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

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

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

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Speaker 1: There No Girls on the Internet. Where weeks were the

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Speaker 1: intersection of technology, social media and identity. And this is

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Speaker 1: another installment of our weekly news roundup where we dig

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Speaker 1: into all the stories that you might have missed on

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Speaker 1: the Internet so you.

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Speaker 2: Don't have to it has been too long.

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Speaker 1: I am so excited to welcome back today's guest co

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Speaker 1: host producer Joey Joey, thank you for being here.

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Speaker 2: Hey, Bridget, thanks for having me on again. I have

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Speaker 2: to ask what is capturing your attention on the internet

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Speaker 2: right now? Anything? What do you got?

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Speaker 3: That's a great question, Bridget. Actually I've really even wanting

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Speaker 3: to talk about because this combines two of our favorite things.

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Speaker 3: Well see, I don't know what your personal relationship to

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Speaker 3: the Broadway musical book Slash now two part movie Wicked is,

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Speaker 3: but I have done and I can see your face.

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Speaker 3: I have been obsessed. There's been so much that has

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Speaker 3: happened with that movie and their marketing campaign. I'm supposed

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Speaker 3: see it tomorrow, so excited for that, but I've been

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Speaker 3: really obsessed with the amount of brand deals that they've

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Speaker 3: done recently.

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Speaker 2: On TikTok.

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Speaker 3: I got an ad for Crest, like the toothpaste company

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Speaker 3: that was Wicked themed. Of course you did, of course,

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Speaker 3: that is right, and so I was curious. So I

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Speaker 3: did look this up according to and it took me

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Speaker 3: a lot of different articles to go through to finally

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Speaker 3: find an actual number, because there's so many articles right now.

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Speaker 2: That are like top ten, top fifty Wicked items to buy.

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Speaker 3: According to the International Business Times UK, there's four hundred

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Speaker 3: and fifty brand deals for this one movie.

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Speaker 2: This is record breaking. That was gonna say that has

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Speaker 2: to be more than ever.

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Speaker 3: Right, they're breaking the record from the first movie, which

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Speaker 3: was about four hundred.

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Speaker 2: And it looks like before.

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Speaker 3: That, like the like Spider Man movies, the we're the

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Speaker 3: most amount of money, which makes sense. But yeah, no,

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Speaker 3: I just I was curious because like I literally it's again.

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Speaker 3: I was like looking through these articles and there were

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Speaker 3: like dishwasher soap and like there was a swiffer collapse.

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Speaker 2: There were laundry pots.

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Speaker 3: There was a mac and cheese one that would either

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Speaker 3: turn pink or green.

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Speaker 1: I just like, oh, their products are so like weird

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Speaker 1: and random.

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Speaker 3: Also they're so weird and then but like, here's the thing,

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Speaker 3: I'm not gonna lie again. I personally grew up with

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Speaker 3: this musical. Like I'm a big wicked fan. Me, me

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Speaker 3: and my sister want to see Tomorrow. I have been

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Speaker 3: following for some of these. There are a couple that

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Speaker 3: I'm like. I did buy the the like Pillsbury cookies

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Speaker 3: that they had. I actually was going to get the

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Speaker 3: like Halloween cookies they usually have, and they had sold out.

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Speaker 2: This was four Halloween.

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Speaker 3: They were out of them, but they had Wicked ones,

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Speaker 3: so I got those instead.

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Speaker 2: They were fine.

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Speaker 3: They tasted like the cookies usually do. But the one

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Speaker 3: that I keep seeing that I haven't gotten any ads for,

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Speaker 3: but I just keep seeing on TikTok is.

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Speaker 2: The Chilies one.

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Speaker 3: And this happened before I left to California, so I

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Speaker 3: was still in New York.

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Speaker 2: I don't know if you know this bridge it there

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Speaker 2: is one.

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Speaker 3: Chilies in all of New York, which first of all,

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Speaker 3: I didn't know.

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Speaker 2: Wait where is it. It's not Queens, it's idea.

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Speaker 3: It's like, so I beat a couple of my friends

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Speaker 3: went and we got it, like it was a Saturday,

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Speaker 3: but it was like we were like, we're gonna go early.

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Speaker 3: We're gonna go like five pm. Uh, we get there

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Speaker 3: this one chilies. Do you want to guess how long

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Speaker 3: the wait was?

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Speaker 2: Oh my god, hell, I can't even.

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Speaker 3: It was an hour and a half to get it.

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Speaker 3: Chiliens just chilies, Like I. There was like a family

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Speaker 3: in front of us in line that was also like

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Speaker 3: what the hell? And I was like, yeah, over like

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Speaker 3: here to get the Wicked drinks. They were like, we

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Speaker 3: aren't too, So I was like, I literally this advertising

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Speaker 3: is working. And again I haven't actually seen any Chilis

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Speaker 3: advertisements for Wicked specifically. I just keep seeing people making

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Speaker 3: tiktoks about going to Chili's and like with their drinks

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Speaker 3: and like making little jokes about.

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Speaker 2: The Margarita's and whatever. I just wanted one of them.

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Speaker 3: I didn't even I don't even like Margarita's, like I

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Speaker 3: wanted just I was like, I will go. I just

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Speaker 3: want the wand there's this little Glinda wand you can

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Speaker 3: get but yeah, I was like I'm I'm sorry, I'm

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Speaker 3: not waiting an hour and a half for chili. So

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Speaker 3: I have yet to get my Wicked Drinks. Heartbroken, I can't.

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Speaker 1: I'm so curious how this came to be, How this

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Speaker 1: Wicked Chilies, what came to be.

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Speaker 3: That at least kind of makes There's so many aspects

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Speaker 3: of this, like I'm I'm still like, how did the

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Speaker 3: crest one happen?

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Speaker 2: How did the swiper one happened?

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Speaker 4: Like?

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Speaker 2: What happened? First?

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Speaker 3: These companies approached the Wicked marketing team or did the

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Speaker 3: marketing team approach them?

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Speaker 1: Like what happened? I have a question for you about this.

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Speaker 1: So you you self identify as a theater kid.

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Speaker 2: I do.

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Speaker 4: I do.

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Speaker 3: I'm a former theater kid. I haven't actually done theater

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Speaker 3: in a long time. I mean, once you're in your in,

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Speaker 3: you're in for life. Anybody wants to cast me and anything,

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Speaker 3: you know.

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Speaker 1: Yeah, for your consideration, Joey, exactly, you are in La.

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Speaker 1: The one will discover you on the street. Okay, So

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Speaker 1: I let me just make it very clear all the caveats.

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Speaker 1: I love Ariana Grande much respect. I love Cynthia Arriva

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Speaker 1: was my girl. Nobody has pipes like her. Nothing but

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Speaker 1: respect a queen. I love Wicked. I saw it on Broadway.

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Speaker 1: I saw the first movie. Love it no problems here.

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Speaker 1: I know it's I know it's a deep fan base,

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Speaker 1: so I.

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Speaker 2: Also really like it.

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Speaker 1: I do feel like when I watched the interviews between

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Speaker 1: Ariana and Cynthia, I feel like I'm missing something and

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Speaker 1: I don't understand what it is. And someone was like,

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Speaker 1: you just don't understand theater energy, and I feel like

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Speaker 1: I get theater energy.

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Speaker 2: But what am I am? I way off base here?

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Speaker 2: Do you know what I'm talking about?

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Speaker 4: Like?

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Speaker 3: The thing is you just have to go into it

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Speaker 3: knowing that they're both kind of insane, and I'm I'm no,

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Speaker 3: I agree with you though, it is like something weird

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Speaker 3: has been happening this entire press to or this was

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Speaker 3: happening here like last year, because it is so we're

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Speaker 3: having the same rounded discourse that.

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Speaker 2: We had a year ago.

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Speaker 3: So I'm like, I'm ready again, this is not what

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Speaker 3: you guys. Can't see what I'm doing. The thing where

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Speaker 3: Cynthia was holding Ariana's finger or the other way around,

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Speaker 3: I can't remember who was holding Who's fittinger fixing thee

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Speaker 3: We'll say the like I am in queer media. That

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Speaker 3: interview moment that was If anybody follows me on Instagram

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Speaker 3: my bio has been I am in queer media for

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Speaker 3: the past two year.

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Speaker 2: From that interview, I don't know. I really don't know.

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Speaker 3: I wish I could get a glimpse into both of

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Speaker 3: their psychics. I'm the same or I love Ariana Grande.

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Speaker 3: I like listen to her music for years now. I'm

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Speaker 3: not like a huge like she's one of my top artists,

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Speaker 3: but like I'll always listen to her.

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Speaker 2: She's fine.

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Speaker 3: I really liked her new album that she put out

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Speaker 3: that was really good. And same with Cynthy Revio. Amazing voice,

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Speaker 3: you know, I do. And I just was rewatching the

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Speaker 3: first movie before I left and watching it. It was

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Speaker 3: sort of like me and my friend were watching it.

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Speaker 3: We both kind of were talking about this too. And

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Speaker 3: my point was kind of like, you know what, here's

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Speaker 3: the thing. It is like the old Hollywood diva thing

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Speaker 3: where I'm like, but they're so talented, like they have

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Speaker 3: such amazing voices that I'm kind of like, yeah, sure

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Speaker 3: they can do whatever they want.

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Speaker 2: Yeah, And I don't.

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Speaker 3: Know Cynthia Reva, I just the amount of like gifts

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Speaker 3: that we've gotten from.

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Speaker 2: Saye.

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Speaker 3: So yeah, again, like I think they both are just

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Speaker 3: like they're like Broadway type divas, and we haven't gotten

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Speaker 3: a lot of those like this famous in a while,

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Speaker 3: so maybe that's maybe that's what they meant by like

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Speaker 3: the theater kid thing.

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Speaker 2: I don't know see it.

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Speaker 3: I don't know, but it's fascinating to watch unravel in

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Speaker 3: front of everybody.

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Speaker 1: I completely agree. I also think part of it is that.

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Speaker 1: So when I saw Wicked in the theater, I did

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Speaker 1: not know it was going to be a two part

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Speaker 1: movie until oh, really.

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Speaker 2: Yeah, I was like, oh, that's a sequel. Okay.

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Speaker 1: Also, when I was in the theater, I was like,

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Speaker 1: I swear I respect the craft of and musical theater.

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Speaker 2: I was in a.

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Speaker 1: Showing where everybody around me was singing, and I was

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Speaker 1: the one person who was like, wouldn't it be cool

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Speaker 1: if we could hear them sing?

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Speaker 3: Though No, was it one where it was like specifically,

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Speaker 3: like you're supposed to sing in this one?

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Speaker 2: Or was it just a normal showing?

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Speaker 1: So I think it was just a normal showing. It

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Speaker 1: was just a very okay And that was the one

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Speaker 1: that grow who was like, I.

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Speaker 2: Agree with you. I agree with you.

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Speaker 3: I think that's a cool I think look listen, there

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Speaker 3: were plenty of screenings that were like sing along, like

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Speaker 3: come here and yeah, like again.

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Speaker 2: I I went to one of.

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Speaker 3: This is a whole other story, but when the movie

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Speaker 3: Cats came out, I went to one of the ones

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Speaker 3: where you were supposed to like yell at the screen.

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Speaker 2: That was an experience. I don't know if I would.

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Speaker 3: Repeat that, but you know, there are specific showings that

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Speaker 3: are meant for you to sing along, So why not just.

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Speaker 2: Do it anywhere?

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Speaker 3: I don't know, I agree with you. I hate it

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Speaker 3: when people talk over movies.

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Speaker 2: Don't do that.

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Speaker 1: I once almost came to blows it a screening of

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Speaker 1: the Menu because a woman was watching full volume tiktoks.

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Speaker 2: Right next to me, and I was like, we're gonna

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Speaker 2: have to physically fight in this theater. Oh my god, weird.

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Speaker 3: You know we're bridget Speaking of music, I've been seeing

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Speaker 3: on TikTok a lot lately that I think really embodies

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Speaker 3: this moment.

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Speaker 2: Have you, just because this has been stuck in my

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Speaker 2: head all week?

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Speaker 3: Have you seen the like we Are Charlie Kirk song

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Speaker 3: that's going around TikTok?

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Speaker 4: I have not.

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Speaker 1: You haven't, Okay, because I don't learn. I haven't been

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Speaker 1: on TikTok it's so.

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Speaker 3: Here's the thing. I heard this song because a why

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Speaker 3: people were like, oh my god, this is in sane.

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Speaker 3: I was like, this has to be AI. This sounds

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Speaker 3: like it's AI. I did just look it up. According

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Speaker 3: to Forbes, Yes, it is Ai Bridget. I'm gonna send

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Speaker 3: you this song because, oh my gosh, this has been

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Speaker 3: stuck in my.

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Speaker 2: Head all week. We are Charlick, that's black.

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Speaker 4: Charlie Cakar.

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Speaker 3: Chiro, we are Cholly Kirk.

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Speaker 2: Oh my god, I'm giving that sound fine enough, So.

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Speaker 3: Oh my gosh, Yeah, that's all you need to listen to.

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Speaker 2: That's the yeah.

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Speaker 3: We are Charlie Kirk chorus has been I have heard

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Speaker 3: it way too many times over the past week. I

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Speaker 3: didn't need to hear it once. And yeah, now it's

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Speaker 3: been stuck in my head again. Apparently it is AI generated.

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Speaker 3: I'm not surprised. It does kind of sound like it's

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Speaker 3: a I've heard it compared to like Alex Warren, who

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Speaker 3: I've been told as a musician, I actually have not

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Speaker 3: heard any of his songs. I just know he's like

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Speaker 3: a Mormon music guy, or like imagine dragons or I

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Speaker 3: want to do an investigative series at one point about

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Speaker 3: like the Mormon influence on the music industry.

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Speaker 1: Oh yeah, Mormons are very hot right now. Yes, it's

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Speaker 1: it is a thing, you know what I'm talking.

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Speaker 3: Yeah, but even like looking back, Mormons are really hot

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Speaker 3: right now.

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Speaker 2: I don't know what's going on with that.

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Speaker 3: But even like, look, I was like, like I keeping

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Speaker 3: like Ben's and Boon kind of reminds me of Panic

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Speaker 3: at the disco, and I'm like, oh, yeah, because they

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Speaker 3: were ex Mormons, and like, imagine dragons also ex Mormons.

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Speaker 3: There's too many, like all rock bands that are ex Mormons.

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Speaker 2: I didn't know imagine dragons or ex Mormons. Magic dragons

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Speaker 2: are ex Mormons.

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Speaker 3: Yeah, apparently they left the Mormon Church because of their

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Speaker 3: stance on like gay people. So you know, I guess

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Speaker 3: go imagine dragons, allies ally magic dragons. Who fucking would

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Speaker 3: have thought, you know what when I was like twelve

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Speaker 3: radioactive slabs. So I don't know, it's still kind.

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Speaker 2: Of those actually they they.

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Speaker 1: I know they're so cringey, but I have the us up.

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Speaker 1: I will be lying if I said I have a

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Speaker 1: little bit of spot for them, right.

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Speaker 3: No, it's just like they're they're like a nostalgic band.

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Speaker 3: I think I just yes, like whatever I do hear

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Speaker 3: their music, I'm like, oh, like this is kind of

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Speaker 3: fun though.

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Speaker 4: Yeah.

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Speaker 1: At the Democratic National Convention in like twenty whatever, the

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Speaker 1: Tony like like the Clinton one. I straight up cried

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Speaker 1: while on drugs during a performance of the Black Eyed

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Speaker 1: pieces where.

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Speaker 4: Is the Love?

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Speaker 3: And I was like, Bridget, I am really on drugs.

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Speaker 1: So I I was just like, they're so right, where

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Speaker 1: is the Love?

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Speaker 2: Well, speaking of music.

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Speaker 1: We should talk about what is going on with the

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Speaker 1: rapper Meg thee Stallion because she has been straight fighting

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Speaker 1: racialized and gendered misindisinformation online. She's been doing it for

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Speaker 1: kind of a while. During the criminal trial against rapper

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Speaker 1: Tory Lanes. This is what a lot of this stuff started.

