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Speaker 1: Hey, guys, Saga and Crystal here.

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Speaker 2: Independent media just played a truly massive role in this election,

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Speaker 1: We need your help to build the future of independent

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Speaker 1: dot com.

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Speaker 3: Well.

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Speaker 4: Jim Clyburn, obviously one of the more high profile Democrats

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Speaker 4: in the House of Representatives, stopped by the podcast of

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Speaker 4: Asteed Herndon last week and got a question about AI.

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Speaker 4: Gave an answer that I want to say is surprising. Unfortunately,

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Speaker 4: it's not surprising, but it is astounding.

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Speaker 3: Nonetheless, let's take a look.

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Speaker 5: I want to ask you about AI. There's so much

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Speaker 5: that it's changing in terms of the future of work

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Speaker 5: and our economy.

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Speaker 6: Have you do you use AI?

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Speaker 3: Have you ever used an lollll No?

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Speaker 7: Somebody was telling me. I ought to, but I.

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Speaker 5: Never have no chatch e p T, no clause for you, believe.

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Speaker 8: It or not.

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Speaker 7: I didn't know what that was until about a week ago.

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Speaker 7: Which one chat GPT or whatever it is.

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Speaker 5: You didn't know until a week ago. Wow, I'm jealous.

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Speaker 5: You've got there something in a bubble.

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Speaker 7: That sounds stranger.

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Speaker 6: I don't know.

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Speaker 7: I didn't know what that was was.

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Speaker 5: Okay, have you been to a data center or anything

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Speaker 5: like that or no?

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Speaker 3: Okay?

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Speaker 5: I guess I'm wondering, like, with the speed of technological

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Speaker 5: changes right now, with how much people are anxious about

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Speaker 5: the ways AI and work might change because of it,

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Speaker 5: how do you effectively legislate as a member who is

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Speaker 5: distant from some of those technological shifts that are affecting

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Speaker 5: folks lives right now.

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Speaker 7: I have a great staff, you know. I wish I

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Speaker 7: could know everything. I don't know everything, and I don't

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Speaker 7: spend my time trying to learn everything. My time, they're

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Speaker 7: trying to surround myself with people who do no stuff.

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Speaker 3: Crystal. This is somehow worse.

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Speaker 4: I think I don't need to get into too much

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Speaker 4: tip for tat, but worse than ted Cer's not knowing

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Speaker 4: there the population of Iran, as he was like agitating

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Speaker 4: for war in Iran. Given how central data centers are

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Speaker 4: right now to the American economy, how companies like open AI, Chat, GPT,

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Speaker 4: how central they are to the American economy, to national security,

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Speaker 4: to people's daily lives.

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Speaker 3: That is insane.

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Speaker 4: And it's not just like saying my staff knows the

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Speaker 4: ins and outs of the building code policy to get

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Speaker 4: this thing up and running, like he literally said, he's

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Speaker 4: outsourcing all of his knowledge of AI to his staff basically.

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Speaker 2: And I want people to understand this is not an outliar.

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Speaker 2: You have members of Congress who approach their jobs very differently.

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Speaker 2: Some of them are really involved in being through policy

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Speaker 2: and educating themselves. They have a worldview, they're pushing that

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Speaker 2: worldview forward. Some of them are like Jim Clyburn, who

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Speaker 2: are happy to you know, he's what eighty some years old,

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Speaker 2: he's happy to outsource all of his work in thinking

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Speaker 2: to his staff. So you're really not electing this person.

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Speaker 2: You're electing whoever there's staffers are who are actually going

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Speaker 2: to be doing the research and telling this man how

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Speaker 2: he should vote. And you're also electing a whole host

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Speaker 2: of like lobbyists and special interests who will also be

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Speaker 2: coming to him and telling him how he should vote

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Speaker 2: on various issues. I just looked it up quickly. South

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Speaker 2: Carolina has been a hotspot for data center construction. There's

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Speaker 2: some roughly thirty projects in existence, more in the pipeline,

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Speaker 2: so this is a very relevant issue for his constituents.

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Speaker 2: And he says, I've never visited a data center. I

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Speaker 2: don't even know what I barely know what chat GPD is.

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Speaker 2: I've never used any of these products. So pretty stunning

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Speaker 2: revelation there. At the same time we were struck by

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Speaker 2: this was pulled by a more perfect union highlighted this

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Speaker 2: local news report about the strain that data centers here

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Speaker 2: in Virginia, which is perhaps the data center capital of

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Speaker 2: the new maybe the world, are putting on the grid

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Speaker 2: right now here in the present, while obviously they have

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Speaker 2: massive plans to expand the data center load across the country.

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Speaker 2: Let's go ahead and take a listen to a little

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Speaker 2: bit of this local news report.

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Speaker 9: Something happened on Wednesday morning that you might have noticed

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Speaker 9: but didn't bat deniye, it happened inside thousands of your

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Speaker 9: homes and businesses and experts say it's a sign the

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Speaker 9: cracks are starting to show in our power infrastructure.

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Speaker 1: Just before eight am, the electricity flickered on and off

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Speaker 1: for about ten minutes.

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Speaker 8: It was the result of data centers in Louden County, Virginia.

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Speaker 10: Experts say the cracks in our infrastructure grid are starting

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Speaker 10: to show as the data center industry consumes electricity at

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Speaker 10: a rate the world has never experienced. Wednesday morning, that

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Speaker 10: crack became visible to millions of Americans inside their own

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Speaker 10: homes in a seemingly small way.

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Speaker 11: This is what experts you're worried about.

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Speaker 12: Right.

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Speaker 11: The data centers are such a big load on the

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Speaker 11: grid that they can have true metal impact on the

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Speaker 11: surrounding grid.

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Speaker 10: Dominion Energy tells News for a transmission line servicing a

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Speaker 10: data center failed, so the data centers switched to their

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Speaker 10: own power supply, temporarily leaving the grid. In a statement

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Speaker 10: to News for, a Dominion Energy spokesperson said, quote, Dominion

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Speaker 10: Energy did not disconnect area data centers from the grid.

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Speaker 10: The data center's own control systems transferred them to back

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Speaker 10: up power for a very short period of time. Think

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Speaker 10: of it like ripples and water. The data centers switching

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Speaker 10: their power sources the rock and when that change impacts

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Speaker 10: the water or the power grid. In this analogy, the

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Speaker 10: massive shift in electricity load sent ripples through the electric

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Speaker 10: current across half the country. Ting Labs provided News for

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Speaker 10: with this graphic that shows the scale of the service disruption.

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Speaker 10: The company says the colors on this map should all

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Speaker 10: stay the same. The big changes in colors means there's

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Speaker 10: a change in electric frequency. It covers more than half

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Speaker 10: of the United States.

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Speaker 11: People working on regulations around this is their concerned that

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Speaker 11: one of these events in the future could cause the

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Speaker 11: grid become unstable and it does not come back to

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Speaker 11: normal in a few minutes or ten minutes, and we're

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Speaker 11: dealing with a real big problem.

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Speaker 2: So Emily, this seems like something our elected leaders should

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Speaker 2: maybe be looking into and care about, and you know,

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Speaker 2: thinking about themselves, not just outsourcing to their staffers. But

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Speaker 2: you know, this is something that we've been warning about

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Speaker 2: and many others besides. The strain on the grid is

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Speaker 2: really a major issue. It's not being resolved and it's

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Speaker 2: only going to get worse over time. So this is

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Speaker 2: a bit of a warning shot here.

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Speaker 4: Well, I was going to say, this is about the

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Speaker 4: concentration of power.

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Speaker 3: But in this case is like literally about the.

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Speaker 4: Concentration of power, and this is all being traced to

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Speaker 4: literally to Loudon County, Virginia Data Center ALLI. And I'm

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Speaker 4: curious how many times Jim Clyburn voted on something in

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Speaker 4: one direction or the other that set up our economy

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Speaker 4: to look like this in a way that enables the

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Speaker 4: concentration of actual power in a sense where it's so

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Speaker 4: so clustered that it can affect the entire East Coast

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Speaker 4: in one fell swoop like that. I'm sure you could

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Speaker 4: go and find votes that you know, indirectly enabled the

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Speaker 4: economy to look the way. Maybe you even find ways

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Speaker 4: that directly enabled the economy to look that the way

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Speaker 4: to look the way that it does. But astounding, he's

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Speaker 4: so comfortable outsourcing the staff. He didn't learn what chat

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Speaker 4: GPT was until a week ago. And meanwhile we're already

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Speaker 4: seeing these ripples from loud and County across the East coast.

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Speaker 3: That's how dramatic the gap and knowledge is.

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Speaker 2: Yeah, it's just extue. I mean, are you living under

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Speaker 2: a rock? Like how do you not even know what

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Speaker 2: this is? Who were you talking to?

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Speaker 6: Where are you.

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Speaker 2: Getting your news from it's just on every level. How

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Speaker 2: did you manage to avoid this particular knowledge and what

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Speaker 2: other pieces of knowledge are you somehow managing to avoid

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Speaker 2: raises a lot of questions. I got a bit of

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Speaker 2: a one two punch for you here in terms of

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Speaker 2: the progress of the tech industry pushing forward with these

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Speaker 2: data centers over the objections of the public. We can

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Speaker 2: put this up on the screen. You've got three hundred

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Speaker 2: bands now and moratoriums that the information is tracking that

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Speaker 2: say they threaten the US data center boom. This has

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Speaker 2: increasingly become a hot political issue, both at the local,

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Speaker 2: the state.

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Speaker 6: And the federal level.

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Speaker 2: It's something I'm going to ask Francesca hung about in

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Speaker 2: our interview with her, because it's something she's certainly even

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Speaker 2: campaigning on. We talked to Will Lawrence, who's a congressional

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Speaker 2: candidate in Michigan who also has been talking a lot

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Speaker 2: about data centers and making sure that there is a

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Speaker 2: slowdown at least, if not a moratorium on the building

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Speaker 2: of these data centers. At the same time, put D

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Speaker 2: four up on the screen. They're going to instead of

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Speaker 2: going through any sort of public process, what they're going

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Speaker 2: to do is something very similar to what happened in Louisiana,

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Speaker 2: where they work behind the scenes with politicians. This has

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Speaker 2: met us specifically with politicians who signed not disclosure agreements,

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Speaker 2: which is incredible. I mean, this should be illegal in

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Speaker 2: my opinion, it's technically not, but I certainly think it's

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Speaker 2: unethical for politicians doing public policy to sign non disclosure

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Speaker 2: agreements with the companies they're negotiating with. They rush through

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Speaker 2: the approvals to get this data center, massive data center

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Speaker 2: built in a very rural and very impoverished part of Louisiana,

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Speaker 2: with very little, really next to no ability for local

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Speaker 2: residents to be able to weigh in on whether they

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Speaker 2: thought this was a good or a bad thing. Now,

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Speaker 2: let me be clear, and I think, well, we're going

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Speaker 2: to see this dynamic develop as well. This was an area,

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Speaker 2: as I mentioned before, it is really rural, impoverished community,

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Speaker 2: and so the promise here was we're going to build

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Speaker 2: this data center. There's going to be tons of job creation,

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Speaker 2: it's going to revitalize this community. And in some senses

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Speaker 2: that has happened. During the construction phase. They've had huge

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Speaker 2: number of construction workers coming into the area. Some of

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Speaker 2: the local people have been able to get construction jobs

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Speaker 2: working on the data center, so it's been good for them.

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Speaker 2: But they also talked to some of the residents who

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Speaker 2: had been living in trailer parks, which are very common there,

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Speaker 2: who had their rent for their lot escalate so dramatically

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Speaker 2: that they had to move out of the town entirely.

