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Speaker 1: Ladies and gentlemen, Welcome back to a numbers game with

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Speaker 1: Ryan or Dusky. Thank you guys for being here. I

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Speaker 1: had an insane weekend that I want to tell you

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Speaker 1: about before I get into the topic at hand. So,

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Speaker 1: first of all, very important. I don't really talk about

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Speaker 1: this very often, but I held I hosted company over

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Speaker 1: the weekend, made my grandmother's homemade meatballs and sauce, and

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Speaker 1: let me tell you it was a home run. More importantly,

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Speaker 1: I had to go to DC to just go for

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Speaker 1: a work meeting. It was a quick twenty four hour

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Speaker 1: turnaround trip. I get there late one night and I said, oh,

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Speaker 1: let me go meet with somebody, just have dinner with somebody.

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Speaker 1: So my reach out to my friend is a very

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Speaker 1: well known report and he said, come to Cafe Milano.

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Speaker 1: This is a very she she restaurant, very expensive, a

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Speaker 1: place that people want to be seen at, right because

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Speaker 1: it's a lot of connections and people in the DC scene.

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Speaker 1: So upon entering, I immediately see three US senators with

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Speaker 1: a very well known DC military contractor. So I, you know,

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Speaker 1: I spot that out of the corner of my eye.

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Speaker 1: I roll my eyes and I just keep walking. Well,

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Speaker 1: we get to the table where my friends at and

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Speaker 1: he has some friends British friends who are reporters and

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Speaker 1: politicians at the table as well. And most Americans that

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Speaker 1: means nothing to them, But for me, because I followed

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Speaker 1: British politics so frequently, I knew exactly who was sitting

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Speaker 1: with us. So it was a former member of the

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Speaker 1: British Conservative Party, a very very prominent member of the

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Speaker 1: British Conservative Party. This was a man who was in

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Speaker 1: charge of all the vaccinations during COVID. This was he

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Speaker 1: ran for Prime Minister and lost to Liz Trust. Most Americans,

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Speaker 1: but I would not that would not register at all.

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Speaker 1: I immediately knew. I only not only knew who he was,

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Speaker 1: I knew his record and he was kind of for

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Speaker 1: an American. He's way too big government for American. I

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Speaker 1: guess in Britain he wouldn't be considered very conservative anyway. Anyway,

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Speaker 1: So we started talking and rich of chatting about, you know,

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Speaker 1: the state of England, the state of American politics, or

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Speaker 1: are Nigel Faraj and Reform UK And he has since

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Speaker 1: left the British Conservative Party to run to work to

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Speaker 1: be a part of Reform UK. And someone at the

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Speaker 1: table asked him, are you going to run for office again?

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Speaker 1: And he said he's being considered, he's considering doing it.

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Speaker 1: He's considered running for office again. And you know, people

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Speaker 1: always accuse me of being abrasive and or putting on

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Speaker 1: a show that I'm abrasive. I am the same way morning,

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Speaker 1: noon and night, whether you see me, whether you don't.

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Speaker 1: I mean, it's it's always the same personality. So I

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Speaker 1: kind of I couldn't hold my tongue back. I just

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Speaker 1: said to him respectfully, sir, your party was in the

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Speaker 1: majority for a decade in the UK and you did

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Speaker 1: virtually nothing, Like you left the country off way worse

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Speaker 1: than when you found it. And why Like what did

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Speaker 1: you learn differently this time than last time? Like why

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Speaker 1: are you going to what else could you possibly you know,

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Speaker 1: wreck if you get elected again? And he said some

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Speaker 1: interesting things, especially about energy policy. The UK is a

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Speaker 1: horrendous energy policy they him at zero, which is doing

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Speaker 1: terrible things for their economy. And I identifies particularly like

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Speaker 1: the Tories, the Conservative Party should have made their identity

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Speaker 1: about wiping away former Prime Minister Tony Blair's record. Tony

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Speaker 1: Blair is the one who kicked open the floodgates of

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Speaker 1: Third World mass immigration to England. Tony Blair pushed forward

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Speaker 1: on a zero. Him and his successor, Tony Blair had

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Speaker 1: the Equality Act, which put all these policemen at risk

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Speaker 1: of losing their jobs if they were accused of racism

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Speaker 1: when the grooming gangs were happening. I mean, Tony Blair

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Speaker 1: was a horrendous Prime Minister to the UK and the

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Speaker 1: same way that Trump's a lot of Trump. What Trump

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Speaker 1: does is to erase the Obama legacy. The Tories should

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Speaker 1: have been very, very complicit in erasing Blair's legacy, and

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Speaker 1: they kind of went along with the continuing a lot

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Speaker 1: of Blair's legacy. It was crazy. So after pushing back,

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Speaker 1: I just I try to make everything nice. I said,

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Speaker 1: what is some interesting things that you were remember from

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Speaker 1: your time there being such a senior ranking member of

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Speaker 1: the ruling party. And he said that they're saying in

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Speaker 1: the UK called Cobra. Now I had heard of it before,

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Speaker 1: what my the other guest did it? Cobra is like

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Speaker 1: the secret government meeting of top notch people when there

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Speaker 1: was a national crisis going on. It's like it would

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Speaker 1: be like going to It's not the same thing as

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Speaker 1: Camp David, but or the situation maybe like going to

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Speaker 1: the situation. It was called COBRA in the UK. It's

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Speaker 1: not the health insurance alternative policy. It's called COBRA anyway,

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Speaker 1: that's also cl cobra, this American cobra the back of

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Speaker 1: the story. So I said, what was What are some

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Speaker 1: things like that you can share that were two like

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Speaker 1: crazy moments during Cobra and he said one was the

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Speaker 1: vote to shut down the government because he said that

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Speaker 1: he wasn't for it. Knowing what he said, I don't.

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Speaker 1: I don't believe that. I think he was probably very

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Speaker 1: far or shutting on the government, but he said it.

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Speaker 1: The weirdest thing is the COBRA meeting was in London,

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Speaker 1: so it's a huge city. It's millions and millions of people.

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Speaker 1: So he would like, they agree we're going to shut

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Speaker 1: the government down. And then he walked down to the

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Speaker 1: street to as he called it, humanity. There's thousands of

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Speaker 1: people walking past them, and he goes the whole time,

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Speaker 1: I'm thinking, you have no idea what we've just decided,

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Speaker 1: Like we're going everyone's on lockdown like in twenty four hours,

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Speaker 1: and you're old just going this is the last moments

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Speaker 1: you have to go about your business the way that

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Speaker 1: you've been doing your entire lives. That was kind of

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Speaker 1: fascinating from a psychologically. He wasn't taking glean it, by

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Speaker 1: the way, he wasn't sounding like a sociopath. He was

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Speaker 1: treating like this is insane. And then the second thing,

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Speaker 1: this is crazy. Because I had not even heard of

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Speaker 1: this and I follow the news pretty closely, he said

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Speaker 1: that they got a cobra call. Because this is several

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Speaker 1: years ago. Putin was going to test a nuclear missile

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Speaker 1: in the Black Sea, which is the of you know,

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Speaker 1: water barrier between Russia and Ukraine and Turkey and all

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Speaker 1: these other and a lot of the Balkan nations, and

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Speaker 1: he was going to test. Yeah, he was going to

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Speaker 1: test the a nuclear bomb. And I said, what did

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Speaker 1: you do, Like, what do you do when you hear

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Speaker 1: that Putin had a test nuclear bomb? He said, We

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Speaker 1: immediately started trying to call China to ask China to

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Speaker 1: turn talk him out of it. And we were trying

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Speaker 1: to figure out every other world leader with a close

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Speaker 1: relationship with Putin to turn to make him change his mind.

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Speaker 1: Anyway he did. He changed his mind in the end,

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Speaker 1: but it was a fascinating story. It really had me

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Speaker 1: kind of gripped to the enter my seat. Ah wait,

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Speaker 1: that was that's the whole story, that was the whole weekend.

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Speaker 1: But that was the weekend trip. But it was thought

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Speaker 1: it was great. That was really an interesting copy that

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Speaker 1: you guys would really like. Okay, So over the last week,

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Speaker 1: something else completely different aside from my trip and the

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Speaker 1: dinners I cooked were that came out and it's around

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Speaker 1: the topic of AI, which you guys, I have not

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Speaker 1: had like an autistic spas I'm talking about AI in

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Speaker 1: quite some time, so give me some credit. But we're

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Speaker 1: going to talk about it now because it involves both

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Speaker 1: politics and policy and polling, all my favorite sobject mantics

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Speaker 1: are put into one. So let's talk about specifically the

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Speaker 1: holding First, David Shore, who's a very very intelligent democratic polster.

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Speaker 1: I'm a big fan. I've invited on this podcast many times.

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Speaker 1: He has not since come. I don't think he's going

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Speaker 1: to come because I think a lot of progressive I've

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Speaker 1: had a lot of good progressives on the show, but

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Speaker 1: a lot of them are afraid that they're going to

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Speaker 1: have be attacked by the liberal mob. If they come

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Speaker 1: on and talk with me. I don't know. I am

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Speaker 1: assuming that I was never been told. I actually was

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Speaker 1: told that by one person, But I'm assuming that's the

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Speaker 1: truth for everyone who doesn't agree to come. Who is

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Speaker 1: a progressive that I that I think is smart. But

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Speaker 1: David Short is a very smart progressive and he had

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Speaker 1: a data about AI that I think you all need

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Speaker 1: to hear. So here's what he found in his data.

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Speaker 1: No issue has increased in importance to average voters than AI.

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Speaker 1: No other issue not. Think of everything that's come in

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Speaker 1: the last year, right, the only other issue that even

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Speaker 1: comes close to how much people I've taken interest in

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Speaker 1: the I is war in the Middle East. Put that

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Speaker 1: into perspective, how much which coverage has war and conflict

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Speaker 1: in the Middle East received in mainstream media, in alternative media,

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Speaker 1: in social media, and versus AI. It's I believe if

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Speaker 1: you studied at you know, dollar for dollar, it's probably

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Speaker 1: one side for warthy Ran and war in the Middle East. Nonetheless,

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Speaker 1: people care about more AI, more than they care about

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Speaker 1: any other issue, including war. Secondly, AI is hitting at

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Speaker 1: a time where most Americans are increasingly saying life is unaffordable.

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Speaker 1: Only nine percent of Americans say that life is getting

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Speaker 1: more affordable. Sixty one percent say life is more unaffordable.

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Speaker 1: Only twenty five percent of voters say they feel confident

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Speaker 1: in their financial future. That is not big, especially when

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Speaker 1: you consider how much of the population is wealthy, retired,

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Speaker 1: or on you know, benefits of some sort where they're

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Speaker 1: not where the government is financing a lot of their life.

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Speaker 1: That's a huge part of the electorate, a huge, huge part,

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Speaker 1: and still only twenty five percent feel good in their

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Speaker 1: financial future. Third, a majority of voters fifty six percent

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Speaker 1: are worried about their job security, and seventy nine percent

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Speaker 1: are concerned the government doesn't have a plan to protect

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Speaker 1: workers from AI job loss. Seventy seven percent are concerned

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Speaker 1: that industries are going to be eliminated, and seventy nine

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Speaker 1: percent are worried there will be fewer opportunities for young people.

