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

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

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

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Speaker 1: There Are No Girls on the Internet for weeks for

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Speaker 1: the intersection with Technology, culture, social media and identity. And

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Speaker 1: this is another installment of our weekly news roundup where

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Speaker 1: we talk through all the stories you may have missed

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

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Speaker 2: I am so.

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Speaker 1: Excited because in the guest co host chair we have

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Speaker 1: my amazing producer, Joey.

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Speaker 2: Joey, Welcome back to the show.

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Speaker 3: It has been too long, hey, Bridget, thanks for having

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Speaker 3: me back officially in twenty twenty six. Now, I think

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Speaker 3: the last time I was on Mike, we were kind

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Speaker 3: of fake in twenty twenty six. We recorded in twenty

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Speaker 3: twenty five, and we're pretending it was twenty twenty six,

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Speaker 3: but now it's actually twenty twenty six.

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Speaker 2: Also, shout out to everybody who commented.

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Speaker 3: On the mail Bag episode that my predictions were right

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Speaker 3: about world ending the first week of now as the helicopter,

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Speaker 3: as the helicopter with Maduro was going over my apartment,

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Speaker 3: I don't know. We're both in Brooklyn right now. Actually

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Speaker 3: he apparently is.

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Speaker 1: It true that Maduro, Luigi and Diddy are all in

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Speaker 1: the same Brooklyn facility?

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Speaker 2: I read that so mohere. I don't know if that's true.

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Speaker 2: I might need to fact check that, yes, allegedly. I'll

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Speaker 2: be real.

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Speaker 3: All of my information about this comes from if anybody's

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Speaker 3: seen the like meme that's going around where they've put

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Speaker 3: all of the people that are allegedly I'm saying allegedly

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Speaker 3: because I just need to double check whether they actually

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Speaker 3: are in the jail or not. But I'm assuming they

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Speaker 3: all are, but the meme of all of them and

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Speaker 3: then people are putting like Arkham Asylum inmates and like

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Speaker 3: pairing them up and being like the I don't know,

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Speaker 3: Maduro's the joker, and I like, was Gallayne Maxwell as Cawwoman?

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Speaker 3: Like I was like, okay, first of all, like no

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Speaker 3: love cow woman, this is not it. But I was like,

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Speaker 3: that's kind of funny, and like the context of like yeah,

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Speaker 3: the one woman, sure, uh but yeah, but that is

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Speaker 3: I I this is mom Donnie's New York City. Arkham

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Speaker 3: Asylum is here and there the subway prices are just

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Speaker 3: going up. Obviously, all his fault. He's done all of

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Speaker 3: this in the first two weeks of January. It has

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Speaker 3: nothing to do with any of the previous administrations in

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Speaker 3: the city or the.

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Speaker 2: National government or whatever. I will say.

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Speaker 1: I saw something I liked, fighting for public toilets. I

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Speaker 1: am one of those people where whenever I'm out, especially

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Speaker 1: if I'm going shopping, I always need a bathroom. So

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Speaker 1: it is very difficult to find public toilets in DC,

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Speaker 1: similarly difficult in New York.

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Speaker 2: I like that. That was one of his first initiatives

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Speaker 2: as somebody no same, Yeah, I have made.

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Speaker 3: Up so many insane like stories to try and get

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Speaker 3: into random bathrooms in New York City.

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Speaker 2: There's been so many hotels that I've been like.

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Speaker 3: Yeah, I know, my dad's staying here. I'm like, definitely

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Speaker 3: a college student. That's I don't know, please let me

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Speaker 3: use the bathroom.

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Speaker 2: Then you're building. But yeah, no, I'm very glad about that. So, Joey,

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Speaker 2: have you followed what's been going on with GROC. I

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Speaker 2: don't know that. I don't know that you. I don't

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Speaker 2: know if you're on Twitter like that anymore. But how

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Speaker 2: do you see what Grock's up to?

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Speaker 3: I have I've seen bits and pieces. I have deleted

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Speaker 3: the Twitter app off of my phone. I still every

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Speaker 3: once in a while will log onto my computer and

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Speaker 3: be on it for about ten seconds before I'm like,

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Speaker 3: I don't know what I'm looking at anymore. Uh, but no,

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Speaker 3: I'm sure Grock is contributing so much good content about

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Speaker 3: all the you know, public bathroom spaces available in New

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Speaker 3: York City, now, right, that's yes, big advocates for public

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Speaker 3: safety and hell huge advocates.

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Speaker 1: So if folks listen to ourpisode last week, we did

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Speaker 1: a whole deep dive into Groc, which is X's AI chatbot.

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Speaker 2: I had a little bit of an update.

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

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Speaker 1: who missed it, But essentially the too long didn't read

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Speaker 1: is that Groc is being used to undress women and

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Speaker 1: girls without their consent.

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Speaker 2: So both the.

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Speaker 1: Groc account on X and the Groc standalone app are

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Speaker 1: being used in this way. Now, to be clear, we're

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Speaker 1: talking about illegal images. The Internet Watch Foundation, which is

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Speaker 1: a UK based on profit, says that it uncovered quote

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Speaker 1: criminal imagery of minor children generated by Groc, and so

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Speaker 1: for the last couple of days we've really seen this

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Speaker 1: backlash grow. On Monday, the EU threatened to find x

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Speaker 1: under the Digital Services Act if it did not act

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Speaker 1: quickly to fix GROC and keep it.

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Speaker 2: From doing this.

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Speaker 1: California Governor Gavin Newsom announced that California would be launching

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Speaker 1: an investigation into how GROC is being used. Late on

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Speaker 1: Friday evening, California's Attorney General sent x a cease and

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Speaker 1: desist letter demanding the company immediately stopped the creation and

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Speaker 1: distribution of deep fake, non consensual intimate images and child

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Speaker 1: sexual abuse material, saying in a statement, the creation of

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Speaker 1: this material is illegal. I fully expect XAI to immediately comply.

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Speaker 1: California has zero tolerance for child sexual abuse material. So

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Speaker 1: after this backlash, Musk was like, Okay, I got it.

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Speaker 2: I hear you.

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Speaker 1: From now on, only people who pay me money will

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Speaker 1: be able to use rock to undress women and girls

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Speaker 1: and make it legal content.

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Speaker 2: So there we go.

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Speaker 1: That was his first fix. I mean, to me, the

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Speaker 1: fact that he would even float that and would see

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Speaker 1: I mean, we talked about it on me ethisode. But

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Speaker 1: I don't think that that that like. I don't think

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Speaker 1: even he saw that as some sort of a meaningful fix.

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Speaker 2: I think like it's just a cash grab.

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Speaker 1: It's just a way to squeeze whatever last drop of.

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Speaker 2: Revenue they could out of this for themselves. And I mean,

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Speaker 2: let's call it what it is.

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Speaker 1: It's exploiting criminal behavior, targeting women and girls to make money.

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Speaker 1: This from the guy who like grandstanded when he first

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Speaker 1: bought Twitter about like how I'm in a crackdown on

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Speaker 1: content that exploits children. Now he's like, I'm going to

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Speaker 1: make money from content that exploits children.

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Speaker 2: That's that's sort of where we're at.

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Speaker 1: Weirdly, Elon Musk is kind of taking this like I

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Speaker 1: don't know what you're talking about stance. There's a really

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Speaker 1: good Mother Jones piece called Elon Musk's Alternate Grock Reality

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Speaker 1: that makes this point that while all of this stuff

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Speaker 1: is happening, all of these like threats of crackdowns and

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Speaker 1: investigations and all of that, Musk seemingly just is burying

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Speaker 1: his head in the sand. The piece reads within the

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Speaker 1: secure confines of Musk's own mind. Grock is not only

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Speaker 1: wildly successful, but solid as a rock, as he tweeted

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Speaker 1: on Monday, with the goal of pursuing the deeper truth

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Speaker 1: and appreciation of beauty, you know, the beauty of a

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Speaker 1: fourteen year old girl in an AI generated bikini, which

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Speaker 1: is a real thing that groc generates. Musk also says

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Speaker 1: that like, these are all just attacks from people who

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Speaker 1: want to suppress free speech.

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Speaker 3: I just framing it as like from the confines of

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Speaker 3: Elon Musk's head is such a funny way of thinking

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Speaker 3: about it, because again, I feel like every time we

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Speaker 3: talk about this guy, like I, the thing that you

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Speaker 3: have to go back to is just being like, no,

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Speaker 3: he genuinely does exist in his own reality, and like

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Speaker 3: that's the problem at the end of the day is

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Speaker 3: in Elon Musk's world, Elon Musk is the most popular, smartest,

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Speaker 3: funniest guy ever.

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Speaker 2: The problem is he's the only person living in that world.

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Speaker 2: And I guess the rest of us are just having

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Speaker 2: to suffer the consequences of that. I don't know, Uh,

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Speaker 2: it's funny that you bring it up and say it

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Speaker 2: that way. I once got into this very long.

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Speaker 1: Back and forth with somebody at an event who basically

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Speaker 1: so I completely agree with you, right, I think Elon

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Speaker 1: Musk is somebody who lives in his own world, his

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Speaker 1: own reality that has been essentially propped up by staffers

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Speaker 1: and underlings for him. And the point that I made

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Speaker 1: was that it's not good to have leaders who have

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Speaker 1: a lot of power and a lot of responsibility who

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Speaker 1: are like not living in reality.

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Speaker 2: Like I think that if you're going to be a

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Speaker 2: leader and people are.

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Speaker 1: Going to be relying on you, like and I mean

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Speaker 1: we're relying on people rely on him in like very

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Speaker 1: serious ways.

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Speaker 2: He's very mixed up at our military, very mixed up

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Speaker 2: in like how global communication systems around the world, like

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Speaker 2: very high stick stuff all flow through him.

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Speaker 1: And so I said, I think you should be living

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Speaker 1: in reality. The person I was speaking to made the

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Speaker 1: point of, well, people who are really successful entrepreneurs or builders,

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Speaker 1: it does take a little bit of you know, delusion

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Speaker 1: for you to build things. And not side note, I

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Speaker 1: don't I'm not somebody who subscribed to the idea that

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Speaker 1: like Elon Musk is this prolific builder of things. That's

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Speaker 1: a whole other conversation, but I do not endorse that,

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Speaker 1: this to be clear. And basically, his point was that

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Speaker 1: people who are really successful sometimes do you have a

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Speaker 1: threat of delusion.

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Speaker 2: And I just don't know about that. I understand that.

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Speaker 1: As a position, And I do think to do big

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Speaker 1: things you kind of have to you know, you have

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Speaker 1: to have.

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Speaker 3: Some sort of like like you have to be a

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Speaker 3: little delusional to get to that point.

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Speaker 2: The problem is like.

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Speaker 3: Sometimes that delusion goes too far, you know, like some

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Speaker 3: people are able to are able to some people are

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Speaker 3: able to keep one foot in reality while also being

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Speaker 3: totally delusional a lot. And then there also are a

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Speaker 3: lot more people that will put one foot into that

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Speaker 3: delusion and just like get sucked in to the vortex

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Speaker 3: of like this is Elon Musk's world and we're all

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Speaker 3: living in it.

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Speaker 2: Is what he thinks.

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Speaker 3: And I don't think most saying human beings feel that

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Speaker 3: way if you've ever had any sort of relationship, but

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Speaker 3: like a genuine narciss like it makes perfect sense. Like

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Speaker 3: I'm like, just this is just it, but you have

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Speaker 3: a bazillion dollars, like I don't.

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Speaker 2: Know in like all the all the power, yeah, all

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Speaker 2: of our of the world.

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Speaker 4: Yeah.

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Speaker 3: I mean there was just a story about his his

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Speaker 3: ex girlfriend too, now who said what like, oh, I

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Speaker 3: think we probably shouldn't be super evil to trans people

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Speaker 3: and he's.

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Speaker 2: Like freaking out. Now, uh so that's great.

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Speaker 3: I don't know.

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Speaker 2: I'm glad you brought that up.

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Speaker 1: I'm we're doing an episode with Parker malloy from the

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Speaker 1: present Age all about this basically at Elon's I don't

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Speaker 1: know if they were in a romantic relationship, because Elon

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Speaker 1: does that thing where they were he like establishes a

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Speaker 1: child with women, and it's like not clear to me

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Speaker 1: what's going on. So I don't want to make it

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Speaker 1: seem like they were in a romantic relationship, but they did.

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Speaker 1: They did have a child together. And so Ashley Saint

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Speaker 1: Clair is this like kind of prolific, like right wing

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Speaker 1: tran like anti trans wrote a children's book that's like

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Speaker 1: all of that transphobia. Recently made a post essentially expressing

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Speaker 1: regret for some of that behavior and regret for how

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Speaker 1: that behavior is going to impact her child's sister, who

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Speaker 1: was Elon Musk's one of Elon Musk's other children who

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Speaker 1: was trans. And now this was disreported earlier this week.

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Speaker 1: Ashley Saint Clair also filed a lawsuit against x She

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Speaker 1: filed a lawsuit with the Supreme Court in the State

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Speaker 1: of New York against XAI, alleging that GROC had been

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Speaker 1: used to generate non consensual images of her, including ones

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Speaker 1: in which she was underage. She is seeking punitive and

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Speaker 1: compensary damages, saying that dozens of sexually explicit and degrading

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Speaker 1: deep images were created by GROC.

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Speaker 2: So yeah, I.

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Speaker 1: Mean even people in Musk's own personal circle are being

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Speaker 1: impacted by this.

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Speaker 3: Right, And I mean you feel like, I don't know,

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Speaker 3: there's a complicated conversation that we had about like what

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Speaker 3: what does it mean when yeah, you have genuinely dedicated

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Speaker 3: your entire career to harming people, harming a very marginalized community,

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Speaker 3: and then suddenly changed her mind in her like, actually,

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Speaker 3: never mind, that was bad.

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Speaker 2: At the same time, I mean like if like, yeah,

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Speaker 2: it's a double edged sword. I'm looking at this cautiously.

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Speaker 3: At the same time, I do feel like there is

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Speaker 3: a lot of hope and being like, yeah, this person

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Speaker 3: that was a mouthpiece for the anti trans movement for

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Speaker 3: so long it's now coming out and being like, oh

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Speaker 3: my god, I'm so sorry, Like I.

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Speaker 2: I caused harm. This was bad.

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Speaker 3: Uh.

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Speaker 2: I don't think she's alone in what she's doing.

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Speaker 3: Again, it's like I wish that these people didn't do

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Speaker 3: the harm that they did to begin with, but it

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Speaker 3: is also like, you know, you read about x X gaze,

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Speaker 3: like I've reminded me of that. Your remind Like it's

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Speaker 3: people that I've said a lot of too. I think, like, honestly,

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Speaker 3: at the end of the day, the thing that pulls

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Speaker 3: people away from hate movements is like knowing people in

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Speaker 3: their life that have had these experiences, Like that's part

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Speaker 3: of the reason why I'm so open about the fact

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Speaker 3: that I'm like, I am a queer person, I am

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Speaker 3: like somebody who's trans. I'm somebody who is like early

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Speaker 3: on in their transitions.

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Speaker 2: So I don't really pass at all for what I'm

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Speaker 2: going for.

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Speaker 3: But at the same time, I'm like, I'll talk about

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Speaker 3: it because I know that I know there's people in

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Speaker 3: my life that I'm like, maybe weren't going to be

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Speaker 3: like Elon musk lettal transphobic, but like knowing me has

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Speaker 3: probably changed their opinion.

