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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. This is

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

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Speaker 1: stories that you might have missed on the Internet so

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Speaker 1: you don't have to. And I am so thrilled to

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Speaker 1: welcome my guest co host for our conversation today, Francesca Fiorantini,

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Speaker 1: journalist and host of The Bituation Room. Thank you so

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Speaker 1: much for being here.

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Speaker 2: He thanks for having me Bridge. It's so good to

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Speaker 2: be back in a different era, but really the same era,

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Speaker 2: a continuation of the awfulness. I'm really happy to be here.

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Speaker 2: We need more shows like yours.

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Speaker 1: We need more voices like yours. I'm happy to see

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Speaker 1: you everywhere. The Bituation Room is fantastic. Also, you've got

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Speaker 1: a live show coming up suit.

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Speaker 2: Right, yes, yes, yes, if you're hearing this next Friday

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Speaker 2: in Los Angeles, or and you are in Los ange

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Speaker 2: Angelus or want to get to Los Angeles, yeah, Friday

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Speaker 2: at the Allegian Theater, May thirtieth. We're gonna fix La

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Speaker 2: Bridget La post fires, pre Olympics. It's it's increasingly unlivable here.

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Speaker 2: But council member Unisses Hernandez, John Iderol of the Damage Report,

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Speaker 2: someone from the Rent Brigade, which has been blowing the

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Speaker 2: whistle on all the price gouging that realtors have been doing.

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Speaker 2: And Rachel Reyis of the LA podcast, which is an

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Speaker 2: excellent podcast if people don't if people want some local

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Speaker 2: politics podcasts. But yeah, it'll be good. It'll be good.

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Speaker 1: Sometimes I gotta laugh to keep from crying when you're

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Speaker 1: tuning into our political landscape these days. Indeed, So with that,

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Speaker 1: are you ready to talk about some stories that are

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Speaker 1: happening across the internet.

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Speaker 2: So ready?

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Speaker 1: Okay, So the first one is not even really a story.

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Speaker 1: It's more just I want people's takes. This was blowing

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Speaker 1: up in my kind of podcast or group chat. So

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Speaker 1: I was like, you know what, I'll bring it to

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Speaker 1: the podcast. Are you familiar with the podcaster theo On? Yes,

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Speaker 1: So for folks who don't know, Theovon is a super

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Speaker 1: popular podcaster. He rose to fame on MTV's road Rules

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Speaker 1: and like competition shows like The Challenge, he hosts a

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Speaker 1: super popular podcast, a podcast that like, I gotta have

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Speaker 1: a million podcasts in my life and it will not

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Speaker 1: equals as popular as his show is. I would say

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Speaker 1: that I personally believe that he is one of the

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Speaker 1: reasons why Trump was reelected. Trump kind of agrees with me,

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Speaker 1: Like he shouted out theovon from his victory stage and

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Speaker 1: like thanked him by name. He is like a pretty

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Speaker 1: vocal supporter of Trump. He's had him on the podcast

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Speaker 1: and everything.

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Speaker 2: But was he at the inauguration? Bridget He was?

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Speaker 1: He was, Oh, And what's funny is that he kind

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Speaker 1: of is doing like a if you if you watch

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Speaker 1: that show the Royal Gemstones. He kind of favors Keith,

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Speaker 1: Like he wears like a mullet, Like that's kind of

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Speaker 1: the So like seeing him at the inauguration was like, huh,

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Speaker 1: that's interesting.

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Speaker 2: But Keith Keith is a good person.

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Speaker 1: Yeah, Keith's He's a good guy. I don't know that

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Speaker 1: I would qualify theopha. Well, that's sort of the question

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Speaker 1: that I'm bringing to the podcast. On his podcast this week,

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Speaker 1: he was talking about Gaza. Here's what he said on

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Speaker 1: the podcast. Quick heads up though that we did edit

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Speaker 1: this clip for length.

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Speaker 3: You know, I wanted to say something. There's been something

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Speaker 3: that's just been kind of on my heart, and so

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Speaker 3: I feel like I should bring it up. There is

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Speaker 3: you know, we've had people on the podcast in the

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Speaker 3: past to talk about it, and there's just a there's

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Speaker 3: a conflict that's been happening in the Middle East. People

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Speaker 3: know about it between Israel and Palestine and some of

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Speaker 3: the areas over there, the Gaza area they talk about,

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Speaker 3: and uh, and I just think it's it feels to me,

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Speaker 3: I don't know if I it just it feels to

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Speaker 3: me like it's a genocide that's happening while we're alive

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Speaker 3: here in front of us, are in front of our lives,

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Speaker 3: and I don't Sometimes I feel like I should say something.

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Speaker 3: I'm not a geologist or geographer or anything like that,

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Speaker 3: you know, so I don't know a lot of the

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Speaker 3: Some of it. I do know, though, like I know

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Speaker 3: the basics of the issues over there. But for me,

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Speaker 3: it's just like how I feel like you see all

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Speaker 3: these photos of people, just children, women, people, body parts,

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Speaker 3: just people like putting their kids back together, and I

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Speaker 3: just can't believe that we're watching that and that more

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Speaker 3: isn't said about it. You notice, like, what are we doing?

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Speaker 1: So I'll stop it there when I saw when I

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Speaker 1: saw this, my friends, my like podcaster friends know that

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Speaker 1: I deeply dislike this person. I deeply dislike the avonn

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Speaker 1: And people were dropping this clip in the group chat,

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Speaker 1: being like, oh, it's so good that he said something.

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Speaker 1: You know, this clip got twenty million views, so they

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Speaker 1: say on X, And I guess for me, I fully

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Speaker 1: don't know what to do with this because, on the

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Speaker 1: one hand, I obviously support anybody who's using a platform

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Speaker 1: to speak out against genocide, but this guy is like

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Speaker 1: all in for Trump, very vocally, and so I have

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Speaker 1: a hard time kind of understanding how somebody can make

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Speaker 1: a statement like this and seemingly not have the tiniest

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Speaker 1: bit of like self reflection on their part of it.

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Speaker 1: And so this rapper, Zach Fox, wasn't having it. He said,

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Speaker 1: don't let Theovon fool you. He'd be blowing a hookah

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Speaker 1: smoke and doing key bumps with Trump, his family and

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Speaker 1: the literal architects of the genocidees fate crying about. Then

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Speaker 1: he posted a picture of Theovon with Avanka Trump and

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Speaker 1: Jared Kushner partying in Miami from Levanka's Instagram just a

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Speaker 1: few days ago and said what do you mean what

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Speaker 1: we are doing? Ask them, which I have to admit

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Speaker 1: is like a pretty funny burn.

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Speaker 4: Yeah.

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Speaker 1: But and like literally a few days before recording this,

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Speaker 1: THEO was with Trump doing an opening set at a

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Speaker 1: military base in Qatar, and so like this actually turned

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Speaker 1: into a bit of an argument because I, on the

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Speaker 1: one hand, totally understand how some of my podcast my

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Speaker 1: like leftist podcaster or friends were like, anybody who's using

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Speaker 1: their platform to speak up is doing a good thing.

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Speaker 1: If twenty million people are getting eyeballs on this and

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Speaker 1: he's making a different subset of the population think about this,

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Speaker 1: that is a good thing. I can understand that point

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Speaker 1: of view, but I just don't buy it.

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Speaker 2: Yeah, I mean, first of all, I love the receipts

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Speaker 2: that were brought against him by that rapper, Like I

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Speaker 2: love and you're like, oh, I'm waiting for this to

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Speaker 2: be really old. No, no, no, it's it's from like a

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Speaker 2: week ago him sitting down with Jared Kushner and Ivanka Trump.

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Speaker 2: I mean Jared Kushner, who spearheaded in part the Abraham Accords,

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Speaker 2: which effectively completely cut out the existence of Palestinians from

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Speaker 2: any kind of peace process in the Middle East, which

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Speaker 2: is kind of it's actually just a oxymoron to even

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Speaker 2: say what I just said, because there can be no

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Speaker 2: peace without you know, Palestinians involved, and so that I

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Speaker 2: think was really important. And also Jared Kushner stands to

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Speaker 2: gain should Trump's ethnic cleansing of Gaza succeed and the

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Speaker 2: Trump of you know, the riviera of the Middle East

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Speaker 2: comes to pass. That's Jared Kushner has openly said, this

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Speaker 2: is beach from property. I mean, this is truly on

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Speaker 2: the bones of hundreds of thousands of Palestinians. Again, official

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Speaker 2: death tolls stopped back when you know there was any

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Speaker 2: kind of infrastructure to account for all the dead.

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Speaker 5: But I really I hate to come on this show

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Speaker 5: and be like I really agree with the host because

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Speaker 5: I want to make it spicy and interesting. To Bridget,

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Speaker 5: I super agree with you, Like I really come down

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Speaker 5: on like very very similar to you on all of this.

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Speaker 2: And I will say two things about it. Like, I

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Speaker 2: do think that the issue of Palestine is and the

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Speaker 2: issue of Gaza and the genocide that's happening is so bipartisan,

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Speaker 2: it's so blanket it's almost cultural in terms of how

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Speaker 2: much people are against this and in ways that I

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Speaker 2: think really supersede any party loyalty or any right left situation.

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Speaker 2: So I think that just has to be named that,

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Speaker 2: Like people who are against genocide are also people who

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Speaker 2: are like I don't know, I don't vote who what

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Speaker 2: is a congress?

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Speaker 4: Like?

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Speaker 2: There are people who are just like you know, there's

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Speaker 2: nothing to do with party, And clearly from Theovonne, dumbass

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Speaker 2: talking his way through that, like I'm not a geologist, Like, bro,

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Speaker 2: what are you talking about? You're like stalagtites here, like

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Speaker 2: what do we like? Geology? I mean a geographer. None,

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Speaker 2: neither of those things actually relevant to this issue. I'm

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Speaker 2: not a geologist or a geographer. And then you know,

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Speaker 2: saying what he said. So I feel like it's like,

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Speaker 2: it's both it's good that he said this to his

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Speaker 2: massive audience, but you're absolutely right if you have I

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Speaker 2: have an audience with Donald fucking Trump, which he does

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Speaker 2: say something to his ass, say something to that instead,

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Speaker 2: it kind of feels like I feel like he probably

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Speaker 2: got he's got comments on it, people talking about it

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Speaker 2: around him. He just wanted to address it, and then

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Speaker 2: he can kind of go on about his way and

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Speaker 2: not do anything activate his community, talk about how Trump

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Speaker 2: is making it worse, talk about all of the genocidal

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Speaker 2: things that the removal of Palestinians to what Libya is,

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Speaker 2: the new proposal receiving a fucking four hundred million dollar

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Speaker 2: jet that now we know Trump's solicited from Cutter and

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Speaker 2: you know, just like just to have. Yeah, it's pretty sickening.

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Speaker 2: And so no, I don't, you know, I have to

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Speaker 2: come back to the like it's not for us, Bridget

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Speaker 2: Like there's a little bit of a like it's not

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Speaker 2: for us. And so hopefully people who don't listen to

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Speaker 2: Theovonne listen to our shows, listen to you, listen to

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Speaker 2: this podcast and are like, we don't got to go

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Speaker 2: to war against these people. But I'm not trying to

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Speaker 2: take time out of my day to like, you know,

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Speaker 2: give them a bunch of flowers when they're very much

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Speaker 2: in bed with just fascists at this point.

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Speaker 1: Yeah, I feel very similarly to you. So like my

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Speaker 1: this is like my Roman Empire. I think I think

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Speaker 1: a lot of these like bro podcasters, but THEO in particular,

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Speaker 1: I think they are playing a character. I think that

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Speaker 1: he plays this kind of like uh, Chuck Stoner everyman, Like,

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Speaker 1: I'm not a geologist or nothing, but this seems bad.

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Speaker 1: I don't think that he's a stupid person or an

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Speaker 1: uninformed person. I think that he's making a ton of

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Speaker 1: money from his association with the Trumps, with the Kushners.

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Speaker 1: I think he is seeing that, like the situation in

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Speaker 1: Gaza is a genocide and is quite bad, and as

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Speaker 1: you said, it's like not a left right issue, it's

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Speaker 1: like a right wrong Like I can see with what's happening,

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Speaker 1: and I can see that it's very bad and very wrong.

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Speaker 1: I think that he's like, oh, shoot, I need to

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Speaker 1: speak to this, but I want to do it in

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Speaker 1: a way where I don't have to. I can still

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Speaker 1: sort of enable it. I can still sort of make

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Speaker 1: money from my participation with the people who are architecting it.

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Speaker 1: I don't want to have to, you know, I want

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Speaker 1: to get to perform sadness about it while also continuing

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Speaker 1: to basically say nothing about it. And so yes, yeah,

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Speaker 1: I don't. I it's hard for me to. I mean,

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Speaker 1: maybe I'm cynical. It's hard for me to take this

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Speaker 1: as a win when it's like, yeah, what do you

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Speaker 1: mean what we are doing? You have audience with the

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Speaker 1: people who are doing this. Talk to them, don't talk

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Speaker 1: to me.

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Speaker 2: Well, it's uh, you know, I have a lot of

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Speaker 2: I have a lot of thoughts. And I was like,

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Speaker 2: uh when we started the show, I was like, I

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Speaker 2: gotta leave soon. But then now I'm like, oh, no,

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Speaker 2: an issue that I really really want to talk a

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Speaker 2: lot about. It's interesting, it's ironic. Trump also said this

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Speaker 2: same line. He's sitting in front of Netanyahu in the

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Speaker 2: Oval office, going it's terrible all the killing that's happening there.

