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Speaker 1: Hi, I'm Molly Jongfast, and this is Fast Politics, where

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Speaker 1: we discuss the top political headlines with some of today's

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Speaker 1: best minds.

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Speaker 2: And U.S.

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Speaker 1: Secretary of Commerce Howard Lutnick made over $ 250 million last year.

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Speaker 1: Charlie Sykes stops by to talk about Trump continuing to

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Speaker 1: ruin our country's economy.

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Speaker 2: Then we'll talk to.

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Speaker 1: The Verge's Nilay Patel about the implications of Meta's unprecedented

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Speaker 1: settlement for their app's addictive behavior.

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Speaker 2: But first, the news.

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Speaker 3: Somali, we finally have an admission of something we knew,

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Speaker 3: which is one of the most common tropes of the

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Speaker 3: Trump administration. Trump has told us why he's launching new

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Speaker 3: vanity projects like a great triumphal arch.

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Speaker 1: This is like we're in the dumbest moment in American history.

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Speaker 1: So basically, Trump did this amazing interview with Ben Terrace

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Speaker 1: from New York magazine. At so many points, John Ossoff

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Speaker 1: has said these like off the cuff things which have

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Speaker 1: gotten Trump so crazy. Because remember, he is responsible for

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Speaker 1: the Natalie Harp news cycle of two weeks ago, too.

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Speaker 1: So basically he said this thing, which is Trump is

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Speaker 1: obsessed with building monuments to himself, quote, because no one

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Speaker 1: will honor him when he's gone.

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Speaker 2: And Trump responded, that's true.

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Speaker 3: It's also a dream team of this because Ben Terrace

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Speaker 3: also gets some of the greatest admissions of things.

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Speaker 4: Yeah.

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Speaker 2: He's a really good reporter.

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Speaker 3: He's responsible for the thing I think about all the time.

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Speaker 3: Ron DeSantis staring at a on a flight for like

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Speaker 3: over 12 hours at the back of the chair and

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Speaker 3: doing nothing.

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Speaker 4: Yeah.

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Speaker 1: And he comes from The Washington Post, another like Bezos

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Speaker 1: fucking up and losing him.

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Speaker 2: But, yeah, he's a really good reporter. And it's just

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Speaker 2: a very interesting story. It's worth reading.

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Speaker 1: It's New York magazine now. And then almost like clockwork.

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Speaker 1: Doug Burgum, you may remember Doug Burgum as being he

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Speaker 1: was at one time the governor of North Dakota. One

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Speaker 1: of the most interesting things I think about Doug Burgum

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Speaker 1: is that Donald Trump picked him for interior secretary because

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Speaker 1: he saw video of him and his this is in

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Speaker 1: the book Regime Change. He saw video of him and

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Speaker 1: his wife on horseback.

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Speaker 4: That was it.

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Speaker 2: And he like really thought the wife was hot.

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Speaker 3: And Admittedly, though, that's better than there were no posts

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Speaker 3: left for Sean Duffy. So that's how he got his.

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Speaker 1: I mean, I would say, like, admittedly, nobody knows what

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Speaker 1: the secretary of the interior does.

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Speaker 2: So and he doesn't care what the secretary of the

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Speaker 2: interior is supposed to do.

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Speaker 1: I mean, people know what it is, but he doesn't know.

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Speaker 1: But anyway, so but what Doug Burgum has basically done

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Speaker 1: has he's just been trying to give Trump what he wants.

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Speaker 1: So on Friday, he announced that the Great Triumphal Arch

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Speaker 1: is going to happen and that earlier in the week.

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Speaker 1: The Supreme Court said that made it so it was

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Speaker 1: virtually impossible to challenge the illegal construction of the $ 600

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Speaker 1: million ballroom. So I guess the administration decided they got

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Speaker 1: the ballroom.

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Speaker 2: Let's go. I want to point out this is so dumb.

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Speaker 3: So, Molly, how did you feel yesterday when you found

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Speaker 3: out your favorite TV host, Fox News' Maria Bartiromo, a.k.a.

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Speaker 3: The Money Honey, will no longer be on your favorite station,

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Speaker 3: Fox News?

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Speaker 2: First of all, she's not on Fox News. She's on

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Speaker 2: Fox Business.

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Speaker 5: That's a good point.

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Speaker 1: Do you know what the numbers are on that morning show?

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Speaker 3: Tell me.

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Speaker 2: She gets under 100,000 viewers. That's less than most of

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Speaker 2: our YouTube videos. It was weird firing, right?

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Speaker 1: She did her Thursday show, and then that was it.

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Speaker 2: She just disappeared.

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Speaker 1: So it was almost immediately reported by Oliver Darcy instead.

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Speaker 2: And good for him.

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Speaker 1: Yet another like amazing Oliver Darcy scoop that she had

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Speaker 1: been fired for leaking to the White House the Fox

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Speaker 1: News guidance on the election. And basically Trump did the speech.

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Speaker 1: He said the election was stolen, the 2020 election. Fox

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Speaker 1: News issued guidance immediately. A lot of times news stations

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Speaker 1: issue guidance with breaking news and they'll say something to

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Speaker 1: the effect of, you know, like you need to fact

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Speaker 1: check this or you need to do this.

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Speaker 2: Or you need to do that. It's pretty common.

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Speaker 1: But remember, Fox News had been sued for millions and

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Speaker 1: millions of dollars by Dominion Voting. So this made sense

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Speaker 1: that this might happen. And she, instead of heeding the guidance,

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Speaker 1: she immediately sent the guidance over to the White House.

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Speaker 1: I think it's possible that Maria ends up in the

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Speaker 1: press shop at the White House. I think that's possible.

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Speaker 1: I also think it's just a great example of the

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Speaker 1: ways in which people try to suck up to Trump

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Speaker 1: and ruin their own lives, right? Like, you didn't need

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Speaker 1: to send him the text message for him to put

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Speaker 1: it together, that that was what was happening. And she

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Speaker 1: really just, like, sabotaged her own life to please Donald Trump.

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Speaker 1: And I just think that's a really interesting dynamic we

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Speaker 1: see happen again and again in Trump world.

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Speaker 5: Yes.

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Speaker 3: Another dynamic we see happen again and again in the

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Speaker 3: Trump world is having to rescind things that they called

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Speaker 3: for because they were not very well thought out and

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Speaker 3: probably happened in a rage. The Pentagon has rescinded its

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Speaker 3: mandatory testosterone screening guidance.

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Speaker 2: Also, it's so stupid. It's so stupid. This is a

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Speaker 2: military that is stretched within an inch of its life.

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Speaker 1: They're going to take these people who are already the

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Speaker 1: morale is terrible and they're going to test them for testosterone.

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Speaker 1: And then what are they going to do if their

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Speaker 1: testosterone is low? They're going to put them on testosterone.

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Speaker 1: That's gender affirming care right there.

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Speaker 5: It's also very expensive.

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Speaker 3: I mean, you know, it's no secret here that you

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Speaker 3: and I are pushing 50 around these parts. And I've

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Speaker 3: had to obviously look into this.

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Speaker 2: First of all, I'm 48, so I'm not pushing anything.

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Speaker 3: That's called pushing 50.

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Speaker 2: And second of.

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Speaker 1: All, it's just insanely stupid. You know, you're going to

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Speaker 1: test everyone for testosterone. I mean, you also just can't,

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Speaker 1: as we know from the vaccines, it's very hard to

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Speaker 1: get people to take anything, even if it's stuff that

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Speaker 1: is actually to save their lives. So it's very stupid.

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Speaker 1: Yet another very stupid idea. You know why it's worth

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Speaker 1: reading the book Regime Changes? Because you see how Donald

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Speaker 1: Trump does a lot of stuff this time where he

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Speaker 1: just is like, no, we're going to do this. And

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Speaker 1: you're like, and he doesn't check with anyone. He doesn't

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Speaker 1: run it through the cabinet. He often just comes up

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Speaker 1: with dumb stuff and then they have to walk it back.

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Speaker 1: And that this is yet another case of that.

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Speaker 3: There is blockbuster reporting from the Wall Street Journal. This

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Speaker 3: is now the third time we've had reporting like this,

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Speaker 3: that John Fetterman really has poor priorities in his Senate office. First,

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Speaker 3: his leftist staffers said this, that his centrist staffers said this,

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Speaker 3: and now his conservative staffers have said this, that my

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Speaker 3: man cares about two things, Fox News and Israel.

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Speaker 1: So this reporting in the Wall Street Journal is incredible

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Speaker 1: and everyone should read it. And it has a number

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Speaker 1: of leaked text messages. And basically they're him being like, no,

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Speaker 1: I don't want to meet with those disabled veterans in

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Speaker 1: the wheelchairs.

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Speaker 2: No. Tell them that I'll be there.

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Speaker 1: And then right before he doesn't show up because he

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Speaker 1: has a Fox News interview. I mean, it is literally

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Speaker 1: at one point in one of these text exchanges, he

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Speaker 1: complains about how he keeps having to talk to Children's

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Speaker 1: Hospital of Pennsylvania, CHOP. which is this amazing hospital that

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Speaker 1: does all of this incredible work. And they say, well,

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Speaker 1: it's because they're worried about these cuts to the vaccine stuff. And,

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Speaker 1: you know, there's a lot of reasons for hospitals to

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Speaker 1: be worried right now, especially children's hospitals. And he basically says, well,

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Speaker 1: I'm not. And the thing is, look, this fucking guy

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Speaker 1: should not be in office. He should resign. He is

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Speaker 1: really terrible. And, you know, Republicans are excited because they

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Speaker 1: think he might vote with them.

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Speaker 2: And maybe he will because he's so unhinged.

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Speaker 1: But The net net of it is this is a

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Speaker 1: person who really should not be in office. And this

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Speaker 1: is just yet another story of that. And it's such

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Speaker 1: a disappointment to us because we've had him on this

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Speaker 1: podcast a bunch of times when he was normal.

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Speaker 2: And he just is. It's just sucks. And it's really terrible.

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Speaker 3: Go ahead.

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Speaker 1: Charlie Sykes is the author of the newsletter To the

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Speaker 1: Contrary and the book How the Right Lost Its Mind.

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Speaker 4: Welcome.

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Speaker 2: Welcome, Charlie Sykes.

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Speaker 4: Hey, great to be back.

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Speaker 1: Great to have you. We're like nine weeks from the

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Speaker 1: midterms and Donald Trump is a little less than nine weeks,

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Speaker 1: I think. And Donald Trump is laser focused on the

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Speaker 1: triumphal arch.

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Speaker 4: Yeah, that's obviously what most Americans are concerned about. It

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Speaker 4: is interesting, though, that, I mean, everybody that's met with

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Speaker 4: Donald Trump lately, if you notice these accounts and they

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Speaker 4: come in and they want to talk about what's happening

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Speaker 4: with the military or the war in Iran or affordability

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Speaker 4: or the midterms, all Donald Trump wants to talk about

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Speaker 4: is his big ballroom and apparently the arch, the arch

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Speaker 4: to Trump. Don't you usually, by the way, have to

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Speaker 4: have a victory or some big success in order to

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Speaker 4: have the triumphal arch? Is this going to be the

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Speaker 4: first arch built after you've actually won the war and

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Speaker 4: presided over the weakening status of the United States and

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Speaker 4: the world? It seems a little ironic.

