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Speaker 1: Hey, Welcome to Stuff to Blow Your Mind. My name

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Speaker 1: is Robert Lamb and I'm Joe McCormick, and it is

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Speaker 1: time to enter the vault. Because it is Saturday, time

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Speaker 1: to go into the archives for an old episode of

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Speaker 1: Stuff to Blow Your Mind. This time we wanted to

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Speaker 1: revisit our original exploration of the Uncanny Valley. This was

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Speaker 1: a two part episode U Part one was originally published

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Speaker 1: April four. I think back on this episode a good bid. Actually,

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Speaker 1: I guess I encounter a lot of strange almost their

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Speaker 1: simulations of the human likeness. Yeah, yeah, this one, this

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Speaker 1: one is one that that I think back to a

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Speaker 1: lot as well, just because, yeah, you're always encountering some

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Speaker 1: imperfect digital recreations of a human likeness, and then we

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Speaker 1: have to sort out how we feel about it, but

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Speaker 1: also how we've perhaps been conditioned to feel about it

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Speaker 1: just by knowing about, uh, the idea of the Uncanny Valley.

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Speaker 1: So yeah, this is gonna first of two episodes of

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Speaker 1: this episode is Into the Uncanny Valley, originally published April four,

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Speaker 1: and then in the subsequent episode, we're going to go

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Speaker 1: Beyond the Uncanny Valley. Welcome to Stuff to Blow Your

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Speaker 1: Mind from how stuff Works dot Com. Hey, welcome to

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Speaker 1: Stuff to Blow your Mind. My name is Robert Lamb

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Speaker 1: and I'm Joe McCormick. And Robert, I want to take

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Speaker 1: you back to a conversation we had. I think it

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Speaker 1: was last December. It was right after I went to

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Speaker 1: see the new, the most recent Star Wars movie, Rogue one.

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Speaker 1: Oh yes, uh, And I am on the cusp, the

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Speaker 1: very cusp of seeing it myself and waiting for it

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Speaker 1: to become rent rental options. So oh it's not yet.

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Speaker 1: Still got still a week or two out. So has

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Speaker 1: everything been spoiled for you so far? No? People have

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Speaker 1: been a little um cooler on this one. Um. I

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Speaker 1: think some things are probably spoiled for me, but not

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Speaker 1: like that last one where every just really felt the

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Speaker 1: need to, you know, just lay it all out on

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Speaker 1: social media. Let me let me spoil one thing for

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Speaker 1: you here and they go to space and there's a

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Speaker 1: war there. Yeah, stars among the stars. But there is

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Speaker 1: one thing in the movie. Okay, so mild spoiler for

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Speaker 1: Rogue one coming out. It's something that probably everybody already knows.

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Speaker 1: It's also not really about the content of the movie,

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Speaker 1: but just about which characters you see. But if you

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Speaker 1: are ready, are you ready for the mild spoiler? Okay,

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Speaker 1: we get to see if you remember back to the

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Speaker 1: original Star Wars. Back go back to the seventies. Peter

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Speaker 1: Cushing as Grand mof Tarkin, the guy who was in

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Speaker 1: fact Darth Vader's boss on the Star Him. Yeah, he's

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Speaker 1: enough of this, Vada release him. And we love Peter

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Speaker 1: Cushing because he was in all these old monster movies.

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Speaker 1: He goes back to the Hammer movies. He was. He

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Speaker 1: was Dr Frankenstein, like the villainous Dr Frankenstein of the

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Speaker 1: Hammer films. And he I think was the hero of

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Speaker 1: the version of the Mummy that has Christopher Lee as

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Speaker 1: as the Mummy. Uh, the one. I've got the poster

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Speaker 1: for it in the House six up. It's the Belgian posters,

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Speaker 1: so it's La Malediction de Feron. But yeah, so Peter

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Speaker 1: Cushing was the original Grand mof Tarkan, this bad Empire

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Speaker 1: guy who was Darth Vader's boss. And the thing they

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Speaker 1: do in the New Rogue One is they bring him back.

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Speaker 1: He's dead, he has passed away. This movie takes place

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Speaker 1: a little bit before the original Star Wars is supposed

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Speaker 1: to have taken place. But they bring this character back

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Speaker 1: and they have an actor stand in as him, but

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Speaker 1: it's not just a recast role. They try to make

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Speaker 1: it look as if this is Peter Cushing standing here

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Speaker 1: delivering the lines with c g I. And this is

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Speaker 1: an odd choice because all right, so you're gonna have

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Speaker 1: Darth Vader in there, that's easy to do. Darth Vader

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Speaker 1: is a dude in a suit, voiced by James Earl Jones.

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Speaker 1: James Earl Jones is still alive, so you can check

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Speaker 1: that one off the list. But Grandma Tarkin, like you said, uh,

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Speaker 1: the actor is dead. So it seems to me like

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Speaker 1: the first easiest thing to do is just don't have

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Speaker 1: those scenes. If you know it's going to be ablematic,

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Speaker 1: don't even mess with it. Or um, just use an

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Speaker 1: actual living actor such as Wayne Pigram who played him

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Speaker 1: in Revenge of the Sith. Or go with Ben Cross,

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Speaker 1: who's another actor that I've seen over the years brought

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Speaker 1: up as potential Tarkan casting, or head go with Ralph Finds, Like,

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Speaker 1: clearly you have the money to throw down the well

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Speaker 1: of expensive c g I equipment, Just go ahead and

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Speaker 1: hire Ralph Finds. I know he's pricey, but he's great

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Speaker 1: and it's consummate evil Brett. Yeah, he even kind of

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Speaker 1: looks like a younger Peter Cushing. He's got that same

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Speaker 1: kind of angular face, like the thin long face with

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Speaker 1: the jaw and the scowl. It's all there. And it's

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Speaker 1: not like fans of various franchise are not clearly cool

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Speaker 1: with recasting. It's not like we're gonna be thrown into,

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Speaker 1: you know, a traumatic spin, because you can look to

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Speaker 1: a Game of Thrones, James Bond, Twilight, Harry Potter, etcetera,

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Speaker 1: like we we get it. We can roll with a recast. Now.

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Speaker 1: I want to go into completely different directions thinking about

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Speaker 1: this c g I grandmof Tarken. One is that I

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Speaker 1: didn't like it in the movie. Okay, I saw it

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Speaker 1: and I was just like, I don't want this. It

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Speaker 1: pulled me out of the movie. It made me stop

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Speaker 1: being in the story and just thinking about how did

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Speaker 1: they do that? I don't On one hand, it looked

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Speaker 1: great like when you see the movie, I think he

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Speaker 1: will kind of have to agree. It's unless I'm missing something.

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Speaker 1: It's the best c g I simulation of a real

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Speaker 1: person that I've ever seen. Like it looks amazing, but

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Speaker 1: it still looks not quite good enough that I can

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Speaker 1: just accept it and go with it. I kept continually thinking, like,

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Speaker 1: what am I looking at? It's almost really him, but

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Speaker 1: it's not quite really him, and it made me feel icky.

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Speaker 1: So in this it made you to send into what

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Speaker 1: we've come to know as a as a as a

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Speaker 1: species as the Uncanny Valley. Right, So today is going

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Speaker 1: to be the first of two episodes we want to

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Speaker 1: do about the Uncanny Valley, and this first one we

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Speaker 1: wanted to descend into the Uncanny Valley, but not us

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Speaker 1: talk about it in terms of the standard pop culture phenomenon,

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Speaker 1: because this is one of those side tech concepts that

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Speaker 1: is totally filtered down into the mainstream. Everybody talks about

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Speaker 1: the Uncanny Valley. It's a totally normal, ground level pop

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Speaker 1: culture phenomenon now, especially with as much bad C. G

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Speaker 1: I as we encounter in the movies. But there it's

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Speaker 1: also a scientific field of study. It's something that people

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Speaker 1: are looking into with empirical research to try to figure

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Speaker 1: out does it really exist, If it does really exist,

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Speaker 1: what causes it, what can be done about it. So

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Speaker 1: we want to look at it from both of these

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Speaker 1: angles today, Right, so we should probably roll through some

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Speaker 1: just fun examples of this. We're gonna try and not

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Speaker 1: to go too long on this. If we do, we'll

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Speaker 1: cut it and save it for trailer talk. Either way,

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Speaker 1: we'll probably do a Facebook live trailer talk on an

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Speaker 1: upcoming Friday about some of these movies. Okay, so I

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Speaker 1: want to go back to a much earlier experience for me, Robert,

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Speaker 1: did you see The Mummy Returns in two thousand one?

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Speaker 1: Remember this one? I don't think I saw The Mummy Returns.

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Speaker 1: I saw the Money and I remember digging it at

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Speaker 1: the time, but not not the old hammer one or

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Speaker 1: the universal one. You know, the Yeah, the the re

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Speaker 1: the reboot of the Money. Is his name, Brendan Fraser. Yeah,

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Speaker 1: and what Arnold Vosslo? Yeah he was he. I I

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Speaker 1: enjoyed him as they kind of brought in some of

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Speaker 1: these aspects of the tragic Mummy figure, which I liked. Yeah, yeah, yeah, okay.

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Speaker 1: But in two thousand one we got the Scorpion King.

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Speaker 1: This is a character that appears in the Mummy Returns

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Speaker 1: and he's pretty much if you want to picture it

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Speaker 1: if you haven't seen the movie, actually you should look

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Speaker 1: up video of this. We're gonna tell you to go

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Speaker 1: look up images and video quite a few times in

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Speaker 1: these episodes because some visual aids will help. But if

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Speaker 1: you want to picture it, picture the concept of a centaur,

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Speaker 1: except replace the horse parts with scorpion parts and some

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Speaker 1: other random arthropod bits, and the man part on top

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Speaker 1: is Dwayne the Rock Johnson, except it's not Dwayne the

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Speaker 1: Rock Johnson. There's a there's a bit of a problem

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Speaker 1: with the rocks. So the corpion Scorpion, the Scorpion King,

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Speaker 1: scuttles into action in the film, and you can tell

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Speaker 1: immediately something is wrong because it's not just the rock.

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Speaker 1: It's this c g I upper body designed to look

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Speaker 1: like the rock. It's supposed to be him, but it

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Speaker 1: doesn't look right. It looks like somebody took the rock,

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Speaker 1: skinned him, and then took the skin suit and then

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Speaker 1: boiled it and then maybe ironed it and rubbed it

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Speaker 1: down with wax, and then stretched it over somebody else,

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Speaker 1: like a bald Crispin Glover wearing a waxed up the

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Speaker 1: rock suit. And and that would be fine if that's

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Speaker 1: what they were going for, But I guess the disconnect

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Speaker 1: here is that clearly they wanted this to be like

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Speaker 1: the Rock as a scorpion center and not this um

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Speaker 1: creepy in human above the nation that you've described, right,

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Speaker 1: And it's sort of I guess works because it's okay

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Speaker 1: if he's creepy, because he's a monster. But he was

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Speaker 1: creepy in a way that he clearly wasn't supposed to be.

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Speaker 1: It wasn't just that, oh he's a monster. He looks weird.

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Speaker 1: Something looked wrong with him. And this was at a

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Speaker 1: time when computer generated animations were hot, right two thousand one.

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Speaker 1: They seem to be getting better all the time, and

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Speaker 1: yet they were terrible producing these characters that were not

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Speaker 1: only not convincingly human, they were literally physically unpleasant to

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Speaker 1: look at. They were repulsive. Yeah, it was a period

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Speaker 1: when everyone was just foolishly optimistic about what we could

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Speaker 1: achieve with c g I, and you know, into in

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Speaker 1: in a sense, maybe that hasn't gone away. We're still

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Speaker 1: very the Rogue one example, Like, clearly everyone was very

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Speaker 1: optimistic about how great this looked, and even though to

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Speaker 1: your point, it does look great, but within the context

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Speaker 1: of the film, something doesn't quite work. Yeah, I would say,

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Speaker 1: now for some people we can get into this more.

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Speaker 1: I think, especially in the next episode when we then

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Speaker 1: the next one, we want to try to go beyond

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Speaker 1: the valley, the Uncanny Valley. But I will say at

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Speaker 1: this point, for some people, Tarkan was not over the

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Speaker 1: line or under the line. I don't know where you

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Speaker 1: put the line. But for for some people it worked,

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Speaker 1: and I do think that's an interesting thing to acknowledge

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Speaker 1: that while for me I I experience this, uh, not

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Speaker 1: to the same extent as the Scorpion King, but a

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Speaker 1: kind of Scorpion King revulsion, not everybody did. Now, one

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Speaker 1: thing about Tarkan is that the Tarkan c Jack character

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Speaker 1: is correct me if I'm wrong, because I have not

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Speaker 1: seen it myself yet. But he is interacting with human

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Speaker 1: actors in this in his scenes, Yeah, I think, so okay,

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Speaker 1: or at least he's in a film with other human actors,

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Speaker 1: even if he's not sharing the exact same scene with them.

