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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 2: and we are so excited about what that means for

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Speaker 2: the future of this show.

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Speaker 1: This is the only place where you can find honest

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Speaker 1: perspectives from the left and the right that simply does

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Speaker 1: not exist anywhere else.

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Speaker 2: So if that is something that's important to you, please

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Speaker 2: go to Breakingpoints dot com. Become a member today and

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Speaker 2: you'll get access to our full shows, unedited, ad free,

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Speaker 2: and all put together for you every morning in your inbox.

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

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Speaker 1: news media and we hope to see you at Breakingpoints

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Speaker 1: dot com. Good morning, everybody, Happy Tuesday. We have an

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Speaker 1: amazing show for everybody today, extra amazing. Crystal is back.

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Speaker 3: Thank you.

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Speaker 2: You guys did a great job of the show yesterday,

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Speaker 2: though I ensored it a consumer.

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Speaker 1: Yes, people seem to enjoy It's not happy.

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Speaker 2: Lots of news coming on of DC and around the world. Actually,

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Speaker 2: there's yet another plane crash, this one in Toronto that

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Speaker 2: will show you just unbelievable images. It's extraordinary. Everyone lived.

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Speaker 2: You do have two people in critical condition, so we'll

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Speaker 2: give you all of the images and the updates there

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Speaker 2: are starting to sound off about how they think about

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Speaker 2: the early days of the Trump administration.

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Speaker 3: Some interesting comments there.

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Speaker 2: Dough is just now coming for Social Security and a

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Speaker 2: weird court filing says like, oh, Elon's actually not technically

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Speaker 2: involved with Dough, She's not technically the head of dog

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Speaker 2: So a.

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Speaker 3: Lot going on there. Eric Admins.

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Speaker 2: Adams administration in New York City seems to be on

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Speaker 2: the verge of collapse. You've got four deputy mayors who

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Speaker 2: are now resigning. Some of the officials there are calling

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Speaker 2: for a meeting that could push him out of office.

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Speaker 2: This is all after that crazy deal struck with him

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Speaker 2: and Tom Homan and the Trump administration, et cetera.

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Speaker 3: So we'll give you those updates.

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Speaker 2: Massive crypto scam backed by Javier Mulay, the President of Argentina,

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Speaker 2: and one of the people who was behind that scam

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Speaker 2: really telling on himself in a long interview with Coffee Zilla.

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Speaker 2: Dave Portnoy is also involved. So a lot of pieces there.

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Speaker 2: But this is like the anatomy of a giant rug pole.

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Speaker 2: The head of the SCIU is going to join us

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Speaker 2: to talk about the lawsuits against Doges that they are

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Speaker 2: involved with. And also the Republican attacks against medicaid, and

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Speaker 2: Ali Bestucky is going to join us to break down

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Speaker 2: her view of Elon's baby mama drum.

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Speaker 1: Yeah, I'm excited for it. This is the way that

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Speaker 1: we get to horseshoe people into traditional values fellas, find

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Speaker 1: a girl, marrier and just stay with her. Otherwise you're

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Speaker 1: going to end up like Elon with your twenty something

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Speaker 1: year younger baby mama tweeting why have you not responded

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Speaker 1: to me? So there's a lot of good stuff that's

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Speaker 1: happening there. Should we get to the plane? What do

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Speaker 1: we got?

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Speaker 3: Yeah, let's go ahead and get to that.

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Speaker 2: So this was a Delta flight into Toronto and crash

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Speaker 2: landed there, completely flipped over. There's unbelievable images coming out.

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Speaker 2: We can put this up on the screen. You know,

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Speaker 2: we're just getting preliminary indications of what may have happened here.

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Speaker 2: But here you see this plane landing. Everything looks normal.

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Speaker 2: It's a very snowy, wintery day in Canada there. But

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Speaker 2: then upon landing, it looks like one of the wings

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Speaker 2: strikes the ground. It causes the plane to burst into flames.

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Speaker 2: It ultimately flips over, and we did get some images

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Speaker 2: also from the passengers coming off of that plane where

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Speaker 2: the thing is completely upside down as they're trying to

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Speaker 2: climb out. As I said before, only two people in

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Speaker 2: critical condition, there were a number of injuries.

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Speaker 3: Here.

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Speaker 2: You can see them being helped off of this upside

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Speaker 2: down plane as the fireworkers are you know, the firefighters

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Speaker 2: are trying to douse the flames as well as this

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Speaker 2: entire thing is catching fire as well. And then you

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Speaker 2: had some passenger images coming out too as they're trying

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Speaker 2: to scrabble.

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Speaker 3: I mean, I guess here you could.

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Speaker 2: The plane is completely upside down, so they're climbing out

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Speaker 2: here on the roof and rescuers helping them there onto

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Speaker 2: the ground. So again we have just early indications of

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Speaker 2: perhaps some sort of a plane malfunction here, but we

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Speaker 2: don't really know. But of course this comes out in

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Speaker 2: the contact Sager of so many plane crash including the

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Speaker 2: one that happened really close to here, which was the

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Speaker 2: deadliest since what two thousand and.

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Speaker 1: Nine or something like that, Ye been almost fifteen twenty, Yeah,

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Speaker 1: almost fifteen years since you had such a deadly crash.

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Speaker 1: This one, well, there's two ways you could look at it.

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Speaker 1: One is it's terrifying, and I think we can all

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Speaker 1: sympathize with that. The other kind of incredible thing is

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Speaker 1: that a plane can literally flip upside down on a runway, looks,

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Speaker 1: catch on fire, lose its wings, and nobody died at

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Speaker 1: least now, which is incredible.

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Speaker 3: Yeah, and everybody is expected.

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Speaker 1: To everybody's expected to pull through the paramedic set. Yeah.

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Speaker 1: I mean, it's a terrifying situation, but passengers were able

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Speaker 1: to crawl out of that. It's genuinely amazing. I read.

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Speaker 1: I used to have a real fear of flying when

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Speaker 1: I was a kid. Mostly after that. Yeah, it was bad,

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Speaker 1: and especially after nin I think nine to eleven. I

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Speaker 1: was young and kind of screwed me. I was flying

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Speaker 1: all the time because my parents and I and anyway,

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Speaker 1: I remember doing a lot of early YouTube viewing in

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Speaker 1: two thousand and six about how these planes are designed

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Speaker 1: to absorb like horrible things that happened to them from

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Speaker 1: turbulence and wings strike, how you can even the plane

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Speaker 1: is designed so that even if the wings strike and

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Speaker 1: like hit each other, that they'll break properly and that

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Speaker 1: everybody in will survive. And so this is somewhat of

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Speaker 1: a estimate to that. We did have a CNN reporter

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Speaker 1: who described some of the stuff around the plane. Why

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Speaker 1: don't we take a listen, because he did a good

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Speaker 1: job breaking some of the safety stuff down.

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Speaker 4: That is the bottom of the fuselage. Now on the top,

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Speaker 4: you can also see the foam truck here and the

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Speaker 4: firefighters responding from the airport firehouse putting out the fire

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Speaker 4: which looked to be primarily on the bottom of the

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Speaker 4: fuselage of the airplane. That is where the fuel is.

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Speaker 4: That is so critical to get that fire out quickly

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Speaker 4: as you're trying to evacuate people.

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Speaker 1: So a lot happening here all at once.

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Speaker 4: Let me recue this so you can see some of

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Speaker 4: what was going on at the very front of the airplane.

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Speaker 4: You're probably familiar with this door here as we pan over.

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Speaker 4: This is the R one exit in the aviation terms.

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Speaker 4: This is what you would board on coming in and

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Speaker 4: out of a jetway. The door is fully open, the

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Speaker 4: slide is not deployed, don't need it because you're upside down.

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Speaker 4: And you can see the folks here coming out of

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Speaker 4: the airplane, which would have been completely dark and on fire.

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Speaker 4: You have to imagine the terror as folks tried to

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Speaker 4: get out of this very quickly. Everybody across the board, pilots,

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Speaker 4: flight attendants, the control tower, the crash fire rescue crews,

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Speaker 4: even the passengers did a good job. The big takeaway here,

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Speaker 4: always leave your stuff behind, especially in a crash like this,

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Speaker 4: because seconds count and meanwives.

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Speaker 1: He's right, that is the big takeaway. Leave your dumb

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Speaker 1: iPad behind. Nobody cares. Okay, no one's gonna care that

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Speaker 1: you lost your AirPod pros or something in the back obviously,

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Speaker 1: although I frankly i'd be the guy. Yeah they are.

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Speaker 1: I've got like four pairs of headphones. I'm constantly losing

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Speaker 1: them and be scrounging around.

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Speaker 3: You can't replace that.

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Speaker 1: That's see, that's that's fair. Actually, I hadn't thought about that.

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Speaker 1: Let's put this up there on the screen the next

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Speaker 1: part here. This has been being passed around, and this

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Speaker 1: does go to show you some of the dangers of

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Speaker 1: what this will look like in the future. I'm not

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Speaker 1: blaming this on FAA firings. This happened in Canada, so

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Speaker 1: let's all remember that. This just what I've been trying

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Speaker 1: to highlight is that if you are not careful around

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Speaker 1: things with dose you will eventually could have a situation

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Speaker 1: like this happened in America and then you have a

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Speaker 1: full on domestic political crisis on your hands. So that's

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Speaker 1: obviously been one that's passed around here. But obviously this

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Speaker 1: happened on Canadian soil. It's actually Canadian company Bombaedier that

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Speaker 1: makes those CRJ regional jets. It was a flight coming

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Speaker 1: from Minneapolis Saint Paul to Toronto. Not that many passengers

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Speaker 1: on board, luckily, but you know, it's still scary. I mean,

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Speaker 1: I can't tell you how many times a phone on

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Speaker 1: those regional jets, the CRJs. So the question is what happened.

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Speaker 1: Nobody knows yet, no indication yet of mechanical function. Obviously

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Speaker 1: was very snowing on the ground, but what Toronto Airport

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Speaker 1: doesn't know how to handle snow's or Minneapolis Saint Paul

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Speaker 1: has never flown into cold conditions. I've landed in Minneapolis

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Speaker 1: with like twenty inches of snow on the ground and

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Speaker 1: where they spray you with all that de icing stuff.

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Speaker 1: So there's just procedures that are that are in place

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Speaker 1: here and we do expect when you get on a plane,

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Speaker 1: no matter what type of safe conditions, that they clear

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Speaker 1: you for takeoff and landing, that you're gonna make it,

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Speaker 1: otherwise you should cancel the flight. So there's still a

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Speaker 1: lot of questions here around what's happening with that. But yeah, honestly,

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Speaker 1: just really happy that all the passengers made it out.

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Speaker 1: Still just terrifying situation. Oh absolutely, yes.

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Speaker 2: It's crazy to me that they thought they were Like,

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Speaker 2: I mean, the flight appeared to be.

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Speaker 1: Totally normal, right and then right there at the.

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Speaker 2: Runway and then suddenly you're upside down, like, holy hell,

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Speaker 2: what just happened? So, I mean a new new terror

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Speaker 2: unlocked for me in terms of air dravel. And I

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Speaker 2: mean that is the big thing is so many plane crashes,

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Speaker 2: so many issues recently. I think you are going to

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Speaker 2: start to spook a significant portion of the public that

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Speaker 2: may have thought nothing. I mean I put myself in

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Speaker 2: this category. I would have thought nothing of getting onto

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Speaker 2: an airplane out it's safe, it's fine, These things never crash.

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Speaker 2: Now I have different thoughts in my head. And you know, again,

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Speaker 2: this doesn't have to do with the FAA firings. It

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Speaker 2: happened in Toronto, but it is crazy that the response

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Speaker 2: to the deadliest commercial airline crash in the US since

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Speaker 2: in you know, over a decade, was to fire a

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Speaker 2: bunch of FAA personnel. And the point that Stoller has

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Speaker 2: been making, I think Ryan's been making as well, is

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Speaker 2: like they have set themselves up to be like legitimately

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Speaker 2: blamed for everything bad that happens in this country that

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Speaker 2: the federal government touches whatsoever from here on out. And

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Speaker 2: so it does outline.

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Speaker 1: Some of the risks. As you said, Zager, it's a warning.

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Speaker 2: Let's go ahead and get to these focus grips and

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Speaker 2: what voters have to say.

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Speaker 1: Yes, that's right. So there's been some indication here about

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Speaker 1: how are Americans feeling about Donald Trump. We can't yet

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Speaker 1: exactly get a real sample of everybody pulls itself can

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Speaker 1: be somewhat unreliable, but in general it's always good let's

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Speaker 1: check in on how people are feeling. So the New

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Speaker 1: York Times put together a focused group six Americans across

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Speaker 1: the spectrum and ask them how they are feeling about

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Speaker 1: the first Trump administration. So why don't we go ahead

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Speaker 1: and we put that up on the screen. So here

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Speaker 1: are six Americans on what they think of Trump, elon Musk,

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Speaker 1: and of Gaza. So why don't we start our slideshow

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Speaker 1: which has some select quotes from each of these individual Americans.

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Speaker 1: Here you have Tally Jack and I hope I pronounced

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Speaker 1: that correctly. She says, sometimes you don't know who is talking.

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Speaker 1: It feels like a tantrum of a four year old boy.

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Speaker 1: The second one here is Hummied Chowdry from Reading Pennsylvania.

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Speaker 1: This is exactly what I expected that unexpected things would happen.

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Speaker 1: Let's go to the next one. It says, mister Musk

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Speaker 1: seemed like a guy who was almost directly in control

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Speaker 1: of the White House. This is mister Dave Abdullah of

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Speaker 1: Dearborn Heights, Michigan.

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Speaker 3: He was a third party voter.

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Speaker 1: That's right, third party voter, along with many other people

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Speaker 1: in Dearborn, Michigan. Here is mister Jime Escobar Junior from Roma,

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Speaker 1: Texas with Trump it just seems to be like boom boom,

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Speaker 1: boom boom. Very apt description. There next one mister Isaiah Thompson,

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Speaker 1: twenty two years old from Washington, d C. He says,

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Speaker 1: right now, everything just seems so much in the air.

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Speaker 1: He's a college student paying attention to this. And then

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Speaker 1: we have a mister Perry Hunter from Sellersburg, Indiana. When

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Speaker 1: someone's trying to cut spending, which is going to help

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Speaker 1: me in the long run, I take him at face value.

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Speaker 1: So you have some interesting takes there from across the spectrum,

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Speaker 1: and it is both important for class dynamics, workplace dynamics,

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Speaker 1: and also I can't hammer this home enough news. Remember

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Speaker 1: that statistic about the more tapped in that you are,

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Speaker 1: the more likely that you voted for Kamala Harris, which

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Speaker 1: is just kind of amazing. But there's also a real

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Speaker 1: refresh element. I think to a lot of liberal activism

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Speaker 1: and others, these people are horse statistically way more likely

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Speaker 1: to read the news anyways. And so that whole feeling

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Speaker 1: of people being in control, or of things being out

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Speaker 1: of control, or things moving in a very very fast

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Speaker 1: paced direction leading to some anxiety, doesn't This definitely comes

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Speaker 1: through this and through some Wall Street journal stuff that

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Speaker 1: we're all about to show you. But I'm not ready

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Speaker 1: to make any broad determines yet. Determinations.

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Speaker 2: Yeah, it's interesting to hear from actual voters. You're the

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Speaker 2: first lady you put up there who said the thing

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Speaker 2: about like seems like a tantrum of a four year

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Speaker 2: old boy. One of the things she said that was

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Speaker 2: kind of interesting. And this is a lady who was

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Speaker 2: traditionally more liberal, more of a Democratic voter, did vote

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Speaker 2: for Trump. Kind of easy about that vote, not super

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Speaker 2: happy with what she's seen so far. But part of

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Speaker 2: what was interesting to me is she said, even though

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Speaker 2: she's not like super psyched about what she's saying, she's like,

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Speaker 2: I have a metric in my head of how long

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Speaker 2: a period of grace I'm going to give him. She's like,

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Speaker 2: he gets quote one hundred days of charity. And I

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Speaker 2: do think that there is that instinct among a lot

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Speaker 2: of the American public of like, well, let's give him.

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Speaker 2: He just got in there, Like, let's give him some

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Speaker 2: time and see how this all shakes out. So, you know,

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Speaker 2: it's indicative of the fact that in a certain sense,

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Speaker 2: he's still in that quote honeymoon phase where presidents typically have,

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Speaker 2: you know, relatively high approval rating. For Trump, he's continued

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Speaker 2: to have for him the highest, some of the highest

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Speaker 2: approval ratings.

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Speaker 1: Of his career. There no question, and that's an important

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Speaker 1: point is don't forget Joe Biden's presidency did not officially

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Speaker 1: sour until October of twenty twenty one. It took nine

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Speaker 1: straight months. We go back to the Bush administration, it

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Speaker 1: wasn't as long, but it took several months to get there.

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Speaker 1: With the privatization of Social Security plus Iraq going down

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Speaker 1: the hill, Trump really the only existential threat that he

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Speaker 1: has to his presidency right because inflation in the economy

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Speaker 1: is much more of a slow burn. In my opinion,

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Speaker 1: I think it's one of those that nobody's going to

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Speaker 1: flip on a dime absence some sort of massive financial crisis.

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Speaker 1: And the biggest existential threat to his presidency is foreign affairs.

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Speaker 1: That's what's nuked Joe Biden, and because of the uncertainty

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Speaker 1: that we currently have with Israel and with Gaza and

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Speaker 1: his current plan to literally occupy Gaza, I think that's

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Speaker 1: one where you could quite literally turn on a dime.

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Speaker 1: The rest of it, I think it's going to be

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Speaker 1: much slower, although my caution around those is that if

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Speaker 1: there is some cut to a government and then there's

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Speaker 1: some horrible economic or financial or natural disaster and something

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Speaker 1: is not seem to be functioning properly, than that actually

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Speaker 1: also could come back to bite you. Let's put some

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Speaker 1: of the Wall Street Journal stuff up there on the

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Speaker 1: screen because this is some similar focus grip, but this

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Speaker 1: one is even more interesting because it's actually with Trump voters.

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Speaker 1: So we thought we would look at some of the

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Speaker 1: stuff here. So you have a voter here, Stacy White.

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Speaker 1: She said she voted for President Trump. She wanted lowers

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Speaker 1: and to stop fentanyl from coming in the border. She said,

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Speaker 1: when we said safer borders, I thought he was thinking

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Speaker 1: let's stop the drugs from coming in this country. I

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Speaker 1: didn't know he was going to start rating places. She said.

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Speaker 1: She didn't believe he would actually follow through on some

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Speaker 1: of the more hardline policies he started doing touted during

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Speaker 1: the campaign. Now I'm like, dang, why didn't I just

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Speaker 1: pick Kamala, said the forty nine year old Omaha, Nebraska resident,

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Speaker 1: referring to the former vice president and last Democratic nominee. Okay,

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Speaker 1: I mean, you know, stood in front of a sign

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Speaker 1: that said mass deportation. But all right, let's continue to

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Speaker 1: the next one. In terms of some of these voters here,

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Speaker 1: you have, for example, Todd why not he's a holistic

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Speaker 1: coach from Cornhill, Arizona. Corn is Cornville? All right, I

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Speaker 1: should visit I don't think they I don't think they

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Speaker 1: grow corn in Arizona.

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Speaker 3: Right.

