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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 Gallup has the Supreme Court's job

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Speaker 1: approval rating at a record level, which is thirty three

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Speaker 1: percent of Americans approving of the High courts work. We

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Speaker 1: have such a great show for you today. Pods Save

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Speaker 1: America's Dan Pfeiffer stops by to talk about Trump's dysfunction.

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Speaker 1: Then we'll talk to The New York Times Eli Tan

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Speaker 1: about the shocking story of Meta's Louisiana data center. But

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Speaker 1: first the news.

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Speaker 2: Somalley Governor Basheer has done an interesting maneuver here that

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Speaker 2: I don't know how effective it'll be to try to

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Speaker 2: get Mitch McConnell to show proof of life before this

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Speaker 2: upcoming deadline next week where there would no longer be

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Speaker 2: a special election for a seat.

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Speaker 1: So here is what's happening. There is a lot of

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Speaker 1: noise about whether or not Mitch McConnell is dead. Probably not,

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Speaker 1: but maybe nobody knows.

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Speaker 3: Doesn't it feel like it would be a fitting part

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Speaker 3: of his legacy to do this like that. That's just

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Speaker 3: basically why this is like it almost feels like we're

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Speaker 3: honoring him by assuming he would do this.

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Speaker 1: I don't think that Mitch McConnell is dead. I'm gonna

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Speaker 1: tell you the truth. I actually don't think he's dead.

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Speaker 1: But maybe he is. I don't know. I mean, I

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Speaker 1: think the more likely scenario is that he's like not

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Speaker 1: as well as those photos make him out to be.

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Speaker 1: So there have been two very bizarre photos that were

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Speaker 1: released by Mitch McConnell's office. Both make Mitch McConnell look

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Speaker 1: very relaxed in a way that if you look at

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Speaker 1: more recent photos of Mitch McConnell, they don't totally track. Now,

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Speaker 1: am I a Mitch McConnell Truther? I am maybe a

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Speaker 1: little bit of a Mitch mcconald truth. Maybe I'm a

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Speaker 1: Mitch mcconald truther. I don't know, but there's something off here.

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Speaker 1: So here's what's happening. Andy Buscher, who's the Democratic governor

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Speaker 1: of the state, is sort of trying to figure out

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Speaker 1: how to do this. So it's forty days since the

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Speaker 1: eighty four year old has been seen. Okay, forty days,

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Speaker 1: that's a little more than a month, and Boucher is

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Speaker 1: like trying every which way to do it. So he

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Speaker 1: has sent a letter to McConnell and his staff that

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Speaker 1: McConnell needs to verbally address his constituents and demonstrate his

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Speaker 1: ability to serve or resign his seat. This is i think,

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Speaker 1: probably again the best possible option. Remember, Boucher is in

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Speaker 1: a red state with a super majority that has actually

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Speaker 1: and again we don't know what the story is with

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Speaker 1: the appointment, but they did something to make it harder

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Speaker 1: or maybe impossible for the Democratic governor to fill the

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Speaker 1: seat because there are Republicans and so they cheat. So

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Speaker 1: we don't really know, if you know, he may have

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Speaker 1: trouble filling that seat. But either way, this is the

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Speaker 1: way that bur Cher is trying to thread the needle.

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Speaker 1: And again it is pretty strange that McConnell has just

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Speaker 1: completely disappeared. And so we'll see this letter was from Monday,

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Speaker 1: and it's the second one that Burscher has sent to

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Speaker 1: Mitch McConnell's office. Remember, Scott Jennings, I'm not sure you

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Speaker 1: want to take that guy to the bank, but he

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Speaker 1: has said that he has talked to McConnell for twenty minutes.

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Speaker 1: Other Republicans have also battered around that figure as well.

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Speaker 3: Yeah, so let's talk about some not some fun things

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Speaker 3: happening on the Democratic side. As we discussed in our

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Speaker 3: last episode, Ken Martin has been accused of being a

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Speaker 3: very ineffective leader at the DCC and as well having

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Speaker 3: a bit of a temperate seat. But what's interesting is

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Speaker 3: Democrats seem to be sticking by him. There's been very

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Speaker 3: few people calling for him to resign in the actual party.

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Speaker 1: Yeah, this is not good. Ken Martin can't raise money

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Speaker 1: and Ken Martin can't do media. So what does Ken

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Speaker 1: Martin do if he can't raise money and he can't

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Speaker 1: do media. Real question. But hell, Democrats do not want

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Speaker 1: to call for him to resign, and so we have

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Speaker 1: Democrats who are scared of asking him to resign. So

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Speaker 1: Greg Meeks said he doesn't think that he should resign.

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Speaker 1: You know, look, it's hard to get people to resign.

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Speaker 1: It's clearly time for Ken Martin to resign. This article

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Speaker 1: has a lot of quotes it's from notice about members

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Speaker 1: of Congress saying they don't think he should resign. But

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Speaker 1: obviously you should resign. I mean, this is just very

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Speaker 1: stupid and it's nice that Democrats support each other, but

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Speaker 1: this is probably time to stop when it comes to

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Speaker 1: this anyway.

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Speaker 3: Yeah, So the fdaight, who as we know, just can't

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Speaker 3: stop winning. There's just things going so well with our

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Speaker 3: food supply, it's amazing. So they're deciding to codify the

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Speaker 3: dojerra policies.

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Speaker 1: It's all fine as long as you don't have lettuce.

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Speaker 3: Yes, keep calm and carry on.

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Speaker 1: Yeah, just without lettuce, no stop all for you. So

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Speaker 1: the agency will stop it's specializing its field instructor inspectors

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Speaker 1: starting in October. They will officially consolidate administrative staff across

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Speaker 1: the agency's nine centers and stop specializing its field inspectors

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Speaker 1: starting in October. This is a doge change, and it

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Speaker 1: means that you will see more explosive diarrhea. This is

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Speaker 1: like just you know, richest man in the world came

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Speaker 1: into our federal government cut all sorts of or shod

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Speaker 1: and this is just such an insane thing the FDA.

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Speaker 1: It's so basically there's an expert who says that proper

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Speaker 1: assessment requires FDA investigators of matching skills and knowledge. You know,

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Speaker 1: the idea is you're going to save money by having

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Speaker 1: people who don't know what they're doing do this. It's

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Speaker 1: really it's just so stupid. I mean, it's like it's

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Speaker 1: absolutely the legacy of good old dumb RFK Junior.

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Speaker 3: Yeah, hendos making things totally stupid, or the Department of

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Speaker 3: Government lack of efficiency. Yeah Sobali. All we've heard is

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Speaker 3: how could Democrats ever ever choose someone with such poor

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Speaker 3: character as Graham Platner when sitting mega Congressman has accusations

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Speaker 3: that now keep pouring in that are very credible, that

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Speaker 3: are literally some of the most monstrous accusations I can

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Speaker 3: remember ever being at this And I'm of course starting

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Speaker 3: about Representative Max Miller, who is married to Bernie Marino's daughter.

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Speaker 1: Yeah, so Max Miller. These are court filings that say

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Speaker 1: that he poured water, hot waters, scalding water on his wife,

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Speaker 1: he put a gun to her head, and he has

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Speaker 1: allegedly broken the collar bone of his daughter. This is

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Speaker 1: pretty dark stuff here. It sounds like domestic abuse. It's

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Speaker 1: shocking to me that Congressman Marino would not defend his daughter.

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Speaker 1: Max Miller also has abuse allegations from other women too.

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Speaker 1: So here's what's happened. Republicans are worried about losing the House,

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Speaker 1: and they don't want him to resign because then their

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Speaker 1: numbers will get so tight that they won't be able

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Speaker 1: to keep the House, to keep the majority. Remember that

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Speaker 1: earlier this year, Eric Swallwell and a representative Tony Gonzalez

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Speaker 1: from Texas both resigned at the same time. They both

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Speaker 1: had allegations, pretty terrible allegations against them. They both resigned.

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Speaker 1: They swapped them out because they canceled each other out. Well,

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Speaker 1: turns out there's another. I know you'll be shocked to

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Speaker 1: hear this. A member of Congress. This guy is now

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Speaker 1: they won't ask him to leave because of course they

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Speaker 1: don't want to lose the House. So he had Democratic

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Speaker 1: strategist on Fox News because Fox News is having a

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Speaker 1: segment on Grand Platner, and he brought this up and

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Speaker 1: Fox News is not pleased. So look, it's all bad

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Speaker 1: and none of this should be happening. And like it,

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Speaker 1: like domestic violence should be a no go on the

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Speaker 1: left and the right. But it is particularly striking to

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Speaker 1: watch people like the Speaker the condemn Democrats who do it,

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Speaker 1: but then keep Republicans who do it in Congress. Dan

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Speaker 1: Pheiffer is a co host of Positive America and the

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Speaker 1: author of the newsletter message Box welcome, Welcome, Dan.

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Speaker 4: I'm excited to be here. It's been a while.

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Speaker 1: I'm thrilled to have you. It's groundhog Day, right, it's

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Speaker 1: the summer of groundhog Day. New tariffs war is over.

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Speaker 1: Net Yahoo in the Oval Office.

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Speaker 5: Discuss sometimes they try to put myself in the position

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Speaker 5: of someone who is running a Republican campaign in the

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Speaker 5: cycle running Republicans superpack at the NRCC or the NRSC,

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Speaker 5: and you just they just must wake up every day

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Speaker 5: and just want to bang their head against the deaths

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Speaker 5: because Trump seems so committed to making their lives harder.

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Speaker 4: Right, Affordabillli's number one issue. So what does he do.

