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Speaker 1: Welcome to Stuff you Should Know from how Stuff Works

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Speaker 1: dot Com. Hey, and welcome to the podcast. I'm Josh Clark,

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Speaker 1: and there's Charles W. Chuck Bryant. There's Jerry over there

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Speaker 1: doing the robot, which means this is stuff you should know.

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Speaker 1: Robot stot. I knew i'd get a laughout. EA, sooner

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Speaker 1: or later? Did you do the robot? Can you do

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Speaker 1: the robot? I think I've seen you do pretty bad robot.

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Speaker 1: I don't know about pretty bad robot. I can do

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Speaker 1: a pretty great robot, that's what you've seen. I can't

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Speaker 1: do any of that stuff. Yeah, I can't really either,

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Speaker 1: and didn't really. If if you're claim to fame is

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Speaker 1: like a really great robot dance, I don't know, maybe

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Speaker 1: take up some other hobbies as well, kind of round

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Speaker 1: that out. You don't want them to be the only

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Speaker 1: thing you're good at, right, because if you list that

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Speaker 1: on the dating site, you might turn ladies off. Yeah,

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Speaker 1: according to e Harmony, Yeah, that's foreshadowing. I love that one,

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Speaker 1: don't you. Yeah, that's some issues with that whole Oh yeah, yeah,

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Speaker 1: we'll get to that. This is tad all right. Well,

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Speaker 1: let's start the at the beginning. Almost the beginning. Chuck,

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Speaker 1: let's go back to nineteen seventy, which was the beginning

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Speaker 1: of the greatest decade in the history of humanity. Yeah,

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Speaker 1: neither one of us were born yet I can finally

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Speaker 1: even say that I'm still not even born. It must

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Speaker 1: feel good. Yeah, okay, well, welcome to the club. I guess. Thanks.

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Speaker 1: And in nineteen seventy, we're not just going just anywhere

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Speaker 1: at nights seven, We're going to Japan in nineteen seventy.

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Speaker 1: Japan was pretty cool in the seventies. Yeah, a lot

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Speaker 1: of bell bottoms, a lot of ninja running around. Still, um,

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Speaker 1: there were calculators being wheelded all over the place. Probably

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Speaker 1: it was a good time, good good time for Japan, right,

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Speaker 1: and one of the one of the things that was

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Speaker 1: going on in nineteen seventy. I could not, for the

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Speaker 1: life of me find what issue of this journal it

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Speaker 1: came out in what month, But at some point in

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Speaker 1: nineteen seventy there was an obscure journal, a Japanese academic

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Speaker 1: journal called Energy, and at some point during that year

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Speaker 1: it published a article by a Japanese roboticist, and his

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Speaker 1: name is Massa Hiro Mori. Thank you, I have a

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Speaker 1: lot of practice, and uh, Massa Hiro Omori uh published

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Speaker 1: this article and he named it Bukimi no Tani gen

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Speaker 1: show is actually the full name of the whole thing.

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Speaker 1: And as we'll see, it's kind of difficult to translate

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Speaker 1: into English, right, and it took many, many years after

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Speaker 1: he wrote this article for it to be translated into

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Speaker 1: English for anybody even try to attempt it. So basically,

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Speaker 1: Mori was this robotic cyst and he wrote this essay

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Speaker 1: and at the time he just put it out there

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Speaker 1: and went back to work, started teaching more and more roboticists.

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Speaker 1: The whole new generation of roboticists learned under him and

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Speaker 1: his his work just kind of sat there. Um unobserved

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Speaker 1: that article, i should say, and then in two thousand

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Speaker 1: five a rough translation of it was leaked out wasn't

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Speaker 1: intended for publication, and the world entirely changed, right because

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Speaker 1: Massa Hiro Morty had in his article put his finger

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Speaker 1: on something that no one had before in his capacities

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Speaker 1: a roboticist and a human and that was what we

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Speaker 1: call today the uncanny Valley. Yeah, so that's um the

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Speaker 1: idea that, uh, you're making a robot and we'll see

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Speaker 1: this apply some more than just robots. But in his case,

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Speaker 1: you're making a robot and you want to make it

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Speaker 1: look like a person um, which I guess not all roboticists,

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Speaker 1: some of them like the clunky jets and style robots

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Speaker 1: like Rosy. But I guess if you're Mori, you're you're

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Speaker 1: on the path to designing lifelike robots. And the closer

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Speaker 1: you get to that lifelike look, everything's going great. Everything's

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Speaker 1: going great, people are like, this is so cool, this

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Speaker 1: is so cool, and then all of a sudden, people

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Speaker 1: go oh like right as it approaches it's most or basically,

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Speaker 1: when it reaches its most lifelike capacity, that this whoever's

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Speaker 1: making it can conjure people are repulsed by it. Yeah,

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Speaker 1: which is something that most people who ever hear of

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Speaker 1: the Uncanny Valley are like, yeah, you know, that's I've

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Speaker 1: noticed that. That's happened to me before too. But the

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Speaker 1: thing is, Chuck, it doesn't it doesn't actually make sense, right, Like,

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Speaker 1: we know a robot is a robot. Yeah, so you know,

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Speaker 1: maybe you could be afraid that it's gonna like pick

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Speaker 1: you up and break you in two or something like

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Speaker 1: a cartoon, but that's different than being creeped out by

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Speaker 1: like why would we be creeped out by a robot?

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Speaker 1: And this is what Morey put his finger on, was

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Speaker 1: there's something to this and it doesn't make sense, and

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Speaker 1: he he didn't. It wasn't even just um this article

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Speaker 1: that he wrote. He created a graph as well that's

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Speaker 1: become quite famous that um really kind of gets the

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Speaker 1: point across more than anything else. Yeah, And he wasn't

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Speaker 1: even the first person to to go over this and

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Speaker 1: to put a put some thought to it. Freud of course,

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Speaker 1: because he'd like to think about everything. He thought about

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Speaker 1: a little bit. And before Freud, there was a a

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Speaker 1: Geman name anst yinched. Oh nice. I did not realize

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Speaker 1: that's how his last name should be pronounced. That's good stuff.

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Speaker 1: I think I put a tea on the end, but

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Speaker 1: the teas in the middle, yinch. Yeah, I think that's right.

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Speaker 1: I've been saying, Gentch. We don't. We'll have to look

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Speaker 1: that up. Then. I think you're no. I think of

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Speaker 1: the two of us, you're you got the German down. Uh.

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Speaker 1: And he had a little term called um heimlich uh

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Speaker 1: that he called it so like you know, different languages

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Speaker 1: had different names for it. Um and you go back

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Speaker 1: in time, all the way back to like the seventeenth century,

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Speaker 1: and people were and I guess you know, robots didn't

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Speaker 1: look super lifelike back then, but whatever their version of

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Speaker 1: life like was. Uh. In the sixteen hundreds, people were like,

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Speaker 1: I don't like that. Why is it looking at me? Yeah,

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Speaker 1: it's got a quill and it's writing things. But like

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Speaker 1: you said, Maury made this graph because he was a roboticist,

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Speaker 1: and he thought, you know, let's look at this on

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Speaker 1: a plotted out so we can stare at it. And

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Speaker 1: on the X axis he had human likeness. Then on

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Speaker 1: the y axis he had affinity, like whether or not

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Speaker 1: you like the way this thing looks. And just as

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Speaker 1: we're talking about um, the graph went up and up

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Speaker 1: as uh, things got more lifelike and people like the

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Speaker 1: way look And then at a certain point there's that

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Speaker 1: valley there's a big dip. Uh. That really just kind

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Speaker 1: of says it all right, And again this all makes

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Speaker 1: sense intuitively, but as we'll see, that's it's been very

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Speaker 1: difficult to prove. And one of the reasons why it's

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Speaker 1: confounded research thus far is because we were not even

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Speaker 1: sure what more meant by some of the words he chose,

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Speaker 1: at least as far as translating them to English. Right.

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Speaker 1: Um For example, boukimi. Right, it was translated in two

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Speaker 1: thousand five as uncanny, but um again that that original

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Speaker 1: translation was not intended for publication, but it leaked out,

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Speaker 1: and so Uncanny Valley became, you know, the the way

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Speaker 1: we all think of it here in the West. But

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Speaker 1: boukimi more closely resembles something like eerie. Like I've seen

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Speaker 1: it explain that, Um, a word like boukimi means more

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Speaker 1: than uncanny is just weird or remarkable or noteworthy. It's

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Speaker 1: not necessarily something that gives you the creeps. Boukimi is

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Speaker 1: something that that gives you the creeps, like Steve Bukimi's exactly. Um.

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Speaker 1: So bukimi probably more should be should have been translated

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Speaker 1: the Eerie Valley. But by the time an actual official

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Speaker 1: translation that um Mori signed off on came out in

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Speaker 1: two thousand twelve, the cat was out of the bag.

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Speaker 1: Everybody knew of it as the Uncanny Valley, and there's

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Speaker 1: no way anybody who's gonna come back and be like, no, no, no,

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Speaker 1: everybody stop calling it that. It's now the Eerie Valley. Okay, right,

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Speaker 1: all right, And it may be one of those things

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Speaker 1: where we're so used to uncanny Valley now that it's

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Speaker 1: hard to imagine eerie Valley. But right, I think that

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Speaker 1: was the issue. Yeah, Like, nobody's gonna go along with that.

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Speaker 1: So this graph, like I said, it starts off on

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Speaker 1: that left hand side, and this is where you have

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Speaker 1: things that are super robotic. Um like you know, a

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Speaker 1: packaging robot in a factory, um that you know, apparently

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Speaker 1: most people don't have funness for I do because I

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Speaker 1: love mechanical processes, um right, right, Okay, So there's there's

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Speaker 1: part of the problem. It's like that's not necessarily the

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Speaker 1: kind of feeling that massa Hiro Morty was talking about.

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Speaker 1: He was like, yeah, yeah, you're interested in robotics and

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Speaker 1: robotic arms and the industrial processes, and you love watching

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Speaker 1: how it's made. Right. What he was talking about was

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Speaker 1: more like how it resembles a human and then how

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Speaker 1: it makes you feel in relation to its resemblance of

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Speaker 1: a human. Right. Well, in that case, it makes me

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Speaker 1: feel nothing because it doesn't look at all like a human. Right, Okay,

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Speaker 1: So that would be at about the origin of the graph.

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Speaker 1: It has no resemblance to a human really, and it's

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Speaker 1: not a listening any real affinity in you at all

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Speaker 1: as far as it looking like a human, right, but

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Speaker 1: lots of affinity as a thing that's just that's called props.

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Speaker 1: So you go a little bit further on the graph

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Speaker 1: and then you have things like um little stuffed animals

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Speaker 1: and uh no. C three po is is a common

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Speaker 1: one that's mentioned because C three p O UM, you know,

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Speaker 1: is built to look like a human. He does a

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Speaker 1: great robot. It talks like a human and acts like

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Speaker 1: a human. But when it comes to that face, and

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Speaker 1: as we'll see, the face is kind of the key

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Speaker 1: to all this um. For the most part, C three

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Speaker 1: po looks nothing like a human in the face. So

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Speaker 1: everything is still good and people love C three po. Right,

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Speaker 1: So if you're looking at the graph, C three p

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Speaker 1: o is going up in human likeness because he kind

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Speaker 1: of you know, he's got some some commonality there, and

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Speaker 1: we're feeling affinity for him based on that human likeness.

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Speaker 1: So it's he's going up. Okay, We're going everything's going

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Speaker 1: pretty well so far, right, Chuck, that's right, Okay, So

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Speaker 1: then we're gonna start hitting some areas where things start

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Speaker 1: looking a little more human, a lot more human, I

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Speaker 1: would say than c three p o, like say the

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Speaker 1: characters in mo Wanna or Frozen, uh picks our characters

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Speaker 1: that kind of thing where where they look like they're

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Speaker 1: supposed to be human, like they're based on human, but

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Speaker 1: they have very exaggerated features that you would never confuse

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Speaker 1: at first glance for an actual human. Right, So they

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Speaker 1: have like bi a guys, small noses, things that make

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Speaker 1: them cute, right, And so our affinity for them is

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Speaker 1: going up as the human likeness is going up. Again,

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Speaker 1: things are going really well so far, that's right, because

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Speaker 1: in Mowanna and Frozen they look a little bit more

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Speaker 1: like people, and we like them a lot more for

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Speaker 1: that reason. And then, like you said earlier, out of nowhere,

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Speaker 1: the whole thing, this line that's just been going up

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Speaker 1: very pleasantly, and a nice little slope just drops downward, right,

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Speaker 1: and it doesn't drop just downward, it goes actually below

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Speaker 1: the X axis into negative territory. And now this is

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Speaker 1: the Uncanny Valley, that's right, And that's why it has

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Speaker 1: that name because it's a valley, right, And this is

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Speaker 1: where those things like really really life like androids live,

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Speaker 1: or um corpses live, or zombies live. Because Maury he

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Speaker 1: he had the idea that if something's moving, is even

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Speaker 1: creepier than something similar to it that's not moving. So

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Speaker 1: he actually created two lines on this graph, one for

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Speaker 1: things that are animate and one for things that are inanimate.

