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Speaker 1: Hi everyone, I'm Kitty Kuric, and this is next question.

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Speaker 1: I love talking with Michael Lewis. He has this incredible

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Speaker 1: ability to zoom in on one person's story and from

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Speaker 1: there reveals something much bigger about our culture. His books

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Speaker 1: leave you seeing the world differently, and his books about

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Speaker 1: federal workers are no exception. So why has the federal

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Speaker 1: government gotten such a bad rap? Why are the workers

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Speaker 1: often maligned even demonized? After all, they're described with words

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Speaker 1: like the deep state and the swamp. Michael Lewis feels

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Speaker 1: very differently after writing about a group of these civil servants,

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Speaker 1: first in The Fifth Risks and now in a new

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Speaker 1: book of essays called Who Is Government? This time Lewis

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Speaker 1: and a powerhouse lineup of writers turn their attention to

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Speaker 1: people who are some of the unsung heroes of our

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Speaker 1: society actually making government work, even though Elon Musk and

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Speaker 1: his posse of doge dudes made beg to differ. Here's

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Speaker 1: my conversation with Michael Lewis. Michael Lewis, you must have

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Speaker 1: a crystal ball, because Who Is Government? The untold story

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Speaker 1: of public service could not be more timely. Now I

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Speaker 1: know this is a continuation of sorts of your twenty

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Speaker 1: eighteen book called The Fifth Risk. You examined the transition

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Speaker 1: and political appointments of the first Trump administration, But what

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Speaker 1: made you decide to do another deep dive into the

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Speaker 1: federal government?

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Speaker 2: So there are two reasons. The good literary argument was

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Speaker 2: at the end of The Fifth Risk, I had to

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Speaker 2: go back and write it afterward for the paperback, and

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Speaker 2: I thought to myself that I'd done a lot to

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Speaker 2: describe the functions of government in that book, but I

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Speaker 2: had not really dwell gone deep on a person really,

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Speaker 2: and I thought might be fun to just go deep

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Speaker 2: on one of our old bureaucrats. And I basically picked

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Speaker 2: a name out of a jar. I mean, it's a

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Speaker 2: long story how I picked the guy, but it was

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Speaker 2: just it was kind of random, and the story. He

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Speaker 2: ended up being an oceanographer in the Coast Guard Search

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Speaker 2: and Rescue Department who had had this quite dramatic encounter

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Speaker 2: with the death of a young woman and her and

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Speaker 2: her daughter that it caught, I mean, it was avoidable.

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Speaker 2: Had they under the Coastguard understood how objects drifted at sea,

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Speaker 2: they kind of knew where they had capsized in the

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Speaker 2: Testapeake Bay. They knew like how the currents were and stuff,

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Speaker 2: but they were upside down on a sailboat and nobody

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Speaker 2: had ever measured how a sailboat drifted at sea. This guy,

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Speaker 2: my subject guard Allen, was so disturbed by the fact

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Speaker 2: that they these two people died because they didn't know

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Speaker 2: how the object had drifted since they discovered they were gone,

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Speaker 2: that he went and created basically a whole science of

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Speaker 2: how objects drifted sea. And it was it was such

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Speaker 2: a he was such an amazing story. I mean, it's

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Speaker 2: a movie his story that I thought, like, if I

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Speaker 2: ever come back to this, I want to come back

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Speaker 2: to the people, because because the stereotype of the of

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Speaker 2: the bureaucrat or whatever you are, the deep state or

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Speaker 2: whatever you want to call him, he was such a

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Speaker 2: He was a mission driven, selfless giver of a person

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Speaker 2: who was also ingenious in how he'd solved a critical

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Speaker 2: problem that has saved thousands of lives. So I thought,

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Speaker 2: if I ever come back to this, I'm gonna see

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Speaker 2: what more of this there is in our government. So

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Speaker 2: that was the first the literary reason. It is like

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Speaker 2: this material here because the people, the way people think

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Speaker 2: of these people, they don't they're faceless. They don't put

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Speaker 2: a face to them, so they're easy to knock around

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Speaker 2: in when you're by politicians, by media, by whoever. Uh.

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Speaker 2: The second reason was I was just astonished after especially

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Speaker 2: after Trump won and then neglect of the federal government

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Speaker 2: during that administration, that the Democrats never offered a full

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Speaker 2: throated like defense or even an explanation of like where

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Speaker 2: are taxpayer dollars? Go, like what is it actually doing?

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Speaker 2: And who are these people? That they never kind of

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Speaker 2: came out and said, like, there's a reason we have

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Speaker 2: this government. So no one ever sold the government. So

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Speaker 2: I thought like there was so there are all these

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Speaker 2: stories that just didn't get told. So the idea, So

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Speaker 2: I thought, like the world needs to understand some of

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Speaker 2: these stories, and so they don't think it's just like

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Speaker 2: Michael Lewis bloviating with his views of government, blah blah blah.

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Speaker 2: I'm going to pick six other writers and it's not

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Speaker 2: going to just be me. It's going to be seven

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Speaker 2: really distinctive personalities on the page, and I'm going to

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Speaker 2: just like drop them into the government, say find a story,

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Speaker 2: could you know, find a story and write up and

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Speaker 2: so much of the book ran in the weeks. About

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Speaker 2: seven eighths of the book ran in the weeks running

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Speaker 2: up to the election in the Washington Post. Weird long pieces.

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Speaker 2: I mean, my longest piece is thirteen thousand words, and

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Speaker 2: it was so powerful the effect, but for a very

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Speaker 2: small audience, because it was like the Washington Post and

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Speaker 2: behind a paywall, and it was pretty obvious these things

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Speaker 2: should They were a coherent hole and they should be collected.

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Speaker 2: But of course, having said that, no one had any

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Speaker 2: I did. Donald Trump was going to be the president

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Speaker 2: of the United States and be doing what he's doing

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Speaker 2: to the federal government where we wrote these things.

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Speaker 1: In fact, in the Washington Post opinion series where the

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Speaker 1: essays in this new book originated, they received four times

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Speaker 1: the session's average readership. And you've said it was like,

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Speaker 1: the country is hungering for an explanation of how government works.

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Speaker 2: Yeah, where do you.

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Speaker 1: Think that hunger is coming from? And why do you

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Speaker 1: think the quote unquote bureaucracy, which is often said in

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Speaker 1: a very pejoradaed way, it's so misunderstood.

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Speaker 2: Well, so remind me to answer the second part of

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Speaker 2: that question, because that's the longer and interesting answer. But

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Speaker 2: the hunger in the first place, we just don't get

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Speaker 2: stories very many stories about the government, or when we

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Speaker 2: get them, they're in the form of some poor civil

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Speaker 2: servants hall in front of Congress to be ritually humiliated

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Speaker 2: for some mistake they made. And I do think I

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Speaker 2: don't know this is true, but I've been told it's

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Speaker 2: true that there has been just to kind of decline

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Speaker 2: in civics education in the country. Like the Civics course

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Speaker 2: you got in the eighth of the ninth grade is

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Speaker 2: not as widely taught anymore, are not taught in the

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Speaker 2: same way. So you know, just like how a bill

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Speaker 2: becomes a law, that kind of stuff just doesn't get

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Speaker 2: into kids' brains.

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Speaker 1: We need Schullhouse rock part too.

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Speaker 2: Yeah, it's something like that. No, it's kind of true.

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Speaker 2: But the second part of this is like these people

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Speaker 2: who work in these jobs are one forbidden from promoting

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Speaker 2: themselves and they don't have time to do it anyway. Two,

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Speaker 2: they're really not the kind of people who tell their

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Speaker 2: own story. They're not self promoters. They're almost the opposite

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Speaker 2: of self promoters. They give you a lit'll tell you

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Speaker 2: a little anc though it's funny. When I went to

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Speaker 2: write that piece about the first the first deep dive

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Speaker 2: I did in a single person. Arthur Allen was his name,

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Speaker 2: the oceanographer of the Coast Guard. I called him up,

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Speaker 2: said I want to come talk to you about what

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Speaker 2: you've done. Without knowing really much about what he'd done,

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Speaker 2: spent three days with him, with his wife, his kids,

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Speaker 2: you know, interviewing people around him, three full days with him.

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Speaker 2: At the end of three days, I was driving back

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Speaker 2: to the airport and he calls my cell phone. He says, says, hey,

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Speaker 2: you're a writer. And I said, yeah, yeah, I'm a writer.

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Speaker 2: Well you think you know? I sit there with a

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Speaker 2: notepad for three days taking notes, and I know. I

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Speaker 2: said I was a writer when I called you. He says,

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Speaker 2: but my son says that like you've written books that

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Speaker 2: have become movies, like you're like big time. And I said, well,

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Speaker 2: don't know if I'm big time, but I am a writer.

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Speaker 2: And he says, you're going to write about this, and

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Speaker 2: I said, yeah, I'm I going to write about this.

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Speaker 2: What do you think I was doing there for three days?

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Speaker 2: And he said, I just thought you were really interested

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Speaker 2: in how objects drift, And I thought, this is the

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Speaker 2: mind of someone He's so different from like the investment

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Speaker 2: banker you go to interview. He's so oblivious, he's interested

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Speaker 2: in his expertise. He's very narrow, he's not thinking like

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Speaker 2: how he appears to the world. He's open to help

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Speaker 2: people who come to him for help, but not thinking

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Speaker 2: at all, like I was going to turn him into

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Speaker 2: some celebrity and didn't know what to do with it

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Speaker 2: or care that they're that way. So they don't project.

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Speaker 2: So someone has to go project them for us because

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Speaker 2: they won't do it themselves. And there's a built in

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Speaker 2: problem in the government. The politicians and I hate to say,

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Speaker 2: I hate to use that word as a pejorative, but

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Speaker 2: it is just true that people who are campaigning and

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Speaker 2: running for elective office find it very useful to be

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Speaker 2: negative about the civil service and to blame them for

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Speaker 2: their or when problems occur. But there's not really any

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Speaker 2: upside for giving them credit. It's like the politicians want

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Speaker 2: the credit. So the people who are junior class senior

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Speaker 2: class president types who are out there waiving at the crowds,

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Speaker 2: have no real interest in selling the mechanism of the government.

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Speaker 2: And I think we all kind of know, you know,

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Speaker 2: the government we sent in the back of our minds.

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Speaker 2: This government is doing something. You know, it's it's kind

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Speaker 2: of magical. You get you turn on the tap and

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Speaker 2: you get cold water you can drink. You know, that's

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Speaker 2: that doesn't just happen and it comes from like a

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Speaker 2: reservoir from three hundred miles away or that you know, Uh,

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Speaker 2: the weather is predictable seven days out. Used to be

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Speaker 2: not predictable at all. Ah, that happened. It just becomes

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Speaker 2: like the the infrastructure of our lives. And I think

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Speaker 2: until it's threatened, you just it's like your parents. Until

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Speaker 2: they're threatened, you just think, well, they're there, Thank God,

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Speaker 2: they're there. Maybe, but I'm not going to pay much

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Speaker 2: attention to them. But the minute it becomes like, oh crap,

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Speaker 2: they're going to take it away, even if it's just

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Speaker 2: a hint of that, people kind of wake up and go, oh, oh, oh,

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Speaker 2: I need maybe I need to know about this.

