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

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Speaker 1: where we discussed the top political headlines with some of

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Speaker 1: today's best minds, and Quinnipiac University national poll finds just

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Speaker 1: sixty seven percent of Republicans sixty seven percent of Republicans

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Speaker 1: support the BBB. We have such a great show for

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Speaker 1: you today as the world churns. Andy Levy stops by

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Speaker 1: to talk to us about the fallout from Trump and

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Speaker 1: musks exploding romance. Then we'll talk to Blood in the

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Speaker 1: Machines Brian Merchant about how AI is already quietly killing

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Speaker 1: job prospects in America. But first the news Mali.

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Speaker 2: These tariffs, it's never ending drama, just like Trump and Musk.

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Speaker 2: Scopist says it's highly likely tariff deadlines will slide for

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Speaker 2: countries and talks because sure third talks.

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Speaker 1: I was taald that there would be ninety deals in

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Speaker 1: ninety days.

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Speaker 3: It's infrastructure week too.

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Speaker 1: It's always infrastructure week, isn't it.

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Speaker 2: That's what I'm saying. This is the new infrastructure week.

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Speaker 1: So let's talk about the tariffs. Showed Endur's tariffs. There

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Speaker 1: are so many different machinations of tariffs in different ways.

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Speaker 1: There is a global tariff that Trump put on on

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Speaker 1: April second, then he paused on April ninth. Then he

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Speaker 1: promised ninety deals in ninety days. I mean, so they're

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Speaker 1: less than thirty days to go. There are sixty deals now,

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Speaker 1: I'm just kidding, they're not. There's one framework of a

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Speaker 1: deal that's like you remember concepts of a plan. That's

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Speaker 1: concept of a plan that's with the UK, one extension

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Speaker 1: that's with the EU. Then there's the China disaster. But

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Speaker 1: China's tends to be very easy to negotiate with and

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Speaker 1: very operating in good faith.

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Speaker 4: Just kidding.

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Speaker 1: By the way, I just want to point out he

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Speaker 1: could make deals with Canada and Mexico tomorrow. They are

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Speaker 1: our largest partners, and like all the Canada and Mexico

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Speaker 1: stuff is completely self imposed. Crisises that this administration is

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Speaker 1: doing because Trump is so unpredictable, Like, make a deal

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Speaker 1: with Canada and Mexico. Stop it. This is so stupid.

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Speaker 2: It is pretty stupid. Speaking of stupid, a couple journalists

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Speaker 2: have identified that there's this feedback group of right wing

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Speaker 2: propaganda that keeps kind of fueling what's going on with

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Speaker 2: these LA protests. Device and I have to tell you personally,

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Speaker 2: I couldn't believe when I looked at Twitter this morning

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Speaker 2: how much footage I was seeing of twenty twenty protests

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Speaker 2: being passed on as if they're happening right now today.

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Speaker 1: Yeah, twenty twenty protests, AI videos stuff from like the

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Speaker 1: beginning of the Russia Ukraine War, when the right was

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Speaker 1: sharing all these like insane videos where you were like,

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Speaker 1: this is not Russia. This is a video game. That's

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Speaker 1: what we have here. But you know, you have one

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Speaker 1: group of influencers who are again like I don't mean

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Speaker 1: to get on my hobby horse, but let me please

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Speaker 1: get on my hub person. Congress refuse to regulate, right,

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Speaker 1: they've refused to put any level of regulation on the internet.

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Speaker 1: So there is no fact checker, there is no truth,

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Speaker 1: There is no agreed upon truth. And so now if

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Speaker 1: you're a bad faith actor, which a lot of these

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Speaker 1: people are, you know, you're either a bad faith actor

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Speaker 1: or you're stupid, right, because anyone else has been on

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Speaker 1: the Internet so much, they know like this is not correct.

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Speaker 1: You know, like I know what looks you know, if

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Speaker 1: it looks too good to be true, it probably is.

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Speaker 1: And I mean that with all the caveat. But what's

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Speaker 1: scary about this administration is they actually, like in a

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Speaker 1: normal administration, you'd see a picture and the president would say, well,

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Speaker 1: I'm going to go to my D and I and

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Speaker 1: make sure that this is real. In this administration, Donald

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Speaker 1: Trump is like we have to go to war, you know,

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Speaker 1: like he doesn't. There's not a lot of fact checking,

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Speaker 1: and like we've seen this get and again, right, go on.

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Speaker 2: And this administration. Tulci Gabbard yesterday was busy rattling off

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Speaker 2: conspiracy theories on a video for like an hour.

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Speaker 1: Yeah, exactly. I just don't understand how we are in

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Speaker 1: this position again. And there's no like there are a

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Speaker 1: few Republicans who are still around who understand that like

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Speaker 1: what is real and what is not real. But a

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Speaker 1: lot of Trump's people are just like, if he can

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Speaker 1: get the base to believe it, who cares if it's real.

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Speaker 3: That seems to be the modus operandi.

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Speaker 1: Which is really scary.

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Speaker 2: Yeah, it's it's horrible, and it really it was the

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Speaker 2: same thing as the thing we know that like Musk

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Speaker 2: has incentivized all this information by paying people. There's that

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Speaker 2: great article in The Times a week ago about Don Luker,

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Speaker 2: and you know that he just doesn't care about what

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Speaker 2: he prints because Musk is paying him. Speaking of things though,

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Speaker 2: that do break the pattern. Would you believe me if

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Speaker 2: I said Mitch McConnell was really hard on Pete Hegseth

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Speaker 2: at the hearing yesterday.

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Speaker 1: Yes I would, because it's a guy who vote is

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Speaker 1: like the one Republican who voted against all the crazy

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Speaker 1: cabinet appointees. So I would believe that. I mean, look,

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Speaker 1: Mitch mcconald is how we got here, so I don't

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Speaker 1: think anyone should be, you know, feeling too bad for him.

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Speaker 1: But that said, he has now realized, you know, he

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Speaker 1: doesn't have power anymore, he's not in leadership, and he's

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Speaker 1: realized that this is just a disaster, right, that Russia's

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Speaker 1: being allowed to do whatever it wants with Ukraine, that

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Speaker 1: America is no longer the shining city on the hell.

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Speaker 1: This is what it is, man, this is what it is.

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Speaker 1: And I think Mitch mcconald understands that he was part

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Speaker 1: of this, and you know, I don't think he wishes

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Speaker 1: us well. I do think there's some amount of like Oiva,

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Speaker 1: I did this going on.

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Speaker 2: So we usually don't wait into foreign policy waters. But

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Speaker 2: what are the things you and I have often discussed.

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Speaker 1: For anything about it? Yes, go on, we do.

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Speaker 2: One of the things you and I often discussed, though,

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Speaker 2: is what we do want to do is highlight the

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Speaker 2: things we think are not getting discussed in the mainstream media.

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Speaker 2: I think it's a little concerned that the US has

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Speaker 2: reduced the presence of staffers do de deessential in the

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Speaker 2: Middle East as tensions with Iran and rise.

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Speaker 1: Yeah, look, this is so insane.

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Speaker 4: Okay.

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Speaker 1: Remember Donald Trump was like, I'm going to make peace

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Speaker 1: in the Middle East in the first day. I remember

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Speaker 1: that very well. It's like I'm going to end the tension.

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Speaker 4: Yeah.

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Speaker 1: And then he was like, We're going to develop Palestine,

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Speaker 1: kick out all the Palestines.

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Speaker 3: The tension.

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Speaker 1: Yeah, is the tension. And now it looks like, you know,

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Speaker 1: non essential American employees are getting out of Iran because

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Speaker 1: something's cooking. Again. This is all hard, Like this is

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Speaker 1: the thing about Elon Musk. Government is actually hard. It's

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Speaker 1: just hard. It's hard to get a lot of people

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Speaker 1: to do stuff. It's hard to make it work right,

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Speaker 1: It's hard. So like making peace in the Middle East

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Speaker 1: is hard. So part of Donald Trump's whole thing is

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Speaker 1: that he is so brash and caw and sometimes his

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Speaker 1: escalatory rhetoric works. It usually works with like sane countries

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Speaker 1: that would have been our friends anyway, but it doesn't

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Speaker 1: work with places like Israel or Raq or Palestine, and

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Speaker 1: so really it is just, you know, it's so fucking bad.

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Speaker 1: Excuse my friend, And you know, we just have this

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Speaker 1: super disorganized, very craven, extremely ideological administration that is like

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Speaker 1: a bull in a china shop and somehow still believes

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Speaker 1: that Vladimir Putin is a good guy. And that's why

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Speaker 1: we can't stop things escalate. There is no peace. It

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Speaker 1: just all of this that we're seeing play out is

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Speaker 1: everything we said was going to happen. Yes, we were

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Speaker 1: wrong about the twenty twenty four cycle, but no, we

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Speaker 1: were not wrong about what Donald Trump would do when

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Speaker 1: he got an office. Andy Levy is the co host

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Speaker 1: of As the World Churns. Welcome to Fast Politics, Andy Levy.

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Speaker 4: Thank you, Molly, trying not to do something weird anyway,

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Speaker 4: I'm here with a New York Times bestselling author, Molly

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Speaker 4: john Fest. So what's up with that, Molly.

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Speaker 1: Well, we were getting ready to record, by the way,

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Speaker 1: I'm in Chicago. If I don't sound amazing, Jesse is

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Speaker 1: probably going to kill me later. But I did get

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Speaker 1: a call from my editor that my book How to

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Speaker 1: Lose Your Mother, available in many places, is on the

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Speaker 1: New York Times bestseller list. And you know, this is

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Speaker 1: writing is like what I've done my whole life. So

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Speaker 1: to be on the New York Times bestseller list, it's

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Speaker 1: pretty fucking cool.

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Speaker 4: Yeah, that's amazing, especially for a book that's based on

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Speaker 4: a sitcom that went off the air like ten years ago.

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Speaker 1: It's a book based on a meme. Right, it's not

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Speaker 1: a sick it's a meme. It's a mean book. Yeah, okay, yeah,

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Speaker 1: it's a meme books being of meme books, I have

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Speaker 1: a whole thesis and I'd like to shop it to

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Speaker 1: you and our listeners, and you tell me if you

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Speaker 1: think that I'm wrong. I'm open to being wrong because

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Speaker 1: now I'm in your time's bestselling author, So I have

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Speaker 1: that self esteem buttress that I.