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Speaker 1: So if you look at this uncanny valley on the

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Speaker 1: inanimate line, the non moving line, you've got corpses are

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Speaker 1: at the bottom of it. But if you look at

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Speaker 1: the animate line, it's even it dips even further below

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Speaker 1: than the inanimate line, and at the bottom of those

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Speaker 1: are zombies. So dead people up and moving around and

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Speaker 1: saying brains is as creepy as it gets as far

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Speaker 1: as this graph is concerned. Yeah, and he Maria wasn't

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Speaker 1: the only one that um earns yinch that we talked about.

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Speaker 1: The German psychiatrists. Uh. He also talked about the fact

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Speaker 1: that if you are looking at something that should not

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Speaker 1: be moving and it moves. Um, I mean, I think

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Speaker 1: we can all agree that a baby doll that suddenly

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Speaker 1: turns its head and looks at you probably one of

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Speaker 1: the creepier things you can witness, right, you know, Yeah,

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Speaker 1: it's about as creepy as it gets or um, have

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Speaker 1: you ever been to an open casket funeral? A few?

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Speaker 1: I'm not a fan at all. No, it is it

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Speaker 1: makes sense. You know, we've really kind of closed or

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Speaker 1: put a lot of space in between us and death,

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Speaker 1: way more than we used to have in like the

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Speaker 1: nineteenth century sit up with the dead. Sure, right, so

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Speaker 1: this seems to be like kind of a holdover from that.

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Speaker 1: But if you've ever been to uh an open casket

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Speaker 1: funeral and have just stared at the corpse long enough,

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Speaker 1: like maybe it's arm or it's fingers or something, your

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Speaker 1: brain is so anticipating that they it's about to start

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Speaker 1: moving that sometimes you can creep yourself out and and

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Speaker 1: make yourself think you did actually see it move. You'll

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Speaker 1: also be asked to leave the funeral. Well you shouldn't

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Speaker 1: be like giving a commentary about this out loud, but

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Speaker 1: you can. You know, you can do it to pass

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Speaker 1: the time in the funeral if you're looking to to

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Speaker 1: kill some time. Uh So, here's the thing with all this, Um,

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Speaker 1: we know this happens because everyone kind of has this feeling,

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Speaker 1: but no one and all this research has been done,

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Speaker 1: and no one is exactly sure why this happens. So, uh,

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Speaker 1: Maury's essay and especially once it was translated, Um, a

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Speaker 1: lot of research started happening in this area. And uh,

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Speaker 1: it's problematic though, because there are there are a few

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Speaker 1: different problems. One is, well, it's it's subjective. This dependent variable,

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Speaker 1: whether you have an affinity for something is very subjective,

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Speaker 1: so it's hard to kind of nail that down scientifically, right,

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Speaker 1: all right, So the number two is human likeness, right,

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Speaker 1: this is the independent variable. And if you have human likeness,

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Speaker 1: like what does that mean? Like what looks human? What

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Speaker 1: doesn't look human? But we haven't pinned that down. So like,

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Speaker 1: if you can't pin the dependent variable down and the

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Speaker 1: independent variable down, it makes it really tough to study correct.

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Speaker 1: And then there's a third one too. I love this one. Yeah.

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Speaker 1: The third one is, uh, you know, the original hypothesis.

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Speaker 1: It doesn't have a mathematical model that like really specifies

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Speaker 1: the shape of this curve, so it's still hypothetical, I guess, right,

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Speaker 1: Which means that so if you look at Mori's graph,

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Speaker 1: it was he just basically made a line, right, It

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Speaker 1: wasn't based on any studies he'd done. The whole thing

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Speaker 1: was really an essay more than anything else. UM. So,

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Speaker 1: researchers who are trying to seriously study the scientifically have

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Speaker 1: nothing that they're actually trying to place their findings against,

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Speaker 1: which leads to uh put it puts them at risk

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Speaker 1: for what's called the Texas sharpshooter fallacy. Greatest name fallacy

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Speaker 1: around and um it's it's based on the idea that

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Speaker 1: if you take a sharpshooter in Texas and have them

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Speaker 1: shoot at the side of a barn a bunch of times,

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Speaker 1: some of them are inevitably going to hit the barn,

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Speaker 1: and then the Texas sharpshooter walks up and then draws

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Speaker 1: the bull's eye around the bullets that he already sunk

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Speaker 1: into the side of the barn. That's the Texas sharpshooter fallacy.

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Speaker 1: It's ignoring data like the ones where he missed the

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Speaker 1: barn in favor of ones that fall into what you're

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Speaker 1: looking for, the bullet holes in the barn. You could

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Speaker 1: do the same thing with the um data that you

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Speaker 1: get from testing the Uncanny Valley if you have no

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Speaker 1: model to fit it into already. Yeah, I think they

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Speaker 1: would have done better if they would have just instead

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Speaker 1: of trying to prove something, uh, to maybe just research

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Speaker 1: and call it a thought experiment, you know, right, But

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Speaker 1: people are taking it seriously and we'll we'll talk about

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Speaker 1: some of this research right after this, chuck. Alright, So

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Speaker 1: we're back. And despite the fact that this is really

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Speaker 1: tough to study, it's not even established that it's a

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Speaker 1: real thing in everyone's mind. By the way, Um, there

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Speaker 1: there are people out there who are really studying the

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Speaker 1: Uncanny Valley and trying to pin it down. Yeah. One

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Speaker 1: of these people is at Dartmouth College psychologists. And I

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Speaker 1: didn't look up there mascot, the the the pub darts,

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Speaker 1: the fighting pub darts at Dartmouth College. We're gonna hear

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Speaker 1: from Dartmouth. But her name is Talia Wheatley. Um. And

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Speaker 1: she's done some research and has found that it's not

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Speaker 1: just like some uniquely Western thing or American thing. It's

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Speaker 1: kind of all over the world. She studied tribes and

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Speaker 1: Cambodia and they have the same sensitivities to these things

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Speaker 1: that look human but aren't human. Uh. And they've even

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Speaker 1: found that and I think it kind of all comes

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Speaker 1: down to the eyes. But they found just looking at

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Speaker 1: the eye can be enough. Yeah, Um, somebody can tell

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Speaker 1: whether it's a human or not just looking at a

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Speaker 1: picture of the eye, right. Yeah. And that's where I

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Speaker 1: think people lose credibility. And and we'll talk about movies

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Speaker 1: and sculpture and all that stuff, but they just never

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Speaker 1: get you can't get the eyes right, Like, you can't

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Speaker 1: put life in lifeless eyes? How are they try? Only

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Speaker 1: God can? Uh? And there was this other experiment where they, um,

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Speaker 1: you know, like where you can morph a face, uh

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Speaker 1: digitally or whatever like that Michael Jackson Black or White video. Yeah.

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Speaker 1: I think some people are creeped out by that even

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Speaker 1: but they would show this dull image and it would

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Speaker 1: morph into a human face. And basically they would have

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Speaker 1: people mark where they where they thought that it would

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Speaker 1: look more human than doll and it you know, it

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Speaker 1: landed about the mark as far as morphing into human,

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Speaker 1: which I mean you can't really apply that necessarily, but

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Speaker 1: just it's interesting. Offhand point is about where the Uncanny

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Speaker 1: Valley happened in Maury's mind. Yeah, I would think it

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Speaker 1: would be higher than that, but um, yeah, it's still

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Speaker 1: super interesting. Um. And you were saying that the eyes,

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Speaker 1: and that's what you're betting on is that it's going

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Speaker 1: to turn out to be the eyes, right. So, trying

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Speaker 1: to investigate what constitutes human likeness, there's a researcher named

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Speaker 1: Angela Tinwell, and she basically says, like, yes, it's all

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Speaker 1: about the upper facial features and that we we detect those,

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Speaker 1: we we read those, and so if there's any anything

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Speaker 1: that's even just slightly off in like you know, the eyes,

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Speaker 1: or the brows or the wrinkles, that form um that

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Speaker 1: will lead to the uncanny valley that's the creeping part

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Speaker 1: or the smile too. She also says, well, yeah, and

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Speaker 1: all these things kind of come down to evolution, and

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Speaker 1: her point is like, you can't battle millions of years

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Speaker 1: of evolution that his honed are our dumb, little human

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Speaker 1: brain to detect something that's off about a face. Uh,

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Speaker 1: it's just too much to overcome. Basically, this other researcher

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Speaker 1: named Carl F. McDorman, who's from the University of Indiana,

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Speaker 1: who actually he's basically like dedicated his career to this. Now. Um,

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Speaker 1: he found that certain kinds of people if you do

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Speaker 1: like a personality inventory before testing for uncanny Valley sensitivity,

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Speaker 1: some types of people are predictably more sensitive to the

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Speaker 1: Uncanny Valley than others. Specifically, he found that very religious

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Speaker 1: people that makes total sense. Yeah, neurotic people, um, and uh,

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Speaker 1: people with high sensitivity to animal reminders. It's basically anything

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Speaker 1: that reminds you that, hey, you're super civilized and you

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Speaker 1: drive a car and you know how to play poker. Um,

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Speaker 1: but you're still an animal, just as much as that

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Speaker 1: ape over there is an animal reminder. Um. People who

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Speaker 1: are sensitive to that kind of thing tend to go

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Speaker 1: off on the uncanny Valley as well. And then people

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Speaker 1: who are anxious are more likely to experience the uncanny

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Speaker 1: Valley as far as McDorman is concerned. Yeah, that interesting

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Speaker 1: makes sense too, because they're probably just more prone to

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Speaker 1: be I don't know, just have a reaction to a

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Speaker 1: lot of things like this. Right. But but we should

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Speaker 1: say the science and all this, the fact that the

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Speaker 1: independent and the dependent variable are still not defined, the

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Speaker 1: science is this. This is like the scientific equivalent of

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Speaker 1: that backward over the head half court basketball shot. Yeah,

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Speaker 1: that's the level of science that these people are carrying

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Speaker 1: out at this point because they're they're a lot of

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Speaker 1: them sadly are conducting experiments based on something that again

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Speaker 1: doesn't have a set dependent or independent variable. So how

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Speaker 1: can you do that? As my question, Well, yeah, I

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Speaker 1: mean because in each experiment, they're going to be using

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Speaker 1: different uh stimuli, um, different faces, whether it's a doll

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Speaker 1: or a wax figure or a c g I character,

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Speaker 1: And then they're gonna be doing different things and have

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Speaker 1: different expressions, and each person has their own subjective takes,

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Speaker 1: so it is very tough thing to kind of nail down. Yeah,

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Speaker 1: And I think some of them are actually trying to

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Speaker 1: form the basis of this field of study right now,

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Speaker 1: they're doing the groundwork. But I think some of them

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Speaker 1: also are like just chasing headlines, Like there's no better

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Speaker 1: way to get get into the media cycle with your

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Speaker 1: study than than releasing some five endings on the Uncanny

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Speaker 1: Valley people just love. Uh. One thing I thought was

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Speaker 1: interesting was, um, at Princeton they tried this with monkeys

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Speaker 1: and they found the same thing happened when they had

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Speaker 1: these realistic looking but fake monkey faces. The monkeys were

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Speaker 1: like it turned away. Um. It did make me think though,

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Speaker 1: like all the you've seen these situations where like an

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Speaker 1: orphaned animal has a a creepy puppet mother. Yeah, I

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Speaker 1: know exactly what you're talking about, and they seem to

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Speaker 1: like that. But however, and this is a bit of

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Speaker 1: a spoiler, but um, towards the end of this article,

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Speaker 1: it points out that human babies don't have this reaction

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Speaker 1: at first either, and that it's kind of learned. So

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Speaker 1: maybe that explains it. Maybe with the animals, I know

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Speaker 1: you're talking about that that cage, Like, why are monkey mother?

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Speaker 1: It's super creepy? Is it? Black and white photo? Well, no,

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Speaker 1: I mean they do it. There's all kinds of animals. Well,

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Speaker 1: they'll they have like a fake tiger or a fake

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Speaker 1: duck or whatever, just so the animal will feed or

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Speaker 1: I mean it's usually an animal that that milks from

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Speaker 1: the mother, I guess. But um, it's a common thing

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Speaker 1: they do for orphaned milk feeding or breastfeed animals. And

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Speaker 1: they're always creepy. Huh. Well, I mean to us, but

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Speaker 1: to a dumb baby monkey, they're just like, sweet give

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Speaker 1: me the teat. There's a T shirt maybe even a

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Speaker 1: band name sweet give Me the Teat. Yeah, yeah, that

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Speaker 1: kind of falls into the long band named category. But

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Speaker 1: here's the thing is, not everyone agrees with this. The

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Speaker 1: whole thing like you said earlier, there's a man named

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Speaker 1: David Hanson and he's a roboticist as well, and plain

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Speaker 1: oh Texas, and uh. He did a very very basic study.

