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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 we have such a great show

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Speaker 1: for you today. Think like an economist. Justin Wolfers joins

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Speaker 1: us to talk about the good, bad, and very bad

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Speaker 1: economic vibes coming from the Trump White House. Then we'll

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Speaker 1: talk to MS now's own Jacob Sober about his fabulous

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Speaker 1: new book Firestorm, the great Los Angeles Fires, and America's

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Speaker 1: new age of disaster. But first the news Somalie.

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Speaker 2: We thankfully taped our episode before the horrific shooting in

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Speaker 2: Minneapolis the other day. I can't think of how long

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Speaker 2: it's been since I've been that angry. As we're seeing

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Speaker 2: here is Mega will never have any shame about what

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Speaker 2: they will turn into a culture war and a message

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Speaker 2: to their base that if you do horrible things, they

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Speaker 2: will stand by.

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Speaker 1: So I want to talk about a few things in

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Speaker 1: this story. One is that the police, or ice or

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Speaker 1: any law enforcement does not have the right to kill you,

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Speaker 1: even if you do bad stuff. They do not have

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Speaker 1: the right. We still have due process in this country,

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Speaker 1: you have bodily autonomy. You cannot kill people even if

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Speaker 1: you don't like them, even if they are a quote

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Speaker 1: unquote leftist, as the New York Post said yesterday. But

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Speaker 1: that said, I think the worst part of this story.

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Speaker 1: And look, not all victims of police violence are beautiful,

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Speaker 1: red haired Christian women who have six year old children

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Speaker 1: who they've just dropped off at school and a glove

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Speaker 1: compartment filled with stuffed animals. Most victims of police violence

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Speaker 1: don't necessarily look like that. But Magilworld has stumbled into

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Speaker 1: a hornet's nest, and they are just keep they just

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Speaker 1: keep kicking at the hornets. Here is a woman who

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Speaker 1: is every woman in Minnesota, right. She looks like everyone

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Speaker 1: in Minnesota. She acts like much of Minnesota. You know,

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Speaker 1: a lot of times Trump World will somehow imply that

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Speaker 1: a victim of police violence is a criminal or deserves

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Speaker 1: this because they were maybe a drug addict, or maybe

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Speaker 1: you know, we're involved, or maybe held a weapon. This

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Speaker 1: is a woman who had just dropped off her six

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Speaker 1: year old at school. So with that, there have been

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Speaker 1: videos that we have seen of her trying to make

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Speaker 1: a three point turn while the ice agents jumped in

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Speaker 1: front of her and shot her three times point blank.

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Speaker 1: Now there is a new video which has audio. So

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Speaker 1: Renee Nicole Good says that's fine, dude, I'm not mad

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Speaker 1: at you, and the ICE agent shoots her three times

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Speaker 1: in the face and says, fucking bitch, we all rage.

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Speaker 2: Al hawk activities right there.

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Speaker 1: But also, you can't shoot people in the face you

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Speaker 1: can't like, even if you don't like them, even if

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Speaker 1: they make you upset, you can't shoot people in the face.

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Speaker 1: And then, by the way, after she's shot in the

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Speaker 1: face three times, a thirty seven year old woman with

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Speaker 1: a six year old child, she is then denied medical care.

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Speaker 1: There is a doctor who comes and tries to treat her,

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Speaker 1: and ICE says no. So not only is this like murder,

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Speaker 1: but it's some kind of terrifying where they keep her hostage,

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Speaker 1: and instead of acting the way normal government might, which

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Speaker 1: is to say we have to investigate this, we can't

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Speaker 1: comment until it's investigated, they without any investigations, say, you know,

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Speaker 1: this is not how any of this looks. She was

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Speaker 1: an activist, she was this, and.

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Speaker 2: Then moleftists movement right radical leftist movement.

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Speaker 1: And they malign her. And then they say the FBI

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Speaker 1: is going to do the investigation and they won't let

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Speaker 1: Minnesota do the investigation. This is not a federal government

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Speaker 1: that any state wants involved in their state. And this

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Speaker 1: is where you're going to see a breakdown of federalism.

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Speaker 1: And I can't tell you how scary it is to

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Speaker 1: have a federal government that we pay taxes to and

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Speaker 1: they come in and do insanity to us. Right, Minnesota

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Speaker 1: was just minding their business and Ice and Border Patrol

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Speaker 1: came in, killed one woman, shot two other people yesterday

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Speaker 1: and now won't let the local authorities investigate because they

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Speaker 1: want what do they want? They want to have their

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Speaker 1: own people do the kind of investigation you see in

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Speaker 1: a Banana Republic. I cannot express to you just the

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Speaker 1: level of corruption. And by the way, two other things.

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Speaker 1: The reason you know that Trump world knows this is

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Speaker 1: a loser and knows that this is going to fuck

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Speaker 1: them and by the way, good.

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Speaker 2: God, yeah they fucking got But.

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Speaker 1: The reason why they know this the problem is because

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Speaker 1: you don't see Donald Trump out there right dancing and

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Speaker 1: being jubilant. You see Jade Vance. And Donald Trump is

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Speaker 1: more than happy to let Jade Vance be the face

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Speaker 1: of failure.

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Speaker 2: It is true, he's going the full bided Kabbola and

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Speaker 2: just letting JD do all the unpopular fish. What I

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Speaker 2: think though, is great. Hats off to Congressman Jared Moskowitz

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Speaker 2: is he did a profound performance of the Congressional for yesterday,

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Speaker 2: bringing the attention to something we need to do, which

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Speaker 2: is it's time for Ice Barbie Christi Noman to go,

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Speaker 2: and many Democrats seem to be calling for this. Though

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Speaker 2: I wish someone in the leadership were a little more

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Speaker 2: stern with it, but that's a different story for a

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Speaker 2: different time.

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Speaker 1: She should be impeached. I think that she should go.

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Speaker 1: I think that Trump world, unless you hold these people accountable,

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Speaker 1: they will not do anything. Two good things happening the

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Speaker 1: Democratic leadership has done that has been good War Powers Act.

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Speaker 1: Five Republicans voted with Democrats in the Senate on this

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Speaker 1: War Powers Act, trying to prevent Donald Trump from doing

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Speaker 1: any more stuff in Venezuela. My strongest guess is that

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Speaker 1: Donald Trump has completely lost interest in Venezuela and we

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Speaker 1: won't hear from it again. Probably not great for Venezuelans.

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Speaker 1: And then the other thing that they did, which I

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Speaker 1: think is good, is that we had Leader Jeffries get

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Speaker 1: this Obamacare tax credit. This expansion for three more years,

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Speaker 1: and that has been seventeen Republicans voted for that. So look,

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Speaker 1: that now goes to the Senate, and there's a world

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Speaker 1: like just like with the Epstein files, which by the way,

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Speaker 1: this DJ has not released to release one percent of

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Speaker 1: the Epstein files. It is still pretty good to see

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Speaker 1: some of these Republicans breaking with Trump. Obviously not what

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Speaker 1: we need, but still good.

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Speaker 2: So, speaking of the Epstein files, Molly, I think this

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Speaker 2: maneuver by Congressman Rocanna and Tom Massey never would have

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Speaker 2: seen us seeing Thomas Massey doing good things a year ago.

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Speaker 2: They're going to try to get a judge to oversee

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Speaker 2: the release of the Epstein files so that Pam Bondi

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Speaker 2: could stop obstructing and protecting the pedophile cabal.

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Speaker 1: Yeah, they want a special Master. Rocanna has been really

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Speaker 1: great on this and this is a really small We

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Speaker 1: know that there's a reporting that says only one percent

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Speaker 1: of the Epstein file stuff has been released. That is

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Speaker 1: absolutely insane. I am just super horrified by that. I think,

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Speaker 1: as far as I can tell, that there is a

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Speaker 1: real appetite for releasing of the Epstein files, and I

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Speaker 1: think that Donald Trump is doing everything he can to

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Speaker 1: obfuscate and try to not let people see them, not

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Speaker 1: have the DOJ release them, and so having a special

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Speaker 1: master would be really great. So I think that this

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Speaker 1: is a really smart way to do it. Again, these

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Speaker 1: guys have had to just do everything they every which

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Speaker 1: way they can to get people to pay attention to this.

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Speaker 2: So, Maali, the continued competence of Mega Rain's true. Again,

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Speaker 2: they just are the most competent.

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Speaker 1: Oh yeah, they're known for their competence.

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Speaker 2: He only hires the best people. And the prosecutor has

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Speaker 2: been disqualified from investigating with James A. Judges ruled great stuff.

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Speaker 1: Yeah, here's where we are. Trump blocked a Trump appointed

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Speaker 1: federal prosecutor from overseeing a criminal investigation into New York

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Speaker 1: Attorney General. Do you know why he did that, Kelly?

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Speaker 1: Because US district judge ruled that Trump loyalist John Sarcone

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Speaker 1: has been unlawfully serving as interim US attorney for the

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Speaker 1: Northern District of New York. There have been a couple

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Speaker 1: of Trump people where he's put them in as US

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Speaker 1: attorneys and they have been ruled to be illegal. So

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Speaker 1: this is yet another one. This federal prosecutor has oversted

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Speaker 1: his legal one hundred and twenty day appointment, and we

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Speaker 1: saw this. This was the thing we saw with everyone's

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Speaker 1: favorite pageant queen in the Southern District of Virginia. You

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Speaker 1: know what they're doing is they're doing emergency power stuff

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Speaker 1: because they can't get congressional approval for stuff. And that

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Speaker 1: is the secret to Trump is you can't get the courts.

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Speaker 1: And that's why, like when we talk about fixing the system,

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Speaker 1: one of the things that we're going to really need

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Speaker 1: is we're going to need all of those emergency powers.

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Speaker 1: I mean, there are emergency Powers Acts that have not

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Speaker 1: been repealed since nine to eleven. There are things that

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Speaker 1: are working not the way they're supposed to. They're working

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Speaker 1: on these sort of emergency war power stuff and that

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Speaker 1: has to stop. We have to sort of reset back

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Speaker 1: to a system of like the most checks and balances

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Speaker 1: you've ever seen, where you have real democratic norms and

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Speaker 1: you really don't have any of these sort of special

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Speaker 1: emergency powers. Because that's how we got That was sort

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Speaker 1: of the first step towards this presidency of a kind

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Speaker 1: of unchecked power. We have exciting news over at our

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Speaker 1: YouTube channel. This second episode from our Project twenty twenty

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Speaker 1: nine series is out now. It's a reimagining where we

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Speaker 1: examined what went wrong with democrats approach to politics and

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Speaker 1: how we can correct it and deliver changes to help

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Speaker 1: people's lives. The first episode dove into the very sexy

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Speaker 1: topic of campaign finance reform, and our second episode deals

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Speaker 1: with an even sexier topic, antitrust and regulation. We look

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Speaker 1: at how antitrust and regulation can protect American citizens and

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Speaker 1: make America thrive in an era of rampant corruption and

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Speaker 1: predatory crony capitalism. We talk to the smartest names in

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Speaker 1: the field like Lena Khan, el Vero Bedoya, Elizabeth Wilkins,

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Speaker 1: and Doha Mechi. Republicans were prepared for when they got

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Speaker 1: the levers of power. We need democrats to be too.

