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Speaker 1: Hello, They're Happy Thursday. Welcome to another episode of the

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Speaker 1: Chuck Podcast. Got a terrific guest today, the former chair

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Speaker 1: of the FTC Federal Trade Commission, Lena kah is going

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Speaker 1: to join me for a conversation about sort of consumer

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Speaker 1: protection in the age of in this age of AI

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Speaker 1: big tech corporate consolidation, the fact that she was one

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Speaker 1: of the few Biden appointees that had a fan base

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Speaker 1: on the right as well as on the left. And

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Speaker 1: I hope it's both one part education about what exactly

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Speaker 1: the FTC should and can do, and one part sort

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Speaker 1: of warning, if you will, about about the things that

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Speaker 1: the government should be doing but hasn't been able to do.

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Speaker 1: I of course believe we're in a moment here not

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Speaker 1: dissimilar to the moment Teddy Roosevelt face miss the original Trustbuster,

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Speaker 1: if you will, And we're in a similar period, right,

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Speaker 1: the rise of the robber barons, the rise of the prologarts.

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Speaker 1: So I really have been looking forward to this interview.

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Speaker 1: I enjoyed it. I hope you will too. But before

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Speaker 1: we get to it, this was kind of Look, we

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Speaker 1: have plenty of days where we say wow, this was

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Speaker 1: kind of a crazy day. In the Trump era. And

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Speaker 1: you know, if you just's you could probably say about

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Speaker 1: half the days, you could say this is kind of

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Speaker 1: a crazy day in the Trump era. But we were

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Speaker 1: felt as if the morning began. I'm speaking to you

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Speaker 1: now it's Wednesday evening on July sixteenth, but this day

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Speaker 1: began on Wednesday, July sixteenth, where we thought we were

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Speaker 1: about to cover a story. Is the President of the

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Speaker 1: United States going to fire the chairman of the Federal

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Speaker 1: Reserve as a way to turn the page on the

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Speaker 1: Jeffrey Epstein scandal. And that's exactly what it seemed to

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Speaker 1: be what was building. There was a leak of this

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Speaker 1: meeting that he had, and I've been in the room

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Speaker 1: when Donald Trump has shown letters. Look, I've got a

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Speaker 1: firing letter. I had a bizarre heads up about his

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Speaker 1: indecision to fire people at one point and had an

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Speaker 1: interesting off the record with him before a firing when

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Speaker 1: he was asking for the opinions. You know, I've come

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Speaker 1: up with this letter saying I'm going to fire so

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Speaker 1: and so and so. He did it. This is not

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Speaker 1: a new thing for him. This is sort of how

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Speaker 1: he operates. He'll get somebody will put me, get me

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Speaker 1: a release, give me a letter, I'm going to fire somebody.

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Speaker 1: So apparently you had this letter together. Whether he's going

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Speaker 1: to fire Jerome Powell. Clearly they've and I told you

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Speaker 1: about this on Monday. I said, this is a story

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Speaker 1: that should be getting more attention, And boy did it

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Speaker 1: start getting attention, because it was clear something was afoot

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Speaker 1: where in order to get around the question about whether

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Speaker 1: the President had the power to fire the chairman of

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Speaker 1: the Federal Reserve. I couldn't fire him over a policy dispute.

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Speaker 1: That was pretty clear. The Supreme Court seemed to make

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Speaker 1: that clear to him, even as they've given him a

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Speaker 1: green light to fire, to have a more executive authority

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Speaker 1: on to hire and fire. The loophole they were developing

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Speaker 1: was all about, well, he's overseeing this renovation of the

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Speaker 1: Federal Reserves headquarters in Washington. There are cost overruns, and

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Speaker 1: the president did they believe they did have the legal

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Speaker 1: authority to fire him early on that so it looked

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Speaker 1: like they were manufacturing this authority. Well, of course, what

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Speaker 1: did the market. The markets had something to say to him.

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Speaker 1: The markets started awfully on Wednesday morning, and then of

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Speaker 1: course by noon he's backed off. But it does feel

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Speaker 1: as if you can't help but wonder. And I'm going

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Speaker 1: to use the words of my friendly and Caldwell over

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Speaker 1: at PAK where she said many Republicans she was talking

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Speaker 1: to over the past few days had predicted that Trump

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Speaker 1: was going to do something pretty dramatic in order to

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Speaker 1: distract from and that the anti Powell letter that he

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Speaker 1: produced was part of that idea that maybe feeding that

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Speaker 1: to his base could distract him. But I think he's

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Speaker 1: finding out now that this story is not not going

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Speaker 1: away at all, and he decided to light the fuse, right,

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Speaker 1: and the fuse that he lit is he attacked his

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Speaker 1: own supporters on this story, and he attacked them in

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Speaker 1: a way that I've always wondered what happens. He attacked

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Speaker 1: him in a way frankly that mainstream media and the

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Speaker 1: left has attacked his supporters at time, like you guys

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Speaker 1: are idiots. You're being duked, and that is usually not

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Speaker 1: a good way. You know, nobody is going when you

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Speaker 1: tell somebody they've been duped, Right, there's an expression it

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Speaker 1: is easier to con somebody than it is to convince

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Speaker 1: somebody they've been conned. Well, here's what he wrote. This

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Speaker 1: is this morning is truth. So the radical left Democrats

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Speaker 1: have hit payder again, just like the fake and fully

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Speaker 1: credited Steele docia, the lying fifty one intelligence agents, the

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Speaker 1: Laptop from Hell, which the Dems swore had come from Russia, No,

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Speaker 1: it came from Hunter Biden's bathroom, and even the Russia

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Speaker 1: Russia Russia scam itself, a totally fake and made up

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Speaker 1: story used in order to hide crooked Hillary Clinton's big

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Speaker 1: loss in the twenty sixteen election. These scams and hoaxes

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Speaker 1: are all the Democrats are good at. They are no

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Speaker 1: good at governing. Also, unlike Republicans, they stick together like

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Speaker 1: glu Actually that's not true. I'm going to have a

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Speaker 1: little comment about that with Hunter Biden, and I don't

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Speaker 1: they got a Biden agrees with them on that. Their

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Speaker 1: new scam, he writes, is what we will forever call

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Speaker 1: the Jeffrey Epstein hoax. And my past supporters have brought

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Speaker 1: into this bullshit, hook line and sinker. They haven't learned

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Speaker 1: their lesson and probably never will, even after being conned

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Speaker 1: by the lunatic left for eight long years. Actually, his

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Speaker 1: supporters weren't cone by the left because they've stuck by him.

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Speaker 1: But anyway, but I digress. I've had more success than

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Speaker 1: six months than perhaps any president in our country's history.

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Speaker 1: And all these people want to talk about with strong

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Speaker 1: prodding by the fake news, and the success star of

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Speaker 1: Dems is the Jeff free Epstein hoax. Let these weaklings

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Speaker 1: continue forward and do the Democrats work. Don't even think

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Speaker 1: about talking of our incredible and unprecedented success because I

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Speaker 1: don't want their support anymore. Thank you for your attention

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Speaker 1: to this matter. Make America great again. Well to say

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Speaker 1: that that went down that that didn't go down well

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Speaker 1: with his supporters is an understatement. And look, he is behaving.

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Speaker 1: What's interesting here The word hoax is an incredibly important

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Speaker 1: word that he used here because hoax is the word

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Speaker 1: that he always attached to Russia, and hoax is in

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Speaker 1: some ways, you know, I would say it's Trump speak

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Speaker 1: for I have no other explanations for my weird behavior. Right.

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Speaker 1: You know, one of the hallmarks of the twenty sixteen

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Speaker 1: Russia scandal was it was it was clear Russia was infiltrating,

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Speaker 1: you know, was trying to you know, manipulate our our

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Speaker 1: political conversation or discourse, or I mean that's been proven. Right,

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Speaker 1: the Justice Department charged a group out of Russia. Sanctions

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Speaker 1: were had like this is this is not in dispute.

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Speaker 1: Marco Rubio signed on to an investigation. The current Secretary

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Speaker 1: of State for Donald Trump signed on to an investigation

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Speaker 1: by the Senate that also, that is not in dispute.

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Speaker 1: The Russian government wanted to get involved, disrupted our election

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Speaker 1: in any way they thought they could, and yes, they

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Speaker 1: had a preference, and their preference they wanted Trump, not Clint. Now,

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Speaker 1: of course, what's in dispute was whether the Trump campaign

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Speaker 1: was colluding with the Russians to do this, or whether

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Speaker 1: they were just happily accepting the help the way you

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Speaker 1: might accept help from a surrogate or a labor union

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Speaker 1: or some other outside group, no different than the Koch

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Speaker 1: brothers paying for advertising to help the Republican ticket. This

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Speaker 1: was just, oh, the enemy of my enemy is my

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Speaker 1: ally and Trump's. But it was Trump's person behavior about

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Speaker 1: it that actually brought on more suspicion, and in fact,

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Speaker 1: there's something very similar is happening here. John chap who's

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Speaker 1: now The Atlantic, formerly of New York Magazine. He writes

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Speaker 1: this se because sometimes people sound guilty even if they aren't,

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Speaker 1: especially if their government officials still, whatever probability you had

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Speaker 1: in your mind that the Epstein files contained damaging material,

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Speaker 1: you should probably raise it after listening to Trump's remarks

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Speaker 1: on the subject. And that's the thing, right, It's the

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Speaker 1: same thing that happened with the Russian investigation. The more

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Speaker 1: he said things like, hey, Russia, if you're listening, you know,

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Speaker 1: the more he would talk about how much he loved

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Speaker 1: the wiki leagues and how much he seemed his campaign

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Speaker 1: appeared to be at least either really nimble for when

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Speaker 1: there were new wikileague releases or sometime Hoow got a

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Speaker 1: heads up and look like they were coordinating. Now, perhaps

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Speaker 1: they just it was Julianasan who was very helpful to

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Speaker 1: the Trump campaign, and it had nothing to do with

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Speaker 1: the Russians. I think there's a lot of I think

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Speaker 1: it is a reasonable conclusion that Trump didn't collude with

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Speaker 1: the Russians. But at the same time, he didn't mind

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Speaker 1: getting their help. Uh, and a lot of a lot

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Speaker 1: of folks didn't mind it, and didn't certainly didn't tell

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Speaker 1: them to stop, and certainly didn't you know, there was

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Speaker 1: one of the great uh, one of the weirder scandal

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Speaker 1: near scandals of the two thousand election. I'm gonna do

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Speaker 1: a little diversionary history lesson here Al Gore, George W. Bush.

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Speaker 1: Al Gore gets mailed a videotape of George W. Bush's

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Speaker 1: debate prep and they don't understand and it clearly came

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Speaker 1: from some staffer, uh in, you know, the Bush's media consultants.

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Speaker 1: Mark McKinnon's firm had never really worked with Republicans before

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Speaker 1: working with with with Bush. So there was some speculation

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Speaker 1: that there was some sort of cranky Democratic staffers working

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Speaker 1: on behalf of McKennon and Bush that may have may

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Speaker 1: have done this. Well, the Gore campaign was petrified, thought

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Speaker 1: they were being framed, and they went directly to the

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Speaker 1: FBI right and it basically became a nothing burger. Donald

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Speaker 1: Trump didn't actually go, you know whatever, they knew what

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Speaker 1: the Russians were, They didn't go running to the FBI going, hey,

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Speaker 1: look we are worried the Russians are doing this. You know,

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Speaker 1: John McCain and Barack Obama's campaign were hacked in eight

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Speaker 1: and they took that dispute and they made sure law

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Speaker 1: enforcement knew before it ever went public. So my point

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Speaker 1: is is that it's pretty clear Donald Trump had no

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Speaker 1: interest in alerting law enforcement, had that something that was

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Speaker 1: benefiting their campaign. But hey, this isn't on the up

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Speaker 1: and up. That ain't the way Donald Trump acts, thanks behaves,

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Speaker 1: et cetera. So my point is that I think it's

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Speaker 1: certainly plausible that two things can be true at the

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Speaker 1: same time. Right, And of course, you know, Trump the

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Speaker 1: advantage of the Steele dosia at the time is what

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Speaker 1: Trump was so successful at doing is if you can

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Speaker 1: discredit the steel dosier, you know, then it makes it

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Speaker 1: easier to discredit everything else. And then still does say

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Speaker 1: there was enough there that they could plausibly discredit the

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Speaker 1: story of Michael Cohen going to the Prague and the

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Speaker 1: whole you know, Ppe tape business that it turned out

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Speaker 1: like you know, I'm one of those that if if

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Speaker 1: it existed, it'd be out already. So it's it's likely

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Speaker 1: that this was and it's possible Christopher Steele was being

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Speaker 1: played by other Russians in that that all of this

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Speaker 1: was a mess there. But let me come back to Epstein, right,

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Speaker 1: which is, you know, I don't think a lot of

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Speaker 1: people Again, you go back to Trump's relationship, and it

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Speaker 1: was something I talked about before that I'm going to

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Speaker 1: go back. The most plausible explanation is yet a whole

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Speaker 1: bunch of rich people who had no problem taking free

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Speaker 1: plane rides with Jeffrey Epstein, free stuff from him, no,

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Speaker 1: you know, and knew who he was, always had the

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Speaker 1: you know, Donald Trump is on the record talking about

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Speaker 1: how young Jeffrey liked them, and they didn't look the

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Speaker 1: other way, right, or they just chose to look the

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Speaker 1: other way. It didn't bob, you know, because that's how

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Speaker 1: much they wanted the free airplane. And this so called

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Speaker 1: client list is. And again I go back to the government.

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Speaker 1: If they have you cannot do what they what what

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Speaker 1: some of these folks want, release everybody that may have

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Speaker 1: been associated with him, which may simply be were you

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Speaker 1: on the air and an airplane with him at any

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Speaker 1: one time? And of course people are going to take

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Speaker 1: that and assume if you were ever on an airplane,

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Speaker 1: you're a ped You're you're a pedophile too, right, And

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Speaker 1: that's where and this is so the question is is

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Speaker 1: that what Trump's afraid of? But now the more that

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Speaker 1: he digs in his heels, the more he digs in

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Speaker 1: his heels, the more he digs in his heels, and

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Speaker 1: now it's like, you know, I'm not going to sit

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Speaker 1: here and say I believe that he was doing the

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Speaker 1: same things Jeffrey was doing Jeffrey Epstein was doing. But

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Speaker 1: the more the more defiant he sounds, the more he

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Speaker 1: digs in his heels, and the more he attacks his

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Speaker 1: own supporters, the more clearly it's going to raise questions.

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Speaker 1: Now let's go back to why is he having a

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Speaker 1: hard time. Normally he can just tell his supporters, you know,

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Speaker 1: do his own Jedi my trick. These aren't the hoaxes

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Speaker 1: you're looking for. Pay no attention. Oh these ass isn't

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Speaker 1: the hoax we're looking for. You know, this work done?

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Speaker 1: Fox News? Oh hey, don't pay any attention to Jeffrey Epstein,

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Speaker 1: got it? And Fox News salutes the flag. They don't

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Speaker 1: cover anything in the Jeffrey Epstein story. Charlie Kirk said,

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Speaker 1: you know, when Trump said he was done with it,

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Speaker 1: Charlie Kirk then saluted the flag, said he's done with it.

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Speaker 1: Then he got attacked for that, then he came back.

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Speaker 1: So he's kind of a mess, right, But there's a

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Speaker 1: reason why. And again I go back to I go

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Speaker 1: back to the point of the hardest thing to do

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Speaker 1: is it is harder to give in somebody they've been

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Speaker 1: conned than to actually con them. And that's where we are.

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Speaker 1: And you've got to understand the importance of Jeffrey Epstein,

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Speaker 1: and the best way to understand it is in this

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Speaker 1: fascinating retort. So Donald Trump drops that explosive truth social

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Speaker 1: post telling anybody on his that supposedly is in MAGA

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Speaker 1: that believes the Jeffrey Epstein hoax, I don't want your

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Speaker 1: support anymore. You're just doing the bidding of the Democrats. Well,

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Speaker 1: the sort of the the unofficial pope of the pedophile

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Speaker 1: conspiracies is now Michael Flynn, the disgraced former general retired

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Speaker 1: general that was the National Security Advisor for about I believe,

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Speaker 1: I believe for about two Scaramucies, right. I think it

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Speaker 1: was twenty two days he survived. Scaramuccie is eleven days.

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Speaker 1: If I'm not mistaken. I hope I have that right.

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Speaker 1: Anthony will let me know if I've gotten that wrong.

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Speaker 1: So I think Flynn was two Scaramucies in office there,

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Speaker 1: and he went real deep into QAnon, to the point

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Speaker 1: where it's almost like he decided whether if no one

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Speaker 1: knows who Q is, I'll let people think it is me.

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Speaker 1: So anyway, you have to understand this. So he writes

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Speaker 1: this very long post on X and he's directed at

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Speaker 1: Donald Trump. Let me read a portion of it. He

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Speaker 1: says to Donald Trump, I hesitated to write this, however,

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Speaker 1: with the utmost respect and deference to you for all

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Speaker 1: you've withstood. If you know it better than me, what

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Speaker 1: the deep state can do when they want to turn

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Speaker 1: on a person. The Epstein affair is not about who

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Speaker 1: killed him or if he committed suicide. Personally, I'm glad

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Speaker 1: this known pedophile is debt, but neither is this a hoax.

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Speaker 1: This issue goes beyond that. Michael Flynn writes, there are

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Speaker 1: millions of Americans who overwhelmingly voted for you to be

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Speaker 1: our president, and we want you to be massively successful,

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Speaker 1: no more than me personally. I still have a target

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Speaker 1: on my forehead. Our country is facing a level of

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Speaker 1: internal subversion, and it is a relentless attack on the

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Speaker 1: very foundation for constitutional republic. So he is knee deep

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Speaker 1: in this belief that there are these hidden forces coming

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Speaker 1: after him. All right, He's really and the question is,

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Speaker 1: does he really believe it, or is this just a

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Speaker 1: giant grift because it bailed him out of financial trouble.

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Speaker 1: I certainly assume it's a financial grift. But we'll see,

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Speaker 1: he continues. I'm not going to read the whole thing,

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Speaker 1: but he continues here at the end, because this is

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Speaker 1: part's important, he says. An element that is of great

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Speaker 1: importance surrounding this Epstein affairs the fact that this man

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Speaker 1: was a known pedophile, had a list of clients who

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Speaker 1: represented the upper crust of society and likely did untowards

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Speaker 1: things to children on his island, in his homes in

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Speaker 1: New York City and New Mexico and maybe elsewhere, and

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Speaker 1: he was convicted of it. I want to single out

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Speaker 1: the word pedophilia here a minute, so as you know,

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Speaker 1: the entire QAnon bizarreness is sort of the importance of

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Speaker 1: believing your political opponents or pedophiles is important in the

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Speaker 1: whole dehumanization process. Right. This is I think at the

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Speaker 1: heart of this of this unfortunate climate that we're all

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Speaker 1: living in right now. And it's it's harsher, of course

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Speaker 1: online than it is in real life, but it's had

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Speaker 1: some real life consequences, right that this gentleman that really

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Speaker 1: thought there was some sort of you know, kids being

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Speaker 1: held captive in the basement of a pizza shop in Washington,

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Speaker 1: d C. He shows up and there is no basement,

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Speaker 1: nothing is there, And he was about to possibly kill

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Speaker 1: a whole bunch of innocent patrons and the owner of

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Speaker 1: of of a pizza shop in Washington, d C. But

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Speaker 1: Jeffrey Epstein doing what he did, he's sort of like

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Speaker 1: the Kevin six degrees of Kevin Bacon game for these

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Speaker 1: for this, for this crazy conspiracy theory, once you have

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Speaker 1: bought in that the Left is not just against you culturally,

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Speaker 1: but is against you because they're a cabal of pedophiles.

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Speaker 1: And again, this is this is what this crowd is believing.

