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Speaker 1: Ah, beaut force. If it doesn't work, you're just not

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Speaker 1: using enough. You're listening to Software Radio Special Operations, military

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Speaker 1: news and straight talk with the guys and the community

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Speaker 1: Software dot Com on time on Target. Very excited to

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Speaker 1: have John Rob coming on. And I know you've been

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Speaker 1: a followers work for years now. Yeah, I started reading

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Speaker 1: John Rob's website. It's called still spelled like Goldal Guerrillas.

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Speaker 1: And Um, he does a lot of theorizing and study

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Speaker 1: of emerging tactics and strategies. Um. He's a very smart

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Speaker 1: guy on essentially the future of warfare, the future of conflict,

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Speaker 1: but also a lot of other subjects. You know, he

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Speaker 1: talked a lot about AI. Um you can even get

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Speaker 1: into some sort of like the cultural uh and um

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Speaker 1: you guess you could say, like mega trends in national

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Speaker 1: and international politics, um, where things are going in the

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Speaker 1: coming years. Um. So you know, we'll definitely talk to

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Speaker 1: him about all that. And he himself is also a

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Speaker 1: former soft guy. I believe he was in soft aviation

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Speaker 1: in the Air Force. Yeah, he was. I was looking

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Speaker 1: up his bio, but took a very unconventional career path

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Speaker 1: after I mean, other than the writing, he's he's not

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Speaker 1: writing about typical stuff that former military guys usually right about. No,

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Speaker 1: he's a futurist in many ways. Um. I feel like

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Speaker 1: he's seen you know, he hasn't. He's able to see

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Speaker 1: what's coming at us in the future and the way

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Speaker 1: things are developing. And it's often very different, um than

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Speaker 1: what you'll hear from other sources, you know. I for

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Speaker 1: when I was reading his work, I started reading it

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Speaker 1: around like two thousand five, two thousand six, and I

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Speaker 1: think John rob was looking at the insurgency brewing in

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Speaker 1: Iraq primarily at that time, and he was seeing how

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Speaker 1: quickly the insurgency evolved. Um. But he of course he

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Speaker 1: can comment on his own work and UM, but he

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Speaker 1: he sees these things and thinking in his thinking about

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Speaker 1: tactics and strategy. He's just like light years ahead of

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Speaker 1: where the Department of Defenses today. And I could see

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Speaker 1: that when I was, you know, a young soldier. Um.

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Speaker 1: But he's still out there, he's still doing some good work.

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Speaker 1: So we'll get into all of that with him. That's cool. Yeah,

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Speaker 1: I'm excited to hear from him. I wanted to mention actually,

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Speaker 1: the first thing that I think I should get into

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Speaker 1: is Oliver North named president of the n r A

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Speaker 1: and because of that, right when I right when I

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Speaker 1: heard the news, I was like, I gotta grab equip

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Speaker 1: of when he was on soft reap radio. So I

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Speaker 1: put that up there for people to hear. I would

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Speaker 1: love to have him back on and talk about the news. Um.

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Speaker 1: I know that there's like obviously some controversy on Twitter

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Speaker 1: about you know, his past or on Contra. I think

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Speaker 1: it's a good pick. I think Aliver North is a

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Speaker 1: very well white guy, and uh, I'm glad to him

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Speaker 1: his president. He's very controversial, um. I mean when I

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Speaker 1: heard the news, I thought that the n r A

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Speaker 1: was like deliberately trolling. Honestly, Like, I think they picked

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Speaker 1: that because they picked him because they knew he was

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Speaker 1: such he'd be such an inflammatory figure for the left.

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Speaker 1: That's true, but he is. I don't know, I've met

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Speaker 1: the guy. I like the guy. Um. I think he's

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Speaker 1: very smart. And also I think people bringing up things

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Speaker 1: like Iran Contra decades ago has nothing to do with

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Speaker 1: the gun rights issue, Like it shouldn't detract him from

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Speaker 1: being the spokesman for a gun rights ad because he

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Speaker 1: grew up in my opinion, I mean, yes, and no,

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Speaker 1: but I mean anybody who gets appointed to a position,

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Speaker 1: people are going to look into their past and see

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Speaker 1: how clean you are, not, which you know brings us

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Speaker 1: to our beloved New York City Attorney General. Yes, I

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Speaker 1: was never mentioned that as well. And the reason I

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Speaker 1: thought it was interesting to bring up is because we

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Speaker 1: we got into a whole discussion last episode about the

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Speaker 1: whole feminism movement and toxic masculinity. And here we have

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Speaker 1: this guy who was this huge advocate for the Me

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Speaker 1: too movement for feminism. He was involved in the civil

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Speaker 1: suit against Harvey Weinstein, I believe. Yeah. Like, I even

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Speaker 1: pulled up a tweet of his. I I wrote something

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Speaker 1: about it, but I'll read it. I like the tweet

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Speaker 1: he sent out where he was talking about how like

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Speaker 1: slavery is still coated into our legal system, we need

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Speaker 1: to fight it. And that turns out he was calling

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Speaker 1: his girlfriend like a brown slave, call me master, and

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Speaker 1: like slapping her around and stuff, and and according to them,

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Speaker 1: from what I've read, not consensual at all. But he's

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Speaker 1: trying to play it off. And yeah, I like this tweet.

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Speaker 1: I'm a proud feminist and I am committed to using

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Speaker 1: the privilege of my office to advance equality, as every

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Speaker 1: elected official should be. And you pretty much said this

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Speaker 1: last episode that these guys who go over the top

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Speaker 1: to say like how feminist they are, they tend to be. Yeah,

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Speaker 1: they're throwing up a smoke screen. Yeah, when you're when

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Speaker 1: you're virtue signaling that much, when you're like out there,

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Speaker 1: hot dog in it, you know, hashtag in it. You

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Speaker 1: know me too. I'm a feminist. I'm a male feminist.

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Speaker 1: I'm with you girls, Let's go. Yeah. I mean those

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Speaker 1: people who are like really out there hot dog and it,

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Speaker 1: I never trust them. I always feel like they're throwing

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Speaker 1: up a smoke screen. It's like them, like the guy,

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Speaker 1: like a guy who's incredibly homophobic. You're like, I think

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Speaker 1: the dude's overcompensating for something, you know what I mean.

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Speaker 1: And that's the case with this guy too. He's throwing

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Speaker 1: up a smoke screen. You know. The guy just treats

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Speaker 1: I mean, it seemed pretty clear. I read the New

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Speaker 1: Yorker article last night, and this guy just treats women

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Speaker 1: like shit. I mean literally, it's like four different women

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Speaker 1: slapping girls around. Well, there's going to be more than

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Speaker 1: four for women. That's just the four main sources in

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Speaker 1: the In the article, Um spinning on women, slapping them around,

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Speaker 1: hitting them, getting drunk all the time, which is not

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Speaker 1: necessarily a crime. But I'm getting intoxicated and beating women

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Speaker 1: and calling them horrors and sluts and all this kind

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Speaker 1: of stuff. It's like, yeah, yeah, And considering that he resigned,

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Speaker 1: I think it's said a few hours after the article

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Speaker 1: was published, that's a pretty big admission of guilt there.

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Speaker 1: I would say, yeah, I read that. I said, I

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Speaker 1: read that article in the New Yorker last night after

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Speaker 1: actually b k Um mentioned it, and I was like,

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Speaker 1: what are you talking about? What are you talking about, dude,

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Speaker 1: And he's like, oh, your attorney general is going down, man.

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Speaker 1: And so I went and I read the article and

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Speaker 1: I finished reading it, and I walked downstairs and I

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Speaker 1: told my wife. I was like, yeah, our attorney general's fucked,

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Speaker 1: but he hasn't coming. And then like an hour later,

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Speaker 1: she she turns to me and she's like, yeah, he resigned.

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Speaker 1: You know what I hate too. I saw an article

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Speaker 1: on CNN that said it was like yet another politician

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Speaker 1: who has let us down, like as if you know

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Speaker 1: they're tied to him. Some op ed and it's just

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Speaker 1: like I never feel the way because I don't think

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Speaker 1: you should put your faith in politics, and I don't

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Speaker 1: think politicians are on our side. Yeah, I don't think

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Speaker 1: any of politician is aligned with me. I don't think

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Speaker 1: that any one of them is my friend or gives

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Speaker 1: a shit about me. The only reason politician gives a

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Speaker 1: shit about you is because you can get them into office.

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Speaker 1: And once you get them into office, their primary goal

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Speaker 1: becomes to get you to get themselves reelected and to

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Speaker 1: get you to keep them in office. It's not the

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Speaker 1: there like nice like hey and Jack, I'm your buddy.

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Speaker 1: We're allied, Bro, we're the same. No, we're not. You know,

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Speaker 1: politicians are part of an elite class and they are

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Speaker 1: self interested actors making sure that they get what they

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Speaker 1: want and you don't. And it's as simple as that.

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Speaker 1: And the only reason why they do anything is because

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Speaker 1: we demanded of them and we hold their feet to

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Speaker 1: the fire. So I mean thinking that like, oh, he's

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Speaker 1: our guy, it's a bunch of bullshit. Uh, you know.

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Speaker 1: And I respect the New Yorker for sticking to principles

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Speaker 1: and prioritizing the truth ahead of a political agenda and

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Speaker 1: I mean, it's a New Yorker magazine. It's fair to

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Speaker 1: say that these are, you know, the intellectual liberal elites

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Speaker 1: of New York City. But they went after this guy

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Speaker 1: despite him being a prominent Democrat, and a lot of

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Speaker 1: people would say, oh, well, he's too important for the movement,

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Speaker 1: he's too important for our politics. Were like, like we

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Speaker 1: saw happen with Al Franklin, Remember all of that Al Franken. Yeah, um,

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Speaker 1: you know he's a Democrat. We need to keep him

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Speaker 1: in office. He's allied And it's like, I don't know,

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Speaker 1: that's such a weird thing for me to hear. It's

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Speaker 1: I think I would also think the New Yorker, like, yes,

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Speaker 1: I give them credit, but when you have a scooped

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Speaker 1: that big, I would think they're not going to pass

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Speaker 1: it up no matter who what's done. I think there's

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Speaker 1: still tremendous pressure um internally, and they're gonna catch heat

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Speaker 1: from their own people's their own peer group, you know,

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Speaker 1: just like I catch heat from my peer group because

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Speaker 1: I say things about the military that people in the

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Speaker 1: military or veterans but may not want out there. But

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Speaker 1: I have to prioritize the truth ahead of what's comfortable

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Speaker 1: because that's my job. And I mean I think the

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Speaker 1: New Yorker did the same in their case, in their

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Speaker 1: um culture and their their peers and journalism. And here

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Speaker 1: you know, the quote unquote liberal elite New York City.

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Speaker 1: I'm sure we'll criticize them for some of those decisions,

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Speaker 1: but you know, they went ahead and they did the

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Speaker 1: right thing. Yeah, I Like I said, I also read

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Speaker 1: the article like yourself. Um, pretty horrifying accounts, definitely, And

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Speaker 1: and the women were very queer because, like I said,

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Speaker 1: his excuse was just this role play this and it's

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Speaker 1: a it's he has an m O. Right, it's across

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Speaker 1: all these different women that the the the abuse files

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Speaker 1: a pattern. It's pretty much the same. Yeah. To be fair, though,

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Speaker 1: I actually didn't even know the name Eric Schneiderman until now. No,

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Speaker 1: I never paid attention to him. Like I said, I

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Speaker 1: don't think that politicians are our friends. Yeah, that's why

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Speaker 1: I always I mean, I wouldn't say all conservatives feel

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Speaker 1: this way, but I guess principal constitutional conservatives have this

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Speaker 1: idea of like, just follow the constitution and kind of

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Speaker 1: get out of my way type of thing. And I think,

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Speaker 1: you know, you do see it with Trump's I can't

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Speaker 1: just say the left, but they have this thing where

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Speaker 1: it's almost like they fall in love with these politicians.

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Speaker 1: The way the way they like falled over Hillary and

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Speaker 1: it absolutely happened, happened with Obama and it happened with Trump,

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Speaker 1: is that they absolutely, yeah, they fell in love. It's incredible.

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Speaker 1: It's incredible to watch. And oftentimes it's the same people

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Speaker 1: who criticize the Obama zombies as being like cult followers

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Speaker 1: and you're drinking the kool aid. They did the same

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Speaker 1: thing with Trump. They fell in love with the guy. Yeah.

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Speaker 1: And I never try to be too you know, uh,

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Speaker 1: I don't. I'll criticize whoever it is if they're on

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Speaker 1: the right of the left, that they're doing something I

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Speaker 1: don't agree with. I mean, the only politician I ever

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Speaker 1: saw that I was like, I agree with this manager

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Speaker 1: about everything was Ron Paul. But if he says something. Actually,

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Speaker 1: he said a few things here and there that I've

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Speaker 1: been critical of. I remember he wrote some pretty inflammatory

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Speaker 1: and I thought just um uncalled for stuff about Chris

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Speaker 1: Kyle after he died on Twitter. I don't remember that.

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Speaker 1: I do remember that I thought it was really uncalled

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Speaker 1: for um, but yeah, I don't think you should fall

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Speaker 1: in love with politicians generally. There we're all flawed human

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Speaker 1: beings and they if you want them to uphold your

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Speaker 1: principles and all that, that's great. But yeah, sometimes this

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Speaker 1: is how they turn out to be. And especially it's

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Speaker 1: like in New York seeing this pattern Anthony Weener, this guy,

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Speaker 1: I mean, this goes I mean, this goes back to

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Speaker 1: like ancient Rome. I mean, why do I have to

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Speaker 1: even tell people that politicians aren't our friends? I mean,

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Speaker 1: these are these people are elites. They like to lord

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Speaker 1: over us, they like to abuse us, and the only

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Speaker 1: reason why they don't is because we hold them accountable. Yeah,

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Speaker 1: that's it. I mean there are no like oh the

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Speaker 1: you know, the conservative politicians are not our friends. The

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Speaker 1: liberal politicians are not our friends. They're really they're all

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Speaker 1: a bunch of assholes who go to the same cocktail parties.

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Speaker 1: I mean they all hang out together. You want to

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Speaker 1: talk about collusion, These people collude with one another to

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Speaker 1: stay empower. Yeah, which which they have to to be fair,

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Speaker 1: I mean, I also don't want to see us in

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Speaker 1: a um well, yeah, they have to be a state

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Speaker 1: of civil war where you know, some people do want

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Speaker 1: to see where it's just like Democrats aren't even talking

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Speaker 1: to Republicans. They won't discuss anything, they won't we won't

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Speaker 1: work on any legislat together. Like that's not a good

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Speaker 1: way of doing No, it's not, And I'm not I'm

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Speaker 1: definitely not saying that our politicians should not work together.

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Speaker 1: Uh in us as politically um interested people, that we

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Speaker 1: shouldn't negotiate. I mean, that's democracies that you you come

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Speaker 1: together and you negotiate. You're not going to agree on

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Speaker 1: all issues, but maybe you'll find some common ground. And

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Speaker 1: if we don't do that, then legislation is never gonna

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Speaker 1: get passed on any subject. And oftentimes the best periods

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Speaker 1: of American history, or when we had like two separate

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Speaker 1: branches of government, when we had like a Democrat Congress

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Speaker 1: and a Republican president, you know, people would say people

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Speaker 1: always talk about Reagan and Tip O'Neil or new get

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Speaker 1: Rich and Bill quentin Um. Those are years that a

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Speaker 1: lot of people think we're the best years of our car. Yeah. Well,

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Speaker 1: I don't know if I necessarily agree, but I'm just

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Speaker 1: I think a lot of times when we have one

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Speaker 1: branch in total power. It's well, the left and the

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Speaker 1: right are just two sides of the same coin, and

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Speaker 1: they desperately need each other. They need each other wrestling. Yeah, yeah,

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Speaker 1: it's pro wrestling. Because when Republicans are in office, they

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Speaker 1: need someone to blame for their failures, and when Democrats

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Speaker 1: are in power, they need someone that they can blame

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Speaker 1: for their failures. So, I mean, these two like they

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Speaker 1: need each other. If it was just one party, then

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Speaker 1: they would be responsible for everything. And then so what

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Speaker 1: does one party become. It becomes something like communism, it

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Speaker 1: becomes something uh that claims to be utopian. It has

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Speaker 1: to be you know, you're sounding like Soviet Russia or

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Speaker 1: North Korea. It's like, man, you guys got it really good.

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Speaker 1: We're living in a utopia. It's those people over there

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Speaker 1: in Western civilization. They're really screwed. You know. It just

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Speaker 1: turns into this nutty nonsense. So or you know, Trump

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Speaker 1: is a fascist. On the other side, people people come

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Speaker 1: up with all these weird ideas about politics and how

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Speaker 1: you know, all the left is destroying America? Are all

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Speaker 1: the right a bunch of neo fascists and they're destroying America?

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Speaker 1: It's like, no, these people they're they're all basically the same.

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Speaker 1: They have way more in common with each other than

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Speaker 1: they do with any of us, and they all desperately,

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Speaker 1: you know, the left and right desperately need one another

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Speaker 1: in order to perpetuate the system that they exist in. Yeah, um,

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Speaker 1: I know, we want to talk about this article that

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Speaker 1: ties into John rob stuff, The Meet the Renegades of

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Speaker 1: the NIAL. I don't know if that necessarily ties directly

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Speaker 1: into Rob's work, Um, but John Robb has commented on

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Speaker 1: um sort of like cultural trends and things like that,

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Speaker 1: and we can ask him about it. He might have

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Speaker 1: some thoughts. I thought it was a good article though.

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Speaker 1: You sent it to me, and it talks about kind

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Speaker 1: of these people who are not in the mainstream going

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Speaker 1: on podcast, like Joe Rose. The New York Times article,

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Speaker 1: what's it called, it's They'll Meet the Renegades of the

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Speaker 1: Intellectual Dark Web, So it's spotlights people that I actually

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Speaker 1: I'm a fan of it. I know you're a fan.

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Speaker 1: I know you're Jordan Peterson, you like a lot. Christina

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Speaker 1: hoff Summers is talked about in there. Ben Shapiro, who

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Speaker 1: I greatly like, I know share I know a little

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Speaker 1: bit about Shapiro. I know, um familiar with Peterson's work,

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Speaker 1: but the othersn't mentioned in the article. I don't really

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Speaker 1: know so well Sam Harris. But I think that the

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Speaker 1: point was that these are people you're not seeing Ben Shaparry.

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Speaker 1: You do see on mainstream media now and again, but

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Speaker 1: they you're generally, I guess, not seeing, and that these

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Speaker 1: are people open to discussing uh their views with with

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Speaker 1: other people on the left on the right. They don't

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Speaker 1: necessarily have anything in common, but they'll these people mentioning

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Speaker 1: the article, they will sit down and have an intellectual

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Speaker 1: debate amongst one another and their their views that contradict

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Speaker 1: the UM the current narrative. It's like there's a narrative

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Speaker 1: that's just feels like it's being shoved down the throats

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Speaker 1: of people who are conservative, but maybe not even conservative,

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Speaker 1: just people who are like not on the far left.

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Speaker 1: You know. Yeah, there's there's a lot of those who, um,

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Speaker 1: I feel like they're being allen alienated because they're you know,

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Speaker 1: moderate Democrats, people like Rick Unger we've had on Brandon's podcast. Um,

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Speaker 1: by the way, I was gonna be speaking of the

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Speaker 1: far left. I was gonna mention this article I commented

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Speaker 1: on Twitter, but did you see this? Uh? And this

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Speaker 1: is from CNN, and it's like, you wonder why CNN

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Speaker 1: just becomes more and more unpopular. So this is by

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Speaker 1: some guy Richard Edmund Vargas. Guns alone don't kill people. Patriarchy.

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Speaker 1: Patriarchy kills people. Um. And the whole article goes into

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Speaker 1: like all these problems of the patriarchy. And this this

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Speaker 1: totally ties into the verse true signaling thing, like it's

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Speaker 1: a man who wrote this article. That stuff is so weird.

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Speaker 1: And they say things, they say, we live in this patriarchy,

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Speaker 1: and like they say a lot of things like I've

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Speaker 1: never experienced in life, but like here it says patriarchy

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Speaker 1: is a social system that defines men as being inherently violent, dominant,

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Speaker 1: and controlling, while rewarding them with power for being that way.

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Speaker 1: It's no secret, especially these days, that we live in

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Speaker 1: a patriarchal, patriarchical society. What are why are we continually

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Speaker 1: surprised when a man takes up arms and commits a

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Speaker 1: mass murder? I mean, I feel like these people live

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Speaker 1: in an alternate reality. And no, you know, I just

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Speaker 1: you don't see these op eds on CNN about psychotropic

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Speaker 1: drugs about I mean, mental health is being discussed, but

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Speaker 1: I think that's a major issue. And then the major

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Speaker 1: issue they of course will not discuss. And I know

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Speaker 1: you talked about Daniel lash saying at the n r

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Speaker 1: A conventions, like they make these mass shooters famous and

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Speaker 1: it gets them ratings. Yeah, they I don't think, CNN,

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Speaker 1: let's talk about that. Um, But that's a complicated issue too.

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Speaker 1: I mean, should the media just not report on mass shootings?

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Speaker 1: I mean I don't believe that. But at the same time,

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Speaker 1: do we need twenty seven coverage of every shooting, you know,

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Speaker 1: like the way we had after say Columbine like that

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Speaker 1: that was just all over the news for but in days.

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Speaker 1: An example I could think of is you remember the

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Speaker 1: Star and I have brother on the cover of Rolling

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Speaker 1: Stone magazine and it was like that Wan is looking

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Speaker 1: at that. That made me angry because I mean it's

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Speaker 1: not necessarily that he was on the cover, but it was, Yeah,

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Speaker 1: they were trying to turn him into like a rock star. Yeah,

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Speaker 1: it was just totally provocative. Um, they just did that

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Speaker 1: to piss people off and get some attention, I think, Um,

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Speaker 1: and it worked. But yeah, that's why I mean I

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Speaker 1: tell all of my friends, like, if you ever get

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Speaker 1: a call from the Rolling Stone, hang up the phone.

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Speaker 1: I've gotten calls from them and emails. I made the

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Speaker 1: mistake of talking to one Rolling Stone journalist, uh, you know,

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Speaker 1: earlier on in my my journalistic career, and I never

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Speaker 1: talked to them again. I know another guy, I don't

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Speaker 1: know if he still works there or not, but he

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Speaker 1: wanted to talk to me about an article actually about

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Speaker 1: Wayne Simmons, and I refused. I was like, I'm not

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Speaker 1: gonna because he was working at Rolling Stone. I was like, look,

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Speaker 1: it's nothing personal, but I don't trust your editors. I

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Speaker 1: don't trust that outlet. I think they have serious ethical issues.

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Speaker 1: And you know, if you decide to go and work

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Speaker 1: for another magazine or another newspaper or something, we can talk.

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Speaker 1: That's fine. But I'm not going to have anything to

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Speaker 1: do with Rolling Stone. And I would advise other people

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Speaker 1: not to I'd tell them the same thing. Yeah, it's understandable,

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Speaker 1: especially after that article and it did because and other stuff.

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Speaker 1: I mean remember the uh that was like one of

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Speaker 1: those campus gang rape stories. Yeah, I think so, and

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Speaker 1: it turned out it wasn't true. Well, yeah, there's been

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Speaker 1: so much to that I may have mentioned on the

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Speaker 1: podcast before, but I went to like middle school and

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Speaker 1: part of high school with one of the Duke Lacrosse

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Speaker 1: kids who was accused of being a rapist. And turns out,

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Speaker 1: if you watch that thirty for thirty on it, he

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Speaker 1: wasn't even there when it went down. A lot of

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Speaker 1: those guys were it. I write my book about the

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Speaker 1: and I don't have any like firsthand knowledge about this

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Speaker 1: at all, um, except that I was there when this

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Speaker 1: whole Fiesco is happening. Was the mattress girl at Columbia,

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Speaker 1: And I was there actually the first day when she

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Speaker 1: got out of the van logan the mattress with her,

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Speaker 1: and she carried the mattress that supposedly she was raped

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Speaker 1: on um around campus as a piece of performance art

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Speaker 1: and was giving course credit for that. So I walk

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Speaker 1: up to school the first day of the semester and

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Speaker 1: there she is getting out of the van, and the

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Speaker 1: paparazzi was just all around her, taking pictures and flashes everywhere.