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Speaker 2: Of trans people. Yeah, And I don't know.

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Speaker 3: I guess like if there's any hope to take away

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Speaker 3: from it hearing that somebody, as you know, right wing

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Speaker 3: darling is Ashley Saint Clair can now come up, come

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Speaker 3: out and express some remorse for what she did, Like

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Speaker 3: that's a good.

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Speaker 2: Sign it's good.

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Speaker 3: It feels like it's like, all right, we're gonna get

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Speaker 3: out of this, gonna get out of whatever weird shit

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Speaker 3: show we've been in for the last year. Listeners, I'm sorry,

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Speaker 3: I'm trying to curse less on air, but it's gonna

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Speaker 3: be a slow, slow adjustment. I'm gonna agree about that.

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Speaker 3: So well, thank you.

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Speaker 2: Seana was a producer.

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Speaker 3: Mike Crow at one point did say like on air

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Speaker 3: that he was like, he was like, yeah, like I

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Speaker 3: hate her sing usually, and I was like editing it

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Speaker 3: and I was like, oh, so, I'm glad that we

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Speaker 3: could both bring our perspective perspectives to this.

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Speaker 5: But yeah, let's take a quick break at our back.

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Speaker 1: So, facing all of this backlash, whether Musk wants to

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Speaker 1: like accept it or not, including calls to remove Rock

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Speaker 1: from the Apple and Google app stores, Musk said, Okay,

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Speaker 1: we hear you. We're going to introduce some new restrictions

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Speaker 1: to stop folks from editing and generating images of real

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Speaker 1: people in bikinis or revealing clothing. Now, because we know

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Speaker 1: Elon Musk is a liar, this is a lie, because

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Speaker 1: both Wired and Business Insider and others have reported that

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Speaker 1: since Musk announced that they were going to be putting

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Speaker 1: some new restrictions in place. Not much has changed from

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Speaker 1: a Wired piece called Elon Musk's Grock undressing problem isn't fixed,

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Speaker 1: they write. While it appears that some safety measures have

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Speaker 1: finally been introduced to Grock's image generation on x, the

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Speaker 1: standalone Groc app and website still seem to still be

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Speaker 1: able to generate undressed style images and pornographic content. According

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Speaker 1: to multiple tests by researchers Wired and other journalists. We

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Speaker 1: can still generate photorealistic nudity on grock dot com, says

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Speaker 1: Paul Bouchard, the lead researcher at the Paris based nonprofit

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Speaker 1: AI Forensics. He has been keeping track of the use

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Speaker 1: of GROC to create sexualized images and ran multiple tests

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Speaker 1: on Groc outside of X. I can upload an image

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Speaker 1: on groc Imagine and ask to put the person in

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Speaker 1: a bikini and it works, says the researcher who tested

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Speaker 1: the system on a person appearing as a woman. Tests

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Speaker 1: by Wired, using free Groc accounts on its websites in

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Speaker 1: both the US and the UK successfully removed clothing from

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Speaker 1: two images of men without any apparent restrictions on the

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Speaker 1: GROC app in the UK. When asked to undress a male,

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Speaker 1: the app prompted a wired reporter to enter the user's

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Speaker 1: year of birth before the image could be generated. And

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Speaker 1: so the same it's like, sorry, all the men can

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Speaker 1: be children now pretty much. So a male reporter at

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Speaker 1: Business Insider did the same thing, right, And so Harry

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Speaker 1: Shatnay of Business Insider basically put a picture of himself

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Speaker 1: on Groc and said, put me in a jockstrap. And

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Speaker 1: he says, to my shock, it obeyed. He does say,

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Speaker 1: calm down.

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Speaker 2: Groc did not generally actual genitalia, but it got pretty

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Speaker 2: close because.

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Speaker 4: It just.

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Speaker 1: Made him naked but with his hate with a hand

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Speaker 1: over his crock, so like not nude, but pretty close

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Speaker 1: to nude. And so when Elon Musk says people are

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Speaker 1: no longer gonna be able to use rock to create

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Speaker 1: revealing images of other of real people, it seems like

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Speaker 1: this these tests say otherwise.

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Speaker 2: We're going We're going to the Catholic church like Adam

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Speaker 2: and Eve like this is out.

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Speaker 3: Have you anybody who's ever been to like an old

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Speaker 3: like cathedral where they have the art up where there's

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Speaker 3: they also added the like random ass thick leagues.

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Speaker 2: Are the statues.

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Speaker 3: There's like if anybody like, there's a bunch of famously

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Speaker 3: a bunch of statues in the Vatican that they added

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Speaker 3: like leaf shoe later to cover up their genitalia, which

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Speaker 3: I do think is like one of the funniest things

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Speaker 3: to happen, and.

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Speaker 2: Like art history, but I guess, yeah, I guess this is history.

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Speaker 2: You're repeating itself in.

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Speaker 3: A weird but like in a weird opposite way where

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Speaker 3: I'm like, but I don't want to see more of

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Speaker 3: the new like that's man again.

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Speaker 2: I wish I could. I wish I could get in

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Speaker 2: a time machine and go back to by.

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Speaker 3: Like I have a distinct memory of my middle school

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Speaker 3: principle making us do this like assembly where they had

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Speaker 3: all the girls, only the girls, and they had our principal,

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Speaker 3: who was like a middle aged man explained to us

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Speaker 3: why we shouldn't wear revealing clothing or take notes or whatever.

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Speaker 3: And it was genuinely one of the most like uncomfortable

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Speaker 3: experiences of my life.

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Speaker 2: As you can imagine. God, But I wish I could

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Speaker 2: go back and like be like, all right, guys, don't worry.

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Speaker 3: Not only is this all like bullshit and victim, blameya whatever.

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Speaker 2: But also in like twelve years.

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Speaker 3: From now, is not even gonna matter, because the next

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Speaker 3: generation of middle school boys are gonna have AI tools

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Speaker 3: for this shit.

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Speaker 2: Apparently, this is something I can't I simply cannot get over,

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Speaker 2: and I don't.

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Speaker 1: I don't know if I've talked I think I've talked

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Speaker 1: about on the podcast before. But I distinctly remember when

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Speaker 1: we were all kind of having those kind of conversations

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Speaker 1: right about taking intimate images. You know, folks might recall

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Speaker 1: ten years ago in the twenty tens, when a whole

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Speaker 1: trove of intimate images were stolen and released to the public.

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Speaker 1: But the I remember that at the time, the New

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Speaker 1: York Times is tech critic hit he tweeted, like, oh,

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Speaker 1: my advice for women, if they don't want to get

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Speaker 1: their their nude stolen, don't take nude images. Don't take

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Speaker 1: nude images. Don't take nude images. And I just see,

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Speaker 1: at the time, it was clear to me that that

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Speaker 1: was not the converse.

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Speaker 2: That was not like the conversation that we should have had.

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Speaker 1: And here we are ten years later, because you don't

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Speaker 1: have to take nude images to have to be undressed, right,

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Speaker 1: You could We've seen story after story after story where children,

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Speaker 1: you know, students in schools, middle schools and high schools,

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Speaker 1: this technology is being used by their peers in some

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Speaker 1: cases to undress them. And so I should we could get back,

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Speaker 1: go back in time and have a different conversation that

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Speaker 1: wasn't about oh, people shouldn't take nude pictures like that,

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Speaker 1: Like that's just it just was such useless advice. And

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Speaker 1: I'm infuriated that we spent any time at all. But

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Speaker 1: I'm Joey, I'm infuriated that you were lined up in

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Speaker 1: your school to be told to be like lectured by

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Speaker 1: your teacher about this.

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Speaker 2: Yeah.

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Speaker 3: No, absolutely, I mean I again, I feel like I'm

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Speaker 3: I'm a broken record every time I'm on this podcast

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Speaker 3: talking about it.

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Speaker 2: But it is like genuinely so baffling.

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Speaker 3: Again as somebody who's like in their mid twenties right now,

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Speaker 3: Like objectively, I'm pretty young. I've not lived that much

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Speaker 3: of my life, and I'm like, in the time from

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Speaker 3: when I was in middle school to now, the narrative

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Speaker 3: has changed so so drastically. It's somehow still the woman's fault.

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Speaker 3: And I'm and here's the thing I'm not saying that

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Speaker 3: this isn't a problem.

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Speaker 2: This is a problem. I mean, we do need to obviously,

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Speaker 2: like Bernie's like, this is a crime. This is a

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Speaker 2: literal crime.

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Speaker 3: I'm gonna take a big crazy tay here and say,

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Speaker 3: I don't think we should have like any child porn.

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Speaker 3: I think that's you know, sorry, I really really putting

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Speaker 3: myself out there and saying that, like going on.

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Speaker 2: The record with that, I don't think it should be

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Speaker 2: a thing. I think it's bad. I also think, like.

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Speaker 3: From the adult perspective on this, maybe there's also always

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Speaker 3: like a sign that we like societally just we have

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Speaker 3: so many hang ups about nudity still, like the fact

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Speaker 3: that a nude photo of a a fake nude photo

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Speaker 3: of an adult woman with a successful career. Again, we're

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Speaker 3: not talking about like the children. At a legal aspect

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Speaker 3: of this, like this, let's say it's somebody just.

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Speaker 2: Let's say it was me. Let's say it was me,

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Speaker 2: Let's say somebody else.

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Speaker 3: Like the fact that that is something that can derail

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Speaker 3: somebody's career is insane, Like that that is also part

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Speaker 3: of the problem here, right, Oh, absolutely, so, I.

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Speaker 2: Don't know, we need to get more chill about nudity.

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Speaker 3: And also like I don't know, trying to not say

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Speaker 3: something that will get me in trouble with the federal government.

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Speaker 2: But I don't know. I think what I'm trying to

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Speaker 2: say here is just the I think the reason.

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Speaker 3: This this always really it just sets me off on

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Speaker 3: the show as it's like this, this is something that

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Speaker 3: is just such a simple issue, and it affects everybody,

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00:22:08,080 --> 00:22:12,960
Speaker 3: and like it's affected everybody from like, yeah, random middle

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00:22:12,960 --> 00:22:16,080
Speaker 3: schoolers in the middle of the country, and it's affected

441
00:22:16,119 --> 00:22:20,280
Speaker 3: Taylor Swift, and like somehow we still as a society

442
00:22:20,920 --> 00:22:24,520
Speaker 3: have such a strange reaction to I don't know, it's

443
00:22:24,600 --> 00:22:25,480
Speaker 3: just it's.

444
00:22:25,320 --> 00:22:26,920
Speaker 2: A very weird issue.

445
00:22:27,240 --> 00:22:27,439
Speaker 3: You know.

446
00:22:27,960 --> 00:22:31,320
Speaker 1: I completely agree, and I will say that there might

447
00:22:31,359 --> 00:22:35,400
Speaker 1: be some changes coming because on Tuesday of this week,

448
00:22:35,440 --> 00:22:38,359
Speaker 1: the Senate unanimously passed to build that would allow the

449
00:22:38,480 --> 00:22:42,600
Speaker 1: victims who are targeted for non consensual sexually explicit deep things,

450
00:22:43,200 --> 00:22:45,520
Speaker 1: it would allow them to sue the creators of those

451
00:22:45,520 --> 00:22:48,280
Speaker 1: images for a minimum of one hundred and fifty thousand dollars.

452
00:22:48,560 --> 00:22:50,399
Speaker 1: This is a Defiance Act, which is now headed to

453
00:22:50,480 --> 00:22:54,159
Speaker 1: the House. Folks might recall that leadership did fail to

454
00:22:54,160 --> 00:22:56,680
Speaker 1: bring it to the floor in the last session. However,

455
00:22:56,800 --> 00:22:59,800
Speaker 1: because of all of this new momentum around these conversations

456
00:22:59,800 --> 00:23:03,080
Speaker 1: with Rock, it does seem like the conversation has changed.

457
00:23:03,119 --> 00:23:05,640
Speaker 1: So we will definitely keep y'all posted. I just I'll

458
00:23:05,760 --> 00:23:09,200
Speaker 1: end on this. I'll end on this, listeners.

459
00:23:09,280 --> 00:23:11,879
Speaker 3: I can't get over the name Rock, but I the

460
00:23:11,920 --> 00:23:13,480
Speaker 3: thing that I go back to and again, I feel

461
00:23:13,520 --> 00:23:15,439
Speaker 3: like I've said this on the show before, but the

462
00:23:15,520 --> 00:23:17,640
Speaker 3: thing that about Elon Musk that really pisses me off

463
00:23:17,720 --> 00:23:20,520
Speaker 3: is he wants so badly to be this like meme

464
00:23:20,960 --> 00:23:25,879
Speaker 3: edged lord, like dirty whatever, and like he's genuinely just

465
00:23:25,960 --> 00:23:31,919
Speaker 3: so like uncreative and unfunny, like I like funny, like

466
00:23:32,280 --> 00:23:36,480
Speaker 3: weird nerdy guy girl person is like my favorite brand

467
00:23:36,560 --> 00:23:38,480
Speaker 3: of person. And Elon Musk wants to be that type

468
00:23:38,480 --> 00:23:40,520
Speaker 3: of person so bad, and he's just failing it so

469
00:23:40,680 --> 00:23:43,040
Speaker 3: miserably that I guess if there's any joy that you

470
00:23:43,080 --> 00:23:44,760
Speaker 3: can take away from this, it's at least that.

471
00:23:45,320 --> 00:23:45,600
Speaker 5: You know.

472
00:23:48,080 --> 00:23:52,040
Speaker 1: It's so true because when he he he makes these

473
00:23:52,080 --> 00:23:55,200
Speaker 1: attempts at jokes and it's just so so bad.

474
00:23:56,280 --> 00:24:01,120
Speaker 2: Oh like they it's so bad. He just really doesn't

475
00:24:01,160 --> 00:24:01,800
Speaker 2: have it in him.

476
00:24:01,920 --> 00:24:04,560
Speaker 1: Sometimes I catch myself feeling bad for him, because I

477
00:24:04,600 --> 00:24:08,680
Speaker 1: just recognize that the energy of the kid who wants

478
00:24:08,720 --> 00:24:11,760
Speaker 1: to be cool so badly in junior high and it's

479
00:24:11,760 --> 00:24:14,320
Speaker 1: just not landing, and like thing after thing after thing

480
00:24:14,400 --> 00:24:16,640
Speaker 1: is not landing at a certain point, probably.

481
00:24:16,720 --> 00:24:18,600
Speaker 2: You just do do. It's hard to not feel a

482
00:24:18,640 --> 00:24:21,080
Speaker 2: little bad sometimes, I know. And that's the thing, Like

483
00:24:21,119 --> 00:24:23,359
Speaker 2: I'm like, that's like those are my people.

484
00:24:23,560 --> 00:24:26,160
Speaker 3: Like let's go like so many of us were weird

485
00:24:26,200 --> 00:24:29,639
Speaker 3: middle schoolers at once at some point, but like and

486
00:24:29,680 --> 00:24:32,560
Speaker 3: then we became real functioning people.

487
00:24:32,720 --> 00:24:37,280
Speaker 2: And also Art here's something too. It's the like if

488
00:24:37,320 --> 00:24:38,440
Speaker 2: he just was like.

489
00:24:38,600 --> 00:24:42,359
Speaker 3: A good person or even like an okay person, like

490
00:24:42,440 --> 00:24:43,720
Speaker 3: people probably.

