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Speaker 1: This episode of the Chuck Podcast is brought to you

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Speaker 1: by Incognate. You know, one of the things we talk

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Speaker 1: taking control of your personal data today. Trust me, I'm

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Speaker 1: constantly working on this for years myself, and here's an

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Speaker 1: opportunity for you to take matters into your own hands

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Speaker 1: as well. Hello thereon, Welcome to the Thursday edition of

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Speaker 1: the Chuck Podcast. I have today's going to be a

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Speaker 1: bit more domestic, a bit moreocused on that obviously. Look

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Speaker 1: that the most important story impacting American politics is and

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Speaker 1: will continue to be the Iran War until it is

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Speaker 1: not right because of the impact it has on our economy,

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Speaker 1: the sort of symbolic impact it has on the economy

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Speaker 1: with gas prices, things like that, but the actual war itself,

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Speaker 1: the conduct of this war will we end up escalating

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Speaker 1: all these questions securing the straight of horn moves. It

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Speaker 1: is going to continue to be essentially, and I think

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Speaker 1: if you're like I said, it's similar I said yesterday.

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Speaker 1: If you're a Republican running on the ballot in twenty

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Speaker 1: twenty six, you just wish this war would end in

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Speaker 1: some form or another, that you could turn the page

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Speaker 1: on this. But it isn't going to happen very quickly,

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Speaker 1: very easily. This is going to continue to be I

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Speaker 1: think the biggest story that will impact the larger sort

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Speaker 1: of perception of the direction of the country, and it

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Speaker 1: will certainly impact what is campaigned on. But at the

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Speaker 1: end of the day, whether the war was happening or not,

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Speaker 1: the issue of the economy and democracy issues would be

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Speaker 1: in some ways front and center the issues. And in fact,

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Speaker 1: a big issue that this episode's going to focus on

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Speaker 1: today is the role of AI, and it's the fear

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Speaker 1: of AI and the disruption of our economy, the fear

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Speaker 1: of AI disruption to culture, the fear and the fact

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Speaker 1: that there are more Americans today that feel apprehension about

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Speaker 1: the development of AI rather more so than enthusiasm. The

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Speaker 1: unpopularity of AI in the American public is starting to increase.

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Speaker 1: And so it brings me to my guests that I

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Speaker 1: am featuring today, and the long form interview that I

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Speaker 1: have today is with a former Democratic member of Congress,

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Speaker 1: long time, twenty years. Has been twenty years since he served,

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Speaker 1: Brad Carson. He was an Oklahoma Democrat. He ran and lost.

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Speaker 1: He left Congress when he ran for the US Senate,

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Speaker 1: lost to Tom Coburn, who just recently not that long ago. Well,

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Speaker 1: I guess it's been a while now since he passed away,

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Speaker 1: but he was a long time member of the Senate,

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Speaker 1: and in fact, Coburn getting elected in four was a

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Speaker 1: big victory for some conservatives. He gets elected in one

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Speaker 1: of the freshman senators that he befriends and becomes fairly

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Speaker 1: close friends with is a future president in Barack Obama.

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Speaker 1: But in Brad Carson. He is the head of a

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Speaker 1: group called Americans for Responsible Innovation. And I know it's

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Speaker 1: one of those what the hell does that mean? Right,

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Speaker 1: who's not for responsible innovation? But it is basically the

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Speaker 1: we're for regulating AI, but we're pro AI group. Right.

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Speaker 1: This is if you're been following the battle between for

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Speaker 1: AI supremacy between your chat GBT Claude Gemini. Well, Claude

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Speaker 1: is the chatbot of Anthropic. Anthropic is the sort of

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Speaker 1: spin off, is the company that grew out of those

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Speaker 1: that left Open AI for fear that there wasn't enough guardrails. Obviously,

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Speaker 1: you know the story of Anthropic now being banned from

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Speaker 1: the Pentagon and being potentially seen as a as a

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Speaker 1: supply chain risk if you do business with Anthropic. So

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Speaker 1: what has happened is there is you know where this

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Speaker 1: is getting into the political campaigns, and some of the

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Speaker 1: biggest spenders in American politics right now are in the

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Speaker 1: AI space. You basically have a collection of those on

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Speaker 1: the no regulation side of AI, that most prominently being

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Speaker 1: being Open AI and the folks behind chat GPT, and

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Speaker 1: then you have Anthropic and that side of the space

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Speaker 1: that is in favor of allowing and encouraging some regulation

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Speaker 1: and some guardrails in the AI space. And the it

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Speaker 1: is I bring this up because this all happened within

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Speaker 1: the same week we had the Illinois primary, and my

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Speaker 1: sub stack theme this week is about how the Illinois

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Speaker 1: primary and I think there's some important political followup from

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Speaker 1: that I'll share with you in a few minutes. A

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Speaker 1: huge win for Juliana Stratton number one, but number two,

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Speaker 1: and maybe in the near term the bigger winner might

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Speaker 1: be JB. Pritzker, the governor of Illinois. I think we

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Speaker 1: those of us. I'm somebody who's you know, not. I

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Speaker 1: wasn't sure I didn't have him in my top tier

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Speaker 1: of twenty twenty eight ers. Let's just say, you know,

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Speaker 1: I'm paying a lot more respect than to him now,

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Speaker 1: and I see him as I think, you know, you're

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Speaker 1: the governor you're able to take on You're a billionaire governor,

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Speaker 1: and you're able to take on these huge super packs

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Speaker 1: from the crypto industry and from the tech and AI industries,

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Speaker 1: and you're able to win. Although in this case, I

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Speaker 1: think it was really more of the crypto folks that

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Speaker 1: he was taking on more than anybody else. It says

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Speaker 1: something and I certainly have and I want to get

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Speaker 1: to that in a minute. But I want to tackle

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Speaker 1: this issue of money in politics because it's all kind

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Speaker 1: of tied in together a little bit. And let's just say,

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Speaker 1: for years I didn't spend a lot of time on

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Speaker 1: the issue of campaign finance and money in politics, not

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Speaker 1: because I didn't think it was a problem. I just

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Speaker 1: never really believed it would ever really become a big

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Speaker 1: issue in American politics, even as you hear as I'll

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Speaker 1: hear plenty of sort of you know, non professional in

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Speaker 1: this space, I E. Voters, I E. Those that pay

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Speaker 1: attention going, we've got to do something about money in politics.

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Speaker 1: Because I was a skeptic when it came that there

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Speaker 1: was any reform that was even possible, that there was

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Speaker 1: no curbing of money. And it wasn't because I thought

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Speaker 1: the system was healthy. Quite the opposite. I just assumed

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Speaker 1: the problem was unbeatable. It was too adaptive, it was

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Speaker 1: too clever, if you will, And I had this working

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Speaker 1: assumption to I used to do this all the time.

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Speaker 1: I'd quote Jeff Goldbloom's character in Jurassic Park when the

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Speaker 1: old man reassures the scientists that he brings to show

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Speaker 1: off his dinosaurs. Oh no, no, no, they're not going

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Speaker 1: to pro create. I've been able to manipulate their DNA

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Speaker 1: so that they can't pro create. And Goldblum's characters, you know,

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Speaker 1: he's the guy who I guess promotes chaos theory and mathematics,

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Speaker 1: and he basically says life finds a way and he

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Speaker 1: turns out to be right. Well, I've always felt that

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Speaker 1: way about money in politics, right, money always finds a way.

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Speaker 1: You try public financing, it gets outgrown, You try to

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Speaker 1: cap contributions. Well then you get bundling, which sort of

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Speaker 1: work around. Every reform in my adult lifetime in Franctly,

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Speaker 1: my entire lifetime has been has been turned against itself. Right,

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Speaker 1: you ban soft money from the major parties, then that

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Speaker 1: money moves outside the parties and you say, have less

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Speaker 1: of an opportunity to keep control of your party. McCain

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Speaker 1: find gold was supposed to clean things up, and instead

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Speaker 1: it helped create the modern superPAC system that is absolutely

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Speaker 1: destructive to the political campaign system as we know it.

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Speaker 1: Every single reform I've seen tried created a workaround that

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Speaker 1: became made the problem worse. So you get to the

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Speaker 1: point you're like, well, just go find your you know,

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Speaker 1: And you saw there was no neither party would ever

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Speaker 1: have a permanent advantage on money, you know, because that's

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Speaker 1: the way markets work, right, When one one side's up,

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Speaker 1: the other side finds it finds disgruntled rich people to

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Speaker 1: help them, right, And so there was an uneasy balance

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Speaker 1: that you would see in this, and so you thought, well,

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Speaker 1: at least it's fair, it's ugly, it's gross, but at

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Speaker 1: least it's balanced between the two parties for time. So

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Speaker 1: it was going to be messy, it was going to

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Speaker 1: be imperfect, but ultimately it was probably unfixable, especially once

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Speaker 1: the courts decided that money was speech, so then you

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Speaker 1: had to have a constitutional moment, and what the hell

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Speaker 1: would that constitutional moment look like? But I do think

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Speaker 1: we missed something along the way because when we pushed

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Speaker 1: big donors out of the parties, this was a I

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Speaker 1: think this, you know, I have you know, McCain fine gold.

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Speaker 1: And there were plenty of detractors of McCain fine gold

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Speaker 1: because they just simply wanted more big money in politics.

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Speaker 1: But there were other detractors of McCain fine gold who

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Speaker 1: worried it would weaken them two political parties. And I

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Speaker 1: think those folks have proven to be right. And let

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Speaker 1: me explain, we didn't just move money. When we got

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Speaker 1: rid of money big money checks being written to political

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Speaker 1: parties directly, we actually removed one of the only guard

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Speaker 1: rails in vetting candidates that we had. When you take

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Speaker 1: the parties out of the candidate vetting business. And you

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Speaker 1: do this when you no longer allow them to have

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Speaker 1: the financial resources to help candidates win, then you had

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Speaker 1: real consequences to what kinds of candidates would suddenly pop

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Speaker 1: up for all of their flaws, and there were plenty.

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Speaker 1: With the party organizations, they did serve a kind as

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Speaker 1: kind of a filter. Wasn't a perfect filter, It wasn't

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Speaker 1: always a fair filter, but they would ask basic questions

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Speaker 1: like is this person stable? Do they have good judgment?

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Speaker 1: Can they handle power? Can they handle stress? Sometimes just

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Speaker 1: the basic vetting process and an HR department would have

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Speaker 1: And because that's where you had to get your resources

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Speaker 1: and your money, you as the candidate sort of where

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Speaker 1: you kind of you had to apply to the parties,

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Speaker 1: if you will, unofficially, and the parties had a stake

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Speaker 1: in the long term health of the coalition. They couldn't

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Speaker 1: just get behind somebody that could win now if they

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Speaker 1: thought that person's reputation could end up harming the overall

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Speaker 1: reputation of the party itself. But now well, that function

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Speaker 1: has been entirely outsourced, and it's been outsourced to donor networks,

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Speaker 1: to ideological entrepreneurs, to outside groups, and those actors aren't

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Speaker 1: asking the same questions that leaders of the two actual

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Speaker 1: political parties used to ask of their candidates. They don't

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Speaker 1: ask is this person fit? They're asking can this person win?

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Speaker 1: And will this person be useful, useful to fund, useful

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Speaker 1: to protect, useful to stop something. They have their own incentive.

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Speaker 1: They're looking for somebody that aligns with them on a

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Speaker 1: specific issue, specific topic of issue focus. Right, So that

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Speaker 1: then Trump's character it, Trump's ethics, Trump's morals, and Trump branding. Right,

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Speaker 1: It's a completely different screening mechanism and it produces a

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Speaker 1: completely different kind of politics. Then you layer on Citizens United,

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Speaker 1: and now the system isn't just adaptive. It's protected. Political

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Speaker 1: spending becomes speech, and suddenly meaningful restrictions are almost impossible

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Speaker 1: without a constitutional fight. So for a long time I

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Speaker 1: thought this is it, this is the system. Until recently

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Speaker 1: that is because something has changed. There's always a tipping point, right,

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Speaker 1: there's always, you know, everything in moderation, But eventually you're

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Speaker 1: not moderating your habits. You've tipped. So let me give

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Speaker 1: you a moment where I clicked for me, and I

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Speaker 1: keep coming back to this, and I bring it up

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Speaker 1: in a lot of my appearances now and I'm going

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Speaker 1: to continue to do so. When Chuck Schumer reportedly told

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Speaker 1: fellow Democratic senators to ease up on their opposition to

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Speaker 1: the crypto industry, not because they changed their minds and

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Speaker 1: they saw that crypto was going to be this incredible,

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Speaker 1: maybe this would be a helpful tool in the financial sector,

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Speaker 1: but because of the political firepower of a singular super

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Speaker 1: pack called fair Shake, these were huge players in Illinois,

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Speaker 1: and by the way, they get their ask kicked in Illinois,

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Speaker 1: they did not have a good night for what it's worth.

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Speaker 1: But think about that elected officials being told to soften

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Speaker 1: their positions on a specific issue because an industry simply

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Speaker 1: has too much money to challenge them. That's not influence,

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Speaker 1: that's not persuasion, that's coersion. It's policy extortion. And once

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Speaker 1: you see that clearly, then all the stuff starts to

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Speaker 1: look differently, because what we're dealing with now is not

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Speaker 1: just a lot of money in politics. It is something bigger.

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Speaker 1: It's the shift from candidate centered politics to donor centered politics.

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Speaker 1: And this is what was so crystal clear about all

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Speaker 1: of the Illinois primaries that happened earlier this week, and

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Speaker 1: it wasn't just in the Senate race. It was also

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Speaker 1: in these house races, where every single candidate came with

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Speaker 1: a descriptor that said the fair shake back candidate, the

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Speaker 1: AI back candidate, the APAC back candidate, this back candidate. Right.

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Speaker 1: It was never just about the candidate, even in Juliana

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Speaker 1: Stratton's case, who didn't have one big industry behind her,

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Speaker 1: she had a big billionaire governor behind her. She was

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Speaker 1: Governor Pritzker's candidate, right, But it was not about the candidates.

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Speaker 1: It was about their supporters, about the donors. So now

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Speaker 1: there was a specific reason why Illinois became kind of

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Speaker 1: ground zero for this moment. Right. It's a very blue state,

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Speaker 1: and they had a bunch of elderly members of Congress

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Speaker 1: who finally decided to retire, the big one being Dick Durbin. Right,

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Speaker 1: you got elected in ninety six, you know, by the way,

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Speaker 1: for what it's worth, I think if you were elected

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Speaker 1: to office in the twentieth century, you probably shouldn't be

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Speaker 1: seeking reelection in twenty six. And if you do, don't

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Speaker 1: be surprised if you get primaried and you have a problem.

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Speaker 1: But I digress. So Dick Derbin retires there's an open

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Speaker 1: seat deep blue state, which means the primary becomes the

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Speaker 1: election and it's not just an election for six years.

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Speaker 1: Dick Derbin got elected in ninety six and was there

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Speaker 1: for thirty years, worked his way up in the leadership,

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Speaker 1: number two in leadership. So this is a very I mean,

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Speaker 1: that's what you're investing in. You're not just investing in

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Speaker 1: one six year two. You're potentially investing in one of

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Speaker 1: the next leaders of the United States Senate over a generation.

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Speaker 1: So if you're you've got interest before Congress, this is

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Speaker 1: a valuable asset to acquire, i e. Having a senator

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Speaker 1: that may feel beholden to your industry. So if you're

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Speaker 1: that interest group and you think you can influence this primary,

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Speaker 1: you may be buying influence for a generation. So what

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Speaker 1: did voters get? Though? They didn't get a traditional campaign,

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Speaker 1: They didn't get a real debate between the candidates. You know,

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Speaker 1: in fact, if you didn't have one of these things yet,

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Speaker 1: it was really hard for the candidates. I never felt

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Speaker 1: like I got to know the candidates. I only knew

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Speaker 1: them through their donors and through who their supporters were.

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Speaker 1: And it turned into a proxy war. Right, you had

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Speaker 1: crypto money, AI money, a pack, link money, billionaire money, governor,

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Speaker 1: money front group, shell packs, you name it. By the

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Speaker 1: end of it, voters knew what these interests wanted, perhaps,

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Speaker 1: but did they really know what kind of candidate they

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Speaker 1: were getting? Now. I think in Stratton she found a

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Speaker 1: way to break through, interestingly enough, because she went viral

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Speaker 1: with an ad that didn't err on mainstream television because

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Speaker 1: you'd had to bleep it out too much. But it

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Speaker 1: was the F Trump at and if you haven't seen it,

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Speaker 1: I encourage you to go see it. During our livestream,

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Speaker 1: we aired a vision of it, but it's just a

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Speaker 1: whole bunch of voters saying F Trump, and then Stratton says,

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Speaker 1: I'm not saying it. But it was her way of

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Speaker 1: basically virtue signaling, Hey, she's going to be a fighter.

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Speaker 1: She wants to punch the bully in the nose. And

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Speaker 1: I think it mattered. It also mattered that the governor,

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Speaker 1: I think is popular with rank and filed Democrats because

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Speaker 1: he's been fighting Trump and he's been you know what,

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Speaker 1: Gavin Newsom has gotten a lot more credit for arguably

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Speaker 1: Pritzker's been doing before. Newsom thought it was a cool

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Speaker 1: way to do. But we still had something odd take

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Speaker 1: place this week in Illinois in that voters again I think,

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Speaker 1: ended up having to select candidates based on what third

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Speaker 1: party groups create. The character of third party groups were

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Speaker 1: created by them. So we're watching messages written by people

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Speaker 1: who may never actually have been on the ballot and

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Speaker 1: will never be on the ballot. And here's the part

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Speaker 1: that should bother everyone. These outside groups, they often don't

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Speaker 1: even campaign on the issue they.

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Speaker 2: Actually care about.

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Speaker 1: Right. A crypto group may never mention Crypto, An AI

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Speaker 1: group may never mention AI entirely. An Israel focused group

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Speaker 1: may decide that's too politically complicated to lead with. So

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Speaker 1: what do they do? They find another issue, immigration, crime, corruption, ideology,

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Speaker 1: and they use that as the delivery system. So voters

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Speaker 1: think they're watching one debate when they're actually being moved

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Speaker 1: on to another. And that's not persuasion. That becomes misdirection. Right,

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Speaker 1: And the candidates don't really feel accountable to it because

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Speaker 1: in some ways they're not. They can't control these outside groups,

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Speaker 1: and the outside groups have no accountability because none of

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Speaker 1: us know who their donors are in time to cover

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Speaker 1: it before the election. Having good life insurance is incredibly important.

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Speaker 1: I know from personal experience. I was sixteen when my

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Speaker 1: father passed away. We didn't have any money. He didn't

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Speaker 1: leave us in the best shape. My mother single mother,

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Speaker 1: now widow, myself sixteen trying to figure out how am

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Speaker 1: I going to pay for college and lo and behold,

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Speaker 1: my dad had one life insurance policy that we found

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Speaker 1: wasn't a lot, but it was important at the time,

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Speaker 1: and it's why I was able to go to college.

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Speaker 1: Little did he know how important that would be in

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Speaker 1: that moment. Well, guess what. That's why I am here

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00:19:26,440 --> 00:19:29,199
Speaker 1: to tell you about Etho's life. They can provide you

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Speaker 1: with peace of mind knowing your family is protected even

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00:19:32,440 --> 00:19:35,320
Speaker 1: if the worst comes to pass. Ethos is an online

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00:19:35,359 --> 00:19:39,080
Speaker 1: platform that makes getting life insurance fast and easy, all

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00:19:39,080 --> 00:19:42,160
Speaker 1: designed to protect your family's future in minutes, not months.

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Speaker 1: There's no complicated process and it's one hundred percent online.

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Speaker 1: There's no medical exam require you just answer a few

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Speaker 1: health questions online. You can get a quote in as

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00:19:51,800 --> 00:19:53,840
Speaker 1: little as ten minutes, and you can get same day

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00:19:53,880 --> 00:19:57,879
Speaker 1: coverage without ever leaving your home. You can get up

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00:19:57,880 --> 00:20:00,359
Speaker 1: to three million dollars in coverage, and some policy start

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00:20:00,400 --> 00:20:02,359
Speaker 1: as low as two dollars a day that would be

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00:20:02,400 --> 00:20:06,120
Speaker 1: billed monthly. As of March twenty twenty five, Business Insider

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Speaker 1: named Ethos the number one no medical exam instant life

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00:20:09,680 --> 00:20:14,320
Speaker 1: insurance provider. So protect your family with life insurance from Ethos.

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Speaker 1: Get your free quoted Ethos dot com slash chuck. So

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00:20:18,200 --> 00:20:23,399
Speaker 1: again that's Ethos dot com slash chuck. Application times may

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00:20:23,480 --> 00:20:26,240
Speaker 1: vary and the rates themselves may vary as well, but

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00:20:26,320 --> 00:20:29,200
Speaker 1: trust me, life insurance is something you should really think

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Speaker 1: about it, especially if you've got a growing family. So

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00:20:35,359 --> 00:20:37,600
Speaker 1: as a candidate, you weirdly kind of stuck because you

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Speaker 1: can't coordinate with the groups, and so they get pulled

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Speaker 1: into campaigns they didn't design. They just sort of participate

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Speaker 1: into a campaign that was created by an outside group

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Speaker 1: on terrain. They didn't choose answering for messages they didn't write.

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Speaker 1: So the whole idea of independent spending becomes part of

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Speaker 1: the problem. And this is where the loss of party

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Speaker 1: control I think matters a lot, because parties used to

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Speaker 1: have to think about the entire electorate, the whole coalition,

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Speaker 1: long term consequences. Now we didn't just decentralize money. We

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Speaker 1: decentralized responsibility, and we hollowed out the institutions and had

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Speaker 1: to care about more than one donor's obsession, which brings

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Speaker 1: us to the core problem inanimity. If you want to

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Speaker 1: vote in secret, you should. The secret ballot is sacred,

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Speaker 1: that's a fundamental right. But if you want to spend

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Speaker 1: millions influencing everyone else's vote, sorry, you don't deserve secrecy.

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Speaker 1: You need to put your name on it immediately, not

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Speaker 1: on some tax reform through a LLC six months later,

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Speaker 1: in real time, in plain English. No shell companies, no

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Speaker 1: front groups, no hiding three layers deep, stand by your money.

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Speaker 1: In fact, let me make it simple, take a page

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Speaker 1: from NASCAR. If you want to spend big money in politics,

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Speaker 1: but the donor on the hood, every ad, every mailer,

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Speaker 1: every digital buy, because that's the trade off. Influence comes

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Speaker 1: with visibility. You want to have influence, everybody needs to

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Speaker 1: know it with her democracy. It's on the ballot, and

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Speaker 1: it needs to be put on the ballot now. Even

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Speaker 1: if that doesn't solve the whole problem, because the deeper

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Speaker 1: issue is what this system does to candidates. It doesn't

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Speaker 1: just reward certain positions, it punishes others. So candidates learn

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Speaker 1: they learn what fights are too expensive, like Crypto apparently,

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Speaker 1: so they soften, they go quiet, they delay, or they

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Speaker 1: stand down entirely not because they've been persuaded, but because

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Speaker 1: they understand the cost that comes with dissent, which in

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Speaker 1: some ways is what they Crypto. I mean, this is

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Speaker 1: what they've done. They've amassed such a financial juggernaut and

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Speaker 1: fair shape that they just want to intimidate politicians into

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Speaker 1: legalizing what is a questionable what many people find questionable

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Speaker 1: in its usefulness. So once that happens, the problem isn't

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Speaker 1: just money in politics. It's that money is defining the

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Speaker 1: boundaries of politics, what can be said, what can't be said,

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Speaker 1: what gets debated, what gets avoided. And here's the thing,

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Speaker 1: this is no longer just a left wing complaint. I'm

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Speaker 1: now hearing it from Republicans, free market conservatives, people with

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Speaker 1: their own scars from dark money, starting to say this

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Speaker 1: out loud. And that's new. And this is why I

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Speaker 1: think why we might have hit a tipping point where

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Speaker 1: maybe the public is ready to do something about it,

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Speaker 1: and maybe the politicians are going to grow a spine

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Speaker 1: and do something about it, because the scale here is undeniable.

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Speaker 1: Not that long ago, billionaire money was a rounding error.

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Speaker 1: I'm not kidding. I mean, you've seen it. It was

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Speaker 1: barely one percent of campaign money came from billionaires pre

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Speaker 1: Citizens United. Now it's approaching one out of every five

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Speaker 1: dollars spent on federal campaigns comes from a billionaire. We

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Speaker 1: are moving towards something new, but it looks like institutionalized

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Speaker 1: billionaire politics, a political gilded age. Now, to be clear,

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Speaker 1: this doesn't mean every candidate backed by wealthy interest is corrupt.

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Speaker 1: American politics has always had patrons, but the structure of

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Speaker 1: it matters, right, and the structure we have now encouraged

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Speaker 1: voters to believe candidates are simply stand ins for their donors,

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Speaker 1: and that perception alone is what is so corrosive, and

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Speaker 1: it creates a barrier to entry that should worry all

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Speaker 1: of us. We got rid of poll taxes for a reason.

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Speaker 1: You can't charge people for access to a constitutional right.

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Speaker 1: But we've built something similar on the candidate side. A

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Speaker 1: system we're running for office seriously requires access to wealth

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Speaker 1: patrons or donor networks. That's a shadow tax on a candidacy. Now,

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Speaker 1: candidates will tell you fairly that they didn't write these

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Speaker 1: rules and they're right, they didn't. But a system can

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Speaker 1: be rational for the participants and still be unacceptable for

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Speaker 1: the public. And this is where we're at. The reforms

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Speaker 1: aren't mysterious, real time disclosure, no anonymous money, clear donor identification.