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Speaker 2: And you're like, oh my god, buddy right next to

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Speaker 2: you as the guy who's doing it. And of course

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Speaker 2: he knows right. But it's much easier to sort of

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Speaker 2: New York Times headline this whole thing like Palestinians died

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Speaker 2: on their own. There is no culprit like and then

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Speaker 2: you cover your ass because you said something, and then

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Speaker 2: you get to move on and you don't have to

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Speaker 2: actually talk about who is doing the thing, but the

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Speaker 2: other thing that happens here. And this is what I

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Speaker 2: think the podcast bros. Because when you said podcast pros,

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Speaker 2: it reminded me of another interview this week that Bernie

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Speaker 2: Sanders did with Andrew Schultz on the Flagrant podcast, in

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Speaker 2: which Schultz tries to say they call us podcast bros.

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Speaker 2: The way they called your supporters Bernie bros. We're the same.

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Speaker 2: And I was like, no, no, no, you're not. And

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Speaker 2: I was very disappointed on you know, as someone who

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Speaker 2: likes Bernie Sanders, super disappointed by his performance there. I

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Speaker 2: did a whole breakdown on my show about it, if

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Speaker 2: you want, Like, way too many thoughts of mine. However,

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Speaker 2: what's crazy about like the right wing podcast Comedian Rise,

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Speaker 2: which I think you're totally right, there is a care

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Speaker 2: there that they are all playing and they're doing it

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Speaker 2: for money, you know, Like, but I was having this

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Speaker 2: conversation this is what is crazy for me, Like every

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Speaker 2: time you ask a liberal excuse me, a liberal comedian

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Speaker 2: doesn't matter, a podcast or whatever, John Oliver, John Stewart,

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Speaker 2: Bill Burr to name three of them, and you say, hey,

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Speaker 2: you seem to have like lots of thoughts about the

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Speaker 2: world and you know everything that's happening, and you know,

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Speaker 2: do you feel like your role is almost larger than

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Speaker 2: just a comic. It's like you're having you know, an impact.

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Speaker 2: They all go like no, no, no, no, no, don't listen

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Speaker 2: to me. I'm just a comedian. I shouldn't be the

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Speaker 2: person leading this conversation. What do you want to talk

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Speaker 2: to me for? And I do agree with that in

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Speaker 2: a way, because what happens when we deify comedians as

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Speaker 2: sort of thought leaders is your theo von Andrew Schultz's,

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Speaker 2: and those two guys have no problem saying, Oh, I'm

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Speaker 2: I am an intellection, a leader. I do speak to like,

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Speaker 2: you know, the voice, the voice of the voice, the

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Speaker 2: voice of the canceled, you know, white male, like that

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Speaker 2: is who I'm speaking for. And so you have this

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Speaker 2: moment where it's like, oh, the right is fully embracing

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Speaker 2: the line between comic and political and politics and the

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Speaker 2: so called left and really left, but the liberals are

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Speaker 2: completely abdicating it, almost out of responsibility, but also leaving

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Speaker 2: this huge gulf where maybe we should be feeling. I

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Speaker 2: don't know what your thoughts are on that.

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Speaker 1: That's such I had never put that together, but that's

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Speaker 1: such a good point, and it's very frustrating to watch

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Speaker 1: because then the voices who get to be amplified and

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Speaker 1: grow are the ones who are spouting nonsense and also

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Speaker 1: spouting nonsense in a way where it's like that you

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Speaker 1: can you They like they want to be intellectuals with it.

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Speaker 1: Like I think that's the thing that gets me is listen,

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Speaker 1: nobody appreciate the hustle and a grif more than I do,

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Speaker 1: Like get your money, do what you gotta do. But

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Speaker 1: they're like, don't, don't pull us into it and make

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Speaker 1: it be like, oh yeah, I'm an intellexual for thinking this.

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Speaker 1: If you want opinions on you know, trans identity, I'm

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Speaker 1: your guy, me the comedian. It's like, no, what what

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Speaker 1: are we doing?

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Speaker 4: Right?

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Speaker 2: And I think it's also the death of the expert.

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Speaker 2: I mean, we the Internet as a show that talks

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Speaker 2: about it. You know, the Internet in its most beautiful

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Speaker 2: periods and in iterations is like Okay, you're listening to

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Speaker 2: or seeing someone who you feel speaks in plain language,

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Speaker 2: is again personable and isn't necessarily an expert, but giving

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Speaker 2: you kind of their gut, you know, reaction, which can

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Speaker 2: be good or bad. But then we get into a

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Speaker 2: lot of trouble when it's like, yeah, we're gonna listen

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Speaker 2: to non trans people talk about trans stuff. We're gonna

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Speaker 2: listen to non black people talk about, you know, issues

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Speaker 2: that affect black community. We're gonna like like all that

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Speaker 2: and you're just like no, no, no, no, Well now now

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Speaker 2: you're literally elevating. And again this is not to say

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Speaker 2: that identity gives you that edge, but we're not going

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Speaker 2: to listen to I don't know a fucking you know,

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Speaker 2: like ethnic studies scholar whose department is being obliterated through

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Speaker 2: different Trump executive orders, like those are the experts that

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Speaker 2: we should be listening to. Instead. It's like the worst

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Speaker 2: of the Internet is just listening to dumb asses talk

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Speaker 2: about things they just learned about.

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Speaker 4: Ough you put that perfectly. Let's hit a quick break

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Speaker 4: at our back.

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Speaker 1: Okay, speaking of dumb asses, we have to talk about

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Speaker 1: this legislation, the Big Beautiful Bill. I know you've been

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Speaker 1: thinking about it and talking about it. Something that I

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Speaker 1: don't feel like is getting enough shine is the fact

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Speaker 1: that this big Beautiful Agenda Bill has a rule baked

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Speaker 1: into it that passed would prohibit states from enforcing any

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Speaker 1: law or regulation regulating AI for ten years. I mean,

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Speaker 1: that does not seem like a good thing to me.

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Speaker 1: The advocacy organization Demand Progress organized a bunch of academic

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Speaker 1: and like civil society organizations one hundred and forty one

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Speaker 1: of them to sign a letter, including organizations like the

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Speaker 1: Georgetown Laws Center on Privacy and Technology, the Southern Poverty

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Speaker 1: Law Center, and employee coalitions like Amazon Employees for Climate Justice,

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Speaker 1: basically being like, this is bad. The letter reads, this

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Speaker 1: moratorium would mean that even if a company deliberately designs

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Speaker 1: an algorithm that causes foreseeable harm, regardless of how intentional

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Speaker 1: or egregious the misconduct or how devastating the consequences, the

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Speaker 1: company making or using that bad tech, would be unaccountable

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Speaker 1: to lawmakers and the public.

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Speaker 2: I mean, it's beyond AI right, because you know, every

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Speaker 2: day we're finding out about some new shit that Meta

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Speaker 2: did deliberately. What was it targeting young girls who I forgot.

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Speaker 1: What the story was. It was girls who who took

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Speaker 1: a selfie of themselves and then deleted it because they

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Speaker 1: were unhappy with it. They have technology that it's like,

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Speaker 1: oh self esteem issues, huh, let's get them, and then

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Speaker 1: they will go, yeah, it's.

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Speaker 2: And then market them with whatever totally totally creams. And yeah,

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Speaker 2: there was like some other study that was like, you know,

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Speaker 2: like children are using like anti aging cream, Like oh

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Speaker 2: my god, yeah, man, this is so bald. Faced like

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Speaker 2: it is so clear what they're trying to do. And

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Speaker 2: this is when kind of like the the tech oligarchy

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Speaker 2: really is showing its whole ass, like this is like, Okay,

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Speaker 2: this is what you wanted. Trump is enacting it, and

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Speaker 2: the Republicans are enacting it for you. A ten year moratorium.

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Speaker 2: And of course, you know, we believe in states rights

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Speaker 2: when it comes to what you want to do with

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Speaker 2: your own body, but we don't believe in states rights

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Speaker 2: and literally anything else on anything. We want to run Roughshotover.

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Speaker 2: You have a sanctuary city, you know, we want to

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Speaker 2: sweep up anybody in your sanctuary city. There's no protections

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Speaker 2: from ice. And same with this AI stuff, which you know,

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Speaker 2: being in California where Gavin Newsom has been very kind

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Speaker 2: of like flirty with AI, like oh, we you know

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Speaker 2: it can maybe it can be good and we have

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Speaker 2: to study it and blow it's like you think those

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Speaker 2: studies have happened in like kept pace with the rollout

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Speaker 2: of AI.

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Speaker 1: No.

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Speaker 2: No, but it's almost like this is a perfect little

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Speaker 2: cover to be like, well, what can we do. We

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Speaker 2: can't regulate against this industry. Guess I must cash in

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Speaker 2: on it.

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Speaker 1: Yeah, that's exactly what's going on, and there are some

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Speaker 1: I mean, I'm glad that you use that example of

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Speaker 1: in California, because like, there are so many ways that

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Speaker 1: AI can be used to make our lives harder as people,

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Speaker 1: and we already we already know that AI can be

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Speaker 1: used to discriminate. So like Colorado pass the law of

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Speaker 1: requiring tech companies to protect consumers from the risk of

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Speaker 1: algorithm discrimination, and so like, if if a is making

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Speaker 1: the decision of employment, they have to inform you that

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Speaker 1: that has happened, and they have to inform you that

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Speaker 1: you're interacting with an AI system that we know can

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Speaker 1: discriminate against you. Where I live in DC, there was

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Speaker 1: a whole study about the use of AI algorithmic rent

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Speaker 1: pricing tools, and so like, if your landlord senses that

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Speaker 1: you're desperate for a place to live and that you'll

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Speaker 1: pay doubles for that apartment, they can use AI to

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Speaker 1: do that. Wouldn't it be great if there was state

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Speaker 1: based legislation to be like, actually, you can't do that,

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Speaker 1: Like the this is legislation that actually has real impact

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Speaker 1: in people's lives, and so having a ten year moratorium

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Speaker 1: on it, I think is really bad. And as you said,

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Speaker 1: like what happened the state's rights?

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Speaker 2: What's going to be left in ten years? Like I'm sorry,

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Speaker 2: like thinking about ten years down the road. I mean,

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Speaker 2: we are going to reach a breaking point very much

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Speaker 2: earlier than ten years. But like AI has already taken

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Speaker 2: so many jobs. AI is already threatening I mean the

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Speaker 2: health sector, to say nothing of what we do, content creation,

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Speaker 2: hoovering up all of our voices are are I mean

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Speaker 2: you already someone signs away if they post on social media,

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Speaker 2: you know, any copyright to that content there, It's like

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Speaker 2: what is what is there left? And these are all

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Speaker 2: systems that are being trained on our labor. I mean,

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Speaker 2: it is a massive labor issue while it's simultaneously under

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Speaker 2: minds labor. So yeah, it's it's terrifying. But also isn't

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Speaker 2: Grok amazing? I mean, the way that Grook knows about

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Speaker 2: white genocide, it's just fantastic.

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Speaker 1: Oh my god, you could not have set me up

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Speaker 1: better for something I want to talk about in a minute.

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Speaker 1: But speaking of taking people's jobs, it's coming for the

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Speaker 1: jobs of women. Traditionally work done by women, we are

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Speaker 1: more vulnerable to AI taking our jobs and work done

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Speaker 1: by men. This is according to a new report from

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Speaker 1: the United Nations International Labor Organization. So this report says

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Speaker 1: that nine point six percent of traditionally female jobs were

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Speaker 1: set to be transformed by AI, compared to only three

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Speaker 1: point five percent of jobs typically carried out by men.

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Speaker 1: And so, to be clear, the report stressed that human

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Speaker 1: involvement is still needed when talking about jobs and displacement.

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Speaker 1: They say. We stressed that such exposure does not imply

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Speaker 1: the immediate automation entire of an entire occupation, but rather

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Speaker 1: the potential for a large share of its current task

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Speaker 1: to be performed using this technology. And so, I don't know,

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Speaker 1: it really reminds me of what the CEO of that

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Speaker 1: app Duo Lingo said, where he was like, oh, in

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Speaker 1: the future, we won't even need teachers. AI is going

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Speaker 1: to be better at teaching everybody than any human could be.

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Speaker 1: By the way, we have no evidence of that being true.

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Speaker 1: And he went on to say, in the future, don't worry,

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Speaker 1: we're still going to need teachers because somebody is going

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Speaker 1: to have to provide childcare. And as a former educator,

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Speaker 1: I was really like that that comment hits a lot

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Speaker 1: of my like, oh yeah, trigger.

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Speaker 2: They called you a childcare provider.

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Speaker 1: Yeah, exactly. So for folks who don't know the first

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Speaker 1: iteration of my career, I was an educator. I spent

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Speaker 1: most of it in a classroom. And I think the

431
00:23:07,720 --> 00:23:14,840
Speaker 1: idea of deprofessionalizing and devaluing education, especially education being like

432
00:23:14,880 --> 00:23:17,480
Speaker 1: a field that is predominantly a field that women have

433
00:23:17,520 --> 00:23:19,920
Speaker 1: a lot of, like we're overrepresented in that field. It

434
00:23:20,600 --> 00:23:24,240
Speaker 1: really I just been deeply offended by this, Like I'm

435
00:23:24,280 --> 00:23:26,760
Speaker 1: offended by the idea that like, oh, AI will be

436
00:23:26,840 --> 00:23:30,040
Speaker 1: teaching young people in the future and human educators, people

437
00:23:30,080 --> 00:23:32,520
Speaker 1: who went to school, went to college, got degrees, They'll

438
00:23:32,560 --> 00:23:36,480
Speaker 1: be essentially like babysitters, gig work style babysitters. And that's

439
00:23:36,520 --> 00:23:37,720
Speaker 1: the future that we'll have.