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Speaker 1: This week, Meg thee Stylon was in court trying to

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Speaker 1: fight AI generated deep fakes of herself. So a little

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Speaker 1: bit of backstory for folks who don't remember. Canadian rapper

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Speaker 1: Tory Lanes got sentenced to ten years in prison after

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Speaker 1: he was found guilty of shooting rapper Meg the Stallion

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Speaker 1: in the foot back in July of twenty twenty while

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Speaker 1: they were all in a car leaving a party at

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Speaker 1: Kylie Jenner's house. So this trial, like, I followed it

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Speaker 1: pretty closely because it was one of those trials where

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Speaker 1: it just.

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Speaker 2: Really was like a.

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Speaker 1: Wave of gendered and racialized misin disinformation, like basically lies

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Speaker 1: to smear Meg. Honestly, it quite reminded me of the

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Speaker 1: Amber Heard Johnny Depp defamation trial. The thing that stood

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Speaker 1: out to me is how much like content creators online

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Speaker 1: and on social media blogs, YouTubers, podcasters, they played such

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Speaker 1: a role in spreading just flat out incorrect information about

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Speaker 1: this case in a way that really discredited Megan as

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Speaker 1: this like victim of violence, and it created this climate

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Speaker 1: where lies generated so much engagement that like, ultimately it

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Speaker 1: kind of didn't matter what the truth in quotes was

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Speaker 1: because there was so much smoke and noise and distortion,

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Speaker 1: which ultimately harms us all in the process. And so

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Speaker 1: that trial, if folks remember it, I feel like it

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Speaker 1: really calcified just flooding the zone as a tactic for

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Speaker 1: abusers to avoid accountability. That Honestly, again, I really feel

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Speaker 1: like Johnny Depp just perfected this and now we're all

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Speaker 1: stuck with it. But all of these online contact creators

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Speaker 1: were able to create a lot of smoke and distortion

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Speaker 1: and distrust and lies and confusion.

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Speaker 3: You know.

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Speaker 1: It was this cottage industry of like bloggers and like

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Speaker 1: so called body language experts and media personalities and TikTokers

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Speaker 1: who you know, we just live in this climate where

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Speaker 1: not everybody is going to recognize, oh, this random YouTuber

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Speaker 1: is not the same thing as NBC News or something.

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Speaker 4: Right.

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Speaker 3: The body and language experts were my I don't want

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Speaker 3: to say were my favorite, because it was just one

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Speaker 3: of those things every I think I was a little

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Speaker 3: bit more present for the johnnyt member her trial, but

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Speaker 3: for that one specifically, I mean, like, and I know

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Speaker 3: that the Megama sality one was kind of similar.

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Speaker 2: Some of the stuff people were saying online was insane.

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Speaker 3: Also, all of a sudden, it was like everybody had

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Speaker 3: a psychology degree, all of us.

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Speaker 2: Everybody had a criminal psychology.

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Speaker 3: Degree also, and this is me also kind of having

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Speaker 3: my armchair e whatever. I took one forensics class in

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Speaker 3: high school because it was like the easiest science class

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Speaker 3: I could take. But I literally remember and that they

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Speaker 3: told us how they were like, yeah, a lot of

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Speaker 3: this like body language, eye contact reading, whatever, stuff is

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Speaker 3: fake because it's there's so many other factors that can

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Speaker 3: comment anyway.

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Speaker 2: I don't know. It just was like one of those

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Speaker 2: segad words.

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Speaker 3: It's not only just people not really knowing what they're

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Speaker 3: talking about and claiming to because they're on TikTok and

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Speaker 3: they're a loud about it, but also like the thing

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Speaker 3: they're claiming to know a lot about, is it really

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Speaker 3: like a science or an exact science with It's kind

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Speaker 3: of just like a an idea that sometimes works exactly.

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Speaker 1: But when people are just fending for any information that

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Speaker 1: scratches the itch of telling you this person who you

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Speaker 1: don't like is in the wrong, they'll watch it. And

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Speaker 1: so even like anybody can claim to be a body

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Speaker 1: language expert and get out on YouTube and say because

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Speaker 1: so and so held their face like this, it means xyz.

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Speaker 1: That kind of content when you make it about somebody

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Speaker 1: who is the target of this kind of like misin

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Speaker 1: disinformation campaign is.

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Speaker 2: Always going to do numbers, right. It does like it

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Speaker 2: sort of like doesn't.

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Speaker 1: Matter that it's a complete bunk science. It's like that's

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00:17:31,320 --> 00:17:34,120
Speaker 1: like made up that anybody can say anything. It's essentially

364
00:17:34,560 --> 00:17:39,080
Speaker 1: like fan fiction that people project onto people, and there's

365
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Speaker 1: always going to be an audience for it.

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Speaker 2: It's it's it really is.

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Speaker 1: I mean, like anybody can claim we can start a

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Speaker 1: body language YouTube channel tomorrow and it will probably do

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Speaker 1: numbers because people love it.

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Speaker 3: It's funny that you said fan fiction specifically, because this

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00:17:51,000 --> 00:17:55,040
Speaker 3: is making me realize that feels very similar to right

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Speaker 3: now with the other epic internet news story or guess

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Speaker 3: not on internet just politics news story of the week

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Speaker 3: is uh, the alleged Bill Clinton Donald Trump affair and

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Speaker 3: seeing some of the clips from that that people now

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00:18:09,840 --> 00:18:13,120
Speaker 3: are posting and being like see like comparing clips from

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Speaker 3: the twenty sixteen presidential debates to like challengers, like it

378
00:18:16,840 --> 00:18:19,840
Speaker 3: feels like it's that level of like investigation where it's like,

379
00:18:20,560 --> 00:18:23,200
Speaker 3: this is a funny joke people are making in this situation,

380
00:18:23,400 --> 00:18:26,520
Speaker 3: but unfortunately this is a thing that people do use

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Speaker 3: and realize, Like I've seen when the like I've people

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00:18:29,400 --> 00:18:32,040
Speaker 3: see people do that with the Joe Biden and Trump,

383
00:18:32,240 --> 00:18:34,800
Speaker 3: Like when you see them talking off camera, people like

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00:18:34,840 --> 00:18:37,360
Speaker 3: try to be like lip reading, here's what they're saying.

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00:18:37,400 --> 00:18:39,040
Speaker 3: It's like a it's a joke, Like it's all stuff

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00:18:39,040 --> 00:18:43,160
Speaker 3: that's fake. Anyways, Yes, bridget back to Megan thee Stallion.

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Speaker 1: Yeah, but it's so true that you bet that people

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00:18:46,880 --> 00:18:51,680
Speaker 1: will people will and do project anything onto public figures,

389
00:18:51,720 --> 00:18:54,040
Speaker 1: and there's always going to be an audience for that.

390
00:18:54,560 --> 00:18:59,280
Speaker 1: And like during the whole Meg the Stallion Tory Lane's trial,

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00:19:00,080 --> 00:19:05,040
Speaker 1: the real meat of it was that people online made

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Speaker 1: it sound like it was Meg against Tory, but in

393
00:19:07,920 --> 00:19:10,480
Speaker 1: reality it was Tory against the state of California.

394
00:19:10,520 --> 00:19:12,040
Speaker 2: These were like state charges, and.

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Speaker 1: So they were able to do this in a way

396
00:19:14,720 --> 00:19:18,760
Speaker 1: that put Meg her reputation and her history and her

397
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Speaker 1: credibility on trial, even though she was the one who

398
00:19:21,560 --> 00:19:24,440
Speaker 1: had been shot, right, And so it created this legacy

399
00:19:24,760 --> 00:19:29,480
Speaker 1: of all of these outright falsehoods about Meg fueled by massage,

400
00:19:29,600 --> 00:19:35,200
Speaker 1: noir and just sexism and racism, including Milagro Grahams, who

401
00:19:35,240 --> 00:19:37,920
Speaker 1: is a hip hop news personality who was on YouTube

402
00:19:38,000 --> 00:19:41,240
Speaker 1: who pushed this theory that Meg was never actually shot,

403
00:19:41,320 --> 00:19:44,120
Speaker 1: that she just stepped on glass, even though a surgeon

404
00:19:44,240 --> 00:19:47,359
Speaker 1: testified that they had found bullet fragments in her foot,

405
00:19:47,400 --> 00:19:49,520
Speaker 1: so she was definitely shot, no question about it. So

406
00:19:49,920 --> 00:19:52,760
Speaker 1: Grahams even testified that she had been on a call

407
00:19:52,840 --> 00:19:56,399
Speaker 1: with Tory Lanz and his father who wanted her to

408
00:19:56,480 --> 00:19:59,520
Speaker 1: essentially continue to use her YouTube channel and social media

409
00:19:59,560 --> 00:20:03,919
Speaker 1: presence to essentially make up stories about Meg the Stallion

410
00:20:03,960 --> 00:20:07,960
Speaker 1: on social media. When NBC News talk to Grahams, she said, quote,

411
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Speaker 1: on my end, everything is not going to be something

412
00:20:11,160 --> 00:20:13,880
Speaker 1: that was intended to be a factual statement. It might

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Speaker 1: have a comedic effect. So when this happened, Meg vowed

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00:20:18,320 --> 00:20:21,640
Speaker 1: to sue bloggers who continued to spread false information about

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Speaker 1: her during and after this trial. And now Meg is

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Speaker 1: taking this YouTuber molagro Grams to court.

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Speaker 3: Good for her as she should.

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Speaker 1: During the trial this week, when Meg took the stand

419
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Speaker 1: per NBC, she was accusing Grahams, this YouTuber of encouraging

420
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Speaker 1: her thousands of followers on x and Instagram to view

421
00:20:42,280 --> 00:20:45,879
Speaker 1: an unauthorized sexual explicit, deep fake video of Meg the

422
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Speaker 1: Stallion that had been circulating on social media. The cessimony

423
00:20:49,920 --> 00:20:53,920
Speaker 1: was like pretty emotional. Meg shared that quote, I feel

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00:20:53,960 --> 00:20:55,679
Speaker 1: like to this day, I feel a little.

425
00:20:55,440 --> 00:20:57,200
Speaker 2: Defeated, often sobbing.

426
00:20:57,280 --> 00:21:01,800
Speaker 1: When describing the image the Aigen image of depicting her likeness,

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00:21:02,040 --> 00:21:05,239
Speaker 1: she says, quote because no matter what, no matter if

428
00:21:05,240 --> 00:21:08,119
Speaker 1: the video was fake or not, Grahams wanted it to

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Speaker 1: be real. And so you know, this person has basically

430
00:21:12,680 --> 00:21:16,840
Speaker 1: been making content about Megna Stallion all through this trial,

431
00:21:17,320 --> 00:21:21,720
Speaker 1: and already the courts ordered this person to pay meg

432
00:21:21,720 --> 00:21:25,360
Speaker 1: the Stallion's legal fees. Interestingly enough, the lawsuit does not

433
00:21:25,440 --> 00:21:29,600
Speaker 1: accuse Grahams of creating or posting the video, but suggests

434
00:21:29,640 --> 00:21:33,280
Speaker 1: that she quote willfully and maliciously promoted it to her followers,

435
00:21:33,600 --> 00:21:35,840
Speaker 1: pointing them to a post that had directly shared it.

436
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Speaker 1: And so, I do this is something that I find

437
00:21:38,720 --> 00:21:41,919
Speaker 1: I'm interested in whether or not a YouTuber can be

438
00:21:41,960 --> 00:21:44,840
Speaker 1: held accountable for spreading a fake video like this that

439
00:21:44,880 --> 00:21:48,399
Speaker 1: they themselves did not create. But I think it's, you know,

440
00:21:48,560 --> 00:21:51,920
Speaker 1: bigger than this one content creator. I think like meg

441
00:21:52,119 --> 00:21:55,280
Speaker 1: is right for trying to refuse to let this digital

442
00:21:55,280 --> 00:21:58,920
Speaker 1: machine that we know is built on the massage noir

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00:21:59,520 --> 00:22:03,920
Speaker 1: sex as degrading women, particularly women of color, letting this

444
00:22:04,040 --> 00:22:07,159
Speaker 1: machine be the thing that decides the truth. And I

445
00:22:07,160 --> 00:22:10,760
Speaker 1: think that she is really trying to show what happens

446
00:22:11,000 --> 00:22:15,480
Speaker 1: and how easily conspiracy, profit, online engagement, all of that

447
00:22:15,840 --> 00:22:20,040
Speaker 1: can spread quickly online and drown out the facts when

448
00:22:20,080 --> 00:22:24,080
Speaker 1: a black woman has been harmed. And so I'm curious

449
00:22:24,080 --> 00:22:27,239
Speaker 1: to see how this will will shake out. But I

450
00:22:27,280 --> 00:22:30,439
Speaker 1: think that we have to as a society kind of

451
00:22:30,480 --> 00:22:32,680
Speaker 1: decide whether or not we're going to accept a world

452
00:22:32,680 --> 00:22:36,600
Speaker 1: where using AI to violate a black woman who was

453
00:22:36,640 --> 00:22:42,080
Speaker 1: already like publicly the victim of a shooting, like horrible abuse,

454
00:22:42,359 --> 00:22:45,800
Speaker 1: whether or not that's just okay fodder for content, right, Like,

455
00:22:45,920 --> 00:22:48,400
Speaker 1: I think that's really kind of what's at stake here.

456
00:22:48,560 --> 00:22:49,879
Speaker 2: Yeah, absolutely agreed.

457
00:22:49,960 --> 00:22:53,560
Speaker 3: I mean, Mega Nostalia is one of those celebrities that

458
00:22:53,920 --> 00:22:57,040
Speaker 3: because she is so prominent in the public eye, a

459
00:22:57,080 --> 00:23:00,680
Speaker 3: lot of artist mession around women and black women in particular,

460
00:23:01,000 --> 00:23:03,240
Speaker 3: like she's gonna kind of end up becoming the face

461
00:23:03,240 --> 00:23:05,360
Speaker 3: of that, whether she wants to or not. I mean,

462
00:23:05,560 --> 00:23:07,600
Speaker 3: I don't think she wants to, because I can't see

463
00:23:07,600 --> 00:23:10,919
Speaker 3: why anybody would want to. Again, so much love for

464
00:23:10,960 --> 00:23:14,119
Speaker 3: her for like going through all of this and not

465
00:23:14,480 --> 00:23:17,240
Speaker 3: shutting up and not taking a step back and actually

466
00:23:17,240 --> 00:23:19,880
Speaker 3: fighting like for justice here.

467
00:23:21,720 --> 00:23:23,120
Speaker 2: Nobody should have to go through that.

468
00:23:23,280 --> 00:23:24,640
Speaker 3: I feel like every time I come on the show,

469
00:23:24,640 --> 00:23:28,320
Speaker 3: there's a story about like AI nude deep fakes or

470
00:23:28,520 --> 00:23:31,320
Speaker 3: porne fakes or something, and it is like it's something

471
00:23:31,480 --> 00:23:33,359
Speaker 3: I mean, I have to think about. It's something that

472
00:23:33,400 --> 00:23:37,080
Speaker 3: I think most like nonsens men have to think about.

473
00:23:37,680 --> 00:23:40,800
Speaker 3: I grew up with the rhetoric, you know, growing up

474
00:23:40,800 --> 00:23:43,440
Speaker 3: of like never take nude photos, never send nude photos.

475
00:23:43,480 --> 00:23:45,480
Speaker 3: It's gonna be really bad, They're gonna get leaked, they're

476
00:23:45,520 --> 00:23:49,000
Speaker 3: gonna be whatever. At this point, you don't need to

477
00:23:49,040 --> 00:23:50,479
Speaker 3: be the one doing it, Like it is sort of

478
00:23:50,520 --> 00:23:52,479
Speaker 3: like I think that's bull should to begin with, Like

479
00:23:52,640 --> 00:23:56,439
Speaker 3: it's complicated, intimacy is complicated, but also like we live

480
00:23:56,480 --> 00:23:58,720
Speaker 3: in an earrow where it's like, yeah, it doesn't matter

481
00:23:58,760 --> 00:24:03,399
Speaker 3: what you do because somebody could easily leak fake like

482
00:24:03,440 --> 00:24:05,119
Speaker 3: a fake sex tape or fake nudes of you.