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Speaker 1: And I didn't even know what this was about at

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Speaker 1: the time. I was like, what in the world, like

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Speaker 1: another day in New York City, you know? Um? And

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Speaker 1: she claimed that she had been raped on campus by

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Speaker 1: another student, a student from Germany, and he got raped

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Speaker 1: over the coals, and I mean it looks like he

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Speaker 1: just did not do it, like and the whole the

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Speaker 1: whole case fell apart and everything. Um, so he's probably

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Speaker 1: an innocent victim and all of that. Holy sh it. So,

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Speaker 1: for the first time on soft Rep Radio, John Robbed

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Speaker 1: former Air Force were special operations pilot and military analyst.

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Speaker 1: Uh now really most known as an author and entrepreneurs

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Speaker 1: pen several books, but right now is doing the Global

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Speaker 1: Guerrillas Report, and we're excited to have you on. I mean,

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Speaker 1: there's a lot to talk about, and you have just

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Speaker 1: such an interesting background. I came upon your work when

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Speaker 1: I was in the military, um, and I was reading

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Speaker 1: your Global Guerilla's blog. This was like right smack in

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Speaker 1: the dab of the insurgency in Iraq, and I just

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Speaker 1: found that you were, you know, light years ahead of

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Speaker 1: where everyone else was as far as understanding what was

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Speaker 1: going on over there. Um. And actually I saw you

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Speaker 1: speak at Austin p University in Clarksville laws in fifth Group.

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Speaker 1: I saw on your website or something like that you

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Speaker 1: announced it and I went over there and saw you

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Speaker 1: speak very interesting stuff. UM, I felt like there were

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Speaker 1: more people in d O D S who should probably

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Speaker 1: be listening to you. Well. Cool, That's how I came

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Speaker 1: across your work, And UM, I hope other people go

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Speaker 1: and check out your Global Guerillas website, which is really interesting.

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Speaker 1: And I guess I was wondering if we could start

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Speaker 1: off talking a little bit about kind of where we've

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Speaker 1: come since that time frame, Like say, you know, when

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Speaker 1: you started writing the website about the evolution of insurgencies

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Speaker 1: and unconventional warfare. I guess you could say, um to

425
00:22:16,640 --> 00:22:22,880
Speaker 1: today and where we're at now in Okay. Um, Well,

426
00:22:22,880 --> 00:22:25,320
Speaker 1: I started writing this site back in two thousand four,

427
00:22:26,320 --> 00:22:28,560
Speaker 1: and I did it because, UM, you know, what I

428
00:22:28,600 --> 00:22:30,879
Speaker 1: was seeing, you know, coming out of the d D

429
00:22:31,160 --> 00:22:35,040
Speaker 1: and and being reported in the press wasn't um making

430
00:22:35,080 --> 00:22:39,480
Speaker 1: sense to me, you know, particularly in light of my background.

431
00:22:39,520 --> 00:22:44,600
Speaker 1: And I also for the last for the years in

432
00:22:44,680 --> 00:22:47,160
Speaker 1: the run up to two thousand four, UM, I had

433
00:22:47,200 --> 00:22:52,080
Speaker 1: been in software companies that I had been immersed in

434
00:22:52,119 --> 00:22:53,560
Speaker 1: the Internet. I was one of the you know, the

435
00:22:53,600 --> 00:22:56,760
Speaker 1: early probably the first you know, full time Internet analysts

436
00:22:56,960 --> 00:23:01,680
Speaker 1: back and you know, it's a lot of things going

437
00:23:01,720 --> 00:23:04,760
Speaker 1: on in the Internet that had applicability to what I

438
00:23:04,800 --> 00:23:07,480
Speaker 1: was seeing in interac you know that you know, kind

439
00:23:07,480 --> 00:23:10,719
Speaker 1: of connected the dots or made more sense to me. UM.

440
00:23:11,880 --> 00:23:13,720
Speaker 1: And one of the things I pulled out was this

441
00:23:13,800 --> 00:23:20,000
Speaker 1: idea of open source insurgency. UH, this idea that you're

442
00:23:20,080 --> 00:23:24,840
Speaker 1: not going to see these big ideological insurgencies anymore, UH,

443
00:23:25,359 --> 00:23:30,240
Speaker 1: their communism or UM sort of like Palestinian nationalism back

444
00:23:30,280 --> 00:23:35,280
Speaker 1: in the seventies, right with these you know, very hierarchical structures,

445
00:23:35,440 --> 00:23:39,439
Speaker 1: you know, and you know, with these different committees that

446
00:23:39,520 --> 00:23:43,280
Speaker 1: are mirror images of the nation state. UM. You have

447
00:23:43,320 --> 00:23:46,920
Speaker 1: the propaganda element, and you have the you know, supply

448
00:23:48,400 --> 00:23:53,400
Speaker 1: uh bureau in the insurgency and and this new type

449
00:23:53,400 --> 00:23:56,840
Speaker 1: of insurgency work like open source software UM with some

450
00:23:56,920 --> 00:23:59,800
Speaker 1: modifications UM. And I had to figure those out as

451
00:24:00,080 --> 00:24:02,320
Speaker 1: was going along, and I started writing in real time

452
00:24:03,040 --> 00:24:05,240
Speaker 1: the Global Grillas plug and I was getting good feedback

453
00:24:05,600 --> 00:24:08,399
Speaker 1: as I was going UM. And I wanted to make

454
00:24:08,400 --> 00:24:10,240
Speaker 1: sure also that you know, when I was writing the theory,

455
00:24:10,320 --> 00:24:14,000
Speaker 1: that I tied it to actual events, because there's nothing

456
00:24:14,040 --> 00:24:18,720
Speaker 1: worse than really getting into theory crafting UM and you know,

457
00:24:18,760 --> 00:24:21,119
Speaker 1: going way out on a limb or going you know,

458
00:24:21,160 --> 00:24:24,600
Speaker 1: way out into space and having this beautiful theory that's elegant,

459
00:24:24,600 --> 00:24:28,960
Speaker 1: that you know, doesn't explain anything, is not predictive UM.

460
00:24:29,000 --> 00:24:34,040
Speaker 1: And that what I found it in kind of modeling

461
00:24:34,080 --> 00:24:38,320
Speaker 1: the insurgency is this idea that there's lots of small groups,

462
00:24:38,760 --> 00:24:41,720
Speaker 1: UM that could work together to take on a much

463
00:24:41,800 --> 00:24:45,119
Speaker 1: larger foe. You know, sixties seventy different groups in Iraq,

464
00:24:45,240 --> 00:24:48,520
Speaker 1: you know, all with their different motivations for fighting UM,

465
00:24:49,400 --> 00:24:54,160
Speaker 1: you know, coming together to you know, share resources, share knowledge,

466
00:24:54,400 --> 00:25:02,440
Speaker 1: sometimes indirectly, sometimes directly UM, and UH putting together an

467
00:25:02,440 --> 00:25:07,200
Speaker 1: ansurgency they can actually you know, do amazingly well UM

468
00:25:07,240 --> 00:25:11,399
Speaker 1: and be you know, amazingly innovative. I don't know what

469
00:25:11,480 --> 00:25:13,880
Speaker 1: your thoughts are, but I feel like we've seen almost

470
00:25:13,960 --> 00:25:18,080
Speaker 1: the culmination of this theory in Syria. UM. And you know,

471
00:25:18,119 --> 00:25:19,879
Speaker 1: the New York Times and others have come out with

472
00:25:20,000 --> 00:25:23,480
Speaker 1: articles recently talking about how like Ice has had this

473
00:25:23,640 --> 00:25:27,840
Speaker 1: um fairly well administrated state. UM. But the way I

474
00:25:27,960 --> 00:25:32,080
Speaker 1: perceived things is that it looked like there were many

475
00:25:32,119 --> 00:25:35,120
Speaker 1: different groups on the ground and they were coming together

476
00:25:35,160 --> 00:25:38,879
Speaker 1: in a very ad hoc manner UM from battle to battle,

477
00:25:39,440 --> 00:25:41,560
Speaker 1: almost like this very kind of like lase a fair

478
00:25:41,760 --> 00:25:44,400
Speaker 1: type of capitalism. If I were to draw some sort

479
00:25:44,440 --> 00:25:47,040
Speaker 1: of parallel um that they're just kind of be thrown

480
00:25:47,040 --> 00:25:50,000
Speaker 1: together for one battle and then the alliance would completely

481
00:25:50,000 --> 00:25:52,320
Speaker 1: shift in a different group of people coming together for

482
00:25:52,359 --> 00:25:56,159
Speaker 1: the next battle. What do you make of of the

483
00:25:56,440 --> 00:26:00,679
Speaker 1: how that insurgency kind of jumped from Iraq Syria in

484
00:26:00,720 --> 00:26:03,840
Speaker 1: some ways and how it evolved. Well, you know, many

485
00:26:03,840 --> 00:26:07,000
Speaker 1: of the same lessons that we're learned by the Iraqi

486
00:26:07,000 --> 00:26:14,000
Speaker 1: insurgency insurgents were ported to the Syrian insurgency and you

487
00:26:14,080 --> 00:26:18,040
Speaker 1: know things like you know, I describe it as stigma gy.

488
00:26:18,119 --> 00:26:22,600
Speaker 1: It's this, it's the kind of communication that ants have, uh,

489
00:26:22,720 --> 00:26:25,639
Speaker 1: you know, ants don't you know, talk to each other directly.

490
00:26:25,680 --> 00:26:28,280
Speaker 1: What they do is they leave a chemical trail to

491
00:26:28,920 --> 00:26:32,199
Speaker 1: a piece of food, and each ant that you know,

492
00:26:32,240 --> 00:26:34,960
Speaker 1: travels at trail. Then it is successful in finding the food.

493
00:26:35,119 --> 00:26:39,000
Speaker 1: You know, it reinforces the trail um and that that

494
00:26:39,119 --> 00:26:43,359
Speaker 1: kind of decentralized information sharing, you know, allows them to

495
00:26:43,400 --> 00:26:46,119
Speaker 1: do you know, act as an act as a group.

496
00:26:46,119 --> 00:26:48,840
Speaker 1: And in the case of an insurgency, if you haven't

497
00:26:50,640 --> 00:26:54,280
Speaker 1: some level of success in conducting attack and it's covered

498
00:26:54,320 --> 00:26:59,360
Speaker 1: by the press or it's picked up as a success

499
00:26:59,359 --> 00:27:02,719
Speaker 1: and it's described. Uh what other groups do is they

500
00:27:02,720 --> 00:27:04,840
Speaker 1: just copy it, just like an open source software. As

501
00:27:04,880 --> 00:27:07,720
Speaker 1: you copy it and then you you apply it. What

502
00:27:07,840 --> 00:27:12,119
Speaker 1: was interesting also about the Assyrian in certaincies that uh,

503
00:27:12,280 --> 00:27:16,840
Speaker 1: you know isis was able to go online and create

504
00:27:16,880 --> 00:27:20,719
Speaker 1: kind of a decentralized version of it online to do

505
00:27:20,800 --> 00:27:22,600
Speaker 1: the kind of recruiting that it that it was able

506
00:27:22,640 --> 00:27:26,639
Speaker 1: to pull off. I mean that was a you know,

507
00:27:26,760 --> 00:27:31,200
Speaker 1: pretty major innovation. I mean it was able to pull

508
00:27:31,200 --> 00:27:34,920
Speaker 1: in about thirty people and also franchising itself out or

509
00:27:34,960 --> 00:27:40,359
Speaker 1: attempting to in Libya, Somalia. I think there were attempts Nigeria,

510
00:27:40,480 --> 00:27:44,480
Speaker 1: I believe in the Philippines absolutely they tried to um

511
00:27:44,640 --> 00:27:48,719
Speaker 1: actor or you saw local groups trying to aspire and

512
00:27:48,760 --> 00:27:51,560
Speaker 1: call themselves. Isis like that sort of plug and play

513
00:27:52,080 --> 00:27:57,920
Speaker 1: ideology or insurgency. Yeah, and it it was pretty effective.

514
00:27:58,359 --> 00:28:01,800
Speaker 1: They were able to play the whole caliphate angle um

515
00:28:02,080 --> 00:28:07,240
Speaker 1: and this idea of fealty which is kind of a

516
00:28:07,400 --> 00:28:10,360
Speaker 1: it's a it's a very medieval concept is different than loyalty,

517
00:28:10,840 --> 00:28:15,440
Speaker 1: you know, I fealty is um well, it's as you also,

518
00:28:15,560 --> 00:28:21,600
Speaker 1: you know, you pledge to uphold your liege lords um

519
00:28:21,920 --> 00:28:25,240
Speaker 1: goals and everything that you do, and you're given incredible

520
00:28:25,280 --> 00:28:28,159
Speaker 1: amounts of leeway and independence in doing that. And you

521
00:28:28,280 --> 00:28:34,719
Speaker 1: just you're you've pledged yourself to your liege and uh,

522
00:28:36,600 --> 00:28:38,720
Speaker 1: it's a you know, a very decentralized kind of thing.

523
00:28:38,760 --> 00:28:42,240
Speaker 1: It's not it's not a you know, in feudal in

524
00:28:42,280 --> 00:28:46,120
Speaker 1: fuel societies. There wasn't like that kind of direct command

525
00:28:46,120 --> 00:28:49,000
Speaker 1: and control of you know, of a bureaucracy or or

526
00:28:49,040 --> 00:28:54,800
Speaker 1: our hierarchy. Each each of the lords were operating independently,

527
00:28:54,840 --> 00:28:59,600
Speaker 1: but they operated in their leege lord's interest fealty is it.

528
00:29:01,320 --> 00:29:03,239
Speaker 1: I was just gonna say they had to operate like

529
00:29:03,240 --> 00:29:07,400
Speaker 1: that because they didn't have the telecommunications infrastructure and um

530
00:29:07,440 --> 00:29:10,360
Speaker 1: and I imagine you know you could probably comment on

531
00:29:10,440 --> 00:29:14,800
Speaker 1: the agrarian practices as well as playing into it. Yeah.

532
00:29:14,920 --> 00:29:17,400
Speaker 1: I mean, but they parted a version of that to

533
00:29:17,640 --> 00:29:20,640
Speaker 1: the online world, and they were able to you know,

534
00:29:20,680 --> 00:29:23,760
Speaker 1: incentivize some people to you know, take up arms and

535
00:29:24,080 --> 00:29:29,360
Speaker 1: conduct relatively um, disconnected attacks. I mean, they didn't go

536
00:29:29,400 --> 00:29:31,960
Speaker 1: through the standard planning process and kind of hand holding

537
00:29:31,960 --> 00:29:36,080
Speaker 1: and support that you typically see with terrorist organizations. Um,

538
00:29:36,120 --> 00:29:41,840
Speaker 1: they in order to pledge their fealty. They were obligated

539
00:29:41,880 --> 00:29:44,080
Speaker 1: to do all the planning on their own and then

540
00:29:44,120 --> 00:29:46,880
Speaker 1: conducted the attack, And the attack itself was actually the pledge.

541
00:29:47,840 --> 00:29:51,360
Speaker 1: And you saw that in numerous instances, um, in recent

542
00:29:51,400 --> 00:29:55,800
Speaker 1: attacks in Europe and even in the US. In the press,

543
00:29:55,840 --> 00:29:59,280
Speaker 1: they often say that, you know, isis is barbaric and

544
00:29:59,360 --> 00:30:02,280
Speaker 1: primitive in medieval and I suppose they really are all

545
00:30:02,280 --> 00:30:04,680
Speaker 1: of those things. But what do you make of the

546
00:30:04,760 --> 00:30:09,400
Speaker 1: appeal to a group like that in twenty fifteen, sixteen,

547
00:30:09,440 --> 00:30:13,640
Speaker 1: seventeen eighteen. Why why does such a primitive barbaric group

548
00:30:14,280 --> 00:30:18,120
Speaker 1: have an enduring appeal to people around the world. And

549
00:30:18,160 --> 00:30:20,160
Speaker 1: I mean it's not the majority of people, of course,

550
00:30:20,200 --> 00:30:22,840
Speaker 1: but a significant minority of people are still drawn to

551
00:30:22,920 --> 00:30:27,000
Speaker 1: that kind of thing. Oh wow, they're well, they're you know,

552
00:30:27,040 --> 00:30:29,840
Speaker 1: approximate factors, you know, having to do with you know,

553
00:30:30,640 --> 00:30:33,720
Speaker 1: bad local economies and lack of opportunity. Um, if you

554
00:30:33,720 --> 00:30:37,360
Speaker 1: don't have a job, you can't get married kind of thing. Um.

555
00:30:37,400 --> 00:30:41,560
Speaker 1: But there's also this kind of sense that you know, globalization,

556
00:30:42,400 --> 00:30:46,320
Speaker 1: uh makes everything relative. And we're seeing this in the

557
00:30:46,360 --> 00:30:49,000
Speaker 1: States too. Is that you know, once you become you know,

558
00:30:49,680 --> 00:30:52,840
Speaker 1: you lower the barriers to everything. Everything is as good

559
00:30:52,840 --> 00:30:58,040
Speaker 1: as the stuff you have cultural uh countries, you know,

560
00:30:59,120 --> 00:31:02,320
Speaker 1: you can't hold up one over the other. UM. And

561
00:31:02,360 --> 00:31:05,360
Speaker 1: that it creates a huge vacuum, kind of a big

562
00:31:05,400 --> 00:31:09,240
Speaker 1: loss in people. Yeah, people don't know what to fill

563
00:31:09,320 --> 00:31:12,160
Speaker 1: that with. Yeah, they just they don't you know, they

564
00:31:12,160 --> 00:31:14,760
Speaker 1: don't have this kind of group that they belong to.

565
00:31:15,760 --> 00:31:20,640
Speaker 1: This kind of in tribalism, it's kind of called fictive kinship,

566
00:31:21,120 --> 00:31:24,040
Speaker 1: this idea that you have this kind of cohesive narrative

567
00:31:24,600 --> 00:31:26,760
Speaker 1: that unites you and you have you know, traditions and

568
00:31:26,760 --> 00:31:30,760
Speaker 1: other things that make you part of a group, and

569
00:31:30,880 --> 00:31:32,680
Speaker 1: that the other people that are part of that group

570
00:31:32,800 --> 00:31:37,760
Speaker 1: is our people that you give some level of loyalty

571
00:31:37,800 --> 00:31:42,760
Speaker 1: to and you protect and they protect you. UM. In

572
00:31:42,800 --> 00:31:45,560
Speaker 1: a globalized world that doesn't exist. It's like this global

573
00:31:45,600 --> 00:31:48,000
Speaker 1: commercial culture is just it is devoid of that that

574
00:31:48,160 --> 00:31:50,840
Speaker 1: and that belonging was. You know, you've got that spashion

575
00:31:50,920 --> 00:31:56,080
Speaker 1: younger approaches that it's it's almost hardwired into our into

576
00:31:56,080 --> 00:31:58,560
Speaker 1: our beings. We're always you know, searching for that kind

577
00:31:58,600 --> 00:32:03,240
Speaker 1: of belonging. UM. So what happens is is it you

578
00:32:03,280 --> 00:32:06,560
Speaker 1: know when nationalism, you know you've heard of the post

579
00:32:06,600 --> 00:32:12,440
Speaker 1: Westphalian stuff out of out of Martin van Kraveldt. I mean,

580
00:32:12,560 --> 00:32:14,320
Speaker 1: I think a lot of people have talked about it,

581
00:32:14,440 --> 00:32:18,000
Speaker 1: even you know, some more notable people Henry Kissinger and such.

582
00:32:18,000 --> 00:32:21,320
Speaker 1: If we're moving into uh, some system like that. I

583
00:32:21,360 --> 00:32:24,280
Speaker 1: know you've commented on the perhaps moving into like a

584
00:32:24,320 --> 00:32:27,320
Speaker 1: post state society. Well, it's the decline of the state

585
00:32:27,400 --> 00:32:28,960
Speaker 1: or it's like kind of a hollowing out of the

586
00:32:29,000 --> 00:32:34,120
Speaker 1: state as as as we globalize, and you know, that

587
00:32:34,160 --> 00:32:37,880
Speaker 1: creates these this kind of this vacuum, and people are

588
00:32:37,960 --> 00:32:41,920
Speaker 1: filling it with all sorts of direct gag get their

589
00:32:41,920 --> 00:32:44,880
Speaker 1: hands on and if they're not in some cases, you know,

590
00:32:44,920 --> 00:32:49,040
Speaker 1: I kind of connect the you know, the high rates

591
00:32:49,080 --> 00:32:53,440
Speaker 1: of alcoholism and the declining uh longevity of Russians after

592
00:32:53,520 --> 00:32:56,480
Speaker 1: the fall of the Soviet Union. You know, they're drinking.

593
00:32:56,760 --> 00:32:58,720
Speaker 1: You know, the guys in the primary life are drinking

594
00:32:58,720 --> 00:33:01,880
Speaker 1: themselves to death. And we're seeing this today to a

595
00:33:01,960 --> 00:33:04,640
Speaker 1: certain extent in the US with the opioid crisis. Is people,

596
00:33:04,920 --> 00:33:07,240
Speaker 1: it's not the young people are the old people who

597
00:33:07,280 --> 00:33:11,360
Speaker 1: you normally expect, you know, expect to have problems with addiction.

598
00:33:12,320 --> 00:33:14,800
Speaker 1: Almost all the deaths are occurring between the thirty five

599
00:33:14,840 --> 00:33:19,280
Speaker 1: and fifty four range. People have lost their personal narrative correct. Yeah,

600
00:33:19,320 --> 00:33:21,480
Speaker 1: they've lost that kind of stuff that connects them. And

601
00:33:21,800 --> 00:33:24,240
Speaker 1: it sounds when you talk about this, it reminds me.

602
00:33:24,320 --> 00:33:28,640
Speaker 1: Have you seen the Robert Curtis documentary Hypernormalization? Yeah? I

603
00:33:28,640 --> 00:33:31,040
Speaker 1: thought that was quite good. Yeah, it sounds exactly what

604
00:33:31,080 --> 00:33:34,520
Speaker 1: you're talking about. That like, we don't have a social,

605
00:33:34,680 --> 00:33:38,960
Speaker 1: societal scale narrative. Everyone knows it doesn't work, that that

606
00:33:39,040 --> 00:33:42,040
Speaker 1: these stories were told by our leaders don't function, they

607
00:33:42,080 --> 00:33:44,400
Speaker 1: don't mean anything anymore. But we have nothing to replace

608
00:33:44,440 --> 00:33:47,200
Speaker 1: it with. Correct and that's a big problem. That's what

609
00:33:47,240 --> 00:33:49,240
Speaker 1: I'm trying to do with the reports as I'm working

610
00:33:49,240 --> 00:33:53,800
Speaker 1: through these, you know different things. You know what you know,

611
00:33:53,880 --> 00:33:57,000
Speaker 1: the open source element has done to our politics as

612
00:33:57,000 --> 00:33:59,280
Speaker 1: we kind of move towards an open source kind of

613
00:33:59,320 --> 00:34:02,680
Speaker 1: non linear politics, UM, and then UM trying to figure

614
00:34:02,680 --> 00:34:05,480
Speaker 1: out you know how AI. You know this basically the

615
00:34:05,480 --> 00:34:09,120
Speaker 1: big social AI s H. I mean we've seen at

616
00:34:09,160 --> 00:34:11,560
Speaker 1: least with Facebook and YouTube and others. I mean, the

617
00:34:11,600 --> 00:34:16,320
Speaker 1: biggest real world, real time application of artificial intelligence is

618
00:34:16,320 --> 00:34:19,359
Speaker 1: is being done in these big social networks and they're

619
00:34:19,360 --> 00:34:22,120
Speaker 1: touching AIS are touching two and a half billion people

620
00:34:22,719 --> 00:34:25,680
Speaker 1: right now and influencing them and managing them. I was

621
00:34:25,960 --> 00:34:28,200
Speaker 1: grappling with that for a bit, and what China is

622
00:34:28,239 --> 00:34:34,200
Speaker 1: doing with that, and and this idea of this declining tribalism.

