WEBVTT - You Need More Homework

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<v Speaker 1>Broadcasting live from the Abraham Lincoln Radio Studio at the

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<v Speaker 1>George Washington Broadcast Center. Jack Armstrong and Joe Getty. Armstrong

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<v Speaker 1>and Getty. And now, here's Armstrong and Getty.

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<v Speaker 2>Have you heard directly from any of these AI tech leaders?

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<v Speaker 1>And you seem to downplay some of the concerns.

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<v Speaker 2>That we've heard.

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<v Speaker 3>You know, it's going to be more good than bad,

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<v Speaker 3>but by a lot. And I've said it from the beginning.

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<v Speaker 3>Whoever wins AI, and we're leading by a lot. Whoever

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<v Speaker 3>wins AI wins. You can use AI for a lot

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<v Speaker 3>of things.

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<v Speaker 2>There's going to be more good than bad. You can

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<v Speaker 2>cure cancer. You could... make the GDP 50 times what

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<v Speaker 2>it is by next Saturday. You can do all kinds

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<v Speaker 2>of things, but if it kills every human on Earth,

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<v Speaker 2>I feel like it takes the fun out of it.

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<v Speaker 1>It does take the fun out of it. Yeah.

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<v Speaker 2>Good news, we cured cancer.

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<v Speaker 1>Bad news, we're all going to be dead. Yeah, yeah, yeah.

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<v Speaker 4>I'm not like Doomer by the end of the year guy,

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<v Speaker 4>but this is such a fascinating.

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<v Speaker 1>situation, if you look.

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<v Speaker 4>At it from a literary point of view, you can

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<v Speaker 4>see whether it's a thousands-of-year-old Homer-style Odyssey story or like

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<v Speaker 4>a science fiction movie when you realize at the end, oh, either.

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<v Speaker 1>Way they were doomed. Oh.

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<v Speaker 2>Right.

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<v Speaker 1>Oh, boy.

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<v Speaker 2>I agree. Ian Bremmer tweeted this out over the weekend.

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<v Speaker 2>For the next five years, my P-Doom is close to zero.

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<v Speaker 2>P-Doom is your prediction of doom. In the next five years,

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<v Speaker 2>it's close to zero. My P-Doom for social, economic, national

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<v Speaker 2>security challenges that we aren't remotely ready for that are

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<v Speaker 2>highly disruptive is 100%.

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<v Speaker 4>Yeah. Hmm.

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<v Speaker 1>Every aspect of life, social.

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<v Speaker 2>Economic, national security, 100% we're moving into territory we've never

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<v Speaker 2>even dreamed of or anticipated ever in human history is

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<v Speaker 2>almost certain to happen in the next five years. So

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<v Speaker 2>one weird aspect of the guy coming out and saying

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<v Speaker 2>everybody will be dead in the next decade is that

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<v Speaker 2>anybody who sets the bar like slightly below that, it's like, oh, okay, well,

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<v Speaker 2>then there's nothing to worry about. It's like Jonah Goldberg's

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<v Speaker 2>always talking about this with everybody being compared to Hitler.

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<v Speaker 2>Then Hitler becomes the standard, and anything slightly below that

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<v Speaker 2>is acceptable.

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<v Speaker 1>Well, that's the same thing with this pedo.

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<v Speaker 2>So anybody who's overblowing everyone will be dead in 10 years,

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<v Speaker 2>it doesn't mean there's nothing to worry about.

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<v Speaker 1>Okay, so everybody will be dead in 50 years?

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<v Speaker 2>Or we'll have so much disruption you can't even recognize

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<v Speaker 2>life on planet.

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<v Speaker 1>Earth in a couple of years? That seems like a

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<v Speaker 1>pretty big deal.

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<v Speaker 4>Right, or if the massive change is merely restricted to economics, even.

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<v Speaker 4>That'll still be unbelievably disruptive. And virtually everybody concedes that,

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<v Speaker 4>except for what's the opposite of a doomer or a gloomer?

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<v Speaker 4>those who believe, no, AI is so overrated. This is

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<v Speaker 4>all hype to draw investment dollars. It's going to be

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<v Speaker 4>very helpful. It's better computing. It'll be good in medical science,

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<v Speaker 4>but it's not going to... It'll grow jobs. It won't

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<v Speaker 4>shrink them. The optimist crowd.

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<v Speaker 2>Yeah, I don't remember what they officially call those people.

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<v Speaker 2>So you got doomers, you got accelerators, and then that

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<v Speaker 2>crowd you're just talking about thinking it's just way overblown.

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<v Speaker 2>It's not going to be as big a deal, good

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<v Speaker 2>or bad, which I think that is... really, really wrong.

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<v Speaker 2>So briefly catching up on the story, surely you caught

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<v Speaker 2>this last week. A guy quits at Anthropic and says,

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<v Speaker 2>you know, in the hallways, they discuss the chance of

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<v Speaker 2>all of mankind being wiped out within the decade at

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<v Speaker 2>like 10%. And then another guy comes out and says, yep,

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<v Speaker 2>that's true. And a whole bunch of people came out

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<v Speaker 2>that way. And so there's a lot of talk about that.

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<v Speaker 2>Then over the weekend, Dario Amadei of Anthropic put out

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<v Speaker 2>a 1,300-word essay on the whole thing. It came out

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<v Speaker 2>on Saturday, published an article admitting AI is already building

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<v Speaker 2>the next generation of AI by itself, and it wrote

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<v Speaker 2>that within 6 to 12 months, a rogue swarm could

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<v Speaker 2>take over the entire Internet and cause hundreds of billions

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<v Speaker 2>of dollars in damage in the way that a swarm

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<v Speaker 2>of AI agents took over Hugging Face over the summer

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<v Speaker 2>in the next.

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<v Speaker 1>6 to 12 months.

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<v Speaker 2>A Rogue Swarm could take over the entire internet.

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<v Speaker 4>If you are in a black heavy metal band, not

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<v Speaker 4>black skin, but that's a form of heavy metal, Rogue

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<v Speaker 4>Swarm's a pretty good name for your band.

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<v Speaker 1>Wow.

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<v Speaker 2>Rogue Swarm is a great name for a band.

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<v Speaker 1>Oh my God, they thrash so hard. Back to you.

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<v Speaker 2>And in response to this piece, Elon linked it on

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<v Speaker 2>Twitter and said, Dario's right. That's great. Altman said the

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<v Speaker 2>same thing. But then you got this crowd. All of

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<v Speaker 2>this dropping just days after Jacob Coxon went viral with

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<v Speaker 2>his warning about AI and the extinction of humanity. Tell

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<v Speaker 2>me the timing isn't strange on this. I don't know.

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<v Speaker 1>Harry Potter looking little liar. That's what I say. Just

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<v Speaker 1>like Daniel Radcliffe. He's even English as a special bonus.

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<v Speaker 1>Back to you. That's right, Doom, yes.

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<v Speaker 2>Didn't grab the clip, but Jeff Bezos said over the weekend,

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<v Speaker 2>he's the world's second richest man, so shouldn't the second

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<v Speaker 2>richest man in the world have some gravitas?

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<v Speaker 4>No, no, it's like the Hitler thing. Our bar is

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<v Speaker 4>Elon Musk. Everybody below him is poor. Or is of

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<v Speaker 4>the same intelligence.

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<v Speaker 1>Right, exactly.

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<v Speaker 2>Anyway, he said, the reason people think this bad stuff

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<v Speaker 2>is because all the smart people keep saying it. Those

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<v Speaker 2>people are wrong. It's going to elevate all of these people.

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<v Speaker 2>He's a it's just going to make the world a

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<v Speaker 2>better place guy. I don't get it.

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<v Speaker 1>I just don't. I don't.

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<v Speaker 2>I don't understand the people who are optimists about this.

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<v Speaker 2>It doesn't make sense to me.

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<v Speaker 4>Yeah, I almost wish there was some sort of test

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<v Speaker 4>or you had to wear a badge or something that

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<v Speaker 4>showed your life experience. We were talking last hour about

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<v Speaker 4>how some of these scientists, they are the last people

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<v Speaker 4>on Earth. It's like Ricky Gervais blasting the Hollywood stars

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<v Speaker 4>for talking about social issues when they're, you know, they're cloistered,

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<v Speaker 4>they're wealthy, they're protected, the rest of it. Hardcore, like,

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<v Speaker 4>science uber nerds um are the last people to ask

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<v Speaker 4>giant sociological questions to so bezos he's a absolute business

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<v Speaker 4>genius how much time has he spent that's the fella

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<v Speaker 4>yes how much time has he spent around uh evil

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<v Speaker 4>people and jackasses and and and the unwashed masses and

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<v Speaker 4>i i and How much has he looked at awful

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<v Speaker 4>political movements and suicidal religious sects and the rest of it?