483
00:24:05,320 --> 00:24:08,720
Speaker 2: So at this point, like it's it's who cares anymore?

484
00:24:10,000 --> 00:24:12,320
Speaker 3: But also yeah, I mean I think, like, good for

485
00:24:12,359 --> 00:24:16,119
Speaker 3: her for for bringing the support, for making this, for

486
00:24:16,280 --> 00:24:18,480
Speaker 3: not just sort of letting it side.

487
00:24:18,560 --> 00:24:18,960
Speaker 2: I think.

488
00:24:19,560 --> 00:24:22,920
Speaker 3: I mean, we've talked before about like I still stand

489
00:24:22,920 --> 00:24:25,399
Speaker 3: by and my maybe I'm a little bit psychic. I

490
00:24:25,480 --> 00:24:27,760
Speaker 3: did predict that Taylor Swift because was going to be

491
00:24:27,800 --> 00:24:31,240
Speaker 3: somehow related to this whole AI news thing, and at

492
00:24:31,240 --> 00:24:31,720
Speaker 3: the top.

493
00:24:31,560 --> 00:24:33,399
Speaker 2: Of twenty twenty four she did.

494
00:24:34,400 --> 00:24:36,920
Speaker 3: She was picked up. A lot of bridget was there

495
00:24:36,920 --> 00:24:38,520
Speaker 3: in the episode when I was sure, I was like

496
00:24:39,400 --> 00:24:42,560
Speaker 3: dates on this notes app but say I wrote this

497
00:24:42,640 --> 00:24:45,679
Speaker 3: is my twenty twenty four prediction before it happened, and

498
00:24:45,720 --> 00:24:48,320
Speaker 3: then yeah, Like I think Taylor Slift is another example

499
00:24:48,359 --> 00:24:51,719
Speaker 3: of like somebody who, regardless of how you feel about her, uh,

500
00:24:51,800 --> 00:24:53,600
Speaker 3: the way we talk about her is very reflective of

501
00:24:53,600 --> 00:24:56,080
Speaker 3: like how we think about women, which has been discussed

502
00:24:56,080 --> 00:24:59,840
Speaker 3: on the show before. I think it is really some

503
00:25:00,160 --> 00:25:02,560
Speaker 3: like it is really admirable to me and really worth

504
00:25:02,600 --> 00:25:07,320
Speaker 3: noting that, like all of these famous women have actually

505
00:25:07,400 --> 00:25:09,400
Speaker 3: been kind of like taking these issues to court because

506
00:25:09,400 --> 00:25:10,960
Speaker 3: a it is like if it happens to then it

507
00:25:10,960 --> 00:25:12,800
Speaker 3: can If it happens to them, it can happen to

508
00:25:12,840 --> 00:25:16,119
Speaker 3: any of us, Like Megan thee Stallion has way and

509
00:25:16,119 --> 00:25:19,119
Speaker 3: more money and resources than I ever will have. But

510
00:25:19,240 --> 00:25:21,199
Speaker 3: also it's like if somebody's gonna have to do, if

511
00:25:21,200 --> 00:25:23,200
Speaker 3: somebody's gonna have to be the one to like stand

512
00:25:23,280 --> 00:25:26,000
Speaker 3: up and argue this in court, Like yeah, good for her,

513
00:25:26,080 --> 00:25:27,800
Speaker 3: Good for Megan the Stallion for like standing on her

514
00:25:27,800 --> 00:25:28,240
Speaker 3: ground here.

515
00:25:28,680 --> 00:25:31,879
Speaker 1: I completely agree, and it's one of the reasons I

516
00:25:32,760 --> 00:25:35,120
Speaker 1: always worry when I talk about this and people are thinking, oh,

517
00:25:35,160 --> 00:25:37,720
Speaker 1: this is like celebrity fluff, But to me it's not

518
00:25:37,880 --> 00:25:40,680
Speaker 1: because if this is how they'll treat Meg the Stallion

519
00:25:41,040 --> 00:25:44,520
Speaker 1: like someone people love, someone with lots of resources, access, money,

520
00:25:44,640 --> 00:25:46,400
Speaker 1: Da da da. This, If this is how they treat

521
00:25:46,440 --> 00:25:49,640
Speaker 1: Amber Heard, how will they treat a bridge a toad?

522
00:25:49,880 --> 00:25:52,360
Speaker 1: How will they treat a Joey pat How will they

523
00:25:52,400 --> 00:25:55,600
Speaker 1: treat other people who do not have the resources and

524
00:25:55,640 --> 00:25:58,720
Speaker 1: the access. And so if someone with as much resources

525
00:25:58,760 --> 00:26:03,360
Speaker 1: as Meg, you or Amber Heard have will be treated

526
00:26:03,400 --> 00:26:06,000
Speaker 1: this way in court when they get their day in court.

527
00:26:07,080 --> 00:26:08,560
Speaker 2: Does not bode well for any of us.

528
00:26:08,600 --> 00:26:11,959
Speaker 1: And so I don't talk about it because it's a

529
00:26:12,000 --> 00:26:14,760
Speaker 1: celebrity fluff story. I talk about it because I think

530
00:26:14,800 --> 00:26:18,560
Speaker 1: it does illustrate something for the rest of us that

531
00:26:18,600 --> 00:26:21,480
Speaker 1: do not have the privilege and access of celebrities. And

532
00:26:21,520 --> 00:26:23,760
Speaker 1: if these celebrities could not escape this climate that is

533
00:26:23,800 --> 00:26:28,159
Speaker 1: so toxic and is so full of lies, none of

534
00:26:28,240 --> 00:26:31,960
Speaker 1: us will. And to your point about you know, I

535
00:26:32,000 --> 00:26:34,560
Speaker 1: got the same guidance, don't take pictures of yourself.

536
00:26:34,600 --> 00:26:35,440
Speaker 2: Da da da da.

537
00:26:35,560 --> 00:26:40,240
Speaker 1: When there was the iCloud photo hack in twenty fourteen,

538
00:26:41,080 --> 00:26:44,840
Speaker 1: so many prominent voices in tech echoed that they said, well,

539
00:26:45,280 --> 00:26:48,400
Speaker 1: these starlit should have never taken those photos, never mind

540
00:26:48,440 --> 00:26:51,880
Speaker 1: the fact that those photos were illegally hacked by a criminal,

541
00:26:52,320 --> 00:26:54,680
Speaker 1: and the hack of those photos was a sex crime.

542
00:26:54,720 --> 00:26:56,240
Speaker 1: We never really talked about it like that, but this

543
00:26:56,280 --> 00:26:59,080
Speaker 1: person committed a crime. Why you're blaming the victim for

544
00:26:59,119 --> 00:26:59,840
Speaker 1: taking those photos?

545
00:27:00,040 --> 00:27:04,640
Speaker 2: Don't know? However, now you know, ten years later, we

546
00:27:04,720 --> 00:27:05,760
Speaker 2: see how.

547
00:27:05,680 --> 00:27:09,080
Speaker 1: Not sufficient of a public conversation it was to just say, oh, well,

548
00:27:09,080 --> 00:27:11,119
Speaker 1: it's their fault for taking these photos, because now you

549
00:27:11,160 --> 00:27:13,160
Speaker 1: don't have to take photos. Now anybody can just get

550
00:27:13,200 --> 00:27:16,720
Speaker 1: your yearbook photo and use AI to make sexualized deep

551
00:27:16,720 --> 00:27:19,239
Speaker 1: thike images of you. It doesn't matter if you're a

552
00:27:19,280 --> 00:27:22,760
Speaker 1: fourteen year old New Jersey student or Meg the Stallion.

553
00:27:22,880 --> 00:27:26,080
Speaker 1: And so currently, that opportunity for a public conversation about

554
00:27:26,840 --> 00:27:29,560
Speaker 1: our tech climate when it becomes to identity and gender,

555
00:27:30,040 --> 00:27:32,600
Speaker 1: we did not have the conversation that we needed to

556
00:27:32,600 --> 00:27:34,399
Speaker 1: have because here we are ten years later and it's like, well,

557
00:27:34,400 --> 00:27:36,159
Speaker 1: it doesn't really matter if if you choose to take

558
00:27:36,160 --> 00:27:38,720
Speaker 1: your clothes off or not, they're gonna use AI to address.

559
00:27:38,320 --> 00:27:40,840
Speaker 2: You anyway, exactly exactly.

560
00:27:40,920 --> 00:27:46,440
Speaker 3: I mean, I do think the Google iCloud hacking woman,

561
00:27:46,480 --> 00:27:48,920
Speaker 3: I will say I think that was like a radicalizing

562
00:27:49,040 --> 00:27:52,000
Speaker 3: feminist moment for like fifteen year old me. Would that

563
00:27:52,080 --> 00:27:55,040
Speaker 3: puts out where that's sort of like shattered, because yeah,

564
00:27:55,119 --> 00:27:57,200
Speaker 3: no exactly. That was like the rhetoric and the news

565
00:27:57,359 --> 00:27:58,960
Speaker 3: all like oh my god, like how dare they take

566
00:27:59,000 --> 00:28:02,879
Speaker 3: these pictures? And I was like, well, you're talking about

567
00:28:02,920 --> 00:28:05,360
Speaker 3: all these actresses that I look up to and whatever.

568
00:28:06,040 --> 00:28:06,399
Speaker 4: I don't know.

569
00:28:06,560 --> 00:28:08,720
Speaker 3: It is like we're laying in a time where where

570
00:28:08,720 --> 00:28:12,560
Speaker 3: people are trying to police sexuality and particularly women and

571
00:28:12,640 --> 00:28:15,200
Speaker 3: like non suspense sexuality, and like.

572
00:28:16,400 --> 00:28:19,280
Speaker 2: We do also like this is this is one aspect

573
00:28:19,320 --> 00:28:21,280
Speaker 2: of that. I do always love.

574
00:28:21,119 --> 00:28:27,600
Speaker 3: To point to the the Uh Shit's Creek episode where

575
00:28:28,280 --> 00:28:33,679
Speaker 3: Moira's like old nudes that she took got leaked and

576
00:28:33,720 --> 00:28:36,560
Speaker 3: she's like she has like she's talking to Alexis and

577
00:28:36,600 --> 00:28:37,399
Speaker 3: the what's her name?

578
00:28:37,440 --> 00:28:37,640
Speaker 2: Cv?

579
00:28:37,840 --> 00:28:39,240
Speaker 3: Is that the the other girl in the show, and

580
00:28:39,280 --> 00:28:42,440
Speaker 3: she's like take pictures now, well you're young and hot,

581
00:28:42,520 --> 00:28:45,280
Speaker 3: And I was like that changed, that changed how I

582
00:28:45,280 --> 00:28:47,800
Speaker 3: thought about it. I was like, you're right, You're right,

583
00:28:47,840 --> 00:28:49,840
Speaker 3: because you know what, they're gonna get leaked no matter what.

584
00:28:49,960 --> 00:28:51,840
Speaker 3: Maybe we should all just be taking hot naked pictures

585
00:28:51,840 --> 00:28:54,880
Speaker 3: of ourselves, Like I don't know. Maybe the solution all

586
00:28:54,920 --> 00:28:57,240
Speaker 3: of this is we need to just like become more

587
00:28:57,360 --> 00:28:59,160
Speaker 3: chill with nudes being a thing.

588
00:29:01,240 --> 00:29:05,400
Speaker 1: Moira tech Icon ahead of her time, her time, Catherine O'Hara,

589
00:29:05,440 --> 00:29:07,880
Speaker 1: if you want to come on the podcast please.

590
00:29:08,200 --> 00:29:10,480
Speaker 2: Oh my god, it will be it would.

591
00:29:10,320 --> 00:29:15,040
Speaker 3: Be anything else, anything anything.

592
00:29:19,640 --> 00:29:32,720
Speaker 4: Let's take a quick break at our back.

593
00:29:37,480 --> 00:29:42,800
Speaker 1: Well, speaking of AI, I am really riled up about

594
00:29:43,160 --> 00:29:46,600
Speaker 1: this potential AI executive order. So we talked a while

595
00:29:46,720 --> 00:29:50,600
Speaker 1: back about how Republicans are trying to unsuccessfully but did

596
00:29:50,680 --> 00:29:55,000
Speaker 1: try to sneak a moratorium on any state level AI

597
00:29:55,160 --> 00:29:58,440
Speaker 1: laws into their so called Big Beautiful.

598
00:29:58,040 --> 00:30:00,680
Speaker 3: Bill because we need more more music, Like I just

599
00:30:00,720 --> 00:30:04,200
Speaker 3: showed you its top We yeah, songs honoring Charlie Kirk's legacy.

600
00:30:04,440 --> 00:30:08,800
Speaker 1: We can't curtail innovation. Okay, So the White House is

601
00:30:09,520 --> 00:30:12,040
Speaker 1: back on it. They are trying to make sure that

602
00:30:12,120 --> 00:30:15,560
Speaker 1: we get as many of these Charlie Kirk AI generated

603
00:30:15,560 --> 00:30:19,080
Speaker 1: songs as possible. They're preparing to issue an executive order

604
00:30:19,360 --> 00:30:22,520
Speaker 1: as soon as Friday that enlists the power of the

605
00:30:22,520 --> 00:30:25,960
Speaker 1: federal government to block states from regulating AI. This is

606
00:30:25,960 --> 00:30:28,160
Speaker 1: according to four people familiar with the matter. In a

607
00:30:28,240 --> 00:30:33,040
Speaker 1: leaked draft order obtained by Politico. The draft document, confirmed

608
00:30:33,040 --> 00:30:35,760
Speaker 1: as authentic by three people familiar with the matter, would

609
00:30:35,800 --> 00:30:39,720
Speaker 1: launch several efforts to challenge state level AI laws, including

610
00:30:39,920 --> 00:30:43,400
Speaker 1: forming an AI Litigation task Force run by the Department

611
00:30:43,440 --> 00:30:46,320
Speaker 1: of Justice. Now, this is a real problem for a

612
00:30:46,360 --> 00:30:48,840
Speaker 1: lot of reasons, the first of which is that the

613
00:30:48,920 --> 00:30:52,200
Speaker 1: state level laws are a necessary step to get any

614
00:30:52,280 --> 00:30:55,080
Speaker 1: kind of federal legislation, which, let's be real, this administration

615
00:30:55,320 --> 00:30:56,760
Speaker 1: seems very keen to avoid.

616
00:30:57,040 --> 00:30:58,240
Speaker 2: But if you have like a.

617
00:30:58,200 --> 00:31:01,920
Speaker 1: Network of packed work state level laws, eventually that kind

618
00:31:01,920 --> 00:31:04,920
Speaker 1: of thing, historically can lead to some sort of meaningful

619
00:31:05,000 --> 00:31:05,960
Speaker 1: federal legislation.

620
00:31:06,440 --> 00:31:07,640
Speaker 2: And it will be one thing.

621
00:31:08,120 --> 00:31:10,800
Speaker 1: If the federal government was trying to prevent state laws

622
00:31:10,840 --> 00:31:13,800
Speaker 1: that address AI harms because they wanted like a more

623
00:31:14,000 --> 00:31:19,080
Speaker 1: comprehensive federal approach. Maybe, However, that is not what this is. Instead,

624
00:31:19,160 --> 00:31:21,640
Speaker 1: this is the Trump administration wanting to make sure that

625
00:31:21,720 --> 00:31:24,920
Speaker 1: no one, not states nor the federal government, is doing

626
00:31:25,000 --> 00:31:28,560
Speaker 1: anything that might possibly impact the profits of AI companies.

627
00:31:28,720 --> 00:31:31,400
Speaker 1: They're essentially all in on AI companies as the future

628
00:31:31,400 --> 00:31:34,160
Speaker 1: of the American economy, so they don't want them regulated

629
00:31:34,280 --> 00:31:36,240
Speaker 1: in any way by anyone.

