1 00:00:05,840 --> 00:00:07,840 Speaker 1: Hey, welcome to Stuff to Blow Your Mind. My name 2 00:00:07,880 --> 00:00:10,640 Speaker 1: is Robert Lamb and I'm Joe McCormick, and it's Saturday. 3 00:00:10,760 --> 00:00:12,840 Speaker 1: Time to go into the vault. This time we're bringing 4 00:00:12,880 --> 00:00:16,480 Speaker 1: you part two of our exploration of the Uncanny Valley. 5 00:00:16,600 --> 00:00:21,880 Speaker 1: This episode was originally published April six. Uh, should we 6 00:00:21,960 --> 00:00:28,360 Speaker 1: jump right in, Robert, Let's do it. Welcome to Stuff 7 00:00:28,360 --> 00:00:37,320 Speaker 1: to Blow your Mind from how Stop works dot com. Hey, 8 00:00:37,479 --> 00:00:39,159 Speaker 1: welcome to Stuff to Blow your Mind. My name is 9 00:00:39,240 --> 00:00:41,640 Speaker 1: Robert Lamb and I'm Joe McCormick. In Today is going 10 00:00:41,720 --> 00:00:44,080 Speaker 1: to be the second part of a two part series 11 00:00:44,120 --> 00:00:47,519 Speaker 1: we're doing on the Uncanny Valley. Last time we ventured 12 00:00:47,640 --> 00:00:50,600 Speaker 1: into the Uncanny Valley, so if you haven't heard that episode, 13 00:00:50,720 --> 00:00:52,440 Speaker 1: you should go back and listen to that. First, we 14 00:00:52,479 --> 00:00:54,240 Speaker 1: lay a lot of the groundwork for what we're gonna 15 00:00:54,280 --> 00:00:57,320 Speaker 1: be talking about today, But we explored the origination of 16 00:00:57,360 --> 00:01:00,360 Speaker 1: the concept of the Uncanny Valley, what it means means 17 00:01:00,480 --> 00:01:03,720 Speaker 1: to to be in the Uncanny Valley, and some research 18 00:01:03,800 --> 00:01:08,000 Speaker 1: on whether this valley actually exists or not. Today, I 19 00:01:08,040 --> 00:01:10,320 Speaker 1: think we want to start off by looking at if, 20 00:01:10,360 --> 00:01:14,600 Speaker 1: if it does exist, what might be some explanations for it. Indeed. Yeah, 21 00:01:14,640 --> 00:01:17,080 Speaker 1: we're gonna we're gonna dive into it a bit more 22 00:01:17,120 --> 00:01:22,160 Speaker 1: and move as the title, uh suggests, beyond the Uncanny Valley. 23 00:01:22,200 --> 00:01:24,160 Speaker 1: But before we do that, I do want to talk 24 00:01:24,200 --> 00:01:27,400 Speaker 1: about RoboCop. Of course you want to talk about RoboCop, 25 00:01:27,560 --> 00:01:30,000 Speaker 1: because we talked about RoboCop pretty much every day. Yeah, 26 00:01:30,000 --> 00:01:33,040 Speaker 1: it's it's it's an important film. Important films, I'll say, 27 00:01:33,160 --> 00:01:35,039 Speaker 1: at least the at least the first two, arguably the 28 00:01:35,080 --> 00:01:37,360 Speaker 1: third one to throwing the TV series if you like. 29 00:01:37,920 --> 00:01:42,039 Speaker 1: But there was a TV series, Yeah, RoboCop TV series. 30 00:01:42,080 --> 00:01:43,200 Speaker 1: It was one of those that would I think it 31 00:01:43,240 --> 00:01:47,240 Speaker 1: would come on sci Fi or it came on various 32 00:01:47,280 --> 00:01:50,920 Speaker 1: cable channels. I only have a vague awareness of it 33 00:01:51,520 --> 00:01:54,320 Speaker 1: because it seemed to be a far lower key RoboCop 34 00:01:54,360 --> 00:01:58,560 Speaker 1: type show. Okay, So in many of the studies that 35 00:01:58,600 --> 00:02:00,800 Speaker 1: we talked about in the last episode, they were looking 36 00:02:00,840 --> 00:02:07,000 Speaker 1: at largely three categories of of robots and humans and androids. 37 00:02:07,000 --> 00:02:10,120 Speaker 1: So you had pure robots things that are just undeniably 38 00:02:10,240 --> 00:02:14,760 Speaker 1: machines and we're mostly okay with. Then you have humans 39 00:02:15,040 --> 00:02:18,880 Speaker 1: or or or perfect human replications. Okay, So you look 40 00:02:18,880 --> 00:02:20,880 Speaker 1: at it, it either is a human or it's such 41 00:02:20,919 --> 00:02:25,000 Speaker 1: a good representation of a human ideally that you would 42 00:02:25,040 --> 00:02:27,360 Speaker 1: not think that it was a robot. Right. The third 43 00:02:27,440 --> 00:02:29,200 Speaker 1: category here is where you're going to get into the 44 00:02:29,280 --> 00:02:33,320 Speaker 1: danger zone, right, the human like robots, where you look 45 00:02:33,360 --> 00:02:35,160 Speaker 1: at it and you say, I see what you're going 46 00:02:35,240 --> 00:02:39,600 Speaker 1: for there, but it's creeping me out. So I think 47 00:02:39,600 --> 00:02:42,320 Speaker 1: it's interesting to align this up with the Holy Trinity 48 00:02:42,320 --> 00:02:45,880 Speaker 1: of robocops. Okay, so this will mostly make sense if 49 00:02:45,919 --> 00:02:48,200 Speaker 1: you've seen the RoboCop films, but I feel like most 50 00:02:48,240 --> 00:02:50,440 Speaker 1: people know what we're talking about here. First of all, 51 00:02:50,480 --> 00:02:53,799 Speaker 1: you had the proto RoboCop and two oh nine. Oh, 52 00:02:53,919 --> 00:02:56,600 Speaker 1: this is maybe the greatest scene in the first film 53 00:02:56,720 --> 00:02:59,880 Speaker 1: is before we get a humanoid RoboCop, they just have 54 00:03:00,120 --> 00:03:03,760 Speaker 1: this big drone object that is supposed to enforce the 55 00:03:03,840 --> 00:03:07,000 Speaker 1: law and it ends up shooting somebody in the boardroom. Yeah, 56 00:03:07,040 --> 00:03:11,440 Speaker 1: it's a walking law enforcement tank with a robot commanding 57 00:03:11,560 --> 00:03:14,560 Speaker 1: robot voice, so that you look at it and there's 58 00:03:14,600 --> 00:03:17,400 Speaker 1: no to not know this is not a friendly device. 59 00:03:17,639 --> 00:03:20,280 Speaker 1: But it's not really humanoid at all, not really at all. 60 00:03:20,280 --> 00:03:23,200 Speaker 1: It hit just walks on big, big legs that can't 61 00:03:23,200 --> 00:03:26,840 Speaker 1: even navigate human stairs. But I would say, I have 62 00:03:26,919 --> 00:03:29,359 Speaker 1: great affinity for ed to oh nine, Yeah, I mean, 63 00:03:29,639 --> 00:03:32,280 Speaker 1: you know, without having to worry about it actually shooting me. 64 00:03:32,960 --> 00:03:36,000 Speaker 1: It's kind of cute in a way. Now, then we 65 00:03:36,080 --> 00:03:42,480 Speaker 1: have RoboCop itself himself, the classic RoboCop, the Peter Peter Weller, 66 00:03:43,240 --> 00:03:47,240 Speaker 1: and uh, he is a cyborg or perhaps an android, 67 00:03:47,280 --> 00:03:50,760 Speaker 1: depending on how you want to view the descriptions. So 68 00:03:50,840 --> 00:03:55,760 Speaker 1: he's he has a relatable, living human face which is 69 00:03:55,760 --> 00:03:59,680 Speaker 1: a fixed to to honor him in some some explanations, 70 00:03:59,800 --> 00:04:02,200 Speaker 1: or has to make him more comfortable not only as 71 00:04:02,240 --> 00:04:05,640 Speaker 1: a police killing machine but also a community law enforcement officer. 72 00:04:05,760 --> 00:04:09,280 Speaker 1: So RoboCop, you know, moves around with very robotic movements, 73 00:04:09,600 --> 00:04:13,000 Speaker 1: speaks in a very robotic voice, but his face is 74 00:04:13,120 --> 00:04:17,159 Speaker 1: a living human face. So in a way like that, 75 00:04:17,160 --> 00:04:19,160 Speaker 1: that seems like it might it just sort of you know, 76 00:04:19,200 --> 00:04:22,400 Speaker 1: to read perhaps more into the original film than was intended. 77 00:04:22,680 --> 00:04:25,680 Speaker 1: Perhaps this was a way to to get beyond the 78 00:04:25,760 --> 00:04:28,440 Speaker 1: Uncanny Valley. We can't replicate the human face, We'll just 79 00:04:28,520 --> 00:04:31,160 Speaker 1: get an actual human face from the dead cop and 80 00:04:31,200 --> 00:04:33,719 Speaker 1: just plaster it up there. Oh but I'd say RoboCop 81 00:04:33,760 --> 00:04:35,839 Speaker 1: with his mask on really does kind of get into 82 00:04:35,880 --> 00:04:38,880 Speaker 1: the uncanny Valley and and Weller does some good work 83 00:04:39,120 --> 00:04:41,640 Speaker 1: forcing us in there, Like I think they're the sort 84 00:04:41,680 --> 00:04:45,880 Speaker 1: of going for it. Yeah, okay, Well that brings us 85 00:04:45,920 --> 00:04:50,160 Speaker 1: to the next generation RoboCop two, which is not just 86 00:04:50,240 --> 00:04:53,080 Speaker 1: the name of the second RoboCop movie, but also the 87 00:04:53,560 --> 00:04:57,400 Speaker 1: model of RoboCop that replaced the original RoboCop. They think, Hey, 88 00:04:57,440 --> 00:04:59,479 Speaker 1: what would happen if we put tom noon in there? 89 00:04:59,680 --> 00:05:03,880 Speaker 1: That's right, So they have another essentially a walking tank 90 00:05:04,080 --> 00:05:06,440 Speaker 1: kind of like d to O nine, except it's powered 91 00:05:06,440 --> 00:05:09,320 Speaker 1: by the brain of a psychotic drug lord named Kane 92 00:05:09,800 --> 00:05:13,760 Speaker 1: played by Tom Noonan. He's fabulous in it. Uh, but 93 00:05:13,839 --> 00:05:16,000 Speaker 1: here's the here's the thing. It's walking around, it's killing 94 00:05:16,040 --> 00:05:18,320 Speaker 1: everything with a gatling gun, but then it can pop 95 00:05:18,520 --> 00:05:20,800 Speaker 1: a flat screen TV out of it out of the 96 00:05:21,000 --> 00:05:24,360 Speaker 1: front of its body, and on that screen is a 97 00:05:24,400 --> 00:05:28,360 Speaker 1: twisted uncanny lawnmower Man esque c g I face of 98 00:05:28,440 --> 00:05:33,000 Speaker 1: tom Noonon. Yeah, so that one really leans into the 99 00:05:33,200 --> 00:05:36,440 Speaker 1: Uncanny Valley. Well yeah, and this this does point out 100 00:05:36,480 --> 00:05:39,080 Speaker 1: another thing, which is that there have been plenty of 101 00:05:39,680 --> 00:05:44,320 Speaker 1: intentional realizations of the Uncanny Valley in film when when 102 00:05:44,360 --> 00:05:48,520 Speaker 1: people are trying to create an unsettling, unpleasant, humanoid for 103 00:05:48,600 --> 00:05:51,200 Speaker 1: story purposes, if it's supposed to be a villain, if 104 00:05:51,200 --> 00:05:53,960 Speaker 1: it's supposed to make people uncomfortable, because that's its role 105 00:05:53,960 --> 00:05:56,080 Speaker 1: in the plot. So one thing I kind of wish 106 00:05:56,080 --> 00:05:58,080 Speaker 1: we'd done. I hadn't even thought about this is too 107 00:05:58,640 --> 00:06:02,080 Speaker 1: if we could talk to somebody who has intentionally made 108 00:06:02,160 --> 00:06:05,200 Speaker 1: things in the Uncanny Valley? What did they do on 109 00:06:05,400 --> 00:06:09,039 Speaker 1: purpose to get it there? If your your job is 110 00:06:09,080 --> 00:06:12,480 Speaker 1: to make a humanoid robot or an animated humanoid figure 111 00:06:12,760 --> 00:06:16,680 Speaker 1: that intentionally pushes all the bad buttons and climbs as 112 00:06:16,680 --> 00:06:18,800 Speaker 1: far down into the valley as it can, what do 113 00:06:18,880 --> 00:06:22,200 Speaker 1: you do that would that would provide some really interesting 114 00:06:22,200 --> 00:06:25,560 Speaker 1: insight into what it actually takes to get there. Well, 115 00:06:25,560 --> 00:06:27,359 Speaker 1: you know, to come back to video games, something that 116 00:06:27,400 --> 00:06:29,960 Speaker 1: comes up a lot. You see these videos going viral 117 00:06:30,040 --> 00:06:32,760 Speaker 1: where it's like just a cut scene or a clip 118 00:06:32,800 --> 00:06:35,680 Speaker 1: from the video game with a humanoid character in a 119 00:06:35,720 --> 00:06:39,200 Speaker 1: more or less human situation, except something screwed up in 120 00:06:39,279 --> 00:06:41,800 Speaker 1: the face is missing, so it's