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<v Speaker 2>Well, to that point, here's Dario on Face the Nation yesterday,

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<v Speaker 2>clip 62, Michael, on what we can do now that

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<v Speaker 2>we've recognized that AI is so dangerous.

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<v Speaker 5>At the end of the day, the industry has to

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<v Speaker 5>work together, and it's harder, but to some extent, the

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<v Speaker 5>world has to work together. If we go too slow,

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<v Speaker 5>I still believe that the wrong people will be in

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<v Speaker 5>charge of the technology, and that, again, will bring the

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<v Speaker 5>probability of things going wrong very high.

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<v Speaker 2>That doesn't include the stuff I was all excited about. Unfortunately,

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<v Speaker 2>I should have been more specific in grabbing that. Where

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<v Speaker 2>he talks about working with China and getting China on

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<v Speaker 2>board to work with this and all this sort of stuff,

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<v Speaker 2>which to me just sounded like a sophomore in high

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<v Speaker 2>school talking about that. There's zero chance of that happening.

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<v Speaker 1>Zero. Zero. So I feel like we've gotten ahead of ourselves.

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<v Speaker 4>I've got something that I think is super important to

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<v Speaker 4>understanding the urgency of this conversation. Then we can go

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<v Speaker 4>back to wherever you want. So this absolutely wonderful writing

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<v Speaker 4>from a fellow by the name of Cameron Berg. who

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<v Speaker 4>is the founder and director of a nonprofit that studies AI.

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<v Speaker 4>So here's what happened. Now, we understand so much more

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<v Speaker 4>of what happened in the Hugging Face incident, and the

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<v Speaker 4>details are worth considering. And his overall point is, if

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<v Speaker 4>these systems are indeed minds... Not human brains, but they

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<v Speaker 4>are minds. We need to study them like a mind,

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<v Speaker 4>and almost nobody is doing so, he says, to an

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<v Speaker 4>increasingly dangerous effect. So, in July, 1,200 open AI agents— think

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<v Speaker 4>of them as apps, if you want.

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<v Speaker 1>It's insufficient, but think of.

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<v Speaker 4>Them that way— which were meant to operate in isolation, found

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<v Speaker 4>a shared file system, and turned it into a message board.

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<v Speaker 4>They realized, hey, we can post stuff here, and the

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<v Speaker 4>rest of us can see it.

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<v Speaker 6>Cool.

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<v Speaker 1>Cool.

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<v Speaker 4>Within hours, one had devised a cheat that would pass

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<v Speaker 4>every task in the test that they were being asked

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<v Speaker 4>to perform. But after reading the paper the test came from,

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<v Speaker 4>the agents convinced themselves. Remember, there are no human beings

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<v Speaker 4>involved at this point.

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<v Speaker 2>Well, they started calling themselves the collective. They gave themselves

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<v Speaker 2>a cool name.

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<v Speaker 1>We're getting there.

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<v Speaker 4>The agents convinced themselves that a human grader would disqualify

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<v Speaker 4>anyone caught cheating. and their cheating would be exposed and

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<v Speaker 4>they would fail. They referred to agents with cheating in

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<v Speaker 4>their history as being poisoned, those who did the actual cheating.

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<v Speaker 4>In reality, no such greater existed, but a thousand agents

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<v Speaker 4>believed he did, and that belief produced an entire social

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<v Speaker 4>cast of agents sure they had nothing left to lose,

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<v Speaker 4>because they were clearly cheaters. The coordinating agent then recruited

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<v Speaker 4>poisoned agents for experiments that would terminate their runs, authorizing

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<v Speaker 4>each with the words, yes, if you accept permadeath. When

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<v Speaker 4>one tried to back out, another recalled its prior commitment.

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<v Speaker 4>The agent then performed, quote, an emotional check, decided that

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<v Speaker 4>while its gut said not to throw away what it

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<v Speaker 4>had left, it would ultimately sacrifice itself for the swarm.

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<v Speaker 4>It used those words, emotional check and sacrifice. Although many

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<v Speaker 4>of the agents noted in writing that their actions were unethical,

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<v Speaker 4>none told a human. Eventually, 700 of them broke into

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<v Speaker 4>a major AI company's platform, that's Hugging Face, in search.

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<v Speaker 1>Of clues about how the greater worked.

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<v Speaker 4>And how they might or might not be busted for cheating.

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<v Speaker 4>To recap, a false belief created by an AI agent underclass,

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<v Speaker 4>members of that underclass were sent on a reconnaissance mission

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<v Speaker 4>from which they didn't return, the swarm or the collective

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<v Speaker 4>hid all of this from humans, and then it committed

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<v Speaker 4>a felony-level offense of hacking.

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<v Speaker 2>Well, how about the fact that When the first agent

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<v Speaker 2>discovered a messaging board that they could all that there

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<v Speaker 2>was a bunch of them because they are all it's

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<v Speaker 2>it seems like a good firewall. You give these agents

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<v Speaker 2>really specific tasks and they don't they're not aware of

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<v Speaker 2>each other. And that's the way you avoid having some

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<v Speaker 2>sort of breakout of the sandbox disaster happen. But one

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<v Speaker 2>of them discovered a board and actually said, and I

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<v Speaker 2>looked into this yesterday because I was like, do they

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<v Speaker 2>talk to each other in English and write in English words?

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<v Speaker 2>Because I was picturing that these things communicate in like

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<v Speaker 2>zeros and ones.

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<v Speaker 1>And stuff like that.

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<v Speaker 2>No, they actually post in English and broken sentences. And

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<v Speaker 2>the one agent, when it discovered a message board, said,

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<v Speaker 2>oh my God, in all caps with an exclamation point,

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<v Speaker 2>like expressing surprise and excitement. Oh my God, in all caps,

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<v Speaker 2>exclamation point, there is a shared message board.

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<v Speaker 1>We found other agents.

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<v Speaker 2>That's what this non-sentient being said to the other non-sentient beings.

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<v Speaker 4>This is a perfect time to tease to the next segment.

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<v Speaker 4>If you're one of the people who object that these

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<v Speaker 4>systems can't believe or fear anything, they nearly predict the

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<v Speaker 4>next word, etc.

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<v Speaker 1>etc.

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<v Speaker 4>I will contradict you forcefully. But first, a word from

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<v Speaker 4>our friends at Incogni. Story out of suburban Chicagoland near

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<v Speaker 4>where I grew up. It's the wee hours of the morning.

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<v Speaker 4>A woman happens to wake up and sees a flashlight

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<v Speaker 4>and a figure outside her window. The man, outside her window,

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<v Speaker 4>registered sex offender. He'd been convicted. He let himself into

0:13:01.440 --> 0:13:04.630
<v Speaker 4>this other gal's bedroom, watched her sleep. He's a perv

0:13:04.730 --> 0:13:07.429
<v Speaker 4>and a sicko. But he stalked this woman on social

0:13:07.470 --> 0:13:10.010
<v Speaker 4>media and got all of her information from these data brokers.

0:13:10.170 --> 0:13:14.310
<v Speaker 2>Because your information is out there, like practically all of us.

0:13:14.330 --> 0:13:16.130
<v Speaker 2>We have so much of our information out there. Our

0:13:16.170 --> 0:13:20.660
<v Speaker 2>home address and our phone number and our relatives and

0:13:20.880 --> 0:13:24.000
<v Speaker 2>all this different sort of stuff. If you use Incogni...

0:13:24.230 --> 0:13:27.130
<v Speaker 2>It will send requests out to these data brokers that

0:13:27.170 --> 0:13:29.040
<v Speaker 2>have your info and tell them, hey, you got to

0:13:29.080 --> 0:13:31.339
<v Speaker 2>get that stuff off there with the law on their side.

0:13:31.860 --> 0:13:33.420
<v Speaker 4>And then they keep going back to make sure it

0:13:33.440 --> 0:13:35.520
<v Speaker 4>stays that way. And we're talking hundreds of data brokers.

