1 00:00:03,080 --> 00:00:06,160 Speaker 1: Welcome to Stuff to Blow Your Mind from how stoffworks 2 00:00:06,200 --> 00:00:14,640 Speaker 1: dot com. Hey, welcome to Stuff to Blow your Mind. 3 00:00:14,680 --> 00:00:17,000 Speaker 1: My name is Robert Lamb and I'm Joe McCormick in. 4 00:00:17,040 --> 00:00:19,159 Speaker 1: Today is going to be the second part of a 5 00:00:19,200 --> 00:00:22,520 Speaker 1: two part series we're doing on the Uncanny Valley. Last time, 6 00:00:22,760 --> 00:00:25,560 Speaker 1: we ventured into the Uncanny Valley, so if you haven't 7 00:00:25,560 --> 00:00:28,200 Speaker 1: heard that episode, you should go back and listen to that. First, 8 00:00:28,240 --> 00:00:29,920 Speaker 1: we lay a lot of the groundwork for what we're 9 00:00:29,920 --> 00:00:33,000 Speaker 1: gonna be talking about today, But we explored the origination 10 00:00:33,159 --> 00:00:36,159 Speaker 1: of the concept of the Uncanny Valley, what it means 11 00:00:36,360 --> 00:00:39,800 Speaker 1: to be in the Uncanny Valley, and some research on 12 00:00:39,920 --> 00:00:44,120 Speaker 1: whether this valley actually exists or not. Today, I think 13 00:00:44,120 --> 00:00:46,400 Speaker 1: we want to start off by looking at if if 14 00:00:46,440 --> 00:00:50,520 Speaker 1: it does exist, what might be some explanations for it. Indeed, Yeah, 15 00:00:50,560 --> 00:00:53,000 Speaker 1: we're gonna we're gonna dive into it a bit more 16 00:00:53,000 --> 00:00:57,280 Speaker 1: and move, as the title, uh suggests, beyond the Uncanny Valley. 17 00:00:58,080 --> 00:01:00,120 Speaker 1: But before we do that, I do want to talk 18 00:01:00,160 --> 00:01:03,280 Speaker 1: about RoboCop. Of course you want to talk about RoboCop, 19 00:01:03,440 --> 00:01:05,880 Speaker 1: because we talked about RoboCop pretty much every day. Yeah, 20 00:01:05,880 --> 00:01:08,920 Speaker 1: it's it's it's an important film important films, I'll say 21 00:01:09,080 --> 00:01:11,160 Speaker 1: at least at least the first to arguably the third 22 00:01:11,160 --> 00:01:14,480 Speaker 1: one to throwing the TV series if you like. But wait, 23 00:01:14,520 --> 00:01:18,280 Speaker 1: there was a TV series RoboCop. It was one of 24 00:01:18,319 --> 00:01:20,319 Speaker 1: those that would I think it would come on Sci 25 00:01:20,360 --> 00:01:25,240 Speaker 1: Fi or it came on various cable channels. I only 26 00:01:25,240 --> 00:01:28,080 Speaker 1: have a vague awareness of it because it seemed to 27 00:01:28,120 --> 00:01:33,600 Speaker 1: be a far lower key RoboCop type show. So in 28 00:01:33,640 --> 00:01:35,120 Speaker 1: many of the studies that we talked about in the 29 00:01:35,240 --> 00:01:40,080 Speaker 1: last episode, they were looking at largely three categories of 30 00:01:40,080 --> 00:01:43,520 Speaker 1: of robots and humans and androids. So you had pure 31 00:01:43,600 --> 00:01:48,200 Speaker 1: robots things that are just undeniably machines and we're mostly 32 00:01:48,240 --> 00:01:52,400 Speaker 1: okay with. Then you have humans or or or perfect 33 00:01:52,440 --> 00:01:55,440 Speaker 1: human replications. Okay, so you look at it, it either 34 00:01:55,600 --> 00:01:58,000 Speaker 1: is a human or it's such a good representation of 35 00:01:58,040 --> 00:02:01,640 Speaker 1: a human ideally that you would not think that it 36 00:02:01,720 --> 00:02:04,240 Speaker 1: was a robot. Right. The third category here is where 37 00:02:04,280 --> 00:02:06,840 Speaker 1: you're gonna get into the danger zone, right, the human 38 00:02:07,000 --> 00:02:09,919 Speaker 1: like robots where you look at it and you say, 39 00:02:09,960 --> 00:02:12,920 Speaker 1: I see what you're going for there, but it's creeping 40 00:02:12,960 --> 00:02:16,640 Speaker 1: me out. So I think it's interesting to aligne this 41 00:02:16,760 --> 00:02:20,760 Speaker 1: up with the Holy Trinity of Robocops. Okay, so this 42 00:02:20,760 --> 00:02:23,200 Speaker 1: will mostly make sense if you've seen the RoboCop films, 43 00:02:23,240 --> 00:02:24,880 Speaker 1: but I feel like most people know what we're talking 44 00:02:24,919 --> 00:02:27,480 Speaker 1: about here. First of all, you had the the proto 45 00:02:27,560 --> 00:02:30,880 Speaker 1: RoboCop add two oh nine. Oh. This is maybe the 46 00:02:30,919 --> 00:02:33,600 Speaker 1: greatest scene in the first film is before we get 47 00:02:33,639 --> 00:02:38,000 Speaker 1: a humanoid RoboCop, they just have this big drone object 48 00:02:38,120 --> 00:02:40,560 Speaker 1: that is supposed to enforce the law and it ends 49 00:02:40,600 --> 00:02:43,720 Speaker 1: up shooting somebody in the boardroom. Yeah. It's a walking 50 00:02:43,840 --> 00:02:49,240 Speaker 1: law enforcement tank with a robot commanding robot voice so 51 00:02:49,280 --> 00:02:50,840 Speaker 1: that you look at it and there's no to not 52 00:02:51,600 --> 00:02:54,600 Speaker 1: this is not a friendly device. But it's not really 53 00:02:54,639 --> 00:02:56,720 Speaker 1: humanoid at all, not really at all. It hit just 54 00:02:56,800 --> 00:03:00,600 Speaker 1: walks on big, big legs that can't even navigate and stairs. 55 00:03:01,720 --> 00:03:03,799 Speaker 1: But I would say I have great affinity for ed 56 00:03:03,880 --> 00:03:06,600 Speaker 1: to oh nine. Yeah, I mean, you know, without having 57 00:03:06,600 --> 00:03:09,240 Speaker 1: to worry about it actually shooting me. Uh, it's kind 58 00:03:09,240 --> 00:03:13,160 Speaker 1: of cute in a way. Now then we have RoboCop 59 00:03:13,880 --> 00:03:19,680 Speaker 1: itself himself, the classic RoboCop, thee Peter Weller, and uh 60 00:03:19,720 --> 00:03:23,560 Speaker 1: he is a cyborg or perhaps an android, depending on 61 00:03:23,600 --> 00:03:27,360 Speaker 1: how you want to view the descriptions. So he's he 62 00:03:27,480 --> 00:03:32,080 Speaker 1: has a relatable, living human face which is a fixed 63 00:03:32,160 --> 00:03:36,200 Speaker 1: to to honor him in some some explanations, or perhaps 64 00:03:36,200 --> 00:03:38,760 Speaker 1: to make him more comfortable not only as a police 65 00:03:38,840 --> 00:03:42,840 Speaker 1: killing machine but also a community law enforcement officer. So RoboCop, 66 00:03:42,960 --> 00:03:45,960 Speaker 1: you know, moves around with very robotic movements, speaks in 67 00:03:45,960 --> 00:03:49,520 Speaker 1: a very robotic voice, but his face is a living 68 00:03:49,600 --> 00:03:53,560 Speaker 1: human face. So in a way like that, that seems 69 00:03:53,560 --> 00:03:55,120 Speaker 1: like it might it just sort of you know, to 70 00:03:55,240 --> 00:03:58,320 Speaker 1: read perhaps more into the original film than was intended. 71 00:03:58,560 --> 00:04:01,560 Speaker 1: Perhaps this was a way to to get beyond the 72 00:04:01,680 --> 00:04:04,360 Speaker 1: Uncanny Valley. We can't replicate the human face. We'll just 73 00:04:04,400 --> 00:04:07,040 Speaker 1: get an actual human face from the dead cop and 74 00:04:07,080 --> 00:04:09,600 Speaker 1: just plaster it up there. Oh but I'd say RoboCop 75 00:04:09,640 --> 00:04:11,720 Speaker 1: with his mask on really does kind of get into 76 00:04:11,760 --> 00:04:14,760 Speaker 1: the Uncanny Valley, and and Weller does some good work 77 00:04:15,000 --> 00:04:17,160 Speaker 1: forcing us in there. Like I think that they're the 78 00:04:17,320 --> 00:04:21,599 Speaker 1: sort of going for it. Yeah, Okay, Well that brings 79 00:04:21,680 --> 00:04:25,800 Speaker 1: us to the next generation RoboCop two, which is not 80 00:04:25,920 --> 00:04:28,440 Speaker 1: just the name of the second RoboCop movie, but also 81 00:04:28,920 --> 00:04:33,279 Speaker 1: the model of RoboCop that replaced the original RoboCop. They think, Hey, 82 00:04:33,320 --> 00:04:35,400 Speaker 1: what would happen if we put tom noon in in there, 83 00:04:35,640 --> 00:04:39,760 Speaker 1: that's right. So they have another essentially a walking tank 84 00:04:39,960 --> 00:04:42,320 Speaker 1: kind of like Ed Too O nine, except it's powered 85 00:04:42,320 --> 00:04:45,200 Speaker 1: by the brain of a psychotic drug lord named Kane 86 00:04:45,680 --> 00:04:49,640 Speaker 1: played by Tom Noonan. He's fabulous in it. Uh. But 87 00:04:49,720 --> 00:04:51,880 Speaker 1: here's the here's the thing. It's walking around, it's killing 88 00:04:51,920 --> 00:04:54,200 Speaker 1: everything with a gatling gun. But then it can pop 89 00:04:54,400 --> 00:04:56,680 Speaker 1: a flat screen TV out of it out of the 90 00:04:56,880 --> 00:05:00,240 Speaker 1: front of its body, and on that screen is a 91 00:05:00,320 --> 00:05:04,240 Speaker 1: twisted uncanny lawnmower man esque c g I face of 92 00:05:04,360 --> 00:05:08,680 Speaker 1: Tom Noonan. Yeah. So so that one really leans into 93 00:05:08,720 --> 00:05:12,200 Speaker 1: the Uncanny Valley. Well yeah, and this this does point 94 00:05:12,200 --> 00:05:14,640 Speaker 1: out another thing, which is that there have been plenty 95 00:05:14,839 --> 00:05:19,919 Speaker 1: of intentional realizations of the Uncanny Valley in film. When 96 00:05:20,000 --> 00:05:24,240 Speaker 1: when people are trying to create an unsettling, unpleasant humanoid 97 00:05:24,320 --> 00:05:26,919 Speaker 1: for story purposes, if it's supposed to be a villain, 98 00:05:26,960 --> 00:05:29,520 Speaker 1: if it's supposed to make people uncomfortable, because that's its 99 00:05:29,640 --> 00:05:31,680 Speaker 1: role in the plot. So one thing I kind of 100 00:05:31,720 --> 00:05:33,800 Speaker 1: wish we'd done. I hadn't even thought about this is 101 00:05:33,839 --> 00:05:37,520 Speaker 1: too if we could talk to somebody who has intentionally 102 00:05:37,680 --> 00:05:40,800 Speaker 1: made things in the Uncanny Valley, what did they do 103 00:05:40,960 --> 00:05:44,320 Speaker 1: on purpose to get it there. If your your job 104 00:05:44,839 --> 00:05:48,039 Speaker 1: is to make a humanoid robot or an animated humanoid 105 00:05:48,080 --> 00:05:52,360 Speaker 1: figure that intentionally pushes all the bad buttons and climbs 106 00:05:52,400 --> 00:05:54,560 Speaker 1: as far down into the valley as it can, what 107 00:05:54,600 --> 00:05:57,600 Speaker 1: do you do that would that would provide some really 108 00:05:57,600 --> 00:06:01,440 Speaker 1: interesting insight into what it actually takes to get there. Well, 109 00:06:01,480 --> 00:06:03,240 Speaker 1: you know, to come back to video games, something that 110 00:06:03,279 --> 00:06:05,839 Speaker 1: comes up a lot. You see these videos going viral 111 00:06:05,920 --> 00:06:08,640 Speaker 1: where it's like just a cut scene or a clip 112 00:06:08,680 --> 00:06:11,560 Speaker 1: from the video game with a humanoid character in a 113 00:06:11,600 --> 00:06:15,120 Speaker 1: more or less human situation, except something screwed up in 114 00:06:15,160 --> 00:06:17,680 Speaker 1: the face is missing, so it's just two floating eyeballs 115 00:06:17,680 --> 00:06:21,560 Speaker 1: and maybe a floating set of digital t So the 116 00:06:21,560 --> 00:06:24,160 Speaker 1: context is key there, Like this thing is acting as 117 00:06:24,200 --> 00:06:26,160 Speaker 1: if it had a face, and it's in an environment 118 00:06:26,200 --> 00:06:29,359 Speaker 1: where we're unsupposed to just roll with it, but clearly 119 00:06:29,400 --> 00:06:32,600 Speaker 1: something's wrong. Yes, okay, Well, as we said in the 120 00:06:32,680 --> 00:06:34,799 Speaker 1: last episode, we talked about the origin of the idea, 121 00:06:34,880 --> 00:06:37,320 Speaker 1: We talked about some evidence for and against the fact 122 00:06:37,360 --> 00:06:41,640 Speaker 1: that the Uncanny Valley actually exists, to to the point 123 00:06:41,720 --> 00:06:44,440 Speaker 1: that it actually does exist to some extent, maybe not 124 00:06:44,520 --> 00:06:47,520 Speaker 1: in the naive original sense everybody would say, where it's 125 00:06:47,680 --> 00:06:52,719 Speaker 1: just related to the amount of realistic human nous in 126 00:06:52,760 --> 00:06:56,480 Speaker 1: a figure, but has other dimensions as well. What causes 127 00:06:56,680 --> 00:07:00,799 Speaker 1: our Uncanny Valley reaction? Obviously people do have this reaction 128 00:07:00,880 --> 00:07:04,800 Speaker 1: they see a humanoid robot or a humanoid animated character, 129 00:07:04,920 --> 00:07:08,600 Speaker 1: the Scorpion King, the final Fantasy, the spirits within characters, 130 00:07:08,640 --> 00:07:13,160 Speaker 1: whatever it is, and we get so, what causes it? 131 00:07:13,360 --> 00:07:16,960 Speaker 1: Why do our brains react that way? Is it biological? 