just two floating eyeballs 121 00:06:41,800 --> 00:06:45,640 Speaker 1: and maybe a floating set of digital teeth. So the 122 00:06:45,680 --> 00:06:48,280 Speaker 1: context is key there, Like this thing is acting as 123 00:06:48,279 --> 00:06:50,280 Speaker 1: if it had a face, and it's in an environment 124 00:06:50,320 --> 00:06:53,440 Speaker 1: where we're unsupposed to just roll with it, but clearly 125 00:06:53,520 --> 00:06:56,720 Speaker 1: something's wrong. Yes, okay, Well, as we said in the 126 00:06:56,800 --> 00:06:58,919 Speaker 1: last episode, we talked about the origin of the idea, 127 00:06:59,000 --> 00:07:01,600 Speaker 1: We talked about evidence for and against the fact that 128 00:07:01,640 --> 00:07:05,919 Speaker 1: the Uncanny Valley actually exists, to to the point that 129 00:07:06,000 --> 00:07:08,719 Speaker 1: it actually does exist to some extent. Maybe not in 130 00:07:08,760 --> 00:07:11,880 Speaker 1: the naive original sense everybody would say, where it's just 131 00:07:12,160 --> 00:07:17,400 Speaker 1: related to the amount of realistic human nous in a figure, 132 00:07:17,440 --> 00:07:22,000 Speaker 1: but has other dimensions as well. What causes our Uncanny 133 00:07:22,080 --> 00:07:25,360 Speaker 1: Valley reaction? Obviously people do have this reaction they see 134 00:07:25,360 --> 00:07:30,000 Speaker 1: a humanoid robot or a humanoid animated character, the Scorpion King, 135 00:07:30,160 --> 00:07:33,400 Speaker 1: the Final Fantasy, the spirits within characters, whatever it is, 136 00:07:33,640 --> 00:07:38,280 Speaker 1: and we get so, what causes it? Why do our 137 00:07:38,280 --> 00:07:42,480 Speaker 1: brains react that way? Is it biological? Is it pure instinct? 138 00:07:42,600 --> 00:07:45,600 Speaker 1: Is it a learned psychological reaction? Is it part of 139 00:07:45,600 --> 00:07:50,600 Speaker 1: our culture? Is something coming from cognitive dissonance of some sort? Now, 140 00:07:50,640 --> 00:07:52,600 Speaker 1: to go back to the origins of the idea with 141 00:07:52,840 --> 00:07:56,000 Speaker 1: massive hero Mari in nineteen seventy and his original paper 142 00:07:56,040 --> 00:08:00,440 Speaker 1: on the Uncanny Valley, Morey speculates that the Uncanny Valley 143 00:08:00,520 --> 00:08:03,880 Speaker 1: might be a side effect of the self preservation instinct. 144 00:08:04,040 --> 00:08:07,200 Speaker 1: In other words, it's a biological adaptation that helps us 145 00:08:07,240 --> 00:08:11,040 Speaker 1: avoid disease and death. Uh. And he starts with the 146 00:08:11,080 --> 00:08:14,760 Speaker 1: observation that when a normal, healthy person becomes sick and 147 00:08:14,800 --> 00:08:19,160 Speaker 1: eventually dies, they basically tend to slide down from the 148 00:08:19,240 --> 00:08:22,000 Speaker 1: second peak of the uncanny valley, what we were calling 149 00:08:22,000 --> 00:08:27,200 Speaker 1: the realism peak, the reality peak, and slide down into 150 00:08:27,400 --> 00:08:30,800 Speaker 1: the uncanny valley. It's like they become more like these 151 00:08:30,880 --> 00:08:34,360 Speaker 1: upsetting puppets and robots. You know. They might uh suffer 152 00:08:34,480 --> 00:08:38,360 Speaker 1: some kind of change in their in their the the 153 00:08:38,360 --> 00:08:42,160 Speaker 1: appearance of their skin, of their eyes, of their facial expressions. 154 00:08:42,200 --> 00:08:45,960 Speaker 1: Things begin to look off about them. And he writes, quote, 155 00:08:46,800 --> 00:08:49,840 Speaker 1: the sense of eeriness is probably a form of instinct 156 00:08:49,880 --> 00:08:54,440 Speaker 1: that protects us from proximal rather than distal sources of danger. 157 00:08:54,960 --> 00:08:59,640 Speaker 1: Proximal sources of danger include corpses, members of different species, 158 00:09:00,000 --> 00:09:03,560 Speaker 1: and other entities we can closely approach. Distal sources of 159 00:09:03,640 --> 00:09:08,200 Speaker 1: danger include windstorms and floods. You know, this is interesting 160 00:09:08,200 --> 00:09:11,720 Speaker 1: that the mention of other species. Um. I don't know 161 00:09:11,760 --> 00:09:15,360 Speaker 1: how many films and documentaries I've seen of say, lions 162 00:09:15,440 --> 00:09:20,080 Speaker 1: running around in the natural habitat, and it's almost never creepy. No, 163 00:09:20,200 --> 00:09:22,160 Speaker 1: not not at all, and yet and then mostly a 164 00:09:22,240 --> 00:09:24,080 Speaker 1: lot of times when I'm in a zoo, it's not creepy. 165 00:09:24,200 --> 00:09:26,439 Speaker 1: But there have been times I take my son to 166 00:09:26,480 --> 00:09:29,400 Speaker 1: the zoo a lot here in Atlanta, and there are 167 00:09:29,400 --> 00:09:31,880 Speaker 1: times when we go down to the lion enclosure and 168 00:09:31,880 --> 00:09:33,760 Speaker 1: we're the only people there at the zoo because we've 169 00:09:33,840 --> 00:09:37,040 Speaker 1: arrived super early, and we just we're hanging out with 170 00:09:37,080 --> 00:09:39,400 Speaker 1: a lion on the other side of the glass. You know, 171 00:09:39,400 --> 00:09:44,120 Speaker 1: we're perfectly safe, but a deep uneasiness comes over me, 172 00:09:44,520 --> 00:09:48,559 Speaker 1: washes over me, and uh, and I'm just confronted by 173 00:09:48,679 --> 00:09:52,240 Speaker 1: the the the danger of this situation, Like there's a 174 00:09:52,320 --> 00:09:56,360 Speaker 1: danger that that goes beyond any reason because I am 175 00:09:56,360 --> 00:10:00,000 Speaker 1: in close proximity to a dangerous member of another species, 176 00:10:00,000 --> 00:10:04,320 Speaker 1: a carnivorous um predator, tory animal that would, in under 177 00:10:04,320 --> 00:10:07,640 Speaker 1: normal conditions, potentially kill me. Now there is I would 178 00:10:07,880 --> 00:10:12,160 Speaker 1: bet a very different kind of sensation going on inside 179 00:10:12,200 --> 00:10:16,360 Speaker 1: you when you're in proximity to a lion than when 180 00:10:16,400 --> 00:10:20,199 Speaker 1: you see a creepy looking humanoid robot or a creepy 181 00:10:20,240 --> 00:10:25,000 Speaker 1: looking animation human animation, right like it's it's probably exciting 182 00:10:25,040 --> 00:10:27,360 Speaker 1: the difference between the when when we talked about the 183 00:10:27,360 --> 00:10:30,520 Speaker 1: creepiness episode the creep the difference between the sort of 184 00:10:30,559 --> 00:10:35,360 Speaker 1: like uncomfortable threat ambiguity versus sensing that there truly is 185 00:10:35,400 --> 00:10:37,880 Speaker 1: a threat of some kind. Right, And you know, we 186 00:10:38,240 --> 00:10:41,400 Speaker 1: spoke to illness here, you know, like certainly someone we 187 00:10:41,440 --> 00:10:43,439 Speaker 1: talked about like what happens when a co worker walks 188 00:10:43,520 --> 00:10:46,640 Speaker 1: up to you and they're they're sniveling or more a 189 00:10:46,679 --> 00:10:50,920 Speaker 1: little bit pale, uh and they say, let's French. Well, 190 00:10:50,920 --> 00:10:53,720 Speaker 1: well hopefully not, but yeah, there's a there's an at 191 00:10:53,760 --> 00:10:57,640 Speaker 1: least an initial sense of, oh, what's wrong with this person? Um? 192 00:10:57,920 --> 00:10:59,760 Speaker 1: I wonder if what they have as contagious, should they 193 00:10:59,800 --> 00:11:02,200 Speaker 1: even be at work? I hope they cover their mouth 194 00:11:02,200 --> 00:11:04,600 Speaker 1: when they sneeze, because we are going to be concerned 195 00:11:04,600 --> 00:11:06,840 Speaker 1: on some level with catching whatever they have. If it's 196 00:11:06,960 --> 00:11:10,360 Speaker 1: if it's it's transmittable, right and it I mean there 197 00:11:10,360 --> 00:11:13,440 Speaker 1: are some ways in which we know that seeing illness 198 00:11:13,520 --> 00:11:18,240 Speaker 1: and other people in sights a reaction in the disgust response, right. Yeah. 199 00:11:18,240 --> 00:11:19,960 Speaker 1: And there's been actually a lot of research on the 200 00:11:20,000 --> 00:11:24,440 Speaker 1: discussed the disgusted response. Darwin wrote about it discussed from 201 00:11:24,480 --> 00:11:29,000 Speaker 1: an evolutionary standpoint, is all about disease avoidance, you know, 202 00:11:29,200 --> 00:11:33,560 Speaker 1: like do not eat this, you know, stay away from Yeah, 203 00:11:33,600 --> 00:11:36,320 Speaker 1: something's not right here. You might hurt yourself or get sick. 204 00:11:36,920 --> 00:11:41,200 Speaker 1: So we're talking about sensuous disgust, So discuss that's tied 205 00:11:41,240 --> 00:11:44,680 Speaker 1: to the senses to sense information that we're absorbing. Uh. 206 00:11:44,720 --> 00:11:47,560 Speaker 1: This is deeply seated in the insula, the area of 207 00:11:47,559 --> 00:11:52,440 Speaker 1: the brain that that malfunctions in patients with obsessive compulsive disorder, 208 00:11:52,920 --> 00:11:55,360 Speaker 1: causing them to say, you know, wash and clean things 209 00:11:55,520 --> 00:12:00,400 Speaker 1: endlessly or vacuum unrelenting lye. So the malfunk of that 210 00:12:00,520 --> 00:12:02,920 Speaker 1: area gives us, you know, gives us a clue into 211 00:12:02,960 --> 00:12:07,680 Speaker 1: its functionality. Uh. One interesting fact about disgusting smells, however, 212 00:12:08,120 --> 00:12:11,880 Speaker 1: is that there's a drop off point for bad smell recognition, 213 00:12:12,080 --> 00:12:15,240 Speaker 1: but not for good smells. So I think we've all 214 00:12:15,520 --> 00:12:18,640 Speaker 1: encountered this where it's that like say, say you're in 215 00:12:18,679 --> 00:12:21,160 Speaker 1: your your office and and you share your office with 216 00:12:21,200 --> 00:12:24,520 Speaker 1: a cat box, and at some point the cat uh 217 00:12:24,880 --> 00:12:28,040 Speaker 1: causes quite a stink in there, and you register it first, 218 00:12:28,040 --> 00:12:29,800 Speaker 1: and like, geez, I should stop what I'm doing and 219 00:12:29,880 --> 00:12:32,480 Speaker 1: clean out that cat box. But you keep working, and 220 00:12:32,520 --> 00:12:35,120 Speaker 1: then after a while you don't smell it anymore. But 221 00:12:35,160 --> 00:12:37,720 Speaker 1: then maybe you step outside to check the mail, or 222 00:12:37,880 --> 00:12:39,840 Speaker 1: you go to the you know, the grocery store to 223 00:12:39,840 --> 00:12:41,960 Speaker 1: pick something up, or you know, your partner comes home 224 00:12:42,280 --> 00:12:45,360 Speaker 1: and when when you or they enter the room, you 225 00:12:45,440 --> 00:12:48,240 Speaker 1: go cheese. What happened in here? Did the cat do 226 00:12:48,320 --> 00:12:51,520 Speaker 1: something again? No, you're just re smelling with their Originally 227 00:12:51,640 --> 00:12:53,920 Speaker 1: you forgot about it, right, Yeah, the the brain kind 228 00:12:53,920 --> 00:12:57,360 Speaker 1: of decides, Look at this point, I assume you know 229 00:12:57,559 --> 00:13:00,440 Speaker 1: that she that the cheese is nasty and you're not 230 00:13:00,480 --> 00:13:03,920 Speaker 1: going to eat it um or or that yes, there 231 00:13:04,000 --> 00:13:06,199 Speaker 1: is animal poop around here. It's it's done, it's part 232 00:13:06,240 --> 00:13:10,079 Speaker 1: it's warned you. But the good smell will keep resonating 233 00:13:10,200 --> 00:13:13,400 Speaker 1: because the good smell is probably saying, hey, there's something 234 00:13:13,400 --> 00:13:16,440 Speaker 1: over here, delicious to eat with some fresh berries or whatnot, 235 00:13:16,720 --> 00:13:19,640 Speaker 1: And it'll keep saying, hey, the berries are still here, 236 00:13:19,720 --> 00:13:22,400 Speaker 1: why haven't you eaten them yet? This is there's not 237 00:13:22,440 --> 00:13:24,439 Speaker 1: a lot of sugar out here. You should get at 238 00:13:24,480 --> 00:13:28,200 Speaker 1: these berries while you have a chance. So the beautiful 239 00:13:28,240 --> 00:13:32,360 Speaker 1: remains beautiful, The sweet smelling remains sweet smelling. But something 240 00:13:32,360 --> 00:13:35,320 Speaker 1: that is disgusting even as you know, discussing as a 241 00:13:35,360 --> 00:13:38,160 Speaker 1: foul smell we can grow accustomed to. Okay, so what's 242 00:13:38,200 --> 00:13:42,400 Speaker 1: the analogy to the Uncanny Valley here? Well, I think 243 00:13:42,400 --> 00:13:45,640 Speaker 1: the the analogy here is that if you have a 244 00:13:45,760 --> 00:13:51,319 Speaker 1: disgusted response to the to visual sense information regarding an 245 00:13:51,360 --> 00:13:56,200 Speaker 1: individual's appearance, a robots appearance, of a computer animated characters appearance, 246 00:13:57,040 --> 00:13:59,480 Speaker 1: there could there could also be this disgust drop off 247 00:13:59,480 --> 00:14:01,640 Speaker 1: point as you grow accustomed to it. Oh, and that's 248 00:14:01,679 --> 00:14:03,440 Speaker 1: something that we have seen. We talked about a little 249 00:14:03,440 --> 00:14:06,640 Speaker 1: bit in the last episode, and that uh, some people 250 00:14:06,720 --> 00:14:11,559 Speaker 1: attest that when you spend time around these robots or uh, 251 00:14:11,600 --> 00:14:14,080 Speaker 1: well it was mainly for the robots. The robots that 252 00:14:14,120 --> 00:14:18,079 Speaker 1: at first seemed creepy, they stop bothering you become accustomed 253 00:14:18,120 --> 00:14:20,800 Speaker 1: to them, they're not creepy anymore. I don't so much 254 00:14:20,920 --> 00:14:22,640 Speaker 1: know if that's always going to be the case for 255 00:14:22,680 --> 00:14:27,560 Speaker 1: creepy looking animated humans. Um, but who knows. Now. Another 256 00:14:27,600 --> 00:14:29,680 Speaker 1: thing to keep in mind too, is that the discussed 257 00:14:29,680 --> 00:14:32,280 Speaker 1: response is going to depend on a number of different factors, 258 00:14:32,880 --> 00:14:36,240 Speaker 1: some of which are going to be tied to hormonal situations. So, 259 00:14:36,360 --> 00:14:39,720 Speaker 1: for instance, pregnant women are more sensitive to discussed and 260 00:14:39,720 --> 00:14:43,800 Speaker 1: this is linked to their elevated progesterone levels. So uh, 261 00:14:44,040 --> 00:14:45,840 Speaker 1: And of course there's gonna be other factors beyond that 262 00:14:45,960 --> 00:14:49,120 Speaker 1: for every individual. Yeah. So I think that there's certainly 263 00:14:49,160 --> 00:14:54,800 Speaker 1: could be some amount of biological instinctual response going on 264 00:14:54,880 --> 00:14:57,680 Speaker 1: in the uncanny value effect to the extent that it exists. 265 00:14:57,680 --> 00:14:59,880 Speaker 1: But I think also, based on what we've seen so far, 266 00:15:00,160 --> 00:15:03,160 Speaker 1: probably does not account for all of it. Uh. And 267 00:15:03,480 --> 00:15:06,920 Speaker 1: I think another thing to consider would be going to 268 00:15:07,120 --> 00:15:12,080 Speaker 1: more more complex sort of cognitive psychology, such as cognitive dissonance. Now, 269 00:15:12,520 --> 00:15:15,760 Speaker 1: if you were to just ask me what I thought 270 00:15:15,880 --> 00:15:19,360 Speaker 1: was the most likely answer before I got into the research, 271 00:15:20,160 --> 00:15:22,600 Speaker 1: I would intuitively tend to think that the best answer 272 00:15:22,640 --> 00:15:27,000 Speaker 1: for what causes the Uncanny value effect primarily is our 273 00:15:27,040 --> 00:15:31,240 Speaker 1: inherent discomfort with category confusions. Uh. This is something that 274 00:15:31,280 --> 00:15:33,600 Speaker 1: I think about a lot, in like the creation of 275 00:15:33,640 --> 00:15:36,120 Speaker 1: monster mythology and stuff like that. We we don't like 276 00:15:36,200 --> 00:15:40,000 Speaker 1: the feeling produced by by things that don't fit into 277 00:15:40,040 --> 00:15:44,080 Speaker 1: our normal taxonomys for objects in the world and seem 278 00:15:44,160 --> 00:15:48,160 Speaker 1: to violate our tax taxonomic ordering system. And this is 279 00:15:48,200 --> 00:15:51,160 Speaker 1: why I think monsters are so often hybrids of existing 280 00:15:51,240 --> 00:15:55,120 Speaker 1: things a bull's head on a man's body, things that 281 00:15:55,320 --> 00:16:00,200 Speaker 1: defy our intuitive classification rules. They make us uncomfortable and 282 00:16:00,320 --> 00:16:03,520 Speaker 1: cause a sense of unease, leading to this uncanny feeling. 283 00:16:04,400 --> 00:16:07,560 Speaker 1: So that that's what I would have intuitively said, Yeah, 284 00:16:07,600 --> 00:16:10,920 Speaker 1: that makes sense. Is it wolf or is it man? 285 00:16:10,280 --> 00:16:15,280 Speaker 1: Or right? But negative affinity resulting from this difficulty and 286 00:16:15,320 --> 00:16:19,320 Speaker 1: assigning the entity to a category is it robot or human? 287 00:16:19,840 --> 00:16:23,400 Speaker 1: Despite my intuitive favor for this explanation, I think it 288 00:16:23,440 --> 00:16:26,360 Speaker 1: looks like experimental evidence for this is not strong, and 289 00:16:26,400 --> 00:16:28,640 Speaker 1: in fact, in some ways some of the studies we've 290 00:16:28,640 --> 00:16:31,760 Speaker 1: looked at have somewhat invalidated this. For example, in the 291 00:16:31,840 --> 00:16:33,880 Speaker 1: last episode at the end, I was talking about that 292 00:16:34,160 --> 00:16:38,560 Speaker 1: study by matherin Rifling, and it did not find evidence 293 00:16:38,560 --> 00:16:42,280 Speaker 1: of a strong correlation between here. Here's what you notice 294 00:16:42,320 --> 00:16:46,080 Speaker 1: here the time it took people to rate the mechano 295 00:16:46,200 --> 00:16:50,960 Speaker 1: humanoid qualities of a robot, and that robot pictures likability. 296 00:16:51,040 --> 00:16:54,480 Speaker 1: So if you were talking it up to category confusion, 297 00:16:54,840 --> 00:16:57,400 Speaker 1: you would probably think the robots that people took the 298 00:16:57,560 --> 00:17:00,440 Speaker 1: longest time to figure out how to ray on the 299 00:17:00,480 --> 00:17:04,880 Speaker 1: mechano humanoid scale, and those would be the least likable, right, 300 00:17:04,920 --> 00:17:09,520 Speaker 1: Because they're the ones causing the most category confusion, right. 301 00:17:09,560 --> 00:17:11,000 Speaker 1: But I mean you could also say that, well, you're 302 00:17:11,040 --> 00:17:13,360 Speaker 1: not maybe having not a you're not having a visceral 303 00:17:13,440 --> 00:17:15,720 Speaker 1: gut reaction to them either, you having to think it 304 00:17:15,760 --> 00:17:18,760 Speaker 1: out and try and you know, analyze how you feel 305 00:17:18,800 --> 00:17:20,639 Speaker 1: about it. Oh yeah, I'd say that's exactly what we 306 00:17:20,680 --> 00:17:23,119 Speaker 1: don't like. I mean, we like to be able to 307 00:17:23,240 --> 00:17:27,080 Speaker 1: viscerally categorize things. But but then the uncanny Valley is often, 308 00:17:27,680 --> 00:17:29,480 Speaker 1: at least in terms of the way you're going to 309 00:17:29,560 --> 00:17:33,399 Speaker 1: find it invoked by the average person. It's often discussed 310 00:17:33,400 --> 00:17:35,840 Speaker 1: if it's as if it's a visceral reaction, the sort 311 00:17:35,880 --> 00:17:38,480 Speaker 1: of i'll kill it with fire reaction that people might have, 312 00:17:38,760 --> 00:17:40,840 Speaker 1: where I hate that saying yes, I'm not a fan 313 00:17:40,880 --> 00:17:43,960 Speaker 1: as well, especially when it is applied to outside of 314 00:17:43,960 --> 00:17:48,040 Speaker 1: of a fictional connotations. Right. But so they point out 315 00:17:48,080 --> 00:17:51,440 Speaker 1: the authors here point out that they did not find this. Uh. 316 00:17:51,480 --> 00:17:54,760 Speaker 1: They point out that it's just not a fact that 317 00:17:54,880 --> 00:17:57,400 Speaker 1: the things that took longer to look at and decide 318 00:17:57,440 --> 00:18:01,360 Speaker 1: where the least likable. Though while this is not statistically important, 319 00:18:01,680 --> 00:18:04,199 Speaker 1: just as a point of curiosity, the single face that 320 00:18:04,240 --> 00:18:08,040 Speaker 1: took the longest to rate on the mechanical versus humanoid quality. 321 00:18:08,440 --> 00:18:11,520 Speaker 1: Was also just about the most disliked face in their 322 00:18:11,520 --> 00:18:15,400 Speaker 1: whole collection of faces, but that was just like one outlier. Overall, 323 00:18:15,440 --> 00:18:19,680 Speaker 1: this did not present as a general effect. Other studies 324 00:18:19,680 --> 00:18:22,280 Speaker 1: have also looked into this and have failed to find 325 00:18:22,320 --> 00:18:25,679 Speaker 1: solid evidence for category confusion as the primary driver of 326 00:18:25,720 --> 00:18:29,280 Speaker 1: the negative affinity at the bottom of the uncanny valley. 327 00:18:29,320 --> 00:18:31,879 Speaker 1: So it looks like my intuitions here I think are wrong. 328 00:18:32,600 --> 00:18:35,960 Speaker 1: But there's something that's kind of related as an idea 329 00:18:36,000 --> 00:18:40,040 Speaker 1: that's been explored, and that is the idea of perceptual mismatch. 330 00:18:40,640 --> 00:18:44,480 Speaker 1: So several authors have advocated the idea that this perceptual 331 00:18:44,600 --> 00:18:48,280 Speaker 1: mismatch could be the primary cause of what we don't 332 00:18:48,320 --> 00:18:51,480 Speaker 1: like about things that we would intuitively say fall into 333 00:18:51,520 --> 00:18:54,760 Speaker 1: the uncanny valley. So one piece of research I want 334 00:18:54,760 --> 00:18:57,960 Speaker 1: to mention is a sort of review by uh Cat 335 00:18:58,040 --> 00:19:01,439 Speaker 1: Siri that is a review of empirical evidence on different 336 00:19:01,520 --> 00:19:05,960 Speaker 1: uncanny valley hypotheses support for perceptual mismatch as one road 337 00:19:06,040 --> 00:19:08,520 Speaker 1: to the valley of eerieness that gott to give it 338 00:19:08,560 --> 00:19:13,760 Speaker 1: a different name, apparently in Frontiers in Psychology. And so 339 00:19:13,800 --> 00:19:17,399 Speaker 1: in this study, the authors review present research and claim 340 00:19:17,520 --> 00:19:20,640 Speaker 1: that experimental research attempting to show the Uncanny Valley has 341 00:19:20,640 --> 00:19:24,040 Speaker 1: been inconsistent. They don't exactly say that the uncanny valley 342 00:19:24,080 --> 00:19:27,119 Speaker 1: doesn't exist, but that it's not as simple as often 343 00:19:27,160 --> 00:19:29,240 Speaker 1: believed to be. Something we've been saying for a while now. 344 00:19:29,320 --> 00:19:33,680 Speaker 1: It's it's not that any manipulation of the variable of 345 00:19:33,800 --> 00:19:38,520 Speaker 1: human likeness leads to Uncanny Valley effects. So, in other words, 346 00:19:38,600 --> 00:19:41,640 Speaker 1: that the horizontal axis on the graph is more complicated 347 00:19:41,720 --> 00:19:44,520 Speaker 1: than just the question of how realistically human is it. 348 00:19:44,600 --> 00:19:46,560 Speaker 1: I've seen this come up enough now that I'm pretty 349 