1 00:00:03,040 --> 00:00:05,840 Speaker 1: Welcome to Stuff to Blow Your Mind from how Stuff 2 00:00:05,840 --> 00:00:14,720 Speaker 1: Works dot com. Hey, welcome to Stuff to Blow your Mind. 3 00:00:14,760 --> 00:00:17,239 Speaker 1: My name is Robert Lamb and I'm Joe McCormick, and 4 00:00:17,280 --> 00:00:20,560 Speaker 1: we're back with part two of our discussion of the 5 00:00:20,560 --> 00:00:22,640 Speaker 1: plate a sex Mac and I think that's what we're 6 00:00:22,640 --> 00:00:25,840 Speaker 1: gonna call it, the comedy of errors that exist in 7 00:00:25,880 --> 00:00:28,840 Speaker 1: the machine and artificial intelligence world. That's right. We were 8 00:00:28,840 --> 00:00:30,600 Speaker 1: gonna do it as one episode, but it just went 9 00:00:30,640 --> 00:00:32,440 Speaker 1: too long, had to break it up into two. But 10 00:00:32,479 --> 00:00:35,519 Speaker 1: it has everything it has, uh, it has humor, it 11 00:00:35,600 --> 00:00:41,320 Speaker 1: has theories of humor, it has killer robots, references to RoboCop, 12 00:00:41,800 --> 00:00:44,040 Speaker 1: everything you could ask for. One of my favorite things 13 00:00:44,120 --> 00:00:49,800 Speaker 1: explaining a joke to death, yes and then yes yeah. Yeah. 14 00:00:49,960 --> 00:00:52,360 Speaker 1: Basically this is a lot of joke explaining. But I 15 00:00:52,400 --> 00:00:54,800 Speaker 1: think by the end of it, everyone will still retain 16 00:00:54,840 --> 00:00:57,040 Speaker 1: their ability to laugh. All right, So, in thinking about 17 00:00:57,120 --> 00:01:01,840 Speaker 1: what's so funny about machine failure, uh, and and even 18 00:01:01,960 --> 00:01:05,520 Speaker 1: machine success along a certain you know, parameter of distance 19 00:01:05,640 --> 00:01:08,840 Speaker 1: from what from what it's ultimate level of success would be, 20 00:01:08,880 --> 00:01:11,720 Speaker 1: you know, AI, that's sort of succeeding but still isn't 21 00:01:11,720 --> 00:01:15,759 Speaker 1: really there. Um, I guess it's worthwhile to look at 22 00:01:15,800 --> 00:01:18,720 Speaker 1: what are some of the main theories out there about 23 00:01:18,760 --> 00:01:21,720 Speaker 1: what humor is? Like, why do we find anything funny 24 00:01:21,760 --> 00:01:25,160 Speaker 1: not just machines? Yeah, because it becomes increasingly difficult to 25 00:01:25,240 --> 00:01:28,160 Speaker 1: really uh nail it down, you know, you come back 26 00:01:28,200 --> 00:01:30,399 Speaker 1: to that whole idea of it's funny because it's funny 27 00:01:30,480 --> 00:01:33,360 Speaker 1: or you know what when you see it. Uh. This 28 00:01:33,600 --> 00:01:35,280 Speaker 1: topic has come up a few times on the show 29 00:01:35,319 --> 00:01:40,120 Speaker 1: before um most recently two thousands, seventeens laughing during horror movies. 30 00:01:40,600 --> 00:01:42,440 Speaker 1: That was when Christian was on the show and we 31 00:01:42,480 --> 00:01:46,080 Speaker 1: talked about you know, what is it about horror movies 32 00:01:46,120 --> 00:01:49,680 Speaker 1: like frightening, terrifying films that that elicits laughter from us? 33 00:01:50,120 --> 00:01:51,880 Speaker 1: And then there were a few other ones in the past, 34 00:01:51,880 --> 00:01:54,520 Speaker 1: The healing power of laughter, the killing joke, funny or Die. 35 00:01:54,640 --> 00:01:56,600 Speaker 1: These are all episodes of stuff to blow your mind. 36 00:01:56,640 --> 00:01:59,080 Speaker 1: You can you can check out in the vault if 37 00:01:59,080 --> 00:02:02,320 Speaker 1: you so desire. Yeah, and so what if you go 38 00:02:02,360 --> 00:02:05,240 Speaker 1: and check those out, I'm sure you as you'll probably 39 00:02:05,240 --> 00:02:07,560 Speaker 1: found before. There's no one theory of human right and 40 00:02:07,640 --> 00:02:11,480 Speaker 1: nobody agrees, but there's sort of a host of competing 41 00:02:11,600 --> 00:02:16,720 Speaker 1: theories that I would say aren't even always totally contradicting 42 00:02:16,760 --> 00:02:19,680 Speaker 1: of one another. They they sort of partially overlap and 43 00:02:19,840 --> 00:02:23,560 Speaker 1: partially contradict one another. Right, Yeah, there's not really a 44 00:02:23,600 --> 00:02:26,840 Speaker 1: theory of everything per se, but like each one feels 45 00:02:26,880 --> 00:02:29,720 Speaker 1: a little bit right, like each theory is is kind 46 00:02:29,760 --> 00:02:34,320 Speaker 1: of fondling the elephant. Yeah, exactly. Uh So, a brief 47 00:02:34,400 --> 00:02:35,919 Speaker 1: run through of a few at the top. And there's 48 00:02:35,960 --> 00:02:37,799 Speaker 1: no way to explore all the theories of humor. But 49 00:02:37,880 --> 00:02:40,480 Speaker 1: if you are the most commonly cited and most popular ones, 50 00:02:41,000 --> 00:02:44,120 Speaker 1: one would be the superiority theory. And this is propounded 51 00:02:44,120 --> 00:02:46,680 Speaker 1: in some classical works, like in the works of Plato 52 00:02:46,720 --> 00:02:49,640 Speaker 1: and Aristotle. This one is actually is kind of nasty, 53 00:02:49,680 --> 00:02:52,440 Speaker 1: But sometimes I guess humor is kind of nasty. It 54 00:02:52,560 --> 00:02:55,880 Speaker 1: proposes that we laugh when we notice someone is less 55 00:02:55,919 --> 00:02:58,720 Speaker 1: fortunate than us in one way or another, and the 56 00:02:58,840 --> 00:03:02,280 Speaker 1: laughter comes from our feeling that we occupy a place 57 00:03:02,320 --> 00:03:04,840 Speaker 1: of superiority. We sort of deploy it as a form 58 00:03:04,880 --> 00:03:10,360 Speaker 1: of scorn on somebody else. And Plato and his Philibus dialogue, 59 00:03:10,360 --> 00:03:13,320 Speaker 1: which is discussing the nature of pleasure and different kinds 60 00:03:13,360 --> 00:03:16,120 Speaker 1: of pleasure, like why pleasures of the mind might be 61 00:03:16,160 --> 00:03:20,000 Speaker 1: superior to pleasures of the flesh. Plato has Socrates claim 62 00:03:20,080 --> 00:03:23,440 Speaker 1: that we laugh at people who do not recognize their 63 00:03:23,440 --> 00:03:26,880 Speaker 1: own misfortune, for example, when people are stupid but think 64 00:03:26,960 --> 00:03:30,600 Speaker 1: themselves brilliant, or when people are ugly but think themselves 65 00:03:30,720 --> 00:03:33,920 Speaker 1: very handsome. And I would say this clearly doesn't cover 66 00:03:34,000 --> 00:03:36,560 Speaker 1: all types of humor, Like, you know, what about self 67 00:03:36,560 --> 00:03:40,320 Speaker 1: deprecating humor when you can laugh at yourself, But there's 68 00:03:40,440 --> 00:03:44,320 Speaker 1: something there that is clearly present in some humor. Yeah, well, 69 00:03:44,320 --> 00:03:46,520 Speaker 1: you know, when it comes to self deprecating humor and 70 00:03:46,880 --> 00:03:48,840 Speaker 1: laughing at yourself, I think it does make sense when 71 00:03:48,840 --> 00:03:52,320 Speaker 1: you consider our abilities to sometimes step outside of ourselves 72 00:03:52,400 --> 00:03:55,080 Speaker 1: and see ourselves as a character in a story, sort 73 00:03:55,120 --> 00:03:59,280 Speaker 1: of the infectious nature of narrative there. But then also 74 00:03:59,360 --> 00:04:01,440 Speaker 1: in the way that we use theory of mind way 75 00:04:01,440 --> 00:04:04,280 Speaker 1: too much to try and imagine how others see us. 76 00:04:04,480 --> 00:04:06,520 Speaker 1: So maybe, like, if you're trying to roll with this theory, 77 00:04:06,560 --> 00:04:09,520 Speaker 1: you'd say that self deprecating humor is almost when we 78 00:04:09,760 --> 00:04:13,720 Speaker 1: pretend that we are ourselves someone else and you like 79 00:04:13,800 --> 00:04:17,960 Speaker 1: step step back and you scorn a different version of yourself. Yeah, 80 00:04:18,000 --> 00:04:21,160 Speaker 1: basically like or you're just kind of imagining how scornful 81 00:04:21,200 --> 00:04:24,000 Speaker 1: other people were being to you because of something you 82 00:04:24,279 --> 00:04:28,159 Speaker 1: did or said or thought. Yeah. Um, I mean another 83 00:04:28,160 --> 00:04:29,880 Speaker 1: thing I would just say is that unless you're a 84 00:04:29,960 --> 00:04:32,520 Speaker 1: horrible person, and maybe you know, Plato and Aristotle were 85 00:04:32,640 --> 00:04:35,799 Speaker 1: in some ways very smart but also very horrible people, 86 00:04:37,000 --> 00:04:39,760 Speaker 1: unless you're a really bad person, you don't find most 87 00:04:40,000 --> 00:04:43,560 Speaker 1: types of misfortunes of other people funny. I mean, I 88 00:04:43,600 --> 00:04:46,720 Speaker 1: do see a certain distinction along Plato's lens in the Philippus, 89 00:04:46,800 --> 00:04:51,080 Speaker 1: where like a person just failing to do things that 90 00:04:51,160 --> 00:04:54,320 Speaker 1: you could succeed at is generally not very funny. Like 91 00:04:54,800 --> 00:04:57,240 Speaker 1: somebody trying to solve a math problem you could solve 92 00:04:57,240 --> 00:05:00,599 Speaker 1: and they can't do it, that's not funny. But like 93 00:05:00,640 --> 00:05:03,080 Speaker 1: if a man proclaims himself to be one of the 94 00:05:03,120 --> 00:05:06,039 Speaker 1: greatest brains of all time and then is making basic 95 00:05:06,160 --> 00:05:08,919 Speaker 1: errors of logic and math, that's usually funny. Yeah. I 96 00:05:08,920 --> 00:05:10,440 Speaker 1: think a lot of it hinges on just you know, 97 00:05:10,480 --> 00:05:12,800 Speaker 1: what are the stakes and what sort of misfortune is 98 00:05:12,839 --> 00:05:15,640 Speaker 1: taking place? Like Another sort of example of this is 99 00:05:15,680 --> 00:05:19,880 Speaker 1: when someone thinks they are refined about something, uh, and 100 00:05:20,160 --> 00:05:22,240 Speaker 1: maybe they're a little snobbish about it but there, but 101 00:05:22,320 --> 00:05:24,200 Speaker 1: it turns out their tastes are not quite as refined 102 00:05:24,200 --> 00:05:27,159 Speaker 1: as they thought. Um. I think there was an episode 103 00:05:27,200 --> 00:05:31,000 Speaker 1: of Three's Company back you know in the day, in 104 00:05:31,000 --> 00:05:33,919 Speaker 1: which a don Knots character is ordering like a fine 105 00:05:33,960 --> 00:05:35,960 Speaker 1: scotch at a bar and he's really talking it up 106 00:05:36,000 --> 00:05:37,800 Speaker 1: like he knows what he's talking about, exactly what kind 107 00:05:37,800 --> 00:05:40,240 Speaker 1: of scotch he wants, and then when the bartender finally 108 00:05:40,240 --> 00:05:42,359 Speaker 1: serves it to him, he requests that the rest of 109 00:05:42,360 --> 00:05:45,520 Speaker 1: the glass be filled up with root beer, and you know, 110 00:05:45,640 --> 00:05:48,200 Speaker 1: it's like, like, that's that's so that's hilarious because he 111 00:05:48,680 --> 00:05:50,719 Speaker 1: turns out he's not as as refined as he thought. 