132 00:07:17,160 --> 00:07:20,760 Speaker 1: Is it pure instinct? Is it a learned psychological reaction? 133 00:07:20,920 --> 00:07:23,800 Speaker 1: Is it part of our culture? Is something coming from 134 00:07:23,880 --> 00:07:26,960 Speaker 1: cognitive dissonance of some sort? Now, to go back to 135 00:07:27,040 --> 00:07:29,720 Speaker 1: the origins of the idea with massive hero Mari in 136 00:07:29,800 --> 00:07:33,480 Speaker 1: nineteen seventy and his original paper on the Uncanny Valley, 137 00:07:33,640 --> 00:07:37,280 Speaker 1: Morey speculates that the Uncanny Valley might be a side 138 00:07:37,280 --> 00:07:40,760 Speaker 1: effect of the self preservation instinct. In other words, it's 139 00:07:40,760 --> 00:07:46,080 Speaker 1: a biological adaptation that helps us avoid disease and death. Uh. 140 00:07:46,120 --> 00:07:48,520 Speaker 1: And he starts with the observation that when a normal, 141 00:07:48,640 --> 00:07:53,200 Speaker 1: healthy person becomes sick and eventually dies, they basically tend 142 00:07:53,240 --> 00:07:57,200 Speaker 1: to slide down from the second peak of the Uncanny Valley. 143 00:07:57,240 --> 00:08:01,000 Speaker 1: What we were calling the realism peak, the reality peak, 144 00:08:01,280 --> 00:08:05,320 Speaker 1: and slide down into the uncanny valley. It's like they 145 00:08:05,360 --> 00:08:08,680 Speaker 1: become more like these upsetting puppets and robots. You know, 146 00:08:08,760 --> 00:08:12,680 Speaker 1: they might uh suffer some kind of change in their 147 00:08:13,320 --> 00:08:16,280 Speaker 1: in their the appearance of their skin, of their eyes, 148 00:08:16,360 --> 00:08:20,760 Speaker 1: of their facial expressions. Things begin to look off about them. 149 00:08:20,840 --> 00:08:24,600 Speaker 1: And he writes, quote, the sense of eeriness is probably 150 00:08:24,640 --> 00:08:28,280 Speaker 1: a form of instinct that protects us from proximal rather 151 00:08:28,360 --> 00:08:33,640 Speaker 1: than distal sources of danger. Proximal sources of danger include corpses, 152 00:08:33,800 --> 00:08:38,160 Speaker 1: members of different species, and other entities we can closely approach. 153 00:08:38,440 --> 00:08:42,720 Speaker 1: Distal sources of danger include windstorms and floods. You know, 154 00:08:43,240 --> 00:08:47,280 Speaker 1: this is interesting the dimension of other species. Um, I 155 00:08:47,320 --> 00:08:50,840 Speaker 1: don't know how many films and documentaries I've seen of say, 156 00:08:50,840 --> 00:08:54,640 Speaker 1: lions running around in the natural habitat, and it's almost 157 00:08:54,679 --> 00:08:57,520 Speaker 1: never creepy, No, not not at all, and yet and 158 00:08:57,559 --> 00:08:59,280 Speaker 1: then mostly a lot of times when I'm in a zoo, 159 00:08:59,280 --> 00:09:01,920 Speaker 1: it's not creepy. But there have been times I take 160 00:09:01,960 --> 00:09:03,600 Speaker 1: my son to the zoo a lot here in Atlanta, 161 00:09:03,760 --> 00:09:06,520 Speaker 1: and there are times when we go down to the 162 00:09:06,800 --> 00:09:08,959 Speaker 1: lion enclosure and we're the only people there at the 163 00:09:09,040 --> 00:09:12,319 Speaker 1: zoo because we've arrived super early and we just we're 164 00:09:12,400 --> 00:09:14,600 Speaker 1: hanging out with a lion on the other side of 165 00:09:14,600 --> 00:09:18,120 Speaker 1: the glass. You know, we're perfectly safe, but a deep 166 00:09:18,320 --> 00:09:22,760 Speaker 1: uneasiness comes over me, washes over me, and uh, and 167 00:09:23,120 --> 00:09:27,400 Speaker 1: I'm just confronted by the the the danger of the situation, 168 00:09:27,480 --> 00:09:31,240 Speaker 1: Like there's a danger that that goes beyond any reason 169 00:09:31,679 --> 00:09:34,760 Speaker 1: because I am in close proximity to a dangerous member 170 00:09:34,880 --> 00:09:39,679 Speaker 1: of another species of carnivorous predator, tory animal that would, 171 00:09:39,800 --> 00:09:42,920 Speaker 1: in under normal conditions, potentially kill me. Now there is 172 00:09:43,080 --> 00:09:47,320 Speaker 1: I would bet a very different kind of sensation going 173 00:09:47,400 --> 00:09:51,200 Speaker 1: on inside you when you're in proximity to a lion 174 00:09:51,679 --> 00:09:55,040 Speaker 1: than when you see a creepy looking humanoid robot or 175 00:09:55,160 --> 00:10:00,160 Speaker 1: a creepy looking animation human animation. Right, Like it's it's 176 00:10:00,160 --> 00:10:02,880 Speaker 1: probably exciting. The difference between the when when we talked 177 00:10:02,880 --> 00:10:06,040 Speaker 1: about the creepiness episode the creed, the difference between the 178 00:10:06,040 --> 00:10:10,640 Speaker 1: sort of like uncomfortable threat ambiguity versus sensing that there 179 00:10:10,640 --> 00:10:13,680 Speaker 1: truly is a threat of some kind, right, And you know, 180 00:10:13,720 --> 00:10:16,760 Speaker 1: we spoke to illness here, you know, and like certainly 181 00:10:16,760 --> 00:10:18,600 Speaker 1: someone we talked about like what happens when a co 182 00:10:18,640 --> 00:10:22,160 Speaker 1: worker walks up to you and they're they're sniveling or 183 00:10:22,320 --> 00:10:26,800 Speaker 1: more a little bit pale. Uh, and they say, let's French. Well, 184 00:10:26,800 --> 00:10:29,600 Speaker 1: well hopefully not, but yeah, there's a there's an at 185 00:10:29,679 --> 00:10:33,760 Speaker 1: least an initial sense of, oh, what's wrong with this person? Um, 186 00:10:33,800 --> 00:10:35,679 Speaker 1: I wonder if what they have as contagious, should they 187 00:10:35,720 --> 00:10:38,080 Speaker 1: even be at work? I hope they cover their mouth 188 00:10:38,080 --> 00:10:40,480 Speaker 1: when they sneeze, because we are going to be concerned 189 00:10:40,480 --> 00:10:42,720 Speaker 1: on some level with catching whatever they have. If it's 190 00:10:43,040 --> 00:10:46,360 Speaker 1: it's it's transmittable, right and it I mean there are 191 00:10:46,400 --> 00:10:49,480 Speaker 1: some ways in which we know that seeing illness and 192 00:10:49,520 --> 00:10:54,120 Speaker 1: other people in sights a reaction in the disgust response, right, yeah, 193 00:10:54,120 --> 00:10:56,600 Speaker 1: And there's been actually a lot of research on the 194 00:10:56,600 --> 00:11:00,360 Speaker 1: the disgust response. Darwin wrote about it. Discuss Us from 195 00:11:00,360 --> 00:11:04,880 Speaker 1: an evolutionary standpoint, is all about disease avoidance, you know, 196 00:11:05,080 --> 00:11:09,440 Speaker 1: like do not eat this, you know, stay away from Yeah, 197 00:11:09,480 --> 00:11:12,200 Speaker 1: something's not right here. You might hurt yourself or get sick. 198 00:11:12,800 --> 00:11:17,120 Speaker 1: So we're talking about sensuous discuss So discuss it's tied 199 00:11:17,160 --> 00:11:20,560 Speaker 1: to the senses to sense information that we're absorbing. Uh. 200 00:11:20,600 --> 00:11:23,440 Speaker 1: This is deeply seated in the insula the area of 201 00:11:23,440 --> 00:11:28,320 Speaker 1: the brain that that malfunctions in patients with obsessive compulsive disorder, 202 00:11:28,800 --> 00:11:31,240 Speaker 1: causing them to say, you know, wash and clean things 203 00:11:31,400 --> 00:11:36,280 Speaker 1: endlessly or vacuum unrelenting lee. So the malfunction of that 204 00:11:36,400 --> 00:11:38,800 Speaker 1: area gives us, you know, gives us a clue into 205 00:11:38,840 --> 00:11:43,559 Speaker 1: its functionality. Uh. One interesting fact about disgusting smells, however, 206 00:11:44,000 --> 00:11:47,760 Speaker 1: is that there's a drop off point for bad smell recognition, 207 00:11:47,960 --> 00:11:51,160 Speaker 1: but not for good smells. So I think we've all 208 00:11:51,400 --> 00:11:54,520 Speaker 1: encountered this where it's that like, say, say you're in 209 00:11:54,559 --> 00:11:57,040 Speaker 1: your your office and and you share your office with 210 00:11:57,080 --> 00:12:00,480 Speaker 1: a cat box, and at some point the cat uh 211 00:12:00,760 --> 00:12:03,880 Speaker 1: causes quite a stink in there, and you register it first, 212 00:12:03,920 --> 00:12:05,679 Speaker 1: and like, jeez, I should stop what I'm doing and 213 00:12:05,760 --> 00:12:08,360 Speaker 1: clean out that cat box, but you keep working and 214 00:12:08,400 --> 00:12:11,000 Speaker 1: then after a while you don't smell it anymore. But 215 00:12:11,080 --> 00:12:13,640 Speaker 1: then maybe you step outside to check the mail, or 216 00:12:13,760 --> 00:12:15,719 Speaker 1: you go to the you know, the grocery store to 217 00:12:15,720 --> 00:12:17,880 Speaker 1: pick something up, or you know, your partner comes home 218 00:12:18,160 --> 00:12:22,079 Speaker 1: and when when you or they enter the room, you go, cheese, 219 00:12:22,120 --> 00:12:24,880 Speaker 1: what happened in here? Did the cat do something? Again? No, 220 00:12:24,920 --> 00:12:28,880 Speaker 1: you're just re smelling there. Originally you forgot about it, right, Yeah, 221 00:12:28,880 --> 00:12:32,160 Speaker 1: the the brain kind of decides. Look at this point, 222 00:12:32,240 --> 00:12:35,160 Speaker 1: I assume you know that she that the the cheese 223 00:12:35,240 --> 00:12:37,960 Speaker 1: is nasty and you're not going to eat it um 224 00:12:38,120 --> 00:12:41,120 Speaker 1: or or that yes, there is animal poop around here. 225 00:12:41,160 --> 00:12:43,720 Speaker 1: It's it's done, it's part. It's warned you. But the 226 00:12:43,840 --> 00:12:47,040 Speaker 1: good smell will keep resonating because the good smell is 227 00:12:47,440 --> 00:12:50,400 Speaker 1: probably saying, hey, there's something over here delicious to eat 228 00:12:50,679 --> 00:12:54,320 Speaker 1: with some fresh berries or whatnot. And it'll keep saying, hey, 229 00:12:54,360 --> 00:12:57,120 Speaker 1: the berries are still here. Why haven't you eaten them yet? 230 00:12:57,400 --> 00:12:59,319 Speaker 1: This is there's not a lot of sugar out here. 231 00:12:59,480 --> 00:13:01,920 Speaker 1: You should it at these berries? Why you have a chance. 232 00:13:03,160 --> 00:13:07,440 Speaker 1: So the beautiful remains beautiful, The sweet smelling remains sweet smelling. 