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Speaker 1: You illuminated, Michael, why people don't appreciate the federal government,

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Speaker 1: why they often take it for granted. But it's even

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Speaker 1: worse than that. There's an enduring, an entrenched negative stereotype

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Speaker 1: in our culture about civil servants that they're stupid, and lazy,

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Speaker 1: as you describe it. How did that happen? I know

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Speaker 1: that they're not good at telling their stories or blowing

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Speaker 1: their own rams horns like politicians are. But where do

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Speaker 1: you think this negative perception comes from?

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Speaker 2: I mean, I think it's a it's a it's like

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Speaker 2: a it's a complicated question to answer, but I mean,

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Speaker 2: most most obviously, they don't do the thing that we

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Speaker 2: value in this culture, which is make money. They don't.

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Speaker 2: They don't have they're not successful people. They're not famous people.

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Speaker 2: They're not you know, they're not there. So they don't

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Speaker 2: have that going for them. They're also they're vulnerable because

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Speaker 2: the enterprise they work for is most complicated enterprise ever

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Speaker 2: created on in the history of the university, the United

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Speaker 2: States government, and they're spending now seven trillion dollars a

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Speaker 2: year there, and they're bound to be problems. You know.

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Speaker 2: It's just sort of like they're bound to be mistakes made,

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Speaker 2: and when they're made, it's sort of it's sort of

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Speaker 2: like it's assumed no mistakes will be made, and when

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Speaker 2: they're made, they get exposed and ridiculed and all the rest.

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Speaker 2: You know, Why else is it this one? I mean,

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Speaker 2: you know, I haven't really thought too much about how

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Speaker 2: this why Ronald Reagan could roll in, you know, forty

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Speaker 2: five years ago or whatever it was fifty years ago

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Speaker 2: and say the most you know, dangerous words in the

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Speaker 2: English languages, I'm from the government and I'm here to

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Speaker 2: help you.

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Speaker 1: Didn't he also say that the government is the problem.

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Speaker 2: Yeah, and the government, you know, there's this fantasy you

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Speaker 2: take it away and everything's going to be better, And

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Speaker 2: the truth is, you don't have markets without the government,

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Speaker 2: you don't have an awful lot of our economic growth

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Speaker 2: is driven by government private partnerships. But what you all,

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Speaker 2: you know, this is part of the reason they're so

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Speaker 2: easy to beat up on is a lot of what

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Speaker 2: they're doing is prevention. Like a lot of what they're

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Speaker 2: doing is stopping things from happening. And when you stop

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Speaker 2: something from happening, you don't get credit. You get credit

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Speaker 2: when you come after the bad thing has happened. So

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Speaker 2: there's an awful lot of work that's out there, I

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Speaker 2: don't know, stopping someone from getting a bomb on a plane.

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Speaker 2: Who do you think is doing that? I can tell

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Speaker 2: you who's doing that. There's a lab called a Livermore

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Speaker 2: lab that's like forty miles from my house, where they

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Speaker 2: are constantly experimenting with different sort of chemicals and ingredients

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Speaker 2: to see what you might be able to make a

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Speaker 2: bottom of. And as they whenever they find something new,

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Speaker 2: they program those machines that you put your bag through

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Speaker 2: to detect those things. And you don't see any of it.

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Speaker 2: But if they weren't there, you would notice. You know,

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Speaker 2: the FAA right, your plane doesn't crash if it doesn't,

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Speaker 2: you know, air safety is a you know, a miracle

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Speaker 2: of modern life. It's the government. But you're not getting

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Speaker 2: credit for the plane not crashing, so a lot I

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Speaker 2: think that's also part of it. It's sort of easy

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Speaker 2: to beat up on them because there's a lot of

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Speaker 2: their work is preventive, a lot of it is just

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Speaker 2: keeping us safe. And as I say, they're just not

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Speaker 2: doing the thing that's celebrated in the culture, which is

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Speaker 2: make money.

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Speaker 1: Meanwhile, the administration, as you know, I've thought about you

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Speaker 1: often with these DOGE government cuts, but even before DOGE

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Speaker 1: was created, they have not only encouraged this stereotype as

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Speaker 1: bureaucrats or government workers being stupid and lazy and extraneous,

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Speaker 1: if you will, but they've turned it into something more sinister.

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Speaker 1: Let me give you a quote that jd Vance said

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Speaker 1: on a podcast in twenty twenty one. If I was

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Speaker 1: giving Trump one piece of advice, it's fire every single

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Speaker 1: mid level bureaucrat, every civil servant in the administrative state,

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Speaker 1: and replace them with our people.

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Speaker 2: So it's just such a misconception of who these people

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Speaker 2: are in the first place, because it's probably true that

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Speaker 2: the government workers generally probably tilt more left than right,

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Speaker 2: but their politics are very hard to predict. You'd be

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Speaker 2: surprised who they voted for, I think. But the bigger

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Speaker 2: point is most of what they're doing is so nonpartisan.

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Speaker 2: It's like it's it's stuff that the Congress has allocated

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Speaker 2: money for because it's problems that needed to be dealt with,

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Speaker 2: and they're dealing with them. And the list is like

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Speaker 2: endless of what these problems are. But you know, you

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Speaker 2: know about air safety, but like there's all this stuff

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Speaker 2: you don't see. Rural America, for example, is propped up

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Speaker 2: by the Agriculture Department. Like there wouldn't be firehouses and

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Speaker 2: schools and all they would It would be a wasteland

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Speaker 2: without the spending from the Agriculture Department. And that's something

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Speaker 2: you can argue that we shouldn't have, but that argument's

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Speaker 2: been had by Congress, and it's authorized. The money and

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Speaker 2: the people who are the people who are in there

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Speaker 2: working are they're just trying to execute tasks and and like,

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Speaker 2: how is it, how is it partisan to like make

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Speaker 2: sure nuclear weapons don't explode when they they they shouldn't explode.

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Speaker 2: It's just it's such a misapprehendsion of what that enterprise

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Speaker 2: is and what they're doing. It's interesting because what they're

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Speaker 2: doing is accusing the existing workforce of being essentially political,

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Speaker 2: like their deep state. They're out to get us, when

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Speaker 2: in fact that it's not who they are. But what

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Speaker 2: they're trying to do is turn it into something. It's

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Speaker 2: very political. It's out to get the other side. And

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Speaker 2: it's taking fifty thousand jobs and turning them from career

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Speaker 2: civil service jobs to essentially patronage jobs that the Trump

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Speaker 2: administration can appoint not based on expertise, but based on loyalty.

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Speaker 1: How dangerous is that replacement in your view.

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Speaker 2: It's dangerous on a couple of levels. It's very dangerous,

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Speaker 2: and it is one it's going to make the government

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Speaker 2: a lot less effective because you're replacing people who actually

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Speaker 2: know things with people who don't and their main qualification

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Speaker 2: is they're just loyal with Donald Trump. That's not a

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Speaker 2: good place to start when you're solving complicated problems. But

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Speaker 2: it's dangerous in another way that if you actually succeed

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Speaker 2: in turning the federal government into what Trump advance say,

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Speaker 2: it is, turning it into this political weapon, it's hard

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Speaker 2: to know. You know, it's from there to like no

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Speaker 2: democracy is a half step, and so it's dangerous on

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Speaker 2: that level too, and it'll have this knock on effect.

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Speaker 2: And this is the knock on effect of a lot

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Speaker 2: of Republican rhetoric is you know, you disable, you villainize

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Speaker 2: this enterprise that's there to serve us all, you make

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Speaker 2: it less effective at what it's supposed to do. And

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Speaker 2: then you could point to it and say, look how

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Speaker 2: ineffective it is, Like the problem is government. Well, no,

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Speaker 2: the problem is how you run the government. The problem

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Speaker 2: is in government.

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Speaker 1: If you want to get smarter every morning with a

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Speaker 1: breakdown of the news and fascinating takes on health and

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Speaker 1: wellness and pop culture, sign up for our daily newsletter

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Speaker 1: Wake Up Call by going to Katiecuric dot Com. I'm

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Speaker 1: curious how you feel this kind of rhetoric, things like

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Speaker 1: weaponizing or demonizing the deep state, how that erodes the

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Speaker 1: public trust in our government and institutions in general.

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Speaker 2: I mean, I'm trying to think of some equivalent. Where

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Speaker 2: can you think of a product or a service or

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Speaker 2: that is just all it gets is negative publicity, and

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Speaker 2: it's like there's like a publicity machine designed to undermine it,

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Speaker 2: and that's all people here. I mean, it's just there's

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Speaker 2: no question that public there is this reflexive public opinion,

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Speaker 2: especially on the right, but not just on the right,

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Speaker 2: that like, oh, it's just government's waste, government's fraud. So

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Speaker 2: this would attracted me to somebody in the first place,

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Speaker 2: is I don't have any big stake in government. I

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Speaker 2: just saw that wasn't true because I wanted around the

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Speaker 2: government and saw what was there. And what's what's what's

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Speaker 2: shocking about it is whatever people believe because of what

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Speaker 2: they've heard from casual this kind of casual loose talk.

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Speaker 2: The opposite is kind of true that if you're looking

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Speaker 2: for waste or fraud, you were so much more likely

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Speaker 2: to find it in a private sector company than you

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Speaker 2: are in a in a government agency, especially fraud like that,

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Speaker 2: that the places are on a hair trigger or alert

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Speaker 2: for like people stealing money. You can't you know, you

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Speaker 2: can't you when you're on Wall Street and you wanted

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Speaker 2: to get business, you could, you know, take people to

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Speaker 2: strip clubs and get them front row seats to watch

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Speaker 2: the Mets and all that stuff. You can't buy a

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Speaker 2: sandwich for someone who works in the federal government. That

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Speaker 2: it is. So it is like and there and all

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Speaker 2: around these places are watchdogs whose job is to prevent

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Speaker 2: money from being stolen. And in fact, the first people

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Speaker 2: the Trumpe administation fired were those watchdogs. So that tells

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Speaker 2: you something about how much they care, actually care about

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Speaker 2: the fraud. The waste is more complicated because it's true that,

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Speaker 2: like there are some ways government does things that if

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Speaker 2: you were starting from scratch, that's not how you do them.