112 00:05:50,839 --> 00:05:53,919 Speaker 1: But then it's also like we were being snobbish in 113 00:05:54,080 --> 00:05:57,040 Speaker 1: making that judgment. Uh, And it's and that's always kind 114 00:05:57,040 --> 00:06:00,280 Speaker 1: of a dick move, right because in anything like whatever 115 00:06:00,320 --> 00:06:02,400 Speaker 1: your thing is, that you feel like you're refined and 116 00:06:02,440 --> 00:06:05,919 Speaker 1: be at food or drinks or film or literature, like 117 00:06:05,960 --> 00:06:07,839 Speaker 1: there was a point in your life when you were 118 00:06:07,880 --> 00:06:10,240 Speaker 1: not when you were the person that was the subject 119 00:06:10,279 --> 00:06:13,280 Speaker 1: of scorn. And you know, ultimately we're being fair. You 120 00:06:13,320 --> 00:06:15,680 Speaker 1: should celebrate that they are at all interested in the 121 00:06:15,800 --> 00:06:17,760 Speaker 1: in this thing at all and that they are on 122 00:06:18,600 --> 00:06:21,839 Speaker 1: hopefully on some sort of the same journey that you are, 123 00:06:22,839 --> 00:06:25,279 Speaker 1: but instead we often laugh and said, can you believe 124 00:06:25,320 --> 00:06:27,880 Speaker 1: that guy just put root beer all in that sky? 125 00:06:30,120 --> 00:06:32,720 Speaker 1: I think that's a really good point. So I don't know. 126 00:06:32,760 --> 00:06:35,520 Speaker 1: I would say I definitely see something going on here 127 00:06:35,560 --> 00:06:37,919 Speaker 1: that there are definitely elements of this in humor, but 128 00:06:37,960 --> 00:06:41,040 Speaker 1: I don't think it explains all humor. I don't know 129 00:06:41,080 --> 00:06:43,080 Speaker 1: if maybe, maybe, maybe not. I don't know if it's 130 00:06:43,080 --> 00:06:45,440 Speaker 1: a good fit for why machines are funny, because obviously 131 00:06:45,520 --> 00:06:48,679 Speaker 1: machines aren't people exactly, but maybe we sort of see 132 00:06:48,720 --> 00:06:51,760 Speaker 1: them as people when we think they're funny. Yeah, I 133 00:06:51,800 --> 00:06:54,360 Speaker 1: think if we if you factor in the actual and 134 00:06:54,560 --> 00:06:58,600 Speaker 1: or perceived abilities of AI and robots, either either what 135 00:06:58,640 --> 00:07:01,039 Speaker 1: they can actually do or more I think, to the 136 00:07:01,080 --> 00:07:05,359 Speaker 1: point what our science fiction and our futurist scenarios have 137 00:07:05,480 --> 00:07:08,760 Speaker 1: proposed that they will do or could do one day, 138 00:07:08,839 --> 00:07:11,800 Speaker 1: because we end up with this situation where like we 139 00:07:11,880 --> 00:07:15,160 Speaker 1: watch our room but do something stupid, and there's it's 140 00:07:15,200 --> 00:07:17,480 Speaker 1: hilarious because like, ha, you're never going to terminate or me, 141 00:07:18,440 --> 00:07:20,280 Speaker 1: like you can't even you can't even deal with the 142 00:07:20,760 --> 00:07:25,040 Speaker 1: uh with this rug or this pile of cat vomit. Well, actually, 143 00:07:25,120 --> 00:07:27,960 Speaker 1: though I would say another reason this does kind of 144 00:07:27,960 --> 00:07:30,360 Speaker 1: connect is it does kind of connect to Plato's thing 145 00:07:30,360 --> 00:07:34,480 Speaker 1: about laughing atself ignorance, because one of the funniest things 146 00:07:34,520 --> 00:07:36,560 Speaker 1: that I sort of identified earlier about like the D 147 00:07:36,560 --> 00:07:38,760 Speaker 1: two O nine scene and all that, one of the 148 00:07:38,760 --> 00:07:41,600 Speaker 1: funniest things about the ways that machines fail is the 149 00:07:41,600 --> 00:07:45,000 Speaker 1: way that they are just so completely oblivious to their 150 00:07:45,040 --> 00:07:48,240 Speaker 1: own shortcomings, the way they just uh, the way I 151 00:07:48,240 --> 00:07:51,120 Speaker 1: think of it is that they fail and then plow 152 00:07:51,360 --> 00:07:54,480 Speaker 1: straight ahead. You know, they have they have done something 153 00:07:54,480 --> 00:07:58,240 Speaker 1: crucially wrong, and they do not appreciate this fact. All right, 154 00:07:58,320 --> 00:08:01,000 Speaker 1: let's keep rolling. What are some other theories can discuss? Okay, 155 00:08:01,080 --> 00:08:04,040 Speaker 1: next one would be like the nervous energy release theory. 156 00:08:04,120 --> 00:08:06,320 Speaker 1: And this is not surprisingly at all a take that 157 00:08:06,400 --> 00:08:09,760 Speaker 1: was popular with Freudians. Under this model, laughter is sort 158 00:08:09,800 --> 00:08:13,680 Speaker 1: of a pleasurable release of built up psychic tension caused 159 00:08:13,720 --> 00:08:16,880 Speaker 1: by fear or apprehension. Uh. And there's a certain kind 160 00:08:16,880 --> 00:08:18,600 Speaker 1: of logic to this, right in the way that's a 161 00:08:18,720 --> 00:08:22,560 Speaker 1: good Comedians repeatedly build at tension and then dissipated in 162 00:08:22,680 --> 00:08:25,920 Speaker 1: various ways. I bet this also goes with the laughing 163 00:08:26,000 --> 00:08:29,200 Speaker 1: during horror movies thing, you know, Yeah, for sure, Like you, 164 00:08:29,200 --> 00:08:31,960 Speaker 1: you get your tension built up when there's something scary 165 00:08:32,000 --> 00:08:34,160 Speaker 1: is about to happen, and then after it's over you 166 00:08:34,160 --> 00:08:36,920 Speaker 1: you release the tension and you can laugh. Yeah. Certainly 167 00:08:36,960 --> 00:08:41,160 Speaker 1: with with comedians who really leaned into like the awkwardness 168 00:08:41,160 --> 00:08:43,400 Speaker 1: and the tension, like say like an Andy Kaufman. You 169 00:08:43,440 --> 00:08:46,480 Speaker 1: know where their whole their whole bits or if you 170 00:08:46,480 --> 00:08:49,120 Speaker 1: want to call them bits, where it's really just making 171 00:08:49,400 --> 00:08:52,640 Speaker 1: everyone uncomfortable. It's not even about punchlines. It's about just 172 00:08:52,679 --> 00:08:56,240 Speaker 1: creating this this tension that at some point has to 173 00:08:56,280 --> 00:08:57,680 Speaker 1: be relief. Like at some point all you can do 174 00:08:57,760 --> 00:09:00,079 Speaker 1: is laugh. Yeah, So there's something there. I I this 175 00:09:00,200 --> 00:09:02,640 Speaker 1: clearly doesn't account for everything that's funny, you know, it 176 00:09:02,679 --> 00:09:04,719 Speaker 1: doesn't account for puns and all that kind of thing. 177 00:09:05,000 --> 00:09:07,400 Speaker 1: Uh It, I don't know if I can see a 178 00:09:07,440 --> 00:09:10,760 Speaker 1: way that it really fits with why technology failing is 179 00:09:10,800 --> 00:09:12,760 Speaker 1: all that funny? No, Yeah, I don't think. I don't 180 00:09:12,760 --> 00:09:16,200 Speaker 1: think there's anything particularly insightful about this theory regarding what 181 00:09:16,200 --> 00:09:18,360 Speaker 1: we're talking about here today. Okay, here's another one. How 182 00:09:18,360 --> 00:09:23,240 Speaker 1: about the adaptation, uh to signal play so that laughter 183 00:09:23,320 --> 00:09:26,640 Speaker 1: would be an evolutionary adaptation that occurs when we're engaged 184 00:09:26,679 --> 00:09:30,680 Speaker 1: in pretend aggression during play behaviors. It occurs as a 185 00:09:30,720 --> 00:09:34,680 Speaker 1: signal to help everybody involved understand the fact the behaviors 186 00:09:34,720 --> 00:09:37,600 Speaker 1: like chasing and wrestling and stuff are meant as play 187 00:09:37,760 --> 00:09:40,400 Speaker 1: rather than as genuine aggression or harm. Yeah, this one 188 00:09:40,480 --> 00:09:43,960 Speaker 1: I think is important to mention here, if only for 189 00:09:44,000 --> 00:09:46,480 Speaker 1: the reason that it touches on the social nature of laughter, 190 00:09:47,080 --> 00:09:51,280 Speaker 1: that that laughter is also about communicating with other people 191 00:09:51,760 --> 00:09:56,120 Speaker 1: regarding various threats, etcetera. Um. It's also I wonder if 192 00:09:56,160 --> 00:09:59,160 Speaker 1: this is one where our storytelling has kind of kind 193 00:09:59,160 --> 00:10:03,199 Speaker 1: of led us astray as well, though, because how many 194 00:10:03,320 --> 00:10:10,200 Speaker 1: um individuals that actually intends harm are laughing hysterically or sardonically. 