440
00:23:37,880 --> 00:23:41,800
Speaker 2: Right, And the reality is none of it is supported

441
00:23:42,000 --> 00:23:47,199
Speaker 2: by any research, any science, any data, any first hand account.

442
00:23:47,760 --> 00:23:50,640
Speaker 2: It is just we can make a book, we want

443
00:23:50,680 --> 00:23:54,720
Speaker 2: to make money. And there's one aspect we haven't completely

444
00:23:54,760 --> 00:23:57,560
Speaker 2: privatized yet, and that is public education. We're going to

445
00:23:57,600 --> 00:24:01,960
Speaker 2: destroy it however possible, and AI is one of the ways.

446
00:24:01,960 --> 00:24:05,440
Speaker 2: I also think, like super remote learning. Despite what the

447
00:24:05,520 --> 00:24:08,119
Speaker 2: right said during COVID, which was like, you know, the

448
00:24:08,200 --> 00:24:10,880
Speaker 2: kids and their mental health and no, no, no, no bullshit

449
00:24:10,960 --> 00:24:15,840
Speaker 2: because Betsy Devas's family has been actively invested in moving

450
00:24:16,560 --> 00:24:21,840
Speaker 2: learning online solely and again literally, my brother is a

451
00:24:21,880 --> 00:24:25,479
Speaker 2: public school teacher in Oakland, and the pandemic was terrible.

452
00:24:25,840 --> 00:24:28,760
Speaker 2: Kids did not learn more. Remote learning, you know, was

453
00:24:28,840 --> 00:24:31,879
Speaker 2: really difficult. It was because we were trying to keep

454
00:24:31,920 --> 00:24:34,520
Speaker 2: people safe. But that is no way to actually teach.

455
00:24:34,880 --> 00:24:39,640
Speaker 2: And that's with him being an actual teacher, a real person.

456
00:24:40,160 --> 00:24:42,679
Speaker 2: But the idea that we're going to just go to

457
00:24:42,800 --> 00:24:48,000
Speaker 2: like online learning by done by AI, I mean, bridget

458
00:24:48,080 --> 00:24:49,679
Speaker 2: doesn't really matter when all you want to do is

459
00:24:49,720 --> 00:24:52,239
Speaker 2: sort of produce little worker bees who can you know,

460
00:24:52,480 --> 00:24:55,520
Speaker 2: never fight for themselves or you know, keep people in

461
00:24:55,600 --> 00:24:58,920
Speaker 2: sort of a constant like I don't know, third grade education.

462
00:24:59,480 --> 00:25:05,240
Speaker 2: They get stuff their podcasts and whatnot, like no authoritarianism, fascism,

463
00:25:05,280 --> 00:25:08,000
Speaker 2: There's no point in educating people in these systems.

464
00:25:08,400 --> 00:25:11,320
Speaker 1: It really reminds me of this quote from Chris Gilliard

465
00:25:11,359 --> 00:25:14,399
Speaker 1: who says every future imagined by a tech company is

466
00:25:14,480 --> 00:25:18,199
Speaker 1: worse than it's a previous iteration, Like I believe that

467
00:25:18,280 --> 00:25:20,200
Speaker 1: in my bones. And when I heard this guy talking

468
00:25:20,240 --> 00:25:22,199
Speaker 1: about the future of education, I was like Damn that

469
00:25:22,359 --> 00:25:22,800
Speaker 1: is bleak.

470
00:25:24,440 --> 00:25:26,679
Speaker 2: Yeah, I mean they really like I think that AI

471
00:25:26,760 --> 00:25:31,480
Speaker 2: and crypto are just I mean, when will the bubble burst?

472
00:25:31,560 --> 00:25:34,320
Speaker 2: That's what I'm camp. I'm like, just burst already, God

473
00:25:34,400 --> 00:25:37,880
Speaker 2: damn it. But it's got to destroy first and then

474
00:25:38,000 --> 00:25:38,919
Speaker 2: maybe it will burst.

475
00:25:39,160 --> 00:25:41,680
Speaker 1: Speaking of destroy, I have to talk to you about

476
00:25:41,720 --> 00:25:46,000
Speaker 1: this piece about how Elon Musk's AI facility is it

477
00:25:46,119 --> 00:25:50,320
Speaker 1: essentially just like polluting a black community. So Elon Musk

478
00:25:50,400 --> 00:25:53,879
Speaker 1: he has this AI company called Xai. They built a

479
00:25:54,000 --> 00:25:57,960
Speaker 1: massive supercomputer in Memphis, Tennessee. He's been championing it with

480
00:25:58,000 --> 00:26:00,560
Speaker 1: all the sort of usual predictable fanfare, saying it's the

481
00:26:00,600 --> 00:26:03,760
Speaker 1: most powerful AI trading system in the world. It's been

482
00:26:03,760 --> 00:26:06,840
Speaker 1: really selling it locally to this community in Memphis, saying

483
00:26:06,880 --> 00:26:08,800
Speaker 1: it's going to be a big source of jobs and money.

484
00:26:08,960 --> 00:26:12,119
Speaker 1: But residents in nearby Boxtown, which is a majority black,

485
00:26:12,160 --> 00:26:16,560
Speaker 1: economically disadvantaged community that has long endured industrial pollution, says

486
00:26:16,600 --> 00:26:19,520
Speaker 1: that this facility is just another threat to their health.

487
00:26:19,840 --> 00:26:23,199
Speaker 1: Now you probably know this. The secret of AI is

488
00:26:23,200 --> 00:26:26,520
Speaker 1: that it's like very power hungry. So when you are

489
00:26:27,160 --> 00:26:31,719
Speaker 1: asking groc about white genocide that is using like or

490
00:26:31,800 --> 00:26:35,359
Speaker 1: like using AI to figure out what it would sound

491
00:26:35,440 --> 00:26:39,720
Speaker 1: like if I don't know, bugs Bunny read the Declaration

492
00:26:39,760 --> 00:26:43,359
Speaker 1: of Independence or whatever you're using it for. You're using

493
00:26:43,400 --> 00:26:44,920
Speaker 1: a lot of power.

494
00:26:44,920 --> 00:26:48,160
Speaker 2: Yes, and displacing a voice actor. Yeah, thank you, Yes,

495
00:26:48,359 --> 00:26:51,520
Speaker 2: because I'm or really good impressionists. Because I'm sure a

496
00:26:51,560 --> 00:26:54,480
Speaker 2: great impressionist could give you that rendition of bugs Buddy

497
00:26:54,520 --> 00:26:56,600
Speaker 2: reading the Declaration of Independence.

498
00:26:56,720 --> 00:27:01,040
Speaker 1: So Elon Musk Company has currently has no airs, appearing

499
00:27:01,080 --> 00:27:03,679
Speaker 1: to rely on a loophole for temporary turbines, and so

500
00:27:04,280 --> 00:27:08,240
Speaker 1: this facility is just like pumping out smog using gas

501
00:27:08,280 --> 00:27:11,960
Speaker 1: powered turbines that are just like completely sickening this community

502
00:27:12,200 --> 00:27:14,680
Speaker 1: and telling the people who live in this community, oh,

503
00:27:14,760 --> 00:27:16,560
Speaker 1: this is this is gonna be good for you, like

504
00:27:16,640 --> 00:27:20,920
Speaker 1: this is for your own good. One resident said, our

505
00:27:20,960 --> 00:27:23,640
Speaker 1: health was never even considered. The safety of our community

506
00:27:23,720 --> 00:27:26,280
Speaker 1: was never ever considered. She lives three miles from this

507
00:27:26,320 --> 00:27:29,800
Speaker 1: facility and already suffers from a lung condition. And I'm

508
00:27:29,800 --> 00:27:32,080
Speaker 1: sad to say this is like not anything new for

509
00:27:32,160 --> 00:27:35,440
Speaker 1: this part of Memphis. It has seventeen other polluting facilities,

510
00:27:35,480 --> 00:27:39,280
Speaker 1: including an oil refinery, a steel plant, gas fired power plant. However,

511
00:27:39,680 --> 00:27:41,879
Speaker 1: none of those facilities are owned by Elon Musk, who

512
00:27:42,000 --> 00:27:45,720
Speaker 1: was obviously like in the Trump administration, and an administration

513
00:27:45,760 --> 00:27:48,560
Speaker 1: that we already talked about is like very invested in

514
00:27:48,680 --> 00:27:50,800
Speaker 1: defanging any kind of AI regulation.

515
00:27:51,400 --> 00:27:56,480
Speaker 2: Yeah, I mean, what's really also disturbing about this is that,

516
00:27:56,680 --> 00:27:59,959
Speaker 2: as you mentioned, Memphis is already you know, an environment

517
00:28:00,000 --> 00:28:05,400
Speaker 2: mentally uh like a toxic site because of corporate pollution,

518
00:28:06,520 --> 00:28:13,720
Speaker 2: and Donald Trump is completely stripped any attention any funds,

519
00:28:13,880 --> 00:28:18,040
Speaker 2: any you know, any projects that are focused on cleanup

520
00:28:19,080 --> 00:28:25,440
Speaker 2: specifically because they mention things like environmental racism or disproportionately

521
00:28:25,440 --> 00:28:28,679
Speaker 2: affect black and brown communities, and you know, and it's like,

522
00:28:29,680 --> 00:28:31,960
Speaker 2: because they do that, it's like, well, how come we

523
00:28:32,000 --> 00:28:34,280
Speaker 2: can't get our toxic sites clean up? It says, you

524
00:28:34,320 --> 00:28:37,840
Speaker 2: don't fucking have them, Like you don't have them, my guy.

525
00:28:37,920 --> 00:28:43,520
Speaker 2: And so your fragility because this mentions race again it's deliberate,

526
00:28:43,680 --> 00:28:47,440
Speaker 2: is it will get people killed. And so this is

527
00:28:47,520 --> 00:28:52,320
Speaker 2: why it matters to actually talk when you say environmental racism,

528
00:28:52,400 --> 00:28:55,840
Speaker 2: that is not just an empty fucking buzzword. It is real.

529
00:28:56,680 --> 00:29:00,720
Speaker 2: But yeah, I didn't know that turbine, like I would

530
00:29:00,840 --> 00:29:03,120
Speaker 2: very much like to see. I'm trying to look at

531
00:29:03,120 --> 00:29:08,040
Speaker 2: the images, but like as someone who's only one time

532
00:29:08,160 --> 00:29:10,560
Speaker 2: used AI when they were like, we're gonna make yourself

533
00:29:10,800 --> 00:29:13,040
Speaker 2: look hot in different context. I remember that was like

534
00:29:13,440 --> 00:29:17,120
Speaker 2: I was like, okay, but that's the only time, like

535
00:29:17,200 --> 00:29:20,560
Speaker 2: hand to God, never asked, grog, never ask Although now

536
00:29:20,600 --> 00:29:24,440
Speaker 2: if you Google's are something, you're sort of inherently forced

537
00:29:24,480 --> 00:29:27,680
Speaker 2: to do AI because it will populate an AI answer

538
00:29:27,800 --> 00:29:30,400
Speaker 2: for you. So there's no choice to be like, hey,

539
00:29:30,400 --> 00:29:33,760
Speaker 2: I'd like to not pollute Memphis or wherever you know

540
00:29:33,800 --> 00:29:38,200
Speaker 2: their data servers and centers are. But I do think

541
00:29:38,240 --> 00:29:41,240
Speaker 2: we have like like where are the exposs on this?

542
00:29:41,360 --> 00:29:43,280
Speaker 2: You know, I hope this is just the beginning of

543
00:29:43,320 --> 00:29:44,400
Speaker 2: the reporting.

544
00:29:44,120 --> 00:29:47,360
Speaker 1: Totally and to your point, like about what this looks like.

545
00:29:47,440 --> 00:29:51,720
Speaker 1: So Representative Pearson, who is a lawmaker there, he said

546
00:29:51,720 --> 00:29:54,160
Speaker 1: that it's pretty much what you're thinking. He said, it's

547
00:29:54,200 --> 00:29:56,840
Speaker 1: an actual gas plant in the middle of a neighborhood.

548
00:29:56,960 --> 00:29:59,600
Speaker 1: And you don't need any permitting to do this. Something

549
00:29:59,640 --> 00:30:03,160
Speaker 1: that's fa drastically and significantly on our system of checks

550
00:30:03,200 --> 00:30:06,640
Speaker 1: and balances, which like, yeah, that wouldn't be people who

551
00:30:06,680 --> 00:30:09,040
Speaker 1: like complain about like well, what are they going to

552
00:30:09,040 --> 00:30:11,160
Speaker 1: clean up our sites? That wouldn't be happening in a

553
00:30:11,240 --> 00:30:14,840
Speaker 1: community that was not economically disadvantage in majority black like,

554
00:30:14,840 --> 00:30:18,320
Speaker 1: I'm sorry, this would not be happening in a wealthy,

555
00:30:19,080 --> 00:30:22,160
Speaker 1: predominantly white community. That's why it's happening there.

556
00:30:23,600 --> 00:30:24,360
Speaker 2: No, of course not.

