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Speaker 1: Welcome to Stuff to Blow your Mind from how Stuffworks

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Speaker 1: dot com. Hey, are welcome to stuff to Blow your Mind.

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Speaker 1: My name is Robert lamp and I'm Christian Seger. You know, Christian.

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Speaker 1: It seems that we should be able to look at

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Speaker 1: where we've been in the past and therefore extrapolate, predict,

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Speaker 1: even simulate where we're going in the future. Right, it does.

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Speaker 1: It does seem that way, And I think that that

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Speaker 1: maybe is a product of like the last century of

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Speaker 1: our uh scientific thinking. Does that make sense? Yeah, well,

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Speaker 1: I mean there's definitely one line in particular that we're

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Speaker 1: that we're often referring to and uh and in generally

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Speaker 1: misquoting I think a lot of the times, and that

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Speaker 1: comes from a philosopher, Georgia Santayana, who said, quote, those

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Speaker 1: who cannot remember the past are condemned to repeat it.

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Speaker 1: That would of course tend to imply, Hey, if you

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Speaker 1: can remember the past, then you can avoid these pitfalls

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Speaker 1: in the future. That there's some uh, there's some system

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Speaker 1: that can be employed that even though we're we're strapped

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Speaker 1: to this linear existence just hurdling through time into the future. Um,

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Speaker 1: if we have some concept of the road that we've traveled,

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Speaker 1: we'll have a better idea about the road to come right. Yeah,

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Speaker 1: and so of bring it back around to our nerdiness. Uh.

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Speaker 1: In our fandom for Stephen King and the newly popular

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Speaker 1: Dark Tower Universe. Uh, there's a quote from King here

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Speaker 1: that he used in the stand under the Guise of

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Speaker 1: Randall flag. Life was such a wheel that no man

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Speaker 1: could stand upon it for long, and it always, at

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Speaker 1: the end came around to the same place again. Uh.

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Speaker 1: This is a terrifying concept though, right, And at the

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Speaker 1: same time it is an idea that seems to fill

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Speaker 1: a lot of people with purpose because they can say, ah,

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Speaker 1: hold on, wait, I've got it figured out, and I

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Speaker 1: can predict what's going to happen next. And in fact,

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Speaker 1: we had a listener right into us about this very idea.

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Speaker 1: Her name is Allison, and she wrote us and said

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Speaker 1: she was wondering if we would do a show about

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Speaker 1: this is something that's been mentioned a lot on the

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Speaker 1: internet lately and apparent eighty year cycle of political social

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Speaker 1: upheaval in our world. And she said she was horrified

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Speaker 1: and intrigued the first time that she heard about it,

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Speaker 1: and so she started looking into this. Uh. And she

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Speaker 1: said that she's heard about the idea in general, but

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Speaker 1: that this the whole like seventy to eighty year cycle

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Speaker 1: as a devastating shake up, whether it's via war, war

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Speaker 1: or turmoil, was kind of new, right, and she wanted

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Speaker 1: to know if we could do some research on it

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Speaker 1: and see what we came up with and provide some

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Speaker 1: perspective on it. And interestingly, because I have also heard

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Speaker 1: about this in the last couple of months, Um, we

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Speaker 1: did the research and it turns out that the one

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Speaker 1: that's making the rounds is not the one that is

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Speaker 1: being academically researched. There's like a little bit of uh

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Speaker 1: confabulation going on here between two different uh specific theories

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Speaker 1: and one is more well, I guess we can describe

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Speaker 1: them as the fifty year theory and the eighty year theory. Yes, yeah, okay, yeah,

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Speaker 1: and these this is this is this is getting into

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Speaker 1: a realm of what is known as cleo dynamics, that

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Speaker 1: is cl i o dynamics. Yeah. So this is a

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Speaker 1: field where scientists are attempting to find meaningful patterns in history.

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Speaker 1: And it was named by a guy named Peter Turch.

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Speaker 1: And we're gonna talk a lot about him today after Cleo,

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Speaker 1: the ancient Greek muse of history. I have been having

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Speaker 1: the hardest time remembering this name trying. You came up

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Speaker 1: with a good idea earlier picture Cleo as miss Cleo

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Speaker 1: the psychic. Uh. The other one I'm thinking is like

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Speaker 1: letters to Cleo Dynamics, Like, I gotta figure out a

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Speaker 1: way to remember this because it's been hard for me.

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Speaker 1: But anyways, there's been a swell of efforts to apply

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Speaker 1: scientific methods to history by identifying in audeling broad social forces.

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Speaker 1: And one argument in favor of this is that historians

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Speaker 1: are too qualitative and that they point to samples of

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Speaker 1: cases from observations that Cleo Dynamics wants to use tools

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Speaker 1: like nonlinear mathematics and simulations that can model the interactions

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Speaker 1: of millions of people at once. Now, I want to

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Speaker 1: be clear about this upfront. It's criticized by traditional historians.

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Speaker 1: They usually believe that there are countless variables interacting within

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Speaker 1: a society that lead to violence and social unrest, and

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Speaker 1: they don't think that there's any one unified theory or

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Speaker 1: general law to history. So so what are we talking

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Speaker 1: about here? Then, Well, we're looking at decades or even

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Speaker 1: century long periods of population expansion, followed by long periods

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Speaker 1: of stagnation and decline price dynamics mirroring population oscillations, strong

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Speaker 1: expansionist phases followed by state failure socio political instead of

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Speaker 1: build pity and territory loss, repeated back and forth swings

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Speaker 1: in demographic, economic, social, and political structures. Uh, just to

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Speaker 1: give you an idea of what what kind of patterns

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Speaker 1: we're talking about here when we're when you're imagining, say

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Speaker 1: the the Cleo dynamics weather person standing in front of

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Speaker 1: green screen, like these are the kind of movements they

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Speaker 1: would be talking about her chart. That's a perfect analogy. Yeah. Now,

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Speaker 1: an example I came across was in the work of

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Speaker 1: two and two individuals, one of whom of which we're

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Speaker 1: going to talk about in greater depth, Peter Turchin and

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Speaker 1: Sergey A. Nevadov, And they have a book titled Secular

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Speaker 1: Cycles in which they looked at England, France, and Russia

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Speaker 1: throughout both the medieval and early modern periods and they

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Speaker 1: closely observed cycles of inequality. So, uh, Nevodov has a

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Speaker 1: great rundown of cleo dynamics and economic inequality as well.

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Speaker 1: In Ian magazine and a couple of other publications. I'll

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Speaker 1: try to include a link to this on the landing

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Speaker 1: page for the episode. But he says that in this case,

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Speaker 1: the cycles break down to this, you have expansion, stagnation, crisis, disintegration,

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Speaker 1: sort of a life cycle of a story arc for

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Speaker 1: for civilization. Right. However, uh Nfidov is quick to point

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Speaker 1: out that we're not talking about rigid clockwork here, So

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Speaker 1: these cycles don't occur in a machine. They occur in

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Speaker 1: a chaotic system in which a great number of variables

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Speaker 1: play apart. So in a way it is it is

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Speaker 1: a lot like the weather. The weather is a system.

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Speaker 1: We know what what's factors influence the movements of atmosphere

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Speaker 1: and weather patterns, but there's so many it's ultimately such

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Speaker 1: a chaotic system it becomes difficult to make um. You know,

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Speaker 1: long term predictions, even short term predictions are are are

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Speaker 1: open to uh to misinterpretation. And does anybody who's checked

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Speaker 1: the weather channel or their weather app on their phone

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Speaker 1: and gone outside and its raining. It's not that a

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Speaker 1: meteorologist doesn't know what they're taught king about. It's that

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Speaker 1: the the system is just that complex and difficult to

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Speaker 1: simulate even with the with our most complicated simulation systems.

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Speaker 1: So the idea here's the human cultures and civilizations. Also

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Speaker 1: that they're bumping up against each other, they're influencing each other.

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Speaker 1: Uh So, there are so many factors that make it

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Speaker 1: complex and it's it's again, it's not as simple as

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Speaker 1: just you know, running a computer versus computer game inside

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Speaker 1: of of a closed system. Still, he maintains that complex

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Speaker 1: interactions do add up to a general rhythm. So if

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Speaker 1: you kind of take a god's eye view of everything,

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Speaker 1: the idea here is that, yes, you will see patterns

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Speaker 1: emerge and then you can extract late that to the future.

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Speaker 1: So Cleo dynamics then is about observing these trends, observing

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Speaker 1: these cycles, this ebb and flow, and then predicting them

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Speaker 1: in the future. And you have a note here about

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Speaker 1: Mercy a eliads book The Terror of History, which I

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Speaker 1: remember reading in grad school. Yeah, and of the Eternal Return,

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Speaker 1: Yeah yeah, he involved in myth studies. Yeah yeah, So

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Speaker 1: he talks about this concept of the terror of history

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Speaker 1: in which humanity has abandoned a cyclical mythic view of

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Speaker 1: time that we used to have in favor of a

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Speaker 1: purely linear existence. We're forced to see history for what

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Speaker 1: it is, a senseless stream of blunders, atrocity, collapsed ideals

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Speaker 1: of fallen states, ruined megaprojects, and just sort of failure

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Speaker 1: in general. Um, it sounds like the greatest setting for

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Speaker 1: a role playing game. Yeah, but not one to live in.

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Speaker 1: It's what it is, legitimately worth thinking about when you're

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Speaker 1: when you're toying with, you know, dungeons and dragons, histories,

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Speaker 1: you know, or thinking about stuff like Game of Thrones. Yeah. Yeah,

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Speaker 1: there's a reason why all of these, like fantasy worlds

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Speaker 1: that are built from the ground up, have ruinous histories

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Speaker 1: to them that that they kind of look back on

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Speaker 1: in wonder. Yeah. So here's a quote from the myth

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Speaker 1: of the Eternal Return. Ileoti says, quote, in our day,

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Speaker 1: when historical pressure no longer allows any escape, how and

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Speaker 1: man tolerate the catastrophes and horrors of history, from collective

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Speaker 1: deportations and massacres to atomic bombings, if beyond them he

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Speaker 1: can glimpse no sign, no transistorical meaning, if they are

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Speaker 1: only the blind play of economic, social, or political forces,

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Speaker 1: or even worse, only the result of the liberties that

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Speaker 1: a minority takes and exercises it directly on the stage

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Speaker 1: of universal history. So Eliade says that for the longest

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Speaker 1: humans were able to place everything within a metahistorical framework.

