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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 Donald Trump has now overseen over

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Speaker 1: a million corporate job losses, the worst since two thousand

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Speaker 1: and three. We have such a great show for you today.

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Speaker 1: The think like an economist Justin Wolfers joins us to

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Speaker 1: talk about Trump's economy and why it's so bad at

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Speaker 1: giving numbers. Then we'll talk to former vice presidential candidate

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Speaker 1: Governor Tim Walls about how the government shutdown is affecting

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Speaker 1: his citizens. But first the news.

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Speaker 2: Smy the Trump administration, they just love starving poor people.

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Speaker 2: You know, we all know the cruelty is the point.

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Speaker 2: We've gotten the memo. But my god, they're ordered to

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Speaker 2: pay snap payments. They could just say, all right, we

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Speaker 2: can see, will give the poor some things that they're

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Speaker 2: like now, got to make sure they suffer. Got to

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Speaker 2: make sure that there's as much harm inflicted on these

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Speaker 2: people as possible.

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Speaker 1: So this is the first time ever that a government

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Speaker 1: has just decided not to pay snap benefits. The money

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Speaker 1: is there, like the Trump administration is is old hat

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Speaker 1: at like having money refusing to use it. It's not

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Speaker 1: their money. I mean, the thing I love about Donald

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Speaker 1: Trump is like he's like, you know, he's like the

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Speaker 1: rich dad being like, no, it's not for you, but

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Speaker 1: it's not yours, daddy. It's not your money, it's the

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Speaker 1: taxpayer's money. His administration is now fighting with the courts

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Speaker 1: about whether or not he has to pay SNAP benefit.

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Speaker 1: Forty percent of SNAP recipients are children, twenty percent are

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Speaker 1: the elderly, ten percent are disabled. They will go to

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Speaker 1: the grocery store and their Snap cards will have no

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Speaker 1: money on them. That is because of Donald J.

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Speaker 3: Trump.

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Speaker 1: If you have a clearer explanation of how Donald Trump

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Speaker 1: is just fucking people overloved right by the way, Ice

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Speaker 1: still having their student loan debt paid, Okay, riddle me this,

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Speaker 1: like who is this for besides Elon Musk who will

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Speaker 1: soon be a trillionaire.

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Speaker 2: Yeah, and let's remember all the air traffic controllers not

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Speaker 2: getting paid right now, all the congressional employees not getting

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Speaker 2: paid right now but still have to work.

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Speaker 1: And members of Congress getting paid. Mike Johnson, my man,

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Speaker 1: he's making his full paycheck.

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Speaker 2: My wife is out literally helping people in the streets

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Speaker 2: for free. That as mandated by her job, but not

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Speaker 2: getting a paycheck as we speak. Yes, So by I

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Speaker 2: don't normally recommend House Democrats imitating a guy who's on

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Speaker 2: videotape abusing his wife, who then became a meme because

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Speaker 2: he'd say change my mind and set college campuses where

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Speaker 2: a grown man would fight with college students. But I

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Speaker 2: have to say what Arizona repens Sorry did here by

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Speaker 2: trolling Mike Johnson and making it realize Mike Johnson's choosing

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Speaker 2: to keep the government shut down. I say more trolling

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Speaker 2: like this.

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Speaker 1: So she's a member of Congress. She sat down in

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Speaker 1: front of Mike Johnson's office in a table with a

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Speaker 1: placard on the front that had written on it Mike

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Speaker 1: Johnson is starving families and gutting health care to cover

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Speaker 1: up the Epstein files. Change my mind. It's a sort

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Speaker 1: of a homage to evil Stephen Crowder, who used to

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Speaker 1: do that in college campuses. But the point of it

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Speaker 1: is that it actually really got people talking, and then

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Speaker 1: it got Mike Johnson playing c span in front of

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Speaker 1: his office as a way to try to dispel it,

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Speaker 1: which ended up having more people coming to talk to her,

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Speaker 1: which ended up creating more attention. And again, like you know,

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Speaker 1: we talk so much about like how politicians can break through,

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Speaker 1: how democrats can connect with voters, and like we see

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Speaker 1: lots of different ways that politicians can do it, even

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Speaker 1: like from Jared Moskowed's to Chris Murphy to Bernie Sanders,

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Speaker 1: Like this is another way in which like if you think,

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Speaker 1: if you're thinking in a creative way, then you can

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Speaker 1: actually connect. And there are a lot of members of

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Speaker 1: Congress and well, you know, Mike Johnson sent a lot

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Speaker 1: of people home. There are still some people that are there.

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Speaker 1: A lot of the Democrats are still there, and like

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Speaker 1: this was an effective way I think to break through.

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Speaker 1: So good for her.

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Speaker 2: Yeah. So another thing, you know, there's been a lot

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Speaker 2: of talk about socialist rule in this country and how

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Speaker 2: you know the socialists are getting in charge. And by

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Speaker 2: that I mean Donald Trump saying that he wants a

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Speaker 2: piece of neurodisc.

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Speaker 1: So Donald Trump is amazing because whatever is happening in

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Speaker 1: his brain, he has no filter and he just says

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Speaker 1: whatever he thinks. So there was a pressor Donald Trump

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Speaker 1: and his administration got them to cut the cost of

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Speaker 1: these weight laws drugs, which is good. And then one

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Speaker 1: of the people on the wave loss drugs, passed out

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Speaker 1: and then RFK Junior ran out of the room. He

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Speaker 1: chap aquidict died out of there, slid But it's so good.

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Speaker 2: It's a really good joke.

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Speaker 1: Damn yeah, we see saw someone those Kennedy's when there's

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Speaker 1: a medical emergency, those are not your people. And then

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Speaker 1: Donald Trump fell asleep at his desk. But between all

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Speaker 1: of those things, that was one of the great meetings.

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Speaker 2: Truly, many people are saying the greatest.

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Speaker 1: One of the greatest. My favorite was when doctor Oz

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Speaker 1: was like, obesity can lead to dementia and pan to

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Speaker 1: Donald Trump.

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Speaker 2: Literally slumped down in his seat like me during history

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Speaker 2: class at eighth grade, just straight.

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Speaker 1: There, very very tired. So anyway, he did make this

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Speaker 1: is he made a threat. One of his favorite. He's

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Speaker 1: very into socialism. He said to the CEO, maybe you

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Speaker 1: should give us a PE's of the company, like I've

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Speaker 1: been asking for, give the United States a nice big

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Speaker 1: chunk of the company. By the way, in case you're wondering,

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Speaker 1: he doesn't want it for the United States. He wants

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Speaker 1: it for Donnie and Eric Somali.

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Speaker 2: We have two big, big Democratic congressional retirements in two

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Speaker 2: different ways. Nancy Pelosi.

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Speaker 1: Yeah, Nancy Pelosi will not seek re election to Congress

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Speaker 1: after forty years in Washington. She's eighty five. She'd stepped

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Speaker 1: down from leadership. She is now leaving the party. Probably

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Speaker 1: the most effective speaker of the House we've ever had.

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Speaker 1: Love her, hate her, feel very betrayed by her husband

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Speaker 1: stock Trading.

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Speaker 2: Can we pour one out for four h four Media's headlight,

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Speaker 2: one of the greatest headlines of all time, one of

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Speaker 2: the greatest Wall Street investors of all time, announces retirement.

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Speaker 1: I mean, yes, that was bad, but she also did

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Speaker 1: some good stuff.

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Speaker 2: I agree, I agree, but also we could laugh at that.

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Speaker 1: We can like love our politicians and also know that

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Speaker 1: they are often less than perfect.

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Speaker 2: So as well, though, somebody you love to bring up

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Speaker 2: on this podcast as a Congressman from main secred district,

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Speaker 2: which is an R plus four district. Representative Jared Golden

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Speaker 2: is retiring and many people are worried that this is

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Speaker 2: a seat that Dems cannot win without him.

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Speaker 1: Yeah, who knows he's retiring. I don't know how happy

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Speaker 1: he was. Ever, the times that I met him, he

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Speaker 1: seems super unhappy. There's a lot of blaming going on

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Speaker 1: of whether people pushed him to drop out or I

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Speaker 1: don't know.

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Speaker 2: Are you telling me people are unhappy being a congressperson.

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Speaker 2: That's such a great job.

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Speaker 1: Everybody wants it like such a good job. But we'll see.

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Speaker 1: I mean again, he's dropping out. That's too bad. There

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Speaker 1: is going to be an open govenmentorial. There's going to

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Speaker 1: be you know, there's a lot of stuff to run

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Speaker 1: for in Maine right now. Justin Wolfers is the host

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Speaker 1: to be Thinking Like an Economist podcast and a professor

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Speaker 1: at the University of Michigan. Welcome back to Fast Polity.

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Speaker 1: It's Justin Wlfer's So the great news for the Trump

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Speaker 1: administration is when the government is shut down, you don't

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Speaker 1: get the numbers right.

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Speaker 4: Just like how we solved COVID so exactly numbers, no problems.

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Speaker 1: But it was he had already before shutting down. In

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Speaker 1: Trump's defense, before shutting down the government, he had fired

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Speaker 1: the head of the Bureau of Labor Statistics.

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Speaker 4: He made his position on data very clear. He's against it.

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Speaker 1: Yeah.

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Speaker 4: He also has very strong position on truth.

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Speaker 1: That's right optional. He likes truthiness.

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Speaker 4: Yep, in small doses and only occasionally yes.

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Speaker 1: At this point, does the government give us public data.

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Speaker 1: Still not really or yes or talk us through it.

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Speaker 4: It's a very sad day. So I'm going to make

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Speaker 4: this personal if I may. Molly is I've been a

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Speaker 4: nerd for a very long time. When I left college,

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Speaker 4: my first deviate job was at the Reserve Bank of Australia.

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Speaker 4: And when you have a like the FED, and when

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Speaker 4: you get a job as a baby economist, they give

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Speaker 4: you one tiny sliver of the economy to look after.

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Speaker 4: And my job was the job's report. And so even

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Speaker 4: as a little baby economist, I would wake up.

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Speaker 1: In a text say country in a very.

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Speaker 4: In a magnificent and beautiful country with a functional democracy

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Speaker 4: and a well functioning economy, you don't love it anymore,

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Speaker 4: which I have family and think about during an anna

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Speaker 4: able winter. The job was like it would be jobs Day,

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Speaker 4: and I would wake up excited for jobs Day, even

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Speaker 4: as a twenty two year old. And then I moved

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Speaker 4: to America and I did my PhD, and you know,

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Speaker 4: you forget about the real world for a little while.

