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Speaker 1: Hello. 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: I'll talk to legendary author Michael Lewis about his new book, Blockers,

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Speaker 1: the story of the people who are helping keep the U.S.

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Speaker 1: government from falling apart. But first, we have the Jim

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Speaker 1: Acosta Show's Jim Acosta to talk about Trump's fantasies of

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Speaker 1: Iran nuking two American cities. Jim Acosta.

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Speaker 2: Jim Acosta.

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Speaker 3: Hi, Molly. Good to see you.

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Speaker 1: Good to see you. Donald Trump says something wildly incendiary. Basically,

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Speaker 1: he made the case that anything was worth it to

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Speaker 1: keep Iran from having a nuke.

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Speaker 3: I want to see a tremendous victory.

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Speaker 2: You want to see a tremendous victory because it verifies

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Speaker 2: all the things we did.

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Speaker 4: And again, remember, with the war, it's just artificial.

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Speaker 3: It's a little bit high.

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Speaker 2: It's a small price to pay for keeping the world safe,

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Speaker 2: keeping our country safe.

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Speaker 3: They could take out a city.

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Speaker 4: Let him take out Los Angeles.

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Speaker 3: Let him take out San Diego.

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Speaker 5: This is a very small price to pay.

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Speaker 4: And it's going to be over very soon. It's essentially

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Speaker 4: almost over with. And they might keep going a little long.

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Speaker 3: You know, they always say they have a big threshold

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Speaker 3: for paying.

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Speaker 1: They need it.

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Speaker 4: Let me tell you, they need it.

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Speaker 3: But it's going to end very soon.

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Speaker 4: And it'll end one way or the other. And your

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Speaker 4: gas and your gasoline and all of the things.

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Speaker 1: What does that sound like to you?

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Speaker 2: It sounds like we have a 25th Amendment crisis in

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Speaker 2: this country.

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Speaker 3: And I, you know, a couple of things.

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Speaker 2: One is, you know, he absolutely stepped in it big time.

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Speaker 2: I think that, you know, he there are unhinged and

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Speaker 2: deranged comments that he makes from time to time. I mean,

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Speaker 2: this is as bad as it gets. This is bottom

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Speaker 2: of the barrel stuff to say that, well, you know,

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Speaker 2: you know, we have to stop Iran from having a

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Speaker 2: nuclear weapon or else.

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Speaker 3: You know, they could take out L.A. and San Diego.

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Speaker 2: Why is he singling out these two cities and why

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Speaker 2: is he going after California? It's always you know, he

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Speaker 2: always goes after blue states. And, you know, to suggest

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Speaker 2: to fantasize about two massive American cities, any American city

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Speaker 2: being taken out by a nuclear weapon to me is

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Speaker 2: just it's as dangerous and insane as it gets. And

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Speaker 2: the thing that that pisses me off is that, you know,

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Speaker 2: almost immediately, of course, the White House, Trump, his people,

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Speaker 2: his gang, they jump into damage control mode and they

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Speaker 2: start to go after everybody in the media. How dare

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Speaker 2: you take him out of context? How dare you, you know,

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Speaker 2: twist things around? And it's like, wait a minute. He's

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Speaker 2: the most dishonest person who's ever lived, you know, that

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Speaker 2: we know of in our lifetime. But putting that to

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Speaker 2: the side. He absolutely said a totally crazy.

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Speaker 3: And deranged and dangerous thing.

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Speaker 2: And the way the crowd responded tells you everything that

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Speaker 2: you need to know. The crowd understood what he was saying.

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Speaker 2: He was fantasizing and hypothesizing about blue cities, or I

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Speaker 2: guess San Diego is kind of a purple city, honestly,

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Speaker 2: getting blown to smithereens.

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Speaker 3: It's totally nuts. And I woke up this morning wondering

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Speaker 3: whether America's.

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Speaker 2: Finally had enough. Has America finally had enough of this

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Speaker 2: crazy political movement that is so totally contrary to American values,

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Speaker 2: where you have a president of the United States, the

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Speaker 2: leader of this movement, a cult-like movement, just talking about

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Speaker 2: the most bizarre, strange, and just unhinged stuff. And I

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Speaker 2: was just waking up this morning hoping and praying that

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Speaker 2: this is hopefully, maybe this is part of the end

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Speaker 2: of this movement, that piece of tape right there.

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Speaker 1: It was interesting to me watching that because what I

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Speaker 1: thought about was all week Trump has been on the

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Speaker 1: trail because the polling for Republicans is just awful. People

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Speaker 1: are really mad about the price of diesel and the

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Speaker 1: price of gas and the price of things because of

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Speaker 1: the tariffs and food and meat. And I mean, he's

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Speaker 1: just gotten into problems with every single thing that he

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Speaker 1: said he was going to make cheaper. But what I

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Speaker 1: was struck by is there are so many of these

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Speaker 1: soundbites from the trail of Donald Trump saying just absolutely,

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Speaker 1: you know, the kind of things that if your grandfather said,

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Speaker 1: you would you would call a doctor to make sure

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Speaker 1: they were OK. I mean, things like the the earlier

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Speaker 1: this week, he talked about shoving it up their asses.

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Speaker 1: Remember that?

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Speaker 3: He said that.

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Speaker 2: Yes.

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Speaker 3: Yes.

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Speaker 2: Well, there was also the comment that he made during

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Speaker 2: the Hispanic Heritage Month event at the White House where

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Speaker 2: he said Hispanics could fall into the bunker pit that

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Speaker 2: he has where the East Wing used to be and survive.

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Speaker 2: Only Hispanics could survive that fall. I still have no

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Speaker 2: idea what that means. To me, it's just like a

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Speaker 2: moment where he's picturing Hispanics as like being animals or something.

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Speaker 2: I don't understand that. But he does this all the time.

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Speaker 2: And the thing that is totally infuriating– is that we

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Speaker 2: have members of the national press and the legacy and

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Speaker 2: corporate media who will sane wash this stuff, who are

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Speaker 2: pressured by the White House. I can guarantee you that

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Speaker 2: right now there are executives at the networks, at these

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Speaker 2: news organizations who are getting pinged, who are getting calls,

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Speaker 2: who are getting pressure from the White House to normalize

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Speaker 2: and sanitize that nutso comment that he made about nuking

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Speaker 2: LA and San Diego. And this is where there's a

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Speaker 2: breakdown in our society. The media, they have to stop

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Speaker 2: doing it. These networks and these newspapers and these wire services,

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Speaker 2: they have to stop doing it. This should be the

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Speaker 2: end of the Sane Washing, in my view, because it's

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Speaker 2: totally beyond the pale.

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Speaker 1: Tell us what happens with the Sane Washing, because you've

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Speaker 1: had this experience during the first Trump administration. Yes. So

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Speaker 1: you were where you were. You had your hard pass

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Speaker 1: taken away. So tell us what happened to you when

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Speaker 1: you reported something which clearly had happened, which clearly you

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Speaker 1: had seen. What did the White House do to push back?

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Speaker 3: I'm telling you, it's worse now.

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Speaker 1: It's worse.

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Speaker 3: It's much worse now.

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Speaker 2: And when I was at my old place, CNN, you know,

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Speaker 2: fortunately at that time, for the most part, until the end,

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Speaker 2: I had executives who backed me up and would just say, hey,

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Speaker 2: just report what you need to report.

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Speaker 3: Push back. Ask your questions. We'll back you up.

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Speaker 2: But what takes place is you will have people like

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Speaker 2: the communications director, the White House press secretary, who will

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Speaker 2: be calling you, texting you, pressuring you to adopt their

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Speaker 2: line of bullshit about what Trump is doing and saying.

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Speaker 2: And I mean, nine times out of 10 times, 10

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Speaker 2: times out of 10, they're calling your boss. They're calling

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Speaker 2: other executives. They're putting pressure in other places to see

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Speaker 2: if the pressure not only goes through you, but it

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Speaker 2: comes down on top of you. to report things the

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Speaker 2: way they want you to do it.

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Speaker 3: And I just, I always.

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Speaker 2: Try to resist that pressure because to me, I think

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Speaker 2: he's always been this very, you know, unstable, dangerous person. Um,

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Speaker 2: but you know, look, Hey, I'm in independent media now.

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Speaker 2: So eventually they got tired of my shit, but I'm

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Speaker 2: telling you, as soon as he made this comment and

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Speaker 2: they saw this blow up in their faces last night,

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Speaker 2: no pun intended, they I can assure you they jumped

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Speaker 2: into damage control mode and started putting pressure on all

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Speaker 2: these outlets. The Rapid Response 47 account retweeted in the

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Speaker 2: LA Times, which is, I think, still owned by a

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Speaker 2: kooky right-wing owner, put out a tweet saying that Trump

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Speaker 2: suggested that Iran could nuke LA and San Diego. The

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Speaker 2: Rapid Response 47 team over at the White House, they

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Speaker 2: retweeted that and called them buffoons and said all this.

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Speaker 2: This is what they do. It's an intimidation racket. In

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Speaker 2: our press corps, enough is enough. We have to stop

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Speaker 2: allowing the same washing these tactics to continue because it,

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Speaker 2: it totally robs the American people of understanding what is

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Speaker 2: going on. And to me, what's going on is we

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Speaker 2: have a president of the United States who is not well,

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Speaker 2: and we have to deal with that as a country.

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Speaker 2: Joe Biden made one comment about killing Medicare during a debate,

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Speaker 2: destroyed his entire political career.

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Speaker 3: He had to get out of the campaign.

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Speaker 2: Donald Trump fantasizes about LA and San Diego being nuked.

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Speaker 2: And somehow the press lets him off the hook.

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Speaker 3: I'm sorry, it has to stop.

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Speaker 2: Not to go too nuts myself, but it has to stop.

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Speaker 1: It is insane moment.

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Speaker 3: Insane.

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Speaker 1: And the thing that I'm struck by is we are

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Speaker 1: watching from what it seems like very clearly to me,

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Speaker 1: American voters are very unhappy with the situation. Yeah. I mean,

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Speaker 1: you just go to any gas station anywhere and what happens, right? Yeah.

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Speaker 3: They're all pissed off. We've seen the soundbites on MS Now.

