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Welcome to Unlimited Hangout

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I'm your host. Whitney Webb. For much of the year this podcast

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has been exploring the phenomenon of the PayPal

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Presidency. That is the extremely significant influence

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of the PayPal Mafia and their allies in Silicon Valley on the

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current Trump administration from healthcare to finance and

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beyond. Today, we will be taking a look at how big tech

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neoconservative think tanks and the Trump administration are

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shaping current education policy, including the so called

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school choice movement and the promised dismantling of the

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Department of Education, that seem at first glance to be about

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reducing federal control over education. However, the deeper

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reality is anything but. Other education policies we will be

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interrogating today include efforts by the current

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administration to control anti-war protests on campuses

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under the guise of combating quote, unquote anti semitism, as

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well as how this effort and other potential future efforts

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to control speech in classrooms and on campuses could soon be

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aided by the growing importance of the FinTech industry On

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education funding, we will also touch on how AI analytics of

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students, learning metrics and other data harvested by big tech

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are being used to steer and determine children's futures.

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Joining me to discuss these topics and more, is John

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Klyczek. John has a master's in English and has taught college

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rhetoric and research argumentation for over a decade.

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He is the author of the book School World Order, and is a

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contributor to several publications, including

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Unlimited Hangout. Today we will be focusing on John's recent

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pieces for Unlimited Hangout on Education Policy, the first

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School Choice Corporatization, Social

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Impact Finance, and the Dismantling of the Department of

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Education, and the most recent being From Project 2025 to the

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School Choice Fin-Tech for a Blockchain Social

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Credit Economy. Thanks for joining me today, John, and

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welcome back to Unlimited Hangout.

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It's great to be here. Whitney, thanks for having me back.

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Of course, my pleasure. So a lot of your recent work on

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education for Unlimited Hangout has focused on the groups behind

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the so called school choice movement. And school choice

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sounds like a good thing just looking at the term

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superficially. So why do you believe this movement is hiding

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ulterior motives and who benefits?

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Well, I mean, you know the reason why I think that it's not

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a great thing was many, many years back, and it really stems

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from the research of my mentor, Charlotte Thomson Iserbyt, who

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worked in the with the Ronald Reagan administration. She was a

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Senior Policy Advisor in the Department of Education, and she

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blew the whistle on something called Project Best, that's

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basic education skills through technology. It was a program to

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set up public private partnerships between big tech

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companies, Department of Education, other local education

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agencies, in order to set up, basically operating conditioning

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through computerized education. And I've written a few pieces at

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Unlimited Hangout, sort of tracing the history of that and

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how it ties in something called UNESCO study 11, and how,

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basically, how that set the groundwork for all things global

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ed tech and fourth industrial revolution. But during her time

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at the Department of Education under Reagan, she was also a

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liaison with a task force on private sector initiatives, and

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during her time there, she's part of that private sector

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initiative, was the school choice movement, and as the

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liaison, she basically asked the question, isn't this like

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corporate fascism? And they're all kind of like, Gee,

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Charlotte, we didn't think about it like that. And then, you

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know, they moved her to another office at that point. But you

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know, is the way that she pointed it out from day one.

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It's essentially, you know, she wouldn't use stakeholder

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capitalism. Was the wouldn't even been the phrase she used,

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but it's public private partnerships. It's the merger of

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corporations in the state. That's, you know, sort of

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Mussolini's definition of fascism. Yeah, it's probably an

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apocryphal quote, but colloquially, we understand that

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to be his definition corporate fascism. And today we would call

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that, you know the stakeholder capitalism, right? It's the

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mixture of the public and private on a global scale. So

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basically, it's stakeholder capitalism for schools. It's

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going to subsidize private companies with public tax

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dollars, and it's also going to remove any sort of civil

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process, right? So you're not going to have a local school

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board to parts of this. The school choice movement, more

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broadly is the charter schooling movement, which is pretty much

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locked in. So charter schools are private corporations that

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are subsidized with public tax dollars. But then this next

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round school choice is basically these different funding

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mechanisms. So, you know, we might just call them all

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vouchers colloquially. I think part of the reason why they've

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come up with these different terms, like education savings

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accounts and scholarship granting organizations or tax

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credited scholarships is largely to kind of muddy the waters make

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it harder to figure out what what they're doing. Now there

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are some there are some nuance differences between how the

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money is distributed and access between, you know, traditional

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voucher, an ESA and a tax credit. But basically what they

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all have in common is you're taking public tax dollars

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instead of subsidizing a school or a, you know, a charter

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school, private corporation, you're just you're subsidizing a

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basket of could be a charter school, could be a private

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school, could be a religious school, or could just be any

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range of ed tech products and services, you know, including

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now they're adding into a therapy so, like mental health

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services as well, that you know, could be also service with

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different technologies we might talk about. So ultimately,

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right? All that, all that together is indicates that, you

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know, with the charter, as I mentioned, with the charter

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schools, there's no they, they don't have an elected board,

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right? And the same thing with if you take those those

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vouchers, or those ESA monies, and you purchase, you know, your

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tech products, I mean, essentially, you're being

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serviced again, by a company that doesn't have an elected

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board. So whether it's the charter schooling system or the

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sort of Neo voucher system, the school choice movement, again,

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right? It's basically destroying the public sector. It's

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privatizing everything, and then it's also cutting off any, any

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routes that we would have had towards any court of civic

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recourse, right, through an elected school board. So those,

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those are all the bad things about school choice.

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So in that kind of scenario, what happens to the kids that

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can't go to these private institutions that are, like, the

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bulk of public school students, right?

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That's the thing. I mean, that's like, if you really think

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about the situation, right? So the pitch is that, Oh, fun

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schools, or fun students, not schools, right? And the idea is

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that, well, how is it fair that you know, if you're stuck in

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this zip code, that you should be forced to have to go to that

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school? You should have an option if you want. And so the

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pitch, you know, like people like Corey DeAngelis, the people

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that are really selling this, if you, if you listen to the

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buzzwords and the sloganeering, it almost sounds like these,

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these students in these impoverished zip codes are going

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to be able to take their voucher money and go to like, some elite

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private school, okay, let me

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that's the sales pitch. Yeah, they're

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nowhere nearby. Okay, so the first problem is transportation,

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if you're in a very impoverished neighborhood, right? It might be

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a food desert, and also, you know, have problems with

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transportation. Now you can use some of your voucher money for

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transportation, but then you're not going to have as much left

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over for the tuition if you could even get to that school.

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The other thing is, the amount that they're going to give you

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with these various esas, vouchers, scholarships, etc,

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wouldn't cover the entire tuition anyways. So where is

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the, where is all that money going to go for the average

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student that actually, you know, really wants to get out of the

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stuck position they're in with whatever, you know, with their

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public school, with their with their so called government

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school, you know, the main thing that's going to be their option

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is maybe there's a charter school nearby, or maybe they

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could go to another public school in a nearby district, but

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most likely, most of that's going to go to ed tech products

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and services that can be serviced online, right, in their

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home, right? So basically turning your home into the

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government school, because with that vouchers comes the

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government regulations, right? So a lot of the other pitch was

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that, oh, you're going to get rid of the woke stuff. And, you

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know, during lockdowns, everybody, you know, that didn't

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want their experimental gene therapy, you know, they exited

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the schools thinking that, right? This whole they're going

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to build this homeschooling Co Op pod movement, and they're

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going to sort of create a parallel structure. Well, that

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could be the case. But if you take that voucher money, as I've

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showed in the first article in this series, at the state

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levels, the Federal pitches are based on all of those come with

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some sort of strings attached, right? And some of them include,

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like, you have to be up on all your health code regulations,

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which would mean, right? You'd have to have your your

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experimental gene therapy, right, and so all of that to say

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that right, the money that you're going to get right is

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going to be largely, is going to be used for bringing in

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government regulations into a quote, unquote homeschool

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environment, and also bring. In big tech to data mine the

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students in your home as well, and so you know that's, that's

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what those children are going to get with those vouchers. Okay,

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so a few months ago, Catherine Boyle, who's a general

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partner at Andreessen Horowitz, which is a VC firm that's very

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much in the PayPal Mafia orbit via Marc Andreessen and other

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figures told an audience at the neocon think tank the American

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Enterprise Institute a few months ago that, quote,

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technology is the backbone of the education choice movement,

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meaning school choice. So how are Silicon Valley, quote,

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unquote, Libertarians and some of the people in Silicon Valley

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backing these pandemic pods and kind of these, this parallel

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idea of a parallel system, at least, you know, publicly. And

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how are they teaming up with neoconservatives to sort of

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shape the role of technology in US schools, whether it's public

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schools or some of these schools that you know, you know, the

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Silicon Valley people are sending their kids to,

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yeah, well, it's interesting to note that, I mean, right

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there, you have a connection between an executive At

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Andreessen Horowitz and also one of the coke backed state policy

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network think tanks known as the American Enterprise Institute,

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and one of their representatives is actually one of the authors

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of project 2025 and the project 2025 education section does call

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For they wanted to transform a certain portion of Title One

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funds into esas, right, ESA vouchers. And then they also

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wanted to push this ecca bill that would basically get tax

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credited scholarships authorized. Now they didn't pass

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that, but the quote, unquote, big, beautiful Bill did ram

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through something that actually kind of combines the worst parts

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of both of those bills. So like the scholarships for the ecca

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was just supposed to go to for tuition for schools, but what

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they have now is this tax credited scholarship program so

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they can use it for a basket of curricular materials,

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educational therapies, personal tutors, etc, etc, okay. And so

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just, that's just one little example of sort of where, like

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the Silicon Valley venture capitalist tech bros, sort of

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overlap with sort of the old school neocon Koch brothers

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think tank consortium. And so do a couple of ways that that sort

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of the Silicon Valley arm of this, this partnership, is

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pushing sort of Ed technocracy. So one we could look at would be

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the FinTech angle. The other one would be the actual educational

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technology products that would be funded by the FinTech

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product. So in general, what we have is they want to service

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these vouchers, scholarships, education savings accounts, et

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cetera. They want to service these through these digital

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wallets. And so you have a range of various companies to do this.

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So one's called Class wallet. Another is called Odyssey.

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Another is merit International. Another is student first

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technologies, and then you have another one called SAP araba. So

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I can sort of break down some of the Silicon Valley venture

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capital connections to some of these companies, and then we can

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talk about how they, how they are used to facilitate the

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funding of the ed tech products through those through those

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voucher systems. So class wallets been around for a while.

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It's been funded by Lazard partners. And Lazard

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Incorporated is a partner with the World Economic Forum. Lazard

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has people that have worked for Lazard that are notable, being

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Nathaniel Rothschild, who's actually a Young Global Leader

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of the WEF, and another one would be Vernon Jordan. Vernon

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Jordan being a close, sort of an advisor to Bill Clinton, I

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believe

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he's the one that took Clinton to Bilderberg, didn't

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he? Yeah, yeah.

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I believe he's one, and brought him to Bilderberg, yeah,

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and he's trilateral as well. And Clinton, again, his world, world

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economic forum. So I know it all that because I want to keep, I

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want to know these World Economic Forum connections,

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because this is right all the the base right wing people that

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think that Trump is like, somehow this foil to the W, E,

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F. I mean, only in so far as it's a dialectic, but not an

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actual. Oh, absolutely,

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yeah. Mark Goodwin and I were saying that, like, January

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of last year, that basically, you know, everything that they

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had tried to sell through the public sector during the COVID

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era, they were going to squirrel it away and try and market it

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through the private sector and from the right instead of. Left,

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yeah, after they demolish trust with COVID, the, you know, the

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the World Economic Forum's goal after that openly stated, was

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rebuild trust. And how do you do that? Well, you you build up the

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opposition, or what looks like the opposition, and you sell the

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same policies through the opposition, right? Yeah, yeah.

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Like Andreessen Horowitz is, I think they're part of the W E

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F like blockchain digital council would not surprise me. I

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got a screenshot of the actual profile up there, and in the

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article, you know that SAP araba company, that's a WEF partner,

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or the parent company is okay, and then that company partners

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with IBM and Amazon, both W E, F partners Peter Thiel, WEF,

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but yeah. So, so other, some of these other companies, FinTech

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companies, that are facilitating these digital wallets, when

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would be Odyssey? Now, Odyssey is funded by Andreessen

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Horowitz. Andreessen Horowitz also funds merit International

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and Odyssey also won the Yass prize for what they call stop

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education. So it's sustainable, transformative, outstanding and

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permissionless education. And Jeff Yes, another billionaire,

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eyes is also supported by Jean Allen center for educational

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reform. Cer I believe I got those words right in the

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acronym, and she's somebody that's partnered with Bill

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Bennett to push was voucher scholarships, or ESA is one of

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those programs, and Bill Bennett was the guy that set up first

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online charter school, former Secretary of Education under

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Ronald Reagan after Charlotte left and K 12, Inc, basically,

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you know, brought in sort of the this online corporate charter

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school industry, which also provided the online platforms

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through which you integrate all these other applications that we

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might mention. So some of these would be like adaptive learning

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course, where, like clever and Newton, these are both funded by

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Peter Thiel. Basically, this is the modern digital version of BF

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Skinner's teaching machine. So it's using operant conditioning

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algorithms that basically trains train students for performative

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compliance. You have something like Course Hero and simbo lab.

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So Course Hero, basically platform, symbol lab. Symbol lab

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is more adaptive learning. Stuff that's been funded by craft

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ventures, which is saxes venture capital firm Andreessen Horowitz

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has funded Udacity and a company called effective, which I've

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written about going all the way back to my book, basically, it

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specializes in what they call social emotional learning. So

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the adaptive learning courseware is going to data mine students

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thinking algorithms or behavioral algorithms. The

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social emotional learning stuff is going to basically data mine

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their effective or emotional algorithms, and that's going to

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be done through like wearables. So either EEG wearables brain

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waves, or EKG wearables, a data mine heart rates.

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Well, HHS has recently announced that they're all

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behind the mass use of wearables and that it's a major priority

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for them. So having it become a priority also for education

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policy, I guess that means they're going to be they're

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going to try and make them be everywhere soon.

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I wrote a piece once upon a time in I think Natural News was

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the only people that put it up, and it's called Precision

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Medicine Initiative. There's two it's a two part series. I can't

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remember. The subtitle is the second one. And the second one,

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I looked at a guy by the name of Eric Dishman. And Eric Dishman

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had this was the head of this thing called all of us. And it

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was this project, like, basically. So precision medicine

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is where they want to basically make personalize your your

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medicine just like you want to personalize your learning. So

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that means AI analytics, but in particular, for medicine, right?

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Analytics, extrapolating correlations between your DNA,

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your actual genes, genetics, and your environment as well. So

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what Dishman was known for before he got on the all of this

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experiment was smart homes for people with Alzheimer's, okay?

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And so basically, what he the project was to come up with,

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it's sort of an epigenetic study. So it's to take a look

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at, like, what sort of genetic predispositions Do you have?