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Speaker 1: I'm thrilled with Trump and he's done more in less

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Speaker 1: than a month than most presidents have in their whole term.

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Speaker 1: A longtime Democrat who had initially been all in on

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Speaker 1: Robert Kennedy Junior, but moved over to Trump after the

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Speaker 1: independent candidate dropped out. So you've got the hippie voter

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Speaker 1: here who Donald Trump, loving Maha, loving the confirmation, and

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Speaker 1: probably loving Doge as well. Let's go to the next one. Please,

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Speaker 1: Here you can actually see some more from You have

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Speaker 1: one resident twenty three year old La cheered on Trump's

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Speaker 1: governments cuts and deportations, saying he would support more widespread

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Speaker 1: removal of people came to the US illegally. I say

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Speaker 1: he's pretty much exceeded at expectations. Honestly, I did not

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Speaker 1: expect him to be this quick in actually making these changes.

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Speaker 1: Let's go to the next one. This one, This one

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Speaker 1: is actually honestly pretty amusing. Here you have Emily Anderson

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Speaker 1: from Duluth, who considers herself a Democrat but back Trump

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Speaker 1: after Kennedy dropped out of the race. Anderson aligned with

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Speaker 1: Kennedy's Maha agenda, particularly the focus on getting toxins out

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Speaker 1: of food, who works with disabled adults, said Kennedy's government

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Speaker 1: role is the only bright spot for a vote that

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Speaker 1: she categorizes now as the biggest mistake of my life. Honestly,

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Speaker 1: I still don't really get this one, because she said

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Speaker 1: she's horrified by deportation, alleged that Trump has been too

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Speaker 1: focused on ridiculous, flashy moves such as banning paper straws

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Speaker 1: and renaming the Gulf of Mexico. Her daughter's preoccupational therapist

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Speaker 1: has stopped taking new patients over fears that the practice

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Speaker 1: will have its funding dry up. She says, I feel

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Speaker 1: so guilty, stupid, and regretful, embarrassed and huge one. I'm

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Speaker 1: absolutely embarrassed that I voted for Donald Trump. Okay, I mean,

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Speaker 1: you know, I'm not gonna tell Emily had a feel

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Speaker 1: I guess, but you literally voted for the guy for

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Speaker 1: RFK Junior. You got what you wanted. I wouldn't say

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Speaker 1: a lot of the rest of this was not telegraphed,

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Speaker 1: but in a certain sense, you have some buyer's remorse,

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Speaker 1: you have some trepidation. You have some people who are

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Speaker 1: like this is absolutely amazing. But I think your honeymoon

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Speaker 1: comment still sticks in terms of how I think things

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Speaker 1: are still going to shake out.

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Speaker 2: It's interesting too that, you know, not across the board,

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Speaker 2: but a number of the people who are like RFK Junior,

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Speaker 2: people who came into the coalition and voted with Trump,

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Speaker 2: seem to be some of the ones that are having

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Speaker 2: some of the bigger regrets.

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Speaker 1: Yeah, but there was also that other guy who I'm.

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Speaker 2: Not saying it's across the board, but that was interesting

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Speaker 2: and it kind of it does make a kind of

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Speaker 2: sense if they're liberals, were liberal you you know, sort

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Speaker 2: of like hippie crunchy, like skeptical of medical science.

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Speaker 3: Whatever. You end up in RFKG camp.

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Speaker 2: He pulls you over to MAGA and yeah he's in

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Speaker 2: at HHS. But let's not pretend like RFK Junior is

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Speaker 2: like a big part of the show at this point.

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Speaker 2: The big part of Elon is a big part of

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Speaker 2: the show. And while on the one hand, yes, Elon

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Speaker 2: was a big part of the campaign, you know it

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Speaker 2: even myself, who was again pretty like you know, upset

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Speaker 2: about what a Trump administration could bring, did not foresee

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Speaker 2: the level of control that Elon Musk would have in

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Speaker 2: this administration. So in that way, it is very much

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Speaker 2: a break from how Trump portrayed himself. And then you know,

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Speaker 2: the other thing that was interesting to me is, you

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Speaker 2: know the lady who was like, yeah, I want the

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Speaker 2: criminals out, but I didn't know he'd be rating workplaces

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Speaker 2: and whatever.

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Speaker 1: Like.

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Speaker 2: There was an effort during the campaign, and this was

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Speaker 2: part of Trump's like gro podcast strategy to make it

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Speaker 2: seem like this guy's not a radical. Their hyperventilate about him,

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Speaker 2: He's just a normal dude. Like whatever it is that

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Speaker 2: they're trying to scare you about, it's not really real.

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Speaker 2: And so my position was always like, no, you need

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Speaker 2: to listen to what he says, like these are his plans.

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Speaker 2: Project twenty twenty five, by the way, is a real thing.

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Speaker 2: They've spent the off season getting their ducks in a

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Speaker 2: row so that they can execute on the more maximal's

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Speaker 2: plans more aggressively. So you should assume that when the

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Speaker 2: president is, you know, the former and now current president

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Speaker 2: is at the R and C with signs that say

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Speaker 2: mass deportation, now that like he literally means that, and

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Speaker 2: you should operate accordingly.

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Speaker 1: And you know, it's.

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Speaker 2: Clear that a number of people who voted for him,

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Speaker 2: didn't really take seriously the most maximalist things that he said,

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Speaker 2: and in certain ways he's gone beyond the most maximalist

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Speaker 2: things that he said, and even some of the more

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Speaker 2: maximalist positions put out in Project twenty twenty five, which

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Speaker 2: of course he lied about and pretend, loh, we have

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Speaker 2: nothing to do with that. And of course the plan's

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Speaker 2: not Project twenty twenty five, et cetera.

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Speaker 1: It wasn't the plan. It just seemed to rhyme with

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Speaker 1: the plan. Let's go and put this one up there,

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Speaker 1: the last one from one of our voters here. This

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Speaker 1: is a sixty six year old telecommunications contractor, said he

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Speaker 1: is enjoying Trump's early days, particularly focusing on addressing government waste.

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Speaker 1: Said he is quote steamrolling the government is unsustainable for

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Speaker 1: the next four years. He's doing eighty miles an hour.

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Speaker 1: I wouldn't mind if he went around fifty five. So

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Speaker 1: we're just saying slow down here a little bit, but overall,

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Speaker 1: I'm with you. I'm with you, So that seems to

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Speaker 1: be what we have. We do have here some voters

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Speaker 1: Arab Americans who voted for Donald Trump sounding off on

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Speaker 1: the Gaza plan. Let's take a listen to that.

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Speaker 5: I could not believe that the president of the United

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Speaker 5: States is altering these words. Even Trump, I did not

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Speaker 5: think that he would go this far, breaking international law

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Speaker 5: and this regard to our own laws. We do not

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Speaker 5: regard Gaza as a land that's for grab. It's Ipalacinian land.

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Speaker 5: I was very shocked and surprise.

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Speaker 6: He made a point to tell me he didn't vote

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Speaker 6: at all for any presidential candidate he usually does, because

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Speaker 6: he just didn't prefer either. I spoke with a young woman,

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Speaker 6: a college senior, who voted in her first presidential election.

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Speaker 6: She did vote for Trump, she said. When she saw

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Speaker 6: his remarks on Gaza, she gasped and was initially shocked,

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Speaker 6: but ultimately not surprised. And I said, do you regret

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Speaker 6: in any way voting for him? She said, maybe, But

434
00:20:20,040 --> 00:20:22,520
Speaker 6: if I hadn't and Kamala Harris had won, maybe we

435
00:20:22,560 --> 00:20:24,200
Speaker 6: wouldn't still have a ceasefire.

436
00:20:24,760 --> 00:20:28,440
Speaker 1: I don't know what to say. Uh, maybe she's right. Look,

437
00:20:28,520 --> 00:20:31,840
Speaker 1: I really try hard not to go blue Maga. But

438
00:20:31,960 --> 00:20:34,240
Speaker 1: what did you expect, Like, did I expect Trump to

439
00:20:34,240 --> 00:20:35,719
Speaker 1: say We're going to take over Gaza?

440
00:20:35,840 --> 00:20:35,919
Speaker 2: No?

441
00:20:36,280 --> 00:20:38,240
Speaker 1: But do you know what I did expect him to say, yeah,

442
00:20:38,280 --> 00:20:40,480
Speaker 1: it's over, the West Bank is going to be ISRAELI

443
00:20:40,600 --> 00:20:44,760
Speaker 1: like that was obviously telegraphed. I mean, I guess the

444
00:20:44,800 --> 00:20:46,680
Speaker 1: position that they made is that it couldn't be any

445
00:20:46,680 --> 00:20:49,480
Speaker 1: worse than Kamala Harris. But I mean, I gotta be honest, Like,

446
00:20:49,520 --> 00:20:51,000
Speaker 1: if that was your number one issue, I still have

447
00:20:51,080 --> 00:20:54,680
Speaker 1: no idea how you voted for Trump because Kamala. Here's

448
00:20:54,720 --> 00:20:57,760
Speaker 1: the thing again about liberals and Democrats. Their worship of

449
00:20:58,200 --> 00:21:01,120
Speaker 1: international norms and of past US policy would have been

450
00:21:01,200 --> 00:21:03,919
Speaker 1: to them that effect, because Kamala, yeah, she probably wouldn't

451
00:21:03,920 --> 00:21:06,000
Speaker 1: have gotten a ceasefire through or any of that, but

452
00:21:06,040 --> 00:21:08,520
Speaker 1: she would have been rhetorically committed to a two state

453
00:21:08,560 --> 00:21:10,840
Speaker 1: solution problem even though we all know that it's fake,

454
00:21:11,040 --> 00:21:13,680
Speaker 1: which means that the status quo would not really change

455
00:21:13,720 --> 00:21:15,760
Speaker 1: all that much. There would be de facto control, but

456
00:21:15,800 --> 00:21:18,800
Speaker 1: there's a big difference between de facto control and US

457
00:21:18,880 --> 00:21:22,480
Speaker 1: government sanctioned taking over the West banker. I mean, that

458
00:21:22,560 --> 00:21:24,919
Speaker 1: question was effectively decided the day that Donald Trump was

459
00:21:24,920 --> 00:21:27,040
Speaker 1: elected the president, and it was pretty clear if you

460
00:21:27,080 --> 00:21:31,240
Speaker 1: were really paying attention. So I don't really know what

461
00:21:31,400 --> 00:21:33,280
Speaker 1: to make of this in a sense, Like I said,

462
00:21:33,320 --> 00:21:35,560
Speaker 1: I don't love to do the whole voter blaming thing,

463
00:21:35,640 --> 00:21:37,560
Speaker 1: but if that was your number one issue, I mean,

464
00:21:37,680 --> 00:21:40,240
Speaker 1: I'm still not really clear how you got to where

465
00:21:40,240 --> 00:21:43,000
Speaker 1: you are. Maybe you could say, well, they got the

466
00:21:43,000 --> 00:21:45,040
Speaker 1: hostages out and there was a ceasefire for a period

467
00:21:45,040 --> 00:21:46,600
Speaker 1: of time, which I think is probably true. I don't

468
00:21:46,600 --> 00:21:48,720
Speaker 1: know if there'd be a ceasefire without Donald Trump here

469
00:21:48,880 --> 00:21:50,719
Speaker 1: in the office. But I mean there's still a long

470
00:21:50,760 --> 00:21:52,800
Speaker 1: way to go on that whole process, yeh, as we

471
00:21:52,800 --> 00:21:54,680
Speaker 1: talked about with Ryan Hey, yeah, very much though.

472
00:21:54,800 --> 00:21:57,440
Speaker 2: And I guess the way I always looked at it is,

473
00:21:57,760 --> 00:22:00,159
Speaker 2: you know, I have very low opinions of all of

474
00:22:00,200 --> 00:22:03,200
Speaker 2: these politicians, of Trump, of Kamala and all the rest.

475
00:22:03,600 --> 00:22:06,760
Speaker 2: I think the way to look at these individuals is

476
00:22:06,840 --> 00:22:10,320
Speaker 2: think about who's in their coalition and who they're subject

477
00:22:10,359 --> 00:22:14,600
Speaker 2: to pressure from. So with Trump, you know, the Republican

478
00:22:14,680 --> 00:22:18,639
Speaker 2: base is way more pro Israel, and his donor base,

479
00:22:18,880 --> 00:22:21,680
Speaker 2: including Mary Maddilson, who was one of his largest donors,

480
00:22:22,200 --> 00:22:26,359
Speaker 2: is very like that's her number one issue. And so

481
00:22:26,880 --> 00:22:30,360
Speaker 2: you know, on the Democratic side, most of the donors

482
00:22:30,359 --> 00:22:33,000
Speaker 2: there too are quite pro Israel. But you do have

483
00:22:33,280 --> 00:22:37,159
Speaker 2: a large percentage of the Democratic base who you know

484
00:22:37,359 --> 00:22:41,360
Speaker 2: were are at this point more sympathetic towards Palestinians, very

485
00:22:41,359 --> 00:22:45,240
Speaker 2: opposed to the ongoing war, and where you know, Donald

486
00:22:45,240 --> 00:22:47,880
Speaker 2: Trump doesn't care what some lefty on college campus has

487
00:22:47,920 --> 00:22:50,960
Speaker 2: to say. But those are part of the Democratic coalition,

488
00:22:51,040 --> 00:22:53,119
Speaker 2: So at least in theory, there's an ability to exert

489
00:22:53,119 --> 00:22:56,200
Speaker 2: some pressure on a democratic administration. I mean, listen, I'm

490
00:22:56,200 --> 00:22:58,160
Speaker 2: sympathetic to the fact that there were just no good

491
00:22:58,280 --> 00:23:01,520
Speaker 2: answers in this election. If this was your number one issue,

492
00:23:01,640 --> 00:23:03,640
Speaker 2: Very sympathetic to the gentleman who said he just didn't

493
00:23:03,680 --> 00:23:06,240
Speaker 2: vote because he couldn't stomach, you know, voting for either

494
00:23:06,280 --> 00:23:07,359
Speaker 2: one of these candidates.

495
00:23:07,520 --> 00:23:10,480
Speaker 3: But yeah, if you thought that you were going to get.

496
00:23:10,320 --> 00:23:13,280
Speaker 2: Some like humanitarian position out of Donald Trump with regard

497
00:23:13,320 --> 00:23:14,280
Speaker 2: to Palestinian it's like, I don't.

498
00:23:14,320 --> 00:23:17,080
Speaker 1: I don't really, That's what I just don't know what

499
00:23:17,119 --> 00:23:17,360
Speaker 1: to do.

500
00:23:17,600 --> 00:23:19,600
Speaker 2: I think we both were both were pretty clear about

501
00:23:19,600 --> 00:23:22,600
Speaker 2: that in our elections, even like being clear eyed about

502
00:23:22,640 --> 00:23:23,320
Speaker 2: what you were getting.

503
00:23:23,320 --> 00:23:25,159
Speaker 1: I think people can go roll the tape. I think

504
00:23:25,200 --> 00:23:27,160
Speaker 1: I did a segment about the Arab and I said, listen,

505
00:23:27,240 --> 00:23:28,920
Speaker 1: no offense. But if you're number one is issue, you

506
00:23:28,920 --> 00:23:30,600
Speaker 1: should vote for Kamala, there's no you.

507
00:23:30,560 --> 00:23:32,040
Speaker 3: Did I think you did say that.

508
00:23:32,160 --> 00:23:34,520
Speaker 1: Yeah, I mean it was pretty obvious what was going

509
00:23:34,600 --> 00:23:37,200
Speaker 1: to happen. Maybe it's because I understand, like you said,

510
00:23:37,400 --> 00:23:39,879
Speaker 1: pressures and coalition, they don't give a shit about you.

511
00:23:39,960 --> 00:23:42,879
Speaker 1: I mean, like at all, They'll use you for window dressing.

512
00:23:42,960 --> 00:23:45,639
Speaker 1: But I mean, look look at who the administration is,

513
00:23:45,880 --> 00:23:47,720
Speaker 1: Look at the promises that I mean, look at the

514
00:23:47,760 --> 00:23:51,040
Speaker 1: secret Oh who the ambassador to Israel, Mike Kabee. There

515
00:23:51,080 --> 00:23:53,800
Speaker 1: has not been a single thing on the gaza policy

516
00:23:53,880 --> 00:23:56,240
Speaker 1: outside of saying we will occupy it that has surprised

517
00:23:56,240 --> 00:23:59,320
Speaker 1: me about the Donald Trump administration. I also do want

518
00:23:59,359 --> 00:24:01,360
Speaker 1: to put this one up there a six. Let's put

519
00:24:01,359 --> 00:24:03,639
Speaker 1: this up there on the screen, and feeling pretty vindicated.

520
00:24:04,000 --> 00:24:07,159
Speaker 1: Financial although put my own cavea on this, Poles can

521
00:24:07,200 --> 00:24:09,280
Speaker 1: offer be bullshit and do not take this to the bank.

522
00:24:09,480 --> 00:24:12,359
Speaker 1: So if you're against this, you should take that into consideration.

523
00:24:12,720 --> 00:24:15,639
Speaker 1: Financial Times did a survey here majority of Americans believe

524
00:24:15,800 --> 00:24:20,479
Speaker 1: foreign aid wasted on corruption. Exclusive Pole suggests voters back

525
00:24:20,520 --> 00:24:23,680
Speaker 1: Donald Trump and Elon Musk's view of DOGE. A poll

526
00:24:23,720 --> 00:24:27,520
Speaker 1: by Financial Trust found that sixty percent of respondents agreed

527
00:24:27,560 --> 00:24:30,320
Speaker 1: that find and set aside for humanitarian causes were quote

528
00:24:30,520 --> 00:24:35,399
Speaker 1: wasted on corruption or administrative fees. Only twelve percent disagreed

529
00:24:35,640 --> 00:24:39,200
Speaker 1: with the proposition. So I mean that honestly, I feel

530
00:24:39,280 --> 00:24:41,840
Speaker 1: very vindicated because that's why I said that the starting

531
00:24:41,840 --> 00:24:46,200
Speaker 1: with USID was brilliant, because nobody cares about USAID, and

532
00:24:46,359 --> 00:24:48,320
Speaker 1: to the extent that they do, they're like, yeah, it's

533
00:24:48,320 --> 00:24:50,760
Speaker 1: fake and it's fraud. And the more that you have

534
00:24:50,880 --> 00:24:54,760
Speaker 1: now all this information coming out, plus this immedia ecosystem

535
00:24:55,040 --> 00:24:57,960
Speaker 1: around USAID and Mike Benson, all that people are gonna

536
00:24:57,960 --> 00:25:01,760
Speaker 1: be like good. I support that. Donald Trump and Elon

537
00:25:01,920 --> 00:25:04,879
Speaker 1: are still, in my opinion, not in any danger. So

538
00:25:05,359 --> 00:25:09,360
Speaker 1: everything about it is about telegraphing what might happen. It's

539
00:25:09,400 --> 00:25:11,640
Speaker 1: like fear. It's like, oh, they have access to Dad.