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Speaker 1: Maybe some structural fixes like runoffs or ranked choice voting

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Speaker 1: won't fix everything, but it will restore one basic idea

428
00:25:09,960 --> 00:25:12,360
Speaker 1: that voters should know who is trying to persuade them

429
00:25:12,400 --> 00:25:15,359
Speaker 1: and why, because in many cases, it's not the candidates

430
00:25:15,440 --> 00:25:19,200
Speaker 1: that are trying to persuade voters anymore. It's some anonymous

431
00:25:19,240 --> 00:25:24,920
Speaker 1: donor who's funding that candidate. So the danger now isn't

432
00:25:24,960 --> 00:25:29,640
Speaker 1: that money influences outcomes. It's that it defines the menu

433
00:25:29,960 --> 00:25:34,679
Speaker 1: of choices itself, Like you don't even know there's an

434
00:25:34,720 --> 00:25:37,800
Speaker 1: alternative because it doesn't have the funding to present itself

435
00:25:37,840 --> 00:25:41,399
Speaker 1: on your menu of options before. It's like what happens

436
00:25:41,440 --> 00:25:44,359
Speaker 1: in Iran? Right, you know, yes, it's a democracy, but

437
00:25:44,400 --> 00:25:46,439
Speaker 1: the regime decides who gets to be on the ballot.

438
00:25:47,680 --> 00:25:49,959
Speaker 1: So is it really a choice in anybody that is

439
00:25:50,040 --> 00:25:52,520
Speaker 1: you know, any presidential candidate that's calling for actual, small

440
00:25:52,600 --> 00:25:55,920
Speaker 1: de democratic reform, they somehow don't make the ballot that's

441
00:25:56,040 --> 00:25:59,639
Speaker 1: essentially what we're seeing here, donors deciding who's viable, who's not,

442
00:26:00,040 --> 00:26:04,200
Speaker 1: what's debated, and what gets dropped. That's how democracy gets

443
00:26:04,280 --> 00:26:08,720
Speaker 1: reshaped into a kleptocracy, quietly before a single vote is

444
00:26:08,720 --> 00:26:12,120
Speaker 1: even cast. And that's why this has finally potentially become

445
00:26:12,160 --> 00:26:15,000
Speaker 1: a voting issue, not because reform is easy, but because

446
00:26:15,040 --> 00:26:16,800
Speaker 1: voters are starting to see the system for what it

447
00:26:16,880 --> 00:26:21,600
Speaker 1: is in Illinois. It's not the exception, it's just a warning.

448
00:26:23,160 --> 00:26:27,480
Speaker 1: And it's interesting because Illinois features a billionaire governor, a

449
00:26:27,520 --> 00:26:33,440
Speaker 1: billionaire governor who's tried to fight some of these other billionaires.

450
00:26:35,680 --> 00:26:38,560
Speaker 1: And you know, this feeds into a notion and this

451
00:26:38,640 --> 00:26:40,360
Speaker 1: is why I think that you know, hey, look we're

452
00:26:40,359 --> 00:26:44,560
Speaker 1: going to look one. One primary does not make a

453
00:26:44,600 --> 00:26:47,360
Speaker 1: presidential candidate, but it is a data point that matters.

454
00:26:48,800 --> 00:26:57,280
Speaker 1: And you know, the f Trump add it's possible that

455
00:26:57,359 --> 00:26:59,560
Speaker 1: you have a group of Democrats who say, well, this

456
00:26:59,640 --> 00:27:05,840
Speaker 1: system so rigged that maybe they've got to find their

457
00:27:05,840 --> 00:27:10,280
Speaker 1: billionaire to fight the other billionaires. And I'm not just

458
00:27:10,320 --> 00:27:15,440
Speaker 1: making this up. One of you, my substact reader, made

459
00:27:15,480 --> 00:27:20,399
Speaker 1: a comment on my substack column that was that was

460
00:27:20,440 --> 00:27:24,840
Speaker 1: similarly themed here, and I just want to read you

461
00:27:24,880 --> 00:27:27,080
Speaker 1: to hand in hand here because I think it. I

462
00:27:27,119 --> 00:27:30,360
Speaker 1: think it's a It's illustrative of where I think there

463
00:27:30,400 --> 00:27:32,720
Speaker 1: is a faction of the Democratic Party, and I've, like

464
00:27:32,760 --> 00:27:35,200
Speaker 1: I said, I've heard other ad a progressive consultant tell

465
00:27:35,240 --> 00:27:37,960
Speaker 1: me I'm looking for my own trump right anyway, let

466
00:27:38,000 --> 00:27:39,600
Speaker 1: me read you to what one of my commenters to

467
00:27:40,040 --> 00:27:43,000
Speaker 1: on substack said, this is the most terrifying thing I've

468
00:27:43,040 --> 00:27:44,320
Speaker 1: read in a while, and I read a lot of

469
00:27:44,359 --> 00:27:47,280
Speaker 1: AI doomsday articles. What do we do about it? Writing

470
00:27:47,400 --> 00:27:50,479
Speaker 1: or calling your congress person feels inadequate. I've known campaign

471
00:27:50,520 --> 00:27:52,040
Speaker 1: finance was a problem for a long time, but it

472
00:27:52,080 --> 00:27:53,879
Speaker 1: feels like the only way to change it is to

473
00:27:53,880 --> 00:27:57,080
Speaker 1: become a billionaire, win elections and then fight the other billionaires.

474
00:27:57,359 --> 00:28:00,000
Speaker 1: What do normal citizens do short of pulling out the guillotine?

475
00:28:00,280 --> 00:28:02,280
Speaker 1: This was just a simple question to him, and what

476
00:28:02,359 --> 00:28:04,720
Speaker 1: I want to say to to Ryan asked who wrote

477
00:28:04,760 --> 00:28:08,280
Speaker 1: this in is you may need to you may need

478
00:28:08,320 --> 00:28:12,000
Speaker 1: to show your guillotine. I'm not saying you use the guillotine,

479
00:28:12,240 --> 00:28:14,600
Speaker 1: but you almost need to. Like it's like you walk

480
00:28:14,680 --> 00:28:17,119
Speaker 1: t you walk quietly and carry a big stick, like

481
00:28:17,160 --> 00:28:21,240
Speaker 1: you're guillotine you're your stick, or maybe you hire a

482
00:28:21,320 --> 00:28:23,960
Speaker 1: billionaire to do this, right, And that's I think the JB.

483
00:28:24,080 --> 00:28:27,680
Speaker 1: Pritzker pitch. Hey, I'm a billionaire. I know how these

484
00:28:27,720 --> 00:28:29,760
Speaker 1: guys work. And in some ways it's the it's the

485
00:28:29,760 --> 00:28:33,840
Speaker 1: mirror image of how Trump convinced a frustrated Republican base

486
00:28:33,920 --> 00:28:36,639
Speaker 1: that was tired of losing, tired of compromising, tired of

487
00:28:36,680 --> 00:28:38,560
Speaker 1: the mccains and the Romneys of the world, and they

488
00:28:38,560 --> 00:28:43,720
Speaker 1: wanted somebody who made them feel better and expressed what

489
00:28:43,760 --> 00:28:45,880
Speaker 1: they thought they couldn't say anymore, right, and that was

490
00:28:45,920 --> 00:28:51,280
Speaker 1: Donald Trump. Well, that's what the Juliana Stratton f Trump ad.

491
00:28:51,600 --> 00:28:55,040
Speaker 1: I think there's a there's it's somewhat analogous, right, there's

492
00:28:55,040 --> 00:28:57,560
Speaker 1: a group of Democrats who are tired of the ship, right,

493
00:28:57,960 --> 00:29:00,320
Speaker 1: and they're like, screw it, give me my own billion Aaron,

494
00:29:00,400 --> 00:29:03,360
Speaker 1: let me punch this bully in the house. And Pritzker

495
00:29:03,400 --> 00:29:05,560
Speaker 1: has been playing this role for quite some time. And

496
00:29:05,800 --> 00:29:09,040
Speaker 1: you know, I've been skeptical that the answer to the

497
00:29:09,080 --> 00:29:11,760
Speaker 1: Trump eras for Democrats to go find their own billionaire. Right.

498
00:29:11,880 --> 00:29:13,360
Speaker 1: This is why I've been a little skeptical of the

499
00:29:13,360 --> 00:29:16,720
Speaker 1: Mark Cuban idea, a little skeptical of the Pritzker idea,

500
00:29:17,440 --> 00:29:21,360
Speaker 1: but watching it in action in you seeing how much

501
00:29:21,520 --> 00:29:24,720
Speaker 1: money and how big these entities are. You know, it

502
00:29:24,800 --> 00:29:27,680
Speaker 1: took a rich guy named Teddy Roosevelt to take on

503
00:29:27,760 --> 00:29:30,920
Speaker 1: the big rich guys, right. It took a rich guy

504
00:29:30,920 --> 00:29:33,880
Speaker 1: in FDR to build the social safety net for the

505
00:29:33,880 --> 00:29:38,000
Speaker 1: working class. It was a rich guy that working class

506
00:29:38,040 --> 00:29:40,840
Speaker 1: America the last ten years has turned to or want

507
00:29:40,840 --> 00:29:42,400
Speaker 1: to be rich guy, depending on your point of view

508
00:29:42,400 --> 00:29:45,800
Speaker 1: of when Trump actually acquired actual wealth. But it doesn't matter,

509
00:29:45,920 --> 00:29:52,800
Speaker 1: perceive Perception is reality in this case. And so I

510
00:29:52,920 --> 00:29:54,960
Speaker 1: know this, Like you know, I always remind people I

511
00:29:55,000 --> 00:29:56,800
Speaker 1: cover politics as it as it is, not as I

512
00:29:56,880 --> 00:29:59,160
Speaker 1: wish it were. I'm not sure this is a good

513
00:29:59,160 --> 00:30:01,840
Speaker 1: long term solution for where we're headed as a country.

514
00:30:02,640 --> 00:30:07,320
Speaker 1: But I also it's possible. This is a this is something,

515
00:30:07,600 --> 00:30:09,720
Speaker 1: this is something that has to be tried first before

516
00:30:09,760 --> 00:30:12,440
Speaker 1: the next thing gets tried. Right, And if you you know,

517
00:30:12,480 --> 00:30:14,560
Speaker 1: I always like to put my shove in the shoes

518
00:30:14,600 --> 00:30:17,040
Speaker 1: of somebody fifty years from now looking back on this

519
00:30:17,120 --> 00:30:19,520
Speaker 1: era we're living through, and how will they see it?

520
00:30:19,560 --> 00:30:25,360
Speaker 1: What will it look like? And you know, you know

521
00:30:25,400 --> 00:30:27,760
Speaker 1: I have a theory that we're we're going to we're

522
00:30:27,800 --> 00:30:29,640
Speaker 1: probably going to have two or three more one term

523
00:30:29,680 --> 00:30:32,920
Speaker 1: presidents before we have a president that's able to sort

524
00:30:32,920 --> 00:30:36,480
Speaker 1: of solidify the country enough to earn a second term.

525
00:30:36,520 --> 00:30:38,080
Speaker 1: And that's when, you know, we'll have turned the page

526
00:30:38,080 --> 00:30:41,200
Speaker 1: on this era until we get there. So we've had

527
00:30:41,240 --> 00:30:42,760
Speaker 1: three in a row. You know, we didn't. We went

528
00:30:42,760 --> 00:30:45,040
Speaker 1: through the entire twentieth century without three one term presidents

529
00:30:45,040 --> 00:30:49,160
Speaker 1: in a row. So I kind of think we're you

530
00:30:49,280 --> 00:30:51,840
Speaker 1: got to go through these stages, right, and so you know,

531
00:30:51,920 --> 00:30:54,440
Speaker 1: you can see this right if down the road we

532
00:30:54,480 --> 00:30:56,640
Speaker 1: get you know, the next Eisenhower becomes president, say in

533
00:30:56,680 --> 00:30:59,440
Speaker 1: twenty thirty six, but we have a one term president

534
00:30:59,480 --> 00:31:02,200
Speaker 1: in twenty eight to one term president in thirty two,

535
00:31:02,240 --> 00:31:04,400
Speaker 1: et cetera. And like, okay, what you know, what what

536
00:31:04,480 --> 00:31:07,080
Speaker 1: will the explanation be? And it be something like, well,

537
00:31:07,880 --> 00:31:11,600
Speaker 1: you know, the frustrated Americans they kept they kept voting,

538
00:31:11,680 --> 00:31:13,760
Speaker 1: you know, they kept looking for something different, and they

539
00:31:13,800 --> 00:31:16,000
Speaker 1: didn't like it, and they voted out. You know, the Democrats,

540
00:31:16,040 --> 00:31:20,600
Speaker 1: they tried the conciliator candidate in Biden, and that didn't work.

541
00:31:20,680 --> 00:31:22,840
Speaker 1: Then they tried you know, if they go with the

542
00:31:23,760 --> 00:31:25,800
Speaker 1: a Pritzker. Let's say then it was oh, they tried

543
00:31:25,840 --> 00:31:28,960
Speaker 1: the fighter, the billionaire fighter to fight back and that

544
00:31:29,000 --> 00:31:30,720
Speaker 1: didn't work in the culture war, and then you know

545
00:31:30,760 --> 00:31:35,720
Speaker 1: who knows, So you know it is it's possible. We're

546
00:31:35,760 --> 00:31:39,440
Speaker 1: just in a this is the next step, you know,

547
00:31:39,520 --> 00:31:42,800
Speaker 1: before you get to whatever the whatever the solution is,

548
00:31:42,880 --> 00:31:44,480
Speaker 1: or maybe this turns out to be the solution, or

549
00:31:44,520 --> 00:31:47,720
Speaker 1: maybe a leader sort of morps into something bigger and

550
00:31:47,880 --> 00:31:50,480
Speaker 1: is able to rise above in a moment. You know, Well,

551
00:31:51,320 --> 00:31:55,280
Speaker 1: that's that's what we do. We find out sometimes after

552
00:31:55,320 --> 00:31:57,600
Speaker 1: we elect these presidents whether they're actually up to the job.

553
00:31:57,920 --> 00:32:00,200
Speaker 1: We never, let's be honest, we're never quite sure these

554
00:32:00,200 --> 00:32:02,480
Speaker 1: folks are up to the job until after they take office.

555
00:32:03,240 --> 00:32:05,280
Speaker 1: There's a lot of skepticism about Bill Clinton, and then

556
00:32:05,280 --> 00:32:07,920
Speaker 1: after a while you understood why he was there. Uh

557
00:32:08,000 --> 00:32:09,760
Speaker 1: did it with w did it with Obama? You know

558
00:32:09,760 --> 00:32:12,000
Speaker 1: there's always a moment where these people fill the suit,

559
00:32:12,720 --> 00:32:15,920
Speaker 1: right and you just sort of see it, you know.

560
00:32:15,960 --> 00:32:18,120
Speaker 1: I think Biden always struggled to fill the suit. I

561
00:32:18,120 --> 00:32:22,640
Speaker 1: think Trump, you know, is always acting, he's always playing

562
00:32:22,640 --> 00:32:25,440
Speaker 1: a role, so he struggles to fill the suit because

563
00:32:25,440 --> 00:32:30,320
Speaker 1: it's never a full. It's never quite quite what he is.

564
00:32:30,360 --> 00:32:33,600
Speaker 1: It's always a performance of some sort. You just have

565
00:32:33,640 --> 00:32:35,720
Speaker 1: to figure out what that performance is at any given time.

566
00:32:38,640 --> 00:32:43,600
Speaker 1: So it's uh, I'm always careful. I don't want to

567
00:32:43,640 --> 00:32:47,360
Speaker 1: be definitive here. Right. We had one primary where the

568
00:32:47,440 --> 00:32:51,360
Speaker 1: candidate who was preaching love instead of a fighter won

569
00:32:51,680 --> 00:32:53,840
Speaker 1: in Texas. Now this one we got the fighter, the

570
00:32:53,920 --> 00:32:54,719
Speaker 1: F Trump candidate.

571
00:32:54,800 --> 00:32:55,000
Speaker 2: Right.

572
00:32:56,640 --> 00:32:58,280
Speaker 1: By the way, every time I say F Trump, I'm

573
00:32:58,360 --> 00:33:00,400
Speaker 1: channeling my old Chris Matthews. He'll be saying, are you

574
00:33:00,400 --> 00:33:02,960
Speaker 1: saying F troop? You know some old TV show back

575
00:33:03,000 --> 00:33:05,520
Speaker 1: in the sixties. So for some of my older viewers

576
00:33:05,520 --> 00:33:07,400
Speaker 1: and listeners, that was a shout out for F Troop.

577
00:33:07,840 --> 00:33:09,240
Speaker 1: Now I'm not saying F troop when I say the

578
00:33:09,280 --> 00:33:14,320
Speaker 1: F Trump had. So, you know, two data points does

579
00:33:14,360 --> 00:33:18,080
Speaker 1: not make a trend, but it's an intriguing data point.

580
00:33:18,760 --> 00:33:21,360
Speaker 1: It's something I'm not going to dismiss about Pritzker. And

581
00:33:21,400 --> 00:33:24,720
Speaker 1: I think that Pritzker's proven to be politically savving his

582
00:33:24,760 --> 00:33:27,080
Speaker 1: own state, so we should be taking him seriously as

583
00:33:27,120 --> 00:33:29,160
Speaker 1: a presidential candidate. I wouldn't put him at the bottom

584
00:33:29,160 --> 00:33:31,400
Speaker 1: of the top tier anymore. I'd be putting them smack

585
00:33:31,480 --> 00:33:37,360
Speaker 1: dab in the contender section of this as we go forward,

586
00:33:39,400 --> 00:33:42,720
Speaker 1: all right, Like I said, coming up my conversation with

587
00:33:42,800 --> 00:33:44,840
Speaker 1: somebody who leads one of these super packs that I'm

588
00:33:44,880 --> 00:33:47,360
Speaker 1: talking about, and we get into whether this is a

589
00:33:47,400 --> 00:33:51,040
Speaker 1: healthy system and what should be And Brad Carson, longtime

590
00:33:51,040 --> 00:33:56,440
Speaker 1: Oklahoma Democrat, also gives his prescription of how Democrats could

591
00:33:56,640 --> 00:34:00,440
Speaker 1: to could improve their brand and read play in red

592
00:34:00,480 --> 00:34:05,040
Speaker 1: states like Oklahoma and elsewhere. So I think you'll find

593
00:34:05,040 --> 00:34:10,279
Speaker 1: the conversation interesting, provocative, and enlightening. And with that, let's

594
00:34:10,320 --> 00:34:12,759
Speaker 1: sneak in a break and when we come back, my

595
00:34:12,880 --> 00:34:20,760
Speaker 1: conversation with about AI influencer politics and the Democratic Party

596
00:34:20,920 --> 00:34:28,440
Speaker 1: with Brad Carson. This episode of The Chuck Podcast is

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Speaker 1: Well everybody is trying to figure out is when it

624
00:36:00,400 --> 00:36:05,080
Speaker 1: comes to artificial intelligence, right, I think as consumers are

625
00:36:05,080 --> 00:36:07,840
Speaker 1: trying to figure out, how is this impacting our lives?

626
00:36:09,080 --> 00:36:11,760
Speaker 1: How is this going to impact our future of work.

627
00:36:12,400 --> 00:36:15,320
Speaker 1: If you've got older kids, you're wondering are you even

628
00:36:16,200 --> 00:36:19,920
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629
00:36:20,000 --> 00:36:23,680
Speaker 1: this new AI driven world. Governments are trying to figure out,

630
00:36:23,840 --> 00:36:29,360
Speaker 1: you know, how do we help this great technology come around,

631
00:36:30,239 --> 00:36:36,080
Speaker 1: but do so with some guardrails, considering how poorly the

632
00:36:36,160 --> 00:36:38,080
Speaker 1: same tech companies that are trying to bring us AI

633
00:36:38,200 --> 00:36:42,799
Speaker 1: brought us social media, and there certainly seems to be

634
00:36:42,840 --> 00:36:47,280
Speaker 1: disputes about that. And what's been interesting is is how

635
00:36:47,360 --> 00:36:51,759
Speaker 1: negative the country is becoming on AI artificial intelligence. And

636
00:36:51,800 --> 00:36:53,680
Speaker 1: I think there's a lot of fear out there. I

637
00:36:53,680 --> 00:36:56,799
Speaker 1: think the fear is understandable. I think the technology is remarkable.

638
00:36:56,880 --> 00:37:00,160
Speaker 1: I think, like many people, I think now we all

639
00:37:00,160 --> 00:37:02,600
Speaker 1: every day we use it more. Sometimes we don't even

640
00:37:02,600 --> 00:37:04,520
Speaker 1: fully realize how much we're using it, but we use

641
00:37:04,560 --> 00:37:08,520
Speaker 1: it more. But the fear factor is definitely gone up.

642
00:37:09,360 --> 00:37:11,279
Speaker 1: And in some ways that fear is driven by the

643
00:37:11,280 --> 00:37:14,239
Speaker 1: people that are bringing us these AI companies because they're

644
00:37:14,280 --> 00:37:16,760
Speaker 1: the ones that tell us, well, there's this small, small

645
00:37:16,840 --> 00:37:19,359
Speaker 1: chance that whatever we're developing is going to consume us all,

646
00:37:19,840 --> 00:37:22,359
Speaker 1: and you're sitting there going so why are we doing this?

647
00:37:24,480 --> 00:37:28,239
Speaker 1: So it is Look, the next ten years probably are

648
00:37:28,280 --> 00:37:33,080
Speaker 1: going to be defined politically by this battle of how

649
00:37:33,120 --> 00:37:38,080
Speaker 1: do we integrate AI into society and how do we

650
00:37:38,080 --> 00:37:40,960
Speaker 1: do it on our terms rather than on AI's terms.

651
00:37:40,960 --> 00:37:43,400
Speaker 1: So my guest today is a former member of Congress,

652
00:37:43,440 --> 00:37:46,400
Speaker 1: former Democrat Brad Carson from the state of Oklahoma, president

653
00:37:46,440 --> 00:37:51,960
Speaker 1: of Fulsea University, and he's president of Americans for Responsible Innovation.

654
00:37:53,560 --> 00:37:55,840
Speaker 1: So the idea is that he's trying to work on

655
00:37:55,920 --> 00:38:02,440
Speaker 1: trying to create some better conditions perhaps, and I say perhaps,

656
00:38:02,480 --> 00:38:08,279
Speaker 1: because we're what this conversation is about, of a regulatory

657
00:38:08,360 --> 00:38:10,560
Speaker 1: environment that could earn the trust of the public. Because,

658
00:38:10,560 --> 00:38:13,799
Speaker 1: as I point out, it's some very recent NBC News poll,

659
00:38:13,880 --> 00:38:19,520
Speaker 1: but this has been pretty consistent so far. Most Americans

660
00:38:19,600 --> 00:38:22,960
Speaker 1: see more negative coming from AI than positive. Now, we're

661
00:38:23,040 --> 00:38:26,200
Speaker 1: unique around the world. Most other Western democracies are a

662
00:38:26,200 --> 00:38:29,560
Speaker 1: bit more pro AI than we are. And I think,

663
00:38:29,719 --> 00:38:33,600
Speaker 1: like I said, the experiences of social media on this country,

664
00:38:33,600 --> 00:38:37,799
Speaker 1: in particular, the experience of what globalization did and the

665
00:38:37,880 --> 00:38:40,319
Speaker 1: fact that that's still a living memory for many of us.

666
00:38:40,880 --> 00:38:45,279
Speaker 1: So in many ways, Americans have earned their skepticism on this.

667
00:38:46,640 --> 00:38:48,320
Speaker 1: Brad Carson, Welcome to the podcast.

668
00:38:48,719 --> 00:38:50,360
Speaker 2: Thanks Chun, great to see you again.

669
00:38:51,080 --> 00:38:53,480
Speaker 1: So let's let me start with that. I want to

670
00:38:53,480 --> 00:38:57,160
Speaker 1: get into some overall politics, whether there's such thing as

671
00:38:57,200 --> 00:39:01,800
Speaker 1: an Oklahoma Democrat anymore, and we can discuss that, because

672
00:39:01,840 --> 00:39:04,640
Speaker 1: even then you were an outlier when you were in Congress.

673
00:39:06,200 --> 00:39:08,680
Speaker 1: But let's start with this. Tell me about your organization

674
00:39:09,880 --> 00:39:13,920
Speaker 1: and be transparent with me. Who's funding it, who's what

675
00:39:14,640 --> 00:39:17,360
Speaker 1: you know? Because I tell you we're in the middle.

676
00:39:17,440 --> 00:39:20,720
Speaker 1: There's so much money flowing into politics right now, coming

677
00:39:20,719 --> 00:39:24,239
Speaker 1: from a handful of people trying to influence the regulation

678
00:39:24,360 --> 00:39:27,480
Speaker 1: of AI. So tell me about organization and tell me

679
00:39:28,120 --> 00:39:28,719
Speaker 1: who's buying it.

680
00:39:29,200 --> 00:39:32,360
Speaker 2: So American's responsible innovation is now about two years old.

681
00:39:32,600 --> 00:39:35,160
Speaker 2: We're by partisan group. I'm a Democrat, I'm the president

682
00:39:35,200 --> 00:39:37,759
Speaker 2: of it. We have several Republicans who work for us,

683
00:39:37,880 --> 00:39:40,200
Speaker 2: and we take great pride in working across the aisle

684
00:39:40,600 --> 00:39:43,360
Speaker 2: because we believe AI should not be a partisan issue

685
00:39:43,520 --> 00:39:45,840
Speaker 2: and that it's some one that both parties have a

686
00:39:45,920 --> 00:39:49,839
Speaker 2: huge stake in managing well. We're funded by family foundations

687
00:39:49,920 --> 00:39:52,960
Speaker 2: or charities. We take no money from the tech sector

688
00:39:53,000 --> 00:39:56,160
Speaker 2: at all. So our biggest funders are groups like Coefficient Giving,

689
00:39:56,440 --> 00:39:59,160
Speaker 2: Ohmed you are a Packard Foundation and a number of

690
00:39:59,200 --> 00:40:02,240
Speaker 2: family offices. So we're independent of the tech sector entirely

691
00:40:02,600 --> 00:40:04,719
Speaker 2: and more often critical of them. But we believe that

692
00:40:04,760 --> 00:40:07,799
Speaker 2: AI can be powerful and transformative, and so we're not

693
00:40:08,200 --> 00:40:10,560
Speaker 2: We don't want to kill the golden goose either.