623
00:34:34,280 --> 00:34:36,600
Speaker 1: This is this, you know, we don't have this fictive

624
00:34:36,640 --> 00:34:39,680
Speaker 1: kinship that connects us as Americans anymore or less. So

625
00:34:40,280 --> 00:34:41,920
Speaker 1: and what we're seeing is a rise of kind of

626
00:34:41,920 --> 00:34:46,680
Speaker 1: an identity politics. We're seeing uh, you know, existential crisis

627
00:34:46,719 --> 00:34:49,480
Speaker 1: with people just basically killing themselves. And for the first

628
00:34:49,520 --> 00:34:53,560
Speaker 1: time and in modern history, the u S life expectancy

629
00:34:53,600 --> 00:34:55,040
Speaker 1: for the second year in a row has gone down,

630
00:34:56,160 --> 00:35:00,160
Speaker 1: and in a modern country, it's gone down. I saw you.

631
00:35:00,800 --> 00:35:02,879
Speaker 1: I was looking over you know, your website a little

632
00:35:02,880 --> 00:35:04,439
Speaker 1: bit before we got started. In one of the things

633
00:35:04,440 --> 00:35:07,200
Speaker 1: that's stuck out to me, you said, we are in uh,

634
00:35:07,320 --> 00:35:10,719
Speaker 1: we're in the middle of uncharted non linear territory when

635
00:35:10,760 --> 00:35:14,560
Speaker 1: it comes to politics. And I think you touched upon that,

636
00:35:14,600 --> 00:35:16,680
Speaker 1: but could you expand a little bit on what you

637
00:35:16,719 --> 00:35:18,600
Speaker 1: mean and that we're kind of like going out into

638
00:35:18,600 --> 00:35:20,560
Speaker 1: the deep end of the pool without really knowing where

639
00:35:20,600 --> 00:35:25,319
Speaker 1: the bottom is. Yeah, it's um. The problem was is

640
00:35:25,360 --> 00:35:28,440
Speaker 1: that our political parties and this left right kind of

641
00:35:28,440 --> 00:35:33,080
Speaker 1: spectrum um started falling apart, you know, around the round

642
00:35:33,080 --> 00:35:37,719
Speaker 1: the turn of the century, and we didn't really have

643
00:35:37,760 --> 00:35:40,839
Speaker 1: anything to replace it. And then we saw the kind

644
00:35:40,880 --> 00:35:43,920
Speaker 1: of the elites making bad decision after bad decision you

645
00:35:43,960 --> 00:35:48,640
Speaker 1: know happens in invade Iraq. Yeah, excuse me, our our

646
00:35:48,719 --> 00:35:54,200
Speaker 1: experts making bad decisions. Yeah, yeah, and you know eleven

647
00:35:54,200 --> 00:35:57,080
Speaker 1: happens and we had invade Iraq, which doesn't make any sense.

648
00:35:57,120 --> 00:35:59,680
Speaker 1: We're trying to connect it or that the you know

649
00:36:00,120 --> 00:36:03,200
Speaker 1: that we allow the whole banking and derivatives saying to

650
00:36:03,760 --> 00:36:07,680
Speaker 1: get totally out of hand and let people take amazing

651
00:36:07,719 --> 00:36:10,720
Speaker 1: bet you know, large bets, and then the financial crisis

652
00:36:10,800 --> 00:36:12,440
Speaker 1: and then they don't have to pay any price for

653
00:36:12,480 --> 00:36:17,160
Speaker 1: doing that. We make them whole um and that we pay,

654
00:36:17,520 --> 00:36:20,279
Speaker 1: and we've socialized the cost of that, you know. And

655
00:36:21,280 --> 00:36:24,480
Speaker 1: we saw after that that that particularly the financial crisis,

656
00:36:24,520 --> 00:36:27,279
Speaker 1: arise of lots of populist movements have been calling them,

657
00:36:27,280 --> 00:36:35,719
Speaker 1: but basically there groups of individuals, each with their own motivation,

658
00:36:35,840 --> 00:36:37,880
Speaker 1: coming together and kind of open source networks that kind

659
00:36:37,920 --> 00:36:40,759
Speaker 1: of express their disgust with how things are being run.

660
00:36:41,880 --> 00:36:45,120
Speaker 1: Occupy movement, Yeah, we saw the occupy movement, we saw

661
00:36:45,160 --> 00:36:47,640
Speaker 1: the Tea Party movement, and then most recently, we saw

662
00:36:47,640 --> 00:36:50,279
Speaker 1: a kind of you know, an insurgency very similar to

663
00:36:50,320 --> 00:36:53,160
Speaker 1: the kind of insurgency I was describing, interact with the

664
00:36:53,160 --> 00:36:55,960
Speaker 1: open source insurgency or the kind of open source protests

665
00:36:56,040 --> 00:37:01,120
Speaker 1: that made it possible to topple Tunisia and pop Tople Egypt.

666
00:37:01,440 --> 00:37:05,399
Speaker 1: And then we saw a flare up in Syria. Um,

667
00:37:05,440 --> 00:37:11,560
Speaker 1: we saw an open source election campaign that propelled Trump,

668
00:37:12,000 --> 00:37:15,319
Speaker 1: and Trump was like this wrecking ball that was sent

669
00:37:15,400 --> 00:37:20,520
Speaker 1: to Washington to actually just expressed displeasure. And then no

670
00:37:20,520 --> 00:37:23,200
Speaker 1: matter what he did, you know, all these people with

671
00:37:23,239 --> 00:37:27,000
Speaker 1: all their different motivations kind of you know, said we're

672
00:37:27,040 --> 00:37:28,719
Speaker 1: here for one reason is just to get him to

673
00:37:28,760 --> 00:37:32,240
Speaker 1: Washington to cost trouble. Right. It's like, it's interesting because

674
00:37:32,239 --> 00:37:35,400
Speaker 1: there are people primarily on the right, but they're expressing

675
00:37:35,400 --> 00:37:40,080
Speaker 1: this very Leninist attitude of like smash the state. Yeah exactly,

676
00:37:40,120 --> 00:37:44,360
Speaker 1: and it basically that insertaincy has overrun the Republican Party.

677
00:37:44,360 --> 00:37:46,920
Speaker 1: It's gone. A lot of that was was Steve Bennon.

678
00:37:47,080 --> 00:37:49,719
Speaker 1: You know, that was like he said, he's a Leninist

679
00:37:50,239 --> 00:37:52,560
Speaker 1: and he was a big believer, but he was influenced

680
00:37:52,560 --> 00:37:55,480
Speaker 1: by that book. Um, do you know what it is? John,

681
00:37:56,080 --> 00:37:57,839
Speaker 1: There was a book that was a huge influence to him.

682
00:37:57,920 --> 00:38:00,000
Speaker 1: Was called like every I don't know if it's every

683
00:38:00,080 --> 00:38:01,719
Speaker 1: hundred Years or something like that, but he was a

684
00:38:01,760 --> 00:38:04,880
Speaker 1: believer that, like a certain amount of time, that the

685
00:38:05,040 --> 00:38:07,759
Speaker 1: entire political system would basically turn on its head and

686
00:38:07,800 --> 00:38:10,359
Speaker 1: you have to collapse the whole system and start new.

687
00:38:10,440 --> 00:38:12,480
Speaker 1: And that was kind of what he wanted to do

688
00:38:12,520 --> 00:38:15,600
Speaker 1: with Trump. Yeah, it was. It was a cycle series

689
00:38:15,640 --> 00:38:18,720
Speaker 1: of Yeah, I'm not a big fan of the cycle serie.

690
00:38:18,920 --> 00:38:20,799
Speaker 1: I mean, you know, you can always look at those

691
00:38:21,320 --> 00:38:26,400
Speaker 1: hun cycles years cycles. But I like that because I

692
00:38:26,440 --> 00:38:29,839
Speaker 1: looked at it's called the Fourth Turning. What psychic track

693
00:38:29,880 --> 00:38:34,160
Speaker 1: tell us about America's next rendezvous with destiny? He apparently,

694
00:38:34,200 --> 00:38:36,560
Speaker 1: I'm looking at an article from Business Insider. Was obsessed

695
00:38:36,560 --> 00:38:40,800
Speaker 1: with this book and I've heard that before. Yeah, he

696
00:38:40,800 --> 00:38:46,200
Speaker 1: he liked that a lot. Um. He definitely had a

697
00:38:46,239 --> 00:38:48,520
Speaker 1: good nose for what was going on in the insurgency.

698
00:38:48,680 --> 00:38:52,040
Speaker 1: He saw the surgency rising in any any fed it. Um.

699
00:38:52,560 --> 00:38:56,440
Speaker 1: You saw the economic discontent, you saw the uh sense

700
00:38:56,480 --> 00:39:00,800
Speaker 1: of betrayal that was driving a lot of this Um

701
00:39:00,840 --> 00:39:03,759
Speaker 1: you know, it's there's just lots of lots of things

702
00:39:03,840 --> 00:39:08,040
Speaker 1: that were yeah, kind of pushed on people very very quickly.

703
00:39:08,080 --> 00:39:11,320
Speaker 1: I mean little things like it's like a Chinese trade

704
00:39:11,400 --> 00:39:14,120
Speaker 1: or trade with China. You know, in the nineties, we

705
00:39:14,160 --> 00:39:16,879
Speaker 1: had the similar problem with Japan and when it hit

706
00:39:16,880 --> 00:39:20,680
Speaker 1: about sixty billion dollars in in a trade deficit and

707
00:39:20,680 --> 00:39:24,120
Speaker 1: it was smashing in the US auto industry. You know, Baker,

708
00:39:24,160 --> 00:39:26,120
Speaker 1: who was a Secretary of State at the time, basically

709
00:39:26,280 --> 00:39:30,479
Speaker 1: told Japan knock it off, keep it at sixty until

710
00:39:30,520 --> 00:39:33,640
Speaker 1: you figure out how to either import more or or

711
00:39:33,680 --> 00:39:36,920
Speaker 1: freeze it where it is, and allowed the Detroit to

712
00:39:36,960 --> 00:39:39,840
Speaker 1: recover and create a you know, a viable car industry

713
00:39:39,840 --> 00:39:44,120
Speaker 1: that we see you today. Um, the problem was is

714
00:39:44,160 --> 00:39:46,719
Speaker 1: like in two thousand two or so, you know, Chinese,

715
00:39:47,000 --> 00:39:51,160
Speaker 1: the Chinese trade deficit was hitting about at billion, and

716
00:39:51,200 --> 00:39:53,480
Speaker 1: then we were focused on our you know nine eleven

717
00:39:53,520 --> 00:39:57,000
Speaker 1: Iraq in Afghanistan, and we didn't do anything about it,

718
00:39:57,080 --> 00:40:01,200
Speaker 1: but just it swept across the the whole country. And

719
00:40:01,239 --> 00:40:05,560
Speaker 1: then by the late late odds you had stories of

720
00:40:05,800 --> 00:40:09,280
Speaker 1: Chinese companies just buying out all of the machine tools

721
00:40:09,280 --> 00:40:11,759
Speaker 1: out of out of factories across the United States. I

722
00:40:11,760 --> 00:40:13,520
Speaker 1: mean it's very similar tout of the way the Russians

723
00:40:13,520 --> 00:40:16,759
Speaker 1: were depopulating Germany after World War Two. It's just it

724
00:40:16,840 --> 00:40:20,440
Speaker 1: was just devastating and the trade came on so quickly

725
00:40:22,000 --> 00:40:24,680
Speaker 1: and it wasn't managed. It wasn't you know, that rate

726
00:40:24,719 --> 00:40:27,920
Speaker 1: of onset you know, swamped us. And you could actually

727
00:40:27,920 --> 00:40:30,520
Speaker 1: see a lot of connection between the areas the counties

728
00:40:30,520 --> 00:40:34,360
Speaker 1: that were impacted heavily by Chinese trade and there you know,

729
00:40:34,440 --> 00:40:38,960
Speaker 1: vote for Trump. Uh. I mean, I'm interested in your

730
00:40:38,960 --> 00:40:41,839
Speaker 1: thoughts on China because I mean we've talked about that

731
00:40:42,160 --> 00:40:44,640
Speaker 1: quite a bit on here in the past, and you

732
00:40:44,680 --> 00:40:47,640
Speaker 1: know some of my feelings that China is you know,

733
00:40:47,920 --> 00:40:50,680
Speaker 1: like a freight train trying to support the United States

734
00:40:50,800 --> 00:40:54,440
Speaker 1: as you know, a global superpower, global hedgemon, or however

735
00:40:54,480 --> 00:40:58,759
Speaker 1: you prefer to think about it. Yeah, well, there's a

736
00:40:58,760 --> 00:41:02,200
Speaker 1: couple of things. Is that Out and Road initiative, right,

737
00:41:02,320 --> 00:41:07,680
Speaker 1: and and basically trying to set up a global transportation

738
00:41:09,640 --> 00:41:12,600
Speaker 1: you know, infrastructure that they own, you know, they own

739
00:41:12,640 --> 00:41:17,480
Speaker 1: the debt on they manage, they provide security for um.

740
00:41:17,600 --> 00:41:20,920
Speaker 1: And that means that you know, if you're a US company,

741
00:41:21,160 --> 00:41:23,080
Speaker 1: you know, trying to trade in Africa, or you're trying

742
00:41:23,120 --> 00:41:26,040
Speaker 1: to trade in Asia and you're trying to ship goods

743
00:41:26,120 --> 00:41:30,239
Speaker 1: or get goods ship to you. What you're gonna run

744
00:41:30,239 --> 00:41:32,960
Speaker 1: into is that your stuff takes to three weeks longer

745
00:41:33,800 --> 00:41:35,880
Speaker 1: to arrive, or ahead gets hit with an extra tariff,

746
00:41:36,320 --> 00:41:38,839
Speaker 1: or it disappears, you know, it doesn't get the kind

747
00:41:38,840 --> 00:41:42,279
Speaker 1: of protection the Chinese goods get. It's the end of

748
00:41:42,360 --> 00:41:46,359
Speaker 1: the end of um what's the term innocent passage? Right, Yeah,

749
00:41:46,400 --> 00:41:50,920
Speaker 1: it's a it's it's a very ambitious and very expensive endeavor.

750
00:41:50,960 --> 00:41:55,560
Speaker 1: And given that we're in no condition to kind of

751
00:41:57,880 --> 00:42:00,520
Speaker 1: fight it or or counter it or anything. You know,

752
00:42:00,640 --> 00:42:02,719
Speaker 1: usually what would happen is that you try to fight

753
00:42:02,719 --> 00:42:04,839
Speaker 1: a kind of rearguard action and kind of just break

754
00:42:04,840 --> 00:42:06,719
Speaker 1: it a little bit, slow it down, and make it

755
00:42:06,719 --> 00:42:09,359
Speaker 1: more expensive. Right. Well, and during the Cold War, there's

756
00:42:09,400 --> 00:42:12,600
Speaker 1: a so called War for the Third World where there's

757
00:42:12,640 --> 00:42:15,080
Speaker 1: the theory that the Soviets were going to you know,

758
00:42:15,160 --> 00:42:17,840
Speaker 1: have many revolutions and all these Third World countries and

759
00:42:17,960 --> 00:42:20,920
Speaker 1: essentially box in the United States by limiting our freedom

760
00:42:20,920 --> 00:42:23,440
Speaker 1: of movement around the world. And at the time, we

761
00:42:23,480 --> 00:42:28,080
Speaker 1: had a national agenda or identity, you know, a national

762
00:42:28,200 --> 00:42:32,160
Speaker 1: narrative the way you had talked about today, where are

763
00:42:32,200 --> 00:42:35,000
Speaker 1: we encountering China and we don't have any of that?

764
00:42:35,280 --> 00:42:39,319
Speaker 1: And the thing that the thing that we have on

765
00:42:39,360 --> 00:42:42,200
Speaker 1: our side, I guess, is that the kind of instability,

766
00:42:42,440 --> 00:42:45,279
Speaker 1: the kind of nonlinearity that's hitting us because of globalization

767
00:42:46,640 --> 00:42:50,200
Speaker 1: is just about to hit China too. Well do you think? Uh?

768
00:42:50,760 --> 00:42:53,720
Speaker 1: I'm really interested to hear you expand on that, because

769
00:42:54,040 --> 00:42:57,400
Speaker 1: you know, with the Chinese control measures and social credit

770
00:42:57,480 --> 00:43:01,359
Speaker 1: schemes that we've talked about, Um, what what's how? How

771
00:43:01,440 --> 00:43:06,000
Speaker 1: is it? How is that nonlinear aspects going to hit China? Yeah?

772
00:43:06,000 --> 00:43:10,640
Speaker 1: That's that's the trying to you know, I've framed it

773
00:43:10,719 --> 00:43:15,360
Speaker 1: as trying to maintain coherence. You know, socio political coherence. Uh.

774
00:43:15,640 --> 00:43:17,600
Speaker 1: Coherence is a really cool word. It's like this idea

775
00:43:17,640 --> 00:43:24,680
Speaker 1: that you can think logically and clearly, you can you know,

776
00:43:24,719 --> 00:43:28,640
Speaker 1: connect this the facts UM in a way that makes sense.

777
00:43:29,480 --> 00:43:32,920
Speaker 1: It's you know, kind of uh logically connected and and

778
00:43:33,040 --> 00:43:36,959
Speaker 1: aligned UM in a global as environment that's tough because

779
00:43:37,000 --> 00:43:40,120
Speaker 1: of all the interconnectivity and complexity UM causing effect kind

780
00:43:40,120 --> 00:43:43,560
Speaker 1: of breakdown in an extremely complex system. It's been impacting

781
00:43:43,640 --> 00:43:45,520
Speaker 1: us and we have yet to figure out a solution

782
00:43:45,560 --> 00:43:48,160
Speaker 1: for that, yet we'll probably come up with a messy

783
00:43:48,160 --> 00:43:52,680
Speaker 1: one that given our given our past, China did exactly opposite.

784
00:43:53,840 --> 00:43:56,200
Speaker 1: They're understanding that, they now understand that they have this

785
00:43:56,320 --> 00:44:00,480
Speaker 1: like incredibly complex system internally as well as that externally,

786
00:44:00,480 --> 00:44:03,000
Speaker 1: and they're gonna have to deal with this. And what

787
00:44:03,040 --> 00:44:05,360
Speaker 1: they decided to do is build a social credit system.

788
00:44:05,360 --> 00:44:08,040
Speaker 1: And um, they're doing it in part by you know,

789
00:44:08,080 --> 00:44:12,600
Speaker 1: outsourcing uh part of it to the big social networks, yeah,

790
00:44:13,239 --> 00:44:18,080
Speaker 1: you know we chat and Ali baba. And they're also

791
00:44:18,840 --> 00:44:22,759
Speaker 1: doing it in part through each of the each of

792
00:44:22,760 --> 00:44:26,440
Speaker 1: the big cities. I mean, they are are implementing versions

793
00:44:26,440 --> 00:44:29,960
Speaker 1: of it. And what that's trying to do is gamify

794
00:44:30,000 --> 00:44:33,279
Speaker 1: this whole idea of you know, what's right and what's

795
00:44:33,320 --> 00:44:36,560
Speaker 1: wrong in society, that that if if you do things

796
00:44:36,600 --> 00:44:42,200
Speaker 1: that are loyal and in the public morality, you get points,

797
00:44:42,840 --> 00:44:46,600
Speaker 1: and if you do things that are they deem immoral

798
00:44:46,800 --> 00:44:49,600
Speaker 1: or unethical, or or if you criticize the state, or

799
00:44:49,600 --> 00:44:54,800
Speaker 1: if you uh say nasty stuff online, you'll lose points

800
00:44:54,840 --> 00:44:58,200
Speaker 1: and those points. The way they designed the system is

801
00:44:58,239 --> 00:45:00,680
Speaker 1: that if you have a lot of you high high

802
00:45:00,680 --> 00:45:04,839
Speaker 1: social credit score, you can get all sorts of great

803
00:45:04,920 --> 00:45:06,880
Speaker 1: benefits you can give, you know, the shang and visa,

804
00:45:07,400 --> 00:45:10,320
Speaker 1: you know, go visit all the different European countries. You

805
00:45:10,360 --> 00:45:15,200
Speaker 1: can uh, you know, get access to loans and and

806
00:45:15,200 --> 00:45:18,440
Speaker 1: and different opportunities you wouldn't be able to get access

807
00:45:18,480 --> 00:45:23,719
Speaker 1: to otherwise. But if you get a low score, what

808
00:45:23,800 --> 00:45:28,560
Speaker 1: happens is that your low score can prevent you from

809
00:45:28,600 --> 00:45:31,400
Speaker 1: getting loans, and can prevent you from running, uh, you know,

810
00:45:31,440 --> 00:45:36,160
Speaker 1: getting buying property. It can prevent you from traveling on

811
00:45:36,280 --> 00:45:41,080
Speaker 1: trains and airplanes. Um. If it gets to the point

812
00:45:41,120 --> 00:45:45,600
Speaker 1: where you're blacklisted, you even get a different dial tone

813
00:45:45,640 --> 00:45:47,919
Speaker 1: in certain parts of China that when people call you,

814
00:45:48,080 --> 00:45:51,160
Speaker 1: it makes a funny sound that identifies you as one

815
00:45:51,160 --> 00:45:54,719
Speaker 1: of the people in the blacklist. But yeah, that the

816
00:45:54,800 --> 00:45:57,400
Speaker 1: architect of it is the way it works as a

817
00:45:57,440 --> 00:46:01,880
Speaker 1: network is really the killer here is your score impacts

818
00:46:01,880 --> 00:46:05,520
Speaker 1: your family's score. Your score impacts your coworkers and your

819
00:46:05,560 --> 00:46:09,720
Speaker 1: friends online. So if you drag them down, pure pressure

820
00:46:09,800 --> 00:46:12,719
Speaker 1: kicks in correct and it's is connected and it's going

821
00:46:13,640 --> 00:46:15,920
Speaker 1: and it has like a Confucian kind of you know,

822
00:46:16,040 --> 00:46:20,600
Speaker 1: han morality built baked into it to provide kind of

823
00:46:20,640 --> 00:46:26,399
Speaker 1: social cohesion Um, it's a it's a it's a kind

824
00:46:26,400 --> 00:46:31,120
Speaker 1: of system that's so locked down though that it um

825
00:46:31,280 --> 00:46:34,680
Speaker 1: has a potential of of really killing off any kind

826
00:46:34,719 --> 00:46:39,040
Speaker 1: of innovation, anything anyone stepping outside a line. Yeah. Absolutely,

827
00:46:39,360 --> 00:46:42,320
Speaker 1: I mean I think the Chinese Communist government has already

828
00:46:43,040 --> 00:46:45,800
Speaker 1: done a pretty good job at that, hence the corporate

829
00:46:45,920 --> 00:46:50,239
Speaker 1: espionage and technology transfers and everything else that have gone

830
00:46:50,280 --> 00:46:53,680
Speaker 1: over you know, the last couple of decades. But uh,

831
00:46:53,719 --> 00:46:56,759
Speaker 1: I mean, human beings don't really like being put in boxes,

832
00:46:56,880 --> 00:46:59,440
Speaker 1: as history shows us. Where do you see this all

833
00:46:59,480 --> 00:47:03,080
Speaker 1: going in the future for China, especially when you factor

834
00:47:03,200 --> 00:47:07,240
Speaker 1: in some of the other chaotic aspects of the uncertainties

835
00:47:07,320 --> 00:47:09,040
Speaker 1: that exist in the modern world that are going to

836
00:47:09,160 --> 00:47:15,040
Speaker 1: impact China as well well. Um, The thing is, I

837
00:47:15,080 --> 00:47:18,560
Speaker 1: think the system actually could be pretty effective in terms

838
00:47:18,600 --> 00:47:21,640
Speaker 1: of providing them stability in the short term, you know,

839
00:47:21,640 --> 00:47:23,960
Speaker 1: because it's supposed to be done by it's going to

840
00:47:24,040 --> 00:47:26,759
Speaker 1: combine that government information and private information in a way

841
00:47:26,760 --> 00:47:29,400
Speaker 1: that we haven't seen. Even you're purchasing habits and they

842
00:47:29,400 --> 00:47:32,480
Speaker 1: don't have a retail infrastructure like we do in China.