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Speaker 2: Even Trump supporters are like, I can't believe I'm paying

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Speaker 2: through the nose for this ridiculous war that Trump started

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Speaker 2: on his own. And this is totally biting him in

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Speaker 2: the ass. They're trying to do all of these things

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Speaker 2: with the supply chains and the diesel supply and the

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Speaker 2: strategic petroleum reserve. They're, they're monkeying around with all of

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Speaker 2: these things, gas taxes in various States. And so I

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Speaker 2: want to try to put pressure downward on these prices.

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Speaker 2: Not going to, it's not going to happen in time

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Speaker 2: to bail them out. And so he is, I've seen

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Speaker 2: him in this mode before he gets frantic. They all

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Speaker 2: get frantic around him. They go into desperation mode and he's,

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Speaker 2: and you can see it at these rallies. It's why

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Speaker 2: he is coming unglued. He sees what is how he sees.

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Speaker 3: It's like that.

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Speaker 2: It's like that giant wave and interstellar that's way off

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Speaker 2: in the distance. And it looks like a planet killer.

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Speaker 2: And he sees that, that interstellar wave coming. And he

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Speaker 2: is so freaked out that they're trying to get the

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Speaker 2: hell out of there in time. And I I'm telling you, I,

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Speaker 2: this is just the beginning of the desperation stage. These

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Speaker 2: next four weeks are going to be one hell of

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Speaker 2: a ride because he knows all if it's as bad as.

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Speaker 3: It sounds right now, where they lose the house, they

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Speaker 3: lose the Senate. The polls are correct.

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Speaker 2: They lose these important governor's races and like Florida and Texas,

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Speaker 2: that's a historic blowout. We've never seen a midterm blowout

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Speaker 2: like the one that is taking shape right now. I'm

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Speaker 2: trying to, I'm trying to say, let's be a little

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Speaker 2: realistic about this. There may be some States that are

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Speaker 2: not going to flip like South Carolina and so on,

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Speaker 2: but they see what's happening. They see what's coming.

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Speaker 1: And, and you know, Trump is not, Trump is tweeting

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Speaker 1: about the South Carolina election. Senate race because he has

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Speaker 1: anxiety about it, not because, right, like this would not.

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Speaker 1: It's because Darlene Graham is a really weak candidate and

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Speaker 1: and he sees it. I mean, he would otherwise would

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Speaker 1: not even be on his radar. And and I would

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Speaker 1: love to talk to you about this Salazar seat. in Miami.

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Speaker 1: So much.

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Speaker 4: Yeah.

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Speaker 1: Because you have a Cuban father, you know, that Cuban

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Speaker 1: voter Latino voters are are going to be probably where

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Speaker 1: it's at for the rest of our careers. Right. They

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Speaker 1: are the biggest And they're growing and growing and growing.

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Speaker 1: And that and it means a lot of different things.

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Speaker 1: But in Florida, a lot of Latino voters are Cuban.

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Speaker 1: And Cuba is a totally different kind of place and

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Speaker 1: has a lot of those people have been here for

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Speaker 1: a long time. And I would love you to talk

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Speaker 1: through what's happening in Miami right now, because that is

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Speaker 1: really interesting.

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Speaker 3: It's very interesting.

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Speaker 2: And I mean, again, Trump only has himself to blame

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Speaker 2: for the political mess that he started in South Florida.

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Speaker 2: The Cuban-American exile community has been there, obviously, for like

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Speaker 2: 60 years. And they have traditionally been very Republican and

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Speaker 2: have supported Republicans for years. I mean, Obama won Florida.

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Speaker 2: He won a lot of those Latin American voters in

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Speaker 2: South Florida. But they went hard for Trump just about

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Speaker 2: every time. And in particular, this last time, And it

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Speaker 2: helped him get back into the White House. There's no

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Speaker 2: question about it. I mean, Florida was going to go

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Speaker 2: Republican probably no matter what. But what they're seeing now

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Speaker 2: is they're seeing ICE come into South Florida and pick

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Speaker 2: up Cubans too. And there have been Cubans that have

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Speaker 2: been deported to places like Africa and I think Ghana

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Speaker 2: and stuff.

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Speaker 3: Like that, Cuban migrants.

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Speaker 2: And it has really caused this tidal wave of outrage

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Speaker 2: down there. So Maria Elvira Salazar the incumbent Congresswoman.

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Speaker 3: Puts out this video. Yeah. She, she won huge the

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Speaker 3: last time. She's a former anchor lady.

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Speaker 2: And now she puts out this video saying, you know,

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Speaker 2: Donald Trump, you've gone too far with ice. Elliot Rodriguez,

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Speaker 2: the Democrat in the race, very smart recruitment on the

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Speaker 2: part of the Democrats.

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Speaker 1: He was a former, yeah.

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Speaker 3: Former anchorman down there too. Very popular.

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Speaker 2: Kind of like the Cuban Walter Cronkite of Miami, like

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Speaker 2: 30 years and whatnot.

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Speaker 3: And I interviewed him the other day. I don't know

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Speaker 3: them that well. I know Elliot.

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Speaker 2: He and I met during the Obama trip to Cuba

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Speaker 2: back in 2016. And, you know, I think that he

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Speaker 2: has a really good shot at winning that race. And

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Speaker 2: to me, it's like the epitome of what Trump has

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Speaker 2: done to piss off Latino voters. That and what's happening

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Speaker 2: in South Texas, it's a massive change.

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Speaker 1: Let's talk about South Texas, because I interviewed a lot

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Speaker 1: of those candidates, too. I interviewed Bobby Polito, who is

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Speaker 1: now up, who is now ahead. And and Garcia, both

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Speaker 1: like in running an R plus 10, 12. That's a

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Speaker 1: different story. That's ICE harassing Mexican voters. But a lot

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Speaker 1: of those Mexican voters have been here for a long time.

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Speaker 3: Right. Yeah, no.

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Speaker 2: And a lot of those districts have been pretty democratic

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Speaker 2: over the years. I mean, people make the mistake of

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Speaker 2: thinking that the Latino vote is like a monolithic voting bloc.

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Speaker 4: It really isn't.

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Speaker 2: It's very different based on different cultural centers like Miami

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Speaker 2: is very Republican. South Texas, Southern California can be very

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Speaker 2: democratic and so on. And but but the immigration policies

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Speaker 2: back down in South Texas have backfired in Trump's face, too.

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Speaker 3: And, you know, a lot of this is driven by economics.

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Speaker 3: People say, oh, it's just immigration. It's just immigration.

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Speaker 4: No, it's not.

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Speaker 2: You know, we saw this in 2024 where Hispanics were

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Speaker 2: voting on inflation. They were voting on, you know, those

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Speaker 2: kinds of price of eggs issues and housing costs and

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Speaker 2: health care costs and so on. Not that, you know,

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Speaker 2: I mean, everybody... You know, understands that Donald Trump is

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Speaker 2: not going to fix any of those problems. But people

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Speaker 2: were voting in that way back in 2024. And they'll

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Speaker 2: vote that way this time, too.

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Speaker 1: But there's other things that he's done, which I think

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Speaker 1: are uniquely incompetent and just very Trumpy, like stuff where

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Speaker 1: he alienated all these cattle farmers because he opened to

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Speaker 1: opened the floodgates for imported beef.

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Speaker 2: He's made Iowa a possibility for the Democrats with Josh Turek,

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Speaker 2: Dan Osborne, the independent Senate candidate in Nebraska.

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Speaker 3: Now that's a possibility.

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Speaker 2: I just saw a clip this morning where a local

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Speaker 2: reporter was grilling Trump on what he's done to the cattlemen,

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Speaker 2: the cattle ranchers out in Nebraska. And so it's almost

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Speaker 2: like they went into a laboratory and they said, let's

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Speaker 2: find animals. every possible policy position that will infuriate our base.

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Speaker 3: And they did it. It's like a light bright screen.

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Speaker 2: They just about plugged in everything and made the whole

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Speaker 2: screen light up blue. And Trump has done this to

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Speaker 2: himself because he stubbornly and insanely clung to some stupid

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Speaker 2: policy positions like tariffs. I mean, that was always going

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Speaker 2: to blow up in his face. And then allowing himself

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Speaker 2: to be cowed into this war in the Middle East,

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Speaker 2: without even contemplating the consequences when it comes to making

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Speaker 2: an energy crisis blow up in his face, that has

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Speaker 2: been a huge problem. And all of this is coming

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Speaker 2: back to haunt him now. The chickens are definitely coming

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Speaker 2: home to roost.

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Speaker 1: What state do you think Donald Trump is in the

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Speaker 1: most trouble in? What state do you think Democrats have

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Speaker 1: the most opportunity?

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Speaker 2: I think that, I don't know, you were about to

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Speaker 2: say something, but I will say that I'm starting to

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Speaker 2: keep my eye on Ohio.

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Speaker 3: Ohio, Ohio, Ohio.

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Speaker 2: The fact that they recruited this, the Republicans recruited Vivek Ramaswamy,

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Speaker 2: who is about as likable as Donald Trump on a

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Speaker 2: good day. I mean, Vivek Ramaswamy is a terrible candidate.

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Speaker 2: He's trying to pick up some little kid at a

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Speaker 2: rally over the weekend.

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Speaker 1: Unbelievable.

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Speaker 2: Trying to take baseball swings. They like baseball in Ohio.

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Speaker 2: I hate to tell it, but they really like baseball.

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Speaker 1: I liked it when Dinesh D'Souza was like, well, that

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Speaker 1: kid's just too big. It's obviously the kid's fault.

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Speaker 3: You can always count on Dinesh D'Souza. Yeah, exactly. That

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Speaker 3: poor guy.

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Speaker 1: But he's using his, he's flying up and down the state.

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Speaker 4: He flew like.

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Speaker 2: 11 miles or something the other day for a campaign event.

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Speaker 2: I'm thinking, yeah, that's the best way to relate to

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Speaker 2: people in Ohio. And then Sherrod Brown, who lost in

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Speaker 2: that wave in 24, has a shot of winning a

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Speaker 2: seat back, going up against John Husted. He's running on

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Speaker 2: data centers and AI. And people are, I mean, this

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Speaker 2: is one of those places where, you know, the Donald Trump, again,

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Speaker 2: he loves data centers. Every chance he gets, he throws

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Speaker 2: his arms like he hugs data centers the way he

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Speaker 2: hugs the American flag in a weird and a grotesque

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Speaker 2: kind of way. And it's going to blow up in

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Speaker 2: his face. So Ohio, if it goes Democrat, that to

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Speaker 2: me is astonishing because Republicans, I will say they have

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Speaker 2: worked pretty hard in making that kind of a red

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Speaker 2: state in recent years. Donald Trump is obliterating that.