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Speaker 1: So you might think, well, if you just had a

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Speaker 1: movie just full of brilliant looking Tarkins, maybe it would

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Speaker 1: be okay. And maybe it would But some of the

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Speaker 1: classic examples of Uncanny Valley happened to be films that

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Speaker 1: are filled with nothing but c g I characters. Yeah,

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Speaker 1: how about one from the same year as The mom

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Speaker 1: of Your Turns two thousand one, if you go back

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Speaker 1: to Oh yes, Final Fantasy, The Spirits Within, I remember

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Speaker 1: kind of liking it. I do too. It was a

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Speaker 1: film that I think I kind of half watched, half

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Speaker 1: worked on, like some just college course workers something. It

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Speaker 1: was just on in the background and and maybe that

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Speaker 1: was the right level of immersion in it. But I

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Speaker 1: remember digging it. But at the same time, there are

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Speaker 1: a lot of dead puppet eyes in this movie. Oh yeah,

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Speaker 1: and it's so I saw it at the time. I

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Speaker 1: remember having mixed feelings about the animation, like in some senses,

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Speaker 1: I remember thinking, Wow, that looks so cool. That again

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Speaker 1: may have been a product of its time. We can

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Speaker 1: talk about that more, how our expectations changes things go on.

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Speaker 1: But also I don't know. There were multiple things wrong

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Speaker 1: with that movie, one of which being that the last

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Speaker 1: line of spoken dialogue in the movie, as a friend

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Speaker 1: of mine pointed out at the time, was oh it's warm.

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Speaker 1: Well I can I don't remember the line, so I

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Speaker 1: can't speak to it how well it landed, But I

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Speaker 1: can see that being a problem. Role credits Now. Another

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Speaker 1: big one, this came out just three years later, is

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Speaker 1: of course, The Polar Express. Now, when people talk about

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Speaker 1: the Uncanny Valley these days, i'd say this is a

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Speaker 1: top three mentioned. Yeah, this is one of the defining

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Speaker 1: nightmare of our time now based on a wonderful children's

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Speaker 1: book about the magic of Christmas time. Yeah, the book

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Speaker 1: is wonderful, but it's certainly one of these examples. If

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Speaker 1: you take a very brief children's book and you try

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Speaker 1: and adapt it into a feature length motion picture, that's

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Speaker 1: very difficult to do. In fact, I'm really grasping for

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Speaker 1: an example where anybody actually pulled it off. Like, the

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Speaker 1: best adaptations of children's books that come to mind are

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Speaker 1: all very short, very short films. Generally, I'm thinking of

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Speaker 1: Dr Seus's adaptations from the seventies and eighties, not The

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Speaker 1: Polar Express, which is just an exercise in psychic trauma

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Speaker 1: brought on by just seemingly intentionally weaponized Uncanny Valley. Um,

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Speaker 1: you know, the soulless puppet people. I've never seen this movie,

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Speaker 1: but I looked up clips to see what people were

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Speaker 1: talking about, and oh man, they they are not kidding it.

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Speaker 1: I don't know how children made it through this movie.

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Speaker 1: It has these it has these creepy elves, It's got

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Speaker 1: a creepy Tom Hanks as a train conductor. Nothing seems right,

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Speaker 1: Everything seems like it's just about to everybody's about to

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Speaker 1: start melting and screaming. Yeah. I think this is one

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Speaker 1: where it was a poor idea in my opinion, and

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Speaker 1: uh in the technology was not there to to rescue

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Speaker 1: the idea. Now the next one we're going to discuss though.

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Speaker 1: I think it was a great idea on paper, but

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Speaker 1: it just didn't work out on the screen. And that's

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Speaker 1: of course. Two thousand seven's Bayowolf. Now as this Robert

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Speaker 1: Zemeckis who did this, Yeah, Robert Zemeckis helmed it. And

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Speaker 1: then the writing it was Neil Gaiman and Roger Avery.

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Speaker 1: So some you know, some some some big names just

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Speaker 1: attached and to the the ideas behind this. Uh this movie,

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Speaker 1: and of course based on the story of Grindel and Beowulf,

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Speaker 1: which is a classic you would think, you know, hard

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Speaker 1: to miss action narrative. I think The Bao Wolf could

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Speaker 1: make a really great movie if somebody did it right. Yeah,

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Speaker 1: I think so too. I have yet to see that movie.

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Speaker 1: But but but certainly has all the potential in the world.

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Speaker 1: And they had a pretty cool vocal cast as well,

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Speaker 1: I think, and Angelina Jolie is in it as the

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Speaker 1: monster's mother. They have ray Winstone as Bowel. Yeah, he

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Speaker 1: does the voice of of Beowulf, and uh and who

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Speaker 1: was it that plays the monster? We were just Crispin

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Speaker 1: Now I've seen it all back home. Not one of

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Speaker 1: my favorite monster depictions of Grenville, by the way, but

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Speaker 1: he's a monster. We can get past that. But everybody

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Speaker 1: else in the film really has the uncanny valleys that

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Speaker 1: going on to to a high degree. I think I

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Speaker 1: read a quote somewhere where film critic was talking about

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Speaker 1: how the monsters in the movie were only slightly less

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Speaker 1: frightening than the humans. Yeah, yeah, the humans. It just

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Speaker 1: it just didn't land. Now at this point you're probably thinking, well,

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Speaker 1: how about video games, because they're certainly when you're thinking

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Speaker 1: about computer animated human beings interacting with each other, staring

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Speaker 1: right into the camera, you think of video games. Yeah,

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Speaker 1: and and I think, you know, here's here's the thing here.

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Speaker 1: I have to say that I haven't noticed it as

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Speaker 1: often these days. I think a lot of game animators

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Speaker 1: have found ways to get around the Uncanny Valley. I

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Speaker 1: don't want to get to ahead of our flow here,

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Speaker 1: but I think one thing that I've noticed they sometimes

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Speaker 1: do is that they don't actually go for photo realism,

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Speaker 1: and they go for a kind of more real than

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Speaker 1: real combination of like a comic book style type character illustration,

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Speaker 1: and then these other realistic aspects that when you when

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Speaker 1: you look at a video game character, you would never

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Speaker 1: mistake it for a photograph of a person, even even

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Speaker 1: one that's got really good graphics. But much like the

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Speaker 1: way dialogue is written in films, you know, you don't

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Speaker 1: want to make dialogue sound like real people talk, because

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Speaker 1: that would be horrible to listen to, but you do

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Speaker 1: want to make it sound quote realistic. You don't want

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Speaker 1: to make your characters look too realistic in animation, but

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Speaker 1: you do want to make them look quote realistic. In

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Speaker 1: other words, they feel real. Yeah, this reminds me of

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Speaker 1: a game franchise that I haven't I don't think I've

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Speaker 1: ever played more than a demo of this, but the

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Speaker 1: Gears of War series. So all the people in this

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Speaker 1: kind of look like like, if you're gonna be critical

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Speaker 1: of it, you might say, well, everyone looks kind of

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Speaker 1: like they're weird guerilla people. Like. It was a like

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Speaker 1: we're in an alternate world where unrealistically huge upper bodies. Yeah,

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Speaker 1: is if evolution took a slightly different turn into an

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Speaker 1: intelligent primates. Uh. And yet they look real. They don't

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Speaker 1: look like they don't get an uncanny effect rolling off them,

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Speaker 1: Like you know, you look at them, you can see pores,

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Speaker 1: you can see hair follicills. They look real, but they

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Speaker 1: are but they are certainly not going for authentic human

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Speaker 1: being there all right, Now, I want to put out

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Speaker 1: one more example here before we move on, and it's

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Speaker 1: a rare example of uncanny valley avoidance, a very specific

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Speaker 1: type of uncanny valley avoidance, and that is from a

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Speaker 1: fantastic stop motion short that was produced by the National

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Speaker 1: Film Board of Canada. And you can find the online

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Speaker 1: if you just do us a search for it. It's

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Speaker 1: Madam Tutley Putly and it's a wonderful little little film,

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Speaker 1: very very French feel to it. Characters on a train, weirds,

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Speaker 1: frightening things occurring. Uh, definitely check it out. But the

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Speaker 1: trick to it there, these are stop motion animated characters

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Speaker 1: and their eyes just feel so alive. They stare right

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Speaker 1: into you, and you don't you don't question for a

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Speaker 1: second that these are that these are people. And the

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Speaker 1: trick that they employed is that they used real human eyes,

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Speaker 1: not in a you know, depraved, evil puppet master kind

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Speaker 1: of a way, either. They videotaped the eyes of human

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Speaker 1: actors and then blended the footage with that of the puppets.

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Speaker 1: That sounds like an incredible gambit, because that sounds like

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Speaker 1: that could have produced some of the worst Uncanny Valley

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Speaker 1: feelings ever if it went wrong. Yeah, and and I

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Speaker 1: don't know, there may be some people who watch this

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Speaker 1: short and and have the opposite effect and think that

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Speaker 1: it's super creepy. I found it to be like this,

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Speaker 1: this interesting example of circumventing the Uncanny Alley. But I'll

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Speaker 1: leave it for you guys to decide. I'll include a

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Speaker 1: link to this one as well as some of the

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Speaker 1: other sources we're talking about on the landing page for

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Speaker 1: this episode. It's stuff to blow your mind dot com.

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Speaker 1: All right, well, we are going to take a quick

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Speaker 1: break and when we come back, we will get into

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Speaker 1: the origin of the scientific idea of the Uncanny Valley

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Speaker 1: and its history. And research. All right, we're back. So

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Speaker 1: the uncanny Valley. Where does this even come from? Right?

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Speaker 1: So we've already been talking about it because most people

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Speaker 1: have heard of this, they're somewhat familiar with it. I

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Speaker 1: was talking to Rachel about it though. She was saying,

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Speaker 1: you know, at least to her, it had this connotation

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Speaker 1: of just generally synthetically generated images being creepy in one

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Speaker 1: way or another. So maybe we should get into the

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Speaker 1: specifics of the origin of the idea. So let's go

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Speaker 1: back to the year nineteen seventy. Everything's great, Wait is it?

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Speaker 1: I don't know, but but everybody, everybody's looking forward to

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Speaker 1: the future in terms of creating humanoid robots. What are

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Speaker 1: we going to be able to do well? The Japanese

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Speaker 1: roboticist massa Hiro Mori of the Tokyo Institute of Technology.

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Speaker 1: He wrote a paper that was published in this Japanese

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Speaker 1: journal Energy that coined the term uncanny Valley to describe

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Speaker 1: a problem that he was predicting with increasingly humanoid robots.

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Speaker 1: And this was based on just some observations he'd had

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Speaker 1: of of different events. So you might say incidents in

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Speaker 1: the progress of designing humanoid robots such as consumer electronics

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Speaker 1: shows in Japan and stuff like that. So what he

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Speaker 1: predicted was that as you had a humanoid robot, robot

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Speaker 1: that looks like a human and it's likeness to a

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Speaker 1: human increased, our attitude toward them would improve. Our affinity

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Speaker 1: would go up as they became more human, until they

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Speaker 1: reached a certain tipping point of similarity to humans, where

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Speaker 1: suddenly our affinity, our friendly attitude, almost immediately shifts and

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Speaker 1: plunges down into strong revulsion. Being human is likable, being

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Speaker 1: sort of human is likable, but being almost human is

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Speaker 1: horrible and repulsive. And then of course at the final end,

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Speaker 1: uh you you would have a real human. So you

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Speaker 1: can think of the uncanny valley as a phase in

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Speaker 1: a graph, an X Y graph, and along the horizontal

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Speaker 1: axis on the bottom, you've got the degree of similarity

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Speaker 1: to a human, and then on the vertical axis you've

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Speaker 1: got the degree of our affinity for the object. And

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Speaker 1: more hypothesized, this graph would have these two peaks. You'd

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Speaker 1: start with zero on both axes, because a thing that

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Speaker 1: has no human like traits basically gets no human affinity

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Speaker 1: response one way or another. And we just don't you know,

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Speaker 1: how much do you really like an industrial conveyor belt

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Speaker 1: that you're just sort of neutral on it. But as

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Speaker 1: you increase the humanity, you give a robot arms or

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Speaker 1: something that looks like a face, eyes, limbs, you climb

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Speaker 1: this gentle, gradual slope to the fur peak and affinity. Um,

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Speaker 1: you know, and he didn't name the peak, but I

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Speaker 1: think we should name the peak. I think this first

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Speaker 1: peak should be called something like the cuteness peak. That's

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Speaker 1: not exactly right because it's not exactly cuteness, but it's

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Speaker 1: recognizing something kind of human about what you're looking at. Yeah, Like,

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Speaker 1: I mean, we don't have to describe cute to everyone here,

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Speaker 1: but certainly this is hello kitty territory, this is the

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Speaker 1: this is the domain of large eye. It's vaguely infant

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Speaker 1: or kitten like creatures that would never be mistaken for

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Speaker 1: human or real, but they resonate with us for a

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Speaker 1: number of reasons. We could do a whole podcast. In fact,

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Speaker 1: we have an old podcast episode about the science of cute.