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Speaker 1: The whole thing is ironic. I mean, look at the

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Speaker 1: Kennedy Center. The tarp is still there to hide the

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Speaker 1: fact that Donald Trump had to take his name off

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Speaker 1: the Kennedy Center.

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Speaker 4: Yeah, but the trees are gone. Okay, so this is...

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Speaker 4: This is the one story that triggered me this week.

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Speaker 1: Okay, go.

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Speaker 4: Remember a few days ago, Trump's legal minions were threatening,

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Speaker 4: if Donald Trump doesn't get his way, he might have

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Speaker 4: to tear down, destroy the entire Kennedy Center. Well, they're

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Speaker 4: doing it bit by bit now. They cut down these

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Speaker 4: 40 willow trees that had been planted as a memorial

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Speaker 4: to John F. Kennedy Jr. They just cut... them down.

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Speaker 4: And if you just wanted an indication of what a

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Speaker 4: petty vandal this guy has become, that's it in the capsule.

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Speaker 1: Why did they cut them down?

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Speaker 4: Because they could.

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Speaker 1: And they took the statue in front and took it down, right?

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Speaker 5: Right. Yeah, yeah, bit by bit.

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Speaker 4: Maybe back to the arch. I mean, the arch is

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Speaker 4: exactly what... I think people do recognize it. It's sort of,

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Speaker 4: you know, a monument to his, you know, bottomless neediness,

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Speaker 4: endless neediness into his narcissism. I mean, this is Donald Trump,

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Speaker 4: who is just now obsessed with putting his name on coins,

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Speaker 4: on art centers, building monuments to himself.

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Speaker 2: And, you know.

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Speaker 4: In the dark of the night, I'm guessing that he's

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Speaker 4: sitting around going, you know, Vladimir Putin would do this.

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Speaker 4: Kim Jong-un would do this. President Xi would do this

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Speaker 4: because that's what he wants to grow up to be.

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Speaker 4: Donald Trump is not somebody who is concerned with conserving

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Speaker 4: the past or with honoring the aesthetic beauty created by others.

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Speaker 4: And again, I'm not telling you something we don't know

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Speaker 4: or we're not told over and over and over again.

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Speaker 4: You know, it's always about Trump, you know, the beginning

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Speaker 4: and the end. And by the way, You know, the

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Speaker 4: flip side of this is this is creating kind of

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Speaker 4: a problem for the Republican Party that bought the ticket,

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Speaker 4: isn't it? Because he's decided that he wants the midterm

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Speaker 4: elections to be all about himself while his approval ratings

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Speaker 4: are headed toward 30 percent. Good luck with that.

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Speaker 1: So this is the reporting today from Politico where the

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Speaker 1: RNC issued a warning. If members choose to keep an

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Speaker 1: arm's length from the president, they risk alienating their base

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Speaker 1: and they risk alienating. 15 to 20 percent of key

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Speaker 1: Republican voters not turning out because they don't feel like

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Speaker 1: they're a good supporter of the president's policies. RNC spokeswoman

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Speaker 1: said that.

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Speaker 4: Well, I mean, this is this is political malpractice on

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Speaker 4: an epic scale, because normally if you're, you know, a

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Speaker 4: swing seat Republican, what you're trying to do is make

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Speaker 4: this anything other than a referendum on Donald Trump. If

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Speaker 4: you make it a referendum on Donald Trump, you are

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Speaker 4: in you're in deep shit. And so what is the

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Speaker 4: message coming from the White House? It's got to be

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Speaker 4: all about me. And next week, they're having that midterm convention.

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Speaker 4: That's going to be now that's going to be a

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Speaker 4: shit show for the ages. Yes, because that's going to

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Speaker 4: be a Trumpapalooza. And so at the very moment when

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Speaker 4: Republican candidates would like to be like back in their

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Speaker 4: districts or their states where they would like to be,

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Speaker 4: you know, putting a little bit of daylight between themselves

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Speaker 4: and Donald Trump. Donald Trump, again, less than 60 days

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Speaker 4: before the midterm is a no. It's all about me.

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Speaker 4: because he believes that he's really on the ballot. And

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Speaker 4: he's making the RNC hammer that message home.

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Speaker 1: So the House is still in session. If you're a

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Speaker 1: House member, you are running for reelection. Republican House member,

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Speaker 1: Trump wants you to come to Trumpapalooza. You have very

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Speaker 1: few days, you know, you have only so many days

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Speaker 1: to campaign. Like, it is actually a real problem.

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Speaker 4: It is a real problem. And I mean, and you

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Speaker 4: can quantify it. Trump's MAGA political action committee, I mean,

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Speaker 4: has something like, what, $ 450 million in the bank. And

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Speaker 4: it's starting to dawn on Republicans that he may not

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Speaker 4: spend it on them. That when it comes to, and

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Speaker 4: there was that report in The Atlantic that You know,

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Speaker 4: Donald Trump said, no, that's my money. I want it

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Speaker 4: to be about me. They're running these. Have you seen

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Speaker 4: these spots that the Trump people have put out? They're

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Speaker 4: all about Donald Trump, Superman, Donald Trump, this Donald Trump that.

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Speaker 4: And it's just another reminder how utterly, you know, separated

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Speaker 4: he is from the actual political world that he ought

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Speaker 4: to be inhabiting.

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Speaker 1: So do you think that's because Natalie Harp is finding

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Speaker 1: him the good poles that he is truthing about? Like,

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Speaker 1: do you think that his bubble is so bubbled that

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Speaker 1: there's no place for real life? Or do you think

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Speaker 1: that he's just old and losing his step?

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Speaker 5: Well, they're not mutually.

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Speaker 4: Exclusive, are they? Right. Both both both those things. I mean,

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Speaker 4: he's clearly lost a step, but he's created this very,

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Speaker 4: very tight bubble. And in an environment in which who's

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Speaker 4: going to walk into the Oval Office and tell him

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Speaker 4: the bad news, especially when he's got the human printer

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Speaker 4: who is telling him how wonderful he is. And I

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Speaker 4: think that you do see this. So, you know, aging

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Speaker 4: man surrounds himself with courtiers and sycophants who tell him

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Speaker 4: what he likes. You know, it does sound like something

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Speaker 4: out of, you know, the decline and fall of the

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Speaker 4: Roman Empire. But I think, again, you and I have

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Speaker 4: talked about this. He used to have this reptilian instinct

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Speaker 4: for public opinion. And you're not seeing that right now.

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Speaker 2: No, you're really not.

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Speaker 1: And what's interesting, too, and again, this is like sort

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Speaker 1: of the Rick thing, right, that everything Trump touches dies.

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Speaker 1: People are so like Maria Bartiromo loses her job. supposedly

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Speaker 1: the reporting is, and we've heard, we've seen multiple outlets

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Speaker 1: confirm this now, that she lost her job.

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Speaker 4: Why?

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Speaker 1: Because she told the White House what the guidance was

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Speaker 1: on Trump's speech. Again and again, we see people ruin

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Speaker 1: their lives in order to ingratiate themselves with Trump.

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Speaker 4: Yes, but don't assume that this is the last chapter for,

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Speaker 4: you know, the money, honey. She could end up working

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Speaker 4: in the White House. she, you know, might be assuming

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Speaker 4: the same position that Natalie Harp does. So a lot

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Speaker 4: of these, I think we're also living in a world

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Speaker 4: where being fired from cable television is no longer the

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Speaker 4: end of your career. In fact, there are a lot

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Speaker 4: of people who are like bigger than ever after they leave. And,

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Speaker 4: you know, Trump's going to have her back. But I

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Speaker 4: think the surprising thing about that particular story was how

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Speaker 4: long she lasted at Fox, given the role that she

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Speaker 4: played in the $ 871 million Dominion lawsuit. I mean, she

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Speaker 4: was one of the worst purveyors of the big lie,

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Speaker 4: one of the worst, you know, fluffers and fabulous that

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Speaker 4: Trump had. So I'm a little bit I was a

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Speaker 4: little bit surprised that she survived initially. But but yeah,

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Speaker 4: she put her loyalty to Trump ahead of her employer.

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Speaker 4: And guess what happened?

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Speaker 1: Right.

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Speaker 5: See how that works out for her.

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Speaker 1: And now I wonder, though, as we like look to

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Speaker 1: the midterms, this every almost every day we're seeing like

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Speaker 1: ratings changes. I did see a change that Sununu is

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Speaker 1: maybe a stronger candidate in New Hampshire. So that is

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Speaker 1: actually a big deal because that's a Democratic seat they

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Speaker 1: have to hold. But I just would love you to

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Speaker 1: talk about like. The landscape, it does seem like, especially

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Speaker 1: with some of these redistricting, they redistricted on these Trump

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Speaker 1: 24 numbers, which may be very, very different than what

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Speaker 1: normal numbers look like.

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Speaker 4: Well, that's right. And that's particularly true in Texas. So, look,

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Speaker 4: the Republicans won the gerrymandering war. I mean, they won

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Speaker 4: the battle. They may not win the war because, you know,

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Speaker 4: some of those voters are either not going to turn out.

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Speaker 4: The switch in the Hispanic vote they were counting on. Boy,

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Speaker 4: that has not played well for them. But I also

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Speaker 4: think that the Senate and governor's races are awfully interesting. And,

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Speaker 4: you know, I, as you know, I try to resist

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Speaker 4: irrational exuberance. I do not chuff the hopium. But I

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Speaker 4: did do a piece in my newsletter this week, How

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Speaker 4: Big a Wave, and looked at the not crazy things

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Speaker 4: that are coming out of places like Iowa, that are

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Speaker 4: coming out of places like Kansas, that actually really smart

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Speaker 4: People are saying, you know what, some of these states

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Speaker 4: that you'd never think would be in play might actually

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Speaker 4: be in play if the wave is big enough. I mean,

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Speaker 4: it would be certainly unfortunate if Democrats would come within

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Speaker 4: one seat and then lose the seat in Michigan or

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Speaker 4: the seat in New Hampshire. I mean, that is possible.

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Speaker 4: But it's also possible that you're going to see states

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Speaker 4: like Alaska, Texas flip. And, you know, it's going to, well,

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Speaker 4: I mean, think about what that would mean. for the

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Speaker 4: failed realignment that we thought, you know, Trump had pulled

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Speaker 4: off in 2024.

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Speaker 1: I also think I was interesting, too, because there's also

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Speaker 1: the farming problem, which is that we have polluted our

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Speaker 1: groundwater in some of these states. And so Iowa, I mean,

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Speaker 1: when you I interviewed both Doug Sand and and Josh Turek,

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Speaker 1: and they both said the number one problem in Iowa

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Speaker 1: is cancer. Like that these farmers and these people who

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Speaker 1: just live in places with polluted groundwater are getting cancer.

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Speaker 1: And so that is, these are the ways in which

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Speaker 1: the Republican states have, and we have it too, but

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Speaker 1: not the same way with farmers. We're seeing the sort

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Speaker 1: of results of it. And that's like the Brownback thing, right?

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Speaker 1: Where you go so right, you have to go left.

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Speaker 4: Right. Yeah, no. And this is a real problem. And

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Speaker 4: it's not just anecdotal. You know, you're seeing I think

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Speaker 4: it was it was a Senator Ken Kramer from South Dakota.

