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Speaker 1: Cable news is ripping us apart, dividing the nation, making

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Speaker 1: it impossible to function as a society and to know

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Speaker 1: what is true and what is false. The good news

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Speaker 1: is that they're failing and they know it. That is

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Speaker 1: why we're building something new. Be part of creating a new, better, healthier,

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Speaker 1: and more trustworthy mainstream by becoming a Breaking Points Premium

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Speaker 1: member today at breakingpoints dot com. Your hard earned money

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Speaker 1: is going to help us build for the midterms and

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Speaker 1: the upcoming presidential election so we can provide unparalleled coverage

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Speaker 1: of what is sure to be one of the most

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Speaker 1: pivotal moments in American history. So what are you waiting for?

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Speaker 1: Go to Breakingpoints dot com to help us out. Good morning, everybody,

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Speaker 1: Happy Thursday. We have an amazing show for everybody today.

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Speaker 1: What do we have, Krystal. Indeed, we do many things

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Speaker 1: to get to not least of which mister and Jettie

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Speaker 1: over here found Ousel of the Center totally unintentionally in

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Speaker 1: the middle of an Elon Musk and Washington postorm So

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Speaker 1: we will definitely have those details for you. But in addition,

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Speaker 1: the Biden administration now actually contemplating maybe canceling some significant

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Speaker 1: amount of student debt, will take you through the arguments

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Speaker 1: for and against and what they are actually thinking. We

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Speaker 1: also have the details on what is a crazy story

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Speaker 1: of potential financial fraud. This is insane, yes, and some

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Speaker 1: actual maybe a little bit of Wall Street accountability. Here.

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Speaker 1: We will see some new developments with mister Cawthorn speaking

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Speaker 1: of financial fraud, allegations that Congressman Madison Cawthorn is at

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Speaker 1: the center of an insider trading scheme regarding a let's

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Speaker 1: go Brandon crypto something. We'll get into it. Yeah, it's

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Speaker 1: kind of it's like a little bit too perfect. And

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Speaker 1: then we also have Bernie Sanders putting a lot of

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Speaker 1: pressure on Biden to use the power of the federal

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Speaker 1: garment to say, listen to Amazon, if you are going

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Speaker 1: to illegally union bus, you're not going to get this

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Speaker 1: ten billion dollar cloud computing contract from the federal government.

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Speaker 1: That's something we've been covering here. The Biden coming in,

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Speaker 1: he promised explicitly that he would do exactly that, that

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Speaker 1: no federal government contracts would go to companies engage in

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Speaker 1: legal union busting. So Bernie calling him out, asking him

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Speaker 1: to actually stick to his campaign promise. There we also

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Speaker 1: have David dan On to give us an update on

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Speaker 1: where exactly we are in terms of inflation and the

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Speaker 1: supply chain crisis. So lots to get to this morning,

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Speaker 1: but we do want to start SAGA with the very

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Speaker 1: latest from the whole Elon Musk taking over Twitter saga.

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Speaker 1: That's right, okay, So we gave you guys all the

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Speaker 1: details of the actual purchase, and basically, I think the

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Speaker 1: story of the last forty eight hours is both the

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Speaker 1: freak out of the press, which we will get to,

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Speaker 1: but also how Elon is approaching Twitter and he's subtweeting

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Speaker 1: both the executives but also really the product itself. So

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Speaker 1: let's start with the product and let's put that up

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Speaker 1: there on the screen. So Elon, in one of very

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Speaker 1: noticed tweets, said truth Social is currently beating Twitter and

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Speaker 1: TikTok on the Apple app store. Let's go ahead and

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Speaker 1: put his next response on there on the screen, going

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Speaker 1: after truth Social, specifically saying truth Social terrible name exists

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Speaker 1: because Twitter censored free speech. He follows up saying it

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Speaker 1: should be called Trumpet instead, which actually is a decent

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Speaker 1: enough name. But the point that he's trying to make

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Speaker 1: there is that this entire extended universe of so called

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Speaker 1: free speech. Twitter alternatives only exists because Twitter did not

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Speaker 1: abide by the principles of free speech. So he's pointing

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Speaker 1: correctly to the fact that truth Social exists because Trump

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Speaker 1: was booted off of Twitter, the fact that gab exists

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Speaker 1: also because of mass cancelation the parlor. I guess does

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Speaker 1: it still exist. I'm not exactly sure. Anyway, it existed

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Speaker 1: for a period of time of which it was semi popular,

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Speaker 1: and then I think that we have Getter now as well.

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Speaker 1: I know that there's another blockchain one called Minds. That's

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Speaker 1: the only one that actually seemed kind of interesting to me. However,

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Speaker 1: the guys were on the Joe Rogan podcast, and I

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Speaker 1: remember listening to it being extraordinarily skeptical, and I said, oh,

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Speaker 1: you know, these guys actually seem interested because it was

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Speaker 1: a blockchain thing. It's decentralized technology, and also they abide

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Speaker 1: by a true First Amendment censorship type policy, so that's

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Speaker 1: obviously something that I support. However, I think what Elon

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Speaker 1: is getting at is that he wants to neuter as

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Speaker 1: the new head of the platform whenever the Steel eventually

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Speaker 1: does close the ability for the Trumps of the world

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Speaker 1: and the adjason Millers of the world over at Getter

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Speaker 1: and others in order to try and grift off of

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Speaker 1: and take off these pieces of the audience. The point

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Speaker 1: that we have tried to make explicitly, the benefit of

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Speaker 1: Twitter is that everybody is on it. The benefit of

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Speaker 1: Facebook is that everybody is on it. The problem is

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Speaker 1: that when you have the lesser network effects on these

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Speaker 1: smaller platforms, they're just not as useful, because that's where

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Speaker 1: the true value of the product actually comes from. They're

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Speaker 1: not as useful, and frankly, they're not as fun. No,

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Speaker 1: they're not, as you are finding out, like what fun

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Speaker 1: is Twitter? Without being able to own the list, the

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Speaker 1: limbs aren't there and you don't get to see them

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Speaker 1: like freak out or whatever you're provocation. So the cons

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Speaker 1: freak out all the time. It's fun to say, very true,

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Speaker 1: very true. So you have to have a diverse ideological

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Speaker 1: array of individuals to trigger on any of these social

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Speaker 1: media sites for them to really be interesting and worthwhile.

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Speaker 1: You know, it's funny because especially that you know the

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Speaker 1: tweet that he's sent of like true social terrible name

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Speaker 1: exists because Twitter censored free speech it sounds like a

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Speaker 1: very Trumpian, oh tweet, which made me realize that, I mean,

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Speaker 1: Elon has really Trump used to be the king of Twitter.

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Speaker 1: Elon has really supplanted him. Oh absolutely. And so even

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Speaker 1: though in certain ways, like obviously it's disproportioning the right

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Speaker 1: end of the political spectrum that's really celebrating this and

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Speaker 1: hoping they bring Trump back and all of these things,

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Speaker 1: this is kind of a mixed bag for Trump himself

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Speaker 1: because he has he has these competing interests. Of number one,

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Speaker 1: you know, if he's uh, he's allowed back on the platform,

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Speaker 1: but that will completely kneecap his financial investment here exactly

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Speaker 1: at truth social the fact that Elon has kind of

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Speaker 1: won uped him now in the the sort of king

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Speaker 1: of Twitter department, so he doesn't have that same hold

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Speaker 1: over the platform that he once did. So I do

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Speaker 1: think it's kind of a mixed bag for him personally.

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Speaker 1: Not to mention, as we've pointed out here many times,

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Speaker 1: I don't know that it was bad for his brand

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Speaker 1: to not be on Twitter and not have his like

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Speaker 1: obnoxious musings in our face every single day. So we'll

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Speaker 1: see how he ultimately handles this. Obviously, he has they

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Speaker 1: all have to pretend like they like it. Yes, they

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Speaker 1: have to pretend like they're happy, that they're really glad that,

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Speaker 1: you know, free speech might return to Twitter, and I

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Speaker 1: think there's a lot of caveats around that and a

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Speaker 1: lot of questions whether that'll actually happen. But they have

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Speaker 1: to pretend like they like it, even though you know,

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Speaker 1: for many of these people who have been involved with

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Speaker 1: some of these various you know, alternative free speech platforms,

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Speaker 1: it's going to really financially undercut them and make their

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Speaker 1: products essentially irrelevant. Yeah, you know's what's interesting to me too,

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Speaker 1: are also some of the network effects that are taking

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Speaker 1: place right now. So let's put this up there on

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Speaker 1: the screen. A lot of people have been taking notice,

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Speaker 1: which is that conservatives question huge spikes in Twitter followers

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Speaker 1: after the Elon Musk takeover, and they're definitely does seem

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Speaker 1: to be something to this crystal, which is that you

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Speaker 1: saw large gains by majority conservative accounts. I'm talking like

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Speaker 1: ten twenty thousand extra announce of followers relative to normal

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Speaker 1: that was pointed out on Social Blade data. So here

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Speaker 1: are some of the biggest swings that we saw in

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Speaker 1: the last twenty four hours Marjorie Taylor Green gained forty

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Speaker 1: one thousand followers. Ted Cruz gained forty thousand followers, Laura

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Speaker 1: Ingram twenty seven thousand, Joe Biden twenty six thousand. The

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Speaker 1: Biden one I would put out because whenever you have

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Speaker 1: millions and millions, I don't think that that really Wait,

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Speaker 1: so Biden jumped up. Apparently Joe Biden jumped up. New

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Speaker 1: Gingris jumped up. However, I mean it says Barack Obama

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Speaker 1: lost five thousand. Again, I mean that's just new Ginger

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Speaker 1: has a great sorter account by the way, you know,

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Speaker 1: lots of pictures of him and Callista various things. Yeah,

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Speaker 1: I enjoyed. Actually, Michelle Obama lost twenty thousand, Bernie Sanders

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Speaker 1: also lost nineteen thousand, and Alexandro Cosio Cortes lost twelve thousand.

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Speaker 1: So I think there is something interesting going on, but

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Speaker 1: we don't actually know. So in terms of Emon's response,

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Speaker 1: here's what he says. Let's put up there, which is

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Speaker 1: that every media outlet on Earth wrote about me acquiring Twitter,

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Speaker 1: causing a massive influx of new users. I don't know

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Speaker 1: if he has any data in order to back that up.

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Speaker 1: I actually have an alternative theory, and I'm curious what

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Speaker 1: you think, which is that what they said is immediately

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Speaker 1: after the sale, Twitter actually went ahead and locked down

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Speaker 1: its core source code and an algorithm. So I'm curious

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Speaker 1: whether there was some sort of daily manipulation or Okay,

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Speaker 1: this sounds more nefarious more, let's just say daily like

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Speaker 1: curation that was happening by engineers that by locking it

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Speaker 1: down just simply changed the way that people are gaining followers. Now,

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Speaker 1: I personally gained about twenty thousand followers they just checked

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Speaker 1: in the last two days. But Elon also replied to me,

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Speaker 1: which we'll get to you. I think that that's really

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Speaker 1: I don't think it has anything to do with that,

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Speaker 1: but I am looking at other accounts who didn't have

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Speaker 1: any of that. I'm right, yeah, I mean I think

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Speaker 1: you and even me just like being tangentially, you know,

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Speaker 1: related to the Elon must replying you and the whole

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Speaker 1: blow up over that. Like I also gained followers, but

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Speaker 1: I would put our a side because we did all

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Speaker 1: the sort of unusual Twitter activity associated with our accounts.

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Speaker 1: But it is strange. I honestly have no idea what

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Speaker 1: to make I mean, you do have some percentage of

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Speaker 1: liberals who are saying like I'm done with the platform

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Speaker 1: and I'm leaving. I am skeptical though, that it's in

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Speaker 1: these kind of mass numbers. So I mean, that would

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Speaker 1: be one explanation of like why people on the left

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Speaker 1: side of the spectrum loss followers and conservatives tend to

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Speaker 1: gain followers because you've got now this is one, you know,

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Speaker 1: sort of organic theory, is you've got all this press

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Speaker 1: about what's going on with Elon and Twitter. So you've

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Speaker 1: got conservatives returning to the side or signing up on

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Speaker 1: the site for the first time, and so that explains

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Speaker 1: those increases and followers. And at the same time you

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Speaker 1: have liberals abandoning ship and saying I'm you know, taking

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Speaker 1: my choice and going home. But I am just a

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Speaker 1: little bit skeptical that there really is that much movement

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Speaker 1: organically in terms of users coming in and users going out.

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Speaker 1: But I don't really have an alter, alternative explanation. I

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Speaker 1: just don't know. It's weird, Yeah, it is, certainly, And look,

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Speaker 1: I think all of this should always be couched in this.

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Speaker 1: Most people are not on Twitter, and I mentioned this,

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Speaker 1: but I went ahead and pulled the data. You know,

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Speaker 1: you guys might have missed this. Snapchat right now is booming.

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Speaker 1: It currently has one hundred and fifteen million more daily

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Speaker 1: active users per day than Twitter. Think about it in

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Speaker 1: terms of cultural impact. Nobody seems to reckon with the

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Speaker 1: fact that the vast majority of people are on YouTube, Facebook, Instagram, Snapchat,

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Speaker 1: and TikTok. Those in terms of popular culture and the

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Speaker 1: everyday user experience for most people are what matter. Twitter, though,

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Speaker 1: is for elites. Now again, why we spend so much

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Speaker 1: time talking about it is it matters because elites run

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Speaker 1: the entire country. They run every institution in American life,

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Speaker 1: so what they think, how they interact, and what they

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Speaker 1: do matters a lot. That's ultimately why you know, Elon

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Speaker 1: even bought it in the first place, and why we

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Speaker 1: will talk about it in terms of followers and all that,

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Speaker 1: because that obviously matters amongst elite cachet, and we spend

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Speaker 1: time talking and thinking about the policies on that platform

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Speaker 1: because that has a major downstream effect on basically everything

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Speaker 1: that normal people at home are consuming, whether they know

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Speaker 1: it or not. You don't think about the news business,

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Speaker 1: think about Hollywood and entertainment and just the most efficient

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Speaker 1: way for celebrities and others in order to communicate with people.

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Speaker 1: A lot of that happens on Twitter in terms of discourse,

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Speaker 1: in terms of exposing to us how a lot of

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Speaker 1: these elites actually think and how they talk to each other.

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Speaker 1: So that is why we are spending such amount of time,

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Speaker 1: even though we know, you know, right now, vast majority

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Speaker 1: of people who are watching or listening to this, they're

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Speaker 1: not consuming it on Twitter. And even if we did

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Speaker 1: put it out on Twitter, I don't think it would

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Speaker 1: do all that well. Relative to our YouTube presence, our Spotify,

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Speaker 1: Apple podcasts, our Instagram channel, our TikTok channel, that's really

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Speaker 1: where people are consuming a lot of this content relative

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Speaker 1: to Twitter itself, even though it does have an obvious

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Speaker 1: downstream impact on people. It is really interesting too, because

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Speaker 1: one thing that we've realized being in the YouTube space

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Speaker 1: for a number of years at this point is that

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Speaker 1: the YouTube world and the Twitter world are very very differparate.

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Speaker 1: And now that we're you know, also a podcast, we've

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Speaker 1: also realized that that world and what people respond to

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Speaker 1: there is also very different. You know. The great thing

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Speaker 1: about the podcast world is it is much more of

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Speaker 1: a neutral platform. It is much more of an actual,

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Speaker 1: like true sort of meritocracy. Now, of course, you have

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Speaker 1: a massive advantage if you come in with some sort

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Speaker 1: of a name, build or platform, because it's hard for

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Speaker 1: people to find new things. It's a little more complicated

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Speaker 1: since there isn't that algorithm surfacing for you. Hey, we

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Speaker 1: think you would like this to that same extent. But

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Speaker 1: you know, I think what the best hope is that

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Speaker 1: there's going to be more transparency on Twitter. I'm excited

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Speaker 1: about the idea of maybe the algorithm would be made transparent,

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Speaker 1: even though that's not the end all be all. At

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Speaker 1: least that provides an opportunity for reporters and experts to

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Speaker 1: dig in and help inform the public about how this

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Speaker 1: is actually happening, what sort of things are being so,

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Speaker 1: what sort of things are being prioritized. And you know,

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Speaker 1: transparency isn't everything, but it can be a tool for

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Speaker 1: helping garner public support for some sort of changes or

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Speaker 1: potentially for making the platform even more neutral. So those

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Speaker 1: are the sort of things I'm you know, hopeful, like

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Speaker 1: cautiously hopeful about. But to the point of the story

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Speaker 1: being important, you know, just the question of what happens

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Speaker 1: to Trump's Twitter account is a justifiable huge news story

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Speaker 1: because I mean, this is a man who continues to

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Speaker 1: be the leader of the Republican Party, very central to

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Speaker 1: our politics, who was one of the if not the

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Speaker 1: most dominant figure on Twitter for lots of years. So

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Speaker 1: you know, just the question of what happens to his

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Speaker 1: Twitter account and how he responds to it alone is

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Speaker 1: something that is worth considering in the context of, you know,

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Speaker 1: how our politics move forward and what that all looks like.

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Speaker 1: And you know, I saw someone making this argument from

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Speaker 1: the left. It may have even been Glenn who was

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Speaker 1: making this argument, But you know, for people who share

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Speaker 1: more my political leanings and more left leaning like you

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Speaker 1: should not be comfortable with the idea that a president

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Speaker 1: who polite society doesn't like can be just completely banned

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Speaker 1: and vanished from the public square, because you don't think

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Speaker 1: that if a Bernie Sanders type candidate or whoever, the

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Speaker 1: next sort of like left standard bearer who really is

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Speaker 1: a kind of dissident and challenges some of the established

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Speaker 1: Democratic Party and cultural liberalism establishment, you don't think that

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Speaker 1: there's going to be a similar effort to deplatform and

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Speaker 1: to marginalize in a sense of that person. Of course,

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Speaker 1: so don't build the tools that are ultimately going to

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Speaker 1: be weaponized against you. Absolutely. I mean that's something that

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Speaker 1: we can't emphasize enough. If you challenge power in any way,

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Speaker 1: power will go after you with the means that it

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Speaker 1: has at its disposal disposal, which is why building in

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Speaker 1: safeguards and abiding by first principles are the most important

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Speaker 1: thing that we can have. Now though it's not like

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Speaker 1: the loss of those power is not having some extraordinary

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Speaker 1: effects inside of Twitter itself, and we're beginning to see

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Speaker 1: that with some leaked audio the project Veritas got its

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Speaker 1: hands on from a Twitter all hands on deck meeting.

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Speaker 1: Just look at the freak out happening inside of Twitter

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Speaker 1: headquarters right now. Let's take a listen. Well, let me

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Speaker 1: it clear in public that a large part of the

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Speaker 1: reason he bought the platform was because of our moderation

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Speaker 1: policies and disagreements in how we deal with help. This

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Speaker 1: puts Twitter service and trust in safety as well as

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Speaker 1: anybody who cares about help on the platform in a

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Speaker 1: very difficult position. I believe Twitter grows as a service

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Speaker 1: allows for more people to use the product and have

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Speaker 1: a better experience because we're able to make the conversation

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Speaker 1: on Twitter be safe because we have built tools processes

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Speaker 1: for people to be able to feel safe and control

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Speaker 1: their experiences. I believe that there is a lot of

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Speaker 1: work we have to do to continue making that better.

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Speaker 1: Sometimes that means more thoughtful moderation. Sometimes that means making

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Speaker 1: things simple. Look Sometimes that means changing product incentives to

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Speaker 1: be able to solve problems through products sometimes instead of policies.

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Speaker 1: So the two people that you heard speaking there are

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Speaker 1: Leslie Berlin, so she is the chief of the CMO,

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Speaker 1: the chief marketing officer at Twitter, and the second person

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Speaker 1: is parag Agarwall, who is the CEO of Twitter. Now.

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Speaker 1: To be fair, yeah, for now and hopefully not for long.

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Speaker 1: To be fair, Leslie claims that she was reading a

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Speaker 1: question to Paragaga Law from the staff. That being said,

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Speaker 1: I think that it's still an important view into the company,

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Speaker 1: which is that they're like, what about health and by

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Speaker 1: that they mean COVID misinformation. Now, nobody's going to say

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Speaker 1: there isn't COVID misinformation on Twitter, but we all remember

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Speaker 1: the lab league story which was censored off Twitter of

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Speaker 1: February of twenty twenty, and hence why a lot of

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Speaker 1: the content regime around all of this is completely ridiculous

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Speaker 1: that they've banned an extraordinary number of accounts for going

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Speaker 1: against the COVID narrative, which actually ended up being true.

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Speaker 1: So that obviously is a big problem. But also I

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Speaker 1: think that what it shows you is that inside of

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Speaker 1: Twitter itself, and this will get to the story that

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Speaker 1: we'll eventually talk about, there is a complete freak out

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Speaker 1: on the side who are the most censorious. We've seen

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Speaker 1: the reports of the executives crying. Like I said, I'll

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Speaker 1: about to get to that, but I think that this

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Speaker 1: is fully represented. I know, I'm so sorry. Fully represented

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Speaker 1: within that clip is the domineering mindset of we control

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Speaker 1: the ability in order to make people feel safe. Now, look,

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Speaker 1: I want people to feel safe. It's a very important thing. However,

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Speaker 1: whenever you use that type of rhetoric, which is what

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Speaker 1: paragag or Wall is reiterating, it comes back to his

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Speaker 1: original declaration of twenty twenty, whenever he was asked about

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Speaker 1: should you abide by the First Amendment, and he said,

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Speaker 1: our job is not to abide by the First Amendment,

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Speaker 1: it's to make people feel safe on the platform. And

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Speaker 1: making people feel quote unquote safe on the platform is

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Speaker 1: just opening the door to accusations BS, accusations of harassment

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Speaker 1: of something else. And once again, I don't think harassment

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Speaker 1: is good. I think if you dock somebody and you

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Speaker 1: reveal their personal information, that should be taken down. However,

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Speaker 1: if you criticize somebody, that is now being painted as harassment, yes,

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Speaker 1: and that is being used as a guys in order

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Speaker 1: to take down accounts. So that's a very very good

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Speaker 1: and clear view into the company itself as to how

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Speaker 1: the sensors and the people who really agree with that

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Speaker 1: and created that mindset are exactly those who are most

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Speaker 1: upset about the Elon thing. I think the most interesting

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Speaker 1: thing that peragh Agrowall current CEO said there is he said,

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Speaker 1: you know, sometimes the way to deal with these questions

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Speaker 1: of safety is through content moderation. Sometimes it's through changing

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Speaker 1: the rules, making through things simpler. But the thing that

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Speaker 1: I thought was most interesting that he said is he's

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Speaker 1: indicated sometimes it's through making changes to the product. And

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Speaker 1: so oftentimes when we think about the health of our

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Speaker 1: public square, kind of the easiest thing to go to

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Speaker 1: is which things are being censored, which things are being

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Speaker 1: taken down? How is this being applied, But actually what

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Speaker 1: really shapes our discourse, perhaps more than anything, is the

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Speaker 1: design of the platforms themselves, definitely, and oftentimes too, you

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Speaker 1: know those surfacing algorithms that we keep talking about, which

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Speaker 1: just determines like what's being basically buried and no one

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Speaker 1: is likely to see, and what is being served to

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Speaker 1: people time and time and time again. So one simple

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Speaker 1: example that we experience all the time here on YouTube is,

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Speaker 1: you know, CNN and these other mainstream cable news platforms,

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Speaker 1: they used to get no views on YouTube, like there

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Speaker 1: was no organic interest in their content. And I think

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Speaker 1: that that has been very much proven out by the

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Speaker 1: colossal failure of CNN, plus that there just isn't that

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Speaker 1: much organic interest in I'm going to go seek out

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Speaker 1: a specific CNN video. But because YouTube listen, we don't

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Speaker 1: know what's going on in their algorithm because it's completely

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Speaker 1: non transparent. But it seems very obvious that what they've

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Speaker 1: decided to do is to prop up these platforms and

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Speaker 1: just serve their videos relentlessly to basically everybody who shows

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Speaker 1: up on YouTube, and so you know, some percentage of

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Speaker 1: those are going to suffer through the video that was

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Speaker 1: just placed in front of them, or it's on AutoPlay

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Speaker 1: and they don't even realize it's playing, and so that

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Speaker 1: ends up propping up those products. And then you don't

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Speaker 1: put in front of them independent media creations you because

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Speaker 1: that's not maybe as safe in your perspective from an

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Speaker 1: advertiser standpoint, So that those sorts of things that are

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Speaker 1: happening in the background, or even just the design of

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Speaker 1: Twitter in terms of you know, being able to retweet things,

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Speaker 1: being able to like things, the length of the characters themselves.

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Speaker 1: Those decisions which are made by you know, high level

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Speaker 1: executives at Twitter have a massive impact on the way

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Speaker 1: that our discourse ultimately unfolds. That's why the culture on

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Speaker 1: these different platforms. If you guys are on a couple

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Speaker 1: different social media platforms, you know, the culture at each

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Speaker 1: of them feels totally different. Kyle is not on Instagram,

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Speaker 1: so he's been shocked by the fact that when I

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Speaker 1: post things on Instagram, most of the comments are at

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Speaker 1: oh yeah, over it's like positive, earnest and sweet and kind.

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Speaker 1: I mean not one hundred percent, but really the overwhelming bulk.

