1 00:00:05,720 --> 00:00:07,640 Speaker 1: Hey, welcome to Stuff to Blow your Mind. My name 2 00:00:07,680 --> 00:00:10,520 Speaker 1: is Robert Lamb and I'm Joe McCormick, and it's Saturday. 3 00:00:10,720 --> 00:00:13,480 Speaker 1: Time for a vault episode. This one originally published on 4 00:00:13,560 --> 00:00:17,640 Speaker 1: March nineteen, and it's part two of the part one 5 00:00:17,720 --> 00:00:19,960 Speaker 1: we were in last Saturday. This is flatea sex mock 6 00:00:20,040 --> 00:00:23,759 Speaker 1: in a part two about why it's so funny when machines, robots, 7 00:00:23,760 --> 00:00:27,360 Speaker 1: and artificial intelligence falls flat on its face. All right, 8 00:00:27,480 --> 00:00:33,120 Speaker 1: let's do it. Welcome to Stuff to Blow your Mind 9 00:00:33,320 --> 00:00:42,200 Speaker 1: from how Stuff Works dot Com. Hey, welcome to Stuff 10 00:00:42,240 --> 00:00:44,280 Speaker 1: to Blow your Mind. My name is Robert Lamb and 11 00:00:44,320 --> 00:00:46,519 Speaker 1: I'm Joe McCormick, and we're back with part two of 12 00:00:46,560 --> 00:00:50,080 Speaker 1: our discussion of the plate to sex mac and I 13 00:00:50,080 --> 00:00:52,839 Speaker 1: think that's what we're gonna call it, the comedy of 14 00:00:52,960 --> 00:00:56,280 Speaker 1: errors that exist in the machine and artificial intelligence world. 15 00:00:56,400 --> 00:00:58,080 Speaker 1: That's right. We were going to do it as one episode, 16 00:00:58,200 --> 00:00:59,600 Speaker 1: but it just went too long. Had to break it 17 00:00:59,680 --> 00:01:02,440 Speaker 1: up into two. But it has everything. It has uh, 18 00:01:02,600 --> 00:01:06,240 Speaker 1: it has humor, it has theories of humor, it has 19 00:01:06,920 --> 00:01:10,880 Speaker 1: killer robots, references to RoboCop, everything you could ask for. 20 00:01:11,080 --> 00:01:14,360 Speaker 1: One of my favorite things explaining a joke to death, yes, 21 00:01:15,120 --> 00:01:19,160 Speaker 1: and then yes yeah. Yeah. Basically this is a lot 22 00:01:19,160 --> 00:01:21,640 Speaker 1: of joke explaining, but I think by the end of it, 23 00:01:21,720 --> 00:01:24,400 Speaker 1: everyone will still retain their ability to laugh. All right, 24 00:01:24,440 --> 00:01:29,240 Speaker 1: So I thinking about what's so funny about machine failure? Uh? 25 00:01:29,280 --> 00:01:32,120 Speaker 1: And and even machine success along a certain you know, 26 00:01:32,240 --> 00:01:36,120 Speaker 1: parameter of distance from what from what it's ultimate level 27 00:01:36,160 --> 00:01:39,080 Speaker 1: of success would be, you know, AI that's sort of succeeding, 28 00:01:39,120 --> 00:01:43,319 Speaker 1: but still isn't really there. Um. I guess it's worthwhile 29 00:01:43,400 --> 00:01:46,000 Speaker 1: to look at what are some of the main theories 30 00:01:46,080 --> 00:01:48,440 Speaker 1: out there about what humor is, Like, why do we 31 00:01:48,640 --> 00:01:52,200 Speaker 1: find anything funny not just machines? Yeah, because it becomes 32 00:01:52,200 --> 00:01:55,720 Speaker 1: increasingly difficult to really uh nail it down, you know, 33 00:01:55,840 --> 00:01:57,760 Speaker 1: you come back to that whole idea of it's funny 34 00:01:57,800 --> 00:02:01,040 Speaker 1: because it's funny or you know what when you see it. Uh. 35 00:02:01,360 --> 00:02:03,160 Speaker 1: This topic has come up a few times on the 36 00:02:03,160 --> 00:02:07,520 Speaker 1: show before, um, most recently two thousands, seventeens laughing during 37 00:02:07,560 --> 00:02:10,399 