540
00:25:11,680 --> 00:25:15,439
Speaker 1: It's like, yeah, well, you know, unnamed bureaucrat has access

541
00:25:15,440 --> 00:25:18,000
Speaker 1: to my data too. Frankly, could be just as much

542
00:25:18,080 --> 00:25:21,520
Speaker 1: of a threat. Maybe people hate the irs, People hate

543
00:25:21,520 --> 00:25:24,520
Speaker 1: the government. Even people who have Social Security have dim

544
00:25:24,600 --> 00:25:27,120
Speaker 1: views of the actual Social Security administration, but they love

545
00:25:27,280 --> 00:25:29,880
Speaker 1: social Security as in the Texas, you know, they hate

546
00:25:29,920 --> 00:25:32,359
Speaker 1: the government and they hate they feel as if it

547
00:25:32,440 --> 00:25:36,040
Speaker 1: is completely unmoored from their own interests. So until like

548
00:25:36,320 --> 00:25:39,119
Speaker 1: millions of people get affected by something like this or

549
00:25:39,160 --> 00:25:41,560
Speaker 1: there's a natural disaster, I think it's just gonna keep

550
00:25:41,600 --> 00:25:45,680
Speaker 1: chugging along that poll. I mean, again, I really hate

551
00:25:45,680 --> 00:25:49,000
Speaker 1: to say it, but you can just see how little

552
00:25:49,040 --> 00:25:53,919
Speaker 1: trust the average American really has in these institutions and

553
00:25:53,960 --> 00:25:57,240
Speaker 1: how they feel so taken advantage of that the idea

554
00:25:57,320 --> 00:25:59,560
Speaker 1: to them. Even whenever people are like, oh, somebody in

555
00:25:59,600 --> 00:26:03,040
Speaker 1: my own didn't get their AIDS medication, they're like, okay, well,

556
00:26:03,119 --> 00:26:05,680
Speaker 1: you know, my cousin or whatever is sick and he's

557
00:26:05,680 --> 00:26:08,760
Speaker 1: paying eight hundred dollars a month for his pharmaceutical drugs.

558
00:26:08,760 --> 00:26:11,439
Speaker 1: Now you could very easily argue, okay, but you know,

559
00:26:11,600 --> 00:26:13,760
Speaker 1: it's not like Republicans want that to be cheaper. But

560
00:26:13,800 --> 00:26:15,720
Speaker 1: they don't want to hear it. They don't care. They're like, well,

561
00:26:15,840 --> 00:26:18,400
Speaker 1: it's at least this, We shouldn't at least be giving

562
00:26:18,400 --> 00:26:20,920
Speaker 1: our tax dollars away to all of that. It's a

563
00:26:20,960 --> 00:26:24,000
Speaker 1: complex system that we live in here. But I don't know,

564
00:26:24,320 --> 00:26:26,520
Speaker 1: listen and I look at this. I just that was

565
00:26:26,560 --> 00:26:28,880
Speaker 1: my ultimate suspicion. I was like, nobody gives a shit

566
00:26:28,880 --> 00:26:30,920
Speaker 1: about USAID except for the people who work there.

567
00:26:31,160 --> 00:26:33,959
Speaker 2: So I think it's very similar to you know, if

568
00:26:34,000 --> 00:26:37,280
Speaker 2: you ask people like do you want to cut government spending,

569
00:26:37,680 --> 00:26:40,360
Speaker 2: They're like yes, absolutely, yeah. You know, do you think

570
00:26:40,400 --> 00:26:44,920
Speaker 2: that foreign aid as a like lump category is corrupt

571
00:26:45,119 --> 00:26:46,639
Speaker 2: or a waste of dollars or whatever?

572
00:26:46,680 --> 00:26:48,040
Speaker 3: They're like, yes, of course.

573
00:26:48,520 --> 00:26:50,399
Speaker 2: But then you know, and I've seen the pulling on

574
00:26:50,440 --> 00:26:53,840
Speaker 2: this when you ask people specifically about like HIV treatment

575
00:26:54,040 --> 00:26:56,480
Speaker 2: for that has you know, been impactful for millions of

576
00:26:56,480 --> 00:26:57,360
Speaker 2: people in Africa?

577
00:26:57,600 --> 00:26:58,280
Speaker 3: They support it.

578
00:26:58,720 --> 00:27:01,320
Speaker 2: So do I think that is Do I think this

579
00:27:01,520 --> 00:27:04,359
Speaker 2: like a deal breaker for you know, killing Usaid?

580
00:27:04,480 --> 00:27:05,800
Speaker 3: Do I think there's a deal breaker.

581
00:27:05,560 --> 00:27:06,040
Speaker 1: For drug No.

582
00:27:06,520 --> 00:27:09,600
Speaker 2: But they've at this point gone a long way beyond

583
00:27:09,800 --> 00:27:14,440
Speaker 2: USAID number one and number two. You know, they are

584
00:27:14,880 --> 00:27:19,800
Speaker 2: right now really playing with fire in terms of both

585
00:27:20,320 --> 00:27:22,600
Speaker 2: what the actual impact of what they're.

586
00:27:22,359 --> 00:27:23,280
Speaker 3: Doing will be.

587
00:27:23,440 --> 00:27:27,919
Speaker 2: I mean, we're only you know, one horrific event like

588
00:27:28,119 --> 00:27:31,720
Speaker 2: a plane crash in the US from them being blamed

589
00:27:32,000 --> 00:27:35,320
Speaker 2: with blood like on their hands. Because of the cuts

590
00:27:35,320 --> 00:27:38,879
Speaker 2: that they've made at the FAA. You're also in a

591
00:27:39,000 --> 00:27:41,359
Speaker 2: very precarious position because you have the specter of the

592
00:27:41,440 --> 00:27:43,400
Speaker 2: richest man on the planets, all these conflicts of interest,

593
00:27:43,400 --> 00:27:46,080
Speaker 2: et cetera, et cetera. You know, a genuine, literal oligarch

594
00:27:46,359 --> 00:27:51,520
Speaker 2: who is running the show and keying up tax cuts

595
00:27:51,560 --> 00:27:56,400
Speaker 2: to Social Security, Medicaid in particular, Republicans very aggressively going

596
00:27:56,440 --> 00:27:59,119
Speaker 2: after medicaid and for what in order to finance a

597
00:27:59,160 --> 00:28:02,600
Speaker 2: giant tax code, a tax cut for the rich. You know,

598
00:28:02,760 --> 00:28:05,320
Speaker 2: this is a lot of why so many people turned

599
00:28:05,680 --> 00:28:09,800
Speaker 2: on the traditional like George W. Bush, Ronald Reagan Republican

600
00:28:09,840 --> 00:28:12,359
Speaker 2: Party and sought out a different approach with a Donald

601
00:28:12,359 --> 00:28:15,600
Speaker 2: Trump who pledged to not be that kind of Republican

602
00:28:15,640 --> 00:28:18,200
Speaker 2: who really didn't care about the debt and the deficit frankly,

603
00:28:18,520 --> 00:28:20,480
Speaker 2: who was like, I'm going to make sure that we

604
00:28:20,520 --> 00:28:24,719
Speaker 2: don't touch your entitlement programs whatsoever. So, you know, if

605
00:28:24,760 --> 00:28:27,400
Speaker 2: you ask people like do you think that a billionaire

606
00:28:27,400 --> 00:28:29,199
Speaker 2: should be in control of the government or even have

607
00:28:29,240 --> 00:28:33,119
Speaker 2: significant influence an unelected billionaire should have significant influence in

608
00:28:33,119 --> 00:28:37,439
Speaker 2: the government, They're like no, because they're fearful of exactly

609
00:28:37,560 --> 00:28:42,520
Speaker 2: that dynamic cuts in austerity for you, largesse subsidies and

610
00:28:42,560 --> 00:28:46,080
Speaker 2: tax cuts for themselves. And that's exactly the road that

611
00:28:46,120 --> 00:28:47,320
Speaker 2: they are traveling right now.

612
00:28:47,400 --> 00:28:49,680
Speaker 1: I actually think that could hit most during the tax bill,

613
00:28:49,800 --> 00:28:52,400
Speaker 1: because remember I always say it, the lowest approval rating

614
00:28:52,400 --> 00:28:54,440
Speaker 1: that Trump ever had was the passage of Tax Cuts

615
00:28:54,440 --> 00:28:57,560
Speaker 1: and Jobs Act in twenty and seventeen. But I also

616
00:28:57,640 --> 00:29:00,240
Speaker 1: think the country has changed a lot since then. I

617
00:29:00,240 --> 00:29:03,040
Speaker 1: think the media environment that people swim in the lack

618
00:29:03,080 --> 00:29:07,160
Speaker 1: of trust, and so will the same messaging hit. I

619
00:29:07,200 --> 00:29:10,040
Speaker 1: also think they're probably gonna do enough that they'll be abe.

620
00:29:10,240 --> 00:29:13,959
Speaker 1: Last time around, the tax messaging was bullshit, right, Remember

621
00:29:14,040 --> 00:29:16,560
Speaker 1: Paul Ryan and the average American family can just spend

622
00:29:16,600 --> 00:29:18,400
Speaker 1: a thousand dollars. I was in a meeting with Paul

623
00:29:18,440 --> 00:29:20,000
Speaker 1: Ryan where it was like me and a bunch of

624
00:29:20,040 --> 00:29:23,080
Speaker 1: journalists and I remember him being like, that's enough for

625
00:29:23,200 --> 00:29:26,280
Speaker 1: someone to get their kitchen cabinets replaced or something. And

626
00:29:26,320 --> 00:29:28,240
Speaker 1: I was looking around, I'm like, do we believe any

627
00:29:28,280 --> 00:29:32,200
Speaker 1: of this ship? It was cost enough.

628
00:29:33,120 --> 00:29:35,720
Speaker 2: I was literally sit giving these people like billions of

629
00:29:35,760 --> 00:29:38,040
Speaker 2: dollars and we're saying we get a cost Co member, right,

630
00:29:38,160 --> 00:29:38,440
Speaker 2: thank you.

631
00:29:38,720 --> 00:29:41,160
Speaker 1: There with all these other journalists and we're all looking

632
00:29:41,160 --> 00:29:44,000
Speaker 1: actually like do they think this is going to hit?

633
00:29:44,720 --> 00:29:46,400
Speaker 1: It was like house is even possible?

634
00:29:46,560 --> 00:29:49,360
Speaker 2: Well even that though, so you know not to we'll

635
00:29:49,360 --> 00:29:51,760
Speaker 2: cover this more in depth in the future. The Republicans

636
00:29:51,800 --> 00:29:55,440
Speaker 2: have set themselves a limit of four point five trillion

637
00:29:55,480 --> 00:29:59,200
Speaker 2: dollars in tax cuts. Just the extension of the tax

638
00:29:59,240 --> 00:30:01,560
Speaker 2: cuts for the rich pe is four trillion. Trump made

639
00:30:01,600 --> 00:30:04,320
Speaker 2: a bunch of promises. No taxes on tips, no taxes

640
00:30:04,360 --> 00:30:05,920
Speaker 2: on Social Security, no taxes on.

641
00:30:05,920 --> 00:30:07,600
Speaker 1: Overtime, salt, don't forget salt.

642
00:30:07,920 --> 00:30:10,000
Speaker 3: And that's but that's the key.

643
00:30:10,160 --> 00:30:14,040
Speaker 2: If you like those pieces that are genuinely appealing and

644
00:30:14,120 --> 00:30:16,880
Speaker 2: helpful to the working class, like the no tax on tips, things,

645
00:30:16,920 --> 00:30:19,240
Speaker 2: they don't fit in that four point five trillion dollar

646
00:30:19,560 --> 00:30:23,680
Speaker 2: budget cap. If you're doing the tax cuts and jobs extension,

647
00:30:23,720 --> 00:30:28,760
Speaker 2: which they're doing that, and you're doing salt. So you know,

648
00:30:28,840 --> 00:30:31,400
Speaker 2: they're very likely and Republicans don't support.

649
00:30:31,040 --> 00:30:31,880
Speaker 3: This stuff anyway.

650
00:30:31,960 --> 00:30:32,760
Speaker 1: Oh yeah, that's true.

651
00:30:32,920 --> 00:30:35,560
Speaker 2: Trump does, but most Republicans don't. I think there's I

652
00:30:35,600 --> 00:30:38,960
Speaker 2: think there's a good chance that some of the promises

653
00:30:38,960 --> 00:30:41,080
Speaker 2: that were made are also not going to be fulfilled.

654
00:30:41,480 --> 00:30:43,680
Speaker 2: At the same time that rich people and the upper

655
00:30:43,720 --> 00:30:45,840
Speaker 2: middle class in states like New York and California are

656
00:30:45,840 --> 00:30:47,240
Speaker 2: getting the things that they want.

657
00:30:47,280 --> 00:30:48,840
Speaker 1: Oh yeah, if you're rich, you're about to have a

658
00:30:48,840 --> 00:30:52,520
Speaker 1: bonanza come in your way, because there are so many

659
00:30:52,560 --> 00:30:55,240
Speaker 1: extensions in the task Code that these people are frothing

660
00:30:55,240 --> 00:30:56,880
Speaker 1: at the mouth for because they want to permit, they

661
00:30:56,880 --> 00:30:59,760
Speaker 1: want to make permanent the adjustment to the overall income

662
00:30:59,800 --> 00:31:01,840
Speaker 1: tax rates all the way at the top from I

663
00:31:01,920 --> 00:31:04,560
Speaker 1: think it's like thirty nine percent something like that where

664
00:31:04,560 --> 00:31:06,480
Speaker 1: it is currently, where previously I think it was like

665
00:31:06,520 --> 00:31:08,440
Speaker 1: forty something. But they want to make that permanent instead

666
00:31:08,440 --> 00:31:10,440
Speaker 1: of a five year extension. There's a bunch of stuff

667
00:31:10,480 --> 00:31:13,160
Speaker 1: going on with the estate tax, small business, but the

668
00:31:13,760 --> 00:31:16,400
Speaker 1: actual the real fights I think will be will be

669
00:31:16,440 --> 00:31:18,880
Speaker 1: tax on tips. It'll be corporate tax rate too. There

670
00:31:18,920 --> 00:31:21,960
Speaker 1: was actually an interesting one that happened previously. It will

671
00:31:21,960 --> 00:31:24,800
Speaker 1: be salt because currently assault cap is at ten percent,

672
00:31:24,920 --> 00:31:27,120
Speaker 1: they want to lift it I think twenty that's what

673
00:31:27,160 --> 00:31:29,880
Speaker 1: i'd heard, although some New York Republicans want to uncap

674
00:31:29,920 --> 00:31:32,440
Speaker 1: it completely. Why would they do that, right? Why would

675
00:31:32,440 --> 00:31:35,240
Speaker 1: they put that into place? So I think that messaging

676
00:31:35,240 --> 00:31:38,920
Speaker 1: will hit much more if and when the tax bill passes.

677
00:31:38,960 --> 00:31:40,840
Speaker 1: But if they're smart, you're going to have to put

678
00:31:40,840 --> 00:31:43,600
Speaker 1: in some of this tip stuff and a few of

679
00:31:43,640 --> 00:31:46,040
Speaker 1: the other What else did he say, no tax on social.

680
00:31:45,720 --> 00:31:49,000
Speaker 2: Securitar overtime, no tax on social security. Yeah, those are

681
00:31:49,040 --> 00:31:49,560
Speaker 2: the ones, you know.

682
00:31:49,600 --> 00:31:52,080
Speaker 1: Philosophically though, I thought, it doesn't make any sense to

683
00:31:52,120 --> 00:31:54,120
Speaker 1: tax social security. Why would you give somebody money and

684
00:31:54,160 --> 00:31:56,040
Speaker 1: then take some of it back. I just don't get it,

685
00:31:56,560 --> 00:31:58,760
Speaker 1: you know. And it's one of those where somebody explained

686
00:31:58,760 --> 00:32:00,400
Speaker 1: it to me. They're like, well, it's because it's just

687
00:32:00,440 --> 00:32:02,560
Speaker 1: to be taxes overall income or et cetera. But why

688
00:32:02,560 --> 00:32:03,960
Speaker 1: would the government give you money and then you have

689
00:32:03,960 --> 00:32:05,400
Speaker 1: to pay taxes on it. It's like, why don't you

690
00:32:05,400 --> 00:32:06,480
Speaker 1: just give me some money and they don't have to

691
00:32:06,520 --> 00:32:08,080
Speaker 1: pay taxes on it? Doesn't make any sense.

692
00:32:08,120 --> 00:32:10,680
Speaker 2: But listen, I am in favor of lowering taxes for

693
00:32:10,800 --> 00:32:13,160
Speaker 2: working class people, and I am in favor of dramatically

694
00:32:13,160 --> 00:32:17,040
Speaker 2: increasing taxes on people like Elon Musk and companies like Tasla,

695
00:32:17,080 --> 00:32:18,040
Speaker 2: which literally.

696
00:32:17,720 --> 00:32:20,040
Speaker 3: Played zero dollars oh in taxes.

697
00:32:20,080 --> 00:32:22,800
Speaker 1: I think whatever. Apparently the reason why they paid zero

698
00:32:23,000 --> 00:32:25,719
Speaker 1: to carry over a bunch of CAPEX losses. Yeah, right

699
00:32:25,760 --> 00:32:28,040
Speaker 1: for them over there, I'm just saying. And they did

700
00:32:28,160 --> 00:32:28,760
Speaker 1: lose a lot.

701
00:32:28,600 --> 00:32:31,320
Speaker 2: Of dollars billions of dollars in profit and it pay

702
00:32:31,440 --> 00:32:32,360
Speaker 2: zero dollars in taxes.

703
00:32:32,400 --> 00:32:35,000
Speaker 1: But it's basic investment analysis, right. It's like, if you

704
00:32:35,040 --> 00:32:37,880
Speaker 1: invest and have losses X, y, and z over five

705
00:32:37,960 --> 00:32:40,800
Speaker 1: ten year period, then it carries over to your tax losses.

706
00:32:40,840 --> 00:32:43,720
Speaker 1: I don't think it's Look, I'm not defending Tesla per se,

707
00:32:43,800 --> 00:32:46,120
Speaker 1: but the idea that you can't burn a bunch of

708
00:32:46,160 --> 00:32:49,000
Speaker 1: CAPEX dollars and then write that off in the future

709
00:32:49,200 --> 00:32:51,640
Speaker 1: when you actually build a successful company. I mean that's

710
00:32:51,880 --> 00:32:54,680
Speaker 1: tried and true. Our tax cut, our tax code is

711
00:32:54,680 --> 00:32:58,320
Speaker 1: supposed to encourage business investment. Now if it's stock buy

712
00:32:58,360 --> 00:33:00,440
Speaker 1: back and stuff like that, then absolutely, I'm with you.

713
00:33:00,680 --> 00:33:01,640
Speaker 3: Well, I think you would.

714
00:33:01,400 --> 00:33:04,680
Speaker 2: Agree that the fact that billionaires pay an effective tax

715
00:33:04,760 --> 00:33:08,600
Speaker 2: rate that is dramatically lower than your average middle class

716
00:33:08,640 --> 00:33:12,240
Speaker 2: person is utterly proposals force situation which is only going

717
00:33:12,280 --> 00:33:14,280
Speaker 2: to be further exacerbatb tax.