195 00:10:10,920 --> 00:10:14,320 Speaker 1: Like I'm sure it happens, I mean, and maybe one 196 00:10:14,400 --> 00:10:16,480 Speaker 1: or two scenarios even come to mind where someone was 197 00:10:17,360 --> 00:10:19,880 Speaker 1: did something horrible and violent and it was seen laughing, 198 00:10:20,200 --> 00:10:23,320 Speaker 1: But I don't feel like it probably occurs anywhere as 199 00:10:23,520 --> 00:10:27,160 Speaker 1: near as often as it does in movies where villains 200 00:10:27,160 --> 00:10:29,840 Speaker 1: are constantly laughing. Be it, you know, an extreme example 201 00:10:29,880 --> 00:10:33,640 Speaker 1: like the Joker, or or just any you know, you know, 202 00:10:33,679 --> 00:10:37,760 Speaker 1: sardonic villain who just doing maniacally laughs while attempting to 203 00:10:37,800 --> 00:10:40,800 Speaker 1: destroy the world. Uh yeah, I mean I would say 204 00:10:40,800 --> 00:10:43,080 Speaker 1: this probably does go along with the theory then. I mean, 205 00:10:43,920 --> 00:10:47,280 Speaker 1: if it if somebody is laughing while they're actually attempting harm, 206 00:10:47,320 --> 00:10:50,520 Speaker 1: there you know their victim is not laughing so like, 207 00:10:50,880 --> 00:10:52,920 Speaker 1: so yeah, I think this goes along there. Like and 208 00:10:52,960 --> 00:10:54,840 Speaker 1: if they are, then it's like that scene in the 209 00:10:54,840 --> 00:10:58,480 Speaker 1: original um what was a Little Shop of Horrors where 210 00:10:58,760 --> 00:11:00,360 Speaker 1: or maybe it was in the remake is well too, 211 00:11:00,480 --> 00:11:04,720 Speaker 1: where the uh, the the the the the evil dentist 212 00:11:04,840 --> 00:11:06,480 Speaker 1: is going to work on this person and this person 213 00:11:06,520 --> 00:11:09,000 Speaker 1: just wants it, They want the pain, and it just 214 00:11:09,040 --> 00:11:11,840 Speaker 1: totally messes up his his vibe. Yeah, I haven't thought 215 00:11:11,880 --> 00:11:14,640 Speaker 1: how it would accommodate the idea of like villains laughing 216 00:11:14,640 --> 00:11:15,920 Speaker 1: while they do what they do. But I mean, I 217 00:11:15,920 --> 00:11:18,839 Speaker 1: think this is clearly true in some cases that people 218 00:11:18,920 --> 00:11:22,600 Speaker 1: laugh during mock aggressive play behaviors. That dogs wag their 219 00:11:22,600 --> 00:11:26,000 Speaker 1: tails during mock aggressive play behaviors. It's like, you know, 220 00:11:26,040 --> 00:11:28,959 Speaker 1: they're growling and snarling and tumbling, but you can tell 221 00:11:29,000 --> 00:11:31,679 Speaker 1: they're not really fighting because their tails are wagging. And 222 00:11:31,720 --> 00:11:34,000 Speaker 1: this is a nice lead into one of one of 223 00:11:34,040 --> 00:11:35,920 Speaker 1: my favorite theories, and this is one that we discussed 224 00:11:35,920 --> 00:11:39,000 Speaker 1: on the show before in the past, and that's the 225 00:11:39,040 --> 00:11:42,880 Speaker 1: benign violation theory. Yeah, and this theory is very popular now. 226 00:11:42,880 --> 00:11:47,319 Speaker 1: This theory proposes that humor occurs when one we perceive 227 00:11:47,360 --> 00:11:50,280 Speaker 1: a way in which rules or norms of some kind 228 00:11:50,320 --> 00:11:52,640 Speaker 1: are broken. And these rules can be any, you know, 229 00:11:52,679 --> 00:11:56,040 Speaker 1: all kinds of things. They can be grammatical rules, they 230 00:11:56,080 --> 00:11:58,960 Speaker 1: could be biological classifications, they can be the rules of 231 00:11:59,080 --> 00:12:03,240 Speaker 1: making sense, they can be moral norms. Uh. And then second, 232 00:12:03,320 --> 00:12:06,800 Speaker 1: we recognize that there has been a violation, but it's 233 00:12:06,800 --> 00:12:10,640 Speaker 1: not harmful, it's benign in nature. And then third we 234 00:12:10,720 --> 00:12:13,960 Speaker 1: see this contradiction between the fact that there's a violation 235 00:12:14,120 --> 00:12:17,720 Speaker 1: and the fact that it's harmless, and that contradiction triggers humor. 236 00:12:18,120 --> 00:12:20,559 Speaker 1: Like we said, this one is very popular. It's supported 237 00:12:20,559 --> 00:12:24,040 Speaker 1: by some empirical research. Just one example of research and 238 00:12:24,120 --> 00:12:26,080 Speaker 1: support that I came across as a two thousand ten 239 00:12:26,200 --> 00:12:30,480 Speaker 1: study in Psychological Science by McGraw and Warren called benign 240 00:12:30,559 --> 00:12:33,400 Speaker 1: violations making im moral behavior funny and too so. To 241 00:12:33,520 --> 00:12:37,520 Speaker 1: just cite one example that they talk about within that study, quote, 242 00:12:38,080 --> 00:12:40,959 Speaker 1: people who are more weakly committed to a norm can 243 00:12:41,000 --> 00:12:44,559 Speaker 1: recognize the violation, but are less likely to be threatened 244 00:12:44,760 --> 00:12:49,360 Speaker 1: or to directly experience the violation's repercussions. Consider a news 245 00:12:49,400 --> 00:12:52,880 Speaker 1: story about a church that raffles off a hummer suv 246 00:12:53,480 --> 00:12:56,440 Speaker 1: as part of a promotion for its members. Engaging in 247 00:12:56,480 --> 00:12:59,720 Speaker 1: such a secular promotion jeopardizes the sanctity of the church. 248 00:13:00,120 --> 00:13:04,080 Speaker 1: End Although most people consider churches sacred, churchgoers should be 249 00:13:04,160 --> 00:13:07,360 Speaker 1: more strongly committed to this belief than are people who 250 00:13:07,400 --> 00:13:11,480 Speaker 1: do not attend church. So the researchers looked at this 251 00:13:11,520 --> 00:13:14,520 Speaker 1: and they found that while churchgoers and non churchgoers alike 252 00:13:14,520 --> 00:13:17,760 Speaker 1: were about equally disgusted with this story, you know, the 253 00:13:17,800 --> 00:13:19,520 Speaker 1: idea that a church would be trying to get people 254 00:13:19,559 --> 00:13:21,680 Speaker 1: to join by giving them a chance to win a car, 255 00:13:22,800 --> 00:13:27,160 Speaker 1: non churchgoers more often found the story humorous, and so 256 00:13:27,240 --> 00:13:30,720 Speaker 1: that was like non churchgoers to churchgoers finding it humorous 257 00:13:30,800 --> 00:13:34,440 Speaker 1: was nine percent to sixty two percent. So the idea 258 00:13:34,520 --> 00:13:37,800 Speaker 1: is that non churchgoers saw this as a benign violation 259 00:13:37,960 --> 00:13:41,000 Speaker 1: and thus funny, and churchgoers saw it as a real 260 00:13:41,160 --> 00:13:44,400 Speaker 1: harmful violation and thus not funny. Yeah, and I think 261 00:13:44,400 --> 00:13:47,240 Speaker 1: that's something that's important to keep in mind. And you know, 262 00:13:47,280 --> 00:13:49,600 Speaker 1: when when looking at the benign violation theory is that 263 00:13:49,960 --> 00:13:53,720 Speaker 1: how ultimately subjective it is going to be. And of 264 00:13:53,760 --> 00:13:57,400 Speaker 1: course that is comedy as well, so it matches up 265 00:13:57,400 --> 00:13:59,720 Speaker 1: in that regard. Right, It depends on whether you actually 266 00:13:59,760 --> 00:14:02,400 Speaker 1: see something as a violation and whether you actually see 267 00:14:02,440 --> 00:14:04,920 Speaker 1: something as harmful or not. Now, there are different ways 268 00:14:04,920 --> 00:14:07,120 Speaker 1: you could play around with the definitions and of this 269 00:14:07,200 --> 00:14:10,080 Speaker 1: theory to like, like, you could make it very elastic 270 00:14:10,200 --> 00:14:12,840 Speaker 1: to accommodate a lot of stuff, or you could more 271 00:14:12,960 --> 00:14:17,360 Speaker 1: narrowly tailor it. I would say one problem potentially with 272 00:14:17,400 --> 00:14:21,120 Speaker 1: it is that lots of things that are benign violations 273 00:14:21,240 --> 00:14:24,480 Speaker 1: aren't funny at all. Uh. An example I came up 274 00:14:24,520 --> 00:14:26,640 Speaker 1: with is, imagine you are not supposed to take home 275 00:14:26,640 --> 00:14:30,080 Speaker 1: office supplies, but you do you take home a pin. Well, 276 00:14:30,120 --> 00:14:32,600 Speaker 1: that's a violation of the rules. It doesn't it's not 277 00:14:32,680 --> 00:14:36,480 Speaker 1: really harmful, it's benign, and it's not really funny. Right. 278 00:14:36,640 --> 00:14:38,760 Speaker 1: But on the other hand, I would I think the 279 00:14:38,800 --> 00:14:41,680 Speaker 1: counter argument here would be, okay, taking one pin home 280 00:14:41,720 --> 00:14:43,880 Speaker 1: from work, like that's I do that all the time, 281 00:14:44,600 --> 00:14:46,080 Speaker 1: most of us do. It's one thing to take a 282 00:14:46,120 --> 00:14:49,520 Speaker 1: pin home, even accidental, accidentally, take one home to you know, 283 00:14:49,680 --> 00:14:52,560 Speaker 1: purposely take one home. But what have we upped it? 284 00:14:52,640 --> 00:14:55,480 Speaker 1: What have instead of accidentally taking a pin home from work, 285 00:14:55,760 --> 00:14:58,720 Speaker 1: you accidentally took all the pins home from work. That's 286 00:14:58,720 --> 00:15:00,680 Speaker 1: funny now that it was getting into you know a 287 00:15:00,720 --> 00:15:03,600 Speaker 1: little more. And I'm not saying that there's it's the 288 00:15:03,600 --> 00:15:06,480 Speaker 1: funniest gag of all time, but certainly there's more room 289 00:15:06,560 --> 00:15:09,000 Speaker 1: for hilarity in this scenario. Well, that starts to be 290 00:15:09,080 --> 00:15:14,080 Speaker 1: more like a machine type comedic mistake because it's so uh, 291 00:15:14,120 --> 00:15:16,560 Speaker 1: it's so over the top. It seems to kind of 292 00:15:16,600 --> 00:15:19,680 Speaker 1: like not just violate a norm but just plows straight 293 00:15:19,720 --> 00:15:22,720 Speaker 1: through it and goes all the way down right where. 