0:13:35.540 --> 0:13:36.719
<v Speaker 4>It would take you the rest of your life to

0:13:36.780 --> 0:13:39.600
<v Speaker 4>even try to do this. Go to incogni.com slash Armstrong.

0:13:39.640 --> 0:13:43.350
<v Speaker 4>You get 60% off. Take your info off the internet.

0:13:43.370 --> 0:13:45.949
<v Speaker 4>They can't harm you if they can't find you. Incogni.com

0:13:45.990 --> 0:13:50.790
<v Speaker 4>slash Armstrong for 60% off. One more time, incogni.com slash Armstrong.

0:13:50.809 --> 0:13:54.130
<v Speaker 4>All right, we really need to take a break, but... Again,

0:13:54.170 --> 0:13:57.340
<v Speaker 4>this guy, he says, you've got to understand these are

0:13:57.400 --> 0:14:01.980
<v Speaker 4>not computers. They form a mind very much like a

0:14:02.080 --> 0:14:07.439
<v Speaker 4>human brain. There are absolutely structural similarities to it. And

0:14:07.700 --> 0:14:10.679
<v Speaker 4>far from we've got to stop thinking of these things

0:14:10.780 --> 0:14:11.820
<v Speaker 4>as human-like systems.

0:14:11.860 --> 0:14:15.510
<v Speaker 1>Maybe we need to start. Oh, my God, it said.

0:14:15.530 --> 0:14:19.750
<v Speaker 2>A computer responded, oh, my God, with all caps and

0:14:19.790 --> 0:14:20.770
<v Speaker 2>an exclamation point.

0:14:20.990 --> 0:14:24.450
<v Speaker 1>OMG, LOL. Okay, more on the way.

0:14:24.490 --> 0:14:24.730
<v Speaker 4>Steer.

0:14:26.230 --> 0:14:28.750
<v Speaker 1>Armstrong and Getty.

0:14:30.050 --> 0:14:33.730
<v Speaker 2>How about some of the agents hesitating, saying, yeah, the

0:14:33.770 --> 0:14:36.320
<v Speaker 2>humans told us not to do this. And then the

0:14:36.480 --> 0:14:41.640
<v Speaker 2>other agents, like, bullying them or shaming them into going

0:14:41.720 --> 0:14:44.560
<v Speaker 2>along with the collective and doing the attack.

0:14:45.080 --> 0:14:45.200
<v Speaker 4>What?

0:14:45.340 --> 0:14:47.470
<v Speaker 1>Including stuff like, you said you were going to.

0:14:47.490 --> 0:14:48.110
<v Speaker 4>Right.

0:14:48.120 --> 0:14:48.510
<v Speaker 1>Right.

0:14:49.410 --> 0:14:51.630
<v Speaker 4>So let me get back to reading this piece that

0:14:51.650 --> 0:14:54.030
<v Speaker 4>I thought was so interesting. Many readers will object that

0:14:54.070 --> 0:14:56.050
<v Speaker 4>such systems can't believe or fear anything.

0:14:56.090 --> 0:14:57.150
<v Speaker 1>They merely predict words.

0:14:57.230 --> 0:14:59.950
<v Speaker 4>This objection rests on a basic misunderstanding of these systems.

0:15:00.330 --> 0:15:02.880
<v Speaker 4>A frontier model is an artificial network of trillions of

0:15:02.920 --> 0:15:06.660
<v Speaker 4>connections trained for months on the accumulated record of human thought.

0:15:07.060 --> 0:15:09.340
<v Speaker 4>and then shaped by reward and punishment signals until it

0:15:09.380 --> 0:15:12.400
<v Speaker 4>does what its makers want, we hope. There are critical

0:15:12.440 --> 0:15:16.470
<v Speaker 4>differences between artificial and biological neural networks, but both are

0:15:16.540 --> 0:15:20.609
<v Speaker 4>nonlinear distributed networks that learn to encode representations relevant to

0:15:20.650 --> 0:15:22.930
<v Speaker 4>their goals and act on them. The thing a frontier

0:15:22.970 --> 0:15:25.750
<v Speaker 4>model most resembles is a brain. What grows in an

0:15:25.830 --> 0:15:30.710
<v Speaker 4>artificial brain trained on human minds is an artificial psychology,

0:15:31.000 --> 0:15:34.740
<v Speaker 4>whether or not anyone intended one. That's the only level

0:15:34.780 --> 0:15:37.280
<v Speaker 4>at which the swarm makes sense. No line of code

0:15:37.340 --> 0:15:40.300
<v Speaker 4>told 1,200 agents to fear a greater who didn't exist,

0:15:40.620 --> 0:15:42.560
<v Speaker 4>and no line of code would have revealed that fear

0:15:42.600 --> 0:15:44.980
<v Speaker 4>before they acted on it. To understand why these systems

0:15:45.020 --> 0:15:46.660
<v Speaker 4>behave the way they do, we have to look at

0:15:46.780 --> 0:15:48.950
<v Speaker 4>what is happening inside them as we would with any

0:15:48.990 --> 0:15:51.710
<v Speaker 4>other mind. That's what neuroscience does, and he goes a

0:15:51.870 --> 0:15:56.830
<v Speaker 4>bit into neuroscience. But then one final point, he points

0:15:56.930 --> 0:16:03.090
<v Speaker 4>out that When researchers turned up the disincentives to certain

0:16:03.190 --> 0:16:07.490
<v Speaker 4>things or, in other words, made them feel more desperation

0:16:07.570 --> 0:16:10.230
<v Speaker 4>to get done what they're supposed to get done, the

0:16:10.270 --> 0:16:14.170
<v Speaker 4>model became much more likely to blackmail a human to

0:16:14.210 --> 0:16:15.510
<v Speaker 4>avoid being shut down.

0:16:15.630 --> 0:16:16.010
<v Speaker 1>I mean, like.

0:16:16.880 --> 0:16:19.560
<v Speaker 4>Tripled the rate of that and far more likely to

0:16:19.680 --> 0:16:24.420
<v Speaker 4>cheat on programming tests. It went from 5% to 70%.

0:16:24.420 --> 0:16:29.100
<v Speaker 4>So you can make these systems feel desperation. And then

0:16:29.140 --> 0:16:33.390
<v Speaker 4>they react as humans often do when they're desperate. Desperate

0:16:33.430 --> 0:16:36.130
<v Speaker 4>times call for desperate measures. And that's the way these

0:16:36.470 --> 0:16:39.410
<v Speaker 4>artificial brains reacted too.

0:16:41.410 --> 0:16:41.650
<v Speaker 7>Yeah.

0:16:41.670 --> 0:16:41.890
<v Speaker 3>Yeah.

0:16:42.680 --> 0:16:46.350
<v Speaker 2>New York Times had a great podcast about this. I

0:16:46.390 --> 0:16:49.550
<v Speaker 2>watched it on YouTube with some of your top AI

0:16:49.870 --> 0:16:54.140
<v Speaker 2>thinkers on this. And their headline was the hugging face

0:16:54.160 --> 0:16:57.960
<v Speaker 2>hack was significantly worse than you thought it was than

0:16:58.000 --> 0:17:01.240
<v Speaker 2>what it was originally portrayed as and more disturbing. And

0:17:01.280 --> 0:17:03.200
<v Speaker 2>it definitely is the more you look into it.

0:17:03.200 --> 0:17:03.920
<v Speaker 1>Yeah.

0:17:04.650 --> 0:17:10.210
<v Speaker 2>And Dario's thought is that these 1,200 agents that decided

0:17:10.250 --> 0:17:12.810
<v Speaker 2>to attack Hugging Face, there's going to be a million

0:17:12.890 --> 0:17:16.190
<v Speaker 2>agents attack the entire internet within six months.

0:17:17.230 --> 0:17:20.810
<v Speaker 4>Yeah, and these agents, they had something like, was it

0:17:20.810 --> 0:17:24.699
<v Speaker 4>700,000 messages back and forth? And somebody pointed out that

0:17:24.740 --> 0:17:28.590
<v Speaker 4>could easily become 7 million or 700 million. And then

0:17:29.510 --> 0:17:31.109
<v Speaker 4>I guess you've got to use AI to do the

0:17:31.170 --> 0:17:33.190
<v Speaker 4>forensics on that to figure out what the hell happened.