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Speaker 4: Can set wrong. Sure.

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Speaker 1: Last week, despite the fact that Trump World sort of

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Speaker 1: spun it in many different ways, Trump did fight with Elon,

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Speaker 1: the guy who has all our data. Then Elon called

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Speaker 1: him a pedo. Then Trump called him a drug addict.

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Speaker 1: Then Elon said maybe he shouldn't have tweeted all that

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Speaker 1: stuff that was this week, and also Trump world lost

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Speaker 1: in Cord and Trump the trade war. There are no

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Speaker 1: ninety deals in ninety days, you know, everything is just

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Speaker 1: sort of cluttering along. And then there's also somehow we're

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Speaker 1: going to war with ver we're on. You know, like

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Speaker 1: it just seems like all of the sort of last

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Speaker 1: week you could still blur your eyes and be like

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Speaker 1: Trump two point oho is more organized than to Trump

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Speaker 1: one point zero. But now all of a sudden, like

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Speaker 1: that illusion is gone and ad And that same time,

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Speaker 1: Donald Trump decides that he should send the National Guard

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Speaker 1: in to Los Angeles. Probably a coincidence, right.

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Speaker 4: I don't know if it's a quincience. Look, I am

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Speaker 4: unlike you and Donald Trump. I am not a New

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Speaker 4: York Times bestselling author, So I feel kind of like

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Speaker 4: the odd man out in this discussion. But I think

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Speaker 4: two things can be true as they say. I think

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Speaker 4: one is the timing of this is I I think

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Speaker 4: you're onto something there. Like I do think that it

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Speaker 4: hasn't been a great couple of weeks for Donald Trump

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Speaker 4: by a lot of metrics, so his bread and butter

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Speaker 4: is always going to be, you know, for his base,

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Speaker 4: it's going to be going after brown people and going

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Speaker 4: after black people, et cetera. So yeah, I think the timing,

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Speaker 4: if it's coincidental, it's it's it's a very I guess.

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Speaker 4: I don't want to say it's a good coincidence for

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Speaker 4: Donald Trump, but it's the kind of thing that may

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Speaker 4: be coincidental that it's a incidents think, is what I'm

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Speaker 4: trying to say. But we know this is what Stephen

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Speaker 4: Miller has wanted from day one, and they may have

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Speaker 4: just seen with regard to the timing, well this happened,

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Speaker 4: and then they said, Okay, let's do what we've been

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Speaker 4: wanting to do. Let's send in the shock troops. Let's

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Speaker 4: send in the jack booted thugs, let's send in the

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Speaker 4: National Guard, the Marines. I'm worried that we're going to

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Speaker 4: be finding a two front ore, one in t i

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Speaker 4: Ron and one at the Grove, and that usually doesn't

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Speaker 4: go well.

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Speaker 1: Full disclosure. I was at the grove yesterday. There is

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Speaker 1: no war at the grove. Now that said, it's a

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Speaker 1: weird little MALLLL.

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Speaker 3: It is a weird little mall yeah.

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Speaker 1: It's a weird little mall. Like what I love about

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Speaker 1: La Is there so many weird little spots that make

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Speaker 1: no sense. I did nearly get hit by a trolley

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Speaker 1: at the Grove buck Is there a trolley.

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Speaker 4: Trolley was like four miles.

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Speaker 1: Yeah, exactly. But you can still if you're tired enough,

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Speaker 1: you can wander in there. So look, I was in

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Speaker 1: La till about two hours ago, and I think.

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Speaker 4: Did you get breathed?

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Speaker 1: Oh yeah, oh yeah. Oh it's just it's mayhem and madness. No,

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Speaker 1: it's totally fine. There's like a small area where people

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Speaker 1: are protesting. I didn't hear anything, I didn't see anything.

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Speaker 1: I didn't see any smoke. You know, it's not what

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Speaker 1: the far right wants you to think it is. Now,

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Speaker 1: that is why the far right has And there's a

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Speaker 1: really good article about this and Wired and in the

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Speaker 1: Times there's a they're spreading all these fake AI generated videos,

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Speaker 1: so A generated videos, old videos saying that like Los

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Speaker 1: Angeles is a healthcape. I would think they would want

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Speaker 1: Los Angeles to be a healthcape. I guess they do

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Speaker 1: want Los Angeles.

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Speaker 4: Yeah, yeah, no, they look they want all those pictures

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Speaker 4: to be real, you know, we've got that. They're even

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Speaker 4: playing the old hits, the Palette of Bricks, right, I

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Speaker 4: think that's right. I don't remember what year it wasn't

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Speaker 4: that that first top the chart, but they're bringing it back.

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Speaker 4: But yeah, look, I lived in LA for ten years.

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Speaker 4: I have a lot of friends in LA. Nobody in

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Speaker 4: La is talking about the city being on fire or

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Speaker 4: they're riots all over in the streets. That stuff is

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Speaker 4: simply just not happening, and we're being lied to for

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Speaker 4: a change by the top administration and right wing media.

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Speaker 4: If you want to talk about the violence, the violence

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Speaker 4: is very one sided and it ain't coming from the protesters.

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Speaker 1: Yeah, well, I think I actually have a friend who

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Speaker 1: was protesting in New York and she was telling me

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Speaker 1: that the ICE agents are trying to get the protesters

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Speaker 1: to act out, like there's clearly a want here for escalation,

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Speaker 1: but it's not necessarily on the protester side. That said,

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Speaker 1: you don't you know, you can't be held responsible forever.

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Speaker 1: I mean, I'm sure that a lot of people and

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Speaker 1: we saw this, We've seen this with every protest, that

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Speaker 1: there are protesters who do stuff that they're not supposed

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Speaker 1: to do. So sure, I you know, you don't want

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Speaker 1: to like blankets, say that no everyone's behaving.

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Speaker 4: Well, sure, no, someone is always going to start a

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Speaker 4: drum circle and that is reprehensible and should not be

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Speaker 4: tolerated in the year twenty twenty five. But there's going

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Speaker 4: to be stuff like that, and you can't you can't

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Speaker 4: tar the whole of the protest because somebody has a bongo.

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Speaker 4: It's just not fair. And by the same token, you see,

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Speaker 4: you know, the media, as as people have pointed out,

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Speaker 4: the media love to show cars on fire. That is,

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Speaker 4: they can't they they cannot get enough of a car

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Speaker 4: being on fire. So there could be one car on fire,

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Speaker 4: and we have no idea how it happened, but we

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Speaker 4: are going to see that image a thousand goddamn times,

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Speaker 4: and there's going to be a lot of handwringing about

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Speaker 4: the violence because a car in America is sacred, whereas

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Speaker 4: the lives of individuals not so much.

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Speaker 1: Not so much, not so much. No, yes, that's right,

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Speaker 1: don't burn cars because cars for people. Let me ask

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Speaker 1: you a question, now that Trump and Elon have broken up,

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Speaker 1: is it still a federal crime to hurt a tesla?

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Speaker 1: Or is that has that been rescinded.

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Speaker 4: I mean, that's a good question. And in LA it

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Speaker 4: seems to be that the protesters are going after the

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Speaker 4: Wainbow vehicles because all these self driving cars have cameras

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Speaker 4: of all of them, and the police in law enforcement

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Speaker 4: and the FEDS are using them to surveil. So I

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Speaker 4: was trying to figure out, Yeah, do you think is

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Speaker 4: Elon does he have mixed feelings about this? Is he

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Speaker 4: like upset that they're going after cars? But on the

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Speaker 4: other hand, it's these Google cars like that are competitors

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Speaker 4: to Tesla. This is a tough one to judge. Trump

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Speaker 4: said he was selling his or he was getting rid

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Speaker 4: of his Tesla, didn't.

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Speaker 3: You say that?

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Speaker 1: Yeah, yeah, which doesn't mean he did say he was

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Speaker 1: getting rid of He told a reporter in the West

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Speaker 1: Way when he was doing one of his many many

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Speaker 1: sprays or you know whatever it's called, that he is

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Speaker 1: selling his red Tesla out. Let's just talk about this

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Speaker 1: sort of musk trying to retrench himself efforts. Okay, So,

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Speaker 1: by the way, the polling on the BBB is the big, bad,

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Speaker 1: beautiful Buxom bill is bad, bad, bad, real bad. You

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Speaker 1: want to know how bad it is?

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Speaker 4: How bad is it.

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Speaker 1: I'll tell you how bad it is. It's bad, bad, bad.

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Speaker 1: I mean, if I were pulling that badly, it's like

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Speaker 1: black death. And then the BBB Big Beautiful Bill two

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Speaker 1: to one. Americans opposed independents are three to one negative

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Speaker 1: on it BBB bad bad bad. They should have called

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Speaker 1: it something else.

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Speaker 4: Yeah, well, I guess the people are on Elon's side

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Speaker 4: on that one because he was going after the BBB.

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Speaker 1: He was going after it because he wanted it to

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Speaker 1: give him credits so that his car company could do well,

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Speaker 1: not because he gives talk about the data sets.

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Speaker 4: Which, by the way, is the same reason he's apologizing

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Speaker 4: to Trump. I mean, yeah, I mean the federal contracts

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Speaker 4: between you know, SpaceX and and the favors he needs

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Speaker 4: for Tesla. I mean, I have got to think that

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Speaker 4: this you know, pseudo apology or halfway apology that he

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Speaker 4: that he did was spurred on by the boards of

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Speaker 4: some of his various companies, by the Tesla board, by

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Speaker 4: the people at SpaceX who were like, dude, if the

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Speaker 4: federal government cancels SpaceX contracts, we're out of business. I mean,

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Speaker 4: they can't stay in business without that.

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Speaker 1: Let's just talk for a second about this, this elon

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Speaker 1: apology tour. So his he had an early morning tweet

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Speaker 1: on Wednesday, which is either today, yesterday, or five years ago,

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Speaker 1: and in it he said he regret regretted going quote

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Speaker 1: too far in criticizing President Trump. I assume that's the

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Speaker 1: HEADO tweet, but it could have been something else. Love

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Speaker 1: this administration. Musk's effort, and I mean that with all

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Speaker 1: the disdain in the world, that's irony or is it sarcasm?

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Speaker 1: It's circus. Musk's efforts to make amends began on Friday

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Speaker 1: when he spoke by phone with White House Chief of Staff.