718
00:33:14,160 --> 00:33:16,720
Speaker 1: Trumpany does want to close the carried interest loophole, which

719
00:33:16,760 --> 00:33:19,320
Speaker 1: even Kirsten Cinema and Mansion voted again, so let's all

720
00:33:19,320 --> 00:33:21,720
Speaker 1: hold him to the left because that would be the

721
00:33:21,840 --> 00:33:26,160
Speaker 1: biggest existential threat to all of his technology donors. The

722
00:33:26,200 --> 00:33:30,000
Speaker 1: tech right people. They are printing money off of their

723
00:33:30,040 --> 00:33:32,280
Speaker 1: carried interest loophole, which we don't have the time to

724
00:33:32,320 --> 00:33:34,320
Speaker 1: go in and explain it fully, but when I do

725
00:33:34,560 --> 00:33:36,840
Speaker 1: to all of you, it basically means that their labor

726
00:33:36,920 --> 00:33:39,600
Speaker 1: is taxes at much less value than yours, which is

727
00:33:39,600 --> 00:33:42,480
Speaker 1: not right, especially if you're a business owner or any

728
00:33:42,520 --> 00:33:45,760
Speaker 1: of these other people. Even small business owners are some

729
00:33:45,800 --> 00:33:50,280
Speaker 1: of the highest paying taxpayers in the United States compared

730
00:33:50,320 --> 00:33:53,200
Speaker 1: to whenever you cross the ten million mark, and you're

731
00:33:53,240 --> 00:33:56,960
Speaker 1: almost certainly involved in finance and or venture capital, you

732
00:33:57,000 --> 00:34:00,520
Speaker 1: pay almost twenty percent, which is ludicrous. Right, Somebody else

733
00:34:00,560 --> 00:34:03,400
Speaker 1: is paying forty five or fifty percent effective tax rate

734
00:34:03,440 --> 00:34:06,040
Speaker 1: if they live in New York or California. At a minimum,

735
00:34:06,120 --> 00:34:07,760
Speaker 1: even if they live in taxes or something like that

736
00:34:07,760 --> 00:34:10,720
Speaker 1: paint almost forty percent taxes. So it doesn't make any sense.

737
00:34:11,320 --> 00:34:13,720
Speaker 1: But I'm actually excited to get to the tack stuff

738
00:34:13,760 --> 00:34:17,359
Speaker 1: because that is one where I'm curious to see how

739
00:34:17,400 --> 00:34:19,879
Speaker 1: the politics actually shake out. Last thing on this Trump

740
00:34:19,960 --> 00:34:23,040
Speaker 1: voter thing, let's put this on the screen. This one

741
00:34:23,080 --> 00:34:26,239
Speaker 1: is they voted for Trump and now some of their

742
00:34:26,360 --> 00:34:30,360
Speaker 1: jobs are at risk. It says that they're writing about

743
00:34:30,360 --> 00:34:34,520
Speaker 1: some of these government employees around who voted for Donald Trump.

744
00:34:34,560 --> 00:34:38,040
Speaker 1: There's about seventy five thousand government employees who apparently accepted

745
00:34:38,040 --> 00:34:42,760
Speaker 1: the buyout and others. But you know, even within this one,

746
00:34:43,200 --> 00:34:44,719
Speaker 1: I'm feeling a little bit like I do with the

747
00:34:44,760 --> 00:34:47,359
Speaker 1: Palestine thing, Crystal. He said he was.

748
00:34:47,320 --> 00:34:50,080
Speaker 3: Going to not run on gutting the entire federal Guard.

749
00:34:50,040 --> 00:34:52,160
Speaker 1: Ran on Schedule F, which was to classify all of

750
00:34:52,160 --> 00:34:52,560
Speaker 1: you as.

751
00:34:52,480 --> 00:34:53,760
Speaker 3: Firalble I know, but he didn't.

752
00:34:53,800 --> 00:34:56,520
Speaker 2: He didn't run on I'm going to get rid of

753
00:34:56,640 --> 00:34:59,920
Speaker 2: ten percent of the federal government workforce across the board,

754
00:35:00,160 --> 00:35:03,360
Speaker 2: without regard to how long you've been there, how effective

755
00:35:03,400 --> 00:35:05,480
Speaker 2: you been, or any of those sorts of things. So

756
00:35:05,640 --> 00:35:08,520
Speaker 2: I don't know, I'll cut these people some slack. Like obviously,

757
00:35:08,560 --> 00:35:10,360
Speaker 2: I think you're full to vote for Trump no matter what,

758
00:35:10,560 --> 00:35:13,399
Speaker 2: but like you had tricked no matter what because of

759
00:35:13,600 --> 00:35:17,360
Speaker 2: the policies that he was campaigning on. But we're nobody

760
00:35:17,400 --> 00:35:22,040
Speaker 2: could have foreseen how much power would be handed to

761
00:35:22,280 --> 00:35:26,239
Speaker 2: Elon Musk, who is an austerity like, anarcho capitalist. I

762
00:35:26,280 --> 00:35:29,640
Speaker 2: want to literally get rid of the entire federal government. Guy,

763
00:35:29,760 --> 00:35:32,240
Speaker 2: That's not what Trump has ever been. You know, Trump

764
00:35:32,239 --> 00:35:35,719
Speaker 2: has not positioned himself as freaking Javier Malay, and yet

765
00:35:35,760 --> 00:35:37,880
Speaker 2: that's exactly the government that we've ended.

766
00:35:37,760 --> 00:35:39,759
Speaker 3: Up with here, So I have I have sympathy for

767
00:35:39,800 --> 00:35:40,240
Speaker 3: these impops.

768
00:35:40,239 --> 00:35:42,120
Speaker 1: I'll say with the Elon thing, but no, he ran

769
00:35:42,160 --> 00:35:44,400
Speaker 1: on schedule. AFT they someone wanted to clean out the government.

770
00:35:44,520 --> 00:35:46,960
Speaker 1: About the deep state, what did you expect? I mean,

771
00:35:47,000 --> 00:35:49,680
Speaker 1: there's a reason that ninety percent of federal employees who

772
00:35:49,680 --> 00:35:51,560
Speaker 1: are not law enforcement vote for the demographic.

773
00:35:51,560 --> 00:35:54,000
Speaker 2: But if you're like, if you're a Trump supporting federal

774
00:35:54,040 --> 00:35:56,120
Speaker 2: government worker, you're like, I'm not the deep state.

775
00:35:56,160 --> 00:35:58,040
Speaker 3: I'm your ally here, I'm loyalty.

776
00:35:57,840 --> 00:35:59,759
Speaker 1: To look around, bro, like, I mean, what do you

777
00:36:00,840 --> 00:36:01,799
Speaker 1: I don't know what to tell you.

778
00:36:02,080 --> 00:36:05,359
Speaker 2: I think it was reasonable to expect that people who

779
00:36:05,400 --> 00:36:09,440
Speaker 2: were especially high up in the government bureaucracy, who were

780
00:36:09,480 --> 00:36:12,160
Speaker 2: sort of like, you know where, their politics really matter.

781
00:36:12,200 --> 00:36:14,120
Speaker 2: I mean, for most of these people, their politics really

782
00:36:14,160 --> 00:36:17,040
Speaker 2: don't matter when they're just carrying out the functions of

783
00:36:17,080 --> 00:36:19,480
Speaker 2: whatever it is they do within the federal government. So

784
00:36:20,000 --> 00:36:24,160
Speaker 2: in any case, I genuinely don't think it was predictable

785
00:36:24,480 --> 00:36:30,359
Speaker 2: the level of control and the radical libertarian bent of

786
00:36:30,400 --> 00:36:31,279
Speaker 2: this administration.

787
00:36:31,520 --> 00:36:33,320
Speaker 3: I don't think that that was entirely.

788
00:36:33,160 --> 00:36:35,120
Speaker 1: I would not have predicted it to be the vehicle

789
00:36:35,239 --> 00:36:39,280
Speaker 1: through the current Doge, But I did expect Stephen Miller

790
00:36:39,320 --> 00:36:42,880
Speaker 1: to issue schedule When did we cover SCHEDULEFT two years ago?

791
00:36:43,280 --> 00:36:45,520
Speaker 1: People should go and watch that segment with Jonathan Swan

792
00:36:45,760 --> 00:36:47,759
Speaker 1: from The New York Times, who wrote all if you

793
00:36:48,080 --> 00:36:50,719
Speaker 1: just read or watched that segment, all of this was

794
00:36:50,760 --> 00:36:53,160
Speaker 1: eminently predictable. Now, I'm not saying that Doge would have

795
00:36:53,160 --> 00:36:55,920
Speaker 1: been the one that cut you, but the entire architecture

796
00:36:55,960 --> 00:36:59,440
Speaker 1: to mass fire millions of people from the government was

797
00:36:59,600 --> 00:37:03,160
Speaker 1: abs absolutely not just a project twenty twenty five. It

798
00:37:03,280 --> 00:37:05,920
Speaker 1: was Schedule F. It was openly endorsed by Donald Trump,

799
00:37:05,960 --> 00:37:09,279
Speaker 1: openly crafted by Stephen Miller, Talk of the town. It

800
00:37:09,360 --> 00:37:11,279
Speaker 1: wasn't just in the news media, it was here. It

801
00:37:11,320 --> 00:37:14,279
Speaker 1: was in the podcast space as well. So I don't know,

802
00:37:14,320 --> 00:37:16,640
Speaker 1: I don't feel nearly as bad for a lot of

803
00:37:16,680 --> 00:37:19,879
Speaker 1: those folks. But let me say this, I will never

804
00:37:20,000 --> 00:37:23,600
Speaker 1: celebrate at a personal level someone losing their job. I

805
00:37:23,640 --> 00:37:26,920
Speaker 1: think it's that and I have unfortunately seen a lot

806
00:37:27,000 --> 00:37:31,120
Speaker 1: of people who are taking pleasure. But listen, no matter

807
00:37:31,160 --> 00:37:34,440
Speaker 1: who you are, government non government, losing your job sucks.

808
00:37:34,520 --> 00:37:36,719
Speaker 1: Not being able to pay your mortgage sucks. It's one

809
00:37:36,719 --> 00:37:38,839
Speaker 1: of the highest predictor one of the most stressful events

810
00:37:38,840 --> 00:37:41,520
Speaker 1: that you've ever experienced in your life. High predictor of suicide.

811
00:37:41,600 --> 00:37:43,880
Speaker 1: That's why a lot of people kill themselves whenever there's recessions.

812
00:37:43,960 --> 00:37:46,080
Speaker 1: It's horrible. So at a personal level, we should not

813
00:37:46,120 --> 00:37:47,840
Speaker 1: wish it on anybody, and I would tell people not

814
00:37:47,880 --> 00:37:51,080
Speaker 1: to be cruel in that regard. It's important to always

815
00:37:51,280 --> 00:37:54,000
Speaker 1: understand the humanity of them, even if you know, I

816
00:37:54,040 --> 00:37:56,239
Speaker 1: did think it was kind of predictable, but that get

817
00:37:56,280 --> 00:37:58,520
Speaker 1: that's more about a voting level as opposed to no one,

818
00:37:58,680 --> 00:37:59,879
Speaker 1: I'm not going to celebrate you.

819
00:38:00,360 --> 00:38:02,880
Speaker 2: Was out there like we're going to fire everyone who's

820
00:38:02,880 --> 00:38:05,560
Speaker 2: still in the probationary period, Like no one said.

821
00:38:05,400 --> 00:38:08,760
Speaker 1: Oh that was actually not just actually think that one.

822
00:38:08,680 --> 00:38:11,799
Speaker 2: Was there, which was not just people who you know,

823
00:38:11,960 --> 00:38:14,280
Speaker 2: are new to the government. It's also people who newly

824
00:38:14,400 --> 00:38:17,560
Speaker 2: changed got a promotion in the government, which means that

825
00:38:17,680 --> 00:38:20,160
Speaker 2: you know, by like sort of definitionally you were doing

826
00:38:20,200 --> 00:38:21,799
Speaker 2: a good job, or at least someone thought you were

827
00:38:21,800 --> 00:38:24,560
Speaker 2: doing a good job enough to promote. So in a

828
00:38:24,600 --> 00:38:27,600
Speaker 2: lot of ways, between that and the structure of the

829
00:38:27,640 --> 00:38:30,880
Speaker 2: deferred resignation program, it really is a calling of a

830
00:38:30,880 --> 00:38:32,800
Speaker 2: lot of the best and the brightest from the federal government.

831
00:38:32,880 --> 00:38:35,759
Speaker 2: So if you were an outstanding performer and you know,

832
00:38:35,840 --> 00:38:39,400
Speaker 2: and generally like in a non political position with the

833
00:38:39,440 --> 00:38:42,040
Speaker 2: respect of your colleagues, I think it was reasonable to

834
00:38:42,080 --> 00:38:45,239
Speaker 2: expect that you wouldn't be on the chopping blocks. So

835
00:38:45,480 --> 00:38:48,520
Speaker 2: in any case, I will just say that even as

836
00:38:48,719 --> 00:38:53,279
Speaker 2: I was taking Donald Trump very seriously about what he

837
00:38:53,320 --> 00:38:55,520
Speaker 2: was saying he was going to do, I knew Project

838
00:38:55,560 --> 00:38:58,640
Speaker 2: twenty twenty five was in fact the plan. This has

839
00:38:58,719 --> 00:39:02,080
Speaker 2: still been far more radical and aggressive than I expected.

840
00:39:02,200 --> 00:39:05,319
Speaker 2: And in particular, the like you know, complete handing over

841
00:39:05,360 --> 00:39:08,080
Speaker 2: of the keys to Elon Musk and the complete deferential

842
00:39:08,160 --> 00:39:11,160
Speaker 2: nature of Donald Trump to Elon Musk is bizarre and

843
00:39:11,320 --> 00:39:12,000
Speaker 2: was not expected.

844
00:39:12,080 --> 00:39:13,640
Speaker 1: I'm with you on that. One of the guys weird.

845
00:39:16,280 --> 00:39:19,120
Speaker 2: The latest fallout over DOGE, as we have put this

846
00:39:19,200 --> 00:39:22,040
Speaker 2: up on the screen. Top social Security official, the acting

847
00:39:22,080 --> 00:39:25,640
Speaker 2: director of or Acting Commissioner rather of the Social Security Administration,

848
00:39:26,040 --> 00:39:29,480
Speaker 2: has now left their job her job this weekend after

849
00:39:29,520 --> 00:39:33,880
Speaker 2: a clash with DOGE and their attempts to access sensitive

850
00:39:33,880 --> 00:39:37,680
Speaker 2: government records within the Social Security Administration. She left her

851
00:39:37,680 --> 00:39:42,160
Speaker 2: position on Sunday after the disagreement. And it's also interesting

852
00:39:42,520 --> 00:39:45,800
Speaker 2: so this, you know, this is reminiscent of the acting

853
00:39:45,880 --> 00:39:49,520
Speaker 2: Director of the Treasury, who also left over a conflict

854
00:39:49,520 --> 00:39:51,440
Speaker 2: with DOJE and didn't want to give them access and

855
00:39:51,520 --> 00:39:54,080
Speaker 2: you know, would rather be pushed out than stay in

856
00:39:54,160 --> 00:39:58,480
Speaker 2: and grant that access. Also interesting here is who Trump

857
00:39:58,640 --> 00:40:02,319
Speaker 2: appointed now to fill this role as Acting Director of

858
00:40:02,560 --> 00:40:08,719
Speaker 2: Social Security. So bypassed dozens of other executive level individuals

859
00:40:08,719 --> 00:40:11,600
Speaker 2: within this administration, like if you're looking at the org chart,

860
00:40:11,640 --> 00:40:15,440
Speaker 2: bypassed dozens of people to pick this person, Leland Duduk,

861
00:40:15,840 --> 00:40:20,520
Speaker 2: who has apparently posted positive remarks on social media about

862
00:40:20,560 --> 00:40:23,480
Speaker 2: Doge's efforts to cut costs and search for fraud in

863
00:40:23,560 --> 00:40:24,640
Speaker 2: federal agencies.

864
00:40:25,080 --> 00:40:27,879
Speaker 3: So literally went through the list and.

865
00:40:27,840 --> 00:40:32,719
Speaker 2: Looked at who had posted praise of DOGE, and that's

866
00:40:32,719 --> 00:40:35,160
Speaker 2: the person that they plucked and put in. Well who

867
00:40:35,400 --> 00:40:38,840
Speaker 2: year while they're waiting for, you know, the more permanent

868
00:40:38,920 --> 00:40:40,480
Speaker 2: replacement to be confirmed by the Senate.

869
00:40:40,640 --> 00:40:43,279
Speaker 1: Yeah, this is where I feel a bit torn, because

870
00:40:43,280 --> 00:40:45,600
Speaker 1: we're about to talk about this with the IRS and others.

871
00:40:46,360 --> 00:40:48,880
Speaker 1: You know, there's this presumption in this that these people

872
00:40:49,000 --> 00:40:51,040
Speaker 1: are good, and maybe they are, and maybe they are,

873
00:40:51,160 --> 00:40:55,200
Speaker 1: but there's this general presumption around this civil servant worship

874
00:40:55,239 --> 00:40:57,800
Speaker 1: where they're like, oh, this is very tightly held data,

875
00:40:57,800 --> 00:40:59,600
Speaker 1: and it's like, yeah, okay, but you know when everyone

876
00:40:59,640 --> 00:41:02,120
Speaker 1: talks about DOGE except they're like, oh, it's scary that

877
00:41:02,120 --> 00:41:04,719
Speaker 1: they're getting access. And I think that's deeply true on

878
00:41:04,760 --> 00:41:07,600
Speaker 1: a conflict of interest level with Elon. But at a

879
00:41:07,640 --> 00:41:10,880
Speaker 1: principal level, why is the civil servant. Supposedly it's supposed

880
00:41:10,920 --> 00:41:12,880
Speaker 1: to be the one who is more trusted with all

881
00:41:12,920 --> 00:41:16,880
Speaker 1: of our Social security, our SSDI paperwork, our taxpayer paperwork.

882
00:41:16,920 --> 00:41:20,239
Speaker 1: I mean, IRS people are convicted or shown to be

883
00:41:20,680 --> 00:41:22,680
Speaker 1: biased all the time. There was all that stuff during

884
00:41:22,680 --> 00:41:25,200
Speaker 1: the Obama administration. Look at all this stuff even during

885
00:41:25,200 --> 00:41:28,520
Speaker 1: the first Trump administration. I remember what were all those

886
00:41:28,600 --> 00:41:31,279
Speaker 1: leaks that happened of that career IRS agent who leaked

887
00:41:31,320 --> 00:41:33,840
Speaker 1: like Peter Tiel and all these other people's tax returns. So,

888
00:41:34,200 --> 00:41:37,680
Speaker 1: I mean, these are not heroes necessarily. Well, you know

889
00:41:37,719 --> 00:41:40,239
Speaker 1: why is a hero? That guy showed how you really

890
00:41:40,280 --> 00:41:43,120
Speaker 1: should do it roth Ira, folks, Peter Tiel's got five

891
00:41:43,120 --> 00:41:45,279
Speaker 1: billion dollars in a roth ira in one of the

892
00:41:45,280 --> 00:41:48,600
Speaker 1: most genius financial retirement schemes I've ever seen. Everyone should

893
00:41:48,600 --> 00:41:50,680
Speaker 1: study it, especially if you're a normal guy.

894
00:41:50,760 --> 00:41:51,640
Speaker 3: Well, here's what I say.