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Speaker 4: He launches more tariffs, something that voters absolute despies, watches

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Speaker 4: more of them. He can't end this war he started

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Speaker 4: that has raised gas prices. He then has net Yahoo

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Speaker 4: to the White House, which is another problem for him,

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Speaker 4: particularly with his base right. And this is like at

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Speaker 4: every turn he is doing what Trump wants to do,

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Speaker 4: not what's good for Republicans.

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Speaker 1: We talk a lot about the Democratic split over Israel,

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Speaker 1: and that is very much like a mainstream media talking point,

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Speaker 1: but there's a real maga split over Israel too, which

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Speaker 1: is in some ways more profound.

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Speaker 4: Yeah, I mean, it's certainly at the very top amongst

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Speaker 4: some of the most powerful media personality, some of the

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Speaker 4: most pro MAGA folks, the Tucker Carlson's of the world,

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Speaker 4: and they're in a constant war with the Ben Shapiro's

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Speaker 4: of the world. Obviously we have our own splits there.

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Speaker 4: But the other thing is is that the young MAGA

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Speaker 4: voters are almost as skeptical as Israel as the young

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Speaker 4: Democratic voters. And that gets is that the change in

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Speaker 4: public opinion on Israel, in particularly US aid to Israel,

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Speaker 4: is generational, not just ideological. And I think that's lost

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Speaker 4: in this to be a lot, and that's going to

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Speaker 4: affect up because those are the voters they need once

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Speaker 4: you turn it out on twenty twenty four, to turnout

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Speaker 4: twenty twenty six, if they have any chance of minimizing

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Speaker 4: their losses here.

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Speaker 1: Yeah, I mean, it's such an important point about Israel

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Speaker 1: because you know, I'm Jewish, my husband's Jewish, my husband's

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Speaker 1: a bit older than I am. And I think the

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Speaker 1: closer you are to the Holo Coast to living through it,

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Speaker 1: the more you under you know, I'm under fifty, quite

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Speaker 1: a bit let me just lie here. And he's over sixty,

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Speaker 1: and so there is a real split there. And with

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Speaker 1: the younger generation, I don't think they understand the Holocaust

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Speaker 1: and the history of Israel.

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Speaker 4: And if you are of a certain age, you have

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Speaker 4: only known the net Nyahoo government. You've never known a

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Speaker 4: time when there was a realistic or even plausible path

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Speaker 4: to a two state solution. You've only known a right

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Speaker 4: wing Israeli leader who has associated himself very explicitly with Republicans,

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Speaker 4: whether it was going to Congress to attack Barack Obama,

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Speaker 4: like getting involved in these elections, being supportive of Trump,

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Speaker 4: all of those things, and that has colored views here

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Speaker 4: and it is like they're like the wherever you come

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Speaker 4: down on the US relation of Israel, people have to

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Speaker 4: recognize that this is not just it's not just a

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Speaker 4: right wing and left wing split. The biggest movement in

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Speaker 4: change both on the question of aid to Israel, US

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Speaker 4: military aid with or without conditions, and on who you

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Speaker 4: sympathize more with the Palacaitians and Israelis, which is this

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Speaker 4: question Gallup has been asking for decades, is among independence,

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Speaker 4: like that is where the big shift has been. That's

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Speaker 4: what it like Democrats have moved, Republicans have moved, and

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Speaker 4: independence have also moved at this basically the same rate

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Speaker 4: as Democrats, and that has changed the politics here in

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Speaker 4: a lot of ways that we'd like we're seeing play

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Speaker 4: out in Michigan of some places like that.

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Speaker 1: I want to talk to you about Michigan, but I

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Speaker 1: also just want to talk to you for a man

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Speaker 1: about the split, because it does strike me that first

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Speaker 1: I want to ask you you were working in the

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Speaker 1: Obama White House when net Yahoo came and took a

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Speaker 1: stand against Obama.

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Speaker 6: Can you?

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Speaker 1: I mean, I just remember that being so shocking.

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Speaker 4: Yeah, I mean it was part of it. Like Obama

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Speaker 4: and net Yeah, who never got along. They had very

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Speaker 4: very big disagreements that really you know, reached their crest

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Speaker 4: at with the Iran deal in twenty fourteen, twenty fifteen,

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Speaker 4: but it started from the beginning. And you know, it

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Speaker 4: was relatively well known that some of Nan Yahou's top

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Speaker 4: aids are working very close with Mitt Romney in the

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Speaker 4: twenty twelve election. You know, here you have a country

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Speaker 4: that is an ally, but the leader of the country

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Speaker 4: is a political adversary of the president. And that's a

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Speaker 4: very complicated dynamic to manage wild so younger voters.

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Speaker 1: Though, it strikes me that there is this real shift

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Speaker 1: that's happening, which is not it's not left versus right,

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Speaker 1: but up versus down. And we've heard Dan Osborne talk

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Speaker 1: about this, we heard Troy Jackson talk about this in May,

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Speaker 1: we've heard other you know, it's more of a Bernie ish,

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Speaker 1: you know that it's really about the it's economic populism

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Speaker 1: and not ideological. It's ideological, but in a way that's

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Speaker 1: more about affordability.

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Speaker 4: Yeah, I think you nailed exactly right. Which is a

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Speaker 4: lot of the conversation within political circles, whether you're on

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Speaker 4: cable news or on podcasts like ours, or especially on

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Speaker 4: Twitter or even Blue Sky is left first right, and

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Speaker 4: that there are these candidates there are more left wing

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Speaker 4: and more and more to the center. And there is

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Speaker 4: certainly an element of that, and certainly the candidates who

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Speaker 4: won in New York were certainly far more liberal and

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Speaker 4: issues other than just the economy than your standard media

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Speaker 4: and democratic member of Congress. But there is this shift

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Speaker 4: in politics where it really is up versus down, and

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Speaker 4: there's this popcast and people think at all, you know,

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Speaker 4: two thirds of voters two thirds of voters think the

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Speaker 4: economic system in this country is raped. Yeah, declining numbers

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Speaker 4: of voters think that if you work hard you can

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Speaker 4: get by and there in, capitalism is decreasing in favorability

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Speaker 4: and socialism is increasing favorability, and all of these things

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Speaker 4: have created an environment where candidates who are can speak

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Speaker 4: with authenticity and passion about how the system is rigged,

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Speaker 4: can offer solutions on how to unrig it, both in

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Speaker 4: terms of government corruption but also just a very basic

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Speaker 4: idea around everyone getting healthcare, better wages, those sorts of things,

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Speaker 4: and can name the name the villains, the same villains

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Speaker 4: that the people have. You're willing to actually call out

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Speaker 4: the corporations special interests of the billionaires you're speaking. You

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Speaker 4: may or may not win your primary, but you are

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Speaker 4: you have the political win that you're back in this environment.

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Speaker 4: And too many Democrats, ically establishment democrats, have struggled to

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Speaker 4: do that because it's not natural for a certain wing

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Speaker 4: of the party that has been around for a while.

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Speaker 6: Now.

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Speaker 1: Yeah, so say more about that because that comes into

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Speaker 1: I think the Michigan primary last night. We have a candidate,

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Speaker 1: Hailey Stevens, who who was the establishment candidate. She has

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Speaker 1: the pretty much the establishment. I think every almost everyone

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Speaker 1: in the.

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Speaker 4: Slocked except slacking. Let's just slock on someone who wasn't endorsed.

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Speaker 1: Yeah, but you had Gretchen, you had I don't know

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Speaker 1: if Dana Nessel.

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Speaker 4: I think the ships Gretchen, Dana Nessel, Gary Peters, and

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Speaker 4: Wie Stabana have all endorsed Haley Stevens and.

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Speaker 1: A lot of corporations, a lot of big packs. And

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Speaker 1: then you have doctor said, who is got Bernie and

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Speaker 1: Elizabeth Warren? And so it's really like, you know, a battle,

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Speaker 1: a real ideological battle here. What did you think about last?

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Speaker 4: This is a fascinating race, and it's partly a fascinating

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Speaker 4: race because there has been no high quality polling of

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Speaker 4: this race. No one has any idea who's actually winning.

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Speaker 4: There's this one poll from a polster who of a

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Speaker 4: sort of spotty reputation that does only live phone calls,

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Speaker 4: doesn't do a lot of weight, that showed Hailey Stevens

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Speaker 4: up I think by seven or eight points on abdul

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Speaker 4: Steed after Mali mcmorro, the third candidate dropped out. But

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Speaker 4: no one really has any idea what is happening in

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Speaker 4: this race. It's sort of like all of the battles

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Speaker 4: within the party have manifested themselves in this race. So

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Speaker 4: you have el said is very is against will vote

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Speaker 4: against Chuck Schumer, is anti establishment. Hailey Stevens is the

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Speaker 4: hand pick candidate of Schumer and the DSCC. The biggest

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Speaker 4: issue is probably between them is Israel. Apak is gonna

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Speaker 4: end up spending sixty million dollars in this primary alone

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Speaker 4: on Hilly Stevens and none of it have actually about Israel,

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Speaker 4: but because she is a candidate they want. Abdul has

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Speaker 4: been a very aggressive critic of Israel, has called it

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Speaker 4: a genocide, wants to end all aid to Israel, has

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Speaker 4: called Israel and apartheid. Say so, this is a big

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Speaker 4: dividing line there. I watched the debate last night, you

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Speaker 4: know all of that was there. We're sort of in

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Speaker 4: the final stretch here where watching the debate, it's hard

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Speaker 4: to tell who thinks they're winning and who thinks they're losing.

