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Speaker 1: You Welcome to Fast Politics. I'm Molly Jongfast, and we

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Speaker 1: have a great show for you today. Later in the show,

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Speaker 1: we'll talk to the New York Times' own Carolyn Ryan

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Speaker 1: about the signs she sees to tell us how the

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Speaker 1: midterms will go. Then, as a bonus, we have Timothy Snyder,

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Speaker 1: and he's going to talk to us about Trump's increasingly

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Speaker 1: insane rhetoric. But first, we have Psycho Politics' own George

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Speaker 1: Conway to talk about Donald Trump destroying America and with debt.

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Speaker 2: George Conway.

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Speaker 3: Hello.

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Speaker 1: Donald Trump is doing to our federal deficit what he

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Speaker 1: did to the Trump organization.

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Speaker 4: Really?

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Speaker 1: Trump steaks, Trump water, the Trump shuttle.

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Speaker 3: Are we talking about like bankruptcy?

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Speaker 1: Yes, we're talking about bankruptcy.

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Speaker 3: Do you see this coming? I somehow, I just felt

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Speaker 3: it coming, yes. Let me tell you a funny story once.

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Speaker 2: Yeah.

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Speaker 3: I was with my ex-wife in Ventnor, New Jersey, and

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Speaker 3: we were with this Washington Post reporter, a guy named

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Speaker 3: Ben Terrace. And this was 2019. I was off the reservation,

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Speaker 3: so he was kind of very curious about what I

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Speaker 3: had to say and what she had to say and

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Speaker 3: how it differed. And I actually got into the newspaper.

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Speaker 3: She started talking about how wonderful it was that Donald

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Speaker 3: Trump had been so good to Atlantic City and that

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Speaker 3: he built the Taj Mahal. And I said, yeah, went

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Speaker 3: bankrupt twice. But anyway, yeah. So you want to talk

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Speaker 3: about the federal debt?

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Speaker 1: I mean, I think since it's hitting, since like it's

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Speaker 1: yet another thing in this administration that is breaking records,

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Speaker 1: it might be.

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Speaker 3: Worth looking at. Yes. I mean, it's sort of like

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Speaker 3: the practical things about running a country get lost in

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Speaker 3: all the insanity and corruption. But the way to think

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Speaker 3: about this is that for the United States, I mean,

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Speaker 3: the debt is at a record figure. And I forget

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Speaker 3: what percentage of that debt, 30, 40, some high percentage

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Speaker 3: of that debt was accumulated by the 45th and 47th

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Speaker 3: presidents of the United States, who was actually just one guy. And,

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Speaker 3: you know, maybe most of it was accumulated by the

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Speaker 3: other 44 or 45. Depends on where you count Grover

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Speaker 3: Cleveland twice. But this one guy somehow managed to do

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Speaker 3: most of himself like no one has ever seen. And

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Speaker 3: the problem also is like, you know, we're not like

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Speaker 3: Kimberly Guilfoyle. The United States of America is not like

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Speaker 3: Kimberly Guilfoyle. We just can't call up someone and say, hey,

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Speaker 3: pay our bills, right? You can't just send a single

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Speaker 3: text and say, look, just send the money directly to

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Speaker 3: our creditors.

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Speaker 1: So you're referencing this incredible reporting from the Wall Street

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Speaker 1: Journal owned by Rupert Murdoch, the story of Kimberly Guilfoyle

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Speaker 1: sending a guy, a donor, a Republican donor, wiring instructions

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Speaker 1: to her American Express card because she owed $ 100, 000 before

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Speaker 1: she was going in front of Congress to get congressional

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Speaker 1: approval to become the ambassador to Greece, a job she

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Speaker 1: was given so that Donald Trump Jr. could marry someone else.

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Speaker 3: I mean, you know, we all, every month when our

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Speaker 3: American Express bills come through, we all have someone we

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Speaker 3: text and say, please pay it. Honey, and don't pay

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Speaker 3: for it. And don't write it down because it'll screw

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Speaker 3: up our congressional hearings. That was actually the smartest thing

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Speaker 3: she said. The little text saying, stop it. You're going

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Speaker 3: to get me. You're going to screw up my confirmation.

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Speaker 3: Smartest thing she said.

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Speaker 1: I want to point out that I'm not sure how

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Speaker 1: many people have a PDF ready of how to wire

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Speaker 1: and pay my Amex. Like that's not something that you

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Speaker 1: generally have available.

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Speaker 3: You don't have one in your purse? Like, do you

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Speaker 3: hand it out as you walk down the street in

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Speaker 3: New York? Say, hey, by the way, I have some

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Speaker 3: bills here.

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Speaker 1: Like, don't you think the fact that she had that

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Speaker 1: on the ready, one could guess that this is not

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Speaker 1: the first time she's done this?

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Speaker 3: But I thought she was like, you know, a professional.

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Speaker 3: I mean, you know, I mean, a professional person.

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Speaker 2: Yes.

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Speaker 3: You know, like a PhD. Yes, a PhD. Yes, yes.

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Speaker 1: A person who works at Fox News, a professional.

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Speaker 3: Has an income that she where she makes her own money.

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Speaker 1: Yeah. No, I don't know.

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Speaker 3: I don't know either. We're just asking questions here.

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Speaker 1: We're just asking questions. But when you read that Wall

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Speaker 1: Street Journal piece about Kimberly Guilfoyle, and it's actually the

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Speaker 1: second one because it was earlier. She's had this lobbyist

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Speaker 1: with her. There's all sorts of strikes. There's clearly a

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Speaker 1: lot of hanky-panky going on or chicanery, right? But my

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Speaker 1: question to you is, doesn't this remind you of Trump 1.0,

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Speaker 1: where there were stories like this every day?

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Speaker 3: Oh, yeah, there were, but it's much worse now.

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Speaker 2: Right.

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Speaker 3: It's much worse now. Talk about it. I mean, you've

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Speaker 3: got all the people who didn't go into the administration,

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Speaker 3: who have been around for years, who are basically collecting

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Speaker 3: money from foreign governments, collecting money from companies who are

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Speaker 3: fearful of being regulated or who want regulation of other

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Speaker 3: people in their industry and one of courage favor with

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Speaker 3: the administration and believe that the way in to the

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Speaker 3: administration is to hire people who are associated with the,

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Speaker 3: you know, either Trump 1.0 or Trump 2.0. And, and I,

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Speaker 3: you know, if we had a real justice department at

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Speaker 3: this moment, there'd be a massive investigation of, of Kimberly

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Speaker 3: Guilfoyle and the way it would work. And this, I

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Speaker 3: don't think Kimberly Guilfoyle is, is the big fish here.

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Speaker 3: And I don't know whether she did anything, frankly, that

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Speaker 3: was illegal or, It certainly was sleazy. I don't know how,

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Speaker 3: you know, the question of illegality would be, you know,

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Speaker 3: whether she was giving something of governmental, you know, as

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Speaker 3: a governmental servant. I don't think that was. I think

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Speaker 3: she was just trying to, whether she disclosed that she

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Speaker 3: was a lobbyist.

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Speaker 1: And ambassadorships are notoriously sketchy because they're usually given to

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Speaker 1: donors and it's.

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Speaker 3: Not, it's either way. It's a slippery slope. Yeah, but

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Speaker 3: I don't know that this had anything to do with

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Speaker 3: her ambassadorship other than she was trying to not have

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Speaker 3: the debt listed when she filed her financial disclosures or

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Speaker 3: whatever disclosures she was concerned about having to file, which

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Speaker 3: you do have to file when you apply for one

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Speaker 3: of these jobs and then subsequently have to disclose under

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Speaker 3: the Ethics and Government Act. So I don't know. I

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Speaker 3: don't know that she did anything illegal. It certainly looks bad,

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Speaker 3: but I think it really does reflect an industry that

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Speaker 3: is going on right now, and it's sleazy. It just

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Speaker 3: has a sleazy look about it, sleazy feel about it,

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Speaker 3: and there are gradations of it that range from just

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Speaker 3: ordinary regular lobbying that goes on under any administration to

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Speaker 3: something that could be much worse. It's all a spectrum

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Speaker 3: and there are lots of different people involved, and the

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Speaker 3: way these investigations sometimes get started is that somebody gets

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Speaker 3: pissed off because they didn't get their money's worth. And

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Speaker 3: I remember, one of the things I was sort of

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Speaker 3: thinking of when I read about this story and was

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Speaker 3: thinking about it last night was the Jack Abramoff situation.

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Speaker 3: Remember Jack Abramoff? And Jack Abramoff had been at one point,

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Speaker 3: I think, a very high official in the RNC. Maybe

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Speaker 3: he was even chairman of the RNC, but he was

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Speaker 3: a very, very prominent Republican, very smart guy. He was

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Speaker 3: kind of an entrepreneur. He had started a couple of

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Speaker 3: great restaurants on Pennsylvania Avenue. He was very religious. Um, and, um, he,

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Speaker 3: but he, you know, he just got his, he had

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Speaker 3: his finger in too many pies and he, he ended

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Speaker 3: up doing this bit where he was convinced he convinced some,

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Speaker 3: I think an Indian tribe that, that, that they, that

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Speaker 3: he could get something done with their Indian casinos or

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Speaker 3: something like that. And they ended up feeling like, you know,

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Speaker 3: we didn't get our money's worth. And that triggered, that

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Speaker 3: was part of a big, big investigation. And he ultimately

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Speaker 3: went to jail. And it's like, when you piss somebody off,

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Speaker 3: and that's what Guilfoyle did here with this guy who

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Speaker 3: is quite a character. He apparently went on the Bulwark podcast,

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Speaker 3: one of the Bulwark podcasts with Sam Stein yesterday. He

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Speaker 3: just basically just let loose.

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Speaker 1: And he also was on MS, and I think he

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Speaker 1: was on CNN. He sort of hit all the places,

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Speaker 1: and he's... loud and maybe a little Sam Nunberg-y. Eric

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Speaker 1: Dieters is his name.

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Speaker 3: Yeah, Eric Dieters. He may be a little over the

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Speaker 3: edge or over the top a little bit, but he's

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Speaker 3: pissed off. And that's actually how investigations of various sorts

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Speaker 3: get started. It's like somebody gets pissed off that they

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Speaker 3: paid money, didn't get their money's worth, and then Then

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Speaker 3: the prosecutors start looking at it or investigators start looking

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Speaker 3: at whether this was legal or not. They look at

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Speaker 3: the issues and they look at where the money went

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Speaker 3: and then maybe somebody didn't pay their taxes or maybe

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Speaker 3: there was something illegal. Maybe they passed on money to

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Speaker 3: someplace else they didn't disclose. Maybe they were committing fraud

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Speaker 3: when they told the person they could do something. Then

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Speaker 3: that person could be like, okay, okay, okay. I know

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Speaker 3: everybody else is doing stuff that's worse and I could

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Speaker 3: tell you about them. And it becomes a bigger and

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Speaker 3: bigger investigation. And that's the kind of thing that would

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Speaker 3: happen if you actually had a Department of Justice that

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Speaker 3: was willing to prosecute people that had something to do

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Speaker 3: with this administration. So, I mean, the real question is,

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Speaker 3: are these people ever going to be held accountable? And again,

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Speaker 3: I'm not saying that Kimberly Guilfoyle herself did anything illegal here.

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Speaker 1: But this is, again, this is norms versus.

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Speaker 2: Right, norms versus laws.

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Speaker 3: But when you have little bits like this, you know

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Speaker 3: there's a lot of things going on there. Some of

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Speaker 3: them are not going to be kosher. It just has

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Speaker 3: that feel to it. I just hope to high heaven

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Speaker 3: that the Democrats win both houses of Congress and start

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Speaker 3: just turning over the rocks here. Now, obviously, the Justice

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Speaker 3: Department's not going to do anything, but some of these

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Speaker 3: things that could, if there are offenses to be found,

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Speaker 3: some of them, they could be federal offenses, but they

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Speaker 3: could also be state law offenses. They could also be

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Speaker 3: offenses under foreign law. You know, when you're dealing with,

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Speaker 3: you know, a lot of these Trumpers are taking money

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Speaker 3: from foreign governments and foreign interests. And, you know, we

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Speaker 3: don't know what that all entails. And I'm just a

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Speaker 3: lot of, there's just a lot of money sloshing around. And,

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Speaker 3: you know, the Wall Street Journal has done a tremendous service,

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Speaker 3: a tremendous job looking into this stuff. ProPublica, ProPublica, I don't,

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Speaker 3: I always pronounce it wrong, ProPublica. you know, with its

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Speaker 3: story about the Don Jr.

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Speaker 1: Wedding.

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Speaker 3: I mean, this stuff, we're going to be finding out

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Speaker 3: stuff like this for years. And the real question is,

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Speaker 3: you know, who's going to be held accountable and how?

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Speaker 3: And I think right now it's, you know, our best

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Speaker 3: hope is that we have a real Justice Department in

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Speaker 3: a couple of years that can pursue this, but it's

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Speaker 3: going to take a while to get that Justice Department

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Speaker 3: up and running because the current Justice Department, you know, people,

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Speaker 3: you know, so many good people have been forced to

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Speaker 3: and have left because they just can't, they can't they

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Speaker 3: can't stand being part of an organization that's being so degraded. Um,

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Speaker 3: and in fact, I know though, I think there's one

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Speaker 3: lot of hope on the horizon. I know that there's somebody,

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Speaker 3: there are people trying to form groups or organizations that

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Speaker 3: are going to get together. You know, these are private

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Speaker 3: groups that are going to get together professional ex prosecutors

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Speaker 3: and investigators. You know, they won't have subpoena power, um,

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Speaker 3: but they can, they can put together based upon these

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Speaker 3: news stories and based upon gumshoe work, um, uh, case

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Speaker 3: files so that people, when we have real prosecutors someday

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Speaker 3: back on the job, they'll have something to work with

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Speaker 3: and get started on.

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Speaker 1: Yeah, I think that's really important. And I think there's

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Speaker 1: definitely going to need to be, and we see this

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Speaker 1: with voters, right? We look at these midterms and we

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Speaker 1: see a huge group of double haters. Those are people

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Speaker 1: who are mad at corruption. They're mad at Republicans, they're

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Speaker 1: madder at Republicans because there's more Republican corruption, but they're

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Speaker 1: mad at both. And if you don't address that corruption,

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Speaker 1: they'll be mad at Democrats too. And so that is

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Speaker 1: That you do that, A, because it's right, and B,

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Speaker 1: because it's politically savvy.

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Speaker 3: It's politically savvy. And also, it's like one of the

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Speaker 3: reasons why we have a criminal law. We have the

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Speaker 3: criminal law for general deterrence. We have it for specific

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Speaker 3: deterrence to keep the bad guy specifically under wraps. But

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Speaker 3: we also have it for there's a retributive. There's the

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Speaker 3: need for retribution. There's a need to feel that there's

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Speaker 3: a fairness in the world. And all of these things

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Speaker 3: are really, really important and we've lost them. And we

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Speaker 3: can't have a society under the rule of law where

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Speaker 3: people feel that they are punished for obeying the law.

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Speaker 3: And that's what we have right now. People feel disadvantaged

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Speaker 3: because they can't, they follow the law, they pay their taxes.

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Speaker 3: They can't buy favors from the government or they're not

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Speaker 3: friendly with people who can give them a wink and

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Speaker 3: a nod and a pass. And that's very, very corrosive

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Speaker 3: to democratic government, very, very corrosive to the rule of law.

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Speaker 3: And I think a lot of that, I mean, I

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Speaker 3: can't figure out the, I mean, I think that's part of,

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Speaker 3: I think what's going to undermine the Republicans this year, specifically,

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Speaker 3: even including among former double or triple Trump voters. I

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Speaker 3: also think, you know, maybe it's part of, I can't

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Speaker 3: figure out the far, far left here. They hate everybody. But,

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Speaker 3: you know, I mean, A lot of the unhappiness in

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Speaker 3: our country, it can be attributed to the fact that

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Speaker 3: people feel that other people are getting away with murder.

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Speaker 3: The irony is that those people voted Trump in, some

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Speaker 3: of those people voted Trump in, and they just made

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Speaker 3: it worse. So we have to undo it and convince

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Speaker 3: people that it's getting better and it's never going to

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Speaker 3: be perfect, but we're trying. You have to do your

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Speaker 3: part by playing by the rules too.

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Speaker 2: Right.

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Speaker 1: And I mean, I just want to push back for

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Speaker 1: a minute on that. There is an inter-party squabble between

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Speaker 1: the left and the never Trump wing, which I would

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Speaker 1: from the, for the very far left in the never

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Speaker 1: Trump wing.

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Speaker 3: And I, and also just mainstream Democrats. Right. And I, Right.