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Speaker 1: And it's because of the differences between those platforms. Totally

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Speaker 1: different cultures have been created. So it is a complex

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Speaker 1: conversation ultimately and how you craft these platforms, but it

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Speaker 1: matters a lot. And transitioning into our next segment, that's

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Speaker 1: why these people are so powerful and why they not

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Speaker 1: only should be held to account, but absolutely must be

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Speaker 1: held to account because the decisions that they are making

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Speaker 1: are having a profound impact on our democracy. And listen,

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Speaker 1: you guys know our position here. Ultimately, there's a lot

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Speaker 1: that's said that tries to make this more complex than

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Speaker 1: it ultimately is. But if you believe in free speech,

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Speaker 1: we have first Amendment right here in this country. You know,

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Speaker 1: people should be able to express their opinions, even when

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Speaker 1: it's messy, even when it's complicated, even when it's offensive,

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Speaker 1: all of those things in the interest of having a

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Speaker 1: healthy democracy. If Twitter is now part a vital part

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Speaker 1: of the public square, those same rules that have been

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Speaker 1: part of our country for generations in which are argued

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Speaker 1: over and fought over, and where are the lines and

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Speaker 1: the batteries and all of that in the courts, that's

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Speaker 1: what should apply there as well. So with all of

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Speaker 1: that being said, let's get to Sager's part in this

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Speaker 1: whole saga. Go ahead and throw this element up there

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Speaker 1: on the screen. So as I was just saying, these

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Speaker 1: executives really deserve a lot of scrutiny, and so Sager

431
00:22:29,520 --> 00:22:32,160
Speaker 1: on Twitter provided a little bit of that scrutiny, saying,

432
00:22:33,240 --> 00:22:36,440
Speaker 1: Vajia Gaddy is that host you listening? The top censorship

433
00:22:36,440 --> 00:22:39,080
Speaker 1: advocate at Twitter who famously gas led the world on

434
00:22:39,160 --> 00:22:42,439
Speaker 1: Joe Rogan's podcast True and Censored the Hunter Biden laptop story,

435
00:22:42,680 --> 00:22:45,000
Speaker 1: is very upset about the Elon must takeover, and he

436
00:22:45,040 --> 00:22:47,880
Speaker 1: includes in there a Politico story that says Twitter's top

437
00:22:47,960 --> 00:22:51,439
Speaker 1: lawyer reassures staff and cries during meeting about most takeover.

438
00:22:51,640 --> 00:22:54,600
Speaker 1: This is reporting from Politico, Okay, this is like he's

439
00:22:54,680 --> 00:22:57,359
Speaker 1: just showing the world what happened here and having some

440
00:22:57,400 --> 00:23:00,560
Speaker 1: commentary about it. I can't stand Vijia Gotte, been able

441
00:23:00,560 --> 00:23:03,639
Speaker 1: to stand her since twenty eighteen when she appeared on

442
00:23:03,680 --> 00:23:06,800
Speaker 1: The Joe Rogan Experience with Jack Dorsey spent ninety percent

443
00:23:06,840 --> 00:23:09,119
Speaker 1: of the time gaslighting all of us and Tim Poole

444
00:23:09,160 --> 00:23:11,919
Speaker 1: as well about the censorship policies over there. So I

445
00:23:12,000 --> 00:23:13,800
Speaker 1: found it amusing, and I'm gonna talk about this in

446
00:23:13,840 --> 00:23:17,119
Speaker 1: my monologue. Was it mean? Yeah? Okay, I'll okay, but

447
00:23:17,200 --> 00:23:18,880
Speaker 1: it was me. I won't even defend you that pet

448
00:23:18,960 --> 00:23:21,800
Speaker 1: us backup on the screen. This is not even that mean. Okay,

449
00:23:21,880 --> 00:23:24,720
Speaker 1: I agree, but I'm the standards of Twitter. I actually

450
00:23:24,720 --> 00:23:26,440
Speaker 1: think you're being a little too hard on yourself. Put

451
00:23:26,440 --> 00:23:28,000
Speaker 1: that part back up on the screen, because we've got

452
00:23:28,040 --> 00:23:29,880
Speaker 1: another part. We've got to get here. So you say,

453
00:23:29,920 --> 00:23:32,520
Speaker 1: she famously gasled world. True, since for the Hunter Biden

454
00:23:32,600 --> 00:23:37,240
Speaker 1: laptop story, true is very upset Also true, just completely factual,

455
00:23:37,600 --> 00:23:40,359
Speaker 1: point by point based on the reporting from Politico. So

456
00:23:40,400 --> 00:23:43,199
Speaker 1: then something very unexpected happens. I did not expect this.

457
00:23:43,440 --> 00:23:47,080
Speaker 1: Elon Musk himself replies and says, also in a pretty

458
00:23:47,119 --> 00:23:50,119
Speaker 1: neutral tony here, Harry, suspending the Twitter account of a

459
00:23:50,160 --> 00:23:53,960
Speaker 1: major news organization for publishing a truthful story was obviously

460
00:23:54,040 --> 00:23:57,200
Speaker 1: incredibly inappropriate. And I don't know who at this point

461
00:23:57,320 --> 00:24:00,800
Speaker 1: really disagrees with me, can disagree with I couldn't believe it.

462
00:24:00,920 --> 00:24:03,600
Speaker 1: But guys, what ends up's happening here is the most

463
00:24:03,760 --> 00:24:07,760
Speaker 1: legitimately insane thing I have ever been a part of.

464
00:24:07,880 --> 00:24:09,359
Speaker 1: So Elon replies to me, and I was like, oh,

465
00:24:09,400 --> 00:24:12,679
Speaker 1: that's kind of interesting. My phone literally that won't stop buzzing.

466
00:24:12,800 --> 00:24:15,800
Speaker 1: People wrote up his comments. All of that. Then in

467
00:24:15,840 --> 00:24:18,760
Speaker 1: the next couple of hours, a narrative begins to develop

468
00:24:18,960 --> 00:24:24,480
Speaker 1: that Elon and me are responsible for targeted harassment against

469
00:24:24,480 --> 00:24:29,280
Speaker 1: this woman, Vijayagada, because apparently some random accounts said she

470
00:24:29,359 --> 00:24:32,959
Speaker 1: should be fired and said some racist stuff against her. Obviously,

471
00:24:33,160 --> 00:24:36,280
Speaker 1: I do not condone anything racist against Vajaya Goada. You

472
00:24:36,359 --> 00:24:39,360
Speaker 1: may not have noticed, but I'm Indian. Furthermore, I did

473
00:24:39,400 --> 00:24:42,560
Speaker 1: some investigation. I called my mom. Now, according to my mom,

474
00:24:42,840 --> 00:24:46,520
Speaker 1: Vijayagada is not only are we both Indian, she is

475
00:24:46,680 --> 00:24:49,919
Speaker 1: also a Telugu person, as in, we are from the

476
00:24:49,960 --> 00:24:53,760
Speaker 1: same region of India. Furthermore, I actually have a cousin

477
00:24:54,000 --> 00:24:57,560
Speaker 1: with the last name who is similar to Vijayagada, so

478
00:24:57,640 --> 00:25:00,320
Speaker 1: we may even be related. So maybe just you're just

479
00:25:00,359 --> 00:25:04,399
Speaker 1: a self hating Indians. So not only are we both Indian,

480
00:25:04,520 --> 00:25:07,400
Speaker 1: we are from the same region of India and our

481
00:25:07,400 --> 00:25:09,920
Speaker 1: families from the same region of India. And I might

482
00:25:09,960 --> 00:25:12,119
Speaker 1: actually be related to the lady. Okay, so let's go,

483
00:25:12,400 --> 00:25:14,719
Speaker 1: let's put that out of the way. Yeah, And so

484
00:25:14,760 --> 00:25:17,840
Speaker 1: then the news media decides this is an angle we

485
00:25:17,880 --> 00:25:22,000
Speaker 1: can pursue because they don't necessarily love being like overtly

486
00:25:22,040 --> 00:25:24,840
Speaker 1: in favor of no, we want the censorship. What if

487
00:25:24,840 --> 00:25:26,720
Speaker 1: they have free speech? Oh my god, because you know

488
00:25:26,800 --> 00:25:29,480
Speaker 1: these places like to pretend that they're pre speech outlets

489
00:25:29,480 --> 00:25:31,720
Speaker 1: and in favor of such things. So now they're like, oh,

490
00:25:31,760 --> 00:25:34,359
Speaker 1: we've got an angle. They've got the got you know,

491
00:25:34,920 --> 00:25:39,600
Speaker 1: targeted harassment of a female executive brought out by these

492
00:25:39,680 --> 00:25:43,199
Speaker 1: powerful figures, et cetera, et cetera. So Washington Post decides

493
00:25:43,240 --> 00:25:47,159
Speaker 1: to go forward with this story Elon Musk boost criticism

494
00:25:47,280 --> 00:25:51,480
Speaker 1: of Twitter executives prompting online attacks and let me read

495
00:25:51,520 --> 00:25:54,840
Speaker 1: to you the framing of this, which is so incredibly

496
00:25:55,320 --> 00:26:00,439
Speaker 1: dystopian and gas lady and dishonest. So they say, Elon

497
00:26:00,560 --> 00:26:03,760
Speaker 1: Musk is using his powerful Twitter account to bolster right

498
00:26:03,800 --> 00:26:09,200
Speaker 1: wing users who sharply criticized two company company executives, exposing

499
00:26:09,280 --> 00:26:13,040
Speaker 1: them to the online masses who join in the attacks,

500
00:26:13,040 --> 00:26:16,160
Speaker 1: exposing them to the online masses. Again, these are powerful,

501
00:26:16,440 --> 00:26:19,600
Speaker 1: very powerful individuals that we're talking about here. It started

502
00:26:19,760 --> 00:26:23,720
Speaker 1: with a Tuesday tweet from political podcast host Sager and

503
00:26:23,800 --> 00:26:26,840
Speaker 1: Jetty Always read to Do That. Twitter users quickly piled

504
00:26:26,880 --> 00:26:30,200
Speaker 1: on to the criticism of Gotti, including calling on must

505
00:26:30,200 --> 00:26:33,080
Speaker 1: to fire her and using racist language to describe her.

506
00:26:33,320 --> 00:26:36,240
Speaker 1: Gotte was born in India, Indian immigrated to the US

507
00:26:36,280 --> 00:26:39,080
Speaker 1: as a child. One user said she would quote go

508
00:26:39,200 --> 00:26:43,520
Speaker 1: down in history as an appalling person. How could you

509
00:26:43,600 --> 00:26:45,679
Speaker 1: say such a thing? I actually found it kind of

510
00:26:45,720 --> 00:26:48,240
Speaker 1: revealing that that was the worst response that they could

511
00:26:48,280 --> 00:26:51,640
Speaker 1: find here. She's so mild. Yeah, I know people said

512
00:26:51,680 --> 00:26:53,800
Speaker 1: horrible things about me. Guess what. I don't care, you

513
00:26:53,840 --> 00:26:56,560
Speaker 1: know whatever, that's what comes with this business. And the

514
00:26:56,560 --> 00:26:59,760
Speaker 1: people who criticized me, which prompted those whatever, it's part

515
00:26:59,800 --> 00:27:01,359
Speaker 1: of the game. I'm not gonna be like, you're a

516
00:27:01,440 --> 00:27:05,080
Speaker 1: racist for coming after me. So what really pissed me off, though, Crystal,

517
00:27:05,119 --> 00:27:07,679
Speaker 1: was not just the framing of this was inside of

518
00:27:07,720 --> 00:27:10,840
Speaker 1: the article they wrote, and they've they've since updated it.

519
00:27:11,000 --> 00:27:14,879
Speaker 1: They said, Jetti did not immediately respond for requests to comment.

520
00:27:15,160 --> 00:27:18,240
Speaker 1: And so I'm literally just spending my Wednesday morning. I

521
00:27:18,280 --> 00:27:21,080
Speaker 1: came back from the gym. It's like seven thirty or whatever.

522
00:27:21,080 --> 00:27:23,200
Speaker 1: I'm like scrolling and I say, and I said, whoh,

523
00:27:23,320 --> 00:27:26,720
Speaker 1: I've never been nobody's contacted me. I checked my Instagram,

524
00:27:26,800 --> 00:27:29,280
Speaker 1: I checked my email, I checked my phone. Nothing. So

525
00:27:29,320 --> 00:27:32,000
Speaker 1: then I called our producer James. And here's what James

526
00:27:32,000 --> 00:27:33,720
Speaker 1: tells me. Let's go ahead and put this up there

527
00:27:33,760 --> 00:27:38,320
Speaker 1: on the screen. This Washington Post lady emails James not

528
00:27:38,440 --> 00:27:43,680
Speaker 1: even me at two six am, and she says, here, Hi, there.

529
00:27:43,920 --> 00:27:46,840
Speaker 1: We are quickly writing up his tweets tonight about Vijaiya

530
00:27:46,920 --> 00:27:50,080
Speaker 1: Goatte with the peg that Musk is piling on. Some questions.

531
00:27:50,080 --> 00:27:52,640
Speaker 1: Here are questions. Listen to this Hilo. Does he have

532
00:27:53,000 --> 00:27:57,000
Speaker 1: any concern that mentioning a specific Twitter executive could result

533
00:27:57,040 --> 00:28:00,159
Speaker 1: in attacks on that exec What are the responsibilities here?

534
00:28:00,359 --> 00:28:03,480
Speaker 1: For example, one of the commenters made racist tweets events

535
00:28:03,520 --> 00:28:06,200
Speaker 1: Gode and others said she should be fired. Number two?

536
00:28:06,560 --> 00:28:09,479
Speaker 1: What does he hope to accomplish by calling out Gode

537
00:28:09,880 --> 00:28:12,439
Speaker 1: and getting Elon involved? So there's a lot going on.

538
00:28:13,560 --> 00:28:16,280
Speaker 1: Number one, everybody in this town has my phone number,

539
00:28:16,440 --> 00:28:19,360
Speaker 1: including half of the people who work in her newspaper. Yes,

540
00:28:19,400 --> 00:28:21,600
Speaker 1: it's not that hard to find. By the way, please

541
00:28:21,600 --> 00:28:25,320
Speaker 1: don't call me randomly. But it's really not that difficult.

542
00:28:25,600 --> 00:28:27,600
Speaker 1: I was a reporter. I know a lot of the

543
00:28:27,600 --> 00:28:30,360
Speaker 1: people here. She could easily have gotten it, and many

544
00:28:30,440 --> 00:28:32,600
Speaker 1: of her colleagues have contacted me and have spoken to

545
00:28:32,640 --> 00:28:36,119
Speaker 1: me many times in the past. Number two, emailing somebody

546
00:28:36,119 --> 00:28:39,200
Speaker 1: for comment at two oh six am Eastern time is

547
00:28:39,360 --> 00:28:42,080
Speaker 1: complete bs. And what time did they go live at

548
00:28:42,120 --> 00:28:44,080
Speaker 1: the story? They went live with the story late, like

549
00:28:44,120 --> 00:28:48,520
Speaker 1: six am. I'm awake. You could I was literally away.

550
00:28:48,520 --> 00:28:50,080
Speaker 1: I got up at five that day in order to

551
00:28:50,080 --> 00:28:51,920
Speaker 1: go work out. You could have called me. I would

552
00:28:51,920 --> 00:28:53,800
Speaker 1: have given you a comment. I would have been happy

553
00:28:53,840 --> 00:28:56,760
Speaker 1: to do so. I'm actually pretty accessible whenever people write

554
00:28:56,840 --> 00:29:00,720
Speaker 1: about breaking points. So seven hours after el Musk replied

555
00:29:00,760 --> 00:29:03,680
Speaker 1: to me, they contact me for the story. Now let's

556
00:29:03,720 --> 00:29:07,960
Speaker 1: get to the actual questions here. Vijayagade was paid seventeen

557
00:29:08,200 --> 00:29:11,800
Speaker 1: million dollars last year. She literally appeared on the Joe

558
00:29:11,920 --> 00:29:15,160
Speaker 1: Rogan podcast and is the top policy executive at Twitter.

559
00:29:15,280 --> 00:29:18,400
Speaker 1: She's a public figure. I'm allowed to criticize public figures.

560
00:29:18,400 --> 00:29:21,000
Speaker 1: In fact, that's literally my job, and under the guise

561
00:29:21,040 --> 00:29:23,760
Speaker 1: of the First Amendment, which I've prized and which I

562
00:29:23,760 --> 00:29:25,760
Speaker 1: think is very important for me being able to do

563
00:29:25,800 --> 00:29:27,720
Speaker 1: the work that I do. That is well within the

564
00:29:27,760 --> 00:29:30,960
Speaker 1: bounds of both accepted in legal speech, but also I

565
00:29:30,960 --> 00:29:35,320
Speaker 1: would think even within the respectability industrial COMPENTX going after

566
00:29:35,360 --> 00:29:38,800
Speaker 1: somebody on a substantive issue is not out of bounds.

567
00:29:38,800 --> 00:29:42,560
Speaker 1: Who is very powerful, very powerful. Her title is Twitter's

568
00:29:42,600 --> 00:29:46,000
Speaker 1: is very dystopian title, Twitter's legal policy and trust leaders.

569
00:29:46,160 --> 00:29:48,360
Speaker 1: So she's the head of the Ministry of Information. Right,

570
00:29:48,440 --> 00:29:52,160
Speaker 1: So my criticism of her on a policy matter that

571
00:29:52,240 --> 00:29:56,120
Speaker 1: she has publicly spoken about, how am I responsible for

572
00:29:56,200 --> 00:29:59,080
Speaker 1: what some random ass Twitter account says to her? And

573
00:29:59,160 --> 00:30:02,960
Speaker 1: same with e He didn't say anything crazy about Vijaiya Gotta.

574
00:30:03,040 --> 00:30:05,760
Speaker 1: He replied to a tweet and criticized her on a

575
00:30:05,920 --> 00:30:08,880
Speaker 1: policy matter that she was directly involved in. She's the

576
00:30:08,920 --> 00:30:12,320
Speaker 1: person who censored the Elon Musk story. Now number two,

577
00:30:12,400 --> 00:30:15,920
Speaker 1: in turn, is our second question. She accuses me of

578
00:30:16,000 --> 00:30:20,120
Speaker 1: bringing in Elon. I've never spoken to Elon Musk in

579
00:30:20,200 --> 00:30:24,360
Speaker 1: my entire life. We've had no connection. He's never tweeted

580
00:30:24,360 --> 00:30:26,880
Speaker 1: at me before. I've never spoken to him. I've never

581
00:30:26,920 --> 00:30:30,000
Speaker 1: corresponded with him. I've never corresponded with anyone at TESLA.

582
00:30:30,320 --> 00:30:33,040
Speaker 1: I think the closest connection that we would have is

583
00:30:33,040 --> 00:30:35,960
Speaker 1: that we also know Joe Rogan. Right, Okay, so just

584
00:30:36,040 --> 00:30:39,600
Speaker 1: so people are completely aware, maybe he knows I'm big,

585
00:30:39,640 --> 00:30:41,680
Speaker 1: which is a large group of people, the people who

586
00:30:41,680 --> 00:30:45,200
Speaker 1: know Joe Rogan. I maybe knows, Zam. I literally have

587
00:30:45,320 --> 00:30:48,800
Speaker 1: no idea, So I didn't bring Elon. What was I

588
00:30:48,840 --> 00:30:51,440
Speaker 1: hoping to accomplish? Was she hoped to accomplish by calling

589
00:30:51,520 --> 00:30:56,120
Speaker 1: out Gade and getting Elon involved? What is anyone hope

590
00:30:56,120 --> 00:30:58,280
Speaker 1: to accomplish? When I'm sending it, I'm making a comment

591
00:30:58,400 --> 00:31:01,000
Speaker 1: on a policy matter. But I think this is the

592
00:31:01,040 --> 00:31:04,239
Speaker 1: perfect example. This is how they try to smear you.

593
00:31:04,600 --> 00:31:09,080
Speaker 1: I make a substantive point. Some random people say something. Now,

594
00:31:09,360 --> 00:31:13,160
Speaker 1: me and Elon are racists and are responsible for the

595
00:31:13,200 --> 00:31:15,760
Speaker 1: harassment that this lady is experiencing. By the way, I

596
00:31:15,800 --> 00:31:18,440
Speaker 1: decry the harassment, okay, and any racist harassment against her

597
00:31:18,440 --> 00:31:22,280
Speaker 1: would be equally applicable to me. So obviously that's not thhing.

598
00:31:22,280 --> 00:31:24,280
Speaker 1: So all of this, as you said at the top,

599
00:31:24,640 --> 00:31:26,480
Speaker 1: they are just covering up for the fact that they

600
00:31:26,560 --> 00:31:29,240
Speaker 1: agree with censorship. And to let me just take you

601
00:31:29,240 --> 00:31:31,120
Speaker 1: a little bit behind the scenes, because I found out

602
00:31:31,160 --> 00:31:34,000
Speaker 1: a little bit more since all of this happened. Vijaya Gade.

603
00:31:34,040 --> 00:31:35,560
Speaker 1: I don't have a confirmation on this, but I'm just

604
00:31:35,600 --> 00:31:38,080
Speaker 1: telling you she has very, very close relationships with a

605
00:31:38,120 --> 00:31:40,480
Speaker 1: lot of these reporters. In fact, the Washington Post reporter

606
00:31:40,520 --> 00:31:42,760
Speaker 1: wrote this story was going and liking a bunch of

607
00:31:42,840 --> 00:31:45,640
Speaker 1: tweets about how Vajaia Godda is like some saint, you know,

608
00:31:45,680 --> 00:31:48,200
Speaker 1: come back to earth and how she know she's somebody

609
00:31:48,240 --> 00:31:50,440
Speaker 1: who's been really helping people out. And it has been

610
00:31:50,880 --> 00:31:52,640
Speaker 1: known to me via cutout. So I'm not going to

611
00:31:52,680 --> 00:31:55,400
Speaker 1: reveal my sources that Vijaia is very very close with

612
00:31:55,440 --> 00:31:57,640
Speaker 1: the entire tech press, which is why they are going

613
00:31:57,680 --> 00:32:02,000
Speaker 1: after this. So what she involved maybe creating this entire narrative,

614
00:32:02,280 --> 00:32:05,240
Speaker 1: I'll let you take that supposition for you. That's the

615
00:32:05,320 --> 00:32:08,320
Speaker 1: thing that is so dishonest here. I mean, first of all,

616
00:32:08,400 --> 00:32:12,600
Speaker 1: I think it really reveals what dishonest Hackey actors they

617
00:32:12,640 --> 00:32:16,080
Speaker 1: are that they would email James at two am for

618
00:32:16,200 --> 00:32:18,720
Speaker 1: comment and then make it sound like, oh you just

619
00:32:18,720 --> 00:32:22,560
Speaker 1: couldn't be bothered to respond or to respond. I mean

620
00:32:22,560 --> 00:32:24,840
Speaker 1: that just is a little window into how these people

621
00:32:24,880 --> 00:32:29,000
Speaker 1: actually operate. And then, yeah, this isn't a straight she

622
00:32:29,000 --> 00:32:30,920
Speaker 1: she wants to present this as just like a straight

623
00:32:30,960 --> 00:32:34,000
Speaker 1: news reform, but clearly this is a you're obviously friends

624
00:32:34,000 --> 00:32:37,920
Speaker 1: with the lady very BENI is advocacy here, and listen,

625
00:32:37,960 --> 00:32:40,360
Speaker 1: the same standard could be applied, you know, turn it

626
00:32:40,440 --> 00:32:43,440
Speaker 1: right back around. How could the Washington Post, you know,

627
00:32:43,600 --> 00:32:46,280
Speaker 1: call you on and target you for harassment and sager,

628
00:32:46,400 --> 00:32:49,000
Speaker 1: are you okay? I mean, you know, it's It's just

629
00:32:49,440 --> 00:32:51,720
Speaker 1: it reminds me a lot of actually what they did

630
00:32:52,320 --> 00:32:55,040
Speaker 1: with with Bernie Sanders and like the whole Bernie Brow

631
00:32:55,200 --> 00:32:58,440
Speaker 1: narrative and trying to blame Bernie for any like bad

632
00:32:58,480 --> 00:33:01,920
Speaker 1: thing that some random supporter of his ultimately said it

633
00:33:02,000 --> 00:33:04,720
Speaker 1: was equally ridiculous. And it's why I was really disappointed

634
00:33:04,720 --> 00:33:06,840
Speaker 1: when he actually sort of gave into that narrative at

635
00:33:06,840 --> 00:33:09,120
Speaker 1: one point, because now you can see the way this

636
00:33:09,160 --> 00:33:12,640
Speaker 1: gets weaponized all the time, and it always gets weaponized

637
00:33:13,040 --> 00:33:16,560
Speaker 1: to protect really powerful people. I mean, this is someone

638
00:33:16,640 --> 00:33:20,520
Speaker 1: who is so clearly a public figure, like not a

639
00:33:20,600 --> 00:33:24,280
Speaker 1: question mark whatsoever, who is also extraordinarily wealthy and has

640
00:33:24,360 --> 00:33:26,840
Speaker 1: all of the privileges and protections that comes with that

641
00:33:26,960 --> 00:33:31,840
Speaker 1: class status as well, and whose influence really matters. So

642
00:33:32,200 --> 00:33:35,000
Speaker 1: for you know, a private citizen or a journalist or

643
00:33:35,040 --> 00:33:38,800
Speaker 1: anyone else to have an opinion on that that you express,

644
00:33:38,880 --> 00:33:40,520
Speaker 1: I mean it was like a little bit snarky, but

645
00:33:40,600 --> 00:33:44,560
Speaker 1: it honestly was really, you know, totally within bounds of

646
00:33:44,720 --> 00:33:48,600
Speaker 1: public discussion of issues that are very fraught and very important.

647
00:33:48,960 --> 00:33:52,280
Speaker 1: To make that into some nefarious thing. I just it's

648
00:33:52,320 --> 00:33:55,640
Speaker 1: like your right to be completely indignant in the way

649
00:33:55,640 --> 00:33:57,080
Speaker 1: that they handled all of this, and I think we

650
00:33:57,080 --> 00:33:59,720
Speaker 1: should also say like they were not the only ones.