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Speaker 1: This is where Marjorie Taylor Green gets her gets her

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Speaker 1: energy from. This is Michael Flynn, this is this, This

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Speaker 1: is this world. This is how Dan Bongino made a

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Speaker 1: fortune uh uh conning these people with his media. And

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Speaker 1: all of a sudden, if Donald Trump is saying that

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Speaker 1: Jeffrey Epstein story is a hoax, it shatters the entire

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Speaker 1: conspiracy that was built up. It's sort of like it's

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Speaker 1: like it's it's an extraordinary It's like knocking down a

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Speaker 1: foundation pillar. Right if you have a house on stilts,

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Speaker 1: and if you get the right one, you know, or

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Speaker 1: if you're in Jenga, it's like if you pull the

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Speaker 1: wrong leg, everything collapses. And if if Jeffrey Epstein is

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Speaker 1: not proven to have been the sort of the chief

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Speaker 1: recruiter of victor of young kids to feed this pediph

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Speaker 1: this manufactured pedophilia, uh uh ring that that this conspiracy

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Speaker 1: supposedly has cocked it and supposedly exists. You need the

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Speaker 1: Jeffrey Epstein story right because Jeffrey Epstein put a face

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Speaker 1: to it. Jeffrey Epstein may actually be a pedophile. Jeffrey

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Speaker 1: Epstein knew all these famous people right now? Does that

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Speaker 1: mean just because he knew these famous people, does that

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Speaker 1: mean all of them are now this well? To Michael Flynn,

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Speaker 1: it is right now, Whether again I go back, I

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Speaker 1: don't know whether Michael Flynn really believes this now or

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Speaker 1: whether this has just been so financially lucrative for him

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Speaker 1: to be the face of this of this crowd that

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Speaker 1: he has as the high unofficial high priest of the

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Speaker 1: QAnon crowd and believers of this conspiracy, he had to

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Speaker 1: push back or his financial empire would crump. So this

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Speaker 1: is the part where you send up. You end up

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Speaker 1: finding out does Donald Trump fully understand his base? Right?

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Speaker 1: There's sort of and there's always been two distinct bases

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Speaker 1: with tru. There's the actual working class space, the ones

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Speaker 1: that demographically are non the non college educated crowd, the

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Speaker 1: people that you know, the different people that shower at night,

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Speaker 1: shower after work versus showering before work. Right, that's sort

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Speaker 1: of like do you shower, do you shower when you

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Speaker 1: come home for work, or do you shower before you

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Speaker 1: go to work? Right? That that sort of blue collar,

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Speaker 1: white collar mindset. And then there's the crazy conspiracy theorists.

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Speaker 1: And Donald Trump fed those conspiracy theorists. Right, he has

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Speaker 1: built his entire political profile on a conspiracy theory. It

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Speaker 1: began with burtherism. Right. How did he how did he

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Speaker 1: convince the anti Obama right, the ones that were the

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Speaker 1: most vocal who decided not to oppose Obama on policy

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Speaker 1: but simply oppose him whether on otherism, right, the fact

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Speaker 1: is he a real American? And questioning whether he was

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Speaker 1: an American? Trump, of course rode that wave of conspiracy theory,

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Speaker 1: and so one of his habits is this comes back

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Speaker 1: to what he did with David Duke. Right, Why couldn't

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Speaker 1: he immediately denounce David Duke because David Duke sent something

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Speaker 1: nice about him? Why couldn't he immediately denounce Vladimir Putin

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Speaker 1: because Putin said something nice about him? So he is

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Speaker 1: sort of catered, right. He appeases this crowd of conspiracy theorists,

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Speaker 1: and he'll feed him every once in a while. Right,

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Speaker 1: He'll feed the velociraptor every once in a while, And

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Speaker 1: suddenly the velociraptor has a taste for this and has

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Speaker 1: a taste for this. And of course they've kept feeding

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Speaker 1: and feeding and feeding until they caught the car. They

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Speaker 1: run the government, the head some of the lead characters

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Speaker 1: pushing the conspiracy theory are actually in now the deep

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Speaker 1: state themselves, Dan Bongino and Cash Patel and Pam Bondi

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Speaker 1: got into it as she's been trying to debushify herself

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Speaker 1: and retrumpify her self, if you will. And here they are.

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Speaker 1: And so whatever the truth is, and I you know,

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Speaker 1: I'm still one of those who believes that what they

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Speaker 1: have they don't if they had evidence that somebody else

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Speaker 1: committed a crime on Jeffrey Epstein's island, they would have

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Speaker 1: brought the charges. Okay, this idea that charges wouldn't have

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Speaker 1: been brought, I just you know, I under I understand.

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Speaker 1: You know, nobody wants to get in the way of

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Speaker 1: a good conspiracy theory. The conspiracy theories are always more

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Speaker 1: interesting than the truth. But when you've spent twelve years

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Speaker 1: torching institutions, torching those who were trying to speak the truth,

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Speaker 1: and then you're in charge of set organization and then

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Speaker 1: you're like, you can't believe they don't believe you, and

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Speaker 1: it's like, well, you know, you reap whatt yourself. So

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Speaker 1: but I do think to truly understand why Trump did.

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Speaker 1: I don't think full appreciates how important Jeffrey Epstein is

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Speaker 1: as a connective tissue to this weird Like I said,

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Speaker 1: one of the dehumanization tactics of the right has been

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Speaker 1: to manufacture this pedophilia business. And so it is it

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Speaker 1: is that is the long tail of crazy here that

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Speaker 1: has brought Epstein into this sort of swirl, if you will,

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Speaker 1: And why it is so important for this crowd that

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Speaker 1: you know, the proof of Epstein's guilt Seeing this is

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Speaker 1: sort of it will become. It is this idea that hey,

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Speaker 1: we're not crazy. See we're right, We're right, We're right.

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Speaker 1: There was a pedophile ring. You know, we kept telling

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Speaker 1: you there was one, and here it is. And if

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Speaker 1: it's not there, you know, for some of these people,

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Speaker 1: if they're true believers, it it becomes a oh my god.

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Speaker 1: You know, this could be the moment that they maybe

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Speaker 1: feel cond I'll say this. You know, we've all wondered

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Speaker 1: when you know the Trump err is going to end

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Speaker 1: at some point, does it end with a whimper? Does

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Speaker 1: it end with a loud bang? Does it end you know?

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Speaker 1: I don't you know, I don't think any of us

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Speaker 1: believe it's going to It was going to end with

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Speaker 1: a rousing closing argument in some sort of courtroom, you know.

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Speaker 1: And there was a lot of prosecutors that dreamed of

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Speaker 1: that they were somehow going to be a TV lawyer

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Speaker 1: and be portrayed in a TV movie someday, that they

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Speaker 1: were going to get him right. It was never going

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Speaker 1: to end this way. It always was going to end

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Speaker 1: when he got exposed for being a hypocrite, right and

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Speaker 1: for for duping his own people. I think a lot

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Speaker 1: of us thought it, but still believe it will be

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Speaker 1: when it hits their own pocketbook, when they realized the

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Speaker 1: policies that he's advocating are a disaster and they're going

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Speaker 1: to be economically punishing here in a few months. Unfortunately.

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Speaker 1: I really hope, uh you know, I mean, look, you know,

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Speaker 1: buried in this sort of story to end about him

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Speaker 1: toying with firing Jay Powell, which clearly doing it feels

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Speaker 1: like he was trying to do it as a way

428
00:25:08,240 --> 00:25:11,560
Speaker 1: to distract from Epstein. But the point is he's going

429
00:25:11,640 --> 00:25:13,359
Speaker 1: to get control of the FED in a year no

430
00:25:13,440 --> 00:25:16,880
Speaker 1: matter what. And the fact that we're going to have

431
00:25:18,000 --> 00:25:22,040
Speaker 1: a president who, by the way, is now showing so

432
00:25:22,200 --> 00:25:26,000
Speaker 1: many signs of age, and it is it is, you know,

433
00:25:26,119 --> 00:25:30,879
Speaker 1: whether it's falling asleep at events more often now, whether

434
00:25:30,960 --> 00:25:34,240
Speaker 1: there's you know, he's there's clearly a bunch of medical issues.

435
00:25:34,240 --> 00:25:37,119
Speaker 1: He's not disclosing, you know, what's wrong with his hand.

436
00:25:37,280 --> 00:25:42,760
Speaker 1: We've seen that, you know, there's there's there's something he's

437
00:25:42,800 --> 00:25:45,960
Speaker 1: dealing with, some sort of health issue that they're not disclosing.

438
00:25:46,400 --> 00:25:50,920
Speaker 1: And of course they've so uh scared the press score

439
00:25:50,920 --> 00:25:54,080
Speaker 1: that covers them. It seems like nobody will ask about

440
00:25:54,080 --> 00:25:56,159
Speaker 1: this as directly, you know, and if they do, he

441
00:25:56,320 --> 00:25:58,720
Speaker 1: you know, he chastises him as evil by the way,

442
00:25:58,840 --> 00:26:01,200
Speaker 1: you know, and all this business, this weird use of

443
00:26:01,240 --> 00:26:04,840
Speaker 1: the word evil, which is again ahuman as dehumanization tactic

444
00:26:05,720 --> 00:26:07,919
Speaker 1: in order to give a green light for his supporters

445
00:26:07,960 --> 00:26:11,399
Speaker 1: to treat fellow Americans like they're not American and that

446
00:26:11,440 --> 00:26:16,520
Speaker 1: they're not human. But something is off about him, right,

447
00:26:16,600 --> 00:26:21,400
Speaker 1: He didn't seem to remember that he appointed J. Powell. Now.

448
00:26:21,440 --> 00:26:23,679
Speaker 1: I accept the premise that in his first term he

449
00:26:23,840 --> 00:26:26,879
Speaker 1: let way too many other people influence him that maybe

450
00:26:26,920 --> 00:26:29,720
Speaker 1: now he regrets. I think there's no doubt he was

451
00:26:29,800 --> 00:26:33,240
Speaker 1: on the job training, he did not understand how everything worked,

452
00:26:33,240 --> 00:26:36,239
Speaker 1: and he took a lot of other people's advice, and

453
00:26:36,280 --> 00:26:38,960
Speaker 1: he was surrounded by folks that were more in the

454
00:26:39,000 --> 00:26:43,600
Speaker 1: mainstream than I think many gave credit. I go back,

455
00:26:43,840 --> 00:26:47,520
Speaker 1: you know, Mike Pens and Wrytes prepus stacked that first

456
00:26:47,560 --> 00:26:51,680
Speaker 1: Trump term with a lot of conservative normies, if you will,

457
00:26:52,040 --> 00:26:57,680
Speaker 1: who I think prevented economic calamity before. They couldn't get

458
00:26:57,720 --> 00:26:59,920
Speaker 1: in his way to you know, once COVID hit the crazy,

459
00:27:00,119 --> 00:27:02,159
Speaker 1: you know, there was only so much they could do

460
00:27:02,280 --> 00:27:06,320
Speaker 1: to keep him from from totally messing things up. And

461
00:27:06,800 --> 00:27:08,840
Speaker 1: you know, by the time COVID came, they couldn't stop it,

462
00:27:09,280 --> 00:27:16,159
Speaker 1: and the public reacted as you might expect. So so,

463
00:27:16,359 --> 00:27:18,800
Speaker 1: but the fact that he can't remember that he appointed

464
00:27:18,840 --> 00:27:21,840
Speaker 1: him or that it's not I don't think that's a denial.

465
00:27:22,000 --> 00:27:26,360
Speaker 1: I think that is some weird you know, maybe it's

466
00:27:26,400 --> 00:27:30,240
Speaker 1: cognitive dissonance, but maybe it's something else. But there's definitely

467
00:27:30,320 --> 00:27:33,560
Speaker 1: he is showing just simple signs of age. He tires earlier.

468
00:27:33,960 --> 00:27:37,399
Speaker 1: You can see it. Anytime after four o'clock in the afternoon,

469
00:27:37,440 --> 00:27:41,560
Speaker 1: he seems to fade a little bit. And you can

470
00:27:41,600 --> 00:27:45,360
Speaker 1: just look. I mean even when he if you look

471
00:27:45,400 --> 00:27:50,320
Speaker 1: at his where he was celebrating with the soccer team,

472
00:27:50,359 --> 00:27:53,119
Speaker 1: even the celebration, he just seemed a little off. He

473
00:27:53,240 --> 00:27:57,320
Speaker 1: seemed like he was a little struggling to sort of

474
00:27:57,359 --> 00:28:02,159
Speaker 1: have the energy to be there. So there's definitely you know,

475
00:28:02,640 --> 00:28:04,919
Speaker 1: who knows, they're not never going to say anything, and

476
00:28:04,960 --> 00:28:06,919
Speaker 1: whatever they release is not going to you know, you

477
00:28:06,960 --> 00:28:09,040
Speaker 1: can't take it to the bank. Right We are now

478
00:28:09,080 --> 00:28:11,879
Speaker 1: living in an era where any press release that the

479
00:28:11,880 --> 00:28:15,560
Speaker 1: Trump administration puts out is not factual. You have to

480
00:28:15,560 --> 00:28:17,720
Speaker 1: assume it's not factual at all, and you have to

481
00:28:17,720 --> 00:28:22,040
Speaker 1: figure out, okay, where what's relevant here. It's very it's

482
00:28:22,080 --> 00:28:26,080
Speaker 1: never been harder to be a reporter on any government

483
00:28:26,119 --> 00:28:31,280
Speaker 1: agency because you certainly have to acknowledge whatever you know

484
00:28:31,320 --> 00:28:36,199
Speaker 1: they're there, Uh, you have to acknowledge their point, you know,

485
00:28:36,240 --> 00:28:40,520
Speaker 1: what their response to an article. But sometimes there's you know,

486
00:28:40,560 --> 00:28:43,840
Speaker 1: it's so much cognitive dissonance that it almost makes your story.

487
00:28:43,840 --> 00:28:45,760
Speaker 1: I mean that guy Stephen Chung will say things that

488
00:28:45,880 --> 00:28:49,239
Speaker 1: just are non sequiturs, right, which is the point? Right?

489
00:28:49,280 --> 00:28:52,360
Speaker 1: They almost kind of want because the more the more

490
00:28:52,400 --> 00:28:55,239
Speaker 1: they confuse the story, the harder it is for a

491
00:28:55,280 --> 00:28:57,600
Speaker 1: negative story to stick. So it's a it's a tactic

492
00:28:57,600 --> 00:29:02,920
Speaker 1: and it's been been quite successful one. But but there's something,

493
00:29:03,040 --> 00:29:05,640
Speaker 1: you know, there's something here. I think this is proof

494
00:29:05,680 --> 00:29:09,880
Speaker 1: he doesn't fully understand his own voters. Sometimes he certainly

495
00:29:09,880 --> 00:29:13,680
Speaker 1: doesn't understand what he the monster he has created with

496
00:29:13,760 --> 00:29:19,640
Speaker 1: this mainstreaming so many conspiracies over the last decade. And

497
00:29:19,760 --> 00:29:24,240
Speaker 1: you know, if this is the way it ends, you

498
00:29:24,320 --> 00:29:26,080
Speaker 1: might want to give an applause to the Writer's room

499
00:29:26,120 --> 00:29:28,080
Speaker 1: on this one. Right, it's a it's a more unique

500
00:29:28,160 --> 00:29:32,120
Speaker 1: ending than something that just uh, that just goes out

501
00:29:32,200 --> 00:29:36,800
Speaker 1: with a whimper. But you know this, I don't think

502
00:29:36,880 --> 00:29:43,000
Speaker 1: he gets out of this Epstein debacle unscathed. I think

503
00:29:43,440 --> 00:29:46,720
Speaker 1: at some point his folks this this also has the feel,

504
00:29:46,800 --> 00:29:49,160
Speaker 1: you know, one of the even in the pre Trump era,

505
00:29:49,920 --> 00:29:53,360
Speaker 1: there was always the summer silly season where there'd be

506
00:29:53,400 --> 00:29:57,959
Speaker 1: some summer scandal that would kind of just catch a

507
00:29:58,000 --> 00:30:01,720
Speaker 1: White House sleeping a little bit, but catch them off guard.

508
00:30:01,760 --> 00:30:03,640
Speaker 1: I think they weren't. You know, they've been focused on

509
00:30:03,640 --> 00:30:08,000
Speaker 1: some other things. They didn't really understand how explosive what

510
00:30:08,080 --> 00:30:10,320
Speaker 1: they were dealing with with Epstein. So if you told

511
00:30:10,320 --> 00:30:12,560
Speaker 1: me by September, they're in a different place and this

512
00:30:12,600 --> 00:30:16,960
Speaker 1: is sort of still still percolating, and there's still some

513
00:30:17,000 --> 00:30:20,080
Speaker 1: people that won't forgive them, But it's a smaller cabala

514
00:30:20,200 --> 00:30:24,160
Speaker 1: people that won't surprise me. But the fact is, you know,

515
00:30:24,200 --> 00:30:28,160
Speaker 1: it's it's like Rocky four and the first time he

516
00:30:28,280 --> 00:30:34,920
Speaker 1: made Drago bleed. It bleeds right, it's human. This one's

517
00:30:34,960 --> 00:30:41,680
Speaker 1: drawn blood and Trump. The question is how debilitating politically

518
00:30:41,960 --> 00:30:44,440
Speaker 1: is it going to be? All Right, I've gone on

519
00:30:44,760 --> 00:30:49,400
Speaker 1: long enough with my intro here. I really hope you

520
00:30:49,480 --> 00:30:53,200
Speaker 1: enjoy this conversation with Lena Khan. It was fascinating to me.

521
00:30:53,440 --> 00:30:56,280
Speaker 1: I think you'll learn a lot and hopefully understand even

522
00:30:56,320 --> 00:31:10,800
Speaker 1: better the role of the ft S And joining me

523
00:31:10,840 --> 00:31:13,760
Speaker 1: now is the former head of the f t C

524
00:31:14,520 --> 00:31:20,200
Speaker 1: Federal Trade Commission. The alphabets sometimes folks get confused. Uh,

525
00:31:20,520 --> 00:31:23,280
Speaker 1: it's Lena Khan. Lena, welcome to the Todd Past. Thanks

526
00:31:23,320 --> 00:31:28,200
Speaker 1: for being here, Thanks for having me so before we

527
00:31:28,240 --> 00:31:30,719
Speaker 1: get into some of the nitty gritty of some of

528
00:31:30,760 --> 00:31:35,760
Speaker 1: the work that you left to your successor, and in

529
00:31:35,800 --> 00:31:38,800
Speaker 1: some cases, I'm curious how pleasantly surprised you are that

530
00:31:38,880 --> 00:31:41,880
Speaker 1: some of your work is continuing. Uh, And we will

531
00:31:41,880 --> 00:31:46,360
Speaker 1: get into that. But you were the youngest FTC chair

532
00:31:46,480 --> 00:31:49,680
Speaker 1: and I guess did you know you wanted to be

533
00:31:50,040 --> 00:31:51,880
Speaker 1: the chair of the FTC? And when did you know

534
00:31:51,920 --> 00:31:54,360
Speaker 1: you wanted to do that? And how does one become that?

535
00:31:55,120 --> 00:31:58,400
Speaker 1: I mean literally, for those that you know, trust busting

536
00:32:00,480 --> 00:32:03,160
Speaker 1: and the demand for government regulation is something that's always

537
00:32:03,200 --> 00:32:05,200
Speaker 1: sort of in the ether, but a lot of people

538
00:32:05,240 --> 00:32:09,040
Speaker 1: don't understand how specifically it would work, how the FTC works.

539
00:32:09,480 --> 00:32:12,240
Speaker 1: How did you know you wanted to do this when

540
00:32:12,240 --> 00:32:13,280
Speaker 1: you were younger?