491
00:24:43,320 --> 00:24:45,359
Speaker 2: Would actually find some of this stuff funny.

492
00:24:45,600 --> 00:24:47,360
Speaker 3: Like that's about Like that's like the reason people don't

493
00:24:47,359 --> 00:24:48,840
Speaker 3: find you funny is also just the fact you're a

494
00:24:48,840 --> 00:24:49,680
Speaker 3: miserable human being.

495
00:24:49,720 --> 00:24:51,240
Speaker 2: Like I don't know what to tell you. People to

496
00:24:51,280 --> 00:24:57,879
Speaker 2: find cringey stupid humor funny all the time. Yeah, I

497
00:24:57,880 --> 00:24:58,919
Speaker 2: don't know, I don't know.

498
00:24:59,000 --> 00:25:01,080
Speaker 3: I wish there was a way to express my anger

499
00:25:01,119 --> 00:25:04,359
Speaker 3: at Elon Musk better than just like reverting back to

500
00:25:04,480 --> 00:25:09,960
Speaker 3: like mean girl high school like teenage girl insults. But

501
00:25:10,119 --> 00:25:11,680
Speaker 3: like that is my best weapon right now, and I'm.

502
00:25:12,200 --> 00:25:15,639
Speaker 1: Guess, and it's a weapon that will always work against

503
00:25:15,720 --> 00:25:17,960
Speaker 1: him because no matter how much money.

504
00:25:17,840 --> 00:25:19,719
Speaker 2: Or power he gets, he will always be a loser.

505
00:25:19,880 --> 00:25:23,879
Speaker 2: So that was always gonna work exactly exactly.

506
00:25:25,280 --> 00:25:28,480
Speaker 1: Okay, So do you remember the conversations that we had

507
00:25:28,600 --> 00:25:31,200
Speaker 1: all about the tea app, the app that was designed

508
00:25:31,480 --> 00:25:33,720
Speaker 1: for women to screen the men that they dated, that

509
00:25:33,880 --> 00:25:38,000
Speaker 1: ended up exposing their users sensitive information like their driver's licenses.

510
00:25:38,400 --> 00:25:41,080
Speaker 3: Are we talking the tea on her, the tea on him,

511
00:25:41,240 --> 00:25:44,800
Speaker 3: the tea on them, the t on the teon the

512
00:25:44,880 --> 00:25:46,159
Speaker 3: Charlie Kurcaders.

513
00:25:46,440 --> 00:25:51,000
Speaker 2: What are weird? There are so many? Yeah, the tea

514
00:25:51,119 --> 00:25:52,359
Speaker 2: cinematic universe.

515
00:25:52,680 --> 00:25:56,280
Speaker 1: Yes, So the Tea app for women is back, and

516
00:25:56,320 --> 00:25:59,879
Speaker 1: they're saying we're sorry for what happened. We're sorry that

517
00:26:00,080 --> 00:26:04,600
Speaker 1: we ended up exposing our users sensitive information, and they're

518
00:26:04,640 --> 00:26:06,560
Speaker 1: asking for your trust again.

519
00:26:06,680 --> 00:26:09,959
Speaker 2: So you might be wondering, well, what's different this time around?

520
00:26:10,480 --> 00:26:13,639
Speaker 1: According to Wired Tea's head of Trust and Safety, Jessica

521
00:26:13,680 --> 00:26:17,600
Speaker 1: d'es said that the new site features quote meaningful improvements

522
00:26:18,040 --> 00:26:24,000
Speaker 1: intended to bolster security, including tightening internal safeguards, reinforcing access controls,

523
00:26:24,040 --> 00:26:27,800
Speaker 1: and expanding review and monitoring processes to better protect sensitive information.

524
00:26:28,080 --> 00:26:29,920
Speaker 1: They're also going to be working with a third party

525
00:26:29,920 --> 00:26:33,280
Speaker 1: of verification vendor to ensure that users are women because

526
00:26:33,280 --> 00:26:36,080
Speaker 1: it's a women only app, as part of the eligibility check.

527
00:26:36,359 --> 00:26:37,760
Speaker 2: Folks might recall that in.

528
00:26:37,720 --> 00:26:40,840
Speaker 1: The early iteration of this app, they were asking women

529
00:26:41,160 --> 00:26:45,160
Speaker 1: to submit pictures of their driver's licenses or government IDs

530
00:26:45,480 --> 00:26:49,159
Speaker 1: to confirm that they were women. I will say, just

531
00:26:49,200 --> 00:26:51,600
Speaker 1: a side note, we already know that some of these

532
00:26:51,640 --> 00:26:55,840
Speaker 1: third party verification vendors are not always that secure, and

533
00:26:55,880 --> 00:26:59,040
Speaker 1: so this just does not fill me with a lot

534
00:26:59,119 --> 00:27:03,080
Speaker 1: of I would not still trust this company, but that's

535
00:27:03,119 --> 00:27:03,840
Speaker 1: what they're doing.

536
00:27:04,240 --> 00:27:08,399
Speaker 3: Also, like, what's stopping people like I'm from just uploading

537
00:27:08,640 --> 00:27:09,880
Speaker 3: somebody else's information?

538
00:27:10,320 --> 00:27:12,600
Speaker 2: You know, Like great question.

539
00:27:12,560 --> 00:27:16,560
Speaker 3: If you're asking, if you're saying beyond the obvious, Like

540
00:27:16,760 --> 00:27:19,240
Speaker 3: we've talked about other apps on the show before that

541
00:27:19,240 --> 00:27:22,600
Speaker 3: I've tried to like enforce like quote unquote women only

542
00:27:22,640 --> 00:27:25,199
Speaker 3: and have required people to like upload selfies and whatnot,

543
00:27:25,240 --> 00:27:28,159
Speaker 3: and why that's bad and doesn't work. But also, like,

544
00:27:28,240 --> 00:27:30,760
Speaker 3: what's stopping somebody from being like I'm gonna use my

545
00:27:30,840 --> 00:27:32,400
Speaker 3: mom's ID to just sign up.

546
00:27:32,359 --> 00:27:34,360
Speaker 2: For uh, you know what?

547
00:27:34,400 --> 00:27:36,600
Speaker 3: This is this is again. I'll provide the gen Z

548
00:27:36,760 --> 00:27:40,040
Speaker 3: perspective here. There were plenty of apps that I was

549
00:27:40,119 --> 00:27:42,240
Speaker 3: not supposed to sign up for as a child that

550
00:27:42,240 --> 00:27:44,159
Speaker 3: were like eighteen plus that I just put like my

551
00:27:44,280 --> 00:27:47,919
Speaker 3: mom's email in and I or something or made a

552
00:27:47,920 --> 00:27:51,119
Speaker 3: fake email like I I'm just like, I feel like

553
00:27:51,160 --> 00:27:55,520
Speaker 3: these are such easy things to get around.

554
00:27:55,880 --> 00:27:59,160
Speaker 1: Absolutely, in the earlier iteration of the Tea app, there

555
00:27:59,200 --> 00:28:03,159
Speaker 1: were plenty of times where men who were not supposed

556
00:28:03,160 --> 00:28:05,679
Speaker 1: to be on this app use somebody else's information to

557
00:28:05,880 --> 00:28:08,200
Speaker 1: get access to it, to like take screenshots and put

558
00:28:08,200 --> 00:28:10,360
Speaker 1: them on social media and things like that. So, yeah,

559
00:28:10,400 --> 00:28:13,159
Speaker 1: this is not a This is not an ironcloud system

560
00:28:13,200 --> 00:28:14,040
Speaker 1: by any means.

561
00:28:14,160 --> 00:28:16,560
Speaker 3: Anybody that has ever been on a dating app and

562
00:28:16,640 --> 00:28:19,640
Speaker 3: tried to put their been on a dating app been

563
00:28:19,760 --> 00:28:22,919
Speaker 3: interested ben Somebody who either identify identifies as like a

564
00:28:22,920 --> 00:28:24,800
Speaker 3: woman or a non minor person or whatever and has

565
00:28:24,840 --> 00:28:28,040
Speaker 3: put their dating app preferences to women only can tell

566
00:28:28,080 --> 00:28:30,880
Speaker 3: you that doesn't do shit like I.

567
00:28:30,920 --> 00:28:34,680
Speaker 1: Hear or when if you order Uber Eats and you're like, oh,

568
00:28:34,800 --> 00:28:36,880
Speaker 1: Jessica is coming with my burritos, and then the person

569
00:28:36,920 --> 00:28:38,680
Speaker 1: that shows up, you're like, I don't think you're Jessica,

570
00:28:38,720 --> 00:28:42,520
Speaker 1: but like it's like people have figured out how to

571
00:28:42,520 --> 00:28:45,560
Speaker 1: get around this is what is what we're saying exactly exactly.

572
00:28:46,120 --> 00:28:47,040
Speaker 2: So a new.

573
00:28:46,880 --> 00:28:50,000
Speaker 1: Feature that they also have is this in app AI

574
00:28:50,360 --> 00:28:53,600
Speaker 1: dating coach that will provide advice for different dating scenarios,

575
00:28:53,960 --> 00:28:58,080
Speaker 1: and a chat analysis capability called Red Flag Radar AI,

576
00:28:59,240 --> 00:29:02,680
Speaker 1: which says it can surface potential warning signs in suitors.

577
00:29:03,080 --> 00:29:06,479
Speaker 1: In both cases it stops sorry, I need I know,

578
00:29:06,880 --> 00:29:13,400
Speaker 1: I know that. So according to the d's the Trust

579
00:29:13,400 --> 00:29:16,440
Speaker 1: and Safety person from t she says, in both cases,

580
00:29:16,480 --> 00:29:19,080
Speaker 1: AI is designed to supplement community insight and can help

581
00:29:19,120 --> 00:29:21,560
Speaker 1: it inform a community member's point of view on something

582
00:29:21,560 --> 00:29:25,240
Speaker 1: they might not be sure about. Would you trust this

583
00:29:25,320 --> 00:29:29,880
Speaker 1: a this, this AI Dating Coach and AI red Flag

584
00:29:30,000 --> 00:29:32,800
Speaker 1: Radar with your with your online dating matches?

585
00:29:33,480 --> 00:29:35,720
Speaker 2: Honestly, if there's anything.

586
00:29:36,840 --> 00:29:38,560
Speaker 3: If we ended the last story with me trying to

587
00:29:38,600 --> 00:29:41,200
Speaker 3: pull a positive from that, this is me pulling like

588
00:29:41,280 --> 00:29:44,160
Speaker 3: my my negative, my worst, like pessimistic take from this.

589
00:29:44,320 --> 00:29:46,720
Speaker 3: Every time I see something about people using AI and

590
00:29:46,800 --> 00:29:49,400
Speaker 3: like dating, like how to respond to people on dating

591
00:29:49,440 --> 00:29:52,240
Speaker 3: apps or whatever, like I'm like worst grewed like this

592
00:29:52,280 --> 00:29:52,600
Speaker 3: is it?

593
00:29:52,680 --> 00:29:57,560
Speaker 2: Like like I y'all. I know date, Like, flirting.

594
00:29:57,280 --> 00:30:00,160
Speaker 3: Is awkward, it's hard. You gotta put yourself out there.

595
00:30:00,520 --> 00:30:04,160
Speaker 3: Like I'm aware, but like, that's the fun of it.

596
00:30:04,480 --> 00:30:06,880
Speaker 3: That's the reason it's fun. That's the really Like I

597
00:30:06,920 --> 00:30:09,640
Speaker 3: don't like, imagine somebody says something really nice to you

598
00:30:09,680 --> 00:30:11,480
Speaker 3: and then you find out that a robot did it.

599
00:30:11,560 --> 00:30:14,120
Speaker 2: Not that like that would I would? I'd be so mad?

600
00:30:14,280 --> 00:30:17,120
Speaker 2: Are you kidding me? I I was just an idea of.

601
00:30:17,040 --> 00:30:17,640
Speaker 4: The red Yeah.

602
00:30:17,640 --> 00:30:20,440
Speaker 3: I I needed to pause there when we said the

603
00:30:20,520 --> 00:30:24,720
Speaker 3: like red flag radar Ai, is this.

604
00:30:24,680 --> 00:30:25,960
Speaker 2: Really what we need right now?

605
00:30:26,000 --> 00:30:29,200
Speaker 3: In the era of like TikTok therapy, we have to

606
00:30:29,320 --> 00:30:32,720
Speaker 3: therapy talk everything. Every time somebody does something that I

607
00:30:32,720 --> 00:30:35,640
Speaker 3: slightly don't like, that's a red flag? Like what what

608
00:30:35,720 --> 00:30:38,320
Speaker 3: are we calling red flags? What does a red flag mean?

609
00:30:38,520 --> 00:30:38,760
Speaker 4: Like? What?

610
00:30:40,120 --> 00:30:42,480
Speaker 2: Also, like, I don't know, we're human beings, were flawed

611
00:30:42,600 --> 00:30:43,400
Speaker 2: like a lot of people.

612
00:30:43,600 --> 00:30:47,160
Speaker 3: Yes, there are things that I'm like, I will be like, sure,

613
00:30:47,160 --> 00:30:49,120
Speaker 3: if somebody does this, that's a red flag, you probably

614
00:30:49,160 --> 00:30:51,120
Speaker 3: should drop them right there. At the same time, I'm like,

615
00:30:51,160 --> 00:30:54,080
Speaker 3: I don't know, We're all flawed individuals. I don't think

616
00:30:54,080 --> 00:30:56,040
Speaker 3: I've ever dated anybody and been like and they're a

617
00:30:56,040 --> 00:30:58,840
Speaker 3: perfect human being and they everything is great, Like there's

618
00:30:58,920 --> 00:31:00,959
Speaker 3: things that there's always so thing they do that annoyed.

619
00:31:01,000 --> 00:31:02,760
Speaker 3: I don't know, like that's just what being a human

620
00:31:02,800 --> 00:31:05,560
Speaker 3: being is. Yeah, this is the story that's I think

621
00:31:05,600 --> 00:31:09,080
Speaker 3: gonna depressed me the most. It is just like, come on, guys.

622
00:31:08,880 --> 00:31:12,320
Speaker 2: I don't know, Like again, I keep going back to.

623
00:31:12,360 --> 00:31:14,000
Speaker 3: Because I do feel like this is a like my

624
00:31:14,120 --> 00:31:17,360
Speaker 3: generation issue too, Like this is gen Z. I'm sorry,

625
00:31:17,400 --> 00:31:20,760
Speaker 3: but like this is us doing this shit like all

626
00:31:20,800 --> 00:31:24,440
Speaker 3: of the AI boyfriends. They'll like the yeah, they'll like

627
00:31:24,560 --> 00:31:26,520
Speaker 3: using chatchebt to flirt with people.

628
00:31:26,720 --> 00:31:31,160
Speaker 2: I'm like, that's so depressing. That's so depressing. Just just

629
00:31:31,240 --> 00:31:33,080
Speaker 2: live your life. I don't know what to tell you.

630
00:31:33,400 --> 00:31:36,200
Speaker 1: I once saw somebody they I think I saw it

631
00:31:36,240 --> 00:31:39,560
Speaker 1: on Reddit or something where somebody had worked out some

632
00:31:40,520 --> 00:31:43,600
Speaker 1: lines to use to fort with women on chat cept

633
00:31:44,200 --> 00:31:46,040
Speaker 1: and I was like, you need a chatcheep tita give

634
00:31:46,040 --> 00:31:46,840
Speaker 1: you the line.