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Speaker 1: Why that connects with us? Yeah, so they would include

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Speaker 1: that would include all kinds of robots that are just

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Speaker 1: kind of have general, very basic faces that don't try

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Speaker 1: to have human skin or anything like that that just

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Speaker 1: might have like kind of a mouth and some cartoonish eyes. Yeah. Sure,

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Speaker 1: there you go. That the C three po boldly on

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Speaker 1: the cuteness peap. But at a certain point after this

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Speaker 1: first peak, this graph drops off steeply. So you keep

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Speaker 1: going along the x axis, but then the y axis

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Speaker 1: drops off, not just down to zero, but far below zero,

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Speaker 1: into the negative affinity range. And this part of the

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Speaker 1: graph is the uncanny valley. As the similarity to a

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Speaker 1: real human continues to increase near a dent. In other words,

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Speaker 1: as it becomes indistinguishable from a real human, our affinity

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Speaker 1: sharply shoots back up the second peak toward reality. So

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Speaker 1: I'd call this second peak the reality peak. It's when

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Speaker 1: you become, for all intents and purposes, a real human being. Yeah.

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Speaker 1: I would also say that if if robots were candy,

425
00:22:43,760 --> 00:22:47,120
Speaker 1: the bottom of the uncanny valley would be banana flavored

426
00:22:47,119 --> 00:22:50,160
Speaker 1: candy like that for me has always been a flavor

427
00:22:50,240 --> 00:22:52,879
Speaker 1: where it's like clearly like not only like runts that

428
00:22:52,960 --> 00:22:56,480
Speaker 1: have bananas, I think, so like like great candy, like

429
00:22:56,520 --> 00:22:59,600
Speaker 1: grape candy doesn't really taste like grapes, but it's if

430
00:22:59,640 --> 00:23:02,159
Speaker 1: it's enough from the Uncanny Valley of Candy the year

431
00:23:02,200 --> 00:23:06,160
Speaker 1: You're okay, whoa, You're right, banana candy actually does taste

432
00:23:06,240 --> 00:23:10,639
Speaker 1: like bananas in a way that makes it not really good. Yeah,

433
00:23:10,800 --> 00:23:14,520
Speaker 1: Like I've candy fans, I don't eat that much candy anymore.

434
00:23:14,520 --> 00:23:18,640
Speaker 1: So maybe the technology has advanced, but uh, my memory

435
00:23:18,680 --> 00:23:23,480
Speaker 1: of the banana candy is is that of an uncanny experience. Now,

436
00:23:23,520 --> 00:23:25,640
Speaker 1: one thing we should note is that so this original

437
00:23:25,640 --> 00:23:29,800
Speaker 1: paper was published in nineteen seventy twelve. English translation was

438
00:23:29,840 --> 00:23:33,720
Speaker 1: published in uh the I Triple A Robotics and Automation magazine.

439
00:23:33,760 --> 00:23:35,439
Speaker 1: And that's what I was using, is my reference, that

440
00:23:35,480 --> 00:23:39,840
Speaker 1: English translation from twelve. Uh. And so it has some

441
00:23:39,920 --> 00:23:43,800
Speaker 1: graphs here, It has Mori's original graphs or interpretations of them,

442
00:23:44,119 --> 00:23:46,119
Speaker 1: and we can get into a little more detail on

443
00:23:46,280 --> 00:23:48,640
Speaker 1: the nuances of Morey's theory. But one thing I did

444
00:23:48,680 --> 00:23:54,080
Speaker 1: read was that many years later somebody contacted more and

445
00:23:54,119 --> 00:23:56,560
Speaker 1: he and they were talking to him about this idea

446
00:23:56,640 --> 00:23:59,000
Speaker 1: he had of the uncanny valley, and they were like, well,

447
00:23:59,119 --> 00:24:02,399
Speaker 1: does does anything lie beyond the peak of reality? And

448
00:24:02,440 --> 00:24:04,880
Speaker 1: he said, hey, oh yeah, actually there is such a thing.

449
00:24:05,440 --> 00:24:07,840
Speaker 1: And he said, you know, beyond the real human, you'd

450
00:24:07,880 --> 00:24:12,919
Speaker 1: have sort of like artistic ideals. Oh wow, like the

451
00:24:12,960 --> 00:24:15,640
Speaker 1: realm of forms even right, Yeah, so well, I think

452
00:24:15,640 --> 00:24:18,360
Speaker 1: he used an example of like a statue of Buddha,

453
00:24:18,400 --> 00:24:21,240
Speaker 1: you know, a beautiful, perfect statue of Buddha. It's almost

454
00:24:21,320 --> 00:24:23,840
Speaker 1: like it we have greater affinity for it than we

455
00:24:23,880 --> 00:24:28,199
Speaker 1: have for a realistic human because we've been, well, to

456
00:24:28,240 --> 00:24:31,720
Speaker 1: a large point, we've been conditioned to rite. Yeah, that

457
00:24:31,720 --> 00:24:34,160
Speaker 1: that kind of gets into this, this idea of conditioned

458
00:24:34,240 --> 00:24:37,960
Speaker 1: familiarity that we not only have with religious icons, but

459
00:24:38,000 --> 00:24:41,280
Speaker 1: also with pop culture icons. So not only the Buddha,

460
00:24:41,320 --> 00:24:46,520
Speaker 1: but also Robbie the robot, or or even the Terminator

461
00:24:46,640 --> 00:24:48,800
Speaker 1: or well, yeah, that does make me think that in

462
00:24:48,840 --> 00:24:52,080
Speaker 1: some ways, if if aesthetic ideals and things that were

463
00:24:52,119 --> 00:24:55,679
Speaker 1: familiar with through our culture might be even beyond humans.

464
00:24:55,720 --> 00:24:58,520
Speaker 1: I mean, again, this is not like rigorous research, This

465
00:24:58,600 --> 00:25:01,720
Speaker 1: is just what more he says, he inks and predicts. Uh,

466
00:25:01,920 --> 00:25:04,480
Speaker 1: could could there be like a robot that we really

467
00:25:04,520 --> 00:25:08,080
Speaker 1: love that's actually better than a than a normal human? Well,

468
00:25:08,119 --> 00:25:10,680
Speaker 1: you know, there's a study that came out last year,

469
00:25:10,680 --> 00:25:13,080
Speaker 1: I believe from Penn State University that was kind of

470
00:25:13,080 --> 00:25:16,400
Speaker 1: interesting alone in these lines. So The researchers survey three

471
00:25:16,800 --> 00:25:20,240
Speaker 1: seven nine adults ages ages sixty to eighty six, and

472
00:25:20,280 --> 00:25:23,640
Speaker 1: they asked them for specific memories of robot films they'd

473
00:25:23,680 --> 00:25:26,960
Speaker 1: seen in their general attitudes towards robots and and the

474
00:25:27,200 --> 00:25:30,359
Speaker 1: you know the age here. As you might imagine, they're

475
00:25:30,400 --> 00:25:33,920
Speaker 1: really looking at at potential care robots, like the idea

476
00:25:33,920 --> 00:25:35,520
Speaker 1: of like, what kind of robots should help you use

477
00:25:35,560 --> 00:25:37,760
Speaker 1: the bathroom? Do you want something that looks like kind

478
00:25:37,760 --> 00:25:39,560
Speaker 1: of like a person, or do you want something that

479
00:25:39,600 --> 00:25:43,640
Speaker 1: looks like a forklift with a forklift mated with an

480
00:25:43,640 --> 00:25:46,000
Speaker 1: easy chair. But if you look at the ages used

481
00:25:46,040 --> 00:25:49,320
Speaker 1: here and twenty sixteen, when the studies took place, you

482
00:25:49,359 --> 00:25:51,879
Speaker 1: can say that these people grew up with science fiction.

483
00:25:52,000 --> 00:25:55,359
Speaker 1: Oh yeah, I mean they might not have personally consumed

484
00:25:55,400 --> 00:25:57,560
Speaker 1: a lot of it, but it's in the culture, right, Yeah.

485
00:25:57,560 --> 00:26:00,760
Speaker 1: They they definitely had access to it. And researchers found

486
00:26:00,760 --> 00:26:04,720
Speaker 1: that individuals who could recall more cinematic robot portrayals were

487
00:26:04,760 --> 00:26:08,000
Speaker 1: increasingly likely to hold positive attitudes towards robots in general.

488
00:26:08,040 --> 00:26:10,919
Speaker 1: So it didn't matter if they remembered murderous kill bots

489
00:26:11,040 --> 00:26:14,720
Speaker 1: or well meaning helper bots. Uh. They the mere memory

490
00:26:14,920 --> 00:26:19,800
Speaker 1: of multiple robotic portrayals correlated to pro robot vibes, so

491
00:26:19,840 --> 00:26:23,080
Speaker 1: the study findings. They also backed up the importance of

492
00:26:23,160 --> 00:26:28,840
Speaker 1: human looking human esque robots to invoke a sympathetic user response.

493
00:26:29,000 --> 00:26:31,879
Speaker 1: But the researchers stressed that robot designers might want to

494
00:26:31,880 --> 00:26:35,520
Speaker 1: incorporate robotic features that older adults will remember from their

495
00:26:35,520 --> 00:26:39,840
Speaker 1: cinematic past. So it's saying that, like, don't just try

496
00:26:39,880 --> 00:26:41,600
Speaker 1: to make it like a human. Try to make it

497
00:26:41,680 --> 00:26:44,280
Speaker 1: like the robots we have known and loved. Yeah, Like

498
00:26:44,440 --> 00:26:47,359
Speaker 1: make it fun. You know, if I'm if I need

499
00:26:47,400 --> 00:26:49,800
Speaker 1: a robot to help me go to the bathroom, make

500
00:26:49,880 --> 00:26:52,159
Speaker 1: it make make them the robots from Silent Running, you know,

501
00:26:52,280 --> 00:26:55,080
Speaker 1: Hulie Do and Louie, the little little guys. Then at

502
00:26:55,119 --> 00:26:57,640
Speaker 1: least I can engage my nostalgia a little bit totally.

503
00:26:58,280 --> 00:26:59,920
Speaker 1: So I want to look at a few more nuances.

504
00:27:00,119 --> 00:27:02,919
Speaker 1: Maury's original paper in nineteen seventy so one thing, I

505
00:27:03,000 --> 00:27:04,720
Speaker 1: do think it's very interesting and I want to come

506
00:27:04,760 --> 00:27:09,000
Speaker 1: back to as we explore this topic more. More hypothesizes

507
00:27:09,040 --> 00:27:12,080
Speaker 1: in the original paper that our perception of an uncanny

508
00:27:12,160 --> 00:27:15,520
Speaker 1: valley might depend on the context in which we're we're

509
00:27:15,600 --> 00:27:18,439
Speaker 1: viewing the being and the example he gives here is

510
00:27:18,480 --> 00:27:22,600
Speaker 1: he's talking about Buon Rocku puppets, and so he says, quote,

511
00:27:22,640 --> 00:27:25,359
Speaker 1: I don't think that on close inspection of bun Rocku

512
00:27:25,400 --> 00:27:29,440
Speaker 1: puppet appears similar to a human being. But when we

513
00:27:29,560 --> 00:27:32,359
Speaker 1: enjoy a puppet show in the theater, were seated at

514
00:27:32,359 --> 00:27:35,960
Speaker 1: a certain distance from the stage, the puppets absolute size

515
00:27:36,040 --> 00:27:40,119
Speaker 1: is ignored. Its total appearance, including hand and eye movements,

516
00:27:40,480 --> 00:27:42,920
Speaker 1: is close to that of a human being. So, given

517
00:27:42,920 --> 00:27:46,200
Speaker 1: our tendency as an audience to become absorbed in this

518
00:27:46,320 --> 00:27:49,080
Speaker 1: form of art, we might feel a high level of

519
00:27:49,119 --> 00:27:52,800
Speaker 1: affinity for the puppet. I think that's interesting. So it's

520
00:27:52,880 --> 00:27:56,000
Speaker 1: it's not just the object, but it's also the context

521
00:27:56,040 --> 00:27:58,680
Speaker 1: in which we experience the object. You might have very

522
00:27:58,720 --> 00:28:02,000
Speaker 1: different feelings about a and rocky puppet lying on the

523
00:28:02,040 --> 00:28:06,000
Speaker 1: floor versus one that you go to see in the

524
00:28:06,040 --> 00:28:08,879
Speaker 1: context of staging a play. Yeah. I think that the

525
00:28:08,920 --> 00:28:12,560
Speaker 1: puppet argument is something to keep in mind throughout considerations

526
00:28:12,600 --> 00:28:14,480
Speaker 1: the Uncanny Valley, because there are a lot of people

527
00:28:14,480 --> 00:28:15,800
Speaker 1: that there are a lot of people who have kind

528
00:28:15,800 --> 00:28:18,840
Speaker 1: of um an irrational version to puppets in general, and

529
00:28:18,880 --> 00:28:21,919
Speaker 1: certainly if you take just a still puppet and you

530
00:28:21,960 --> 00:28:24,520
Speaker 1: hold it up. There are various puppets that one might

531
00:28:24,560 --> 00:28:27,600
Speaker 1: find a little bit uncanny or creepy, etcetera. But in

532
00:28:27,600 --> 00:28:31,280
Speaker 1: the process of performing with a talented performer is going

533
00:28:31,359 --> 00:28:33,560
Speaker 1: to bring that to life. Like that's the art form.