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Speaker 2: One woman who has I think four kids, three or

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Speaker 2: four kids, was living there. She was paying two hundred

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Speaker 2: and fifty dollars a month in rent. She owned her trailer,

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Speaker 2: but you have to rent the lot that it sits on.

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Speaker 2: They jacked her rent up in a single month to

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Speaker 2: twelve hundred dollars, so more than one thousand dollars increase

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Speaker 2: that she was just supposed to swallow.

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Speaker 6: She couldn't do it.

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Speaker 2: Oftentimes, you either it's expensive to move the trailer or

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Speaker 2: they're just not really constructed in a way to be

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Speaker 2: sturdy enough to be able to move them. She had

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Speaker 2: to sit there and watch as they cut her trailer

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Speaker 2: down into pieces. Her kids and her had to live

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Speaker 2: for a time out of her car. So this sort

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Speaker 2: of disruption is taking place as well. And then the

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Speaker 2: mayor of the town said, you know, it's okay for now,

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Speaker 2: you've got a lot of people coming in after it's built.

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Speaker 2: Our longtime resident are being pushed out of the area.

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Speaker 2: Who and what is going to be left here after

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Speaker 2: this thing is ultimately built. So, but the important piece

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Speaker 2: I wanted to highlight is that number one, it's going

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Speaker 2: to be a lot of poor communities that these things

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Speaker 2: are foisted upon because they are desperate and they need

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Speaker 2: the tax revenue, and they'll grab onto anything that looks

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Speaker 2: like jobs and opportunity. And number two, that legislators will

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Speaker 2: increasingly find ways, given that there their campaign conferences are

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Speaker 2: being flooded with cash from these companies and with the

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Speaker 2: promise of future board seats or lobbying gigs, et cetera,

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Speaker 2: that they will find ways to circumvent a democratic public

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Speaker 2: process and do this behind the scenes so they can

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Speaker 2: continue to push this forward over the objections of the public.

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Speaker 4: Yeah, and meanwhile DC is being flooded with lobbying cash

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Speaker 4: from these companies, and like you said, the revolving door.

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Speaker 3: Politicians know it'll be wide open.

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Speaker 4: Maybe not for Jim Cliburn, who would probably have to

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Speaker 4: brush up on chat GPT and fully intense to remain

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Speaker 4: in that seat till he McConnell's, which we'll be talking

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Speaker 4: about in Just My Crystal.

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Speaker 2: But uh, why Reid calls him glitchy Mitchie, which I

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Speaker 2: kind of like glitch McConnell.

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Speaker 4: Man, He's and this has been going on for years

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Speaker 4: with Glitch, Senator glitch.

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Speaker 3: And so it's just like that, like you said, it's

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Speaker 3: not isolated.

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Speaker 4: The fact that he came out and said this aloud

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Speaker 4: and seemed to have zero shame about it and just said, well,

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Speaker 4: it may sound strange to you, it's like no, no, no,

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Speaker 4: it's note to literally everyone.

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Speaker 3: Yeah, my man, Like that's that's brutal.

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Speaker 6: Yeah.

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Speaker 4: And again they're all getting his staff is getting lobbied. Uh,

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Speaker 4: they're all getting lobbied enormously. So that tells you, to

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Speaker 4: your point, Crystal, about who's making the decisions. If you

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Speaker 4: are offloading a lot of these big decisions to your

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Speaker 4: staff and you're doing it so comfortably, well, they're getting

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Speaker 4: a lobbied. They're going to junkets happy hours like they

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Speaker 4: have these people in their ear and they're not the

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Speaker 4: elected representative.

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Speaker 6: That's exactly right.

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Speaker 2: We've got a couple of stories here too that speak

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Speaker 2: to this sort of more I guess existential nature of

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Speaker 2: the AI threat. This is really disturbing. Put D five

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Speaker 2: up on the screen. AI companies have been bulk buying

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Speaker 2: rare books, scanning them through high speed machines that cut

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Speaker 2: the spines off and then shred the originals they you

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Speaker 2: know this This has been tracked by number of news outlets.

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Speaker 2: This particular account is called hedge markets. In any case,

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Speaker 2: this is really disturbing because you're talking about the entire

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Speaker 2: corpus of human knowledge. You're talking about books that there

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Speaker 2: may only be one remaining in existence, or only a

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Speaker 2: handful remaining in existence, that are not have not been

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Speaker 2: you know, scanned into the Internet so you can just

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Speaker 2: access them at some later time. This is the only

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Speaker 2: proof of their existence, and they're just being chopped up

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Speaker 2: and fed into this AI beast. I think this really

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Speaker 2: struck a nerve with people Emily, because it does feel

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Speaker 2: like a direct assault on our humanity, on our creativity,

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Speaker 2: on our you know, the bank of knowledge that we've

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Speaker 2: built up over man and here you have, you know,

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Speaker 2: what is this sort of like a virtual or modern

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Speaker 2: day mass book burning that has been occurring in the

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Speaker 2: background that we didn't even know about.

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Speaker 4: A man named Charlie Becker posted a really interesting post

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Speaker 4: on x about this. He his family runs Houston's largest

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Speaker 4: used and rare bookstore, according to his post, and he's

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Speaker 4: been working to build an AI tool for bookstores like his.

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Speaker 4: He says, every ingredient of the viral story is true.

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Speaker 4: Booksellers really are getting bizarre book orders, but quote rare

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Speaker 4: here is and what you're picturing it's the Insider's Guide

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Speaker 4: to Metro Denver from nineteen ninety five and how to

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Speaker 4: Use Word Perfect nineteen ninety one manuals obscure but often

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Speaker 4: not precious. And he goes on to say, though that

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Speaker 4: this is more mundane than the shredder story. The actual

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Speaker 4: risk is worse because it's quieter. Books that don't sell

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Speaker 4: eventually get liquidated. So if they don't sell via FBA,

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Speaker 4: they end up getting liquidated. And he says, if we

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Speaker 4: really hold the last copies of some of these, we're

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Speaker 4: feeding them into a portal they may not come back from.

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Speaker 3: No AI company required.

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Speaker 4: So basically he's saying he thinks that these are bulk

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Speaker 4: orders done by an AI to mark up and resell

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Speaker 4: things on Amazon. But because when you do that, most

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Speaker 4: of the books don't sell, they end up getting shredded anyway,

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Speaker 4: and so it's like a mess no matter how you

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Speaker 4: slice it. And one that is doing exactly what you

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Speaker 4: just said is going to do in the name of

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Speaker 4: like turning around profits with this technology that allows you

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Speaker 4: to spread the cost out in mass mass mass around

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Speaker 4: the world.

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Speaker 2: And then, Emily, I wonder what do you think about this?

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Speaker 2: We talk a lot, I think understandably because people are

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Speaker 2: concerned about it, about the way AI is already and

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Speaker 2: is promising to displace a lot of human beings. But

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Speaker 2: there's also a real existential layer to this as well,

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Speaker 2: of like what is our purpose and what are we

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Speaker 2: passionate about? And you know, what gives our lives meaning?

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Speaker 2: And there is this extraordinary substack. We can put this

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Speaker 2: up on the screen from this man, Kirwin Hampshire, who

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Speaker 2: was a mathematician, and he's describing the way that he

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Speaker 2: is experiencing this crisis of identity. Because the headline here

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Speaker 2: is the Dark Knight of mathematics. What are we really doing?

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Speaker 2: Because you've had AI now be able to solve some

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Speaker 2: longstanding what are called conjectures these you know, math like

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Speaker 2: math problems.

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Speaker 6: I don't know what I'm talking about. Here, guys.

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Speaker 2: Sorry, but in any case been able to solve these

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Speaker 2: problems that have existed for years, in you know, or decades,

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Speaker 2: that mathematicians and math enthusiasts have been puzzling over for

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Speaker 2: years and years and years. And now you have AI

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Speaker 2: just basically come in and like, oh, here's the answer done,

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Speaker 2: And so he says, I'm going insane. During the last

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Speaker 2: week or so, lms have produced a number of counter

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Speaker 2: examples to significant, long standing conjectures. I won't recount these

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Speaker 2: happenings here. There are many places where you can find

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Speaker 2: the details. Mathematicians, math, and zest and curiously, people are

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Speaker 2: responding these developments in ways that I believe obscure what

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Speaker 2: is for me the true heart of the problem. I

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Speaker 2: don't speak for everyone in the math community in my response,

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Speaker 2: but I suspect I'm not alone. I'm suffering a profound

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Speaker 2: spiritual crisis due to these developments. I've been screaming internally

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Speaker 2: for days. It feels as though I'm living inside of

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Speaker 2: a nightmare.

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Speaker 6: He says.

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Speaker 2: The recent lead in declaration on AI and mathematics is

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Speaker 2: to me a well muffled screen, a sacraine may lounge

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Speaker 2: of self serving or which illums a painfully obvious absence

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Speaker 2: and effectively. He says, Okay, so if mathematical discovery, if

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Speaker 2: that's just over now, like the lms are just better

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Speaker 2: than us, Now, what's left for us? And he goes

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Speaker 2: on to say, look, even if you were to ban

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Speaker 2: all of the AI and put it back, this discovery

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Speaker 2: process back in the hands of humans, we would always

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Speaker 2: know it was a sort of lie that we had

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Speaker 2: rigged it so that we could be the ones that

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Speaker 2: discover the answer. When you have this technology out there

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Speaker 2: that would have reached you know, would have been able

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Speaker 2: to solve these problems much more rapidly. And so, you know,

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Speaker 2: I thought it was pretty profound to think about. And

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Speaker 2: he's experiencing this in math. He says, I don't know

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Speaker 2: what to do. There may be nothing you can do.

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Speaker 2: I have no prescriptions, policy recommendations, or coherent calls to action.

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Speaker 2: I just want to be honest and open about my

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Speaker 2: emotional and spiritual response. I want to feel seen. I

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Speaker 2: want folks like me to feel seen. I feel need

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Speaker 2: the architects of our new mathematical paradigm to look me

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Speaker 2: in the eye, acknowledge our shared humanity and soul before

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Speaker 2: they deliver the Kuda. Gross I need most of all

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Speaker 2: for us to understand what we are really doing. So

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Speaker 2: I don't know, what do you think about that.

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Speaker 4: I mean, we are layering computer on top of computer

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Speaker 4: on top of computer. Everything is computer, as Trump would say,

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Speaker 4: but that might be the truest thing that he's ever said.

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Speaker 4: Math is the infrastructure around us, Like, that's what builds

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Speaker 4: the infrastructure around us. So think of when you have

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Speaker 4: a further reduction of the human element. Of course, some

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Speaker 4: of this has already been offloaded to computers, and you

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Speaker 4: take the human element almost completely out of it, and

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Speaker 4: then you have computer solving problem on top of computer

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Speaker 4: solving problem on top of computer solving problem. Obviously, there

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Speaker 4: are things that can get baked into that that are

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Speaker 4: enormously problematic. And also high level math is art. It

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Speaker 4: is It is literally art. It's like culturane, it's music.

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Speaker 4: It's not just you know these like abstract goodwill hunting

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Speaker 4: chalkboard problems. They're really meaningful problems, human problems. And it's

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Speaker 4: great that we can progress. If we can, if it's

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Speaker 4: used for genuine progress, it's great that we can. We

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Speaker 4: can do it more more quickly and perhaps more efficiently

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Speaker 4: and with more sense of accuracy.

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Speaker 3: Maybe that's that's great in.