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Speaker 1: Uh so, yeah, something fell apart because it was the

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Speaker 1: end of a decade an age. It was the punishment

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Speaker 1: of God, et cetera. Now, Cleo dynamics stands in an

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Speaker 1: interesting place by comparison, because they are, in a way

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Speaker 1: attempting to resurrect a cyclical view of history. There they're

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Speaker 1: turning not to divine mechanics, however, or the imagined astrological

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Speaker 1: influence of the spheres. Uh, but rather to a modeling

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Speaker 1: of history sort of fluid dynamics based on cultural evolution,

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Speaker 1: macro sociology, economics, and other factors. Plus in a refreshingly

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Speaker 1: optimistic humanist twist that I really like. It also opens

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Speaker 1: the door for control over those cycles, right Yeah, And

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Speaker 1: I think that's absolutely crucial to keep in mind with

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Speaker 1: all of this. It's not just another version of Oh,

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Speaker 1: humanity is screwed. And here's why. There's the potential for

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Speaker 1: self awareness. Here, there's the potential for change. Right. So,

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Speaker 1: the general methodology that's being used in these studies at

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Speaker 1: least at least church and studies is to focus on

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Speaker 1: four main variables that are measured in several ways, and

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Speaker 1: and Robert you just mentioned many of these. He boils

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Speaker 1: them down pretty quickly to population numbers, social structure, state strength,

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Speaker 1: and political instability. And then he says, the way to

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Speaker 1: measure these is actually through proxies that are connected to

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Speaker 1: these things that you can measure quantitatively. So he looks,

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Speaker 1: for instance, at social structure, He looks at the quantitative

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Speaker 1: data on life expectancy and wealth in a quality, and

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Speaker 1: that's one of his measurement points. So who's this Peter

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Speaker 1: Churching guy that that like has just come out of

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Speaker 1: nowhere with the cleo dynamics At least it seems like that, right,

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Speaker 1: He's actually been doing it for a while. He's an

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Speaker 1: ecologist and evolutionary biologist and a mathematician out of the

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Speaker 1: University of Connecticut and stores he studies population dynamics and

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Speaker 1: takes mathematical techniques that he used to use to track

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Speaker 1: predator pray cycles in forest ecosystems, and then he applies

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Speaker 1: those to human history. Now, Turchen looks at historical records

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Speaker 1: of economic activity, demographic trends, and outbursts of violence in

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Speaker 1: the United States, and he argues history is not just

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Speaker 1: one damn thing after another. His main research questions are essentially,

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Speaker 1: first of all, what general mechanisms explain the collapse of

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Speaker 1: historical empires? And then how did large scale states and

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Speaker 1: empires evolved in the first place. So this is some

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Speaker 1: pretty big heavy stuff when it comes to anthropology. Now,

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Speaker 1: church and first conceived of Cleo dynamics in nineteen seven

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Speaker 1: when he felt that all major ecological questions about population

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Speaker 1: dynamics had been answered, so he turned to that's a

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Speaker 1: direct quote from him. That's not me. I don't I

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Speaker 1: don't know necessarily that they have all been answered. But

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Speaker 1: he turned to history. And actually his father had previously

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Speaker 1: looked into us. His father was Valentine Church and a

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Speaker 1: computer scientist, and he had written dissident writings about the

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Speaker 1: origins of totalitarianism that got him exiled from the Soviet

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Speaker 1: Union in nineteen seventies seven. Now, the younger Church and

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Speaker 1: he recognizes that this kind of search for patterns in history,

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Speaker 1: this is not a new thing, right. Obviously, we're all

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Speaker 1: familiar with the idea of there being a cyclical nature

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Speaker 1: to history. I remember learning about this in like, uh,

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Speaker 1: probably like a junior high history class. Well, I mean

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Speaker 1: it's just basically pattern recognition in history class. Right, Oh,

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Speaker 1: an empire rye is and then it falls, you know,

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Speaker 1: you have you're gonna end up with some sort of

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Speaker 1: horrible emperor ruler and then then there's a revolution that happens.

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Speaker 1: Like you just you just began to recognize the same

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Speaker 1: patterns within these different stories. Yeah, that was the way

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Speaker 1: it was framed to us when I was like whatever,

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Speaker 1: twelve maybe thirteen years old. They're essentially like war happens,

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Speaker 1: then like there's peace, then there's war, then there's peace,

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Speaker 1: then there's war, and they happen in these like they

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Speaker 1: actually were able to this elementary school tape teacher was

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Speaker 1: able to map it out for us, you know. And

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Speaker 1: that's essentially what he's doing, but with just like a

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Speaker 1: broader set of data points, right. And he's really currently

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Speaker 1: focused on coordinating something called the c CHAT Global History

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Speaker 1: Data Bank, And this is a database of history and

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Speaker 1: cultural evolution that is hoped to be used to empirically

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Speaker 1: test out theoretical predictions from Cleo dynamics. So they're essentially

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Speaker 1: housing as much data as they possibly can gather to

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Speaker 1: run these predictive models against. So there are a couple

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Speaker 1: of moments of other Cleo dynamics though too rite and

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Speaker 1: we don't want to confuse Urchin with too many of

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Speaker 1: the other folks that are involved in this. And we

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Speaker 1: haven't even gotten to the actual purported eighty year cycle

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Speaker 1: that is making the rounds right now. What we're really

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Speaker 1: talking about with Urchin is the fifty year and then

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Speaker 1: two hundred year cycles. But uh, there's actually and you

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Speaker 1: and I both found this. There's a peer reviewed journal

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Speaker 1: on Cleo dynamics and it's open access, meaning anybody out

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Speaker 1: there can get get it, and you can share it

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Speaker 1: and reuse it under a Creative Commons attribution. You'll find

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Speaker 1: lots of different articles about cleo dynamic views of history.

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Speaker 1: You try to include a link to that on the

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Speaker 1: landing page for this episode is stuff to about your

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Speaker 1: mind dot com. Yeah, so here's a couple of people.

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Speaker 1: Uh they they have been doing similar work to church In,

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Speaker 1: but they're not, you know, part of his necessary research projects.

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Speaker 1: So you've got Claudio sea Offee Reveala, who is a

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Speaker 1: computer social scientist in Virginia, UH. They're trying to use

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Speaker 1: cleo dynamics by running simulations on computer models. Specifically, his

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Speaker 1: team is looking at the Rift Valley region of East

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Speaker 1: Africa and the effects of modern climate change there. And

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Speaker 1: so they've seen that there was a drought there and

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Speaker 1: then subsequently labor specialization and vulnerability emerged spontaneously. So they

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Speaker 1: hope to be able to predict the flow of refugees

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Speaker 1: and identify potential conflict hot spots in the region using

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Speaker 1: using these Cleo dynamic methods. Another guy, Jack Goldstone, is

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Speaker 1: the director of the Center for Global Policy at George

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Speaker 1: Mason University. He's also a member of the Political Instability

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Speaker 1: Task Force, which is funded by the CIA to forecast

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Speaker 1: events outside of the United States. He's tried finding patterns

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Speaker 1: in past revolutions and he projects that Egypt will actually

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Speaker 1: have a few more years of struggle and another five

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Speaker 1: to ten years of rebuilding its institutions before it can

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Speaker 1: regain stability. Now this is in reference to the Arab

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Speaker 1: Spring Revolution of uh That might be a little bit this.

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Speaker 1: The information here might have been written closer to that

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Speaker 1: date than to our present date. So I take those

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Speaker 1: those numbers with a grain of salt. Goldstone, though, thinks

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Speaker 1: that cleo dynamics is only useful for looking at broad

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Speaker 1: trends and not useful for predicting unique events, so he

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Speaker 1: wanted to be clear about that. I think that's important

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Speaker 1: to note. And when we get into criticism later, you

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Speaker 1: do find that it's not necessarily the situation where people

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Speaker 1: are like cleo dynamics is awesome or Cleo dynamics is

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Speaker 1: is trash. It's a lot a lot of times it's

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Speaker 1: a discussion about to what extent these kinds of exercises

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Speaker 1: are useful or accurate. Right, Yeah. So another person who

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Speaker 1: felt the same way is Herbert Gentis, and this is

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Speaker 1: a retired economist working out of U mass Ammerst, who

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Speaker 1: also doubts that cleo dynamics can be used to predict

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Speaker 1: specific events, but he does think the patterns and causal

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Speaker 1: connections within it can reveal lessons for policymakers. So he's

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Speaker 1: essentially arguing this is something that people who are constructing

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Speaker 1: policy in our government should be paying attention to. And

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Speaker 1: the last person here I have here is Harvey Whitehouse,

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Speaker 1: who is an anthropologist at the University of Oxford, and

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Speaker 1: he oversees the construction of a database on rituals, social structures,

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Speaker 1: and conflict around the globe. Now, he believes this research

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Speaker 1: can complement the approach of Cleo dynamics by shedding light

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Speaker 1: on the triggers of political violence. In his argument, this

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Speaker 1: violence happens when individuals strongly identify with a political group,

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Speaker 1: and that identification is cemented through what he calls rituals.

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Speaker 1: And these can be frightening and painful. And the reason

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Speaker 1: why is the more frightening and painful they are, the

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Speaker 1: stronger the shared memories they create. Are This sounds very

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Speaker 1: familiar to us. We are you know, we're trying to

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Speaker 1: keep this episode evergreen, but we were actually recording this

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Speaker 1: the weekend after the riot events in Charlottesville, Virginia and

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Speaker 1: uh where you know, there were collisions between I guess

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Speaker 1: white nationalist protesters and counter protesters and there was a

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Speaker 1: woman killed by a car that drove into a number

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Speaker 1: of the participants in this. Uh, it's it was super upsetting.