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Speaker 4: This is really bad. This is we're in a really

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Speaker 4: bad situation. And diesel fuel, by the way, just hit

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Speaker 4: hit a new high. And so and this translates, you know,

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Speaker 4: rather dramatically into the agricultural areas. I actually did a

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Speaker 4: podcast the other day with the leading independent candidate for

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Speaker 4: Senate in Montana. They have an open seat there. And

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Speaker 4: they have a really good candidate named Seth Bodnar. And

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Speaker 4: he points out, in a state like Montana, do you

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Speaker 4: know what gas prices actually mean when people have to

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Speaker 4: drive those long distances? Not to mention. Montana is a

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Speaker 4: border state. It has probably the longest border with Canada.

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Speaker 4: So you can just imagine how the trade war, the

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Speaker 4: price of gas, all of those things are playing in

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Speaker 4: a state that At the beginning of the year, nobody

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Speaker 4: even remotely thought would be in play. And I got

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Speaker 4: to throw in Nebraska, too. Right.

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Speaker 1: And that's and that's the situation with Maine, too. Like

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Speaker 1: when you look at a Troy Jackson, like there's the

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Speaker 1: trade war, but there's also I had him on my

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Speaker 1: podcast since we all we do is talk to candidates

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Speaker 1: now that we're in the run up to the midterm.

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Speaker 1: But like and he was talking about how expensive heating

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Speaker 1: oil is. And how cold Maine is and how you

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Speaker 1: have these people who are going to need, you know,

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Speaker 1: you start your you start heating your house sometimes early

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Speaker 1: because at night it gets really, really cold. I mean,

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Speaker 1: and so you have a problem where you have people

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Speaker 1: who can't afford to heat their houses or who are

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Speaker 1: just breaking themselves to pay to heat their houses.

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Speaker 4: Yeah, but they get but they get they get a

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Speaker 4: triumphal arch. So you mentioned Maine, which also triggers me

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Speaker 4: a little bit. because Susan Collins gave that interview, which

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Speaker 4: I know that you've talked about. She sat down with

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Speaker 4: Jonathan Martin from Politico, and he was asking her about

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Speaker 4: the various roles people have played in the Republican Party

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Speaker 4: under Trump. There's, you know, the Lindsey Graham, just, you know,

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Speaker 4: slavering sycophant. And then there's, of course, in contrast to

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Speaker 4: Liz Cheney, who defied him on principle. And Susan Collins

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Speaker 4: took the opportunity to take a shot at Liz Cheney.

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Speaker 4: Even though You know, she also voted to impeach and

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Speaker 4: convict Trump after January 6th. In fact, I could read

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Speaker 4: to you Susan Collins speech that she gave on the floor.

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Speaker 4: And I would say, who said this, Molly? Who said this?

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Speaker 4: Liz Cheney or or Susan Collins? And it would be

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Speaker 4: it would be tough. But now she's going, yeah, but

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Speaker 4: that Liz Cheney, because she actually stood up and had

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Speaker 4: some principle and thought that honor was more important than party.

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Speaker 4: She has no influence whatsoever. It's not that she lost

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Speaker 4: her seat. She has no impact whatsoever, which I thought

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Speaker 4: was rich. Coming from someone, a concerned troll like Susan Collins,

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Speaker 4: who has become, I think, famous for her sort of

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Speaker 4: limp-wisted hand waves. And I'm concerned. And I mean, she

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Speaker 4: doesn't really, I think, fully understand how completely irrelevant she

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Speaker 4: is and will be in the future. I mean, she's not.

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Speaker 4: She's going to be a cipher in history. And yet

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Speaker 4: she is she's dissing Liz Cheney, who and she knows

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Speaker 4: that Liz Cheney was right about this. But she just

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Speaker 4: lacked the courage.

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Speaker 1: This is what Susan Collins says to herself at night. Right.

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Speaker 1: This is how she sleeps. She says, well, you know,

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Speaker 1: Liz Cheney is out of the thing. And at least,

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Speaker 1: you know, I may have sold all my principles up

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Speaker 1: the river, but at least I'm still in the game.

436
00:22:43,460 --> 00:22:47,379
Speaker 4: That's exactly it. And that's the rationalization of all the

437
00:22:47,420 --> 00:22:50,139
Speaker 4: Republicans who think that they have to be in the room.

438
00:22:50,740 --> 00:22:52,000
Speaker 4: They have to be in the room because that could

439
00:22:52,040 --> 00:22:54,859
Speaker 4: be influential. But when it comes down to being influential

440
00:22:54,920 --> 00:22:57,120
Speaker 4: on things that matter, they go, oh, I can't actually

441
00:22:57,160 --> 00:22:59,149
Speaker 4: say anything about this because then I won't be in

442
00:22:59,190 --> 00:23:01,590
Speaker 4: the room. So I call this a doom loop of

443
00:23:01,670 --> 00:23:05,290
Speaker 4: relevance where you give up all of your principles to

444
00:23:05,330 --> 00:23:07,350
Speaker 4: stay in the room because you think you need to

445
00:23:07,390 --> 00:23:09,550
Speaker 4: be in the room to fight for your principles. But

446
00:23:09,570 --> 00:23:11,469
Speaker 4: you're never going to fight for your principles because you

447
00:23:11,490 --> 00:23:13,270
Speaker 4: want to be in the room. So it's just like

448
00:23:13,450 --> 00:23:14,550
Speaker 4: this makes sense in their heads.

449
00:23:15,200 --> 00:23:16,740
Speaker 2: I love doom loop of relevance.

450
00:23:16,760 --> 00:23:20,170
Speaker 1: That's brilliant. Now, I have a question, which is when

451
00:23:20,210 --> 00:23:22,530
Speaker 1: we talk about Collins, though, part of what we're not

452
00:23:22,609 --> 00:23:24,950
Speaker 1: talking about with Collins is the reason why Collins gets

453
00:23:25,050 --> 00:23:28,750
Speaker 1: reelected is two reasons, right? One is that she raises

454
00:23:28,810 --> 00:23:32,189
Speaker 1: a boatload of money and people, you know, there are

455
00:23:32,210 --> 00:23:35,790
Speaker 1: enough Republicans who are like, oh, maybe someday we can

456
00:23:35,830 --> 00:23:38,699
Speaker 1: go back to this. And then the other reason is

457
00:23:38,760 --> 00:23:41,340
Speaker 1: because she does well with appropriations, right?

458
00:23:41,619 --> 00:23:43,900
Speaker 4: Well, and she has that image of being a maverick.

459
00:23:44,670 --> 00:23:48,110
Speaker 4: of being independent. She votes against Trump on enough things.

460
00:23:48,130 --> 00:23:51,020
Speaker 4: She can say, see, I'm not like those other Republicans.

461
00:23:51,040 --> 00:23:53,760
Speaker 4: I mean, a Republican normally should not be able to

462
00:23:53,800 --> 00:23:56,139
Speaker 4: win in Maine, given what's been, you know, the trend there.

463
00:23:56,180 --> 00:23:59,320
Speaker 4: But she says, I'm a different kind of Republican because,

464
00:23:59,340 --> 00:24:02,590
Speaker 4: you know, I voted, look, I voted against this nominee.

465
00:24:03,010 --> 00:24:06,389
Speaker 4: But I don't come to it whether we were on

466
00:24:06,430 --> 00:24:09,350
Speaker 4: the same podcast where, I'm going to actually quote her,

467
00:24:09,369 --> 00:24:13,320
Speaker 4: I probably shouldn't, but Senator Barbara Boxer, Said, you know,

468
00:24:13,540 --> 00:24:16,200
Speaker 4: I work with Susan Collins for years. And what we

469
00:24:16,260 --> 00:24:18,840
Speaker 4: used to say about her is Susan Collins will always

470
00:24:18,920 --> 00:24:23,760
Speaker 4: be there for you when you don't need her. Yes.

471
00:24:23,780 --> 00:24:26,260
Speaker 2: I think we were on a show together with her.

472
00:24:26,300 --> 00:24:26,659
Speaker 4: Yeah.

473
00:24:26,940 --> 00:24:27,420
Speaker 1: Yeah.

474
00:24:27,600 --> 00:24:30,960
Speaker 4: And I thought that was the perfect thing because her deal,

475
00:24:31,000 --> 00:24:33,970
Speaker 4: the deal that she's cut with Trump is, OK, I'm

476
00:24:34,010 --> 00:24:36,570
Speaker 4: going to, you know, you let me vote against you

477
00:24:36,630 --> 00:24:39,189
Speaker 4: on a few things. But when you really need me,

478
00:24:39,250 --> 00:24:42,480
Speaker 4: I'm going to be there. Because she's never going to

479
00:24:42,520 --> 00:24:45,440
Speaker 4: cast the decisive vote to block Donald Trump.

480
00:24:45,720 --> 00:24:46,399
Speaker 5: Right. Right.

481
00:24:46,480 --> 00:24:47,790
Speaker 4: Just is never going to do it.

482
00:24:48,420 --> 00:24:48,620
Speaker 5: Right.

483
00:24:48,680 --> 00:24:51,669
Speaker 1: And that's the math problem. And that but the reason

484
00:24:51,710 --> 00:24:55,530
Speaker 1: her constituents keep voting for her is is appropriate, is appropriate.

485
00:24:55,550 --> 00:24:56,470
Speaker 1: It's the Susan Collins.

486
00:24:56,530 --> 00:24:57,290
Speaker 4: It's the money.

487
00:24:57,330 --> 00:25:01,250
Speaker 1: Yeah, it's money. And so the so the question is,

488
00:25:01,270 --> 00:25:05,330
Speaker 1: will voters vote? be willing to take a chance that

489
00:25:05,350 --> 00:25:07,810
Speaker 1: Troy Jackson can keep getting them the money because they're

490
00:25:07,869 --> 00:25:11,820
Speaker 1: so mad at her about Trump, right? I mean, that's

491
00:25:11,840 --> 00:25:13,720
Speaker 1: the calculus.

492
00:25:13,800 --> 00:25:16,100
Speaker 4: Then that's the big question. It depends what kind of

493
00:25:16,160 --> 00:25:19,260
Speaker 4: a year it is. It depends whether they're more interested

494
00:25:19,280 --> 00:25:22,760
Speaker 4: in the appropriations or whether they're more angry about, you know,

495
00:25:22,820 --> 00:25:25,000
Speaker 4: what ICE is doing and what's happening to the country.

496
00:25:25,020 --> 00:25:25,879
Speaker 2: Right.

497
00:25:26,200 --> 00:25:31,419
Speaker 4: You know, there's a moment, and I've I know that

498
00:25:31,440 --> 00:25:33,520
Speaker 4: politics are different now than they were in the past.

499
00:25:34,100 --> 00:25:36,060
Speaker 4: But one of the lessons that I learned many, many

500
00:25:36,080 --> 00:25:39,619
Speaker 4: years ago, sometimes there's a wave election and it is

501
00:25:39,760 --> 00:25:43,520
Speaker 4: so big that this you can spend all your time

502
00:25:43,580 --> 00:25:46,420
Speaker 4: thinking about this ad or this strategy or this issue.