00:19:46,560 --> 00:19:50,160 Speaker 1: convinced that that is not necessarily the only or even 350 00:19:50,200 --> 00:19:53,680 Speaker 1: the primary factor here. But they still recognize that there 351 00:19:53,720 --> 00:19:55,520 Speaker 1: is some kind of effect here. So they claim that 352 00:19:55,560 --> 00:19:59,000 Speaker 1: there's evidence against the category confusion basis that we were 353 00:19:59,040 --> 00:20:01,520 Speaker 1: just talking about. But they claim that there has been 354 00:20:01,520 --> 00:20:05,159 Speaker 1: good evidence in support of the perceptual mismatch hypothesis. And 355 00:20:05,200 --> 00:20:07,040 Speaker 1: I want to read what they say. They say quote 356 00:20:07,280 --> 00:20:11,440 Speaker 1: taken together, the present review suggested that although not any 357 00:20:11,520 --> 00:20:14,600 Speaker 1: kind of human likeness manipulation leads to the Uncanny Valley, 358 00:20:14,640 --> 00:20:18,840 Speaker 1: the uncanny valley could be caused by more specific perceptual 359 00:20:18,920 --> 00:20:23,720 Speaker 1: mismatch conditions. Such conditions could originate at least from inconsistent 360 00:20:23,880 --> 00:20:28,560 Speaker 1: realism levels between individual features, and the examples they give 361 00:20:28,600 --> 00:20:33,240 Speaker 1: would be like artificial eyes on a humanlike face, or 362 00:20:33,280 --> 00:20:36,840 Speaker 1: the presence of atypical features such as a typically large 363 00:20:36,920 --> 00:20:41,119 Speaker 1: eyes on an otherwise humanlike character. So what they're saying 364 00:20:41,160 --> 00:20:44,720 Speaker 1: there is not necessarily that you can't tell whether it's 365 00:20:44,720 --> 00:20:47,320 Speaker 1: a robot or a human, but that there have been 366 00:20:47,400 --> 00:20:50,840 Speaker 1: multiple experiments that seem to show people are unsettled and 367 00:20:51,160 --> 00:20:55,439 Speaker 1: made unhappy by things where the features on the face 368 00:20:55,760 --> 00:20:58,400 Speaker 1: or the features of the figure as a whole are 369 00:20:58,600 --> 00:21:03,320 Speaker 1: inconsistently realistic. Like, we're more okay with a robot that's 370 00:21:03,400 --> 00:21:08,000 Speaker 1: consistently realistic at a certain level it maybe say, seventy 371 00:21:08,040 --> 00:21:11,800 Speaker 1: percent than something that has eyes at nine d percent 372 00:21:11,960 --> 00:21:16,880 Speaker 1: and skin at This reminds me, this is just coming 373 00:21:16,880 --> 00:21:18,000 Speaker 1: off the top of my head. So I don't have 374 00:21:18,040 --> 00:21:21,240 Speaker 1: the artist's name here, but there's there's an artist who's 375 00:21:21,240 --> 00:21:24,080 Speaker 1: worth made the rounds where they took cartoon characters and 376 00:21:24,119 --> 00:21:27,600 Speaker 1: they depicted them realistically. So it's Homer Simpson. Yes, Homer 377 00:21:27,640 --> 00:21:32,040 Speaker 1: Simpson with like pores on his skin, you know, horrible. Yeah, 378 00:21:32,320 --> 00:21:33,879 Speaker 1: So that comes to mind is a kind of a 379 00:21:33,880 --> 00:21:37,040 Speaker 1: possible example of this. Yeah. I think that's a good explanation. 380 00:21:37,160 --> 00:21:39,479 Speaker 1: So I want to get into my main takeaways from 381 00:21:39,520 --> 00:21:41,840 Speaker 1: looking at the Uncanny Valley research so far. Maybe you 382 00:21:41,840 --> 00:21:44,280 Speaker 1: can let me know what you think about this. I'd say, 383 00:21:44,359 --> 00:21:46,560 Speaker 1: first of all, I think the Uncanny Valley is a 384 00:21:46,640 --> 00:21:49,880 Speaker 1: real thing, but it's not as simple as Maury's original 385 00:21:49,960 --> 00:21:53,280 Speaker 1: hypothesis would lead you to believe. Uh. First of all, 386 00:21:53,320 --> 00:21:56,960 Speaker 1: people definitely do get creeped out by lots of almost 387 00:21:57,080 --> 00:22:01,120 Speaker 1: human looking things, but it's not a necessarily just that 388 00:22:01,240 --> 00:22:06,000 Speaker 1: the near failed human realism is what makes them unsettling. 389 00:22:06,000 --> 00:22:08,119 Speaker 1: There are other things that appear to be making them 390 00:22:08,240 --> 00:22:12,600 Speaker 1: unsettling though, that the near humanness plays some kind of role. 391 00:22:13,400 --> 00:22:15,040 Speaker 1: And the other big thing is that there appear to 392 00:22:15,040 --> 00:22:19,359 Speaker 1: be multiple dimensions to explain the phenomenon. Right, So, synthetic 393 00:22:19,440 --> 00:22:24,080 Speaker 1: humanoid images, whether robotic or animated, offer multiple dimensions of 394 00:22:24,119 --> 00:22:27,439 Speaker 1: attraction and revulsion. I think it's possible that there are 395 00:22:27,480 --> 00:22:31,720 Speaker 1: some biologically triggered effects the appearance of health or disease, 396 00:22:31,880 --> 00:22:34,440 Speaker 1: the appearance of life or death. But then I think 397 00:22:34,440 --> 00:22:38,080 Speaker 1: there are possibly other things triggered by psychological cognitive dissonance, 398 00:22:38,119 --> 00:22:43,640 Speaker 1: probably not category confusion, um, but but some good evidence 399 00:22:43,680 --> 00:22:46,639 Speaker 1: for this idea of the perceptual mismatch being the cause. 400 00:22:47,440 --> 00:22:50,520 Speaker 1: And then the final thing is that the Uncanny Valley 401 00:22:50,600 --> 00:22:54,480 Speaker 1: effect is context dependent. How long have you been exposed 402 00:22:54,480 --> 00:22:57,800 Speaker 1: to the image in what's setting? Is it part of 403 00:22:57,840 --> 00:23:00,400 Speaker 1: a narrative or some other context in which you're being 404 00:23:00,480 --> 00:23:04,040 Speaker 1: asked to suspend your disbelief or otherwise put yourself in 405 00:23:04,080 --> 00:23:07,280 Speaker 1: a state of openness. Robert, what do you think about 406 00:23:07,280 --> 00:23:10,199 Speaker 1: all this so far? You've got any disagreement? No, I 407 00:23:10,200 --> 00:23:12,800 Speaker 1: mean I I feel like my view on it closely 408 00:23:12,880 --> 00:23:15,560 Speaker 1: lines up with with with yours here basically that it's 409 00:23:15,560 --> 00:23:18,200 Speaker 1: just that there is an effect going on, but it's 410 00:23:18,280 --> 00:23:22,120 Speaker 1: far it's far more nuanced than simply oh these are 411 00:23:22,320 --> 00:23:25,280 Speaker 1: these are the factors that make something fall into the 412 00:23:25,359 --> 00:23:29,240 Speaker 1: Uncanny Valley, not just how realistically human. There's there's other 413 00:23:29,359 --> 00:23:32,240 Speaker 1: stuff going on, right, and not just a mere hybridization. 414 00:23:33,119 --> 00:23:36,800 Speaker 1: It was instantly thinking about um, the borg and UH 415 00:23:36,840 --> 00:23:40,600 Speaker 1: and occasionally the sort of sexy boards that show up 416 00:23:40,920 --> 00:23:44,280 Speaker 1: in the Star Trek universe. No, like, there's there's clearly 417 00:23:44,320 --> 00:23:48,800 Speaker 1: category confusion going on there, but they're they're not depicted 418 00:23:48,880 --> 00:23:53,760 Speaker 1: as particularly uncanny, Like was the board queen? Was she uncanny? 419 00:23:54,400 --> 00:23:56,400 Speaker 1: Kind of? I don't know, I mean, even when I'm 420 00:23:56,400 --> 00:24:00,240 Speaker 1: not a big fan of the way the board look well, 421 00:24:01,440 --> 00:24:04,119 Speaker 1: but the outside of the board. You can also think of, 422 00:24:04,560 --> 00:24:08,280 Speaker 1: you know, various sort of hybrid human creatures depicted in 423 00:24:08,359 --> 00:24:12,040 Speaker 1: fantasy and fiction that that are created in such a 424 00:24:12,080 --> 00:24:15,639 Speaker 1: way to be the alluring, uh, like they managed to 425 00:24:15,680 --> 00:24:21,120 Speaker 1: fetishize the inhuman qualities of them the category of confusion. Yeah, 426 00:24:21,440 --> 00:24:23,760 Speaker 1: uh yeah. It makes me think that there are certain 427 00:24:23,840 --> 00:24:27,600 Speaker 1: qualities of the human appearance that, if altered, are much 428 00:24:27,640 --> 00:24:31,120 Speaker 1: more significant in terms of our affects response than others. 429 00:24:31,800 --> 00:24:34,000 Speaker 1: So it could be and I'm just making this up. 430 00:24:34,040 --> 00:24:36,560 Speaker 1: I don't know if this is true, but that like, uh, 431 00:24:36,960 --> 00:24:41,320 Speaker 1: getting the getting the size of the eyes wrong could 432 00:24:41,440 --> 00:24:45,600 Speaker 1: quite easily lead to a disgust response and revulsion. But 433 00:24:45,680 --> 00:24:49,040 Speaker 1: getting the size of the nose wrong wouldn't. Does that 434 00:24:49,080 --> 00:24:52,240 Speaker 1: make sense? Yeah? Yeah? Or just thinking of eyes, like 435 00:24:52,359 --> 00:24:56,720 Speaker 1: definitely making the eyes inappropriately large leads a creepy factor, 436 00:24:56,760 --> 00:24:59,440 Speaker 1: and this is often employed. I instantly think of the 437 00:24:59,760 --> 00:25:03,240 Speaker 1: Van Piate movie. What twenty thirty Days of Night? Is 438 00:25:03,240 --> 00:25:05,879 Speaker 1: that the name of it? Oh? Something like that. Yeah, 439 00:25:05,880 --> 00:25:07,800 Speaker 1: where they did some sort of digital effect to make ority. 440 00:25:07,840 --> 00:25:10,960 Speaker 1: I don't remember the number, some number of days of PPD, 441 00:25:11,040 --> 00:25:14,119 Speaker 1: days of night. Um. I didn't actually see if the 442 00:25:14,160 --> 00:25:18,560 Speaker 1: trailers were we're certainly interesting. But likewise, if you just 443 00:25:18,600 --> 00:25:21,600 Speaker 1: take an individual and have them wear blackout contact lenses 444 00:25:22,080 --> 00:25:24,560 Speaker 1: like that is often sometimes that's played up for creepiness, 445 00:25:24,560 --> 00:25:26,159 Speaker 1: but a lot of times it's played up for to 446 00:25:26,240 --> 00:25:30,359 Speaker 1: be alluring. You'll have uh, male or female characters that 447 00:25:30,440 --> 00:25:34,119 Speaker 1: are are otherwise dressed in some alluring fashion, but they 448 00:25:34,119 --> 00:25:36,040 Speaker 1: have blacked out eyes and it's who It's kind of 449 00:25:36,080 --> 00:25:39,640 Speaker 1: like supernatural, sexy, cool, as opposed to just like, oh 450 00:25:39,680 --> 00:25:43,120 Speaker 1: my god, why why are your eyes pits of darkness? Yeah, 451 00:25:44,040 --> 00:25:46,119 Speaker 1: but maybe that's just me. Okay, well, I think we 452 00:25:46,119 --> 00:25:48,040 Speaker 1: should take a quick break and when we come back, 453 00:25:48,200 --> 00:25:57,159 Speaker 1: we will go beyond the Uncanny Valley. All right, we're back, Okay, 454 00:25:57,160 --> 00:26:00,560 Speaker 1: So Robert, I can recall discussions going back for years 455 00:26:00,680 --> 00:26:02,280 Speaker 1: about whether we're going to make it out of the 456 00:26:02,359 --> 00:26:05,520 Speaker 1: Uncanny Valley in the realm of robotics or animation, and 457 00:26:05,640 --> 00:26:08,359 Speaker 1: I think from here on I want to focus primarily 458 00:26:08,440 --> 00:26:11,840 Speaker 1: on animation, just to just to keep us focused and 459 00:26:11,880 --> 00:26:14,879 Speaker 1: I think there are actually two separate questions here, assuming 460 00:26:14,920 --> 00:26:18,800 Speaker 1: that the Uncanny Valley is to some extent to coherent idea. 461 00:26:18,880 --> 00:26:21,600 Speaker 1: We've already explained all the ways in which it's obviously 462 00:26:21,600 --> 00:26:25,800 Speaker 1: way more complicated than the naive popular culture culture understanding 463 00:26:25,840 --> 00:26:30,400 Speaker 1: of it. But the two big questions. Number one, can 464 00:26:30,480 --> 00:26:34,520 Speaker 1: we make realistic looking humanoid characters that aren't creepy? I 465 00:26:34,560 --> 00:26:37,000 Speaker 1: think the answer here is yes. I think it's not 466 00:26:37,080 --> 00:26:39,840 Speaker 1: a two dimensional graph. I think you can make things 467 00:26:39,880 --> 00:26:43,840 Speaker 1: that aren't quite photo realistic but look realistic that aren't creepy. 