895
00:41:51,719 --> 00:41:54,640
Speaker 2: I'm part of why it's important, and it matters who

896
00:41:55,040 --> 00:41:57,960
Speaker 2: has access to that data and with the Treasury, it

897
00:41:58,080 --> 00:42:00,600
Speaker 2: was also not just access to the data, was also

898
00:42:00,880 --> 00:42:05,520
Speaker 2: that this you know, doge operatic had read write access

899
00:42:05,560 --> 00:42:09,480
Speaker 2: on the code which controls the trillions of dollars in

900
00:42:09,560 --> 00:42:13,440
Speaker 2: payments that go out from the Treasury Department. Similarly, obviously

901
00:42:13,480 --> 00:42:16,959
Speaker 2: people really depend on getting them social Security checks out

902
00:42:17,040 --> 00:42:17,800
Speaker 2: and on time.

903
00:42:18,080 --> 00:42:21,200
Speaker 3: So there's also a fear that these doge.

904
00:42:20,880 --> 00:42:24,480
Speaker 2: Operatic hackers whatever you want to call them, mess around

905
00:42:24,480 --> 00:42:27,000
Speaker 2: with things in a way that causes things to break.

906
00:42:27,239 --> 00:42:32,319
Speaker 2: In addition, there are very specific laws regarding privacy of

907
00:42:32,440 --> 00:42:36,760
Speaker 2: your data with the federal government, and so the civil

908
00:42:36,760 --> 00:42:40,839
Speaker 2: servants are trained in those laws and have you know,

909
00:42:41,160 --> 00:42:43,960
Speaker 2: are subject to the laws when they don't comply with them,

910
00:42:44,200 --> 00:42:46,960
Speaker 2: whereas the doge people seem to be totally above and

911
00:42:47,000 --> 00:42:49,040
Speaker 2: beyond the law. Not to mention, some of the things

912
00:42:49,040 --> 00:42:51,439
Speaker 2: that have come out about some of these individuals makes

913
00:42:51,480 --> 00:42:54,600
Speaker 2: them not exactly the most trustworthy people. I'm not sure

914
00:42:54,600 --> 00:42:57,040
Speaker 2: who it is exactly who's inside of Social Security. I'm

915
00:42:57,040 --> 00:42:59,759
Speaker 2: not sure that that's publicly available information, which another thing too,

916
00:42:59,880 --> 00:43:03,440
Speaker 2: is that there's like no transparency around what they're actually doing.

917
00:43:03,760 --> 00:43:06,000
Speaker 2: But you know, one of these dudes was like fired

918
00:43:06,040 --> 00:43:08,920
Speaker 2: from his job because he was sharing company secrets. I

919
00:43:08,920 --> 00:43:10,440
Speaker 2: think that same guy as the one that you and

920
00:43:10,560 --> 00:43:13,000
Speaker 2: Ryan were talking about, created the website where or maybe

921
00:43:13,000 --> 00:43:14,600
Speaker 2: it was Ryan and Emily that were talking and created

922
00:43:14,600 --> 00:43:20,120
Speaker 2: the website where you could, you know, referencing child sexual

923
00:43:20,120 --> 00:43:22,799
Speaker 2: abuse material. Whether that was just a troll or whether

924
00:43:22,840 --> 00:43:24,680
Speaker 2: it was really a way for encrypting this type of

925
00:43:24,680 --> 00:43:28,920
Speaker 2: stuff hard to say. So in any case, we know

926
00:43:29,120 --> 00:43:31,520
Speaker 2: very little about these individuals, and what we do know

927
00:43:31,560 --> 00:43:35,000
Speaker 2: has not exactly put anyone's mind at ease about them

928
00:43:35,040 --> 00:43:39,160
Speaker 2: being in such a sensitive position as being inside of

929
00:43:39,200 --> 00:43:41,280
Speaker 2: social security systems, being inside of the treasures.

930
00:43:41,280 --> 00:43:42,879
Speaker 1: I think that's fair. I just get I get back

931
00:43:42,880 --> 00:43:44,279
Speaker 1: to the civil serving point where like I don't know

932
00:43:44,320 --> 00:43:46,640
Speaker 1: who that's access over my IRS data, I certainly don't

933
00:43:46,640 --> 00:43:51,160
Speaker 1: trust them based on my track record or the social

934
00:43:51,200 --> 00:43:53,959
Speaker 1: security on elected bureaucrats. It just gets to that heart

935
00:43:54,000 --> 00:43:57,000
Speaker 1: of in a certain sense, we're dealing with two unelected

936
00:43:57,000 --> 00:43:59,760
Speaker 1: parties and a lot of this is about partisan interest,

937
00:44:00,280 --> 00:44:03,400
Speaker 1: as I showed with the USAID thing, which I think aligns.

938
00:44:03,440 --> 00:44:06,239
Speaker 1: I'm not one hundred percent sure. I'm willing to bet

939
00:44:06,320 --> 00:44:09,600
Speaker 1: people are much more skeptical. I think of the career

940
00:44:09,680 --> 00:44:12,200
Speaker 1: civil servant. Now, these people, I've lived around these people

941
00:44:12,239 --> 00:44:14,839
Speaker 1: my entire adult life. They think they're heroes and they

942
00:44:14,840 --> 00:44:17,160
Speaker 1: think they're like the greatest, smartest people on earth. But

943
00:44:17,200 --> 00:44:20,800
Speaker 1: they're also deeply partisan in their all like capital liberal

944
00:44:20,840 --> 00:44:23,640
Speaker 1: way are they truly to be trusted? You know? And

945
00:44:23,840 --> 00:44:26,680
Speaker 1: if anything, when you elected Donald Trump and who is

946
00:44:26,800 --> 00:44:30,480
Speaker 1: genuinely like a scream and an f you against the system,

947
00:44:30,520 --> 00:44:32,359
Speaker 1: It's like, why would anyone trust that you are going

948
00:44:32,400 --> 00:44:35,759
Speaker 1: to faithally carry out whatever the elected office wants you

949
00:44:35,840 --> 00:44:37,920
Speaker 1: to do. Now, if it's illegal, that's one different thing.

950
00:44:38,000 --> 00:44:40,880
Speaker 1: But you know, at a base trust level, everyone's like, oh,

951
00:44:40,920 --> 00:44:44,040
Speaker 1: it's so horrible that the top civil servant resigned. I'm like, yeah,

952
00:44:44,040 --> 00:44:45,600
Speaker 1: but who is this lady? I don't even know who

953
00:44:45,680 --> 00:44:47,400
Speaker 1: you are, Nobody elected you.

954
00:44:47,480 --> 00:44:50,560
Speaker 2: At the someone who's been there for decades, I think

955
00:44:50,640 --> 00:44:54,480
Speaker 2: even worse, this individual and it's been part of making

956
00:44:54,520 --> 00:44:58,680
Speaker 2: sure that Social Security checks went out on time and

957
00:44:58,719 --> 00:45:01,000
Speaker 2: in a reliable fashion. So am I going to put

958
00:45:01,000 --> 00:45:03,000
Speaker 2: my trust in that person who's been there for over

959
00:45:03,040 --> 00:45:05,120
Speaker 2: a decade and been doing the job and doing that

960
00:45:05,239 --> 00:45:08,200
Speaker 2: job effectively, or some arrogant twenty year old brat who

961
00:45:08,280 --> 00:45:11,240
Speaker 2: was like fired for sharing illegally share or not illegally,

962
00:45:11,280 --> 00:45:13,359
Speaker 2: but sharing company secrets from his previous job.

963
00:45:13,480 --> 00:45:15,680
Speaker 3: Like, no doubt in my mind who I would.

964
00:45:15,920 --> 00:45:18,239
Speaker 1: But that's my point about institutional trust is you have

965
00:45:18,239 --> 00:45:20,520
Speaker 1: a baseline institutional trust. You think these programs are good.

966
00:45:20,520 --> 00:45:22,000
Speaker 1: Most people think that these programs are best.

967
00:45:22,080 --> 00:45:23,520
Speaker 3: Those people think Social Security is good.

968
00:45:23,960 --> 00:45:27,279
Speaker 1: Okay again when we talk at them. First of all,

969
00:45:27,400 --> 00:45:30,879
Speaker 1: nobody again unless you're old, is logging in and knows

970
00:45:30,920 --> 00:45:33,959
Speaker 1: what the Social Security Administration is. They know it comes

971
00:45:33,960 --> 00:45:38,160
Speaker 1: from the government. Now in terms of the Social Security Administration,

972
00:45:38,640 --> 00:45:41,440
Speaker 1: somebody my age, right, I doom not have deep familiarity

973
00:45:41,480 --> 00:45:44,920
Speaker 1: unless I did this job with Center of Medicaid CMS.

974
00:45:45,200 --> 00:45:47,239
Speaker 1: How all this stuff works. I know because of I

975
00:45:47,680 --> 00:45:50,839
Speaker 1: literally from the job. But the average voter is not

976
00:45:51,000 --> 00:45:53,680
Speaker 1: having a deep amount of participation in all this. When

977
00:45:53,680 --> 00:45:57,759
Speaker 1: they hear civil servant bureaucrat distrust immediately, I think, at

978
00:45:57,840 --> 00:46:00,160
Speaker 1: least for the people who voted for Donn I think.

979
00:46:00,120 --> 00:46:02,840
Speaker 2: When they hear the richest man on the planet is

980
00:46:02,880 --> 00:46:06,600
Speaker 2: messing around in the social Security administration red flags go up.

981
00:46:06,680 --> 00:46:09,920
Speaker 2: And I mean to that point, Elon is sort of

982
00:46:10,080 --> 00:46:11,880
Speaker 2: building a case and has been, by the way, for

983
00:46:11,960 --> 00:46:14,800
Speaker 2: months something we have been pointing out here for cuts

984
00:46:14,800 --> 00:46:15,760
Speaker 2: to Social Security.

985
00:46:15,760 --> 00:46:17,080
Speaker 3: He routinely shares.

986
00:46:16,840 --> 00:46:19,399
Speaker 2: These posts from Mike Lee, who is a libertarian who

987
00:46:19,400 --> 00:46:21,960
Speaker 2: thinks that Social Security is a Ponzi scheme or pyramid

988
00:46:22,040 --> 00:46:25,799
Speaker 2: scheme and should be dismantled, and as inherently as a program,

989
00:46:26,160 --> 00:46:28,960
Speaker 2: not talking about like improper payments to this person that person,

990
00:46:29,000 --> 00:46:32,960
Speaker 2: but as a program is fraudulent, like Elon shares that

991
00:46:33,080 --> 00:46:36,239
Speaker 2: and agrees with that. And so now he's out with

992
00:46:36,360 --> 00:46:41,080
Speaker 2: this preposterous bunch of bullshit attacking the Social Security and

993
00:46:41,120 --> 00:46:43,960
Speaker 2: its administration. Put us up on the screen claiming that

994
00:46:44,280 --> 00:46:47,000
Speaker 2: we went in and we looked at the database and

995
00:46:47,080 --> 00:46:49,239
Speaker 2: look at all these people who are one hundred and

996
00:46:49,239 --> 00:46:52,040
Speaker 2: fifty years old or who are three hundred years old,

997
00:46:52,360 --> 00:46:56,360
Speaker 2: who are still receiving payment. So, first of all, again

998
00:46:57,480 --> 00:47:00,320
Speaker 2: this could literally have just been invented, this brought to you.

999
00:47:00,400 --> 00:47:02,560
Speaker 2: We don't even know that this is based on anything.

1000
00:47:02,840 --> 00:47:04,880
Speaker 2: But let's give him the benefit of the doubt that

1001
00:47:04,920 --> 00:47:08,239
Speaker 2: these are actually some numbers that was pulled from the

1002
00:47:08,320 --> 00:47:13,839
Speaker 2: Social Security database. We know on basic math that this

1003
00:47:13,880 --> 00:47:17,360
Speaker 2: is not indicative of people who are receiving payments, but

1004
00:47:17,440 --> 00:47:19,120
Speaker 2: also if you look at the number of people or

1005
00:47:19,200 --> 00:47:20,919
Speaker 2: one hundred and fifty years old. One thing I saw

1006
00:47:20,920 --> 00:47:23,200
Speaker 2: this morning, saga is that this could be a result

1007
00:47:23,280 --> 00:47:25,799
Speaker 2: of all these systems are program using COBOL, which is

1008
00:47:25,800 --> 00:47:29,360
Speaker 2: like this old ass programming language, and it has this

1009
00:47:29,440 --> 00:47:32,520
Speaker 2: particular quirk where if you don't fill in the birth date,

1010
00:47:32,800 --> 00:47:36,200
Speaker 2: then it defaults to it being eighteen seventy five, which

1011
00:47:36,200 --> 00:47:39,920
Speaker 2: would indicate a year of age of one hundred and

1012
00:47:39,920 --> 00:47:42,799
Speaker 2: fifty years old in this year. So, and this is

1013
00:47:42,840 --> 00:47:44,719
Speaker 2: part of the thing is just keep this up on

1014
00:47:44,760 --> 00:47:47,040
Speaker 2: this screen and then I'll explain this as well. Is

1015
00:47:47,440 --> 00:47:49,919
Speaker 2: you know these apparatics that he has going and they're

1016
00:47:49,920 --> 00:47:53,160
Speaker 2: twenty years old, Okay, they I'm sure maybe are very

1017
00:47:53,200 --> 00:47:56,880
Speaker 2: technically proficient at the latest and greatest. I used to

1018
00:47:56,960 --> 00:48:00,440
Speaker 2: work as a consultant for the government and I actually

1019
00:48:00,600 --> 00:48:04,400
Speaker 2: was like in these old ass SQL databases, and I

1020
00:48:04,400 --> 00:48:06,879
Speaker 2: can tell you they are quirky and weird and they're

1021
00:48:06,920 --> 00:48:09,400
Speaker 2: certainly not state of the art. And if that's the

1022
00:48:09,440 --> 00:48:11,880
Speaker 2: thing you want to address, that would be a massive

1023
00:48:11,960 --> 00:48:14,680
Speaker 2: undertaking and could make the government more efficient. I'm not

1024
00:48:14,680 --> 00:48:16,839
Speaker 2: opposed to it, but to just go in and pull

1025
00:48:16,880 --> 00:48:18,440
Speaker 2: some data and be like, oh my god, look at

1026
00:48:18,440 --> 00:48:20,440
Speaker 2: all these three hundred year olds that are getting paid Like,

1027
00:48:21,040 --> 00:48:23,680
Speaker 2: do some basic logic and math and maybe ask the

1028
00:48:23,680 --> 00:48:26,200
Speaker 2: people around you what you were getting wrong before you

1029
00:48:26,280 --> 00:48:28,640
Speaker 2: just put out to the public this attack on Social Security.

1030
00:48:28,640 --> 00:48:31,160
Speaker 2: So in any case, this journalist goes in, runs the

1031
00:48:31,239 --> 00:48:33,400
Speaker 2: numbers and finds, of course it doesn't add up.

1032
00:48:33,440 --> 00:48:35,680
Speaker 3: This would indicate that they would be paying.

1033
00:48:35,480 --> 00:48:39,279
Speaker 2: Forty one million more beneficiaries than we actually are, at

1034
00:48:39,320 --> 00:48:42,239
Speaker 2: a cost of about one trillion dollars a year more

1035
00:48:42,280 --> 00:48:46,440
Speaker 2: than we're actually spending. If in fact, that social Security

1036
00:48:46,520 --> 00:48:49,680
Speaker 2: data that Elon tweeted was remotely real and consistent with

1037
00:48:49,719 --> 00:48:52,600
Speaker 2: the number of people that get paid out. So again,

1038
00:48:52,800 --> 00:48:56,400
Speaker 2: bottom line here in my humble opinion, is that Elon

1039
00:48:56,520 --> 00:48:59,920
Speaker 2: is trying to build a case against Social Security, period,

1040
00:49:00,080 --> 00:49:03,480
Speaker 2: end of story. Not just against improper payments or fraud

1041
00:49:03,640 --> 00:49:07,279
Speaker 2: or whatever, but against the program as a whole. Now,

1042
00:49:07,280 --> 00:49:10,080
Speaker 2: well that workout, Will he be able to get those cuts?

1043
00:49:10,480 --> 00:49:11,120
Speaker 3: Who knows.

1044
00:49:11,160 --> 00:49:13,360
Speaker 2: Donald Trump has been very consistent in saying that he

1045
00:49:13,400 --> 00:49:15,520
Speaker 2: would stay hands off Social Security, But I don't think

1046
00:49:15,520 --> 00:49:17,640
Speaker 2: there's any doubt that that's the attempt here is to,

1047
00:49:18,200 --> 00:49:20,480
Speaker 2: you know, to make it seem like you can cut

1048
00:49:20,560 --> 00:49:22,640
Speaker 2: this program, that you can take money out of this

1049
00:49:22,680 --> 00:49:26,680
Speaker 2: program without and actually hitting recipients because there's so much fraud.

1050
00:49:27,040 --> 00:49:29,279
Speaker 2: This data, though, and many of the other things you

1051
00:49:29,360 --> 00:49:32,320
Speaker 2: shared besides are is completely made up bullshit.

1052
00:49:32,360 --> 00:49:34,160
Speaker 1: Well, I'm with you on this data because it's hilarious.

1053
00:49:34,200 --> 00:49:35,720
Speaker 1: The guy who was there was from the Tax Foundation,

1054
00:49:35,760 --> 00:49:37,959
Speaker 1: which is actually very good. They do a good job.

