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Speaker 1: There Are No Girls on the Internet. As a production

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

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

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Speaker 2: Joey, welcome back to the show. It's so nice to

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Speaker 2: see you.

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Speaker 3: Okay, Bridget, it's nice to you too.

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Speaker 1: So before folks ask if my voice sounds a little different,

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Speaker 1: it's because I'm a bit under the weather. I've been

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Speaker 1: saving my voice all day. This is the first time

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Speaker 1: that I've really spoken out loud all day.

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Speaker 2: So hopefully it'll agree with us for me to record this.

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Speaker 1: But if you're thinking, oh, Bridget sounds raspy or husky,

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Speaker 1: that's what's going on.

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Speaker 2: So bear with me. Joey.

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Speaker 1: I want to start with a question. I know it

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Speaker 1: has been a weird week. January is also that month,

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Speaker 1: at least for me, that it feels like nothing is right.

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Speaker 1: Everybody is broke, tired, cold, sober. If you're doing a

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Speaker 1: dry January. All of that said, is there something on

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Speaker 1: the internet that is giving you joy in this moment?

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Speaker 4: Oh, that's a good question. There's definitely a lot that

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Speaker 4: is stressing me out right now. But oh my god,

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Speaker 4: there was this TikTok trend recently that was I can't

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Speaker 4: remember who it was, but it was like this clip

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Speaker 4: from the View and it was the person like, you

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Speaker 4: know what, it was the clip of somebody going Donald Trump,

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Speaker 4: if you pick out.

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Speaker 1: All the like, my gosh, whatever, it's Kelly Osbourne. I

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Speaker 1: know exactly what you're talking about. Oh my god, I'm

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Speaker 1: still glad that you brought this up. It's Kelly Osbourne's

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Speaker 1: are going like, if you kicked, if you click out

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Speaker 1: all out of this country, who is going.

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Speaker 2: To scrub your Toilet's Donald Trump.

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Speaker 4: So it was like people doing that meme, but like

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Speaker 4: different formats, but you know, there were just there were

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Speaker 4: a lot of fun ones going around.

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Speaker 3: Love a good trend.

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Speaker 1: That is one of those pop culture moments that lives

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Speaker 1: in my mind, rent Free. I also love the reaction

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Speaker 1: of all the different people at the View because Kelly

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Speaker 1: Osborne says it, and she says that very you can

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Speaker 1: tell that she was like trying to make a point

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Speaker 1: that like didn't land and immediately everybody's like, oh no,

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Speaker 1: and she's like no, but in the sense that and

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Speaker 1: they're just like, uh no.

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Speaker 2: And I just read this interview with her.

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Speaker 1: About that moment because it's been taking off on TikTok

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Speaker 1: and honestly, like, we'll throw the link to the interview

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Speaker 1: in the show notes if I can find it. But

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Speaker 1: she's like, you know, sometimes you have to learn in public.

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Speaker 1: And I know the point that I was trying to

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Speaker 1: make and maybe it didn't land, but you know, you

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Speaker 1: have to grow sometimes. And I appreciated how she handled it.

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Speaker 1: And I did see a TikTok where somebody made the

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Speaker 1: point that she was trying to make more succinctly. They

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Speaker 1: were like, well, if you kick out all of the

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Speaker 1: immigrants in this country, that is going to be impactful

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Speaker 1: to all of us, because immigrants bring give so much

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Speaker 1: to our country, and actually, like we should be respectful

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Speaker 1: and honor the different ways that their labor makes our

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Speaker 1: country great. And then in his version, it's like, oh,

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Speaker 1: that actually makes sense. So she was trying to make

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Speaker 1: a point. The point didn't land, but it is a

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Speaker 1: pop culture moment that will stick with me.

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Speaker 3: Yeah, I know, that was so funny, and that's good

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Speaker 3: to hear that.

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Speaker 4: At least it seems like she's handling it, you know,

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Speaker 4: with grace to something I said, because yeah, that is

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Speaker 4: that is like a you know I'm not gonna say

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Speaker 4: that when she said wasn't wrong, that was definitely a

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Speaker 4: weird thing to say, But.

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Speaker 3: You know, we all got to Maiger mistakes and grow.

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Speaker 4: And I do also agree with the point where it's like, yeah,

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Speaker 4: we you know, there's a conversation about the like labor

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Speaker 4: that goes unnoticed and particularly like jobs that people you

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Speaker 4: know don't necessarily.

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Speaker 3: Want to have, and immigration and all that, and that's

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Speaker 3: definitely a.

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Speaker 4: Conversation if you had so yeah, but got a fun

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Speaker 4: TikTok trend out of it.

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Speaker 2: Yeah, I feel I.

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Speaker 1: Mean, as podcasters, having to grow in public and learn

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Speaker 1: stuff in public has been part of the So I

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Speaker 1: definitely feel for Kelly Osbourne of oh yeah, oh yeah,

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Speaker 1: I embarrassed myself and a lot of people probably heard

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Speaker 1: it and that was that was humbling.

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Speaker 4: Oh yeah, I like I could not imagine like having

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Speaker 4: to be on live TV like this is very closely edited.

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Speaker 4: I'm definitely grateful for that because there's a lot of

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Speaker 4: times when I'm like I need to like stop and think.

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Speaker 2: Yes, oh my god, Joey.

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Speaker 1: If you're like listeners, if you're ever listening and you're like, wow,

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Speaker 1: I can't believe Bridget or Mike or one of the

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Speaker 1: guests was able to say that so eloquently on the fly.

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Speaker 2: It's because we didn't. That is the magic of Joey

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Speaker 2: and our other editor, Tari, making us sound smarter and

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Speaker 2: more eloquent than we are on the fly if this

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Speaker 2: was live TV. Never absolutely not. And also want to

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Speaker 2: show like.

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Speaker 1: The view where the whole point is you're sort of

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Speaker 1: arguing and like talking over each other and having discourse.

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Speaker 1: I would have to be like, everybody be quiet so

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Speaker 1: I can catch my thoughts, like, so I can get

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Speaker 1: my thoughts together every five minutes.

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Speaker 3: Yeah, definitely.

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Speaker 1: Okay, So this election season fully kicked off. The New

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Speaker 1: Humpshire primary appened this week and some voters got a

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Speaker 1: call at the very last minute from someone giving them

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Speaker 1: information about the election.

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Speaker 5: You know the value of voting democratic on our vote's count,

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Speaker 5: It's important that you save your vote for the November election.

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Speaker 5: Will need your help in electing Democrats up and down

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Speaker 5: the ticket. Voting this Tuesday only enables the Republicans in

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Speaker 5: their quest to elect Donald Trump again. Your vote makes

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Speaker 5: a difference in November, not just Tuesday. If you would

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Speaker 5: like to be removed from future calls please press two.

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Speaker 1: So that sounded like Joe Biden, but that was not

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Speaker 1: Joe Biden. That was an AI generated audio deep fake

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Speaker 1: that voters in New Hampshire before this week's primary got

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Speaker 1: on the phone telling them not to vote. And I

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Speaker 1: don't have a ton to say about this that I

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Speaker 1: have not already said, but I'll just reiterate it does

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Speaker 1: not vode well for the use of AI to spread

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Speaker 1: disinformation and make that impact a lot worse this election cycle.

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Speaker 1: This is something that I'm worried about thinking about all

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Speaker 1: of the folks who I am in community with who

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Speaker 1: also study and work on disan misinformation, particularly how it

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Speaker 1: impacts democracies, are all sort of saying the same thing,

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Speaker 1: which is that AI could be poised to really make disinformation,

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Speaker 1: which is already a problem so much, so much worse.

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Speaker 1: And what's worse is that we're not really doing a

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Speaker 1: ton about it right now. The nonprofit consumer advocacy group

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Speaker 1: Public Citizen says that that robo call really underscores the

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Speaker 1: need for federal regulation of AI generated deep fakes and

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Speaker 1: that it is way past time for action. I completely agree,

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Speaker 1: but this comes as Republican SEC Chairman Sean Cooksey says

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Speaker 1: that they're not even looking at establishing any kind of

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Speaker 1: updated rules federally around deep fakes and political ads. At

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Speaker 1: the earliest, they're going to do it early summer, which

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Speaker 1: that is after many states have their primary. So it

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Speaker 1: just seems pretty late to be like, oh, we will

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Speaker 1: be rolling out in summertime, you know, after states have

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Speaker 1: already held their primaries. Feels pretty late in the game

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Speaker 1: to be trying to curb the impact.

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Speaker 2: Of this kind of thing.

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Speaker 4: Yeah, I'm glad you opened with the positive question because

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Speaker 4: I do feel like, I think because the primary started now,

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Speaker 4: like the reality of the fact that there's going to

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Speaker 4: be an election this year has like started to hit

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Speaker 4: and it's just been like.

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Speaker 3: Absolute terror every time I think.

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Speaker 4: About it, Like there really is no kind of good

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Speaker 4: outcome I could see right now.

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Speaker 3: Not to be.

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Speaker 4: Complete pestmost, but yeah, I know, I feel like this

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Speaker 4: is going to be a weird, weird year.

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Speaker 2: Friend, don't even get me started.

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Speaker 1: I it's one of those things that if I I've

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Speaker 1: told myself that I'm not going to start really thinking

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Speaker 1: about the election in earnest in a meaningful way until summer, Like.

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Speaker 2: I guess I'm kind of like the fec here. I'm

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Speaker 2: like I because if I start thinking about it.

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Speaker 1: Now, there's plenty of time for me to spin out

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Speaker 1: and doom and gloom. Everybody that I know who works

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Speaker 1: on these issues is having almost a sort of like

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Speaker 1: philosophical crisis around the upcoming election. I genuinely don't know

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Speaker 1: how it is going to go. We are very worried

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Speaker 1: as a community. And it's so weird because I remember

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Speaker 1: when we were preparing in the like Disinfo Election Disinfo

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Speaker 1: Democracy space, preparing for the last election. We were gaming

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Speaker 1: out all the different scenarios, and I will never forget

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Speaker 1: one of the scenarios that we were gaming out was

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Speaker 1: some sort of a so it was like, oh, if

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Speaker 1: Trump wins, here's the plan. If Trump loses, here's the plan.

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Speaker 1: And then a third thing that was like if there

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Speaker 1: is a widespread election related incident flash irregularity. And at

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Speaker 1: the time, like we didn't know what we were preparing for.

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Speaker 1: Turns out it was January sixth. That was very precient. Yeah,

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Speaker 1: it feels like we're there all over again.

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Speaker 4: Oh my god, God, that's so weird to think that

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Speaker 4: that was like, yeah, there was the election, and then

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Speaker 4: that I don't know, I feel like it all kind

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Speaker 4: of blurs together. But yeah, that was such a crazy

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Speaker 4: time and it's definitely gonna be an interesting next couple

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Speaker 4: of months. Yeah, not looking forward to it. I I'm

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Speaker 4: not surprised to hear that people are having their own

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Speaker 4: kind of crisisies around it.

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Speaker 1: This might be like, like too personal. But during that election,

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Speaker 1: my dad, who is chronically ill and disabled, he was

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Speaker 1: in the hospital and I went to I dropped everything

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Speaker 1: all the election work to go be with him in

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Speaker 1: the hospital. And it was a cognitive issue and so

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Speaker 1: he was, you know, not awake, was asleep for a

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Speaker 1: lot of that time, resting, and we were watching it

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Speaker 1: was it was election night, right, and so we were

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Speaker 1: watching the election results in his hospital room. And so

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Speaker 1: he woke up from this like drugged up, medically induced

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Speaker 1: sleep to seeing Donald Trump on television the day after

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Speaker 1: the election claiming that he had won, and my dad

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Speaker 1: was like what, like what did I miss it?

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Speaker 2: Did he win? And I remember being like, Dad, I know.

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Speaker 1: It looks like the the how where I would have

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Speaker 1: to start to be like why are you why you

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Speaker 1: are watching Donald Trump on CNN claiming that he won

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Speaker 1: an election, and he being like he didn't win.

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Speaker 2: Don't worry.

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Speaker 1: I know it seems like he did because what you're

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Speaker 1: seeing on TV, but just take my word for it,

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Speaker 1: he didn't.

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Speaker 2: It was a very weird time, I guess, is what

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Speaker 2: I'm saying.

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Speaker 3: Yeah, I know that's sounds like a crazy conversation.

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Speaker 1: So, you know, thinking about how I feel, and you know,

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Speaker 1: civil society groups who are looking at this really feel

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Speaker 1: like not enough is being done. If there was a

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Speaker 1: theme to this episode, it would be do something, listen

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Speaker 1: to people, don't wait till it's too late.

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Speaker 2: It feels like it's becoming too late.

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Speaker 1: And another way that we are seeing that this week

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Speaker 1: is through non consensual AI generated sexually explicit deep fake.

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Speaker 1: So last week on the News round Up, Mike and

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Speaker 1: I were talking about this New Jersey high school student

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Speaker 1: who has been advocating for legislation that criminalizes non consensual

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Speaker 1: AI deep fakes after the boys in her class were

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Speaker 1: trading deep fake sexualized images of her and about thirty

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Speaker 1: other girls in her school. And this week, a school

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Speaker 1: district in Aurora, Colorado, is dealing with the very same thing.

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Speaker 1: This week, the Aurora Police Department has released the names

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Speaker 1: of schools involved in a sextortion investigation, which includes two

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Speaker 1: middle schools. When I was in middle school that was

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Speaker 1: grade six to eight. So like, you're like eleven, twelve, thirteen, fourteen,

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Speaker 1: you are so young to be dealing with the impacts

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Speaker 1: of a sexually charged deep fake sextortion ring. Like, I

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Speaker 1: don't think it is okay for kids to be having

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Speaker 1: to deal with this. So police say that in six

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Speaker 1: different instances, students at that school district reported being a

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Speaker 1: direct target of sextortion scheme after being contacted by the

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Speaker 1: suspect or suspects through Instagram. In dozens of other cases,

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Speaker 1: students received unsolicited invitations to pay to join a close

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Speaker 1: friends list on Instagram where sexually explicit material had been posted.

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Speaker 1: So it really is a marketplace where kids are either

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Speaker 1: being invited to pay to get this sexual content or

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Speaker 1: being made to pay to keep that content from being

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Speaker 1: shared on these platforms. A nightmare. And again, like, I

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Speaker 1: don't think this is something that should just become normalized

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Speaker 1: for our kids. If we did another update every single

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Speaker 1: time one of these AI related sextortion rings was reported

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Speaker 1: on in a different school district across the country, it

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Speaker 1: would be all we talked about. Because it is happening

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Speaker 1: so much. This should not become a normal thing for

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Speaker 1: our kids, and it seems like it is becoming normal,

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Speaker 1: and lawmakers are just dragging their feet to actually do

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Speaker 1: anything to prevent this from becoming a new thing that

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Speaker 1: kids just have to deal with.

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Speaker 4: Yeah, no, that's so scary and yeah, like exactly, Like

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Speaker 4: I don't know. I think I was like eleven when

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Speaker 4: I started middle school, Like you're a baby, that is

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Speaker 4: a child, like.