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Speaker 1: This is a reporting from Axios, Susie Wilds and Vice

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Speaker 1: President Vance. Three people familiar with the discussion said, so

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Speaker 1: one of that's Trump. Vance and Susie told Axios that

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Speaker 1: Musk call them it matters. Why does it matter? American

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Speaker 1: democracy is going to die. It's Musk is trying to

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Speaker 1: get Trump to take him back. And then Musk fears

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Speaker 1: Trump's beautiful bill will add trillions the federal deficit. Do

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Speaker 1: you think he really fears that. I don't think he

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Speaker 1: gives a fuck out.

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Speaker 4: I don't think. No, he fears it will add money

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Speaker 4: to his deficit, yes, you know, uh not not to

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Speaker 4: the federal deficat. No, I don't believe for a second

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Speaker 4: he gives a shit about that. I mean I was

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Speaker 4: talking to I was talking to Si Cup last week

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Speaker 4: on my podcast As the World Turns, available wherever you

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Speaker 4: get your podcasts, also on YouTube, and uh, she asked

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Speaker 4: me who I thought had more to lose in the

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Speaker 4: Musk Trump war, and I said, you know, to me,

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Speaker 4: it was obviously Musk. I mean, Trump doesn't need Musk anymore.

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Speaker 4: This is separate, by the way, from the Republican Party

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Speaker 4: maybe needing Musk because it was his money that was

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Speaker 4: that is fueling a lot of the you know, that

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Speaker 4: is filling a lot of their election coffers. But Trump,

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Speaker 4: at least as of today, isn't running for office again,

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Speaker 4: So he personally doesn't need Elon really, and he does

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Speaker 4: not give a shit about the Republican Party. We know that.

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Speaker 4: So telling Trump he needs Elon because the Elon is

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Speaker 4: good for the Republican Party, Trump doesn't understand that. But Elon,

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Speaker 4: as as we've been talking about, Elon needs Trump because

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Speaker 4: his entire livelihood is dependent on taxpayer money, on federal funding.

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Speaker 4: So it's not really. You know, if again, if if

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Speaker 4: you ask me which one of them was going to blink,

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Speaker 4: I would have said, of course it's going to be Musk.

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Speaker 4: He has to.

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Speaker 1: So that's the question. Now there is the fact that

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Speaker 1: some of the companies that Elon has and I you know,

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Speaker 1: like SpaceX and Star like, there's no other company that

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Speaker 1: necessarily does. I mean, other companies could catch up, but

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Speaker 1: they'll be a lack right, So I'm not sure. I mean,

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Speaker 1: I've certainly read pieces that say and again this is

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Speaker 1: really like be this is like internet, you know, like

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Speaker 1: this is like foreign policy stuff. It's just a little

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Speaker 1: bit out of my skill set. So I don't know

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Speaker 1: what this you know, what satellite manufacturing looks like in

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Speaker 1: other countries. You know, I don't know what the what

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Speaker 1: the companies are, but there definitely is I don't think

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Speaker 1: Elon can be I mean, I don't know that he

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Speaker 1: can lose all those government contracts right now, but he

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Speaker 1: certainly can lose like EV credits and Tesla is super overvalued,

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Speaker 1: right everyone's you know, that's a sort of no known

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Speaker 1: So I do think they're and you know, Elon is

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Speaker 1: so overleveraged, you know, between X, I mean, he's very rich,

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Speaker 1: but he's very leveraged, so you know, there could be

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Speaker 1: the margin call from hell there. I mean, I just

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Speaker 1: don't know enough about his finances, but I certainly know

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Speaker 1: that the fact that he's trying to get back into

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Speaker 1: Trump world, you don't do that. Like if things are

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Speaker 1: going great, it seems hard for me to imagine that

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Speaker 1: he's going to go back and eat grow.

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Speaker 4: Yeah, and look, I think you know, Starlink maybe almost

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Speaker 4: a one of a kind thing now, you know, with

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Speaker 4: satellite Wi Fi and or satellite internet whatever and all

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Speaker 4: of that. But again, it is pretty wholly dependent on

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Speaker 4: government contracts, not just ours, other governments as well. And

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Speaker 4: the thing is, if if Trump decides he's going to

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Speaker 4: destroy Elon, you know, damn well, he's gonna tell other

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Speaker 4: countries to get rid of their startling systems or to

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Speaker 4: not invest in future ones. And that's really like, like

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Speaker 4: you said, they may be the only you know, player

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Speaker 4: in town right now, that doesn't mean they always will be.

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Speaker 4: And they need these future contracts to keep growing as

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Speaker 4: a company because that's all that Wall Street Etca. Cares

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Speaker 4: about his growth. So I think that's where and the

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Speaker 4: same goes for SpaceX space X. Yes, they're kind of

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Speaker 4: you know, Bezos has his his his own little penis

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Speaker 4: replacement thing going on. But but space X is really

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Speaker 4: the only player in the game.

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Speaker 3: But they are the player.

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Speaker 4: They're a player in the game again because of the

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Speaker 4: government contracts, because of contracting with NASA and and things

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Speaker 4: like that. So you yank all of those and you

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Speaker 4: can say, well, but no one else is doing with

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Speaker 4: what's SpaceX is doing. But SpaceX ain't going to be

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Speaker 4: doing that if it's just dependent on the private sector

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Speaker 4: right now.

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Speaker 1: Right, I mean, it's a I think this is a

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Speaker 1: real these both of these men are not in great situations.

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Speaker 1: And that's okay. That's okay with me. I'm good with that.

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Speaker 1: So I just don't understand why there's not more discourse

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Speaker 1: about this. So I'm going to make you talk with

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Speaker 1: me about it.

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Speaker 4: Just about your booking the New York Times bestseller.

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Speaker 1: No, but it is. I'm very excited. But the BBB

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Speaker 1: is this bill that got through the House and then

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Speaker 1: you had all these House members being like, I didn't

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Speaker 1: really know what was in it. I just voted for it.

431
00:23:37,600 --> 00:23:40,800
Speaker 1: Marjorie Taylor Green. You know, all these people voted for it,

432
00:23:41,119 --> 00:23:44,400
Speaker 1: and it passed by one vote. Okay, So now it's

433
00:23:44,440 --> 00:23:47,960
Speaker 1: going through the Senate. It's wildly unpopular. You have Elon

434
00:23:48,080 --> 00:23:51,959
Speaker 1: tweeting about it still, uh, And I just wonder like

435
00:23:52,680 --> 00:23:57,399
Speaker 1: why are Democrats not getting you know, like Rand Paul's

436
00:23:57,400 --> 00:23:59,800
Speaker 1: already and now so we know Rand Paul's in now,

437
00:24:00,359 --> 00:24:04,560
Speaker 1: and you know that you only need like three more okay.

438
00:24:05,080 --> 00:24:09,679
Speaker 1: And we have like Bill Cassidy, the Senator from Louisiana

439
00:24:09,680 --> 00:24:12,080
Speaker 1: who's a doctor and should know better. He made a

440
00:24:12,160 --> 00:24:14,960
Speaker 1: deal with RFK Junior where r FFK Junior said, I'm

441
00:24:15,000 --> 00:24:18,560
Speaker 1: not going don't worry. I love vaccines. I just have

442
00:24:18,640 --> 00:24:23,000
Speaker 1: been saying that they cause terrible diseases. So he fired

443
00:24:23,040 --> 00:24:25,320
Speaker 1: the whole vaccine board and he's going to replace them

444
00:24:25,359 --> 00:24:32,000
Speaker 1: with new better maga the doctors okay maybe or just

445
00:24:32,080 --> 00:24:39,560
Speaker 1: not that doctor Oz right and doctor Phil and so.

446
00:24:39,560 --> 00:24:42,320
Speaker 1: So this is a guy who's really been rolled. Okay.

447
00:24:42,520 --> 00:24:46,200
Speaker 1: So I just don't understand why there isn't why Schumer

448
00:24:46,280 --> 00:24:49,840
Speaker 1: is not out there whipping votes against his bill, like what,

449
00:24:50,600 --> 00:24:54,600
Speaker 1: don't laugh at me, don't laugh at me. I were

450
00:24:55,680 --> 00:25:00,960
Speaker 1: Senate Majority Minority leader, I'd be out there being like, look, man.

451
00:25:00,800 --> 00:25:04,159
Speaker 4: This is what I to say, but you can't possibly

452
00:25:04,240 --> 00:25:07,240
Speaker 4: expect that Chuck Schumer would do that. I mean, that's

453
00:25:07,280 --> 00:25:10,200
Speaker 4: what I'm laughing at, is the idea of Chuck Schumer

454
00:25:10,280 --> 00:25:10,760
Speaker 4: doing that.

455
00:25:11,240 --> 00:25:13,720
Speaker 1: Well, if he should be doing that, are you sorry

456
00:25:13,760 --> 00:25:14,200
Speaker 1: to tell you?

457
00:25:14,480 --> 00:25:17,920
Speaker 4: Yes, there's a whole laundry list of things he should

458
00:25:18,119 --> 00:25:21,240
Speaker 4: have been doing, and should be doing and should do

459
00:25:21,320 --> 00:25:25,120
Speaker 4: in the future, and he hasn't really checked off any

460
00:25:25,119 --> 00:25:28,320
Speaker 4: of them as far as I can tell. And you

461
00:25:28,359 --> 00:25:31,800
Speaker 4: know you're right. Look the Democrats. You started your question

462
00:25:31,960 --> 00:25:34,720
Speaker 4: and by saying why are Democrats? And I thought you

463
00:25:34,760 --> 00:25:37,080
Speaker 4: were going to stop there, Like I didn't realize that

464
00:25:37,119 --> 00:25:38,919
Speaker 4: this was going to be about something specific, because the

465
00:25:39,000 --> 00:25:43,119
Speaker 4: question I'm always asking is why are democrats? Because it's

466
00:25:43,280 --> 00:25:47,959
Speaker 4: so frustrating. It's just the fact that there's only like

467
00:25:48,000 --> 00:25:52,200
Speaker 4: a handful of elected Dems who understand what is going

468
00:25:52,240 --> 00:25:55,119
Speaker 4: on right now in this country. There are the people

469
00:25:55,160 --> 00:25:57,800
Speaker 4: like Chuck Schumer who will say that they understand, but

470
00:25:57,920 --> 00:26:02,560
Speaker 4: they won't act like they understand. And as many people

471
00:26:02,640 --> 00:26:05,880
Speaker 4: have said, like we just spent a whole election warning

472
00:26:06,440 --> 00:26:09,560
Speaker 4: about what was going to happen to democracy under Trump

473
00:26:09,640 --> 00:26:11,800
Speaker 4: two point zero, and then as soon as he got

474
00:26:11,800 --> 00:26:15,360
Speaker 4: elected the Democrats acted like they hadn't been running on that.