541
00:32:13,880 --> 00:32:17,160
Speaker 2: Yeah, I've had a somewhat unusual path to antitrust and

542
00:32:17,200 --> 00:32:20,880
Speaker 2: consumer protection. I actually always growing up, wanted to be

543
00:32:21,000 --> 00:32:24,479
Speaker 2: a journalist and was really into kind of research and

544
00:32:24,520 --> 00:32:27,640
Speaker 2: reporting and figuring out how to tell stories that are

545
00:32:27,760 --> 00:32:31,360
Speaker 2: kind of holding power to account. I graduated shortly after

546
00:32:31,400 --> 00:32:34,120
Speaker 2: the financial crisis, and so journalism jobs were pretty difficult

547
00:32:34,160 --> 00:32:36,960
Speaker 2: to come by, and ended up landing at a think

548
00:32:36,960 --> 00:32:40,760
Speaker 2: tank and research organization where my job was to document

549
00:32:40,960 --> 00:32:44,200
Speaker 2: the effects of market consolidation. And so I was doing

550
00:32:44,240 --> 00:32:47,680
Speaker 2: a lot of reporting by talking to farmers, say, and

551
00:32:47,760 --> 00:32:51,160
Speaker 2: figuring out, hey, this big merger happened a few years ago,

552
00:32:51,680 --> 00:32:53,600
Speaker 2: what does it look like to be a chicken farmer

553
00:32:53,640 --> 00:32:59,400
Speaker 2: in today's America. I was on book publishing, rental cars, airlines,

554
00:33:00,040 --> 00:33:04,080
Speaker 2: and really saw how over the last few decades, a

555
00:33:04,160 --> 00:33:09,360
Speaker 2: secret trend across the American economy has been increasing consolidation.

556
00:33:09,680 --> 00:33:13,120
Speaker 2: And so whereas decades ago you would have dozens and

557
00:33:13,160 --> 00:33:17,080
Speaker 2: dozens of competitors, increasingly now you just have a small

558
00:33:17,160 --> 00:33:20,800
Speaker 2: number of companies that dominate, be it in meatpacking, be

559
00:33:20,880 --> 00:33:23,880
Speaker 2: it in airlines. If you go to the grocery store,

560
00:33:24,400 --> 00:33:26,600
Speaker 2: it might look like there are dozens of brands, but

561
00:33:26,640 --> 00:33:29,440
Speaker 2: they're actually just owned by a handful of companies, be

562
00:33:29,560 --> 00:33:33,440
Speaker 2: it for diapers or laundry detergent or snacks. And the

563
00:33:33,520 --> 00:33:37,160
Speaker 2: costs of this are really severe. I mean, Americans pay more,

564
00:33:37,920 --> 00:33:42,040
Speaker 2: wages are lower, small and independent businesses can't compete on

565
00:33:42,080 --> 00:33:45,560
Speaker 2: a level playing field. And yet, at least a decade ago,

566
00:33:45,640 --> 00:33:48,440
Speaker 2: it seemed like something that was really fringe and marginal

567
00:33:48,440 --> 00:33:51,120
Speaker 2: to the public conversation. And so I got really excited

568
00:33:51,120 --> 00:33:55,240
Speaker 2: about the possibility of trying to reinvigorate our nation's anti

569
00:33:55,320 --> 00:33:57,720
Speaker 2: monopoly laws. And that's kind of what led me on

570
00:33:57,760 --> 00:33:58,200
Speaker 2: this work.

571
00:33:58,960 --> 00:34:01,160
Speaker 1: One of the ways that I try to provide optimism

572
00:34:01,240 --> 00:34:04,200
Speaker 1: when I do my talks and explaining the current era

573
00:34:04,720 --> 00:34:06,760
Speaker 1: is I always ground it in, hey, this is kind

574
00:34:06,800 --> 00:34:09,400
Speaker 1: of familiar. And if you look at our politics today,

575
00:34:09,640 --> 00:34:11,520
Speaker 1: if you look at sort of the issue of income

576
00:34:11,600 --> 00:34:14,760
Speaker 1: and equality today, our polarization today, it's very very similar

577
00:34:14,800 --> 00:34:17,319
Speaker 1: to the late nineteenth century, early twentieth century. Right, you

578
00:34:17,360 --> 00:34:20,200
Speaker 1: have the big titans of industry, we have the tech

579
00:34:20,200 --> 00:34:24,239
Speaker 1: brologarchs today, you have you know, you have this sort

580
00:34:24,239 --> 00:34:27,640
Speaker 1: of you know, we had a rise of nativism back

581
00:34:27,680 --> 00:34:31,480
Speaker 1: then that seems to be coming back. Obviously, there's concern

582
00:34:31,520 --> 00:34:33,800
Speaker 1: as we transition. Back then it was a grand economy

583
00:34:33,840 --> 00:34:36,759
Speaker 1: to an industrial economy. Now we're transitioning from an industrial

584
00:34:36,760 --> 00:34:39,520
Speaker 1: economy to do whatever we're going to call us right,

585
00:34:39,560 --> 00:34:41,760
Speaker 1: we still haven't figured it out. Is it a service economy,

586
00:34:41,840 --> 00:34:44,239
Speaker 1: is it a tech economy? However we want to call it,

587
00:34:44,840 --> 00:34:49,799
Speaker 1: And with it will come over time more people noticing, Hey,

588
00:34:49,800 --> 00:34:55,719
Speaker 1: wait a minute, something's off here. Looking at that historical comparison,

589
00:34:58,160 --> 00:35:00,480
Speaker 1: he said, play professor for me. We're am I right,

590
00:35:00,520 --> 00:35:02,040
Speaker 1: and where do you think I'm a little off base

591
00:35:02,200 --> 00:35:02,960
Speaker 1: on a comparison.

592
00:35:03,239 --> 00:35:05,640
Speaker 2: I'm so glad you noted that, because you're right. The

593
00:35:05,840 --> 00:35:12,000
Speaker 2: historical parallels are incredibly striking. It was the Industrial Revolution

594
00:35:12,360 --> 00:35:16,440
Speaker 2: that delivered so many advances for Americans, but also allowed

595
00:35:16,719 --> 00:35:20,680
Speaker 2: a very small number of companies and individuals to concentrate

596
00:35:20,800 --> 00:35:24,640
Speaker 2: a tremendous amount of power. And it was the ability

597
00:35:24,680 --> 00:35:28,080
Speaker 2: of these monopolists and these industrial trusts to abuse that

598
00:35:28,239 --> 00:35:32,840
Speaker 2: power that set in motion of movement anti monopoly movement

599
00:35:32,960 --> 00:35:35,799
Speaker 2: to make sure that government had the tools and the

600
00:35:35,840 --> 00:35:39,720
Speaker 2: authority to check corporate abuse and to try to create

601
00:35:39,760 --> 00:35:43,759
Speaker 2: an economy that's really delivering fairness for everyday people. And

602
00:35:43,800 --> 00:35:47,240
Speaker 2: I think you know, at the FTC, I was able

603
00:35:47,280 --> 00:35:49,880
Speaker 2: to travel the country and meet with a lot of

604
00:35:49,920 --> 00:35:53,800
Speaker 2: communities and try to understand what are the economic points

605
00:35:53,800 --> 00:35:57,520
Speaker 2: that people are facing, and so many of the daily challenges,

606
00:35:57,960 --> 00:36:01,839
Speaker 2: be it, you know, the inability to afford your medicines,

607
00:36:02,160 --> 00:36:06,120
Speaker 2: having to ration things like insulin, to not being able

608
00:36:06,120 --> 00:36:09,600
Speaker 2: to afford your groceries, to having another job offer but

609
00:36:09,719 --> 00:36:12,360
Speaker 2: not being able to switch because you have a noncompete,

610
00:36:12,400 --> 00:36:16,040
Speaker 2: to you know, being abused by your corporate landlord. I mean,

611
00:36:16,120 --> 00:36:18,799
Speaker 2: so many of the day to day pain points that

612
00:36:18,880 --> 00:36:22,399
Speaker 2: are really squeezing Americans and making them feel like they're

613
00:36:22,400 --> 00:36:24,879
Speaker 2: not getting a fair shake no matter how how hard

614
00:36:24,880 --> 00:36:27,200
Speaker 2: they're work than not able to get ahead. I think

615
00:36:27,280 --> 00:36:30,239
Speaker 2: a lot of that economic anxiety is very ripe and

616
00:36:30,320 --> 00:36:32,480
Speaker 2: not all too different from what people were facing a

617
00:36:32,600 --> 00:36:33,160
Speaker 2: century ago.

618
00:36:33,840 --> 00:36:35,680
Speaker 1: I'll be honest, I hear I've heard a few of

619
00:36:35,719 --> 00:36:37,359
Speaker 1: the phrases and words I feel like, and I feel

620
00:36:37,360 --> 00:36:40,640
Speaker 1: like when we all talk about these things, the famous

621
00:36:40,640 --> 00:36:44,080
Speaker 1: Teddy Roosevelt speech, and also otomy right like, I can

622
00:36:44,120 --> 00:36:46,359
Speaker 1: sort of hear some of that language just known and

623
00:36:46,360 --> 00:36:51,239
Speaker 1: what you were talking about. I guess the question, you know,

624
00:36:51,360 --> 00:36:53,040
Speaker 1: one of the things that strikes me about hearing you.

625
00:36:53,239 --> 00:36:55,040
Speaker 1: The way you talk about this is as we have

626
00:36:55,120 --> 00:36:58,719
Speaker 1: this debate on the left about capitalism versus you know,

627
00:36:58,840 --> 00:37:01,360
Speaker 1: is it are we in late today capitalism? Is it failing?

628
00:37:01,760 --> 00:37:06,319
Speaker 1: In some ways you're articulating that, hey, if capital you know,

629
00:37:06,440 --> 00:37:13,960
Speaker 1: capitalism in its purest or free market form should be uh,

630
00:37:14,280 --> 00:37:18,040
Speaker 1: should be egalitarian of sorts. And in some ways we've

631
00:37:18,840 --> 00:37:22,440
Speaker 1: we're perverting capitalism with this consolidation of power. It's not

632
00:37:23,000 --> 00:37:25,839
Speaker 1: that isn't capitalism, right? I mean, it's like I always

633
00:37:25,920 --> 00:37:29,480
Speaker 1: joke the NFL is one of the great socialistic enterprises

634
00:37:29,520 --> 00:37:32,080
Speaker 1: that exists, right, it is not. The teams do not

635
00:37:32,120 --> 00:37:34,600
Speaker 1: compete against each other, right, They share all of their

636
00:37:34,640 --> 00:37:37,560
Speaker 1: revenues equally, and they have marginal ways that they get

637
00:37:37,600 --> 00:37:43,920
Speaker 1: to do this. Do you count yourself as a sort

638
00:37:43,960 --> 00:37:46,440
Speaker 1: of in some ways a pure capitalist who just thinks

639
00:37:46,440 --> 00:37:47,560
Speaker 1: the rules need to be fair.

640
00:37:48,960 --> 00:37:52,480
Speaker 2: I mean, we absolutely need the rules to be fair.

641
00:37:52,719 --> 00:37:55,360
Speaker 2: And one of the key principles that we've used to

642
00:37:55,400 --> 00:37:59,120
Speaker 2: structure our economy is this idea of competition, right, the

643
00:37:59,200 --> 00:38:02,040
Speaker 2: idea that we want to have markets where if you

644
00:38:02,160 --> 00:38:05,200
Speaker 2: have a good idea, if you have the talent to

645
00:38:05,280 --> 00:38:07,319
Speaker 2: kind of bring a new idea to market, bring a

646
00:38:07,320 --> 00:38:09,800
Speaker 2: new business to market. You should be able to compete

647
00:38:09,800 --> 00:38:12,000
Speaker 2: on a level playing field, right, And so much of

648
00:38:12,040 --> 00:38:15,839
Speaker 2: the innovation, the breakthrough advances in our country, be it

649
00:38:15,880 --> 00:38:19,480
Speaker 2: in Silicon Valley, be it in areas like medicines have

650
00:38:19,600 --> 00:38:22,160
Speaker 2: come from upstarts, right, from somebody with a good thing

651
00:38:22,440 --> 00:38:25,600
Speaker 2: being able to fairly compete. And you're absolutely right that

652
00:38:25,719 --> 00:38:29,120
Speaker 2: as our markets become more and more dominated by smaller

653
00:38:29,160 --> 00:38:33,000
Speaker 2: and smaller number of companies, and those monopolies abuse their

654
00:38:33,120 --> 00:38:36,600
Speaker 2: power to squash out their arrivals to kind of rig

655
00:38:36,640 --> 00:38:40,680
Speaker 2: the playing field, we all lose out right. People. People

656
00:38:40,719 --> 00:38:44,000
Speaker 2: feel like it's not fair, and materially the consequences and

657
00:38:44,040 --> 00:38:47,560
Speaker 2: the outcomes are worse for us as an economy.

658
00:38:48,000 --> 00:38:50,279
Speaker 1: Some of the places where I think that there is

659
00:38:50,320 --> 00:38:54,680
Speaker 1: a left right convergence on agreement that the government needs

660
00:38:54,680 --> 00:38:58,000
Speaker 1: to do something is the role of the tech big

661
00:38:58,080 --> 00:39:01,200
Speaker 1: tech companies. Right. I'm going to ask from a very

662
00:39:01,200 --> 00:39:05,200
Speaker 1: selfish point of view, which is media. I look at

663
00:39:05,320 --> 00:39:08,560
Speaker 1: the issue of distribution and we in media, and I

664
00:39:08,560 --> 00:39:12,560
Speaker 1: don't care where you are these days, whether you're at CBSNBC, ABC,

665
00:39:12,719 --> 00:39:17,520
Speaker 1: whether you're an independent substacker or somewhere in between. You

666
00:39:17,640 --> 00:39:21,880
Speaker 1: do not control your distribution. Distribution is in the hands

667
00:39:21,960 --> 00:39:26,160
Speaker 1: of some a handful of tech companies who can dial

668
00:39:26,239 --> 00:39:29,640
Speaker 1: up or dial down the algorithms, and there is no

669
00:39:29,719 --> 00:39:34,719
Speaker 1: transparency and how it works and how it does walk

670
00:39:34,800 --> 00:39:37,920
Speaker 1: me through the difficulties. It is for THETC to play

671
00:39:37,960 --> 00:39:40,440
Speaker 1: a role here in trying to because I just I

672
00:39:40,719 --> 00:39:43,600
Speaker 1: think you've been I think you tried. I think you're trying.

673
00:39:43,800 --> 00:39:46,520
Speaker 1: I think there's some form of this of your successor

674
00:39:47,200 --> 00:39:51,200
Speaker 1: at least keeping some of these cases going. But is

675
00:39:52,239 --> 00:39:53,880
Speaker 1: in my great fear is that we're going to get

676
00:39:53,920 --> 00:39:58,359
Speaker 1: resolution and it'll be obsolete tech that we finally were

677
00:39:58,400 --> 00:40:01,720
Speaker 1: able to you know, we're finally able to resolve some issues,

678
00:40:01,760 --> 00:40:06,480
Speaker 1: but it's no longer the prominent thing. Meanwhile, this consolidation

679
00:40:06,600 --> 00:40:09,400
Speaker 1: of power has destroyed the entire media ecosystem.

680
00:40:10,880 --> 00:40:15,879
Speaker 2: It's a very valid fear, and candidly, I think enforcers

681
00:40:16,200 --> 00:40:20,680
Speaker 2: and policymakers in DC were generally slow to kind of

682
00:40:20,760 --> 00:40:24,799
Speaker 2: recognize the enormous problem of tech consolidation. Right in the

683
00:40:24,800 --> 00:40:28,680
Speaker 2: early two thousands, there was almost this like religious zeal

684
00:40:28,920 --> 00:40:31,839
Speaker 2: that these tech companies were spreading this idea that there

685
00:40:31,840 --> 00:40:36,080
Speaker 2: were these revolutionary companies that were just going to be

686
00:40:36,280 --> 00:40:39,560
Speaker 2: you know, really fantastic for people. And there was almost

687
00:40:39,719 --> 00:40:43,960
Speaker 2: like this you know, move fast and break things type mentality,

688
00:40:44,440 --> 00:40:47,080
Speaker 2: and there was a sense that these markets moved so

689
00:40:47,239 --> 00:40:50,040
Speaker 2: quickly that if anything, it's better to get out of

690
00:40:50,040 --> 00:40:52,359
Speaker 2: the way, that the government should be a stands off

691
00:40:52,400 --> 00:40:55,120
Speaker 2: as possible. And I think what we've seen is that

692
00:40:55,160 --> 00:40:58,200
Speaker 2: there were enormous costs to that. Right, we now have

693
00:40:58,960 --> 00:41:02,600
Speaker 2: just a handful of companies that are controlling key arteries

694
00:41:02,960 --> 00:41:07,560
Speaker 2: of commerce, key arteries of communication, and that functionally means

695
00:41:07,640 --> 00:41:10,759
Speaker 2: that these companies are getting to call the shots on

696
00:41:11,040 --> 00:41:14,719
Speaker 2: slots of business activity. Right. You noted, they're getting to

697
00:41:14,760 --> 00:41:18,000
Speaker 2: effectively call the shots on what content gets heard or

698
00:41:18,040 --> 00:41:22,439
Speaker 2: seen with no transparency and no accountability, right because there's

699
00:41:22,440 --> 00:41:25,560
Speaker 2: no competition in the market. If you don't like what

700
00:41:25,600 --> 00:41:28,680
Speaker 2: a Google algorithm is doing, you don't really have that

701
00:41:28,840 --> 00:41:32,200
Speaker 2: much choice. And that's what was so eye opening for

702
00:41:32,239 --> 00:41:37,040
Speaker 2: me is that there were actually thousands upon thousands of

703
00:41:37,160 --> 00:41:42,440
Speaker 2: businesses that were enormously alarmed and disturbed about the power

704
00:41:42,480 --> 00:41:46,200
Speaker 2: that these tech companies had accumulated because they could only

705
00:41:46,320 --> 00:41:51,000
Speaker 2: their access to customers was entirely dependent on the whims

706
00:41:51,040 --> 00:41:53,120
Speaker 2: of an Amazon or a Google, and I would have

707
00:41:53,160 --> 00:41:56,200
Speaker 2: companies tell me, you know, I woke up today for

708
00:41:56,239 --> 00:41:58,799
Speaker 2: some reason, on Amazon, I went from page one to

709
00:41:58,880 --> 00:42:02,040
Speaker 2: page seven, or on Google from page one page seven.

710
00:42:02,560 --> 00:42:04,760
Speaker 2: And if this does I don't know why, nothing changed

711
00:42:04,800 --> 00:42:07,360
Speaker 2: on my end, But if this doesn't get fixed, my

712
00:42:07,440 --> 00:42:10,680
Speaker 2: business is going to go bankrupt. And you know, I

713
00:42:10,719 --> 00:42:14,760
Speaker 2: remember there was a business who was quoted saying Google

714
00:42:14,800 --> 00:42:17,279
Speaker 2: has more power than the government. Right, the government can

715
00:42:17,360 --> 00:42:20,520
Speaker 2: tax me, but if changes an algorithm, my business is

716
00:42:20,560 --> 00:42:23,320
Speaker 2: going to go under. And so I think people started

717
00:42:23,320 --> 00:42:26,520
Speaker 2: to realize just the enormous power these companies have. If

718
00:42:26,520 --> 00:42:30,800
Speaker 2: it's not how to account can just be extremely abusive.

719
00:42:31,040 --> 00:42:32,799
Speaker 1: Let's good to something. How did we get to the

720
00:42:32,840 --> 00:42:39,600
Speaker 1: point where I have to be I have to consent

721
00:42:40,680 --> 00:42:45,000
Speaker 1: for my data to use an app versus the app

722
00:42:45,320 --> 00:42:48,080
Speaker 1: having to consent to me to get data. Do you

723
00:42:48,120 --> 00:42:53,400
Speaker 1: see what I mean? Like we've totally reversed the permission structure,

724
00:42:53,800 --> 00:42:58,960
Speaker 1: which is I basically I'm being coersed to give up

725
00:42:59,000 --> 00:43:02,280
Speaker 1: something to use a product, right to use a Google

726
00:43:02,280 --> 00:43:06,920
Speaker 1: apport simply to update a product I've already purchased. But

727
00:43:07,000 --> 00:43:10,400
Speaker 1: if I want a free update, I've got to you know,

728
00:43:10,520 --> 00:43:12,600
Speaker 1: instead of you know, I got to give something in return,

729
00:43:12,920 --> 00:43:14,880
Speaker 1: And there's no alternative, like I could say, Hey, I

730
00:43:14,920 --> 00:43:17,399
Speaker 1: don't want to give you this data? Can I buy it? Right?