694
00:40:12,040 --> 00:40:14,760
Speaker 1: All Right, you say you're entirely independent from the tech sector,

695
00:40:14,800 --> 00:40:17,239
Speaker 1: and then you also mentioned the Packard family. I mean

696
00:40:17,280 --> 00:40:19,840
Speaker 1: that's part of Hewlett Packard. I mean I assume you

697
00:40:19,880 --> 00:40:22,200
Speaker 1: have some family offices that made money in the tech sector.

698
00:40:22,719 --> 00:40:24,839
Speaker 2: Sure, some people who gave give to us actually even

699
00:40:24,880 --> 00:40:27,440
Speaker 2: work for the labs today. They might work for OPAI

700
00:40:27,640 --> 00:40:30,319
Speaker 2: or Anthropy. We don't take any kind of corporate contributions

701
00:40:30,320 --> 00:40:32,479
Speaker 2: like you might see at other groups in Washington, DC.

702
00:40:34,520 --> 00:40:36,520
Speaker 1: Look the reason I asked that you've got We're in

703
00:40:36,560 --> 00:40:40,640
Speaker 1: the middle of primary season, and you see you literally

704
00:40:40,680 --> 00:40:44,279
Speaker 1: have super PACs that open AI is supporting versus a

705
00:40:44,280 --> 00:40:47,560
Speaker 1: super pac that Anthropic is supporting. Because they're actually not

706
00:40:47,640 --> 00:40:50,920
Speaker 1: always on the same page. When it comes to the

707
00:40:51,200 --> 00:40:55,920
Speaker 1: regular regulation issue. Do you do you guys have that

708
00:40:56,040 --> 00:40:57,640
Speaker 1: tension inside your organization.

709
00:40:58,680 --> 00:41:00,400
Speaker 2: We do have a bit of a tension of that.

710
00:41:00,440 --> 00:41:02,960
Speaker 2: Although you should know that that super pac network, of

711
00:41:02,960 --> 00:41:05,920
Speaker 2: which Anthropic is a contributor, I actually run that as

712
00:41:05,960 --> 00:41:08,839
Speaker 2: well as kind of something I do in addition to

713
00:41:08,880 --> 00:41:11,600
Speaker 2: my work as AARI, and that's a group we found

714
00:41:11,760 --> 00:41:14,120
Speaker 2: that kind of spun out of AARI and we raised

715
00:41:14,120 --> 00:41:16,320
Speaker 2: a lot of money for it, and then we convinced

716
00:41:16,320 --> 00:41:19,400
Speaker 2: Anthropic to contribute to it because to their credit, Anthropic,

717
00:41:19,520 --> 00:41:21,760
Speaker 2: like the other donors, believe that we should have reasonable

718
00:41:21,760 --> 00:41:23,960
Speaker 2: guard rails around that. So I'm very involved in the

719
00:41:23,960 --> 00:41:26,760
Speaker 2: politics of it, very involved in the Illinois Races today

720
00:41:26,800 --> 00:41:30,360
Speaker 2: as we tape this, but also involved to AARI and

721
00:41:30,480 --> 00:41:32,359
Speaker 2: kind of the advocacy work on the hill. So both

722
00:41:32,360 --> 00:41:33,280
Speaker 2: of those kinds of things.

723
00:41:33,920 --> 00:41:40,360
Speaker 1: Do you why should we Yeah, let me put it

724
00:41:40,360 --> 00:41:42,960
Speaker 1: this way, the amount of money you brought up the

725
00:41:43,000 --> 00:41:45,279
Speaker 1: Illinois races. By time people hear this, we will have

726
00:41:45,280 --> 00:41:48,680
Speaker 1: already had these primaries. But it's funny you bring up

727
00:41:48,680 --> 00:41:51,960
Speaker 1: the Illinois Races. I think it's I'm just I can't

728
00:41:51,960 --> 00:41:56,160
Speaker 1: believe the amount of money from outside groups that's involved

729
00:41:56,160 --> 00:41:58,920
Speaker 1: in the center race. Now I understand it. The primary

730
00:41:59,120 --> 00:42:01,320
Speaker 1: is the center race, right, The winner of the Democratic

731
00:42:01,320 --> 00:42:03,560
Speaker 1: primary has like a ninety five percent chance of being

732
00:42:03,600 --> 00:42:08,160
Speaker 1: the United States cent are barring some unforeseen event, scandal, etc.

733
00:42:08,880 --> 00:42:12,120
Speaker 1: So the game is the primary. But you were you

734
00:42:12,239 --> 00:42:15,480
Speaker 1: ran for office. Can you imagine having to run for

735
00:42:15,560 --> 00:42:19,560
Speaker 1: office now in this era of super PACs where you

736
00:42:19,680 --> 00:42:21,719
Speaker 1: may have a theory of the case of what kind

737
00:42:21,760 --> 00:42:25,680
Speaker 1: of campaign you'd run a run, but the outside group

738
00:42:25,719 --> 00:42:29,040
Speaker 1: that supposedly wants you to win has more money. And

739
00:42:29,080 --> 00:42:30,760
Speaker 1: if they say, you know, we don't like your messaging,

740
00:42:30,800 --> 00:42:34,560
Speaker 1: we're going to do another messaging, you're you no longer

741
00:42:34,600 --> 00:42:38,200
Speaker 1: have control of your own campaign. Have you? Can you

742
00:42:38,280 --> 00:42:40,239
Speaker 1: imagine what life would have been like for you as

743
00:42:40,280 --> 00:42:43,440
Speaker 1: a candidate under these under these conditions.

744
00:42:43,000 --> 00:42:44,759
Speaker 2: Well, I think it's one of the greatest changes in

745
00:42:44,800 --> 00:42:48,080
Speaker 2: American politics that most people don't appreciate the hard dollars

746
00:42:48,360 --> 00:42:52,680
Speaker 2: campaign raises, they're almost insignificant. You look at the Illinois primaries,

747
00:42:52,960 --> 00:42:56,840
Speaker 2: candidates they're often raising one hundred thousand, two hundred thousand dollars.

748
00:42:57,160 --> 00:42:59,800
Speaker 2: Super PACs are then spending four or five million dollars

749
00:43:00,200 --> 00:43:02,759
Speaker 2: or against you We're involved in a race in North

750
00:43:02,800 --> 00:43:05,960
Speaker 2: Carolina's fourth district. In the research triangle, each candidates spend

751
00:43:06,000 --> 00:43:08,640
Speaker 2: about one hundred thousand dollars. The super PACs spent a

752
00:43:08,680 --> 00:43:11,440
Speaker 2: couple of million on each side. So you see, happily

753
00:43:11,440 --> 00:43:13,879
Speaker 2: in American politics is in some ways you would even

754
00:43:13,960 --> 00:43:16,360
Speaker 2: have to raise money as a candidate. You could just

755
00:43:16,360 --> 00:43:18,439
Speaker 2: sit back in your house let the super PACs fight

756
00:43:18,480 --> 00:43:21,279
Speaker 2: it out. Because whatever you raise and asks hard it

757
00:43:21,440 --> 00:43:23,839
Speaker 2: is to raise when you're running for office, how exhausting

758
00:43:23,880 --> 00:43:27,440
Speaker 2: that is, it's going to be matched probably ten x

759
00:43:27,560 --> 00:43:31,240
Speaker 2: or more by the super PACs. So really extraordinary should

760
00:43:31,239 --> 00:43:32,120
Speaker 2: this should?

761
00:43:33,600 --> 00:43:35,880
Speaker 1: It doesn't sound like you think this is a good system.

762
00:43:36,000 --> 00:43:38,800
Speaker 1: Obviously they're working within the system that it is. I

763
00:43:38,840 --> 00:43:40,920
Speaker 1: always joke I cover politics as it is, not as

764
00:43:40,920 --> 00:43:44,680
Speaker 1: I wish it were, and you're participating in the system

765
00:43:44,719 --> 00:43:46,640
Speaker 1: as it is, perhaps not as you wish it were.

766
00:43:47,520 --> 00:43:52,279
Speaker 1: But my word, I mean this is if the candidates

767
00:43:52,800 --> 00:43:55,400
Speaker 1: aren't in charge of their messaging or their campaign, then

768
00:43:55,480 --> 00:43:56,280
Speaker 1: what's the point.

769
00:43:56,880 --> 00:43:59,600
Speaker 2: That's a great question. American democracy is really at stake

770
00:43:59,640 --> 00:44:02,359
Speaker 2: here the superPAC era. But you're going to really see

771
00:44:02,360 --> 00:44:04,640
Speaker 2: it manifested this cycle and the next one. You know,

772
00:44:04,719 --> 00:44:08,160
Speaker 2: Crypto pioneered this strategy. Apex very involved with it too.

773
00:44:08,480 --> 00:44:09,279
Speaker 2: Both of them have a hut.

774
00:44:09,440 --> 00:44:10,880
Speaker 1: You're not alone. I don't want to. You're right, I'm

775
00:44:10,920 --> 00:44:12,160
Speaker 1: picking on you because you're here.

776
00:44:12,480 --> 00:44:15,719
Speaker 2: No, Well, four or five of us were playing big

777
00:44:15,920 --> 00:44:18,400
Speaker 2: are super PACs at seventy five million dollars. I'd be

778
00:44:18,440 --> 00:44:20,759
Speaker 2: happy to stand down if everyone else would as well,

779
00:44:20,880 --> 00:44:24,000
Speaker 2: because it's really destroying American democracy, changing the way elections

780
00:44:24,000 --> 00:44:27,360
Speaker 2: are had. So it's a terrible system that we've to

781
00:44:27,560 --> 00:44:30,960
Speaker 2: Supreme Court, both Supreme Court and FEC interpretations of that

782
00:44:31,040 --> 00:44:33,799
Speaker 2: Supreme Court opinion. We permitted it to get completely out

783
00:44:33,800 --> 00:44:34,120
Speaker 2: of hand.

784
00:44:35,040 --> 00:44:37,720
Speaker 1: Look, when you served in Congress, do you think back

785
00:44:37,920 --> 00:44:44,319
Speaker 1: about the do you have any regrets collectively, not you

786
00:44:44,440 --> 00:44:46,960
Speaker 1: the individual member of Congress, but collectively, because it was

787
00:44:47,000 --> 00:44:49,400
Speaker 1: the entire era had a hands off approach on the Internet,

788
00:44:50,280 --> 00:44:53,120
Speaker 1: very hands off on regulating, you know. I mean, I

789
00:44:53,120 --> 00:44:55,440
Speaker 1: remember at one point John McCain advocating we should have

790
00:44:55,600 --> 00:44:58,000
Speaker 1: the Internet should be tax free forever, and I remember thinking,

791
00:44:58,040 --> 00:45:00,280
Speaker 1: you know, at some point that's not going to work,

792
00:45:00,520 --> 00:45:03,000
Speaker 1: and it didn't. The Internet shouldn't have any sales tax.

793
00:45:03,040 --> 00:45:04,719
Speaker 1: You know, at some point that's not going to work,

794
00:45:04,800 --> 00:45:08,440
Speaker 1: and it didn't right. But we had such a light

795
00:45:08,600 --> 00:45:15,040
Speaker 1: touch on the Internet and it worked until it didn't right.

796
00:45:15,160 --> 00:45:19,719
Speaker 1: Social media, to me, is the greatest failed experiment on

797
00:45:19,760 --> 00:45:22,759
Speaker 1: the human brain that is still ongoing. And I don't

798
00:45:22,760 --> 00:45:27,880
Speaker 1: know why we haven't stopped the experiment yet right looking back.

799
00:45:27,920 --> 00:45:30,480
Speaker 1: And the reason I'm asking it that way, because how

800
00:45:30,480 --> 00:45:33,240
Speaker 1: do we avoid the same mistakes with AI? And what's

801
00:45:33,280 --> 00:45:37,640
Speaker 1: something you think Congress and government should have done differently

802
00:45:37,680 --> 00:45:40,560
Speaker 1: in the late nineties and early adds with the Internet.

803
00:45:40,040 --> 00:45:42,080
Speaker 2: Because I would actually say we did more than just

804
00:45:42,160 --> 00:45:44,279
Speaker 2: not have a light or more than just a light touch.

805
00:45:44,520 --> 00:45:48,680
Speaker 2: We effectively immunized all of the Internet companies from any liability.

806
00:45:48,960 --> 00:45:51,560
Speaker 2: This is the famous section two thirty of the Communications

807
00:45:51,560 --> 00:45:53,560
Speaker 2: Decency Act. And so it wasn't that we just said

808
00:45:53,560 --> 00:45:55,520
Speaker 2: we're not going to regulate you. We said we will

809
00:45:55,560 --> 00:45:58,920
Speaker 2: immunize you from any claims that you defamed people, that

810
00:45:58,960 --> 00:46:01,480
Speaker 2: you hurt them in any way, that you intentionally inflicted

811
00:46:01,520 --> 00:46:06,040
Speaker 2: emotional distress, that you're liable for products liability, all of

812
00:46:06,040 --> 00:46:08,600
Speaker 2: those things. We actually told the companies you're free from

813
00:46:08,680 --> 00:46:11,160
Speaker 2: having to worry about that. That was in nineteen ninety

814
00:46:11,160 --> 00:46:13,600
Speaker 2: six at a time when only seven percent of the

815
00:46:13,600 --> 00:46:17,120
Speaker 2: people even had Internet. Google and Facebook were just a

816
00:46:17,160 --> 00:46:20,920
Speaker 2: gleam in their founder's eyes. So it was a terrible

817
00:46:20,960 --> 00:46:23,520
Speaker 2: air for us. We celebrate the thirtieth anniversary of that

818
00:46:23,640 --> 00:46:26,320
Speaker 2: this year. Well, we want to make sure with AI

819
00:46:26,440 --> 00:46:27,880
Speaker 2: is we don't do the same thing. So one of

820
00:46:27,920 --> 00:46:30,640
Speaker 2: the big fights in Washington, DC right now is about

821
00:46:30,719 --> 00:46:33,800
Speaker 2: the preemption of state laws. So a lot of the

822
00:46:33,880 --> 00:46:36,600
Speaker 2: venture capitalists Open AI has been in this camp that

823
00:46:36,680 --> 00:46:39,080
Speaker 2: we want to pre empt all state regulation of AI

824
00:46:39,800 --> 00:46:42,560
Speaker 2: in many ways, that's just two thirty reprized for the

825
00:46:42,600 --> 00:46:45,600
Speaker 2: AI age. Basically say be no law. We're going to

826
00:46:45,600 --> 00:46:48,759
Speaker 2: basically hold these companies unaccountable. And I think there's a

827
00:46:48,800 --> 00:46:50,839
Speaker 2: way to have your cake and eat it too by

828
00:46:50,880 --> 00:46:53,319
Speaker 2: saying we need some light touch regulation. They should be

829
00:46:53,360 --> 00:46:56,279
Speaker 2: held accountable for their harms, which allow the courts to

830
00:46:56,320 --> 00:46:59,719
Speaker 2: develop common law over the years, which is finally calibrated

831
00:46:59,760 --> 00:47:03,239
Speaker 2: to the actual risks that the AI systems present, rather

832
00:47:03,239 --> 00:47:05,480
Speaker 2: than like giving them a blanket immunity. That's what we

833
00:47:05,520 --> 00:47:07,719
Speaker 2: did to social media, and the stories that come out

834
00:47:07,719 --> 00:47:10,880
Speaker 2: of social media are obviously horrifying, and when those families

835
00:47:11,040 --> 00:47:15,640
Speaker 2: sue Facebook, TikTok or someone, they have no recourse at all.

836
00:47:15,960 --> 00:47:19,319
Speaker 2: That's a terrible system that obviously harms the family. It

837
00:47:19,320 --> 00:47:22,240
Speaker 2: gives them no redress, but doesn't make the companies fully

838
00:47:22,280 --> 00:47:25,400
Speaker 2: internalize the many costs are opposing on society.

839
00:47:25,920 --> 00:47:28,560
Speaker 1: Well, and I get, I mean, many of my listeners

840
00:47:28,600 --> 00:47:32,440
Speaker 1: know I have this pet peeve about Section two thirty,

841
00:47:32,760 --> 00:47:36,920
Speaker 1: specifically when I don't understand how it is any not

842
00:47:36,960 --> 00:47:40,080
Speaker 1: only that, I don't understand how it has any function

843
00:47:40,160 --> 00:47:44,120
Speaker 1: anymore for this reason, not that you know, yes, government

844
00:47:44,120 --> 00:47:46,680
Speaker 1: should have withdrawn it a while ago, but forget that

845
00:47:47,320 --> 00:47:54,839
Speaker 1: the second Facebook or Instagram or Google created an algorithm

846
00:47:56,120 --> 00:48:01,799
Speaker 1: to determine what I see and what gets fed to

847
00:48:01,920 --> 00:48:06,840
Speaker 1: me quicker. They have become a publisher. They are an editor.

848
00:48:06,880 --> 00:48:09,880
Speaker 1: They made the decision what goes above the fold, Brad,

849
00:48:10,320 --> 00:48:12,880
Speaker 1: and what goes below the fold in the old fashioned

850
00:48:12,880 --> 00:48:16,359
Speaker 1: news stand. That is a decision, it was not, you know,

851
00:48:16,880 --> 00:48:20,239
Speaker 1: and you're a publisher at that point. So I don't

852
00:48:20,320 --> 00:48:23,520
Speaker 1: understand how the courts have interpreted Section two thirty as

853
00:48:23,600 --> 00:48:26,280
Speaker 1: even being functional anymore for any of these entities.

854
00:48:27,080 --> 00:48:29,760
Speaker 2: It's a great question, and the use of algorithmic curation

855
00:48:30,560 --> 00:48:33,719
Speaker 2: is one of the kind of emerging questions. I think

856
00:48:33,719 --> 00:48:35,680
Speaker 2: you know, we've already talked about how the Supreme Court

857
00:48:35,760 --> 00:48:38,640
Speaker 2: bollock stuff campaign finance and brought us the superpack era.

858
00:48:39,280 --> 00:48:42,040
Speaker 2: Their interpretation of First Amendment law over the last few

859
00:48:42,120 --> 00:48:45,000
Speaker 2: years is equally troublesome because they now hold things like

860
00:48:45,040 --> 00:48:48,160
Speaker 2: the use of algorithm as being no different than you know,

861
00:48:48,160 --> 00:48:51,080
Speaker 2: when you were back in the editor of Hotline, back

862
00:48:51,120 --> 00:48:52,960
Speaker 2: when I first met you a long time ago. You're

863
00:48:53,000 --> 00:48:56,120
Speaker 2: making editorial decisions every day, right, that's covered by the

864
00:48:56,120 --> 00:48:58,640
Speaker 2: First Amendment. You can be for a candidate, you can

865
00:48:58,680 --> 00:49:01,560
Speaker 2: be against a candidate, you can write for against. The

866
00:49:01,560 --> 00:49:04,280
Speaker 2: Supreme Court now holds those kind of algorithms are equivalent

867
00:49:04,400 --> 00:49:07,239
Speaker 2: to that. That makes no sense to me. But as

868
00:49:07,280 --> 00:49:10,719
Speaker 2: long as that jurisprudence exists, right, it's very hard to

869
00:49:10,840 --> 00:49:13,680
Speaker 2: argue that algorithms are outside of Section two thirty is immunity.

870
00:49:13,800 --> 00:49:15,839
Speaker 2: So we have a problem with how the Supreme Court

871
00:49:15,880 --> 00:49:18,480
Speaker 2: is interpreting the First Amendment as it comes to like

872
00:49:18,520 --> 00:49:20,000
Speaker 2: these tech platforms as well.

873
00:49:20,600 --> 00:49:24,959
Speaker 1: No, look, it's a fair pushback on my pushback, which

874
00:49:25,000 --> 00:49:28,239
Speaker 1: is this First Amendment interpretation of an algorithm. But the

875
00:49:28,280 --> 00:49:32,280
Speaker 1: point is is that they've the initial instance of section

876
00:49:32,320 --> 00:49:34,759
Speaker 1: two thirty was, well, where they're not publishers, they're just

877
00:49:34,840 --> 00:49:38,080
Speaker 1: a platform that they somehow don't have any influence on

878
00:49:38,120 --> 00:49:41,000
Speaker 1: their platform. And while that might still be true of

879
00:49:41,000 --> 00:49:43,920
Speaker 1: our reddit, you know, in the way that Reddit works,

880
00:49:44,160 --> 00:49:46,960
Speaker 1: that is not true of X, that is not true

881
00:49:47,000 --> 00:49:51,360
Speaker 1: of Instagram. They you know, yes, you know, they don't

882
00:49:51,400 --> 00:49:54,640
Speaker 1: create the content, but they go out of their way

883
00:49:54,680 --> 00:49:58,279
Speaker 1: to make sure I see certain content based on my

884
00:49:59,320 --> 00:50:02,320
Speaker 1: profile that they have decided to suck up with data.

885
00:50:02,680 --> 00:50:06,360
Speaker 1: So that's why I'm that's where my you know what,

886
00:50:06,480 --> 00:50:08,920
Speaker 1: I don't understand of how they can then say no, no,

887
00:50:08,960 --> 00:50:10,799
Speaker 1: no, no no, we're just a plot. We're just in charge

888
00:50:10,800 --> 00:50:12,680
Speaker 1: of a platform. You can't hold us accountable for it.

889
00:50:13,000 --> 00:50:14,359
Speaker 2: I mean that shows you the danger of a two

890
00:50:14,440 --> 00:50:16,879
Speaker 2: thirty pass at a time when no one even understood what.

891
00:50:16,800 --> 00:50:18,480
Speaker 1: The Internet didn't know what they were passing.

892
00:50:18,520 --> 00:50:20,799
Speaker 2: So you pass these like vague terms that are in

893
00:50:20,880 --> 00:50:23,640
Speaker 2: the law, Courts are forced to interpret them, and right

894
00:50:23,719 --> 00:50:26,440
Speaker 2: courts go off on this or that tangent. And they

895
00:50:26,440 --> 00:50:28,680
Speaker 2: have a lot of money now, the social media companies do,

896
00:50:28,760 --> 00:50:31,160
Speaker 2: so they fight back in Congress with millions of dollars.

897
00:50:31,320 --> 00:50:33,680
Speaker 2: They all have super packs of their own and so

898
00:50:33,719 --> 00:50:35,640
Speaker 2: it's very hard to change. And so one of the

899
00:50:35,640 --> 00:50:38,480
Speaker 2: great lessons of two thirty for AI is like, don't

900
00:50:38,520 --> 00:50:41,200
Speaker 2: pass some kind of metal law before you even understand

901
00:50:41,200 --> 00:50:43,319
Speaker 2: like what's going to happen in five years, because then

902
00:50:43,320 --> 00:50:45,160
Speaker 2: you can't change it. You know, it's very hard to

903
00:50:45,239 --> 00:50:47,279
Speaker 2: politics to get these things reversed.

904
00:50:48,719 --> 00:50:52,680
Speaker 1: Well, this is what I love federal federalism. We have

905
00:50:52,719 --> 00:50:57,920
Speaker 1: fifty states, and it does seem as if it's a

906
00:50:58,280 --> 00:51:01,640
Speaker 1: we're The divide on whether states should be allowed to

907
00:51:01,680 --> 00:51:07,040
Speaker 1: regulate AI is I think an interesting fight because it's

908
00:51:07,080 --> 00:51:11,719
Speaker 1: not a left right divide. This really is a industry

909
00:51:11,840 --> 00:51:15,919
Speaker 1: versus everybody else fight. Right, you have Ron DeSantis, who

910
00:51:16,000 --> 00:51:19,920
Speaker 1: is who's marching forward on trying to get AI regulation

911
00:51:20,040 --> 00:51:22,759
Speaker 1: in the state of Florida, while Donald Trump's still trying

912
00:51:22,760 --> 00:51:25,920
Speaker 1: to give immunity to these companies. I imagine if you're

913
00:51:25,920 --> 00:51:28,200
Speaker 1: taking anthropic money, you're on the side of letting the

914
00:51:28,239 --> 00:51:30,200
Speaker 1: states give this a shot. First.

915
00:51:30,600 --> 00:51:33,279
Speaker 2: Yeah, we actually said we've always advocated for that. They've

916
00:51:33,280 --> 00:51:35,640
Speaker 2: brought it twice before Congress, and we led the coalition

917
00:51:35,719 --> 00:51:40,120
Speaker 2: to AARI to defeat that. Again. Republicans and Democrats Republican ags.

918
00:51:40,480 --> 00:51:45,400
Speaker 2: Sarah huckeby Standers was rallying Republican governors DeSantis. Steve Bannon

919
00:51:45,880 --> 00:51:49,239
Speaker 2: was on the Hustings like really active in this. So

920
00:51:49,280 --> 00:51:52,640
Speaker 2: it does transcend party label in some way, and really

921
00:51:52,640 --> 00:51:55,200
Speaker 2: it's a world now. I think only people actually for

922
00:51:55,320 --> 00:51:58,279
Speaker 2: this policy are like three people. They're a sixteen z

923
00:51:59,000 --> 00:52:03,040
Speaker 2: Anderson with the VC firm that Mark Andrews ben Horowitz

924
00:52:03,120 --> 00:52:06,000
Speaker 2: runs and the Open AI guys. That's really who's for it.

925
00:52:06,160 --> 00:52:09,160
Speaker 2: Anthropics not for it again, anthropics of the industry. They're

926
00:52:09,200 --> 00:52:12,279
Speaker 2: very divided. Anthropics says, well, we prefer to have a

927
00:52:12,280 --> 00:52:15,360
Speaker 2: comprehensive federal standard. That would be wonderful, but the absence

928
00:52:15,400 --> 00:52:17,360
Speaker 2: of that, you have to have the states do their work,

929
00:52:17,800 --> 00:52:19,840
Speaker 2: and so through a lot of divisions, and it's actually

930
00:52:19,880 --> 00:52:22,839
Speaker 2: just a few small people. Unfortunately, they have, you know,

931
00:52:22,920 --> 00:52:25,600
Speaker 2: billions of dollars and the ear of the White House

932
00:52:25,600 --> 00:52:28,319
Speaker 2: as we speak, because of the tech rights influence there

933
00:52:29,160 --> 00:52:31,120
Speaker 2: that they can get their way against really people in

934
00:52:31,200 --> 00:52:31,840
Speaker 2: both parties.