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Speaker 4: And then my better half, Betsy Stevenson, became the chief

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Speaker 4: economist at the Department of Labor, and so it became

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Speaker 4: this thing Friday, The first Friday of every month was

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Speaker 4: Job's Day, and she had to get in early and

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Speaker 4: brief the labor secretary and talk to the media and

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Speaker 4: crunch the numbers for what was then the first a

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Speaker 4: Bama administration, and so jobs. There was such a big

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Speaker 4: day in our household. And then I was writing for

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Speaker 4: New York Times, and I used to write about the

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Speaker 4: jobs numbers, and it was all very exciting, and it stays.

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Speaker 4: It's just a regular part of our monthly life ever since,

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Speaker 4: to the point that I literally our nanny would walk

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Speaker 4: in and say, Oh, it's a job's day today, how

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Speaker 4: are you feeling about the economy? And today I woke

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Speaker 4: up and it's the first Friday of the month, and

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Speaker 4: there was an enormous void in my life, the sense

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Speaker 4: of checking in on the workers and seeing how they're doing,

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Speaker 4: of hoping that the economy is moving forward and producing

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Speaker 4: more for more of us, of wondering what's next, of

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Speaker 4: thinking about policies that could make a difference. I did

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Speaker 4: none of that. I sat in the dark room, staring

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Speaker 4: at the corner, rocking backward and forward, crying, just one

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Speaker 4: solitary tear down my cheek, talk us through this.

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Speaker 1: We don't have the government data, but we do have

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Speaker 1: some private data. Does that fill the void or does not?

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Speaker 4: It's sort of like, you know, when mum and dad

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Speaker 4: get divorced and then mum starts dating a new guy,

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Speaker 4: but she's not really sure that he's going to be

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Speaker 4: around for very long, and maybe they've been dating two

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Speaker 4: months and he takes you out to the zoo. That

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Speaker 4: is the ADP Job Report. The ADGP job report is

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Speaker 4: not something well loved, has no particular track record, is

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Speaker 4: not particularly reliable, and when you need it, you don't

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Speaker 4: know if it'll always be there for you.

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Speaker 2: So no, we don't.

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Speaker 4: There's going to be a lot of press attention around

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Speaker 4: the ADP Job Report, and it came in yesterday, it

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Speaker 4: was or the day before. It was not as bad

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Speaker 4: as the past few have been, but still the important

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Speaker 4: thing is not the comparison with are you as bad

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Speaker 4: as last month? But are you good or bad? It

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Speaker 4: was unequickly pointing to a weak economy, but I don't

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Speaker 4: want anyone to place much stock in it. It is

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Speaker 4: a very unreliable indicator. So the truth is we're all

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Speaker 4: alone in the dock right now. I hope this doesn't

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Speaker 4: sound like I'm talking about my childhood.

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Speaker 1: So I want you to I need you to sort

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Speaker 1: of pull back from the job support into what you

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Speaker 1: think the economy. So we have a federal government that's

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Speaker 1: pretty hostile, that's a the longest shutdown ever, be pretty

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Speaker 1: hostile to facts, reason truth. So how do you figure

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Speaker 1: out where the economy is? Knowing those two sayings?

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Speaker 4: Okay, so the good news, then the bad news. The

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Speaker 4: good news is the government data is not the only

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Speaker 4: data that we have. I did warn you a moment

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Speaker 4: ago that private sick the data about the state of

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Speaker 4: the labor market is not as good as government data,

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Speaker 4: and that's absolutely stunningly true. So we have lost some

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Speaker 4: very important things. There do exist many other data sets.

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Speaker 4: For instance, the Federal Reserve, which is not affected by

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Speaker 4: the shutdown, collects industrial production, and so we know how

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Speaker 4: much stuff is coming out of factories. We're not going

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Speaker 4: to be getting GDP data, but we are going to

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Speaker 4: continue to see surveys of companies telling us how they're doing.

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Speaker 4: We have all sorts of things about our daily lives

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Speaker 4: and measured in all sorts of ways. We know restaurant

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Speaker 4: reservations through open table, and we've got a lot of

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Speaker 4: practice of this during the pandemic, when a lot of

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Speaker 4: our normal ways of thinking about the economy were broken.

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Speaker 4: What are some creative ways. So the good news is

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Speaker 4: we're not purely in the dark. The bad news is

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Speaker 4: it's pretty damn foggy, which is it's going to be

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Speaker 4: very hard to have any great sense of what's going

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Speaker 4: on that really really matters right now. Why right now?

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Speaker 4: Because it's possible, but by no means certain that we're

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Speaker 4: at a turning point. It's possible that. Remember we've been

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Speaker 4: talking about tariffs for eight months, and I know I've

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Speaker 4: brought everyone on this, but actually Trump has only really

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Speaker 4: truly imposed them a couple of months ago, and so

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Speaker 4: if they're going to have an effect, it would be

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Speaker 4: any day now. We are seeing some hints that the

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Speaker 4: economy is slowed right off, not just because of tariff's

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Speaker 4: by the way, but also we've had a huge to

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Speaker 4: immigration and new people create new stuff, and so that's

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Speaker 4: something that's really going to be missing as well. Those

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Speaker 4: are two enormous shocks that are hitting the economy right now.

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Speaker 4: And we do know enough to know that the economy

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Speaker 4: was slowing, and the question is are we slowing into

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Speaker 4: comfortable or are we slowing into a recession and we

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Speaker 4: actually have no way of knowing that right now, which

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Speaker 4: is a very very uncomfortable place to be in.

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Speaker 1: Yeah, that does not sound good. And then the other question,

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Speaker 1: which you know, people will be listening to this podcast

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Speaker 1: on Saturday morning and we will be in the middle

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Speaker 1: of what Sean Duffy lovingly refers to as airplane armageddon,

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Speaker 1: where they basically just slow down air traffic because vibes.

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Speaker 1: So that seems like it could have larger consequences to

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Speaker 1: the economy.

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Speaker 4: Well, you usually bring me in for the stuff that

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Speaker 4: you feel less confident on, and that's usually macroeconomics. You

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Speaker 4: feel terrific on finance, and when it comes to fashion, wow,

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Speaker 4: and politics for sure, and peace on gender. I thought

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Speaker 4: the other in the New York Times. I love that

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Speaker 4: l Thank you. So you want to talk about macroeconomics.

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Speaker 4: And the truth is that the government shutdown is going

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Speaker 4: to be a small impact in terms of its overall

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Speaker 4: macro stuff, right, So the headlines aren't going to change

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Speaker 4: a lot. That's position one. Position two that's also true

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Speaker 4: is every single holiday that's destroyed, every snap beneficiary who

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Speaker 4: went to bed, hungry and fearful last night.

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Speaker 1: Right, and that's started now. SNAP. The Trump administration is

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Speaker 1: not funding SNAP, even though federal judges have told them

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Speaker 1: they have to.

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Speaker 4: So then they should be. And I don't you know,

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Speaker 4: none of us will believe it until the money's on

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Speaker 4: the card, which means the most vulnerable people in our

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Speaker 4: society who have no stockpile of cash, no.

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Speaker 1: Waves, forty percent of which are children, elderly, and ten

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Speaker 1: percent are disabled.

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Speaker 2: Let's just pause on that for a moment.

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Speaker 1: Mine, yeah, and FYI are white like even.

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Speaker 4: That, we know that is and should be irrelevant. Let's

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Speaker 4: pull on the very human thing you said. It's profoundly important.

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Speaker 4: Many of our listeners, just like you and I Moly,

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Speaker 4: are fortunate enough. We're doing okay economically, and so we

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Speaker 4: don't think about how will I go to the grocery

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Speaker 4: store next week? What can I afford to buy?

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Speaker 3: What is in the covert?

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Speaker 1: But we do notice, I mean, I certainly noticed that

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Speaker 1: my grocery bells are humongous, like crazy high compared to

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Speaker 1: what I mean, there are much more, and if we're

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Speaker 1: noticing it, it means it's real. Everywhere.

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Speaker 4: Food prices are up about three percent over the past year.

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Speaker 4: I am profoundly disgusted by anyone who can take the

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Speaker 4: most vulnerable and make them pawns in the political game.

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Speaker 3: Why don't we just have a.

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Speaker 4: Different kind of shutdown where tax cuts for millionaires get

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Speaker 4: put off for a few weeks. I mean, it's only

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Speaker 4: a weird accident, and well it's not even a weed accident.

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Speaker 4: It's also the illegality and then the approach to the administration.

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Speaker 4: But it's one of the most awful things I've seen

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Speaker 4: the American government do to its own people. And it

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Speaker 4: doesn't need to do it. There's money there, we know

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Speaker 4: how to spend it. I also want to pan back

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Speaker 4: because Molly, you're also you know, you're like, oh, what's

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Speaker 4: the fifth of the chapter, and you think about next

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Speaker 4: quarter's GDP When we go back to the things that

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Speaker 4: you were talking about, things like we no longer have

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Speaker 4: statistical agencies that are being told it's important to tell

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Speaker 4: the truth. Now so far they are telling the truth,

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Speaker 4: and they want to remind our listeners of that. But

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Speaker 4: when you fire the head of the BLS for no reason,

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Speaker 4: you're sending them a message. You can stop with that

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Speaker 4: truth stuff. When you have CEOs of major corporations walk

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Speaker 4: into the White House and walk out ten minutes later

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Speaker 4: with ten percent less of their company. When you have

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Speaker 4: the present.

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Speaker 1: Telling them that it's called socialism.

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Speaker 4: It's called something asm and you have the administration ignoring

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Speaker 4: the courts when you have real questions, when you have

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Speaker 4: ice on the streets. All of this stuff. None of

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Speaker 4: it shows up in this quarter's GDP. But it's more

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Speaker 4: important than anything that shows up in next quarter's GDP.

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Speaker 4: That is not a political statement. That is an economic statement.

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Speaker 4: That is a statement that, on average, the average populist

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Speaker 4: leader over the last hundred years, when you elect them

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Speaker 4: a decade later, has led GDP to be about fifteen

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Speaker 4: percent lower. Let me say that more human terms. GDP's

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Speaker 4: a fancy word for you elect Trump like characters, and

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Speaker 4: history shows that a decade later, average income is fifteen

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Speaker 4: percent lower, and he could be worse. When you look

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Speaker 4: at these big questions, what makes the United States rich

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Speaker 4: and the country of my birth, which was Papulnian Guinea poor,

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Speaker 4: It's really about state capacity. It's about how we run

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Speaker 4: our economy. It's our political and economic institutions, and they're

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Speaker 4: all being burned down right now. None of that is

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Speaker 4: going to be next quarter's GDP. But everything we know

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Speaker 4: about how economies work tell us this is overwhelmingly the

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Speaker 4: most important thing going on. You can't see it, but

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Speaker 4: what we will know is that our kids are going

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Speaker 4: to wake up in ten or twenty years time and

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Speaker 4: the opportunities in front of them are going to simply

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Speaker 4: not be there. And it's these unborn opportunities. It's the

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Speaker 4: new ideas, the new industries that just simply never happened,

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Speaker 4: and that's the real cost and.