233 00:13:07,679 --> 00:13:11,000 Speaker 1: But something that is disgusting, even as you know, discussing 234 00:13:11,000 --> 00:13:13,720 Speaker 1: as a foul smell, we can grow accustomed to. Okay, 235 00:13:13,720 --> 00:13:18,000 Speaker 1: So what's the analogy to the Uncanny Valley here? Well, 236 00:13:18,040 --> 00:13:21,040 Speaker 1: I think the analogy here is that if you have 237 00:13:21,440 --> 00:13:27,200 Speaker 1: a discussed response to to visual sense information regarding an 238 00:13:27,240 --> 00:13:32,080 Speaker 1: individual's appearance, a robots appearance, a computer animated characters appearance, 239 00:13:32,920 --> 00:13:35,360 Speaker 1: there could there could also be this disgust drop off 240 00:13:35,400 --> 00:13:37,560 Speaker 1: point as you grow accustomed to it. Oh, and that's 241 00:13:37,559 --> 00:13:39,320 Speaker 1: something that we have seen. We talked about a little 242 00:13:39,320 --> 00:13:42,560 Speaker 1: bit in the last episode, and that, uh, some people 243 00:13:42,600 --> 00:13:47,240 Speaker 1: attest that when you spend time around these robots or uh, 244 00:13:47,480 --> 00:13:49,960 Speaker 1: well it was mainly for the robots. The robots that 245 00:13:50,000 --> 00:13:53,400 Speaker 1: at first seemed creepy, they they stop bothering. You become 246 00:13:53,440 --> 00:13:56,320 Speaker 1: accustomed to them, they're not creepy anymore. I don't so 247 00:13:56,400 --> 00:13:58,400 Speaker 1: much know if that's always going to be the case 248 00:13:58,440 --> 00:14:03,120 Speaker 1: for creepy looking animated humans. Um, but who knows. Now. 249 00:14:03,160 --> 00:14:05,040 Speaker 1: Another thing to keep in mind too, is that the 250 00:14:05,080 --> 00:14:07,319 Speaker 1: discussed response is going to depend on a number of 251 00:14:07,360 --> 00:14:10,040 Speaker 1: different factors, some of which are going to be tied 252 00:14:10,400 --> 00:14:14,240 Speaker 1: to hormonal situations. So, for instance, pregnant women are more 253 00:14:14,280 --> 00:14:17,000 Speaker 1: sensitive to discussed and this is linked to their elevated 254 00:14:17,000 --> 00:14:20,760 Speaker 1: progesterone levels. So uh, and of course there's gonna be 255 00:14:20,760 --> 00:14:24,000 Speaker 1: other factors beyond that for every individual. Yeah. So I 256 00:14:24,040 --> 00:14:28,400 Speaker 1: think that there's certainly could be some amount of biological 257 00:14:29,000 --> 00:14:32,280 Speaker 1: instinctual response going on in the uncanny value effect, to 258 00:14:32,320 --> 00:14:34,840 Speaker 1: the extent that it exists. But I think also based 259 00:14:34,880 --> 00:14:36,800 Speaker 1: on what we've seen so far, that probably does not 260 00:14:36,880 --> 00:14:40,000 Speaker 1: account for all of it. Uh, And I think another 261 00:14:40,040 --> 00:14:44,080 Speaker 1: thing to consider would be going to more more complex 262 00:14:44,120 --> 00:14:48,520 Speaker 1: sort of cognitive psychology, such as cognitive dissonance. Now, if 263 00:14:48,600 --> 00:14:51,840 Speaker 1: you were to just ask me what I thought was 264 00:14:51,920 --> 00:14:55,240 Speaker 1: the most likely answer before I got into the research, 265 00:14:56,040 --> 00:14:58,480 Speaker 1: I would intuitively tend to think that the best answer 266 00:14:58,520 --> 00:15:02,880 Speaker 1: for what causes the uncanny value effect primarily is our 267 00:15:02,960 --> 00:15:07,120 Speaker 1: inherent discomfort with category confusions. Uh. This is something that 268 00:15:07,160 --> 00:15:09,480 Speaker 1: I think about a lot, in like the creation of 269 00:15:09,520 --> 00:15:12,000 Speaker 1: monster mythology and stuff like that. We we don't like 270 00:15:12,120 --> 00:15:15,880 Speaker 1: the feeling produced by by things that don't fit into 271 00:15:15,920 --> 00:15:19,960 Speaker 1: our normal taxonomys for objects in the world and seem 272 00:15:20,040 --> 00:15:24,080 Speaker 1: to violate our tax taxonomic ordering system. And this is 273 00:15:24,080 --> 00:15:27,040 Speaker 1: why I think monsters are so often hybrids of existing 274 00:15:27,120 --> 00:15:31,000 Speaker 1: things a bull's head on a man's body, things that 275 00:15:31,240 --> 00:15:36,080 Speaker 1: defy our intuitive classification rules. They make us uncomfortable and 276 00:15:36,200 --> 00:15:39,400 Speaker 1: cause a sense of unease, leading to this uncanny feeling. 277 00:15:40,280 --> 00:15:43,480 Speaker 1: So that that's what I would have intuitively said, Yeah, 278 00:15:43,480 --> 00:15:45,160 Speaker 1: that makes sense. Is it wolf or is it man? 279 00:15:45,320 --> 00:15:49,200 Speaker 1: Is it or is it man? Right? But negative affinity 280 00:15:49,280 --> 00:15:53,680 Speaker 1: resulting from this difficulty and assigning the entity to a category. 281 00:15:54,040 --> 00:15:57,680 Speaker 1: Is it robot or human. Despite my intuitive favor for 282 00:15:57,720 --> 00:16:00,800 Speaker 1: this explanation, I think it looks like your mental evidence 283 00:16:00,840 --> 00:16:03,080 Speaker 1: for this is not strong. And in fact, in some 284 00:16:03,120 --> 00:16:05,640 Speaker 1: ways some of the studies we've looked at have somewhat 285 00:16:05,680 --> 00:16:08,720 Speaker 1: invalidated this. For example, in the last episode at the end, 286 00:16:08,760 --> 00:16:11,720 Speaker 1: I was talking about that study by Mather and Rifling, 287 00:16:12,520 --> 00:16:15,720 Speaker 1: and it did not find evidence of a strong correlation 288 00:16:16,120 --> 00:16:19,400 Speaker 1: between here. Here's what you notice here, the time it 289 00:16:19,480 --> 00:16:23,920 Speaker 1: took people to rate the mechano humanoid qualities of a robot, 290 00:16:24,640 --> 00:16:28,760 Speaker 1: and that robot pictures likability. So if you were talking 291 00:16:28,760 --> 00:16:31,800 Speaker 1: it up to category confusion, you would probably think the 292 00:16:31,960 --> 00:16:35,280 Speaker 1: robots that people took the longest time to figure out 293 00:16:35,280 --> 00:16:39,160 Speaker 1: how to rate on the mechano humanoid scale, and those 294 00:16:39,200 --> 00:16:41,600 Speaker 1: would be the least likable, right, because they're the ones 295 00:16:41,640 --> 00:16:45,840 Speaker 1: causing the most category confusion. Right. But I mean you 296 00:16:45,840 --> 00:16:47,760 Speaker 1: could also say that, well, you're not maybe having not 297 00:16:47,880 --> 00:16:50,640 Speaker 1: a you're not having a visceral gut reaction to them either. 298 00:16:50,680 --> 00:16:53,480 Speaker 1: You haven't to think it out and try and you know, 299 00:16:53,560 --> 00:16:55,720 Speaker 1: analyze how you feel about it. Oh yeah, I'd say 300 00:16:55,720 --> 00:16:58,280 Speaker 1: that's exactly what we don't like. I mean, we like 301 00:16:58,400 --> 00:17:01,200 Speaker 1: to be able to viscerally category arise things. But but 302 00:17:01,240 --> 00:17:04,600 Speaker 1: then the uncanny valley is often, at least in terms 303 00:17:04,640 --> 00:17:06,359 Speaker 1: of the way you're going to find it invoked by 304 00:17:06,359 --> 00:17:09,919 Speaker 1: the average person. It's often discussed if it's as if 305 00:17:09,960 --> 00:17:12,479 Speaker 1: it's a visceral reaction, the sort of i'll kill it 306 00:17:12,480 --> 00:17:15,359 Speaker 1: with fire reaction people might have where I hate that 307 00:17:15,440 --> 00:17:17,720 Speaker 1: saying yes, I'm not a fan as well, especially when 308 00:17:17,720 --> 00:17:21,760 Speaker 1: it is applied to outside of of of fictional connotations. Right. 309 00:17:22,320 --> 00:17:24,960 Speaker 1: But so, they point out The authors here point out 310 00:17:25,000 --> 00:17:28,040 Speaker 1: that they did not find this. Uh. They point out 311 00:17:28,080 --> 00:17:31,359 Speaker 1: that it's just not a fact that the things that 312 00:17:31,440 --> 00:17:34,480 Speaker 1: took longer to look at and decide where the least likable. 313 00:17:34,560 --> 00:17:38,000 Speaker 1: Though while this is not statistically important, just as a 314 00:17:38,040 --> 00:17:41,040 Speaker 1: point of curiosity, the single face that took the longest 315 00:17:41,119 --> 00:17:44,840 Speaker 1: to rate on the mechanical versus humanoid quality was also 316 00:17:45,040 --> 00:17:48,080 Speaker 1: just about the most disliked face in their whole collection 317 00:17:48,160 --> 00:17:51,280 Speaker 1: of faces, But that was just like one outlier overall, 318 00:17:51,320 --> 00:17:55,560 Speaker 1: this did not present as a general effect. Other studies 319 00:17:55,560 --> 00:17:58,160 Speaker 1: have also looked into this and have failed to find 320 00:17:58,200 --> 00:18:01,320 Speaker 1: solid evidence for category confused and as the primary driver 321 00:18:01,480 --> 00:18:05,160 Speaker 1: of the negative affinity at the bottom of the uncanny valley. 322 00:18:05,200 --> 00:18:07,800 Speaker 1: So it looks like my intuitions here I think are wrong. 323 00:18:08,480 --> 00:18:11,840 Speaker 1: But there's something that's kind of related as an idea 324 00:18:11,880 --> 00:18:15,920 Speaker 1: that's been explored, and that is the idea of perceptual mismatch. 325 00:18:16,520 --> 00:18:20,360 Speaker 1: So several authors have advocated the idea that this perceptual 326 00:18:20,480 --> 00:18:24,160 Speaker 1: mismatch could be the primary cause of what we don't 327 00:18:24,200 --> 00:18:27,400 Speaker 1: like about things that we would intuitively say fall into 328 00:18:27,400 --> 00:18:30,680 Speaker 1: the uncanny valley. So one piece of research I want 329 00:18:30,680 --> 00:18:33,840 Speaker 1: to mention is a sort of review by uh Cat 330 00:18:33,920 --> 00:18:37,320 Speaker 1: Siri that is a review of empirical evidence on different 331 00:18:37,400 --> 00:18:41,879 Speaker 1: uncanny valley hypotheses support for perceptual mismatch as one road 332 00:18:41,960 --> 00:18:44,399 Speaker 1: to the valley of eeriness that gott to give it 333 00:18:44,440 --> 00:18:49,639 Speaker 1: a different name, apparently in Frontiers in Psychology. And so 334 00:18:49,680 --> 00:18:53,280 Speaker 1: in this study, the author's review present research and claim 335 00:18:53,400 --> 00:18:56,520 Speaker 1: that experimental research attempting to show the uncanny valley has 336 00:18:56,520 --> 00:18:59,880 Speaker 1: been inconsistent. They don't exactly say that the uncanny valley 337 00:19:00,000 --> 00:19:03,000 Speaker 1: doesn't exist, but that it's not as simple as often 338 00:19:03,040 --> 00:19:05,120 Speaker 1: believed to be. Something we've been saying for a while now. 339 00:19:05,200 --> 00:19:09,600 Speaker 1: It's it's not that any manipulation of the variable of 340 00:19:09,680 --> 00:19:14,399 Speaker 1: human likeness leads to Uncanny Valley effects. So, in other words, 341 00:19:14,520 --> 00:19:17,520 Speaker 1: that the horizontal axis on the graph is more complicated 342 00:19:17,600 --> 00:19:20,399 Speaker 1: than just the question of how realistically human is it. 343 00:19:20,480 --> 00:19:22,440 Speaker 1: I've seen this come up enough now that I'm pretty 344 00:19:22,440 --> 00:19:26,040 Speaker 1: convinced that that is not necessarily the only or even 345 00:19:26,080 --> 00:19:29,560 Speaker 1: the primary factor here. But they still recognize that there 346 00:19:29,640 --> 00:19:31,399 Speaker 1: is some kind of effect here. So they claim that 347 00:19:31,440 --> 00:19:34,879 Speaker 1: there's evidence against the category confusion basis that we were 348 00:19:34,920 --> 00:19:37,400 Speaker 1: just talking about. But they claim that there has been 349 00:19:37,400 --> 00:19:41,040 Speaker 1: good evidence in support of the perceptual mismatch hypothesis, And 350 00:19:41,080 --> 00:19:42,919 Speaker 1: I want to read what they say. They say quote 351 00:19:43,160 --> 00:19:47,280 Speaker 1: taken together, The present review suggested that although not any 352 00:19:47,400 --> 00:19:50,520 Speaker 1: kind of human likeness manipulation leads to the uncanny Valley, 353 00:19:50,520 --> 00:19:54,720 Speaker 1: the uncanny valley could be caused by more specific perceptual 354 00:19:54,800 --> 00:19:59,600 Speaker 1: mismatch conditions. Such conditions could originate at least from inconsistent 355 00:19:59,760 --> 00:20:04,160 Speaker 1: real is um levels between individual features, and the examples 356 00:20:04,160 --> 00:20:07,480 Speaker 1: they give would be like artificial eyes on a human 357 00:20:07,520 --> 00:20:11,479 Speaker 1: like face, or the presence of atypical features such as 358 00:20:11,560 --> 00:20:16,320 Speaker 1: a typically large eyes on an otherwise humanlike character. So 359 00:20:16,359 --> 00:20:19,840 Speaker 1: what they're saying there is not necessarily that you can't 360 00:20:19,880 --> 00:20:22,600 Speaker 1: tell whether it's a robot or a human, but that 361 00:20:22,800 --> 00:20:25,359 Speaker 1: there have been multiple experiments that seem to show people 362 00:20:25,400 --> 00:20:30,520 Speaker 1: are unsettled and made unhappy by things where the features 363 00:20:30,560 --> 00:20:33,400 Speaker 1: on the face or the features of the figure as 364 00:20:33,400 --> 00:20:38,239 Speaker 1: a whole are inconsistently realistic. Like we're more okay with 365 00:20:38,280 --> 00:20:42,840 Speaker 1: a robot that's consistently realistic at a certain level at 366 00:20:42,880 --> 00:20:46,720 Speaker 1: maybe say seventy percent, than something that has eyes at 367 00:20:46,800 --> 00:20:52,439 Speaker 1: nine percent and skin attent. This reminds me. This is 368 00:20:52,480 --> 00:20:53,560 Speaker 1: just coming off the top of my head. So I 369 00:20:53,600 --> 00:20:56,560 Speaker 1: don't have the artist's name here, but there's there's an 370 00:20:56,600 --> 00:20:59,480 Speaker 1: artist who's worth made the rounds where they took cartoon characters, 371 00:21:00,040 --> 00:21:03,960 Speaker 1: they depicted them realistically. So it's Simpson. Yes, Homer Simpson 372 00:21:04,040 --> 00:21:07,280 Speaker 1: with like pores on his skin, you know, like horrible. Yeah, 373 00:21:08,200 --> 00:21:09,680 Speaker 1: So that comes to mind. It is a kind of 374 00:21:09,680 --> 00:21:12,159 Speaker 1: a possible example of this. Yeah, I think that's a 375 00:21:12,160 --> 00:21:14,600 Speaker 1: good explanation. So I want to get into my main 376 00:21:14,680 --> 00:21:17,400 Speaker 1: takeaways from looking at the Uncanny Valley research so far. 377 00:21:17,440 --> 00:21:19,240 Speaker 1: Maybe you can let me know what you think about this. 378 00:21:19,760 --> 00:21:22,200 Speaker 1: I'd say, first of all, I think the Uncanny Valley 379 00:21:22,280 --> 00:21:24,919 Speaker 1: is a real thing, but it's not as simple as 380 00:21:24,960 --> 00:21:28,880 Speaker 1: Maury's original hypothesis would lead you to believe. Uh. First 381 00:21:28,920 --> 00:21:32,080 Speaker 1: of all, people definitely do get creeped out by lots 382 00:21:32,119 --> 00:21:36,680 Speaker 1: of almost human looking things, But it's not necessarily just 383 00:21:36,840 --> 00:21:41,879 Speaker 1: that the near failed human realism is what makes them unsettling. 384 00:21:41,880 --> 00:21:45,040 Speaker 1: There are other things that appear to be making them unsettling, though, 385 00:21:45,080 --> 00:21:49,359 Speaker 1: that the near humanness plays some kind of role. And 386 00:21:49,400 --> 00:21:51,000 Speaker 1: the other big thing is that there appear to be 387 00:21:51,080 --> 00:21:56,280 Speaker 1: multiple dimensions to explain the phenomenon. Right, So, synthetic humanoid images, 388 00:21:56,280 --> 00:22:01,359 Speaker 1: whether robotic or animated, offer multiple dimensions of attraction and revulsion. 389 00:22:01,800 --> 00:22:05,400 Speaker 1: I think it's possible that there are some biologically triggered effects, 390 00:22:05,760 --> 00:22:08,840 Speaker 1: the appearance of health or disease, the appearance of life 391 00:22:08,920 --> 00:22:11,360 Speaker 1: or death. But then I think there are possibly other 392 00:22:11,400 --> 00:22:17,040 Speaker 1: things triggered by psychological cognitive dissonance. Probably not category confusion, um, 393 00:22:17,200 --> 00:22:20,320 Speaker 1: but but some good evidence for this idea of the 394 00:22:20,359 --> 00:22:24,440 Speaker 1: perceptual mismatch being the cause. And then the final thing 395 00:22:24,680 --> 00:22:29,200 Speaker 1: is that the Uncanny Valley effect is context dependent. How 396 00:22:29,240 --> 00:22:32,440 Speaker 1: long have you been exposed to the image in what's setting? 397 00:22:33,160 --> 00:22:35,440 Speaker 1: Is it part of a narrative or some other context 398 00:22:35,560 --> 00:22:38,320 Speaker 1: in which you're being asked to suspend your disbelief or 399 00:22:38,359 --> 00:22:42,560 Speaker 1: otherwise put yourself in a state of openness. Robert, what 400 00:22:42,560 --> 00:22:44,239 Speaker 1: do you think about all this so far? You've got 401 00:22:44,280 --> 00:22:47,760 Speaker 1: any disagreement? No, I mean I feel like my view 402 00:22:47,760 --> 00:22:50,680 Speaker 1: on it closely lines up with with with yours here 403 00:22:50,720 --> 00:22:53,640 Speaker 1: basically that it's just that there is an effect going on, 404 00:22:53,720 --> 00:22:57,600 Speaker 1: but it's far it's far more nuanced than simply oh 405 00:22:57,640 --> 00:23:00,760 Speaker 1: these are these are the factors that make something fall 406 00:23:00,840 --> 00:23:04,600 Speaker 1: into the uncanny valley, not just how realistically human. There's 407 00:23:04,640 --> 00:23:07,080 Speaker 1: there's other stuff going on, right, and not just a 408 00:23:07,119 --> 00:23:12,120 Speaker 1: mere hybridization. I was instantly thinking about um, the borg 409 00:23:12,200 --> 00:23:15,360 Speaker 1: and uh and occasionally, you know the sort of sexy 410 00:23:15,400 --> 00:23:19,119 Speaker 1: boards that show up in the Star Trek universe, like 411 00:23:19,160 --> 00:23:23,720 Speaker 1: there's there's clearly category confusion going on there, but they're 412 00:23:23,760 --> 00:23:27,720 Speaker 1: they're not depicted as particularly uncanny, like it was the 413 00:23:27,760 --> 00:23:31,280 Speaker 1: board Queen. Was she uncanny kind of? I don't know. 414 00:23:31,440 --> 00:23:33,040 Speaker 1: I mean, even when I'm not a big fan of 415 00:23:33,080 --> 00:23:38,800 Speaker 1: the way the board look well, but the outside of 416 00:23:38,800 --> 00:23:41,199 Speaker 1: the board. You can also think of, you know, various 417 00:23:41,240 --> 00:23:45,360 Speaker 1: sort of hybrid human creatures depicted in fantasy and fiction 418 00:23:45,840 --> 00:23:48,719 Speaker 1: that that are created in such a way to the 419 00:23:48,720 --> 00:23:53,240 Speaker 1: the alluring. Uh, like they managed to fetishize the inhuman 420 00:23:53,320 --> 00:23:57,840 Speaker 1: qualities of them the category confusion. Yeah, uh yeah. It 421 00:23:57,880 --> 00:24:01,119 Speaker 1: makes me think that there are certain qualities of the 422 00:24:01,200 --> 00:24:04,639 Speaker 1: human appearance that, if altered, are much more significant in 423 00:24:04,720 --> 00:24:08,359 Speaker 1: terms of our affects response than others. So it could 424 00:24:08,440 --> 00:24:10,399 Speaker 1: be I'm just making this up. I don't know if 425 00:24:10,440 --> 00:24:14,479 Speaker 1: this is true, but that like getting the getting the 426 00:24:14,640 --> 00:24:18,560 Speaker 1: size of the eyes wrong could quite easily lead to 427 00:24:18,600 --> 00:24:22,600 Speaker 1: a disgust response and revulsion, but getting the size of 428 00:24:22,640 --> 00:24:26,359 Speaker 1: the nose wrong wouldn't. Does that make sense? Yeah? Yeah, 429 00:24:26,480 --> 00:24:29,480 Speaker 1: or just thinking of eyes like definitely, making the eyes 430 00:24:30,080 --> 00:24:33,720 Speaker 1: inappropriately large leads a creepy factor, and this is often employed. 431 00:24:34,440 --> 00:24:38,320 Speaker 1: I instantly think of the vampire movie. What twenty thirty 432 00:24:38,400 --> 00:24:40,760 Speaker 1: days of Night is that the name of it? Oh, 433 00:24:40,920 --> 00:24:42,480 Speaker 1: something like that, Yeah, where they did some sort of 434 00:24:42,520 --> 00:24:44,720 Speaker 1: digital effect to make ory. I don't remember the number, 435 00:24:45,440 --> 00:24:48,600 Speaker 1: some number of days of PPD days of night. Um, 436 00:24:48,920 --> 00:24:53,119 Speaker 1: I didn't actually see if the trailers were we're certainly interesting. 437 00:24:53,560 --> 00:24:55,520 Speaker 1: But likewise, if you just take an individual and have 438 00:24:55,600 --> 00:24:58,840 Speaker 1: them wear blackout contact lenses, yeah, like that is often 439 00:24:58,960 --> 00:25:00,800 Speaker 1: sometimes that's played up for creepiness, but a lot of 440 00:25:00,800 --> 00:25:04,080 Speaker 1: times it's played up for to be alluring. You'll have uh, 441 00:25:04,480 --> 00:25:08,520 Speaker 1: male or female characters that are are otherwise dressed in 442 00:25:08,560 --> 00:25:11,040 Speaker 1: some alluring fashion, but they have blacked out eyes and 443 00:25:11,080 --> 00:25:14,560 Speaker 1: it's who it's kind of like supernatural, sexy cool, as 444 00:25:14,560 --> 00:25:16,639 Speaker 1: opposed to just like, oh my god, why why are 445 00:25:16,640 --> 00:25:21,719 Speaker 1: your eyes pits of darkness? Yeah, but maybe that's just me. Okay, Well, 446 00:25:21,760 --> 00:25:23,320 Speaker 1: I think we should take a quick break and when 447 00:25:23,320 --> 00:25:30,760 Speaker 1: we come back, we will go beyond the Uncanny Valley. 448 00:25:31,400 --> 00:25:34,560 Speaker 1: All right, we're back, Okay, So Robert, I can recall 449 00:25:34,680 --> 00:25:37,440 Speaker 1: discussions going back for years about whether we're going to 450 00:25:37,520 --> 00:25:39,560 Speaker 1: make it out of the Uncanny Valley in the realm 451 00:25:39,600 --> 00:25:42,399 Speaker 1: of robotics or animation, And I think from here on 452 00:25:42,880 --> 00:25:45,960 Speaker 1: I want to focus primarily on animation, just just to 453 00:25:46,040 --> 00:25:49,000 Speaker 1: keep us focused. And I think there are actually two 454 00:25:49,000 --> 00:25:52,960 Speaker 1: separate questions here, assuming that the Uncanny Valley is to 455 00:25:53,119 --> 00:25:55,800 Speaker 1: some extent to go heerent idea. We've already explained all 456 00:25:55,840 --> 00:25:58,800 Speaker 1: the ways in which it's obviously way more complicated than 457 00:25:58,840 --> 00:26:03,800 Speaker 1: the naive popular culture culture understanding of it. But the 458 00:26:03,880 --> 00:26:07,760 Speaker 1: two big questions. Number one, can we make realistic looking 459 00:26:07,840 --> 00:26:11,240 Speaker 1: humanoid characters that aren't creepy I think the answer here 460 00:26:11,280 --> 00:26:14,560 Speaker 1: is yes, I think it's not a two dimensional graph. 