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Speaker 1: So please head over to YouTube and search Molli John

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Speaker 1: Fast Project twenty twenty nine or go to the Fast

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Speaker 1: Politics YouTube channel and find it there and help us

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Speaker 1: spread the word. Justin Wolfers, as a host of The

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Speaker 1: Thing Like an Economists podcast and a professor at the

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Speaker 1: University of Michigan, Welcome back, too Vast Politics.

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Speaker 3: Justin Wolfers, Well, I love Hall exaud If you always

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Speaker 3: said about talking, ready can only she say, Thank goodness,

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Speaker 3: it's economic style.

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Speaker 1: Can totally.

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Speaker 2: I'm so excited.

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Speaker 1: Things are going great every time we talk about the

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Speaker 1: numbers that come out of this admin. We finally got

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Speaker 1: some labor numbers from the Bureau of Labor and Statistics.

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Speaker 1: Talk us through what these numbers mean.

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Speaker 3: Okay, can we do a second rehearsal. Will you sound

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Speaker 3: liss bored?

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Speaker 1: Well, no, I'm not bored. I'm cynical about these numbers.

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Speaker 1: And I don't know how cynical to be about these numbers,

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Speaker 1: because remember, I mean, I know it was six months ago,

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Speaker 1: but Trump did fire the head of this organization because

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Speaker 1: he didn't like the set of numbers they released. So

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Speaker 1: I want you to sort of talk us through what

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Speaker 1: they mean, if they're real, etc. Etc. It's not boredom,

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Speaker 1: it's cynicism.

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Speaker 3: Okay, great, So the numbers were good enough that he

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Speaker 3: didn't fire anyone this morning. Right, So let me go

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Speaker 3: back a step and bring your whole audience in.

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Speaker 2: Right.

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Speaker 3: We're always trying to get a pulse of what's going

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Speaker 3: on in the economy. You might think that measuring the

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Speaker 3: economy is very straightforward. It turns out, for an economy

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Speaker 3: this big and this complicated. It's very very complicated, indeed, because.

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Speaker 1: You have different element of the economy.

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Speaker 3: Yeah, how do you even know who's doing business? How

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Speaker 3: do you know how many people are out there? How

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Speaker 3: do you know? You might be able to say what

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Speaker 3: share of people have a job, but how many people

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Speaker 3: are there in the US even there are so many

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Speaker 3: unknowns and this makes this a surprisingly difficult technical task.

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Speaker 3: So the most reliable indicator is what we call the

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Speaker 3: jobs report. That's why you and I, Molly tend to

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Speaker 3: talk on average after the first Friday of every month,

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Speaker 3: which is when these latest numbers come out. Measures the

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Speaker 3: unemployment right, which is one of the best indicators for

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Speaker 3: how the economy is doing for you and I, But

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Speaker 3: the one the markets really watches employment growth. They watch

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Speaker 3: that because it's got very good statistical properties. There's more

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Speaker 3: signal than noise normally in a normal hero then end

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Speaker 3: the lesson there and move to talking about the world.

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Speaker 3: But we're not in the normal moment, or in a

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Speaker 3: moment where as you say, Molly, the president fires statisticians

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Speaker 3: who give him facts he doesn't like, has tried to

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Speaker 3: put in place Charlattan's and clowns and undermined the very

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Speaker 3: notion of truth. So how much should you believe these numbers?

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Speaker 3: And the answer is so far these are as honest

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Speaker 3: as can be, so I believe them. Now, let me

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Speaker 3: be clear about what I do and don't believe. What

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Speaker 3: I believe is that these are a serious estimate of

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Speaker 3: what's going on, using serious, high quality statistical methods. Now,

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Speaker 3: remember it's always difficult, so that doesn't mean they're exactly right.

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Speaker 3: Second thing is right. Now things are even more complicated

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Speaker 3: because we just had a government shutdown where some numbers

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Speaker 3: weren't collected, and even more, the Bureau of Labour's satistics

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Speaker 3: is under resource.

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Speaker 2: But what I don't.

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Speaker 1: Believe is that we had the longest government shut down ever,

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Speaker 1: so there's not a precedent for it.

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Speaker 3: Right, For the first time since nineteen thirty nine, we

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Speaker 3: literally skipped a month of measuring employment and unemployment in

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Speaker 3: the United States, which we've never done before.

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Speaker 2: I know, Molly, like me.

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Speaker 3: It kept you awake, thrashing in the middle of the night,

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Speaker 3: yea cold space.

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Speaker 1: What did it to the viewers?

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Speaker 3: I should that the audience. I should know Molly would

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Speaker 3: call me and just say, hold me, what is going on?

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Speaker 3: So all of this makes things more complicated. Plus, the

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Speaker 3: economy is even more complicated because what we have is

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Speaker 3: an enormous immigration shock going on, and so it makes

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Speaker 3: it even more difficult to know literally how many Americans

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Speaker 3: there are. What hasn't happened is these numbers went to

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Speaker 3: the White House, and the White House said no, no,

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Speaker 3: The Department of Lies and Propaganda would like you to

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Speaker 3: believe the following instant. So these are true numbers. Now

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Speaker 3: here's the other way I know they're true. They don't

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Speaker 3: serve the administration's purpose. What happened this month as we

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Speaker 3: learned that job growth last month was fifty thousand, which

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Speaker 3: is very very low. That's so low that you could

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Speaker 3: say you'd call it nearly zero. We had almost no

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Speaker 3: job growth. And then the other thing that happens is

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Speaker 3: every month we learn more about what happened earlier in

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Speaker 3: our history. Sometimes mentioned businesses don't send in their reports

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Speaker 3: of how many people are on payroll on time, and

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Speaker 3: they send them in a little bit later. As a result,

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Speaker 3: we revised the numbers to make them more accurate. And

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Speaker 3: one of the really big things that happened was that

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Speaker 3: we learned in the fact that October is one of the

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Speaker 3: worst recent months we've had that jobs fell enormously in

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Speaker 3: October and they rose by lesson we previously thought November. Again,

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Speaker 3: for the audience, I don't want you to take month

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Speaker 3: to month up and downs very seriously.

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Speaker 4: Often, what we'll do is.

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Speaker 3: We'll average over what's happening over the past three months,

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Speaker 3: and when you do that, here's the payoff long later. Finally,

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Speaker 3: the poff when you look at the last three months,

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Speaker 3: we're losing.

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Speaker 1: Jobs and it's proof that they're not juicing the numbers.

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Speaker 1: The point you're saying is that they if they were

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Speaker 1: juicing the numbers, they have made them great.

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Speaker 3: If they were liars, if there were high quality liars,

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Speaker 3: these wouldn't be the liars they'd tell. There's a little

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Speaker 3: bit of leave unsaid right there, but no, these are

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Speaker 3: absolutely serious estimates. What these estimates tell us, though, is

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Speaker 3: that we're in a job's recession, by which I mean

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Speaker 3: it's not clear. A recession typically means output is declining.

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Speaker 3: It may be we're going to find out, but the

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Speaker 3: number of jobs is declining, the number of workers people

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Speaker 3: in work is declining. It's been declining for the past

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Speaker 3: three months. It's also the case that for wildly oninteresting

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Speaker 3: technical reasons, these numbers may be overstated. FED Chair Powell

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Speaker 3: said of this last press conference, he thinks they're overstated

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Speaker 3: by sixty thousand per month. Based on these numbers, ever

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Speaker 3: since Liberation Day, remember the beginning of Trump's trade war

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Speaker 3: that happened in April, We've created almost no jobs. It

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Speaker 3: may be that we subsequently learned we've actually been shrinking

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Speaker 3: the number of jobs we have in the economy since

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Speaker 3: Liberation Day.

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Speaker 1: So it could literally be zero right now.

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Speaker 3: It's awful close to zero.

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Speaker 1: But it could literally be negative fifty thousand.

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Speaker 3: More than that, it negatives fifty thousand per month over

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Speaker 3: the last seven months.

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Speaker 1: So and this is just and you don't have and

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Speaker 1: these measures don't measure every aspect of employment, right because

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Speaker 1: certain employment comes in later. That's why there's revisions.

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Speaker 3: What Powell said, FED Chair, who has the best economic

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Speaker 3: staff in the world, is he said, their estimate is

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Speaker 3: that these numbers overestimate monthly job growth by sixty thousand

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Speaker 3: for quote technical reasons. Now, let me explain what technical

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Speaker 3: reasons are so you understand why this isn't so simple. Really,

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Speaker 3: what the way we measure employment is we send out

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Speaker 3: forms to all the firms that are out there and

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Speaker 3: ask them how many workers they have. Now, if I

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Speaker 3: sent out a form to one in every hundred firms

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Speaker 3: that are out there, then all I do is I

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Speaker 3: take the total number of workers and I multiply by

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Speaker 3: one hundred, and that would tell me how many jobs

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Speaker 3: they were. The problem is, we don't know if we're

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Speaker 3: sending them out to one and one hundred or one

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Speaker 3: on one hundred and one, because we don't know how

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Speaker 3: many firms there are. The reason for that is every

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Speaker 3: day businesses are dying and every day new businesses are

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Speaker 3: being born, and the government doesn't necessarily see them until

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Speaker 3: the next tax season. So we literally don't know how

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Speaker 3: many businesses there are. And so if there are fewer

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Speaker 3: small businesses being born, or if there are more old

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Speaker 3: businesses dying than we'd previously thought, and there's good reasons

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Speaker 3: to think that's the case based on other statistics than

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Speaker 3: our existing methods, which are honest, are honest, but inaccurate.

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Speaker 3: So it looked no one expects that the current pessimistic

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Speaker 3: numbers that show no job growth. Let me get rid

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Speaker 3: of the negatives, double negatives. The current numbers show no

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Speaker 3: job growth, effectively no job growth since Liberation Day. Everyone

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Speaker 3: expects that to be an overstatement, too rosy, too optimistic. Wow,

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Speaker 3: If anything, reality is worse.