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Data, mine what you're doing all day. What are you eating? How

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many steps do you get right your your activities and see what

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correlations between your activities in the environment

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might trigger, right, the pathological expression of a

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particular gene, etc, right? And so I've said, I said it a long

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time ago, and I was, you know, I speculated. I said, you know, I

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feel like, you know, I Bobby, I was, you know, you. Me some hope

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during the during the lockdown years, but when I sort of looked

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into some of his investments, I was in the and they let him in

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there, and then they put Jim O'Neill in behind him. I'm like,

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we're gonna see wearables all over people. I bet you we're

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gonna see the Dishman problem. And I guess I was right.

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Oh yeah, totally. Well, it goes back to what I was sort of

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saying about the the rebrand of the quote, unquote opposition

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during the COVID era. A lot of those people were the big names

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recorded by, you know, Neo cons, or Neo conservative adjacent

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types, like during COVID. I mean, you had people like Frank

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Gaffney creating websites like stop vaccine, passports and

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stuff. And Gaffney used to work under Richard Pearl, if I'm not

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mistaken. I mean, he's like a well known Neo conservative

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figure, and Pearl helped create Palantir, among other things,

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which is, you know, I mean, the more you look at the Silicon

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Valley, quote, unquote, libertarian types that have been

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really elevated in the last election cycle or so by figures

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like Trump and also, like in Argentina of Malay, a lot of

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them have a surprising amount of overlap with the Neo

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conservatives who I you know, have, at least you know, in

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terms of what their policy solutions are for things. And I

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think that's, you know, neocons used to be so hated in the US,

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and now this very successful rebranding and built, rebuilding

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of trust has allowed them to, basically, you know, continue

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pursuing, you know, their policies under, you know

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different names, basically. And so I think that's why it's very

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interesting that it's also happening in education, among

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among other areas. But I think it's been a very successful

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rebrand. And it's not exclusive to, you know, where these guys

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most often operate, which is, you know, finance or social

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media, or some of the things we most you know are most publicly

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associated with Silicon Valley. You know, it's, it's really a

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partnership that is permeating through everything is very bad,

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and a lot of these, I mean, I think the wearable thing is

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definitely something to watch. I know in the past, you've covered

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it pretty extensively for unlimited Hangout, where it sort

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of fits in with the education stuff. But this push to have it

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be in healthcare, and I'm sure there'll be, you know, pushes to

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have it, you know, for other reasons too, at some point, you

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know, it's, it's gonna get it's gonna get weird. And also, a lot

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of these people that are known, you know, Silicon Valley

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billionaires that are known for funding a lot of the suspect

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stuff in healthcare and also education, like Bill Gates, if

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I'm not, if I, if I remember correctly, he, like, funded a

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wearable that was being piloted in New York State for students

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where, like, if they weren't paying attention, it would like

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give them a light shock. It's like a shock collar, basically,

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but like, it's on your wrist or something like that. I mean,

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just absolutely, I don't know. And I mean, I have like, a seven

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year old in, you know, basically, kind of a public

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school here, and she, like, gets distracted. I mean, she's just

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an easily distracted kid. I can't imagine her having to go

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through that kind of stuff at school. Or, like most kids, you

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know, yeah, I know what you're

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talking about. It was a galvanic skin response monitor

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they called GSR. Like, through skin conductivity, they're

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supposed to be able to infer some sort of the emotional

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intensity that you're experiencing, but they have to

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kind of correlate it with other other metrics. I don't know

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about the shock part, but I do know that Amazon, which I also

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wrote about my book, did have something like that. I don't

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know if it was a shock, but it's like a it's a very disturbing

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vibration, I guess, you know, like, it's like, that's

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what it was, it was, it was, it was that, but it basically

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came across as being like, you know, a nice version of a shot

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caller. I probably shouldn't have said that in the sense that

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it's not exactly accurate, but I think that the idea of, like,

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giving you a jolt that's non painful, or whatever to you

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know, because the algorithm decided that you're too

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distracted from learning. I don't know. We don't need that

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kind of stuff for our kids, obviously. I mean, it's just so

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bonkers.

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It's entirely skin area, right? So, I mean, you know,

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familiar, but you know, it's basically a very simple system

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of punishments and rewards with four quadrants, so positive and

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negative punishment. And negative, punishment, reward,

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positive and negative just means adding or removing stimulus,

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okay? And so the idea that is that, you know Skinner,

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basically believe he wrote a book called Beyond freedom and

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dignity. So for him, there is no bad students. A bad student is

401
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just the student whose environment has not conditioned

402
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them to respond appropriately, right? And so it's the best mix

403
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of reward and punishment or stimulus response is going to

404
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get the student to so called, learn, right? Or, in other

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words, to be programmed the way that that you want that student

406
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to be programmed. Now, if you believe that humans are

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basically just little widgets in a supply chain, I guess that's a

408
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great way to make things efficient. But if you believe

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that human. Beings are agents that have, you know, soul, or at

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least a consciousness. Yeah, it's pretty it's pretty

411
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horrific,

412
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yeah, just say the least. Well, where to go from here, I

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guess, in talking about all of these things, you know, it comes

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to my mind how Trump has been pledging to make the the US the

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world capital of crypto and artificial intelligence, and

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obviously that's going to have an impact on his

417
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administration's education policy, and it arguably already

418
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is. So you sort of already broached the topic of FinTech in

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education, but we didn't really talk about, you know, crypto, in

420
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the sense of the recent passage of the genius Act, which is,

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according to Treasury Secretary Scott Besant, going to unleash

422
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billions of stable coins around the world. And obviously that's

423
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going to affect some of these things he brought up earlier,

424
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like education savings accounts and scholarship granting

425
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organizations, but also AI. So there was this recent executive

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order from Trump, I believe, in April, and it was called

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advancing artificial intelligence education for

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American youth, which is part of, according to the order,

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quote, ensuring the United States remains a global leader

430
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in this, meaning, AI, technological revolution. So

431
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what are some of the impacts of these policies on education thus

432
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far, and where do you see this ultimately going?

433
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Well, okay, so that AI executive order is largely

434
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focused on training, basically like stem so basically making

435
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students literate for the artificial intelligence era more

436
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so than it is about using AI to teach students now obviously,

437
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you know they're gonna it's gonna be a recursive sort of

438
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reciprocal relationship there. I didn't mention this in my

439
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article, but the American Federation of Teachers, who I

440
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have written about at unlimited Hangout, and I traced the

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history of their long term involvement, not only with

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Rockefellers and the Trilateral Commission, but big tech

443
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companies like IBM and the whole ed tech industry. They recently

444
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Randi Weingarten, who was part of a global union federation

445
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called education International, with all sorts of ties to the

446
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World Economic Forum, they the aft just announced that they're

447
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going 500,000 a big chunk of the aft unionized teachers are going

448
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to be trained to integrate open AI, I think There's two other I

449
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think anthropic is in there, and then the third one's either

450
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Google or Microsoft. And then she also announced specifically

451
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a partnership with the World Economic Forum to directly

452
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partner with them to set curriculum. So it's interesting

453
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to note that open AI and anthropic were also to the AI

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companies that were supposed to be part of this ai.gov platform

455
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that now that it's actually been launched, doesn't seem to be

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launching the same things that the the archived website had

457
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previously announced, but two of them were were the same

458
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companies. We know that open AI is also part of the Stargate

459
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Project, so this is so this is sort of indicating to to us

460
00:28:27,140 --> 00:28:32,120
that, right, we're basically setting up a centralized

461
00:28:32,120 --> 00:28:34,520
panopticon, while everything else is going to be so called

462
00:28:34,520 --> 00:28:38,420
decentralized, right? We're still, we're going to have as

463
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much as it looks like open AI and Palantir and these different

464
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companies are competing. If you go through my article, you'll

465
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see that the portfolios of sax and feel and horror Andreessen,

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the A large portion of their portfolios overlap, like a lot

467
00:28:56,980 --> 00:29:00,540
of these AI companies. Yeah. So I mean, that's, you know,

468
00:29:00,600 --> 00:29:03,720
indicates to me, it's all part of the same sort of ecosystem,

469
00:29:04,080 --> 00:29:06,540
okay? And, you know, they got that recent article about

470
00:29:06,540 --> 00:29:12,840
palantir's master database. I mean, maybe I'm, you know, maybe

471
00:29:12,840 --> 00:29:16,980
I'm a stickler for being overly precise, but technically not

472
00:29:16,980 --> 00:29:20,420
making a master database. It's just the case that it basically

473
00:29:20,420 --> 00:29:23,540
has contracts with essentially every federal agency. And then

474
00:29:23,540 --> 00:29:26,780
there's an executive order that was recently Trump issued to

475
00:29:26,780 --> 00:29:31,100
basically remove any barriers to sharing information across

476
00:29:31,100 --> 00:29:35,120
agency, right? So therefore you can see how all these different

477
00:29:35,180 --> 00:29:38,360
AI companies are basically have the green light to share all

478
00:29:38,360 --> 00:29:42,160
this information. This is gonna this is why, you know, the the

479
00:29:42,460 --> 00:29:46,180
deep the so called decentralization part is super

480
00:29:46,180 --> 00:29:49,900
important, because then we can actually have personalized

481
00:29:49,900 --> 00:29:53,260
profiles on everybody, right? And that personalized social

482
00:29:53,260 --> 00:29:57,940
credit profile is going to aggregate your HHS, Dishman

483
00:29:57,940 --> 00:30:02,040
wearable data with your AI. School choice, voucher, FinTech,

484
00:30:02,040 --> 00:30:05,520
Ed Tech Data, right? And it's going to give you career

485
00:30:05,520 --> 00:30:11,760
pathways and maybe mental health services based on those, those

486
00:30:11,760 --> 00:30:16,620
analytics. And so that's sort of the that's why the FinTech is

487
00:30:16,620 --> 00:30:20,040
super important to this, to this process. Now they pitch it as

488
00:30:20,340 --> 00:30:23,660
well. Look, if you got, if you have an education savings

489
00:30:23,660 --> 00:30:27,320
account for each individual student, and the education

490
00:30:27,320 --> 00:30:31,340
savings account can be used to purchase, you know, a huge array

491
00:30:31,340 --> 00:30:33,740
of products, right? This is a lot of accounting to make sure

492
00:30:33,740 --> 00:30:36,260
there's no fraud and waste and abuse and stuff like that,

493
00:30:36,260 --> 00:30:39,740
right? So how are we going to solve that problem? Oh, well, if

494
00:30:39,740 --> 00:30:44,620
we can have programmable money, and we can have these third

495
00:30:44,620 --> 00:30:48,940
party digital wallet companies service it. Basically that's

496
00:30:48,940 --> 00:30:51,700
supposed to solve the accounting problems and the waste, fraud

497
00:30:51,700 --> 00:30:57,280
and abuse problem, but what it also is basically it's putting

498
00:30:57,280 --> 00:31:01,500
in the building blocks for a tokenized system in which right,

499
00:31:02,640 --> 00:31:06,000
the monies that you get are programmed only for particular

500
00:31:06,000 --> 00:31:10,380
types of school choice, products, services, etc, and

501
00:31:10,680 --> 00:31:16,560
then right, based on how you perform, you'll either get new

502
00:31:16,560 --> 00:31:19,320
tokens or you'll get less tokens, or maybe you know you

503
00:31:19,320 --> 00:31:23,240
and those tokens can be either be used for maybe career

504
00:31:23,240 --> 00:31:26,960
pathways, training or mental health services, but all of this

505
00:31:26,960 --> 00:31:32,780
is basically a way to not only track and trace all the data,

506
00:31:32,780 --> 00:31:36,020
right in terms of learning data, health data, etc, but also to

507
00:31:36,020 --> 00:31:40,480
control how it can be used, and sort of make it like, you know,

508
00:31:40,480 --> 00:31:46,300
a global or a Skinner box on steroids, right? Where, like,

509
00:31:46,300 --> 00:31:49,060
everything, like, if punishments and rewards, we just mentioned,

510
00:31:49,060 --> 00:31:51,880
like, maybe have a wearable, this is right, another one that

511
00:31:52,240 --> 00:31:55,900
might, you know, like, just peer pressure, okay, back in the day,

512
00:31:55,900 --> 00:31:58,840
maybe it was a detention or a gold star for punishments and

513
00:31:58,840 --> 00:32:01,260
rewards. Well, you know, one of the, probably one of the

514
00:32:01,260 --> 00:32:04,560
strongest incentives, is money, right? So, if you take away

515
00:32:04,560 --> 00:32:07,740
people's money, right, as a you know, that's a pretty good way

516
00:32:07,740 --> 00:32:13,920
to sort of condition people to behave accordingly, so that. So

517
00:32:13,920 --> 00:32:19,080
that's why this the FinTech system is it's integral to

518
00:32:19,320 --> 00:32:22,400
funnel people, to forcibly funnel them into these ed tech

519
00:32:22,400 --> 00:32:26,900
products and services to data mine, data track for social

520
00:32:26,900 --> 00:32:30,980
credit, but then also, right? This is important to streamline

521
00:32:30,980 --> 00:32:35,720
this new stablecoin economy that's also being set up to

522
00:32:35,720 --> 00:32:37,580
basically prop up the dying dollar,

523
00:32:38,000 --> 00:32:42,400
right? So bringing up stablecoins Here, so the genius

524
00:32:42,400 --> 00:32:45,640
act, I mean, you know, since it's passed, Treasury has been

525
00:32:45,640 --> 00:32:49,600
asking for comment about various pillars that are required to

526
00:32:49,600 --> 00:32:54,100
implement the genius act and enable, you know, the bulk of

527
00:32:54,100 --> 00:32:57,880
Americans to hold digital dollar stable coins, as opposed to

528
00:32:57,880 --> 00:33:00,780
digital dollars. And I don't know, a Bank of America account

529
00:33:00,900 --> 00:33:05,520
or something like that. And one of those pillars is Surprise,

530
00:33:05,520 --> 00:33:10,440
surprise digital ID. And so questions are being fielded

531
00:33:10,440 --> 00:33:14,160
about that. So it seems likely that, you know, with stable

532
00:33:14,160 --> 00:33:20,660
coins, you know, if they move to only fund these wallets, you

533
00:33:20,660 --> 00:33:23,840
know, these digital wallets for education funding, they only

534
00:33:23,840 --> 00:33:26,960
will work with stable coins. At some point, it seems more likely

535
00:33:26,960 --> 00:33:31,820
than not. Then, in order to finance an education with these

536
00:33:32,360 --> 00:33:35,420
savings accounts or granting organizations or whatever,

537
00:33:35,960 --> 00:33:38,540
you'll have to have a digital ID. Yeah, well,

538
00:33:38,540 --> 00:33:41,020
and one of the companies, I think I mentioned, Merit

539
00:33:41,020 --> 00:33:43,720
International. This is another one that's funded by Andreessen

540
00:33:43,720 --> 00:33:47,440
Horowitz. It's also funded by another venture capital firm

541
00:33:47,440 --> 00:33:50,260
called alumni ventures, which shares common investments with

542
00:33:50,260 --> 00:33:54,100
Andreessen Horowitz and also with Peter Thiel, Founders Fund

543
00:33:54,100 --> 00:33:57,220
another, another company that funds merit International's

544
00:33:57,220 --> 00:33:59,920
Experian, which is one of the big three credit reporting

545
00:33:59,920 --> 00:34:04,140
agencies, and I remember during lockdowns that in Illinois, they

546
00:34:04,140 --> 00:34:06,960
were supposed to be somehow managing the databases that were

547
00:34:06,960 --> 00:34:10,740
going to have your vaccine passport, and so, you know,

548
00:34:10,740 --> 00:34:14,580
it's, you know. So when I see a credit company basically

549
00:34:14,580 --> 00:34:16,980
allowing me to come to work based on my health records, I

550
00:34:16,980 --> 00:34:20,600
see like social credit. I mean, essentially, that's a step in

551
00:34:20,600 --> 00:34:23,720
that direction, right? One other company that funds it, or

552
00:34:23,720 --> 00:34:25,940
rather, I should say it's another venture capital

553
00:34:26,480 --> 00:34:30,800
institution, is stand together. Venture Labs. Stand together is

554
00:34:30,800 --> 00:34:35,660
another one of these SPN coke backed think tanks, which is

555
00:34:35,660 --> 00:34:39,680
which, you know, again, the SPN state policy network and its

556
00:34:39,680 --> 00:34:43,300
consortium of think tanks being adjacent with and behind the

557
00:34:43,360 --> 00:34:45,940
development of project 2025

558
00:34:47,139 --> 00:34:51,099
they're neocons, right? I mean, the Koch brothers and

559
00:34:51,159 --> 00:34:54,939
American Enterprise Institute and the Heritage Foundation of

560
00:34:54,939 --> 00:34:57,759
project 2025 infamy, right?