534
00:28:33,920 --> 00:28:37,119
Speaker 1: And and there's so many different varieties of puppetry. Certainly

535
00:28:37,119 --> 00:28:42,400
Speaker 1: they're they're too broad. Categories are its situations where the

536
00:28:42,440 --> 00:28:46,040
Speaker 1: puppeteer is visible and puppet situations where puppeteers not. You know,

537
00:28:46,080 --> 00:28:48,680
Speaker 1: so you have your basic the muppet situation where you

538
00:28:48,720 --> 00:28:50,760
Speaker 1: don't see the puppeteers, but there are plenty of art

539
00:28:50,800 --> 00:28:55,760
Speaker 1: forms of puppetry performance styles in which the puppeteers very visible,

540
00:28:56,080 --> 00:28:59,240
Speaker 1: either completely or just their face. You see their eyes,

541
00:28:59,280 --> 00:29:02,080
Speaker 1: You see that there's a person involved here, and uh,

542
00:29:02,120 --> 00:29:06,120
Speaker 1: and there's not this this mystery or this sense of deception, right, yeah,

543
00:29:06,120 --> 00:29:09,920
Speaker 1: I think conceptual clues like that are very important. Also

544
00:29:10,240 --> 00:29:12,960
Speaker 1: is when you consider the the idea of going to

545
00:29:13,000 --> 00:29:17,720
Speaker 1: a puppet theater, it also includes a certain attitude charging

546
00:29:17,720 --> 00:29:21,600
Speaker 1: effect in the audience, Like an an audience member goes

547
00:29:21,680 --> 00:29:25,880
Speaker 1: to a puppet theater prepared to suspend their disbelief, like

548
00:29:26,040 --> 00:29:28,120
Speaker 1: you know what I mean, Like you put yourself in

549
00:29:28,320 --> 00:29:31,480
Speaker 1: an intentional state of open mindedness about what you're viewing,

550
00:29:32,120 --> 00:29:35,800
Speaker 1: and you give yourself an interpretive framework through which to Like,

551
00:29:36,120 --> 00:29:38,840
Speaker 1: if you were not prepared to watch a puppet theater

552
00:29:39,000 --> 00:29:42,360
Speaker 1: story and suddenly a puppet was just moving around, that

553
00:29:42,440 --> 00:29:45,520
Speaker 1: might be a lot creepier. Yeah, I agree. So part

554
00:29:45,520 --> 00:29:48,239
Speaker 1: of the Uncanny Valley effect is probably also in the

555
00:29:48,320 --> 00:29:51,200
Speaker 1: viewer themselves and in the so the context is not

556
00:29:51,320 --> 00:29:53,720
Speaker 1: just where you are, what's going on with what you're

557
00:29:53,720 --> 00:29:57,520
Speaker 1: looking at, but what you're expecting to see. Now, one

558
00:29:57,560 --> 00:30:00,880
Speaker 1: more thing that Morey points out is he thinks that

559
00:30:00,920 --> 00:30:03,880
Speaker 1: they're going to be very different rules governing the Uncanny

560
00:30:03,960 --> 00:30:08,960
Speaker 1: Valley for still objects versus moving objects. And essentially his

561
00:30:09,040 --> 00:30:13,000
Speaker 1: hypothesis is that movement is going to amplify both the

562
00:30:13,040 --> 00:30:16,160
Speaker 1: peaks and the valleys of the graph. So if you

563
00:30:16,200 --> 00:30:19,040
Speaker 1: imagine the graph we said earlier, gentle slope up to

564
00:30:19,160 --> 00:30:22,000
Speaker 1: first peak, you know, kind of cute whatever has some

565
00:30:22,120 --> 00:30:25,400
Speaker 1: human characteristics, then a dip down into too close to

566
00:30:25,480 --> 00:30:28,360
Speaker 1: human but not there, and then a final rise up

567
00:30:28,360 --> 00:30:31,920
Speaker 1: to actually human. He he would say, if it's moving,

568
00:30:32,040 --> 00:30:34,200
Speaker 1: the peaks are going to be higher and the valleys

569
00:30:34,240 --> 00:30:37,640
Speaker 1: are going to be lower. So a thing that is

570
00:30:37,720 --> 00:30:40,840
Speaker 1: moving gets greater affinity if it's good if it's at

571
00:30:40,840 --> 00:30:44,040
Speaker 1: one of these two peaks, but it's even more revolting

572
00:30:44,080 --> 00:30:47,240
Speaker 1: and unpleasant if it's at the valley. Uh So, this

573
00:30:47,400 --> 00:30:50,960
Speaker 1: this makes me think of Samara in The Ring, those

574
00:30:50,960 --> 00:30:53,560
Speaker 1: scenes where Samara is emerging from the TV or the well,

575
00:30:53,880 --> 00:30:57,640
Speaker 1: her movement is is jerky and and I understand that

576
00:30:57,920 --> 00:31:00,960
Speaker 1: they created that effect by having the actor or actress

577
00:31:01,000 --> 00:31:04,560
Speaker 1: walk backwards and then reversing the footage. So you have this,

578
00:31:05,280 --> 00:31:08,240
Speaker 1: you have this this movement that is, you know, natural,

579
00:31:08,320 --> 00:31:12,080
Speaker 1: but being reversed it it feels very unnatural and it's

580
00:31:12,080 --> 00:31:16,040
Speaker 1: hard to really pinpoint what's not working for you about it. Right.

581
00:31:16,400 --> 00:31:19,800
Speaker 1: So More in the end concludes he gives this recommendation

582
00:31:19,960 --> 00:31:23,640
Speaker 1: based on his hypothesis. He says, don't go for realism, right,

583
00:31:24,040 --> 00:31:27,959
Speaker 1: It's gonna be so hard if you're designing a humanoid robot. Now,

584
00:31:28,000 --> 00:31:30,240
Speaker 1: a lot of what we're we're talking about in these

585
00:31:30,240 --> 00:31:33,840
Speaker 1: episodes is animation. He's talking primarily about humanoid robots. But

586
00:31:33,880 --> 00:31:38,400
Speaker 1: typically these uh two fields get somewhat conflated in discussion

587
00:31:38,400 --> 00:31:40,520
Speaker 1: of the Uncanny Valley because in both cases you're trying

588
00:31:40,520 --> 00:31:44,400
Speaker 1: to create something that looks pleasingly human. Um. He wrote,

589
00:31:44,400 --> 00:31:46,520
Speaker 1: it's gonna be so hard to get out of the

590
00:31:46,600 --> 00:31:49,960
Speaker 1: valley up the second peak, that that's the reality peak

591
00:31:50,080 --> 00:31:54,479
Speaker 1: is so steep. Instead, roboticists should not try, and instead

592
00:31:54,560 --> 00:31:57,440
Speaker 1: they should aim for the very tip of the first peak.

593
00:31:58,040 --> 00:32:00,280
Speaker 1: Stick on the cuteness peak, because we know we can

594
00:32:00,320 --> 00:32:04,720
Speaker 1: get there. Think think Wally or other cute humanoid robots.

595
00:32:04,760 --> 00:32:07,360
Speaker 1: The first peak is not really that hard to attain.

596
00:32:07,760 --> 00:32:10,040
Speaker 1: People respond well to it, So why do you need

597
00:32:10,080 --> 00:32:13,080
Speaker 1: to try to go past it? Um? You know. As

598
00:32:13,120 --> 00:32:15,640
Speaker 1: for animated humans, I think a good analogy might be

599
00:32:16,480 --> 00:32:20,880
Speaker 1: here's one Pixars The Incredibles versus Final Fantasy the Spirits,

600
00:32:20,920 --> 00:32:24,000
Speaker 1: within which we already mentioned. The former they don't look

601
00:32:24,040 --> 00:32:27,320
Speaker 1: like real humans at all, right, they're cute, cartoonish, non

602
00:32:27,360 --> 00:32:30,920
Speaker 1: realistic humans, but they're quite pleasant. The latter goes for

603
00:32:31,240 --> 00:32:35,680
Speaker 1: and fails at photo realism and creates these characters that

604
00:32:35,720 --> 00:32:38,720
Speaker 1: are stiff and unsettling. In other words, he says, don't

605
00:32:38,720 --> 00:32:40,719
Speaker 1: try to climb out of the valley, just don't go

606
00:32:40,760 --> 00:32:43,880
Speaker 1: into the valley to begin with. Yeah, this this really

607
00:32:43,920 --> 00:32:46,400
Speaker 1: brings to mind just the idea of like filmmakers and

608
00:32:46,480 --> 00:32:50,680
Speaker 1: creators standing on the edge of this physical valley and

609
00:32:50,720 --> 00:32:53,200
Speaker 1: there's a local guide. They're saying, don't do it. Don't

610
00:32:53,240 --> 00:32:55,360
Speaker 1: do it, the value will consume you. And they're like, no,

611
00:32:55,600 --> 00:32:57,719
Speaker 1: you're Lucasfilm. We can do it. Yeah, we got all

612
00:32:57,720 --> 00:33:00,840
Speaker 1: this high text gear. There's no way that anything's going

613
00:33:00,880 --> 00:33:02,480
Speaker 1: to take us down there. And then they go down

614
00:33:02,520 --> 00:33:05,520
Speaker 1: there and it's just Jurassic Park or Congo with they

615
00:33:05,600 --> 00:33:09,200
Speaker 1: just get torn apart. You know, I do. I do

616
00:33:09,320 --> 00:33:12,320
Speaker 1: think the dinosaurs in Jurassic Park come out of the

617
00:33:12,400 --> 00:33:15,800
Speaker 1: uncanny valley for dinosaurs. They do. Yeah, And that introduces

618
00:33:16,000 --> 00:33:19,200
Speaker 1: an interesting wrinkle in that, like Maury is talking about

619
00:33:19,280 --> 00:33:23,800
Speaker 1: human wide qualities, it would probably be a related but

620
00:33:23,920 --> 00:33:31,040
Speaker 1: different thing to just say animal reality versus specifically human reality. Yeah,

621
00:33:31,400 --> 00:33:34,720
Speaker 1: because I mean when for non human creatures, certainly we've

622
00:33:34,720 --> 00:33:38,240
Speaker 1: been able to nail that. For ages, to stop motion creatures, often,

623
00:33:38,440 --> 00:33:40,640
Speaker 1: even if their movements are kind of herky jerky, they

624
00:33:40,760 --> 00:33:45,440
Speaker 1: feel great. Um that heard of stop motion robots in

625
00:33:45,560 --> 00:33:48,560
Speaker 1: older films, so that I've never had a problem buying

626
00:33:48,640 --> 00:33:51,160
Speaker 1: into them. And yeah, you're look into the eye of

627
00:33:51,200 --> 00:33:54,400
Speaker 1: the track or the t rex or the velociraptor and

628
00:33:54,440 --> 00:33:56,920
Speaker 1: you never doubt for a second. Yeah. But so one

629
00:33:56,960 --> 00:33:59,040
Speaker 1: thing I think we should point out is that as

630
00:33:59,200 --> 00:34:03,400
Speaker 1: prescient as Mori was of what would become this widely

631
00:34:03,440 --> 00:34:07,120
Speaker 1: recognized pop culture phenomenon his paper, it's not it's not

632
00:34:07,480 --> 00:34:11,600
Speaker 1: research really, it's just sort of observation and interesting speculation.

633
00:34:12,239 --> 00:34:14,680
Speaker 1: So what we should shift now to do, I think,

634
00:34:14,800 --> 00:34:17,600
Speaker 1: is talk about whether there's really any evidence that the

635
00:34:17,680 --> 00:34:21,000
Speaker 1: Uncanny Valley Number one exists at all? Is it really

636
00:34:21,000 --> 00:34:24,239
Speaker 1: a thing? Number two? Is it a is it a

637
00:34:24,320 --> 00:34:27,279
Speaker 1: unified phenomenon, or is it there there's some separate things

638
00:34:27,320 --> 00:34:30,520
Speaker 1: getting pulled into the net together here. And then finally

639
00:34:30,560 --> 00:34:33,399
Speaker 1: maybe we should look at if it's real, what causes it?