731
00:43:17,400 --> 00:43:20,120
Speaker 1: They're not even they're not even giving me access to

732
00:43:20,160 --> 00:43:25,239
Speaker 1: this updated version of the apps. How did we get

733
00:43:25,280 --> 00:43:28,800
Speaker 1: here where we're they're not asking us permission, but essentially

734
00:43:28,800 --> 00:43:29,640
Speaker 1: we're being coerced.

735
00:43:30,800 --> 00:43:35,080
Speaker 2: It's a really important question. And a key moment was

736
00:43:35,440 --> 00:43:39,520
Speaker 2: in the early two thousands where some of these businesses

737
00:43:39,840 --> 00:43:45,200
Speaker 2: started adopting business models that were premised effectively on surveiling

738
00:43:45,280 --> 00:43:47,120
Speaker 2: you and harvesting all of your data.

739
00:43:47,520 --> 00:43:47,680
Speaker 1: Right.

740
00:43:47,719 --> 00:43:51,560
Speaker 2: Companies like Google, Facebook decided they were going to monetize

741
00:43:51,680 --> 00:43:55,880
Speaker 2: their companies not by charging customers in terms of dollars,

742
00:43:56,280 --> 00:43:59,640
Speaker 2: but instead by collecting data on them and then selling

743
00:43:59,640 --> 00:44:02,840
Speaker 2: that to advertisers. And what that did from a business

744
00:44:02,880 --> 00:44:07,160
Speaker 2: perspective was create an incentive to collect as much information

745
00:44:07,400 --> 00:44:10,480
Speaker 2: on you as possible. Right, And so they're collecting it

746
00:44:10,520 --> 00:44:12,960
Speaker 2: when you're on their website, but they're also collecting it

747
00:44:13,000 --> 00:44:17,440
Speaker 2: across the internet. Now it can be combined with data

748
00:44:17,440 --> 00:44:21,959
Speaker 2: collected on your phone, including your precise geolocation, and there's

749
00:44:22,040 --> 00:44:25,640
Speaker 2: just a huge business incentive because that's how they make money.

750
00:44:26,239 --> 00:44:28,920
Speaker 2: And it's really striking because you know, America has a

751
00:44:29,280 --> 00:44:33,799
Speaker 2: long tradition of being very skeptical of government surveillance, but

752
00:44:33,880 --> 00:44:37,600
Speaker 2: we are now increasingly being surveilled by these private companies

753
00:44:38,280 --> 00:44:41,400
Speaker 2: and we don't know what's happening with that data. At

754
00:44:41,400 --> 00:44:44,799
Speaker 2: the FTP sometimes found it was actually being sold just

755
00:44:44,840 --> 00:44:47,400
Speaker 2: to the highest bidder, even if that meant selling it

756
00:44:47,440 --> 00:44:51,080
Speaker 2: to foreign adversaries, and sometimes it is sold to the

757
00:44:51,080 --> 00:44:53,680
Speaker 2: government or used by the government, and so it seems

758
00:44:53,719 --> 00:44:57,880
Speaker 2: like there's this whole workaround. And you know, companies have

759
00:44:57,960 --> 00:45:01,560
Speaker 2: adopted this notice and consent where they think if they

760
00:45:01,640 --> 00:45:04,640
Speaker 2: just present you this long terms of service and you

761
00:45:05,000 --> 00:45:07,480
Speaker 2: agree that that means you're consenting. But we all know

762
00:45:07,600 --> 00:45:10,480
Speaker 2: that's a fiction. And as you noted, we have to

763
00:45:10,560 --> 00:45:13,120
Speaker 2: use these services to navigate day to day life, and

764
00:45:13,200 --> 00:45:14,800
Speaker 2: so it does feel like coercion.

765
00:45:15,960 --> 00:45:21,319
Speaker 1: Well, the South Park Boys probably have the best illustration

766
00:45:21,480 --> 00:45:24,600
Speaker 1: of what happens with the agreement. They did a whole episode.

767
00:45:24,640 --> 00:45:26,279
Speaker 1: I have no idea how familiar with that, but this

768
00:45:26,400 --> 00:45:28,680
Speaker 1: is I recommend it. They did this like a decade ago,

769
00:45:29,440 --> 00:45:31,960
Speaker 1: sort of mocking the automate. What do you mean you

770
00:45:31,960 --> 00:45:34,200
Speaker 1: didn't read your permits and services and now one of

771
00:45:34,200 --> 00:45:37,400
Speaker 1: the boys ends up being a human experiment for Apple

772
00:45:37,480 --> 00:45:39,920
Speaker 1: to become a human centipede iPad or something like that.

773
00:45:40,200 --> 00:45:43,160
Speaker 1: I mean, it's absurd, but it was really well, it

774
00:45:43,200 --> 00:45:48,040
Speaker 1: was satire done exactly to point out this absurdity of

775
00:45:48,200 --> 00:45:51,000
Speaker 1: terms and conditions and the fact that nobody actually reads

776
00:45:51,000 --> 00:45:54,040
Speaker 1: it and you have no idea what you've just consented to,

777
00:45:54,840 --> 00:45:57,200
Speaker 1: and this idea that oh it's on you. Oh come

778
00:45:57,239 --> 00:46:04,520
Speaker 1: on like that. That's not where, that's not realistic. What

779
00:46:05,160 --> 00:46:10,520
Speaker 1: let's this you just talked about the hands off approach

780
00:46:11,400 --> 00:46:15,000
Speaker 1: that essentially government decided to take on the tech industry

781
00:46:15,200 --> 00:46:17,880
Speaker 1: in the first two decades of the century. Here we

782
00:46:17,920 --> 00:46:21,200
Speaker 1: are at AI at this moment, and that is exactly

783
00:46:21,239 --> 00:46:25,839
Speaker 1: the same conversation all these AI had, don't regulate us, right,

784
00:46:25,880 --> 00:46:28,360
Speaker 1: And we just saw that bill there was going to

785
00:46:28,360 --> 00:46:31,359
Speaker 1: be an attempt to put a moratorium on state based

786
00:46:31,400 --> 00:46:34,120
Speaker 1: regulations for ten years. As soon as it popped up

787
00:46:34,239 --> 00:46:37,360
Speaker 1: there there were there were at least a few people

788
00:46:37,400 --> 00:46:40,680
Speaker 1: howling about it, and they got stripped out. A reminder

789
00:46:40,719 --> 00:46:44,080
Speaker 1: sometimes transparency is still the best disinfected that you have

790
00:46:44,239 --> 00:46:48,279
Speaker 1: on sometimes on bad policy, but it certainly looks like

791
00:46:48,320 --> 00:46:50,400
Speaker 1: we're about to do the same make the same mistakes

792
00:46:50,400 --> 00:46:53,360
Speaker 1: with AI that we made with social media.

793
00:46:53,680 --> 00:46:56,440
Speaker 2: It's a key risk. And you know, I think we've

794
00:46:56,480 --> 00:47:00,719
Speaker 2: seen some interesting dynamics with AI where some times these

795
00:47:00,760 --> 00:47:04,920
Speaker 2: moments of you know, technological advances and break through advances

796
00:47:05,360 --> 00:47:08,120
Speaker 2: are actually a moment where the market opens up and

797
00:47:08,160 --> 00:47:11,680
Speaker 2: you get new players. And so it was actually you know,

798
00:47:11,800 --> 00:47:15,799
Speaker 2: Microsoft being disciplined by anti trusts that allowed thes and

799
00:47:15,800 --> 00:47:18,040
Speaker 2: the facebooks and the Googles to come in and and

800
00:47:18,160 --> 00:47:21,480
Speaker 2: youer more competition. The risk we're seeing now is that

801
00:47:21,560 --> 00:47:27,680
Speaker 2: this technological revolution will instead allow the existing giants to

802
00:47:27,880 --> 00:47:30,240
Speaker 2: just expand and double down on their power.

803
00:47:30,920 --> 00:47:33,600
Speaker 1: Well let's talk about that real quick, because who could

804
00:47:33,600 --> 00:47:35,640
Speaker 1: start up an AI company on their own? Right now?

805
00:47:36,000 --> 00:47:38,600
Speaker 1: You need to have so much money to get power,

806
00:47:39,000 --> 00:47:41,759
Speaker 1: so much money to get the computer, you know, actual electricity,

807
00:47:42,520 --> 00:47:46,520
Speaker 1: computing power. The barrier to entry is super high. This

808
00:47:46,560 --> 00:47:49,239
Speaker 1: is not so the only companies that can afford it

809
00:47:49,239 --> 00:47:51,480
Speaker 1: are the companies that have already the already have the

810
00:47:51,520 --> 00:47:52,800
Speaker 1: power and the resources.

811
00:47:52,880 --> 00:47:56,720
Speaker 2: Right, That's exactly right. Kind of every step of the way,

812
00:47:57,239 --> 00:48:00,280
Speaker 2: you're basically dependent on the whims of these existing giant

813
00:48:00,120 --> 00:48:04,759
Speaker 2: And I think the other really incredible component here is

814
00:48:04,800 --> 00:48:07,920
Speaker 2: that a lot of these models are being trained on

815
00:48:08,000 --> 00:48:10,960
Speaker 2: people's data. Right, we were just talking about consent and

816
00:48:11,000 --> 00:48:13,120
Speaker 2: the lack of consent. I mean, when I was at

817
00:48:13,120 --> 00:48:18,680
Speaker 2: the FTC, we were talking to creators, writers, graphic designers

818
00:48:19,000 --> 00:48:21,680
Speaker 2: who said, I just woke up one day and my

819
00:48:21,760 --> 00:48:24,880
Speaker 2: life's work had been ingested by this model that is

820
00:48:24,920 --> 00:48:27,839
Speaker 2: now spitting out stuff that is competing with me, and

821
00:48:27,880 --> 00:48:30,000
Speaker 2: it was trained on me, and nobody asked me, and

822
00:48:30,000 --> 00:48:33,600
Speaker 2: nobody paid me. How is that fit? Right? And so

823
00:48:33,680 --> 00:48:37,360
Speaker 2: we've already seen what some of people would call theft

824
00:48:37,400 --> 00:48:39,640
Speaker 2: in terms of just how much of that information has

825
00:48:39,680 --> 00:48:43,839
Speaker 2: already been ingested and monetized without any consent or compensation.

826
00:48:44,440 --> 00:48:47,400
Speaker 2: I think the other potential abusive practice we could see

827
00:48:47,520 --> 00:48:51,920
Speaker 2: is this idea of surveillance pricing. We're not only is

828
00:48:51,960 --> 00:48:54,480
Speaker 2: your data being collected on you, but then it is

829
00:48:54,520 --> 00:48:59,000
Speaker 2: being used against you to price as much as you

830
00:48:59,080 --> 00:49:01,960
Speaker 2: will pay. So imagine you had a death in the

831
00:49:02,000 --> 00:49:04,400
Speaker 2: family and you got an email notice about where the

832
00:49:04,480 --> 00:49:07,000
Speaker 2: services are going to be. You go to buy a

833
00:49:07,000 --> 00:49:10,000
Speaker 2: plane ticket and the airline company knows you are trying

834
00:49:10,040 --> 00:49:13,279
Speaker 2: to get to a funeral, it's an emergency, and maybe

835
00:49:13,280 --> 00:49:16,120
Speaker 2: they'll overcharge you, right, And I think that's going to

836
00:49:16,160 --> 00:49:18,880
Speaker 2: be one of the next frontiers of potential abuse that

837
00:49:18,880 --> 00:49:20,160
Speaker 2: we have to be on guard for.

838
00:49:20,960 --> 00:49:25,839
Speaker 1: Now, this is something you know. Is the FTC set

839
00:49:25,920 --> 00:49:29,120
Speaker 1: up to be proactive or is the entire premise of

840
00:49:29,160 --> 00:49:34,160
Speaker 1: the agency or reactive agency? Right? And I think I

841
00:49:34,200 --> 00:49:36,600
Speaker 1: know the answer to that question, but I feel like

842
00:49:36,640 --> 00:49:38,480
Speaker 1: that's the inherent flaw in the FTC.

843
00:49:38,760 --> 00:49:41,759
Speaker 2: Now, well, it's a good question, and I mean, I

844
00:49:41,760 --> 00:49:44,400
Speaker 2: think what it sounds like what you're suggesting by reactive

845
00:49:44,520 --> 00:49:47,520
Speaker 2: is if the agency is primarily bringing lawsuits, is it

846
00:49:47,600 --> 00:49:50,680
Speaker 2: bringing lawsuits effectively after the fact, once it's too late

847
00:49:51,280 --> 00:49:54,319
Speaker 2: you're going to Yes, No, you're You're right that one

848
00:49:54,400 --> 00:49:57,839
Speaker 2: of the main things the agency does is bring lawsuits

849
00:49:58,320 --> 00:50:01,200
Speaker 2: to kind of go after kind of conduct that's already happened.

850
00:50:01,719 --> 00:50:04,279
Speaker 2: We did also do making and so we can get

851
00:50:04,320 --> 00:50:07,080
Speaker 2: through rules like one of the ones we pushed through

852
00:50:07,280 --> 00:50:11,120
Speaker 2: was a ban on noncompete clauses. These are clauses that

853
00:50:11,280 --> 00:50:15,280
Speaker 2: basically block you from taking a job editor or starting

854
00:50:15,280 --> 00:50:16,120
Speaker 2: your own business.

855
00:50:16,440 --> 00:50:18,440
Speaker 1: It's a huge thing in the media business. It's a

856
00:50:18,520 --> 00:50:22,239
Speaker 1: huge thing in me. Now there's coercion ways to do it.

857
00:50:22,320 --> 00:50:24,719
Speaker 1: You know, they can pay you to be you know,

858
00:50:24,760 --> 00:50:27,520
Speaker 1: to try to try to do that and compensated. And

859
00:50:27,920 --> 00:50:34,080
Speaker 1: is that still legal or noncompete they still compensate. Yeah, no,

860
00:50:34,200 --> 00:50:34,760
Speaker 1: I think if.

861
00:50:34,600 --> 00:50:37,239
Speaker 2: You're compensated, that's a very different situation.

862
00:50:37,600 --> 00:50:40,160
Speaker 1: Believe, not compete without compensation.

863
00:50:40,120 --> 00:50:44,319
Speaker 2: Compensation, and not even for executives in the boardroom, but

864
00:50:44,360 --> 00:50:48,239
Speaker 2: for security guards and janitors and fast food workers. I mean,

865
00:50:48,480 --> 00:50:50,880
Speaker 2: when we were doing this work at the FTC, we

866
00:50:50,960 --> 00:50:54,520
Speaker 2: heard from a bartender in Florida who was being harassed

867
00:50:54,520 --> 00:50:56,879
Speaker 2: at her job. She went to go find a job

868
00:50:56,920 --> 00:50:59,959
Speaker 2: at a different restaurant, and once she was going to start,

869
00:51:00,280 --> 00:51:03,000
Speaker 2: she got hit with a lawsuit for tens of thousands

870
00:51:03,040 --> 00:51:05,040
Speaker 2: of dollars because she had a non compete and her

871
00:51:05,080 --> 00:51:07,799
Speaker 2: original restaurant was trying to block it. I mean, they're

872
00:51:07,840 --> 00:51:11,399
Speaker 2: just such absurd and horrifying stories about how these non

873
00:51:11,440 --> 00:51:14,279
Speaker 2: competes are abused. So we've got put through a rule

874
00:51:14,360 --> 00:51:17,399
Speaker 2: to ban them in the vast majority of contexts, it's

875
00:51:17,440 --> 00:51:21,440
Speaker 2: currently being litigated pushed back against. I think the biggest

876
00:51:21,640 --> 00:51:25,920
Speaker 2: challenge for the FTC candidly is its size. I mean,

877
00:51:25,920 --> 00:51:30,240
Speaker 2: this is a tiny agency relative to its mission and mandate.

878
00:51:30,920 --> 00:51:35,480
Speaker 2: It oversees economic activity across the vast majority of the

879
00:51:35,560 --> 00:51:39,279
Speaker 2: US economy, and at its height when I was there

880
00:51:39,719 --> 00:51:44,000
Speaker 2: was around thirteen hundred people. Now smaller, we've seen, you know,

881
00:51:44,239 --> 00:51:47,120
Speaker 2: a brain drain, a lot of attrition, people kind of

882
00:51:47,160 --> 00:51:51,200
Speaker 2: trying to flee. And it's tough. You know, we've heard

883
00:51:51,200 --> 00:51:54,600
Speaker 2: about DOGE cuts and the agency shrinking further, and so

884
00:51:54,760 --> 00:51:57,040
Speaker 2: I think that's a challenge.

885
00:51:57,239 --> 00:52:00,319
Speaker 1: And yet there is you know, there is a heart

886
00:52:00,400 --> 00:52:04,600
Speaker 1: of of the populist right that very much. You know,

887
00:52:04,680 --> 00:52:08,319
Speaker 1: we're cheering you on when it came to Facebook and that,

888
00:52:08,560 --> 00:52:11,239
Speaker 1: and cheering you on when it came to Amazon. And

889
00:52:11,320 --> 00:52:15,320
Speaker 1: yet it doesn't seem as if that is it doesn't

890
00:52:15,360 --> 00:52:19,360
Speaker 1: seem like that part of that base as a voice

891
00:52:19,360 --> 00:52:22,360
Speaker 1: in this current administration. That's what it's been more lip service.

892
00:52:22,920 --> 00:52:26,480
Speaker 2: It's such an interesting question, and you know sometimes it

893
00:52:26,600 --> 00:52:29,480
Speaker 2: changes week by week, but you're right, it does seem

894
00:52:29,560 --> 00:52:32,439
Speaker 2: like overall there has been a drift right, if there's

895
00:52:32,440 --> 00:52:36,040
Speaker 2: a fight between the kind of populist wing and the

896
00:52:36,080 --> 00:52:39,440
Speaker 2: corporateest wing. It does seem like more and more the

897
00:52:39,520 --> 00:52:42,440
Speaker 2: kind of corporatist wing is winning out. I mean, we

898
00:52:42,480 --> 00:52:46,000
Speaker 2: do see some pushback and kind of efforts to grapple

899
00:52:46,040 --> 00:52:49,600
Speaker 2: through this, you know, at the FTC. I think you're

900
00:52:49,680 --> 00:52:53,120
Speaker 2: right that there was kind of support among Republican members

901
00:52:53,120 --> 00:52:57,160
Speaker 2: of Congress, but there's almost support at a grassroots level, right,

902
00:52:57,200 --> 00:52:58,040
Speaker 2: I mean, I would get.

903
00:52:58,280 --> 00:53:00,640
Speaker 1: More support on the grassroots level, frankly, right, Yeah, I

904
00:53:00,680 --> 00:53:01,239
Speaker 1: think that's right.

905
00:53:01,280 --> 00:53:04,279
Speaker 2: I would get letters from, you know, people saying I'm

906
00:53:04,280 --> 00:53:08,560
Speaker 2: a lifelong Republican, a hardcore free market capitalist, but if

907
00:53:08,560 --> 00:53:11,960
Speaker 2: the FTC bans noncompetes, it'll be the best thing government

908
00:53:12,000 --> 00:53:16,560
Speaker 2: has ever done. I would have Republican business owners coming

909
00:53:16,600 --> 00:53:21,880
Speaker 2: to me nearly in tears, right, independent pharmacists, farmers, saying

910
00:53:22,000 --> 00:53:24,719
Speaker 2: my business is about to go under because of this

911
00:53:25,160 --> 00:53:29,120
Speaker 2: massive middleman that's squeezing me out. And so I think,

912
00:53:29,239 --> 00:53:32,560
Speaker 2: you know, this issue of unchecked corporate power, of monopoly

913
00:53:32,640 --> 00:53:36,439
Speaker 2: abuse has become so acute that it affects every part

914
00:53:36,480 --> 00:53:39,040
Speaker 2: of our country, then there's a lot of support for

915
00:53:39,080 --> 00:53:39,560
Speaker 2: taking it on.