461 00:26:14,640 --> 00:26:16,879 Speaker 1: I think you can make things that aren't quite photo 462 00:26:16,920 --> 00:26:21,160 Speaker 1: realistic but look realistic that aren't creepy. Current generation video 463 00:26:21,200 --> 00:26:23,639 Speaker 1: games have been doing this, and as I mentioned in 464 00:26:23,640 --> 00:26:26,119 Speaker 1: the last episode, I think that their tricks to doing 465 00:26:26,160 --> 00:26:30,159 Speaker 1: this it's apparently in achieving like the right combination of 466 00:26:30,240 --> 00:26:33,760 Speaker 1: realistic traits and unrealistic traits that maybe you would just 467 00:26:33,920 --> 00:26:37,119 Speaker 1: land on by doing trial and error in design over time. 468 00:26:37,600 --> 00:26:41,600 Speaker 1: You would never mistake these characters for photographs of real humans. 469 00:26:42,080 --> 00:26:45,720 Speaker 1: But they're also not cartoony. They've got this feeling of 470 00:26:45,920 --> 00:26:49,919 Speaker 1: really real ishness, if you know what I mean. But 471 00:26:50,000 --> 00:26:53,480 Speaker 1: they've they've they've attained sort of a generally acceptable plateau 472 00:26:53,680 --> 00:26:57,520 Speaker 1: of realistic affect, but they're not skewing into these different 473 00:26:57,600 --> 00:27:01,600 Speaker 1: danger zones adjacent photo real is him where the shortcomings 474 00:27:01,640 --> 00:27:04,200 Speaker 1: become creepy and off putting and we don't like it. 475 00:27:05,800 --> 00:27:08,600 Speaker 1: Then there would be another question, and that's just can 476 00:27:08,680 --> 00:27:13,720 Speaker 1: we make animated characters that are robustly indistinguishable from human like? 477 00:27:13,760 --> 00:27:16,240 Speaker 1: Can we get all the way up the other side 478 00:27:16,480 --> 00:27:20,760 Speaker 1: of the mountain, up to the peak of reality? And 479 00:27:20,920 --> 00:27:23,520 Speaker 1: last week, if you'd asked me, my personal answer would 480 00:27:23,520 --> 00:27:26,240 Speaker 1: have been no, not yet. But I think that's actually 481 00:27:26,280 --> 00:27:29,240 Speaker 1: not as clear cut as we would first guess, because 482 00:27:29,280 --> 00:27:31,520 Speaker 1: you think that perhaps many of the humans we see 483 00:27:31,520 --> 00:27:35,439 Speaker 1: on TV are actually digital creations. Oh I know for 484 00:27:35,520 --> 00:27:40,600 Speaker 1: a fact that that who's that guy, that Jimmy Fallon guy. 485 00:27:40,720 --> 00:27:45,359 Speaker 1: Oh yeah, Jimmy Fallon might be a computer generated that 486 00:27:45,480 --> 00:27:48,159 Speaker 1: is not a person. He has been generated by a 487 00:27:48,160 --> 00:27:53,159 Speaker 1: computer that's in Palo Alto, California. It's a supercomputer. I mean, 488 00:27:53,160 --> 00:27:55,680 Speaker 1: it's a really good computer. But yeah, Well, I often 489 00:27:55,720 --> 00:27:58,720 Speaker 1: feel the same way about Michael Fastbender, And granted it's 490 00:27:58,720 --> 00:28:01,280 Speaker 1: complicated by the fact that he has he has a 491 00:28:01,359 --> 00:28:04,919 Speaker 1: thing for playing androids recently, but at times you're just like, no, 492 00:28:05,160 --> 00:28:07,359 Speaker 1: he's just a little too handsome. There's something in human 493 00:28:07,400 --> 00:28:10,879 Speaker 1: about this, this man's handsomeness, in his charm. So I 494 00:28:10,920 --> 00:28:13,639 Speaker 1: want to talk about one thing that is that has 495 00:28:13,680 --> 00:28:16,640 Speaker 1: given me pause on this subject, and it's going back 496 00:28:16,680 --> 00:28:18,000 Speaker 1: to what we talked about at the beginning of the 497 00:28:18,080 --> 00:28:21,840 Speaker 1: last episode Rogue one. Yes, So back to the c 498 00:28:22,000 --> 00:28:24,640 Speaker 1: G I grandmof Tarken when I saw when I first 499 00:28:24,680 --> 00:28:26,600 Speaker 1: saw Rogue one, I liked a lot of things about 500 00:28:26,600 --> 00:28:28,720 Speaker 1: the movie. But I did not really like the the 501 00:28:28,800 --> 00:28:32,719 Speaker 1: c g I Tarken, the the almost Peter Cushing was 502 00:28:33,320 --> 00:28:36,040 Speaker 1: very very good, and I really mean that, I mean 503 00:28:36,720 --> 00:28:40,280 Speaker 1: shockingly good, but still not quite real to me, still 504 00:28:40,360 --> 00:28:44,160 Speaker 1: kind of distracting because of how slightly off it was. 505 00:28:44,320 --> 00:28:47,080 Speaker 1: I would not have mistaken it for a real person. 506 00:28:47,680 --> 00:28:50,240 Speaker 1: But the other day I was talking in the office 507 00:28:50,280 --> 00:28:53,200 Speaker 1: to Holly fry Who. It's Holly a Star Wars fan. 508 00:28:54,760 --> 00:28:56,760 Speaker 1: She's so, she's one of the hosts of Stuff You 509 00:28:56,800 --> 00:28:58,880 Speaker 1: Missed in History Class, one of our one of our 510 00:28:59,440 --> 00:29:02,600 Speaker 1: podcast in the podcast family here. Yeah, she has hands 511 00:29:02,640 --> 00:29:05,320 Speaker 1: down the most Star Wars knowledgeable person in the office 512 00:29:05,360 --> 00:29:08,360 Speaker 1: in an office full of nerds. Yeah, I should point 513 00:29:08,400 --> 00:29:12,280 Speaker 1: out that Holly has slash had like a golden ticket 514 00:29:12,320 --> 00:29:14,479 Speaker 1: to go see Rogue one anytime she wanted to at 515 00:29:14,520 --> 00:29:18,360 Speaker 1: the theater. What are you serious? And serious? This is? Yeah? Yeah, 516 00:29:18,400 --> 00:29:20,960 Speaker 1: leget where'd that come from? I don't know, I don't know. 517 00:29:21,000 --> 00:29:23,280 Speaker 1: I'm not I'm not at that level of a fandom 518 00:29:23,320 --> 00:29:25,840 Speaker 1: where I'm even offered such things. I know. So if 519 00:29:26,160 --> 00:29:28,160 Speaker 1: you want to have a funny experience, go up to 520 00:29:28,200 --> 00:29:32,280 Speaker 1: Holly and just like ask some really obscure random question 521 00:29:32,360 --> 00:29:35,240 Speaker 1: about Star Wars where you think it could not be 522 00:29:35,360 --> 00:29:38,960 Speaker 1: possible that there's an actual answer to this, like, oh, 523 00:29:39,040 --> 00:29:42,040 Speaker 1: that stormtrooper on the left, where did he? What planet 524 00:29:42,080 --> 00:29:44,400 Speaker 1: was he born on? Holly will have an answer. She'll 525 00:29:44,440 --> 00:29:46,840 Speaker 1: be like, oh, that was actually addressed in dialogue in 526 00:29:46,880 --> 00:29:50,360 Speaker 1: the Greek dub of this episode of Clone Wars. So 527 00:29:50,480 --> 00:29:53,160 Speaker 1: Holly has amazing Star Wars knowledge. She is super fun 528 00:29:53,200 --> 00:29:56,160 Speaker 1: to talk to about the Star Wars universe. But anyway, 529 00:29:56,600 --> 00:29:58,840 Speaker 1: Holly pointed out that while a lot of people like 530 00:29:58,960 --> 00:30:01,160 Speaker 1: me were saying that the c G I. Tarkan was 531 00:30:01,200 --> 00:30:04,760 Speaker 1: a few pixels short of escaping the valley, then again, 532 00:30:04,800 --> 00:30:07,280 Speaker 1: there were plenty of people, including some older people that 533 00:30:07,400 --> 00:30:10,560 Speaker 1: she knew, who couldn't tell that it wasn't a real person. 534 00:30:11,080 --> 00:30:14,480 Speaker 1: They literally they couldn't tell. Well, I'm worried about my 535 00:30:14,560 --> 00:30:17,280 Speaker 1: viewing upcoming viewing of the film because I have I've 536 00:30:17,320 --> 00:30:21,840 Speaker 1: been preconditioned to have a certain response to the to 537 00:30:21,960 --> 00:30:25,440 Speaker 1: the Tarkan bot here. Oh, I'm sorry that we've had 538 00:30:25,440 --> 00:30:27,520 Speaker 1: this discussion before you were able to see the movie 539 00:30:27,560 --> 00:30:30,840 Speaker 1: for yourself. It'll be interesting being preconditioned. Will I go 540 00:30:30,920 --> 00:30:34,880 Speaker 1: into it, you know, expecting an abomination, and like that 541 00:30:35,000 --> 00:30:37,440 Speaker 1: the level of detail will overwhelm me and it won't matter. 542 00:30:37,920 --> 00:30:40,040 Speaker 1: Or am I going to go into there and nothing 543 00:30:40,120 --> 00:30:41,960 Speaker 1: is gonna fool me because I'm gonna be looking for 544 00:30:41,960 --> 00:30:46,440 Speaker 1: the cracks, You know, I can. I can put myself 545 00:30:46,440 --> 00:30:51,480 Speaker 1: in a mindset where I think it's possible. I might 546 00:30:51,520 --> 00:30:54,160 Speaker 1: not have known that it was a c g I 547 00:30:54,200 --> 00:30:56,760 Speaker 1: effect if I wasn't familiar with what to look for, 548 00:30:56,840 --> 00:30:58,680 Speaker 1: Like if I didn't watch a lot of movies that 549 00:30:58,800 --> 00:31:00,960 Speaker 1: had c g I effects in them, and if I 550 00:31:01,000 --> 00:31:03,680 Speaker 1: didn't complain about c g I a lot. I'm sorry, 551 00:31:03,680 --> 00:31:07,400 Speaker 1: guilty is I'm guilty of that? Uh? If I wasn't 552 00:31:07,480 --> 00:31:11,280 Speaker 1: aware that Peter Cushing was dead, Um, if it wasn't 553 00:31:11,320 --> 00:31:13,400 Speaker 1: if I wasn't sort of prepared to see a lot 554 00:31:13,440 --> 00:31:15,760 Speaker 1: of high tech c g I by virtue of the 555 00:31:15,800 --> 00:31:18,480 Speaker 1: fact that I'm sitting in a theater for a Lucasfilm movie, 556 00:31:18,960 --> 00:31:21,240 Speaker 1: all those things. If you took away all the context 557 00:31:21,320 --> 00:31:25,080 Speaker 1: and my pre knowledge, I'm very might possibly have fallen 558 00:31:25,120 --> 00:31:27,440 Speaker 1: for it. I think I might have just it might 559 00:31:27,480 --> 00:31:29,520 Speaker 1: have just gone past me. If I was absorbed in 560 00:31:29,520 --> 00:31:31,840 Speaker 1: the story, I might have thought, Yeah, it's kind of strange. 561 00:31:31,880 --> 00:31:35,440 Speaker 1: Looking dude. But it's just a dude, and I think 562 00:31:35,480 --> 00:31:39,320 Speaker 1: it gets better or worse depending on your perspective. So 563 00:31:39,400 --> 00:31:44,880 Speaker 1: I have in October newspiece from BBC Asia here about 564 00:31:44,880 --> 00:31:49,800 Speaker 1: a character called Saia, a computer animated character created by 565 00:31:49,920 --> 00:31:53,320 Speaker 1: the Japanese husband and wife graphic design team Terry Yuki 566 00:31:53,400 --> 00:31:56,800 Speaker 1: and Yuka Ishikawa. And I mentioned this one in particular 567 00:31:56,840 --> 00:31:58,719 Speaker 1: because before we did this episode, I went and I 568 00:31:58,760 --> 00:32:00,840 Speaker 1: looked up what can that ared a lot of the 569 00:32:00,880 --> 00:32:05,560 Speaker 1: most realistic c g I character creations, the most impressive animations, 570 00:32:06,040 --> 00:32:08,120 Speaker 1: this one came up, and I think this was the 571 00:32:08,120 --> 00:32:12,000 Speaker 1: most impressive to me. It's probably the most photo real 572 00:32:12,600 --> 00:32:16,320 Speaker 1: computer generated human I've come across so far. So Siah 573 00:32:16,480 --> 00:32:19,400 Speaker 1: is supposed to be a seventeen year old Japanese student 574 00:32:20,080 --> 00:32:22,760 Speaker 1: and the creators have been working on her design for 575 00:32:22,800 --> 00:32:25,840 Speaker 1: a couple of years now, and as versions of Siah 576 00:32:25,920 --> 00:32:28,720 Speaker 1: have been posted on the Internet, people have widely reacted 577 00:32:28,720 --> 00:32:31,760 Speaker 1: with comments like I can't believe that's not a real person, 578 00:32:32,920 --> 00:32:35,520 Speaker 1: and I kind of have to agree. I'm looking at 579 00:32:35,560 --> 00:32:37,760 Speaker 1: these these pictures of her. There are a couple of 580 00:32:37,760 --> 00:32:41,720 Speaker 1: different generations of her design up, and the most recent 581 00:32:41,720 --> 00:32:45,880 Speaker 1: one just looks like a photograph of a person. Yeah, 582 00:32:45,920 --> 00:32:48,960 Speaker 1: I I can't tell that that is not a person. 