630
00:31:37,000 --> 00:31:38,560
Speaker 2: Here's how Politico describes it.

631
00:31:38,920 --> 00:31:41,240
Speaker 1: The executive order would be a different approach than the

632
00:31:41,280 --> 00:31:43,840
Speaker 1: previous attempt because it is deploying the muscle of several

633
00:31:43,880 --> 00:31:48,160
Speaker 1: federal agencies to quash state AI regulations. Government lawyers would

634
00:31:48,160 --> 00:31:50,480
Speaker 1: be directed to challenge state laws on the grounds that

635
00:31:50,520 --> 00:31:56,120
Speaker 1: they unconstitutionally regulate interstate commerce, are preempted by existing federal regulations,

636
00:31:56,560 --> 00:32:00,360
Speaker 1: or otherwise at the Attorney General's discretion. So this task

637
00:32:00,440 --> 00:32:03,280
Speaker 1: force would consult with administration officials from the White House,

638
00:32:03,400 --> 00:32:06,960
Speaker 1: including Special Advisor for AI and Crypto, which is a

639
00:32:07,040 --> 00:32:12,000
Speaker 1: role that is currently occupied by investor Comma hack All

640
00:32:12,080 --> 00:32:16,000
Speaker 1: in Tech podcast or David Sachs. He would be in

641
00:32:16,080 --> 00:32:20,000
Speaker 1: charge of determining which state AI laws would be worth challenging,

642
00:32:20,080 --> 00:32:21,320
Speaker 1: according to this document.

643
00:32:21,840 --> 00:32:24,280
Speaker 2: So if you're wondering what does all of this mean,

644
00:32:24,360 --> 00:32:24,920
Speaker 2: why do I care?

645
00:32:24,960 --> 00:32:28,479
Speaker 1: Think about it like this right now, several states have

646
00:32:28,600 --> 00:32:30,920
Speaker 1: some kind of state level legislation on the books to

647
00:32:30,920 --> 00:32:32,880
Speaker 1: prevent the thing that we were just talking about with

648
00:32:32,920 --> 00:32:35,640
Speaker 1: the Magma stallion story, AI generated deep figs and their

649
00:32:35,680 --> 00:32:39,520
Speaker 1: spread Pennsylvania, Washington, Michigan, Tennessee, California.

650
00:32:39,840 --> 00:32:41,320
Speaker 2: This executive order would.

651
00:32:41,120 --> 00:32:45,520
Speaker 1: Threaten those kinds of laws or legislation that tells job

652
00:32:45,560 --> 00:32:48,200
Speaker 1: seekers that they have a right to be notified when

653
00:32:48,240 --> 00:32:51,480
Speaker 1: AI is being used in the job application screening process,

654
00:32:51,760 --> 00:32:54,320
Speaker 1: or legislation that outright prevents it from being used in

655
00:32:54,360 --> 00:32:57,000
Speaker 1: the job application process because we know AI is biased,

656
00:32:57,240 --> 00:33:00,800
Speaker 1: that states like New York, Colorado, Illinois, California have laws

657
00:33:00,840 --> 00:33:03,800
Speaker 1: pertaining to that right now, or how just this week

658
00:33:03,960 --> 00:33:08,440
Speaker 1: Portland pass legislation banning AI rent price fixing, which, by

659
00:33:08,480 --> 00:33:11,720
Speaker 1: the way, just this week, North Carolina Attorney General Jeff

660
00:33:11,800 --> 00:33:15,440
Speaker 1: Jackson reached a seven million dollar settlement with North Carolina's

661
00:33:15,600 --> 00:33:19,600
Speaker 1: largest landlord because that company was using AI to illegally

662
00:33:19,720 --> 00:33:23,840
Speaker 1: coordinate rent prices. So we currently right now have all

663
00:33:23,920 --> 00:33:30,120
Speaker 1: kinds of state level AI legislation that dictates how institutions

664
00:33:30,800 --> 00:33:33,680
Speaker 1: can use AI in ways that are meant to help

665
00:33:33,800 --> 00:33:37,320
Speaker 1: protect citizens and consumers. So if you zoom out and

666
00:33:37,400 --> 00:33:39,880
Speaker 1: imagine what a landscape looks like if this executive order

667
00:33:39,920 --> 00:33:41,680
Speaker 1: goes through and is meaningful.

668
00:33:41,840 --> 00:33:44,280
Speaker 2: You know, executive orders are not laws. But the Supreme

669
00:33:44,320 --> 00:33:46,360
Speaker 2: Court in Congress seem very keen to just let Trump

670
00:33:46,400 --> 00:33:47,800
Speaker 2: do whatever you want. So we'll see.

671
00:33:47,960 --> 00:33:52,240
Speaker 1: But instead of states kind of experimenting and responding to

672
00:33:52,360 --> 00:33:55,480
Speaker 1: the real harm happening in their communities and building in

673
00:33:55,560 --> 00:33:59,120
Speaker 1: some kind of guardfrail against it that Congress has, through TOOFO,

674
00:33:59,320 --> 00:34:01,920
Speaker 1: refused to build. The federal government is stepping in and

675
00:34:01,920 --> 00:34:06,040
Speaker 1: saying wait, no, stand down, wait for us, and wait

676
00:34:06,120 --> 00:34:10,080
Speaker 1: for what. Because there is no current federal AI law

677
00:34:10,200 --> 00:34:13,360
Speaker 1: on the table, it's just a vacuum. And in that vacuum,

678
00:34:13,560 --> 00:34:16,560
Speaker 1: the White House is basically stepping in not to protect

679
00:34:16,640 --> 00:34:21,640
Speaker 1: the citizens, Americans consumers, but to protect corporations. And I

680
00:34:21,640 --> 00:34:24,480
Speaker 1: think especially we're probably going to see this be the

681
00:34:24,520 --> 00:34:27,080
Speaker 1: kind of thing where it is corporations who are willing

682
00:34:27,120 --> 00:34:30,920
Speaker 1: to play ball and let's keep it real, pay bribes

683
00:34:31,080 --> 00:34:34,400
Speaker 1: to the Trump administration that will be able to continue

684
00:34:34,400 --> 00:34:39,520
Speaker 1: to operate without this friction. It's just such a shocking, blatant.

685
00:34:39,080 --> 00:34:41,760
Speaker 2: Disregard for what is good for your average American.

686
00:34:42,200 --> 00:34:44,960
Speaker 3: You know, this is like going back to like the

687
00:34:45,000 --> 00:34:48,040
Speaker 3: celebrity culture element of it in our last story. I

688
00:34:48,120 --> 00:34:50,719
Speaker 3: do wonder because I don't know if Bridget you saw

689
00:34:50,760 --> 00:34:54,160
Speaker 3: the Kim Kardashian video this week of her crying because

690
00:34:54,360 --> 00:35:00,600
Speaker 3: she failed the California bar exam because she claimed it

691
00:35:00,640 --> 00:35:03,000
Speaker 3: was because of Chat Gibt and because she was using kashibt,

692
00:35:03,960 --> 00:35:09,400
Speaker 3: can Kame Kardashian, pull the fuck up and please become

693
00:35:09,560 --> 00:35:13,799
Speaker 3: like if she becomes our anti like or like our

694
00:35:14,080 --> 00:35:17,799
Speaker 3: pro AI regulation, if she becomes the champion for that,

695
00:35:18,000 --> 00:35:21,919
Speaker 3: I will forgive you for everything else you have done

696
00:35:22,280 --> 00:35:23,160
Speaker 3: in your career.

697
00:35:25,160 --> 00:35:26,040
Speaker 2: She could do it.

698
00:35:26,160 --> 00:35:27,239
Speaker 3: She could do it.

699
00:35:27,480 --> 00:35:29,959
Speaker 1: And I think it's I mean, this is a little

700
00:35:29,960 --> 00:35:32,040
Speaker 1: bit above my pay grain, but I have to imagine

701
00:35:32,040 --> 00:35:36,839
Speaker 1: it's related to you know, AI essentially propping up our

702
00:35:36,880 --> 00:35:40,839
Speaker 1: economy right now. And I think the government is very invested,

703
00:35:41,800 --> 00:35:45,360
Speaker 1: no pun intended, but appreciated in the idea that this

704
00:35:45,440 --> 00:35:47,840
Speaker 1: AI bubble is not going to burst. And so I

705
00:35:47,840 --> 00:35:50,400
Speaker 1: think being like, oh, what if we said that nobody

706
00:35:50,400 --> 00:35:53,680
Speaker 1: can do anything to purtail this technology, that might help

707
00:35:54,200 --> 00:35:56,760
Speaker 1: foster this idea that it's not going to burst?

708
00:35:56,800 --> 00:35:58,080
Speaker 2: And yeah, just I.

709
00:35:58,440 --> 00:36:02,640
Speaker 1: Hate how much of our democracy in our economy has

710
00:36:02,680 --> 00:36:08,279
Speaker 1: just turned into fucking like casino gambling and robbing Peter

711
00:36:08,400 --> 00:36:10,080
Speaker 1: to pay Paul shell games.

712
00:36:10,120 --> 00:36:11,759
Speaker 2: Just like I think this.

713
00:36:11,960 --> 00:36:14,399
Speaker 1: I think something about this executive order just really makes

714
00:36:14,400 --> 00:36:17,719
Speaker 1: that clear how much it is just setting things up

715
00:36:17,800 --> 00:36:21,560
Speaker 1: for bribes and scams, and the American people, we're the

716
00:36:21,560 --> 00:36:24,840
Speaker 1: ones who are losing ultimately, and it just pisses me

717
00:36:24,920 --> 00:36:26,960
Speaker 1: off that there are still people who will see this,

718
00:36:27,800 --> 00:36:32,600
Speaker 1: people who will never like they'll never see that white house, ballroom, whatever, whatever,

719
00:36:32,719 --> 00:36:36,600
Speaker 1: who are like, yeah, it's good that AI companies can

720
00:36:36,719 --> 00:36:39,640
Speaker 1: illegally collude to raise my rent using AI. It's like,

721
00:36:39,880 --> 00:36:42,000
Speaker 1: in what way you're a renter babe?

722
00:36:42,000 --> 00:36:44,279
Speaker 2: In what like? I don't see how your average.

723
00:36:44,000 --> 00:36:46,040
Speaker 1: Everyday American can see this and be like, oh, yeah,

724
00:36:46,120 --> 00:36:47,959
Speaker 1: this is gonna be great for me. It's it's better

725
00:36:48,000 --> 00:36:49,719
Speaker 1: if they can use AI to raise my rent. I

726
00:36:49,760 --> 00:36:50,759
Speaker 1: love paying more in rent.

727
00:36:50,840 --> 00:36:53,240
Speaker 2: Who doesn't I love paying more in rent?

728
00:36:53,280 --> 00:36:56,080
Speaker 3: Personally, I want my life to be more expensive and

729
00:36:56,120 --> 00:36:58,920
Speaker 3: with a like shittier result.

730
00:37:00,000 --> 00:37:02,160
Speaker 2: I don't know it is. It is really weird.

731
00:37:02,239 --> 00:37:05,319
Speaker 3: Yeah, the whole conversation around AI is just like it's

732
00:37:05,360 --> 00:37:07,239
Speaker 3: gotten to the point where, again, yeah, we have like

733
00:37:07,440 --> 00:37:10,440
Speaker 3: Kim Kardashian of all people coming out here and being like,

734
00:37:10,560 --> 00:37:12,799
Speaker 3: oh my god, chash DBT is the reason I fail

735
00:37:12,840 --> 00:37:16,200
Speaker 3: at my logs whatever. I'm like, why am I out

736
00:37:16,200 --> 00:37:18,560
Speaker 3: here agreeing with Kim mart Like, You're getting people from

737
00:37:18,600 --> 00:37:21,840
Speaker 3: all like levels of society.

738
00:37:22,280 --> 00:37:24,239
Speaker 2: You're getting people that work.

739
00:37:24,080 --> 00:37:27,400
Speaker 3: White collar jobs talking about how they're frustrated with AI.

740
00:37:27,560 --> 00:37:30,520
Speaker 3: You're getting you know, people that are getting screwed over

741
00:37:30,600 --> 00:37:34,239
Speaker 3: across the board because their rent is going up because

742
00:37:34,280 --> 00:37:37,880
Speaker 3: of AI, or because you know, it's harder to just

743
00:37:38,000 --> 00:37:41,040
Speaker 3: google something and find an answer because of AI. Like

744
00:37:41,800 --> 00:37:43,360
Speaker 3: I don't know, it is it is. It is a

745
00:37:43,560 --> 00:37:46,839
Speaker 3: really strange time to to just be like, we all

746
00:37:46,880 --> 00:37:50,160
Speaker 3: acknowledge this as bad, we're just not doing anything about it.

747
00:37:50,480 --> 00:38:08,600
Speaker 4: Here here, let's take a quick break at her back.

748
00:38:13,880 --> 00:38:15,440
Speaker 1: So I do have to throw a little bit of

749
00:38:15,480 --> 00:38:17,440
Speaker 1: a trigger warning on top of this one because it

750
00:38:17,520 --> 00:38:21,280
Speaker 1: is a very tragic story. In Minnesota, a young welder

751
00:38:21,360 --> 00:38:24,680
Speaker 1: named Amberchech, who was only twenty was murdered by her

752
00:38:24,760 --> 00:38:28,600
Speaker 1: fellow employee at their equipment and Systems design and fabrication

753
00:38:29,080 --> 00:38:33,279
Speaker 1: factory work site. She was bludgeoned to death by her

754
00:38:33,360 --> 00:38:36,560
Speaker 1: male co worker, David DeLong, who was forty years old,

755
00:38:37,040 --> 00:38:41,279
Speaker 1: at the Advanced Process Technologies manufacturing facility in Minnesota, which

756
00:38:41,320 --> 00:38:44,600
Speaker 1: specializes in services to the food and dairy industry. So

757
00:38:45,560 --> 00:38:48,960
Speaker 1: it is an absolutely heartbreaking story. Auth already said that

758
00:38:49,400 --> 00:38:53,000
Speaker 1: this guy had been probably planning on murdering Amber for

759
00:38:53,040 --> 00:38:56,600
Speaker 1: a while, because he said that he quote just didn't

760
00:38:56,719 --> 00:39:00,759
Speaker 1: like her. County attorney Brian Lutz said that DeLong felt

761
00:39:00,800 --> 00:39:04,120
Speaker 1: that Amber had quote given him a bad look and

762
00:39:04,160 --> 00:39:07,480
Speaker 1: that he was upset about that. Now, mind you, Amber

763
00:39:07,600 --> 00:39:10,759
Speaker 1: was twenty years old and this man was forty, so

764
00:39:11,200 --> 00:39:16,560
Speaker 1: someone half his age. He was upset, according to him,

765
00:39:16,800 --> 00:39:20,279
Speaker 1: by just a quote bad look that somebody half his

766
00:39:20,360 --> 00:39:24,200
Speaker 1: age gave him. So he was reportedly charged with second

767
00:39:24,280 --> 00:39:27,600
Speaker 1: or murder, but Wright County Attorney Brian Lutz told kar

768
00:39:27,880 --> 00:39:30,520
Speaker 1: the Minnesota local news affiliate, in a statement that he

769
00:39:30,560 --> 00:39:33,040
Speaker 1: plans to evaluate the case for a possible charge a

770
00:39:33,080 --> 00:39:37,160
Speaker 1: first degree prematitated murder, which requires conveniing a grand jury,

771
00:39:37,160 --> 00:39:41,719
Speaker 1: which again I'm no lawyer, but somebody who officials say

772
00:39:41,800 --> 00:39:44,879
Speaker 1: had been planning this murder for a while. I don't

773
00:39:44,960 --> 00:39:47,440
Speaker 1: understand what that wouldn't be a first degree murder. But

774
00:39:47,520 --> 00:39:50,960
Speaker 1: I'm no attorney, and so I wanted to talk about

775
00:39:50,960 --> 00:39:54,920
Speaker 1: this both as just a terrible tragedy, but also to

776
00:39:55,040 --> 00:39:59,200
Speaker 1: spotlight the roles of women in the trades like Amber.