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Speaker 1: And by the way, I don't think that an inter-party

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Speaker 1: squabble is necessary because if you're a big tent, you're

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Speaker 1: going to have that.

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Speaker 3: Correct.

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Speaker 1: Right. But an inter-party squabble is, is I think much better, right?

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Speaker 1: You don't want to have a big tent where everybody's

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Speaker 1: in lockstep, but an inter-party squabble, I think is much,

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Speaker 1: much better than having Nazis take over your party, which

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Speaker 1: is what.

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Speaker 3: We're seeing on the right. Yeah, no, I agree with that.

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Speaker 3: And I'm, I'm, you know, I've, glad now to belong

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Speaker 3: to a political party that has different factions and has

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Speaker 3: disagreements and has debates. But what I don't like right

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Speaker 3: now that's going on is that we should be able

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Speaker 3: to agree that these people over there are worse and

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Speaker 3: we should be able to unite to fight that person.

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Speaker 3: I mean, you can see it with, you know, there

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Speaker 3: are never Trumpers and there are mainstream Democrats who supported

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Speaker 3: What was their name? The one with the funny accent

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Speaker 3: in Michigan.

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Speaker 1: But I want to say one thing, which I do

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Speaker 1: think we're seeing... Haley Stevens.

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Speaker 3: Haley Stevens, yeah.

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Speaker 1: But we're seeing, Haley Stevens has been one of the

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Speaker 1: great campaign surrogates to Dr.

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Speaker 3: El-Saeed.

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Speaker 1: Exactly.

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Speaker 3: And so it's a great example.

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Speaker 2: And I maxed out to Dr.

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Speaker 3: El-Saeed just the other day. I mean, you know, he's

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Speaker 3: grown on me. And it's like, I may not agree

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Speaker 3: with him on everything, but I, you know, he's going

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Speaker 3: to fight Trump with everything he's got. And that's what

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Speaker 3: I want.

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Speaker 1: And he is a very, and what I've been struck

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Speaker 1: by is, There have been these very good debates between

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Speaker 1: him and Mike Rogers, Florida's own Mike Rogers, where we

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Speaker 1: do see a lot of really good, smart pushback. The

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Speaker 1: thing that I've been really struck by with him, and

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Speaker 1: we've seen this with some of the other candidates, and

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Speaker 1: I thought that in Maine, Troy Jackson has done a

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Speaker 1: pretty good job of this too, which is just focusing

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Speaker 1: on money in your pocket. you know, a public option

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Speaker 1: for health care or Medicare for all or something like that,

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Speaker 1: you know, a sort of solution based, you know, you

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Speaker 1: push back on these Republicans, but then you get right

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Speaker 1: to a solution.

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Speaker 3: Yeah. Yeah. And I also like his I like Jackson's

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Speaker 3: line about rock salt.

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Speaker 1: Yes, you can't eat rock salt.

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Speaker 3: You can't eat rock salt. These candidates are great. It's

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Speaker 3: just I'm just amazed at some of the discussion I

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Speaker 3: see online. And of course, online is not a real

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Speaker 3: sample of what's going on in the real world. Where

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Speaker 3: people are more focused on settling scores within the tent

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Speaker 3: than they are uniting to fire outside the tent. Yeah.

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Speaker 1: I mean, I do want to just add one thing there, though,

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Speaker 1: which is in some ways, Elon Musk has done a

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Speaker 1: great favor for Democrats because X is such a cesspool

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Speaker 1: of bots. Yeah. And there's so little like actual natural

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Speaker 1: engagement on the platform that it's interesting to see how little,

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Speaker 1: you know, he's really, it used to be, and I

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Speaker 1: bemoan this because I really appreciate it, but used to be,

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Speaker 1: you could go to X and see what everybody was reading.

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Speaker 1: You could see, you know, if their story, if a

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Speaker 1: piece of writing was shared, you could see who had

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Speaker 1: shared it and what they had said about it. So

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Speaker 1: you could really get a sense of where public thinkers were.

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Speaker 1: And it's no longer that.

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Speaker 3: Oh, I agree with that.

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Speaker 1: Because this weekend, this Musk film came out. It's about

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Speaker 1: to come out, this Alex Gibney movie, which is four

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Speaker 1: hours long. And it talks about what he did to Twitter.

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Speaker 1: He actually does the same exact thing and uses the

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Speaker 1: same emails to the federal government.

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Speaker 3: Yep.

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Speaker 2: Yep.

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Speaker 3: No. And there's actually, my fiancée has brought this book

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Speaker 3: that she started reading on the plane over. We're in

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Speaker 3: Europe right now.

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Speaker 1: Your fiance, you say?

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Speaker 2: Yeah.

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Speaker 3: So it's the Michael Lewis book.

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Speaker 1: Yeah.

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Speaker 3: Basically on Doge. So it's absolutely fabulous. And, you know, anyway.

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Speaker 1: And Michael Lewis, who is very smart and who's been

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Speaker 1: on this podcast and who has written this whole book

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Speaker 1: about what the federal government does and what Doge, the

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Speaker 1: kind of carnage that Doge wrought.

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Speaker 3: Yeah.

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Speaker 2: Yeah.

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Speaker 3: Anyway.

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Speaker 1: George Conway, what races are you looking at right now?

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Speaker 3: I don't think I'm looking at anything different than anybody else.

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Speaker 3: I mean, I'm fascinated with Tallarico. I hope he recovers

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Speaker 3: fully from the flu and gets back out on the trail.

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Speaker 3: I am fascinated with Michigan.

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Speaker 1: Yeah.

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Speaker 3: I watched some of the clips of that debate this morning.

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Speaker 1: Kansas.

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Speaker 3: And Kansas.

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Speaker 1: Adam Hamilton in Kansas, who just got almost all of

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Speaker 1: the Republicans. Republican governors of Kansas to endorse him with

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Speaker 1: the exception of Sam Brownback.

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Speaker 3: Yeah, no, it's incredible. It's incredible. And, um, you know, he's,

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Speaker 3: he's a very, you know, he's, he's the exactly kind

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Speaker 3: of Democrat that should be able to succeed out in

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Speaker 3: the Midwest and, um, need more of him. He's a

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Speaker 3: good man, a pastor. No, so nobody's going to, you know,

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Speaker 3: nobody's going to trash him for being some kind of

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Speaker 3: irreligious Easterner or something like that. Um, He's great. Ossoff

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Speaker 3: was on fire the other day. I love him. He's

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Speaker 3: going to, he's going to, not even a question. And

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Speaker 3: the other thing I saw is that the Republicans are

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Speaker 3: moving money into South Carolina. They're worried about Darlene Graham

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Speaker 3: and my grandnanny Andrews there, who I maxed out to

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Speaker 3: like a year ago. She's getting some traction there. I

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Speaker 3: hope and pray that would be so glorious.

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Speaker 2: Yeah.

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Speaker 1: And And the lesson there is if you run good

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Speaker 1: candidates who are hyperlocal and come from the place as

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Speaker 1: opposed to live in Florida, which a lot of these

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Speaker 1: Republicans do.

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Speaker 3: Two Republicans in Florida. That's who I heard it was.

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Speaker 1: They all live in Florida.

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Speaker 2: They all live in Florida.

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Speaker 1: George Conway.

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Speaker 3: All right.

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Speaker 1: Will you come back?

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Speaker 3: I will always come back.

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Speaker 4: Well, it's time for the headlines. And last night we

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Speaker 4: saw the people who have to defend the indefensible, the

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Speaker 4: senators who are trying to win against Dr. Abdul El-Said

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Speaker 4: and John Ossoff, just have some of the worst debate

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Speaker 4: showings I've ever seen in my entire life.

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Speaker 1: My favorite. I mean, first of all, Mike Collins is

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Speaker 1: a really terrible candidate, but John Ossoff. I mean, it's

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Speaker 1: like Ossoff is like a good candidate, but also.

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Speaker 3: And a great debater.

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Speaker 1: And a great debater. But he's also running against someone

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Speaker 1: who's just like, you know, every story is like this

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Speaker 1: guy who works for Mike Collins has a swastika on

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Speaker 1: his Facebook page.

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Speaker 3: I mean, like every story. His line was amazing.

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Speaker 4: He said you were employing half the Third Reich in

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Speaker 4: your office.

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Speaker 2: Is that what he said?

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Speaker 4: Yeah, he really said that. It was very funny.

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Speaker 1: Yeah, I missed that. But he did say if John

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Speaker 1: Lewis were marching today from Selma to Montgomery, Mike Collins

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Speaker 1: would be grabbing a billy club.

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Speaker 3: So good.

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Speaker 1: So look, this is the candidate quality problem. Like if

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Speaker 1: you're going to run against someone who is alt-right adjacent,

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Speaker 1: who is Nazi curious, you're going to have lines like that.

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Speaker 1: And so Mike Collins, pretty amazing candidate in Georgia. In Michigan,

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Speaker 1: we have Florida's own Mike Rogers, who lives in Florida.

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Speaker 1: The thing I like about Mike Rogers is that he

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Speaker 1: always looks so angry.

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Speaker 2: Yeah.

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Speaker 4: And you could just see Abdul making him insane. And

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Speaker 4: I think one of the things that the two Mikes

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Speaker 4: had in common is that both got tied to the

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Speaker 4: election denial and both got tied to, like, their fealty

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Speaker 4: to Trump. They literally were both, like, speechless when, like,

439
00:22:21,140 --> 00:22:23,330
Speaker 4: they were put in the corner of, like, You know,

440
00:22:23,710 --> 00:22:25,550
Speaker 4: your boy does all these things.

441
00:22:25,950 --> 00:22:28,810
Speaker 1: But this is the problem for all these candidates is

442
00:22:28,850 --> 00:22:31,820
Speaker 1: like he Trump is not a normal president. So like

443
00:22:31,890 --> 00:22:35,040
Speaker 1: a Biden will say run against me. A Clinton will

444
00:22:35,100 --> 00:22:39,180
Speaker 1: say you're on your own. George W. Bush will say

445
00:22:39,200 --> 00:22:41,500
Speaker 1: you got to do what you got to do. And

446
00:22:41,980 --> 00:22:48,230
Speaker 1: Donald Trump will say. you know, elevate mean stuff about

447
00:22:48,290 --> 00:22:52,670
Speaker 1: Representative Salazar because she said that he's gone too far

448
00:22:52,690 --> 00:22:56,850
Speaker 1: in immigration because she knows that he's losing Latino voters

449
00:22:57,250 --> 00:23:00,830
Speaker 1: and she needs them to win in her very Latino district.

450
00:23:00,970 --> 00:23:03,109
Speaker 1: And that is the problem for a lot of these Republicans.

451
00:23:03,550 --> 00:23:08,550
Speaker 1: So Mike Rogers needs to convince Michigan that he's like

452
00:23:08,590 --> 00:23:11,209
Speaker 1: a real Senate vote and not just a rubber stamp

453
00:23:11,250 --> 00:23:13,830
Speaker 1: for Trump. But we've seen for the last two years,

454
00:23:13,990 --> 00:23:17,379
Speaker 1: all Republicans have done is rubber stamp for Trump. So

455
00:23:17,400 --> 00:23:19,920
Speaker 1: there's no one to even point to. There's no precedent

456
00:23:20,040 --> 00:23:22,580
Speaker 1: for the last two years of a Republican trying to

457
00:23:22,619 --> 00:23:26,920
Speaker 1: hold Trump accountable with the very, very slim sort of

458
00:23:27,920 --> 00:23:31,280
Speaker 1: group that are largely people who are not returning to

459
00:23:31,820 --> 00:23:36,060
Speaker 1: to the Senate, people like Tom Tallis, or people who've

460
00:23:36,100 --> 00:23:39,950
Speaker 1: lost their seat, like John Cornyn. And even those guys,

461
00:23:39,970 --> 00:23:48,040
Speaker 1: Senator Cassidy, even those people have been pretty muted. So

462
00:23:48,180 --> 00:23:51,200
Speaker 1: you really haven't seen Republicans run any kind of check

463
00:23:51,280 --> 00:23:56,520
Speaker 1: on Trump, despite him doing impossibly destructive and dangerous things.

464
00:23:56,640 --> 00:23:58,750
Speaker 1: And so there's no precedent for it. So people are

465
00:23:58,790 --> 00:24:00,929
Speaker 1: just don't believe that these Republicans will do it. And

466
00:24:00,970 --> 00:24:02,070
Speaker 1: that's good because they won't.

467
00:24:02,790 --> 00:24:02,930
Speaker 2: Yep.

468
00:24:03,109 --> 00:24:05,970
Speaker 4: Once they get elected, they are afraid of the mean

469
00:24:06,050 --> 00:24:08,889
Speaker 4: truth social posts. And we saw this last night also

470
00:24:09,109 --> 00:24:11,790
Speaker 4: with at a candidate for him. The man with the

471
00:24:11,830 --> 00:24:16,060
Speaker 4: worst beard dye in America, Mike Waller, literally almost walked

472
00:24:16,260 --> 00:24:17,740
Speaker 4: out of the debate. It had to be told to

473
00:24:17,800 --> 00:24:21,120
Speaker 4: sit down because he threw a baby tantrum about his

474
00:24:21,180 --> 00:24:21,720
Speaker 4: ties to Trump.

475
00:24:22,040 --> 00:24:24,830
Speaker 1: So that was an amazing moment because he was like,

476
00:24:24,910 --> 00:24:28,730
Speaker 1: because I've worked on this salt deduction, you are now

477
00:24:28,830 --> 00:24:29,530
Speaker 1: getting debt.

478
00:24:29,609 --> 00:24:30,790
Speaker 4: Your favorite issue.

479
00:24:31,230 --> 00:24:34,760
Speaker 1: Right. Salt, which everyone is very excited. Concerned event at

480
00:24:34,780 --> 00:24:40,210
Speaker 1: Blue State's, the state and local tax deduction. And she says,

481
00:24:40,270 --> 00:24:43,790
Speaker 1: now you're going to get this. And Kate Connelly. says

482
00:24:43,850 --> 00:24:46,810
Speaker 1: you could have done that if you hadn't done anything.

483
00:24:47,210 --> 00:24:49,950
Speaker 1: And he gets so mad. And like, this is a

484
00:24:49,990 --> 00:24:53,609
Speaker 1: man who posed with a cake with Trump's face on it.

485
00:24:53,850 --> 00:24:54,669
Speaker 1: This is a man.

486
00:24:54,690 --> 00:24:58,970
Speaker 4: We're not doing blackface at Michael Jackson's trial and harassing people.

487
00:24:59,430 --> 00:25:03,709
Speaker 1: We know too much about this candidate because we've, you know,

488
00:25:03,770 --> 00:25:07,210
Speaker 1: and I've had to meet him in person. And, but

489
00:25:07,280 --> 00:25:09,980
Speaker 1: he is, you know, the, point here is that there

490
00:25:10,040 --> 00:25:14,260
Speaker 1: is no lane for an independent Republican. If you're a Republican,

491
00:25:14,800 --> 00:25:18,450
Speaker 1: you are a Trump rubber stamp. And so we're seeing

492
00:25:18,530 --> 00:25:21,850
Speaker 1: these voters have real problems here. I did think it

493
00:25:21,869 --> 00:25:25,410
Speaker 1: was interesting. This is something that I think is really upsetting,

494
00:25:25,750 --> 00:25:29,040
Speaker 1: in my mind, is we're seeing so much.

495
00:25:30,750 --> 00:25:34,010
Speaker 1: Push back to Dr. Al-Saeed, not about how he'd vote,

496
00:25:34,510 --> 00:25:39,070
Speaker 1: not about his policy, but about him being Muslim. And

497
00:25:39,130 --> 00:25:42,230
Speaker 1: that stuff really upsets me. And even like on CNN,

498
00:25:42,310 --> 00:25:47,119
Speaker 1: it feels like CNN is elevating the anti-Muslim rhetoric the

499
00:25:47,260 --> 00:25:50,020
Speaker 1: same way as a lot of these right wing outlets.

500
00:25:50,140 --> 00:25:53,980
Speaker 1: And it's really disappointing to me because like this is racism,

501
00:25:54,100 --> 00:25:58,550
Speaker 1: like not, you know, judging someone for how they pray

502
00:25:58,570 --> 00:26:02,669
Speaker 1: is racism. Just so disappointing on the part of CNN

503
00:26:02,869 --> 00:26:05,190
Speaker 1: and of other of these other outlets that seem to

504
00:26:05,250 --> 00:26:06,410
Speaker 1: really be leaning into that.

505
00:26:06,710 --> 00:26:11,080
Speaker 4: So, Molly, the DOJ is weighing perjury charges against Cassidy Hutchinson,

506
00:26:11,100 --> 00:26:14,160
Speaker 4: who you may remember from her testimony during the January

507
00:26:14,380 --> 00:26:14,859
Speaker 4: 6th hearings.