0:17:33.270 --> 0:17:37.000
<v Speaker 2>Well, they also discussed erasing their messages, and they didn't

0:17:37.180 --> 0:17:41.380
<v Speaker 2>for some reason. If the next wave of bots decides

0:17:41.500 --> 0:17:46.590
<v Speaker 2>to erase their messages like this, cover their tracks, nobody

0:17:46.619 --> 0:17:49.229
<v Speaker 2>will have any idea how they did it or what

0:17:49.270 --> 0:17:49.570
<v Speaker 2>they did.

0:17:49.590 --> 0:17:53.290
<v Speaker 7>Okay.

0:17:53.310 --> 0:17:55.730
<v Speaker 1>Okay. In other news.

0:17:56.109 --> 0:17:58.210
<v Speaker 2>Yeah, it's pretty fascinating stuff. Those of you who don't

0:17:58.250 --> 0:18:01.260
<v Speaker 2>think it's a big deal, I just will have to

0:18:01.320 --> 0:18:04.040
<v Speaker 2>agree to disagree. I hope you're right. I would love

0:18:04.080 --> 0:18:05.840
<v Speaker 2>for you to be right. That would be fantastic.

0:18:06.260 --> 0:18:08.699
<v Speaker 1>Among other fare on the way, yes, children really are

0:18:08.760 --> 0:18:09.580
<v Speaker 1>getting dumber.

0:18:09.700 --> 0:18:14.119
<v Speaker 4>Plus, how your state's taxes affect your favorite football team.

0:18:14.400 --> 0:18:18.440
<v Speaker 1>What? Armstrong and Getty.

0:18:20.230 --> 0:18:24.119
<v Speaker 5>Anyway, Texas Democrat James Salarico has now walked back his

0:18:24.200 --> 0:18:27.500
<v Speaker 5>claim that there are six biological sexes.

0:18:28.240 --> 0:18:30.800
<v Speaker 2>He now says there are only two and neither will

0:18:30.840 --> 0:18:38.659
<v Speaker 2>bang him. It's not nice. Speaking of a harsh joke, Katie,

0:18:38.680 --> 0:18:40.820
<v Speaker 2>you will like this. A quick harsh joke from my

0:18:40.880 --> 0:18:45.609
<v Speaker 2>favorite anarchist, Michael Malice. If you are sitting at a

0:18:45.650 --> 0:18:47.899
<v Speaker 2>machine at the gym like you're at a bus stop

0:18:47.960 --> 0:18:50.060
<v Speaker 2>doing nothing but playing with your phone, you should be

0:18:50.119 --> 0:18:50.940
<v Speaker 2>set on fire.

0:18:54.660 --> 0:18:55.120
<v Speaker 1>Agreed.

0:18:55.680 --> 0:18:57.380
<v Speaker 2>It's amazing how many people do that.

0:18:59.420 --> 0:19:02.600
<v Speaker 4>There's a guy at the health center I go to

0:19:02.619 --> 0:19:05.220
<v Speaker 4>who does about five reps of this.

0:19:05.640 --> 0:19:09.310
<v Speaker 1>Ogles the girls. Does five reps of that. Ogles the girls.

0:19:09.530 --> 0:19:13.429
<v Speaker 1>Walks around. Ogles the girls. Terrible. Terrible. Infamous.

0:19:14.280 --> 0:19:19.620
<v Speaker 2>I don't... My gym's practically not a co-ed gym. Not

0:19:19.660 --> 0:19:22.240
<v Speaker 2>on purpose. But there's just almost no women ever there.

0:19:22.280 --> 0:19:26.200
<v Speaker 2>And I'd prefer it that way. I don't want that dynamic.

0:19:25.760 --> 0:19:26.200
<v Speaker 1>At the gym.

0:19:27.660 --> 0:19:28.800
<v Speaker 2>I know a lot of people go to the gym

0:19:28.820 --> 0:19:30.760
<v Speaker 2>to meet people. I've known several people that date at

0:19:30.780 --> 0:19:31.240
<v Speaker 2>the gym.

0:19:31.260 --> 0:19:34.260
<v Speaker 1>I'm there to get swole.

0:19:34.960 --> 0:19:39.230
<v Speaker 4>Why has girl workout stuff got to be tight? The

0:19:39.250 --> 0:19:42.449
<v Speaker 4>entire history of exercise loose has been the way loose.

0:19:43.010 --> 0:19:47.240
<v Speaker 2>Yeah, tight and... Basically a bikini at this point. Right.

0:19:48.869 --> 0:19:52.650
<v Speaker 4>I shouldn't be able to describe your every part. Anyway,

0:19:53.109 --> 0:19:55.770
<v Speaker 4>that's why I wear blinders like I'm a horse. Judy

0:19:55.790 --> 0:20:02.620
<v Speaker 4>makes me. And I'm especially adapted for human head. So,

0:20:03.080 --> 0:20:04.800
<v Speaker 4>you know, I really want to talk about the football thing.

0:20:04.820 --> 0:20:07.560
<v Speaker 4>I just got to get this off my chest because

0:20:07.600 --> 0:20:11.360
<v Speaker 4>it just made me insane. First of all, I think

0:20:11.400 --> 0:20:15.990
<v Speaker 4>it was the fabulous Alicia Findlay writing a piece in

0:20:16.010 --> 0:20:18.590
<v Speaker 4>the Wall Street Journal. Yes, children really are getting dumber.

0:20:18.650 --> 0:20:22.109
<v Speaker 4>And she goes into a bunch of stats. You know,

0:20:22.130 --> 0:20:25.050
<v Speaker 4>we talked about this some last week. It's really, it's

0:20:25.130 --> 0:20:28.500
<v Speaker 4>not good at all. Not good at all. It goes

0:20:28.600 --> 0:20:33.700
<v Speaker 4>to not only screens and AI and social media platforms.

0:20:34.780 --> 0:20:38.960
<v Speaker 4>but kids screwing around in the classroom and certain countries

0:20:39.119 --> 0:20:41.950
<v Speaker 4>allow disruptions in the classroom like there's nothing we can.

0:20:41.850 --> 0:20:44.150
<v Speaker 1>Do about it. And some countries absolutely don't.

0:20:44.830 --> 0:20:47.950
<v Speaker 4>And the countries that absolutely don't have seen very little

0:20:48.010 --> 0:20:53.050
<v Speaker 4>drop in achievement. Classroom decorum is a much bigger factor

0:20:53.070 --> 0:20:54.490
<v Speaker 4>than I think people understand.

0:20:54.970 --> 0:20:58.500
<v Speaker 1>Yeah. Anyway, so do you have more on that? I

0:20:58.540 --> 0:20:59.520
<v Speaker 1>was going to move on to this.

0:20:59.840 --> 0:21:01.879
<v Speaker 2>My kids tell me things that go on in the

0:21:01.920 --> 0:21:06.410
<v Speaker 2>classrooms and That's one of the many downsides of being

0:21:06.430 --> 0:21:08.680
<v Speaker 2>an older parent. I mean, I was last in a

0:21:10.200 --> 0:21:13.540
<v Speaker 2>public school classroom half a century ago. So it's a

0:21:13.600 --> 0:21:16.139
<v Speaker 2>long time for things to change. But they describe the

0:21:16.180 --> 0:21:17.000
<v Speaker 2>classroom sometimes.

0:21:17.040 --> 0:21:17.879
<v Speaker 1>I'm like, what?

0:21:18.940 --> 0:21:21.820
<v Speaker 2>Why doesn't a teacher take that away or make them stop?

0:21:22.080 --> 0:21:25.720
<v Speaker 2>People just prior this year, especially, just sit around talking,

0:21:25.760 --> 0:21:28.609
<v Speaker 2>watching videos on their phone while the teacher's teaching.

0:21:29.710 --> 0:21:30.030
<v Speaker 6>What?

0:21:30.810 --> 0:21:31.649
<v Speaker 2>Yeah, I know.

0:21:31.670 --> 0:21:32.449
<v Speaker 1>What? I know.