557
00:30:24,520 --> 00:30:26,200
Speaker 1: And so I have to give it up to some

558
00:30:26,320 --> 00:30:28,680
Speaker 1: of the residents who were quoted in this CNN piece,

559
00:30:29,280 --> 00:30:31,640
Speaker 1: because the residents of this area of Memphis have been

560
00:30:31,680 --> 00:30:33,719
Speaker 1: fighting this kind of fight for a long time. They

561
00:30:33,720 --> 00:30:36,960
Speaker 1: spoke to Kashan Pearson, a resident who said that they

562
00:30:37,040 --> 00:30:40,520
Speaker 1: see their area as a quote sacrifice zone where companies

563
00:30:40,560 --> 00:30:44,720
Speaker 1: put facilities that sicken residents. They in twenty twenty one,

564
00:30:44,840 --> 00:30:47,680
Speaker 1: residents successfully fought off a crude oil pipeline that would

565
00:30:47,680 --> 00:30:51,600
Speaker 1: have crossed Boxtown and multiple other predominantly black communities in Memphis.

566
00:30:51,880 --> 00:30:55,040
Speaker 1: In twenty twenty three, they successfully campaigned to close a

567
00:30:55,080 --> 00:30:58,040
Speaker 1: medical sterilizing facility which had been there since the seventies,

568
00:30:58,040 --> 00:31:01,479
Speaker 1: which was pumping out toxic pollutione and link to breast cancer.

569
00:31:01,560 --> 00:31:03,800
Speaker 1: So like, they have been fighting this fight for a

570
00:31:03,920 --> 00:31:06,280
Speaker 1: very long time. And something that I thought was really

571
00:31:06,280 --> 00:31:09,600
Speaker 1: interesting is that even though memphis Is Mayor Paul Jung

572
00:31:09,760 --> 00:31:11,880
Speaker 1: is very supportive of this facility and says like, Oh,

573
00:31:11,920 --> 00:31:14,800
Speaker 1: it's gonna bring new jobs and economically revitalized the area.

574
00:31:15,280 --> 00:31:18,280
Speaker 1: The residents there are smart enough to be very skeptical

575
00:31:18,320 --> 00:31:21,200
Speaker 1: of back claim. They're like, oh, you know, even though

576
00:31:21,200 --> 00:31:23,680
Speaker 1: they're making it seem like there's going to be training

577
00:31:23,760 --> 00:31:26,440
Speaker 1: for like white collar jobs and like tech jobs, the

578
00:31:26,480 --> 00:31:29,800
Speaker 1: residents are like, it's my understanding that data centers do

579
00:31:29,880 --> 00:31:32,520
Speaker 1: not typically need large numbers of workers. And I think

580
00:31:32,520 --> 00:31:34,520
Speaker 1: that we're being sold to false promise and the only

581
00:31:34,640 --> 00:31:38,280
Speaker 1: jobs that might possibly manifest for us or like janitorial jobs.

582
00:31:38,280 --> 00:31:41,720
Speaker 2: And he is right, yeah, yeah, yeah, no, I think

583
00:31:41,760 --> 00:31:43,680
Speaker 2: that's really important. And I also think it's a it's

584
00:31:43,720 --> 00:31:46,840
Speaker 2: a challenge for you know, on a local level, on

585
00:31:46,880 --> 00:31:51,040
Speaker 2: a statewide level, like we need better we need better representatives,

586
00:31:51,080 --> 00:31:53,080
Speaker 2: we need we need folks who are actually going to

587
00:31:53,120 --> 00:31:57,960
Speaker 2: fight this. Not sadly this week, senators like Kirsten Gillibrand

588
00:31:58,280 --> 00:32:01,680
Speaker 2: or you know, Reuben Diego who voted in favor of

589
00:32:01,760 --> 00:32:06,240
Speaker 2: basically a crypto currency you know, so called you know,

590
00:32:06,520 --> 00:32:10,160
Speaker 2: uh like regulation bill, but it absolutely does not regulate

591
00:32:10,200 --> 00:32:14,200
Speaker 2: crypto or stable coin and allows Trump to continue his

592
00:32:14,280 --> 00:32:16,880
Speaker 2: meme coins and everybody else. So like again, it's all

593
00:32:16,960 --> 00:32:20,840
Speaker 2: kind of part of like the tech oligarchy getting their way.

594
00:32:22,240 --> 00:32:24,680
Speaker 2: The other thing that's important to know, and I'm not

595
00:32:24,680 --> 00:32:26,960
Speaker 2: sure if this is part of this story, is also

596
00:32:27,600 --> 00:32:30,800
Speaker 2: that in order to cool down the data centers to

597
00:32:31,080 --> 00:32:34,880
Speaker 2: do the generative AI you which is just so funny,

598
00:32:34,960 --> 00:32:37,720
Speaker 2: like generative, like like who the fuck is generating? In

599
00:32:37,760 --> 00:32:42,000
Speaker 2: a punch of power and fresh water? You have to

600
00:32:42,160 --> 00:32:46,160
Speaker 2: use fresh water to cool down the systems, not even saltwater,

601
00:32:46,280 --> 00:32:49,920
Speaker 2: so like they get super super hot because everyone's like

602
00:32:50,000 --> 00:32:53,360
Speaker 2: trying to like manufacture you know, the perfect AI girlfriend.

603
00:32:54,040 --> 00:32:56,560
Speaker 2: Uh and then you know, and then a bunch of

604
00:32:56,560 --> 00:32:58,600
Speaker 2: fresh water gets used. Where do you think that freshwater

605
00:32:58,640 --> 00:33:03,560
Speaker 2: comes from? Probably the same community. So it's I mean,

606
00:33:03,560 --> 00:33:07,880
Speaker 2: it's truly pillaging local communities like this one.

607
00:33:08,040 --> 00:33:11,920
Speaker 1: Yeah, and I really it broke my heart, but was

608
00:33:11,960 --> 00:33:15,520
Speaker 1: so accurate to hear that resident describe his own community

609
00:33:15,560 --> 00:33:18,520
Speaker 1: as like a sacrifice zone that people just take and

610
00:33:18,560 --> 00:33:21,120
Speaker 1: take and take and exploit and exploit and exploit. And

611
00:33:21,440 --> 00:33:25,680
Speaker 1: they do so for these you know, so called innovations,

612
00:33:25,800 --> 00:33:27,920
Speaker 1: and they're just supposed to be okay with it. They're

613
00:33:27,920 --> 00:33:31,800
Speaker 1: supposed to be okay with being deprived taken from having

614
00:33:31,840 --> 00:33:35,200
Speaker 1: their resources taken and sickened in the process, or they're

615
00:33:35,240 --> 00:33:37,320
Speaker 1: meant to be like thank you for these opportunities to

616
00:33:37,560 --> 00:33:40,920
Speaker 1: do this. It's really just a toxic dynamic, and it's

617
00:33:40,960 --> 00:33:44,720
Speaker 1: one that I think we really need to change. Like

618
00:33:44,720 --> 00:33:51,280
Speaker 1: like I it makes me angry that lawmakers who are

619
00:33:51,400 --> 00:33:53,520
Speaker 1: meant to be representing the folks who put them in

620
00:33:53,560 --> 00:33:56,880
Speaker 1: office have just like abdicated the responsibility on this and

621
00:33:56,920 --> 00:33:59,160
Speaker 1: thrown up their hands and said, oh, maybe maybe they'll

622
00:33:59,160 --> 00:34:01,280
Speaker 1: be a janitorial in it for you. Like, it's just

623
00:34:01,400 --> 00:34:02,440
Speaker 1: very deeply insulting.

624
00:34:06,800 --> 00:34:20,520
Speaker 4: More after a quick break, let's get right back into it.

625
00:34:24,400 --> 00:34:27,399
Speaker 1: So Elon Musk was interviewed and he said that he's

626
00:34:27,400 --> 00:34:30,120
Speaker 1: going to spend a lot less money and time in politics.

627
00:34:30,120 --> 00:34:32,719
Speaker 1: He said, I think I've done enough. We'll see if

628
00:34:32,760 --> 00:34:34,800
Speaker 1: I have a reason to do political spending in the future.

629
00:34:35,360 --> 00:34:38,040
Speaker 1: I don't really see a reason. He's also talking about

630
00:34:38,040 --> 00:34:41,680
Speaker 1: politics a lot less. He used to post about politics NonStop,

631
00:34:41,800 --> 00:34:44,200
Speaker 1: but now it's mostly just about his companies. According to

632
00:34:44,239 --> 00:34:47,160
Speaker 1: the Post, in February, more than half of Musk's posts

633
00:34:47,160 --> 00:34:50,440
Speaker 1: and reposts on x were about Doge. About thirteen percent

634
00:34:50,480 --> 00:34:53,440
Speaker 1: of his February post mentioned Trump by name, nearly double

635
00:34:53,480 --> 00:34:55,920
Speaker 1: that proportion named one of his companies. So far in May,

636
00:34:55,960 --> 00:34:59,400
Speaker 1: those numbers have reversed. Now under twenty percent of his

637
00:34:59,480 --> 00:35:02,799
Speaker 1: posts are out doge or politics, and more than half

638
00:35:02,800 --> 00:35:06,239
Speaker 1: are about his business ventures. So yeah, this is a

639
00:35:06,239 --> 00:35:09,520
Speaker 1: pretty big shift. And I have heard people say like, oh,

640
00:35:09,880 --> 00:35:13,080
Speaker 1: because if companies are taking a hit, he's super unpopular.

641
00:35:13,480 --> 00:35:15,840
Speaker 1: What he's doing in government is unpopular, so he's retreating.

642
00:35:16,160 --> 00:35:18,200
Speaker 1: But I actually see it differently. I think what he's

643
00:35:18,200 --> 00:35:21,120
Speaker 1: actually saying is like, I've got what I wanted, so

644
00:35:21,239 --> 00:35:23,839
Speaker 1: now I can be done. I have, like you know,

645
00:35:24,440 --> 00:35:27,160
Speaker 1: grifted my grift. I have gotten rid of the voices

646
00:35:27,160 --> 00:35:31,200
Speaker 1: who would have regulated my companies. I have made some cushy,

647
00:35:31,400 --> 00:35:33,960
Speaker 1: lucrative contracts. I've got a little money in my pocket.

648
00:35:34,400 --> 00:35:36,319
Speaker 1: I think the government grift has paid off for him.

649
00:35:36,360 --> 00:35:38,919
Speaker 1: He has personally enriched himself and now he can back off.

650
00:35:38,960 --> 00:35:39,640
Speaker 1: That's what I think.

651
00:35:40,880 --> 00:35:43,719
Speaker 2: Again, I really want to disagree with you here, Bridget,

652
00:35:44,280 --> 00:35:46,319
Speaker 2: but I think it's yes, I think it is that.

653
00:35:46,760 --> 00:35:51,920
Speaker 2: But I also do think that the amount of Tesla

654
00:35:52,000 --> 00:35:56,960
Speaker 2: takedown protests, which I mean hats off to the continued

655
00:35:57,000 --> 00:35:59,480
Speaker 2: protests that are taking place on all different kinds of

656
00:35:59,520 --> 00:36:04,640
Speaker 2: dealership and whatnot, as well as the Wisconsin you know,

657
00:36:04,800 --> 00:36:08,200
Speaker 2: Judge seat loss after he poured, however, many millions and

658
00:36:08,200 --> 00:36:10,440
Speaker 2: millions of dollars into that and got his ass handed

659
00:36:10,520 --> 00:36:14,839
Speaker 2: him handed to him by the people of Wisconsin is amazing. Like,

660
00:36:14,880 --> 00:36:18,799
Speaker 2: those two things are huge, and so he even just

661
00:36:18,880 --> 00:36:21,880
Speaker 2: on a pr level, knows that he's not helpful to

662
00:36:21,960 --> 00:36:25,000
Speaker 2: the MAGA brand. But you're I do think you're right

663
00:36:25,040 --> 00:36:29,480
Speaker 2: that the behind the scenes, if you have gotten all

664
00:36:29,560 --> 00:36:35,640
Speaker 2: of our irs information, our social security data, you know,

665
00:36:36,040 --> 00:36:40,759
Speaker 2: if you have now allowed for sharing between federal agencies

666
00:36:40,920 --> 00:36:45,640
Speaker 2: of our private information in addition to, according to whistleblowers,

667
00:36:46,160 --> 00:36:51,120
Speaker 2: possibly foreign governments, you've got a fuck ton of leverage

668
00:36:51,440 --> 00:36:54,080
Speaker 2: and a fucked onn of way to make even more

669
00:36:54,160 --> 00:36:57,200
Speaker 2: money than you already have. So he might have a

670
00:36:57,239 --> 00:37:01,440
Speaker 2: little dip right now. You know, he obviously borrowed or

671
00:37:01,480 --> 00:37:05,640
Speaker 2: he bought Twitter on some Tesla stock that's not doing

672
00:37:05,760 --> 00:37:09,120
Speaker 2: very well. But give him some time when you know,

673
00:37:09,239 --> 00:37:14,120
Speaker 2: big Balls and some other little pepe meme can develop

674
00:37:14,280 --> 00:37:20,280
Speaker 2: some new payment system for federal workers who remain and

675
00:37:20,280 --> 00:37:22,399
Speaker 2: and or sell our data to a foreign I mean,

676
00:37:22,480 --> 00:37:25,440
Speaker 2: like then he's like, we also know that he's strong

677
00:37:25,560 --> 00:37:29,640
Speaker 2: arming other nations into using starlink to get their internet,

678
00:37:29,800 --> 00:37:34,600
Speaker 2: so like bullshit that he's going away, bullshit, he's taking

679
00:37:34,680 --> 00:37:39,640
Speaker 2: a break, He's just pressing pause while more evil is done.