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Speaker 1: So I want we're going to go to the next

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Speaker 1: question here, which is the Dow, which is not the economy,

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Speaker 1: the markets, public markets.

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Speaker 3: I just want to stick on jobs for a moment

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Speaker 3: because I think that I really do want people to

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Speaker 3: understand the job market is in a very dire strait.

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Speaker 3: So the first thing I want to say is, this

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Speaker 3: is the end of December data, and so we have

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Speaker 3: the full year.

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Speaker 2: What happened in twenty twenty five. Twenty twenty five is one.

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Speaker 3: Of the worst years outside of a recession, we've ever had.

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Speaker 3: Second fact I like, just because I think it's fun,

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Speaker 3: is since Liberation Day, Canada has produced more jobs than

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Speaker 3: the United States. Canada, who arguably will meant to be

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Speaker 3: one of the biggest losers out of trade War, Canada,

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Speaker 3: which is one tenth the size of the United States,

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Speaker 3: is producing almost twice as many jobs. So really, what's

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Speaker 3: going on is the United States economy has stopped? Why problem?

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Speaker 2: Why look around?

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Speaker 1: No, I know why the American economy has stopped, But

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Speaker 1: I want to know why Canada. So what Cana has

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Speaker 1: picked up all the slack.

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Speaker 3: No, it's not that American jobs have gone across the

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Speaker 3: boarder necessarily. It's just that the American economy has stopped

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Speaker 3: and other economies have not.

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Speaker 1: So they're picking up this slack. So if you could buy,

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Speaker 1: if you could import export with the US, and now

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Speaker 1: you can't because it's too expensive, you just go to

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Speaker 1: Canada where it's cheaper.

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Speaker 2: I'm not going to buy at that.

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Speaker 3: I just want to say, there are two economies that

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Speaker 3: happen to me, next to each other. One of them

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Speaker 3: has stopped growing and the other has not. That right

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Speaker 3: tells you something has gone wrong in the United States

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Speaker 3: that has not happened elsewhere through North America.

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Speaker 4: That's the one.

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Speaker 3: You think of. Anything that's happened in the United States

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Speaker 3: but not in other countries.

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Speaker 1: No, certainly not, and certainly not a trade war that's

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Speaker 1: good and easy to win. Even though the real number

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Speaker 1: of tariffs we know from the New York Times supporting

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Speaker 1: is the tariff numbers are actually about half what the

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Speaker 1: administration is they are, it's still enough to kill the economy.

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Speaker 3: Let's go back and explain that two ways. I want

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Speaker 3: to be clear about what the New York Times is saying,

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Speaker 3: and I want to be clear about what's going on

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Speaker 3: with the economy. I'm sorry for being a boring professor.

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Speaker 3: Every time you see something interesting, I'm like, let's slow

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Speaker 3: down and explain right now, it's.

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Speaker 2: Good, okay.

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Speaker 3: So a question I've gotten frequently is if tariff's are

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Speaker 3: so bad, why hasn't it destroyed the American economy. But

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Speaker 3: one of the things is we actually haven't had tariffs

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Speaker 3: very much.

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Speaker 2: Right.

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Speaker 3: Remember Trump was elected in January, everyone said, where's your

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Speaker 3: tariff regim and he finally got around to.

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Speaker 4: It in April.

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Speaker 3: He announced it in April and Liberation Day, and then

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Speaker 3: seven days later said, oh, just kidding, I didn't realize

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Speaker 3: that would freak global markets out. I'm now going to

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Speaker 3: take ninety days off. He then took ninety days off.

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Speaker 3: That takes you from April through to April, May, June, July,

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Speaker 3: and then he got to July and then realized he

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Speaker 3: hadn't made ninety deals in ninety days. In fact, he'd

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Speaker 3: made none, and said, well, we're going to put the

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Speaker 3: tariffs back on. But he realized in that ninety days

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Speaker 3: he'd forgotten to think about what they should be. So

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Speaker 3: he gave himself another twenty four day extension, then announced

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Speaker 3: a set of tariffs actually were remarkably similar to what

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Speaker 3: they'd been way back in April. And then his tariff

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Speaker 3: nerds said, well, we can't get that entered in the

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Speaker 3: computers quick enough. That'll take another seven days. And so

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Speaker 3: once we start to faff around, it takes to like

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Speaker 3: August or September until we get tariffs, by which point

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Speaker 3: he also starts offering exceptions. So went back, renegotiated with Canada,

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Speaker 3: and basically most trade with Canada became tariff free. He

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Speaker 3: backed down on a range of things. Remember the term taco.

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Speaker 3: And it turns out, if you're willing to bring just

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Speaker 3: the right bauble to the White House, you can whisper

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Speaker 3: and say, hey, we'd like a special exemption or exception

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Speaker 3: here there or somewhere else. And so it turns out

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Speaker 3: there's the tariff regime as announced, and there's the tariff

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Speaker 3: regime has actually implemented. So first of all, the announcements

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Speaker 3: were months ahead of the implementation. The second thing is

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Speaker 3: the announcements were big and public, and the walkbacks were

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Speaker 3: fairly private, and so it turns out the amount of

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Speaker 3: tariff revenue we've taken in is much less than you

438
00:23:05,760 --> 00:23:08,560
Speaker 3: would have expected given the bold pronouncements, which is to say,

439
00:23:08,600 --> 00:23:11,679
Speaker 3: there are now so many exceptions, loopholes riddled through the

440
00:23:11,720 --> 00:23:14,520
Speaker 3: whole darn thing that and I think there's as good news.

441
00:23:14,880 --> 00:23:17,359
Speaker 3: Trump has actually implemented fewer tariffs than you said he would.

442
00:23:17,480 --> 00:23:20,280
Speaker 3: That's the reporting from the New York Times. So we

443
00:23:20,320 --> 00:23:22,960
Speaker 3: do have tariffs, but they're not quite as bad as Trump.

444
00:23:22,800 --> 00:23:25,240
Speaker 1: And they're at a lower rate than he says they are.

445
00:23:25,640 --> 00:23:29,560
Speaker 3: Right now, let's come back, Well, if there's not huge tariffs,

446
00:23:29,600 --> 00:23:31,520
Speaker 3: what's going on with the economy? So, first of all, one,

447
00:23:31,800 --> 00:23:34,000
Speaker 3: these are still big. These are still the biggest tariffs

448
00:23:34,000 --> 00:23:36,760
Speaker 3: we've had in about eighty ninety hundred years. Second of all,

449
00:23:37,280 --> 00:23:39,760
Speaker 3: tariffs aren't the only thing. Tariff's might be the only

450
00:23:39,800 --> 00:23:41,520
Speaker 3: thing people like to talk to me about, but they're

451
00:23:41,520 --> 00:23:44,359
Speaker 3: not the whole economy. So what else is going on

452
00:23:44,400 --> 00:23:47,159
Speaker 3: in the economy? I think the first thing is a

453
00:23:47,240 --> 00:23:51,160
Speaker 3: huge crash in confidence. You look at consumer confidence, it's

454
00:23:51,200 --> 00:23:53,440
Speaker 3: never been this low. You look at the share of

455
00:23:53,520 --> 00:23:57,240
Speaker 3: Americans who judge the quality of American macroeconomic policies being poor.

456
00:23:57,320 --> 00:24:00,479
Speaker 3: It's literally never been this high right away, that's going

457
00:24:00,560 --> 00:24:03,159
Speaker 3: to cause problems. The second thing is you've got this

458
00:24:03,240 --> 00:24:07,639
Speaker 3: tremendous rise in uncertainty. Right The uncertainty is partly tariffs.

459
00:24:07,640 --> 00:24:09,920
Speaker 3: Will we get into trade war with China next weekend

460
00:24:10,680 --> 00:24:13,440
Speaker 3: probably depends on what's happening with Epstein more than anything else.

461
00:24:13,840 --> 00:24:16,760
Speaker 3: The uncertainty of those far greater than that, right. Remember

462
00:24:16,800 --> 00:24:19,000
Speaker 3: the CEO of Intel walked into the White House and

463
00:24:19,040 --> 00:24:21,879
Speaker 3: walked out having accidentally left behind ten percent of his

464
00:24:21,960 --> 00:24:26,160
Speaker 3: company that somehow got nationalized. The White House is taking

465
00:24:26,160 --> 00:24:29,199
Speaker 3: big positions in private sector companies. The White House is

466
00:24:29,240 --> 00:24:32,200
Speaker 3: calling CEOs and telling them what to do. The White

467
00:24:32,240 --> 00:24:35,680
Speaker 3: House is picking up foreign leaders and just bringing them home.

468
00:24:35,880 --> 00:24:39,280
Speaker 3: The White House is deciding their wives and their wives,

469
00:24:39,320 --> 00:24:42,720
Speaker 3: and the White House is deciding if and which states

470
00:24:42,840 --> 00:24:45,800
Speaker 3: American states that wants to invade next. All of this

471
00:24:46,160 --> 00:24:49,200
Speaker 3: it's tremendous cause of uncertainty. We're two weeks away from

472
00:24:49,280 --> 00:24:52,120
Speaker 3: a healthcare overhaul. Of course, we've been two weeks away

473
00:24:52,160 --> 00:24:55,160
Speaker 3: from a new healthcare plan now for ten years. All

474
00:24:55,200 --> 00:24:59,080
Speaker 3: of this means if you were my staff and you

475
00:24:59,080 --> 00:25:02,000
Speaker 3: came to me with a big vestment project. He said,

476
00:25:02,680 --> 00:25:05,399
Speaker 3: justin we should invest millions in this new factory. I

477
00:25:05,400 --> 00:25:08,919
Speaker 3: would say to you, hey, Molly, how much does it

478
00:25:08,960 --> 00:25:10,800
Speaker 3: cost to wait a few months and see if some

479
00:25:10,840 --> 00:25:14,960
Speaker 3: of these regulations actually pan out in ways that would

480
00:25:15,000 --> 00:25:17,800
Speaker 3: undermine my investment. I've always got the possibility of delaying,

481
00:25:18,480 --> 00:25:21,240
Speaker 3: and that's become an absolutely compelling choice now for a

482
00:25:21,280 --> 00:25:23,760
Speaker 3: lot of companies. And that's part of what's going on

483
00:25:23,800 --> 00:25:24,800
Speaker 3: with the economy too.