843
00:47:32,600 --> 00:47:34,600
Speaker 1: Everything is mostly done online where you get it delivered,

844
00:47:35,200 --> 00:47:37,600
Speaker 1: you know, all of your purchasing is being factored into

845
00:47:37,600 --> 00:47:41,200
Speaker 1: this thing. And this peer pressure in you know, in

846
00:47:41,239 --> 00:47:44,239
Speaker 1: a society that that is used to peer pressure or

847
00:47:44,280 --> 00:47:48,040
Speaker 1: accepts it. UH, could provide them a lot of sensibility.

848
00:47:48,040 --> 00:47:49,800
Speaker 1: But over the long term, I think they're going to

849
00:47:49,880 --> 00:47:53,880
Speaker 1: run into the same problem that you know, communism ran into. UM,

850
00:47:54,000 --> 00:47:57,920
Speaker 1: is that you know, by leaving out the market element

851
00:47:58,040 --> 00:48:01,880
Speaker 1: in that old system market decision making, UH, and sticking

852
00:48:01,880 --> 00:48:05,360
Speaker 1: only with the bureaucratic decision making model. UH, they weren't

853
00:48:05,360 --> 00:48:07,759
Speaker 1: able to innovate and come up with stuff like computers

854
00:48:08,880 --> 00:48:10,680
Speaker 1: and you know, at least the kind of computers that

855
00:48:10,840 --> 00:48:13,279
Speaker 1: you know, and the kind of innovations that allowed us

856
00:48:13,320 --> 00:48:15,920
Speaker 1: to kind of spread way ahead and create a you know,

857
00:48:15,960 --> 00:48:22,120
Speaker 1: a very complex, widely complex economy by by the mid eighties. UM,

858
00:48:22,160 --> 00:48:28,040
Speaker 1: that's probably going to be their problem too. But UM,

859
00:48:28,080 --> 00:48:32,960
Speaker 1: you know, if they can stay stable while we fall apart, right,

860
00:48:33,640 --> 00:48:38,279
Speaker 1: then maybe it's a price that's worth paying. I mean,

861
00:48:38,440 --> 00:48:40,160
Speaker 1: do you do you see that happening here in the

862
00:48:40,200 --> 00:48:42,920
Speaker 1: United States. I mean we've talked about you know, you

863
00:48:42,920 --> 00:48:45,759
Speaker 1: you had just mentioned earlier about how these these so

864
00:48:45,880 --> 00:48:51,040
Speaker 1: called insurgencies political insurgencies, UM, ideas about smashing the state,

865
00:48:51,160 --> 00:48:54,840
Speaker 1: not having a political or social identity. Where is it

866
00:48:54,880 --> 00:48:57,520
Speaker 1: going to go in the in the United States? How's

867
00:48:57,560 --> 00:49:01,080
Speaker 1: that going to happen? Yeah, that's a that's an open question.

868
00:49:01,080 --> 00:49:03,120
Speaker 1: I was kind of debating whether or not to kind

869
00:49:03,160 --> 00:49:06,279
Speaker 1: of do a report on or you know reports. What

870
00:49:06,360 --> 00:49:09,880
Speaker 1: they do is they they're so ruthlessly logical. For me,

871
00:49:10,000 --> 00:49:12,520
Speaker 1: is I walk through the argument and it kind of

872
00:49:12,560 --> 00:49:14,960
Speaker 1: teaches me as I go through. I learned as I'm writing,

873
00:49:15,760 --> 00:49:18,120
Speaker 1: because I do write this. I have this very structured

874
00:49:18,160 --> 00:49:20,560
Speaker 1: style with a paragraph bullet bulletla. It's he really easy

875
00:49:20,560 --> 00:49:23,239
Speaker 1: to read. But the logic is like inexhorable as it

876
00:49:23,280 --> 00:49:25,840
Speaker 1: goes through. Whether I was going to write a report

877
00:49:25,880 --> 00:49:32,320
Speaker 1: on potential for civil conflict in states and there's there's

878
00:49:32,400 --> 00:49:36,200
Speaker 1: a rising potential in terms of all of these different

879
00:49:36,280 --> 00:49:39,640
Speaker 1: centers are gravity that have kind of erupted um and

880
00:49:39,719 --> 00:49:43,200
Speaker 1: that a lot of the older structures are starting to

881
00:49:43,400 --> 00:49:48,960
Speaker 1: be de legitimized. I mean, institutional de legitimization is rampant.

882
00:49:49,040 --> 00:49:52,440
Speaker 1: Now you look at everybody, I mean every single institution

883
00:49:52,440 --> 00:49:56,000
Speaker 1: in the United States, even the U S. Militaries in decline,

884
00:49:56,080 --> 00:49:58,560
Speaker 1: everything from the Department of Justice to the Boy scouts,

885
00:49:58,600 --> 00:50:01,000
Speaker 1: it seems. Oh yeah, and every time we try to

886
00:50:01,080 --> 00:50:06,320
Speaker 1: fix a crisis in particular, we we end up destroying

887
00:50:06,320 --> 00:50:11,480
Speaker 1: an institution. So right now we're destroying FBI. It's credibility.

888
00:50:11,520 --> 00:50:17,720
Speaker 1: It's just getting shot to hell um and that can't

889
00:50:17,760 --> 00:50:21,759
Speaker 1: be good. You know. It's the distrust is growing and

890
00:50:21,840 --> 00:50:26,040
Speaker 1: that there's increasing amount of this is this is kind

891
00:50:26,040 --> 00:50:29,799
Speaker 1: of interesting to me? Is this similarity to our Civil war?

892
00:50:30,239 --> 00:50:34,879
Speaker 1: Is that you'll see you know, jurisdictions disregarding laws, yes,

893
00:50:35,160 --> 00:50:40,680
Speaker 1: and that you know they won't comply, and uh, they'll

894
00:50:40,719 --> 00:50:44,560
Speaker 1: start passing laws that are uh that do funkies. Things

895
00:50:44,600 --> 00:50:50,279
Speaker 1: like Connecticut just yesterday passed all hill that said that

896
00:50:50,360 --> 00:50:53,480
Speaker 1: they give all their electoral votes to the majority winner

897
00:50:53,640 --> 00:50:58,080
Speaker 1: in the popular vote nationally. So say they voted, Uh yeah,

898
00:50:58,280 --> 00:51:01,279
Speaker 1: I can understand that's legal, though, is it? Yeah? I

899
00:51:01,320 --> 00:51:04,960
Speaker 1: guess I guess it is, really yeah, And so everybody votes,

900
00:51:05,320 --> 00:51:08,759
Speaker 1: saying in Connecticut and say all the votes go to

901
00:51:08,840 --> 00:51:11,640
Speaker 1: a Republican candidate, which is not likely for Connecticut, but

902
00:51:11,760 --> 00:51:14,200
Speaker 1: say it did. And then they say the national vote

903
00:51:14,960 --> 00:51:18,400
Speaker 1: right now, you know, the popular vote goes democratic. They

904
00:51:18,440 --> 00:51:21,239
Speaker 1: would switch that whole state and give it to the

905
00:51:21,280 --> 00:51:26,520
Speaker 1: Democratic like a form of like anarcho uh what in

906
00:51:26,560 --> 00:51:31,640
Speaker 1: anarcho capitalism or something like yeah, what we want? Yeah,

907
00:51:31,680 --> 00:51:34,240
Speaker 1: not only are they the kind of negating the votes

908
00:51:34,239 --> 00:51:37,920
Speaker 1: of their citizens, it's it's um. It's a thing that

909
00:51:38,040 --> 00:51:44,040
Speaker 1: makes a connection between that negates the the election tooral process.

910
00:51:44,800 --> 00:51:46,560
Speaker 1: You know. It's like it's what I call it is

911
00:51:46,600 --> 00:51:49,279
Speaker 1: it's like a financial derivative. It makes a connection that

912
00:51:49,320 --> 00:51:53,160
Speaker 1: goes around the market right when you when you build

913
00:51:53,160 --> 00:51:55,239
Speaker 1: a financial I was in financial drivers for a bit

914
00:51:55,320 --> 00:51:57,800
Speaker 1: for back in the nineties, and a lot of the

915
00:51:57,840 --> 00:52:01,000
Speaker 1: stuff was just trying to make connections, um, non market

916
00:52:01,040 --> 00:52:05,239
Speaker 1: connections that connected you know, different indicries in ways that

917
00:52:05,280 --> 00:52:08,719
Speaker 1: allowed you to bet or reduce risk um. And all

918
00:52:08,719 --> 00:52:10,799
Speaker 1: these connections, because they didn't go through the clearing house

919
00:52:10,840 --> 00:52:14,239
Speaker 1: of the election or in this case election, in that

920
00:52:14,280 --> 00:52:16,200
Speaker 1: case it would be the clearing house of the market,

921
00:52:17,239 --> 00:52:21,120
Speaker 1: created all sorts of instabilities. When things went bad, these

922
00:52:21,120 --> 00:52:24,000
Speaker 1: things started moving and things, you know, companies started going bankrupt,

923
00:52:24,080 --> 00:52:27,040
Speaker 1: and that risk got spread globally and it didn't go

924
00:52:27,080 --> 00:52:29,719
Speaker 1: through the markets. It went on this parallel network of

925
00:52:29,800 --> 00:52:33,680
Speaker 1: this parallel spider web of of derivatives. The same thing.

926
00:52:33,800 --> 00:52:36,400
Speaker 1: If you could see this happening in politics. Is is

927
00:52:36,440 --> 00:52:42,160
Speaker 1: all these different connections are being made a weird kind

928
00:52:42,160 --> 00:52:45,200
Speaker 1: of political derivatives, like we saw in Connecticut or or

929
00:52:45,239 --> 00:52:53,600
Speaker 1: California complying with immigration law. Is that you end up

930
00:52:53,600 --> 00:53:00,120
Speaker 1: with these pockets of instability and you know, drives to

931
00:53:00,200 --> 00:53:02,440
Speaker 1: kind of say, Okay, we're not going to listen to

932
00:53:02,440 --> 00:53:06,920
Speaker 1: anything you say. Or the converse is that they you know,

933
00:53:07,320 --> 00:53:09,880
Speaker 1: the state tries to enforce the laws in a heavy

934
00:53:09,920 --> 00:53:13,400
Speaker 1: handed way, which causes the reaction that the boast. By

935
00:53:13,400 --> 00:53:15,360
Speaker 1: the way, I just pulled up the article about this

936
00:53:15,440 --> 00:53:17,919
Speaker 1: since you know we were talking about it. The one

937
00:53:18,040 --> 00:53:21,000
Speaker 1: catch here is that this will not kick in, and

938
00:53:21,040 --> 00:53:24,280
Speaker 1: I'm talking about Connecticut unless it's backed by enough states

939
00:53:24,400 --> 00:53:27,920
Speaker 1: and other voting areas to claim a majority Electoral College votes.

940
00:53:28,640 --> 00:53:31,319
Speaker 1: So it says, in addition to Connecticut, the other jurisdictions

941
00:53:31,320 --> 00:53:35,600
Speaker 1: in the Pactrick California, Hawaii, Illinois, Maryland, Massachusetts, New Jersey,

942
00:53:35,640 --> 00:53:39,359
Speaker 1: New York, Rhode Island, Vermont, Washington stayed along with d C. So,

943
00:53:39,880 --> 00:53:42,640
Speaker 1: but I highly doubt it's gonna pass in all those areas.

944
00:53:42,640 --> 00:53:45,400
Speaker 1: So I'm guessing what that means is unless it passes

945
00:53:45,440 --> 00:53:49,040
Speaker 1: in quite a bit of the map. This probably won't

946
00:53:49,480 --> 00:53:53,680
Speaker 1: actually happen, Yeah, potentially. I mean it's just the it's

947
00:53:53,680 --> 00:53:56,200
Speaker 1: just the effort. Yeah, it's it's a lot of people

948
00:53:56,239 --> 00:54:00,160
Speaker 1: who are guests. I feel disenfranchised by the electoral college system.

949
00:54:00,200 --> 00:54:02,799
Speaker 1: And I mean it's a weird thing because this is

950
00:54:02,840 --> 00:54:05,000
Speaker 1: not the first time that the person who won the

951
00:54:05,040 --> 00:54:08,640
Speaker 1: popular vote didn't win the electoral vote. But I think

952
00:54:08,680 --> 00:54:12,480
Speaker 1: it's almost like this uh attitude in the country of

953
00:54:12,560 --> 00:54:14,759
Speaker 1: like that Trump somehow like cheated his way to win

954
00:54:14,800 --> 00:54:17,680
Speaker 1: the presidency and it's like he won fair and square

955
00:54:17,800 --> 00:54:21,319
Speaker 1: on the rules that we have. Yeah, it's um, it's

956
00:54:21,360 --> 00:54:23,960
Speaker 1: a funny situation. I mean, the electoral college was set

957
00:54:24,000 --> 00:54:26,360
Speaker 1: up so you wouldn't have regional candidates right right to

958
00:54:26,400 --> 00:54:30,040
Speaker 1: protect the farmers and people. It kind of spread the

959
00:54:30,280 --> 00:54:33,120
Speaker 1: kind of make sure that you have candidates that at

960
00:54:33,200 --> 00:54:36,200
Speaker 1: least semi middle of the road. You couldn't have a

961
00:54:36,239 --> 00:54:38,920
Speaker 1: candidate as well in one region, and because you know

962
00:54:39,000 --> 00:54:42,680
Speaker 1: that candidate gets the vote in that region, you know,

963
00:54:42,840 --> 00:54:47,280
Speaker 1: swamps the system and then that would cause, you know, breakup.

964
00:54:47,560 --> 00:54:49,720
Speaker 1: And in this case, what we're seeing is that the

965
00:54:49,800 --> 00:54:54,880
Speaker 1: extreme popularity um of the Dems in California and the

966
00:54:55,200 --> 00:54:58,680
Speaker 1: you know, the East Coast has created kind of a

967
00:54:58,719 --> 00:55:03,880
Speaker 1: barbell of of votes. UM. You know where you you

968
00:55:04,480 --> 00:55:09,359
Speaker 1: have you know support in California, UM, and you have

969
00:55:09,880 --> 00:55:12,400
Speaker 1: a pretty tight race across most of the rest of

970
00:55:12,400 --> 00:55:14,480
Speaker 1: the country until you get the East Coast and then

971
00:55:14,480 --> 00:55:18,840
Speaker 1: you have you know again that six in Massachusetts and

972
00:55:18,840 --> 00:55:23,600
Speaker 1: New York for the Dems. UM. That's the reason why

973
00:55:23,640 --> 00:55:26,360
Speaker 1: the polls. Incidentally, I think that's the reason why the

974
00:55:26,360 --> 00:55:31,520
Speaker 1: polls were so off going into the last presidential election,

975
00:55:32,040 --> 00:55:35,600
Speaker 1: is that they were looking at the national polls and

976
00:55:35,640 --> 00:55:37,799
Speaker 1: they were seeing a significant lead for Hillary, but they

977
00:55:37,800 --> 00:55:42,239
Speaker 1: didn't account for the regionalization of the regional bias. John,

978
00:55:42,280 --> 00:55:45,000
Speaker 1: were you one of the I would say a few

979
00:55:45,040 --> 00:55:48,680
Speaker 1: people in the media who predicted it Trump victory while

980
00:55:48,719 --> 00:55:50,359
Speaker 1: I said it was too close to call. And then

981
00:55:50,400 --> 00:55:52,920
Speaker 1: that morning when I when I said, man, this is

982
00:55:52,920 --> 00:55:56,120
Speaker 1: not this sounds like a Trump victory, and people are

983
00:55:56,160 --> 00:55:58,080
Speaker 1: like all quiet on the thing. And then as a

984
00:55:58,239 --> 00:56:01,760
Speaker 1: day went on, just you know, you get the feel

985
00:56:01,800 --> 00:56:03,520
Speaker 1: for the thing and it's like, oh boy, this is

986
00:56:03,520 --> 00:56:06,239
Speaker 1: gonna this is going to go in a way that

987
00:56:06,280 --> 00:56:09,520
Speaker 1: people didn't expect. I gotta I was on the I

988
00:56:09,600 --> 00:56:12,879
Speaker 1: was on the you know that Donald on read I've

989
00:56:12,920 --> 00:56:16,719
Speaker 1: seen it. Yes, yeah, it's like thousand people. And it

990
00:56:16,840 --> 00:56:21,680
Speaker 1: was like the big kind of centipede kind of engine

991
00:56:21,719 --> 00:56:25,359
Speaker 1: for supporting the Trump and surgency. And and they had

992
00:56:25,400 --> 00:56:27,759
Speaker 1: interviewed Trump and then they interviewed me the next week,

993
00:56:28,040 --> 00:56:31,600
Speaker 1: and uh, which is kind of cool, I mean, and

994
00:56:31,600 --> 00:56:33,880
Speaker 1: that they were asking and they were actually pretty respectful,

995
00:56:33,880 --> 00:56:37,040
Speaker 1: and then moderators didn't let them savage me even though

996
00:56:37,080 --> 00:56:38,520
Speaker 1: I was I was kind of trying to stay more

997
00:56:38,640 --> 00:56:40,160
Speaker 1: middle of the ground, in the middle of the road,

998
00:56:40,160 --> 00:56:43,400
Speaker 1: because I like, I like the kind of perspective it

999
00:56:43,440 --> 00:56:45,520
Speaker 1: provides me. You know, if you're too much in one

1000
00:56:45,520 --> 00:56:49,319
Speaker 1: camp or another, you can't see what's going on. It

1001
00:56:49,360 --> 00:56:53,200
Speaker 1: tends to blind you a bit. And uh, they were

1002
00:56:53,239 --> 00:56:56,640
Speaker 1: like kind of disheartened and demoralized and that that, you know,

1003
00:56:57,040 --> 00:57:00,840
Speaker 1: the press was to be just savaging Trump and it

1004
00:57:01,000 --> 00:57:03,040
Speaker 1: didn't look like he was gonna make it. And I go,

1005
00:57:03,680 --> 00:57:06,880
Speaker 1: just he's being held up by this insurgency and there

1006
00:57:06,960 --> 00:57:10,319
Speaker 1: a surgency is pushing him forward and and it won't matter,

1007
00:57:10,600 --> 00:57:14,120
Speaker 1: you know what the press says that no matter what

1008
00:57:14,239 --> 00:57:17,280
Speaker 1: you know, it's even if you get that access Hollywood

1009
00:57:17,320 --> 00:57:21,000
Speaker 1: thing Um that would have crushed anyone else, but he

1010
00:57:21,080 --> 00:57:23,800
Speaker 1: was backed by an insurgency. And it wasn't Trump per se.

1011
00:57:24,320 --> 00:57:27,440
Speaker 1: It was the insurgency that said that didn't matter. So

1012
00:57:27,520 --> 00:57:30,800
Speaker 1: all these people you see with an open source insurgency.

1013
00:57:30,920 --> 00:57:33,800
Speaker 1: With open source software, when when I create a piece

1014
00:57:33,800 --> 00:57:39,120
Speaker 1: of open source software, uh, what I do is I

1015
00:57:39,200 --> 00:57:41,960
Speaker 1: demonstrate that it that it works, and that means it's

1016
00:57:42,080 --> 00:57:45,240
Speaker 1: it's plausible, and I also show that has some promise,

1017
00:57:45,720 --> 00:57:48,240
Speaker 1: so it's called a plausible promise. And then other people

1018
00:57:49,080 --> 00:57:50,720
Speaker 1: they look at that piece of software and they go

1019
00:57:51,400 --> 00:57:54,160
Speaker 1: or you know, the some piece of hardware that I built,

1020
00:57:54,200 --> 00:57:56,480
Speaker 1: and they go, wow, that's cool. I can see it

1021
00:57:56,560 --> 00:57:59,280
Speaker 1: doing this and scratching my itch. You know, this thing

1022
00:57:59,320 --> 00:58:02,080
Speaker 1: could do something really cool for me, And they may

1023
00:58:02,120 --> 00:58:06,720
Speaker 1: see it as promising for something entirely different than the

1024
00:58:06,720 --> 00:58:09,640
Speaker 1: person that initially put it up than me Um and that.

1025
00:58:10,680 --> 00:58:13,600
Speaker 1: But it's that you know, simple plausible promise of that

1026
00:58:13,800 --> 00:58:16,680
Speaker 1: software that or that hardware that keep gets all these

1027
00:58:16,680 --> 00:58:19,920
Speaker 1: different people to come together and and work on it

1028
00:58:19,960 --> 00:58:22,000
Speaker 1: and move it forward and push it forward, and then

1029
00:58:22,040 --> 00:58:27,440
Speaker 1: they differentiate it and and later later down the down

1030
00:58:27,520 --> 00:58:30,440
Speaker 1: the development cycle. Same thing with the politics is that

1031
00:58:31,880 --> 00:58:35,520
Speaker 1: if the possible promise was to get Trump into office,

1032
00:58:36,680 --> 00:58:39,360
Speaker 1: you know, so you can be that wrecking ball, and

1033
00:58:39,440 --> 00:58:41,480
Speaker 1: that he proved that he was plausible because he had

1034
00:58:41,480 --> 00:58:46,240
Speaker 1: some early victories unexpected victories or it did surprisingly well

1035
00:58:46,480 --> 00:58:51,240
Speaker 1: in the in some of the early debates. Um, people

1036
00:58:52,560 --> 00:58:55,880
Speaker 1: held that one simple thing, that plausible promise, that one

1037
00:58:56,200 --> 00:58:59,760
Speaker 1: simple goal that united all these different people with all

1038
00:58:59,760 --> 00:59:02,400
Speaker 1: these different motivations, and they were all pushing it forward

1039
00:59:02,600 --> 00:59:05,880
Speaker 1: and something that only online can really do well, um

1040
00:59:06,200 --> 00:59:08,960
Speaker 1: and do what scale. And we saw the development of

1041
00:59:09,000 --> 00:59:12,480
Speaker 1: this first it's kind of online political party on the

1042
00:59:12,600 --> 00:59:17,920
Speaker 1: right anomaly the right, um, and uh, it put Trump

1043
00:59:17,920 --> 00:59:20,200
Speaker 1: in office. What's going on on the left is pretty

1044
00:59:20,200 --> 00:59:23,360
Speaker 1: cool too. It may actually swamp the Democratic Party then

1045
00:59:23,360 --> 00:59:27,040
Speaker 1: this next next presidential go run, Well, what's happening there? Yeah,

1046
00:59:27,040 --> 00:59:30,640
Speaker 1: it's different. It's a different kind of open source incertaency.

1047
00:59:31,040 --> 00:59:36,520
Speaker 1: It's not even it. You know. Whereas on the right

1048
00:59:36,560 --> 00:59:39,200
Speaker 1: side they came together over Trump, on the left they're

1049
00:59:39,200 --> 00:59:43,920
Speaker 1: coming together over these kind of moral propositions and it

1050
00:59:43,920 --> 00:59:47,280
Speaker 1: which is kind of kind of a public morality consensus morality. Uh,

1051
00:59:47,280 --> 00:59:49,920
Speaker 1: you know, there's this me too thing, and there's a

1052
00:59:50,360 --> 00:59:55,400
Speaker 1: there's a this never again thing with a guns um,

1053
00:59:55,440 --> 01:00:00,800
Speaker 1: and that you know, this asymmetry of capacity for violence. UM.

1054
01:00:01,720 --> 01:00:05,640
Speaker 1: And then there's this uh you know, using disparaging words

1055
01:00:05,680 --> 01:00:08,960
Speaker 1: or hate speech online or any in public life or

1056
01:00:09,680 --> 01:00:14,840
Speaker 1: anytime it's recorded. Um. And then you know, there's a

1057
01:00:14,840 --> 01:00:19,040
Speaker 1: little bit of American social credit scoring going on. I believe, Yeah,

1058
01:00:19,160 --> 01:00:22,800
Speaker 1: it's a it's basically a social credit score. UM. It's

1059
01:00:22,840 --> 01:00:26,680
Speaker 1: creating a public morality. It's filling the gap or the

1060
01:00:26,680 --> 01:00:30,480
Speaker 1: the this you know, this vacuum that was created with

1061
01:00:30,520 --> 01:00:32,480
Speaker 1: the decline of the nation state and decline of this

1062
01:00:32,600 --> 01:00:35,400
Speaker 1: kind of fictive kinship that we've had. And they're creating

1063
01:00:35,400 --> 01:00:38,400
Speaker 1: this new morality this in real time. We're seeing it

1064
01:00:38,560 --> 01:00:43,360
Speaker 1: built um. And it's being enforced, and it's being enforced

1065
01:00:43,360 --> 01:00:47,200
Speaker 1: through shame. Man. Is they find an individual that's violated

1066
01:00:47,240 --> 01:00:50,520
Speaker 1: this thing. Um. You see it a lot in the

1067
01:00:50,600 --> 01:00:53,640
Speaker 1: me too, and they you know, pilarium and they destroy

1068
01:00:53,720 --> 01:00:56,240
Speaker 1: their careers and they make it impossible for them to work.