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Speaker 1: It's still super upsetting. And as I'm reading about cleo

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Speaker 1: dynamics and these applications of it, it seems to be

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Speaker 1: like a moment that will obviously join this data set,

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Speaker 1: which sounds sounds somewhat unemotional, right because these are like

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Speaker 1: real people that it's affecting. But it also makes me

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Speaker 1: wonder like, how can this How could could we have

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Speaker 1: predicted events like this? Or can we trace back why

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Speaker 1: events like this are happening? Yeah, exactly, because again, it's

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Speaker 1: it's it's not just about knowing where we're going. It's

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Speaker 1: it's about being able to take control of it, being

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Speaker 1: able to sort of take control of the wheel to

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Speaker 1: a certain extent. Alright, let's take a break, and when

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Speaker 1: we come back, let's jump into this fifty year cycle,

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Speaker 1: this fifty year scale. Alright, we're back. So yeah, So

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Speaker 1: Turchen is actually the one who came up with the

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Speaker 1: fifty year scale, and this is the one that's getting

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Speaker 1: conflated with the eighty year scale that's making the rounds

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Speaker 1: on the internet right now. Uh, And we'll explain all

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Speaker 1: that later, but let's talk about what he actually means

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Speaker 1: with this fifty year scale. So the theory goes, he

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Speaker 1: calls this the father and Son's scale. The theory goes

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Speaker 1: that every fifty years there's a moment of violent upheaval

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Speaker 1: in the United States, and he looks at this as

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Speaker 1: beginning in eighteen seventy with the Civil War, then in

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Speaker 1: nineteen twenty there was violence over labor and race. Then

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Speaker 1: again in nineteen seventy we had the Vietnam War and

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Speaker 1: the Civil rights movement. So he's our you doing that

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Speaker 1: twenty is around when we're going to have our next

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Speaker 1: cycle and basically saying everybody needs to prepare themselves. We're

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Speaker 1: gonna go through another moment of turmoil. You know, I, UM,

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Speaker 1: I don't want to criticize this this because obviously there

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Speaker 1: are a number of issues going on, but I mean

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Speaker 1: instantly you think to yourself, oh, I'm glad there was

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Speaker 1: that stretch of a relative peace between ninety uh and

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Speaker 1: the and the nineteen seventy Um, you know obviously that's

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Speaker 1: when we had the World War two Great War. Yeah, yeah, yeah, exactly.

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Speaker 1: He's not tracking events like that because they aren't, I guess,

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Speaker 1: specifically within the borders of the United States. So that's

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Speaker 1: an interesting But you're making a really interesting counter argument here,

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Speaker 1: which is like, what's the then diagram of overlap of

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Speaker 1: global events on top of this right? Right? And then

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Speaker 1: you I guess you can also say two are you

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Speaker 1: have these key moments generationally where you have all these

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Speaker 1: factors coming together and opening us up for the potential

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Speaker 1: for unrest. But I guess there's also going to be

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Speaker 1: this um, this possibility for cascading effects, and I imagine

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Speaker 1: you could apply that to to the you know, the

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Speaker 1: decades to follow. He sort of addresses that, and I'll

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Speaker 1: get to that in the future, because he calls that's

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Speaker 1: part of his two hundred year scale. But let's wrap

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Speaker 1: up the fifty year scale. Yeah, Actually, that's a good

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Speaker 1: that's a good times you're going to have like two

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Speaker 1: different bruds of cicadas emerging at the same time exactly.

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Speaker 1: So he argues all of this in a published article

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Speaker 1: in a July issue of the Journal of Peace Research,

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Speaker 1: and he believes the model that he presents there suggests

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Speaker 1: that violence will be even worse because of quote demographic

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Speaker 1: variables such as wages, standards of living, and a number

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Speaker 1: of measures of intra elite confrontation. Now, his reasoning for

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Speaker 1: all of this is that there's a period of sustained

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Speaker 1: explosive violence, and then that is usually followed and maintained

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Speaker 1: as peace for around twenty to thirty years until a

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Speaker 1: new generation arises and this generation hasn't experienced any of

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Speaker 1: the horrors of the previous generations. So church And thinks

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Speaker 1: that this cycle occurs every two generations, or every forty

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Speaker 1: to sixty years. So that's why he places its smack

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Speaker 1: in the middle there with a fifty year cycle. This

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Speaker 1: is why he calls it the father's and son's cycle,

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Speaker 1: which is a little gendered. But the idea here is

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Speaker 1: that the father responds violently to perceived social justice, and

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Speaker 1: then their son lives with that legacy of conflict and abstains.

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Speaker 1: But with the third generation, the cycle begins again. Now

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Speaker 1: church And compares this to a forest fire, and he

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Speaker 1: says it will burn out until underbrush accumulates, and then

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Speaker 1: the cycle recommences again. Okay, I can definitely follow that. Yeah.

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Speaker 1: I like looking at my life and how my lifespan

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Speaker 1: has played against the cycles that he's outlining. I can

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Speaker 1: see this, you know, Like I was born just after

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Speaker 1: the Civil Rights movement, just after Vietnam. I learned from

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Speaker 1: my parents that those events were catastrophic and that it

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Speaker 1: was you know, essentially I learned to try to be

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Speaker 1: peaceful as as he's arguing here, and then I think

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Speaker 1: we're seeing like the generation maybe two generations behind you

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Speaker 1: and I are they didn't they didn't have those lessons, right,

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Speaker 1: and so subsequently they're sort of feeling the pressures of economy.

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Speaker 1: Really is what it comes down to with Turchin's arguments

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Speaker 1: upon themselves and then looking for a scapegoat. Yeah, I mean,

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Speaker 1: I have thought a lot in the past about what

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Speaker 1: it means to be entering into an age in which

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Speaker 1: there are no uh, you know, fewer and then ultimately

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Speaker 1: no firsthand accounts of the Second World War, you know. Yeah, yeah, absolutely,

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Speaker 1: that totally ties into this. Yeah. So he also identifies

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Speaker 1: the cause as get this political entrepreneurs who are trying

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Speaker 1: to get power. There are people who are already in

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Speaker 1: the elite, but they want to overturn the political order

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Speaker 1: to better suit themselves. Does this sound familiar anybody? And

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Speaker 1: he says that this subsequently has a historical precedent of

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Speaker 1: leading to revolution. But hold on a second. You're probably

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Speaker 1: saying to yourself, wait a minute, there was no peak

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Speaker 1: in the eighteen twenties. If this fits a fifty year model,

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Speaker 1: If I go back to the eighteen twenties, there wasn't

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Speaker 1: any upheaval, then why and he says, actually, that's because

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Speaker 1: the social variables like wages and employment were excellent at

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Speaker 1: that time. So he's looking at and he's thinking that

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Speaker 1: our current polarization here in the United States and the

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Speaker 1: current amount of inequality we're experiencing will reach a peak

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Speaker 1: in our discourse and political class will become even more

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Speaker 1: fragmented than it already is right now. In addition, he

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Speaker 1: finds uh things that are indicators are corruption increase and

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Speaker 1: political cooperation unraveling. Right before there are these big periods

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Speaker 1: of instability or violence that are imminent. And again this

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Speaker 1: sounds eerily familiar. I guess I should try to place

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Speaker 1: this too. So the article was written in twelve. He

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Speaker 1: started talking about this stuff back, and what would I say? So,

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Speaker 1: you know, he's been talking about this for a while now,

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Speaker 1: and now here we are in seventeen and we're experiencing

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Speaker 1: a lot of the things that he predicted. I'm not

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Speaker 1: saying that that necessarily means for I agree with his

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Speaker 1: prediction or I agree with this model, but it is

429
00:25:37,160 --> 00:25:39,600
Speaker 1: kind of scary how a lot of this is playing out.

430
00:25:40,440 --> 00:25:43,760
Speaker 1: So remember that other CLEO dynamic speaker I mentioned earlier,

431
00:25:43,760 --> 00:25:47,600
Speaker 1: Harvey white House. He says that if Turchin's prediction of

432
00:25:47,720 --> 00:25:50,920
Speaker 1: unrest in the United States is correct, we can actually

433
00:25:51,240 --> 00:25:56,120
Speaker 1: expect to see an increase in tightly knit groups who

434
00:25:56,280 --> 00:26:00,159
Speaker 1: use rituals with a threatening quality. But these ritual is

435
00:26:00,200 --> 00:26:05,760
Speaker 1: also promised great rewards for their members. And again I

436
00:26:05,840 --> 00:26:08,560
Speaker 1: have to remind us we're recording this a couple of

437
00:26:08,640 --> 00:26:11,320
Speaker 1: days after Charlottesville, and that describes that to a t

438
00:26:11,960 --> 00:26:15,240
Speaker 1: is a group with a threatening quality that's promising great

439
00:26:15,240 --> 00:26:17,920
Speaker 1: rewards to its members. What's the great reward in that case?