640
00:34:34,520 --> 00:34:37,759
Speaker 1: Why do human brains tend to react this way? So

641
00:34:37,800 --> 00:34:39,719
Speaker 1: maybe we should take a quick break, and then when

642
00:34:39,800 --> 00:34:47,680
Speaker 1: we come back we will get into more recent research. Thank. Okay,

643
00:34:47,680 --> 00:34:51,040
Speaker 1: so there's there's really no denying that there is some

644
00:34:51,120 --> 00:34:55,600
Speaker 1: kind of creepy humanoid synthetic figure effect. Right. We we've

645
00:34:55,600 --> 00:34:57,719
Speaker 1: all seen these c g I movies. We've all seen

646
00:34:57,760 --> 00:35:01,359
Speaker 1: these creepy robots and had that feeling don't like it.

647
00:35:02,160 --> 00:35:06,840
Speaker 1: But that doesn't necessarily mean that the uncanny Valley, as

648
00:35:07,200 --> 00:35:11,520
Speaker 1: described by more or as popularly conceived in culture, is

649
00:35:11,600 --> 00:35:15,440
Speaker 1: in fact a correct description of what's happening there. Right,

650
00:35:15,520 --> 00:35:18,560
Speaker 1: just because it it feels truthy, just because it lines

651
00:35:18,680 --> 00:35:21,400
Speaker 1: up with to a certain degree with how we feel

652
00:35:21,440 --> 00:35:24,080
Speaker 1: about the world, doesn't mean that it is. You know

653
00:35:24,160 --> 00:35:27,799
Speaker 1: that it is an actual effect that's taking place, and

654
00:35:28,120 --> 00:35:30,400
Speaker 1: or that it's even a fixed effect, et cetera. There

655
00:35:30,400 --> 00:35:33,200
Speaker 1: are a lot of factors to contemplate here, Like for

656
00:35:33,320 --> 00:35:36,120
Speaker 1: my own part, I've always found it interesting and I

657
00:35:36,160 --> 00:35:40,719
Speaker 1: definitely think there's something to it. However, you line it

658
00:35:40,840 --> 00:35:45,480
Speaker 1: up with similar cases in life, such as say, individuals

659
00:35:45,520 --> 00:35:49,600
Speaker 1: that you may encounter who have some degree of facial disfigurement,

660
00:35:49,640 --> 00:35:52,000
Speaker 1: and it might be extremely mild, it might be it

661
00:35:52,080 --> 00:35:54,800
Speaker 1: might be nothing more than a uh, and then you

662
00:35:54,840 --> 00:35:57,600
Speaker 1: know a lazy eye, or or you know some sort

663
00:35:57,600 --> 00:36:01,680
Speaker 1: of cleft lip or cleft palate scenario, or it just

664
00:36:01,760 --> 00:36:05,480
Speaker 1: might be like their faces maybe not all that symmetrical, right,

665
00:36:05,680 --> 00:36:09,719
Speaker 1: and you know nobody whose face is perfectly symmetrical. But

666
00:36:10,920 --> 00:36:13,360
Speaker 1: with all of these individuals, you interact with them, you

667
00:36:13,360 --> 00:36:16,960
Speaker 1: get to know them maybe, and whatever kind of like

668
00:36:17,000 --> 00:36:21,560
Speaker 1: initial um reaction is present, be it just kind of

669
00:36:21,600 --> 00:36:25,480
Speaker 1: a huh or that goes away, and you can unless

670
00:36:25,480 --> 00:36:27,799
Speaker 1: you're a total jerk, Unless you're a total jerk, or

671
00:36:28,120 --> 00:36:30,440
Speaker 1: you're gonna be able to relate to that person. You're

672
00:36:30,480 --> 00:36:32,680
Speaker 1: gonna be able to communicate with that person, and you're

673
00:36:32,719 --> 00:36:34,759
Speaker 1: not going to be thrown for a curve every time

674
00:36:34,800 --> 00:36:37,160
Speaker 1: they make eye contact with you. Yeah, I would agree

675
00:36:37,200 --> 00:36:41,600
Speaker 1: with that. So there is certainly, like in Maury's original formulation,

676
00:36:41,760 --> 00:36:45,640
Speaker 1: he he would, I think, put different kinds of um

677
00:36:45,800 --> 00:36:49,920
Speaker 1: physical abnormality somewhere on the ascending slope, on the on

678
00:36:50,080 --> 00:36:53,760
Speaker 1: the on the uncanny valley slope. So you have a normal,

679
00:36:53,840 --> 00:36:56,520
Speaker 1: healthy human up at the peak, I guess somewhere below

680
00:36:56,560 --> 00:36:59,280
Speaker 1: the artistic ideal of the great Buddhist statue or something.

681
00:36:59,640 --> 00:37:02,680
Speaker 1: But you'd have normal, healthy human. Then somewhere below them

682
00:37:02,680 --> 00:37:05,120
Speaker 1: would be people who have who look like there is

683
00:37:05,160 --> 00:37:09,160
Speaker 1: something wrong with them in terms of having uh, you know,

684
00:37:09,280 --> 00:37:12,360
Speaker 1: perfect health and symmetricality. I mean, certainly because just an

685
00:37:12,400 --> 00:37:15,759
Speaker 1: ill person. You encounter someone who is clearly a little

686
00:37:15,800 --> 00:37:18,440
Speaker 1: bit sick or a little bit hungover or whatever you

687
00:37:18,480 --> 00:37:20,920
Speaker 1: can tell, and it causes a light to go off

688
00:37:20,920 --> 00:37:24,279
Speaker 1: in your head. Yeah. Uh, And and yet we can

689
00:37:24,360 --> 00:37:27,680
Speaker 1: quite easily adapt to people like, you know, you see

690
00:37:27,719 --> 00:37:30,040
Speaker 1: somebody like that, it is you just know it is

691
00:37:30,080 --> 00:37:34,160
Speaker 1: not proper to react to somebody with revulsion. Oh yeah,

692
00:37:34,200 --> 00:37:37,040
Speaker 1: like right now in Atlanta as we're recording, this pollen

693
00:37:37,160 --> 00:37:40,399
Speaker 1: is everywhere. So there are several people in my life.

694
00:37:40,440 --> 00:37:42,560
Speaker 1: I'm not really affected by the pollen so much, but

695
00:37:42,800 --> 00:37:46,480
Speaker 1: it totally debilitates some of my coworkers, some of my

696
00:37:46,600 --> 00:37:50,520
Speaker 1: friends and red face puffy eyes. Yeah, and and sometimes

697
00:37:50,520 --> 00:37:54,160
Speaker 1: they're like walked out on allergy medication to boot and

698
00:37:54,320 --> 00:37:56,800
Speaker 1: you just get you just you know, you accept it.

699
00:37:56,840 --> 00:37:59,520
Speaker 1: You realize, oh, well, you know, my my friend here

700
00:37:59,600 --> 00:38:01,839
Speaker 1: is going to be kind of a pollen zombie for

701
00:38:01,880 --> 00:38:04,760
Speaker 1: a couple of weeks. But that doesn't mean we can't

702
00:38:05,239 --> 00:38:06,840
Speaker 1: hang out. It doesn't mean we can't work on this

703
00:38:07,040 --> 00:38:11,880
Speaker 1: or that. Yeah, so definitely, The Uncanny Valley has plenty

704
00:38:12,080 --> 00:38:15,880
Speaker 1: of critics, and plenty I think a very fair criticisms

705
00:38:15,960 --> 00:38:17,880
Speaker 1: leveled at it. I just want to go back to

706
00:38:18,080 --> 00:38:20,960
Speaker 1: one popular article. I came across a two thousand ten

707
00:38:21,120 --> 00:38:25,799
Speaker 1: article in Popular Mechanics by Eric Softge where he sort

708
00:38:25,840 --> 00:38:28,479
Speaker 1: of points out that at the time people were as

709
00:38:28,520 --> 00:38:30,960
Speaker 1: I think they are still now treating the Uncanny Valley

710
00:38:31,000 --> 00:38:34,240
Speaker 1: as a proven fact, but in fact, at the time,

711
00:38:34,320 --> 00:38:37,480
Speaker 1: he says, you know, there's really almost no convincing evidence

712
00:38:37,480 --> 00:38:40,600
Speaker 1: that such a thing even exists, and he speaks to

713
00:38:40,760 --> 00:38:44,440
Speaker 1: an expert named Carl McDorman, director of the Android Science

714
00:38:44,480 --> 00:38:48,720
Speaker 1: Center at Indiana University, and McDorman, who has conducted research

715
00:38:48,760 --> 00:38:51,960
Speaker 1: on the valley, offered his opinion in the article, saying, quote,

716
00:38:52,239 --> 00:38:54,439
Speaker 1: it turns out that there may be more than one

717
00:38:54,640 --> 00:38:57,880
Speaker 1: Uncanny Valley. It's not the overall degree of human likeness

718
00:38:58,000 --> 00:39:01,279
Speaker 1: that makes a robot or animated care acter uncanny. It's

719
00:39:01,320 --> 00:39:04,279
Speaker 1: more a matter of mismatch. If you have an extremely

720
00:39:04,640 --> 00:39:08,240
Speaker 1: realistic skin texture but at the same time cartoonish eyes

721
00:39:08,719 --> 00:39:13,760
Speaker 1: or realistic eyes and an unrealistic skin texture, that's very uncanny,

722
00:39:14,120 --> 00:39:16,759
Speaker 1: uh and the art. So that's an idea about the

723
00:39:16,800 --> 00:39:19,680
Speaker 1: perceptual mismatch that I do want to revisit later in

724
00:39:19,719 --> 00:39:22,640
Speaker 1: this episode. But the article also speaks to a guy

725
00:39:22,719 --> 00:39:27,480
Speaker 1: named David Hanson who's a roboticist who specifically specializes in

726
00:39:27,560 --> 00:39:30,800
Speaker 1: creating very realistic humanoid robots. I think he did that

727
00:39:30,800 --> 00:39:35,400
Speaker 1: that Einstein head thing. Oh yeah, nothing. So Hansen claims

728
00:39:35,440 --> 00:39:39,040
Speaker 1: that even if people find overly realistic robots creepy at first,

729
00:39:39,600 --> 00:39:41,640
Speaker 1: they get used to them within minutes. This is sort

730
00:39:41,640 --> 00:39:43,600
Speaker 1: of what you were just talking about. I think, you know,

731
00:39:44,040 --> 00:39:47,920
Speaker 1: you become acclimated even to something that you might uh,

732
00:39:48,040 --> 00:39:52,439
Speaker 1: at some kind of base level, have a negative reaction to. Yeah,

733
00:39:52,520 --> 00:39:55,279
Speaker 1: I keep thinking of having an isolation in this because

734
00:39:55,280 --> 00:39:57,480
Speaker 1: it's the game I'm currently playing, and uh and I

735
00:39:57,480 --> 00:39:59,640
Speaker 1: feel like that the c G characters are are a

736
00:39:59,719 --> 00:40:02,239
Speaker 1: pretty well done in there. I haven't felt that the

737
00:40:02,280 --> 00:40:06,440
Speaker 1: tinge of of Uncanny Valley washing over me. Some of

738
00:40:06,440 --> 00:40:09,760
Speaker 1: the voice actings a little weak. But but but speaking

739
00:40:09,760 --> 00:40:13,080
Speaker 1: of the voice, like the the the androids you encounter

740
00:40:13,160 --> 00:40:17,280
Speaker 1: though with the sex and uh androids that key. Yeah,

741
00:40:17,440 --> 00:40:20,000
Speaker 1: and when I first on Canny Valley, well, yeah, but

742
00:40:20,080 --> 00:40:22,360
Speaker 1: when I first encountered them, yeah, they had the uncanny

743
00:40:22,360 --> 00:40:26,480
Speaker 1: intentionally kind of creepy appearance and the very creepy robot voice.

744
00:40:26,840 --> 00:40:30,279
Speaker 1: But yet when they were not actively attacking me, I

745
00:40:30,360 --> 00:40:31,960
Speaker 1: kind of was. I was kind of cool with it.

746
00:40:31,960 --> 00:40:35,680
Speaker 1: It wasn't until he started becoming violent that that that

747
00:40:35,600 --> 00:40:37,960
Speaker 1: the mere sound of their voice or the appearance of

748
00:40:37,960 --> 00:40:40,520
Speaker 1: one uh down there, you know, in the distance down

749
00:40:40,520 --> 00:40:43,880
Speaker 1: the Hallway would would cause my nerves to react. I mean,

750
00:40:43,960 --> 00:40:47,040
Speaker 1: those things are funny, they're uh, they're a good part

751
00:40:47,080 --> 00:40:51,120
Speaker 1: of that game. But anyway, So in this UH article,

752
00:40:51,200 --> 00:40:55,040
Speaker 1: the author also cites some other unnamed robots roboticists, as

753
00:40:55,040 --> 00:40:57,880
Speaker 1: well as his own experience when he's talking about meeting

754
00:40:58,080 --> 00:41:01,640
Speaker 1: robots that he had previously seen on video, and one

755
00:41:01,640 --> 00:41:04,920
Speaker 1: thing he says is, you know, an Uncanny Valley effect

756
00:41:05,000 --> 00:41:06,640
Speaker 1: that was present when I saw a video of this

757
00:41:06,760 --> 00:41:09,640
Speaker 1: robot went away when I saw it in person. I

758
00:41:09,680 --> 00:41:12,560
Speaker 1: don't know if that's generally true of people. He claims

759
00:41:12,600 --> 00:41:15,200
Speaker 1: it's true. But even if this is truly the case

760
00:41:15,239 --> 00:41:17,799
Speaker 1: for robots, I'm not sure how it would apply to animations.