651
00:34:00,360 --> 00:34:03,040
Speaker 1: Insider also wrote it up in a really sleazy and

652
00:34:03,040 --> 00:34:07,560
Speaker 1: dishonest way. They called you a right wing activist. Okay,

653
00:34:07,680 --> 00:34:10,080
Speaker 1: I mean, guys, ask the real right wing activists. I

654
00:34:10,160 --> 00:34:13,920
Speaker 1: can't stand Ye's it's just but you know, it's very

655
00:34:13,920 --> 00:34:16,839
Speaker 1: clearly the language is chosen to make you sound like

656
00:34:16,920 --> 00:34:21,880
Speaker 1: some nefarious actor who's tried the stirruption. You're in kahoots,

657
00:34:21,920 --> 00:34:24,200
Speaker 1: you know that's the sort of insinuation here from the watch.

658
00:34:24,239 --> 00:34:27,719
Speaker 1: You're incahoots with Elon to target this harassment at this

659
00:34:27,800 --> 00:34:30,840
Speaker 1: vulnerable person. Give me a break. It's ridiculous. No, it

660
00:34:30,880 --> 00:34:33,080
Speaker 1: really pissed me off because, like you said, it's spawned. Actually,

661
00:34:33,080 --> 00:34:35,719
Speaker 1: that Washington Post story then spawned Business Insider and a

662
00:34:35,719 --> 00:34:38,439
Speaker 1: bunch of other outlets are referring to me either as

663
00:34:38,719 --> 00:34:42,520
Speaker 1: a right wing activist or conservative YouTuber. I'm like, guys,

664
00:34:42,760 --> 00:34:46,640
Speaker 1: why does we have to apply any of these like adjectives?

665
00:34:46,719 --> 00:34:49,279
Speaker 1: Why can't it just be host of Breaking Points a

666
00:34:49,320 --> 00:34:52,239
Speaker 1: popular political show. I mean, what's wrong with that? It's

667
00:34:52,239 --> 00:34:55,080
Speaker 1: a right left show. Even incredibly diverse audience asked people

668
00:34:55,239 --> 00:34:57,520
Speaker 1: who actually know me, who actually listened to me, none

669
00:34:57,560 --> 00:34:59,719
Speaker 1: of them would use that moniker whenever they're trying to

670
00:34:59,800 --> 00:35:03,359
Speaker 1: just But beyond that, it's not even exactly how they

671
00:35:03,400 --> 00:35:06,399
Speaker 1: refer to me. It's the tactics, and like, guys, this

672
00:35:06,480 --> 00:35:09,000
Speaker 1: is what I want to show you, the inside the

673
00:35:09,040 --> 00:35:13,080
Speaker 1: two am emails, the ridiculous questions, they rely on you

674
00:35:13,239 --> 00:35:16,319
Speaker 1: not knowing how the sausage is made. And it comes

675
00:35:16,360 --> 00:35:18,760
Speaker 1: back to the Taylor Lorenz point I made. Listen, lady,

676
00:35:18,880 --> 00:35:21,480
Speaker 1: if you like Vajaia Gade, write an op at about it,

677
00:35:21,520 --> 00:35:24,000
Speaker 1: be like Sager and Jeti's a dishonest hack. I honestly

678
00:35:24,000 --> 00:35:26,120
Speaker 1: wouldn't care. I'd be like, okay, fine, whatever, I disagree

679
00:35:26,160 --> 00:35:28,120
Speaker 1: with you. I would probably do something here about it.

680
00:35:28,160 --> 00:35:31,160
Speaker 1: But to do this all within a news story is

681
00:35:31,239 --> 00:35:34,279
Speaker 1: just so incredibly dishonest. It shows you why we're trying

682
00:35:34,280 --> 00:35:35,960
Speaker 1: to do the work that we are here, both in

683
00:35:36,040 --> 00:35:38,719
Speaker 1: order to expose this but trying to build something so

684
00:35:38,880 --> 00:35:41,839
Speaker 1: currentble apart from this so and it does really relate

685
00:35:41,920 --> 00:35:45,320
Speaker 1: to to Taylor Lorenz, because this is like the tactic

686
00:35:45,360 --> 00:35:47,600
Speaker 1: that she uses all the time to shield herself from

687
00:35:47,600 --> 00:35:52,880
Speaker 1: criticism and the weaponizing of these like of identity to

688
00:35:53,080 --> 00:35:56,840
Speaker 1: again shield powerful actors from scrutiny. I mean, Taylor, the

689
00:35:56,880 --> 00:35:59,360
Speaker 1: thing that makes it so ridiculous with her as everyone

690
00:35:59,360 --> 00:36:02,960
Speaker 1: wants to has sort of like infantilize her. It's like,

691
00:36:03,320 --> 00:36:06,600
Speaker 1: how could you do this to this young woman? First

692
00:36:06,600 --> 00:36:09,319
Speaker 1: of all, she's we don't know exactly how old she is,

693
00:36:10,239 --> 00:36:12,440
Speaker 1: but she's not that young at this point, It's like,

694
00:36:13,440 --> 00:36:17,480
Speaker 1: And second of all, this is a well paid, prominent

695
00:36:17,560 --> 00:36:21,160
Speaker 1: journalist at one of the top outlets in the entire country,

696
00:36:21,320 --> 00:36:24,800
Speaker 1: in a tremendous position of power. And I don't doubt

697
00:36:24,880 --> 00:36:27,239
Speaker 1: that there has been ugliness directed her way. And I

698
00:36:27,280 --> 00:36:30,319
Speaker 1: do not want that for her or anyone else whatsoever.

699
00:36:30,760 --> 00:36:35,080
Speaker 1: But to make yourself like you're the victim in this country,

700
00:36:35,480 --> 00:36:39,120
Speaker 1: Like do you know anyone who has suffered anything real

701
00:36:39,320 --> 00:36:42,600
Speaker 1: in your life? Like look around at this nation and

702
00:36:42,719 --> 00:36:45,440
Speaker 1: think about all of the pain and suffering that is

703
00:36:45,480 --> 00:36:47,960
Speaker 1: going on, and you're gonna make it about yourself and

704
00:36:48,000 --> 00:36:50,359
Speaker 1: you're the victim in the story. That's why these things

705
00:36:50,480 --> 00:36:54,560
Speaker 1: are so disturbing, because Ultimately, again it is used to

706
00:36:54,600 --> 00:36:58,080
Speaker 1: make sure you cannot critique the powerful. And so this

707
00:36:58,239 --> 00:37:03,680
Speaker 1: is a perfect example of how they use these tactics

708
00:37:03,880 --> 00:37:06,920
Speaker 1: really cynically to try to shut down what is a

709
00:37:07,040 --> 00:37:10,920
Speaker 1: legitimate debate and discussion about the policies that should govern

710
00:37:11,000 --> 00:37:12,839
Speaker 1: our public speare. And last thing I'll say on this

711
00:37:12,920 --> 00:37:15,279
Speaker 1: is I'm lucky. Okay, I got this show. I have

712
00:37:15,400 --> 00:37:18,239
Speaker 1: you guys, I have the premium subscribers like I. My

713
00:37:18,440 --> 00:37:21,040
Speaker 1: livelihood is not going to be affected by this. But

714
00:37:21,120 --> 00:37:22,960
Speaker 1: let's say I still let's say we still worked at

715
00:37:22,960 --> 00:37:25,279
Speaker 1: the Hill. This is a problem, all right, This is

716
00:37:25,320 --> 00:37:28,719
Speaker 1: a real problem point. If I still worked in a

717
00:37:28,760 --> 00:37:31,960
Speaker 1: normal corporation or media company, this is a real issue

718
00:37:32,040 --> 00:37:33,799
Speaker 1: in terms of the way that you're getting described and

719
00:37:33,840 --> 00:37:36,040
Speaker 1: your colleagues and hey, you know, why are you being

720
00:37:36,080 --> 00:37:39,799
Speaker 1: unprofessional all of this. I have the liberty in order

721
00:37:39,840 --> 00:37:42,879
Speaker 1: to expose all of it and just say here's what

722
00:37:42,920 --> 00:37:46,440
Speaker 1: they said to me, here's the email. This is complete bs,

723
00:37:46,480 --> 00:37:49,000
Speaker 1: I can fully express myself. So I just want to

724
00:37:49,040 --> 00:37:51,560
Speaker 1: say another thank you to everybody who listens to the show,

725
00:37:51,560 --> 00:37:54,080
Speaker 1: to all the people who support the show. I am

726
00:37:54,160 --> 00:37:57,120
Speaker 1: only able to do what I am able to because

727
00:37:57,560 --> 00:38:00,879
Speaker 1: I know that you're my boss and not any we're

728
00:38:00,880 --> 00:38:03,200
Speaker 1: still working in media. This is a real problem. But

729
00:38:03,280 --> 00:38:06,480
Speaker 1: let me say, I have no doubt that our audience

730
00:38:06,600 --> 00:38:09,719
Speaker 1: is going to, you know, almost one hundred percent support

731
00:38:10,360 --> 00:38:12,759
Speaker 1: what you know. The fact that you were clearly in

732
00:38:12,800 --> 00:38:15,200
Speaker 1: the right of the washing post is ridiculous here. But

733
00:38:15,280 --> 00:38:18,000
Speaker 1: this is not without a cost for us either, because

734
00:38:18,160 --> 00:38:21,080
Speaker 1: we're very dependent, you know, in terms of the YouTube world.

735
00:38:21,440 --> 00:38:23,719
Speaker 1: We're dependent on whether they deem us to be a

736
00:38:23,719 --> 00:38:27,120
Speaker 1: trustworthy news source or not, and how the algorithm deals

737
00:38:27,160 --> 00:38:29,120
Speaker 1: with our videos and how much they serve them, and

738
00:38:29,239 --> 00:38:32,160
Speaker 1: all of those things. So it's not without a cost

739
00:38:32,239 --> 00:38:35,880
Speaker 1: and a price when the mainstream comes after you and

740
00:38:36,000 --> 00:38:40,600
Speaker 1: tries to sideline you as some crank, some bully, some troll,

741
00:38:40,719 --> 00:38:43,680
Speaker 1: et cetera. Are we a conservative YouTube show? Ask yourself

742
00:38:43,680 --> 00:38:46,800
Speaker 1: that are we a conservative YouTube show? That's bs okay

743
00:38:47,080 --> 00:38:49,319
Speaker 1: and just the way. Yeah. Look, I mean, I don't

744
00:38:49,320 --> 00:38:52,160
Speaker 1: want to belabor the point, but it has real costs

745
00:38:52,280 --> 00:38:54,920
Speaker 1: to us. Not as much because we rely on our

746
00:38:54,960 --> 00:38:58,080
Speaker 1: premium subs and on our audience, but you know, this

747
00:38:58,280 --> 00:39:00,480
Speaker 1: really could have been a big problem for all of us.

748
00:39:00,480 --> 00:39:01,959
Speaker 1: So anyway, I want to thank you all once again

749
00:39:02,200 --> 00:39:03,799
Speaker 1: just for having my back and it gives me the

750
00:39:03,800 --> 00:39:06,040
Speaker 1: confidence in order to speak out against the time. This was,

751
00:39:06,239 --> 00:39:08,480
Speaker 1: I mean, this was not a borderline case. There was

752
00:39:08,520 --> 00:39:12,000
Speaker 1: really no nuance here. You're very clearly well within the

753
00:39:12,000 --> 00:39:15,280
Speaker 1: bounds of public debate and discussion, and the Washington Post

754
00:39:15,440 --> 00:39:18,880
Speaker 1: is lost their minds in a very dishonest and nasty way.

755
00:39:18,920 --> 00:39:21,120
Speaker 1: All right, let's talk about substantive stuff. Okay, I mean

756
00:39:21,160 --> 00:39:23,520
Speaker 1: I think that was substantive too, in my opinion. But yes,

757
00:39:23,600 --> 00:39:26,279
Speaker 1: let's stop talking about us and start talking about the

758
00:39:26,280 --> 00:39:31,600
Speaker 1: Biden administration is thinking about maybe canceling some student loan debt.

759
00:39:31,680 --> 00:39:33,840
Speaker 1: Let's go ahead and put this Wall Street Journal article

760
00:39:33,920 --> 00:39:36,320
Speaker 1: up on the screen. They say, Biden seriously considering student

761
00:39:36,360 --> 00:39:39,200
Speaker 1: loan forgiveness. Official say President may be warming to take

762
00:39:39,239 --> 00:39:42,200
Speaker 1: executive action to a race at least some loan debt.

763
00:39:42,280 --> 00:39:47,160
Speaker 1: Some Democrats believe a move would motivate young voters in midterms. Basically,

764
00:39:47,239 --> 00:39:50,240
Speaker 1: what happened is he was in one of these caucus

765
00:39:50,239 --> 00:39:54,040
Speaker 1: meetings and didn't detail his plans, but responded positively when

766
00:39:54,080 --> 00:39:57,439
Speaker 1: lawmakers pushed him to forgive ten thousand dollars in student debt.

767
00:39:57,760 --> 00:40:00,319
Speaker 1: The people said suggesting they would be happy with his

768
00:40:00,360 --> 00:40:03,440
Speaker 1: final decision. He also indicated he's open to further extending

769
00:40:03,600 --> 00:40:05,839
Speaker 1: the current pause on student loan payments, which is set

770
00:40:05,880 --> 00:40:08,640
Speaker 1: to expire on August thirty first. Obviously, this is a

771
00:40:09,000 --> 00:40:12,920
Speaker 1: massive issue just because the astronomical amounts of debt that

772
00:40:13,000 --> 00:40:16,480
Speaker 1: are held by student loan debt holders about forty million people.

773
00:40:16,520 --> 00:40:19,520
Speaker 1: Forty million people, oh, around one point six trillion dollars

774
00:40:19,560 --> 00:40:22,320
Speaker 1: in federal student debt. That makes up around ninety percent

775
00:40:22,360 --> 00:40:25,760
Speaker 1: of student debt outstanding. So just pointing out there this, obviously,

776
00:40:25,800 --> 00:40:28,399
Speaker 1: whatever Biden would do would only apply to the debt

777
00:40:28,400 --> 00:40:30,759
Speaker 1: that's held by the government that makes up about ninety

778
00:40:30,800 --> 00:40:34,520
Speaker 1: percent of student debt outstanding. The politics of this, let's

779
00:40:34,520 --> 00:40:36,840
Speaker 1: go ahead and put this Insider report up on the screen.

780
00:40:37,320 --> 00:40:40,640
Speaker 1: So the reason that they are at long last considering

781
00:40:40,680 --> 00:40:44,759
Speaker 1: this move is because young people are not happy with

782
00:40:44,800 --> 00:40:48,040
Speaker 1: the Biden administration and are extraordinarily apathetic about whether they're

783
00:40:48,040 --> 00:40:50,440
Speaker 1: going to vote in the mid terms. But you have

784
00:40:50,560 --> 00:40:53,680
Speaker 1: a Harvard poll that found eighty five percent of young

785
00:40:53,719 --> 00:40:57,200
Speaker 1: Americans wanting Biden to take some form of action on

786
00:40:57,320 --> 00:41:00,560
Speaker 1: student debt. The flip side of that is, in this

787
00:41:00,600 --> 00:41:03,040
Speaker 1: Harvard Polish. It's actually interesting worth digging into in and

788
00:41:03,040 --> 00:41:05,800
Speaker 1: of itself. But they found forty two percent of voters

789
00:41:05,880 --> 00:41:08,600
Speaker 1: under thirty don't believe their votes make a real difference.

790
00:41:08,640 --> 00:41:11,080
Speaker 1: And part of that is because, you know whatever, and

791
00:41:11,120 --> 00:41:13,480
Speaker 1: we're going to debate the merits of this particular proposal

792
00:41:13,480 --> 00:41:15,680
Speaker 1: in a moment, But whatever you think of it, Biden

793
00:41:15,719 --> 00:41:18,160
Speaker 1: did promise to do something on student loan debt. Has

794
00:41:18,239 --> 00:41:20,720
Speaker 1: all of the power at his disposal to do something

795
00:41:20,719 --> 00:41:23,440
Speaker 1: about student loan debt, made that promise on the campaign

796
00:41:23,480 --> 00:41:25,759
Speaker 1: trail very popular with young voters, and then here we

797
00:41:25,800 --> 00:41:28,239
Speaker 1: are and he still hasn't done it. So gee, I

798
00:41:28,280 --> 00:41:30,640
Speaker 1: wonder why so many young voters feel like their votes

799
00:41:30,680 --> 00:41:34,080
Speaker 1: don't make a real difference. And again to the question

800
00:41:34,239 --> 00:41:36,920
Speaker 1: of you know how this may impact them politically, go

801
00:41:36,960 --> 00:41:39,800
Speaker 1: ahead and put this up on the screen. Biden's approval

802
00:41:39,920 --> 00:41:44,919
Speaker 1: with voters under thirty now drops to forty one percent. Now,

803
00:41:45,000 --> 00:41:48,200
Speaker 1: this was one of the strongest groups that helped to

804
00:41:48,280 --> 00:41:52,040
Speaker 1: elect him president. You know, he won young voters overwhelmingly

805
00:41:52,520 --> 00:41:55,920
Speaker 1: at the beginning of his presidency. His highest approval ratings

806
00:41:56,280 --> 00:41:59,640
Speaker 1: came among this youngest demographic. And now, as I covered

807
00:41:59,680 --> 00:42:03,640
Speaker 1: last week, that has completely flipped. So actually Biden's approval

808
00:42:03,719 --> 00:42:07,720
Speaker 1: rating is best with the oldest age demographic and worst

809
00:42:08,080 --> 00:42:12,280
Speaker 1: with young voters. So they're looking at the midterms saying, guys,

810
00:42:12,360 --> 00:42:15,120
Speaker 1: it looks like we are completely screwed. What can we

811
00:42:15,280 --> 00:42:18,400
Speaker 1: possibly do? Joe Manchin continues to jerk us around and

812
00:42:18,400 --> 00:42:20,640
Speaker 1: build back better, and that seems like as hopeless as

813
00:42:20,640 --> 00:42:23,360
Speaker 1: it ever has. So this is something in our power. Jeez,

814
00:42:23,400 --> 00:42:26,160
Speaker 1: maybe we should actually do something at this point. Now.

815
00:42:26,200 --> 00:42:27,839
Speaker 1: I do think the politics here are a little bit

816
00:42:27,840 --> 00:42:32,200
Speaker 1: more complicated. For one thing, young voters not particularly reliable

817
00:42:32,239 --> 00:42:35,719
Speaker 1: midterm voters are or otherwise, but particularly in the midterms.

818
00:42:36,000 --> 00:42:40,120
Speaker 1: I do think that there is you know, the backlash

819
00:42:40,200 --> 00:42:42,400
Speaker 1: or the argument against this is basically like, well what

820
00:42:42,440 --> 00:42:46,040
Speaker 1: about people who aren't college you know, college student loan folders?

821
00:42:46,520 --> 00:42:50,799
Speaker 1: And the other question, which our friend Philip asked Densaki,

822
00:42:50,920 --> 00:42:53,440
Speaker 1: is about, Okay, well what about people who you know

823
00:42:53,719 --> 00:42:56,279
Speaker 1: worked hard and their parents grimpton saved and they actually

824
00:42:56,320 --> 00:42:58,480
Speaker 1: paid off their student loan debt. Aren't they kind of

825
00:42:58,520 --> 00:43:00,480
Speaker 1: getting a raw deal? Let's take a listen to that question.

826
00:43:00,840 --> 00:43:03,960
Speaker 1: All up on the student loansness, you said that the

827
00:43:04,000 --> 00:43:06,720
Speaker 1: president is looking at a range of options with regards

828
00:43:06,719 --> 00:43:09,960
Speaker 1: to canceling some student debt. But is the president looking

829
00:43:10,000 --> 00:43:13,560
Speaker 1: at any options for those students and parents who saved

830
00:43:13,560 --> 00:43:15,799
Speaker 1: and sacrificed so that they wouldn't have to take out

831
00:43:15,960 --> 00:43:19,000
Speaker 1: such massive loans. Is he looking at including them in

832
00:43:19,040 --> 00:43:22,160
Speaker 1: relief retroactively? How would they be made whole if there

833
00:43:22,239 --> 00:43:24,040
Speaker 1: was some sort of canceling debt. You mean for people

834
00:43:24,080 --> 00:43:26,839
Speaker 1: who have paid off all of their student loans, made

835
00:43:26,840 --> 00:43:29,319
Speaker 1: sacrifices so that they wouldn't have to take out some

836
00:43:29,360 --> 00:43:31,920
Speaker 1: of those loans. It's a good question. What I can

837
00:43:31,960 --> 00:43:34,839
Speaker 1: tell you at this point is that there's legislation he'd

838
00:43:34,880 --> 00:43:37,200
Speaker 1: be happy to sign for individuals who have ten thousand

839
00:43:37,200 --> 00:43:40,560
Speaker 1: dollars in existing student debt. If Congress wanted to send

840
00:43:40,600 --> 00:43:42,160
Speaker 1: that to him, he'd be happy to sign. And he's

841
00:43:42,200 --> 00:43:44,960
Speaker 1: looking at executive actions and authorities. But I don't have

842
00:43:45,040 --> 00:43:47,560
Speaker 1: anything to preview on that front. So I think those

843
00:43:47,600 --> 00:43:51,560
Speaker 1: two things are potentially politically potent. Both the questions fair questions. Well,

844
00:43:51,560 --> 00:43:54,560
Speaker 1: it's definitely a fair question. I will point out on

845
00:43:54,600 --> 00:43:56,640
Speaker 1: the substance, and I want to get your thought on

846
00:43:56,640 --> 00:43:58,440
Speaker 1: the politics, and then we can talk more about, like,

847
00:43:58,560 --> 00:44:01,040
Speaker 1: you know, who actually would benefit some of the details

848
00:44:01,080 --> 00:44:05,600
Speaker 1: behind this, but you already do have subsidies for people

849
00:44:05,719 --> 00:44:08,920
Speaker 1: who are higher wealth and able to save in advance

850
00:44:09,160 --> 00:44:12,400
Speaker 1: for their kids college. So you have covered out and

851
00:44:12,560 --> 00:44:15,640
Speaker 1: five twenty nine education savings accounts so that you can

852
00:44:15,640 --> 00:44:19,480
Speaker 1: have tuition functioning as a tax advantage intergenerational transfer. So

853
00:44:19,520 --> 00:44:23,200
Speaker 1: you actually do already have subsidies in place for those

854
00:44:23,239 --> 00:44:25,680
Speaker 1: parents that phil is talking about there who are able

855
00:44:25,840 --> 00:44:30,359
Speaker 1: to save in advance for their kids' education. So, in fact,

856
00:44:30,480 --> 00:44:32,279
Speaker 1: you know, the system is kind of unfair right now

857
00:44:32,280 --> 00:44:34,279
Speaker 1: towards those who don't have the ability to save in

858
00:44:34,320 --> 00:44:37,160
Speaker 1: advance and have to take out these massive student loans.

859
00:44:37,320 --> 00:44:39,239
Speaker 1: But on the politics of it, I think it is

860
00:44:39,480 --> 00:44:43,839
Speaker 1: overwhelmingly popular with young voters, who disproportionately are the ones

861
00:44:43,880 --> 00:44:46,400
Speaker 1: who are burdened by the student loan debt, who feel

862
00:44:46,400 --> 00:44:49,040
Speaker 1: their futures are constrained by the amount of debt that

863
00:44:49,080 --> 00:44:52,000
Speaker 1: they oftentimes graduate college with, who were sold this bill

864
00:44:52,040 --> 00:44:54,560
Speaker 1: of goods of like, you know, the answer to everything

865
00:44:54,600 --> 00:44:56,799
Speaker 1: is to get a college education. I think that's particularly

866
00:44:56,800 --> 00:44:59,640
Speaker 1: true of Black Americans who were told basically like this

867
00:44:59,680 --> 00:45:01,520
Speaker 1: is the way to build wealth, this is the way

868
00:45:01,520 --> 00:45:04,480
Speaker 1: to close the racial wealth gap, and ultimately, you know,

869
00:45:04,600 --> 00:45:07,319
Speaker 1: it didn't end up being the certain ticket that they

870
00:45:07,320 --> 00:45:10,680
Speaker 1: thought it would be, and because the costs are so outrageous,

871
00:45:11,000 --> 00:45:14,600
Speaker 1: they've been saddled with something for life. So for young voters,

872
00:45:14,640 --> 00:45:17,520
Speaker 1: do I think it will help? Maybe marginally at this point,

873
00:45:17,680 --> 00:45:19,600
Speaker 1: but I do think the overall politics are a little

874
00:45:19,600 --> 00:45:21,960
Speaker 1: more fraud than maybe people would want to, people with

875
00:45:22,040 --> 00:45:24,080
Speaker 1: my ideological view would want to. I'm glad you you

876
00:45:24,120 --> 00:45:25,680
Speaker 1: could say that. I mean, because I do think that

877
00:45:25,760 --> 00:45:27,600
Speaker 1: this is an important point. More than half of young

878
00:45:27,600 --> 00:45:29,520
Speaker 1: people did not go to college, and so look, I

879
00:45:29,560 --> 00:45:32,080
Speaker 1: believe ultimately I think the people who got saddled with

880
00:45:32,080 --> 00:45:34,600
Speaker 1: student debt got sold a bill of goods. But you

881
00:45:34,640 --> 00:45:36,799
Speaker 1: know who I blamed the bill of goods for the

882
00:45:36,960 --> 00:45:40,640
Speaker 1: university system. So bailing out the university system who continues

883
00:45:40,719 --> 00:45:43,640
Speaker 1: to builk these kids not have any you know, actual

884
00:45:43,680 --> 00:45:47,239
Speaker 1: stake in how they're doing, and also not change university financing.