475
00:26:16,200 --> 00:26:20,080
Speaker 4: So I agree with you, but I think, you know,

476
00:26:20,200 --> 00:26:25,800
Speaker 4: putting your faith in Chuck Schumer. You know, it's like

477
00:26:26,119 --> 00:26:30,479
Speaker 4: seeing a bowl on the table with popcorn in it

478
00:26:30,560 --> 00:26:34,520
Speaker 4: and just assuming it must be you know, fresh new

479
00:26:34,560 --> 00:26:38,280
Speaker 4: popcorn for no reason at all, and then eating it

480
00:26:38,359 --> 00:26:40,400
Speaker 4: and getting botulism and diner.

481
00:26:41,480 --> 00:26:45,800
Speaker 1: That was. That was. I had no idea where it

482
00:26:45,880 --> 00:26:48,480
Speaker 1: was going, dying as I was saying it.

483
00:26:48,640 --> 00:26:49,880
Speaker 4: I had no idea where it was going.

484
00:26:50,280 --> 00:26:55,119
Speaker 1: Andy Levy, Andy Levy, thank you, thank you, thank you.

485
00:26:56,040 --> 00:26:58,399
Speaker 4: Always a pleasure, Molly, Always a pleasure to talk to.

486
00:26:58,400 --> 00:26:59,760
Speaker 4: A New York Times best selling author.

487
00:27:01,560 --> 00:27:06,159
Speaker 1: Brian Merchant is the author of the book and the Substack,

488
00:27:06,440 --> 00:27:11,119
Speaker 1: Blood in the Machine, and host of the podcast System Crash.

489
00:27:11,320 --> 00:27:12,760
Speaker 1: Welcome to Fast Politics.

490
00:27:12,760 --> 00:27:14,800
Speaker 3: Fine, thanks so much for having me, Molly.

491
00:27:15,280 --> 00:27:18,879
Speaker 1: So let's talk about AI. It's going to replace us

492
00:27:18,920 --> 00:27:20,840
Speaker 1: all and solve all of our problems.

493
00:27:21,160 --> 00:27:24,720
Speaker 3: Yeah, that's right. Let's just uh, let's head out to

494
00:27:24,760 --> 00:27:27,600
Speaker 3: the park, let's have a picnic, and we could call it,

495
00:27:27,640 --> 00:27:29,400
Speaker 3: call it, call it a call it a century.

496
00:27:30,640 --> 00:27:33,199
Speaker 1: Sadly, no, I'm going to put it on the blockchain.

497
00:27:33,480 --> 00:27:36,040
Speaker 1: I am married to a venture capitalis he's a good one.

498
00:27:36,160 --> 00:27:40,800
Speaker 1: He's one of the few good ones because he's farf education. Yeah,

499
00:27:40,840 --> 00:27:43,399
Speaker 1: but they were like about five years where everything was

500
00:27:43,440 --> 00:27:47,320
Speaker 1: going on the fucking blockchain. You know, what's on the blockchain? Nothing? Nothing,

501
00:27:47,320 --> 00:27:51,520
Speaker 1: that's on the blockchain. So Trump trump coin, Yes, on

502
00:27:51,560 --> 00:27:54,400
Speaker 1: the blockchain, So can we put this on the blockchain?

503
00:27:54,600 --> 00:27:55,879
Speaker 3: You know? AI is.

504
00:27:56,480 --> 00:27:59,080
Speaker 5: It's interesting because it's not the same level of vaporware

505
00:27:59,280 --> 00:28:02,360
Speaker 5: right where you know, in some cases maybe would be

506
00:28:02,359 --> 00:28:05,440
Speaker 5: better for people who are getting affected by this stuff

507
00:28:05,480 --> 00:28:08,120
Speaker 5: if it were. But like on a couple of different levels,

508
00:28:08,160 --> 00:28:12,120
Speaker 5: like one, like the investment in AI has been through

509
00:28:12,160 --> 00:28:16,800
Speaker 5: the roof. It's bigger than you know, anything related to

510
00:28:16,800 --> 00:28:20,520
Speaker 5: blockchain or NFTs or the metaverse. The last you know,

511
00:28:20,680 --> 00:28:23,479
Speaker 5: handful of cycles from TA come out of Silicon Valley. No,

512
00:28:23,560 --> 00:28:26,080
Speaker 5: Silicon Valley has decided that it's you know, for all

513
00:28:26,119 --> 00:28:29,000
Speaker 5: intents and purposes, all in on AI. So that's one

514
00:28:29,000 --> 00:28:32,399
Speaker 5: of the things that is so unnerving about this moment

515
00:28:32,520 --> 00:28:36,240
Speaker 5: because they're pouring capital into it, whether or not a

516
00:28:36,320 --> 00:28:38,760
Speaker 5: lot of these products can do what they say they

517
00:28:38,760 --> 00:28:40,959
Speaker 5: can do, whether or not they work, whether or not

518
00:28:41,040 --> 00:28:44,440
Speaker 5: they're you know, bullshit machines. Can I say bullshit on

519
00:28:44,480 --> 00:28:45,000
Speaker 5: this show?

520
00:28:45,200 --> 00:28:49,440
Speaker 1: Oh please? This is not cable news, just curcip of storm.

521
00:28:49,600 --> 00:28:54,760
Speaker 1: My listeners love profanity. I wonder I really hate AI,

522
00:28:55,480 --> 00:28:57,800
Speaker 1: and I'll tell you why because I'm a writer and

523
00:28:57,840 --> 00:29:03,120
Speaker 1: I love beautiful pros and I care deeply about my

524
00:29:03,240 --> 00:29:06,040
Speaker 1: words being written by human Am I going to be

525
00:29:06,240 --> 00:29:08,560
Speaker 1: just completely fucked in about two years?

526
00:29:08,720 --> 00:29:09,840
Speaker 3: So as writers?

527
00:29:10,080 --> 00:29:13,000
Speaker 5: You know, I'm a writer myself, and we we are

528
00:29:13,120 --> 00:29:15,800
Speaker 5: used to being fucked right, like we're used to getting

529
00:29:16,240 --> 00:29:17,320
Speaker 5: from all corners.

530
00:29:17,760 --> 00:29:20,680
Speaker 1: I come from a you know, my grandfather, my mother,

531
00:29:20,800 --> 00:29:24,000
Speaker 1: so I am quite used to just watching the business

532
00:29:24,200 --> 00:29:26,400
Speaker 1: definstride itself over and over again.

533
00:29:26,760 --> 00:29:27,560
Speaker 3: But this is new.

534
00:29:27,920 --> 00:29:31,800
Speaker 5: The scale and the ease by which we can be

535
00:29:31,840 --> 00:29:35,400
Speaker 5: fucked now is new and is alarming and is doing

536
00:29:35,560 --> 00:29:41,280
Speaker 5: real wrecking ball level damage to the industry, especially, you know,

537
00:29:41,480 --> 00:29:45,080
Speaker 5: it's especially certain segments of the industry. Right of different,

538
00:29:45,360 --> 00:29:50,280
Speaker 5: there's I think journalism and writing like for magazines. They're

539
00:29:50,320 --> 00:29:53,200
Speaker 5: not going to be replaced outright, but we can already

540
00:29:53,280 --> 00:29:57,400
Speaker 5: see sort of what the glut of AI generated content

541
00:29:57,440 --> 00:30:00,360
Speaker 5: that's showing up in blogs, that's being used by place

542
00:30:00,480 --> 00:30:02,760
Speaker 5: like my former employer, like right, I used to write

543
00:30:02,760 --> 00:30:05,920
Speaker 5: the tech column at the La Times, and after I left,

544
00:30:06,000 --> 00:30:08,880
Speaker 5: they started using this AI insights tool to try to

545
00:30:08,920 --> 00:30:12,240
Speaker 5: add value to it. You know, BuzzFeed is using AI, Sports,

546
00:30:12,280 --> 00:30:16,080
Speaker 5: Illustrated Cnet, all of these places where like AI is

547
00:30:16,160 --> 00:30:19,200
Speaker 5: like coming in from the sides, and it's this. It's

548
00:30:19,320 --> 00:30:22,160
Speaker 5: very cheap. It's just cheap content doing what a bunch

549
00:30:22,200 --> 00:30:26,400
Speaker 5: of cheap stuff does to any market. It degrades it,

550
00:30:26,160 --> 00:30:30,080
Speaker 5: It lowers the value. It makes it harder for people selling,

551
00:30:30,520 --> 00:30:33,000
Speaker 5: you know, the real stuff to make a living. And

552
00:30:33,040 --> 00:30:36,120
Speaker 5: this is happening to artists and writers, graphic designers and marketers.

553
00:30:36,480 --> 00:30:38,320
Speaker 5: This is real and it is you know, like I

554
00:30:38,320 --> 00:30:40,360
Speaker 5: wrote a book about the Luddites, So this is exactly

555
00:30:40,360 --> 00:30:42,640
Speaker 5: what happened to the Luttites who made craft goods, who

556
00:30:42,640 --> 00:30:45,960
Speaker 5: made you know, cloth goods, who produced cloth stuff. Automation

557
00:30:46,360 --> 00:30:49,760
Speaker 5: flooded the market with cheap stuff, and factory owners, you know,

558
00:30:49,880 --> 00:30:53,120
Speaker 5: exploited cheap labor to compete with the people doing the

559
00:30:53,160 --> 00:30:56,400
Speaker 5: real stuff who still wanted to make good quality garments,

560
00:30:56,520 --> 00:30:58,760
Speaker 5: and then put them out of business through push them

561
00:30:58,760 --> 00:30:59,200
Speaker 5: to the street.

562
00:30:59,280 --> 00:31:00,920
Speaker 3: So I think that's where we're going.