561
00:34:57,940 --> 00:35:01,800
Yeah, that's yes. This is the neocon. Arm. And I'll tie

562
00:35:01,860 --> 00:35:04,320
that into sort of, because, because it was interesting to

563
00:35:04,320 --> 00:35:07,500
find that right, we think of the sort of PayPal mafias like the

564
00:35:07,500 --> 00:35:11,460
Silicon Valley arm, maybe, sort of maybe, like a so called

565
00:35:11,460 --> 00:35:15,240
Radical libertarian arm that, you know, maybe holders with the

566
00:35:15,240 --> 00:35:21,140
neocon that's why I use so called and radical right. But

567
00:35:21,140 --> 00:35:23,540
right, sort of like the CATO type, right? Which, again,

568
00:35:23,540 --> 00:35:26,360
that's a coke funded Institute, you know, before they start, it

569
00:35:26,360 --> 00:35:29,300
was founded by the Koch brothers before they broke away from

570
00:35:29,360 --> 00:35:33,980
Rothbard. But you know that that so called libertarian arm has

571
00:35:33,980 --> 00:35:37,280
always in this sort of, you know, old school neocon, yeah,

572
00:35:37,280 --> 00:35:39,380
you know, they would maybe get together, but, you know, you

573
00:35:39,380 --> 00:35:42,280
know, maybe, maybe didn't always agree on stuff, but if you, if

574
00:35:42,280 --> 00:35:46,600
you go back far enough, you know, feel and David Sacks, you

575
00:35:46,600 --> 00:35:50,020
know, starting Stanford review as basically this pushback

576
00:35:50,020 --> 00:35:55,060
against Jesse Jackson's Rainbow PUSH coalition. And then later

577
00:35:55,060 --> 00:35:57,820
come up with this book, the diversity myth, which is becomes

578
00:35:57,820 --> 00:36:01,020
like this, you know, pillar against, you know, so called all

579
00:36:01,020 --> 00:36:04,560
things woke like they've been sort of, you know, I guess,

580
00:36:04,920 --> 00:36:09,420
rubbing elbows with or also fueling some of the culture wars

581
00:36:09,420 --> 00:36:12,540
that the neocons have propped up just as much as they've been

582
00:36:13,260 --> 00:36:16,440
funding this futurist arm of this, you know, pseudo

583
00:36:16,440 --> 00:36:21,380
libertarian Cato arm of basically the right wing

584
00:36:21,800 --> 00:36:27,260
establishment, but I had set all that up on merit International

585
00:36:27,260 --> 00:36:29,780
to say that one of the things that they specialize in is a

586
00:36:29,780 --> 00:36:34,700
digital identity ecosystem to verify their purchases. Okay?

587
00:36:34,700 --> 00:36:37,820
Now if you look at another one of these companies called

588
00:36:37,820 --> 00:36:40,900
student first technologies, which partners with MasterCard,

589
00:36:41,440 --> 00:36:44,320
they have their platform which, quote, unquote, empowers

590
00:36:44,320 --> 00:36:48,880
stakeholders, uses a PLA, uses something called Quinn IQ,

591
00:36:49,120 --> 00:36:52,000
artificial intelligence, human in the loop, machine learning.

592
00:36:52,180 --> 00:36:57,340
Ai, a third company that I mentioned, SAP araba, right?

593
00:36:57,400 --> 00:37:01,080
They They do all sorts of FinTech services, but they'll do

594
00:37:01,080 --> 00:37:05,100
blockchain AI and then also do ESG monitoring. So between those

595
00:37:05,100 --> 00:37:08,340
three companies, what you have is digital wallets, digital

596
00:37:08,340 --> 00:37:14,220
identity, AI, ESG monitoring and blockchain. So you know they're

597
00:37:14,220 --> 00:37:17,640
not, there's not one company that's, I guess SAP kind of is,

598
00:37:17,820 --> 00:37:20,840
but you know that it largely is like servicing other companies,

599
00:37:20,840 --> 00:37:23,300
so that it's up to the company how much of their product they

600
00:37:23,300 --> 00:37:25,640
want to integrate together. Technically, they could give you

601
00:37:25,640 --> 00:37:28,880
all of it. But the point is this digital wallet industry, which

602
00:37:28,880 --> 00:37:32,240
has been funded by right, all these PayPal Mafia venture

603
00:37:32,240 --> 00:37:38,480
capital people backed by these coke backed neocon people across

604
00:37:38,480 --> 00:37:44,320
the board, they're all leaning towards either digital identity,

605
00:37:45,280 --> 00:37:50,140
AI or blockchain platform. Eventually, all this stuff is

606
00:37:50,140 --> 00:37:52,720
going to converge, and when you do, you're going to have a

607
00:37:52,720 --> 00:37:57,040
system in which, right, the government takes taxes, sends it

608
00:37:57,040 --> 00:38:00,100
to a digital wallet company. The digital wallet company looks at

609
00:38:00,100 --> 00:38:03,240
your AI, your analytics for your ed tech learning. It's going to

610
00:38:03,240 --> 00:38:05,520
give you the money, it's going to tell you what you're eligible

611
00:38:05,520 --> 00:38:08,640
to buy. It's going to the AI is going to analyze not just your

612
00:38:08,640 --> 00:38:11,340
learning analytics on the Ed Tech product, but also it's

613
00:38:11,340 --> 00:38:17,040
going to correlate like which types of voucher payouts and

614
00:38:17,220 --> 00:38:21,260
correlated with which kinds of outcomes, right? And so there's

615
00:38:21,320 --> 00:38:23,960
going to be predictive analytics on the Ed Tech, and there's

616
00:38:23,960 --> 00:38:26,660
gonna be predictive analytics on the FinTech and and then the

617
00:38:26,660 --> 00:38:29,300
blockchain part is the one that's going to basically lock

618
00:38:29,300 --> 00:38:32,540
you into a permanent profile ledger. And it's going to

619
00:38:32,540 --> 00:38:36,200
program so that you can write to restrict how you get to use your

620
00:38:36,200 --> 00:38:40,840
coins, until you, you know, comply with your get your social

621
00:38:40,840 --> 00:38:43,780
credit up to use them in a different way. Basically,

622
00:38:44,860 --> 00:38:48,640
this is turning out to be a real mess. Yeah. I mean, it's

623
00:38:48,640 --> 00:38:52,000
crazy. I haven't really heard Well, I haven't really been

624
00:38:52,000 --> 00:38:55,060
looking extensively, but you would think, since digital ID

625
00:38:55,060 --> 00:39:00,180
was such a big issue during the COVID era, with the people that

626
00:39:00,180 --> 00:39:04,200
now form a large part of Trump's base, there'd be a lot of

627
00:39:06,540 --> 00:39:12,240
uproar, perhaps, maybe that's hoping too much about about

628
00:39:12,240 --> 00:39:15,000
this, whether it's coming through, you know, the Treasury

629
00:39:15,000 --> 00:39:17,700
Department or, you know, education policy and these

630
00:39:17,700 --> 00:39:20,100
things, and it just really, really doesn't seem like it's

631
00:39:20,100 --> 00:39:22,940
happening at All. I mean, it's not really surprising, if you

632
00:39:22,940 --> 00:39:25,160
were paying attention and noticed all the Silicon Valley

633
00:39:25,160 --> 00:39:29,660
people and some of the worst people in the crypto industry

634
00:39:29,660 --> 00:39:36,440
line up behind Trump pretty early on. And I don't know, I'm

635
00:39:36,560 --> 00:39:39,860
unsettled by it. And I think, you know, I was thinking the

636
00:39:39,860 --> 00:39:42,460
other day, I don't want to get on too much of a sidebar here,

637
00:39:43,480 --> 00:39:48,400
but I was trying to figure out something. Because along with

638
00:39:48,400 --> 00:39:50,680
the genius act, you know, it was passed during the so called

639
00:39:50,680 --> 00:39:54,100
crypto week, there was another piece of legislation passed that

640
00:39:54,100 --> 00:39:57,040
was called the clarity act. And in there, there were a few

641
00:39:57,040 --> 00:39:59,560
blockchains that they like, singled out as they gave them

642
00:39:59,560 --> 00:40:03,600
the mature. Labeling. And they classified all these blockchains

643
00:40:03,600 --> 00:40:07,680
based on their maturity, and only three were in sort of this

644
00:40:07,680 --> 00:40:10,920
top tier. And it was, it was blockchain, I think the second

645
00:40:10,920 --> 00:40:13,500
one was Ethereum, which had been around, you know, the longest,

646
00:40:13,500 --> 00:40:16,920
arguably, but then they put another one called Cardano there

647
00:40:16,920 --> 00:40:21,920
when it doesn't belong there, in my opinion, I think in a lot of

648
00:40:21,920 --> 00:40:25,100
other people's opinion, but it's interesting because Cardano was

649
00:40:25,100 --> 00:40:29,960
created by Charles Hoskinson, um, who was a co founder of

650
00:40:29,960 --> 00:40:32,960
Ethereum, but he's also, you know, the Cardano guy. And

651
00:40:32,960 --> 00:40:37,640
Cardano, um, if you look into them at all, well, not only have

652
00:40:37,640 --> 00:40:40,360
they're teamed up with the extremely Epstein funded

653
00:40:40,360 --> 00:40:43,540
scientist Ben gertzel, very extensively, who's behind

654
00:40:43,540 --> 00:40:48,160
Sophia, the robot and all of this stuff. But they also did a

655
00:40:48,160 --> 00:40:54,400
digital ID for education for all Ethiopian school children. And

656
00:40:54,400 --> 00:40:58,540
so I wonder, why was Cardano put in the clarity act and given

657
00:40:58,540 --> 00:41:02,400
this boost? Well, they have this whole, you know, digital ID

658
00:41:02,400 --> 00:41:06,600
platform for school children and basically for, you know, I guess

659
00:41:06,600 --> 00:41:11,220
the general public already ready to go. So if you need a digital

660
00:41:11,220 --> 00:41:15,480
ID on a blockchain out the door to make the genius act stuff

661
00:41:15,480 --> 00:41:20,540
work, why not sort of King make, you know, something like

662
00:41:20,540 --> 00:41:22,940
Cardano, which, by the way, Hoskinson was a big donor to

663
00:41:22,940 --> 00:41:28,040
Trump last last cycle. Why not sort of single out, you know,

664
00:41:28,040 --> 00:41:30,680
the blockchain that you want to use for digital ID while you're

665
00:41:30,680 --> 00:41:34,460
signal signaling out the ones that you want to use for a lot

666
00:41:34,460 --> 00:41:37,040
of the, you know, stable coin crap too.

667
00:41:38,059 --> 00:41:40,159
You know, the other thing about like, so with class

668
00:41:40,159 --> 00:41:44,919
wallet, it got a really big boom during lockdowns, because it

669
00:41:44,919 --> 00:41:49,359
was, it was a lot of states. I can't remember the particular

670
00:41:49,359 --> 00:41:52,839
number. It's in the article, but you know, many states, and I

671
00:41:52,839 --> 00:41:57,339
think some federal I think maybe some, like FEMA projects, etc.

672
00:41:57,759 --> 00:42:01,319
If they're not doing FEMA on HHS yet, they are set up to do it.

673
00:42:01,319 --> 00:42:05,399
But they definitely were distributing some of the cares,

674
00:42:05,399 --> 00:42:08,999
money and cares, you know, under cares, there was, like, the gear

675
00:42:08,999 --> 00:42:14,519
and here and ESF, I think it's cares and ESF, but that was how

676
00:42:14,519 --> 00:42:17,999
it sort of got its foot in, in the door. I mean, it had been

677
00:42:17,999 --> 00:42:20,659
around, like, that's really how it, like, locked itself in as

678
00:42:20,659 --> 00:42:24,679
like one of the go tos for this FinTech stuff. So I mean that

679
00:42:24,679 --> 00:42:26,839
alone, you would think, right, these, you know, the people that

680
00:42:26,839 --> 00:42:29,479
were against lockdowns, you might look at something like,

681
00:42:29,479 --> 00:42:32,959
well, maybe this all of a sudden, the the people that are,

682
00:42:33,199 --> 00:42:36,439
you know, supposed to be against this, are basically propping up

683
00:42:36,439 --> 00:42:40,719
the company that you know took off during lockdowns. Is maybe,

684
00:42:40,719 --> 00:42:45,039
maybe a red flag, but in the long term, and this is kind of

685
00:42:45,039 --> 00:42:47,679
speculative, but I'm pretty sure, I'm pretty sure this is

686
00:42:47,679 --> 00:42:51,939
the case, you know. And shout out to mark Goodwin, who took

687
00:42:52,299 --> 00:42:54,999
his time to help me make sure that I understand some of the

688
00:42:54,999 --> 00:42:57,519
financial stuff better. And one of the things I was asking about

689
00:42:57,519 --> 00:43:00,219
was, like, you know, like, what exactly is the definition of a

690
00:43:00,219 --> 00:43:02,559
security, right? Because they were trying to figure out what

691
00:43:02,559 --> 00:43:04,439
these did. Figure out these digital assets, should they be

692
00:43:04,439 --> 00:43:08,519
like a security or not? Come on? Well, yeah, right. And so he

693
00:43:08,519 --> 00:43:11,459
basically explained it was security is basically expected

694
00:43:11,459 --> 00:43:14,759
future profits, and not on just like the appreciation of a

695
00:43:14,759 --> 00:43:17,279
basic, you know, asset, like a house would, but it's like

696
00:43:17,279 --> 00:43:21,439
you're buying of the an increased value that is expected

697
00:43:21,439 --> 00:43:25,999
in the future that is not just part of its, you know, natural

698
00:43:25,999 --> 00:43:31,459
valuation as an asset. So if you think about like, I think where

699
00:43:31,459 --> 00:43:35,359
they're going to go is basically securitize human beings and,

700
00:43:35,359 --> 00:43:39,859
like, own them with, like, human capital, yeah, human capital

701
00:43:39,859 --> 00:43:42,579
development. And I'll tell you about a company that's already

702
00:43:42,579 --> 00:43:45,579
taking some of my tutoring hours at the end of this thing. It's

703
00:43:45,579 --> 00:43:49,359
called upswing, and it ties into this because So basically, this

704
00:43:49,359 --> 00:43:52,959
is how I see it. So where's the expected or the future value?