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Speaker 3: And I don't know, it's I was so like when

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Speaker 3: I was in middle school.

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Speaker 4: That was kind of like the beginning of or I

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Speaker 4: guess not the beginning technically, but like social media was

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Speaker 4: just kind of like becoming a thing like Instagram and Snapchat.

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Speaker 3: Or like starting to become big.

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Speaker 4: And I mean it's so sad because I do remember

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Speaker 4: then like a lot of the conversations were about like

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Speaker 4: sending nudes or like sending or like sexting or all

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Speaker 4: of that, or.

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Speaker 3: You know, people getting groomed online and.

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Speaker 4: All of that, and it's it's it's weird now being like, wow,

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Speaker 4: that all was so messed up and it is continuing

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Speaker 4: to happen, and it's continuing to happen in a way

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Speaker 4: that's like even more dangerous kind of and even more

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Speaker 4: sort of like out of control, which just is so scary,

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Speaker 4: Like I can't imagine being a kid right now, Like, yeah,

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Speaker 4: that honestly just sounds terrifying.

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Speaker 1: It's terrifying. And our kids should not have to be

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Speaker 1: dealing with this, Like nobody should have to be dealing

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Speaker 1: with this. We cannot have a healthy society when this

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Speaker 1: is just tolerated and is like just becomes part of

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Speaker 1: the experience of being a young person, which I just

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Speaker 1: don't accept that this has to be part of that.

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Speaker 6: Let's hit a quick break at our back.

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Speaker 1: And this week, Taylor Swift was also targeted by non

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Speaker 1: consensual deep faith images that flooded Twitter. According to Verge,

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Speaker 1: these images got forty five million views, twenty four thousand reposts,

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Speaker 1: and hundreds of thousands of likes and bookmarks before the

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Speaker 1: verified blue checked user who shared the images had their

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Speaker 1: account suspended for violating platform policy. The post was live

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Speaker 1: on the platform for about seventeen hours prior to its removal.

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Speaker 1: So four o four Media has this really in depth

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Speaker 1: piece of reporting about how those images originated on Telegram,

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Speaker 1: which if you don't know what telegram is, it's kind

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Speaker 1: of like an alternative messaging platform that really gained popularity

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Speaker 1: with right wing extremists, but other folks use it too,

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Speaker 1: like a lot of journalists depend on it. So Twitter

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Speaker 1: actually has rules that ban AI generated deep fake images,

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Speaker 1: but I can confirm, as of this recording, many of

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Speaker 1: those images of Taylor Swift, those deep faked, non consensual

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Speaker 1: sexual explicit images, were still floating around Twitter.

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Speaker 2: You know.

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Speaker 1: The one user who brought those images from Telegram to

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Speaker 1: Twitter might have had their account deleted, but they's because

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Speaker 1: of the way the internet works. Plenty of them are

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Speaker 1: floating around as we speak, and so the hashtag Taylor

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Speaker 1: Swift ai was even trending. So you might think, like,

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Speaker 1: why is Twitter allowing this? Shouldn't they do something? But

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Speaker 1: remember when Elon Musk took over Twitter, one of the

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Speaker 1: first things he did was gut the trust and Safety team,

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Speaker 1: and content moderation there has kind of been like more

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Speaker 1: or less non existent, like not totally not existent, but

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Speaker 1: there's just not a lot of robust content moderation happening there.

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Speaker 1: Like the fact that this could be up for seventeen

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Speaker 1: hours kind of says something.

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Speaker 4: Yeah, I was gonna say, I I feel like at

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Speaker 4: this point. Nothing, there's nothing, There's very, very little that

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Speaker 4: could happen that would make me think, wow, why is

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Speaker 4: Twitter allowing this? Because I know the answer is Elon

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Speaker 4: Musk does not care and in fact is probably encouraging this.

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Speaker 4: I will say, obviously the story is terrible and horrible.

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Speaker 4: This is weirdly the second thing on my like twenty

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Speaker 4: twenty four predictions.

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Speaker 3: Thing that I made at the beginning of the year

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Speaker 3: to happen.

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Speaker 4: What twitch is, Yeah, because like I don't know if

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Speaker 4: there were like tiktoks that were going around and stuff

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Speaker 4: where people were like making a list and they're usually

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Speaker 4: kind of goofy.

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Speaker 3: And I I did one too, and one of them

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Speaker 3: was I was.

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Speaker 4: Like, there, I feel like there's going to be some

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Speaker 4: Taylor swift Ai controversy where like explicit photos are made

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Speaker 4: and she's gonna get Like, I mean, I don't We'll

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Speaker 4: see where this story ends, but like you know, I

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Speaker 4: believe that the Swifties is a powerful.

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Speaker 3: Political force, so who's say. Yeah.

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Speaker 4: The other one was that uh, Brian Gosling was gonna

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Speaker 4: get ATN nominated and Marco Robbie is not going to

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Speaker 4: get an obmated.

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Speaker 3: Oh my god, so it has been a weird week

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Speaker 3: of psychic predictions.

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Speaker 1: Apparently, keep us posted if any of the of any

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Speaker 1: of the other predictions, the other Joey twenty twenty four

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Speaker 1: predictions come true, that one's happened to me. I predicted

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Speaker 1: that this was back when he was like much more popular.

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Speaker 1: I predicted that Justin Bieber was going to get caught

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Speaker 1: saying the.

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Speaker 2: N word, and he did.

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Speaker 1: I was like, wow, yeah, so you so you said

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Speaker 1: that the Swifties are this powerful force, and you are

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Speaker 1: right about that because even though Elon Musk has not

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Speaker 1: been able or Elon Musk and his team have not

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Speaker 1: been able to rid the platform from this image these images,

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Speaker 1: Swifties actually took it upon themselves to try to flood

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Speaker 1: the Taylor Swift AI hashtag with real actual content of

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Speaker 1: Taylor Swift performing to drive down that sexually explicit fake content.

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Speaker 1: And you know, I know, the Swifties are like a

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Speaker 1: big force, Like they're like an organized force for good

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Speaker 1: at times, I firmly believe that like they should be

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Speaker 1: being able to spend their time like you know, like

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Speaker 1: they shouldn't have to do this is is what I'm saying.

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Speaker 1: They should be able to spend their time like buying

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Speaker 1: merch and trading merch and making bracelets and all of

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Speaker 1: all of the fun, the sparkly things that come that

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Speaker 1: go with being a Swiftie.

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Speaker 3: Yeah, like they should just be allowed. Yeah, Like they

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Speaker 3: should be able to just be fans of the thing.

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Speaker 4: They should have to be like the PR team for

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Speaker 4: the volunteer PR team for like a billionaire celebrit and

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Speaker 4: not that it's on her team to like, you know

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Speaker 4: that this happened, but it is like they shouldn't have

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Speaker 4: to be the content moderators for Twitter probably some other

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Speaker 4: way of putting it, Yeah, especially because I'm sure a

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Speaker 4: lot of these people are pretty young.

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Speaker 1: Yeah, you like we should it should not be up

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Speaker 1: to like one thousand Swifties to keep potentially a legal

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Speaker 1: content off of a platform that's run by a billion ere.

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Speaker 1: That's not a dynamic that I'm comfortable with. And I

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Speaker 1: have to say, like, it feels really gross to talk

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Speaker 1: about those images, but I just want to add, because

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Speaker 1: it's something that has been in my mind a lot,

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Speaker 1: is that the images are football themed. They depict Taylor

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Speaker 1: Swift at a big football game. And I don't know

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Speaker 1: for sure, but I have to assume that this is

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Speaker 1: related to the fact that she's gotten so much attention

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Speaker 1: from going to those NFL games because her boyfriend is

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Speaker 1: a football player, and every time she goes to a game,

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Speaker 1: it is like breathlessly reported on. And I guess I

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Speaker 1: just don't think that it's a coincident that these images

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Speaker 1: depict her at a football game, and I think they're

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Speaker 1: meant to humiliate her on the basis of the attention

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Speaker 1: that she has gotten from the NFL.

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Speaker 2: And I think that they're they're meant.

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Speaker 1: To like, like, people who make visual disinformation are so

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Speaker 1: good at doing so in a way that works to

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Speaker 1: get people. They're just very charged. They're very good at

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Speaker 1: making images that are very charged. And I can't help

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Speaker 1: but notice the ways that these images seemed charged to

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Speaker 1: humiliate her in a very specific kind of way about

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Speaker 1: a very specific thing about her personal life.

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Speaker 3: Yeah, that definitely doesn't seem like it's a coincidence.

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Speaker 1: Yeah, And you know, I've seen some takes that are like, well,

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Speaker 1: I'm glad it's happening to Taylor Swift. She is so

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Speaker 1: powerful and so rich, and that like she'll will be

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Speaker 1: able to do something like certainly her team will be

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Speaker 1: able to do something. But I push back on those

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Speaker 1: takes because like, these images are up, right, like I

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Speaker 1: confirmed that before we started recording, and it so like

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Speaker 1: even if Twitter wanted to remove these images, I don't

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Speaker 1: think they would be able to just by the nature

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Speaker 1: of how the Internet works.

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Speaker 2: And I think it just speaks to the.

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Speaker 1: Fact that the powers that be have let this problem

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Speaker 1: get so out of hand that I don't know what

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Speaker 1: a fix looks like. And if it's happening to Taylor Swift,

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Speaker 1: one of the wealthiest, most popular, and most powerful women

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Speaker 1: in the world, I don't think that it's like, oh, well,

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Speaker 1: she'll be able to figure out something where this won't

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Speaker 1: happen to other people.

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Speaker 2: It's already happening to her.

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Speaker 1: So if it's going If it happens to her and

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Speaker 1: those pictures are up for seventeen hours and then still

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Speaker 1: up after that, what hope is there for any of us,

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Speaker 1: Like what happens when it happens to a high schooler

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Speaker 1: or a child or any of us, Like lawmakers have

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Speaker 1: ignored the warnings and gotten no traction on legislation on this,

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Speaker 1: and I just don't think any of it bodes well

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Speaker 1: for anybody.

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Speaker 3: Yeah, definitely.

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Speaker 4: Like I'm glad, and again, I you know, it is

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Speaker 4: it's I don't obviously like it shouldn't happen to anybody.

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Speaker 3: It just kind of it. It's horrible for her on

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Speaker 3: a personal level.

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Speaker 4: And then also like it just kind of enforces that

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Speaker 4: sort of idea that like women's bodies are like public property,

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Speaker 4: and especially if they're like in the spotlight.

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Speaker 3: But yeah, like, I don't.

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Speaker 4: Think if this happened to me, my like three hundred

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Speaker 4: Twitter followers would be able to you know, change like

440
00:22:25,000 --> 00:22:27,040
Speaker 4: flood the hash not that there would be a hashtag,

441
00:22:27,119 --> 00:22:30,239
Speaker 4: but you know, yeah, it is.

442
00:22:30,440 --> 00:22:32,360
Speaker 3: It is sort of concerning.

443
00:22:31,800 --> 00:22:35,840
Speaker 4: That like one of the most powerful women in the

444
00:22:35,840 --> 00:22:38,760
Speaker 4: world cannot this happen to her with like very little

445
00:22:38,840 --> 00:22:40,280
Speaker 4: consequences at the moment.

446
00:22:40,680 --> 00:22:43,200
Speaker 2: Yeah, I mean that you just really nicely articulated.

447
00:22:43,200 --> 00:22:45,840
Speaker 1: One of the things I always say about this kind

448
00:22:45,840 --> 00:22:50,879
Speaker 1: of garbage is that these kinds of exploitative content, it

449
00:22:51,640 --> 00:22:57,159
Speaker 1: reinforces the idea that women, by virtue of showing up online,

450
00:22:58,040 --> 00:23:02,280
Speaker 1: our body and our images are just open for whoever

451
00:23:02,320 --> 00:23:04,520
Speaker 1: wants to use them or exploit them in any way

452
00:23:04,560 --> 00:23:06,520
Speaker 1: they can. And so I've seen people be like, oh, well,

453
00:23:06,680 --> 00:23:08,919
Speaker 1: these pictures aren't real, and she's a public figure, so

454
00:23:09,040 --> 00:23:11,760
Speaker 1: like that it goes along with it absolutely fucking not

455
00:23:12,400 --> 00:23:15,679
Speaker 1: the cost of showing up and being a public figure,

456
00:23:15,760 --> 00:23:19,199
Speaker 1: and you know, being on the internet should not be

457
00:23:19,320 --> 00:23:22,680
Speaker 1: to be sexually humiliated. Like and I do think it's

458
00:23:22,720 --> 00:23:27,000
Speaker 1: something about reinforcing this idea that, yeah, our bodies are

459
00:23:27,040 --> 00:23:30,480
Speaker 1: just up for the taking to be depicted however anybody wants.

460
00:23:30,520 --> 00:23:32,520
Speaker 1: And then on top of that, we're supposed to not

461
00:23:32,560 --> 00:23:36,000
Speaker 1: be upset by it because it's quote not real, absolutely not,

462
00:23:36,400 --> 00:23:39,000
Speaker 1: absolutely not that as a terrible dynamic, that is a

463
00:23:39,080 --> 00:23:42,280
Speaker 1: terrible norm. We should all be pushing back on that

464
00:23:42,320 --> 00:23:46,040
Speaker 1: because certainly, I'm sure you know that high schooler who

465
00:23:46,560 --> 00:23:48,840
Speaker 1: is having the high school student who is having this

466
00:23:48,880 --> 00:23:51,640
Speaker 1: happen to her, isn't saying like, oh, it's not real images.

467
00:23:52,000 --> 00:23:55,280
Speaker 1: These images, whether they are real or not, they can

468
00:23:55,320 --> 00:23:58,600
Speaker 1: do real damage and really impact people's lives. And yeah,

469
00:23:58,640 --> 00:24:00,399
Speaker 1: I just think that we should all be pushed for

470
00:24:00,480 --> 00:24:02,440
Speaker 1: a culture that recognizes that.

471
00:24:02,960 --> 00:24:05,480
Speaker 4: Yeah, and I definitely it's this is one of those

472
00:24:05,480 --> 00:24:08,239
Speaker 4: things too where it's like it's it's terrible, and it's

473
00:24:08,320 --> 00:24:10,679
Speaker 4: terrible it's happening to again, it's it's it's terrible that

474
00:24:10,760 --> 00:24:11,600
Speaker 4: it happens to anybody.

475
00:24:11,720 --> 00:24:13,600
Speaker 3: I think, like obviously.

476
00:24:13,920 --> 00:24:16,040
Speaker 4: Taylor's story is going to get a lot of attention,

477
00:24:16,119 --> 00:24:17,720
Speaker 4: and it is something that is happening to like a

478
00:24:17,760 --> 00:24:20,040
Speaker 4: lot of people, and it's probably going to continue to happen.