916
00:53:41,040 --> 00:53:45,320
Speaker 1: It sort of in hearing about some of the most

917
00:53:46,000 --> 00:53:50,800
Speaker 1: egregious monopolistic practices, it seems as if it's more egregious,

918
00:53:50,840 --> 00:53:56,160
Speaker 1: the more mature said industry is, So take pharmaceuticals. You

919
00:53:56,200 --> 00:54:00,600
Speaker 1: brought up the independent pharmacy issue versus Frank, you know,

920
00:54:01,080 --> 00:54:03,360
Speaker 1: the two giants, and I guess it's one and a

921
00:54:03,400 --> 00:54:06,279
Speaker 1: half giants, right. I think Walgreens is struggling to keep

922
00:54:06,360 --> 00:54:10,000
Speaker 1: up with CBS. Is it even possible to be an

923
00:54:10,000 --> 00:54:13,440
Speaker 1: independent pharmacist anymore? And is it just that feels like

924
00:54:13,480 --> 00:54:19,960
Speaker 1: an extraordinarily consolidated thing. And what role should the FDC

925
00:54:20,120 --> 00:54:22,879
Speaker 1: have in something like this? On behalf of independent pharmacists.

926
00:54:24,160 --> 00:54:26,239
Speaker 2: So this was a big area of focus for us

927
00:54:26,280 --> 00:54:31,640
Speaker 2: because independent pharmacies, especially in rural area areas, play such

928
00:54:31,640 --> 00:54:33,640
Speaker 2: a critical role. I mean sometimes they are the only

929
00:54:33,719 --> 00:54:38,080
Speaker 2: kind of healthcare provider nearby. And what's been so interesting

930
00:54:38,280 --> 00:54:42,279
Speaker 2: is that communities generally love their independent pharmacists, and these

931
00:54:42,280 --> 00:54:45,080
Speaker 2: independent pharmacists are kind of, you know, offers.

932
00:54:44,840 --> 00:54:48,040
Speaker 1: Kind of like doctors. I mean, look, I'm my my

933
00:54:48,200 --> 00:54:52,600
Speaker 1: grew up in northwest Florida. Pensacola is a pretty mature community.

934
00:54:52,600 --> 00:54:55,319
Speaker 1: But some of the outlier communities where are families from

935
00:54:55,640 --> 00:54:58,480
Speaker 1: very much and there's a you know, small independent pharmacist

936
00:54:58,880 --> 00:55:01,600
Speaker 1: that was like the family called them up right, you know, Hey,

937
00:55:01,680 --> 00:55:03,799
Speaker 1: my kids got a cold. What what should I tell?

938
00:55:03,800 --> 00:55:06,880
Speaker 1: I mean, they treat the pharmacist almost like a doctor.

939
00:55:07,320 --> 00:55:10,959
Speaker 1: That's how important they are, you know. And just see

940
00:55:11,040 --> 00:55:14,200
Speaker 1: I've seen it sook, you know, with an in law

941
00:55:14,239 --> 00:55:17,880
Speaker 1: who was suffering and a prescription ran out on a Saturday.

942
00:55:17,920 --> 00:55:19,560
Speaker 1: They didn't know what else to do, right, and it

943
00:55:20,120 --> 00:55:23,360
Speaker 1: so it really is a community lifeline in these smaller

944
00:55:23,440 --> 00:55:25,279
Speaker 1: and these smaller communities.

945
00:55:25,160 --> 00:55:28,800
Speaker 2: That's right. And a lot of these independent pharmacies are

946
00:55:28,880 --> 00:55:32,239
Speaker 2: being squeezed, not because their communities don't love them and

947
00:55:32,280 --> 00:55:35,560
Speaker 2: benefit from them, but because there are these actors called

948
00:55:35,640 --> 00:55:39,640
Speaker 2: pharmacy benefit managers. There are these kind of middlemen in

949
00:55:39,680 --> 00:55:43,840
Speaker 2: the healthcare system that coordinate between the pharmacy and the

950
00:55:43,840 --> 00:55:46,000
Speaker 2: health insurance and the drug manufacturer.

951
00:55:46,400 --> 00:55:51,040
Speaker 1: Why do they exists? I mean, this is my big question.

952
00:55:51,080 --> 00:55:53,680
Speaker 1: I don't I'm going to I watched a lot of

953
00:55:54,080 --> 00:55:55,520
Speaker 1: you know, if you're living, if you live in the

954
00:55:55,600 --> 00:55:58,719
Speaker 1: DC market, you hear about PBMs. It's the only place

955
00:55:58,760 --> 00:56:01,680
Speaker 1: you hear about it, right, because it's a fight over legislation,

956
00:56:01,760 --> 00:56:03,480
Speaker 1: and they're trying to fight for their existence and all

957
00:56:03,480 --> 00:56:06,399
Speaker 1: of this stuff. And no matter how much I even

958
00:56:06,400 --> 00:56:08,520
Speaker 1: follow the issue, and I like, what the hell are

959
00:56:08,520 --> 00:56:10,879
Speaker 1: these and why do they exist?

960
00:56:11,239 --> 00:56:13,839
Speaker 2: So in theory they came into existence to try to

961
00:56:14,000 --> 00:56:18,600
Speaker 2: make prices lower for people, but there's good evidence that

962
00:56:18,600 --> 00:56:21,440
Speaker 2: they're actually having the opposite effect, right, And so now

963
00:56:21,480 --> 00:56:25,360
Speaker 2: these PBMs have actually vertically integrated with the health insurer.

964
00:56:25,760 --> 00:56:28,640
Speaker 2: Some of them have their own mail order pharmacy, and

965
00:56:28,719 --> 00:56:31,719
Speaker 2: pharmacies will tell us that patients are coming to them

966
00:56:31,760 --> 00:56:34,839
Speaker 2: and saying, Hey, I've been fulfilling my prescription with you

967
00:56:34,920 --> 00:56:37,759
Speaker 2: for years, but I just got this letter from my

968
00:56:37,800 --> 00:56:41,839
Speaker 2: insurance company saying now I can only fulfill this through

969
00:56:41,840 --> 00:56:44,719
Speaker 2: their mail order pharmacy. And guess what. The mail order

970
00:56:44,719 --> 00:56:47,960
Speaker 2: pharmacy is using trucks in the heat, and by the

971
00:56:48,000 --> 00:56:50,000
Speaker 2: time your medicine gets to you, it actually ended up

972
00:56:50,040 --> 00:56:53,640
Speaker 2: getting spoilt. And so they're just all these perversions. The

973
00:56:53,640 --> 00:56:58,560
Speaker 2: PBMs are also responsible for reimbursing the pharmacies. Pharmacies tell

974
00:56:58,600 --> 00:57:02,120
Speaker 2: us they are routinely under reimbursed, and so they're actually

975
00:57:02,320 --> 00:57:06,960
Speaker 2: losing money when they are providing patients with life saving medicines,

976
00:57:07,000 --> 00:57:09,920
Speaker 2: and so it seems like a big, big perversion. We

977
00:57:09,960 --> 00:57:13,480
Speaker 2: investigated this at the FTC. We sued the PBMs for

978
00:57:13,800 --> 00:57:18,040
Speaker 2: practices that we alleged lading drug prices. But there's a

979
00:57:18,080 --> 00:57:19,360
Speaker 2: lot more to be done here.

980
00:57:28,120 --> 00:57:31,200
Speaker 1: Let's talk about the cases that you didn't you weren't

981
00:57:31,200 --> 00:57:33,720
Speaker 1: able to finish, right you, you know, would would have

982
00:57:33,880 --> 00:57:37,479
Speaker 1: liked that more time. And what's going to continue? Where

983
00:57:37,480 --> 00:57:40,640
Speaker 1: are you relieved? Where it looks like the FTC is

984
00:57:40,680 --> 00:57:41,400
Speaker 1: going to stay on this?

985
00:57:43,640 --> 00:57:47,560
Speaker 2: Well, so far we have seen the Facebook litigation continue.

986
00:57:48,040 --> 00:57:51,520
Speaker 2: We s that there was a huge scramble by Mark

987
00:57:51,640 --> 00:57:54,280
Speaker 2: Zuckerberg to try to settle that on the eve of trial.

988
00:57:54,760 --> 00:57:56,960
Speaker 2: They didn't do it. They'll let the trial happen. We're

989
00:57:57,000 --> 00:57:57,640
Speaker 2: waiting to get out.

990
00:57:57,640 --> 00:57:59,640
Speaker 1: It was a cynic. I assumed he was going to

991
00:57:59,640 --> 00:58:03,080
Speaker 1: get it. I'll be honest. I figured somebody would tell

992
00:58:03,120 --> 00:58:04,760
Speaker 1: him what the number was and he'd write the check.

993
00:58:05,640 --> 00:58:08,600
Speaker 1: The fact that it didn't happen was oddly surprising.

994
00:58:10,400 --> 00:58:12,680
Speaker 2: Yeah, it's interesting, and I think we're all going to

995
00:58:12,720 --> 00:58:16,520
Speaker 2: have to be very vigilant about what happens down the line,

996
00:58:17,080 --> 00:58:20,440
Speaker 2: because there is a world in which the FTC wins,

997
00:58:20,880 --> 00:58:22,920
Speaker 2: and then that's another leverage point.

998
00:58:23,000 --> 00:58:24,800
Speaker 1: And is that and they settle anyway?

999
00:58:25,000 --> 00:58:29,480
Speaker 2: Right backed something? And I think that's why a lot

1000
00:58:29,520 --> 00:58:31,440
Speaker 2: of this seems like a double edged short, it just

1001
00:58:31,520 --> 00:58:34,760
Speaker 2: seems like so much willingness by the White House to

1002
00:58:35,000 --> 00:58:39,240
Speaker 2: use law enforcement as a political cudgel to extract favors

1003
00:58:39,360 --> 00:58:43,360
Speaker 2: or kind of punt received enemies, and so the potential

1004
00:58:43,560 --> 00:58:46,560
Speaker 2: corruption of these cases is a big risk to my mind.

1005
00:58:47,120 --> 00:58:50,920
Speaker 2: So far, our lawsuit against Amazon is going forward. Our

1006
00:58:51,000 --> 00:58:54,360
Speaker 2: lawsuit against John Deere is going forward. This is a

1007
00:58:54,400 --> 00:58:58,200
Speaker 2: lawsuit where we alleged Deer was illegally making it very

1008
00:58:58,200 --> 00:59:02,320
Speaker 2: difficult for farmers to fix their own tractors and equipment

1009
00:59:03,920 --> 00:59:06,240
Speaker 2: fixed by a deer dealer, which meant not only was

1010
00:59:06,280 --> 00:59:09,680
Speaker 2: it more expensive, but you had to wait an incredibly

1011
00:59:09,760 --> 00:59:12,880
Speaker 2: long time, and sometimes that would result in farmer's crop

1012
00:59:13,000 --> 00:59:18,400
Speaker 2: getting ruined. So that those litigations are still going forward.

1013
00:59:18,840 --> 00:59:22,640
Speaker 2: We have seen some backtracking on the consumer protection side,

1014
00:59:23,800 --> 00:59:25,880
Speaker 2: which is where we've been very active in terms of

1015
00:59:25,920 --> 00:59:30,480
Speaker 2: taking on these junk fees, requiring that businesses make it

1016
00:59:30,520 --> 00:59:33,600
Speaker 2: as easy to cancel a subscription as it is to sign.

1017
00:59:34,560 --> 00:59:37,240
Speaker 2: A judge just tossed out that rule, and we're going

1018
00:59:37,320 --> 00:59:39,680
Speaker 2: to have to see where the FTC stays strong or

1019
00:59:39,720 --> 00:59:40,240
Speaker 2: backs off.

1020
00:59:41,040 --> 00:59:43,760
Speaker 1: Well, I could, I could, I could go on a

1021
00:59:43,840 --> 00:59:49,360
Speaker 1: number that they went the impossibility when you sign up

1022
00:59:49,400 --> 00:59:53,840
Speaker 1: for something to then cancel it. It is And it

1023
00:59:53,880 --> 00:59:57,480
Speaker 1: doesn't matter whether I'm talking about national season tickets, who

1024
00:59:57,920 --> 01:00:00,480
Speaker 1: like they will literally send an email on a notice

1025
01:00:00,520 --> 01:00:03,000
Speaker 1: but no link, and then they'll like be on the

1026
01:00:03,000 --> 01:00:05,120
Speaker 1: lookout for the link two or three weeks later and

1027
01:00:05,160 --> 01:00:07,440
Speaker 1: they don't ever And that's just them, And this is

1028
01:00:07,680 --> 01:00:09,920
Speaker 1: this is just an example across the board with these

1029
01:00:09,960 --> 01:00:13,000
Speaker 1: subscription services, no matter what it is, right, whether it's

1030
01:00:13,000 --> 01:00:18,000
Speaker 1: a small subscription for for for a magazine or something,

1031
01:00:18,080 --> 01:00:21,400
Speaker 1: or a large one for a streaming service or season

1032
01:00:21,440 --> 01:00:24,680
Speaker 1: tickets or whatever it is, it does seem as if

1033
01:00:25,320 --> 01:00:27,800
Speaker 1: that there is a lot of fast and loose when

1034
01:00:27,800 --> 01:00:31,040
Speaker 1: it comes to these auto renewals, if you will, and

1035
01:00:31,520 --> 01:00:37,640
Speaker 1: that that feels that feels like one of those one

1036
01:00:37,720 --> 01:00:41,240
Speaker 1: of those issues that if the government could find a

1037
01:00:41,280 --> 01:00:44,160
Speaker 1: way to clamp down on it, it would be enormously popular.

1038
01:00:45,240 --> 01:00:49,120
Speaker 2: Yeah, you know, we tried to clamp down on it.

1039
01:00:49,160 --> 01:00:51,680
Speaker 2: I mean, I think the idea that companies shouldn't be

1040
01:00:51,680 --> 01:00:55,320
Speaker 2: able to trap you in subscriptions is as unobjectionable as

1041
01:00:55,320 --> 01:00:58,520
Speaker 2: it comes, frankly, and unfortunately, it's an area where we've

1042
01:00:58,560 --> 01:01:02,400
Speaker 2: seen increasing abuse because more and more businesses are becoming

1043
01:01:02,400 --> 01:01:06,840
Speaker 2: a reliant on subscription based revenues. So even for things

1044
01:01:06,920 --> 01:01:09,560
Speaker 2: like a printer, sometimes you need a subscription for your

1045
01:01:09,600 --> 01:01:10,680
Speaker 2: printer to work.

1046
01:01:10,640 --> 01:01:13,920
Speaker 1: Right, Can I thank you for bringing that up? That

1047
01:01:14,000 --> 01:01:16,680
Speaker 1: drives me bonkers? No, I'm not doing that with your

1048
01:01:16,720 --> 01:01:19,840
Speaker 1: tone or subscription. And it's like, it is, like, what

1049
01:01:19,920 --> 01:01:21,320
Speaker 1: do you lean I've got to sign up for a

1050
01:01:21,320 --> 01:01:25,240
Speaker 1: subscription after I bought your product. That's just a weird

1051
01:01:25,360 --> 01:01:27,440
Speaker 1: I am. Now. Maybe I'm just old guy, right and

1052
01:01:27,480 --> 01:01:29,200
Speaker 1: I'm just like not used to it, but I'm like,

1053
01:01:29,520 --> 01:01:33,320
Speaker 1: it's funny just because I did like a subscription. Really, God,

1054
01:01:33,440 --> 01:01:36,200
Speaker 1: you are just nickel and Diamond. It goes back in.

1055
01:01:36,240 --> 01:01:39,120
Speaker 1: This may be a tad before your time, but it

1056
01:01:39,160 --> 01:01:41,439
Speaker 1: was Circuit City and best Buy used to just try

1057
01:01:41,440 --> 01:01:44,080
Speaker 1: to force you to buy these, and Amazon now does

1058
01:01:44,120 --> 01:01:47,240
Speaker 1: it too. Actually, if you buy any sort of product, hey,

1059
01:01:47,240 --> 01:01:49,000
Speaker 1: do you want to buy insurance on it? Or you

1060
01:01:49,040 --> 01:01:51,240
Speaker 1: want to buy a you know, they sort of force

1061
01:01:51,360 --> 01:01:53,440
Speaker 1: these back then. It was a bit predatory the way

1062
01:01:53,440 --> 01:01:56,200
Speaker 1: Circuit City did it. I think actually the government claimed

1063
01:01:56,200 --> 01:01:57,240
Speaker 1: down on them at the time.

1064
01:01:57,920 --> 01:02:01,720
Speaker 2: Interesting, and what was really suprising was when we started

1065
01:02:01,760 --> 01:02:06,120
Speaker 2: investigating some of these practices. The executives internally were not

1066
01:02:06,280 --> 01:02:10,080
Speaker 2: subtle that this was a deliberate business strategy, and sometimes

1067
01:02:10,120 --> 01:02:13,560
Speaker 2: they would actually have kind of low level employees saying, hey,

1068
01:02:13,560 --> 01:02:16,520
Speaker 2: we're getting a lot of customer complaints that our subscription

1069
01:02:16,640 --> 01:02:20,600
Speaker 2: process theems deceptive, where people are being enruled without knowing it,

1070
01:02:20,720 --> 01:02:22,960
Speaker 2: or once they're enrolled they can't easily cancel.

1071
01:02:23,200 --> 01:02:24,960
Speaker 1: And as you're saying, the execs, let's see it as

1072
01:02:24,960 --> 01:02:26,000
Speaker 1: a feature, not a bug.

1073
01:02:26,440 --> 01:02:29,600
Speaker 2: Yeah. I mean sometimes, and this happened at Amazon, you

1074
01:02:29,600 --> 01:02:33,200
Speaker 2: know where it happened at Adobe, where a lower level

1075
01:02:33,200 --> 01:02:35,840
Speaker 2: employee said, let's fix this, here's an alternative, and the

1076
01:02:35,880 --> 01:02:37,960
Speaker 2: executive said, no, you know, I think we'll leave it

1077
01:02:38,000 --> 01:02:41,720
Speaker 2: how it is. So, you know, I think another component

1078
01:02:41,760 --> 01:02:45,160
Speaker 2: here is the courts. I mean the number of rules

1079
01:02:45,360 --> 01:02:48,480
Speaker 2: that were pushed through in the last administration that would

1080
01:02:48,480 --> 01:02:51,520
Speaker 2: have materially improved people's lives. I mean this click to

1081
01:02:51,560 --> 01:02:54,840
Speaker 2: cancel rule, our rule banning non competes. We had rules

1082
01:02:54,840 --> 01:02:58,840
Speaker 2: from the Consumer Financial Protection Bureau that would limit medical

1083
01:02:58,880 --> 01:03:01,800
Speaker 2: debt from being used on your credit report, that would

1084
01:03:01,800 --> 01:03:06,000
Speaker 2: have limited overdraft fees. A whole set of rules have

1085
01:03:06,080 --> 01:03:09,360
Speaker 2: been tossed out by courts. Sometimes I think on pretty

1086
01:03:09,400 --> 01:03:12,800
Speaker 2: bogus basis. I think there is going to be if

1087
01:03:12,880 --> 01:03:15,080
Speaker 2: kind of Democrats get a chance to govern again in

1088
01:03:15,120 --> 01:03:18,880
Speaker 2: four years, it kind of broader reassessment of how is

1089
01:03:18,920 --> 01:03:21,760
Speaker 2: to govern when you have courts that are so hostile

1090
01:03:21,840 --> 01:03:23,080
Speaker 2: to some of this governing.

1091
01:03:23,680 --> 01:03:25,800
Speaker 1: Well, you know, some of this stuff though is not

1092
01:03:25,880 --> 01:03:28,760
Speaker 1: everybody knows about it, and in some ways, you know,

1093
01:03:29,040 --> 01:03:32,840
Speaker 1: what lessons have you learned about how to communicate what

1094
01:03:32,880 --> 01:03:36,240
Speaker 1: you're doing, because that sometimes you know, if you can

1095
01:03:36,240 --> 01:03:40,440
Speaker 1: communicate it right, well, the public won't, you know, won't

1096
01:03:40,480 --> 01:03:44,360
Speaker 1: accept the idea of another administration rolling it back. And

1097
01:03:44,680 --> 01:03:46,680
Speaker 1: there were times that I thought, oh my god, you

1098
01:03:46,680 --> 01:03:49,680
Speaker 1: guys are doing a tremendous amount of stuff, but it's

1099
01:03:49,720 --> 01:03:52,360
Speaker 1: almost like you're over the public's not. There's too much

1100
01:03:52,400 --> 01:03:54,200
Speaker 1: and the public's not going to realize what you're doing.