440
00:26:17,920 --> 00:26:21,959
Speaker 1: I wonder, well, I think that talking about greatness. They

441
00:26:22,400 --> 00:26:25,440
Speaker 1: so I've told a lot of people about this. Their

442
00:26:25,680 --> 00:26:28,600
Speaker 1: Vice actually made a video on the ground there. It's

443
00:26:28,600 --> 00:26:32,879
Speaker 1: about like minutes long. It's super upsetting, but I highly

444
00:26:32,880 --> 00:26:35,840
Speaker 1: recommend watching it to sort of get a first hand

445
00:26:35,840 --> 00:26:38,320
Speaker 1: account of what's going on there. When you when you

446
00:26:38,640 --> 00:26:42,760
Speaker 1: watch the people in these groups talking about why they're there,

447
00:26:42,800 --> 00:26:45,720
Speaker 1: a lot of it is about it comes down to

448
00:26:46,800 --> 00:26:51,000
Speaker 1: a cultural reclamation of the country and economic like they

449
00:26:51,040 --> 00:26:54,560
Speaker 1: feel like something's been taken away from them that they deserve,

450
00:26:55,200 --> 00:26:58,200
Speaker 1: and so I think that's what the groups are sort

451
00:26:58,240 --> 00:27:00,480
Speaker 1: of promising. It's like, if you part us have paid

452
00:27:00,480 --> 00:27:04,440
Speaker 1: in this you will reap rewards in the end. Okay,

453
00:27:04,440 --> 00:27:07,760
Speaker 1: So there's talking about like the return of say jobs,

454
00:27:08,400 --> 00:27:11,719
Speaker 1: uh so you know, manufacturing jobs in particular, that may

455
00:27:11,760 --> 00:27:16,639
Speaker 1: not actually be coming back. Then they're talking about like

456
00:27:17,320 --> 00:27:21,760
Speaker 1: some sort of a cultural focus that that either you know,

457
00:27:21,840 --> 00:27:24,719
Speaker 1: previously was in place or is misremembered as being um,

458
00:27:24,960 --> 00:27:27,960
Speaker 1: you know, more central than it was. Yeah, exactly. In fact,

459
00:27:28,000 --> 00:27:31,200
Speaker 1: like there's there's an idea along these lines. So remember

460
00:27:31,200 --> 00:27:35,240
Speaker 1: that eighteen twenties example. That's sort of like if we can,

461
00:27:35,400 --> 00:27:39,520
Speaker 1: as a entire society and with our government get it

462
00:27:39,560 --> 00:27:43,400
Speaker 1: together and try to pull together are for instance, make

463
00:27:43,400 --> 00:27:47,000
Speaker 1: our wages better and make sure everybody is employed, that

464
00:27:47,560 --> 00:27:52,720
Speaker 1: would be something that could stave this off. But basically

465
00:27:52,800 --> 00:27:55,840
Speaker 1: the argument is like there's so much chaos going on

466
00:27:55,920 --> 00:27:59,040
Speaker 1: with all of this, this complex system at work right

467
00:27:59,040 --> 00:28:02,200
Speaker 1: now that people like church and doubt that that's possible

468
00:28:02,240 --> 00:28:07,200
Speaker 1: at this point. Now. Church And also identifies three kinds

469
00:28:07,240 --> 00:28:10,679
Speaker 1: of violence that he said leads to these upheavals. He

470
00:28:10,760 --> 00:28:13,119
Speaker 1: calls these group on group violence. This is when you

471
00:28:13,160 --> 00:28:15,520
Speaker 1: see riots in modern day America, just like what we

472
00:28:15,520 --> 00:28:19,720
Speaker 1: were just talking about. There's groups against individuals and his

473
00:28:19,720 --> 00:28:24,280
Speaker 1: his example of this is lynchings. And then there's individuals

474
00:28:24,359 --> 00:28:27,800
Speaker 1: against groups, which we refer to as rampage killings. And

475
00:28:28,040 --> 00:28:31,600
Speaker 1: Urchin makes a point that we could identify a person

476
00:28:31,840 --> 00:28:37,399
Speaker 1: killing a group by themselves as terrorism, except he needs

477
00:28:37,400 --> 00:28:40,760
Speaker 1: to make a specific here in America. When this violence

478
00:28:40,800 --> 00:28:43,680
Speaker 1: is an American on American, we tend not to talk

479
00:28:43,720 --> 00:28:46,440
Speaker 1: about it in terms of terrorism. So his examples are

480
00:28:46,840 --> 00:28:50,880
Speaker 1: the Dark Knight shooting in Aurora or Timothy McVeigh. These

481
00:28:50,920 --> 00:28:54,280
Speaker 1: are usually rampage attacks that are directed in institutions like

482
00:28:54,440 --> 00:28:58,080
Speaker 1: education or government and church, and says they've grown by

483
00:28:58,080 --> 00:29:02,400
Speaker 1: a factor of twenty in the last generation. So this

484
00:29:03,040 --> 00:29:06,520
Speaker 1: is actually I have to provide a personal note aside here.

485
00:29:06,800 --> 00:29:10,360
Speaker 1: This is why I find it really troubling when I

486
00:29:10,400 --> 00:29:15,200
Speaker 1: see a positive reaction to violence against white supremacists or

487
00:29:15,200 --> 00:29:18,880
Speaker 1: white nationalists. We're talking about the like punching Nazis thing. Yeah,

488
00:29:18,880 --> 00:29:20,560
Speaker 1: there's a lot of this on the internet. There was

489
00:29:20,560 --> 00:29:23,840
Speaker 1: a lot of this right after that one I don't

490
00:29:23,840 --> 00:29:26,160
Speaker 1: remember this guy's name, but that that one guy who's

491
00:29:26,200 --> 00:29:27,880
Speaker 1: like a leader of one of these groups got punched

492
00:29:27,920 --> 00:29:30,520
Speaker 1: in the head earlier this year, and everybody was sort

493
00:29:30,560 --> 00:29:35,720
Speaker 1: of with schaden freud laughing at him, and then, uh,

494
00:29:35,840 --> 00:29:38,720
Speaker 1: you know, after this weekend, there's just an increase of

495
00:29:38,800 --> 00:29:41,080
Speaker 1: rhetoric from people who are friends and family with that

496
00:29:41,080 --> 00:29:43,520
Speaker 1: are saying like, yeah, this is great, let's get them,

497
00:29:43,560 --> 00:29:48,760
Speaker 1: you know. And and the rhetoric of using violence really

498
00:29:48,800 --> 00:29:52,440
Speaker 1: troubles me, and especially because it comes right back to

499
00:29:52,520 --> 00:29:56,080
Speaker 1: what Church and saying. He's saying, if you allowed these

500
00:29:56,120 --> 00:29:59,280
Speaker 1: three types of violence to grow, it's going to lead

501
00:29:59,320 --> 00:30:01,360
Speaker 1: to this up evil where it's going to be even worse.

502
00:30:01,520 --> 00:30:03,400
Speaker 1: And I for and I makes the world go blind,

503
00:30:03,520 --> 00:30:07,560
Speaker 1: right exactly. So you actually have something here that's a

504
00:30:07,640 --> 00:30:11,320
Speaker 1: quote of hope after that maybe ten minutes of dour

505
00:30:11,480 --> 00:30:13,880
Speaker 1: research prediction. Well, yeah, I have a couple of quotes here.

506
00:30:13,880 --> 00:30:16,680
Speaker 1: The first one is from Sergey A and Nephidoff, who

507
00:30:16,720 --> 00:30:19,640
Speaker 1: I mentioned earlier, one of the co authors with the Church,

508
00:30:19,760 --> 00:30:23,640
Speaker 1: and and he said in his Ian magazine piece quote,

509
00:30:23,840 --> 00:30:26,480
Speaker 1: we are rapidly approaching a historical cusp in with the

510
00:30:26,560 --> 00:30:30,320
Speaker 1: US will be particularly vulnerable to violent upheaval. This prediction

511
00:30:30,480 --> 00:30:34,440
Speaker 1: is not a prophecy. I don't believe the disaster is preordained,

512
00:30:34,520 --> 00:30:37,200
Speaker 1: no matter what we do. On the contrary, if we

513
00:30:37,360 --> 00:30:40,160
Speaker 1: understand the causes we have a chance to prevent it

514
00:30:40,160 --> 00:30:42,440
Speaker 1: from happening. But the first thing we have to do

515
00:30:42,560 --> 00:30:46,200
Speaker 1: is reverse the trend of ever growing inequality. And then

516
00:30:46,440 --> 00:30:50,760
Speaker 1: church In himself said, the descent is not inevitable. We

517
00:30:50,920 --> 00:30:54,120
Speaker 1: can avoid the worst, perhaps by switching to a less

518
00:30:54,120 --> 00:31:00,200
Speaker 1: harrowing track, perhaps by redesigning the roller coaster altogether. Yeah,

519
00:31:00,000 --> 00:31:04,080
Speaker 1: I um, I don't know if I a hundred percent

520
00:31:04,200 --> 00:31:07,920
Speaker 1: subscribe to Turchan's version of Cleo dynamics, but it does

521
00:31:07,960 --> 00:31:11,000
Speaker 1: seem a lot more grounded and quantitative data to me

522
00:31:11,120 --> 00:31:15,120
Speaker 1: than than other sort of predictive factors. I've talked about

523
00:31:15,160 --> 00:31:17,120
Speaker 1: on the show before about how my father thought the

524
00:31:17,160 --> 00:31:19,360
Speaker 1: world was gonna end like two years ago, and he

525
00:31:19,440 --> 00:31:22,160
Speaker 1: was like absolutely certain that there were It was exactly

526
00:31:22,200 --> 00:31:25,400
Speaker 1: like this, but it also like included historical events tied

527
00:31:25,440 --> 00:31:29,040
Speaker 1: into religious predictions, and he was certain the world was

528
00:31:29,040 --> 00:31:32,840
Speaker 1: gonna end. This is also like, uh, when we thought

529
00:31:32,960 --> 00:31:35,200
Speaker 1: like the Mayan predictions were gonna come true right or

530
00:31:35,240 --> 00:31:37,200
Speaker 1: well not weak, but you know, there there was a

531
00:31:37,200 --> 00:31:39,680
Speaker 1: lot of talk about about that, like, oh, is is

532
00:31:39,680 --> 00:31:41,840
Speaker 1: the world going to end in twelve because the mind's

533
00:31:41,880 --> 00:31:44,520
Speaker 1: predicted it. It's on these calendars. Yeah, I mean and

534
00:31:44,560 --> 00:31:47,280
Speaker 1: of course this comes back to weather forecasts again. You know,

535
00:31:47,560 --> 00:31:49,560
Speaker 1: it didn't rain on Wednesday, but they were saying it

