59:19,200
Speaker 1: has had a hard time finding work ever since. The

964
00:59:19,320 --> 00:59:23,720
Speaker 1: article says the program offered ethnic minority workers opportunities to

965
00:59:23,800 --> 00:59:27,000
Speaker 1: shadow professionals and learn new skills, and this guy said

966
00:59:27,000 --> 00:59:29,920
Speaker 1: that while working on a contract job for Meta, one

967
00:59:29,960 --> 00:59:32,520
Speaker 1: of those apprentices was given a title and a role

968
00:59:32,600 --> 00:59:36,920
Speaker 1: superior to him, even though in his view, that person

969
00:59:37,160 --> 00:59:41,400
Speaker 1: had less experience. So Meta and other defendants said in

970
00:59:41,440 --> 00:59:44,840
Speaker 1: illegal filing that this person actually never even applied for

971
00:59:44,920 --> 00:59:48,040
Speaker 1: the role in question and was simply not eligible for

972
00:59:48,080 --> 00:59:51,440
Speaker 1: that program, and also lacked the legal standing to sue

973
00:59:51,440 --> 00:59:53,919
Speaker 1: over it. His case was dismissed in twenty twenty four

974
00:59:54,000 --> 00:59:58,160
Speaker 1: and now is pending appeal. So I think so much

975
00:59:58,200 --> 01:00:00,960
Speaker 1: of this is exactly what you were just talking about,

976
01:00:01,240 --> 01:00:05,440
Speaker 1: because I am seeing a lot of white men being

977
01:00:05,480 --> 01:00:10,240
Speaker 1: told anytime somebody gets something that they want, it is

978
01:00:10,280 --> 01:00:14,520
Speaker 1: an injustice. Anytime something doesn't go their way, it is

979
01:00:14,560 --> 01:00:17,960
Speaker 1: an injustice. And I think that's really the crux of

980
01:00:18,000 --> 01:00:22,160
Speaker 1: the problem. That nobody can ever be just more qualified

981
01:00:22,240 --> 01:00:26,080
Speaker 1: for you or better positioned for a role, especially if

982
01:00:26,080 --> 01:00:29,360
Speaker 1: the person that gets something that you want is black,

983
01:00:29,600 --> 01:00:33,880
Speaker 1: or trans or queer or otherwise the minoritized person, that

984
01:00:34,040 --> 01:00:37,960
Speaker 1: is an injustice. And we now have a dynamic where

985
01:00:38,400 --> 01:00:42,680
Speaker 1: that kind of white male grievance is being codified into

986
01:00:42,680 --> 01:00:45,880
Speaker 1: a kind of legitimate public policy. You will have the

987
01:00:45,920 --> 01:00:50,480
Speaker 1: federal government deciding that it's legal authority and ability to

988
01:00:50,640 --> 01:00:55,120
Speaker 1: sue companies and individuals will come down on protecting that

989
01:00:55,600 --> 01:01:00,800
Speaker 1: very fragile white male need to get what they feel

990
01:01:00,840 --> 01:01:03,200
Speaker 1: they deserve. And I think that's exactly what we're seeing

991
01:01:03,240 --> 01:01:06,439
Speaker 1: play out here. I see the same thing playing out

992
01:01:06,480 --> 01:01:09,880
Speaker 1: in conversations about who gets into college. You can just

993
01:01:10,280 --> 01:01:14,280
Speaker 1: blame all of your problems or shortcomings, or maybe maybe

994
01:01:14,280 --> 01:01:16,880
Speaker 1: they're not even shortcomings, maybe they're just things that didn't

995
01:01:16,880 --> 01:01:23,760
Speaker 1: go your way on this hypothetical mythical unqualified, minoritized person

996
01:01:23,920 --> 01:01:27,880
Speaker 1: who got something that you saw was as rightfully yours

997
01:01:28,080 --> 01:01:31,120
Speaker 1: and now you want to sue about it. And again,

998
01:01:31,240 --> 01:01:33,920
Speaker 1: I mean we've talked about this on the show so often.

999
01:01:34,280 --> 01:01:36,800
Speaker 1: They don't give us shit if a black let me

1000
01:01:36,800 --> 01:01:39,120
Speaker 1: tell you something, if a black woman gets into a

1001
01:01:39,120 --> 01:01:42,280
Speaker 1: C suite, people are pissed about it, and it's just

1002
01:01:42,400 --> 01:01:44,520
Speaker 1: got there because she earned it, it because she was like

1003
01:01:44,840 --> 01:01:47,880
Speaker 1: better than everybody. They don't, they would not allow they

1004
01:01:47,880 --> 01:01:52,280
Speaker 1: would not allow people into these positions willy nilly if

1005
01:01:52,280 --> 01:01:54,880
Speaker 1: we were not qualified. And so yeah, I just I

1006
01:01:55,000 --> 01:01:59,840
Speaker 1: just hate how our current government is allowing for these

1007
01:02:00,040 --> 01:02:04,720
Speaker 1: feelings of grievance. We all have to experience not getting

1008
01:02:04,760 --> 01:02:07,440
Speaker 1: things that we want in life, that's life as an adult.