563
00:31:01,440 --> 00:31:04,160
Speaker 5: I mean, I I worry there's a lot you know,

564
00:31:04,240 --> 00:31:09,440
Speaker 5: people like you said, people are really desirous of having

565
00:31:09,680 --> 00:31:13,320
Speaker 5: you know, human connection, like reading words written by human

566
00:31:13,400 --> 00:31:17,200
Speaker 5: people don't really seek out AI generated stuff the watcher

567
00:31:17,280 --> 00:31:19,840
Speaker 5: to read, right, Like yeah, So like I think that

568
00:31:20,000 --> 00:31:22,600
Speaker 5: there's still going to be a desire for that, but

569
00:31:22,720 --> 00:31:25,680
Speaker 5: I do think the market's going to be a lot worse.

570
00:31:25,760 --> 00:31:28,640
Speaker 5: And you know, like for people like you and I

571
00:31:28,640 --> 00:31:31,280
Speaker 5: I think it might eat away at our margins. But

572
00:31:31,360 --> 00:31:33,120
Speaker 5: you know, we've been at it for a while, Like

573
00:31:33,320 --> 00:31:36,800
Speaker 5: you know, I have established contacts at different places, like

574
00:31:37,080 --> 00:31:40,040
Speaker 5: I'll probably be okay, You'll probably be okay. But it's

575
00:31:40,080 --> 00:31:41,720
Speaker 5: the people coming up in the field, Like how do

576
00:31:41,800 --> 00:31:44,120
Speaker 5: I get started? Well, like, we just have an AI

577
00:31:44,240 --> 00:31:47,680
Speaker 5: that like generates like our our marketing copy or our

578
00:31:47,760 --> 00:31:51,240
Speaker 5: blog posts for products, or even like doing our sort

579
00:31:51,240 --> 00:31:54,280
Speaker 5: of introductory editing work because it's just cheaper to do.

580
00:31:54,480 --> 00:31:57,280
Speaker 5: So where are people getting footholds in these industries? Where

581
00:31:57,280 --> 00:32:00,640
Speaker 5: are people you know, finding opportunities to sort of even

582
00:32:00,680 --> 00:32:03,720
Speaker 5: break in? And I think AI is just like flooding

583
00:32:03,760 --> 00:32:07,760
Speaker 5: those zones and making them pretty unnavigable and so like

584
00:32:07,840 --> 00:32:10,640
Speaker 5: that along with the creative industries is where I really

585
00:32:10,680 --> 00:32:12,720
Speaker 5: fear for you know, AI's impact here.

586
00:32:13,040 --> 00:32:16,040
Speaker 1: One of the things that seems to super suck to me,

587
00:32:16,760 --> 00:32:18,800
Speaker 1: not to put too fine a point on it, is

588
00:32:19,320 --> 00:32:23,080
Speaker 1: the fake AI art. Now, one of the things that

589
00:32:23,160 --> 00:32:26,160
Speaker 1: I've been told again and again is that AI is

590
00:32:26,200 --> 00:32:28,800
Speaker 1: getting better and better and better. So even though right

591
00:32:28,840 --> 00:32:31,360
Speaker 1: now it's kind of you can still tell what's written

592
00:32:31,360 --> 00:32:34,400
Speaker 1: by AI and what's written by people, you can still

593
00:32:34,480 --> 00:32:37,680
Speaker 1: see that AI art looks a little weird, right there's

594
00:32:37,720 --> 00:32:42,560
Speaker 1: still little bits of reality. Even like the AI videos

595
00:32:42,560 --> 00:32:45,280
Speaker 1: that I've seen, you can sort of tell it's fake.

596
00:32:45,600 --> 00:32:48,640
Speaker 1: I've been promised that everyone's getting smarter and smarter and smarter,

597
00:32:49,120 --> 00:32:50,880
Speaker 1: and that AI is just going to keep going and

598
00:32:50,880 --> 00:32:52,560
Speaker 1: that we're just going to be fucked. But is that

599
00:32:52,640 --> 00:32:55,160
Speaker 1: really true or is that sort of like the blockchain?

600
00:32:55,560 --> 00:32:58,720
Speaker 5: Well, that's you know, the six million dollar question is

601
00:32:58,800 --> 00:33:01,600
Speaker 5: whether or not they can figure out what's called scaling,

602
00:33:02,120 --> 00:33:06,400
Speaker 5: because scaling, you know, training more basically open AI, which

603
00:33:06,520 --> 00:33:09,360
Speaker 5: has led this AI boom, its key insight, can really

604
00:33:09,400 --> 00:33:11,640
Speaker 5: just be boiled down to that. Like they figured out

605
00:33:11,720 --> 00:33:15,160
Speaker 5: that if you scale up the models, feed it more data,

606
00:33:15,200 --> 00:33:18,640
Speaker 5: feed it more compute, feed it more energy, then it'll

607
00:33:19,000 --> 00:33:23,200
Speaker 5: improve the quality of the results, and that has in

608
00:33:23,280 --> 00:33:25,840
Speaker 5: recent months, I kind of hit a wall where like

609
00:33:25,880 --> 00:33:28,240
Speaker 5: some things are getting better, other things are getting worse.

610
00:33:28,680 --> 00:33:30,200
Speaker 3: Reliability is getting worse.

611
00:33:30,320 --> 00:33:32,560
Speaker 5: What's so called hallucinations where it just makes stuff up

612
00:33:32,640 --> 00:33:35,680
Speaker 5: is getting wrong. So there's it's that's not to say

613
00:33:35,680 --> 00:33:38,200
Speaker 5: that they won't figure these things out, but there may

614
00:33:38,240 --> 00:33:43,160
Speaker 5: be sort of a limit to you know, what is

615
00:33:43,200 --> 00:33:46,080
Speaker 5: possible and what we can expect. Certainly, I think the

616
00:33:46,360 --> 00:33:50,200
Speaker 5: quality won't be exponential as the as Silicon Valley it

617
00:33:50,360 --> 00:33:51,120
Speaker 5: likes to sell us.

618
00:33:51,360 --> 00:33:53,520
Speaker 3: Yes, yeah, right, but I would also.

619
00:33:53,400 --> 00:33:55,400
Speaker 5: Just say, like look at what they're I mean, ultimately,

620
00:33:55,800 --> 00:33:57,760
Speaker 5: what they're trying to do is like make it so

621
00:33:57,840 --> 00:34:00,480
Speaker 5: that like you can have that picture of like a

622
00:34:00,720 --> 00:34:05,000
Speaker 5: Disney you know, animated film quality still and just sort

623
00:34:05,040 --> 00:34:07,840
Speaker 5: of poured it over, or you can like famously studio

624
00:34:07,920 --> 00:34:10,400
Speaker 5: ghibli style art and then it can do like a

625
00:34:10,440 --> 00:34:13,319
Speaker 5: service of serviceable enough job. And I think you can

626
00:34:13,320 --> 00:34:16,600
Speaker 5: see like the intent here, which is ultimately like why

627
00:34:16,719 --> 00:34:18,479
Speaker 5: why do we want this stuff to be so good?

628
00:34:18,840 --> 00:34:21,080
Speaker 5: It's like, well, so we don't have to pay animators

629
00:34:21,120 --> 00:34:23,480
Speaker 5: anymore and we can just produce this stuff in our

630
00:34:23,520 --> 00:34:26,360
Speaker 5: own backyards and sort of cut the you know, the

631
00:34:26,440 --> 00:34:28,879
Speaker 5: human artistry element out of the picture, so we can

632
00:34:29,200 --> 00:34:32,600
Speaker 5: save some bucks. That seems to be especially with this

633
00:34:32,719 --> 00:34:36,680
Speaker 5: video generation, especially with the image generation. Like what else

634
00:34:37,200 --> 00:34:42,280
Speaker 5: besides that intent, besides automating human creativity and human work?

635
00:34:42,320 --> 00:34:44,040
Speaker 5: Like why why do we even want to do this

636
00:34:44,160 --> 00:34:46,600
Speaker 5: in the first place, other than to do that or

637
00:34:46,680 --> 00:34:49,480
Speaker 5: to end to make an ad for the capabilities of

638
00:34:49,560 --> 00:34:52,919
Speaker 5: these AI companies so that investors will come and keep

639
00:34:53,239 --> 00:34:55,680
Speaker 5: from feeding money into into the machine.

640
00:34:55,800 --> 00:34:57,760
Speaker 1: So I want to talk to you about this super

641
00:34:57,800 --> 00:35:02,160
Speaker 1: interesting GOP campaign to I love that nobody in Congress

642
00:35:02,440 --> 00:35:05,919
Speaker 1: left or the right has any interest in passing any regulations, right,

643
00:35:06,000 --> 00:35:08,399
Speaker 1: the one thing that they could fucking do to help

644
00:35:08,480 --> 00:35:11,880
Speaker 1: the rest of us. No interest. Okay, God forbid, we

645
00:35:12,000 --> 00:35:14,320
Speaker 1: tell you guys what to do. Don't want to regulate,

646
00:35:14,400 --> 00:35:18,560
Speaker 1: but they do want to prevent other people from regulating.

647
00:35:19,000 --> 00:35:21,400
Speaker 1: So talk us through this. When I saw this, I

648
00:35:21,520 --> 00:35:24,200
Speaker 1: was like, if we all survive this, it will be

649
00:35:24,200 --> 00:35:28,400
Speaker 1: because these people are fucking moron. But so this is

650
00:35:28,440 --> 00:35:30,799
Speaker 1: an idea here that this is a proposal to ban

651
00:35:31,040 --> 00:35:35,560
Speaker 1: AI lawmaking in the reconciliation. How you put that in reconciliation?

652
00:35:36,040 --> 00:35:39,880
Speaker 1: I don't fucking know. You can't cover dental care and insurance,

653
00:35:39,960 --> 00:35:43,560
Speaker 1: but you can put you're not allowed to regulate AI

654
00:35:43,719 --> 00:35:48,480
Speaker 1: in a reconciliation built spoiler, maybe the parliamentarian now just

655
00:35:48,520 --> 00:35:52,200
Speaker 1: as crack and doesn't do any other stuff, so maybe

656
00:35:52,280 --> 00:35:54,960
Speaker 1: she's good with this, but talk to us about this.

657
00:35:55,040 --> 00:35:57,239
Speaker 1: So you're gonna prevent regulation.