680
00:37:39,920 --> 00:37:43,560
Speaker 1: Yeah, the grift is truly global with him. I I mean,

681
00:37:43,640 --> 00:37:45,440
Speaker 1: I we talked about this on the show before, but

682
00:37:45,840 --> 00:37:48,439
Speaker 1: when he was doing his sort of woe with Me tour,

683
00:37:48,600 --> 00:37:51,439
Speaker 1: being like I'm losing so much money and I'm only

684
00:37:51,480 --> 00:37:53,359
Speaker 1: all I'm trying to do is point out waste and

685
00:37:53,400 --> 00:37:56,160
Speaker 1: fraud and what like, I'm not a bad guy, cry

686
00:37:56,840 --> 00:38:02,520
Speaker 1: merely like I I wish that Like he in my mind,

687
00:38:02,520 --> 00:38:05,160
Speaker 1: he is like the ultimate welfare queen of Like he

688
00:38:05,239 --> 00:38:08,560
Speaker 1: is actually the person who was like scamming and personally

689
00:38:08,680 --> 00:38:11,680
Speaker 1: enriching himself at our dime. He is taking from me

690
00:38:12,040 --> 00:38:14,800
Speaker 1: brokies who live in fucking one bedroom apartments like myself

691
00:38:14,960 --> 00:38:17,400
Speaker 1: to enrich himself. And he's the richest man on earth.

692
00:38:17,320 --> 00:38:20,120
Speaker 2: Three children. He's he's definitionally a welfare.

693
00:38:20,200 --> 00:38:23,560
Speaker 1: To a tea and so it just is wild to me.

694
00:38:24,440 --> 00:38:27,120
Speaker 1: I don't know. I when he's when he's talking about

695
00:38:27,239 --> 00:38:29,400
Speaker 1: like retreating from politics, that completely agree. I don't think

696
00:38:29,440 --> 00:38:31,000
Speaker 1: he I don't think he's retreating at all. I think

697
00:38:31,040 --> 00:38:35,880
Speaker 1: he's like it's just getting he can do more behind

698
00:38:35,920 --> 00:38:38,480
Speaker 1: the scenes than he can in front of the scenes,

699
00:38:38,520 --> 00:38:40,920
Speaker 1: because I think that when he's publicly attached to stuff,

700
00:38:41,200 --> 00:38:43,719
Speaker 1: it doesn't like people don't like him, Like, yeah.

701
00:38:43,480 --> 00:38:45,879
Speaker 2: He's talks and he's got the opposite effect. I mean,

702
00:38:46,160 --> 00:38:47,960
Speaker 2: he should have never been in the public eye. They

703
00:38:48,040 --> 00:38:51,000
Speaker 2: prove that he also you know, in oval office meetings,

704
00:38:51,120 --> 00:38:53,800
Speaker 2: you know, he would get into big fights with different

705
00:38:53,840 --> 00:38:56,920
Speaker 2: agency heads and you know, he was not a pleasant

706
00:38:56,960 --> 00:38:59,560
Speaker 2: person to be around. Dude was like sleeping on couches

707
00:38:59,600 --> 00:39:01,520
Speaker 2: in the White House and not showering and wearing the

708
00:39:01,520 --> 00:39:04,600
Speaker 2: same shit over and over again, like you know, all

709
00:39:04,719 --> 00:39:09,080
Speaker 2: for the American people, like no, all for massive security

710
00:39:09,120 --> 00:39:15,319
Speaker 2: breaches and again stealing our information. So I'm here's my

711
00:39:15,440 --> 00:39:20,520
Speaker 2: thing is like if and when Democrats ever regained control.

712
00:39:21,520 --> 00:39:25,960
Speaker 2: To me, the damage that Doge has done is probably

713
00:39:26,120 --> 00:39:30,160
Speaker 2: the biggest thing that needs remedy. And if there is

714
00:39:30,239 --> 00:39:34,279
Speaker 2: not accountability, if there is not a restoration of both

715
00:39:34,400 --> 00:39:39,439
Speaker 2: jobs but also our data privacy of you know, security protocols,

716
00:39:40,200 --> 00:39:43,880
Speaker 2: I mean, it's really sick to bridge it because like

717
00:39:43,920 --> 00:39:45,799
Speaker 2: you know, we're in a moment where like the oligarchy

718
00:39:45,880 --> 00:39:47,879
Speaker 2: is such, where like the lines have been drawn. If

719
00:39:47,960 --> 00:39:49,480
Speaker 2: a lot of tech people are just like, well, I'm

720
00:39:49,480 --> 00:39:51,520
Speaker 2: in it for the money. Fuck democracy and all the

721
00:39:51,560 --> 00:39:56,680
Speaker 2: sort of veneer of we are an innovative future looking democratic,

722
00:39:57,239 --> 00:40:01,360
Speaker 2: multicultural da da d all. That's bullshit. It's been bullshit.

723
00:40:01,400 --> 00:40:04,960
Speaker 2: But I'm like, I know there are good people in

724
00:40:05,040 --> 00:40:08,080
Speaker 2: Silicon Valley and in tech. I know there are. They're

725
00:40:08,080 --> 00:40:10,920
Speaker 2: not in power, but I know there are, and I

726
00:40:11,000 --> 00:40:14,400
Speaker 2: know there are people who could work with the federal

727
00:40:14,400 --> 00:40:16,880
Speaker 2: government to help us. Shit, So this is me is

728
00:40:16,960 --> 00:40:19,120
Speaker 2: sort of like think, you know, future dripping about like

729
00:40:19,960 --> 00:40:22,360
Speaker 2: how do we get all of this back? How do

730
00:40:22,440 --> 00:40:25,520
Speaker 2: we wrest this control back from these gorules?

731
00:40:25,840 --> 00:40:28,840
Speaker 1: Yeah, I firmly believe that. I mean, there was a

732
00:40:28,880 --> 00:40:33,520
Speaker 1: time where you had more thoughtful, ethical voices and tech

733
00:40:33,520 --> 00:40:36,680
Speaker 1: who genuinely were interested in using technology to build a

734
00:40:36,719 --> 00:40:39,440
Speaker 1: better future. And I think that, you know, a lot

735
00:40:39,440 --> 00:40:42,959
Speaker 1: of those voices got sideline erased, pushed out. Those happen

736
00:40:43,080 --> 00:40:45,760
Speaker 1: to be diverse voices as well, and so those people

737
00:40:45,800 --> 00:40:49,280
Speaker 1: are there, they exist. I think that people like Elon

738
00:40:49,360 --> 00:40:51,440
Speaker 1: Musk and other tech leaders have really been able to

739
00:40:51,440 --> 00:40:54,680
Speaker 1: flip the script and make it seem like one technology

740
00:40:54,719 --> 00:40:56,520
Speaker 1: only gets built on a handful of companies by a

741
00:40:56,520 --> 00:40:59,600
Speaker 1: handful of people. That's so not true too, that the

742
00:40:59,640 --> 00:41:02,400
Speaker 1: only people who are doing anything, or the only voices

743
00:41:02,440 --> 00:41:07,000
Speaker 1: worth listening to in tech are the most unethical, not thoughtful,

744
00:41:07,440 --> 00:41:13,960
Speaker 1: paranoid like delusional, like not with it, people like it

745
00:41:14,360 --> 00:41:17,400
Speaker 1: truly is. And it's like like we have gotten mixed

746
00:41:17,520 --> 00:41:20,480
Speaker 1: up and are tape being taken along for the ride

747
00:41:20,640 --> 00:41:22,960
Speaker 1: of these horrible people who are telling us this is

748
00:41:23,000 --> 00:41:24,759
Speaker 1: the way it has to be. And I know, I

749
00:41:24,880 --> 00:41:26,960
Speaker 1: firmly believe that that is a lie. It does not

750
00:41:27,120 --> 00:41:29,120
Speaker 1: have to be this way. It was not always that way,

751
00:41:29,360 --> 00:41:31,919
Speaker 1: and they're banking on us like memory, holding the fact

752
00:41:31,920 --> 00:41:33,680
Speaker 1: that it used to not be that way. That when

753
00:41:33,680 --> 00:41:35,000
Speaker 1: you thought there was a time where when you thought

754
00:41:35,000 --> 00:41:39,280
Speaker 1: about technology, it was exciting, You had apps that you loved.

755
00:41:39,480 --> 00:41:41,400
Speaker 1: When you thought about what the internet was, it was

756
00:41:41,440 --> 00:41:44,200
Speaker 1: like lots of weird little sites that people were running

757
00:41:44,239 --> 00:41:45,600
Speaker 1: just because of the fun of it, or just because

758
00:41:45,600 --> 00:41:48,480
Speaker 1: they cared about something, or it was a community of

759
00:41:48,480 --> 00:41:51,760
Speaker 1: people gathering, you know, around one idea or one passion.

760
00:41:52,080 --> 00:41:54,120
Speaker 1: And I think that we have forgotten, we have allowed

761
00:41:54,120 --> 00:41:56,920
Speaker 1: these tech leaders to memory hold that and make us

762
00:41:56,920 --> 00:41:59,160
Speaker 1: forget what it used to be like it used. I

763
00:41:59,160 --> 00:42:01,560
Speaker 1: don't want to get too nostalgic, because like it definitely

764
00:42:01,560 --> 00:42:03,920
Speaker 1: had problems back in the day as well, but like

765
00:42:04,360 --> 00:42:05,960
Speaker 1: it used to be better than this, and it can.

766
00:42:06,520 --> 00:42:08,359
Speaker 1: It has been better than this, and it can be

767
00:42:08,360 --> 00:42:10,040
Speaker 1: better than this. We deserve better than this.

768
00:42:10,480 --> 00:42:13,399
Speaker 2: Yes, And and actually the height of freedom, I mean,

769
00:42:13,440 --> 00:42:16,719
Speaker 2: what's so? I mean they're open hypocrites and elon and

770
00:42:17,360 --> 00:42:20,160
Speaker 2: you know the rest of the Peter thiels like they're

771
00:42:20,160 --> 00:42:22,640
Speaker 2: all full of shit. I mean they're all like, oh,

772
00:42:22,840 --> 00:42:26,719
Speaker 2: free speech and free society and and and it's like, yeah,

773
00:42:26,719 --> 00:42:30,480
Speaker 2: but the old Internet was the freest we've ever been,

774
00:42:30,840 --> 00:42:35,120
Speaker 2: you know, like the Internet being run by ten companies,

775
00:42:35,200 --> 00:42:39,760
Speaker 2: tech being run by like three companies is not freedom

776
00:42:40,040 --> 00:42:42,839
Speaker 2: at all. So I think that's the other thing is

777
00:42:42,840 --> 00:42:45,719
Speaker 2: like we also have to reclaim this mantle of freedom

778
00:42:46,000 --> 00:42:50,120
Speaker 2: and free speech. And it's just wild to me that

779
00:42:50,600 --> 00:42:52,960
Speaker 2: And it's such a failure of the Democratic Party too,

780
00:42:53,000 --> 00:42:56,680
Speaker 2: that like we can I started to get really sick

781
00:42:56,719 --> 00:42:58,200
Speaker 2: to my stomach when I think about all the things

782
00:42:58,200 --> 00:43:01,600
Speaker 2: that we could have, would should have, But like Democratic

783
00:43:01,600 --> 00:43:05,640
Speaker 2: Party could have been the party of privacy and you

784
00:43:05,640 --> 00:43:10,080
Speaker 2: know ending, you know, surveillance, and of course Obama did

785
00:43:10,080 --> 00:43:12,040
Speaker 2: a lot of good things, but Mom also went after

786
00:43:12,239 --> 00:43:14,400
Speaker 2: Edward Stein. And it's like, no, we could have actually

787
00:43:14,440 --> 00:43:17,400
Speaker 2: planted a flag on that and been like, we protect

788
00:43:17,400 --> 00:43:19,920
Speaker 2: your data. There's nothing more important than protecting your data.

789
00:43:20,000 --> 00:43:22,800
Speaker 2: You have the freedom to you know, use the Internet

790
00:43:22,840 --> 00:43:24,480
Speaker 2: as you want, and it shouldn't be just a bunch

791
00:43:24,520 --> 00:43:28,759
Speaker 2: of conglomerates and Biden's antitrusts, you know, FTC started doing

792
00:43:28,800 --> 00:43:32,640
Speaker 2: some of that. So I just it's like, god, it

793
00:43:32,680 --> 00:43:35,120
Speaker 2: makes me so terrified because this is one thing where

794
00:43:35,160 --> 00:43:39,600
Speaker 2: also Democrats still believe in that old culture of tech

795
00:43:40,120 --> 00:43:43,759
Speaker 2: and they use it again as like a shield to

796
00:43:43,880 --> 00:43:47,880
Speaker 2: still raise money from actually really villainous people.

797
00:43:48,239 --> 00:43:51,160
Speaker 1: I think that democrats get to sort of in ways

798
00:43:51,160 --> 00:43:53,960
Speaker 1: that are unearned, in my opinion, get to enjoy like

799
00:43:54,040 --> 00:43:56,359
Speaker 1: being a little bit better on the issue, even though

800
00:43:56,400 --> 00:43:58,359
Speaker 1: like you're not really doing much on it. And like,

801
00:43:58,760 --> 00:44:02,200
Speaker 1: I if we could go back in time and have

802
00:44:03,560 --> 00:44:07,680
Speaker 1: the Democratic Party, Yeah, as you said, make privacy and

803
00:44:07,760 --> 00:44:10,880
Speaker 1: internet freedom part and parcel of what it meant to

804
00:44:10,920 --> 00:44:13,359
Speaker 1: be a democrat. Imagine we're going to be today, Like,

805
00:44:13,400 --> 00:44:15,560
Speaker 1: but things could be would be so different.