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Speaker 1: It was a survey where they showed images of two

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Speaker 1: different robots that were animated to simulate human facial expressions

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Speaker 1: and basically just asked, Hey, what do you think of

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Speaker 1: this and said I like them? Yeah. Can you see

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Speaker 1: why people have trouble with this study? Though? Yeah, he

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Speaker 1: said not one person said they were disturbed. Okay, sounds

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Speaker 1: good for the most part, though, Studies into the uncanny

416
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Speaker 1: valley or like, now, we we're finding something here, although

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Speaker 1: we should be suspicious of ones that basically show the

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Speaker 1: uncanny valley that Moriy just graphed out of his like

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Speaker 1: with freehand, Like if you if you've come across the

420
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Speaker 1: study that shows that same thing, they're probably cherry picking data,

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Speaker 1: we got to say, out of his butt. Maybe there

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Speaker 1: was another study Edward Schneider at Suny Potsdam in New York.

423
00:25:48,720 --> 00:25:51,719
Speaker 1: I bet they don't even have a mascot. They got

424
00:25:51,800 --> 00:25:58,960
Speaker 1: together characters from cartoons and video games, everyone from Mickey

425
00:25:59,040 --> 00:26:04,199
Speaker 1: Mouse to law Acroft and who is very attractive by

426
00:26:04,200 --> 00:26:10,919
Speaker 1: the way she's a computer character. Yeah. Well no, I'm

427
00:26:10,960 --> 00:26:14,560
Speaker 1: talking about playing tomb Rater. Oh I never played. Yeah,

428
00:26:14,600 --> 00:26:16,480
Speaker 1: when it first came out, you know, I played tomb

429
00:26:16,520 --> 00:26:18,520
Speaker 1: Rater and I was like, oh, I look at her

430
00:26:18,800 --> 00:26:22,480
Speaker 1: act kind of hut. She Well, she's she gets a

431
00:26:22,520 --> 00:26:27,320
Speaker 1: lot of stuff done. That's very attractive. That's true. That means, well,

432
00:26:27,480 --> 00:26:31,359
Speaker 1: she travels a lot, she's an independent person. Yeah, that's

433
00:26:31,359 --> 00:26:32,960
Speaker 1: what I meant. I was attracted to her mind in

434
00:26:33,040 --> 00:26:37,000
Speaker 1: her adventures. Uh So, anyway, they asked people in this study, Um,

435
00:26:37,400 --> 00:26:40,440
Speaker 1: how attractive do you think these characters are? Or how

436
00:26:40,600 --> 00:26:43,560
Speaker 1: repulsive do you think they are? And again there was

437
00:26:43,880 --> 00:26:46,560
Speaker 1: um a graph with a dip in it at a

438
00:26:46,640 --> 00:26:53,600
Speaker 1: certain point, as you would expect. Yep. Careful, careful, everybody.

439
00:26:54,760 --> 00:26:57,920
Speaker 1: So if you're if you're a robot designer, right, one

440
00:26:57,960 --> 00:27:00,639
Speaker 1: of the things like even back in his essay written

441
00:27:00,640 --> 00:27:07,159
Speaker 1: in nine seventy, Masahiro Morey said, um, there's there's problems

442
00:27:07,200 --> 00:27:10,320
Speaker 1: here with movement. There's problems here with the smile. It

443
00:27:10,440 --> 00:27:14,480
Speaker 1: has something to do with the face, right, Um, and

444
00:27:14,920 --> 00:27:17,000
Speaker 1: it's somebody else said I don't remember who it was,

445
00:27:17,080 --> 00:27:19,360
Speaker 1: but there's there always seems to be a lag time

446
00:27:19,440 --> 00:27:23,399
Speaker 1: between how realistic a designer can make a robot and

447
00:27:23,600 --> 00:27:29,560
Speaker 1: how realistic a an engineer can make that robot look right,

448
00:27:30,040 --> 00:27:33,200
Speaker 1: and that that disconnected. Maury's mind was a big part

449
00:27:33,280 --> 00:27:35,240
Speaker 1: of the on Canny Valley, but he also seemed to

450
00:27:35,280 --> 00:27:39,760
Speaker 1: focus on the smile on the eyes and one of

451
00:27:39,840 --> 00:27:42,600
Speaker 1: the things that's at stake, like besides this just being

452
00:27:42,680 --> 00:27:46,959
Speaker 1: like an interesting topic of discussion, like, there are actual

453
00:27:47,280 --> 00:27:50,719
Speaker 1: real world implications for this whole thing, right, Like, if

454
00:27:50,720 --> 00:27:54,960
Speaker 1: you're a robot designer, you want to create something that's

455
00:27:55,000 --> 00:27:57,960
Speaker 1: not going to freak people out, because the whole purpose

456
00:27:58,040 --> 00:28:01,720
Speaker 1: of robots is to interact with humans, and you want

457
00:28:01,800 --> 00:28:04,040
Speaker 1: them to interact with humans. I should say life like

458
00:28:04,680 --> 00:28:08,399
Speaker 1: looking at robots, right, because like four motor companies ever

459
00:28:08,480 --> 00:28:12,160
Speaker 1: gonna buy an android that looks human to just work

460
00:28:12,240 --> 00:28:14,600
Speaker 1: on an assembly line when they can get the same

461
00:28:14,720 --> 00:28:17,560
Speaker 1: thing that does the same job cheaper when it just

462
00:28:17,680 --> 00:28:21,040
Speaker 1: looks like a robotic arm or something. Right, the whole

463
00:28:21,160 --> 00:28:24,760
Speaker 1: purpose of a lifelike looking robots because that robot is

464
00:28:24,800 --> 00:28:27,720
Speaker 1: being designed to interact with humans. And if you are

465
00:28:27,800 --> 00:28:30,960
Speaker 1: going to run into this spot, some people say it's

466
00:28:31,000 --> 00:28:33,600
Speaker 1: not even a valley. Some people think it's insurmountable a

467
00:28:33,680 --> 00:28:36,159
Speaker 1: cliff or a wall. So if you're gonna run up

468
00:28:36,160 --> 00:28:38,920
Speaker 1: against this, you want to figure out how to overcome

469
00:28:38,960 --> 00:28:40,920
Speaker 1: it because you don't want to creep people out with

470
00:28:41,040 --> 00:28:43,800
Speaker 1: your creations. Well, and you don't want to spend a

471
00:28:43,840 --> 00:28:49,160
Speaker 1: lot of money, um to develop a robotic Walmart greeter

472
00:28:49,920 --> 00:28:54,480
Speaker 1: at every store because it's it's happening like this is

473
00:28:54,560 --> 00:28:58,440
Speaker 1: coming people. Yeah, there's a robot called Geminoid F or

474
00:28:58,600 --> 00:29:01,360
Speaker 1: acterroid f depends on who you ask. I've also seen

475
00:29:01,400 --> 00:29:04,400
Speaker 1: he called Ellie, and she is out of this lab

476
00:29:04,520 --> 00:29:09,080
Speaker 1: by a guy named Hiroshi Ishiguro, and he is probably

477
00:29:09,160 --> 00:29:12,800
Speaker 1: the world's leading roboticist. If you've seen any life like android,

478
00:29:13,360 --> 00:29:16,760
Speaker 1: it probably came out of this guy's lab, right, And

479
00:29:17,080 --> 00:29:19,600
Speaker 1: she is starting to get out there in the world.

480
00:29:19,720 --> 00:29:23,920
Speaker 1: She's been a debriefer of soldiers coming back from more

481
00:29:24,040 --> 00:29:28,360
Speaker 1: with PTSD, based on the idea that they might share

482
00:29:28,440 --> 00:29:30,680
Speaker 1: more with a robot that they knew was just a

483
00:29:30,840 --> 00:29:34,560
Speaker 1: robot than they would an actual human. Um. She's in

484
00:29:34,640 --> 00:29:40,840
Speaker 1: a play. She stars as an android, right. And then

485
00:29:40,880 --> 00:29:45,520
Speaker 1: there's Casper. There's a little robot called Casper. Yeah, Casper

486
00:29:45,800 --> 00:29:49,960
Speaker 1: is a robot boy with a great cause created to

487
00:29:50,000 --> 00:29:54,520
Speaker 1: help children with autism learn to read facial emotions. If

488
00:29:54,560 --> 00:29:57,400
Speaker 1: you look up photos of both of these giminoid, f

489
00:29:58,280 --> 00:30:03,360
Speaker 1: uh looks great and really like Ishiguro is doing great,

490
00:30:03,400 --> 00:30:09,800
Speaker 1: great work. Casper looks terrifying, right, and so Casper is creepy.

491
00:30:10,080 --> 00:30:13,800
Speaker 1: But that's not his purpose at all, right, his purpose

492
00:30:13,920 --> 00:30:18,240
Speaker 1: is to like teach kids with autism how to connect.

493
00:30:18,720 --> 00:30:23,120
Speaker 1: But if he's repelling them through this uncanny valley, he's

494
00:30:23,160 --> 00:30:26,160
Speaker 1: defeating the purpose. Well, they should go to Ishi Gurro

495
00:30:26,920 --> 00:30:29,400
Speaker 1: and say, hey, we have this great cause, can you

496
00:30:29,480 --> 00:30:32,400
Speaker 1: make us something that doesn't look like the stuff of nightmares?

497
00:30:32,920 --> 00:30:36,920
Speaker 1: Right exactly? I wonder if Casper has been um effective,

498
00:30:37,280 --> 00:30:41,120
Speaker 1: you know, I don't know. I don't know. Now I

499
00:30:41,160 --> 00:30:44,440
Speaker 1: feel bad I didn't look into that. Well, I just

500
00:30:44,720 --> 00:30:47,800
Speaker 1: I don't know. He's very creepy looking. I agree wholeheartedly.

501
00:30:47,920 --> 00:30:50,760
Speaker 1: It's kind of like, no, he's not finished, get back

502
00:30:50,800 --> 00:30:54,160
Speaker 1: to the drawing board. Either that or and this is

503
00:30:54,240 --> 00:30:57,280
Speaker 1: what Morey said, like go the other way, like just

504
00:30:57,440 --> 00:31:01,520
Speaker 1: make him not um he himan at all, just cute

505
00:31:01,640 --> 00:31:06,160
Speaker 1: or approachable. So the robotists are not the only ones

506
00:31:06,200 --> 00:31:09,760
Speaker 1: who are facing this chuck. There is a a pretty

507
00:31:09,880 --> 00:31:15,400
Speaker 1: powerful moneyed contingent of people who are interested stakeholders in

508
00:31:15,640 --> 00:31:18,479
Speaker 1: overcoming the uncanny Valley, or at least figuring out if

509
00:31:18,560 --> 00:31:24,000
Speaker 1: it's totally insurmountable. And that is Hollywood. Yeah. Um, Hollywood

510
00:31:24,040 --> 00:31:27,600
Speaker 1: has a sort of a rich history of getting it

511
00:31:27,720 --> 00:31:32,600
Speaker 1: wrong when it comes to creepy c g I characters. Um.

512
00:31:33,480 --> 00:31:35,880
Speaker 1: Pixar had their very first short film. Actually it's called

513
00:31:35,920 --> 00:31:38,960
Speaker 1: Tin Toy, uh, a little five minutes short, and they

514
00:31:39,000 --> 00:31:41,320
Speaker 1: showed it to this you know, this proceded toy story

515
00:31:41,360 --> 00:31:43,560
Speaker 1: and everything. Yeah, it was actually kind of like the

516
00:31:44,000 --> 00:31:47,160
Speaker 1: outline of toy stories plot. Yeah, but they showed it

517
00:31:47,240 --> 00:31:50,080
Speaker 1: to test audiences and they made the mistake of making

518
00:31:50,960 --> 00:31:56,920
Speaker 1: the baby Billy look too realistic, and everyone loved Tin

519
00:31:57,000 --> 00:32:00,480
Speaker 1: Toy and everyone hated Billy. Yeah have you seen it?

520
00:32:00,960 --> 00:32:05,320
Speaker 1: Yeah yeah, yeah, he's pretty hateable for sure, and he

521
00:32:05,440 --> 00:32:08,720
Speaker 1: has the antagonist, but he he struck some chord with

522
00:32:08,880 --> 00:32:12,320
Speaker 1: viewers that that Pixar did not mean to strike. And

523
00:32:12,400 --> 00:32:15,840
Speaker 1: they actually, I mean, this is extraordinarily fortunate for Pixarre.

524
00:32:16,480 --> 00:32:19,760
Speaker 1: This is very early on in their history. And um,

525
00:32:20,280 --> 00:32:24,240
Speaker 1: they they learned from it. Actually they're like, Okay, note

526
00:32:24,280 --> 00:32:27,240
Speaker 1: to self, don't try to make any of these characters life. Like,

527
00:32:27,360 --> 00:32:30,200
Speaker 1: let's go a different direction, and so they came up

528
00:32:30,240 --> 00:32:35,880
Speaker 1: with those um exaggerated features that we've all just come

529
00:32:35,960 --> 00:32:39,440
Speaker 1: to know and love. Yeah, which was a great, great

530
00:32:39,520 --> 00:32:42,600
Speaker 1: direction to go in, obviously, because they've had tons of

531
00:32:42,640 --> 00:32:45,200
Speaker 1: success with that model. Right, you can make the case

532
00:32:45,280 --> 00:32:49,080
Speaker 1: that it may have saved the company because other companies

533
00:32:49,120 --> 00:32:52,520
Speaker 1: and other movies, for sure, have not been nearly as fortunate. Yeah.