294 00:15:22,720 --> 00:15:25,000 Speaker 1: I guess another way that would work is if one 295 00:15:25,080 --> 00:15:28,720 Speaker 1: meant to steal something of greater value, like one intended 296 00:15:29,120 --> 00:15:34,360 Speaker 1: to to um to perpetrate some greater violation of office norms, 297 00:15:34,400 --> 00:15:36,080 Speaker 1: and then in the end you only stole a pin, 298 00:15:36,760 --> 00:15:38,120 Speaker 1: but even in a done land as well, and it 299 00:15:38,160 --> 00:15:39,760 Speaker 1: really needs to be a box of pins or all 300 00:15:39,840 --> 00:15:41,920 Speaker 1: the pins. Yeah, I guess you could say. I mean, 301 00:15:41,960 --> 00:15:44,560 Speaker 1: I think you could probably play around with exactly how 302 00:15:44,600 --> 00:15:48,040 Speaker 1: you define the terms of benign violation to maybe accommodate 303 00:15:48,040 --> 00:15:51,320 Speaker 1: those counter examples. I would say also though lots of 304 00:15:51,360 --> 00:15:53,720 Speaker 1: things that are funny too, people can feel like they're 305 00:15:53,720 --> 00:15:56,160 Speaker 1: not at all benign, and like think of videos of 306 00:15:56,160 --> 00:15:59,200 Speaker 1: people falling off skateboards and smashing their faces or the 307 00:15:59,240 --> 00:16:02,680 Speaker 1: crotches and the handrails and brick walls and stuff. People 308 00:16:02,760 --> 00:16:05,360 Speaker 1: find these things quite funny, and people can get really 309 00:16:05,440 --> 00:16:08,600 Speaker 1: hurt in them. Yeah, I think with with that, I 310 00:16:08,640 --> 00:16:11,120 Speaker 1: think part of it is that we generally see confirmation 311 00:16:11,200 --> 00:16:14,040 Speaker 1: that they survived, or if we don't see confirmation that 312 00:16:14,120 --> 00:16:17,520 Speaker 1: they survived whatever, they're horrible, you know, skateboarding accident was, 313 00:16:17,800 --> 00:16:20,160 Speaker 1: then we at least don't see them going to the 314 00:16:20,200 --> 00:16:22,880 Speaker 1: e er, you know, like we have no additional information 315 00:16:22,920 --> 00:16:25,800 Speaker 1: to go on, no additional context, and we can just 316 00:16:25,880 --> 00:16:29,480 Speaker 1: kind of assume that they were okay. So, and I 317 00:16:29,600 --> 00:16:32,840 Speaker 1: also was wondering about this. I wondered what extent comedic 318 00:16:32,960 --> 00:16:37,360 Speaker 1: interpretations of slapstick injuries in which harm generally doesn't extend 319 00:16:37,360 --> 00:16:41,840 Speaker 1: beyond the punch line. Um, if these program us to 320 00:16:41,840 --> 00:16:46,080 Speaker 1: to make these kind of comedic interpretations. Uh, for instance, 321 00:16:46,080 --> 00:16:48,080 Speaker 1: you know, when you think about comedic violence, you think 322 00:16:48,120 --> 00:16:51,720 Speaker 1: about the Three Stooges, and certainly they're just always brutalizing 323 00:16:51,760 --> 00:16:54,280 Speaker 1: each other and then they're fine, and then they're back 324 00:16:54,320 --> 00:16:57,640 Speaker 1: for another adventure. They're fine. You don't worry about their health. 325 00:16:58,480 --> 00:17:02,200 Speaker 1: Take a good old fashioned three Stooges fingerpoke. Um, you 326 00:17:02,240 --> 00:17:03,880 Speaker 1: know we have in the in the eye do you 327 00:17:03,920 --> 00:17:05,679 Speaker 1: have two fingers and then you go right for the 328 00:17:05,720 --> 00:17:08,520 Speaker 1: eyes and if nobody gets the block up, bam, there's 329 00:17:08,560 --> 00:17:12,520 Speaker 1: like as more of a blank noise, right. So yeah, 330 00:17:13,000 --> 00:17:16,200 Speaker 1: so when the Stooges do it, uh, it's hilarious, right, 331 00:17:16,200 --> 00:17:20,400 Speaker 1: there's a lot of slapstick hilarity with with the double fingerpoke. 332 00:17:20,920 --> 00:17:24,040 Speaker 1: But and then likewise you look at something like pro wrestling, 333 00:17:24,840 --> 00:17:27,800 Speaker 1: in pro wrestling, which of course is this like sports 334 00:17:27,840 --> 00:17:32,760 Speaker 1: theater thing. Uh, the fingerpoke is a comedy spot, you know, 335 00:17:32,800 --> 00:17:34,920 Speaker 1: it's it's if someone goes for the double eye poke, 336 00:17:35,440 --> 00:17:37,520 Speaker 1: it's going to be a moment of hilarity as well. 337 00:17:38,040 --> 00:17:40,520 Speaker 1: But if somebody does it in a basketball game, that's 338 00:17:40,520 --> 00:17:43,159 Speaker 1: not really funny, right, or or if someone does it 339 00:17:43,200 --> 00:17:47,080 Speaker 1: in most if not all combat sports, it is it 340 00:17:47,200 --> 00:17:50,280 Speaker 1: is a band maneuver. Like generally, if you're going for 341 00:17:50,359 --> 00:17:54,080 Speaker 1: somebody's eyes, like that's either it's either really evil or 342 00:17:54,119 --> 00:17:57,040 Speaker 1: it's a move of desperation. Yeah, this does certainly make 343 00:17:57,040 --> 00:17:59,840 Speaker 1: that to whatever extent the benign violation theory is true, 344 00:17:59,840 --> 00:18:04,320 Speaker 1: it's highly context dependent and and maybe the truth there, 345 00:18:04,440 --> 00:18:07,240 Speaker 1: if there is something to this theory is that um 346 00:18:07,400 --> 00:18:11,520 Speaker 1: is that the context makes us determine what's benign and 347 00:18:11,560 --> 00:18:14,320 Speaker 1: what's not right, and it's gonna be highly dependent on 348 00:18:14,640 --> 00:18:17,520 Speaker 1: the culture you're in, the time you live in. I mean, certainly, 349 00:18:17,560 --> 00:18:20,120 Speaker 1: just thinking of workplace humor, there are a lot of 350 00:18:20,600 --> 00:18:24,760 Speaker 1: violations today that are serious that may have been perceived 351 00:18:24,880 --> 00:18:27,760 Speaker 1: as more benign in days past, or as or seen 352 00:18:27,800 --> 00:18:30,960 Speaker 1: as not violations at all. Oh yeah, this go back 353 00:18:30,960 --> 00:18:34,639 Speaker 1: to like the nineteen eighties, and like workplace sexual harassment 354 00:18:34,840 --> 00:18:38,400 Speaker 1: was a common like sitcom gag at the time. It's 355 00:18:38,440 --> 00:18:41,200 Speaker 1: just like, oh, it's hilarious, you know, he's he's harassing 356 00:18:41,240 --> 00:18:44,480 Speaker 1: Tina again. Uh, And now like that's not really funny 357 00:18:44,520 --> 00:18:46,600 Speaker 1: at all anymore because we see that, I think, I 358 00:18:46,640 --> 00:18:49,840 Speaker 1: think because people see that as a more genuine violation, 359 00:18:49,920 --> 00:18:52,440 Speaker 1: not as something that's just a harmless you can wave 360 00:18:52,480 --> 00:18:54,560 Speaker 1: it off, that's just ted being ted. So how do 361 00:18:54,560 --> 00:18:59,760 Speaker 1: you feel about about benign violation and neural networks? Well, strangely, 362 00:18:59,800 --> 00:19:02,840 Speaker 1: I do see part of a fit here. Um, because 363 00:19:03,000 --> 00:19:06,840 Speaker 1: I along the lines of the Church suv example. The 364 00:19:06,920 --> 00:19:10,840 Speaker 1: more serious and reverent the context in which the technology 365 00:19:10,920 --> 00:19:14,280 Speaker 1: is presented, the funnier it is when it fails. I 366 00:19:14,320 --> 00:19:16,760 Speaker 1: think about like ED two oh nine. This the scene 367 00:19:16,840 --> 00:19:19,040 Speaker 1: is sort of made by the fact that Dick Jones 368 00:19:19,080 --> 00:19:22,159 Speaker 1: and all the biz bros Are proudly boasting about this 369 00:19:22,240 --> 00:19:25,760 Speaker 1: marvelous new technology that will be the future, and then 370 00:19:25,800 --> 00:19:29,360 Speaker 1: it fails in such a spectacular way. I think in general, 371 00:19:29,400 --> 00:19:32,280 Speaker 1: the failures of AI are much funnier when they're presented 372 00:19:32,359 --> 00:19:36,159 Speaker 1: within a context of us knowing about people who believe 373 00:19:36,200 --> 00:19:40,280 Speaker 1: in AI messiahs and you know AI Basilisks and Satan's 374 00:19:40,280 --> 00:19:43,400 Speaker 1: and all that who who uh see this great future 375 00:19:43,560 --> 00:19:47,359 Speaker 1: of of power and dominance among Aiyes, watching them mess 376 00:19:47,480 --> 00:19:51,640 Speaker 1: up in hilarious ways becomes all the more poignant and perfect. 