705
00:43:52,959 --> 00:43:57,759
Well, let's see if we can get student X to reach education

706
00:43:57,759 --> 00:44:03,299
goal y through career pathway, Z, right? That will produce so

707
00:44:03,299 --> 00:44:06,059
much money in the economy, because they'll get this job,

708
00:44:06,059 --> 00:44:09,059
and they'll produce these products, and it'll also save us

709
00:44:09,059 --> 00:44:13,319
the money that we would have had to spend on retraining. And

710
00:44:13,439 --> 00:44:16,019
maybe the student needs, maybe they need, you know, they fall

711
00:44:16,019 --> 00:44:18,239
out of the fall through the cracks, and they need to have

712
00:44:18,239 --> 00:44:20,959
mental health, or maybe they become delinquent, they go to

713
00:44:20,959 --> 00:44:23,899
jail, right? So, and I've seen metrics at like AEI, where they

714
00:44:23,899 --> 00:44:27,019
actually are talking about impact investments. In this

715
00:44:27,019 --> 00:44:30,259
manner, they're quantifying education outcomes in terms of,

716
00:44:31,879 --> 00:44:35,359
you know, either monies lost in those ways, right, student falls

717
00:44:35,359 --> 00:44:37,459
through cracks, goes into, you know, they got to take care of

718
00:44:37,459 --> 00:44:41,139
them with health care or prison or right? What do they produce

719
00:44:41,139 --> 00:44:44,739
if they're successful? So you quantify that algorithmically,

720
00:44:44,739 --> 00:44:47,439
right with this, with this, all these AI analytics and supply

721
00:44:47,439 --> 00:44:52,119
chain dynamics, and then basically the you send that

722
00:44:52,119 --> 00:44:54,399
information out to these companies. Maybe it's one of the

723
00:44:54,459 --> 00:44:58,119
SGOs and the SGO which right a lot of them are focused on

724
00:44:58,179 --> 00:45:01,079
impact investing, social impact. Active vesting. So they look

725
00:45:01,079 --> 00:45:05,339
around and they go, they go, Okay, well, I'll sponsor this

726
00:45:05,339 --> 00:45:08,459
student. They've got some decent analytics. I'll give them these

727
00:45:08,459 --> 00:45:11,399
tokens through this digital wallet to buy these products,

728
00:45:11,399 --> 00:45:14,759
because I know these products are the most likely to make

729
00:45:14,759 --> 00:45:18,059
these outcomes. And if they make these outcomes, then I get my

730
00:45:18,059 --> 00:45:20,839
money back. And potentially, if they exceed those outcomes, I

731
00:45:20,839 --> 00:45:25,939
get a profit if I don't. You know, the way something like Pay

732
00:45:25,939 --> 00:45:28,879
for Success, impact investing is basically a company puts the

733
00:45:28,879 --> 00:45:32,179
money up front, and if, for some reason, the student doesn't meet

734
00:45:32,179 --> 00:45:36,019
any outcomes, then the government doesn't subsidize it,

735
00:45:36,019 --> 00:45:39,079
right? The government eats it. But if they do, if they do meet

736
00:45:39,079 --> 00:45:42,459
those right, then, then they get the money back with interest,

737
00:45:42,519 --> 00:45:45,399
right? And so basically, what you'll have in that situation is

738
00:45:45,399 --> 00:45:48,219
basically, right, you'll have these human capital bonds.

739
00:45:48,519 --> 00:45:51,519
You'll have companies, quote, unquote, sponsoring students.

740
00:45:51,519 --> 00:45:54,099
Or, in other words, they'll be like, you know, this will be a

741
00:45:54,099 --> 00:45:57,699
legit techno feudal system in which, right, you'll have these

742
00:45:57,699 --> 00:46:01,619
feudal, big tech overlords that, basically, you know, own these

743
00:46:01,919 --> 00:46:04,619
digital serfs on these blockchain digital wallets, and

744
00:46:04,619 --> 00:46:07,379
they'll be forced to go through their skin area and operant

745
00:46:07,379 --> 00:46:10,979
conditioning programs through whatever wearables or screen

746
00:46:10,979 --> 00:46:14,399
based AI platforms they got. And then that'll all be geared

747
00:46:14,399 --> 00:46:19,079
towards them, sort of stabilizing or growing the

748
00:46:19,319 --> 00:46:22,519
global supply chain economics.

749
00:46:22,940 --> 00:46:25,100
This reminds me, actually, some of the stuff we're talking

750
00:46:25,100 --> 00:46:29,060
about, of this policy that Javier Millay promoted, I think,

751
00:46:29,060 --> 00:46:32,180
a year ago, and I'm not sure what progress he's had on it

752
00:46:32,180 --> 00:46:37,700
since it was announced, but I think it's kind of fitting to go

753
00:46:37,700 --> 00:46:40,600
over in some of these because of some of the things you brought

754
00:46:40,600 --> 00:46:44,560
up. And also, because this, this shift in dialectics from public

755
00:46:44,560 --> 00:46:48,280
to private, and whatever that we were talking about earlier, I

756
00:46:48,280 --> 00:46:51,160
think Javier Millay was absolutely the poster child for

757
00:46:51,160 --> 00:46:54,700
that. He's like, beta testing, kind of, for all these policies,

758
00:46:55,060 --> 00:46:57,340
you know. So, like, he was the first one to be like, I'm going

759
00:46:57,340 --> 00:47:00,360
to eliminate the Department of Education. And now Trump, you

760
00:47:00,360 --> 00:47:04,500
know, has made that part of his policy. But, you know, in Malays

761
00:47:04,500 --> 00:47:09,300
also, you know, been like public education is not a right, and

762
00:47:09,300 --> 00:47:12,000
all of all of these things and has sort of promised to sort of

763
00:47:12,000 --> 00:47:14,340
take the state out of schooling entirely. But what has he

764
00:47:14,340 --> 00:47:18,840
proposed in its place? Right? And so the thing that he sort of

765
00:47:18,840 --> 00:47:23,180
proposed as a replacement for public schools was basically

766
00:47:23,180 --> 00:47:27,560
having Facebook come in with their a or meta, you know, their

767
00:47:27,560 --> 00:47:34,580
parent company, come in and he, his quote is, so meta has has a

768
00:47:34,580 --> 00:47:38,660
whole system set up for the formation of human capital, for

769
00:47:38,660 --> 00:47:43,720
the formation Of the people so that they can set up a career.

770
00:47:43,960 --> 00:47:48,280
And said that he, you know, plan, planted this idea with his

771
00:47:48,760 --> 00:47:51,940
minister, who's in charge of this stuff, and we're going to

772
00:47:51,940 --> 00:47:54,460
start making the contacts with the people that made us so we

773
00:47:54,460 --> 00:47:58,180
can implement an artificial intelligence plan for the

774
00:47:58,180 --> 00:48:01,860
formation, or let you know the schooling of our of our kids,

775
00:48:02,040 --> 00:48:06,480
basically. And so I'm kind of thinking back to what we sort of

776
00:48:06,480 --> 00:48:08,940
broached earlier about school choice, how a lot of it leaves,

777
00:48:08,940 --> 00:48:13,620
kind of like public, public school kids behind, and sort of

778
00:48:13,620 --> 00:48:17,460
this idea of human capital and where it's going. And, you know,

779
00:48:17,520 --> 00:48:21,920
the idea of, oh, we need more efficiency, and like rightly

780
00:48:21,920 --> 00:48:24,440
identifying that there's a lot broken with the education

781
00:48:24,440 --> 00:48:28,100
system. But also, you know, offering a solution that's

782
00:48:28,100 --> 00:48:32,600
arguably just as bad, if not worse. And in this case, you

783
00:48:32,600 --> 00:48:36,920
know, he's having talking about Facebook AI coming in and

784
00:48:36,920 --> 00:48:39,980
deciding basically what you laid out, this idea of career

785
00:48:39,980 --> 00:48:46,300
pathways for kids and having AI, you know, be teaching kids from

786
00:48:46,300 --> 00:48:48,340
the beginning all the way through having, you know,

787
00:48:48,340 --> 00:48:52,840
preparing them for a career that the AI determines, essentially.

788
00:48:53,500 --> 00:48:58,120
And I, you know, I would like that not to happen in the US,

789
00:48:58,120 --> 00:49:00,360
but it seems like that, you know, as you've been pointing

790
00:49:00,360 --> 00:49:04,080
out that kind of is where it's ultimately going. And I'm also

791
00:49:04,080 --> 00:49:07,380
thinking about, you know, so, you know, if Facebook were to do

792
00:49:07,380 --> 00:49:11,400
that in the US, and you have, you know, all of these FinTech

793
00:49:11,400 --> 00:49:15,660
wallets, you know, to fund education or whatever, and a lot

794
00:49:15,660 --> 00:49:18,960
of them are set up by, you know, entities to like Peter Thiel or

795
00:49:18,960 --> 00:49:21,980
other people in the PayPal Mafia. So what better way to

796
00:49:21,980 --> 00:49:25,100
have, you know, those companies that are tied to people, like

797
00:49:25,100 --> 00:49:28,580
Thiel, manage your funds, and then Facebook, that was put on

798
00:49:28,580 --> 00:49:31,460
the map by Peter Thiel, who was on the board for decades, and

799
00:49:31,460 --> 00:49:34,220
I'm pretty sure he still has stock in it. You know, they're

800
00:49:34,220 --> 00:49:38,780
the ones that are being funded, funded by their funded FinTech

801
00:49:38,780 --> 00:49:42,820
company. And then, you know, I mean, it's just like a passing

802
00:49:42,820 --> 00:49:45,700
the money around the same people, basically at the end of

803
00:49:45,700 --> 00:49:48,340
the day, is kind of what it's starting to look like. And

804
00:49:48,340 --> 00:49:53,860
doesn't really seem to be about, you know, education. It seems to

805
00:49:53,860 --> 00:49:56,860
be a lot more about profit motives and, quote, unquote,

806
00:49:56,860 --> 00:50:01,320
efficiency, but efficiency under the paradigm. Of like, you know,

807
00:50:01,320 --> 00:50:05,820
humans are hackable, programmable animals, and this

808
00:50:05,820 --> 00:50:10,500
is how we can, you know, more efficiently, efficiently milk

809
00:50:10,500 --> 00:50:14,340
them for profit. I don't know if I'm, I don't know if you agree

810
00:50:14,340 --> 00:50:16,020
with all that. I kind of just went on a,

811
00:50:16,020 --> 00:50:20,120
yeah, no, I 100% I mean, look, it's in, it's even, you

812
00:50:20,120 --> 00:50:24,620
know, I had conversation with my socialist friends not too long

813
00:50:24,620 --> 00:50:27,380
ago, and, you know, they talk about profit and capital. I

814
00:50:27,380 --> 00:50:29,840
think it's a little bit past, I think it's, think we need to go

815
00:50:29,840 --> 00:50:32,780
a little bit further than that. It's really just about supply

816
00:50:32,780 --> 00:50:36,320
chain management systems, dynamic control and creating a

817
00:50:36,320 --> 00:50:39,500
cybernetic control grid. I mean, because at this point, like, I

818
00:50:39,500 --> 00:50:43,840
mean, I don't see how the very notion of profit, when

819
00:50:43,840 --> 00:50:47,440
everything becomes automated, and basically the human beings

820
00:50:47,440 --> 00:50:51,760
become again, these human capital bonds, essentially, like

821
00:50:51,760 --> 00:50:54,340
you own everything. You know what I mean now, it's just

822
00:50:54,340 --> 00:50:57,160
controlling the slaves and keeping everything, keeping the

823
00:50:57,160 --> 00:51:01,320
wheels turning as smoothly as possible. Okay? I think that

824
00:51:01,320 --> 00:51:03,720
like, if you look at the history of like, so the Macy's

825
00:51:03,720 --> 00:51:06,960
cybernetics conferences, these are set up in like, 40s and 50s.

826
00:51:06,960 --> 00:51:09,660
Well, this is basically the exact same time that some of the

827
00:51:09,660 --> 00:51:12,600
first venture capital firms are set up. Now, you know, what did

828
00:51:12,600 --> 00:51:12,960
they do at

829
00:51:12,960 --> 00:51:15,600
Macy's cybernetics conference with military

830
00:51:15,600 --> 00:51:17,400
involvement, exactly.