479
00:24:20,400 --> 00:24:25,040
Speaker 4: And interestingly, Slash not surprisingly, you know, it's happening around

480
00:24:25,080 --> 00:24:27,399
Speaker 4: the same time and like by the same people that

481
00:24:27,640 --> 00:24:29,960
Speaker 4: want to crack down on like sex workers and sex

482
00:24:29,960 --> 00:24:33,600
Speaker 4: workers rights. And I think this is another situation looking

483
00:24:33,680 --> 00:24:37,960
Speaker 4: at AI where you know, it really is important to

484
00:24:38,000 --> 00:24:40,200
Speaker 4: listen to sex workers about these issues because a lot

485
00:24:40,200 --> 00:24:43,080
Speaker 4: of times they're going to be like the first ones

486
00:24:43,080 --> 00:24:48,159
Speaker 4: harmed by this kind of stuff, Slash exploit it, and

487
00:24:49,280 --> 00:24:51,359
Speaker 4: we all are going to end up suffering because of

488
00:24:51,400 --> 00:24:54,679
Speaker 4: these sort of exploitative things. So yeah, no, I just

489
00:24:55,080 --> 00:24:58,600
Speaker 4: I think listen to sex workers about these issues. Like

490
00:24:59,240 --> 00:25:02,920
Speaker 4: is the weird sort of like duality of those efforts

491
00:25:02,920 --> 00:25:06,479
Speaker 4: to take away like agency over the bodies of like

492
00:25:06,640 --> 00:25:10,120
Speaker 4: non CIS men and at the same time, like those

493
00:25:10,160 --> 00:25:13,639
Speaker 4: bodies are kind of seen as public property in these

494
00:25:13,680 --> 00:25:16,200
Speaker 4: sort of situations, which is scary.

495
00:25:16,800 --> 00:25:21,760
Speaker 1: Yeah, almost every one of the tech and internet facilitated

496
00:25:21,760 --> 00:25:23,240
Speaker 1: harms that we talk about on this show.

497
00:25:23,560 --> 00:25:25,600
Speaker 2: Sex workers have been like, oh, yeah, we called that. Yeah,

498
00:25:25,640 --> 00:25:26,480
Speaker 2: we were warning about that.

499
00:25:26,720 --> 00:25:29,040
Speaker 1: You knew about that, And if only people with power

500
00:25:29,440 --> 00:25:32,680
Speaker 1: I don't know, listened, I wonder where we would be.

501
00:25:37,760 --> 00:25:56,520
Speaker 6: Let's take a quick break.

502
00:25:50,200 --> 00:25:50,760
Speaker 2: At our back.

503
00:25:52,960 --> 00:25:56,520
Speaker 1: So from one unsavory story to another, there are kind

504
00:25:56,560 --> 00:25:59,000
Speaker 1: of a lot of unsavory stories on this episode. I apologize,

505
00:25:59,280 --> 00:26:04,720
Speaker 1: but also it's the happier stories. So I know, I know,

506
00:26:05,880 --> 00:26:09,240
Speaker 1: I really deeply hate talking about this person. I think

507
00:26:09,240 --> 00:26:11,760
Speaker 1: we've only ever talked about this person once before on

508
00:26:11,800 --> 00:26:15,480
Speaker 1: the podcast, I think, But here we go. So far

509
00:26:15,640 --> 00:26:19,520
Speaker 1: right hate mongering influencer Chai Rachik, who runs the inflammatory

510
00:26:19,520 --> 00:26:22,399
Speaker 1: account Libs of TikTok, has just been appointed to the

511
00:26:22,440 --> 00:26:27,639
Speaker 1: Oklahoma Education Departments Library Media Advisory Committee, despite the fact

512
00:26:27,680 --> 00:26:31,520
Speaker 1: that this person does not live in Oklahoma, it's not

513
00:26:31,520 --> 00:26:33,800
Speaker 1: an Oklahoma resident, does not have a child in the

514
00:26:33,800 --> 00:26:37,159
Speaker 1: Oklahoma school system, and is a former real estate agent

515
00:26:37,240 --> 00:26:40,800
Speaker 1: with no clear background or history or ties to education.

516
00:26:41,160 --> 00:26:43,280
Speaker 1: And this person is going to be advising the state

517
00:26:43,400 --> 00:26:47,440
Speaker 1: on what kind of media should be in school libraries. Wow, Okay,

518
00:26:47,960 --> 00:26:49,720
Speaker 1: So if you don't know what Libs of TikTok is

519
00:26:49,800 --> 00:26:53,160
Speaker 1: it is an account where they will like post videos

520
00:26:53,440 --> 00:26:57,199
Speaker 1: a lot of times of perceived LGBTQ use or the

521
00:26:57,240 --> 00:27:00,600
Speaker 1: adults who support those youth to their millions of followers

522
00:27:00,920 --> 00:27:05,040
Speaker 1: to like make fun of them, demonize them, you know,

523
00:27:05,480 --> 00:27:08,679
Speaker 1: smear them, lie about them, all of that, and in

524
00:27:08,760 --> 00:27:14,560
Speaker 1: several instances, educators or school libraries or hospitals that are

525
00:27:14,600 --> 00:27:17,560
Speaker 1: featured on that account will then get death threats or

526
00:27:18,080 --> 00:27:21,800
Speaker 1: lots and lots of coordinated harassment. So Libs of TikTok

527
00:27:21,840 --> 00:27:24,680
Speaker 1: has been linked to threats at schools and hospitals across

528
00:27:24,720 --> 00:27:27,040
Speaker 1: the country. A friend of mine, will Caroless, who writes

529
00:27:27,040 --> 00:27:29,920
Speaker 1: about extremism at the USA Today, has chronicled how her

530
00:27:30,000 --> 00:27:33,480
Speaker 1: content has led to real world harm and disruptions. So

531
00:27:33,680 --> 00:27:36,840
Speaker 1: in Davis, California, a library received a bomb threat that

532
00:27:36,920 --> 00:27:39,920
Speaker 1: included hate speech according to police, and the library and

533
00:27:39,960 --> 00:27:42,200
Speaker 1: the school nearby had to be evacuated.

534
00:27:42,560 --> 00:27:44,360
Speaker 2: So this came after a group of.

535
00:27:44,280 --> 00:27:47,879
Speaker 1: Speakers started referring to a group of female trans athletes

536
00:27:47,920 --> 00:27:51,760
Speaker 1: as quote biological males. A librarian asked them to leave rightly,

537
00:27:51,800 --> 00:27:54,280
Speaker 1: so that interaction is caught on a video, and then

538
00:27:54,640 --> 00:27:57,920
Speaker 1: a far right backlash from Libs of TikTok and others

539
00:27:58,000 --> 00:28:01,439
Speaker 1: ensued in Tulsa, Oklahoma, where this woman has just been

540
00:28:01,480 --> 00:28:05,200
Speaker 1: appointed to you know, guide the material that children should

541
00:28:05,200 --> 00:28:09,200
Speaker 1: be receiving. Well, in Tulsa, Oklahoma, their school received bomb

542
00:28:09,280 --> 00:28:11,920
Speaker 1: threats the day after. Libs of TikTok tweeted about the

543
00:28:11,960 --> 00:28:16,400
Speaker 1: school's librarian, who posted a video that was obviously meant

544
00:28:16,400 --> 00:28:18,199
Speaker 1: to be a joke, obviously meant to be tongue in chic,

545
00:28:18,320 --> 00:28:19,840
Speaker 1: Like anybody who saw this would be like, yeah, she's

546
00:28:19,880 --> 00:28:23,959
Speaker 1: kidding around. The librarian and Tulsa posted my radical liberal

547
00:28:24,000 --> 00:28:27,000
Speaker 1: agenda is teaching kids to love books and be kind.

548
00:28:27,280 --> 00:28:30,960
Speaker 1: So obviously that video is meant to be a joke,

549
00:28:32,119 --> 00:28:33,760
Speaker 1: but they took it seriously.

550
00:28:33,880 --> 00:28:35,520
Speaker 2: That's another thing about these people. It's like they have

551
00:28:35,560 --> 00:28:36,639
Speaker 2: the worst sense of humor.

552
00:28:37,520 --> 00:28:41,360
Speaker 4: Okay, it's two things, because one, I'm so sorry, but

553
00:28:41,680 --> 00:28:43,400
Speaker 4: how much of a loser do you have to be

554
00:28:43,520 --> 00:28:46,880
Speaker 4: to like care this much about what's happening in like high.

555
00:28:46,640 --> 00:28:49,680
Speaker 3: Schools, like huge losers on with your life, like.

556
00:28:51,560 --> 00:28:54,680
Speaker 4: And then second of all, yeah, that is like that

557
00:28:54,840 --> 00:28:58,280
Speaker 4: is the most basic like joke you can may I

558
00:28:58,320 --> 00:28:58,600
Speaker 4: don't know.

559
00:28:58,760 --> 00:29:00,920
Speaker 3: That is so weird to be like, oh my god,

560
00:29:01,240 --> 00:29:02,280
Speaker 3: they're so scary.

561
00:29:03,040 --> 00:29:05,160
Speaker 2: Wow, I make this point a lot.

562
00:29:05,280 --> 00:29:08,840
Speaker 1: Do you follow the comedian and writer or I guess

563
00:29:08,840 --> 00:29:12,640
Speaker 1: the actress to multi halfenite, multi hyphen it Trace Lassette.

564
00:29:13,000 --> 00:29:16,440
Speaker 1: So Trace was talking about Dave Chappelle's most recent net

565
00:29:16,440 --> 00:29:19,520
Speaker 1: Netflix special and TRACE's trans and she was talking about how,

566
00:29:19,600 --> 00:29:23,360
Speaker 1: like what is going on that? Like, so, okay, we

567
00:29:23,440 --> 00:29:26,840
Speaker 1: get it. Dave Chappelle doesn't like trans people. You need

568
00:29:26,880 --> 00:29:29,640
Speaker 1: to release multiple comedy specials about this, these people that

569
00:29:29,680 --> 00:29:33,440
Speaker 1: you apparently hate. Who spends this much time focused on

570
00:29:33,520 --> 00:29:36,160
Speaker 1: and talking about and thinking about and writing about stuff

571
00:29:36,200 --> 00:29:39,080
Speaker 1: like this, Like like, it is not normal. It's not

572
00:29:39,120 --> 00:29:41,880
Speaker 1: a normal way to exist. She's such a v if

573
00:29:41,960 --> 00:29:44,320
Speaker 1: y'all don't follow her on TikTok and on Twitter. She

574
00:29:44,440 --> 00:29:46,600
Speaker 1: is so cool, She's very funny.

575
00:29:47,040 --> 00:29:50,760
Speaker 3: Oh my god. Yeah, and no, like absolutely it is giving,

576
00:29:50,840 --> 00:29:54,240
Speaker 3: like why why why are you so obsessed with me?

577
00:29:54,320 --> 00:29:57,720
Speaker 3: You know? It is really weird.

578
00:29:57,880 --> 00:30:01,160
Speaker 4: I I gotta say, I don't think I've I've given

579
00:30:01,240 --> 00:30:04,719
Speaker 4: a single thought to what a high school curriculum is

580
00:30:04,800 --> 00:30:10,240
Speaker 4: like in my time since graduating high school. And yeah,

581
00:30:10,280 --> 00:30:13,440
Speaker 4: I don't typically, you know, hyper focus on people's gender

582
00:30:13,480 --> 00:30:16,400
Speaker 4: identity that have nothing to do with me or my life.

583
00:30:16,480 --> 00:30:18,520
Speaker 3: But yeah, glad, that's.

584
00:30:18,440 --> 00:30:23,640
Speaker 7: Yeah, people you'll never meet, Like it's a wild yeah,

585
00:30:23,680 --> 00:30:27,440
Speaker 7: I's And honestly, like when we were doing episodes earlier

586
00:30:27,480 --> 00:30:29,840
Speaker 7: in the summer about like book bands and stuff, one

587
00:30:29,840 --> 00:30:31,320
Speaker 7: of the things that was really surprising to me is

588
00:30:31,320 --> 00:30:35,800
Speaker 7: that oftentimes challenges for entire public school districts were.

589
00:30:35,600 --> 00:30:39,080
Speaker 1: Coming from one parent who did not live in that

590
00:30:39,080 --> 00:30:41,200
Speaker 1: school district and did not have kids in that school districts.

591
00:30:41,280 --> 00:30:44,440
Speaker 2: Was like, so you're just like obsessed.

592
00:30:44,280 --> 00:30:47,800
Speaker 1: Over what students in a school that you don't have

593
00:30:47,880 --> 00:30:49,400
Speaker 1: any connection to our reading.

594
00:30:49,800 --> 00:30:52,240
Speaker 2: What in the fucking world? Like that is just that

595
00:30:52,360 --> 00:30:54,480
Speaker 2: is not who is who does that?

596
00:30:54,520 --> 00:30:54,600
Speaker 6: Like?

597
00:30:54,600 --> 00:30:56,840
Speaker 1: I just like, obviously maybe you want to be a

598
00:30:56,880 --> 00:30:59,640
Speaker 1: Fox Newstar whatever whatever, I get it, But like, at

599
00:30:59,640 --> 00:31:03,840
Speaker 1: the or that is so I just I cannot understand

600
00:31:03,920 --> 00:31:07,280
Speaker 1: that mindset at all. I'm with you here in DC

601
00:31:07,400 --> 00:31:10,360
Speaker 1: where I live. Chaia Rachik from Lives of TikTok posted

602
00:31:10,360 --> 00:31:14,080
Speaker 1: a video where she films herself calling Children's Hospital, which

603
00:31:14,120 --> 00:31:17,400
Speaker 1: is like our major PDXTRA hospital here in DC, pretending

604
00:31:17,440 --> 00:31:20,280
Speaker 1: that she was looking for a gender affirming hysterectomy for

605
00:31:20,360 --> 00:31:23,479
Speaker 1: a non existent sixteen year old child. She posted this

606
00:31:23,560 --> 00:31:26,160
Speaker 1: recording of this conversation to Lives of TikTok last summer,

607
00:31:26,240 --> 00:31:30,520
Speaker 1: in which she is questioning two unidentified hospital employees about

608
00:31:30,520 --> 00:31:34,080
Speaker 1: whether or not they offer gender affirming hyst directomies to

609
00:31:34,240 --> 00:31:35,560
Speaker 1: patients who are sixteen.

610
00:31:35,880 --> 00:31:37,840
Speaker 2: So it's a little bit of a weird situation.

611
00:31:38,000 --> 00:31:42,160
Speaker 1: Basically, the hospital was inundated with harassing calls and threats,

612
00:31:42,520 --> 00:31:45,120
Speaker 1: accompanied by a social media post suggesting that the hospital

613
00:31:45,160 --> 00:31:48,040
Speaker 1: should be bombed and that its doctor should be jailed,

614
00:31:48,360 --> 00:31:51,000
Speaker 1: placed in a woodshipper or worse, and in the end,

615
00:31:51,240 --> 00:31:54,240
Speaker 1: Children's Hospital confirmed that whoever she was speaking to in

616
00:31:54,240 --> 00:31:57,760
Speaker 1: that video one were not medical care providers for the

617
00:31:57,760 --> 00:32:02,160
Speaker 1: hospital and that the hospital does not even hysterectomies on minors.