761
00:41:17,880 --> 00:41:22,560
Speaker 1: Probably wouldn't apply to animations. Um, But I think that

762
00:41:22,680 --> 00:41:25,920
Speaker 1: there are some good threads to start tugging at here,

763
00:41:26,000 --> 00:41:30,000
Speaker 1: because it's probably the case that there are more dimensions

764
00:41:30,080 --> 00:41:33,720
Speaker 1: to the Uncanny Valley than more he imagined in nineteen seventy,

765
00:41:33,840 --> 00:41:38,200
Speaker 1: meaning more than just that X axis of um closeness

766
00:41:38,280 --> 00:41:43,520
Speaker 1: to realistic human appearance versus distance from realistic human appearance. Yeah,

767
00:41:43,560 --> 00:41:45,879
Speaker 1: I mean, just what makes a person human, what makes

768
00:41:45,880 --> 00:41:49,080
Speaker 1: a lightness human? There's arguably a whole chorus of things

769
00:41:49,120 --> 00:41:52,160
Speaker 1: going on there. Yeah, so it would make sense that

770
00:41:52,160 --> 00:41:54,680
Speaker 1: that that chorus would play into the Uncanny Valley. Yeah.

771
00:41:54,719 --> 00:41:57,760
Speaker 1: So I do think that there are multiple other dimensions

772
00:41:57,840 --> 00:42:00,560
Speaker 1: to be explored, But I also don't think that means

773
00:42:00,600 --> 00:42:03,720
Speaker 1: we can conclude that there's nothing to the Uncanny Valley.

774
00:42:03,840 --> 00:42:06,279
Speaker 1: And in the past decade there's actually been an explosion

775
00:42:06,320 --> 00:42:08,520
Speaker 1: of research on the Uncanny Valley. So I think we

776
00:42:08,520 --> 00:42:11,120
Speaker 1: should look at a few interesting studies on the effect.

777
00:42:11,440 --> 00:42:15,240
Speaker 1: All right, Well, first one here that I came across

778
00:42:15,920 --> 00:42:18,759
Speaker 1: was a two thousand nine Princeton University study and they

779
00:42:18,800 --> 00:42:21,920
Speaker 1: looked into the effects of uncanny value of the Uncanny

780
00:42:22,000 --> 00:42:26,879
Speaker 1: Valley on maccaque monkeys, so so non human subjects. Yeah,

781
00:42:26,960 --> 00:42:28,960
Speaker 1: because that that makes sense, right if Yeah, if you

782
00:42:28,960 --> 00:42:31,839
Speaker 1: want to see if this is an evolved response, let's

783
00:42:31,840 --> 00:42:35,360
Speaker 1: look beyond the complications of human intelligence and human culture

784
00:42:35,680 --> 00:42:38,800
Speaker 1: and looked something closely related to us. Is it biological

785
00:42:38,920 --> 00:42:42,160
Speaker 1: rather than say cultural? Right, And so they showed a

786
00:42:42,200 --> 00:42:46,480
Speaker 1: selection of the primates close to real quote unquote computer

787
00:42:46,600 --> 00:42:50,160
Speaker 1: visuals of macaques to see if they responded with coups

788
00:42:50,200 --> 00:42:53,680
Speaker 1: and lip smacking as they do with their fellow monkeys. Uh,

789
00:42:53,719 --> 00:42:57,960
Speaker 1: and these these close to real computer visuals were essentially

790
00:42:58,480 --> 00:43:01,600
Speaker 1: lawnmower man monkeys. If you see lawnmower man. They kind

791
00:43:01,600 --> 00:43:04,680
Speaker 1: of asking if I've seen lawnmower man, Robert, you know

792
00:43:04,719 --> 00:43:08,479
Speaker 1: I've seen lawnmower man. Yes, so yeah, I think lawn

793
00:43:08,480 --> 00:43:10,720
Speaker 1: more man. Uh, and you kind of have an idea

794
00:43:10,800 --> 00:43:14,359
Speaker 1: that that level of computer animation, and the monkeys did

795
00:43:14,360 --> 00:43:16,399
Speaker 1: not want any part of it. They averted their eyes,

796
00:43:16,440 --> 00:43:20,680
Speaker 1: they acted frightened when confronted with lawnmower man monkey. So

797
00:43:21,400 --> 00:43:25,040
Speaker 1: it's not much, I admit, but it's a little experimental

798
00:43:25,080 --> 00:43:29,680
Speaker 1: evidence for the argument that Uncanny Valley is an evolutionary response. Right,

799
00:43:29,719 --> 00:43:32,440
Speaker 1: So if you can observe it in monkeys, there's probably

800
00:43:32,520 --> 00:43:36,080
Speaker 1: some element of it that that is biological in the brain.

801
00:43:36,280 --> 00:43:39,920
Speaker 1: It's instinctual and and not just something we've all learned

802
00:43:39,960 --> 00:43:44,080
Speaker 1: to say about weirdly looking animated characters and robots. Yeah,

803
00:43:44,520 --> 00:43:47,680
Speaker 1: and that would be maybe a weak piece of evidence,

804
00:43:47,680 --> 00:43:49,480
Speaker 1: but still a piece of evidence you could put in

805
00:43:49,520 --> 00:43:52,040
Speaker 1: the column of saying there is something there. The valley

806
00:43:52,080 --> 00:43:56,240
Speaker 1: does to some extent exist. Right now, the next study

807
00:43:56,280 --> 00:43:59,040
Speaker 1: that I ran across this comes back this to one

808
00:43:59,040 --> 00:44:02,000
Speaker 1: of the graphics that you pulled out of the believe

809
00:44:02,040 --> 00:44:05,600
Speaker 1: the original h study correct, Yeah, yeah, the original Morey's

810
00:44:05,640 --> 00:44:09,120
Speaker 1: original graphs. So in this graph and we talked about

811
00:44:09,239 --> 00:44:12,080
Speaker 1: diving down into the valley and then steadily trying to

812
00:44:12,120 --> 00:44:15,919
Speaker 1: claw yourself out on the other side, very very steep ascent. Yeah,

813
00:44:15,960 --> 00:44:18,240
Speaker 1: so you hit bottom and that's where you have a zombie.

814
00:44:19,000 --> 00:44:22,320
Speaker 1: And as you begin to scale out of the uncanny valley,

815
00:44:22,400 --> 00:44:26,640
Speaker 1: he has um uh myo electric hand and prosthetic hand

816
00:44:27,000 --> 00:44:30,360
Speaker 1: down there. As you climb back up, eventually hitting ordinary

817
00:44:30,400 --> 00:44:35,200
Speaker 1: doll and puppets and ill person and maybe hitting healthy

818
00:44:35,239 --> 00:44:37,480
Speaker 1: person at the very top. Again. But it's interesting you

819
00:44:37,520 --> 00:44:40,520
Speaker 1: have prosthetic hand down there, because this next study looks

820
00:44:40,600 --> 00:44:43,759
Speaker 1: at prosthetic and robotic and human hands. Yeah, this is

821
00:44:43,800 --> 00:44:47,080
Speaker 1: in the original study. More He talks about the variable

822
00:44:47,120 --> 00:44:50,279
Speaker 1: creepiness of prosthetic hands. And I found I found this

823
00:44:50,320 --> 00:44:52,239
Speaker 1: interesting because I don't know about you, but but growing up,

824
00:44:52,280 --> 00:44:57,200
Speaker 1: I felt like crazy robot hands, especially we're everywhere like

825
00:44:57,239 --> 00:45:01,960
Speaker 1: every G. I. Joe show or he Man type franchise,

826
00:45:02,160 --> 00:45:04,560
Speaker 1: there's always somebody. It could be a villain, it could

827
00:45:04,560 --> 00:45:08,680
Speaker 1: be a hero. But there were crazy robot hands galore. Uh,

828
00:45:08,960 --> 00:45:11,279
Speaker 1: And I always found them cool, and I feel like

829
00:45:11,719 --> 00:45:13,640
Speaker 1: a lot of us probably even fetishized them to a

830
00:45:13,800 --> 00:45:16,359
Speaker 1: certain point, Like we we didn't understand what it would

831
00:45:16,440 --> 00:45:19,359
Speaker 1: necessarily be like to lose and lose a hand and

832
00:45:19,640 --> 00:45:23,279
Speaker 1: the shortfall and the ability of technology at the time

833
00:45:23,320 --> 00:45:27,839
Speaker 1: and even today to replace that missing limb, but we thought, well,

834
00:45:27,880 --> 00:45:30,719
Speaker 1: that looks cool. Superpowered robot hands signed me up. Right.

835
00:45:31,120 --> 00:45:34,279
Speaker 1: But back to the study two thousand thirteen University of

836
00:45:34,320 --> 00:45:37,920
Speaker 1: Manchester study, and they looked at prosthetic hands. UH. They

837
00:45:38,040 --> 00:45:42,080
Speaker 1: used of forty three right handed participants, thirty six female

838
00:45:42,120 --> 00:45:44,680
Speaker 1: and seven male, and they were all looking at photos,

839
00:45:44,680 --> 00:45:47,800
Speaker 1: and the photos were divided into three categories human hands,

840
00:45:48,120 --> 00:45:51,000
Speaker 1: robotic hands like no question about it, that's a robot

841
00:45:51,040 --> 00:45:54,759
Speaker 1: hand I'm looking at like straight up terminator exoskeleton or

842
00:45:55,120 --> 00:45:59,480
Speaker 1: or or even less human, and then prosthetic hands. The results,

843
00:45:59,640 --> 00:46:02,160
Speaker 1: I have to say, reading through some some of the

844
00:46:02,200 --> 00:46:04,680
Speaker 1: writing about this UH and the original press release, the

845
00:46:04,760 --> 00:46:09,120
Speaker 1: results were kind of confusing sounding. They the subjects here

846
00:46:09,120 --> 00:46:13,319
Speaker 1: preferred human hands and robot hands, but but rated and

847
00:46:13,360 --> 00:46:17,080
Speaker 1: certainly rated prosthetic hands is more uncanny, But prosthetics that

848
00:46:17,200 --> 00:46:22,760
Speaker 1: looked more human were less eerie. Okay, so, so something

849
00:46:22,800 --> 00:46:25,760
Speaker 1: that's clearly a robot that's not too creepy. Something's clearly

850
00:46:25,800 --> 00:46:28,440
Speaker 1: a human that's not too creepy. If something is a

851
00:46:28,560 --> 00:46:31,640
Speaker 1: robot trying to be human, that might be more creepy,

852
00:46:31,760 --> 00:46:35,640
Speaker 1: but as it gets better at being human, it's less creepy,

853
00:46:35,880 --> 00:46:37,560
Speaker 1: I think. So, I think that's my take. I mean,

854
00:46:37,640 --> 00:46:41,120
Speaker 1: it also makes me wonder if if the hand alone

855
00:46:41,760 --> 00:46:45,040
Speaker 1: is an is like a subset of the uncanny Valley,

856
00:46:45,040 --> 00:46:47,920
Speaker 1: because certainly if you're if you're just working with a

857
00:46:48,000 --> 00:46:50,799
Speaker 1: hand and trying to replicate the movements, the look, the

858
00:46:50,840 --> 00:46:53,920
Speaker 1: feel of a human limb for an observer, not we're

859
00:46:53,960 --> 00:46:55,840
Speaker 1: not going to even get into the the you know,

860
00:46:55,880 --> 00:46:59,440
Speaker 1: the problems of creating something that the user can experience

861
00:46:59,680 --> 00:47:02,480
Speaker 1: as a life like limb. But if you're just looking

862
00:47:02,520 --> 00:47:04,000
Speaker 1: at it, if you don't have to worry about its

863
00:47:04,040 --> 00:47:07,200
Speaker 1: eye contact, you don't have to worry about micro expressions. Uh,

864
00:47:07,239 --> 00:47:12,160
Speaker 1: it seems like it would be an easier peak to surmount. Yeah,

865
00:47:12,239 --> 00:47:14,799
Speaker 1: so that if that is in fact the correct interpretation,

866
00:47:14,800 --> 00:47:18,200
Speaker 1: that would seem to undercut the steepness in Maury's original

867
00:47:18,239 --> 00:47:21,319
Speaker 1: graph right on the on the final peak. Yeah, that's

868
00:47:21,320 --> 00:47:24,920
Speaker 1: I mean, that's what I'm wondering, because the hand had

869
00:47:24,920 --> 00:47:28,440
Speaker 1: taken in isolation, is if you thinking to be easier

870
00:47:28,480 --> 00:47:32,799
Speaker 1: to replicate? Yeah, uh and uncanny Valley. Let's face it,

871
00:47:32,840 --> 00:47:34,440
Speaker 1: when we talk about it, most of the time we're

872
00:47:34,440 --> 00:47:41,120
Speaker 1: talking about faces. Right now, Speaking of faces, there's another study. UM.