806
00:44:15,320 --> 00:44:18,279
Speaker 2: Right, And actually I do think like the grift of

807
00:44:18,880 --> 00:44:23,520
Speaker 2: oh I'm a forward thinking you know, pro democracy, multi

808
00:44:23,760 --> 00:44:28,800
Speaker 2: and multiracial, multi religious, you know, like support DEI program's company,

809
00:44:29,120 --> 00:44:32,760
Speaker 2: I think that grift was kind of meant to pull

810
00:44:32,840 --> 00:44:36,439
Speaker 2: the wool over on. I think some liberals eyes and

811
00:44:36,680 --> 00:44:40,440
Speaker 2: that you know, the final form really is monopoly and control.

812
00:44:40,920 --> 00:44:44,360
Speaker 2: And you know, now Mark Zuckerberg god to be Sheryl Sandberg,

813
00:44:44,400 --> 00:44:46,440
Speaker 2: which is just so funny and rich, and I just

814
00:44:47,239 --> 00:44:50,600
Speaker 2: could I just like this, I need I could write

815
00:44:50,640 --> 00:44:54,120
Speaker 2: like a ten episode podcast about the rise and fall

816
00:44:54,200 --> 00:44:57,879
Speaker 2: of lean In, you know, because it's like, nah, man,

817
00:44:57,920 --> 00:45:02,440
Speaker 2: the final form is we're in control where the oligarchs,

818
00:45:02,480 --> 00:45:05,120
Speaker 2: fuck you you allowed us to get this big ha

819
00:45:05,200 --> 00:45:08,400
Speaker 2: ha ha. We just played with some you know, lightweight

820
00:45:09,080 --> 00:45:12,239
Speaker 2: DEI programs, which are good again, but we just you know,

821
00:45:12,480 --> 00:45:16,680
Speaker 2: we don't actually care about real equity or real inclusion

822
00:45:16,960 --> 00:45:21,440
Speaker 2: or you know, actually doing you know, making sure our

823
00:45:21,520 --> 00:45:29,000
Speaker 2: spaces are not actually hotbeds of racism and misogyny. So anyway, first.

824
00:45:28,800 --> 00:45:32,279
Speaker 1: Of all, I have met Sheryl Sandberg in person, and

825
00:45:33,360 --> 00:45:34,480
Speaker 1: I don't know if I've told this story in the

826
00:45:34,480 --> 00:45:37,920
Speaker 1: podcast before, but I was like barely invited to a

827
00:45:37,920 --> 00:45:40,319
Speaker 1: book launch she did, and I will never forget it

828
00:45:40,360 --> 00:45:42,960
Speaker 1: was sort of like it was right after Trump got elected,

829
00:45:43,160 --> 00:45:47,080
Speaker 1: and it was like it was at a very different time,

830
00:45:47,160 --> 00:45:49,680
Speaker 1: and I remember it was all of these like journalists

831
00:45:49,719 --> 00:45:53,320
Speaker 1: and like women media, like Rah rah women in media.

832
00:45:53,400 --> 00:45:56,200
Speaker 1: And this was right when we were starting to learn

833
00:45:56,239 --> 00:45:58,880
Speaker 1: more about like Cambridge Analytica and what the role that

834
00:45:58,920 --> 00:46:02,840
Speaker 1: Facebook had is getting Trump elected. And Cheryl Sandberg is

835
00:46:02,840 --> 00:46:07,680
Speaker 1: there doing a very kind of like puffy Q and

836
00:46:07,719 --> 00:46:10,920
Speaker 1: A about her new book about grief, Option B and

837
00:46:11,120 --> 00:46:13,440
Speaker 1: somebody asked. She was like, oh, I've been reading about

838
00:46:13,480 --> 00:46:18,239
Speaker 1: the way that Facebook has been perhaps illegally using all

839
00:46:18,280 --> 00:46:20,239
Speaker 1: of our data to help get you know, to help

840
00:46:20,280 --> 00:46:22,759
Speaker 1: get Trump elected and meddle our elections. And I'll never forget.

841
00:46:22,840 --> 00:46:26,240
Speaker 1: She was like, today's about women's empowerment. Let's stay on focus.

842
00:46:26,520 --> 00:46:32,040
Speaker 1: Like that's how she answered the question. Today's about the women.

843
00:46:32,200 --> 00:46:34,560
Speaker 1: Let's let's let's keep our focus on that.

844
00:46:34,680 --> 00:46:39,080
Speaker 2: I have so many words, but that is truly disgraceful.

845
00:46:39,920 --> 00:46:43,240
Speaker 1: It was, And I have to say, you're it's almost

846
00:46:43,239 --> 00:46:46,680
Speaker 1: like you are a mind reader with the whole company's

847
00:46:47,000 --> 00:46:50,359
Speaker 1: kind of limply embracing DEI and then just using it

848
00:46:50,400 --> 00:46:52,760
Speaker 1: to gobble up more power. Because did you hear about

849
00:46:53,000 --> 00:46:58,560
Speaker 1: Verizon and DEI, So basically, in twenty twenty, Verizon claimed

850
00:46:58,560 --> 00:47:01,560
Speaker 1: to be like all in on DEE. They put out

851
00:47:01,600 --> 00:47:03,840
Speaker 1: statements after the death of George Floyd that was like,

852
00:47:03,880 --> 00:47:07,320
Speaker 1: diversity and inclusion are greatest superpowers. YadA, YadA, YadA. Cut

853
00:47:07,360 --> 00:47:11,000
Speaker 1: to this week, Verizon sends a letter to the FCC

854
00:47:11,400 --> 00:47:14,319
Speaker 1: stating that it is ending all DEI policy, So no

855
00:47:14,400 --> 00:47:17,719
Speaker 1: more DEI teams or roles. They're taking all the all

856
00:47:17,760 --> 00:47:21,200
Speaker 1: the references to DEI from their training materials, no more

857
00:47:21,239 --> 00:47:24,520
Speaker 1: workforce diversity goals, and they're taking it further because they're

858
00:47:24,560 --> 00:47:27,600
Speaker 1: basically like memory holding it. They scrubbed the fact that

859
00:47:27,719 --> 00:47:30,400
Speaker 1: Verizon was ever involved in any of this from their website.

860
00:47:30,719 --> 00:47:33,920
Speaker 1: When you go to the DEI pages online, it just

861
00:47:34,000 --> 00:47:36,600
Speaker 1: redirects to generic Verizon content, and.

862
00:47:37,000 --> 00:47:37,600
Speaker 2: Oh my god.

863
00:47:37,680 --> 00:47:40,840
Speaker 1: The Verizon said that this was because of like Trump's

864
00:47:40,880 --> 00:47:43,960
Speaker 1: executive orders and Supreme Court and federal mandates, but like

865
00:47:44,320 --> 00:47:47,920
Speaker 1: there's no Supreme Court ruling banning DEI or you know,

866
00:47:48,280 --> 00:47:52,080
Speaker 1: those kinds of goals, and you know, certainly other companies

867
00:47:52,120 --> 00:47:54,720
Speaker 1: like Costco when Trump was like, you need to stop DEI.

868
00:47:54,800 --> 00:47:56,520
Speaker 1: They were like, kick rock, will do what we want.

869
00:47:56,920 --> 00:48:00,360
Speaker 1: And the timing of this is very suspicious because Verrizon

870
00:48:00,360 --> 00:48:03,759
Speaker 1: announced this just a day before the FCC approved Verizon's

871
00:48:03,760 --> 00:48:08,000
Speaker 1: twenty billion dollar acquisition of Frontier Communications. UH. The SCC's

872
00:48:08,000 --> 00:48:12,000
Speaker 1: approval emphasized that Verizon had gotten rid of their their

873
00:48:12,080 --> 00:48:15,880
Speaker 1: quote discriminatory DEI policies, and it really does seem like

874
00:48:16,040 --> 00:48:20,040
Speaker 1: Verizon was like, fine, well, abandon all of our commitments

875
00:48:20,080 --> 00:48:22,719
Speaker 1: to DEI if you were if we're able to get

876
00:48:22,719 --> 00:48:27,320
Speaker 1: this merger, and the SCC was like, bet sure, great dude,

877
00:48:27,600 --> 00:48:28,840
Speaker 1: that's exactly what happened.

878
00:48:29,160 --> 00:48:33,560
Speaker 2: It's not even there. That is exactly what happened. There's

879
00:48:33,680 --> 00:48:38,839
Speaker 2: no mystery here. That is so terrifying and disgusting. I mean,

880
00:48:38,880 --> 00:48:41,960
Speaker 2: and you see the same thing with you know, CBS,

881
00:48:42,040 --> 00:48:45,359
Speaker 2: right paramount is trying to what is it work with

882
00:48:45,480 --> 00:48:49,359
Speaker 2: like Skynet News one, I don't know where the fuck

883
00:48:49,440 --> 00:48:51,640
Speaker 2: is sky something, and they're trying to get their merger

884
00:48:51,680 --> 00:48:53,759
Speaker 2: and it's like, yeah, oh, we can just do this

885
00:48:54,080 --> 00:48:58,160
Speaker 2: by getting rid of all of these policies. These are

886
00:48:58,160 --> 00:49:01,279
Speaker 2: going to have massive impacts on workers. I mean, that's

887
00:49:01,360 --> 00:49:03,200
Speaker 2: I think the other thing that we need to remember

888
00:49:03,239 --> 00:49:07,480
Speaker 2: about the anti DEI backlash is it's it's really it's

889
00:49:07,520 --> 00:49:11,400
Speaker 2: a worker's fight. It's a fight on an attack on workers.

890
00:49:11,480 --> 00:49:13,600
Speaker 2: Everything we're seeing as an attack on workers, and we

891
00:49:13,760 --> 00:49:16,560
Speaker 2: have to like again, whenever you know, it's like, the

892
00:49:16,600 --> 00:49:19,640
Speaker 2: working class is women of color, predominantly women of color.

893
00:49:19,719 --> 00:49:23,320
Speaker 2: That is just what it is. The amount of Black

894
00:49:23,400 --> 00:49:26,760
Speaker 2: Americans in federal jobs. What is it like twenty percent

895
00:49:26,800 --> 00:49:28,959
Speaker 2: of the workforce or something, or twenty percent. I forgot

896
00:49:29,000 --> 00:49:31,719
Speaker 2: what the twenty percent was, but it's a huge percentage.

897
00:49:32,320 --> 00:49:34,799
Speaker 2: This is deliberate. It's an attack on workers. It's a

898
00:49:34,920 --> 00:49:36,960
Speaker 2: racist attack on workers.

899
00:49:36,960 --> 00:49:37,520
Speaker 1: Absolutely.

900
00:49:38,120 --> 00:49:42,400
Speaker 2: But yeah, that's that's so sick. God, I'm so glad

901
00:49:42,480 --> 00:49:44,520
Speaker 2: Verizon has shipped service in my neighborhood and we had

902
00:49:44,520 --> 00:49:46,840
Speaker 2: to switch to AT and T. I'm sure AT and

903
00:49:46,880 --> 00:49:48,520
Speaker 2: T is up to no good and I'm gonna be

904
00:49:48,560 --> 00:49:50,880
Speaker 2: a T mobile bitch at some point. It's gonna have

905
00:49:50,960 --> 00:49:56,719
Speaker 2: to happen more.

906
00:49:56,719 --> 00:50:08,759
Speaker 4: After a quick break, let's get right back into it.

907
00:50:12,280 --> 00:50:14,719
Speaker 1: Wait, I have to ask switching gears a little bit.

908
00:50:14,920 --> 00:50:19,400
Speaker 1: Did you hear about this fake AI generated booklist that

909
00:50:19,480 --> 00:50:21,080
Speaker 1: was published in the Chicago Sun Times.

910
00:50:22,120 --> 00:50:22,319
Speaker 3: Oh?

911
00:50:22,360 --> 00:50:24,920
Speaker 1: My gosh, okay, it's all I've been thinking about for

912
00:50:25,400 --> 00:50:27,680
Speaker 1: the whole week. So it's just like a very wild

913
00:50:27,680 --> 00:50:31,720
Speaker 1: story to me. Basically, some newspapers, like print newspapers, including

914
00:50:31,760 --> 00:50:34,360
Speaker 1: the Chicago Sun Times and at least one edition of

915
00:50:34,360 --> 00:50:39,279
Speaker 1: the Philadelphia Inquirer, published a syndicated summer booklist that was

916
00:50:39,320 --> 00:50:43,680
Speaker 1: like obviously AI generated that included fake books, like made

917
00:50:43,760 --> 00:50:48,800
Speaker 1: up books by famous authors. So it said that Perceville Emritt,

918
00:50:48,800 --> 00:50:51,640
Speaker 1: who won the Pulitzer this year for fiction, was coming

919
00:50:51,640 --> 00:50:54,200
Speaker 1: out with a book called The rain Makers that's supposedly

920
00:50:54,200 --> 00:50:57,600
Speaker 1: set in quote the near future American West, where artificially

921
00:50:57,600 --> 00:51:00,560
Speaker 1: induced rain has become a luxury commodity. Uh, bullshit, that

922
00:51:00,560 --> 00:51:02,800
Speaker 1: book doesn't exist. He did not publish that book.

923
00:51:02,840 --> 00:51:03,440
Speaker 2: Oh my god.

924
00:51:03,520 --> 00:51:06,279
Speaker 1: They said that Chilean author Isabella Allende was putting out

925
00:51:06,280 --> 00:51:09,520
Speaker 1: a book called Tidewater Dreams, and they described it as

926
00:51:10,040 --> 00:51:15,239
Speaker 1: these the first climate fiction novel all the first, have

927
00:51:15,320 --> 00:51:18,560
Speaker 1: the very first. These are not real books.