508
00:26:15,260 --> 00:26:18,919
Speaker 1: I mean, this is like, this is this Trump trying

509
00:26:19,000 --> 00:26:22,500
Speaker 1: to get some kind of revenge for January 6th and

510
00:26:22,580 --> 00:26:27,979
Speaker 1: for the prosecution stuff. You know, again, this is so

511
00:26:28,380 --> 00:26:33,790
Speaker 1: out of the mainstream. It's meant to scare. She is

512
00:26:33,830 --> 00:26:37,510
Speaker 1: really young and it seems like, you know, it's just

513
00:26:37,590 --> 00:26:40,250
Speaker 1: a stupid waste of taxpayer dollars to try to make

514
00:26:40,750 --> 00:26:41,909
Speaker 1: Donald Trump happy.

515
00:26:41,930 --> 00:26:42,530
Speaker 2: Yeah.

516
00:26:42,790 --> 00:26:45,040
Speaker 4: And, uh, If it goes the way the rest of

517
00:26:45,080 --> 00:26:46,680
Speaker 4: them have gone, it's not going to go so well.

518
00:26:46,960 --> 00:26:47,200
Speaker 3: Yeah.

519
00:26:47,340 --> 00:26:50,160
Speaker 1: I mean, it's just an insane, I mean, it's just

520
00:26:50,180 --> 00:26:53,110
Speaker 1: an insane way to run a country. Like, you know,

521
00:26:53,270 --> 00:26:56,490
Speaker 1: she's not a danger to anyone. This is all about revenge.

522
00:26:56,850 --> 00:27:01,670
Speaker 4: So while we were not taping yesterday, the psychotic person

523
00:27:01,730 --> 00:27:05,170
Speaker 4: known as Pete Hegseth decided that we're going to televise

524
00:27:05,410 --> 00:27:11,300
Speaker 4: the shooting of the Fort Hood shooter. And it's not

525
00:27:11,340 --> 00:27:15,639
Speaker 4: going over so well in Republican land even. And, you know,

526
00:27:15,720 --> 00:27:18,679
Speaker 4: his competitor for the next presidential nominee, J.D. Vance, is

527
00:27:18,720 --> 00:27:19,970
Speaker 4: even saying he won't watch it.

528
00:27:20,230 --> 00:27:20,610
Speaker 3: Yeah.

529
00:27:20,890 --> 00:27:24,189
Speaker 1: I mean, good for, I'm not going to hand it

530
00:27:24,210 --> 00:27:25,470
Speaker 1: to J.D. Vance here. Really?

531
00:27:25,530 --> 00:27:27,250
Speaker 3: I'm not either.

532
00:27:27,690 --> 00:27:30,730
Speaker 1: But he did question why it would actually be public,

533
00:27:30,780 --> 00:27:35,780
Speaker 1: which I also would like to know. America's had, first

534
00:27:35,800 --> 00:27:38,919
Speaker 1: of all, the idea that we do executions is so insane.

535
00:27:39,080 --> 00:27:41,840
Speaker 1: Second of all, I don't think that people should be

536
00:27:41,880 --> 00:27:44,580
Speaker 1: able to watch it. And third of all, I'm not

537
00:27:44,640 --> 00:27:48,080
Speaker 1: even sure why we're even on this. It's the first

538
00:27:48,140 --> 00:27:51,340
Speaker 1: public execution in 90 years, and it's the first military

539
00:27:51,480 --> 00:27:56,570
Speaker 1: one since 1961. It makes no sense. Tom Tillis, who's

540
00:27:56,590 --> 00:28:02,290
Speaker 1: suddenly gotten very brave, said he condemned it. He doesn't

541
00:28:02,330 --> 00:28:05,910
Speaker 1: have a job anymore. But thank you for condemning what

542
00:28:05,990 --> 00:28:09,380
Speaker 1: is the bare minimum, Tom. But yeah, I mean, like

543
00:28:09,410 --> 00:28:11,960
Speaker 1: this is, you know, what are they trying to do here?

544
00:28:12,040 --> 00:28:12,220
Speaker 4: Right.

545
00:28:12,260 --> 00:28:16,400
Speaker 1: Like what's the underlying situation? They were trying to scare people.

546
00:28:16,660 --> 00:28:19,060
Speaker 1: They want people to think they have power. They want

547
00:28:19,080 --> 00:28:22,080
Speaker 1: people think that the power of the state can kill people.

548
00:28:22,420 --> 00:28:27,570
Speaker 1: It's stupid. It's scary. It's pretty bleak. I don't know

549
00:28:27,590 --> 00:28:30,450
Speaker 1: that this does anything for anyone. I mean, like that's

550
00:28:30,670 --> 00:28:33,050
Speaker 1: all of this stuff. It's like it's a huge waste

551
00:28:33,090 --> 00:28:38,030
Speaker 1: of money. It's ridiculous. And also, what does it do

552
00:28:38,070 --> 00:28:38,670
Speaker 1: for anyone?

553
00:28:38,930 --> 00:28:40,010
Speaker 2: Well, Molly, as a.

554
00:28:40,010 --> 00:28:42,610
Speaker 4: Producer, I have to say the producers at Trump TV

555
00:28:42,730 --> 00:28:44,850
Speaker 4: don't have a lot to put on Trump TV. So

556
00:28:44,910 --> 00:28:48,890
Speaker 4: this gives them programming. So think of the producers for once,

557
00:28:48,930 --> 00:28:49,280
Speaker 4: will you?

558
00:28:49,640 --> 00:28:49,920
Speaker 3: Yes.

559
00:28:50,840 --> 00:28:52,000
Speaker 2: Something for no one.

560
00:28:52,460 --> 00:28:57,580
Speaker 4: So the DHS is getting a lot of blowback after

561
00:28:57,660 --> 00:29:03,420
Speaker 4: coming after congressional candidate Janelle Stelzen. This is very strange.

562
00:29:03,860 --> 00:29:06,620
Speaker 1: I mean, this is like, is it incompetence? Is it

563
00:29:06,680 --> 00:29:10,100
Speaker 1: just somebody in the office? So Stenson is running against

564
00:29:10,120 --> 00:29:14,420
Speaker 1: Republican Scott Perry in Pennsylvania's 10th district. They have spent

565
00:29:14,880 --> 00:29:20,560
Speaker 1: more than $ 26 million on this race. The DHS published

566
00:29:20,640 --> 00:29:24,270
Speaker 1: a press release on Wednesday announcing they were arresting an

567
00:29:24,290 --> 00:29:28,830
Speaker 1: illegal alien from Nigeria who exposed themselves in public while

568
00:29:28,870 --> 00:29:33,340
Speaker 1: working for the campaign. congressional campaign. Here's the thing. There

569
00:29:33,760 --> 00:29:38,110
Speaker 1: is no record of this guy working for the Stelson campaign.

570
00:29:38,710 --> 00:29:44,740
Speaker 1: Nobody named that. was paid by Stelson. As of September 30th,

571
00:29:44,860 --> 00:29:49,610
Speaker 1: according to disbursements, the campaign showed Axios, a search of

572
00:29:49,650 --> 00:29:53,550
Speaker 1: its volunteer database with no results for the name, in

573
00:29:53,610 --> 00:29:57,110
Speaker 1: a cease and desist letter, the campaign said, that this

574
00:29:57,170 --> 00:30:00,690
Speaker 1: individual had never been employed by the vendors of any campaign.

575
00:30:00,710 --> 00:30:03,590
Speaker 1: So there's a fair amount of evidence to show that

576
00:30:03,690 --> 00:30:08,050
Speaker 1: none of this happened. DHS cited a New Jersey-based news

577
00:30:08,210 --> 00:30:13,180
Speaker 1: outlet called Shore News Network as a source for the claims.

578
00:30:14,000 --> 00:30:20,180
Speaker 1: The outlet cited a social media post from conservative activist

579
00:30:20,780 --> 00:30:27,210
Speaker 1: and long-haired aficionado Scott Pressler. who I think we can

580
00:30:27,430 --> 00:30:30,350
Speaker 1: all assume made this up.

581
00:30:30,570 --> 00:30:33,150
Speaker 4: No, not Scott Pressler making things up.

582
00:30:33,190 --> 00:30:39,470
Speaker 1: Never. He did tweet it, so it probably happened. But

583
00:30:39,610 --> 00:30:43,510
Speaker 1: I'm going to go with this is totally made up.

584
00:30:43,810 --> 00:30:45,250
Speaker 4: Yeah, you know what's not made up, though, is one

585
00:30:45,270 --> 00:30:52,130
Speaker 4: of Mike Lawler's campaign supporters stealing campaign signs for his

586
00:30:52,170 --> 00:30:54,090
Speaker 4: opponent and then getting caught because he was too dumb

587
00:30:54,110 --> 00:30:55,590
Speaker 4: to realize they had air tags on them.

588
00:30:55,940 --> 00:30:57,880
Speaker 1: Don't be mean to Michael. No, I'm just kidding.

589
00:30:57,940 --> 00:30:58,290
Speaker 2: Do it.

590
00:31:01,080 --> 00:31:06,580
Speaker 1: Carolyn Ryan is the co-managing editor of The New York Times. Welcome, welcome,

591
00:31:06,640 --> 00:31:07,520
Speaker 1: Carolyn Ryan.

592
00:31:07,860 --> 00:31:10,300
Speaker 2: Thank you. It's so nice to see you.

593
00:31:10,700 --> 00:31:14,040
Speaker 1: It is the midterms. We're less than, I think, we're

594
00:31:14,540 --> 00:31:15,220
Speaker 1: less than a month.

595
00:31:15,260 --> 00:31:15,720
Speaker 2: Three weeks.

596
00:31:15,800 --> 00:31:18,240
Speaker 1: So I want you to talk about this phenomenon that

597
00:31:18,340 --> 00:31:21,800
Speaker 1: Charlie Cook of the Cook Political Report who is a

598
00:31:21,840 --> 00:31:25,630
Speaker 1: person that you only know if you really follow politics.

599
00:31:25,870 --> 00:31:28,210
Speaker 1: He's a pollster. He's very smart. He's been around for

600
00:31:28,230 --> 00:31:31,070
Speaker 1: a million years. He has this thing he said that

601
00:31:31,210 --> 00:31:36,200
Speaker 1: it is a blue wave-ish, but with a red undertow.

602
00:31:36,880 --> 00:31:39,340
Speaker 1: And I want to talk to you about the red

603
00:31:39,460 --> 00:31:44,380
Speaker 1: undertow because I'm not sure that I have really covered

604
00:31:44,810 --> 00:31:47,870
Speaker 1: a midterm that was more about a red undertale.

605
00:31:48,190 --> 00:31:50,430
Speaker 2: I have to say, I have never seen a midterm

606
00:31:50,550 --> 00:31:53,530
Speaker 2: quite like this. First of all, as you know, the

607
00:31:54,250 --> 00:31:58,010
Speaker 2: map has expanded in all these unexpected ways. Now you

608
00:31:58,050 --> 00:32:00,940
Speaker 2: have to understand, you know, the New York times for us,

609
00:32:01,520 --> 00:32:05,440
Speaker 2: elections are kind of our high Holy days. Right. And, uh,

610
00:32:05,480 --> 00:32:08,970
Speaker 2: we've been running through scenarios, uh, believe it or not, uh,

611
00:32:09,410 --> 00:32:13,810
Speaker 2: On September 23rd, we basically took 70 of our people

612
00:32:14,230 --> 00:32:17,370
Speaker 2: and we simulated a midterm election. So they were down

613
00:32:17,430 --> 00:32:22,340
Speaker 2: on the second floor scraping. We basically have relationships with

614
00:32:22,400 --> 00:32:25,570
Speaker 2: secretaries of state all over the country. But we basically

615
00:32:25,610 --> 00:32:27,730
Speaker 2: did a mock election. We didn't tell them, and I'm

616
00:32:27,750 --> 00:32:30,270
Speaker 2: not going to tell you who won, but we are

617
00:32:30,310 --> 00:32:33,590
Speaker 2: getting ready in so many different ways. And frankly, this

618
00:32:33,610 --> 00:32:37,190
Speaker 2: has been, you know, a more expansive election. I've had

619
00:32:37,590 --> 00:32:40,870
Speaker 2: five trips to Alaska. We've sent reporters out there. Alaska

620
00:32:41,210 --> 00:32:46,360
Speaker 2: is not usually this competitive. And to have Mary Peltola competing,

621
00:32:46,410 --> 00:32:49,220
Speaker 2: basically tied maybe a little bit ahead, that is a

622
00:32:49,320 --> 00:32:53,370
Speaker 2: very different scenario. And you've seen the places that now, Kansas,

623
00:32:53,410 --> 00:32:56,170
Speaker 2: we have a good story today. Democrats are putting money

624
00:32:56,210 --> 00:33:00,050
Speaker 2: into Kansas. That wasn't the case before. So, Molly, believe

625
00:33:00,070 --> 00:33:04,840
Speaker 2: it or not, we've already written this year over 1,700

626
00:33:04,840 --> 00:33:09,950
Speaker 2: articles about the midterms. Our readers are really engaged. And

627
00:33:10,310 --> 00:33:13,340
Speaker 2: the map is expanding. The polling has to expand to

628
00:33:13,390 --> 00:33:16,180
Speaker 2: reach that because people want to know what is going on.

629
00:33:16,540 --> 00:33:19,220
Speaker 1: So you guys have, and actually this gets me to

630
00:33:19,260 --> 00:33:22,500
Speaker 1: my next question because I realize you guys have a

631
00:33:22,680 --> 00:33:27,970
Speaker 1: huge data organization. Besides being a newspaper, there's like this

632
00:33:28,310 --> 00:33:30,950
Speaker 1: data situation. So I would love you to talk us

633
00:33:30,990 --> 00:33:34,050
Speaker 1: through because the reason you gamed out a midterm was

634
00:33:34,130 --> 00:33:37,030
Speaker 1: because you have a huge quantity of data, which it

635
00:33:37,070 --> 00:33:39,090
Speaker 1: sounds like you get some data.

636
00:33:38,820 --> 00:33:41,800
Speaker 2: From secretaries of state. It's kind of fascinating. I don't

637
00:33:41,840 --> 00:33:43,860
Speaker 2: want to geek out too much, but I'll tell you this.

638
00:33:43,900 --> 00:33:47,800
Speaker 1: You're here for geek. If people are listening, they're here

639
00:33:47,840 --> 00:33:48,520
Speaker 1: for the geekdom.

640
00:33:48,580 --> 00:33:52,200
Speaker 2: Once you said Charlie Cook, I'm like, I'm home. Yeah. No,

641
00:33:52,220 --> 00:33:57,370
Speaker 2: but like in Maine alone, you have 500 different communities

642
00:33:57,400 --> 00:34:00,690
Speaker 2: that are reporting election results. Our people have gone through

643
00:34:00,850 --> 00:34:04,950
Speaker 2: election after election. They know who to talk to in

644
00:34:05,090 --> 00:34:08,390
Speaker 2: each of these battleground states. They have relationships with people.

645
00:34:08,700 --> 00:34:11,540
Speaker 2: We're scraping the data, but we're also able to see

646
00:34:11,600 --> 00:34:14,020
Speaker 2: if something looks off. I mean, some of these Maine

647
00:34:14,060 --> 00:34:17,770
Speaker 2: officials are still like in pen and pencil, like handing

648
00:34:17,850 --> 00:34:23,540
Speaker 2: off the results. So with the AP, we are collecting statewide, countywide, citywide,

649
00:34:24,020 --> 00:34:27,620
Speaker 2: townwide and then precinct wide data. So for us, it's

650
00:34:27,660 --> 00:34:31,620
Speaker 2: a huge undertaking, but it's also a huge public service.

651
00:34:31,660 --> 00:34:34,810
Speaker 2: Like if you look at who are people paying attention

652
00:34:34,850 --> 00:34:39,130
Speaker 2: to on election night, whether they're Republican, Democrat, conservative, whatever,

653
00:34:39,450 --> 00:34:41,970
Speaker 2: it's the New York times. And it's because our maps

654
00:34:42,030 --> 00:34:45,089
Speaker 2: are the best and there's nothing like it. So we're

655
00:34:45,130 --> 00:34:48,310
Speaker 2: essentially modeling for each state, but because we want you,

656
00:34:48,710 --> 00:34:52,040
Speaker 2: let's say you come to Maine. And Troy Jackson, the Democrat,

657
00:34:52,100 --> 00:34:54,140
Speaker 2: is way ahead. We want to be able to say

658
00:34:54,180 --> 00:34:58,680
Speaker 2: to you, Molly, like these Republican areas haven't reported yet. Don't,

659
00:34:58,980 --> 00:35:01,380
Speaker 2: you know, don't believe that this is because part of

660
00:35:01,420 --> 00:35:04,060
Speaker 2: what happens with disinformation is people say, oh, I was

661
00:35:04,100 --> 00:35:07,390
Speaker 2: way ahead. And then suddenly something happened. We want you

662
00:35:07,410 --> 00:35:09,590
Speaker 2: to be more sophisticated. So for us, it's kind of

663
00:35:09,650 --> 00:35:12,250
Speaker 2: like a civic literacy effort as well.