503
00:25:46,500 --> 00:25:51,270
Speaker 4: And ultimately, it doesn't matter. It's just too big. And

504
00:25:51,450 --> 00:25:55,550
Speaker 4: and I remember thinking that back in 2006, where, you know,

505
00:25:55,570 --> 00:26:00,780
Speaker 4: Democrats just wiped out so many, you know, Republicans. And

506
00:26:00,800 --> 00:26:03,859
Speaker 4: this may be one of those issues. And particularly given

507
00:26:03,920 --> 00:26:08,560
Speaker 4: her age, given her, you know, kind of, you know, ineffectualness,

508
00:26:09,359 --> 00:26:11,740
Speaker 4: given the fact that now she's she's now having to

509
00:26:11,820 --> 00:26:14,760
Speaker 4: ask questions about, well, you know, that, you know, big

510
00:26:14,820 --> 00:26:16,460
Speaker 4: bankrollers is Elon Musk.

511
00:26:16,500 --> 00:26:16,790
Speaker 1: Right.

512
00:26:16,810 --> 00:26:19,869
Speaker 4: You know. I mean, I'm hoping that every Republican in

513
00:26:19,930 --> 00:26:23,390
Speaker 4: America is asked about Elon Musk. Did you read about

514
00:26:23,430 --> 00:26:25,530
Speaker 4: that new documentary coming out about Elon Musk?

515
00:26:25,710 --> 00:26:28,730
Speaker 2: I'm supposed to see it on Tuesday. It's four hours long.

516
00:26:29,490 --> 00:26:33,750
Speaker 1: There's like a special in an office building somewhere. And

517
00:26:33,770 --> 00:26:35,670
Speaker 1: I was like, yep, I'm going, you know.

518
00:26:36,310 --> 00:26:37,010
Speaker 5: I would go.

519
00:26:37,250 --> 00:26:39,389
Speaker 4: Now, what I wrote earlier this week was, you know,

520
00:26:39,790 --> 00:26:42,650
Speaker 4: if Democrats have a Hassan Piker problem, if we have

521
00:26:42,790 --> 00:26:46,580
Speaker 4: one candidate has to has to denounce Hassan Piker, and

522
00:26:46,640 --> 00:26:50,000
Speaker 4: it's become the big litmus test, then every single Republican

523
00:26:50,020 --> 00:26:53,510
Speaker 4: in America needs to be asked about Elon Musk, who

524
00:26:53,609 --> 00:26:57,090
Speaker 4: is the world's richest, most virulent bigot and anti-Semite, who

525
00:26:57,130 --> 00:26:59,250
Speaker 4: has announced that he is going to spend maybe another

526
00:26:59,250 --> 00:27:04,409
Speaker 4: $ 100 million electing Republicans. So every Republican on the ballot

527
00:27:05,010 --> 00:27:09,439
Speaker 4: is linked directly to the world's richest man, not a

528
00:27:09,540 --> 00:27:13,790
Speaker 4: Twitch influencer or streamer, but to arguably one of the

529
00:27:13,830 --> 00:27:16,910
Speaker 4: most powerful bigots in the world. And so just like

530
00:27:16,950 --> 00:27:19,909
Speaker 4: Susan Collins, they all should be asked about her. And

531
00:27:19,950 --> 00:27:23,390
Speaker 4: Democrats ought to hang Elon Musk around their necks.

532
00:27:24,150 --> 00:27:27,879
Speaker 1: And Susan Collins, in her answer, said she didn't know

533
00:27:28,260 --> 00:27:30,460
Speaker 1: that Elon Musk was giving money to her, which is

534
00:27:30,480 --> 00:27:31,899
Speaker 1: a lot.

535
00:27:32,520 --> 00:27:35,260
Speaker 4: Well, now she knows. So what is she going to

536
00:27:35,300 --> 00:27:39,030
Speaker 4: do about it? Okay, so fine. Now you know. Are

537
00:27:39,070 --> 00:27:42,430
Speaker 4: you going to denounce? Are you going to separate yourself

538
00:27:42,450 --> 00:27:45,630
Speaker 4: or putiate some of the things? And again, it's very

539
00:27:45,810 --> 00:27:48,300
Speaker 4: easy just to line up all the things that he said,

540
00:27:48,390 --> 00:27:51,880
Speaker 4: all of the quotes. And, you know, I mean, you've

541
00:27:51,920 --> 00:27:55,100
Speaker 4: seen how many Democrats have had to issue statements about

542
00:27:55,119 --> 00:27:58,840
Speaker 4: Hassan Piker. How many Republicans have issued a statement about

543
00:27:58,920 --> 00:27:59,680
Speaker 4: Elon Musk?

544
00:28:00,080 --> 00:28:04,669
Speaker 1: But also, is Elon even more destructive? Like Elon is

545
00:28:04,710 --> 00:28:08,880
Speaker 1: very unpopular. I guess he's more unpopular than Trump. But

546
00:28:09,190 --> 00:28:12,619
Speaker 1: Trump is pretty unpopular. Well, that's that's true.

547
00:28:12,780 --> 00:28:14,699
Speaker 4: But I think that right now I kind of get

548
00:28:14,740 --> 00:28:22,160
Speaker 4: the sense that the public public opinion about evil, oligarchical

549
00:28:22,480 --> 00:28:27,379
Speaker 4: billionaires and trillionaires with space lasers, it's probably peaking right now.

550
00:28:27,440 --> 00:28:28,790
Speaker 4: You know, I mean, he thought he was going to

551
00:28:28,810 --> 00:28:31,389
Speaker 4: be Iron Man. He's kind of our Lex Luthor. It's

552
00:28:31,430 --> 00:28:34,770
Speaker 4: one of the reasons why. And again, switching to slightly this,

553
00:28:34,810 --> 00:28:38,050
Speaker 4: you know, the AI data center issue has become so toxic.

554
00:28:38,400 --> 00:28:40,860
Speaker 4: Because I think it's an issue about all of this stuff, right?

555
00:28:41,280 --> 00:28:45,240
Speaker 4: About rich people, about the tech pros. And who is

556
00:28:45,300 --> 00:28:49,300
Speaker 4: the symbol of that entire evil universe? I understand there

557
00:28:49,320 --> 00:28:52,060
Speaker 4: are still people who are going around thinking, I believe

558
00:28:52,120 --> 00:28:56,070
Speaker 4: the Tesla truck is actually beautiful. I mean, fine. But

559
00:28:56,680 --> 00:28:59,430
Speaker 4: if there's ever a moment where you need to say,

560
00:29:00,150 --> 00:29:03,130
Speaker 4: you know, you guys are worried about anti-Semitism, you're worried

561
00:29:03,170 --> 00:29:07,890
Speaker 4: about bigotry, you're worried about the concentration, you know, again...

562
00:29:08,590 --> 00:29:12,270
Speaker 4: Elon Musk, Hassan Piker, Elon Musk is a much bigger deal,

563
00:29:12,290 --> 00:29:12,770
Speaker 4: don't you think?

564
00:29:13,450 --> 00:29:14,030
Speaker 2: Oh, for sure.

565
00:29:14,650 --> 00:29:16,920
Speaker 1: Charlie Sykes, thank you, thank you, thank you.

566
00:29:17,760 --> 00:29:18,260
Speaker 4: Anytime.

567
00:29:20,260 --> 00:29:24,440
Speaker 2: Nilay Patel is the editor of The Verge. Welcome, welcome, Nilay.

568
00:29:24,520 --> 00:29:26,220
Speaker 5: Thanks for having me. I'm excited to be back. It's

569
00:29:26,240 --> 00:29:26,500
Speaker 5: been a minute.

570
00:29:26,780 --> 00:29:28,400
Speaker 2: I'm always like, we should get him.

571
00:29:28,500 --> 00:29:31,380
Speaker 1: And then, but, you know, like the tech news cycle

572
00:29:31,400 --> 00:29:36,080
Speaker 1: is complicated. So first explain to us this meta-settlement, because

573
00:29:36,100 --> 00:29:40,200
Speaker 1: Rob Bonta in California, who I think has sort of

574
00:29:40,620 --> 00:29:42,880
Speaker 1: done more to hold tech accountable.

575
00:29:43,020 --> 00:29:44,880
Speaker 2: At least in this way.

576
00:29:44,900 --> 00:29:47,160
Speaker 1: I mean, I know this is an AG, a group

577
00:29:47,200 --> 00:29:50,410
Speaker 1: of AGs, but certainly more than Chuck Schumer. Can you

578
00:29:50,490 --> 00:29:54,210
Speaker 1: explain to us what this means, this not going to

579
00:29:54,250 --> 00:29:56,150
Speaker 1: trial and the settlement?

580
00:29:56,530 --> 00:29:59,230
Speaker 5: Yeah, it's funny you brought up Chuck Schumer. Kathy Hochul

581
00:29:59,350 --> 00:30:01,430
Speaker 5: was just on Decoder, and she took a lot of

582
00:30:01,470 --> 00:30:04,010
Speaker 5: credit for the settlement. Everyone wants a piece.

583
00:30:04,530 --> 00:30:04,950
Speaker 2: Right.

584
00:30:05,410 --> 00:30:09,270
Speaker 5: So a group of states had sued Meta over harms

585
00:30:09,370 --> 00:30:11,710
Speaker 5: to teens, over false advertising. There was a lot of

586
00:30:11,730 --> 00:30:14,600
Speaker 5: claims in this lawsuit. It was one of many cases

587
00:30:14,630 --> 00:30:16,220
Speaker 5: that are coming. There was another case in New Mexico

588
00:30:16,360 --> 00:30:19,520
Speaker 5: that was also settled. There's also cases against TikTok and

589
00:30:19,560 --> 00:30:22,880
Speaker 5: YouTube and all the other social platforms. And what has

590
00:30:22,900 --> 00:30:27,350
Speaker 5: been building over the past decade— is new ways of

591
00:30:27,430 --> 00:30:30,710
Speaker 5: trying to get these platforms to regulate what's on them

592
00:30:31,130 --> 00:30:34,100
Speaker 5: and in particular, how they treat young users. And so

593
00:30:34,190 --> 00:30:36,420
Speaker 5: probably everybody is familiar at this point, if they're listening

594
00:30:36,440 --> 00:30:39,180
Speaker 5: to the show, at all of the arguments we had

595
00:30:39,220 --> 00:30:41,800
Speaker 5: about Section 230 and whether or not the platforms could

596
00:30:41,840 --> 00:30:45,840
Speaker 5: regulate misinformation. And the problem with that approach broadly is

597
00:30:45,860 --> 00:30:48,100
Speaker 5: that it ran straight into the First Amendment, right? The

598
00:30:48,120 --> 00:30:50,570
Speaker 5: government should not pass speech regulations. This is a thing

599
00:30:50,590 --> 00:30:53,970
Speaker 5: that most Americans tend to believe. And we just could

600
00:30:54,030 --> 00:30:57,220
Speaker 5: not figure out ways to square the first amendment with,

601
00:30:57,400 --> 00:31:00,220
Speaker 5: we need to pass rules about how the platforms moderate content.

602
00:31:00,540 --> 00:31:03,459
Speaker 5: So the approach pivoted and pivoted in the past few

603
00:31:03,500 --> 00:31:06,780
Speaker 5: years to a real focus on child safety and how

604
00:31:06,840 --> 00:31:10,370
Speaker 5: the products are designed. And that gets you away from

605
00:31:10,380 --> 00:31:12,400
Speaker 5: the first amendment. It gets you away from the content itself.