928
00:51:18,600 --> 00:51:20,680
Speaker 2: In fact, Octavia Butler.

929
00:51:20,840 --> 00:51:24,600
Speaker 1: She would be to differ. In fact, of the fifteen

930
00:51:24,680 --> 00:51:27,880
Speaker 1: books on this like must read twenty twenty five summer

931
00:51:28,080 --> 00:51:30,920
Speaker 1: fiction list, only five of the books were real. The

932
00:51:30,960 --> 00:51:32,400
Speaker 1: rest of them were all made up.

933
00:51:32,880 --> 00:51:35,880
Speaker 2: Yo, So they straight up outsourced their reading list to

934
00:51:36,000 --> 00:51:37,720
Speaker 2: AI and thought no one would notice.

935
00:51:37,800 --> 00:51:40,480
Speaker 1: Yes, and they're not, Like they're like, it would be

936
00:51:40,560 --> 00:51:42,680
Speaker 1: bad enough if it was just like an online thing.

937
00:51:42,840 --> 00:51:45,760
Speaker 1: This was in their print edition. Like people got pictures

938
00:51:45,800 --> 00:51:49,840
Speaker 1: of themselves holding the print edition of this, So like,

939
00:51:50,080 --> 00:51:52,000
Speaker 1: how did this come to be? I saw on Blue

940
00:51:52,040 --> 00:51:54,440
Speaker 1: Sky that the Chicago Sun Time. Somebody who worked there

941
00:51:54,520 --> 00:51:57,280
Speaker 1: was like, we're looking into how this got published, which

942
00:51:57,840 --> 00:52:00,600
Speaker 1: that also raises questions of, like you don't know how

943
00:52:00,600 --> 00:52:03,680
Speaker 1: this got published? Very good question, like definitely worth looking into,

944
00:52:04,200 --> 00:52:07,120
Speaker 1: so it gets a little stickier. According to Victor Limb,

945
00:52:07,160 --> 00:52:09,680
Speaker 1: the marketing director of the Chicago Sun Times parent company,

946
00:52:09,760 --> 00:52:12,760
Speaker 1: Chicago Public Media, the list was part of licensed content

947
00:52:12,840 --> 00:52:16,920
Speaker 1: provided by King Features, a unit of the publisher Hearst Newspapers.

948
00:52:17,320 --> 00:52:19,800
Speaker 1: According to NPR, even though the piece has no byline,

949
00:52:20,600 --> 00:52:23,960
Speaker 1: a writer did claim responsibility for it and did say

950
00:52:23,960 --> 00:52:27,759
Speaker 1: that it was generated by AI. Obviously, he says, huge

951
00:52:27,800 --> 00:52:29,480
Speaker 1: mistake on my part and has nothing to do with

952
00:52:29,480 --> 00:52:31,840
Speaker 1: the Sun Times. They trust the content that they purchased

953
00:52:31,840 --> 00:52:33,880
Speaker 1: from me is accurate, and I've betrayed that trust. It

954
00:52:33,960 --> 00:52:35,320
Speaker 1: is on me one hundred percent.

955
00:52:36,160 --> 00:52:39,839
Speaker 2: Wait, I love it. I love reading a little bit more.

956
00:52:39,960 --> 00:52:44,680
Speaker 2: This guy, the freelancer says that while he does sometimes

957
00:52:44,760 --> 00:52:47,320
Speaker 2: use AI to create content, he typically checks it before

958
00:52:47,360 --> 00:52:47,960
Speaker 2: submitting it.

959
00:52:49,200 --> 00:52:54,360
Speaker 1: Oh so you what I can what I can, Yo, bridgie.

960
00:52:54,520 --> 00:52:59,040
Speaker 2: Like I used to write when I lived in Argentina

961
00:52:59,120 --> 00:53:01,359
Speaker 2: years and years and years, I'm not really like ten

962
00:53:01,440 --> 00:53:03,440
Speaker 2: years ago. Like one of the things that there was,

963
00:53:03,440 --> 00:53:06,560
Speaker 2: like a freelance gig was farmed out. Was just like

964
00:53:06,640 --> 00:53:11,719
Speaker 2: writing travel guides for some online site about cities I

965
00:53:11,719 --> 00:53:15,120
Speaker 2: had never been to. But I did my research and

966
00:53:15,239 --> 00:53:17,680
Speaker 2: looked at other guides and looked at the city explanations

967
00:53:17,719 --> 00:53:20,160
Speaker 2: and just kind of like I didn't plagiarize, but I

968
00:53:20,200 --> 00:53:23,360
Speaker 2: wrote my own after reading a bunch of other guides

969
00:53:23,520 --> 00:53:27,560
Speaker 2: version for this guide. Now, that is very much like

970
00:53:28,719 --> 00:53:30,920
Speaker 2: that job right there, which maybe I don't know how

971
00:53:30,960 --> 00:53:34,399
Speaker 2: much should I get one hundred dollars is definitely being

972
00:53:34,400 --> 00:53:38,400
Speaker 2: farmed out to AI as we speak. But like I

973
00:53:38,480 --> 00:53:41,480
Speaker 2: love the idea that, like if I had that job now,

974
00:53:41,600 --> 00:53:44,520
Speaker 2: my lazy ass couldn't even do my own fucking reasearch

975
00:53:44,600 --> 00:53:49,319
Speaker 2: on a listical on a fucking listicle of books, and

976
00:53:49,480 --> 00:53:50,880
Speaker 2: ironically their.

977
00:53:50,920 --> 00:53:53,120
Speaker 1: Books you have to read.

978
00:53:53,160 --> 00:53:54,600
Speaker 2: You don't even have to read the book when you

979
00:53:54,680 --> 00:53:55,920
Speaker 2: got to read the title.

980
00:53:56,360 --> 00:53:59,000
Speaker 1: You just go to the books that've been released in.

981
00:53:59,000 --> 00:54:03,160
Speaker 2: Twenty twenty five. I just look at just go to publishers.

982
00:54:03,400 --> 00:54:05,880
Speaker 2: I don't even like I don't follow books, but like,

983
00:54:06,040 --> 00:54:08,960
Speaker 2: I don't know Penguin Random House, Like, it's so wild

984
00:54:08,960 --> 00:54:11,160
Speaker 2: to me that someone And and look if he's like

985
00:54:11,600 --> 00:54:13,960
Speaker 2: if he came clean and was like, listen, I got

986
00:54:13,960 --> 00:54:17,200
Speaker 2: fifty dollars to do this article sucked the Sun Times,

987
00:54:17,440 --> 00:54:20,960
Speaker 2: I will I'm like, I'm with him, But come on,

988
00:54:21,320 --> 00:54:25,640
Speaker 2: my guy, how many people in Memphis can't breathe because

989
00:54:25,680 --> 00:54:29,520
Speaker 2: you had to do this Canada bai for how much

990
00:54:29,600 --> 00:54:32,200
Speaker 2: fresh water was used so we could create a fake

991
00:54:32,520 --> 00:54:33,760
Speaker 2: Isabella Yende book.

992
00:54:34,200 --> 00:54:36,640
Speaker 1: And that's I mean that. The commentary around that pretty

993
00:54:36,719 --> 00:54:39,880
Speaker 1: much said exactly that. Kelly Jensen, who is a former

994
00:54:39,920 --> 00:54:42,920
Speaker 1: librarian and the editor of Book Riot, had a very

995
00:54:42,960 --> 00:54:45,359
Speaker 1: good point. She said, this is the future of book

996
00:54:45,360 --> 00:54:49,359
Speaker 1: recommendations when libraries are defunded and dismantled. Trained professionals are

997
00:54:49,400 --> 00:54:53,480
Speaker 1: removed in exchange for made up, inaccurate garbage. And it's

998
00:54:53,560 --> 00:54:56,160
Speaker 1: just like what you were saying, Like you couldn't even

999
00:54:57,280 --> 00:54:59,879
Speaker 1: scroll Amazon and be like, well, I haven't read this book,

1000
00:54:59,880 --> 00:55:02,040
Speaker 1: but it's a book you could buy it that exist.

1001
00:55:01,800 --> 00:55:08,320
Speaker 2: Exactly exactly, It's real, Like what was the prompt to

1002
00:55:08,800 --> 00:55:11,640
Speaker 2: like AI is also bad? You know what I'm saying.

1003
00:55:11,680 --> 00:55:13,759
Speaker 2: AI is not actually good at it. And that's even

1004
00:55:13,800 --> 00:55:16,680
Speaker 2: if it were good, and in some cases it is,

1005
00:55:16,880 --> 00:55:21,880
Speaker 2: I still contest fuck AI and I just again I

1006
00:55:22,160 --> 00:55:26,400
Speaker 2: don't know, like especially as writers, because what you're doing

1007
00:55:27,080 --> 00:55:31,440
Speaker 2: is you're actively undermining your goddamn job. I don't know.

1008
00:55:31,440 --> 00:55:33,040
Speaker 2: I have a lot of thoughts because as I came

1009
00:55:33,040 --> 00:55:35,400
Speaker 2: from aj plus you know, Valgaiesier Media, and they were like,

1010
00:55:35,440 --> 00:55:37,239
Speaker 2: you know, we were doing spearheading a lot of this

1011
00:55:37,440 --> 00:55:40,400
Speaker 2: like short form content, but but BA text on screen

1012
00:55:40,760 --> 00:55:44,600
Speaker 2: over images, right, that was like now this news and

1013
00:55:44,760 --> 00:55:48,120
Speaker 2: aj plus were really big on Facebook. Now all of

1014
00:55:48,160 --> 00:55:51,960
Speaker 2: that stuff is just AI. I think I'm assuming. I

1015
00:55:52,000 --> 00:55:55,359
Speaker 2: believe it can generate like a couple of images from

1016
00:55:55,400 --> 00:56:01,600
Speaker 2: a story text on screen and then done. So it

1017
00:56:01,680 --> 00:56:04,440
Speaker 2: is it's not like, oh, yeah, we've we shouldn't have

1018
00:56:04,520 --> 00:56:07,320
Speaker 2: created the terminator, you know, or the T one thousand,

1019
00:56:07,440 --> 00:56:10,400
Speaker 2: but like there is a little bit of like this,

1020
00:56:10,520 --> 00:56:14,360
Speaker 2: what is what happens when like with the I don't know,

1021
00:56:14,440 --> 00:56:18,640
Speaker 2: the sort of shorthand and shittification of content and news

1022
00:56:18,680 --> 00:56:21,959
Speaker 2: in general. I'm having a little bit of a existential

1023
00:56:22,000 --> 00:56:22,560
Speaker 2: moment here.

1024
00:56:22,680 --> 00:56:25,719
Speaker 1: Yeah, I mean, I wish so deeply I could say

1025
00:56:25,800 --> 00:56:29,520
Speaker 1: I've never used AI, but I have been known to

1026
00:56:29,600 --> 00:56:33,160
Speaker 1: use chatshept if I have to write a rough email,

1027
00:56:33,200 --> 00:56:34,759
Speaker 1: like an email where I'm like, oh, I really don't

1028
00:56:34,760 --> 00:56:36,759
Speaker 1: want to write this, or like this is I don't

1029
00:56:36,760 --> 00:56:39,320
Speaker 1: know what to say, like a like a like a

1030
00:56:39,360 --> 00:56:41,839
Speaker 1: complic an email, right, I have to convey a complicated

1031
00:56:42,000 --> 00:56:43,400
Speaker 1: set of feelings.

1032
00:56:43,280 --> 00:56:48,640
Speaker 2: And oh, okay, it's complicated feelings. Let's say AI.

1033
00:56:49,280 --> 00:56:53,040
Speaker 1: I feel like that's probably the worst, the worst youth.

1034
00:56:52,920 --> 00:56:55,600
Speaker 2: Say tell me you're talking about a breakup without telling

1035
00:56:55,640 --> 00:56:55,919
Speaker 2: me your.

1036
00:56:56,080 --> 00:56:59,040
Speaker 1: Yeah, right, it's I don't see it will help you

1037
00:56:59,680 --> 00:57:02,880
Speaker 1: if you dreading writing a breakup email, it could help you.

1038
00:57:02,880 --> 00:57:05,160
Speaker 1: I'll put it that way. But I will say, like

1039
00:57:05,239 --> 00:57:09,160
Speaker 1: having a big think about it. I had a similar

1040
00:57:09,200 --> 00:57:12,000
Speaker 1: existential like spin out about this because I was like,

1041
00:57:12,280 --> 00:57:15,040
Speaker 1: don't I owe the people who are like actually in

1042
00:57:15,120 --> 00:57:17,720
Speaker 1: my life the time to sit down and like put

1043
00:57:17,760 --> 00:57:20,080
Speaker 1: my thoughts together, and even if it's hard, even if

1044
00:57:20,120 --> 00:57:23,640
Speaker 1: it's cathartic even if it's difficult, don't I owe them

1045
00:57:23,680 --> 00:57:26,920
Speaker 1: me the human actually sitting down and like like writing

1046
00:57:26,960 --> 00:57:29,040
Speaker 1: out how I feel before I send it, as opposed

1047
00:57:29,080 --> 00:57:31,800
Speaker 1: to just like asking chat GBT to do it for me.

1048
00:57:32,240 --> 00:57:35,960
Speaker 1: I really had a like deep, deep, I don't want

1049
00:57:35,960 --> 00:57:38,320
Speaker 1: to say crisis, but like you know, and I think

1050
00:57:38,360 --> 00:57:40,480
Speaker 1: when I hear people like Mark Zuckerberg talking about the

1051
00:57:40,520 --> 00:57:44,560
Speaker 1: future of friendship, how you know, Facebook, he admits, is

1052
00:57:44,600 --> 00:57:47,040
Speaker 1: like no longer for friends in the future, role have

1053
00:57:47,160 --> 00:57:49,280
Speaker 1: AI friends on Facebook and that's who we'll talk to.