885
00:45:47,440 --> 00:45:49,919
Speaker 1: Let's be honest to where is the major bloat coming

886
00:45:49,960 --> 00:45:53,960
Speaker 1: in university budgets? That's increasing tuition, diversity and inclusion initiative?

887
00:45:54,080 --> 00:45:57,840
Speaker 1: So we should all bail out the diversity departments of Yale, Harvard?

888
00:45:58,000 --> 00:46:00,520
Speaker 1: Is that true? But I don't genuinely don't know. I

889
00:46:00,520 --> 00:46:04,120
Speaker 1: know administration overall, so I don't know that I have

890
00:46:04,200 --> 00:46:06,560
Speaker 1: seen any numbers that back up that the overwhelming amount

891
00:46:06,560 --> 00:46:08,759
Speaker 1: of the blow as well, let's just say it's all administration.

892
00:46:08,920 --> 00:46:11,680
Speaker 1: You can ask yourself where most administrative costs new cost

893
00:46:11,800 --> 00:46:13,320
Speaker 1: is being outlaid to, and I say, is both my

894
00:46:13,360 --> 00:46:16,879
Speaker 1: parents working here? There's an escalation and administration for many, many,

895
00:46:16,920 --> 00:46:18,759
Speaker 1: many years. Oh absolutely, But I'm talking in the last

896
00:46:18,760 --> 00:46:20,400
Speaker 1: ten years, which is also when the highest spike has

897
00:46:20,400 --> 00:46:23,680
Speaker 1: also been. So I think I think the most valid

898
00:46:24,080 --> 00:46:27,920
Speaker 1: critique and the most good faith critique here is the

899
00:46:28,000 --> 00:46:31,239
Speaker 1: idea of like, okay, but what what then? Yeah, you

900
00:46:31,280 --> 00:46:33,759
Speaker 1: do this, you do this one time thing now for

901
00:46:33,840 --> 00:46:36,359
Speaker 1: me personally, because I do think that this is such

902
00:46:36,360 --> 00:46:39,560
Speaker 1: an outrageous situation and a relatively new one too. I mean,

903
00:46:39,600 --> 00:46:42,200
Speaker 1: it's easy for us to forget because we've always come

904
00:46:42,239 --> 00:46:45,759
Speaker 1: of age during a time when college tuition is fucking insane.

905
00:46:45,840 --> 00:46:48,680
Speaker 1: But this is actually a really new phenomenon of it

906
00:46:48,760 --> 00:46:52,360
Speaker 1: being so insanely expensive that no one could hope to

907
00:46:52,400 --> 00:46:54,440
Speaker 1: be very few people could hope to be able to

908
00:46:54,520 --> 00:46:57,640
Speaker 1: actually afford it up front, and since it is such

909
00:46:57,680 --> 00:47:01,200
Speaker 1: a burden that really does weigh down younger generations. And

910
00:47:01,280 --> 00:47:03,960
Speaker 1: we've talked here about how you know, this sets everybody

911
00:47:04,040 --> 00:47:05,600
Speaker 1: back from being able to own a home, from being

912
00:47:05,640 --> 00:47:08,880
Speaker 1: able to start a family. Student loan debt really puts

913
00:47:08,920 --> 00:47:12,080
Speaker 1: this weight on top of both millennials and gen z

914
00:47:12,640 --> 00:47:16,360
Speaker 1: that it is worth some sort of solution, even if

915
00:47:16,480 --> 00:47:18,799
Speaker 1: it is, you know, not one hundred percent of what

916
00:47:18,840 --> 00:47:21,840
Speaker 1: you would ultimately want. So what I would say is,

917
00:47:21,880 --> 00:47:24,080
Speaker 1: don't let the perfect be the enemy of the good.

918
00:47:24,440 --> 00:47:26,799
Speaker 1: This is the tool that is at their disposal. This

919
00:47:26,840 --> 00:47:30,440
Speaker 1: would provide tremendous relief for you know, millions and millions

920
00:47:30,440 --> 00:47:32,880
Speaker 1: of people, And so I do think it's worth pursuing,

921
00:47:33,000 --> 00:47:35,560
Speaker 1: even as I acknowledge it's nowhere near a complete solution

922
00:47:35,719 --> 00:47:38,520
Speaker 1: without those other reforms that you're talking. My point would be,

923
00:47:38,560 --> 00:47:39,720
Speaker 1: first of all, I think it would be a political

924
00:47:39,760 --> 00:47:41,880
Speaker 1: disaster because I think a lot of people will feel slighted.

925
00:47:41,920 --> 00:47:43,719
Speaker 1: But two is it like And I should also be clear,

926
00:47:43,719 --> 00:47:46,840
Speaker 1: I actually believe in very four student loan forgiveness. However,

927
00:47:46,920 --> 00:47:49,040
Speaker 1: it has to be paired with the complete change in

928
00:47:49,080 --> 00:47:51,719
Speaker 1: the financing system of the universities. Number two, we can

929
00:47:51,760 --> 00:47:53,759
Speaker 1: never let this happen again. I was looking at some

930
00:47:53,800 --> 00:47:55,399
Speaker 1: of the data. Even if you wipe out one point

931
00:47:55,480 --> 00:47:57,560
Speaker 1: nine trillion dollars in debt, the debt load in about

932
00:47:57,560 --> 00:47:59,640
Speaker 1: five to ten years would also be one point nine trillion.

933
00:47:59,719 --> 00:48:01,399
Speaker 1: So what we're going to wipe it out do it again?

934
00:48:01,520 --> 00:48:03,200
Speaker 1: No way, But we can't do that because we're just

935
00:48:03,200 --> 00:48:05,400
Speaker 1: bailing out the university system. So but that's just an

936
00:48:05,520 --> 00:48:08,000
Speaker 1: argument for you know, Okay, you do this, and then

937
00:48:08,040 --> 00:48:10,840
Speaker 1: you have to actually reform, you have to have you know,

938
00:48:10,920 --> 00:48:14,280
Speaker 1: I personally think we should have free public college. Public

939
00:48:14,400 --> 00:48:17,359
Speaker 1: university at this point are at least very affordable. So

940
00:48:17,840 --> 00:48:20,560
Speaker 1: that's just an argument for this isn't the end all

941
00:48:20,600 --> 00:48:23,560
Speaker 1: be all. This is just the beginning. But I think

942
00:48:23,600 --> 00:48:27,120
Speaker 1: it's I think again to say, well, it's not perfect

943
00:48:27,200 --> 00:48:30,000
Speaker 1: and it doesn't actually solve the whole problem, so let's

944
00:48:30,000 --> 00:48:33,239
Speaker 1: just forget about it. Well, that's that denies a lot

945
00:48:33,280 --> 00:48:36,160
Speaker 1: of people relief right now that would be very beneficial

946
00:48:36,200 --> 00:48:39,040
Speaker 1: to them. And so we have some stats that you know,

947
00:48:39,160 --> 00:48:40,879
Speaker 1: kind of make points in vote directly. Let's go ahead

948
00:48:40,920 --> 00:48:43,160
Speaker 1: and put the next piece up on the screen there

949
00:48:43,160 --> 00:48:45,840
Speaker 1: From Brookings, this is interesting because a lot of the

950
00:48:46,080 --> 00:48:48,920
Speaker 1: help would go to people who are relatively high income

951
00:48:49,360 --> 00:48:53,120
Speaker 1: who went to graduate school if you did doctors, you know,

952
00:48:53,360 --> 00:48:56,279
Speaker 1: and this is if you did complete debt cancelation. So

953
00:48:56,280 --> 00:48:59,560
Speaker 1: what Biden's talking about at most is ten thousand dollars.

954
00:48:59,719 --> 00:49:02,880
Speaker 1: Even that's uncertain, and they've also floated, like you know,

955
00:49:02,920 --> 00:49:05,640
Speaker 1: it may be income based, so some of this debate

956
00:49:05,680 --> 00:49:07,920
Speaker 1: may be a little bit moot. But you know, they

957
00:49:07,920 --> 00:49:09,640
Speaker 1: point out that in this piece, which I actually hadn't

958
00:49:09,640 --> 00:49:12,560
Speaker 1: really thought about that in fact, the way to think

959
00:49:12,600 --> 00:49:15,400
Speaker 1: about it is, Okay, well, how much of this debt?

960
00:49:15,640 --> 00:49:18,400
Speaker 1: How much is this debt as a percentage of your income,

961
00:49:18,680 --> 00:49:22,080
Speaker 1: because obviously, if you're someone who's earning a relatively low income,

962
00:49:22,360 --> 00:49:25,200
Speaker 1: you're going to experience that ten thousand dollars in debt

963
00:49:25,360 --> 00:49:28,080
Speaker 1: as a much heavier burden than someone who's at the

964
00:49:28,160 --> 00:49:32,040
Speaker 1: high end of the income threshold. And the person who

965
00:49:32,120 --> 00:49:34,719
Speaker 1: wrote this analysis made the case of like you know,

966
00:49:34,880 --> 00:49:38,440
Speaker 1: sales tax is widely considered a regressive tax because it

967
00:49:38,480 --> 00:49:41,200
Speaker 1: takes up more of your income if you are a

968
00:49:41,239 --> 00:49:44,120
Speaker 1: low income person. Even the wealthy people, because they spend

969
00:49:44,120 --> 00:49:47,160
Speaker 1: more money, they pay more of the tax. So it

970
00:49:47,200 --> 00:49:50,600
Speaker 1: really is important to think about it in relation to

971
00:49:50,840 --> 00:49:53,279
Speaker 1: a percent of income. And then also we'll get to

972
00:49:53,360 --> 00:49:56,120
Speaker 1: in a moment, it also is very different. The picture

973
00:49:56,200 --> 00:49:58,600
Speaker 1: is very different when you're thinking about income versus when

974
00:49:58,640 --> 00:50:02,120
Speaker 1: you're thinking about total wealth. And one thing we've talked

975
00:50:02,160 --> 00:50:04,960
Speaker 1: here a lot about recently is how much the sort

976
00:50:04,960 --> 00:50:08,680
Speaker 1: of asset and wealth economy is even more important indicator

977
00:50:08,719 --> 00:50:11,840
Speaker 1: at this point than thinking about just what your income is,

978
00:50:11,840 --> 00:50:13,719
Speaker 1: because you could have a relatively low income, but if

979
00:50:13,760 --> 00:50:16,080
Speaker 1: you've got you know, if you own a home, for example,

980
00:50:16,120 --> 00:50:18,680
Speaker 1: then you're in a much better position. So people have

981
00:50:18,840 --> 00:50:22,200
Speaker 1: high levels of student loan debt that really puts a

982
00:50:22,280 --> 00:50:24,719
Speaker 1: huge burden on them in terms of being able to

983
00:50:24,920 --> 00:50:27,200
Speaker 1: buy a home or have that asset creation that puts

984
00:50:27,280 --> 00:50:29,400
Speaker 1: them into middle class life. So that's why I think,

985
00:50:29,880 --> 00:50:31,680
Speaker 1: even as it's not you know, one hundred percent or

986
00:50:31,680 --> 00:50:33,840
Speaker 1: perfect solution or all that I would see, all that

987
00:50:33,880 --> 00:50:36,400
Speaker 1: I would want to see, having at least some student

988
00:50:36,400 --> 00:50:39,360
Speaker 1: loan debt relief will really be significant for a generation

989
00:50:39,440 --> 00:50:41,520
Speaker 1: that has just come screwed over again and again and

990
00:50:41,520 --> 00:50:43,200
Speaker 1: again their entire life. Let's put the next one up

991
00:50:43,239 --> 00:50:45,560
Speaker 1: there on the screen because this is also important. So

992
00:50:45,680 --> 00:50:48,719
Speaker 1: take a look actually at that pie chart, because the

993
00:50:48,840 --> 00:50:52,040
Speaker 1: largest amount of the benefit, only sixty percent of household

994
00:50:52,040 --> 00:50:54,680
Speaker 1: bottom sixty percent receive only thirty four percent of the benefit.

995
00:50:54,920 --> 00:50:57,280
Speaker 1: Because of the outstanding load of the amount of debt,

996
00:50:57,719 --> 00:51:00,239
Speaker 1: people cannot conceive of just how much debt these lawyers

997
00:51:00,440 --> 00:51:02,640
Speaker 1: and these doctors are holding. And once again, I just

998
00:51:02,680 --> 00:51:05,640
Speaker 1: am completely against the idea of bailing out these low

999
00:51:05,719 --> 00:51:08,440
Speaker 1: rate law schools which are charging sixty to one hundred grand,

1000
00:51:08,719 --> 00:51:11,319
Speaker 1: really criminalizing a lot of these students and setting them

1001
00:51:11,400 --> 00:51:13,880
Speaker 1: up for lifelong Are you supposed though, even to the

1002
00:51:14,000 --> 00:51:16,439
Speaker 1: more like ten thousand dollars or if it's income coany

1003
00:51:16,480 --> 00:51:18,640
Speaker 1: it depends because once again, even on the ten thousand,

1004
00:51:18,719 --> 00:51:20,279
Speaker 1: you know, here's another point which is part of the

1005
00:51:20,280 --> 00:51:22,440
Speaker 1: reason why the student debt is so high amongst the

1006
00:51:22,440 --> 00:51:25,960
Speaker 1: bottom quintile, because the bottom quintile is also disproportionately more

1007
00:51:26,040 --> 00:51:28,239
Speaker 1: likely not to have gone to college or not graduated

1008
00:51:28,239 --> 00:51:30,239
Speaker 1: from college. So the data does show us that if

1009
00:51:30,280 --> 00:51:33,400
Speaker 1: you actually graduate, you're mostly on track in order to

1010
00:51:33,400 --> 00:51:36,120
Speaker 1: pay off your debt if you went to a public university. However,

1011
00:51:36,160 --> 00:51:38,640
Speaker 1: the people who get most screwed who take out loans

1012
00:51:38,680 --> 00:51:41,160
Speaker 1: and then they drop out. So actually those people I'm

1013
00:51:41,200 --> 00:51:42,920
Speaker 1: the most concerned about it, and I'll be most in

1014
00:51:42,960 --> 00:51:45,480
Speaker 1: favor of wiping out their debt because they have none

1015
00:51:45,480 --> 00:51:48,319
Speaker 1: of the benefit all of the saddle. So that's really tough.

1016
00:51:48,640 --> 00:51:50,239
Speaker 1: Like I said, and I think about this a little

1017
00:51:50,239 --> 00:51:52,479
Speaker 1: bit like Wall Street. Look, there was a decent case

1018
00:51:52,560 --> 00:51:54,399
Speaker 1: to bail out Wall Street, right, like, Hey, we got

1019
00:51:54,400 --> 00:51:56,920
Speaker 1: to bail out Wall Street. People need able to make payroll,

1020
00:51:57,080 --> 00:52:00,319
Speaker 1: we need a financial system, all of that. But did

1021
00:52:00,400 --> 00:52:03,000
Speaker 1: we deal with the underlying problem. No, we actually have

1022
00:52:03,040 --> 00:52:05,120
Speaker 1: a probably more of a criminal Wall Street system than

1023
00:52:05,160 --> 00:52:09,359
Speaker 1: we do today than before because these restular borrowers are

1024
00:52:09,400 --> 00:52:11,920
Speaker 1: not equivalent to Wall Street ghules who deserve to go

1025
00:52:11,920 --> 00:52:13,719
Speaker 1: to pres Right. But but the whole point was at

1026
00:52:13,719 --> 00:52:15,560
Speaker 1: the time is how are people going to make payroll?

1027
00:52:15,640 --> 00:52:18,360
Speaker 1: Normal ask people need to get their paychecks. People all this,

1028
00:52:18,480 --> 00:52:20,839
Speaker 1: That's why we did it. Ultimately, in the first place,

1029
00:52:20,880 --> 00:52:22,640
Speaker 1: there was a case, a decent case at the time,

1030
00:52:22,680 --> 00:52:24,919
Speaker 1: that real people's lives were going to be affected by

1031
00:52:24,960 --> 00:52:27,840
Speaker 1: a complete bank collapse, which was correct. But and I

1032
00:52:27,840 --> 00:52:29,680
Speaker 1: think the correct case at the time, which I know

1033
00:52:29,719 --> 00:52:32,640
Speaker 1: you agree with, is we had to change the underlying system,

1034
00:52:32,840 --> 00:52:35,520
Speaker 1: which we did not do. But I don't think it's

1035
00:52:35,520 --> 00:52:37,839
Speaker 1: a good analogy, because you're talking about bailing on people

1036
00:52:37,880 --> 00:52:40,680
Speaker 1: who profoundly did not deserve it. This is talking about

1037
00:52:40,680 --> 00:52:44,040
Speaker 1: people who profoundly do deserve it, who were really like

1038
00:52:44,480 --> 00:52:47,040
Speaker 1: sold a bill of goods, you know, walk down this

1039
00:52:47,480 --> 00:52:51,000
Speaker 1: rosy path of just take on the debt, go to college,

1040
00:52:51,040 --> 00:52:53,439
Speaker 1: this is a way to build wealth, and then we're

1041
00:52:53,440 --> 00:52:55,879
Speaker 1: stuck with a bill that is just completely insane, and which,

1042
00:52:55,960 --> 00:52:57,840
Speaker 1: by the way, if we're just being real, many of

1043
00:52:57,880 --> 00:53:00,319
Speaker 1: them will never pay. I mean that's part of it too,

1044
00:53:00,480 --> 00:53:04,320
Speaker 1: is like the amount of debt that has been loaded

1045
00:53:04,360 --> 00:53:06,880
Speaker 1: on top of these generations, it's just going to be

1046
00:53:07,000 --> 00:53:10,080
Speaker 1: with them hanging like a rock around their neck for

1047
00:53:10,120 --> 00:53:14,920
Speaker 1: their entire lives. So yeah, it's you know, I would

1048
00:53:14,960 --> 00:53:17,279
Speaker 1: like to see us reform our systems so that we

1049
00:53:17,360 --> 00:53:19,680
Speaker 1: have free public college. I would like to have debt

1050
00:53:19,719 --> 00:53:24,360
Speaker 1: completely wipe down, but I would support even a limited

1051
00:53:25,239 --> 00:53:28,600
Speaker 1: forgiveness so that people can start to get ahead again,

1052
00:53:28,640 --> 00:53:32,279
Speaker 1: because you know, the real path to the American dream

1053
00:53:32,320 --> 00:53:34,399
Speaker 1: at this point is to be able to own a home.

1054
00:53:34,480 --> 00:53:36,719
Speaker 1: And if you've got this debt burden on top of you,

1055
00:53:36,760 --> 00:53:40,440
Speaker 1: if your entire life, it makes it so difficult for

1056
00:53:40,480 --> 00:53:43,360
Speaker 1: you to be able to ever become part of the

1057
00:53:43,360 --> 00:53:46,360
Speaker 1: asset ownership class, which is why we see millennials and

1058
00:53:46,440 --> 00:53:50,400
Speaker 1: gen z so consistently screwed. We have some this is

1059
00:53:50,640 --> 00:53:53,600
Speaker 1: let's put Matt Bernigg's analysis up on the screen here

1060
00:53:53,600 --> 00:53:57,239
Speaker 1: because this is interesting as well. He's got just some

1061
00:53:57,400 --> 00:54:00,160
Speaker 1: numbers about what is the current student debt situation, and

1062
00:54:00,200 --> 00:54:03,480
Speaker 1: you could see there just how much money is owed

1063
00:54:03,520 --> 00:54:06,200
Speaker 1: somewhere between one point one trillion and one point sixty

1064
00:54:06,280 --> 00:54:08,320
Speaker 1: five trillion. Let's go ahead and put the next piece

1065
00:54:08,400 --> 00:54:10,439
Speaker 1: up on the screen, the next chart that we have here.

1066
00:54:10,760 --> 00:54:13,160
Speaker 1: So this makes the case you're making Zaga of if

1067
00:54:13,200 --> 00:54:15,359
Speaker 1: you look at the shriff student debt owed by each

1068
00:54:15,360 --> 00:54:19,160
Speaker 1: income quintile, it actually goes up as you become wealthier.

1069
00:54:19,480 --> 00:54:21,680
Speaker 1: But he points out another way of thinking about it

1070
00:54:21,760 --> 00:54:24,480
Speaker 1: is if you look at the shriff student debt by

1071
00:54:25,160 --> 00:54:27,399
Speaker 1: wealth rather than income, go ahead and put this next

1072
00:54:27,400 --> 00:54:30,920
Speaker 1: piece up on the screen. The dynamic actually flips. And

1073
00:54:30,960 --> 00:54:34,239
Speaker 1: that's partly because if you are weighed down by student debt,

1074
00:54:34,320 --> 00:54:38,120
Speaker 1: then you know undoubtedly you're going to have less wealth overall,

1075
00:54:38,160 --> 00:54:40,719
Speaker 1: because that student debt is putting a tremendous burden on

1076
00:54:40,760 --> 00:54:42,680
Speaker 1: you and bringing your wealth down to really low levels.

1077
00:54:42,719 --> 00:54:47,520
Speaker 1: So you have here the least wealthy fifth quintile has

1078
00:54:47,680 --> 00:54:51,480
Speaker 1: fifty five percent of the share of student debt. So

1079
00:54:52,040 --> 00:54:54,640
Speaker 1: I think, you know, that's a really important distinction to

1080
00:54:54,680 --> 00:54:56,960
Speaker 1: make too. Is it's one thing to think about income

1081
00:54:57,000 --> 00:55:00,520
Speaker 1: flows in, but not everybody who is, you know, earning

1082
00:55:00,560 --> 00:55:02,520
Speaker 1: the same level of income is in the same boat

1083
00:55:02,600 --> 00:55:05,279
Speaker 1: in terms of their overall wealth and ability to own assets. Yeah,

1084
00:55:05,280 --> 00:55:06,640
Speaker 1: and let's put the next one up here, just to

1085
00:55:06,680 --> 00:55:09,560
Speaker 1: be entirely clear about what the Biden people are actually considering.

1086
00:55:09,600 --> 00:55:12,600
Speaker 1: So a source familiar Catael's NBC that they are thinking

1087
00:55:12,600 --> 00:55:14,919
Speaker 1: no decision is made and that any loan cancelation would

1088
00:55:14,960 --> 00:55:17,040
Speaker 1: be linked to income. So, according to the people I've

1089
00:55:17,080 --> 00:55:19,800
Speaker 1: spoken to, a ten k up to ten k capped

1090
00:55:19,800 --> 00:55:22,600
Speaker 1: by income is the most likely scenario. Look, I mean,

1091
00:55:22,640 --> 00:55:24,880
Speaker 1: I guess I would be okay with it, but actually

1092
00:55:24,880 --> 00:55:27,440
Speaker 1: think it would be dramatically unpopular. And one of the

1093
00:55:27,440 --> 00:55:29,879
Speaker 1: reasons why I'm against this type of ad hoc type

1094
00:55:29,880 --> 00:55:32,560
Speaker 1: policy is we have to have everybody have some buy

1095
00:55:32,560 --> 00:55:34,360
Speaker 1: in here. So I would be much more in favor

1096
00:55:34,600 --> 00:55:37,239
Speaker 1: of a ten thousand dollars type wipeout as long as

1097
00:55:37,280 --> 00:55:40,520
Speaker 1: we restructure the incentive systems for all younger Americans. So

1098
00:55:40,600 --> 00:55:43,799
Speaker 1: think about how many working class young people over the

1099
00:55:43,840 --> 00:55:46,320
Speaker 1: last couple of years have been saddled down by credit

1100
00:55:46,360 --> 00:55:48,360
Speaker 1: card debt and others. If you even look at the

1101
00:55:48,360 --> 00:55:51,400
Speaker 1: polling data on why people aren't getting married or having children,

1102
00:55:51,520 --> 00:55:53,960
Speaker 1: the number one reason is financing. So again, in a

1103
00:55:54,000 --> 00:55:55,880
Speaker 1: country where fifty five percent of people don't even go

1104
00:55:55,920 --> 00:55:58,360
Speaker 1: to college, don't even try, they also have an immense

1105
00:55:58,360 --> 00:56:00,920
Speaker 1: amount of debt, I would be much more favor of Okay,

1106
00:56:00,960 --> 00:56:03,640
Speaker 1: let's say ten k cap it by income those people

1107
00:56:03,840 --> 00:56:05,800
Speaker 1: all is here frame. It is like a new start,

1108
00:56:05,800 --> 00:56:08,080
Speaker 1: a new deal, some sort of thing. Yeah, for those folks,

1109
00:56:08,160 --> 00:56:11,880
Speaker 1: because universal systems like social Security and medicare where everybody

1110
00:56:11,880 --> 00:56:14,800
Speaker 1: in a generation actually universally benefits from something. Is just

1111
00:56:14,920 --> 00:56:17,200
Speaker 1: much more preferable to me, because right now this is

1112
00:56:17,200 --> 00:56:19,480
Speaker 1: class warfare. I mean, let's be honest, like, these people

1113
00:56:19,520 --> 00:56:22,799
Speaker 1: are disproportionately Democrats, so it's a bailout also of their

1114
00:56:22,840 --> 00:56:25,560
Speaker 1: own voters. And also it's just I don't think it's

1115
00:56:25,600 --> 00:56:28,080
Speaker 1: right to have the educated class get a bailout when

1116
00:56:28,320 --> 00:56:31,880
Speaker 1: young working class folks who actually pay taxes are getting

1117
00:56:31,880 --> 00:56:34,279
Speaker 1: nothing from me. It all depends on what problem you're

1118
00:56:34,280 --> 00:56:36,000
Speaker 1: trying to solve, Right, If the problem you're trying to

1119
00:56:36,040 --> 00:56:38,520
Speaker 1: solve is just like people have been screwed overall, and

1120
00:56:38,560 --> 00:56:42,160
Speaker 1: so they should get help overall, like which I believe honestly,

1121
00:56:42,320 --> 00:56:44,640
Speaker 1: Like I'm totally good sending out a ten thousand dollars

1122
00:56:44,680 --> 00:56:46,880
Speaker 1: check to everybody in the country and having it happen

1123
00:56:46,960 --> 00:56:49,840
Speaker 1: on a routine basis, and you know, redistribution so that

1124
00:56:49,880 --> 00:56:52,319
Speaker 1: we have you know, massive transfer well to make the

1125
00:56:52,360 --> 00:56:55,239
Speaker 1: country less unequal. I am one hundred percent on board

1126
00:56:55,239 --> 00:56:58,759
Speaker 1: with that. I don't hear that particular argument coming from

1127
00:56:58,760 --> 00:57:01,880
Speaker 1: many conservatives. No, mostly they just want to argue against

1128
00:57:01,920 --> 00:57:05,720
Speaker 1: any help for anybody. And so you know that if

1129
00:57:05,760 --> 00:57:07,560
Speaker 1: the problem you're trying to solve is people are poor

1130
00:57:07,560 --> 00:57:10,040
Speaker 1: and they need help overall, in general, they've been screwed, Okay,

1131
00:57:10,080 --> 00:57:12,960
Speaker 1: that's one problem that requires a universal solution. If the

1132
00:57:12,960 --> 00:57:15,560
Speaker 1: problem you're trying to solve is people have been screwed over,

1133
00:57:15,640 --> 00:57:21,000
Speaker 1: specifically by the college education system and the massive tuition bills,

1134
00:57:21,320 --> 00:57:24,000
Speaker 1: then this makes more sense as a solution. And by

1135
00:57:24,080 --> 00:57:25,960
Speaker 1: the way, you know, the younger you go on the

1136
00:57:27,320 --> 00:57:30,160
Speaker 1: demographics scale, the more likely you are to have gone

1137
00:57:30,160 --> 00:57:36,520
Speaker 1: to college. So like gen Z, overwhelming majority do some college.