583 00:32:49,160 --> 00:32:53,680 Speaker 1: I I have no recourse to critical faculties in my 584 00:32:53,720 --> 00:32:56,080 Speaker 1: mind that would say no, here's where you can tell 585 00:32:56,160 --> 00:32:59,200 Speaker 1: that that's not a real person. Now, at the same time, 586 00:32:59,240 --> 00:33:00,720 Speaker 1: I do have to come to to come in a 587 00:33:00,800 --> 00:33:03,520 Speaker 1: made earlier that that this is also a it's a 588 00:33:03,640 --> 00:33:06,840 Speaker 1: it's a it's a pretty face, it's a very standard 589 00:33:06,880 --> 00:33:10,480 Speaker 1: face like this is this is leading lady material. Whereas 590 00:33:10,840 --> 00:33:12,880 Speaker 1: I think it gets more problematic when you look at 591 00:33:12,920 --> 00:33:16,760 Speaker 1: the character actor type figures such as Peter Cushing exactly. 592 00:33:16,840 --> 00:33:19,520 Speaker 1: They have such a distinctive face, yes, and Peter Cushing. 593 00:33:19,840 --> 00:33:22,040 Speaker 1: So this is one thing that helps, I think is 594 00:33:22,080 --> 00:33:26,800 Speaker 1: that it's a young character who has very smooth features. Uh, 595 00:33:26,840 --> 00:33:29,480 Speaker 1: Peter Cushing has a lot of cracks and crags, a 596 00:33:29,560 --> 00:33:31,479 Speaker 1: lot of wrinkles, And I think that that may actually 597 00:33:31,520 --> 00:33:35,400 Speaker 1: be simply having more texture on your face could make 598 00:33:35,440 --> 00:33:38,479 Speaker 1: it much more difficult to make a photo real copy 599 00:33:38,560 --> 00:33:42,840 Speaker 1: of you. That's entirely possible. But to get back to Saia. 600 00:33:43,000 --> 00:33:46,760 Speaker 1: So in October of last year, the Artist's debuted the 601 00:33:46,800 --> 00:33:50,800 Speaker 1: first animated clip of Siah, which they created using motion 602 00:33:50,840 --> 00:33:54,760 Speaker 1: capture technology, and they debuted at a Japanese consumer electronics show. 603 00:33:55,520 --> 00:33:59,280 Speaker 1: I watched this footage, and I think Maury's distinction about 604 00:33:59,320 --> 00:34:03,800 Speaker 1: having different standards for motion and still images does apply, 605 00:34:03,960 --> 00:34:07,200 Speaker 1: because while with the still image, I can't tell that's 606 00:34:07,240 --> 00:34:10,600 Speaker 1: not a real person, with the short animated clip, I can. 607 00:34:10,760 --> 00:34:12,560 Speaker 1: I can tell it's not a real person, but it's 608 00:34:12,560 --> 00:34:18,520 Speaker 1: still very very impressive, not as absolutely photo real as 609 00:34:18,520 --> 00:34:21,880 Speaker 1: the still images. But I don't know. I wonder to 610 00:34:21,960 --> 00:34:26,239 Speaker 1: what extent this gap is just um that motion animation 611 00:34:26,280 --> 00:34:29,400 Speaker 1: is a bigger technical project, it takes more investment and 612 00:34:29,440 --> 00:34:32,400 Speaker 1: money and all that um, And to what extent the 613 00:34:32,400 --> 00:34:36,000 Speaker 1: gap is within the viewers mind? Essentially, to what extent 614 00:34:36,080 --> 00:34:38,480 Speaker 1: it's caused by the fact that the climb out of 615 00:34:38,520 --> 00:34:42,560 Speaker 1: the uncanny valley is steeper if you're moving. Now. I 616 00:34:42,600 --> 00:34:44,719 Speaker 1: know we're not talking about robots here, but this, of course, 617 00:34:44,760 --> 00:34:47,120 Speaker 1: this brings up the thought that as where as we 618 00:34:47,160 --> 00:34:51,000 Speaker 1: attempt to conquer this in the realm of humanoid robotics, 619 00:34:51,680 --> 00:34:54,319 Speaker 1: you're gonna inevitably have situations where oh, it looks just 620 00:34:54,360 --> 00:34:56,600 Speaker 1: like a person that it's walking down the street, but 621 00:34:56,680 --> 00:35:00,000 Speaker 1: if it climbs stairs, there you go it's not necessarily 622 00:35:00,200 --> 00:35:03,160 Speaker 1: edge to oh nine, there it lays in the air, 623 00:35:03,480 --> 00:35:05,640 Speaker 1: but maybe there would be something telling like, oh, it 624 00:35:05,680 --> 00:35:07,640 Speaker 1: looks like a human most of the time. But they're 625 00:35:07,640 --> 00:35:12,880 Speaker 1: gonna be certain movements, certain environmental reactions that are just 626 00:35:12,920 --> 00:35:15,920 Speaker 1: not going to hold up to scrutiny, right, So, I 627 00:35:15,920 --> 00:35:18,520 Speaker 1: don't know. Looking at these things, looking at Tarkan in 628 00:35:18,840 --> 00:35:22,000 Speaker 1: Rogue one, looking at Siah, I think it's clear that 629 00:35:22,040 --> 00:35:25,880 Speaker 1: we're getting closer and closer to really bridging the gap 630 00:35:26,080 --> 00:35:31,520 Speaker 1: on indistinguishable photo real humanity and computer animation. Whether you'd 631 00:35:31,520 --> 00:35:34,080 Speaker 1: call that an uncanny value or not. Obviously this is 632 00:35:34,120 --> 00:35:38,000 Speaker 1: a related but maybe different issue. What we're definitely drawing 633 00:35:38,040 --> 00:35:41,759 Speaker 1: near is that peak of reality where there are synthetically 634 00:35:41,760 --> 00:35:45,440 Speaker 1: generated images of humans that you can't tell from the 635 00:35:45,520 --> 00:35:49,600 Speaker 1: real thing. And since things in the uncanny value are creepy, 636 00:35:49,640 --> 00:35:52,120 Speaker 1: I think we usually just assume that overcoming it is 637 00:35:52,120 --> 00:35:55,359 Speaker 1: a good thing, right, like designs getting better? Uh, and't 638 00:35:55,360 --> 00:35:57,400 Speaker 1: it kind of cool that we can generate these photo 639 00:35:57,440 --> 00:36:02,000 Speaker 1: real images without without actually having to photograph someone. But 640 00:36:02,160 --> 00:36:04,919 Speaker 1: I'm not so sure that's a good thing. I think 641 00:36:04,960 --> 00:36:07,359 Speaker 1: we should maybe think about the implications of this, like 642 00:36:08,000 --> 00:36:11,880 Speaker 1: what would happen in the world where human simulations, especially 643 00:36:11,920 --> 00:36:16,719 Speaker 1: computer animation, can reliably climb up that second peak. So 644 00:36:16,840 --> 00:36:18,600 Speaker 1: we are going to take a quick break and when 645 00:36:18,600 --> 00:36:25,040 Speaker 1: we come back, we will go beyond the Uncanny Valley. 646 00:36:25,920 --> 00:36:28,000 Speaker 1: All right, we're back. You know, I'm glad you brought 647 00:36:28,040 --> 00:36:29,879 Speaker 1: up this idea of you know, is it a bad thing? 648 00:36:29,920 --> 00:36:32,000 Speaker 1: Is it a good thing? It does remind me of 649 00:36:32,040 --> 00:36:33,920 Speaker 1: a fabulous book that came out a few years back. 650 00:36:33,960 --> 00:36:35,880 Speaker 1: I think I just referenced it in our Sex Spots 651 00:36:35,920 --> 00:36:40,480 Speaker 1: episode toddled The wind Up Girl by Paolo bag Um. 652 00:36:40,520 --> 00:36:44,560 Speaker 1: It's a near future science fiction tale, just really a 653 00:36:44,560 --> 00:36:48,279 Speaker 1: wonderful novel, very fun. But the wind up Girl in 654 00:36:48,400 --> 00:36:53,040 Speaker 1: question is a essentially a sex Spot character. It goes 655 00:36:53,280 --> 00:36:55,200 Speaker 1: you know that that ends up rebelling, and you have 656 00:36:55,280 --> 00:36:58,239 Speaker 1: sort of a typical narrative with her. But they call 657 00:36:58,320 --> 00:37:02,319 Speaker 1: her a wind up girl because she's she's she's very 658 00:37:02,320 --> 00:37:05,520 Speaker 1: convincing as a humanoid, except that her skin pours are 659 00:37:05,520 --> 00:37:10,200 Speaker 1: too small and she has an intentionally herky jerky movement 660 00:37:10,280 --> 00:37:13,880 Speaker 1: to uh to as she walks around. That they did 661 00:37:14,080 --> 00:37:17,000 Speaker 1: so that she could not be mistaken as a person. 662 00:37:17,800 --> 00:37:20,200 Speaker 1: So that so that apparently, like all the I think 663 00:37:20,200 --> 00:37:22,359 Speaker 1: they were called the new people and some in some 664 00:37:22,400 --> 00:37:25,640 Speaker 1: cases so that the new people could not be mistaken 665 00:37:25,920 --> 00:37:28,920 Speaker 1: for the old people. Whoa. It reminds me of how 666 00:37:28,960 --> 00:37:32,799 Speaker 1: they had to add artificial sounds to electric cars for 667 00:37:32,840 --> 00:37:36,160 Speaker 1: safety purposes, because the cars are too quiet, they can 668 00:37:36,160 --> 00:37:38,239 Speaker 1: really sneak up on you from behind, so they had 669 00:37:38,280 --> 00:37:43,239 Speaker 1: to make them rumble a little bit. Yeah, I think 670 00:37:43,239 --> 00:37:46,360 Speaker 1: that's an apt comparison. So here's a question for you, Robert, 671 00:37:47,320 --> 00:37:52,000 Speaker 1: what is the gold standard of evidence that somebody did something? 672 00:37:53,160 --> 00:37:56,319 Speaker 1: Imagine you're on a jury. I'm the defendant. I've been 673 00:37:56,360 --> 00:37:59,440 Speaker 1: accused of offering a cash bribe to a police officer 674 00:37:59,560 --> 00:38:02,919 Speaker 1: if she'll me borrow her gun for five minutes. She says, 675 00:38:02,960 --> 00:38:05,640 Speaker 1: I did it. I plead not guilty. What what's the 676 00:38:05,680 --> 00:38:10,160 Speaker 1: best evidence to convince you that I really did that. Well, 677 00:38:10,239 --> 00:38:13,279 Speaker 1: it's not human memory, because if we've touched on many 678 00:38:13,280 --> 00:38:16,080 Speaker 1: times before, human memory is fallible and uh, and it's 679 00:38:16,080 --> 00:38:20,000 Speaker 1: a legitimate problem when it comes to to eyewitness testimony. 680 00:38:20,520 --> 00:38:24,080 Speaker 1: But when the eyewitness is a video camera digital camera 681 00:38:24,600 --> 00:38:27,760 Speaker 1: that has a long photographic evidence as well to certain 682 00:38:27,760 --> 00:38:30,240 Speaker 1: degrees like this has been held up as the gold standard. 683 00:38:30,719 --> 00:38:33,400 Speaker 1: I mean assuming the footage is clear enough that the 684 00:38:33,400 --> 00:38:37,720 Speaker 1: individual's face is visible. All of that. Uh Like even 685 00:38:37,719 --> 00:38:40,600 Speaker 1: in our science fiction right, we have so many examples 686 00:38:40,600 --> 00:38:43,200 Speaker 1: of like on Star Trek. Again, there would be scenes 687 00:38:43,480 --> 00:38:46,480 Speaker 1: where the card would command it we zoom in and enhance, 688 00:38:47,080 --> 00:38:49,520 Speaker 1: and it was never questioned that there were any problems 689 00:38:49,520 --> 00:38:51,839 Speaker 1: with the enhancing of the image. It was just something 690 00:38:51,840 --> 00:38:53,880 Speaker 1: that was done. It's like, oh, yeah, the image is enhanced, 691 00:38:53,880 --> 00:38:56,400 Speaker 1: and now we see exactly who the killer is. So 692 00:38:56,520 --> 00:38:59,360 Speaker 1: we should look at this this booming new research field. 