935
00:52:41,320 --> 00:52:44,120
Speaker 1: So, I mean, is this when you're when you're getting

936
00:52:44,120 --> 00:52:47,600
Speaker 1: involved in these campaigns. How much are you spending money

937
00:52:47,640 --> 00:52:49,440
Speaker 1: on the issue of AI itself and how much are

938
00:52:49,480 --> 00:52:52,040
Speaker 1: you just involved in helping somebody who you think will

939
00:52:52,040 --> 00:52:55,480
Speaker 1: be on your side in the in the in the

940
00:52:55,520 --> 00:52:56,960
Speaker 1: battle over regulating AAP.

941
00:52:57,360 --> 00:52:58,920
Speaker 2: So it's a bit of both. It's people we know

942
00:52:59,080 --> 00:53:01,040
Speaker 2: are going to be on our side, and then we

943
00:53:01,080 --> 00:53:04,000
Speaker 2: are spending some money on trying to socialize AI make

944
00:53:04,040 --> 00:53:06,760
Speaker 2: people more aware of it because right now many people

945
00:53:06,800 --> 00:53:09,000
Speaker 2: have a lot of concerns, but it's not the top

946
00:53:09,000 --> 00:53:10,320
Speaker 2: of mind for them in voting.

947
00:53:10,520 --> 00:53:12,520
Speaker 1: So are you surprised that how negative people are about this?

948
00:53:13,160 --> 00:53:15,080
Speaker 2: I know I'm not really because I can see it

949
00:53:15,120 --> 00:53:17,520
Speaker 2: even here in Oklahoma where I still live. You know,

950
00:53:17,680 --> 00:53:21,319
Speaker 2: people who are very Trump oriented, very conservative state. This

951
00:53:21,400 --> 00:53:23,799
Speaker 2: is the seventy to thirty Trump state. You know, I

952
00:53:23,800 --> 00:53:26,759
Speaker 2: don't know many liberal Democrats here, and many people are

953
00:53:26,800 --> 00:53:29,480
Speaker 2: fired up. We have a huge data center rebellion from

954
00:53:29,480 --> 00:53:32,759
Speaker 2: people who are deeply religious, conservative across the board Trump

955
00:53:32,880 --> 00:53:35,359
Speaker 2: voters and they don't want data centers, which is one

956
00:53:35,400 --> 00:53:38,319
Speaker 2: manifestation of this fight. And you know, we actually polled

957
00:53:38,360 --> 00:53:41,680
Speaker 2: a lot. You know, the only thing more unpopular than

958
00:53:41,680 --> 00:53:44,920
Speaker 2: Benjamin net and Yahoo in a Democratic primary electorate or

959
00:53:44,960 --> 00:53:48,440
Speaker 2: AI companies. It's kind of extraordinary, actually, And I think

960
00:53:48,480 --> 00:53:50,000
Speaker 2: you know what you said at the outset is actually

961
00:53:50,000 --> 00:53:52,880
Speaker 2: really telling every other country in the world. AI is

962
00:53:52,960 --> 00:53:55,680
Speaker 2: much more popular In China, something like eighty five percent

963
00:53:55,719 --> 00:53:58,680
Speaker 2: of the people are very positive about AI. So it's

964
00:53:58,680 --> 00:54:02,000
Speaker 2: not the technology itself it's unpopular. It's how it's interactive

965
00:54:02,000 --> 00:54:05,640
Speaker 2: with our somewhat dysfunctional political system. That's what makes it

966
00:54:05,680 --> 00:54:08,040
Speaker 2: so unpopular here. I think that does speak to the

967
00:54:08,120 --> 00:54:11,360
Speaker 2: need to really have like a better social contract with people.

968
00:54:11,680 --> 00:54:14,440
Speaker 2: You know, more people sense like this, the political system

969
00:54:14,440 --> 00:54:16,960
Speaker 2: can't be hijacked by a couple of people that you know,

970
00:54:17,040 --> 00:54:19,000
Speaker 2: we'll work against us. That's why I think what makes

971
00:54:19,040 --> 00:54:21,520
Speaker 2: it so unpopular here because we are an outlier in

972
00:54:21,520 --> 00:54:23,759
Speaker 2: that respect, and you the only explanation for it is

973
00:54:23,760 --> 00:54:26,280
Speaker 2: our unique kind of socio political dynamic.

974
00:54:26,960 --> 00:54:29,600
Speaker 1: Well, I hear you there. At the other two points,

975
00:54:29,600 --> 00:54:33,319
Speaker 1: I think there's no doubt it's the fear of our

976
00:54:33,360 --> 00:54:35,719
Speaker 1: politics and whether they can manage the moment. And I

977
00:54:35,800 --> 00:54:40,960
Speaker 1: certainly have those concerns. But you know that, I just

978
00:54:41,000 --> 00:54:44,560
Speaker 1: think trust in the tech companies is so low because

979
00:54:45,080 --> 00:54:46,960
Speaker 1: I don't think you know, social media is one of

980
00:54:47,000 --> 00:54:52,360
Speaker 1: these phenomenons that it really is turned into the smoking

981
00:54:52,360 --> 00:54:54,640
Speaker 1: of the twenty first century. We all know it's not

982
00:54:54,680 --> 00:54:58,120
Speaker 1: good for us. We all know it's unhealthy. We're desperate

983
00:54:58,160 --> 00:55:01,000
Speaker 1: to make sure our kids, don't. You know, We're like,

984
00:55:01,320 --> 00:55:03,239
Speaker 1: let's get it out of schools. You want to talk

985
00:55:03,280 --> 00:55:05,000
Speaker 1: about it something by partisan right, that a matter of

986
00:55:05,000 --> 00:55:07,680
Speaker 1: red state blue, get the social get the springs out

987
00:55:07,680 --> 00:55:12,799
Speaker 1: of the schools. Right, And yet we can't quit. We

988
00:55:12,880 --> 00:55:13,640
Speaker 1: all can't quit.

989
00:55:13,800 --> 00:55:13,960
Speaker 2: Right.

990
00:55:14,000 --> 00:55:18,920
Speaker 1: It's it powers economy. It helps to fuel this economy

991
00:55:18,960 --> 00:55:23,920
Speaker 1: in some ways, we don't know how to. We know

992
00:55:24,000 --> 00:55:25,640
Speaker 1: this is bad and we don't know how to stop it.

993
00:55:26,239 --> 00:55:29,920
Speaker 1: And I think the fear that's my theory, and that,

994
00:55:30,200 --> 00:55:32,160
Speaker 1: oh my god, if we do AI, then we'll never

995
00:55:32,239 --> 00:55:33,200
Speaker 1: be able to unwind this.

996
00:55:34,080 --> 00:55:36,360
Speaker 2: That's exactly right. I mean we know now from the

997
00:55:36,400 --> 00:55:39,920
Speaker 2: various leaks, for example, from Meta who know about things

998
00:55:39,960 --> 00:55:42,920
Speaker 2: they knew that they tolerated, that they were almost willing

999
00:55:42,920 --> 00:55:47,160
Speaker 2: to encourage behavior that is criminal and shocking in lots

1000
00:55:47,200 --> 00:55:49,880
Speaker 2: of ways, right, because it promoted engagement. You know, we

1001
00:55:50,000 --> 00:55:52,759
Speaker 2: know the AI companies, especially we've seen Chat GPT because

1002
00:55:52,760 --> 00:55:55,720
Speaker 2: it's the most consumer facing of all the AI products

1003
00:55:55,719 --> 00:55:59,879
Speaker 2: out there, more than Anthropic or Google's products are right,

1004
00:56:00,160 --> 00:56:02,960
Speaker 2: people can like misuse them and become addicted to them.

1005
00:56:03,000 --> 00:56:05,839
Speaker 2: We can lead people to self harm, I think, I mean,

1006
00:56:05,880 --> 00:56:08,160
Speaker 2: because you covered DC so much. There's a question like

1007
00:56:08,760 --> 00:56:11,160
Speaker 2: take the Kids Online Safety Act, which is a response

1008
00:56:11,200 --> 00:56:13,960
Speaker 2: to the social media problems. It passes the House and

1009
00:56:14,000 --> 00:56:18,120
Speaker 2: the Senate overwhelmingly. It gets bottled up in leadership. Why

1010
00:56:18,440 --> 00:56:20,920
Speaker 2: because they're on the phone with like meta you know,

1011
00:56:21,000 --> 00:56:23,640
Speaker 2: that's got millions of dollars to give to the superpacks,

1012
00:56:23,719 --> 00:56:27,400
Speaker 2: the majority and minority leadership packs, these kind of things.

1013
00:56:27,719 --> 00:56:30,200
Speaker 2: And so that's the dysfunction. It's like people know it

1014
00:56:30,560 --> 00:56:32,919
Speaker 2: and their politicians look kind of the rank and vile.

1015
00:56:32,960 --> 00:56:36,640
Speaker 2: They do support changes, but it gets bottled up because

1016
00:56:36,680 --> 00:56:39,680
Speaker 2: again a couple of phone calls from people you know

1017
00:56:39,840 --> 00:56:42,040
Speaker 2: really kind of like can can stranglehold it. That's a

1018
00:56:42,120 --> 00:56:45,400
Speaker 2: unique aspect of American politics. That's again about the money,

1019
00:56:45,480 --> 00:56:47,880
Speaker 2: and it's one of the terrible aspects of American politics.

1020
00:56:48,200 --> 00:56:51,120
Speaker 1: Well this is I mean, look, you keep coming back

1021
00:56:51,120 --> 00:56:53,400
Speaker 1: to something that I don't think is unfair to coming

1022
00:56:53,440 --> 00:56:56,520
Speaker 1: back to, which is as you know, here we have

1023
00:56:56,560 --> 00:57:01,640
Speaker 1: a we have a democracy that desperately needs updating. I'm

1024
00:57:01,640 --> 00:57:03,799
Speaker 1: not going to call it broken, I'm going to call

1025
00:57:03,840 --> 00:57:07,040
Speaker 1: it in disrepair, and it needs modernizing. You know, we

1026
00:57:07,120 --> 00:57:10,480
Speaker 1: need some cases, it's just simply catching up to reality,

1027
00:57:10,719 --> 00:57:15,239
Speaker 1: particularly when it comes down money and politics works and

1028
00:57:15,280 --> 00:57:21,680
Speaker 1: things like that. But it is I don't We're not

1029
00:57:21,800 --> 00:57:25,320
Speaker 1: going to improve the democracy in time to get AI right.

1030
00:57:25,960 --> 00:57:30,040
Speaker 1: So let's put on our well, we got to deal

1031
00:57:30,080 --> 00:57:32,280
Speaker 1: with the politics that we have now that we wish

1032
00:57:32,520 --> 00:57:37,760
Speaker 1: we had. What's a safer way within this system that

1033
00:57:37,800 --> 00:57:40,640
Speaker 1: we can be rolling out AI to help people feel

1034
00:57:40,640 --> 00:57:41,240
Speaker 1: better about this.

1035
00:57:42,080 --> 00:57:43,440
Speaker 2: I think the first thing is we should let the

1036
00:57:43,480 --> 00:57:46,720
Speaker 2: stakes which are more agile, less captured by big money interests,

1037
00:57:47,760 --> 00:57:49,800
Speaker 2: have the ability to take a stab at this and

1038
00:57:49,840 --> 00:57:52,280
Speaker 2: to experiment with it. That's the first thing. I think

1039
00:57:52,320 --> 00:57:55,000
Speaker 2: The second thing is we should minimally demand that these

1040
00:57:55,240 --> 00:57:57,920
Speaker 2: frontier labs. These are the five big companies used to

1041
00:57:57,960 --> 00:58:01,440
Speaker 2: have the very well known model. This is ex Google,

1042
00:58:02,400 --> 00:58:05,880
Speaker 2: Meta aanthropic open AI right. They need to be more

1043
00:58:05,920 --> 00:58:08,800
Speaker 2: transparent about what they're doing. They need to be reporting

1044
00:58:08,840 --> 00:58:12,440
Speaker 2: to government authorities like can this great novel pathogens? Can

1045
00:58:12,480 --> 00:58:15,360
Speaker 2: it promote offensive cybersecurity risk? Can it help?

1046
00:58:15,400 --> 00:58:17,200
Speaker 1: By the way, what is the government entity that ought

1047
00:58:17,200 --> 00:58:17,960
Speaker 1: to be overseeing this?

1048
00:58:18,720 --> 00:58:20,280
Speaker 2: I would like to see something of the Department of Commerce

1049
00:58:20,360 --> 00:58:22,920
Speaker 2: or Department of Energy said, okay, are there already doing

1050
00:58:23,000 --> 00:58:25,960
Speaker 2: nuclear weapons or a lot of export controls, So that's

1051
00:58:25,960 --> 00:58:28,280
Speaker 2: where they should do it. They should be reporting up there.

1052
00:58:28,680 --> 00:58:30,360
Speaker 2: And I think, you know, if you have a model

1053
00:58:30,640 --> 00:58:34,080
Speaker 2: that actually say it can be proven to develop novel pathogens,

1054
00:58:34,280 --> 00:58:36,040
Speaker 2: and we already know that most of these models are

1055
00:58:36,040 --> 00:58:39,800
Speaker 2: better than PhD virologists, so they're incredibly good at this

1056
00:58:39,880 --> 00:58:41,840
Speaker 2: kind of thing. And if it could develop a bioweapon,

1057
00:58:42,200 --> 00:58:44,880
Speaker 2: you should be actually prohibited from releasing that. Today you're

1058
00:58:44,920 --> 00:58:47,160
Speaker 2: not prohibited in any way from releasing that, and you

1059
00:58:47,160 --> 00:58:49,000
Speaker 2: don't even have to test for it. And so the

1060
00:58:49,040 --> 00:58:50,920
Speaker 2: idea is like, there are certain things that should be

1061
00:58:51,000 --> 00:58:54,400
Speaker 2: testing for, you know, and that you shouldn't be able

1062
00:58:54,400 --> 00:58:56,200
Speaker 2: to release these, and you should have safeguards. So if

1063
00:58:56,240 --> 00:58:59,280
Speaker 2: you can develop child pornography, for example, we should know

1064
00:58:59,360 --> 00:59:00,960
Speaker 2: ahead of time and you should be.

1065
00:59:01,040 --> 00:59:04,560
Speaker 1: Rock Look at what GROC has pulled off, right, Elon

1066
00:59:04,680 --> 00:59:11,480
Speaker 1: must decides to sexualize GROC and usership what triples? Yes, exactly,

1067
00:59:11,640 --> 00:59:13,959
Speaker 1: I don't want to. We can make a comment about

1068
00:59:13,960 --> 00:59:17,080
Speaker 1: our own society about that. But let's humans are going

1069
00:59:17,120 --> 00:59:20,320
Speaker 1: to human okay, So that that is that is what

1070
00:59:20,360 --> 00:59:23,320
Speaker 1: it is. Humans are going to human You know, I

1071
00:59:23,320 --> 00:59:27,160
Speaker 1: always say our problems in this country are incentive structures, right.

1072
00:59:27,360 --> 00:59:30,040
Speaker 1: Good people can do bad things with bad incentives. Bad

1073
00:59:30,080 --> 00:59:34,840
Speaker 1: people will do good things with good incentives. So what

1074
00:59:34,920 --> 00:59:38,320
Speaker 1: Groc basically did is, Hey, let's imagine I have the

1075
00:59:38,360 --> 00:59:42,920
Speaker 1: worst incentives imaginable. Could I triple the amount of users

1076
00:59:42,960 --> 00:59:43,160
Speaker 1: I have?

1077
00:59:43,360 --> 00:59:47,680
Speaker 2: Well, the answers yes, exactly, either new deifying images. Of course,

1078
00:59:47,720 --> 00:59:49,800
Speaker 2: there's the whole Mecha Hitler episode. Do you know where

1079
00:59:49,800 --> 00:59:52,840
Speaker 2: it took on the persona of Adol Hitler. It kind

1080
00:59:52,840 --> 00:59:56,040
Speaker 2: of blows your mind. Actually, And these products like take Groc,

1081
00:59:56,080 --> 00:59:58,920
Speaker 2: the one we're just talking about, it's now embedded increasingly

1082
00:59:58,960 --> 01:00:02,360
Speaker 2: in the Defense department. You know, he's replacing Anthropic and

1083
01:00:02,400 --> 01:00:04,800
Speaker 2: the and Claude's product there in many ways. And this

1084
01:00:04,880 --> 01:00:07,920
Speaker 2: is the most, the least reliable, the least safeguarded of

1085
01:00:08,000 --> 01:00:10,400
Speaker 2: all of them. And so you know, someone who spent

1086
01:00:10,440 --> 01:00:12,160
Speaker 2: a lot of time working at the Department of Defense

1087
01:00:12,240 --> 01:00:15,400
Speaker 2: under the Obama administration and think, he's like, I can't

1088
01:00:15,480 --> 01:00:17,600
Speaker 2: I wouldn't want to rely on this. But well, again,

1089
01:00:17,680 --> 01:00:20,120
Speaker 2: because humans will be human, we often do rely on

1090
01:00:20,160 --> 01:00:22,000
Speaker 2: computer outputs that think like, oh, that must be right.

1091
01:00:22,160 --> 01:00:25,160
Speaker 2: The computer said this, and we don't actually interrogate it enough.

1092
01:00:25,200 --> 01:00:28,360
Speaker 2: So it's actually very parallel situation we're finding ourselves in.

1093
01:00:29,040 --> 01:00:33,560
Speaker 1: You know, I was speaking with he wanted to say

1094
01:00:33,560 --> 01:00:36,160
Speaker 1: this off the record, but it was a retired general

1095
01:00:37,280 --> 01:00:41,960
Speaker 1: who was knee deep in COVID, so he was helping

1096
01:00:41,960 --> 01:00:45,200
Speaker 1: in that world. Has does not, has not been has

1097
01:00:45,240 --> 01:00:48,960
Speaker 1: been in the private sector since. But he remarked to me,

1098
01:00:49,080 --> 01:00:51,160
Speaker 1: he said, I do not understand. He said, you know,

1099
01:00:52,280 --> 01:00:58,000
Speaker 1: the government made sure, you know, if they were in

1100
01:00:58,120 --> 01:01:01,960
Speaker 1: charge of the scientists making the nuclear weapons. The government

1101
01:01:02,240 --> 01:01:07,040
Speaker 1: created the Internet, then it took the internet public. We

1102
01:01:07,080 --> 01:01:11,640
Speaker 1: are letting the private sector do this without much government

1103
01:01:11,720 --> 01:01:16,120
Speaker 1: supervision at all. And I say this. We know how

1104
01:01:16,200 --> 01:01:18,560
Speaker 1: people feel about government these days, and you may not

1105
01:01:18,640 --> 01:01:21,800
Speaker 1: trust who's in charge of the government depending on your

1106
01:01:22,240 --> 01:01:30,000
Speaker 1: political persuasion. But previous instances, you know, collective collective concern

1107
01:01:30,080 --> 01:01:36,320
Speaker 1: by government proved probably a good thing with nuclear weapons,

1108
01:01:36,360 --> 01:01:39,000
Speaker 1: and proved a good thing with the initial creation of

1109
01:01:39,040 --> 01:01:44,040
Speaker 1: the Internet as a as a defense thing. This general

1110
01:01:44,200 --> 01:01:47,720
Speaker 1: was mortified that the government had no was not essentially

1111
01:01:48,120 --> 01:01:49,640
Speaker 1: holding the hands of these companies.

1112
01:01:50,800 --> 01:01:52,920
Speaker 2: I think he should be mortified. It's really the first

1113
01:01:53,280 --> 01:01:56,840
Speaker 2: kind of transformative military technology that's being developed by the

1114
01:01:56,840 --> 01:01:59,880
Speaker 2: private sector, private companies. We don't even see there. We

1115
01:02:00,080 --> 01:02:02,280
Speaker 2: sch we have no idea like what's happening in the

1116
01:02:02,280 --> 01:02:06,120
Speaker 2: skunk works of these labs, no visibility into it. And

1117
01:02:06,640 --> 01:02:09,120
Speaker 2: it's really quite extraordinary. And now we see with Claude

1118
01:02:09,160 --> 01:02:11,560
Speaker 2: and this whole be with p Hegseth Department of War,

1119
01:02:11,880 --> 01:02:14,760
Speaker 2: how reliant they are on AI and the Iraq War

1120
01:02:14,800 --> 01:02:18,640
Speaker 2: has shown some examples of Claude's use there and so

1121
01:02:18,680 --> 01:02:21,160
Speaker 2: I think, yes, he should be mortified because what's happening

1122
01:02:21,240 --> 01:02:23,800
Speaker 2: in San Francisco within you know, a six by six

1123
01:02:23,960 --> 01:02:27,480
Speaker 2: square mile area there. It's transforming the world. It's going

1124
01:02:27,520 --> 01:02:31,000
Speaker 2: to transform military power, and we really have no oversight

1125
01:02:31,160 --> 01:02:33,120
Speaker 2: or even insight into what's going on.

1126
01:02:34,240 --> 01:02:36,080
Speaker 1: Do you ever say to yourself that are we living

1127
01:02:36,120 --> 01:02:39,880
Speaker 1: a Bond movie? Right? I mean, this is the plot

1128
01:02:40,000 --> 01:02:42,720
Speaker 1: of one of those b minus Bond movies, like not

1129
01:02:42,760 --> 01:02:43,720
Speaker 1: even a really good one.

1130
01:02:44,880 --> 01:02:46,960
Speaker 2: It's some people, I think are waking up to it.

1131
01:02:47,000 --> 01:02:49,200
Speaker 2: And that's why people are scared about this. That's why

1132
01:02:49,200 --> 01:02:51,720
Speaker 2: the unpopularity is there. People are like, you know, I

1133
01:02:51,760 --> 01:02:54,040
Speaker 2: see a lot of polling data and people do recognize

1134
01:02:54,040 --> 01:02:56,360
Speaker 2: it might be able to do some amazing things, you know,

1135
01:02:56,440 --> 01:02:58,520
Speaker 2: cure diseases, new materials.

1136
01:02:58,040 --> 01:03:01,000
Speaker 1: Social media. Look, I'm old enough to remember the Arab Spring.

1137
01:03:01,080 --> 01:03:05,720
Speaker 1: We thought, wow, we have democratized the world. Social media

1138
01:03:05,840 --> 01:03:09,320
Speaker 1: is going to get rid of authoritarianism. Oops. You know,

1139
01:03:09,400 --> 01:03:11,880
Speaker 1: it's like, it's funny you bring up we all talk

1140
01:03:11,920 --> 01:03:14,480
Speaker 1: about the health benefits. There's a story out there about

1141
01:03:14,480 --> 01:03:17,720
Speaker 1: the guy in Australia who developed the cancer treatment for

1142
01:03:17,760 --> 01:03:20,360
Speaker 1: his dog. Right, and as a dog lover, you know,

1143
01:03:21,400 --> 01:03:23,680
Speaker 1: I was, I'm like, yeah, I might. I could see

1144
01:03:23,680 --> 01:03:29,080
Speaker 1: myself doing that for Cali, you know, my puppy. That's

1145
01:03:29,120 --> 01:03:32,440
Speaker 1: the good part. But if you can develop, if somebody

1146
01:03:32,480 --> 01:03:37,280
Speaker 1: without scientific training can develop this amazing treatment to shrink

1147
01:03:37,320 --> 01:03:41,240
Speaker 1: a tumor on their dog, what could they do to

1148
01:03:41,400 --> 01:03:45,880
Speaker 1: actually give you a tumor and to actually create cancers

1149
01:03:45,920 --> 01:03:48,800
Speaker 1: if they chose to. It's the same thing with the

1150
01:03:48,800 --> 01:03:52,280
Speaker 1: Arab Spring. That's what we learned with the Arab Spring. Right,

1151
01:03:52,360 --> 01:03:56,320
Speaker 1: what was a positive the minute, Well, you could break

1152
01:03:56,360 --> 01:04:00,280
Speaker 1: through until the authoritarians decided, oh we'll control the flow

1153
01:04:00,320 --> 01:04:01,200
Speaker 1: of information again.

1154
01:04:01,640 --> 01:04:03,760
Speaker 2: Yeah, And I think that's one of the lessons of

1155
01:04:03,920 --> 01:04:07,000
Speaker 2: social media is there's good and bad to both these things.

1156
01:04:07,040 --> 01:04:10,720
Speaker 2: They're not unalloyed one way of the other. And you

1157
01:04:10,800 --> 01:04:13,320
Speaker 2: have to have a regulatory scheme that's flexible enough, which

1158
01:04:13,360 --> 01:04:15,240
Speaker 2: isn't easy to achieve, but it must be allowed to

1159
01:04:15,240 --> 01:04:17,840
Speaker 2: be flexible. Social media we froze it, you know, in

1160
01:04:17,960 --> 01:04:20,440
Speaker 2: ICE in nineteen ninety six, so section two thirty it

1161
01:04:20,520 --> 01:04:23,400
Speaker 2: was over, yep, and it's basically been unregulated since and

1162
01:04:23,480 --> 01:04:25,400
Speaker 2: immunize from any harm. And if you try to get

1163
01:04:25,440 --> 01:04:27,440
Speaker 2: after it, they always say, it's section two thirty. We're

1164
01:04:27,440 --> 01:04:30,360
Speaker 2: immunized from this. You can't allow that to happen for

1165
01:04:30,480 --> 01:04:32,760
Speaker 2: major technologies, and that is the danger of AI. That's

1166
01:04:32,800 --> 01:04:33,840
Speaker 2: really the big fight to AI.

1167
01:04:33,960 --> 01:04:34,200
Speaker 1: Now.

1168
01:04:34,360 --> 01:04:36,280
Speaker 2: It's like, do you want to repeat section two thirty.

1169
01:04:36,640 --> 01:04:38,439
Speaker 2: I think it's fair to say that like that tech

1170
01:04:38,560 --> 01:04:42,240
Speaker 2: rite crowd David Sachs A sixteen Z people like that

1171
01:04:42,400 --> 01:04:44,680
Speaker 2: open AI. That really is what they want to do.