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Speaker 1: Those are those eighty twenty issues. That is like a

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Speaker 1: pole question asking should a known rapist with a penis

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Speaker 1: be allowed to shower next to a nine year old

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Speaker 1: girl in a public bathroom? And if he declares that

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Speaker 1: he is a woman like that's that lopsided, right. I

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Speaker 1: want you to put this into perspective. This is not

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Speaker 1: an issue where there's a lot of gray nuance. People

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Speaker 1: have serious opinions that are extremely one way. It is

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Speaker 1: like the transgender issue. It is one way, and it

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Speaker 1: is going towards that way. It is increasingly moving towards

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Speaker 1: that way. We're going to have a transgender episode next episode,

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Speaker 1: by the way, but another transgender episode. But anyway, this

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Speaker 1: is where it's going. It's a moving in one direction. Fourth,

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Speaker 1: voters do not trust the notion that everything is going

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Speaker 1: to be fine. When told that AI will create economic

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Speaker 1: productivity that benefits everyone, fifty six percent of voters don't

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Speaker 1: trust that statement. Thirty six percent say they trust it

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Speaker 1: somewhat to a lot. Voters also do not trust the

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Speaker 1: idea that AI will not cause widespread job loss twenty

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Speaker 1: six Only twenty six percent of voters believe that AI

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Speaker 1: will not cause widespread job loss. Sixty seven percent do

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Speaker 1: not trust people who say that. When I asked, what

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Speaker 1: is the more important funding the creation of new jobs

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Speaker 1: and basic benefits like healthcare, even if it even if

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Speaker 1: it means limiting the amount that American tech companies can

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Speaker 1: profit from AI or keep innovation so the American outcompetes

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Speaker 1: the rest of the world and developing AI even if

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Speaker 1: it allows tech companies to profit from eliminating jobs. By

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Speaker 1: the way, David Shore, who made that question a little biased,

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Speaker 1: a little bias of a question anyway, obviously they cared

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Speaker 1: more about protecting jobs than innovation. Next question, and while

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Speaker 1: I want you to hear this, I want you to

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Speaker 1: if you hear nothing else from this entire podcast, listen

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Speaker 1: to the next two points. I have said over and

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Speaker 1: over and over again. AI is how Democrats are going

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Speaker 1: to put socialism in this country. Roucana was on this

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Speaker 1: podcast and basically said it. It's his plan for the

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Speaker 1: New Deal, massive redistribution of wealth, even at mass unemployment levels.

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Speaker 1: When ask if people would rather have a job or

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Speaker 1: direct handouts, like Rocanna said, fifty four percent said they

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Speaker 1: would rather have a job and rather have the government

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Speaker 1: ensure they have a job. Only seventeen percent want direct

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Speaker 1: handouts fifteen percent. Only fifteen percent are libertarians who say

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Speaker 1: we don't want the government to do anything. Fifty five

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Speaker 1: percent want to make sure tech companies cannot make unlimited profits.

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Speaker 1: They include a plurality of Trump voters. Listen to me

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Speaker 1: and listen to me carefully with what I just said.

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Speaker 1: More Trump voters believe tech companies should be held financially

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Speaker 1: responsible for the jobs they destroy through AI that AI eliminates,

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Speaker 1: then believes they should be able to profit off of it.

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Speaker 1: This is not a small thing. This is not a oh,

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Speaker 1: maybe there's some gray area, maybe we're gonna maybe no.

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Speaker 1: Remember I had on I had on the Polster a

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Speaker 1: couple weeks ago who said that he was shocked by

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Speaker 1: how politic has become a circle that very far right

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Speaker 1: wing people are believing in very far left wing things,

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Speaker 1: and we're not a linear political belief anymore. This is

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Speaker 1: a perfect example when nearly fifty percent of Trump voters

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Speaker 1: are saying tech companies should not make unlimited profits. We

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Speaker 1: need to regulate them. It is not a question of

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Speaker 1: if those regulations are going to come, It is a

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Speaker 1: question of when and to the severity. You need a

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Speaker 1: very smart politician to make sure you do not destroy

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Speaker 1: the entire system. Or they just vote for someone who

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Speaker 1: will throw a you know, a Molotov cocktails. They will

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Speaker 1: vote for a Trump of the left, they will vote

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Speaker 1: for an AOC type. I'm not joking when I say this.

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Speaker 1: It is a very sincere point I am making right now.

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Speaker 1: It's not a question of if, it's a question of when.

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Speaker 1: Last two points on this poll. And while voters prefer

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Speaker 1: a tax that specifically taxes companies on AI, they like

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Speaker 1: that more than like the idea of a wealth tax.

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Speaker 1: Remember the California wealth tax. They're taxing billionaires on These

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Speaker 1: billionaires are fleeing. Only twenty seven percent of voters want

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Speaker 1: a wealth tax because overall we are a capitalist nation.

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Speaker 1: But forty nine percent want an AI tax. And if

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Speaker 1: you don't do one, Republicans, listen, if you don't do one,

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Speaker 1: you will end up with the other. I'm making it

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Speaker 1: perfectly crystal clear. If you don't push for some kind

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Speaker 1: of AI tax or movement, you will end up with

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Speaker 1: a wealth tax. Lastly, AI specific populism outperforms all other

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Speaker 1: conversations around economic populism and AI when it comes to

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Speaker 1: support helping Democrats win elections. It moves the need into

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Speaker 1: the needle, the electric needle. An average four percent towards Democrats.

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Speaker 1: Do you understand what that means? It means you go

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Speaker 1: from a Trump twenty twenty four election to an Obama

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Speaker 1: twenty twelve style election. If just the AI populism point

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Speaker 1: is hit on. Now, obviously there's other issues. There's transgender issues,

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Speaker 1: there's immigration, there's a lot of things Democrats believe that

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Speaker 1: are nutty and batty and crazy. You put the unemployment

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Speaker 1: level at ten to twenty percent because of all the

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Speaker 1: AI regulations and AI innovations, rather we are in a

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Speaker 1: different world. Then. Now this all comes as two things

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Speaker 1: are happening. There are two competing Republican rollouts when it

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Speaker 1: comes to AI regulations. The first is from the White House.

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Speaker 1: It is a four page memo on the AI framework policy.

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Speaker 1: It is pretty straightforward. It's only four pages. If you

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Speaker 1: want to go read it, it's pretty simple. I'll go

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Speaker 1: through a few few points because it is it's a

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Speaker 1: lot to read. But basically, the first point is about

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Speaker 1: protecting kids. It says congression empower parents and guardians with

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Speaker 1: robust tools to manage their child privacy settings, screen times,

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Speaker 1: content exposure, and account account controls a meaning it's on

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Speaker 1: the parents. They're going to do the same thing they

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Speaker 1: do for YouTube and all the other stuff that has

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Speaker 1: gone forward for a lot of these social media websites.

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Speaker 1: But it's all on the parents. It's not to the

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Speaker 1: AI companies. Congressould establish commercially reasonable privacy, protective and age

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Speaker 1: assurance requirements for the AI platform sets on the AI companies.

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Speaker 1: Congress require AI platforms and services likely to be accessed

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Speaker 1: by miners to implement features that reduce the risk of

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Speaker 1: sexual exploitation and self harm to minors. Congress should affirm

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Speaker 1: that the existing child privacy policies apply to the AI systems,

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Speaker 1: including limits on data collection for model training and targeted advertising.

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Speaker 1: All of the most regulatory or regulatory language around AI

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Speaker 1: came from the child section about protecting kids, where I

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Speaker 1: think you're going to get the most of bipartisan support.

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Speaker 1: And also that taxpayers should not be increased, should not

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Speaker 1: feel increase electricity costs from data centers, streamline Federal permits

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Speaker 1: are on AIAI infrastructure. That's a boom for the I industry.

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Speaker 1: Grants for small businesses so they could develop AI in

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Speaker 1: their businesses, once again boom for the I industry. More

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Speaker 1: antitrust liabilities for AI that means that you can't just

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Speaker 1: steal people's content. More protections on copyright allow for collective rights,

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Speaker 1: and licensing framework prevent government from forcing AI companies to

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Speaker 1: comply with ideological standards. That's the whole free speech stuff.

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Speaker 1: And when the next Democrat comes in, Congress should not

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Speaker 1: create any new federal rulemaking body that regulates AI once

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Speaker 1: again big one for the I industry, and should instead

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Speaker 1: support a development and deployment of sector specific AI applications

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Speaker 1: through existing regulatory bodies with a subject matter expertise and

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Speaker 1: thorough industry standard level lad standards, expand efforts to study

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Speaker 1: trends with job losses. What a stupid freaking part of

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Speaker 1: the bill, and develop AI AI Youth Development program also incredible,

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Speaker 1: police stupid. Also, we're gonna have an education episode about

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Speaker 1: what we're discovered with AI and education. It's gonna make

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Speaker 1: your jars drop. But okay, but mostly the AI companies

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Speaker 1: win big time because what this outlines on the build.

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Speaker 1: What an outline does is it says to the states,

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Speaker 1: it gives them. It gives a little bit around child protection,

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Speaker 1: a little bit around copyright protection guidelines for Congress. But

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Speaker 1: what it mainly says is Congress should preempt state AI

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Speaker 1: laws that impose undue burdens to ensure a minimally burdened

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Speaker 1: some national standards consistent with the With these recommendations, not

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Speaker 1: fifty discordant ones. This national standard should respect key principles

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Speaker 1: of federalisms and not pre in a traditional police powers

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Speaker 1: retained by the states to enforce laws of general applicability

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Speaker 1: against AI developers and users, state zoning laws, requirements of

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Speaker 1: governors to state the one's own use of AI, whether

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Speaker 1: it be procurement or services. Preemption must also ensure that

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Speaker 1: state laws do not govern areas better student for the

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Speaker 1: federal government. States should not be permitted to regular AI

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Speaker 1: development because it is inherently an interstate phenomenon. States should

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Speaker 1: not unduly burden American's use of AI for activity that

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Speaker 1: would be lawful if performed without AI. State should not

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Speaker 1: be permitted to penalize AI developers for third parties unlawful conduct,

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Speaker 1: including involving their models. I e. What that means is

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Speaker 1: someone using AI to harm you. AI company is not.

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Speaker 1: They're not responsible to huge win for the AI companies.

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Speaker 1: Huge win. It is. It's as if somebody that the

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Speaker 1: whole outlines of as if somebody just woke up one

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Speaker 1: day from the White House and said, guys, we're doing

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Speaker 1: the bare minimum today. That's what it is. It's the

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Speaker 1: bare minimum. I mean the voters are going to respond

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Speaker 1: positively to the child protection stuff that put you know,

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Speaker 1: respond respond positively towards issues around copyright and licensing. What

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Speaker 1: they will not respond positively too, because we know how

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Speaker 1: slow Congress moves as all other regulation only can go

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Speaker 1: through Congress when they're giving so limited regulations in this bill.

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Speaker 1: I mean, there's not a lot there. This doesn't have

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Speaker 1: a ton of teeth, and it's more protections for AI

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Speaker 1: industry than it is regulations to protect citizens and protect

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Speaker 1: workers is not in there at all now. Senator Marsha

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Speaker 1: Blackburn of Tennessee, Republican of Tennessee also issued her own

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Speaker 1: bill around AI regulation. Unlike the four pages from the

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Speaker 1: White House, this bill was two hundred and ninety one

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Speaker 1: pages long. I'm not going to retime I read it.

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Speaker 1: I did not read it, but it covers a series

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Speaker 1: of AI regulations that are overwhelmingly popular voters and absolutely

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Speaker 1: encroaches on AI companies ability to make endless profits while

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Speaker 1: displacing American workers. That is why the AI tech people,

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Speaker 1: the minute the bill came out, started screaming how horrible

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Speaker 1: it was. And you could already see by the way

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Speaker 1: the White House has reached out to all their influencers

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Speaker 1: to talk about how amazing their framework is. The people

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Speaker 1: who don't have a high school diploma screaming how great

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Speaker 1: they know, they know every AI regulation at this point.

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Speaker 1: It's amazing. It's the Marshall Blackburn bill is obviously an

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Speaker 1: open opening, you know, offer. It's not a perfect bill.

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Speaker 1: It will go through many, many different cycles, but it

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Speaker 1: is there. It is something. It is also baffling to

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Speaker 1: my mind how the White House is doing this now

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Speaker 1: in March, knowing how few dates are available left for

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Speaker 1: this Congress to even offer an AI bill, knowing that

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Speaker 1: parts of the billbard is so unpopular ahead of the midterms.

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Speaker 1: This makes no sense. What's so? I mean? I cannot

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Speaker 1: even get into the whole political standings of this entire thing.