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Speaker 4: Theory, but I don't know that anybody trusts that this

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Speaker 4: is actually happening in a way that's good for humanity

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Speaker 4: and not actually unsafe uh and less human and in

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Speaker 4: a less safe way.

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Speaker 3: I don't have that trust.

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Speaker 4: And it just scares me that those processes happening all

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Speaker 4: around us so quickly. It is not like the transition

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Speaker 4: from horses to automobiles. It is not like the transition

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Speaker 4: from or to air travel, right like this is happening.

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Speaker 4: Those all happen actually pretty quickly. This is happening even faster,

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Speaker 4: and it's building on itself, and there's just no trust.

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Speaker 6: It reminds me.

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Speaker 2: It makes me think about the rapid transition that was

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Speaker 2: experiencing the industrial Midwest where all of these factories closed.

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Speaker 2: You know, towns that were built around the factories just

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Speaker 2: completely collapsed. You had men who had previously mostly men

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Speaker 2: who had previously been able to earn a good living

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Speaker 2: and support a family and buy house, etc.

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Speaker 6: Who lose all of that.

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Speaker 2: And a lot of that is we tend to focus

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Speaker 2: on what's measurable, that's the material loss, but it's also

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Speaker 2: profound psychological blow. And I think our politics today really

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Speaker 2: reflects the lack of recovery and tending to that psychological

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Speaker 2: blow of now you have no skill that's relevant to people.

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Speaker 2: Now you were unable to provide for yourself and for

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Speaker 2: your family, and you aspire for better things for your kids.

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Speaker 2: And I think we aren't really grappling with what the

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Speaker 2: psychological toll of AI will be, because in a sense,

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Speaker 2: how can we We don't really know what it's going

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Speaker 2: to be. But it did remind me. And I'll just

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Speaker 2: end with this because we have a guest standing by.

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Speaker 2: But I read these the Three Body Problem trilogy and

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Speaker 2: in the first book, and I'm not really giving away

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Speaker 2: anything here, but everybody should read them because they're fantastic books.

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Speaker 2: But anyway, there's a spate of scientists who are committing suicide,

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Speaker 2: and it starts with this sort of mystery of like,

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Speaker 2: what is going on with these scientists?

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Speaker 6: Why do they keep killing themselves?

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Speaker 2: And come to find out, Okay, I'm giving away a

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Speaker 2: little bit, but basically they've been thwarted and their experiments

439
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Speaker 2: are coming out in these crazy ways where they're sort

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Speaker 2: of becoming convinced that the science that they expect accepted

441
00:21:47,560 --> 00:21:49,520
Speaker 2: wasn't real, and that there's no way for them to

442
00:21:49,600 --> 00:21:53,119
Speaker 2: progress in science and specifically in quantum physics. And for

443
00:21:53,200 --> 00:21:55,760
Speaker 2: reasons that I won't divulge, because that does give them away.

444
00:21:56,000 --> 00:21:58,560
Speaker 2: It comes to be realized that they have in fact

445
00:21:58,600 --> 00:22:01,920
Speaker 2: been thwarted and they are are being prevented from making

446
00:22:01,960 --> 00:22:05,720
Speaker 2: any further progress in this particular discipline and others as well.

447
00:22:05,800 --> 00:22:08,760
Speaker 6: And so it's sort of reminded of that reading his.

448
00:22:10,200 --> 00:22:13,879
Speaker 2: Reading his explanation of what he describes as the spiritual crisis.

449
00:22:13,520 --> 00:22:14,359
Speaker 6: That he's going through.

450
00:22:14,400 --> 00:22:16,720
Speaker 2: So anyway, one more impact of AI that we're all

451
00:22:16,760 --> 00:22:17,680
Speaker 2: going to have to grapple with.

452
00:22:18,720 --> 00:22:19,920
Speaker 4: No. I mean, my mom grew up in one of

453
00:22:19,960 --> 00:22:21,719
Speaker 4: those towns, and a bunch of my family is still there,

454
00:22:21,720 --> 00:22:23,919
Speaker 4: and we all have seen what happens.

455
00:22:24,359 --> 00:22:25,120
Speaker 3: That was in Wisconsin.

456
00:22:25,160 --> 00:22:28,480
Speaker 4: We've all seen what happens where opioids filled the gap.

457
00:22:29,440 --> 00:22:29,880
Speaker 6: That's right.

458
00:22:31,200 --> 00:22:33,520
Speaker 4: I remember David Obie represented that district for a long

459
00:22:33,560 --> 00:22:37,080
Speaker 4: time and he said he regretted how ineffective the job

460
00:22:37,119 --> 00:22:40,240
Speaker 4: training programs that they were promised. After I forget whether

461
00:22:40,280 --> 00:22:42,640
Speaker 4: it was an after a WTO came in. He ended

462
00:22:42,720 --> 00:22:44,760
Speaker 4: up losing his seat by the way, to Sean Duffy

463
00:22:44,960 --> 00:22:49,320
Speaker 4: in twenty ten, before really the Maga Revolution it flipped.

464
00:22:49,359 --> 00:22:52,879
Speaker 4: That was a demn district for forty years. So people

465
00:22:52,920 --> 00:22:58,439
Speaker 4: get really, really, really profoundly psychologically unsettled. And then, of

466
00:22:58,440 --> 00:23:01,320
Speaker 4: course our special interest feel the economy sweeps in with

467
00:23:01,359 --> 00:23:03,959
Speaker 4: something awful to fill the gap often and that breeds

468
00:23:04,000 --> 00:23:08,280
Speaker 4: more and more resentment and division and suffering, and it

469
00:23:08,320 --> 00:23:11,119
Speaker 4: seems like we're heading straight down that road once again.

470
00:23:11,200 --> 00:23:13,760
Speaker 2: Well, let's talk about one of the architects of that

471
00:23:14,359 --> 00:23:16,000
Speaker 2: world that we live in now, Mitch McConnell.

472
00:23:18,800 --> 00:23:22,080
Speaker 4: We're joined now by Desiree Townsend, journalist who has been

473
00:23:22,119 --> 00:23:25,040
Speaker 4: doing the Lord's work tracking down what on earth is

474
00:23:25,119 --> 00:23:28,880
Speaker 4: going on with Mitch McConnell's Senator, Mitch McConnell. Desiray, thank

475
00:23:28,920 --> 00:23:29,800
Speaker 4: you so much for being here.

476
00:23:30,920 --> 00:23:33,479
Speaker 13: Of course, thank you for having me so, as you know,

477
00:23:33,840 --> 00:23:36,560
Speaker 13: the Senator, at least from yesterday, I'm going to head

478
00:23:36,560 --> 00:23:40,160
Speaker 13: over there shortly soon again is still hospitalized.

479
00:23:40,600 --> 00:23:41,879
Speaker 14: So if you look closely at.

480
00:23:41,720 --> 00:23:45,600
Speaker 13: The statement his office had made, they said that he's

481
00:23:45,640 --> 00:23:50,160
Speaker 13: been discharged, and the way they sort of framed it

482
00:23:50,200 --> 00:23:53,000
Speaker 13: is they made it sound like he's being discharged from

483
00:23:53,000 --> 00:23:56,840
Speaker 13: the hospital, but he's really not. He's just apparently being

484
00:23:57,320 --> 00:24:02,760
Speaker 13: being moved or currently in the rehabilitation facility of the hospital.

485
00:24:02,800 --> 00:24:05,320
Speaker 13: Now this is interesting because there was a viral video

486
00:24:06,240 --> 00:24:09,720
Speaker 13: from yesterday that I think may have actually triggered this

487
00:24:09,920 --> 00:24:15,320
Speaker 13: statement where a rapid CPR girl apparently walked through the hospital,

488
00:24:15,359 --> 00:24:17,720
Speaker 13: walked through the public areas of the hospital on a

489
00:24:17,760 --> 00:24:21,080
Speaker 13: different sort of business there, and she went to the

490
00:24:21,119 --> 00:24:25,280
Speaker 13: rehabilitation floor and wing on the fourth on the fourth floor,

491
00:24:25,320 --> 00:24:28,959
Speaker 13: George Washington Hospital, and she didn't see his Capitol Police

492
00:24:28,960 --> 00:24:32,879
Speaker 13: detail or him. So it's it's interesting as well because

493
00:24:32,880 --> 00:24:36,719
Speaker 13: if he's actually in rehabilitation and he's capable of being moved,

494
00:24:36,880 --> 00:24:39,640
Speaker 13: you would almost immediately move him out of that hospital.

495
00:24:39,720 --> 00:24:45,520
Speaker 13: There's Paparotski everywhere. It's also a teaching university. It's at

496
00:24:45,520 --> 00:24:49,440
Speaker 13: a university, so there are you know, twenty year olds everywhere.

497
00:24:49,480 --> 00:24:52,000
Speaker 14: Following this story, you would want to.

498
00:24:52,000 --> 00:24:55,400
Speaker 13: Move him out of that hospital and put him somewhere

499
00:24:55,640 --> 00:24:58,639
Speaker 13: like Walter Reed. Senators have access to Walter Reed. I

500
00:24:58,720 --> 00:25:02,520
Speaker 13: think John Fetterman had gone to Well to Read not

501
00:25:02,600 --> 00:25:05,640
Speaker 13: too long ago, so they have access to Congress has

502
00:25:05,680 --> 00:25:08,880
Speaker 13: access to Well to Read. They have access to better facilities.

503
00:25:09,440 --> 00:25:12,199
Speaker 13: If he's actually capable of being moved, why is he

504
00:25:12,440 --> 00:25:16,000
Speaker 13: still there? So that's leading me to believe after we're

505
00:25:16,000 --> 00:25:18,200
Speaker 13: coming in on seven weeks now, it's leading me to

506
00:25:18,240 --> 00:25:19,919
Speaker 13: believe that he cannot be moved.

507
00:25:20,440 --> 00:25:20,760
Speaker 6: Desire.

508
00:25:20,960 --> 00:25:25,200
Speaker 2: I have so many questions for you, for him for

509
00:25:25,359 --> 00:25:28,080
Speaker 2: a stab, I mean, because there's so many pieces of

510
00:25:28,119 --> 00:25:31,000
Speaker 2: this that don't make sense to me. Right, first, we

511
00:25:31,359 --> 00:25:35,080
Speaker 2: find out he's in the hospital. We hear that the

512
00:25:35,119 --> 00:25:38,120
Speaker 2: EMS was called because of a heart attack. We get

513
00:25:38,160 --> 00:25:40,720
Speaker 2: some images of him looking very bad being taken out

514
00:25:40,760 --> 00:25:43,479
Speaker 2: of his home on a stretcher. We don't hear anything

515
00:25:43,520 --> 00:25:48,400
Speaker 2: then for weeks. Then we get this message from him saying, oh,

516
00:25:48,520 --> 00:25:52,800
Speaker 2: I suffered a minor fall, no stroke, no concussion. I'm good,

517
00:25:53,359 --> 00:25:56,440
Speaker 2: but they want to keep me here indefinitely. Okay, Well,

518
00:25:56,680 --> 00:25:58,959
Speaker 2: that doesn't really pair with what you're saying about how

519
00:25:59,000 --> 00:26:01,960
Speaker 2: this is a small injury, no big deal. We've gone

520
00:26:01,960 --> 00:26:04,439
Speaker 2: a couple of proof of life photos. We have a

521
00:26:04,440 --> 00:26:07,320
Speaker 2: few Republicans who have claimed that they've spoken on the phone,

522
00:26:07,359 --> 00:26:09,040
Speaker 2: and he's sharp with the never and he's good to go,

523
00:26:09,119 --> 00:26:12,720
Speaker 2: et cetera, et cetera. We have not gotten any statement.