484
00:25:25,040 --> 00:25:31,440
Speaker 1: All important and relevant things. So let's talk through what

485
00:25:31,880 --> 00:25:34,680
Speaker 1: we are going to see now. The markets are doing

486
00:25:34,680 --> 00:25:38,159
Speaker 1: really well, and there's a set there's an understanding that

487
00:25:38,240 --> 00:25:41,040
Speaker 1: it's like a ke shaped economy that there are it's

488
00:25:41,080 --> 00:25:46,359
Speaker 1: a recovery where we're seeing tech giants make money. Maybe

489
00:25:46,359 --> 00:25:48,720
Speaker 1: it's an AI I mean, is this a bubble or

490
00:25:48,800 --> 00:25:51,280
Speaker 1: is this a part of a healthy economy? Explain to

491
00:25:51,320 --> 00:25:52,560
Speaker 1: us what is happening.

492
00:25:52,760 --> 00:25:55,400
Speaker 3: Okay, I'm going to start again once a lot of there,

493
00:25:55,440 --> 00:25:58,040
Speaker 3: so we'll go slowly. Let me start with the claim

494
00:25:58,240 --> 00:26:01,359
Speaker 3: that the stock market is doing well well. It's perhaps

495
00:26:01,440 --> 00:26:04,840
Speaker 3: the White House's most frequent economic claim. They're like every

496
00:26:04,880 --> 00:26:07,960
Speaker 3: economist out there says, our policies suck, but look what's

497
00:26:07,960 --> 00:26:09,800
Speaker 3: happening to the stock market. Now, the thing is, the

498
00:26:09,840 --> 00:26:13,680
Speaker 3: stock market reflects two things. That reflects the underlying innovation

499
00:26:13,840 --> 00:26:18,880
Speaker 3: impulses from the private sector and then possible changes caused

500
00:26:18,920 --> 00:26:21,000
Speaker 3: by the public sector. One way of figuring out what

501
00:26:21,560 --> 00:26:23,520
Speaker 3: they is going on with the private sector is to

502
00:26:23,520 --> 00:26:27,200
Speaker 3: look in other countries, because things like AI are genuinely global, right,

503
00:26:27,280 --> 00:26:30,239
Speaker 3: things like a shift in global demand genuinely global. And

504
00:26:30,320 --> 00:26:32,040
Speaker 3: so once you do that, it turns out that the

505
00:26:32,119 --> 00:26:35,600
Speaker 3: US stock market performance has actually been genuinely weak. Almost

506
00:26:35,600 --> 00:26:39,359
Speaker 3: any other industrialized country you visit has had stronger stock

507
00:26:39,400 --> 00:26:43,840
Speaker 3: market growth since Inauguration Day than the United States. We're

508
00:26:43,840 --> 00:26:47,639
Speaker 3: at the very very bottom. So that says there is

509
00:26:47,760 --> 00:26:52,840
Speaker 3: something that's driving global markets up. Whatever it is, the

510
00:26:53,040 --> 00:26:58,520
Speaker 3: US is doing worse relative to every other country. So normally,

511
00:26:58,520 --> 00:27:00,840
Speaker 3: if I were to look for, you know, what could

512
00:27:00,840 --> 00:27:04,480
Speaker 3: an administration claim credit for, I'd say, compare the US

513
00:27:04,520 --> 00:27:06,119
Speaker 3: to the rest of the world. Well, the US is

514
00:27:06,160 --> 00:27:08,879
Speaker 3: doing worse than the rest of the world. That says

515
00:27:08,960 --> 00:27:12,760
Speaker 3: markets have become relatively less optimistic about the US economy

516
00:27:12,840 --> 00:27:15,680
Speaker 3: relative to every other economy since the administration came to power.

517
00:27:16,680 --> 00:27:21,320
Speaker 3: So the claim that the stock market is says markets

518
00:27:21,359 --> 00:27:23,879
Speaker 3: believe that what the administration is doing is good. I

519
00:27:23,920 --> 00:27:26,960
Speaker 3: think is upside down and wrong. It shows the infatuation.

520
00:27:27,320 --> 00:27:29,920
Speaker 3: It shows that American business reporters know how to look

521
00:27:29,960 --> 00:27:31,720
Speaker 3: up the Dow Jones, but don't know how to look

522
00:27:31,800 --> 00:27:34,080
Speaker 3: up what's happening in the rest of the world. I

523
00:27:34,160 --> 00:27:36,040
Speaker 3: know it's weird to say that Americans can be a

524
00:27:36,080 --> 00:27:37,200
Speaker 3: little inward looking, but.

525
00:27:37,640 --> 00:27:38,840
Speaker 2: Certainly for a moment.

526
00:27:38,960 --> 00:27:43,760
Speaker 3: Yeah, so, actually, I think stocks are not voting for

527
00:27:43,760 --> 00:27:47,880
Speaker 3: the president. Second, what the hell is going on? Well,

528
00:27:48,200 --> 00:27:51,400
Speaker 3: we are in the middle of this extraordinary AI transformation,

529
00:27:51,640 --> 00:27:54,520
Speaker 3: whatever you think of it. AI is an extraordinary technology.

530
00:27:54,680 --> 00:27:58,199
Speaker 3: There's two parts to the AI story. One part is

531
00:27:59,000 --> 00:28:01,479
Speaker 3: the long run, which is many of the jobs that

532
00:28:01,560 --> 00:28:03,320
Speaker 3: many of us do, it many of the boring parts

533
00:28:03,359 --> 00:28:05,879
Speaker 3: of our jobs computers are going to be able to do.

534
00:28:06,000 --> 00:28:09,159
Speaker 3: I choose to speak about that in optimistic terms, which is,

535
00:28:09,200 --> 00:28:11,119
Speaker 3: if it takes away the boring parts of yours and

536
00:28:11,200 --> 00:28:13,480
Speaker 3: my job, my you and I get to spend more

537
00:28:13,520 --> 00:28:16,639
Speaker 3: time doing fun things. And that's been what past technological

538
00:28:16,680 --> 00:28:17,679
Speaker 3: revolutions have done.

539
00:28:17,760 --> 00:28:19,960
Speaker 2: So the structure of our labor.

540
00:28:19,640 --> 00:28:22,520
Speaker 3: Market, of our economy, of our lives, what our children

541
00:28:22,560 --> 00:28:24,320
Speaker 3: are going to grow up and do is going to.

542
00:28:24,240 --> 00:28:25,280
Speaker 2: Be fundamentally different.

543
00:28:25,280 --> 00:28:29,520
Speaker 3: But that's a statement about future decades. In order to

544
00:28:29,640 --> 00:28:32,120
Speaker 3: create that AI companies are going to have to build

545
00:28:32,160 --> 00:28:34,440
Speaker 3: out these huge data centers, which are literally just big

546
00:28:34,520 --> 00:28:36,560
Speaker 3: rooms full of computers. And so what they're doing is

547
00:28:36,600 --> 00:28:39,200
Speaker 3: they're at a race for the future, and so they're

548
00:28:39,200 --> 00:28:44,880
Speaker 3: spending trillions of dollars gajillions, eleventy kajillion dollars on these

549
00:28:44,960 --> 00:28:47,560
Speaker 3: data centers. And it turns out that that's a huge

550
00:28:47,600 --> 00:28:50,480
Speaker 3: part of what's actually growing in the US economy right now.

551
00:28:50,600 --> 00:28:52,400
Speaker 3: So then you can think about the US as been

552
00:28:52,480 --> 00:28:56,160
Speaker 3: two economic stories. There's what's going on with your AI buildout,

553
00:28:56,440 --> 00:28:59,320
Speaker 3: which is going to be short term, and there's what's

554
00:28:59,360 --> 00:29:01,080
Speaker 3: going on with the rest of the economy. Well, the

555
00:29:01,120 --> 00:29:03,600
Speaker 3: AI build out has been very strong. That has kept

556
00:29:03,640 --> 00:29:08,080
Speaker 3: stocks up around the world. It's kept the American economy growing.

557
00:29:08,200 --> 00:29:10,480
Speaker 3: The rest of the economy, though it has been very weak,

558
00:29:10,600 --> 00:29:13,080
Speaker 3: in particular the parts of the economy Trump claims to

559
00:29:13,080 --> 00:29:15,640
Speaker 3: care about, and that his policy agenda is meant to

560
00:29:15,760 --> 00:29:19,280
Speaker 3: benefit manufacturing, the goods producing sector, which is helped by

561
00:29:19,720 --> 00:29:21,600
Speaker 3: which if anyone is helped by tariffs, it would be

562
00:29:21,640 --> 00:29:25,000
Speaker 3: goods because tariffs are on goods, they're actually doing incredibly poorly.

563
00:29:25,320 --> 00:29:28,280
Speaker 3: Much of the rest of the economy is looking pretty weak.

564
00:29:29,200 --> 00:29:30,520
Speaker 3: Is that responsive, Molly.

565
00:29:31,040 --> 00:29:34,280
Speaker 1: Yes, justin Wolfer's will come back?

566
00:29:36,000 --> 00:29:36,800
Speaker 3: Yes, when of you won.

567
00:29:40,080 --> 00:29:44,040
Speaker 1: Jacob sober Off is a correspondent for NBC News and

568
00:29:44,480 --> 00:29:48,400
Speaker 1: ms NOW and the author of Firestorm, The Great Los

569
00:29:48,440 --> 00:29:55,720
Speaker 1: Angeles Fires, and America's New Age of Disaster. Welcome Too Fast, Pology.

570
00:29:55,720 --> 00:29:58,200
Speaker 4: It's Jacob sober Molly, thanks for having me back.

571
00:29:58,400 --> 00:30:01,000
Speaker 1: I'm so excited. So let's talk about this book. You

572
00:30:01,080 --> 00:30:04,640
Speaker 1: were on the ground covering those fires the minute they started.

573
00:30:04,960 --> 00:30:10,400
Speaker 1: You grew up in one of the most affected areas,

574
00:30:10,560 --> 00:30:13,000
Speaker 1: the Palastaates. Yeah, yeah, so let's talk about it.