664
00:35:13,290 --> 00:35:16,570
Speaker 1: But early voting in some places has already started.

665
00:35:16,590 --> 00:35:17,840
Speaker 2: It's getting under way.

666
00:35:18,430 --> 00:35:18,710
Speaker 3: Right.

667
00:35:18,730 --> 00:35:21,110
Speaker 1: So you're getting those numbers too, right?

668
00:35:21,550 --> 00:35:23,109
Speaker 2: Yeah. Let me walk you through that a little bit.

669
00:35:23,160 --> 00:35:27,580
Speaker 2: We were sort of skeptical about everybody's early voting trackers,

670
00:35:27,620 --> 00:35:31,460
Speaker 2: so we're starting one of our own. And what we're

671
00:35:31,500 --> 00:35:34,540
Speaker 2: basically going to do, because people are saying to me

672
00:35:34,620 --> 00:35:37,460
Speaker 2: just about every day, should I believe these polls? And

673
00:35:37,480 --> 00:35:40,860
Speaker 2: we're basically doing a state of the race every Monday,

674
00:35:41,000 --> 00:35:42,600
Speaker 2: and then at the end, it will be every day.

675
00:35:42,620 --> 00:35:45,350
Speaker 2: So we're going to tell you the early voting You know,

676
00:35:45,390 --> 00:35:47,640
Speaker 2: what are the trends? Where are those votes coming from?

677
00:35:47,660 --> 00:35:51,049
Speaker 2: We'll obviously tell you the polls. But also, as you know,

678
00:35:51,070 --> 00:35:55,090
Speaker 2: one of the big signals to pay attention to is money.

679
00:35:55,110 --> 00:35:58,800
Speaker 2: If Republicans are pulling their money out of one state

680
00:35:58,860 --> 00:36:01,239
Speaker 2: that says, you know, that they don't believe that they

681
00:36:01,280 --> 00:36:03,900
Speaker 2: can compete or the Democrats are likely to win. And

682
00:36:03,960 --> 00:36:06,960
Speaker 2: so we're trying to give you all these metrics because

683
00:36:07,040 --> 00:36:10,410
Speaker 2: people get a little bit obsessive about polls. We have

684
00:36:10,450 --> 00:36:12,810
Speaker 2: very good polls. We're very proud of them. We'll spend

685
00:36:12,850 --> 00:36:14,610
Speaker 2: a lot of money on them. I think they're the best.

686
00:36:14,950 --> 00:36:16,170
Speaker 2: But we want you to be able to put it

687
00:36:16,250 --> 00:36:18,570
Speaker 2: into context with all these different measurements.

688
00:36:19,100 --> 00:36:21,279
Speaker 1: And the money, one of the things at times I

689
00:36:21,320 --> 00:36:25,190
Speaker 1: think has done really well is this, like you have

690
00:36:25,230 --> 00:36:28,350
Speaker 1: like a money and technology beat from the sort of

691
00:36:28,410 --> 00:36:31,630
Speaker 1: tech oligarch crew who has started really getting involved and

692
00:36:31,650 --> 00:36:32,130
Speaker 1: giving money.

693
00:36:32,350 --> 00:36:34,310
Speaker 2: He is the best. I mean, we have Teddy Schleifer

694
00:36:34,330 --> 00:36:38,759
Speaker 2: who has Silicon Valley Wired. And as you know, like

695
00:36:38,820 --> 00:36:42,600
Speaker 2: the AI money, the moguls getting involved, I think we'll

696
00:36:42,640 --> 00:36:45,700
Speaker 2: see some activity late. And I feel like he is

697
00:36:45,800 --> 00:36:48,330
Speaker 2: able to attract money like nobody else in the business can.

698
00:36:48,820 --> 00:36:49,100
Speaker 3: Yeah.

699
00:36:49,640 --> 00:36:55,380
Speaker 1: So when you have a map that looks like this,

700
00:36:55,640 --> 00:36:57,969
Speaker 1: and I would love to talk about some of these

701
00:36:58,090 --> 00:37:01,430
Speaker 1: states because I think it's pretty interesting. We're talking about Alaska.

702
00:37:02,030 --> 00:37:07,390
Speaker 1: Alaska has this Democrat. Again, it's also ranked choice. So

703
00:37:07,430 --> 00:37:10,290
Speaker 1: that sort of changes the calculus a little bit, right?

704
00:37:10,650 --> 00:37:13,950
Speaker 2: Yeah. And you have two people with the same, almost

705
00:37:14,050 --> 00:37:16,950
Speaker 2: identical name, which is a little bizarre. Yes. And we've

706
00:37:17,390 --> 00:37:20,450
Speaker 2: written a little bit about that. But you have Mary Peltola,

707
00:37:20,590 --> 00:37:24,950
Speaker 2: who has run before. We've done some stories about some

708
00:37:24,989 --> 00:37:30,040
Speaker 2: of her staff turmoil. But she also has a resonant

709
00:37:30,080 --> 00:37:33,240
Speaker 2: political message, I think. And so she's able to compete

710
00:37:33,260 --> 00:37:36,459
Speaker 2: in that state the way Democrats haven't always been able to.

711
00:37:37,719 --> 00:37:40,299
Speaker 2: So I think we're going back. Go ahead. No, you go. Well,

712
00:37:40,400 --> 00:37:42,540
Speaker 2: I was just really struck that Donald Trump is going

713
00:37:42,580 --> 00:37:45,050
Speaker 2: to Alaska next. As you know, he doesn't like to

714
00:37:45,540 --> 00:37:48,160
Speaker 2: do a lot of rigorous travel. So that really tells

715
00:37:48,180 --> 00:37:50,100
Speaker 2: you something. He's going to be there this coming week.

716
00:37:50,760 --> 00:37:54,860
Speaker 1: I have to say the Mary Patola story about her,

717
00:37:55,430 --> 00:38:01,220
Speaker 1: her foul language and her mean text messages. I had one. I,

718
00:38:01,690 --> 00:38:06,180
Speaker 1: I really don't. it's interesting because Alaska is famous for having, uh,

719
00:38:07,200 --> 00:38:10,620
Speaker 1: this member of Congress who carried a knife and beat

720
00:38:10,660 --> 00:38:16,510
Speaker 1: people up and had all sorts of strange Don, uh, Don.

721
00:38:17,090 --> 00:38:19,530
Speaker 2: Alaskans are a different breed. I think it's fair to say.

722
00:38:19,670 --> 00:38:21,549
Speaker 2: And if you look at that poll, I think we

723
00:38:21,570 --> 00:38:23,930
Speaker 2: did our poll after a lot of that had come

724
00:38:24,090 --> 00:38:28,049
Speaker 2: out and, uh, her numbers are still strong. Uh, some

725
00:38:28,090 --> 00:38:31,330
Speaker 2: people argued that it even helped her, but, uh, I think, uh,

726
00:38:32,270 --> 00:38:36,609
Speaker 2: Alaskans are very used to combative personalities. It's a rough

727
00:38:36,670 --> 00:38:39,740
Speaker 2: and rugged life out there. And I think she has

728
00:38:39,800 --> 00:38:41,700
Speaker 2: relationships with a lot of voters already.

729
00:38:43,730 --> 00:38:46,930
Speaker 1: And I thought that she did very well in the debates.

730
00:38:48,489 --> 00:38:51,629
Speaker 1: And again, it's this red undertow question, right? Did she

731
00:38:51,670 --> 00:38:53,890
Speaker 1: do very well in the debates or was he just

732
00:38:53,930 --> 00:38:55,779
Speaker 1: completely unprepared?

733
00:38:56,040 --> 00:38:59,259
Speaker 2: Yeah, I mean, I think the red undertow theme that

734
00:38:59,300 --> 00:39:02,640
Speaker 2: you're getting at, and we'll have some more reporting on this,

735
00:39:02,739 --> 00:39:06,200
Speaker 2: is just looking at the voters who powered Trump's win

736
00:39:06,219 --> 00:39:10,529
Speaker 2: in 2024 and them either Trending toward the Democrats are

737
00:39:10,610 --> 00:39:13,110
Speaker 2: really trending toward not voting. Staying home, yeah. So if

738
00:39:13,130 --> 00:39:16,010
Speaker 2: you look at younger voters, if you look at Latino

739
00:39:16,050 --> 00:39:19,509
Speaker 2: voters in Texas, Texas is a big question mark. We

740
00:39:19,550 --> 00:39:22,969
Speaker 2: have six people on the ground now in Texas. And

741
00:39:23,630 --> 00:39:27,859
Speaker 2: today they are looking for James Tellerico, as I think

742
00:39:27,940 --> 00:39:30,660
Speaker 2: everybody is. I think he has said he has the flu.

743
00:39:31,600 --> 00:39:34,900
Speaker 2: But that race has been a real surprise. And Trump's

744
00:39:34,940 --> 00:39:38,340
Speaker 2: involvement has been, you know, at times a little uneven,

745
00:39:38,380 --> 00:39:40,939
Speaker 2: and it's not clear how that's going to help or hurt.

746
00:39:42,070 --> 00:39:45,830
Speaker 1: I wonder if you could talk about how hard it is.

747
00:39:46,170 --> 00:39:51,680
Speaker 1: You have to release news in a non-partisan fashion. And

748
00:39:51,700 --> 00:39:55,020
Speaker 1: so that means sometimes you're going to write pieces about

749
00:39:55,040 --> 00:39:59,569
Speaker 1: Mary Padilla because the story is there. And sometimes you're

750
00:39:59,590 --> 00:40:03,810
Speaker 1: going to write stories about Roger Marshall because the story

751
00:40:03,870 --> 00:40:07,870
Speaker 1: is there. So tell me about, we live in a

752
00:40:07,910 --> 00:40:13,299
Speaker 1: world now where people want their, not even reporters, people

753
00:40:13,340 --> 00:40:17,100
Speaker 1: want their pundits to be for them, to So how

754
00:40:17,280 --> 00:40:19,840
Speaker 1: is that hard for a place like the New York Times,

755
00:40:20,300 --> 00:40:23,960
Speaker 1: which focuses on a not, you know, certainly on the

756
00:40:24,020 --> 00:40:26,020
Speaker 1: news side, I mean, the opinion side is different. That's

757
00:40:26,060 --> 00:40:28,440
Speaker 1: where I am, which is totally different. But like on

758
00:40:28,460 --> 00:40:30,540
Speaker 1: the news side, how do you do that? Because you

759
00:40:30,580 --> 00:40:33,680
Speaker 1: really are swimming upstream in the current climate.

760
00:40:34,000 --> 00:40:36,319
Speaker 2: I mean, it's the most important thing that we do.

761
00:40:37,020 --> 00:40:41,940
Speaker 2: We just turned 175 and our commitment is to independent journalism.

762
00:40:42,410 --> 00:40:44,630
Speaker 2: I mean, you've seen just in the course of this year,

763
00:40:45,010 --> 00:40:48,290
Speaker 2: we wrote stories about Graham Plattner that were really important,

764
00:40:49,150 --> 00:40:52,689
Speaker 2: that really had a depth and an impact. And you've

765
00:40:52,730 --> 00:40:54,650
Speaker 2: seen it. I mean, people get mad at us. They

766
00:40:54,690 --> 00:40:57,430
Speaker 2: want us to be rooting for their candidates or their party.

767
00:40:57,770 --> 00:40:59,730
Speaker 2: But the New York Times does not do that. We

768
00:40:59,770 --> 00:41:02,870
Speaker 2: are not, you know our slogan, without fear or favor.

769
00:41:03,250 --> 00:41:07,080
Speaker 2: So we want to give you independent, confirmed facts. We

770
00:41:07,120 --> 00:41:09,120
Speaker 2: want to provide them to you in a way that

771
00:41:09,180 --> 00:41:12,430
Speaker 2: helps you make good decisions. But we're going to write

772
00:41:12,860 --> 00:41:16,890
Speaker 2: stories that you love and stories that you might not love.

773
00:41:17,250 --> 00:41:20,180
Speaker 2: But you will know our process. We'll be transparent about it.

774
00:41:20,890 --> 00:41:23,710
Speaker 2: And I think when you look around in our industry,

775
00:41:24,430 --> 00:41:27,490
Speaker 2: the Times and its mission of independence really stands apart.

776
00:41:27,969 --> 00:41:30,969
Speaker 2: So I'm thinking about all the big stories that have

777
00:41:31,010 --> 00:41:34,550
Speaker 2: broken during these midterms. And it's really been the Times.

778
00:41:34,610 --> 00:41:38,350
Speaker 2: And that means tough stories on Republicans, tough stories on Democrats.

779
00:41:39,730 --> 00:41:41,250
Speaker 1: One of the things that I think is good. And

780
00:41:41,390 --> 00:41:43,810
Speaker 1: I mean, I would, I'm going to push back as

781
00:41:43,890 --> 00:41:46,689
Speaker 1: much as I love you because like ProPublica is done.

782
00:41:46,770 --> 00:41:50,310
Speaker 1: I mean, that piece about Don Jr. 's wedding was amazing.

783
00:41:50,750 --> 00:41:52,550
Speaker 2: You know, Don Jr. 's wedding was a good story.

784
00:41:52,590 --> 00:41:54,880
Speaker 2: I guess I don't think of it as directly a

785
00:41:54,910 --> 00:41:57,680
Speaker 2: midterm story, but I'm not going to say they do do,

786
00:41:57,880 --> 00:41:59,120
Speaker 2: they do some really good work.

787
00:41:59,160 --> 00:42:01,419
Speaker 1: Yeah, they do. But you know, you guys, I mean,

788
00:42:01,500 --> 00:42:04,100
Speaker 1: you're number one for reporting. I mean, there's just no

789
00:42:04,180 --> 00:42:06,680
Speaker 1: one else. And, but the journal has done some really,

790
00:42:06,700 --> 00:42:08,980
Speaker 1: that Kimberly Guilfoyle, Inc.

791
00:42:09,870 --> 00:42:13,450
Speaker 2: That was an interesting story. It's fascinating.

792
00:42:14,890 --> 00:42:17,870
Speaker 1: And you've got to give props to Rupert Murdoch for

793
00:42:19,210 --> 00:42:22,549
Speaker 1: letting the Wall Street Journal do the reporting about, you know,

794
00:42:22,670 --> 00:42:26,910
Speaker 1: another arm of the organization, which is the Trump administration.

795
00:42:26,969 --> 00:42:32,040
Speaker 2: I'm just kidding. Sorry. I want to just revise my

796
00:42:32,100 --> 00:42:32,919
Speaker 2: answer a little bit.

797
00:42:33,300 --> 00:42:33,500
Speaker 1: Yeah.

798
00:42:33,960 --> 00:42:38,480
Speaker 2: Look, we stand for independent reporting, and we have the

799
00:42:38,520 --> 00:42:42,279
Speaker 2: most comprehensive reporting. coverage of any of these races. It

800
00:42:42,320 --> 00:42:45,090
Speaker 2: makes me glad, you know, even though I get jealous

801
00:42:45,330 --> 00:42:49,710
Speaker 2: if one of our competitors has a good story. But

802
00:42:49,750 --> 00:42:53,270
Speaker 2: we want independent journalism, and that's what we stand for.

803
00:42:53,450 --> 00:42:56,420
Speaker 2: And I'm really proud of what we've done, you know,

804
00:42:56,640 --> 00:42:59,640
Speaker 2: during these midterms. And I think readers, even when they

805
00:42:59,680 --> 00:43:03,279
Speaker 2: get upset about a particular story, they're really coming to

806
00:43:03,360 --> 00:43:05,759
Speaker 2: us for this midterms, which has turned out to be

807
00:43:05,780 --> 00:43:07,480
Speaker 2: a really dramatic cycle.

808
00:43:08,090 --> 00:43:12,130
Speaker 1: Yeah, so let's talk more about that dramatic cycle. Florida

809
00:43:12,530 --> 00:43:17,089
Speaker 1: is a fascinating state and fascinating at this moment. You

810
00:43:17,210 --> 00:43:21,759
Speaker 1: guys hired someone really good from Florida, Patricia Mazzetti.