1138
00:57:36,560 --> 00:57:38,480
Speaker 1: They may not graduate with a four year college degree,

1139
00:57:38,480 --> 00:57:40,560
Speaker 1: which gets your point of like, those are the people

1140
00:57:40,600 --> 00:57:44,040
Speaker 1: who really get screwed. But you know, to paint this

1141
00:57:44,120 --> 00:57:46,280
Speaker 1: as like, oh, it's just for the educated class, I

1142
00:57:46,280 --> 00:57:48,680
Speaker 1: don't think that's fair because you have so many young

1143
00:57:48,720 --> 00:57:51,520
Speaker 1: people now who do go to college because they've been

1144
00:57:51,520 --> 00:57:53,200
Speaker 1: sold this is the only way you can even have

1145
00:57:53,240 --> 00:57:56,680
Speaker 1: a chance at succeeding in American society. So listen to

1146
00:57:56,760 --> 00:57:59,560
Speaker 1: your point. What we're likely looking at here is going

1147
00:57:59,600 --> 00:58:03,520
Speaker 1: to be probably very limited if it happens ultimately at all,

1148
00:58:04,160 --> 00:58:06,040
Speaker 1: and I think that will limit some of the Republican

1149
00:58:06,080 --> 00:58:08,200
Speaker 1: attacks on it as well, because if it is constrained

1150
00:58:08,200 --> 00:58:10,120
Speaker 1: by income, that makes it much harder to paint it

1151
00:58:10,160 --> 00:58:13,360
Speaker 1: is just like a wealthy class bailout. But you know,

1152
00:58:13,440 --> 00:58:16,400
Speaker 1: I think it would be at least some help to

1153
00:58:16,920 --> 00:58:19,680
Speaker 1: a lot of people in generations that have been pretty

1154
00:58:19,720 --> 00:58:25,720
Speaker 1: much scared. We'll see how it works out. Let's talk

1155
00:58:25,720 --> 00:58:28,120
Speaker 1: about Bernie Sanders here doing putting a little bit of

1156
00:58:28,120 --> 00:58:29,800
Speaker 1: pressure on Joe Biden. We'll see how far they go

1157
00:58:29,880 --> 00:58:32,240
Speaker 1: with this. So one thing we've been talking about here

1158
00:58:32,960 --> 00:58:35,960
Speaker 1: is the fact that all right, Amazon labor union won

1159
00:58:36,280 --> 00:58:41,480
Speaker 1: historic victory against Amazon against all odds, absolutely incredible. Now

1160
00:58:41,640 --> 00:58:44,880
Speaker 1: they have to get a contract negotiated, and that is

1161
00:58:45,040 --> 00:58:48,000
Speaker 1: no small feat because these companies, the way the laws

1162
00:58:48,040 --> 00:58:50,160
Speaker 1: written now, they can drive their feet. They can. We

1163
00:58:50,240 --> 00:58:53,520
Speaker 1: already know Amazon is even challenging the legality of this election.

1164
00:58:54,080 --> 00:58:56,479
Speaker 1: Then if that, you know, once that goes down, which

1165
00:58:56,480 --> 00:58:58,480
Speaker 1: it is likely to, not certain to, but when it's

1166
00:58:58,560 --> 00:59:01,320
Speaker 1: likely to, then they can drag their feet on negotiats,

1167
00:59:01,360 --> 00:59:04,120
Speaker 1: pretend they're negotiating in good faith, that's the language and

1168
00:59:04,160 --> 00:59:07,160
Speaker 1: the law, and never ultimately come to a contract. And

1169
00:59:07,160 --> 00:59:09,880
Speaker 1: there's basically nothing to stop them from doing that except

1170
00:59:09,920 --> 00:59:14,240
Speaker 1: for the militancy of the workers themselves. However, Joe Biden,

1171
00:59:15,280 --> 00:59:17,080
Speaker 1: on the campaign trail, when he promised to be the

1172
00:59:17,080 --> 00:59:20,320
Speaker 1: most pro union president in history, said, hey, we're not

1173
00:59:20,360 --> 00:59:23,280
Speaker 1: going to give federal government contracts anymore to companies that

1174
00:59:23,440 --> 00:59:27,360
Speaker 1: union bust. Well, okay, you have Amazon now accused by

1175
00:59:27,360 --> 00:59:31,840
Speaker 1: the NLRB of illegally union busting, including firing workers like

1176
00:59:31,920 --> 00:59:37,560
Speaker 1: Christian Smalls in retaliation for organizing, and they're up for

1177
00:59:37,600 --> 00:59:41,800
Speaker 1: a ten billion dollar cloud contract cloud computing contract with

1178
00:59:41,920 --> 00:59:45,000
Speaker 1: the NSA so Bernie, let's put this element on on

1179
00:59:45,040 --> 00:59:48,240
Speaker 1: the screen, has just sent a letter to Joe Biden

1180
00:59:48,560 --> 00:59:51,200
Speaker 1: urging him to bar companies that violate labor laws from

1181
00:59:51,200 --> 00:59:54,760
Speaker 1: eligibility for any federal contract, specifically calling out Amazon for

1182
00:59:54,800 --> 00:59:57,479
Speaker 1: illegal anti union activity and noting it is in line

1183
00:59:57,520 --> 01:00:01,360
Speaker 1: to receive that ten billion dollar NSA Cloud contract. So

1184
01:00:01,440 --> 01:00:04,120
Speaker 1: Bernie writes this letter just basically saying, hey, listen, I

1185
01:00:04,120 --> 01:00:06,600
Speaker 1: loved it when you said this. That was great. Now

1186
01:00:06,600 --> 01:00:08,840
Speaker 1: it's time to actually do it. And I want to

1187
01:00:08,880 --> 01:00:11,560
Speaker 1: give credit to our friends and partners over at Lever

1188
01:00:11,680 --> 01:00:13,760
Speaker 1: News because they have been on top of this from

1189
01:00:13,760 --> 01:00:15,680
Speaker 1: the beginning. I think this is part of why independent

1190
01:00:15,720 --> 01:00:20,240
Speaker 1: news is so incredibly important. The Bezos Washington Post unlikely

1191
01:00:20,280 --> 01:00:23,880
Speaker 1: to cover this story with quite of quite the tenacity

1192
01:00:23,920 --> 01:00:25,720
Speaker 1: that our friends iver at Lever News will put this

1193
01:00:25,760 --> 01:00:28,720
Speaker 1: tweet up on the screen. They exposed that Biden was

1194
01:00:28,760 --> 01:00:31,960
Speaker 1: giving that ten million dollar contract after pledging to ensure

1195
01:00:32,000 --> 01:00:35,400
Speaker 1: federal contracts only go to employers who sign neutrality agreements

1196
01:00:35,400 --> 01:00:39,200
Speaker 1: and commit not to run anti union campaigns. However, not

1197
01:00:39,320 --> 01:00:42,560
Speaker 1: mentioned very much in corporate media. So Lever News really

1198
01:00:42,600 --> 01:00:44,800
Speaker 1: provides the sort of cudgel here that Bernie then was

1199
01:00:44,840 --> 01:00:49,240
Speaker 1: able to use in writing this letter. So listen, next

1200
01:00:49,360 --> 01:00:52,040
Speaker 1: question is what are you going to do to apply pressure?

1201
01:00:52,960 --> 01:00:55,480
Speaker 1: So I really, you know, it was great seeing Bernie

1202
01:00:55,520 --> 01:00:58,240
Speaker 1: and AOC there rallying with the workers. There was some

1203
01:00:58,280 --> 01:01:02,160
Speaker 1: beautiful footage that came out recently, Bernie talking to Starbucks

1204
01:01:02,240 --> 01:01:06,800
Speaker 1: workers behind the scene. Heartbreaking story of a young worker

1205
01:01:06,840 --> 01:01:10,200
Speaker 1: there who had cancer and was working, had to work

1206
01:01:10,240 --> 01:01:12,640
Speaker 1: full time to afford their healthcare, and was going through

1207
01:01:12,720 --> 01:01:16,120
Speaker 1: chemo therapy. I mean, it's just horrendous what these workers

1208
01:01:16,160 --> 01:01:18,640
Speaker 1: are ultimately put through. So I've been really you know,

1209
01:01:18,680 --> 01:01:20,720
Speaker 1: it's been great to see burning out there stating in

1210
01:01:20,760 --> 01:01:23,120
Speaker 1: solidarity with these workers. But now it's like, okay, you

1211
01:01:23,360 --> 01:01:25,200
Speaker 1: and the squad and the rest, how are you going

1212
01:01:25,240 --> 01:01:28,280
Speaker 1: to apply pressure and continue to call out Biden to

1213
01:01:28,480 --> 01:01:31,160
Speaker 1: actually make it possible that this happens, Because this is

1214
01:01:31,240 --> 01:01:34,920
Speaker 1: how the government, even with the laws as they're written now,

1215
01:01:35,240 --> 01:01:37,960
Speaker 1: could help to back up the workers and help provide

1216
01:01:37,960 --> 01:01:40,960
Speaker 1: them with leverage to actually get these contracts done. Yeah,

1217
01:01:41,000 --> 01:01:42,800
Speaker 1: and look, this is a real story. I mean, people

1218
01:01:42,840 --> 01:01:45,840
Speaker 1: forget the Jedi contract. The ten billion dollar cloud computing

1219
01:01:45,840 --> 01:01:48,600
Speaker 1: contract has been hard fought between Amazon and Microsoft for

1220
01:01:48,640 --> 01:01:52,760
Speaker 1: the last like five years. Basically, Amazon sued the Pentagon

1221
01:01:52,840 --> 01:01:56,920
Speaker 1: and started this whole process, alleging political interference by Trump

1222
01:01:57,200 --> 01:01:59,600
Speaker 1: by saying that they were retaliated against because he doesn't

1223
01:01:59,640 --> 01:02:02,240
Speaker 1: like Base. Maybe true, but honestly I don't particularly care

1224
01:02:02,280 --> 01:02:04,120
Speaker 1: because I don't think they deserve the ten billion dollar

1225
01:02:04,120 --> 01:02:06,640
Speaker 1: contract for a variety of reasons, like you're saying. But

1226
01:02:07,000 --> 01:02:09,160
Speaker 1: what ended up happening is that legal warfare happened over

1227
01:02:09,240 --> 01:02:12,600
Speaker 1: three years, and the Biden administration specifically are the people

1228
01:02:12,640 --> 01:02:16,240
Speaker 1: who gave Amazon the contract in August of twenty twenty

1229
01:02:16,280 --> 01:02:19,920
Speaker 1: twenty one. This is a ten billion dollar cloud computing

1230
01:02:19,960 --> 01:02:23,840
Speaker 1: contract for the National Security Agency and the NSA. Now

1231
01:02:23,880 --> 01:02:26,560
Speaker 1: Microsoft has now been screwed out of the deal. Amazon

1232
01:02:26,640 --> 01:02:28,840
Speaker 1: is getting the ten billion and as you say, the

1233
01:02:28,840 --> 01:02:32,240
Speaker 1: Biden administration, having awarded the contract, is full within their

1234
01:02:32,320 --> 01:02:35,360
Speaker 1: rights in order to enforce administration policy. We don't do

1235
01:02:35,440 --> 01:02:38,400
Speaker 1: business as a government with people who do this type

1236
01:02:38,400 --> 01:02:40,919
Speaker 1: of stuff. So look, it really is on Biden right now.

1237
01:02:41,320 --> 01:02:43,120
Speaker 1: My money is he's not going to do anything about it.

1238
01:02:43,160 --> 01:02:46,560
Speaker 1: But right, but that's why, Like now, the question is

1239
01:02:46,600 --> 01:02:48,960
Speaker 1: how do we apply pressure, How do we make enough

1240
01:02:49,000 --> 01:02:52,040
Speaker 1: public outrage and enough for talking about it here. Yeah, Yeah,

1241
01:02:52,160 --> 01:02:54,720
Speaker 1: enough damage done to the Biden administration where they have

1242
01:02:54,760 --> 01:02:58,520
Speaker 1: to actually consider doing something about it. So the other

1243
01:02:58,560 --> 01:03:01,200
Speaker 1: thing that I will say here it's important to remember

1244
01:03:01,560 --> 01:03:06,200
Speaker 1: is you know, oftentimes Biden and all these other politicians

1245
01:03:06,240 --> 01:03:08,080
Speaker 1: they want to pretend like, oh, we have no power,

1246
01:03:08,240 --> 01:03:10,760
Speaker 1: we can't really do anything. The best I can do

1247
01:03:11,040 --> 01:03:14,320
Speaker 1: is like sort of, you know, signal support for the

1248
01:03:14,360 --> 01:03:18,240
Speaker 1: Amazon labor union before my Press secretary quickly walks it

1249
01:03:18,280 --> 01:03:21,360
Speaker 1: back and it's like, oh, we're totally neutral. That's just

1250
01:03:21,400 --> 01:03:24,960
Speaker 1: a lie. First of all, you know, it is actually

1251
01:03:24,960 --> 01:03:30,080
Speaker 1: the responsibility of the government to encourage collective bargaining. Is

1252
01:03:30,240 --> 01:03:31,960
Speaker 1: that is in the law. That is the status of

1253
01:03:31,960 --> 01:03:34,920
Speaker 1: the law. And you can see that they do, in

1254
01:03:34,960 --> 01:03:37,440
Speaker 1: fact if they want to have a lot of tools

1255
01:03:37,440 --> 01:03:41,080
Speaker 1: at their disposal to make like life difficult for companies

1256
01:03:41,120 --> 01:03:44,720
Speaker 1: that want to engage in illegal union busting. And that's

1257
01:03:44,720 --> 01:03:46,560
Speaker 1: not just at the federal government level. We're actually going

1258
01:03:46,600 --> 01:03:48,120
Speaker 1: to talk to our friends at lever News for a

1259
01:03:48,120 --> 01:03:51,800
Speaker 1: segment that I'll post on Friday about the state subsidies

1260
01:03:52,000 --> 01:03:56,120
Speaker 1: that Amazon gets with also written into this provision, let's

1261
01:03:56,120 --> 01:03:59,960
Speaker 1: say you're not going to union fust so enforce the contract,

1262
01:04:00,280 --> 01:04:03,680
Speaker 1: enforce the law against these large companies the way that

1263
01:04:03,760 --> 01:04:06,280
Speaker 1: you know, though certainly the book gets thrown at individual

1264
01:04:06,360 --> 01:04:09,320
Speaker 1: regular people when they transgress, and so I think it

1265
01:04:09,440 --> 01:04:12,800
Speaker 1: just exposes also the lie that these actors are powerless

1266
01:04:12,840 --> 01:04:15,520
Speaker 1: and can't help to try to bring these companies to

1267
01:04:15,600 --> 01:04:18,720
Speaker 1: heal and backstop the workers in their efforts both to

1268
01:04:18,800 --> 01:04:21,640
Speaker 1: unionize and to gain win contracts. I think that's well said. Okay,

1269
01:04:21,720 --> 01:04:24,320
Speaker 1: let's go ahead and move on. This is a hilarious story. Also, apologies,

1270
01:04:24,400 --> 01:04:27,040
Speaker 1: looks like we spell that wrong. It's our Chagos, not Ajago's.

1271
01:04:27,120 --> 01:04:29,680
Speaker 1: But it's okay, as it's up there on the screen.

1272
01:04:29,960 --> 01:04:34,520
Speaker 1: Our Chagos founder Bill Wang, the former CFO charged with

1273
01:04:34,800 --> 01:04:39,000
Speaker 1: securities fraud. Guys, this story is completely insane. So if

1274
01:04:39,000 --> 01:04:41,600
Speaker 1: you don't know Bill Wang is he was worth roughly

1275
01:04:41,680 --> 01:04:45,160
Speaker 1: twenty billion dollars as of a year ago. But now

1276
01:04:45,280 --> 01:04:48,680
Speaker 1: him and the former CFO of his company, Our Chego's Capital,

1277
01:04:48,960 --> 01:04:53,200
Speaker 1: have been indicted on securities fraud and racketeering in what

1278
01:04:53,240 --> 01:04:55,480
Speaker 1: they say is one of the most massive fraud and

1279
01:04:55,600 --> 01:04:59,520
Speaker 1: manipulation schemes in the history of Wall Street that nearly

1280
01:04:59,640 --> 01:05:04,600
Speaker 1: Jeppard guys, the entire US financial system. And this is

1281
01:05:04,720 --> 01:05:08,440
Speaker 1: nuts because what it exposes are all kinds of queered

1282
01:05:08,560 --> 01:05:14,040
Speaker 1: regulatory loopholes through which family offices are governed loose regulation

1283
01:05:14,160 --> 01:05:17,360
Speaker 1: based upon that, and the way that the banks themselves

1284
01:05:17,680 --> 01:05:21,600
Speaker 1: just simply believe the words of companies. So to be clear, here,

1285
01:05:22,320 --> 01:05:25,720
Speaker 1: the word of Bill Wang and his company Archegos was

1286
01:05:25,800 --> 01:05:29,920
Speaker 1: good enough for the top banks on all of Wall Street.

1287
01:05:30,280 --> 01:05:33,480
Speaker 1: They show that under the family office founder that the

1288
01:05:33,520 --> 01:05:36,400
Speaker 1: blind spot makes it so they will simply take your

1289
01:05:36,480 --> 01:05:40,440
Speaker 1: word as a company to loan you hundreds of millions

1290
01:05:40,480 --> 01:05:43,480
Speaker 1: and billions of dollars, which you can then use that

1291
01:05:43,640 --> 01:05:47,200
Speaker 1: money in order to place immense bets on other people's

1292
01:05:47,280 --> 01:05:51,240
Speaker 1: stock and then wildly swing the US financial system. So

1293
01:05:51,320 --> 01:05:53,240
Speaker 1: here's what they say. This is from the US Attorney

1294
01:05:53,600 --> 01:05:57,360
Speaker 1: lies fed inflation, inflation fed more lies. Last year, the

1295
01:05:57,440 --> 01:06:00,480
Speaker 1: music stopped, the bubble burst, the prices dropped, and when

1296
01:06:00,520 --> 01:06:05,280
Speaker 1: they did, billions of dollars evaporated overnight. So what they're

1297
01:06:05,360 --> 01:06:09,400
Speaker 1: charged worth is securities fraud that manipulating hundreds of billions

1298
01:06:09,440 --> 01:06:12,480
Speaker 1: of dollars in stock. So what they point to is

1299
01:06:12,520 --> 01:06:16,120
Speaker 1: that they have trades as counterparties are allowing large purchases

1300
01:06:16,120 --> 01:06:18,959
Speaker 1: then increase people's stock price. They increase in stock price,

1301
01:06:18,960 --> 01:06:21,760
Speaker 1: which he uses or the purchases he uses with using

1302
01:06:21,760 --> 01:06:25,040
Speaker 1: his fake word are then used to inflight securities, which

1303
01:06:25,080 --> 01:06:28,320
Speaker 1: then through complicated securities fraud, you were able to reap

1304
01:06:28,360 --> 01:06:30,960
Speaker 1: profits off of that. But it requires everything to keep

1305
01:06:30,960 --> 01:06:33,960
Speaker 1: going on going up, so when the music stops, the

1306
01:06:34,000 --> 01:06:37,120
Speaker 1: bottom falls out. Crystal. They went from one point five

1307
01:06:37,200 --> 01:06:40,720
Speaker 1: billion to allegedly thirty five billion under management in a

1308
01:06:40,840 --> 01:06:43,680
Speaker 1: single years, which is totally nuts. Yeah, I mean, the

1309
01:06:43,720 --> 01:06:46,240
Speaker 1: way this is a little bit complicated, The way I

1310
01:06:46,320 --> 01:06:48,919
Speaker 1: understood it is basically like a high class pyramids. Yeah,

1311
01:06:48,920 --> 01:06:50,680
Speaker 1: that's it, because that's exactly what I did. I mean,

1312
01:06:50,720 --> 01:06:53,440
Speaker 1: they keep you know, as long as you keep going

1313
01:06:53,520 --> 01:06:55,919
Speaker 1: up and up and up, you don't have to ever

1314
01:06:56,000 --> 01:06:58,480
Speaker 1: pay the piper. But the minute that there was a

1315
01:06:58,520 --> 01:07:02,600
Speaker 1: faltering than ever everything the whole house of cards completely collapsed.

1316
01:07:02,800 --> 01:07:04,800
Speaker 1: The way the New York Times described it, as they say,

1317
01:07:04,840 --> 01:07:07,480
Speaker 1: prosecutor say, Bill Huang, the her firm's owner and his

1318
01:07:07,600 --> 01:07:11,680
Speaker 1: former's chief financial officer, had deliberately misled their banks. So

1319
01:07:11,720 --> 01:07:13,760
Speaker 1: they lied to the banks to borrow money and then

1320
01:07:13,760 --> 01:07:16,760
Speaker 1: place these enormous bets on a handful of stocks through

1321
01:07:16,760 --> 01:07:21,280
Speaker 1: sophisticated securities. Those trades were obfiscated, so it was not transparent.

1322
01:07:21,360 --> 01:07:23,320
Speaker 1: That was part of the problem by the loose regulations

1323
01:07:23,360 --> 01:07:27,440
Speaker 1: governing so called family offices like Arceagos, where wealthy individuals

1324
01:07:27,520 --> 01:07:30,680
Speaker 1: manage their investments, when that strategy collapsed, so when the

1325
01:07:30,680 --> 01:07:33,240
Speaker 1: price went down on one of these stocks significantly, the

1326
01:07:33,280 --> 01:07:36,960
Speaker 1: whole thing collapses. In just a few days, one hundred

1327
01:07:37,040 --> 01:07:40,840
Speaker 1: billion dollars in shareholder value vanished, hitting the portfolios of

1328
01:07:40,840 --> 01:07:43,640
Speaker 1: investors who had invested when the unseen hand of Archagos

1329
01:07:44,000 --> 01:07:46,920
Speaker 1: was actually what was pushing those stocks to new heights.

1330
01:07:47,120 --> 01:07:52,120
Speaker 1: So their use of these highly leveraged, sophisticated financial instruments

1331
01:07:52,320 --> 01:07:55,320
Speaker 1: was what was actually driving the price spikes. So they

1332
01:07:55,320 --> 01:07:58,160
Speaker 1: had effectively rigged the market. And because you had no

1333
01:07:58,200 --> 01:08:02,000
Speaker 1: transparency around it, the banks and financial nobody knew that

1334
01:08:02,080 --> 01:08:04,320
Speaker 1: it was really them that were causing the inflation of

1335
01:08:04,360 --> 01:08:06,439
Speaker 1: these stocks, and so then when one of them fell,

1336
01:08:06,480 --> 01:08:08,840
Speaker 1: they were so highly leveraged that then there were margin

1337
01:08:08,920 --> 01:08:11,400
Speaker 1: calls and the whole thing ultimately collected. What else is fascinating,

1338
01:08:11,440 --> 01:08:13,560
Speaker 1: like I was referring to the family offices, which is

1339
01:08:13,600 --> 01:08:17,120
Speaker 1: that in recent years there are not any regulations over

1340
01:08:17,200 --> 01:08:20,160
Speaker 1: family offices in the same way for public disclosure as

1341
01:08:20,160 --> 01:08:23,000
Speaker 1: for hedge funds. So our Chagos was just one of

1342
01:08:23,080 --> 01:08:26,360
Speaker 1: several hedge funds which is converted to a family office

1343
01:08:26,400 --> 01:08:29,960
Speaker 1: in recent years because they are not under the same

1344
01:08:30,040 --> 01:08:34,559
Speaker 1: number of amount of regulations by the SEC. And thus

1345
01:08:34,800 --> 01:08:38,200
Speaker 1: what's been happening is that these family office hedge funds

1346
01:08:38,320 --> 01:08:40,640
Speaker 1: are able to just simply tell the banks take our

1347
01:08:40,680 --> 01:08:42,640
Speaker 1: word for it. And what I love about this is

1348
01:08:42,720 --> 01:08:45,439
Speaker 1: it just exposes how bs it all is. Think about it, right,

1349
01:08:45,960 --> 01:08:48,040
Speaker 1: and Carlan, how many people out there had to go

1350
01:08:48,040 --> 01:08:51,880
Speaker 1: get a car loan paperwork, Oh my god, mortgage, any

1351
01:08:52,680 --> 01:08:55,720
Speaker 1: credit application you have to go through and talk to

1352
01:08:55,760 --> 01:08:58,600
Speaker 1: your landlord from like nine years ago in order to

1353
01:08:58,600 --> 01:09:00,680
Speaker 1: get all this time when you're trying to borrow like

1354
01:09:00,760 --> 01:09:05,400
Speaker 1: half a million dollars, these guys are getting spotted billions

1355
01:09:05,680 --> 01:09:10,120
Speaker 1: based upon their word. No due diligence done by the bank,

1356
01:09:10,240 --> 01:09:12,840
Speaker 1: which is illegal. Actually you're not supposed to just loan

1357
01:09:12,880 --> 01:09:15,160
Speaker 1: people money. But they're like, ah, yeah, he's good for it.