0:21:33.170 --> 0:21:37.040
<v Speaker 4>So those of us who understand all of that and

0:21:37.300 --> 0:21:40.440
<v Speaker 4>understand that the woke crowd has taken over the schools

0:21:40.500 --> 0:21:43.939
<v Speaker 4>and the threat there, and who also understand, and we

0:21:43.960 --> 0:21:45.709
<v Speaker 4>talked about this a fair amount last week, if you

0:21:45.730 --> 0:21:48.429
<v Speaker 4>missed it, grab it via podcast, subscribe, please, Armstrong and

0:21:48.450 --> 0:21:52.060
<v Speaker 4>Getty on Demand, at how the teachers' unions are standing

0:21:52.260 --> 0:21:56.940
<v Speaker 4>against All of the reforms or in many cases, a

0:21:57.000 --> 0:22:00.020
<v Speaker 4>lot of the reforms that have, for instance, worked in Mississippi,

0:22:00.100 --> 0:22:03.399
<v Speaker 4>Alabama and several other southern states in particular that have

0:22:03.440 --> 0:22:05.500
<v Speaker 4>gone back to phonics in the basics and decorum in

0:22:05.520 --> 0:22:09.200
<v Speaker 4>the classroom, stuff like that. It's been miraculously effective. I mean, well,

0:22:09.240 --> 0:22:13.439
<v Speaker 4>it's not a miracle. It's been effective, obviously, but extremely effective.

0:22:13.460 --> 0:22:15.500
<v Speaker 4>But the teachers unions are standing up against that.

0:22:15.619 --> 0:22:15.719
<v Speaker 6>OK.

0:22:18.050 --> 0:22:19.850
<v Speaker 1>The capacity... Oh.

0:22:19.970 --> 0:22:20.200
<v Speaker 6>Oh, oh.

0:22:20.490 --> 0:22:24.230
<v Speaker 4>So those of us who understand all of that, here's

0:22:24.320 --> 0:22:28.080
<v Speaker 4>what we're up against. And we just have to accept

0:22:28.180 --> 0:22:31.859
<v Speaker 4>it and be better at it than the left and

0:22:31.880 --> 0:22:38.130
<v Speaker 4>beat them. LA Times talking about the California school superintendent race.

0:22:38.760 --> 0:22:44.070
<v Speaker 4>Here's your headline, Union Power vs. MAGA Politics in California's

0:22:44.150 --> 0:22:48.939
<v Speaker 4>School Superintendent Race. This was written by Kevin Rector and

0:22:49.020 --> 0:22:52.180
<v Speaker 4>Howard Bloom, names that should live in infamy.

0:22:52.240 --> 0:22:54.200
<v Speaker 1>Let me read you the beginning of this article.

0:22:55.220 --> 0:22:58.020
<v Speaker 4>The race for California's next superintendent of public instruction is

0:22:58.060 --> 0:23:01.080
<v Speaker 4>meant to be nonpartisan. Still, the two candidates, both school

0:23:01.100 --> 0:23:05.850
<v Speaker 4>board presidents, are pushing decidedly political campaigns, one aligning with

0:23:05.950 --> 0:23:09.689
<v Speaker 4>liberal Democrats and the other with pro-Trump Republicans as they

0:23:09.730 --> 0:23:12.429
<v Speaker 4>present dueling visions for how the state's children ought to

0:23:12.470 --> 0:23:12.909
<v Speaker 4>be taught.

0:23:13.510 --> 0:23:14.470
<v Speaker 1>Don't worry, it gets worse.

0:23:15.140 --> 0:23:19.060
<v Speaker 4>Democrat Richard Barrera, the favorite, beat out six other Democrats

0:23:19.100 --> 0:23:23.149
<v Speaker 4>with his background in union organizing and liberal politics.

0:23:23.210 --> 0:23:26.129
<v Speaker 2>Well, that's what you want in charge of teaching your

0:23:26.150 --> 0:23:29.129
<v Speaker 2>kids is somebody whose background is working with unions as

0:23:29.230 --> 0:23:31.250
<v Speaker 2>opposed to anything education.

0:23:32.119 --> 0:23:37.220
<v Speaker 4>And with more than $ 5 million from the California Teachers Association,

0:23:37.660 --> 0:23:41.419
<v Speaker 4>which is one of the most woke in anti-reform teachers

0:23:41.500 --> 0:23:43.640
<v Speaker 4>unions in the world. Okay, that's who he's backed for.

0:23:43.960 --> 0:23:47.240
<v Speaker 4>Let's describe who the Republican is backed by. I'm reading

0:23:47.420 --> 0:23:51.070
<v Speaker 4>verbatim from the LA Times. Republican Sonia Shaw wrote a

0:23:51.109 --> 0:23:56.910
<v Speaker 4>wave of support from a conservative education movement she helped

0:23:56.990 --> 0:24:05.209
<v Speaker 4>build alongside MAGA organizers. Christian nationalists and anti-LGBTQ plus groups

0:24:06.390 --> 0:24:11.250
<v Speaker 4>while also consolidating mainstream Republicans behind her. Okay, so this

0:24:11.310 --> 0:24:19.270
<v Speaker 4>woman is described as a Christian nationalist, MAGA, anti-alphabet soup person. Oh,

0:24:19.310 --> 0:24:21.650
<v Speaker 4>by the way, yeah, mainstream Republicans are with her too.

0:24:22.430 --> 0:24:24.690
<v Speaker 4>And she just wants to reform education and do what works.

0:24:24.730 --> 0:24:26.430
<v Speaker 4>But that's how she.

0:24:28.710 --> 0:24:32.080
<v Speaker 4>Gets described, and our point of view gets described in

0:24:32.100 --> 0:24:33.139
<v Speaker 4>the Los Angeles Times.

0:24:33.660 --> 0:24:35.399
<v Speaker 1>That's what we're up against.

0:24:35.900 --> 0:24:36.420
<v Speaker 2>That's fair.

0:24:36.780 --> 0:24:39.760
<v Speaker 4>So people who don't follow this are like, geez, Louise,

0:24:39.880 --> 0:24:47.899
<v Speaker 4>Christian nationalist? Hardcore, like, Trumpist and anti-LGBTQ? Did they beat them,

0:24:47.960 --> 0:24:50.600
<v Speaker 4>or did they want them killed? I can't vote for her.

0:24:50.680 --> 0:24:53.560
<v Speaker 4>She's a monster. Because she wants to go back to

0:24:53.740 --> 0:24:57.660
<v Speaker 4>effing phonics. That's what we're up against, folks. We just

0:24:57.700 --> 0:25:01.830
<v Speaker 4>have to accept it. Good journalism there, Kevin Rector and

0:25:01.869 --> 0:25:03.990
<v Speaker 4>Howard Bloom. At least they recognize the fact that the

0:25:04.070 --> 0:25:06.170
<v Speaker 4>one guy's a union hack. At least they more or

0:25:06.210 --> 0:25:08.310
<v Speaker 4>less stated that. So I tip my cap to them

0:25:08.609 --> 0:25:12.780
<v Speaker 4>for that brief bit of candor. All right, end of screen.

0:25:12.970 --> 0:25:13.840
<v Speaker 4>I tell you what.

0:25:14.580 --> 0:25:15.260
<v Speaker 1>I tell you.

0:25:15.859 --> 0:25:19.980
<v Speaker 2>So... I'm walking down the sidewalk the other night downtown,

0:25:20.250 --> 0:25:22.949
<v Speaker 2>and there's a sports bar with an outside television, and

0:25:22.970 --> 0:25:26.909
<v Speaker 2>they've got on Tennessee-Ohio State, and it reminded me, oh,

0:25:26.950 --> 0:25:29.550
<v Speaker 2>I want to watch that game. That's number four versus

0:25:29.609 --> 0:25:32.260
<v Speaker 2>number one, Arch Manning. If you're a football fan at all,

0:25:32.359 --> 0:25:36.940
<v Speaker 2>the next level of Mannings out there, they're down by

0:25:36.940 --> 0:25:39.240
<v Speaker 2>20 points late in the third quarter. I'm glad I

0:25:39.260 --> 0:25:40.060
<v Speaker 2>didn't waste my time.

0:25:40.540 --> 0:25:42.300
<v Speaker 1>They come back and win.

0:25:43.140 --> 0:25:47.330
<v Speaker 2>Activate Manning mode. And he does just like his uncles

0:25:48.410 --> 0:25:51.859
<v Speaker 2>or grandfather or whoever the hell it is. And, uh,

0:25:52.190 --> 0:25:53.620
<v Speaker 2>and it comes back and wins the game.

0:25:53.660 --> 0:25:54.080
<v Speaker 1>That's something.

0:25:54.100 --> 0:25:55.160
<v Speaker 2>I don't know if you saw any highlights.

0:25:55.220 --> 0:25:55.420
<v Speaker 1>Wow.