Speaker 1: horror movies. That was when Christian was on the show 38 00:02:10,400 --> 00:02:13,079 Speaker 1: and we talked about, you know, what is it about 39 00:02:13,440 --> 00:02:17,240 Speaker 1: horror movies like frightening, terrifying films that that elicits laughter 40 00:02:17,400 --> 00:02:19,519 Speaker 1: from us? And then there were a few other ones 41 00:02:19,560 --> 00:02:21,799 Speaker 1: in the past, the healing power of laughter, the killing joke, 42 00:02:21,960 --> 00:02:24,200 Speaker 1: funny or Die. These are all episodes of stuff to 43 00:02:24,200 --> 00:02:26,320 Speaker 1: blow your mind. You can you can check out in 44 00:02:26,480 --> 00:02:29,440 Speaker 1: the vault if you so desire. Yeah, and so what 45 00:02:29,880 --> 00:02:31,840 Speaker 1: if you go and check those out, I'm sure you 46 00:02:32,440 --> 00:02:35,200 Speaker 1: as you'll probably found before. There's no one theory of 47 00:02:35,280 --> 00:02:38,360 Speaker 1: human right and nobody agrees, But there's sort of a 48 00:02:38,440 --> 00:02:41,840 Speaker 1: host of competing theories that I would say aren't even 49 00:02:41,919 --> 00:02:46,160 Speaker 1: always totally contradicting of one another. They they sort of 50 00:02:46,320 --> 00:02:51,200 Speaker 1: partially overlap and partially contradict one another. Right, Yeah, there's 51 00:02:51,200 --> 00:02:54,000 Speaker 1: not really a theory of everything per se, but like 52 00:02:54,080 --> 00:02:56,600 Speaker 1: each one feels a little bit right, like each theory 53 00:02:56,760 --> 00:03:01,799 Speaker 1: is is kind of fondling the elephant exactly. Uh So, 54 00:03:02,080 --> 00:03:03,720 Speaker 1: a brief runthrough of a few of the top wing. 55 00:03:03,840 --> 00:03:05,880 Speaker 1: There's no way to explore all the theories of humor, 56 00:03:05,919 --> 00:03:07,920 Speaker 1: but a few of the most commonly cited and most 57 00:03:07,919 --> 00:03:11,520 Speaker 1: popular ones. One would be the superiority theory, and this 58 00:03:11,600 --> 00:03:14,400 Speaker 1: is propounded in some classical works, like in the works 59 00:03:14,400 --> 00:03:17,040 Speaker 1: of Plato and Aristotle. This one is actually is kind 60 00:03:17,040 --> 00:03:20,080 Speaker 1: of nasty, But sometimes I guess humor is kind of nasty. 61 00:03:20,480 --> 00:03:23,679 Speaker 1: It proposes that we laugh when we notice someone is 62 00:03:23,760 --> 00:03:26,720 Speaker 1: less fortunate than us in one way or another, and 63 00:03:26,760 --> 00:03:30,120 Speaker 1: the laughter comes from our feeling that we occupy a 64 00:03:30,120 --> 00:03:32,640 Speaker 1: place of superiority. We sort of deploy it as a 65 00:03:32,680 --> 00:03:37,120 Speaker 1: form of scorn on somebody else. And Plato and his 66 00:03:37,400 --> 00:03:40,840 Speaker 1: Philibus dialogue, which is discussing the nature of pleasure and 67 00:03:40,880 --> 00:03:43,800 Speaker 1: different kinds of pleasure, like why pleasures of the mind 68 00:03:43,960 --> 00:03:47,240 Speaker 1: might be superior to pleasures of the flesh, Plato has 69 00:03:47,240 --> 00:03:50,520 Speaker 1: Socrates claim that we laugh at people who do not 70 00:03:50,720 --> 00:03:54,400 Speaker 1: recognize their own misfortune, for example, when people are stupid 71 00:03:54,480 --> 00:03:57,680 Speaker 1: but think themselves brilliant, or when people are ugly but 72 00:03:57,840 --> 00:04:01,480 Speaker 1: think themselves very handsome. And I would say this clearly 73 00:04:01,520 --> 00:04:04,040 Speaker 