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Speaker 1: Tone deafness must be clinical to a lot of this

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Speaker 1: White House. Tone deafness must be completely clinical. It must

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Speaker 1: be I don't know, contagious. I have no idea. Something

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Speaker 1: is going on where they are not reading the room

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Speaker 1: and they're only hearing influencers who want to be invited

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Speaker 1: to the right parties and people in the business sector

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Speaker 1: who want some profits, because that's all it seems to be,

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Speaker 1: and everyone else is getting scraps. I can't describe it

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Speaker 1: any other way. I think this is insane. I just

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Speaker 1: think this is completely insane. While all this is going on,

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Speaker 1: there's a primary in Chicago where AI and Crypto and

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Speaker 1: the American is rarely political action committee all we're working

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Speaker 1: to have their own candidates went. Thirty two million dollars

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Speaker 1: was spent on four house races in Illinois. Staggering amounts

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Speaker 1: of monies, larger than all the campaigns themselves. Is the

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Speaker 1: outside money that these companies, especially AI, are now putting

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Speaker 1: to get their chosen person elected to Congress that will

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Speaker 1: play ball with them on the issues. And they're not

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Speaker 1: even running on the AI issue. It's very complicated, but

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Speaker 1: it's very interesting. Stay tuned for my interview with David Weigel,

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Speaker 1: national reporter who covered this that's coming up next with

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Speaker 1: me on today's episode is David Weigel, the national political

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Speaker 1: reporter for Semaphore. David, thanks for coming on this podcast.

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Speaker 1: It's great to be here. Thanks for having me so. David.

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Speaker 1: You covered the Illinois elections. As I said in my monologue,

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Speaker 1: this was an incredibly expensive series of house primaries, over

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Speaker 1: thirty two million dollars. Spent by just a few groups,

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Speaker 1: and that's something including the progressive interests who were the

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Speaker 1: biggest winners of this election cycle.

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Speaker 2: The absolute biggest winner in Illinois was Governor Britzker.

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Speaker 1: So Governor J. B.

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Speaker 2: Pritzker, I think famously is a billionaire, is able to

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Speaker 2: fund whatever campaign he wants. He did this when we

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Speaker 2: first ran for governor. He's done it in the subsequent

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Speaker 2: Gay Pains. He's show hold money to state parties where

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Speaker 2: he might run he might want to favor later if

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Speaker 2: he runs for president. He basically helped elect Juliana's or

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Speaker 2: nominate his Giliana Stratt, his lieutenant governor. The sense I

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Speaker 2: got there from covering that campaign is that it was

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Speaker 2: Roger Christian Murphy, the congressman who had spent forty million dollars,

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Speaker 2: much more than ever been spent to win that seat

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Speaker 2: in Illinois, the US the US Senate seat, US Senate

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Speaker 2: seat to replace Tick Turpin.

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Speaker 1: He had the advantage that fritz gre were.

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Speaker 2: Deciding to put millions of dollars into superpack for Stratton.

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Speaker 1: That that changed that race.

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Speaker 2: He down the ballot, he helped helped let people that

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Speaker 2: he wanted. I think he had a one hundred percent record.

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Speaker 2: Now he wasn't as involved in the House races, and

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Speaker 2: so that was a nice messy story. There was not

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Speaker 2: one particular store narrative from the election. What you saw

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Speaker 2: instead was groups that had played in it come out

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Speaker 2: quickly to declare victory. APEX was the most the most

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Speaker 2: vocal saying we had a great election night. It was

432
00:24:49,119 --> 00:24:51,080
Speaker 2: not that great of election night. Was better than They

433
00:24:51,359 --> 00:24:54,840
Speaker 2: started the year in New Jersey with a debacle where

434
00:24:54,880 --> 00:24:57,680
Speaker 2: APAX spent millions of dollars to beat Tom Malinowski ended

435
00:24:57,760 --> 00:24:58,880
Speaker 2: up with a more left wing.

436
00:24:59,800 --> 00:25:02,440
Speaker 1: Let's yeah, look, okay, sure, sorry to go too fast

437
00:25:02,480 --> 00:25:04,520
Speaker 1: because no, no, no, no, I want to I want to

438
00:25:04,520 --> 00:25:07,240
Speaker 1: set the stage. That is true. Yeah, So the biggest

439
00:25:07,280 --> 00:25:09,680
Speaker 1: winner is the Governor Pritzker, who's likely running for president

440
00:25:09,760 --> 00:25:12,360
Speaker 1: or at least floating on yes. A pack, the American

441
00:25:12,440 --> 00:25:15,320
Speaker 1: Israeli Political Action Committee, they are the pro Israel pack,

442
00:25:15,840 --> 00:25:18,840
Speaker 1: as you said in New Jersey earlier this year, really

443
00:25:18,960 --> 00:25:22,720
Speaker 1: campaigned against Tom Olanowski, the former congressman, to defeat him,

444
00:25:23,040 --> 00:25:26,200
Speaker 1: ended up with a further laugh wing anti Israel candidate. Now,

445
00:25:26,240 --> 00:25:28,320
Speaker 1: they invested in how many seats in this election in

446
00:25:28,320 --> 00:25:31,000
Speaker 1: Illinois went to how they come out in four.

447
00:25:31,359 --> 00:25:34,120
Speaker 2: They won two. They lost to the one that they

448
00:25:34,240 --> 00:25:38,520
Speaker 2: had the biggest victory in uh In outside Chicago and

449
00:25:38,560 --> 00:25:41,560
Speaker 2: the suburbs that that's where Jesse Jackson Junior lost. They

450
00:25:41,600 --> 00:25:44,119
Speaker 2: were helped by Jesse Jackson Junior being pretty toxic to

451
00:25:44,160 --> 00:25:46,320
Speaker 2: all but his base of voters. The other one they

452
00:25:46,359 --> 00:25:51,400
Speaker 2: won Northwest suburbs of Chicago, like Schomberg places like that.

453
00:25:52,280 --> 00:25:55,080
Speaker 2: They were pulling in the same direction as Fair Shake

454
00:25:55,200 --> 00:25:57,439
Speaker 2: and the AI packs that are new to this cycle

455
00:25:57,440 --> 00:25:59,879
Speaker 2: that also had a pretty mixed night. So APA w

456
00:26:00,119 --> 00:26:06,040
Speaker 2: two races. It declared victory overall, and I'm not critical.

457
00:26:06,080 --> 00:26:09,080
Speaker 2: Since the election, which is pointing out factually, as it

458
00:26:09,160 --> 00:26:11,760
Speaker 2: was clear that they were not going to run the table,

459
00:26:12,160 --> 00:26:15,199
Speaker 2: APEX public spin started to be, well, we want to

460
00:26:15,240 --> 00:26:18,640
Speaker 2: keep these potential squad members out of Congress, and so

461
00:26:18,680 --> 00:26:23,040
Speaker 2: we're going to keep Katuba Gazella busher A Miwala who

462
00:26:23,119 --> 00:26:26,359
Speaker 2: was running in the ninth district is Evanston, Illinois and

463
00:26:26,359 --> 00:26:29,600
Speaker 2: part of Chicago. Frankly, I went to Northwestern and I

464
00:26:29,600 --> 00:26:32,399
Speaker 2: lived in Evanston. It's really the district where people are there.

465
00:26:32,960 --> 00:26:35,880
Speaker 2: They go to school. They usually live in Wrigleyville. When

466
00:26:35,920 --> 00:26:38,280
Speaker 2: they graduate, uh, and maybe they get a kid and

467
00:26:38,320 --> 00:26:41,480
Speaker 2: move to the suburbs. That very very district I know

468
00:26:41,520 --> 00:26:45,760
Speaker 2: a lot about. They wanted Dan Biss to lose, the

469
00:26:45,760 --> 00:26:49,560
Speaker 2: mayor of Evanston, who is a what he called when

470
00:26:49,600 --> 00:26:52,960
Speaker 2: I talked to him, a progressive Zionist. Israel should exist,

471
00:26:53,040 --> 00:26:55,480
Speaker 2: but we should stop funding them militarily.

472
00:26:55,880 --> 00:26:56,800
Speaker 1: They wanted to beat him.

473
00:26:56,840 --> 00:26:59,120
Speaker 2: They got behind Laura find who's a state senator who's

474
00:26:59,200 --> 00:27:02,359
Speaker 2: much more pro is down the line this and this,

475
00:27:02,560 --> 00:27:04,840
Speaker 2: he was telling everyone before the election, talk about more.

476
00:27:04,880 --> 00:27:08,240
Speaker 2: But after this is polling said APAX brand is terrible

477
00:27:08,640 --> 00:27:11,560
Speaker 2: in a highly educated progressive district. He ran against a

478
00:27:11,680 --> 00:27:14,240
Speaker 2: pack and he said, my opponent is supported by APAK.

479
00:27:15,040 --> 00:27:17,080
Speaker 2: I am a progressive who's going to oppose them and

480
00:27:17,080 --> 00:27:19,200
Speaker 2: never take their money and never be influenced by them.

481
00:27:19,760 --> 00:27:20,359
Speaker 1: So they did.

482
00:27:20,400 --> 00:27:23,840
Speaker 2: They did spend to beat a Gazella, who was more

483
00:27:23,960 --> 00:27:26,399
Speaker 2: left wing on Israel, more calling it a genocide. She

484
00:27:26,440 --> 00:27:28,879
Speaker 2: didn't even support iron Dome. During one of the debates,

485
00:27:28,880 --> 00:27:31,280
Speaker 2: she said, you know, supporting weapons. There's no such thing

486
00:27:31,320 --> 00:27:32,240
Speaker 2: as defensive weapons.

487
00:27:32,520 --> 00:27:36,080
Speaker 1: Yeah, she is on CNN a lot, you famously, she mean,

488
00:27:36,280 --> 00:27:38,639
Speaker 1: if anyone may know her, she was the woman who

489
00:27:38,680 --> 00:27:41,640
Speaker 1: went to the ice protests and they literally threw her

490
00:27:41,680 --> 00:27:44,360
Speaker 1: on her ass, like they picked her up and threw

491
00:27:44,400 --> 00:27:47,520
Speaker 1: her on her ass. Yeah, she she but she wasn't

492
00:27:47,520 --> 00:27:51,040
Speaker 1: even from the district when she ran. She wasn't.

493
00:27:51,080 --> 00:27:54,240
Speaker 2: She had no ties to the district. Her partner, which

494
00:27:54,280 --> 00:27:58,000
Speaker 2: she disclosed as Ben Collins, who took over the Onion

495
00:27:58,600 --> 00:28:00,359
Speaker 2: last year, I believe in the twenty twenty four believes

496
00:28:00,359 --> 00:28:02,320
Speaker 2: when he took it over and they moved there because

497
00:28:02,760 --> 00:28:05,240
Speaker 2: she lost her job at Media Matters when they downsized

498
00:28:05,320 --> 00:28:08,760
Speaker 2: after a bunch of state and Elon Musk lawsuits. She

499
00:28:09,320 --> 00:28:12,800
Speaker 2: ran as I have fought billionaires. I'm responsible for getting

500
00:28:12,840 --> 00:28:15,680
Speaker 2: Tucker Carlson off the air. Yes I'm not from here,

501
00:28:15,720 --> 00:28:18,920
Speaker 2: but I'm the sort of Democrat you want to get

502
00:28:19,000 --> 00:28:21,520
Speaker 2: to have in DC fighting for you. Actually did a

503
00:28:21,520 --> 00:28:24,000
Speaker 2: good job with no ties in the district twenty six

504
00:28:24,000 --> 00:28:26,400
Speaker 2: percent of the vote, and turnout was very high there.

505
00:28:28,000 --> 00:28:30,879
Speaker 2: What's the biggest left wing victory that set off a

506
00:28:30,960 --> 00:28:34,159
Speaker 2: lot of their strategy was AOC winning in twenty eighteen.

507
00:28:34,359 --> 00:28:36,959
Speaker 2: More people voted for kat In Abogazella in this district

508
00:28:36,960 --> 00:28:41,600
Speaker 2: than voted period in the AOC race. Think thirty one

509
00:28:41,600 --> 00:28:44,640
Speaker 2: thousand or thirty two thousand votes, So she did tap

510
00:28:44,680 --> 00:28:47,600
Speaker 2: into something there. But Bess had a record as a

511
00:28:47,600 --> 00:28:51,160
Speaker 2: progressive critic of Israel, and I think if this is

512
00:28:51,200 --> 00:28:53,720
Speaker 2: not in that race, in a divided field, she probably

513
00:28:53,760 --> 00:28:56,959
Speaker 2: could have won. She had more support than Laura Fine.