575
00:30:13,160 --> 00:30:15,200
Speaker 5: I'll cover a lot of things in my time at

576
00:30:15,440 --> 00:30:19,360
Speaker 5: MS NOW and before that MSNBC and NBC News, but nothing,

577
00:30:19,440 --> 00:30:22,080
Speaker 5: I think, in all of my years here has ever

578
00:30:22,120 --> 00:30:24,880
Speaker 5: made me sort of stop and think I cannot understand

579
00:30:25,360 --> 00:30:28,560
Speaker 5: or comprehend what I'm witnessing in real time, as watching

580
00:30:28,600 --> 00:30:31,720
Speaker 5: my own childhood neighborhood carbonized in front of my face,

581
00:30:31,800 --> 00:30:34,760
Speaker 5: before my eyes, and in a way, I felt like,

582
00:30:35,280 --> 00:30:36,960
Speaker 5: you know, almost it was a time machine. I was

583
00:30:36,960 --> 00:30:39,040
Speaker 5: going back in time, and I could see my childhood

584
00:30:39,320 --> 00:30:43,120
Speaker 5: literally disappear as I was reporting on Primetime MSNBC on

585
00:30:43,160 --> 00:30:47,760
Speaker 5: the night of January seventh, twenty twenty five. And really,

586
00:30:47,800 --> 00:30:50,280
Speaker 5: I think now that I've spent so much time diving

587
00:30:50,280 --> 00:30:53,000
Speaker 5: deep on this is to look into the future. It

588
00:30:53,040 --> 00:30:55,720
Speaker 5: was the fire of the future, and firestorm means a

589
00:30:55,720 --> 00:30:58,960
Speaker 5: lot of things. It means the actual literal event that

590
00:30:59,000 --> 00:31:01,440
Speaker 5: I experienced, but it's all so the politics around the

591
00:31:01,440 --> 00:31:04,520
Speaker 5: moment and how that contributed to what I went through,

592
00:31:04,560 --> 00:31:05,680
Speaker 5: and so there's so.

593
00:31:05,680 --> 00:31:06,280
Speaker 2: Much it read.

594
00:31:06,320 --> 00:31:08,640
Speaker 5: The book was really like a real time, minute by

595
00:31:08,680 --> 00:31:11,120
Speaker 5: minute TikTok of what it felt like to be inside

596
00:31:11,120 --> 00:31:13,840
Speaker 5: the middle of the costliest wildfire event in American history.

597
00:31:13,920 --> 00:31:16,200
Speaker 5: But it's also an exploration of sort of the factors

598
00:31:16,240 --> 00:31:17,920
Speaker 5: that made it happen and why it's definitely going to

599
00:31:17,920 --> 00:31:18,440
Speaker 5: happen again.

600
00:31:18,600 --> 00:31:21,000
Speaker 1: When you say the fire of the future, what does

601
00:31:21,000 --> 00:31:24,360
Speaker 1: that mean? Because I think of that part of California

602
00:31:24,600 --> 00:31:28,480
Speaker 1: because of the winds, it's a different situation, So explain

603
00:31:28,560 --> 00:31:29,000
Speaker 1: what you mean.

604
00:31:29,160 --> 00:31:30,880
Speaker 5: I think that the Fire of the Future is a

605
00:31:30,880 --> 00:31:32,680
Speaker 5: lot of things, and I didn't really understand what it

606
00:31:32,720 --> 00:31:35,480
Speaker 5: was until I went to Washington actually in the fire

607
00:31:35,520 --> 00:31:37,640
Speaker 5: happened in January, and I went to Washington for the

608
00:31:38,000 --> 00:31:41,800
Speaker 5: correspondence dinner and we did this town hall on Ms.

609
00:31:41,800 --> 00:31:45,400
Speaker 5: Stephanie Rule, and I with fired federal workers. That same weekend,

610
00:31:45,640 --> 00:31:48,560
Speaker 5: I sat down with a career emergency management official that

611
00:31:48,600 --> 00:31:51,000
Speaker 5: I had met when I was covering the family separation crisis.

612
00:31:51,120 --> 00:31:53,280
Speaker 5: And he went from AJHS and tried to help the

613
00:31:53,360 --> 00:31:56,280
Speaker 5: children during that to leaving that job because of his

614
00:31:56,320 --> 00:31:59,800
Speaker 5: opposition to the policy, and went to every mass casualty

615
00:32:00,200 --> 00:32:03,040
Speaker 5: fire event over the last five years. And this guy,

616
00:32:03,160 --> 00:32:05,240
Speaker 5: Captain Jonathan White, said to me, he's the one who

617
00:32:05,280 --> 00:32:08,480
Speaker 5: said what you experienced was not some aberration. This is

618
00:32:08,520 --> 00:32:10,160
Speaker 5: the fire of the future and it's here now. And

619
00:32:10,200 --> 00:32:12,320
Speaker 5: the reason why is and he said, give me your notebook.

620
00:32:12,360 --> 00:32:14,960
Speaker 5: I was taking notes sort of a Mexican restaurant in Washington,

621
00:32:15,000 --> 00:32:16,840
Speaker 5: and he said he drew an X on the page

622
00:32:17,120 --> 00:32:20,240
Speaker 5: and he said, it is the confluence of four things.

623
00:32:20,400 --> 00:32:24,360
Speaker 5: One obviously climate change. Two our infrastructures falling apart. Three

624
00:32:24,520 --> 00:32:28,240
Speaker 5: changes in the way we live with electric car batteries exploding.

625
00:32:28,480 --> 00:32:31,000
Speaker 5: You know, these toxic substances of the past now coming out.

626
00:32:31,120 --> 00:32:34,520
Speaker 5: But for misinformation and disinformation, the amount of misinfo and

627
00:32:34,560 --> 00:32:38,479
Speaker 5: dis info that permeated literally as toxic as the fire

628
00:32:38,560 --> 00:32:41,840
Speaker 5: and the things that we're all breathing in ourself was,

629
00:32:42,200 --> 00:32:44,760
Speaker 5: if not unprecedented, I think a sign of what's to come,

630
00:32:44,840 --> 00:32:47,200
Speaker 5: particularly during this administration, which is why the book is

631
00:32:47,240 --> 00:32:50,560
Speaker 5: called Firestorm, the Great Los Angeles Fires in America's New

632
00:32:50,560 --> 00:32:53,320
Speaker 5: Age of disaster. Donald Trump was a president elect, but

633
00:32:53,360 --> 00:32:58,400
Speaker 5: it didn't stop him from interjecting, injecting himself into the

634
00:32:58,800 --> 00:33:01,880
Speaker 5: not only the recovery process, and lying about what was

635
00:33:01,920 --> 00:33:04,920
Speaker 5: going on, and picking fights with Gavin Newsom and Karen Bass,

636
00:33:05,160 --> 00:33:07,440
Speaker 5: but really in real time as the fire was unfolding.

637
00:33:07,680 --> 00:33:10,200
Speaker 5: I don't think it is an overstatement to say it

638
00:33:10,320 --> 00:33:14,320
Speaker 5: changed the way that people experience the fire itself. No politician,

639
00:33:14,400 --> 00:33:17,080
Speaker 5: Democrat or Republican has absolved for and there'll be lots

640
00:33:17,080 --> 00:33:18,760
Speaker 5: of investigative reporting how did this happen?

641
00:33:18,800 --> 00:33:19,640
Speaker 4: Why did it happen?

642
00:33:19,840 --> 00:33:22,120
Speaker 5: But the thing that makes it new and different is

643
00:33:22,160 --> 00:33:26,120
Speaker 5: the amount of politics that surrounds events like this today

644
00:33:26,480 --> 00:33:29,480
Speaker 5: and how harmful it is to the people that experienced them.

645
00:33:29,760 --> 00:33:33,520
Speaker 1: So I want to talk about that more because that

646
00:33:33,920 --> 00:33:39,400
Speaker 1: is really interesting. So the disinformation, misinformation is certainly one

647
00:33:39,760 --> 00:33:44,640
Speaker 1: element of this and the politicization of something that is

648
00:33:45,160 --> 00:33:47,960
Speaker 1: right should not be politicized one way or the other.

649
00:33:48,320 --> 00:33:51,360
Speaker 1: But the thing about this fire and why it was

650
00:33:51,400 --> 00:33:55,760
Speaker 1: so much worse than any other fire we've had, maybe ever, right,

651
00:33:55,880 --> 00:33:56,760
Speaker 1: was because it moves so.

652
00:33:56,800 --> 00:34:00,720
Speaker 4: Quickly Hurricane force wins. Yeah, I mean hurricanes.

653
00:34:00,920 --> 00:34:03,800
Speaker 5: I've covered up the natural disasters, have covered humanitarian crises

654
00:34:03,840 --> 00:34:05,560
Speaker 5: all over the world. But what this was and why

655
00:34:05,600 --> 00:34:07,959
Speaker 5: it was different was that you had hurricane force winds

656
00:34:08,000 --> 00:34:09,960
Speaker 5: coming over and it was predicted by the way. I mean,

657
00:34:10,000 --> 00:34:11,920
Speaker 5: this is a story as much as it is about

658
00:34:11,920 --> 00:34:14,719
Speaker 5: the fire and about the politicians you know, who are

659
00:34:14,719 --> 00:34:16,680
Speaker 5: involved in the fire, as it is about the workers,

660
00:34:16,719 --> 00:34:19,719
Speaker 5: the government workers who were involved, the first responders who

661
00:34:19,719 --> 00:34:21,360
Speaker 5: were involved, the people that try to stop us, and

662
00:34:21,400 --> 00:34:24,880
Speaker 5: the National Weather Service. Two guys in particular, doctor Riel

663
00:34:24,960 --> 00:34:27,840
Speaker 5: Cohen and Dave Gomberg from the National Weather Services office

664
00:34:27,840 --> 00:34:30,799
Speaker 5: in Oxnard, just west of LA predicted that these were

665
00:34:30,840 --> 00:34:34,000
Speaker 5: we're called mountain wave winds. If there was a spark

666
00:34:34,080 --> 00:34:36,480
Speaker 5: coming over the Santa Monica Mountains or the San Gabriels,

667
00:34:36,560 --> 00:34:40,360
Speaker 5: would result in catastrophic fire like we have never seen before.

668
00:34:40,440 --> 00:34:43,360
Speaker 5: And guess what, that's exactly what happened, and all it

669
00:34:43,400 --> 00:34:45,680
Speaker 5: took literally in the Palisades was you know, there are

670
00:34:45,680 --> 00:34:48,000
Speaker 5: two different approximate causes. I guess you could say of

671
00:34:48,000 --> 00:34:50,400
Speaker 5: the fire the Palisades was a holdover fire from an

672
00:34:50,480 --> 00:34:53,000
Speaker 5: arson fire seven days earlier and an Alta Dana. The

673
00:34:53,000 --> 00:34:57,560
Speaker 5: Eaton fire was faulty electrical equipment. The prevailing theory.

674
00:34:57,560 --> 00:34:59,440
Speaker 1: Is falty electrical equipment.