377 00:19:52,359 --> 00:19:54,119 Speaker 1: All right, time to take a quick break. Well, we 378 00:19:54,160 --> 00:19:59,000 Speaker 1: will be right back. Thank alright, we're back. So one 379 00:19:59,000 --> 00:20:02,199 Speaker 1: more theory is the in congruity resolution theory. This is 380 00:20:02,240 --> 00:20:04,760 Speaker 1: a theory that's had various forms over the years, for 381 00:20:04,800 --> 00:20:09,080 Speaker 1: example advocated by Manuel Kant and others, but essentially the 382 00:20:09,119 --> 00:20:13,080 Speaker 1: idea here is that there is an incongruity between expectations 383 00:20:13,080 --> 00:20:17,639 Speaker 1: and reality. Laughter occurs when we realize this incongruity can 384 00:20:17,680 --> 00:20:21,479 Speaker 1: be resolved, and this is there's clearly a strong element 385 00:20:21,520 --> 00:20:24,240 Speaker 1: of this in lots of humors. Again, what joke involves 386 00:20:24,240 --> 00:20:26,640 Speaker 1: a set up and then a punch line, and most 387 00:20:26,720 --> 00:20:30,120 Speaker 1: often the set up sets you up to expect one 388 00:20:30,160 --> 00:20:33,520 Speaker 1: type of thing. The punch line subverts your expectations. So 389 00:20:33,560 --> 00:20:36,280 Speaker 1: that's clearly there. But then again, there are lots of 390 00:20:36,320 --> 00:20:39,480 Speaker 1: things that are surprising and turn our expectations on their heads, 391 00:20:39,480 --> 00:20:42,399 Speaker 1: and they're not funny. Yeah, like we incongruity has to 392 00:20:42,440 --> 00:20:45,160 Speaker 1: be novel. Yeah, you know, it can't be a situation 393 00:20:45,200 --> 00:20:47,600 Speaker 1: where I thought I was buying mozzarella, but I really 394 00:20:47,600 --> 00:20:51,480 Speaker 1: got monster. That's not that. That's really not funny. Now, 395 00:20:51,560 --> 00:20:53,400 Speaker 1: it would be funny if you thought you were buying 396 00:20:53,440 --> 00:20:56,760 Speaker 1: mozzarella you got home and it was like rat eggs, 397 00:20:57,440 --> 00:21:00,840 Speaker 1: especially because rats don't lay eggs. Yeah, it's like that. Yeah, 398 00:21:00,840 --> 00:21:03,800 Speaker 1: that would be that would be a lot more of hilarious. 399 00:21:03,840 --> 00:21:07,080 Speaker 1: One different but somewhat similar theory. I was reading about that. 400 00:21:07,160 --> 00:21:09,359 Speaker 1: I'd like to read this book now that I know 401 00:21:09,400 --> 00:21:12,879 Speaker 1: it exists. It's a two thousand eleven book from M 402 00:21:12,920 --> 00:21:16,479 Speaker 1: I t press called Inside Jokes by the author's Matthew Hurley, 403 00:21:16,560 --> 00:21:21,000 Speaker 1: Daniel Dennett, and Reginald Adams Reginald Adams Jr. And they 404 00:21:21,080 --> 00:21:24,040 Speaker 1: argue against the sufficiency of any of these models we've 405 00:21:24,040 --> 00:21:27,560 Speaker 1: talked about already. They propose instead that humor is an 406 00:21:27,560 --> 00:21:32,479 Speaker 1: evolutionary reward system. It's a pleasurable reward feeling that we 407 00:21:32,560 --> 00:21:36,960 Speaker 1: get when we recognize the inappropriateness of a mental representation 408 00:21:37,160 --> 00:21:40,640 Speaker 1: and then fix it. So it's the brains. It's it's 409 00:21:40,640 --> 00:21:43,200 Speaker 1: an internal reward system like we get from other things 410 00:21:43,240 --> 00:21:46,320 Speaker 1: that are good for the body, like eating or something. Uh. 411 00:21:46,359 --> 00:21:51,000 Speaker 1: It's the brain's reward system for debugging itself. And so 412 00:21:51,080 --> 00:21:52,960 Speaker 1: you can imagine this is why many jokes have a 413 00:21:53,040 --> 00:21:56,800 Speaker 1: set up. The setup prepares you to establish an inappropriate 414 00:21:56,880 --> 00:22:01,840 Speaker 1: or incongruous mental representation. The punch line suddenly creates that 415 00:22:01,920 --> 00:22:06,600 Speaker 1: inappropriate representation, and then the debugging that immediately happens in 416 00:22:06,640 --> 00:22:11,560 Speaker 1: your brain following is rewarded with this pleasurable feeling of humor. Interesting. 417 00:22:11,600 --> 00:22:13,760 Speaker 1: I think that's something that that probably matches as a 418 00:22:13,800 --> 00:22:16,600 Speaker 1: model that matches with a lot of our experience of 419 00:22:16,600 --> 00:22:21,760 Speaker 1: of having hilarious or ridiculous notions enter our head and 420 00:22:21,760 --> 00:22:23,880 Speaker 1: then you just miss them, or you even don't, you're 421 00:22:23,880 --> 00:22:27,680 Speaker 1: not even considering them, but they just rise up from 422 00:22:27,720 --> 00:22:29,800 Speaker 1: the depths of your psyche. Yeah, and I think it 423 00:22:29,960 --> 00:22:32,720 Speaker 1: kind of fits well with what's funny about each entry 424 00:22:32,800 --> 00:22:36,600 Speaker 1: in these like machine generated pieces of text, because each 425 00:22:36,720 --> 00:22:39,399 Speaker 1: moment you're going through this text, you're sort of being 426 00:22:39,520 --> 00:22:42,720 Speaker 1: set up to think about the text in a certain 427 00:22:42,760 --> 00:22:45,800 Speaker 1: way given the category you're already looking for, like names 428 00:22:45,840 --> 00:22:48,960 Speaker 1: of spells and stuff. Then constantly you're given something that 429 00:22:49,040 --> 00:22:51,960 Speaker 1: doesn't really fit, and then your brain has to debug 430 00:22:52,000 --> 00:22:54,720 Speaker 1: why it doesn't really fit, and that feels good. I'm 431 00:22:54,760 --> 00:22:56,840 Speaker 1: not sure it's a perfect theory that covers all of 432 00:22:56,920 --> 00:22:59,800 Speaker 1: humor either, but I am interested in Maybe you know, 433 00:22:59,840 --> 00:23:02,920 Speaker 1: another thing is that, like you said earlier, it's possible 434 00:23:02,960 --> 00:23:07,480 Speaker 1: there's no single, perfect, overarching theory of humor, Like what 435 00:23:07,600 --> 00:23:10,679 Speaker 1: if humor is a category held together not by a 436 00:23:10,760 --> 00:23:14,359 Speaker 1: single all inclusive set of criteria, but by a Wittgensteinian 437 00:23:14,520 --> 00:23:18,840 Speaker 1: kind of family resemblances principle. There's no one thing that 438 00:23:18,840 --> 00:23:23,240 Speaker 1: that all humor is. Humor is instead multiple different related 439 00:23:23,400 --> 00:23:27,399 Speaker 1: sets of things, none of which are entirely contained in 440 00:23:27,400 --> 00:23:29,320 Speaker 1: a single box. By the way, you know, if you 441 00:23:29,320 --> 00:23:30,800 Speaker 1: open that box, it's going to be one of those 442 00:23:30,800 --> 00:23:34,480 Speaker 1: spring snakes that comes flying out, Like open the fake 443 00:23:34,560 --> 00:23:37,040 Speaker 1: cannon nuts. Which one does that fit in? Um? I 444 00:23:37,040 --> 00:23:38,760 Speaker 1: guess you know. It has to do with expectation, but 445 00:23:38,800 --> 00:23:42,520 Speaker 1: also it's benign violation. So if you're expecting nuts, not snakes, 446 00:23:42,640 --> 00:23:44,399 Speaker 1: but you've got a snake. But then, well it's not 447 00:23:44,440 --> 00:23:47,800 Speaker 1: a real snake, which is a perfect animal to include 448 00:23:47,800 --> 00:23:51,600 Speaker 1: in that gag given our you know, our our evolutionary 449 00:23:51,640 --> 00:23:55,480 Speaker 1: response to a serpentine form. What if it's a real 450 00:23:55,520 --> 00:23:57,760 Speaker 1: snake that bites you on the throat, I would like 451 00:23:57,800 --> 00:23:59,560 Speaker 1: to see that happen more or what. One of my 452 00:23:59,640 --> 00:24:02,800 Speaker 1: favorite gags that I did this is that a workplace 453 00:24:02,840 --> 00:24:04,800 Speaker 1: at some point there was this I had to like 454 00:24:04,840 --> 00:24:08,040 Speaker 1: kind of this lame boss who had a can. He 455 00:24:08,080 --> 00:24:11,040 Speaker 1: had this exact gag of fake nuts, fake peanuts, and 456 00:24:11,080 --> 00:24:13,800 Speaker 1: if you opened it, a snake jumped out. Um. So 457 00:24:14,320 --> 00:24:16,199 Speaker 1: one day he was gone for the day and so 458 00:24:16,320 --> 00:24:18,800 Speaker 1: I took the snake, got rid of the snake, and 459 00:24:18,800 --> 00:24:22,000 Speaker 1: I filled it with actual peanuts, and it gave me 460 00:24:22,080 --> 00:24:23,800 Speaker 1: so much pleasure. I don't I never even got to 461 00:24:23,800 --> 00:24:26,399 Speaker 1: witness the payoff. But I just love the idea of 462 00:24:26,480 --> 00:24:29,000 Speaker 1: him going to like pull this out on somebody or 463 00:24:29,040 --> 00:24:31,639 Speaker 1: to just amuse himself, and then it's actually filled with nuts. 464 00:24:31,840 --> 00:24:33,679 Speaker 1: And I don't know how lame the boss was. This 465 00:24:33,720 --> 00:24:35,400 Speaker 1: was This is kind of a time in my life 466 00:24:35,400 --> 00:24:37,960 Speaker 1: when all bosses were lame. So if any of my 467 00:24:38,000 --> 00:24:41,119 Speaker 1: previous bosses are listening to me, I'm probably not talking 468 00:24:41,160 --> 00:24:43,600 Speaker 1: about you. Well, there's another theory of humor that kind 469 00:24:43,600 --> 00:24:46,680 Speaker 1: of fits that because of the way in which humor 470 00:24:46,920 --> 00:24:49,960 Speaker 1: sort of interlocks with our expectations of people based on 471 00:24:50,000 --> 00:24:54,200 Speaker 1: their individual characteristics. Uh So, the next one clearly doesn't 472 00:24:54,200 --> 00:24:56,600 Speaker 1: account for everything that's funny, but it does have a 473 00:24:56,640 --> 00:24:59,320 Speaker 1: kind of elegant, elegant connection to what we're talking about. 474 00:24:59,320 --> 00:25:01,360 Speaker 1: So this is a theory of humor put forward by 475 00:25:01,760 --> 00:25:05,240 Speaker 1: a philosopher named Henri Bergson in a book called Laughter, 476 00:25:05,400 --> 00:25:08,640 Speaker 1: published in nineteen hundred and One of the ideas Bergson 477 00:25:08,720 --> 00:25:12,000 Speaker 1: puts forward here is that laughter is often our response 478 00:25:12,160 --> 00:25:17,600 Speaker 1: to rigidity, inflexibility, and failure to adapt. And this is 479 00:25:17,600 --> 00:25:21,240 Speaker 1: one of the reasons why comedies involve us being aware 480 00:25:21,240 --> 00:25:24,720 Speaker 1: of like the particular flaws of a character and then 481 00:25:24,840 --> 00:25:28,240 Speaker 1: seeing those same flaws acted out over and over again. 