1101
01:03:54,960 --> 01:03:59,040
Speaker 1: And if they don't, then it doesn't take root. And

1102
01:03:59,080 --> 01:04:02,400
Speaker 1: if it doesn't take root, becomes easy to throw out.

1103
01:04:02,640 --> 01:04:04,560
Speaker 1: What what have you? What did you learned ear in

1104
01:04:04,560 --> 01:04:07,160
Speaker 1: your four years that if you ever got another shot

1105
01:04:07,160 --> 01:04:10,440
Speaker 1: at this, what would you is there is there different

1106
01:04:10,440 --> 01:04:13,440
Speaker 1: ways would you would you sort of tackle less at

1107
01:04:13,480 --> 01:04:16,040
Speaker 1: any one time? Right? Because there's so much you want

1108
01:04:16,080 --> 01:04:19,160
Speaker 1: to do, like, how much do you think the communications

1109
01:04:19,200 --> 01:04:21,320
Speaker 1: strategy has to be a part of what you're doing.

1110
01:04:22,520 --> 01:04:25,240
Speaker 2: You're right that it's absolutely essential. And you know, the

1111
01:04:25,320 --> 01:04:29,760
Speaker 2: ftc U for some years now had had been kind

1112
01:04:29,760 --> 01:04:32,880
Speaker 2: of in the shadows, uh, you know, people didn't know

1113
01:04:32,960 --> 01:04:35,480
Speaker 2: what it was, what the agency did, and so it

1114
01:04:35,520 --> 01:04:38,040
Speaker 2: was a bit of a departure candidly when I was

1115
01:04:38,040 --> 01:04:41,000
Speaker 2: there for for the FTC to be as out there

1116
01:04:41,040 --> 01:04:43,360
Speaker 2: as it had been. And we did that for a

1117
01:04:43,400 --> 01:04:47,360
Speaker 2: couple of reasons. One was I think in DC sometimes

1118
01:04:47,360 --> 01:04:51,120
Speaker 2: there can be this tendency to over index on kind

1119
01:04:51,120 --> 01:04:54,120
Speaker 2: of the expert class for how we understand the economy,

1120
01:04:54,600 --> 01:04:57,200
Speaker 2: and that can create certain blind spots where you really

1121
01:04:57,200 --> 01:04:59,680
Speaker 2: have to talk to people and understand what is people's

1122
01:04:59,680 --> 01:05:02,960
Speaker 2: lived in experience to understand what those pain points are.

1123
01:05:03,000 --> 01:05:05,760
Speaker 2: And so we did listening sessions, We did regular open

1124
01:05:05,800 --> 01:05:09,080
Speaker 2: commission meetings where anybody in America could sign up and

1125
01:05:09,280 --> 01:05:12,960
Speaker 2: talk to the Federal Trade Commissioners, and just really broadened

1126
01:05:13,240 --> 01:05:15,760
Speaker 2: the voices we were hearing to make sure we had

1127
01:05:16,560 --> 01:05:19,959
Speaker 2: a real three sixty view of the economy rather than

1128
01:05:20,520 --> 01:05:23,280
Speaker 2: of you that was dominated by the kind of lobbyists

1129
01:05:23,280 --> 01:05:27,280
Speaker 2: and the lawyers and the kind of class. But it

1130
01:05:27,320 --> 01:05:29,480
Speaker 2: was also to be able to communicate, right, I mean,

1131
01:05:29,520 --> 01:05:32,720
Speaker 2: the FTC is the agency where if it's doing its job,

1132
01:05:33,000 --> 01:05:36,200
Speaker 2: if it's taking on monopolies and corporate law breakers, it

1133
01:05:36,280 --> 01:05:39,360
Speaker 2: is going to face pushback from those corporate interests, and

1134
01:05:39,400 --> 01:05:42,000
Speaker 2: you need to make sure that you are building the

1135
01:05:42,160 --> 01:05:46,200
Speaker 2: countervailing support from the people that are benefiting from this work.

1136
01:05:46,880 --> 01:05:49,040
Speaker 2: You know, we had a small agency. We had a

1137
01:05:49,040 --> 01:05:52,280
Speaker 2: heroic comms team, but it was very small, and so,

1138
01:05:52,520 --> 01:05:54,440
Speaker 2: you know, I think figuring out how can kind of

1139
01:05:54,480 --> 01:05:59,200
Speaker 2: other players and government and political system alsolifying this will

1140
01:05:59,200 --> 01:05:59,560
Speaker 2: be key.

1141
01:06:00,280 --> 01:06:02,320
Speaker 1: You know, one of the challenges. It's funny you bring

1142
01:06:02,400 --> 01:06:08,480
Speaker 1: up to sort of kind of broaden what the FTC

1143
01:06:08,520 --> 01:06:12,280
Speaker 1: folks were hearing about the economy. And one of my

1144
01:06:12,600 --> 01:06:16,280
Speaker 1: more complaints about traditional media over the last two decades

1145
01:06:16,320 --> 01:06:18,360
Speaker 1: when it comes to coverage of the economy is I

1146
01:06:18,440 --> 01:06:21,080
Speaker 1: used to argue we don't cover the economy, we cover markets,

1147
01:06:21,960 --> 01:06:27,200
Speaker 1: and the CNBC afflication of business coverage right when I

1148
01:06:27,280 --> 01:06:30,160
Speaker 1: was you know, coverage of the economy was much different

1149
01:06:30,200 --> 01:06:32,920
Speaker 1: in the eighties and nineties, and then when we all

1150
01:06:32,960 --> 01:06:37,480
Speaker 1: became so market focused, Right, there's a part of me

1151
01:06:37,560 --> 01:06:40,720
Speaker 1: that thinks that it almost made people more comfortable with

1152
01:06:40,800 --> 01:06:44,120
Speaker 1: consolidation because consolidation was good for the stock market than

1153
01:06:44,160 --> 01:06:46,520
Speaker 1: stock market was good for retirement. Like we sort of

1154
01:06:46,560 --> 01:06:54,240
Speaker 1: perverted what even economics reporting was right. The economy is people.

1155
01:06:54,640 --> 01:06:57,720
Speaker 1: The economy is not markets. And the only business coverage

1156
01:06:57,720 --> 01:07:00,600
Speaker 1: in mainstream media today is markets. Right, whether it's Fox

1157
01:07:00,640 --> 01:07:04,200
Speaker 1: Business Channel or SANBC, you don't really get the same

1158
01:07:04,280 --> 01:07:08,200
Speaker 1: kind of consumer protection coverage that used to be quote

1159
01:07:08,240 --> 01:07:11,080
Speaker 1: unquote business coverage. Now it feels like it's all about

1160
01:07:11,080 --> 01:07:12,320
Speaker 1: markets and all about equity.

1161
01:07:13,280 --> 01:07:16,120
Speaker 2: That's such a profoundly important point, and I think one

1162
01:07:16,160 --> 01:07:20,040
Speaker 2: of those kind of hidden shifts that does really have

1163
01:07:20,320 --> 01:07:23,720
Speaker 2: enormous downstream consequences for how policy makers, even as you said,

1164
01:07:23,840 --> 01:07:26,880
Speaker 2: understand what the economy is. Right, and if you're just

1165
01:07:27,040 --> 01:07:30,720
Speaker 2: using for your understanding of the economy the stock market

1166
01:07:30,760 --> 01:07:33,040
Speaker 2: as the key proxy of whether people are doing well

1167
01:07:33,160 --> 01:07:35,840
Speaker 2: or not, we're going to miss a lot. And sometimes candidly,

1168
01:07:36,280 --> 01:07:38,800
Speaker 2: stock prices go up because companies are doing things that

1169
01:07:38,800 --> 01:07:41,800
Speaker 2: are profitable for them but actually bad for regular people.

1170
01:07:42,080 --> 01:07:44,880
Speaker 2: And so not only can it be inadequate, but it

1171
01:07:44,880 --> 01:07:48,520
Speaker 2: can sometimes be you know, the inverse, and so I

1172
01:07:48,600 --> 01:07:50,560
Speaker 2: think that's a problem. And I think, you know, one

1173
01:07:50,560 --> 01:07:54,320
Speaker 2: thing that's been interesting is this broader conversation now happening

1174
01:07:54,760 --> 01:07:57,880
Speaker 2: in DC but across the country about how it is

1175
01:07:57,920 --> 01:08:00,680
Speaker 2: it that that people should govern and how is it

1176
01:08:00,760 --> 01:08:03,160
Speaker 2: that people should kind of win elections. And it does

1177
01:08:03,200 --> 01:08:07,840
Speaker 2: seem like those people who are focusing on listening to people, right,

1178
01:08:07,880 --> 01:08:10,920
Speaker 2: we just had money when in New York City he

1179
01:08:11,040 --> 01:08:13,520
Speaker 2: went to all cards and asked them, Hey, what is

1180
01:08:13,520 --> 01:08:16,439
Speaker 2: it that's making your business? Right, kind of that on

1181
01:08:16,479 --> 01:08:21,360
Speaker 2: the ground level economics, economy reporting, and to bring to

1182
01:08:21,400 --> 01:08:24,439
Speaker 2: it a sense of curiosity, right, just like there's a

1183
01:08:24,479 --> 01:08:27,639
Speaker 2: lot we don't know in DC, and making sure we're

1184
01:08:27,640 --> 01:08:30,080
Speaker 2: actually going out there and asking people who are kind

1185
01:08:30,080 --> 01:08:32,800
Speaker 2: of experts in their own domain. So I think we

1186
01:08:32,880 --> 01:08:33,640
Speaker 2: need a lot more of that.

1187
01:08:34,720 --> 01:08:36,760
Speaker 1: So one of the things that I've I sort of

1188
01:08:36,760 --> 01:08:38,680
Speaker 1: get on my hobby horse about when it comes to

1189
01:08:38,840 --> 01:08:43,519
Speaker 1: government regulation is algorithms. I don't see any good that

1190
01:08:43,520 --> 01:08:47,320
Speaker 1: comes from an algorithm personally, I understand, you know, and

1191
01:08:48,000 --> 01:08:51,200
Speaker 1: I feel like they're you know, I don't want an

1192
01:08:51,240 --> 01:08:54,360
Speaker 1: algorithm trying to suggest what I might like. I want

1193
01:08:54,360 --> 01:08:57,400
Speaker 1: to decide what I like, and then I might say Yeah,

1194
01:08:57,479 --> 01:09:00,280
Speaker 1: let's personalize a search, and you go ahead and me

1195
01:09:00,360 --> 01:09:03,160
Speaker 1: stuff that's similar to this. But I want control of that.

1196
01:09:03,880 --> 01:09:06,439
Speaker 1: If I'm going to sound a little rubish and go

1197
01:09:06,479 --> 01:09:08,360
Speaker 1: ahead and say it, which is, God damn it, I

1198
01:09:08,400 --> 01:09:13,720
Speaker 1: want my government to I mean, who's who's regulating these algorithms?

1199
01:09:13,960 --> 01:09:17,880
Speaker 1: They're black boxes and it is it is. How I

1200
01:09:17,920 --> 01:09:20,599
Speaker 1: interact with Google is different than somebody else interacts with Google,

1201
01:09:22,240 --> 01:09:25,160
Speaker 1: and I have nobody sort of I have no idea

1202
01:09:25,200 --> 01:09:28,599
Speaker 1: whether I'm I'm getting a fair look or not because

1203
01:09:29,120 --> 01:09:32,719
Speaker 1: I don't know how the algorithm works. Do you should

1204
01:09:32,760 --> 01:09:37,320
Speaker 1: the act? Who should and should government basically be in

1205
01:09:37,400 --> 01:09:39,320
Speaker 1: the business of regulating algorithms.

1206
01:09:41,400 --> 01:09:43,160
Speaker 2: It's a great question, and I think one of the

1207
01:09:43,280 --> 01:09:46,920
Speaker 2: places where it's most acute right now is when it

1208
01:09:46,960 --> 01:09:50,840
Speaker 2: comes to kids. Right there's been a huge epidemic of

1209
01:09:51,439 --> 01:09:56,360
Speaker 2: you know, social media addiction abuse on these platforms, and

1210
01:09:56,439 --> 01:09:58,760
Speaker 2: parents feel like they don't have any control of what

1211
01:09:58,800 --> 01:10:02,719
Speaker 2: their kids are seeing. And these companies, again, their business

1212
01:10:02,760 --> 01:10:08,000
Speaker 2: model is to monetize data. And it's been shown that

1213
01:10:08,160 --> 01:10:12,679
Speaker 2: the content that is does best is oftenheims the content

1214
01:10:12,720 --> 01:10:16,360
Speaker 2: that is most divisive or most inflammatory.

1215
01:10:15,960 --> 01:10:19,439
Speaker 3: Because there's exspectives of you, all right, the incentives to

1216
01:10:19,479 --> 01:10:21,840
Speaker 3: keep you on the platform, to see more advertisements, to

1217
01:10:21,840 --> 01:10:26,400
Speaker 3: see more whatever, and well, okay, you've learned human psychology,

1218
01:10:27,400 --> 01:10:31,040
Speaker 3: and if you're using human psychology against us, that's I

1219
01:10:31,080 --> 01:10:32,320
Speaker 3: thought that was manipulative.

1220
01:10:32,600 --> 01:10:34,840
Speaker 1: I thought that was something that the FDC was supposed

1221
01:10:34,880 --> 01:10:36,200
Speaker 1: to say, No, you can't do that.

1222
01:10:37,280 --> 01:10:39,600
Speaker 2: I mean, we've had executives from some of these companies

1223
01:10:39,880 --> 01:10:43,759
Speaker 2: acknowledge publicly that some of the techniques that they're using

1224
01:10:43,920 --> 01:10:48,240
Speaker 2: are basically similar to how people are designing slot machines

1225
01:10:48,360 --> 01:10:51,760
Speaker 2: for gambling in terms of like they're designed to keep

1226
01:10:51,800 --> 01:10:55,519
Speaker 2: you addicted. And so the fact that we haven't had

1227
01:10:55,720 --> 01:11:00,599
Speaker 2: kind of extensive government involvement here, I think is creating

1228
01:11:00,640 --> 01:11:02,400
Speaker 2: a lot of pain and going to lead to a

1229
01:11:02,439 --> 01:11:04,520
Speaker 2: lot of problems.

1230
01:11:05,080 --> 01:11:08,960
Speaker 1: We got a few more minutes here. Who owns data

1231
01:11:10,479 --> 01:11:13,920
Speaker 1: and where should you know? So Frank McCort, the former

1232
01:11:13,960 --> 01:11:17,479
Speaker 1: owner of the Dodgers, was working on something called Project Liberty.

1233
01:11:18,360 --> 01:11:20,559
Speaker 1: He wrote a piece he was now, I think he's

1234
01:11:20,560 --> 01:11:22,639
Speaker 1: trying to be one of the folks that might buy TikTok.

1235
01:11:22,680 --> 01:11:28,439
Speaker 1: We'll see, but he's actually, you know, he he he

1236
01:11:28,600 --> 01:11:30,880
Speaker 1: has pitched this idea that data should be in a

1237
01:11:30,920 --> 01:11:34,240
Speaker 1: public trust that Amazon should known data, Google should know

1238
01:11:34,240 --> 01:11:37,160
Speaker 1: own data that you know, they essentially should license the

1239
01:11:37,240 --> 01:11:39,200
Speaker 1: use of data, but that data should be almost like

1240
01:11:39,200 --> 01:11:44,920
Speaker 1: a public utility. I guess what would that could that happen,

1241
01:11:45,040 --> 01:11:46,920
Speaker 1: what would that look like? I mean, at what point,

1242
01:11:47,080 --> 01:11:49,840
Speaker 1: you know, I've been waiting for my data built privacy

1243
01:11:49,840 --> 01:11:52,840
Speaker 1: Bill of Rights to be passed by a Congress for

1244
01:11:52,880 --> 01:11:56,000
Speaker 1: the last twenty years, and it's not happened. I think

1245
01:11:56,640 --> 01:12:00,000
Speaker 1: we inherently and here's what's sort of frustrating. Individual data

1246
01:12:00,200 --> 01:12:07,479
Speaker 1: is worthless, collective data is infinitely valuable. It seems that

1247
01:12:07,520 --> 01:12:10,559
Speaker 1: we've got that this is sort of one of the

1248
01:12:10,600 --> 01:12:14,920
Speaker 1: hardest issues to tackle, and yet it's at the heart

1249
01:12:14,920 --> 01:12:17,960
Speaker 1: of almost all of these current antitrust conversations.

1250
01:12:19,920 --> 01:12:22,000
Speaker 2: You're right, and the companies will say that they own

1251
01:12:22,080 --> 01:12:25,400
Speaker 2: the data, effectively, that once they have collected it, that

1252
01:12:25,479 --> 01:12:27,519
Speaker 2: it is their property, and there are all these basic

1253
01:12:27,600 --> 01:12:29,400
Speaker 2: questions about, well, how does that work if it was

1254
01:12:29,439 --> 01:12:32,160
Speaker 2: actually my data, but now it's being complete your data,

1255
01:12:32,680 --> 01:12:34,840
Speaker 2: you know. To my mind, that's a key question. But

1256
01:12:34,960 --> 01:12:38,160
Speaker 2: another key question is should some of this data be

1257
01:12:38,240 --> 01:12:41,760
Speaker 2: off limits for monetization in the first place? I mean,

1258
01:12:41,800 --> 01:12:44,360
Speaker 2: at the FTC. We would do investigations where we would

1259
01:12:44,439 --> 01:12:49,960
Speaker 2: find that companies like health apps, we're collecting sensitive information,

1260
01:12:50,080 --> 01:12:54,720
Speaker 2: health information from people and then selling that on to

1261
01:12:54,800 --> 01:12:57,400
Speaker 2: these data brokers and then you know, all sorts of

1262
01:12:57,439 --> 01:12:59,960
Speaker 2: bad actors could get their hands on it. We had

1263
01:13:00,600 --> 01:13:05,800
Speaker 2: geolocation from your phone being sold, including to stalkers and abusers.

1264
01:13:07,160 --> 01:13:09,760
Speaker 2: There's just huge risks here. And so one thing that

1265
01:13:09,800 --> 01:13:12,840
Speaker 2: we did through some of these law enforcement actions was

1266
01:13:13,439 --> 01:13:17,280
Speaker 2: say that for sensitive data, for data about your browsing

1267
01:13:17,360 --> 01:13:21,280
Speaker 2: history on the internet, your precise location, your health, that

1268
01:13:21,360 --> 01:13:25,200
Speaker 2: data by default cannot be sold. That unless you are

1269
01:13:25,280 --> 01:13:29,280
Speaker 2: affirmatively agreeing and consenting to that data be sold. The

1270
01:13:29,360 --> 01:13:32,400
Speaker 2: default is it cannot be And so you know, I

1271
01:13:32,400 --> 01:13:35,320
Speaker 2: think we need some more of those bright line rules

1272
01:13:35,439 --> 01:13:39,120
Speaker 2: to get past this fiction. The default is everything is

1273
01:13:39,160 --> 01:13:42,200
Speaker 2: collected and sold. And then we need to think about

1274
01:13:42,200 --> 01:13:44,479
Speaker 2: some of the business models and the monetization and the

1275
01:13:44,520 --> 01:13:46,479
Speaker 2: algorithm and how all of that fits together.

1276
01:13:47,439 --> 01:13:51,600
Speaker 1: Look, I give Apple credit the ask app not to track, Like,

1277
01:13:51,880 --> 01:13:54,840
Speaker 1: why was that so hard? Why is that so hard?