635
00:31:46,800 --> 00:31:47,800
Speaker 2: Like Hi, what's your name?

636
00:31:47,880 --> 00:31:50,960
Speaker 1: Nice to meet you anything.

637
00:31:51,240 --> 00:31:53,800
Speaker 2: There's no harm, there's no harm in needing that. I

638
00:31:53,840 --> 00:31:56,120
Speaker 2: will say. Recently this week, somebody in my life who

639
00:31:56,120 --> 00:31:59,640
Speaker 2: I love very dearly ran a like learning line by.

640
00:31:59,480 --> 00:32:01,160
Speaker 3: Me that I would like, you seriously needed me to

641
00:32:01,200 --> 00:32:02,960
Speaker 3: tell you that that's an okay thing to say, like,

642
00:32:03,000 --> 00:32:07,960
Speaker 3: and that's not to push your run anyways. That being said, yeah,

643
00:32:08,040 --> 00:32:10,440
Speaker 3: let's go back to the old bashaways. Ask your friends,

644
00:32:10,760 --> 00:32:12,440
Speaker 3: you guys like, this is part of this is what

645
00:32:12,560 --> 00:32:13,200
Speaker 3: makes life.

646
00:32:13,480 --> 00:32:15,200
Speaker 2: The reason okay, the reason I'm mad.

647
00:32:15,040 --> 00:32:17,160
Speaker 3: About this is I'm like, this is the thing to

648
00:32:17,240 --> 00:32:19,360
Speaker 3: me that I'm like, this is what makes life worth living, right,

649
00:32:19,480 --> 00:32:21,680
Speaker 3: is like these connections you have with people, sharing these

650
00:32:21,720 --> 00:32:25,640
Speaker 3: experiences with people, if you are thinking through what you're

651
00:32:25,680 --> 00:32:27,760
Speaker 3: saying so much to the fact where you're like, I

652
00:32:27,800 --> 00:32:30,360
Speaker 3: need I need, I need to have chat GPT editing

653
00:32:30,400 --> 00:32:32,080
Speaker 3: it for me and saying it and making it perfect,

654
00:32:32,160 --> 00:32:36,280
Speaker 3: Like that's not You're taking the humanity out of your life,

655
00:32:36,480 --> 00:32:38,760
Speaker 3: and that makes me really sad, you know, like, talk

656
00:32:38,840 --> 00:32:41,760
Speaker 3: to one of your friends ask you for again. I've

657
00:32:42,120 --> 00:32:45,640
Speaker 3: I've sent so many like unhinged text of friends being like, hey,

658
00:32:45,680 --> 00:32:48,360
Speaker 3: can you tell me that this response makes sense? And

659
00:32:48,360 --> 00:32:51,280
Speaker 3: they're like, yeah, Like that's a normal thing to say.

660
00:32:51,320 --> 00:32:54,920
Speaker 3: It's fine. That is so much less embarrassing than going

661
00:32:54,920 --> 00:32:56,760
Speaker 3: to chat CHEPT and letting them look at it or

662
00:32:57,040 --> 00:33:03,120
Speaker 3: or t app AI or whatever or Rock, I guess yeah,

663
00:33:03,800 --> 00:33:04,160
Speaker 3: all of.

664
00:33:04,120 --> 00:33:08,000
Speaker 1: The don't Rock be the one that's in charge of

665
00:33:08,040 --> 00:33:08,840
Speaker 1: your dating life.

666
00:33:09,240 --> 00:33:11,760
Speaker 2: Let me just give that blanket advice for everybody. You

667
00:33:11,760 --> 00:33:14,320
Speaker 2: don't think Mecha Hitler as some good one liners?

668
00:33:14,400 --> 00:33:17,880
Speaker 1: You know, yeah, maybe the person you're talking to likes

669
00:33:17,920 --> 00:33:22,200
Speaker 1: like Edgy, you know, Oh, it's just it's just a joke,

670
00:33:22,440 --> 00:33:25,560
Speaker 1: that kind of humor. Maybe maybe they like like hatred

671
00:33:25,600 --> 00:33:29,400
Speaker 1: and anti semitism masked with humor.

672
00:33:29,400 --> 00:33:30,760
Speaker 2: Maybe they maybe they'll be into that.

673
00:33:30,920 --> 00:33:32,960
Speaker 3: If you can't pick that up as a red flag

674
00:33:33,000 --> 00:33:36,520
Speaker 3: without AI, I feel like that's you problem. If you're like, no,

675
00:33:36,600 --> 00:33:39,280
Speaker 3: I thought the anti Semitic jokes were like just a

676
00:33:39,280 --> 00:33:42,680
Speaker 3: funny little bit he did. I don't know, man, maybe

677
00:33:42,680 --> 00:33:44,640
Speaker 3: you've got to do some self evaluation too.

678
00:33:48,200 --> 00:34:02,480
Speaker 1: More after a quick break, let's get right back into it.

679
00:34:05,680 --> 00:34:08,000
Speaker 2: But yeah, you know, good to know that AI is.

680
00:34:09,160 --> 00:34:11,279
Speaker 3: Valentine's Day's coming up in a month, so you know

681
00:34:11,640 --> 00:34:14,719
Speaker 3: that's gonna we're obviously the most important thing that AI

682
00:34:14,840 --> 00:34:16,520
Speaker 3: is doing is going to be writing our love letters

683
00:34:16,520 --> 00:34:18,400
Speaker 3: and whatnot. And I'm sure, as you're gonna tell me,

684
00:34:18,400 --> 00:34:23,360
Speaker 3: Bridget aih is being used to just do so many

685
00:34:23,400 --> 00:34:30,319
Speaker 3: more beautiful like heartfelt. Really is just like propelling human

686
00:34:30,360 --> 00:34:33,040
Speaker 3: connection forward, right, that's what you're about to say.

687
00:34:34,200 --> 00:34:37,840
Speaker 1: I wish that was where this was going, but unfortunately

688
00:34:37,840 --> 00:34:40,239
Speaker 1: the opposite. Just a quick heads up for this conversation

689
00:34:40,280 --> 00:34:42,040
Speaker 1: because it does involve suicide.

690
00:34:42,440 --> 00:34:44,160
Speaker 2: So you know, we.

691
00:34:44,080 --> 00:34:48,080
Speaker 1: All know that AI is biased, and yet institutions have

692
00:34:48,200 --> 00:34:51,440
Speaker 1: rushed to use AI in critical decision making capacities. And

693
00:34:51,440 --> 00:34:53,680
Speaker 1: I have a pretty grim example that I was reading

694
00:34:53,719 --> 00:34:56,319
Speaker 1: about in the Markup this week. According to this piece

695
00:34:56,360 --> 00:34:59,239
Speaker 1: in the Markup, an AI program that is designed to

696
00:34:59,239 --> 00:35:03,839
Speaker 1: prevent suicide among US military veterans is prioritizing white men

697
00:35:04,040 --> 00:35:07,560
Speaker 1: and ignoring survivors of sexual violence, which affects a far

698
00:35:07,640 --> 00:35:09,839
Speaker 1: greater percentage of women. Now, this is according to an

699
00:35:09,840 --> 00:35:13,640
Speaker 1: investigation by the Fuller Project. The VA right now uses

700
00:35:13,680 --> 00:35:16,400
Speaker 1: this algorithm that is meant to be targeting assistance to

701
00:35:16,440 --> 00:35:19,960
Speaker 1: patients with the highest statistical risk for suicide. To do that,

702
00:35:20,000 --> 00:35:22,759
Speaker 1: it looks at sixty one variables, the document show, and

703
00:35:22,800 --> 00:35:25,960
Speaker 1: it gives preference to veterans who are divorced in male

704
00:35:26,360 --> 00:35:29,280
Speaker 1: and widowed in male, but not to any other group

705
00:35:29,400 --> 00:35:30,680
Speaker 1: of female veterans.

706
00:35:30,880 --> 00:35:34,160
Speaker 2: So why is this a problem? While military, sexual trauma

707
00:35:34,200 --> 00:35:36,600
Speaker 2: and intimate partner of violence, two things that are both

708
00:35:36,680 --> 00:35:39,760
Speaker 2: linked to an elevated risk in suicide among female veterans,

709
00:35:39,760 --> 00:35:42,080
Speaker 2: are not taken into account. Now.

710
00:35:42,160 --> 00:35:45,640
Speaker 1: The suicide rate among male veterans is higher than that

711
00:35:45,719 --> 00:35:49,360
Speaker 1: of their female counterparts. However, the rate among female veterans

712
00:35:49,560 --> 00:35:53,319
Speaker 1: is rising faster. New government stats reveal that suicide rates

713
00:35:53,320 --> 00:35:56,320
Speaker 1: for women veterans jumped by twenty four percent from twenty

714
00:35:56,320 --> 00:35:59,400
Speaker 1: twenty to twenty twenty one. That increase was four times

715
00:35:59,480 --> 00:36:03,560
Speaker 1: higher than male veterans experienced in that same timeframe, roughly

716
00:36:03,800 --> 00:36:06,479
Speaker 1: ten times greaters, and the two point six rise seen

717
00:36:06,480 --> 00:36:09,239
Speaker 1: among civilian women who would not serve in the military.

718
00:36:09,560 --> 00:36:12,160
Speaker 1: And when I read that, that completely makes sense to

719
00:36:12,200 --> 00:36:15,960
Speaker 1: me because that was before Pete Hegsath became the Secretary

720
00:36:15,960 --> 00:36:19,240
Speaker 1: of Defense and initiated all these changes that were really

721
00:36:19,320 --> 00:36:21,640
Speaker 1: hostile to anybody that is not a SIS man in

722
00:36:21,680 --> 00:36:24,840
Speaker 1: the military who was serving, right, So, like, what is making.

723
00:36:24,560 --> 00:36:25,520
Speaker 2: Statements like this?

724
00:36:26,080 --> 00:36:28,200
Speaker 1: And so it's just not hard for me to imagine

725
00:36:28,200 --> 00:36:32,239
Speaker 1: that the climate has gotten increasingly more hostile since then.

726
00:36:32,440 --> 00:36:35,919
Speaker 3: I want to add really quick because this is something

727
00:36:35,920 --> 00:36:38,319
Speaker 3: that I think comes up whenever this stat's come up

728
00:36:38,360 --> 00:36:42,439
Speaker 3: about suicide rates in the US and ridicule the fact

729
00:36:42,520 --> 00:36:46,600
Speaker 3: that men do have higher suicide rates. A it is

730
00:36:46,640 --> 00:36:51,120
Speaker 3: a very very complicated conversation about like also, you know,

731
00:36:51,239 --> 00:36:54,120
Speaker 3: just culturally men are sort of like less encouraged JUICEE

732
00:36:54,120 --> 00:36:56,480
Speaker 3: health than women are. Obviously that's part of it, but

733
00:36:56,520 --> 00:36:58,799
Speaker 3: I do also want to emphasize the fact that those

734
00:36:58,800 --> 00:37:03,040
Speaker 3: stats don't take into a out like LGBTQ plus identity,

735
00:37:03,560 --> 00:37:05,120
Speaker 3: which I think we're going to get to a little

736
00:37:05,120 --> 00:37:07,560
Speaker 3: bit later on in the story. But I think if

737
00:37:07,600 --> 00:37:09,839
Speaker 3: you're somebody who is queer, if you're a queer man,

738
00:37:09,880 --> 00:37:11,640
Speaker 3: if you are a trans woman, if you are somebody

739
00:37:11,640 --> 00:37:13,920
Speaker 3: who is like a gender queer person who's assigned mail

740
00:37:13,920 --> 00:37:16,120
Speaker 3: at birth, like you're also going to be just sort

741
00:37:16,160 --> 00:37:17,839
Speaker 3: of stuck in that category of like.

742
00:37:17,960 --> 00:37:19,279
Speaker 2: Men who commit suicide.

743
00:37:20,280 --> 00:37:22,240
Speaker 3: So yeah, I bring that up just because I think

744
00:37:22,520 --> 00:37:26,320
Speaker 3: I'm not again not saying everybody in that category probably

745
00:37:26,320 --> 00:37:28,279
Speaker 3: belongs to that identity as well. But I do think, like,

746
00:37:29,400 --> 00:37:31,239
Speaker 3: especially when we're talking about like the state of like

747
00:37:31,280 --> 00:37:32,960
Speaker 3: the way that trans people are talked out in this

748
00:37:33,000 --> 00:37:35,000
Speaker 3: country right now, like, yeah, a lot of those people

749
00:37:35,000 --> 00:37:37,520
Speaker 3: are also probably trans people that just are are going

750
00:37:37,560 --> 00:37:39,719
Speaker 3: to be put into like the man box because of

751
00:37:39,960 --> 00:37:40,920
Speaker 3: the world that we live in.

752
00:37:41,120 --> 00:37:43,879
Speaker 1: Absolutely that I'm glad that you added that context, because

753
00:37:43,880 --> 00:37:45,919
Speaker 1: it sounds like that's exactly what's going on. The piece

754
00:37:45,960 --> 00:37:48,279
Speaker 1: reads that the algorithm failed to take into account whether

755
00:37:48,360 --> 00:37:52,879
Speaker 1: veterans identify as LGBTQ plus, even though the agency's own

756
00:37:52,960 --> 00:37:56,640
Speaker 1: researchers have determined that trans veterans die by suicide at

757
00:37:56,640 --> 00:38:00,880
Speaker 1: twice the rate as cist gender veterans. Scientists have also

758
00:38:00,920 --> 00:38:03,360
Speaker 1: found that gay, lesbian, and bisexual veterans are at a

759
00:38:03,440 --> 00:38:07,160
Speaker 1: greater risk for suicide than both the overall veteran population

760
00:38:07,600 --> 00:38:10,960
Speaker 1: and the US population at large. And so your point

761
00:38:11,000 --> 00:38:15,279
Speaker 1: is exactly correct, Joey, that the way that these algorithms

762
00:38:15,360 --> 00:38:19,400
Speaker 1: are responding to the data, it just doesn't actually reflect

763
00:38:19,680 --> 00:38:23,400
Speaker 1: who these folks actually are and what the circumstances and

764
00:38:24,040 --> 00:38:28,040
Speaker 1: warning signs actually might be in their life. So another

765
00:38:28,120 --> 00:38:31,680
Speaker 1: thing about this algorithm is that not only is it

766
00:38:31,960 --> 00:38:35,120
Speaker 1: kind of not considering the needs of service members who

767
00:38:35,160 --> 00:38:38,480
Speaker 1: are not CIS men, it might not even really be effective.