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Speaker 1: Yeah, the Husted, I mean, that guy is such a

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Speaker 1: uniquely bad candidate. It's kind of incredible. Right. He's got,

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Speaker 1: that's the J.D. Vance seat. Somehow Governor DeWine, who is

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Speaker 1: a candidate who has done really well in Ohio, put

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Speaker 1: someone in there who's just about as bad as J.D. Vance.

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Speaker 1: And he is, he reminds me a lot of Mike

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Speaker 1: Rogers in Michigan, like sort of, angry white guy who

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Speaker 1: lives in florida though i guess he doesn't live in

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Speaker 1: florida yeah.

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Speaker 2: The other thing too is i think over the weekend

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Speaker 2: trump was doing a rally in ohio and he was

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Speaker 2: saying how john husted is a pain in the ass

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Speaker 2: or he was like going off on john and the

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Speaker 2: way he goes off on ken paxton.

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Speaker 3: You know it's a it's not really.

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Speaker 2: A great political tactic to go into these rallies and

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Speaker 2: trash the candidates who are struggling to win because of

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Speaker 2: you donald trump i mean it's i.

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Speaker 1: I love Donald Trump on Ken Paxton. He's like, we

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Speaker 1: don't like the way he dresses. He doesn't speak that well.

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Speaker 1: He's kind of funny looking. Yeah, he's not that appealing,

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Speaker 1: but you have to vote for him because he's a

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Speaker 1: good AG.

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Speaker 3: Yeah.

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Speaker 2: The way he, you know, what's that expression about find

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Speaker 2: someone you love the way, you know, find someone you

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Speaker 2: love the way that way Donald Trump hates Ken Paxton,

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Speaker 2: you know, that Find somebody who loves you the way

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Speaker 2: Donald Trump hates Ken Paxton.

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Speaker 3: That might be the new expression now.

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Speaker 2: But I mean, yeah, no, Ken Paxton, who said that

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Speaker 2: the Trumpapalooza is hurting his campaign.

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Speaker 3: And it is.

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Speaker 1: Two different leaked audio from the Ken Paxton campaign. So

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Speaker 1: either Ken Paxton is telling everyone all the time or

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Speaker 1: he has got someone who is working for him who

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Speaker 1: is finding the leaking. Who is the leaker? He's got

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Speaker 1: to find the leaker.

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Speaker 2: He's got to find the leaker. And somebody something tells

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Speaker 2: me the leaker is Ken Paxton. I have a feeling

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Speaker 2: that Ken.

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Speaker 3: Paxton is like, here's the audio. It's like, or he

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Speaker 3: told his comms guy, you know, give that to the

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Speaker 3: New York Times.

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Speaker 1: It is amazing. Yeah. I mean, it's like with the J.D. Vance.

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Speaker 1: I mean, I do wonder, though, when you look at

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Speaker 1: the map, like if Democrats flip Texas and that's, you know,

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Speaker 1: I mean, if it's a big if that said, we

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Speaker 1: have seen Tellerico ahead in all the polls. But again,

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Speaker 1: we've seen a lot of stuff in polling that hasn't

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Speaker 1: borne out. But if he does, I mean, that would be.

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Speaker 1: you could see a world where Republicans will go for

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Speaker 1: a national popular vote because they'll know that they can't

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Speaker 1: use the Electoral College.

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Speaker 2: Yeah, they will certainly start changing their tune on on

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Speaker 2: the Electoral College, I think.

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Speaker 3: But, you know, and James Tallarico.

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Speaker 2: Again, to win a Senate seat, to flip a Senate

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Speaker 2: seat in Texas to blue, I mean, we haven't seen

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Speaker 2: that since, what was it, Lloyd Benson or something like that?

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Speaker 3: I mean, that is a long time.

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Speaker 4: That's a long drought.

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Speaker 1: A lot of dreams have been crushed in Texas. Jim Acosta.

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Speaker 3: Good to see you. Thank you, Molly.

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Speaker 5: It's time to do some headlines.

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Speaker 6: After bipartisan criticism, Trump is saying that the taxpayer dollars

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Speaker 6: will no longer be used for TV ads promoting him.

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Speaker 6: Many people always tell me that pushing back on Trump

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Speaker 6: is useless, but this seems like this is what happens

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Speaker 6: when even the Republicans are mad at him for something.

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Speaker 1: Yeah, I mean, I think actually pushing back on Trump

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Speaker 1: does work if the pushing is hard enough and loud enough.

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Speaker 1: And this is a great example of that. That said...

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Speaker 1: Trump's super PAC, MAGA Inc., which has hundreds of millions

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Speaker 1: of dollars, will not repay the taxpayers for the ads.

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Speaker 1: It's already aired ads that are basically shot for shot,

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Speaker 1: the same as Trump's 2024 ads, some of them. And

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Speaker 1: he announces it on True Social. The radical left is

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Speaker 1: upset with the fact that I am taking ads, which

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Speaker 1: I consider to be positive promotion for our great United States,

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Speaker 1: and paying for them with USA money. That's called taxpayer dollars.

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Speaker 1: This is a rather standard thing to do. It is not.

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Speaker 1: My favorite part of this whole story actually is that

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Speaker 1: Trump announces this on True Social literally minutes after J.D.

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Speaker 1: Vance has been talking to the press and says, like,

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Speaker 1: this is totally normal. There's nothing untoward about doing campaign

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Speaker 1: ads and using taxpayer dollars for them. So I thought

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Speaker 1: this was amazing. Another layer in this story is that

439
00:22:03,650 --> 00:22:07,330
Speaker 1: supposedly the person who cooked this all up was Russ Vaught.

440
00:22:07,410 --> 00:22:10,990
Speaker 1: You'll remember Russ Vaught as the person who tried to, like,

441
00:22:11,350 --> 00:22:17,940
Speaker 1: cut your grandmother's SNAP payments. And that guy, that Russ Vaught,

442
00:22:18,640 --> 00:22:22,580
Speaker 1: somehow found millions of dollars for Trump to do campaign ads.

443
00:22:23,420 --> 00:22:26,160
Speaker 5: Yeah, I can't imagine that they're using that guy to

444
00:22:26,240 --> 00:22:28,510
Speaker 5: figure out how to make chaos with funds.

445
00:22:29,590 --> 00:22:31,740
Speaker 1: Yeah. And it is, I mean, and we had Tom

446
00:22:31,780 --> 00:22:39,520
Speaker 1: Tillis and Schumer both say that Tillis compared Trump to

447
00:22:39,700 --> 00:22:40,550
Speaker 1: Viktor Orban.

448
00:22:41,420 --> 00:22:44,050
Speaker 5: So I think this is interesting. I'd be curious because

449
00:22:44,070 --> 00:22:46,330
Speaker 5: there's like two different theories on this. So a new

450
00:22:46,390 --> 00:22:49,310
Speaker 5: poll from Gallup, who one of the great authorities on polling,

451
00:22:49,750 --> 00:22:52,500
Speaker 5: says more Americans now identify as Democrats than at any

452
00:22:52,560 --> 00:22:55,790
Speaker 5: point since 2009. So as we know, there's Warring factions

453
00:22:55,830 --> 00:22:59,060
Speaker 5: that say the Democratic Party is unpopular because the leadership

454
00:22:59,100 --> 00:23:02,420
Speaker 5: doesn't pay attention to what the party wants. And then

455
00:23:02,440 --> 00:23:05,320
Speaker 5: there's people that say, you know, Trump is the only

456
00:23:05,359 --> 00:23:07,330
Speaker 5: reason this is happening. I'm curious what you think is

457
00:23:07,369 --> 00:23:08,030
Speaker 5: happening here, Molly.

458
00:23:09,090 --> 00:23:09,159
Speaker 2: Oh.

459
00:23:09,630 --> 00:23:12,560
Speaker 1: What's wrong with you? This is the argument we all

460
00:23:12,630 --> 00:23:15,120
Speaker 1: have been having endlessly, which is the question is.

461
00:23:15,080 --> 00:23:17,379
Speaker 4: Like, yeah, but it's never been this high.

462
00:23:17,720 --> 00:23:20,080
Speaker 5: Yeah, this has never been this high for a long time.

463
00:23:20,119 --> 00:23:21,760
Speaker 1: It hasn't. Well, it hasn't been 17 years, 70 since 2009.

464
00:23:21,740 --> 00:23:23,420
Speaker 4: Have Americans so identified again?

465
00:23:23,440 --> 00:23:26,160
Speaker 1: Here is what I would say about this is that

466
00:23:26,180 --> 00:23:42,669
Speaker 1: my sense here is that. I think that there are

467
00:23:42,710 --> 00:23:47,290
Speaker 1: a lot of reasons why Republicans are mad at Trump

468
00:23:47,470 --> 00:23:50,850
Speaker 1: and they go from everything. I mean, like, we just

469
00:23:50,910 --> 00:23:55,429
Speaker 1: don't have a precedent of someone running for president saying,

470
00:23:55,609 --> 00:23:57,430
Speaker 1: I'm going to make things cheaper. I'm going to make

471
00:23:57,470 --> 00:24:01,409
Speaker 1: gas cheaper. I'm going to make, you know, eggs cheaper

472
00:24:01,520 --> 00:24:05,379
Speaker 1: and then immediately doing exactly the opposite. And so you

473
00:24:05,400 --> 00:24:08,260
Speaker 1: could see where people would that would make voters really mad.

474
00:24:08,320 --> 00:24:12,200
Speaker 1: And I think every time we see voters at a

475
00:24:12,200 --> 00:24:15,660
Speaker 1: gas station, they're filling up their cars and they're furious.

476
00:24:16,270 --> 00:24:19,030
Speaker 1: And I think that's real. And I don't think there's

477
00:24:19,070 --> 00:24:21,250
Speaker 1: a precedent for it. And so I do think you

478
00:24:21,290 --> 00:24:23,850
Speaker 1: could see Democrats have a big win here.