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Speaker 2: And there is, for sure ways to go in and

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Speaker 2: make it work work somewhat better. But the way but

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Speaker 2: the way to when that in that case, the way

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Speaker 2: to go in is with an appreciation of why it

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Speaker 2: works the way it is, because you're just gonna end

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Speaker 2: up recreating with what was created. If you don't understand

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Speaker 2: why it got the way it was. It's like, there

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Speaker 2: are reasons, there are reasons. It's like there's analyst bureaucracy

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Speaker 2: around contracting. You know, it's to revent the fraud kind

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Speaker 2: of thing. And it's maddening how it's done because basically

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Speaker 2: there's no trust. You know, it's a low trust environment.

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Speaker 2: And in a low trust environment, it's a very inefficient environment.

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Speaker 2: When you got to sign pieces of paper to get

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Speaker 2: an extra box to take the paper clips, you're going

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Speaker 2: to be less efficient. And if you can just go

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Speaker 2: to the storeroom and take one. So there are problems there,

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Speaker 2: but a lot of the wasteful problems will rise from

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Speaker 2: the mistrust about the institution. It's been sown into the

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Speaker 2: public mind by this rhetoric. I mean, let me ask

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Speaker 2: you a question. You're asking me questions, but I want

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Speaker 2: to ask you a question. Is it not if you

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Speaker 2: just back away from it? Kind of weird that we're

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Speaker 2: in a democracy where we elected people to do stuff,

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Speaker 2: and these things that got done by the government. It's

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Speaker 2: not like some autocrat did it. We the people did it,

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Speaker 2: and that we view the these civil servants, the instruments

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Speaker 2: of our will, as somehow our enemies, somehow like insiders

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Speaker 2: trying to bring us down. It's a really odd thing

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Speaker 2: for in a democracy for people to feel that way

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Speaker 2: about their government. And anyway, I didn't have it, As

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Speaker 2: I said, I came into this, I didn't have any

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Speaker 2: particular view. I'm not like some screaming liberal. I like

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Speaker 2: people who make money and none of that. It was

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Speaker 2: just I could not believe like the heroism basically in

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Speaker 2: the civil service, could not believe the quality of the

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Speaker 2: people that were engaged in such critical stuff, like the

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Speaker 2: society falls apart if they're not there. And I started

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Speaker 2: pulling my hair out when I realized, like, oh, they've

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Speaker 2: been doing this for thirty years and all they've heard is,

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Speaker 2: you know, abuse from the outside. It just like there's

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Speaker 2: something untrue about this. So my question for you is,

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Speaker 2: how do you explain this, Like it just seems really odd.

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Speaker 1: I think that government workers for as long as I

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Speaker 1: can remember, growing up in Arlington, Virginia, outside DC, where

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Speaker 1: a lot of people did work for the government, I

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Speaker 1: think there was an attitude that there was excess and

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Speaker 1: redundancy and inefficiency in the federal government. And I think

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Speaker 1: it's just been a stereotype that for whatever reason, has

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Speaker 1: been baked in yes to our national consciousness, and that's

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Speaker 1: but of course there are critical jobs. But I think

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Speaker 1: that there has always been the impression, Michael, that there

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Speaker 1: were extraneous jobs or jobs that weren't really necessary. And

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Speaker 1: I think the very word bureaucracy has gotten, you know,

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Speaker 1: has become a dirty word in the public's mind. And

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Speaker 1: with bureaucracy it means unnecessary levels of maloney that you

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Speaker 1: have to kind of get through. So I think all

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Speaker 1: those things have kind of come together to make people

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Speaker 1: feel fairly anti government. And I think to your point,

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Speaker 1: we haven't heard enough stories about civil servants. And I

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Speaker 1: also think there's something about having a job for life.

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Speaker 1: You know, this is all just kind of things that

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Speaker 1: when I was a kid growing up right outside DC,

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Speaker 1: like that some jobs are protected like tenure, when other

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Speaker 1: people are subjected to performance reviews, and there was a

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Speaker 1: feeling of a meritocracy. When you've got in the civil service,

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Speaker 1: you basically had a job for life. Yeah, I think

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Speaker 1: that probably explained some of the negative things that I've

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Speaker 1: heard about government workers.

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Speaker 2: Right, some of that's valid, and I can understand hostility

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Speaker 2: towards tenure. Basically they don't exactly have tenure. You can

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Speaker 2: fire a civil servant, you just have to have cause.

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Speaker 2: But I think at the I do think at the

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Speaker 2: bottom of this is some false kind of like false

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Speaker 2: ideas that people have in their heads about what goes

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Speaker 2: on inside the places and its relationship to the society.

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Speaker 2: So if you ask people that most I bet most

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Speaker 2: people say government just has been growing out of control.

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Speaker 2: For example, like it has gotten bigger and bigger and bigger.

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Speaker 2: Now it's true, our deficits have gotten bigger and bigger

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Speaker 2: and bigger. That's not the big generals, it's trunk. It's

431
00:23:56,640 --> 00:24:00,080
Speaker 2: like the civil service, not the military. Fifty years ago

432
00:24:00,320 --> 00:24:02,720
Speaker 2: was two point three million workers. It's still two point

433
00:24:02,720 --> 00:24:05,960
Speaker 2: three million workers. The society is you know, forty percent

434
00:24:06,000 --> 00:24:09,040
Speaker 2: bigger or whatever. So in relationship to the society, it

435
00:24:09,119 --> 00:24:13,680
Speaker 2: is shrunk. So people can flate like government spending, which

436
00:24:13,720 --> 00:24:17,359
Speaker 2: is a different thing on the government workforce. That the

437
00:24:17,400 --> 00:24:21,680
Speaker 2: fact that Elon Musk, when he goes in to say

438
00:24:21,960 --> 00:24:25,400
Speaker 2: to eliminate, to reduce, to cut two trillion dollars out

439
00:24:25,400 --> 00:24:29,000
Speaker 2: of the budget deficit, he said, and eliminate all this inefficiency,

440
00:24:29,680 --> 00:24:34,320
Speaker 2: finds himself cutting so he finds the cutting in such

441
00:24:34,320 --> 00:24:37,480
Speaker 2: a this he cutting just the civil service. But it's

442
00:24:37,520 --> 00:24:40,040
Speaker 2: such a small sliver of the actual spending that has

443
00:24:40,160 --> 00:24:43,480
Speaker 2: almost no effect. I mean, eighty six percent of government

444
00:24:43,520 --> 00:24:47,120
Speaker 2: spending is either interest payments on the debt, defense, or entitlements,

445
00:24:47,440 --> 00:24:50,360
Speaker 2: So it's only fourteen percent of the budget that's these

446
00:24:50,359 --> 00:24:56,000
Speaker 2: people anyway. So but that nobody says, oh, wait, he's

447
00:24:56,040 --> 00:24:58,879
Speaker 2: doing he's trying to cut a big chunk out of

448
00:24:58,880 --> 00:25:01,159
Speaker 2: the pie, but he's confined himself to a little slipper

449
00:25:01,200 --> 00:25:04,800
Speaker 2: of the pie. This is impossible, it will never happen. Instead,

450
00:25:04,840 --> 00:25:06,760
Speaker 2: people cheer and say, yeah, he's getting rid of all

451
00:25:06,760 --> 00:25:08,440
Speaker 2: of that, and we're going to get rid of our deficits.

452
00:25:09,320 --> 00:25:14,520
Speaker 2: It's just it's, I mean, we're ignorant. So here's another

453
00:25:14,600 --> 00:25:17,720
Speaker 2: answer to your question, like, how did we come to

454
00:25:17,800 --> 00:25:25,240
Speaker 2: this past? Why are these people so easily distorted by

455
00:25:25,240 --> 00:25:28,920
Speaker 2: the political process so that people think of them differently

456
00:25:29,000 --> 00:25:33,240
Speaker 2: than they actually are. The answer is, we've been afforded

457
00:25:33,320 --> 00:25:36,880
Speaker 2: that luxury that we've lived through a very long period

458
00:25:37,200 --> 00:25:41,120
Speaker 2: without great existential risk to ourselves. It hasn't been all

459
00:25:41,160 --> 00:25:45,520
Speaker 2: peace and prosperity, but by world historic standards, a lot

460
00:25:45,560 --> 00:25:48,320
Speaker 2: of peace and prosperity. We don't wake up thinking our

461
00:25:48,359 --> 00:25:52,120
Speaker 2: society is about to be invaded by barbarians or we're

462
00:25:52,160 --> 00:25:54,920
Speaker 2: all going to die because of a pandemic or whatever.

463
00:25:55,520 --> 00:25:58,880
Speaker 2: So we can afford to take the parents for granted.

464
00:25:59,080 --> 00:26:02,280
Speaker 2: You know, it's like we've been safe for so long

465
00:26:02,359 --> 00:26:05,280
Speaker 2: and we don't it's not till something really bad happens

466
00:26:05,320 --> 00:26:08,199
Speaker 2: that people don't realize why we needed this thing. And

467
00:26:08,359 --> 00:26:10,199
Speaker 2: what I worry is that's what has to happen, Like

468
00:26:10,240 --> 00:26:13,360
Speaker 2: something really bad is going to happen, and people are, oh,

469
00:26:13,359 --> 00:26:16,720
Speaker 2: that's why we had the government'll bring it back, And

470
00:26:17,000 --> 00:26:18,719
Speaker 2: it's a shame it has to come to that. And

471
00:26:18,760 --> 00:26:20,760
Speaker 2: the point of the book is, like, you know, just

472
00:26:20,800 --> 00:26:24,800
Speaker 2: read this seven random profiles from inside the government and

473
00:26:24,840 --> 00:26:27,320
Speaker 2: see if you can you can you can preserve that

474
00:26:27,640 --> 00:26:31,639
Speaker 2: bigotry you have about the civil servant, See if you can't, like,

475
00:26:32,359 --> 00:26:34,240
Speaker 2: see if you can avoid opening up your mind to

476
00:26:34,280 --> 00:26:37,200
Speaker 2: the possibility that this is actually a useful enterprise.

477
00:26:38,160 --> 00:26:40,439
Speaker 1: I want to talk to you about some of those essays,

478
00:26:40,520 --> 00:26:44,400
Speaker 1: and particularly the person you profile. But since you mentioned

479
00:26:44,440 --> 00:26:49,320
Speaker 1: Elon Musk, I have wondered, Michael, how you have felt

480
00:26:49,440 --> 00:26:54,440
Speaker 1: given the fifth risk, and given your interests in profiling

481
00:26:54,480 --> 00:26:59,560
Speaker 1: the federal workforce, how you have felt watching Elon Musk

482
00:26:59,640 --> 00:27:04,439
Speaker 1: and his so called doge Bros go in and just

483
00:27:05,560 --> 00:27:09,760
Speaker 1: wholesale fire tens of thousands of people.