606
00:31:12,750 --> 00:31:14,890
Speaker 5: And it gets you to, are these products designed in

607
00:31:14,930 --> 00:31:19,510
Speaker 5: a way that harms children, specifically teens. And we know

608
00:31:19,630 --> 00:31:21,510
Speaker 5: that teens are using these platforms at high rates. We

609
00:31:21,550 --> 00:31:24,810
Speaker 5: know that the platforms have features that people call addictive.

610
00:31:24,830 --> 00:31:28,170
Speaker 5: There's a lot of debate in the academic circles about

611
00:31:28,190 --> 00:31:30,750
Speaker 5: the very nature of that addiction and whether it's measurable.

612
00:31:31,130 --> 00:31:33,970
Speaker 5: But if you have children, if you are a user

613
00:31:33,990 --> 00:31:35,910
Speaker 5: of these platforms, they certainly, there's an argument that they

614
00:31:35,930 --> 00:31:39,490
Speaker 5: feel subjectively addictive. That approach has been successful. It was

615
00:31:39,530 --> 00:31:41,590
Speaker 5: successful in New Mexico. We think it's going to be

616
00:31:41,610 --> 00:31:44,840
Speaker 5: successful in the other cases. And in the California case,

617
00:31:45,180 --> 00:31:48,400
Speaker 5: which had 47 other states, it was not going well

618
00:31:49,000 --> 00:31:52,030
Speaker 5: for the meta executives on the stand. Adam Asario was

619
00:31:52,090 --> 00:31:54,790
Speaker 5: on the stand. And at one point they showed him

620
00:31:54,930 --> 00:31:58,010
Speaker 5: emails from his team saying, we can't show this to

621
00:31:58,130 --> 00:32:01,840
Speaker 5: Adam because it will create litigation risk. This is very bad.

622
00:32:03,720 --> 00:32:07,600
Speaker 5: So they're cruising for a bruise in this case. And

623
00:32:07,640 --> 00:32:09,840
Speaker 5: there's a lot of reporting now that Meta decided it

624
00:32:09,880 --> 00:32:11,840
Speaker 5: needed to settle so it could focus on AI or

625
00:32:11,860 --> 00:32:15,420
Speaker 5: whatever it needs to focus on. And that it would

626
00:32:15,520 --> 00:32:18,050
Speaker 5: at least in settlement be able to sort of dictate

627
00:32:18,090 --> 00:32:20,810
Speaker 5: the terms. The settlement is pretty straightforward. I think if

628
00:32:20,830 --> 00:32:22,630
Speaker 5: you're a parent, you're going to like a lot of

629
00:32:22,670 --> 00:32:26,070
Speaker 5: what the settlement says. It's going to limit the ability

630
00:32:26,110 --> 00:32:28,590
Speaker 5: for teens to use Instagram and other meta platforms by

631
00:32:28,630 --> 00:32:29,750
Speaker 5: default during school hours.

632
00:32:29,770 --> 00:32:32,750
Speaker 1: I just want to pause for a second. I'm sorry

633
00:32:32,790 --> 00:32:35,550
Speaker 1: to be so annoying here, but like the reason that

634
00:32:35,590 --> 00:32:38,970
Speaker 1: they're settling is because they know that if they went

635
00:32:39,010 --> 00:32:41,690
Speaker 1: to trial, they would be beyond fucked.

636
00:32:42,080 --> 00:32:44,800
Speaker 5: Yeah, they were headed towards some kind of loss. Now,

637
00:32:44,860 --> 00:32:48,540
Speaker 5: there are a lot of questions about the shape of

638
00:32:48,580 --> 00:32:51,100
Speaker 5: that loss and what it might look like. And if

639
00:32:51,200 --> 00:32:54,390
Speaker 5: Meta had decided to fight to the very end, whether

640
00:32:54,450 --> 00:32:58,150
Speaker 5: they would have maybe won, again, because of the First Amendment, right? Like,

641
00:32:58,510 --> 00:33:02,370
Speaker 5: we are now still talking about speech restrictions imposed by

642
00:33:02,390 --> 00:33:04,510
Speaker 5: the government in some way. And there's some good questions

643
00:33:04,570 --> 00:33:08,720
Speaker 5: about whether if Kathy Hochul had written a law imposing

644
00:33:08,760 --> 00:33:11,500
Speaker 5: these restrictions, if she could have overcome the First Amendment.

645
00:33:12,220 --> 00:33:13,980
Speaker 5: because there would have been a First Amendment. If you

646
00:33:14,000 --> 00:33:18,120
Speaker 5: write a law saying teenagers cannot speak online after 8 p.m., well,

647
00:33:18,140 --> 00:33:21,020
Speaker 5: you're going to face a First Amendment challenge. And maybe

648
00:33:21,040 --> 00:33:23,060
Speaker 5: you'll overcome it because the harm to teens is so

649
00:33:23,140 --> 00:33:26,090
Speaker 5: great by letting them use Instagram after 8 p.m. that

650
00:33:26,630 --> 00:33:29,610
Speaker 5: it can withstand strict scrutiny of First Amendment challenge. I

651
00:33:29,630 --> 00:33:32,650
Speaker 5: don't know the answer to that question because Meta decided

652
00:33:32,910 --> 00:33:35,130
Speaker 5: the fight wasn't worth it, that they had bigger fish

653
00:33:35,150 --> 00:33:37,210
Speaker 5: to fry, and I don't know, the Metaverse or AI,

654
00:33:37,650 --> 00:33:39,890
Speaker 5: and they would agree to these restrictions. And the biggest

655
00:33:40,320 --> 00:33:42,750
Speaker 5: condition of those restrictions is is they would only pay

656
00:33:42,790 --> 00:33:45,590
Speaker 5: the full fine that they were assessed if Google and

657
00:33:45,670 --> 00:33:48,250
Speaker 5: TikTok agree to the same restrictions. Again, I think if

658
00:33:48,270 --> 00:33:50,150
Speaker 5: you're a parent, you're gonna like some of these restrictions.

659
00:33:50,170 --> 00:33:52,730
Speaker 5: You're gonna like no notifications late at night. You're gonna

660
00:33:52,770 --> 00:33:56,270
Speaker 5: like a default to RevCron instead of algorithmic recommendations. You're

661
00:33:56,290 --> 00:33:58,450
Speaker 5: gonna like that certain kind of makeup filters won't be allowed,

662
00:33:58,850 --> 00:34:00,670
Speaker 5: especially if you have a teenage daughter or something that

663
00:34:00,710 --> 00:34:03,820
Speaker 5: might give them body issues. There's all this stuff that

664
00:34:03,840 --> 00:34:06,180
Speaker 5: you would like as a parent that Meta agreed to

665
00:34:06,280 --> 00:34:07,900
Speaker 5: and said, you have to go, we have to go

666
00:34:07,980 --> 00:34:10,600
Speaker 5: push the other platforms to agree to as well. And

667
00:34:10,640 --> 00:34:12,900
Speaker 5: then if you just stand one step outside of it

668
00:34:13,300 --> 00:34:17,580
Speaker 5: and kind of do the first amendment analysis, you think, boy,

669
00:34:17,640 --> 00:34:21,680
Speaker 5: we just slid into a bunch of speech restrictions. And there's,

670
00:34:21,930 --> 00:34:24,770
Speaker 5: there's a lot of question marks around that. And there's

671
00:34:24,810 --> 00:34:26,730
Speaker 5: a lot of question marks around the age restriction piece,

672
00:34:26,750 --> 00:34:27,430
Speaker 5: which we can come to.

673
00:34:27,650 --> 00:34:31,250
Speaker 1: So, but, and that's why people like the reason crew

674
00:34:31,350 --> 00:34:32,250
Speaker 1: are freaking.

675
00:34:32,070 --> 00:34:32,630
Speaker 4: Out, right?

676
00:34:33,030 --> 00:34:36,470
Speaker 5: Yeah. I think broadly, you know, um, I think government

677
00:34:36,489 --> 00:34:38,950
Speaker 5: speech regulations are bad and this is a set of

678
00:34:38,989 --> 00:34:44,180
Speaker 5: government speech regulations. And they happened for business reasons. Meta

679
00:34:44,200 --> 00:34:47,700
Speaker 5: made a business decision to agree to these regulations. I

680
00:34:47,739 --> 00:34:49,650
Speaker 5: don't think anyone is out there saying Meta made a

681
00:34:49,680 --> 00:34:52,350
Speaker 5: moral choice here. They made a business decision to not

682
00:34:52,770 --> 00:34:55,390
Speaker 5: incur all these costs and fight this battle. And the

683
00:34:55,410 --> 00:34:57,130
Speaker 5: state got what it wanted. And again, I think a

684
00:34:57,190 --> 00:34:59,630
Speaker 5: lot of parents are very happy about this. But a

685
00:34:59,690 --> 00:35:03,089
Speaker 5: lot of First Amendment types, a lot of libertarian types,

686
00:35:03,110 --> 00:35:05,469
Speaker 5: a lot of civil liberties folks, the ACLU is unhappy

687
00:35:05,489 --> 00:35:07,980
Speaker 5: about this as well. They're going to say, And I

688
00:35:08,000 --> 00:35:11,490
Speaker 5: think they will continue saying we should not slide into

689
00:35:11,590 --> 00:35:15,910
Speaker 5: government speech regulations without process, without doing the actual balancing

690
00:35:15,930 --> 00:35:18,350
Speaker 5: of harms. I don't know if they're going to challenge

691
00:35:18,390 --> 00:35:20,390
Speaker 5: this or not. There's a lot of noise around it,

692
00:35:20,430 --> 00:35:22,950
Speaker 5: as you mentioned, but we're going to see more cases

693
00:35:23,320 --> 00:35:27,400
Speaker 5: and the other companies at issue might make different decisions

694
00:35:27,440 --> 00:35:28,219
Speaker 5: that run this to ground.

695
00:35:28,739 --> 00:35:31,839
Speaker 1: But when you settle like this, you open the door

696
00:35:31,880 --> 00:35:33,180
Speaker 1: to more settlements like this.

697
00:35:34,000 --> 00:35:34,950
Speaker 2: You set a precedent.

698
00:35:35,320 --> 00:35:36,899
Speaker 5: You set a precedent and now, you know, the various

699
00:35:36,920 --> 00:35:40,600
Speaker 5: state AGs can walk into the offices of TikTok and

700
00:35:40,660 --> 00:35:44,560
Speaker 5: Snap and Google and say, this is the standard. We

701
00:35:44,600 --> 00:35:47,660
Speaker 5: expect at least this, if not more, to protect the

702
00:35:47,700 --> 00:35:51,220
Speaker 5: teens in our state. And that again is, well, that's

703
00:35:51,260 --> 00:35:55,550
Speaker 5: the floor of speech restriction. And I want to continue

704
00:35:55,570 --> 00:35:58,250
Speaker 5: to emphasize, I am a parent. And there's a part

705
00:35:58,270 --> 00:36:01,570
Speaker 5: of me that's thrilled that my daughter will have restrictions

706
00:36:01,690 --> 00:36:05,820
Speaker 5: around how she uses social media imposed by some regulatory process.

707
00:36:06,219 --> 00:36:08,700
Speaker 5: I think a good question on the other side that

708
00:36:08,739 --> 00:36:12,969
Speaker 5: complicates it was, is this the appropriate regulatory process to

709
00:36:13,090 --> 00:36:15,969
Speaker 5: balance speech restrictions in America. I think you can debate

710
00:36:15,989 --> 00:36:16,549
Speaker 5: either side of that.