514
00:28:57,200 --> 00:29:00,520
Speaker 2: So APEC took credit after the election. But they they

515
00:29:00,600 --> 00:29:04,000
Speaker 2: learned in that district that the brand the APAC brand.

516
00:29:04,040 --> 00:29:05,640
Speaker 2: After a couple of cycles of doing this, and I've

517
00:29:05,640 --> 00:29:08,640
Speaker 2: been covering this since the beginning, APEX starting up a

518
00:29:08,640 --> 00:29:10,840
Speaker 2: pack with a different name running in a seat. If

519
00:29:10,840 --> 00:29:13,680
Speaker 2: people say APAX supports you, it is now a huge

520
00:29:13,680 --> 00:29:16,080
Speaker 2: demerit in a Democratic primary. And the other race they

521
00:29:16,120 --> 00:29:19,760
Speaker 2: lost was kind of a loop of Chicago, a very

522
00:29:19,800 --> 00:29:21,800
Speaker 2: safe seat in downtown Chicago.

523
00:29:22,400 --> 00:29:22,880
Speaker 1: Uh.

524
00:29:23,080 --> 00:29:27,680
Speaker 2: They they backed uh City Treasurer Melissa Conyers iervan she

525
00:29:27,840 --> 00:29:31,520
Speaker 2: flopped UH and another Democrat was elected. A PAC sort

526
00:29:31,520 --> 00:29:34,200
Speaker 2: of show credit because a more pro a more anti

527
00:29:34,280 --> 00:29:35,720
Speaker 2: Israel democrat was not elected.

528
00:29:35,960 --> 00:29:38,920
Speaker 1: But no, that was so far from the cycle. A

529
00:29:39,080 --> 00:29:41,120
Speaker 1: PAK is they're.

530
00:29:41,240 --> 00:29:43,520
Speaker 2: Two for two for five on who they actually want

531
00:29:43,560 --> 00:29:44,240
Speaker 2: to be in Congress.

532
00:29:44,240 --> 00:29:48,120
Speaker 1: Winning They're they're they're winning by losing uh in their words,

533
00:29:48,600 --> 00:29:50,840
Speaker 1: And the one person that they backed. It's what's what's

534
00:29:50,880 --> 00:29:52,240
Speaker 1: what is it? Pearis? Uh?

535
00:29:52,520 --> 00:29:54,560
Speaker 2: What was since Peis said or somebody said to Puris,

536
00:29:54,640 --> 00:29:56,680
Speaker 2: you know, another victory like that and we're done for.

537
00:29:57,280 --> 00:29:59,800
Speaker 2: That's kind of been the the apax style in these primaries.

538
00:30:00,480 --> 00:30:03,640
Speaker 1: The other person that they really back was Melissa Bean.

539
00:30:03,800 --> 00:30:08,800
Speaker 1: She was a former congressman running again. She was backed

540
00:30:08,800 --> 00:30:14,480
Speaker 1: by Apak, Crypto andn Ai. She basically had the everyone

541
00:30:14,640 --> 00:30:18,320
Speaker 1: supporting her with all this outside money, and she was

542
00:30:18,360 --> 00:30:21,080
Speaker 1: the one victor for basis everybody, Before I go to Ai,

543
00:30:21,240 --> 00:30:23,760
Speaker 1: let's go to Crypto. They spent a lot of money,

544
00:30:23,800 --> 00:30:26,120
Speaker 1: the Crypto people, they're putting a lot into this entire

545
00:30:26,240 --> 00:30:31,040
Speaker 1: election cycle. How did their election shake out? No? Not great.

546
00:30:31,080 --> 00:30:33,400
Speaker 2: So this is the worst night for the Crypto pack

547
00:30:33,520 --> 00:30:35,960
Speaker 2: since they've gotten involved in politics that started in twenty

548
00:30:36,000 --> 00:30:36,520
Speaker 2: twenty four.

549
00:30:37,120 --> 00:30:38,240
Speaker 1: They didn't pretend it wasn't.

550
00:30:38,640 --> 00:30:40,720
Speaker 2: They quickly reacted to the results and said, look, we

551
00:30:40,760 --> 00:30:41,800
Speaker 2: spent for these candidates.

552
00:30:41,840 --> 00:30:43,880
Speaker 1: We got three people elected. They took credit.

553
00:30:43,960 --> 00:30:45,920
Speaker 2: There was a Nicki Bozinski, who's a Democrat in a

554
00:30:45,920 --> 00:30:49,400
Speaker 2: safe seat in the Illinois jerry manders famous these a

555
00:30:49,400 --> 00:30:51,440
Speaker 2: lot of sea seats because they'll draw a line across

556
00:30:51,480 --> 00:30:53,680
Speaker 2: the state to get all the Democratic precincts.

557
00:30:54,160 --> 00:30:56,600
Speaker 1: She had a progressive challenger. She smoked them.

558
00:30:56,640 --> 00:30:58,760
Speaker 2: They took credit for that, but that wasn't really competitive.

559
00:30:59,400 --> 00:31:02,440
Speaker 2: Fair Shake Bean was the biggest victory they had so

560
00:31:02,520 --> 00:31:05,880
Speaker 2: being this former congress woman she lost in the twenty

561
00:31:05,880 --> 00:31:08,680
Speaker 2: ten wave. She was one of the most conservative Democrats

562
00:31:08,680 --> 00:31:12,000
Speaker 2: in the House when she was there, and the campaigns

563
00:31:12,040 --> 00:31:14,280
Speaker 2: all of them, including hers, but fair Shak's ads really

564
00:31:14,560 --> 00:31:17,120
Speaker 2: lean on this. They kind of reintroduced her as a progressive,

565
00:31:17,480 --> 00:31:21,600
Speaker 2: pro Obamacare, anti ice Democrat. The victory had a lot

566
00:31:21,640 --> 00:31:25,880
Speaker 2: to do with Progressives did not unite behind anybody, so

567
00:31:26,080 --> 00:31:28,760
Speaker 2: Bernie Sanders and AOC got behind the same person. Warrant

568
00:31:28,760 --> 00:31:32,120
Speaker 2: got behind him to United Ahmed who was a pretty

569
00:31:32,160 --> 00:31:35,400
Speaker 2: well known progressive in the district. But the Congression Black

570
00:31:35,400 --> 00:31:39,640
Speaker 2: haukust back somebody else. There were other electeds in the

571
00:31:39,640 --> 00:31:41,920
Speaker 2: brace who had no support, but they kept running. So

572
00:31:42,000 --> 00:31:44,360
Speaker 2: Bean wins with about thirty two percent. There's no runoffs

573
00:31:44,360 --> 00:31:46,760
Speaker 2: in Illinois. That was a good victory for fair Shake.

574
00:31:46,800 --> 00:31:49,480
Speaker 2: Fair Shak is also on the right side.

575
00:31:50,920 --> 00:31:51,120
Speaker 1: In the.

576
00:31:52,800 --> 00:31:55,080
Speaker 2: District that Jesse Jackson Junior lost the second in the

577
00:31:55,120 --> 00:31:58,600
Speaker 2: south side, but it spent ten million dollars to help

578
00:31:58,680 --> 00:32:02,480
Speaker 2: Roger Christa Morphy. I was double checking. That's the most

579
00:32:02,480 --> 00:32:04,720
Speaker 2: they've spent on the candidate who lost. And fair Shake

580
00:32:04,800 --> 00:32:07,360
Speaker 2: has made these very a little bit ironic. If you're

581
00:32:07,480 --> 00:32:10,080
Speaker 2: a crypto investor, you have some capacity for risks.

582
00:32:10,120 --> 00:32:11,240
Speaker 1: Fair Shake's pretty careful.

583
00:32:11,640 --> 00:32:14,400
Speaker 2: Fairshak generally moves into winnable races or races where somebody's

584
00:32:14,440 --> 00:32:17,640
Speaker 2: winning already, like who is a Democratic support In twenty

585
00:32:17,720 --> 00:32:20,360
Speaker 2: twenty four, Reuben Diego, who was always favored to beat

586
00:32:20,720 --> 00:32:23,160
Speaker 2: carry Lake It really wanted to beat Shared Brown, spent

587
00:32:23,200 --> 00:32:24,280
Speaker 2: a lot of demands Fared Brown.

588
00:32:24,320 --> 00:32:24,600
Speaker 1: It has.

589
00:32:25,000 --> 00:32:28,320
Speaker 2: It's been good in races where the battlefields might go

590
00:32:28,360 --> 00:32:31,680
Speaker 2: their way anyway. They took this risk on what did

591
00:32:31,720 --> 00:32:34,080
Speaker 2: not look like a risk on Raja and he lost.

592
00:32:34,560 --> 00:32:37,800
Speaker 1: So this he a pretty decent amount too. He was

593
00:32:37,880 --> 00:32:41,040
Speaker 1: here than people thought. Yeah, it was particularly close. And

594
00:32:41,160 --> 00:32:44,920
Speaker 1: the ironic thing with his race is he won rural,

595
00:32:45,240 --> 00:32:49,120
Speaker 1: excurb and white parts of the state and got demolished

596
00:32:49,160 --> 00:32:52,160
Speaker 1: in the progressive areas and in the ethnic areas and

597
00:32:52,200 --> 00:32:53,560
Speaker 1: in the black areas.

598
00:32:54,240 --> 00:32:57,200
Speaker 2: Yeah that and you could tell on election night talking

599
00:32:57,240 --> 00:33:00,560
Speaker 2: to campaigns they knew Rajia was in trouble early on

600
00:33:00,600 --> 00:33:02,640
Speaker 2: because some of the first counties that are reporting or

601
00:33:02,680 --> 00:33:06,480
Speaker 2: more rural outside the city, places where Stratton did not

602
00:33:06,480 --> 00:33:07,800
Speaker 2: have the money to put a go on the air,

603
00:33:07,840 --> 00:33:10,120
Speaker 2: even with a super pack, and he wasn't doing that

604
00:33:10,160 --> 00:33:13,680
Speaker 2: great like rural Illinois outside of East Saint Louis was.

605
00:33:13,840 --> 00:33:14,440
Speaker 1: He was tied.

606
00:33:14,480 --> 00:33:17,680
Speaker 2: They were losing to Stratton parts of that any place

607
00:33:17,720 --> 00:33:19,760
Speaker 2: where there was a college, any sort of any place

608
00:33:19,800 --> 00:33:21,959
Speaker 2: with a lot of state workers, he was getting crushed.

609
00:33:21,960 --> 00:33:25,000
Speaker 2: So he uh Thratton And I talked to her ad

610
00:33:25,000 --> 00:33:27,520
Speaker 2: makers for something else, I'm writing Stratton in this very

611
00:33:27,560 --> 00:33:30,320
Speaker 2: smart campaign where she her first ad was a bunch

612
00:33:30,360 --> 00:33:34,080
Speaker 2: of people saying f Trump Virguliana. But they said the

613
00:33:34,120 --> 00:33:36,200
Speaker 2: word the letters after app the three letters after a

614
00:33:36,400 --> 00:33:39,640
Speaker 2: they said that, And the goal was, let's identify her

615
00:33:39,680 --> 00:33:42,840
Speaker 2: as the not just Pritzker's friend, but the Democratic fighter,

616
00:33:42,880 --> 00:33:46,320
Speaker 2: whereas Raja is this much more merely mouth guy who

617
00:33:46,400 --> 00:33:46,720
Speaker 2: raised a.

618
00:33:46,680 --> 00:33:47,840
Speaker 1: Lot of money.

619
00:33:47,480 --> 00:33:50,760
Speaker 2: They made her the fighter candidate, which is very successful.