482 00:25:28,320 --> 00:25:31,200 Speaker 1: Think about sitcoms, like, it's not just that the characters 483 00:25:31,280 --> 00:25:35,160 Speaker 1: have failures, but they tend to fail repeatedly in in 484 00:25:35,160 --> 00:25:40,160 Speaker 1: individually characteristic ways. Homer Simpson is lazy, and he's thoughtless, 485 00:25:40,240 --> 00:25:43,399 Speaker 1: and he's motivated by donuts and gluttony and all that. Uh. 486 00:25:43,520 --> 00:25:46,720 Speaker 1: Michael Scott in the office is needy and attention seeking 487 00:25:46,760 --> 00:25:50,000 Speaker 1: and unaware of how he's perceived by others. Characters have 488 00:25:50,080 --> 00:25:53,560 Speaker 1: these sort of trademarks and they keep making the same 489 00:25:53,680 --> 00:25:57,840 Speaker 1: kinds of mistakes over and over, and it's their inability 490 00:25:57,920 --> 00:26:01,640 Speaker 1: to adapt that makes humorous in this point of view. Now, 491 00:26:01,640 --> 00:26:04,280 Speaker 1: clearly this doesn't account for everything that's funny, but it 492 00:26:04,400 --> 00:26:06,920 Speaker 1: sort of ties in loosely with the Hurley Dinnett Adams 493 00:26:06,960 --> 00:26:11,000 Speaker 1: theory that humor rewards adaptation and mental debugging. These people, 494 00:26:11,280 --> 00:26:13,880 Speaker 1: if they're making the same mistakes over and over, they're 495 00:26:13,920 --> 00:26:17,359 Speaker 1: not debugging, and you're like debugging by watching them. But 496 00:26:17,400 --> 00:26:18,639 Speaker 1: then again, of course we have to come back to 497 00:26:18,680 --> 00:26:20,760 Speaker 1: sort of the benign violation theory a little bit here, 498 00:26:20,800 --> 00:26:24,920 Speaker 1: because we don't want characters that uh failed too much, 499 00:26:25,040 --> 00:26:26,439 Speaker 1: you know, like you don't want it to be like 500 00:26:26,480 --> 00:26:29,760 Speaker 1: a tragic level of failure, right yeah. And of course 501 00:26:29,760 --> 00:26:32,680 Speaker 1: in reality people fail to adapt all the all the time, 502 00:26:32,720 --> 00:26:34,840 Speaker 1: and ways that aren't funny but are actually like sad 503 00:26:34,960 --> 00:26:37,200 Speaker 1: or tragic or you know, it's something very bad about it. 504 00:26:37,240 --> 00:26:39,479 Speaker 1: And then there's that whole sliding scale too, because especially 505 00:26:39,520 --> 00:26:43,320 Speaker 1: with something like like Michael Scott, especially like the Office 506 00:26:43,359 --> 00:26:47,360 Speaker 1: got into so much awkward territory just every week, week 507 00:26:47,400 --> 00:26:51,080 Speaker 1: after week, and um, a lot of that really got 508 00:26:51,119 --> 00:26:56,840 Speaker 1: into sort of painful, pitiful territory, so that they definitely 509 00:26:56,920 --> 00:27:00,840 Speaker 1: changed exactly where the line was in the sand, but 510 00:27:00,840 --> 00:27:03,679 Speaker 1: but still ultimately, like you know, Michael Scott didn't die 511 00:27:03,720 --> 00:27:05,680 Speaker 1: at the end of an episode, well, it helped by 512 00:27:05,720 --> 00:27:08,679 Speaker 1: coming back and making the character lovable, like he wasn't 513 00:27:09,040 --> 00:27:12,680 Speaker 1: getting into that like sad awkwardness and then just ending 514 00:27:12,680 --> 00:27:16,280 Speaker 1: in a place where you hate him, right yeah. But anyway, 515 00:27:16,320 --> 00:27:19,959 Speaker 1: I think this theory about like rigidity and inflexibility and 516 00:27:20,400 --> 00:27:24,200 Speaker 1: like repeating the same types of mistakes without adapting has 517 00:27:24,280 --> 00:27:28,640 Speaker 1: some strong purchase on the funniest features of machine failure comedy. 518 00:27:28,720 --> 00:27:31,000 Speaker 1: It's not just that the machine fails, but that the 519 00:27:31,040 --> 00:27:36,679 Speaker 1: machine fails repeatedly mechanically. According to inflexible guidelines, like the 520 00:27:36,680 --> 00:27:39,639 Speaker 1: way it just keeps following the rules, when a neural 521 00:27:39,720 --> 00:27:43,280 Speaker 1: net text generator spits out not just one nonsensical phrase, 522 00:27:43,359 --> 00:27:47,239 Speaker 1: but like reams and reams of text without acknowledging or 523 00:27:47,280 --> 00:27:49,520 Speaker 1: knowing it all that the first few words didn't make 524 00:27:49,560 --> 00:27:52,080 Speaker 1: any sense. Or when I think about when a glitching 525 00:27:52,200 --> 00:27:55,720 Speaker 1: video game character is stuck inside a table and just 526 00:27:55,880 --> 00:27:59,840 Speaker 1: keeps running in place and talking. That's one of my favorites. 527 00:28:00,119 --> 00:28:03,399 Speaker 1: Or that lack of contacts, lack of context, lack of 528 00:28:03,440 --> 00:28:07,000 Speaker 1: self awareness, and lack of adaptability. The way machines just 529 00:28:07,240 --> 00:28:11,080 Speaker 1: plow ahead despite problems that are obvious to us that 530 00:28:11,160 --> 00:28:14,119 Speaker 1: they're clearly not aware of. I think that's key to 531 00:28:14,200 --> 00:28:17,160 Speaker 1: what makes them so especially funny. And in this sense, 532 00:28:17,160 --> 00:28:20,240 Speaker 1: they're kind of like the Homer Simpsons and the Michael Scott's, 533 00:28:20,440 --> 00:28:24,960 Speaker 1: the characters with inflexible, repetitive behaviors that lead to disaster 534 00:28:25,080 --> 00:28:28,080 Speaker 1: but which they never learned from or change. You know, 535 00:28:28,160 --> 00:28:30,440 Speaker 1: I can't help but come back to the idea of 536 00:28:30,680 --> 00:28:32,480 Speaker 1: of a child and all of this and the child 537 00:28:32,520 --> 00:28:34,840 Speaker 1: analogy here, so you know we can we can laugh 538 00:28:34,880 --> 00:28:38,480 Speaker 1: at our own children's mistakes are weird interpretations because we 539 00:28:38,600 --> 00:28:41,560 Speaker 1: know that they're they're largely going to adapt, they're going 540 00:28:41,600 --> 00:28:44,240 Speaker 1: to grow up, uh, and that they're going to leave 541 00:28:44,240 --> 00:28:48,280 Speaker 1: behind their their dragons or hopefully they're just gonna remember 542 00:28:48,280 --> 00:28:51,360 Speaker 1: how to summon them in appropriate ways now. But if 543 00:28:51,360 --> 00:28:54,080 Speaker 1: they're the robot is hilarious because it continues to fail, 544 00:28:54,120 --> 00:28:55,960 Speaker 1: and of course also because it is a machine and 545 00:28:56,000 --> 00:28:59,000 Speaker 1: not a human child. Perhaps part of the issue too, 546 00:28:59,120 --> 00:29:01,880 Speaker 1: is that a machine is but a prototype, and it's 547 00:29:02,040 --> 00:29:06,200 Speaker 1: next phase of advancement does not necessarily exist within itself, 548 00:29:06,600 --> 00:29:10,200 Speaker 1: but in the next prototype and another individual, if you will. 549 00:29:10,320 --> 00:29:12,680 Speaker 1: I think that's a really good point. Yes, Like, so 550 00:29:12,720 --> 00:29:15,960 Speaker 1: a child can make a funny mistake, but then the 551 00:29:16,080 --> 00:29:21,280 Speaker 1: child immediately within themselves learn something and or you know, 552 00:29:21,320 --> 00:29:24,000 Speaker 1: at least as the potential learn something and grow and 553 00:29:24,040 --> 00:29:26,440 Speaker 1: get better at not making that kind of mistake anymore, 554 00:29:26,520 --> 00:29:28,920 Speaker 1: which in some cases kind of tragic because the mistakes 555 00:29:28,920 --> 00:29:32,160 Speaker 1: are glorious. Oh yeah, like half the in jokes that 556 00:29:32,200 --> 00:29:35,280 Speaker 1: my wife and I make are two things that my 557 00:29:35,280 --> 00:29:38,080 Speaker 1: my son has not said in years, but he said 558 00:29:38,080 --> 00:29:40,280 Speaker 1: it was and it was hilarious, and now we repeat 559 00:29:40,280 --> 00:29:42,800 Speaker 1: it to each other. But like most of these machines, 560 00:29:43,320 --> 00:29:45,800 Speaker 1: even though they might have the ability to learn from 561 00:29:45,800 --> 00:29:49,080 Speaker 1: their mistakes. They learn from their their mistakes in like 562 00:29:49,200 --> 00:29:52,680 Speaker 1: new instantiations of one of themselves, like you're saying, it's 563 00:29:52,680 --> 00:29:56,080 Speaker 1: the next prototype. They don't automatically learn from their mistakes. 564 00:29:56,160 --> 00:29:59,080 Speaker 1: You have to do something to them to reboot them 565 00:29:59,160 --> 00:30:01,479 Speaker 1: or retrain the them or something right. And if it's 566 00:30:01,480 --> 00:30:04,400 Speaker 1: a video game that, yeah, this, this character is gonna 567 00:30:04,440 --> 00:30:06,360 Speaker 1: keep getting stuck in that table. Maybe there'll be a 568 00:30:06,400 --> 00:30:08,479 Speaker 1: patch that fixes it, but for the most part, it's 569 00:30:08,520 --> 00:30:10,560 Speaker 1: going to be the sequel that tries to get it right. 