675
00:34:59,480 --> 00:35:01,840
Speaker 5: Where when you look at the San Gabriels, yeah, and

676
00:35:01,920 --> 00:35:05,560
Speaker 5: Eaton Canyon, there are these huge lattice steel towers that

677
00:35:05,800 --> 00:35:08,600
Speaker 5: run electrical equipment up and over the San Gabriels, and

678
00:35:08,840 --> 00:35:12,600
Speaker 5: one of them was inactive and through a process of electrification,

679
00:35:12,880 --> 00:35:15,799
Speaker 5: yet one spark, and once that spark happens, it led

680
00:35:15,840 --> 00:35:18,920
Speaker 5: to literally not only thirty one deaths between the Palisades

681
00:35:18,920 --> 00:35:22,600
Speaker 5: and Altadina, but literally thousands of homes destroyed. I always

682
00:35:22,640 --> 00:35:25,319
Speaker 5: think that these events become x ray vision, and for

683
00:35:25,360 --> 00:35:27,279
Speaker 5: me they were, especially in the aftermath of reporting this

684
00:35:27,280 --> 00:35:29,600
Speaker 5: book x ray vision about the things that are underneath

685
00:35:29,640 --> 00:35:32,920
Speaker 5: the surface of our society. And in the homeless capital

686
00:35:32,960 --> 00:35:35,680
Speaker 5: of America, more unhoused people sleeping on the street than

687
00:35:35,719 --> 00:35:38,880
Speaker 5: anywhere else. Instantly, tens of thousands of more people were

688
00:35:38,920 --> 00:35:41,719
Speaker 5: homeless forced from their homes, and we're only a year in,

689
00:35:42,000 --> 00:35:43,880
Speaker 5: but so many of them have not returned, and so

690
00:35:43,920 --> 00:35:46,000
Speaker 5: there's just so much, so much to talk about, so

691
00:35:46,080 --> 00:35:48,000
Speaker 5: much I learned at the end of the day, it's

692
00:35:48,000 --> 00:35:50,760
Speaker 5: a story about people as much as it is about politics.

693
00:35:50,840 --> 00:35:53,960
Speaker 5: And while this is a tough story, it's also a

694
00:35:53,960 --> 00:35:57,560
Speaker 5: hopeful one because I met so many people with whom

695
00:35:57,600 --> 00:35:59,800
Speaker 5: I shared, you know, the experience of I lost my

696
00:35:59,800 --> 00:36:02,279
Speaker 5: own childhood home in this fire. My brother lost the

697
00:36:02,280 --> 00:36:04,600
Speaker 5: house that he was living in, friends of mine on

698
00:36:04,680 --> 00:36:06,720
Speaker 5: both sides of town. My son had his ninth birthday

699
00:36:06,719 --> 00:36:09,400
Speaker 5: party in Altadena at a pizza place called Sidepi that

700
00:36:09,440 --> 00:36:12,080
Speaker 5: burned down in the fire. And so there's so much

701
00:36:12,080 --> 00:36:15,319
Speaker 5: that we share too. And that's why as depressing of

702
00:36:15,360 --> 00:36:17,239
Speaker 5: a year as it was, as hard as it was

703
00:36:17,239 --> 00:36:19,479
Speaker 5: for me to cover this and to spend the better

704
00:36:19,520 --> 00:36:21,879
Speaker 5: part of the last year researching how something like this could happen,

705
00:36:22,000 --> 00:36:25,000
Speaker 5: I left feeling really hopeful because of the people that

706
00:36:25,040 --> 00:36:27,000
Speaker 5: I got to meet and learn about, whether it was

707
00:36:27,080 --> 00:36:29,400
Speaker 5: JPL engineers two hundred of them lost their homes in

708
00:36:29,440 --> 00:36:32,319
Speaker 5: the fire living in Alta Dina to Caltech, or the

709
00:36:32,320 --> 00:36:34,920
Speaker 5: firefighters that did everything they could just to stop the

710
00:36:34,960 --> 00:36:36,239
Speaker 5: fire from each and every home.

711
00:36:36,360 --> 00:36:37,960
Speaker 4: That's why I love this job. That's why I love

712
00:36:38,000 --> 00:36:38,759
Speaker 4: getting to do what I do.

713
00:36:39,120 --> 00:36:44,040
Speaker 1: I want you to talk about what it's like now,

714
00:36:44,160 --> 00:36:49,239
Speaker 1: because it is environmental catastrophe. I would love you to

715
00:36:49,239 --> 00:36:53,640
Speaker 1: talk us through, like the stages of the post fire,

716
00:36:54,080 --> 00:36:57,160
Speaker 1: what the area is like now, what it looks like

717
00:36:57,239 --> 00:36:58,080
Speaker 1: it could become.

718
00:36:58,719 --> 00:36:59,600
Speaker 2: There's so much.

719
00:36:59,400 --> 00:37:01,960
Speaker 5: Work to do, and what I had hoped was that

720
00:37:02,520 --> 00:37:04,960
Speaker 5: what it would be was sort of a unifying moment.

721
00:37:05,200 --> 00:37:07,000
Speaker 5: And I can talk about all the details of the recovery,

722
00:37:07,040 --> 00:37:09,600
Speaker 5: but the reason I hoped it would be unifying as obvious.

723
00:37:09,800 --> 00:37:11,759
Speaker 5: And there was one story in particular that's in the

724
00:37:11,760 --> 00:37:14,560
Speaker 5: book that to me exemplifies how we sort of took

725
00:37:14,560 --> 00:37:16,840
Speaker 5: a wrong turn. I was standing in the Palisades on

726
00:37:16,880 --> 00:37:20,040
Speaker 5: the second morning of the fire. It was January eighth,

727
00:37:20,080 --> 00:37:21,440
Speaker 5: and I was about to go up on a special

728
00:37:21,440 --> 00:37:23,560
Speaker 5: report with Lester Holton. I looked down at my phone

729
00:37:23,880 --> 00:37:27,880
Speaker 5: and it said Katie Waldman was calling me. Katie Waldman

730
00:37:28,280 --> 00:37:30,120
Speaker 5: is now Katie Miller, which was in my phone as

731
00:37:30,200 --> 00:37:32,920
Speaker 5: Katie Waldman because I knew her during family separation as

732
00:37:32,920 --> 00:37:35,720
Speaker 5: the junior most Press deputy at the Department of Homeland Security.

733
00:37:35,800 --> 00:37:38,760
Speaker 5: She married Stephen Miller during that policy. This is Stephen

734
00:37:38,800 --> 00:37:40,759
Speaker 5: Miller's wife. And while I told her I had to

735
00:37:40,760 --> 00:37:41,960
Speaker 5: call her back because I was about to go up

736
00:37:42,000 --> 00:37:44,520
Speaker 5: on this special report, she texted me, just like so

737
00:37:44,560 --> 00:37:46,360
Speaker 5: many other people did when I was in the Palisades,

738
00:37:46,360 --> 00:37:48,600
Speaker 5: can you go check this address. You're the only person

739
00:37:48,680 --> 00:37:51,200
Speaker 5: I know who is there. And I said, what could

740
00:37:51,239 --> 00:37:54,919
Speaker 5: this possibly be about? It was Stephen Miller's parents' house.

741
00:37:55,239 --> 00:37:57,600
Speaker 5: She asked me to go by and check and see

742
00:37:57,640 --> 00:37:59,160
Speaker 5: if it was still standing. And just like I did

743
00:37:59,200 --> 00:38:01,920
Speaker 5: for the kids that i'd oaken carpool or my brother,

744
00:38:02,200 --> 00:38:04,000
Speaker 5: more other people that called, I did. I went by

745
00:38:04,160 --> 00:38:05,800
Speaker 5: and it had burned down. And I had hoped that

746
00:38:05,800 --> 00:38:08,040
Speaker 5: it was going be this moment of like Olive Branch,

747
00:38:08,280 --> 00:38:10,959
Speaker 5: that we would find common cost. And to your point

748
00:38:10,960 --> 00:38:13,279
Speaker 5: about the recovery in the aftermath, not only was she

749
00:38:13,360 --> 00:38:16,680
Speaker 5: working for Elon Musk, who was spreading misinformation about why

750
00:38:16,719 --> 00:38:20,120
Speaker 5: the water sources had run dry during the fire and

751
00:38:20,280 --> 00:38:23,840
Speaker 5: amplifying Donald Trump's conspiracy theories about the fire during the fire,

752
00:38:24,080 --> 00:38:27,560
Speaker 5: but this is an administration that has decimated so many

753
00:38:27,600 --> 00:38:29,840
Speaker 5: of the key agencies that are going to be critical

754
00:38:29,880 --> 00:38:33,320
Speaker 5: in the recovery. National Weather Service meteorologists have been fired.

755
00:38:33,560 --> 00:38:37,520
Speaker 5: Scientists and NASA's Earth Science program that study wildfires are

756
00:38:37,560 --> 00:38:41,520
Speaker 5: on the chopping block. At NIOSH National Institute for Occupational

757
00:38:41,560 --> 00:38:43,360
Speaker 5: Safety and Health. I had stood there on the corner

758
00:38:43,360 --> 00:38:46,040
Speaker 5: in Morgantown, West Virginia, talking to some of these employees

759
00:38:46,080 --> 00:38:47,799
Speaker 5: that look out for the health and well being of

760
00:38:47,800 --> 00:38:50,520
Speaker 5: firefighters and firefighters safety at a time when there were

761
00:38:50,520 --> 00:38:52,359
Speaker 5: a risk of cancer more than ever before. I had

762
00:38:52,360 --> 00:38:55,480
Speaker 5: firefighters during this fire say because of the environmental catastrophe.

763
00:38:55,520 --> 00:38:57,880
Speaker 5: I thought during the fire and certainly after that, I'm

764
00:38:57,920 --> 00:39:00,799
Speaker 5: probably going to get cancer from battling this. And that

765
00:39:00,920 --> 00:39:05,000
Speaker 5: office was decimated by this administration during the DOGE cuts,

766
00:39:05,200 --> 00:39:06,279
Speaker 5: and the list goes on and on.

767
00:39:06,440 --> 00:39:07,520
Speaker 4: That's just a partial list.

768
00:39:07,640 --> 00:39:09,920
Speaker 5: And so when you talk about the recovery, Yeah, there

769
00:39:09,920 --> 00:39:12,680
Speaker 5: are toxic substances all over as part of these fires,

770
00:39:12,680 --> 00:39:14,600
Speaker 5: and there will be more when a fire like this

771
00:39:14,680 --> 00:39:16,799
Speaker 5: happens again. The question is how do we deal with them?

772
00:39:16,880 --> 00:39:18,279
Speaker 5: You know, the answers we have to reckon with the

773
00:39:18,280 --> 00:39:19,880
Speaker 5: fact that politics is getting in the way of us

774
00:39:19,920 --> 00:39:20,480
Speaker 5: actually doing that.