524
00:26:13,000 --> 00:26:15,240
Speaker 2: You can correct me if I'm wrong about Lindsey Graham.

525
00:26:15,640 --> 00:26:18,879
Speaker 2: You know, someone who's known for a very long time dying.

526
00:26:19,080 --> 00:26:22,639
Speaker 13: He put out something after the fact on I believe

527
00:26:22,640 --> 00:26:24,840
Speaker 13: it was on July twelveth, through the day after he

528
00:26:24,920 --> 00:26:27,440
Speaker 13: finally puts something out, but to your point, he didn't

529
00:26:27,440 --> 00:26:28,000
Speaker 13: address it.

530
00:26:28,040 --> 00:26:31,560
Speaker 14: There's a funeral today in Washington, Yes, is he going

531
00:26:31,640 --> 00:26:32,240
Speaker 14: to show up?

532
00:26:32,480 --> 00:26:32,640
Speaker 6: Right?

533
00:26:32,680 --> 00:26:34,679
Speaker 2: And so he puts on this statement and you pointed

534
00:26:34,680 --> 00:26:36,960
Speaker 2: this out, saying, oh, I won't be at Fancy Farm

535
00:26:37,080 --> 00:26:38,600
Speaker 2: this week, and I've been to Fancy Farm is a

536
00:26:38,600 --> 00:26:41,639
Speaker 2: big deal in Kentucky, But it seems like Lindsay Graham's

537
00:26:41,640 --> 00:26:44,280
Speaker 2: funeral is maybe a bigger deal, and we're not talking

538
00:26:44,320 --> 00:26:47,240
Speaker 2: about that. I don't know what are what are you

539
00:26:47,359 --> 00:26:49,040
Speaker 2: gleaning from all of this, and what are some of

540
00:26:49,080 --> 00:26:51,479
Speaker 2: the big questions that you have since you've been covering

541
00:26:51,480 --> 00:26:52,320
Speaker 2: this so intently.

542
00:26:54,320 --> 00:26:58,000
Speaker 13: So what I am kind of taking from these statements

543
00:26:58,440 --> 00:27:01,520
Speaker 13: is I think I think somebody, most likely his staff

544
00:27:01,640 --> 00:27:04,439
Speaker 13: or his wife, because a wife would largely be the

545
00:27:04,440 --> 00:27:06,920
Speaker 13: one in charge of an advanced directive in a living will.

546
00:27:07,440 --> 00:27:11,320
Speaker 13: I believe they are haphazardly putting these statements together and

547
00:27:11,359 --> 00:27:13,760
Speaker 13: putting them out without fully thinking them through.

548
00:27:14,200 --> 00:27:17,680
Speaker 14: To me, it smells more of trying to buy more.

549
00:27:17,560 --> 00:27:22,040
Speaker 13: Time and using every mechanism possible to do that. The

550
00:27:22,080 --> 00:27:23,760
Speaker 13: other thing you have to keep in mind. I think

551
00:27:23,760 --> 00:27:26,520
Speaker 13: this is kind of worried a lot of people in Washington.

552
00:27:26,600 --> 00:27:26,840
Speaker 6: D c.

553
00:27:27,119 --> 00:27:30,480
Speaker 13: Elaine Chow is very well connected to China. She met

554
00:27:30,480 --> 00:27:34,440
Speaker 13: with the vice president of the CCP three days after

555
00:27:34,560 --> 00:27:37,480
Speaker 13: he was had this event cardiac arrest.

556
00:27:38,320 --> 00:27:41,639
Speaker 14: And China has access to a lot.

557
00:27:41,400 --> 00:27:45,520
Speaker 13: Of AI technology and the ability to make photos, and

558
00:27:45,560 --> 00:27:48,119
Speaker 13: I think that's why maybe we haven't seen a video yet.

559
00:27:48,640 --> 00:27:52,760
Speaker 13: So I think the question is so I work in

560
00:27:52,840 --> 00:27:54,560
Speaker 13: litigation as well, and I think you kind of have

561
00:27:54,640 --> 00:27:58,280
Speaker 13: to look at what is the motive here. So originally

562
00:27:58,359 --> 00:28:01,960
Speaker 13: I thought the motive was to shut the US government

563
00:28:02,000 --> 00:28:05,800
Speaker 13: down because without Senator McConnell's vote, they almost certainly cannot

564
00:28:05,920 --> 00:28:10,639
Speaker 13: move forward appropriations. But Speaker Mike Johnson has before they

565
00:28:10,680 --> 00:28:13,159
Speaker 13: left for recess in the House, they've already started the

566
00:28:13,200 --> 00:28:17,240
Speaker 13: process of reconciliation. So at least we ensure the military

567
00:28:17,320 --> 00:28:20,080
Speaker 13: is funded. So if for some reason, this warranty we're

568
00:28:20,080 --> 00:28:23,480
Speaker 13: on goes on for long a longer amount of time,

569
00:28:23,640 --> 00:28:27,040
Speaker 13: we at least have the resources to defend the country

570
00:28:27,040 --> 00:28:30,880
Speaker 13: with the troops, so that takes that takes China out

571
00:28:30,960 --> 00:28:34,280
Speaker 13: of the equation in any foreign government that would want

572
00:28:34,320 --> 00:28:36,280
Speaker 13: to see the government shut down for sort of a

573
00:28:36,400 --> 00:28:37,840
Speaker 13: national security reason.

574
00:28:38,360 --> 00:28:39,640
Speaker 14: So that motive's gone.

575
00:28:39,760 --> 00:28:43,720
Speaker 13: So now we have this election, right, so we have

576
00:28:43,800 --> 00:28:47,560
Speaker 13: this August third date. That August third date, I think

577
00:28:47,600 --> 00:28:51,000
Speaker 13: it's it's really going to end up being nothing because

578
00:28:51,160 --> 00:28:55,120
Speaker 13: the August third refers to two different statutes of election

579
00:28:55,280 --> 00:28:59,480
Speaker 13: laws in the state of Kentucky. Those two statutes aren't

580
00:28:59,560 --> 00:29:02,520
Speaker 13: really reconciled right now, but it's something a court can

581
00:29:02,560 --> 00:29:06,960
Speaker 13: easily reconcile, and it wouldn't really in my opinion, it

582
00:29:07,000 --> 00:29:10,520
Speaker 13: shouldn't harm a special election. We could still move forward

583
00:29:10,560 --> 00:29:13,600
Speaker 13: with a special election. So that motive's gone. So the

584
00:29:13,680 --> 00:29:17,320
Speaker 13: only motive left that I can really point to is

585
00:29:17,400 --> 00:29:21,840
Speaker 13: keeping the staff paid. So the staff makes a lot

586
00:29:21,960 --> 00:29:25,959
Speaker 13: of money, and the staff I think also has maybe

587
00:29:26,360 --> 00:29:30,160
Speaker 13: potentially some of elaying Chill's friends or family.

588
00:29:30,520 --> 00:29:31,600
Speaker 14: I know there's a driver.

589
00:29:31,760 --> 00:29:33,800
Speaker 13: I don't know if the driver is a friend of

590
00:29:33,840 --> 00:29:37,760
Speaker 13: the family, but is paid by the Senator's office. So

591
00:29:37,960 --> 00:29:40,920
Speaker 13: at this point, the only motive I can point to

592
00:29:41,120 --> 00:29:42,480
Speaker 13: is to keep the staff paid.

593
00:29:42,800 --> 00:29:43,840
Speaker 6: You know, it does a right one thing.

594
00:29:43,880 --> 00:29:46,000
Speaker 2: I' s offloaded and let's just be clear, like they've

595
00:29:46,040 --> 00:29:49,640
Speaker 2: given us no information, so we can't do anything but speculate, right,

596
00:29:49,720 --> 00:29:53,360
Speaker 2: So just for people who we're going through, what is

597
00:29:53,400 --> 00:29:55,920
Speaker 2: possible because the things they put out don't make sense,

598
00:29:56,160 --> 00:29:58,520
Speaker 2: there are big questions. It would be very if he's

599
00:29:58,560 --> 00:30:00,720
Speaker 2: doing so great looking a as good as he looks

600
00:30:00,720 --> 00:30:03,760
Speaker 2: in these photos, shouldn't be hard to call into a

601
00:30:03,800 --> 00:30:06,920
Speaker 2: news organ to talk to you like anyone, Right, so

602
00:30:07,040 --> 00:30:07,600
Speaker 2: we could get.

603
00:30:07,520 --> 00:30:09,400
Speaker 14: To show up to Lindsay Graham's funeral or.

604
00:30:10,080 --> 00:30:13,720
Speaker 2: I mean something, right, get something beyond what could be

605
00:30:13,800 --> 00:30:16,200
Speaker 2: an easily generated AI photo given the tools that we

606
00:30:16,240 --> 00:30:18,520
Speaker 2: have at our disposal these days. So one theory that

607
00:30:18,560 --> 00:30:22,920
Speaker 2: I saw tasire is that let's say he's in he's live,

608
00:30:22,960 --> 00:30:25,520
Speaker 2: but he's in like a vegetative state, where it's then

609
00:30:25,680 --> 00:30:28,400
Speaker 2: on the family to decide are you going to you know,

610
00:30:28,480 --> 00:30:31,040
Speaker 2: continue this care or are you going to effectively, sorry

611
00:30:31,040 --> 00:30:31,280
Speaker 2: to be.

612
00:30:31,240 --> 00:30:32,320
Speaker 6: Crude, but pull the block.

613
00:30:32,760 --> 00:30:36,640
Speaker 2: And if that becomes public, then suddenly you have every

614
00:30:36,760 --> 00:30:38,960
Speaker 2: you know one in the world with an opinion for

615
00:30:39,040 --> 00:30:41,800
Speaker 2: the family about what they should do in the circumstance

616
00:30:42,040 --> 00:30:45,560
Speaker 2: given the political ramifications, and maybe they just don't want

617
00:30:45,760 --> 00:30:47,880
Speaker 2: all of that public pressure on them at what is

618
00:30:47,920 --> 00:30:51,280
Speaker 2: a very sensitive moment in their lives. What do you

619
00:30:51,360 --> 00:30:52,880
Speaker 2: make of that potential theory.

620
00:30:53,840 --> 00:30:56,200
Speaker 13: I flirted with that idea, and I do think that

621
00:30:56,360 --> 00:31:00,840
Speaker 13: is a possibility, but it kind of would child didn't

622
00:31:00,880 --> 00:31:05,000
Speaker 13: immediately return from China kind of throws that argument completely

623
00:31:05,120 --> 00:31:09,880
Speaker 13: out the door because she was in China prior to

624
00:31:10,000 --> 00:31:11,640
Speaker 13: his hospitalization.

625
00:31:12,160 --> 00:31:13,320
Speaker 14: She then met with.

626
00:31:13,640 --> 00:31:16,200
Speaker 13: The Vice President of China three days later, but she

627
00:31:16,320 --> 00:31:19,240
Speaker 13: didn't actually return to the United States until closer to

628
00:31:19,360 --> 00:31:22,440
Speaker 13: July sixth, and then issue these statements that it didn't

629
00:31:22,480 --> 00:31:25,680
Speaker 13: warrant her return to the to the United States. So

630
00:31:25,840 --> 00:31:28,200
Speaker 13: if she is in fact in love with her husband,

631
00:31:28,760 --> 00:31:32,959
Speaker 13: cares about his life well, and advanced directive, you would

632
00:31:33,320 --> 00:31:36,920
Speaker 13: you would think that, you know, I don't know, you

633
00:31:36,960 --> 00:31:41,400
Speaker 13: would return sooner. So that to me, it just doesn't

634
00:31:41,440 --> 00:31:44,360
Speaker 13: point to somebody who's struggling with with what do we

635
00:31:44,440 --> 00:31:45,440
Speaker 13: do end of life?