620
00:33:51,720 --> 00:33:55,320
Speaker 2: Robin Kelly, this congressman who left her seat in the Southside,

621
00:33:55,360 --> 00:33:57,360
Speaker 2: that's why it was open. She ran as a more

622
00:33:57,400 --> 00:33:59,720
Speaker 2: progressive Democrat. She was the only one to say that

623
00:33:59,840 --> 00:34:01,760
Speaker 2: is was carrying out a genocide in a debate.

624
00:34:02,000 --> 00:34:03,560
Speaker 1: It's kind of a she didn't roll that in a

625
00:34:03,560 --> 00:34:04,000
Speaker 1: weird way.

626
00:34:04,120 --> 00:34:05,720
Speaker 2: We neither hear the or there, but just just this

627
00:34:06,120 --> 00:34:08,320
Speaker 2: she at the last minute said, oh, it's a genocide.

628
00:34:08,680 --> 00:34:10,680
Speaker 1: So people who.

629
00:34:10,600 --> 00:34:13,040
Speaker 2: Wanted Roja to win were pushing her, saying, if you're

630
00:34:13,040 --> 00:34:15,000
Speaker 2: a progressive, please waste your vote on her.

631
00:34:15,480 --> 00:34:19,040
Speaker 1: Didn't really work. And so talk to the campaigns what

632
00:34:19,360 --> 00:34:21,600
Speaker 1: Raja did. Raja always had a heavy carry.

633
00:34:21,600 --> 00:34:23,279
Speaker 2: I mean, he was a congressman from the suburbs, but

634
00:34:23,320 --> 00:34:26,320
Speaker 2: he was not a He had never been a dynamic,

635
00:34:26,640 --> 00:34:31,000
Speaker 2: celebrity candidate. He's a more progressive down the line, but

636
00:34:31,040 --> 00:34:36,040
Speaker 2: we'll break from the party sometimes democrat. Very good fundraiser,

637
00:34:36,080 --> 00:34:40,839
Speaker 2: but not really somebody who generated passion. And the fact

638
00:34:40,840 --> 00:34:43,520
Speaker 2: that he ran those these ads are running for him

639
00:34:43,480 --> 00:34:48,040
Speaker 2: across the state backfired in an important way. So the

640
00:34:48,120 --> 00:34:51,960
Speaker 2: fair Shake ads and some of his ads attacked Stratton

641
00:34:52,200 --> 00:34:54,759
Speaker 2: because one of her group packs got donations from an

642
00:34:54,800 --> 00:34:59,000
Speaker 2: ICE contractor a private prison company that the contracts of ICE.

643
00:34:59,520 --> 00:35:01,800
Speaker 2: They ran the as those student packs in the campaign

644
00:35:02,120 --> 00:35:05,160
Speaker 2: saying Stratton was taking money from ICE contractors. And what

645
00:35:05,960 --> 00:35:08,359
Speaker 2: I was learning during and after the campaign. Is that

646
00:35:08,360 --> 00:35:10,799
Speaker 2: that backfire just because voters did not look at Jabe

647
00:35:10,800 --> 00:35:13,439
Speaker 2: Pritzker's lieutenant governor and think, oh, she's bought off by Ice.

648
00:35:13,960 --> 00:35:16,560
Speaker 2: Stratton had already attacked Raja by saying he'd gotten money

649
00:35:16,560 --> 00:35:20,040
Speaker 2: from Pallentier very just, and there was a bit of

650
00:35:20,040 --> 00:35:22,800
Speaker 2: a race to who could be the most pure, most

651
00:35:23,560 --> 00:35:26,160
Speaker 2: unwilling to take money from anybody who did something bad,

652
00:35:26,239 --> 00:35:29,520
Speaker 2: accord to Democrats to twenty twenty six. But she won

653
00:35:29,560 --> 00:35:31,799
Speaker 2: that argument and people didn't think, they didn't believe that

654
00:35:31,840 --> 00:35:35,760
Speaker 2: she was truly soft on Ice, and Ice was huge

655
00:35:35,760 --> 00:35:39,399
Speaker 2: issue in this the fact that Pritzker, whatever credit, wont

656
00:35:39,400 --> 00:35:43,040
Speaker 2: people want to give him for working against Ice in

657
00:35:43,080 --> 00:35:45,120
Speaker 2: the state, trying to get them out stop the operation.

658
00:35:45,760 --> 00:35:46,719
Speaker 1: Democrats love that.

659
00:35:46,800 --> 00:35:50,440
Speaker 2: You mentioned Kadobi Gazella getting thrown at at the protest

660
00:35:50,440 --> 00:35:53,200
Speaker 2: to broad view the Ice detention center that really made

661
00:35:53,200 --> 00:35:55,480
Speaker 2: her that and her getting indicted for doing that.

662
00:35:56,120 --> 00:35:58,520
Speaker 1: She went from and the polling.

663
00:35:58,320 --> 00:35:59,640
Speaker 2: Was all over the map, but she went from somebody

664
00:35:59,680 --> 00:36:02,440
Speaker 2: who was an interesting story but not really in fighting

665
00:36:02,440 --> 00:36:06,560
Speaker 2: for first place. After that she was very credible and Democrats,

666
00:36:06,600 --> 00:36:10,239
Speaker 2: really have we learned in this primary really put a

667
00:36:10,360 --> 00:36:13,880
Speaker 2: premium on if you are willing to fight Trump on

668
00:36:13,960 --> 00:36:17,320
Speaker 2: specific things he's doing and maybe risk your own safety

669
00:36:17,360 --> 00:36:19,239
Speaker 2: to do it. You know, oh, I'm going to vote

670
00:36:19,239 --> 00:36:21,160
Speaker 2: for medicare for all. That matters less than if you

671
00:36:21,200 --> 00:36:23,560
Speaker 2: are going to prove that you're really fighting Trump.

672
00:36:23,719 --> 00:36:26,279
Speaker 1: You have a really in a French revolution era of

673
00:36:26,320 --> 00:36:29,040
Speaker 1: the Democratic Party where it's like the Age of Enlightened.

674
00:36:29,440 --> 00:36:31,680
Speaker 1: Everyone has to a n age of enlignment. But the

675
00:36:32,640 --> 00:36:37,239
Speaker 1: whereas Bros. Pierre putting everyone on trial of terror, part

676
00:36:38,040 --> 00:36:40,399
Speaker 1: asy of terror, part of the Democratic primary cycle, that's

677
00:36:40,440 --> 00:36:42,200
Speaker 1: just spoiling down to New York where they have that

678
00:36:42,520 --> 00:36:45,120
Speaker 1: really important primary in the New Year twelve, where Alex

679
00:36:45,200 --> 00:36:48,800
Speaker 1: Boris is the is the AI regulation guy, and he

680
00:36:48,960 --> 00:36:52,640
Speaker 1: happened to used to work for Pallenteer. So the AI

681
00:36:52,760 --> 00:36:55,759
Speaker 1: companies are saying, you worked for Palentiner. Meanwhile they all

682
00:36:56,000 --> 00:37:00,320
Speaker 1: are associated Balenteer and it doesn't really matter anybody. Okay,

683
00:37:00,400 --> 00:37:02,359
Speaker 1: A I speaking of AI, Let's go into AI. How

684
00:37:02,440 --> 00:37:05,120
Speaker 1: did AI spend in this election? How do they fare?

685
00:37:06,719 --> 00:37:09,239
Speaker 2: One thing I will note at the top, and when

686
00:37:09,239 --> 00:37:11,440
Speaker 2: I was writing about the races, I was fairly sympathetic

687
00:37:11,480 --> 00:37:14,440
Speaker 2: to something the left was saying which was these companies

688
00:37:14,480 --> 00:37:17,600
Speaker 2: are spending money on packs. They're not saying vote for

689
00:37:17,680 --> 00:37:19,799
Speaker 2: this candidate. He's good on our issues. They were saying,

690
00:37:20,680 --> 00:37:22,759
Speaker 2: vote for this candidate. We've told and this is the

691
00:37:22,800 --> 00:37:25,319
Speaker 2: best issue for him. He's a fighter for affordability where

692
00:37:25,560 --> 00:37:29,520
Speaker 2: he's fighting ice or something. So the ai I packs

693
00:37:29,719 --> 00:37:31,640
Speaker 2: split their money. They were in for being as you

694
00:37:31,719 --> 00:37:33,799
Speaker 2: were saying, she was the biggest win for all these

695
00:37:33,840 --> 00:37:36,840
Speaker 2: groups of the day. They went in for Jesse Jackson

696
00:37:37,120 --> 00:37:40,360
Speaker 2: in his comeback or Jesse Jackson Junior. I should say not.

697
00:37:40,960 --> 00:37:44,040
Speaker 1: That is Jesse Jackson obviously, but it's his son is

698
00:37:44,160 --> 00:37:47,960
Speaker 1: at pertment with how do I say this play? Seemings

699
00:37:48,000 --> 00:37:51,759
Speaker 1: have a long history of mental health issues. Yes, his

700
00:37:51,840 --> 00:37:52,719
Speaker 1: sigary well known.

701
00:37:53,440 --> 00:37:57,520
Speaker 2: His son went to jail for misusing campaign funds about

702
00:37:57,880 --> 00:37:59,800
Speaker 2: three quarters of a million dollars in campaign funds he

703
00:38:00,200 --> 00:38:03,160
Speaker 2: spent on himself. And the story there is he he

704
00:38:03,320 --> 00:38:04,759
Speaker 2: was in a safe seat. He wanted to run for

705
00:38:04,800 --> 00:38:06,959
Speaker 2: Senate one day or be appointed the Senate. He asked

706
00:38:07,040 --> 00:38:09,640
Speaker 2: rob Igoyovitch, who has been pardoned by Trump, about that

707
00:38:09,719 --> 00:38:10,440
Speaker 2: Senate appointment.

708
00:38:10,960 --> 00:38:12,839
Speaker 1: After he didn't get that appointment he had.

709
00:38:13,120 --> 00:38:15,960
Speaker 2: He has struggled with depression and was spending a lot

710
00:38:16,000 --> 00:38:18,400
Speaker 2: of money on gifts or himself and his wife is

711
00:38:18,480 --> 00:38:23,799
Speaker 2: now has now separated, divorced partner, and he went to jail.

712
00:38:23,920 --> 00:38:24,480
Speaker 1: He came out.

713
00:38:24,840 --> 00:38:27,680
Speaker 2: He tried to re establish himself in his his his

714
00:38:27,800 --> 00:38:30,960
Speaker 2: sixties now as a different man, as a man who'd learned.

715
00:38:31,000 --> 00:38:32,920
Speaker 2: He wrote a book, his mom wrote a book of

716
00:38:32,920 --> 00:38:36,440
Speaker 2: their prison letters. It just wasn't very credible in the

717
00:38:36,480 --> 00:38:39,839
Speaker 2: South Side Chicago. So I got the sense the AI

718
00:38:39,960 --> 00:38:42,000
Speaker 2: packed thought, well, this makes sense. This is the kind

719
00:38:42,040 --> 00:38:44,640
Speaker 2: of UH that can win in this district. And he

720
00:38:44,719 --> 00:38:47,640
Speaker 2: was also very pliable. Jesse Jackson Junior is putting out

721
00:38:47,680 --> 00:38:51,799
Speaker 2: these videos about his economic plans that basically said, yes,

722
00:38:51,880 --> 00:38:53,560
Speaker 2: I'm I'm for building data.

723
00:38:53,719 --> 00:38:56,239
Speaker 1: I've built brit Dilon data centers. I'm for what AI

724
00:38:56,360 --> 00:38:56,759
Speaker 1: wants to do.

725
00:38:56,840 --> 00:38:59,279
Speaker 2: It's if you've seen Eddington, they're basically the ads that

726
00:39:00,040 --> 00:39:01,759
Speaker 2: Pedro Pascal's mayor is running.

727
00:39:01,800 --> 00:39:06,880
Speaker 1: In that movie and didn't work. So they did.

728
00:39:07,000 --> 00:39:08,960
Speaker 2: They did for Melissa be and it didn't work there.