479
00:24:23,869 --> 00:24:25,030
Speaker 4: Yeah.

480
00:24:25,070 --> 00:24:29,720
Speaker 5: And I also just wonder if the conning, grifting, lying

481
00:24:29,840 --> 00:24:32,340
Speaker 5: and robbing us blind is just so apparent to see

482
00:24:32,380 --> 00:24:34,120
Speaker 5: that a lot of people have gone, I'm done with this.

483
00:24:34,970 --> 00:24:38,080
Speaker 1: Yeah. I mean, you can tell in the fact that

484
00:24:38,340 --> 00:24:42,700
Speaker 1: there aren't the same kind of MAGA. You know, you're

485
00:24:42,720 --> 00:24:46,290
Speaker 1: not seeing the flags. You're not seeing the bumper stickers.

486
00:24:46,310 --> 00:24:49,030
Speaker 1: You're not seeing the signs anywhere. And every time I

487
00:24:49,050 --> 00:24:50,890
Speaker 1: talk to people, I ask them, like, if they're driving

488
00:24:50,910 --> 00:24:54,510
Speaker 1: through different areas, like, are they seeing the MAGA signs?

489
00:24:54,570 --> 00:24:57,620
Speaker 1: And they're not. And that's a big difference than any

490
00:24:57,660 --> 00:24:59,120
Speaker 1: other time over the last decade.

491
00:25:00,100 --> 00:25:02,540
Speaker 5: Yeah, I really noticed it as I drove through a

492
00:25:02,560 --> 00:25:05,350
Speaker 5: more mega part of New Jersey two weekends ago. So

493
00:25:06,710 --> 00:25:08,350
Speaker 5: it was much less than the last time I took

494
00:25:08,390 --> 00:25:12,770
Speaker 5: that drive about nine months before. So we talked about

495
00:25:12,790 --> 00:25:15,820
Speaker 5: in the last episode with Rick Wilson that Trump's hanging

496
00:25:15,890 --> 00:25:18,500
Speaker 5: out with some new characters ahead of the midterms, but.

497
00:25:19,140 --> 00:25:22,419
Speaker 5: This one really, really is something Trump is meeting with

498
00:25:22,480 --> 00:25:25,260
Speaker 5: election denier Tina Peters at the White House again.

499
00:25:25,280 --> 00:25:25,619
Speaker 2: Yeah.

500
00:25:26,100 --> 00:25:31,200
Speaker 1: Thank you, Governor Polis, for releasing Tina Peters and giving

501
00:25:31,240 --> 00:25:35,230
Speaker 1: her clemency. I mean, such a dumb fucking idea. So

502
00:25:35,290 --> 00:25:39,430
Speaker 1: here's what we have. We have. Tina Peters, Ed Martin.

503
00:25:39,710 --> 00:25:43,380
Speaker 1: Ed Martin, former Department of Justice official. That guy will

504
00:25:43,390 --> 00:25:48,040
Speaker 1: do anything to help their man, Donald Trump. And Tina Peters,

505
00:25:48,100 --> 00:25:52,580
Speaker 1: he tells Eric Bolling, Tina Peters, you know, from Colorado,

506
00:25:52,619 --> 00:25:55,119
Speaker 1: was in the Oval Office meeting with the president on

507
00:25:55,280 --> 00:26:02,180
Speaker 1: election integrity. Here's what election integrity means to this crew. Cheating.

508
00:26:02,980 --> 00:26:10,110
Speaker 1: They mean cheating. And I mean, again, this is this

509
00:26:10,190 --> 00:26:15,190
Speaker 1: is these are the Mike Lindell crew. So the good

510
00:26:15,290 --> 00:26:17,590
Speaker 1: news here is that these people are not smart. The

511
00:26:17,630 --> 00:26:20,300
Speaker 1: bad news here is that they control the federal government

512
00:26:20,359 --> 00:26:22,600
Speaker 1: right now. And that's particularly scary.

513
00:26:23,600 --> 00:26:24,540
Speaker 4: Yeah.

514
00:26:24,960 --> 00:26:29,970
Speaker 5: So your man, RFK Jr., I know you're his reply gal.

515
00:26:30,510 --> 00:26:30,730
Speaker 1: Yeah.

516
00:26:30,930 --> 00:26:31,750
Speaker 5: Over on threads.

517
00:26:32,170 --> 00:26:32,310
Speaker 1: Yeah.

518
00:26:33,390 --> 00:26:36,560
Speaker 5: He he's really, really dealing with the measles cases so

519
00:26:36,619 --> 00:26:40,139
Speaker 5: well that we now have a thousand measles cases in

520
00:26:40,240 --> 00:26:44,060
Speaker 5: Pennsylvania and New York is declaring an emergency since we're

521
00:26:44,140 --> 00:26:46,000
Speaker 5: right next door. Yeah.

522
00:26:46,140 --> 00:26:51,050
Speaker 1: I mean, look, these are rural communities, religious communities where

523
00:26:51,150 --> 00:26:57,429
Speaker 1: people are not vaccinating their kids. And now we're seeing

524
00:26:57,450 --> 00:27:01,649
Speaker 1: the what happens when you don't vaccinate vaccinate your kids.

525
00:27:02,109 --> 00:27:05,350
Speaker 1: kids getting measles and then it's measles spreading. And look,

526
00:27:05,850 --> 00:27:09,530
Speaker 1: this is so easy because like if you get this vaccine,

527
00:27:09,570 --> 00:27:14,470
Speaker 1: there's a 97% protection against, it's a measles, mumps and rubella.

528
00:27:15,320 --> 00:27:19,280
Speaker 1: And in fact, like measles are so dangerous. If you

529
00:27:19,300 --> 00:27:22,520
Speaker 1: get measles when you're pregnant, your baby can have all

530
00:27:22,560 --> 00:27:24,440
Speaker 1: sorts of birth defects. I mean, this is just such

531
00:27:24,500 --> 00:27:28,119
Speaker 1: an easy thing not to die of. And we're seeing

532
00:27:28,180 --> 00:27:31,480
Speaker 1: people who aren't vaccinated in their 30s and 40s. We

533
00:27:31,540 --> 00:27:33,940
Speaker 1: had a woman in her 40s die. I mean, this

534
00:27:34,020 --> 00:27:38,250
Speaker 1: is just absolutely so stupid. And, you know, the problem

535
00:27:38,369 --> 00:27:41,390
Speaker 1: is instead of having a normal health and human services

536
00:27:41,430 --> 00:27:45,840
Speaker 1: secretary where they would, you know, come out for vaccines,

537
00:27:45,859 --> 00:27:50,940
Speaker 1: you have you have Kennedy and Kennedy is actually arguing

538
00:27:50,960 --> 00:27:55,240
Speaker 1: with Governor Shapiro about whether they died from measles or

539
00:27:55,420 --> 00:27:58,060
Speaker 1: with measles, right? Like that they died of something else

540
00:27:58,119 --> 00:28:02,510
Speaker 1: and they just happened to have measles. And that is just,

541
00:28:03,790 --> 00:28:07,090
Speaker 1: that's how you get this kind of thing. And remember,

542
00:28:07,170 --> 00:28:11,470
Speaker 1: like literally two years ago, we had almost gotten rid

543
00:28:11,510 --> 00:28:14,310
Speaker 1: of measles. Like no one ever has to die of measles.

544
00:28:14,650 --> 00:28:16,909
Speaker 1: The only reason that people are dying of measles is

545
00:28:16,950 --> 00:28:20,939
Speaker 1: because we have an anti-vaxxer in charge of HHS. And

546
00:28:21,460 --> 00:28:24,000
Speaker 1: that's really scary. And it's also like, this is what

547
00:28:24,020 --> 00:28:26,639
Speaker 1: we're seeing on the surface. Think about what we're not seeing.

548
00:28:26,700 --> 00:28:32,940
Speaker 1: Think about all of the scientific, protocols, the trials, the drugs,

549
00:28:33,480 --> 00:28:38,110
Speaker 1: all the science we're missing because our country's health system

550
00:28:38,190 --> 00:28:42,110
Speaker 1: is being run by a person who is at best

551
00:28:42,330 --> 00:28:43,030
Speaker 1: a moron.

552
00:28:43,430 --> 00:28:43,650
Speaker 4: Yeah.

553
00:28:43,670 --> 00:28:45,570
Speaker 5: And we can remember this back in COVID when they

554
00:28:45,590 --> 00:28:47,100
Speaker 5: were trying to have their way with this.

555
00:28:47,130 --> 00:28:49,580
Speaker 4: They're like, oh, yeah, it was all comorbidities.

556
00:28:49,600 --> 00:28:53,300
Speaker 5: It wasn't the vaccine. And then now they play that

557
00:28:53,340 --> 00:28:55,460
Speaker 5: hand again. And this is just part of their silly

558
00:28:55,500 --> 00:28:56,120
Speaker 5: little playbook.

559
00:28:57,100 --> 00:28:59,860
Speaker 1: It's also it's just all they have is they just

560
00:29:00,480 --> 00:29:05,400
Speaker 1: think that somehow if you the idea somehow the idea

561
00:29:05,440 --> 00:29:08,910
Speaker 1: that if you die and have measles, you don't die

562
00:29:09,110 --> 00:29:15,630
Speaker 1: of measles is it's just it's so preposterous. Michael Lewis

563
00:29:15,690 --> 00:29:18,650
Speaker 1: is the author of many, many books, including Moneyball, The

564
00:29:18,820 --> 00:29:25,140
Speaker 1: Undoing Project and his latest Blockers, Rebels in the Deep State. Welcome, welcome,

565
00:29:25,180 --> 00:29:25,820
Speaker 1: Michael Lewis.

566
00:29:26,410 --> 00:29:27,290
Speaker 4: Molly, good to see you.

567
00:29:27,830 --> 00:29:30,030
Speaker 1: Good to see you. OK, I want you to talk

568
00:29:30,050 --> 00:29:32,220
Speaker 1: about how you decided to write this book, because it's

569
00:29:32,280 --> 00:29:36,060
Speaker 1: clear to me that you did an anthology of stories

570
00:29:36,260 --> 00:29:39,770
Speaker 1: about these federal workers. And it feels like that's the

571
00:29:39,810 --> 00:29:42,200
Speaker 1: way you got to this, unless I'm making this up.