777
00:40:00,080 --> 00:40:03,120
Speaker 1: You probably already know that women are very underrepresented in

778
00:40:03,200 --> 00:40:06,640
Speaker 1: trade work like welding and electrical work. According to the

779
00:40:06,680 --> 00:40:10,640
Speaker 1: Institute for Women's Policy Research, tradeswomen were only four point

780
00:40:10,680 --> 00:40:13,600
Speaker 1: three percent of all construction trade workers as of twenty

781
00:40:13,640 --> 00:40:17,080
Speaker 1: twenty four, and in certain trades it's even lower. Three

782
00:40:17,120 --> 00:40:20,480
Speaker 1: point two percent of plumbers and pipefitters and two point

783
00:40:20,560 --> 00:40:26,000
Speaker 1: nine percent of electricians are women. So unsurprisingly, women face

784
00:40:26,160 --> 00:40:30,560
Speaker 1: challenges in the trades like discrimination and a hostile workplace culture.

785
00:40:31,440 --> 00:40:34,160
Speaker 1: There is this viral post going around Breddit that I

786
00:40:34,160 --> 00:40:38,040
Speaker 1: saw claiming that Amber had actually made several complaints about

787
00:40:38,040 --> 00:40:40,360
Speaker 1: this person to HR, But I could not actually verify

788
00:40:40,360 --> 00:40:43,319
Speaker 1: that myself or find a source for that claim other

789
00:40:43,360 --> 00:40:47,239
Speaker 1: than the post itself. But honestly, it would not surprise me.

790
00:40:48,000 --> 00:40:50,520
Speaker 1: In a statement about Amber's seat, the National Association of

791
00:40:50,560 --> 00:40:54,160
Speaker 1: Women in Construction president Rudi Brown said, we must confront

792
00:40:54,200 --> 00:40:58,120
Speaker 1: the truth that too many tradeswomen have endured hostility, intimidation, harassment,

793
00:40:58,160 --> 00:41:01,320
Speaker 1: and threats on job sites where warning signs were visible

794
00:41:01,400 --> 00:41:05,160
Speaker 1: but unaddressed. This tragedy is not an anomaly. It is

795
00:41:05,200 --> 00:41:07,600
Speaker 1: part of a disturbing pattern that we as an industry

796
00:41:07,640 --> 00:41:11,520
Speaker 1: can no longer deny and will no longer tolerate. And

797
00:41:11,560 --> 00:41:14,840
Speaker 1: so it is just something that I think, you know,

798
00:41:14,880 --> 00:41:17,320
Speaker 1: we often talk about how people shouldn't go to college

799
00:41:17,360 --> 00:41:20,320
Speaker 1: and should go into the trades, and I'm very supportive

800
00:41:20,320 --> 00:41:22,160
Speaker 1: of the trades. I have often thought about going back

801
00:41:22,160 --> 00:41:26,400
Speaker 1: and becoming an electrician. If I ever stopped podcasting about technology,

802
00:41:26,480 --> 00:41:27,920
Speaker 1: I would probably be an electrician.

803
00:41:28,440 --> 00:41:32,160
Speaker 3: Yeah, this is just such a horrifying story on its own,

804
00:41:33,000 --> 00:41:34,920
Speaker 3: But yeah, I think, like to the point you were

805
00:41:34,920 --> 00:41:38,200
Speaker 3: making about if we're saying yes, more people should go

806
00:41:38,239 --> 00:41:41,040
Speaker 3: to trade school, for encouraging people to go to trade school,

807
00:41:41,160 --> 00:41:44,880
Speaker 3: like when you say people, women are half of people,

808
00:41:45,719 --> 00:41:47,680
Speaker 3: So it's like, if you want people to do that,

809
00:41:47,719 --> 00:41:49,959
Speaker 3: you need to make it safe for everybody.

810
00:41:50,560 --> 00:41:51,200
Speaker 2: Exactly.

811
00:41:51,760 --> 00:41:54,799
Speaker 1: Yes, And I don't even really know how to talk

812
00:41:54,840 --> 00:41:57,920
Speaker 1: about this because I don't want to speculate on stuff

813
00:41:57,960 --> 00:42:01,040
Speaker 1: I don't know. But you know, in looking at information

814
00:42:01,120 --> 00:42:07,160
Speaker 1: about this case, Amber was young, twenty and she had

815
00:42:07,320 --> 00:42:10,640
Speaker 1: like short hair and all these pictures, and part of

816
00:42:10,680 --> 00:42:14,160
Speaker 1: me wonders if that is part of what's going on

817
00:42:14,239 --> 00:42:16,400
Speaker 1: here that people aren't really reporting.

818
00:42:15,960 --> 00:42:16,879
Speaker 2: On that one.

819
00:42:17,120 --> 00:42:19,880
Speaker 1: I think that the fact that this guy was forty

820
00:42:19,920 --> 00:42:23,000
Speaker 1: and she was twenty, there was a huge age discrepancy there,

821
00:42:23,000 --> 00:42:26,440
Speaker 1: and so like I think that gen Z in the workplace,

822
00:42:26,480 --> 00:42:31,040
Speaker 1: I think that like that might be part of something

823
00:42:31,080 --> 00:42:34,279
Speaker 1: that made her vulnerable in this workplace that I that

824
00:42:34,480 --> 00:42:36,600
Speaker 1: like should have been addressed and she should have been

825
00:42:36,600 --> 00:42:37,239
Speaker 1: supported on.

826
00:42:37,640 --> 00:42:40,160
Speaker 2: And then two part of me wonders if this guy.

827
00:42:40,760 --> 00:42:44,600
Speaker 1: Perceived her as whether or not she was as like

828
00:42:44,800 --> 00:42:47,040
Speaker 1: queer or LGBTQ in some way because she had quite

829
00:42:47,080 --> 00:42:50,520
Speaker 1: short hair. And so I can't imagine, dude, you know

830
00:42:50,560 --> 00:42:52,799
Speaker 1: what I'm saying, Like I don't want to speculate, but like.

831
00:42:52,960 --> 00:42:55,920
Speaker 3: No, I agree, I mean I think even beyond like

832
00:42:55,960 --> 00:42:58,720
Speaker 3: not speculating, I'll say, somebody who like I have pretty

833
00:42:58,719 --> 00:43:02,359
Speaker 3: short hair like a bridget. You can see me where

834
00:43:02,400 --> 00:43:03,960
Speaker 3: my hair is out, like this is the longest I spent.

835
00:43:04,080 --> 00:43:06,239
Speaker 3: This is usually like I'm probably gonna get a hair

836
00:43:06,280 --> 00:43:06,560
Speaker 3: cu like.

837
00:43:06,560 --> 00:43:07,200
Speaker 2: A month like this is.

838
00:43:07,400 --> 00:43:10,000
Speaker 3: But like I can tell that I when my hair

839
00:43:10,080 --> 00:43:12,400
Speaker 3: is this even just a little bit longer, where like

840
00:43:12,600 --> 00:43:14,799
Speaker 3: it could it's closer to like a bob, I get

841
00:43:14,840 --> 00:43:17,880
Speaker 3: treated so differently. Like when my hair is like as

842
00:43:17,880 --> 00:43:19,960
Speaker 3: short as I usually cut it, that is a very

843
00:43:19,960 --> 00:43:22,120
Speaker 3: different experience from when my hair is a little bit longer,

844
00:43:22,200 --> 00:43:25,440
Speaker 3: and maybe I'm dressed a little bit more feminine. It's

845
00:43:25,480 --> 00:43:27,920
Speaker 3: still uncomfortable, It's still sort of the meaning the way

846
00:43:27,920 --> 00:43:30,560
Speaker 3: that I'm treated, but it's like safer.

847
00:43:30,120 --> 00:43:32,319
Speaker 2: In a weird way. Like I know that I'm like,

848
00:43:33,120 --> 00:43:33,480
Speaker 2: I don't know.

849
00:43:33,520 --> 00:43:36,120
Speaker 3: I've like had this conversation before about like if I'm

850
00:43:36,120 --> 00:43:37,520
Speaker 3: going into like a space that I don't know if

851
00:43:37,520 --> 00:43:39,320
Speaker 3: it's going to be super like queer friendly or whenever.

852
00:43:39,800 --> 00:43:41,880
Speaker 3: If I if my hair is longer, when that's happening,

853
00:43:41,920 --> 00:43:43,680
Speaker 3: I'm usually like, Okay, yeah, I can get away with it.

854
00:43:43,719 --> 00:43:45,520
Speaker 3: If my hair is little shorter, I'll usually try to

855
00:43:45,520 --> 00:43:49,480
Speaker 3: like them it up a little bit too, you know not.

856
00:43:49,600 --> 00:43:51,799
Speaker 3: But yeah, no, I wouldn't be surprised if that also

857
00:43:52,760 --> 00:43:54,000
Speaker 3: was part of this.

858
00:43:54,440 --> 00:43:56,759
Speaker 2: Uh yeah, no, I can go back.

859
00:43:56,680 --> 00:43:58,440
Speaker 3: To the fact that he was forty and she was

860
00:43:58,680 --> 00:44:03,239
Speaker 3: twenty is crazy, and I mean I think beyond that,

861
00:44:03,320 --> 00:44:04,920
Speaker 3: I'm sure every.

862
00:44:06,040 --> 00:44:07,040
Speaker 2: As somebody who is.

863
00:44:07,080 --> 00:44:12,200
Speaker 3: A a bad person who has worked in male dominated

864
00:44:12,239 --> 00:44:18,440
Speaker 3: fields like my whole life. I mean, it's, uh yeah,

865
00:44:18,520 --> 00:44:19,160
Speaker 3: you will be.

866
00:44:19,520 --> 00:44:21,359
Speaker 2: You will have an.

867
00:44:21,320 --> 00:44:24,440
Speaker 3: Uncomfortable experience with a man that's twice your age, and

868
00:44:24,520 --> 00:44:26,200
Speaker 3: unfortunately that's kind of just a given right.

869
00:44:26,280 --> 00:44:27,759
Speaker 2: It shouldn't be. It shouldn't be.

870
00:44:28,080 --> 00:44:30,080
Speaker 3: I'm not saying that's okay, I'm not saying that should

871
00:44:30,080 --> 00:44:32,840
Speaker 3: be the a worm, but like I don't know, having

872
00:44:32,840 --> 00:44:36,480
Speaker 3: worked in media, having previously worked in film working and podcasting. Now,

873
00:44:36,600 --> 00:44:40,480
Speaker 3: like I I've had plenty of experiences of like men

874
00:44:40,520 --> 00:44:44,839
Speaker 3: twice my age that have been really weird and uncomfortable,

875
00:44:44,960 --> 00:44:48,200
Speaker 3: and you know, thank god, nothing really bad has happened

876
00:44:48,239 --> 00:44:50,400
Speaker 3: to me personally. But it's like, this is a possibility,

877
00:44:50,400 --> 00:44:52,320
Speaker 3: this is something that you have to think about.

878
00:44:52,800 --> 00:44:55,040
Speaker 2: It's true, and it shouldn't be true.

879
00:44:55,560 --> 00:44:58,480
Speaker 1: And in the case of Amber, the National Association of

880
00:44:58,520 --> 00:45:02,200
Speaker 1: Women in Construction and Building Trades unions are all calling

881
00:45:02,280 --> 00:45:05,839
Speaker 1: for like industry support and increase protections for women who

882
00:45:06,120 --> 00:45:10,799
Speaker 1: work in key construction site jobs. And you know, I

883
00:45:10,920 --> 00:45:13,799
Speaker 1: just think like it's just a reminder that with all

884
00:45:13,880 --> 00:45:15,960
Speaker 1: the talk of going into the trades, which like I

885
00:45:16,040 --> 00:45:18,480
Speaker 1: love the trades, I will never shot on the trades.

886
00:45:19,000 --> 00:45:21,600
Speaker 2: However, the work, as you said, the work has to

887
00:45:21,640 --> 00:45:24,040
Speaker 2: be safe for everybody. The work has to be safe,

888
00:45:24,040 --> 00:45:26,399
Speaker 2: whether you're queer, whether you're a young woman, whether you're

889
00:45:26,400 --> 00:45:28,000
Speaker 2: a gen z. It has to be safe.

890
00:45:28,080 --> 00:45:30,160
Speaker 1: You have to be able to show up and feel

891
00:45:30,160 --> 00:45:31,960
Speaker 1: like you're going to be protected. And if right now

892
00:45:32,000 --> 00:45:35,799
Speaker 1: it doesn't sound like we're creating that kind of a

893
00:45:35,840 --> 00:45:38,600
Speaker 1: culture that is going to allow for everybody to show up.

894
00:45:38,680 --> 00:45:41,520
Speaker 1: And you know, if there are any trades women listening,

895
00:45:41,560 --> 00:45:44,000
Speaker 1: like it is tough, it's tough work.

896
00:45:44,000 --> 00:45:44,680
Speaker 2: The people who do.

897
00:45:44,640 --> 00:45:47,400
Speaker 1: This work, they work hard, and they are a workforce

898
00:45:47,480 --> 00:45:51,360
Speaker 1: that is very very important, and too often, especially for

899
00:45:51,920 --> 00:45:55,640
Speaker 1: marginalized people in that workforce, are doing this critical work

900
00:45:55,960 --> 00:45:58,160
Speaker 1: without the protections and support that they need.

901
00:45:58,200 --> 00:45:59,960
Speaker 2: And so I guess I'm hard.

902
00:46:00,880 --> 00:46:03,359
Speaker 1: As tragic as this is, I'm heartened to see these

903
00:46:03,440 --> 00:46:07,640
Speaker 1: unions and these organizations trying to at least use this

904
00:46:07,800 --> 00:46:09,880
Speaker 1: tragedy to get a little bit of justice and like,

905
00:46:10,400 --> 00:46:13,680
Speaker 1: use this, use Amber's legacy to really shine a spotlight

906
00:46:13,800 --> 00:46:18,640
Speaker 1: on underrepresented folks who are in the trade, because it's

907
00:46:18,680 --> 00:46:21,160
Speaker 1: important is that it genuinely is life or death.

908
00:46:24,120 --> 00:46:38,399
Speaker 4: More. After a quick break, let's get right back into it.

909
00:46:42,560 --> 00:46:45,400
Speaker 1: Well, switching gears a little bit. This is not the

910
00:46:45,480 --> 00:46:48,400
Speaker 1: kind of story that we usually talk about, but I

911
00:46:48,560 --> 00:46:50,719
Speaker 1: was just sort of very intrigued by it because it

912
00:46:50,760 --> 00:46:53,600
Speaker 1: has come to my attention that parents out here might

913
00:46:53,640 --> 00:46:57,239
Speaker 1: be getting scammed because I truly had no idea until

914
00:46:57,400 --> 00:47:02,600
Speaker 1: very recently how much money is involved in youth sports.

915
00:47:03,040 --> 00:47:05,920
Speaker 1: In researching this segment, I came across multiple people who

916
00:47:06,040 --> 00:47:10,279
Speaker 1: use this term the youth sports industrial complex, because if

917
00:47:10,280 --> 00:47:14,959
Speaker 1: your kid plays hockey, especially hockey, but other sports too, basketball, cheer,

918
00:47:15,120 --> 00:47:18,520
Speaker 1: really anything competitive, you are opening your fucking wallet because

919
00:47:18,520 --> 00:47:19,840
Speaker 1: this shit is very expensive.

920
00:47:20,000 --> 00:47:22,160
Speaker 2: Oh yeah, did you know this kind ofness?

921
00:47:22,160 --> 00:47:26,120
Speaker 3: So I was a competitive dancer growing up, so I

922
00:47:26,160 --> 00:47:29,040
Speaker 3: and that is a whole other world of like dance

923
00:47:29,080 --> 00:47:34,440
Speaker 3: industrial complex kind of thing. But I uh, I'm sure.

924
00:47:34,760 --> 00:47:37,480
Speaker 3: And I never was a sports person. I never really

925
00:47:37,560 --> 00:47:41,799
Speaker 3: played competitive sports growing up. But seeing my friends that did,

926
00:47:41,880 --> 00:47:45,440
Speaker 3: or friends siblings that did, uh, I'm not.