831
00:51:17,460 --> 00:51:19,560
And they laid out, right? They what they said, basically

832
00:51:19,560 --> 00:51:24,020
two things, the the theoretical implications of how the feedback

833
00:51:24,020 --> 00:51:26,300
loop, computerized feedback loop, so That's right. It's

834
00:51:26,300 --> 00:51:29,840
transmitting data, analyzing the way that that the response to

835
00:51:29,840 --> 00:51:33,740
that data, taking that new data, that response data, and then

836
00:51:35,600 --> 00:51:39,860
adjusting the the transmission in accordance with right the

837
00:51:39,860 --> 00:51:43,780
feedback right? And you could do this to map right, the human

838
00:51:43,780 --> 00:51:46,960
psyche, cognitively, what they called the conditioned reflex,

839
00:51:46,960 --> 00:51:49,600
but also the subconscious, right, what they called, I

840
00:51:49,600 --> 00:51:52,300
think, mesmerism or hypnosis, but it's basically the Freudian,

841
00:51:52,300 --> 00:51:55,000
the psychoanalytic, the two parts of right, the behavioral

842
00:51:55,000 --> 00:51:58,480
School of Psychology and the psychoanalytic school. So you

843
00:51:58,480 --> 00:52:02,040
take that they understand theoretically, that this is

844
00:52:02,040 --> 00:52:05,940
possible. Then you get these venture capital firms set up,

845
00:52:06,420 --> 00:52:09,720
they get Moore's Law laid out, and they basically know how long

846
00:52:09,720 --> 00:52:12,720
it's going to take for the transition transistors to

847
00:52:12,720 --> 00:52:18,480
exponentially grow or be improved until they can actually

848
00:52:18,480 --> 00:52:22,880
process all the data right? And so they and they look, okay, we

849
00:52:22,880 --> 00:52:25,940
have however many decades, and what do we have to do in the

850
00:52:25,940 --> 00:52:29,240
meantime? Well, we set up these venture capital firms, some of

851
00:52:29,240 --> 00:52:32,240
them, like in Q, Tel, directly set up by the CIA. Others, like

852
00:52:32,240 --> 00:52:38,540
Sequoia, like you know, all you know, saturated with with CIA

853
00:52:38,660 --> 00:52:45,100
connections. And basically, what do they do? They throw they they

854
00:52:45,400 --> 00:52:50,440
for that time period, they look around to see which programmers

855
00:52:50,440 --> 00:52:53,380
are coming up with something that might be promising or

856
00:52:53,380 --> 00:52:56,260
otherwise useful. They throw money at it. If it doesn't go

857
00:52:56,260 --> 00:52:59,680
anywhere, no biggie. If it does, they pull it into their control

858
00:52:59,680 --> 00:53:03,840
grid. And so basically, in the meantime, they have to do two

859
00:53:03,840 --> 00:53:06,540
things between the Macy cybernetics conference and sort

860
00:53:06,540 --> 00:53:10,260
of the climax of the fruition of Moore's law, and that is,

861
00:53:10,560 --> 00:53:14,280
control the development of the technology through venture

862
00:53:14,280 --> 00:53:19,560
capital, and also manipulate the culture in ways that people will

863
00:53:19,560 --> 00:53:23,540
be will will accept this or otherwise be unaware of it. And

864
00:53:23,540 --> 00:53:26,720
that's your sort of this right wing, left wing, you know,

865
00:53:26,720 --> 00:53:32,420
culture war stuff, and so, I mean, I think that all of that

866
00:53:32,420 --> 00:53:35,780
together, and as you know, you know, as you as you've done, you

867
00:53:35,780 --> 00:53:39,200
know, good research on you show that. You know, companies like

868
00:53:39,380 --> 00:53:43,480
Palantir and Facebook basically, were life log and total

869
00:53:43,480 --> 00:53:47,140
information awareness right, which came out of post 911 era.

870
00:53:47,260 --> 00:53:49,960
And we can argue that that was sort of this inflection point

871
00:53:49,960 --> 00:53:53,500
where, like, we were able to start to sort of integrate some

872
00:53:53,500 --> 00:53:56,260
of these technologies, right? We went from the theoretical and

873
00:53:56,260 --> 00:53:59,620
sort of the pilot phases and right we and at that point right

874
00:53:59,620 --> 00:54:03,720
with the national security threat. We had sort of reasons

875
00:54:03,780 --> 00:54:06,480
to onboard this stuff. So, I mean, if you just look at the

876
00:54:06,480 --> 00:54:11,340
last, you know, 60 years, it looks like it was all, very

877
00:54:11,340 --> 00:54:15,900
much, all everything converging, not accidentally, towards

878
00:54:15,900 --> 00:54:20,160
basically creating this control grid. I do want to note

879
00:54:20,160 --> 00:54:23,660
something you mentioned about Venezuela. I just thought it was

880
00:54:23,660 --> 00:54:26,420
really interesting. And that is that, you know, so Charlotte

881
00:54:26,420 --> 00:54:28,700
wrote, before she wrote the deliberate dumbing down of

882
00:54:28,700 --> 00:54:32,000
America, she had wrote a shorter piece called Back to Basics

883
00:54:32,240 --> 00:54:36,020
reform, or obe scannerian international curriculum. It's a

884
00:54:36,020 --> 00:54:39,020
short little thing she used to rail about how she said, I

885
00:54:39,020 --> 00:54:41,380
wouldn't have had to write the big book that's deliberate

886
00:54:41,380 --> 00:54:43,660
dumbing down, if not, the Conservatives wouldn't have

887
00:54:43,660 --> 00:54:47,800
boycotted me on the little book. And that was a big thing. She

888
00:54:47,920 --> 00:54:50,260
used to tell me to say, you know why you don't get as much

889
00:54:50,260 --> 00:54:53,020
traction as you should? She says, Because of me and because

890
00:54:53,020 --> 00:54:57,220
of school choice. Those are the those are the two things. And in

891
00:54:57,220 --> 00:55:01,020
this piece, she mentions here, I. Um, this is according to

892
00:55:01,020 --> 00:55:04,680
March, April, 1981 issue of human intelligence international

893
00:55:04,680 --> 00:55:08,640
newsletter, critical thinking skills research is taking place

894
00:55:08,640 --> 00:55:11,460
within the United Nations Educational scientific cultural

895
00:55:11,460 --> 00:55:13,740
organization, the Office of Economic Cooperation and

896
00:55:13,740 --> 00:55:16,620
Development and the World Bank, which plans on increasing the

897
00:55:16,620 --> 00:55:19,740
bank's international lending for education training to about $900

898
00:55:20,220 --> 00:55:23,240
million a year. The Department of Education, that's the US

899
00:55:23,240 --> 00:55:26,300
Department of Education's National Institute of Education,

900
00:55:26,300 --> 00:55:29,420
possibly in response to a meeting Luis Alberto Machado,

901
00:55:29,420 --> 00:55:32,060
the Venezuelan Minister for Human intelligence, had with

902
00:55:32,060 --> 00:55:34,580
former Secretary of Education, Terrell Bell, and various

903
00:55:34,580 --> 00:55:37,940
senators, to update them on the progress of this his nation's

904
00:55:37,940 --> 00:55:40,460
work in human intelligence, and was awarded a three year

905
00:55:40,460 --> 00:55:45,040
contract totaling approximately 780 approximately $780,000 to

906
00:55:45,040 --> 00:55:48,160
bolt bear Mac and Newman incorporated that was a tech

907
00:55:48,160 --> 00:55:51,580
company back in the day and might still exist, to analyze

908
00:55:51,580 --> 00:55:54,940
current programs of instruction on cognitive skills. And then

909
00:55:54,940 --> 00:55:58,300
she also cites in here a bill that had, in there they were

910
00:55:58,300 --> 00:56:01,380
proposed, there's a quote from it, the community intelligence

911
00:56:01,380 --> 00:56:04,200
project and the applied thinking skills project in Santa Barbara,

912
00:56:04,200 --> 00:56:06,660
California, and the nationwide intelligence project in

913
00:56:06,660 --> 00:56:09,180
Venezuela have shown good results with promising social

914
00:56:09,180 --> 00:56:12,120
and educational benefits. So it looks like Venezuela, Terrell

915
00:56:12,120 --> 00:56:14,700
Bell, by the way, that is this Secretary of Education that

916
00:56:14,700 --> 00:56:17,040
Charlotte was under. He was the one that was in charge of

917
00:56:17,040 --> 00:56:20,040
project best. So while they're setting up project best, and you

918
00:56:20,040 --> 00:56:25,760
had sort of, right, all the precursors to this Trump version

919
00:56:25,760 --> 00:56:30,980
of neocon Silicon Valley, you know, weird amalgamation, you

920
00:56:30,980 --> 00:56:36,020
know, the the origins of this school of choice revamp. Go back

921
00:56:36,020 --> 00:56:38,720
to th Bell and looks like Venezuela was basically on the

922
00:56:38,720 --> 00:56:42,040
same page as us then as well, and as we know, you know, I

923
00:56:42,040 --> 00:56:44,800
mean, if we look at this administration as, like, you

924
00:56:44,800 --> 00:56:47,440
know, I know that for a long time, the word fascist got

925
00:56:47,440 --> 00:56:51,160
thrown around way too loosely, but this is corporate fascism.

926
00:56:51,220 --> 00:56:55,540
And where did all the Nazi fascists go? Or a lot of them go

927
00:56:55,540 --> 00:56:58,660
after the, you know, project, paper clip. Well, they came

928
00:56:58,660 --> 00:57:01,060
here, and they also went to the Latin American countries. I

929
00:57:01,060 --> 00:57:03,480
don't know if they went to Venezuela, but you Venezuela,

930
00:57:03,480 --> 00:57:04,320
but, you know, I know

931
00:57:04,320 --> 00:57:07,320
Brazil in our Argentina, and they definitely do. They go

932
00:57:07,320 --> 00:57:09,420
there also, right? So,

933
00:57:09,720 --> 00:57:11,700
you know what I mean? I just, you got to wonder, you

934
00:57:11,700 --> 00:57:15,180
know, how much of that is, how much of the parallels between

935
00:57:15,180 --> 00:57:18,300
the way that these different, these Latin American countries

936
00:57:18,300 --> 00:57:22,280
and we're going maybe, maybe stems back to some, some of

937
00:57:22,280 --> 00:57:25,460
those, some of the stuff that they both brought back from

938
00:57:25,460 --> 00:57:27,080
Project, Project, paper clip,

939
00:57:27,500 --> 00:57:30,080
yeah. Well, whether it's from then, I mean, I don't

940
00:57:30,080 --> 00:57:34,580
really know, but definitely now there's a lot in sync between,

941
00:57:34,640 --> 00:57:37,700
you know, the Trump administration in South America,

942
00:57:37,700 --> 00:57:42,520
and it's likely to only increase, particularly with

943
00:57:42,520 --> 00:57:46,240
Chile's upcoming election. I mean, the kind of Malay Trump

944
00:57:46,240 --> 00:57:49,060
equivalent candidate is probably going to end up winning. So

945
00:57:49,060 --> 00:57:52,900
we'll probably see a lot of those policies pop up here too,

946
00:57:52,900 --> 00:57:57,700
in the not so distant future. So before we wrap up here, John, I

947
00:57:57,700 --> 00:58:02,980
wanted to bring up something in the context of these the fin

948
00:58:02,980 --> 00:58:07,680
FinTech angle here, and the stable coin angle here. So in

949
00:58:07,680 --> 00:58:10,440
terms of Trump's education policy, you know, a lot of it

950
00:58:10,440 --> 00:58:14,280
hasn't gotten that much coverage. And just in general, I

951
00:58:14,280 --> 00:58:19,080
think, you know, in favor of a lot of the other wild stuff

952
00:58:19,080 --> 00:58:22,460
that's been going on over the past, you know, eight ish months

953
00:58:22,460 --> 00:58:26,840
or so. But one thing that I think most people are familiar

954
00:58:26,840 --> 00:58:31,040
with in terms of Trump's what he's done with respect to

955
00:58:31,040 --> 00:58:34,340
educational institutions has sort of been this, this

956
00:58:34,340 --> 00:58:37,160
crackdown. Well, it's been framed. It was initially framed

957
00:58:37,160 --> 00:58:42,100
as a crackdown on, quote, unquote, woke ideology, right in

958
00:58:42,100 --> 00:58:45,100
schools and universities. But then it sort of became this,

959
00:58:46,960 --> 00:58:51,280
this clamp down, particularly on finances of educational

960
00:58:51,280 --> 00:58:55,780
institutions, where students were protesting the war in Gaza

961
00:58:55,780 --> 00:58:59,020
being waged by Israel, and the administration justified these

962
00:58:59,020 --> 00:59:03,180
moves under the guise of combating quote, unquote, anti

963
00:59:03,180 --> 00:59:06,960
semitism. So if we're in sort of this paradigm where education

964
00:59:06,960 --> 00:59:09,840
funding and just basically Americans money in general, is

965
00:59:10,020 --> 00:59:14,220
going to be moved to these digital dollar stable coins that

966
00:59:14,220 --> 00:59:17,520
are just in the sense of being similar to CBDCs, they can be

967
00:59:17,520 --> 00:59:20,580
seized, you know, and they're survivable, and they're

968
00:59:20,580 --> 00:59:24,740
programmable, you know, if, as you brought up earlier, the

969
00:59:24,920 --> 00:59:29,840
administration could program these, you know, education

970
00:59:29,840 --> 00:59:33,080
savings accounts and things like that, to only be used on certain

971
00:59:33,080 --> 00:59:38,180
things. It seems more likely than not that there's also a

972
00:59:38,180 --> 00:59:41,020
precedent being sent here where they could just turn off

973
00:59:42,220 --> 00:59:46,120
institutions money, or also turn off, you know, offending

974
00:59:46,120 --> 00:59:51,220
students money, you know, off at the spigot, basically, with some

975
00:59:51,220 --> 00:59:56,440
of these, you know, FinTech companies. Not sure how you feel

976
00:59:56,440 --> 00:59:59,320
about that, but you know, do you see this, the creep of these

977
00:59:59,320 --> 01:00:02,880
technologies? Is enabling the government's capacity to control

978
01:00:02,880 --> 01:00:06,840
speech on campuses, whether it's about Gaza or really anything

979
01:00:06,840 --> 01:00:10,560
else, like if we have another sort of COVID scenario and

980
01:00:10,560 --> 01:00:14,940
criticism of, you know, the narratives there or the policies

981
01:00:14,940 --> 01:00:17,700
there, you know, what are your thoughts?

982
01:00:19,260 --> 01:00:21,980
Yeah, you know. So there's the third, I think it's the

983
01:00:21,980 --> 01:00:27,320
third chapter in my book. I looked at what are called P

984
01:00:27,320 --> 01:00:31,520
Well, there's P 16, P 20 and P 20 plus, you know, one, another

985
01:00:31,520 --> 01:00:34,400
one of these where they got to have 12 different acronyms for

986
01:00:34,460 --> 01:00:37,640
one thing. So you can't have a concise conversation about it,

987
01:00:37,640 --> 01:00:40,660
but they're, we'll just call them p 20 councils, okay, to

988
01:00:40,780 --> 01:00:43,420
expedite. And basically, there's these consortiums or these

989
01:00:43,420 --> 01:00:46,360
clearing houses to set up public private partnerships between

990
01:00:46,600 --> 01:00:49,600
educational institutions at the state level, almost I think, I

991
01:00:49,600 --> 01:00:52,720
think every state does it. If it's not everyone, it's very

992
01:00:52,720 --> 01:00:58,000
close to all 50 between the education department or a local

993
01:00:58,000 --> 01:01:03,720
education agency and various other what they call in the

994
01:01:03,720 --> 01:01:07,140
community schooling model. So called Community schooling model

995
01:01:07,380 --> 01:01:09,720
would be what they call wraparound services. So these

996
01:01:09,720 --> 01:01:12,300
are public, private partnerships between, again, these, these

997
01:01:12,300 --> 01:01:16,560
schools and either healthcare institutions, but also what they

998
01:01:16,560 --> 01:01:19,080
call community oriented policing. So in other words,

999
01:01:19,080 --> 01:01:23,840
right? They're part of these, the these p 20 consortiums is

1000
01:01:23,840 --> 01:01:26,540
not just to write help the students with their workforce

1001
01:01:26,540 --> 01:01:29,000
training skills, but also to help them with their mental

1002
01:01:29,000 --> 01:01:32,360
health, and also to make sure that they become delinquent and

1003
01:01:32,360 --> 01:01:34,460
fall through the cracks, right? So they have this, like

1004
01:01:34,460 --> 01:01:38,240
preemptive criminal justice component as well. You can, you

1005
01:01:38,240 --> 01:01:41,800
know, tie that in both of these in, actually, with national

1006
01:01:41,800 --> 01:01:44,680
security, and that is mental health and criminal justice.