570 00:30:10,760 --> 00:30:12,400 Speaker 1: All right, we're gonna take a quick break, but we'll 571 00:30:12,400 --> 00:30:17,600 Speaker 1: be right back. And we're back now. I think this 572 00:30:17,720 --> 00:30:19,959 Speaker 1: is all one of one of the reasons that the 573 00:30:19,960 --> 00:30:26,000 Speaker 1: Black Mirror episode Metal Head from is so effective. Oh 574 00:30:26,080 --> 00:30:29,400 Speaker 1: it's it's it's one of my favorites. Um this was 575 00:30:29,440 --> 00:30:32,240 Speaker 1: This was again seen. And this came after years of 576 00:30:32,440 --> 00:30:37,560 Speaker 1: us watching impressive, yet ultimately clumsy and imperfect Boston Dynamics 577 00:30:37,680 --> 00:30:42,280 Speaker 1: walking robot videos, videos of such you know entities as 578 00:30:42,320 --> 00:30:44,880 Speaker 1: Big Dog, you know, which kind of has this springy 579 00:30:45,040 --> 00:30:49,000 Speaker 1: brant kind of a sound as it prances along, and 580 00:30:49,240 --> 00:30:51,680 Speaker 1: it's very impressive to look at and yet at the 581 00:30:51,720 --> 00:30:54,240 Speaker 1: same time, you know their videos of being kicked around, 582 00:30:54,560 --> 00:30:56,960 Speaker 1: and you know, certainly if it's succeeding a lot, but 583 00:30:57,040 --> 00:31:00,800 Speaker 1: also not quite it's not reaching that level of like 584 00:31:01,080 --> 00:31:05,000 Speaker 1: mature technology. Yeah, though I worry how much I already 585 00:31:05,000 --> 00:31:08,320 Speaker 1: sympathize with it, Like watching those Boston Dynamics robots when 586 00:31:08,360 --> 00:31:10,640 Speaker 1: somebody kicks the dog. I know it's just a robot, 587 00:31:10,680 --> 00:31:13,440 Speaker 1: but I don't like that person who kicked it. I'm like, 588 00:31:13,560 --> 00:31:16,680 Speaker 1: that's cruel. How could you do that? Well? In the 589 00:31:16,880 --> 00:31:20,280 Speaker 1: Metal Head, Uh, Basically, the whole thing is kind of 590 00:31:20,280 --> 00:31:25,840 Speaker 1: a post um apocalyptic scenario, killer robot scenario, and the 591 00:31:25,920 --> 00:31:29,760 Speaker 1: killer robot we see is not a juvenile prototype, but 592 00:31:29,760 --> 00:31:34,080 Speaker 1: what you might classify as an adult that the technology 593 00:31:34,600 --> 00:31:37,440 Speaker 1: in a proceed at a perceived level of maturity. So 594 00:31:38,160 --> 00:31:42,400 Speaker 1: the Boston Dynamics Big Dog all grown up into a 595 00:31:42,680 --> 00:31:48,720 Speaker 1: terrifying lethal, quadrupedal killing machine that it overcomes every challenge 596 00:31:48,760 --> 00:31:51,280 Speaker 1: in the natural or man made world that it is 597 00:31:51,320 --> 00:31:54,560 Speaker 1: presented with. Uh. And I think that's that's one of 598 00:31:54,560 --> 00:31:57,560 Speaker 1: the reasons it is terrifying, because it's kind of like, oh, yeah, 599 00:31:57,680 --> 00:32:00,200 Speaker 1: these things are going to grow up. We're for a 600 00:32:00,240 --> 00:32:02,600 Speaker 1: lot of money and effort into making them grow up, 601 00:32:03,040 --> 00:32:05,240 Speaker 1: and uh and and how are we going to relate 602 00:32:05,280 --> 00:32:07,520 Speaker 1: to that technology when it reaches that point? Well, that 603 00:32:07,560 --> 00:32:09,640 Speaker 1: brings us back to something you were saying earlier about 604 00:32:09,680 --> 00:32:12,600 Speaker 1: like the CS Lewis quote, Like clearly our machines and 605 00:32:12,640 --> 00:32:17,120 Speaker 1: their failures I think are becoming much funnier over time. 606 00:32:17,640 --> 00:32:20,080 Speaker 1: Like a steam engine designed to pump water out of 607 00:32:20,080 --> 00:32:22,920 Speaker 1: a coal mine is really not funny when it malfunctions, 608 00:32:22,960 --> 00:32:26,600 Speaker 1: maybe like cut somebody's arm off, like it's it's not hilarious. 609 00:32:27,240 --> 00:32:30,120 Speaker 1: Automatic doors are still not very funny. Maybe a little 610 00:32:30,160 --> 00:32:32,120 Speaker 1: bit funnier, like I was saying, when they're trying to 611 00:32:32,160 --> 00:32:34,480 Speaker 1: close on something over and over, and you know when 612 00:32:34,480 --> 00:32:38,720 Speaker 1: it gets repetitive like that room buzz are funnier. Anything 613 00:32:38,720 --> 00:32:43,520 Speaker 1: attempting to generate real human language or simulate direct human behaviors, 614 00:32:43,560 --> 00:32:47,560 Speaker 1: like say the DARPA challenge bipedal robots. You know when 615 00:32:47,560 --> 00:32:49,800 Speaker 1: you watch them like collapsing in the sand, or like 616 00:32:50,480 --> 00:32:52,640 Speaker 1: when one of them like opens a door and the 617 00:32:52,680 --> 00:32:55,040 Speaker 1: door goes open and then they just crumple in a 618 00:32:55,040 --> 00:32:58,760 Speaker 1: heap on the ground and that kind of thing. It 619 00:32:58,840 --> 00:33:01,320 Speaker 1: is definitely even funny to hear, like machines seem to 620 00:33:01,360 --> 00:33:06,080 Speaker 1: get funnier. The closer they get too resembling real human behaviors, 621 00:33:06,080 --> 00:33:09,040 Speaker 1: the better they simulate. And I wonder, so it's almost 622 00:33:09,040 --> 00:33:11,880 Speaker 1: like there's an uncanny Valley of humor in a way. Yeah, 623 00:33:11,920 --> 00:33:15,240 Speaker 1: I think uncanny valley definitely gets into this territory. I'm 624 00:33:15,280 --> 00:33:19,760 Speaker 1: specifically reminded of Sophia, the smiling humanoid robot. It's becomes 625 00:33:19,760 --> 00:33:22,400 Speaker 1: something of a meme and it's very impressive, like that's 626 00:33:22,400 --> 00:33:25,440 Speaker 1: the thing. At the same time it is amazing, like 627 00:33:25,480 --> 00:33:27,320 Speaker 1: this thing we be worshiped as a god in the 628 00:33:27,360 --> 00:33:30,440 Speaker 1: previous dage that it smiles too fast, smiles too fast, 629 00:33:30,480 --> 00:33:33,160 Speaker 1: and it's just it's not right, and you can't help 630 00:33:33,200 --> 00:33:35,560 Speaker 1: but either look away or laugh. But yeah, I mean, 631 00:33:35,600 --> 00:33:37,760 Speaker 1: I wonder if there there is an element. I don't 632 00:33:37,760 --> 00:33:39,560 Speaker 1: think it's the whole thing, but I do wonder if 633 00:33:39,560 --> 00:33:42,600 Speaker 1: it's there's sort of an undercurrent in machine humor, of 634 00:33:42,640 --> 00:33:46,280 Speaker 1: a kind of nervous laughter at you know, in machines 635 00:33:46,680 --> 00:33:49,960 Speaker 1: potentially becoming more human, more threatening to our sense of 636 00:33:50,040 --> 00:33:54,200 Speaker 1: species specialness, and potentially more threatening to our safety. Like 637 00:33:54,240 --> 00:33:57,240 Speaker 1: we were talking about, you know, I'm reminded of something 638 00:33:57,280 --> 00:33:59,440 Speaker 1: we mentioned fairly often on the show. Actually, ever since 639 00:33:59,440 --> 00:34:01,960 Speaker 1: our conversation with our Scott Baker about this about how 640 00:34:02,320 --> 00:34:07,200 Speaker 1: you don't need terminators or matrix agents or other evil 641 00:34:07,320 --> 00:34:11,960 Speaker 1: super intelligent villains who want to exterminate humans for AI 642 00:34:12,040 --> 00:34:15,120 Speaker 1: to represent a threat to humanity. In fact, I'm much 643 00:34:15,200 --> 00:34:18,640 Speaker 1: more worried about the threat from stupid AI that is 644 00:34:18,760 --> 00:34:21,799 Speaker 1: powerful before it is wise, sort of like the way 645 00:34:21,800 --> 00:34:25,360 Speaker 1: that so many examples we've discussed already just plow ahead 646 00:34:25,880 --> 00:34:29,320 Speaker 1: carrying out their functions without realizing they're going the wrong way, 647 00:34:29,440 --> 00:34:31,840 Speaker 1: or they're they're stuck, or they're not making any sense. 648 00:34:32,520 --> 00:34:36,360 Speaker 1: Uh like attached that kind of logic to practical functions 649 00:34:36,400 --> 00:34:38,839 Speaker 1: that have power over our lives, and there can be 650 00:34:38,920 --> 00:34:42,000 Speaker 1: terrible consequences, which also kind of comes back to children. 651 00:34:42,040 --> 00:34:44,200 Speaker 1: It's like, these are the these are the humans that 652 00:34:44,200 --> 00:34:47,560 Speaker 1: will one day rule the world, and uh and just 653 00:34:47,719 --> 00:34:51,600 Speaker 1: listen to the weird things that keep saying to us, right, Yeah, well, 654 00:34:51,640 --> 00:34:53,360 Speaker 1: I guess there's always kind of a terror at the 655 00:34:53,480 --> 00:34:56,200 Speaker 1: upcoming generations in there because there's always a little bit 656 00:34:56,239 --> 00:34:58,440 Speaker 1: of lack of understanding. Oh yeah, for sure, I mean 657 00:34:58,640 --> 00:35:02,040 Speaker 1: kids are always going to be amusing, but also, yeah, 658 00:35:02,040 --> 00:35:03,920 Speaker 1: you want you wonder, you know, if they're going to 659 00:35:04,000 --> 00:35:06,000 Speaker 1: be able to really grow out of this, and then likewise, 660 00:35:06,000 --> 00:35:09,080 Speaker 1: teenagers are always going to be terrifying to the older generations, 661 00:35:09,360 --> 00:35:13,320 Speaker 1: right well, So bringing it back to neural networks generating text, 662 00:35:13,440 --> 00:35:15,080 Speaker 1: one of the things that I see come up most 663 00:35:15,120 --> 00:35:18,800 Speaker 1: often in like articles about the subject is fears about 664 00:35:19,520 --> 00:35:24,680 Speaker 1: machine generated news articles, like specifically machine generated fake news 665 00:35:24,800 --> 00:35:27,959 Speaker 1: or hoax news articles. Of course, I'm not talking about 666 00:35:27,960 --> 00:35:30,680 Speaker 1: the version of fake news that has become a politicized term. 667 00:35:30,719 --> 00:35:34,839 Speaker 1: I mean like articles that are generated to contain false information, right, 668 00:35:35,080 --> 00:35:40,279 Speaker 1: even intentionally uh created it's a propaganda or misinformation, yeah, 669 00:35:40,560 --> 00:35:43,480 Speaker 1: or just nonsense. And so it shouldn't come as a 670 00:35:43,480 --> 00:35:46,719 Speaker 1: shock that they're already programs that can and do right 671 00:35:46,840 --> 00:35:51,000 Speaker 1: fake articles from AI generated text. The problem is not 672 00:35:51,200 --> 00:35:55,000 Speaker 1: that these programs exist like humans, right, hoax and propaganda 673 00:35:55,080 --> 00:35:57,560 Speaker 1: articles all the time. It's not that we couldn't create 674 00:35:57,600 --> 00:36:01,400 Speaker 1: them without machines. My fear is maybe about volume. Like, 675 00:36:01,480 --> 00:36:05,799 Speaker 1: if the process of putting out hoax nonsense articles and 676 00:36:05,840 --> 00:36:09,600 Speaker 1: stuff can be automated, you can just do so much 677 00:36:09,640 --> 00:36:12,359 Speaker 1: of it. And one of the keys is that it 678 00:36:12,400 --> 00:36:16,040 Speaker 1: doesn't have to be good or convincing to be damaging. 