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Speaker 1: The problems in China.

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Speaker 4: I am trying to figure out how you tell this story,

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Speaker 4: so I need your help because it's not a story.

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Speaker 4: It's economic research. This is findings from serious people studying

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Speaker 4: hundreds of years of economic history among every country around

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Speaker 4: the world. And it's not so obvious, but this is

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Speaker 4: Folks like Emily do a great job telling it as

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Speaker 4: a political story, but this is an economic story as well.

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Speaker 4: And the American poor will be poorer as a result

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Speaker 4: of our pie being smaller as a result of everything

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Speaker 4: that's going on.

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Speaker 1: Yeah, thank you, Elon mush. So let's talk about where

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Speaker 1: we are right now. When it comes to we don't

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Speaker 1: have the data, we have have these tariffs. We have

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Speaker 1: the Supreme Court fight, this insane Supreme Court fight whether

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Speaker 1: Donald Trump has the power to do everything he's ever

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Speaker 1: wanted to do period paragraph. The questions with the Supreme Court,

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Speaker 1: this case, this tariff case, are so big because the

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Speaker 1: courts could side that Trump doesn't have the economic power

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Speaker 1: to do these things and it could not necessarily matter,

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Speaker 1: right Like they could say he has time to pay back,

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Speaker 1: or he has this, or is that. So I would

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Speaker 1: love it if you could explain to us, don't predict

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Speaker 1: the future, but just lay out what the possible lanes are.

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Speaker 4: I think what you just says. Can you be an

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Speaker 4: economics professor for about five.

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Speaker 1: Minutes, but I'm the Supreme Court case.

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Speaker 4: Yeah, okay. So here's the critical things for people to understand.

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Speaker 4: The Constitution. So the Constitution gives the power to tax

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Speaker 4: to Congress. Congress has delegated some of those authorities to

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Speaker 4: the White House because Congress understands that Congress is not

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Speaker 4: very nimble, and so for things like national security and

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Speaker 4: so on, you can live in new tariffs through the

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Speaker 4: White House without Congress.

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Speaker 3: There's a process. But that's it.

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Speaker 4: Trump decided he granted himself a new set of powers

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Speaker 4: that had never been used before. All of the tariffs

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Speaker 4: that are on individual countries, on China, on Canada, and

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Speaker 4: actually on every country around the world. Eighty percent of

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Speaker 4: what he's done has been country by country tariffs. There's

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Speaker 4: no legal authority for that. Trump claims he gets one

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Speaker 4: through what's called the Emergency Powers Act. The Emergency Powers

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Speaker 4: Act is two things are really important about it. One,

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Speaker 4: no where does it mention the word tariff or tax.

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Speaker 1: You're suit a stickler for these words. And wait.

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Speaker 4: Second, well, good that you're thinking about that, because the

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Speaker 4: second thing is stickler for words. It's called the Emergency

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Speaker 4: Powers Act. Yeah, so I know he wants the powers.

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Speaker 4: I think that means you got to have the emergency.

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Speaker 1: As just as Amy brought up, what is the national

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Speaker 1: security reason for now? You could say Tokyo, you know,

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Speaker 1: you could say Japan, but then you can't also.

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Speaker 4: Say tariff's'm bananas, right, you know?

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Speaker 1: And me and Italy like it has it out?

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Speaker 4: What about the aggression coming from north of the border

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Speaker 4: as Canadians far out won the World lost the World

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Speaker 4: Series even thank you, Yes, that's good. So those are

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Speaker 4: the central issues I listened to the Supreme Court argument.

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Speaker 4: They actually focused almost exclusively on the first days, which

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Speaker 4: was does the Emergency Powers Act give the President the

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Speaker 4: right over tariffs. The government's view was, Oh, if tariffs

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Speaker 4: work properly, no one will ever buy anything from abroad,

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Speaker 4: which means we'll collect no revenue. So therefore the revenue

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Speaker 4: is merely incidental. This is about regulating other countries. The

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Speaker 4: justices fought back and they said, if you want people

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Speaker 4: to not buy from other countries, here's a simple thing,

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Speaker 4: have an embargo. So it was the Boston tea Party,

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Speaker 4: not the Boston embargo Party, was sort of the claim. So,

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Speaker 4: in fact, the government made up a new word. It

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Speaker 4: took me a long time to realize they made up

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Speaker 4: a new word. They talked about revenue tariffs versus regulatory tariffs.

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Speaker 4: One of these there's actually only tariffs a book behind me.

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Speaker 4: On the bookshelf I might have written. It defines a

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Speaker 4: tariff as attacks on imports. It is a tax. So

437
00:23:09,720 --> 00:23:12,000
Speaker 4: the government wants to claim there's something called a regulation tariff.

438
00:23:12,040 --> 00:23:15,160
Speaker 4: It's literally a word. They just invent it. Yeah, doesn't exist.

439
00:23:15,760 --> 00:23:18,240
Speaker 4: So that's where most of the argument was. The justices

440
00:23:18,280 --> 00:23:21,359
Speaker 4: were pretty hostile because when Congress wants to get rid

441
00:23:21,359 --> 00:23:23,600
Speaker 4: of its taxing powers. It tends to be very very

442
00:23:23,800 --> 00:23:26,440
Speaker 4: very clear, and it didn't even use the word here.

443
00:23:27,240 --> 00:23:29,199
Speaker 4: But then you still get to the second problem, which is,

444
00:23:29,280 --> 00:23:31,200
Speaker 4: even if it had the power, does Trump have a

445
00:23:31,280 --> 00:23:35,160
Speaker 4: national emergency? This is where as an economist, the administration says,

446
00:23:35,160 --> 00:23:37,719
Speaker 4: we have a national emergency because we have a trade

447
00:23:38,440 --> 00:23:41,760
Speaker 4: unbalanced trade with specific countries. That's what it's called a

448
00:23:41,800 --> 00:23:47,480
Speaker 4: bilateral trade deficit. No economist alive thinks they matter. Not

449
00:23:47,600 --> 00:23:50,240
Speaker 4: even do we not think they're an emergency. We don't

450
00:23:50,240 --> 00:23:51,320
Speaker 4: even think they're interesting.

451
00:23:51,520 --> 00:23:54,359
Speaker 1: So even like a Kevin Hasset.

452
00:23:54,600 --> 00:23:57,840
Speaker 4: Even Kevin Hasset, if you tied him down and injected

453
00:23:57,920 --> 00:24:02,280
Speaker 4: him with honesty juice, yeah, Asset, it would take a

454
00:24:02,280 --> 00:24:03,320
Speaker 4: lot of honesty Jews.

455
00:24:03,520 --> 00:24:05,080
Speaker 1: What about Stephen Moore?

456
00:24:06,320 --> 00:24:07,679
Speaker 4: So stupid that it hurts?

457
00:24:07,960 --> 00:24:09,480
Speaker 1: I mean, I just want to know who is the

458
00:24:09,600 --> 00:24:11,240
Speaker 1: dumbest MAGA economist.

459
00:24:11,680 --> 00:24:13,320
Speaker 3: I am going to be really nice.

460
00:24:13,440 --> 00:24:15,240
Speaker 4: I'm just gonna say I'm glad that there are people

461
00:24:15,440 --> 00:24:17,480
Speaker 4: now I can't even say nice things. I'm just going

462
00:24:17,560 --> 00:24:19,919
Speaker 4: to stay out of that. But like serious point for

463
00:24:19,960 --> 00:24:22,880
Speaker 4: the audience, what happens when a new administration comes to

464
00:24:22,880 --> 00:24:25,480
Speaker 4: town is usually they recruit the best and the brightest

465
00:24:26,200 --> 00:24:28,480
Speaker 4: every administration, not only in my lifetime, in the previous

466
00:24:28,480 --> 00:24:30,240
Speaker 4: fifty years. You can look at who was the chair

467
00:24:30,280 --> 00:24:32,520
Speaker 4: of the Council of Economic Advisors, Who were the nerds

468
00:24:32,520 --> 00:24:35,080
Speaker 4: and the wonks around the president, and they were the

469
00:24:35,119 --> 00:24:38,119
Speaker 4: best and brightest of their generation. Many a former Nobel

470
00:24:38,160 --> 00:24:40,800
Speaker 4: Prize winners, for ins a Nobel Prize winners, for instance.

471
00:24:41,240 --> 00:24:43,159
Speaker 4: What we have in the current White House is you

472
00:24:43,200 --> 00:24:46,159
Speaker 4: can take any ranking of the horsepower of economists, and

473
00:24:46,240 --> 00:24:49,240
Speaker 4: many exist. By the way, there is no one in

474
00:24:49,280 --> 00:24:53,399
Speaker 4: the White House who is in America's ten thousand best economists.

475
00:24:53,880 --> 00:24:56,320
Speaker 4: That's not a hint of exactly, that's a quantitative statement.

476
00:24:56,560 --> 00:25:00,600
Speaker 4: They've gone dragging through the gutter. Stupid is jupid does?

477
00:25:01,280 --> 00:25:03,240
Speaker 4: I don't want to be that guy. I hate being

478
00:25:03,280 --> 00:25:06,439
Speaker 4: that guy. But it's not a well advised White House.

479
00:25:07,600 --> 00:25:09,520
Speaker 4: Maybe in competence is part of the strategy.

480
00:25:09,960 --> 00:25:12,200
Speaker 1: We're at a time. What are you going to watch

481
00:25:12,240 --> 00:25:16,359
Speaker 1: for over the next couple of weeks, economic indicators, what's

482
00:25:16,359 --> 00:25:17,200
Speaker 1: coming down the pike.