618
00:32:02,200 --> 00:32:04,640
Speaker 1: The hospital said, none of the people who were secretly

619
00:32:04,680 --> 00:32:07,840
Speaker 1: recorded by this activist group deliver character our patients. The

620
00:32:07,920 --> 00:32:10,440
Speaker 1: information in the recording is not accurate. We do not

621
00:32:10,560 --> 00:32:14,200
Speaker 1: perform gender affirming hysterectomies for anyone under the age of eighteen.

622
00:32:15,080 --> 00:32:15,920
Speaker 3: Yeah.

623
00:32:15,960 --> 00:32:19,520
Speaker 4: Also, it is insanely hard to get a hysterectomy as

624
00:32:19,520 --> 00:32:22,680
Speaker 4: an adult, like somebody over the age of eighteen, like

625
00:32:23,320 --> 00:32:24,240
Speaker 4: as somebody.

626
00:32:23,960 --> 00:32:26,600
Speaker 3: Who like I'll be totally honest.

627
00:32:27,080 --> 00:32:30,600
Speaker 4: My late teen years, almost every single doctor's appointment asked

628
00:32:30,640 --> 00:32:32,480
Speaker 4: if I can get a hysterectomy just because I didn't

629
00:32:32,520 --> 00:32:34,760
Speaker 4: want to keep getting my period and don't want.

630
00:32:34,640 --> 00:32:39,640
Speaker 3: To have kids. Like it's a no every time. It

631
00:32:39,720 --> 00:32:42,880
Speaker 3: is a staunch no. That is insane.

632
00:32:42,920 --> 00:32:46,480
Speaker 4: Yeah, and again, like as as an adult, there's just

633
00:32:46,520 --> 00:32:48,360
Speaker 4: so many hoops you have to go through, even if

634
00:32:48,400 --> 00:32:50,360
Speaker 4: it's like a legitimate medical issue.

635
00:32:50,640 --> 00:32:51,760
Speaker 3: Yeah, so crazy.

636
00:32:52,120 --> 00:32:55,080
Speaker 1: I've heard from friends. But one of my friends was

637
00:32:55,120 --> 00:32:58,400
Speaker 1: able to get a hysterectomy, but she had two doctors

638
00:32:58,440 --> 00:33:00,400
Speaker 1: be like I'm not going to perform it just in

639
00:33:00,480 --> 00:33:02,880
Speaker 1: case you want to have kids someday, and she's like,

640
00:33:03,120 --> 00:33:05,120
Speaker 1: I don't want to have kids.

641
00:33:05,200 --> 00:33:07,120
Speaker 2: I am in a relation. I am a woman in

642
00:33:07,120 --> 00:33:08,200
Speaker 2: a relationship with a woman.

643
00:33:08,480 --> 00:33:11,680
Speaker 1: So like, accidental pregnancy is not a thing that's like

644
00:33:11,720 --> 00:33:15,040
Speaker 1: on my I have no plans for children in the future.

645
00:33:15,200 --> 00:33:18,800
Speaker 1: But like making a medical decision based on a hypothetical

646
00:33:18,960 --> 00:33:22,760
Speaker 1: maybe someday man who might maybe someday hypothetically want to

647
00:33:22,760 --> 00:33:24,360
Speaker 1: be in the mix to have a baby, it is

648
00:33:24,680 --> 00:33:26,920
Speaker 1: all I have to say, Like, you are so right.

649
00:33:27,240 --> 00:33:29,920
Speaker 1: These people are trafficking in fictions where they are just

650
00:33:30,240 --> 00:33:34,400
Speaker 1: handing out hysterectomies to whoever wants one, regardless of anything

651
00:33:34,680 --> 00:33:37,239
Speaker 1: that is not happening. And it's like it's like not

652
00:33:37,280 --> 00:33:39,600
Speaker 1: based in reality these things that they And it doesn't

653
00:33:39,600 --> 00:33:41,600
Speaker 1: surprise me that the hospital has to be like, yeah, this

654
00:33:41,640 --> 00:33:43,960
Speaker 1: is the thing that they said happened that to lie

655
00:33:44,320 --> 00:33:47,240
Speaker 1: doesn't happen. And a similar thing happened at a children's

656
00:33:47,240 --> 00:33:52,200
Speaker 1: hospital in Boston as well, where their services for children,

657
00:33:52,280 --> 00:33:55,400
Speaker 1: for babies, their healthcare were disrupted because of all of

658
00:33:55,440 --> 00:33:59,840
Speaker 1: these calls and threats and harassment because of this libs

659
00:33:59,840 --> 00:34:03,000
Speaker 1: of TikTok stunts. It's so infuriating to me.

660
00:34:03,720 --> 00:34:07,240
Speaker 4: Yeah, also like what I mean, I guess it's it's

661
00:34:07,320 --> 00:34:11,239
Speaker 4: the same trying to apply logic to people that are

662
00:34:11,280 --> 00:34:14,279
Speaker 4: not acting logically. But it's like, I guess it's the

663
00:34:14,280 --> 00:34:17,600
Speaker 4: same stuff as like people that bomb abortion clinics, But

664
00:34:18,080 --> 00:34:23,360
Speaker 4: what is the point of bombing a hospital? Like literally

665
00:34:23,440 --> 00:34:26,200
Speaker 4: they just would rather people be dead than me trans

666
00:34:26,560 --> 00:34:30,640
Speaker 4: like that is that's the endgame of this, which is yeah, scary.

667
00:34:31,200 --> 00:34:35,200
Speaker 1: Yeah, it's so fucked up. So Superintendent of Public Instruction

668
00:34:35,320 --> 00:34:38,560
Speaker 1: Ryan Walters said CHAIA is on the front lines of

669
00:34:38,600 --> 00:34:41,360
Speaker 1: showing the world exactly what the radical left is all about,

670
00:34:41,600 --> 00:34:45,799
Speaker 1: lowering standards, pourn in schools and pushing woke indoctrination on

671
00:34:45,840 --> 00:34:48,640
Speaker 1: our kids. Because of her work, families across the country

672
00:34:48,719 --> 00:34:51,200
Speaker 1: know what is going on in schools across the country.

673
00:34:51,880 --> 00:34:55,640
Speaker 2: This is so like, this is like like what the fuck?

674
00:34:55,760 --> 00:34:56,760
Speaker 2: Levels are bad.

675
00:34:57,000 --> 00:34:58,680
Speaker 1: But I will say, though, as bad as this is,

676
00:34:58,960 --> 00:35:00,600
Speaker 1: some folks in Oklahoma are pushing back.

677
00:35:00,880 --> 00:35:01,479
Speaker 2: State Rep.

678
00:35:01,560 --> 00:35:05,200
Speaker 1: Mark McBride, chairman of the House Appropriation Subcommittee on Education, said,

679
00:35:05,480 --> 00:35:07,120
Speaker 1: I don't see any need to have a twenty eight

680
00:35:07,200 --> 00:35:09,640
Speaker 1: year old realtor from New York that has no children

681
00:35:09,880 --> 00:35:13,360
Speaker 1: appointed to this position when there are extremely qualified parents, teachers,

682
00:35:13,360 --> 00:35:16,879
Speaker 1: and librarians in Oklahoma, which I think like a little

683
00:35:16,920 --> 00:35:20,120
Speaker 1: bit of a drag mare. Like when somebody from Oklahoma

684
00:35:20,200 --> 00:35:22,560
Speaker 1: highlights that somebody is from New York, I think it's

685
00:35:22,560 --> 00:35:24,040
Speaker 1: like clear that that's not a compliment.

686
00:35:25,640 --> 00:35:32,400
Speaker 4: Yeah, from the Midwest, who's from Chicago, which is veryd Oklahoma,

687
00:35:32,480 --> 00:35:35,640
Speaker 4: But like when somebody really emphasizes the New York that

688
00:35:35,719 --> 00:35:37,920
Speaker 4: is not a compliment. Also, I did not realize that

689
00:35:37,960 --> 00:35:41,640
Speaker 4: she was twenty eight. That's wild, girl, You should be

690
00:35:41,640 --> 00:35:42,240
Speaker 4: at the club.

691
00:35:42,719 --> 00:35:46,600
Speaker 2: What are you doing so Representative.

692
00:35:46,600 --> 00:35:49,840
Speaker 1: Mickey Dollans, an Oklahoma City Democrat and former public school teacher,

693
00:35:50,080 --> 00:35:53,280
Speaker 1: said that this appointment might actually violate the department's rules

694
00:35:53,600 --> 00:35:57,040
Speaker 1: for advisory committees, which require members to be representative of

695
00:35:57,080 --> 00:36:00,279
Speaker 1: the people served. She's not from Oklahoma, like not a

696
00:36:00,400 --> 00:36:03,200
Speaker 1: parent in that district, so like difficult to say how

697
00:36:03,239 --> 00:36:05,640
Speaker 1: she would be representative of the people served.

698
00:36:06,000 --> 00:36:08,520
Speaker 2: And something I always.

699
00:36:08,440 --> 00:36:10,319
Speaker 1: I feel like I never really make it explicitly clear

700
00:36:10,360 --> 00:36:12,560
Speaker 1: when I'm talking about limbs of TikTok, which isn't often

701
00:36:12,600 --> 00:36:16,000
Speaker 1: because I cannot stand this person. But you might be thinking, like, well,

702
00:36:16,239 --> 00:36:18,960
Speaker 1: she doesn't come out and explicitly tell people to call

703
00:36:19,000 --> 00:36:22,319
Speaker 1: in bomb threats or harrass educators or like prevent kids

704
00:36:22,360 --> 00:36:24,920
Speaker 1: from getting care at hospitals. But that is part of

705
00:36:24,960 --> 00:36:28,080
Speaker 1: the strategy. It's called stochastic terror, and it's when you

706
00:36:28,239 --> 00:36:31,680
Speaker 1: use media or communications to sort of wink wink, nudge

707
00:36:31,800 --> 00:36:35,720
Speaker 1: nudge make somebody or something or an institution a target

708
00:36:35,800 --> 00:36:38,640
Speaker 1: of this kind of harassment. And so she's never going

709
00:36:38,719 --> 00:36:41,279
Speaker 1: to come out and say harass these people. She might

710
00:36:41,280 --> 00:36:44,200
Speaker 1: actually come out and say like, oh, well, I would

711
00:36:44,239 --> 00:36:48,680
Speaker 1: never advocate for harassment of people. But then she'll continue

712
00:36:48,719 --> 00:36:51,600
Speaker 1: to do the same thing that gets people and institutions

713
00:36:51,640 --> 00:36:54,080
Speaker 1: harassed time and time and time again. So I would

714
00:36:54,160 --> 00:36:56,399
Speaker 1: argue that she knows exactly what she's doing. And think

715
00:36:56,400 --> 00:36:58,719
Speaker 1: about it, like if every time you mentioned something that

716
00:36:58,760 --> 00:37:02,080
Speaker 1: you didn't like happening a school on your massive platform,

717
00:37:02,320 --> 00:37:04,680
Speaker 1: if a few hours later that school had to be

718
00:37:04,719 --> 00:37:07,799
Speaker 1: evacuated because of a bomb threat or harassment, what did

719
00:37:07,880 --> 00:37:10,120
Speaker 1: you stop doing that after a while, Like if you

720
00:37:10,160 --> 00:37:11,360
Speaker 1: really didn't want that to happen.

721
00:37:11,880 --> 00:37:15,080
Speaker 3: Yeah, it's always funny, And.

722
00:37:15,080 --> 00:37:18,600
Speaker 4: By funny, I mean just depressing that this is the case,

723
00:37:18,760 --> 00:37:21,760
Speaker 4: and probably intentionally the case, but it was always funny

724
00:37:21,800 --> 00:37:24,600
Speaker 4: that they seem to be doing exactly what they always are,

725
00:37:24,640 --> 00:37:27,640
Speaker 4: accusing the quote unquote radical left of doing where it's like,

726
00:37:27,800 --> 00:37:31,760
Speaker 4: I'm sorry, like the quote left you were talking about.

727
00:37:31,800 --> 00:37:34,560
Speaker 3: The response to everything is just we'll go out and

728
00:37:34,680 --> 00:37:37,200
Speaker 3: vote and like whatever or like give us what.

729
00:37:37,320 --> 00:37:37,680
Speaker 2: I don't know.

730
00:37:37,719 --> 00:37:40,840
Speaker 3: It's kind of like, this is it's so crazy.

731
00:37:40,960 --> 00:37:43,319
Speaker 4: You only the ones bombing people, You all the ones

732
00:37:43,320 --> 00:37:46,360
Speaker 4: called in bomb threats, like take a look at the mirror.

733
00:37:46,080 --> 00:37:49,160
Speaker 1: Please absolutely, And to put this in a larger context,

734
00:37:49,280 --> 00:37:52,640
Speaker 1: last year, a court ruled that Oklahoma can enforce its

735
00:37:52,719 --> 00:37:57,160
Speaker 1: law banning and criminalizing gender affirming care for transminors, while

736
00:37:57,200 --> 00:38:00,279
Speaker 1: a suit against it is being heard, that law into

737
00:38:00,280 --> 00:38:03,600
Speaker 1: effect would make providing gender affirming care in Oklahoma a

738
00:38:03,640 --> 00:38:06,640
Speaker 1: felony right. And so when you when we're talking about

739
00:38:06,640 --> 00:38:09,279
Speaker 1: this happening in Oklahoma, it's really important to understand that

740
00:38:09,400 --> 00:38:12,920
Speaker 1: larger context of what folks there are up against. The

741
00:38:13,000 --> 00:38:15,800
Speaker 1: climate that they're up against. It is not a safe

742
00:38:15,840 --> 00:38:19,800
Speaker 1: climate for these youths. And I just think that it

743
00:38:19,880 --> 00:38:23,359
Speaker 1: breaks my heart that you've got dipshits like this who

744
00:38:23,400 --> 00:38:27,640
Speaker 1: are promoting people like Chaia to positions of power within

745
00:38:27,680 --> 00:38:29,560
Speaker 1: a school district that she does not even have any

746
00:38:29,560 --> 00:38:33,279
Speaker 1: connection to. Just to drive home how much they are

747
00:38:33,320 --> 00:38:37,360
Speaker 1: not welcome there, and yeah, it's just really horrifying. I

748
00:38:37,400 --> 00:38:41,279
Speaker 1: think that Superintendent of Public Instruction Ryan Walters should really

749
00:38:41,320 --> 00:38:45,080
Speaker 1: be a shame because also this is not serving the

750
00:38:45,160 --> 00:38:47,920
Speaker 1: constituents and the parents and the youth of that community,

751
00:38:48,000 --> 00:38:51,560
Speaker 1: like inviting a hate monger in. And they're always like,

752
00:38:51,680 --> 00:38:53,680
Speaker 1: just kind of like what you said. They're always like, oh, well,

753
00:38:53,880 --> 00:38:55,960
Speaker 1: it's people on the left who are making everything woke

754
00:38:56,040 --> 00:38:59,719
Speaker 1: and making everything political, and blah blah blah. You are doing that, sir,

755
00:39:00,120 --> 00:39:02,640
Speaker 1: by you bringing this person with no connection to the

756
00:39:02,640 --> 00:39:05,480
Speaker 1: community in and giving them a bigger platform, giving them

757
00:39:05,480 --> 00:39:08,160
Speaker 1: a position of power in your community, you are the

758
00:39:08,160 --> 00:39:10,799
Speaker 1: one who is politicizing everything. You are the one who

759
00:39:10,840 --> 00:39:14,319
Speaker 1: is making everything inflammatory. I just I really hate it.