1172
01:04:45,120 --> 01:04:47,040
Speaker 2: And the question is like, we have learned our lesson,

1173
01:04:47,440 --> 01:04:49,200
Speaker 2: you know. And it's not to say AI should be

1174
01:04:49,240 --> 01:04:52,000
Speaker 2: prohibited or that it can't do many good things. It can,

1175
01:04:52,480 --> 01:04:54,840
Speaker 2: but you do have to have a certain agility which

1176
01:04:54,840 --> 01:04:57,560
Speaker 2: the law permits, and to freeze that like we did

1177
01:04:57,560 --> 01:05:00,760
Speaker 2: with social media is just a disastrous mistake that you

1178
01:05:00,800 --> 01:05:02,640
Speaker 2: know has changed society irrevocably.

1179
01:05:03,560 --> 01:05:06,720
Speaker 1: What are some good state regulations being developed that you'd

1180
01:05:06,760 --> 01:05:09,960
Speaker 1: like to see. Let's see how that sticks. Maybe that

1181
01:05:10,080 --> 01:05:12,720
Speaker 1: will work. I mean, you know, this is the laboratory

1182
01:05:12,720 --> 01:05:14,480
Speaker 1: of we call the fifth we like to call the

1183
01:05:14,480 --> 01:05:18,920
Speaker 1: fifty States, right, the laboratory of democracy. What's what's a

1184
01:05:19,000 --> 01:05:23,160
Speaker 1: few in attempts you'd like to see to see if okay,

1185
01:05:23,280 --> 01:05:25,520
Speaker 1: and maybe this will be a good national regulation. But

1186
01:05:25,600 --> 01:05:28,240
Speaker 1: let's try it. Let's try it in Indiana or Oklahoma

1187
01:05:28,400 --> 01:05:29,040
Speaker 1: or yeah.

1188
01:05:29,120 --> 01:05:31,000
Speaker 2: First, I'll give you like three or four of those.

1189
01:05:31,000 --> 01:05:33,320
Speaker 2: For one thing, Ron DeSantis is opposing an AI Bill

1190
01:05:33,360 --> 01:05:35,800
Speaker 2: of Rights in Florida. It gives you know, your right

1191
01:05:35,880 --> 01:05:39,160
Speaker 2: to like hone your data and have transparency into AI

1192
01:05:39,200 --> 01:05:42,920
Speaker 2: decision making. I like laws like that. California and New

1193
01:05:43,000 --> 01:05:47,280
Speaker 2: York for the Frontier labs have required transparency in reporting requirements.

1194
01:05:47,880 --> 01:05:50,520
Speaker 2: I have added to those requirements. That's not enough, but

1195
01:05:50,560 --> 01:05:53,240
Speaker 2: that's a good a good step in the right direction.

1196
01:05:53,920 --> 01:05:56,400
Speaker 2: Maybe the third bucket is it's a whole different type

1197
01:05:56,400 --> 01:05:59,960
Speaker 2: of AI than like GROCK or chat GPT. It's very pervasive.

1198
01:06:00,440 --> 01:06:02,320
Speaker 2: It's how AI is being used in our day to

1199
01:06:02,440 --> 01:06:08,360
Speaker 2: day lives, for example, surveillance you know, facial recognition, algorithms

1200
01:06:08,360 --> 01:06:11,160
Speaker 2: deciding whether we're going to hire you or not, algorithms

1201
01:06:11,160 --> 01:06:13,560
Speaker 2: determining whether your health claim is going to be a.

1202
01:06:13,640 --> 01:06:15,160
Speaker 1: Prob Let me give you the one that I'm just

1203
01:06:15,720 --> 01:06:21,320
Speaker 1: rip us about surveillance pricing. I think this is so

1204
01:06:21,680 --> 01:06:25,800
Speaker 1: unconstitutionally illegal, and it's like, I am you want to

1205
01:06:25,840 --> 01:06:27,840
Speaker 1: really make you know, It's like, do you want when

1206
01:06:27,840 --> 01:06:30,000
Speaker 1: the middle class, an upper middle class decides to pick

1207
01:06:30,040 --> 01:06:33,000
Speaker 1: up a pitchfork. That's when politicians are troubled in Surveillance

1208
01:06:33,040 --> 01:06:34,200
Speaker 1: pricing is one of those.

1209
01:06:34,040 --> 01:06:35,680
Speaker 2: Well, this shows you the power of state law. So

1210
01:06:35,720 --> 01:06:37,040
Speaker 2: you know, you may have seen this. It kind of

1211
01:06:37,040 --> 01:06:39,400
Speaker 2: broke in the news last week where I'm a Washington

1212
01:06:39,480 --> 01:06:43,440
Speaker 2: Post subscriber online and to renew right, it quoted me

1213
01:06:43,480 --> 01:06:45,600
Speaker 2: a price and at the bottom it had a little

1214
01:06:45,640 --> 01:06:48,600
Speaker 2: note that this was based on an algorithmic determination. Right

1215
01:06:48,640 --> 01:06:51,120
Speaker 2: of my use patterns they knew about. The thing is,

1216
01:06:51,120 --> 01:06:53,120
Speaker 2: they know my credit history. They probably know how much

1217
01:06:53,120 --> 01:06:55,360
Speaker 2: money I make, so they probably you know Taylor, like, hey,

1218
01:06:55,360 --> 01:06:56,280
Speaker 2: he's a super user.

1219
01:06:56,640 --> 01:07:01,360
Speaker 1: Hey do you remember when you clicked when you accepted

1220
01:07:01,440 --> 01:07:03,600
Speaker 1: terms and conditions? That allowed the Washington Post to do

1221
01:07:03,640 --> 01:07:04,440
Speaker 1: a credit check on you.

1222
01:07:05,200 --> 01:07:06,760
Speaker 2: I don't I don't think I did that, but like

1223
01:07:06,800 --> 01:07:09,000
Speaker 2: all terms of said, I'm sure we did. That's my right.

1224
01:07:09,080 --> 01:07:11,680
Speaker 1: I hate those goddamn things because I'm sure they'll say, oh,

1225
01:07:11,760 --> 01:07:15,320
Speaker 1: you accepted terms and conditions. You mean oh, because you

1226
01:07:15,360 --> 01:07:17,040
Speaker 1: put a gun to my head to accept terms and

1227
01:07:17,040 --> 01:07:21,000
Speaker 1: conditions every time you update the app. But they looked

1228
01:07:21,000 --> 01:07:22,160
Speaker 1: at your credit report.

1229
01:07:22,320 --> 01:07:25,680
Speaker 2: Think about that, Brad, among other things. Right, they have

1230
01:07:25,840 --> 01:07:27,760
Speaker 2: all the consumer data you could want on me. They

1231
01:07:27,760 --> 01:07:29,440
Speaker 2: know what I else I subscribe to. They know I'm

1232
01:07:29,440 --> 01:07:31,880
Speaker 2: a New York Times subscriber and The Atlantic and things.

1233
01:07:32,120 --> 01:07:33,840
Speaker 2: But the only reason we even got who noticed about

1234
01:07:33,840 --> 01:07:36,200
Speaker 2: that is because New York has a law that says

1235
01:07:36,240 --> 01:07:38,919
Speaker 2: if you engage in algorithmic pricing, you have to put

1236
01:07:38,920 --> 01:07:40,680
Speaker 2: a little note on it. And they obviously have a

1237
01:07:40,680 --> 01:07:43,080
Speaker 2: lot of New York readers. And it's only because of

1238
01:07:43,120 --> 01:07:46,400
Speaker 2: that state law that I in Oklahoma got notified of that.

1239
01:07:46,920 --> 01:07:48,560
Speaker 2: So these are the kind of things like that's not

1240
01:07:48,720 --> 01:07:52,680
Speaker 2: frontier level AI. They're not using CHATDPT, that's AI, And

1241
01:07:52,720 --> 01:07:55,920
Speaker 2: the average American should know about that, and we should

1242
01:07:55,920 --> 01:07:59,080
Speaker 2: like have a debate and that goes into the broader

1243
01:07:59,160 --> 01:08:01,920
Speaker 2: question like surveillance. You know that anthropic Department of War

1244
01:08:02,000 --> 01:08:04,560
Speaker 2: got into the things that we call legal in this

1245
01:08:04,640 --> 01:08:07,920
Speaker 2: country that you and I my over cocktails call surveillance,

1246
01:08:08,320 --> 01:08:11,040
Speaker 2: or ordinary people like that's surveillance. The government doesn't call

1247
01:08:11,040 --> 01:08:13,680
Speaker 2: it surveillance. I mean, it's shocking the amount of data

1248
01:08:13,720 --> 01:08:17,240
Speaker 2: they have. Llms can create a whole dossier about you.

1249
01:08:17,240 --> 01:08:21,040
Speaker 2: You know that there wasn't possible before lllms existed to

1250
01:08:21,120 --> 01:08:24,479
Speaker 2: really assimilate all this data, and so those kind of

1251
01:08:24,479 --> 01:08:26,640
Speaker 2: things like I like that New York law, things like

1252
01:08:26,680 --> 01:08:29,599
Speaker 2: that that make you, at least even if we don't

1253
01:08:29,600 --> 01:08:32,200
Speaker 2: prohibit it, you need to be notified. Like if I'm

1254
01:08:32,240 --> 01:08:34,720
Speaker 2: doing a job interview and this happens in places you

1255
01:08:34,800 --> 01:08:37,439
Speaker 2: often now will like stare into the screen and the

1256
01:08:37,479 --> 01:08:39,840
Speaker 2: AI will say like is this person smarter or not

1257
01:08:39,880 --> 01:08:43,040
Speaker 2: because of my gestures or maybe my glasses. You know,

1258
01:08:43,080 --> 01:08:46,360
Speaker 2: it's like I deserve to know if AI is evaluating

1259
01:08:46,360 --> 01:08:48,680
Speaker 2: me in some way. Those kind of laws I like

1260
01:08:48,720 --> 01:08:51,440
Speaker 2: to see.

1261
01:08:53,200 --> 01:08:57,320
Speaker 1: What do you think what is your biggest concern in

1262
01:08:57,360 --> 01:09:02,720
Speaker 1: this fight that that you're you don't have enough of

1263
01:09:02,760 --> 01:09:04,479
Speaker 1: the big tech titans on your side.

1264
01:09:05,600 --> 01:09:07,960
Speaker 2: I think that's part of it. I think, you know,

1265
01:09:08,040 --> 01:09:11,280
Speaker 2: there's a political economy aspect of this right where you

1266
01:09:11,320 --> 01:09:13,639
Speaker 2: have to fight. And we know that good ideas don't

1267
01:09:13,640 --> 01:09:16,960
Speaker 2: just prevail because they're sound and even popular ones kids

1268
01:09:17,000 --> 01:09:21,120
Speaker 2: Online safety shows that big money can prevail in American politics.

1269
01:09:21,360 --> 01:09:23,639
Speaker 2: So I think that's the biggest concern. You know, if

1270
01:09:23,640 --> 01:09:26,200
Speaker 2: people are left my job leading a super pac is

1271
01:09:26,240 --> 01:09:28,439
Speaker 2: quite easy. The often aspect, well, what do I have

1272
01:09:28,479 --> 01:09:30,760
Speaker 2: to believe to earn your support? And I say, all

1273
01:09:30,760 --> 01:09:33,160
Speaker 2: you have to do is believe in having a democratic

1274
01:09:33,200 --> 01:09:35,840
Speaker 2: debate about AI. If that happens, I think most people

1275
01:09:35,840 --> 01:09:38,040
Speaker 2: will probably come to my side. What I don't want

1276
01:09:38,080 --> 01:09:39,960
Speaker 2: to do is for close it, you know, like we've

1277
01:09:39,960 --> 01:09:42,559
Speaker 2: had with crypto policy in this country, where today there's

1278
01:09:42,600 --> 01:09:45,320
Speaker 2: no real debate on crypto policy because the super pac

1279
01:09:45,720 --> 01:09:48,599
Speaker 2: has now made it impossible for people to be against

1280
01:09:48,680 --> 01:09:51,000
Speaker 2: that issue. We don't want that for AI right. We

1281
01:09:51,000 --> 01:09:53,000
Speaker 2: want it to be free where people can have actually,

1282
01:09:53,360 --> 01:09:56,280
Speaker 2: you know, an argument about what we should do, and

1283
01:09:56,320 --> 01:09:58,920
Speaker 2: if so, I have confidence in the American people to

1284
01:09:58,960 --> 01:09:59,959
Speaker 2: come to the right conclusion.

1285
01:10:10,280 --> 01:10:12,679
Speaker 1: It doesn't feel like we're having enough of it to date.

1286
01:10:12,840 --> 01:10:15,240
Speaker 1: It doesn't feel like we've had enough of a tutorial,

1287
01:10:15,880 --> 01:10:19,160
Speaker 1: you know, in a in a healthier democratic system, because

1288
01:10:19,160 --> 01:10:22,680
Speaker 1: there are systems, you know, some version of we have

1289
01:10:22,720 --> 01:10:24,920
Speaker 1: a cold, we can some of you may decide how

1290
01:10:24,920 --> 01:10:27,559
Speaker 1: bad are is it? The flu? Is it? How bad

1291
01:10:27,640 --> 01:10:33,280
Speaker 1: is it? But we're definitely not healthy. Who would be

1292
01:10:33,360 --> 01:10:36,800
Speaker 1: leading this conversation about about AI? I mean, do we

1293
01:10:36,840 --> 01:10:41,240
Speaker 1: need an old time fireside chat? Do we need a

1294
01:10:41,400 --> 01:10:46,200
Speaker 1: general Eisenhower to sort of, you know, explain things? You

1295
01:10:46,240 --> 01:10:49,040
Speaker 1: know what what would what what? What would a healthier,

1296
01:10:49,280 --> 01:10:52,680
Speaker 1: small d democratic system be doing right now with the

1297
01:10:52,720 --> 01:10:56,800
Speaker 1: development of AI and bringing the public along and making

1298
01:10:56,840 --> 01:10:58,960
Speaker 1: them feel a little more secure about it.

1299
01:10:59,640 --> 01:11:01,720
Speaker 2: I think two groups can do this. One is if

1300
01:11:01,760 --> 01:11:04,640
Speaker 2: the company leaders themselves were more open about it. I

1301
01:11:04,640 --> 01:11:06,320
Speaker 2: think Anthropic has actually done a good job of that.

1302
01:11:06,320 --> 01:11:09,360
Speaker 2: They've been pretty forward leading, They've expressed concerns. That's made

1303
01:11:09,400 --> 01:11:11,920
Speaker 2: people aware. If you had all the lab leaders come

1304
01:11:11,920 --> 01:11:14,960
Speaker 2: together and talk about these things more openly, not simply

1305
01:11:15,080 --> 01:11:17,920
Speaker 2: like be arguing their own book, like what's best for

1306
01:11:17,960 --> 01:11:21,839
Speaker 2: the narrow share interest here, but like the broader social context,

1307
01:11:21,960 --> 01:11:24,479
Speaker 2: that would help. I think my real hope is in

1308
01:11:24,520 --> 01:11:27,559
Speaker 2: the twenty twenty eight presidential race, you need someone at

1309
01:11:27,560 --> 01:11:30,679
Speaker 2: that level of platform, that level of free media covering

1310
01:11:30,720 --> 01:11:34,040
Speaker 2: them say look, America, look what's happening here, you know,

1311
01:11:34,080 --> 01:11:36,360
Speaker 2: and to like that it kind of like raises the

1312
01:11:36,360 --> 01:11:38,960
Speaker 2: consciousness of the whole country. Ron DeSantis has done a

1313
01:11:38,960 --> 01:11:40,439
Speaker 2: bit of that in Florida. Have been a great leader

1314
01:11:40,439 --> 01:11:43,000
Speaker 2: on this issue. But if you're Robert president and you said, look,

1315
01:11:43,000 --> 01:11:45,360
Speaker 2: you know, technology is actually a defining issue of our day.

1316
01:11:45,640 --> 01:11:50,000
Speaker 2: It's redefining party allegiances where Steve Bannon and Elizabeth Warren

1317
01:11:50,120 --> 01:11:52,320
Speaker 2: or like eye to eye on these kind of questions,

1318
01:11:52,800 --> 01:11:54,800
Speaker 2: you know, and you should be paying attention. And here's

1319
01:11:54,800 --> 01:11:57,519
Speaker 2: some solutions for it as well, not just decrying about

1320
01:11:57,560 --> 01:11:59,040
Speaker 2: solutions that works.

1321
01:11:59,560 --> 01:12:01,840
Speaker 1: You know. Strikes me is the safest place to be

1322
01:12:01,920 --> 01:12:05,759
Speaker 1: politically is if you're pro consumer. You know what you're describing,

1323
01:12:05,800 --> 01:12:10,240
Speaker 1: what essentially what Governor DeSantis is proposing. And in some

1324
01:12:10,280 --> 01:12:13,719
Speaker 1: ways it is very much a small C conservative approach,

1325
01:12:13,960 --> 01:12:17,519
Speaker 1: which is, hey, we got to have a specific essentially

1326
01:12:17,560 --> 01:12:21,960
Speaker 1: a bill of rights, right, which is really a consumer protection.

1327
01:12:22,600 --> 01:12:24,720
Speaker 1: You know, we can have larger arguments about, you know,

1328
01:12:24,720 --> 01:12:27,000
Speaker 1: what should this be allowed and should this be allowed? Right?

1329
01:12:27,680 --> 01:12:30,040
Speaker 1: And that's where sometimes you lose people on the right. Well,

1330
01:12:30,040 --> 01:12:34,599
Speaker 1: I don't want government to involved with all the decision making,

1331
01:12:35,040 --> 01:12:39,240
Speaker 1: but let's have some basic protections for the consumer, right.

1332
01:12:39,320 --> 01:12:43,200
Speaker 1: And it feels like if you put if the north

1333
01:12:43,240 --> 01:12:46,400
Speaker 1: star is consumer protection hardstop.

1334
01:12:47,439 --> 01:12:49,040
Speaker 2: I think it's a political message that.

1335
01:12:49,040 --> 01:12:51,599
Speaker 1: You probably can get to the right place without without

1336
01:12:52,280 --> 01:12:54,080
Speaker 1: feeling that you're too blue or too red.

1337
01:12:54,760 --> 01:12:56,200
Speaker 2: I think it is actually a great message, and I

1338
01:12:56,240 --> 01:12:58,880
Speaker 2: think though you need someone of stature to inject that

1339
01:12:58,920 --> 01:13:02,120
Speaker 2: into the debate. People know, like AI is changing your life.

1340
01:13:02,240 --> 01:13:03,680
Speaker 2: You may not even be able to see all the

1341
01:13:03,720 --> 01:13:05,880
Speaker 2: things that's doing right, you don't even know it. Sometimes

1342
01:13:05,880 --> 01:13:09,280
Speaker 2: it's invisible to you. But consumer protection claims are very

1343
01:13:09,320 --> 01:13:11,960
Speaker 2: powerful and to make kind of a major issue. That's

1344
01:13:12,000 --> 01:13:13,840
Speaker 2: what I hope twenty twenty eight brings. And I actually

1345
01:13:13,880 --> 01:13:15,559
Speaker 2: think it's going to be a major issue in twenty

1346
01:13:15,600 --> 01:13:18,360
Speaker 2: twenty eight. So I'm pretty optimistic that it's going to

1347
01:13:18,360 --> 01:13:20,519
Speaker 2: be a huge question. And once it's become part of

1348
01:13:20,560 --> 01:13:24,160
Speaker 2: the broader discussion, a few people can't control it anymore. Right,

1349
01:13:24,160 --> 01:13:26,200
Speaker 2: it can't be just like two guys in Silicon Valley

1350
01:13:26,240 --> 01:13:30,000
Speaker 2: plotting against you. Once it's in South Carolina, New Hampshire,

1351
01:13:30,439 --> 01:13:30,840
Speaker 2: it's a.

1352
01:13:30,800 --> 01:13:33,720
Speaker 1: Thing, you know, It's funny. You know, the Internet never

1353
01:13:33,840 --> 01:13:38,640
Speaker 1: did become a centerpiece conversation in a presidential election, not

1354
01:13:38,760 --> 01:13:41,719
Speaker 1: ninety six, not two thousand. You know, I remember McCain

1355
01:13:42,080 --> 01:13:45,479
Speaker 1: tried with the tax free Internet and thought there'd be

1356
01:13:45,520 --> 01:13:51,439
Speaker 1: some there would be a somewhat of a centralizing you

1357
01:13:51,479 --> 01:13:55,040
Speaker 1: know that you'd have been dismissed as a candidate if

1358
01:13:55,040 --> 01:13:58,599
Speaker 1: you didn't have a policy talking about how to integrate

1359
01:13:58,680 --> 01:14:02,920
Speaker 1: the Internet into every date, commerce, et cetera. I'm with you.

1360
01:14:03,000 --> 01:14:05,920
Speaker 1: I think twenty eight is going to be the year

1361
01:14:06,080 --> 01:14:09,080
Speaker 1: where that is focused on fear of AI job displacement.

1362
01:14:09,080 --> 01:14:10,800
Speaker 1: I'm not saying AI job displacement is going to be

1363
01:14:10,840 --> 01:14:13,880
Speaker 1: taking place, but the fear of it, I think is

1364
01:14:13,920 --> 01:14:16,519
Speaker 1: going to be at a more heightened state come twenty

1365
01:14:16,560 --> 01:14:18,920
Speaker 1: twenty eight. We've seen already a few things like the

1366
01:14:20,439 --> 01:14:22,920
Speaker 1: Jack Dorsey company where he just laid off forty percent

1367
01:14:22,960 --> 01:14:27,639
Speaker 1: of his folks. Whether that was really AI driven, you know, right,

1368
01:14:27,840 --> 01:14:32,600
Speaker 1: every you're like, oh, that's that's interesting. Let's see if

1369
01:14:32,600 --> 01:14:34,800
Speaker 1: two or three more companies do this, then it's a trend. Right.

1370
01:14:36,880 --> 01:14:40,040
Speaker 1: But I do sense fear of AI job displacement is

1371
01:14:40,600 --> 01:14:48,040
Speaker 1: probably going to be a a central concern particularly you're

1372
01:14:48,040 --> 01:14:49,760
Speaker 1: certainly seeing it in labor units right now.

1373
01:14:50,280 --> 01:14:54,040
Speaker 2: I think also rising electricity prices and perhaps water usage.

1374
01:14:54,200 --> 01:14:57,000
Speaker 2: Some of those concerns are more serious than others. People

1375
01:14:57,520 --> 01:15:01,520
Speaker 2: overestimate the use of water things. But you've seen Spanberger

1376
01:15:01,640 --> 01:15:03,799
Speaker 2: run all those kind of issues. Loud and County flip

1377
01:15:03,840 --> 01:15:07,120
Speaker 2: a seat from red to blue a couple Georgia political public.

1378
01:15:07,200 --> 01:15:10,000
Speaker 1: Well, Brad, I mean not to get like very specific here,

1379
01:15:10,080 --> 01:15:14,240
Speaker 1: because I've my electric bills gone up through the roof

1380
01:15:14,520 --> 01:15:17,719
Speaker 1: and I'm in Arlington County, which is not far from Loudon.

1381
01:15:18,360 --> 01:15:22,120
Speaker 1: But the reason we're paying a steeper price is because

1382
01:15:22,160 --> 01:15:26,479
Speaker 1: of how electricity is transmitted along off the grid into

1383
01:15:26,560 --> 01:15:29,519
Speaker 1: the mid Atlantic. And it turns out that you know,

1384
01:15:30,240 --> 01:15:34,200
Speaker 1: like you know, it's gonna hurt us more than it

1385
01:15:34,200 --> 01:15:38,520
Speaker 1: will hurt another state more because they get their electricity

1386
01:15:38,560 --> 01:15:42,759
Speaker 1: slightly differently than Maryland gets THEIRS. Then Pennsylvania gets THEIRS,

1387
01:15:43,080 --> 01:15:47,479
Speaker 1: Virginia gets THEIRS. You know, what it's done for me

1388
01:15:47,560 --> 01:15:50,160
Speaker 1: is that it's highlighted. Hey, our grid is a mess.

1389
01:15:50,520 --> 01:15:55,120
Speaker 1: We probably need to restructure the grid in a way

1390
01:15:55,320 --> 01:16:01,040
Speaker 1: to minimize consumer pain and maximize stability.

1391
01:16:01,960 --> 01:16:03,880
Speaker 2: You know, I think that's one of the underappreciated aspects

1392
01:16:03,880 --> 01:16:06,840
Speaker 2: of what AI has done is there's this incredible energy

1393
01:16:06,880 --> 01:16:08,160
Speaker 2: build out across the country.

1394
01:16:08,280 --> 01:16:11,040
Speaker 1: Yeah no, but it's exposed some problems problems too.

1395
01:16:11,280 --> 01:16:13,400
Speaker 2: But it's actually I think probably will lead more than

1396
01:16:13,439 --> 01:16:16,120
Speaker 2: anything else, has to some solutions to those. Right, you're right.

1397
01:16:16,120 --> 01:16:18,839
Speaker 2: The grid has to have probably a trillion dollars invested

1398
01:16:18,920 --> 01:16:21,960
Speaker 2: into it. Right, we need more interconnection agreements. The regulation

1399
01:16:22,120 --> 01:16:23,040
Speaker 2: is pretty come by.

1400
01:16:23,120 --> 01:16:24,519
Speaker 1: I know who should pay for it. We don't have

1401
01:16:24,600 --> 01:16:26,320
Speaker 1: to pay for it now, the friends that want to

1402
01:16:26,360 --> 01:16:28,800
Speaker 1: build these data centers, this should be the price. Nothing

1403
01:16:28,840 --> 01:16:29,559
Speaker 1: wrong with that.