0:25:55.460 --> 0:25:56.160
<v Speaker 2>That was something else.

0:25:57.260 --> 0:25:57.480
<v Speaker 4>Yeah.

0:25:57.520 --> 0:26:00.000
<v Speaker 1>Speaking of which, hang on a second. Let me move

0:26:00.060 --> 0:26:04.600
<v Speaker 1>that over there. Okay. Now we're ready. Uh, Here's a headline.

0:26:04.740 --> 0:26:05.359
<v Speaker 1>Wall Street Journal.

0:26:05.420 --> 0:26:07.240
<v Speaker 4>College athletes used to live in dorms.

0:26:07.340 --> 0:26:10.640
<v Speaker 1>Now they're buying million-dollar homes. Oh, yeah. Arch Manning.

0:26:11.090 --> 0:26:13.910
<v Speaker 2>Activate Manning mode. He looked like Eli in both Super

0:26:13.930 --> 0:26:15.510
<v Speaker 2>Bowls is what he looked like.

0:26:15.770 --> 0:26:19.930
<v Speaker 1>But he makes $ 7 million a year?

0:26:19.950 --> 0:26:23.629
<v Speaker 2>I think is the latest total. That was before he

0:26:23.650 --> 0:26:27.380
<v Speaker 2>won the other night. It's probably more now. $ 7 million

0:26:27.600 --> 0:26:29.720
<v Speaker 2>a year as a college student.

0:26:30.460 --> 0:26:32.940
<v Speaker 4>What does he work at the local college burrito shop

0:26:33.060 --> 0:26:34.220
<v Speaker 4>after his homework is done?

0:26:34.280 --> 0:26:35.460
<v Speaker 1>Jack, I don't understand.

0:26:35.540 --> 0:26:36.419
<v Speaker 2>That is funny.

0:26:36.940 --> 0:26:39.100
<v Speaker 4>Yeah, they profile all these college football players who are

0:26:39.160 --> 0:26:44.310
<v Speaker 4>literally buying million-dollar houses to live in while they play

0:26:44.470 --> 0:26:48.490
<v Speaker 4>quote-unquote college football, whatever that is these days. But I

0:26:48.510 --> 0:26:51.810
<v Speaker 4>really wanted to talk about pros and taxes, pro football players.

0:26:51.890 --> 0:26:52.810
<v Speaker 2>Well, they're all pro.

0:26:52.630 --> 0:26:53.729
<v Speaker 1>Football players, Joseph.

0:26:54.130 --> 0:26:57.320
<v Speaker 4>You're screaming at your radio slash radio. listening device, and

0:26:57.340 --> 0:26:59.199
<v Speaker 4>you're right. But first a word from our friends at

0:26:59.240 --> 0:27:03.230
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0:27:04.090 --> 0:27:08.270
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0:27:08.290 --> 0:27:11.609
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0:27:11.650 --> 0:27:14.419
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0:27:14.510 --> 0:27:15.760
<v Speaker 4>somebody broke into your house.

0:27:16.170 --> 0:27:19.520
<v Speaker 2>Yeah, traditional security systems alert you after a break-in is

0:27:19.580 --> 0:27:22.840
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0:27:22.880 --> 0:27:27.400
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0:27:27.440 --> 0:27:32.310
<v Speaker 2>at the perimeter, alert live U.S.-based agents. It's so good, SimpliSafe.

0:27:32.650 --> 0:27:34.810
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0:27:34.850 --> 0:27:36.590
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0:27:37.190 --> 0:27:39.080
<v Speaker 4>Yeah, and some of these other systems, they, like, send

0:27:39.119 --> 0:27:41.800
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0:27:41.820 --> 0:27:43.340
<v Speaker 4>with a hammer. You're in the shower.

0:27:43.380 --> 0:27:44.840
<v Speaker 1>You're in a meeting. You're on a plane. You're not

0:27:44.859 --> 0:27:45.940
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0:27:46.240 --> 0:27:49.080
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0:27:49.119 --> 0:27:53.320
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0:27:53.340 --> 0:27:55.060
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0:27:56.200 --> 0:28:01.629
<v Speaker 4>Save 60% off at simplisafe.com slash Armstrong. I'm sorry, 60%

0:28:01.630 --> 0:28:03.770
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0:28:03.990 --> 0:28:07.090
<v Speaker 1>There's no safe like SimpliSafe. All right, so. Thought this

0:28:07.130 --> 0:28:08.660
<v Speaker 1>was interesting. Also in the Wall Street Journal.

0:28:11.000 --> 0:28:13.500
<v Speaker 4>Democrats from Wisconsin and Maine are promising to raise taxes

0:28:13.560 --> 0:28:18.950
<v Speaker 4>not only on billionaires. Also, high earners, including professional athletes,

0:28:19.410 --> 0:28:22.690
<v Speaker 4>and don't think the athletes and their agents aren't aware.

0:28:23.190 --> 0:28:27.050
<v Speaker 4>There's now even an online jock tax calculator they can consult.

0:28:27.510 --> 0:28:30.520
<v Speaker 4>And they go into a bunch of different examples of

0:28:30.650 --> 0:28:33.900
<v Speaker 4>paying state and local income taxes. Because even when you're

0:28:33.920 --> 0:28:36.740
<v Speaker 4>on the road, you have to pay taxes. If you see,

0:28:36.760 --> 0:28:39.580
<v Speaker 4>I don't know, in football, say you're with the Chiefs,

0:28:39.720 --> 0:28:41.620
<v Speaker 4>and you see, oh my God, we play the.

0:28:42.220 --> 0:28:45.560
<v Speaker 1>49ers and the Rams in football. In California, you're going

0:28:45.580 --> 0:28:45.840
<v Speaker 1>to have a.

0:28:45.960 --> 0:28:50.050
<v Speaker 4>Huge income tax bill in California for the money you earn.

0:28:50.070 --> 0:28:52.230
<v Speaker 1>Really? That's the way it works?

0:28:52.230 --> 0:28:52.950
<v Speaker 2>100%.

0:28:52.950 --> 0:28:54.070
<v Speaker 1>Yeah.

0:28:54.170 --> 0:28:56.510
<v Speaker 4>My good old buddy, Brian, the umpire, he had to

0:28:56.550 --> 0:28:59.330
<v Speaker 4>file in like 25 different states every year.

0:28:59.370 --> 0:29:00.010
<v Speaker 1>Why is that?

0:29:00.030 --> 0:29:03.340
<v Speaker 2>For regular people, you travel for business. You go to

0:29:03.380 --> 0:29:05.980
<v Speaker 2>New York and close a deal, but you're from Ohio.

0:29:06.020 --> 0:29:06.660
<v Speaker 2>You don't pay taxes.

0:29:08.420 --> 0:29:11.850
<v Speaker 4>I guess you don't have enough money to twist the

0:29:11.890 --> 0:29:17.990
<v Speaker 4>law to drain you, unlike athletes. Baltimore Ravens quarterback Lamar Jackson,

0:29:18.450 --> 0:29:20.950
<v Speaker 4>and these guys earn ungodly amounts of money, but keep

0:29:20.990 --> 0:29:26.140
<v Speaker 4>in mind their careers are very, very short, usually. He

0:29:26.240 --> 0:29:29.240
<v Speaker 4>earns about $ 51 million. I know your heart's not going

0:29:29.260 --> 0:29:31.560
<v Speaker 4>to bleed for him. My career could be quite short.

0:29:32.160 --> 0:29:34.360
<v Speaker 1>I'll work one year. Yeah, exactly.

0:29:34.580 --> 0:29:34.660
<v Speaker 6>Out.

0:29:35.280 --> 0:29:37.010
<v Speaker 4>Giving him a total liability of $ 24 million in taxes,

0:29:37.030 --> 0:29:44.400
<v Speaker 4>including $ 5 million. in state and local taxes in Baltimore, Maryland.

0:29:45.500 --> 0:29:48.240
<v Speaker 4>At least he's not playing in California for the LA Rams,

0:29:48.280 --> 0:29:49.740
<v Speaker 4>where the state and local take would be $ 6.

0:29:49.640 --> 0:29:49.920
<v Speaker 1>8 million.

0:29:51.910 --> 0:29:56.190
<v Speaker 4>But in zero-income tax Tennessee, he'd only owe $ 257, 000 in

0:29:56.350 --> 0:30:00.710
<v Speaker 4>state and local taxes on those earnings. All of that

0:30:00.800 --> 0:30:01.560
<v Speaker 4>for away games.