534
00:32:52,880 --> 00:32:56,520
Speaker 1: One of the first big photo real computer animated movies

535
00:32:56,600 --> 00:33:00,720
Speaker 1: was Final Fantasy Colon the Spirits Within. You should never

536
00:33:00,800 --> 00:33:02,480
Speaker 1: have a colon in your movie title, by the way,

537
00:33:03,120 --> 00:33:06,080
Speaker 1: that was the first mistake. But this one was from

538
00:33:06,120 --> 00:33:10,160
Speaker 1: two thousand one and based on the video game, and

539
00:33:10,480 --> 00:33:13,600
Speaker 1: it was off putting to a lot of people, and

540
00:33:13,680 --> 00:33:16,880
Speaker 1: it was a big, big bomb for Columbia Pictures. And

541
00:33:17,040 --> 00:33:20,560
Speaker 1: but this is before Uncanny Valley had really been established,

542
00:33:20,800 --> 00:33:25,720
Speaker 1: before Maury's essay was translated, so reviewers didn't quite know

543
00:33:25,880 --> 00:33:28,160
Speaker 1: what to say. Now they would just say we've tumbled

544
00:33:28,200 --> 00:33:31,440
Speaker 1: into the Uncanny Valley again, but they would say things

545
00:33:31,520 --> 00:33:35,800
Speaker 1: like Peter Traver's great reviewer from Rolling Stone said, at first,

546
00:33:35,840 --> 00:33:41,680
Speaker 1: it's fun to watch the characters. Ellipsis ellipsips But what's

547
00:33:41,720 --> 00:33:43,880
Speaker 1: an ellipsis is that two of them, couple of them.

548
00:33:44,960 --> 00:33:46,840
Speaker 1: But then you notice a coldness in the eyes, a

549
00:33:46,920 --> 00:33:50,560
Speaker 1: mechanical quality in the movements, familiar voices emerging from the

550
00:33:50,640 --> 00:33:55,040
Speaker 1: mouths of replicants erect a distance. Yeah, so he's describing

551
00:33:55,080 --> 00:33:57,320
Speaker 1: young Canny Valley. He just didn't have the name of

552
00:33:57,440 --> 00:34:00,600
Speaker 1: it yet. Um. And then a couple of years later

553
00:34:01,120 --> 00:34:05,320
Speaker 1: the Polar Express, which became I think even more famous

554
00:34:05,400 --> 00:34:09,200
Speaker 1: than Final Fantasy as far as the Uncanny Valley goes.

555
00:34:09,560 --> 00:34:12,520
Speaker 1: But again, it's like you said, you know, the reviewers

556
00:34:12,600 --> 00:34:14,640
Speaker 1: didn't know how quite to put their finger on it,

557
00:34:15,160 --> 00:34:18,560
Speaker 1: and I'm not quite sure how Final Fantasy was done,

558
00:34:18,600 --> 00:34:23,239
Speaker 1: but I know that polar Express used similar um software

559
00:34:23,280 --> 00:34:29,239
Speaker 1: and hardware to what roboticists are using now, where it's

560
00:34:29,320 --> 00:34:32,719
Speaker 1: like motion capture, but rather than translating the motion to

561
00:34:33,080 --> 00:34:36,600
Speaker 1: the robot, it's translating the motion into like a digital

562
00:34:36,920 --> 00:34:42,240
Speaker 1: three D rendering of the character. Right, So polar Express

563
00:34:42,360 --> 00:34:47,120
Speaker 1: was really really expressive, but not quite there, so it

564
00:34:47,239 --> 00:34:50,520
Speaker 1: fell really hard in the Uncanny Valley, and um, I

565
00:34:50,640 --> 00:34:55,880
Speaker 1: think David Germaine of the Associated Press uh compared the

566
00:34:56,040 --> 00:35:00,400
Speaker 1: kids in this heartwarming family Christmas movie to the Children

567
00:35:00,480 --> 00:35:03,479
Speaker 1: from Village of the Damned, which is not what you want.

568
00:35:04,040 --> 00:35:06,200
Speaker 1: It's not at all what the studio wanted, and I

569
00:35:06,320 --> 00:35:08,959
Speaker 1: think it lost a pretty decent amount of money. Yeah,

570
00:35:09,320 --> 00:35:11,480
Speaker 1: there was another one of uh. And these are all,

571
00:35:11,719 --> 00:35:15,080
Speaker 1: by the way, courtesy of Robert Zemecas he really had

572
00:35:15,239 --> 00:35:19,719
Speaker 1: his He went all in on this technology. I don't

573
00:35:19,800 --> 00:35:22,960
Speaker 1: know why. I think he just I think sometimes you

574
00:35:23,080 --> 00:35:25,920
Speaker 1: as an artist, you can get so wrapped up and

575
00:35:26,840 --> 00:35:29,000
Speaker 1: the coolness of wow, look what we can do now

576
00:35:29,960 --> 00:35:33,360
Speaker 1: that you don't step back and look at what you're doing, like,

577
00:35:33,560 --> 00:35:38,120
Speaker 1: should should we be doing this? Because he also had

578
00:35:38,160 --> 00:35:41,359
Speaker 1: a part in the Bowolf movie in two thousand seven

579
00:35:41,400 --> 00:35:43,640
Speaker 1: that was a huge bomb. Um in The New York

580
00:35:43,719 --> 00:35:45,719
Speaker 1: Times said this about that people who are meant to

581
00:35:45,760 --> 00:35:48,600
Speaker 1: be enraged, who are at risk of plummeting to their deaths,

582
00:35:49,040 --> 00:35:51,279
Speaker 1: just look a little out of sorts. When it was over,

583
00:35:51,440 --> 00:35:53,880
Speaker 1: I felt relieved to be back in the company of

584
00:35:54,080 --> 00:35:59,319
Speaker 1: un creepy flesh and blood humans again. Sad and then uh,

585
00:35:59,800 --> 00:36:03,080
Speaker 1: just the Adventures of Tintin. Yeah, I really liked Tintin,

586
00:36:03,160 --> 00:36:06,520
Speaker 1: though I did too. I think Spielberg, I mean, there

587
00:36:06,760 --> 00:36:10,720
Speaker 1: is that Uncanny Valley a little bit, but the story

588
00:36:10,800 --> 00:36:13,560
Speaker 1: in the movie were so good he overcame that. I

589
00:36:13,640 --> 00:36:17,279
Speaker 1: think I was about to say, I think Spielberg has

590
00:36:17,320 --> 00:36:23,480
Speaker 1: come the closest to to overcoming that chasm of anybody.

591
00:36:23,719 --> 00:36:25,919
Speaker 1: But did he do it through good storytelling or through

592
00:36:26,120 --> 00:36:28,759
Speaker 1: the eyes I I don't know. I don't know if

593
00:36:28,840 --> 00:36:30,680
Speaker 1: it I don't know if it was a combination of

594
00:36:30,760 --> 00:36:35,000
Speaker 1: the two. Um, I don't know, but it is extraordinarily,

595
00:36:36,520 --> 00:36:39,680
Speaker 1: it's an extraordit. So you know those that that that

596
00:36:39,840 --> 00:36:41,719
Speaker 1: stuff you'll see every once a while, which somebody does

597
00:36:41,800 --> 00:36:44,200
Speaker 1: like what Beavis and butt Head would actually look like

598
00:36:44,320 --> 00:36:48,560
Speaker 1: in real life or what Charlie Brown was in real life. Right,

599
00:36:49,160 --> 00:36:53,200
Speaker 1: So it's still has kind of got a cartoonish quality

600
00:36:53,280 --> 00:36:55,760
Speaker 1: to it. It's the same thing with the Tintin movie.

601
00:36:56,320 --> 00:36:59,000
Speaker 1: But it was like it was as if you were

602
00:36:59,120 --> 00:37:03,480
Speaker 1: living in a dementia and where humans looked somewhat cartoonish.

603
00:37:04,840 --> 00:37:06,680
Speaker 1: Is that making any sense or does that just make

604
00:37:06,760 --> 00:37:09,040
Speaker 1: the whole thing even harder to understand? No? I get that.

605
00:37:09,480 --> 00:37:12,840
Speaker 1: So so he somehow was like, here, I'm not trying

606
00:37:12,920 --> 00:37:16,600
Speaker 1: to nail what humans look like. I'm going to take

607
00:37:16,640 --> 00:37:19,120
Speaker 1: you to another world where these people live and if

608
00:37:19,160 --> 00:37:21,319
Speaker 1: you lived in this world, you would look like this too.

609
00:37:21,400 --> 00:37:24,040
Speaker 1: It's it's weird. It's like he he bridged an uncanny

610
00:37:24,120 --> 00:37:26,959
Speaker 1: valley that doesn't exist in this dimension. Yeah, he built

611
00:37:27,000 --> 00:37:32,279
Speaker 1: a temporary disintegrating bridge across the uncanny valley. I think

612
00:37:32,320 --> 00:37:34,799
Speaker 1: the biggest example in recent years was, or the one

613
00:37:34,840 --> 00:37:37,480
Speaker 1: that got the most attention was in Rogue One. Did

614
00:37:37,560 --> 00:37:39,680
Speaker 1: you see that? The Star Wars movie? I haven't a

615
00:37:39,680 --> 00:37:41,840
Speaker 1: seen any of the new Star Wars ones except for

616
00:37:42,040 --> 00:37:46,239
Speaker 1: a seen the first six, I guess, but none of

617
00:37:46,280 --> 00:37:50,279
Speaker 1: the two new new ones. Uh. Well, in Rogue One,

618
00:37:50,640 --> 00:37:54,480
Speaker 1: they completely bring back to life Grand Moth Tarkin, who

619
00:37:55,080 --> 00:37:59,520
Speaker 1: was played by the deceased Peter Cushing, and they brought

620
00:37:59,600 --> 00:38:03,840
Speaker 1: him back as a character in this movie and in

621
00:38:03,960 --> 00:38:07,520
Speaker 1: the theater like when he when it first happens, he's

622
00:38:07,560 --> 00:38:09,320
Speaker 1: got his back to you and it's sort of in

623
00:38:09,360 --> 00:38:13,200
Speaker 1: the shadows and you're like, oh wow, like that's pretty cool.

624
00:38:13,400 --> 00:38:15,600
Speaker 1: And I didn't know that they would do that, but

625
00:38:15,760 --> 00:38:20,520
Speaker 1: they they got too comfortable, I think, and uh showed

626
00:38:20,560 --> 00:38:23,640
Speaker 1: too much and gave him too many lines and too

627
00:38:23,719 --> 00:38:28,480
Speaker 1: much light, and then it became uncanny Valley. Oh yeah,

628
00:38:28,600 --> 00:38:31,640
Speaker 1: for sure. I think about poor Peter Cushing's family having

629
00:38:31,719 --> 00:38:34,560
Speaker 1: to see that. Yeah, I don't know how often they

630
00:38:34,680 --> 00:38:37,479
Speaker 1: just weep during that that movie. Well, I'm curious about

631
00:38:37,520 --> 00:38:39,400
Speaker 1: like life rights and image rights and stuff like that,

632
00:38:39,480 --> 00:38:41,640
Speaker 1: if they had to get that cleared. I don't even

633
00:38:41,680 --> 00:38:44,400
Speaker 1: know that. I'm sure there's a backstory there. Cushing was

634
00:38:44,480 --> 00:38:48,200
Speaker 1: famously mellow that he would have taken a draw off

635
00:38:48,280 --> 00:38:51,360
Speaker 1: his DUBI and been like, that's whatever, man. Yeah, I

636
00:38:51,400 --> 00:38:53,200
Speaker 1: think he spent the last year of his life on

637
00:38:53,320 --> 00:38:58,200
Speaker 1: his weed farm in northern California. What about this Mars

638
00:38:58,360 --> 00:39:01,080
Speaker 1: Needs Moms. I had never ever heard of that movie,

639
00:39:01,160 --> 00:39:03,560
Speaker 1: and so I went and watched the trailer and it

640
00:39:03,719 --> 00:39:06,200
Speaker 1: still was like, I have no idea what this is. Yeah,

641
00:39:06,600 --> 00:39:09,719
Speaker 1: you know that comic strip bloom County. Well, you know,

642
00:39:09,840 --> 00:39:12,760
Speaker 1: I'm a huge, huge life along bloom County fan. Okay,

643
00:39:12,920 --> 00:39:15,520
Speaker 1: so Burke, so maybe you know how to say the

644
00:39:15,600 --> 00:39:21,719
Speaker 1: last name. It's Berkeley breathed, her breathed, But I don't

645
00:39:21,719 --> 00:39:23,560
Speaker 1: know if I've ever heard it said out loud breath.