1404
01:16:29,720 --> 01:16:32,640
Speaker 2: And that's the right, right, that's actually and this is

1405
01:16:32,640 --> 01:16:34,360
Speaker 2: why I think it's going to be a good issue. Actually,

1406
01:16:34,400 --> 01:16:36,240
Speaker 2: you know, you asked to me like Oklahoma democrats and

1407
01:16:36,280 --> 01:16:39,360
Speaker 2: like Southern democrats, like this is actually a classic wedge

1408
01:16:39,439 --> 01:16:41,720
Speaker 2: issue if you're a Democrat in these states, because you're

1409
01:16:41,760 --> 01:16:43,719
Speaker 2: something like you know what I'm I'm actually for lowering

1410
01:16:43,760 --> 01:16:46,479
Speaker 2: your electricity bill. I'm like, I want these data centers

1411
01:16:46,520 --> 01:16:49,640
Speaker 2: to pay their way. Sometimes like pro business Republicans have

1412
01:16:49,640 --> 01:16:52,400
Speaker 2: a hard time getting themselves to that position. And so

1413
01:16:52,439 --> 01:16:54,040
Speaker 2: you've seen in a couple of places, Right, it's a

1414
01:16:54,080 --> 01:16:57,280
Speaker 2: really good issue to kind of like get these conservatives

1415
01:16:57,280 --> 01:17:00,960
Speaker 2: who care about affordability and water, environment and use, I mean,

1416
01:17:01,000 --> 01:17:03,559
Speaker 2: who are skeptical at ai in Silicon Valley as well.

1417
01:17:03,680 --> 01:17:06,080
Speaker 2: Kind of inherently all that comes into kind of a

1418
01:17:06,120 --> 01:17:08,040
Speaker 2: world where he's going to make for a lot of

1419
01:17:08,040 --> 01:17:08,919
Speaker 2: strange politics.

1420
01:17:08,920 --> 01:17:12,840
Speaker 1: Actually, and let me let me end with a little

1421
01:17:12,880 --> 01:17:17,320
Speaker 1: bit of just your observations. What's going on in particularly

1422
01:17:17,320 --> 01:17:20,080
Speaker 1: in your I don't know, is it your former political

1423
01:17:20,120 --> 01:17:22,479
Speaker 1: party or your current one? First, do you consider yourself

1424
01:17:22,520 --> 01:17:23,080
Speaker 1: a Democrat?

1425
01:17:22,960 --> 01:17:24,040
Speaker 2: St Oh, yes, of course.

1426
01:17:24,320 --> 01:17:29,519
Speaker 1: Okay, what's the difference between an Oklahoma Democrat and a

1427
01:17:29,600 --> 01:17:31,879
Speaker 1: national Democrat these days? Or is there one?

1428
01:17:32,760 --> 01:17:35,799
Speaker 2: I'm about the last Democrat in the state of Oklahoma today,

1429
01:17:36,040 --> 01:17:38,560
Speaker 2: so I'm kind of like, you know, the last of

1430
01:17:39,080 --> 01:17:42,720
Speaker 2: the Mohicans here, I'd say, I think, you know, my

1431
01:17:42,800 --> 01:17:46,439
Speaker 2: view has always been that the parties do capture by

1432
01:17:46,439 --> 01:17:50,040
Speaker 2: the values of the professional managerial class, you know, whose

1433
01:17:50,080 --> 01:17:53,800
Speaker 2: concerns are almost post material, right about things like if

1434
01:17:53,840 --> 01:17:56,400
Speaker 2: you come like I do from eastern Oklahoma, small towns,

1435
01:17:56,400 --> 01:17:58,639
Speaker 2: that's what I represented in Congress where I was from,

1436
01:17:59,000 --> 01:18:04,200
Speaker 2: their concerns are very material health care, jobs, roads, schools.

1437
01:18:04,400 --> 01:18:08,000
Speaker 2: We have meth and opiate addiction that are endemic. You know,

1438
01:18:08,160 --> 01:18:12,000
Speaker 2: these concerns of like kind of esoteric social questions, which

1439
01:18:12,360 --> 01:18:15,200
Speaker 2: if you're like living you know in loud In County,

1440
01:18:15,240 --> 01:18:16,840
Speaker 2: one of the richest counties in the country, there are

1441
01:18:16,880 --> 01:18:19,599
Speaker 2: not that many people who like worry about these things

1442
01:18:19,640 --> 01:18:20,880
Speaker 2: with the same intensity.

1443
01:18:21,400 --> 01:18:24,760
Speaker 1: And to me, I like to say, you have the

1444
01:18:24,840 --> 01:18:26,160
Speaker 1: luxury to worry about those.

1445
01:18:26,000 --> 01:18:28,280
Speaker 2: Things, yeah, exactly, And so things that you know, even

1446
01:18:28,320 --> 01:18:30,240
Speaker 2: if they're in the right about it, they make them

1447
01:18:30,280 --> 01:18:32,599
Speaker 2: more salient than they should be. You know. It's like,

1448
01:18:33,200 --> 01:18:34,479
Speaker 2: you know, in my mind, like I think the whole

1449
01:18:34,520 --> 01:18:37,400
Speaker 2: question that the party's debating about trans issues, you know,

1450
01:18:37,439 --> 01:18:40,439
Speaker 2: you could be four or against it. These are different positions.

1451
01:18:40,720 --> 01:18:43,680
Speaker 2: It's really not that salient to the average voter. And

1452
01:18:43,760 --> 01:18:45,439
Speaker 2: so you know, we should focus on things that are

1453
01:18:45,479 --> 01:18:48,920
Speaker 2: like driving their their kind of household decision making, and

1454
01:18:48,960 --> 01:18:51,760
Speaker 2: Democrats need to be better about that. So that's the

1455
01:18:51,800 --> 01:18:54,600
Speaker 2: problem with the Coastal Party. But I still think Democrats

1456
01:18:54,600 --> 01:18:57,200
Speaker 2: have the best message for people who have those very

1457
01:18:57,240 --> 01:19:00,479
Speaker 2: material concerns about health care and public schools like that.

1458
01:19:00,560 --> 01:19:03,839
Speaker 2: So I'm working do my best to reclaim that tradition.

1459
01:19:04,760 --> 01:19:07,360
Speaker 1: I have a specific question about Oklahoma. You know, one

1460
01:19:07,400 --> 01:19:09,120
Speaker 1: of the things I like to remind people is that

1461
01:19:09,160 --> 01:19:13,559
Speaker 1: even in one party states and a political a strong

1462
01:19:13,640 --> 01:19:18,479
Speaker 1: political opposition develops some and it isn't Sometimes it's within

1463
01:19:18,520 --> 01:19:20,960
Speaker 1: the party. Right, We've seen that in Texas there are

1464
01:19:20,960 --> 01:19:24,400
Speaker 1: basically two Republican parties and they're clashing right now in

1465
01:19:24,400 --> 01:19:26,840
Speaker 1: that center base. But we had seen this, right, the

1466
01:19:27,040 --> 01:19:29,559
Speaker 1: one part of the Republican Party wanted to impeach impact,

1467
01:19:30,080 --> 01:19:33,240
Speaker 1: another part is trying to defend him. But you know,

1468
01:19:33,280 --> 01:19:36,240
Speaker 1: the weak Democratic Party and it's perhaps getting a little

1469
01:19:36,280 --> 01:19:39,320
Speaker 1: stronger down there today, but at the time, but you know,

1470
01:19:39,680 --> 01:19:42,559
Speaker 1: there's the reason the phrase exists, politics of horz vacuum.

1471
01:19:42,600 --> 01:19:46,280
Speaker 1: What I've noticed about in Oklahoma is as the Democratic

1472
01:19:46,320 --> 01:19:50,960
Speaker 1: Party has fallen away as the chief opposition to the

1473
01:19:51,280 --> 01:19:57,000
Speaker 1: to the majority governing governance in the state, that the

1474
01:19:57,040 --> 01:20:03,360
Speaker 1: tribes have become the Czech the oppositional check. And sometimes

1475
01:20:03,400 --> 01:20:07,519
Speaker 1: it'll be by the tribes funding a Republican primary candidate

1476
01:20:07,520 --> 01:20:11,000
Speaker 1: to a certain sitting governor or sitting attorney general. Maybe

1477
01:20:11,000 --> 01:20:13,320
Speaker 1: it will be finding a former Republican to run as

1478
01:20:13,360 --> 01:20:19,280
Speaker 1: a Democrat for governor or. It's, you know, is Oklahoma

1479
01:20:19,320 --> 01:20:21,880
Speaker 1: politics it's it's a two party state, but it's not

1480
01:20:21,960 --> 01:20:25,720
Speaker 1: Democrats and Republicans, it's Republicans, and that the next most

1481
01:20:25,760 --> 01:20:27,519
Speaker 1: powerful interest group is the tribes.

1482
01:20:28,680 --> 01:20:30,920
Speaker 2: That's probably a fair assessment of it. The tribes are

1483
01:20:31,000 --> 01:20:34,519
Speaker 2: historically very democratic. Unsurprisingly, over the last twenty years, I've

1484
01:20:34,520 --> 01:20:36,840
Speaker 2: become very wealthy and have a lot more political interest

1485
01:20:36,880 --> 01:20:40,120
Speaker 2: at stake, and they've spread that money around because Republicans

1486
01:20:40,120 --> 01:20:43,600
Speaker 2: are in ascendancy really and have like basically every office

1487
01:20:44,120 --> 01:20:46,200
Speaker 2: at every level. Right, They've played in a lot more

1488
01:20:46,240 --> 01:20:48,679
Speaker 2: Republican politics to find people who are supportive of them.

1489
01:20:49,040 --> 01:20:52,400
Speaker 2: They've been real at war with Kevin sitt or governess.

1490
01:20:52,080 --> 01:20:55,479
Speaker 1: They have, and that's basically been over a over good

1491
01:20:55,479 --> 01:20:58,160
Speaker 1: old fashioned economics. Right, how much does they get in

1492
01:20:58,240 --> 01:21:00,479
Speaker 1: the gambling revenue urisdiction?

1493
01:21:00,560 --> 01:21:03,040
Speaker 2: You know of things. But now they have people running

1494
01:21:03,040 --> 01:21:05,559
Speaker 2: for governor, which is all about the Republican primary. Again,

1495
01:21:05,600 --> 01:21:08,280
Speaker 2: there's no serious democratic cant is. Some of them are

1496
01:21:08,360 --> 01:21:11,439
Speaker 2: very strongly aligned with the tribes, some less so, and

1497
01:21:11,520 --> 01:21:13,880
Speaker 2: so the tribal issues are actually driving a lot of it.

1498
01:21:13,920 --> 01:21:16,800
Speaker 2: They fund a lot of things independent expenditures. So I

1499
01:21:16,840 --> 01:21:19,320
Speaker 2: think it probably is fair to say that after kind

1500
01:21:19,360 --> 01:21:22,400
Speaker 2: of state government. They have a kind of rump oil

1501
01:21:22,400 --> 01:21:25,040
Speaker 2: and gas industry that still has some power, but probably

1502
01:21:25,080 --> 01:21:28,080
Speaker 2: the tribes are the most organized kind of figures. They

1503
01:21:28,160 --> 01:21:29,160
Speaker 2: keep a check on government.

1504
01:21:29,680 --> 01:21:33,160
Speaker 1: Yeah, we're seeing Look, this is what you're seeing a

1505
01:21:33,200 --> 01:21:34,519
Speaker 1: little bit in the state of Florida, and what you're

1506
01:21:34,520 --> 01:21:36,559
Speaker 1: seeing a little bit in the state of California, where the

1507
01:21:36,600 --> 01:21:41,560
Speaker 1: tribes are becoming the sort of the bulwark against a

1508
01:21:41,680 --> 01:21:46,000
Speaker 1: majority you know, the majority party running amok, almost running unopposed.

1509
01:21:46,400 --> 01:21:48,639
Speaker 1: And I think we all know our democracy doesn't work

1510
01:21:48,640 --> 01:21:51,559
Speaker 1: without a little bit of friction, that's sure, And in

1511
01:21:51,560 --> 01:21:54,320
Speaker 1: that sense it develops a friction. What would you tell

1512
01:21:54,479 --> 01:21:57,040
Speaker 1: you gave some advice about, like how you viewed the

1513
01:21:57,080 --> 01:22:01,759
Speaker 1: party in general? What kind of anybody out there running

1514
01:22:01,880 --> 01:22:05,639
Speaker 1: in twenty eight that you're like, boy, they're at least

1515
01:22:05,880 --> 01:22:10,000
Speaker 1: talking about issues differently and it's about time, or you

1516
01:22:10,040 --> 01:22:12,360
Speaker 1: know who's who's just standing out to you is sort

1517
01:22:12,360 --> 01:22:14,679
Speaker 1: of like, well, I hope to hear from hear more

1518
01:22:14,720 --> 01:22:15,880
Speaker 1: from them after twenty six.

1519
01:22:16,439 --> 01:22:18,599
Speaker 2: You know, I hear John Assoff on the stump. I'm

1520
01:22:18,600 --> 01:22:21,360
Speaker 2: always very impressed by him and how he's thinking of things.

1521
01:22:21,800 --> 01:22:24,360
Speaker 2: And I hear Buddha judge that kind of similar rhetoric.

1522
01:22:24,520 --> 01:22:27,400
Speaker 2: I think kind of that analysis I gave, perhaps offered

1523
01:22:27,600 --> 01:22:31,080
Speaker 2: less stridently than I did, is one people recognize, you know,

1524
01:22:31,160 --> 01:22:32,479
Speaker 2: that we need to get back to more of a

1525
01:22:32,479 --> 01:22:36,360
Speaker 2: class based politics than that we've had in the past.

1526
01:22:36,600 --> 01:22:39,240
Speaker 1: Well that's what Trump did. He ran a good old

1527
01:22:39,240 --> 01:22:43,599
Speaker 1: flashion class wharf, you know, class warfare campaign which Bob

1528
01:22:43,640 --> 01:22:46,439
Speaker 1: Shrum used to help Democrats run back in the dates

1529
01:22:46,479 --> 01:22:50,000
Speaker 1: of Gore and Carrie and and and those campaigns, which

1530
01:22:50,000 --> 01:22:50,960
Speaker 1: were quite competitive.

1531
01:22:51,439 --> 01:22:53,400
Speaker 2: Yeah, I actually can envision. This is one of my

1532
01:22:53,439 --> 01:22:55,759
Speaker 2: goals in life is have a Democrat go on Steve

1533
01:22:55,800 --> 01:22:58,920
Speaker 2: Bannon's war room and say to the magabase that listened

1534
01:22:58,880 --> 01:23:01,720
Speaker 2: to him, like, the truth is, Trump has betrayed the

1535
01:23:01,760 --> 01:23:04,400
Speaker 2: MAGA base, right, all the things you cared about about

1536
01:23:04,800 --> 01:23:05,840
Speaker 2: the swamp and all this.

1537
01:23:05,960 --> 01:23:08,160
Speaker 1: That's my wife's theory. She's like that you should say

1538
01:23:08,200 --> 01:23:11,280
Speaker 1: he lied to you. Yeah, don't tell them they were dumb.

1539
01:23:11,800 --> 01:23:13,720
Speaker 1: Go the other way around. I mean, this has been

1540
01:23:13,760 --> 01:23:16,400
Speaker 1: the problem with the left. They keep attacking the voter

1541
01:23:16,720 --> 01:23:21,200
Speaker 1: for supporting Trump, rather than understanding why the voter wants

1542
01:23:21,240 --> 01:23:22,160
Speaker 1: Trump in the first place.

1543
01:23:22,520 --> 01:23:24,559
Speaker 2: So if you want to make America great again, so

1544
01:23:24,760 --> 01:23:27,240
Speaker 2: what a great thing that is you should vote Democratic, right,

1545
01:23:27,240 --> 01:23:28,840
Speaker 2: because we are the ones who are actually going to

1546
01:23:28,880 --> 01:23:31,240
Speaker 2: deliver this message to you. I actually think that's the

1547
01:23:31,360 --> 01:23:34,200
Speaker 2: jiu jitsu that that's probably too hard.

1548
01:23:34,080 --> 01:23:37,599
Speaker 1: For people to You're, well, it's why. It's a reminder.

1549
01:23:37,600 --> 01:23:40,639
Speaker 1: I always say, today's MAGA voter was a Clinton voter

1550
01:23:40,680 --> 01:23:41,240
Speaker 1: in the nineties.

1551
01:23:41,280 --> 01:23:43,639
Speaker 2: One hundred percent those were all Democratic voters.

1552
01:23:44,240 --> 01:23:46,479
Speaker 1: I think they were all Bill Clinton voters. I wonder,

1553
01:23:46,880 --> 01:23:49,000
Speaker 1: don't you agree they were Reagan voters and they were

1554
01:23:49,000 --> 01:23:49,760
Speaker 1: Bill Clinton voters.

1555
01:23:49,800 --> 01:23:52,000
Speaker 2: I bet they were. All of them were registered Democrats

1556
01:23:52,000 --> 01:23:54,639
Speaker 2: back in the day, and they were your constituents. Yeah, exactly.

1557
01:23:54,840 --> 01:23:57,280
Speaker 2: And my district now that I won is seventy five

1558
01:23:57,400 --> 01:24:01,280
Speaker 2: twenty five Trump And so it shows you like these people,

1559
01:24:01,680 --> 01:24:03,960
Speaker 2: they have certain interests, and Trump spoke to them in

1560
01:24:03,960 --> 01:24:06,200
Speaker 2: a brilliant way, and we shouldn't take that away from

1561
01:24:06,200 --> 01:24:08,880
Speaker 2: like the genius of his campaigning. We should try to

1562
01:24:08,920 --> 01:24:11,040
Speaker 2: like re channel that in some way.

1563
01:24:11,920 --> 01:24:14,599
Speaker 1: President of Tulsa University did love it or hate it.

1564
01:24:15,320 --> 01:24:17,599
Speaker 2: I left there actually Jane in June to do full

1565
01:24:17,640 --> 01:24:19,920
Speaker 2: time AI work, But I loved it. University of Tulsa

1566
01:24:19,920 --> 01:24:20,439
Speaker 2: is a great place.

1567
01:24:20,479 --> 01:24:23,200
Speaker 1: That's worst it is it as bad politically. I mean,

1568
01:24:23,240 --> 01:24:25,320
Speaker 1: you know that's the old joke, right, The politics are

1569
01:24:25,320 --> 01:24:27,400
Speaker 1: worse on a college campus because the stakes are so low.

1570
01:24:27,880 --> 01:24:30,519
Speaker 2: It was far harder politics than the actual being an

1571
01:24:30,560 --> 01:24:31,679
Speaker 2: elective office ever.

1572
01:24:31,680 --> 01:24:36,479
Speaker 1: Was well, it's I always had a soft spot being

1573
01:24:36,520 --> 01:24:39,080
Speaker 1: a Miami Hurricane. Boy. I always had a soft spot

1574
01:24:39,080 --> 01:24:39,759
Speaker 1: for the Golden.

1575
01:24:39,600 --> 01:24:42,400
Speaker 2: Hurricanes, exactly where the two hurricane in the world, right

1576
01:24:42,439 --> 01:24:44,720
Speaker 2: of course, being oh, you grad myself, I have to

1577
01:24:44,720 --> 01:24:45,360
Speaker 2: hate Miami.

1578
01:24:45,600 --> 01:24:47,439
Speaker 1: I know you don't, but that's all right. We had to.

1579
01:24:47,600 --> 01:24:49,840
Speaker 1: If it wasn't bar Oklahoma, Miami wouldn't have gotten into

1580
01:24:49,840 --> 01:24:50,400
Speaker 1: the top tier.

1581
01:24:50,880 --> 01:24:51,360
Speaker 2: That's true.

1582
01:24:51,360 --> 01:24:56,280
Speaker 1: Beating Oklahoma gave Miami an identity, so losing I'm very

1583
01:24:56,320 --> 01:24:59,320
Speaker 1: thankful for the old Big Eight sent to our.

1584
01:24:59,200 --> 01:25:02,680
Speaker 2: Coaches, Jimmy Johnson right from Oklahoma, since you are best people.

1585
01:25:02,560 --> 01:25:04,800
Speaker 1: That's right. Well, and then we sent you one back

1586
01:25:04,800 --> 01:25:08,080
Speaker 1: with Snellenberger that didn't go so hot, But that's that's

1587
01:25:08,120 --> 01:25:10,759
Speaker 1: neither hear door there. Hey, Brad Carson, this was great.

1588
01:25:11,720 --> 01:25:15,559
Speaker 1: I appreciate you coming on and uh, look this this

1589
01:25:15,680 --> 01:25:18,760
Speaker 1: is I see why you're engaged in this. I mean

1590
01:25:18,760 --> 01:25:24,600
Speaker 1: this really is in some ways more how if we

1591
01:25:24,680 --> 01:25:26,040
Speaker 1: got to get a right. We got to get this

1592
01:25:26,200 --> 01:25:30,160
Speaker 1: right because getting it wrong could be could be very,

1593
01:25:30,760 --> 01:25:31,960
Speaker 1: very damaging to me.

1594
01:25:32,200 --> 01:25:34,599
Speaker 2: It is the most important fight going on right now.

1595
01:25:35,000 --> 01:25:38,400
Speaker 1: That's for sure. All Right, we'll be well, let's let's

1596
01:25:38,439 --> 01:25:53,000
Speaker 1: stay in touch, sing you Chuck. Well, if you pass

1597
01:25:53,040 --> 01:25:55,160
Speaker 1: forwarded through the end of the Carson interview, I encourage

1598
01:25:55,200 --> 01:25:56,720
Speaker 1: you to go rewind and listen to the end. There

1599
01:25:56,760 --> 01:26:00,720
Speaker 1: he made an interesting observation about why he believes Democrats

1600
01:26:00,720 --> 01:26:06,320
Speaker 1: have lost touch with basically Democrats with voters in the

1601
01:26:06,320 --> 01:26:10,720
Speaker 1: middle of the country, in working class America, and it

1602
01:26:10,800 --> 01:26:14,559
Speaker 1: was an interesting observation about the coast essentially the coastal

1603
01:26:14,600 --> 01:26:17,760
Speaker 1: Democrats versus everybody else. So I highly encourage you to

1604
01:26:18,560 --> 01:26:22,200
Speaker 1: go listen to that portion. If you didn't, and if

1605
01:26:22,200 --> 01:26:25,400
Speaker 1: you did, I'm very curious in your reaction, So please

1606
01:26:25,720 --> 01:26:29,519
Speaker 1: feel free to share at Asschuck at thechucktodcast dot com.

1607
01:26:29,560 --> 01:26:34,040
Speaker 1: That email address again is Asschuck atthchucktodcast dot com. And

1608
01:26:34,120 --> 01:26:37,960
Speaker 1: speaking of ass Chuck, we got questions. You got had

1609
01:26:37,960 --> 01:26:40,559
Speaker 1: a lot of them today. Let's dig in ask Chuck.

1610
01:26:43,800 --> 01:26:47,639
Speaker 1: First question comes from Bill in Boston and he writes, Hey, Chuck,

1611
01:26:47,680 --> 01:26:49,559
Speaker 1: I started listening to your podcast after hearing you on

1612
01:26:49,640 --> 01:26:52,639
Speaker 1: Jim and Marjorie's show, and have not missed an episode since.

1613
01:26:52,760 --> 01:26:55,600
Speaker 1: Oh I'm glad to hear that. Jim and Marjorie are fantastic.

1614
01:26:55,680 --> 01:27:00,599
Speaker 1: They have a terrific daily program on BPR. Up there,

1615
01:27:00,640 --> 01:27:05,479
Speaker 1: Boston Public Radio, and they're two of my favorite people.

1616
01:27:06,280 --> 01:27:10,479
Speaker 1: I just adore them and it is it is probably

1617
01:27:10,520 --> 01:27:13,400
Speaker 1: my favorite guest appearance I make on anything I do.

1618
01:27:13,960 --> 01:27:17,600
Speaker 1: It's just a total joy with with with them. So

1619
01:27:17,800 --> 01:27:21,959
Speaker 1: thank you for giving them a shout out. You continue.

1620
01:27:22,000 --> 01:27:23,800
Speaker 1: I devour the commentaries as soon as they drop and

1621
01:27:23,800 --> 01:27:25,600
Speaker 1: then save the interviews for the weekend. So excellent. My

1622
01:27:25,640 --> 01:27:27,760
Speaker 1: niece just graduated from journalism school and is moving to

1623
01:27:27,840 --> 01:27:30,240
Speaker 1: DC to start her career in the world of political journalism.

1624
01:27:30,240 --> 01:27:32,320
Speaker 1: I was thinking of getting our membership at the National

1625
01:27:32,360 --> 01:27:34,599
Speaker 1: Press Club as a graduation. Get Is that still where

1626
01:27:34,640 --> 01:27:36,840
Speaker 1: the center of gravity is for the DC press these days?

1627
01:27:37,240 --> 01:27:41,280
Speaker 1: Thanks Bill and Boston. It actually isn't. The National Press

1628
01:27:41,280 --> 01:27:45,880
Speaker 1: Club is really it's really a PR mechanism. Now more

1629
01:27:45,920 --> 01:27:48,240
Speaker 1: public relations firms are members of the Press Club than

1630
01:27:48,280 --> 01:27:53,520
Speaker 1: actual journalists associations. It's still an if you're an international journalist,

1631
01:27:53,560 --> 01:27:57,320
Speaker 1: the Press Club is a helpful tool, but it does

1632
01:27:57,360 --> 01:28:02,200
Speaker 1: not play the role it once did. And it's interesting

1633
01:28:06,280 --> 01:28:10,599
Speaker 1: I might suggest, I know this sounds I might suggest

1634
01:28:10,800 --> 01:28:17,960
Speaker 1: just getting her a subscription, so like punch Bowl, right,

1635
01:28:18,040 --> 01:28:21,360
Speaker 1: and some one of these insider newsletters that you really

1636
01:28:21,439 --> 01:28:24,719
Speaker 1: need to know. You know, that can really help drive

1637
01:28:25,120 --> 01:28:27,400
Speaker 1: you know, on Congress that's punch Bowl, and that's not

1638
01:28:27,520 --> 01:28:32,439
Speaker 1: a cheap publication. But you know the DC publication world, right,

1639
01:28:32,479 --> 01:28:38,400
Speaker 1: whether it's your subscription, and it really is punchable for Congress.