1069
01:00:56,960 --> 01:00:59,400
Speaker 1: It really is strange too, because I feel like, you

1070
01:00:59,440 --> 01:01:01,280
Speaker 1: know too, of the out of those three things, I

1071
01:01:01,320 --> 01:01:04,440
Speaker 1: think the gun laws in America and our free speech

1072
01:01:04,520 --> 01:01:07,480
Speaker 1: laws or what separates us from the culture of Europe,

1073
01:01:07,880 --> 01:01:10,960
Speaker 1: you know where in many places, Yeah, but I mean,

1074
01:01:11,000 --> 01:01:13,760
Speaker 1: for example, in in many parts of Europe, if you

1075
01:01:13,760 --> 01:01:16,760
Speaker 1: write a book denying that the Holocaust happens, you will

1076
01:01:16,800 --> 01:01:19,439
Speaker 1: be put in jail or defaming the royal family. Yeah,

1077
01:01:19,480 --> 01:01:22,160
Speaker 1: and these are things that they consider hate speech. And

1078
01:01:22,240 --> 01:01:25,600
Speaker 1: in America we really don't have anything called hate speech.

1079
01:01:25,640 --> 01:01:28,680
Speaker 1: It's it's not a clearer line being drawn. Oh yeah,

1080
01:01:28,800 --> 01:01:32,080
Speaker 1: that's it's it's really wild to see these things develop.

1081
01:01:32,480 --> 01:01:35,240
Speaker 1: It it's you know, how do you develop a morality

1082
01:01:35,280 --> 01:01:40,560
Speaker 1: when um your multicultural? Truly multiculture? I mean what what

1083
01:01:40,640 --> 01:01:47,400
Speaker 1: morality crosses lines? I mean, so everybody you know what ethics? What? Uh?

1084
01:01:48,560 --> 01:01:53,520
Speaker 1: What do you what regulates or limits public behavior? Well,

1085
01:01:53,640 --> 01:01:55,760
Speaker 1: when you when you don't have you know, a single

1086
01:01:55,760 --> 01:01:59,480
Speaker 1: culture or a single thing that connects you otherwise and

1087
01:01:59,760 --> 01:02:02,680
Speaker 1: this kind of consensus morality, it's kind of a tough

1088
01:02:02,720 --> 01:02:05,240
Speaker 1: concept to get your head around to see it being

1089
01:02:05,240 --> 01:02:09,680
Speaker 1: done online, but it's being um, it's being built online,

1090
01:02:09,760 --> 01:02:14,280
Speaker 1: and it's being enforced online, and and the enforcement action

1091
01:02:14,320 --> 01:02:17,640
Speaker 1: through shaming is pretty could be pretty brutal. Some of

1092
01:02:17,640 --> 01:02:20,680
Speaker 1: these guys that they get their hands on, it's just

1093
01:02:21,480 --> 01:02:25,320
Speaker 1: they're done. I mean they're not working anymore. And it

1094
01:02:26,120 --> 01:02:28,640
Speaker 1: there was a interesting thing and I put it into

1095
01:02:28,680 --> 01:02:30,360
Speaker 1: I put a little brief together and I put it

1096
01:02:30,400 --> 01:02:35,640
Speaker 1: into a uh the report stream. Um. It was about

1097
01:02:35,680 --> 01:02:39,920
Speaker 1: this what they call the Shitty Men and Media List. Yeah,

1098
01:02:40,000 --> 01:02:41,720
Speaker 1: it was the thing that came out like in December,

1099
01:02:42,240 --> 01:02:45,600
Speaker 1: and there was this, uh, a young woman who was

1100
01:02:45,640 --> 01:02:49,360
Speaker 1: working in media, and she thought, you know what, there's

1101
01:02:49,400 --> 01:02:53,200
Speaker 1: this kind of uh rumor mill or this kind of

1102
01:02:53,200 --> 01:02:56,360
Speaker 1: back room warnings that women give to each other about

1103
01:02:56,760 --> 01:03:01,080
Speaker 1: certain guys, and so what if I take I make

1104
01:03:01,160 --> 01:03:03,640
Speaker 1: this kind of shaming process in this back room information

1105
01:03:03,800 --> 01:03:07,360
Speaker 1: more tangible and they can be shared. And so what

1106
01:03:07,400 --> 01:03:10,040
Speaker 1: you just did is create a spreadsheet she called the

1107
01:03:10,040 --> 01:03:12,360
Speaker 1: Shitty Men and Media List that listed, you know, all

1108
01:03:12,400 --> 01:03:15,880
Speaker 1: these different guys who were known for getting drunk and

1109
01:03:16,160 --> 01:03:19,400
Speaker 1: being assholes or or as little as uh, having you know,

1110
01:03:19,480 --> 01:03:23,880
Speaker 1: creepy lunch meetings, all right, and she put it had

1111
01:03:23,920 --> 01:03:28,600
Speaker 1: about dozen people in that this spreadsheet, and she floated

1112
01:03:28,600 --> 01:03:33,920
Speaker 1: it among different writers and media people. Um, and it

1113
01:03:33,960 --> 01:03:36,880
Speaker 1: took off. I mean within twenty four hours was up

1114
01:03:36,920 --> 01:03:39,440
Speaker 1: to seventy people. I mean there were thousands of people

1115
01:03:39,560 --> 01:03:43,240
Speaker 1: investing time, hours and hours and hours building this list out.

1116
01:03:43,560 --> 01:03:46,000
Speaker 1: I mean, if you're like I've been in software a

1117
01:03:46,000 --> 01:03:48,920
Speaker 1: long time and if you float a prototype piece of

1118
01:03:48,960 --> 01:03:53,520
Speaker 1: software that gets you know, serious people investing incredible amounts

1119
01:03:53,560 --> 01:03:57,480
Speaker 1: of time and effort into building out Uh. And it

1120
01:03:57,520 --> 01:03:59,400
Speaker 1: has been you know, you can just see the ramp

1121
01:03:59,400 --> 01:04:02,040
Speaker 1: and you can fee this thing. Just zoom. Man, you've

1122
01:04:02,040 --> 01:04:04,280
Speaker 1: got something on your hands. You've got something that's explosive.

1123
01:04:04,960 --> 01:04:08,360
Speaker 1: And it got up to you know, seventies two people

1124
01:04:08,560 --> 01:04:13,160
Speaker 1: and um, she pulled it because it was starting to

1125
01:04:13,200 --> 01:04:14,960
Speaker 1: get to the you know, people who wanted to report

1126
01:04:15,000 --> 01:04:19,439
Speaker 1: on it to the press, um and to shut it down,

1127
01:04:19,560 --> 01:04:22,000
Speaker 1: and you know, people were discussing it and you know,

1128
01:04:22,280 --> 01:04:24,480
Speaker 1: very mad at it. I included some examples I was

1129
01:04:24,520 --> 01:04:27,520
Speaker 1: able to pull off. But it's the kind of thing

1130
01:04:27,560 --> 01:04:29,560
Speaker 1: that if you take it to the next level, you

1131
01:04:29,640 --> 01:04:31,600
Speaker 1: put it into a black chain, for instance, where it's

1132
01:04:32,480 --> 01:04:36,600
Speaker 1: you can't be raised, and do you have like you

1133
01:04:36,640 --> 01:04:38,600
Speaker 1: can even bring it up to another level where you

1134
01:04:38,640 --> 01:04:42,200
Speaker 1: can you know, attach names and addresses. Even facial recognition

1135
01:04:42,240 --> 01:04:45,360
Speaker 1: is now really really easy. Um. But the picture of

1136
01:04:45,360 --> 01:04:47,480
Speaker 1: the person in and it just runs through generic facial

1137
01:04:47,480 --> 01:04:49,840
Speaker 1: recognition and says, okay, this is a person off the

1138
01:04:49,920 --> 01:04:52,960
Speaker 1: shitty men I media list or shitty men list. I

1139
01:04:52,960 --> 01:04:55,600
Speaker 1: mean there are some people who haven't coming. I mean,

1140
01:04:55,640 --> 01:04:59,200
Speaker 1: our our Attorney general here in New York City probably

1141
01:04:59,480 --> 01:05:01,720
Speaker 1: uh yeah, got what he had come in to him.

1142
01:05:01,760 --> 01:05:03,640
Speaker 1: But I mean, doesn't this sound like some sort of

1143
01:05:03,680 --> 01:05:06,880
Speaker 1: neo McCarthy is um at a certain point, Yeah, it

1144
01:05:06,960 --> 01:05:10,000
Speaker 1: just say it's just the same thing though the same

1145
01:05:10,680 --> 01:05:14,400
Speaker 1: the same problem with the social credit system in China.

1146
01:05:14,680 --> 01:05:16,360
Speaker 1: It can grow in away. I mean in China, if

1147
01:05:16,400 --> 01:05:21,440
Speaker 1: you have a problem with your score, um, there's no

1148
01:05:21,800 --> 01:05:24,840
Speaker 1: legal redress because it's not done in the courts. It's

1149
01:05:24,840 --> 01:05:29,480
Speaker 1: done all through a voluntary basis. That's what the government says, um.

1150
01:05:29,640 --> 01:05:33,400
Speaker 1: And there's you know, no way of actually forcing them

1151
01:05:33,440 --> 01:05:37,320
Speaker 1: to revise your score or uh doing anything about it.

1152
01:05:37,480 --> 01:05:39,840
Speaker 1: The same could happen here, and it could get to

1153
01:05:39,840 --> 01:05:42,240
Speaker 1: the point where it's just like, you know, it's either

1154
01:05:42,280 --> 01:05:46,480
Speaker 1: an untrue allegation or you know somebody who's you know,

1155
01:05:46,840 --> 01:05:54,120
Speaker 1: being accused of something very very minor um definitely disputable

1156
01:05:54,160 --> 01:05:57,440
Speaker 1: that ends up getting getting hammered, not getting a job,

1157
01:05:57,600 --> 01:06:03,680
Speaker 1: not getting opper tunities, having problems in social life everything.

1158
01:06:03,760 --> 01:06:06,400
Speaker 1: It's just you could apply the same thing to any

1159
01:06:06,440 --> 01:06:09,320
Speaker 1: of the other morality things. If you said anything, uh,

1160
01:06:09,480 --> 01:06:12,720
Speaker 1: you said any kind of you know, racial slur, you

1161
01:06:12,760 --> 01:06:16,040
Speaker 1: said anything that you know, people could call, you know,

1162
01:06:17,080 --> 01:06:21,080
Speaker 1: sexist or whatever that could be captured off your Twitter

1163
01:06:21,160 --> 01:06:23,960
Speaker 1: or if you're captured off a video phone and that

1164
01:06:23,960 --> 01:06:26,800
Speaker 1: would be used as evidence that would then be put

1165
01:06:26,840 --> 01:06:29,800
Speaker 1: into a list like this. I mean, not many Americans,

1166
01:06:29,840 --> 01:06:32,920
Speaker 1: I feel really truly understand this. But when you go

1167
01:06:33,040 --> 01:06:35,680
Speaker 1: traveling the other parts of the world, um, places in

1168
01:06:35,680 --> 01:06:38,880
Speaker 1: the Middle East and such, to sit down and have

1169
01:06:39,520 --> 01:06:42,120
Speaker 1: a conversation like we're having now, or even a more

1170
01:06:42,560 --> 01:06:46,400
Speaker 1: benign conversation, maybe just some superficial talk about politics and

1171
01:06:46,440 --> 01:06:49,680
Speaker 1: a cafe or a restaurant, that would not happen like

1172
01:06:49,800 --> 01:06:53,440
Speaker 1: that never happens in many countries around the world because

1173
01:06:53,440 --> 01:06:56,040
Speaker 1: people are so afraid of the regime. And it's it's

1174
01:06:56,040 --> 01:06:58,640
Speaker 1: not even a fear, it's just an understanding like that's

1175
01:06:58,680 --> 01:07:00,600
Speaker 1: part of the social bargain that yeah, I guess you

1176
01:07:00,600 --> 01:07:04,280
Speaker 1: have with the with the regime, yep um. And it

1177
01:07:04,320 --> 01:07:06,360
Speaker 1: feels like we're kind of moving to that. I mean,

1178
01:07:06,400 --> 01:07:11,000
Speaker 1: I've had some funny experiences where, um, you know, people

1179
01:07:11,000 --> 01:07:13,160
Speaker 1: in the media are afraid to talk in front of

1180
01:07:13,160 --> 01:07:15,480
Speaker 1: their peers, but then they know who I am and

1181
01:07:15,840 --> 01:07:17,800
Speaker 1: kind of like when we're by ourselves will kind of

1182
01:07:17,840 --> 01:07:19,920
Speaker 1: like give me a little elbow and be like, yeah, man,

1183
01:07:20,000 --> 01:07:23,040
Speaker 1: don't believe the media narratives. You know, they're they're like

1184
01:07:23,080 --> 01:07:26,640
Speaker 1: closeted conservatives. Oh I get yeah, I get that all

1185
01:07:26,640 --> 01:07:31,080
Speaker 1: the time from people. Yeah, it's like they can't say

1186
01:07:31,120 --> 01:07:34,520
Speaker 1: certain things in certain ways because they'll get they'll get hammered,

1187
01:07:34,560 --> 01:07:38,200
Speaker 1: they'll be unemployable, they won't work with them. Um. And

1188
01:07:38,240 --> 01:07:42,000
Speaker 1: then this, this has the potential to become explicit um

1189
01:07:42,040 --> 01:07:44,120
Speaker 1: and if it's a part of a blockchain or part

1190
01:07:45,200 --> 01:07:48,640
Speaker 1: you know, baked in in in the right way, it's unstoppable.

1191
01:07:48,960 --> 01:07:50,440
Speaker 1: I mean, it's not something you could like go to

1192
01:07:50,520 --> 01:07:53,200
Speaker 1: courts and get expunged. You know, there's no one to

1193
01:07:53,240 --> 01:07:56,160
Speaker 1: talk to, you can't clear your name correct. It's just yeah,

1194
01:07:56,200 --> 01:08:01,000
Speaker 1: it's like this this you know, global block job that

1195
01:08:01,360 --> 01:08:04,360
Speaker 1: kind of strangles us and it becomes as oppressive as

1196
01:08:04,400 --> 01:08:08,320
Speaker 1: the Chinese system, but something that we don't really have

1197
01:08:08,440 --> 01:08:11,880
Speaker 1: much control over, you know. In um. I think this

1198
01:08:12,040 --> 01:08:14,360
Speaker 1: is kind of a well known phenomena that when when

1199
01:08:14,360 --> 01:08:18,679
Speaker 1: societies are shaking shaking up and it reshuffles our mental deck.

1200
01:08:18,720 --> 01:08:21,400
Speaker 1: It takes a couple of generations for people to kind

1201
01:08:21,400 --> 01:08:25,320
Speaker 1: of fully understand the new system. Um, social media is

1202
01:08:25,320 --> 01:08:28,000
Speaker 1: a very new development for us. And you know, I

1203
01:08:28,320 --> 01:08:30,559
Speaker 1: grew up. I'm young enough that I came up and

1204
01:08:30,560 --> 01:08:33,519
Speaker 1: grew up as we moved from analog to digital and

1205
01:08:33,600 --> 01:08:35,080
Speaker 1: you know then we got a O L and our

1206
01:08:35,080 --> 01:08:37,400
Speaker 1: fifty six K modem and watch this whole development of

1207
01:08:37,439 --> 01:08:40,800
Speaker 1: social media. Um, do you think that you know, say,

1208
01:08:41,000 --> 01:08:44,320
Speaker 1: you know, our kids are grandkids. Eventually they're gonna there's

1209
01:08:44,320 --> 01:08:46,920
Speaker 1: gonna be a maturing in society and we'll start to

1210
01:08:47,000 --> 01:08:50,599
Speaker 1: use social media and more responsible. Um dare I say

1211
01:08:50,720 --> 01:08:57,240
Speaker 1: adult ways? Yeah? I think the I think the way

1212
01:08:57,240 --> 01:09:01,040
Speaker 1: that that actually gets up gets used is that kind

1213
01:09:01,040 --> 01:09:05,679
Speaker 1: of this open source network, kind of organizational form gets

1214
01:09:05,880 --> 01:09:13,240
Speaker 1: gets tamed. Just like we tamed institutions bureaucracy to provide

1215
01:09:13,320 --> 01:09:18,960
Speaker 1: us positive functionality and decision making, we've tamed markets to

1216
01:09:19,000 --> 01:09:21,559
Speaker 1: a large extent to help us with our decision making,

1217
01:09:21,560 --> 01:09:25,439
Speaker 1: societal decision making. We also trained tame tribalism. We we

1218
01:09:25,600 --> 01:09:28,800
Speaker 1: changed it, we abstracted it and turned it into uh,

1219
01:09:29,360 --> 01:09:33,920
Speaker 1: the mechanism behind religions and and also in profession behind nationalism.

1220
01:09:33,920 --> 01:09:37,920
Speaker 1: You know, nationalism is as a form of tribalism um.

1221
01:09:37,960 --> 01:09:41,920
Speaker 1: And those have all served useful purposes, and you know,

1222
01:09:42,520 --> 01:09:45,400
Speaker 1: they can be used in bad ways. I mean, bureaucracy

1223
01:09:45,640 --> 01:09:48,519
Speaker 1: can be used as a bad thing, uh when when

1224
01:09:48,520 --> 01:09:50,400
Speaker 1: in the dictator's hands, it can be making them very

1225
01:09:50,439 --> 01:09:53,880
Speaker 1: efficient at killing people, or it would be used in

1226
01:09:53,920 --> 01:09:56,960
Speaker 1: a good thing in terms of you know, mobilizing resources

1227
01:09:57,000 --> 01:10:00,439
Speaker 1: to undertake big projects that are positive. But so this,

1228
01:10:00,439 --> 01:10:03,639
Speaker 1: this networked form of organization made possible by social networking,

1229
01:10:03,680 --> 01:10:07,479
Speaker 1: this you know, these open source networks like I was

1230
01:10:07,520 --> 01:10:11,760
Speaker 1: talking about in the political sense. Uh, we'll figure out.

1231
01:10:11,760 --> 01:10:13,160
Speaker 1: We're going to have to figure out how to tame

1232
01:10:13,200 --> 01:10:15,040
Speaker 1: them and make them part of our system because they

1233
01:10:15,080 --> 01:10:19,439
Speaker 1: can do things that uh, the other older systems, the

1234
01:10:19,479 --> 01:10:25,120
Speaker 1: other older organizations can do. Right. And there's people like

1235
01:10:25,720 --> 01:10:29,080
Speaker 1: probably you and I who both you know, have read

1236
01:10:29,280 --> 01:10:31,920
Speaker 1: you know, science fiction and also just seeing technology and

1237
01:10:32,280 --> 01:10:35,720
Speaker 1: have these great aspirations for what technology can do. Um.

1238
01:10:35,760 --> 01:10:38,959
Speaker 1: But I feel like this is actually a positive development

1239
01:10:38,960 --> 01:10:43,080
Speaker 1: that because of the Trumpell action and the charges of

1240
01:10:43,160 --> 01:10:46,599
Speaker 1: collusion and Russian meddling, not not the collusion, I should

1241
01:10:46,600 --> 01:10:50,639
Speaker 1: say the Russian meddaling the disinformation campaigns um that people

1242
01:10:50,640 --> 01:10:53,320
Speaker 1: are becoming more aware of social media and the negative

1243
01:10:53,360 --> 01:11:00,719
Speaker 1: ways that it can be used. Yeah. They of course

1244
01:11:00,760 --> 01:11:04,720
Speaker 1: that has the potential of causing all sorts of you know,

1245
01:11:05,160 --> 01:11:08,240
Speaker 1: setting emotion a lot of constraints, or for the big

1246
01:11:08,240 --> 01:11:12,559
Speaker 1: social networking companies to start changing their aiyes, which right, Yeah,

1247
01:11:13,000 --> 01:11:15,479
Speaker 1: one of the reports I was writing about writing about

1248
01:11:15,479 --> 01:11:17,880
Speaker 1: the social aies is that you know, now that we're

1249
01:11:17,880 --> 01:11:21,120
Speaker 1: putting pressure on Facebook and YouTube and others, is that

1250
01:11:21,160 --> 01:11:27,639
Speaker 1: they'll start training their aies to minimize complaints about content,

1251
01:11:28,520 --> 01:11:31,400
Speaker 1: minimized complaints that is, fake news, or minimize complaints that

1252
01:11:31,560 --> 01:11:34,400
Speaker 1: is you know, obnoxious or or hate speech or or

1253
01:11:34,439 --> 01:11:37,240
Speaker 1: the like. And when you start training in AI light that,

1254
01:11:37,520 --> 01:11:43,880
Speaker 1: um it, it gets really good at kind of minimizing

1255
01:11:44,000 --> 01:11:47,120
Speaker 1: the complaints. It iterates towards that goal. You know, it's

1256
01:11:47,240 --> 01:11:49,760
Speaker 1: interacting with billions of people and it changes sit you know,

1257
01:11:50,120 --> 01:11:53,200
Speaker 1: it deletes certain things or soft bands certain types of content.

1258
01:11:53,360 --> 01:11:57,599
Speaker 1: Is it wipes out visibility of a content some uploaded

1259
01:11:57,680 --> 01:12:01,760
Speaker 1: video before anyone even sees it. Uh. And if if

1260
01:12:01,760 --> 01:12:05,599
Speaker 1: it moves the complaint meter down, you know, it reduces complaints,

1261
01:12:05,640 --> 01:12:09,519
Speaker 1: then that feature gets kept and and iterates again and

1262
01:12:09,520 --> 01:12:15,000
Speaker 1: again and again. The unintendive side effect if something like

1263
01:12:15,040 --> 01:12:18,560
Speaker 1: that is that we end up having people you know, surrounded,

1264
01:12:18,640 --> 01:12:21,160
Speaker 1: you know, kind of encased in this big ball of

1265
01:12:21,200 --> 01:12:23,800
Speaker 1: cotton where they don't see anything negative or anything that

1266
01:12:23,840 --> 01:12:26,400
Speaker 1: they don't they disagree with. Oh. I saw that during

1267
01:12:26,439 --> 01:12:29,880
Speaker 1: the election where I had um conservative friends who are

1268
01:12:29,920 --> 01:12:31,680
Speaker 1: like kind of reaching out. It's kind of funny to

1269
01:12:31,680 --> 01:12:34,559
Speaker 1: see and they're saying, like, can can can a Hillary

1270
01:12:34,600 --> 01:12:37,080
Speaker 1: supporter please tell me why they support Hillary? Like I'm

1271
01:12:37,120 --> 01:12:39,760
Speaker 1: not trying to be uh, you know, a dick. I'm

1272
01:12:39,800 --> 01:12:42,760
Speaker 1: seriously asking, like, I'm interested to hear your point of view.