572
00:29:42,620 --> 00:29:44,280
Speaker 4: No, no, I'll tell you exactly how it happened. So

573
00:29:44,360 --> 00:29:46,020
Speaker 4: I actually wrote a book called The Fifth Risk about

574
00:29:46,060 --> 00:29:50,800
Speaker 4: Trump's first administration. And what got me interested in the

575
00:29:50,840 --> 00:29:54,010
Speaker 4: first place was just his, what seemed to be his

576
00:29:54,070 --> 00:29:57,210
Speaker 4: total indifference to the government. It was that he had

577
00:29:57,290 --> 00:30:02,160
Speaker 4: fired the 550-person transition team the day after he was elected.

578
00:30:02,880 --> 00:30:04,780
Speaker 4: He told Chris Christie that they didn't need to know

579
00:30:04,820 --> 00:30:06,239
Speaker 4: what was going on in the government because they could

580
00:30:06,260 --> 00:30:08,360
Speaker 4: figure it out in an hour. He was like, this

581
00:30:08,400 --> 00:30:11,480
Speaker 4: dog caught the bus and then he didn't care. It

582
00:30:12,140 --> 00:30:16,450
Speaker 4: was odd. In the course of doing that book, but

583
00:30:16,630 --> 00:30:19,950
Speaker 4: only at the very end, I realized that these people

584
00:30:19,990 --> 00:30:24,140
Speaker 4: who were inside the government are often unbelievable characters. doing

585
00:30:24,440 --> 00:30:28,370
Speaker 4: unbelievably interesting things. I had set out kind of just

586
00:30:28,390 --> 00:30:31,690
Speaker 4: to describe the function, like what he was ignoring. And

587
00:30:31,810 --> 00:30:34,720
Speaker 4: so that found the people. And that anthology, Who Is Government?,

588
00:30:34,970 --> 00:30:37,230
Speaker 4: was cooked up. It was a kind of piece of

589
00:30:37,310 --> 00:30:39,770
Speaker 4: stunt journalism. Like I said to David Shipley, who was

590
00:30:39,790 --> 00:30:43,050
Speaker 4: then the editor of the Washington Post opinion section, I said, David,

591
00:30:43,630 --> 00:30:46,090
Speaker 4: it's like the material is so good. We could pick

592
00:30:46,130 --> 00:30:48,470
Speaker 4: six writers, drop them into the government, and just say,

593
00:30:48,600 --> 00:30:51,240
Speaker 4: find a person, and the stories would light up the post.

594
00:30:51,940 --> 00:30:54,640
Speaker 4: And they did. It was like, it was great writers,

595
00:30:55,060 --> 00:30:57,860
Speaker 4: Geraldine Brooks and Dave Eggers and John Lanchester and, and

596
00:30:57,940 --> 00:31:02,140
Speaker 4: Sarah Val and so on, Kamau Bell, Casey Sepp. And they,

597
00:31:02,660 --> 00:31:06,800
Speaker 4: they became a, they became a book. Now, when Trump

598
00:31:06,800 --> 00:31:10,880
Speaker 4: 2 happens, it's an, it's such an indifferent story. It's

599
00:31:10,960 --> 00:31:17,420
Speaker 4: like this multi-pronged assault on these people. And, and I thought,

600
00:31:17,920 --> 00:31:18,920
Speaker 4: I didn't think I was going to write another book

601
00:31:18,940 --> 00:31:21,380
Speaker 4: about the government, but what happened was I started to

602
00:31:21,460 --> 00:31:24,100
Speaker 4: see I started to see that the frame of the

603
00:31:24,120 --> 00:31:27,160
Speaker 4: story is pretty simple. It's like, we're going to turn

604
00:31:27,200 --> 00:31:31,650
Speaker 4: the executive branch from this kind of complicated place where

605
00:31:31,690 --> 00:31:35,550
Speaker 4: power is sort of distributed some into a 2 million

606
00:31:35,590 --> 00:31:38,890
Speaker 4: person operation who serves at the pleasure of a single

607
00:31:38,930 --> 00:31:42,830
Speaker 4: person and a loyalist operation. So you're going to really

608
00:31:42,950 --> 00:31:46,090
Speaker 4: radically kind of change the environment of our government. And

609
00:31:46,110 --> 00:31:47,990
Speaker 4: I asked myself, like, I started to see people being

610
00:31:48,030 --> 00:31:51,010
Speaker 4: driven out, people who I knew were really, really, really

611
00:31:51,030 --> 00:31:53,990
Speaker 4: good at their jobs. and jobs I thought were really

612
00:31:54,050 --> 00:31:57,410
Speaker 4: interesting jobs. And I thought, I'm going to, I'm going

613
00:31:57,430 --> 00:32:01,100
Speaker 4: to try to map the Trump administration by, by mapping

614
00:32:01,260 --> 00:32:04,080
Speaker 4: what no longer belongs in it. Like we couldn't, we

615
00:32:04,200 --> 00:32:06,700
Speaker 4: no longer can survive sort of like an extinction event,

616
00:32:07,020 --> 00:32:10,540
Speaker 4: like meteor hits the planet. Uh, all these species die.

617
00:32:11,010 --> 00:32:13,490
Speaker 4: You can describe the new habitat by what species can

618
00:32:13,530 --> 00:32:16,650
Speaker 4: exist in it. And, um, that was kind of the

619
00:32:16,690 --> 00:32:19,950
Speaker 4: general idea. And I knew going in, you will know

620
00:32:19,970 --> 00:32:21,750
Speaker 4: this as a writer that when you're in a, when

621
00:32:21,770 --> 00:32:23,830
Speaker 4: you're in, I didn't have to worry very much about

622
00:32:23,850 --> 00:32:27,110
Speaker 4: the quality of the characters. I knew that I could find,

623
00:32:27,210 --> 00:32:29,610
Speaker 4: I could almost cast the book, that I could think

624
00:32:29,670 --> 00:32:34,170
Speaker 4: in terms of basic things the government does, public safety

625
00:32:34,390 --> 00:32:39,760
Speaker 4: or the long-term science project or there's a refereeing function

626
00:32:39,800 --> 00:32:43,240
Speaker 4: the government serves or gathering information about ourselves or whatever

627
00:32:43,260 --> 00:32:47,260
Speaker 4: it is. And I could go in and find someone

628
00:32:48,240 --> 00:32:52,040
Speaker 4: whose situation had changed so much And that that change

629
00:32:52,060 --> 00:32:55,060
Speaker 4: would tell us how we just changed as a society.

630
00:32:55,340 --> 00:32:58,660
Speaker 4: Like how we just changed in the way we govern ourselves.

631
00:32:59,290 --> 00:33:01,330
Speaker 4: So that was the idea of the book. And I'll

632
00:33:01,350 --> 00:33:03,730
Speaker 4: shut up in a sec, but just as writer to writer,

633
00:33:04,550 --> 00:33:08,750
Speaker 4: it was so much fun. So much fun. Figuring out

634
00:33:09,290 --> 00:33:13,100
Speaker 4: the form that each section wanted to take. And the

635
00:33:13,120 --> 00:33:15,680
Speaker 4: way I imagined it is like six main characters and

636
00:33:15,700 --> 00:33:18,040
Speaker 4: that they were kind of linked trunk to tail like

637
00:33:18,080 --> 00:33:21,300
Speaker 4: circus elephants. but how to kind of build the story.

638
00:33:21,340 --> 00:33:23,420
Speaker 4: So it felt like a narrative that to me was

639
00:33:23,480 --> 00:33:26,970
Speaker 4: a challenge of the book. And anyway, so that's the

640
00:33:26,990 --> 00:33:29,450
Speaker 4: book and it comes and it comes out in a week.

641
00:33:29,510 --> 00:33:31,050
Speaker 4: So I don't know what anybody thinks.

642
00:33:30,930 --> 00:33:31,290
Speaker 3: About it yet.

643
00:33:34,410 --> 00:33:37,830
Speaker 1: How did you make the narrative work? Because that is

644
00:33:38,470 --> 00:33:40,140
Speaker 1: sounds hard, actually sounds hard.

645
00:33:40,740 --> 00:33:44,200
Speaker 4: Yeah, it actually was, but it wasn't, it wasn't that

646
00:33:44,240 --> 00:33:46,020
Speaker 4: trick was made easy for the reader. Even though it

647
00:33:46,060 --> 00:33:49,910
Speaker 4: was hard for me, but, but what, became clear is

648
00:33:49,950 --> 00:33:52,530
Speaker 4: that there was a kind of logic to the way

649
00:33:52,570 --> 00:33:58,590
Speaker 4: the Trump administration had attacked this enterprise. And then I

650
00:33:58,610 --> 00:34:01,650
Speaker 4: could follow the logic. So here's the logic. The first

651
00:34:01,690 --> 00:34:03,950
Speaker 4: thing they do is make sure they have all the guns.

652
00:34:04,450 --> 00:34:08,870
Speaker 4: They're seizing power. They're seizing powers that they don't actually

653
00:34:08,989 --> 00:34:11,450
Speaker 4: legally have. They're doing all kinds of that kind of thing.

654
00:34:12,380 --> 00:34:15,160
Speaker 4: And the seizure of the story I tell in the

655
00:34:15,180 --> 00:34:17,000
Speaker 4: beginning of the seizure of the Institute of Peace and

656
00:34:17,040 --> 00:34:21,090
Speaker 4: this actual security guard who's physically guarding the place, is

657
00:34:21,110 --> 00:34:25,930
Speaker 4: faced with not just the FBI, but the newly co-opted

658
00:34:25,969 --> 00:34:29,710
Speaker 4: DC police, his own private security detail, all turn against,

659
00:34:29,830 --> 00:34:33,150
Speaker 4: all the guns are pointing in. And so it starts there,

660
00:34:33,570 --> 00:34:39,069
Speaker 4: and then it moves to eliminating all the possibility, all

661
00:34:39,090 --> 00:34:42,700
Speaker 4: the referees in the system, all the people whose job

662
00:34:42,719 --> 00:34:47,920
Speaker 4: it is to sort of adjudicate fairly disputes within the government.

663
00:34:48,530 --> 00:34:52,270
Speaker 1: And um so that's inspectors general.