484
00:27:10,720 --> 00:27:14,880
Speaker 2: Right in the very beginning, there was a little part

485
00:27:14,920 --> 00:27:16,760
Speaker 2: of me that was hopeful. And the little part of

486
00:27:16,760 --> 00:27:19,840
Speaker 2: me that was hopeful was it is true that the

487
00:27:19,880 --> 00:27:23,080
Speaker 2: government has been kind of starved young talent for a

488
00:27:23,119 --> 00:27:25,960
Speaker 2: long time. People, young bright, young people have not been

489
00:27:26,040 --> 00:27:29,840
Speaker 2: encouraged to go into government service, and particularly in the

490
00:27:29,840 --> 00:27:31,880
Speaker 2: tech world, because you could get paid so much better

491
00:27:31,960 --> 00:27:34,119
Speaker 2: just going and work for a Silicon Valley startup. And

492
00:27:34,160 --> 00:27:36,359
Speaker 2: the idea that he might channel some of this talent

493
00:27:36,440 --> 00:27:39,720
Speaker 2: into the government and actually fix some old and broken systems,

494
00:27:40,160 --> 00:27:42,720
Speaker 2: that was a I thought, maybe there's hope there, like,

495
00:27:42,880 --> 00:27:45,160
Speaker 2: but then when then they started doing what they were doing,

496
00:27:45,240 --> 00:27:50,440
Speaker 2: which is like cutting agencies, you know, like without explanation exactly,

497
00:27:50,680 --> 00:27:54,480
Speaker 2: and going in and randomly cutting seemingly big chunks of

498
00:27:54,480 --> 00:27:57,880
Speaker 2: the federal workforce without a whole lot of explanation about why,

499
00:27:58,000 --> 00:27:59,879
Speaker 2: except to say that they were cutting fat out of

500
00:27:59,880 --> 00:28:03,200
Speaker 2: the out of the budget. But so then I became

501
00:28:03,280 --> 00:28:05,640
Speaker 2: puzzled because what they said they were doing was clearly

502
00:28:05,680 --> 00:28:08,040
Speaker 2: not what they were doing. The first thing they said

503
00:28:08,040 --> 00:28:10,080
Speaker 2: they were doing was going after fraud. And when they

504
00:28:10,080 --> 00:28:12,840
Speaker 2: got rid of all the inspector generals at the agencies,

505
00:28:12,920 --> 00:28:16,840
Speaker 2: those people, they're not deep state bureaucrats who are there

506
00:28:16,880 --> 00:28:19,160
Speaker 2: to help fraud happen. They're there to point out fraud

507
00:28:19,200 --> 00:28:22,520
Speaker 2: to Congress. They are the refs, the cops on the beat.

508
00:28:22,800 --> 00:28:25,679
Speaker 2: So they got rid all the cops. So that's not

509
00:28:25,760 --> 00:28:27,560
Speaker 2: what you do. If you're trying to catch the crooks,

510
00:28:27,600 --> 00:28:29,000
Speaker 2: you don't get rid of all the cocks and then

511
00:28:29,080 --> 00:28:31,000
Speaker 2: the cops who know the most. So it was an

512
00:28:31,040 --> 00:28:33,280
Speaker 2: odd thing to do. So I thought, they're not going

513
00:28:33,280 --> 00:28:36,920
Speaker 2: after fraud, that's not what this is about. And when

514
00:28:37,000 --> 00:28:39,560
Speaker 2: with a waist, it was like, are you know the fat?

515
00:28:40,240 --> 00:28:42,280
Speaker 2: They were dealing with such a small part of the government.

516
00:28:42,320 --> 00:28:43,840
Speaker 2: They were never going to make that much of a dent.

517
00:28:44,080 --> 00:28:45,720
Speaker 2: So it was not about that they're not going to

518
00:28:45,800 --> 00:28:48,040
Speaker 2: like get the bud get rid of the budget deaf

519
00:28:48,040 --> 00:28:49,680
Speaker 2: as they're doing what they're doing. They're not going to

520
00:28:49,760 --> 00:28:51,680
Speaker 2: cut two trillion dollars like they claim they might. They

521
00:28:51,680 --> 00:28:53,760
Speaker 2: probably got to cut a hundred billion dollars it's like

522
00:28:54,000 --> 00:28:56,840
Speaker 2: they're dealing with rounding errors and so like, if they're

523
00:28:56,840 --> 00:28:59,760
Speaker 2: not doing what they say they're doing, or they're doing

524
00:28:59,800 --> 00:29:01,920
Speaker 2: it so badly, they might as well not be But

525
00:29:02,240 --> 00:29:04,880
Speaker 2: I don't think they're that dumb. Like, what is the motive?

526
00:29:05,840 --> 00:29:09,840
Speaker 2: And so far as I can tell, the motive is

527
00:29:09,880 --> 00:29:13,000
Speaker 2: to turn this enterprise that's supposed to be serving the

528
00:29:13,120 --> 00:29:17,160
Speaker 2: entire society and it's filled with these exquisite human beings

529
00:29:17,200 --> 00:29:20,479
Speaker 2: doing extremely complicated and important things. Is to turn this

530
00:29:20,520 --> 00:29:23,960
Speaker 2: into an instrument of personal political power for Elon Musk

531
00:29:23,960 --> 00:29:26,959
Speaker 2: and Donald Trump and so turn it into something that

532
00:29:27,040 --> 00:29:29,640
Speaker 2: just doesn't get in their way whenever they do whatever

533
00:29:29,720 --> 00:29:33,000
Speaker 2: they want to do, whatever that might be. And it's

534
00:29:33,040 --> 00:29:34,760
Speaker 2: hard to know how the size is going to react

535
00:29:34,760 --> 00:29:36,640
Speaker 2: to this, because it's been told for so long that

536
00:29:36,760 --> 00:29:40,120
Speaker 2: this government is so awful they mighty might just let

537
00:29:40,200 --> 00:29:43,160
Speaker 2: him get away with it. I'm not sure of that.

538
00:29:43,320 --> 00:29:45,840
Speaker 2: But so now I'm just sitting watching, like how are

539
00:29:45,840 --> 00:29:49,280
Speaker 2: we going to react? How upset are people going to be?

540
00:29:50,000 --> 00:29:51,600
Speaker 2: How much of a stand are they going to take?

541
00:29:51,880 --> 00:29:54,560
Speaker 2: Will Republicans in Congress have the nerve to stand up

542
00:29:54,600 --> 00:29:57,920
Speaker 2: and actually argue against this when they know it's wrong

543
00:29:58,360 --> 00:30:01,280
Speaker 2: or bad, and I just don't no. But I've become,

544
00:30:01,400 --> 00:30:03,880
Speaker 2: you know, in the course of the first six weeks

545
00:30:03,880 --> 00:30:07,680
Speaker 2: of the Trump administration, pretty cynical about them because I

546
00:30:07,720 --> 00:30:11,240
Speaker 2: don't see a whole lot of reason to it. Like

547
00:30:11,280 --> 00:30:13,440
Speaker 2: I don't see them doing things that I think, oh,

548
00:30:13,480 --> 00:30:16,880
Speaker 2: that's going to make us stronger. I see them doing

549
00:30:16,920 --> 00:30:20,120
Speaker 2: things that they're going to make them more powerful, but

550
00:30:20,400 --> 00:30:23,400
Speaker 2: at our expense. And I have this feeling. It's a

551
00:30:23,480 --> 00:30:26,880
Speaker 2: visceral feeling. I have a feelings. It's a feeling you

552
00:30:26,960 --> 00:30:29,600
Speaker 2: have when the risk in your life has just gone up.

553
00:30:30,680 --> 00:30:33,320
Speaker 2: It's a feeling that like, oh, we're all always kind

554
00:30:33,320 --> 00:30:36,480
Speaker 2: of playing Russian Roulette. They're always risks, but they're just

555
00:30:36,520 --> 00:30:39,040
Speaker 2: sticking Willy Nelly more bullets in the chamber of the gun.

556
00:30:39,920 --> 00:30:43,320
Speaker 2: That and we're now playing Russian Roulette with greater risk

557
00:30:43,360 --> 00:30:48,440
Speaker 2: of fatality. And I feel that So that's agitating because

558
00:30:48,480 --> 00:30:51,840
Speaker 2: it seems like wholly unnecessary to be inflicting this risk

559
00:30:51,920 --> 00:30:54,160
Speaker 2: on the population. You know, you go in and you

560
00:30:54,200 --> 00:30:58,280
Speaker 2: start firing air traffic controllers, or you start firing people

561
00:30:58,280 --> 00:31:00,920
Speaker 2: whose job it is to monitor the the cleanliness of

562
00:31:00,920 --> 00:31:03,240
Speaker 2: the wader, or you fire people whose job it is

563
00:31:03,680 --> 00:31:07,560
Speaker 2: overseas to monitor and control disease that might find its

564
00:31:07,560 --> 00:31:10,720
Speaker 2: way to our shores, or you fire the nuclear the

565
00:31:10,720 --> 00:31:13,240
Speaker 2: people in charge of the nuclear weapons. I mean, sometimes

566
00:31:13,240 --> 00:31:14,640
Speaker 2: they've done this and then they've said, oh, we made

567
00:31:14,680 --> 00:31:16,520
Speaker 2: a mistake and we're going to bring them back. But

568
00:31:16,560 --> 00:31:20,040
Speaker 2: there's been an awful lot of mucking around with the

569
00:31:20,120 --> 00:31:24,000
Speaker 2: mechanisms for controlling existential risk, and that makes just makes

570
00:31:24,040 --> 00:31:27,240
Speaker 2: me really uneasy. Like so I don't don't I don't

571
00:31:27,280 --> 00:31:29,160
Speaker 2: really feel good about it. I wrote a note. I mean,

572
00:31:29,200 --> 00:31:30,880
Speaker 2: I don't know where you got it. I wrote elon muskin.

573
00:31:30,960 --> 00:31:33,200
Speaker 2: Note said, like, if you're so sure this is right,

574
00:31:33,240 --> 00:31:35,160
Speaker 2: I'd love to come to sit and watch and you

575
00:31:35,160 --> 00:31:37,640
Speaker 2: can explain to me why this is. This is smart.

576
00:31:37,880 --> 00:31:41,240
Speaker 2: I've spent a lot of time inside this institution, a

577
00:31:41,280 --> 00:31:43,920
Speaker 2: lot more than you. Happy to come and like talk

578
00:31:43,960 --> 00:31:45,440
Speaker 2: to you about it. And I didn't get a response.