1358
01:09:15,360 --> 01:09:18,080
Speaker 1: Why are in behalf of huh and five billion? Ten billion?

1359
01:09:18,200 --> 01:09:20,559
Speaker 1: This dude had been in trouble for doing something very

1360
01:09:20,600 --> 01:09:23,760
Speaker 1: similarly four and had been like disbarred, and he kind

1361
01:09:23,760 --> 01:09:26,080
Speaker 1: of fell off the radar for a while, and then

1362
01:09:26,120 --> 01:09:29,680
Speaker 1: he makes this big comeback basically like with a revamped

1363
01:09:29,960 --> 01:09:34,320
Speaker 1: scheme of his previous frauds. So pretty interesting, and I

1364
01:09:34,360 --> 01:09:37,880
Speaker 1: think you're right. It really does expose how fake and

1365
01:09:38,000 --> 01:09:42,080
Speaker 1: rigged and non transparent so much of this is. I mean,

1366
01:09:42,640 --> 01:09:45,799
Speaker 1: there is no way that this individual is the only

1367
01:09:45,880 --> 01:09:48,639
Speaker 1: one who's engaging these type of shenanigans. Not a chance,

1368
01:09:48,920 --> 01:09:51,479
Speaker 1: not a chance. Interesting trunk fang. He does these great

1369
01:09:51,800 --> 01:09:53,679
Speaker 1: threads on Twitter. Let's put this up there. I highly

1370
01:09:53,680 --> 01:09:55,920
Speaker 1: recommend everybody go and check his thread out. But he

1371
01:09:56,040 --> 01:09:58,280
Speaker 1: says in the thread that due to the nature of

1372
01:09:58,320 --> 01:10:01,440
Speaker 1: the swaps that our chegos had built up, their portfolio,

1373
01:10:01,520 --> 01:10:03,320
Speaker 1: like I mentioned, went from one point five to thirty

1374
01:10:03,360 --> 01:10:05,679
Speaker 1: five billion, but with the nature of the swaps crystal

1375
01:10:05,920 --> 01:10:11,360
Speaker 1: they were, total exposure was one hundred billion dollars And

1376
01:10:11,560 --> 01:10:15,320
Speaker 1: just simply the decline of Viacom stock alone is what

1377
01:10:15,439 --> 01:10:18,519
Speaker 1: led to this entire thing going down, because they were

1378
01:10:18,600 --> 01:10:22,080
Speaker 1: leveraged at five times, so just a fifteen to twenty

1379
01:10:22,080 --> 01:10:25,320
Speaker 1: percent sell off is enough to wipe out an entire

1380
01:10:25,479 --> 01:10:28,720
Speaker 1: element of the portfolio. And then what happens is that

1381
01:10:28,720 --> 01:10:32,160
Speaker 1: when the banks start selling all their large blocks of

1382
01:10:32,320 --> 01:10:35,439
Speaker 1: Archegos linked companies and a thirty percent decline on a

1383
01:10:35,479 --> 01:10:39,440
Speaker 1: single day boom, you just see how it all completely

1384
01:10:39,680 --> 01:10:42,479
Speaker 1: falls apart. So look, guys, all it really is is

1385
01:10:42,479 --> 01:10:44,720
Speaker 1: a perfect view, and it's hard. It's enough to try

1386
01:10:44,720 --> 01:10:47,519
Speaker 1: and explain swaps, and the way this all works is

1387
01:10:47,840 --> 01:10:51,080
Speaker 1: at a very basic level, you can manipulate stock and

1388
01:10:51,120 --> 01:10:53,200
Speaker 1: then tell the banks that you're not doing it, and

1389
01:10:53,240 --> 01:10:55,320
Speaker 1: then they'll still wire you money as long as you're

1390
01:10:55,320 --> 01:10:58,200
Speaker 1: worth over a billion dollars while normal people, I mean,

1391
01:10:58,320 --> 01:10:59,519
Speaker 1: think about how hard it is to get a freaking

1392
01:10:59,520 --> 01:11:01,400
Speaker 1: credit card for half the people in this country right now.

1393
01:11:01,479 --> 01:11:05,400
Speaker 1: So really it's just completely ridiculous. Yeah, absolutely, Okay, speaking

1394
01:11:05,520 --> 01:11:08,800
Speaker 1: completely ridiculous, Let's talk about Madison Cawthorne. I have to say,

1395
01:11:08,920 --> 01:11:11,920
Speaker 1: we have not covered a lot of these stories, right

1396
01:11:12,520 --> 01:11:17,160
Speaker 1: because ultimately he's one member, extremely cringe member of Congress.

1397
01:11:17,360 --> 01:11:21,599
Speaker 1: But now he's implicated potentially in a sort of insider

1398
01:11:21,640 --> 01:11:25,160
Speaker 1: trading scheme, and so there have been a whole litany

1399
01:11:25,280 --> 01:11:28,080
Speaker 1: of things that have been going on with mister Cawthorn.

1400
01:11:28,160 --> 01:11:31,320
Speaker 1: So let's just go through the list here. First of all,

1401
01:11:31,800 --> 01:11:33,760
Speaker 1: you know, he had that whole thing which we did cover,

1402
01:11:33,840 --> 01:11:37,120
Speaker 1: where he like you know, said, oh, you wouldn't believe

1403
01:11:37,240 --> 01:11:41,200
Speaker 1: the orgies the cocaine youth said that I've been invited

1404
01:11:41,240 --> 01:11:44,040
Speaker 1: to And he's one of these whose position himself is

1405
01:11:44,080 --> 01:11:47,479
Speaker 1: like super Christian and super we gotta you know, the

1406
01:11:47,520 --> 01:11:49,960
Speaker 1: real men have to come back, and this is sexual.

1407
01:11:50,000 --> 01:11:52,760
Speaker 1: Devians is terrible. That's the type of like way that

1408
01:11:52,800 --> 01:11:55,639
Speaker 1: he's framed in the position himself. So somebody who clearly

1409
01:11:55,640 --> 01:11:58,679
Speaker 1: hates him released these photographs of him. Let's go ahead

1410
01:11:58,680 --> 01:12:01,320
Speaker 1: and put this up on the screen to Politico. That

1411
01:12:01,479 --> 01:12:05,759
Speaker 1: shows him cross dressing see some women's lingerie here, clearly

1412
01:12:05,840 --> 01:12:09,160
Speaker 1: some sort of public party scene. And I am the

1413
01:12:09,240 --> 01:12:12,639
Speaker 1: last person in the world to criticize someone for taking

1414
01:12:12,840 --> 01:12:17,280
Speaker 1: you know, embarrassing or riskue photos. However, I also didn't

1415
01:12:17,280 --> 01:12:21,000
Speaker 1: position myself as some sort of like Christian fundamentalist, you know,

1416
01:12:21,960 --> 01:12:25,160
Speaker 1: puritan type of individual. And he has so I think,

1417
01:12:25,240 --> 01:12:28,880
Speaker 1: you know, listen, currently taking on a cruise ship whatever color.

1418
01:12:29,000 --> 01:12:30,880
Speaker 1: He can do whatever the helling wants in his personal life.

1419
01:12:30,880 --> 01:12:33,280
Speaker 1: I really don't care, but don't be a hypocrite about it. Okay,

1420
01:12:33,320 --> 01:12:36,720
Speaker 1: so that's number one. Next up, he has for the

1421
01:12:36,840 --> 01:12:41,960
Speaker 1: second time now been found and detained ultimately for having

1422
01:12:42,000 --> 01:12:44,720
Speaker 1: a gun, trying to bring a gun onto an airplane.

1423
01:12:45,040 --> 01:12:47,679
Speaker 1: Just put this up on the screen, all right. Officials

1424
01:12:47,720 --> 01:12:50,639
Speaker 1: say a loaded gun loaded has been found in North

1425
01:12:50,640 --> 01:12:53,600
Speaker 1: Carolina US Representative Madison Cawthorne's carry on bag at an

1426
01:12:53,640 --> 01:12:56,760
Speaker 1: airport security checkpoint. It's the second time that he'd been

1427
01:12:56,800 --> 01:12:59,040
Speaker 1: stopped with a gun at an airport in the past

1428
01:12:59,200 --> 01:13:04,640
Speaker 1: fourteen months, subject to a fine. I guess apparently he was.

1429
01:13:04,640 --> 01:13:07,040
Speaker 1: He says he forgot it in his back, but twice,

1430
01:13:07,280 --> 01:13:10,439
Speaker 1: I mean call man twice, Like, how does that happen? Right?

1431
01:13:10,560 --> 01:13:12,360
Speaker 1: And I have to think that it would be a

1432
01:13:12,400 --> 01:13:15,720
Speaker 1: pretty extreme disposition the people who are super comfortable with

1433
01:13:16,120 --> 01:13:20,360
Speaker 1: anyone bringing a loaded gun onto an airplane. So weird

1434
01:13:20,760 --> 01:13:23,920
Speaker 1: that happened. He also last month, for the third time

1435
01:13:23,920 --> 01:13:26,479
Speaker 1: in five months, was cited by state troopers for a

1436
01:13:26,479 --> 01:13:29,880
Speaker 1: traffic violation, including driving with a revoked license. So that's

1437
01:13:29,920 --> 01:13:33,479
Speaker 1: another thing that happened. But this is the incident that

1438
01:13:33,520 --> 01:13:35,439
Speaker 1: really caused us to want to cover all of this.

1439
01:13:35,920 --> 01:13:37,920
Speaker 1: Go ahead and put this, I think is Washington Examiner

1440
01:13:38,040 --> 01:13:41,960
Speaker 1: report up on the screen Madison Cawthorn implicated in potential

1441
01:13:42,000 --> 01:13:46,519
Speaker 1: insider trading scheme. Experts say, all right, so here are

1442
01:13:46,640 --> 01:13:50,040
Speaker 1: the details. They say Cawthorn may have violated federal insider

1443
01:13:50,080 --> 01:13:53,280
Speaker 1: trading laws as he hyped up an alleged pump and

1444
01:13:53,439 --> 01:13:58,560
Speaker 1: dump cryptocurrency scheme. Multiple watchhout groups told The Washington Examiner

1445
01:13:58,920 --> 01:14:02,160
Speaker 1: worth noting Washington's amner is a conservative outlet, so this

1446
01:14:02,280 --> 01:14:05,280
Speaker 1: is not some like liberal elite media hit job here.

1447
01:14:05,320 --> 01:14:07,160
Speaker 1: Oh yeah, and the reporter is actually a guy I

1448
01:14:07,240 --> 01:14:09,360
Speaker 1: know a long time, Andrew Kurr. He's a good dude.

1449
01:14:09,439 --> 01:14:12,439
Speaker 1: Solid I mean, this is obviously a very solidly reported piece,

1450
01:14:12,800 --> 01:14:16,599
Speaker 1: they say. On December twenty ninth, Cawthorne posed a party

1451
01:14:17,040 --> 01:14:20,759
Speaker 1: with a hedge fund manager and ringleader of the Let's

1452
01:14:20,800 --> 01:14:24,080
Speaker 1: Go Brandon cryptocurrency, a meme coin set up in the

1453
01:14:24,080 --> 01:14:27,639
Speaker 1: wake of the chant Moncking president Joe Biden. Cawthorne posted

1454
01:14:27,920 --> 01:14:32,120
Speaker 1: LGB legends Tomorrow we go to the Moon. The next day.

1455
01:14:32,680 --> 01:14:37,000
Speaker 1: That coin ended up performing extraordinarily well. Why because NASCAR

1456
01:14:37,120 --> 01:14:40,880
Speaker 1: driver Brandon Brown announced that the meme coin would be

1457
01:14:40,920 --> 01:14:44,959
Speaker 1: his primary sponsor of his twenty twenty two season, causing

1458
01:14:45,040 --> 01:14:49,160
Speaker 1: that coin's value to spike by seventy five percent. Multiple

1459
01:14:49,200 --> 01:14:52,679
Speaker 1: watch shot groups told the Examiner that his Instagram posts

1460
01:14:52,720 --> 01:14:56,599
Speaker 1: suggests he may have had advanced, non public knowledge of

1461
01:14:56,760 --> 01:15:00,760
Speaker 1: that deal with NASCAR driver Brandon Brown. Chucks at the post,

1462
01:15:00,800 --> 01:15:04,920
Speaker 1: combined with Cawthorn's statement that he owns some of lgb coin,

1463
01:15:05,320 --> 01:15:08,800
Speaker 1: warrants an investigation from the DOJ and the Securities in

1464
01:15:08,840 --> 01:15:12,559
Speaker 1: Exchange Commission to determine whether the lawmaker violated federal insider

1465
01:15:12,600 --> 01:15:17,080
Speaker 1: trading lawns. So this cryptocurrency price goes through the roof

1466
01:15:17,600 --> 01:15:22,720
Speaker 1: after this deal is ultimately announced. However, then NASCAR ultimately

1467
01:15:22,760 --> 01:15:27,959
Speaker 1: rejected the sponsorship deal. Unidentified insiders that owned an outside

1468
01:15:27,960 --> 01:15:30,519
Speaker 1: share of the coin dumped all their holdings at once.

1469
01:15:31,360 --> 01:15:35,280
Speaker 1: The coin completely collapses, and so it goes from being

1470
01:15:35,439 --> 01:15:40,679
Speaker 1: worth five hundred and seventy million to being worth nothing. Wow.

1471
01:15:41,040 --> 01:15:43,599
Speaker 1: And so Cawthorne is caught up in all of this

1472
01:15:43,800 --> 01:15:47,080
Speaker 1: because before this deal is announced, he's posting, Hey, you know,

1473
01:15:47,320 --> 01:15:49,479
Speaker 1: I love this coin, I've got this I own some

1474
01:15:49,560 --> 01:15:51,680
Speaker 1: of this coin. It's going to the route through what

1475
01:15:51,720 --> 01:15:53,640
Speaker 1: do you say, going to the moon. And then the

1476
01:15:53,760 --> 01:15:56,680
Speaker 1: very next day this deal is announced. So at the

1477
01:15:56,760 --> 01:16:01,040
Speaker 1: very least. It looks extremely sketchy, worst a nice wrongdoing

1478
01:16:01,120 --> 01:16:04,479
Speaker 1: or his office or whatever. But it's catching the attention

1479
01:16:04,600 --> 01:16:07,559
Speaker 1: of some of his Republican colleagues. This is his fellow

1480
01:16:07,600 --> 01:16:10,800
Speaker 1: North Carolinian Senator Tom Tillis, who already, it should be said,

1481
01:16:10,840 --> 01:16:14,320
Speaker 1: has endorsed against Cawthorn. Ye he hates in his primary. Yeah,

1482
01:16:14,360 --> 01:16:16,040
Speaker 1: and he says, put the tweet up on the screen.

1483
01:16:16,479 --> 01:16:18,920
Speaker 1: Insider trading by a member of Congress is a serious

1484
01:16:18,920 --> 01:16:21,599
Speaker 1: betrayal of their oath, and Congressman Cawthorne owes to North

1485
01:16:21,640 --> 01:16:24,479
Speaker 1: Carolinians an explanation. There needs to be a thorough and

1486
01:16:24,560 --> 01:16:28,040
Speaker 1: bipartisan inquiry into the matter by the House Ethics Committee.

1487
01:16:28,080 --> 01:16:30,280
Speaker 1: So that is where things stands on. Yeah, I mean, look,

1488
01:16:30,760 --> 01:16:33,040
Speaker 1: it looks bad. You know. This is also why you

1489
01:16:33,040 --> 01:16:35,760
Speaker 1: shouldn't be pumping any coin whatsoever, I mean anything you

1490
01:16:35,960 --> 01:16:39,880
Speaker 1: are a member of Congress of itself. It's gross. Look, yeah, exactly.

1491
01:16:39,960 --> 01:16:41,960
Speaker 1: And by the way, I'm pro bitcoin, but even whenever

1492
01:16:42,000 --> 01:16:45,240
Speaker 1: I see bitcoin congressmen who are like go bitcoin, they

1493
01:16:45,240 --> 01:16:47,240
Speaker 1: owns bitcoin, I think it's an issue. So like I

1494
01:16:47,240 --> 01:16:49,200
Speaker 1: can say it. You know, I'm not a public official.

1495
01:16:49,240 --> 01:16:52,360
Speaker 1: And even then I always disclose. I'm like, just let

1496
01:16:52,360 --> 01:16:54,720
Speaker 1: people know I'm into bitcoin. So this is one of

1497
01:16:54,760 --> 01:16:56,800
Speaker 1: those things where I always think that at the very

1498
01:16:56,840 --> 01:16:59,479
Speaker 1: least public disclosure is needed. But yeah, when you're a

1499
01:16:59,520 --> 01:17:02,799
Speaker 1: public of fan elected official and you're personally netting whoever

1500
01:17:02,840 --> 01:17:05,240
Speaker 1: knows how much money off of this, that's a real issue.

1501
01:17:05,280 --> 01:17:07,240
Speaker 1: I do think there needs to be And he did

1502
01:17:07,720 --> 01:17:10,080
Speaker 1: use his authority, they say, as a lawmaker, to introduce

1503
01:17:10,120 --> 01:17:13,240
Speaker 1: the resolution of the House in February that would deregulate cryptocurrencies.

1504
01:17:13,280 --> 01:17:16,400
Speaker 1: So he has been involved in trying to promulgate legislation

1505
01:17:16,520 --> 01:17:19,000
Speaker 1: that ultimately would personally financially benefit him. And I would

1506
01:17:19,000 --> 01:17:21,280
Speaker 1: probably even support that type of legislation as long as

1507
01:17:21,439 --> 01:17:25,160
Speaker 1: I'm at it. But yet exactly cannot be conflicted whenever

1508
01:17:25,160 --> 01:17:26,880
Speaker 1: you're a member of Congress. So just look, we're going

1509
01:17:26,960 --> 01:17:29,120
Speaker 1: to call this out anytime that we see. I think

1510
01:17:29,160 --> 01:17:31,600
Speaker 1: it is important that it came from the Washington Examiner,

1511
01:17:31,840 --> 01:17:34,200
Speaker 1: and I do think that it does merit an investigation,

1512
01:17:34,320 --> 01:17:36,479
Speaker 1: and just in general, I mean, it just seems like

1513
01:17:36,520 --> 01:17:38,400
Speaker 1: his life is a mess right now. I don't really

1514
01:17:38,439 --> 01:17:40,040
Speaker 1: know what's going I don't know how you forget a

1515
01:17:40,040 --> 01:17:42,840
Speaker 1: gun in your luggage twice. But look, I would just

1516
01:17:43,120 --> 01:17:46,960
Speaker 1: generally say conduct yourself and some better decorum. Congressman, you're

1517
01:17:47,000 --> 01:17:49,360
Speaker 1: already running in a tough re election. Somebody said that

1518
01:17:49,400 --> 01:17:52,280
Speaker 1: he's trying to run for reelection on hard mode. This

1519
01:17:52,360 --> 01:17:55,800
Speaker 1: is a gamer term, those things where I'm like, I

1520
01:17:55,800 --> 01:17:58,599
Speaker 1: don't exactly know why anyone would choose that, But good

1521
01:17:58,680 --> 01:18:04,519
Speaker 1: luck to you, Cristal. What do you taking a look at? Well?

1522
01:18:04,560 --> 01:18:07,040
Speaker 1: Guys over on Fox Business, your Varney is using Elon

1523
01:18:07,160 --> 01:18:10,439
Speaker 1: musk takeover Twitter to fan the undying flame of his

1524
01:18:10,600 --> 01:18:13,600
Speaker 1: romance with the billionaire class. Here we go again. The

1525
01:18:13,680 --> 01:18:17,599
Speaker 1: left hates what they call the billionaire class. Musk's takeover

1526
01:18:17,680 --> 01:18:19,840
Speaker 1: of Twitter. That's really got them going. We need a

1527
01:18:19,840 --> 01:18:22,280
Speaker 1: wealth tax. Since Santra Elizabeth Warren, we must demand the

1528
01:18:22,320 --> 01:18:25,080
Speaker 1: extremely wealthy pay their fast share, says Bernie Sanders, to

1529
01:18:25,120 --> 01:18:28,920
Speaker 1: which Elon Musk cheekily replied, I keep forgetting You're still alive.

1530
01:18:29,520 --> 01:18:32,000
Speaker 1: Socialists never have a sense of humor. The New York

1531
01:18:32,040 --> 01:18:33,880
Speaker 1: Times chimes in today with a study is showing the

1532
01:18:33,920 --> 01:18:36,360
Speaker 1: top eighteen families in America have an average networth of

1533
01:18:36,400 --> 01:18:39,800
Speaker 1: sixty six billion dollars. All the horror, Now, I don't

1534
01:18:39,800 --> 01:18:41,920
Speaker 1: expect billionaires to get much sympathy, and I think they

1535
01:18:41,920 --> 01:18:45,639
Speaker 1: should get some respect. First of all, Musk, Bezos, Zuckerberg Gates.

1536
01:18:45,840 --> 01:18:49,240
Speaker 1: They've created companies that employed millions, and those people enjoy

1537
01:18:49,320 --> 01:18:51,320
Speaker 1: high income and very strong benefits. Isn't that what the

1538
01:18:51,360 --> 01:18:54,120
Speaker 1: left wants? Yes, but the left wants government to provide

1539
01:18:54,120 --> 01:18:56,360
Speaker 1: those goodies, which of course they never do. And look

1540
01:18:56,360 --> 01:18:58,200
Speaker 1: at what the super rich have done with their billions.

1541
01:18:58,520 --> 01:19:02,439
Speaker 1: Musk has developed Tesla, SpaceX, Solar City, the Boring Company,

1542
01:19:02,520 --> 01:19:06,519
Speaker 1: New Ruling, and now Twitter, all dynamic breakthrough companies, thank you.

1543
01:19:06,520 --> 01:19:10,480
Speaker 1: Elon Bezos has developed the world's best online shopping company, Anyws,

1544
01:19:10,479 --> 01:19:15,040
Speaker 1: Cloud Services, Whole Foods, Ring, Twitch, Pillback or dynamic breakthrough companies.