1009
01:02:07,640 --> 01:02:12,920
Speaker 1: But telling people no, anytime you've experienced having to watch

1010
01:02:12,960 --> 01:02:15,720
Speaker 1: somebody get something that you wanted, it's not just that

1011
01:02:15,760 --> 01:02:19,200
Speaker 1: things didn't go your way, you are being discriminated against.

1012
01:02:19,400 --> 01:02:21,040
Speaker 1: That's what I think is so insidious.

1013
01:02:21,360 --> 01:02:27,200
Speaker 2: And that's their whole campaign, just encouraging grievance, nursing grievances.

1014
01:02:27,680 --> 01:02:30,919
Speaker 1: Yes, it is all about grievance with these people. And

1015
01:02:31,160 --> 01:02:34,480
Speaker 1: you know, last week I was talking about how I

1016
01:02:34,520 --> 01:02:36,280
Speaker 1: took a break from the news round up because of

1017
01:02:36,280 --> 01:02:38,960
Speaker 1: it just getting me down. I'm going to try to

1018
01:02:39,080 --> 01:02:43,880
Speaker 1: be intentional about including a win or a positive story

1019
01:02:44,040 --> 01:02:48,120
Speaker 1: in every episode. And we actually do have a positive

1020
01:02:48,160 --> 01:02:52,200
Speaker 1: story as it pertains to the Trump administration and DEI initiatives,

1021
01:02:52,240 --> 01:02:55,520
Speaker 1: because this week the Trump administration agreed to drop its

1022
01:02:55,640 --> 01:03:00,360
Speaker 1: ban on DEI initiatives in public schools nationally, which is

1023
01:03:00,440 --> 01:03:03,400
Speaker 1: great news. A federal judge dismissed a case in New

1024
01:03:03,400 --> 01:03:06,720
Speaker 1: Hampshire this week, which then triggered the administration to dropping

1025
01:03:06,760 --> 01:03:10,000
Speaker 1: the ban nationwide. We covered a little bit of the

1026
01:03:10,160 --> 01:03:14,720
Speaker 1: fallout of the administration's attacks on anything even remotely related

1027
01:03:15,000 --> 01:03:18,240
Speaker 1: to DEI, so this is very positive news. So New

1028
01:03:18,240 --> 01:03:22,640
Speaker 1: Hampshire's largest teachers union for school districts and civil rights

1029
01:03:22,640 --> 01:03:25,960
Speaker 1: groups like the ACLU sued the Trump administration last year,

1030
01:03:26,520 --> 01:03:29,560
Speaker 1: arguing that the ban violated free speech and equal protection.

1031
01:03:30,240 --> 01:03:33,600
Speaker 1: This was pretty serious. Schools risked losing federal funding if

1032
01:03:33,640 --> 01:03:37,040
Speaker 1: they did not comply. The administration then told the court

1033
01:03:37,320 --> 01:03:39,960
Speaker 1: that it would not withhold federal funding from schools that

1034
01:03:40,040 --> 01:03:44,680
Speaker 1: maintained DEI programs. Didn't really give an explanation for why

1035
01:03:44,520 --> 01:03:48,480
Speaker 1: they were pulling this, but a similar challenge in Maryland

1036
01:03:48,600 --> 01:03:51,720
Speaker 1: got the same result. Teachers at this point were saying

1037
01:03:51,760 --> 01:03:55,600
Speaker 1: that this ban had them afraid to teach basic American

1038
01:03:55,760 --> 01:03:58,440
Speaker 1: history because they were worried that lessons on things like

1039
01:03:58,560 --> 01:04:03,720
Speaker 1: racism or discriminate could trigger an investigation and potentially cost

1040
01:04:03,800 --> 01:04:08,040
Speaker 1: schools their funding. According to the ACLU's guiles of the Sinnett,

1041
01:04:08,480 --> 01:04:11,520
Speaker 1: the lawsuit forced the government to prove the necessity for

1042
01:04:11,600 --> 01:04:14,600
Speaker 1: why they're doing what they're doing, and here they certainly

1043
01:04:14,600 --> 01:04:17,280
Speaker 1: could not do that. This is the case where teachers

1044
01:04:17,280 --> 01:04:20,400
Speaker 1: and civil rights groups really pushed back and held the

1045
01:04:20,480 --> 01:04:26,040
Speaker 1: line and one, and in the process protected classrooms nationwide