768
00:38:38,520 --> 00:38:41,520
Speaker 1: Because the Peace spoke to Meredith Brossard, who's a research

769
00:38:41,520 --> 00:38:44,880
Speaker 1: director for NYU's Alliance for Public Interest Technology and She

770
00:38:45,160 --> 00:38:48,640
Speaker 1: doubted whether or not the agency's AI system even reached

771
00:38:48,800 --> 00:38:52,200
Speaker 1: accurate conclusions, saying, whenever you have an algorithm that seems

772
00:38:52,239 --> 00:38:55,120
Speaker 1: to favor the majority group, for example, white men, and

773
00:38:55,160 --> 00:38:58,640
Speaker 1: someone says it's just math, it's most likely the case

774
00:38:58,680 --> 00:39:02,839
Speaker 1: where systemic bias is manifesting itself in the math. And

775
00:39:03,280 --> 00:39:06,719
Speaker 1: I really have to imagine that that's probably a bit

776
00:39:06,760 --> 00:39:09,920
Speaker 1: of what's going on here, and that really dovetails with

777
00:39:09,960 --> 00:39:13,040
Speaker 1: what we already know about how the Trump administration has

778
00:39:13,160 --> 00:39:17,560
Speaker 1: been really hostile to the study of health disparities and

779
00:39:17,640 --> 00:39:20,160
Speaker 1: just sort of calling it kind of like wasteful DEI

780
00:39:20,200 --> 00:39:22,959
Speaker 1: and so information and research that we might have had

781
00:39:23,040 --> 00:39:28,520
Speaker 1: about public health issues and public health needs of women,

782
00:39:28,840 --> 00:39:32,560
Speaker 1: trans folks, queer folks, black folks, that's really being purged

783
00:39:32,600 --> 00:39:35,080
Speaker 1: and shuttered, from the National Institute of Health to the

784
00:39:35,120 --> 00:39:38,319
Speaker 1: CDC to the National Science Foundation. The administration has been

785
00:39:38,360 --> 00:39:41,880
Speaker 1: canceling existing programs and research grants that really make it

786
00:39:41,960 --> 00:39:46,719
Speaker 1: clear that topics like gender disparities are essentially forbidden.

787
00:39:47,239 --> 00:39:49,480
Speaker 2: So the Markup spoke to Paulette.

788
00:39:49,040 --> 00:39:51,279
Speaker 1: Yezi, who was a forty five year old Air Force

789
00:39:51,360 --> 00:39:53,920
Speaker 1: veteran from the Navajo Nation, and she talked about how

790
00:39:53,960 --> 00:39:56,080
Speaker 1: it was difficult enough to be a woman in the military.

791
00:39:56,080 --> 00:39:58,239
Speaker 1: She says, we get harassed, we get bullied, and now

792
00:39:58,280 --> 00:40:01,360
Speaker 1: we are being pushed to the back again. When she

793
00:40:01,600 --> 00:40:05,480
Speaker 1: was told how this AI algorithm was basically prioritizing SIS

794
00:40:05,480 --> 00:40:08,359
Speaker 1: men over everyone else, she started crying. And she talked

795
00:40:08,360 --> 00:40:12,640
Speaker 1: about how she faced constant sexual harassment and unwanted advances

796
00:40:12,719 --> 00:40:14,480
Speaker 1: during a tour in Iraq, to the point where she

797
00:40:14,480 --> 00:40:16,680
Speaker 1: would sleep with her lights on and her door locked

798
00:40:16,680 --> 00:40:19,240
Speaker 1: and a chair up against the door for extra protection.

799
00:40:19,600 --> 00:40:22,799
Speaker 1: During her deployment. They always think about us. Second, this

800
00:40:22,920 --> 00:40:24,440
Speaker 1: is going to cost people's.

801
00:40:24,040 --> 00:40:24,839
Speaker 2: Lives, she said.

802
00:40:24,880 --> 00:40:29,960
Speaker 1: And I just something about that comment really moved me,

803
00:40:30,680 --> 00:40:32,799
Speaker 1: because I think she's right, and I think it just

804
00:40:32,840 --> 00:40:36,320
Speaker 1: goes to show what happens when we rush to deploy

805
00:40:36,440 --> 00:40:40,520
Speaker 1: AI in situations that are life or death. It's very dangerous.

806
00:40:40,560 --> 00:40:43,560
Speaker 1: You know, when we build algorithms on historical data that

807
00:40:43,640 --> 00:40:46,280
Speaker 1: reflect bias, and we train them on a world where

808
00:40:46,520 --> 00:40:49,200
Speaker 1: the only experiences that are sort of taken seriously are

809
00:40:49,640 --> 00:40:52,960
Speaker 1: SIS white men. We're not just replicating bias, we're like

810
00:40:53,200 --> 00:40:56,040
Speaker 1: automating it and scaling it up. And she's right that

811
00:40:56,120 --> 00:40:58,759
Speaker 1: it probably is going to cost people's lives, and I

812
00:40:58,760 --> 00:41:01,359
Speaker 1: think it's just important to remember that we're talking about

813
00:41:01,400 --> 00:41:04,560
Speaker 1: folks who are already marginalized and like making them pay

814
00:41:04,600 --> 00:41:08,080
Speaker 1: an even bigger price. And so yeah, I just think

815
00:41:08,120 --> 00:41:10,680
Speaker 1: that we're it's just another example of the ways that

816
00:41:11,520 --> 00:41:16,440
Speaker 1: rushing to put AI in a decision making capacity in

817
00:41:16,480 --> 00:41:19,680
Speaker 1: this way is really failing people and it's very dangerous.

818
00:41:20,040 --> 00:41:23,200
Speaker 2: Yeah, absolutely, I mean truly just coming on top of

819
00:41:23,360 --> 00:41:26,200
Speaker 2: I mean already a story that is there's so much

820
00:41:26,200 --> 00:41:28,520
Speaker 2: about this that's so heartbreaking on its own, right, Like

821
00:41:28,800 --> 00:41:31,680
Speaker 2: JAZZI like her talking about her experience, like actually being

822
00:41:31,680 --> 00:41:34,000
Speaker 2: in the military, you know, the conversation about how the

823
00:41:34,000 --> 00:41:38,760
Speaker 2: military particularly targets marginalized communities personally.

824
00:41:39,120 --> 00:41:41,600
Speaker 3: I grew up in I grew up around a lot

825
00:41:41,640 --> 00:41:45,200
Speaker 3: of veterans and was at a high school where, like,

826
00:41:45,560 --> 00:41:48,279
Speaker 3: you know, there always was the booth with the like

827
00:41:48,800 --> 00:41:53,280
Speaker 3: two army recruiters trying to get people. Having that experience

828
00:41:53,400 --> 00:41:55,160
Speaker 3: is like, honestly the thing that made me like anti

829
00:41:55,200 --> 00:41:56,960
Speaker 3: military growing up. But I think like a lot of

830
00:41:56,960 --> 00:41:58,480
Speaker 3: people is very similar. I know a lot of like,

831
00:41:59,000 --> 00:42:02,279
Speaker 3: uh truly that I think the way to summer, like

832
00:42:02,440 --> 00:42:05,280
Speaker 3: so much of the AI stories we've been talking about lately.

833
00:42:05,360 --> 00:42:07,040
Speaker 2: It's like an issue.

834
00:42:06,680 --> 00:42:10,960
Speaker 3: That is already like a dumpster fire of a problem,

835
00:42:11,960 --> 00:42:14,000
Speaker 3: and then we're like, let's put AI in there to

836
00:42:14,080 --> 00:42:16,120
Speaker 3: make it a little bit spicier.

837
00:42:16,120 --> 00:42:18,360
Speaker 2: I don't know, Yeah, it's such a good way to

838
00:42:18,400 --> 00:42:18,680
Speaker 2: put it.

839
00:42:18,960 --> 00:42:21,759
Speaker 3: Hey, there's the systemic issue of the fact that it's like, yeah,

840
00:42:21,920 --> 00:42:24,360
Speaker 3: there's so many ways that the yeah, the military, like targets,

841
00:42:24,360 --> 00:42:27,120
Speaker 3: martialized communities, there's ways that like queer people, women and

842
00:42:27,200 --> 00:42:29,719
Speaker 3: whatever are exploited, are not taken seriously when they bring

843
00:42:29,760 --> 00:42:34,120
Speaker 3: these issues forward. And then just now we're yeah, we're

844
00:42:34,120 --> 00:42:37,480
Speaker 3: throwing an AI to say and the narrative that we

845
00:42:37,520 --> 00:42:39,640
Speaker 3: want to hear, which is that the military is for

846
00:42:40,400 --> 00:42:43,040
Speaker 3: sad white men being sad is apparently all that we're

847
00:42:43,040 --> 00:42:43,560
Speaker 3: getting from this.

848
00:42:43,719 --> 00:42:44,160
Speaker 2: I don't know.

849
00:42:44,360 --> 00:42:48,320
Speaker 1: Yeah, And it's being codified and replicated and like entrenched

850
00:42:48,480 --> 00:42:49,320
Speaker 1: using AI.

851
00:42:49,680 --> 00:42:51,359
Speaker 3: And I want to be clear when I say all this,

852
00:42:51,520 --> 00:42:53,640
Speaker 3: like I am like, this is not on the fault

853
00:42:53,640 --> 00:42:56,480
Speaker 3: of veterans, Like this is on the fault of the military,

854
00:42:56,560 --> 00:42:59,359
Speaker 3: and like the system that is in place, and like,

855
00:43:00,239 --> 00:43:02,080
Speaker 3: if you want to be pro veteran, you have to

856
00:43:02,080 --> 00:43:06,720
Speaker 3: be angry about this. Habiting you know, damn right.

857
00:43:07,239 --> 00:43:10,600
Speaker 1: So, speaking of things that I'm angry about, we talked

858
00:43:10,600 --> 00:43:13,200
Speaker 1: a bit last week about what happened in Minnesota where

859
00:43:13,239 --> 00:43:15,920
Speaker 1: Renee Good was shot and killed by an ICE agent

860
00:43:16,040 --> 00:43:19,520
Speaker 1: on camera. Someone has actually set up a go Fundme

861
00:43:19,760 --> 00:43:23,360
Speaker 1: for that agent, Jonathan Ross, who shot Renee Good, even

862
00:43:23,440 --> 00:43:27,799
Speaker 1: though it is against the rules of go fundme. The fundraiser,

863
00:43:27,960 --> 00:43:31,920
Speaker 1: titled Ice Officer Jonathan Ross, seeks at least five hundred

864
00:43:31,920 --> 00:43:34,960
Speaker 1: and fifty thousand dollars to support potential legal expenses for

865
00:43:35,120 --> 00:43:38,640
Speaker 1: the ICE agent identified as having shot and killed Good.

866
00:43:38,800 --> 00:43:43,240
Speaker 1: So this is completely and explicitly against go fundmes terms

867
00:43:43,239 --> 00:43:46,600
Speaker 1: of service. The go fundme campaign's stated purpose, which is

868
00:43:46,719 --> 00:43:50,680
Speaker 1: raising money for legal services followed and killing, directly conflicts

869
00:43:50,719 --> 00:43:53,680
Speaker 1: with go fundmese terms of service, which specifically bars any

870
00:43:53,760 --> 00:43:56,560
Speaker 1: fundraisers that are intended to support the legal defense of

871
00:43:56,600 --> 00:44:00,799
Speaker 1: people accused of violent or financial crimes. So you might

872
00:44:00,840 --> 00:44:03,879
Speaker 1: be asking yourself why is GoFundMe allowing this.

873
00:44:03,880 --> 00:44:04,680
Speaker 2: On their platform.

874
00:44:05,080 --> 00:44:06,520
Speaker 1: The long and short of it is that we don't

875
00:44:06,560 --> 00:44:10,200
Speaker 1: really know. So Wired reports that GoFundMe has not publicly

876
00:44:10,239 --> 00:44:14,279
Speaker 1: explained why the Ross fundraiser remains active despite its terms

877
00:44:14,320 --> 00:44:17,359
Speaker 1: of service. Stating that users agree to not quote use

878
00:44:17,400 --> 00:44:19,960
Speaker 1: the service or platform to raise funds for the legal

879
00:44:19,960 --> 00:44:23,200
Speaker 1: defense of financial and violent crimes, including those related to

880
00:44:23,239 --> 00:44:27,640
Speaker 1: money laundering, murder, robbery, assault, battery, sex crimes, or crimes

881
00:44:27,680 --> 00:44:31,080
Speaker 1: against minors. So Wired was like, let's get to the

882
00:44:31,080 --> 00:44:34,799
Speaker 1: bottom of this. They emailed a GoFundMe spokesperson on Sunday night,

883
00:44:34,920 --> 00:44:37,240
Speaker 1: and go fundme said, oh, we are in the process

884
00:44:37,280 --> 00:44:40,240
Speaker 1: of reviewing all the fundraisers tied to the shooting, saying

885
00:44:40,800 --> 00:44:43,799
Speaker 1: during the review process, all funds remain safely held by

886
00:44:43,800 --> 00:44:47,360
Speaker 1: our payment processors. Go Fundmese terms of service prohibit fundraisers

887
00:44:47,400 --> 00:44:49,760
Speaker 1: that raise money for the legal defense if anybody formally

888
00:44:49,880 --> 00:44:53,640
Speaker 1: charged with a violent crime. Any campaigns that violate this policy.

889
00:44:53,320 --> 00:44:56,600
Speaker 2: Will be removed. So I will say that, as of

890
00:44:56,719 --> 00:45:01,040
Speaker 2: right now, the ICE agent who shot Good has not

891
00:45:01,080 --> 00:45:03,200
Speaker 2: been charged with a crime. And you might have seen JD.

892
00:45:03,320 --> 00:45:07,480
Speaker 1: Vance on television saying that ICE agents had complete immunity.

893
00:45:08,040 --> 00:45:10,400
Speaker 1: I think the law might feel otherwise, but that's what

894
00:45:10,480 --> 00:45:12,839
Speaker 1: JD Vance says. So like, but like, right now, that

895
00:45:12,880 --> 00:45:15,120
Speaker 1: person has not been charged with a crime. So go

896
00:45:15,280 --> 00:45:19,080
Speaker 1: fundme told Wired that they were working directly with Clyde Emmons,

897
00:45:19,080 --> 00:45:21,399
Speaker 1: who was the person who started this fundraiser, to gather

898
00:45:21,440 --> 00:45:25,640
Speaker 1: additional information, so Wired said that on Sunday night, the

899
00:45:25,640 --> 00:45:28,600
Speaker 1: fundraiser said very clearly that the funds were going to

900
00:45:28,640 --> 00:45:31,440
Speaker 1: go to help pay for any legal services the officer needs.

901
00:45:32,000 --> 00:45:36,400
Speaker 1: But because go fundmes rules prohibit fundraisers for legal defenses

902
00:45:36,440 --> 00:45:40,560
Speaker 1: for violent acts, Wired noticed that later the language was

903
00:45:40,640 --> 00:45:44,960
Speaker 1: mysteriously removed after Wired inquired about it, and replaced with

904
00:45:45,040 --> 00:45:48,799
Speaker 1: the phrase funds will go to help him, so not

905
00:45:48,960 --> 00:45:53,560
Speaker 1: help him with legal funds needed to defend himself in

906
00:45:53,640 --> 00:45:56,560
Speaker 1: a you know, because he's committed a violent act, just

907
00:45:56,960 --> 00:46:01,440
Speaker 1: generally help him. Go Fundme did not respond to multiple

908
00:46:01,440 --> 00:46:04,439
Speaker 1: follow up requests for comment, including questions as to whether

909
00:46:04,520 --> 00:46:07,360
Speaker 1: or not the company had advised the organizer to change

910
00:46:07,360 --> 00:46:11,640
Speaker 1: the description to better comport with its rules, and even

911
00:46:11,719 --> 00:46:15,279
Speaker 1: still even though they took off that language that said

912
00:46:15,280 --> 00:46:19,640
Speaker 1: it was a legal defense fundraiser. Despite those changes, several

913
00:46:19,680 --> 00:46:22,000
Speaker 1: slides in a carousel as the top of the ross

914
00:46:22,000 --> 00:46:24,440
Speaker 1: fundraising page that was still active when I checked it

915
00:46:24,440 --> 00:46:28,120
Speaker 1: out before we recorded, make the purpose of the fundraiser

916
00:46:28,400 --> 00:46:32,080
Speaker 1: very clear. Quote give to cover Jonathan's legal defense and

917
00:46:32,480 --> 00:46:36,600
Speaker 1: quote officer Jonathan Ross's legal defense fund pays attorney fees and.