1278
01:13:54,880 --> 01:13:57,680
Speaker 1: And is that now I've heard that there are a

1279
01:13:57,760 --> 01:14:01,360
Speaker 1: whole bunch of small I guess in gaming companies, you know,

1280
01:14:01,400 --> 01:14:04,200
Speaker 1: who may who made money simply on quote unquote free acts,

1281
01:14:04,560 --> 01:14:09,920
Speaker 1: right that it hurt their businesses. I'm not shedding a

1282
01:14:09,960 --> 01:14:12,920
Speaker 1: tear over that. If that's how they if that was there,

1283
01:14:13,200 --> 01:14:16,679
Speaker 1: if that was their north star and how to make

1284
01:14:16,720 --> 01:14:17,679
Speaker 1: money for their business.

1285
01:14:19,680 --> 01:14:21,680
Speaker 2: Yeah, I mean, I think what was so striking is

1286
01:14:21,720 --> 01:14:24,720
Speaker 2: once Apple introduced that. I think they reported that over

1287
01:14:24,840 --> 01:14:28,160
Speaker 2: sixty percent of Americans chose not to have their data,

1288
01:14:28,479 --> 01:14:31,679
Speaker 2: you know, shared, which is very important because sometimes hear

1289
01:14:31,680 --> 01:14:34,800
Speaker 2: from these companies as well, Americans don't really care about

1290
01:14:34,800 --> 01:14:37,040
Speaker 2: privacy because if they did, they wouldn't agree to use

1291
01:14:37,040 --> 01:14:39,800
Speaker 2: all our services. And as we started off with, you know,

1292
01:14:39,880 --> 01:14:42,519
Speaker 2: the consent here is a fiction, and when you actually

1293
01:14:42,520 --> 01:14:45,760
Speaker 2: get people to overwhelming there is.

1294
01:14:45,960 --> 01:14:48,640
Speaker 1: Some generational data on this. You know, my kids, I

1295
01:14:48,680 --> 01:14:50,120
Speaker 1: have an eighteen year old and twenty one year old,

1296
01:14:51,840 --> 01:14:56,080
Speaker 1: they're you know, they they're sort of they're weirdly more

1297
01:14:56,160 --> 01:14:58,800
Speaker 1: comfortable with more of their data out there, you know.

1298
01:14:59,040 --> 01:15:02,920
Speaker 1: And now I would argue, well, they've been sort of

1299
01:15:03,200 --> 01:15:07,720
Speaker 1: you know, they've been sort of trained, if you will. Unfortunately,

1300
01:15:07,920 --> 01:15:10,040
Speaker 1: you know, and maybe that's on me as a parent,

1301
01:15:10,120 --> 01:15:12,800
Speaker 1: didn't realize how much this was happening, right, You just

1302
01:15:12,840 --> 01:15:16,000
Speaker 1: don't fully appreciate it until they're like, yeah, you know,

1303
01:15:16,360 --> 01:15:19,719
Speaker 1: this is the price of doing business and on the internet,

1304
01:15:20,120 --> 01:15:24,519
Speaker 1: which you know, you know, I guess that's what these

1305
01:15:24,520 --> 01:15:26,800
Speaker 1: big tech companies are counting on, right, that we're just

1306
01:15:26,880 --> 01:15:29,160
Speaker 1: going to be we care about using the products too

1307
01:15:29,240 --> 01:15:32,880
Speaker 1: much to worry about the personal stuff.

1308
01:15:34,160 --> 01:15:36,679
Speaker 2: Yeah, I mean, I think sometimes this is also true

1309
01:15:36,680 --> 01:15:40,160
Speaker 2: where privacy can sound kind of abstract, but once you

1310
01:15:40,280 --> 01:15:42,840
Speaker 2: lay out how this data can be used against you,

1311
01:15:43,439 --> 01:15:46,519
Speaker 2: including by setting a specific price for you that is

1312
01:15:46,560 --> 01:15:48,160
Speaker 2: different from the price you're friends.

1313
01:15:47,960 --> 01:15:50,719
Speaker 1: Or surveillance pricing, like how do you well? That feels

1314
01:15:50,760 --> 01:15:53,160
Speaker 1: like how are you going to be able to prevent

1315
01:15:53,200 --> 01:15:58,519
Speaker 1: that without sort of micro managing and regulating algorithms in general? Right?

1316
01:15:58,560 --> 01:16:01,439
Speaker 1: I mean, isn't that that to me? That gets that

1317
01:16:01,560 --> 01:16:04,280
Speaker 1: to why I want this? And I know the tech

1318
01:16:04,280 --> 01:16:07,040
Speaker 1: companies would find this invasive and onerous because they don't

1319
01:16:07,040 --> 01:16:11,559
Speaker 1: want to admit how manipulative, intentionally manipulative these algorithms are

1320
01:16:11,680 --> 01:16:12,400
Speaker 1: being built to do.

1321
01:16:14,200 --> 01:16:16,880
Speaker 2: That's right, and there are real battles happening, I mean

1322
01:16:16,920 --> 01:16:20,640
Speaker 2: in state legislatures in Congress. It does it's clear that

1323
01:16:20,680 --> 01:16:23,439
Speaker 2: whenever lawmakers have tried to do something here. There has

1324
01:16:23,479 --> 01:16:27,799
Speaker 2: been ferocious pushback, farrocious lobbying, and just a clear example

1325
01:16:27,840 --> 01:16:31,880
Speaker 2: of companies using their economic power as political power.

1326
01:16:33,360 --> 01:16:35,439
Speaker 1: Let me get you out in here on this. How

1327
01:16:35,479 --> 01:16:38,720
Speaker 1: can the average person keep an eye on this or

1328
01:16:39,439 --> 01:16:42,760
Speaker 1: this issue of surveillance pricing? Just my guess is this

1329
01:16:42,800 --> 01:16:44,760
Speaker 1: is something that's going to become a bigger issue. It's

1330
01:16:44,760 --> 01:16:46,320
Speaker 1: not going to go away. It's actually going to become

1331
01:16:46,840 --> 01:16:51,719
Speaker 1: more as this happens. Is there any good consumer tips

1332
01:16:52,800 --> 01:16:57,320
Speaker 1: to sort of to you know, double check to see

1333
01:16:57,320 --> 01:17:00,000
Speaker 1: if this is happening to you.

1334
01:17:00,040 --> 01:17:02,360
Speaker 2: Yeah, it's a great question, and it's ultimately not something

1335
01:17:02,400 --> 01:17:04,880
Speaker 2: that can be fixed by us as individuals. Really, do

1336
01:17:04,880 --> 01:17:06,439
Speaker 2: you need the government to kind of come in and

1337
01:17:06,920 --> 01:17:09,400
Speaker 2: work on our behalf? I mean, you know there are

1338
01:17:10,479 --> 01:17:13,920
Speaker 2: browsers that are more designed for privacy and more designed

1339
01:17:13,920 --> 01:17:16,120
Speaker 2: to limit how much data can be collected on you.

1340
01:17:16,560 --> 01:17:20,200
Speaker 2: They recommend kind of clearing your cookies to try to

1341
01:17:20,240 --> 01:17:22,360
Speaker 2: limit collections. So you know, there are things on the

1342
01:17:22,400 --> 01:17:24,840
Speaker 2: margins that people can do to try to protect more

1343
01:17:24,840 --> 01:17:28,599
Speaker 2: of their privacy. But it's tough, and I think kind

1344
01:17:28,600 --> 01:17:31,519
Speaker 2: of telling lunched officials to kind of work on this

1345
01:17:31,640 --> 01:17:32,040
Speaker 2: is going to.

1346
01:17:31,960 --> 01:17:35,639
Speaker 1: Be key if it sounds like I've always joked that

1347
01:17:35,760 --> 01:17:37,599
Speaker 1: thank God for the EU. They seem to care about

1348
01:17:37,600 --> 01:17:42,360
Speaker 1: my privacy more than my United States government? Does you know?

1349
01:17:42,439 --> 01:17:45,400
Speaker 2: It's an interesting question. They do have this, this GDPR.

1350
01:17:45,840 --> 01:17:48,240
Speaker 2: I think there are split opinions on how effective it

1351
01:17:48,280 --> 01:17:50,719
Speaker 2: has been. Some people have said, Okay, it's just created

1352
01:17:50,720 --> 01:17:54,120
Speaker 2: this kind of endless set of clicking, and we don't

1353
01:17:54,160 --> 01:17:55,839
Speaker 2: know if there are actually any.

1354
01:17:55,800 --> 01:17:59,280
Speaker 4: Serious contract company hate it. The tech companies hate it.

1355
01:17:59,520 --> 01:18:03,559
Speaker 4: And if they hate it, I'm like, well, maybe you

1356
01:18:03,600 --> 01:18:06,000
Speaker 4: know they're squealing. That tells me something.

1357
01:18:06,760 --> 01:18:09,200
Speaker 2: Yeah, yeah, I know the US is behind on this one.

1358
01:18:09,240 --> 01:18:10,920
Speaker 2: We don't have any federal privacy lows.

1359
01:18:11,000 --> 01:18:18,080
Speaker 1: So what's next for you, Leanah.

1360
01:18:15,640 --> 01:18:18,240
Speaker 2: You know, figuring out how to continue this work. I

1361
01:18:18,240 --> 01:18:22,760
Speaker 2: think there's a huge movement afoot, candidly to figure out

1362
01:18:22,760 --> 01:18:24,880
Speaker 2: how do we have our government be more responsive on

1363
01:18:24,920 --> 01:18:28,519
Speaker 2: these economic power issues. I'll be teaching anti trust law

1364
01:18:28,520 --> 01:18:31,680
Speaker 2: and so excited to help train the next generation, but

1365
01:18:31,840 --> 01:18:34,840
Speaker 2: very interested and how do we make sure that people

1366
01:18:34,880 --> 01:18:39,040
Speaker 2: in DC are really hearing from people across the economy

1367
01:18:39,080 --> 01:18:40,760
Speaker 2: and as you put it, you know, not just using

1368
01:18:40,800 --> 01:18:43,559
Speaker 2: the stock markets as a barometer for whether the economy

1369
01:18:43,640 --> 01:18:45,400
Speaker 2: is working, and how do we make that better? How

1370
01:18:45,400 --> 01:18:46,120
Speaker 2: do we govern better?

1371
01:18:46,600 --> 01:18:49,879
Speaker 1: Yeah, I'm unfortunately worried that the c has been captured

1372
01:18:50,080 --> 01:18:51,720
Speaker 1: a little bit on this, that there's a little bit

1373
01:18:51,720 --> 01:18:56,080
Speaker 1: of bipartisan capture on markets, on tech, on fear of

1374
01:18:56,200 --> 01:18:58,880
Speaker 1: China being used. Right, every time they want to stop

1375
01:18:58,880 --> 01:19:00,400
Speaker 1: a rate, no, no, no, no, that is going to

1376
01:19:00,439 --> 01:19:06,360
Speaker 1: bet us. It's almost used as a threat. So I definitely,

1377
01:19:06,479 --> 01:19:08,200
Speaker 1: I definitely think that you're going to have plenty of

1378
01:19:08,240 --> 01:19:11,680
Speaker 1: people very curious on what you do next and how

1379
01:19:11,760 --> 01:19:15,000
Speaker 1: much you can amplify it. So good luck and and

1380
01:19:15,680 --> 01:19:18,400
Speaker 1: enjoy the person you teaching this fall. You're going right

1381
01:19:18,479 --> 01:19:22,840
Speaker 1: back into it. Yeah, all right, Well, there's there's nothing

1382
01:19:22,840 --> 01:19:25,559
Speaker 1: more uplifting than teaching college kids. That's what I have

1383
01:19:25,640 --> 01:19:29,040
Speaker 1: found in it. No matter how cynical you get, right,

1384
01:19:29,560 --> 01:19:33,200
Speaker 1: it sort of it gives you hope. So enjoy that

1385
01:19:33,280 --> 01:19:35,679
Speaker 1: time back in academia. And I hope we talk again.

1386
01:19:36,400 --> 01:19:37,080
Speaker 2: Thanks so much.

1387
01:19:46,680 --> 01:19:49,040
Speaker 1: So I hope you enjoyed the conversation with Lena Kahan.

1388
01:19:49,200 --> 01:19:51,880
Speaker 1: I want to you know, one of the things that

1389
01:19:51,920 --> 01:19:56,280
Speaker 1: we dabbled in on is the issue of AI right

1390
01:19:56,320 --> 01:19:58,840
Speaker 1: and what what is government's role and how are consumers

1391
01:19:58,880 --> 01:20:02,240
Speaker 1: going to get protected as we advance in AI And

1392
01:20:02,880 --> 01:20:05,360
Speaker 1: as I was preparing, I stumbled on something. And this

1393
01:20:05,439 --> 01:20:08,080
Speaker 1: is going to be come across a bit self surfing serving,

1394
01:20:08,120 --> 01:20:11,040
Speaker 1: and I apologize in advance. I'm not usually interested in

1395
01:20:11,080 --> 01:20:15,720
Speaker 1: trying to insert myself into a story, says the guy

1396
01:20:15,760 --> 01:20:19,599
Speaker 1: that's trying that's broadcasting on YouTube. But I take anyway,

1397
01:20:19,720 --> 01:20:21,559
Speaker 1: So go ahead and stark at me. I get it,

1398
01:20:21,760 --> 01:20:24,479
Speaker 1: but in all seriousness. So what happened earlier this morning?

1399
01:20:24,520 --> 01:20:26,519
Speaker 1: I was preparing my interview of Lena Khan and I

1400
01:20:26,520 --> 01:20:28,360
Speaker 1: had interviewed Jonathan Canner, who was the head of the

1401
01:20:28,400 --> 01:20:33,120
Speaker 1: Anti Trust Division during the previous Justice Department, and it

1402
01:20:33,160 --> 01:20:36,240
Speaker 1: was an interview I conducted with him when NBC owned

1403
01:20:36,240 --> 01:20:39,080
Speaker 1: my podcast, And so I was looking for it, right,

1404
01:20:39,160 --> 01:20:41,559
Speaker 1: did the old fashioned Google search? Right, They're seeing if

1405
01:20:41,600 --> 01:20:44,320
Speaker 1: I could find it somewhere archive. I just wanted to

1406
01:20:44,320 --> 01:20:46,880
Speaker 1: see if I could find transcript something of it. And

1407
01:20:46,920 --> 01:20:49,120
Speaker 1: as I'm you know, I rarely I hadn't Googled myself

1408
01:20:49,200 --> 01:20:51,840
Speaker 1: in a while. I was just doing Chuck Todd podcast

1409
01:20:51,920 --> 01:20:54,920
Speaker 1: Jonathan Canter, right, And as I'm typing, you know, Google

1410
01:20:54,960 --> 01:20:57,519
Speaker 1: will helpfully give you other things as you type a

1411
01:20:57,560 --> 01:21:02,400
Speaker 1: person's name, and suddenly the words Duck Todd illness shows up,

1412
01:21:02,400 --> 01:21:05,000
Speaker 1: and I'm like, I wonder what that is. I was curious,

1413
01:21:05,000 --> 01:21:07,760
Speaker 1: so I hit it. And now, of course everybody has

1414
01:21:07,840 --> 01:21:11,439
Speaker 1: experienced the Google the way the Google pages work. Now

1415
01:21:11,439 --> 01:21:15,400
Speaker 1: you get the AI, you get Gemini's quick summary of

1416
01:21:15,520 --> 01:21:20,880
Speaker 1: the search in your thing. And so when you do

1417
01:21:21,080 --> 01:21:27,040
Speaker 1: Chuck Todd illness, here's what happens. The AI overview ends

1418
01:21:27,120 --> 01:21:29,120
Speaker 1: up saying the following. Chuck Todd, the former host of

1419
01:21:29,160 --> 01:21:31,799
Speaker 1: Meet the Press, is publicly disclosed that he has Parkinson's disease.

1420
01:21:32,240 --> 01:21:34,839
Speaker 1: He revealed his diagnosis in twenty eighteen after being diagnosed

1421
01:21:34,880 --> 01:21:37,800
Speaker 1: in twenty thirteen. While specific details about the progression of

1422
01:21:37,840 --> 01:21:40,160
Speaker 1: his illness are not widely publicized, there have been reports

1423
01:21:40,160 --> 01:21:42,519
Speaker 1: of symptoms like fatigue, any way changes, as well as

1424
01:21:42,520 --> 01:21:47,400
Speaker 1: a decrease in public appearances. Okay, there's nothing about this

1425
01:21:47,479 --> 01:21:49,320
Speaker 1: is true. I don't I'm not going to say it.

1426
01:21:49,320 --> 01:21:52,280
Speaker 1: I don't feel like i've been you know, this is defamatory.

1427
01:21:53,720 --> 01:21:58,120
Speaker 1: I don't have Parkinson's disease. I get a physical anyway.

1428
01:21:58,400 --> 01:22:00,360
Speaker 1: My point is, none of this is true. I've not

1429
01:22:00,400 --> 01:22:03,280
Speaker 1: had any illness. I would tell you. Is there something nothing?

1430
01:22:03,840 --> 01:22:05,680
Speaker 1: You know, I've had a few kidney stones that I've

1431
01:22:05,720 --> 01:22:08,519
Speaker 1: gone public with. I've not gone what I've gone. I

1432
01:22:08,520 --> 01:22:11,200
Speaker 1: think I'm up to nearly a year without a kidney stone,

1433
01:22:11,280 --> 01:22:14,120
Speaker 1: but I frequently get those. That's about the worst health

1434
01:22:14,160 --> 01:22:19,040
Speaker 1: problem I've had to deal with. And I'm sitting here going,

1435
01:22:19,040 --> 01:22:21,640
Speaker 1: wait a minute, this is in a this is the

1436
01:22:22,560 --> 01:22:25,240
Speaker 1: AI search. And then of course you can do Chuck

1437
01:22:25,320 --> 01:22:28,360
Speaker 1: Todd illness update. And then it claims Chuck Todd, who

1438
01:22:28,360 --> 01:22:31,200
Speaker 1: was diagnosed with Parkinson's disease in twenty thirteen, has publicly

1439
01:22:31,200 --> 01:22:34,120
Speaker 1: acknowledged his condition and has been managing it while continuing

1440
01:22:34,160 --> 01:22:37,519
Speaker 1: his media career. I have never publicly acknowledged this because

1441
01:22:37,560 --> 01:22:41,479
Speaker 1: there is nothing to acknowledge. And then it says he

1442
01:22:41,560 --> 01:22:43,639
Speaker 1: shared his diagnosis in twenty eighteen and has since been

1443
01:22:43,680 --> 01:22:47,120
Speaker 1: involved with the Parkinson Association of Central Florida, even serving

1444
01:22:47,120 --> 01:22:51,120
Speaker 1: as president in twenty twenty one. Not true, says Todd

1445
01:22:51,160 --> 01:22:53,800
Speaker 1: has spoken about his low gluten free diet. That is true,

1446
01:22:54,040 --> 01:22:58,320
Speaker 1: and his exercise routine. That is true, but everything else

1447
01:22:58,479 --> 01:23:02,479
Speaker 1: is not true. It appears that there is a gentleman

1448
01:23:02,520 --> 01:23:04,519
Speaker 1: with the first name of Todd who's involved with the

1449
01:23:04,520 --> 01:23:07,760
Speaker 1: Parkinson Association in Central Florida, So that got conflated. The

1450
01:23:07,800 --> 01:23:10,920
Speaker 1: point is is that here I am, who is going

1451
01:23:11,040 --> 01:23:14,360
Speaker 1: to you know, where does one go? I have sent

1452
01:23:14,400 --> 01:23:17,920
Speaker 1: a note to Google to say, hey, this is all wrong.

1453
01:23:18,160 --> 01:23:19,800
Speaker 1: I don't know how much more to tell you this

1454
01:23:19,840 --> 01:23:25,040
Speaker 1: is all wrong, and you know it's it's it gets

1455
01:23:25,040 --> 01:23:26,719
Speaker 1: into a large you know, this could have been something,

1456
01:23:27,120 --> 01:23:30,160
Speaker 1: you know, truly defamatory, could have been something horrendous. You

1457
01:23:30,160 --> 01:23:32,760
Speaker 1: could be accused of a crime. You know where do

1458
01:23:32,840 --> 01:23:33,599
Speaker 1: you who?