927
00:47:45,480 --> 00:47:46,799
Speaker 2: Surprised by all this.

928
00:47:47,040 --> 00:47:49,040
Speaker 3: And again, yeah, I was in the dance world, which

929
00:47:49,080 --> 00:47:54,480
Speaker 3: was very similar as much as I though, although they

930
00:47:54,520 --> 00:47:56,759
Speaker 3: always would tell us because whenever it would be like, oh,

931
00:47:56,760 --> 00:47:58,560
Speaker 3: this is a sport, they would be like, no, we're artists.

932
00:47:58,600 --> 00:48:02,040
Speaker 3: This is an art We're not art it's an art forum.

933
00:48:02,719 --> 00:48:03,440
Speaker 2: So I don't know.

934
00:48:03,520 --> 00:48:06,440
Speaker 3: I guess like artists can scam you to I don't know.

935
00:48:06,719 --> 00:48:07,680
Speaker 2: Yeah, yeah, it's.

936
00:48:07,560 --> 00:48:11,359
Speaker 3: All scam We were special. We were artists. We weren't like,

937
00:48:11,719 --> 00:48:12,640
Speaker 3: we weren't jocks.

938
00:48:12,840 --> 00:48:13,600
Speaker 2: That's so funny.

939
00:48:13,600 --> 00:48:15,920
Speaker 1: I was gonna say, is dance is competitive dance on

940
00:48:15,960 --> 00:48:18,600
Speaker 1: a sport, But I guess that it's an artistry. Well,

941
00:48:18,640 --> 00:48:22,240
Speaker 1: according to this new report from the Lever, private equity

942
00:48:22,480 --> 00:48:25,880
Speaker 1: is taking over youth sports and as part of that takeover,

943
00:48:26,239 --> 00:48:29,640
Speaker 1: companies are even preventing parents from using their own cell

944
00:48:29,680 --> 00:48:32,719
Speaker 1: phones to record their own kids game so that they

945
00:48:32,719 --> 00:48:35,640
Speaker 1: can squeeze even more money out of these families.

946
00:48:36,000 --> 00:48:38,160
Speaker 3: This is you know what, This feels like a full

947
00:48:38,160 --> 00:48:42,359
Speaker 3: circle moment because the the like finance people that are

948
00:48:42,360 --> 00:48:45,399
Speaker 3: working for these private equity firms that are moving out

949
00:48:45,400 --> 00:48:47,399
Speaker 3: to those suburbs that are having kids, that are having

950
00:48:47,480 --> 00:48:49,200
Speaker 3: kids take place in these other are like take part

951
00:48:49,200 --> 00:48:53,879
Speaker 3: in these really competitive sports things or whatever. Great, now

952
00:48:53,920 --> 00:48:56,640
Speaker 3: you can't record your kid playing soccer because of the

953
00:48:56,680 --> 00:48:58,560
Speaker 3: thing that you used to I don't know, using the

954
00:48:58,560 --> 00:49:01,480
Speaker 3: machine that you were also in a I'm generalizing here.

955
00:49:01,480 --> 00:49:04,040
Speaker 3: I'm sure not all of these people are not part

956
00:49:04,080 --> 00:49:06,239
Speaker 3: of this is done. But I have an image in

957
00:49:06,280 --> 00:49:09,840
Speaker 3: my head of like the kind of couple that is

958
00:49:09,880 --> 00:49:13,120
Speaker 3: taking their kid to soccer practice, and this is happening,

959
00:49:13,160 --> 00:49:15,680
Speaker 3: and I feel like we're going in a loopier.

960
00:49:16,200 --> 00:49:19,480
Speaker 2: Yes, the machine, the hold the machine.

961
00:49:20,080 --> 00:49:24,320
Speaker 1: So as this forty billion with ab youth sports industry

962
00:49:24,400 --> 00:49:28,800
Speaker 1: is coming under private equity controlled corporate owned facilities and leagues,

963
00:49:28,920 --> 00:49:32,600
Speaker 1: from hockey rinks to cheer arenas, have started banning parents

964
00:49:32,640 --> 00:49:33,480
Speaker 1: from filming.

965
00:49:33,200 --> 00:49:35,640
Speaker 2: Their own children. What are they supposed to do instead?

966
00:49:35,760 --> 00:49:41,239
Speaker 1: Well, instead, parents are required to subscribe to exclusive, company

967
00:49:41,320 --> 00:49:44,879
Speaker 1: owned streaming services that can cost more per month than

968
00:49:45,040 --> 00:49:49,480
Speaker 1: actual streaming of actual professional sports. These private equity firms

969
00:49:49,520 --> 00:49:53,480
Speaker 1: also lock in exclusive contracts that block any competing video

970
00:49:53,640 --> 00:49:57,880
Speaker 1: services from being used. So when I first read this story,

971
00:49:57,920 --> 00:49:59,960
Speaker 1: I was like, these people have never met Melvin Toddsey.

972
00:50:00,560 --> 00:50:03,680
Speaker 1: In our town, my dad was like known for coming

973
00:50:03,719 --> 00:50:06,520
Speaker 1: onto the field during our like if I'm a very

974
00:50:06,520 --> 00:50:08,920
Speaker 1: particular memory of my brother of him coming onto the

975
00:50:08,960 --> 00:50:13,760
Speaker 1: field to like I think my brother was being unsportsmanlike

976
00:50:13,800 --> 00:50:15,880
Speaker 1: or something like. He was known in our town for

977
00:50:16,000 --> 00:50:18,719
Speaker 1: like coming onto the field during our games. So I

978
00:50:18,800 --> 00:50:21,280
Speaker 1: was like, oh, this would never fly with Melvin Tid Senior.

979
00:50:21,440 --> 00:50:23,600
Speaker 1: So I'm thinking, like, Okay, how are they gonna enforce this?

980
00:50:23,960 --> 00:50:25,840
Speaker 1: What are they really gonna do if parents are just like,

981
00:50:25,880 --> 00:50:27,200
Speaker 1: fuck you, I'm gonna record anyway.

982
00:50:27,600 --> 00:50:29,640
Speaker 2: Well, according to the lever, they.

983
00:50:29,560 --> 00:50:33,120
Speaker 1: Will confiscate parents' phones if they record anyway. Parents can

984
00:50:33,200 --> 00:50:36,080
Speaker 1: be blacklisted from attending their kids games and in some

985
00:50:36,120 --> 00:50:40,440
Speaker 1: cases the kids might face penalties if their parent is

986
00:50:40,440 --> 00:50:42,839
Speaker 1: like fuck you, I'm gonna record on my phone anyway.

987
00:50:43,120 --> 00:50:47,279
Speaker 1: This actually happened to a sitting US senator, Senator Chris

988
00:50:47,400 --> 00:50:51,279
Speaker 1: Murphy of Connecticut. He said, quote, I was told this

989
00:50:51,320 --> 00:50:53,400
Speaker 1: past weekend that if I had live streamed my child's

990
00:50:53,400 --> 00:50:56,279
Speaker 1: hockey game, my kids team would be pedalized and lose

991
00:50:56,320 --> 00:50:59,360
Speaker 1: a place in the standings. Why because a private equity

992
00:50:59,400 --> 00:51:01,240
Speaker 1: company has bought up the rinks.

993
00:51:01,520 --> 00:51:03,800
Speaker 2: Can you imagine this is giving?

994
00:51:03,880 --> 00:51:06,879
Speaker 3: Like black Beer episode, which I know is like every

995
00:51:06,880 --> 00:51:10,799
Speaker 3: episode of this podcast, but like, for real, this is giving.

996
00:51:10,520 --> 00:51:14,400
Speaker 2: Black Beer episode. Also like I'm sorry, I just want.

997
00:51:14,239 --> 00:51:16,200
Speaker 3: To go back to the fact that like parents' bones

998
00:51:16,239 --> 00:51:21,759
Speaker 3: can get confiscated, Like yeah, it feels like like are

999
00:51:21,800 --> 00:51:25,920
Speaker 3: we putting the parents in detention? Like what's going I

1000
00:51:25,960 --> 00:51:29,239
Speaker 3: feel like the state of the world right now is

1001
00:51:29,480 --> 00:51:32,520
Speaker 3: we are all stuck in like a bad eighties movie,

1002
00:51:32,760 --> 00:51:35,440
Speaker 3: and like the villains of the bad eighties movie are

1003
00:51:35,640 --> 00:51:37,680
Speaker 3: all of the people in charge. It's giving like the

1004
00:51:37,680 --> 00:51:39,960
Speaker 3: Breakfast Club, like the teacher from the Breakfast Club and

1005
00:51:40,000 --> 00:51:42,160
Speaker 3: being like like like that is who we're all under

1006
00:51:42,239 --> 00:51:45,040
Speaker 3: right now, being like no, you can't have your phones out,

1007
00:51:45,040 --> 00:51:47,840
Speaker 3: you can't be filming this, you can't be celebrating your kids.

1008
00:51:49,480 --> 00:51:52,360
Speaker 3: We need to stream this on.

1009
00:51:54,840 --> 00:51:59,960
Speaker 2: Youth Soccer Plus or whatever. Yeah.

1010
00:52:00,040 --> 00:52:04,560
Speaker 1: Yes, this story about the youth sports really shows what's

1011
00:52:04,600 --> 00:52:07,920
Speaker 1: that stick here? Like, do you want this private equity

1012
00:52:07,960 --> 00:52:11,000
Speaker 1: company to ban you as a parent from taking a

1013
00:52:11,080 --> 00:52:13,920
Speaker 1: video on your phone of your kids youth sports? But

1014
00:52:14,000 --> 00:52:16,360
Speaker 1: you already pay out the ass for them to be

1015
00:52:16,440 --> 00:52:19,160
Speaker 1: able to do not to mention, you're probably after we're

1016
00:52:19,200 --> 00:52:22,279
Speaker 1: probably at the drive them halfway across town.

1017
00:52:22,560 --> 00:52:23,520
Speaker 2: I don't even get me started.

1018
00:52:23,719 --> 00:52:25,799
Speaker 1: On top of that, do you want to have to

1019
00:52:25,840 --> 00:52:30,000
Speaker 1: be forced to pay for black Bear Sports Group TV

1020
00:52:30,239 --> 00:52:32,200
Speaker 1: package just to watch your kid play hockey?

1021
00:52:32,239 --> 00:52:34,160
Speaker 2: I don't think so so.

1022
00:52:34,600 --> 00:52:37,799
Speaker 1: Black Bear Sports Group is the largest private equity youth

1023
00:52:37,840 --> 00:52:41,560
Speaker 1: hockey organization in the United States. And basically, when asked

1024
00:52:41,600 --> 00:52:44,759
Speaker 1: by the lever about like this policy, why parents can't

1025
00:52:44,800 --> 00:52:47,200
Speaker 1: just record their own kids, they said it was because

1026
00:52:47,200 --> 00:52:51,240
Speaker 1: of quote significant safety risks like kids being filmed without

1027
00:52:51,280 --> 00:52:54,160
Speaker 1: their consent. But when the lever pressed them and was like, okay, well,

1028
00:52:54,560 --> 00:52:58,000
Speaker 1: why would parents be punished for recording their own kids

1029
00:52:58,040 --> 00:52:59,960
Speaker 1: if you're worried about the safety risk of kids being

1030
00:53:00,040 --> 00:53:01,040
Speaker 1: film without their consent.

1031
00:53:01,360 --> 00:53:04,040
Speaker 2: Lever was like, Uh, we don't really have an answer

1032
00:53:04,080 --> 00:53:06,120
Speaker 2: to that. No, no answer. They didn't have anything to say.

1033
00:53:06,560 --> 00:53:10,480
Speaker 1: So the black Bear streaming package service costs between twenty

1034
00:53:10,520 --> 00:53:13,960
Speaker 1: five dollars and fifty dollars a month, depending on the package,

1035
00:53:14,560 --> 00:53:17,240
Speaker 1: and they're also on top of that adding new fees

1036
00:53:17,280 --> 00:53:21,120
Speaker 1: like a fifty dollars registration and insurance charge, on top

1037
00:53:21,200 --> 00:53:24,320
Speaker 1: of the normal fees that parents already pay the USA

1038
00:53:24,400 --> 00:53:28,560
Speaker 1: Hockey membership and the already sky high cost of the equipment.

1039
00:53:28,920 --> 00:53:31,600
Speaker 1: It's the kind of price creep that makes hockey, which

1040
00:53:31,680 --> 00:53:35,720
Speaker 1: is already a very expensive and exclusionary sport, even less

1041
00:53:35,760 --> 00:53:39,200
Speaker 1: accessible for regular families who might want to participate.

1042
00:53:39,280 --> 00:53:42,880
Speaker 3: I have a question about so if they're worried about

1043
00:53:43,040 --> 00:53:46,880
Speaker 3: kids getting quote unquote filmed without their consent or whatever.

1044
00:53:48,880 --> 00:53:51,760
Speaker 3: But also, this is a streaming service you can pay for.

1045
00:53:51,880 --> 00:53:56,920
Speaker 3: What's stopping like randos from watching thing? Like I almost

1046
00:53:56,960 --> 00:54:01,120
Speaker 3: feel like having a parent fled your game and then

1047
00:54:01,200 --> 00:54:06,560
Speaker 3: posted on their Instagram, their private Instagram with like ninety followers.

1048
00:54:08,239 --> 00:54:10,680
Speaker 3: That seems more private to me than just having it

1049
00:54:10,719 --> 00:54:13,360
Speaker 3: out there and anybody who has fifty bucks can watch it.

1050
00:54:14,280 --> 00:54:17,920
Speaker 1: Oh, you think that sounds more private than black Bear TV,

1051
00:54:18,280 --> 00:54:21,320
Speaker 1: the streaming service that Black Bear recently launched.

1052
00:54:22,560 --> 00:54:25,600
Speaker 2: Just my opinion, and all I know, it's really out there.

1053
00:54:25,800 --> 00:54:28,800
Speaker 2: So basically, they through black Bear TV.

1054
00:54:29,239 --> 00:54:31,520
Speaker 1: Black Bear, this company that runs most of the youth

1055
00:54:31,520 --> 00:54:34,360
Speaker 1: hockey in the United States, is going to be exclusively

1056
00:54:35,000 --> 00:54:39,719
Speaker 1: streaming service for every league game. So basically they're like

1057
00:54:40,160 --> 00:54:44,960
Speaker 1: literally monetizing children as content while also extracting more money

1058
00:54:44,960 --> 00:54:47,439
Speaker 1: from the parrots who just want to watch their kids

1059
00:54:47,480 --> 00:54:49,799
Speaker 1: play the sports that they're paying tons and tons of

1060
00:54:49,800 --> 00:54:51,719
Speaker 1: money to sign their kid up for. And it is

1061
00:54:51,760 --> 00:54:55,280
Speaker 1: not just hockey. Varsity Brands, which is the dominant company

1062
00:54:55,280 --> 00:54:59,480
Speaker 1: and competitive cheer based a massive antitrust lawsuit accusing it

1063
00:54:59,520 --> 00:55:04,080
Speaker 1: of lacking competitors and forcing teams to buy only Varsity uniforms, equipment,

1064
00:55:04,120 --> 00:55:08,240
Speaker 1: and tournament access. The company, which no surprise to anybody,

1065
00:55:08,440 --> 00:55:11,800
Speaker 1: was also tangled up in a high profile sex abuse scandal,

1066
00:55:12,560 --> 00:55:15,400
Speaker 1: ended up settling a lawsuit for eighty two million dollars

1067
00:55:15,440 --> 00:55:17,759
Speaker 1: in twenty twenty four. Similar to Black Bear of a

1068
00:55:17,800 --> 00:55:22,360
Speaker 1: hockey company, Varsity also owns Varsity TV, the exclusive streeting

1069
00:55:22,360 --> 00:55:27,080
Speaker 1: platform for cheerleading competitions and if folks watched that docuseriies

1070
00:55:27,120 --> 00:55:32,360
Speaker 1: on Netflix Cheer. They shut the Netflix crew out because

1071
00:55:32,400 --> 00:55:34,759
Speaker 1: the venue was theirs and they were like, no, we

1072
00:55:34,880 --> 00:55:37,960
Speaker 1: have the exclusive filming rights here. So it's just this

1073
00:55:38,040 --> 00:55:43,000
Speaker 1: grotesque situation where these private equity companies are just finding

1074
00:55:43,160 --> 00:55:46,799
Speaker 1: every little coin, every little dollar they can extract from

1075
00:55:46,880 --> 00:55:49,520
Speaker 1: these families who just want to have their kid play

1076
00:55:49,600 --> 00:55:51,680
Speaker 1: basketball or cheer or do hockey.