664
00:34:51,550 --> 00:34:56,000
Speaker 4: Inspectors general uh regulators in some cases their merit systems

665
00:34:56,080 --> 00:34:58,700
Speaker 4: protection board where you go if you're fired for political

666
00:34:58,760 --> 00:35:03,720
Speaker 4: reasons if you're a civil servant um and so the

667
00:35:04,640 --> 00:35:06,440
Speaker 4: it was sort of like the first couple bits are

668
00:35:06,719 --> 00:35:09,020
Speaker 4: creating the conditions for being able to do whatever they

669
00:35:09,060 --> 00:35:12,180
Speaker 4: want with the other parts um and what i found

670
00:35:12,219 --> 00:35:14,480
Speaker 4: was i guess i think i got lucky we'll see

671
00:35:14,780 --> 00:35:17,239
Speaker 4: the book hasn't come out but it i found that

672
00:35:17,600 --> 00:35:22,049
Speaker 4: as the that building a kind of logical argument without

673
00:35:22,070 --> 00:35:24,989
Speaker 4: ever saying what the argument was through the characters of

674
00:35:25,070 --> 00:35:30,030
Speaker 4: how this change worked, this kind of partial, almost kind

675
00:35:30,050 --> 00:35:36,280
Speaker 4: of partial coup worked was it ended up naturally building

676
00:35:36,500 --> 00:35:40,140
Speaker 4: towards a kind of a darker and darker emotional place.

677
00:35:41,100 --> 00:35:44,580
Speaker 4: And so that was one way. The other way was

678
00:35:44,620 --> 00:35:48,890
Speaker 4: there were actual just natural linkages between the characters. There's

679
00:35:48,950 --> 00:35:51,610
Speaker 4: a lady who was in charge of privacy at the IRS.

680
00:35:51,650 --> 00:35:55,569
Speaker 4: She's who sits between your tax return and the White House.

681
00:35:56,050 --> 00:36:00,859
Speaker 4: She's who was there to prevent that information from being

682
00:36:00,910 --> 00:36:06,180
Speaker 4: weaponized against you, American citizen. She got run out. She

683
00:36:06,219 --> 00:36:09,160
Speaker 4: got run out because they want to get their hands

684
00:36:09,260 --> 00:36:13,799
Speaker 4: on the tax returns of undocumented immigrants and 7 million

685
00:36:13,820 --> 00:36:15,700
Speaker 4: of them so they could find them because they had

686
00:36:15,739 --> 00:36:22,170
Speaker 4: their addresses. But it was that naturally flowed into the

687
00:36:22,210 --> 00:36:25,469
Speaker 4: next character who was an immigrant, you know, it was like,

688
00:36:25,489 --> 00:36:26,890
Speaker 4: it was just, you know, it was just like one,

689
00:36:27,230 --> 00:36:29,290
Speaker 4: there were ways that sort of the story just started

690
00:36:29,330 --> 00:36:33,660
Speaker 4: to flow. Um, so, um, anyway, why I did it

691
00:36:33,739 --> 00:36:36,640
Speaker 4: was the reason I wrote it was it just felt

692
00:36:36,680 --> 00:36:41,500
Speaker 4: like I had been kind of poking around this environment

693
00:36:41,620 --> 00:36:44,660
Speaker 4: with a couple of other books for different reasons. And

694
00:36:44,700 --> 00:36:48,969
Speaker 4: then this Trump, this trauma happens inside the environment. that

695
00:36:49,630 --> 00:36:54,250
Speaker 4: it reframed the characters and the environment. It was a

696
00:36:54,270 --> 00:36:56,350
Speaker 4: new story. And now I think I'm done. I think

697
00:36:56,390 --> 00:36:58,590
Speaker 4: like no more government for me. This was it. It

698
00:36:58,640 --> 00:37:02,320
Speaker 4: was like a way to describe something that was really unusual.

699
00:37:02,920 --> 00:37:07,700
Speaker 4: And last thing I'll say is that I had this

700
00:37:07,800 --> 00:37:11,640
Speaker 4: hope that when I wrote it, that it would be

701
00:37:12,030 --> 00:37:15,250
Speaker 4: something that like Republicans could read with interest, that it

702
00:37:15,310 --> 00:37:18,950
Speaker 4: wasn't a tribal document, That it was an attempt to say,

703
00:37:18,969 --> 00:37:21,609
Speaker 4: I mean, like if Trump read books that he might

704
00:37:21,630 --> 00:37:24,129
Speaker 4: be interested in reading it, like this is what your

705
00:37:24,250 --> 00:37:28,899
Speaker 4: government did. And now it doesn't do it that way.

706
00:37:28,920 --> 00:37:33,200
Speaker 4: And think about what that means to you. And, and

707
00:37:33,219 --> 00:37:36,400
Speaker 4: the characters, the characters themselves, because they'd all been in

708
00:37:36,480 --> 00:37:39,600
Speaker 4: government 25 years or whatever, and they all really were

709
00:37:39,640 --> 00:37:43,200
Speaker 4: extremely competent, but they were all very aware of the problems,

710
00:37:43,320 --> 00:37:47,319
Speaker 4: the existing problems they faced before this administration. that they

711
00:37:47,360 --> 00:37:49,340
Speaker 4: were almost the people you would want to line up

712
00:37:49,400 --> 00:37:51,960
Speaker 4: in a congressional hearing and ask them, what do we

713
00:37:51,980 --> 00:37:53,279
Speaker 4: do to fix it? Like, what do we do if

714
00:37:53,300 --> 00:37:55,940
Speaker 4: we're going to rebuild this thing? How do we build

715
00:37:55,980 --> 00:37:57,520
Speaker 4: it so it's better than it was before?

716
00:37:58,060 --> 00:38:02,200
Speaker 1: Government employees have these federal workers. How did you get

717
00:38:02,239 --> 00:38:04,800
Speaker 1: them to talk to you? Because in some ways, those

718
00:38:04,840 --> 00:38:08,600
Speaker 1: are the people who are totally nonpartisan and who have

719
00:38:08,640 --> 00:38:11,339
Speaker 1: like basically shunned the, I mean, the reason why they

720
00:38:11,360 --> 00:38:14,660
Speaker 1: were in such a precarious situation was because nobody knew

721
00:38:14,700 --> 00:38:16,680
Speaker 1: what they did in a certain way.

722
00:38:17,210 --> 00:38:19,730
Speaker 4: That's totally right. You just put your finger on one

723
00:38:19,770 --> 00:38:23,170
Speaker 4: of the odd facts about American government, that there are

724
00:38:23,190 --> 00:38:27,069
Speaker 4: actually laws against promoting their own work using federal money.

725
00:38:27,290 --> 00:38:31,270
Speaker 4: So as a group, I mean, I think most American

726
00:38:31,290 --> 00:38:35,230
Speaker 4: people conflate politics and government. When you ask them, what's

727
00:38:35,250 --> 00:38:37,250
Speaker 4: the government that say it's like, I don't know, Gavin

728
00:38:37,270 --> 00:38:44,200
Speaker 4: Newsom in California, or it's Donald Trump versus AOC. And

729
00:38:44,260 --> 00:38:48,360
Speaker 4: in fact, It's not. In fact, there's a 2 million

730
00:38:48,390 --> 00:38:51,440
Speaker 4: person nonpartisan civil service whose job it is to carry

731
00:38:51,460 --> 00:38:53,420
Speaker 4: out a lot of things that everybody basically agrees need

732
00:38:53,440 --> 00:38:59,100
Speaker 4: to be carried out. And who are, they take an

733
00:38:59,219 --> 00:39:02,160
Speaker 4: oath not to a president, but to the constitution. And

734
00:39:02,200 --> 00:39:09,710
Speaker 4: they are assiduously, like mostly, totally nonpartisan. Like sometimes in

735
00:39:09,730 --> 00:39:12,150
Speaker 4: the most, and they really do see it as their

736
00:39:12,170 --> 00:39:15,180
Speaker 4: job to execute whatever the policy is the president's coming with,

737
00:39:15,219 --> 00:39:19,200
Speaker 4: as long as they're not breaking the law. And it

738
00:39:19,239 --> 00:39:21,219
Speaker 4: is breaking the law to use your tax returns as

739
00:39:21,239 --> 00:39:27,330
Speaker 4: a weapon. And so these people stay out in the

740
00:39:27,390 --> 00:39:29,290
Speaker 4: first place with the fifth risk. It was really hard

741
00:39:29,350 --> 00:39:32,759
Speaker 4: to like get, to people inside the government because they

742
00:39:32,800 --> 00:39:35,060
Speaker 4: just don't talk to journalists and and when they do

743
00:39:35,400 --> 00:39:37,320
Speaker 4: if you call them up if you call up i

744
00:39:37,360 --> 00:39:39,310
Speaker 4: don't know like one of my characters is a guy

745
00:39:39,330 --> 00:39:42,930
Speaker 4: who invented a fire science the science of wildland urban

746
00:39:43,210 --> 00:39:47,470
Speaker 4: fires uh in nist the national institute of technology standards

747
00:39:47,510 --> 00:39:49,920
Speaker 4: and technology you called him up He would say, I

748
00:39:49,940 --> 00:39:51,680
Speaker 4: can't talk to you. He said, if you really want

749
00:39:51,700 --> 00:39:53,860
Speaker 4: to talk to me, you've got to call the political

750
00:39:53,880 --> 00:39:55,850
Speaker 4: people and ask. They can talk to you. You can

751
00:39:55,890 --> 00:39:58,710
Speaker 4: talk to me. The political people will either say no.

752
00:39:59,280 --> 00:40:00,980
Speaker 4: Or send us three questions and we're going to sit

753
00:40:01,020 --> 00:40:02,569
Speaker 4: in the room with him while he answers them.

754
00:40:02,640 --> 00:40:03,009
Speaker 2: Right.

755
00:40:03,430 --> 00:40:05,390
Speaker 4: So what happened? You know, so in this case, it

756
00:40:05,410 --> 00:40:07,050
Speaker 4: was perfect. They'd all been fired.

757
00:40:07,410 --> 00:40:07,890
Speaker 1: Right.

758
00:40:08,710 --> 00:40:08,970
Speaker 4: Right.