483
00:25:17,800 --> 00:25:19,399
Speaker 4: I think the most interesting thing is going to be

484
00:25:19,400 --> 00:25:22,560
Speaker 4: the Supreme Court tariff case. It's probably going to happen quickly,

485
00:25:22,600 --> 00:25:25,879
Speaker 4: according to the legal nerds I talked to, not tomorrow quickly,

486
00:25:25,920 --> 00:25:29,119
Speaker 4: but maybe you know even before Thanksgiving. That'd be amazing,

487
00:25:29,160 --> 00:25:32,399
Speaker 4: wouldn't it. Have you Thanksgiving talk about tariffs around the Turkey. If,

488
00:25:32,720 --> 00:25:36,040
Speaker 4: as I expect, the Trump tarift's areroyalt illegal, we're going

489
00:25:36,080 --> 00:25:40,280
Speaker 4: to move from eight months of unconstitutional, illegal tariff turmoil

490
00:25:40,359 --> 00:25:43,600
Speaker 4: that have created all sorts of headaches to a whole

491
00:25:43,640 --> 00:25:46,280
Speaker 4: new set of tariff turmoil, some of which in the

492
00:25:46,280 --> 00:25:50,560
Speaker 4: future may even be constitutional. But it'll be this crazy,

493
00:25:50,640 --> 00:25:54,000
Speaker 4: crazy soap opera in which the president tries to run

494
00:25:54,280 --> 00:25:56,920
Speaker 4: an economy by pretending he and he alone can move

495
00:25:56,960 --> 00:26:02,080
Speaker 4: the pieces around the global economy chessboard. So if you

496
00:26:02,200 --> 00:26:06,520
Speaker 4: think you've seen myhem strapping this plenty more ahead.

497
00:26:06,840 --> 00:26:09,440
Speaker 1: I was told trade wars are good and easy to win.

498
00:26:10,240 --> 00:26:11,520
Speaker 1: Thank you, justin.

499
00:26:11,720 --> 00:26:12,359
Speaker 3: Thank you, Molly.

500
00:26:14,520 --> 00:26:18,720
Speaker 1: Governor Tim Walls is a former vice presidential candidate and

501
00:26:19,040 --> 00:26:24,000
Speaker 1: the governor of the great state of Minnesota. Welcome back

502
00:26:24,359 --> 00:26:26,639
Speaker 1: too fast Politics, Governor Walls.

503
00:26:27,000 --> 00:26:29,160
Speaker 3: It's good to be with you, Molly. It's been too long,

504
00:26:29,400 --> 00:26:32,199
Speaker 3: but you had a whole row of great guests you've

505
00:26:32,240 --> 00:26:34,040
Speaker 3: had on so glad to be back.

506
00:26:34,240 --> 00:26:36,240
Speaker 1: I just wanted to talk to you. I just felt

507
00:26:36,240 --> 00:26:40,920
Speaker 1: like we needed to catch up about how and there's

508
00:26:40,960 --> 00:26:46,320
Speaker 1: something about this particular moment in American life after this,

509
00:26:46,520 --> 00:26:49,600
Speaker 1: you know, we're talking in the week of the twenty

510
00:26:49,720 --> 00:26:52,840
Speaker 1: twenty five cycle, which was a tiny, tiny cycle, but

511
00:26:52,920 --> 00:26:56,000
Speaker 1: a huge repudiation of trump Ism.

512
00:26:56,320 --> 00:26:59,040
Speaker 3: Absolutely, And look it helps me process too, because I

513
00:26:59,119 --> 00:27:01,920
Speaker 3: keep thinking, you know, year ago, we needed to see

514
00:27:01,920 --> 00:27:05,160
Speaker 3: these numbers, but these candidates and the American people showed

515
00:27:05,240 --> 00:27:07,639
Speaker 3: up in huge numbers. We were just talking. You know,

516
00:27:07,680 --> 00:27:10,639
Speaker 3: we now have the most female governors we've ever had

517
00:27:10,680 --> 00:27:16,159
Speaker 3: in American history, with Governor Alex Banberger and Cheryl and

518
00:27:16,200 --> 00:27:18,120
Speaker 3: then of course, you know winning in New York City

519
00:27:18,560 --> 00:27:21,520
Speaker 3: governor's race. The party is broad and we're proud of that.

520
00:27:21,880 --> 00:27:24,680
Speaker 3: But I just think for me, it was just good

521
00:27:24,720 --> 00:27:27,480
Speaker 3: to see what we all knew, that the American people

522
00:27:27,520 --> 00:27:31,000
Speaker 3: at heart are kinder people, They care more, that this

523
00:27:31,280 --> 00:27:34,159
Speaker 3: cruelty and this stuff isn't what they're looking for. So

524
00:27:35,000 --> 00:27:37,280
Speaker 3: I agree this is it was therapeutic. We know that

525
00:27:37,320 --> 00:27:42,280
Speaker 3: it was one moment in time, but it's encouraging and

526
00:27:42,520 --> 00:27:44,439
Speaker 3: I'm just grateful to the folks that went out and

527
00:27:44,480 --> 00:27:47,080
Speaker 3: voted and some of the massive swings we saw of

528
00:27:47,160 --> 00:27:51,120
Speaker 3: young people coming back and Hispanic voters, and so good

529
00:27:51,119 --> 00:27:52,520
Speaker 3: to be with you at this point.

530
00:27:52,720 --> 00:27:56,520
Speaker 1: It's interesting because it's like, you know, the twenty twenty

531
00:27:56,520 --> 00:27:59,399
Speaker 1: four cycle for me, and I know for you too,

532
00:28:00,440 --> 00:28:04,239
Speaker 1: was just there was something about it that was just

533
00:28:04,320 --> 00:28:09,080
Speaker 1: devastating that I felt that, you know, it was in

534
00:28:09,160 --> 00:28:13,240
Speaker 1: all different ways, you know, a referendum on sort of

535
00:28:13,320 --> 00:28:18,560
Speaker 1: goodness and sandy and the American people said yet again

536
00:28:18,800 --> 00:28:21,600
Speaker 1: for the second time, and so I just would love

537
00:28:21,720 --> 00:28:24,560
Speaker 1: you know, we haven't talked since that election. You want

538
00:28:24,600 --> 00:28:27,640
Speaker 1: to talk about like what it was like for you,

539
00:28:27,680 --> 00:28:29,800
Speaker 1: because I know what it was like for me, and

540
00:28:30,040 --> 00:28:31,840
Speaker 1: it wasn't my name on that ticket.

541
00:28:32,640 --> 00:28:35,240
Speaker 3: Well, first of all, you know, and I think Vice

542
00:28:35,280 --> 00:28:38,040
Speaker 3: President Harris articulated so well that night when we found

543
00:28:38,080 --> 00:28:40,120
Speaker 3: out we weren't going to win, my first thought went

544
00:28:40,160 --> 00:28:42,400
Speaker 3: to what we knew would happened the most vulnerable. And

545
00:28:42,680 --> 00:28:46,840
Speaker 3: here we sat with Donald Trump building a ballroom and

546
00:28:47,040 --> 00:28:50,200
Speaker 3: going to court to deny food to children, not just

547
00:28:50,280 --> 00:28:52,680
Speaker 3: trying to do it. He did it, tried it, lost court.

548
00:28:52,720 --> 00:28:55,920
Speaker 3: Did you know, provide the food and that's not good enough.

549
00:28:55,960 --> 00:28:59,240
Speaker 3: So my thought, you know, the sense of ownership I had,

550
00:28:59,280 --> 00:29:00,600
Speaker 3: and that I knew there was going to be the

551
00:29:00,600 --> 00:29:02,240
Speaker 3: most vulnerable We're going to feel this.

552
00:29:02,240 --> 00:29:05,040
Speaker 1: This is the first shutdown ever, the longest shutdown ever,

553
00:29:05,120 --> 00:29:07,280
Speaker 1: and the first one where the government has decided the

554
00:29:07,320 --> 00:29:09,719
Speaker 1: Trump administration has decided not to fund snap.

555
00:29:10,000 --> 00:29:11,640
Speaker 3: Yeah, it's it's beyond the payout.

556
00:29:11,960 --> 00:29:12,320
Speaker 2: It is.

557
00:29:12,440 --> 00:29:14,800
Speaker 3: It is a cruelty. But look if at this point

558
00:29:14,840 --> 00:29:17,520
Speaker 3: in time, we don't understand that cruelty is not a bug,

559
00:29:17,560 --> 00:29:22,400
Speaker 3: it's a feature revenge and pettiness. If if selfishness is it.

560
00:29:22,400 --> 00:29:25,920
Speaker 3: It's all grounded in that. And and look, I Molly,

561
00:29:25,960 --> 00:29:29,680
Speaker 3: you talked about this. I don't think this surprises you.

562
00:29:29,880 --> 00:29:33,120
Speaker 3: It doesn't. It doesn't surprise me. But as a teacher

563
00:29:33,240 --> 00:29:36,280
Speaker 3: and as an elected official, I you know, I needed

564
00:29:36,280 --> 00:29:39,440
Speaker 3: to articulate that stronger. I think about that election and

565
00:29:39,520 --> 00:29:42,560
Speaker 3: elections are always about change. And you know, and I

566
00:29:42,600 --> 00:29:45,400
Speaker 3: think we got we were seen as status quo. I

567
00:29:45,440 --> 00:29:47,400
Speaker 3: would I would say what you said, Molly, is I

568
00:29:47,400 --> 00:29:50,200
Speaker 3: think we were status quo of decency and goodness and

569
00:29:50,320 --> 00:29:53,800
Speaker 3: order and not chaos. But the public wanted to see

570
00:29:53,800 --> 00:29:56,840
Speaker 3: something else. And you know, Trump promised these farmers they

571
00:29:56,840 --> 00:29:58,920
Speaker 3: were going to be rich. Well, now they're going bankrupt,

572
00:29:59,240 --> 00:30:01,840
Speaker 3: he crisis were going to come down. He didn't. So

573
00:30:01,880 --> 00:30:04,080
Speaker 3: I think what happened is the American people And look,

574
00:30:04,120 --> 00:30:06,360
Speaker 3: I think we saw what seven percent of Trump voters

575
00:30:06,360 --> 00:30:10,920
Speaker 3: in some of these states switched back. He lied to them,

576
00:30:11,080 --> 00:30:14,600
Speaker 3: and they're tired of it. And now we have an opportunity,

577
00:30:14,800 --> 00:30:17,760
Speaker 3: which I think our candidates did tell them what we

578
00:30:17,880 --> 00:30:20,160
Speaker 3: stand for. Yeah, you can scream all you want of

579
00:30:20,200 --> 00:30:24,680
Speaker 3: them trying to make you know, Mayor elect Mondania face

580
00:30:24,720 --> 00:30:28,600
Speaker 3: of the Democratic Party. He's talking about bringing housing costs deck,

581
00:30:29,280 --> 00:30:31,880
Speaker 3: he's talking about making a city more liveable, if at

582
00:30:31,880 --> 00:30:34,800
Speaker 3: all possible, you know, I think. And then you see

583
00:30:34,800 --> 00:30:37,760
Speaker 3: that in Virginia, you see it in uh, you know,

584
00:30:37,920 --> 00:30:40,680
Speaker 3: state house races across the country. So I think the

585
00:30:40,720 --> 00:30:43,200
Speaker 3: Democrats now have a chance to say, look, you obviously

586
00:30:43,200 --> 00:30:45,400
Speaker 3: are sick of Trump. Here's what we can offer you.