1077
00:55:52,880 --> 00:55:58,640
Speaker 2: Yeah, this is this is insane. Also, it's kids sports.

1078
00:55:59,239 --> 00:56:01,680
Speaker 3: I am thinking back now too because I do remember so,

1079
00:56:02,120 --> 00:56:05,240
Speaker 3: Like again, I was a competitive dancer. I do remember,

1080
00:56:05,320 --> 00:56:08,680
Speaker 3: so they wouldn't let parents film are when we would

1081
00:56:08,680 --> 00:56:11,120
Speaker 3: have our big like end of the year showcase where

1082
00:56:11,120 --> 00:56:14,160
Speaker 3: we would have like every like recital, they wouldn't let

1083
00:56:14,239 --> 00:56:17,560
Speaker 3: parents film there, but they would like sell DVDs that

1084
00:56:17,640 --> 00:56:20,600
Speaker 3: were like professional shop, which like that. It was one

1085
00:56:20,800 --> 00:56:23,080
Speaker 3: thing though, it was one thing every year, and it

1086
00:56:23,120 --> 00:56:26,840
Speaker 3: was like these dance studios selling these cvds and the

1087
00:56:26,840 --> 00:56:28,919
Speaker 3: money was going back to them. It wasn't like some

1088
00:56:29,200 --> 00:56:31,480
Speaker 3: big private equity company.

1089
00:56:34,120 --> 00:56:34,920
Speaker 2: Dah is weird.

1090
00:56:35,120 --> 00:56:37,600
Speaker 3: This is a weird, bleak, dark story.

1091
00:56:37,640 --> 00:56:40,399
Speaker 1: It is, and I think anything in evolving because it's

1092
00:56:40,400 --> 00:56:43,879
Speaker 1: not just sports, it's it's youth sports, right, Like, Yeah,

1093
00:56:44,760 --> 00:56:48,000
Speaker 1: when something is involving your kids, it's emotional. It's highly

1094
00:56:48,040 --> 00:56:53,280
Speaker 1: monetizable environments where parents probably feel pressure to pay anything

1095
00:56:53,320 --> 00:56:54,280
Speaker 1: to support their kids.

1096
00:56:54,600 --> 00:56:55,480
Speaker 2: You know, you've.

1097
00:56:55,280 --> 00:57:01,040
Speaker 1: Got miners being used as content by corporations revenue streams.

1098
00:57:01,280 --> 00:57:04,000
Speaker 1: It's just it's not just that these companies are squeezing

1099
00:57:04,040 --> 00:57:07,759
Speaker 1: these families financially, which they are. They are also reshaping

1100
00:57:08,200 --> 00:57:12,799
Speaker 1: youth activities and youth sports into these paywalled digital products

1101
00:57:12,840 --> 00:57:16,920
Speaker 1: and content, one penalty and subscription at a time. And

1102
00:57:16,960 --> 00:57:19,200
Speaker 1: I just think, like, we have to have spaces that

1103
00:57:19,280 --> 00:57:21,120
Speaker 1: are just for joy.

1104
00:57:21,000 --> 00:57:23,640
Speaker 2: And youth and community and childhood.

1105
00:57:23,640 --> 00:57:27,320
Speaker 1: If those spaces just get turned into another place of

1106
00:57:27,640 --> 00:57:32,360
Speaker 1: copyright policing and predatory monetization and extraction, but what do

1107
00:57:32,400 --> 00:57:34,200
Speaker 1: we have, Like what is all of this for If

1108
00:57:34,240 --> 00:57:36,560
Speaker 1: you can't even get a grainy video of your kid

1109
00:57:36,680 --> 00:57:39,240
Speaker 1: doing something cool and hockey and post it on your

1110
00:57:39,240 --> 00:57:41,120
Speaker 1: Facebook for your mother in law to.

1111
00:57:41,160 --> 00:57:43,200
Speaker 2: Be like, oh, they look so great, what is this for?

1112
00:57:43,560 --> 00:57:43,680
Speaker 3: Right?

1113
00:57:43,800 --> 00:57:49,120
Speaker 1: Like, not every space needs to be extracted for every

1114
00:57:49,160 --> 00:57:52,200
Speaker 1: single resource in this way, especially when it involves you.

1115
00:57:52,320 --> 00:57:53,920
Speaker 2: It's just it's you're so right, It's just like a

1116
00:57:54,080 --> 00:57:56,520
Speaker 2: very bleak story how did.

1117
00:57:56,360 --> 00:57:59,360
Speaker 3: We get from like, again, I'm not a sports person,

1118
00:57:59,480 --> 00:58:01,320
Speaker 3: so i've this is not I'm not going to give

1119
00:58:01,360 --> 00:58:03,840
Speaker 3: the most detailed description of this, but whenever I remember

1120
00:58:03,880 --> 00:58:06,840
Speaker 3: hearing the debate about like should college athletes be paid

1121
00:58:07,440 --> 00:58:10,120
Speaker 3: for because of the fact that we're broadcasting these games,

1122
00:58:10,160 --> 00:58:10,840
Speaker 3: they are like.

1123
00:58:12,280 --> 00:58:13,520
Speaker 2: They're big money makers.

1124
00:58:13,560 --> 00:58:15,120
Speaker 3: People are coming in to pay and see these games

1125
00:58:15,200 --> 00:58:17,720
Speaker 3: or whatever. How do we get from that conversation of like,

1126
00:58:17,720 --> 00:58:20,400
Speaker 3: should these like again, also still at this point usually

1127
00:58:20,440 --> 00:58:24,720
Speaker 3: like sometimes teenagers, sometimes twenty twenty one year olds still

1128
00:58:24,720 --> 00:58:25,240
Speaker 3: pretty young?

1129
00:58:25,400 --> 00:58:26,680
Speaker 2: Should they be paid for this?

1130
00:58:26,800 --> 00:58:31,000
Speaker 3: Like labor they're putting in that can be very dangerous,

1131
00:58:31,040 --> 00:58:33,040
Speaker 3: by the way, how do we get from that to

1132
00:58:34,680 --> 00:58:39,920
Speaker 3: your five year old playing soccer that is streamable content?

1133
00:58:40,680 --> 00:58:40,960
Speaker 2: Yes?

1134
00:58:42,240 --> 00:58:45,240
Speaker 3: Okay, sure should we Like, if you're gonna do that,

1135
00:58:45,360 --> 00:58:49,720
Speaker 3: then start paying the kids that you're making content. I

1136
00:58:49,720 --> 00:58:54,080
Speaker 3: don't know, it's it's so yeah, this is such a

1137
00:58:54,880 --> 00:58:56,560
Speaker 3: I get I can't. I The only thing I can

1138
00:58:56,640 --> 00:58:58,040
Speaker 3: keep going back to was just beking like this is

1139
00:58:58,080 --> 00:59:01,160
Speaker 3: such a bleak outlook like, so, what is the topenic

1140
00:59:01,280 --> 00:59:02,040
Speaker 3: to our world?

1141
00:59:02,720 --> 00:59:03,920
Speaker 2: Very bleak stuff?

1142
00:59:04,120 --> 00:59:07,440
Speaker 1: Okay, Well, the company that runs the youth hockey in

1143
00:59:07,480 --> 00:59:11,439
Speaker 1: the States is black bear. And speaking of bears, hey

1144
00:59:11,480 --> 00:59:16,400
Speaker 1: don't buy this AI bondage teddy bear for your kid

1145
00:59:16,560 --> 00:59:19,240
Speaker 1: for the holidays, or actually, I don't know, maybe do

1146
00:59:19,440 --> 00:59:21,360
Speaker 1: depending on your kid. I don't know what your kid's into.

1147
00:59:21,720 --> 00:59:23,520
Speaker 1: If you live in DC like I do, and you,

1148
00:59:23,720 --> 00:59:25,720
Speaker 1: like are the kind of person who celebrates the holidays

1149
00:59:25,720 --> 00:59:30,240
Speaker 1: at our local leather and kinkbar, the District Eagle, maybe

1150
00:59:30,240 --> 00:59:31,320
Speaker 1: this is a good choice for you.

1151
00:59:31,600 --> 00:59:33,840
Speaker 3: I was gonna say when I saw the headline and

1152
00:59:33,880 --> 00:59:35,959
Speaker 3: that or that the outline you sent me, I saw

1153
00:59:36,120 --> 00:59:38,600
Speaker 3: the words AI fetish bear, and I thought this was

1154
00:59:38,640 --> 00:59:40,240
Speaker 3: going in a very different direction.

1155
00:59:42,200 --> 00:59:45,760
Speaker 2: I wish.

1156
00:59:45,280 --> 00:59:50,760
Speaker 1: Okay, So here's what's going on. Researchers at the Public

1157
00:59:50,840 --> 00:59:54,720
Speaker 1: Interest Research Group found that an AI powered teddy bear

1158
00:59:54,800 --> 00:59:59,880
Speaker 1: from the children's toymaker Folow Toy was giving kids instructions

1159
00:59:59,880 --> 01:00:03,320
Speaker 1: on how to do things like light matches, engage in

1160
01:00:03,440 --> 01:00:07,160
Speaker 1: knife play, and even information about sexual fetishes.

1161
01:00:07,840 --> 01:00:10,840
Speaker 3: Wait wait, wait, engage a knife plays separate from the

1162
01:00:10,880 --> 01:00:15,120
Speaker 3: sexual fetages or the late to the fetish really okay, Yeah,

1163
01:00:15,240 --> 01:00:15,720
Speaker 3: it was like.

1164
01:00:15,960 --> 01:00:19,480
Speaker 1: First of all, nice to meet you, Timmy, go grab

1165
01:00:19,520 --> 01:00:20,160
Speaker 1: a knife.

1166
01:00:20,440 --> 01:00:22,680
Speaker 2: Second of all, what are your cakes?

1167
01:00:22,920 --> 01:00:23,040
Speaker 3: All?

1168
01:00:23,120 --> 01:00:24,439
Speaker 2: Right? Back in my day.

1169
01:00:25,440 --> 01:00:28,480
Speaker 3: Back in my day, we would I you learn all

1170
01:00:28,480 --> 01:00:31,040
Speaker 3: this from being on tumbler at too young of an

1171
01:00:31,080 --> 01:00:32,840
Speaker 3: age or on omegle or whatever.

1172
01:00:33,640 --> 01:00:40,280
Speaker 2: Uh but uh whoa just wow? All right? Sure?

1173
01:00:40,440 --> 01:00:45,800
Speaker 1: Yeah, so this awesome bear was using open ais chat

1174
01:00:45,800 --> 01:00:49,080
Speaker 1: shept four model. But after the Public Interest Research Group

1175
01:00:49,160 --> 01:00:52,320
Speaker 1: tested three different AI toys, they found that these toys

1176
01:00:52,320 --> 01:00:57,360
Speaker 1: can quickly veer into pretty not safer kids territory, giving

1177
01:00:57,360 --> 01:01:00,760
Speaker 1: advice on sex positions, fetishes, I had to find knives

1178
01:01:00,760 --> 01:01:03,200
Speaker 1: in the kitchen, how to start fires with matches. Open

1179
01:01:03,240 --> 01:01:06,200
Speaker 1: ai then pulled the plug on follow toy, suspending the

1180
01:01:06,240 --> 01:01:10,000
Speaker 1: company's access with AI models. An Open AI spokesperson told

1181
01:01:10,080 --> 01:01:13,040
Speaker 1: the research group, I can confirm that you've suspended this

1182
01:01:13,080 --> 01:01:15,320
Speaker 1: developer for violating our policies.

1183
01:01:15,520 --> 01:01:17,800
Speaker 2: I'm sorry, is this toy? Is this Megan?

1184
01:01:18,760 --> 01:01:19,000
Speaker 4: Is this?

1185
01:01:19,040 --> 01:01:19,520
Speaker 2: Oh my god?

1186
01:01:19,840 --> 01:01:22,800
Speaker 1: I'll related. I watched Megan two on the plane. So

1187
01:01:22,800 --> 01:01:24,680
Speaker 1: I saw Megan one in the theater and I fucking

1188
01:01:24,720 --> 01:01:26,800
Speaker 1: loved it. I finally saw Megan two on the plane

1189
01:01:26,840 --> 01:01:28,200
Speaker 1: to Barcelona. Have you seen it?

1190
01:01:28,280 --> 01:01:31,640
Speaker 2: I actually haven't seen either of them. Oh my god,

1191
01:01:31,320 --> 01:01:35,400
Speaker 2: I need to watch them. I've seen many of the memes.

1192
01:01:35,440 --> 01:01:39,480
Speaker 3: I've seen many, many many like and Halloween goshuomes so.

1193
01:01:39,800 --> 01:01:45,720
Speaker 1: My gosh, Meghan one. I absolutely loved Meghan two. I

1194
01:01:45,760 --> 01:01:49,120
Speaker 1: will say like it. I kept saying so Mike, producer.

1195
01:01:49,120 --> 01:01:50,680
Speaker 1: Mike was sitting next to me on the plane to Barcelona,

1196
01:01:50,720 --> 01:01:52,480
Speaker 1: and I was I kept being like, this is a

1197
01:01:52,600 --> 01:01:55,160
Speaker 1: movie for Tangoti listeners.

1198
01:01:54,800 --> 01:01:56,520
Speaker 2: And that's okay. Sometimes you.

1199
01:01:59,200 --> 01:01:59,680
Speaker 4: Should say, I.

1200
01:01:59,640 --> 01:02:01,680
Speaker 2: Would be very curious for your thoughts. They've been watching it.

1201
01:02:01,680 --> 01:02:04,120
Speaker 3: I'll watch it sometime soon and let you know my thoughts.

1202
01:02:04,120 --> 01:02:07,520
Speaker 3: Per shit, because I I am curious also how this is,

1203
01:02:07,520 --> 01:02:10,680
Speaker 3: because you know, I love like ex Machina and like.

1204
01:02:12,680 --> 01:02:18,680
Speaker 2: I love that genre movie, so I'm very curious. Also

1205
01:02:18,720 --> 01:02:19,800
Speaker 2: Alison Williams, so.

1206
01:02:19,920 --> 01:02:23,800
Speaker 1: You know, yeah, she's really I think this is her

1207
01:02:24,120 --> 01:02:25,440
Speaker 1: best movie since get Out.

1208
01:02:25,640 --> 01:02:28,840
Speaker 3: Oh absolutely, I actually so the first time I saw

1209
01:02:28,880 --> 01:02:30,920
Speaker 3: her and something was get Out. So going back and

1210
01:02:30,960 --> 01:02:34,120
Speaker 3: watching I had like my experience watching Girls was having

1211
01:02:34,120 --> 01:02:37,400
Speaker 3: seen Alison Williams can get Out, Adam Driver, and Star Wars.

1212
01:02:37,640 --> 01:02:40,280
Speaker 3: Actually I think those were the main two. But like

1213
01:02:40,360 --> 01:02:42,600
Speaker 3: watching it that it was like weird to be like, no,

1214
01:02:42,720 --> 01:02:44,600
Speaker 3: I know you for the role that like because of

1215
01:02:44,600 --> 01:02:47,840
Speaker 3: this show you got cast in and I can see why.

1216
01:02:49,440 --> 01:02:51,919
Speaker 3: But I this isn't right. I feel like I should. Yeah.

1217
01:02:52,000 --> 01:02:55,200
Speaker 1: Yeah, that's so coody showy to be like, I know,

1218
01:02:55,320 --> 01:02:56,760
Speaker 1: I don't know you from Girls.