759
00:40:08,989 --> 00:40:09,730
Speaker 1: So they can all talk to you.

760
00:40:09,770 --> 00:40:13,230
Speaker 4: They'd all been run out. So it was all like, well, some.

761
00:40:13,350 --> 00:40:17,230
Speaker 1: In a very horrible way that made them furious. Not

762
00:40:17,350 --> 00:40:20,469
Speaker 1: in a sort of nice, respectful way. I mean, I

763
00:40:20,810 --> 00:40:22,209
Speaker 1: think that also- Mostly not.

764
00:40:22,270 --> 00:40:25,210
Speaker 4: Though in the case, you know, it's funny. Alex Marangides,

765
00:40:25,270 --> 00:40:28,250
Speaker 4: who's the guy almost at the center of the book

766
00:40:28,310 --> 00:40:31,350
Speaker 4: who has invented this fire science inside the government and

767
00:40:31,370 --> 00:40:34,489
Speaker 4: the most extraordinary kind of character and stuff he's done.

768
00:40:34,550 --> 00:40:39,270
Speaker 4: But Alex just read the book yesterday or the day before.

769
00:40:39,290 --> 00:40:45,450
Speaker 4: And he's still working free, for free, just because he's

770
00:40:45,550 --> 00:40:47,969
Speaker 4: created this thing that's going to save gazillions of lives.

771
00:40:48,030 --> 00:40:49,279
Speaker 1: And he's probably worried.

772
00:40:50,090 --> 00:40:53,750
Speaker 4: He's worried it's just going to vanish. So he's got

773
00:40:53,810 --> 00:40:57,450
Speaker 4: a laptop from the government to help him try to

774
00:40:57,610 --> 00:41:01,029
Speaker 4: keep some of the work up and running. And he

775
00:41:01,370 --> 00:41:03,280
Speaker 4: called me and said, I'm going to take this laptop

776
00:41:03,360 --> 00:41:06,259
Speaker 4: back because after this book comes out, they're going to

777
00:41:06,300 --> 00:41:10,040
Speaker 4: get in trouble for being associated with me. So he

778
00:41:10,060 --> 00:41:17,799
Speaker 4: didn't realize... So even then, he's not even employed by them.

779
00:41:17,860 --> 00:41:21,160
Speaker 4: He's doing us a favor. He's an immigrant, by the way.

780
00:41:22,560 --> 00:41:28,020
Speaker 4: And even he was thinking, like, my free labor will

781
00:41:28,060 --> 00:41:31,620
Speaker 4: not even be welcome now. So I think they were

782
00:41:31,760 --> 00:41:33,739
Speaker 4: all willing to talk and the people around them willing

783
00:41:33,780 --> 00:41:39,239
Speaker 4: to talk because they'd been blown up. And they were

784
00:41:39,260 --> 00:41:42,160
Speaker 4: not just traumatized. This is an odd way to put it.

785
00:41:42,590 --> 00:41:45,130
Speaker 4: but they were kind of interested in what just happened.

786
00:41:45,370 --> 00:41:47,830
Speaker 4: What have we just done to our society kind of way?

787
00:41:48,489 --> 00:41:52,700
Speaker 4: And they aren't incendiary people. They aren't like angry people.

788
00:41:52,739 --> 00:41:55,540
Speaker 4: They're like puzzled people. Like, what have we done?

789
00:41:55,560 --> 00:42:01,120
Speaker 1: I want you to talk about the Elon Musk of

790
00:42:01,180 --> 00:42:01,620
Speaker 1: it all.

791
00:42:04,800 --> 00:42:07,400
Speaker 4: It is a great mystery what Elon Musk thought he

792
00:42:07,440 --> 00:42:11,739
Speaker 4: was doing. Now, what he said he was doing In

793
00:42:11,760 --> 00:42:14,220
Speaker 4: the beginning, he was going to cut $ 2 trillion out

794
00:42:14,239 --> 00:42:18,069
Speaker 4: of the $ 7 trillion deficit. Now, just so we know,

795
00:42:19,010 --> 00:42:20,509
Speaker 4: what has happened in the first two years of the

796
00:42:20,530 --> 00:42:26,170
Speaker 4: Trump administration is they've added $ 3. 5 trillion of debt. But

797
00:42:26,450 --> 00:42:29,400
Speaker 4: the way he went about it, it seemed like, oh,

798
00:42:29,440 --> 00:42:32,960
Speaker 4: that makes sense only if you knew nothing about the government.

799
00:42:33,180 --> 00:42:38,820
Speaker 4: But if you look at the government spending, I don't know. two-thirds,

800
00:42:38,860 --> 00:42:41,590
Speaker 4: three-quarters or something, some huge amount, maybe more than that.

801
00:42:41,910 --> 00:42:42,830
Speaker 1: Servicing the debt.

802
00:42:43,430 --> 00:42:47,989
Speaker 4: It's servicing the debt, military expenditures, defense department, and entitlements.

803
00:42:49,710 --> 00:42:53,630
Speaker 4: And that was off the table. They didn't even talk

804
00:42:53,670 --> 00:42:56,750
Speaker 4: about that. And then the rest of the sliver of

805
00:42:56,790 --> 00:43:01,040
Speaker 4: the pie they attacked has been pretty starved just generally,

806
00:43:01,440 --> 00:43:05,839
Speaker 4: but it's not like it's grown massively in But to

807
00:43:06,060 --> 00:43:08,120
Speaker 4: deal with that, you'd have to go to Congress, really,

808
00:43:08,180 --> 00:43:10,620
Speaker 4: to change the spending. And they never even tried to

809
00:43:10,660 --> 00:43:14,860
Speaker 4: go to Congress. What they did was sort of assume

810
00:43:14,880 --> 00:43:18,200
Speaker 4: they had powers that they probably didn't, but the courts

811
00:43:18,260 --> 00:43:20,900
Speaker 4: are sorting it out. And they went and they fired

812
00:43:20,920 --> 00:43:25,760
Speaker 4: whoever they could fire, which was... It wasn't the people.

813
00:43:25,840 --> 00:43:29,000
Speaker 4: It wasn't like the old dead wood. There were people

814
00:43:29,060 --> 00:43:32,390
Speaker 4: in every... There's this classification in the civil service called

815
00:43:32,430 --> 00:43:35,930
Speaker 4: probationary worker. And It's like the first 18 months on

816
00:43:35,950 --> 00:43:37,630
Speaker 4: the job, they want to make sure you're good at

817
00:43:37,670 --> 00:43:40,890
Speaker 4: it before they give you the protection of the civil service.

818
00:43:41,600 --> 00:43:46,420
Speaker 4: And they were able to fire all those people, probably illegally,

819
00:43:46,460 --> 00:43:51,010
Speaker 4: but they did it. And who's in that pool? It

820
00:43:51,140 --> 00:43:55,339
Speaker 4: is young people, which the government is desperate for. And

821
00:43:55,440 --> 00:43:57,180
Speaker 4: people who have been brought in to deal with some

822
00:43:57,560 --> 00:44:01,060
Speaker 4: immediate problem because it's an immediate problem. So it's probably

823
00:44:01,100 --> 00:44:04,720
Speaker 4: exactly who you didn't want to fire. And to BD,

824
00:44:04,800 --> 00:44:08,009
Speaker 4: what the consequences of that are, we'll be figuring it out.

825
00:44:08,150 --> 00:44:09,989
Speaker 4: I mean, I think one reason, like when you eat

826
00:44:10,010 --> 00:44:12,529
Speaker 4: the lettuce and you get a sick stomach, now it's like,

827
00:44:12,790 --> 00:44:16,790
Speaker 4: that's what's going on. But the second thing they did

828
00:44:17,330 --> 00:44:18,930
Speaker 4: was they said, we're going to cut all these contracts.

829
00:44:19,410 --> 00:44:21,770
Speaker 4: So I'll give you an example. They did this everywhere,

830
00:44:21,810 --> 00:44:25,299
Speaker 4: but he would tell his 25-year-old Muskrats, the people who

831
00:44:25,340 --> 00:44:29,390
Speaker 4: came to kind of work with him. Go in there, say,

832
00:44:29,430 --> 00:44:31,669
Speaker 4: find the blockers. He said, get rid of the people

833
00:44:31,690 --> 00:44:34,009
Speaker 4: who get in the way. And he said, just cut

834
00:44:34,170 --> 00:44:37,890
Speaker 4: and go find the woke contracts or something. So they

835
00:44:37,930 --> 00:44:41,089
Speaker 4: go into the, this is an example, the Veterans Administration.

836
00:44:41,800 --> 00:44:46,279
Speaker 4: Department of Veterans Administration has 90,000 contracts in a database.

837
00:44:46,920 --> 00:44:50,460
Speaker 4: And some poor kid who didn't know anything, like he

838
00:44:50,500 --> 00:44:54,520
Speaker 4: just discovered the Veterans Administration existed. was sent in and

839
00:44:54,540 --> 00:45:05,290
Speaker 4: just started plugging keywords into the file, bias, women, gender, bias, whatever.

840
00:45:05,770 --> 00:45:08,029
Speaker 4: And just without even knowing what it was, just cut it.

841
00:45:08,350 --> 00:45:14,310
Speaker 4: And so that was insane. That's just insane. So Elon

842
00:45:14,330 --> 00:45:17,070
Speaker 4: Musk isn't dumb. The question is like, what was he doing?

843
00:45:17,860 --> 00:45:21,460
Speaker 4: And I interviewed some of the Doge guys, the young guys.

844
00:45:22,260 --> 00:45:25,880
Speaker 4: And I never really got a very good answer, except

845
00:45:26,580 --> 00:45:28,540
Speaker 4: several of them kind of thought, you know, in the end,

846
00:45:28,580 --> 00:45:30,180
Speaker 4: what he was really here for was his own personal

847
00:45:30,219 --> 00:45:33,279
Speaker 4: business interests. And what he did get out of it

848
00:45:33,380 --> 00:45:36,360
Speaker 4: was he got his friend installed as the NASA administrator.