729
00:39:09,719 --> 00:39:13,080
Speaker 2: And these are tough. Remember it's we were saying it's jerrymandered.

730
00:39:13,120 --> 00:39:15,759
Speaker 2: So some two of these seats were in Chicago, in

731
00:39:15,840 --> 00:39:19,640
Speaker 2: the city. We're working class districts, mostly black districts. Two

732
00:39:19,680 --> 00:39:22,440
Speaker 2: of them were more suburban. Uh, the suburban ones are

733
00:39:22,480 --> 00:39:24,680
Speaker 2: more amenable to it. And because there was so much

734
00:39:24,760 --> 00:39:27,000
Speaker 2: money and it didn't become like that Alex Pores race,

735
00:39:27,040 --> 00:39:29,680
Speaker 2: Boris is really trying to turn his campaign to a

736
00:39:29,760 --> 00:39:32,960
Speaker 2: referendum on I can't be bought by AI. The IE

737
00:39:33,040 --> 00:39:34,920
Speaker 2: money just didn't become as big of a story. It

738
00:39:35,000 --> 00:39:38,880
Speaker 2: was just this cloud of pack spending and they blurred

739
00:39:38,920 --> 00:39:40,960
Speaker 2: into it. Well, I think that I think the two

740
00:39:41,000 --> 00:39:43,640
Speaker 2: things you said were really important. One, the amount of

741
00:39:43,800 --> 00:39:47,080
Speaker 2: money from third party entities is now larger than any

742
00:39:47,160 --> 00:39:49,680
Speaker 2: campaign or really larger than almost all the campaigns put

743
00:39:49,719 --> 00:39:52,920
Speaker 2: together at this point. Yeah, it is its own I mean,

744
00:39:53,080 --> 00:39:56,239
Speaker 2: this is this is the outside money for these four

745
00:39:56,320 --> 00:39:57,920
Speaker 2: house races is large enough to.

746
00:39:58,040 --> 00:40:00,680
Speaker 1: Be a US Senate race in itself in the primary.

747
00:40:01,120 --> 00:40:03,040
Speaker 1: Can you speak about that at all, Like the immense

748
00:40:03,080 --> 00:40:04,960
Speaker 1: amount of money being put into these races?

749
00:40:05,719 --> 00:40:08,760
Speaker 2: Oh yeah, these are again safe democratic seats. Were usually

750
00:40:08,880 --> 00:40:11,800
Speaker 2: the winner. Now there's always gonna be packs and groups

751
00:40:11,800 --> 00:40:14,560
Speaker 2: to get involved, but the winner typically only has to

752
00:40:14,600 --> 00:40:16,680
Speaker 2: spend maybe two or three million dollars to win those

753
00:40:16,760 --> 00:40:19,320
Speaker 2: things and has no Republican opponent in the fall, so

754
00:40:19,360 --> 00:40:20,880
Speaker 2: they'd only become big fundraisers.

755
00:40:21,560 --> 00:40:24,239
Speaker 1: So everyone was outspent by these by these super packs.

756
00:40:24,440 --> 00:40:27,640
Speaker 2: The Senate race was only not lopsided because Raja Christian

757
00:40:27,680 --> 00:40:29,560
Speaker 2: Morphy had raised so much for his own campaign, but

758
00:40:30,360 --> 00:40:32,319
Speaker 2: the money that Fair Shakee spent the ten million dollars

759
00:40:32,360 --> 00:40:34,600
Speaker 2: in that race, that's as much as Dick Durban spent

760
00:40:34,760 --> 00:40:36,920
Speaker 2: for every one of his Senate rate each year. He

761
00:40:36,920 --> 00:40:38,960
Speaker 2: would spend about ten million, twelve million dollars to the

762
00:40:39,120 --> 00:40:42,440
Speaker 2: entire race. And so that became a major issue in

763
00:40:42,520 --> 00:40:45,120
Speaker 2: Chicago and all across Illinois. But most of this in

764
00:40:45,239 --> 00:40:48,520
Speaker 2: Chicago of people turning because it's one big media market

765
00:40:48,680 --> 00:40:52,040
Speaker 2: at the TV. The mail was dominated by these new

766
00:40:52,120 --> 00:40:54,040
Speaker 2: packs and people had not heard of them, and a

767
00:40:54,080 --> 00:40:56,880
Speaker 2: lot of bitterness. Now the progressive the most progressive can

768
00:40:57,040 --> 00:40:59,920
Speaker 2: is lost. But they were very bitter, not inclined to

769
00:40:59,960 --> 00:41:01,879
Speaker 2: be pro AI in the first place. This is you're

770
00:41:01,880 --> 00:41:05,200
Speaker 2: saying this division where progressives are a little bit more luddite,

771
00:41:05,480 --> 00:41:09,319
Speaker 2: a little more anti anti progress on AI because they

772
00:41:09,360 --> 00:41:14,360
Speaker 2: see the working class job lost part of it. But

773
00:41:14,560 --> 00:41:19,880
Speaker 2: they they were really turning on these facts because suddenly

774
00:41:19,880 --> 00:41:22,080
Speaker 2: people were getting mail in their in their mailboxes that

775
00:41:22,160 --> 00:41:24,640
Speaker 2: talked about this candate was corrupt and this candate took

776
00:41:24,680 --> 00:41:27,399
Speaker 2: money from corporate interest, so the ad was coming from

777
00:41:27,440 --> 00:41:28,279
Speaker 2: crypto or from AI.

778
00:41:28,680 --> 00:41:30,480
Speaker 1: Well, I think that's what I think the most important

779
00:41:30,480 --> 00:41:32,440
Speaker 1: to what you said is that they're not even talking

780
00:41:32,480 --> 00:41:34,840
Speaker 1: about the subject of AI. They're not talking about crypto,

781
00:41:34,880 --> 00:41:37,279
Speaker 1: they're not talking about anything that. They're talking about other

782
00:41:37,440 --> 00:41:41,320
Speaker 1: things like ice an, immigration and UH and making that

783
00:41:41,400 --> 00:41:43,759
Speaker 1: the referendum and not telling you who's spending or what

784
00:41:43,800 --> 00:41:46,879
Speaker 1: they're spending on behalf, it's a very it's it's it's

785
00:41:46,960 --> 00:41:49,080
Speaker 1: different then back in the day when there would be

786
00:41:49,400 --> 00:41:52,800
Speaker 1: corporations giving candidates a lot of money for their to

787
00:41:52,840 --> 00:41:55,640
Speaker 1: make their own case. But this immense manster pac spending

788
00:41:55,760 --> 00:41:59,719
Speaker 1: is beyond what you usually see it is and and

789
00:41:59,800 --> 00:42:00,440
Speaker 1: that's important.

790
00:42:00,440 --> 00:42:03,719
Speaker 2: The last thing you said because the old there's disclosure

791
00:42:04,800 --> 00:42:08,680
Speaker 2: regulation for money campaigns take, there's less for the super

792
00:42:08,760 --> 00:42:11,200
Speaker 2: PACs that this has been. The the number of it

793
00:42:11,280 --> 00:42:13,960
Speaker 2: I think has made people very cynical. Is this this

794
00:42:14,440 --> 00:42:18,000
Speaker 2: area where packs can raise some packs and five oh

795
00:42:18,040 --> 00:42:20,560
Speaker 2: one C three is can raise money and either never

796
00:42:20,640 --> 00:42:21,960
Speaker 2: report exactly where it came from.

797
00:42:22,200 --> 00:42:23,399
Speaker 1: Progressives do this all the time.

798
00:42:23,480 --> 00:42:25,319
Speaker 2: You know there's a there are donor funds and they

799
00:42:25,360 --> 00:42:27,160
Speaker 2: gave to some group and you never find out where

800
00:42:27,160 --> 00:42:29,920
Speaker 2: the money really came from. Or those packs that could

801
00:42:29,960 --> 00:42:32,920
Speaker 2: start up on the on the calendar where they're not

802
00:42:32,960 --> 00:42:35,200
Speaker 2: going to release their donors until after the election's over.

803
00:42:35,360 --> 00:42:37,600
Speaker 1: That's what happened in Illinois where all of a sudden

804
00:42:37,680 --> 00:42:38,800
Speaker 1: in January.

805
00:42:39,320 --> 00:42:43,640
Speaker 2: Elect Chicago Women, Chicago Progressive Partnership, these groups were popping

806
00:42:43,760 --> 00:42:46,520
Speaker 2: up with the everyone's awareness they're not going to report

807
00:42:46,719 --> 00:42:48,719
Speaker 2: who took who their money is from. APEC, did not

808
00:42:48,800 --> 00:42:51,239
Speaker 2: get credit, did not take credit, i should say, for

809
00:42:51,360 --> 00:42:53,759
Speaker 2: putting these packs into the field. And so that has

810
00:42:53,760 --> 00:42:56,920
Speaker 2: made people very cynical because the old way is this

811
00:42:57,120 --> 00:42:59,520
Speaker 2: candidate is taking here's here are his donors. You can

812
00:42:59,560 --> 00:43:02,080
Speaker 2: go the f see him pull down. Okay, he took

813
00:43:02,200 --> 00:43:05,279
Speaker 2: this much from the dialysis industry. Isn't it coincidental that

814
00:43:05,360 --> 00:43:08,040
Speaker 2: he has a dialysis bill in the Congress. This this

815
00:43:08,200 --> 00:43:12,640
Speaker 2: really has broken that connection where uh, and it's led

816
00:43:12,680 --> 00:43:16,040
Speaker 2: to a lot of parenoia about where money's coming from.

817
00:43:16,080 --> 00:43:16,120
Speaker 1: It.

818
00:43:16,200 --> 00:43:18,000
Speaker 2: So you were seeing that the final stage of these

819
00:43:18,080 --> 00:43:20,960
Speaker 2: races were just people accusing each other of well you

820
00:43:21,040 --> 00:43:23,040
Speaker 2: took money from this guy, and you took money from this,

821
00:43:23,400 --> 00:43:25,120
Speaker 2: and you ten years ago took money from this, and

822
00:43:25,160 --> 00:43:27,920
Speaker 2: then it was it became very much about donors of

823
00:43:27,960 --> 00:43:30,719
Speaker 2: the campaigns in a way that was much messier and

824
00:43:30,800 --> 00:43:33,040
Speaker 2: less enlightening than it than it used to be. Where somebody, oh,

825
00:43:33,280 --> 00:43:34,960
Speaker 2: this guy's taking money from the oil industry and he

826
00:43:35,040 --> 00:43:39,319
Speaker 2: represents the Houston that makes sense. It was much much

827
00:43:39,400 --> 00:43:41,800
Speaker 2: more scattershot in terms of connecting the money to what

828
00:43:41,880 --> 00:43:42,319
Speaker 2: they were doing.

829
00:43:42,640 --> 00:43:44,680
Speaker 1: Okay, my last question, and you mentioned that all the

830
00:43:44,760 --> 00:43:46,600
Speaker 1: progressive of the progress accounts lost a lot. I was

831
00:43:46,640 --> 00:43:48,360
Speaker 1: don't talk about that, but it's not that interesting. What

832
00:43:48,520 --> 00:43:51,400
Speaker 1: is interesting is going into the next couple of elections cycles.

833
00:43:51,440 --> 00:43:54,239
Speaker 1: In the next level primaries, where are these three major

834
00:43:54,280 --> 00:43:59,600
Speaker 1: groups Crypto, AI and Israel APAC spending and where is

835
00:43:59,640 --> 00:44:01,719
Speaker 1: the next big spike and I take place in which

836
00:44:01,800 --> 00:44:05,400
Speaker 1: primaries or were states? One coming up is Colorado.

837
00:44:05,480 --> 00:44:08,360
Speaker 2: The answer is these packs are going to spend in

838
00:44:08,440 --> 00:44:14,040
Speaker 2: places where there are for mostly Democrats, because I think

839
00:44:14,120 --> 00:44:16,279
Speaker 2: that most people expect Democrats at least to win the House.