711
00:36:16,810 --> 00:36:19,009
Speaker 1: Right. But so I would love you to go back

712
00:36:19,050 --> 00:36:22,600
Speaker 1: to Section 230 for a minute, because Section 230 is

713
00:36:22,640 --> 00:36:27,100
Speaker 1: this idea that technology platforms don't have the same kind

714
00:36:27,120 --> 00:36:30,359
Speaker 1: of culpability that a newspaper or a magazine or the

715
00:36:30,380 --> 00:36:34,390
Speaker 1: New York Times or a television station has, right? I mean,

716
00:36:34,410 --> 00:36:37,330
Speaker 1: they are protected from things that are posted on there.

717
00:36:38,430 --> 00:36:43,010
Speaker 1: Wouldn't this... be a moment if you wanted free speech,

718
00:36:43,130 --> 00:36:46,770
Speaker 1: but consequences for things that happen on those sites, whatever

719
00:36:46,810 --> 00:36:50,510
Speaker 1: they may be, to relook at Section 230?

720
00:36:50,510 --> 00:36:53,890
Speaker 5: I don't think so. But over time, I've slid to

721
00:36:54,340 --> 00:36:57,299
Speaker 5: a fuzzier version of I don't think so. Section 230

722
00:36:57,300 --> 00:37:00,740
Speaker 5: only works if you concede that some speech is illegal

723
00:37:00,800 --> 00:37:02,640
Speaker 5: and you should be punished for it. And we do

724
00:37:02,660 --> 00:37:06,020
Speaker 5: have categories of that speech, right? Defamation is the biggest

725
00:37:06,060 --> 00:37:08,940
Speaker 5: category of speech that publishers worry about constantly. If you

726
00:37:09,380 --> 00:37:11,660
Speaker 5: tell lies about somebody and cause them some reputational harm,

727
00:37:12,000 --> 00:37:14,100
Speaker 5: especially if they're not famous, they can sue you for defamation.

728
00:37:14,500 --> 00:37:16,719
Speaker 5: If you say Donald Trump's name three times in a row,

729
00:37:16,760 --> 00:37:18,440
Speaker 5: he sues you for defamation. This is a way he

730
00:37:18,460 --> 00:37:22,200
Speaker 5: chills speech. So if you remove the Section 230 shield

731
00:37:22,719 --> 00:37:25,360
Speaker 5: from the big platforms and say the speech of the

732
00:37:25,400 --> 00:37:29,419
Speaker 5: people posting counts as your speech too, because you distributed it, well,

733
00:37:29,440 --> 00:37:32,680
Speaker 5: then the defamation risk for platforms skyrockets. What are they

734
00:37:32,700 --> 00:37:34,799
Speaker 5: going to do in response to that? They're going to

735
00:37:35,680 --> 00:37:38,339
Speaker 5: censor more speech. They're going to moderate harder. And maybe

736
00:37:38,380 --> 00:37:40,779
Speaker 5: that's the goal that you have. But I don't think

737
00:37:40,800 --> 00:37:44,069
Speaker 5: that cuts down on lies. I don't think that cuts

738
00:37:44,110 --> 00:37:46,210
Speaker 5: down on bullying. I don't think that cuts down on

739
00:37:46,250 --> 00:37:48,690
Speaker 5: harassment because that speech is not illegal.

740
00:37:48,710 --> 00:37:49,610
Speaker 1: Right.

741
00:37:49,650 --> 00:37:52,210
Speaker 5: So all you're really doing is you're increasing the amount

742
00:37:52,270 --> 00:37:54,549
Speaker 5: of speech that will be held in review to make

743
00:37:54,610 --> 00:37:58,300
Speaker 5: sure it doesn't defame someone. And you might be catching

744
00:37:58,340 --> 00:38:00,020
Speaker 5: a lot of speech in the mix. And that has

745
00:38:00,060 --> 00:38:02,400
Speaker 5: always been the problem with 230, is that under it

746
00:38:02,780 --> 00:38:06,180
Speaker 5: is the First Amendment, which generally says most speech is legal.

747
00:38:07,080 --> 00:38:07,719
Speaker 2: I understand.

748
00:38:07,739 --> 00:38:10,200
Speaker 1: It's just more of a question of, like, if you

749
00:38:10,219 --> 00:38:15,410
Speaker 1: have one set of rules for all of the mainstream media,

750
00:38:15,530 --> 00:38:19,250
Speaker 1: however small it is becoming, and another set of rules

751
00:38:19,370 --> 00:38:23,989
Speaker 1: for all of social media, that seems problematic to me.

752
00:38:24,730 --> 00:38:26,469
Speaker 5: It does, although let me flip that around a little bit.

753
00:38:26,550 --> 00:38:31,110
Speaker 5: The mainstream media loves to distribute its work on these platforms.

754
00:38:31,469 --> 00:38:31,730
Speaker 1: Right.

755
00:38:31,770 --> 00:38:33,690
Speaker 5: So we're making this podcast that's going to go out

756
00:38:33,750 --> 00:38:35,650
Speaker 5: on YouTube and Spotify and whatever else it might go

757
00:38:35,670 --> 00:38:38,680
Speaker 5: out on. Do you want YouTube and Spotify to hold

758
00:38:38,739 --> 00:38:41,660
Speaker 5: this in review, even if we criticize YouTube and Spotify

759
00:38:41,680 --> 00:38:45,300
Speaker 5: and say, well, we've got this big, you know, defamation risk.

760
00:38:45,660 --> 00:38:47,799
Speaker 5: We need to review your content before it goes out.

761
00:38:48,120 --> 00:38:50,540
Speaker 5: Do you want Google to hold the New York Times

762
00:38:50,600 --> 00:38:53,290
Speaker 5: in review before it surfaces in search results? Like, There's

763
00:38:53,330 --> 00:38:56,640
Speaker 5: another side of that argument where that shield is actually

764
00:38:56,739 --> 00:38:59,219
Speaker 5: really important to the dissemination of news, even if that

765
00:38:59,260 --> 00:39:01,779
Speaker 5: news is critical of the platforms. I can actually make

766
00:39:01,820 --> 00:39:04,680
Speaker 5: this even more complicated in another way, and this is

767
00:39:04,700 --> 00:39:07,770
Speaker 5: the issue with a lot of tech regulation. One of

768
00:39:07,810 --> 00:39:10,350
Speaker 5: the things in this settlement is age verification. We're gonna

769
00:39:10,410 --> 00:39:13,049
Speaker 5: make sure teens are under these controls, which means you

770
00:39:13,070 --> 00:39:15,529
Speaker 5: gotta make sure they're teens. which means you and I

771
00:39:15,750 --> 00:39:16,690
Speaker 5: have to prove we're adults.

772
00:39:17,110 --> 00:39:22,360
Speaker 1: Right, right. Which means privacy violations and more information, more data.

773
00:39:22,660 --> 00:39:25,880
Speaker 5: Right, it de-anonymizes the internet, right? But like, that's a

774
00:39:25,920 --> 00:39:27,580
Speaker 5: big deal. If every time I go to use one

775
00:39:27,600 --> 00:39:30,259
Speaker 5: of these platforms to speak as an adult, I have

776
00:39:30,300 --> 00:39:32,380
Speaker 5: to show my ID and prove that I'm an adult.

777
00:39:33,020 --> 00:39:36,400
Speaker 5: Now I would connect that to section 230. If I'm

778
00:39:36,420 --> 00:39:38,580
Speaker 5: going to publish something that's risky or critical of the

779
00:39:38,620 --> 00:39:43,830
Speaker 5: government and a platform has increased risk of some kind

780
00:39:43,870 --> 00:39:45,890
Speaker 5: of lawsuit because they're going to take ownership of it

781
00:39:46,330 --> 00:39:48,969
Speaker 5: and they know who I am, how are they going

782
00:39:48,989 --> 00:39:51,100
Speaker 5: to get out of that risk? they're going to tell

783
00:39:51,140 --> 00:39:53,969
Speaker 5: the government, this is the anonymous speaker that criticized you

784
00:39:54,030 --> 00:39:55,770
Speaker 5: and they don't like. And that is just a big

785
00:39:55,969 --> 00:39:57,930
Speaker 5: swirl of problems that is worth contending with.

786
00:39:57,950 --> 00:40:01,390
Speaker 1: I just wonder, and again, I'm not disagreeing or agreeing

787
00:40:01,410 --> 00:40:05,010
Speaker 1: because this is not my field of expertise, really, more

788
00:40:05,050 --> 00:40:07,989
Speaker 1: just as a consumer. But I just wonder if like

789
00:40:08,010 --> 00:40:13,390
Speaker 1: the way we have, tech companies have really acted in

790
00:40:13,489 --> 00:40:17,420
Speaker 1: such bad faith for such, since their inception, really, that

791
00:40:17,480 --> 00:40:20,989
Speaker 1: I just wonder if when we talk about this It's

792
00:40:21,190 --> 00:40:24,270
Speaker 1: almost like we're assuming they'll act in more bad faith

793
00:40:24,350 --> 00:40:28,270
Speaker 1: going forward because they will. And I just wonder how

794
00:40:28,290 --> 00:40:32,250
Speaker 1: I just want to sort of note that, you know.

795
00:40:32,350 --> 00:40:32,689
Speaker 2: Oh, yeah.

796
00:40:33,290 --> 00:40:35,670
Speaker 5: It's called malicious compliance. It's one of my favorite phrases.

797
00:40:35,790 --> 00:40:39,660
Speaker 5: And the tech companies have sort of operationalized malicious compliance.

798
00:40:40,380 --> 00:40:43,000
Speaker 5: You pass a regulation. Everyone knows what that regulation is

799
00:40:43,020 --> 00:40:45,580
Speaker 5: supposed to do. And then they meet it with the

800
00:40:45,800 --> 00:40:47,860
Speaker 5: letter of the law and absolutely not the spirit. And

801
00:40:47,880 --> 00:40:50,160
Speaker 5: we are just kind of confused about it. I'll give

802
00:40:50,180 --> 00:40:53,560
Speaker 5: you a really good example. Epic Games, which makes Fortnite,

803
00:40:53,900 --> 00:40:57,000
Speaker 5: has been suing Apple over how apps are distributed in

804
00:40:57,020 --> 00:41:00,540
Speaker 5: the App Store for 100 years. That case has just

805
00:41:00,560 --> 00:41:03,359
Speaker 5: been going forever. And Apple has won some pieces, they've

806
00:41:03,380 --> 00:41:08,780
Speaker 5: lost some pieces, and they've appealed, and they keep ending

807
00:41:08,840 --> 00:41:11,190
Speaker 5: up back in front of the same judge in California

808
00:41:11,489 --> 00:41:15,010
Speaker 5: who keeps screaming at them for not following her ruling.

809
00:41:15,950 --> 00:41:20,740
Speaker 5: She's furious that Apple has found ways... approach after approach

810
00:41:21,140 --> 00:41:23,589
Speaker 5: to avoid the thing she said they needed to do,

811
00:41:23,910 --> 00:41:26,030
Speaker 5: which is open up the stores and change the fee structure.

812
00:41:27,070 --> 00:41:29,650
Speaker 5: They have found approach after approach to avoid the thing

813
00:41:29,670 --> 00:41:31,590
Speaker 5: she told them to do, which is open up the

814
00:41:31,610 --> 00:41:33,790
Speaker 5: store in certain ways and changes fee structure in certain ways.