1055
00:49:38,239 --> 00:49:39,880
Speaker 1: This is a You're going to have to explain this

1056
00:49:39,920 --> 00:49:41,600
Speaker 1: to me because I'm not a database guy. I haven't

1057
00:49:41,600 --> 00:49:46,320
Speaker 1: mentioned since my econometrics class. But the politically neutral sequel

1058
00:49:46,520 --> 00:49:50,040
Speaker 1: reddit you've taught me it's not SQL subreddit is apparently

1059
00:49:50,200 --> 00:49:52,879
Speaker 1: very upset about the way that this was compiled. Let's

1060
00:49:52,880 --> 00:49:55,200
Speaker 1: put this out there on the screen. This is classic

1061
00:49:55,200 --> 00:49:57,439
Speaker 1: subreddit behavior. I love it. If I know one thing,

1062
00:49:57,719 --> 00:50:00,399
Speaker 1: it's Star Wars. However, if I know two thing, it's

1063
00:50:00,400 --> 00:50:03,799
Speaker 1: acquiring domain knowledge of company data using SQL. He is

1064
00:50:03,840 --> 00:50:06,120
Speaker 1: either that dumb and has done zero due diligence on

1065
00:50:06,160 --> 00:50:09,239
Speaker 1: his claim and simply done a select age count from

1066
00:50:09,239 --> 00:50:12,520
Speaker 1: people grouped by age, where dead equals true without checking

1067
00:50:12,560 --> 00:50:15,840
Speaker 1: maybe if these people are actually drawing benefits via transactional data,

1068
00:50:16,000 --> 00:50:19,080
Speaker 1: or he just wants to spread misinformation. Let's go to

1069
00:50:19,160 --> 00:50:22,480
Speaker 1: the next one. This is several of these screenshots. So

1070
00:50:22,480 --> 00:50:24,760
Speaker 1: again we can't know everything about all the data right queries,

1071
00:50:24,760 --> 00:50:27,080
Speaker 1: but we can sanity check stuff. The one to eighty

1072
00:50:27,120 --> 00:50:28,719
Speaker 1: one to eighty nine range means that people were born

1073
00:50:28,719 --> 00:50:30,759
Speaker 1: in the eighteen thirties. Social Security didn't start till in

1074
00:50:30,800 --> 00:50:32,520
Speaker 1: nineteen thirty five, meaning many of these people would have

1075
00:50:32,520 --> 00:50:35,120
Speaker 1: been in their nineties. Unlikely these people's records have made

1076
00:50:35,120 --> 00:50:36,719
Speaker 1: it to the computer age. I could be wrong, but

1077
00:50:36,760 --> 00:50:38,440
Speaker 1: it would make me want to check the source records

1078
00:50:38,440 --> 00:50:41,239
Speaker 1: before sending it to operational for folks, which in this

1079
00:50:41,280 --> 00:50:43,960
Speaker 1: case is citizens of the US. Plus, we don't have

1080
00:50:43,960 --> 00:50:46,040
Speaker 1: the query. Just because you have a record in SSDB

1081
00:50:46,440 --> 00:50:48,759
Speaker 1: does not mean that you are collecting. No way to

1082
00:50:48,800 --> 00:50:51,200
Speaker 1: tell with a grid only view, I can only do

1083
00:50:51,320 --> 00:50:54,239
Speaker 1: that in XCEL. So you've got some SQL warriors here

1084
00:50:54,880 --> 00:50:57,680
Speaker 1: that are very very upset about the way that this

1085
00:50:58,000 --> 00:51:01,480
Speaker 1: data has been compiled. And that is what I think

1086
00:51:01,560 --> 00:51:04,200
Speaker 1: validates your point most which is that Elon is an

1087
00:51:04,440 --> 00:51:09,040
Speaker 1: quote imperfect messenger in the nicest way to possibly put

1088
00:51:09,040 --> 00:51:12,920
Speaker 1: it around this. He's maniacal, he doesn't check his work,

1089
00:51:13,280 --> 00:51:17,280
Speaker 1: he's constantly posting about it has massive conflicts of interest,

1090
00:51:17,880 --> 00:51:20,080
Speaker 1: and that's why I think it's become like a culture

1091
00:51:20,120 --> 00:51:22,759
Speaker 1: war in and of itself, of like a choose your

1092
00:51:22,800 --> 00:51:25,200
Speaker 1: own fighter, and to choose your own fighter again, in

1093
00:51:25,239 --> 00:51:29,240
Speaker 1: my opinion, splits very well along a political valance. Somebody

1094
00:51:29,280 --> 00:51:33,440
Speaker 1: like myself who generally doesn't trust career civil servant's bureaucrats,

1095
00:51:33,440 --> 00:51:35,839
Speaker 1: I'm like, yeah, I don't know if you're such a hero.

1096
00:51:36,080 --> 00:51:38,840
Speaker 1: Just my experience, that seems to also be the general

1097
00:51:39,000 --> 00:51:41,200
Speaker 1: like valance. I think of a lot of people who

1098
00:51:41,280 --> 00:51:44,239
Speaker 1: voted for Trump or anti establishment, whereas for a lot

1099
00:51:44,239 --> 00:51:47,120
Speaker 1: of people who are much more establishment minded or who

1100
00:51:47,160 --> 00:51:50,160
Speaker 1: are much more trustful of institutions they look at somebody

1101
00:51:50,160 --> 00:51:52,880
Speaker 1: like Elon will correctly point out all of their flaws

1102
00:51:52,880 --> 00:51:54,960
Speaker 1: and say, no, I'm going to stick with whoever. This

1103
00:51:55,000 --> 00:51:58,839
Speaker 1: eighteen year career lady is at the Social Security Administration.

1104
00:51:58,960 --> 00:52:02,080
Speaker 1: So I understand why it's very difficult. I totally get

1105
00:52:02,120 --> 00:52:05,359
Speaker 1: also why a lot of liberals are furious about all

1106
00:52:05,360 --> 00:52:07,640
Speaker 1: of this. I try to think about the way that

1107
00:52:07,680 --> 00:52:11,399
Speaker 1: it will hit and until they actually do and cut

1108
00:52:11,440 --> 00:52:15,279
Speaker 1: a program that affects millions on a actual basis. I

1109
00:52:15,280 --> 00:52:18,160
Speaker 1: don't think there will be any large political outcry just

1110
00:52:18,160 --> 00:52:20,520
Speaker 1: because I do think we're still living through a very

1111
00:52:20,560 --> 00:52:21,920
Speaker 1: anti institutional moment.

1112
00:52:22,640 --> 00:52:25,759
Speaker 2: I think what I want people to understand is that

1113
00:52:25,840 --> 00:52:29,120
Speaker 2: the real goal of DOGE is not cutting spending or

1114
00:52:29,200 --> 00:52:33,200
Speaker 2: rooting out waste and fraud. It's not efficiency. It is

1115
00:52:33,760 --> 00:52:38,440
Speaker 2: consolidating power in the hands of Elon Musk and whoever's

1116
00:52:38,480 --> 00:52:43,360
Speaker 2: billionaire allies are. And it is an ideological anti government

1117
00:52:43,680 --> 00:52:47,120
Speaker 2: project at least as it goes for social safety net

1118
00:52:47,160 --> 00:52:49,960
Speaker 2: programs that benefit you. I mean, and this is again

1119
00:52:50,160 --> 00:52:52,160
Speaker 2: he says this thing, these things out loud. You only

1120
00:52:52,239 --> 00:52:55,399
Speaker 2: need to listen to what he's saying. He believes that

1121
00:52:55,600 --> 00:52:59,360
Speaker 2: every in his ideal world, every government worker would be

1122
00:52:59,440 --> 00:53:02,080
Speaker 2: fired and put into the private sector, which means a

1123
00:53:02,120 --> 00:53:07,600
Speaker 2: complete privatization of government, something that I think most people

1124
00:53:07,600 --> 00:53:10,360
Speaker 2: would be deeply opposed to. But more to the point

1125
00:53:10,480 --> 00:53:13,480
Speaker 2: about how you know that this isn't about cutting government spending.

1126
00:53:13,960 --> 00:53:16,480
Speaker 2: They're using the like all of these things that they're

1127
00:53:16,480 --> 00:53:20,480
Speaker 2: talking about cutting USAID, you know, even the trioming of

1128
00:53:20,520 --> 00:53:22,840
Speaker 2: the federal workforce, taking a hatchet to a ten percent

1129
00:53:23,320 --> 00:53:27,719
Speaker 2: is a trivial part of the federal government budget, and

1130
00:53:27,800 --> 00:53:30,120
Speaker 2: what are they doing. On the other hand, They're securing

1131
00:53:30,280 --> 00:53:35,680
Speaker 2: for trillion dollars in tax cuts for themselves, alongside things

1132
00:53:35,719 --> 00:53:38,279
Speaker 2: like Medicaid cuts, alongside you know, Elon trying to build

1133
00:53:38,320 --> 00:53:40,560
Speaker 2: the case against Social Security, trying to build the case

1134
00:53:40,600 --> 00:53:44,040
Speaker 2: against Medicare, et cetera. So that's what I want people

1135
00:53:44,040 --> 00:53:46,839
Speaker 2: to understand is that this really has nothing to do

1136
00:53:47,000 --> 00:53:51,480
Speaker 2: with government efficiency or you know, or rooting out fraud

1137
00:53:51,719 --> 00:53:54,560
Speaker 2: or any of those sorts of things. And if you

1138
00:53:54,680 --> 00:53:56,800
Speaker 2: look at what they're actually doing and the way that

1139
00:53:56,840 --> 00:53:59,640
Speaker 2: they're going about it, that becomes very clear. And I

1140
00:53:59,640 --> 00:54:02,600
Speaker 2: think piece of that is, you know, there's also a

1141
00:54:02,600 --> 00:54:06,640
Speaker 2: fight right now about access to IRS information, and IRS

1142
00:54:06,719 --> 00:54:08,600
Speaker 2: data can put the tear sheet up on the screen,

1143
00:54:09,000 --> 00:54:11,200
Speaker 2: so you know, this is same sort of thing, like

1144
00:54:11,960 --> 00:54:16,200
Speaker 2: your most sensitive personal financial details held in this database,

1145
00:54:16,280 --> 00:54:21,359
Speaker 2: and these you know, twenty year old Elon musk acolytes

1146
00:54:21,400 --> 00:54:24,520
Speaker 2: going in and rooting around and doing whatever. There's also

1147
00:54:24,600 --> 00:54:26,920
Speaker 2: questions about, okay, are they also going to have ReadWrite

1148
00:54:26,960 --> 00:54:30,440
Speaker 2: access to this system as well. But in addition, more

1149
00:54:30,440 --> 00:54:32,000
Speaker 2: to the point of what I was saying about what

1150
00:54:32,040 --> 00:54:35,360
Speaker 2: this project is really about. You know, the IRS certainly

1151
00:54:35,400 --> 00:54:40,280
Speaker 2: as an agency not beloved, let's be quite clear about that. However,

1152
00:54:40,480 --> 00:54:43,280
Speaker 2: it does get one of the best returns on investment

1153
00:54:43,400 --> 00:54:48,319
Speaker 2: of any government agency that exists. So the Trump administration

1154
00:54:48,400 --> 00:54:51,759
Speaker 2: expected to lay off thousands of IRS employees in the

1155
00:54:51,840 --> 00:54:55,680
Speaker 2: coming days. The IRS collected in twenty twenty four about

1156
00:54:55,719 --> 00:54:58,680
Speaker 2: five point one trillion dollars in revenue with a budget

1157
00:54:58,719 --> 00:55:01,520
Speaker 2: of twelve point three billion, and so again very high

1158
00:55:01,600 --> 00:55:06,320
Speaker 2: return on investment. And specifically there was you guys probably

1159
00:55:06,360 --> 00:55:09,160
Speaker 2: remember there's a big fight over the additional funds for

1160
00:55:09,239 --> 00:55:12,880
Speaker 2: IRS enforcement so that they can more effectively go after

1161
00:55:13,320 --> 00:55:17,400
Speaker 2: the millionaire and billionaire class. Because if you have fewer

1162
00:55:17,520 --> 00:55:20,440
Speaker 2: enforcement resources, guess who are the easiest people to go

1163
00:55:20,520 --> 00:55:23,680
Speaker 2: after your waitress who is not reporting all of her

1164
00:55:23,719 --> 00:55:27,040
Speaker 2: tipped income or whatever. They go after the lowest hanging

1165
00:55:27,080 --> 00:55:30,320
Speaker 2: through as a legitimate and horrible criticism of the IRS.

1166
00:55:30,560 --> 00:55:33,360
Speaker 2: So there's additional funds put in to try to enhance

1167
00:55:33,440 --> 00:55:37,000
Speaker 2: enforcement activities to more effectively go after billions, billionaires and

1168
00:55:37,040 --> 00:55:41,719
Speaker 2: millionaires for their tax cheat activities. And it was really successful.

1169
00:55:41,760 --> 00:55:45,319
Speaker 2: It secured nearly one hundred billion dollars through audits. That

1170
00:55:45,400 --> 00:55:48,200
Speaker 2: was an additional twenty five billion compared to the prior year.

1171
00:55:48,600 --> 00:55:50,880
Speaker 2: The IRS spent only thirty four cents for every one

1172
00:55:50,960 --> 00:55:54,879
Speaker 2: hundred dollars that was collected through these audits that were

1173
00:55:54,920 --> 00:55:58,520
Speaker 2: targeted at going after rich tax cheats, and a lot

1174
00:55:58,560 --> 00:56:02,000
Speaker 2: of that is being attempted to be rolled back, So

1175
00:56:02,120 --> 00:56:05,200
Speaker 2: again it's just a sort of blanket assault on government.

1176
00:56:05,520 --> 00:56:07,759
Speaker 2: And of course, if you're Elon Musk, if you're his

1177
00:56:07,840 --> 00:56:10,640
Speaker 2: billionaire friends and allies, et cetera, et cetera, you don't

1178
00:56:10,680 --> 00:56:12,880
Speaker 2: want the IRS to have the ability to audit your

1179
00:56:12,920 --> 00:56:15,839
Speaker 2: taxes and to be able to go after rich tax chiefs.

1180
00:56:15,880 --> 00:56:18,439
Speaker 2: You're happy to have them just going after the low

1181
00:56:18,480 --> 00:56:21,360
Speaker 2: hanging fruit, and that's the status quo that they're trying.

1182
00:56:21,200 --> 00:56:23,480
Speaker 1: To return to. Problem I always find here because I

1183
00:56:23,480 --> 00:56:25,480
Speaker 1: don't disagree with this single thing you said, and we

1184
00:56:25,520 --> 00:56:27,759
Speaker 1: talked a lot about that. The problem for me with

1185
00:56:27,800 --> 00:56:30,040
Speaker 1: the IRS is that they have so little public trust.

1186
00:56:30,160 --> 00:56:33,160
Speaker 1: It's not just about people who perceive about getting rich

1187
00:56:33,160 --> 00:56:35,200
Speaker 1: in the future and they don't want that. It's from

1188
00:56:35,239 --> 00:56:38,720
Speaker 1: their decades of going after people who are the lowest

1189
00:56:38,719 --> 00:56:41,560
Speaker 1: income bracket. You're multiple times more likely to get audited

1190
00:56:41,760 --> 00:56:43,839
Speaker 1: if you make less than twenty five thousand dollars, then

1191
00:56:43,880 --> 00:56:46,239
Speaker 1: if you make two point five million dollars, Now I

1192
00:56:46,280 --> 00:56:48,920
Speaker 1: mean statistic. People have tried to come at me on that.

1193
00:56:48,920 --> 00:56:50,759
Speaker 1: There's a lot more people who make less than twenty

1194
00:56:50,760 --> 00:56:54,560
Speaker 1: five thousand, et cetera. And you know, for in terms

1195
00:56:54,600 --> 00:56:57,760
Speaker 1: of their own enforcement. There are these automatically generated letters

1196
00:56:57,760 --> 00:56:59,719
Speaker 1: where they go after all of these people. But it's

1197
00:56:59,760 --> 00:57:01,360
Speaker 1: one of the most stressful events that a lot of

1198
00:57:01,400 --> 00:57:04,280
Speaker 1: people can go through. So they've burned all their public

1199
00:57:04,320 --> 00:57:07,920
Speaker 1: credibility over the years that Venmo thing, if you recall

1200
00:57:08,200 --> 00:57:11,200
Speaker 1: the six hundred dollars transaction limit to go after people

1201
00:57:11,200 --> 00:57:13,680
Speaker 1: like hairdressers and other folks who are getting tips and

1202
00:57:13,719 --> 00:57:17,480
Speaker 1: things off of Venmo. That burned a ton of public credibility.

1203
00:57:17,520 --> 00:57:20,280
Speaker 1: So a lot of people like just generally feel they'll

1204
00:57:20,320 --> 00:57:22,920
Speaker 1: like screw you, I don't care, which leaves it open

1205
00:57:23,000 --> 00:57:26,280
Speaker 1: to weaponization or gutting, you know, by a lot of

1206
00:57:26,320 --> 00:57:29,240
Speaker 1: people who are like elon. So this is this is

1207
00:57:29,240 --> 00:57:31,440
Speaker 1: my general thing with all of this is that because

1208
00:57:31,480 --> 00:57:34,560
Speaker 1: public trust is rock bottom and because people are so

1209
00:57:34,760 --> 00:57:37,600
Speaker 1: have lack of faith in the government, Yes, it absolutely

1210
00:57:37,720 --> 00:57:40,840
Speaker 1: opens the door for conflict of interest folks and others

1211
00:57:40,960 --> 00:57:43,360
Speaker 1: to use it to their own advantage. But it is

1212
00:57:43,400 --> 00:57:46,720
Speaker 1: incumbent upon people who are pro institution to not only

1213
00:57:46,760 --> 00:57:48,760
Speaker 1: have to make their case but prove to the public

1214
00:57:48,920 --> 00:57:50,440
Speaker 1: that they won't use it against them, and they have

1215
00:57:50,560 --> 00:57:52,640
Speaker 1: the track record is that they have used it against them.

1216
00:57:53,800 --> 00:57:57,439
Speaker 2: What I would say is there's a real parallel here

1217
00:57:58,280 --> 00:58:02,360
Speaker 2: with the crypto scam meme coins that we're going to

1218
00:58:02,400 --> 00:58:05,720
Speaker 2: talk about later that exciting, which is that they're you know,

1219
00:58:07,040 --> 00:58:09,200
Speaker 2: we're going to go through the whole thing. But one

1220
00:58:09,240 --> 00:58:11,160
Speaker 2: of the scammers who was involved with using that this

1221
00:58:11,280 --> 00:58:14,280
Speaker 2: long interview with Coffee sell and part of it, Coffee

1222
00:58:14,840 --> 00:58:18,080
Speaker 2: is pressing him on like, hey, you know, aren't these

1223
00:58:18,080 --> 00:58:20,920
Speaker 2: things basically just scams? And he's like, yeah, they're all

1224
00:58:21,360 --> 00:58:25,720
Speaker 2: They're all scams. They're all scammy you know, every single

1225
00:58:25,920 --> 00:58:29,760
Speaker 2: meme coin launch. It's the same sort of like rug pull,

1226
00:58:29,840 --> 00:58:33,840
Speaker 2: market manipulation, insider trading bullshit, that's the nature.

1227
00:58:33,600 --> 00:58:34,280
Speaker 1: Of what it is.

1228
00:58:34,880 --> 00:58:39,120
Speaker 2: His justification for that is, well, the regular financial system

1229
00:58:39,360 --> 00:58:43,240
Speaker 2: has scams too, and so you know the answer to that,

1230
00:58:43,600 --> 00:58:46,360
Speaker 2: in my humble opinion, isn't. So let's just have a

1231
00:58:46,400 --> 00:58:50,560
Speaker 2: completely lawless situation where we just scam people as much

1232
00:58:50,560 --> 00:58:53,440
Speaker 2: as we possibly want to and totally rig the system

1233
00:58:53,440 --> 00:58:56,320
Speaker 2: in favor of the of the rich. Instead, it's hey,

1234
00:58:56,400 --> 00:58:58,960
Speaker 2: how about we put more regulation, how we put more

1235
00:58:59,000 --> 00:59:02,040
Speaker 2: protections into place, How that we make the existing financial

1236
00:59:02,040 --> 00:59:06,680
Speaker 2: system more fair and less extractive and less corrupt, rather

1237
00:59:06,720 --> 00:59:08,840
Speaker 2: than just being like, so, let's just be as corrupt

1238
00:59:08,840 --> 00:59:11,440
Speaker 2: as we possibly can. And I think there's a similar

1239
00:59:11,480 --> 00:59:14,840
Speaker 2: mentality that you're describing when it comes to something like

1240
00:59:15,080 --> 00:59:18,360
Speaker 2: the IRS. Like, the problem with the IRS is that

1241
00:59:18,400 --> 00:59:22,960
Speaker 2: they have not gone after there are billions of dollars

1242
00:59:23,360 --> 00:59:27,400
Speaker 2: in unpaid taxes from millionaires and billionaires, that is who

1243
00:59:27,520 --> 00:59:30,960
Speaker 2: much of their enforcement should go after. But actually, because

1244
00:59:31,040 --> 00:59:35,880
Speaker 2: the IRS budget has been cut back over successive administrations

1245
00:59:36,240 --> 00:59:40,720
Speaker 2: that have bought into this libertarian or at least neoliberal

1246
00:59:41,000 --> 00:59:46,440
Speaker 2: idea of privatization and crushing the federal government, that's exactly

1247
00:59:46,480 --> 00:59:49,040
Speaker 2: how you end up in this situation to begin with,

1248
00:59:49,280 --> 00:59:52,880
Speaker 2: where they don't have the resources to effectively go after

1249
00:59:52,960 --> 00:59:55,720
Speaker 2: the millionaires and billionaires who have their own lawyers and

1250
00:59:55,760 --> 00:59:58,760
Speaker 2: who have much more complicated schemes for hiding their money

1251
00:59:58,960 --> 01:00:01,600
Speaker 2: versus the waitress who you know doesn't fully declare her

1252
01:00:01,600 --> 01:00:05,800
Speaker 2: tips or whatever. So what you're advocating for is actually

1253
01:00:05,840 --> 01:00:10,240
Speaker 2: just accelerating the very trajectory that has led us to

1254
01:00:10,400 --> 01:00:14,080
Speaker 2: this bad place to begin with, rather than trying to

1255
01:00:14,320 --> 01:00:17,280
Speaker 2: fix the problem and give them the resources they need

1256
01:00:17,480 --> 01:00:21,760
Speaker 2: to actually be an effective, you know, agency within government

1257
01:00:21,880 --> 01:00:24,439
Speaker 2: and be fair and equitable in the way that their

1258
01:00:24,560 --> 01:00:28,480
Speaker 2: enforcement is rolled out. So, you know, I do think

1259
01:00:28,520 --> 01:00:31,080
Speaker 2: you're you're right that that is part of the perception, don't.