873
00:47:41,160 --> 00:47:43,920
Speaker 1: This is a two thousand and eleven University of California,

874
00:47:44,040 --> 00:47:47,399
Speaker 1: San Diego study. UM. This is published in the Social

875
00:47:47,480 --> 00:47:50,719
Speaker 1: Cognitive and Effective Neuroscience. And they did exactly what you'd

876
00:47:50,760 --> 00:47:53,880
Speaker 1: expect researchers to do when confronted with the Uncanny Valley.

877
00:47:54,160 --> 00:47:56,480
Speaker 1: Grab the f m r I and see what our

878
00:47:56,480 --> 00:47:58,680
Speaker 1: brains are doing when we're looking at all these images.

879
00:47:58,719 --> 00:48:02,239
Speaker 1: So all these fMRI I studies, all right, well, what

880
00:48:02,239 --> 00:48:04,440
Speaker 1: what did they find? All right, I'll roll through the

881
00:48:04,440 --> 00:48:07,040
Speaker 1: basics of the study here. So twenty subjects, not a

882
00:48:07,120 --> 00:48:10,040
Speaker 1: not a huge study here, aged twenty to thirty six.

883
00:48:10,480 --> 00:48:13,120
Speaker 1: And here were some of the caveats they had in

884
00:48:13,160 --> 00:48:18,200
Speaker 1: selecting these individuals. No experience working with robots, no time

885
00:48:18,239 --> 00:48:21,640
Speaker 1: spent in Japan, no friends or family from Japan because

886
00:48:21,640 --> 00:48:25,760
Speaker 1: they wanted to avoid uh, any you know, potential cultural

887
00:48:25,800 --> 00:48:28,239
Speaker 1: exposure that would have made them would make them more

888
00:48:28,360 --> 00:48:31,680
Speaker 1: accepting of androids. Okay, so the idea is that maybe

889
00:48:31,680 --> 00:48:36,480
Speaker 1: in Japan people just experience humanoid robots way too much. Already,

890
00:48:36,560 --> 00:48:40,520
Speaker 1: they're too they're acclimatized to them. Yeah, that that's the

891
00:48:40,360 --> 00:48:43,239
Speaker 1: the argument they made, and laying out the study, let's

892
00:48:43,400 --> 00:48:45,480
Speaker 1: let's not even go there, let's just deal with people

893
00:48:45,520 --> 00:48:48,680
Speaker 1: who have less exposure to robots. And they were shown

894
00:48:48,719 --> 00:48:53,000
Speaker 1: twelve videos of a humanoid robot named repley Q two.

895
00:48:53,160 --> 00:48:55,680
Speaker 1: Oh man, I'm looking it up right now. It's it's

896
00:48:55,760 --> 00:48:58,680
Speaker 1: it's rough. But well, they watch video twelve videos of

897
00:48:58,719 --> 00:49:01,640
Speaker 1: this robot doing there is things, and they were shown

898
00:49:01,760 --> 00:49:04,600
Speaker 1: videos of humans doing the same things. And in fact,

899
00:49:04,840 --> 00:49:09,440
Speaker 1: the robots movements and mannerisms were patterned directly after the humans.

900
00:49:09,480 --> 00:49:12,480
Speaker 1: So you had a you had a human version of

901
00:49:12,520 --> 00:49:15,920
Speaker 1: the actions, you had an android version of the actions, uh,

902
00:49:15,960 --> 00:49:18,560
Speaker 1: you know, a lifelike robot, and then you had a

903
00:49:18,560 --> 00:49:21,279
Speaker 1: a stripped down version of the androids. So basically the

904
00:49:21,360 --> 00:49:23,520
Speaker 1: android of all its skin ripped off, so it looks

905
00:49:23,560 --> 00:49:26,520
Speaker 1: more like a robot, clearly a robot, and it's doing

906
00:49:26,560 --> 00:49:29,920
Speaker 1: the same motions as well. So this broke it all

907
00:49:29,960 --> 00:49:33,040
Speaker 1: down to a human with biological appearance in movement, a

908
00:49:33,160 --> 00:49:36,560
Speaker 1: robot with mechanical appearance and mechanical motion, and a human

909
00:49:36,600 --> 00:49:41,160
Speaker 1: seeming agent with the exact same mechanical movements as the robot.

910
00:49:42,680 --> 00:49:46,239
Speaker 1: Then in came the f M R I scans. So

911
00:49:46,400 --> 00:49:49,520
Speaker 1: the main brain area of note here, the the area

912
00:49:49,520 --> 00:49:51,440
Speaker 1: that that that that lit up where we saw the

913
00:49:51,440 --> 00:49:57,759
Speaker 1: most activity, the parietal cortex on both sides of the brain,

914
00:49:57,840 --> 00:50:00,480
Speaker 1: specifically in the areas that connect the part of the

915
00:50:00,480 --> 00:50:04,640
Speaker 1: brain's visual cortex that process bodily movements with the section

916
00:50:04,719 --> 00:50:08,920
Speaker 1: of the motor cortex thought to contain mirror neurons. Okay,

917
00:50:08,960 --> 00:50:12,440
Speaker 1: so those would be like the empathy parts of the

918
00:50:12,440 --> 00:50:14,719
Speaker 1: brain where you know, we we see something going on

919
00:50:15,120 --> 00:50:17,759
Speaker 1: in some other creature like us, and we empathize with

920
00:50:17,800 --> 00:50:21,280
Speaker 1: it exactly. Yeah, So when viewing the human looking android,

921
00:50:21,480 --> 00:50:25,080
Speaker 1: the brain lit up at the recognition of a human form,

922
00:50:25,120 --> 00:50:29,320
Speaker 1: but registered essentially a computing error over the movement. Something

923
00:50:29,360 --> 00:50:32,480
Speaker 1: didn't match up. Uh so it's it's not. According to

924
00:50:32,520 --> 00:50:34,680
Speaker 1: this study, it would seem that it's not the biological

925
00:50:34,719 --> 00:50:38,839
Speaker 1: movement or the biological appearance, it's the congruents or lack

926
00:50:38,880 --> 00:50:42,040
Speaker 1: of congruents between the two. You look alive, but you're dead,

927
00:50:42,120 --> 00:50:44,440
Speaker 1: you look dead, but you move you or you speak

928
00:50:44,480 --> 00:50:47,719
Speaker 1: as if you're alive. Um. So, the researchers noted that

929
00:50:47,760 --> 00:50:52,520
Speaker 1: this is something that could be retuned through exposure, but

930
00:50:52,600 --> 00:50:55,440
Speaker 1: it could be at the heart of what's going on

931
00:50:55,560 --> 00:50:58,480
Speaker 1: with the Uncanny Valley. Interesting. Well, I think we should

932
00:50:58,480 --> 00:51:02,520
Speaker 1: look at one more study potentially providing recent support for

933
00:51:02,560 --> 00:51:05,239
Speaker 1: the existence of the Uncanny Valley, and then maybe after

934
00:51:05,280 --> 00:51:07,360
Speaker 1: that we should break and then come back next time

935
00:51:07,400 --> 00:51:10,360
Speaker 1: to get into the causes, what what would be causing

936
00:51:10,360 --> 00:51:13,759
Speaker 1: this effect and uh in the future. So I want

937
00:51:13,760 --> 00:51:15,640
Speaker 1: to look at a study that came out in two

938
00:51:15,920 --> 00:51:20,200
Speaker 1: sixteen in the journal Cognition by Mather and Ricling called

939
00:51:20,320 --> 00:51:24,839
Speaker 1: Navigating a Social World with Robot Partners. A Quantitative cartography

940
00:51:24,840 --> 00:51:29,040
Speaker 1: of the Uncanny Valley. Cute invocation of map making there

941
00:51:29,080 --> 00:51:31,120
Speaker 1: because it does kind of make sense. I like the

942
00:51:31,160 --> 00:51:34,440
Speaker 1: idea of mapping the valley because that indicates that it

943
00:51:34,520 --> 00:51:38,440
Speaker 1: may expand beyond just the one dimensional dip and is

944
00:51:38,480 --> 00:51:42,000
Speaker 1: in fact more of a topographical space, you know, like

945
00:51:42,040 --> 00:51:45,480
Speaker 1: we can extend into three dimensions. But anyway, so to

946
00:51:45,520 --> 00:51:47,799
Speaker 1: get into the study, the author's note that while the

947
00:51:47,920 --> 00:51:51,200
Speaker 1: Uncanny Valley has very strong intuitive support, people tend to

948
00:51:51,239 --> 00:51:54,240
Speaker 1: take it as fact. Experimental evidence for it has been

949
00:51:54,280 --> 00:51:58,240
Speaker 1: limited and inconsistent. As as we mentioned earlier, some studies

950
00:51:58,239 --> 00:52:01,200
Speaker 1: seem to find evidence for the valley. Others don't you know,

951
00:52:01,239 --> 00:52:05,160
Speaker 1: they say this, this isn't necessarily a thing. So there

952
00:52:05,200 --> 00:52:08,319
Speaker 1: are multiple experiments here. First, they did a thing that

953
00:52:08,360 --> 00:52:10,239
Speaker 1: I think was pretty smart. If they were trying to

954
00:52:10,320 --> 00:52:14,200
Speaker 1: chart a linear progression of the up and down peaks

955
00:52:14,200 --> 00:52:18,799
Speaker 1: and valleys, they tried to generate an objectively determined gradient

956
00:52:19,000 --> 00:52:22,640
Speaker 1: of more and less human looking robots. So what a

957
00:52:22,640 --> 00:52:25,040
Speaker 1: lot of these studies do is maybe along the macaques

958
00:52:25,560 --> 00:52:29,000
Speaker 1: study ideas, they show you a lawnmower man, they show

959
00:52:29,040 --> 00:52:32,239
Speaker 1: you a real person, they show you a robot, uh,

960
00:52:32,239 --> 00:52:34,200
Speaker 1: and they ask you to characterize you know, how do

961
00:52:34,239 --> 00:52:37,040
Speaker 1: you feel about these? What they did here is that

962
00:52:37,080 --> 00:52:40,720
Speaker 1: they gathered a very large sample or relatively large sample

963
00:52:40,800 --> 00:52:44,880
Speaker 1: of eight images quote from the wild, meaning from the internet.

964
00:52:45,400 --> 00:52:47,960
Speaker 1: So these wild type robots samples, and they had a

965
00:52:47,960 --> 00:52:50,840
Speaker 1: bunch of inclusion and exclusion criteria. I don't want to

966
00:52:50,840 --> 00:52:52,640
Speaker 1: get into all of them, but they tried to limit

967
00:52:52,719 --> 00:52:56,120
Speaker 1: it to where it would it would kind of throw

968
00:52:56,160 --> 00:52:58,719
Speaker 1: out all these variables. They could complicate things like they

969
00:52:58,760 --> 00:53:02,239
Speaker 1: tried to keep just certain types of pictures of faces

970
00:53:02,320 --> 00:53:06,480
Speaker 1: of real robots that are built and uh, and they

971
00:53:06,480 --> 00:53:09,120
Speaker 1: had some exclusion criteria like it couldn't be a well

972
00:53:09,160 --> 00:53:13,400
Speaker 1: known character, a famous person, um, it couldn't have objects

973
00:53:13,400 --> 00:53:16,359
Speaker 1: overlapping the face, It couldn't be a toy, it had

974
00:53:16,400 --> 00:53:19,120
Speaker 1: to be a real humanoid robot. And then they had

975
00:53:19,160 --> 00:53:22,800
Speaker 1: subjects rate these images on what they call the mechano

976
00:53:22,880 --> 00:53:27,080
Speaker 1: humanoid scale, basically to come up with an objectively derived

977
00:53:27,239 --> 00:53:31,000
Speaker 1: score for each image by using this this empirical research,

978
00:53:31,080 --> 00:53:32,640
Speaker 1: by going to a bunch of people and saying, hey,

979
00:53:32,680 --> 00:53:36,720
Speaker 1: how mechanical is this? How human is this? And then

980
00:53:37,080 --> 00:53:40,000
Speaker 1: after they had a rating for each of these eight images,

981
00:53:40,040 --> 00:53:43,200
Speaker 1: and Robert have included an image, uh, I think down

982
00:53:43,280 --> 00:53:46,120
Speaker 1: here to show you, like what all these robots where

983
00:53:46,120 --> 00:53:48,920
Speaker 1: you can kind of see. It starts with things that

984
00:53:48,960 --> 00:53:51,200
Speaker 1: look not human at all, just like a lump of

985
00:53:51,239 --> 00:53:54,880
Speaker 1: wires and junk, and then it proceeds up to something