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Speaker 4: But it seems like they both think the race is

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Speaker 4: close enough that they're trying to score a few points

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Speaker 4: here and there and not take wild swings. The other

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Speaker 4: part of this race that really is is that you

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Speaker 4: have these all these super packs and a lot of

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Speaker 4: corporations supporting Haley Stevens. That is a big Abdul does

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Speaker 4: not take corporate pac money, although he does have super packs,

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Speaker 4: but their labor superpacks supporting him, and so the influence

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Speaker 4: of corporations corporate money is a big part of this

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Speaker 4: race too. And then all over top of it is

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Speaker 4: this unanswerable question about electability. It is the very strong

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Speaker 4: belief of a lot of the establishment that Hailey Stevens

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Speaker 4: is much more electable than Abdul, and that if we

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Speaker 4: were to not if the people Michigan were to nominate Abdul,

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Speaker 4: then we would make it less likely, not impossible, but

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Speaker 4: less likely that Democrats would win Michigan. If we don't

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Speaker 4: win Michigan or not, it's hard to get to send

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Speaker 4: a majority without Michigan. You know, whether that a right

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Speaker 4: or not is a question you can debate. But it's

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Speaker 4: like a truly fascinating race. I think we're going to

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Speaker 4: get a pulled maybe as soon as today. In this race,

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Speaker 4: they'll maybe tell us a little bit more. But it's

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Speaker 4: everything that everyone's in finding about in the party on

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Speaker 4: Twitter since twenty twenty four is happening in Michigan.

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Speaker 1: For a long time, I thought she was such a

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Speaker 1: bad speaker that it would be his to get because

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Speaker 1: but she seems like she's gotten a little better.

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Speaker 4: She has, she absolutely has. I think she is a

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Speaker 4: has come into her own as a candidate. In the

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Speaker 4: final stretch here, she was a She does very Up

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Speaker 4: until the recent party here, she did very few events, basically,

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Speaker 4: like very few town halls. Abdullah is everywhere all the

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Speaker 4: time on social media in events. I think he said

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Speaker 4: last night they di done four hundred some events across

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Speaker 4: Michigan town halls where he's taking questions. She's had a

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Speaker 4: much more cautious engage strategy of engagement with the voters

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Speaker 4: and the media. But she's definitely sort of There was

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Speaker 4: a clip that went viral of her that a lot

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Speaker 4: of people left really made fun of about her, like

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Speaker 4: a very aggressive Michigan accent saying talking about give him

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Speaker 4: some sticket to them or whatever it was. She leaned

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Speaker 4: into that and I think a way that was effective.

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Speaker 4: The question here really is in Michigan, you have one

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Speaker 4: in five in typical Michigan primary, one in five Democratic

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Speaker 4: primary voters is black, when well over half are going

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Speaker 4: to be women, and so the strategy from the pro

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Speaker 4: Hailey Stephens side is to win on women and black voters.

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Speaker 4: They've done this through two ways. One is they've run

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Speaker 4: the APAC super Pac has run a lot of ads

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Speaker 4: saying calling Abdul a misogynist, saying he's toxic women, sort

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Speaker 4: of trying to play a little bit on the like

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Speaker 4: this to swim in the wake of bank platinirm. And

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Speaker 4: then the other thing is black voters. They have run there.

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Speaker 4: If you can't turn on a TV in Michigan without

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Speaker 4: seeing a clip of Barack Obama in twenty eighteen campaigning

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Speaker 4: for Haley Stevens complimenting her for having worked the work

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Speaker 4: she had done on the Auto Task Force when she

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Speaker 4: worked in the Obama administration, and that has been that

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Speaker 4: clip is not dated in any of these of you know, Angeliy,

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Speaker 4: hear a lot of voters saying they think Obama has

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Speaker 4: endorsed here, which he hasn't. He is not, He has

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Speaker 4: not endorsed any candidate in his race. And so how

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Speaker 4: effected that'll be, what the turnout will look like in

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Speaker 4: Wayne County is all going to determine what's happened here.

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Speaker 4: But it's fascinating and Honestly, this election can't come soon

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Speaker 4: enough because I'd like this fight to end.

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Speaker 1: When she FORFM, what percentage of voters in Michigan are Muslim, You.

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Speaker 4: Know, I should know that off the top of my head,

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Speaker 4: but it is the highest percentage of any state in

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Speaker 4: the country. Early voting is not always a great predictor.

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Speaker 4: Michigan had early vote by mail and then they have

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Speaker 4: they had started in person a couple of days ago

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Speaker 4: in Dearborn County, which is where the sort of the

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Speaker 4: nexus of that population is. Turnout has been quite high. Now,

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Speaker 4: sometimes when there's a lot of enthusiasm, you cannibalize your

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Speaker 4: election day vote with your early vote. So it's it's hard.

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Speaker 4: It's hard to say but that this is what is

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Speaker 4: kind of what makes us race so fascinates because it

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Speaker 4: is this big giant debate over Israel with a candidate

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Speaker 4: being largely bankrolled by an Apex super pac with the

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Speaker 4: as the as the hand pick Canada of the Senate

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Speaker 4: leadership in the state with the largest Muslim population that

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Speaker 4: was the birthplace of the uncommitted movement against Joe Biden,

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Speaker 4: and then Kamala Harris, right.

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Speaker 1: I mean this is rough, Like you know, and the

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Speaker 1: big question I think in my mind, what I care

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Speaker 1: about is will whoever wins be able to get the

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Speaker 1: voters of the other person.

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Speaker 4: Yeah, it's going to be a really interesting question. This

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Speaker 4: goes the electability Like this, The electability argument is Haley

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Speaker 4: Stephen slips a Republican district. That is absolutely true in

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Speaker 4: twenty eighteen. Since then, she's basically performed critically twenty four

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Speaker 4: as a generic Democrat like no, good, fine, this is

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Speaker 4: a fifty to fifty state that should be three to

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Speaker 4: four to five points more democratic if the national environment

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Speaker 4: states the way it is, you know, and that she

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Speaker 4: would be functions essentially a generic Democrat who like who

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Speaker 4: seems very Michigan in a state where the majority of

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Speaker 4: the electorate in general election are women like you know.

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Speaker 4: And that's a good argument that Abdul has these weaknesses

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Speaker 4: because he is endorsed by Bernie, endorsed by AOC, is

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Speaker 4: seen as the lefty candidate, is you know, has you

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Speaker 4: know had There are some comments about defunding the police

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Speaker 4: from twenty twenty that he has walked back, but that

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Speaker 4: that exists, that he has more vulnerabilities now. The counter

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Speaker 4: argument I think is he's very very talented. She's talented too,

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Speaker 4: but it's in a different way. But he is, like

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Speaker 4: he is very deft as a communicatus, and that can

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Speaker 4: help you navigate some of these things.

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Speaker 1: It's really good. I mean, he's really good at speaking. Yes,

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Speaker 1: And I think she's gotten better.

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Speaker 4: But she has definitely gotten better. She's definitely gotten better,

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Speaker 4: for sure. But you can just see he's someone who

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Speaker 4: could go everywhere all the time, do all the hard interviews,

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Speaker 4: take all the questions. She may be able to do

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Speaker 4: that too, she is not shown a willingness to do

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Speaker 4: that thus far. I think one question is you know

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Speaker 4: you asked the big questions. Can you unite after this? Yeah,

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Speaker 4: it might be easier, some would argue, And I think

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Speaker 4: someone Ubdul said it for Hailey Stephens supporters to come

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Speaker 4: to Abdul right then the other way because of how

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Speaker 4: young voters in particular, not just Muslim but all young

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Speaker 4: voters in Michigan feel about Israel and getting them to

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Speaker 4: turn out support a candidate that Apax spent fifty to

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Speaker 4: sixty million dollars to support is could be a tole

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Speaker 4: order business. So I think people will you know, everyone

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Speaker 4: will recognize, you know, there's always a rough period aphte

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Speaker 4: the primaries, people do tend to come together. That tends

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Speaker 4: to have in particularly in it when they party has

434
00:24:32,400 --> 00:24:34,320
Speaker 4: the other party has the White House and the Senate

435
00:24:34,400 --> 00:24:36,400
Speaker 4: and the House. But that is a big question, and

436
00:24:37,040 --> 00:24:38,720
Speaker 4: both the winner and the loser of this thing are

437
00:24:38,720 --> 00:24:40,760
Speaker 4: going to have to be very gracious in how they

438
00:24:40,840 --> 00:24:44,400
Speaker 4: in how they build rebuild the coalitions gonna take to win.

439
00:24:44,520 --> 00:24:48,879
Speaker 1: Ken Martin had a tough news cycle A chair what

440
00:24:48,920 --> 00:24:50,960
Speaker 1: do you think is happening? I mean, it strikes me

441
00:24:51,000 --> 00:24:53,200
Speaker 1: there are a couple of places I'm actually going to

442
00:24:53,240 --> 00:24:56,200
Speaker 1: ask a sort of broader question, a couple of places

443
00:24:56,240 --> 00:25:00,800
Speaker 1: here where, like Ken Martin and also in Montagne, we

444
00:25:00,920 --> 00:25:05,520
Speaker 1: have an independent who could win if the Democratic candidate

445
00:25:05,680 --> 00:25:08,320
Speaker 1: dropped out or at least the polls showed the possibility

446
00:25:08,720 --> 00:25:11,119
Speaker 1: that he could win. And I just wonder they are

447
00:25:11,119 --> 00:25:13,480
Speaker 1: a couple of plays there where it feels like were

448
00:25:13,520 --> 00:25:17,159
Speaker 1: they're a really good leader in the party, someone could

449
00:25:17,840 --> 00:25:19,600
Speaker 1: call that woman and be like, look you got to

450
00:25:19,640 --> 00:25:22,400
Speaker 1: drop out, or stated Ken Martin, you're not raising money,

451
00:25:22,440 --> 00:25:25,760
Speaker 1: you can't do media like what are you doing? Like

452
00:25:25,800 --> 00:25:30,320
Speaker 1: I think about Republicans and if they had something like this,

453
00:25:30,400 --> 00:25:34,440
Speaker 1: they would be all over that person. So what do

454
00:25:34,520 --> 00:25:34,840
Speaker 1: you think.