468 00:26:44,080 --> 00:26:47,200 Speaker 1: Current generation video games have been doing this, and as 469 00:26:47,200 --> 00:26:49,040 Speaker 1: I mentioned in the last episode, I think that there 470 00:26:49,040 --> 00:26:52,679 Speaker 1: are tricks to doing this. It's apparently in achieving like 471 00:26:52,720 --> 00:26:57,000 Speaker 1: the right combination of realistic traits and unrealistic traits that 472 00:26:57,160 --> 00:26:59,399 Speaker 1: maybe you would just land on by doing trial and 473 00:26:59,520 --> 00:27:03,080 Speaker 1: error in design over time. You would never mistake these 474 00:27:03,160 --> 00:27:08,160 Speaker 1: characters for photographs of real humans. But they're also not cartoony. 475 00:27:08,200 --> 00:27:12,520 Speaker 1: They've got this feeling of really real ishness, if you 476 00:27:12,560 --> 00:27:15,560 Speaker 1: know what I mean. But they've they've they've attained sort 477 00:27:15,600 --> 00:27:19,960 Speaker 1: of a generally acceptable plateau of realistic affect. But they're 478 00:27:20,000 --> 00:27:24,639 Speaker 1: not skewing into these different danger zones adjacent photo realism, 479 00:27:24,640 --> 00:27:27,600 Speaker 1: where the shortcomings become creepy and off putting and we 480 00:27:27,640 --> 00:27:31,800 Speaker 1: don't like it. Then there would be another question, and 481 00:27:31,880 --> 00:27:35,600 Speaker 1: that's just can we make animated characters that are robustly 482 00:27:35,720 --> 00:27:39,000 Speaker 1: indistinguishable from human like, can we get all the way 483 00:27:39,080 --> 00:27:42,600 Speaker 1: up the other side of the mountain, up to the 484 00:27:42,880 --> 00:27:46,480 Speaker 1: peak of reality? And last week, if you'd ask me, 485 00:27:46,560 --> 00:27:49,399 Speaker 1: my personal answer would have been no, not yet. But 486 00:27:49,480 --> 00:27:51,879 Speaker 1: I think that's actually not as clear cut as we 487 00:27:51,880 --> 00:27:54,800 Speaker 1: would first guess, because you think that perhaps many of 488 00:27:54,840 --> 00:27:58,640 Speaker 1: the humans we see on TV are actually digital creations. 489 00:27:58,840 --> 00:28:03,200 Speaker 1: Oh I know, for a act that that who's that guy, 490 00:28:03,440 --> 00:28:06,320 Speaker 1: that Jimmy Fallon guy? Oh yeah, Jimmy Fallon might be 491 00:28:06,480 --> 00:28:11,199 Speaker 1: a computer generated that is not a person. He has 492 00:28:11,240 --> 00:28:15,320 Speaker 1: been generated by a computer that's in Palo Alto, California. 493 00:28:16,040 --> 00:28:18,400 Speaker 1: It's a super computer. I mean, it's a really good computer. 494 00:28:18,520 --> 00:28:20,760 Speaker 1: But yeah, well, I often feel the same way about 495 00:28:21,080 --> 00:28:24,360 Speaker 1: Michael Fastbender, And granted it's complicated by the fact that 496 00:28:24,400 --> 00:28:27,320 Speaker 1: he has he has a thing for playing androids recently, 497 00:28:27,760 --> 00:28:29,720 Speaker 1: but at times you're just like, no, he's just a 498 00:28:29,720 --> 00:28:32,199 Speaker 1: little too handsome. There's something in human about this this 499 00:28:32,280 --> 00:28:35,480 Speaker 1: man's handsomeness in his charm. So I want to talk 500 00:28:35,520 --> 00:28:38,480 Speaker 1: about one thing that is that has given me pause 501 00:28:38,560 --> 00:28:41,080 Speaker 1: on this subject. And it's going back to what we 502 00:28:41,120 --> 00:28:44,080 Speaker 1: talked about at the beginning of the last episode Rogue one. Yes, 503 00:28:44,720 --> 00:28:47,320 Speaker 1: so back to the c G I Grand mof Tarken 504 00:28:47,720 --> 00:28:49,680 Speaker 1: when I saw When I first saw Rogue one, I 505 00:28:49,720 --> 00:28:51,440 Speaker 1: liked a lot of things about the movie, but I 506 00:28:51,480 --> 00:28:54,000 Speaker 1: did not really like the the c g I. Tarken. 507 00:28:54,560 --> 00:28:58,959 Speaker 1: The the almost Peter Cushing was very, very good, and 508 00:28:59,000 --> 00:29:03,200 Speaker 1: I really mean that, I'm shockingly good, but still not 509 00:29:03,320 --> 00:29:06,440 Speaker 1: quite real to me, still kind of distracting because of 510 00:29:06,440 --> 00:29:10,080 Speaker 1: how slightly off it was. I would not have mistaken 511 00:29:10,080 --> 00:29:13,280 Speaker 1: it for a real person. But the other day I 512 00:29:13,320 --> 00:29:15,920 Speaker 1: was talking in the office to Holly fry Who it's 513 00:29:15,960 --> 00:29:19,959 Speaker 1: It's Holly, a Star Wars fan. She's so, she's one 514 00:29:19,960 --> 00:29:21,959 Speaker 1: of the hosts of Stuff You Missed in History Class, 515 00:29:22,040 --> 00:29:24,960 Speaker 1: one of our one of our podcasts in the podcast 516 00:29:25,000 --> 00:29:27,760 Speaker 1: family here. Yeah, she has hands down the most Star 517 00:29:27,800 --> 00:29:30,360 Speaker 1: Wars knowledgeable person in the office in an office full 518 00:29:30,400 --> 00:29:33,920 Speaker 1: of nerds. Yeah, I should point out that Holly has 519 00:29:34,440 --> 00:29:37,240 Speaker 1: slash had like a golden ticket to go see Rogue 520 00:29:37,240 --> 00:29:40,680 Speaker 1: one anytime she wanted to at the theater. What are 521 00:29:40,720 --> 00:29:43,240 Speaker 1: you serious? And serious? This is? Yeah, yeah, legit, where'd 522 00:29:43,240 --> 00:29:45,320 Speaker 1: that come from? I don't know, I don't know. I'm 523 00:29:45,320 --> 00:29:47,600 Speaker 1: not I'm not at that level of a fandom where 524 00:29:47,600 --> 00:29:50,200 Speaker 1: I'm even offered such things. I know. So if if 525 00:29:50,240 --> 00:29:52,280 Speaker 1: you want to have a funny experience, go up to 526 00:29:52,320 --> 00:29:56,400 Speaker 1: Holly and just like, ask some really obscure random question 527 00:29:56,480 --> 00:29:59,240 Speaker 1: about Star Wars where you think it could not be 528 00:29:59,480 --> 00:30:03,080 Speaker 1: possible that there's an actual answer to this, like oh, 529 00:30:03,120 --> 00:30:06,160 Speaker 1: that stormtrooper on the left, where did he? What planet 530 00:30:06,200 --> 00:30:08,520 Speaker 1: was he born on? Holly will have an answer. She'll 531 00:30:08,560 --> 00:30:10,960 Speaker 1: be like, oh, that was actually addressed in dialogue in 532 00:30:11,000 --> 00:30:14,479 Speaker 1: the Greek dub of this episode of Clone Wars. So 533 00:30:14,600 --> 00:30:17,400 Speaker 1: Holly has amazing Star Wars knowledge. She's super fun to 534 00:30:17,400 --> 00:30:21,040 Speaker 1: talk to about the Star Wars universe. But anyway, Holly 535 00:30:21,080 --> 00:30:23,160 Speaker 1: pointed out that while a lot of people like me 536 00:30:23,280 --> 00:30:25,440 Speaker 1: were saying that the c G I. Tarkan was a 537 00:30:25,480 --> 00:30:29,080 Speaker 1: few pixels short of escaping the valley, then again, there 538 00:30:29,080 --> 00:30:31,960 Speaker 1: were plenty of people, including some older people that she knew, 539 00:30:32,440 --> 00:30:35,400 Speaker 1: who couldn't tell that it wasn't a real person they 540 00:30:35,440 --> 00:30:39,000 Speaker 1: literally they couldn't tell. Well, I'm worried about my viewing 541 00:30:39,120 --> 00:30:41,640 Speaker 1: upcoming viewing of the film because I have I've been 542 00:30:42,240 --> 00:30:46,160 Speaker 1: preconditioned to have a certain response to the to the 543 00:30:46,600 --> 00:30:49,640 Speaker 1: Tarkan bot here. Oh, I'm sorry that we've had this 544 00:30:49,680 --> 00:30:52,080 Speaker 1: discussion before you were able to see the movie for yourself. 545 00:30:52,440 --> 00:30:55,480 Speaker 1: It'll be interesting being preconditioned. Will I go into it, 546 00:30:56,120 --> 00:30:59,520 Speaker 1: you know, expecting an abomination and like, but the level 547 00:30:59,520 --> 00:31:02,120 Speaker 1: of detail will overwhelm me and it won't matter. Or 548 00:31:02,280 --> 00:31:04,280 Speaker 1: Am I going to go into there and nothing is 549 00:31:04,280 --> 00:31:06,600 Speaker 1: gonna fool me because I'm gonna be looking for the cracks? 550 00:31:07,760 --> 00:31:10,720 Speaker 1: You know, I can, I can put myself in a 551 00:31:10,760 --> 00:31:15,960 Speaker 1: mindset where I think it's possible. I might not have 552 00:31:16,120 --> 00:31:18,920 Speaker 1: known that it was a c g I effect if 553 00:31:18,960 --> 00:31:21,160 Speaker 1: I wasn't familiar with what to look for, Like if 554 00:31:21,200 --> 00:31:23,240 Speaker 1: I didn't watch a lot of movies that had c 555 00:31:23,360 --> 00:31:25,960 Speaker 1: g I effects in them, and if I didn't complain 556 00:31:26,040 --> 00:31:28,880 Speaker 1: about c G I a lot. I'm sorry, guilty is charged, 557 00:31:29,080 --> 00:31:32,280 Speaker 1: I'm guilty of that. Uh. If I wasn't aware that 558 00:31:32,320 --> 00:31:35,719 Speaker 1: Peter Cushing was dead, um, if it wasn't if I 559 00:31:35,760 --> 00:31:38,040 Speaker 1: wasn't sort of prepared to see a lot of high 560 00:31:38,040 --> 00:31:40,200 Speaker 1: tech c g I by virtue of the fact that 561 00:31:40,240 --> 00:31:43,240 Speaker 1: I'm sitting in a theater for a Lucasfilm movie, all 562 00:31:43,280 --> 00:31:45,520 Speaker 1: those things. If you took away all the context and 563 00:31:45,600 --> 00:31:49,520 Speaker 1: my pre knowledge, I'm very might possibly have fallen for it. 564 00:31:49,560 --> 00:31:51,800 Speaker 1: I think I might have just it might have just 565 00:31:51,840 --> 00:31:54,080 Speaker 1: gone past me. If I was absorbed in the story, 566 00:31:54,160 --> 00:31:56,560 Speaker 1: I might have thought, Yeah, it's kind of strange looking dude, 567 00:31:56,600 --> 00:31:59,880 Speaker 1: but it's just a dude. And I think it gets 568 00:32:00,040 --> 00:32:03,760 Speaker 1: better or worse, depending on your perspective. So I have 569 00:32:04,120 --> 00:32:09,040 Speaker 1: in October news piece from BBC Asia here about a 570 00:32:09,160 --> 00:32:14,080 Speaker 1: character called Saia, a computer animated character created by the 571 00:32:14,240 --> 00:32:17,600 Speaker 1: Japanese husband and wife graphic design team Terry Yuki and 572 00:32:17,640 --> 00:32:21,200 Speaker 1: Yuka Ishikawa. And I mentioned this one in particular because 573 00:32:21,240 --> 00:32:23,160 Speaker 1: before we did this episode, I went and I looked 574 00:32:23,200 --> 00:32:26,040 Speaker 1: up what are considered a lot of the most realistic 575 00:32:26,080 --> 00:32:30,320 Speaker 1: c g I character creations, the most impressive animations. This 576 00:32:30,360 --> 00:32:32,480 Speaker 1: one came up, and I think this was the most 577 00:32:32,520 --> 00:32:37,160 Speaker 1: impressive to me. It's probably the most photo real computer 578 00:32:37,280 --> 00:32:40,680 Speaker 1: generated human I've come across so far. So Siah is 579 00:32:40,680 --> 00:32:44,360 Speaker 1: supposed to be a seventeen year old Japanese student and 580 00:32:44,400 --> 00:32:46,920 Speaker 1: The creators have been working on her design for a 581 00:32:46,960 --> 00:32:50,120 Speaker 1: couple of years now, and as versions of Saia have 582 00:32:50,200 --> 00:32:52,920 Speaker 1: been posted on the Internet, people have widely reacted with 583 00:32:53,000 --> 00:32:55,880 Speaker 1: comments like, I can't believe that's not a real person. 