811
00:43:21,880 --> 00:43:22,359
Speaker 2: Is that her name?

812
00:43:22,390 --> 00:43:23,160
Speaker 1: She's amazing.

813
00:43:23,480 --> 00:43:24,600
Speaker 2: Yeah, Patty Mazzetti.

814
00:43:25,280 --> 00:43:26,000
Speaker 1: Mazzetti, yeah.

815
00:43:26,020 --> 00:43:27,860
Speaker 2: She came out of the Miami Herald.

816
00:43:27,880 --> 00:43:30,600
Speaker 1: I used to read her at the Miami Herald.

817
00:43:30,860 --> 00:43:35,819
Speaker 2: Amazing. She's got a writer's colorful approach, but she's just

818
00:43:35,860 --> 00:43:38,660
Speaker 2: got the heart of a tiger when it comes to reporting.

819
00:43:39,140 --> 00:43:43,029
Speaker 2: And she is a wonderful reporter. And, you know, previously

820
00:43:43,150 --> 00:43:46,070
Speaker 2: she was Florida-based and she was really focused on the region,

821
00:43:46,350 --> 00:43:48,810
Speaker 2: but now she's going to roam. And I think we

822
00:43:48,850 --> 00:43:50,800
Speaker 2: don't even have to get into this, but you know,

823
00:43:50,820 --> 00:43:54,580
Speaker 2: as soon as the midterms happens, the next day, the

824
00:43:54,580 --> 00:43:59,000
Speaker 2: 2028 presidential cycle kind of kicks in. People start announcing,

825
00:43:59,060 --> 00:44:02,060
Speaker 2: people start making moves, and Patty Mazzei is going to

826
00:44:02,100 --> 00:44:03,770
Speaker 2: be really key to us on that.

827
00:44:04,450 --> 00:44:08,009
Speaker 1: And what's happening in Florida is pretty interesting because we're

828
00:44:08,030 --> 00:44:12,790
Speaker 1: seeing like this Latino voting pool is really a swing pool.

829
00:44:12,850 --> 00:44:15,430
Speaker 1: And it seems like in Texas, certainly with the candidacy

830
00:44:15,469 --> 00:44:19,790
Speaker 1: of Bobby Polito and some of these Democrats, they've managed

831
00:44:19,830 --> 00:44:22,230
Speaker 1: to appeal to some of those voters and really make

832
00:44:22,270 --> 00:44:24,930
Speaker 1: a connection. I mean, Polito is in like a very

833
00:44:24,969 --> 00:44:28,910
Speaker 1: Republican district and is right now polling ahead. But it

834
00:44:29,030 --> 00:44:31,870
Speaker 1: seems like Florida may be a more complicated story.

835
00:44:31,890 --> 00:44:34,370
Speaker 2: I think it's, yeah. I mean, for the Democrats, I

836
00:44:34,390 --> 00:44:37,700
Speaker 2: think it's more challenging. I think Texas has all these

837
00:44:37,820 --> 00:44:41,520
Speaker 2: elements and it has these kind of swing elements that

838
00:44:41,600 --> 00:44:45,080
Speaker 2: have been favorable to the Republicans. The Republicans also have

839
00:44:45,180 --> 00:44:51,010
Speaker 2: the unfortunate situation of the candidate quality question in Texas,

840
00:44:51,070 --> 00:44:55,109
Speaker 2: like on the Senate and even Republicans, a lot of them,

841
00:44:55,660 --> 00:45:00,350
Speaker 2: dislike Paxton, even if they align with him ideologically. So

842
00:45:00,390 --> 00:45:03,930
Speaker 2: that's very difficult. And people seem a little tired of Paxton.

843
00:45:05,630 --> 00:45:09,050
Speaker 2: And Trump has sort of been giving him these bizarre

844
00:45:09,110 --> 00:45:12,670
Speaker 2: kind of backhanded compliments, which seem to diminish him a

845
00:45:12,690 --> 00:45:15,590
Speaker 2: little bit more. So I thought that one of the

846
00:45:15,630 --> 00:45:20,009
Speaker 2: best stories we had was about Paxton's wife and the

847
00:45:20,050 --> 00:45:22,899
Speaker 2: kind of role that she was playing, even as she's

848
00:45:22,940 --> 00:45:25,680
Speaker 2: going through this you know, biblical divorce with him.

849
00:45:26,040 --> 00:45:31,040
Speaker 1: Yeah. The Angela Paxton saga is fascinating. And she actually,

850
00:45:31,060 --> 00:45:36,740
Speaker 1: the fact that that hostage video was actually her idea

851
00:45:37,180 --> 00:45:39,890
Speaker 1: because she spoke at a women's club, right?

852
00:45:39,950 --> 00:45:42,770
Speaker 2: Well, remember she is, uh, you know, she's a political

853
00:45:42,810 --> 00:45:46,380
Speaker 2: figure herself. She's part of the party, uh, And I,

854
00:45:47,430 --> 00:45:49,989
Speaker 2: you know, I wouldn't call it a hostage video. I mean,

855
00:45:50,010 --> 00:45:53,009
Speaker 2: I think she's a pretty savvy person and knows, you know,

856
00:45:53,050 --> 00:45:56,209
Speaker 2: what she wants to do. And she has stood by

857
00:45:56,250 --> 00:45:57,530
Speaker 2: him in a whole bunch of ways.

858
00:45:57,630 --> 00:46:00,730
Speaker 1: So she drove him away from the process server.

859
00:46:01,050 --> 00:46:01,350
Speaker 3: Right.

860
00:46:01,670 --> 00:46:04,750
Speaker 2: Yeah, that was part of that story. But I don't know,

861
00:46:04,930 --> 00:46:07,350
Speaker 2: you know, is that enough? That's going to be a

862
00:46:07,370 --> 00:46:10,870
Speaker 2: really interesting question. And a lot of people, you know,

863
00:46:10,890 --> 00:46:14,279
Speaker 2: they don't even want to talk about Texas just because

864
00:46:14,680 --> 00:46:17,940
Speaker 2: for so many years, cycles it has seemed to be

865
00:46:17,980 --> 00:46:19,900
Speaker 2: more competitive than it ends up being.

866
00:46:19,900 --> 00:46:23,319
Speaker 1: Yeah texas is uh super interesting too like you have

867
00:46:23,340 --> 00:46:26,600
Speaker 1: to wonder if greg abbott if that's like the curse

868
00:46:26,640 --> 00:46:29,010
Speaker 1: of the third term you know just because you can

869
00:46:29,050 --> 00:46:31,630
Speaker 1: run for a third term doesn't mean you should.

870
00:46:31,550 --> 00:46:34,310
Speaker 2: Yeah it'll be really interesting i'm really interested in his

871
00:46:34,370 --> 00:46:36,029
Speaker 2: numbers and i think we're going to get some more

872
00:46:36,050 --> 00:46:37,450
Speaker 2: on texas.

873
00:46:38,030 --> 00:46:40,759
Speaker 1: Um How do you guys poll?

874
00:46:41,180 --> 00:46:44,020
Speaker 2: So I think we have right now what Nate Silver

875
00:46:44,080 --> 00:46:47,480
Speaker 2: has called the best poll. And what we did, we

876
00:46:47,900 --> 00:46:50,820
Speaker 2: started out thinking that we had a universe of competitive

877
00:46:50,890 --> 00:46:56,210
Speaker 2: states that was smaller. So we've done national polls. But frankly,

878
00:46:57,210 --> 00:46:59,330
Speaker 2: we've had to spend more money than we expected just

879
00:46:59,530 --> 00:47:03,549
Speaker 2: because so many more states are competitive. Right. We spend

880
00:47:03,590 --> 00:47:05,850
Speaker 2: a lot of money on this and we go deeper.

881
00:47:05,870 --> 00:47:09,890
Speaker 2: We get bigger sample sizes. We try to have subgroups

882
00:47:09,930 --> 00:47:12,680
Speaker 2: that are worth looking at, whether that's Latino voters or

883
00:47:12,739 --> 00:47:16,520
Speaker 2: young voters. And we spend a lot of time on

884
00:47:16,600 --> 00:47:21,480
Speaker 2: it because non-response rates and people just turning off their

885
00:47:21,520 --> 00:47:24,680
Speaker 2: phones or turning away from polling, that is a real phenomenon.

886
00:47:24,980 --> 00:47:27,220
Speaker 2: So you have to work and make hundreds of calls

887
00:47:27,460 --> 00:47:29,779
Speaker 2: just to get some responses. And then you have to

888
00:47:29,820 --> 00:47:34,200
Speaker 2: really test it. Is there a bias toward who actually

889
00:47:34,219 --> 00:47:38,980
Speaker 2: responds to polls? Do they have an ideological tilt? But

890
00:47:39,020 --> 00:47:41,219
Speaker 2: the best person I've talked to, I know you know

891
00:47:41,540 --> 00:47:44,360
Speaker 2: Nate Cohn, who's done a bunch of explainers about our polls.

892
00:47:44,890 --> 00:47:47,049
Speaker 2: And I think what we're going to do just heading

893
00:47:47,180 --> 00:47:51,649
Speaker 2: into the election is just have him try to walk

894
00:47:51,710 --> 00:47:56,670
Speaker 2: people through the process and what kind of belief to

895
00:47:56,710 --> 00:47:59,390
Speaker 2: put in these polls, how to check them, what kind

896
00:47:59,430 --> 00:48:01,879
Speaker 2: of trends to look at. And then we started our

897
00:48:01,960 --> 00:48:04,640
Speaker 2: own polling tracker where we sort of point you toward

898
00:48:04,660 --> 00:48:07,200
Speaker 2: the more higher quality, high quality polls.

899
00:48:07,820 --> 00:48:10,370
Speaker 1: One of the anxieties I think that a lot of

900
00:48:10,450 --> 00:48:14,730
Speaker 1: people have, including myself, is that there's an undersampling of

901
00:48:14,850 --> 00:48:20,359
Speaker 1: rural voters. How do you account for that?

902
00:48:20,760 --> 00:48:23,010
Speaker 2: Well, I mean, you have to make more calls. I mean, we,

903
00:48:23,530 --> 00:48:27,650
Speaker 2: we did an experiment actually to test this, uh, uh,

904
00:48:27,770 --> 00:48:30,370
Speaker 2: in Wisconsin during one of the off cycles. And we

905
00:48:30,410 --> 00:48:33,000
Speaker 2: tried a whole bunch of different methods to get people,

906
00:48:33,380 --> 00:48:38,400
Speaker 2: including mailing them letters, uh, financial incentives? Would we get

907
00:48:38,440 --> 00:48:41,020
Speaker 2: a different makeup? Would you get a different composition? Would

908
00:48:41,040 --> 00:48:43,580
Speaker 2: you have more rural people? Would you have more people

909
00:48:44,140 --> 00:48:48,120
Speaker 2: with high school degrees respond? To tell you the truth,

910
00:48:48,180 --> 00:48:52,180
Speaker 2: there was not a significant difference in the actual composition

911
00:48:52,300 --> 00:48:55,120
Speaker 2: of the electorate you got through our traditional method and

912
00:48:55,140 --> 00:48:59,430
Speaker 2: that method. But we're always open to, you know, new efforts. And,

913
00:48:59,870 --> 00:49:01,819
Speaker 2: you know, if they if If there was a way

914
00:49:01,860 --> 00:49:03,700
Speaker 2: to knock on doors and that was going to get

915
00:49:03,739 --> 00:49:07,060
Speaker 2: us a better result, we would do it. But right now,

916
00:49:07,140 --> 00:49:10,739
Speaker 2: I think we have the best method, the best call centers. And,

917
00:49:11,280 --> 00:49:14,450
Speaker 2: you know, polls are imperfect measurements, but they are the

918
00:49:14,630 --> 00:49:17,570
Speaker 2: best measurement we have right now. So we're going to

919
00:49:17,610 --> 00:49:19,710
Speaker 2: try to contextualize them for a reason.

920
00:49:20,540 --> 00:49:22,279
Speaker 1: Thank you, Carolyn Ryan.

921
00:49:22,560 --> 00:49:25,170
Speaker 2: Thank you. This is terrific. I hope to see you soon.

922
00:49:26,560 --> 00:49:30,299
Speaker 1: Timothy Snyder is a professor at University of Toronto and

923
00:49:30,340 --> 00:49:35,200
Speaker 1: the author of the book On Freedom. Welcome, welcome, Timothy.

924
00:49:35,580 --> 00:49:36,100
Speaker 3: Great to see you.

925
00:49:36,280 --> 00:49:40,880
Speaker 1: We have to first talk about where you think America

926
00:49:40,960 --> 00:49:41,520
Speaker 1: is right now.

927
00:49:42,380 --> 00:49:45,340
Speaker 5: I mean, I think there are cross currents. There's a

928
00:49:45,410 --> 00:49:46,569
Speaker 5: lot of good reason for hope.

929
00:49:47,260 --> 00:49:50,149
Speaker 6: I think the mass protests are very important. I think

930
00:49:50,190 --> 00:49:54,510
Speaker 6: the example of mobilizing around deportation in Minnesota and elsewhere

931
00:49:54,570 --> 00:49:57,690
Speaker 6: is really important. I think grassroots efforts to protect the

932
00:49:57,730 --> 00:50:02,360
Speaker 6: vote are really important. And then I think Trump is

933
00:50:02,400 --> 00:50:07,200
Speaker 6: palpably weak. And I think that's like, tactically, that's something

934
00:50:07,219 --> 00:50:08,719
Speaker 6: I would advise people to try to get hold of.

935
00:50:08,940 --> 00:50:12,799
Speaker 6: Like he's a flailing weakling. And the only thing which

936
00:50:12,860 --> 00:50:16,160
Speaker 6: keeps him from looking like a flailing weakling is the

937
00:50:16,200 --> 00:50:18,940
Speaker 6: people who refuse to see that or the people who

938
00:50:18,960 --> 00:50:22,260
Speaker 6: are immediately around him. And he will do the things,

939
00:50:22,660 --> 00:50:24,380
Speaker 6: he will say the things and he will try to

940
00:50:24,420 --> 00:50:27,489
Speaker 6: do the things around November. that you always say and

941
00:50:27,510 --> 00:50:30,029
Speaker 6: try to do when you're an aspiring authoritarian in an

942
00:50:30,090 --> 00:50:33,279
Speaker 6: election where you're about to get a pounding. So that's

943
00:50:33,320 --> 00:50:33,779
Speaker 6: where we are.

944
00:50:33,920 --> 00:50:37,640
Speaker 5: I mean, I think it's terrible what Trump is doing

945
00:50:37,680 --> 00:50:39,560
Speaker 5: and what he's trying to do, but it's also an

946
00:50:39,680 --> 00:50:42,900
Speaker 5: eminently winnable situation. And I think ideally his situation, if

947
00:50:43,520 --> 00:50:46,640
Speaker 5: it works out well in November, he gets personally humiliated

948
00:50:46,960 --> 00:50:52,299
Speaker 5: and the bubble of strongman charisma bursts. And then the

949
00:50:52,320 --> 00:50:53,960
Speaker 5: second thing which has to happen is that the Democrats

950
00:50:54,020 --> 00:50:58,420
Speaker 5: after they win, have to do bold, surprising things so

951
00:50:58,460 --> 00:51:01,120
Speaker 5: that people don't immediately think, Oh, well, yes, it's just

952
00:51:01,180 --> 00:51:01,969
Speaker 5: the same old people.

953
00:51:02,630 --> 00:51:02,910
Speaker 3: Okay.

954
00:51:02,930 --> 00:51:07,190
Speaker 1: So I want you to, let's just go back still

955
00:51:07,570 --> 00:51:10,370
Speaker 1: for the, like where America is right now, because, uh,

956
00:51:11,960 --> 00:51:14,919
Speaker 1: Trump is definitely an autocrat, and he has, I think,

957
00:51:15,160 --> 00:51:17,780
Speaker 1: in a lot of ways, turned out to be worse

958
00:51:17,840 --> 00:51:19,520
Speaker 1: than a lot of us thought he would be, at

959
00:51:19,560 --> 00:51:21,180
Speaker 1: least for me. I thought he was going to be

960
00:51:21,219 --> 00:51:26,129
Speaker 1: really problematic, and he's problematic in ways the way that

961
00:51:26,190 --> 00:51:32,820
Speaker 1: people have facilitated him has been easy. even more craven

962
00:51:32,860 --> 00:51:36,480
Speaker 1: and shocking than I thought it would be. It's been

963
00:51:36,520 --> 00:51:39,239
Speaker 1: the opposite of Trump 1.0 in a certain way, right?