1459
01:23:34,040 --> 01:23:34,280
Speaker 4: You know?

1460
01:23:34,439 --> 01:23:37,600
Speaker 1: Do I can I control what is said about me,

1461
01:23:37,800 --> 01:23:40,080
Speaker 1: especially when it's not true what is said about me?

1462
01:23:40,120 --> 01:23:42,360
Speaker 1: And look, as somebody who's been a public figure, there's

1463
01:23:42,360 --> 01:23:44,840
Speaker 1: been plenty of garbage said about me that hasn't been true,

1464
01:23:44,880 --> 01:23:46,840
Speaker 1: plenty of garbage that has been set about my family

1465
01:23:46,840 --> 01:23:49,240
Speaker 1: that isn't true. And for the longest time we all

1466
01:23:49,280 --> 01:23:51,680
Speaker 1: just sort of ignored it. We figured, oh, you know,

1467
01:23:51,880 --> 01:23:54,160
Speaker 1: it sort of will go, you know, the non truth

1468
01:23:54,200 --> 01:23:56,960
Speaker 1: stuff just sort of goes away and dies. But what

1469
01:23:57,000 --> 01:24:00,000
Speaker 1: has happened with these all these AI tools, these large

1470
01:24:00,160 --> 01:24:04,200
Speaker 1: language models have trained themselves on the garbage that has

1471
01:24:04,240 --> 01:24:07,200
Speaker 1: been saved on the internet. So even if you know,

1472
01:24:07,280 --> 01:24:10,040
Speaker 1: take Gemini. In this AI business, it's probably eighty five

1473
01:24:10,080 --> 01:24:13,719
Speaker 1: percent correct, which is B plus right BB plus material.

1474
01:24:13,880 --> 01:24:17,040
Speaker 1: The problem is that fifteen percent that is wrong taints

1475
01:24:17,080 --> 01:24:20,200
Speaker 1: at all. And this is the inherent flaw right now.

1476
01:24:20,280 --> 01:24:22,559
Speaker 1: I think in where we are in AI, I hope

1477
01:24:22,560 --> 01:24:25,240
Speaker 1: this is a good lesson right, like the Grock incident

1478
01:24:25,640 --> 01:24:28,040
Speaker 1: with how quickly you know? And Elon Musk wanted to

1479
01:24:28,040 --> 01:24:29,920
Speaker 1: do He didn't like the answers that groc was giving

1480
01:24:29,960 --> 01:24:31,559
Speaker 1: and he wanted to give new answers, and suddenly he

1481
01:24:31,640 --> 01:24:38,680
Speaker 1: created a Nazi AI persona you know I. You know,

1482
01:24:38,960 --> 01:24:42,360
Speaker 1: maybe by sharing this story more people will to understand

1483
01:24:42,400 --> 01:24:44,720
Speaker 1: is that that AI is not all knowing A has

1484
01:24:44,720 --> 01:24:48,200
Speaker 1: got a lot more flaws right now, and an inherent

1485
01:24:48,240 --> 01:24:51,400
Speaker 1: flaw is what you the data you have trained the

1486
01:24:51,479 --> 01:24:57,240
Speaker 1: AI on right. And Google doesn't fully appreciate that there

1487
01:24:57,320 --> 01:25:00,519
Speaker 1: is a lot of garbage, particularly about public figures that

1488
01:25:00,600 --> 01:25:06,200
Speaker 1: isn't true for a variety of reasons, right, And nobody

1489
01:25:06,280 --> 01:25:09,960
Speaker 1: is saying they have to fact check everything, but you know,

1490
01:25:10,000 --> 01:25:15,639
Speaker 1: there's got to be some form of of truthiness that

1491
01:25:15,640 --> 01:25:18,599
Speaker 1: that is there, and a consumer, whoever it is, an

1492
01:25:18,680 --> 01:25:23,680
Speaker 1: individual has got to have some right to correct you

1493
01:25:23,680 --> 01:25:26,960
Speaker 1: know a right to get this, you know, because this again,

1494
01:25:27,600 --> 01:25:32,160
Speaker 1: I you know, this is not being accused of having

1495
01:25:32,160 --> 01:25:34,280
Speaker 1: a disease that you don't have, is not you know,

1496
01:25:34,320 --> 01:25:37,519
Speaker 1: it's not going to you know, cause me problems personal

1497
01:25:37,680 --> 01:25:41,280
Speaker 1: whatever it is, that's not the issue. I don't. You know,

1498
01:25:41,320 --> 01:25:43,160
Speaker 1: this is not fair to people that are dealing with

1499
01:25:43,160 --> 01:25:46,240
Speaker 1: Parkinson's whose stories should be told and who's you know,

1500
01:25:46,320 --> 01:25:49,519
Speaker 1: should be and things like that. So I just wanted

1501
01:25:49,520 --> 01:25:52,200
Speaker 1: to share this story because this is a warning. All right,

1502
01:25:52,560 --> 01:25:56,519
Speaker 1: AI is very flawed right now, Okay, I have a

1503
01:25:56,560 --> 01:26:01,880
Speaker 1: personal experience with it, and clearly Google's AI is not

1504
01:26:02,160 --> 01:26:05,040
Speaker 1: as and yet what is Google doing every time you

1505
01:26:05,080 --> 01:26:08,320
Speaker 1: do a Google search it produces the AI overview. First,

1506
01:26:08,400 --> 01:26:11,479
Speaker 1: I watch my son. He just takes AI overview and

1507
01:26:11,520 --> 01:26:15,080
Speaker 1: just assumes it's fact. And you know, like the early

1508
01:26:15,200 --> 01:26:19,240
Speaker 1: days of Wikipedia, there's a lot of manipulation still out there.

1509
01:26:19,280 --> 01:26:21,559
Speaker 1: I'm not saying that over time this won't get better

1510
01:26:22,120 --> 01:26:24,839
Speaker 1: as these AI, but to put it out there in public,

1511
01:26:24,840 --> 01:26:26,679
Speaker 1: I mean, this is what happens when these tech companies

1512
01:26:26,800 --> 01:26:30,519
Speaker 1: essentially want to test their technology out in public, sort

1513
01:26:30,560 --> 01:26:34,400
Speaker 1: of let it all crowdsource the problems away. Well, there

1514
01:26:34,439 --> 01:26:38,840
Speaker 1: are people that get caught up in that crowdsourcing of

1515
01:26:39,280 --> 01:26:44,240
Speaker 1: information where you may defame them, you may harm them,

1516
01:26:44,600 --> 01:26:47,040
Speaker 1: you may do harm to them, or you may cause

1517
01:26:47,080 --> 01:26:50,760
Speaker 1: them so much anxiety they do self harm. So I

1518
01:26:50,800 --> 01:26:55,719
Speaker 1: share the story. I hope Google. I am happy whoever's

1519
01:26:55,760 --> 01:26:59,280
Speaker 1: listening from Google, I am happy to participate. So you

1520
01:26:59,320 --> 01:27:02,640
Speaker 1: guys need to figure out why how this happened. I'm

1521
01:27:02,720 --> 01:27:05,479
Speaker 1: happy to help out in any way if I can

1522
01:27:05,560 --> 01:27:09,519
Speaker 1: help you, Because look, I'm not an AI skeptic. I

1523
01:27:09,560 --> 01:27:12,160
Speaker 1: want to. I want to. This is a probability. You know,

1524
01:27:12,640 --> 01:27:15,360
Speaker 1: I know what AI is. It's not intelligence, it's not

1525
01:27:15,720 --> 01:27:19,639
Speaker 1: you know, a robot. It is simply probability. Uh, it's

1526
01:27:19,720 --> 01:27:23,160
Speaker 1: it's a probability, uh, sample of of what you know,

1527
01:27:23,600 --> 01:27:26,559
Speaker 1: what's likely to be said next, what's the next word,

1528
01:27:26,560 --> 01:27:29,559
Speaker 1: et cetera. So I'm you know, I'm I am pro

1529
01:27:30,360 --> 01:27:32,960
Speaker 1: the concept of continuing to try to make this work.

1530
01:27:33,600 --> 01:27:38,879
Speaker 1: But it's possible. We haven't fully uh Uh. This stuff's

1531
01:27:39,280 --> 01:27:42,960
Speaker 1: half baked and it's being released to the public, probably

1532
01:27:43,080 --> 01:27:44,840
Speaker 1: in an attempt to try to catch up to the

1533
01:27:44,880 --> 01:27:47,600
Speaker 1: folks over at Open AI. Why why Google's doing this

1534
01:27:47,640 --> 01:27:49,519
Speaker 1: and all this stuff? And they're pushing it out there

1535
01:27:49,960 --> 01:27:52,720
Speaker 1: for for a variety of reasons on that. Maybe it

1536
01:27:52,720 --> 01:27:55,439
Speaker 1: has to do with making it look like they're on Hey,

1537
01:27:55,520 --> 01:27:58,479
Speaker 1: we have AI tools too, but I'm here to tell

1538
01:27:58,520 --> 01:28:03,200
Speaker 1: you this AI tool ain't working the way it's supposed to.

1539
01:28:03,920 --> 01:28:06,960
Speaker 1: And anybody that's been in the public space, like myself,

1540
01:28:07,000 --> 01:28:10,120
Speaker 1: who has had so much bullshit written about them, stuff

1541
01:28:10,160 --> 01:28:12,080
Speaker 1: that's not true. This is how it can all get

1542
01:28:12,160 --> 01:28:18,760
Speaker 1: cobbled together and create literally a fictional story that the

1543
01:28:18,800 --> 01:28:20,680
Speaker 1: only thing that is correct is that I've worked for

1544
01:28:20,800 --> 01:28:24,280
Speaker 1: NBC and my name is Chuck Tad. All right, let

1545
01:28:24,320 --> 01:28:27,240
Speaker 1: me deal with a couple of questions there. So, Helena Khan,

1546
01:28:27,600 --> 01:28:29,360
Speaker 1: I didn't I would have told you about that, but

1547
01:28:29,360 --> 01:28:31,000
Speaker 1: I didn't want to make the interview about that. But

1548
01:28:31,560 --> 01:28:35,120
Speaker 1: the FTC come on, Where where do we go as

1549
01:28:35,160 --> 01:28:42,080
Speaker 1: citizens to essentially correct when our persona is misidentified and

1550
01:28:42,120 --> 01:28:48,800
Speaker 1: miss h and frankly just wrong by the by by

1551
01:28:48,840 --> 01:28:51,519
Speaker 1: one of these big tech companies on this front. All right,

1552
01:28:51,640 --> 01:28:58,320
Speaker 1: let's do a couple of ask Chucks, Ask Chuck. Okay,

1553
01:28:58,600 --> 01:29:02,000
Speaker 1: first question comes from the Essa in Charleston, South Carolina,

1554
01:29:03,120 --> 01:29:08,200
Speaker 1: home arguably to one of the best eating towns in America,

1555
01:29:09,640 --> 01:29:12,000
Speaker 1: probably at least you know, in the top five, not

1556
01:29:12,600 --> 01:29:15,040
Speaker 1: tops of New Orleans. But it's if I said about Charleston,

1557
01:29:15,120 --> 01:29:19,120
Speaker 1: it's New Orleans without the refraff, and yet some of

1558
01:29:19,200 --> 01:29:20,880
Speaker 1: us do like the riffraff in New Orleans. Don't get

1559
01:29:20,880 --> 01:29:23,400
Speaker 1: me wrong, but here's the question. If the Trump administration

1560
01:29:23,479 --> 01:29:25,880
Speaker 1: is so adamant about deporting violent illegal criminals, why didn't

1561
01:29:25,880 --> 01:29:28,519
Speaker 1: they start by clearing out the prison system. Republicans love

1562
01:29:28,520 --> 01:29:30,599
Speaker 1: to use Lake and Riley as their example for ridding

1563
01:29:30,640 --> 01:29:34,400
Speaker 1: America of this dangerous criminals, but her killer, Jose Antonio Evara,

1564
01:29:34,520 --> 01:29:36,320
Speaker 1: is still sitting in a Georgia prison living off of

1565
01:29:36,320 --> 01:29:38,800
Speaker 1: taxpayer dollars. It seems that if Republicans were serious about

1566
01:29:38,800 --> 01:29:40,840
Speaker 1: cleaning up fraud, waste, and abuse, this would be a

1567
01:29:40,880 --> 01:29:42,880
Speaker 1: good place to start. Instead of rounding up migrant workers

1568
01:29:42,920 --> 01:29:45,160
Speaker 1: from the fields they are working in people off the

1569
01:29:45,160 --> 01:29:48,400
Speaker 1: streets who may actually be US citizens. Am I missing something, Vanessa,

1570
01:29:48,439 --> 01:29:51,000
Speaker 1: You're not. You know, I don't have a good answer

1571
01:29:51,080 --> 01:29:54,439
Speaker 1: to this question other than boy, that's a really What

1572
01:29:54,479 --> 01:29:57,160
Speaker 1: I want to do is send this over to whoever's

1573
01:29:57,160 --> 01:29:59,840
Speaker 1: going to interview Christino next. Right, this is a ter

1574
01:30:00,479 --> 01:30:02,600
Speaker 1: question that needs to be asked if I get an

1575
01:30:02,640 --> 01:30:06,080
Speaker 1: opportunity to ask anybody in the in the DHS system,

1576
01:30:06,160 --> 01:30:09,519
Speaker 1: whether it's Stephen Miller, who I may you know, whether

1577
01:30:09,520 --> 01:30:12,519
Speaker 1: it's for my newsphere show or here So I did.

1578
01:30:12,600 --> 01:30:15,240
Speaker 1: It's a terrific question and I want to know the

1579
01:30:15,240 --> 01:30:18,080
Speaker 1: answer to that, and hopefully somebody listening also wants to

1580
01:30:18,120 --> 01:30:22,040
Speaker 1: know the answer to that. That is a outstanding observation.

1581
01:30:22,960 --> 01:30:26,439
Speaker 1: Second question comes from Jeff H. By the way, like

1582
01:30:26,520 --> 01:30:31,280
Speaker 1: you know, if you're absolutely right sidey, that seems to

1583
01:30:31,320 --> 01:30:33,439
Speaker 1: be would probably I bet you if you pulled that question,

1584
01:30:33,640 --> 01:30:40,000
Speaker 1: should American tax dollars be used to how's criminals who

1585
01:30:40,200 --> 01:30:43,280
Speaker 1: are here illegally? I have a feeling I know how

1586
01:30:43,360 --> 01:30:47,599
Speaker 1: that would how that poll question would go. This next

1587
01:30:47,680 --> 01:30:49,800
Speaker 1: question comes from Jeff H. He says, what do you

1588
01:30:49,840 --> 01:30:52,720
Speaker 1: think about eighteen years for term elaments on senators and representatives?

1589
01:30:52,720 --> 01:30:54,920
Speaker 1: We've got to get people out of these positions before

1590
01:30:54,920 --> 01:30:57,760
Speaker 1: they become decrepit. Jeff, here's all I want to tell you.

1591
01:30:57,840 --> 01:31:03,200
Speaker 1: I'm on Monday next week. I'm dropping an interview with

1592
01:31:03,439 --> 01:31:09,080
Speaker 1: Larry Lessik, who is a Harvard Law School professor who

1593
01:31:09,479 --> 01:31:16,120
Speaker 1: is focused and he's got this campaign finance law that

1594
01:31:16,200 --> 01:31:20,280
Speaker 1: has passed in Maine that the Feds are that some

1595
01:31:20,400 --> 01:31:24,480
Speaker 1: are trying to say is unconstitutional. But if they successfully

1596
01:31:24,600 --> 01:31:26,240
Speaker 1: argue their case, he thinks he might be able to

1597
01:31:26,280 --> 01:31:31,280
Speaker 1: make super Pack essentially obsolete right by limiting all donations

1598
01:31:31,280 --> 01:31:33,200
Speaker 1: to super packs to five thousand dollars. I'm not going

1599
01:31:33,200 --> 01:31:35,960
Speaker 1: to get into the details of this, but in that conversation,

1600
01:31:36,600 --> 01:31:39,200
Speaker 1: Larry and I talk about the idea of a constitutional convention,

1601
01:31:39,400 --> 01:31:42,720
Speaker 1: because ultimately term limits would have to be put in

1602
01:31:42,760 --> 01:31:46,560
Speaker 1: the constitution. That the only way you can make it constitutional.

1603
01:31:47,479 --> 01:31:50,120
Speaker 1: And there's a lot of argument to be made. We're

1604
01:31:50,280 --> 01:31:53,519
Speaker 1: due for a constitutional convention. Deal with campaign money, right,

1605
01:31:53,600 --> 01:31:55,960
Speaker 1: things that the Supreme Court is said is unconstitutional, deal

1606
01:31:56,000 --> 01:32:00,160
Speaker 1: with campaign money, deal with age limits, term limits. It's

1607
01:32:00,200 --> 01:32:02,240
Speaker 1: you know, maybe you do it as age limits we have,

1608
01:32:02,560 --> 01:32:05,040
Speaker 1: we have age minimums to run for office, right, twenty

1609
01:32:05,040 --> 01:32:06,920
Speaker 1: five for the House, thirty for the Senate, thirty five

1610
01:32:06,920 --> 01:32:09,679
Speaker 1: for the presidency. I'd argue those are kind of obsolete now,

1611
01:32:10,120 --> 01:32:13,200
Speaker 1: you know, you know, should there really you know, maybe

1612
01:32:13,240 --> 01:32:15,519
Speaker 1: you just if you're eligible to be in Congress of

1613
01:32:15,560 --> 01:32:18,080
Speaker 1: twenty five, why is there you know, why make a

1614
01:32:18,080 --> 01:32:20,519
Speaker 1: difference on the Senate and the presidency at that point.

1615
01:32:20,920 --> 01:32:24,000
Speaker 1: But if you're going to put in age maximum, since

1616
01:32:24,040 --> 01:32:26,880
Speaker 1: age minimums are in the constitution, age maximums have to

1617
01:32:26,920 --> 01:32:28,960
Speaker 1: be in the constitution. So I think this is a

1618
01:32:29,520 --> 01:32:31,759
Speaker 1: is it eighteen years? I think eighteen years for instance,

1619
01:32:31,800 --> 01:32:34,080
Speaker 1: is a I'd call that a generation right? And is

1620
01:32:34,120 --> 01:32:36,599
Speaker 1: it eighteen years collectively? Right? That? Or is it eighteen

1621
01:32:36,640 --> 01:32:40,920
Speaker 1: years in each chamber too? That that's another question that

1622
01:32:41,600 --> 01:32:44,960
Speaker 1: some might have. But a good constitutional convention, balance budget

1623
01:32:45,000 --> 01:32:47,360
Speaker 1: amendments another thing where you might have some some people

1624
01:32:47,360 --> 01:32:48,800
Speaker 1: on the right want this, some people on the left

1625
01:32:48,840 --> 01:32:52,240
Speaker 1: want this, you know, just like the original constitutional convention,

1626
01:32:52,439 --> 01:32:57,439
Speaker 1: you would get some interesting compromises. And I'm going to

1627
01:32:57,520 --> 01:33:00,760
Speaker 1: leave it at there. This is the long one. And

1628
01:33:01,400 --> 01:33:04,120
Speaker 1: on that so I've got a bunch of other questions.

1629
01:33:04,160 --> 01:33:06,760
Speaker 1: We'll save it. We'll save it for We'll save some

1630
01:33:06,800 --> 01:33:08,439
Speaker 1: of them for next week. I promise you know me,

1631
01:33:08,520 --> 01:33:11,280
Speaker 1: I will get to all of them. That is the goal.

1632
01:33:11,360 --> 01:33:14,000
Speaker 1: All right. With that, I hope you enjoy your weekend

1633
01:33:16,360 --> 01:33:19,080
Speaker 1: and I will see you in about seventy two hours

1634
01:33:19,160 --> 01:33:20,759
Speaker 1: or so until we upload again.