587
00:30:45,680 --> 00:30:46,280
Speaker 3: And that's what.

588
00:30:46,960 --> 00:30:49,239
Speaker 1: Yeah, but what was it? I just am curious, like

589
00:30:49,280 --> 00:30:53,280
Speaker 1: for my own just because we're friends, Like, what was it? Like,

590
00:30:53,400 --> 00:30:56,280
Speaker 1: I mean, I just basically wrote, you know, I wrote

591
00:30:56,280 --> 00:30:58,120
Speaker 1: a bunch of pieces about the stuff I got wrong.

592
00:30:58,200 --> 00:31:00,880
Speaker 1: I tried to sort of take stock I think of

593
00:31:01,040 --> 00:31:04,760
Speaker 1: you as I don't know I feel like you you

594
00:31:05,040 --> 00:31:10,280
Speaker 1: are sturdy midwestern governor who really did show the country

595
00:31:10,320 --> 00:31:15,160
Speaker 1: that you're that you had a real national profile. You

596
00:31:15,320 --> 00:31:18,080
Speaker 1: got a lot of the kind of criticism that you

597
00:31:18,160 --> 00:31:21,080
Speaker 1: get when you have a national profile. But was it

598
00:31:21,240 --> 00:31:23,080
Speaker 1: I mean, first of all, what was it like to

599
00:31:23,120 --> 00:31:28,360
Speaker 1: go from sturdy midwestern governor to like, you know, to

600
00:31:28,480 --> 00:31:31,360
Speaker 1: everyone's did he you know, was was he the right pick?

601
00:31:31,440 --> 00:31:34,080
Speaker 1: And then also just like was it like I mean,

602
00:31:34,440 --> 00:31:35,600
Speaker 1: and has it changed you?

603
00:31:36,400 --> 00:31:38,239
Speaker 3: Yeah? Well, first of all was an honor and it

604
00:31:38,280 --> 00:31:40,240
Speaker 3: was And I view all these jobs just like I

605
00:31:40,320 --> 00:31:42,640
Speaker 3: viewed my teaching job, and you know, in Congress and

606
00:31:42,680 --> 00:31:44,560
Speaker 3: thing it was public service. And I got asked by

607
00:31:44,560 --> 00:31:46,480
Speaker 3: the Vice President of the United States to try and

608
00:31:46,520 --> 00:31:50,080
Speaker 3: help her win. That was my job. I did it

609
00:31:50,120 --> 00:31:53,120
Speaker 3: to the best of my ability. Certainly not flawless. We

610
00:31:53,240 --> 00:31:56,840
Speaker 3: all have, you know, our things we can do better at.

611
00:31:57,000 --> 00:31:59,680
Speaker 3: But I was very proud that we were articulating at decency.

612
00:31:59,720 --> 00:32:02,720
Speaker 3: We are articulating a vision around whether it was healthcare, expansion,

613
00:32:02,800 --> 00:32:06,200
Speaker 3: home ownership, we were going to tackle problems like climate change.

614
00:32:06,800 --> 00:32:09,239
Speaker 3: So I was really proud. It was very short the

615
00:32:09,240 --> 00:32:13,840
Speaker 3: times that we were there. Again, I think back and

616
00:32:13,880 --> 00:32:16,000
Speaker 3: I think you have to do this reassessed. Could I

617
00:32:16,040 --> 00:32:19,480
Speaker 3: have been more you know, effective doing this? And I

618
00:32:19,520 --> 00:32:23,800
Speaker 3: don't think it's necessarily you know, rehashing something. But I

619
00:32:23,800 --> 00:32:26,080
Speaker 3: think we as ingercress have to learn why didn't we win?

620
00:32:26,400 --> 00:32:29,000
Speaker 3: Why did we win? What could we do better? Now?

621
00:32:29,000 --> 00:32:31,240
Speaker 3: Obviously I said, it's really frustrating to me. Is we

622
00:32:31,400 --> 00:32:34,760
Speaker 3: not only did we not win, we lost to that guy? Yeah,

623
00:32:34,960 --> 00:32:38,000
Speaker 3: and the it is the worst part. And I feel,

624
00:32:38,200 --> 00:32:40,320
Speaker 3: you know, personally, but like people said, you know, are

625
00:32:40,360 --> 00:32:43,080
Speaker 3: you doing okay? Are you going to be okay? Look,

626
00:32:44,120 --> 00:32:47,440
Speaker 3: older white guys who are governors, they tend to land

627
00:32:47,480 --> 00:32:50,800
Speaker 3: pretty song you're okay. But I said where I wasn't

628
00:32:50,840 --> 00:32:52,840
Speaker 3: okay was is knowing what I needed to do so

629
00:32:52,880 --> 00:32:54,560
Speaker 3: for me. And this is where I think, you know,

630
00:32:54,680 --> 00:32:56,920
Speaker 3: I've talked some but I haven't talked in depth of

631
00:32:57,000 --> 00:33:01,320
Speaker 3: Vice President Harris. I think it was very both therapeutic

632
00:33:01,400 --> 00:33:03,960
Speaker 3: and good. I just came right back home and got

633
00:33:03,960 --> 00:33:06,800
Speaker 3: to work. And we had a horrific summer. My best

634
00:33:06,800 --> 00:33:09,240
Speaker 3: friend was murdered, we had children shot in a church,

635
00:33:09,440 --> 00:33:12,440
Speaker 3: you know, so it was a horrific summer. But I was.

636
00:33:12,440 --> 00:33:19,480
Speaker 1: Talking about this the minute speaker Melissa Wortman murdered, political

637
00:33:19,560 --> 00:33:22,240
Speaker 1: murder in her bed with her dog and her husband

638
00:33:22,440 --> 00:33:25,320
Speaker 1: by a conservative right.

639
00:33:25,360 --> 00:33:28,160
Speaker 3: And a president who used that as an opportunity to

640
00:33:28,720 --> 00:33:33,160
Speaker 3: and senators from Utah to slander Minnesota.

641
00:33:33,240 --> 00:33:33,280
Speaker 4: Me.

642
00:33:33,800 --> 00:33:35,560
Speaker 3: So, look, I had something to do, and.

643
00:33:35,800 --> 00:33:37,800
Speaker 1: Your name was on that list too.

644
00:33:37,920 --> 00:33:40,920
Speaker 3: Yeah, well yeah, all of us, all the Democrats were,

645
00:33:41,360 --> 00:33:42,960
Speaker 3: you know. And then he would have killed more people

646
00:33:42,960 --> 00:33:45,560
Speaker 3: had he and he had the chance. So all that's

647
00:33:45,600 --> 00:33:47,640
Speaker 3: going on. Then we have children murdered on the first

648
00:33:47,720 --> 00:33:50,360
Speaker 3: day of school. I'm trying to fight for gun violence.

649
00:33:50,360 --> 00:33:52,160
Speaker 3: I'm trying to get rid of assault weapons and high

650
00:33:52,200 --> 00:33:55,360
Speaker 3: capacity magazines. So I had a place to go back

651
00:33:55,400 --> 00:33:57,440
Speaker 3: to and to do the work. And I think for me,

652
00:33:57,560 --> 00:33:59,800
Speaker 3: what was so encouraging about this is is that, look,

653
00:34:00,480 --> 00:34:04,040
Speaker 3: this was a catastrophic loss last fall, catastrophic for the country,

654
00:34:04,160 --> 00:34:07,880
Speaker 3: catastrophic for democracy. We have innocent people being swept up

655
00:34:07,920 --> 00:34:10,160
Speaker 3: off the streets. We have moms being yanked out of

656
00:34:10,200 --> 00:34:12,719
Speaker 3: their car and their babies driven away, you know, and things.

657
00:34:12,800 --> 00:34:16,200
Speaker 3: I mean, this is so horrific. But I have the

658
00:34:16,239 --> 00:34:19,359
Speaker 3: capacity to do something about it, at least in Minnesota,

659
00:34:18,960 --> 00:34:21,600
Speaker 3: so I'm back at it. I do think there were

660
00:34:21,680 --> 00:34:23,680
Speaker 3: lessons learned the affordability piece on this.

661
00:34:23,840 --> 00:34:25,719
Speaker 1: Can I just ask one question? This is like a

662
00:34:25,719 --> 00:34:28,400
Speaker 1: hobby horse of mine, as someone who's written so much

663
00:34:28,520 --> 00:34:32,839
Speaker 1: about that CSYCHO, I felt that the consultant class would

664
00:34:32,920 --> 00:34:35,359
Speaker 1: constantly get in there and be like, you know, like

665
00:34:35,560 --> 00:34:38,080
Speaker 1: I think of you as a politician with very good instincts,

666
00:34:38,360 --> 00:34:41,000
Speaker 1: and that every time something would take off, the consultant

667
00:34:41,000 --> 00:34:43,799
Speaker 1: class would go in there and like smush it is

668
00:34:43,840 --> 00:34:48,000
Speaker 1: that just my own fantasy? Did you see that happening?

669
00:34:48,040 --> 00:34:50,480
Speaker 1: I mean, there was so much. There was such a

670
00:34:52,000 --> 00:34:55,560
Speaker 1: group of very no i know, making a ton of

671
00:34:55,680 --> 00:34:57,759
Speaker 1: you know, just you know.

672
00:34:57,920 --> 00:35:00,360
Speaker 3: Yeah, well, look, first, it is so big. You know,

673
00:35:00,360 --> 00:35:03,719
Speaker 3: I've run statewide campaigns, but they pale in comparison. It

674
00:35:03,760 --> 00:35:07,320
Speaker 3: was so big. There's so many moving pieces in plans

675
00:35:07,880 --> 00:35:10,360
Speaker 3: that have to go. And look, I signed on very clearly.

676
00:35:10,440 --> 00:35:13,560
Speaker 3: My job was to get Kamala Harris elected president and

677
00:35:13,600 --> 00:35:15,560
Speaker 3: then to serve her in the role of her vice

678
00:35:15,600 --> 00:35:18,319
Speaker 3: president whatever she needed, whatever that looked like. So I'm

679
00:35:18,360 --> 00:35:20,839
Speaker 3: a team player, I have agency. You know. There were

680
00:35:20,880 --> 00:35:23,480
Speaker 3: things like I can speak up and there were things

681
00:35:23,520 --> 00:35:25,239
Speaker 3: that I did. But when I signed up and said

682
00:35:25,239 --> 00:35:27,680
Speaker 3: I'm on board, I said I'll follow the plan, and

683
00:35:27,719 --> 00:35:32,759
Speaker 3: I think retrospectively, you know, I've said this not critique.