455
00:25:35,400 --> 00:25:37,680
Speaker 4: There's a couple things happen here, Like historically Republicans pre

456
00:25:37,760 --> 00:25:39,640
Speaker 4: Trump were very bad at this. This is why they

457
00:25:39,680 --> 00:25:43,160
Speaker 4: blew the Senate races in ten and twelve and twenty two. Honestly,

458
00:25:43,160 --> 00:25:45,439
Speaker 4: even though Trump was around me, I mean Trump, he

459
00:25:45,480 --> 00:25:47,920
Speaker 4: picked all the wrong people. But they had all bad candidates.

460
00:25:49,040 --> 00:25:53,480
Speaker 4: But there is something happening where the voters do not

461
00:25:53,680 --> 00:25:56,800
Speaker 4: trust the Democratic Party leadership and are actually sort of

462
00:25:56,880 --> 00:26:00,800
Speaker 4: negatively polarized by candidates who are support by democraticalership and

463
00:26:00,840 --> 00:26:03,440
Speaker 4: there's no one with the credibility like it is if

464
00:26:03,440 --> 00:26:05,879
Speaker 4: everyone keeps asking like how did Ken Martin end up there?

465
00:26:05,920 --> 00:26:07,560
Speaker 4: And if you're someone who's like like us, who's been

466
00:26:07,640 --> 00:26:09,199
Speaker 4: very well the politics for the last decade, you're very

467
00:26:09,200 --> 00:26:12,000
Speaker 4: familiar with Ben Wickler who was the former Wisconsin Party

468
00:26:12,080 --> 00:26:17,280
Speaker 4: Cherry ran against them, and Ben had the support of Schumer, Jeffries,

469
00:26:17,680 --> 00:26:21,520
Speaker 4: basically everyone, and that was actually ended up being a

470
00:26:21,640 --> 00:26:25,919
Speaker 4: state party chair a negative yeah yeah, and up being

471
00:26:25,960 --> 00:26:28,640
Speaker 4: a negative for him. And you have the same thing Herry,

472
00:26:28,720 --> 00:26:30,600
Speaker 4: it's happening like they're really we are sort of an

473
00:26:30,600 --> 00:26:33,439
Speaker 4: old lord of a flies moment for the party, whatever

474
00:26:33,480 --> 00:26:36,080
Speaker 4: else you think about Ken Martin and I supported Ben.

475
00:26:36,280 --> 00:26:39,240
Speaker 4: I called for Ken to resign after the autopsy. He's

476
00:26:39,280 --> 00:26:41,200
Speaker 4: doing the best he can. But I think the well

477
00:26:41,240 --> 00:26:43,199
Speaker 4: has now become so poison that you can't look at

478
00:26:43,280 --> 00:26:45,760
Speaker 4: and say the best thing for the party is to

479
00:26:45,800 --> 00:26:46,800
Speaker 4: maintain the status quo.

480
00:26:47,119 --> 00:26:47,320
Speaker 1: Right.

481
00:26:47,359 --> 00:26:49,280
Speaker 4: We can debate howping a disaster is if we don't,

482
00:26:49,280 --> 00:26:51,920
Speaker 4: But if you were maximizing your chances of winning now

483
00:26:51,920 --> 00:26:54,960
Speaker 4: and beyond, someone would go to him and say, now,

484
00:26:55,080 --> 00:26:56,159
Speaker 4: the best thing you can do for the party is

485
00:26:56,200 --> 00:26:59,080
Speaker 4: to step down. Please step down, and will replace someone.

486
00:26:59,119 --> 00:27:02,000
Speaker 4: It's not an easy do that. But then you mentioned

487
00:27:02,040 --> 00:27:06,600
Speaker 4: Montana in Michigan. In the seventh district of Michigan, which

488
00:27:06,640 --> 00:27:09,080
Speaker 4: is Alissa slockins old seat. We lost it in twenty

489
00:27:09,160 --> 00:27:11,280
Speaker 4: twenty four when she ran for Senate. It's a very

490
00:27:11,280 --> 00:27:14,040
Speaker 4: close race. There are three candidates in that race. One

491
00:27:14,080 --> 00:27:19,320
Speaker 4: is Joe Biden's ambassador to Ukraine, Bridget Brink. Another is

492
00:27:19,320 --> 00:27:22,199
Speaker 4: Matt Masden, who carried the nuclear football for Obama. Is

493
00:27:22,240 --> 00:27:26,160
Speaker 4: a veteran right right yeah. And the third one is

494
00:27:26,320 --> 00:27:31,080
Speaker 4: a progressive supported by Bernie. I haven't studied enough to

495
00:27:31,680 --> 00:27:34,520
Speaker 4: know to really be able to validate these claims. But

496
00:27:34,560 --> 00:27:37,159
Speaker 4: a lot of people believe that the Progressive is the

497
00:27:37,240 --> 00:27:41,720
Speaker 4: least likely to win that race. The two like more moderate,

498
00:27:42,320 --> 00:27:46,400
Speaker 4: you know, credentialed candidates both stayed in the race, and

499
00:27:46,480 --> 00:27:49,320
Speaker 4: they're going to split the vote. And Lawrence is likely

500
00:27:49,440 --> 00:27:52,400
Speaker 4: by according to some internal polling that I've read about,

501
00:27:52,400 --> 00:27:54,680
Speaker 4: but not seen, going to win by a lot. And

502
00:27:54,760 --> 00:27:56,960
Speaker 4: so in a different world, someone would have had the

503
00:27:57,000 --> 00:27:59,959
Speaker 4: credibility to go to one of the other two candidates

504
00:28:00,000 --> 00:28:01,800
Speaker 4: and say, one of you, you know, if we our

505
00:28:01,800 --> 00:28:02,920
Speaker 4: best things to win in the seat, is one of

506
00:28:02,960 --> 00:28:04,760
Speaker 4: you is the nominee. One of you's got to get

507
00:28:04,760 --> 00:28:07,880
Speaker 4: out flip a correct right, right, right, because no one

508
00:28:07,960 --> 00:28:10,760
Speaker 4: has the credibility in the party right now to do that,

509
00:28:11,359 --> 00:28:14,200
Speaker 4: and not just with voters, but even with other Democratic politicians.

510
00:28:14,240 --> 00:28:15,960
Speaker 4: And you're going to see this be a real issue

511
00:28:16,320 --> 00:28:18,119
Speaker 4: in twenty twenty eight when there's no one's going to

512
00:28:18,119 --> 00:28:20,640
Speaker 4: be able to like ride her and over the process. Right.

513
00:28:21,720 --> 00:28:26,200
Speaker 1: Yeah, Oh, it's so crazy, right, and that we'll see

514
00:28:26,240 --> 00:28:30,720
Speaker 1: that in twenty twenty eight. Dan Pfeiffer, thank you.

515
00:28:31,040 --> 00:28:31,800
Speaker 6: Thanks for having me.

516
00:28:33,160 --> 00:28:37,199
Speaker 1: Eli tan is a reporter covering the technology industry for

517
00:28:37,320 --> 00:28:40,480
Speaker 1: The New York Times. Welcome, Welcome, Eli, Thanks much for

518
00:28:40,520 --> 00:28:42,520
Speaker 1: having me. We're having you on to talk about this

519
00:28:42,840 --> 00:28:45,680
Speaker 1: data center in Louisiana, but I want you to tell

520
00:28:45,720 --> 00:28:48,760
Speaker 1: us about this first data center story you wrote two

521
00:28:48,840 --> 00:28:49,280
Speaker 1: years ago.

522
00:28:49,760 --> 00:28:52,640
Speaker 6: Yeah, two years ago, I saw this on Facebook actually,

523
00:28:52,680 --> 00:28:55,320
Speaker 6: that there was a town that was fighting against a

524
00:28:55,440 --> 00:28:58,400
Speaker 6: data center. The town was a Peculiar, Missouri south of

525
00:28:58,480 --> 00:29:01,000
Speaker 6: Kansas City, and it was like the first instance I

526
00:29:01,000 --> 00:29:02,960
Speaker 6: had seen of this. So I went to the town,

527
00:29:03,320 --> 00:29:05,240
Speaker 6: wrote this big story about it. You know, they were

528
00:29:05,240 --> 00:29:07,280
Speaker 6: some of the first people to print out these signs

529
00:29:07,280 --> 00:29:09,680
Speaker 6: that said no data centers and stick them in their

530
00:29:09,760 --> 00:29:12,360
Speaker 6: yard and kind of stage this big, you know, revolt

531
00:29:12,400 --> 00:29:14,760
Speaker 6: against this project. At the time, I thought, this is interesting,

532
00:29:14,800 --> 00:29:17,320
Speaker 6: these data centers are becoming a thing. And past forward

533
00:29:17,360 --> 00:29:20,080
Speaker 6: two years now this is like a huge issue ahead

534
00:29:20,080 --> 00:29:22,600
Speaker 6: of the midterms. It's like every state is fighting about

535
00:29:22,600 --> 00:29:24,880
Speaker 6: this stuff. So it's been pretty crazy to just to

536
00:29:24,880 --> 00:29:27,600
Speaker 6: see how it's all developed. Did they win, Yeah, they

537
00:29:27,640 --> 00:29:30,520
Speaker 6: did win. They fought back against this data center. And

538
00:29:30,760 --> 00:29:33,720
Speaker 6: after my story came out, actually they ousted the mayor

539
00:29:33,800 --> 00:29:36,800
Speaker 6: and they ousked the city administrator and they kind of

540
00:29:36,840 --> 00:29:39,120
Speaker 6: they all the people that were the leaders of this

541
00:29:39,440 --> 00:29:41,960
Speaker 6: charge to stop the data centers. They like promoted them

542
00:29:42,000 --> 00:29:44,800
Speaker 6: to leadership positions in the town. So it's like reshaped

543
00:29:44,800 --> 00:29:46,560
Speaker 6: this town in a lot of ways. But they're doing well.