536
00:31:49,600 --> 00:31:52,040
Speaker 1: was gonna gonna rain on Wednesday back when I checked

537
00:31:52,040 --> 00:31:55,120
Speaker 1: the weather on a Sunday. That doesn't mean the the

538
00:31:55,280 --> 00:31:59,560
Speaker 1: forecast was not based on scientific principles and and uh

539
00:31:59,600 --> 00:32:02,640
Speaker 1: an x up to patterns, but they're just too many

540
00:32:02,640 --> 00:32:06,520
Speaker 1: factors to properly chart. So and and to throw another

541
00:32:06,560 --> 00:32:09,200
Speaker 1: wrench into the works, this is where Turchands starts talking

542
00:32:09,200 --> 00:32:11,440
Speaker 1: about the two hundred years scale, and you alluded to

543
00:32:11,480 --> 00:32:14,040
Speaker 1: this earlier with the paper you referenced. He calls this

544
00:32:14,160 --> 00:32:17,400
Speaker 1: the secular cycle um and he talks about how there's

545
00:32:17,480 --> 00:32:19,960
Speaker 1: these two types of cycles. It's the fifty year wave

546
00:32:20,040 --> 00:32:22,360
Speaker 1: that we were just talking about. Then there's a longer

547
00:32:22,520 --> 00:32:26,520
Speaker 1: term oscillation that repeats every two hundred to three hundred years,

548
00:32:26,680 --> 00:32:30,040
Speaker 1: and depending on how these land, they can augment or

549
00:32:30,200 --> 00:32:33,560
Speaker 1: suppress those fifty year peaks. So his examples are the

550
00:32:33,680 --> 00:32:39,160
Speaker 1: Roman Empire, medieval France, and ancient China, with societies swinging

551
00:32:39,200 --> 00:32:42,880
Speaker 1: between peace and conflict every one hundred to one hundred

552
00:32:42,880 --> 00:32:46,280
Speaker 1: and fifty years. And he sees the United States as

553
00:32:46,320 --> 00:32:50,560
Speaker 1: a similar society to these previous empires, so he's predicting

554
00:32:50,600 --> 00:32:53,880
Speaker 1: that it will follow the same route. Now, he and

555
00:32:53,920 --> 00:32:56,640
Speaker 1: his associates, like I said, they call this the secular cycle.

556
00:32:56,720 --> 00:33:00,680
Speaker 1: They say it starts out first with an egalitarian society

557
00:33:01,000 --> 00:33:04,600
Speaker 1: where supply and demand for labor is roughly balanced out.

558
00:33:05,160 --> 00:33:08,880
Speaker 1: But then what happens is as the population grows, labor

559
00:33:08,960 --> 00:33:14,200
Speaker 1: begins to outstrip demands. Subsequently, you get elite classes that form.

560
00:33:14,240 --> 00:33:17,800
Speaker 1: This allows living standards for the poor to fall. Society

561
00:33:17,840 --> 00:33:20,760
Speaker 1: becomes top heavy with elites who start fighting for power,

562
00:33:21,240 --> 00:33:26,160
Speaker 1: and then political instability ensues and leads subsequently to collapse.

563
00:33:26,560 --> 00:33:29,040
Speaker 1: So his example of this, actually going back to that

564
00:33:29,080 --> 00:33:33,160
Speaker 1: other example earlier, is the Egyptian Uprising of eleven. He says,

565
00:33:33,720 --> 00:33:36,800
Speaker 1: you saw an interaction of the two cycles. They're explaining

566
00:33:36,920 --> 00:33:40,600
Speaker 1: events uh in Egypt, So he said, it seems like

567
00:33:40,600 --> 00:33:43,600
Speaker 1: Egypt's economy was growing and that poverty levels were low,

568
00:33:43,880 --> 00:33:46,480
Speaker 1: so you would have assumed that there would be stability.

569
00:33:46,520 --> 00:33:49,280
Speaker 1: But he argues that in a decade leading up to

570
00:33:49,320 --> 00:33:52,800
Speaker 1: the revolution, the country actually saw four times its amount

571
00:33:52,880 --> 00:33:57,360
Speaker 1: of graduates come out with no employment prospects. So for

572
00:33:57,480 --> 00:33:59,320
Speaker 1: church and it ultimately boils down. This is kind of

573
00:33:59,320 --> 00:34:03,040
Speaker 1: like a Marxist prediction, right, like it's based on economic factors,

574
00:34:03,280 --> 00:34:05,880
Speaker 1: how many workers you have, how many jobs are available,

575
00:34:05,920 --> 00:34:09,120
Speaker 1: how much money they've spent on education, so on. Alright,

576
00:34:09,120 --> 00:34:11,080
Speaker 1: on that note, let's take one more break, and when

577
00:34:11,080 --> 00:34:14,640
Speaker 1: we come back, we'll we'll discuss clear dynamics a little

578
00:34:14,640 --> 00:34:16,880
Speaker 1: bit more and then get into some of the some

579
00:34:16,960 --> 00:34:24,040
Speaker 1: of the criticisms and critiques. Thank alright, we're back. So

580
00:34:24,160 --> 00:34:27,480
Speaker 1: turch And he's actually taken the models of Cleo dynamics

581
00:34:27,520 --> 00:34:32,319
Speaker 1: and applied them as well to models of religious growth. Now,

582
00:34:32,400 --> 00:34:35,200
Speaker 1: one model he looks at here is linear. He says,

583
00:34:35,760 --> 00:34:40,000
Speaker 1: as believers start seeing the light quote unquote, the religion

584
00:34:40,000 --> 00:34:42,440
Speaker 1: will start to grow, right. But then he's got another model,

585
00:34:42,480 --> 00:34:45,880
Speaker 1: and he says religion can grow like a contagion sometime,

586
00:34:46,280 --> 00:34:50,319
Speaker 1: where converts increase exponentially. And so what he says is

587
00:34:50,360 --> 00:34:55,640
Speaker 1: he's he's mapped conversions for Islam in medieval Iran and

588
00:34:55,800 --> 00:34:59,960
Speaker 1: Spain and found that the data fits the contagion model

589
00:35:00,200 --> 00:35:03,400
Speaker 1: more closely than it does the linear model. There. Likewise,

590
00:35:03,400 --> 00:35:05,799
Speaker 1: he argues that there's models that explain the expansion of

591
00:35:05,880 --> 00:35:10,120
Speaker 1: Christianity in the first century a d. And Mormonism here

592
00:35:10,160 --> 00:35:13,280
Speaker 1: in the US since World War Two, so that's also

593
00:35:13,440 --> 00:35:16,600
Speaker 1: pretty interesting. Again, I don't know, I feel like you'd

594
00:35:16,680 --> 00:35:19,960
Speaker 1: really have to drill down deep to determine, like how

595
00:35:20,560 --> 00:35:24,479
Speaker 1: methodologically sound this is, um, But there is, like we said,

596
00:35:24,520 --> 00:35:27,360
Speaker 1: like there's this growing group of academics who are writing

597
00:35:27,400 --> 00:35:30,640
Speaker 1: about it and researching it and accumulating data to try

598
00:35:30,640 --> 00:35:33,000
Speaker 1: to see if it if it pans out, you know.

599
00:35:33,080 --> 00:35:35,799
Speaker 1: In researching all of this, I am, once again, in

600
00:35:35,880 --> 00:35:39,400
Speaker 1: my life, um disappointed that I have not read Isaac

601
00:35:39,440 --> 00:35:43,239
Speaker 1: Asimov's The Foundation books, because I know that what I

602
00:35:43,280 --> 00:35:45,920
Speaker 1: know of the books without getting into deep because I

603
00:35:45,920 --> 00:35:48,719
Speaker 1: don't want to spoil myself, is that it does concern

604
00:35:49,160 --> 00:35:52,560
Speaker 1: predictive models of the future and uh and and does

605
00:35:52,600 --> 00:35:55,560
Speaker 1: so you know, in great depth because it's Isaac Asimov,

606
00:35:55,800 --> 00:35:57,440
Speaker 1: So of course, of course you put a lot of

607
00:35:57,440 --> 00:35:59,640
Speaker 1: time into it. But sadly I have not. I have

608
00:35:59,640 --> 00:36:01,359
Speaker 1: not read those and did not have time to read

609
00:36:01,400 --> 00:36:04,080
Speaker 1: them before this recording. But I would love to hear

610
00:36:04,200 --> 00:36:06,640
Speaker 1: from anyone out there who has read the Foundation series

611
00:36:06,680 --> 00:36:09,520
Speaker 1: and and and has related inside on this topic. Yeah,

612
00:36:09,520 --> 00:36:12,400
Speaker 1: I'm curious if if those asthma seems like the kind

613
00:36:12,400 --> 00:36:16,360
Speaker 1: of guy who would explore through fiction like the arguments

614
00:36:16,400 --> 00:36:19,359
Speaker 1: against these kind of predictive models, right, because one thing

615
00:36:19,760 --> 00:36:22,120
Speaker 1: that people are concerned about is if you apply these

616
00:36:22,120 --> 00:36:24,840
Speaker 1: predictive models and then you start using them on a

617
00:36:24,920 --> 00:36:29,280
Speaker 1: policy level through government, then what happens when the predictive

618
00:36:29,280 --> 00:36:32,880
Speaker 1: model says things are going to get dire in in

619
00:36:32,960 --> 00:36:38,080
Speaker 1: the government suddenly becomes like really dictatorial trying to make

620
00:36:38,120 --> 00:36:42,520
Speaker 1: sure that that that negative outcome doesn't happen. Right, So

621
00:36:42,680 --> 00:36:45,799
Speaker 1: so you can get like a minority report kind of situation. Yeah,

622
00:36:45,840 --> 00:36:48,800
Speaker 1: it's kind of like envisioning. Okay, you're you're predicting the weather.