684
00:35:32,800 --> 00:35:34,719
Speaker 3: I think it's just reality. I think we were too

685
00:35:34,800 --> 00:35:38,719
Speaker 3: cautious and played to not lose, play to win.

686
00:35:39,000 --> 00:35:41,399
Speaker 1: That is the consultant class that did.

687
00:35:41,520 --> 00:35:43,680
Speaker 3: That's their job. That's their job, and I have to

688
00:35:43,680 --> 00:35:46,440
Speaker 3: trust them. So I mean, in retrospect on everything, you

689
00:35:46,480 --> 00:35:48,720
Speaker 3: go back and say, maybe we should have done this differently.

690
00:35:48,360 --> 00:35:50,800
Speaker 1: But certainly do you wish she hadn't trusted them a

691
00:35:50,840 --> 00:35:53,040
Speaker 1: little bit? Though, Like because I see.

692
00:35:52,920 --> 00:35:54,799
Speaker 3: So many I don't know if it's an option though.

693
00:35:55,000 --> 00:35:57,120
Speaker 3: You know, when in this year on the ticket, my

694
00:35:57,239 --> 00:35:59,160
Speaker 3: job was to not cause any grief. And you know

695
00:35:59,280 --> 00:36:01,399
Speaker 3: I could give my put in and that there's great

696
00:36:01,400 --> 00:36:04,000
Speaker 3: folks in there and lots of thousands of people working.

697
00:36:04,040 --> 00:36:07,120
Speaker 3: They would take a look. I'll just give you one example.

698
00:36:07,760 --> 00:36:10,120
Speaker 3: I had a few minutes one afternoon I know, some

699
00:36:10,200 --> 00:36:12,920
Speaker 3: hotel somewhere and it's when I'm watching a football game

700
00:36:12,960 --> 00:36:15,040
Speaker 3: on a Sunday afternoon before we get ready to go again,

701
00:36:15,560 --> 00:36:18,759
Speaker 3: and the transgender at popped up. I very you know,

702
00:36:18,840 --> 00:36:22,000
Speaker 3: instinctively felt this. I said, this ad is dangerous. It's

703
00:36:22,120 --> 00:36:25,680
Speaker 3: dangerous if we don't respond because I think we have

704
00:36:25,800 --> 00:36:27,879
Speaker 3: to to defend people who shouldn't be you know where

705
00:36:27,920 --> 00:36:32,040
Speaker 3: my position is on transgender Yes, I'm only.

706
00:36:32,400 --> 00:36:36,239
Speaker 1: There's no reason to throw the throw one under the

707
00:36:36,239 --> 00:36:39,520
Speaker 1: bus in anyone, but there's no reason to respond.

708
00:36:39,760 --> 00:36:42,120
Speaker 3: Yeah, and there's no reason after Tuesday to change that either,

709
00:36:42,120 --> 00:36:45,120
Speaker 3: because we can do two things at once. Make affordability

710
00:36:45,120 --> 00:36:48,120
Speaker 3: a prisent but support human rights. That's one where I

711
00:36:48,160 --> 00:36:51,480
Speaker 3: think you get kind of paralyzed and decided that that

712
00:36:51,520 --> 00:36:54,360
Speaker 3: one would just slide by. And it wasn't the old

713
00:36:54,640 --> 00:36:57,640
Speaker 3: because it was a double killer because to not respond

714
00:36:57,680 --> 00:37:00,359
Speaker 3: to it, I felt like allies felt like they being

715
00:37:00,360 --> 00:37:02,360
Speaker 3: a band and that wasn't the case. Kamala Harris has

716
00:37:02,360 --> 00:37:05,720
Speaker 3: stood with them. You always would. So you've got smart

717
00:37:05,760 --> 00:37:08,360
Speaker 3: people making decisions and looking at polling and all that.

718
00:37:08,800 --> 00:37:11,120
Speaker 3: And I think my biggest thing is is that I

719
00:37:11,160 --> 00:37:13,719
Speaker 3: would loyal and I'm loyaled and will continue till the

720
00:37:13,760 --> 00:37:16,760
Speaker 3: day I died to Kamala Harris and the team made decisions.

721
00:37:16,800 --> 00:37:18,560
Speaker 3: Did we get them all right? Well, if we had,

722
00:37:18,600 --> 00:37:19,359
Speaker 3: we probably would have won.

723
00:37:19,960 --> 00:37:22,600
Speaker 1: And so I mean, I just I just think about

724
00:37:22,600 --> 00:37:24,759
Speaker 1: it so much because I think about like the sort

725
00:37:24,800 --> 00:37:28,759
Speaker 1: of successful Democrats who break through, right, the kind of

726
00:37:28,840 --> 00:37:33,280
Speaker 1: Chris Murphy's yes, or the Bernie Sanders, so it's not ideological,

727
00:37:33,480 --> 00:37:37,640
Speaker 1: or the even the governor Pritzker's right, the people. Pritzker

728
00:37:37,680 --> 00:37:40,320
Speaker 1: obviously it's a little bit different because he's got ice

729
00:37:40,600 --> 00:37:44,120
Speaker 1: attacking his city twenty seven. But like Tho, you know,

730
00:37:44,200 --> 00:37:47,280
Speaker 1: those three they're not ideological, but they all have managed

731
00:37:47,320 --> 00:37:51,040
Speaker 1: to sort of permeate the news bubble.

732
00:37:50,920 --> 00:37:54,040
Speaker 3: Where they're authentic. They're authentic, and they're in the moment.

733
00:37:54,200 --> 00:37:55,879
Speaker 3: You can feel them in the moment.

734
00:37:55,920 --> 00:37:59,359
Speaker 1: Whereas you have, like democratic leadership, it's hard to think

735
00:37:59,400 --> 00:38:02,000
Speaker 1: of a moment that Chuck Schumer has really nailed or

736
00:38:02,120 --> 00:38:04,040
Speaker 1: Hakeem And so that's my question.

737
00:38:04,040 --> 00:38:06,160
Speaker 3: The job is hard. No, you're right, and look, I

738
00:38:06,160 --> 00:38:09,520
Speaker 3: think it's a healthy exercise to talk about it. But

739
00:38:09,760 --> 00:38:12,839
Speaker 3: I also think we have seen this, that authenticity. You've

740
00:38:12,840 --> 00:38:15,280
Speaker 3: got to be disciplined enough. You talked about this, Molly,

741
00:38:15,280 --> 00:38:17,840
Speaker 3: and I told the Vice president this. I said, Look,

742
00:38:17,880 --> 00:38:21,160
Speaker 3: I think, you know, I think you'll get good stuff

743
00:38:21,160 --> 00:38:24,120
Speaker 3: out of me most of the time, and about ten

744
00:38:24,160 --> 00:38:25,959
Speaker 3: percent of the time I think it'll be really good.

745
00:38:26,640 --> 00:38:28,359
Speaker 3: And then there's going to be about ten percent that'll

746
00:38:28,400 --> 00:38:32,160
Speaker 3: be problematic. I think, you know, you talk, and I

747
00:38:32,200 --> 00:38:35,120
Speaker 3: think it's about managing risk. And I think there's a

748
00:38:35,239 --> 00:38:38,719
Speaker 3: risk averseness in these campaigns that I don't even say

749
00:38:38,719 --> 00:38:42,560
Speaker 3: that as a pejorative, but the route to take less risky,

750
00:38:42,680 --> 00:38:45,479
Speaker 3: and I think in an extrasential race like we saw

751
00:38:45,880 --> 00:38:48,160
Speaker 3: because I was convinced, I keep telling this story, Molly.

752
00:38:48,200 --> 00:38:50,239
Speaker 3: I didn't know this, but we did an off the

753
00:38:50,280 --> 00:38:53,600
Speaker 3: record stop in southern Georgia and I was on the

754
00:38:53,600 --> 00:38:57,000
Speaker 3: bus with the Vice President. We're driving down small rural

755
00:38:57,080 --> 00:38:59,560
Speaker 3: roads and there's little girls, little black girls out there

756
00:38:59,560 --> 00:39:02,319
Speaker 3: with signs, unpaigned signs that said Kamala and it you know,

757
00:39:02,360 --> 00:39:05,000
Speaker 3: I'm like, oh. And we stopped at a school. We're

758
00:39:05,040 --> 00:39:08,560
Speaker 3: in a band room and it's a Friday afternoon in

759
00:39:08,600 --> 00:39:11,480
Speaker 3: the fall. The band is playing the fight song, the

760
00:39:11,560 --> 00:39:13,720
Speaker 3: cheerleaders are in there, the football team is in there.

761
00:39:13,880 --> 00:39:15,239
Speaker 3: We're going to go in there and do a little

762
00:39:15,280 --> 00:39:17,520
Speaker 3: off the record for the cameras type of thing whenever.

763
00:39:17,560 --> 00:39:20,120
Speaker 3: And we walk in there and the first thing Kamala

764
00:39:20,120 --> 00:39:22,040
Speaker 3: Harris says is, oh, I love this room. I was

765
00:39:22,080 --> 00:39:25,120
Speaker 3: a band kid, and I'm like, you were a band kid.

766
00:39:25,160 --> 00:39:28,319
Speaker 3: American needs to know you're a band. You know what

767
00:39:28,320 --> 00:39:32,480
Speaker 3: I'm saying. There's something quintessentially about being in band in

768
00:39:32,520 --> 00:39:35,000
Speaker 3: a school, just like there is about being a football coach,

769
00:39:35,080 --> 00:39:37,520
Speaker 3: a science teacher, whatever it might be. It was such

770
00:39:37,520 --> 00:39:41,399
Speaker 3: a humanizing moment, It was so good, and I just thought, Man,

771
00:39:41,440 --> 00:39:43,960
Speaker 3: we should run with this stuff. We should do more

772
00:39:44,000 --> 00:39:46,560
Speaker 3: of this. I don't think America knew that, because you know,

773
00:39:46,760 --> 00:39:50,640
Speaker 3: that's their goal, to make us unlikable. We can't possible

774
00:39:50,680 --> 00:39:53,080
Speaker 3: this guy can't possibly be a football coach and a

775
00:39:53,120 --> 00:39:55,319
Speaker 3: soldier who grew up on a farm and knows about

776
00:39:55,360 --> 00:39:57,600
Speaker 3: agg economy. So we got to do whatever we can

777
00:39:57,680 --> 00:40:01,560
Speaker 3: to make him just so alien to us. And I

778
00:40:01,600 --> 00:40:03,920
Speaker 3: don't think the consultant class responds to that.

779
00:40:04,200 --> 00:40:06,880
Speaker 1: I didn't know that, and I covered the campaign and

780
00:40:07,000 --> 00:40:09,960
Speaker 1: interviewed her a bunch. I think that kind of carefulness

781
00:40:10,120 --> 00:40:15,040
Speaker 1: is sort of is ultimately the undoing of some of

782
00:40:15,080 --> 00:40:18,840
Speaker 1: these of some of some democratic politicians.