815
00:41:34,330 --> 00:41:36,970
Speaker 5: And Apple just won't do it. It is crystal clear

816
00:41:37,270 --> 00:41:39,070
Speaker 5: what she wants them to do and they won't do it.

817
00:41:39,570 --> 00:41:40,930
Speaker 5: And so they keep ending up in front of her

818
00:41:40,969 --> 00:41:43,030
Speaker 5: and she keeps basically being like, what are you doing?

819
00:41:43,410 --> 00:41:45,570
Speaker 5: Here's another set of sanctions. And then they appeal the sanctions.

820
00:41:45,610 --> 00:41:47,610
Speaker 5: We do this again. And that's Apple. They have the

821
00:41:47,690 --> 00:41:51,110
Speaker 5: best reputation of all these companies. Every other company is

822
00:41:51,140 --> 00:41:54,560
Speaker 5: playing the same games, and in many cases, even more aggressively.

823
00:41:55,000 --> 00:41:55,780
Speaker 2: So interesting.

824
00:41:56,460 --> 00:41:59,310
Speaker 1: So let's talk about my other favorite tech company.

825
00:42:00,110 --> 00:42:01,330
Speaker 2: Product, AI.

826
00:42:01,670 --> 00:42:04,410
Speaker 1: It seems as if there's been a moment now where

827
00:42:05,160 --> 00:42:09,020
Speaker 1: very wealthy people have decided or the people involved in

828
00:42:09,140 --> 00:42:11,479
Speaker 1: AI have decided that they have to try to sell

829
00:42:11,520 --> 00:42:15,620
Speaker 1: data centers with more than just Trump saying they're good

830
00:42:15,660 --> 00:42:18,140
Speaker 1: and if you don't like them, you're backwards. Would you

831
00:42:18,219 --> 00:42:20,900
Speaker 1: explain sort of where we are with data centers at

832
00:42:20,940 --> 00:42:21,540
Speaker 1: this moment?

833
00:42:22,280 --> 00:42:26,450
Speaker 5: Yes, it's complicated like everything. The industry is seeing a

834
00:42:27,030 --> 00:42:30,780
Speaker 5: so much explosive improvement in the capability of the big

835
00:42:30,880 --> 00:42:35,200
Speaker 5: AI models, and they are seeing tons of demand for inference,

836
00:42:35,260 --> 00:42:38,540
Speaker 5: for using AI. So the desire to build as many

837
00:42:38,580 --> 00:42:40,940
Speaker 5: data centers as they can to both service the demand

838
00:42:41,020 --> 00:42:43,919
Speaker 5: and figure out what this market really looks like and

839
00:42:44,120 --> 00:42:47,610
Speaker 5: build even more capable models is massive. And they're doing it.

840
00:42:47,630 --> 00:42:50,350
Speaker 5: You can see they're constantly announcing these projects. Whether or

841
00:42:50,370 --> 00:42:52,750
Speaker 5: not the projects are actually funded or come to fruition

842
00:42:52,790 --> 00:42:56,239
Speaker 5: or even begin right? There's a lot of that swirl

843
00:42:56,320 --> 00:42:59,739
Speaker 5: where things haven't happened. Right next to that is they

844
00:42:59,780 --> 00:43:02,239
Speaker 5: haven't asked for enough permission, and they're asking for a

845
00:43:02,320 --> 00:43:05,000
Speaker 5: lot here, right? They're asking for lots of land. They're

846
00:43:05,020 --> 00:43:07,580
Speaker 5: asking for lots of energy. They're asking for some amount

847
00:43:07,600 --> 00:43:09,200
Speaker 5: of water, although the amount of water is not what

848
00:43:09,219 --> 00:43:10,700
Speaker 5: people always say. Right.

849
00:43:10,780 --> 00:43:13,739
Speaker 1: It's not as much as almonds, as I was told

850
00:43:13,780 --> 00:43:16,620
Speaker 1: by Sam Allman. But you know, almonds you can eat.

851
00:43:17,440 --> 00:43:20,360
Speaker 5: I think they did not realize that the products are

852
00:43:20,440 --> 00:43:24,469
Speaker 5: not as good or as compelling for everyday people as

853
00:43:24,510 --> 00:43:27,370
Speaker 5: they are for businesses. So if you run a law

854
00:43:27,390 --> 00:43:31,230
Speaker 5: firm and you can do a piece of legal research

855
00:43:31,290 --> 00:43:36,060
Speaker 5: or prepare a trial brief in five minutes inside of

856
00:43:36,060 --> 00:43:37,799
Speaker 5: 15 hours, which is a real thing that lawyers tell

857
00:43:37,820 --> 00:43:40,839
Speaker 5: me all the time, that is incredibly compelling. You're going

858
00:43:40,860 --> 00:43:44,400
Speaker 5: to pay money for that. If you run an accounting

859
00:43:44,440 --> 00:43:46,219
Speaker 5: firm and you can automate a bunch of accounting flows,

860
00:43:46,380 --> 00:43:48,360
Speaker 5: if you're on an ad agency and you can automate

861
00:43:48,410 --> 00:43:49,910
Speaker 5: a bunch of marketing, which is what all the ad

862
00:43:49,950 --> 00:43:53,150
Speaker 5: agencies are doing, your demand for these tokens is through

863
00:43:53,170 --> 00:43:57,109
Speaker 5: the roof. And that's not AI slop, right? That's not one,

864
00:43:57,230 --> 00:43:58,969
Speaker 5: we're gonna file a brief to the judge that was

865
00:43:59,010 --> 00:44:01,140
Speaker 5: entirely written by AI. That is the actual nuts and

866
00:44:01,160 --> 00:44:03,340
Speaker 5: bolts work that these companies are doing that they can

867
00:44:03,440 --> 00:44:06,480
Speaker 5: automate instead of having someone do in some boring, repetitive way.

868
00:44:07,080 --> 00:44:10,819
Speaker 5: That demand is real. On the consumer side, Well, what

869
00:44:10,840 --> 00:44:12,900
Speaker 5: do we get, man? We get slop in our feeds.

870
00:44:12,980 --> 00:44:15,759
Speaker 5: We get AI overviews that are full of lies. We

871
00:44:16,100 --> 00:44:18,049
Speaker 5: have the free version of ChatGPT that's going to have

872
00:44:18,140 --> 00:44:21,969
Speaker 5: ads in it. Like those products are compelling in one

873
00:44:22,010 --> 00:44:24,730
Speaker 5: way and people really like them, but they're not great.

874
00:44:24,969 --> 00:44:27,710
Speaker 5: And I think that industry assumed they were great. They

875
00:44:27,730 --> 00:44:32,030
Speaker 5: confused the business adoption and the business excitement for consumer

876
00:44:32,070 --> 00:44:35,259
Speaker 5: adoption for what would create the political capital to go

877
00:44:35,300 --> 00:44:37,420
Speaker 5: make these big asks. And then on top of it,

878
00:44:37,440 --> 00:44:39,180
Speaker 5: they all ran around saying they're going to take all

879
00:44:39,200 --> 00:44:41,340
Speaker 5: the jobs away. So now you've got a bunch of

880
00:44:41,360 --> 00:44:43,779
Speaker 5: young people who are like, I will never use AI.

881
00:44:43,820 --> 00:44:45,500
Speaker 5: This thing is going to threaten the world I live in.

882
00:44:45,500 --> 00:44:47,780
Speaker 2: I'm not even young. And I feel that way.

883
00:44:48,300 --> 00:44:50,180
Speaker 5: Some of the products are good. It is important to

884
00:44:50,219 --> 00:44:52,239
Speaker 5: say some of the products are very compelling and like

885
00:44:52,260 --> 00:44:55,880
Speaker 5: very specific ways, but they're all, it's all business software.

886
00:44:56,300 --> 00:44:58,200
Speaker 5: It is just not consumer software in the way you

887
00:44:58,239 --> 00:45:00,719
Speaker 5: want it to be. And if these AI, I've said

888
00:45:00,760 --> 00:45:03,240
Speaker 5: this to the leaders of the AI companies, if you

889
00:45:03,930 --> 00:45:06,870
Speaker 5: would just pay for healthcare in America, If you would

890
00:45:06,890 --> 00:45:09,270
Speaker 5: just set aside some of your profits and make it

891
00:45:09,410 --> 00:45:12,210
Speaker 5: so that people could get healthcare, a real thing that

892
00:45:12,250 --> 00:45:15,710
Speaker 5: might happen is more people would feel inspired to quit

893
00:45:15,770 --> 00:45:18,370
Speaker 5: their job and start their own little company because the

894
00:45:18,469 --> 00:45:21,469
Speaker 5: AI could do all the administrative work of starting a

895
00:45:21,510 --> 00:45:25,339
Speaker 5: company and running all the bureaucracy of having a little company.

896
00:45:25,360 --> 00:45:27,380
Speaker 5: And you could just do lawn care or whatever it

897
00:45:27,420 --> 00:45:29,219
Speaker 5: is that you want to do. But most people don't

898
00:45:29,260 --> 00:45:31,100
Speaker 5: do that. I have kids. One of the reasons you

899
00:45:31,120 --> 00:45:32,759
Speaker 5: don't do that is because I need health insurance for

900
00:45:32,780 --> 00:45:35,840
Speaker 5: my kids. And so actually, if you would just provide

901
00:45:35,900 --> 00:45:39,460
Speaker 5: this benefit from your outsized profits or find a way

902
00:45:39,500 --> 00:45:42,830
Speaker 5: to provide this benefit, maybe people would see a benefit

903
00:45:42,870 --> 00:45:45,050
Speaker 5: to them. This is going to let me live a

904
00:45:45,070 --> 00:45:47,350
Speaker 5: life more agency or freedom or whatever it is that

905
00:45:47,750 --> 00:45:50,930
Speaker 5: makes Americans want to adopt technology. And they just can't.

906
00:45:51,710 --> 00:45:53,730
Speaker 5: That's a tax, right? They can't see it. So instead

907
00:45:53,750 --> 00:45:55,489
Speaker 5: they're running around being like, we're going to do drug

908
00:45:55,530 --> 00:45:58,730
Speaker 5: discovery and we'll cure all disease. Just let me build

909
00:45:58,750 --> 00:46:03,370
Speaker 5: this data center. And I think the political reality is

910
00:46:03,410 --> 00:46:06,750
Speaker 5: hitting them really hard. And it is also importantly realigning

911
00:46:06,790 --> 00:46:11,170
Speaker 5: our politics, right? Kathy Hochul signed a data center moratorium.

912
00:46:11,570 --> 00:46:14,569
Speaker 5: There's Greg Abbott signed a faker sort of data center

913
00:46:14,590 --> 00:46:18,339
Speaker 5: moratorium in Texas. It's state by state, we're seeing all

914
00:46:18,380 --> 00:46:20,569
Speaker 5: the politicians running against it because the people actually don't

915
00:46:20,660 --> 00:46:21,410
Speaker 5: like the products.

916
00:46:22,110 --> 00:46:24,410
Speaker 2: I like when Trump said that it's great.

917
00:46:24,850 --> 00:46:28,819
Speaker 5: It's weird that he's misreading this one, right? You know

918
00:46:28,900 --> 00:46:31,759
Speaker 5: more about that pathology. Usually he's really good at where

919
00:46:31,780 --> 00:46:34,140
Speaker 5: the wind is blowing, and he's just missing this one.