1640
01:28:39,400 --> 01:28:41,800
Speaker 1: You know, this is what gets really expensive in the

1641
01:28:41,800 --> 01:28:44,000
Speaker 1: world of journalism, is being able to keep track of

1642
01:28:44,439 --> 01:28:50,320
Speaker 1: everybody else's work, whether it's the punch Bowl, Wall Street Journal, Politico, Axios.

1643
01:28:52,160 --> 01:28:55,240
Speaker 1: None of this stuff is free, and in many cases

1644
01:28:55,320 --> 01:29:00,400
Speaker 1: it's exuberant, it's uber expensive. But I think back on

1645
01:29:00,439 --> 01:29:03,280
Speaker 1: what I needed as a subscription to my old stomping grounds,

1646
01:29:03,280 --> 01:29:07,000
Speaker 1: the Hotline. You know, if you did punch Bowl, Wall

1647
01:29:07,000 --> 01:29:10,840
Speaker 1: Street Journal, Politico and the Hotline, that's probably what a

1648
01:29:10,880 --> 01:29:14,800
Speaker 1: membership to the National Press Club would cost. And I

1649
01:29:14,800 --> 01:29:19,400
Speaker 1: would dare say those publications if your niece doesn't end

1650
01:29:19,479 --> 01:29:21,360
Speaker 1: up working at one of them, and she may end

1651
01:29:21,439 --> 01:29:24,320
Speaker 1: up and yes, over time, if one of the not

1652
01:29:24,400 --> 01:29:30,080
Speaker 1: every news organization. Well we'll spring for some of these subscriptions.

1653
01:29:30,120 --> 01:29:33,639
Speaker 1: So anyway that I'm just thinking out loud, but that's

1654
01:29:33,840 --> 01:29:37,679
Speaker 1: probably you know, where I would begin to sort of engrace,

1655
01:29:37,720 --> 01:29:40,920
Speaker 1: you know, to have help somebody sort of get used

1656
01:29:40,960 --> 01:29:43,679
Speaker 1: to the rhythms of this town, you know, from an

1657
01:29:43,680 --> 01:29:47,439
Speaker 1: internal cultural sense, and that's where punch Bowl, Politico Playbook

1658
01:29:47,479 --> 01:29:50,719
Speaker 1: in particular come come in. And then with this particular

1659
01:29:50,760 --> 01:29:52,840
Speaker 1: White House axios in the Wall Street Journal, I think

1660
01:29:52,840 --> 01:29:55,800
Speaker 1: I have the best access to the to the west

1661
01:29:55,800 --> 01:30:01,160
Speaker 1: wing and have the probably the more consistent scoopages. You know,

1662
01:30:01,240 --> 01:30:03,000
Speaker 1: this is no disrespect to the times in the Post,

1663
01:30:03,040 --> 01:30:07,479
Speaker 1: but in this case, the times in the Post are

1664
01:30:07,479 --> 01:30:11,920
Speaker 1: a bit cheaper, and one could argue she could she

1665
01:30:11,920 --> 01:30:15,040
Speaker 1: could pay for those. Those other ones are a little

1666
01:30:15,040 --> 01:30:18,080
Speaker 1: price here, So just a thought. Anyway, I hope that helps, Bill,

1667
01:30:18,160 --> 01:30:22,559
Speaker 1: and congratulations and you know, at some point we're going

1668
01:30:22,600 --> 01:30:24,479
Speaker 1: to be hiring interns here at the Check Podcast, but

1669
01:30:24,560 --> 01:30:29,320
Speaker 1: we haven't fully fully expanded there for now. Next up

1670
01:30:29,360 --> 01:30:31,400
Speaker 1: is Howard W. From Los Angeles. Any rates, when the

1671
01:30:31,439 --> 01:30:34,280
Speaker 1: Declaration of Independence was signed, were we a country or

1672
01:30:34,320 --> 01:30:36,960
Speaker 1: thirteen colonies? Didn't we actually become a country when the

1673
01:30:37,000 --> 01:30:41,760
Speaker 1: Articles of Confederation ratified in seventeen eighty one. That is

1674
01:30:41,800 --> 01:30:45,280
Speaker 1: a fair point, right, we declared our independence and then

1675
01:30:45,400 --> 01:30:47,960
Speaker 1: we didn't really and we sort of formed an army,

1676
01:30:48,280 --> 01:30:51,400
Speaker 1: and you know, there was a coalition and it was

1677
01:30:52,200 --> 01:30:55,200
Speaker 1: I guess you could call it a tree, you know,

1678
01:30:55,400 --> 01:31:02,519
Speaker 1: a coalition of the willing, But it's a it's man,

1679
01:31:02,560 --> 01:31:04,200
Speaker 1: why do you want to mess up a good myth? Right?

1680
01:31:04,200 --> 01:31:05,320
Speaker 1: Are you telling us we have to put off the

1681
01:31:05,320 --> 01:31:09,599
Speaker 1: two hundred and fiftieth birthday for at least another six years?

1682
01:31:09,920 --> 01:31:12,880
Speaker 1: But it's a and we certainly have only been a

1683
01:31:12,920 --> 01:31:18,080
Speaker 1: constitutional republic I guess is probably since since seventeen eighty one,

1684
01:31:18,200 --> 01:31:23,280
Speaker 1: so the first time we attempted a constitution. But hey,

1685
01:31:23,320 --> 01:31:26,639
Speaker 1: that's a that's a that's a that's a fair that's

1686
01:31:26,680 --> 01:31:30,639
Speaker 1: a fair argument. So I had a little fun. You'll

1687
01:31:30,640 --> 01:31:35,280
Speaker 1: appreciate this. So I decided to tap I typed your

1688
01:31:35,360 --> 01:31:39,240
Speaker 1: question into chat cheept to see what our AI would say,

1689
01:31:39,920 --> 01:31:42,439
Speaker 1: when did America become an actual country? So here's the

1690
01:31:42,479 --> 01:31:45,280
Speaker 1: response that chat ChiPT gave and he goes, well, that

1691
01:31:45,280 --> 01:31:47,840
Speaker 1: depends on what you mean by become a country, because

1692
01:31:47,840 --> 01:31:49,640
Speaker 1: the United States didn't flip a switch over night. It

1693
01:31:49,640 --> 01:31:52,280
Speaker 1: emerged in stages, and each one answers your question a

1694
01:31:52,320 --> 01:31:57,000
Speaker 1: little differently. So the Declaration of Independence chat Chept calls

1695
01:31:57,040 --> 01:32:02,000
Speaker 1: a symbolic birth that they're commonly simply declared themselves independent

1696
01:32:02,000 --> 01:32:08,360
Speaker 1: from Great Britain. So there's that. Seventeen eighty three the

1697
01:32:08,360 --> 01:32:11,400
Speaker 1: Treaty of Paris, So this is when the international world

1698
01:32:11,439 --> 01:32:14,439
Speaker 1: recognized America as a country. The Treaty of Paris officially

1699
01:32:14,520 --> 01:32:17,360
Speaker 1: ended the war. Britain had to formally recognize the United

1700
01:32:17,400 --> 01:32:20,679
Speaker 1: States as a sovereign nation, and in other countries would

1701
01:32:20,680 --> 01:32:26,000
Speaker 1: acknowledge the existence of the United States. So they argue

1702
01:32:26,000 --> 01:32:29,559
Speaker 1: that the legal recognition recognized moment then would be seventeen

1703
01:32:29,640 --> 01:32:34,040
Speaker 1: eighty three, seventeen eighty nine, our Constitution takes effect, so

1704
01:32:34,600 --> 01:32:37,880
Speaker 1: you know, and you could then make your argument about

1705
01:32:37,880 --> 01:32:44,519
Speaker 1: the articles and confederation and that that being so, there

1706
01:32:44,520 --> 01:32:50,080
Speaker 1: you go, and arguably we still have to wait until

1707
01:32:53,479 --> 01:32:55,800
Speaker 1: we may have to. The two hundred and fiftieth anniversary

1708
01:32:55,840 --> 01:33:01,840
Speaker 1: of the Constitutional Republic would be the next decade, and

1709
01:33:01,880 --> 01:33:06,920
Speaker 1: so our two hundred and fiftieth celebration for the Constitution,

1710
01:33:07,439 --> 01:33:10,759
Speaker 1: I assume we'll all be centered around Philadelphia in twenty

1711
01:33:10,800 --> 01:33:16,320
Speaker 1: thirty nine, So make your reservations now. All right. That

1712
01:33:16,439 --> 01:33:19,120
Speaker 1: was a fun little exercise and I love the provocative question.

1713
01:33:21,479 --> 01:33:24,400
Speaker 1: See Howard, these are my listeners. This is what I expect.

1714
01:33:24,880 --> 01:33:29,080
Speaker 1: I expect this kind of this kind of nuance in details.

1715
01:33:29,120 --> 01:33:29,559
Speaker 2: So thank you.

1716
01:33:30,240 --> 01:33:32,960
Speaker 1: Next question comes from Brad Chuck. Greetings from Grand Rapids

1717
01:33:32,960 --> 01:33:36,799
Speaker 1: in Michigan's third district, and thanks for the great podcast.

1718
01:33:36,840 --> 01:33:39,080
Speaker 1: You often say citizens should reach out to their representatives,

1719
01:33:39,120 --> 01:33:40,479
Speaker 1: But what if you're a member of Congress like my

1720
01:33:40,520 --> 01:33:45,000
Speaker 1: representative Hillary Schulton and Michigan senators already share your concerns?

1721
01:33:45,160 --> 01:33:48,040
Speaker 1: Is it still worthwhile to contact them just to reinforce support,

1722
01:33:48,120 --> 01:33:50,320
Speaker 1: encourage them to push even harder in Washington? How much

1723
01:33:50,400 --> 01:33:53,479
Speaker 1: influence do constituents really have when they're asking leaders who

1724
01:33:53,479 --> 01:33:55,920
Speaker 1: already agree with them to do more. I think it's

1725
01:33:55,960 --> 01:33:58,519
Speaker 1: more of the tactical. You know, it's interesting. I am

1726
01:33:59,600 --> 01:34:02,599
Speaker 1: one of the fun pleasures I have in teaching. As

1727
01:34:02,600 --> 01:34:05,080
Speaker 1: many of you know, I teach a class called how

1728
01:34:05,120 --> 01:34:10,040
Speaker 1: Washington Works for USC and it's their DC program USC

1729
01:34:10,160 --> 01:34:12,200
Speaker 1: University of Southern California, and I to be confused with

1730
01:34:12,240 --> 01:34:15,360
Speaker 1: my friends in Columbia, South Carolina who believe the University

1731
01:34:15,400 --> 01:34:21,400
Speaker 1: of South Carolina is the original usc AS. I like

1732
01:34:21,400 --> 01:34:23,840
Speaker 1: to say to them, have a more successful program and

1733
01:34:23,920 --> 01:34:28,519
Speaker 1: you can reclaim usc IS yours. Sorry couldn't help myself,

1734
01:34:29,640 --> 01:34:34,160
Speaker 1: but about half the class is interning on the hill.

1735
01:34:34,200 --> 01:34:35,880
Speaker 1: And when you intern on the hill, what does that mean?

1736
01:34:36,120 --> 01:34:38,880
Speaker 1: You answer the phones? But answering the phones in a

1737
01:34:38,920 --> 01:34:43,759
Speaker 1: congressional office is fascinating, especially when you're a young intern,

1738
01:34:43,800 --> 01:34:49,360
Speaker 1: because usually it's calls from constituents, not always, you know,

1739
01:34:49,439 --> 01:34:56,200
Speaker 1: sometimes they're planned campaign sometimes they're genuine locals. But here's

1740
01:34:56,240 --> 01:34:59,600
Speaker 1: what I can tell you. I've learned from these conversations

1741
01:34:59,640 --> 01:35:02,320
Speaker 1: I've had these with people that answer phones over the years.

1742
01:35:02,320 --> 01:35:04,320
Speaker 1: It's all offices want to keep track. They want to

1743
01:35:04,360 --> 01:35:08,160
Speaker 1: know what issues are coming up, what's being called in

1744
01:35:08,200 --> 01:35:09,679
Speaker 1: it because a lot of times it is an early

1745
01:35:09,720 --> 01:35:11,479
Speaker 1: warning system. All of a sudden, you get some there

1746
01:35:11,560 --> 01:35:15,160
Speaker 1: might be some local thing that's happening that the congressional

1747
01:35:15,160 --> 01:35:17,559
Speaker 1: office is getting a lot of calls on. It actually

1748
01:35:17,640 --> 01:35:19,680
Speaker 1: is something that a local mayor ought to deal with.

1749
01:35:19,720 --> 01:35:21,400
Speaker 1: Maybe it's something the mayor of Grand Rapids has to

1750
01:35:21,439 --> 01:35:23,639
Speaker 1: deal with, and they're able to say, hey, we're getting

1751
01:35:23,640 --> 01:35:25,040
Speaker 1: calls about this. Are you aware of this?

1752
01:35:25,720 --> 01:35:25,920
Speaker 2: Right?

1753
01:35:26,000 --> 01:35:28,599
Speaker 1: So it can be just sort of an early warning system, right,

1754
01:35:31,280 --> 01:35:34,439
Speaker 1: but they but but the members care, and it's it's

1755
01:35:37,439 --> 01:35:41,120
Speaker 1: I think there's more power in numbers, right, But you

1756
01:35:41,120 --> 01:35:43,280
Speaker 1: don't want to look like you're manufacturing and you're reading

1757
01:35:43,320 --> 01:35:46,720
Speaker 1: from a script. So the point is is that sometimes

1758
01:35:46,760 --> 01:35:50,839
Speaker 1: it's not you may your representatives may support you generally,

1759
01:35:50,960 --> 01:35:54,519
Speaker 1: but are they doing something specifically? You know, you might

1760
01:35:55,240 --> 01:35:57,479
Speaker 1: you might want to say, how come you're not doing this?

1761
01:35:58,080 --> 01:36:00,360
Speaker 1: You know, I know you share the same concern I

1762
01:36:00,479 --> 01:36:04,240
Speaker 1: do about X. So explain to me why you're not

1763
01:36:04,320 --> 01:36:08,120
Speaker 1: doing why? You know. Maybe let's say you're you're skeptical

1764
01:36:08,160 --> 01:36:11,040
Speaker 1: of this around war, Well, maybe you might want to

1765
01:36:11,120 --> 01:36:15,240
Speaker 1: encourage them. Look, don't just vote symbolically, know against funding

1766
01:36:15,280 --> 01:36:17,559
Speaker 1: this war. What are you going to do to actually

1767
01:36:17,640 --> 01:36:20,080
Speaker 1: try to bring this to an end? You know, maybe

1768
01:36:20,520 --> 01:36:23,720
Speaker 1: force any answer out of them, force a response out

1769
01:36:23,720 --> 01:36:26,599
Speaker 1: of them. But I you know, or you can call

1770
01:36:26,680 --> 01:36:36,960
Speaker 1: other you know, these these these members of Congress. You

1771
01:36:37,000 --> 01:36:39,280
Speaker 1: won't for some of them, you won't be as impactful.

1772
01:36:39,280 --> 01:36:44,000
Speaker 1: But they do log complaints that come in from constituents

1773
01:36:44,000 --> 01:36:46,519
Speaker 1: that don't live in their district or state and just say, look,

1774
01:36:46,560 --> 01:36:48,519
Speaker 1: I'm and you should be honest about it, and I'm

1775
01:36:48,560 --> 01:36:50,800
Speaker 1: calling you, you know, my my senator's already believe in this,

1776
01:36:50,880 --> 01:36:53,559
Speaker 1: but I'm concerned, you know, and maybe find a way

1777
01:36:53,600 --> 01:36:55,559
Speaker 1: to connect with that senator. I you know, I thought

1778
01:36:56,000 --> 01:36:59,120
Speaker 1: Senator X really was worried about why so why why

1779
01:36:59,120 --> 01:37:05,920
Speaker 1: aren't they also standing up on this issue? But there's

1780
01:37:05,920 --> 01:37:11,000
Speaker 1: all sorts of ways to I think, influence a senator

1781
01:37:11,000 --> 01:37:13,360
Speaker 1: that you think already shares some of your values. Maybe

1782
01:37:13,360 --> 01:37:15,439
Speaker 1: it's more in what are they doing about it? How

1783
01:37:15,439 --> 01:37:17,720
Speaker 1: are they expressing themselves? You know, It's one thing to

1784
01:37:17,720 --> 01:37:20,800
Speaker 1: share your concerns, it's and other things to do some action.

1785
01:37:21,840 --> 01:37:25,240
Speaker 1: So that'd be another way to look at it. Next

1786
01:37:25,320 --> 01:37:27,200
Speaker 1: question comes from David and he writes, Chuck, I'm a

1787
01:37:27,240 --> 01:37:29,479
Speaker 1: twenty nine year old living in California now, but previously

1788
01:37:29,520 --> 01:37:31,720
Speaker 1: a federal worker in DC before being cut during last

1789
01:37:31,760 --> 01:37:35,000
Speaker 1: year's doze terminations. You've often mentioned mississippis a state to watch,

1790
01:37:35,000 --> 01:37:37,200
Speaker 1: even though most analysts don't see it as viable for Democrats.

1791
01:37:37,240 --> 01:37:39,880
Speaker 1: What can we learn from the Mississippi primaris past Tuesday

1792
01:37:39,880 --> 01:37:41,519
Speaker 1: in terms of turn out in enthusiasm and do you

1793
01:37:41,520 --> 01:37:44,559
Speaker 1: see the same potential for competitiveness there that we've seen

1794
01:37:44,560 --> 01:37:46,719
Speaker 1: in southern races like Alabama in twenty seventeen, in Georgia

1795
01:37:46,760 --> 01:37:50,800
Speaker 1: in twenty twenty. Well, look, I've had this Mississippi conversation

1796
01:37:50,880 --> 01:37:55,559
Speaker 1: with quite a few people, and I'm trying to remember recently.

1797
01:37:55,560 --> 01:37:57,080
Speaker 1: I feel like I can't remember if I did it

1798
01:37:57,080 --> 01:38:01,200
Speaker 1: in this podcast or it was a newspair episode, but

1799
01:38:01,280 --> 01:38:03,559
Speaker 1: when we talk about different states, or it may have been.

1800
01:38:06,920 --> 01:38:12,599
Speaker 1: It may have been a conversation I had with when

1801
01:38:12,600 --> 01:38:15,799
Speaker 1: I was moderating a panel up at Harvard and Jamie Harrison,

1802
01:38:15,840 --> 01:38:18,160
Speaker 1: who was the former DNC chair and candidate for office

1803
01:38:18,160 --> 01:38:22,360
Speaker 1: in South Carolina, and it was in this You know,

1804
01:38:22,400 --> 01:38:26,000
Speaker 1: the whole point of pointing out of Mississippi, for one thing,

1805
01:38:26,120 --> 01:38:31,160
Speaker 1: is is looking at what the electoral map could look

1806
01:38:31,200 --> 01:38:33,680
Speaker 1: like in twenty thirty two. When we have reapportionment in

1807
01:38:33,720 --> 01:38:37,720
Speaker 1: the electoral college, numbers shift again and the power continues

1808
01:38:37,760 --> 01:38:39,400
Speaker 1: to grow in the Sun Belt and in the South.

1809
01:38:39,920 --> 01:38:42,720
Speaker 1: So Democrats have to make inroads in the Sun Belt, right,

1810
01:38:42,760 --> 01:38:45,160
Speaker 1: You've got to make inroads where the people live. Texas

1811
01:38:45,160 --> 01:38:47,320
Speaker 1: and Florida are two obvious targets. They're big, they're huge,

1812
01:38:47,360 --> 01:38:51,639
Speaker 1: and they're very difficult. Georgia is a success story. It's

1813
01:38:51,680 --> 01:38:54,640
Speaker 1: an organizational success story. And the point is when you

1814
01:38:54,720 --> 01:38:59,840
Speaker 1: look at the population in Mississippi and you look at

1815
01:39:00,080 --> 01:39:02,519
Speaker 1: look at those general election results, they're always you know,

1816
01:39:03,280 --> 01:39:07,160
Speaker 1: Sydney Hyde Smith versus Mike Esipe in twenty eighteen fifty

1817
01:39:07,200 --> 01:39:11,160
Speaker 1: four to forty six race, that's not a blowout. That

1818
01:39:11,280 --> 01:39:19,400
Speaker 1: does not mean Mississippi's not competitive. Tate Reeves and the

1819
01:39:19,439 --> 01:39:27,640
Speaker 1: Presley cousin was also somebody that was also one of

1820
01:39:27,680 --> 01:39:30,600
Speaker 1: the closest governor's races in thirty years or in the

1821
01:39:30,680 --> 01:39:36,400
Speaker 1: last twenty years. Excuse me, but what you have is

1822
01:39:36,439 --> 01:39:39,360
Speaker 1: an under investment in the state party. And there's a

1823
01:39:39,760 --> 01:39:44,479
Speaker 1: there's an under voter, there's an under there's basically a

1824
01:39:44,479 --> 01:39:48,160
Speaker 1: lot of unregistered African American voters in Mississippi who've kind

1825
01:39:48,160 --> 01:39:51,000
Speaker 1: of given up on the system. It was a similar

1826
01:39:51,040 --> 01:39:55,760
Speaker 1: phenomenon in Alabama, and you had Doug Jones will tell

1827
01:39:55,760 --> 01:39:58,479
Speaker 1: you it was black women in particular that you know,

1828
01:39:58,560 --> 01:40:02,080
Speaker 1: helped organize for his camp and that upset over Roy Moore. Now,

1829
01:40:02,800 --> 01:40:04,800
Speaker 1: there's nothing like having an opponent who's an accused of

1830
01:40:04,800 --> 01:40:07,640
Speaker 1: pedophile in order to assist you in a in a

1831
01:40:08,640 --> 01:40:11,280
Speaker 1: very deeply religious state like Alabama, and I don't think

1832
01:40:11,320 --> 01:40:16,760
Speaker 1: we should we should overlook that factoid on that one

1833
01:40:16,840 --> 01:40:21,840
Speaker 1: success in Alabama. But Mississippi there's more consistent. You see it, right,

1834
01:40:21,840 --> 01:40:24,800
Speaker 1: there's a lower ceiling for Republicans than there is in

1835
01:40:24,840 --> 01:40:32,280
Speaker 1: an Alabama or but it's it's not a one cycle investment, right.

1836
01:40:32,320 --> 01:40:35,280
Speaker 1: And I think the problem, the difference between the Democrats

1837
01:40:35,280 --> 01:40:38,600
Speaker 1: and the Republicans in my adult lifetime is that Republicans

1838
01:40:39,120 --> 01:40:42,040
Speaker 1: have always taken a longer view in trying to flip

1839
01:40:42,040 --> 01:40:45,480
Speaker 1: a state and Democrats are always looking for a shortcut,

1840
01:40:45,680 --> 01:40:48,080
Speaker 1: and they've not taken that longer. One of the few

1841
01:40:48,120 --> 01:40:51,799
Speaker 1: exceptions to the longer views has been Arizona in Georgia,

1842
01:40:52,240 --> 01:40:55,880
Speaker 1: and now that is paid necessary dividends, right, it's kept

1843
01:40:55,880 --> 01:40:59,080
Speaker 1: them in the game. Without Georgia and Arizona, the downfall

1844
01:40:59,120 --> 01:41:02,439
Speaker 1: of the Midwestern states and of Florida and Ohio in

1845
01:41:02,439 --> 01:41:06,040
Speaker 1: particular would be catastrophic for the party. But it's not

1846
01:41:06,400 --> 01:41:11,519
Speaker 1: because of a concerted twenty year effort to essentially get

1847
01:41:11,560 --> 01:41:15,439
Speaker 1: competitive in Georgia and Arizona. And you had look the

1848
01:41:16,160 --> 01:41:20,200
Speaker 1: losing Stacey Abrams campaigns, did a lot made a lot

1849
01:41:20,200 --> 01:41:23,920
Speaker 1: of progress for George Democrats, and that's what you need.

1850
01:41:23,960 --> 01:41:29,520
Speaker 1: You need somebody that sort of, you know, makes progress

1851
01:41:29,520 --> 01:41:33,320
Speaker 1: in losing and sticks to it. And in Mississippi, you've

1852
01:41:33,320 --> 01:41:38,800
Speaker 1: had too many examples of well funded, singular campaigns that

1853
01:41:38,840 --> 01:41:43,760
Speaker 1: have never sort of stayed engaged after they've lost. And

1854
01:41:43,880 --> 01:41:47,280
Speaker 1: until you do, that's that's the moment. But it's if

1855
01:41:47,320 --> 01:41:49,240
Speaker 1: you look at the population numbers and you look at

1856
01:41:49,280 --> 01:41:52,240
Speaker 1: the voter registration numbers, that's why you see if you

1857
01:41:52,360 --> 01:41:56,559
Speaker 1: ever could maximize African American voter registration in Mississippi, you

1858
01:41:56,640 --> 01:41:59,880
Speaker 1: suddenly are in a different place competitively in that state.

1859
01:42:10,479 --> 01:42:14,639
Speaker 1: Next question comes from JR. JR. Rights. Hey, second time asker,

1860
01:42:14,680 --> 01:42:17,559
Speaker 1: Thanks again for taking questions. Virginia's leg Governor Spamberger signature

1861
01:42:17,600 --> 01:42:20,600
Speaker 1: bringing the electoral vote count for its triggering up to

1862
01:42:20,640 --> 01:42:22,439
Speaker 1: two twenty two still a ways off from the required

1863
01:42:22,439 --> 01:42:23,840
Speaker 1: two to seventy. But what do you think the odds

1864
01:42:23,840 --> 01:42:25,800
Speaker 1: are that the MPV will gain momentum and get the

1865
01:42:25,840 --> 01:42:28,040
Speaker 1: requisite numbers to go into effect. Do you think Trump's

1866
01:42:28,040 --> 01:42:30,280
Speaker 1: popular vote win in twenty twenty four may jostle free

1867
01:42:30,280 --> 01:42:33,040
Speaker 1: some reticent red states to join. Thanks interesting in your

1868
01:42:33,080 --> 01:42:36,080
Speaker 1: thoughts on the MPV Compact as a whole as well. Well, look,

1869
01:42:36,120 --> 01:42:38,720
Speaker 1: I've I dug into the compact quite a bit about

1870
01:42:38,760 --> 01:42:40,680
Speaker 1: fifteen or twenty years ago when it first started up.