783
00:40:19,080 --> 00:40:21,160
Speaker 3: No, I think you're right, and I look, say what

784
00:40:21,200 --> 00:40:24,000
Speaker 3: you will, and my wife Gwyn gets this ride or whatever,

785
00:40:24,320 --> 00:40:27,560
Speaker 3: the horrificness of the character of Donald Trump, But that

786
00:40:27,680 --> 00:40:30,319
Speaker 3: whole thing of there's something in that when people say

787
00:40:30,360 --> 00:40:32,840
Speaker 3: I know it drives us all nuts if you're progressive, well,

788
00:40:32,880 --> 00:40:35,200
Speaker 3: at least Donald Trump, you know, speaks how he's feeling

789
00:40:35,239 --> 00:40:37,880
Speaker 3: or whatever. There is some truth in that he doesn't

790
00:40:37,920 --> 00:40:41,120
Speaker 3: get penalized for the horrific things he says, like you know,

791
00:40:41,640 --> 00:40:45,120
Speaker 3: you name it. There's countless ones that's viewed more as well.

792
00:40:45,120 --> 00:40:47,399
Speaker 3: At least he's authentic, and I don't feel like I'm

793
00:40:47,400 --> 00:40:49,880
Speaker 3: being sold to Bill of goods. You know. It's not

794
00:40:49,960 --> 00:40:52,600
Speaker 3: an excuse to be sloppy, but it should be an

795
00:40:52,640 --> 00:40:54,719
Speaker 3: excuse to if you get asked a question, try your

796
00:40:54,719 --> 00:40:57,160
Speaker 3: best to answer it. Yeah, your best to answer it.

797
00:40:57,239 --> 00:40:58,880
Speaker 3: Try and be there, you know. And I think we

798
00:40:58,920 --> 00:41:02,719
Speaker 3: watched this and the Republicans obviously trying to make Mayor

799
00:41:02,719 --> 00:41:05,759
Speaker 3: Elec Mandani the face of the party. But if you're

800
00:41:05,760 --> 00:41:09,040
Speaker 3: a Democrat, why are you running from other Democrats? You know,

801
00:41:09,840 --> 00:41:11,520
Speaker 3: you can disagree and say, look, I don't agree with

802
00:41:11,560 --> 00:41:13,759
Speaker 3: all of his policies, this is not something I would do,

803
00:41:14,080 --> 00:41:16,400
Speaker 3: but the people of New York should be able to vote.

804
00:41:16,440 --> 00:41:18,920
Speaker 3: And look, if you're living in Albuquerque, New Mexico, I

805
00:41:18,960 --> 00:41:21,120
Speaker 3: don't think you should be probably overly concerned who the

806
00:41:21,120 --> 00:41:23,879
Speaker 3: mayor of New York City is. And I think there's

807
00:41:23,920 --> 00:41:26,319
Speaker 3: a cautiousness. You see people like go out of their

808
00:41:26,360 --> 00:41:30,320
Speaker 3: way to like deny that these things happen.

809
00:41:30,800 --> 00:41:34,879
Speaker 1: My favorite things that you did in the campaign were

810
00:41:35,200 --> 00:41:38,640
Speaker 1: the stuff about fixing your car like this sort of no,

811
00:41:38,719 --> 00:41:41,040
Speaker 1: but seriously, like the car talk. I don't know, did

812
00:41:41,040 --> 00:41:42,319
Speaker 1: you ever listen to car talk?

813
00:41:42,840 --> 00:41:45,359
Speaker 3: What did click and clack? Yeah? Yeah, I loved it.

814
00:41:45,480 --> 00:41:47,440
Speaker 1: When I was a kid, my dad would drive me

815
00:41:47,520 --> 00:41:49,400
Speaker 1: to stuff and we listened to car talk and it

816
00:41:49,600 --> 00:41:52,600
Speaker 1: was like, you know, it was just an American thing.

817
00:41:52,840 --> 00:41:56,400
Speaker 1: And that kind of stuff I felt like was some

818
00:41:56,600 --> 00:41:59,399
Speaker 1: of the stuff and I don't, you know, I barely drive,

819
00:41:59,560 --> 00:42:02,799
Speaker 1: but the kind of stuff that I felt was very

820
00:42:02,960 --> 00:42:05,840
Speaker 1: relatable and just who you are.

821
00:42:06,160 --> 00:42:07,719
Speaker 3: Yeah. And I think the same thing would be true

822
00:42:07,760 --> 00:42:10,320
Speaker 3: of Kamala when she talked about like cooking and things.

823
00:42:10,360 --> 00:42:12,399
Speaker 3: And I think there's lessons in this, and we saw

824
00:42:12,400 --> 00:42:14,200
Speaker 3: it with these candidates. You know, to be real who

825
00:42:14,239 --> 00:42:17,440
Speaker 3: you are, don't try and be something you're not, and

826
00:42:17,480 --> 00:42:20,319
Speaker 3: then proudly stand on the things that we believe in

827
00:42:20,480 --> 00:42:22,200
Speaker 3: and and then do it for people.

828
00:42:22,360 --> 00:42:25,200
Speaker 1: And also more I mean like Donald Trump, you know

829
00:42:25,280 --> 00:42:28,440
Speaker 1: he did fall asleep at his desk yesterday or the

830
00:42:28,520 --> 00:42:31,239
Speaker 1: day before, or maybe both, but he did do like

831
00:42:31,320 --> 00:42:34,080
Speaker 1: he does do five pool sprays. He he does do

832
00:42:34,160 --> 00:42:35,880
Speaker 1: a ton of.

833
00:42:36,000 --> 00:42:38,520
Speaker 3: I couldn't agree more. No, I couldn't agree more. And

834
00:42:38,560 --> 00:42:40,839
Speaker 3: that's a lesson we learned. And I think, you know,

835
00:42:40,960 --> 00:42:46,560
Speaker 3: not seeing podcasters and you know, and influencers or wherever

836
00:42:46,600 --> 00:42:48,759
Speaker 3: you're gonna go with it, not seeing them as like

837
00:42:48,920 --> 00:42:51,200
Speaker 3: you know, this novelty thing on the side, but seeing

838
00:42:51,280 --> 00:42:54,560
Speaker 3: part of your bigger plan. And you do this and

839
00:42:54,560 --> 00:42:57,880
Speaker 3: then understand the simplicity of I gotta tell you, Molly again.

840
00:42:57,960 --> 00:43:01,760
Speaker 3: I think it was either North care Liner Georgia. Final

841
00:43:01,800 --> 00:43:04,080
Speaker 3: weeks of the campaign, I started seeing these little signs

842
00:43:04,120 --> 00:43:07,600
Speaker 3: all over the place pop up Trump good, Kamala bad,

843
00:43:08,120 --> 00:43:11,400
Speaker 3: Trump saved, Kamala crime, and it was They're good and

844
00:43:11,640 --> 00:43:13,600
Speaker 3: they were just random that had been printed and they

845
00:43:13,640 --> 00:43:16,960
Speaker 3: were all over and my first instinct would be, and

846
00:43:17,000 --> 00:43:18,560
Speaker 3: this is where you can get kind of trapped in.

847
00:43:18,600 --> 00:43:21,280
Speaker 3: This is like, h it's ridiculous. And then I started

848
00:43:21,280 --> 00:43:24,319
Speaker 3: to realize, holy crap, those things are super effective. They

849
00:43:24,320 --> 00:43:26,279
Speaker 3: are super one small piece. I don't know how much

850
00:43:26,280 --> 00:43:29,719
Speaker 3: money they spent on them, combination of things and was

851
00:43:29,760 --> 00:43:31,960
Speaker 3: there enough of us? And then you know, in no

852
00:43:32,080 --> 00:43:37,440
Speaker 3: disrespect to the large legacy media, but preparing and prepping

853
00:43:38,120 --> 00:43:40,720
Speaker 3: for an interview on CNN that probably had less viewers

854
00:43:40,760 --> 00:43:43,440
Speaker 3: than I would get on this podcast. Yeah, no, for

855
00:43:43,520 --> 00:43:44,959
Speaker 3: sure true and.

856
00:43:44,920 --> 00:43:48,239
Speaker 1: So yeah no, I mean and also like I do

857
00:43:48,360 --> 00:43:52,919
Speaker 1: think there should be more of like, especially people like you,

858
00:43:53,040 --> 00:43:56,319
Speaker 1: going on stuff like Rogan, because Joe Rogan did not

859
00:43:56,600 --> 00:43:59,680
Speaker 1: leave the Democratic Party, right, it's just that Donald Trump

860
00:43:59,680 --> 00:44:03,560
Speaker 1: made his bat you know, try desperately to get on.

861
00:44:03,760 --> 00:44:06,120
Speaker 1: I mean, it's going on there. I mean they you know.

862
00:44:06,239 --> 00:44:08,520
Speaker 3: I agree, And look, it's not about being arrogant. I mean,

863
00:44:08,520 --> 00:44:11,320
Speaker 3: it's just know this stuff whatever I find this happened

864
00:44:11,360 --> 00:44:13,759
Speaker 3: time and time again. When you're in a position like

865
00:44:13,800 --> 00:44:16,120
Speaker 3: this and when you can't meet everybody, they will caricature.

866
00:44:16,120 --> 00:44:18,160
Speaker 3: They make a caricature. Of course, their go to is

867
00:44:18,160 --> 00:44:19,960
Speaker 3: if we're in the military, they swift boat us. It

868
00:44:19,960 --> 00:44:21,759
Speaker 3: doesn't matter if it's true or not. They have this

869
00:44:21,880 --> 00:44:25,200
Speaker 3: pattern and it sinks in enough to erode faith. And

870
00:44:25,239 --> 00:44:27,759
Speaker 3: what I said is I feel very confident in this.

871
00:44:27,840 --> 00:44:30,959
Speaker 3: If people like Rogan and other people, if I meet

872
00:44:30,960 --> 00:44:33,360
Speaker 3: them and sit down and talk to them, I guarantee

873
00:44:33,360 --> 00:44:35,719
Speaker 3: you they leave saying well, I didn't expect that. Yeah,

874
00:44:35,760 --> 00:44:38,799
Speaker 3: we expect that because they've been fed a line that's

875
00:44:38,840 --> 00:44:42,240
Speaker 3: not true. Michaels is in public service and servant leadership

876
00:44:42,320 --> 00:44:45,040
Speaker 3: is to find solutions going forward. And I have worked

877
00:44:45,040 --> 00:44:46,960
Speaker 3: with Republicans and right now I know that there's some

878
00:44:47,000 --> 00:44:50,600
Speaker 3: Democrats that, oh, that guy's willing to compromise. You know,

879
00:44:51,000 --> 00:44:53,680
Speaker 3: I'm not with him. That's our problem inside our party.