646
00:39:23,600 --> 00:39:26,520
Speaker 1: It sounds nice. Let's go with that. So Berkeley brother,

647
00:39:26,719 --> 00:39:30,319
Speaker 1: the person, the guy who did bloom County. He wrote

648
00:39:30,360 --> 00:39:33,719
Speaker 1: a book, a children's book, called Mars Needs Moms, and

649
00:39:33,840 --> 00:39:37,400
Speaker 1: basically Mars had some sort of shortage of moms, so

650
00:39:37,760 --> 00:39:40,520
Speaker 1: the Martians came and kidnapped human moms and it was

651
00:39:40,600 --> 00:39:42,600
Speaker 1: up to the human kids to go get their moms

652
00:39:42,680 --> 00:39:45,719
Speaker 1: back from Mars. Right, pretty cute little premise, but they

653
00:39:45,800 --> 00:39:48,399
Speaker 1: took it and ran it through z Mecha's nightmare. Mill

654
00:39:49,360 --> 00:39:54,359
Speaker 1: Um Image Movers Digital was the was the trade name

655
00:39:54,400 --> 00:39:56,480
Speaker 1: of it, but everybody knew it's just steer clear of

656
00:39:56,560 --> 00:40:00,560
Speaker 1: this place, right, And this was like the Apex or

657
00:40:00,719 --> 00:40:04,480
Speaker 1: the what's the opposite of the Apex? The Valley, I guess,

658
00:40:04,560 --> 00:40:07,840
Speaker 1: so the deepest part of the c g I Valley

659
00:40:08,239 --> 00:40:12,000
Speaker 1: of the Uncanny Valley, right, it was what what the

660
00:40:12,040 --> 00:40:15,560
Speaker 1: stuff that they created? It was so off and just

661
00:40:15,680 --> 00:40:19,920
Speaker 1: so spectacularly and colostly off that when I guess Disney

662
00:40:20,000 --> 00:40:23,640
Speaker 1: came along and bought this company that came in looked

663
00:40:23,680 --> 00:40:27,120
Speaker 1: around and said, we're shutting you down. This movie is

664
00:40:27,120 --> 00:40:29,359
Speaker 1: that we're not doing this anymore. What you guys are

665
00:40:29,400 --> 00:40:33,200
Speaker 1: doing here is wrong, um, and you're all going to jail. Yeah,

666
00:40:33,280 --> 00:40:35,680
Speaker 1: here's my thoughts on that. I watched the trailer and

667
00:40:36,239 --> 00:40:38,319
Speaker 1: it didn't look any worse than any of the other

668
00:40:38,360 --> 00:40:40,759
Speaker 1: ones to me, and in fact I don't know the

669
00:40:40,840 --> 00:40:42,759
Speaker 1: character's names, but there's a kid and then there's this

670
00:40:42,840 --> 00:40:46,200
Speaker 1: one kind of chubby guy in Mars. The chubby guy

671
00:40:46,239 --> 00:40:49,160
Speaker 1: looked pretty good. Actually, I thought. I think this was

672
00:40:49,239 --> 00:40:52,800
Speaker 1: a victim. I bet the movie sucked really bad, and

673
00:40:52,920 --> 00:40:55,040
Speaker 1: I think it was the last straw the end of

674
00:40:55,120 --> 00:40:59,040
Speaker 1: all these Uncanny Valley failures. Yeah, because this again, this

675
00:40:59,200 --> 00:41:03,760
Speaker 1: is the same company that had created um Polar Express,

676
00:41:04,040 --> 00:41:07,000
Speaker 1: the Nightmare Factory, and a Christmas Carol did not do

677
00:41:07,239 --> 00:41:10,000
Speaker 1: very well either, So yeah, I think it. It definitely

678
00:41:10,120 --> 00:41:13,520
Speaker 1: bore the brunt of its predecessors as well. I but

679
00:41:13,640 --> 00:41:16,440
Speaker 1: I thought this was as bad as it got. If

680
00:41:16,480 --> 00:41:18,919
Speaker 1: you ask me, I totally saw what what Disney saw

681
00:41:19,560 --> 00:41:22,680
Speaker 1: with this one. Anytime something is marked as the thing

682
00:41:22,760 --> 00:41:26,399
Speaker 1: that killed the thing, right, it's always just the last thing. Yeah,

683
00:41:26,440 --> 00:41:29,640
Speaker 1: you're right, you know, yeah, but it could have also

684
00:41:29,719 --> 00:41:32,799
Speaker 1: been the thing that saved the thing had they gotten

685
00:41:32,840 --> 00:41:36,399
Speaker 1: it right. You know, that's true. So, like I said,

686
00:41:36,520 --> 00:41:38,799
Speaker 1: Mariy was like and every time I say Maury, now

687
00:41:38,880 --> 00:41:43,560
Speaker 1: unless I say it like Morty just saying Maury, think

688
00:41:43,640 --> 00:41:48,279
Speaker 1: I think of the Whigs, Salesman and Goodfellas is like

689
00:41:48,440 --> 00:41:51,440
Speaker 1: give me my money and ray leodis this in their

690
00:41:51,520 --> 00:41:55,120
Speaker 1: laughing because Morey's to pay falls off. Imagine that guy

691
00:41:55,280 --> 00:41:57,920
Speaker 1: is the guy who came up with the young Canny Valley. Okay,

692
00:41:58,239 --> 00:42:03,759
Speaker 1: it gives a full different spin too, right, So Maury says, um,

693
00:42:04,520 --> 00:42:07,160
Speaker 1: you just don't even try. Guys like you're never going

694
00:42:07,280 --> 00:42:09,560
Speaker 1: to be able to do this. Even if you can,

695
00:42:09,719 --> 00:42:11,800
Speaker 1: We're so far away from it. And this is the

696
00:42:12,480 --> 00:42:14,600
Speaker 1: vy he was saying it, and it still holds true.

697
00:42:14,680 --> 00:42:17,920
Speaker 1: Now we're so far away from this that that just

698
00:42:18,160 --> 00:42:22,240
Speaker 1: maybe put your put your emphasis elsewhere. And the example

699
00:42:22,320 --> 00:42:25,279
Speaker 1: he gave was say, like a prosthetic hand, right, rather

700
00:42:25,360 --> 00:42:28,719
Speaker 1: than trying to create a lifelike prosthetic hand, that that

701
00:42:29,000 --> 00:42:32,920
Speaker 1: was in danger of creeping people out, which is the

702
00:42:33,000 --> 00:42:36,480
Speaker 1: opposite of what somebody wearing a prosthetic hand wants when

703
00:42:36,520 --> 00:42:39,080
Speaker 1: they're walking around the prosthetic hand. He said, you know,

704
00:42:39,480 --> 00:42:44,160
Speaker 1: maybe choose some like like would well sanded beautifully grained

705
00:42:44,200 --> 00:42:47,319
Speaker 1: wood in the shape of a human hand. It gets

706
00:42:47,360 --> 00:42:49,839
Speaker 1: the point across this is my hand. I lost my hand,

707
00:42:49,880 --> 00:42:51,640
Speaker 1: I don't have my hand, but there's nothing to be

708
00:42:51,719 --> 00:42:54,480
Speaker 1: creeped out about here. It's kind of beautiful. Looking, isn't it.

709
00:42:55,040 --> 00:42:58,080
Speaker 1: That was Maury's take, and a lot of people side

710
00:42:58,160 --> 00:43:00,200
Speaker 1: with him as well. As a matter of fact, you know,

711
00:43:00,280 --> 00:43:02,239
Speaker 1: I said, I think at the beginning that he was

712
00:43:02,400 --> 00:43:06,680
Speaker 1: already an established roboticist when he wrote The Uncanny Valley

713
00:43:06,719 --> 00:43:09,759
Speaker 1: in NINEV and he went on to teach a lot

714
00:43:09,840 --> 00:43:13,399
Speaker 1: of people roboticists or a lot of roboticists as well.

715
00:43:13,760 --> 00:43:17,040
Speaker 1: And um, that very famous robot uh a s m

716
00:43:17,080 --> 00:43:21,000
Speaker 1: o Asmo, you know, the one I'm talking about. He

717
00:43:21,160 --> 00:43:23,280
Speaker 1: was one of the first ones that could jog in place.

718
00:43:23,520 --> 00:43:27,120
Speaker 1: And he's kind of humanoid for sure, but very cute,

719
00:43:27,320 --> 00:43:32,239
Speaker 1: all white, shiny lacquer plastic. You've seen him before. Um.

720
00:43:32,800 --> 00:43:36,560
Speaker 1: He was created by one of Morey's students, who clearly

721
00:43:36,640 --> 00:43:40,399
Speaker 1: subscribe to Maury's theory that you you're not gonna you're

722
00:43:40,440 --> 00:43:43,799
Speaker 1: not gonna overcome the Uncanny Valley. So just make these

723
00:43:43,880 --> 00:43:47,719
Speaker 1: things exaggerated and non human like, and you'll you'll have

724
00:43:47,880 --> 00:43:51,160
Speaker 1: people love your robot. Yeah. I think that's a good tech. Yeah,

725
00:43:51,719 --> 00:43:53,920
Speaker 1: all right, we're gonna take another break here and then

726
00:43:54,440 --> 00:43:57,160
Speaker 1: come back and finish up with a little bit. We're

727
00:43:57,160 --> 00:44:00,840
Speaker 1: gonna take a step back and just talk generally about creepiness,

728
00:44:22,200 --> 00:44:30,840
Speaker 1: all right, So I promised that we would talk about creepiness.

729
00:44:31,880 --> 00:44:36,360
Speaker 1: So that's what we'll do. The creeps such a great phrase.

730
00:44:36,680 --> 00:44:39,279
Speaker 1: Everyone says, it gives me the creeps. It's just such

731
00:44:39,360 --> 00:44:42,359
Speaker 1: a just It's one of those phrases that sums things

732
00:44:42,560 --> 00:44:47,120
Speaker 1: up so perfectly. It's livid as a fresh bruise. And um,

733
00:44:47,640 --> 00:44:51,240
Speaker 1: we have Charles Dickens to thank for this, evidently because

734
00:44:51,280 --> 00:44:54,280
Speaker 1: he gets credit for using the creeps. Uh In David

735
00:44:54,320 --> 00:44:59,560
Speaker 1: Copperfield in people had had this feeling before, this sort

736
00:44:59,600 --> 00:45:02,560
Speaker 1: of pleasn't off you know what it feels like to

737
00:45:02,600 --> 00:45:04,800
Speaker 1: get the creeps. But they said things like eel like

738
00:45:05,080 --> 00:45:08,120
Speaker 1: or clammy. Not bad, not bad. But if you said

739
00:45:08,840 --> 00:45:11,040
Speaker 1: that thing makes me feel eel like today, people be like,

740
00:45:11,200 --> 00:45:13,759
Speaker 1: what the heck are you talking about? Right? I think

741
00:45:13,800 --> 00:45:16,719
Speaker 1: also you would use that to describe somebody who gave

742
00:45:16,760 --> 00:45:18,960
Speaker 1: you the creeps as well, like that guy is really clammy,

743
00:45:20,480 --> 00:45:22,279
Speaker 1: you know what I mean? Sure? Well, that means you're

744
00:45:22,320 --> 00:45:25,280
Speaker 1: touching them though, like like Peter Lori would be clammy

745
00:45:25,400 --> 00:45:28,279
Speaker 1: or eel like in some of his characters. You know,

746
00:45:28,360 --> 00:45:33,800
Speaker 1: Peter Lourie, how do you too? Um, So everybody understands

747
00:45:33,840 --> 00:45:36,560
Speaker 1: that there is such thing as the creeps, right, but

748
00:45:38,120 --> 00:45:42,360
Speaker 1: we don't understand why we get the creeps still to

749
00:45:42,480 --> 00:45:44,759
Speaker 1: this day, and again this is important and relates it

750
00:45:44,800 --> 00:45:48,240
Speaker 1: on Canny Valley because another way to put the creeps

751
00:45:49,239 --> 00:45:53,719
Speaker 1: is negative affinity. Remember affinity was the x axis, and

752
00:45:53,880 --> 00:45:57,000
Speaker 1: when the valley dropped down below the x axis, you

753
00:45:57,120 --> 00:46:00,279
Speaker 1: dipped into negative affinity. You dip into the creep the

754
00:46:00,440 --> 00:46:06,160
Speaker 1: creeps exactly right. So you talked about um Ernst yinch Yeah, yeah,

755
00:46:06,239 --> 00:46:09,600
Speaker 1: I get it. It was probably the first person to

756
00:46:09,640 --> 00:46:15,040
Speaker 1: actually sit down and study the creeps or creepiness creepy himself.

757
00:46:15,440 --> 00:46:17,200
Speaker 1: I don't know. I think he was just kind of

758
00:46:17,280 --> 00:46:22,000
Speaker 1: a neat thinking man, right, So yinch Man, I like

759
00:46:22,120 --> 00:46:25,839
Speaker 1: saying his name a lot more now. He wrote an

760
00:46:26,000 --> 00:46:29,200
Speaker 1: essay in nineteen o six called on the Psychology of

761
00:46:29,320 --> 00:46:33,920
Speaker 1: the Uncanny and that's the English translation. Um. The German

762
00:46:34,040 --> 00:46:38,400
Speaker 1: word he used, like you said, is unheimlich, Is that right? Um?