544
00:29:46,600 --> 00:29:48,320
Speaker 6: I still talk to those people every once in a while.

545
00:29:48,360 --> 00:29:53,200
Speaker 1: Actually, that's really cute. So let's talk about Meta's giant

546
00:29:53,280 --> 00:29:57,640
Speaker 1: data center in Louisiana. There's so much here, but I

547
00:29:57,640 --> 00:30:00,720
Speaker 1: think this secrecy is the thing I'm the most interested in.

548
00:30:01,240 --> 00:30:03,840
Speaker 1: First of all, I would love you to also explain

549
00:30:03,960 --> 00:30:07,160
Speaker 1: like how many data centers Meta needs, and a little

550
00:30:07,200 --> 00:30:10,560
Speaker 1: bit about sort of Meta's data center relationship to.

551
00:30:11,080 --> 00:30:14,600
Speaker 6: Yeah, right now, Meta is building about a dozen of

552
00:30:14,680 --> 00:30:18,480
Speaker 6: these huge hyper scale data centers to power AI. Each

553
00:30:18,480 --> 00:30:21,080
Speaker 6: of these data centers is billions and billions of dollars.

554
00:30:21,320 --> 00:30:24,240
Speaker 6: The one in Louisiana is its largest. It's going to

555
00:30:24,280 --> 00:30:27,200
Speaker 6: be you know, fifty billion dollars. It'll have like over

556
00:30:27,240 --> 00:30:30,520
Speaker 6: one hundred billion dollars of you know, these Nvidia chips

557
00:30:30,600 --> 00:30:32,880
Speaker 6: in it. And yeah, they need you know, the company

558
00:30:32,920 --> 00:30:36,360
Speaker 6: needs these to train AI. And it makes sense to

559
00:30:36,440 --> 00:30:40,440
Speaker 6: build massive ones in specific places as opposed to you know,

560
00:30:40,600 --> 00:30:42,600
Speaker 6: hundreds of smaller ones all across the country.

561
00:30:42,920 --> 00:30:45,240
Speaker 1: First of all, where would be, how big will it be,

562
00:30:45,560 --> 00:30:49,959
Speaker 1: and what is the effect it don't have on the neighborhood.

563
00:30:50,240 --> 00:30:53,760
Speaker 6: Yeah. So it'll be in this parish called Richland Parish

564
00:30:53,800 --> 00:30:56,479
Speaker 6: in Louisiana. It's in the corner of the state. It's

565
00:30:56,560 --> 00:31:01,600
Speaker 6: kind of this poor rural farming community. Comparison that everyone

566
00:31:01,600 --> 00:31:06,520
Speaker 6: makes is Manhattan. Mark Zuckerberg, he gave Donald Trump a

567
00:31:06,560 --> 00:31:09,240
Speaker 6: photo of the data center, you know, kind of imposed

568
00:31:09,280 --> 00:31:11,640
Speaker 6: over Manhattan. We didn't say that in the story because

569
00:31:11,640 --> 00:31:13,520
Speaker 6: it's not quite as big as Manhattan. It's about like

570
00:31:13,640 --> 00:31:17,560
Speaker 6: the top of Central Park to the Financial district you're

571
00:31:17,560 --> 00:31:19,800
Speaker 6: familiar with, you know, New York. But it's huge. I

572
00:31:19,840 --> 00:31:21,760
Speaker 6: mean I went there in person and it's like it's

573
00:31:21,760 --> 00:31:25,480
Speaker 6: like six miles long, a mile wide. It's like its

574
00:31:25,480 --> 00:31:27,480
Speaker 6: own city. I mean, you know, I did a tour

575
00:31:28,120 --> 00:31:29,960
Speaker 6: on a you know, on a truck kind of driving

576
00:31:30,000 --> 00:31:32,320
Speaker 6: around and it's it's huge. It is. It's like it's

577
00:31:32,440 --> 00:31:33,960
Speaker 6: it is kind of like being in a you know,

578
00:31:33,960 --> 00:31:36,040
Speaker 6: a Manhattan sized construction site.

579
00:31:36,240 --> 00:31:41,160
Speaker 1: Will this sort of all of the AI needs of Facebook?

580
00:31:41,280 --> 00:31:45,240
Speaker 1: I mean, what will it work for Facebook? Instagram? I mean,

581
00:31:45,280 --> 00:31:46,000
Speaker 1: what's it doing?

582
00:31:46,440 --> 00:31:50,200
Speaker 6: Yeah, it'll be Facebook Instagram Meta has these new AI

583
00:31:50,320 --> 00:31:52,680
Speaker 6: models that it's coming out with. But you know, when

584
00:31:52,720 --> 00:31:55,440
Speaker 6: you're in Instagram or Facebook and you're asking, you know,

585
00:31:55,480 --> 00:31:58,440
Speaker 6: the AI chatbot they have any questions, That's the type

586
00:31:58,440 --> 00:31:59,840
Speaker 6: of thing it's it's going towards.

587
00:32:00,120 --> 00:32:02,920
Speaker 1: So is this happening and what will mean for the

588
00:32:03,320 --> 00:32:04,400
Speaker 1: area surrounding it.

589
00:32:04,680 --> 00:32:08,880
Speaker 6: So it's completely remaking the area just on the construction alone.

590
00:32:09,000 --> 00:32:12,680
Speaker 6: I mean, they're going to have seven thousand construction workers

591
00:32:12,760 --> 00:32:14,960
Speaker 6: in this tiny parish. The parish is something like twenty

592
00:32:15,000 --> 00:32:17,600
Speaker 6: thousand people. This is one of the poorest parts of

593
00:32:17,640 --> 00:32:19,880
Speaker 6: the entire country and you have, you know, one of

594
00:32:19,920 --> 00:32:22,920
Speaker 6: the richest companies basically coming in and totally remaking it.

595
00:32:23,040 --> 00:32:26,520
Speaker 6: The thing about the project is that there's no sales

596
00:32:26,560 --> 00:32:30,320
Speaker 6: tax on the hundreds of billions of chips. They're not

597
00:32:30,360 --> 00:32:31,960
Speaker 6: really paying property taxes.

598
00:32:32,320 --> 00:32:35,240
Speaker 1: Wait, why aren't they playing property taxes?

599
00:32:35,800 --> 00:32:38,440
Speaker 6: That was part of Meta's deal if they were going

600
00:32:38,520 --> 00:32:41,800
Speaker 6: to come to Louisiana, they didn't want to pay certain taxes.

601
00:32:41,880 --> 00:32:44,720
Speaker 6: So the way it benefits the area is that there's

602
00:32:44,760 --> 00:32:47,360
Speaker 6: these sales tax from thousands and thousands of people that

603
00:32:47,400 --> 00:32:49,680
Speaker 6: are coming in and spending money and you know, buying

604
00:32:49,680 --> 00:32:50,960
Speaker 6: equipment and that sort of thing.

605
00:32:51,360 --> 00:32:51,760
Speaker 1: That's it.

606
00:32:52,080 --> 00:32:54,480
Speaker 6: That's the main one. We're talking tens of millions of

607
00:32:54,480 --> 00:32:57,520
Speaker 6: dollars in sales tax every year. It's not nothing, right.

608
00:32:57,720 --> 00:33:01,880
Speaker 1: Yeah, but if you're like a poor you're paying more

609
00:33:02,000 --> 00:33:04,080
Speaker 1: property tax than metas.

610
00:33:04,080 --> 00:33:06,360
Speaker 6: In some cases. Yeah, I think it's I think that's

611
00:33:06,400 --> 00:33:07,360
Speaker 6: probably true to say.

612
00:33:07,520 --> 00:33:10,720
Speaker 1: Yeah, and what about the electricity and the water.

613
00:33:11,200 --> 00:33:15,080
Speaker 6: Yeah, the electricity is the big one. This company called

614
00:33:15,240 --> 00:33:18,840
Speaker 6: Entergy Louisiana, the largest in the state. They're building for

615
00:33:18,880 --> 00:33:22,000
Speaker 6: Meta ten new natural gas turbines, so it's enough to

616
00:33:22,000 --> 00:33:24,680
Speaker 6: power New Orleans like six or seven times over or

617
00:33:24,720 --> 00:33:27,960
Speaker 6: something like that. The incredible amount of natural gas.

618
00:33:27,640 --> 00:33:31,640
Speaker 1: And natural gas turbines are super polluting. They're not like

619
00:33:31,960 --> 00:33:35,080
Speaker 1: a solar turbines or polluters.