1260
01:00:31,120 --> 01:00:33,480
Speaker 2: I don't deny about the public perception. What I would

1261
01:00:33,480 --> 01:00:35,439
Speaker 2: say is that the cure that is being offered here

1262
01:00:35,600 --> 01:00:38,920
Speaker 2: is actually what made the irs sick to begin with.

1263
01:00:39,440 --> 01:00:41,480
Speaker 2: This will just push it more in the direction of

1264
01:00:41,520 --> 01:00:44,640
Speaker 2: targeting those waitresses and you know, those people who.

1265
01:00:44,480 --> 01:00:47,000
Speaker 3: Are getting there like cash app or their venmo.

1266
01:00:46,840 --> 01:00:50,040
Speaker 2: Or whatever, and will make sure that Elon Musk and

1267
01:00:50,080 --> 01:00:51,800
Speaker 2: his buddies and people at the top end of the

1268
01:00:51,840 --> 01:00:56,040
Speaker 2: income bracket are unscathed. And so you know, that's why

1269
01:00:56,080 --> 01:00:58,200
Speaker 2: I think it's important for to try to explain those

1270
01:00:58,200 --> 01:01:01,400
Speaker 2: things and for people to understand what's happening here, not

1271
01:01:01,640 --> 01:01:03,320
Speaker 2: just going off with the vibes of like, well, I

1272
01:01:03,360 --> 01:01:05,520
Speaker 2: don't like the irs, so let's just destroy them.

1273
01:01:05,680 --> 01:01:07,400
Speaker 3: That's actually going to make things.

1274
01:01:07,360 --> 01:01:10,640
Speaker 2: Worse and make the irs worse, which again is part

1275
01:01:10,680 --> 01:01:12,680
Speaker 2: of the goal, and this is part of the goal

1276
01:01:12,800 --> 01:01:15,760
Speaker 2: of conservatives over years and years and years, which by

1277
01:01:15,760 --> 01:01:19,680
Speaker 2: the way, again Clinton was big into privatization like Democrats

1278
01:01:19,680 --> 01:01:22,680
Speaker 2: have participated as well. But the idea is, if you

1279
01:01:22,720 --> 01:01:26,200
Speaker 2: strip government of capacity and you make government fail, then

1280
01:01:26,240 --> 01:01:29,040
Speaker 2: people turn on government, and then you can further strip

1281
01:01:29,080 --> 01:01:32,080
Speaker 2: the government of capacity, and the people who really benefit

1282
01:01:32,640 --> 01:01:36,000
Speaker 2: are the very wealthy, because then the government cannot check

1283
01:01:36,040 --> 01:01:38,760
Speaker 2: their accesses, and then those social safety net programs that

1284
01:01:38,800 --> 01:01:41,280
Speaker 2: benefit you are always the first ones on the chopping block.

1285
01:01:41,400 --> 01:01:43,360
Speaker 1: I think I think it's well said. I just think

1286
01:01:43,360 --> 01:01:46,440
Speaker 1: it's a vicious political cycle because you can't prove your

1287
01:01:46,480 --> 01:01:50,480
Speaker 1: bona fides or credibility on this without the funding that

1288
01:01:50,480 --> 01:01:53,200
Speaker 1: you're talking about with the fund, it's a decade long problem.

1289
01:01:53,200 --> 01:01:54,640
Speaker 1: I want to save some of this for the crypto

1290
01:01:54,680 --> 01:01:56,760
Speaker 1: discussion because I still have a lot to say, Okay,

1291
01:01:57,160 --> 01:01:59,200
Speaker 1: people who want to get scammed, which we will get to.

1292
01:02:01,840 --> 01:02:03,960
Speaker 2: So in addition, we've had a bunch of attacks on

1293
01:02:04,440 --> 01:02:08,800
Speaker 2: well so OSHA is the Occupational Safety and Health Administration

1294
01:02:09,200 --> 01:02:12,040
Speaker 2: and actually, if we could go to B six first,

1295
01:02:12,360 --> 01:02:15,000
Speaker 2: Trump has put in and like maybe one of the

1296
01:02:15,000 --> 01:02:17,840
Speaker 2: worst people you could possibly put in to head the

1297
01:02:17,920 --> 01:02:21,760
Speaker 2: agency that is supposed to protect workers. This dude, David

1298
01:02:21,840 --> 01:02:24,720
Speaker 2: Keeling is his name comes from. He was the safety

1299
01:02:24,720 --> 01:02:29,240
Speaker 2: executive from UPS and Amazon. Now, if you've watched our

1300
01:02:29,280 --> 01:02:33,080
Speaker 2: coverage over the years, you know that UPS was in

1301
01:02:33,640 --> 01:02:37,240
Speaker 2: trouble because they didn't have air conditioning in their trucks

1302
01:02:37,520 --> 01:02:40,720
Speaker 2: and a worker literally died of heat exhaustion because these

1303
01:02:40,720 --> 01:02:44,200
Speaker 2: things bake in oven like conditions, like I'm talking one

1304
01:02:44,320 --> 01:02:47,480
Speaker 2: hundred and thirty degrees in the back of these trucks. Now,

1305
01:02:47,480 --> 01:02:50,920
Speaker 2: I do believe the new team stirs contracts, secured air conditioning,

1306
01:02:50,880 --> 01:02:55,600
Speaker 2: improved conditions. But he was overseeing UPS safety back when

1307
01:02:55,640 --> 01:02:58,960
Speaker 2: they were you know, cooking drivers alive. And then Amazon,

1308
01:02:59,240 --> 01:03:02,040
Speaker 2: like need I say more? They have the worst record

1309
01:03:02,240 --> 01:03:05,600
Speaker 2: of safety in the entire warehouse industry, something like forty

1310
01:03:05,680 --> 01:03:09,560
Speaker 2: one percent of their workers get injured on the job.

1311
01:03:09,840 --> 01:03:13,000
Speaker 2: He was specifically the company was cited numerous times for

1312
01:03:13,120 --> 01:03:17,040
Speaker 2: serious violations while he was the head of quote unquote

1313
01:03:17,200 --> 01:03:20,920
Speaker 2: safety at Amazon. So you've picked someone who's just a

1314
01:03:20,960 --> 01:03:24,400
Speaker 2: complete industry show. And then you know, let's put the

1315
01:03:24,480 --> 01:03:28,120
Speaker 2: one before this b five up on the screen. In addition,

1316
01:03:28,520 --> 01:03:33,480
Speaker 2: they've now taken down a bunch of workplace safety practice publications.

1317
01:03:33,920 --> 01:03:37,400
Speaker 2: And this is also very revealing SAGA because what they've

1318
01:03:37,400 --> 01:03:40,360
Speaker 2: done here is something they've done in other places with DOGE,

1319
01:03:40,360 --> 01:03:43,600
Speaker 2: which is they'll just search for words that are now

1320
01:03:43,680 --> 01:03:47,160
Speaker 2: on their band list, things like you know, diversity or

1321
01:03:47,200 --> 01:03:50,840
Speaker 2: equity or whatever. And a bunch of these workplace safety

1322
01:03:50,880 --> 01:03:54,760
Speaker 2: publications have nothing to do with anything DEI related. But

1323
01:03:54,880 --> 01:03:59,400
Speaker 2: as as one example, there was a guidelines for EMS

1324
01:03:59,440 --> 01:04:03,520
Speaker 2: agency that cited a quote diversity of state specific certification,

1325
01:04:03,600 --> 01:04:07,120
Speaker 2: training and regulatory requirements. And since it had the word diversity,

1326
01:04:07,480 --> 01:04:09,920
Speaker 2: even though it has nothing to do again with DEI,

1327
01:04:10,560 --> 01:04:15,160
Speaker 2: it just gets blanket taken down. I saw another another

1328
01:04:15,200 --> 01:04:18,040
Speaker 2: situation I think actually right here in Virginia and Spotsylvan Counts,

1329
01:04:18,080 --> 01:04:20,640
Speaker 2: not too far from here or from where I live,

1330
01:04:20,880 --> 01:04:26,200
Speaker 2: where a program to help disabled teenagers be able to

1331
01:04:26,280 --> 01:04:30,160
Speaker 2: transition to some sort of a job was blanket cut

1332
01:04:30,240 --> 01:04:33,560
Speaker 2: because it also, you know, used diversity in some other

1333
01:04:33,640 --> 01:04:36,560
Speaker 2: context or some other band word, and so they're just

1334
01:04:36,680 --> 01:04:39,440
Speaker 2: doing a blanket search for these terms, and even if

1335
01:04:39,480 --> 01:04:43,200
Speaker 2: it has nothing to do with DEI, just completely cutting

1336
01:04:43,360 --> 01:04:45,840
Speaker 2: and cutting it. And so that's another table.

1337
01:04:45,720 --> 01:04:48,080
Speaker 1: The Amazon one. I'm like, look, Jeff Bezos doesn't stand

1338
01:04:48,160 --> 01:04:50,960
Speaker 1: behind you for nothing, right. I think these guys they

1339
01:04:50,960 --> 01:04:53,200
Speaker 1: know what they're doing. This is we don't do we

1340
01:04:53,280 --> 01:04:56,520
Speaker 1: have the No, we don't the Steve Bannon oligarchy warning.

1341
01:04:56,600 --> 01:04:58,320
Speaker 1: I don't think we do. But no, he did a

1342
01:04:58,480 --> 01:05:01,919
Speaker 1: he this is exactly what he's talking about a lot

1343
01:05:01,920 --> 01:05:03,480
Speaker 1: of and you know, the crazy thing is is a

1344
01:05:03,480 --> 01:05:05,760
Speaker 1: lot of the promises and all those people have made

1345
01:05:06,280 --> 01:05:09,520
Speaker 1: for Trump and all that haven't even materialized. I talked previously,

1346
01:05:09,600 --> 01:05:13,720
Speaker 1: Zuckerberg promised to stop fact checking on Facebook and I

1347
01:05:13,880 --> 01:05:16,680
Speaker 1: literally got a fact check on my Instagram from one

1348
01:05:16,680 --> 01:05:19,840
Speaker 1: of his, like you know, news organizations. I'm only putting

1349
01:05:20,160 --> 01:05:24,240
Speaker 1: the two together because this was the reason that you

1350
01:05:24,320 --> 01:05:27,480
Speaker 1: had Bezos and all these other people stop the endorsement

1351
01:05:27,800 --> 01:05:31,040
Speaker 1: or stand behind Donald Trump at the inauguration. They do

1352
01:05:31,080 --> 01:05:34,240
Speaker 1: it because it's not just about cachet. It's they get

1353
01:05:34,240 --> 01:05:36,880
Speaker 1: something in return. That's what a lot of this is about.

1354
01:05:36,920 --> 01:05:39,920
Speaker 1: And I mean, I think quite a lot of that

1355
01:05:40,000 --> 01:05:42,320
Speaker 1: was pretty open before the election. A lot of it

1356
01:05:42,360 --> 01:05:45,400
Speaker 1: is pretty open right now. I mean in terms of

1357
01:05:45,600 --> 01:05:48,160
Speaker 1: will there be pushback and all of this other stuff,

1358
01:05:48,600 --> 01:05:50,920
Speaker 1: I'm not so sure not in the current media environment.

1359
01:05:51,040 --> 01:05:53,600
Speaker 2: There was some rules changes that came out at the

1360
01:05:53,640 --> 01:05:55,800
Speaker 2: National Labor Relations for too. We don't have an element

1361
01:05:55,840 --> 01:05:57,400
Speaker 2: for it, but some of the best things that the

1362
01:05:57,400 --> 01:06:02,120
Speaker 2: Biden administration did for labor organizing have been rolled back.

1363
01:06:02,200 --> 01:06:05,200
Speaker 2: So things like they banned captive audience meetings, which is

1364
01:06:05,280 --> 01:06:07,360
Speaker 2: like just you know, you have to you force your

1365
01:06:07,400 --> 01:06:09,960
Speaker 2: workers to go and sit through some union busting speech.

1366
01:06:10,400 --> 01:06:13,800
Speaker 2: Captive audience meetings are back. The rule that they put

1367
01:06:13,800 --> 01:06:18,120
Speaker 2: out about non companning non competes, so giving workers more flexibility,

1368
01:06:18,200 --> 01:06:20,920
Speaker 2: more ability to you know, manoeuver and change jobs whatever,

1369
01:06:21,280 --> 01:06:24,560
Speaker 2: that also is rescinded. So they're you know, rolling back

1370
01:06:24,640 --> 01:06:27,760
Speaker 2: even the the you know, some of these things were significant,

1371
01:06:27,800 --> 01:06:30,080
Speaker 2: but even the more minimal changes that were made in

1372
01:06:30,120 --> 01:06:33,240
Speaker 2: favor of workers and labor under the Biden administration are

1373
01:06:33,240 --> 01:06:35,720
Speaker 2: being rolled back. And this again where you know, I

1374
01:06:35,760 --> 01:06:37,840
Speaker 2: mean Trump went out in a garbage truck and worked

1375
01:06:37,880 --> 01:06:40,720
Speaker 2: at McDonald's and talked a big game about labor, and

1376
01:06:40,760 --> 01:06:42,280
Speaker 2: there was all this rudder, Oh, it's going to be

1377
01:06:42,280 --> 01:06:45,040
Speaker 2: different with Republicans. The labor unions like you should never

1378
01:06:45,080 --> 01:06:46,920
Speaker 2: have bought that bullshit. Donald Trump has always been a

1379
01:06:47,240 --> 01:06:50,400
Speaker 2: union buster, he'd always been a strike breaker. Yeah, but well,

1380
01:06:50,400 --> 01:06:53,080
Speaker 2: I mean, Sean O'Brien seems like he did so some people.

1381
01:06:53,200 --> 01:06:55,480
Speaker 2: Some people did for sure, and you had this was

1382
01:06:55,600 --> 01:06:59,240
Speaker 2: part of a strategy to convince union workers to drop

1383
01:06:59,280 --> 01:07:01,520
Speaker 2: their long time so she went Democratic cross and vote

1384
01:07:01,560 --> 01:07:04,520
Speaker 2: for Trump because he was going to be different on labor.

1385
01:07:05,000 --> 01:07:07,840
Speaker 2: And that is like, very plainly not the case of.

1386
01:07:07,920 --> 01:07:09,400
Speaker 1: Well, it's just one of those where I'm not going

1387
01:07:09,480 --> 01:07:11,680
Speaker 1: to tell a union guy what to do. Clearly he

1388
01:07:11,720 --> 01:07:13,640
Speaker 1: doesn't give a shit about the NLRB, or he would

1389
01:07:13,680 --> 01:07:16,000
Speaker 1: have voted one hundred percent for Joe Biden and for

1390
01:07:16,200 --> 01:07:19,160
Speaker 1: Kamala Harris. They've got other things that they hold important,

1391
01:07:19,160 --> 01:07:24,000
Speaker 1: culture stuff, wars, manufacturing, tariffs, general vibe, and they decided

1392
01:07:24,320 --> 01:07:26,760
Speaker 1: that's important. I mean, I think it was pretty good.

1393
01:07:27,000 --> 01:07:29,040
Speaker 2: But don't you think having Sean O'Brien at the RNC

1394
01:07:29,240 --> 01:07:31,440
Speaker 2: was an attempt to convince them that Trump would be

1395
01:07:31,440 --> 01:07:32,320
Speaker 2: different on labor.

1396
01:07:32,440 --> 01:07:35,440
Speaker 1: Because Seawan O'Brien smartly looked at the poll of his

1397
01:07:35,480 --> 01:07:37,440
Speaker 1: own voters and said, oh shit, half of these guys

1398
01:07:37,480 --> 01:07:39,080
Speaker 1: are going to vote for Trump anyway, and I want

1399
01:07:39,080 --> 01:07:41,600
Speaker 1: to burn any ability of me to be actually the

1400
01:07:41,640 --> 01:07:43,440
Speaker 1: get in the room. You want to be shut out

1401
01:07:43,440 --> 01:07:45,280
Speaker 1: of the door, or at least have one foot in

1402
01:07:45,320 --> 01:07:47,600
Speaker 1: that door. I'd rather have at least one foot if

1403
01:07:47,640 --> 01:07:50,280
Speaker 1: my job is to represent the union. He can't control

1404
01:07:50,360 --> 01:07:51,480
Speaker 1: what all of his people do.

1405
01:07:51,640 --> 01:07:54,360
Speaker 2: No, I mean he could have made the case. I

1406
01:07:54,400 --> 01:07:56,760
Speaker 2: mean he's in a leadership position. So you do what

1407
01:07:56,840 --> 01:07:59,600
Speaker 2: a leader does, and you make the case for why listen.

1408
01:07:59,640 --> 01:08:01,760
Speaker 2: You can vot however you want, if like guns or

1409
01:08:01,840 --> 01:08:04,000
Speaker 2: gays or whatever is most important to you, you vote

1410
01:08:04,000 --> 01:08:04,600
Speaker 2: how you want.

1411
01:08:04,760 --> 01:08:05,400
Speaker 3: But in terms of.

1412
01:08:05,440 --> 01:08:08,640
Speaker 2: Labor issues, here's the track record. It's pretty clear cut

1413
01:08:08,800 --> 01:08:12,480
Speaker 2: with the Biden administration versus the previous Trump administration. And

1414
01:08:12,560 --> 01:08:14,760
Speaker 2: so yeah, I think he comes off looking like a

1415
01:08:14,760 --> 01:08:18,080
Speaker 2: fool because they're union busting even more aggressively than they

1416
01:08:18,120 --> 01:08:20,799
Speaker 2: did before. But that's not even my point. My point

1417
01:08:20,920 --> 01:08:23,599
Speaker 2: is that the whole reason that Trump and the RNC

1418
01:08:23,800 --> 01:08:26,439
Speaker 2: invited Sean O'Brien to speak at the R and C

1419
01:08:26,640 --> 01:08:28,880
Speaker 2: was to try to create an impression that they were

1420
01:08:28,880 --> 01:08:31,200
Speaker 2: going to be different on labor, when clearly they are

1421
01:08:31,200 --> 01:08:33,000
Speaker 2: not different on labor whatsoever.