920
00:46:34,400 --> 00:46:37,700
Speaker 1: He's slowed down a lot, and he doesn't have the

921
00:46:37,739 --> 00:46:41,810
Speaker 1: same kind of thing he had before. Okay, explain to us,

922
00:46:41,930 --> 00:46:43,790
Speaker 1: one last question, we're out of time, but I want

923
00:46:43,810 --> 00:46:47,489
Speaker 1: to know this for me. What is happening with the

924
00:46:47,550 --> 00:46:52,640
Speaker 1: tech bros more generally? Like, This crew, Elon said he's

925
00:46:52,680 --> 00:46:54,600
Speaker 1: going to put money into the midterms and then he

926
00:46:54,640 --> 00:46:57,299
Speaker 1: puts in 800K, which just doesn't seem like a lot

927
00:46:57,340 --> 00:47:01,160
Speaker 1: of money to me. There's this documentary coming out about him,

928
00:47:01,180 --> 00:47:05,669
Speaker 1: which clearly he, you know, he's anxious about. It strikes

929
00:47:05,730 --> 00:47:07,670
Speaker 1: me that this is like not a great moment for

930
00:47:07,690 --> 00:47:08,649
Speaker 1: tech billionaires.

931
00:47:09,050 --> 00:47:10,810
Speaker 5: It is not a great moment for tech billionaires.

932
00:47:10,910 --> 00:47:11,530
Speaker 2: Which is good.

933
00:47:12,090 --> 00:47:15,070
Speaker 5: There's a real populist backlash to them. I have a

934
00:47:15,110 --> 00:47:18,759
Speaker 5: very reductive view of the American voter after all this time.

935
00:47:19,430 --> 00:47:22,150
Speaker 5: And it just comes down to, this is just my

936
00:47:22,190 --> 00:47:24,710
Speaker 5: personal view. I don't think Americans like being told what

937
00:47:24,730 --> 00:47:27,320
Speaker 5: to do. And maybe all of our elections are explained

938
00:47:27,340 --> 00:47:30,299
Speaker 5: by that more than anything. And the tech pros are

939
00:47:30,739 --> 00:47:32,819
Speaker 5: out there trying to tell people what to do. They

940
00:47:32,860 --> 00:47:34,780
Speaker 5: are in control of our lives. They are in control

941
00:47:34,800 --> 00:47:37,780
Speaker 5: of our feeds. They are in control of the information flow.

942
00:47:37,800 --> 00:47:41,660
Speaker 5: A lot of people. I started believing in conspiracy theory

943
00:47:41,680 --> 00:47:44,029
Speaker 5: that Elon controlled the voting machines this last time.

944
00:47:44,050 --> 00:47:45,830
Speaker 2: Yeah, a lot of people believe that.

945
00:47:45,850 --> 00:47:49,250
Speaker 5: Instead of whatever dictator that Biden was in control of.

946
00:47:49,890 --> 00:47:52,550
Speaker 5: There's a sense that they're in control of these computers

947
00:47:52,610 --> 00:47:54,950
Speaker 5: and the computers run our lives and AI will make

948
00:47:54,989 --> 00:47:58,350
Speaker 5: them even more powerful and they will capture even more profits.

949
00:47:58,450 --> 00:48:00,030
Speaker 5: And we still don't have health care and we still

950
00:48:00,050 --> 00:48:02,259
Speaker 5: don't have great roads and we still have bad water

951
00:48:02,300 --> 00:48:05,040
Speaker 5: in Flint. All of these things are a swirl that

952
00:48:05,060 --> 00:48:08,299
Speaker 5: they cannot contend with. And then I'll just leave with this,

953
00:48:08,360 --> 00:48:11,810
Speaker 5: which is, I think about this all the time. The

954
00:48:11,969 --> 00:48:14,009
Speaker 5: first thing they wanted to do with AI, the thing

955
00:48:14,050 --> 00:48:16,930
Speaker 5: they always talk about is replacing art and culture.

956
00:48:16,950 --> 00:48:17,529
Speaker 1: Right.

957
00:48:17,870 --> 00:48:18,969
Speaker 2: That's their favorite thing.

958
00:48:19,030 --> 00:48:19,170
Speaker 4: Yeah.

959
00:48:19,190 --> 00:48:21,010
Speaker 2: Because they hate writers and artists.

960
00:48:21,730 --> 00:48:25,180
Speaker 5: If only I could get three more seasons of The Sopranos,

961
00:48:25,300 --> 00:48:26,859
Speaker 5: one day I'll be able to prompt AI and just

962
00:48:27,200 --> 00:48:29,500
Speaker 5: I'll have more of it. And you're like, well, I

963
00:48:29,540 --> 00:48:32,180
Speaker 5: think David Chase brought that show to an end exactly

964
00:48:32,219 --> 00:48:34,960
Speaker 5: the way he wanted to. Like, that's not for you.

965
00:48:35,560 --> 00:48:37,880
Speaker 5: And one of the reasons I think they turn to

966
00:48:37,940 --> 00:48:42,319
Speaker 5: it so often is that the great creators, the great

967
00:48:42,460 --> 00:48:46,340
Speaker 5: artists of our time command so much literal love and

968
00:48:46,380 --> 00:48:49,680
Speaker 5: affection in a way that our industrialists kind of don't.

969
00:48:50,219 --> 00:48:52,270
Speaker 5: There's actually only one industrialist in our time who has,

970
00:48:52,330 --> 00:48:55,230
Speaker 5: it's Steve Jobs, right? And even he, like there's a

971
00:48:55,330 --> 00:48:57,670
Speaker 5: swirl of controversy around him at all the time. But

972
00:48:57,730 --> 00:49:00,049
Speaker 5: you know, I went to, years ago, I went to

973
00:49:00,090 --> 00:49:02,330
Speaker 5: the Eros tour with my niece and nephew, and I

974
00:49:02,330 --> 00:49:05,850
Speaker 5: was like, this is 80,000 people singing these songs. And

975
00:49:06,290 --> 00:49:09,290
Speaker 5: she's just alone on that stage. And no tech bro

976
00:49:09,370 --> 00:49:12,150
Speaker 5: can achieve that moment. And I would just point at

977
00:49:12,230 --> 00:49:16,410
Speaker 5: that very specifically as a thing that drives the pathology.

978
00:49:16,770 --> 00:49:20,200
Speaker 5: Elon Musk wants to be loved. He cannot manufacture that

979
00:49:20,239 --> 00:49:22,390
Speaker 5: moment and every time he's like i'll just make art

980
00:49:23,160 --> 00:49:26,620
Speaker 5: it is in my my mind it's an attempt to

981
00:49:26,680 --> 00:49:30,940
Speaker 5: somehow either defang the real culture that makes people feel

982
00:49:30,980 --> 00:49:33,200
Speaker 5: whatever they feel or it's an attempt to take it.

983
00:49:33,640 --> 00:49:37,370
Speaker 2: You think that they can make art in the end No. Yeah,

984
00:49:37,390 --> 00:49:38,310
Speaker 2: I don't think so either.

985
00:49:38,330 --> 00:49:42,170
Speaker 5: And I am of the mind that great products, great design,

986
00:49:42,750 --> 00:49:46,510
Speaker 5: there's something about them that is, it rhymes with art, right?

987
00:49:46,530 --> 00:49:48,799
Speaker 5: It makes people feel, like a beautiful car makes people

988
00:49:48,840 --> 00:49:51,420
Speaker 5: feel emotions in a way that art makes people feel emotions.

989
00:49:51,980 --> 00:49:54,440
Speaker 5: The iPhone, that first iPhone, it made people feel a

990
00:49:54,440 --> 00:49:56,880
Speaker 5: lot of emotions. Like there's something about those products that

991
00:49:56,940 --> 00:49:59,819
Speaker 5: rhyme with art, but it's something else.

992
00:50:00,360 --> 00:50:04,620
Speaker 2: Yeah, so interesting. I agree. Thank you, thank you, thank you.

993
00:50:04,900 --> 00:50:05,910
Speaker 5: Thank you for having me. This was so much fun.

994
00:50:08,320 --> 00:50:12,880
Speaker 2: And now your moment of fuckery. Jesse Cannon.

995
00:50:13,260 --> 00:50:16,680
Speaker 3: So my junk fast, we have seen flock cameras become

996
00:50:16,780 --> 00:50:20,600
Speaker 3: deeply unpopular very fast. And now we have a video

997
00:50:20,860 --> 00:50:24,660
Speaker 3: where it shows that they train cops to watch no

998
00:50:24,700 --> 00:50:29,060
Speaker 3: Kings protests with flock cameras. So everything the CEO has

999
00:50:29,100 --> 00:50:32,359
Speaker 3: been saying to try to quiet the public's disapproval is

1000
00:50:32,469 --> 00:50:32,890
Speaker 3: all bullshit.

1001
00:50:33,219 --> 00:50:37,890
Speaker 1: I still think, you know, get online because the stuff

1002
00:50:37,910 --> 00:50:40,570
Speaker 1: that these people are trying to convince you that data

1003
00:50:40,590 --> 00:50:44,150
Speaker 1: centers do for the good of humanity, they want to

1004
00:50:44,180 --> 00:50:45,920
Speaker 1: make money and they want to trick you and they

1005
00:50:45,940 --> 00:50:48,719
Speaker 1: want to build big data centers in your neighborhood.

1006
00:50:48,739 --> 00:50:49,960
Speaker 2: And that's it.

1007
00:50:51,210 --> 00:50:53,490
Speaker 1: You know, and they'll say it's like good paying jobs.

1008
00:50:53,530 --> 00:50:57,930
Speaker 1: What they mean is it's temporary construction jobs. And they'll

1009
00:50:57,989 --> 00:51:00,270
Speaker 1: say you can make, you know, that the towns will

1010
00:51:00,310 --> 00:51:03,350
Speaker 1: get taxes from it. And what they mean is maybe

1011
00:51:03,510 --> 00:51:06,819
Speaker 1: they'll get some taxes, but you'd be much better off

1012
00:51:06,860 --> 00:51:11,120
Speaker 1: with just having like things that are real factories.

1013
00:51:10,520 --> 00:51:12,340
Speaker 2: Where people work. than this.

1014
00:51:12,460 --> 00:51:17,020
Speaker 1: So it's a complete disaster. It's a loser for Republicans.

1015
00:51:17,239 --> 00:51:20,260
Speaker 1: And I think they'll try to figure out some, you know,

1016
00:51:20,330 --> 00:51:23,109
Speaker 1: lobbying thing. But I think it's going to be tough

1017
00:51:23,130 --> 00:51:26,640
Speaker 1: for them, which is good because fuck them. That's it

1018
00:51:26,760 --> 00:51:33,700
Speaker 1: for this episode of Fast Politics. Tune in every Monday, Wednesday, Thursday,

1019
00:51:33,900 --> 00:51:37,790
Speaker 1: and Saturday to hear the best minds in politics make

1020
00:51:37,870 --> 00:51:41,890
Speaker 1: sense of all this chaos. If you enjoy this podcast,

1021
00:51:42,310 --> 00:51:45,740
Speaker 1: please send it to a friend and keep the conversation going.

1022
00:51:46,140 --> 00:51:47,280
Speaker 2: Thanks for listening.