1007
01:01:46,000 --> 01:01:49,060
So now, yes, yes, yeah. And now they're

1008
01:01:49,059 --> 01:01:51,159
gonna, they're gonna, the next part is, you know, this is,

1009
01:01:51,159 --> 01:01:53,619
this is one of the scariest things to me, is this homeless

1010
01:01:53,619 --> 01:01:56,259
thing that they're doing, because if you're going to

1011
01:01:56,259 --> 01:01:59,139
destroy the economy and basically make it so that even

1012
01:01:59,139 --> 01:02:03,299
people with multiple jobs can't, you know, can't get by then,

1013
01:02:03,479 --> 01:02:07,319
then right? You know, it's not just going to be, and even then

1014
01:02:07,319 --> 01:02:11,279
it wouldn't be, right, you know, because of explain why. But even

1015
01:02:11,339 --> 01:02:14,579
then, I wouldn't recommend this, this homeless project. But you

1016
01:02:14,579 --> 01:02:18,119
know, it's not going to be necessarily because, you know,

1017
01:02:18,119 --> 01:02:21,679
you had a substance abuse problem or gambling problems.

1018
01:02:21,679 --> 01:02:24,199
This is going to be that the economy's pushed you out of your

1019
01:02:24,259 --> 01:02:27,559
house, and then, you know, if you get angry, or, you know, you

1020
01:02:27,559 --> 01:02:30,139
have the wrong tone of voice, when somebody tells you, you

1021
01:02:30,139 --> 01:02:34,159
know, get off the street, they just put you in a mental health

1022
01:02:34,159 --> 01:02:36,859
facility and be basically become a ward of the state and under

1023
01:02:36,859 --> 01:02:40,099
conservatorship. And if you know this is part, part of where this

1024
01:02:40,819 --> 01:02:44,199
defund the police stuff is going to go the middle ground is going

1025
01:02:44,199 --> 01:02:46,839
to be, oh, well, we're going to have AI. I've seen, I've written

1026
01:02:46,839 --> 01:02:47,439
about it, make

1027
01:02:47,440 --> 01:02:50,560
them more efficient by outsourcing police work to

1028
01:02:50,560 --> 01:02:54,820
artificial intelligence and predictive policing algorithms.

1029
01:02:55,660 --> 01:02:59,800
That's the Palantir bread and butter. And there's a litany of

1030
01:02:59,800 --> 01:03:01,200
companies that are doing that

1031
01:03:01,980 --> 01:03:04,020
right. And then on the other end, they also have for and

1032
01:03:04,020 --> 01:03:07,560
that's just to catch him, right? Oh, he's mentally ill. He might,

1033
01:03:07,560 --> 01:03:11,040
which means he might be a national security threat or or

1034
01:03:11,040 --> 01:03:12,780
criminal threat, etc. They

1035
01:03:13,500 --> 01:03:18,300
also want AI to determine if you're mentally ill. That is the

1036
01:03:18,300 --> 01:03:23,180
new CDC director, Susan manarez. She used to be head but this

1037
01:03:23,180 --> 01:03:28,700
number two at ARPA H, the health DARPA that Biden made and her

1038
01:03:28,700 --> 01:03:31,880
whole, one of her main priorities there was about

1039
01:03:31,880 --> 01:03:35,420
having like generative AI, determine if people screen

1040
01:03:35,420 --> 01:03:38,660
people for mental illness. And Trump, in his first term,

1041
01:03:39,800 --> 01:03:42,640
promised that he was or called on social media companies to

1042
01:03:42,640 --> 01:03:46,360
stop mass shootings before they happen, by going over their

1043
01:03:46,660 --> 01:03:50,560
their people's posts and like analyzing them. And then he was

1044
01:03:50,560 --> 01:03:54,520
considering this program for Harpa, which again was made

1045
01:03:54,520 --> 01:03:58,540
under Biden, under the name of ARPA H, to have people's social

1046
01:03:58,540 --> 01:04:01,380
media post analyzed by an algorithm to determine if

1047
01:04:01,380 --> 01:04:04,740
they're mentally ill and that they might be violent at some

1048
01:04:04,740 --> 01:04:08,100
point, and if they do, determine that, you know, so don't get

1049
01:04:08,100 --> 01:04:12,360
angry on social media, guys. But basically, you know, you could

1050
01:04:12,360 --> 01:04:16,380
be ordered to, like, a court ordered physician or like rehab

1051
01:04:16,380 --> 01:04:22,520
place or put under house arrest by an algorithm. So the homeless

1052
01:04:22,520 --> 01:04:25,220
stuff, I mean, people need to see it in the in the appropriate

1053
01:04:25,220 --> 01:04:27,740
context. And also the move to federalized police, if that

1054
01:04:27,740 --> 01:04:30,080
happens on a bigger scale, that just means the federal

1055
01:04:30,080 --> 01:04:32,540
government can be like, well, we're going to have the

1056
01:04:32,540 --> 01:04:36,080
federalized police outsource their police work to these

1057
01:04:36,080 --> 01:04:39,620
specific AI algorithm companies, you know.

1058
01:04:40,159 --> 01:04:42,399
And they're also going to do for the no cash bail, they're

1059
01:04:42,399 --> 01:04:45,339
going to say, Oh, you get arrested. So Palantir goes

1060
01:04:45,339 --> 01:04:47,859
predictive analytics say, Oh, you're this type of a threat,

1061
01:04:47,859 --> 01:04:50,859
and you go in and, oh, well, or let's say they get you after the

1062
01:04:50,919 --> 01:04:53,019
crime. Doesn't matter. They bring you in there, and they go,

1063
01:04:53,019 --> 01:04:57,519
Well, you know, bail. They're going to determine your bail not

1064
01:04:57,519 --> 01:05:00,779
by money amount, but by the same analytics. Oh, well, you know,

1065
01:05:00,779 --> 01:05:03,599
you've reoffended three times in the past, and you live in this

1066
01:05:03,599 --> 01:05:06,359
zip code where, you know, everybody's a criminal in your

1067
01:05:06,359 --> 01:05:09,419
neighborhood. So we're gonna add that to the analytics, whatever,

1068
01:05:09,659 --> 01:05:13,619
right? And that's gonna determine whether you get in or

1069
01:05:13,859 --> 01:05:16,679
whether you get so, you know, like people that think that

1070
01:05:16,679 --> 01:05:20,719
sending a mental health person and having a no cash. Like do

1071
01:05:20,719 --> 01:05:24,079
you think that if you I will take my chances with the prison?

1072
01:05:24,079 --> 01:05:26,899
I'm sorry, I'll take my chances with because at least I still

1073
01:05:26,899 --> 01:05:32,419
have, if I am going to the courts, I still have, you know,

1074
01:05:32,419 --> 01:05:36,139
I can still make a case, right pro se or with a lawyer, etc. If

1075
01:05:36,139 --> 01:05:39,199
you're mentally ill and they put you in conservatorship, doesn't

1076
01:05:39,199 --> 01:05:41,919
matter what you say. I don't care how lucid you are about it,

1077
01:05:41,919 --> 01:05:45,519
you don't have agency as a human being anymore, like you don't

1078
01:05:45,519 --> 01:05:48,279
get to challenge it in court. So I mean, that's terrifying to me,

1079
01:05:48,939 --> 01:05:52,239
and to your point about AI and mental health. So maybe this one

1080
01:05:52,239 --> 01:05:54,519
last thing we'll wrap up on. So I know you got to keep going a

1081
01:05:54,519 --> 01:05:59,979
little bit, but so I come to find out I got a big chunk of my

1082
01:05:59,979 --> 01:06:03,779
tutoring hours taken from me because at one of the schools,

1083
01:06:03,779 --> 01:06:07,019
this is the school right where I tutor, we're going to contract

1084
01:06:07,019 --> 01:06:10,379
with a company called upswing and Upswing

1085
01:06:11,579 --> 01:06:14,519
beat John, yeah, it's fun. Somebody's

1086
01:06:16,500 --> 01:06:19,080
gonna have to swing me up, because I'm gonna swing me. I'm

1087
01:06:19,080 --> 01:06:21,680
gonna swing me up by my bootstraps here when I don't

1088
01:06:21,680 --> 01:06:24,980
have a job, and by the end of the year. So they're gonna do

1089
01:06:24,980 --> 01:06:30,380
half and half. Now, okay, it's gonna give, it's using

1090
01:06:30,380 --> 01:06:34,520
generative AI to tutor students, but it also gives them mental

1091
01:06:34,520 --> 01:06:38,660
health checks, and it also will make them connections with like,

1092
01:06:38,660 --> 01:06:42,700
what they call basic needs, like transportation, food, etc.

1093
01:06:42,700 --> 01:06:46,900
There's a little tutorial on it. When you go into company and

1094
01:06:46,900 --> 01:06:50,620
it's, like, got this really happy music day, yeah. And like,

1095
01:06:50,620 --> 01:06:54,100
then there's, and it just shows a text, you know, between the,

1096
01:06:54,100 --> 01:06:56,500
you know, supposedly, the student and the bot. And it

1097
01:06:56,500 --> 01:06:59,200
starts off with, like, oh, you know, I need some help. And

1098
01:06:59,200 --> 01:07:01,680
like, this, AI is, like, overly Affirmative. It's like, it's

1099
01:07:01,680 --> 01:07:05,280
okay. A lot of students have that problem. Like, every

1100
01:07:05,280 --> 01:07:08,040
response before it gives them the solution is like, you know,

1101
01:07:08,040 --> 01:07:10,260
to me, if somebody talked to me like, I'm like, Man, I'm an

1102
01:07:10,260 --> 01:07:13,860
adult. Please don't, you know, please don't belittle me. But by

1103
01:07:13,860 --> 01:07:16,260
the end of the thing, I'll cut to the chase. By the end of the

1104
01:07:16,260 --> 01:07:18,900
thing this, this, you know, a little video they made. It's

1105
01:07:18,900 --> 01:07:22,280
like, it doesn't say I love you to the bot, but it's like, it

1106
01:07:22,280 --> 01:07:25,280
says, I can't believe you cared so much about me, and you're a

1107
01:07:25,280 --> 01:07:28,520
total stranger, and it clicks the heart emoji. So, I mean,

1108
01:07:28,520 --> 01:07:31,820
might as well say it loved it like so, you know. Now, so this

1109
01:07:31,820 --> 01:07:37,700
thing is going to be, you know, not just replacing me, but it's

1110
01:07:37,700 --> 01:07:40,460
basically going to be checking this student mental health. So

1111
01:07:40,460 --> 01:07:43,780
it's going to be also collecting the students education records

1112
01:07:43,840 --> 01:07:47,020
under FERPA and their health records, which is HIPAA, okay,

1113
01:07:47,020 --> 01:07:49,720
so I don't even know how, how they're gonna does it have two

1114
01:07:49,720 --> 01:07:53,200
different databases that they go into, or is it just allowed to

1115
01:07:53,200 --> 01:07:54,940
aggregate them? And then I don't

1116
01:07:54,940 --> 01:07:57,280
really aggregate them. I mean, like you said way earlier.

1117
01:07:57,280 --> 01:08:00,420
They want to remove the information silos, right? And

1118
01:08:00,420 --> 01:08:02,700
here's I'm gonna lean towards that. I just, you know,

1119
01:08:02,700 --> 01:08:05,160
I like to steel man. My case, here's what I'm gonna lean

1120
01:08:05,160 --> 01:08:08,220
towards that because half the companies that fund it are

1121
01:08:08,220 --> 01:08:12,240
venture capital firms and impact investing funds, and I had some

1122
01:08:12,240 --> 01:08:16,260
of them. I gotta go. Luckily, the director is actually

1123
01:08:16,260 --> 01:08:19,920
skeptical. I'm gonna go and meet with the director tomorrow. And

1124
01:08:20,280 --> 01:08:23,480
so I got some these tabs up, but it's a little fresh in my mind.

1125
01:08:23,480 --> 01:08:25,880
But a bunch of them. Social finance is one of them. I've

1126
01:08:25,880 --> 01:08:29,120
written about social finance in the previous piece, I mentioned

1127
01:08:29,120 --> 01:08:32,060
that they were in some partnership with one of the

1128
01:08:32,060 --> 01:08:35,240
impact investing companies that I wrote about in the first

1129
01:08:35,240 --> 01:08:39,020
project, 2025, piece. But I also mentioned social finance in a

1130
01:08:39,020 --> 01:08:44,860
video I did on UNESCO's study 11, a follow up to the article I

1131
01:08:44,860 --> 01:08:47,980
did for unlimited hangout and social finance partners with, I

1132
01:08:47,980 --> 01:08:50,860
think it's Future Learn, which is this online learning company

1133
01:08:50,860 --> 01:08:55,240
out of the UK that was partnering with study 11 back in

1134
01:08:55,240 --> 01:08:58,960
the day. But so, so when I'm so and then it's showing you like

1135
01:08:59,200 --> 01:09:04,140
on the it's, it's it's like, oh, we improve students by this

1136
01:09:04,140 --> 01:09:07,500
amount, this percent, had all these different metrics that

1137
01:09:07,500 --> 01:09:11,520
it's going to give you about how the students improving. Okay, so

1138
01:09:11,520 --> 01:09:14,940
if it's taking all that, all that data, and it says in it,

1139
01:09:14,940 --> 01:09:17,820
they sent us an email, it's going to keep it not just for

1140
01:09:17,820 --> 01:09:21,800
the student, but for the institution. So that means that

1141
01:09:21,980 --> 01:09:24,620
what I see here is that what we're leaning into is the

1142
01:09:24,620 --> 01:09:27,440
company is going to become or the school is going to be

1143
01:09:27,440 --> 01:09:30,500
leaning into social impact grants. I think social impact

1144
01:09:30,500 --> 01:09:33,260
grants are going to take off big, and you're going to have to

1145
01:09:33,260 --> 01:09:37,040
have the AI, because in order to get the the impact grant, you're

1146
01:09:37,100 --> 01:09:39,200
not just going to do an old school grant, like,

1147
01:09:39,200 --> 01:09:41,740
qualitatively, like, Hey, I got a good idea for the for the

1148
01:09:41,800 --> 01:09:44,320
money you want to hand out? No, no, you're going to have to show

1149
01:09:44,500 --> 01:09:48,100
very precise metrics, the types of metrics that can only be

1150
01:09:48,100 --> 01:09:51,760
calculated and crunched with something like generative AI, at

1151
01:09:51,760 --> 01:09:54,700
least at the speed and scale. Okay, and so. So, in other

1152
01:09:54,700 --> 01:09:58,240
words, the extra incentive for this company to get this upswing

1153
01:09:58,240 --> 01:10:01,860
isn't just to pay me less. Get me save money and not have me

1154
01:10:01,920 --> 01:10:05,820
tutoring, but they're going to use that data to go, oh, look,

1155
01:10:05,820 --> 01:10:09,120
we contracted with upswing, and our students mental health

1156
01:10:09,120 --> 01:10:12,000
increased by this much, and their education outcomes

1157
01:10:12,000 --> 01:10:15,960
increased. So then they'll take that data and they'll write a

1158
01:10:15,960 --> 01:10:19,440
grant proposal to some for Pay for Success for some big tech

1159
01:10:19,440 --> 01:10:23,780
company or venture capital firm or whatever, and and then that

1160
01:10:23,780 --> 01:10:27,860
person will, you know, that will be how they finance this new

1161
01:10:27,860 --> 01:10:31,640
education system. And so, I mean, like, I mean, he said we

1162
01:10:31,640 --> 01:10:34,820
got one semester, and I'm going to tell him, like, Listen, I

1163
01:10:34,820 --> 01:10:36,800
don't know what we're going to do, but at the end of the

1164
01:10:36,800 --> 01:10:39,200
semester, they're going to have a bunch of numbers to show that

1165
01:10:39,200 --> 01:10:42,340
it's either as efficient, or more efficient than paying us,

1166
01:10:42,340 --> 01:10:45,220
and I'm pretty sure that by next year, I'm going to be done

1167
01:10:45,220 --> 01:10:47,500
tutoring at that school. I mean, they're not going to let me

1168
01:10:47,560 --> 01:10:51,100
anymore. So that'd be maybe that's a happy ending.