1545
01:19:15,040 --> 01:19:17,720
Speaker 1: That's where the money went, thanks you. My point here

1546
01:19:17,840 --> 01:19:21,200
Speaker 1: is that the accumulation of great wealth has actually enriched America,

1547
01:19:21,400 --> 01:19:24,040
Speaker 1: all of us. But left believes the government should take

1548
01:19:24,120 --> 01:19:27,519
Speaker 1: the billionaire's money and redistribute it. They will deliberately ignore

1549
01:19:27,560 --> 01:19:30,040
Speaker 1: what these entrepreneurs have achieved. They know the government could

1550
01:19:30,040 --> 01:19:32,400
Speaker 1: never invent and run an Amazon or a Tespla, but

1551
01:19:32,400 --> 01:19:34,680
Speaker 1: they don't care about that. All they want is the

1552
01:19:34,720 --> 01:19:38,240
Speaker 1: power to bring them down. I hope they fail. All right,

1553
01:19:38,520 --> 01:19:40,439
Speaker 1: there's a lot to unpack there. So, first of all,

1554
01:19:40,479 --> 01:19:42,559
Speaker 1: he seems to believe that if billionaires were actually taxed

1555
01:19:42,560 --> 01:19:44,360
Speaker 1: at rates like what you and I are tax said,

1556
01:19:44,360 --> 01:19:46,360
Speaker 1: that they would throw a temper tantrum, go home, and

1557
01:19:46,439 --> 01:19:49,960
Speaker 1: stop inventing their wonderful things. In a sense, musk Ashley

1558
01:19:50,000 --> 01:19:52,840
Speaker 1: provides a powerful counter to that, he at least professes

1559
01:19:52,920 --> 01:19:55,439
Speaker 1: to be interested in Twitter for reasons other than adding

1560
01:19:55,439 --> 01:19:58,599
Speaker 1: to his already limitless fortunes. These dudes already have more

1561
01:19:58,640 --> 01:20:02,000
Speaker 1: money than anyone could ever spend an entire lifetime. Would

1562
01:20:02,000 --> 01:20:04,320
Speaker 1: they really just close up shop if we close some

1563
01:20:04,320 --> 01:20:06,720
Speaker 1: loopholes or how to wealth tax or made them pay

1564
01:20:06,720 --> 01:20:09,919
Speaker 1: their workers enough to make rent. Speaking in which Varney's

1565
01:20:09,920 --> 01:20:11,800
Speaker 1: portrait of the left is of course total straw man,

1566
01:20:11,880 --> 01:20:14,120
Speaker 1: he argues, the left wants to close Amazon and like

1567
01:20:14,160 --> 01:20:16,800
Speaker 1: have it run by Anthony Fauci or something. Here's what

1568
01:20:16,840 --> 01:20:20,599
Speaker 1: the godfather of the left, Bernie Sanders, actually wants from Amazon. Now,

1569
01:20:20,640 --> 01:20:24,000
Speaker 1: are you worth one hundred and seventy billion dollars as

1570
01:20:24,080 --> 01:20:27,479
Speaker 1: Bezos is? When you've got a corporation that is making

1571
01:20:27,800 --> 01:20:31,240
Speaker 1: huge profits, you know what you can pay your work

1572
01:20:31,360 --> 01:20:35,280
Speaker 1: is good wages. You can provide good benefits, and you

1573
01:20:35,400 --> 01:20:41,439
Speaker 1: can have decent working conditions. It is so recognizing a

1574
01:20:41,520 --> 01:20:45,200
Speaker 1: lawful union, negotiating a contract treating people like human beings

1575
01:20:45,320 --> 01:20:47,840
Speaker 1: doesn't seem like such a crazy thing to me, and,

1576
01:20:48,000 --> 01:20:52,040
Speaker 1: judging by the overwhelming bipartisan support for the Amazon labor Union,

1577
01:20:52,360 --> 01:20:54,479
Speaker 1: is not crazy of the American people either. What is

1578
01:20:54,520 --> 01:20:58,120
Speaker 1: actually extreme is Varney's fawning appraisal of our elite ruling

1579
01:20:58,120 --> 01:21:00,840
Speaker 1: class and desire to do nothing but their taxes and

1580
01:21:00,960 --> 01:21:04,960
Speaker 1: worshiped their very existence for all eternity. After all, Varney's

1581
01:21:04,960 --> 01:21:08,800
Speaker 1: core thesis is this quote, the accumulation of great wealth

1582
01:21:08,880 --> 01:21:12,800
Speaker 1: has actually enriched America, all of us, has it, though

1583
01:21:13,200 --> 01:21:16,400
Speaker 1: the overwhelming majority of Americans, including Fox News viewers, certainly

1584
01:21:16,439 --> 01:21:18,920
Speaker 1: don't agree with that. According to a pupole from last year,

1585
01:21:19,040 --> 01:21:22,280
Speaker 1: only twenty one percent of Republicans think that billionaires are

1586
01:21:22,280 --> 01:21:25,000
Speaker 1: good for the country. A comprehensive Vox and Data for

1587
01:21:25,080 --> 01:21:28,240
Speaker 1: Progress poll that dived even deeper into the nation's increasing

1588
01:21:28,280 --> 01:21:30,880
Speaker 1: animosity towards the billionaire class has a lot to say

1589
01:21:30,920 --> 01:21:33,760
Speaker 1: about this. Seventy two percent of voters polled felt it

1590
01:21:33,800 --> 01:21:36,760
Speaker 1: was unfair that billionaires profited off of the pandemic, A

1591
01:21:36,840 --> 01:21:39,760
Speaker 1: mere twenty three percent felt the billionaires were good role

1592
01:21:39,840 --> 01:21:42,760
Speaker 1: models for the country. Only thirty six percent felt at

1593
01:21:42,800 --> 01:21:46,479
Speaker 1: all positively about billionaires. Majorities also felt the billionaires were

1594
01:21:46,520 --> 01:21:49,680
Speaker 1: already too powerful. Sixty one percent felt that they were

1595
01:21:49,680 --> 01:21:52,559
Speaker 1: too influential in the twenty twenty election, including actually higher

1596
01:21:52,640 --> 01:21:56,120
Speaker 1: numbers of Republicans than of Democrats. And it is no

1597
01:21:56,240 --> 01:21:59,519
Speaker 1: mystery why the public increasingly views the entire billionaire class

1598
01:21:59,520 --> 01:22:03,000
Speaker 1: with complete contempt. While the working class was struggling, suffering,

1599
01:22:03,040 --> 01:22:06,679
Speaker 1: and dying during the pandemic, our plutocrat overlords were raking

1600
01:22:06,680 --> 01:22:10,320
Speaker 1: it in, growing exponentially richer off the backs of poorly paid,

1601
01:22:10,439 --> 01:22:13,960
Speaker 1: mistreated workers. In fact, the pandemic helped to swell the

1602
01:22:14,040 --> 01:22:16,519
Speaker 1: ranks of the billionaire class, adding five hundred and seventy

1603
01:22:16,560 --> 01:22:19,320
Speaker 1: three new names to the list. Not only that, but

1604
01:22:19,360 --> 01:22:22,280
Speaker 1: the overlords running our largest monopolies are taking advantage of

1605
01:22:22,320 --> 01:22:26,880
Speaker 1: inflation to increasingly price gouged consumers, adding to mass misery

1606
01:22:27,000 --> 01:22:29,160
Speaker 1: and suffering. And we all see it, guys, it's not

1607
01:22:29,200 --> 01:22:32,040
Speaker 1: a secret. But there is a catch here. While Americans

1608
01:22:32,040 --> 01:22:34,439
Speaker 1: look with disgust on the billionaire class as a whole,

1609
01:22:34,840 --> 01:22:38,000
Speaker 1: when they're asked about specific billionaires, namely the famous ones

1610
01:22:38,000 --> 01:22:40,959
Speaker 1: that Varney happens to mention, they have much more positive feelings.

1611
01:22:41,120 --> 01:22:43,639
Speaker 1: Musk in particular, is actually quite popular with both Democrats

1612
01:22:43,680 --> 01:22:47,479
Speaker 1: and Republicans, contrary to current perception on Twitter. Varney likely

1613
01:22:47,520 --> 01:22:50,160
Speaker 1: knows that, so he holds Musk and Bezos up as

1614
01:22:50,200 --> 01:22:53,360
Speaker 1: if they are typical representatives of the billionaire class. The

1615
01:22:53,400 --> 01:22:56,400
Speaker 1: reality is that precious few of our nations ever expanding

1616
01:22:56,400 --> 01:22:59,960
Speaker 1: billionaire class are actually even delivering anything that the American

1617
01:22:59,840 --> 01:23:03,559
Speaker 1: people might want. Quite the opposite. According to Forbes, the

1618
01:23:03,760 --> 01:23:07,240
Speaker 1: largest single industry concentration of billionaires is actually Wall Street's

1619
01:23:07,240 --> 01:23:10,840
Speaker 1: money changers, whose wild speculation has for decades destabilized our

1620
01:23:10,880 --> 01:23:14,040
Speaker 1: economic system and which has long been divorced from simply

1621
01:23:14,040 --> 01:23:17,320
Speaker 1: supporting the real economy. People who did little except be

1622
01:23:17,400 --> 01:23:20,040
Speaker 1: born to the right family also have quite a significant

1623
01:23:20,080 --> 01:23:23,559
Speaker 1: precedence among our nations billionaire class. Looking at the Forbes

1624
01:23:23,600 --> 01:23:26,240
Speaker 1: list of the four hundred wealthiest people in America, one

1625
01:23:26,320 --> 01:23:30,920
Speaker 1: hundred and seventeen inherited fortunes. Have those billionaires accumulation of

1626
01:23:30,960 --> 01:23:34,519
Speaker 1: great wealth actually enriched America enriched all of us? As

1627
01:23:34,600 --> 01:23:38,160
Speaker 1: Varney claims, Are you better off because the Walton errors

1628
01:23:38,200 --> 01:23:40,400
Speaker 1: could throw their weight around in politics, including by the

1629
01:23:40,439 --> 01:23:43,600
Speaker 1: way pushing privatization of water rights in the West, And

1630
01:23:43,720 --> 01:23:46,840
Speaker 1: even with the supposedly good billionaires. Are you better off

1631
01:23:46,920 --> 01:23:50,320
Speaker 1: because Bill Gates persuaded the entire global public health community

1632
01:23:50,479 --> 01:23:53,679
Speaker 1: to cower before Big Pharmer's patent rights? Is your life

1633
01:23:53,720 --> 01:23:56,360
Speaker 1: improved by the millions that Michael Bloomberg has spent to

1634
01:23:56,360 --> 01:23:59,280
Speaker 1: buy off politicians from Stacy Abrams to San Francisco mayor

1635
01:23:59,320 --> 01:24:03,480
Speaker 1: London Breed? And are we actually better off? Because apparently

1636
01:24:03,640 --> 01:24:05,719
Speaker 1: the best we can hope for in our modern public

1637
01:24:05,800 --> 01:24:09,120
Speaker 1: square is to perhaps get a slightly better billionaire in charge.

1638
01:24:09,360 --> 01:24:11,840
Speaker 1: Because if, like me, you actually care about free speech,

1639
01:24:11,880 --> 01:24:15,000
Speaker 1: you'd know that the only real protection of such fundamental

1640
01:24:15,080 --> 01:24:19,360
Speaker 1: constitutional rights is through public democratic accountability. As Ben Burgess

1641
01:24:19,360 --> 01:24:22,760
Speaker 1: writes over at Jacobin, many centrist commentators seem alarmed at

1642
01:24:22,800 --> 01:24:25,160
Speaker 1: the thought that ordinary working class people will be too

1643
01:24:25,240 --> 01:24:27,960
Speaker 1: free to express themselves as they please and access a

1644
01:24:28,000 --> 01:24:29,800
Speaker 1: broad range of points of view so they can make

1645
01:24:29,880 --> 01:24:32,240
Speaker 1: up their own minds about what's right and what's wrong.

1646
01:24:32,720 --> 01:24:36,080
Speaker 1: I have the opposite concerns. I worry that we won't

1647
01:24:36,120 --> 01:24:37,960
Speaker 1: be able to count on Musk to stick to his

1648
01:24:38,000 --> 01:24:41,040
Speaker 1: stated principles when they come into conflict with his profits.

1649
01:24:41,360 --> 01:24:43,400
Speaker 1: It's as if we lived in a kind of libertarian

1650
01:24:43,439 --> 01:24:47,080
Speaker 1: dystopia where every inch of every city was private property

1651
01:24:47,160 --> 01:24:49,640
Speaker 1: and we could only hold protest marches on sidewalks that

1652
01:24:49,720 --> 01:24:52,400
Speaker 1: happen to have been bought by billionaires who were personally

1653
01:24:52,439 --> 01:24:55,519
Speaker 1: friendly to free speech. A horrible thought, indeed, but very

1654
01:24:55,600 --> 01:24:57,960
Speaker 1: much what we're facing now, at least was sor Varney.

1655
01:24:57,960 --> 01:24:59,960
Speaker 1: You can say the man's been consistent. I have never

1656
01:25:00,080 --> 01:25:02,799
Speaker 1: known him to do anything other than simp for wealthy elites.

1657
01:25:03,080 --> 01:25:04,519
Speaker 1: But there is a portion of the right that is

1658
01:25:04,560 --> 01:25:07,120
Speaker 1: postured as anti elite. You have really exposed themselves as

1659
01:25:07,200 --> 01:25:10,080
Speaker 1: exultant at elite power so long as the elites are

1660
01:25:10,080 --> 01:25:12,720
Speaker 1: seen as on their team. Writing at The American Conservative,

1661
01:25:12,720 --> 01:25:15,120
Speaker 1: Matthew Walter observes that quote the question for the new

1662
01:25:15,200 --> 01:25:17,360
Speaker 1: right appears to be not whether we should be ruled

1663
01:25:17,360 --> 01:25:21,400
Speaker 1: by billionaire capitalists, but which billionaire capitalists should hold sway quote.

1664
01:25:21,520 --> 01:25:24,439
Speaker 1: Conservatives who want must to purchase Twitter are not interested

1665
01:25:24,439 --> 01:25:28,120
Speaker 1: in altering or even seriously questioning the essentially oligarchic structure

1666
01:25:28,120 --> 01:25:31,240
Speaker 1: of American society. Instead of committing themselves to a program

1667
01:25:31,280 --> 01:25:34,599
Speaker 1: of broad based structural reform, one that might entail, for example,

1668
01:25:34,600 --> 01:25:37,679
Speaker 1: the nationalization of ISPs or social media and other basic

1669
01:25:37,720 --> 01:25:41,240
Speaker 1: Internet functions as public utilities and thus subject directly to

1670
01:25:41,320 --> 01:25:44,360
Speaker 1: various First Amendment protections. They accept that the money power

1671
01:25:44,400 --> 01:25:47,880
Speaker 1: will continue to hold illimitable dominion. Now, Sagre I think

1672
01:25:47,880 --> 01:25:49,920
Speaker 1: has been among those with an honest take that look.

1673
01:25:50,320 --> 01:25:53,840
Speaker 1: Relying on billionaire benevolence not ideal, but might be the

1674
01:25:53,880 --> 01:25:56,479
Speaker 1: best we can hope for in the current order. Fair enough,

1675
01:25:56,800 --> 01:25:59,280
Speaker 1: but if there was a genuinely aligned left right horseshoe

1676
01:25:59,360 --> 01:26:01,800
Speaker 1: movement to change that current order, we might have a

1677
01:26:01,800 --> 01:26:04,200
Speaker 1: little bit of a prayer. Unfortunately, what we've seen in

1678
01:26:04,240 --> 01:26:06,960
Speaker 1: the caveat free cheerleading coming from Plenty is that they're

1679
01:26:06,960 --> 01:26:10,400
Speaker 1: actually much closer to Stuart Vernie's over embrace of a

1680
01:26:10,479 --> 01:26:14,200
Speaker 1: new feudalism led by modern day billionaire aristocrats. Then they

1681
01:26:14,200 --> 01:26:17,080
Speaker 1: are committed to any actual populist belief in the democratic

1682
01:26:17,160 --> 01:26:20,599
Speaker 1: voice of the people. Spoiler alert For everyone pinning their

1683
01:26:20,640 --> 01:26:23,120
Speaker 1: hopes on the good graces and principled stances of Elon

1684
01:26:23,240 --> 01:26:26,840
Speaker 1: Musk or of any other billionaire, he, like every other

1685
01:26:26,920 --> 01:26:30,320
Speaker 1: flawed human being, is going to disappoint. The varning thing

1686
01:26:30,439 --> 01:26:33,560
Speaker 1: is so incredible. He like uses this and if you

1687
01:26:33,600 --> 01:26:36,360
Speaker 1: want to hear my reaction to Crystal's monologue, become a

1688
01:26:36,400 --> 01:26:41,080
Speaker 1: premium subscriber today at Breakingpoints dot com. All right, Sager,

1689
01:26:41,080 --> 01:26:42,920
Speaker 1: what are you looking at? Well, Okay, let me say

1690
01:26:42,920 --> 01:26:45,639
Speaker 1: this to the outset. I never set to cause chaos.

1691
01:26:46,120 --> 01:26:49,000
Speaker 1: On Tuesday evening, I was mine email business, I went

1692
01:26:49,040 --> 01:26:51,519
Speaker 1: to the gym, I sat down on my computer catch

1693
01:26:51,600 --> 01:26:54,679
Speaker 1: up on the news. I noticed a funny story. Vijaya Gade,

1694
01:26:54,720 --> 01:26:56,960
Speaker 1: the head of Twitter's policy team, the chief censor at

1695
01:26:57,000 --> 01:26:59,479
Speaker 1: the company who famously sat on the Joe Rogan podcast,

1696
01:26:59,479 --> 01:27:01,800
Speaker 1: gas lit the world on their policies when she was

1697
01:27:01,840 --> 01:27:04,640
Speaker 1: pressed by Tim Poole, reportedly broke down crying in a

1698
01:27:04,680 --> 01:27:08,720
Speaker 1: meeting after Musk bought the company. Here's a tweet. Basically

1699
01:27:09,040 --> 01:27:11,360
Speaker 1: what I said my editorial was that she was quote

1700
01:27:11,439 --> 01:27:13,840
Speaker 1: very upset about the Elon must takeover, and noted that

1701
01:27:13,880 --> 01:27:15,880
Speaker 1: she was the one responsible for censoring the Hunter Biden

1702
01:27:15,960 --> 01:27:19,240
Speaker 1: laptop story. Was it means spirited kind of, but I

1703
01:27:19,280 --> 01:27:20,920
Speaker 1: have no sympathy for the people at the top of

1704
01:27:20,920 --> 01:27:23,479
Speaker 1: the censorship regime, and I admit some serious shot and

1705
01:27:23,520 --> 01:27:25,519
Speaker 1: freud was going on. So I sent it and I

1706
01:27:25,600 --> 01:27:28,040
Speaker 1: moved on until my phone buzzed, and since then has

1707
01:27:28,080 --> 01:27:30,479
Speaker 1: basically not stop buzzing. I checked it and turned out

1708
01:27:30,479 --> 01:27:32,840
Speaker 1: that Elon Musk himself had replied to that tweet with

1709
01:27:32,960 --> 01:27:36,400
Speaker 1: quote suspending the Twitter account of a major news organization

1710
01:27:36,600 --> 01:27:39,760
Speaker 1: for publishing a truthful story was obviously inappropriate. Now, look,

1711
01:27:39,800 --> 01:27:42,439
Speaker 1: obviously I never expected Elon to reply, and I agree

1712
01:27:42,439 --> 01:27:44,240
Speaker 1: with the sentiment. I thought it was a good thing

1713
01:27:44,280 --> 01:27:46,400
Speaker 1: to see the new owner of Twitter respond on a

1714
01:27:46,439 --> 01:27:50,120
Speaker 1: matter where Twitter so obviously flagrantly titled it's censorship regime

1715
01:27:50,280 --> 01:27:53,160
Speaker 1: on the part of a single candidate in the race. Honestly,

1716
01:27:53,360 --> 01:27:55,320
Speaker 1: I didn't see how anyone could really disagree with what

1717
01:27:55,360 --> 01:27:58,840
Speaker 1: he said. But was I wrong? The blue tech technology

1718
01:27:58,880 --> 01:28:01,640
Speaker 1: press got very upset, not just with me but with

1719
01:28:01,720 --> 01:28:04,760
Speaker 1: Elon and reverted to their favorite accusation that Elon and

1720
01:28:04,800 --> 01:28:08,320
Speaker 1: I were apparently racist and sexist for targeting Vejaia Gade.

1721
01:28:08,560 --> 01:28:11,760
Speaker 1: The San Francisco correspondent for The Financial Times, Dave Lee

1722
01:28:11,920 --> 01:28:15,519
Speaker 1: immediately said moments after, Elon must publicly criticize the work

1723
01:28:15,560 --> 01:28:18,639
Speaker 1: of Twitter policy executive Vijia. Her Twitter mentions are full

1724
01:28:18,680 --> 01:28:21,040
Speaker 1: of hateful tweets? Is this how he plans to run

1725
01:28:21,040 --> 01:28:24,200
Speaker 1: the company? It was retweeted thousands of times. Oh God,

1726
01:28:24,400 --> 01:28:28,320
Speaker 1: not hateful tweets. Oh no, So Elon is responsible for

1727
01:28:28,400 --> 01:28:31,479
Speaker 1: what random people say because he and I highlight that

1728
01:28:31,560 --> 01:28:33,640
Speaker 1: she was part of one of the most shameful events

1729
01:28:33,720 --> 01:28:36,920
Speaker 1: in the company's history and behind one of the top

1730
01:28:37,080 --> 01:28:40,920
Speaker 1: reasons Elon bought the company in the first place. Tech

1731
01:28:40,920 --> 01:28:43,880
Speaker 1: Press dean Kara Swisher jumped in, saying it was appalling

1732
01:28:43,960 --> 01:28:46,960
Speaker 1: to see Vigia attack. She begged Jack Dorsey to come

1733
01:28:47,000 --> 01:28:49,880
Speaker 1: to her defense, to cry and quote racist rants against

1734
01:28:49,880 --> 01:28:53,800
Speaker 1: her on Twitter. So let's say it. Racist tweets against

1735
01:28:53,840 --> 01:28:57,040
Speaker 1: Vagia are obviously bad. But this is a Taylor Lorenz

1736
01:28:57,240 --> 01:29:00,400
Speaker 1: tried and true tactic. You are not allowed to criticize people,

1737
01:29:00,640 --> 01:29:03,120
Speaker 1: even if they are in immense positions of power, because

1738
01:29:03,160 --> 01:29:06,240
Speaker 1: people might be mean to them now noticeably. Of course,

1739
01:29:06,320 --> 01:29:08,599
Speaker 1: they're allowed to be mean to you. And when people

1740
01:29:08,600 --> 01:29:10,880
Speaker 1: are mean to you as a result of their criticism,

1741
01:29:11,040 --> 01:29:14,000
Speaker 1: then anything that you have to say is totally illegitimate.

1742
01:29:14,240 --> 01:29:16,519
Speaker 1: How about this, Let's be mean to each other. If

1743
01:29:16,560 --> 01:29:19,799
Speaker 1: there's fallout, so be it. Furthermore, this fits a pattern.

1744
01:29:20,040 --> 01:29:22,360
Speaker 1: If this were a normal Twitter employee making like one

1745
01:29:22,479 --> 01:29:25,120
Speaker 1: hundred grand a twenty seven year old program or something.

1746
01:29:25,280 --> 01:29:28,080
Speaker 1: That's a fair enough response. But this woman was literally

1747
01:29:28,080 --> 01:29:30,719
Speaker 1: in charge of the most censorious action in Twitter history,

1748
01:29:30,800 --> 01:29:33,320
Speaker 1: from Hunter Biden laptops to making the call to take

1749
01:29:33,360 --> 01:29:36,479
Speaker 1: Trump off the platform. Furthermore, as you see before you,

1750
01:29:36,760 --> 01:29:40,519
Speaker 1: she received a one hundred and thirty percent raise last year,

1751
01:29:40,960 --> 01:29:45,360
Speaker 1: bringing her total compensation to sixteen point nine million dollars,

1752
01:29:45,640 --> 01:29:48,200
Speaker 1: up from the eight million she was paid in twenty twenty.

1753
01:29:49,040 --> 01:29:51,479
Speaker 1: I got no sympathy for somebody who is a public

1754
01:29:51,479 --> 01:29:56,839
Speaker 1: figure and a multimillionaire getting criticized for purely policy reasons.

1755
01:29:57,080 --> 01:29:59,360
Speaker 1: The fallout continued, though the press really just would not

1756
01:29:59,439 --> 01:30:02,200
Speaker 1: let it go. Will Ormius, he's the technology reporter at

1757
01:30:02,200 --> 01:30:06,040
Speaker 1: the Washington Post, was extraordinarily upset, saying Elon now publicly

1758
01:30:06,040 --> 01:30:09,200
Speaker 1: agreed with and amplified criticisms from the right of two

1759
01:30:09,280 --> 01:30:14,280
Speaker 1: Twitter employees, one myself who accused the top policy executive censorship,

1760
01:30:14,439 --> 01:30:18,400
Speaker 1: and another a company lawyer for facilitating fraud. Now, let's

1761
01:30:18,520 --> 01:30:22,000
Speaker 1: dissect that latter tweet. In the latter one, Mike Cernovich

1762
01:30:22,160 --> 01:30:26,200
Speaker 1: on Twitter highlighted that Twitter's lawyer Jim Baker, who was

1763
01:30:26,280 --> 01:30:29,160
Speaker 1: General counsel at the FBI, was one of the people

1764
01:30:29,360 --> 01:30:33,879
Speaker 1: who personally arranged a meeting between the FBI and Michael Sussman,

1765
01:30:34,120 --> 01:30:37,680
Speaker 1: who you might remember as a fabulous liar pushing Russiagate

1766
01:30:37,800 --> 01:30:41,360
Speaker 1: lies ahead of the twenty sixteen election. Baker was later

1767
01:30:41,439 --> 01:30:45,160
Speaker 1: criminally investigated by the FBI for lying and was forced

1768
01:30:45,200 --> 01:30:49,320
Speaker 1: out for his role in Russiagate. All Elon replied was,

1769
01:30:49,400 --> 01:30:54,120
Speaker 1: quote sounds pretty bad. Yeah, it is a Russiagate liar

1770
01:30:54,439 --> 01:30:58,160
Speaker 1: working as a lawyer at the company seems bad, especially

1771
01:30:58,200 --> 01:31:02,040
Speaker 1: when that company censored the Hunter Biden laptop story. Calling

1772
01:31:02,080 --> 01:31:05,479
Speaker 1: those things out doesn't even seem crazy. This is how

1773
01:31:05,479 --> 01:31:08,960
Speaker 1: the Washington Post phrased it. Imagine getting up and going

1774
01:31:09,000 --> 01:31:11,280
Speaker 1: to work in the morning for a company whose new

1775
01:31:11,320 --> 01:31:14,679
Speaker 1: owner is systematically attacking your colleagues to his eighty four

1776
01:31:14,760 --> 01:31:17,000
Speaker 1: million followers in public, for a site you work for,

1777
01:31:17,240 --> 01:31:20,120
Speaker 1: and knowing you might be next. This is the worst

1778
01:31:20,200 --> 01:31:25,320
Speaker 1: case scenario. Twitter employees feared, Yeah, good, They should be afraid.