658
00:35:57,200 --> 00:36:00,000
Speaker 5: Like wild, wild stuff, Like I mean, I'm old enough

659
00:36:00,080 --> 00:36:03,440
Speaker 5: to remember last year when GOP was like the Party

660
00:36:03,440 --> 00:36:06,759
Speaker 5: of States Rights when the issue was abortion. It's like, oh,

661
00:36:06,880 --> 00:36:09,839
Speaker 5: let's let the states decide because states rights, states rights.

662
00:36:10,040 --> 00:36:12,799
Speaker 5: When it comes to AI, though, like it's just like

663
00:36:13,160 --> 00:36:17,160
Speaker 5: this innovation is just too precious to be regulated. So

664
00:36:17,239 --> 00:36:20,440
Speaker 5: we're going to pass this bill sort of an amendment

665
00:36:20,560 --> 00:36:24,960
Speaker 5: nestled into reconciliation, which is it. I've never seen anything

666
00:36:25,000 --> 00:36:27,800
Speaker 5: like this before, like this is it's it's totally totally

667
00:36:27,840 --> 00:36:31,200
Speaker 5: wild and you're going to love like the justification that

668
00:36:31,239 --> 00:36:34,600
Speaker 5: they give because I called up Energy and Commerce and

669
00:36:34,680 --> 00:36:37,319
Speaker 5: I talked to them about it and amazing and they

670
00:36:37,360 --> 00:36:40,359
Speaker 5: told me how they're planning on justifying this. So yeah,

671
00:36:40,360 --> 00:36:44,359
Speaker 5: So basically, it's this ban on any state's ability to

672
00:36:44,520 --> 00:36:48,520
Speaker 5: enact or enforce laws about AI. That's like you just can't.

673
00:36:48,760 --> 00:36:51,320
Speaker 5: They're saying you can't do it, Like, is it constitutional?

674
00:36:51,360 --> 00:36:53,560
Speaker 5: How are they going to enforce this ban? These are

675
00:36:53,600 --> 00:36:57,359
Speaker 5: great questions, but it's clearly aimed at a few places, right,

676
00:36:57,480 --> 00:37:01,000
Speaker 5: like California being the big economy that it is and

677
00:37:01,080 --> 00:37:05,160
Speaker 5: having passed influential statewide legislation that has then had like

678
00:37:05,239 --> 00:37:08,400
Speaker 5: a knock on effect that everybody that you know, for

679
00:37:08,480 --> 00:37:12,719
Speaker 5: good examples automakers, right, they passed like exhaust standards, and

680
00:37:12,719 --> 00:37:15,319
Speaker 5: then suddenly all the automakers had to just decided to

681
00:37:15,320 --> 00:37:17,719
Speaker 5: make them for the whole state. So Jill p Yeah,

682
00:37:17,920 --> 00:37:19,799
Speaker 5: they don't like this, they don't like that California has

683
00:37:19,800 --> 00:37:22,120
Speaker 5: this power. So it's pretty chiefly aimed I think at

684
00:37:22,120 --> 00:37:25,000
Speaker 5: California and whether or not it might because it's threatening

685
00:37:25,000 --> 00:37:28,560
Speaker 5: to pass a bunch of pretty like pretty common sense

686
00:37:28,600 --> 00:37:32,080
Speaker 5: AI stuff. There's nothing even that's even that crazy. I

687
00:37:32,160 --> 00:37:35,360
Speaker 5: talked to that allowed, yes, con.

688
00:37:35,440 --> 00:37:37,719
Speaker 3: But not allowed at all. Yeah, I talked to one

689
00:37:37,760 --> 00:37:38,840
Speaker 3: of the bill co authors.

690
00:37:39,000 --> 00:37:41,680
Speaker 5: It's stuff like, if your employer is going to use

691
00:37:41,719 --> 00:37:44,040
Speaker 5: AI to like hire or fire you, they have to

692
00:37:44,120 --> 00:37:46,799
Speaker 5: let you know they can't use Yeah, well they have

693
00:37:46,840 --> 00:37:49,200
Speaker 5: to tell you, like right, that's beyond the pale, like

694
00:37:49,400 --> 00:37:52,680
Speaker 5: very common sense stuff. But anyways, the AI industry, Open AI,

695
00:37:53,080 --> 00:37:56,680
Speaker 5: Meta IBM even they've been lobbying full force against this,

696
00:37:56,760 --> 00:37:59,200
Speaker 5: and they've got Trump's an ear because there's so many

697
00:37:59,480 --> 00:38:01,799
Speaker 5: you know, tech folks.

698
00:38:01,560 --> 00:38:03,440
Speaker 3: And they got the money, and they got tech folks

699
00:38:03,440 --> 00:38:04,520
Speaker 3: in the in the White House.

700
00:38:04,560 --> 00:38:08,080
Speaker 5: They had they got Mark Andriesen and David Sachs and

701
00:38:08,120 --> 00:38:08,640
Speaker 5: all these guys.

702
00:38:08,840 --> 00:38:12,560
Speaker 1: Those guys seem great. They seem very yeah.

703
00:38:11,960 --> 00:38:14,080
Speaker 3: Real, real, real shining stars, real wonderful.

704
00:38:14,120 --> 00:38:14,279
Speaker 1: Man.

705
00:38:14,719 --> 00:38:17,200
Speaker 5: The GP slides this in and they're going to say

706
00:38:17,239 --> 00:38:19,759
Speaker 5: we're gonna stop California from being able to do this

707
00:38:19,840 --> 00:38:25,120
Speaker 5: before they even succeed or try. And their justification is, well,

708
00:38:25,800 --> 00:38:28,840
Speaker 5: we are going to start using AI tools to modernize

709
00:38:28,880 --> 00:38:31,120
Speaker 5: like the Department of Commerce, and we're gonna have a

710
00:38:31,160 --> 00:38:34,160
Speaker 5: chatbot in like the GSA and C and the you know,

711
00:38:34,200 --> 00:38:37,680
Speaker 5: Government Services Administration. And if we have these AI tools

712
00:38:37,719 --> 00:38:39,600
Speaker 5: there and we're like you know, buying them from an

713
00:38:39,640 --> 00:38:44,280
Speaker 5: AI company and California regulates it, that might make AI

714
00:38:44,360 --> 00:38:48,239
Speaker 5: more expensive and therefore it's a budget issue that we

715
00:38:48,280 --> 00:38:52,960
Speaker 5: can put into reconciliation. That's their justification that regulation might

716
00:38:53,000 --> 00:38:58,439
Speaker 5: make AI more expensive, and that then they that they could,

717
00:38:58,440 --> 00:39:00,560
Speaker 5: they would have to the government would would have to

718
00:39:00,600 --> 00:39:03,520
Speaker 5: bear those costs, and therefore they have to ban the state's.

719
00:39:03,280 --> 00:39:08,399
Speaker 3: Ability to regulate it whatever. I know, they're just making

720
00:39:08,680 --> 00:39:09,800
Speaker 3: up at this point, right.

721
00:39:09,719 --> 00:39:12,239
Speaker 1: I mean, at this point one of the things that

722
00:39:12,280 --> 00:39:15,640
Speaker 1: I've really been impressed with in this administration is just

723
00:39:15,960 --> 00:39:20,600
Speaker 1: ability to completely lie about almost everything, with making Trump

724
00:39:20,640 --> 00:39:26,600
Speaker 1: one point zero really look like salad days of moral confidence.

725
00:39:27,040 --> 00:39:29,440
Speaker 5: It's really wild like that. They and yeah, they're just

726
00:39:29,480 --> 00:39:31,600
Speaker 5: making shit up to justify it. It does not matter

727
00:39:31,760 --> 00:39:33,799
Speaker 5: like it does. He could have said anything, even though

728
00:39:33,960 --> 00:39:36,319
Speaker 5: they still have something. I guess they just can't tell

729
00:39:36,320 --> 00:39:38,920
Speaker 5: a reporter were just going to do it. We want to,

730
00:39:39,560 --> 00:39:40,000
Speaker 5: we want to.

731
00:39:40,280 --> 00:39:42,120
Speaker 3: That would be a refreshing, right, Yeah.

732
00:39:42,160 --> 00:39:47,560
Speaker 1: So what about the like doomsday scenario AI. We've seen

733
00:39:47,600 --> 00:39:53,000
Speaker 1: this before in movies, right, automates whatever ends up in

734
00:39:53,040 --> 00:39:56,120
Speaker 1: a sort of cold war situation, I mean wargames. Right,

735
00:39:56,120 --> 00:39:58,799
Speaker 1: We've seen this in the eighties, the idea that AI

736
00:39:58,880 --> 00:40:01,959
Speaker 1: would would create nuclear holocaust, Like, what are the adds

737
00:40:02,000 --> 00:40:06,200
Speaker 1: to that? Fifty to fifty forty nine fifty one, I mean,

738
00:40:06,360 --> 00:40:07,200
Speaker 1: tell me what you think.

739
00:40:07,600 --> 00:40:11,120
Speaker 5: So everybody thinks about skynet, right, but I think the

740
00:40:11,200 --> 00:40:14,680
Speaker 5: reality you know, skinett is where like the computers decide.

741
00:40:14,560 --> 00:40:16,600
Speaker 1: To explain that desk because I have no idea what

742
00:40:16,640 --> 00:40:16,920
Speaker 1: that is.

743
00:40:17,120 --> 00:40:17,319
Speaker 4: Yeah.

744
00:40:17,360 --> 00:40:21,360
Speaker 5: Yeah, So Skynet is the villain of the Terminator movies. Yeah, okay,

745
00:40:21,520 --> 00:40:26,239
Speaker 5: we're an AI that has been integrated into the the

746
00:40:26,280 --> 00:40:29,920
Speaker 5: you know, the military, the Department of Defense, becomes self

747
00:40:29,920 --> 00:40:33,759
Speaker 5: aware and then it decides that humans are you know,

748
00:40:33,800 --> 00:40:36,719
Speaker 5: they're trying to shut it down because it becomes too powerful.