623
00:36:48,840 --> 00:36:52,480
Speaker 1: You're basing it on the natural state of the atmosphere

624
00:36:52,480 --> 00:36:56,160
Speaker 1: and weather patterns, and of course you're factoring and human

625
00:36:56,200 --> 00:36:58,960
Speaker 1: influence on the weather pattering patterns. But if you reach

626
00:36:59,040 --> 00:37:02,720
Speaker 1: the point where they humans can can and are intentionally

627
00:37:02,840 --> 00:37:05,719
Speaker 1: altering the weather, so like you know, I guess like

628
00:37:05,760 --> 00:37:08,680
Speaker 1: blasting tornadoes out of the sky or turning off her

629
00:37:08,719 --> 00:37:12,719
Speaker 1: acnes or diverting them, then you're you're having to factor

630
00:37:13,360 --> 00:37:19,080
Speaker 1: intentional human interaction, uh into the overall simulation and forecast

631
00:37:19,160 --> 00:37:23,240
Speaker 1: for the atmosphere. Yeah, wow, that's true. So that would

632
00:37:23,239 --> 00:37:27,200
Speaker 1: really that would be another factor added on to cleo dynamics.

633
00:37:27,280 --> 00:37:30,760
Speaker 1: Then is trying to figure out outside of the predictive models,

634
00:37:30,800 --> 00:37:34,160
Speaker 1: then what the influence of humans using the predictive models

635
00:37:34,320 --> 00:37:38,120
Speaker 1: upon the actual events would do to change the predictions.

636
00:37:38,360 --> 00:37:40,680
Speaker 1: I think so yeah. I mean, if you have individuals

637
00:37:40,719 --> 00:37:44,160
Speaker 1: who understand how it was working and are manipulating it,

638
00:37:44,400 --> 00:37:45,880
Speaker 1: then they have to factor that in. It's kind of like,

639
00:37:45,960 --> 00:37:48,239
Speaker 1: if you have one wizard in the world who can

640
00:37:48,520 --> 00:37:53,000
Speaker 1: bend uh natural law to their will, then that's one thing.

641
00:37:53,400 --> 00:37:56,400
Speaker 1: But then what if you have two wizards? Now it

642
00:37:56,440 --> 00:38:00,480
Speaker 1: seems like that that just doubles the complexity of the scenario. Well,

643
00:38:00,520 --> 00:38:04,360
Speaker 1: there is another wizard here, but he's not Churching and

644
00:38:05,080 --> 00:38:08,040
Speaker 1: so his name is Charles Hughes Smith and he writes

645
00:38:08,160 --> 00:38:10,960
Speaker 1: for Business Insider. I don't know necessarily that he considers

646
00:38:11,000 --> 00:38:15,160
Speaker 1: himself a cleo dynamicist. Is that what you would refer

647
00:38:15,200 --> 00:38:21,920
Speaker 1: to them as damn dynamos dynamo? Yeah? Maybe? Uh so Smith.

648
00:38:22,680 --> 00:38:25,160
Speaker 1: He's written about this in like I said, Business Insider,

649
00:38:25,200 --> 00:38:27,520
Speaker 1: in his own books. He has a website that's full

650
00:38:27,560 --> 00:38:29,880
Speaker 1: of this stuff. To the all of his theories, he

651
00:38:30,040 --> 00:38:33,720
Speaker 1: argues there are other reasons why we're looking at seeing

652
00:38:33,760 --> 00:38:38,160
Speaker 1: trouble somewhere between, he says, or two, so we can

653
00:38:38,200 --> 00:38:40,319
Speaker 1: put it off a couple of years. That's how he's frying.

654
00:38:40,360 --> 00:38:42,720
Speaker 1: I want to get all the Avatar sequels in before

655
00:38:44,400 --> 00:38:46,600
Speaker 1: that four or five movies. Man can't reme better start

656
00:38:46,600 --> 00:38:50,800
Speaker 1: cranking those out. So Smith says, there's four grand cycles.

657
00:38:50,880 --> 00:38:54,360
Speaker 1: And let me be clear. That eighty year cycle that

658
00:38:54,400 --> 00:38:57,319
Speaker 1: we were talking about that's floating around right now, that

659
00:38:57,480 --> 00:39:00,799
Speaker 1: is one of these four grand cycles. Now that that

660
00:39:00,920 --> 00:39:05,120
Speaker 1: first one is it's a generational cycle of eighty years,

661
00:39:05,160 --> 00:39:08,160
Speaker 1: that's every four generations, and it is said to lead

662
00:39:08,200 --> 00:39:12,880
Speaker 1: to nation changing social, political, and economic upheaval. This is

663
00:39:12,960 --> 00:39:16,560
Speaker 1: referenced in a book called The Fourth Turning by Willem

664
00:39:16,680 --> 00:39:20,920
Speaker 1: Strauss or William Strauss and Neil how And it also

665
00:39:21,040 --> 00:39:24,120
Speaker 1: argues that after eighty years, there are few humans who

666
00:39:24,120 --> 00:39:27,560
Speaker 1: can actually recall the last crisis. So your example of

667
00:39:27,560 --> 00:39:29,759
Speaker 1: World War two there, now, this is the one that

668
00:39:29,880 --> 00:39:32,960
Speaker 1: that's currently making the rounds uh. It's part of Hughes

669
00:39:33,040 --> 00:39:35,359
Speaker 1: sort of thing. His other cycles included here that we're

670
00:39:35,400 --> 00:39:38,280
Speaker 1: gonna hit peak oil, where there will be a depletion

671
00:39:38,360 --> 00:39:41,920
Speaker 1: of the global economy's reliance on fossil fuels, that credit

672
00:39:42,000 --> 00:39:46,320
Speaker 1: expansion and contraction will transition from a bubble to a collapse,

673
00:39:46,400 --> 00:39:49,440
Speaker 1: and that's subsequently going to lead to a global depression.

674
00:39:50,000 --> 00:39:54,919
Speaker 1: And I have to say from other articles, like all

675
00:39:54,960 --> 00:39:59,239
Speaker 1: of this doesn't really seem to be quantitatively mapped the

676
00:39:59,320 --> 00:40:04,160
Speaker 1: same way that Hurchin and other cleo dynamos are. This

677
00:40:04,239 --> 00:40:09,040
Speaker 1: seems to be more based on him citing other books

678
00:40:09,040 --> 00:40:12,120
Speaker 1: and he that includes Churchen's work. He does cite urchins work,

679
00:40:12,520 --> 00:40:17,239
Speaker 1: but he's providing observational, qualitative examples. And the last, the

680
00:40:17,360 --> 00:40:20,000
Speaker 1: last factor he throws in here is a hundred years

681
00:40:20,040 --> 00:40:24,120
Speaker 1: cycle of price inflation that is met by a stagnation

682
00:40:24,160 --> 00:40:26,440
Speaker 1: of wages. So this this seems a little bit closer

683
00:40:26,440 --> 00:40:30,560
Speaker 1: to what Churchens talking about here that leads to shortages, famine,

684
00:40:30,600 --> 00:40:33,120
Speaker 1: and crisis. He says this is because humanity is a

685
00:40:33,320 --> 00:40:38,280
Speaker 1: species tries to expand into every ecological niche when food

686
00:40:38,360 --> 00:40:42,479
Speaker 1: and energy supplies are rising, and so this he calls

687
00:40:42,480 --> 00:40:45,800
Speaker 1: a hundred years cycle of rising prices for food, energy,

688
00:40:45,840 --> 00:40:50,920
Speaker 1: and water. Uh And and Smith's argument is essentially, the

689
00:40:51,000 --> 00:40:53,400
Speaker 1: government might be able to deal with any one of

690
00:40:53,480 --> 00:40:56,919
Speaker 1: these things, but four of these things at once might

691
00:40:57,000 --> 00:41:00,360
Speaker 1: prove to be too much for any institution of human beings.

692
00:41:00,960 --> 00:41:03,879
Speaker 1: So I don't know where I really fall in terms

693
00:41:03,920 --> 00:41:08,920
Speaker 1: of these arguments, Like, if you apply traditional syllogistic logic

694
00:41:09,000 --> 00:41:11,520
Speaker 1: to these arguments, do they do they still hold up?

695
00:41:11,560 --> 00:41:14,760
Speaker 1: Does the evidence for these claims actually warrant a connection

696
00:41:14,840 --> 00:41:18,600
Speaker 1: between them? I'm not sure about that, So I want

697
00:41:18,600 --> 00:41:21,480
Speaker 1: to throw that out there. This is just we're accumulating

698
00:41:21,800 --> 00:41:25,360
Speaker 1: and presenting to you the variations on these cyclical theories.