763
00:46:38,600 --> 00:46:45,880
Speaker 1: Not unheimlich? Unheimlich Okay, better, thank you? Uh? He he

764
00:46:46,040 --> 00:46:49,680
Speaker 1: used that word, And unheimlich is a variation of the

765
00:46:49,719 --> 00:46:53,520
Speaker 1: word heimlich um, which is not just to say the maneuver,

766
00:46:54,040 --> 00:46:59,040
Speaker 1: It means something else entirely which is homie, we're familiar, right,

767
00:47:00,120 --> 00:47:04,000
Speaker 1: Unheimlich is the opposite of that. It's something strange and foreign,

768
00:47:04,360 --> 00:47:08,000
Speaker 1: and very frequently is translated into uncanny here in the West,

769
00:47:08,080 --> 00:47:13,359
Speaker 1: here here in in England. Yeah, and he he has, uh,

770
00:47:14,280 --> 00:47:15,880
Speaker 1: he thought a lot about this. And one of the

771
00:47:15,960 --> 00:47:18,200
Speaker 1: things that he noted, which I think thought was pretty interesting,

772
00:47:18,800 --> 00:47:23,399
Speaker 1: was that people that he thought were more intellectually discriminating, um,

773
00:47:24,160 --> 00:47:27,799
Speaker 1: are more prone to have these uncanny experiences because they're

774
00:47:27,880 --> 00:47:32,480
Speaker 1: critical thinkers about the world. Right, So, uh that makes sense,

775
00:47:32,560 --> 00:47:34,879
Speaker 1: Like just they pay attention maybe a little more, Yeah,

776
00:47:35,040 --> 00:47:37,200
Speaker 1: or they're curious, like they're they're like, why am I

777
00:47:37,280 --> 00:47:38,840
Speaker 1: creeped out? Let me get to the bottom of this,

778
00:47:39,000 --> 00:47:40,640
Speaker 1: rather than oh I'm creeped out him and then go

779
00:47:41,160 --> 00:47:44,000
Speaker 1: eat the whole thing at chips ahoy and hide under

780
00:47:44,040 --> 00:47:47,879
Speaker 1: the covers. Uh. He He also actually went even further

781
00:47:48,000 --> 00:47:52,360
Speaker 1: and said, it's it's possible that all of humanities knowledge

782
00:47:52,600 --> 00:47:56,759
Speaker 1: has been accrued over these millions of years from the

783
00:47:57,120 --> 00:48:02,320
Speaker 1: the people investigating what'spah this creepiness. It's a pretty weird

784
00:48:02,360 --> 00:48:06,400
Speaker 1: and neat theory of knowledge. Well, yeah, and speaking of theories,

785
00:48:06,400 --> 00:48:09,759
Speaker 1: there are a bunch of theories on creepiness, UM and

786
00:48:09,840 --> 00:48:12,000
Speaker 1: why this happens, and I think they're all pretty interesting.

787
00:48:12,800 --> 00:48:15,560
Speaker 1: The first one is called pathogen avoidance theory, and we

788
00:48:15,640 --> 00:48:19,440
Speaker 1: talked earlier about evolution and UM, this one kind of

789
00:48:19,480 --> 00:48:24,239
Speaker 1: fits into that bucket. Uh. Basically a warning that we

790
00:48:24,440 --> 00:48:28,360
Speaker 1: have evolved to have in our brain. It says that

791
00:48:28,600 --> 00:48:32,319
Speaker 1: person is off, they are diseased. Even you don't want

792
00:48:32,400 --> 00:48:35,520
Speaker 1: to go near them, you want to avoid that pathogen.

793
00:48:36,680 --> 00:48:40,879
Speaker 1: It makes sense. Yeah, it's pretty pretty approachable. Um. There's

794
00:48:40,880 --> 00:48:43,560
Speaker 1: another one that I've seen that I think fairly recent,

795
00:48:43,640 --> 00:48:48,560
Speaker 1: and it's the idea that things give us the creeps when, um,

796
00:48:49,280 --> 00:48:55,320
Speaker 1: when they're trying to nonverbally mimic people and so, like

797
00:48:55,440 --> 00:48:59,120
Speaker 1: a robot doesn't do it, so we're like, oh, that's unsettling.

798
00:48:59,560 --> 00:49:03,120
Speaker 1: Or somebody who you would describe as clammy or eel

799
00:49:03,160 --> 00:49:06,640
Speaker 1: like maybe overdes it a little bit, like they're trying

800
00:49:06,719 --> 00:49:10,239
Speaker 1: to fit in. It's not natural to them and that

801
00:49:10,520 --> 00:49:12,839
Speaker 1: can give you the creep as well. That makes sense,

802
00:49:12,960 --> 00:49:16,320
Speaker 1: but it doesn't really encompass everything. It's definitely not a

803
00:49:16,880 --> 00:49:19,480
Speaker 1: unified theory of creepiness. It just seems to kind of

804
00:49:19,560 --> 00:49:24,359
Speaker 1: inhabit one corner of the creepy spectrum. Yeah, there's another

805
00:49:24,400 --> 00:49:29,120
Speaker 1: one called violation of expectation. Um, this is like, you know,

806
00:49:29,280 --> 00:49:32,120
Speaker 1: you've shaken hands with thousands of people over your life.

807
00:49:32,560 --> 00:49:34,960
Speaker 1: But if you go and you shake a hand and

808
00:49:35,400 --> 00:49:37,680
Speaker 1: you don't know that you're going to get a prosthetic,

809
00:49:37,800 --> 00:49:41,279
Speaker 1: can it may give you the creeps? Uh? And that

810
00:49:41,880 --> 00:49:45,040
Speaker 1: is probably very fleeting because you might just say, oh, okay,

811
00:49:45,160 --> 00:49:47,120
Speaker 1: well it doesn't give me the creeps now, but it's

812
00:49:47,200 --> 00:49:50,480
Speaker 1: just unexpected for me. And actually you said that was fleeting, right, Chuck.

813
00:49:50,560 --> 00:49:54,320
Speaker 1: So I think it was uniche or somebody who said

814
00:49:55,120 --> 00:49:59,600
Speaker 1: that creepiness what gives us the creeps one time might

815
00:49:59,680 --> 00:50:02,480
Speaker 1: not of us the creeps later on, which will kind

816
00:50:02,520 --> 00:50:05,759
Speaker 1: of come into play later. Like Ernst n basically he

817
00:50:05,880 --> 00:50:09,080
Speaker 1: laid the groundwork for the study of creepiness and it

818
00:50:09,160 --> 00:50:11,520
Speaker 1: seems to have gotten a lot of it right right

819
00:50:11,560 --> 00:50:14,719
Speaker 1: out of the gate. Yeah. And like you said, if

820
00:50:14,760 --> 00:50:17,120
Speaker 1: it if it doesn't give you the creeps later, then

821
00:50:17,160 --> 00:50:21,160
Speaker 1: that would fit neatly into the violation of expectation because

822
00:50:22,120 --> 00:50:25,239
Speaker 1: then you can change your expectation right exactly. Yes. Yes,

823
00:50:25,960 --> 00:50:31,480
Speaker 1: another one's mortality salience theory. Yeah, this one, MORI and uh,

824
00:50:31,640 --> 00:50:35,480
Speaker 1: Freud both subscribed to and it basically said that, um,

825
00:50:36,200 --> 00:50:41,120
Speaker 1: we when we encounter like a robot or an automaton

826
00:50:41,320 --> 00:50:44,880
Speaker 1: in Freud's day, um, they remind us of dead people,

827
00:50:45,120 --> 00:50:47,279
Speaker 1: which in turn gets our mind to thinking about how

828
00:50:47,480 --> 00:50:49,400
Speaker 1: we're going to die one day. And so all of

829
00:50:49,440 --> 00:50:52,520
Speaker 1: a sudden we find ourselves in the uncanny valley right,

830
00:50:52,960 --> 00:50:56,240
Speaker 1: which again raises another sorry for the sidetrack, but raises

831
00:50:56,239 --> 00:51:01,960
Speaker 1: another of Unch's points. Um is uncanny nous inherent in

832
00:51:02,040 --> 00:51:05,920
Speaker 1: the object? Or is it inside the observer who's experiencing

833
00:51:06,000 --> 00:51:10,600
Speaker 1: the creeps or uncanny nous? I think it's in the observer. Yeah,

834
00:51:10,640 --> 00:51:12,680
Speaker 1: I think it is, too, which would explain why it

835
00:51:12,760 --> 00:51:16,400
Speaker 1: can go away when you when you come to experience

836
00:51:16,480 --> 00:51:19,520
Speaker 1: it again, like this, when you go through that, when

837
00:51:19,560 --> 00:51:22,720
Speaker 1: you shake the same prosthetic hand again, it's not creepy

838
00:51:22,840 --> 00:51:25,520
Speaker 1: the second time. It might even be interesting, or why

839
00:51:25,600 --> 00:51:29,000
Speaker 1: some people might not experience it at all. Like someone

840
00:51:29,120 --> 00:51:31,800
Speaker 1: might sit there and see a doll and the doll's

841
00:51:31,880 --> 00:51:34,000
Speaker 1: head turns and looks at them, and they're like, neat,

842
00:51:35,160 --> 00:51:37,520
Speaker 1: how much for that doll? Which means you've just met

843
00:51:37,560 --> 00:51:43,040
Speaker 1: a serial killer? And then the dolls creeped out after that, Uh,

844
00:51:43,200 --> 00:51:45,799
Speaker 1: this one, I like the UM even though I can

845
00:51:45,840 --> 00:51:51,640
Speaker 1: never say this word for some reason, and throw po morphism, dehumanization, dichotomy,

846
00:51:51,719 --> 00:51:55,320
Speaker 1: which basically as we attribute these human attributes to the

847
00:51:55,440 --> 00:52:00,680
Speaker 1: robot until we realize that they don't have them. Right. So, like,

848
00:52:00,800 --> 00:52:02,919
Speaker 1: we're looking at this robot that looks like a person.

849
00:52:03,000 --> 00:52:05,160
Speaker 1: We're saying, oh, look, it's just like a human. And

850
00:52:05,200 --> 00:52:07,080
Speaker 1: they're walking and they're talking and they're smiling, and then

851
00:52:07,120 --> 00:52:09,839
Speaker 1: oh god, look at their eyes. Their eyes are dead.

852
00:52:09,920 --> 00:52:12,080
Speaker 1: Look at the eyes. They don't they don't have any

853
00:52:12,200 --> 00:52:15,680
Speaker 1: internal thoughts at all. They're not human. And then all

854
00:52:15,680 --> 00:52:18,640
Speaker 1: of a sudden, on Canny Valley, which is a little

855
00:52:18,640 --> 00:52:22,080
Speaker 1: bit about expectation too. I think there's a crossover a little,

856
00:52:22,120 --> 00:52:27,840
Speaker 1: I think, and so creepiness, I think, especially the modern

857
00:52:28,040 --> 00:52:31,840
Speaker 1: incarnation of creepiness. This is my These are my thoughts.

858
00:52:32,320 --> 00:52:37,800
Speaker 1: They seem to be They represent a crossroads right where evolutionarily,

859
00:52:38,520 --> 00:52:43,480
Speaker 1: creepiness I think UM was probably it's alerts us. We're

860
00:52:43,520 --> 00:52:46,560
Speaker 1: on alert when something's creeping us out. We're really focused

861
00:52:46,600 --> 00:52:50,400
Speaker 1: on that thing, right then. But we're also bound by

862
00:52:50,520 --> 00:52:54,160
Speaker 1: society not to just turn and run from anything that

863
00:52:54,280 --> 00:52:57,080
Speaker 1: could conceivably be a threat. You can also take it

864
00:52:57,120 --> 00:53:00,719
Speaker 1: a little further and say that evolutionarily speaking, it would

865
00:53:00,760 --> 00:53:02,560
Speaker 1: not make sense for us to turn and run from

866
00:53:02,640 --> 00:53:05,359
Speaker 1: every single thing that could conceivably be a threat before

867
00:53:05,480 --> 00:53:07,759
Speaker 1: we've identified it as a threat, because we would be

868
00:53:07,840 --> 00:53:10,320
Speaker 1: using up a lot of calories and energy, and we

869
00:53:10,360 --> 00:53:12,239
Speaker 1: would have to find more food than we do. Would

870
00:53:12,239 --> 00:53:15,440
Speaker 1: be inefficient. Right, So we're kind of bound socially to

871
00:53:15,560 --> 00:53:19,120
Speaker 1: stand in place until we identify something as a threat

872
00:53:19,200 --> 00:53:23,319
Speaker 1: or not, in which case, during this period, that's when

873
00:53:23,360 --> 00:53:27,560
Speaker 1: we experience creepiness. Yeah, and I think everyone has experienced this. Um.