1273
01:12:42,800 --> 01:12:44,920
Speaker 1: And I thought it was interesting to see people posting

1274
01:12:44,960 --> 01:12:47,400
Speaker 1: stuff like that because what it means is they're literally

1275
01:12:47,479 --> 01:12:50,640
Speaker 1: not seeing the other side of the other side of

1276
01:12:50,680 --> 01:12:54,360
Speaker 1: the political spectrum. Yeah. And and that was just you know,

1277
01:12:54,439 --> 01:12:57,800
Speaker 1: through section of the kind of friends that you have,

1278
01:12:58,360 --> 01:13:01,679
Speaker 1: and and and the stuff that a post because they're

1279
01:13:01,680 --> 01:13:03,600
Speaker 1: posting a lot because they get positive kind of the

1280
01:13:03,600 --> 01:13:08,559
Speaker 1: serotonin kick whenever they get a like, uh, the it

1281
01:13:08,600 --> 01:13:11,400
Speaker 1: gets even worse and far worse when the ai start

1282
01:13:11,479 --> 01:13:13,920
Speaker 1: kicking in, and that that you don't even see the

1283
01:13:14,000 --> 01:13:16,400
Speaker 1: things I mean, you know they're talking about you know,

1284
01:13:16,479 --> 01:13:19,000
Speaker 1: millions of videos not even showing up on YouTube because

1285
01:13:19,600 --> 01:13:24,479
Speaker 1: they're screened before they even hit yeah, or they screen

1286
01:13:24,560 --> 01:13:27,320
Speaker 1: before they hit you. They may be visible to other

1287
01:13:27,360 --> 01:13:29,840
Speaker 1: people and you and you could have people, you know,

1288
01:13:29,880 --> 01:13:32,280
Speaker 1: three years from now going, oh, I don't have any

1289
01:13:32,280 --> 01:13:34,759
Speaker 1: problems with Trump or I don't have any problems with whoever,

1290
01:13:35,360 --> 01:13:38,640
Speaker 1: because I haven't seen any negative news on right, I

1291
01:13:38,640 --> 01:13:42,120
Speaker 1: haven't seen anything anyone disagree or say it was terrible.

1292
01:13:42,280 --> 01:13:44,680
Speaker 1: And now another element is added to that with the

1293
01:13:44,720 --> 01:13:46,880
Speaker 1: monetization of everything. I mean, I've talked about it on

1294
01:13:46,920 --> 01:13:49,200
Speaker 1: the show, and we do a live stream now or

1295
01:13:49,240 --> 01:13:52,000
Speaker 1: like a fraction of a fraction of our Facebook audience

1296
01:13:52,040 --> 01:13:54,960
Speaker 1: is seeing that show up on their true and you know,

1297
01:13:55,240 --> 01:13:57,840
Speaker 1: it's it's kind of weird, and it's also them trying

1298
01:13:57,880 --> 01:13:59,600
Speaker 1: to make money, but yea, it is you living in

1299
01:13:59,680 --> 01:14:01,800
Speaker 1: a neck chamber. And then I've also seen the thing

1300
01:14:01,840 --> 01:14:04,479
Speaker 1: recently where there's a way you could look up on

1301
01:14:04,600 --> 01:14:10,040
Speaker 1: your profile how Facebook has you, um like situated as

1302
01:14:10,040 --> 01:14:15,519
Speaker 1: a conservative liberal moderate and that from my perspective, yeah,

1303
01:14:15,520 --> 01:14:17,400
Speaker 1: it has me as a moderate. I I don't have

1304
01:14:17,400 --> 01:14:19,760
Speaker 1: anything listed under my political views, and I guess it's

1305
01:14:19,800 --> 01:14:22,280
Speaker 1: just because of like who my friends are, and you know,

1306
01:14:22,320 --> 01:14:24,479
Speaker 1: I have friends of all different backgrounds. But yeah, it

1307
01:14:24,880 --> 01:14:27,720
Speaker 1: is pretty interesting that so that that way, you know,

1308
01:14:27,760 --> 01:14:31,160
Speaker 1: if you're listed as a conservative, they're targeting conservative ads

1309
01:14:31,200 --> 01:14:33,240
Speaker 1: to you. And I mean, it is a whole lot

1310
01:14:33,280 --> 01:14:35,360
Speaker 1: of social engineering. Like it does make me want to

1311
01:14:35,400 --> 01:14:39,400
Speaker 1: get off there very but that's also the um, that's

1312
01:14:39,400 --> 01:14:41,519
Speaker 1: just the world we live in now, is is that

1313
01:14:41,560 --> 01:14:44,040
Speaker 1: they know, you know, what you're clicking on, and what

1314
01:14:44,120 --> 01:14:46,240
Speaker 1: type of stuff you're responding to, and what stores you

1315
01:14:46,320 --> 01:14:50,360
Speaker 1: shop at, both online and offline, and uh, it's a

1316
01:14:50,400 --> 01:14:53,080
Speaker 1: whole lot of big brother stuff going on. I think

1317
01:14:53,080 --> 01:14:55,120
Speaker 1: you're probably better off stand on. I mean, you know,

1318
01:14:55,160 --> 01:14:57,720
Speaker 1: I saw a lot of I mean, granted, I was

1319
01:14:57,760 --> 01:14:59,960
Speaker 1: involved in a lot of the early tech that became

1320
01:15:00,080 --> 01:15:03,240
Speaker 1: social networking. So you know, I joined a company in

1321
01:15:03,240 --> 01:15:04,760
Speaker 1: two thousand and one that built the you know, the

1322
01:15:04,800 --> 01:15:09,320
Speaker 1: first networked blogging tool, did RSS and all that other

1323
01:15:09,320 --> 01:15:11,439
Speaker 1: stuff that you know, that kind of network blog that

1324
01:15:11,560 --> 01:15:14,240
Speaker 1: became Facebook and Twitter and stuff. So I've been kind

1325
01:15:14,280 --> 01:15:17,120
Speaker 1: of a big proponent of this stuff really early on.

1326
01:15:18,160 --> 01:15:22,360
Speaker 1: UM and uh, I found it it's actually more positive

1327
01:15:22,400 --> 01:15:27,000
Speaker 1: than negative. Even now, because if you disconnect, you lose

1328
01:15:27,040 --> 01:15:29,920
Speaker 1: all those people and all those connections. You know, you

1329
01:15:30,080 --> 01:15:32,880
Speaker 1: become a nonentity. I've seen people just disappear. I mean,

1330
01:15:33,640 --> 01:15:36,800
Speaker 1: and you know, people that would be great to interact with,

1331
01:15:36,840 --> 01:15:40,840
Speaker 1: they just become who are they talking to a few

1332
01:15:40,840 --> 01:15:42,559
Speaker 1: people that are you know, they can't talk about the

1333
01:15:42,600 --> 01:15:45,200
Speaker 1: topics that that they they're interested in because they they

1334
01:15:45,200 --> 01:15:48,280
Speaker 1: don't have access to them online, right right, especially you

1335
01:15:48,280 --> 01:15:51,559
Speaker 1: know smarter people. Do we really want them disconnecting people

1336
01:15:51,560 --> 01:15:54,200
Speaker 1: who you know, really have something to say on a subject.

1337
01:15:54,240 --> 01:15:56,360
Speaker 1: And then what we're going to get is like teenage

1338
01:15:56,400 --> 01:16:00,200
Speaker 1: girls on Snapchat, you know, having that dog Phil there

1339
01:16:00,240 --> 01:16:04,680
Speaker 1: for their face. That's gonna be our social media I

1340
01:16:04,720 --> 01:16:08,599
Speaker 1: don't know, go ahead, John, Yeah, No, I mean what's interesting,

1341
01:16:08,640 --> 01:16:13,280
Speaker 1: I mean, at least from a security perspective, is everything

1342
01:16:13,280 --> 01:16:16,439
Speaker 1: that we're talking about here is magnified globally because no

1343
01:16:16,880 --> 01:16:18,439
Speaker 1: people are talking about to say that the client of

1344
01:16:18,479 --> 01:16:22,720
Speaker 1: Facebook in the US. But you know, Facebook's adding five

1345
01:16:23,080 --> 01:16:30,040
Speaker 1: thousand new users every day, a number, five thousand daily daily. Yeah,

1346
01:16:30,240 --> 01:16:32,479
Speaker 1: and you know it's two and a half billion people.

1347
01:16:32,560 --> 01:16:34,400
Speaker 1: And it's gonna slow down because they're gonna saturate the

1348
01:16:34,479 --> 01:16:40,439
Speaker 1: planet outside of China, but the it's replaced the local news.

1349
01:16:41,400 --> 01:16:44,200
Speaker 1: It's replaced the kind of news source for a good

1350
01:16:44,240 --> 01:16:46,800
Speaker 1: portion of the world. So if you're like in Cambodia,

1351
01:16:46,920 --> 01:16:50,800
Speaker 1: this is the news source, wouldn't you say? I mean

1352
01:16:50,840 --> 01:16:55,400
Speaker 1: it's connected, but I would say Twitter especially, Um, you

1353
01:16:55,439 --> 01:16:58,000
Speaker 1: know when you've seen when you've seen the protests in

1354
01:16:58,000 --> 01:17:00,800
Speaker 1: in the Middle East and all that stuff that you

1355
01:17:00,800 --> 01:17:02,679
Speaker 1: found out about it first on Twitter. I found out

1356
01:17:02,680 --> 01:17:05,320
Speaker 1: about the Vin Wadden death on Twitter first. When when

1357
01:17:05,680 --> 01:17:08,960
Speaker 1: news hits it's way before the mainstream media. Oh yeah,

1358
01:17:09,000 --> 01:17:11,960
Speaker 1: Twitter is definitely um, you know, just it's basically a

1359
01:17:12,000 --> 01:17:15,920
Speaker 1: big RSS feed. Is is great at broadcasting, you know,

1360
01:17:16,040 --> 01:17:18,519
Speaker 1: and and as a as a news source. Um, it's

1361
01:17:18,520 --> 01:17:25,080
Speaker 1: actually even probably more destabilizing than Facebook. Facebook is limited

1362
01:17:25,080 --> 01:17:28,439
Speaker 1: to a certain number of friends, and you don't have

1363
01:17:28,520 --> 01:17:32,519
Speaker 1: that kind of broadcast aspect, and it had a little

1364
01:17:32,520 --> 01:17:36,280
Speaker 1: bit of broadcast aspect when it had the uh, the

1365
01:17:36,280 --> 01:17:40,759
Speaker 1: the AI s that they had initially built were focused

1366
01:17:40,760 --> 01:17:43,880
Speaker 1: on finding viral pieces of content that people tended to

1367
01:17:43,920 --> 01:17:47,880
Speaker 1: like and then propagating it. So instead of like having

1368
01:17:47,920 --> 01:17:50,200
Speaker 1: only a fraction of the people actually see your video

1369
01:17:51,600 --> 01:17:56,360
Speaker 1: on Facebook, kind of that negative damper. Uh, it would

1370
01:17:56,400 --> 01:17:59,360
Speaker 1: take that video and then ten times your audience would

1371
01:17:59,400 --> 01:18:02,799
Speaker 1: see it if if it had a strong initial reaction.

1372
01:18:03,040 --> 01:18:06,679
Speaker 1: I also, this could just be the way I see things.

1373
01:18:06,720 --> 01:18:09,120
Speaker 1: You'd have a better view on this. But I feel

1374
01:18:09,120 --> 01:18:11,759
Speaker 1: like people pay more attention to what's friending on Twitter

1375
01:18:11,880 --> 01:18:14,360
Speaker 1: than on Facebook. You know, if you see something in

1376
01:18:14,400 --> 01:18:16,720
Speaker 1: that those top three trends, if it's a name, if

1377
01:18:16,720 --> 01:18:19,559
Speaker 1: it's a country, You're like, all right, what's going on here?

1378
01:18:19,600 --> 01:18:21,920
Speaker 1: And I want to have the news before everybody else.

1379
01:18:22,280 --> 01:18:25,439
Speaker 1: It's definitely a much cleaner way of getting news from

1380
01:18:25,439 --> 01:18:27,599
Speaker 1: a direct source. So you can find that one person

1381
01:18:28,040 --> 01:18:31,800
Speaker 1: that's that live kind of person on the spot and

1382
01:18:32,240 --> 01:18:34,559
Speaker 1: you can directly connect to them, directly follow them and

1383
01:18:34,600 --> 01:18:40,559
Speaker 1: watch what they're doing. It's awesome. Yeah, it's a but

1384
01:18:40,800 --> 01:18:42,519
Speaker 1: it does put a lot of power in some of

1385
01:18:42,560 --> 01:18:46,000
Speaker 1: the big hubs that you don't get on Facebook. I mean,

1386
01:18:46,320 --> 01:18:48,240
Speaker 1: maybe it's because of the circle I'm in, but I

1387
01:18:48,280 --> 01:18:51,880
Speaker 1: feel like Twitter is just saturated by journalists and academics

1388
01:18:51,920 --> 01:18:54,439
Speaker 1: who are like training snarky barbs at one another on

1389
01:18:54,479 --> 01:18:57,280
Speaker 1: a daily basis. I'm not I'm not a big fan

1390
01:18:57,320 --> 01:19:00,599
Speaker 1: of Twitter. Yeah, there's whether there's just two pieces. That's

1391
01:19:00,640 --> 01:19:04,000
Speaker 1: that a lot of what we're seeing in that kind

1392
01:19:04,000 --> 01:19:08,680
Speaker 1: of the consensus morality is being built by that group, right,

1393
01:19:09,160 --> 01:19:13,000
Speaker 1: and they're using that. It's that I'd say probably you know,

1394
01:19:13,040 --> 01:19:18,679
Speaker 1: two million people in the government, bureaucracy and and in media,

1395
01:19:19,400 --> 01:19:23,479
Speaker 1: in academia, um, you know, it's much smaller the group

1396
01:19:23,520 --> 01:19:26,360
Speaker 1: that's you know, truly active, probably a hundred thousand or

1397
01:19:26,439 --> 01:19:30,840
Speaker 1: less who are actually driving this kind of consensus morality forward.

1398
01:19:31,040 --> 01:19:35,160
Speaker 1: It's like the new power elite. Yeah, exactly. And it's

1399
01:19:35,200 --> 01:19:38,080
Speaker 1: great at shaming. You can shame Pearson a person really

1400
01:19:38,120 --> 01:19:41,680
Speaker 1: quickly on Twitter. I mean, the way that Trump has

1401
01:19:41,760 --> 01:19:44,760
Speaker 1: used it has really changed everything. That before he olds

1402
01:19:44,760 --> 01:19:47,400
Speaker 1: a press conference, before he talks to the media, goes

1403
01:19:47,439 --> 01:19:49,360
Speaker 1: on the news, he just tweets what he wants. And

1404
01:19:49,520 --> 01:19:52,240
Speaker 1: I remember there was actually a really uh I mean,

1405
01:19:52,280 --> 01:19:54,880
Speaker 1: it's just a funny but interesting tweet of Trump's is

1406
01:19:54,920 --> 01:19:58,240
Speaker 1: where he said, like me, I don't remember what he

1407
01:19:58,320 --> 01:20:00,839
Speaker 1: was talking about specifically, but he said, like me tweeting

1408
01:20:00,840 --> 01:20:02,800
Speaker 1: out this stuff before I hold the press conference and

1409
01:20:02,800 --> 01:20:07,240
Speaker 1: all that. He's like, it's not presidential, it's modern day presidential. Right,

1410
01:20:07,280 --> 01:20:10,840
Speaker 1: It's kind of true, Like this is the future. I don't.

1411
01:20:10,960 --> 01:20:13,280
Speaker 1: I don't think the president following Trump is going to

1412
01:20:13,360 --> 01:20:16,120
Speaker 1: be off of Twitter and not doing you know, somewhat

1413
01:20:16,160 --> 01:20:19,559
Speaker 1: similar things. Well. Yeah, Twitter definitely allowed him to route

1414
01:20:19,560 --> 01:20:23,480
Speaker 1: around the media and directly connect with is with the insurgency,

1415
01:20:23,520 --> 01:20:27,719
Speaker 1: and it was it was very effective. It's also allowed

1416
01:20:27,760 --> 01:20:30,200
Speaker 1: the insurgency to interact with him. So what they did

1417
01:20:30,320 --> 01:20:31,840
Speaker 1: is that whenever they came up with a meme or

1418
01:20:31,880 --> 01:20:36,719
Speaker 1: some idea that was in you know, what I thought

1419
01:20:36,760 --> 01:20:38,680
Speaker 1: was good, it would be propagated and would show up

1420
01:20:38,680 --> 01:20:41,439
Speaker 1: in Trump's feed and Trump would find it, you know,

1421
01:20:41,479 --> 01:20:43,640
Speaker 1: would go great past the media minders and all the

1422
01:20:43,680 --> 01:20:46,960
Speaker 1: people that were massaging you know, the information didn't take

1423
01:20:46,960 --> 01:20:49,840
Speaker 1: it the going into Trump and you see that thing

1424
01:20:49,840 --> 01:20:52,720
Speaker 1: and then he What made him the perfect kind of

1425
01:20:52,800 --> 01:20:54,639
Speaker 1: vehicle for this is that he would pick that up

1426
01:20:55,800 --> 01:20:59,959
Speaker 1: and use it tweeting the thing of him body slamming CNN,

1427
01:21:00,120 --> 01:21:03,240
Speaker 1: which was originally like Vince McMahon, Oh yeah, he picks

1428
01:21:03,320 --> 01:21:07,160
Speaker 1: up all these ideas, you know, right off as Twitter feed. John,

1429
01:21:07,800 --> 01:21:10,360
Speaker 1: I was wondering if you could just backtrack one second.

1430
01:21:10,360 --> 01:21:12,679
Speaker 1: I was wondering if you could finish that thought about

1431
01:21:12,800 --> 01:21:15,920
Speaker 1: how there's you know, perhaps a hundred thousand people who

1432
01:21:15,960 --> 01:21:19,759
Speaker 1: are engaged in this building of consensus morality on social media.

1433
01:21:20,160 --> 01:21:22,080
Speaker 1: And it's kind of flushed out that thought that you

1434
01:21:22,120 --> 01:21:23,960
Speaker 1: were making, because that's really important, I think, and I

1435
01:21:23,960 --> 01:21:33,760
Speaker 1: haven't heard anyone quite phrase it that way. Oh well, um, yeah,

1436
01:21:33,800 --> 01:21:37,840
Speaker 1: it's it's a decentral it's a decentralized network, like we

1437
01:21:37,840 --> 01:21:43,479
Speaker 1: were describing earlier. Yeah. The way I the way I

1438
01:21:43,560 --> 01:21:45,839
Speaker 1: kind of framed it, you know, I bought the framework

1439
01:21:45,880 --> 01:21:50,040
Speaker 1: for myself about this is that they had the I

1440
01:21:50,080 --> 01:21:52,519
Speaker 1: put it into kind of the dimensions of war. So

1441
01:21:52,600 --> 01:21:55,960
Speaker 1: you have you know that the physical and the psychological

1442
01:21:56,000 --> 01:22:01,599
Speaker 1: and the and the moral um, you know, the kind

1443
01:22:01,640 --> 01:22:05,280
Speaker 1: of a Buoidian framework and the psychological kind of maneuver.

1444
01:22:05,360 --> 01:22:10,680
Speaker 1: Warfare was the insurgency, you know, very memetic, Uh, you know,

1445
01:22:10,840 --> 01:22:17,400
Speaker 1: lots of disinformation, lots of uh. They would swarm on targets,

1446
01:22:18,439 --> 01:22:24,120
Speaker 1: threaten them, yell, let them shout them down. Very very effective, uh,

1447
01:22:24,760 --> 01:22:30,840
Speaker 1: constantly moving. Uh. The moral the this the kind of

1448
01:22:30,840 --> 01:22:33,920
Speaker 1: new moral network obviously fights in the moral space. Um.

1449
01:22:34,120 --> 01:22:36,640
Speaker 1: And it tries to you know, it builds by you know,

1450
01:22:36,680 --> 01:22:39,960
Speaker 1: creating this consensus and then it fights by you know,

1451
01:22:40,000 --> 01:22:42,880
Speaker 1: through this shaming and by this you know disconnection, it

1452
01:22:42,960 --> 01:22:48,240
Speaker 1: disconnects you from from the network, and that disconnection actually

1453
01:22:48,280 --> 01:22:53,479
Speaker 1: does you damage because you know, right now, so much

1454
01:22:53,520 --> 01:22:57,840
Speaker 1: of what we do, both personally and and you know financially,

1455
01:22:58,000 --> 01:23:00,160
Speaker 1: you know, through our jobs is done online. If you

1456
01:23:00,160 --> 01:23:04,320
Speaker 1: become disconnected, to become less valuable, uh, your trunk hated,

1457
01:23:04,400 --> 01:23:09,440
Speaker 1: your life is diminished. And that's been very very effective

1458
01:23:10,080 --> 01:23:13,800
Speaker 1: in terms of you know, how they actually you know

1459
01:23:13,920 --> 01:23:19,639
Speaker 1: a chief success. UM. Twitter has been a amazing vehicle

1460
01:23:19,680 --> 01:23:22,320
Speaker 1: for that, much more so than Facebook. You know, Facebook

1461
01:23:22,360 --> 01:23:25,200
Speaker 1: allowed you know, the small groups, the kind of the

1462
01:23:25,240 --> 01:23:29,639
Speaker 1: insurgency to operate below the radar because you know, there's

1463
01:23:29,640 --> 01:23:31,800
Speaker 1: not one place on Facebook you can see all the

1464
01:23:31,840 --> 01:23:38,080
Speaker 1: flow and UM an interesting kind of uh spin off

1465
01:23:38,080 --> 01:23:41,360
Speaker 1: from this whole Cambridge analytical thing, because the Cambridge analytical

1466
01:23:41,400 --> 01:23:44,040
Speaker 1: thing is that Facebook didn't sell data. Allowed a researcher

1467
01:23:44,120 --> 01:23:47,680
Speaker 1: to gather some data using an app by voluntary participants

1468
01:23:47,800 --> 01:23:51,320
Speaker 1: that gathered a teeny bit from a lot of people, um,

1469
01:23:51,360 --> 01:23:53,080
Speaker 1: in order to kind of learn more about how the

1470
01:23:53,120 --> 01:23:57,160
Speaker 1: networked work. And that's and then this guy turned around

1471
01:23:57,160 --> 01:23:59,200
Speaker 1: and sold it to Cambrige Analytical for a million bucks.

1472
01:23:59,320 --> 01:24:01,160
Speaker 1: So it's he made a lot of money and he

1473
01:24:01,320 --> 01:24:04,839
Speaker 1: kind of betrayed the agreement that he had with Facebook

1474
01:24:04,880 --> 01:24:10,000
Speaker 1: over this. Now Facebook shutting down all these researchers, So

1475
01:24:11,640 --> 01:24:14,040
Speaker 1: the ability to actually see what's going on across the

1476
01:24:14,080 --> 01:24:17,160
Speaker 1: board is going to be less so than than ever

1477
01:24:17,240 --> 01:24:21,040
Speaker 1: and that kind of you know, murky kind of small networks,

1478
01:24:21,080 --> 01:24:24,720
Speaker 1: you know, people with two, three, four friends. Uh, is

1479
01:24:24,760 --> 01:24:30,920
Speaker 1: it you know, perfect for kind of the insurgency to operate? Um,

1480
01:24:31,000 --> 01:24:33,479
Speaker 1: you can't be you know, there's no real top down

1481
01:24:33,560 --> 01:24:37,040
Speaker 1: enforcement except through Facebook. If they used AIS to do it.

1482
01:24:38,439 --> 01:24:39,800
Speaker 1: What do you I mean, if you were to make

1483
01:24:39,840 --> 01:24:45,240
Speaker 1: a prediction for these big social media tech companies Facebook, Twitter, etcetera,

1484
01:24:45,920 --> 01:24:48,559
Speaker 1: where do you think that's gonna go? Um in the future.