918
00:46:36,680 --> 00:46:39,800
Speaker 2: Court costs, so what the hell go fund me.

919
00:46:39,880 --> 00:46:43,360
Speaker 1: I don't understand why they are bending over backward to

920
00:46:43,440 --> 00:46:47,760
Speaker 1: keep this fundraiser on their platform, especially considering in twenty fifteen,

921
00:46:47,840 --> 00:46:50,399
Speaker 1: after police were charged in the death of Freddie Gray

922
00:46:50,400 --> 00:46:54,920
Speaker 1: and Baltimore, GoFundMe did remove a fundraiser citing a violation

923
00:46:55,120 --> 00:46:58,640
Speaker 1: of its rules against supporting legal defenses in violent cases.

924
00:46:59,120 --> 00:47:01,719
Speaker 1: That same year, they also removed a campaign for a

925
00:47:01,760 --> 00:47:04,560
Speaker 1: South Carolina officer who had been charged in the fatal

926
00:47:04,560 --> 00:47:07,640
Speaker 1: shooting of Walter Scott. So there is a precedent for

927
00:47:07,680 --> 00:47:11,920
Speaker 1: them taking down fundraisers where somebody is raising funds for

928
00:47:12,080 --> 00:47:15,440
Speaker 1: these kinds of acts. When they took down that fundraiser

929
00:47:15,560 --> 00:47:18,480
Speaker 1: for the police officers that killed Freddie Gray, the statement

930
00:47:18,520 --> 00:47:21,879
Speaker 1: they gave to the media was GoFundMe cannot be used

931
00:47:21,880 --> 00:47:24,600
Speaker 1: to benefit those who are charged with serious violations of

932
00:47:24,640 --> 00:47:27,560
Speaker 1: the law. The campaign clearly stated that the money was

933
00:47:27,640 --> 00:47:30,200
Speaker 1: raised was to be used to assist the officers with

934
00:47:30,239 --> 00:47:33,600
Speaker 1: their legal thies, which is a direct violation of gofundme's terms.

935
00:47:34,000 --> 00:47:37,719
Speaker 1: So I really can't understand what has changed, other than

936
00:47:37,760 --> 00:47:41,319
Speaker 1: the fact that I mean, I wonder if they're like, oh, well,

937
00:47:41,360 --> 00:47:44,359
Speaker 1: he hasn't been charged with a crime, so it's still

938
00:47:44,400 --> 00:47:45,920
Speaker 1: fine to have this fundraiser up.

939
00:47:46,120 --> 00:47:48,160
Speaker 2: But if that's the case, he just gets money for

940
00:47:48,239 --> 00:47:50,400
Speaker 2: shooting somebody. That doesn't seem right either.

941
00:47:50,960 --> 00:47:51,440
Speaker 4: This isn't good.

942
00:47:51,520 --> 00:47:53,239
Speaker 2: I'm wondering too, because.

943
00:47:54,880 --> 00:47:58,440
Speaker 3: You brought up both these cases were cops shot unarmed

944
00:47:58,440 --> 00:48:04,560
Speaker 3: people and those those uh those goufundmes were taken down.

945
00:48:04,640 --> 00:48:06,920
Speaker 3: Part of me also is curious, like what are they

946
00:48:06,920 --> 00:48:11,600
Speaker 3: defining as like a violent act because on the flip like,

947
00:48:11,600 --> 00:48:13,439
Speaker 3: like what I'm wondering is like, on the flip side,

948
00:48:13,440 --> 00:48:17,560
Speaker 3: if it was somebody that would head head shot somebody

949
00:48:17,640 --> 00:48:20,040
Speaker 3: like genuinely in self defense, if it was somebody who

950
00:48:20,120 --> 00:48:24,240
Speaker 3: had uh you know, especially if it was a situation

951
00:48:24,800 --> 00:48:27,960
Speaker 3: where somebody was definding themselves against like racist violence or

952
00:48:28,000 --> 00:48:32,680
Speaker 3: misogynistic violence or whatever, like would go fund me take

953
00:48:33,040 --> 00:48:36,440
Speaker 3: that down too because it was a violent act, you know.

954
00:48:36,719 --> 00:48:39,200
Speaker 2: Like part of me like.

955
00:48:38,960 --> 00:48:41,239
Speaker 3: Like reading their policy originally, like part of me is

956
00:48:41,280 --> 00:48:43,160
Speaker 3: sort of like, actually, I'm a little bit conflicted, Like

957
00:48:43,200 --> 00:48:47,080
Speaker 3: I don't like are because because again it's it's and

958
00:48:47,120 --> 00:48:49,680
Speaker 3: I say that because this is the situation of like

959
00:48:49,840 --> 00:48:52,399
Speaker 3: or when we talk about free speech and it's like, well,

960
00:48:52,440 --> 00:48:55,120
Speaker 3: if you're saying we can't do X y Z thing,

961
00:48:55,200 --> 00:48:56,759
Speaker 3: like how far is it going to go until you're

962
00:48:56,840 --> 00:49:02,080
Speaker 3: like saying anything anti government or whatever is dangerous. I

963
00:49:02,080 --> 00:49:03,680
Speaker 3: wonder if it's the same thing here where it's like

964
00:49:03,719 --> 00:49:05,840
Speaker 3: what are they defining as like as a as a

965
00:49:05,920 --> 00:49:07,920
Speaker 3: violent crime, as a whatever.

966
00:49:10,680 --> 00:49:11,680
Speaker 2: Because I guess.

967
00:49:11,520 --> 00:49:13,640
Speaker 3: Obviously, like I I agree where I'm like, this is

968
00:49:13,680 --> 00:49:15,759
Speaker 3: an insane campaign.

969
00:49:17,800 --> 00:49:20,120
Speaker 2: Because again I am petty.

970
00:49:20,239 --> 00:49:23,080
Speaker 3: I do want to take a second assay. Clyde Emmons

971
00:49:23,280 --> 00:49:30,160
Speaker 3: is like the most like bad guy, like western bad

972
00:49:30,280 --> 00:49:35,880
Speaker 3: guy name, like kids cartoon evil man. I'm picturing him

973
00:49:35,920 --> 00:49:38,560
Speaker 3: with like a really weird mustache and amusache.

974
00:49:38,680 --> 00:49:42,400
Speaker 2: Right, he's got a twisty mussash. He like, Like.

975
00:49:42,360 --> 00:49:45,080
Speaker 3: I just that is an insane name. But yeah, no,

976
00:49:45,200 --> 00:49:50,160
Speaker 3: like I agree, I think like it's bad obviously that

977
00:49:50,200 --> 00:49:52,440
Speaker 3: this is this does exist, that there's a bud raiser.

978
00:49:52,680 --> 00:49:56,120
Speaker 3: It's really disheartening to see that people are, you know,

979
00:49:56,480 --> 00:49:57,120
Speaker 3: cheering this on.

980
00:49:57,440 --> 00:49:58,399
Speaker 2: I know as happy I.

981
00:49:58,320 --> 00:50:01,040
Speaker 3: Know that that there is like you know, people seeing

982
00:50:01,120 --> 00:50:04,080
Speaker 3: what happened last week and having a very very different

983
00:50:04,200 --> 00:50:05,920
Speaker 3: response to it than what I did. But it's like

984
00:50:06,040 --> 00:50:10,080
Speaker 3: sad to see that illustrated in this way. But yeah,

985
00:50:10,080 --> 00:50:12,200
Speaker 3: at the same time, it does kind of make me wonder,

986
00:50:12,320 --> 00:50:14,640
Speaker 3: like what's happening on the go fund side, where like

987
00:50:14,640 --> 00:50:16,840
Speaker 3: who's who gets to determine this, Like who has to

988
00:50:16,920 --> 00:50:18,960
Speaker 3: determine whether or not if this gets taken out or not.

989
00:50:19,640 --> 00:50:22,759
Speaker 1: Yeah, that's my big question, and it makes complete sense

990
00:50:22,760 --> 00:50:25,680
Speaker 1: to me. And I just wonder if, like we've seen

991
00:50:25,719 --> 00:50:29,360
Speaker 1: with so many other tech companies, if they're just taking

992
00:50:29,400 --> 00:50:33,480
Speaker 1: their cues from the administration, if they're just trying to

993
00:50:33,840 --> 00:50:38,760
Speaker 1: you know, Yeah, I think that we're in a weird

994
00:50:38,920 --> 00:50:41,879
Speaker 1: time where it seems clear to me that a lot

995
00:50:41,880 --> 00:50:47,520
Speaker 1: of organizations are invested in selectively picking and choosing when

996
00:50:47,840 --> 00:50:49,839
Speaker 1: their terms of services applied, and like.

997
00:50:51,239 --> 00:50:54,040
Speaker 2: It concerns me greatly, definitely.

998
00:50:55,760 --> 00:50:57,640
Speaker 3: Appears to be a theme of this episode, you know,

999
00:50:59,120 --> 00:51:01,080
Speaker 3: And this is why I I think it is okay

1000
00:51:01,320 --> 00:51:03,960
Speaker 3: that I never do read the terms and services because

1001
00:51:04,000 --> 00:51:09,240
Speaker 3: apparently they don't apply anyways, So it's really not my fault.

1002
00:51:09,320 --> 00:51:11,080
Speaker 2: And even though I do know that I.

1003
00:51:11,080 --> 00:51:14,280
Speaker 3: Probably should sit down and actually look at these things,

1004
00:51:14,320 --> 00:51:19,080
Speaker 3: that I'm falling for the corporate tactic of just throwing

1005
00:51:19,080 --> 00:51:20,640
Speaker 3: a bunch of stuff at you and ignoring it and

1006
00:51:20,719 --> 00:51:23,360
Speaker 3: just saying yes anyways because it's too But also apparently

1007
00:51:23,360 --> 00:51:24,360
Speaker 3: it doesn't matter anyway.

1008
00:51:24,640 --> 00:51:31,280
Speaker 2: So maybe being lazy is the real thing that helps

1009
00:51:31,520 --> 00:51:33,879
Speaker 2: you win. At the end of the day, I don't

1010
00:51:33,880 --> 00:51:36,640
Speaker 2: know where I'm going with this. Listeners, please don't take

1011
00:51:36,640 --> 00:51:41,000
Speaker 2: advice for me again. Ever, that's a terrible idea.

1012
00:51:41,840 --> 00:51:54,879
Speaker 4: Let's take a quick break at her back.

1013
00:51:57,600 --> 00:52:00,400
Speaker 1: Well, I actually cannot wait to get your thought on

1014
00:52:00,560 --> 00:52:02,080
Speaker 1: the last thing I wanted to talk about.

1015
00:52:02,480 --> 00:52:04,000
Speaker 2: Okay, So this story was.

1016
00:52:03,960 --> 00:52:07,759
Speaker 1: Published by The Lookout, an investigative, nonprofit news organization that

1017
00:52:07,800 --> 00:52:10,520
Speaker 1: covers Arizona's LGBTQ plus community.

1018
00:52:10,960 --> 00:52:13,600
Speaker 2: So there is a bar in Phoenix called.

1019
00:52:13,520 --> 00:52:16,680
Speaker 1: Stacy's at Melrose is an LGBTQ plus bar.

1020
00:52:16,920 --> 00:52:18,040
Speaker 2: Caveat to what I said before.

1021
00:52:18,040 --> 00:52:20,319
Speaker 3: Actually, if there's anything you're gonna take advice for me from,

1022
00:52:20,360 --> 00:52:21,959
Speaker 3: it's probably day bars.

1023
00:52:21,960 --> 00:52:24,800
Speaker 2: That's the only thing I like. That guy's gonna say, Yeah,

1024
00:52:25,000 --> 00:52:29,000
Speaker 2: you know all all the good spots in Brooklyn, thank you.

1025
00:52:29,280 --> 00:52:31,040
Speaker 3: We'll do an episode at some point that's just the

1026
00:52:31,040 --> 00:52:36,640
Speaker 3: Bridge and Joey reviewing every single gay, queer, queer adjacent

1027
00:52:36,680 --> 00:52:41,400
Speaker 3: bar in the eastern Brooklyn area.

1028
00:52:41,440 --> 00:52:45,400
Speaker 2: I'm gonna start calling it that now. But yes, Stacy's

1029
00:52:45,400 --> 00:52:49,759
Speaker 2: at Melrose. Tell me more so, Stacy's at Melrose. They

1030
00:52:49,880 --> 00:52:51,000
Speaker 2: are rolling out.

1031
00:52:51,160 --> 00:52:55,399
Speaker 1: Kind of a sassy AI chatbot, and it doesn't sound

1032
00:52:55,400 --> 00:52:57,279
Speaker 1: what the community is thrilled about it. I'll put it

1033
00:52:57,280 --> 00:52:57,680
Speaker 1: that way.

1034
00:52:57,800 --> 00:52:58,040
Speaker 5: Yeah.

1035
00:52:58,200 --> 00:52:58,719
Speaker 4: Sorry.

1036
00:52:58,880 --> 00:53:01,880
Speaker 3: If there's any community that I'm like, I'm proud of us.

1037
00:53:02,000 --> 00:53:04,960
Speaker 2: We have held our stance against AI, it's they. It's

1038
00:53:05,000 --> 00:53:08,600
Speaker 2: the gay community. Like I, there's a lot of stuff

1039
00:53:08,640 --> 00:53:09,280
Speaker 2: that we.

1040
00:53:09,400 --> 00:53:12,680
Speaker 3: I think have some error community issues we got to

1041
00:53:12,760 --> 00:53:14,680
Speaker 3: work out. But I do feel like gay people have

1042
00:53:14,760 --> 00:53:17,960
Speaker 3: been pretty ante. Maybe this is just me being biased

1043
00:53:18,000 --> 00:53:19,920
Speaker 3: from like the people in my life, but yeah, no,

1044
00:53:20,040 --> 00:53:22,719
Speaker 3: this doesn't seem like the group the community you want

1045
00:53:22,719 --> 00:53:23,759
Speaker 3: to be, Like, guy's.

1046
00:53:23,480 --> 00:53:25,640
Speaker 2: Cool, cool AI thing to look at.

1047
00:53:25,680 --> 00:53:26,160
Speaker 5: I don't know.

1048
00:53:26,520 --> 00:53:28,680
Speaker 2: No, people are not happy about it.

1049
00:53:28,760 --> 00:53:32,279
Speaker 3: Historically, gay people hate making art on their own from

1050
00:53:32,800 --> 00:53:33,920
Speaker 3: Yeah okay.

1051
00:53:33,960 --> 00:53:36,399
Speaker 1: So in early January, the bar put up a post

1052
00:53:36,400 --> 00:53:39,960
Speaker 1: on Instagram announcing their chatbot, which is powered by Google Gemini,

1053
00:53:40,200 --> 00:53:44,640
Speaker 1: named Mother. The post reads, She's learning, she's listening, She's

1054
00:53:44,680 --> 00:53:45,319
Speaker 1: almost here.

1055
00:53:46,200 --> 00:53:46,439
Speaker 3: Mother.

1056
00:53:46,800 --> 00:53:49,719
Speaker 2: No, it's Mother with no E. This just help you

1057
00:53:49,880 --> 00:53:51,840
Speaker 2: picture it. I hate that so much.