760
00:39:14,360 --> 00:39:15,160
Speaker 1: I really hate it.

761
00:39:15,440 --> 00:39:15,880
Speaker 6: Yeah.

762
00:39:16,080 --> 00:39:19,200
Speaker 4: I also like most of these people, I'm like, name

763
00:39:19,280 --> 00:39:21,919
Speaker 4: a single trans kid that you know, Like, yeah, I

764
00:39:22,000 --> 00:39:26,160
Speaker 4: guarantee you are just this is something you think is

765
00:39:26,200 --> 00:39:27,520
Speaker 4: going to be a big issue, but.

766
00:39:27,480 --> 00:39:29,480
Speaker 3: Without even really looking at the reality, which is not

767
00:39:29,520 --> 00:39:31,440
Speaker 3: to say that there aren't trans kids in these communities.

768
00:39:31,880 --> 00:39:32,799
Speaker 3: There absolutely are.

769
00:39:33,120 --> 00:39:35,560
Speaker 4: Like it's always coming from people that just kind of

770
00:39:35,600 --> 00:39:39,480
Speaker 4: have this imagined threat in their brain without ever having

771
00:39:39,520 --> 00:39:42,480
Speaker 4: interacted with the trans community or again, like a single

772
00:39:42,520 --> 00:39:45,960
Speaker 4: trans kid, which you know. Yeah, usually people that actually

773
00:39:46,080 --> 00:39:48,880
Speaker 4: have experience talking to trans kids or talking to the

774
00:39:48,920 --> 00:39:52,239
Speaker 4: trans community don't end up feeling this way, which is

775
00:39:52,320 --> 00:39:56,160
Speaker 4: part of why this happens. But yeah, why you know,

776
00:39:56,200 --> 00:40:00,960
Speaker 4: the lack of exposure to trans people is why this happens.

777
00:40:01,000 --> 00:40:01,560
Speaker 3: But yeah, it is.

778
00:40:01,640 --> 00:40:03,480
Speaker 4: It is always weird that is coming from kind of

779
00:40:03,480 --> 00:40:07,200
Speaker 4: this imagined threat than even any sense of reality.

780
00:40:07,600 --> 00:40:11,520
Speaker 2: Absolutely, it's infuriating. I do have a little bit of good.

781
00:40:11,280 --> 00:40:14,839
Speaker 1: News, and that was an upsetting story for all of us,

782
00:40:14,840 --> 00:40:19,200
Speaker 1: but so little good news. So called conversion therapy is

783
00:40:19,239 --> 00:40:22,680
Speaker 1: an abusive practice that is sensibly meant to change someone's

784
00:40:22,680 --> 00:40:26,120
Speaker 1: sexual orientation or gender identity that has been widely debunked,

785
00:40:26,120 --> 00:40:29,920
Speaker 1: and pretty much every medical association, like the American Psychological Association,

786
00:40:30,000 --> 00:40:33,360
Speaker 1: the American Psychiatric Association, the American Medical Association consider it

787
00:40:33,400 --> 00:40:36,799
Speaker 1: to be a dangerous pseudoscience. Rightly, twenty two states and

788
00:40:37,040 --> 00:40:40,160
Speaker 1: DC currently have laws banning this practice from being used

789
00:40:40,160 --> 00:40:43,160
Speaker 1: on minors. It's horrible, But here's the good news to

790
00:40:43,480 --> 00:40:47,400
Speaker 1: Twitter alternatives. Spoutable run by Christopher Bouse, who we actually

791
00:40:47,400 --> 00:40:50,160
Speaker 1: have talked to on the podcast before, and Post have

792
00:40:50,320 --> 00:40:55,720
Speaker 1: both banned content promoting conversion therapy. So most mainstream social

793
00:40:55,760 --> 00:40:59,400
Speaker 1: media platforms like TikTok, Pinterest, nextdoor, and Facebook and Instagram

794
00:40:59,800 --> 00:41:03,280
Speaker 1: all all explicitly ban content promoting conversion therapy.

795
00:41:03,640 --> 00:41:05,680
Speaker 2: And now these smaller.

796
00:41:05,239 --> 00:41:09,239
Speaker 1: Sort of niche Twitter alternatives Post and spoutable are also

797
00:41:09,440 --> 00:41:12,759
Speaker 1: joining that. Glad had this to say. The leadership of

798
00:41:12,760 --> 00:41:15,920
Speaker 1: both Post and spoutable and adopting new policies prohibiting so

799
00:41:16,000 --> 00:41:19,720
Speaker 1: called conversion therapy content puts these companies ahead of many others.

800
00:41:19,960 --> 00:41:23,399
Speaker 1: This is from GLAD CEO Sarah Kate Ellis. Glad are

801
00:41:23,520 --> 00:41:26,080
Speaker 1: just all social media platforms to adopt and enforce this

802
00:41:26,160 --> 00:41:30,120
Speaker 1: policy to protect their LGBTQ users. So this is good,

803
00:41:30,239 --> 00:41:31,839
Speaker 1: I think for a couple of reasons. One of them

804
00:41:31,880 --> 00:41:34,680
Speaker 1: is that we've talked on the podcast before about how changes,

805
00:41:34,719 --> 00:41:38,480
Speaker 1: both good changes and bad changes for bigger platforms can

806
00:41:38,560 --> 00:41:41,400
Speaker 1: be this domino effect where other platforms feel the need

807
00:41:41,440 --> 00:41:43,319
Speaker 1: to follow suit, and I think this is a good

808
00:41:43,320 --> 00:41:46,239
Speaker 1: example of the way that for smaller platforms it can

809
00:41:46,280 --> 00:41:48,560
Speaker 1: create a domino effect of the same thing, where these

810
00:41:48,960 --> 00:41:52,920
Speaker 1: smaller niche platforms are making this change and that changes

811
00:41:52,960 --> 00:41:55,040
Speaker 1: and being reflected for other small platforms.

812
00:41:55,080 --> 00:41:57,240
Speaker 2: And so yeah, I think it's cool to see how.

813
00:41:57,080 --> 00:42:00,520
Speaker 1: That domino effect can be working to create positive change

814
00:42:00,760 --> 00:42:03,000
Speaker 1: for smaller alternative platforms as well.

815
00:42:03,200 --> 00:42:06,080
Speaker 3: Yeah, definitely great to hear some good news.

816
00:42:06,080 --> 00:42:09,319
Speaker 4: And yeah, it was like the bare minimum of you know,

817
00:42:09,400 --> 00:42:16,560
Speaker 4: protecting your queer and trans users, customers, whatever, but it is.

818
00:42:16,640 --> 00:42:18,600
Speaker 4: It is such an important stepstake and it's good to

819
00:42:18,640 --> 00:42:21,120
Speaker 4: see that that's becoming more common.

820
00:42:25,200 --> 00:42:25,359
Speaker 6: More.

821
00:42:25,360 --> 00:42:38,520
Speaker 1: After a quick break, let's get right back into it.

822
00:42:41,400 --> 00:42:44,799
Speaker 1: So we already know that technology like facial recognition is

823
00:42:45,000 --> 00:42:48,400
Speaker 1: racist and sexist and unreliable and should not be used

824
00:42:48,440 --> 00:42:50,879
Speaker 1: for a whole host of reasons. And here is yet

825
00:42:50,920 --> 00:42:54,160
Speaker 1: another story that is a horrifying example of what happens

826
00:42:54,160 --> 00:42:57,640
Speaker 1: when police rely on it anyway to make arrests. So

827
00:42:57,840 --> 00:43:00,600
Speaker 1: Harvey Murphy Junior is a sixty one year old man

828
00:43:00,680 --> 00:43:03,200
Speaker 1: who was arrested in Texas for an armed robbery of

829
00:43:03,200 --> 00:43:06,480
Speaker 1: a Sunglasses Hut retail store in twenty twenty two, a

830
00:43:06,520 --> 00:43:09,280
Speaker 1: crime that he did not and could not have committed.

831
00:43:09,600 --> 00:43:13,719
Speaker 1: After facial recognition technology Fossley matched him as a suspect. So,

832
00:43:13,760 --> 00:43:16,560
Speaker 1: according to The Washington Post, a representative of a nearby

833
00:43:16,680 --> 00:43:20,920
Speaker 1: Macy's told Houston police during the investigation that the company's system,

834
00:43:21,200 --> 00:43:24,640
Speaker 1: which scanned surveillance camera footage for faces in an internal

835
00:43:24,640 --> 00:43:28,600
Speaker 1: shoplifter database, found evidence that Murphy had robbed both stores,

836
00:43:28,640 --> 00:43:31,680
Speaker 1: both the Sunglasses Hut and the Macy's. Now, police do

837
00:43:31,760 --> 00:43:35,120
Speaker 1: say that after the facial recognition technology flagged Murphy, they

838
00:43:35,160 --> 00:43:38,120
Speaker 1: then showed his image to the cashier at Sunglasses Hut,

839
00:43:38,200 --> 00:43:42,040
Speaker 1: who positively idd Murphy as the assailant, but it could

840
00:43:42,040 --> 00:43:44,479
Speaker 1: not have been him because he was actually already in

841
00:43:44,520 --> 00:43:48,680
Speaker 1: prison in Sacramento, California, some two thousand miles away at

842
00:43:48,719 --> 00:43:51,560
Speaker 1: the time the crime was committed. And he actually only

843
00:43:51,600 --> 00:43:53,360
Speaker 1: even found out that there was a warrant for his

844
00:43:53,480 --> 00:43:56,239
Speaker 1: arrest for this crime in Texas when he was going

845
00:43:56,280 --> 00:43:59,520
Speaker 1: to renew his driver's license in Sacramento, when the DMV

846
00:43:59,680 --> 00:44:02,200
Speaker 1: flat that he had an outstanding warrant and arrested him

847
00:44:02,239 --> 00:44:04,279
Speaker 1: for this crime that he could not have done. So

848
00:44:04,440 --> 00:44:07,160
Speaker 1: here's where the story gets really awful. While he was

849
00:44:07,200 --> 00:44:09,720
Speaker 1: in prison awaiting trial for this crime that he could

850
00:44:09,719 --> 00:44:13,000
Speaker 1: not have committed, he was beaten and sexually assaulted by

851
00:44:13,040 --> 00:44:17,440
Speaker 1: three men. So hours after that assault, he was cleared

852
00:44:17,440 --> 00:44:21,480
Speaker 1: of all charges and released, and now he assuming Macy's

853
00:44:21,600 --> 00:44:25,000
Speaker 1: Sunglasses Huts parent company and three people that his attorneys

854
00:44:25,000 --> 00:44:27,239
Speaker 1: say were involved in the case. He's seeking ten million

855
00:44:27,280 --> 00:44:29,520
Speaker 1: dollars in damages and says the assault left him with

856
00:44:29,640 --> 00:44:30,799
Speaker 1: lifelong injuries.

857
00:44:31,400 --> 00:44:37,360
Speaker 4: Yeah, that is such a horrifying story. It's look also,

858
00:44:37,400 --> 00:44:42,520
Speaker 4: I mean, I we know that prisons are a place

859
00:44:42,640 --> 00:44:44,920
Speaker 4: where this happens a lot of times, and it is

860
00:44:45,000 --> 00:44:51,040
Speaker 4: so for some reason, the solution is never to fix

861
00:44:51,320 --> 00:44:55,520
Speaker 4: those problems and like maybe stop so many people going

862
00:44:55,520 --> 00:44:58,480
Speaker 4: to prison and do prison reform, and the solution is

863
00:44:58,520 --> 00:45:00,000
Speaker 4: always just to send more people to prison.

864
00:45:00,000 --> 00:45:03,600
Speaker 3: And what else is new that is? Yeah, that is

865
00:45:03,680 --> 00:45:08,040
Speaker 3: so horrifying. I don is. I hope he sues them

866
00:45:08,080 --> 00:45:09,920
Speaker 3: for whatever they're worth.

867
00:45:09,960 --> 00:45:12,880
Speaker 4: And yeah, that's that's horrible.

868
00:45:13,360 --> 00:45:16,440
Speaker 1: It is And I also hate this statement from macy

869
00:45:16,560 --> 00:45:20,320
Speaker 1: So Macy's, when Washington Posts talked to them, they declined

870
00:45:20,360 --> 00:45:23,120
Speaker 1: to comment on the pending litigation, but they did say

871
00:45:23,120 --> 00:45:27,440
Speaker 1: in a previous statement that Macy's quote uses facial recognition

872
00:45:27,480 --> 00:45:30,920
Speaker 1: and conjunction with other securities methods in a small subset

873
00:45:30,960 --> 00:45:34,040
Speaker 1: of Macy's stores with high incidences of organized retail theft

874
00:45:34,040 --> 00:45:38,040
Speaker 1: and repeat offenders, and so that statement is not about

875
00:45:38,200 --> 00:45:40,279
Speaker 1: this specific case. They were like, oh, we're not going

876
00:45:40,320 --> 00:45:42,520
Speaker 1: to talk about that. However, it almost sounds like they're

877
00:45:42,560 --> 00:45:45,320
Speaker 1: saying like, well, if a few people have to be

878
00:45:45,440 --> 00:45:50,799
Speaker 1: arrested wrongly because of our faulty use of this surveillance

879
00:45:50,840 --> 00:45:55,440
Speaker 1: techt it's okay if it protects our merchandise. Like, I

880
00:45:55,520 --> 00:45:59,120
Speaker 1: just feel like the focus on retail theft and like

881
00:45:59,520 --> 00:46:03,640
Speaker 1: quote organized theft, it makes it seem like the most

882
00:46:03,719 --> 00:46:07,279
Speaker 1: important thing here is the Macy's merchandise, not the fact

883
00:46:07,320 --> 00:46:10,680
Speaker 1: that they are routinely falsely arresting people.

884
00:46:10,560 --> 00:46:12,920
Speaker 2: Who then are could be assaulted in prison.

885
00:46:13,040 --> 00:46:19,600
Speaker 4: Well, yeah, this is America where yeah, property damage is first,

886
00:46:19,920 --> 00:46:22,680
Speaker 4: is the worst crime you could commit, or property theft

887
00:46:22,840 --> 00:46:25,440
Speaker 4: is the worst ufront, especially if it's sort of a

888
00:46:25,440 --> 00:46:28,120
Speaker 4: corporation that is big bad.

889
00:46:29,160 --> 00:46:32,800
Speaker 1: The most important thing we should be protecting are the sunglasses, Jolie.

890
00:46:32,880 --> 00:46:33,799
Speaker 2: I cannot stress that.