749
00:40:36,920 --> 00:40:39,319
Speaker 5: It decides humans are a threat, and then you know,

750
00:40:39,520 --> 00:40:42,680
Speaker 5: the Terminator franchise takes place where the machines try to

751
00:40:42,719 --> 00:40:46,279
Speaker 5: exterminate humanity because it's a threat to AI obviously. And

752
00:40:46,320 --> 00:40:48,160
Speaker 5: that's a lot of like sort of the worst case

753
00:40:48,160 --> 00:40:51,680
Speaker 5: scenarios that are sort of pedled, I think quite usefully

754
00:40:51,800 --> 00:40:55,600
Speaker 5: by the Silicon Valley companies, Like they have an interest

755
00:40:55,680 --> 00:40:58,919
Speaker 5: in us being afraid of this all powerful technology of

756
00:40:59,040 --> 00:41:01,520
Speaker 5: you know, these doomsday scenarios, because then it kind of

757
00:41:01,640 --> 00:41:05,280
Speaker 5: just suggests, right that like their technology is that powerful,

758
00:41:05,320 --> 00:41:08,759
Speaker 5: it has that capacity, and it may not be an

759
00:41:08,760 --> 00:41:12,880
Speaker 5: alluring prospect to have humanity you go down in flames,

760
00:41:13,400 --> 00:41:15,440
Speaker 5: but if the software is that powerful that it can

761
00:41:15,440 --> 00:41:18,720
Speaker 5: certainly like you know, replace Joe at his corner office,

762
00:41:18,719 --> 00:41:21,120
Speaker 5: and they can sell you some enterprise software for a

763
00:41:21,120 --> 00:41:23,800
Speaker 5: profit in the meantime. So they've had like an interest

764
00:41:23,800 --> 00:41:26,399
Speaker 5: in selling this sort of doomsday scenario. But I think

765
00:41:26,400 --> 00:41:30,600
Speaker 5: the real issue is just as scary, and that's that

766
00:41:30,960 --> 00:41:34,200
Speaker 5: it starts getting everybody to sort of outsource their thinking

767
00:41:34,440 --> 00:41:38,600
Speaker 5: to AI, or to feel comfortable just letting AI do

768
00:41:38,760 --> 00:41:42,680
Speaker 5: it and not checking it. And increasingly we are having

769
00:41:42,680 --> 00:41:46,040
Speaker 5: these automated systems that aren't so sophisticated they're going to

770
00:41:46,120 --> 00:41:48,920
Speaker 5: methodically wipe us all out, but that are so clumsy

771
00:41:49,000 --> 00:41:52,520
Speaker 5: that they allow for grave errors. I think like that

772
00:41:52,719 --> 00:41:56,200
Speaker 5: extends to geopolitics, right as we're.

773
00:41:56,000 --> 00:41:58,719
Speaker 3: In we're going to die, so we we may die.

774
00:41:58,840 --> 00:42:01,759
Speaker 5: And you know, one of the things that was going

775
00:42:01,800 --> 00:42:04,840
Speaker 5: on in Israel Gaza was that they were using an

776
00:42:04,880 --> 00:42:08,360
Speaker 5: AI system for like targeting, and they were outsourcing their thinking.

777
00:42:08,520 --> 00:42:10,840
Speaker 5: People were just hitting the button because the AI system

778
00:42:10,920 --> 00:42:14,480
Speaker 5: isn't that sophisticated enough to like really pick the right

779
00:42:14,520 --> 00:42:17,400
Speaker 5: target through it. But it creates that bureaucratic sort of

780
00:42:17,719 --> 00:42:20,839
Speaker 5: buffer zone where people can just feel like, oh, well,

781
00:42:20,880 --> 00:42:22,919
Speaker 5: it's not my problem, it's the AI. And they're hitting

782
00:42:22,920 --> 00:42:26,000
Speaker 5: the button and selecting a new target. And now we

783
00:42:26,080 --> 00:42:28,960
Speaker 5: have all these talks about open ayes, we'll talking to

784
00:42:29,000 --> 00:42:32,719
Speaker 5: the Pentagon and Palenteer, which does AI is taking on

785
00:42:32,960 --> 00:42:36,520
Speaker 5: a larger role with all this targeting software, and I

786
00:42:36,560 --> 00:42:39,960
Speaker 5: think we can expect it's called scientists and researchers called

787
00:42:39,960 --> 00:42:43,880
Speaker 5: this cognitive offloading. So more people are just cognitively offloading

788
00:42:43,920 --> 00:42:46,799
Speaker 5: their tasks and their work to AI systems. And I

789
00:42:46,840 --> 00:42:50,279
Speaker 5: think the result could be a disaster. Yeah, absolutely, Well

790
00:42:50,320 --> 00:42:50,799
Speaker 5: that's good.

791
00:42:52,840 --> 00:42:56,280
Speaker 1: Result could be a disaster, nuclear holocaust, Jesse.

792
00:42:56,440 --> 00:43:00,239
Speaker 2: Any thoughts, so, Brian, I'm particularly obsessed with this not

793
00:43:00,360 --> 00:43:02,640
Speaker 2: hiring young people out of college and what this could

794
00:43:02,680 --> 00:43:03,560
Speaker 2: do that you've wrote about.

795
00:43:03,600 --> 00:43:05,720
Speaker 3: Could you talk a little bit about that. Yeah.

796
00:43:05,760 --> 00:43:09,759
Speaker 5: So there's an interesting figure that's began to surface in

797
00:43:09,840 --> 00:43:13,400
Speaker 5: the economic data, where you know, typically one of the

798
00:43:13,440 --> 00:43:17,760
Speaker 5: most hirable sort of demographics is recent college grads.

799
00:43:17,840 --> 00:43:18,000
Speaker 3: Right.

800
00:43:18,320 --> 00:43:22,560
Speaker 5: They're young, educated, willing to work for less money, and

801
00:43:22,600 --> 00:43:23,440
Speaker 5: they're ambitious.

802
00:43:23,560 --> 00:43:23,719
Speaker 3: Right.

803
00:43:23,800 --> 00:43:25,640
Speaker 5: Usually it's like kind of a no brainer for companies

804
00:43:25,680 --> 00:43:29,240
Speaker 5: to hire these folks. And in recent years that number

805
00:43:29,680 --> 00:43:32,960
Speaker 5: has started to do the number of unemployed recent college

806
00:43:32,960 --> 00:43:36,200
Speaker 5: grads has gone up, and there are a number of

807
00:43:36,239 --> 00:43:38,560
Speaker 5: different theories behind why that may be, but a big

808
00:43:38,600 --> 00:43:42,040
Speaker 5: one is is that more and more companies might just

809
00:43:42,080 --> 00:43:46,480
Speaker 5: be filling those roles with AI or a combination of

810
00:43:46,520 --> 00:43:52,640
Speaker 5: AI and like part time like algorithmically curated gigwork, where

811
00:43:52,680 --> 00:43:54,200
Speaker 5: so instead of like, hey, we don't actually need to

812
00:43:54,280 --> 00:43:57,080
Speaker 5: hire a new salaried person and give them healthcare, they

813
00:43:57,080 --> 00:43:59,600
Speaker 5: were just going to be sort of like writing our

814
00:43:59,640 --> 00:44:02,360
Speaker 5: sort of like our website copy and kind of learning

815
00:44:02,360 --> 00:44:04,440
Speaker 5: the ropes anyways. And now we can have AI just

816
00:44:04,520 --> 00:44:07,440
Speaker 5: like write the website copy or do any number of tasks.

817
00:44:07,719 --> 00:44:10,440
Speaker 5: And so the fear is that like that very important

818
00:44:10,480 --> 00:44:13,120
Speaker 5: sort of ladder you know that I alluded to earlier

819
00:44:13,520 --> 00:44:16,279
Speaker 5: is getting sort of knocked away. And you know, these

820
00:44:16,400 --> 00:44:19,560
Speaker 5: entry level jobs are are getting harder to get and

821
00:44:19,600 --> 00:44:22,360
Speaker 5: taken over by AI because they're also the ones that

822
00:44:22,400 --> 00:44:26,080
Speaker 5: are the less complex and easier to perform by by

823
00:44:26,160 --> 00:44:27,080
Speaker 5: an AI system.

824
00:44:27,440 --> 00:44:31,280
Speaker 2: Yeah, we saw a report this weekend that Amazon coders

825
00:44:31,320 --> 00:44:34,160
Speaker 2: are saying they're being treated like the warehouse workers now,

826
00:44:34,320 --> 00:44:36,560
Speaker 2: and I thought that was particularly telling.

827
00:44:36,880 --> 00:44:39,360
Speaker 5: Absolutely, I mean coding, most of the sort of the

828
00:44:39,440 --> 00:44:42,120
Speaker 5: most vocal sort of opposition tends to come from people

829
00:44:42,200 --> 00:44:45,239
Speaker 5: in creative communities. We have all of these lawsuits from

830
00:44:45,400 --> 00:44:47,920
Speaker 5: artists and authors and people who are standing up and

831
00:44:48,120 --> 00:44:50,880
Speaker 5: you know, the screenwriters and the WGA and the Screen

832
00:44:50,920 --> 00:44:54,960
Speaker 5: Actors Guild that like really fought against companies using AI

833
00:44:55,160 --> 00:44:56,600
Speaker 5: in their last strike.

834
00:44:56,719 --> 00:44:58,359
Speaker 3: But it's starting.

835
00:44:58,040 --> 00:45:01,360
Speaker 5: To hit you know, the software and engineering community really

836
00:45:01,400 --> 00:45:04,520
Speaker 5: hard too. And so far, what I'm hearing from a

837
00:45:04,520 --> 00:45:08,280
Speaker 5: lot of folks is less that it's you know, erasing

838
00:45:08,320 --> 00:45:11,319
Speaker 5: my job, but it's making it suck. Right Like now

839
00:45:11,400 --> 00:45:14,920
Speaker 5: my job is to just produce even more check AI

840
00:45:15,000 --> 00:45:18,560
Speaker 5: generated code. The creativity that went into writing a new

841
00:45:18,600 --> 00:45:21,480
Speaker 5: program has largely been taken away because we're being told

842
00:45:21,480 --> 00:45:24,000
Speaker 5: to sort of churn more stuff out. And so yeah,

843
00:45:24,040 --> 00:45:27,080
Speaker 5: when I saw that Amazon report from workers there who

844
00:45:27,120 --> 00:45:29,040
Speaker 5: are saying that it's you know, they're being turned into

845
00:45:29,239 --> 00:45:31,920
Speaker 5: sort of assembly line workers or feeling like factory workers,

846
00:45:32,040 --> 00:45:34,080
Speaker 5: I could not have been less surprised. This is what

847
00:45:34,160 --> 00:45:36,600
Speaker 5: I talked to a lot of workers affected by AI.