636
00:31:46,200 --> 00:31:47,280
Speaker 14: Do we pull the plug?

637
00:31:47,400 --> 00:31:50,360
Speaker 13: And also I don't know how close he was with

638
00:31:50,440 --> 00:31:53,920
Speaker 13: his children, because no one's seen them at the hospital,

639
00:31:53,960 --> 00:31:56,600
Speaker 13: and there are a lot of us there. I'm not

640
00:31:56,680 --> 00:31:59,520
Speaker 13: the only one there. There's there's other paparazzis that are

641
00:31:59,560 --> 00:32:03,600
Speaker 13: staking out the hospital. No one's seen as kids, So

642
00:32:03,720 --> 00:32:05,840
Speaker 13: I don't know if that's really the struggle.

643
00:32:05,880 --> 00:32:09,240
Speaker 4: Sure, go ahead, Well no, Actually that's so interesting because

644
00:32:09,280 --> 00:32:11,120
Speaker 4: I was going to ask next. I don't know that

645
00:32:11,160 --> 00:32:14,360
Speaker 4: anybody has spent more time sticking out the house or

646
00:32:14,400 --> 00:32:15,760
Speaker 4: the hospital than you have.

647
00:32:15,960 --> 00:32:17,600
Speaker 3: And this is such a bizarre story.

648
00:32:18,240 --> 00:32:21,800
Speaker 4: Just that anecdote about people not seeing the kids is

649
00:32:21,840 --> 00:32:24,000
Speaker 4: a really interesting aspect of this. And I feel like

650
00:32:24,040 --> 00:32:27,360
Speaker 4: we're doing a true crime documentary here and it's endlessly fascinating.

651
00:32:27,400 --> 00:32:33,600
Speaker 4: But what have you picked up on just atmospherically, what

652
00:32:33,720 --> 00:32:38,600
Speaker 4: oddities have you observed from your position watching both the

653
00:32:38,640 --> 00:32:40,400
Speaker 4: house and the hospital.

654
00:32:40,680 --> 00:32:41,520
Speaker 3: What's it been like?

655
00:32:43,120 --> 00:32:47,880
Speaker 13: It's all very very odd. It's so tight lipped. There's

656
00:32:48,080 --> 00:32:53,760
Speaker 13: really no movement or no appearances from family, and no

657
00:32:53,800 --> 00:32:57,640
Speaker 13: one can really seem to find Elaine Chaw of mainstream media.

658
00:32:57,760 --> 00:33:02,720
Speaker 13: Even that photo where they some paparazzi found her outside

659
00:33:02,760 --> 00:33:06,680
Speaker 13: of George Washington Hospital, it all looked stage to me,

660
00:33:06,800 --> 00:33:11,200
Speaker 13: because what paparazzi wouldn't take a video and.

661
00:33:11,200 --> 00:33:12,920
Speaker 14: Ask her questions?

662
00:33:13,240 --> 00:33:15,800
Speaker 13: And so what was really interesting about all of that

663
00:33:16,080 --> 00:33:19,560
Speaker 13: is I found another person at George Washington Hospital. He

664
00:33:19,600 --> 00:33:22,040
Speaker 13: actually went and talked to that paparazzi. He's like, why

665
00:33:22,080 --> 00:33:24,360
Speaker 13: didn't you take a video? Like what's wrong with you?

666
00:33:24,400 --> 00:33:29,400
Speaker 13: Why weren't you asking questions? And I guess the paparazzi

667
00:33:29,560 --> 00:33:31,560
Speaker 13: was like, oh, I made a mistake. I hit the

668
00:33:31,560 --> 00:33:35,680
Speaker 13: wrong button. That's you don't make mistakes like that. I'm sorry.

669
00:33:36,000 --> 00:33:36,760
Speaker 14: I'm new to.

670
00:33:36,760 --> 00:33:40,160
Speaker 13: This and I've only been doing journalism and filming and

671
00:33:40,200 --> 00:33:42,600
Speaker 13: doing all of this for a year. You don't screw

672
00:33:42,720 --> 00:33:44,880
Speaker 13: up like that, and you have enough time to fix it,

673
00:33:44,920 --> 00:33:48,080
Speaker 13: which leads me to believe that paparazzi was not there

674
00:33:48,320 --> 00:33:50,840
Speaker 13: to take video. He was there to take a photo.

675
00:33:50,920 --> 00:33:53,120
Speaker 13: Could have been tipped off by Elaine Chow.

676
00:33:53,520 --> 00:33:55,720
Speaker 14: But she's missing. We can't find the kids.

677
00:33:56,280 --> 00:33:58,960
Speaker 13: It's just very, very odd because usually you would have

678
00:33:59,000 --> 00:34:01,719
Speaker 13: a family member to a statement saying, please give us

679
00:34:01,720 --> 00:34:04,400
Speaker 13: our privacy, we want to figure out what we're doing

680
00:34:04,400 --> 00:34:06,720
Speaker 13: with my father or my husband.

681
00:34:07,040 --> 00:34:09,120
Speaker 14: Nothing. There's been nothing from the family.

682
00:34:09,200 --> 00:34:12,399
Speaker 13: In fact, I believe it was porter McConnell deleted her

683
00:34:12,520 --> 00:34:15,680
Speaker 13: ex account, So this is all very odd.

684
00:34:16,440 --> 00:34:19,640
Speaker 2: Well, Desire, thank you so much for doing this work.

685
00:34:19,719 --> 00:34:22,919
Speaker 2: I feel like I'm going insane that there's not more

686
00:34:23,280 --> 00:34:26,960
Speaker 2: coverage of what is an incredibly consequential story, both in

687
00:34:27,040 --> 00:34:28,919
Speaker 2: terms of is there a cover up, what it means

688
00:34:28,920 --> 00:34:31,840
Speaker 2: for our politics, and moving forward all of those questions,

689
00:34:31,880 --> 00:34:34,600
Speaker 2: and there seems to be very little curiosity in the

690
00:34:34,640 --> 00:34:36,960
Speaker 2: mainstream press. And that is one other point I want

691
00:34:37,000 --> 00:34:39,280
Speaker 2: to make here is people may be under the impression

692
00:34:39,320 --> 00:34:42,240
Speaker 2: this is all unfolding in Kentucky. No, this is unfolding

693
00:34:42,239 --> 00:34:45,680
Speaker 2: here in Washington, DC. It is undoubtedly the case. Just

694
00:34:45,680 --> 00:34:48,000
Speaker 2: as there were many people who know about Joe Biden's decline,

695
00:34:48,000 --> 00:34:50,239
Speaker 2: there are many people, many of them probably in the

696
00:34:50,320 --> 00:34:52,600
Speaker 2: Washington press corps, who know exactly what is going on

697
00:34:52,640 --> 00:34:55,200
Speaker 2: with Mitch McConnell and are keeping their lips sealed. So

698
00:34:55,360 --> 00:34:58,000
Speaker 2: I think it's important for people to understand that as well.

699
00:34:58,640 --> 00:35:00,560
Speaker 2: Tell people where they can follow you and where they

700
00:35:00,560 --> 00:35:02,040
Speaker 2: can find your work, and I hope you'll come back

701
00:35:02,040 --> 00:35:04,160
Speaker 2: and keep us updated as well.

702
00:35:04,400 --> 00:35:06,640
Speaker 13: So real quickly to address that, I want to let

703
00:35:06,640 --> 00:35:08,680
Speaker 13: all of you know. So I put out videos back

704
00:35:08,680 --> 00:35:11,640
Speaker 13: in February of the state of Senator Mitch McConnell, and

705
00:35:11,760 --> 00:35:15,000
Speaker 13: I ask them questions as I'm walking past the press

706
00:35:15,040 --> 00:35:18,040
Speaker 13: gaggle they knew the condition he was in, they have

707
00:35:18,280 --> 00:35:20,680
Speaker 13: never covered it, and to this day, I still find

708
00:35:20,719 --> 00:35:24,000
Speaker 13: it incredibly odd that they're ignoring this story.

709
00:35:24,560 --> 00:35:25,280
Speaker 14: So you can.

710
00:35:25,160 --> 00:35:29,640
Speaker 13: Find me Desra Townsend. I'm on all the platforms except

711
00:35:29,640 --> 00:35:31,560
Speaker 13: for Facebook. I'm sorry, it's a lot of work to

712
00:35:31,600 --> 00:35:33,880
Speaker 13: have all these things up. So you can find me

713
00:35:33,920 --> 00:35:37,040
Speaker 13: on TikTok, Instagram, and X.

714
00:35:37,840 --> 00:35:39,239
Speaker 2: Thank you so much for your work and thank you

715
00:35:39,239 --> 00:35:40,680
Speaker 2: for your time today. Dosre good to meet you.

716
00:35:41,520 --> 00:35:43,439
Speaker 14: Thank you both. Have a great day, you two.

717
00:35:46,560 --> 00:35:49,960
Speaker 2: There is a very consequential governor's race unfolding in Emily's

718
00:35:49,960 --> 00:35:52,640
Speaker 2: home state of Wisconsin, and we are joined now by

719
00:35:52,640 --> 00:35:55,720
Speaker 2: one of the leading candidates, Francesca Hang, is a state

720
00:35:55,760 --> 00:35:56,560
Speaker 2: representative there.

721
00:35:56,640 --> 00:35:59,239
Speaker 6: She is also a socialist.

722
00:35:58,760 --> 00:36:03,160
Speaker 2: And is running to be the first socialist governor of

723
00:36:03,200 --> 00:36:04,520
Speaker 2: any state in the country.

724
00:36:04,600 --> 00:36:05,880
Speaker 6: Welcome, It's great to have you.

725
00:36:06,040 --> 00:36:06,879
Speaker 3: Happy to be here.

726
00:36:07,040 --> 00:36:09,640
Speaker 2: Yeah, of course, polls have you up, so looks like

727
00:36:09,680 --> 00:36:12,040
Speaker 2: things are going pretty well for you. What do you

728
00:36:12,120 --> 00:36:13,960
Speaker 2: see on the campaign trail? What do you think are

729
00:36:13,960 --> 00:36:15,920
Speaker 2: the core issues that voters are considering right now in

730
00:36:15,960 --> 00:36:16,920
Speaker 2: the Democratic primary?

731
00:36:17,719 --> 00:36:21,640
Speaker 15: Grappling with rising costs, public schools that have been defunded

732
00:36:21,719 --> 00:36:25,560
Speaker 15: for over sixteen years, the construction of ad data centers

733
00:36:25,600 --> 00:36:27,080
Speaker 15: and affordable healthcare.

734
00:36:27,480 --> 00:36:29,120
Speaker 4: Tell us a little bit more when you're on the

735
00:36:29,160 --> 00:36:33,360
Speaker 4: campaign trail, how people Wisconsin has a very interesting particular

736
00:36:33,400 --> 00:36:37,319
Speaker 4: history actually in America with socialism, So talk to us

737
00:36:37,360 --> 00:36:39,480
Speaker 4: a bit about how that label is playing on a

738
00:36:39,520 --> 00:36:42,120
Speaker 4: campaign tral. Obviously you're in a primary right now. Do

739
00:36:42,200 --> 00:36:45,239
Speaker 4: you get questions about electability? What have those discussions looked like?