620
00:33:35,480 --> 00:33:38,640
Speaker 6: They are polluters. But the governor of Louisiana he actually

621
00:33:38,640 --> 00:33:42,840
Speaker 6: declared natural gas or renewable energy before the project. He

622
00:33:42,920 --> 00:33:45,280
Speaker 6: like signed something so that it would be considered a

623
00:33:45,280 --> 00:33:47,440
Speaker 6: renewable energy or something like that. Don't have to look

624
00:33:47,480 --> 00:33:49,360
Speaker 6: up the specifics, butt. I mean, that's just like one

625
00:33:49,400 --> 00:33:52,120
Speaker 6: example of all the ways that the government of Louisiana

626
00:33:52,120 --> 00:33:54,560
Speaker 6: has done everything they could to kind of accommodate META.

627
00:33:54,680 --> 00:33:56,720
Speaker 1: What about the water, the water.

628
00:33:56,960 --> 00:33:59,160
Speaker 6: I mean, this is a you know, this is a

629
00:33:59,200 --> 00:34:03,360
Speaker 6: part of the state that has really old infrastructure. So

630
00:34:03,800 --> 00:34:06,360
Speaker 6: Meta has kind of gone in and like paid. They've

631
00:34:06,400 --> 00:34:08,520
Speaker 6: spent actually a billion dollars of their own money to

632
00:34:08,640 --> 00:34:14,080
Speaker 6: just upgrade things like the water tables, waste water, the roads.

633
00:34:14,120 --> 00:34:15,960
Speaker 6: I mean, they just they didn't have roads that could

634
00:34:16,160 --> 00:34:19,480
Speaker 6: handle like NonStop construction. So yeah, I Meta spent you know,

635
00:34:19,480 --> 00:34:21,800
Speaker 6: its own money to basically pay for all the stuff

636
00:34:21,800 --> 00:34:22,640
Speaker 6: the water included.

637
00:34:23,040 --> 00:34:25,799
Speaker 1: When this thing is done, it's not going to have

638
00:34:25,880 --> 00:34:29,239
Speaker 1: a lot of people from Louisiana working in it, right.

639
00:34:29,360 --> 00:34:32,879
Speaker 6: Yeah, it's not super clear. These projects. They hire these

640
00:34:32,920 --> 00:34:38,480
Speaker 6: really specialized technicians and electricians to work in the data centers.

641
00:34:38,880 --> 00:34:42,080
Speaker 6: But what the state is kind of banking on is that,

642
00:34:42,320 --> 00:34:45,440
Speaker 6: you know, these construction jobs, they're actually like changing the

643
00:34:45,440 --> 00:34:48,880
Speaker 6: curriculum at all the community colleges nearby to train people

644
00:34:48,920 --> 00:34:51,600
Speaker 6: to work on data centers because they think that when

645
00:34:52,080 --> 00:34:55,360
Speaker 6: this project's done, they can just go build another project

646
00:34:55,360 --> 00:34:57,640
Speaker 6: and they'll have this this sort of like economy on

647
00:34:57,719 --> 00:35:00,239
Speaker 6: wheels where there's gonna be like ten thousand people that

648
00:35:00,280 --> 00:35:01,799
Speaker 6: all they do is they work on data centers and

649
00:35:01,800 --> 00:35:04,080
Speaker 6: they go, you know, travel around the state. That's that's

650
00:35:04,160 --> 00:35:05,360
Speaker 6: kind of the governor's vision.

651
00:35:05,800 --> 00:35:09,520
Speaker 1: But won't you only need a finite amount of data centers?

652
00:35:10,040 --> 00:35:12,040
Speaker 6: I mean, we'll see where it's all going. Meta is

653
00:35:12,080 --> 00:35:15,759
Speaker 6: building this one. Amazon is building one in the other

654
00:35:15,960 --> 00:35:18,560
Speaker 6: in the northwest corner of the state, and they're hoping

655
00:35:18,560 --> 00:35:20,400
Speaker 6: that you know, this deal with Meta, they can just

656
00:35:20,440 --> 00:35:22,480
Speaker 6: kind of keep doing it with other projects.

657
00:35:22,880 --> 00:35:25,359
Speaker 1: Explain to us, like, if you're a farmer and you

658
00:35:25,520 --> 00:35:28,600
Speaker 1: live near this data center, how will your life change?

659
00:35:28,760 --> 00:35:31,359
Speaker 6: Well, most of the farmers that live near the data

660
00:35:31,400 --> 00:35:34,960
Speaker 6: center actually sold their land to Meta, right and made

661
00:35:35,040 --> 00:35:37,640
Speaker 6: a killing millions of dollars in a lot of cases.

662
00:35:37,680 --> 00:35:41,200
Speaker 6: Oh wow, so the landowners are getting off great, right,

663
00:35:41,360 --> 00:35:43,000
Speaker 6: It's a story. It's like a lot of people are

664
00:35:43,000 --> 00:35:46,160
Speaker 6: benefiting a lot from the data center. Other people aren't. So,

665
00:35:46,440 --> 00:35:48,440
Speaker 6: you know, if you're a farmer and you're making millions

666
00:35:48,480 --> 00:35:51,480
Speaker 6: of dollars, you own a construction company nearby, you're you know,

667
00:35:51,520 --> 00:35:54,720
Speaker 6: you're selling contracting the Meta. Maybe you own a restaurant nearby,

668
00:35:54,840 --> 00:35:56,920
Speaker 6: Met is buying like hundreds of meals from you every

669
00:35:57,120 --> 00:35:59,799
Speaker 6: every week. But then if you're just a person that

670
00:35:59,800 --> 00:36:02,560
Speaker 6: lives in this parish, there was someone in my story.

671
00:36:02,800 --> 00:36:05,160
Speaker 6: Her name's Tracy Williams. Her rent got raised from two

672
00:36:05,200 --> 00:36:08,080
Speaker 6: hundred dollars to almost fifteen hundred dollars a month. You know,

673
00:36:08,160 --> 00:36:10,640
Speaker 6: so that these construction workers have places to live, It's

674
00:36:10,680 --> 00:36:12,359
Speaker 6: like where do you go? So a lot of them,

675
00:36:12,400 --> 00:36:14,719
Speaker 6: you know, they get displaced, They have to live in

676
00:36:14,920 --> 00:36:17,719
Speaker 6: houses with ten people, you know, living in a three

677
00:36:17,719 --> 00:36:20,600
Speaker 6: bedroom house like I've seen. Maybe they leave the parish altogether.

678
00:36:21,120 --> 00:36:23,480
Speaker 6: So those are the people that are really kind of left,

679
00:36:23,840 --> 00:36:24,879
Speaker 6: you know, wondering what to do.

680
00:36:25,360 --> 00:36:30,719
Speaker 1: So talk us through what you saying. The larger pollution

681
00:36:31,960 --> 00:36:33,080
Speaker 1: matrixes here.

682
00:36:33,400 --> 00:36:36,320
Speaker 6: I mean natural gas turbines I don't think are great

683
00:36:36,360 --> 00:36:39,319
Speaker 6: for the environment compared to you know, solar are other

684
00:36:39,640 --> 00:36:42,160
Speaker 6: renewable energies, but I'm not really up to speed on

685
00:36:42,200 --> 00:36:43,360
Speaker 6: the pollution aspect.

686
00:36:43,800 --> 00:36:48,160
Speaker 1: This will radically reshape the town and the government too

687
00:36:48,239 --> 00:36:52,000
Speaker 1: of the town. The local government is meta trying to

688
00:36:52,040 --> 00:36:54,399
Speaker 1: mess around with the local government or is the local

689
00:36:54,440 --> 00:36:57,759
Speaker 1: government totally bought in? I mean, is this a story

690
00:36:58,000 --> 00:37:01,080
Speaker 1: of a town versus a day data center? Are now?

691
00:37:01,520 --> 00:37:03,759
Speaker 6: In this case, it's really not a story of a

692
00:37:03,800 --> 00:37:06,520
Speaker 6: town versus a data center. And that's because the way

693
00:37:06,560 --> 00:37:09,120
Speaker 6: they did this deal. It was entirely secretive. It was

694
00:37:09,160 --> 00:37:12,280
Speaker 6: with NDAs, it was behind closed doors. Meta just announced

695
00:37:12,280 --> 00:37:14,959
Speaker 6: and the stages announced, Yeah, we've got this deal done.

696
00:37:14,960 --> 00:37:17,120
Speaker 6: We're coming to this parish. There was no opportunity for

697
00:37:17,120 --> 00:37:20,160
Speaker 6: people to you know, get their posters and fight back.

698
00:37:20,200 --> 00:37:22,560
Speaker 6: But for the most part, the people that live in

699
00:37:22,600 --> 00:37:24,840
Speaker 6: this town, I mean, you know, they're a little overwhelmed

700
00:37:24,840 --> 00:37:28,160
Speaker 6: by it, but they're pretty optimistic. They hope that this

701
00:37:28,239 --> 00:37:30,880
Speaker 6: is going to help all their lives. You know, you

702
00:37:31,000 --> 00:37:33,359
Speaker 6: drive through town and it's you know, you have these

703
00:37:33,480 --> 00:37:36,080
Speaker 6: Baptist churches that have the signs that have you know,

704
00:37:36,200 --> 00:37:38,400
Speaker 6: welcome META, and then they have these Bible verses that

705
00:37:38,440 --> 00:37:42,440
Speaker 6: they've put out about opportunity and labor. And you know,

706
00:37:42,480 --> 00:37:44,160
Speaker 6: it wasn't really up to them whether or not this

707
00:37:44,200 --> 00:37:45,960
Speaker 6: project was going to come here, but they're trying to

708
00:37:45,960 --> 00:37:46,759
Speaker 6: make the most of it.