964
00:51:39,260 --> 00:51:44,450
Speaker 1: Trump 1.0 was about resistance. Trump 2.0 is about just

965
00:51:44,530 --> 00:51:51,370
Speaker 1: completely enabling the oligarch at every turn. But it hasn't

966
00:51:51,410 --> 00:51:54,430
Speaker 1: turned out as badly as I thought it would. And

967
00:51:54,469 --> 00:51:56,569
Speaker 1: I'd love you to talk about that sort of, like,

968
00:51:56,610 --> 00:51:59,430
Speaker 1: do you think, like, that first year that he was

969
00:51:59,469 --> 00:52:02,600
Speaker 1: in office, I thought, oh, wow, we are really cooked.

970
00:52:03,260 --> 00:52:06,540
Speaker 1: And it hasn't, but it hasn't actually gone that way.

971
00:52:07,380 --> 00:52:08,720
Speaker 5: Well, I don't, I mean, I guess there are different

972
00:52:08,760 --> 00:52:12,940
Speaker 5: ways to be cooked. And there are different ways for

973
00:52:12,960 --> 00:52:17,560
Speaker 5: things to go badly. I mean, if you care, you know,

974
00:52:17,580 --> 00:52:19,540
Speaker 5: this may not be the biggest topic on your show,

975
00:52:19,580 --> 00:52:23,410
Speaker 5: but If you care about American power, wow, has this

976
00:52:23,430 --> 00:52:26,989
Speaker 5: been catastrophic. I mean, it's really hard to think of

977
00:52:27,030 --> 00:52:30,310
Speaker 5: an example. And I've been straining and asking colleagues of

978
00:52:30,410 --> 00:52:34,340
Speaker 5: a major power, superpower, a big empire, whatever you prefer,

979
00:52:35,980 --> 00:52:42,640
Speaker 5: catastrophically self-destructing in this way, right? So we have, I mean,

980
00:52:42,680 --> 00:52:44,410
Speaker 5: wherever you want to look or however you want to

981
00:52:44,620 --> 00:52:48,270
Speaker 5: qualify it, like we lost a humiliating war to a

982
00:52:48,310 --> 00:52:52,379
Speaker 5: middle power in about three days. We tried to help

983
00:52:52,460 --> 00:52:55,240
Speaker 5: Russia beat Ukraine, and we haven't even succeeded in that.

984
00:52:56,540 --> 00:52:58,259
Speaker 5: We've opened the way for China to do whatever it

985
00:52:58,300 --> 00:53:02,420
Speaker 5: was once in the Pacific. We've presided over a military

986
00:53:02,460 --> 00:53:06,780
Speaker 5: which is now subject to political, gender, and racial purging,

987
00:53:07,030 --> 00:53:11,530
Speaker 5: and whose weapon systems are either no longer existent because

988
00:53:11,570 --> 00:53:15,750
Speaker 5: left in the sand in Iran, or increasingly archaic. There

989
00:53:15,810 --> 00:53:18,710
Speaker 5: is no world leader in the world who respects our president.

990
00:53:20,800 --> 00:53:23,940
Speaker 5: And then even deeper than that, we're trying to do

991
00:53:24,000 --> 00:53:27,060
Speaker 5: away with the fundamental bases of power, which are education

992
00:53:27,120 --> 00:53:32,300
Speaker 5: and research, which again, no self-respecting great power, empire, superpower,

993
00:53:32,340 --> 00:53:37,009
Speaker 5: whatever does that. So if you care about American power,

994
00:53:37,390 --> 00:53:41,489
Speaker 5: it's really hard to imagine a worse scenario than this.

995
00:53:42,210 --> 00:53:43,930
Speaker 5: And then, I mean, another, and then again, if you

996
00:53:43,950 --> 00:53:47,589
Speaker 5: think about the long-term, like being cooked, if you think

997
00:53:47,640 --> 00:53:50,080
Speaker 5: about cooking as being slow, there's been a lot of

998
00:53:50,160 --> 00:53:55,580
Speaker 5: really damage to research, attracting students, public education, which it's

999
00:53:55,600 --> 00:53:58,020
Speaker 5: going to take half a century to get back. And

1000
00:53:58,040 --> 00:54:01,180
Speaker 5: in that sense, I would say we're pretty cooked in

1001
00:54:01,239 --> 00:54:05,080
Speaker 5: terms of like the flat out authoritarian scenario. I mean,

1002
00:54:05,120 --> 00:54:07,940
Speaker 5: I think there's their strengths or their weaknesses, right? Because

1003
00:54:08,450 --> 00:54:12,350
Speaker 5: They're fascists insofar as it allows them to scam you.

1004
00:54:12,810 --> 00:54:16,489
Speaker 5: And although that's not great, like this oligarchical fascism or

1005
00:54:16,530 --> 00:54:19,720
Speaker 5: flaccid fascism, whatever you want to call it, it is

1006
00:54:19,760 --> 00:54:21,739
Speaker 5: a limit on the fascism, right? The oligarchy is a

1007
00:54:21,739 --> 00:54:24,160
Speaker 5: limit on the fascism. But the oligarchy is also not

1008
00:54:24,200 --> 00:54:26,739
Speaker 5: great because Trump is not the real oligarch. I mean,

1009
00:54:26,760 --> 00:54:28,560
Speaker 5: Trump is an old-fashioned guy who thinks if he has

1010
00:54:28,600 --> 00:54:32,299
Speaker 5: a couple billion dollars, he's rich. He is the enabler

1011
00:54:32,980 --> 00:54:34,660
Speaker 5: from the point of view of the Peter Thiel's and

1012
00:54:34,680 --> 00:54:35,739
Speaker 5: Elon Musk's of the world.

1013
00:54:36,180 --> 00:54:36,660
Speaker 3: He is the.

1014
00:54:36,600 --> 00:54:39,860
Speaker 5: Enabler of something completely different where government no longer functions

1015
00:54:40,140 --> 00:54:45,750
Speaker 5: and where we are just objects working for some better world,

1016
00:54:45,969 --> 00:54:48,370
Speaker 5: which is driven by social media and AI or whatever.

1017
00:54:48,930 --> 00:54:51,910
Speaker 5: So there are different ways to be cooked. And how

1018
00:54:51,989 --> 00:54:54,049
Speaker 5: bad it looks, I think, kind of depends upon which

1019
00:54:54,090 --> 00:54:56,250
Speaker 5: of those narratives you are focusing on at the moment.

1020
00:54:57,120 --> 00:55:00,190
Speaker 1: So you actually think that America's much worse off? I mean,

1021
00:55:00,290 --> 00:55:04,230
Speaker 1: I think America's obviously much worse off after two and

1022
00:55:04,250 --> 00:55:07,069
Speaker 1: a half years of Trump or almost two years of Trump.

1023
00:55:07,110 --> 00:55:12,900
Speaker 1: But my question, I think the power stuff on the

1024
00:55:12,980 --> 00:55:17,279
Speaker 1: international stage is... hugely diminished and may never return. And

1025
00:55:17,320 --> 00:55:23,140
Speaker 1: I think the cuts to the grants and science are

1026
00:55:23,500 --> 00:55:26,879
Speaker 1: pretty catastrophic. But I do think the thing that I've

1027
00:55:26,920 --> 00:55:29,020
Speaker 1: been struck by, and maybe I didn't articulate this the

1028
00:55:29,060 --> 00:55:33,100
Speaker 1: right way, is that the American people, Donald Trump has,

1029
00:55:33,460 --> 00:55:38,359
Speaker 1: you know, Donald Trump came into power pretty popular, won

1030
00:55:38,410 --> 00:55:41,950
Speaker 1: the popular vote, and then just managed to do all

1031
00:55:41,989 --> 00:55:44,650
Speaker 1: of the things he could possibly do to alienate his

1032
00:55:44,710 --> 00:55:50,020
Speaker 1: voters in a way that as catastrophic as what he

1033
00:55:50,060 --> 00:55:53,660
Speaker 1: did to American power is, it is also catastrophic what

1034
00:55:53,700 --> 00:55:56,520
Speaker 1: he's done to his own electoral power.

1035
00:55:57,140 --> 00:55:57,520
Speaker 2: Yeah.

1036
00:55:58,260 --> 00:56:02,489
Speaker 5: I mean, I would say it Or do you not

1037
00:56:02,570 --> 00:56:04,270
Speaker 5: believe that? I don't agree with that. I mean, I

1038
00:56:04,270 --> 00:56:09,520
Speaker 5: think in terms of geopolitics, we've gone from like, on

1039
00:56:09,560 --> 00:56:11,540
Speaker 5: a scale of 100, we've gone from like, you know,

1040
00:56:11,560 --> 00:56:15,359
Speaker 5: we've gone from 92 to like 25, you know. Whereas

1041
00:56:15,420 --> 00:56:18,839
Speaker 5: on the scale of his popularity, again, just like, you know,

1042
00:56:18,880 --> 00:56:22,540
Speaker 5: he's gone from like whatever, high 40s to low 30s.

1043
00:56:22,670 --> 00:56:25,290
Speaker 5: You know, these are kind of both imaginary pseudo-empirical things.

1044
00:56:26,310 --> 00:56:28,229
Speaker 5: But you see what I mean? Like, yeah, he's lost

1045
00:56:28,270 --> 00:56:32,430
Speaker 5: a lot of support, but it's troubling that he has 30%

1046
00:56:32,430 --> 00:56:37,219
Speaker 5: support because 30% is enough with plus rigging, plus cheating,

1047
00:56:37,600 --> 00:56:41,120
Speaker 5: plus getting lucky. Like it's enough to stay in power, right?

1048
00:56:41,600 --> 00:56:44,340
Speaker 5: So I'm not, I mean, I wanna be clear. I

1049
00:56:44,719 --> 00:56:46,359
Speaker 5: started out by talking about the good stuff, right? Like

1050
00:56:47,420 --> 00:56:50,859
Speaker 5: the rallies, the civil society, the protection of the vote.

1051
00:56:51,320 --> 00:56:53,450
Speaker 5: And I do think that the Democrats are gonna clobber

1052
00:56:53,489 --> 00:56:58,270
Speaker 5: him in November. I'm quite sure of that. Like on

1053
00:56:58,290 --> 00:57:01,129
Speaker 5: the domestic side, for me, like if we're on like

1054
00:57:01,230 --> 00:57:04,170
Speaker 5: the domestic, how bad are things? Will there still be elections?

1055
00:57:04,210 --> 00:57:06,169
Speaker 5: You know, they'll be elections. They're going to be tough.

1056
00:57:06,190 --> 00:57:08,169
Speaker 5: They're going to be uphill. They can still be one.

1057
00:57:08,750 --> 00:57:11,969
Speaker 5: For me, the question there is not Trump. Trump is

1058
00:57:11,989 --> 00:57:14,719
Speaker 5: largely a spent force. It's a matter of like who's

1059
00:57:14,760 --> 00:57:17,600
Speaker 5: around him, who's exploiting him, like who's his zombie master

1060
00:57:17,640 --> 00:57:21,220
Speaker 5: at this point. For me, the real issue is who

1061
00:57:21,280 --> 00:57:24,160
Speaker 5: can shoot out of the box on November 4th. That's

1062
00:57:24,200 --> 00:57:27,200
Speaker 5: the real issue because there ain't like, Again, this comes

1063
00:57:27,270 --> 00:57:29,270
Speaker 5: back to how bad one thinks that things are. And so,

1064
00:57:29,290 --> 00:57:30,810
Speaker 5: you know, I may disagree, but I don't think there's

1065
00:57:30,870 --> 00:57:33,070
Speaker 5: any going back to anything. Like, I think there's no

1066
00:57:33,110 --> 00:57:35,170
Speaker 5: status quo. There's like no going back to Biden, no

1067
00:57:35,190 --> 00:57:37,820
Speaker 5: going back to Obama, no going back to Clinton, right?

1068
00:57:37,890 --> 00:57:41,320
Speaker 5: What there is, is an opportunity to say, wow, things

1069
00:57:41,360 --> 00:57:43,600
Speaker 5: have gotten bad enough that we need to do some

1070
00:57:43,660 --> 00:57:46,900
Speaker 5: radical stuff, like get money out of politics, for example.

1071
00:57:47,320 --> 00:57:49,840
Speaker 5: And if the Democrats do that coming out of the

1072
00:57:49,890 --> 00:57:53,030
Speaker 5: box in November, I think then domestically, we've got a shot.

1073
00:57:53,420 --> 00:57:57,500
Speaker 5: But if they don't, not exactly Trump who's the problem anymore.

1074
00:57:57,880 --> 00:57:59,840
Speaker 5: If they don't, the problem for me then is that

1075
00:57:59,860 --> 00:58:02,680
Speaker 5: we don't have a two-party system because people don't love

1076
00:58:02,720 --> 00:58:04,020
Speaker 5: the Democrats, right?

1077
00:58:04,220 --> 00:58:04,600
Speaker 1: They don't.

1078
00:58:04,900 --> 00:58:09,060
Speaker 5: And people, whether it's Democratic voters or independents or even

1079
00:58:09,100 --> 00:58:11,040
Speaker 5: some Trump voters, what they want is for somebody to

1080
00:58:11,080 --> 00:58:13,940
Speaker 5: come out and say, hey, we agree the system is

1081
00:58:13,980 --> 00:58:16,300
Speaker 5: corrupt and here's how we're going to fix it. And

1082
00:58:16,360 --> 00:58:18,770
Speaker 5: we're going to be the ones who do it. But

1083
00:58:18,810 --> 00:58:22,360
Speaker 5: if nobody does that, then I'm afraid that in 2027,

1084
00:58:22,340 --> 00:58:25,020
Speaker 5: what you get is a kind of Trump resurgence because

1085
00:58:25,080 --> 00:58:27,820
Speaker 5: Trump can then say he can do the thing with

1086
00:58:27,840 --> 00:58:32,020
Speaker 5: Teelan from Putin, which works, which is everybody's corrupt. But look,

1087
00:58:32,140 --> 00:58:34,880
Speaker 5: I'm more charming about being corrupt than everybody else is.

1088
00:58:34,980 --> 00:58:37,120
Speaker 5: And I'm more honest about it. And so look at me,

1089
00:58:37,420 --> 00:58:40,100
Speaker 5: you know? So for me, like the key stuff is,

1090
00:58:40,700 --> 00:58:43,340
Speaker 5: I mean, I'm afraid of what can happen on November 3rd,

1091
00:58:43,360 --> 00:58:45,700
Speaker 5: but I'm honestly more afraid of what could happen on

1092
00:58:45,720 --> 00:58:48,830
Speaker 5: November 4th after the, let's say, 10 days afterwards, after

1093
00:58:48,870 --> 00:58:52,330
Speaker 5: it's clear that they've won, they need to show that

1094
00:58:52,410 --> 00:58:55,100
Speaker 5: they know what they're going to do with power. And

1095
00:58:55,120 --> 00:58:58,000
Speaker 5: if they don't do that, that's when I think the

1096
00:58:58,060 --> 00:59:00,920
Speaker 5: trouble really starts. Because there's nothing... I mean, Trump is

1097
00:59:00,960 --> 00:59:03,800
Speaker 5: down now, and he's weak, and he's pathetic, and he's

1098
00:59:03,840 --> 00:59:06,510
Speaker 5: a loser who deserves to lose. But losers who deserve

1099
00:59:06,550 --> 00:59:09,580
Speaker 5: to lose, they still don't lose on their own. Like

1100
00:59:09,620 --> 00:59:11,700
Speaker 5: you have to help them lose, you know, you have

1101
00:59:11,720 --> 00:59:14,110
Speaker 5: to beat them. And then after they're beaten, you have

1102
00:59:14,150 --> 00:59:15,770
Speaker 5: to show them what it means that they've been beaten.

1103
00:59:15,810 --> 00:59:17,590
Speaker 5: And it's that last part where, which I'm a little

1104
00:59:17,610 --> 00:59:18,190
Speaker 5: concerned about.

1105
00:59:18,870 --> 00:59:19,130
Speaker 2: Yeah.