874
00:53:27,680 --> 00:53:30,360
Speaker 1: Like you're in a coffee shop or something and like

875
00:53:30,520 --> 00:53:34,920
Speaker 1: some super creepy dude comes in, and if you're liking me,

876
00:53:35,040 --> 00:53:38,399
Speaker 1: you're just like, um, all right, I'm gonna I'm gonna

877
00:53:38,480 --> 00:53:40,719
Speaker 1: keep my eye on that guy. I'm not I'm not

878
00:53:40,760 --> 00:53:44,160
Speaker 1: gonna bolt and run, but it might stay near the door. Sure,

879
00:53:44,440 --> 00:53:48,680
Speaker 1: you know, I might get my car keys ready, exactly right. Uh,

880
00:53:49,080 --> 00:53:52,520
Speaker 1: it is, it's this weird social contract, um, And you

881
00:53:52,600 --> 00:53:55,719
Speaker 1: know I feel bad for people that just inherently look

882
00:53:55,760 --> 00:53:59,640
Speaker 1: a little creepy. Well, yeah, let's talk about that. So

883
00:53:59,800 --> 00:54:02,520
Speaker 1: the was these there were these researchers from Knox College

884
00:54:02,760 --> 00:54:05,960
Speaker 1: who did what they build is the first empirical study

885
00:54:06,000 --> 00:54:09,839
Speaker 1: of creepiness. And this is in two thousand sixteen. And um,

886
00:54:10,040 --> 00:54:13,560
Speaker 1: it was an online survey, very little heavy lifting, but

887
00:54:13,680 --> 00:54:16,640
Speaker 1: it was a pretty pretty cool survey. It was in

888
00:54:16,760 --> 00:54:22,359
Speaker 1: four parts, and UM. What they found overall was that, Yeah,

889
00:54:22,680 --> 00:54:27,920
Speaker 1: physical characteristics, physical traits that are almost stereotypically linked to

890
00:54:28,280 --> 00:54:33,080
Speaker 1: creepy people do have an effect. They are creepy. Um,

891
00:54:33,840 --> 00:54:37,200
Speaker 1: as far as as the participants in this study are concerned.

892
00:54:38,320 --> 00:54:42,160
Speaker 1: So the first section said, hey, you know what, what

893
00:54:42,360 --> 00:54:45,440
Speaker 1: is the likelihood that this person is creepy? And there's like,

894
00:54:45,880 --> 00:54:50,799
Speaker 1: you know, descriptions of them with forty four different behaviors. Right. Um.

895
00:54:51,160 --> 00:54:54,680
Speaker 1: And the second part was participants rated the creepiness of

896
00:54:54,719 --> 00:55:01,279
Speaker 1: twenty one different occupations. Um. The third section it said,

897
00:55:01,400 --> 00:55:04,960
Speaker 1: list two hobbies that you think are creepy. They only

898
00:55:05,040 --> 00:55:07,759
Speaker 1: needed to it was open ended to. And then the

899
00:55:07,880 --> 00:55:11,520
Speaker 1: last section, um, the participants said whether or not they

900
00:55:11,560 --> 00:55:15,919
Speaker 1: agreed with fifteen statements about the nature of creepy people. Yeah.

901
00:55:16,520 --> 00:55:19,360
Speaker 1: And overall, again like they found like, yes, if you

902
00:55:19,480 --> 00:55:23,280
Speaker 1: have physical traits that people find creepy, like bulging eyes

903
00:55:23,480 --> 00:55:26,200
Speaker 1: or you lick your lips a lot, or you know,

904
00:55:26,400 --> 00:55:28,759
Speaker 1: your you arch your fingers and then just kind of

905
00:55:28,840 --> 00:55:33,440
Speaker 1: tap them together a lot. Okay, it's kind of creepy,

906
00:55:33,560 --> 00:55:38,200
Speaker 1: but the Knox researchers concluded that those aren't creepy necessarily

907
00:55:38,320 --> 00:55:41,080
Speaker 1: in and of themselves. It's when it's in conjunction with

908
00:55:41,239 --> 00:55:47,920
Speaker 1: other creepy behavior that somebody comes across as creepy. Right. Uh.

909
00:55:48,080 --> 00:55:50,279
Speaker 1: And of course, the one behavior they put in here

910
00:55:50,280 --> 00:55:53,359
Speaker 1: I think that was probably universally creepy was someone who

911
00:55:53,440 --> 00:55:57,919
Speaker 1: persistently steers the conversation towards a sexual topic, right, yeah,

912
00:55:58,000 --> 00:56:00,800
Speaker 1: you don't, you don't do that. They they also found

913
00:56:01,560 --> 00:56:05,320
Speaker 1: they also found of participants, and this is like, I

914
00:56:05,400 --> 00:56:10,439
Speaker 1: think eight hundred and forty one people of them said

915
00:56:10,480 --> 00:56:13,440
Speaker 1: that men were more likely to be creepy than women.

916
00:56:14,560 --> 00:56:18,680
Speaker 1: I think that's generally true. Um. I don't remember getting

917
00:56:18,680 --> 00:56:22,600
Speaker 1: the creeps a lot in my life by uh, strictly

918
00:56:23,040 --> 00:56:26,040
Speaker 1: from the appearance of a woman, right, but a lot

919
00:56:26,200 --> 00:56:28,320
Speaker 1: of dudes on a weekly basis give me the creeps.

920
00:56:29,400 --> 00:56:31,759
Speaker 1: But we we should say so. There's a website called

921
00:56:31,840 --> 00:56:35,160
Speaker 1: girl dot com g u r l dot com and

922
00:56:35,360 --> 00:56:37,400
Speaker 1: they went on to read it and found a thread

923
00:56:37,480 --> 00:56:40,160
Speaker 1: somewhere that they wrote a blog post about and now

924
00:56:40,239 --> 00:56:43,520
Speaker 1: we're reporting on it, so it's really come full circle.

925
00:56:44,520 --> 00:56:47,240
Speaker 1: But it was a threat about how women can be creepy,

926
00:56:47,400 --> 00:56:51,359
Speaker 1: and it was written by dudes, and um, there are

927
00:56:51,480 --> 00:56:57,480
Speaker 1: some things that apparently are universally creepy among boys with women, right,

928
00:56:58,560 --> 00:57:02,359
Speaker 1: Women that are too needy can be creepy. Women who

929
00:57:02,480 --> 00:57:06,279
Speaker 1: use baby talk too much, or who quote never leave

930
00:57:06,320 --> 00:57:10,239
Speaker 1: a guy alone. Yeah, I just I'm just gonna go

931
00:57:10,280 --> 00:57:14,160
Speaker 1: ahead and dump that right into the trash ben. That's

932
00:57:14,200 --> 00:57:18,320
Speaker 1: my only comment on that. Okay, what about e harmony?

933
00:57:18,560 --> 00:57:21,280
Speaker 1: I mean, if you come home and Glenn closes in

934
00:57:21,320 --> 00:57:26,720
Speaker 1: your kitchen boiling your pet bunny, well, that's a threat. Yeah,

935
00:57:26,760 --> 00:57:29,920
Speaker 1: that's not even creepy. That's just a threat. Although I

936
00:57:29,960 --> 00:57:34,440
Speaker 1: will say in Fatal Attraction, the the scene where she

937
00:57:34,680 --> 00:57:37,920
Speaker 1: is sitting there clicking the light on and off, listening

938
00:57:37,960 --> 00:57:40,760
Speaker 1: to Mad and Butterfly, that was that was kind of creepy.

939
00:57:41,160 --> 00:57:45,040
Speaker 1: I was trying to think of like a creepy woman,

940
00:57:45,240 --> 00:57:47,920
Speaker 1: and I really couldn't come up with anybody. Well, these

941
00:57:47,960 --> 00:57:51,120
Speaker 1: are creepy behaviors, though, you know, not like Glenn cost

942
00:57:51,160 --> 00:57:53,400
Speaker 1: Close walked into the room and you're like, oh, I

943
00:57:53,440 --> 00:57:57,920
Speaker 1: don't know about that, right, right, right, there's a difference

944
00:57:58,600 --> 00:58:02,360
Speaker 1: right there. There's a difference between genuine creepiness and just

945
00:58:02,480 --> 00:58:05,600
Speaker 1: doing creepy things. I think it is much harder for

946
00:58:05,640 --> 00:58:08,000
Speaker 1: women to be creepy than men. Cannot think of a

947
00:58:08,120 --> 00:58:16,080
Speaker 1: single actual creepy woman I'd like to hear from people, though. Yeah. Uh,

948
00:58:16,240 --> 00:58:20,439
Speaker 1: e harmony. So we talked about Reddit. Now we're gonna

949
00:58:20,480 --> 00:58:23,480
Speaker 1: talk about e harmony. They had an article where they

950
00:58:23,560 --> 00:58:26,560
Speaker 1: wrote advice to dudes. It was called how to Avoid

951
00:58:26,600 --> 00:58:32,400
Speaker 1: the creep Zone, um, and their advice was for your

952
00:58:32,480 --> 00:58:35,640
Speaker 1: hobbies that you list to be just sort of vanilla,

953
00:58:36,400 --> 00:58:40,400
Speaker 1: don't like and even if you are an amateur taxidermist,

954
00:58:40,800 --> 00:58:44,520
Speaker 1: maybe don't put that down right. They said, it can

955
00:58:44,600 --> 00:58:46,800
Speaker 1: be attractive for a guy to have an off the

956
00:58:46,880 --> 00:58:50,440
Speaker 1: beaten path hobby, and one of the examples they gave

957
00:58:50,520 --> 00:58:54,080
Speaker 1: of an off the beaten path hobby was collecting punk records.

958
00:58:55,440 --> 00:58:58,600
Speaker 1: But don't get weirder than that. Yeah, and if you

959
00:58:58,680 --> 00:59:01,360
Speaker 1: know taxidermy in and of itself, some people might say

960
00:59:01,400 --> 00:59:03,360
Speaker 1: a super creepy. We did an episode on that. Other

961
00:59:03,440 --> 00:59:06,600
Speaker 1: people might say, no, it's just just beautiful artwork. But

962
00:59:07,280 --> 00:59:09,480
Speaker 1: Norman Bates was in a taxidermy for a reason. In

963
00:59:09,560 --> 00:59:14,440
Speaker 1: Psycho it was unsettling. Yeah, you know, yeah, and so

964
00:59:14,840 --> 00:59:20,080
Speaker 1: um there the Knox people who carried out this survey,

965
00:59:20,480 --> 00:59:24,160
Speaker 1: the Knox University researchers, they basically said, here's what we

966
00:59:24,280 --> 00:59:28,200
Speaker 1: think it is. Here's creepiness explained. And what they explained

967
00:59:28,360 --> 00:59:33,360
Speaker 1: was what can be called is the threat ambiguity um theory. Yeah,

968
00:59:33,440 --> 00:59:35,080
Speaker 1: this this one, I think we kind of put a

969
00:59:35,160 --> 00:59:37,240
Speaker 1: cherry on top on this one. Yeah, we really did

970
00:59:37,320 --> 00:59:40,200
Speaker 1: like it. It's just basically where you are creeped out

971
00:59:40,200 --> 00:59:43,280
Speaker 1: by something because your hackles are raised right then, and

972
00:59:44,040 --> 00:59:46,640
Speaker 1: it's because you haven't determined whether that things a threat

973
00:59:46,760 --> 00:59:51,360
Speaker 1: or not. Right. There's another one though that I subscribe to.

974
00:59:51,600 --> 00:59:55,560
Speaker 1: I think it is finally the unified theory of creepiness.

975
00:59:55,640 --> 00:59:58,880
Speaker 1: I think it covers everything. And it's called the category

976
00:59:59,000 --> 01:00:04,320
Speaker 1: ambiguity theory. Yeah. That was Now did David Livingstone Smith

977
01:00:04,680 --> 01:00:07,320
Speaker 1: make this up or was he just champion this? I

978
01:00:07,920 --> 01:00:10,880
Speaker 1: think he made it up because he wrote about the

979
01:00:11,040 --> 01:00:14,200
Speaker 1: Knox researchers and said, what they're talking about you can

980
01:00:14,280 --> 01:00:19,520
Speaker 1: call threat ambiguity category or threat ambiguity theory with category

981
01:00:19,560 --> 01:00:22,160
Speaker 1: ambiguity theory. He didn't cite anybody else, so it seemed

982
01:00:22,160 --> 01:00:25,080
Speaker 1: to be his own construct. Yeah, so this is the idea.

983
01:00:25,280 --> 01:00:28,240
Speaker 1: It's sort of like the threat ambiguity in that there

984
01:00:28,360 --> 01:00:32,320
Speaker 1: is some confusion, but it's not a threat like I

985
01:00:32,360 --> 01:00:34,400
Speaker 1: think this dude in the coffee shop is gonna kill me.