584 00:32:57,040 --> 00:32:59,640 Speaker 1: And I kind of have to agree. I'm looking at 585 00:32:59,680 --> 00:33:01,880 Speaker 1: these these pictures of her. There are a couple of 586 00:33:01,880 --> 00:33:05,800 Speaker 1: different generations of her design up and the most recent 587 00:33:05,840 --> 00:33:09,920 Speaker 1: one just looks like a photograph of a person. Yeah, 588 00:33:10,040 --> 00:33:13,120 Speaker 1: I I can't tell that that is not a person. 589 00:33:13,280 --> 00:33:18,000 Speaker 1: I have no recourse to critical faculties in my mind 590 00:33:18,080 --> 00:33:20,440 Speaker 1: that would say no, here's where you can tell that 591 00:33:20,440 --> 00:33:23,360 Speaker 1: that's not a real person. Now. At the same time, 592 00:33:23,360 --> 00:33:24,840 Speaker 1: I do have to come back to a comment I 593 00:33:24,880 --> 00:33:27,640 Speaker 1: made earlier that that this is also a it's a 594 00:33:27,760 --> 00:33:30,960 Speaker 1: it's a it's a pretty face, it's a very standard 595 00:33:31,000 --> 00:33:34,600 Speaker 1: face like this is this is leading lady material, Whereas 596 00:33:34,960 --> 00:33:37,000 Speaker 1: I think it gets more problematic when you look at 597 00:33:37,280 --> 00:33:41,120 Speaker 1: character actor type figures such Peter Cushing, because they have 598 00:33:41,320 --> 00:33:44,360 Speaker 1: such a distinctive face. Yes, and Peter Cushing. So this 599 00:33:44,440 --> 00:33:46,560 Speaker 1: is one thing that helps, I think, is that it's 600 00:33:46,640 --> 00:33:51,240 Speaker 1: a young character who has very smooth features. Uh, Peter 601 00:33:51,320 --> 00:33:53,800 Speaker 1: Cushing has a lot of cracks and crags, a lot 602 00:33:53,800 --> 00:33:55,880 Speaker 1: of wrinkles, and I think that that may actually be 603 00:33:56,360 --> 00:33:59,640 Speaker 1: simply having more texture on your face could make it 604 00:33:59,720 --> 00:34:03,000 Speaker 1: much more difficult to make a photo real copy of you. 605 00:34:03,360 --> 00:34:06,960 Speaker 1: That that's entirely possible. But to get back to Saia, 606 00:34:07,080 --> 00:34:10,880 Speaker 1: So in October of last year, the Artist's debuted the 607 00:34:10,920 --> 00:34:14,880 Speaker 1: first animated clip of Siah, which they created using motion 608 00:34:14,920 --> 00:34:18,880 Speaker 1: capture technology, and they debuted at a Japanese consumer electronics show. 609 00:34:19,640 --> 00:34:23,400 Speaker 1: I watched this footage and I think Morey's distinction about 610 00:34:23,440 --> 00:34:27,920 Speaker 1: having different standards for motion and still images does apply 611 00:34:28,080 --> 00:34:31,319 Speaker 1: because while with the still image, I can't tell that's 612 00:34:31,360 --> 00:34:34,719 Speaker 1: not a real person, with the short animated clip, I can. 613 00:34:34,880 --> 00:34:36,680 Speaker 1: I can tell it's not a real person, but it's 614 00:34:36,680 --> 00:34:42,600 Speaker 1: still very very impressive, not as absolutely photo real as 615 00:34:42,640 --> 00:34:46,000 Speaker 1: the still images. But I don't know. I wonder to 616 00:34:46,080 --> 00:34:50,320 Speaker 1: what extent this gap is just um that motion animation 617 00:34:50,400 --> 00:34:53,480 Speaker 1: is a bigger technical project, it takes more investment and 618 00:34:53,560 --> 00:34:56,520 Speaker 1: money and all that, um, And to what extent the 619 00:34:56,520 --> 00:34:59,879 Speaker 1: gap is within the viewers mind essentially, to what ext 620 00:35:00,000 --> 00:35:02,520 Speaker 1: and it's caused by the fact that the climb out 621 00:35:02,520 --> 00:35:06,560 Speaker 1: of the uncanny valley is steeper if you're moving. Now. 622 00:35:06,600 --> 00:35:08,440 Speaker 1: I know we're not talking about robots here, but this, 623 00:35:08,480 --> 00:35:10,879 Speaker 1: of course, this brings up the thought that as where 624 00:35:10,960 --> 00:35:13,680 Speaker 1: as we attempt to conquer this in the realm of 625 00:35:13,880 --> 00:35:18,080 Speaker 1: humanoid robotics, you're gonna inevitably have situations where, oh, it 626 00:35:18,080 --> 00:35:20,200 Speaker 1: looks just like a person if it's walking down the street, 627 00:35:20,640 --> 00:35:23,640 Speaker 1: but if it climbs stairs. There you go. It's not 628 00:35:23,680 --> 00:35:26,960 Speaker 1: necessarily going to add to oh nine the lights in 629 00:35:27,000 --> 00:35:29,600 Speaker 1: the air, but maybe there would be something telling like, oh, 630 00:35:29,680 --> 00:35:31,520 Speaker 1: it looks like a human most of the time. But 631 00:35:31,560 --> 00:35:36,880 Speaker 1: they're gonna be certain movements, certain environmental reactions that are 632 00:35:36,920 --> 00:35:39,560 Speaker 1: just not going to hold up to scrutiny, right, So, 633 00:35:39,960 --> 00:35:42,240 Speaker 1: I don't know. Looking at these things, looking at Tarkan 634 00:35:42,520 --> 00:35:46,000 Speaker 1: in Rogue one, looking at Siah, I think it's clear 635 00:35:46,040 --> 00:35:49,680 Speaker 1: that we're getting closer and closer to really bridging the 636 00:35:49,719 --> 00:35:55,400 Speaker 1: gap on indistinguishable photo real humanity in computer animation. Whether 637 00:35:55,440 --> 00:35:58,040 Speaker 1: you'd call that an uncanny valley or not, obviously this 638 00:35:58,120 --> 00:36:01,239 Speaker 1: is a related but maybe different an issue. What we're 639 00:36:01,280 --> 00:36:05,040 Speaker 1: definitely drawing near is that peak of reality where there 640 00:36:05,040 --> 00:36:09,040 Speaker 1: are synthetically generated images of humans that you can't tell 641 00:36:09,200 --> 00:36:12,960 Speaker 1: from the real thing, and since things in the Uncanny 642 00:36:13,040 --> 00:36:15,239 Speaker 1: Valley are creepy, I think we usually just assume that 643 00:36:15,400 --> 00:36:19,200 Speaker 1: overcoming it is a good thing, right, like designs getting better? Uh. 644 00:36:19,239 --> 00:36:21,160 Speaker 1: In't it kind of cool that we can generate these 645 00:36:21,160 --> 00:36:25,200 Speaker 1: photo real images without without actually having to photograph someone. 646 00:36:26,040 --> 00:36:28,799 Speaker 1: But I'm not so sure that's a good thing. I 647 00:36:28,840 --> 00:36:31,160 Speaker 1: think we should maybe think about the implications of this, 648 00:36:31,320 --> 00:36:34,960 Speaker 1: like what would happen in the world where human simulations, 649 00:36:35,520 --> 00:36:39,960 Speaker 1: especially computer animation, can reliably climb up that second peak. 650 00:36:40,719 --> 00:36:42,480 Speaker 1: So we are going to take a quick break and 651 00:36:42,520 --> 00:36:49,440 Speaker 1: when we come back, we will go beyond the Uncanny Valley. 652 00:36:50,080 --> 00:36:52,120 Speaker 1: All right, we're back. You know, I'm glad you brought 653 00:36:52,160 --> 00:36:54,000 Speaker 1: up this idea of you know, is it a bad thing? 654 00:36:54,040 --> 00:36:56,120 Speaker 1: Is it a good thing? It does remind me of 655 00:36:56,160 --> 00:36:58,080 Speaker 1: a fabulous book that came out a few years back. 656 00:36:58,080 --> 00:36:59,960 Speaker 1: I think I just referenced it in our Sex Spots 657 00:37:00,040 --> 00:37:04,600 Speaker 1: episode titled The wind Up Girl by Paolo baglapi Um. 658 00:37:04,640 --> 00:37:08,680 Speaker 1: It's a near future science fiction tale, just really a 659 00:37:08,680 --> 00:37:12,000 Speaker 1: wonderful novel, very fun, but that the wind Up Girl 660 00:37:12,280 --> 00:37:16,920 Speaker 1: in question is a essentially a sex Spot character. It 661 00:37:16,960 --> 00:37:19,319 Speaker 1: goes you know, that ends up rebelling and you have 662 00:37:19,400 --> 00:37:22,319 Speaker 1: sort of a typical narrative with her, but they call 663 00:37:22,440 --> 00:37:26,439 Speaker 1: her a wind up girl because she's she's she's very 664 00:37:26,440 --> 00:37:29,600 Speaker 1: convincing as a humanoid, except that her skin pours are 665 00:37:29,640 --> 00:37:34,320 Speaker 1: too small and she has an intentionally herkey jerky movement 666 00:37:34,400 --> 00:37:38,000 Speaker 1: to uh to as she walks around. That they did 667 00:37:38,200 --> 00:37:41,080 Speaker 1: so that she could not be mistaken as a person. 668 00:37:41,920 --> 00:37:44,279 Speaker 1: So that so that apparently, like all the I think 669 00:37:44,320 --> 00:37:46,920 Speaker 1: they were called the new people, it's in some cases 670 00:37:47,120 --> 00:37:50,120 Speaker 1: so that the new people could not be mistaken for 671 00:37:50,200 --> 00:37:53,200 Speaker 1: the old people. Whoa It reminds me of how they 672 00:37:53,200 --> 00:37:57,920 Speaker 1: had to add artificial sounds to electric cars for safety purposes. 673 00:37:58,120 --> 00:38:00,840 Speaker 1: Because the cars are too quiet, they can really sneak 674 00:38:00,920 --> 00:38:02,759 Speaker 1: up on you from behind, so they had to make 675 00:38:02,840 --> 00:38:07,600 Speaker 1: them rumble a little bit. Yeah, I think that's an 676 00:38:07,600 --> 00:38:11,640 Speaker 1: app comparison. So here's a question for you, Robert, what 677 00:38:11,840 --> 00:38:16,120 Speaker 1: is the gold standard of evidence that somebody did something? 678 00:38:17,280 --> 00:38:20,440 Speaker 1: Imagine you're on a jury. I'm the defendant. I've been 679 00:38:20,440 --> 00:38:23,560 Speaker 1: accused of offering a cash bribe to a police officer 680 00:38:23,680 --> 00:38:25,880 Speaker 1: if she'll let me borrow her gun for five minutes. 681 00:38:26,600 --> 00:38:29,359 Speaker 1: She says, I did it. I plead not guilty. What 682 00:38:29,360 --> 00:38:32,240 Speaker 1: what's the best evidence to convince you that I really 683 00:38:32,280 --> 00:38:36,640 Speaker 1: did that. Well, it's not human memory, because if we've 684 00:38:36,680 --> 00:38:39,560 Speaker 1: touched on many times before, human memory is falliable and 685 00:38:39,800 --> 00:38:42,360 Speaker 1: and it's a legitimate problem when it comes to to 686 00:38:42,719 --> 00:38:47,120 Speaker 1: eyewitness testimony. But when the eyewitness is a video camera, 687 00:38:47,200 --> 00:38:50,680 Speaker 1: a digital camera that has a long photographic evidence as 688 00:38:50,719 --> 00:38:53,400 Speaker 1: well to certain degrees, like this has been held up 689 00:38:53,400 --> 00:38:56,520 Speaker 1: as the gold standard. I mean, assuming the footage is 690 00:38:56,560 --> 00:39:00,680 Speaker 1: clear enough that the individual's face is visible, all of that. Uh. 691 00:39:00,840 --> 00:39:03,759 Speaker 1: Like even in our science fiction, right, we have so 692 00:39:03,800 --> 00:39:06,960 Speaker 1: many examples of like on Star Trek, again, there would 693 00:39:06,960 --> 00:39:09,920 Speaker 1: be scenes where Picard would command it we zoom in 694 00:39:09,960 --> 00:39:12,920 Speaker 1: and enhance and it was never questioned that there were 695 00:39:12,920 --> 00:39:15,560 Speaker 1: any problems with the enhancing of the image. It was 696 00:39:15,600 --> 00:39:17,239 Speaker 1: just something that was done. It's like, oh, yeah, the 697 00:39:17,280 --> 00:39:19,120 Speaker 1: image is enhanced, and now we see exactly who the 698 00:39:19,160 --> 00:39:21,640 Speaker 1: killer is. Huh. So we should look at this this 699 00:39:21,760 --> 00:39:24,920 Speaker 1: booming new research field. I shouldn't say booming, I just 700 00:39:24,960 --> 00:39:29,680 Speaker 1: mean there are some papers on it, okay, called facial reenactment. 