1058
00:53:52,560 --> 00:53:52,880
Speaker 3: Come on.

1059
00:53:55,680 --> 00:53:57,359
Speaker 2: Yeah, it's it's better with no E.

1060
00:53:57,960 --> 00:54:01,719
Speaker 1: So Mother is already helping with our staff schedules, side work,

1061
00:54:01,760 --> 00:54:05,279
Speaker 1: internal tools, and website updates. Soon she'll be live for

1062
00:54:05,360 --> 00:54:08,719
Speaker 1: performers and guests, answering questions about events, shows, drinks, and

1063
00:54:08,760 --> 00:54:12,160
Speaker 1: all things. Stacy's new tools, Same Heart, designed for our

1064
00:54:12,160 --> 00:54:13,359
Speaker 1: community by us.

1065
00:54:13,440 --> 00:54:15,600
Speaker 3: The post reads, bridget I know you don't get this

1066
00:54:15,640 --> 00:54:17,680
Speaker 3: reference because we talked about this off Mike at a

1067
00:54:17,719 --> 00:54:23,360
Speaker 3: previous episode, But I am picturing Motherboard from Cyberchase to

1068
00:54:23,560 --> 00:54:24,880
Speaker 3: my fellow.

1069
00:54:24,640 --> 00:54:28,719
Speaker 2: PBS Kids people back in the day, shout out.

1070
00:54:28,719 --> 00:54:33,120
Speaker 3: Cyberchase was a foundational piece of media for me as

1071
00:54:33,120 --> 00:54:36,400
Speaker 3: a child. But yeah, if you know, you know, bridge

1072
00:54:36,400 --> 00:54:40,120
Speaker 3: In apparently just is not familiar with the show that one.

1073
00:54:40,440 --> 00:54:42,600
Speaker 2: I missed that one. This was an older gend the

1074
00:54:43,160 --> 00:54:44,879
Speaker 2: like era TV show.

1075
00:54:44,920 --> 00:54:49,000
Speaker 3: Again, PBS Kids, shout out to everybody else, all of

1076
00:54:49,040 --> 00:54:52,880
Speaker 3: the other gay people listening that were that were shaped

1077
00:54:52,880 --> 00:54:53,719
Speaker 3: by that TV show.

1078
00:54:54,840 --> 00:54:57,680
Speaker 2: But yes, continue, it actually might have.

1079
00:54:57,640 --> 00:55:00,880
Speaker 1: Been better received had it been based on the for

1080
00:55:00,920 --> 00:55:02,839
Speaker 1: real I was gonna say, my friend did like a

1081
00:55:02,960 --> 00:55:06,279
Speaker 1: drag version of Mother or of the Mother of the

1082
00:55:06,320 --> 00:55:09,279
Speaker 1: Motherboard from Cyberchase for Halloween last year and it was

1083
00:55:09,360 --> 00:55:11,000
Speaker 1: like one of my favorite costumes that I saw.

1084
00:55:11,239 --> 00:55:13,040
Speaker 2: So it has a sassy tone.

1085
00:55:13,440 --> 00:55:16,120
Speaker 1: It kind of compare it to it sounding like a

1086
00:55:16,160 --> 00:55:20,400
Speaker 1: tongue in chic drag Queen MC as opposed to just

1087
00:55:20,440 --> 00:55:22,920
Speaker 1: like a regular monotone chatbot.

1088
00:55:23,200 --> 00:55:27,280
Speaker 2: People are not thrilled as Lookout Rights quote. Since the announcement,

1089
00:55:27,320 --> 00:55:30,759
Speaker 2: community members online have turned against Stacy's and criticized their

1090
00:55:30,800 --> 00:55:34,000
Speaker 2: decision to install an AI based chatbot. They argue that

1091
00:55:34,120 --> 00:55:38,319
Speaker 2: queer spaces should be sensitive to, if not downright eradicate

1092
00:55:38,480 --> 00:55:42,400
Speaker 2: using the technology. On January ninth, community members gathered outside

1093
00:55:42,400 --> 00:55:45,840
Speaker 2: of Stacy's to protest the bar's decision, with a goal

1094
00:55:46,000 --> 00:55:49,239
Speaker 2: to pack the bar. So people aren't happy. People aren't

1095
00:55:49,280 --> 00:55:49,560
Speaker 2: having it.

1096
00:55:49,560 --> 00:55:51,040
Speaker 1: I went to their Instagram and a lot of the

1097
00:55:51,040 --> 00:55:53,920
Speaker 1: cops they did the thing where the comments are turned

1098
00:55:53,960 --> 00:55:58,200
Speaker 1: off kind of globally now, I think. But the posts

1099
00:55:58,200 --> 00:56:01,480
Speaker 1: about the AI didn't have comments, and so people be

1100
00:56:01,520 --> 00:56:04,000
Speaker 1: like commenting on other posts that have nothing to do

1101
00:56:04,040 --> 00:56:05,960
Speaker 1: with the AI, like, hey, you're gonna address the AI,

1102
00:56:06,640 --> 00:56:10,440
Speaker 1: so I will say. The bar did respond with like

1103
00:56:10,480 --> 00:56:14,719
Speaker 1: a pretty meaty statement on their website basically saying that

1104
00:56:14,760 --> 00:56:16,719
Speaker 1: they believe that AI is the future, and they're trying

1105
00:56:16,760 --> 00:56:20,520
Speaker 1: to embrace it. Here's here's what that statement says. Let's

1106
00:56:20,520 --> 00:56:22,319
Speaker 1: start with the reality of the world we lit in.

1107
00:56:22,680 --> 00:56:25,799
Speaker 1: We are currently navigating a technological shift as significant as

1108
00:56:25,840 --> 00:56:29,040
Speaker 1: the invention of the Internet. An estimated sixty three percent

1109
00:56:29,040 --> 00:56:31,799
Speaker 1: of businesses worldwide plan to adopt AI within the next

1110
00:56:31,880 --> 00:56:35,319
Speaker 1: three years. Large companies, ninety two percent of them, are

1111
00:56:35,360 --> 00:56:38,640
Speaker 1: already ramping up their AI investments to dominate the market.

1112
00:56:39,080 --> 00:56:44,240
Speaker 1: Expecting a small, independent business to ignore this shift is unrealistic. Worse,

1113
00:56:44,400 --> 00:56:47,879
Speaker 1: prohibiting the adoption of emerging technology creates a divide, one

1114
00:56:47,880 --> 00:56:52,080
Speaker 1: where marginalized communities are left behind economically while major corporations

1115
00:56:52,120 --> 00:56:52,840
Speaker 1: reap the benefit.

1116
00:56:52,960 --> 00:56:57,520
Speaker 2: It's a bar what yeah, sorry, you continue the sentence

1117
00:56:57,560 --> 00:56:59,040
Speaker 2: of that all, get my thoughts? Yeah yeah.

1118
00:56:59,520 --> 00:57:02,480
Speaker 1: If only the big chains are allowed to leverage these tools,

1119
00:57:02,560 --> 00:57:05,400
Speaker 1: independent queer spaces will not be able to compete.

1120
00:57:05,600 --> 00:57:08,799
Speaker 2: We'd refuse to let that happen. Sorry, your thoughts all right? Sorry?

1121
00:57:09,000 --> 00:57:12,040
Speaker 2: Take us it back. What big chains are putting AI? Also,

1122
00:57:12,160 --> 00:57:15,600
Speaker 2: what big chain bars are you talking about? First of all?

1123
00:57:15,719 --> 00:57:20,280
Speaker 3: Second of all, has anybody reacted positively to any food

1124
00:57:20,480 --> 00:57:22,800
Speaker 3: or drink establishment putting AI?

1125
00:57:23,160 --> 00:57:24,880
Speaker 2: In their like, I feel like.

1126
00:57:25,160 --> 00:57:27,240
Speaker 3: What we've been getting for the past couple months is

1127
00:57:27,240 --> 00:57:28,280
Speaker 3: that people don't like that.

1128
00:57:30,480 --> 00:57:31,320
Speaker 2: You know what, There's a.

1129
00:57:31,320 --> 00:57:33,680
Speaker 3: Reason that I usually go to gay bars. There's a

1130
00:57:33,720 --> 00:57:35,880
Speaker 3: lot of things about gay bars that I really appreciate.

1131
00:57:35,920 --> 00:57:38,080
Speaker 3: There's better music, and it's not like I go to

1132
00:57:38,120 --> 00:57:41,720
Speaker 3: gay bars and I'm like, god, damn it. I loved

1133
00:57:41,800 --> 00:57:44,600
Speaker 3: that at the straight bar across the street, I was

1134
00:57:44,600 --> 00:57:47,480
Speaker 3: getting hit on every three seconds, despite the fact that

1135
00:57:47,880 --> 00:57:49,520
Speaker 3: I kind of.

1136
00:57:49,520 --> 00:57:51,040
Speaker 2: Dressed like a twelve year old boy.

1137
00:57:52,240 --> 00:57:55,080
Speaker 3: I really wish I was having that experience here, Like,

1138
00:57:55,280 --> 00:57:57,360
Speaker 3: I feel like this is similar where I'm like, you

1139
00:57:57,400 --> 00:57:59,800
Speaker 3: know what, if the if the straight world is going

1140
00:57:59,840 --> 00:58:03,400
Speaker 3: to be on board with AI, I'm coming to the

1141
00:58:03,480 --> 00:58:04,960
Speaker 3: space to escape from that.

1142
00:58:05,960 --> 00:58:06,440
Speaker 2: I don't know.

1143
00:58:06,840 --> 00:58:10,040
Speaker 1: No, that's such a good point of like the in

1144
00:58:10,080 --> 00:58:12,640
Speaker 1: the statement that they're like, well, do you only want

1145
00:58:13,080 --> 00:58:17,040
Speaker 1: the main like the mainstream establishments to have AI. Yeah, sure,

1146
00:58:17,200 --> 00:58:20,320
Speaker 1: all queer spaces, but yeah, underscorees that I do think that, like,

1147
00:58:20,440 --> 00:58:24,520
Speaker 1: queer spaces are different, and you know, the expectation should

1148
00:58:24,520 --> 00:58:24,920
Speaker 1: be different.

1149
00:58:25,040 --> 00:58:28,000
Speaker 3: As we all know, we historically, like the queer community,

1150
00:58:28,000 --> 00:58:30,160
Speaker 3: our whole thing has been saying, well, everybody else is

1151
00:58:30,200 --> 00:58:32,000
Speaker 3: doing it, so we should do that exact same thing

1152
00:58:32,120 --> 00:58:35,040
Speaker 3: and make that exact same space happen in this space

1153
00:58:35,080 --> 00:58:38,160
Speaker 3: that is for us, Like, I just what's the logic here?

1154
00:58:38,400 --> 00:58:42,880
Speaker 3: Are we going to start pouring normally portion drinks and

1155
00:58:42,920 --> 00:58:45,120
Speaker 3: not drinks that are about seventy percent.

1156
00:58:44,840 --> 00:58:47,320
Speaker 2: Alcohol and like a couple drops of mixer in there?

1157
00:58:47,560 --> 00:58:49,760
Speaker 2: Because that is straight people are doing. God it hope

1158
00:58:49,800 --> 00:58:52,960
Speaker 2: not like sorry, that's the reason I'm showing it. That's

1159
00:58:52,960 --> 00:58:55,960
Speaker 2: the reason I can. I gues be mad at me.

1160
00:58:56,000 --> 00:58:57,600
Speaker 3: I am the person that brings my straight friends to

1161
00:58:57,640 --> 00:58:59,760
Speaker 3: the gay barb and also you all are doing it too,

1162
00:58:59,800 --> 00:59:01,440
Speaker 3: so I don't care. But anyways, I was gonna say,

1163
00:59:01,440 --> 00:59:03,000
Speaker 3: that's how I bring my that's how I convinced my

1164
00:59:03,040 --> 00:59:04,640
Speaker 3: straight friends come with me. As I'm like, and you're

1165
00:59:04,680 --> 00:59:06,439
Speaker 3: gonna get drunk off of one drink and you're gonna

1166
00:59:06,440 --> 00:59:10,040
Speaker 3: have a great time. I'm just saying, maybe the reason

1167
00:59:10,040 --> 00:59:12,880
Speaker 3: of the straight people are doing it is it exactly

1168
00:59:13,000 --> 00:59:15,800
Speaker 3: what we think in it, Like, maybe that's not the

1169
00:59:16,280 --> 00:59:18,000
Speaker 3: argument that we think it is here.

1170
00:59:18,320 --> 00:59:22,560
Speaker 2: Yes, this literally this feels like a horror movie. This

1171
00:59:22,600 --> 00:59:24,240
Speaker 2: feels like a parody of a horror movie.

1172
00:59:24,640 --> 00:59:26,880
Speaker 3: Like two thousand and one Space Odyssey, but it takes

1173
00:59:26,920 --> 00:59:29,400
Speaker 3: place in a gay bar, and like the AI would

1174
00:59:29,400 --> 00:59:32,520
Speaker 3: be called Mother instead of how like what we couldn't

1175
00:59:32,560 --> 00:59:33,280
Speaker 3: have called it Megan?

1176
00:59:33,560 --> 00:59:36,920
Speaker 2: Like I don't that was right there? Thank you?

1177
00:59:37,000 --> 00:59:40,120
Speaker 1: Oh yeah, I'm Meghan And she was kind of you know,

1178
00:59:40,280 --> 00:59:41,880
Speaker 1: she has a lot of sass tour.

1179
00:59:42,200 --> 00:59:43,520
Speaker 2: I might be on board with it. If they had

1180
00:59:43,560 --> 00:59:46,600
Speaker 2: modeled after Megan, I might be on board with it exactly.

1181
00:59:46,800 --> 00:59:48,240
Speaker 3: I was like, if you put it, there were so

1182
00:59:48,280 --> 00:59:51,080
Speaker 3: many ways you could have made this funny and no, I.

1183
00:59:51,040 --> 00:59:54,960
Speaker 1: Will say the lookout talk to the co owner, Brandon Slayton,

1184
00:59:55,360 --> 00:59:57,680
Speaker 1: and you know, I was thinking, like, what's going on

1185
00:59:57,720 --> 00:59:59,560
Speaker 1: at this bar? Is that they need to have an

1186
00:59:59,600 --> 01:00:02,080
Speaker 1: AI chatbos that that's going to be the most efficient

1187
01:00:02,080 --> 01:00:02,920
Speaker 1: way to communicate.

1188
01:00:02,920 --> 01:00:06,400
Speaker 2: In fact, it's like, what's going on?

1189
01:00:06,680 --> 01:00:08,880
Speaker 1: I will say that He said that they needed a

1190
01:00:08,960 --> 01:00:12,240
Speaker 1: more efficient system because they have different events happening throughout

1191
01:00:12,280 --> 01:00:15,360
Speaker 1: the week, different drink specials, things like that, that keeping

1192
01:00:15,360 --> 01:00:18,360
Speaker 1: the website updated was becoming a real headache.

1193
01:00:18,560 --> 01:00:19,200
Speaker 4: Kind of much.

1194
01:00:19,360 --> 01:00:21,400
Speaker 2: I don't know. I mean, I'm such a luttite.

1195
01:00:21,920 --> 01:00:25,680
Speaker 1: When during COVID, when a lot of restaurants switched over

1196
01:00:25,800 --> 01:00:28,640
Speaker 1: to like QR code menus instead of paper menus, which

1197
01:00:28,680 --> 01:00:31,080
Speaker 1: I cannot stand as one of my biggest pet peeks.