1485
01:24:48,840 --> 01:24:51,200
Speaker 1: I mean you kind of pointed out, No, that's not

1486
01:24:51,240 --> 01:24:53,759
Speaker 1: going to become the next MySpace. They're they're still adding

1487
01:24:53,760 --> 01:24:56,800
Speaker 1: a lot of new users. Um, is there going to

1488
01:24:56,880 --> 01:24:59,280
Speaker 1: be like some anti trust issues? What do you think

1489
01:24:59,320 --> 01:25:04,720
Speaker 1: is going to happen? Um? Well, what's happening in the

1490
01:25:04,880 --> 01:25:09,200
Speaker 1: US is that they are basically relying on Facebook to

1491
01:25:09,880 --> 01:25:14,040
Speaker 1: maintain stability. They've outsourced social stability to Facebook. Our our

1492
01:25:14,120 --> 01:25:19,640
Speaker 1: government has Yeah, I mean basically UM. And that's the deal. UM,

1493
01:25:19,680 --> 01:25:23,599
Speaker 1: that they provide us insight into all these different countries

1494
01:25:23,640 --> 01:25:27,800
Speaker 1: around the world, and that they provide us which you know,

1495
01:25:27,800 --> 01:25:29,519
Speaker 1: with two and a half billion users, they know more

1496
01:25:29,560 --> 01:25:32,240
Speaker 1: about a lot of the what's going on in in

1497
01:25:32,240 --> 01:25:34,760
Speaker 1: in places around the world. And UM, a lot of

1498
01:25:34,800 --> 01:25:36,600
Speaker 1: the countries do themselves. Now that's some hell of a

1499
01:25:36,600 --> 01:25:40,040
Speaker 1: good census data if you can get. Oh yeah, and

1500
01:25:40,160 --> 01:25:44,200
Speaker 1: it's moving towards a global census. And Facebook is also

1501
01:25:44,320 --> 01:25:47,599
Speaker 1: getting to the point where, um, they did some AI

1502
01:25:47,640 --> 01:25:50,320
Speaker 1: official recognition work. About a year and a half ago,

1503
01:25:50,600 --> 01:25:53,320
Speaker 1: some data came out that said, did they build a

1504
01:25:53,400 --> 01:25:58,360
Speaker 1: database of safe million people you know, users of Facebook,

1505
01:25:58,920 --> 01:26:03,000
Speaker 1: and um they train their AI to find them you

1506
01:26:03,040 --> 01:26:05,240
Speaker 1: know too, if you gave it a new picture of

1507
01:26:05,280 --> 01:26:07,800
Speaker 1: one of the people in that database, it could find

1508
01:26:07,880 --> 01:26:13,120
Speaker 1: you in five seconds out of million people. Now you

1509
01:26:13,160 --> 01:26:16,200
Speaker 1: can find you out of billions. And the interesting thing

1510
01:26:16,200 --> 01:26:18,120
Speaker 1: about this AI is once it's trained, it can run

1511
01:26:18,120 --> 01:26:26,080
Speaker 1: on a cell phone, so one you could that's like

1512
01:26:26,240 --> 01:26:28,759
Speaker 1: a perfect tool for a lot of you know what,

1513
01:26:28,760 --> 01:26:32,240
Speaker 1: what what we'd like to do globally, UM, in terms

1514
01:26:32,240 --> 01:26:35,800
Speaker 1: of identifying people people of interest and when you're saying

1515
01:26:35,880 --> 01:26:39,160
Speaker 1: the look at you know, people globally, and I talked

1516
01:26:39,200 --> 01:26:42,519
Speaker 1: about this just earlier. A lot of people credit like

1517
01:26:42,560 --> 01:26:45,760
Speaker 1: the Arab spring happening because of Twitter. You know, like

1518
01:26:45,840 --> 01:26:48,680
Speaker 1: how far down the line is it when they can

1519
01:26:48,760 --> 01:26:51,719
Speaker 1: no longer suppress the people of North Korea from seeing

1520
01:26:51,760 --> 01:26:53,760
Speaker 1: what's going on. Well, it's interesting that it can be

1521
01:26:53,800 --> 01:26:57,400
Speaker 1: a tool for revolution or a tool for social control. Yeah,

1522
01:26:57,479 --> 01:26:59,160
Speaker 1: I think it's going to end up being more social

1523
01:26:59,200 --> 01:27:02,360
Speaker 1: control as we go forward. You know, I turned it

1524
01:27:02,479 --> 01:27:07,000
Speaker 1: kind of a long night is um. You know, you

1525
01:27:07,040 --> 01:27:09,800
Speaker 1: know what happens when bureaucracy of the twentieth century went bad,

1526
01:27:09,800 --> 01:27:12,840
Speaker 1: It created a lot of you know, very efficient killing

1527
01:27:12,840 --> 01:27:15,800
Speaker 1: the shaderships, yeah, killing machines or or just you know,

1528
01:27:16,280 --> 01:27:20,120
Speaker 1: incredible oppression. And in this now we can build systems,

1529
01:27:20,400 --> 01:27:24,720
Speaker 1: these networks that can say through the same purpose and

1530
01:27:24,840 --> 01:27:29,240
Speaker 1: that you know, it can it can. It can using AI,

1531
01:27:29,560 --> 01:27:34,200
Speaker 1: you can it's not just censoring like the broadcast. It

1532
01:27:34,240 --> 01:27:37,800
Speaker 1: can you know, censor the living room conversations as well.

1533
01:27:39,680 --> 01:27:42,439
Speaker 1: You know, it's like, you know, not just having a

1534
01:27:42,439 --> 01:27:45,800
Speaker 1: sensor in the broadcast studio, it's in every single living room,

1535
01:27:45,920 --> 01:27:49,479
Speaker 1: every single discussion, every water cooler discussion. That's done via

1536
01:27:49,479 --> 01:27:55,680
Speaker 1: the network. Y. Yeah, and this is how this is

1537
01:27:55,680 --> 01:27:59,120
Speaker 1: how Facebook and Twitter and others, you know, stay off

1538
01:27:59,160 --> 01:28:02,679
Speaker 1: the government radar. Is that they provide the social stability

1539
01:28:02,680 --> 01:28:07,720
Speaker 1: and they make sure that that Trump doesn't happen next time. Um,

1540
01:28:07,760 --> 01:28:13,559
Speaker 1: and that they ensure that you know, destabilizing ideas and

1541
01:28:13,680 --> 01:28:16,760
Speaker 1: people in groups don't get any purchase. I mean the

1542
01:28:16,800 --> 01:28:19,280
Speaker 1: way you describe it, and I don't disagree with you,

1543
01:28:19,800 --> 01:28:22,679
Speaker 1: is that like Facebook is our new government, that they're

1544
01:28:22,680 --> 01:28:25,160
Speaker 1: almost like our new God or new religion that has

1545
01:28:25,200 --> 01:28:28,840
Speaker 1: a divine power kingmaker. Well, they do, they serve, they're

1546
01:28:28,880 --> 01:28:30,599
Speaker 1: serving a purpose. I mean you would see a lot

1547
01:28:30,600 --> 01:28:34,519
Speaker 1: of corporate kind of governance Act activism now coming out

1548
01:28:34,520 --> 01:28:37,479
Speaker 1: of companies like black Rock. I mean black Rock is

1549
01:28:37,520 --> 01:28:41,720
Speaker 1: like this major influence over like fourteen trillion dollars. Yeahs,

1550
01:28:41,840 --> 01:28:44,680
Speaker 1: like the size of the U. S economy. Um. That

1551
01:28:44,720 --> 01:28:48,840
Speaker 1: that has, you know, through boards of directors control over

1552
01:28:48,880 --> 01:28:55,160
Speaker 1: that kind of thing. And I remember hearing this, hearing

1553
01:28:55,200 --> 01:28:59,200
Speaker 1: an interview with the think who is the CEO of

1554
01:28:59,200 --> 01:29:01,839
Speaker 1: black Rock, and he said, you know, I'm not concerned

1555
01:29:01,840 --> 01:29:06,160
Speaker 1: about Putin. Putin and his his gang and most of

1556
01:29:06,160 --> 01:29:10,439
Speaker 1: the other people bad guys around the world. Because they're

1557
01:29:10,439 --> 01:29:13,720
Speaker 1: in my network. All their financial net worth, everything that

1558
01:29:13,760 --> 01:29:16,120
Speaker 1: they own, everything, their kids own, everything there, you know,

1559
01:29:16,920 --> 01:29:20,519
Speaker 1: entire family owns is in my network. I can see them,

1560
01:29:20,880 --> 01:29:24,200
Speaker 1: I can see where it goes. So they're not going

1561
01:29:24,280 --> 01:29:27,120
Speaker 1: to rock the boat too much because they're part of

1562
01:29:27,120 --> 01:29:29,559
Speaker 1: the system. Yeah. And the only thing that gave him

1563
01:29:29,560 --> 01:29:31,639
Speaker 1: little pause was isis because it was a black hole.

1564
01:29:31,680 --> 01:29:33,439
Speaker 1: It's like an ink blot in a system. Is It

1565
01:29:33,479 --> 01:29:36,320
Speaker 1: wasn't part of this big financial network. It was like

1566
01:29:36,439 --> 01:29:42,360
Speaker 1: spreading this kind of parallel system that was disconnecting dark wet. Yeah.

1567
01:29:42,560 --> 01:29:47,720
Speaker 1: It that thing scared him a bit. But you know,

1568
01:29:47,760 --> 01:29:49,840
Speaker 1: so black Rock is now like pushing on the on

1569
01:29:49,920 --> 01:29:52,960
Speaker 1: the gun front, the gun control front, and we're gonna

1570
01:29:52,960 --> 01:29:55,040
Speaker 1: see a lot of companies start to move in this direction.

1571
01:29:55,160 --> 01:29:59,360
Speaker 1: Is you know, they're responding to that that consensus morality

1572
01:29:59,400 --> 01:30:02,959
Speaker 1: that's developed. They're becoming partners in that, and they're enforcing

1573
01:30:03,000 --> 01:30:07,440
Speaker 1: it by uh, you know, reducing investments in gun companies.

1574
01:30:07,920 --> 01:30:11,639
Speaker 1: And they're putting pressure on them to modify what they sell.

1575
01:30:13,000 --> 01:30:16,240
Speaker 1: UM if they're retailers or uh, you know, producers, and

1576
01:30:16,360 --> 01:30:19,439
Speaker 1: here's the things that you should make and shouldn't make, UM,

1577
01:30:19,520 --> 01:30:21,519
Speaker 1: and eventually, you know, that gets to a point where

1578
01:30:21,920 --> 01:30:24,760
Speaker 1: I think it's possible to imagine a scenario where you

1579
01:30:24,760 --> 01:30:28,920
Speaker 1: get to a point where, um, if you own a weapon,

1580
01:30:31,080 --> 01:30:33,640
Speaker 1: it's going to be tough in large parts of the

1581
01:30:33,680 --> 01:30:36,519
Speaker 1: country to get a job or do do certain things.

1582
01:30:36,960 --> 01:30:40,519
Speaker 1: But kind of social shaming. Because of social shaming, and

1583
01:30:40,560 --> 01:30:43,240
Speaker 1: I know people already who who who won't let their

1584
01:30:43,280 --> 01:30:47,600
Speaker 1: kids go play at a house that has a gun unbelievable.

1585
01:30:47,800 --> 01:30:49,920
Speaker 1: Well they make it, they asked the question. And if that,

1586
01:30:50,240 --> 01:30:52,920
Speaker 1: if you're if you're listed as a person with who

1587
01:30:52,920 --> 01:30:58,200
Speaker 1: owns a gun, then that could make you unfit to

1588
01:30:58,240 --> 01:31:01,959
Speaker 1: go to the p t A. This is extremely nineteen

1589
01:31:02,000 --> 01:31:04,599
Speaker 1: eighty for any of those Well, I mean we're already

1590
01:31:04,600 --> 01:31:08,320
Speaker 1: seeing it with it with the division with Donald Trump,

1591
01:31:08,439 --> 01:31:11,000
Speaker 1: because I mean people will be like, oh, your husband

1592
01:31:11,080 --> 01:31:13,200
Speaker 1: voted for Donald Trump. Why don't you divorce him. He's

1593
01:31:13,200 --> 01:31:15,799
Speaker 1: a horrible person. You're like, well, it is not necessarily

1594
01:31:15,800 --> 01:31:17,840
Speaker 1: a horrible person. He's like everyone else in America. He

1595
01:31:17,880 --> 01:31:19,560
Speaker 1: looked at a ballot that had two choices on it

1596
01:31:19,560 --> 01:31:23,439
Speaker 1: and he picked one. Oh, it definitely, it definitely hurts

1597
01:31:23,439 --> 01:31:25,400
Speaker 1: you at work. I mean, my son was works in

1598
01:31:25,439 --> 01:31:30,120
Speaker 1: New York. He's a software developer, and um you saw that.

1599
01:31:30,200 --> 01:31:32,519
Speaker 1: You know, there was this one young guy that who

1600
01:31:32,560 --> 01:31:35,160
Speaker 1: was a great developers, a great guy, very nice to everybody,

1601
01:31:35,160 --> 01:31:37,920
Speaker 1: but they was identified as a Trump supporter. Yikes. I

1602
01:31:37,960 --> 01:31:41,320
Speaker 1: saw people get Crafford where I worked, man um where

1603
01:31:41,320 --> 01:31:44,000
Speaker 1: where I worked, Like the next day in the women's bathroom,

1604
01:31:44,040 --> 01:31:46,120
Speaker 1: I found out because they put it up on social media.

1605
01:31:46,400 --> 01:31:49,800
Speaker 1: They created like a shrine to Hillary on the mirror

1606
01:31:50,200 --> 01:31:52,559
Speaker 1: and and it had like all of these you know,

1607
01:31:52,800 --> 01:31:56,360
Speaker 1: women's empowerment things. It pictures of Hillary Clinton. And the

1608
01:31:56,400 --> 01:31:58,879
Speaker 1: only reason got taken down is there were a handful

1609
01:31:58,960 --> 01:32:01,280
Speaker 1: of female Trump's orders there that were like I'm not

1610
01:32:01,360 --> 01:32:04,320
Speaker 1: okay with this. What happened? What happened to the guy

1611
01:32:04,320 --> 01:32:08,160
Speaker 1: in your son's office? Well, the good portion of the

1612
01:32:08,200 --> 01:32:11,280
Speaker 1: office didn't want to work with that. We won't work

1613
01:32:11,280 --> 01:32:16,040
Speaker 1: on projects with him. Wow, unbelievable ostracizing. Yeah, you had

1614
01:32:16,040 --> 01:32:18,919
Speaker 1: to go do something else. There really wasn't any if

1615
01:32:19,040 --> 01:32:20,639
Speaker 1: no one's going to work with you, and then it's

1616
01:32:20,680 --> 01:32:23,479
Speaker 1: like and then you could argue the opposite saying you know, hey,

1617
01:32:23,479 --> 01:32:26,080
Speaker 1: he's one of the pests. I mean, very very personable,

1618
01:32:26,280 --> 01:32:28,880
Speaker 1: wouldn't say a negative thing versus you know, other people

1619
01:32:28,920 --> 01:32:32,280
Speaker 1: who are really nasty. Yeah, yeah, I didn't have that

1620
01:32:32,280 --> 01:32:35,280
Speaker 1: political well. I mean, meanwhile, you can have people like that,

1621
01:32:35,360 --> 01:32:38,360
Speaker 1: like the Attorney General of ours, who you know is

1622
01:32:38,439 --> 01:32:41,200
Speaker 1: very open. Me too, I'm on your side, girls, But

1623
01:32:41,280 --> 01:32:47,599
Speaker 1: in reality, you know, it's monster very different. Yeah. You know,

1624
01:32:47,960 --> 01:32:51,120
Speaker 1: it's important to remember that the US is has a

1625
01:32:51,240 --> 01:32:54,080
Speaker 1: very puritanical streak. I mean, you look at me and

1626
01:32:54,160 --> 01:32:57,880
Speaker 1: look at the prohibition. Yeah, I mean there's a reason,

1627
01:32:57,920 --> 01:32:59,720
Speaker 1: I guess. I guess there was a good reason why

1628
01:32:59,760 --> 01:33:02,240
Speaker 1: we had prohibition because Americans drank like four times more

1629
01:33:02,280 --> 01:33:05,560
Speaker 1: than any other country in the world up until prohibition.

1630
01:33:05,600 --> 01:33:08,720
Speaker 1: I mean, we were we were just pickled. I mean,

1631
01:33:08,720 --> 01:33:10,640
Speaker 1: I can't believe the amount of hard alcohol we used

1632
01:33:10,640 --> 01:33:16,360
Speaker 1: to drink relative to everybody else. And you know what

1633
01:33:16,400 --> 01:33:20,400
Speaker 1: other countries could shut down alcohol use? Well, we also,

1634
01:33:20,920 --> 01:33:25,160
Speaker 1: I mean, we expect moral purity, I feel like from people,

1635
01:33:25,320 --> 01:33:27,879
Speaker 1: you know, especially in how we build up our heroes

1636
01:33:27,960 --> 01:33:30,680
Speaker 1: and then we like to tear them down. It's like,

1637
01:33:31,040 --> 01:33:34,720
Speaker 1: I mean, no, nobody is a saint. Yeah, it's a

1638
01:33:36,200 --> 01:33:39,080
Speaker 1: But we're in this kind of uncharted territory where Trump

1639
01:33:39,080 --> 01:33:42,200
Speaker 1: broke all those rules. So none of that old shamming worked,

1640
01:33:43,200 --> 01:33:45,640
Speaker 1: and you know that kind of hyper reaction to that,

1641
01:33:45,720 --> 01:33:48,360
Speaker 1: this new kind of puritan is m This new moral

1642
01:33:48,439 --> 01:33:54,160
Speaker 1: network has emerged, this consensus morality to kind of to

1643
01:33:54,160 --> 01:33:58,920
Speaker 1: to refashion you know, this public morality in a way

1644
01:33:58,960 --> 01:34:02,160
Speaker 1: that they can in a post Trump world. And I

1645
01:34:02,240 --> 01:34:05,800
Speaker 1: saw you had written something u back on the gun

1646
01:34:05,880 --> 01:34:08,599
Speaker 1: issue that I thought was interesting saying that what you're

1647
01:34:08,600 --> 01:34:12,879
Speaker 1: seeing is these mega corporations, these transnational corporations, are stepping

1648
01:34:12,920 --> 01:34:16,479
Speaker 1: in to fill a perceived void and governance. They're seeing

1649
01:34:16,479 --> 01:34:19,640
Speaker 1: that our government isn't taking action that at least a

1650
01:34:19,720 --> 01:34:24,040
Speaker 1: large portion of Americans want some sort of action. Um,

1651
01:34:24,080 --> 01:34:28,040
Speaker 1: and so you're seeing a corporation and unelected corporations step

1652
01:34:28,080 --> 01:34:32,800
Speaker 1: into that that void. Yeah, that's it's all kind of

1653
01:34:33,120 --> 01:34:35,760
Speaker 1: tied to that whole post West family and you know,

1654
01:34:35,800 --> 01:34:40,160
Speaker 1: hollowing out of the nation state. I mean, look, there

1655
01:34:40,160 --> 01:34:42,200
Speaker 1: was a guy, got Philip Bobbitt wrote a book Shield

1656
01:34:42,200 --> 01:34:44,519
Speaker 1: of Achilles back in two thousand and one or so,

1657
01:34:44,920 --> 01:34:47,599
Speaker 1: and uh, it was like very popular at the time,

1658
01:34:47,600 --> 01:34:49,160
Speaker 1: and he said, we're moving from a nation state to

1659
01:34:49,200 --> 01:34:52,599
Speaker 1: a market state. And the idea is a nation state

1660
01:34:52,640 --> 01:34:55,559
Speaker 1: has borders and it has. You know, it provides a

1661
01:34:55,600 --> 01:34:57,920
Speaker 1: promise to people that will protect you and will provide

1662
01:34:57,920 --> 01:35:04,040
Speaker 1: you economic advancement. And what we saw with globalization that

1663
01:35:04,160 --> 01:35:06,120
Speaker 1: is that we moved towards something called the market state,

1664
01:35:06,160 --> 01:35:10,400
Speaker 1: which market states like it doesn't say it's going to

1665
01:35:10,479 --> 01:35:13,519
Speaker 1: protect you per se. It's gonna give you some level

1666
01:35:13,560 --> 01:35:16,280
Speaker 1: of protection, but the most the thing it really provides

1667
01:35:16,280 --> 01:35:21,840
Speaker 1: you is you know, opportunity. And you know it does

1668
01:35:21,880 --> 01:35:25,440
Speaker 1: that by lowering barriers, lowering barriers to you know, immigration,

1669
01:35:26,000 --> 01:35:31,639
Speaker 1: lowing barriers to multi culture, cultural barriers, gender barriers, all

1670
01:35:31,680 --> 01:35:35,080
Speaker 1: the all the barriers that were up are wiped out

1671
01:35:35,160 --> 01:35:40,440
Speaker 1: and you're now directly connected to the world. Wow. And

1672
01:35:40,479 --> 01:35:45,559
Speaker 1: we're in that kind of market state situation now, and um,

1673
01:35:45,600 --> 01:35:47,280
Speaker 1: you know, a good portion of people are saying, wait

1674
01:35:47,280 --> 01:35:53,280
Speaker 1: a second, h We liked a few barriers, we liked

1675
01:35:53,280 --> 01:35:56,080
Speaker 1: to some level of you know, social safety nets, and

1676
01:35:56,160 --> 01:35:59,559
Speaker 1: we liked certain ethical and moral behavior you know by

1677
01:35:59,560 --> 01:36:05,320
Speaker 1: our um establishment elites, and this this new market state

1678
01:36:05,360 --> 01:36:08,559
Speaker 1: doesn't have that. It's like, it's it's hollow, I think.

1679
01:36:08,600 --> 01:36:10,920
Speaker 1: I mean it's the premise of globalization is that every

1680
01:36:11,000 --> 01:36:15,120
Speaker 1: human being is in competition with every other human being. Globally. Yeah,

1681
01:36:15,160 --> 01:36:20,920
Speaker 1: but in a market state, you're just you're directly in competition.

1682
01:36:20,920 --> 01:36:24,840
Speaker 1: There's no help from government. The state. Yeah, the state

1683
01:36:24,920 --> 01:36:28,040
Speaker 1: is just making that ability to compete, the ability to

1684
01:36:28,040 --> 01:36:33,160
Speaker 1: get that information easy and without any barrier to it.

1685
01:36:33,600 --> 01:36:36,240
Speaker 1: And you know that allows a lot of bad behavior

1686
01:36:36,280 --> 01:36:39,439
Speaker 1: at the the corporate level and the elite level, and um,

1687
01:36:39,479 --> 01:36:43,639
Speaker 1: it makes government very ineffective. It gets less and less

1688
01:36:43,680 --> 01:36:48,040
Speaker 1: capable of actually undertaking anything, loses control of its borders,

1689
01:36:48,040 --> 01:36:50,880
Speaker 1: it loses controls of his of his people flow, it

1690
01:36:50,920 --> 01:36:53,720
Speaker 1: loses control of its finances, and it loses control of

1691
01:36:53,760 --> 01:36:59,519
Speaker 1: its economy. Trade. Uh obviously you know, control of the information, throw,

1692
01:37:00,080 --> 01:37:03,640
Speaker 1: control of the media. It all all the things that

1693
01:37:03,800 --> 01:37:06,880
Speaker 1: used to you know, prop up the nation state disappear

1694
01:37:07,080 --> 01:37:11,439
Speaker 1: or diminished substantially. Well, I guess to kind of finish

1695
01:37:11,479 --> 01:37:16,440
Speaker 1: off this interview, which is pretty wide ranging but fascinating. UM,

1696
01:37:16,479 --> 01:37:19,160
Speaker 1: I know you've done some work on resiliency and things

1697
01:37:19,200 --> 01:37:20,559
Speaker 1: like this, and I just want to kind of pick

1698
01:37:20,560 --> 01:37:24,840
Speaker 1: your brain your current thoughts about potential models that might

1699
01:37:24,880 --> 01:37:28,680
Speaker 1: work for us in the future. Um, some solutions. I

1700
01:37:28,720 --> 01:37:31,040
Speaker 1: mean there probably is no like silver bullet, of course,

1701
01:37:31,120 --> 01:37:35,480
Speaker 1: but um, some potential models for how the future economy,

1702
01:37:35,640 --> 01:37:38,200
Speaker 1: future governance, and I guess what it all comes down

1703
01:37:38,200 --> 01:37:40,559
Speaker 1: to is how we relate to one one another as

1704
01:37:40,640 --> 01:37:44,559
Speaker 1: human beings. Um, how how could you potentially see that

1705
01:37:44,680 --> 01:37:50,040
Speaker 1: functioning in the future. Well, there's um, you know the

1706
01:37:50,080 --> 01:37:53,360
Speaker 1: thing I got into, you know, after the financial crisis,

1707
01:37:53,439 --> 01:37:57,880
Speaker 1: this idea of you know, decentralized resilience that you you

1708
01:37:58,000 --> 01:38:01,839
Speaker 1: produce more locally, you have more local control, you connect

1709
01:38:01,880 --> 01:38:04,720
Speaker 1: with the bigger system on your own terms instead of

1710
01:38:05,040 --> 01:38:09,440
Speaker 1: having the terms dictated to you because of your dependence.