579
00:31:46,240 --> 00:31:47,880
Speaker 1: I was going to ask if he wrote you back,

580
00:31:47,920 --> 00:31:50,800
Speaker 1: but you just told me it seems like the whole

581
00:31:50,920 --> 00:31:54,480
Speaker 1: tech adage of moving fast and breaking things right, being

582
00:31:54,560 --> 00:31:59,440
Speaker 1: complete disruptors is what is at play here. Well, what

583
00:31:59,560 --> 00:32:03,640
Speaker 1: strikes me is it doesn't seem that this is being

584
00:32:03,720 --> 00:32:07,520
Speaker 1: done reducing government in any kind of thoughtful way, and

585
00:32:07,560 --> 00:32:13,080
Speaker 1: if anything, it is so insulting and demoralizing and demeaning

586
00:32:13,480 --> 00:32:16,600
Speaker 1: to some of these public servants who have dedicated their

587
00:32:16,680 --> 00:32:21,400
Speaker 1: lives to their area of expertise. And not surprisingly I

588
00:32:21,600 --> 00:32:23,760
Speaker 1: just read that many of them are dealing with some

589
00:32:23,880 --> 00:32:28,520
Speaker 1: serious mental health issues. They're also getting abused online, and

590
00:32:28,880 --> 00:32:33,240
Speaker 1: these are people who were not seeking out attention. I

591
00:32:33,280 --> 00:32:36,360
Speaker 1: don't understand why this is being done with a sledgehammer

592
00:32:36,400 --> 00:32:39,440
Speaker 1: and not a scalpel, but maybe this is just not

593
00:32:39,560 --> 00:32:41,160
Speaker 1: Elon Musk's m O.

594
00:32:42,160 --> 00:32:46,360
Speaker 2: Why it's being done with such malice is that it's malicious, right,

595
00:32:47,040 --> 00:32:49,640
Speaker 2: and there is there's a there's a point to there's

596
00:32:49,680 --> 00:32:53,440
Speaker 2: a point to be made here about like his MO,

597
00:32:53,840 --> 00:32:57,600
Speaker 2: how he how he operates. I'm sure most people think

598
00:32:57,600 --> 00:33:00,880
Speaker 2: Elon Musk is like an incredibly smart guy, and in

599
00:33:00,960 --> 00:33:03,320
Speaker 2: some ways, I'm sure he is incredibly smart, but that

600
00:33:03,320 --> 00:33:06,600
Speaker 2: doesn't mean he's like universally smart, doesn't mean he's like

601
00:33:06,720 --> 00:33:12,800
Speaker 2: good at everything. And he's actually not demonstrated that he's

602
00:33:12,880 --> 00:33:17,160
Speaker 2: all that good at managing a large institution. He's really

603
00:33:17,200 --> 00:33:22,400
Speaker 2: good at products like peddling products. He's but he looked

604
00:33:22,560 --> 00:33:26,600
Speaker 2: he took Twitter, which was, you know, whatever it was,

605
00:33:26,640 --> 00:33:30,760
Speaker 2: it was a successful issue business. He bought it, and

606
00:33:31,000 --> 00:33:33,239
Speaker 2: he's reduced its value by more than half. I mean,

607
00:33:33,280 --> 00:33:35,960
Speaker 2: anybody who invested alongside of him has lost sixty percent

608
00:33:36,040 --> 00:33:38,000
Speaker 2: of their money. And he did it much the same

609
00:33:38,040 --> 00:33:40,680
Speaker 2: way he ran, and he came into this existing institution.

610
00:33:40,920 --> 00:33:43,680
Speaker 2: I'm so smart. All you all are fired unless you

611
00:33:43,720 --> 00:33:48,239
Speaker 2: can prove that you belong here. Humiliated everybody, and that

612
00:33:48,280 --> 00:33:52,640
Speaker 2: doesn't seem to have worked out very well. And I'd

613
00:33:52,680 --> 00:33:54,600
Speaker 2: like to hear You're not hearing any of these voices

614
00:33:54,600 --> 00:33:57,280
Speaker 2: because everybody's scared of Donald Trump. But I'd love to

615
00:33:57,360 --> 00:34:02,160
Speaker 2: hear with people who are genuinely gifted running big, complicated institutions,

616
00:34:02,440 --> 00:34:05,160
Speaker 2: like people who run big corporations. Think of this as

617
00:34:05,160 --> 00:34:08,719
Speaker 2: a management style. It's not something you see in successful

618
00:34:08,840 --> 00:34:13,680
Speaker 2: it's successful big companies. The CEO doesn't run insulting the employees,

619
00:34:13,960 --> 00:34:16,360
Speaker 2: telling them how valueless they are and all the rest.

620
00:34:16,680 --> 00:34:20,720
Speaker 2: It's that's that's not historically been like a recipe for success.

621
00:34:21,040 --> 00:34:25,760
Speaker 2: Why would it work here? And on top of it,

622
00:34:25,920 --> 00:34:29,840
Speaker 2: maybe that maybe in some weird corporation might work, but

623
00:34:29,880 --> 00:34:31,759
Speaker 2: it's definitely not going to work in a workforce where

624
00:34:31,760 --> 00:34:34,479
Speaker 2: you can't actually pay people very much like that. They're

625
00:34:34,520 --> 00:34:37,279
Speaker 2: working there. They're not there for the money, they're not

626
00:34:37,320 --> 00:34:39,600
Speaker 2: there for the fame. They're there if they're the best

627
00:34:39,600 --> 00:34:42,160
Speaker 2: people for the mission. And so if you're going to

628
00:34:42,200 --> 00:34:44,839
Speaker 2: come in and like undermine their sense of selves and

629
00:34:44,960 --> 00:34:47,799
Speaker 2: undermine the mission, I mean, that's just got to be

630
00:34:47,880 --> 00:34:51,560
Speaker 2: just especially toxic in a in the government environment. So

631
00:34:51,719 --> 00:34:54,600
Speaker 2: I think, you know, I suspect that it's going to

632
00:34:54,640 --> 00:34:58,000
Speaker 2: all end so badly that we'll look back and say,

633
00:34:58,040 --> 00:35:00,319
Speaker 2: how do we let that happen? And we'll go to

634
00:35:00,320 --> 00:35:04,480
Speaker 2: fix the things he broke. But you never know, because

635
00:35:04,520 --> 00:35:06,680
Speaker 2: we have a world where people believe all kinds of

636
00:35:06,719 --> 00:35:09,480
Speaker 2: stuff that isn't true, and people will be being told

637
00:35:09,480 --> 00:35:11,080
Speaker 2: that this was a big success even if it's a

638
00:35:11,080 --> 00:35:14,200
Speaker 2: big failure. My biggest fear in a funny way in

639
00:35:14,200 --> 00:35:16,479
Speaker 2: the back of my head right now, and I'm thinking about,

640
00:35:16,520 --> 00:35:19,000
Speaker 2: like what if I write something else, what purpose would

641
00:35:19,000 --> 00:35:24,080
Speaker 2: it serve. My theory is the bad thing happens because

642
00:35:24,080 --> 00:35:27,600
Speaker 2: of something they've disabled in government. The mechanism for preventing

643
00:35:27,640 --> 00:35:31,560
Speaker 2: the bad thing, whatever the bad thing is, was disabled,

644
00:35:32,000 --> 00:35:34,640
Speaker 2: and the bad thing happened, and it can be traced

645
00:35:34,640 --> 00:35:38,080
Speaker 2: by a rational person directly back to what Elon Musk

646
00:35:38,120 --> 00:35:41,160
Speaker 2: and Donald Trump have just done, but that after the

647
00:35:41,200 --> 00:35:45,440
Speaker 2: bad thing happens, a narrative of war follows and their

648
00:35:45,560 --> 00:35:48,719
Speaker 2: side gets to make up all kinds of facts and

649
00:35:48,840 --> 00:35:50,799
Speaker 2: say that, no, we didn't have anything to do with

650
00:35:51,120 --> 00:35:53,160
Speaker 2: the bad thing. The bad thing was the response with

651
00:35:53,200 --> 00:35:55,919
Speaker 2: the responsibility of the deep state, which we haven't rooted out,

652
00:35:56,000 --> 00:35:59,680
Speaker 2: or however they frame it. I'm trying to think, how

653
00:35:59,680 --> 00:36:01,439
Speaker 2: do you vent them from being able to do that?

654
00:36:01,600 --> 00:36:04,320
Speaker 2: How do you make sure that when the bad thing happens,

655
00:36:04,320 --> 00:36:07,760
Speaker 2: everybody understands it was their fault. I am groping towards

656
00:36:07,800 --> 00:36:11,280
Speaker 2: like what the next literary response is to this this book.

657
00:36:11,280 --> 00:36:13,120
Speaker 2: It's funny. The timing of this book is so funny,

658
00:36:13,160 --> 00:36:16,400
Speaker 2: just because like if everybody read it, you put it

659
00:36:16,400 --> 00:36:19,120
Speaker 2: in the hands of just red state people and made

660
00:36:19,160 --> 00:36:20,880
Speaker 2: them read it, and so you can think whatever you

661
00:36:20,880 --> 00:36:22,640
Speaker 2: think about it, but you got to read it. I

662
00:36:22,680 --> 00:36:24,239
Speaker 2: do think a lot of people would say, yeah, I know,

663
00:36:24,280 --> 00:36:26,280
Speaker 2: good people work in government. Yeah it's not as simple

664
00:36:26,320 --> 00:36:28,279
Speaker 2: as like it, but it's just like that's not what

665
00:36:28,320 --> 00:36:32,160
Speaker 2: they hear every day. And so I do think there's

666
00:36:32,200 --> 00:36:35,359
Speaker 2: some hope of changing shifting the narrative a bit.

667
00:36:53,600 --> 00:36:57,120
Speaker 1: Michael, I'm wondering if you have found it hypocritical that

668
00:36:57,239 --> 00:37:00,799
Speaker 1: Elon must praises private sector led in a but a

669
00:37:00,840 --> 00:37:04,280
Speaker 1: lot of these breakthroughs come from NASA and the Department

670
00:37:04,320 --> 00:37:07,759
Speaker 1: of Energy, and he couldn't do what he does without them.

671
00:37:08,360 --> 00:37:12,240
Speaker 2: It's sinister because it's not just typic critical. He's claiming

672
00:37:12,320 --> 00:37:16,319
Speaker 2: credit for stuff he doesn't deserve credit for. Not that

673
00:37:16,400 --> 00:37:19,640
Speaker 2: he doesn't deserve credit for some stuff, but like he says,

674
00:37:19,719 --> 00:37:22,280
Speaker 2: he was the founder of Tesla and the founder of PayPal,

675
00:37:22,320 --> 00:37:26,120
Speaker 2: and he wasn't someone else founded the company. He came in. Tesla.