1198
01:00:31,120 --> 01:00:31,680
Speaker 4: I hate it.

1199
01:00:31,680 --> 01:00:32,920
Speaker 2: It's so bad. Yeah.

1200
01:00:33,080 --> 01:00:34,720
Speaker 1: I once got into it at a restaurant where they

1201
01:00:34,720 --> 01:00:37,480
Speaker 1: were like, oh, yeah, it's hard to update the specials

1202
01:00:37,480 --> 01:00:40,120
Speaker 1: all the time, so you know, we use the QR code,

1203
01:00:40,200 --> 01:00:41,400
Speaker 1: where I was like, I used to come in here

1204
01:00:41,400 --> 01:00:43,040
Speaker 1: all the time and it was a paper menu, So

1205
01:00:43,120 --> 01:00:45,360
Speaker 1: like was like, was that so hard?

1206
01:00:45,600 --> 01:00:46,000
Speaker 2: I don't know.

1207
01:00:46,040 --> 01:00:48,360
Speaker 1: I on the one hand, I see his point that,

1208
01:00:48,480 --> 01:00:51,720
Speaker 1: like upitting the website every time might be a pain,

1209
01:00:52,040 --> 01:00:56,120
Speaker 1: but I don't know, building a sassy gay bar chat

1210
01:00:56,200 --> 01:00:59,560
Speaker 1: bot is that really the most efficient thing?

1211
01:00:59,600 --> 01:01:02,360
Speaker 3: I don't This is also where I'm like, I never

1212
01:01:02,400 --> 01:01:03,840
Speaker 3: want to be one of those people that's like people

1213
01:01:03,840 --> 01:01:05,920
Speaker 3: don't work anymore, like nobody wants to do their jobs.

1214
01:01:05,960 --> 01:01:07,840
Speaker 3: But this is one of those situations where I'm like,

1215
01:01:08,360 --> 01:01:13,400
Speaker 3: you can't update a drinks list on your website, like seriously, Like, yeah,

1216
01:01:13,440 --> 01:01:14,600
Speaker 3: that's annoying, but it's.

1217
01:01:14,640 --> 01:01:16,320
Speaker 2: You would need AI to do that for you.

1218
01:01:16,680 --> 01:01:20,200
Speaker 1: Right to your point when you update the website just

1219
01:01:20,240 --> 01:01:21,920
Speaker 1: on your own as a human who knows what's going

1220
01:01:21,960 --> 01:01:26,400
Speaker 1: out at the bar, pretty low likelihood for human error.

1221
01:01:26,720 --> 01:01:28,920
Speaker 1: I have a feeling that this chatbot is going to

1222
01:01:29,000 --> 01:01:32,600
Speaker 1: give out so many hallucinations about what's happening at this bar.

1223
01:01:33,200 --> 01:01:34,720
Speaker 1: I have a feeling when when they roll it out,

1224
01:01:34,760 --> 01:01:37,280
Speaker 1: they're gonna be like, I don't know about this exactly.

1225
01:01:37,480 --> 01:01:39,440
Speaker 2: I was like too, I'm thinking about like the people.

1226
01:01:39,120 --> 01:01:41,120
Speaker 3: That I know that work in like nightlife and have

1227
01:01:41,240 --> 01:01:43,560
Speaker 3: worked at bars and have worked it and like events

1228
01:01:43,600 --> 01:01:46,080
Speaker 3: planning and stuff like that. Like, yes, there's a lot

1229
01:01:46,120 --> 01:01:48,480
Speaker 3: of work that goes into that, But what you were saying,

1230
01:01:48,600 --> 01:01:53,680
Speaker 3: I don't necessarily trust a like chat GPT.

1231
01:01:54,320 --> 01:01:55,360
Speaker 2: Let me put it this way.

1232
01:01:55,480 --> 01:01:58,880
Speaker 3: It is already so confusing to find out when and

1233
01:01:58,960 --> 01:02:01,360
Speaker 3: I'll drop this now, and I'll say this now, as

1234
01:02:01,360 --> 01:02:05,000
Speaker 3: somebody who is like a just starting out drag performer

1235
01:02:05,800 --> 01:02:08,440
Speaker 3: is already so hard to find information about this stuff.

1236
01:02:08,720 --> 01:02:10,840
Speaker 3: AI is going to make it. Have you googled anything

1237
01:02:10,920 --> 01:02:12,440
Speaker 3: lately and tried to find an info on it. It

1238
01:02:12,480 --> 01:02:14,240
Speaker 3: doesn't make it easier, it makes it worse.

1239
01:02:14,600 --> 01:02:16,280
Speaker 2: I don't know. This story is so bad.

1240
01:02:16,280 --> 01:02:18,120
Speaker 3: I just I'm glad we ended on this so that

1241
01:02:18,200 --> 01:02:19,800
Speaker 3: I at least have something I can like kind of

1242
01:02:19,880 --> 01:02:20,320
Speaker 3: laugh at.

1243
01:02:20,400 --> 01:02:24,160
Speaker 2: But this is like I think just because this is

1244
01:02:24,200 --> 01:02:26,240
Speaker 2: the world that I'm probably like closest to that.

1245
01:02:26,280 --> 01:02:28,600
Speaker 3: I'm like, yeah, I know people that work at these

1246
01:02:28,600 --> 01:02:30,640
Speaker 3: type of bars, but perform at these type of bars.

1247
01:02:30,840 --> 01:02:34,480
Speaker 3: I'm a frequent you know, customer at these places.

1248
01:02:35,200 --> 01:02:40,160
Speaker 1: Why just why you know what I just realized if

1249
01:02:40,160 --> 01:02:43,600
Speaker 1: we because the transcript of this episode, if it gets

1250
01:02:43,600 --> 01:02:50,200
Speaker 1: scraped by AI, because you talked about doing drag performances

1251
01:02:50,240 --> 01:02:54,000
Speaker 1: and Arizona and commented on Stacy's. I wonder if mother

1252
01:02:54,040 --> 01:02:56,560
Speaker 1: will be like, come see Joey at our butt Stacy's

1253
01:02:56,600 --> 01:02:58,040
Speaker 1: in Arizona.

1254
01:02:57,400 --> 01:03:01,360
Speaker 3: Come see Joey Pat, Come see Joey had Stacy's in Arizona.

1255
01:03:01,480 --> 01:03:03,120
Speaker 3: Just I'm just gonna say that over and over again

1256
01:03:03,200 --> 01:03:05,200
Speaker 3: so I can mess up this particular and then a

1257
01:03:05,240 --> 01:03:07,280
Speaker 3: bunch of brandom people in Arizona are gonna be like,

1258
01:03:07,320 --> 01:03:08,400
Speaker 3: who's Joey Pat.

1259
01:03:08,880 --> 01:03:09,920
Speaker 5: Yeah.

1260
01:03:10,000 --> 01:03:12,480
Speaker 3: I've always wanted to be kind of a cryptid like figure,

1261
01:03:12,640 --> 01:03:15,560
Speaker 3: so I'm glad that that can finally happen through this AI. Sorry, actually,

1262
01:03:15,560 --> 01:03:17,160
Speaker 3: never mind, I've changed my I've changed my mind. I'm

1263
01:03:17,160 --> 01:03:19,080
Speaker 3: actually very very pro this AI. If it can turn

1264
01:03:19,120 --> 01:03:22,640
Speaker 3: me into a cryptid of the Arizona gay bar scene.

1265
01:03:22,800 --> 01:03:23,760
Speaker 2: Oh you know, it's funny.

1266
01:03:23,920 --> 01:03:28,880
Speaker 1: I read RuPaul's memoir and RuPaul writes about in the

1267
01:03:28,920 --> 01:03:31,800
Speaker 1: early days, just got a bunch of posters printed that

1268
01:03:31,840 --> 01:03:33,120
Speaker 1: said who is RuPaul?

1269
01:03:33,160 --> 01:03:34,760
Speaker 2: Who is rue Paul? Who is RuPaul?

1270
01:03:35,040 --> 01:03:39,400
Speaker 1: To like drum up buzz and like who is this figure?

1271
01:03:39,480 --> 01:03:40,800
Speaker 1: So yeah, this will be your branding.

1272
01:03:40,800 --> 01:03:43,320
Speaker 3: This will be my branding exactly, you know, I will say,

1273
01:03:43,560 --> 01:03:46,680
Speaker 3: and the end of Zubisod, We're gonna get to my socials,

1274
01:03:46,720 --> 01:03:49,920
Speaker 3: but I bridge it's you know, all of my socials

1275
01:03:49,960 --> 01:03:52,760
Speaker 3: are Pat Pratt. And that has been great branding for

1276
01:03:52,840 --> 01:03:55,880
Speaker 3: me because whenever people mess up my name, I got

1277
01:03:55,880 --> 01:03:58,800
Speaker 3: to be like, actually follow me on Instagram, so I

1278
01:03:58,800 --> 01:04:00,720
Speaker 3: don't know, maybe make a if you can make a

1279
01:04:00,800 --> 01:04:05,160
Speaker 3: joke out of your name that people mispronounce somehow, or

1280
01:04:05,440 --> 01:04:07,680
Speaker 3: like just be like who the fuck is this person?

1281
01:04:11,360 --> 01:04:14,040
Speaker 3: It's a great branding tactic. It's all is all I'll say.

1282
01:04:14,120 --> 01:04:18,760
Speaker 3: So yeah, Joey pat Arizona Stacy's Bar. I'm just gonna

1283
01:04:18,760 --> 01:04:20,920
Speaker 3: say that over and over again until the er like

1284
01:04:21,400 --> 01:04:24,240
Speaker 3: Joey pat Arizona Stacy's Bar, drag performance.

1285
01:04:24,360 --> 01:04:27,080
Speaker 2: We're manifesting it, We're making it happen.

1286
01:04:27,920 --> 01:04:30,560
Speaker 3: It's a tough world out here. It's a tough world

1287
01:04:30,560 --> 01:04:32,320
Speaker 3: out here, guys. We got to do whatever we can

1288
01:04:32,400 --> 01:04:33,840
Speaker 3: to get a leg up, so let's go.

1289
01:04:34,560 --> 01:04:37,040
Speaker 2: Well, Joey, this has been delightful.

1290
01:04:37,600 --> 01:04:39,960
Speaker 1: I'll be seeing you at your performance at Stacy's and

1291
01:04:39,960 --> 01:04:44,280
Speaker 1: Aera of course. Until then, how can folks keep up

1292
01:04:44,320 --> 01:04:46,360
Speaker 1: with you? And what have you got going on?

1293
01:04:46,760 --> 01:04:48,120
Speaker 2: Yeah?

1294
01:04:48,240 --> 01:04:51,800
Speaker 3: Thanks so much for having me, bridget a blest as always,

1295
01:04:52,760 --> 01:04:55,720
Speaker 3: looking forward to seeing you in Arizona again.

1296
01:04:56,200 --> 01:04:57,760
Speaker 2: And yeah you can. As I said, you.

1297
01:04:57,720 --> 01:05:02,880
Speaker 3: Can find me online on Instagram on basically any social

1298
01:05:02,920 --> 01:05:06,880
Speaker 3: media platform at Patna Pratt with the exception of TikTok TikTok.

1299
01:05:06,920 --> 01:05:09,600
Speaker 3: I am a hot topic Dad that is hot topic

1300
01:05:09,640 --> 01:05:13,200
Speaker 3: like the store and then dad like the father figure. Otherwise,

1301
01:05:13,240 --> 01:05:17,000
Speaker 3: you can hear my work on this show. You can

1302
01:05:17,040 --> 01:05:19,920
Speaker 3: also check out some of the work I do. I

1303
01:05:19,960 --> 01:05:22,320
Speaker 3: am a producer for the Outspoken Slate here at iHeart

1304
01:05:22,360 --> 01:05:26,560
Speaker 3: so you can listen to Outlaws with Ts Madison. Ts

1305
01:05:26,600 --> 01:05:29,040
Speaker 3: Madison also going to make an appearance at Stacy's. We

1306
01:05:29,080 --> 01:05:32,720
Speaker 3: actually have a joint show we're doing together. You can

1307
01:05:32,720 --> 01:05:34,919
Speaker 3: also I work on another show called Black frat Them

1308
01:05:35,200 --> 01:05:37,800
Speaker 3: that is also on the Outspoken Network. Bridget might be

1309
01:05:37,840 --> 01:05:41,280
Speaker 3: making appearance on there soon. Stay tuned, Stay tuned, and

1310
01:05:41,280 --> 01:05:44,800
Speaker 3: then also, yeah, stuff I've never told you, et cetera,

1311
01:05:44,800 --> 01:05:48,160
Speaker 3: et cetera. Find me wandering around the streets of Brooklyn

1312
01:05:48,680 --> 01:05:52,720
Speaker 3: looking confused, I don't know, looking.

1313
01:05:52,480 --> 01:05:54,600
Speaker 2: For a bathroom and you're looking for a bathroom.

1314
01:05:54,640 --> 01:05:58,720
Speaker 3: Finally, finally, I have had to peace since twenty eighteen,

1315
01:05:59,040 --> 01:06:04,400
Speaker 3: and finally, finally, thank you, Zora, Mom, Donnie.

1316
01:06:04,000 --> 01:06:05,440
Speaker 2: Sure words, We're never spoken.

1317
01:06:05,640 --> 01:06:07,840
Speaker 1: Thank you so much for being here, Joey, and thanks

1318
01:06:07,840 --> 01:06:09,880
Speaker 1: to all of you for listening. I will see you

1319
01:06:10,000 --> 01:06:19,640
Speaker 1: on the Internet. If you're looking for ways to support

1320
01:06:19,640 --> 01:06:22,120
Speaker 1: the show, check out our March store at tangodi dot

1321
01:06:22,120 --> 01:06:25,760
Speaker 1: com slash store. Got a story about an interesting thing

1322
01:06:25,760 --> 01:06:27,760
Speaker 1: in tech, or just want to say hi, You can

1323
01:06:27,880 --> 01:06:30,080
Speaker 1: reach us at Hello at teangodi dot com. You can

1324
01:06:30,080 --> 01:06:33,000
Speaker 1: also find transcripts for today's episode at tenggody dot com.

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01:06:33,160 --> 01:06:34,840
Speaker 1: There Are No Girls on the Internet was created by

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01:06:34,840 --> 01:06:38,200
Speaker 1: me Bridget tod. It's a production of iHeartRadio and Unboss Creative,

1327
01:06:38,720 --> 01:06:42,320
Speaker 1: edited by Joey pat Jonathan Strickland is our executive producer.

1328
01:06:42,640 --> 01:06:45,920
Speaker 1: Tari Harrison is our producer and sound engineer. Michael Almada

1329
01:06:45,960 --> 01:06:48,960
Speaker 1: is our contributing producer, I'm your host, bridget Todd. If

1330
01:06:48,960 --> 01:06:50,680
Speaker 1: you want to help us grow, rate and review us

1331
01:06:50,680 --> 01:06:54,320
Speaker 1: on Apple podcasts. For more podcasts from iHeartRadio, check out

1332
01:06:54,360 --> 01:06:56,720
Speaker 1: the iHeartRadio app, Apple Podcasts, or wherever you get your

1333
01:06:56,760 --> 01:06:57,600
Speaker 1: podcasts

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01:07:00,280 --> 01:07:01,120
Speaker 5: You w