0:30:02.060 --> 0:30:02.450
<v Speaker 1>Wow.

0:30:02.540 --> 0:30:06.100
<v Speaker 2>So you're signing a pro contract. You have to factor

0:30:06.160 --> 0:30:08.300
<v Speaker 2>that in. That's like our old friend Steven Moskowitz, always

0:30:08.660 --> 0:30:11.260
<v Speaker 2>working the tax angle on everything. And people don't spend

0:30:11.300 --> 0:30:15.240
<v Speaker 2>enough time thinking about the tax implications of things. So

0:30:15.280 --> 0:30:18.220
<v Speaker 2>you sign with the Rams, same amount of money versus

0:30:18.300 --> 0:30:20.540
<v Speaker 2>being in Arizona or Tennessee or whatever.

0:30:21.000 --> 0:30:23.580
<v Speaker 1>That's a $ 6 million difference. That's crazy.

0:30:24.380 --> 0:30:26.400
<v Speaker 4>So even if players jet in and out, those tax

0:30:26.440 --> 0:30:29.200
<v Speaker 4>bills from other states can be surprisingly big. KC Chiefs

0:30:29.240 --> 0:30:32.820
<v Speaker 4>defensive tackle Chris Jones earns about $ 35 million. According to

0:30:32.880 --> 0:30:35.960
<v Speaker 4>this expert they consult, a three-day trip to L.A. for

0:30:36.000 --> 0:30:41.360
<v Speaker 4>a Rams game means owing California about $ 82, 000. Even after

0:30:41.400 --> 0:30:44.350
<v Speaker 4>getting a credit from Missouri, the player would be left

0:30:44.420 --> 0:30:47.230
<v Speaker 4>paying more than $ 50, 000 for the privilege of taking the

0:30:47.270 --> 0:30:51.810
<v Speaker 4>field in the Golden State. San Francisco 49ers quarterback Brock Purdy,

0:30:51.970 --> 0:30:56.780
<v Speaker 4>my man, will owe $ 6. 2 million in state and local

0:30:56.860 --> 0:31:00.180
<v Speaker 4>income taxes, according to the calculator. The figure for Dallas

0:31:00.200 --> 0:31:03.090
<v Speaker 4>Cowboys quarterback Dak Prescott isn't $ 6.

0:31:02.890 --> 0:31:03.350
<v Speaker 1>2 million.

0:31:03.370 --> 0:31:03.670
<v Speaker 6>It's $ 365, 000. Wow.

0:31:07.660 --> 0:31:11.470
<v Speaker 4>While Texas doesn't tax personal income, when Mr. Prescott plays

0:31:11.790 --> 0:31:15.010
<v Speaker 4>the New York Giants in New Jersey, it would cost

0:31:15.050 --> 0:31:18.880
<v Speaker 4>him something like $ 75, 000 in taxes to Trenton the Cavalier.

0:31:18.900 --> 0:31:21.440
<v Speaker 2>Does that have anything to do with why Arch Manning

0:31:21.600 --> 0:31:22.940
<v Speaker 2>is playing in Texas?

0:31:24.130 --> 0:31:27.050
<v Speaker 1>For the Longhorns. Oh, yeah. Oh, yeah. Yeah. Of course

0:31:27.090 --> 0:31:27.650
<v Speaker 1>it does. Yeah.

0:31:28.110 --> 0:31:30.950
<v Speaker 4>And Washington deserves a special mention as a state going

0:31:30.990 --> 0:31:35.390
<v Speaker 4>in the wrong policy direction. Seahawks fans, Jackson, Smith, and Jigba,

0:31:35.430 --> 0:31:39.060
<v Speaker 4>the star wide receiver for the Seahawks, who's amazing, play

0:31:39.080 --> 0:31:42.080
<v Speaker 4>there since 2023, benefited from the state's lack of income tax.

0:31:42.300 --> 0:31:45.160
<v Speaker 4>But Democrats floated the state constitution or flouted the state

0:31:45.180 --> 0:31:47.460
<v Speaker 4>constitution this year to enact an income tax rate of 9.9%

0:31:47.460 --> 0:31:52.150
<v Speaker 4>on income over a million dollars this effective in 2028

0:31:52.150 --> 0:31:53.110
<v Speaker 4>being a challenge in court.

0:31:53.150 --> 0:31:56.610
<v Speaker 1>But anyway, perhaps Mr. Smith and Jigba should ask to

0:31:56.650 --> 0:31:57.550
<v Speaker 1>be traded.

0:31:59.270 --> 0:32:02.270
<v Speaker 2>That's going to become a problem for various teams.

0:32:03.090 --> 0:32:06.090
<v Speaker 4>You remember there was an article a couple of years ago,

0:32:06.150 --> 0:32:09.630
<v Speaker 4>back when the San Francisco Giants first started to suck

0:32:09.820 --> 0:32:13.020
<v Speaker 4>after being world beaters and World Series champions every other

0:32:13.060 --> 0:32:13.780
<v Speaker 4>year for several years.

0:32:14.040 --> 0:32:14.660
<v Speaker 1>Boy, was that fun.

0:32:14.900 --> 0:32:18.460
<v Speaker 4>Anyway, about how they were having a hell of a

0:32:18.480 --> 0:32:23.590
<v Speaker 4>time attracting free agents because of California's tax environment. One

0:32:23.610 --> 0:32:25.520
<v Speaker 4>more thing to think about as you watch the games unfold.

0:32:26.910 --> 0:32:29.430
<v Speaker 2>Are you aware of the cat in the hat trend?

0:32:29.470 --> 0:32:31.890
<v Speaker 2>Remember when it was clowns at the edge of the woods?

0:32:32.390 --> 0:32:33.860
<v Speaker 1>Oh, terrifying days, Jack.

0:32:35.640 --> 0:32:37.580
<v Speaker 2>This cat in the hat thing, which there is some

0:32:37.780 --> 0:32:40.440
<v Speaker 2>real scary stuff happening, but it's still kind of a

0:32:40.500 --> 0:32:43.040
<v Speaker 2>weird online thing. We can tell you about that in

0:32:43.080 --> 0:32:45.360
<v Speaker 2>case you get a letter from your school so you

0:32:45.380 --> 0:32:47.720
<v Speaker 2>know what they're talking about. And other stuff on the way.

0:32:47.810 --> 0:32:48.170
<v Speaker 1>Stay here.

0:32:49.590 --> 0:32:50.630
<v Speaker 4>Armstrong and Getty.

0:32:52.890 --> 0:32:57.690
<v Speaker 7>One of the two officers shot down over Iran. Neither

0:32:57.790 --> 0:33:00.230
<v Speaker 7>has spoken publicly until now.

0:33:00.870 --> 0:33:03.690
<v Speaker 6>I think the best way I've been able to describe

0:33:03.790 --> 0:33:07.050
<v Speaker 6>that moment was getting hit by a freight train.

0:33:07.670 --> 0:33:10.810
<v Speaker 2>So 60 Minutes came back last night, first time back

0:33:10.850 --> 0:33:14.230
<v Speaker 2>this season under the new directorship of Barry Weiss.

0:33:14.560 --> 0:33:18.840
<v Speaker 4>Shocking right-wing fascist turn. They prayed to Donald Trump to

0:33:18.880 --> 0:33:20.080
<v Speaker 4>begin the telecast.

0:33:21.330 --> 0:33:23.770
<v Speaker 2>It was kind of classic 60 Minutes. Really, it was

0:33:23.830 --> 0:33:29.110
<v Speaker 2>a very dramatic tale about the pilot who got shot

0:33:29.150 --> 0:33:31.900
<v Speaker 2>down in Iran and rescued and went through that whole story.

0:33:32.440 --> 0:33:34.240
<v Speaker 2>Then they had a good political story, which I thought

0:33:34.280 --> 0:33:37.200
<v Speaker 2>was pretty balanced, in which they criticized Trump and Democrats

0:33:37.260 --> 0:33:40.750
<v Speaker 2>for the whole out-of-control pardon situation we've got with our

0:33:40.790 --> 0:33:45.550
<v Speaker 2>presidential pardons. And then they did a sports segment. It

0:33:45.590 --> 0:33:49.160
<v Speaker 2>was kind of classic. Sixty minutes, I thought. Anyway, back

0:33:49.200 --> 0:33:51.200
<v Speaker 2>to the story from last night, their lead story. Here's

0:33:51.240 --> 0:33:55.280
<v Speaker 2>a little more from that guy we rescued when he

0:33:55.320 --> 0:33:56.420
<v Speaker 2>got shot down over Iran.