709
00:37:46,920 --> 00:37:50,439
Speaker 1: Do you feel like they're being taken advantage of Yeah.

710
00:37:50,680 --> 00:37:55,640
Speaker 6: I think that the most concerning part of this project

711
00:37:55,719 --> 00:37:59,759
Speaker 6: was that data centers. They're this really controversial thing nowadays.

712
00:38:00,040 --> 00:38:01,600
Speaker 6: A lot of people don't like them. They want to

713
00:38:01,640 --> 00:38:03,919
Speaker 6: have some input into how these things are built and

714
00:38:04,280 --> 00:38:07,920
Speaker 6: the state government and Meta's response to that was okay,

715
00:38:08,000 --> 00:38:10,160
Speaker 6: let's just cut them out of it entirely. Let's just

716
00:38:10,200 --> 00:38:12,839
Speaker 6: do the deal behind their backs. And maybe the deal

717
00:38:12,920 --> 00:38:14,759
Speaker 6: is going to be a great thing for this area.

718
00:38:14,840 --> 00:38:17,200
Speaker 6: Maybe it won't be. But I think that, you know,

719
00:38:17,239 --> 00:38:19,880
Speaker 6: it's a fair question to ask, like, should people that

720
00:38:19,920 --> 00:38:21,920
Speaker 6: actually live there have some kind of input into.

721
00:38:21,760 --> 00:38:24,839
Speaker 1: This, Like is this sort of a new way they're

722
00:38:24,880 --> 00:38:26,960
Speaker 1: going to do it with data centers or is this

723
00:38:27,040 --> 00:38:28,480
Speaker 1: how metas always done it.

724
00:38:28,680 --> 00:38:30,640
Speaker 6: This could be it could be a blueprint for how

725
00:38:30,640 --> 00:38:32,800
Speaker 6: everybody wants to do it. If you look in places

726
00:38:32,920 --> 00:38:37,040
Speaker 6: like Arizona, Michigan, people hate data centers. People don't want

727
00:38:37,040 --> 00:38:39,560
Speaker 6: them at all. They don't want to negotiate the terms.

728
00:38:39,560 --> 00:38:41,560
Speaker 6: They just want them out of there. And it's a

729
00:38:41,600 --> 00:38:44,080
Speaker 6: tough environment. I think if you're one of these tech

730
00:38:44,080 --> 00:38:47,040
Speaker 6: companies to you know, convince people that these things are

731
00:38:47,080 --> 00:38:49,240
Speaker 6: good when they're you know, really setting their ways already

732
00:38:49,239 --> 00:38:50,719
Speaker 6: that they don't want them at all.

733
00:38:50,920 --> 00:38:54,480
Speaker 1: Does it seem like the promise of these data centers

734
00:38:54,640 --> 00:38:56,640
Speaker 1: is possible to deliver or now?

735
00:38:56,880 --> 00:38:59,520
Speaker 6: I think so, Okay, the thing about these data centers

736
00:38:59,600 --> 00:39:02,280
Speaker 6: is that they're just not paying very much tax revenue

737
00:39:02,320 --> 00:39:05,120
Speaker 6: to the places they're going like relative to how expensive

738
00:39:05,160 --> 00:39:07,879
Speaker 6: they are. And you know, you'd think that the state

739
00:39:07,920 --> 00:39:10,200
Speaker 6: could say, Okay, we're gonna just do an open call

740
00:39:10,440 --> 00:39:13,600
Speaker 6: for data centers to come into this huge property we

741
00:39:13,680 --> 00:39:16,360
Speaker 6: have and whoever can give us the best package, like,

742
00:39:16,400 --> 00:39:18,480
Speaker 6: we'll accept them. But it says the opposite. It's like

743
00:39:18,560 --> 00:39:20,759
Speaker 6: these companies say, Okay, unless you're willing to do this

744
00:39:20,880 --> 00:39:23,359
Speaker 6: with just me behind closed doors, we're not even going

745
00:39:23,400 --> 00:39:25,960
Speaker 6: to entertain it. And in some places, like data centers

746
00:39:25,960 --> 00:39:29,080
Speaker 6: have been great, like they're counties in Northern Virginia and

747
00:39:29,080 --> 00:39:31,920
Speaker 6: in Looten County that they have great tax incentives, and

748
00:39:32,320 --> 00:39:34,839
Speaker 6: you know, these data centers are like paying for new

749
00:39:34,880 --> 00:39:37,239
Speaker 6: schools and roads and all this stuff. And then you

750
00:39:37,239 --> 00:39:40,160
Speaker 6: have other places where they're not and they're taking up

751
00:39:40,360 --> 00:39:42,560
Speaker 6: a lot of the energy and raising people's energy bills,

752
00:39:42,600 --> 00:39:45,279
Speaker 6: They're using a lot of water. It's like the real

753
00:39:45,320 --> 00:39:47,480
Speaker 6: story of data centers to me, has been that you

754
00:39:47,520 --> 00:39:51,680
Speaker 6: have these high tech companies going into these really underserved

755
00:39:51,960 --> 00:39:55,120
Speaker 6: parts of the country that have really aging infrastructure, and

756
00:39:55,239 --> 00:39:58,680
Speaker 6: the companies aren't really willing to pay to upgrade that infrastructure.

757
00:39:59,160 --> 00:40:02,040
Speaker 6: But nowadays, like with this data center, it's starting to

758
00:40:02,120 --> 00:40:04,160
Speaker 6: change a little bit where the companies say, Okay, if

759
00:40:04,160 --> 00:40:05,880
Speaker 6: we want to have the energy, we're going to just

760
00:40:05,920 --> 00:40:08,080
Speaker 6: have to get these turbines built ourselves.

761
00:40:08,320 --> 00:40:11,919
Speaker 1: So let's talk about the Virginia data centers, because there's

762
00:40:11,960 --> 00:40:16,640
Speaker 1: this thing called Data center Alley where they're using so

763
00:40:16,840 --> 00:40:21,120
Speaker 1: much power that it's causing the power other people's power

764
00:40:21,120 --> 00:40:25,200
Speaker 1: to flicker across the East Coast. Took us through that.

765
00:40:25,800 --> 00:40:28,600
Speaker 6: Yeah, this is happening in Virginia. I think in a

766
00:40:28,640 --> 00:40:31,759
Speaker 6: lot of the southern United States that people's energy bills

767
00:40:31,800 --> 00:40:34,759
Speaker 6: are going up because the data centers, the way they

768
00:40:34,880 --> 00:40:37,160
Speaker 6: use energy, it's so much of it, the way it

769
00:40:37,160 --> 00:40:39,960
Speaker 6: impacts the great I mean, it's just raising people's rates,

770
00:40:39,960 --> 00:40:42,800
Speaker 6: and it's something that it's become a big problem because

771
00:40:42,920 --> 00:40:44,920
Speaker 6: it's like it's kind of been wrapped into this whole

772
00:40:44,960 --> 00:40:48,560
Speaker 6: affordability narrative where it's like the cost of groceries, the

773
00:40:48,600 --> 00:40:51,160
Speaker 6: cost of eggs, power bills from data centers. It's like

774
00:40:51,200 --> 00:40:52,760
Speaker 6: it's all become kind of one movement.

775
00:40:52,840 --> 00:40:55,840
Speaker 1: Seems like, if you live in a state with a

776
00:40:55,840 --> 00:40:59,279
Speaker 1: lot of data centers, like Virginia, is your power bill

777
00:40:59,400 --> 00:41:02,440
Speaker 1: more expense because of the data centers.

778
00:41:02,360 --> 00:41:05,880
Speaker 6: In some cases, yes, but the energy companies kind of

779
00:41:05,920 --> 00:41:08,440
Speaker 6: dispute that. Honestly, I'm not I'm not super familiar with

780
00:41:08,480 --> 00:41:10,920
Speaker 6: the way that it increases the prices, but it's something

781
00:41:10,960 --> 00:41:13,040
Speaker 6: that there's like a ton of legislation.

782
00:41:12,560 --> 00:41:16,160
Speaker 1: A but it's certainly been reported that it does increase.

783
00:41:16,280 --> 00:41:19,120
Speaker 1: Can you just tell me what these data centers do?

784
00:41:19,440 --> 00:41:22,040
Speaker 1: The Meta one, like, what will do? What is it

785
00:41:22,239 --> 00:41:23,200
Speaker 1: or is it not clear?

786
00:41:23,640 --> 00:41:26,600
Speaker 6: I mean, it's built around these these chips from Nvidia.

787
00:41:26,800 --> 00:41:30,000
Speaker 6: They basically they take the chips and actually build the

788
00:41:30,080 --> 00:41:33,080
Speaker 6: data centers essentially around the chips. So they're like these

789
00:41:33,200 --> 00:41:36,439
Speaker 6: racks of servers and they're all just made to uh,

790
00:41:36,520 --> 00:41:39,879
Speaker 6: you know, accommodate these chips and cool them and power

791
00:41:39,960 --> 00:41:43,600
Speaker 6: them with electricity. And Meta's data centers like there's like

792
00:41:43,760 --> 00:41:46,600
Speaker 6: five buildings and there's like a brain in the middle,

793
00:41:47,680 --> 00:41:49,719
Speaker 6: and yeah, if you go in them, it's based you know,

794
00:41:49,760 --> 00:41:51,520
Speaker 6: it hasn't been built yet, but it's basically just like

795
00:41:51,640 --> 00:41:53,200
Speaker 6: racks and racks of servers.