1106
00:59:19,290 --> 00:59:21,340
Speaker 1: I mean, you still, though, this is still a pretty

1107
00:59:21,360 --> 00:59:24,480
Speaker 1: big sea change from the last times I've heard you

1108
00:59:24,520 --> 00:59:29,100
Speaker 1: speak on this. Like, I mean, and again, do I

1109
00:59:29,560 --> 00:59:34,980
Speaker 1: agree that I, too, am much more worried about what

1110
00:59:35,040 --> 00:59:39,030
Speaker 1: happens when Democrats have power back because they are going

1111
00:59:39,070 --> 00:59:40,570
Speaker 1: to have to operate in a way that we have

1112
00:59:40,610 --> 00:59:44,450
Speaker 1: not ever seen them operate, which is that this is

1113
00:59:44,510 --> 00:59:47,310
Speaker 1: a brave new world, that if these things are not

1114
00:59:47,410 --> 00:59:50,390
Speaker 1: fixed in the next two years, which is gonna be tricky,

1115
00:59:51,830 --> 00:59:54,410
Speaker 1: we're gonna be really in a lot of trouble when

1116
00:59:54,450 --> 00:59:58,400
Speaker 1: we come into the general election, right? Like money out

1117
00:59:58,440 --> 01:00:03,620
Speaker 1: of politics, I think there's going to be there. There's real,

1118
01:00:04,700 --> 01:00:06,740
Speaker 1: you know, we're going to have to protect elections. We're

1119
01:00:06,760 --> 01:00:09,690
Speaker 1: going to have to protect voting, you know, and we're

1120
01:00:09,710 --> 01:00:12,950
Speaker 1: going to have to build infrastructure in the South. I mean,

1121
01:00:13,370 --> 01:00:15,710
Speaker 1: there are all sorts of things that need to happen

1122
01:00:15,830 --> 01:00:20,990
Speaker 1: in order for America to go to be more democratic than,

1123
01:00:21,110 --> 01:00:24,630
Speaker 1: you know, where we are on the democracy scale. But

1124
01:00:24,670 --> 01:00:28,450
Speaker 1: I do think like it has been we have been

1125
01:00:28,530 --> 01:00:32,730
Speaker 1: really lucky, I think, as a country that Donald Trump

1126
01:00:32,750 --> 01:00:35,510
Speaker 1: has made any number of really bad decisions.

1127
01:00:36,010 --> 01:00:36,360
Speaker 6: Yeah.

1128
01:00:36,430 --> 01:00:39,060
Speaker 5: So the thing about that logic, though, is that it's

1129
01:00:39,260 --> 01:00:41,380
Speaker 5: not really that affirming of us.

1130
01:00:42,180 --> 01:00:42,400
Speaker 2: Right.

1131
01:00:43,160 --> 01:00:46,960
Speaker 5: So the fact like if the argument is where it

1132
01:00:47,080 --> 01:00:52,340
Speaker 5: could be worse because he's a buffoon who makes mistakes that.

1133
01:00:53,280 --> 01:00:56,300
Speaker 5: That only takes you so far, right? And the risk

1134
01:00:56,420 --> 01:00:58,740
Speaker 5: is that thinking like he's a buffoon who makes mistakes.

1135
01:00:58,760 --> 01:01:01,640
Speaker 5: So like I agree, like Iran was a terrible, I mean,

1136
01:01:01,680 --> 01:01:06,080
Speaker 5: it was a crime. Like whatever register you're in, like ethically,

1137
01:01:06,100 --> 01:01:09,300
Speaker 5: it was a crime. Legally, it was a crime. Geopolitically,

1138
01:01:09,610 --> 01:01:12,960
Speaker 5: it was a total cell phone and everyone's laughing at us.

1139
01:01:13,810 --> 01:01:16,290
Speaker 5: Wherever you look at it, and then domestic politically, it

1140
01:01:16,330 --> 01:01:17,470
Speaker 5: was very stupid.

1141
01:01:17,730 --> 01:01:19,290
Speaker 1: Catastrophic.

1142
01:01:19,490 --> 01:01:21,640
Speaker 5: And I think his only hope with it, and my

1143
01:01:21,700 --> 01:01:23,280
Speaker 5: read of his speech at the UN is that he's

1144
01:01:23,380 --> 01:01:26,000
Speaker 5: really hoping that Iran will do something inside the United

1145
01:01:26,020 --> 01:01:28,060
Speaker 5: States before the elections. I think there's a reason why

1146
01:01:28,520 --> 01:01:30,620
Speaker 5: he keeps talking about Iran and the elections together, even

1147
01:01:30,640 --> 01:01:31,990
Speaker 5: though they don't have anything to do with each other.

1148
01:01:34,670 --> 01:01:38,350
Speaker 5: So he makes mistakes. Okay, I agree. He makes mistakes.

1149
01:01:38,850 --> 01:01:41,190
Speaker 5: But what that means is that if he were better

1150
01:01:41,230 --> 01:01:44,630
Speaker 5: at this... We would be in worse trouble, right?

1151
01:01:44,650 --> 01:01:45,510
Speaker 1: I think that's right.

1152
01:01:46,110 --> 01:01:49,580
Speaker 5: And so therefore, what follows from that is that we

1153
01:01:49,620 --> 01:01:52,760
Speaker 5: need to be better at this because we can't count, right?

1154
01:01:52,820 --> 01:01:55,720
Speaker 5: We can't count on the next person being, you know,

1155
01:01:55,880 --> 01:01:58,720
Speaker 5: like we can't count on Vance being like this. We

1156
01:01:58,760 --> 01:02:01,790
Speaker 5: can't even count on Rubio being like this. We certainly

1157
01:02:01,850 --> 01:02:04,350
Speaker 5: can't count on Peter Thiel and Elon Musk and the

1158
01:02:04,370 --> 01:02:06,310
Speaker 5: people who are behind Trump and hoping to get through

1159
01:02:06,430 --> 01:02:08,930
Speaker 5: Trump into a world without government power to be like this.

1160
01:02:09,370 --> 01:02:12,630
Speaker 5: And so that's why I agree with you about how

1161
01:02:13,590 --> 01:02:17,050
Speaker 5: the country has to be democratized after. And I think

1162
01:02:17,470 --> 01:02:19,700
Speaker 5: one has to go on the offensive. You have to

1163
01:02:20,450 --> 01:02:24,800
Speaker 5: have investigations of obvious soft corruption targets who Trump can

1164
01:02:24,820 --> 01:02:26,980
Speaker 5: then personally pardon, but then that kind of makes things

1165
01:02:27,020 --> 01:02:29,060
Speaker 5: worse for him. You have to do some stuff which

1166
01:02:29,120 --> 01:02:32,380
Speaker 5: is spectacular, partly because a lot of the things you'll

1167
01:02:32,400 --> 01:02:34,660
Speaker 5: do will lead to vetoes, right? You have to do

1168
01:02:34,700 --> 01:02:37,160
Speaker 5: things that are spectacular, which kind of sets the stage

1169
01:02:37,220 --> 01:02:37,600
Speaker 5: for 28 as well.

1170
01:02:39,220 --> 01:02:42,460
Speaker 1: So give me an example of one of those spectacular things.

1171
01:02:42,740 --> 01:02:46,280
Speaker 5: You do congressional investigations and hearings of people who don't

1172
01:02:46,300 --> 01:02:49,000
Speaker 5: work for the federal government in any kind of real role,

1173
01:02:49,560 --> 01:02:51,780
Speaker 5: who aren't the president of the United States, who might

1174
01:02:51,840 --> 01:02:54,240
Speaker 5: be like his blood relatives or whatever, who might be

1175
01:02:54,260 --> 01:02:57,740
Speaker 5: his friends, and who are clearly profiting, right? Because Trump

1176
01:02:57,820 --> 01:03:00,200
Speaker 5: is profiting, but a lot of other people are profiting.

1177
01:03:00,550 --> 01:03:03,130
Speaker 5: Nobody should be making millions or billions of dollars because

1178
01:03:03,170 --> 01:03:05,250
Speaker 5: they are friends with or relatives of the president of

1179
01:03:05,270 --> 01:03:08,630
Speaker 5: the United States. That's absolutely absurd. Almost everybody agrees with that,

1180
01:03:08,650 --> 01:03:12,090
Speaker 5: including Republicans. So do spectacular investigations of people who are

1181
01:03:12,110 --> 01:03:14,390
Speaker 5: making lots of money because they're close to the President

1182
01:03:14,410 --> 01:03:16,530
Speaker 5: of the United States. And then put the heat on

1183
01:03:16,570 --> 01:03:19,480
Speaker 5: the President of the United States that way. And also

1184
01:03:19,960 --> 01:03:22,520
Speaker 5: deter people from trying to do this in the next

1185
01:03:22,580 --> 01:03:26,840
Speaker 5: two years. Because the Trump presidency is not run by Trump.

1186
01:03:27,600 --> 01:03:30,580
Speaker 5: He's a grifter with grifter gravity, and he draws other

1187
01:03:30,600 --> 01:03:33,740
Speaker 5: grifters close to him. And then our policy towards Brazil

1188
01:03:33,840 --> 01:03:37,400
Speaker 5: or Venezuela or the EU or Ukraine or whatever it is,

1189
01:03:37,920 --> 01:03:40,480
Speaker 5: our domestic policy too, ends up being written by these

1190
01:03:40,520 --> 01:03:42,900
Speaker 5: people who get close to him. And if you show

1191
01:03:43,160 --> 01:03:45,300
Speaker 5: that there's a risk of getting close to him, which

1192
01:03:45,340 --> 01:03:46,610
Speaker 5: is that we're going to put you up on a

1193
01:03:46,890 --> 01:03:48,810
Speaker 5: media pedestal and we're going to show how you made

1194
01:03:48,830 --> 01:03:50,870
Speaker 5: your money and we're going to embarrass you, then that

1195
01:03:50,910 --> 01:03:52,630
Speaker 5: makes it hard for Trump to govern because he doesn't

1196
01:03:52,710 --> 01:03:54,790
Speaker 5: govern by way of our diplomats and our civil service.

1197
01:03:54,830 --> 01:03:56,950
Speaker 5: He governs by way of the grifters who come to him.

1198
01:03:57,470 --> 01:04:01,470
Speaker 1: And bullying. Right. So you were just in Ukraine. Talk

1199
01:04:01,490 --> 01:04:04,729
Speaker 1: to us about being in Ukraine and what's happening there.

1200
01:04:05,430 --> 01:04:08,710
Speaker 5: Well, it's really good for me to be in Ukraine.

1201
01:04:10,320 --> 01:04:12,090
Speaker 5: It's good for me. I feel very lucky to be

1202
01:04:12,140 --> 01:04:16,460
Speaker 5: among people who are well-organized and courageous. And a lot

1203
01:04:17,420 --> 01:04:20,060
Speaker 5: of the hope that I have about situations which are

1204
01:04:20,100 --> 01:04:23,400
Speaker 5: not so drastic comes from that situation, which is much

1205
01:04:23,500 --> 01:04:28,710
Speaker 5: more drastic, where they're facing the sharper end of the

1206
01:04:28,750 --> 01:04:34,180
Speaker 5: problem of, as I see it, of oligarchy, of hydrocarbons, right?

1207
01:04:34,420 --> 01:04:38,320
Speaker 5: Hootens is a hydrocarbon oligarchy. If we had green energy,

1208
01:04:38,360 --> 01:04:40,420
Speaker 5: there wouldn't be a Russia. If we had green energy,

1209
01:04:40,460 --> 01:04:44,500
Speaker 5: there wouldn't be a Trump regime either. And it's like

1210
01:04:44,540 --> 01:04:47,970
Speaker 5: the sharp end of these oligarchical fantasies, you know, the

1211
01:04:48,050 --> 01:04:52,870
Speaker 5: oligarchical fantasies of people like David Sachs. Yeah, like the

1212
01:04:52,910 --> 01:04:54,770
Speaker 5: guy who, you know, thinks we should have unregulated, like

1213
01:04:54,810 --> 01:04:59,150
Speaker 5: that's an oligarchical fantasy. Putin has an oligarchal fantasy, which

1214
01:04:59,170 --> 01:05:01,650
Speaker 5: is that Ukraine doesn't exist. But you let these cluster

1215
01:05:01,690 --> 01:05:04,190
Speaker 5: of very rich people be too close to power and

1216
01:05:04,210 --> 01:05:06,970
Speaker 5: their fantasies end up crowding out the future. Ukraine is

1217
01:05:06,990 --> 01:05:09,620
Speaker 5: an extreme example of that, but it's also a wonderful

1218
01:05:09,660 --> 01:05:14,640
Speaker 5: example of community self-organization. We use the word resilience, but

1219
01:05:14,660 --> 01:05:17,720
Speaker 5: that's not quite enough for this because humans don't automatically

1220
01:05:17,760 --> 01:05:22,330
Speaker 5: snap back. They hurt and then they recover. And it's

1221
01:05:23,080 --> 01:05:26,080
Speaker 5: The civil society, support of the army, the fact that

1222
01:05:26,100 --> 01:05:28,000
Speaker 5: they're still at it after four and a half years,

1223
01:05:28,500 --> 01:05:31,590
Speaker 5: and the visible courage of people who insist on living

1224
01:05:31,610 --> 01:05:34,150
Speaker 5: their lives, all of that is very good for me

1225
01:05:34,210 --> 01:05:37,229
Speaker 5: as an example, but it also makes me hopeful because

1226
01:05:37,270 --> 01:05:39,530
Speaker 5: it shows that you can go several notches worse and

1227
01:05:39,570 --> 01:05:43,490
Speaker 5: people can still continue to behave effectively. As far as

1228
01:05:43,510 --> 01:05:46,040
Speaker 5: the war itself, the Ukrainians are doing fine on the front.

1229
01:05:46,360 --> 01:05:48,380
Speaker 5: The Russians aren't going to advance on the front. The

1230
01:05:48,420 --> 01:05:51,670
Speaker 5: main change is that since the United States has decided

1231
01:05:51,830 --> 01:05:55,890
Speaker 5: no longer to give Ukraine interceptors, Russian ballistic missiles now

1232
01:05:55,930 --> 01:05:58,310
Speaker 5: just hit. They just launch and they hit, they just land.

1233
01:05:59,030 --> 01:06:02,780
Speaker 5: And that's different and that's worse because the Russians can

1234
01:06:02,820 --> 01:06:05,220
Speaker 5: now not just kill a lot of civilians, which they're doing,

1235
01:06:05,280 --> 01:06:08,280
Speaker 5: but they can destroy the fundaments of the Ukrainian economy.

1236
01:06:08,740 --> 01:06:10,320
Speaker 5: So I think the Russians are trying to win this

1237
01:06:10,400 --> 01:06:14,420
Speaker 5: winter by destroying the Ukrainian economy, and they're not going

1238
01:06:14,440 --> 01:06:18,340
Speaker 5: to win on the front. But if they could win,

1239
01:06:18,360 --> 01:06:21,040
Speaker 5: it would be like that, which means that the Ukrainians

1240
01:06:21,060 --> 01:06:22,980
Speaker 5: need a lot of economic support. And it would be

1241
01:06:23,060 --> 01:06:25,800
Speaker 5: nice if people would find ways to get interceptors into

1242
01:06:25,840 --> 01:06:28,240
Speaker 5: their hands so they could protect their own economy. So

1243
01:06:28,260 --> 01:06:30,200
Speaker 5: that's where we are. The Ukrainians aren't going to lose

1244
01:06:30,260 --> 01:06:32,790
Speaker 5: anytime soon. The only way they can lose is if

1245
01:06:32,850 --> 01:06:35,370
Speaker 5: we completely give up on them and let their economy

1246
01:06:35,410 --> 01:06:36,130
Speaker 5: just be destroyed.

1247
01:06:37,270 --> 01:06:41,470
Speaker 1: But Russia is also in a bad spot there, right?

1248
01:06:41,590 --> 01:06:42,590
Speaker 1: Say more about that.

1249
01:06:43,130 --> 01:06:45,070
Speaker 5: Yeah, good point. I mean, when I say Russia wants

1250
01:06:45,110 --> 01:06:47,390
Speaker 5: to win this winter, It's a little bit like Trump, right?

1251
01:06:47,430 --> 01:06:50,730
Speaker 5: Like you act like you're strong because you're not, right?

1252
01:06:50,870 --> 01:06:53,169
Speaker 5: And at a certain point, that logic no longer works

1253
01:06:53,230 --> 01:06:59,490
Speaker 5: for you. So Putin right now, he's rushing, he's committing

1254
01:06:59,510 --> 01:07:01,710
Speaker 5: like a new level of war crime, basically trying to

1255
01:07:01,730 --> 01:07:05,370
Speaker 5: destroy the entire Ukrainian economy. And he's also trying to

1256
01:07:05,430 --> 01:07:09,870
Speaker 5: intimidate the Europeans by sort of drone attacks that don't

1257
01:07:09,890 --> 01:07:13,730
Speaker 5: look like drone attacks or sabotage things. Sadly, he doesn't

1258
01:07:13,770 --> 01:07:16,820
Speaker 5: have to intimidate us because our president basically does the

1259
01:07:16,840 --> 01:07:20,420
Speaker 5: stuff he wants to already. But Putin's trying to create

1260
01:07:20,440 --> 01:07:24,300
Speaker 5: a situation this winter by destroying the Ukrainian economy and

1261
01:07:24,320 --> 01:07:26,820
Speaker 5: by intimidating the Europeans where he can win by spring.