1169
01:10:53,620 --> 01:10:56,380
Just think it's a it's a signpost of where we're going

1170
01:10:56,380 --> 01:10:59,500
with with AI, and how a lot of the hype around it. I mean,

1171
01:10:59,500 --> 01:11:04,980
ultimately, what's happening is just the the outsourcing of way

1172
01:11:04,980 --> 01:11:09,720
too much stuff to AI. And when you start outsourcing, you know,

1173
01:11:11,520 --> 01:11:16,500
education so extensively to AI. I mean, historically, you know,

1174
01:11:16,500 --> 01:11:19,500
student, teacher relationships were really important, you know.

1175
01:11:19,740 --> 01:11:23,000
And so having that relationship be built instead with a with an

1176
01:11:23,000 --> 01:11:26,420
algorithm, maybe they'll put it in a, like, a little nice, cute

1177
01:11:26,420 --> 01:11:28,940
robot casing, or whatever, like they're doing with domestic

1178
01:11:28,940 --> 01:11:31,820
robots that they're, you know, they have similar videos, like

1179
01:11:31,820 --> 01:11:34,040
you mentioned for those two where it's like, the kid is

1180
01:11:34,040 --> 01:11:38,000
like, I love you robot. It's like, very creepy. But the idea

1181
01:11:38,000 --> 01:11:41,620
is to sort of, you know, prepare the future generations for to

1182
01:11:41,620 --> 01:11:47,260
have this sort of very extreme connection to an AI that knows

1183
01:11:47,260 --> 01:11:50,020
everything about them and can predict what they're going to

1184
01:11:50,020 --> 01:11:54,880
do. And, you know, it basically, you know, leads to a very

1185
01:11:54,880 --> 01:11:59,920
Orwellian future when you consider to the impact of

1186
01:11:59,920 --> 01:12:02,340
wearables and some of these things that, some of these, you

1187
01:12:02,340 --> 01:12:05,460
know, Silicon Valley house philosophers like Yvonne Noah

1188
01:12:05,460 --> 01:12:08,760
Harari have said about, you know, hackable animals and the

1189
01:12:08,760 --> 01:12:12,180
end of Free Will when the algorithm has studied you so

1190
01:12:12,180 --> 01:12:15,180
extensively. And so even though a lot of this is frame, you

1191
01:12:15,180 --> 01:12:18,540
know, a lot of these introductions of AI into schools

1192
01:12:18,540 --> 01:12:21,980
and and things like that, is sort of being framed as having

1193
01:12:21,980 --> 01:12:25,760
kids learn how to use AI. It seems increasingly like where

1194
01:12:25,760 --> 01:12:30,440
it's going to end up is it's going to be about AI learning

1195
01:12:30,440 --> 01:12:36,740
how to use us most efficiently, not the inverse. And who does

1196
01:12:36,740 --> 01:12:37,940
that benefit? You know,

1197
01:12:38,479 --> 01:12:40,459
I've said it. I that was one of the that was, like my

1198
01:12:40,459 --> 01:12:43,179
epiphany moment, why I even wrote the book? Because I was

1199
01:12:43,179 --> 01:12:45,579
sitting there and I was tutoring for, I'll say the company now,

1200
01:12:45,579 --> 01:12:48,579
because it's the non compete clause is way past. But it was

1201
01:12:48,579 --> 01:12:51,219
Pearson. I used to work for Pearson. They had a subsidiary

1202
01:12:51,219 --> 01:12:53,859
called Smart thinking, and guess what? They paid me with my

1203
01:12:53,859 --> 01:12:57,279
master's degree. They paid me $11 an hour. Now, you know, mind

1204
01:12:57,279 --> 01:13:00,419
you, if I would have went and five years more school and got

1205
01:13:00,419 --> 01:13:03,239
my PhD, I could've got a whole 12 hours, dollars an hour. Now,

1206
01:13:03,239 --> 01:13:06,959
you know, so, but they had, one day, sent me an email and said,

1207
01:13:06,959 --> 01:13:10,199
Hey, IBM's Watson, which, you know, people don't know, was

1208
01:13:10,199 --> 01:13:14,519
basically like the premier AI system before generative AI, by

1209
01:13:14,519 --> 01:13:17,279
the way, it's named after Thomas J Watson, who did business with

1210
01:13:17,279 --> 01:13:21,259
Hitler and processed the punch cards for the Nazi concentration

1211
01:13:21,259 --> 01:13:24,859
camps, okay, but so I'm looking at it, and I go, well, so

1212
01:13:25,579 --> 01:13:27,739
basically, every day I go to work, this thing's gonna

1213
01:13:27,799 --> 01:13:31,159
basically data mine me and replace me. And I go, Well,

1214
01:13:31,159 --> 01:13:33,619
okay, so I start thinking, you know, you think down the line,

1215
01:13:33,619 --> 01:13:39,619
you go, Well, if it replaces me, then if it can teach better than

1216
01:13:39,619 --> 01:13:42,699
the teacher, then it can learn better than the student. In

1217
01:13:42,699 --> 01:13:44,499
other words, right? Like anything I can teach the

1218
01:13:44,499 --> 01:13:48,519
student, the AI can, right? It can do that just as good as it

1219
01:13:48,519 --> 01:13:51,459
can teach it. So not only did Are you making the teacher

1220
01:13:51,459 --> 01:13:54,579
obsolete, making the student obsolete, like over time,

1221
01:13:54,699 --> 01:13:57,699
whatever you might be gaining from the algorithm, or you might

1222
01:13:57,819 --> 01:14:01,079
so called, be learning from it, it's learning more and it's

1223
01:14:01,079 --> 01:14:05,339
learning faster. So the fact that it's data mining you and

1224
01:14:05,339 --> 01:14:08,459
you're basically feeding it is not a secondary effect. It is

1225
01:14:08,459 --> 01:14:12,359
the primary effect. Because if I can think that from just being a

1226
01:14:12,359 --> 01:14:15,119
tutor that's making $11 an hour and going like, well, let me see

1227
01:14:15,119 --> 01:14:18,359
if I just go three steps down the line. Know where the

1228
01:14:18,359 --> 01:14:20,879
ultimate outcome you're telling me these venture capitalists,

1229
01:14:20,879 --> 01:14:23,779
PayPal Mafia, these big technocrats that they don't know

1230
01:14:23,779 --> 01:14:25,999
that, of course, these are people that write the code.

1231
01:14:26,119 --> 01:14:28,939
Which goes back to why I you know, why I speculate that? You

1232
01:14:28,939 --> 01:14:31,399
know that timeline I gave you, from the Macy cybernetics

1233
01:14:31,399 --> 01:14:33,799
conferences, through venture capital, through Moore's law, to

1234
01:14:33,799 --> 01:14:37,039
911 to where we're at now. You know they were basically just

1235
01:14:37,039 --> 01:14:39,979
doing their scenario planning. You know, ran Corporation style

1236
01:14:39,979 --> 01:14:44,919
scenario planning for 1015, years at a time, right? The

1237
01:14:44,919 --> 01:14:48,579
scariest part for me now, though, you know, is something

1238
01:14:48,579 --> 01:14:51,819
that I never really thought of a whole lot, you know, when I was

1239
01:14:51,819 --> 01:14:55,479
seeing how eventually, you know, I'm looking at it, the Ed Tech,

1240
01:14:55,479 --> 01:14:58,839
and extrapolate out, well, it's basically just building AI. And

1241
01:14:58,839 --> 01:15:01,979
then you also look at, well. Just one part of this broader

1242
01:15:01,979 --> 01:15:04,619
panopticon. So the Ed Tech metrics, or the education

1243
01:15:04,619 --> 01:15:07,379
metrics and healthcare metrics and the workforce metrics and

1244
01:15:07,379 --> 01:15:10,739
the criminal justice metrics, it's all one system. At the end,

1245
01:15:11,219 --> 01:15:14,519
what I didn't anticipate was that people were gonna have

1246
01:15:14,579 --> 01:15:18,539
emotional attachments to these bots, which is frightening

1247
01:15:18,539 --> 01:15:21,919
because we watched a little short piece on, like people that

1248
01:15:21,919 --> 01:15:26,059
are dating their AI chat bots. Well, this product that I just

1249
01:15:26,059 --> 01:15:30,079
mentioned upswing, by the end of it, it's, it's advertising it to

1250
01:15:30,079 --> 01:15:33,079
the teachers, as if it's a great thing that your student is going

1251
01:15:33,079 --> 01:15:37,099
to have an emotional connection to a bot. Like, if it's one

1252
01:15:37,099 --> 01:15:39,859
thing for it to be pushing you around algorithmically, it's

1253
01:15:39,859 --> 01:15:42,939
another thing for you to actually bond with it. When that

1254
01:15:42,939 --> 01:15:47,679
happens, I just, you know, I don't know. I don't know where

1255
01:15:47,679 --> 01:15:50,259
we go at that point that is, that is terrifying to me,

1256
01:15:50,740 --> 01:15:52,900
yeah, well, ultimately, you know, I mean, there's been a lot

1257
01:15:52,900 --> 01:15:55,900
said about, like, the cognitive drain of regular people just

1258
01:15:55,900 --> 01:16:00,420
using AI for whatever, you know, but having that, I mean, I feel

1259
01:16:00,420 --> 01:16:03,180
like it's so different than having, like, a grown adult use

1260
01:16:03,300 --> 01:16:06,780
it and the cognitive drain that causes, versus a kid learning

1261
01:16:06,780 --> 01:16:10,680
stuff in schools and then having that cognitive drain happen,

1262
01:16:10,740 --> 01:16:14,880
like, before they're they've, like, learned very much at all,

1263
01:16:14,880 --> 01:16:18,120
or, like, learned how to think any sort of critical thinking.

1264
01:16:18,120 --> 01:16:20,900
Not that schools are good at teaching critical thinking

1265
01:16:20,900 --> 01:16:23,660
anymore. But you know what I mean? Like, it's just, I feel

1266
01:16:23,660 --> 01:16:27,920
like the developmental the impact on something that's still

1267
01:16:27,920 --> 01:16:30,500
in development versus something that's more developed is

1268
01:16:30,500 --> 01:16:34,700
obviously going to be the type of dependency that'll create on

1269
01:16:34,700 --> 01:16:36,860
AI, I think is going to be really different and really

1270
01:16:36,920 --> 01:16:41,020
significant and very troubling. And I just, the more I think

1271
01:16:41,020 --> 01:16:45,220
about AI, the more I kind of see it as, like, you're feeding

1272
01:16:45,220 --> 01:16:48,400
stuff into it to make it basically, you know, you're

1273
01:16:48,400 --> 01:16:51,880
feeding it to become this. You're like, basically giving it

1274
01:16:51,880 --> 01:16:56,620
your brain power to become a big, giant, global brain. And

1275
01:16:56,620 --> 01:17:00,100
then at the same time, it's like, also taking all of these

1276
01:17:00,100 --> 01:17:02,400
things, like the amount of pollution it's creating, it's

1277
01:17:02,400 --> 01:17:05,520
sucking up all the water, it's using all the power, and, like,

1278
01:17:05,520 --> 01:17:10,380
raising our power bills, like, Why? Why are people, like, still

1279
01:17:10,380 --> 01:17:13,920
using this? I mean, not that, I know I want to crap on people

1280
01:17:13,920 --> 01:17:16,380
for using it, you know, but it's like, the more we become

1281
01:17:16,380 --> 01:17:20,360
dependent on it, the more that trend is going to exacerbate to

1282
01:17:20,360 --> 01:17:24,800
the point where, like, we don't have brains left, we don't have

1283
01:17:24,800 --> 01:17:28,520
an environment left, and it just seems like crazy that there's

1284
01:17:28,520 --> 01:17:31,760
really no talk about it, and there's just all this hype about

1285
01:17:31,820 --> 01:17:35,420
it online, and also, like, AI slop everywhere, like, I feel

1286
01:17:35,420 --> 01:17:38,840
like even people in independent media are leaning so much on the

1287
01:17:38,900 --> 01:17:43,300
AI, and then, Like, I don't use that at all, but I have people,

1288
01:17:43,300 --> 01:17:48,160
I have like, AI bots and like aI using people clip up my

1289
01:17:48,160 --> 01:17:51,880
interviews, and they get like, tons of views on YouTube. And

1290
01:17:51,940 --> 01:17:54,880
it's like they put like clickbait titles of like things

1291
01:17:54,880 --> 01:17:55,720
I've never said.

1292
01:17:56,920 --> 01:17:59,380
They're everywhere. The way it's narrated too. It's like

1293
01:17:59,380 --> 01:18:00,040
that and like

1294
01:18:00,220 --> 01:18:02,760
and they attribute things to me that I've never said. And so

1295
01:18:02,760 --> 01:18:05,160
I'll have people be like, I don't like Whitney because she

1296
01:18:05,160 --> 01:18:07,260
says this. And I'm like, I've never said that. And then

1297
01:18:07,260 --> 01:18:11,520
they'll like, link to the video, and I'm like, oh my god, I can't

1298
01:18:11,520 --> 01:18:14,100
get rid of them. I tried to go on James Corbett, like, a year

1299
01:18:14,100 --> 01:18:16,800
ago to talk about this problem, but like, I feel like I have to

1300
01:18:16,800 --> 01:18:20,240
constantly remind people, and then, like, a lot of them will

1301
01:18:20,240 --> 01:18:23,000
say, like, Whitney's final warning, or Whitney warns. This

1302
01:18:23,000 --> 01:18:26,240
will happen by June or and then there's another one that comes

1303
01:18:26,240 --> 01:18:28,820
out two weeks later. This will happen by July. This will, I

1304
01:18:28,820 --> 01:18:31,400
mean, they like, constantly come out. And I'm like, I'm not

1305
01:18:31,400 --> 01:18:35,060
warning about anything with, like, a date. I've seen more

1306
01:18:35,060 --> 01:18:38,360
like, I mean, it's so crazy. And so it just,

1307
01:18:40,280 --> 01:18:43,120
I saw one where it cut you. It was like, it cut you off

1308
01:18:43,120 --> 01:18:44,920
yours, like you said something, like, halfway through the

1309
01:18:44,920 --> 01:18:47,500
sentence, it literally goes to the narrator, and they finish

1310
01:18:47,500 --> 01:18:51,880
your sentence. I was like, wait, what you know, but the cadence

1311
01:18:51,880 --> 01:18:54,640
of them in the way they like splice in these still images.