1422
01:08:33,040 --> 01:08:34,799
Speaker 1: I don't know. I think people who look more foolish

1423
01:08:34,840 --> 01:08:38,400
Speaker 1: are those who like constantly preach at their own union

1424
01:08:38,439 --> 01:08:40,120
Speaker 1: members and tell them what to do, and then they

1425
01:08:40,200 --> 01:08:42,400
Speaker 1: keep not voting for them, or they're moving more in

1426
01:08:42,439 --> 01:08:43,799
Speaker 1: the Republican directly.

1427
01:08:43,800 --> 01:08:47,559
Speaker 2: But isn't their job to its not telling people what

1428
01:08:47,640 --> 01:08:51,360
Speaker 2: to do. But the law idea is you make if

1429
01:08:51,360 --> 01:08:55,400
Speaker 2: you are in a leadership position, explaining the very clear

1430
01:08:56,040 --> 01:09:00,720
Speaker 2: difference in the track record on labor specific issues between

1431
01:09:01,400 --> 01:09:05,360
Speaker 2: Joe Biden, Kamala Harris and the Trump administration. Yeah, I

1432
01:09:05,360 --> 01:09:07,960
Speaker 2: think is your job to explain those difference as people

1433
01:09:07,960 --> 01:09:10,560
Speaker 2: can do with that what they want, But to equivocate

1434
01:09:10,760 --> 01:09:12,640
Speaker 2: and pretend like, oh, he's going to be good on

1435
01:09:12,760 --> 01:09:15,040
Speaker 2: labor or actually it's the Democrats who are worse, Like

1436
01:09:15,080 --> 01:09:16,080
Speaker 2: that was just a lie.

1437
01:09:16,160 --> 01:09:16,800
Speaker 1: So then you're just.

1438
01:09:16,840 --> 01:09:19,719
Speaker 2: Lying to your members and you're confusing them about the choice.

1439
01:09:19,760 --> 01:09:21,240
Speaker 2: You're not helping them to make a better desires.

1440
01:09:21,280 --> 01:09:22,760
Speaker 1: I don't think that. And again this is the problem

1441
01:09:22,800 --> 01:09:25,200
Speaker 1: with union leadership. They've been you know, sucking at the

1442
01:09:25,240 --> 01:09:28,280
Speaker 1: Democratic teat for forty years or whatever, and they've lost

1443
01:09:28,360 --> 01:09:33,080
Speaker 1: all their membership and they keep endorsings. Also support also

1444
01:09:33,120 --> 01:09:35,599
Speaker 1: are endorse in Sea Spires and Gaza, which is pretty

1445
01:09:35,600 --> 01:09:38,720
Speaker 1: stupid or c spire or BLM protests or any of

1446
01:09:38,760 --> 01:09:41,200
Speaker 1: this to keep on signing on to socially liberal causes

1447
01:09:41,200 --> 01:09:44,000
Speaker 1: and lo and behold, but membership starts going.

1448
01:09:44,160 --> 01:09:46,439
Speaker 2: Is the exact opposite of that songer, which is that

1449
01:09:46,840 --> 01:09:49,800
Speaker 2: you're saying that, oh, well, they should just you know,

1450
01:09:50,200 --> 01:09:53,559
Speaker 2: because their members are more culturally conservative, they should focus

1451
01:09:53,560 --> 01:09:56,960
Speaker 2: on those cultural values. What I'm saying is actually they

1452
01:09:57,000 --> 01:10:01,640
Speaker 2: needed to be more specific about the economic labor related

1453
01:10:01,720 --> 01:10:05,880
Speaker 2: like directly related to their unions. And you know, that's

1454
01:10:05,920 --> 01:10:08,760
Speaker 2: where I think there was a real failure to communicate

1455
01:10:08,800 --> 01:10:12,880
Speaker 2: from Sean O'Brien specifically the very clear differences when it

1456
01:10:12,920 --> 01:10:16,479
Speaker 2: comes to union organizing. I mean, the Nationally Relations Board

1457
01:10:16,560 --> 01:10:18,840
Speaker 2: under Trump now is not even defending its own right

1458
01:10:18,920 --> 01:10:21,599
Speaker 2: to exist. It has been gutted so that it cannot

1459
01:10:21,600 --> 01:10:24,720
Speaker 2: even function because they don't have a quorum. You know,

1460
01:10:24,720 --> 01:10:29,080
Speaker 2: they're probably illegally removed from This is an ongoing court case,

1461
01:10:29,080 --> 01:10:31,639
Speaker 2: but in any case, they've gutted it so it cannot

1462
01:10:31,680 --> 01:10:35,880
Speaker 2: even advance any of the claims of union busting and

1463
01:10:35,960 --> 01:10:40,160
Speaker 2: other illegal behavior like. That's so, and this was all

1464
01:10:40,320 --> 01:10:43,519
Speaker 2: very predictable to your point about people knowing what they

1465
01:10:43,520 --> 01:10:46,360
Speaker 2: were getting and if you weren't telling your union members that,

1466
01:10:46,400 --> 01:10:48,360
Speaker 2: if you weren't making that clear. And again, people can

1467
01:10:48,400 --> 01:10:49,920
Speaker 2: do with that information whatever they want. If there are

1468
01:10:49,960 --> 01:10:51,960
Speaker 2: other issues that are more important to them, that's fine.

1469
01:10:52,200 --> 01:10:54,200
Speaker 2: But if you aren't making that clear, you are just

1470
01:10:54,280 --> 01:10:56,479
Speaker 2: lying to your members, You are confusing them, and you

1471
01:10:56,479 --> 01:10:57,280
Speaker 2: are failing at your job.

1472
01:10:57,320 --> 01:10:59,280
Speaker 1: I bring it back to the government point I made,

1473
01:10:59,360 --> 01:11:01,519
Speaker 1: is it because they lost so much credibility with their

1474
01:11:01,600 --> 01:11:04,080
Speaker 1: leadership or with their member base, which is basically what

1475
01:11:04,120 --> 01:11:07,040
Speaker 1: has happened with the divergence of the leadership basically just

1476
01:11:07,080 --> 01:11:10,000
Speaker 1: being career as Democrats and the rest of their guys

1477
01:11:10,040 --> 01:11:12,720
Speaker 1: twenty sixteen onwards voting more and more for Trump. They

1478
01:11:12,720 --> 01:11:15,840
Speaker 1: don't have any trust individually on that basis. The reason

1479
01:11:15,880 --> 01:11:19,320
Speaker 1: I'll defend O'Brien is because O'Brien's tried to hold on

1480
01:11:19,360 --> 01:11:22,080
Speaker 1: to some credibility with an administration which but won the

1481
01:11:22,080 --> 01:11:25,360
Speaker 1: popular vote all seven swing states and not willing to

1482
01:11:25,360 --> 01:11:28,360
Speaker 1: say one hundred percent or sorry, fifty percent of his

1483
01:11:28,520 --> 01:11:31,479
Speaker 1: union members, but a very good number of them. So

1484
01:11:31,920 --> 01:11:34,280
Speaker 1: you know, you have to follow where your people are.

1485
01:11:34,360 --> 01:11:36,519
Speaker 1: You're a representative of them. You don't just work for

1486
01:11:36,600 --> 01:11:40,479
Speaker 1: some NLRB worship, like, you have to actually clearly listen

1487
01:11:40,720 --> 01:11:44,400
Speaker 1: to your union voting base and say, well, clearly, these

1488
01:11:44,439 --> 01:11:46,080
Speaker 1: guys like Trump, so I need to figure out a

1489
01:11:46,120 --> 01:11:49,200
Speaker 1: worry to work with them. So I just think it's

1490
01:11:49,520 --> 01:11:52,600
Speaker 1: the same structural problem from the government direction and on

1491
01:11:52,720 --> 01:11:55,320
Speaker 1: the union front. I just come back to this on

1492
01:11:55,360 --> 01:11:58,719
Speaker 1: the NLRB. If people really cared the union voters about NLRB,

1493
01:11:58,800 --> 01:12:00,800
Speaker 1: and they probably know more about it even then I do.

1494
01:12:01,360 --> 01:12:03,360
Speaker 1: Then a lot of these union other people who talk

1495
01:12:03,360 --> 01:12:05,519
Speaker 1: about it online and they still voted for Trump. What

1496
01:12:05,560 --> 01:12:07,360
Speaker 1: does that tell you they don't actually care that much.

1497
01:12:07,439 --> 01:12:09,439
Speaker 2: But Sager is not all it is never will be

1498
01:12:09,800 --> 01:12:13,360
Speaker 2: union like, belonging to a union is still one of

1499
01:12:13,400 --> 01:12:18,320
Speaker 2: the biggest indicators of voting Democrats. So obviously it does

1500
01:12:18,360 --> 01:12:21,800
Speaker 2: still matter to a lot of union members. And all

1501
01:12:21,840 --> 01:12:25,600
Speaker 2: I'm saying is that if you were not explaining the

1502
01:12:25,640 --> 01:12:29,240
Speaker 2: differences between these two candidates when it comes to union

1503
01:12:29,360 --> 01:12:34,360
Speaker 2: issues specifically, then you were not being honest about the

1504
01:12:34,439 --> 01:12:38,160
Speaker 2: choice in this election. And listen, he wanted to preserve

1505
01:12:38,240 --> 01:12:40,479
Speaker 2: his access and his ability to get in the room.

1506
01:12:40,600 --> 01:12:42,720
Speaker 2: Whatever congratulations you did at you were invited to the

1507
01:12:42,720 --> 01:12:44,519
Speaker 2: inauguration you're on Trump's good list.

1508
01:12:44,720 --> 01:12:45,760
Speaker 3: You accomplished your goal.

1509
01:12:46,120 --> 01:12:49,240
Speaker 2: But if your goal was to help people understand what

1510
01:12:49,360 --> 01:12:53,479
Speaker 2: the differences were between these two candidates on labor issues specifically, you.

1511
01:12:53,479 --> 01:12:54,400
Speaker 3: Did not accomplish that.

1512
01:12:54,640 --> 01:12:57,240
Speaker 2: You confuse people, you were not honest about what the

1513
01:12:57,320 --> 01:13:00,799
Speaker 2: clear difference was. And now you've got an This is important,

1514
01:13:00,880 --> 01:13:04,080
Speaker 2: especially for the teamsters because they're trying to organize Amazon.

1515
01:13:04,960 --> 01:13:06,880
Speaker 2: One of the things that matters a lot for that

1516
01:13:07,400 --> 01:13:11,480
Speaker 2: is that the drivers Amazon drivers be classified as employees

1517
01:13:11,920 --> 01:13:17,080
Speaker 2: of Amazon. That was something that the Biden administration, Biden

1518
01:13:17,120 --> 01:13:21,400
Speaker 2: Harris administration was in favor of, and the Trump administration.

1519
01:13:20,960 --> 01:13:23,400
Speaker 3: Is opposed to. So you've just set back.

1520
01:13:23,240 --> 01:13:27,280
Speaker 2: Even your own organizing efforts in terms of trying to

1521
01:13:27,640 --> 01:13:31,519
Speaker 2: unionize Amazon. So you know, I'm also just not gonna

1522
01:13:31,520 --> 01:13:34,200
Speaker 2: I'm not going to buy this was some noble attempt

1523
01:13:34,280 --> 01:13:36,280
Speaker 2: to like, you know, represent his members. I think he

1524
01:13:36,360 --> 01:13:38,679
Speaker 2: wanted to be in the room. I think he wanted

1525
01:13:38,680 --> 01:13:40,880
Speaker 2: that invite to the inauguration. I think he wanted to

1526
01:13:40,920 --> 01:13:42,439
Speaker 2: be buddy buddy here, and you like.

1527
01:13:42,600 --> 01:13:44,800
Speaker 1: I mean, I'd rather be him than some idiot on

1528
01:13:44,880 --> 01:13:47,080
Speaker 1: the on some idiot preaching next to.

1529
01:13:47,120 --> 01:13:49,679
Speaker 2: High wouldn't because at least I didn't lie to my members.

1530
01:13:49,760 --> 01:13:51,200
Speaker 1: I don't think he lied to his members. He didn't

1531
01:13:51,439 --> 01:13:51,880
Speaker 1: what he did.

1532
01:13:52,120 --> 01:13:55,760
Speaker 2: Yeah, he was very I think it was very deceitful

1533
01:13:56,160 --> 01:13:58,880
Speaker 2: the way that he portrayed the Democrats as the real

1534
01:13:59,040 --> 01:14:02,000
Speaker 2: opposition to labor. And I'm not here to cape for Democrats.

1535
01:14:02,080 --> 01:14:04,240
Speaker 2: Lord knows, I've been critical as well. But if you

1536
01:14:04,320 --> 01:14:06,439
Speaker 2: look over the past number of decades, like there's a

1537
01:14:06,520 --> 01:14:10,000
Speaker 2: reason why the unions at this point do typically always

1538
01:14:10,080 --> 01:14:13,720
Speaker 2: endorse Democrats, it's because Repulicans hate them and want them

1539
01:14:13,720 --> 01:14:15,800
Speaker 2: to not exist. Like Elon Musk, who is in charge

1540
01:14:15,800 --> 01:14:18,240
Speaker 2: of our government now doesn't think the National Labor Relations

1541
01:14:18,280 --> 01:14:21,360
Speaker 2: Board should exist and hates unions and thinks they should

1542
01:14:21,360 --> 01:14:24,160
Speaker 2: all be illegal. So like, yeah, you're not going to

1543
01:14:24,200 --> 01:14:26,519
Speaker 2: You shouldn't back that person because they think you, they

1544
01:14:26,600 --> 01:14:28,040
Speaker 2: hate you, and they think you should die.

1545
01:14:28,520 --> 01:14:30,639
Speaker 1: I think that the Teamsters in the long run, will

1546
01:14:30,640 --> 01:14:33,000
Speaker 1: probably be indicated because they're going to get something out

1547
01:14:33,040 --> 01:14:35,160
Speaker 1: of the Trump administration that the rest of these guys

1548
01:14:35,160 --> 01:14:37,559
Speaker 1: whispering in Hakim Jeffrey's years are not going to get.

1549
01:14:37,800 --> 01:14:40,479
Speaker 1: And that's probably better than absolutely nothing. So I don't

1550
01:14:40,520 --> 01:14:41,400
Speaker 1: blame Jean O'Brien.

1551
01:14:41,479 --> 01:14:45,800
Speaker 2: They got a Department of Labor nominee secretary who's who

1552
01:14:46,120 --> 01:14:51,639
Speaker 2: has a very bad AFLCIO supported the program, but it's

1553
01:14:51,640 --> 01:14:54,679
Speaker 2: completely irreal, irrelevant. Now that the National Labor Relations Board

1554
01:14:54,720 --> 01:14:56,560
Speaker 2: is gutted and headed to the Supreme Court to be

1555
01:14:56,560 --> 01:14:57,680
Speaker 2: deemed unconstable, we're not.

1556
01:14:57,600 --> 01:14:59,800
Speaker 1: Even one month in the Trump administration. Yeah, over forty

1557
01:15:00,080 --> 01:15:03,120
Speaker 1: already clear over a four year clear a four year period.

1558
01:15:03,160 --> 01:15:05,759
Speaker 1: I am absolutely certain O'Brien will be much more vindicated

1559
01:15:05,760 --> 01:15:08,160
Speaker 1: than the rest of these people were completely shut out

1560
01:15:08,200 --> 01:15:09,680
Speaker 1: of government. So if you want to be bitching on

1561
01:15:09,720 --> 01:15:12,240
Speaker 1: the sidelines, like okay, I mean, good luck to you

1562
01:15:12,439 --> 01:15:15,559
Speaker 1: while your union membership continues to decline, your own and

1563
01:15:15,640 --> 01:15:18,519
Speaker 1: your own people continue to vote against the things that

1564
01:15:18,560 --> 01:15:20,360
Speaker 1: you tell them to do. I just that's where I

1565
01:15:20,439 --> 01:15:22,920
Speaker 1: keep coming back to. It's like, clearly you are you

1566
01:15:23,000 --> 01:15:26,000
Speaker 1: do not have credibility with your own voting base. Now,

1567
01:15:26,120 --> 01:15:28,360
Speaker 1: union is still one of the best predictors, but highest

1568
01:15:28,360 --> 01:15:30,680
Speaker 1: percentage of union members going for Trump, I think, was

1569
01:15:30,680 --> 01:15:32,559
Speaker 1: in the twenty twenty four election, which was a trend

1570
01:15:32,600 --> 01:15:35,200
Speaker 1: that started in twenty sixteen. We should learn from that.

1571
01:15:35,240 --> 01:15:38,320
Speaker 1: It's also very I think patronizing to try and tell people,

1572
01:15:38,439 --> 01:15:40,360
Speaker 1: and LRB is the only thing that matters when the

1573
01:15:40,400 --> 01:15:43,200
Speaker 1: Democrats say that, no, but but for them, they get

1574
01:15:43,200 --> 01:15:46,960
Speaker 1: to decide that immigration, tariffs, manufacturing, and altern all of them.

1575
01:15:46,960 --> 01:15:47,720
Speaker 3: I'm not saying that.

1576
01:15:47,840 --> 01:15:49,800
Speaker 2: What I'm saying is that if you are not being

1577
01:15:49,880 --> 01:15:52,600
Speaker 2: honest that this man is a union buster and a

1578
01:15:52,640 --> 01:15:55,719
Speaker 2: strike brigger and was celebrating with Elon Musk Elon Musk

1579
01:15:55,800 --> 01:15:58,559
Speaker 2: breaking strikes, if you were if you did not know

1580
01:15:59,200 --> 01:16:02,800
Speaker 2: that the utting of the NLRB was coming and that

1581
01:16:02,840 --> 01:16:06,719
Speaker 2: he was going to return to his longtime union busting ways,

1582
01:16:07,000 --> 01:16:09,519
Speaker 2: and you were not being honest about that, then you

1583
01:16:09,600 --> 01:16:10,400
Speaker 2: are a fool.

1584
01:16:10,720 --> 01:16:11,559
Speaker 3: That's what I'm saying.

1585
01:16:11,840 --> 01:16:14,160
Speaker 2: Same way you're saying that people were like, oh, I

1586
01:16:14,200 --> 01:16:16,280
Speaker 2: didn't think they'd be raiding the workplaces, Like you're a

1587
01:16:16,320 --> 01:16:20,439
Speaker 2: fool too, because the track record is incredibly clear. So

1588
01:16:20,520 --> 01:16:22,599
Speaker 2: if you are the leader of a union, then yes,

1589
01:16:22,680 --> 01:16:26,080
Speaker 2: I think definitionally your number one priority should be labor issues,

1590
01:16:26,400 --> 01:16:28,720
Speaker 2: and if you're not being honest about those, then you're

1591
01:16:28,760 --> 01:16:31,400
Speaker 2: a liar and you're a fool, and you're actually misleading

1592
01:16:31,439 --> 01:16:34,840
Speaker 2: people versus helping to clarify and allow them to make

1593
01:16:34,880 --> 01:16:37,560
Speaker 2: their own educated decisions based on whatever it is.

1594
01:16:37,600 --> 01:16:39,720
Speaker 3: The range of issues that they care about are