699
00:41:25,680 --> 00:41:28,520
Speaker 1: All right, well, let's let's get into some of the

700
00:41:28,520 --> 00:41:31,520
Speaker 1: the arguments against cleo dynamics, some of the critiques of

701
00:41:31,520 --> 00:41:34,600
Speaker 1: cleo dynamics. So the weekend, you know, maybe wave this

702
00:41:34,640 --> 00:41:37,600
Speaker 1: out a little bit, right, So some people are arguing

703
00:41:37,680 --> 00:41:40,799
Speaker 1: that the mathematical models may simply be a case of

704
00:41:40,840 --> 00:41:44,560
Speaker 1: seeing patterns in random data. So so once again the hindsight,

705
00:41:45,480 --> 00:41:48,560
Speaker 1: Yeah exactly. Uh. And then also the data set that

706
00:41:48,600 --> 00:41:51,320
Speaker 1: Turchin is working with has been criticized for being too

707
00:41:51,400 --> 00:41:54,719
Speaker 1: short because it only covers a period from seventeen eighty

708
00:41:54,800 --> 00:41:59,440
Speaker 1: to So maybe cleo dynamics does work, but humanity probably

709
00:41:59,480 --> 00:42:01,680
Speaker 1: needs to back up another couple of centuries of good

710
00:42:01,680 --> 00:42:06,520
Speaker 1: record keeping before we can actually apply it in any sense. Also,

711
00:42:06,640 --> 00:42:11,560
Speaker 1: historians in general argue that cleo dynamics weakness is that

712
00:42:11,680 --> 00:42:15,359
Speaker 1: when it attempts to make predictions based on trends when

713
00:42:15,440 --> 00:42:19,960
Speaker 1: historical information availability is usually patchy at best. Right, So

714
00:42:20,239 --> 00:42:24,200
Speaker 1: our records are preserved or destroyed based on chance, for instance,

715
00:42:24,320 --> 00:42:28,120
Speaker 1: our palam sess episode, right, uh, and knowledge tends to

716
00:42:28,160 --> 00:42:32,920
Speaker 1: pool around narrow subject areas. The example that immediately comes

717
00:42:32,920 --> 00:42:35,279
Speaker 1: to mind for me on this, pop culture wise is

718
00:42:35,320 --> 00:42:41,160
Speaker 1: The Strain. I've started watching The Strain again. Oh man, well,

719
00:42:41,200 --> 00:42:44,200
Speaker 1: I'm actually I'm watching season three. I haven't hit the

720
00:42:44,239 --> 00:42:47,960
Speaker 1: final season yet, but yeah, they've got that book the

721
00:42:48,080 --> 00:42:50,920
Speaker 1: Lumen that is like the book of all the answers

722
00:42:50,920 --> 00:42:54,000
Speaker 1: on how to deal with these vampires translates to how

723
00:42:54,000 --> 00:42:57,279
Speaker 1: to kill vampire basically, yeah, yeah, And it's like they're

724
00:42:57,360 --> 00:43:01,160
Speaker 1: facing in the world of the Strain, this this total

725
00:43:01,280 --> 00:43:05,080
Speaker 1: upheaval as vampires start taking over the world and killing

726
00:43:05,080 --> 00:43:08,520
Speaker 1: off the human race. But the only record of how

727
00:43:08,560 --> 00:43:10,520
Speaker 1: to deal with this is in this one book that

728
00:43:10,560 --> 00:43:14,680
Speaker 1: takes what two seasons to find ye, and then they

729
00:43:14,719 --> 00:43:16,960
Speaker 1: find it and it takes another season to translate it.

730
00:43:17,840 --> 00:43:20,960
Speaker 1: So yeah, I think that's like, you know, that's obviously

731
00:43:20,960 --> 00:43:23,920
Speaker 1: a fictional example. But to be fair, you know, our

732
00:43:23,960 --> 00:43:27,600
Speaker 1: record keeping is hasn't been that great until recently. Yeah,

733
00:43:27,680 --> 00:43:29,880
Speaker 1: actually a recent by the time it's published, as it

734
00:43:29,920 --> 00:43:31,480
Speaker 1: will be a recent episode. But Joe and I did

735
00:43:31,480 --> 00:43:35,880
Speaker 1: an episode on Greek Fire, the Byzantine secret weapon, so

736
00:43:36,120 --> 00:43:40,279
Speaker 1: secret in fact that that it's a mystery regarding exactly

737
00:43:40,360 --> 00:43:43,200
Speaker 1: what it entailed in terms of formula and the system

738
00:43:43,239 --> 00:43:46,000
Speaker 1: of deployment. Yeah, you just have to go under King's landing.

739
00:43:46,040 --> 00:43:49,239
Speaker 1: That's where it's Okay, that's that's true, alright. So I

740
00:43:49,680 --> 00:43:53,520
Speaker 1: mentioned the you know, hindsight is because again that's one

741
00:43:53,560 --> 00:43:55,680
Speaker 1: of the criticisms here, that it's one thing to inflict

742
00:43:55,719 --> 00:43:58,879
Speaker 1: cyclical order on the past, because historians have been doing

743
00:43:58,920 --> 00:44:01,320
Speaker 1: this for ages. Right, Even our systems of the system

744
00:44:01,360 --> 00:44:05,040
Speaker 1: of years or classification of the ages and empires are

745
00:44:05,080 --> 00:44:09,800
Speaker 1: boiling down of of the past into narratives is ultimately

746
00:44:09,840 --> 00:44:13,320
Speaker 1: a form of this UM. And then plus there's always

747
00:44:13,360 --> 00:44:17,320
Speaker 1: the potential impact of unforeseen events that buck perceived patterns.

748
00:44:17,760 --> 00:44:20,839
Speaker 1: So we've talked a lot about outside context events um

749
00:44:21,360 --> 00:44:25,040
Speaker 1: the terminology coined by Ian and Banks before, but there's

750
00:44:25,080 --> 00:44:30,120
Speaker 1: also a similar notion explored in black swan theory. So

751
00:44:30,520 --> 00:44:33,000
Speaker 1: this was this is an idea that came from an

752
00:44:33,120 --> 00:44:37,360
Speaker 1: seem Nicholas Taleb and he he uh he takes this

753
00:44:37,440 --> 00:44:39,520
Speaker 1: to the name of this black swan theory from the

754
00:44:39,520 --> 00:44:44,640
Speaker 1: fact that before the discovery of Australia, scientific observation suggested

755
00:44:44,760 --> 00:44:47,920
Speaker 1: that all swans were white. Huh okay, there was no

756
00:44:47,960 --> 00:44:51,400
Speaker 1: such thing as a black swan as there uh was

757
00:44:51,520 --> 00:44:53,239
Speaker 1: a you know, no more than there was a green

758
00:44:53,320 --> 00:44:56,320
Speaker 1: or a purple one. But then the European explorers discovered

759
00:44:56,360 --> 00:44:59,680
Speaker 1: the world down under and they discovered black swans, so

760
00:44:59,760 --> 00:45:04,040
Speaker 1: that which was you know, possible but but had not

761
00:45:04,160 --> 00:45:08,839
Speaker 1: been observed yet, became reality. So the black swan here

762
00:45:08,880 --> 00:45:13,520
Speaker 1: was an outlier existing beyond the realm of reasonable expectation.

763
00:45:14,160 --> 00:45:17,600
Speaker 1: But the human mind depends on pattern recognition, so to

764
00:45:17,760 --> 00:45:21,160
Speaker 1: Leb writes in his Black Swan book that we humans

765
00:45:21,560 --> 00:45:25,080
Speaker 1: uh think up explanations for an outlier's occurrence after we

766
00:45:25,200 --> 00:45:29,400
Speaker 1: encounter it to make it explainable and predictable. So, you know,

767
00:45:29,440 --> 00:45:31,919
Speaker 1: the idea here is that we were looking back in time,

768
00:45:31,960 --> 00:45:35,680
Speaker 1: we're looking at history, and we're just reinterpreting black swan

769
00:45:35,760 --> 00:45:39,120
Speaker 1: events as being something that could have been predicted and foreseen,

770
00:45:39,200 --> 00:45:42,279
Speaker 1: and therefore thinking they will be foreseen uh perceived, perceivable,

771
00:45:42,280 --> 00:45:45,520
Speaker 1: and predictable in our future. But by their very nature,

772
00:45:45,520 --> 00:45:49,880
Speaker 1: outliers are unpredictable, and according to to to leave Uh,

773
00:45:49,920 --> 00:45:53,080
Speaker 1: this implies the inability to predict the course of history,

774
00:45:53,160 --> 00:45:58,160
Speaker 1: given how much outliers um have impacted our past, such

775
00:45:58,200 --> 00:46:02,600
Speaker 1: as he brings up the nineteen eighty seven market crash,

776
00:46:03,000 --> 00:46:06,600
Speaker 1: the demise of the Soviet block, uh, the September eleven

777
00:46:06,920 --> 00:46:10,680
Speaker 1: two one terrorist attacks. How these drastically informed the shape

778
00:46:10,719 --> 00:46:15,640
Speaker 1: of human events. But we're not necessarily predictable. Now that's,

779
00:46:15,680 --> 00:46:17,640
Speaker 1: of course, you can get into a whole argument about

780
00:46:17,640 --> 00:46:20,319
Speaker 1: to what degree these were predictable, But that's kind of

781
00:46:20,320 --> 00:46:22,359
Speaker 1: playing into his argument to saying that again you look

782
00:46:22,400 --> 00:46:25,640
Speaker 1: back hindsight. It's one thing to look back and say, no,

783
00:46:25,760 --> 00:46:27,960
Speaker 1: this was predictable, look at these patterns, but are you

784
00:46:28,000 --> 00:46:31,120
Speaker 1: just informing? Are you are you just enforcing a pattern

785
00:46:31,440 --> 00:46:33,880
Speaker 1: on the past. Now, all of this being said, I

786
00:46:33,880 --> 00:46:36,240
Speaker 1: want to stress what I restress what I said earlier

787
00:46:36,320 --> 00:46:39,040
Speaker 1: is that there you don't see a lot of people saying, oh,

788
00:46:39,080 --> 00:46:42,319
Speaker 1: cleo dynamics, who just is just all crap? Just throw

789
00:46:42,360 --> 00:46:44,640
Speaker 1: it all out the generally, your argument is, I don't

790
00:46:44,680 --> 00:46:49,160
Speaker 1: think that these models are as precise as you would

791
00:46:49,200 --> 00:46:51,799
Speaker 1: want them to be, or that we can predict the

792
00:46:51,840 --> 00:46:55,600
Speaker 1: future as well as as the proponents of cleo dynamics

793
00:46:55,600 --> 00:46:59,840
Speaker 1: are claiming. Right, Yeah, And also like this isn't a

794
00:47:00,000 --> 00:47:02,680
Speaker 1: again bringing it back to minority report, It's not like

795
00:47:03,040 --> 00:47:05,560
Speaker 1: if we get cleo dynamics just right, we're gonna have

796
00:47:05,640 --> 00:47:08,239
Speaker 1: the equivalent of psychics in a bathtub that tell us

797
00:47:08,600 --> 00:47:10,399
Speaker 1: you know when crimes are going to be committed, Like

798
00:47:11,000 --> 00:47:13,239
Speaker 1: and even that, as we've seen in that Philip K.