1711
01:38:10,360 --> 01:38:12,639
Speaker 1: So you produce more energy, and you produce more food,

1712
01:38:12,680 --> 01:38:16,760
Speaker 1: and you uh, you'd have local communities and networks that

1713
01:38:16,800 --> 01:38:19,519
Speaker 1: would protect you and sustain you if things broke down.

1714
01:38:20,880 --> 01:38:23,639
Speaker 1: And that made sense because we saw that the big

1715
01:38:23,760 --> 01:38:29,160
Speaker 1: global system it almost yeah, and that you know, it's

1716
01:38:29,240 --> 01:38:31,559
Speaker 1: very easy now to you know, you break one thing

1717
01:38:31,600 --> 01:38:36,919
Speaker 1: and in one piece of the infrastructure, global infrastructure, and

1718
01:38:36,560 --> 01:38:40,640
Speaker 1: it generates cascades of failure that go everywhere, and they

1719
01:38:40,680 --> 01:38:44,600
Speaker 1: amplify and and things get worse and worse. H and

1720
01:38:44,640 --> 01:38:46,439
Speaker 1: things break down for quite a long time. You could

1721
01:38:46,479 --> 01:38:50,519
Speaker 1: end up without power and without UH supplies for weeks

1722
01:38:50,520 --> 01:38:55,479
Speaker 1: at a time. Um or if you're like Puerto Rico.

1723
01:38:55,520 --> 01:38:57,320
Speaker 1: If you're outside of this kind of golden circle of

1724
01:38:57,360 --> 01:39:00,720
Speaker 1: people who get the kind of high end support, uh,

1725
01:39:00,960 --> 01:39:04,120
Speaker 1: you'll be short change. You won't even get any of that.

1726
01:39:04,479 --> 01:39:06,360
Speaker 1: Then you're on your own for once. Things break for

1727
01:39:06,400 --> 01:39:11,080
Speaker 1: a lot longer um. And you know, there's lots of

1728
01:39:11,080 --> 01:39:13,040
Speaker 1: cool stuff you can do at the individual level to

1729
01:39:13,080 --> 01:39:16,400
Speaker 1: make your house more productive. You know, I put in

1730
01:39:16,439 --> 01:39:19,760
Speaker 1: a generator, for instance. It allowed me to you know,

1731
01:39:19,760 --> 01:39:24,519
Speaker 1: when I we lost power for two three days, was

1732
01:39:24,560 --> 01:39:27,200
Speaker 1: an on it not entity for me. It didn't it

1733
01:39:27,200 --> 01:39:30,000
Speaker 1: didn't phaze me. Within five seconds, I'm sorry about the dogs.

1734
01:39:30,240 --> 01:39:33,439
Speaker 1: So then five seconds the the generators on and it

1735
01:39:33,520 --> 01:39:37,840
Speaker 1: was a whole house generator and you know, uh, it

1736
01:39:37,880 --> 01:39:40,600
Speaker 1: seemed like just a normal day. Um. And then it

1737
01:39:40,680 --> 01:39:43,439
Speaker 1: provided you made made it possible for me to provide

1738
01:39:44,280 --> 01:39:47,639
Speaker 1: you know, recharging and hot showers to anyone else who

1739
01:39:47,640 --> 01:39:51,080
Speaker 1: needed to in my neighborhood who didn't have the the generator.

1740
01:39:51,200 --> 01:39:57,680
Speaker 1: So made everyone's life better. Um. But you know, that

1741
01:39:57,800 --> 01:40:03,120
Speaker 1: kind of resilience may not work, um, particularly well if

1742
01:40:03,160 --> 01:40:08,680
Speaker 1: there's kind of civil strife or violent civil strife that

1743
01:40:08,800 --> 01:40:13,280
Speaker 1: becomes an entirely different beast and how that plays out

1744
01:40:13,400 --> 01:40:19,200
Speaker 1: is you know, in this kind of modern environment is

1745
01:40:19,840 --> 01:40:21,920
Speaker 1: a programs. I mean what we've seen is that it

1746
01:40:21,960 --> 01:40:25,519
Speaker 1: gets everything falls apart. There isn't you know, there's dozens

1747
01:40:25,560 --> 01:40:28,920
Speaker 1: of groups and their violence everywhere, and no one can

1748
01:40:28,960 --> 01:40:32,640
Speaker 1: agree on anything, and um, the trocities just mount and

1749
01:40:32,720 --> 01:40:36,439
Speaker 1: things break down, and um, you don't have time to

1750
01:40:36,479 --> 01:40:39,840
Speaker 1: actually plant things, and you won't get the you know,

1751
01:40:39,880 --> 01:40:42,000
Speaker 1: any kind of real benefit from the kind of local

1752
01:40:42,040 --> 01:40:45,120
Speaker 1: resilience that you would have if you were focused on

1753
01:40:45,240 --> 01:40:48,479
Speaker 1: kind of systems. So we are going to have to

1754
01:40:48,520 --> 01:40:51,639
Speaker 1: find some sort of renewed social contract and some shape

1755
01:40:51,720 --> 01:40:56,360
Speaker 1: or form. Yeah. That that that's so exactly. So the

1756
01:40:56,360 --> 01:40:58,639
Speaker 1: way we get through this is to find some new

1757
01:40:58,720 --> 01:41:03,519
Speaker 1: source effective kinship. Is there something that unites us, connects us.

1758
01:41:04,479 --> 01:41:08,960
Speaker 1: That so when you interact with somebody, uh, they're not

1759
01:41:09,040 --> 01:41:11,479
Speaker 1: an enemy, they're not They're not somebody to you know,

1760
01:41:11,680 --> 01:41:14,120
Speaker 1: if you transact with them, you're not trying to you know,

1761
01:41:15,560 --> 01:41:18,160
Speaker 1: get one over on them and and they do damage

1762
01:41:18,200 --> 01:41:21,200
Speaker 1: to them. Um that you can trust people when you

1763
01:41:21,240 --> 01:41:24,400
Speaker 1: see them implicitly because they're part of this larger group.

1764
01:41:24,760 --> 01:41:26,719
Speaker 1: And factive kinship is different than the kind of blood

1765
01:41:26,800 --> 01:41:29,280
Speaker 1: kinship that we've had, you know, in the initial clans

1766
01:41:29,280 --> 01:41:31,920
Speaker 1: and stuff. This is this idea that it's expansive. It's

1767
01:41:31,960 --> 01:41:34,840
Speaker 1: like anyone who follows these rules and goes through these

1768
01:41:34,920 --> 01:41:38,600
Speaker 1: rituals and believes in this narrative can join, you know.

1769
01:41:38,720 --> 01:41:41,880
Speaker 1: And and you know, that's the same thing that just

1770
01:41:42,200 --> 01:41:45,080
Speaker 1: I mean, when modern humans came out of Africa and

1771
01:41:45,479 --> 01:41:50,360
Speaker 1: ran into the Neanderthals, Neanderthals were clannish at best and

1772
01:41:50,560 --> 01:41:53,960
Speaker 1: families that you know, expanded families that at worst, and

1773
01:41:54,200 --> 01:41:57,479
Speaker 1: they were you know, real kid I mean, and they

1774
01:41:57,479 --> 01:42:00,200
Speaker 1: were didn't have this kind of stored information in the

1775
01:42:00,240 --> 01:42:03,400
Speaker 1: social structure, and they didn't they couldn't expand beyond that

1776
01:42:03,479 --> 01:42:07,200
Speaker 1: you know that relate you know that DNA relationship um,

1777
01:42:07,240 --> 01:42:09,760
Speaker 1: and it limited them. And here they were coming up

1778
01:42:09,800 --> 01:42:17,160
Speaker 1: against tribes of people, were multiple families that were not

1779
01:42:17,280 --> 01:42:22,599
Speaker 1: related in the traditional sense um, and that they believed

1780
01:42:22,600 --> 01:42:26,639
Speaker 1: in the narrative. They saw a kinship in the narrative

1781
01:42:26,680 --> 01:42:29,200
Speaker 1: and through the rituals, and that the narrative that told

1782
01:42:29,240 --> 01:42:33,400
Speaker 1: them that they were special, uh, that they it was

1783
01:42:33,439 --> 01:42:36,400
Speaker 1: a reason why they worked together and they joined together,

1784
01:42:36,680 --> 01:42:40,439
Speaker 1: and that they were better off together than than apart um.

1785
01:42:40,800 --> 01:42:43,920
Speaker 1: We have to find that. Yes, I hope, so, I

1786
01:42:43,920 --> 01:42:46,720
Speaker 1: hope some people wake up to that idea. I don't

1787
01:42:46,720 --> 01:42:48,320
Speaker 1: know what it is. I mean, I don't know anything.

1788
01:42:48,479 --> 01:42:49,800
Speaker 1: You know, I looked at the global level and I

1789
01:42:49,800 --> 01:42:53,000
Speaker 1: didn't see anything. I mean, there isn't. I mean, those

1790
01:42:53,360 --> 01:42:56,240
Speaker 1: those ideas haven't been invented yet. Yeah. If you look

1791
01:42:56,240 --> 01:42:59,320
Speaker 1: at the environmental narrative, we're a plague in the world,

1792
01:42:59,439 --> 01:43:02,800
Speaker 1: we're destroying. If you look at the commercial kind of

1793
01:43:02,880 --> 01:43:06,360
Speaker 1: corporate world, we're exploiting everybody and making them work for

1794
01:43:06,600 --> 01:43:09,600
Speaker 1: Pittan's and we're concentrating on all the income. If you

1795
01:43:09,600 --> 01:43:12,080
Speaker 1: look at the national level, what's left of the nation state,

1796
01:43:12,080 --> 01:43:15,880
Speaker 1: it's all you know, colonial exploitation and and uh, you

1797
01:43:15,920 --> 01:43:20,439
Speaker 1: know wars, and you know tyranny's and the like. So

1798
01:43:20,560 --> 01:43:24,160
Speaker 1: I don't I don't know of any kind of cohesive

1799
01:43:24,760 --> 01:43:27,400
Speaker 1: global narrative. I don't know what could replace what we're seeing,

1800
01:43:27,439 --> 01:43:29,240
Speaker 1: you know, seeing with the decline in the nation state.

1801
01:43:29,400 --> 01:43:32,479
Speaker 1: But we have to have something, we have to have

1802
01:43:32,560 --> 01:43:38,280
Speaker 1: something interesting. Well, John, I think we've probably taken up

1803
01:43:38,360 --> 01:43:41,559
Speaker 1: enough of your time today. We've also covered a ton

1804
01:43:41,600 --> 01:43:44,519
Speaker 1: of different topics here, and you know, it's hard to

1805
01:43:45,120 --> 01:43:47,920
Speaker 1: when you're covering such broad concepts hard to dig down

1806
01:43:47,920 --> 01:43:49,960
Speaker 1: into it, but I think we really I mean, I

1807
01:43:50,080 --> 01:43:52,240
Speaker 1: heard you articulate a number of different ideas that I

1808
01:43:52,320 --> 01:43:55,160
Speaker 1: haven't really thought of. I hadn't put I didn't connected

1809
01:43:55,200 --> 01:43:56,640
Speaker 1: the dots in that way. So I mean, this has

1810
01:43:56,680 --> 01:43:59,080
Speaker 1: been very helpful and I think our listeners will really

1811
01:43:59,120 --> 01:44:02,200
Speaker 1: enjoy it as well. Oh cool, it's been a lot

1812
01:44:02,200 --> 01:44:06,080
Speaker 1: of fun, and thanks for having me on you know, UM.

1813
01:44:06,080 --> 01:44:07,439
Speaker 1: You know what I do is I try to come

1814
01:44:07,479 --> 01:44:09,360
Speaker 1: up with frameworks with the reports in the way I

1815
01:44:09,400 --> 01:44:12,080
Speaker 1: think UM and the frameworks help you just deal with

1816
01:44:12,120 --> 01:44:15,000
Speaker 1: the onslaught of new information, and I kind of categorize it.

1817
01:44:15,920 --> 01:44:18,760
Speaker 1: If your decision maker unfreezes you, you know, sometimes when

1818
01:44:18,800 --> 01:44:22,080
Speaker 1: things change too fast, you're you're frozen. You're you're unable

1819
01:44:22,120 --> 01:44:24,479
Speaker 1: to act, You're unable to make decisions. And if you

1820
01:44:24,479 --> 01:44:25,960
Speaker 1: have a framework, you can you can get through. And

1821
01:44:26,000 --> 01:44:30,519
Speaker 1: the framework doesn't have to be corrects mostly correct. It

1822
01:44:30,520 --> 01:44:32,800
Speaker 1: allows you, you know, allows it frees you up to

1823
01:44:32,840 --> 01:44:35,160
Speaker 1: make decisions that you have to make and and makes

1824
01:44:35,200 --> 01:44:37,559
Speaker 1: you feel more confident about moving forward in the world.

1825
01:44:37,800 --> 01:44:40,200
Speaker 1: And that's what I try to do. I also, I

1826
01:44:40,240 --> 01:44:43,519
Speaker 1: didn't want to interrupt John's train of thought a while

1827
01:44:43,600 --> 01:44:45,160
Speaker 1: back in the interview when he said it, but I'm

1828
01:44:45,160 --> 01:44:47,880
Speaker 1: pretty sure you're the first person on the podcast to

1829
01:44:48,000 --> 01:44:51,720
Speaker 1: use the word mamatic. And it went totally above my

1830
01:44:51,760 --> 01:44:53,400
Speaker 1: head at first, and then I had to process it,

1831
01:44:53,439 --> 01:44:56,200
Speaker 1: and then I was like, oh, meme in there, maematic,

1832
01:44:56,600 --> 01:44:59,280
Speaker 1: I'm going to start using that word. So thank you

1833
01:44:59,320 --> 01:45:03,240
Speaker 1: for expanding my vocabulary. Well, yeah, this is a lot

1834
01:45:03,240 --> 01:45:07,120
Speaker 1: of fun. Thanks great, and once again at John Rob

1835
01:45:07,240 --> 01:45:09,639
Speaker 1: on Twitter, which, as you can tell from this interview

1836
01:45:09,680 --> 01:45:11,880
Speaker 1: is definitely someone you want to follow on Twitter. And

1837
01:45:11,960 --> 01:45:15,599
Speaker 1: also his book it's called Brave New War right. Yeah,

1838
01:45:15,640 --> 01:45:17,479
Speaker 1: I read I read it, but it was a while back,

1839
01:45:17,600 --> 01:45:22,000
Speaker 1: but it was definitely an eye opener um, mostly about insurgency. Um,

1840
01:45:22,080 --> 01:45:25,240
Speaker 1: so people should go read that. Yeah, and then um,

1841
01:45:25,360 --> 01:45:27,920
Speaker 1: then my report is on Patreon is ghen rob or

1842
01:45:28,040 --> 01:45:31,000
Speaker 1: Patreon slash genre. Yeah I saw that as well, So

1843
01:45:31,040 --> 01:45:33,160
Speaker 1: you have a Patreon and so check that out, check

1844
01:45:33,160 --> 01:45:36,160
Speaker 1: out the Global Guerrillas Report, And once again it's John

1845
01:45:36,880 --> 01:45:40,160
Speaker 1: Rob with two bees. So at John Rob R O

1846
01:45:40,320 --> 01:45:44,160
Speaker 1: B B on Twitter and on Patreon, and uh, yeah,

1847
01:45:44,160 --> 01:45:46,439
Speaker 1: we really appreciate you coming on. This has been a

1848
01:45:46,479 --> 01:45:50,240
Speaker 1: great episode, Oh my pleasure, thanks guys. Yeah, and at

1849
01:45:50,280 --> 01:45:51,920
Speaker 1: some point I should say, I'd love to have you

1850
01:45:51,960 --> 01:45:54,960
Speaker 1: back on to talk about your Air Force days and

1851
01:45:55,000 --> 01:45:58,160
Speaker 1: Special operations. I think that could be a whole other episode.

1852
01:45:58,360 --> 01:46:00,920
Speaker 1: Oh yeah, our audience is definitely interested in that stuff.

1853
01:46:01,400 --> 01:46:04,880
Speaker 1: All right, pretty cool? All right? Thanks John, all right,

1854
01:46:04,920 --> 01:46:08,439
Speaker 1: take care, guys, to my pleasure. But thanks again to

1855
01:46:08,560 --> 01:46:12,040
Speaker 1: John rob for coming on. Excellent UM interview there. I

1856
01:46:12,080 --> 01:46:14,479
Speaker 1: think we went really in depth. And no, we didn't

1857
01:46:14,479 --> 01:46:16,960
Speaker 1: get into any of his special operations background, and I'm

1858
01:46:16,960 --> 01:46:18,760
Speaker 1: sure a lot of you would have liked to have

1859
01:46:18,800 --> 01:46:20,800
Speaker 1: heard that. So I think that a part two is

1860
01:46:20,840 --> 01:46:22,680
Speaker 1: in order at some point, and if you want to

1861
01:46:22,680 --> 01:46:25,719
Speaker 1: hear that, let us know at Software Radio on Twitter

1862
01:46:26,240 --> 01:46:29,799
Speaker 1: UM and then individually at Ian Scotto at Jack Murphy

1863
01:46:30,000 --> 01:46:33,439
Speaker 1: r g R on Twitter. Of course, there's only one

1864
01:46:33,520 --> 01:46:37,240
Speaker 1: club out there with gear handpicked by special operations military

1865
01:46:37,320 --> 01:46:41,599
Speaker 1: veterans from several branches, and that, of course, is Create Club.

1866
01:46:41,920 --> 01:46:44,360
Speaker 1: Past items we've had in our premium crates have been

1867
01:46:44,400 --> 01:46:48,440
Speaker 1: a survival belt which included a stainless steel knife, firestarter,

1868
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Speaker 1: bottle opener, and an LED flashlight. Great item, I know

1869
01:46:52,360 --> 01:46:54,880
Speaker 1: both of us have it. UM also in a premium

1870
01:46:54,920 --> 01:46:57,360
Speaker 1: Create we had a ballistic shield insert for your backpack

1871
01:46:57,439 --> 01:47:01,479
Speaker 1: made by cry Precision. Creatu is really stepping it up

1872
01:47:01,560 --> 01:47:04,960
Speaker 1: right now though, as t and progresses, by putting out

1873
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Speaker 1: custom products that you're not going to find anywhere else.

1874
01:47:08,479 --> 01:47:11,200
Speaker 1: We have different tiers of membership depending on how prepared

1875
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Speaker 1: you want to be, and gift options are available as well,

1876
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Speaker 1: so if this is something you want to give you know,

1877
01:47:17,000 --> 01:47:19,160
Speaker 1: for example, if you're a female listener to your husband

1878
01:47:19,280 --> 01:47:22,160
Speaker 1: or it's your friend, check it out. It's at Create

1879
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Speaker 1: Club dot us once again, that's great Club dot us

1880
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Speaker 1: to see all of that and all of the different

1881
01:47:28,600 --> 01:47:31,479
Speaker 1: tiers for your dog owners, check this out. You're gonna

1882
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1884
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Speaker 1: your dog each month of healthy treats and training aids.

1885
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1886
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Speaker 1: US sourced products, all natural and they not only promote

1887
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Speaker 1: a healthy diet but also promote being active with your dog.

1888
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Speaker 1: You can see all of that at Kuna dot Dog.

1889
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Speaker 1: That's Kuna dot Dog. It's efficient for you, your dog

1890
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Speaker 1: will appreciate it as well, of course, and that's spelled

1891
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Speaker 1: see U n A dot d O G. We just

1892
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Speaker 1: sent out the first box and people are loving it.

1893
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Speaker 1: We have a multivitamin in there for your dog, a

1894
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Speaker 1: toy for your dog, and uh, it's all just great

1895
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Speaker 1: stuff that they're going to really love and it's going

1896
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Speaker 1: to be helpful to use a dog on her. Also

1897
01:48:18,000 --> 01:48:20,120
Speaker 1: as a reminder for all of those who are listening,

1898
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Speaker 1: for a limited time, you can receive a fifty percent

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Speaker 1: discounted membership to the spec Ops Channel, our channel that

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Speaker 1: offers the most exclusive shows, documentaries and interviews covering the

1901
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Speaker 1: most exciting military content today. The spec Ops channel premier

1902
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Speaker 1: show Training Sell follows former Special Operations Forces as they

1903
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Speaker 1: participate in the most advanced training in the country, everything

1904
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Speaker 1: from shooting schools, defensive driving, jungle and winter warfare, climbing

1905
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Speaker 1: and much more. Again, you can watch this content by

1906
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Speaker 1: subscribing to the spec Ops Channel and that's at spec

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Speaker 1: ops channel dot com and you can take advantage of

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Speaker 1: a limited time offer of fifth deeper cent off your membership.

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Speaker 1: That's only four nine a month and the app is

1910
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Speaker 1: available now for iOS for you iPhone users. Android will

1911
01:49:08,920 --> 01:49:12,720
Speaker 1: be available early next month. I think that wraps it up.

1912
01:49:12,760 --> 01:49:15,760
Speaker 1: We went pretty long here. Um, you know what I'm

1913
01:49:15,760 --> 01:49:17,240
Speaker 1: gonna plug and I have nothing to do with it.

1914
01:49:17,240 --> 01:49:19,839
Speaker 1: I was telling you before. Check out Cobra Kai on YouTube.

1915
01:49:20,000 --> 01:49:23,120
Speaker 1: Its fucking great. I love it, and everybody who's watched

1916
01:49:23,120 --> 01:49:25,680
Speaker 1: it as really enjoyed it. And I'm not, even, like

1917
01:49:25,720 --> 01:49:27,760
Speaker 1: I say on the podcast, pretty often not a big

1918
01:49:27,960 --> 01:49:31,240
Speaker 1: movie or show guy. And on a recent show you

1919
01:49:31,280 --> 01:49:33,200
Speaker 1: were saying how everything is a remake, everything is a

1920
01:49:33,240 --> 01:49:36,200
Speaker 1: reboot now and I would agree, Um, and they're usually

1921
01:49:36,240 --> 01:49:38,519
Speaker 1: you're very poorly done. This is like a reboot that

1922
01:49:38,960 --> 01:49:41,799
Speaker 1: it kept like that classic eighties heel of that original

1923
01:49:41,920 --> 01:49:45,920
Speaker 1: Karate Kid, but updated it to now I'm loving and

1924
01:49:45,960 --> 01:49:48,160
Speaker 1: I'm only two episodes in, but I'm probably gonna watch

1925
01:49:48,400 --> 01:49:51,439
Speaker 1: some more of that when i get home. Yeah. I

1926
01:49:51,520 --> 01:49:53,680
Speaker 1: know this has nothing to do with that, but I'm

1927
01:49:53,680 --> 01:49:55,720
Speaker 1: throwing it out there because it's of interest to me.

1928
01:49:55,840 --> 01:49:58,680
Speaker 1: Then it Well, thanks for checking this out. Um. We

1929
01:49:58,800 --> 01:50:00,600
Speaker 1: got a lot of other great stuff wind up for

1930
01:50:00,720 --> 01:50:10,320
Speaker 1: you where you're the month, and we appreciate office you've

1931
01:50:10,320 --> 01:50:14,439
Speaker 1: been listening to soff rep Radio. New episodes up every

1932
01:50:14,479 --> 01:50:17,880
Speaker 1: Wednesday and Friday for all of the great content. From

1933
01:50:17,880 --> 01:50:21,200
Speaker 1: our veteran journalists. Join us and become a team room

1934
01:50:21,240 --> 01:50:24,840
Speaker 1: member today at soft rep dot com. Follow the show

1935
01:50:24,920 --> 01:50:28,880
Speaker 1: on Instagram and Twitter at soft rep Radio, and be

1936
01:50:29,040 --> 01:50:32,080
Speaker 1: sure to also check out the Power of Thought podcast

1937
01:50:32,520 --> 01:50:37,200
Speaker 1: hosted by Hurricane Group CEO and Navy Seal Sniper instructor

1938
01:50:37,680 --> 01:50:38,599
Speaker 1: Brandon Webb.