775
00:39:21,480 --> 00:39:23,880
Speaker 1: Are people rebuilding or now slowly?

776
00:39:23,920 --> 00:39:25,120
Speaker 4: I went to McNally Avenue.

777
00:39:25,200 --> 00:39:28,400
Speaker 5: McNally Avenue is the street that I interviewed Gavenusam on

778
00:39:28,640 --> 00:39:30,800
Speaker 5: for me the Pressed the Saturday after the fire started.

779
00:39:30,840 --> 00:39:32,960
Speaker 5: He and I spent I think twenty minutes there talking

780
00:39:32,960 --> 00:39:35,480
Speaker 5: about what he would do, and you know, he by

781
00:39:35,520 --> 00:39:37,680
Speaker 5: the way, you know, nobody's absolved in terms of the

782
00:39:37,680 --> 00:39:39,840
Speaker 5: politics of this, about what they've been able to do

783
00:39:39,920 --> 00:39:41,680
Speaker 5: and what they've been able to accomplish. He promised a

784
00:39:41,760 --> 00:39:44,000
Speaker 5: Marshall Plan two point zero in the wake of the fire,

785
00:39:44,040 --> 00:39:46,239
Speaker 5: and there's still a really, really long way to go.

786
00:39:46,440 --> 00:39:49,719
Speaker 5: But on McNally Avenue where I met Kate Henigan, who's

787
00:39:49,760 --> 00:39:52,279
Speaker 5: a senior JPL engineer who lost her home and her

788
00:39:52,280 --> 00:39:55,360
Speaker 5: story is detailed in the fire or Herbin Lloyda Wilson,

789
00:39:55,560 --> 00:39:58,960
Speaker 5: a married couple who met at UPS and are incredible too,

790
00:39:59,080 --> 00:40:01,840
Speaker 5: incredible working class pe people, like so many people in Altadena,

791
00:40:02,120 --> 00:40:04,480
Speaker 5: that block was it looked like it was firebombd you know,

792
00:40:04,760 --> 00:40:07,360
Speaker 5: And I was just there, I think last week, checking

793
00:40:07,400 --> 00:40:09,160
Speaker 5: up on the block again. I'm going to see them

794
00:40:09,200 --> 00:40:11,840
Speaker 5: actually tomorrow, and there's one home or two homes that

795
00:40:11,880 --> 00:40:15,160
Speaker 5: are starting to be rebuilt. It's a long way from

796
00:40:15,280 --> 00:40:17,600
Speaker 5: coming back from this, and that's the case also on

797
00:40:17,640 --> 00:40:19,480
Speaker 5: the other side of the town in the Palisades, because

798
00:40:19,719 --> 00:40:23,680
Speaker 5: in addition to becoming victims of this horrible, horrible tragedy,

799
00:40:23,719 --> 00:40:25,839
Speaker 5: we live in a city that is unaffordable.

800
00:40:25,920 --> 00:40:28,560
Speaker 1: But is it safe to rebuild there? I mean, what's

801
00:40:28,600 --> 00:40:30,840
Speaker 1: the toxicity in the groundwater?

802
00:40:31,000 --> 00:40:33,000
Speaker 4: And then, yeah, it's such a good question.

803
00:40:33,040 --> 00:40:34,520
Speaker 5: The La Times has been doing and I was with

804
00:40:34,560 --> 00:40:37,000
Speaker 5: Tony Briscoe actually last night LA Times reporter who has

805
00:40:37,000 --> 00:40:40,879
Speaker 5: done some extraordinary reporting on why the federal government didn't

806
00:40:40,920 --> 00:40:44,439
Speaker 5: do soil testing for certain toxic substances the Army Corps

807
00:40:44,480 --> 00:40:46,920
Speaker 5: of Engineers. The answer is when the La Times tested

808
00:40:46,920 --> 00:40:48,720
Speaker 5: the soil, I think, he said, because the federal government

809
00:40:48,800 --> 00:40:51,319
Speaker 5: wasn't twenty percent of the homes, if I have this right,

810
00:40:51,640 --> 00:40:54,480
Speaker 5: had the toxic substances above the level of what would

811
00:40:54,520 --> 00:40:56,960
Speaker 5: be safe to rebuild. And so the onus is on

812
00:40:57,080 --> 00:40:59,440
Speaker 5: so many home owners and people to decide whether or

813
00:40:59,480 --> 00:41:02,120
Speaker 5: not they even want to come back now knowing that

814
00:41:02,400 --> 00:41:05,319
Speaker 5: this stuff, whether it's lead or asbestos, which is in

815
00:41:05,360 --> 00:41:08,680
Speaker 5: the lungs of the firefighters who battled it, but also

816
00:41:09,160 --> 00:41:11,839
Speaker 5: in the ground. According to this reporting of so many

817
00:41:11,880 --> 00:41:13,600
Speaker 5: the people who want to come back to their homes.

818
00:41:13,760 --> 00:41:15,200
Speaker 4: I mean, what would you do. I don't know what.

819
00:41:15,239 --> 00:41:18,240
Speaker 1: I would not come back. Yeah, wouldn't you not come back?

820
00:41:18,640 --> 00:41:19,560
Speaker 4: No? I don't think so.

821
00:41:19,719 --> 00:41:22,239
Speaker 5: What's the question my own brother is facing in the Palisades.

822
00:41:22,280 --> 00:41:24,439
Speaker 5: Their daughter was born in the weeks after the fire.

823
00:41:24,520 --> 00:41:26,759
Speaker 5: They're not going back to their house anytime soon. And

824
00:41:27,080 --> 00:41:29,640
Speaker 5: it's a part of the story that this firestorm, this

825
00:41:29,760 --> 00:41:32,000
Speaker 5: hurricane of fire. I have never seen anything like it,

826
00:41:32,040 --> 00:41:33,520
Speaker 5: by the way, and I describe it in detail in

827
00:41:33,560 --> 00:41:37,560
Speaker 5: the book embers flying horizontally, buildings burning horizontally, as as

828
00:41:37,600 --> 00:41:40,240
Speaker 5: the fire flies past her face with data mount arrowinds.

829
00:41:40,480 --> 00:41:43,239
Speaker 1: I mean, as as a student of Joan Didion, as

830
00:41:43,360 --> 00:41:48,000
Speaker 1: all female journalists consider themselves to base more successfully than others.

831
00:41:48,160 --> 00:41:52,080
Speaker 1: This is what she writes, you know, she writes about

832
00:41:52,120 --> 00:41:54,640
Speaker 1: this all the time. And I do wonder how much

833
00:41:54,680 --> 00:41:57,759
Speaker 1: of this, Like, obviously, environmentally we're in a lot of

834
00:41:57,800 --> 00:42:01,480
Speaker 1: trouble and the climate has changed in numerous ways. But

835
00:42:01,520 --> 00:42:03,480
Speaker 1: I just wonder how much of this more for my

836
00:42:03,520 --> 00:42:06,879
Speaker 1: own edification, Like what is California here? And what is

837
00:42:07,200 --> 00:42:10,000
Speaker 1: because the wind stuff? I don't know the say it

838
00:42:10,080 --> 00:42:12,279
Speaker 1: to Anna, I don't know that that I mean, it

839
00:42:12,320 --> 00:42:15,920
Speaker 1: may we may see changes in the jet stream that

840
00:42:16,000 --> 00:42:18,279
Speaker 1: will create that, but we don't have that.

841
00:42:18,440 --> 00:42:19,759
Speaker 4: Yeah, I think you're right.

842
00:42:19,800 --> 00:42:23,280
Speaker 5: Nobody's written more beautifully about the Santa Annas than Johan Diddyon.

843
00:42:23,320 --> 00:42:23,600
Speaker 4: Another.

844
00:42:23,920 --> 00:42:25,640
Speaker 5: I mean, I read so many books about fire as

845
00:42:25,640 --> 00:42:27,960
Speaker 5: I was sort of researching how this possibly could happen.

846
00:42:28,080 --> 00:42:31,360
Speaker 5: Mike Davis wrote The Ecology of Fear, and he famously

847
00:42:31,960 --> 00:42:35,359
Speaker 5: made the case for letting Malibu burn in the wake

848
00:42:35,440 --> 00:42:36,320
Speaker 5: of those fires.

849
00:42:36,680 --> 00:42:39,080
Speaker 4: And the thing that makes me think.

850
00:42:38,920 --> 00:42:42,200
Speaker 5: About, in addition to really how this has been a

851
00:42:42,200 --> 00:42:45,960
Speaker 5: grieving process for so many, especially me in particular, but

852
00:42:46,080 --> 00:42:48,000
Speaker 5: tens of thousands, if not millions of people who live

853
00:42:48,040 --> 00:42:50,799
Speaker 5: here and experience their city falling apart, and then, by

854
00:42:50,800 --> 00:42:52,680
Speaker 5: the way, followed by the ice rates that happened here.

855
00:42:52,800 --> 00:42:54,080
Speaker 4: And there's intersections with all of that.

856
00:42:54,120 --> 00:42:57,080
Speaker 5: The day laborers who were working to rebuild are being

857
00:42:57,160 --> 00:42:59,720
Speaker 5: targeted by the same administration as they tried to rebuild

858
00:42:59,719 --> 00:43:02,759
Speaker 5: from the fires. An undocumented worker was killed as he

859
00:43:02,800 --> 00:43:05,600
Speaker 5: was chased from home depot across the two ten Freeway

860
00:43:05,640 --> 00:43:08,520
Speaker 5: that was engulfed under an umbrella of smoke from the

861
00:43:08,520 --> 00:43:09,920
Speaker 5: flames in January.

862
00:43:10,200 --> 00:43:11,799
Speaker 4: Yeah, climate change is a big part of this.

863
00:43:11,960 --> 00:43:14,960
Speaker 5: But when I say when I talk about a proximate causes,

864
00:43:15,200 --> 00:43:16,160
Speaker 5: it's not the only one.

865
00:43:16,280 --> 00:43:18,360
Speaker 4: And if there's anything that I have taken away from.