840
00:44:17,239 --> 00:44:20,799
Speaker 2: Democrats who are facing progressive challenges or open seats where

841
00:44:20,920 --> 00:44:24,640
Speaker 2: somebody has a pro AI position, somebody's anti So Colorado

842
00:44:24,800 --> 00:44:28,800
Speaker 2: has a couple of competitive races it has in the

843
00:44:28,920 --> 00:44:33,040
Speaker 2: Denver district and to get she's experiencing what happened to

844
00:44:33,480 --> 00:44:36,919
Speaker 2: some candids in Illinois, which is the Sunrise Movement, which

845
00:44:36,960 --> 00:44:38,799
Speaker 2: is a climate group, and I have a story as

846
00:44:38,920 --> 00:44:41,120
Speaker 2: Yer grown is now doing a lot of campaigning around

847
00:44:41,480 --> 00:44:45,799
Speaker 2: a pack and Data Centers less climate. It has people

848
00:44:45,920 --> 00:44:47,839
Speaker 2: what they call bird dogging and going up to her

849
00:44:47,920 --> 00:44:50,640
Speaker 2: and asking her about her funding for Israel, recording it.

850
00:44:52,400 --> 00:44:53,000
Speaker 1: Targeting her.

851
00:44:53,239 --> 00:44:55,879
Speaker 2: Now, that's the sort of race that I think these

852
00:44:55,960 --> 00:44:57,560
Speaker 2: packs are going to look at and say, is it

853
00:44:57,640 --> 00:45:00,520
Speaker 2: worth spending some money to defend somebody who's good on

854
00:45:00,600 --> 00:45:02,960
Speaker 2: our issues against the progressive who's going to tear us up.

855
00:45:03,920 --> 00:45:07,160
Speaker 2: That's what happened North Carolina. Not to expand that after more,

856
00:45:07,200 --> 00:45:10,719
Speaker 2: but North Carolina had its primary two weeks ago, and

857
00:45:11,200 --> 00:45:15,360
Speaker 2: it was really AI interest that one of that saved

858
00:45:15,360 --> 00:45:18,640
Speaker 2: a Democrat who had a progressive challenger because she was

859
00:45:18,719 --> 00:45:22,359
Speaker 2: on the AI Democrats Special Committee. She was not going

860
00:45:22,440 --> 00:45:24,359
Speaker 2: to regularly well I'm not going to give her all

861
00:45:24,400 --> 00:45:27,080
Speaker 2: in politics, but her opponent was running against AI and

862
00:45:27,200 --> 00:45:29,399
Speaker 2: Data Centers. They said, well, this is clear but we'd

863
00:45:29,480 --> 00:45:31,080
Speaker 2: rather have a Democrat who deals with us than one

864
00:45:31,120 --> 00:45:32,160
Speaker 2: who's running against us.

865
00:45:33,520 --> 00:45:36,960
Speaker 1: That will matter. In California, You're going to see some

866
00:45:37,040 --> 00:45:37,560
Speaker 1: of this spending.

867
00:45:38,320 --> 00:45:40,960
Speaker 2: The one who is more pro AI won yes, and

868
00:45:41,600 --> 00:45:44,200
Speaker 2: the one is more pro AI won by one point.

869
00:45:44,640 --> 00:45:46,520
Speaker 2: You're going to see this in California too, because of

870
00:45:46,560 --> 00:45:49,920
Speaker 2: the new map drawn by Democrats there. In Virginia, if

871
00:45:50,000 --> 00:45:52,959
Speaker 2: this new gerrymanders succeeds, which they has to be voted

872
00:45:53,000 --> 00:45:55,120
Speaker 2: on April first, same thing there, there are gonna be

873
00:45:55,160 --> 00:45:58,319
Speaker 2: new open districts. And you saw wherever there is an

874
00:45:58,360 --> 00:46:01,080
Speaker 2: open seat, candidates faced the question should I put something

875
00:46:01,120 --> 00:46:03,600
Speaker 2: on my website or have a meeting with one of

876
00:46:03,640 --> 00:46:06,680
Speaker 2: these groups, or sign a pledge that says I'm pro technology,

877
00:46:06,719 --> 00:46:09,520
Speaker 2: pro AI, pro crypto. If i am, I might get

878
00:46:09,600 --> 00:46:11,680
Speaker 2: money spent for me. Because you can't actually coordinate. You

879
00:46:11,719 --> 00:46:13,799
Speaker 2: can just say you can't go to a super pac.

880
00:46:13,840 --> 00:46:16,080
Speaker 2: You're not allowed to still legally, although it's not really

881
00:46:16,080 --> 00:46:17,359
Speaker 2: probably the FEC doesn't really.

882
00:46:17,280 --> 00:46:17,840
Speaker 1: Do anything about it.

883
00:46:18,080 --> 00:46:20,080
Speaker 2: Can't go to a superPAC and say I'm with it

884
00:46:20,280 --> 00:46:22,320
Speaker 2: with you, please spend this much money here. What you

885
00:46:22,440 --> 00:46:27,080
Speaker 2: do is sign some forms or take some pledges. That

886
00:46:27,440 --> 00:46:29,640
Speaker 2: signal what your politics are, or if you have a record,

887
00:46:29,760 --> 00:46:31,960
Speaker 2: you say, look at your voting record and then put

888
00:46:32,000 --> 00:46:34,400
Speaker 2: on your website. It'd be really nice if somebody ran

889
00:46:34,480 --> 00:46:36,480
Speaker 2: ads for us on these topics and this topic and

890
00:46:36,560 --> 00:46:39,680
Speaker 2: this topic. The downside is, and you saw a littlevis

891
00:46:39,719 --> 00:46:42,600
Speaker 2: and LLOI, if you're that candidate in a Democratic primary,

892
00:46:42,680 --> 00:46:44,480
Speaker 2: you're going to get a progressive hitting you in saying

893
00:46:44,560 --> 00:46:45,719
Speaker 2: this person's bought and paid for.

894
00:46:46,640 --> 00:46:48,960
Speaker 1: So that is the risk. That is the risk assessment

895
00:46:49,040 --> 00:46:49,680
Speaker 1: candidates are doing.

896
00:46:50,120 --> 00:46:51,759
Speaker 2: Is it worth getting free money if I might get

897
00:46:51,800 --> 00:46:53,359
Speaker 2: accused of taking too much free money?

898
00:46:54,000 --> 00:46:55,959
Speaker 1: Right? Well, Dave Legol, where do we go to follow

899
00:46:56,000 --> 00:46:58,240
Speaker 1: your reporting? You write a lot of really interesting stuff

900
00:46:58,280 --> 00:47:00,560
Speaker 1: on the congressional side, and all these elections are coming out.

901
00:47:01,120 --> 00:47:03,080
Speaker 2: Yeah, so it's a semaphore dot com. I have a

902
00:47:03,160 --> 00:47:06,479
Speaker 2: newsletter whocomes that weekly called Americana. That's a reporters around

903
00:47:06,520 --> 00:47:08,480
Speaker 2: the country. We have other newsletters every day. We have

904
00:47:08,640 --> 00:47:11,800
Speaker 2: independent stories. I put a lot on Twitter too. On

905
00:47:12,080 --> 00:47:14,600
Speaker 2: x I I link to the stories, but also I

906
00:47:14,680 --> 00:47:16,960
Speaker 2: build out a lot of stuff on x because it's

907
00:47:17,040 --> 00:47:17,640
Speaker 2: really helpful.

908
00:47:17,960 --> 00:47:19,440
Speaker 1: Whatever people think of the site.

909
00:47:19,600 --> 00:47:21,799
Speaker 2: It's really helpful to in real time say what if

910
00:47:21,840 --> 00:47:24,480
Speaker 2: people think of this, get reactions and sometimes somebody comes

911
00:47:24,480 --> 00:47:26,759
Speaker 2: out of the woodwork and says, check out this race.

912
00:47:26,840 --> 00:47:29,960
Speaker 2: But the reporting that I am going to I could

913
00:47:29,960 --> 00:47:32,560
Speaker 2: the quote, I the quotes I travel, I put it

914
00:47:32,640 --> 00:47:33,320
Speaker 2: into stories.

915
00:47:33,400 --> 00:47:36,320
Speaker 1: That's semiphore dot com. Well, thank you so much on

916
00:47:36,400 --> 00:47:42,279
Speaker 1: this podcast. I really appreciate it. Thank you. Now it's

917
00:47:42,320 --> 00:47:43,920
Speaker 1: time for the ask Me Anything segment. If you want

918
00:47:43,920 --> 00:47:45,680
Speaker 1: to be part of the Ask Me Anything segment segment,

919
00:47:45,760 --> 00:47:48,879
Speaker 1: email me Ryan at Numbers Gamepodcast dot com. That's Ryan

920
00:47:48,960 --> 00:47:52,440
Speaker 1: at numbers Lural Numbers Gamepodcast dot com. Love getting to

921
00:47:52,520 --> 00:47:54,520
Speaker 1: all your questions. This one comes from Chris. Is a

922
00:47:54,600 --> 00:47:56,680
Speaker 1: little long, So Chris, and when I abbreviate it, he says,

923
00:47:57,239 --> 00:47:59,200
Speaker 1: you've been knocking out of the part with Park with

924
00:47:59,280 --> 00:48:02,239
Speaker 1: your scorch earth Deep Dives an interesting guest. Thank you, Chris.

925
00:48:02,360 --> 00:48:04,480
Speaker 1: I really really been working hard on this podcast to

926
00:48:04,520 --> 00:48:05,879
Speaker 1: trying to make it something good and I think people

927
00:48:05,920 --> 00:48:10,000
Speaker 1: are starting to take notice. You were mentioning how Ohio

928
00:48:10,120 --> 00:48:12,879
Speaker 1: has changed significantly over time. You write that the private

929
00:48:12,920 --> 00:48:15,040
Speaker 1: sector labor unions that provided such a blue wall and

930
00:48:15,080 --> 00:48:18,720
Speaker 1: support in northeast Ohio have disappeared with offshoring. And automation.

931
00:48:19,280 --> 00:48:22,560
Speaker 1: Hamilton County, which had a healthy balance of Republican leadership,

932
00:48:22,640 --> 00:48:25,880
Speaker 1: has basically gone out of the city and into the suburbs.

933
00:48:26,560 --> 00:48:29,640
Speaker 1: But it's all Democrats at this point. Anyway, your main

934
00:48:29,760 --> 00:48:33,560
Speaker 1: question is Amy Acton as a Democrat is a formidable

935
00:48:33,600 --> 00:48:37,800
Speaker 1: candidate in the sense that Gannette Papers Cincinnati acquire Columbus Dispatch,

936
00:48:37,880 --> 00:48:41,160
Speaker 1: elevated her to a fauci esque status during COVID, and

937
00:48:41,280 --> 00:48:44,160
Speaker 1: continue to fawn over her. I hope that Jessica Anderson

938
00:48:44,239 --> 00:48:47,239
Speaker 1: is correct in her assessment that Houston and Ramaswami will

939
00:48:47,280 --> 00:48:50,799
Speaker 1: be competent, each will compliment each other, because I'm very

940
00:48:50,840 --> 00:48:53,279
Speaker 1: concerned of the lower PENSI Trump voter sitting this out.