986
00:53:54,920 --> 00:53:57,759
Speaker 1: that looks like a picture of a guy. Yes, yeah,

987
00:53:57,840 --> 00:54:01,759
Speaker 1: very much. So. You start off with very kind of

988
00:54:02,200 --> 00:54:05,839
Speaker 1: wally asque heads. When you move in through like like

989
00:54:06,080 --> 00:54:09,920
Speaker 1: skinless gremlins, and then through the sort of the the

990
00:54:09,960 --> 00:54:15,480
Speaker 1: expected hierarchy of humanoid robots. Okay, so they've got this thing,

991
00:54:15,520 --> 00:54:18,399
Speaker 1: and then they rate all these images and sort them

992
00:54:18,440 --> 00:54:22,520
Speaker 1: into an ascending scale of humanness. And then they took

993
00:54:22,640 --> 00:54:26,600
Speaker 1: ratings in multiple different ways of likability and trustworthiness. Now,

994
00:54:26,640 --> 00:54:30,600
Speaker 1: in likability, they claimed to find a robust uncanny valley effect,

995
00:54:30,600 --> 00:54:35,000
Speaker 1: where likability increased linearly with humanoid qualities up to a

996
00:54:35,040 --> 00:54:38,439
Speaker 1: certain point, and then it took a negative dip as

997
00:54:38,480 --> 00:54:42,080
Speaker 1: the humanoid qualities continued to increase past that point, and

998
00:54:42,120 --> 00:54:44,960
Speaker 1: then once again began to rise at the far end

999
00:54:45,000 --> 00:54:47,080
Speaker 1: of the scale. Now, one thing I want to say,

1000
00:54:47,120 --> 00:54:49,440
Speaker 1: just looking at the results is it does not appear

1001
00:54:49,800 --> 00:54:52,560
Speaker 1: that people were the most bothered by the things that

1002
00:54:52,600 --> 00:54:56,400
Speaker 1: were the most human looking. Like given my understanding of

1003
00:54:56,400 --> 00:54:58,759
Speaker 1: the uncanny valley, I would have expected the stuff at

1004
00:54:58,800 --> 00:55:01,640
Speaker 1: the very top end the scale to be the most disturbing.

1005
00:55:02,400 --> 00:55:04,680
Speaker 1: But they actually kind of liked the stuff at the

1006
00:55:04,800 --> 00:55:07,960
Speaker 1: very top end of the scale. It was somewhere closer

1007
00:55:08,000 --> 00:55:10,920
Speaker 1: to the upper half middle of the scale that they

1008
00:55:10,960 --> 00:55:14,279
Speaker 1: really didn't like. Um, So, to whatever extent there is

1009
00:55:14,320 --> 00:55:17,000
Speaker 1: a real uncanny valley, it might not lie so close

1010
00:55:17,040 --> 00:55:20,200
Speaker 1: to the quote realism into the spectrum as we think.

1011
00:55:20,840 --> 00:55:24,200
Speaker 1: They also performed some trust experiments by creating a scenario

1012
00:55:24,280 --> 00:55:26,920
Speaker 1: where subjects would be asked to trust these robots to

1013
00:55:27,000 --> 00:55:30,960
Speaker 1: invest money for them, and the results there were basically

1014
00:55:31,040 --> 00:55:35,160
Speaker 1: they claimed that the trust uh experiments did show some

1015
00:55:35,280 --> 00:55:37,759
Speaker 1: Uncanny Valley effects, but the results were a little more

1016
00:55:37,800 --> 00:55:42,759
Speaker 1: complicated than on the straightforward superficial likability scale, the likability

1017
00:55:42,920 --> 00:55:47,400
Speaker 1: really did look like Uncanny Valley was being displayed. They

1018
00:55:47,440 --> 00:55:51,800
Speaker 1: also performed experiments with a more traditional quote controlled series

1019
00:55:51,800 --> 00:55:54,319
Speaker 1: of composed face images, so it would just be a

1020
00:55:54,400 --> 00:55:58,560
Speaker 1: series of basically the same face as a robot than

1021
00:55:58,640 --> 00:56:00,919
Speaker 1: a little bit more human, little it more human, little

1022
00:56:00,920 --> 00:56:04,040
Speaker 1: bit more human on this gradient of human nous. And

1023
00:56:04,120 --> 00:56:06,920
Speaker 1: they generally claim to find that there was evidence for

1024
00:56:06,960 --> 00:56:10,640
Speaker 1: the Uncanny Valley effect in both likability and trust with

1025
00:56:10,880 --> 00:56:14,959
Speaker 1: both the wild caught robot image samples and with these

1026
00:56:15,000 --> 00:56:18,760
Speaker 1: composed face images that they came up with, But as always,

1027
00:56:18,840 --> 00:56:21,160
Speaker 1: more studies are needed. But that looks like there is

1028
00:56:21,760 --> 00:56:26,000
Speaker 1: one study showing pretty solid evidence that there is something

1029
00:56:26,080 --> 00:56:29,200
Speaker 1: like an Uncanny Valley effect. Yeah, and I like the

1030
00:56:29,239 --> 00:56:32,680
Speaker 1: idea that that that that it's it's an uncanny valley.

1031
00:56:32,800 --> 00:56:36,080
Speaker 1: But maybe it's just a more more nuanced from a

1032
00:56:36,239 --> 00:56:40,720
Speaker 1: topographical standpoint. You know, they're they're more a little little

1033
00:56:40,760 --> 00:56:44,720
Speaker 1: bumps and little valleys within the overall valley, little caves

1034
00:56:44,760 --> 00:56:48,239
Speaker 1: you can crawl into and just yourself inside, and maybe

1035
00:56:48,239 --> 00:56:51,040
Speaker 1: even caves that turn into tunnels that emerge on the

1036
00:56:51,040 --> 00:56:53,359
Speaker 1: other side. Yeah, that that's an interesting thing. I mean,

1037
00:56:53,480 --> 00:56:55,480
Speaker 1: like they point out that there's a lot of variability

1038
00:56:55,520 --> 00:56:58,160
Speaker 1: in their data. Actually, like it wasn't um If you

1039
00:56:58,320 --> 00:57:01,799
Speaker 1: look at their their plot chart of where all the

1040
00:57:01,880 --> 00:57:04,120
Speaker 1: data points fall and then they plot a line going

1041
00:57:04,120 --> 00:57:06,080
Speaker 1: through it, If you plot a line going through all

1042
00:57:06,120 --> 00:57:08,799
Speaker 1: their data, it does show the uncanny valley effect. But

1043
00:57:09,120 --> 00:57:11,800
Speaker 1: you know, there there are outliers all over the place,

1044
00:57:12,200 --> 00:57:15,680
Speaker 1: like there is some there are some robots that are

1045
00:57:15,719 --> 00:57:18,960
Speaker 1: just consistently more like more than the other ones. I

1046
00:57:19,000 --> 00:57:21,720
Speaker 1: find it interestingly that the some of the higher rated ones,

1047
00:57:21,840 --> 00:57:25,400
Speaker 1: or at least I think what number seventy nine in particular,

1048
00:57:25,800 --> 00:57:30,880
Speaker 1: kind of looks like a generic human as opposed to say,

1049
00:57:30,920 --> 00:57:33,320
Speaker 1: go down to seventy four that looks like a very

1050
00:57:33,320 --> 00:57:36,360
Speaker 1: specific human, Like if I had to pick him or

1051
00:57:36,480 --> 00:57:40,880
Speaker 1: pick the human he's patterned after assumingly out of a

1052
00:57:40,920 --> 00:57:43,320
Speaker 1: police lineup. I feel like I'd be able to do it,

1053
00:57:43,360 --> 00:57:46,080
Speaker 1: but also seventy four looks angry. I'm sorry, folks, you

1054
00:57:46,120 --> 00:57:49,120
Speaker 1: can't see what we're talking about, but it's frowning at you,

1055
00:57:49,560 --> 00:57:52,520
Speaker 1: kind of like should I kill all humans or just

1056
00:57:52,960 --> 00:57:55,760
Speaker 1: shrug it off? And maybe two day's the day that

1057
00:57:55,840 --> 00:57:59,080
Speaker 1: does introduce There are a lot of complicating factories here,

1058
00:57:59,080 --> 00:58:01,919
Speaker 1: and the authors icknoled this, like these images don't all

1059
00:58:01,960 --> 00:58:05,120
Speaker 1: have necessarily the same emotional affect, like some of them

1060
00:58:05,160 --> 00:58:09,040
Speaker 1: seem happy, some seem unhappy. There's enough variability across the

1061
00:58:09,080 --> 00:58:12,960
Speaker 1: board that you can think you're getting a reasonably decent

1062
00:58:13,120 --> 00:58:17,520
Speaker 1: answer when you plot reactions across all samples. But yeah,

1063
00:58:17,680 --> 00:58:20,680
Speaker 1: there's definitely a lot of different stuff going on here

1064
00:58:21,000 --> 00:58:24,760
Speaker 1: in addition to just being more or less human. I

1065
00:58:24,800 --> 00:58:27,600
Speaker 1: like how thirty four on our on our chart here

1066
00:58:27,880 --> 00:58:31,840
Speaker 1: it seems to rely heavily on animated mustache and eyebrows.

1067
00:58:32,000 --> 00:58:34,040
Speaker 1: Oh yeah, what is that? It looks like a It

1068
00:58:34,080 --> 00:58:37,160
Speaker 1: looks like a very mustache. I can't add to what

1069
00:58:37,240 --> 00:58:40,120
Speaker 1: you've just said. It's got a white mustache and brow

1070
00:58:40,240 --> 00:58:43,000
Speaker 1: and beard, and it's saying, oh boy, it looks like

1071
00:58:43,280 --> 00:58:46,080
Speaker 1: a lot of these incomplete puppets are stripped awaite puppets,

1072
00:58:46,080 --> 00:58:47,800
Speaker 1: you see where they're like, all right, we got a

1073
00:58:47,840 --> 00:58:49,280
Speaker 1: lot of work to do on this thing, but at

1074
00:58:49,320 --> 00:58:51,320
Speaker 1: least we got the eyebrows and a mustache in place.

1075
00:58:51,400 --> 00:58:53,600
Speaker 1: But see, I find that one very likable. It doesn't

1076
00:58:53,640 --> 00:58:56,360
Speaker 1: look very human at all, but it's very I want

1077
00:58:56,360 --> 00:58:58,640
Speaker 1: to play with it. Yeah, okay, Robert, Well, we've got

1078
00:58:58,680 --> 00:59:00,200
Speaker 1: a bunch of more stuff to talk about, but think

1079
00:59:00,240 --> 00:59:02,480
Speaker 1: we should call it there and come back and finish

1080
00:59:02,480 --> 00:59:05,439
Speaker 1: our discussion of the Uncanny Valley next time. Yeah, we'll

1081
00:59:05,440 --> 00:59:07,920
Speaker 1: get into we'll go be on the Uncanny Valley. Yeah,

1082
00:59:08,000 --> 00:59:10,840
Speaker 1: so we'll we'll talk about what might cause the Uncanny

1083
00:59:10,880 --> 00:59:13,920
Speaker 1: Valley effect to whatever extent it does exist, and we

1084
00:59:13,960 --> 00:59:17,320
Speaker 1: can talk about you know, what happens when you ascend

1085
00:59:17,440 --> 00:59:21,000
Speaker 1: that that far slow? All right? Well, hey, in the meantime,

1086
00:59:21,240 --> 00:59:23,360
Speaker 1: head on over to stuff to Blow your Mind dot com.

1087
00:59:23,400 --> 00:59:25,840
Speaker 1: That is where you will find all the podcast episodes.

1088
00:59:25,920 --> 00:59:29,240
Speaker 1: You'll find videos, blog posts, as well as links out

1089
00:59:29,240 --> 00:59:31,720
Speaker 1: to our various social media accounts, and the landing page

1090
00:59:31,760 --> 00:59:34,440
Speaker 1: for this episode should include some links to some of

1091
00:59:34,480 --> 00:59:37,280
Speaker 1: the resources we're talking about here today, and if you

1092
00:59:37,320 --> 00:59:39,360
Speaker 1: want to get in touch with us as always, with

1093
00:59:39,440 --> 00:59:41,960
Speaker 1: feedback on this episode or any other, or you just

1094
00:59:42,000 --> 00:59:43,720
Speaker 1: want to say hi, or you want to let us

1095
00:59:43,760 --> 00:59:45,880
Speaker 1: know an episode topic you'd like us to cover in

1096
00:59:45,920 --> 00:59:48,560
Speaker 1: the future. You can email us at blow the Mind

1097
00:59:48,640 --> 01:00:00,240
Speaker 1: at how stuff works dot com for more on this

1098
01:00:00,400 --> 01:00:02,920
Speaker 1: and thousands of other topics. Is it how stuff works

1099
01:00:02,920 --> 01:00:14,880
Speaker 1: dot com. They can't even big, Big,