740
00:36:46,640 --> 00:36:50,759
Speaker 15: Almost every day I have to remind folks that the

741
00:36:50,800 --> 00:36:53,200
Speaker 15: person who is most electable is the person who wins

742
00:36:53,239 --> 00:36:58,160
Speaker 15: the most votes. But Wisconsin has a strong progressive history. Milwaukee,

743
00:36:58,160 --> 00:37:01,880
Speaker 15: Wisconsin is where sewer socialism was born. This is the

744
00:37:01,960 --> 00:37:08,279
Speaker 15: state of kindergarten, environmentalism, social security and unemployment insurance. We've

745
00:37:08,320 --> 00:37:12,200
Speaker 15: had trailblazers like Fighting Bob la Follett, Bel Phillips, and

746
00:37:12,280 --> 00:37:15,319
Speaker 15: gay Lord Nelson. I get asked every day, you know

747
00:37:15,440 --> 00:37:19,040
Speaker 15: why run as a Democratic socialist, And I remind folks

748
00:37:19,120 --> 00:37:22,040
Speaker 15: that I'm a Democratic socialist running on the Democratic ticket.

749
00:37:22,360 --> 00:37:25,800
Speaker 15: But being a Democratic socialist means that I am committed

750
00:37:25,880 --> 00:37:29,480
Speaker 15: to the work and workers first, in ensuring that we

751
00:37:29,560 --> 00:37:32,880
Speaker 15: are fixing a rigged system that is designed to uphold

752
00:37:33,080 --> 00:37:36,239
Speaker 15: the billionaire class and the elite. When we focus on

753
00:37:36,320 --> 00:37:39,640
Speaker 15: making sure that working class people across the state have

754
00:37:39,880 --> 00:37:42,200
Speaker 15: what they need to live a life of dignity, the

755
00:37:42,360 --> 00:37:43,560
Speaker 15: entire state will thrive.

756
00:37:44,480 --> 00:37:46,399
Speaker 2: Representative of hang As, I'm sure you're well aware. There's

757
00:37:46,400 --> 00:37:49,440
Speaker 2: been a bit of a centrist establishment freacount happening in

758
00:37:49,440 --> 00:37:52,800
Speaker 2: the Democratic Party about the rise of candidates such as yourself,

759
00:37:52,920 --> 00:37:56,160
Speaker 2: or Zara Mundani or dary Liza Vila Chevalier or Claire

760
00:37:56,200 --> 00:38:00,239
Speaker 2: Valdez in New York City. One entrance in this freak

761
00:38:00,239 --> 00:38:04,440
Speaker 2: out husband Van Jones, of course, prominent commentator on CNN.

762
00:38:04,600 --> 00:38:06,799
Speaker 2: I want to get your reaction to a video that

763
00:38:06,880 --> 00:38:10,200
Speaker 2: he put out recently about how he sees this kind

764
00:38:10,200 --> 00:38:16,240
Speaker 2: of intra party fight.

765
00:38:17,239 --> 00:38:19,120
Speaker 8: All right, A quick message to my friends on the

766
00:38:19,120 --> 00:38:22,520
Speaker 8: far left. Quit pooping in the kool aid bowl and

767
00:38:22,560 --> 00:38:25,080
Speaker 8: telling us that the thurds are ice cubes. They're not

768
00:38:25,160 --> 00:38:25,720
Speaker 8: ice cubes.

769
00:38:25,760 --> 00:38:28,280
Speaker 3: And I want to talk about Van Jones.

770
00:38:28,719 --> 00:38:31,759
Speaker 8: Everything that's good in our party I believe in have

771
00:38:31,840 --> 00:38:34,000
Speaker 8: been leaved in for a long time. Do I want

772
00:38:34,080 --> 00:38:36,640
Speaker 8: universal health care, Medicare for all, whatever you want to

773
00:38:36,640 --> 00:38:39,120
Speaker 8: call it. Absolutely, if you are sick, you should be

774
00:38:39,160 --> 00:38:41,120
Speaker 8: able to go see a doctor, that's a good idea.

775
00:38:41,239 --> 00:38:44,440
Speaker 8: I want free education for everybody as long as they

776
00:38:44,480 --> 00:38:46,960
Speaker 8: want to keep learning. I think I say, good idea,

777
00:38:47,160 --> 00:38:50,359
Speaker 8: the Green New Deal. I'm the author of the Green

778
00:38:50,400 --> 00:38:53,279
Speaker 8: New Deal. The Green New Deal is my phrase from

779
00:38:53,280 --> 00:38:56,040
Speaker 8: my first book in two thousand and eight. There's nobody

780
00:38:56,040 --> 00:38:59,759
Speaker 8: more committed to criminal justice reform them than me, Equal

781
00:38:59,800 --> 00:39:04,759
Speaker 8: out solutions, the whole deal. These are our ideals as progressives.

782
00:39:05,080 --> 00:39:07,600
Speaker 8: We should fight for them. We need them now more

783
00:39:07,640 --> 00:39:10,600
Speaker 8: than ever. But what does that have to do with

784
00:39:10,719 --> 00:39:13,880
Speaker 8: supporting hamas? What does it have to do with putting

785
00:39:13,960 --> 00:39:18,239
Speaker 8: up candidates who say we should have no police, no prisons,

786
00:39:18,400 --> 00:39:22,360
Speaker 8: we can't deport anybody even if they commit rape or murder.

787
00:39:22,640 --> 00:39:27,839
Speaker 8: Israel shouldn't exist. These aren't terrible ideas, these are awful ideas.

788
00:39:28,000 --> 00:39:31,040
Speaker 8: Where did these ideas even come from? If we want

789
00:39:31,040 --> 00:39:33,759
Speaker 8: people to join this party, When people come to the party,

790
00:39:33,800 --> 00:39:35,640
Speaker 8: you want to give them a wonderful punch bowl of

791
00:39:35,680 --> 00:39:37,040
Speaker 8: wonderful ideas like this.

792
00:39:38,200 --> 00:39:41,280
Speaker 3: Who is putting the poop in the punch bowl?

793
00:39:41,880 --> 00:39:44,280
Speaker 8: Why these ideas in are punch bowl?

794
00:39:44,920 --> 00:39:48,279
Speaker 2: Interesting stylistic choices being made there? But respond to his

795
00:39:48,680 --> 00:39:52,279
Speaker 2: concerns here and his critiques He says that bad, regressive

796
00:39:52,400 --> 00:39:55,759
Speaker 2: ideas are being snuck into the party by candidates such

797
00:39:55,800 --> 00:39:56,360
Speaker 2: as yourself.

798
00:39:56,440 --> 00:39:59,520
Speaker 12: What is your response to that we need to build

799
00:39:59,560 --> 00:40:02,719
Speaker 12: the broad, big time coalition that we can to fight

800
00:40:02,800 --> 00:40:06,600
Speaker 12: fascism and rising authoritarium and the Trump regime together.

801
00:40:07,200 --> 00:40:10,279
Speaker 15: I think that if we alienate voters, especially those who

802
00:40:10,320 --> 00:40:14,080
Speaker 15: are committed to human rights with what's happening in Gaza

803
00:40:14,239 --> 00:40:17,600
Speaker 15: is a genocide, that you know, fighting to ensure that

804
00:40:17,760 --> 00:40:21,840
Speaker 15: we actually fix the systemic issues around criminal legal reform

805
00:40:22,120 --> 00:40:24,960
Speaker 15: and make sure that we're investing in systems of care first.

806
00:40:25,320 --> 00:40:28,040
Speaker 15: I think it's disappointing that we would continue to be

807
00:40:28,200 --> 00:40:34,359
Speaker 15: divisive when our campaign is focused on building this really wonderful,

808
00:40:34,719 --> 00:40:39,880
Speaker 15: multi racial, multi geographic, multi faith coalition with voters in

809
00:40:39,960 --> 00:40:44,359
Speaker 15: every corner of the state, including Republicans and independents. And

810
00:40:44,760 --> 00:40:47,319
Speaker 15: I think that if we are to be stronger as

811
00:40:47,360 --> 00:40:50,200
Speaker 15: a democratic party, if we are going to build durable

812
00:40:50,280 --> 00:40:54,640
Speaker 15: power as a democratic party, we cannot alienate those on

813
00:40:54,680 --> 00:40:57,800
Speaker 15: the left. And I think that, you know, I welcome

814
00:40:57,920 --> 00:41:01,759
Speaker 15: some of Van Jones's commitments to universal policies. I think

815
00:41:01,760 --> 00:41:04,279
Speaker 15: they're the only ones that will make sure that we

816
00:41:04,360 --> 00:41:07,600
Speaker 15: don't come back to these moments that we ensure human

817
00:41:07,680 --> 00:41:14,120
Speaker 15: rights for folks. But to make this about the human

818
00:41:14,200 --> 00:41:18,799
Speaker 15: rights violations of Israel and making this about the left.

819
00:41:18,920 --> 00:41:22,440
Speaker 15: Focusing on these slogans, I think is a disservice to

820
00:41:22,480 --> 00:41:25,080
Speaker 15: building this coalition that we need to build together.

821
00:41:26,080 --> 00:41:29,319
Speaker 4: Senator Bernie Sanders famously once called open borders a Koch

822
00:41:29,400 --> 00:41:32,480
Speaker 4: Brothers proposal. And I'm curious if you think the Biden

823
00:41:32,520 --> 00:41:36,680
Speaker 4: immigration surge, which according to New York Times was eight

824
00:41:36,719 --> 00:41:39,320
Speaker 4: million not a citizens coming in over the course about

825
00:41:39,600 --> 00:41:42,160
Speaker 4: three years, do you think that put downward pressure on

826
00:41:42,200 --> 00:41:46,239
Speaker 4: Wisconsin workers wages? And is there any room then for

827
00:41:46,600 --> 00:41:50,200
Speaker 4: deportation of people who are non criminals, whether it's through

828
00:41:50,239 --> 00:41:53,319
Speaker 4: ICE or another law enforcement agency, in the name of

829
00:41:53,880 --> 00:41:56,480
Speaker 4: controlling wages and putting American workers first.

830
00:41:57,239 --> 00:42:03,200
Speaker 15: Right now, our dairy farms are agricultural center, meet packing, education,

831
00:42:03,600 --> 00:42:07,480
Speaker 15: every single sector across the state relies on the leadership

832
00:42:07,520 --> 00:42:12,640
Speaker 15: and the contributions of immigrants. And I think that right now,

833
00:42:12,960 --> 00:42:16,080
Speaker 15: when it comes to suppression of wages or those conversations

834
00:42:16,080 --> 00:42:21,640
Speaker 15: around potential deportation or impact in the workforce, we are

835
00:42:21,920 --> 00:42:24,560
Speaker 15: struggling to make sure that all of our communities feel

836
00:42:24,600 --> 00:42:27,160
Speaker 15: safe to be able to go to work, and you know,

837
00:42:27,440 --> 00:42:31,560
Speaker 15: policies like driver's license for all and in state tuition

838
00:42:31,840 --> 00:42:37,440
Speaker 15: for doctor recipients. These are incredibly popular positions that you know,

839
00:42:37,520 --> 00:42:40,520
Speaker 15: we have the Farm Bureau supporting driver's licenses for all

840
00:42:40,520 --> 00:42:41,560
Speaker 15: here in Wisconsin.

841
00:42:42,040 --> 00:42:43,799
Speaker 14: So I think that this.