880
00:44:53,680 --> 00:44:57,400
Speaker 3: We'll figure that. But the vast majority of Americans just

881
00:44:57,440 --> 00:44:59,400
Speaker 3: want effectiveness. And I think if you don't go on

882
00:44:59,480 --> 00:45:02,640
Speaker 3: those shows, you don't show them, it's easy to demonize you.

883
00:45:02,680 --> 00:45:05,480
Speaker 3: I watched, just not that long ago, Joe Rogan going

884
00:45:05,480 --> 00:45:08,279
Speaker 3: off on an AI video of me. It's some guy

885
00:45:08,320 --> 00:45:11,279
Speaker 3: wearing a you know, f Donald Trump shirt dancing down

886
00:45:11,280 --> 00:45:12,080
Speaker 3: an escalator.

887
00:45:12,440 --> 00:45:13,239
Speaker 1: Right, it's not true.

888
00:45:13,280 --> 00:45:15,080
Speaker 3: Why the hell would I ever do anything like that,

889
00:45:15,239 --> 00:45:17,280
Speaker 3: And it's pretty out of character.

890
00:45:17,800 --> 00:45:21,319
Speaker 1: You're running for reelection, I am. This will be your

891
00:45:21,360 --> 00:45:22,160
Speaker 1: third term.

892
00:45:22,280 --> 00:45:26,680
Speaker 3: Yes, tell me, well, I think the moment is it again.

893
00:45:26,760 --> 00:45:28,520
Speaker 3: I don't think that I'm the only one. I don't

894
00:45:28,840 --> 00:45:30,960
Speaker 3: can do this. I don't think that you have a

895
00:45:31,719 --> 00:45:33,759
Speaker 3: lock on these These are not your jobs. I think

896
00:45:33,800 --> 00:45:37,319
Speaker 3: here in Minnesota we're a truly purple state that I

897
00:45:37,320 --> 00:45:40,520
Speaker 3: think people don't recognize. Of all the swing states, thank goodness,

898
00:45:40,520 --> 00:45:42,919
Speaker 3: Minnesota we won, and you know that was my job

899
00:45:42,960 --> 00:45:45,279
Speaker 3: to help win the other ones. But I think right

900
00:45:45,320 --> 00:45:47,759
Speaker 3: now we've moved Minnesota in a progressive way where we're

901
00:45:47,840 --> 00:45:50,719
Speaker 3: consistently seeing now we ranked near the top of whether

902
00:45:50,719 --> 00:45:53,360
Speaker 3: it's raising a child, starting a business. We're going to

903
00:45:53,400 --> 00:45:55,839
Speaker 3: start and have the most aggressive paid family medical leave

904
00:45:55,960 --> 00:45:58,640
Speaker 3: kicks in on the first. We are protecting reproductive rights,

905
00:45:58,680 --> 00:46:02,680
Speaker 3: We're protecting our transgender children, we are innovating around healthcare,

906
00:46:02,800 --> 00:46:06,480
Speaker 3: and lots of things are in absolute opposition to Trump.

907
00:46:06,960 --> 00:46:09,680
Speaker 3: And right now, every single day, I spend my time

908
00:46:09,719 --> 00:46:11,840
Speaker 3: thinking about how we can improve the lives of Minnesota

909
00:46:11,840 --> 00:46:15,040
Speaker 3: and fighting a rearguard action about the nonsense that Trump

910
00:46:15,080 --> 00:46:17,960
Speaker 3: is bringing. And I think I have twelve years of

911
00:46:18,000 --> 00:46:21,000
Speaker 3: congressional experience, eight years as governor. I've been through everything

912
00:46:21,040 --> 00:46:24,120
Speaker 3: from the pandemic to George Floyd to seeing the national stage.

913
00:46:24,520 --> 00:46:27,239
Speaker 3: I think I'm best prepared and probably better qualified than

914
00:46:27,239 --> 00:46:29,799
Speaker 3: anybody who's ever run for governor. And I think I

915
00:46:29,840 --> 00:46:33,080
Speaker 3: can provide a bit of that firewall. But I don't

916
00:46:33,080 --> 00:46:35,200
Speaker 3: take it for granted. The people of Minnesota will speak.

917
00:46:35,280 --> 00:46:37,799
Speaker 3: I feel like right now I'm working harder than on

918
00:46:37,840 --> 00:46:41,280
Speaker 3: any campaign I've ever worked, and I feel like last

919
00:46:41,360 --> 00:46:44,160
Speaker 3: fall showed me this. If a Republican wins in Minnesota,

920
00:46:44,239 --> 00:46:46,319
Speaker 3: we will get rid of reproductive rights and we are

921
00:46:46,320 --> 00:46:50,120
Speaker 3: the beacon for the Midwest Usin Illinois, we will turn

922
00:46:50,120 --> 00:46:53,600
Speaker 3: our backs on climate change, we will demonize the most

923
00:46:53,680 --> 00:46:56,759
Speaker 3: vulnerable amongst US, and we will weaken what is America's

924
00:46:56,800 --> 00:47:00,520
Speaker 3: most progressive taxation system. And so I really feel like

925
00:47:00,560 --> 00:47:02,920
Speaker 3: protecting those things we did that I'm best positioned to

926
00:47:02,960 --> 00:47:05,160
Speaker 3: do that. We've got an open Senate seat here, and

927
00:47:05,200 --> 00:47:06,640
Speaker 3: I think you know how these things work in a

928
00:47:06,680 --> 00:47:09,120
Speaker 3: state the size of Minnesota, having an open Senate and

929
00:47:09,120 --> 00:47:11,400
Speaker 3: an open governor massively expensive.

930
00:47:11,760 --> 00:47:13,719
Speaker 1: Yes, thank you, Governor Wall.

931
00:47:14,160 --> 00:47:15,880
Speaker 3: We'll get back again. You're the best.

932
00:47:16,160 --> 00:47:22,440
Speaker 1: You're the best. Thank you, Thank you, No no moment second.

933
00:47:23,640 --> 00:47:28,520
Speaker 2: Jesse Cannon, my Trumpism often has talked about us saying

934
00:47:28,560 --> 00:47:32,640
Speaker 2: the quiet part out loud constantly. Steve Betta just going

935
00:47:32,640 --> 00:47:34,560
Speaker 2: for new heights, like, you know, like the guy's not

936
00:47:34,640 --> 00:47:38,440
Speaker 2: in the best shape, but he's jumping Olympic levels high

937
00:47:38,680 --> 00:47:40,000
Speaker 2: of telling on themselves.

938
00:47:40,320 --> 00:47:44,200
Speaker 1: Yeah, you know, so when I saw this video. It

939
00:47:44,320 --> 00:47:46,799
Speaker 1: was like, you know how it is now You're like,

940
00:47:46,840 --> 00:47:50,399
Speaker 1: this is probably AI and then you're like, oh, no, no,

941
00:47:50,480 --> 00:47:53,919
Speaker 1: it's not. This is a quote. I tell you right

942
00:47:54,400 --> 00:47:58,400
Speaker 1: as God as my witness. If we lose the midterms

943
00:47:58,520 --> 00:48:02,399
Speaker 1: and we lose twenty twenty, some in this room are

944
00:48:02,560 --> 00:48:07,320
Speaker 1: going to prison, Bannon told the crowd at the awards

945
00:48:07,360 --> 00:48:10,680
Speaker 1: event hosted by the Conservative Partnership Academy. I think he

946
00:48:10,760 --> 00:48:14,960
Speaker 1: then added, didn't he add I am two or no?

947
00:48:15,200 --> 00:48:16,120
Speaker 1: I guess he didn't.

948
00:48:16,280 --> 00:48:18,160
Speaker 2: I think that that was implied by some in this

949
00:48:18,239 --> 00:48:20,480
Speaker 2: room because if we remember, he did the build the

950
00:48:20,520 --> 00:48:23,000
Speaker 2: wall thing, and he narrowly.

951
00:48:22,640 --> 00:48:24,400
Speaker 1: Evaded he went to prison.

952
00:48:24,840 --> 00:48:26,920
Speaker 2: He did go to prison. Actually that was for the

953
00:48:26,960 --> 00:48:30,000
Speaker 2: contempt around the other thing as well. You know, there's

954
00:48:30,040 --> 00:48:32,520
Speaker 2: still hell to pay with many of his deeds.

955
00:48:32,760 --> 00:48:34,040
Speaker 1: Yes, no question.

956
00:48:34,719 --> 00:48:36,239
Speaker 2: You know, for people like you and me, this is

957
00:48:36,239 --> 00:48:39,080
Speaker 2: a real get out the vote operation. Bring Ben into jail.

958
00:48:39,520 --> 00:48:43,279
Speaker 1: Yeah, correct, that is true. It is a get out

959
00:48:43,280 --> 00:48:45,200
Speaker 1: of the vote. I also think, like the fact that

960
00:48:45,239 --> 00:48:48,959
Speaker 1: they're saying this now shows there's just a lot of anxiety.

961
00:48:49,480 --> 00:48:51,400
Speaker 1: I think they're going to do a lot of crazy

962
00:48:51,400 --> 00:48:54,920
Speaker 1: stuff to try and make it hard for people to vote.

963
00:48:55,000 --> 00:48:58,160
Speaker 1: I think that seems like it's clearly on the horizon,

964
00:48:58,440 --> 00:49:02,439
Speaker 1: so certainly worrying, certainly something to keep watching out for,

965
00:49:02,640 --> 00:49:07,200
Speaker 1: and certainly the Steve Bannon we know, delivering the hits

966
00:49:07,560 --> 00:49:08,680
Speaker 1: as only he can.

967
00:49:08,920 --> 00:49:11,640
Speaker 2: Oh, when you talk that many hours on air all day,

968
00:49:12,120 --> 00:49:13,840
Speaker 2: you're gonna say some real dumb things.

969
00:49:14,040 --> 00:49:21,000
Speaker 1: Thad for yourself. That's it for this episode of Fast Politics.

970
00:49:21,480 --> 00:49:27,200
Speaker 1: Tune in every Monday, Wednesday, Thursday and Saturday to hear

971
00:49:27,480 --> 00:49:31,799
Speaker 1: the best minds and politics make sense of all this chaos.

972
00:49:32,120 --> 00:49:34,960
Speaker 1: If you enjoy this podcast, please send it to a

973
00:49:35,040 --> 00:49:39,000
Speaker 1: friend and keep the conversation going. Thanks for listening.