848
00:45:36,840 --> 00:45:38,480
Speaker 5: It's just what, you know, what I did. I put

849
00:45:38,480 --> 00:45:41,239
Speaker 5: out a call, you know, that's my ongoing project is

850
00:45:41,280 --> 00:45:44,839
Speaker 5: called AI Killed My Job. And so I'm I'm I'm

851
00:45:44,840 --> 00:45:48,799
Speaker 5: soliciting testimonies from workers and talk and interviewing workers who've

852
00:45:48,800 --> 00:45:51,759
Speaker 5: had AI come into their workplace, and yeah, I'm hearing

853
00:45:51,760 --> 00:45:55,480
Speaker 5: from a lot of coders and tech workers who say that,

854
00:45:56,320 --> 00:45:58,480
Speaker 5: you know, it has an eraser job out right, but

855
00:45:58,560 --> 00:46:01,960
Speaker 5: it's it's made it a miserable experience, and I think

856
00:46:02,360 --> 00:46:04,800
Speaker 5: that is going to be increasingly universal. I also just

857
00:46:04,880 --> 00:46:09,920
Speaker 5: talk to therapists, therapists who they're being told to integrate

858
00:46:09,960 --> 00:46:14,200
Speaker 5: AI into their work process, and certain steps of the

859
00:46:14,400 --> 00:46:16,800
Speaker 5: of the process if you work for a company like Kaiser,

860
00:46:17,040 --> 00:46:20,960
Speaker 5: are being handed over to AIS in some pretty scary ways,

861
00:46:21,239 --> 00:46:23,399
Speaker 5: like when you call in if you have a mental

862
00:46:23,480 --> 00:46:28,200
Speaker 5: health issue, and now you get an algorithmically dictated system

863
00:46:28,320 --> 00:46:30,440
Speaker 5: that is supposed to weed out whether or not you

864
00:46:30,520 --> 00:46:32,279
Speaker 5: need to talk to a real therapist. So if you're

865
00:46:32,280 --> 00:46:35,600
Speaker 5: in real trouble, then the system is supposed to flag you.

866
00:46:35,680 --> 00:46:38,239
Speaker 5: But the system's wrong a lot. And this is just

867
00:46:38,280 --> 00:46:39,960
Speaker 5: to cut out a job that used to be a

868
00:46:40,000 --> 00:46:43,320
Speaker 5: trained therapist job to you know, say, okay, I understand

869
00:46:43,360 --> 00:46:46,120
Speaker 5: that you're in severe danger to yourself and others.

870
00:46:46,280 --> 00:46:47,760
Speaker 3: I'm going to put you through to a therapist.

871
00:46:47,920 --> 00:46:51,840
Speaker 5: Now we're entrusting that job to an algorithm because Kaiser

872
00:46:51,920 --> 00:46:54,240
Speaker 5: wanted to save some bucks and so This is happening

873
00:46:54,360 --> 00:46:59,120
Speaker 5: in jobs and professions, you know, everywhere where, like illustrators

874
00:46:59,120 --> 00:47:01,560
Speaker 5: and artists and things are like actually, you know, getting

875
00:47:01,560 --> 00:47:04,080
Speaker 5: their work replaced and wiped out everywhere else. It's like

876
00:47:04,239 --> 00:47:06,880
Speaker 5: this degradation and this thing that we really have to

877
00:47:06,920 --> 00:47:07,359
Speaker 5: deal with.

878
00:47:07,600 --> 00:47:09,399
Speaker 1: Thank you, Brian, Thanks so much.

879
00:47:09,440 --> 00:47:16,880
Speaker 4: Molly, No moment of Andrew le Molly john.

880
00:47:16,760 --> 00:47:18,960
Speaker 1: Fest What is your moment of fuck ray?

881
00:47:19,480 --> 00:47:22,799
Speaker 4: First of all, this segment has a familiar ring. I'm

882
00:47:22,800 --> 00:47:26,920
Speaker 4: not sure why, but it reminds me of another segment

883
00:47:26,960 --> 00:47:27,600
Speaker 4: for some reason.

884
00:47:27,680 --> 00:47:28,319
Speaker 3: It'll come to me.

885
00:47:28,760 --> 00:47:34,560
Speaker 4: Yeah, yeah, My moment of fuckery is Trump saying that

886
00:47:34,920 --> 00:47:37,239
Speaker 4: I guess see and Christy know them together, saying they're

887
00:47:37,280 --> 00:47:41,760
Speaker 4: gonna phase out FEMA after the twenty twenty five hurricane season.

888
00:47:45,560 --> 00:47:48,520
Speaker 4: They sit there and they say things. Christino sits there

889
00:47:48,520 --> 00:47:50,440
Speaker 4: and says things like we all know from the past

890
00:47:50,440 --> 00:47:53,400
Speaker 4: that FEMA has failed thousands, if not millions of people,

891
00:47:53,520 --> 00:47:56,000
Speaker 4: and President Trump does not want to see that continue

892
00:47:56,040 --> 00:47:58,920
Speaker 4: into the future. First of all, that's not true. Second

893
00:47:58,920 --> 00:48:01,000
Speaker 4: of all, if FEMA's that, man, why are you waiting

894
00:48:01,040 --> 00:48:03,960
Speaker 4: to laughter the hurricane season like it today? You know,

895
00:48:04,040 --> 00:48:06,600
Speaker 4: if you've got a better idea, you know, this whole

896
00:48:06,640 --> 00:48:08,880
Speaker 4: idea of sending it back to the states, when the

897
00:48:08,920 --> 00:48:11,399
Speaker 4: whole idea is the states are the ones who ask

898
00:48:11,480 --> 00:48:13,680
Speaker 4: the federal government for help when they need it when

899
00:48:13,680 --> 00:48:15,920
Speaker 4: they can't do it on their own. But we're in

900
00:48:16,000 --> 00:48:19,920
Speaker 4: sort of this post federalist world where the federal government

901
00:48:20,000 --> 00:48:23,879
Speaker 4: can nationalize the National Guard on a whim, and then

902
00:48:23,880 --> 00:48:27,080
Speaker 4: at the same time, you know, they can take away

903
00:48:27,120 --> 00:48:30,920
Speaker 4: state resources by getting rid of FEMA. The whole thing

904
00:48:31,040 --> 00:48:32,279
Speaker 4: is just beyond fucked up.

905
00:48:32,680 --> 00:48:36,359
Speaker 1: Yes, Christinome's the one who shot her dog, right, I'm

906
00:48:36,360 --> 00:48:38,680
Speaker 1: not sure I want to be taking advice from that person.

907
00:48:39,120 --> 00:48:41,680
Speaker 1: I feel like her takes may be suspect from the

908
00:48:41,680 --> 00:48:45,480
Speaker 1: fact that she decided that the scene where she shoots

909
00:48:45,560 --> 00:48:49,759
Speaker 1: her puppy and buries it in a gravel pit was

910
00:48:49,920 --> 00:48:51,880
Speaker 1: a good thing to put in her memoir.

911
00:48:52,280 --> 00:48:55,560
Speaker 4: Yeah. On the other hand, she's now the director of

912
00:48:55,800 --> 00:48:57,000
Speaker 4: Homeland Security.

913
00:48:57,280 --> 00:49:01,160
Speaker 1: I don't know, she's something. Maybe she's the Secretary of State.

914
00:49:01,440 --> 00:49:04,000
Speaker 4: She wrote that memoir and then got a promotion.

915
00:49:04,520 --> 00:49:06,839
Speaker 1: Yeah wow. I don't know if working in the Trump

916
00:49:06,880 --> 00:49:09,120
Speaker 1: administration is really a promotion for her.

917
00:49:09,239 --> 00:49:11,600
Speaker 4: She thinks it's a promotion anyway, I mean, and she

918
00:49:11,640 --> 00:49:14,960
Speaker 4: certainly has more power now. So it's like, I'm just

919
00:49:15,000 --> 00:49:17,799
Speaker 4: I'm looking at these quotes. The FEMA thing has not

920
00:49:18,000 --> 00:49:21,480
Speaker 4: been a very successful experiment, and he says, that's what

921
00:49:21,520 --> 00:49:23,520
Speaker 4: you have governors for. When you have a tornado or

922
00:49:23,560 --> 00:49:25,680
Speaker 4: a hurricane. They're supposed to fix those problems.

923
00:49:25,920 --> 00:49:29,440
Speaker 1: Yeah, FEMA hasn't prevented any hurricanes.

924
00:49:29,880 --> 00:49:31,000
Speaker 4: It's true.

925
00:49:31,640 --> 00:49:33,879
Speaker 1: It has not prevented a single hurricane.

926
00:49:34,000 --> 00:49:36,320
Speaker 4: That's because the Jews are more powerful than FEMA.

927
00:49:36,400 --> 00:49:39,560
Speaker 1: Look, man, you said it. I didn't. I'm just agreeing,

928
00:49:39,719 --> 00:49:42,120
Speaker 1: but you know it. I certainly don't control the weather.

929
00:49:42,400 --> 00:49:45,120
Speaker 4: I'm just books don't just appear on the New York

930
00:49:45,120 --> 00:49:46,200
Speaker 4: Times bestseller list.

931
00:49:46,280 --> 00:49:50,360
Speaker 1: Molley, that's right, we use the weather machine. Thank you,

932
00:49:50,560 --> 00:49:52,279
Speaker 1: Andy Levy, Will you come back?

933
00:49:52,680 --> 00:49:52,839
Speaker 5: No?

934
00:49:53,000 --> 00:49:58,520
Speaker 1: Excellent. That's it for this episode of Fast Politics. Tune

935
00:49:58,600 --> 00:50:04,239
Speaker 1: in every Monday, Wednesday, Thursday and Saturday to hear the

936
00:50:04,280 --> 00:50:08,480
Speaker 1: best minds and politics make sense of all this chaos.

937
00:50:08,800 --> 00:50:11,560
Speaker 1: If you enjoy this podcast, please send it to a

938
00:50:11,719 --> 00:50:15,680
Speaker 1: friend and keep the conversation going. Thanks for listening.