676
00:37:26,960 --> 00:37:30,920
Speaker 2: Isn't just the triumph of the private sector that Tesla

677
00:37:31,160 --> 00:37:34,760
Speaker 2: does not get off the ground without a four hundred

678
00:37:34,760 --> 00:37:37,920
Speaker 2: and fifty million dollar loan, our loan guarantee from the

679
00:37:37,960 --> 00:37:41,839
Speaker 2: Department of Energy. At the time, he said this saved us,

680
00:37:41,880 --> 00:37:44,200
Speaker 2: and other people at Tesla said we just wouldn't exist

681
00:37:44,239 --> 00:37:47,040
Speaker 2: without this. It was like a little bit of a

682
00:37:47,080 --> 00:37:50,080
Speaker 2: moonshot technology, and the Department of Energy has a little

683
00:37:50,320 --> 00:37:54,160
Speaker 2: has two a couple of programs that back moonshot technologies,

684
00:37:54,680 --> 00:37:58,560
Speaker 2: and they've had astonishing success with it, and it's true

685
00:37:58,560 --> 00:38:01,680
Speaker 2: of a lot of our economy. It's that it especially

686
00:38:01,680 --> 00:38:06,040
Speaker 2: a lot of innovation, it starts with some public private partnership.

687
00:38:06,480 --> 00:38:09,200
Speaker 2: So to try to pitch people on the idea this

688
00:38:09,239 --> 00:38:11,280
Speaker 2: is all a bunch of smart guys in Silicon Valley

689
00:38:11,320 --> 00:38:14,000
Speaker 2: who'd be even who'd be doing even greater things if

690
00:38:14,000 --> 00:38:18,040
Speaker 2: the government wasn't in their way, is a complete misreading

691
00:38:18,080 --> 00:38:21,120
Speaker 2: of what has happened. But also it's very self serving.

692
00:38:21,160 --> 00:38:23,400
Speaker 2: It's like, now I'm on top, I'm gonna I'm going

693
00:38:23,440 --> 00:38:26,640
Speaker 2: to disable this mechanism for like people coming up from

694
00:38:26,640 --> 00:38:31,319
Speaker 2: beneath me to challenge me, and and I'm gonna I'm

695
00:38:31,360 --> 00:38:34,160
Speaker 2: a swarm around telling the story that I'm basically responsible

696
00:38:34,160 --> 00:38:34,680
Speaker 2: for all this.

697
00:38:35,800 --> 00:38:37,680
Speaker 1: Not a big fan of Blon, must are you?

698
00:38:38,280 --> 00:38:40,919
Speaker 2: I mean less and less? So I didn't have a view.

699
00:38:40,960 --> 00:38:43,440
Speaker 2: I didn't I wasn't born with the animist towards him.

700
00:38:43,480 --> 00:38:45,880
Speaker 2: But I think he's been very, very bad for the

701
00:38:45,920 --> 00:38:52,239
Speaker 2: country and any It's just to tell when someone is

702
00:38:52,320 --> 00:38:55,280
Speaker 2: lying all the time, it's just like when they're putting

703
00:38:55,400 --> 00:39:01,160
Speaker 2: lies out constantly, it's just that this this underlying rot

704
00:39:01,760 --> 00:39:05,560
Speaker 2: and they'll they're all these lies about what they've achieved

705
00:39:05,640 --> 00:39:08,839
Speaker 2: in the government when they haven't achieved them. There are

706
00:39:08,880 --> 00:39:12,160
Speaker 2: lies about other people and the other thing's offensive about him.

707
00:39:12,239 --> 00:39:14,920
Speaker 2: He's a bully. You know, He's got this platform and

708
00:39:14,920 --> 00:39:18,279
Speaker 2: he'll and he can turn his fans against anybody at

709
00:39:18,320 --> 00:39:23,160
Speaker 2: any time, and does it routinely, you know, outing civil

710
00:39:23,200 --> 00:39:26,759
Speaker 2: servants by name disgusting. I mean, it's just disgusting. And

711
00:39:26,840 --> 00:39:29,360
Speaker 2: so I think, you know, I think he's a bully,

712
00:39:29,960 --> 00:39:32,279
Speaker 2: and I don't react. I just don't react very well

713
00:39:32,320 --> 00:39:32,760
Speaker 2: to bullies.

714
00:39:33,800 --> 00:39:36,720
Speaker 1: Getting back to your book, Who Is Government, The Untold

715
00:39:36,800 --> 00:39:40,200
Speaker 1: Story of Public Service? You, as you mentioned, got a

716
00:39:40,280 --> 00:39:44,160
Speaker 1: number of great writers to profile different government workers, and

717
00:39:44,280 --> 00:39:48,319
Speaker 1: you picked someone named Christopher Mark. You met him, I guess,

718
00:39:48,560 --> 00:39:52,000
Speaker 1: via something called the Sammy's when you described as the

719
00:39:52,040 --> 00:39:56,080
Speaker 1: Oscars for Public Service. Out of the five hundred fifty

720
00:39:56,200 --> 00:39:59,200
Speaker 1: names on that list, what made you stop in your

721
00:39:59,239 --> 00:40:01,359
Speaker 1: tracks when came across Chris Mark?

722
00:40:02,080 --> 00:40:04,319
Speaker 2: So, Chrismak cannot want any award. When I met him,

723
00:40:04,320 --> 00:40:07,360
Speaker 2: it was just a list of nominees, right, And what

724
00:40:07,520 --> 00:40:10,719
Speaker 2: made me stop was he was the one nominee where

725
00:40:10,760 --> 00:40:15,880
Speaker 2: there was some trace of personal information, some trace of

726
00:40:16,239 --> 00:40:19,080
Speaker 2: a human being that the way the nominations were laid out.

727
00:40:19,120 --> 00:40:20,880
Speaker 2: It was a couple of sentences, and it was like

728
00:40:21,840 --> 00:40:27,520
Speaker 2: Joe Schmoe from the FBI discovered and disrupted a child

729
00:40:27,680 --> 00:40:30,719
Speaker 2: sex trafficking ring. And then they moved on not telling

730
00:40:30,760 --> 00:40:33,480
Speaker 2: you anything about Joe Schmoe. And it got the Christopher

731
00:40:33,520 --> 00:40:36,719
Speaker 2: Mark and it said, Christopher Mark inside the Department of

732
00:40:36,800 --> 00:40:40,360
Speaker 2: Labor has solved the problem of coal miner whos collapsing

733
00:40:40,400 --> 00:40:43,040
Speaker 2: on the heads of coal miners, a problem which killed

734
00:40:43,080 --> 00:40:46,799
Speaker 2: fifty thousand coal miners in the last century. And then

735
00:40:46,840 --> 00:40:50,000
Speaker 2: it said Christopher Mark is a former coal miner. And

736
00:40:50,080 --> 00:40:53,120
Speaker 2: I thought there's a story here. I mean, there's probably

737
00:40:53,120 --> 00:40:56,520
Speaker 2: a story everywhere, but like, how does a former coal

738
00:40:56,560 --> 00:40:59,240
Speaker 2: miner get himself in the position of solving was probably

739
00:40:59,400 --> 00:41:02,520
Speaker 2: a really tech and a complicated problem. And I had

740
00:41:02,560 --> 00:41:05,239
Speaker 2: assumed that, like he had a personal mode, he did

741
00:41:05,280 --> 00:41:07,080
Speaker 2: have personal motivation, but I assumed the wrong one. I

742
00:41:07,080 --> 00:41:08,840
Speaker 2: assuming he like grew up in West Virginia and his

743
00:41:08,960 --> 00:41:11,600
Speaker 2: dad had been killed by a falling roof for something

744
00:41:11,680 --> 00:41:14,880
Speaker 2: like that. So that's what got me to him. But

745
00:41:16,280 --> 00:41:19,359
Speaker 2: then the story ended up being wildly different and even

746
00:41:19,400 --> 00:41:21,239
Speaker 2: more interesting than I expected.

747
00:41:21,719 --> 00:41:24,680
Speaker 1: He grew up in Princeton, New Jersey. He wasn't from

748
00:41:24,680 --> 00:41:26,520
Speaker 1: West Virginia at all, No, he was.

749
00:41:26,719 --> 00:41:30,120
Speaker 2: He grew up in an upper middle class family, child

750
00:41:30,160 --> 00:41:34,560
Speaker 2: of a Princeton professor, and had rebelled against his father

751
00:41:36,600 --> 00:41:38,680
Speaker 2: kind of it was a kind of lefty rebellion against

752
00:41:38,760 --> 00:41:42,640
Speaker 2: his bourgeois father in the late sixties early seventies and

753
00:41:42,680 --> 00:41:44,759
Speaker 2: set out to become be a working man rather than

754
00:41:44,800 --> 00:41:47,440
Speaker 2: go to Harvard or Princeton, which he could have done.

755
00:41:47,600 --> 00:41:49,960
Speaker 2: And what then I find all this out like the

756
00:41:49,960 --> 00:41:52,440
Speaker 2: first thirty minutes, and this just blew me away. His

757
00:41:52,680 --> 00:41:57,760
Speaker 2: dad had become famous as a civil engineer for building

758
00:41:58,040 --> 00:42:02,640
Speaker 2: technology that analyzed kept the roofs of Gothic cathedrals from falling.

759
00:42:03,239 --> 00:42:05,600
Speaker 2: And he was so good at it, I mean Robert

760
00:42:05,600 --> 00:42:07,760
Speaker 2: Marcus's name, you can go. There were like TV shows

761
00:42:07,760 --> 00:42:10,200
Speaker 2: made about it. But he's so good that he could

762
00:42:10,239 --> 00:42:14,160
Speaker 2: like predict where in the Sharps Cathedral the stones would

763
00:42:14,160 --> 00:42:18,719
Speaker 2: be crumbling because the designers made a mistake. And so

764
00:42:18,960 --> 00:42:21,080
Speaker 2: it was like he was answering question everybody has who

765
00:42:21,120 --> 00:42:23,399
Speaker 2: goes to those gorgeous buildings, like what keeps the roof off?

766
00:42:23,800 --> 00:42:26,080
Speaker 2: And the son said, put a middle finger in the

767
00:42:26,080 --> 00:42:28,160
Speaker 2: air of the father when he was seventeen years old,

768
00:42:28,320 --> 00:42:32,359
Speaker 2: left home, went away and started working in factories and

769
00:42:32,400 --> 00:42:35,400
Speaker 2: warehouses and ends up working in a coal mine, thinking

770
00:42:35,440 --> 00:42:36,960
Speaker 2: I'm not going to have anything to do with what

771
00:42:37,000 --> 00:42:40,800
Speaker 2: my father did, and then realizes the roof step fall

772
00:42:40,520 --> 00:42:45,040
Speaker 2: and killed me and goes and he's very clever, and

773
00:42:45,120 --> 00:42:48,560
Speaker 2: the intellectual journey's wild. But how he figures out how

774
00:42:48,600 --> 00:42:50,680
Speaker 2: to keep roofs from collapsing on cole Myers is his

775
00:42:50,760 --> 00:42:53,799
Speaker 2: own story. But what's even wilder is when I get

776
00:42:53,880 --> 00:42:56,200
Speaker 2: him and I hear this story, I say, wow, you

777
00:42:56,280 --> 00:42:57,880
Speaker 2: rebelled against your dad and then you kind of like

778
00:42:57,880 --> 00:42:59,759
Speaker 2: went in your dad's line of work. You all about

779
00:42:59,760 --> 00:43:02,040
Speaker 2: it keeps the roof up, and he goes, that is

780
00:43:02,120 --> 00:43:04,480
Speaker 2: not true. What I did had nothing to do with

781
00:43:04,520 --> 00:43:07,600
Speaker 2: my father. She was like, nope, no, no, And I said,

782
00:43:08,440 --> 00:43:11,640
Speaker 2: this is a character. He's got a little bit of himself.