891
00:46:33,880 --> 00:46:39,360
Speaker 4: Enough, those sunglasses huts. That is a staple of American culture.

892
00:46:39,520 --> 00:46:41,640
Speaker 4: And if we're not going to if.

893
00:46:41,560 --> 00:46:44,479
Speaker 3: The facial recognition isn't going to protect it, who will.

894
00:46:44,520 --> 00:46:48,840
Speaker 1: Apparently, so, this isn't the first time that something like

895
00:46:48,880 --> 00:46:51,440
Speaker 1: this has happened. We talked about Portia Woodruff, the heavily

896
00:46:51,480 --> 00:46:53,719
Speaker 1: pregnant black woman who was arrested for a crime she

897
00:46:53,760 --> 00:46:56,160
Speaker 1: had nothing to do with because of this technology. Rite

898
00:46:56,200 --> 00:46:59,520
Speaker 1: Aid was actually banned from using facial recognition technology for

899
00:46:59,600 --> 00:47:03,440
Speaker 1: five years after the ftc found at the store. Misused

900
00:47:03,440 --> 00:47:06,960
Speaker 1: facial recognition to fossly accuse people of theft and harass them,

901
00:47:07,040 --> 00:47:12,120
Speaker 1: causing embarrassment, harassment, and other harm, including physically searching an

902
00:47:12,120 --> 00:47:14,359
Speaker 1: eleven year old girl in a way that left her

903
00:47:14,440 --> 00:47:17,200
Speaker 1: so distraught that her mom had to miss work.

904
00:47:17,360 --> 00:47:19,360
Speaker 3: Oh my god, like awful.

905
00:47:19,400 --> 00:47:21,000
Speaker 1: I honestly can't believe that. It's like, okay, well you

906
00:47:21,040 --> 00:47:23,759
Speaker 1: can't use this technology for five years. I feel like,

907
00:47:23,800 --> 00:47:26,120
Speaker 1: once your technology has been misused to the point where

908
00:47:26,120 --> 00:47:29,560
Speaker 1: you are traumatizing children for no real reason, you should

909
00:47:29,600 --> 00:47:30,760
Speaker 1: lose those privileges forever.

910
00:47:30,840 --> 00:47:33,040
Speaker 3: In my book, yeah, I there.

911
00:47:33,040 --> 00:47:36,680
Speaker 4: Well, so there's something already so dystopian about living in

912
00:47:36,719 --> 00:47:40,000
Speaker 4: this like hyper police state that we're all in, where

913
00:47:40,000 --> 00:47:43,640
Speaker 4: it's just like we're constantly, constantly being monitored, and there

914
00:47:43,719 --> 00:47:46,680
Speaker 4: is another level of dystopia of that that it's like

915
00:47:47,280 --> 00:47:47,719
Speaker 4: it's not.

916
00:47:47,680 --> 00:47:50,760
Speaker 3: Even like, oh, you can't be doing any crime.

917
00:47:50,800 --> 00:47:52,919
Speaker 4: You gotta be at your best behavior old times because

918
00:47:52,920 --> 00:47:55,839
Speaker 4: you're always being watched. Now it's just like you never know,

919
00:47:56,000 --> 00:47:58,520
Speaker 4: and like especially if you are a person of color,

920
00:47:58,520 --> 00:48:01,880
Speaker 4: if you're a black person. Yeah, it's just there's just

921
00:48:01,960 --> 00:48:04,919
Speaker 4: like another level of dystopia.

922
00:48:04,160 --> 00:48:09,799
Speaker 1: And doing it in service of like protecting merchandise and

923
00:48:09,880 --> 00:48:12,320
Speaker 1: keeping the wheels of capitalism Greece, Like it's.

924
00:48:12,200 --> 00:48:15,320
Speaker 4: Just protecting Macy's and the song glass is my like,

925
00:48:15,360 --> 00:48:16,040
Speaker 4: are you kidding me?

926
00:48:17,400 --> 00:48:21,440
Speaker 1: It's just so it's just so like it's just so sad.

927
00:48:21,800 --> 00:48:25,240
Speaker 1: We deserve such, we deserve better. It's just so sad.

928
00:48:25,960 --> 00:48:29,120
Speaker 1: And to your point about like, we know that this

929
00:48:29,239 --> 00:48:34,160
Speaker 1: kind of technology disproportionately impacts women, people of color, black people,

930
00:48:34,239 --> 00:48:38,000
Speaker 1: black women especially. However, I should tell you Murphy is white.

931
00:48:38,239 --> 00:48:40,120
Speaker 1: There have been six other people that we know of

932
00:48:40,160 --> 00:48:42,560
Speaker 1: who have been falsely arrested because of this technology. All

933
00:48:42,560 --> 00:48:44,960
Speaker 1: of them have been black. Murphy is the first white

934
00:48:45,120 --> 00:48:48,360
Speaker 1: man that we know of this happening to being falsely

935
00:48:48,440 --> 00:48:50,560
Speaker 1: arrested because of facial recognition technology.

936
00:48:50,600 --> 00:48:51,799
Speaker 2: And so I don't know.

937
00:48:51,840 --> 00:48:53,200
Speaker 1: Part of me wonders if this is going to be

938
00:48:53,200 --> 00:48:55,400
Speaker 1: one of those things where it's like when the harms

939
00:48:55,640 --> 00:48:59,040
Speaker 1: were impacting women and black people and people of color,

940
00:48:59,200 --> 00:49:02,959
Speaker 1: people were like, eh, whatever, but maybe the harm will

941
00:49:03,000 --> 00:49:05,680
Speaker 1: then extend to everybody and then it's like, oh wait,

942
00:49:06,200 --> 00:49:08,640
Speaker 1: I could be falsely arrested for this, like hold on.

943
00:49:09,560 --> 00:49:10,680
Speaker 2: So we will have to.

944
00:49:10,680 --> 00:49:14,040
Speaker 1: See, but it definitely is again people like we talked

945
00:49:14,080 --> 00:49:16,920
Speaker 1: to doctor Joy Bolamwini, I'm an AI researcher on the

946
00:49:16,920 --> 00:49:20,480
Speaker 1: podcast a while back. People have been very clear about

947
00:49:20,520 --> 00:49:26,120
Speaker 1: the psychic, cosmic, deep threat that this technology poses to

948
00:49:26,200 --> 00:49:31,080
Speaker 1: all of us and police departments and retail establishments just

949
00:49:31,160 --> 00:49:34,320
Speaker 1: keep using it. It's like those warnings are just going unheard.

950
00:49:34,840 --> 00:49:40,200
Speaker 4: Yeah, absolutely, Like they're just there's no logical reason for

951
00:49:40,280 --> 00:49:43,200
Speaker 4: this to be continued to be used at such a

952
00:49:43,200 --> 00:49:46,160
Speaker 4: wide scale, Like it only causes like it seems like

953
00:49:46,239 --> 00:49:49,360
Speaker 4: it's just causing more harm than actually like and I

954
00:49:49,600 --> 00:49:51,640
Speaker 4: don't know what the numbers are for, like the times

955
00:49:51,680 --> 00:49:54,479
Speaker 4: to accurate or whatever, but I guarantee it's not enough

956
00:49:54,520 --> 00:49:58,640
Speaker 4: to kind of justify the opposite. And again, there is

957
00:49:58,680 --> 00:50:01,080
Speaker 4: something really weird about the fact that it's like we've

958
00:50:01,080 --> 00:50:05,719
Speaker 4: all just kind of given up the ability to have

959
00:50:05,800 --> 00:50:08,920
Speaker 4: any sense of privacy in public, which I guess I

960
00:50:08,920 --> 00:50:11,080
Speaker 4: don't know privacy and public whatever, but like, have any

961
00:50:11,080 --> 00:50:12,840
Speaker 4: sense of privacy, you have any sense of just like

962
00:50:13,320 --> 00:50:15,400
Speaker 4: being able to exist in the world without having like

963
00:50:15,520 --> 00:50:19,560
Speaker 4: eyes on you, metaphorical eyes on you, you know.

964
00:50:20,680 --> 00:50:23,320
Speaker 1: And speaking of folks trying to warn folks in power

965
00:50:23,360 --> 00:50:26,640
Speaker 1: of the harm that this kind of technology presents, parents

966
00:50:26,680 --> 00:50:30,440
Speaker 1: are actually talking about the threats posed by AI to

967
00:50:30,760 --> 00:50:33,680
Speaker 1: young people. A coalition of parents working alongside the group

968
00:50:33,800 --> 00:50:37,400
Speaker 1: Parents together wrote a letter to TikTok expressing concerns about

969
00:50:37,480 --> 00:50:42,120
Speaker 1: AI generated influencers, asking the platform to clearly label when

970
00:50:42,160 --> 00:50:45,719
Speaker 1: an influencer is not real but AI generated, warning that

971
00:50:45,760 --> 00:50:48,880
Speaker 1: AI generated influencers can make things like poor body image,

972
00:50:48,920 --> 00:50:51,360
Speaker 1: body dysmorphia, and self esteem issues worse.

973
00:50:51,800 --> 00:50:53,560
Speaker 2: So the letter was sent to TikTok.

974
00:50:53,280 --> 00:50:57,160
Speaker 1: CEO and it reads, TikTok is flooding kids feeds with

975
00:50:57,200 --> 00:51:01,760
Speaker 1: fake computer generated people pretending to be real influencers. AI

976
00:51:01,840 --> 00:51:05,319
Speaker 1: generated influencers created by companies to make a profit, post

977
00:51:05,400 --> 00:51:07,719
Speaker 1: photos and videos of people who appear to be real

978
00:51:07,880 --> 00:51:11,359
Speaker 1: but don't actually exist. These AI generated people do things

979
00:51:11,440 --> 00:51:14,600
Speaker 1: like apply makeup on flawless skin and show off perfect bodies,

980
00:51:14,680 --> 00:51:18,279
Speaker 1: creating an extreme and utterly unattainable beauty standard. Most of

981
00:51:18,280 --> 00:51:20,960
Speaker 1: the millions of kids who encounter these accounts won't know

982
00:51:21,000 --> 00:51:23,160
Speaker 1: the people they aspire to look like are not real

983
00:51:23,200 --> 00:51:25,960
Speaker 1: people at all. Right now, TikTok relies on companies that

984
00:51:26,040 --> 00:51:28,680
Speaker 1: create these accounts to label them as AI but with

985
00:51:28,760 --> 00:51:31,240
Speaker 1: thousands of dollars per post on the line, they often

986
00:51:31,280 --> 00:51:35,000
Speaker 1: do not. That's why TikTok must proactively and clearly identify

987
00:51:35,040 --> 00:51:37,439
Speaker 1: these accounts so young users know which accounts are real

988
00:51:37,440 --> 00:51:40,960
Speaker 1: people and which are computer generated, so the parents their

989
00:51:41,480 --> 00:51:44,960
Speaker 1: concerns are not unfounded. Nearly half forty six percent of

990
00:51:45,000 --> 00:51:48,799
Speaker 1: adolescents aged thirteen to seventeen said that social media platforms

991
00:51:48,880 --> 00:51:51,919
Speaker 1: make them feel worse, and TikTok has already been taken

992
00:51:51,960 --> 00:51:55,040
Speaker 1: to task for kind of I want maybe allowing is

993
00:51:55,080 --> 00:51:59,520
Speaker 1: too strong, but containing content that glorifies disordered eating, right,

994
00:51:59,680 --> 00:52:02,640
Speaker 1: they have rules against that content, but those rules are

995
00:52:02,640 --> 00:52:05,600
Speaker 1: pretty easily circumvented, and then they sort of don't then,

996
00:52:05,760 --> 00:52:08,160
Speaker 1: so they might be like, oh, like pro eating disorder

997
00:52:08,239 --> 00:52:12,239
Speaker 1: content is disallowed, but then when people easily get around it,

998
00:52:12,280 --> 00:52:14,319
Speaker 1: they don't really have a fix for that. And so

999
00:52:14,600 --> 00:52:18,920
Speaker 1: right now, TikTok is supposed to clearly label AI generated content,

1000
00:52:19,280 --> 00:52:22,520
Speaker 1: but Parents Together campaign director Shelby NOTx says that it's

1001
00:52:22,560 --> 00:52:25,520
Speaker 1: really kind of not doing that because how that works

1002
00:52:25,560 --> 00:52:29,200
Speaker 1: now is that the AI virtual influencer will just put

1003
00:52:29,280 --> 00:52:33,160
Speaker 1: in their bio like hashtag AI influencer, and you would

1004
00:52:33,200 --> 00:52:37,680
Speaker 1: only know that that influencer was AI generated if you

1005
00:52:37,719 --> 00:52:40,800
Speaker 1: look at their bio, not on the content itself. Knox

1006
00:52:40,840 --> 00:52:43,799
Speaker 1: told NBC, I'm not sure that your average kid knows

1007
00:52:43,800 --> 00:52:47,040
Speaker 1: that a virtual influencer is industry speak for this person

1008
00:52:47,120 --> 00:52:49,640
Speaker 1: is not real. So because these companies are making money

1009
00:52:49,680 --> 00:52:52,880
Speaker 1: on TikTok's platform, and it is contributing to a dangerous culture.

1010
00:52:53,200 --> 00:52:55,680
Speaker 1: Our view is that TikTok has a responsibility to come

1011
00:52:55,680 --> 00:52:58,759
Speaker 1: in and figure out how to consistently and visibly label.

1012
00:52:58,600 --> 00:53:00,319
Speaker 2: These accounts and these videos.

1013
00:53:00,600 --> 00:53:03,440
Speaker 1: I had never really thought about the threat posed by

1014
00:53:03,480 --> 00:53:06,719
Speaker 1: these AI influencers. I will say this though. Some of

1015
00:53:06,760 --> 00:53:09,719
Speaker 1: them really do look real, but they have this like

1016
00:53:10,840 --> 00:53:16,440
Speaker 1: impossibly conventionally attractive look, like they're skinny to the point

1017
00:53:16,440 --> 00:53:19,880
Speaker 1: where it's like bodies like this is not how a

1018
00:53:19,880 --> 00:53:22,120
Speaker 1: body looks, or like they're They're beautiful to a point

1019
00:53:22,160 --> 00:53:25,160
Speaker 1: that is like unachievable and unrealistic. And it's like, yeah,

1020
00:53:25,160 --> 00:53:27,560
Speaker 1: because they're not real. And so I'm an adult when

1021
00:53:27,600 --> 00:53:30,719
Speaker 1: I see content like that, I generally can tell when

1022
00:53:30,719 --> 00:53:32,439
Speaker 1: it's not a real person. But if you're a little

1023
00:53:32,520 --> 00:53:35,080
Speaker 1: kid and you're looking for an influencer to look up to,

1024
00:53:35,480 --> 00:53:36,200
Speaker 1: you might not know.

1025
00:53:36,840 --> 00:53:39,480
Speaker 4: So I just look this up now because I have

1026
00:53:39,560 --> 00:53:41,880
Speaker 4: not had this come up on my free paget. I

1027
00:53:41,920 --> 00:53:46,160
Speaker 4: have had the weird like AI kind of MPC things

1028
00:53:46,200 --> 00:53:47,640
Speaker 4: come up on my page.