866
00:43:18,239 --> 00:43:21,000
Speaker 5: This is that the story that is told in my

867
00:43:21,080 --> 00:43:23,879
Speaker 5: book in Firestorm is a story that in some issuer

868
00:43:23,880 --> 00:43:26,959
Speaker 5: has already happened. Look at Lahina people literally jumping into

869
00:43:26,960 --> 00:43:30,120
Speaker 5: the ocean two years prior to run away from another

870
00:43:30,560 --> 00:43:35,680
Speaker 5: urban conflagration fueled by winds just like this, and Maui exactly,

871
00:43:35,800 --> 00:43:39,480
Speaker 5: and the campfire in Paradise in northern California. At the

872
00:43:39,480 --> 00:43:41,800
Speaker 5: beginning of Newsom told me a story. I spent a

873
00:43:41,840 --> 00:43:43,719
Speaker 5: lot of time with Newsomb for this book. He told

874
00:43:43,719 --> 00:43:46,640
Speaker 5: me a story of how when he was governor elect

875
00:43:46,640 --> 00:43:49,000
Speaker 5: and Jerry Brown was governor, Trump came out to Paradise.

876
00:43:49,040 --> 00:43:52,440
Speaker 4: What did he call it, pleasure or didn't golf Paradise?

877
00:43:52,480 --> 00:43:53,840
Speaker 4: I don't remember when he called it.

878
00:43:54,080 --> 00:43:55,640
Speaker 5: And that was the first time he had seen something

879
00:43:55,719 --> 00:43:57,920
Speaker 5: like this, But since then he has gone to fires

880
00:43:58,320 --> 00:44:02,920
Speaker 5: with similar inputs. I'm at change related inputs all over California.

881
00:44:03,120 --> 00:44:06,319
Speaker 5: The difference between the LA fires and those were this

882
00:44:06,560 --> 00:44:10,600
Speaker 5: was a urban conflagration, This was a city in multiple

883
00:44:10,640 --> 00:44:14,120
Speaker 5: locations because of the winds that you describe ember cast

884
00:44:14,239 --> 00:44:17,279
Speaker 5: that went for miles and miles things for catching on fire,

885
00:44:17,320 --> 00:44:20,040
Speaker 5: miles away from the front lines of the blaze, and

886
00:44:20,200 --> 00:44:22,760
Speaker 5: that in terms of climate, in terms of the mountain

887
00:44:22,800 --> 00:44:25,160
Speaker 5: wave winds that were predicted by the National Weather Service

888
00:44:25,200 --> 00:44:27,640
Speaker 5: workers colleagues of the guys that had been fired by

889
00:44:27,680 --> 00:44:30,840
Speaker 5: this administration since then, that was the thing to me

890
00:44:30,960 --> 00:44:33,440
Speaker 5: on the ground, and as you'll read about, that was

891
00:44:33,440 --> 00:44:36,840
Speaker 5: the most the most unbelievable thing to experience physically, you know,

892
00:44:36,880 --> 00:44:39,319
Speaker 5: I could. I remember one night it was almost Stephanie Rule.

893
00:44:39,480 --> 00:44:40,759
Speaker 5: It was the first night of the fire. I could

894
00:44:40,800 --> 00:44:41,520
Speaker 5: barely stand.

895
00:44:41,320 --> 00:44:43,080
Speaker 1: Up straight right because it was so winding.

896
00:44:43,320 --> 00:44:44,640
Speaker 4: It wouldn't even feel like wind.

897
00:44:44,680 --> 00:44:47,040
Speaker 5: It felt like you were being picked up and thrown

898
00:44:47,080 --> 00:44:51,279
Speaker 5: around every direction you could imagine within seconds. And that's

899
00:44:51,280 --> 00:44:53,160
Speaker 5: why when people want to point a finger at what

900
00:44:53,280 --> 00:44:55,799
Speaker 5: happened here, I'm not so sure that there will ever

901
00:44:55,880 --> 00:44:58,680
Speaker 5: be one person to blame. There'll be plenty of investigative

902
00:44:58,719 --> 00:45:01,719
Speaker 5: reporting about like could there been more fire trucks preposition,

903
00:45:01,840 --> 00:45:04,120
Speaker 5: should Karen mass have been back from Ghana in time?

904
00:45:04,400 --> 00:45:05,920
Speaker 4: Could Kevin Usom have done anything differently?

905
00:45:05,960 --> 00:45:08,759
Speaker 5: Should the reservoir have been full in the Palisades, you know,

906
00:45:09,000 --> 00:45:11,080
Speaker 5: you name it, and then investigative reporting will go on

907
00:45:11,120 --> 00:45:13,239
Speaker 5: for years and years and years. But the reality is,

908
00:45:13,440 --> 00:45:16,760
Speaker 5: once those these guys predicted it, once the fire sparked,

909
00:45:17,280 --> 00:45:19,359
Speaker 5: there was nothing you could do to stop it. And

910
00:45:19,960 --> 00:45:22,600
Speaker 5: that's what I hope I captured well in the book,

911
00:45:22,880 --> 00:45:26,000
Speaker 5: which is that this was once the train went off

912
00:45:26,040 --> 00:45:28,560
Speaker 5: the tracks, there was no turning back. And that's where

913
00:45:28,560 --> 00:45:30,319
Speaker 5: the politics of the moment really took this to a

914
00:45:30,320 --> 00:45:31,239
Speaker 5: place that didn't need to go.

915
00:45:31,600 --> 00:45:34,200
Speaker 1: Yeah, Jacob sober Off, I hope you'll come.

916
00:45:34,120 --> 00:45:38,040
Speaker 4: Back anytime, Molly for you anything anytime. Thanks for caring

917
00:45:38,040 --> 00:45:38,600
Speaker 4: about La.

918
00:45:38,920 --> 00:45:41,360
Speaker 1: Oh yeah, we love La.

919
00:45:41,440 --> 00:45:42,440
Speaker 4: Thanks for having me on.

920
00:45:44,440 --> 00:45:49,120
Speaker 1: No moment, Jesse Canna Malli.

921
00:45:49,239 --> 00:45:52,359
Speaker 2: There is some blockbuster reporting from four h four media

922
00:45:52,400 --> 00:45:54,960
Speaker 2: who continues to kill it. And this is some of

923
00:45:55,000 --> 00:45:57,479
Speaker 2: the most disturbing report egg I've seen it a while,

924
00:45:57,520 --> 00:46:00,959
Speaker 2: which is that ICE now has a tool that uses

925
00:46:01,000 --> 00:46:05,200
Speaker 2: surveillance technology to track phones without a warrant and follow

926
00:46:05,320 --> 00:46:08,680
Speaker 2: their owner's home or to their employer. Yeah.

927
00:46:08,719 --> 00:46:14,000
Speaker 1: So this is a great example of how we don't

928
00:46:14,040 --> 00:46:17,200
Speaker 1: really know what's happening here, but ICE has billions of

929
00:46:17,280 --> 00:46:20,680
Speaker 1: dollars like billions and billions and billions of dollars. These

930
00:46:20,719 --> 00:46:25,600
Speaker 1: are these two surveillance systems called Tangle and Weblock. And

931
00:46:25,880 --> 00:46:29,240
Speaker 1: there are surveillance systems. They were purchased by ICE. ICE, remember,

932
00:46:29,280 --> 00:46:33,120
Speaker 1: has a gazillion dollars. Weblock can track phones without a

933
00:46:33,200 --> 00:46:37,480
Speaker 1: warrant and follow their owners home or to their employers. Okay,

934
00:46:37,719 --> 00:46:41,319
Speaker 1: so first of all, we really have ICE operating in

935
00:46:41,520 --> 00:46:45,320
Speaker 1: like an extra legal you know, they're operating like Donald Trump.

936
00:46:45,400 --> 00:46:48,120
Speaker 1: They just don't think the law applies to them. So

937
00:46:48,360 --> 00:46:51,279
Speaker 1: and here's this will have sort of you will have

938
00:46:51,400 --> 00:46:55,080
Speaker 1: your city, neighborhood or block will be monitored by ICE.

939
00:46:55,160 --> 00:46:57,640
Speaker 1: They can track the movement of the devices and their

940
00:46:57,640 --> 00:47:00,480
Speaker 1: owners over time, follows them from places of work to

941
00:47:00,560 --> 00:47:04,080
Speaker 1: other locations. According to the material that describes how the

942
00:47:04,120 --> 00:47:08,520
Speaker 1: system works from four four Media, it's really scary. It

943
00:47:08,719 --> 00:47:11,800
Speaker 1: is stalking. It should not be illegal. It's a huge

944
00:47:11,920 --> 00:47:16,239
Speaker 1: violation of our civil liberties. You know, maybe it's for deportation,

945
00:47:16,520 --> 00:47:19,839
Speaker 1: maybe it's for intimidation, maybe it's for any number of things.

946
00:47:19,840 --> 00:47:24,759
Speaker 1: I mean, for example, Renee Good was not a danger.

947
00:47:25,040 --> 00:47:27,160
Speaker 1: Even if she had been a danger, she should not

948
00:47:27,239 --> 00:47:29,640
Speaker 1: have been murdered. But she wasn't a danger, and she

949
00:47:29,920 --> 00:47:33,200
Speaker 1: wasn't here illegally, and she wasn't the worst of the worst.

950
00:47:33,320 --> 00:47:35,480
Speaker 1: In fact, she was an American citizen who had just

951
00:47:35,560 --> 00:47:37,440
Speaker 1: dropped out for a six year old at school. So

952
00:47:37,560 --> 00:47:41,040
Speaker 1: we know these people. They are not focused on the worst,

953
00:47:41,080 --> 00:47:45,040
Speaker 1: the worst. They're just focused on hurting people and doing

954
00:47:45,120 --> 00:47:50,680
Speaker 1: Trumpism and blaming people for getting her. And so here

955
00:47:50,719 --> 00:47:55,480
Speaker 1: we are, ladies and gentlemen, mass deportation now right, it

956
00:47:55,560 --> 00:47:58,319
Speaker 1: wasn't a vibe. It was what they were thinking. And

957
00:47:58,400 --> 00:48:01,960
Speaker 1: by the way, none of that was about deportation. Right.

958
00:48:01,960 --> 00:48:04,719
Speaker 1: It was about violence, it was about hurting people, It

959
00:48:04,800 --> 00:48:10,200
Speaker 1: was about crackdown retribution. Yeah, that's it for this episode

960
00:48:10,280 --> 00:48:16,360
Speaker 1: of Fast Politics. Tune in every Monday, Wednesday, Thursday and

961
00:48:16,640 --> 00:48:20,640
Speaker 1: Saturday to hear the best minds and politics make sense

962
00:48:20,680 --> 00:48:25,040
Speaker 1: of all this chaos. If you enjoy this podcast, please

963
00:48:25,040 --> 00:48:28,120
Speaker 1: send it to a friend and keep the conversation going.

964
00:48:28,560 --> 00:48:29,680
Speaker 1: Thanks for listening.