783
00:43:11,680 --> 00:43:15,279
Speaker 2: He doesn't fully understand. And I know he's great. I mean,

784
00:43:15,280 --> 00:43:17,880
Speaker 2: he was really great fun to write about.

785
00:43:18,800 --> 00:43:23,399
Speaker 1: And theirs similar stories are very inspiring stories by all

786
00:43:23,400 --> 00:43:26,600
Speaker 1: these other writers in the book. Can you just tell

787
00:43:26,680 --> 00:43:27,960
Speaker 1: us some of your favorites.

788
00:43:28,840 --> 00:43:30,319
Speaker 2: It would take a long time to go there all

789
00:43:30,360 --> 00:43:32,040
Speaker 2: of them, but I'll tell you who the writers are,

790
00:43:32,080 --> 00:43:36,240
Speaker 2: because it's an illustrious class. It's John Lanchester, Dave Eggers,

791
00:43:36,280 --> 00:43:40,919
Speaker 2: Sarah val Casey Spp, Geraldine Brooks, and camal Bell and

792
00:43:41,360 --> 00:43:45,319
Speaker 2: Casey Sepp in the New Yorker young writer. She's going

793
00:43:45,320 --> 00:43:47,920
Speaker 2: to be very famous one day. She's a little famous already.

794
00:43:48,320 --> 00:43:50,600
Speaker 2: She I'll tell you her story. She found a guy

795
00:43:51,600 --> 00:43:54,080
Speaker 2: inside the Department of Veterans Affairs. I don't know if

796
00:43:54,120 --> 00:43:57,279
Speaker 2: he's still there. They've goutted it, but his name is

797
00:43:57,360 --> 00:44:01,799
Speaker 2: Ron Walters, and Alters had walked into a job that

798
00:44:01,920 --> 00:44:04,759
Speaker 2: is a kind of sacred duty. It's caring for the

799
00:44:04,880 --> 00:44:11,200
Speaker 2: national cemeteries. It's it's providing the experience for the families

800
00:44:11,680 --> 00:44:16,600
Speaker 2: of veterans when they bury their dead. And when he

801
00:44:16,719 --> 00:44:19,200
Speaker 2: comes into it, and this is like twenty years ago,

802
00:44:19,800 --> 00:44:24,520
Speaker 2: the customer approval rating is not great. It's kind of eh.

803
00:44:24,680 --> 00:44:29,440
Speaker 2: And he sets about attacking the problem with such panache

804
00:44:30,040 --> 00:44:33,920
Speaker 2: that kind of a decade. In the surveys that the

805
00:44:34,000 --> 00:44:37,480
Speaker 2: Universe in Michigan does of customer satisfaction across the economy,

806
00:44:37,520 --> 00:44:41,000
Speaker 2: and they measure satisfaction of government agencies as well as

807
00:44:41,000 --> 00:44:44,440
Speaker 2: with like private companies, so Amazon and the Department of

808
00:44:44,480 --> 00:44:47,400
Speaker 2: Agriculture is in these surveys. By the time Round Walters

809
00:44:47,440 --> 00:44:51,840
Speaker 2: is done, this National Cemetery's burial program has the highest

810
00:44:51,840 --> 00:44:57,560
Speaker 2: customer satisfaction of empty institution in our country. And nobody

811
00:44:57,560 --> 00:44:59,960
Speaker 2: knows who he is. He doesn't he's not out there

812
00:45:00,120 --> 00:45:02,800
Speaker 2: telling people how to manage businesses because he's a genius manager,

813
00:45:02,800 --> 00:45:05,719
Speaker 2: though he obviously is. All he cares about is this

814
00:45:05,760 --> 00:45:09,080
Speaker 2: sacred duty we have to our veterans. It's a moving story.

815
00:45:09,160 --> 00:45:11,319
Speaker 2: I mean, it's like who this guy is and why

816
00:45:11,360 --> 00:45:13,040
Speaker 2: he did what he did, and then he did what

817
00:45:13,120 --> 00:45:16,080
Speaker 2: he did and all I mean, I think she just

818
00:45:16,160 --> 00:45:18,480
Speaker 2: kind of scratched the surface in some places, because I

819
00:45:18,560 --> 00:45:20,920
Speaker 2: do think that the Harvard Business School should go figure

820
00:45:20,960 --> 00:45:24,799
Speaker 2: out what he did, because it's an amazing transformation like

821
00:45:25,320 --> 00:45:29,640
Speaker 2: the private, public, whatever sector to do that with a

822
00:45:29,840 --> 00:45:33,440
Speaker 2: very delicate problem. But you never hear about it that happened,

823
00:45:33,880 --> 00:45:37,399
Speaker 2: and you never hear about it, Like if that had

824
00:45:37,440 --> 00:45:41,520
Speaker 2: happened in one of Elon Musk's company or got amazing

825
00:45:41,719 --> 00:45:45,120
Speaker 2: Donald Trump's companies, Donald Trump would be telling you how

826
00:45:45,160 --> 00:45:47,799
Speaker 2: he took the company from here to there, and you'd

827
00:45:47,800 --> 00:45:50,279
Speaker 2: be celebrating Donald Trump as a manager, and you know,

828
00:45:50,360 --> 00:45:52,600
Speaker 2: but that's different personality.

829
00:45:53,480 --> 00:45:57,160
Speaker 1: I'm wondering if you're hoping that this book will inspire

830
00:45:57,280 --> 00:46:02,040
Speaker 1: more people at this terrible time for government workers to

831
00:46:02,120 --> 00:46:06,680
Speaker 1: become public servants, because even now, people younger than thirty

832
00:46:07,080 --> 00:46:11,360
Speaker 1: represent only seven percent of a full time civil service,

833
00:46:11,719 --> 00:46:15,720
Speaker 1: despite being twenty percent of the overall US labor force,

834
00:46:16,600 --> 00:46:20,120
Speaker 1: and sixty eight percent say they'd never consider pursuing a

835
00:46:20,200 --> 00:46:21,719
Speaker 1: non military federal job.

836
00:46:22,640 --> 00:46:24,680
Speaker 2: Yeah, now you wonder why, right, because all they hear

837
00:46:24,800 --> 00:46:28,120
Speaker 2: is what they hear. So this is what I hope for.

838
00:46:28,400 --> 00:46:32,319
Speaker 2: I hope that young people read the book or read

839
00:46:32,320 --> 00:46:36,359
Speaker 2: these stories somehow, some way, and they don't rule out

840
00:46:36,480 --> 00:46:39,480
Speaker 2: the possibility that they'll be called to serve. That they

841
00:46:39,480 --> 00:46:43,319
Speaker 2: will develop their skills and whatever feel they choose. But

842
00:46:43,440 --> 00:46:46,560
Speaker 2: if there comes a time when those skills clearly are

843
00:46:46,600 --> 00:46:49,320
Speaker 2: needed by the country, they don't just turn up their

844
00:46:49,360 --> 00:46:51,239
Speaker 2: nose at the federal government because they think the federal

845
00:46:51,280 --> 00:46:54,040
Speaker 2: government is all a waste. That they realize it's just

846
00:46:54,080 --> 00:46:57,239
Speaker 2: the opposite, that this is the place where you can

847
00:46:57,280 --> 00:47:01,239
Speaker 2: have the greatest impact with those You won't make a

848
00:47:01,239 --> 00:47:03,480
Speaker 2: lot of money, and then you won't just make money,

849
00:47:03,920 --> 00:47:07,759
Speaker 2: but you will change lives save lives, and if that

850
00:47:07,920 --> 00:47:10,799
Speaker 2: idea is still kind of alive, there's hope. You know,

851
00:47:10,920 --> 00:47:13,360
Speaker 2: it's like and it is alive. It's very clearly alive.

852
00:47:14,080 --> 00:47:16,759
Speaker 2: These are role models we're writing about. And it wasn't

853
00:47:16,840 --> 00:47:19,040
Speaker 2: rigged that way. It wasn't like I didn't tell the writers,

854
00:47:19,120 --> 00:47:21,760
Speaker 2: go find a role model. I said, go find a story.

855
00:47:22,280 --> 00:47:25,320
Speaker 2: And this same kind of story just kept presenting itself

856
00:47:25,360 --> 00:47:28,480
Speaker 2: because it's there, you know, It's just it's right there

857
00:47:28,960 --> 00:47:30,880
Speaker 2: on the surface, waiting to be described.

858
00:47:31,600 --> 00:47:34,640
Speaker 1: You wrote a book called Going Infinite, the story of

859
00:47:34,920 --> 00:47:39,239
Speaker 1: billionaire Sam Bankman Free who's now serving time, and I'm

860
00:47:39,320 --> 00:47:43,560
Speaker 1: curious how you feel about his latest interview with Tucker

861
00:47:43,640 --> 00:47:47,319
Speaker 1: Carlson and reports that their efforts from his family and

862
00:47:47,400 --> 00:47:49,960
Speaker 1: allies to receive a pardon from Donald Trump.

863
00:47:50,360 --> 00:47:53,080
Speaker 2: I mean, if you had to ask me the moment

864
00:47:53,280 --> 00:47:56,080
Speaker 2: Trump was elected what the Bankman Freeds were going to do,

865
00:47:56,080 --> 00:47:57,600
Speaker 2: I'd have told you they're going to seek a pardon

866
00:47:57,600 --> 00:48:01,319
Speaker 2: from Donald Trump. That doesn't that part doesn't surprise me.

867
00:48:01,880 --> 00:48:04,160
Speaker 2: And there's even a kind of a weird sort of

868
00:48:04,280 --> 00:48:07,839
Speaker 2: narrative path to it because the judge that's sentence Sam

869
00:48:07,920 --> 00:48:10,360
Speaker 2: Bangman freed to twenty five years in jail. It was

870
00:48:10,440 --> 00:48:13,600
Speaker 2: also the judge in the Egen Carroll case, so there

871
00:48:13,600 --> 00:48:17,120
Speaker 2: will be some natural hostility Trump would feel towards that judge.