1029
00:53:47,320 --> 00:53:49,680
Speaker 3: All the time, which are always weird. But yeah, that

1030
00:53:49,760 --> 00:53:50,560
Speaker 3: is that is free.

1031
00:53:50,840 --> 00:53:55,160
Speaker 4: That is not really expected those are actually like uncanny,

1032
00:53:55,400 --> 00:53:58,440
Speaker 4: like weird, Like I could totally guesh see like a

1033
00:53:58,520 --> 00:54:00,960
Speaker 4: kid looking at that and it's a real.

1034
00:54:00,800 --> 00:54:04,520
Speaker 3: Person that is so creepy.

1035
00:54:04,560 --> 00:54:07,799
Speaker 4: And again, like going to the other side of this

1036
00:54:07,960 --> 00:54:14,600
Speaker 4: issue is like influencing is real work that's often you know,

1037
00:54:14,719 --> 00:54:19,000
Speaker 4: not taken seriously because it is primarily women that do it.

1038
00:54:19,000 --> 00:54:21,600
Speaker 4: It is like a lot of the kind of like

1039
00:54:22,200 --> 00:54:25,319
Speaker 4: are their valid criticisms of influencers. Yes, However, like yeah,

1040
00:54:25,320 --> 00:54:27,160
Speaker 4: a lot of a lot of the criticism does also

1041
00:54:27,239 --> 00:54:31,960
Speaker 4: just come from misogyny. And it's like, you know, again,

1042
00:54:32,440 --> 00:54:35,400
Speaker 4: the jobs that are always going to be affected first

1043
00:54:35,440 --> 00:54:37,200
Speaker 4: or kind of the people that are already are always

1044
00:54:37,239 --> 00:54:40,520
Speaker 4: going to be like affected warriors are sex workers, women,

1045
00:54:41,120 --> 00:54:44,560
Speaker 4: women of color. And it's like this is another example

1046
00:54:44,560 --> 00:54:47,880
Speaker 4: of like an industry that is primarily female and is

1047
00:54:48,760 --> 00:54:52,000
Speaker 4: you know not taken seriously because it is primarily female

1048
00:54:52,600 --> 00:54:54,960
Speaker 4: being taken over by all these tech bros that are

1049
00:54:54,960 --> 00:54:57,960
Speaker 4: just gonna make the situation way worse and take take

1050
00:54:58,000 --> 00:55:00,879
Speaker 4: all the bad things about influencing and make that the

1051
00:55:00,920 --> 00:55:05,160
Speaker 4: main thing. Yeah, that is so scary. I can we

1052
00:55:05,200 --> 00:55:07,160
Speaker 4: go to like can we can we backtrack on the

1053
00:55:07,200 --> 00:55:10,719
Speaker 4: whole like trying to make fake people thing and like

1054
00:55:11,080 --> 00:55:13,200
Speaker 4: just make like if you want a fake thing to

1055
00:55:13,280 --> 00:55:15,560
Speaker 4: be your influencer, Like, can it be like a cartoon?

1056
00:55:16,320 --> 00:55:19,840
Speaker 4: Just be like a like a what's the like space

1057
00:55:19,920 --> 00:55:21,680
Speaker 4: jam or something where we just have like a Looney

1058
00:55:21,680 --> 00:55:23,520
Speaker 4: Tunes character in the real world for no reasons.

1059
00:55:23,560 --> 00:55:25,880
Speaker 3: Like it's like I don't know, Like I feel like.

1060
00:55:25,880 --> 00:55:28,480
Speaker 4: There there's got to be a better option if you

1061
00:55:28,640 --> 00:55:30,400
Speaker 4: really don't want to pay human being.

1062
00:55:30,840 --> 00:55:35,800
Speaker 1: Give Lola Buddy a spot right, Like it doesn't Yeah,

1063
00:55:36,080 --> 00:55:38,439
Speaker 1: I gin guess part of me is like when people work,

1064
00:55:38,520 --> 00:55:42,040
Speaker 1: when when conversations about AI became so ubiquitous, who does

1065
00:55:42,080 --> 00:55:45,719
Speaker 1: something like why is it? Why aren't we starting from

1066
00:55:45,719 --> 00:55:49,080
Speaker 1: a place of like, well, AI can write our movies.

1067
00:55:48,800 --> 00:55:52,480
Speaker 2: Be our artists, be are be our creatives, do our influencing?

1068
00:55:52,600 --> 00:55:55,480
Speaker 1: Like who decided that the kind of creative jobs and

1069
00:55:55,520 --> 00:55:59,160
Speaker 1: creative labor that people aspire to you that is, those

1070
00:55:59,160 --> 00:56:00,640
Speaker 1: are the jobs that we were to have. I mean,

1071
00:56:00,760 --> 00:56:02,839
Speaker 1: I'm sure people who make money, that's who decided it.

1072
00:56:02,840 --> 00:56:06,319
Speaker 1: It's like, oh we can, we can humans who have

1073
00:56:07,280 --> 00:56:09,359
Speaker 1: needs cut them out of the equation and just like

1074
00:56:09,680 --> 00:56:14,320
Speaker 1: pay some tech bro company to make an AI influencer.

1075
00:56:14,400 --> 00:56:15,680
Speaker 2: Cool, here's your money.

1076
00:56:16,480 --> 00:56:19,240
Speaker 4: Right, And it's also like, you know, the tech bros

1077
00:56:19,239 --> 00:56:21,440
Speaker 4: that have been told their entire life that arts and

1078
00:56:21,520 --> 00:56:25,400
Speaker 4: humanities aren't real important things, that it's only technology and

1079
00:56:25,440 --> 00:56:28,160
Speaker 4: now only seeing this kind of stuff as the products

1080
00:56:28,280 --> 00:56:30,480
Speaker 4: rather than the creation.

1081
00:56:30,239 --> 00:56:32,919
Speaker 3: And the products aren't even good like it is, Yeah,

1082
00:56:32,920 --> 00:56:33,680
Speaker 3: it is. It is.

1083
00:56:34,040 --> 00:56:38,840
Speaker 4: We live in a weird, dystopian capitalist hellscape and it

1084
00:56:39,000 --> 00:56:40,520
Speaker 4: just gets weirder every day.

1085
00:56:40,760 --> 00:56:43,560
Speaker 1: Well, this last story kind of fits into that what

1086
00:56:43,600 --> 00:56:46,359
Speaker 1: you're saying, So, oh no, let's talk about this because

1087
00:56:46,360 --> 00:56:49,480
Speaker 1: it's it's like a it is pretty depressing. So Indigenous

1088
00:56:49,560 --> 00:56:53,080
Speaker 1: artists in Australia say that AI is basically ripping off

1089
00:56:53,120 --> 00:56:56,480
Speaker 1: their work without permission or credit and using it to

1090
00:56:56,600 --> 00:57:02,000
Speaker 1: create knockoff fake Indigenous art, toll on online retailers like Etsy,

1091
00:57:02,280 --> 00:57:05,919
Speaker 1: and it's turning into yet another threat to their livelihoods

1092
00:57:05,960 --> 00:57:09,040
Speaker 1: and cultures. So these artists, who are already struggling to

1093
00:57:09,080 --> 00:57:11,840
Speaker 1: compete with the tens of millions of dollars worth of

1094
00:57:11,880 --> 00:57:16,040
Speaker 1: fake art produced every year by non indigenous artists, now

1095
00:57:16,080 --> 00:57:19,040
Speaker 1: have to compete with AI. So major shout out to

1096
00:57:19,360 --> 00:57:23,480
Speaker 1: Cam Wilson at The Australian News site Criche for coverage

1097
00:57:23,480 --> 00:57:25,439
Speaker 1: on this, We'll link to Cam's Peace in the show

1098
00:57:25,440 --> 00:57:26,360
Speaker 1: notes because it's very good.

1099
00:57:26,600 --> 00:57:28,840
Speaker 4: I think it's funny that there's an Australian news site

1100
00:57:28,880 --> 00:57:36,640
Speaker 4: called I Know. This is a very serious story and important.

1101
00:57:37,160 --> 00:57:40,280
Speaker 1: Yeah, don't let the name Criche fool you. This is

1102
00:57:40,280 --> 00:57:43,960
Speaker 1: a very serious story. So Wilson says that AI generated

1103
00:57:43,960 --> 00:57:47,400
Speaker 1: Indigenous art is appearing on online marketplaces where art and

1104
00:57:47,480 --> 00:57:50,720
Speaker 1: derivative products are being sold, and that those AI generated

1105
00:57:50,760 --> 00:57:54,080
Speaker 1: fakes are often directly competing with the work from real

1106
00:57:54,200 --> 00:57:58,640
Speaker 1: Indigenous artists, even though platforms often have policies that are

1107
00:57:58,640 --> 00:58:02,840
Speaker 1: supposed to protect Indigenous culture from exactly this kind of thing.

1108
00:58:03,440 --> 00:58:07,960
Speaker 1: So Adobe and Shutterstock run popular stock images websites where

1109
00:58:07,960 --> 00:58:11,080
Speaker 1: people can buy AI generated images for a variety of

1110
00:58:11,080 --> 00:58:13,480
Speaker 1: commercial purposes, and on both of those platforms there are

1111
00:58:13,560 --> 00:58:17,880
Speaker 1: dozens of fake Indigenous art style images. The images do

1112
00:58:18,160 --> 00:58:20,760
Speaker 1: have a label that they have been created using AI,

1113
00:58:21,000 --> 00:58:24,480
Speaker 1: but they're often like vaguely listed as being Aboriginal or

1114
00:58:24,480 --> 00:58:28,560
Speaker 1: Indigenous art. On Adobe, people can upload AI images for

1115
00:58:28,640 --> 00:58:30,920
Speaker 1: sale and then earn a cut of the money every

1116
00:58:30,920 --> 00:58:34,320
Speaker 1: time those images are purchased. Now the company is meant

1117
00:58:34,320 --> 00:58:37,080
Speaker 1: to only allow users to submit images that they own

1118
00:58:37,440 --> 00:58:40,520
Speaker 1: the intellectual property of. But it's not really clear like

1119
00:58:40,720 --> 00:58:43,960
Speaker 1: how this is being policed. Platforms like Etsy and eBay

1120
00:58:44,000 --> 00:58:47,880
Speaker 1: are filled with cheap digital AI generated prints intended to

1121
00:58:47,920 --> 00:58:50,960
Speaker 1: be printed and framed, and some of these online platforms

1122
00:58:51,000 --> 00:58:52,960
Speaker 1: do have policies in place to prevent this kind of

1123
00:58:52,960 --> 00:58:56,160
Speaker 1: thing from happening, but it's like not clear how or

1124
00:58:56,240 --> 00:58:59,160
Speaker 1: why it's not really being enforced very well, so when

1125
00:58:59,200 --> 00:59:02,240
Speaker 1: we'll see it. Chris spoke to US spokesperson at Adobe.

1126
00:59:02,480 --> 00:59:06,000
Speaker 1: They didn't answer questions about whether AI produced indigenous art

1127
00:59:06,280 --> 00:59:09,240
Speaker 1: violates their policies, but instead gave kind of a.

1128
00:59:09,240 --> 00:59:11,600
Speaker 2: General blah blah blah, we care statement.

1129
00:59:11,680 --> 00:59:15,040
Speaker 1: They said, we are continually auditing, evaluating, and improving the

1130
00:59:15,080 --> 00:59:18,200
Speaker 1: Adobe stock collections to serve our customers needs. That's like,

1131
00:59:18,800 --> 00:59:20,480
Speaker 1: you may as well have said nothing at that point,

1132
00:59:20,520 --> 00:59:24,439
Speaker 1: Like that's a statement that says nothing. EBAs policies say

1133
00:59:24,480 --> 00:59:27,960
Speaker 1: that sellers must not list, sell or promote materials, products,

1134
00:59:28,000 --> 00:59:31,280
Speaker 1: or services that use indigenous culture and intellectual property in

1135
00:59:31,360 --> 00:59:35,120
Speaker 1: unauthorized ways, according to their spokesperson, but when pressed on

1136
00:59:35,120 --> 00:59:38,280
Speaker 1: whether or not AI generated art would violate this policy,

1137
00:59:38,440 --> 00:59:41,120
Speaker 1: they said, how an artwork is created is irrelevant, and

1138
00:59:41,160 --> 00:59:44,280
Speaker 1: that a listing using indigenous art in an unauthorized way

1139
00:59:44,640 --> 00:59:45,880
Speaker 1: may breach that policy.

1140
00:59:46,160 --> 00:59:46,360
Speaker 2: Etc.

1141
00:59:46,480 --> 00:59:49,320
Speaker 1: Has a policy that prohibits users from selling items falsely

1142
00:59:49,320 --> 00:59:52,400
Speaker 1: listed as being produced by Indigenous people, but only in

1143
00:59:52,480 --> 00:59:57,760
Speaker 1: North America and does allow quote indigenous style products by

1144
00:59:57,840 --> 01:00:02,000
Speaker 1: non indigenous people. So yeah, it just sounds like people

1145
01:00:02,240 --> 01:00:06,720
Speaker 1: are stealing from indigenous artists. AI is being trained on

1146
01:00:07,360 --> 01:00:11,520
Speaker 1: artwork and cultural work that has been stolen from Indigenous artists,

1147
01:00:11,560 --> 01:00:14,680
Speaker 1: and then that art that fake artwork is being used

1148
01:00:14,920 --> 01:00:19,040
Speaker 1: to undercut actual Indigenous artists who already have to compete

1149
01:00:19,040 --> 01:00:24,280
Speaker 1: with non AI generated fake indigenous artwork a complete mess.

1150
01:00:24,880 --> 01:00:26,600
Speaker 3: Yeah, it's really just.

1151
01:00:28,160 --> 01:00:34,280
Speaker 4: Technology, you know, the latest technology aiding further colonization and

1152
01:00:34,520 --> 01:00:39,480
Speaker 4: colonial kind of ideas, and I that is really messed up.

1153
01:00:39,520 --> 01:00:41,200
Speaker 3: Also, Like again I.

1154
01:00:41,560 --> 01:00:45,280
Speaker 4: Was surprised to hear that that Etsy prohibits users from

1155
01:00:45,320 --> 01:00:48,280
Speaker 4: selling like items that you know are listen is being

1156
01:00:48,320 --> 01:00:50,919
Speaker 4: produced by it as people to art, because again, yeah,

1157
01:00:50,960 --> 01:00:52,800
Speaker 4: I feel like there's a lot of ways people get

1158
01:00:52,800 --> 01:00:54,920
Speaker 4: around that, Like there's a lot of weird especially like

1159
01:00:54,960 --> 01:00:57,360
Speaker 4: in within like New Age kind of stuff, like a

1160
01:00:57,360 --> 01:01:04,720
Speaker 4: lot of very coded words that you know, people used

1161
01:01:04,720 --> 01:01:08,200
Speaker 4: to kind of ignore the fact that they are just

1162
01:01:08,680 --> 01:01:12,640
Speaker 4: culturally or like appropriating cultures that aren't their own or

1163
01:01:12,760 --> 01:01:15,560
Speaker 4: that aren't you know, being made by the people that

1164
01:01:16,840 --> 01:01:18,920
Speaker 4: it's claiming to come from and all that.