701 00:39:30,360 --> 00:39:32,480 Speaker 1: So this employs some of the same techniques that you 702 00:39:32,520 --> 00:39:36,479 Speaker 1: would see used in uh in studios. If if people 703 00:39:36,520 --> 00:39:39,040 Speaker 1: are doing motion capture for c g I characters In 704 00:39:39,080 --> 00:39:43,000 Speaker 1: movies and video games. You have an actor performer who 705 00:39:43,040 --> 00:39:45,719 Speaker 1: puts on special gear and a special environment surrounded by 706 00:39:45,800 --> 00:39:49,439 Speaker 1: lights and cameras, and the performer acts out motions. These 707 00:39:49,480 --> 00:39:53,359 Speaker 1: motions are captured from multiple angles and different lighting conditions, 708 00:39:53,760 --> 00:39:56,719 Speaker 1: and then they're translated by a computer into the motions 709 00:39:56,760 --> 00:39:58,600 Speaker 1: of a c g I character. You could make a 710 00:39:58,680 --> 00:40:01,239 Speaker 1: c g I me that was doing all the same 711 00:40:01,280 --> 00:40:05,440 Speaker 1: things I did with my body. But what if instead 712 00:40:05,440 --> 00:40:09,000 Speaker 1: of a c g I character you used captured motion 713 00:40:09,080 --> 00:40:13,880 Speaker 1: to manipulate existing video or images of a real person, 714 00:40:14,040 --> 00:40:17,800 Speaker 1: not a c g I character. This technology is already 715 00:40:17,800 --> 00:40:20,520 Speaker 1: in development today, and one example is the research being 716 00:40:20,560 --> 00:40:23,440 Speaker 1: done under the heading as I said, of facial reenactment. 717 00:40:23,440 --> 00:40:26,520 Speaker 1: There are a couple of papers along with accompanying video 718 00:40:26,600 --> 00:40:29,839 Speaker 1: demonstrations by a group of researchers based out of Stanford, 719 00:40:29,960 --> 00:40:33,279 Speaker 1: out of the Max Planck Institute for Informatics and the 720 00:40:33,400 --> 00:40:37,920 Speaker 1: University of Erlangen Nuremberg, and in their own words quote, 721 00:40:38,040 --> 00:40:41,040 Speaker 1: we present a method for the real time transfer of 722 00:40:41,160 --> 00:40:45,279 Speaker 1: facial expressions from an actor in a source video to 723 00:40:45,400 --> 00:40:49,120 Speaker 1: an actor in a target video, thus enabling the ad 724 00:40:49,160 --> 00:40:53,080 Speaker 1: hoc control of the facial expressions of the target actor. 725 00:40:54,239 --> 00:40:55,840 Speaker 1: And so if you haven't seen video of this, you 726 00:40:55,840 --> 00:40:59,600 Speaker 1: should look it up trying facial reenactment video. If you 727 00:40:59,680 --> 00:41:03,359 Speaker 1: have efficient sample video of your target, you can use 728 00:41:03,400 --> 00:41:08,240 Speaker 1: a regular camera to project new facial expressions, including mouth 729 00:41:08,320 --> 00:41:12,520 Speaker 1: movements which form the shapes of words, onto your your 730 00:41:12,560 --> 00:41:15,200 Speaker 1: target in your video. So I could take video of 731 00:41:15,320 --> 00:41:19,160 Speaker 1: Robert talking if I had all this technology, if I 732 00:41:19,160 --> 00:41:21,800 Speaker 1: could take video of Robert talking, and then I could 733 00:41:21,840 --> 00:41:26,040 Speaker 1: film myself saying Halloween five is the best entry in 734 00:41:26,080 --> 00:41:30,640 Speaker 1: the Halloween franchise, and then map that onto Robert's face 735 00:41:30,719 --> 00:41:33,719 Speaker 1: to make his lips say those words, to make his 736 00:41:33,880 --> 00:41:37,279 Speaker 1: face move along with my face as it's being recorded. 737 00:41:37,719 --> 00:41:40,879 Speaker 1: And in the demonstrations of this it looks nearly photo real. 738 00:41:40,960 --> 00:41:44,279 Speaker 1: They do it with with public figures, making them move 739 00:41:44,320 --> 00:41:47,839 Speaker 1: their faces around, move their lips to say things. In 740 00:41:47,880 --> 00:41:50,880 Speaker 1: some cases, I think the average observer already would not 741 00:41:51,040 --> 00:41:54,759 Speaker 1: be able to tell the difference in this video and 742 00:41:54,800 --> 00:41:57,160 Speaker 1: in fact that a similar thing appears to be happening 743 00:41:57,160 --> 00:41:59,839 Speaker 1: with voice. This thing you might have read about last 744 00:41:59,880 --> 00:42:02,200 Speaker 1: year of this thing Adobe Voco, where they came out 745 00:42:02,239 --> 00:42:05,040 Speaker 1: with this announcement that Adobe is working on software where 746 00:42:05,120 --> 00:42:07,680 Speaker 1: you can take a twenty minute sample of your audio 747 00:42:07,800 --> 00:42:10,040 Speaker 1: to learn from. If you've got a recording of somebody 748 00:42:10,120 --> 00:42:12,840 Speaker 1: talking for twenty minutes, I can take it, make a 749 00:42:12,880 --> 00:42:15,879 Speaker 1: recording of you saying things you never said in your 750 00:42:15,880 --> 00:42:19,800 Speaker 1: own voice. I wanna. I seem to remember that before 751 00:42:19,800 --> 00:42:22,920 Speaker 1: his death, Roger Ebert was involved with the project with 752 00:42:22,960 --> 00:42:25,360 Speaker 1: some of this technology. The idea of being that, of 753 00:42:25,360 --> 00:42:29,279 Speaker 1: course he had lost his his availability to talk due 754 00:42:29,320 --> 00:42:34,400 Speaker 1: to illness, but there was so much Roger Ebert audio 755 00:42:34,719 --> 00:42:36,560 Speaker 1: out there from all of his years as a as 756 00:42:36,600 --> 00:42:39,400 Speaker 1: a as a film critic and a TV personality that 757 00:42:39,440 --> 00:42:41,920 Speaker 1: they had this they had, they had everything they needed 758 00:42:42,280 --> 00:42:45,799 Speaker 1: to enable him to say anything new. Yeah, and that 759 00:42:45,800 --> 00:42:49,480 Speaker 1: that explores the totally non nefarious aspect of this. I mean, 760 00:42:49,520 --> 00:42:51,640 Speaker 1: I I don't think people who are pursuing these lines 761 00:42:51,680 --> 00:42:54,279 Speaker 1: of research are just trying to create a world where 762 00:42:54,320 --> 00:42:57,680 Speaker 1: we can fake video evidence of things. But wouldn't that 763 00:42:57,680 --> 00:42:59,960 Speaker 1: be a wonderful thing for somebody who lost their capacity 764 00:43:00,040 --> 00:43:02,759 Speaker 1: for speech they had recordings of their voice to be 765 00:43:02,800 --> 00:43:05,840 Speaker 1: able to create a text to speech voice box that 766 00:43:05,880 --> 00:43:10,600 Speaker 1: could speak with their own voice. That's amazing, that's kind 767 00:43:10,600 --> 00:43:15,240 Speaker 1: of beautiful. But there are these other ways of looking 768 00:43:15,239 --> 00:43:17,879 Speaker 1: at this, and the authors also that they point out that, 769 00:43:18,080 --> 00:43:20,719 Speaker 1: you know, they they in their own defense, they're like, look, 770 00:43:20,760 --> 00:43:22,680 Speaker 1: we're not trying to create a world where people can 771 00:43:22,719 --> 00:43:25,319 Speaker 1: fake video. We also try to show how you can 772 00:43:25,360 --> 00:43:28,840 Speaker 1: detect altered video. So that's another thing they're trying to 773 00:43:28,880 --> 00:43:31,440 Speaker 1: explore and make public because you know, they're not the 774 00:43:31,480 --> 00:43:34,520 Speaker 1: only people pursuing this research. Obviously, people all over the 775 00:43:34,520 --> 00:43:38,200 Speaker 1: place are doing stuff like this, and stuff like this 776 00:43:38,239 --> 00:43:39,960 Speaker 1: has been in the use, has been in use in 777 00:43:40,000 --> 00:43:42,879 Speaker 1: the movie industry for years. Yeah, I mean it makes 778 00:43:42,880 --> 00:43:44,440 Speaker 1: me think that what you would need to go for 779 00:43:44,680 --> 00:43:47,319 Speaker 1: is the equivalent of a water mark. I don't know 780 00:43:47,360 --> 00:43:50,200 Speaker 1: exactly what that watermark would be and what form it 781 00:43:50,239 --> 00:43:53,279 Speaker 1: would take, but it does make me think, well, we're 782 00:43:53,320 --> 00:43:55,440 Speaker 1: going to reach a point where any kind of footage 783 00:43:55,440 --> 00:43:59,680 Speaker 1: has to have the watermark of authenticity, otherwise doubt will 784 00:43:59,719 --> 00:44:04,520 Speaker 1: be asked upon it. Yeah, I'm concerned about the idea 785 00:44:04,560 --> 00:44:07,600 Speaker 1: of living in a world where you can make very 786 00:44:07,680 --> 00:44:12,960 Speaker 1: convincing looking fake video evidence of things, and not just 787 00:44:13,080 --> 00:44:16,160 Speaker 1: because of the specific example of somebody can make a 788 00:44:16,280 --> 00:44:18,840 Speaker 1: video of me or somebody I like, you know, saying 789 00:44:18,920 --> 00:44:21,480 Speaker 1: or doing something that they didn't do. It's not just 790 00:44:21,560 --> 00:44:25,680 Speaker 1: the specifics, it's the general degrading of our trust in 791 00:44:25,719 --> 00:44:29,960 Speaker 1: the ability to look at things and know that they're true. Yeah. 792 00:44:30,000 --> 00:44:32,680 Speaker 1: I mean, we look at the current news cycle and 793 00:44:32,680 --> 00:44:36,120 Speaker 1: there's been a lot of discussion about the reliability of information, 794 00:44:36,239 --> 00:44:40,799 Speaker 1: of so called fake news, the idea that you read, 795 00:44:40,920 --> 00:44:43,520 Speaker 1: do you reach this point where nobody knows what to 796 00:44:43,560 --> 00:44:46,480 Speaker 1: trust anymore? Set of just trusting nothing? And you already 797 00:44:46,520 --> 00:44:49,440 Speaker 1: know this because you don't trust any weird looking picture 798 00:44:49,560 --> 00:44:51,759 Speaker 1: of somebody you see, right, because you know what can 799 00:44:51,800 --> 00:44:54,920 Speaker 1: be done with photoshop. We're already there with still images. 