849
00:45:36,390 --> 00:45:40,169
Speaker 4: Which is what? He cared about. Maybe he cared about

850
00:45:40,190 --> 00:45:42,170
Speaker 4: some other stuff, too. Like if I've had people say

851
00:45:42,190 --> 00:45:43,529
Speaker 4: to me, oh, he really wanted to get rid of

852
00:45:43,630 --> 00:45:46,770
Speaker 4: USAID because of how it meddled in South Africa. I

853
00:45:46,790 --> 00:45:50,690
Speaker 4: don't know. But I don't think he actually... I don't

854
00:45:50,710 --> 00:45:53,600
Speaker 4: think he actually... thought much about it. I think that

855
00:45:54,380 --> 00:46:02,049
Speaker 4: it was a substance-enhanced, ego-driven, nobody-ever-told-him-he-was-wrong-about-anything kind of moment, and

856
00:46:03,150 --> 00:46:07,200
Speaker 4: no one stopped him. So that's the Elon Musk of

857
00:46:07,219 --> 00:46:07,480
Speaker 4: it all.

858
00:46:07,940 --> 00:46:13,440
Speaker 1: So we talked to one of the USAID administrators who

859
00:46:13,480 --> 00:46:17,799
Speaker 1: had been fired by Doge, And, uh, because he wrote

860
00:46:17,820 --> 00:46:21,180
Speaker 1: a book because he was so trauma, you know, when

861
00:46:21,200 --> 00:46:23,759
Speaker 1: you've seen, you know, base, I mean, I, I don't

862
00:46:23,780 --> 00:46:26,089
Speaker 1: have to tell you this, but just, you know, the

863
00:46:26,160 --> 00:46:31,530
Speaker 1: people who have, uh, there are like babies starving in Africa,

864
00:46:31,610 --> 00:46:33,770
Speaker 1: you know, the moment they did that, they, you know,

865
00:46:33,850 --> 00:46:36,480
Speaker 1: starved children. They did, you know, things that are.

866
00:46:36,680 --> 00:46:39,380
Speaker 4: Estimates, 14 million children or some, yeah.

867
00:46:39,400 --> 00:46:39,540
Speaker 3: Yeah.

868
00:46:40,989 --> 00:46:45,549
Speaker 1: Incomprehensible kind of, the kind of thing that I think

869
00:46:45,890 --> 00:46:48,089
Speaker 1: that if you really knew about it, you would not

870
00:46:48,130 --> 00:46:50,890
Speaker 1: be able to sleep at night, you know, forever. And

871
00:46:50,969 --> 00:46:54,029
Speaker 1: he said that he tried to get Elon on the phone,

872
00:46:54,070 --> 00:46:56,180
Speaker 1: you know, that he never met Elon, that he met

873
00:46:56,239 --> 00:46:59,359
Speaker 1: the Doge people like three times and that they were

874
00:46:59,520 --> 00:47:03,120
Speaker 1: so disorganized, but also just totally disinterested.

875
00:47:03,140 --> 00:47:06,880
Speaker 4: And dismissive. Yeah. So I think, I thought this the

876
00:47:06,920 --> 00:47:09,160
Speaker 4: first time around, but they didn't really, when Trump won,

877
00:47:09,180 --> 00:47:11,330
Speaker 4: that they didn't, They didn't really have much of an

878
00:47:11,410 --> 00:47:15,750
Speaker 4: agenda then, but that when you go in and behave

879
00:47:15,790 --> 00:47:21,779
Speaker 4: this way, your ignorance isn't a bug. It's a feature

880
00:47:22,300 --> 00:47:26,219
Speaker 4: that you have to retain your ignorance to do the

881
00:47:26,580 --> 00:47:30,260
Speaker 4: things that are this awful. And the minute you bother

882
00:47:30,280 --> 00:47:33,160
Speaker 4: to kind of start to learn, you get troubled. So

883
00:47:33,200 --> 00:47:35,800
Speaker 4: this is interesting that one of the Doge, he becomes

884
00:47:35,820 --> 00:47:39,700
Speaker 4: the character in the book, one of the Doge recruits,

885
00:47:40,450 --> 00:47:46,359
Speaker 4: was a early 30s guy named sahil lavingia and he

886
00:47:46,380 --> 00:47:49,120
Speaker 4: got he can't he joined doge and the way people

887
00:47:49,160 --> 00:47:50,660
Speaker 4: came to doge was like you heard about it at

888
00:47:50,680 --> 00:47:53,319
Speaker 4: a cocktail party right you were a friend of it

889
00:47:53,340 --> 00:47:57,479
Speaker 4: was a social network and um and he came because

890
00:47:57,520 --> 00:48:00,700
Speaker 4: he was really upset that the irs had not figured

891
00:48:00,739 --> 00:48:02,660
Speaker 4: out how to deliver an app to the american people

892
00:48:02,700 --> 00:48:04,680
Speaker 4: that they still got paper and so he had his

893
00:48:04,700 --> 00:48:06,839
Speaker 4: he had his thing in his head and actually made

894
00:48:06,860 --> 00:48:09,080
Speaker 4: some sense he's a technologist he could go in and

895
00:48:09,440 --> 00:48:10,620
Speaker 4: But they didn't stick him there. They sent him to

896
00:48:10,640 --> 00:48:11,540
Speaker 4: the Veterans Administration.

897
00:48:11,560 --> 00:48:11,759
Speaker 3: Of course.

898
00:48:11,780 --> 00:48:13,600
Speaker 4: They saw what they were doing in the Veterans Administration.

899
00:48:14,320 --> 00:48:16,960
Speaker 4: And he actually poked around and tried to learn something

900
00:48:17,020 --> 00:48:20,170
Speaker 4: before he did anything. And he made the mistake of

901
00:48:20,210 --> 00:48:23,750
Speaker 4: giving an interview to Fast Company Magazine in which he said,

902
00:48:23,850 --> 00:48:26,330
Speaker 4: you know, I've been here a few weeks and I'm

903
00:48:26,370 --> 00:48:30,569
Speaker 4: kind of surprised by how efficient the government is. And

904
00:48:30,590 --> 00:48:31,799
Speaker 4: he got him fired.

905
00:48:32,300 --> 00:48:32,590
Speaker 1: Yeah.

906
00:48:32,719 --> 00:48:36,200
Speaker 4: It's like the one thing you can't do in this operation,

907
00:48:36,219 --> 00:48:39,049
Speaker 4: you can do anything. You can make up colleges you

908
00:48:39,090 --> 00:48:41,490
Speaker 4: never went to on your resume. You can have sexual

909
00:48:41,510 --> 00:48:46,009
Speaker 4: assault charges. You can repost net white supremacist stuff. That

910
00:48:46,050 --> 00:48:49,089
Speaker 4: doesn't get you fired. That actually helps you. Yeah, what

911
00:48:49,130 --> 00:48:51,790
Speaker 4: actually gets you fired is saying the government's not so bad.

912
00:48:52,030 --> 00:48:54,109
Speaker 4: And I thought, oh my God.

913
00:48:54,489 --> 00:48:58,380
Speaker 1: It's just such an important thing to document what the

914
00:48:58,420 --> 00:49:00,480
Speaker 1: federal government does because people don't know.

915
00:49:01,380 --> 00:49:05,480
Speaker 4: And what's happening in this moment? People don't know what

916
00:49:05,520 --> 00:49:07,319
Speaker 4: they just lost and they don't know what it's being

917
00:49:07,340 --> 00:49:08,030
Speaker 4: replaced with.

918
00:49:08,969 --> 00:49:11,190
Speaker 1: Michael Lewis, thank you.

919
00:49:11,870 --> 00:49:17,190
Speaker 4: Good to see you, Molly. And now your moment of suffering.

920
00:49:17,550 --> 00:49:18,570
Speaker 1: Jesse Cannon.

921
00:49:19,120 --> 00:49:19,910
Speaker 4: Molly Jung fast.

922
00:49:19,930 --> 00:49:24,610
Speaker 5: So the Trump administration is refusing international election monitors for

923
00:49:24,650 --> 00:49:26,330
Speaker 5: the first time in over two decades.

924
00:49:27,469 --> 00:49:31,550
Speaker 1: Yes, they don't want to have intellectual. But I can't

925
00:49:31,650 --> 00:49:36,640
Speaker 1: imagine why they would do this. It's a mystery. They

926
00:49:36,780 --> 00:49:42,390
Speaker 1: join Russia and Belarus as being countries that do not

927
00:49:42,469 --> 00:49:47,130
Speaker 1: want to have election monitors. I mean, this is one

928
00:49:47,150 --> 00:49:50,030
Speaker 1: of these things that it's like, if you think your

929
00:49:50,270 --> 00:49:55,930
Speaker 1: president is behaving like a authoritarian dictator and he's doing

930
00:49:55,989 --> 00:50:01,279
Speaker 1: the same things that authoritarian dictators do, perhaps, you know, like,

931
00:50:01,320 --> 00:50:05,350
Speaker 1: you know, this is just... It's bad, but it's also

932
00:50:05,450 --> 00:50:10,050
Speaker 1: more than that. It's like absolutely... A really good example

933
00:50:10,090 --> 00:50:16,129
Speaker 1: is here's a former U.S. ambassador from the Obama administration saying,

934
00:50:16,170 --> 00:50:19,310
Speaker 1: refusing election observers is usually something that countries in a

935
00:50:19,350 --> 00:50:23,590
Speaker 1: position of weakness do when they know they have corrupt

936
00:50:23,690 --> 00:50:27,219
Speaker 1: or unfair elections. It's very strange for the United States,

937
00:50:27,280 --> 00:50:31,060
Speaker 1: which has historically been a standard setter in free and

938
00:50:31,120 --> 00:50:35,680
Speaker 1: fair elections, to... refuse observers. And I think we all

939
00:50:35,739 --> 00:50:39,950
Speaker 1: know what Donald Trump is hoping for. And that is really,

940
00:50:39,969 --> 00:50:45,700
Speaker 1: really not good. That's it for this episode of Fast Politics.

941
00:50:46,160 --> 00:50:52,040
Speaker 1: Tune in every Monday, Wednesday, Thursday, and Saturday to hear

942
00:50:52,180 --> 00:50:56,450
Speaker 1: the best minds in politics make sense of all this chaos.

943
00:50:56,910 --> 00:50:59,650
Speaker 1: If you enjoy this podcast, please send it to a

944
00:50:59,710 --> 00:51:03,710
Speaker 1: friend and keep the conversation going. Thanks for listening.