1054
00:57:49,360 --> 00:57:52,000
Speaker 1: It's like, that's not a future that I want. Even

1055
00:57:52,120 --> 00:57:56,440
Speaker 1: when human to human connection is difficult or hard or emotional,

1056
00:57:56,840 --> 00:57:58,840
Speaker 1: that's the point of being alive. Like, I don't want

1057
00:57:58,840 --> 00:58:00,440
Speaker 1: to outsource that. I don't want my I don't want

1058
00:58:00,440 --> 00:58:02,320
Speaker 1: my friend to be AI and never like.

1059
00:58:02,440 --> 00:58:07,040
Speaker 2: But also that is the point when you are an

1060
00:58:07,160 --> 00:58:13,600
Speaker 2: unsuckable little shit, uh you know, and you all got

1061
00:58:13,640 --> 00:58:17,560
Speaker 2: into tech starting to rank chicks rather than talk to

1062
00:58:17,600 --> 00:58:22,320
Speaker 2: them in their face. That's what happens. I mean again,

1063
00:58:22,360 --> 00:58:25,640
Speaker 2: we're just creating all Like the word tech bro's been

1064
00:58:25,680 --> 00:58:29,760
Speaker 2: around forever and it is a smarmy kid that cannot

1065
00:58:29,800 --> 00:58:33,520
Speaker 2: make eye contact with anybody, but also makes more money

1066
00:58:33,520 --> 00:58:35,840
Speaker 2: than you'll ever see in your life and dresses like shit.

1067
00:58:36,320 --> 00:58:38,600
Speaker 1: Yeah, And are these the people we want to take

1068
00:58:38,640 --> 00:58:40,680
Speaker 1: our cues for the future of friendship from? Like, do

1069
00:58:40,720 --> 00:58:43,960
Speaker 1: you want someone like Mark Zuckerberd in charge of design?

1070
00:58:44,000 --> 00:58:47,560
Speaker 1: If using technology to design the future of what friendship

1071
00:58:47,600 --> 00:58:49,760
Speaker 1: will look like in your life? I would argue no.

1072
00:58:49,880 --> 00:58:53,720
Speaker 1: I would argue that again, that iteration of the future

1073
00:58:53,840 --> 00:58:55,800
Speaker 1: is worse than the one that came before it.

1074
00:58:56,280 --> 00:59:01,000
Speaker 2: Okay, bridget question for you. What happened to the metaverse?

1075
00:59:01,480 --> 00:59:02,600
Speaker 2: Is it still a verse?

1076
00:59:02,720 --> 00:59:02,800
Speaker 4: No?

1077
00:59:03,160 --> 00:59:07,280
Speaker 1: They kind of abandoned it. H Yeah, they kind of

1078
00:59:07,280 --> 00:59:09,720
Speaker 1: abandoned the meta They were all in on the metaverse.

1079
00:59:09,960 --> 00:59:13,000
Speaker 1: They even had a big announcement when their metaverse AI

1080
00:59:13,800 --> 00:59:16,720
Speaker 1: characters kind have legs. They had a whole big announcement.

1081
00:59:16,720 --> 00:59:21,200
Speaker 1: They're like, we've got legs now. It took them a

1082
00:59:21,200 --> 00:59:23,880
Speaker 1: long time to break the legs code. But no, it's

1083
00:59:23,880 --> 00:59:25,120
Speaker 1: no longer really a thing.

1084
00:59:25,640 --> 00:59:28,200
Speaker 2: Okay, So so it kind of went the way of

1085
00:59:28,200 --> 00:59:31,320
Speaker 2: the Google glass because I've been talking to people about like, look,

1086
00:59:31,360 --> 00:59:36,120
Speaker 2: it is possible to shame people's product to shit.

1087
00:59:36,440 --> 00:59:38,720
Speaker 1: You know. Yeah, do you remember when Google? I mean

1088
00:59:38,760 --> 00:59:41,440
Speaker 1: you you live in California, so maybe you've lived through this.

1089
00:59:41,680 --> 00:59:44,520
Speaker 1: When Google Glass first came out, and like it was

1090
00:59:44,560 --> 00:59:46,560
Speaker 1: all the stories were like I went into a bar

1091
00:59:46,640 --> 00:59:48,640
Speaker 1: in San Francisco, We're in Google glass, and I got

1092
00:59:48,680 --> 00:59:51,720
Speaker 1: thrown out. Like it was just like story after story.

1093
00:59:51,760 --> 00:59:55,919
Speaker 2: Crazy about that. It was crazy about that. I don't

1094
00:59:55,960 --> 00:59:59,440
Speaker 2: actually think there were that many stories, but there was

1095
00:59:59,520 --> 01:00:03,200
Speaker 2: that one story where this woman goes into a bar

1096
01:00:03,280 --> 01:00:05,960
Speaker 2: with the Google glass and then writes some posts as

1097
01:00:06,000 --> 01:00:10,760
Speaker 2: if she's the victim. But everyone was like, honestly, you

1098
01:00:10,880 --> 01:00:13,480
Speaker 2: sound so unfun and I would have kicked you out too,

1099
01:00:14,080 --> 01:00:17,520
Speaker 2: And the and the reverb of that story of how

1100
01:00:17,640 --> 01:00:20,560
Speaker 2: like again before we even had Karen language, how Karen

1101
01:00:20,600 --> 01:00:24,000
Speaker 2: it was, and how corny it was, and what a

1102
01:00:24,120 --> 01:00:27,640
Speaker 2: tech idiot and kind of just a loser you looked

1103
01:00:27,680 --> 01:00:32,080
Speaker 2: like it it was magical. So it's like it's it's

1104
01:00:32,080 --> 01:00:35,480
Speaker 2: almost like, I don't know, it's like mythical, that story

1105
01:00:35,520 --> 01:00:41,920
Speaker 2: because it really tamed the Google glass wearers. And I

1106
01:00:41,920 --> 01:00:46,040
Speaker 2: don't know what, what's the big faculous Yeah, the big

1107
01:00:46,040 --> 01:00:48,640
Speaker 2: oculus or the Google one that people kind of walk around,

1108
01:00:48,680 --> 01:00:51,960
Speaker 2: Oh about shame, shoot, what is that? Oh, it's the

1109
01:00:52,080 --> 01:00:55,520
Speaker 2: it's the new Apple VR. What is the Apple Vision Pro? Oh, yeah,

1110
01:00:55,880 --> 01:00:59,880
Speaker 2: Apple Vision Pro, the Apple Vision Pro. Like, I don't

1111
01:00:59,920 --> 01:01:03,160
Speaker 2: know if people are actually wearing that out.

1112
01:01:03,600 --> 01:01:07,040
Speaker 1: So I have a theory that people don't want wearables.

1113
01:01:07,120 --> 01:01:10,080
Speaker 1: This is I've said this from day one. The only

1114
01:01:10,160 --> 01:01:12,760
Speaker 1: wearables that have actually ever seen anybody wear are the

1115
01:01:12,760 --> 01:01:16,040
Speaker 1: ones that are that like essentially look like sunglasses. So

1116
01:01:16,120 --> 01:01:19,560
Speaker 1: I will say, like Meta does have a collab with

1117
01:01:19,680 --> 01:01:21,800
Speaker 1: ray Bands, I would never wear it, but those are

1118
01:01:21,840 --> 01:01:24,000
Speaker 1: the only wearables I think that people would actually wear

1119
01:01:24,040 --> 01:01:26,919
Speaker 1: ones that just look like like regular sunglasses. I don't

1120
01:01:26,920 --> 01:01:29,800
Speaker 1: think people want big shit on their face, Like, I

1121
01:01:29,800 --> 01:01:33,520
Speaker 1: don't think that you would, like imagine sharing a space

1122
01:01:33,560 --> 01:01:36,360
Speaker 1: with like your partner or your roommate, and as opposed

1123
01:01:36,360 --> 01:01:38,520
Speaker 1: to it as like holding your phone, you've got a

1124
01:01:38,560 --> 01:01:40,400
Speaker 1: big thing on your face. It's like it's like too

1125
01:01:40,480 --> 01:01:42,320
Speaker 1: much shit on your face. I don't think people want that.

1126
01:01:42,320 --> 01:01:44,400
Speaker 2: That is my like, Yeah, there's too much.

1127
01:01:45,080 --> 01:01:46,680
Speaker 1: I don't even want to be around anymore.

1128
01:01:47,200 --> 01:01:48,560
Speaker 2: Yeah, I don't want to be around anymore. There's too

1129
01:01:48,640 --> 01:01:50,080
Speaker 2: much shit on me and words to live by.

1130
01:01:50,160 --> 01:01:56,080
Speaker 1: Really, Oh, frand Jasica, talking to you is such a delight,

1131
01:01:56,280 --> 01:01:58,720
Speaker 1: Like you, Oh my God, you have such a like

1132
01:01:59,200 --> 01:02:01,200
Speaker 1: you just bring such an energy and a light to

1133
01:02:01,240 --> 01:02:03,480
Speaker 1: these stories. I do this every week and like this,

1134
01:02:03,640 --> 01:02:06,560
Speaker 1: you have a you really bring a player to this.

1135
01:02:06,640 --> 01:02:07,480
Speaker 1: I really appreciate it.

1136
01:02:07,520 --> 01:02:09,840
Speaker 2: Oh my God. Likewise, thank you so much. These are

1137
01:02:09,840 --> 01:02:12,880
Speaker 2: great stories and also stories I was haven't even talked

1138
01:02:12,880 --> 01:02:15,760
Speaker 2: about this week, which is wild because I talk about everything. No,

1139
01:02:16,120 --> 01:02:19,080
Speaker 2: but like, that's why I think this show is so excellent,

1140
01:02:19,080 --> 01:02:23,440
Speaker 2: because you're like, you miss this so and everyone's over here,

1141
01:02:23,720 --> 01:02:28,280
Speaker 2: Bridge is over here, so and they're very important. But yeah, man,

1142
01:02:28,360 --> 01:02:29,200
Speaker 2: thank you for having me.

1143
01:02:29,520 --> 01:02:31,840
Speaker 1: Where can folks listen to the Situation Room?

1144
01:02:32,120 --> 01:02:35,520
Speaker 2: I was gonna segue into the plugs. I just teed

1145
01:02:35,560 --> 01:02:40,200
Speaker 2: you up instead, YouTube dot com, slash Franny fo f

1146
01:02:40,280 --> 01:02:42,920
Speaker 2: r A and I FIO for the live show Tuesday's

1147
01:02:42,920 --> 01:02:45,920
Speaker 2: Wednesday Fridays one being Pacific four pm Eastern, or the

1148
01:02:45,920 --> 01:02:48,840
Speaker 2: Bituation Room wherever you get your podcasts.

1149
01:02:48,440 --> 01:02:51,200
Speaker 1: And you can find me on social media. I'm on

1150
01:02:51,280 --> 01:02:54,720
Speaker 1: Instagram at bridget Ran DC, I'm on TikTok at bridget

1151
01:02:54,800 --> 01:02:57,000
Speaker 1: Ran d C. And I'm on YouTube at there are

1152
01:02:57,000 --> 01:02:59,160
Speaker 1: no girls on the Internet. Yeah, that's right, I just

1153
01:02:59,160 --> 01:03:04,120
Speaker 1: started it, so I'm have not memorized you'll be my

1154
01:03:04,280 --> 01:03:09,320
Speaker 1: like ninety third follower subscriber, Earli. Thanks so much for listening.

1155
01:03:09,440 --> 01:03:15,480
Speaker 1: We will see you on the Internet. If you're looking

1156
01:03:15,480 --> 01:03:17,560
Speaker 1: for ways to support the show, check out our March

1157
01:03:17,600 --> 01:03:21,400
Speaker 1: store at tegoty dot com slash store. Got a story

1158
01:03:21,440 --> 01:03:23,320
Speaker 1: about an interesting thing in tech, or just want to

1159
01:03:23,360 --> 01:03:25,720
Speaker 1: say hi, You can reach us at Hello at tangody

1160
01:03:25,760 --> 01:03:28,320
Speaker 1: dot com. You can also find transcripts for today's episode

1161
01:03:28,320 --> 01:03:30,480
Speaker 1: at tengody dot com. There Are No Girls on the

1162
01:03:30,560 --> 01:03:33,160
Speaker 1: Internet was created by me Bridget Tod. It's a production

1163
01:03:33,200 --> 01:03:37,520
Speaker 1: of iHeartRadio and Unbossed Creative edited by Joey pat Jonathan

1164
01:03:37,520 --> 01:03:40,520
Speaker 1: Strickland is our executive producer. Tari Harrison is our producer

1165
01:03:40,560 --> 01:03:44,040
Speaker 1: and sound engineer. Michael Almado is our contributing producer. I'm

1166
01:03:44,080 --> 01:03:46,400
Speaker 1: your host, Bridget Todd. If you want to help us grow,

1167
01:03:46,560 --> 01:03:47,320
Speaker 1: rate and review us.

1168
01:03:47,280 --> 01:03:48,240
Speaker 4: On Apple Podcasts.

1169
01:03:49,000 --> 01:03:51,800
Speaker 1: For more podcasts from iHeartRadio, check out the iHeartRadio app,

1170
01:03:51,840 --> 01:03:54,200
Speaker 1: Apple podcast, or wherever you get your podcasts.