1046
01:04:26,320 --> 01:04:30,440
Speaker 1: without the need to have a single trial. Two separate

1047
01:04:30,520 --> 01:04:34,680
Speaker 1: New Hampshire state level laws restricting DEI and limiting teaching

1048
01:04:34,720 --> 01:04:37,880
Speaker 1: around racism are still being challenged in court. So, like,

1049
01:04:38,280 --> 01:04:39,720
Speaker 1: I don't want to give the impression that the fight

1050
01:04:39,800 --> 01:04:42,840
Speaker 1: is entirely over, but I'm going to take this as

1051
01:04:42,840 --> 01:04:45,000
Speaker 1: a win, giving all, given all that we talked about

1052
01:04:45,040 --> 01:04:45,720
Speaker 1: in this episode.

1053
01:04:46,160 --> 01:04:49,680
Speaker 2: Absolutely it's a win. I saw on I was on

1054
01:04:49,720 --> 01:04:52,720
Speaker 2: Blue Sky when this happened, and it was so interesting

1055
01:04:52,720 --> 01:04:55,400
Speaker 2: to me that so many people seem to want to

1056
01:04:55,520 --> 01:04:59,720
Speaker 2: like diminish the importance of this win and be like, oh, well,

1057
01:05:00,320 --> 01:05:02,240
Speaker 2: they're just gonna find some other way to do it,

1058
01:05:02,280 --> 01:05:05,440
Speaker 2: and like, yeah, no kidding. The Trump administration is gonna

1059
01:05:05,560 --> 01:05:10,840
Speaker 2: like keep looking for ways to push their white supremacy agenda.

1060
01:05:11,280 --> 01:05:13,800
Speaker 2: But like this is still a win, right, Like the

1061
01:05:14,960 --> 01:05:17,760
Speaker 2: fight is going on, but this is a big win

1062
01:05:19,120 --> 01:05:23,080
Speaker 2: about something very important. So what a nice thing to

1063
01:05:23,160 --> 01:05:24,160
Speaker 2: end on here.

1064
01:05:24,440 --> 01:05:27,600
Speaker 1: And especially in this climate. Let's learn to take a

1065
01:05:27,760 --> 01:05:30,200
Speaker 1: w when we get a W. Huh, Let's let's not

1066
01:05:30,480 --> 01:05:35,320
Speaker 1: we don't need there is so much to be discouraged about.

1067
01:05:35,800 --> 01:05:38,400
Speaker 1: I don't know. I'm taking my wins when I get them.

1068
01:05:38,480 --> 01:05:41,320
Speaker 1: Hell yeah, Well, Mike, thank you so much for being here.

1069
01:05:41,720 --> 01:05:43,880
Speaker 1: Where can folks stay in touch with all the stuff

1070
01:05:43,880 --> 01:05:44,920
Speaker 1: that we're doing on the show.

1071
01:05:45,400 --> 01:05:47,960
Speaker 2: Thanks for having me here at Bridget. People can leave

1072
01:05:48,040 --> 01:05:50,520
Speaker 2: us comments on Spotify. A lot of people have been

1073
01:05:50,520 --> 01:05:52,680
Speaker 2: doing that and it's been great to get that feedback.

1074
01:05:52,720 --> 01:05:55,200
Speaker 2: Please keep it coming. You can send us an email

1075
01:05:55,320 --> 01:05:59,480
Speaker 2: at Hello at tangote dot com. You can follow Bridget

1076
01:05:59,520 --> 01:06:04,560
Speaker 2: on Instagram or TikTok at Bridget Marie in DC, and

1077
01:06:04,760 --> 01:06:08,920
Speaker 2: you can follow the show on YouTube or Blue Sky

1078
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Speaker 2: at There Are No Girls on the Internet.

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Speaker 1: Thanks so much for listening, y'all. I will see you

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Speaker 1: on the Internet. Got a story about an interesting thing

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Speaker 1: in tech, or just want to say hi? You can

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Speaker 1: reach us at Hello at tangody dot com. You can

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Speaker 1: also find transcripts for today's episode at tenggody dot com.

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Speaker 1: There Are No Girls on the Internet was created by

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Speaker 1: me Bridget Todd. It's a production of iHeartRadio and Unbossed

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Speaker 1: creative Jonathan Strickland as our executive producer. Tari Harrison is

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Speaker 1: our producer and sound engineer. Michael Amado is our contributing producer.

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Speaker 1: Edited by Joey pat I'm your host, Bridget Todd. If

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Speaker 1: you want to help us grow, rate and review us

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Speaker 1: on Apple Podcasts. For more podcasts from iHeartRadio, check out

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Speaker 1: the iHeartRadio app, Apple Podcasts, or wherever you get your podcasts.

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Speaker 3: A the w W