1871
01:42:40,720 --> 01:42:43,559
Speaker 1: The guy who founded the University of Phoenix was sort

1872
01:42:43,600 --> 01:42:45,519
Speaker 1: of the initial brainchild of this. By the way, for

1873
01:42:45,560 --> 01:42:49,200
Speaker 1: what it's worth, and this goes back to two thousand

1874
01:42:49,200 --> 01:42:50,840
Speaker 1: and three, two thousand and four to two thousand and five,

1875
01:42:51,439 --> 01:42:54,680
Speaker 1: memory serves, I have this vision. I remember packing my

1876
01:42:54,720 --> 01:42:56,680
Speaker 1: office at the Hotline to move to NBC, and I

1877
01:42:56,680 --> 01:43:01,960
Speaker 1: remember this guy's the Voter Compact pamphlet wasn't a pamphlet.

1878
01:43:02,000 --> 01:43:05,240
Speaker 1: It was this massive if you remember the remember the

1879
01:43:05,280 --> 01:43:10,080
Speaker 1: old chain Kinkos, It was like a Kinko's put together book,

1880
01:43:10,680 --> 01:43:16,479
Speaker 1: if you will, And I you know, just to if

1881
01:43:16,600 --> 01:43:18,240
Speaker 1: people are going to wonder how this works. So the

1882
01:43:18,280 --> 01:43:21,439
Speaker 1: idea is that states, would you know, which is do

1883
01:43:21,560 --> 01:43:24,360
Speaker 1: the thanks to the commerce clause perveralily or states will

1884
01:43:24,400 --> 01:43:29,360
Speaker 1: agree that if if there are the minute there's enough

1885
01:43:29,400 --> 01:43:33,320
Speaker 1: states that add up to two hundred and seventy electoral votes,

1886
01:43:33,800 --> 01:43:39,760
Speaker 1: then the states agree that their electoral votes will go

1887
01:43:40,000 --> 01:43:45,080
Speaker 1: to the winner of the popular vote. And but not,

1888
01:43:45,360 --> 01:43:48,200
Speaker 1: but it doesn't trigger until there are enough states that

1889
01:43:48,280 --> 01:43:52,599
Speaker 1: add up to two hundred and seventy electoral votes. And

1890
01:43:52,720 --> 01:43:55,920
Speaker 1: so it is, as you noted, we're up to two

1891
01:43:56,000 --> 01:43:59,639
Speaker 1: twenty two, so there's still there's still forty eight electoral

1892
01:43:59,720 --> 01:44:04,040
Speaker 1: votes away. I haven't seen the latest list of states,

1893
01:44:04,080 --> 01:44:05,719
Speaker 1: but I think a lot of the big states haven't

1894
01:44:05,720 --> 01:44:17,800
Speaker 1: done it yet, if I'm not mistaken. So I'm a

1895
01:44:17,840 --> 01:44:23,200
Speaker 1: skeptic that it will be accepted by the public. I

1896
01:44:23,240 --> 01:44:25,080
Speaker 1: think you would have. I mean, look at all of

1897
01:44:25,120 --> 01:44:30,919
Speaker 1: the rage you see among Nebraska Republicans, the loan electoral

1898
01:44:31,000 --> 01:44:38,639
Speaker 1: vote that continues to nag at Republicans right with Omaha

1899
01:44:38,760 --> 01:44:44,559
Speaker 1: sort of almost now consistently voting voting against the state's interest,

1900
01:44:48,160 --> 01:44:51,320
Speaker 1: and the calls and demands for change, and the minute

1901
01:44:51,439 --> 01:44:55,880
Speaker 1: this compact has agreed to, the second a state feels

1902
01:44:55,880 --> 01:44:59,280
Speaker 1: as if their votes cost their guy an election, then

1903
01:44:59,320 --> 01:45:02,439
Speaker 1: there's going to right. So I'm skeptical that this will ever,

1904
01:45:02,920 --> 01:45:05,519
Speaker 1: even when it hits the requisite number, that it will

1905
01:45:05,600 --> 01:45:10,240
Speaker 1: ever be implemented. That essentially, this is an easy thing

1906
01:45:10,280 --> 01:45:12,840
Speaker 1: to say you're willing to do before you get to

1907
01:45:12,920 --> 01:45:16,599
Speaker 1: the number. Itself now on you. Once you catch once

1908
01:45:16,600 --> 01:45:19,880
Speaker 1: you're the dog that catches the proverbial car. What actually

1909
01:45:19,880 --> 01:45:21,639
Speaker 1: happens here? What do you plan to do with this?

1910
01:45:23,840 --> 01:45:30,600
Speaker 1: You know, I I'm I think we need a constitutional

1911
01:45:30,600 --> 01:45:32,599
Speaker 1: amendment to change this. If you want to change it.

1912
01:45:34,240 --> 01:45:36,400
Speaker 1: My work around these days is doubling the size of

1913
01:45:36,439 --> 01:45:38,280
Speaker 1: the house. If you did that, then you would write,

1914
01:45:38,479 --> 01:45:42,000
Speaker 1: then the electoral college would follow the popular vote in

1915
01:45:42,200 --> 01:45:44,840
Speaker 1: ninety eight percent of the circumstances, rather than in the

1916
01:45:44,880 --> 01:45:47,760
Speaker 1: situation we're in now, which is only about something like

1917
01:45:47,800 --> 01:45:49,880
Speaker 1: eighty five to ninety percent of the time, will the

1918
01:45:50,000 --> 01:45:54,639
Speaker 1: popular vote in the electoral vote be the same winner?

1919
01:45:56,720 --> 01:45:59,960
Speaker 1: And that that GAP's a big deal. That's a big

1920
01:46:00,240 --> 01:46:03,479
Speaker 1: you know, as I like to say, you know, would

1921
01:46:03,520 --> 01:46:05,360
Speaker 1: you get on a plane that had a ninety percent

1922
01:46:05,479 --> 01:46:10,200
Speaker 1: chance of landing safely? Would you get on a plane

1923
01:46:10,200 --> 01:46:12,920
Speaker 1: that had a ninety nine percent chance of landing safely? Right?

1924
01:46:14,400 --> 01:46:16,880
Speaker 1: You do that all the time. Nothing's one hundred percent.

1925
01:46:17,640 --> 01:46:20,040
Speaker 1: But once you hear that it's ninety how about eighty five?

1926
01:46:20,920 --> 01:46:21,160
Speaker 2: Right?

1927
01:46:22,320 --> 01:46:24,080
Speaker 1: Right? Then it's suddenly you're like, oh, I know, plenty

1928
01:46:24,120 --> 01:46:26,880
Speaker 1: of one in fifteen you know, I'm fifteen percent chance

1929
01:46:26,920 --> 01:46:29,160
Speaker 1: things happen. There's a ten percent chance of something happening

1930
01:46:29,240 --> 01:46:33,479
Speaker 1: wait a minute, that's that that could actually happen. So,

1931
01:46:36,160 --> 01:46:40,360
Speaker 1: you know, I'm I'm so, I'm I'm skeptical that this

1932
01:46:40,400 --> 01:46:44,160
Speaker 1: would ever successfully be implemented because I think there's states

1933
01:46:44,160 --> 01:46:46,840
Speaker 1: that have agreed to do it. You'll see, especially since

1934
01:46:46,840 --> 01:46:48,479
Speaker 1: we've become so one party. I mean, look at a

1935
01:46:48,520 --> 01:46:52,240
Speaker 1: state like Virginia suddenly as a one party controlled state.

1936
01:46:52,800 --> 01:46:54,840
Speaker 1: It's still kind of a I would argue, it's a

1937
01:46:54,880 --> 01:46:58,200
Speaker 1: fifty five to forty five dem lean overall, right, but

1938
01:46:58,280 --> 01:47:00,920
Speaker 1: it behaves like it's an eighty twenty state these days

1939
01:47:01,560 --> 01:47:04,320
Speaker 1: with its legislature and its democratic governance. Right, It's just

1940
01:47:04,360 --> 01:47:06,960
Speaker 1: like Mississippi's really like a fifty five to forty five state,

1941
01:47:07,000 --> 01:47:09,320
Speaker 1: but it behaves in governance if it's an eighty twenty

1942
01:47:09,520 --> 01:47:14,880
Speaker 1: Republican state. And so that's where I you know, So

1943
01:47:14,920 --> 01:47:17,960
Speaker 1: I'm I needed, like I said, I need to do

1944
01:47:17,960 --> 01:47:19,920
Speaker 1: a better analysis of how many which states in there.

1945
01:47:19,960 --> 01:47:21,640
Speaker 1: But I just have a feeling a bunch of them

1946
01:47:21,640 --> 01:47:25,000
Speaker 1: will chicken out when this starts, and just when it

1947
01:47:25,000 --> 01:47:27,240
Speaker 1: looks like they're getting to somebody, somebody will you know,

1948
01:47:27,640 --> 01:47:30,640
Speaker 1: it'll be it'll be like lucying the football. You know,

1949
01:47:30,720 --> 01:47:33,160
Speaker 1: she'll pull it away, some state will withdraw from the

1950
01:47:33,200 --> 01:47:35,840
Speaker 1: compact and all of a sudden they're short again. So

1951
01:47:37,040 --> 01:47:40,400
Speaker 1: you know, that's my guess. And again I go back

1952
01:47:40,439 --> 01:47:45,600
Speaker 1: to the the easiest way to fix this is just

1953
01:47:45,680 --> 01:47:48,439
Speaker 1: expanding the House. Then you don't even need a constitutional amendment.

1954
01:47:48,600 --> 01:47:54,040
Speaker 1: After that a constitutional amendment. But I do think you're

1955
01:47:54,080 --> 01:47:55,839
Speaker 1: not going to be able to get the constitutional amendment

1956
01:47:56,960 --> 01:48:00,839
Speaker 1: until you convince both parties that this will be helpful

1957
01:48:00,880 --> 01:48:04,479
Speaker 1: to that. And I think repealing the electoral College won't

1958
01:48:04,479 --> 01:48:08,040
Speaker 1: get you there. But expanding the House in theory benefits.

1959
01:48:08,200 --> 01:48:11,519
Speaker 1: You can make a case that it can strengthen both

1960
01:48:11,560 --> 01:48:14,200
Speaker 1: parties depending on how you look at it. You know,

1961
01:48:14,240 --> 01:48:18,000
Speaker 1: shouldn't you have more voting power in Congress than Wyoming has? Right?

1962
01:48:18,000 --> 01:48:21,439
Speaker 1: Shouldn't you have more voting power in Congress than Delaware has?

1963
01:48:21,520 --> 01:48:21,640
Speaker 2: Right?

1964
01:48:21,680 --> 01:48:23,360
Speaker 1: You can make that case to a Republican state or

1965
01:48:23,360 --> 01:48:28,320
Speaker 1: a democratic state. So that's why I sort of lean

1966
01:48:28,400 --> 01:48:32,680
Speaker 1: more in that territory. But thanks for asking about that.

1967
01:48:32,880 --> 01:48:35,679
Speaker 1: The MPV is always I got into it until I didn't.

1968
01:48:38,040 --> 01:48:41,680
Speaker 1: Next question comes from Kenny from Massive Pequa. Thank you

1969
01:48:41,720 --> 01:48:43,439
Speaker 1: for letting me say Massive Peak would approve that I

1970
01:48:43,479 --> 01:48:45,200
Speaker 1: can say it. Hey, Chuck, I share your dad's love

1971
01:48:45,200 --> 01:48:47,240
Speaker 1: of coins collecting, and while the bi centennial coins may

1972
01:48:47,280 --> 01:48:50,160
Speaker 1: not be worth much more than face values, sometimes the

1973
01:48:50,200 --> 01:48:52,200
Speaker 1: memories attached to them are priceless. My wife and I

1974
01:48:52,280 --> 01:48:54,639
Speaker 1: also have a question, what's the deal with daylight saving time?

1975
01:48:54,960 --> 01:48:58,000
Speaker 1: With Senator Rubio no longer championing the issue in the Senate,

1976
01:48:58,040 --> 01:49:00,160
Speaker 1: is there anyone likely to take up the push to

1977
01:49:00,200 --> 01:49:02,439
Speaker 1: either keep it permanent or in the clock changes together

1978
01:49:02,479 --> 01:49:05,240
Speaker 1: twice a year of the timeshift disrupts sleep, community and families,

1979
01:49:05,360 --> 01:49:07,280
Speaker 1: So is there any real chance Congress fundly fixes it?

1980
01:49:07,360 --> 01:49:10,160
Speaker 1: Kenny from Messapequa, Kenny, I hope you heard my time

1981
01:49:10,200 --> 01:49:14,519
Speaker 1: Machine segment earlier this week on this very issue, the

1982
01:49:14,520 --> 01:49:18,880
Speaker 1: initial creation of time zones, daylight saving and how often

1983
01:49:18,960 --> 01:49:22,920
Speaker 1: we've the problem is there is no solution because the

1984
01:49:23,000 --> 01:49:27,320
Speaker 1: solution for you becomes a problem for somebody else. And

1985
01:49:27,720 --> 01:49:29,840
Speaker 1: I went through three different periods of time where we

1986
01:49:29,920 --> 01:49:33,360
Speaker 1: had sort of permanent versions of you know, temporary permanent

1987
01:49:33,760 --> 01:49:36,719
Speaker 1: versions of our time, and the big the most recent

1988
01:49:36,760 --> 01:49:39,040
Speaker 1: attempt that we did this in seventy four to conserve

1989
01:49:39,160 --> 01:49:41,439
Speaker 1: energy during the energy crisis, where a year long daylight

1990
01:49:41,479 --> 01:49:44,160
Speaker 1: saving time is you basically had a hope. You know,

1991
01:49:44,439 --> 01:49:47,800
Speaker 1: there's a bunch of we had actual accidents. Kids were

1992
01:49:47,880 --> 01:49:53,439
Speaker 1: killed at bus stops because of traffic accidents before the

1993
01:49:53,439 --> 01:49:57,479
Speaker 1: sun came up. So, you know, I think this is

1994
01:49:57,520 --> 01:50:00,120
Speaker 1: one of those cases where and this is why I

1995
01:50:00,200 --> 01:50:03,880
Speaker 1: enjoyed that time machine. You know, before the Railroad's you know,

1996
01:50:04,479 --> 01:50:08,400
Speaker 1: every town noon was slightly different and everybody used the

1997
01:50:08,439 --> 01:50:11,679
Speaker 1: sun to decide while it's noon in Massapequa, which means

1998
01:50:11,680 --> 01:50:14,559
Speaker 1: it's eleven fifty nine some in the next town over,

1999
01:50:14,600 --> 01:50:17,200
Speaker 1: and it's eleven fifty eight two towns from there. Right,

2000
01:50:18,600 --> 01:50:21,200
Speaker 1: So anyway, I encourage you go check my last time

2001
01:50:21,240 --> 01:50:27,439
Speaker 1: Machine episode from the Monday episode. I'd like to think

2002
01:50:27,920 --> 01:50:30,120
Speaker 1: that after you listen to that, you'll be like, oh,

2003
01:50:30,560 --> 01:50:34,320
Speaker 1: this is why it will never change, because it's too complicated.

2004
01:50:34,600 --> 01:50:40,519
Speaker 1: There's no good answer because every every you know, now,

2005
01:50:41,280 --> 01:50:43,759
Speaker 1: when we were in a grarian economy, we just adjusted,

2006
01:50:44,200 --> 01:50:46,519
Speaker 1: you know, when living in this fixed time zone, this

2007
01:50:46,600 --> 01:50:48,760
Speaker 1: is going to be this is going to be the

2008
01:50:49,520 --> 01:50:54,080
Speaker 1: challenge here. And I think everybody has different interests, right

2009
01:50:54,240 --> 01:50:57,559
Speaker 1: if you're you know, I remember as a little kid,

2010
01:50:57,600 --> 01:50:59,800
Speaker 1: I couldn't wait for daylight saving time, and the older

2011
01:50:59,840 --> 01:51:03,360
Speaker 1: I've gotten I resent daylight saving time, right, So I

2012
01:51:03,400 --> 01:51:06,240
Speaker 1: think it that's another issue here, is that there's just

2013
01:51:06,360 --> 01:51:09,960
Speaker 1: not a there's no clean there's there's no clean answer.

2014
01:51:10,880 --> 01:51:13,519
Speaker 1: And in some ways, going through the motions of trying

2015
01:51:13,560 --> 01:51:16,200
Speaker 1: to figure out how we took control of time as

2016
01:51:16,240 --> 01:51:20,360
Speaker 1: it is as a country and as a government, I

2017
01:51:20,479 --> 01:51:25,960
Speaker 1: now feel I feel satisfied with my unsatis with this unsatisfactory,

2018
01:51:27,600 --> 01:51:30,320
Speaker 1: uncomfortable way that we've done this. Now, I do wish

2019
01:51:30,640 --> 01:51:34,880
Speaker 1: we would at least, you know, we keep we keep

2020
01:51:34,920 --> 01:51:37,200
Speaker 1: moving when we do daylight saving time more than the

2021
01:51:37,200 --> 01:51:39,400
Speaker 1: rest of the world does. I wish we would synchronize

2022
01:51:39,439 --> 01:51:42,400
Speaker 1: a little bit better with other countries so that it went,

2023
01:51:42,439 --> 01:51:44,519
Speaker 1: all right, we're all going to move our we're all

2024
01:51:44,560 --> 01:51:46,760
Speaker 1: going to move up an hour early here. But we

2025
01:51:46,840 --> 01:51:50,160
Speaker 1: keep we keep doing the mission creep and I think

2026
01:51:50,200 --> 01:51:54,439
Speaker 1: it also kind of messes things up there. All right,

2027
01:51:54,520 --> 01:51:57,760
Speaker 1: take one more question? No, Actually, I got to end

2028
01:51:57,800 --> 01:51:59,720
Speaker 1: it there. I'm going to wrap things up here.

2029
01:51:59,760 --> 01:51:59,920
Speaker 2: Though.

2030
01:52:00,360 --> 01:52:03,760
Speaker 1: It is the best weekend of one of the best

2031
01:52:03,800 --> 01:52:06,400
Speaker 1: sports weekends of the year. It's the first and second

2032
01:52:06,479 --> 01:52:09,280
Speaker 1: round of the NCAA Tournament. I will tell you I'm

2033
01:52:09,320 --> 01:52:11,880
Speaker 1: such an addict about the NCAA Tournament that I instituted

2034
01:52:12,439 --> 01:52:16,960
Speaker 1: no hotline Fridays for in celebration of the NCAA Tournament.

2035
01:52:17,000 --> 01:52:23,200
Speaker 1: We would literally put everybody we stop. We made Friday holiday.

2036
01:52:23,360 --> 01:52:26,479
Speaker 1: We published right before noon the twelve fifteen tip off

2037
01:52:26,520 --> 01:52:31,040
Speaker 1: on Thursday, and everybody scattered. It was one of my

2038
01:52:31,120 --> 01:52:37,000
Speaker 1: prouder managerial decisions that I made. And that's how much

2039
01:52:37,040 --> 01:52:41,600
Speaker 1: I love the NCAA Tournament. I have a couple of

2040
01:52:41,640 --> 01:52:44,120
Speaker 1: fun pools that I do want my favorite, and I've

2041
01:52:44,120 --> 01:52:47,320
Speaker 1: been doing it with a group of friends probably almost

2042
01:52:47,320 --> 01:52:49,320
Speaker 1: thirty years now, where there's eight of us and we

2043
01:52:50,040 --> 01:52:52,719
Speaker 1: do a draft. You know, we all throw two hundred

2044
01:52:52,720 --> 01:52:54,280
Speaker 1: bucks in and we do a draft and we do

2045
01:52:54,360 --> 01:52:57,519
Speaker 1: eight teams and randomized pick. So then you go through

2046
01:52:57,520 --> 01:53:01,360
Speaker 1: and you know you basically you have. So I thought

2047
01:53:01,360 --> 01:53:04,080
Speaker 1: i'd have some fun and share with you quickly what

2048
01:53:04,160 --> 01:53:11,559
Speaker 1: those what those picks are it is. So I and

2049
01:53:11,760 --> 01:53:15,040
Speaker 1: the draft, I had the fourth pick, so I got Florida.

2050
01:53:15,400 --> 01:53:18,040
Speaker 1: They were the remaining number one seed, and I came

2051
01:53:18,120 --> 01:53:21,280
Speaker 1: really close to drafting Houston, but I didn't want to

2052
01:53:21,320 --> 01:53:23,080
Speaker 1: leave a one seat on board, said Florida. And then

2053
01:53:23,080 --> 01:53:24,559
Speaker 1: when it came back to me in the Snake Draft.

2054
01:53:24,560 --> 01:53:28,880
Speaker 1: I got Arkansas, then I have Wisconsin, Miami, Saint Louis,

2055
01:53:29,320 --> 01:53:34,400
Speaker 1: South Florida, Wright State, and Howard. You get for every

2056
01:53:34,479 --> 01:53:37,719
Speaker 1: win your team gets, you you get and everybody throws

2057
01:53:37,760 --> 01:53:40,680
Speaker 1: a pile of money into the pool. So you know,

2058
01:53:41,000 --> 01:53:43,200
Speaker 1: there have been years where people have gotten two final

2059
01:53:43,240 --> 01:53:45,479
Speaker 1: four teams with their team, and there are years they

2060
01:53:45,479 --> 01:53:50,720
Speaker 1: are limited after the first weekend. Sometimes it's a bit random,

2061
01:53:51,000 --> 01:53:52,800
Speaker 1: but it's one of my favorite pools that I do.

2062
01:53:53,200 --> 01:53:55,840
Speaker 1: But like, you end up with teams you don't necessarily

2063
01:53:55,880 --> 01:53:58,880
Speaker 1: want to root for, Like I'm like, really Florida, but

2064
01:53:59,080 --> 01:54:00,720
Speaker 1: and I wasn't gonna leave my on the board. I

2065
01:54:00,720 --> 01:54:02,559
Speaker 1: don't enjoy rooting for but at least now if they win,

2066
01:54:02,600 --> 01:54:06,280
Speaker 1: I might win something. But I do. I am happy,

2067
01:54:06,520 --> 01:54:08,599
Speaker 1: Like I went out of my way to draft Miami,

2068
01:54:08,640 --> 01:54:10,120
Speaker 1: and I went out of my way to draft Saint Louis,

2069
01:54:10,160 --> 01:54:16,120
Speaker 1: an A ten team for Chocolate upgw SO. But my

2070
01:54:16,320 --> 01:54:18,080
Speaker 1: in case you're wondering the Final four that I read

2071
01:54:18,120 --> 01:54:21,640
Speaker 1: to Tony Kornheiser, my participation in their bracket challenge Arizona

2072
01:54:22,280 --> 01:54:30,160
Speaker 1: Duke Houston, and I have Houston beating Florida. There in Arizona.

2073
01:54:30,280 --> 01:54:37,720
Speaker 1: I have Houston winning the whole thing over. I think

2074
01:54:37,680 --> 01:54:42,240
Speaker 1: I've Houston beating Michigan in the final game. I believe

2075
01:54:42,240 --> 01:54:45,360
Speaker 1: that's what I ended up doing. So and if you're

2076
01:54:45,440 --> 01:54:49,240
Speaker 1: wondering what my first early round upsets are, I will

2077
01:54:49,280 --> 01:54:54,320
Speaker 1: say the only twelve seeds that intrigued me Akron Akron

2078
01:54:54,440 --> 01:54:57,080
Speaker 1: is one that I put in my pool to go

2079
01:54:57,200 --> 01:55:03,640
Speaker 1: a couple of rounds. I want to believe that one

2080
01:55:03,640 --> 01:55:06,000
Speaker 1: of the eleven seeds will do a little something for me.

2081
01:55:06,080 --> 01:55:09,800
Speaker 1: That's South Florida. I have them going around or two

2082
01:55:11,080 --> 01:55:12,840
Speaker 1: on that front. But mostly I think this is going

2083
01:55:12,920 --> 01:55:16,360
Speaker 1: to be chalky, chalky, chalky chalky, lots of ones and

2084
01:55:16,400 --> 01:55:20,919
Speaker 1: twos in the Elite eight, with maybe only Saint John's

2085
01:55:21,520 --> 01:55:24,800
Speaker 1: blowing up that party and being hot. The highest seed

2086
01:55:25,640 --> 01:55:29,400
Speaker 1: remaining in uh come the elite eight, I guess is

2087
01:55:29,480 --> 01:55:33,240
Speaker 1: the johnnies at five. If anybody over a five seed

2088
01:55:33,320 --> 01:55:37,240
Speaker 1: gets to the Elite eight, my guess is that it

2089
01:55:37,320 --> 01:55:44,680
Speaker 1: would be boy I struggle. You know, two a month

2090
01:55:44,680 --> 01:55:46,840
Speaker 1: ago I might have said Saint Louis, I don't buy

2091
01:55:46,840 --> 01:55:51,280
Speaker 1: it now, And a month ago I might have said Miami,

2092
01:55:51,440 --> 01:55:53,760
Speaker 1: but I don't. I don't think We're deep enough to

2093
01:55:53,840 --> 01:55:56,800
Speaker 1: make that type of run. But I like Miami's path.

2094
01:55:57,080 --> 01:56:00,360
Speaker 1: I don't hate Miami's path. I think they cannot Purdue

2095
01:56:00,360 --> 01:56:03,000
Speaker 1: off in the second round, and obviously they pull that off,

2096
01:56:03,040 --> 01:56:08,160
Speaker 1: then hey, than anything is possible. So there you go.

2097
01:56:08,320 --> 01:56:13,320
Speaker 1: Enjoy the weekend, enjoy college basketball. It's a good way

2098
01:56:13,360 --> 01:56:16,600
Speaker 1: to distract yourself from the craziness that is the world

2099
01:56:17,440 --> 01:56:22,000
Speaker 1: and this country in politics. Thanks for listening, and I'll

2100
01:56:22,000 --> 01:56:22,480
Speaker 1: see them on that