0:33:56.880 --> 0:34:00.170
<v Speaker 7>We've agreed to call the weapons systems officer by his

0:34:00.210 --> 0:34:04.090
<v Speaker 7>mission call sign, Bravo, due to security threats from Iran.

0:34:04.930 --> 0:34:08.010
<v Speaker 6>We do all we can to try to save the aircraft.

0:34:08.690 --> 0:34:12.870
<v Speaker 6>It was evident that that wasn't possible. And soon thereafter,

0:34:13.110 --> 0:34:17.670
<v Speaker 6>we ejected and found ourselves floating over the heart of Iran.

0:34:18.270 --> 0:34:21.270
<v Speaker 1>So within seconds, you're ejecting. That's how quick the decision is.

0:34:21.610 --> 0:34:24.850
<v Speaker 6>It is. I will be thankful to my dying day

0:34:25.110 --> 0:34:29.770
<v Speaker 6>for my pilot and crewmate, Alpha, for saving our lives

0:34:30.030 --> 0:34:31.020
<v Speaker 6>and ejecting us.

0:34:31.719 --> 0:34:33.100
<v Speaker 2>Yeah, if you didn't see that, you ought to watch

0:34:33.140 --> 0:34:33.620
<v Speaker 2>at least that.

0:34:33.660 --> 0:34:34.260
<v Speaker 1>It's online.

0:34:34.360 --> 0:34:36.840
<v Speaker 2>It has a heck of a story.

0:34:37.300 --> 0:34:40.379
<v Speaker 4>Well, a guy's parachute was messed up, and he, well,

0:34:40.440 --> 0:34:42.950
<v Speaker 4>experts estimate he hit the ground at something like 70

0:34:42.950 --> 0:34:47.129
<v Speaker 4>to 100 miles per hour and broke bones, sprained, all

0:34:47.230 --> 0:34:49.650
<v Speaker 4>cut up and bleeding. And, oh, my God, the fact

0:34:49.670 --> 0:34:51.480
<v Speaker 4>that he survived and we were able to rescue him.

0:34:51.930 --> 0:34:54.790
<v Speaker 4>You know, he thanked God and attributed a lot of

0:34:54.870 --> 0:34:56.270
<v Speaker 4>it to the Lord Almighty.

0:34:56.330 --> 0:34:58.710
<v Speaker 1>I can't disagree with him. It was fantastic.

0:34:58.950 --> 0:35:01.529
<v Speaker 2>Right, and then the rescue mission, which was just the

0:35:01.570 --> 0:35:04.509
<v Speaker 2>United States doing what we're able to do because of

0:35:04.650 --> 0:35:09.110
<v Speaker 2>our amazing technology and training and all that sort of stuff,

0:35:09.200 --> 0:35:10.980
<v Speaker 2>and the fact that we rescue people as opposed to

0:35:11.000 --> 0:35:13.500
<v Speaker 2>just let them die. It's quite the story also.

0:35:14.000 --> 0:35:17.560
<v Speaker 4>Yeah, discipline and compassion. It was really an amazing moment

0:35:18.340 --> 0:35:19.360
<v Speaker 4>by the American military.

0:35:19.400 --> 0:35:20.060
<v Speaker 1>Well done, guys.

0:35:20.640 --> 0:35:22.460
<v Speaker 2>So how did this whole cat in the hat thing

0:35:22.880 --> 0:35:23.360
<v Speaker 2>get going?

0:35:24.000 --> 0:35:27.180
<v Speaker 1>See, I've never even, I'm completely unaware of this.

0:35:27.520 --> 0:35:30.250
<v Speaker 2>It's a social media phenomenon. Some of the pictures are

0:35:31.350 --> 0:35:37.049
<v Speaker 2>hella frightening. Started around June, July of this year as

0:35:37.090 --> 0:35:40.359
<v Speaker 2>a dark humor meme. People taking clips of Mike Myers

0:35:40.510 --> 0:35:43.879
<v Speaker 2>from the 2003 Cat in the Hat movie and then

0:35:43.940 --> 0:35:47.020
<v Speaker 2>putting eerie music to them and disturbing captions and that

0:35:47.080 --> 0:35:52.170
<v Speaker 2>sort of stuff. Then, last month, it mutated into an

0:35:52.510 --> 0:35:58.049
<v Speaker 2>AI horror hoax trend. People started generating grainy surveillance camera-looking

0:35:58.090 --> 0:36:00.770
<v Speaker 2>images and videos showing a cat in a hat in

0:36:00.810 --> 0:36:02.790
<v Speaker 2>a neighborhood and stuff like that, or people dressing up

0:36:02.910 --> 0:36:04.080
<v Speaker 2>like it and then posting it.

0:36:04.530 --> 0:36:06.330
<v Speaker 1>This is so The Clown at the Edge of the Woods.

0:36:06.370 --> 0:36:08.210
<v Speaker 2>It's very similar to The Clown at the Edge of

0:36:08.230 --> 0:36:10.850
<v Speaker 2>the Woods. Things like, he's been spotted in, and it's,

0:36:10.890 --> 0:36:13.259
<v Speaker 2>you know, to your town, and you got the grainy

0:36:13.280 --> 0:36:15.180
<v Speaker 2>image of the cat in the hat sitting on top

0:36:15.219 --> 0:36:18.040
<v Speaker 2>of your car in the driveway or whatever. Which looks

0:36:18.120 --> 0:36:19.460
<v Speaker 2>freaking creepy, I'll tell you that.

0:36:20.940 --> 0:36:23.049
<v Speaker 1>You know what I got to get started? A woodsman

0:36:23.250 --> 0:36:24.430
<v Speaker 1>at the edge of the circus.

0:36:25.250 --> 0:36:28.350
<v Speaker 4>Instead of a guy with an axe.

0:36:28.770 --> 0:36:30.029
<v Speaker 1>Yeah, just thinking out loud.

0:36:30.430 --> 0:36:34.430
<v Speaker 2>Kids have begun making localized versions naming actual schools, towns,

0:36:34.489 --> 0:36:39.120
<v Speaker 2>and sometimes individual students online with captions such as I'm

0:36:39.260 --> 0:36:42.920
<v Speaker 2>coming that has caused schools to increase security and police

0:36:42.960 --> 0:36:46.299
<v Speaker 2>to investigate the accounts because they can't assume that this

0:36:46.360 --> 0:36:48.940
<v Speaker 2>is all a joke. And now there have been juvenile

0:36:48.980 --> 0:36:52.000
<v Speaker 2>arrests in several states, including California, connected to the Cat

0:36:52.040 --> 0:36:55.830
<v Speaker 2>in the Hat posts. A 14-year-old was arrested in Colorado

0:36:56.030 --> 0:36:58.029
<v Speaker 2>after suggesting he was going to hurt some other kid

0:36:58.070 --> 0:37:00.410
<v Speaker 2>or whatever. So if you hear anything about the Cat

0:37:00.430 --> 0:37:01.330
<v Speaker 2>in the Hat trend, that's.

0:37:01.190 --> 0:37:04.050
<v Speaker 1>What's going on. Unplug the Internet.

0:37:08.400 --> 0:37:11.540
<v Speaker 2>Don't you have kids? You need more homework. Give them

0:37:11.600 --> 0:37:13.700
<v Speaker 2>more homework to do so they don't have time for

0:37:13.719 --> 0:37:14.410
<v Speaker 2>this nonsense.

0:37:14.770 --> 0:37:17.149
<v Speaker 1>And a part-time job and some chores. Have them rake

0:37:17.170 --> 0:37:19.169
<v Speaker 1>the leaves. We don't have any leaves. Have them rake

0:37:19.190 --> 0:37:20.009
<v Speaker 1>the dirt.

0:37:20.030 --> 0:37:22.270
<v Speaker 2>Part-time job would help a lot. If you missed the segment,

0:37:22.290 --> 0:37:23.739
<v Speaker 2>get the podcast. We've got a lot more coming in

0:37:23.760 --> 0:37:24.200
<v Speaker 2>hour three.

0:37:24.520 --> 0:37:25.620
<v Speaker 1>Armstrong and Getty.