1779
01:31:25,560 --> 01:31:29,200
Speaker 1: They've been running our public square with their censorious ideology

1780
01:31:29,360 --> 01:31:32,840
Speaker 1: for nearly a decade. The fusion of the sensors with

1781
01:31:32,960 --> 01:31:36,519
Speaker 1: their lapdogs and defenders in the press are exactly how

1782
01:31:36,560 --> 01:31:39,280
Speaker 1: we got where we are today. It shows you just

1783
01:31:39,320 --> 01:31:42,719
Speaker 1: how dangerous the machine became. The press sets the tone

1784
01:31:42,920 --> 01:31:46,639
Speaker 1: for what is disinformation, the sensors act on that. Then

1785
01:31:46,800 --> 01:31:49,720
Speaker 1: if you attack the censors, the press attacks you. It's

1786
01:31:49,720 --> 01:31:52,599
Speaker 1: a fascinating and an important lesson how fuse the entire

1787
01:31:52,640 --> 01:31:55,600
Speaker 1: system is. It's exactly why I have many, many reservations

1788
01:31:55,640 --> 01:31:58,000
Speaker 1: about Elon and look, I don't think that putting your

1789
01:31:58,000 --> 01:31:59,840
Speaker 1: faith in any one person is a good thing. But

1790
01:32:00,000 --> 01:32:01,880
Speaker 1: this purchase of Twitter and making it known it will

1791
01:32:01,920 --> 01:32:05,000
Speaker 1: no longer be business as usual is unambiguously a net

1792
01:32:05,040 --> 01:32:07,719
Speaker 1: positive at least right now. And watching these people freak

1793
01:32:07,800 --> 01:32:10,960
Speaker 1: out and cry, kick and scream, is they lose power

1794
01:32:11,040 --> 01:32:14,280
Speaker 1: over us. That's something we should celebrate. Let the tears flow,

1795
01:32:14,560 --> 01:32:16,680
Speaker 1: let speech go unhindered, because it's going to be a

1796
01:32:16,680 --> 01:32:19,519
Speaker 1: fun few years. And that's the thing. Chrystal. The Russia

1797
01:32:19,560 --> 01:32:21,599
Speaker 1: Gate one we've beaten. And if you want to hear

1798
01:32:21,840 --> 01:32:25,360
Speaker 1: my reaction to Sager's monologue, become a premium subscriber today

1799
01:32:25,439 --> 01:32:30,040
Speaker 1: at breakingpoints dot com. Join us now. Is the executive

1800
01:32:30,120 --> 01:32:32,880
Speaker 1: editor at The American Prospect. The one and only David Dayan.

1801
01:32:32,960 --> 01:32:36,160
Speaker 1: Great to see you, David. Good to be here. First

1802
01:32:36,160 --> 01:32:38,519
Speaker 1: of all, I just just say that I cannot say

1803
01:32:38,600 --> 01:32:41,360
Speaker 1: enough what great work you guys do over the American prospect.

1804
01:32:41,400 --> 01:32:43,479
Speaker 1: We really lean on it in the show. You guys

1805
01:32:43,520 --> 01:32:46,880
Speaker 1: do in depth analysis that nobody seems to, you know,

1806
01:32:46,920 --> 01:32:48,760
Speaker 1: dig into the numbers the way that you guys do.

1807
01:32:48,800 --> 01:32:50,200
Speaker 1: So I just want to applaud you for the work

1808
01:32:50,200 --> 01:32:52,679
Speaker 1: that you're doing, first and foremost. But second of all,

1809
01:32:53,000 --> 01:32:56,720
Speaker 1: we'll get to the news here. Unexpectedly this morning, we

1810
01:32:56,760 --> 01:32:59,559
Speaker 1: have a new report that says that the US economy

1811
01:32:59,600 --> 01:33:02,640
Speaker 1: the GDE, shrank at a one point four percent annual

1812
01:33:02,760 --> 01:33:05,280
Speaker 1: rate in the first quarter. That is, according to the

1813
01:33:05,280 --> 01:33:09,360
Speaker 1: Commerce Department, that is its first contraction since early in

1814
01:33:09,400 --> 01:33:12,600
Speaker 1: the pandemic. Just the news just came out, So I

1815
01:33:12,600 --> 01:33:14,400
Speaker 1: know you're just sorting through it as we are, But

1816
01:33:14,560 --> 01:33:16,960
Speaker 1: what do you make of these numbers? Yeah, I mean,

1817
01:33:17,000 --> 01:33:20,320
Speaker 1: I think the expectation was for pretty slow growth, for

1818
01:33:20,439 --> 01:33:23,479
Speaker 1: something around one percent, So this is a surprise of

1819
01:33:23,520 --> 01:33:27,840
Speaker 1: the downside. I think there are a couple factors. Number One,

1820
01:33:28,320 --> 01:33:32,680
Speaker 1: the first quarter we had Omicron, which really at the

1821
01:33:32,680 --> 01:33:37,719
Speaker 1: beginning of the year was a significant you know, lead

1822
01:33:37,760 --> 01:33:41,080
Speaker 1: weight on the economy, and then for the last month

1823
01:33:41,120 --> 01:33:43,240
Speaker 1: you had the war in Ukraine and what that did

1824
01:33:43,680 --> 01:33:48,720
Speaker 1: to gas prices, And I think overall you're seeing the

1825
01:33:48,760 --> 01:33:53,640
Speaker 1: effects of inflation on consumer spending. But also, you know,

1826
01:33:53,680 --> 01:33:56,680
Speaker 1: my understanding is that a lot of this has to

1827
01:33:56,680 --> 01:34:01,800
Speaker 1: do with inventory reductions that yeah, yeah, there's a weird

1828
01:34:01,840 --> 01:34:04,519
Speaker 1: thing about GDP where if you end up having a

1829
01:34:04,520 --> 01:34:07,400
Speaker 1: lot of build up of inventory that kind of counts

1830
01:34:07,439 --> 01:34:10,160
Speaker 1: as as part of your gross domestic product because it's

1831
01:34:10,200 --> 01:34:13,400
Speaker 1: sitting there in a warehouse, and if you have less,

1832
01:34:13,479 --> 01:34:16,759
Speaker 1: then it counts less. So sometimes GDP is a little

1833
01:34:16,800 --> 01:34:20,719
Speaker 1: noisy as that goes. And this is also the first

1834
01:34:21,000 --> 01:34:25,200
Speaker 1: advanced estimate, and we'll get a more fine grained understanding

1835
01:34:25,280 --> 01:34:29,200
Speaker 1: of it and it could change from there. But yeah,

1836
01:34:29,240 --> 01:34:32,800
Speaker 1: sometimes you get these weird swings because of inventory. So

1837
01:34:32,880 --> 01:34:36,439
Speaker 1: the other one here is about exports, David, which also

1838
01:34:36,920 --> 01:34:39,120
Speaker 1: links back to what we were going to be talking

1839
01:34:39,120 --> 01:34:43,240
Speaker 1: about with you. I mean, so, why are exports contracting

1840
01:34:43,320 --> 01:34:46,200
Speaker 1: in our trade deficit ballooning, because that also seems to

1841
01:34:46,240 --> 01:34:50,599
Speaker 1: be a significant part of the reduction here in GDP. Yeah,

1842
01:34:50,960 --> 01:34:56,160
Speaker 1: I mean it's a good question. Obviously, as demand has

1843
01:34:56,280 --> 01:35:05,360
Speaker 1: increased for goods basic goods, necessities, and durable goods like furniture,

1844
01:35:05,680 --> 01:35:10,439
Speaker 1: washing machines or whatever. You almost can see it like, Okay,

1845
01:35:10,479 --> 01:35:13,400
Speaker 1: we don't make any of that stuff. So if the

1846
01:35:13,479 --> 01:35:17,120
Speaker 1: demand increases, the trade deficit is going to increase. People

1847
01:35:17,120 --> 01:35:19,680
Speaker 1: are going to eat the same amount of food. Agriculture

1848
01:35:19,760 --> 01:35:24,680
Speaker 1: is largely our biggest export, So unless people are consuming

1849
01:35:24,800 --> 01:35:28,400
Speaker 1: massive amounts of food, that's going to stay pretty even.

1850
01:35:28,720 --> 01:35:33,439
Speaker 1: But if people are consuming more durable items, just more

1851
01:35:33,640 --> 01:35:37,439
Speaker 1: more stuff that's going to come in from overseas. So

1852
01:35:38,000 --> 01:35:40,439
Speaker 1: that's one way to think about it. So, David, you

1853
01:35:40,479 --> 01:35:43,040
Speaker 1: had a great piece kind of evaluating where we are

1854
01:35:43,080 --> 01:35:45,160
Speaker 1: in terms of the supply chain crisis. Where we are

1855
01:35:45,200 --> 01:35:47,559
Speaker 1: in terms of you know, as inflation just continuing to

1856
01:35:47,600 --> 01:35:49,320
Speaker 1: go up and up and up. Are there any signs

1857
01:35:49,360 --> 01:35:51,439
Speaker 1: of that abating and any sectors. Let's go ahead and

1858
01:35:51,439 --> 01:35:53,479
Speaker 1: put this tear sheet up on the screen. It says

1859
01:35:53,479 --> 01:35:56,640
Speaker 1: supply chains are easing or they're not. Our system is

1860
01:35:56,680 --> 01:35:59,559
Speaker 1: so unstable that we could be seeing endless waves of

1861
01:35:59,600 --> 01:36:04,240
Speaker 1: supply dysfunction with dangerous impacts on the economy. You point

1862
01:36:04,240 --> 01:36:07,240
Speaker 1: to the fact that you've got variables pointing in sort

1863
01:36:07,280 --> 01:36:10,479
Speaker 1: of every direction that enable you to look at this

1864
01:36:10,680 --> 01:36:13,280
Speaker 1: a number of different ways. And you also talk about

1865
01:36:13,320 --> 01:36:16,280
Speaker 1: something called the bull whip effect, which is what could

1866
01:36:16,320 --> 01:36:20,080
Speaker 1: cause us sort of careening from one problem to another problem,

1867
01:36:20,120 --> 01:36:21,680
Speaker 1: back and forth. Can you just break some of that

1868
01:36:21,760 --> 01:36:24,760
Speaker 1: down for us, Yeah, I mean the bullwhip effect is

1869
01:36:24,840 --> 01:36:32,479
Speaker 1: this sort of standard understanding of supply chains where it

1870
01:36:32,600 --> 01:36:36,760
Speaker 1: takes time from when you order something if you're a retailer,

1871
01:36:37,040 --> 01:36:41,120
Speaker 1: to it actually getting to you, and conditions could change

1872
01:36:41,600 --> 01:36:44,519
Speaker 1: in that time period, and that's the bull whip. It's

1873
01:36:44,560 --> 01:36:47,439
Speaker 1: the time for the whip, the crack, and then you know,

1874
01:36:48,240 --> 01:36:55,519
Speaker 1: move back and straighten out again. So, for example, a

1875
01:36:55,600 --> 01:36:59,720
Speaker 1: lot of companies, fearing that they're not going to be

1876
01:36:59,760 --> 01:37:01,680
Speaker 1: able to get all of their supply, but they might

1877
01:37:01,680 --> 01:37:04,240
Speaker 1: be able to get some of it, they over ordered

1878
01:37:04,320 --> 01:37:08,639
Speaker 1: or double ordered uh in in you know, the past

1879
01:37:08,680 --> 01:37:12,080
Speaker 1: six months, hoping that they'd get something that they'd have

1880
01:37:12,560 --> 01:37:17,760
Speaker 1: to be able to sell. And by the time they

1881
01:37:17,800 --> 01:37:23,799
Speaker 1: actually start getting that stuff, then the demand has shrunk

1882
01:37:23,880 --> 01:37:28,400
Speaker 1: because of inflation, and there's there's now you've gone from

1883
01:37:28,479 --> 01:37:33,479
Speaker 1: shortage to glut. And there was a sense, especially in

1884
01:37:33,479 --> 01:37:36,120
Speaker 1: the beginning of April, I mean, the the GDP number

1885
01:37:36,200 --> 01:37:41,000
Speaker 1: comes out now and we were a month into beyond

1886
01:37:41,120 --> 01:37:46,840
Speaker 1: where the GDP is measuring, so April in particular, you

1887
01:37:47,000 --> 01:37:53,240
Speaker 1: started to see this softening in freight, particularly trucking, where

1888
01:37:53,600 --> 01:37:57,679
Speaker 1: there just weren't as many orders being asked for to

1889
01:37:57,680 --> 01:38:01,160
Speaker 1: to you know, move goods and things like that. And

1890
01:38:01,240 --> 01:38:04,680
Speaker 1: you're seeing what could be what has been described by

1891
01:38:04,760 --> 01:38:09,800
Speaker 1: some experts as a recession in trucking, and that's because

1892
01:38:09,840 --> 01:38:14,799
Speaker 1: of lower consumer spending, right, but the goods are already

1893
01:38:14,840 --> 01:38:16,759
Speaker 1: on the way by the time we get the lower

1894
01:38:16,760 --> 01:38:19,760
Speaker 1: consumer spending, and so you could end up with this

1895
01:38:19,920 --> 01:38:22,799
Speaker 1: glut from these retailers that have a bunch of inventory

1896
01:38:22,840 --> 01:38:25,280
Speaker 1: they can't sell. Now, that's like sort of you know,

1897
01:38:25,439 --> 01:38:28,760
Speaker 1: happening on the you know, it's kind of happening in

1898
01:38:28,800 --> 01:38:33,160
Speaker 1: real time. But the other part of this that cuts

1899
01:38:33,200 --> 01:38:37,960
Speaker 1: against that whole concept is the fact that Shanghai has

1900
01:38:38,000 --> 01:38:40,479
Speaker 1: been locked down for three weeks and now we're seeing

1901
01:38:40,520 --> 01:38:45,200
Speaker 1: Beijing potentially going into lockdown. Shanghai is more important as

1902
01:38:45,280 --> 01:38:50,559
Speaker 1: manufacturing goes because it's more of a hub you could see,

1903
01:38:50,760 --> 01:38:52,439
Speaker 1: you know, you have you have factories that have been

1904
01:38:52,439 --> 01:38:56,760
Speaker 1: shut down for a month and for basic items, for

1905
01:38:56,840 --> 01:39:01,880
Speaker 1: things that people just ordinarily consume. That's going to create shortages,

1906
01:39:01,960 --> 01:39:05,600
Speaker 1: and it could create shortages of component parts for manufacturing

1907
01:39:05,600 --> 01:39:08,559
Speaker 1: in other parts of the world. And so the bullwhip

1908
01:39:08,680 --> 01:39:11,400
Speaker 1: is going to whip back, right, I mean, you have

1909
01:39:11,600 --> 01:39:14,439
Speaker 1: this shortage, you went to glut, and now you might

1910
01:39:14,479 --> 01:39:19,439
Speaker 1: go back to shortage, and it's just an indicator of

1911
01:39:19,520 --> 01:39:24,120
Speaker 1: the essential instability of the way that our commerce and

1912
01:39:24,200 --> 01:39:27,920
Speaker 1: logistics systems work right now. Well, that's the point is

1913
01:39:28,520 --> 01:39:31,200
Speaker 1: this is none of this has to be built that way.

1914
01:39:31,600 --> 01:39:35,080
Speaker 1: It's just that you know, this microthin like ability to

1915
01:39:35,120 --> 01:39:38,439
Speaker 1: have a slightly higher profit margin trumped any sort of

1916
01:39:38,680 --> 01:39:42,160
Speaker 1: focus on resiliency that would keep us from careening from

1917
01:39:42,160 --> 01:39:46,200
Speaker 1: crisis to crisis to crisis and having such fragility built in,

1918
01:39:46,240 --> 01:39:48,800
Speaker 1: which is really what's been exposed over the past couple

1919
01:39:48,840 --> 01:39:53,080
Speaker 1: of years. David. I'm also wondering, are we seeing impacts

1920
01:39:53,120 --> 01:39:56,559
Speaker 1: from the Federal Reserve hiking interest rates and indicating they're

1921
01:39:56,560 --> 01:39:58,000
Speaker 1: going to do that at you know, at least the

1922
01:39:58,000 --> 01:40:01,519
Speaker 1: same pace potentially and even more accelerated pace, and also

1923
01:40:01,600 --> 01:40:04,080
Speaker 1: indicating that they're planning to sell out, you know, get

1924
01:40:04,280 --> 01:40:08,080
Speaker 1: unload assets from their balance sheet at a pretty good

1925
01:40:08,080 --> 01:40:10,360
Speaker 1: clip as well. Are we seeing an impact from that

1926
01:40:10,400 --> 01:40:14,519
Speaker 1: policy play out here too. I think not direct effects yet,

1927
01:40:14,600 --> 01:40:17,759
Speaker 1: because they've only raised a quarter point at this point.

1928
01:40:17,800 --> 01:40:21,360
Speaker 1: There's an expectation of a half pointer or maybe even

1929
01:40:21,360 --> 01:40:27,439
Speaker 1: the point seventy five point rise in May. But expectations

1930
01:40:27,880 --> 01:40:31,120
Speaker 1: are trending in that direction, and that particularly comes through

1931
01:40:31,120 --> 01:40:35,479
Speaker 1: the channel of mortgages. Mortgage rates are over five percent,

1932
01:40:35,760 --> 01:40:37,920
Speaker 1: and so it costs a lot more to buy a home,

1933
01:40:38,439 --> 01:40:40,920
Speaker 1: and we're starting to see that play out and some

1934
01:40:41,000 --> 01:40:47,719
Speaker 1: softening of housing markets. But to get back to your point,

1935
01:40:47,840 --> 01:40:51,280
Speaker 1: I think there there's one very key thing that you

1936
01:40:51,320 --> 01:40:55,679
Speaker 1: can say about the Federal reserves intention to increase these

1937
01:40:55,720 --> 01:41:00,320
Speaker 1: interest rates to break the back of inflation, and that's

1938
01:41:00,880 --> 01:41:05,120
Speaker 1: to ask the question, what are increased interest rates? How

1939
01:41:05,160 --> 01:41:09,200
Speaker 1: are they going to end the lockdown in Shanghai? How

1940
01:41:09,240 --> 01:41:12,439
Speaker 1: are they going to stop the five hundred ships that

1941
01:41:12,479 --> 01:41:16,599
Speaker 1: are currently off the coast of Shanghai Harbor. How are

1942
01:41:16,600 --> 01:41:20,320
Speaker 1: they going to shrink that number? They're not. I mean,

1943
01:41:20,360 --> 01:41:24,160
Speaker 1: we have a supply problem, and the FED is targeting

1944
01:41:24,240 --> 01:41:29,639
Speaker 1: demand essentially, is the issue to me, and I think

1945
01:41:29,680 --> 01:41:35,120
Speaker 1: what we've seen is not only the chaos that can

1946
01:41:35,160 --> 01:41:40,519
Speaker 1: arise from a pandemic, but the fact that we're in

1947
01:41:40,600 --> 01:41:43,400
Speaker 1: kind of a world where there are these threats to

1948
01:41:43,439 --> 01:41:46,840
Speaker 1: supply shocks at every turn. I mean, the war in

1949
01:41:47,439 --> 01:41:52,479
Speaker 1: Ukraine has been a much bigger spur, particularly on food prices,

1950
01:41:53,680 --> 01:41:58,400
Speaker 1: Wheat being a very major commodity export out of Ukraine.

1951
01:41:59,520 --> 01:42:02,800
Speaker 1: We've seen that be a much bigger deal, and of

1952
01:42:02,800 --> 01:42:08,559
Speaker 1: course oil than them what we saw. You know, in

1953
01:42:08,560 --> 01:42:12,320
Speaker 1: the two years leading up to the pandemic, climate issues

1954
01:42:12,560 --> 01:42:19,240
Speaker 1: have been periodically problems for supply. Last year in China,

1955
01:42:19,280 --> 01:42:22,919
Speaker 1: the Yante River flooding led to a lot of production delays.

1956
01:42:23,560 --> 01:42:26,559
Speaker 1: A heat wave, led because of the way in which

1957
01:42:26,760 --> 01:42:31,760
Speaker 1: China's energy sector goes, led to shutdowns at factories of

1958
01:42:31,800 --> 01:42:35,400
Speaker 1: electricity for several weeks, and that led to shutdowns we've

1959
01:42:35,439 --> 01:42:39,479
Speaker 1: seen like freak fires. There was a fire in Japan

1960
01:42:39,680 --> 01:42:44,320
Speaker 1: that reduced a lot of semiconductor capacity, and then there

1961
01:42:44,400 --> 01:42:47,559
Speaker 1: was a fire early this year in Berlin at the

1962
01:42:47,600 --> 01:42:51,920
Speaker 1: factory that makes the machines that make semiconductors. Right, So

1963
01:42:52,160 --> 01:42:57,920
Speaker 1: I mean there we don't. I mean, we've been able

1964
01:42:57,960 --> 01:43:05,160
Speaker 1: to make the very long intermediated supply chains work for

1965
01:43:05,320 --> 01:43:08,080
Speaker 1: I mean work to the extent, not really for workers,

1966
01:43:08,080 --> 01:43:11,000
Speaker 1: but at least for cheap prices for a long time.

1967
01:43:11,200 --> 01:43:15,439
Speaker 1: But I feel like the threats to this are rising.

1968
01:43:15,560 --> 01:43:19,280
Speaker 1: The hidden risks that this kind of system draws out

1969
01:43:19,840 --> 01:43:23,080
Speaker 1: have risen over the last several years, whether it's through

1970
01:43:23,600 --> 01:43:29,439
Speaker 1: more political unrest, climate and extreme weather events and now

1971
01:43:29,600 --> 01:43:35,120
Speaker 1: a pandemic, and I think I think it demands a

1972
01:43:35,200 --> 01:43:38,080
Speaker 1: rethink of this system. I think that we are all

1973
01:43:38,240 --> 01:43:40,160
Speaker 1: living through that in real time. David, thank you so

1974
01:43:40,240 --> 01:43:41,880
Speaker 1: much for breaking it down. Great to see you, Thank

1975
01:43:41,920 --> 01:43:45,120
Speaker 1: you absolutely, thank you, pleasure, Thank you guys so much

1976
01:43:45,120 --> 01:43:47,679
Speaker 1: for watching. We really appreciate it. And I'll just reiterate

1977
01:43:47,720 --> 01:43:49,760
Speaker 1: it one more time. Look, I mean, you know when

1978
01:43:49,760 --> 01:43:51,559
Speaker 1: the Washington Post and then were coming after me and

1979
01:43:51,600 --> 01:43:55,840
Speaker 1: by extension you by demeaning us definitely, yeah, denigrating that

1980
01:43:55,960 --> 01:44:00,200
Speaker 1: I would associate myself such a villainous character. All I

1981
01:44:00,240 --> 01:44:02,920
Speaker 1: could think about was thank God that we have you guys,

1982
01:44:03,120 --> 01:44:06,599
Speaker 1: our audience, our supporters, and the premium subs. By building

1983
01:44:06,600 --> 01:44:08,160
Speaker 1: the business the way that we did, it makes us

1984
01:44:08,160 --> 01:44:10,280
Speaker 1: as we can actually stand up to them. So thank

1985
01:44:10,280 --> 01:44:13,320
Speaker 1: you all so much for your support at this time.

1986
01:44:13,439 --> 01:44:15,200
Speaker 1: It really does mean more than you can ever know.

1987
01:44:15,320 --> 01:44:18,559
Speaker 1: We really appreciate it, and look for your hard earned money.

1988
01:44:18,840 --> 01:44:21,120
Speaker 1: We are using it as best as we possibly can.

1989
01:44:21,160 --> 01:44:24,120
Speaker 1: We've got all these new partnerships. We've got Jordan Sheridan

1990
01:44:24,200 --> 01:44:26,080
Speaker 1: who's on the ground. We're just talking to him. He's

1991
01:44:26,080 --> 01:44:28,439
Speaker 1: got a new place he's gonna be visiting, traveling for us.

1992
01:44:28,520 --> 01:44:30,679
Speaker 1: Got an exclusive footage. We're gonna have a highlight reel

1993
01:44:30,720 --> 01:44:32,680
Speaker 1: of all of his interviews. It's going to drop over

1994
01:44:32,720 --> 01:44:35,479
Speaker 1: the weekend. Marshall's been doing great interviews. Kyle's clips have

1995
01:44:35,560 --> 01:44:38,280
Speaker 1: been doing great as well. We've got Maximilian Alvarez. Matt

1996
01:44:38,320 --> 01:44:40,439
Speaker 1: Stole is coming into the studio right whenever we're done

1997
01:44:40,439 --> 01:44:42,800
Speaker 1: today to film something new for all of you. James

1998
01:44:42,880 --> 01:44:46,240
Speaker 1: Lee's video is fantastic. So yeah, all of it is

1999
01:44:46,320 --> 01:44:48,759
Speaker 1: just geared towards how can we give you the best

2000
01:44:48,760 --> 01:44:51,599
Speaker 1: possible value for your money. Now, We've got the newsletter

2001
01:44:51,680 --> 01:44:54,360
Speaker 1: going as well, a written description of everything we talk

2002
01:44:54,360 --> 01:44:56,320
Speaker 1: about in the show. So we're just gonna keep on

2003
01:44:56,360 --> 01:44:58,599
Speaker 1: building here. Guys. Thank you all so much. Yeah, we

2004
01:44:58,680 --> 01:45:01,439
Speaker 1: have never I think been more grateful for you all

2005
01:45:01,640 --> 01:45:03,360
Speaker 1: because it does provide you piece of more. Like the

2006
01:45:03,400 --> 01:45:05,000
Speaker 1: watching post thing is a pain in the ass and

2007
01:45:05,000 --> 01:45:07,240
Speaker 1: it's not cost free because the more that we get

2008
01:45:07,280 --> 01:45:10,519
Speaker 1: pushed down of like mainstream respectability. Obviously, you know that

2009
01:45:10,720 --> 01:45:13,240
Speaker 1: determines our treatment with Algorth them all those sorts of things,

2010
01:45:13,280 --> 01:45:15,800
Speaker 1: but it really does give you peace of mind that

2011
01:45:16,080 --> 01:45:19,120
Speaker 1: you know, yeah, we're gonna be fine, and we know

2012
01:45:19,200 --> 01:45:21,479
Speaker 1: you guys are gonna back us up and back Sagger up.

2013
01:45:21,560 --> 01:45:24,519
Speaker 1: So we have never been more grateful. We love you, guys.

2014
01:45:24,520 --> 01:45:26,240
Speaker 1: We got a lot of great content to post for

2015
01:45:26,280 --> 01:45:28,080
Speaker 1: you this weekend, so make sure you watch out for

2016
01:45:28,120 --> 01:45:29,559
Speaker 1: that and we'll see you back for a full show

2017
01:45:29,600 --> 01:45:58,840
Speaker 1: on Monday.