799
00:47:13,360 --> 00:47:16,759
Speaker 1: Dick story, is fraught with peril. Right, So where does

800
00:47:16,800 --> 00:47:19,399
Speaker 1: that leave us at the end here? Well, I think

801
00:47:19,440 --> 00:47:22,560
Speaker 1: what we have to ask, and I'm asking you too, listeners,

802
00:47:23,280 --> 00:47:26,840
Speaker 1: is this a valid scientific method? Like like, is cleo

803
00:47:26,920 --> 00:47:31,080
Speaker 1: dynamics something we should be continuing to look into? And

804
00:47:31,200 --> 00:47:35,200
Speaker 1: like should we be following what's going on in this journal? Uh?

805
00:47:35,280 --> 00:47:38,720
Speaker 1: And then how does you know somebody like a smith

806
00:47:38,800 --> 00:47:41,360
Speaker 1: for instance, like how did his predictions which don't seem

807
00:47:41,400 --> 00:47:44,200
Speaker 1: to be as as grounded in data sets? How do

808
00:47:44,280 --> 00:47:47,240
Speaker 1: how do those play together with it? So I'm curious

809
00:47:47,280 --> 00:47:50,560
Speaker 1: about that. But then also many of you, like myself

810
00:47:50,600 --> 00:47:54,240
Speaker 1: are probably wondering during these events of turmoil we're experiencing, now,

811
00:47:54,520 --> 00:47:59,160
Speaker 1: how do we prevent this violence? Right? Well, Urchen, he says,

812
00:47:59,760 --> 00:48:02,120
Speaker 1: if I'm right, this is how I think we can

813
00:48:02,160 --> 00:48:05,960
Speaker 1: help things. He argues, first of all, inequality is almost

814
00:48:06,120 --> 00:48:09,360
Speaker 1: always a bad thing for societies, So he says, to

815
00:48:09,440 --> 00:48:13,080
Speaker 1: prevent violence, we have to learn from history, and to

816
00:48:13,200 --> 00:48:16,399
Speaker 1: do that, we need to create more jobs for our

817
00:48:16,440 --> 00:48:23,279
Speaker 1: graduates while acting decisively to reduce inequality. But others are

818
00:48:23,400 --> 00:48:27,680
Speaker 1: arguing maybe a revolution, maybe uprisings, These are for the

819
00:48:27,760 --> 00:48:32,240
Speaker 1: best because they can remedy social stresses. For example, people

820
00:48:32,239 --> 00:48:34,520
Speaker 1: look back at the Civil rights movement and they say,

821
00:48:34,760 --> 00:48:37,279
Speaker 1: was that a bad thing? What came out of the

822
00:48:37,320 --> 00:48:42,239
Speaker 1: Civil rights movement is quote good, right, But there were

823
00:48:42,640 --> 00:48:45,960
Speaker 1: certainly violent upheaval and turmoil during that period of time

824
00:48:45,960 --> 00:48:49,480
Speaker 1: as well. I guess it depends on what what uprising

825
00:48:49,560 --> 00:48:52,120
Speaker 1: you're looking at, because certainly, you know, it's one thing

826
00:48:52,160 --> 00:48:55,279
Speaker 1: to say, you know, the civil rights movement was it

827
00:48:55,440 --> 00:48:58,239
Speaker 1: was a positive movement, but nobody wants an uprising, say

828
00:48:58,320 --> 00:49:01,640
Speaker 1: like the kind we see in the hands tail Yeah exactly,

829
00:49:01,680 --> 00:49:03,400
Speaker 1: And I think to like when you're talking about it

830
00:49:03,440 --> 00:49:05,600
Speaker 1: in those terms, like it's sort of like talking about

831
00:49:05,600 --> 00:49:08,520
Speaker 1: a fever burning and illness out of your body, right,

832
00:49:08,600 --> 00:49:11,799
Speaker 1: And I don't know. I don't know. I try to

833
00:49:12,080 --> 00:49:14,280
Speaker 1: as much as possible. I try to fall back on

834
00:49:14,080 --> 00:49:17,600
Speaker 1: non violence and so any ways in which we can

835
00:49:17,640 --> 00:49:21,359
Speaker 1: try to avoid that. Look, I'm gonna be supportive of

836
00:49:21,520 --> 00:49:23,479
Speaker 1: So I look at this and I see what turch

837
00:49:23,560 --> 00:49:28,160
Speaker 1: and saying. It doesn't sound illogical to me. It sounds like, yeah, sure,

838
00:49:28,640 --> 00:49:31,360
Speaker 1: if there were more jobs available for graduates in this country,

839
00:49:31,400 --> 00:49:33,239
Speaker 1: that would be great. I don't I don't know how

840
00:49:33,239 --> 00:49:36,120
Speaker 1: to do that, right, And then how do you reduce

841
00:49:36,160 --> 00:49:40,719
Speaker 1: inequality across a broad band? You know, I mean, it's

842
00:49:40,920 --> 00:49:43,759
Speaker 1: something we've been working on for decades. Now. We get

843
00:49:43,800 --> 00:49:46,440
Speaker 1: into some of those wicked problems, right exactly. Yeah, So

844
00:49:46,560 --> 00:49:48,520
Speaker 1: if you don't know what we're speaking of there, we

845
00:49:48,560 --> 00:49:51,080
Speaker 1: have another episode similar to this one actually kind of

846
00:49:51,120 --> 00:49:56,480
Speaker 1: looking at broader sociological issues about a theory called wicked problems.

847
00:49:56,520 --> 00:49:58,160
Speaker 1: If you go to stuff to Blow your Mind dot com,

848
00:49:58,200 --> 00:50:00,560
Speaker 1: type in Wicked Problems that episode of them up, or

849
00:50:00,640 --> 00:50:03,279
Speaker 1: you can find it on any of your podcast readers. Yeah,

850
00:50:03,400 --> 00:50:05,000
Speaker 1: but it does get into a lot of a lot

851
00:50:05,040 --> 00:50:07,680
Speaker 1: of the similar territory here, So I would highly recommend

852
00:50:07,719 --> 00:50:10,640
Speaker 1: that episode if you found this episode of very thought,

853
00:50:10,719 --> 00:50:12,960
Speaker 1: Let's try to uh on the landing page for this episode,

854
00:50:13,040 --> 00:50:15,879
Speaker 1: let's try to link back to Wicked Problems. Okay, So

855
00:50:16,480 --> 00:50:18,279
Speaker 1: I asked you that question. Do you think it's a

856
00:50:18,320 --> 00:50:21,200
Speaker 1: valid scientific method? If you do, If you don't, there's

857
00:50:21,239 --> 00:50:23,640
Speaker 1: ways to let us know. We're on social media. You

858
00:50:23,680 --> 00:50:27,880
Speaker 1: can talk to us about Cleo Dynamics on Facebook, Twitter, Tumbler,

859
00:50:27,880 --> 00:50:32,279
Speaker 1: and Instagram. We also have our Facebook discussion module up

860
00:50:32,280 --> 00:50:34,520
Speaker 1: where if you want to have just like a closed

861
00:50:34,560 --> 00:50:40,399
Speaker 1: conversation with people who are like fans of the podcast. Specifically,

862
00:50:40,400 --> 00:50:43,560
Speaker 1: it's a closed group on Facebook. Uh, try to join

863
00:50:43,760 --> 00:50:45,359
Speaker 1: us over there. You can find the link to that

864
00:50:45,400 --> 00:50:48,239
Speaker 1: on our Facebook page. Right. Yeah, And you know, I

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00:50:48,360 --> 00:50:49,960
Speaker 1: just in all of this, I do want to stress

866
00:50:50,040 --> 00:50:53,360
Speaker 1: that I think there is optimism in this topic. Um,

867
00:50:53,400 --> 00:50:55,480
Speaker 1: you know, the very fact that people are doing this

868
00:50:55,680 --> 00:50:58,960
Speaker 1: research lends to optimism. So I would I would encourage

869
00:50:58,960 --> 00:51:02,880
Speaker 1: everyone to take the optimist excite of this because for starters,

870
00:51:03,480 --> 00:51:05,839
Speaker 1: optimism is a place of action. You can you can

871
00:51:05,880 --> 00:51:09,440
Speaker 1: act out of optimism. Uh, It's often very difficult to

872
00:51:09,600 --> 00:51:12,879
Speaker 1: act in any constructive way out of a state of pessimism.

873
00:51:13,239 --> 00:51:16,759
Speaker 1: So so yeah, take take this as you know, individuals

874
00:51:16,800 --> 00:51:20,000
Speaker 1: who are trying to use the best tools available to

875
00:51:20,120 --> 00:51:23,000
Speaker 1: us to figure out where we're going, and how how

876
00:51:23,040 --> 00:51:24,799
Speaker 1: to get to the places we want to go, how

877
00:51:24,800 --> 00:51:27,799
Speaker 1: to avoid all the strife, you know, and and and

878
00:51:27,840 --> 00:51:30,160
Speaker 1: maybe even get to that point where we eventually have

879
00:51:30,280 --> 00:51:33,120
Speaker 1: some sort of a post scarcity society and will be

880
00:51:34,520 --> 00:51:40,719
Speaker 1: arguably largely immune to some of these societal pitfalls. Exactly.

881
00:51:40,880 --> 00:51:44,720
Speaker 1: I think you said that perfectly, all right, And uh yeah, finally,

882
00:51:44,760 --> 00:51:46,480
Speaker 1: if you want to get in touch with us directly,

883
00:51:46,680 --> 00:51:49,040
Speaker 1: then you know which email addressed to turn to. That

884
00:51:49,160 --> 00:52:00,920
Speaker 1: is blow the mind at how stuff works dot com.

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00:52:00,960 --> 00:52:03,480
Speaker 1: For more on this and thousands of other topics, visit

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00:52:03,560 --> 00:52:27,480
Speaker 1: how stuff works dot com.