941
00:48:53,880 --> 00:48:56,800
Speaker 1: There's a Jesuit joke in there somewhere about why Vivek

942
00:48:56,920 --> 00:48:59,160
Speaker 1: is so unlikable. He mentions it in his book, but

943
00:48:59,400 --> 00:49:02,480
Speaker 1: plays ask and loose with his high school education at

944
00:49:02,560 --> 00:49:08,040
Speaker 1: Saint Xavier, And yeah, I don't. Here's the thing about

945
00:49:08,200 --> 00:49:10,799
Speaker 1: I think the question is about is Amy acting as

946
00:49:10,880 --> 00:49:13,719
Speaker 1: formidable or do the Republicans have a chance. It's a

947
00:49:13,800 --> 00:49:17,120
Speaker 1: Democrat year. It's just it's way it's playing out. And

948
00:49:17,239 --> 00:49:21,880
Speaker 1: Sharon Brown's a very well known name. But this is

949
00:49:21,960 --> 00:49:27,440
Speaker 1: Sharon Brown's fourth time or fifth time at bat. Voters

950
00:49:27,560 --> 00:49:29,640
Speaker 1: do know him, and they just kicked him out. And

951
00:49:29,760 --> 00:49:35,359
Speaker 1: I think what Johnny used did. He's as bland as

952
00:49:35,400 --> 00:49:38,759
Speaker 1: you could possibly get. There's nothing that I mean. I

953
00:49:38,800 --> 00:49:41,560
Speaker 1: think he had a quib the other day that kind

954
00:49:41,600 --> 00:49:44,680
Speaker 1: of went out that didn't land. But besides that, he's

955
00:49:44,719 --> 00:49:47,560
Speaker 1: been He's very, very, very bland, and he's very smart

956
00:49:47,600 --> 00:49:52,960
Speaker 1: because he's making voting voter idea a big issue. He's

957
00:49:53,000 --> 00:49:56,640
Speaker 1: even throwing into the Democrats. Now. I don't think he's

958
00:49:56,800 --> 00:50:01,319
Speaker 1: very controversial, and I think Sharon Brown just gonna attack

959
00:50:01,360 --> 00:50:04,000
Speaker 1: him as being a Trump supporter, but in overwhelmingly Trump state.

960
00:50:04,640 --> 00:50:07,640
Speaker 1: So I've heard that there's polling that share is up

961
00:50:07,800 --> 00:50:10,320
Speaker 1: but not by much at this point in Ohio A

962
00:50:10,400 --> 00:50:12,399
Speaker 1: lot of times the Democrats up, but not by much.

963
00:50:12,719 --> 00:50:17,160
Speaker 1: And it seems that shared is actually polling worse than acting.

964
00:50:17,920 --> 00:50:20,840
Speaker 1: Here's the thing about acting. Yes, acting was all about

965
00:50:20,880 --> 00:50:23,320
Speaker 1: shutting down the government. Acting was all about you know,

966
00:50:24,760 --> 00:50:29,160
Speaker 1: all about about you know COVID, how she gained prominence.

967
00:50:30,080 --> 00:50:33,640
Speaker 1: The thing is is there's two major issues. Remember when

968
00:50:33,680 --> 00:50:37,360
Speaker 1: I said on this podcast, all the Ohio listeners Ramaswami

969
00:50:37,520 --> 00:50:40,880
Speaker 1: is not going to show himself much in the ads

970
00:50:41,360 --> 00:50:44,680
Speaker 1: because they did, and I know this from the presidential campaign.

971
00:50:45,120 --> 00:50:49,000
Speaker 1: They tested that when he was on camera, people liked

972
00:50:49,080 --> 00:50:52,000
Speaker 1: him less with that when people talked about him. And

973
00:50:52,160 --> 00:50:54,000
Speaker 1: in his second ad that came out, his first ad

974
00:50:54,080 --> 00:50:55,759
Speaker 1: was his wife, and his wife is very lovely and

975
00:50:55,840 --> 00:50:58,480
Speaker 1: sounded very smart and you know, was very compassionate and

976
00:50:58,560 --> 00:51:02,160
Speaker 1: did a great job. In this second ad, his it

977
00:51:02,280 --> 00:51:04,600
Speaker 1: was somebody else also talking about him. It was not

978
00:51:04,920 --> 00:51:08,600
Speaker 1: him talking about himself. And then he got on television

979
00:51:08,680 --> 00:51:10,719
Speaker 1: or wherever he was and he said, our problem is

980
00:51:10,760 --> 00:51:15,080
Speaker 1: we have too many public colleges. We should condense them. Now,

981
00:51:15,680 --> 00:51:18,040
Speaker 1: you could say that's a really smart idea, or yes,

982
00:51:18,160 --> 00:51:22,640
Speaker 1: that's possibly true, or let's look as analytically, that's something

983
00:51:22,760 --> 00:51:25,399
Speaker 1: you do once you are in office and not something

984
00:51:25,480 --> 00:51:29,520
Speaker 1: you say when you are running for office. Because what

985
00:51:29,800 --> 00:51:35,040
Speaker 1: that means for Joe Schmoe in Miami, Ohio, or you know,

986
00:51:35,360 --> 00:51:38,640
Speaker 1: in parts of the state that are really in not

987
00:51:38,920 --> 00:51:42,320
Speaker 1: great financial shape, is it means one of the biggest

988
00:51:42,520 --> 00:51:46,120
Speaker 1: job providers for their local community it may possibly go

989
00:51:46,280 --> 00:51:49,920
Speaker 1: out of business because of vec. It's not that you

990
00:51:50,120 --> 00:51:53,000
Speaker 1: don't say something like that. Like, you don't say, hey,

991
00:51:53,120 --> 00:51:56,239
Speaker 1: let's put kids in school all year long while you're campaigning,

992
00:51:56,320 --> 00:51:59,720
Speaker 1: which is other thing that a VEC did. Don't try

993
00:52:00,080 --> 00:52:05,120
Speaker 1: to think you're smarter than the voters. Running for office

994
00:52:05,840 --> 00:52:07,879
Speaker 1: is not an excuse my language, but this is truth.

995
00:52:08,200 --> 00:52:11,200
Speaker 1: Running for office is not an exercise and mental masturbation.

996
00:52:11,880 --> 00:52:14,759
Speaker 1: It's not to show everyone, look how bright I am.

997
00:52:15,239 --> 00:52:18,160
Speaker 1: I can think of seven million different ideas that you

998
00:52:18,400 --> 00:52:21,920
Speaker 1: have to live on there. That's not the point. The

999
00:52:22,040 --> 00:52:24,440
Speaker 1: point of a good candidate to run for office is

1000
00:52:24,560 --> 00:52:29,840
Speaker 1: to repeat what their people already feel. Promote ideals that

1001
00:52:30,040 --> 00:52:33,040
Speaker 1: they understand. You're not trying to educate them. You don't

1002
00:52:33,280 --> 00:52:35,800
Speaker 1: be able to bring up fifty that we're gonna launch

1003
00:52:35,800 --> 00:52:37,680
Speaker 1: people into space and then they're gonna bring their own

1004
00:52:37,760 --> 00:52:40,239
Speaker 1: energy from the sun. No, no, listen, talk to them

1005
00:52:40,320 --> 00:52:43,400
Speaker 1: about things that they already know, things that are tangible,

1006
00:52:43,800 --> 00:52:49,319
Speaker 1: tangible solutions. I always tell it to candidate's tangible solutions.

1007
00:52:49,400 --> 00:52:52,759
Speaker 1: If you can't run on just you know, words and

1008
00:52:52,880 --> 00:52:56,320
Speaker 1: phrases like hope and change or the free market or

1009
00:52:56,560 --> 00:52:58,960
Speaker 1: American exceptionalism, if you can't reuse that and you need

1010
00:52:59,040 --> 00:53:03,000
Speaker 1: actual policy solutions, run on things that people understand, don't

1011
00:53:03,040 --> 00:53:06,200
Speaker 1: try to sound smart them and make the solutions tangible.

1012
00:53:06,440 --> 00:53:08,880
Speaker 1: If you close your eyes and you thought of what

1013
00:53:09,040 --> 00:53:11,239
Speaker 1: build the wall looks like, you could think of what

1014
00:53:11,400 --> 00:53:14,040
Speaker 1: that tangibly looks like. Close your eyes you can think

1015
00:53:14,080 --> 00:53:17,799
Speaker 1: of what medicare for all actually looks like. It's a tangible,

1016
00:53:18,160 --> 00:53:22,880
Speaker 1: easy to understand, comprehensible solution. The Vek is not doing

1017
00:53:23,000 --> 00:53:25,839
Speaker 1: any of that right now, and that is why Amy

1018
00:53:25,880 --> 00:53:28,560
Speaker 1: Acton is winning. Some I think was cook Political or

1019
00:53:29,239 --> 00:53:32,879
Speaker 1: one of these posters that analyze the sailor race move

1020
00:53:32,960 --> 00:53:36,279
Speaker 1: the Ohio race from likely Republican to lean Republican and

1021
00:53:36,360 --> 00:53:38,680
Speaker 1: then blamed it on the fact that a Vek is Indian.

1022
00:53:38,880 --> 00:53:42,600
Speaker 1: It is nothing to do with that at all. It

1023
00:53:42,800 --> 00:53:46,799
Speaker 1: is literally because he is making himself as unlikable as

1024
00:53:46,920 --> 00:53:49,880
Speaker 1: humanly possible. And to answer your question question Chris, I

1025
00:53:50,120 --> 00:53:54,600
Speaker 1: think that there is a world out there where Houston wins,

1026
00:53:54,880 --> 00:53:57,320
Speaker 1: but so does Amy acting I don't think they have

1027
00:53:57,400 --> 00:53:59,120
Speaker 1: to win as a pair. I do think there will

1028
00:53:59,160 --> 00:54:02,080
Speaker 1: be crossover because I think Favec is doing everything he

1029
00:54:02,200 --> 00:54:06,480
Speaker 1: possibly can to turn people in these college towns and say, hey,

1030
00:54:06,560 --> 00:54:09,000
Speaker 1: your whole livelihood could be down the drain. We don't know.

1031
00:54:09,160 --> 00:54:11,400
Speaker 1: We'll see. I think this is a good idea, possibly

1032
00:54:11,680 --> 00:54:14,240
Speaker 1: telling moms, hey, guess what those summer vacations you were planning.

1033
00:54:14,920 --> 00:54:17,160
Speaker 1: Let's talk about having school a year long and you

1034
00:54:17,800 --> 00:54:20,040
Speaker 1: and changing the way you've done things, and you've done

1035
00:54:20,080 --> 00:54:23,840
Speaker 1: things for generations. He's creating instability in people's minds, but

1036
00:54:23,960 --> 00:54:26,440
Speaker 1: the future of their state, and that's a scary thing,

1037
00:54:26,600 --> 00:54:28,360
Speaker 1: and he's not doing a great job at it. He

1038
00:54:28,600 --> 00:54:30,960
Speaker 1: still is the likeliest candidate to win. I want to

1039
00:54:31,000 --> 00:54:33,640
Speaker 1: emphasize it to you because Ohio is so Republican, but

1040
00:54:33,800 --> 00:54:37,040
Speaker 1: he's doing everything he can to lose. It is he

1041
00:54:37,320 --> 00:54:40,359
Speaker 1: is his race to lose, and he is making sure

1042
00:54:40,440 --> 00:54:42,400
Speaker 1: he can try to lose it. That's all. And you

1043
00:54:42,440 --> 00:54:43,719
Speaker 1: guys know, I'm not a fan of the vac I'm

1044
00:54:43,719 --> 00:54:46,880
Speaker 1: trying to really call it balls and strikes as it

1045
00:54:47,000 --> 00:54:51,560
Speaker 1: is and not temper my personal feelings with my political assessment.

1046
00:54:52,239 --> 00:54:54,080
Speaker 1: He does. Also one of the things that Beck has

1047
00:54:54,120 --> 00:54:56,440
Speaker 1: a lot of union support, which Republicans usually don't have,

1048
00:54:56,560 --> 00:54:59,200
Speaker 1: so maybe that will also will beil him out. Unions

1049
00:54:59,280 --> 00:55:02,680
Speaker 1: don't always vote for for who their bosses support. Just FYI,

1050
00:55:02,920 --> 00:55:05,400
Speaker 1: all right, that's this episode. I'll see you guys on Wednesday.

1051
00:55:05,400 --> 00:55:07,480
Speaker 1: If you like this podcast, please like and subscribe on

1052
00:55:07,480 --> 00:55:10,280
Speaker 1: the iHeartRadio app, Apple Podcasts, wherever you get your podcasts,

1053
00:55:10,280 --> 00:55:12,520
Speaker 1: and on YouTube. And if you're feeling generous, give me

1054
00:55:12,560 --> 00:55:15,280
Speaker 1: a five star review. It really helps share this podcast everybody.

1055
00:55:15,520 --> 00:55:17,120
Speaker 1: I will see you guys on Wednesday.