1165
01:01:19,200 --> 01:01:22,120
Speaker 3: But yeah, that is that is depressing.

1166
01:01:22,600 --> 01:01:25,960
Speaker 1: Yeah, it's and it's just like another way, just like

1167
01:01:26,040 --> 01:01:30,000
Speaker 1: you said, another way that AI is being used to

1168
01:01:31,080 --> 01:01:34,439
Speaker 1: further oppress people who are already oppressed and already face

1169
01:01:34,520 --> 01:01:37,680
Speaker 1: so much, right, Like it's just such a grim use

1170
01:01:37,720 --> 01:01:42,840
Speaker 1: of technology to continue to cut people out of their

1171
01:01:42,840 --> 01:01:45,840
Speaker 1: own culture so that other people can profit off of it.

1172
01:01:46,080 --> 01:01:48,000
Speaker 4: Yeah, right, and kind of like what I was saying

1173
01:01:48,000 --> 01:01:49,760
Speaker 4: with that the other story too, where it's like I

1174
01:01:49,760 --> 01:01:51,280
Speaker 4: feel like a lot of this is coming from these

1175
01:01:51,280 --> 01:01:55,480
Speaker 4: companies that don't understand that like art, like the the

1176
01:01:55,600 --> 01:01:58,120
Speaker 4: value of art is like part of it is the

1177
01:01:58,880 --> 01:02:02,120
Speaker 4: actual process this is making the art and the culture

1178
01:02:02,200 --> 01:02:04,520
Speaker 4: that is coming from and the like art is culture,

1179
01:02:04,640 --> 01:02:07,439
Speaker 4: art is a part of who we are. It's it's

1180
01:02:07,480 --> 01:02:11,840
Speaker 4: so like it's such a closed minded kind of it's

1181
01:02:11,840 --> 01:02:14,600
Speaker 4: such an almost honestly, it is a sad kind like

1182
01:02:14,640 --> 01:02:16,880
Speaker 4: I feel sad for these people if your only view

1183
01:02:16,920 --> 01:02:20,160
Speaker 4: of art is like, oh, well, like but computer can

1184
01:02:20,200 --> 01:02:24,160
Speaker 4: do it faster and cheaper, and like that's what people

1185
01:02:24,200 --> 01:02:27,320
Speaker 4: want definitely, Like that's just that's just sad at a

1186
01:02:27,320 --> 01:02:31,560
Speaker 4: certain point, like I truly like you must not have

1187
01:02:31,640 --> 01:02:33,440
Speaker 4: any Like do you feel.

1188
01:02:33,320 --> 01:02:34,000
Speaker 3: Joy at all?

1189
01:02:34,440 --> 01:02:34,680
Speaker 4: Damn?

1190
01:02:34,840 --> 01:02:36,040
Speaker 3: Okay, I don't know.

1191
01:02:36,640 --> 01:02:39,360
Speaker 1: And like I mean, this was the thing that struck

1192
01:02:39,400 --> 01:02:43,360
Speaker 1: me over the conversations around like screenwriters and actors and

1193
01:02:43,400 --> 01:02:47,200
Speaker 1: AI over the Hollywood strikes. It's like, if you value

1194
01:02:47,240 --> 01:02:49,200
Speaker 1: something so little, why do you want to be in

1195
01:02:49,280 --> 01:02:50,480
Speaker 1: charge of it? Why do you want to be a

1196
01:02:50,520 --> 01:02:53,680
Speaker 1: part of it? If you cannot see what makes this

1197
01:02:53,720 --> 01:02:57,400
Speaker 1: stuff great and special and what brings people and makes

1198
01:02:57,440 --> 01:02:59,440
Speaker 1: them feel connected to it, why do you even want

1199
01:02:59,440 --> 01:03:00,760
Speaker 1: to Why do you even want it? Why do you

1200
01:03:00,800 --> 01:03:02,080
Speaker 1: even want to be part of it? It's like you

1201
01:03:02,120 --> 01:03:04,200
Speaker 1: can't see that, then what are you doing? You clearly

1202
01:03:04,200 --> 01:03:07,440
Speaker 1: don't get it. It's like another way that like rich people.

1203
01:03:08,040 --> 01:03:10,280
Speaker 1: We talked about this in a previous episode. I can't

1204
01:03:10,280 --> 01:03:12,400
Speaker 1: remember which one. My brain is mush from being sick.

1205
01:03:12,480 --> 01:03:18,120
Speaker 1: But rich people they bought they use their capital to

1206
01:03:18,280 --> 01:03:21,560
Speaker 1: acquire things and then they hate or don't understand those things.

1207
01:03:21,600 --> 01:03:23,680
Speaker 1: They buy things and then they hate those things. And

1208
01:03:23,680 --> 01:03:26,240
Speaker 1: then ruin them because of that. It's just like such

1209
01:03:26,240 --> 01:03:28,080
Speaker 1: a it was the pitch messed up dynamic.

1210
01:03:28,280 --> 01:03:31,280
Speaker 3: Yeah it yeah, a Pitchfork story right last week? Yeah, yeah,

1211
01:03:31,320 --> 01:03:35,280
Speaker 3: because it absolutely was. Yeah, I like it is.

1212
01:03:35,320 --> 01:03:38,080
Speaker 4: So it's so weird that like the people that are

1213
01:03:38,240 --> 01:03:41,480
Speaker 4: ruining the world and like little livelihoods of all of

1214
01:03:41,480 --> 01:03:43,919
Speaker 4: these people are like the people that also it's like.

1215
01:03:44,320 --> 01:03:48,240
Speaker 3: What are you doing? Like seriously, like where do you how?

1216
01:03:48,440 --> 01:03:51,840
Speaker 3: How is this how why you've chosen to live your life?

1217
01:03:51,880 --> 01:03:54,160
Speaker 3: Like do you not? Yeah?

1218
01:03:54,280 --> 01:03:56,960
Speaker 4: Do you not derive joy from anything? If this is

1219
01:03:56,960 --> 01:03:57,959
Speaker 4: how you're viewing the world?

1220
01:03:58,080 --> 01:04:02,040
Speaker 3: It is. It is really weird. It is. But you know,

1221
01:04:02,480 --> 01:04:05,160
Speaker 3: line go up? Brain, which line go up?

1222
01:04:06,600 --> 01:04:09,440
Speaker 2: Yeah? And this is a real issue.

1223
01:04:09,440 --> 01:04:12,000
Speaker 1: I mean, Indigenous artists have already have a hard time

1224
01:04:13,120 --> 01:04:15,960
Speaker 1: competing with people who create fake art and then try

1225
01:04:16,000 --> 01:04:19,480
Speaker 1: to pond that art office Indigenous, even without AI being

1226
01:04:19,480 --> 01:04:22,720
Speaker 1: part of the conversation. A twenty twenty two Productivity Commission

1227
01:04:22,800 --> 01:04:25,520
Speaker 1: report found that seventy five percent of Indigenous style goods

1228
01:04:25,600 --> 01:04:29,480
Speaker 1: were created by non Indigenous people. Online art businesses were

1229
01:04:29,520 --> 01:04:33,280
Speaker 1: particularly bad. One stock image site analyzed the Commission had

1230
01:04:33,320 --> 01:04:36,200
Speaker 1: eighty percent of its Indigenous style images authored by non

1231
01:04:36,280 --> 01:04:40,360
Speaker 1: indigenous people. Similarly, sixty percent of listings on a print

1232
01:04:40,440 --> 01:04:44,520
Speaker 1: on demand marketplace were also produced by non indigenous creatives.

1233
01:04:44,680 --> 01:04:47,880
Speaker 1: Kriikie spoke to this Indigenous artist Amy Allerton, who said

1234
01:04:48,240 --> 01:04:52,080
Speaker 1: that this is really offensive because oftentimes the art will

1235
01:04:52,120 --> 01:04:55,880
Speaker 1: just be like a random mishmash of designs, and it's

1236
01:04:55,920 --> 01:05:01,240
Speaker 1: like will mix or mess up very like distinctive and

1237
01:05:01,360 --> 01:05:04,640
Speaker 1: special styles from different indigenous nations and artists and just

1238
01:05:04,640 --> 01:05:07,360
Speaker 1: sort of like mush them together. Allerton said, it's a

1239
01:05:07,480 --> 01:05:10,720
Speaker 1: very colonial mindset that they are entitled to the entirety

1240
01:05:10,720 --> 01:05:13,959
Speaker 1: of us. Indigenous people don't have the power for self

1241
01:05:13,960 --> 01:05:16,640
Speaker 1: determination that we want. This adds to the weight of

1242
01:05:16,680 --> 01:05:19,360
Speaker 1: all of that. It's like making me redundant. I think

1243
01:05:19,360 --> 01:05:23,360
Speaker 1: about myself. If I were made redundant, that would be devastating.

1244
01:05:23,440 --> 01:05:24,440
Speaker 2: And yeah, I just.

1245
01:05:24,400 --> 01:05:28,800
Speaker 1: Really think that, like, does everything have to be a

1246
01:05:28,920 --> 01:05:31,960
Speaker 1: soulless cash grab? Does everything have to be about that?

1247
01:05:32,040 --> 01:05:34,480
Speaker 2: Even art? It just that's not the world I want

1248
01:05:34,480 --> 01:05:34,800
Speaker 2: to live.

1249
01:05:34,680 --> 01:05:35,800
Speaker 3: In, absolutely.

1250
01:05:36,560 --> 01:05:38,640
Speaker 1: But the world I do want to live in is

1251
01:05:38,680 --> 01:05:40,040
Speaker 1: one where I get to turn round up the news

1252
01:05:40,040 --> 01:05:42,439
Speaker 1: with you, Joey, So thank you so much for being

1253
01:05:42,480 --> 01:05:46,120
Speaker 1: here where can folks, what do you got going on

1254
01:05:46,120 --> 01:05:48,760
Speaker 1: that folk should know about. Maybe the answer is nothing,

1255
01:05:48,840 --> 01:05:50,600
Speaker 1: but maybe maybe you want to plug something.

1256
01:05:51,320 --> 01:05:52,040
Speaker 3: Thank you, Bridget.

1257
01:05:53,320 --> 01:05:59,320
Speaker 4: It was lovely as always, but as the dystopian chaos continues.

1258
01:06:00,720 --> 01:06:03,520
Speaker 4: If you want to hear more things that I'm working on,

1259
01:06:03,560 --> 01:06:06,520
Speaker 4: you should check out After Lives, the Leleien Planco story,

1260
01:06:08,920 --> 01:06:12,160
Speaker 4: hopefully some new projects a lug way. I should be

1261
01:06:12,320 --> 01:06:15,680
Speaker 4: on stuff Mom've never told you soon talking about more

1262
01:06:16,440 --> 01:06:21,440
Speaker 4: TikTok chaos and this state of TikTok at the moment,

1263
01:06:21,440 --> 01:06:22,479
Speaker 4: which will be a fun time.

1264
01:06:23,280 --> 01:06:24,200
Speaker 3: So TVD on that.

1265
01:06:24,440 --> 01:06:27,880
Speaker 4: But yeah, if you want to follow me as always,

1266
01:06:27,880 --> 01:06:31,400
Speaker 4: you can to follow me on Twitter or Instagram at

1267
01:06:31,520 --> 01:06:32,360
Speaker 4: Pat not Pratt.

1268
01:06:32,400 --> 01:06:34,560
Speaker 3: It's p a t t n O T p r

1269
01:06:34,680 --> 01:06:35,200
Speaker 3: a t T.

1270
01:06:35,880 --> 01:06:38,880
Speaker 1: The first time I had you on the show, Joey,

1271
01:06:38,920 --> 01:06:41,880
Speaker 1: I think I credited you as Joey Pratt and you

1272
01:06:41,920 --> 01:06:44,280
Speaker 1: were like, it's actually Pat not Pratt.

1273
01:06:44,640 --> 01:06:46,280
Speaker 2: Actually why it's my social.

1274
01:06:47,760 --> 01:06:50,160
Speaker 4: It has been my social since I was sixteen, and

1275
01:06:50,200 --> 01:06:52,760
Speaker 4: it was because if I have Pat my entire life.

1276
01:06:52,760 --> 01:06:54,160
Speaker 3: People calling me.

1277
01:06:55,640 --> 01:07:00,600
Speaker 4: My last name Pratt, which is an understandable mistake, but

1278
01:07:00,640 --> 01:07:02,320
Speaker 4: that is not in fact my last name.

1279
01:07:02,520 --> 01:07:06,000
Speaker 1: So pat not Pratch. Thank you for being here, and

1280
01:07:06,320 --> 01:07:07,919
Speaker 1: thanks to all of you for listening. If you want

1281
01:07:07,960 --> 01:07:10,840
Speaker 1: more ad free content, check out our Patreon at patreon

1282
01:07:10,920 --> 01:07:18,040
Speaker 1: dot com. Flash Tegody see you on the Internet. If

1283
01:07:18,080 --> 01:07:20,200
Speaker 1: you're looking for ways to support the show, check out

1284
01:07:20,240 --> 01:07:24,080
Speaker 1: our merch store at tegoty dot com slash store. Got

1285
01:07:24,080 --> 01:07:26,080
Speaker 1: a story about an interesting thing in tech, or just

1286
01:07:26,080 --> 01:07:28,080
Speaker 1: want to say hi, You can reach us at Hello

1287
01:07:28,120 --> 01:07:30,640
Speaker 1: at tegodi dot com. You can also find transcripts for

1288
01:07:30,680 --> 01:07:31,640
Speaker 1: today's episode.

1289
01:07:31,320 --> 01:07:32,640
Speaker 2: At tengody dot com.

1290
01:07:32,760 --> 01:07:34,400
Speaker 1: There Are No Girls on the Internet was created by

1291
01:07:34,440 --> 01:07:37,800
Speaker 1: me Bridget Tood. It's a production of iHeartRadio and Unboss Creative,

1292
01:07:38,280 --> 01:07:41,880
Speaker 1: edited by Joey pat Jonathan Strickland as our executive producer.

1293
01:07:42,240 --> 01:07:45,440
Speaker 1: Tari Harrison is our producer and sound engineer. Michael Almada

1294
01:07:45,520 --> 01:07:48,520
Speaker 1: is our contributing producer. I'm your host, Bridge Tood. If

1295
01:07:48,560 --> 01:07:50,240
Speaker 1: you want to help us grow, rate and review us

1296
01:07:50,280 --> 01:07:53,920
Speaker 1: on Apple Podcasts. For more podcasts from iHeartRadio, check out

1297
01:07:53,920 --> 01:07:57,200
Speaker 1: the iHeartRadio app, Apple Podcasts, or wherever you get your podcasts.

1298
01:08:00,200 --> 01:08:00,240
Speaker 6: He