800 00:44:55,080 --> 00:44:59,600 Speaker 1: Photoshop is is basically in many contexts become a verb 801 00:45:01,040 --> 00:45:04,359 Speaker 1: for for the the distortion of truth. But what what 802 00:45:04,440 --> 00:45:08,880 Speaker 1: if we had photoshop to undermine moving video evidence to 803 00:45:08,920 --> 00:45:13,359 Speaker 1: the same extent that photoshop has undermined still images. I mean, 804 00:45:13,400 --> 00:45:15,560 Speaker 1: this is what a lot of these viral fake news 805 00:45:15,560 --> 00:45:17,920 Speaker 1: stories are based on, is a photoshopped image. If you 806 00:45:17,960 --> 00:45:20,520 Speaker 1: go to Snopes or something and you look at what 807 00:45:20,600 --> 00:45:22,759 Speaker 1: a lot a lot of what they're debunking is, it's 808 00:45:22,840 --> 00:45:25,640 Speaker 1: just an image that claims to be real of somebody 809 00:45:25,680 --> 00:45:28,480 Speaker 1: doing something, and they have to track down where it 810 00:45:28,520 --> 00:45:33,040 Speaker 1: came from Yeah, it's difficult to imagine what that what 811 00:45:33,080 --> 00:45:35,840 Speaker 1: would slash will be like when we reach that point 812 00:45:35,880 --> 00:45:39,640 Speaker 1: to where there's where where video even digital footage is 813 00:45:39,680 --> 00:45:41,520 Speaker 1: no longer the gold standard it was. I mean, I 814 00:45:41,600 --> 00:45:46,880 Speaker 1: think it's actually a very important project to maintain a 815 00:45:47,040 --> 00:45:51,920 Speaker 1: version of the Uncanny Valley, to to help people find 816 00:45:51,960 --> 00:45:55,839 Speaker 1: a way to all to separate real video evidence from 817 00:45:55,840 --> 00:45:58,920 Speaker 1: fake video evidence of things, to understand that there are 818 00:45:58,920 --> 00:46:01,800 Speaker 1: things you can look for that separate real moving imagery 819 00:46:01,920 --> 00:46:05,400 Speaker 1: from falsified or synthetic moving imagery. Now, one way you 820 00:46:05,400 --> 00:46:08,960 Speaker 1: can approach this is to do what the authors of 821 00:46:08,960 --> 00:46:11,279 Speaker 1: this research I was talking about do is they say, look, 822 00:46:11,480 --> 00:46:15,160 Speaker 1: here are things that are are signs that video has 823 00:46:15,200 --> 00:46:18,719 Speaker 1: been manipulated. And that's one thing. And maybe there will 824 00:46:18,760 --> 00:46:20,720 Speaker 1: be a lot of experts on this in the future, 825 00:46:20,800 --> 00:46:23,040 Speaker 1: Like it could be a whole field of people who 826 00:46:23,080 --> 00:46:27,919 Speaker 1: are just there to have expertise in authenticating purportedly real 827 00:46:28,040 --> 00:46:31,960 Speaker 1: video of you doing things or not. Uh. Then on 828 00:46:32,000 --> 00:46:35,719 Speaker 1: the other hand, we could hope that there is in 829 00:46:35,880 --> 00:46:40,400 Speaker 1: fact an adaptive response in our discernment in general. And 830 00:46:40,400 --> 00:46:42,800 Speaker 1: this is where I want to go to the concept 831 00:46:42,840 --> 00:46:47,279 Speaker 1: of an of the uncanny Wall. So paper in the 832 00:46:47,320 --> 00:46:51,640 Speaker 1: International Journal of Arts and Technology, authored by Tinwell Grimshawn 833 00:46:51,719 --> 00:46:56,280 Speaker 1: Williams offers this interesting counter hypothesis to the Uncanny Valley. 834 00:46:56,320 --> 00:46:59,240 Speaker 1: And I want to emphasize again we've sort of shifted 835 00:46:59,239 --> 00:47:01,920 Speaker 1: back and forth betwe in the Uncanny Valley itself in 836 00:47:02,000 --> 00:47:05,960 Speaker 1: terms of what causes negative affinity, and then over slightly 837 00:47:06,160 --> 00:47:08,960 Speaker 1: just to the issue of nearing photo realism or not. 838 00:47:09,120 --> 00:47:12,239 Speaker 1: So keep in mind the difference in those subjects. But 839 00:47:13,920 --> 00:47:17,680 Speaker 1: they proposed this idea of the uncanny wall. To put 840 00:47:17,680 --> 00:47:23,239 Speaker 1: it succinctly, they proposed that quote, increasing technological sophistication in 841 00:47:23,320 --> 00:47:27,880 Speaker 1: the creation of realism for humanlike virtual characters is matched 842 00:47:28,480 --> 00:47:33,040 Speaker 1: by increasing technological discernment on the part of the viewer. 843 00:47:33,800 --> 00:47:38,320 Speaker 1: In other words, as humanoid characters become more real, our 844 00:47:38,400 --> 00:47:42,799 Speaker 1: standards for what looks realistic go up. And I do 845 00:47:42,880 --> 00:47:46,799 Speaker 1: think they're just anecdotally personally that I think there's some 846 00:47:46,880 --> 00:47:48,920 Speaker 1: support for this, and I kind of hope this is 847 00:47:48,920 --> 00:47:52,520 Speaker 1: true so we can avoid this world where all video 848 00:47:52,560 --> 00:47:55,960 Speaker 1: evidence is in question. Because I immediately think, right now, 849 00:47:56,000 --> 00:48:00,480 Speaker 1: I've got I've got antennae for photoshopped images, unlike had 850 00:48:00,520 --> 00:48:04,040 Speaker 1: ten years ago. I think stuff that would look obviously 851 00:48:04,160 --> 00:48:07,479 Speaker 1: photoshop to me today would have fooled me ten years ago. 852 00:48:07,760 --> 00:48:11,480 Speaker 1: I think I've simply adapted. And another thing is it 853 00:48:11,520 --> 00:48:13,560 Speaker 1: makes me flashback to the early days of c g 854 00:48:13,680 --> 00:48:17,040 Speaker 1: I in movies and like the thirty two bit video 855 00:48:17,160 --> 00:48:21,759 Speaker 1: game era, or think about like PlayStation one games and 856 00:48:21,880 --> 00:48:24,800 Speaker 1: back then. I remember looking at games for the original 857 00:48:24,840 --> 00:48:29,920 Speaker 1: PlayStation and thinking, wow, that looks so real. And you 858 00:48:29,960 --> 00:48:31,960 Speaker 1: try and play him now and it's painful. Yeah, you 859 00:48:32,000 --> 00:48:36,799 Speaker 1: can't blocky polygons. People's faces have all these sharp corners. 860 00:48:36,960 --> 00:48:40,880 Speaker 1: It's it's hilarious. Uh, there was some kind of geometrical 861 00:48:41,120 --> 00:48:44,360 Speaker 1: nightmare world everything was taking place in where there's just 862 00:48:45,080 --> 00:48:48,240 Speaker 1: lots of sharp angles. But at the time it looked 863 00:48:48,360 --> 00:48:50,839 Speaker 1: so real to me. And another fun trick is go 864 00:48:50,920 --> 00:48:53,839 Speaker 1: back and read movie reviews for movies with bad c 865 00:48:53,960 --> 00:48:58,359 Speaker 1: g I from the nineties. Professional movie reviewers at the time, 866 00:48:58,400 --> 00:49:02,160 Speaker 1: we're often praising the X. One example is like the 867 00:49:02,239 --> 00:49:05,960 Speaker 1: Mortal Kombat movie, the original Mortal Kombat movie. Remember this. 868 00:49:06,280 --> 00:49:08,799 Speaker 1: You can find reviews at the time where people are like, well, 869 00:49:08,840 --> 00:49:13,279 Speaker 1: the stories then an immature but dazzling special effects. Now 870 00:49:13,360 --> 00:49:17,799 Speaker 1: even mentioning those special effects conjures a kind of delirious hilarity. 871 00:49:17,880 --> 00:49:20,160 Speaker 1: You just start laughing when you think about the c 872 00:49:20,280 --> 00:49:23,480 Speaker 1: G I in Mortal Kombat. But that being said, the 873 00:49:23,480 --> 00:49:27,640 Speaker 1: GOA puppet was above reproach, really good. It did have 874 00:49:27,719 --> 00:49:31,799 Speaker 1: kind of nasty beady eyes, kind of crypt keeper ask. Yeah, 875 00:49:31,960 --> 00:49:34,400 Speaker 1: oh yeah, it was like a very It was like 876 00:49:34,440 --> 00:49:40,120 Speaker 1: a bloated, buffed up crypt kicker. But yeah, it's so 877 00:49:40,280 --> 00:49:43,840 Speaker 1: ugly it provokes uncontrollable laughter. But at the time people 878 00:49:43,880 --> 00:49:47,680 Speaker 1: were like, dazzling, looks amazing. Uh. So it makes me 879 00:49:47,719 --> 00:49:51,320 Speaker 1: think that I hope that there is something to this, 880 00:49:51,320 --> 00:49:55,360 Speaker 1: this idea that these authors have that as things continue 881 00:49:55,400 --> 00:49:59,120 Speaker 1: to chase photo realism, as synthetic imagery of humans gets 882 00:49:59,160 --> 00:50:01,799 Speaker 1: closer and closer to the real thing, we just get 883 00:50:01,880 --> 00:50:06,920 Speaker 1: more and more attuned to the minute problems with them 884 00:50:06,960 --> 00:50:11,279 Speaker 1: with them and never really get fully fooled. Well. I 885 00:50:11,320 --> 00:50:14,640 Speaker 1: have two thoughts here, One on the whole water mark thing. 886 00:50:14,640 --> 00:50:17,080 Speaker 1: Maybe it would be some sort of a Bitcoin type 887 00:50:17,120 --> 00:50:21,120 Speaker 1: of authentication system that would be in place. Uh. The 888 00:50:21,560 --> 00:50:23,720 Speaker 1: other is maybe you have to go beyond the real 889 00:50:24,080 --> 00:50:26,239 Speaker 1: maybe safe for a head of state to appear in 890 00:50:26,239 --> 00:50:29,600 Speaker 1: a video and it'd be authentic. They have to appear 891 00:50:29,800 --> 00:50:33,880 Speaker 1: as an as a computer generated avatar so advanced than 892 00:50:33,960 --> 00:50:36,920 Speaker 1: it is that it is beyond the ability of any 893 00:50:37,120 --> 00:50:41,360 Speaker 1: like non state production or company to create like something 894 00:50:41,800 --> 00:50:45,359 Speaker 1: I'm I'm something that at this point in what would 895 00:50:45,360 --> 00:50:47,719 Speaker 1: be their past, I cannot even conceive of, like a 896 00:50:48,000 --> 00:50:51,160 Speaker 1: I don't know, like a five dimensional unfolding c g 897 00:50:51,440 --> 00:50:55,200 Speaker 1: I god being, because how he's going to fake that? 898 00:50:55,239 --> 00:50:57,480 Speaker 1: You can fake a person, but good luck faking the 899 00:50:57,760 --> 00:51:01,680 Speaker 1: fifth dimension hole of avatar or a fish new Okay, 900 00:51:01,680 --> 00:51:05,640 Speaker 1: like like the algorithms for faking a person with a 901 00:51:05,640 --> 00:51:11,040 Speaker 1: lot of photo and and audio visual cues to sample from. 902 00:51:11,080 --> 00:51:12,600 Speaker 1: If you've got a lot of footage out there, you 903 00:51:12,600 --> 00:51:16,280 Speaker 1: could simulate that person, But you couldn't simulate this brand 904 00:51:16,280 --> 00:51:20,680 Speaker 1: new creation that is it requires you know, supercomputers to generate. 905 00:51:20,800 --> 00:51:22,600 Speaker 1: And yeah, and it was probably built from the bottom 906 00:51:22,719 --> 00:51:26,439 Speaker 1: up with completely alien physiology and movements. Just a thought. 907 00:51:26,520 --> 00:51:28,799 Speaker 1: That's kind of a crazy idea, but I like it. Well, 908 00:51:28,840 --> 00:51:31,480 Speaker 1: that's what I'm here for with the crazy ideas. I 909 00:51:31,520 --> 00:51:33,960 Speaker 1: don't know, have you got anything else, Robert, any anything 910 00:51:34,000 --> 00:51:35,799 Speaker 1: else you can think of to save us from the 911 00:51:35,800 --> 00:51:39,719 Speaker 1: future of uh synthetic human imagery? Oh? You know, I 912 00:51:39,719 --> 00:51:41,480 Speaker 1: could sit around here all day and talk about c 913 00:51:41,600 --> 00:51:45,240 Speaker 1: g I, monsters and UH and Uncanny Valley and films 914 00:51:45,239 --> 00:51:47,520 Speaker 1: and video games and whatnot. But you don't have to 915 00:51:47,760 --> 00:51:49,640 Speaker 1: what to save that for another time. Maybe save some 916 00:51:49,719 --> 00:51:52,960 Speaker 1: of it for trailer talk, which will If you're listening 917 00:51:52,960 --> 00:51:54,799 Speaker 1: to this on a Thursday, hopefully you can tune in 918 00:51:54,800 --> 00:51:58,680 Speaker 1: tomorrow around eleven am on our Facebook page. I like 919 00:51:58,719 --> 00:52:00,719 Speaker 1: our Facebook page. While you're at it, follow us there, 920 00:52:00,760 --> 00:52:04,000 Speaker 1: but tune into a little discussion of trailers that are 921 00:52:04,040 --> 00:52:07,760 Speaker 1: associated with the Uncanny Valley. Oh yeah, And in the meantime, 922 00:52:07,960 --> 00:52:09,719 Speaker 1: heading over to stuff to Blow your Mind dot com. 923 00:52:09,719 --> 00:52:12,560 Speaker 1: That's the mothership. That's we will find all of our 924 00:52:12,640 --> 00:52:15,960 Speaker 1: blog posts, our podcast, our videos, and links out to 925 00:52:16,000 --> 00:52:18,600 Speaker 1: our various social media accounts such that Facebook page or 926 00:52:18,719 --> 00:52:21,799 Speaker 1: the Twitter page, the Instagram account, you name it. And 927 00:52:21,880 --> 00:52:23,680 Speaker 1: if you want to get in touch with us directly, 928 00:52:23,760 --> 00:52:26,760 Speaker 1: as always, you can email us at blow the Mind 929 00:52:27,000 --> 00:52:38,880 Speaker 1: at how stuff works dot com for more on this 930 00:52:39,080 --> 00:52:41,600 Speaker 1: and thousands of other topics. Is that how stuff Works 931 00:52:41,600 --> 00:53:02,200 Speaker 1: dot com has atance by the bar