842
00:42:45,440 --> 00:42:49,680
Speaker 15: Manufactured crisis at times and fear mongering, especially in the

843
00:42:49,719 --> 00:42:55,480
Speaker 15: aid of growing late from the era of AI. It's

844
00:42:55,480 --> 00:42:57,680
Speaker 15: important to recognize that we have to be fighting for

845
00:42:57,719 --> 00:42:58,560
Speaker 15: our neighbors.

846
00:42:59,440 --> 00:43:01,400
Speaker 2: You mentioned that you get a lot of questions about

847
00:43:01,440 --> 00:43:04,200
Speaker 2: why identify as a socialist and are you electable in

848
00:43:04,239 --> 00:43:07,680
Speaker 2: a general election. There was a Marquette poll recently was

849
00:43:07,719 --> 00:43:11,600
Speaker 2: featured on the Wisconsin Public Radio site that had all

850
00:43:11,600 --> 00:43:14,960
Speaker 2: of the candidates and everybody was within you know, was

851
00:43:15,040 --> 00:43:19,120
Speaker 2: within target distance of the Republican candidate. But they did

852
00:43:19,160 --> 00:43:23,200
Speaker 2: have Mendela Barnes outperforming and winning, and you were somewhat

853
00:43:23,200 --> 00:43:27,600
Speaker 2: behind the Republican candidate, Tiffany. So I'm curious, you know,

854
00:43:27,680 --> 00:43:30,640
Speaker 2: how do you view that poll, What do you make

855
00:43:30,800 --> 00:43:34,120
Speaker 2: of how you will sell you know, a socialist candidate

856
00:43:34,160 --> 00:43:38,120
Speaker 2: and a socialist ideology to a broader Wisconsin electorate.

857
00:43:38,680 --> 00:43:41,320
Speaker 15: It's important to remember that we still have about forty

858
00:43:41,440 --> 00:43:44,680
Speaker 15: forty five percent of voters in that last Marquette pole

859
00:43:44,960 --> 00:43:48,799
Speaker 15: who were undecided. That will have another market poll coming

860
00:43:48,840 --> 00:43:52,280
Speaker 15: out on Wednesday, because we had some shifts in the

861
00:43:52,480 --> 00:43:55,920
Speaker 15: Democratic primary candidates with the county executive coming back in

862
00:43:55,960 --> 00:43:59,520
Speaker 15: with the governor's endorsement. I think one of the advantages

863
00:43:59,560 --> 00:44:02,600
Speaker 15: that the form lieutenant governor has is that there is

864
00:44:02,600 --> 00:44:05,080
Speaker 15: a broader name recognition, and so in a head to

865
00:44:05,160 --> 00:44:07,760
Speaker 15: head oftentimes you'll find the person who has the broadest

866
00:44:07,840 --> 00:44:12,520
Speaker 15: name recognition in a better position. But I think that

867
00:44:12,719 --> 00:44:16,680
Speaker 15: our movement is growing. We have new donors every day.

868
00:44:16,920 --> 00:44:20,080
Speaker 15: We're already beating Tom Tiffany, who is a trader, an

869
00:44:20,120 --> 00:44:24,799
Speaker 15: election denier, somebody who supports a national abortion ban and

870
00:44:24,880 --> 00:44:28,080
Speaker 15: has voted to gut healthcare and food share away from

871
00:44:28,120 --> 00:44:31,640
Speaker 15: our kids. The more people see that who he is

872
00:44:31,680 --> 00:44:33,640
Speaker 15: and what his voting record is, because right now they're

873
00:44:33,640 --> 00:44:35,640
Speaker 15: out here trying to make him out to be this

874
00:44:36,000 --> 00:44:39,239
Speaker 15: you know, grew up on the dairy farm and is

875
00:44:39,360 --> 00:44:42,800
Speaker 15: this nice, average guy. But who he is is truly

876
00:44:42,840 --> 00:44:45,959
Speaker 15: somebody who's going to put Trump ahead of every single wisconsinight.

877
00:44:46,280 --> 00:44:49,560
Speaker 15: So we're excited to have more individual donors than tiffany

878
00:44:49,960 --> 00:44:54,359
Speaker 15: more individual donations over twenty two thousand donations in fact,

879
00:44:54,360 --> 00:44:57,560
Speaker 15: from every county here in this state. I think having

880
00:44:57,640 --> 00:45:01,080
Speaker 15: led in every market poll and growing our lead shows

881
00:45:01,120 --> 00:45:04,560
Speaker 15: that the coalition is growing, that we are an organizing

882
00:45:04,600 --> 00:45:08,359
Speaker 15: first campaign. That over the weekend our volunteers hit over

883
00:45:08,440 --> 00:45:12,120
Speaker 15: thirty five thousand doors across the state, and we are

884
00:45:12,200 --> 00:45:16,120
Speaker 15: growing momentum in rural, more purple or red areas.

885
00:45:16,239 --> 00:45:18,600
Speaker 3: And it's a multi generational coalition.

886
00:45:18,880 --> 00:45:21,680
Speaker 15: And I think this sort of excitement and joy belongs

887
00:45:21,719 --> 00:45:24,160
Speaker 15: in a new type of politics and is part of

888
00:45:24,280 --> 00:45:27,160
Speaker 15: resistance building as well. We get to have fun when

889
00:45:27,239 --> 00:45:30,560
Speaker 15: it comes to campaigns and be serious about the issue too.

890
00:45:31,440 --> 00:45:34,040
Speaker 2: Abdola Saieto over in Michigan, We've covered his race a lot.

891
00:45:34,040 --> 00:45:36,960
Speaker 2: I'm sure you're following it closely as well. He has

892
00:45:37,080 --> 00:45:40,400
Speaker 2: a similar worldview, but he does not describe himself as

893
00:45:40,440 --> 00:45:42,120
Speaker 2: a socialist. Who was asking in a debate last night

894
00:45:42,160 --> 00:45:45,279
Speaker 2: he says, no, I'm a capitalist. And I'm wondering if

895
00:45:45,320 --> 00:45:50,000
Speaker 2: you think that the socialist label is still scary for voters,

896
00:45:50,280 --> 00:45:53,360
Speaker 2: and how you put them at ease, how you explain

897
00:45:53,600 --> 00:45:56,719
Speaker 2: your view of what socialism or democratic socialism is.

898
00:45:58,600 --> 00:46:01,319
Speaker 15: I am a former small business owner. I owned a

899
00:46:01,320 --> 00:46:05,160
Speaker 15: small restaurant in downtown Madison close to my legislative office

900
00:46:05,239 --> 00:46:10,800
Speaker 15: for almost seven years. I support union rights and making

901
00:46:10,840 --> 00:46:14,000
Speaker 15: sure that we have living wages, health care for all,

902
00:46:14,200 --> 00:46:19,000
Speaker 15: universal childcare, fully funded public schools, and followy funding our

903
00:46:19,040 --> 00:46:23,359
Speaker 15: local governments. Democratic socialism to me means that we are

904
00:46:23,560 --> 00:46:29,280
Speaker 15: a government that puts working class people first, ahead of corporations.

905
00:46:28,440 --> 00:46:31,600
Speaker 14: And the elite and the ultra wealthy.

906
00:46:31,680 --> 00:46:35,440
Speaker 15: And so when I explain democratic socialism in a way

907
00:46:35,480 --> 00:46:39,560
Speaker 15: through the Green Bay packers filling potholes, making sure that

908
00:46:39,600 --> 00:46:43,200
Speaker 15: we're funding public schools, you know, the pride and the

909
00:46:43,400 --> 00:46:47,680
Speaker 15: collective joy that comes with our only publicly owned NFL team,

910
00:46:48,360 --> 00:46:50,640
Speaker 15: it helps folks to realize this is so much more

911
00:46:51,000 --> 00:46:54,960
Speaker 15: about the economic populist issues that are growing in popularity.

912
00:46:55,320 --> 00:46:58,920
Speaker 15: I think democratic socialism is sensible. What is radical is

913
00:46:58,960 --> 00:47:00,720
Speaker 15: the fact that we still have a seven to twenty

914
00:47:00,840 --> 00:47:03,680
Speaker 15: five minimum wage in our state two thirty three hour

915
00:47:03,760 --> 00:47:07,440
Speaker 15: for a tipped minimum wage. So these sort of working

916
00:47:07,520 --> 00:47:12,319
Speaker 15: class people first policies are are what is popular with

917
00:47:12,400 --> 00:47:15,960
Speaker 15: folks across our state, and democratic socialism holds me accountable

918
00:47:16,040 --> 00:47:20,319
Speaker 15: to my principles of human rights democracy and fairness. It's

919
00:47:20,360 --> 00:47:23,160
Speaker 15: why we need to tax the rich and so. And

920
00:47:23,600 --> 00:47:30,920
Speaker 15: I think with growing momentum organizations like DSA, the political

921
00:47:30,960 --> 00:47:33,800
Speaker 15: home they're providing, even though they're not a party, the

922
00:47:33,920 --> 00:47:37,279
Speaker 15: organizing skills and tools, you know, we reflect a lot

923
00:47:37,280 --> 00:47:40,360
Speaker 15: of that too. We want communities across the state to

924
00:47:40,440 --> 00:47:42,799
Speaker 15: have the organizing tools and knowledge to be able to

925
00:47:42,840 --> 00:47:47,120
Speaker 15: continue to build local community power, community safety, community care,

926
00:47:47,840 --> 00:47:51,080
Speaker 15: and that should grow out and be across the state.

927
00:47:51,160 --> 00:47:54,920
Speaker 15: And so for me, democratic socialism is also an accountability

928
00:47:54,960 --> 00:47:57,600
Speaker 15: measure to make sure I'm holding true to my principles.

929
00:47:58,760 --> 00:48:01,080
Speaker 4: My last question is on this I was just going

930
00:48:01,160 --> 00:48:03,160
Speaker 4: to say, crysal on the taxation issue, it's pretty well

931
00:48:03,160 --> 00:48:06,640
Speaker 4: documented that Wisconsin has benefited from people and businesses coming

932
00:48:06,719 --> 00:48:10,560
Speaker 4: up from Illinois in the sense that Wisconsin has the

933
00:48:10,600 --> 00:48:13,080
Speaker 4: scene as having a more competitive business climate. So is

934
00:48:13,120 --> 00:48:18,280
Speaker 4: there are you sensitive to the issue of perhaps losing

935
00:48:18,320 --> 00:48:21,600
Speaker 4: some of that competitive edge if taxes go up. How

936
00:48:21,640 --> 00:48:24,880
Speaker 4: do we increase taxes in the state of Wisconsin in

937
00:48:24,880 --> 00:48:27,239
Speaker 4: a way that also ensures we're still working, you said,

938
00:48:27,239 --> 00:48:29,520
Speaker 4: your small business owner working with the business community to

939
00:48:29,520 --> 00:48:33,640
Speaker 4: make sure that people aren't going to other nearby states

940
00:48:33,680 --> 00:48:36,120
Speaker 4: that maybe border in the southeastern part or in different

941
00:48:36,120 --> 00:48:37,959
Speaker 4: parts of the state. And at the same time, though,

942
00:48:38,600 --> 00:48:40,160
Speaker 4: make sure that the system is fair.