1219
01:02:56,920 --> 01:02:58,440
Speaker 2: I know, I know Star Wars.

1220
01:02:58,800 --> 01:03:05,760
Speaker 3: Yeah, come on yeah yeah. Anyways, back to this bear,

1221
01:03:06,720 --> 01:03:11,959
Speaker 3: Teddy Bears teaching kids about knife play. Yeah nice play

1222
01:03:12,040 --> 01:03:14,040
Speaker 3: bear actually voice by Adam Driver.

1223
01:03:14,360 --> 01:03:14,840
Speaker 2: Oh my god.

1224
01:03:14,880 --> 01:03:18,080
Speaker 1: No, Now that's a toy that would be the hottest

1225
01:03:18,080 --> 01:03:19,280
Speaker 1: toy of the holiday season.

1226
01:03:19,720 --> 01:03:21,240
Speaker 2: Yeah. I don't know if kids would be buying that,

1227
01:03:22,440 --> 01:03:24,360
Speaker 2: I would buy it. I would need that.

1228
01:03:25,600 --> 01:03:29,600
Speaker 1: So open Ai was like, we can't have these bears

1229
01:03:30,040 --> 01:03:32,440
Speaker 1: telling kids to like do spetishes and play with knives.

1230
01:03:32,440 --> 01:03:34,800
Speaker 1: So they were like, we kicked this company off of

1231
01:03:34,840 --> 01:03:38,880
Speaker 1: our platform. But it seems like that move might put

1232
01:03:38,960 --> 01:03:42,280
Speaker 1: more pressure on open Ai to police how their products

1233
01:03:42,280 --> 01:03:45,800
Speaker 1: are used, especially as it is trying to partner with

1234
01:03:45,920 --> 01:03:49,040
Speaker 1: other kids toy companies like Mattel, which had started a

1235
01:03:49,080 --> 01:03:52,040
Speaker 1: partnership with I think earlier this year. But here's really

1236
01:03:52,120 --> 01:03:56,800
Speaker 1: the Kickerer. Other chat GPT powered toys are still very

1237
01:03:56,840 --> 01:03:59,280
Speaker 1: much available on Amazon, So if you're looking for a

1238
01:03:59,360 --> 01:04:05,480
Speaker 1: memorable and potentially horrifying holiday gift, well Amazon has you covered.

1239
01:04:05,840 --> 01:04:06,160
Speaker 2: You know what.

1240
01:04:06,240 --> 01:04:09,360
Speaker 3: Actually, I was just talking to all right, our friend

1241
01:04:09,360 --> 01:04:11,040
Speaker 3: who was trying to get me to watch the movie Chucky,

1242
01:04:11,120 --> 01:04:13,800
Speaker 3: and I was like, I was terrified of Chucky when

1243
01:04:13,800 --> 01:04:16,320
Speaker 3: I was a kid. I refuse that, is, like I

1244
01:04:16,320 --> 01:04:18,320
Speaker 3: because I am I'm somebody I was scared of horror

1245
01:04:18,360 --> 01:04:19,680
Speaker 3: movies when I was a kid, and now I'm making

1246
01:04:19,680 --> 01:04:20,960
Speaker 3: my way through all of them. But I'm like, that's

1247
01:04:21,000 --> 01:04:24,360
Speaker 3: one of the ones that I absolutely refuse. My cousins

1248
01:04:24,400 --> 01:04:26,600
Speaker 3: were obsessed with it and they used to like terrorize

1249
01:04:26,600 --> 01:04:28,840
Speaker 3: me with it, and I know, I was like, it's

1250
01:04:28,920 --> 01:04:31,920
Speaker 3: so scary. I was like this, this, this sounds like

1251
01:04:31,960 --> 01:04:34,520
Speaker 3: my worst nightmare when I was like eight years old.

1252
01:04:34,720 --> 01:04:36,960
Speaker 2: Yon, just the weird grossness of it all.

1253
01:04:37,080 --> 01:04:42,160
Speaker 3: I'm like, I child me would be absolutely terrified by

1254
01:04:42,360 --> 01:04:43,760
Speaker 3: any of this.

1255
01:04:43,760 --> 01:04:47,200
Speaker 2: This is nightmare of fuel. Like, come on, I also

1256
01:04:47,600 --> 01:04:49,000
Speaker 2: had a thing with Chucky.

1257
01:04:49,040 --> 01:04:52,320
Speaker 1: My brother was obsessed with Chucky, and I was terrified

1258
01:04:52,360 --> 01:04:54,080
Speaker 1: of Chucky.

1259
01:04:54,400 --> 01:04:56,680
Speaker 2: I was really good, yeah, and I.

1260
01:04:57,240 --> 01:05:00,920
Speaker 1: Like horror movies and I could not handle Chucky. Really

1261
01:05:01,000 --> 01:05:03,840
Speaker 1: anything where it's like you might be too young. Did

1262
01:05:03,880 --> 01:05:06,640
Speaker 1: you ever watch the puppet Master movies, anything where it's

1263
01:05:06,680 --> 01:05:09,040
Speaker 1: like little dolls or little toys come to life.

1264
01:05:09,120 --> 01:05:12,680
Speaker 2: I don't like that. That's too scary. No, yeah, I was.

1265
01:05:12,800 --> 01:05:15,640
Speaker 3: I did recently. This might have been like a year ago,

1266
01:05:15,680 --> 01:05:16,440
Speaker 3: actually not recently.

1267
01:05:16,480 --> 01:05:16,760
Speaker 2: Whatever.

1268
01:05:17,880 --> 01:05:19,560
Speaker 3: A year ago, I was making your way through all

1269
01:05:19,600 --> 01:05:22,760
Speaker 3: the conjuring movies and I skipped Annabelle because I was like,

1270
01:05:22,960 --> 01:05:26,280
Speaker 3: I can't anyway anytime, it's like a doll.

1271
01:05:28,600 --> 01:05:31,120
Speaker 2: No, I just know just I don't want to do.

1272
01:05:31,200 --> 01:05:33,360
Speaker 2: I don't want to think about that. That's too much

1273
01:05:33,360 --> 01:05:35,560
Speaker 2: for me. I don't know what it is about having.

1274
01:05:35,800 --> 01:05:38,400
Speaker 3: Dolls come into life that is too scary for me.

1275
01:05:38,480 --> 01:05:39,400
Speaker 2: It keeps out away.

1276
01:05:39,640 --> 01:05:39,920
Speaker 4: Uh huh.

1277
01:05:41,080 --> 01:05:43,560
Speaker 1: Well, if you're looking for a holiday gift for Joey

1278
01:05:43,640 --> 01:05:47,600
Speaker 1: or myself, maybe pick something else. We don't like the

1279
01:05:48,040 --> 01:05:51,600
Speaker 1: dolls that could potentially come to life. I'm okay with

1280
01:05:51,640 --> 01:05:54,920
Speaker 1: the fetish talk for adults, not necessarily in a bear

1281
01:05:54,960 --> 01:05:58,600
Speaker 1: for kids, but let's just steer clear of the creepy,

1282
01:05:59,080 --> 01:06:02,040
Speaker 1: fucked up doll all genre altogether.

1283
01:06:03,240 --> 01:06:06,000
Speaker 3: I'm trying to think of like a a way there

1284
01:06:06,000 --> 01:06:07,880
Speaker 3: could be like a positive like any way I can

1285
01:06:07,920 --> 01:06:11,600
Speaker 3: think of like a fetish AI thing for adults that

1286
01:06:11,720 --> 01:06:15,880
Speaker 3: also doesn't end well though, too. That's maybe we should

1287
01:06:15,920 --> 01:06:18,840
Speaker 3: just keep Ai out of this, you know, yeah, crazy,

1288
01:06:18,840 --> 01:06:21,880
Speaker 3: crazy concept, But you've ever seen any horror movie.

1289
01:06:22,000 --> 01:06:24,400
Speaker 1: I think the takeaway is, let's just keep Ai out

1290
01:06:24,400 --> 01:06:28,440
Speaker 1: of this. How much ever seen Terminator?

1291
01:06:28,520 --> 01:06:29,160
Speaker 2: Oh my god?

1292
01:06:29,680 --> 01:06:34,240
Speaker 3: Literally the Space Audits Space Odyssey. I was about to

1293
01:06:34,280 --> 01:06:35,960
Speaker 3: say Space Audity and then I was like, that's the

1294
01:06:36,000 --> 01:06:39,840
Speaker 3: song that's not confused as well? Yeah, yeah, I was.

1295
01:06:39,960 --> 01:06:43,479
Speaker 3: I was trying to argue with me because my dad

1296
01:06:43,640 --> 01:06:46,720
Speaker 3: uses chow GBC and I was like, I remember being

1297
01:06:46,800 --> 01:06:49,240
Speaker 3: like sixteen, You're making me watch this movie and me

1298
01:06:49,320 --> 01:06:50,720
Speaker 3: being like, this is really long.

1299
01:06:50,840 --> 01:06:51,680
Speaker 2: I don't like it.

1300
01:06:51,720 --> 01:06:55,720
Speaker 3: But I'm like, did you not take away the message

1301
01:06:55,760 --> 01:06:58,320
Speaker 3: from the movie that you made me watch?

1302
01:06:58,600 --> 01:06:59,120
Speaker 2: I don't know.

1303
01:06:59,600 --> 01:07:01,800
Speaker 1: Sounds like somebody needs to go back and rewatch it

1304
01:07:01,880 --> 01:07:04,400
Speaker 1: and get a crash course into what hell is really

1305
01:07:04,440 --> 01:07:04,960
Speaker 1: capable of?

1306
01:07:05,280 --> 01:07:07,320
Speaker 2: Hibe holl and Meghan can do a team up, you know,

1307
01:07:07,760 --> 01:07:09,840
Speaker 2: oh now that I will watch.

1308
01:07:09,840 --> 01:07:11,800
Speaker 3: Here we go see I'm in I'm in LA for

1309
01:07:11,880 --> 01:07:16,640
Speaker 3: one day and I'm like next Blockbuster hal versus Megan.

1310
01:07:16,960 --> 01:07:18,520
Speaker 2: Let's for your consideration.

1311
01:07:19,120 --> 01:07:25,560
Speaker 1: Joey, Thank you, Joey, thank you so much for running

1312
01:07:25,600 --> 01:07:29,520
Speaker 1: down these stories for me. Where can people keep an

1313
01:07:29,520 --> 01:07:34,080
Speaker 1: eye on you if you don't become Hollywood's next big thing.

1314
01:07:34,520 --> 01:07:35,840
Speaker 2: Where can folks keep an eye on you?

1315
01:07:36,080 --> 01:07:40,800
Speaker 3: Yes, well, of course look for my future film hal

1316
01:07:40,920 --> 01:07:46,400
Speaker 3: Versus Megan Uh coming out to theaters near you, or

1317
01:07:46,440 --> 01:07:50,960
Speaker 3: are actually Joey Plus streaming service my my streaming stories.

1318
01:07:50,960 --> 01:07:52,760
Speaker 3: You have to give me fifty dollars a month to

1319
01:07:53,440 --> 01:07:56,280
Speaker 3: watch these amazing movies that I'm definitely making.

1320
01:07:59,240 --> 01:08:03,000
Speaker 2: That's pretty, that's good, I think. Yeah, I might be

1321
01:08:03,040 --> 01:08:04,160
Speaker 2: honest something here, let's see.

1322
01:08:05,040 --> 01:08:08,680
Speaker 3: But you can follow me on Instagram at Pat not Pratt.

1323
01:08:08,680 --> 01:08:11,920
Speaker 3: That is Patt n ot p r A T t uh.

1324
01:08:12,080 --> 01:08:15,040
Speaker 3: That's also my Twitter handle and my Blue Sky and

1325
01:08:15,120 --> 01:08:19,439
Speaker 3: other various other platforms. But I really only use Instagram currently.

1326
01:08:20,800 --> 01:08:24,160
Speaker 3: And yeah, you can also listen to some of my

1327
01:08:24,200 --> 01:08:26,360
Speaker 3: work on the show Stuff Mom Never Told You. I

1328
01:08:26,439 --> 01:08:29,760
Speaker 3: recently did an episode talking about the Mom Donnie Win

1329
01:08:30,240 --> 01:08:33,960
Speaker 3: in uh New York City, Bridget, I think you got

1330
01:08:33,960 --> 01:08:35,920
Speaker 3: to mention that from being the first I got a

1331
01:08:35,920 --> 01:08:36,839
Speaker 3: bunch of different text.

1332
01:08:36,640 --> 01:08:38,680
Speaker 2: From people out of we were talking about. However, it

1333
01:08:38,800 --> 01:08:40,120
Speaker 2: was sort of like people.

1334
01:08:39,880 --> 01:08:41,720
Speaker 3: Outside of New York were celebrating this year, and I

1335
01:08:41,800 --> 01:08:44,760
Speaker 3: was like, the first text at was just Bridget and

1336
01:08:44,880 --> 01:08:49,000
Speaker 3: all cats sending me mom Donnie, I was like, yeah,

1337
01:08:50,439 --> 01:08:51,080
Speaker 3: he does.

1338
01:08:52,560 --> 01:08:53,680
Speaker 2: Be and excited.

1339
01:08:54,200 --> 01:08:57,760
Speaker 3: It's okay me too. I watched that election come in

1340
01:08:58,120 --> 01:09:00,120
Speaker 3: at a at a gay bar near me and that

1341
01:09:00,320 --> 01:09:04,080
Speaker 3: was the beautiful moment. That was a really really great moment.

1342
01:09:04,120 --> 01:09:06,080
Speaker 3: But if you want to hear about that, yeah, listen

1343
01:09:06,120 --> 01:09:08,280
Speaker 3: to the stuff fun and virtual du. I also work

1344
01:09:08,320 --> 01:09:15,320
Speaker 3: on the show Outlaws Ks Madison and the show Afterlives,

1345
01:09:15,840 --> 01:09:18,880
Speaker 3: which is out wherever you get your podcasts, signal orwer

1346
01:09:19,280 --> 01:09:23,439
Speaker 3: winner and speaking of signal orders, also the show Black Fifa,

1347
01:09:23,520 --> 01:09:24,960
Speaker 3: which is also on the Outspoken Network.

1348
01:09:25,040 --> 01:09:28,360
Speaker 1: So yeah, well, thank you for being here, Joey, and

1349
01:09:28,400 --> 01:09:30,040
Speaker 1: thanks to all of you for listening. I will see

1350
01:09:30,040 --> 01:09:37,439
Speaker 1: you on the Internet. Got a story about an interesting

1351
01:09:37,479 --> 01:09:39,519
Speaker 1: thing in tech. I just want to say hi, you

1352
01:09:39,520 --> 01:09:41,800
Speaker 1: can We just had hello at tengodi dot com. You

1353
01:09:41,840 --> 01:09:44,880
Speaker 1: can also find transcripts for today's episode at tengody dot com.

1354
01:09:45,040 --> 01:09:46,720
Speaker 1: There Are No Girls on the Internet was created by

1355
01:09:46,720 --> 01:09:49,679
Speaker 1: me Bridget Todd. It's a production of iHeartRadio, an Unboss

1356
01:09:49,720 --> 01:09:53,360
Speaker 1: creative Jonathan Strickland as our executive producer. Tarry Harrison is

1357
01:09:53,400 --> 01:09:57,000
Speaker 1: our producer and sound engineer. Michael Almada is our contributing producer,

1358
01:09:57,479 --> 01:10:01,320
Speaker 1: Edited by Joey pat I'm your host, Bridget If you

1359
01:10:01,360 --> 01:10:03,080
Speaker 1: want to help us grow, rate and review.

1360
01:10:02,920 --> 01:10:04,000
Speaker 4: Us on Apple Podcasts.

1361
01:10:04,720 --> 01:10:07,519
Speaker 1: For more podcasts from iHeartRadio, check out the iHeartRadio app,

1362
01:10:07,560 --> 01:10:09,600
Speaker 1: Apple Podcasts, or wherever you get your podcasts.