679 00:36:16,400 --> 00:36:20,359 Speaker 1: If you simply flood the zone of people's Internet experience 680 00:36:20,360 --> 00:36:24,480 Speaker 1: with obvious nonsense and trash, they don't have to believe it. 681 00:36:24,480 --> 00:36:26,640 Speaker 1: It can just do lots of damage to a culture 682 00:36:27,280 --> 00:36:30,920 Speaker 1: simply by flooding out everything else, right, I mean you 683 00:36:30,920 --> 00:36:33,600 Speaker 1: can you can almost imagine a future generation looking back 684 00:36:33,640 --> 00:36:35,920 Speaker 1: at a time like that and saying, well, you know, 685 00:36:36,080 --> 00:36:38,440 Speaker 1: it's really difficult to know exactly what they've they felt 686 00:36:38,440 --> 00:36:42,600 Speaker 1: in thought because of all the nonsense that was created, say, 687 00:36:42,640 --> 00:36:47,440 Speaker 1: not not just textual but video nonsense, photoshop nonsense like 688 00:36:48,239 --> 00:36:50,840 Speaker 1: wh where are the real people and their actual concerns 689 00:36:50,880 --> 00:36:53,480 Speaker 1: and all of this. Yeah, I really worry about the 690 00:36:53,480 --> 00:36:58,600 Speaker 1: the potential for dumb, context ignorant algorithms that seemed perfectly 691 00:36:58,640 --> 00:37:01,719 Speaker 1: capable of steering user is intellectably into more and more 692 00:37:01,760 --> 00:37:05,279 Speaker 1: horrible in mind destroying content on platforms like YouTube, you know, 693 00:37:05,520 --> 00:37:10,400 Speaker 1: and YouTube content serving algorithms that's already the world destroying AI. 694 00:37:10,520 --> 00:37:12,600 Speaker 1: But here's the thing, Joe, what if it's all funny? 695 00:37:12,640 --> 00:37:15,280 Speaker 1: What if it's all really funny? Well, in some cases 696 00:37:15,320 --> 00:37:18,680 Speaker 1: it is like top shelf ClickHole funny, Then then I 697 00:37:18,719 --> 00:37:21,759 Speaker 1: don't know, maybe them all in for the age of unreasoned. 698 00:37:22,040 --> 00:37:24,760 Speaker 1: I worry about this more than the kind of mind 699 00:37:24,840 --> 00:37:27,440 Speaker 1: ravaging dumb ai, way more than I worry about the 700 00:37:27,440 --> 00:37:30,680 Speaker 1: great basilisk I agree with you there. All right, Well, 701 00:37:30,680 --> 00:37:32,680 Speaker 1: well I want to bring it back to lighter territory here. 702 00:37:33,040 --> 00:37:37,080 Speaker 1: Uh the joke telling capabilities of Siri on an iPhone. Now, 703 00:37:37,160 --> 00:37:40,080 Speaker 1: imagine anyone out there who has an iPhone and probably 704 00:37:40,480 --> 00:37:43,120 Speaker 1: there's some degree of this in any kind of you know, 705 00:37:43,280 --> 00:37:47,279 Speaker 1: voice interface system, Alexa or or what have you. But 706 00:37:47,480 --> 00:37:49,279 Speaker 1: when you when you ask Serri to tell you a 707 00:37:49,360 --> 00:37:51,920 Speaker 1: knockdot joke, she will tell you a knockdoc joke, and 708 00:37:51,960 --> 00:37:55,000 Speaker 1: some of them are pretty funny. Um, and then she'll 709 00:37:55,080 --> 00:37:56,920 Speaker 1: you you ask her other things so they'll be a 710 00:37:56,960 --> 00:37:59,239 Speaker 1: hilarious response. Like if you ask her about how nine 711 00:37:59,239 --> 00:38:02,359 Speaker 1: thousand she has a funny response that's you know, preprogrammed. Again, 712 00:38:02,400 --> 00:38:04,840 Speaker 1: it's it's something that somebody wrote and created. This is 713 00:38:04,960 --> 00:38:08,200 Speaker 1: human human augmented humor. Yeah. But one of my favorites 714 00:38:08,920 --> 00:38:12,080 Speaker 1: is is one that Siri told me where clearly it 715 00:38:12,120 --> 00:38:14,560 Speaker 1: was there was an error that took place, and I'm 716 00:38:14,560 --> 00:38:18,359 Speaker 1: not perfectly replicating it here, but it was something like this, uh, 717 00:38:18,560 --> 00:38:22,640 Speaker 1: knock knock. I say who's there? And then Siri says Sophia, 718 00:38:23,160 --> 00:38:26,320 Speaker 1: And I say Sophia, who, and then she says, I'm sorry, 719 00:38:26,320 --> 00:38:29,640 Speaker 1: there's nobody in your call list or your contact listen Sophia. 720 00:38:30,239 --> 00:38:32,080 Speaker 1: And so I never get to find out what the 721 00:38:32,120 --> 00:38:36,239 Speaker 1: rest of that joke is because in asking, in responding 722 00:38:36,280 --> 00:38:38,799 Speaker 1: to the knock knock joke, she thinks I'm trying to 723 00:38:38,800 --> 00:38:43,080 Speaker 1: make a call. And so that that makes me laugh 724 00:38:43,120 --> 00:38:45,239 Speaker 1: every time that I've heard it. That's really good. It's 725 00:38:45,280 --> 00:38:47,759 Speaker 1: like a performance art kind of joke. Yeah. So it's 726 00:38:47,800 --> 00:38:50,640 Speaker 1: it's trying to be, you know, actual funny joke telling, 727 00:38:50,680 --> 00:38:53,440 Speaker 1: but then it gets into this machine error level of 728 00:38:53,520 --> 00:38:57,400 Speaker 1: joke telling, and it's probably the more hilarious outcome of 729 00:38:57,440 --> 00:38:59,879 Speaker 1: the two. There is no one called big Cat, big Cat, 730 00:39:00,040 --> 00:39:03,080 Speaker 1: big Cat, big Cat in your address, but there should 731 00:39:03,080 --> 00:39:06,000 Speaker 1: be that I should create that. All right, Well, there 732 00:39:06,040 --> 00:39:09,080 Speaker 1: you have it. Um, I feel like we have completely 733 00:39:09,080 --> 00:39:14,480 Speaker 1: explained humor and artificial intelligence. We hope you never find 734 00:39:14,520 --> 00:39:19,279 Speaker 1: anything funny again. Uh yeah, as so. As always, if 735 00:39:19,280 --> 00:39:21,240 Speaker 1: you want more content, you want more episodes of stuff 736 00:39:21,239 --> 00:39:23,120 Speaker 1: to blow your mind, head on over to Stuff to 737 00:39:23,120 --> 00:39:25,200 Speaker 1: Blow your Mind dot com. That is the mother ship. 738 00:39:25,239 --> 00:39:26,920 Speaker 1: That's where we'll find all the episodes. That's where we'll 739 00:39:26,920 --> 00:39:29,200 Speaker 1: find links out to social media accounts. That's where we'll 740 00:39:29,200 --> 00:39:32,040 Speaker 1: find a link to our t shirt store where you 741 00:39:32,080 --> 00:39:35,719 Speaker 1: can get the all Hail the Great Basilist t shirt. Uh. 742 00:39:35,840 --> 00:39:37,960 Speaker 1: So you can. You can have a little fun, have 743 00:39:38,040 --> 00:39:40,600 Speaker 1: a little uh, find a little humor in the idea 744 00:39:40,640 --> 00:39:44,840 Speaker 1: of future of hyper powerful AI Overlord scoring the machines. 745 00:39:45,080 --> 00:39:47,160 Speaker 1: That's right, it's a fun way to support the show. 746 00:39:47,360 --> 00:39:49,120 Speaker 1: You can also support us to the best way to 747 00:39:49,120 --> 00:39:51,440 Speaker 1: support us is just to rate and review us wherever 748 00:39:51,520 --> 00:39:53,840 Speaker 1: you have the power to do so. Like whatever platform 749 00:39:53,880 --> 00:39:56,680 Speaker 1: you're using to listen to podcasts, make sure you've thrown 750 00:39:56,719 --> 00:39:58,680 Speaker 1: a few stars in a nice review our way. Hey, 751 00:39:58,800 --> 00:40:01,919 Speaker 1: you subscribe to in Engine yet If you haven't, that's 752 00:40:01,920 --> 00:40:04,520 Speaker 1: our other podcast. We bring the same kind of approach. 753 00:40:04,560 --> 00:40:06,000 Speaker 1: We bring on stuff to blow your mind, but we 754 00:40:06,040 --> 00:40:09,160 Speaker 1: talk about inventions from history. If you like this show, 755 00:40:09,200 --> 00:40:10,840 Speaker 1: we're pretty sure you'll like that one too, so you 756 00:40:10,840 --> 00:40:13,680 Speaker 1: should go check it out and subscribe. Yeah, two whole 757 00:40:13,680 --> 00:40:16,320 Speaker 1: episodes on toilets, for instance. Oh man, that was fun. 758 00:40:16,440 --> 00:40:19,160 Speaker 1: Never look at a toilet the same way way again. Honestly, 759 00:40:19,239 --> 00:40:21,919 Speaker 1: I don't I have way more appreciation of toilet kind 760 00:40:22,000 --> 00:40:24,520 Speaker 1: than I did before. And there's an example technology that 761 00:40:24,640 --> 00:40:28,480 Speaker 1: is inherently funny and inherently good. Yeah, it's very good, 762 00:40:28,640 --> 00:40:32,160 Speaker 1: very important. Anyway, huge thanks to our excellent audio producers 763 00:40:32,200 --> 00:40:35,120 Speaker 1: Alex Williams and Tor Harrison. If you would like to 764 00:40:35,800 --> 00:40:38,279 Speaker 1: reach out to us, to send us an email and 765 00:40:38,360 --> 00:40:40,720 Speaker 1: let us know what you think about the show, feedback 766 00:40:40,760 --> 00:40:43,920 Speaker 1: on this episode, or any other suggestions for future topics, 767 00:40:44,239 --> 00:40:46,000 Speaker 1: or just let us know maybe how you found out 768 00:40:46,000 --> 00:40:47,960 Speaker 1: about us where you listen from that kind of stuff. 769 00:40:48,160 --> 00:40:50,640 Speaker 1: You can email us at blow the Mind at how 770 00:40:50,680 --> 00:41:03,800 Speaker 1: stuff works dot com for more on this and thousands 771 00:41:03,800 --> 00:41:28,960 Speaker 1: of other topics. Is it how stuff works dot com