796
00:41:53,440 --> 00:41:57,040
Speaker 1: That's it. It's just like racks and racks of servers.

797
00:41:57,120 --> 00:41:59,960
Speaker 1: And then eventually there'll be a few people to watch

798
00:42:00,520 --> 00:42:01,400
Speaker 1: those chips.

799
00:42:01,640 --> 00:42:04,840
Speaker 6: Right, Yeah, this project's big. I mean Meta says that

800
00:42:04,880 --> 00:42:08,040
Speaker 6: there will be as many as a thousand people employed.

801
00:42:08,080 --> 00:42:11,040
Speaker 6: I mean, who knows how many of that's security versus

802
00:42:11,320 --> 00:42:13,800
Speaker 6: electricians or whoever it is. But still, when you think about,

803
00:42:13,840 --> 00:42:16,000
Speaker 6: you know, the size of the fifty billion dollar project,

804
00:42:16,120 --> 00:42:17,640
Speaker 6: a thousand people, it's not all that many.

805
00:42:18,239 --> 00:42:20,760
Speaker 1: It's just such a crazy story. And like, if you're

806
00:42:21,080 --> 00:42:23,880
Speaker 1: a person who wants to not live next to a

807
00:42:24,000 --> 00:42:28,400
Speaker 1: data center, what are the lessons from this data center disaster?

808
00:42:29,280 --> 00:42:34,480
Speaker 1: The lessons like, are there regulations that that governors have?

809
00:42:34,760 --> 00:42:36,520
Speaker 1: I mean, I know in New York State we have

810
00:42:36,719 --> 00:42:40,720
Speaker 1: like a banning of data centers. Are democratic governors doing

811
00:42:40,800 --> 00:42:44,040
Speaker 1: things to prevent stuff like what's happening in Louisiana or

812
00:42:44,040 --> 00:42:44,880
Speaker 1: have you not seen that?

813
00:42:45,239 --> 00:42:48,239
Speaker 6: Yeah, definitely they are. New York has put a temporary

814
00:42:48,400 --> 00:42:51,920
Speaker 6: pause on data centers. Seattle did the same thing. But

815
00:42:52,040 --> 00:42:54,640
Speaker 6: it's really not it's really not the liberal states that

816
00:42:54,680 --> 00:42:57,040
Speaker 6: are getting these investments for the most part. It's going

817
00:42:57,040 --> 00:43:00,440
Speaker 6: to be you know, Republican led governors that are leading

818
00:43:00,440 --> 00:43:03,120
Speaker 6: most of these projects. And I think a lesson that

819
00:43:03,200 --> 00:43:04,719
Speaker 6: I've taken away from this is that you know, if

820
00:43:04,760 --> 00:43:07,080
Speaker 6: you're someone who lives near your data center, it's likely

821
00:43:07,120 --> 00:43:09,080
Speaker 6: that you're not going to know about any of these

822
00:43:09,080 --> 00:43:12,160
Speaker 6: talks if they're happening, and if you ask, you're elected official,

823
00:43:12,200 --> 00:43:13,680
Speaker 6: they might not even be able to tell you because

824
00:43:13,719 --> 00:43:16,160
Speaker 6: they've signed an NDA with the company talking about it.

825
00:43:16,200 --> 00:43:18,600
Speaker 6: But that doesn't necessarily mean that the talks aren't happening

826
00:43:18,680 --> 00:43:21,440
Speaker 6: or that the data center's not going to be built nearby.

827
00:43:21,560 --> 00:43:23,520
Speaker 6: And they are all sorts of blueprints for the ways

828
00:43:23,520 --> 00:43:25,800
Speaker 6: that people are fighting back, but most of them involve

829
00:43:25,920 --> 00:43:27,759
Speaker 6: like just figuring out what's going on.

830
00:43:28,040 --> 00:43:32,120
Speaker 1: Pretty good case from not having NDAs. Thank you, Thank you, Eli,

831
00:43:32,440 --> 00:43:33,560
Speaker 1: thanks for so much for me on.

832
00:43:35,680 --> 00:43:38,040
Speaker 4: No moment.

833
00:43:38,480 --> 00:43:40,160
Speaker 1: Jesse Cannon smile.

834
00:43:40,480 --> 00:43:43,560
Speaker 3: You may remember the Heritage Foundation as the authors of

835
00:43:43,719 --> 00:43:47,960
Speaker 3: Project twenty twenty five, a document that has run a

836
00:43:48,000 --> 00:43:50,520
Speaker 3: lot of damage to our country. I have really sad

837
00:43:50,600 --> 00:43:54,840
Speaker 3: news for you. The Heritage Foundation is an absolute disarray

838
00:43:54,880 --> 00:43:55,919
Speaker 3: in having a civil war.

839
00:43:56,280 --> 00:44:00,640
Speaker 1: Could not have happened to a better anything me more

840
00:44:00,960 --> 00:44:01,720
Speaker 1: Jesse Cannon.

841
00:44:03,280 --> 00:44:08,680
Speaker 3: Well, as always, there's factions that break out in these institutions,

842
00:44:08,840 --> 00:44:11,359
Speaker 3: and so what you have is you have the more

843
00:44:11,400 --> 00:44:14,640
Speaker 3: people who are a little bit more into Christian fundamentalism,

844
00:44:15,040 --> 00:44:16,840
Speaker 3: and then you have the other people who are just

845
00:44:17,040 --> 00:44:20,920
Speaker 3: there going we want to be close to power and

846
00:44:21,239 --> 00:44:22,960
Speaker 3: they're now having a little squabble.

847
00:44:24,560 --> 00:44:28,240
Speaker 1: Yeah, let's just be happy about this. I mean, these

848
00:44:28,239 --> 00:44:32,280
Speaker 1: guys have raised so much money and they have done

849
00:44:32,480 --> 00:44:36,320
Speaker 1: so much damage. And it's like the biggest, baddest think

850
00:44:36,400 --> 00:44:40,400
Speaker 1: tank and it's headed by Kevin Roberts. You know he is,

851
00:44:41,040 --> 00:44:44,560
Speaker 1: you know, the head of Heritage. Kevin Roberts is a

852
00:44:44,600 --> 00:44:49,120
Speaker 1: big Tucker Carlson fan. And that created a division obviously,

853
00:44:49,160 --> 00:44:54,279
Speaker 1: because Tucker Carlson is at best white supremacist curious and

854
00:44:54,480 --> 00:44:57,160
Speaker 1: so you know, you have to sort of thread the

855
00:44:57,200 --> 00:45:01,320
Speaker 1: needle here of how white supreme do you want to know?

856
00:45:01,920 --> 00:45:03,399
Speaker 1: So that's a real division here.

857
00:45:03,680 --> 00:45:05,200
Speaker 3: Can I tell you what? I think The funniest one

858
00:45:05,360 --> 00:45:09,440
Speaker 3: is all the people who were like, we're Reagan Conservatives,

859
00:45:09,440 --> 00:45:12,160
Speaker 3: We're for free trade, free markets, and then they're seeing

860
00:45:12,160 --> 00:45:15,200
Speaker 3: what Trump has done here, which is just grift grift, grift,

861
00:45:15,280 --> 00:45:19,920
Speaker 3: grift grift. Yeah, they're like, wait, that's that's market distortions.

862
00:45:19,960 --> 00:45:22,440
Speaker 3: What do you mean I thought we're gonna do free trade.

863
00:45:22,920 --> 00:45:26,680
Speaker 1: Yeah exactly, So there we are. We just have a

864
00:45:26,960 --> 00:45:33,080
Speaker 1: real dark, kind of stupid and I'm glad to see it,

865
00:45:33,160 --> 00:45:35,440
Speaker 1: quite frankly, because these guys have really done a lot

866
00:45:35,480 --> 00:45:36,200
Speaker 1: of damage.

867
00:45:36,320 --> 00:45:38,320
Speaker 3: I think it's one of the great stories of Trump

868
00:45:38,360 --> 00:45:40,520
Speaker 3: is and we don't tell enough, which is that when

869
00:45:40,560 --> 00:45:44,040
Speaker 3: you believe in you know, your cheeto Jesus is going

870
00:45:44,080 --> 00:45:46,040
Speaker 3: to be your savior, you get a cheetah.

871
00:45:46,480 --> 00:45:49,360
Speaker 1: Yeah. Well, and it's also just what are we doing here?

872
00:45:49,680 --> 00:45:53,839
Speaker 1: It's just an insane way to run. You know, all

873
00:45:53,920 --> 00:45:58,880
Speaker 1: these organizations ultimately fall apart because the only thing that

874
00:45:58,920 --> 00:46:02,040
Speaker 1: they believe is fieldy to Donald Trump. And Donald Trump

875
00:46:02,040 --> 00:46:06,960
Speaker 1: doesn't have political positions particularly, so you know, his positions

876
00:46:06,960 --> 00:46:10,520
Speaker 1: are whatever he feels like. And so this is where

877
00:46:10,760 --> 00:46:15,720
Speaker 1: we are is just you know, a completely nonsensical kind

878
00:46:16,080 --> 00:46:21,399
Speaker 1: of craziness. That's it for this episode of Fast Politics.

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00:46:21,840 --> 00:46:27,560
Speaker 1: Tune in every Monday, Wednesday, Thursday and Saturday to hear

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00:46:27,840 --> 00:46:32,279
Speaker 1: the best minds and politics make sense of all this chaos.

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00:46:32,520 --> 00:46:35,359
Speaker 1: If you enjoy this podcast, please send it to a

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00:46:35,400 --> 00:46:39,400
Speaker 1: friend and keep the conversation going. Thanks for listening.