1262
01:07:27,420 --> 01:07:29,760
Speaker 5: And the reason he needs to do that, in my view,

1263
01:07:30,000 --> 01:07:31,840
Speaker 5: is that the Ukrainians are doing a good job of

1264
01:07:32,550 --> 01:07:37,090
Speaker 5: destroying Russian high hydrocarbons. So Ukrainians now have long range drones,

1265
01:07:37,130 --> 01:07:39,350
Speaker 5: which allow them to go off to Russian refineries and such.

1266
01:07:39,870 --> 01:07:43,150
Speaker 5: And that's critical because Russia, like I said before, it's

1267
01:07:43,650 --> 01:07:46,110
Speaker 5: a hydrocarbon oligarchy. It can only exist. It can only

1268
01:07:46,130 --> 01:07:49,150
Speaker 5: send troops to the front. It can only buy the

1269
01:07:49,290 --> 01:07:53,110
Speaker 5: unsadly American tech that goes into its missiles, including NVIDIA,

1270
01:07:53,130 --> 01:07:57,340
Speaker 5: by the way. Russia's new jet-powered AI drones use NVIDIA chips,

1271
01:07:58,140 --> 01:08:00,540
Speaker 5: which is something that's hard to forget when you're actually there.

1272
01:08:02,060 --> 01:08:06,260
Speaker 5: But the point is that Russia's trying to do all

1273
01:08:06,300 --> 01:08:09,220
Speaker 5: this because they're trying to create a situation where it

1274
01:08:09,240 --> 01:08:11,880
Speaker 5: could be over soon. And the reason is that their

1275
01:08:11,920 --> 01:08:16,519
Speaker 5: hydrocarbon earning capacity is at risk. And also, they're starting

1276
01:08:16,550 --> 01:08:19,189
Speaker 5: to have to draft people, which is a different political

1277
01:08:19,210 --> 01:08:21,610
Speaker 5: situation than just paying people to go to the front.

1278
01:08:22,070 --> 01:08:26,490
Speaker 5: And I think Putin is aware that drafting people is risky,

1279
01:08:26,870 --> 01:08:28,630
Speaker 5: that they might not fight as well, they might be

1280
01:08:28,650 --> 01:08:30,930
Speaker 5: more rebellious, but also that their families aren't going to

1281
01:08:30,950 --> 01:08:33,890
Speaker 5: like it. So I think Russia is rushing to try

1282
01:08:33,910 --> 01:08:35,610
Speaker 5: to bring this thing to an end in the next

1283
01:08:35,689 --> 01:08:38,240
Speaker 5: six or seven months. But the reason they're doing it

1284
01:08:38,260 --> 01:08:41,120
Speaker 5: is because they're facing, as you rightly say, they're facing

1285
01:08:41,160 --> 01:08:42,180
Speaker 5: weaknesses on their side.

1286
01:08:43,479 --> 01:08:45,479
Speaker 1: I want you to talk about, this is probably a

1287
01:08:45,520 --> 01:08:51,730
Speaker 1: weird question, but Ukrainians have drone technology that they offer

1288
01:08:51,810 --> 01:08:57,110
Speaker 1: to America that probably could have really helped America in Iran.

1289
01:08:58,470 --> 01:09:03,000
Speaker 1: We rejected it. it. I mean, can you talk about

1290
01:09:03,040 --> 01:09:03,960
Speaker 1: the drones a little bit?

1291
01:09:04,560 --> 01:09:08,769
Speaker 5: I'm glad you asked about that. I try to put

1292
01:09:08,780 --> 01:09:12,150
Speaker 5: it more conceptually. And by the way, there's a terrific

1293
01:09:12,210 --> 01:09:17,950
Speaker 5: reporter called Natalia Gouminiouk who is publishing a book um,

1294
01:09:18,290 --> 01:09:21,630
Speaker 5: about drone warfare and about basically about contemporary war and

1295
01:09:21,650 --> 01:09:24,310
Speaker 5: how the Ukrainians have revolutionized it, which I would recommend

1296
01:09:24,330 --> 01:09:27,830
Speaker 5: to everybody. It catches all this very well. I've been

1297
01:09:27,890 --> 01:09:29,430
Speaker 5: pretty close to some of this stuff and I've been

1298
01:09:29,470 --> 01:09:31,430
Speaker 5: inside some of the workshops and I, and I know

1299
01:09:31,470 --> 01:09:33,730
Speaker 5: a fair number of people who are practicing this kind

1300
01:09:33,750 --> 01:09:36,810
Speaker 5: of war, which sadly distinguishes me from the people who

1301
01:09:36,840 --> 01:09:40,439
Speaker 5: are making decisions at the top of the department of defense,

1302
01:09:40,540 --> 01:09:43,360
Speaker 5: I'm afraid. So, I mean, putting it in the broadest terms,

1303
01:09:44,140 --> 01:09:47,080
Speaker 5: what Ukraine and Russia are fighting a different kind of war.

1304
01:09:47,680 --> 01:09:51,650
Speaker 5: where there are drone swarms which are defended, right? So

1305
01:09:51,830 --> 01:09:53,770
Speaker 5: Russia can launch hundreds and soon it's going to be

1306
01:09:53,830 --> 01:09:58,030
Speaker 5: thousands of combinations of drones and missiles. Ukraine can do

1307
01:09:58,070 --> 01:10:01,350
Speaker 5: the same thing on both offense and defense. There is

1308
01:10:01,410 --> 01:10:03,800
Speaker 5: no Western country, including the United States, that can do this.

1309
01:10:04,660 --> 01:10:06,920
Speaker 5: And that means that when we try to fight a

1310
01:10:06,920 --> 01:10:10,019
Speaker 5: war against Iran, which is a very small drone power

1311
01:10:10,080 --> 01:10:13,190
Speaker 5: compared to Russia or Ukraine, we end up doing idiotic

1312
01:10:13,229 --> 01:10:16,429
Speaker 5: things like firing our firing Patriots at drones and stuff.

1313
01:10:16,470 --> 01:10:20,290
Speaker 5: We end up using hugely expensive munitions that we can't

1314
01:10:20,350 --> 01:10:24,810
Speaker 5: replace in order to destroy stuff that basically some guy

1315
01:10:24,850 --> 01:10:29,719
Speaker 5: built in his basement for $ 40. Slight exaggeration, but not much.

1316
01:10:29,860 --> 01:10:32,280
Speaker 1: But not much. Not much of an exaggeration there.

1317
01:10:32,640 --> 01:10:37,120
Speaker 5: And so what's happened is that the Russians and the Ukrainians...

1318
01:10:36,760 --> 01:10:41,950
Speaker 5: So the Ukrainians innovate, and the Russians copy, and... the

1319
01:10:42,150 --> 01:10:45,750
Speaker 5: various kinds of drones are mostly Ukrainian innovations, but the

1320
01:10:45,790 --> 01:10:49,050
Speaker 5: Russians then copy and scale it, which has the consequence

1321
01:10:49,090 --> 01:10:52,500
Speaker 5: that the Russians and Ukrainians are on their own level now,

1322
01:10:52,900 --> 01:10:55,760
Speaker 5: which no one else is on, which is dangerous, by

1323
01:10:55,800 --> 01:11:01,740
Speaker 5: the way, for Western countries. But the specific danger for

1324
01:11:01,760 --> 01:11:04,080
Speaker 5: the Americans is this, that the people who run the

1325
01:11:04,460 --> 01:11:07,750
Speaker 5: Department of Defense are, I mean, I'm searching for a

1326
01:11:07,770 --> 01:11:12,240
Speaker 5: polite word for this, but Their minds are organized in

1327
01:11:12,320 --> 01:11:17,500
Speaker 5: categories which don't have to do with national security. It

1328
01:11:19,060 --> 01:11:21,580
Speaker 5: makes them very happy. You can see this with HEXA.

1329
01:11:21,620 --> 01:11:25,120
Speaker 5: They launch a missile. It literally gives them an endorphin

1330
01:11:25,150 --> 01:11:27,830
Speaker 5: burst or whatever. But you can't win wars that way,

1331
01:11:28,030 --> 01:11:32,890
Speaker 5: and you're not going to win wars that way. So

1332
01:11:32,950 --> 01:11:36,190
Speaker 5: now the Iranians then basically made the American bases in

1333
01:11:36,210 --> 01:11:37,770
Speaker 5: the Middle East inhabitable.

1334
01:11:38,210 --> 01:11:38,390
Speaker 1: Right?

1335
01:11:38,410 --> 01:11:41,259
Speaker 5: They've completely wiped us out over there. And we have

1336
01:11:41,570 --> 01:11:44,639
Speaker 5: no answer except to bluster, right? We have no answer.

1337
01:11:45,200 --> 01:11:49,220
Speaker 5: And so this goes back to the power question. There's

1338
01:11:49,260 --> 01:11:51,580
Speaker 5: a problem when you're spending a trillion and you want

1339
01:11:51,600 --> 01:11:54,880
Speaker 5: to spend a trillion and a half, but your mindset

1340
01:11:55,080 --> 01:11:59,160
Speaker 5: is to bring the American military back to an age

1341
01:11:59,620 --> 01:12:03,550
Speaker 5: where wars were won by battleships and artificial injections of testosterone.

1342
01:12:03,930 --> 01:12:08,090
Speaker 5: which is A, an age that never existed, right? But B,

1343
01:12:08,130 --> 01:12:10,229
Speaker 5: it's just wild incompatible with the way that wars are

1344
01:12:10,270 --> 01:12:12,390
Speaker 5: actually fought now, which is with lots and lots of

1345
01:12:12,570 --> 01:12:16,900
Speaker 5: small things flying great distances. So it's not just that

1346
01:12:16,920 --> 01:12:19,019
Speaker 5: we have a particularly inept Secretary of Defense. It's that

1347
01:12:19,080 --> 01:12:22,660
Speaker 5: his ideology keeps him away from contact with the ways

1348
01:12:22,680 --> 01:12:26,280
Speaker 5: that wars are actually fought and thereby makes things much

1349
01:12:26,360 --> 01:12:29,689
Speaker 5: more dangerous for Americans and for America. And the notion

1350
01:12:29,710 --> 01:12:31,710
Speaker 5: that we're spending, that we want to increase the defense

1351
01:12:31,750 --> 01:12:35,260
Speaker 5: budget by 50%, without taking into account what actually happens

1352
01:12:35,320 --> 01:12:38,620
Speaker 5: in wars is just incredibly preposterous. We should be scaling down.

1353
01:12:38,680 --> 01:12:40,880
Speaker 5: We should be having an audit. We should be figuring

1354
01:12:40,939 --> 01:12:42,800
Speaker 5: out how wars are actually fought and won and then

1355
01:12:42,920 --> 01:12:47,930
Speaker 5: spending less money on things that are actually less expensive. Yeah,

1356
01:12:47,950 --> 01:12:49,670
Speaker 5: but there's an underlying thing in your question too, which

1357
01:12:49,710 --> 01:12:52,410
Speaker 5: I want to get to. Trump and Hegseth can't look

1358
01:12:52,430 --> 01:12:55,889
Speaker 5: at the war in Ukraine because it's unimaginable to them

1359
01:12:56,310 --> 01:12:59,259
Speaker 5: that human beings would actually defend things which go beyond

1360
01:12:59,300 --> 01:13:03,400
Speaker 5: their own personal transactional interests. And because that's what Ukrainians do,

1361
01:13:03,900 --> 01:13:08,360
Speaker 5: people like Vance, Trump, Hegseth can't look at Ukraine without

1362
01:13:08,390 --> 01:13:12,170
Speaker 5: getting angry. Because in their world, everything is transactional, everything's selfish,

1363
01:13:12,229 --> 01:13:14,750
Speaker 5: and everyone is a coward. And the moment that that's

1364
01:13:14,910 --> 01:13:18,490
Speaker 5: not true, they get upset. And so they can't learn

1365
01:13:18,550 --> 01:13:21,339
Speaker 5: from Ukraine because they can't physically go there. None of

1366
01:13:21,350 --> 01:13:23,140
Speaker 5: them has and none of them will. And they just

1367
01:13:23,180 --> 01:13:26,880
Speaker 5: can't imagine that people like that could actually be fighting

1368
01:13:26,920 --> 01:13:31,260
Speaker 5: a real war. So to them, the real war is non-existent.

1369
01:13:31,680 --> 01:13:34,500
Speaker 5: And the thing which matters is the boom-boom of missiles

1370
01:13:34,560 --> 01:13:37,860
Speaker 5: and the feeling that things are going great. So we

1371
01:13:38,200 --> 01:13:40,390
Speaker 5: have these warriors of unreality who are in charge.

1372
01:13:41,450 --> 01:13:44,990
Speaker 1: So interesting, and I think very important. Thank you. Thanks.

1373
01:13:46,790 --> 01:13:49,370
Speaker 3: And now your moment of fuckery.

1374
01:13:49,830 --> 01:13:51,050
Speaker 1: Jesse Cannon.

1375
01:13:51,450 --> 01:13:52,220
Speaker 3: Bye, Jugfast!

1376
01:13:52,610 --> 01:13:53,879
Speaker 4: Everyone's favorite candidate.

1377
01:13:53,979 --> 01:13:54,820
Speaker 3: One of the worst.

1378
01:13:54,600 --> 01:13:59,480
Speaker 4: Candidates in a cycle of just the worst candidates. Ken Paxton.

1379
01:14:00,030 --> 01:14:04,890
Speaker 4: has been caught using taxpayer funds for hundreds, hundreds of vacations.

1380
01:14:05,310 --> 01:14:09,229
Speaker 4: But what's funny is he's taken thousands of business trips

1381
01:14:09,290 --> 01:14:09,950
Speaker 4: during this time.

1382
01:14:10,610 --> 01:14:15,309
Speaker 1: Yeah, he's the hardest working man. And just kidding. Senate

1383
01:14:15,330 --> 01:14:19,389
Speaker 1: candidate Ken Paxton took nearly a thousand business trips during

1384
01:14:19,430 --> 01:14:24,269
Speaker 1: his tenure as Texas attorney general, costing taxpayers millions of

1385
01:14:24,310 --> 01:14:28,120
Speaker 1: dollars along the way. Only one in six of them

1386
01:14:28,200 --> 01:14:31,760
Speaker 1: had to do with work. A new report from ProPublica

1387
01:14:31,820 --> 01:14:34,860
Speaker 1: and the Texas Trib shows that Paxton has taken almost

1388
01:14:34,939 --> 01:14:39,640
Speaker 1: a thousand trips. So it cost about $ 3. 3 million to

1389
01:14:39,680 --> 01:14:44,630
Speaker 1: his constituents. His security detail, yes, that man has a

1390
01:14:44,670 --> 01:14:51,840
Speaker 1: security detail, cost $ 24, 000 a month. See, of those 1,000 trips,

1391
01:14:52,100 --> 01:14:56,689
Speaker 1: only 138 of them were linked to actual business. Paxton

1392
01:14:56,729 --> 01:15:00,470
Speaker 1: didn't even record them as such. Paxton took 53 trips

1393
01:15:00,570 --> 01:15:05,309
Speaker 1: to every Republican's favorite state, Florida, 24 trips to Utah,

1394
01:15:05,350 --> 01:15:09,330
Speaker 1: where his family trust owns property, and 19 trips out

1395
01:15:09,370 --> 01:15:13,639
Speaker 1: of the country, all on the taxpayer's dime. Paxton did

1396
01:15:13,700 --> 01:15:17,820
Speaker 1: not offer any specific explanation for his lack of business

1397
01:15:18,360 --> 01:15:22,000
Speaker 1: records for the trips. My favorite is that would mean

1398
01:15:22,100 --> 01:15:26,269
Speaker 1: that his trip with his mistress in France would have

1399
01:15:26,410 --> 01:15:31,230
Speaker 1: been paid for by tax dollars. I'm sure that's not right.

1400
01:15:31,670 --> 01:15:34,229
Speaker 1: Ken Paxton, call your office.

1401
01:15:35,220 --> 01:15:36,299
Speaker 3: That's it for.

1402
01:15:36,180 --> 01:15:42,020
Speaker 7: This episode of Fast Politics. Tune in every Monday, Wednesday,

1403
01:15:42,280 --> 01:15:46,700
Speaker 7: Thursday and Saturday to hear the best minds in politics

1404
01:15:46,780 --> 01:15:51,110
Speaker 7: make sense of all this chaos. If you enjoy this podcast,

1405
01:15:51,530 --> 01:15:54,950
Speaker 7: please send it to a friend and keep the conversation going.

1406
01:15:55,370 --> 01:15:56,490
Speaker 1: Thanks for listening.