693 00:38:59,440 --> 00:39:01,920 Speaker 1: I shouldn't booming. I just mean there are some papers 694 00:39:01,960 --> 00:39:07,120 Speaker 1: on it, okay, called facial reenactment. So this employs some 695 00:39:07,160 --> 00:39:09,680 Speaker 1: of the same techniques that you would see used in 696 00:39:10,160 --> 00:39:13,520 Speaker 1: UH in studios. If if people are doing motion capture 697 00:39:13,600 --> 00:39:16,280 Speaker 1: for c g I characters in movies and video games, 698 00:39:16,800 --> 00:39:19,919 Speaker 1: you have an actor performer who puts on special gear 699 00:39:20,000 --> 00:39:23,120 Speaker 1: and a special environment surrounded by lights and cameras, and 700 00:39:23,160 --> 00:39:26,640 Speaker 1: the performer acts out motions. These motions are captured from 701 00:39:26,719 --> 00:39:30,839 Speaker 1: multiple angles and different lighting conditions, and then they're translated 702 00:39:30,840 --> 00:39:33,040 Speaker 1: by a computer into the motions of a c g 703 00:39:33,239 --> 00:39:35,400 Speaker 1: I character. You could make a c g I me 704 00:39:35,760 --> 00:39:37,840 Speaker 1: that was doing all the same things I did with 705 00:39:37,880 --> 00:39:41,800 Speaker 1: my body. But what if instead of a c g 706 00:39:41,960 --> 00:39:47,400 Speaker 1: I character, you used captured motion to manipulate existing video 707 00:39:47,560 --> 00:39:50,480 Speaker 1: or images of a real person, not a c g 708 00:39:50,640 --> 00:39:54,759 Speaker 1: I character. This technology is already in development today, and 709 00:39:54,960 --> 00:39:57,440 Speaker 1: one example is the research being done under the heading 710 00:39:57,440 --> 00:39:59,799 Speaker 1: as I said, of facial reenactment. There are a couple 711 00:39:59,840 --> 00:40:03,839 Speaker 1: of papers along with accompanying video demonstrations by a group 712 00:40:03,840 --> 00:40:06,600 Speaker 1: of researchers based out of Stanford, out of the Max 713 00:40:06,640 --> 00:40:11,279 Speaker 1: Plank Institute for Informatics and the University of Erlanga, Nuremberg, 714 00:40:11,880 --> 00:40:14,960 Speaker 1: and in their own words quote, we present a method 715 00:40:15,080 --> 00:40:19,200 Speaker 1: for the real time transfer of facial expressions from an 716 00:40:19,200 --> 00:40:22,359 Speaker 1: actor in a source video to an actor in a 717 00:40:22,440 --> 00:40:26,279 Speaker 1: target video, thus enabling the ad hoc control of the 718 00:40:26,320 --> 00:40:30,600 Speaker 1: facial expressions of the target actor. And so if you 719 00:40:30,600 --> 00:40:32,400 Speaker 1: haven't seen video of this, you should look it up. 720 00:40:32,440 --> 00:40:37,120 Speaker 1: Try facial reenactment video. If you have sufficient sample video 721 00:40:37,160 --> 00:40:40,719 Speaker 1: of your target, you can use a regular camera to 722 00:40:40,800 --> 00:40:45,840 Speaker 1: project new facial expressions, including mouth movements which form the 723 00:40:45,880 --> 00:40:49,560 Speaker 1: shapes of words, onto your your target in your video. 724 00:40:49,880 --> 00:40:52,560 Speaker 1: So I could take video of Robert talking if I 725 00:40:52,600 --> 00:40:55,960 Speaker 1: had all this technology, If I could take video of 726 00:40:56,040 --> 00:41:00,000 Speaker 1: Robert talking, and then I could film myself saying how 727 00:41:00,000 --> 00:41:03,239 Speaker 1: Halloween five is the best entry in the Halloween franchise, 728 00:41:04,120 --> 00:41:07,319 Speaker 1: and then map that onto Robert's face to make his 729 00:41:07,440 --> 00:41:11,080 Speaker 1: lips say those words, to make his face move along 730 00:41:11,160 --> 00:41:13,920 Speaker 1: with my face as it's being recorded. And in the 731 00:41:13,960 --> 00:41:17,120 Speaker 1: demonstrations of this it looks nearly photo real. They do 732 00:41:17,200 --> 00:41:21,240 Speaker 1: it with with public figures, making them move their faces around, 733 00:41:21,400 --> 00:41:24,400 Speaker 1: move their lips to say things. In some cases, I 734 00:41:24,480 --> 00:41:27,520 Speaker 1: think the average observer already would not be able to 735 00:41:27,600 --> 00:41:31,239 Speaker 1: tell the difference in this video, and in fact that 736 00:41:31,360 --> 00:41:33,960 Speaker 1: a similar thing appears to be happening with voice, this 737 00:41:34,040 --> 00:41:36,239 Speaker 1: thing you might have read about last year, this thing 738 00:41:36,280 --> 00:41:39,000 Speaker 1: Adobe Voco, where they came out with this announcement that 739 00:41:39,040 --> 00:41:41,840 Speaker 1: Adobe is working on software where you can take a 740 00:41:41,880 --> 00:41:44,640 Speaker 1: twenty minute sample of your audio to learn from. If 741 00:41:44,640 --> 00:41:47,080 Speaker 1: you've got a recording of somebody talking for twenty minutes, 742 00:41:47,520 --> 00:41:50,080 Speaker 1: I can take it make a recording of you saying 743 00:41:50,120 --> 00:41:53,280 Speaker 1: things you never said in your own voice. I wanna. 744 00:41:53,480 --> 00:41:56,960 Speaker 1: I seem to remember that before his death, Roger Ebert 745 00:41:57,600 --> 00:42:00,239 Speaker 1: was involved with the project with some of this technology, 746 00:42:00,400 --> 00:42:02,040 Speaker 1: the idea of being that, of course he had lost 747 00:42:02,120 --> 00:42:06,440 Speaker 1: his his availability to talk due to illness, But there 748 00:42:06,520 --> 00:42:11,359 Speaker 1: was so much Roger Ebert audio out there from all 749 00:42:11,400 --> 00:42:13,040 Speaker 1: of his years as a as a as a film 750 00:42:13,080 --> 00:42:16,360 Speaker 1: critic and a TV personality that they had this they had, 751 00:42:16,400 --> 00:42:19,800 Speaker 1: they had everything they needed to enable him to say 752 00:42:19,920 --> 00:42:23,360 Speaker 1: anything new. Yeah, and that that explores the totally non 753 00:42:23,360 --> 00:42:26,040 Speaker 1: nefarious aspect of this. I mean, I I don't think 754 00:42:26,080 --> 00:42:28,719 Speaker 1: people who are pursuing these lines of research are just 755 00:42:28,800 --> 00:42:31,160 Speaker 1: trying to create a world where we can fake video 756 00:42:31,239 --> 00:42:34,279 Speaker 1: evidence of things. But wouldn't that be a wonderful thing 757 00:42:34,280 --> 00:42:37,239 Speaker 1: for somebody who lost their capacity for speech they had 758 00:42:37,280 --> 00:42:39,920 Speaker 1: recordings of their voice to be able to create a 759 00:42:40,000 --> 00:42:42,719 Speaker 1: text to speech voice box that could speak with their 760 00:42:42,760 --> 00:42:48,840 Speaker 1: own voice. That's amazing, That's kind of beautiful. But there 761 00:42:48,880 --> 00:42:51,839 Speaker 1: are these other ways of looking at this. And the 762 00:42:51,840 --> 00:42:54,400 Speaker 1: authors also that they point out that, you know, they 763 00:42:54,560 --> 00:42:56,920 Speaker 1: they in their own defense, they're like, look, we're not 764 00:42:56,960 --> 00:42:59,240 Speaker 1: trying to create a world where people can fake video. 765 00:42:59,560 --> 00:43:02,560 Speaker 1: We also try to show how you can detect altered video. 766 00:43:03,160 --> 00:43:05,880 Speaker 1: So that's another thing they're trying to explore and make public. 767 00:43:05,920 --> 00:43:09,520 Speaker 1: Because you know, they're not the only people pursuing this research. Obviously, 768 00:43:09,560 --> 00:43:13,000 Speaker 1: people all over the place are doing stuff like this, 769 00:43:13,080 --> 00:43:15,279 Speaker 1: and stuff like this has been in the use, has 770 00:43:15,280 --> 00:43:18,000 Speaker 1: been in use in the movie industry for years. Yeah, 771 00:43:18,160 --> 00:43:19,719 Speaker 1: I mean it makes me think that what you would 772 00:43:19,760 --> 00:43:22,520 Speaker 1: need to go for is the equivalent of a water mark. 773 00:43:22,840 --> 00:43:25,480 Speaker 1: I don't know exactly what that watermark would be and 774 00:43:25,520 --> 00:43:28,960 Speaker 1: what form it would take, but it does make me think, well, 775 00:43:29,040 --> 00:43:30,840 Speaker 1: we're going to reach a point where any kind of 776 00:43:30,840 --> 00:43:35,400 Speaker 1: footage has to have the watermark of authenticity otherwise doubt 777 00:43:35,440 --> 00:43:40,040 Speaker 1: will be cast upon it. Yeah. I'm concerned about the 778 00:43:40,080 --> 00:43:43,080 Speaker 1: idea of living in a world where you can make 779 00:43:43,280 --> 00:43:48,560 Speaker 1: very convincing looking fake video evidence of things, and not 780 00:43:48,680 --> 00:43:51,960 Speaker 1: just because of the specific example of somebody can make 781 00:43:52,000 --> 00:43:54,359 Speaker 1: a video of me or somebody I like, you know, 782 00:43:54,440 --> 00:43:57,200 Speaker 1: saying or doing something that they didn't do. It's not 783 00:43:57,239 --> 00:44:00,759 Speaker 1: just the specifics. It's the general degray eating of our 784 00:44:00,880 --> 00:44:04,440 Speaker 1: trust in the ability to look at things and know 785 00:44:04,560 --> 00:44:06,800 Speaker 1: that they're true. Yeah. I mean, we look at the 786 00:44:07,640 --> 00:44:09,680 Speaker 1: current news cycle and there's been a lot of discussion 787 00:44:09,680 --> 00:44:15,040 Speaker 1: about the reliability of information, of so called fake news. Uh, 788 00:44:15,120 --> 00:44:17,840 Speaker 1: the idea that you read, do you reach this point 789 00:44:17,840 --> 00:44:20,520 Speaker 1: where nobody knows what to trust anymore? End of just 790 00:44:20,520 --> 00:44:23,399 Speaker 1: trusting nothing and you already know this because you don't 791 00:44:23,400 --> 00:44:26,839 Speaker 1: trust any weird looking picture of somebody you see, right, 792 00:44:26,840 --> 00:44:29,120 Speaker 1: because you know what can be done with photoshop. We're 793 00:44:29,160 --> 00:44:33,239 Speaker 1: already there with still images. Photoshop is is basically in 794 00:44:33,239 --> 00:44:38,640 Speaker 1: many contexts become a verb for for the the distortion 795 00:44:38,680 --> 00:44:42,520 Speaker 1: of truth. But what what if we had photoshop to 796 00:44:42,719 --> 00:44:46,400 Speaker 1: undermine moving video evidence to the same extent that photoshop 797 00:44:46,480 --> 00:44:49,840 Speaker 1: has undermined still images. I mean, this is what a 798 00:44:49,840 --> 00:44:52,360 Speaker 1: lot of these viral fake news stories are based on, 799 00:44:52,480 --> 00:44:55,400 Speaker 1: is a photoshopped image. If you go to Snopes or 800 00:44:55,440 --> 00:44:57,160 Speaker 1: something and you look at what a lot a lot 801 00:44:57,200 --> 00:44:59,719 Speaker 1: of what they're debunking is, it's just an image that 802 00:45:00,000 --> 00:45:03,279 Speaker 1: aims to be real of somebody doing something, and they 803 00:45:03,280 --> 00:45:06,440 Speaker 1: have to track down where it came from. Yeah, it's 804 00:45:06,480 --> 00:45:10,200 Speaker 1: difficult to imagine what that what would slash will be 805 00:45:10,320 --> 00:45:13,439 Speaker 1: like when we reach that point to where there's where 806 00:45:13,480 --> 00:45:16,160 Speaker 1: where video, even digital footage is no longer the gold 807 00:45:16,200 --> 00:45:18,640 Speaker 1: standard it was. I mean, I think it's actually a 808 00:45:18,760 --> 00:45:24,400 Speaker 1: very important project to maintain a version of the Uncanny Valley, 809 00:45:24,920 --> 00:45:29,520 Speaker 1: to to help people find a way to all to 810 00:45:29,600 --> 00:45:33,240 Speaker 1: separate real video evidence from fake video evidence of things, 811 00:45:33,320 --> 00:45:35,520 Speaker 1: to understand that there are things you can look for 812 00:45:35,640 --> 00:45:40,680 Speaker 1: that separate real moving imagery from falsified or synthetic moving imagery. Now, 813 00:45:40,719 --> 00:45:43,960 Speaker 1: one way you can approach this is to do what 814 00:45:44,120 --> 00:45:46,279 Speaker 1: the authors of this research I was talking about do 815 00:45:46,440 --> 00:45:49,399 Speaker 1: is they say, look, here are things that are are 816 00:45:49,600 --> 00:45:53,920 Speaker 1: signs that video has been manipulated. And that's one thing. 