1312
01:18:54,640 --> 01:18:57,340
Like, I've seen a lot of videos where I'm like, this is AI.

1313
01:18:57,520 --> 01:18:57,880
Like,

1314
01:18:57,880 --> 01:19:01,740
you know they are AI. It sucks and they're but, I mean,

1315
01:19:01,740 --> 01:19:04,740
it's ultimately a weapon of perception at the end of the

1316
01:19:04,740 --> 01:19:09,240
day, you know? And so it's like people that like my interviews

1317
01:19:09,240 --> 01:19:12,660
and my points, I won't say what they want me to say, so they've

1318
01:19:12,660 --> 01:19:15,900
taken AI to make it sound like I'm saying what they want me to

1319
01:19:15,900 --> 01:19:18,960
say, even though I'm not saying it isn't that crazy.

1320
01:19:19,380 --> 01:19:22,700
To your point, uh, look, you know, he said, I don't want to

1321
01:19:22,700 --> 01:19:25,760
poo poo on people that are using it. But, you know, I think

1322
01:19:25,760 --> 01:19:30,320
you've also been had the black pill label thrown at you, like,

1323
01:19:30,320 --> 01:19:33,320
I have you here. You want a black pill? I'll give you a

1324
01:19:33,320 --> 01:19:36,500
black pill. Keep using it, you know, I'm sorry. I don't want

1325
01:19:36,500 --> 01:19:38,960
to, like, you know, poo poo on people who are using it, because

1326
01:19:38,960 --> 01:19:41,620
I lots friends and, you know, people in, you know, my

1327
01:19:41,620 --> 01:19:46,360
colleagues, etc. Here's the thing, though, like, I expect

1328
01:19:46,360 --> 01:19:48,760
the average consumer to use it because it's, you know,

1329
01:19:48,760 --> 01:19:51,580
convenient, etc, and, you know, it's just, if you just buy into

1330
01:19:51,640 --> 01:19:55,120
the way it's commercialized. I expect the administrators and

1331
01:19:55,120 --> 01:19:57,280
the people that run big companies, right, because it's

1332
01:19:57,280 --> 01:20:00,120
going to make them profit. I don't expect people that. I've

1333
01:20:00,120 --> 01:20:02,640
had these types of conversations, conversations

1334
01:20:02,640 --> 01:20:05,040
with people that are on the snow wavelength, people didn't know

1335
01:20:05,040 --> 01:20:09,120
about social credit, technocracy, transhumanism, all

1336
01:20:09,120 --> 01:20:12,060
of this, people that know that, like I was in a meeting the

1337
01:20:12,060 --> 01:20:15,720
other day for a conference, right? And all nice people and

1338
01:20:15,720 --> 01:20:18,060
everything, but somebody was supposed to take notes for the

1339
01:20:18,060 --> 01:20:20,400
conference. Well, I didn't register at the time, and I'm

1340
01:20:20,400 --> 01:20:23,240
looking at it, and it and it didn't, didn't mean anything to

1341
01:20:23,240 --> 01:20:25,700
me. It's time. But one of the windows in the in the meeting

1342
01:20:25,700 --> 01:20:30,440
was like something.ai and didn't have a person on it like so

1343
01:20:30,440 --> 01:20:33,380
later they email out the minutes, you know, because the

1344
01:20:33,380 --> 01:20:35,780
person thought that would be faster than writing them down.

1345
01:20:36,200 --> 01:20:39,560
Well, that's fine enough, except that when you read the printout

1346
01:20:39,620 --> 01:20:44,440
of the notes, it had three other metrics in there. One was, uh,

1347
01:20:44,740 --> 01:20:49,060
was is, did you get the the objective finished, right? So,

1348
01:20:49,060 --> 01:20:51,700
like, whatever the title of the thing was, did you actually come

1349
01:20:51,700 --> 01:20:55,840
to the solution? The two others ones, one was engagement, and

1350
01:20:55,840 --> 01:20:58,840
the other one was like, interest or something. So engagement was

1351
01:20:58,840 --> 01:21:01,380
like, How often were people participating? But the other one

1352
01:21:01,380 --> 01:21:03,780
was, like, an emotional analytic, like, did we like it?

1353
01:21:03,780 --> 01:21:06,240
So I don't know if it was just going qualitatively on the

1354
01:21:06,240 --> 01:21:09,540
things we said, or if it had facial recognition and was like

1355
01:21:09,540 --> 01:21:12,180
looking at, like the facial expressions. But this is in the

1356
01:21:12,780 --> 01:21:15,420
part of this conversation, right? We're talking about part

1357
01:21:15,420 --> 01:21:19,440
of it. We discussed my presentation and data mining and

1358
01:21:19,440 --> 01:21:23,660
social we talked so if you know, if the people that, the few

1359
01:21:23,660 --> 01:21:26,720
people that are aware of where this goes, are just going to

1360
01:21:26,720 --> 01:21:29,780
lean into it, that's a black pill that you're going to

1361
01:21:29,780 --> 01:21:33,080
swallow, whether you want to or not, because you know people

1362
01:21:33,320 --> 01:21:36,260
you're just getting I feel like I'm going to get dragged into

1363
01:21:36,260 --> 01:21:38,600
this, whether I use it or not. The

1364
01:21:39,680 --> 01:21:44,440
slipperiest slippery slope, I feel like, and the more you

1365
01:21:44,440 --> 01:21:48,160
slip down the slippery slope, the harder it is to get back up.

1366
01:21:48,160 --> 01:21:51,400
So I know a lot of people sort of in this space, like you're

1367
01:21:51,400 --> 01:21:55,120
mentioning, you know, use it for only a few things. But

1368
01:21:55,120 --> 01:21:58,360
eventually, if you don't check yourself frequently, your

1369
01:21:58,360 --> 01:22:03,180
reliance on it grows and grows and grows, and then how do you

1370
01:22:03,180 --> 01:22:07,080
get back to a point where you're not using it at all? Or, you

1371
01:22:07,080 --> 01:22:10,920
know, it just kind of it gets harder for people. The

1372
01:22:10,920 --> 01:22:16,920
dependency thing is super real, and that's really troubling. And

1373
01:22:16,920 --> 01:22:19,800
also, I mean, some of the stories about people like doing

1374
01:22:19,800 --> 01:22:23,180
insane stuff and, like, starting new religions with chat GBT and

1375
01:22:23,180 --> 01:22:26,900
all this stuff. I mean, it's crazy. And having the idea of

1376
01:22:26,900 --> 01:22:29,720
that being in, like, elementary schools, and telling elementary

1377
01:22:29,720 --> 01:22:32,780
school kids to, like, develop relationships with this stuff,

1378
01:22:32,780 --> 01:22:36,260
and middle schoolers, like, if adults are having like, these

1379
01:22:36,260 --> 01:22:39,080
psychotic episodes where, like, they're creating their own cult

1380
01:22:39,080 --> 01:22:42,500
with chat GPT and stuff. I mean, you don't think that's going to

1381
01:22:42,500 --> 01:22:45,520
be even worse. To be even worse with, like, preteens and teens

1382
01:22:45,520 --> 01:22:47,620
and kids, you know, with

1383
01:22:47,740 --> 01:22:49,960
with trans, you know, like, so people that are worried about

1384
01:22:49,960 --> 01:22:52,420
transhumanism and they're worried about neural link in the

1385
01:22:52,420 --> 01:22:55,780
brain, shit, dude, you don't have to have anything plugged

1386
01:22:55,780 --> 01:22:59,740
into you to have, uh, technology, take over half of

1387
01:22:59,740 --> 01:23:03,000
your consciousness. All you got to do is outsource half of your

1388
01:23:03,000 --> 01:23:06,300
thinking to generative AI. Now, you know, I'm not a math

1389
01:23:06,300 --> 01:23:09,060
teacher, maybe a generative a large language model might be

1390
01:23:09,720 --> 01:23:13,440
maybe could help you with like numeracy, quantitative skills,

1391
01:23:13,440 --> 01:23:16,140
but I'll tell you that as a language arts instructor, as a

1392
01:23:16,140 --> 01:23:21,020
as an instructor of Writing and Rhetoric, that if you're using

1393
01:23:21,020 --> 01:23:23,900
generative AI, I don't care if it's just a Grammarly to, like,

1394
01:23:23,900 --> 01:23:26,060
make your sentences more efficient, but if you're

1395
01:23:26,060 --> 01:23:29,240
definitely, if you're doing it to organize your paper or to

1396
01:23:29,360 --> 01:23:32,780
make the connection between the thesis and the topic sentence,

1397
01:23:32,840 --> 01:23:36,980
you know, more clear. If you're doing that, you're outsourcing

1398
01:23:36,980 --> 01:23:40,660
your thinking skills to generative AI. And if, if

1399
01:23:40,840 --> 01:23:43,060
there's one thing that makes you a better writer, a better

1400
01:23:43,060 --> 01:23:47,020
speaker, better communicator, it's having an inner monolog and

1401
01:23:47,020 --> 01:23:50,980
monitoring it. It's having an introspective awareness of

1402
01:23:50,980 --> 01:23:54,820
whether or not the words in your head right, the categories of

1403
01:23:54,820 --> 01:23:58,060
your mind match the categories of reality, being able to look

1404
01:23:58,060 --> 01:24:01,020
in and see, did I contradict myself, right? And so when

1405
01:24:01,020 --> 01:24:03,720
you're writing a piece, I had a moment where it was like, you

1406
01:24:03,840 --> 01:24:06,120
know, I wonder if I could just do, like, a rough draft, really,

1407
01:24:06,120 --> 01:24:08,460
like, throw all my citations in there and just have it, throw

1408
01:24:08,460 --> 01:24:11,340
stuff in there. Well, the problem with that is that, like,

1409
01:24:11,460 --> 01:24:14,100
for me to be able to have this conversation as efficiently as

1410
01:24:14,100 --> 01:24:17,580
possible, a lot of that comes from the recursive process, not

1411
01:24:17,580 --> 01:24:20,600
just of, right, throwing information on a page and having

1412
01:24:20,600 --> 01:24:24,080
something organized it, but like the process where I write, make

1413
01:24:24,080 --> 01:24:26,660
sure that the thesis connects to each topic. Sense each topic

1414
01:24:26,660 --> 01:24:29,000
sentence has reasoning evidence warrant that the summary

1415
01:24:29,000 --> 01:24:31,880
statement connects right, that there's transitions between each

1416
01:24:31,880 --> 01:24:34,640
paragraph, that everything is cohesive, that I have a citation

1417
01:24:34,640 --> 01:24:37,040
for each sentence, that there's no wasted words at each side,

1418
01:24:37,160 --> 01:24:40,660
that recursive process is not only what makes me better at

1419
01:24:40,720 --> 01:24:44,560
speaking and writing, but it's also the my ability gives me the

1420
01:24:44,560 --> 01:24:48,460
ability to actually have a cognitive map of the thing that

1421
01:24:48,460 --> 01:24:52,480
I just researched and wrote about. So, you know, there is no

1422
01:24:52,480 --> 01:24:56,620
way in which you can have this thing do part of your reading,

1423
01:24:56,620 --> 01:25:00,300
writing or speaking, and have the your language. Charge

1424
01:25:00,300 --> 01:25:03,180
muscles in your brain atrophy. There's no way you can do it,

1425
01:25:03,420 --> 01:25:04,860
right? And so at that point, the

1426
01:25:04,859 --> 01:25:07,619
studies that have been done on it, they basically show that

1427
01:25:07,619 --> 01:25:10,499
when kids do that, they don't retain anything, like they're

1428
01:25:10,499 --> 01:25:13,019
able to execute the task with AI, but they didn't actually

1429
01:25:13,019 --> 01:25:15,599
like learn anything, and the information just doesn't stay in

1430
01:25:15,599 --> 01:25:18,359
the like they've learned, literally nothing, you know.

1431
01:25:18,659 --> 01:25:21,739
And add the emotional attachment to it on top of that,

1432
01:25:25,399 --> 01:25:28,459
getting weird. And now, you know, they'll dress them up as

1433
01:25:28,519 --> 01:25:33,739
anime girls, or, I guess, like the grok one. And grok also has

1434
01:25:33,739 --> 01:25:38,659
an Alex Jones Alter Ego, so, you know, a chat bot for every

1435
01:25:39,259 --> 01:25:44,199
segment of the populace, I guess it's a mess. Well, John, I

1436
01:25:44,199 --> 01:25:48,939
probably have to run here, but it's been a great conversation,

1437
01:25:48,939 --> 01:25:52,719
I think. And are there? Do you have any final thoughts as we

1438
01:25:52,899 --> 01:25:53,439
wrap up?

1439
01:25:53,979 --> 01:25:56,559
No, that was that was good. We covered pretty much the

1440
01:25:56,559 --> 01:25:57,159
waterfront.

1441
01:25:57,520 --> 01:26:01,620
Okay, super well, where can people find your work and follow

1442
01:26:01,620 --> 01:26:02,400
you and support you.

1443
01:26:03,059 --> 01:26:05,879
So all my most recent articles always, you can find

1444
01:26:05,879 --> 01:26:08,759
that unlimited Hangout. I'm always kind of slow on updating

1445
01:26:08,759 --> 01:26:11,759
the website, so that's where you find the most recent articles.

1446
01:26:12,119 --> 01:26:16,319
I'm Taoist professor on X but the website is school world

1447
01:26:16,379 --> 01:26:19,919
order dot info, which has links to all the social media. There's

1448
01:26:19,919 --> 01:26:23,059
also a link to trying day where you can get my book that school

1449
01:26:23,059 --> 01:26:27,079
world order the technocratic globalization of corporatized

1450
01:26:27,079 --> 01:26:29,179
education. Well,

1451
01:26:29,180 --> 01:26:32,120
thanks so much. And thanks to everybody that that listens

1452
01:26:32,120 --> 01:26:34,700
to this podcast and that supports it. And if you found

1453
01:26:34,700 --> 01:26:38,660
this content interesting, please share far and wide, especially

1454
01:26:38,660 --> 01:26:42,100
as social media algorithms become more restrictive, and it

1455
01:26:42,100 --> 01:26:45,400
gets harder to distribute important information like this.

1456
01:26:45,700 --> 01:26:49,000
And yeah, thanks a lot, John for being here. And thanks again to

1457
01:26:49,000 --> 01:26:51,700
everyone who listened, and we'll catch you all in The next

1458
01:26:51,700 --> 01:26:52,060
episode.

1459
01:27:02,860 --> 01:30:00,120
You You You You You You You. I'm.