872
00:48:17,600 --> 00:48:20,759
Speaker 2: It's sort of the rule in life that wherever Sam

873
00:48:20,760 --> 00:48:24,839
Speaker 2: Bangman freed is, even when it's jail, gets way more

874
00:48:24,840 --> 00:48:28,160
Speaker 2: interesting because he's there than it ever was before. So

875
00:48:28,320 --> 00:48:31,120
Speaker 2: I was wondering when he went to jail, like, what's

876
00:48:31,120 --> 00:48:34,439
Speaker 2: going to happen here? It's going to generate story because

877
00:48:34,440 --> 00:48:37,719
Speaker 2: everywhere he goes he generates story, and we're kind of

878
00:48:37,719 --> 00:48:40,560
Speaker 2: spoiled for choice. Now he's given secret interviews to Tucker

879
00:48:40,560 --> 00:48:43,520
Speaker 2: Carlson from his prison cell without the Bureau of Prisons knowing.

880
00:48:43,800 --> 00:48:47,120
Speaker 2: He's got p Diddy in the next bunk. Luigi passed

881
00:48:47,120 --> 00:48:51,360
Speaker 2: through for a nano second. It's like, I mean, his

882
00:48:51,440 --> 00:48:55,000
Speaker 2: life is like a sitcom wherever he goes, and I

883
00:48:55,040 --> 00:48:57,560
Speaker 2: just think it's like, that's just who he is. It's

884
00:48:57,600 --> 00:48:59,640
Speaker 2: what attracted to me, me to him as a subject.

885
00:48:59,680 --> 00:49:01,800
Speaker 2: In the first it's like where we win. It was funny,

886
00:49:02,160 --> 00:49:05,880
Speaker 2: but there is some if this happens. There is some

887
00:49:06,160 --> 00:49:12,320
Speaker 2: irony in the fact that the idea of Trump pardoning

888
00:49:12,360 --> 00:49:14,560
Speaker 2: a guy who is trying to pay him five billion

889
00:49:14,600 --> 00:49:17,680
Speaker 2: dollars a year not to run for president. Sam Bangfree

890
00:49:17,760 --> 00:49:19,640
Speaker 2: was trying to pay Donald Trump not to run for

891
00:49:19,719 --> 00:49:23,200
Speaker 2: president four years ago, and that Donald Trump getting him

892
00:49:23,200 --> 00:49:25,840
Speaker 2: out of jail. I mean, somehow that feels like the

893
00:49:25,920 --> 00:49:26,200
Speaker 2: end of.

894
00:49:26,120 --> 00:49:29,120
Speaker 1: A story, right, at least a Michael Lewis story.

895
00:49:29,280 --> 00:49:29,960
Speaker 2: Yeah, that's right.

896
00:49:32,880 --> 00:49:34,960
Speaker 1: The other question I wanted to ask you quickly and

897
00:49:34,960 --> 00:49:36,880
Speaker 1: then I'll let you go. What do you think of

898
00:49:36,960 --> 00:49:41,560
Speaker 1: Jeff Bezos's new attitude toward the opinion pages of the

899
00:49:41,680 --> 00:49:46,560
Speaker 1: Washington Post. Your essays originally appeared in those pages, and

900
00:49:46,640 --> 00:49:50,520
Speaker 1: now he has said that alternative points of view that

901
00:49:50,600 --> 00:49:55,439
Speaker 1: aren't focused on I guess liberties right, personal liberties and

902
00:49:55,719 --> 00:49:58,799
Speaker 1: free Marcus will not be welcome at the paper. There

903
00:49:58,840 --> 00:50:03,040
Speaker 1: are other places to read those kinds of things. What

904
00:50:03,040 --> 00:50:06,680
Speaker 1: do you think of Jeff Bezos's attitude now, a new

905
00:50:06,920 --> 00:50:10,000
Speaker 1: edict towards opinion writers at the Washington Post.

906
00:50:10,360 --> 00:50:12,719
Speaker 2: It's gonna kill interest in the Washington Post. I mean,

907
00:50:12,760 --> 00:50:17,600
Speaker 2: it already has. And the editor of this series, David Shipley,

908
00:50:17,840 --> 00:50:22,400
Speaker 2: left because of this decision of Bezos'. So I think it.

909
00:50:23,280 --> 00:50:25,160
Speaker 2: I could see why he did it. I can see

910
00:50:25,200 --> 00:50:28,200
Speaker 2: why people feel they need to suck up to Donald Trump.

911
00:50:31,239 --> 00:50:34,520
Speaker 2: I don't. I don't think this was it's it's it's

912
00:50:34,560 --> 00:50:37,239
Speaker 2: a particular shame in this case because I think I

913
00:50:37,520 --> 00:50:39,319
Speaker 2: kind of like Jeff Bezos. I think he's a good guy.

914
00:50:39,640 --> 00:50:42,200
Speaker 2: I mean, just as a guy. I don't feel the

915
00:50:42,200 --> 00:50:46,440
Speaker 2: way I feel towards Elon Musk towards Jeff Bezos. But

916
00:50:46,520 --> 00:50:48,600
Speaker 2: the thing that's so disturbing is that there are not

917
00:50:48,760 --> 00:50:52,440
Speaker 2: many places in the country where if you write something,

918
00:50:53,560 --> 00:50:57,680
Speaker 2: all the Democratic legislators and all the Republican legislators read it.

919
00:50:58,440 --> 00:51:01,480
Speaker 2: They don't all read the New York Times. They the

920
00:51:02,840 --> 00:51:06,000
Speaker 2: media has gotten so polarized. But the Washington Post still

921
00:51:06,000 --> 00:51:09,680
Speaker 2: had this kind of like it was the industry towns newspaper,

922
00:51:10,280 --> 00:51:13,200
Speaker 2: and you could get to everybody through it. And if

923
00:51:13,200 --> 00:51:15,920
Speaker 2: you had a party that the Washington at the Washington Post,

924
00:51:16,239 --> 00:51:19,360
Speaker 2: Republican senators would turn up. You know, it wasn't it

925
00:51:19,600 --> 00:51:23,000
Speaker 2: Obviously it leaned left, but it was it was a

926
00:51:23,000 --> 00:51:26,359
Speaker 2: way to speak to the the industry, to the politicians.

927
00:51:27,120 --> 00:51:29,680
Speaker 2: And he's now abandoned. It's not. Now it isn't and

928
00:51:29,719 --> 00:51:32,480
Speaker 2: now it's it's lost, it's lost. Its appeal to me

929
00:51:32,600 --> 00:51:34,040
Speaker 2: is a place to write. I won't write. I'm not

930
00:51:34,040 --> 00:51:36,000
Speaker 2: going to. I have a piece that the last piece

931
00:51:36,000 --> 00:51:39,440
Speaker 2: of this book appears on Thursday in the Post. It's

932
00:51:39,480 --> 00:51:43,640
Speaker 2: another long piece about a civil servant. But I wrote

933
00:51:43,640 --> 00:51:45,759
Speaker 2: it a couple of months ago, and I won't write

934
00:51:45,800 --> 00:51:47,600
Speaker 2: for it in its current incarnation.

935
00:51:47,840 --> 00:51:52,520
Speaker 1: Again, I'm sure a lot of government workers, whether they're

936
00:51:52,560 --> 00:51:55,840
Speaker 1: still employed or have gotten the acts, will be so

937
00:51:56,120 --> 00:52:01,640
Speaker 1: grateful for this book and for someone actually celebrating the

938
00:52:01,680 --> 00:52:04,319
Speaker 1: work that they do if they get it.

939
00:52:04,520 --> 00:52:08,640
Speaker 2: Yeah, yeah, I mean, that wasn't the real purpose in

940
00:52:08,680 --> 00:52:10,719
Speaker 2: my mind. The purpose in my mind was to sort

941
00:52:10,719 --> 00:52:13,759
Speaker 2: of attack the stereotype, like I just to make it,

942
00:52:13,800 --> 00:52:17,399
Speaker 2: make people's minds more interesting, Like get off this kind

943
00:52:17,440 --> 00:52:20,400
Speaker 2: of weird, this weird picture you have of the federal

944
00:52:20,440 --> 00:52:23,040
Speaker 2: bureaucrat and get to something a little more real. That

945
00:52:23,200 --> 00:52:25,879
Speaker 2: was the goal. But one side effect maybe makes people

946
00:52:25,960 --> 00:52:27,120
Speaker 2: feel better, that would be all right.

947
00:52:27,680 --> 00:52:30,640
Speaker 1: Well. The book is called Who Is Government? The untol

948
00:52:30,719 --> 00:52:34,160
Speaker 1: Story of Public Service, and Michael, it really is kind

949
00:52:34,160 --> 00:52:38,240
Speaker 1: of an addendum to your previous book, The Fifth Risk,

950
00:52:38,760 --> 00:52:43,319
Speaker 1: which paints a very different picture of the men and

951
00:52:43,360 --> 00:52:47,440
Speaker 1: women in our federal workforce. I always love talking to

952
00:52:47,440 --> 00:52:59,320
Speaker 1: you Michael, Thank you, Thank you, Katie, thanks for listening. Everyone.

953
00:52:59,719 --> 00:53:02,360
Speaker 1: If you have a question for me, a subject you

954
00:53:02,400 --> 00:53:04,640
Speaker 1: want us to cover, or you want to share your

955
00:53:04,680 --> 00:53:08,399
Speaker 1: thoughts about how you navigate this crazy world, reach out

956
00:53:08,760 --> 00:53:11,440
Speaker 1: send me a DM on Instagram. I would love to

957
00:53:11,440 --> 00:53:15,360
Speaker 1: hear from you. Next Question is a production of iHeartMedia

958
00:53:15,400 --> 00:53:19,720
Speaker 1: and Katie Couric Media. The executive producers are Me, Katie Kuric,

959
00:53:19,840 --> 00:53:24,319
Speaker 1: and Courtney Ltz. Our supervising producer is Ryan Martz, and

960
00:53:24,400 --> 00:53:29,520
Speaker 1: our producers are Adriana Fazzio and Meredith Barnes. Julian Weller

961
00:53:29,640 --> 00:53:34,200
Speaker 1: composed our theme music. For more information about today's episode,

962
00:53:34,440 --> 00:53:36,840
Speaker 1: or to sign up for my newsletter, wake Up Call,

963
00:53:37,280 --> 00:53:40,160
Speaker 1: go to the description in the podcast app, or visit

964
00:53:40,280 --> 00:53:43,440
Speaker 1: us at Katiecuric dot com. You can also find me

965
00:53:43,520 --> 00:53:47,239
Speaker 1: on Instagram and all my social media channels. For more

966
00:53:47,320 --> 00:53:52,640
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967
00:53:52,680 --> 00:53:55,000
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