817 00:45:53,960 --> 00:45:55,759 Speaker 1: And maybe there will be a lot of experts on 818 00:45:55,760 --> 00:45:57,600 Speaker 1: this in the future, like it could be a whole 819 00:45:57,640 --> 00:46:01,000 Speaker 1: field of people who are just there to have expertise 820 00:46:01,040 --> 00:46:07,120 Speaker 1: in authenticating purportedly real video of you doing things or not. Uh. 821 00:46:07,280 --> 00:46:11,080 Speaker 1: Then on the other hand, we could hope that there 822 00:46:11,239 --> 00:46:16,040 Speaker 1: is in fact an adaptive response in our discernment in general. 823 00:46:16,160 --> 00:46:18,160 Speaker 1: And this is where I want to go to the 824 00:46:18,200 --> 00:46:22,920 Speaker 1: concept of an of the uncanny wall. So a paper 825 00:46:22,960 --> 00:46:26,239 Speaker 1: in the International Journal of Arts and Technology, authored by 826 00:46:26,280 --> 00:46:31,080 Speaker 1: Tinwell Grimshawn Williams offers this interesting counter hypothesis to the 827 00:46:31,200 --> 00:46:34,520 Speaker 1: uncanny Valley. And I want to emphasize again we've sort 828 00:46:34,560 --> 00:46:37,440 Speaker 1: of shifted back and forth between the uncanny valley itself 829 00:46:37,680 --> 00:46:41,319 Speaker 1: in terms of what causes negative affinity and then over 830 00:46:41,400 --> 00:46:44,839 Speaker 1: slightly just to the issue of nearing photo realism or not. 831 00:46:45,000 --> 00:46:48,120 Speaker 1: So keep in mind the difference in those subjects, but 832 00:46:49,800 --> 00:46:53,560 Speaker 1: they proposed this idea of the uncanny wall. To put 833 00:46:53,560 --> 00:46:59,120 Speaker 1: it succinctly, they proposed that quote, increasing technological sophistication in 834 00:46:59,200 --> 00:47:03,760 Speaker 1: the creation of realism for humanlike virtual characters is matched 835 00:47:04,360 --> 00:47:08,920 Speaker 1: by increasing technological discernment on the part of the viewer. 836 00:47:09,680 --> 00:47:14,200 Speaker 1: In other words, as humanoid characters become more real, our 837 00:47:14,280 --> 00:47:18,680 Speaker 1: standards for what looks realistic go up. And I do 838 00:47:18,760 --> 00:47:22,680 Speaker 1: think they're just anecdotally personally that I think there's some 839 00:47:22,760 --> 00:47:24,799 Speaker 1: support for this, and I kind of hope this is 840 00:47:24,840 --> 00:47:28,400 Speaker 1: true so we can avoid this world where all video 841 00:47:28,440 --> 00:47:31,839 Speaker 1: evidence is in question. Because I immediately think, right now, 842 00:47:31,880 --> 00:47:35,920 Speaker 1: I've got I've got antenna for photoshopped images, unlike I 843 00:47:36,000 --> 00:47:39,040 Speaker 1: had ten years ago. I think stuff that would look 844 00:47:39,160 --> 00:47:42,799 Speaker 1: obviously photoshop to me today would have fooled me ten 845 00:47:42,880 --> 00:47:46,919 Speaker 1: years ago. I think I've simply adapted. And another thing 846 00:47:47,120 --> 00:47:49,120 Speaker 1: is it makes me flashback to the early days of 847 00:47:49,160 --> 00:47:52,000 Speaker 1: c G I in movies and like the thirty two 848 00:47:52,080 --> 00:47:56,439 Speaker 1: bit video game era, or think about like PlayStation one 849 00:47:56,640 --> 00:48:00,160 Speaker 1: games now. Back then, I remember looking at games for 850 00:48:00,160 --> 00:48:04,480 Speaker 1: the original PlayStation and thinking, Wow, that looks so real, 851 00:48:05,560 --> 00:48:07,680 Speaker 1: and you try and play him. Now and it's painful. Yeah, 852 00:48:07,719 --> 00:48:12,680 Speaker 1: you can't blocky polygons. People's faces have all these sharp corners. 853 00:48:12,840 --> 00:48:16,800 Speaker 1: It's it's hilarious. Uh, there was some kind of geometrical 854 00:48:17,000 --> 00:48:20,239 Speaker 1: nightmare world everything was taking place in where there's just 855 00:48:20,960 --> 00:48:24,120 Speaker 1: lots of sharp angles. But at the time it looked 856 00:48:24,239 --> 00:48:26,719 Speaker 1: so real to me. And another fun trick is go 857 00:48:26,800 --> 00:48:29,719 Speaker 1: back and read movie reviews for movies with bad c 858 00:48:29,840 --> 00:48:34,239 Speaker 1: g I from the nineties. Professional movie reviewers at the time, 859 00:48:34,280 --> 00:48:38,040 Speaker 1: we're often praising the effects. One example is like the 860 00:48:38,120 --> 00:48:41,840 Speaker 1: Mortal Kombat movie, the original Mortal Kombat movie. Remember this. 861 00:48:42,160 --> 00:48:44,680 Speaker 1: You can find reviews at the time where people are like, well, 862 00:48:44,719 --> 00:48:49,160 Speaker 1: the stories then an immature but dazzling special effects. Now 863 00:48:49,239 --> 00:48:53,680 Speaker 1: even mentioning those special effects conjures a kind of delirious hilarity. 864 00:48:53,760 --> 00:48:56,040 Speaker 1: You just start laughing when you think about the c 865 00:48:56,200 --> 00:48:59,360 Speaker 1: g I in Mortal Kombat. But that being said, the 866 00:48:59,360 --> 00:49:02,239 Speaker 1: gore pup it was above approach just looks really good. 867 00:49:03,040 --> 00:49:05,920 Speaker 1: It did have kind of nasty, beady eyes, kind of 868 00:49:05,960 --> 00:49:09,040 Speaker 1: crypt keep keeper asked, Yeah, oh yeah, it was like 869 00:49:09,080 --> 00:49:12,080 Speaker 1: a very it was like a bloated, buffed up crypt 870 00:49:12,160 --> 00:49:16,600 Speaker 1: kicker at the buff But yeah, it's so ugly. It 871 00:49:16,680 --> 00:49:20,120 Speaker 1: provokes uncontrollable laughter, But at the time people were like, 872 00:49:20,200 --> 00:49:24,000 Speaker 1: dazzling looks amazing. Uh. So it makes me think that 873 00:49:24,120 --> 00:49:27,880 Speaker 1: I hope that there is something to this, this idea 874 00:49:27,960 --> 00:49:31,800 Speaker 1: that these authors have that as things continue to chase 875 00:49:31,880 --> 00:49:35,520 Speaker 1: photo realism, as synthetic imagery of humans gets closer and 876 00:49:35,560 --> 00:49:38,239 Speaker 1: closer to the real thing, we just get more and 877 00:49:38,320 --> 00:49:43,279 Speaker 1: more attuned to the minute problems with him with them 878 00:49:43,320 --> 00:49:47,480 Speaker 1: and never really get fully fooled. Well. I have two 879 00:49:47,600 --> 00:49:50,800 Speaker 1: thoughts here, One on the whole watermark thing. Maybe it 880 00:49:50,800 --> 00:49:54,040 Speaker 1: would be some sort of a Bitcoin type of authentication 881 00:49:54,160 --> 00:49:58,439 Speaker 1: system that would be in place. The other is maybe 882 00:49:58,440 --> 00:50:00,600 Speaker 1: you have to go beyond the real may be safe 883 00:50:00,600 --> 00:50:02,600 Speaker 1: for a head of state to appear in a video 884 00:50:02,719 --> 00:50:06,080 Speaker 1: and it'd be authentic. They have to appear as an 885 00:50:06,080 --> 00:50:10,040 Speaker 1: as a computer generated avatar so advanced that it is 886 00:50:10,200 --> 00:50:13,600 Speaker 1: that it is beyond the ability of any like non 887 00:50:13,680 --> 00:50:18,279 Speaker 1: state production or company to create like something I'm I'm 888 00:50:18,920 --> 00:50:21,920 Speaker 1: something that at this point in what would be their past, 889 00:50:22,040 --> 00:50:24,200 Speaker 1: I cannot even conceive of like a I don't know, 890 00:50:24,280 --> 00:50:29,480 Speaker 1: like a five dimensional unfolding c G I god being. Uh, 891 00:50:29,800 --> 00:50:31,960 Speaker 1: because how he's gonna fake that? You can fake a person, 892 00:50:32,000 --> 00:50:35,840 Speaker 1: but good luck faking the fifth dimension hole of Avatar 893 00:50:35,960 --> 00:50:40,680 Speaker 1: of Vishnu. Okay, like like the algorithms for faking a 894 00:50:40,760 --> 00:50:45,240 Speaker 1: person with a lot of photo and an audio visual 895 00:50:45,360 --> 00:50:47,640 Speaker 1: cues to sample from. If you've got a lot of 896 00:50:47,680 --> 00:50:50,480 Speaker 1: footage out there, you could simulate that person. But you 897 00:50:50,520 --> 00:50:54,759 Speaker 1: couldn't simulate this brand new creation that is it requires 898 00:50:54,760 --> 00:50:57,279 Speaker 1: you know, supercomputers to generate. And yeah, and it was 899 00:50:57,280 --> 00:51:00,080 Speaker 1: probably built from the bottom up with completely alien is 900 00:51:00,160 --> 00:51:02,960 Speaker 1: theology and movements. Just a thought. That's kind of a 901 00:51:02,960 --> 00:51:05,120 Speaker 1: crazy idea, but I like it. Well that's what I'm 902 00:51:05,160 --> 00:51:07,880 Speaker 1: here for with the crazy ideas. I don't know. Have 903 00:51:07,960 --> 00:51:10,319 Speaker 1: you got anything else, Robert, any anything else you can 904 00:51:10,320 --> 00:51:13,240 Speaker 1: think of to save us from the future of uh 905 00:51:13,360 --> 00:51:16,239 Speaker 1: synthetic human imagery? Oh you know, I could sit around 906 00:51:16,239 --> 00:51:17,759 Speaker 1: here all day and talk about the c g I 907 00:51:18,000 --> 00:51:21,600 Speaker 1: monsters and UH and Uncanny Valley and films and video 908 00:51:21,640 --> 00:51:23,719 Speaker 1: games and whatnot, But you know, we'll have to what 909 00:51:23,920 --> 00:51:25,719 Speaker 1: to save that for another time, maybe save some of 910 00:51:25,719 --> 00:51:28,920 Speaker 1: it for trailer talk, which will If you're listening to 911 00:51:28,960 --> 00:51:31,279 Speaker 1: this on a Thursday, hopefully you can tune in tomorrow 912 00:51:31,560 --> 00:51:35,359 Speaker 1: around eleven am on our Facebook page, like our Facebook page. 913 00:51:35,360 --> 00:51:37,520 Speaker 1: While you're at it, follow us there, but tune into 914 00:51:37,600 --> 00:51:40,759 Speaker 1: a little discussion of trailers that are associated with the 915 00:51:40,840 --> 00:51:44,319 Speaker 1: Uncanny Valley. Oh yeah, and in the meantime, heading over 916 00:51:44,320 --> 00:51:46,320 Speaker 1: to stuff to Blow your Mind dot com. That's the mothership. 917 00:51:46,360 --> 00:51:50,080 Speaker 1: That's we will find all of our blog posts, our podcast, 918 00:51:50,200 --> 00:51:52,759 Speaker 1: our videos, and links out to our various social media 919 00:51:52,760 --> 00:51:55,360 Speaker 1: accounts such that Facebook page or the Twitter page, the 920 00:51:55,400 --> 00:51:58,239 Speaker 1: Instagram account, you name it. And if you want to 921 00:51:58,239 --> 00:52:00,440 Speaker 1: get in touch with us directly as all ways, you 922 00:52:00,480 --> 00:52:03,600 Speaker 1: can email us at blow the Mind at how stuff 923 00:52:03,600 --> 00:52:15,600 Speaker 1: works dot com for more on this and thousands of 924 00:52:15,640 --> 00:52:40,680 Speaker 1: other topics. Is it how stuff works dot com.