943
00:48:41,719 --> 00:48:45,280
Speaker 15: Percent of the businesses in Wisconsin are small businesses, which

944
00:48:45,320 --> 00:48:48,359
Speaker 15: means they either make up to or less than five

945
00:48:48,360 --> 00:48:52,200
Speaker 15: million dollars in revenue or they have twenty or fewer

946
00:48:52,280 --> 00:48:57,000
Speaker 15: full time employees. Right now, we have manufacturing, agricultural large

947
00:48:57,040 --> 00:49:00,319
Speaker 15: business tax credits where some of the largest corporations are

948
00:49:00,360 --> 00:49:04,440
Speaker 15: paying point nine percent or less of corporate tax rates.

949
00:49:04,680 --> 00:49:08,239
Speaker 15: We have a very regressive income tax structure where some

950
00:49:08,320 --> 00:49:11,240
Speaker 15: of our lowest income earners are paying a higher tax

951
00:49:11,360 --> 00:49:14,560
Speaker 15: rate some some of our highest tax bracket earners. And

952
00:49:14,640 --> 00:49:18,040
Speaker 15: so when we have, you know, a millionaire tax, and

953
00:49:18,239 --> 00:49:21,120
Speaker 15: we add a one percent tax to billionaires, we're looking

954
00:49:21,160 --> 00:49:24,799
Speaker 15: at actually lowering property taxes, putting them by up to

955
00:49:24,880 --> 00:49:28,120
Speaker 15: forty four percent for folks across the state, and putting

956
00:49:28,120 --> 00:49:30,680
Speaker 15: that funding into public education because we have a very

957
00:49:30,760 --> 00:49:36,680
Speaker 15: antiquated public school funding formula that ties property taxes to

958
00:49:37,239 --> 00:49:41,600
Speaker 15: school funding. So in addition to changing this formula, you know,

959
00:49:41,760 --> 00:49:46,160
Speaker 15: fair taxation is actually good for growing local and state economies.

960
00:49:46,600 --> 00:49:50,360
Speaker 15: Policies like universal childcare and funding schools and paidly for

961
00:49:50,480 --> 00:49:54,480
Speaker 15: all is good for strengthening workforce and expanding our tax

962
00:49:54,520 --> 00:49:58,640
Speaker 15: revenue bank. We've had very minimal net migration. We have

963
00:49:58,760 --> 00:50:02,040
Speaker 15: to make Wisconsin a place where all working class folks

964
00:50:02,080 --> 00:50:04,880
Speaker 15: can thrive and grow families. I think that as a

965
00:50:04,920 --> 00:50:09,479
Speaker 15: small business owner, I understand the cost of trans of

966
00:50:11,080 --> 00:50:15,000
Speaker 15: workers where it's there's more turnover. I understand the costs

967
00:50:15,000 --> 00:50:17,719
Speaker 15: that come with closing and reopening a business. And I

968
00:50:17,760 --> 00:50:20,719
Speaker 15: think that you know, in the Scott Walker era and

969
00:50:20,760 --> 00:50:24,719
Speaker 15: even into these last eight years under Governor Evers, we

970
00:50:24,880 --> 00:50:28,239
Speaker 15: haven't seen the growth of manufacturing jobs. In fact, we've

971
00:50:28,239 --> 00:50:32,560
Speaker 15: actually seen manufacturers leave our state and so reinvesting in

972
00:50:32,640 --> 00:50:37,319
Speaker 15: green new jobs and renewable energy companies, manufacturing jobs in

973
00:50:38,320 --> 00:50:41,200
Speaker 15: you know, in the tech sector. I think that we're

974
00:50:41,440 --> 00:50:44,240
Speaker 15: we're going to be able to invest in the local

975
00:50:44,320 --> 00:50:47,480
Speaker 15: and state economies in a way that's much more durable

976
00:50:47,560 --> 00:50:50,279
Speaker 15: and sustainable than the tax credits we're giving to the

977
00:50:50,320 --> 00:50:54,640
Speaker 15: business businesses, some which aren't even headquartered in Wisconsin.

978
00:50:54,719 --> 00:50:55,640
Speaker 3: They're in Florida.

979
00:50:55,719 --> 00:50:59,560
Speaker 15: Fox I don't want to get Fox cond again. Yeah,

980
00:51:00,160 --> 00:51:04,239
Speaker 15: they're putting a data center where Foxcom was supposed to go. Wow,

981
00:51:04,360 --> 00:51:07,040
Speaker 15: you know, I think that speaks to the absurdity of

982
00:51:07,400 --> 00:51:10,560
Speaker 15: where we are in large corporations coming in taking over

983
00:51:10,560 --> 00:51:11,200
Speaker 15: a community.

984
00:51:11,480 --> 00:51:14,880
Speaker 2: Wow, Francesca hon tell people where they can find more

985
00:51:14,880 --> 00:51:17,600
Speaker 2: information about your campaign and support you if they're interested.

986
00:51:19,000 --> 00:51:22,439
Speaker 15: Yes, you can go to www dot franchusca hog dot

987
00:51:22,440 --> 00:51:26,960
Speaker 15: com or follow us on socials at Francesca Hong Wi.

988
00:51:27,160 --> 00:51:28,160
Speaker 6: Well, thank you so much.

989
00:51:28,280 --> 00:51:30,760
Speaker 2: I know you have a very busy life between campaign

990
00:51:30,840 --> 00:51:32,840
Speaker 2: and family and all of the things that come in between.

991
00:51:32,880 --> 00:51:34,560
Speaker 6: We really appreciate you making time for us.

992
00:51:35,120 --> 00:51:37,560
Speaker 15: Happy to be here, and folks, if you're in Wisconsin,

993
00:51:37,600 --> 00:51:39,520
Speaker 15: don't forget to make your plan to vote on or

994
00:51:39,560 --> 00:51:40,840
Speaker 15: before August eleventh.

995
00:51:41,800 --> 00:51:43,880
Speaker 2: So, Emily, did she convert you to socialism with that

996
00:51:43,920 --> 00:51:45,440
Speaker 2: Green Bay Packers pitch?

997
00:51:46,040 --> 00:51:49,399
Speaker 4: It's all over according to our right wing commenters. I've

998
00:51:49,400 --> 00:51:52,239
Speaker 4: been converted to socialism for years now though, so she

999
00:51:52,280 --> 00:51:55,960
Speaker 4: didn't have to do much. But now it's good to

1000
00:51:56,000 --> 00:51:59,840
Speaker 4: have these conversations, especially during I think the primaries, where

1001
00:52:00,080 --> 00:52:04,800
Speaker 4: you're often getting questions that are understandably from the left,

1002
00:52:04,880 --> 00:52:06,799
Speaker 4: so like from the right. Sometimes it's fun to pop

1003
00:52:06,840 --> 00:52:09,000
Speaker 4: in and be like, here's a question that you might

1004
00:52:09,040 --> 00:52:10,480
Speaker 4: get later down the road too.

1005
00:52:10,680 --> 00:52:13,040
Speaker 2: Yeah, well, and I mean, she is getting some of

1006
00:52:13,080 --> 00:52:15,560
Speaker 2: those questions from the centrists and the party right now.

1007
00:52:15,600 --> 00:52:20,000
Speaker 2: This is a I think increasingly common instance of centrist

1008
00:52:20,000 --> 00:52:23,640
Speaker 2: and disarray in this race because there are two more

1009
00:52:23,719 --> 00:52:28,000
Speaker 2: established ci Yes, there are two more establishment candidates in

1010
00:52:28,440 --> 00:52:31,680
Speaker 2: the race who are dividing some of that vote, and

1011
00:52:31,760 --> 00:52:33,480
Speaker 2: so there's been all this pressure of like, okay, one

1012
00:52:33,480 --> 00:52:36,359
Speaker 2: of y'all got to drop out, and now we're coming

1013
00:52:36,360 --> 00:52:38,640
Speaker 2: down to election pain. No one's dropping out, and that

1014
00:52:38,760 --> 00:52:40,759
Speaker 2: is helping to pave the path. Not to say she

1015
00:52:40,760 --> 00:52:42,680
Speaker 2: couldn't win if it was her versus one or the

1016
00:52:42,680 --> 00:52:45,360
Speaker 2: other of them, but that is certainly making her task easier,

1017
00:52:45,520 --> 00:52:47,200
Speaker 2: which is why at this point I think she's you know,

1018
00:52:47,239 --> 00:52:49,239
Speaker 2: I hate to use the betting market odds, but she's

1019
00:52:49,320 --> 00:52:53,439
Speaker 2: like eighty percent favored to win the Democratic primary, and

1020
00:52:53,680 --> 00:52:55,359
Speaker 2: in a year that looks like it's a very good

1021
00:52:55,360 --> 00:52:57,760
Speaker 2: one for Democrats, she's going to have a good shot

1022
00:52:58,040 --> 00:53:00,279
Speaker 2: to win the governor's mansion, which would be you know,

1023
00:53:00,520 --> 00:53:05,080
Speaker 2: it would genuinely be a historic, historic victory. First time

1024
00:53:05,440 --> 00:53:07,759
Speaker 2: socialists would win a state wide race, and in a

1025
00:53:07,760 --> 00:53:10,560
Speaker 2: swing state like Wisconsin, and obviously people watch very closely,

1026
00:53:10,640 --> 00:53:12,759
Speaker 2: so very important and interesting race that people are going

1027
00:53:12,800 --> 00:53:13,800
Speaker 2: to be following very closely.

1028
00:53:14,880 --> 00:53:18,239
Speaker 4: Tom Tiffany is probably a stronger candidate than Republicans have

1029
00:53:18,320 --> 00:53:18,960
Speaker 4: put up in a while.

1030
00:53:19,040 --> 00:53:21,320
Speaker 3: Kind of is sort of because of the lack of RIZ.

1031
00:53:21,480 --> 00:53:23,919
Speaker 6: So we'll see you. I don't know anything about him.

1032
00:53:24,719 --> 00:53:27,200
Speaker 4: He's from the northern part of the state, as Francesca

1033
00:53:27,239 --> 00:53:30,359
Speaker 4: Hung was saying, his background as a dairy farmer, very

1034
00:53:30,680 --> 00:53:36,320
Speaker 4: normy Republican who is like kind of Maga Freedom Caucus

1035
00:53:36,440 --> 00:53:40,840
Speaker 4: coded as he was in Congress, but is also just

1036
00:53:40,920 --> 00:53:43,600
Speaker 4: doesn't have the like Maga riz that some of the

1037
00:53:43,760 --> 00:53:46,920
Speaker 4: hardcore people do. So just from like a political standpoint,

1038
00:53:47,239 --> 00:53:50,560
Speaker 4: he's a little bit I think, more difficult to paint

1039
00:53:50,600 --> 00:53:51,640
Speaker 4: in one direction or the other.

1040
00:53:51,680 --> 00:53:53,200
Speaker 3: A little maybe slippery is the word.

1041
00:53:53,960 --> 00:53:54,400
Speaker 6: Gotcha?

1042
00:53:54,560 --> 00:53:57,560
Speaker 2: All right, well we will watch this one closely. Emily,

1043
00:53:57,560 --> 00:53:59,920
Speaker 2: thank you so much. It'll be us again tomorrow, but

1044
00:54:00,040 --> 00:54:01,840
Speaker 2: we're in switch places. Emily will be in the studio,

1045
00:54:01,960 --> 00:54:03,560
Speaker 2: I'll be at home, Chris will.

1046
00:54:03,480 --> 00:54:04,040
Speaker 3: Be at my home.

1047
00:54:04,280 --> 00:54:08,759
Speaker 2: Yeah, exactly, just swatch, just swap this out anyway. If

1048
00:54:08,760 --> 00:54:10,279
Speaker 2: you guys, have a great day, and we will both

1049
00:54:10,280 --> 00:54:11,120
Speaker 2: see you back here tomorrow.