986
01:00:34,560 --> 01:00:38,439
Speaker 1: It's more like I don't know how to categorize that guy,

987
01:00:39,040 --> 01:00:42,200
Speaker 1: and that freaks me out. And it's based on what's

988
01:00:42,240 --> 01:00:45,880
Speaker 1: called um essential is um right, where if you are

989
01:00:46,000 --> 01:00:49,160
Speaker 1: a member of a species of animal, whether human or

990
01:00:49,320 --> 01:00:54,440
Speaker 1: raccoon or tiger, there's something about you where there's some

991
01:00:54,720 --> 01:00:58,680
Speaker 1: collection or set of things about you that that are

992
01:00:59,320 --> 01:01:04,640
Speaker 1: totally unique to your species. It's something you possess because

993
01:01:04,720 --> 01:01:08,000
Speaker 1: you remember that species, and because you remember that species,

994
01:01:08,280 --> 01:01:10,840
Speaker 1: you possess these things, and it can be very difficult

995
01:01:11,080 --> 01:01:12,840
Speaker 1: to put your finger on it, but it's just one

996
01:01:12,880 --> 01:01:15,000
Speaker 1: of those things that you know when you see it,

997
01:01:15,160 --> 01:01:17,400
Speaker 1: or no, when you don't see it right, and there

998
01:01:17,400 --> 01:01:21,200
Speaker 1: are clear borders between these things. You either have this

999
01:01:21,440 --> 01:01:23,800
Speaker 1: essence fully or you don't have it at all. You're

1000
01:01:23,840 --> 01:01:27,000
Speaker 1: lacking and you're missing it and something's really wrong. So

1001
01:01:27,280 --> 01:01:29,800
Speaker 1: in this article he used UM the example of a

1002
01:01:29,840 --> 01:01:32,760
Speaker 1: wax dummy. Yeah, have you ever been to like Madame

1003
01:01:32,800 --> 01:01:36,360
Speaker 1: Tusso's um, I find that the ones and again with

1004
01:01:36,440 --> 01:01:38,920
Speaker 1: the eyes, the ones that work the best, or the

1005
01:01:39,000 --> 01:01:43,120
Speaker 1: ones where they have sunglasses on. Oh yeah again Michael Jackson,

1006
01:01:43,680 --> 01:01:46,240
Speaker 1: that's right. But the whole point with these wax dummies

1007
01:01:46,400 --> 01:01:49,840
Speaker 1: with the eyes is they're fixed. They're not moving around.

1008
01:01:50,160 --> 01:01:53,920
Speaker 1: The facial expression is locked in. Um, the skin itself.

1009
01:01:54,040 --> 01:01:56,720
Speaker 1: You know, you can only do so much. And Madame

1010
01:01:56,840 --> 01:01:59,920
Speaker 1: Tussos and museums like that are the best of the best,

1011
01:02:00,200 --> 01:02:02,560
Speaker 1: and they do look pretty good. But that's the whole

1012
01:02:02,600 --> 01:02:06,800
Speaker 1: point with the Uncanny Valley is you can't get there

1013
01:02:07,560 --> 01:02:10,120
Speaker 1: and say we're fine. It's that one per cent that

1014
01:02:10,280 --> 01:02:15,200
Speaker 1: still gives people the creeps exactly. And that's and it

1015
01:02:15,320 --> 01:02:18,400
Speaker 1: sums up everything, like the threat ambiguity could fall into this,

1016
01:02:18,840 --> 01:02:21,400
Speaker 1: whether you're talking about robots, whether you're talking about a

1017
01:02:21,960 --> 01:02:26,040
Speaker 1: half dog half lizard combo. Which living stone sites are

1018
01:02:26,080 --> 01:02:30,560
Speaker 1: living stones smith sites? Yeah, a dessert would be creepy

1019
01:02:30,600 --> 01:02:33,760
Speaker 1: when you saw it, But so things that are a

1020
01:02:33,840 --> 01:02:37,640
Speaker 1: threat are creepy. But there's also things that are creepy

1021
01:02:37,720 --> 01:02:40,840
Speaker 1: that aren't a threat. And this category ambiguity theory figured

1022
01:02:40,880 --> 01:02:45,080
Speaker 1: it out. So if that's true, Chuck and David Livingstone

1023
01:02:45,120 --> 01:02:47,920
Speaker 1: Smith figured out what is the basis of creepiness. We

1024
01:02:48,240 --> 01:02:54,560
Speaker 1: finally have the independent variable licked and massa hiro Morty's

1025
01:02:54,800 --> 01:02:57,920
Speaker 1: Uncanny Valley graph and we can get to work. Is

1026
01:02:58,000 --> 01:03:01,680
Speaker 1: he still around? Yeah? Yes, when that's happy about all this?

1027
01:03:03,440 --> 01:03:06,880
Speaker 1: I get the impression that he's kind of like just whatever,

1028
01:03:07,240 --> 01:03:10,400
Speaker 1: gone off on his own little thing, and he's fine.

1029
01:03:10,920 --> 01:03:13,560
Speaker 1: He wrote it in v after all, you know, I

1030
01:03:13,600 --> 01:03:17,120
Speaker 1: mean most fifty years ago, so he's probably up there.

1031
01:03:19,080 --> 01:03:22,160
Speaker 1: Uh you anything else? I got nothing else? Good ones? Yeah,

1032
01:03:22,520 --> 01:03:24,439
Speaker 1: if you want to know more about the Uncanny Valley,

1033
01:03:24,560 --> 01:03:27,320
Speaker 1: we should say this was based originally on a grabsto article.

1034
01:03:28,600 --> 01:03:30,560
Speaker 1: But if you want to know more about the Uncanny Valley,

1035
01:03:30,600 --> 01:03:33,280
Speaker 1: come read that grab Sto article. You can type Uncanny

1036
01:03:33,360 --> 01:03:35,439
Speaker 1: Valley and the search bar at how stuff works dot com.

1037
01:03:35,840 --> 01:03:41,080
Speaker 1: And since I said search bars, time for listener mail. Well,

1038
01:03:41,160 --> 01:03:43,680
Speaker 1: and today it's a very special listener mail. This is

1039
01:03:44,200 --> 01:03:46,880
Speaker 1: Josh edition because you picked out a very special one.

1040
01:03:47,200 --> 01:03:49,360
Speaker 1: I love this one. I'm gonna butcher the dude's name,

1041
01:03:49,440 --> 01:03:51,600
Speaker 1: but that's right, take it away. It's a good one. Okay,

1042
01:03:52,440 --> 01:03:57,160
Speaker 1: I'm gonna call this one email from a real Irish historian,

1043
01:03:58,920 --> 01:04:01,360
Speaker 1: and it feels pretty good to come out of a job.

1044
01:04:01,560 --> 01:04:04,840
Speaker 1: Yeah maybe, Okay, Hi guys, I'm a big fan of

1045
01:04:04,880 --> 01:04:07,480
Speaker 1: the show. It's informative and insightful, and I find myself

1046
01:04:07,560 --> 01:04:10,560
Speaker 1: interested in things that I never looked twice at before.

1047
01:04:11,120 --> 01:04:14,160
Speaker 1: One subject that I'd always found fascinating was the correlation

1048
01:04:14,240 --> 01:04:17,840
Speaker 1: between the Native American Choctaw tribe and the people of Ireland.

1049
01:04:18,000 --> 01:04:20,360
Speaker 1: I didn't realize that was a thing that you at all.

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01:04:20,800 --> 01:04:23,040
Speaker 1: This is a story which isn't well known, okay, which

1051
01:04:23,120 --> 01:04:25,680
Speaker 1: isn't well known outside of some areas of Ireland and

1052
01:04:25,800 --> 01:04:27,720
Speaker 1: of course within the tribe. But it's a really good

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01:04:27,800 --> 01:04:30,640
Speaker 1: story of solidarity between two groups of people, despite being

1054
01:04:30,720 --> 01:04:33,560
Speaker 1: thousands of miles apart. Less than twenty years after the

1055
01:04:33,600 --> 01:04:37,120
Speaker 1: Trail of Tears, which forcibly displaced thousands of natives, the

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01:04:37,240 --> 01:04:39,960
Speaker 1: Great Famine hit Ireland. During this time, as you know,

1057
01:04:40,120 --> 01:04:42,560
Speaker 1: Ireland was colonized by the British and the people of

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01:04:42,640 --> 01:04:45,640
Speaker 1: Ireland were treated poorly due to the common misconception that

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01:04:45,720 --> 01:04:49,560
Speaker 1: Irish Catholics were lower caliber of human uh. He goes

1060
01:04:49,640 --> 01:04:51,880
Speaker 1: on to to give more examples, but just suffice to

1061
01:04:51,960 --> 01:04:54,880
Speaker 1: say it was not good for the Irish people. During

1062
01:04:54,920 --> 01:04:59,040
Speaker 1: the famine, words spread to America and to the Choctaw tribe.

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01:04:59,400 --> 01:05:01,960
Speaker 1: They sympathy eased with the Irish people so much that

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01:05:02,120 --> 01:05:05,240
Speaker 1: only fifteen years after the Trail of Tears, they donated

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01:05:05,320 --> 01:05:08,960
Speaker 1: seven hundred and ten dollars during eighteen forty five to

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01:05:09,120 --> 01:05:12,200
Speaker 1: send to Ireland as part of a relief fund. This

1067
01:05:12,400 --> 01:05:15,040
Speaker 1: is estimated to be roughly sixty eight thousand dollars in

1068
01:05:15,080 --> 01:05:18,439
Speaker 1: today's money. This was greatly appreciated by the Irish people

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01:05:18,480 --> 01:05:21,360
Speaker 1: and after the famine the bond continued. In Cork, we

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01:05:21,440 --> 01:05:24,560
Speaker 1: have a sculpture honoring the tribute of the Choctaw people,

1071
01:05:24,920 --> 01:05:27,200
Speaker 1: and in nineteen ninety members of the tribe came to

1072
01:05:27,280 --> 01:05:30,560
Speaker 1: Ireland and walked the Famine Walk in Mayo to replicate

1073
01:05:30,640 --> 01:05:33,160
Speaker 1: the walk that starving people made to ask the landlord

1074
01:05:33,280 --> 01:05:37,240
Speaker 1: for help. In nine in Irish Commemoration group walked from

1075
01:05:37,280 --> 01:05:40,840
Speaker 1: Oklahoma to Mission to replicate the Trail of Tears and

1076
01:05:41,120 --> 01:05:45,120
Speaker 1: raised seven hundred thousand dollars to help poverty in Africa.

1077
01:05:45,680 --> 01:05:47,720
Speaker 1: These two groups continue to work together and to this

1078
01:05:47,880 --> 01:05:50,400
Speaker 1: day our President has declared an honorary member of the

1079
01:05:50,480 --> 01:05:54,000
Speaker 1: Choctaw tribe. Along with the Quakers, who fed Irish people

1080
01:05:54,040 --> 01:05:56,840
Speaker 1: to the point that their members ended starving themselves. The

1081
01:05:56,960 --> 01:06:00,080
Speaker 1: Choctaw tribe remained some of the unsung heroes of the

1082
01:06:00,120 --> 01:06:02,720
Speaker 1: famine story of Ireland. Sorry it went on so long.

1083
01:06:02,800 --> 01:06:05,240
Speaker 1: I'm an Irish historian, so I tend to waffle. Love

1084
01:06:05,320 --> 01:06:09,160
Speaker 1: the show. Best of luck with yourselves, Uh, Roison kill

1085
01:06:09,280 --> 01:06:14,680
Speaker 1: Roy fan, fantastic, great story. Thanks a lot, Roison. I'm

1086
01:06:14,800 --> 01:06:17,200
Speaker 1: quite sure that's not the actual pronunciation of your name,

1087
01:06:17,240 --> 01:06:19,760
Speaker 1: because there's a lot of accent marks over letters there

1088
01:06:19,880 --> 01:06:23,560
Speaker 1: normally aren't. Um, So I apologized for that, but I

1089
01:06:24,080 --> 01:06:26,600
Speaker 1: nailed your last name. I'm positive of it. And Josh

1090
01:06:26,680 --> 01:06:29,200
Speaker 1: Clark three and a half stars, not bad out of

1091
01:06:29,240 --> 01:06:32,160
Speaker 1: three and a half? Right, remember what was star search

1092
01:06:32,440 --> 01:06:35,560
Speaker 1: the four stars? Oh? I don't remember. I just just

1093
01:06:35,800 --> 01:06:40,200
Speaker 1: now remember there was such thing as Starson. Uh. Well, okay,

1094
01:06:40,240 --> 01:06:42,400
Speaker 1: well you take the in part, Chuck, since I took

1095
01:06:42,440 --> 01:06:47,800
Speaker 1: listener mail. Oh geez uh, thanks for listening. Um Hey,

1096
01:06:47,880 --> 01:06:49,040
Speaker 1: if you want to get in touch with us, you

1097
01:06:49,120 --> 01:06:53,840
Speaker 1: can find Josh at josh um Clark on Twitter and

1098
01:06:54,120 --> 01:06:57,800
Speaker 1: me uh in Facebook at Charles W. Chuck Bryant, or

1099
01:06:57,880 --> 01:07:01,240
Speaker 1: you can go to our official pages. Stuff you should know, podcasts,

1100
01:07:01,440 --> 01:07:04,120
Speaker 1: what else? Uh, let's see if they want to send

1101
01:07:04,160 --> 01:07:06,960
Speaker 1: us an email. Oh yeah, email us at stuff podcast

1102
01:07:07,040 --> 01:07:10,640
Speaker 1: at how stuff works dot com and have a good day.

1103
01:07:10,920 --> 01:07:13,440
Speaker 1: Is that what you say? That's good enough? All right?

1104
01:07:18,800 --> 01:07:21,240
Speaker 1: For more on this and thousands of other topics, is

1105
01:07:21,280 --> 01:07:22,480
Speaker 1: it how stuff works dot com.