1: doesn't cover all types of humor, Like, you know, what 74 00:04:04,120 --> 00:04:07,000 Speaker 1: about self deprecating humor when you can laugh at yourself, 75 00:04:07,160 --> 00:04:12,440 Speaker 1: But there's something there that is clearly present in some humor. Yeah, well, 76 00:04:12,440 --> 00:04:14,640 Speaker 1: you know, when it comes to self deprecating humor and 77 00:04:15,000 --> 00:04:16,960 Speaker 1: laughing at yourself, I think it does make sense when 78 00:04:16,960 --> 00:04:20,520 Speaker 1: you consider our abilities to sometimes step outside of ourselves 79 00:04:20,520 --> 00:04:23,240 Speaker 1: and see ourselves as a character in a story. Sort 80 00:04:23,240 --> 00:04:27,400 Speaker 1: of the infectious nature of narrative there, but then also 81 00:04:27,480 --> 00:04:29,559 Speaker 1: in the way that we use theory of mind way 82 00:04:29,560 --> 00:04:32,360 Speaker 1: too much to try and imagine how others see us. 83 00:04:32,600 --> 00:04:34,640 Speaker 1: So maybe, like, if you're trying to roll with this theory, 84 00:04:34,680 --> 00:04:37,640 Speaker 1: you'd say that self deprecating humor is almost when we 85 00:04:37,880 --> 00:04:41,839 Speaker 1: pretend that we are ourselves someone else and you like 86 00:04:41,920 --> 00:04:46,080 Speaker 1: step step back and you scorn a different version of yourself. Yeah, 87 00:04:46,120 --> 00:04:49,279 Speaker 1: basically like or you're just kind of imagining how scornful 88 00:04:49,320 --> 00:04:52,120 Speaker 1: other people are being to you because of something you 89 00:04:52,400 --> 00:04:56,279 Speaker 1: did or said or thought. Yeah, um, I mean another 90 00:04:56,320 --> 00:04:58,080 Speaker 1: thing I would just say is that unless you're a 91 00:04:58,080 --> 00:05:00,600 Speaker 1: horrible person, and maybe you know, Plato and Style were 92 00:05:00,760 --> 00:05:03,960 Speaker 1: in some ways very smart but also very horrible people, 93 00:05:05,120 --> 00:05:07,880 Speaker 1: unless you're a really bad person, you don't find most 94 00:05:08,120 --> 00:05:11,680 Speaker 1: types of misfortunes of other people funny. I mean, I 95 00:05:11,720 --> 00:05:14,840 Speaker 1: do see a certain distinction along Plato's lands in the Philibus, 96 00:05:14,920 --> 00:05:19,200 Speaker 1: where like a person just failing to do things that 97 00:05:19,279 --> 00:05:22,440 Speaker 1: you could succeed at is generally not very funny. Like 98 00:05:22,920 --> 00:05:25,359 Speaker 1: somebody trying to solve a math problem you could solve 99 00:05:25,400 --> 00:05:28,719 Speaker 1: and they can't do it, that's not funny. But like 100 00:05:28,760 --> 00:05:31,200 Speaker 1: if a man proclaims himself to be one of the 101 00:05:31,240 --> 00:05:34,159 Speaker 1: greatest brains of all time and then is making basic 102 00:05:34,320 --> 00:05:37,000 Speaker 1: errors of logic and math. That's usually funny. Yeah, I 103 00:05:37,040 --> 00:05:38,560 Speaker 1: think a lot of it hinges on just you know, 104 00:05:38,600 --> 00:05:40,919 Speaker 1: what are the stakes and what sort of misfortune is 105 00:05:40,960 --> 00:05:43,760 Speaker 1: taking place? Like Another sort of example of this is 106 00:05:43,800 --> 00:05:48,040 Speaker 1: when someone thinks they are refined about something, uh, and 107 00:05:48,279 --> 00:05:50,560 Speaker 1: maybe they're a little snobvish about it, but but it 108 00:05:50,560 --> 00:05:52,480 Speaker 1: turns out their tastes are not quite as refined as 109 00:05:52,480 --> 00:05:55,400 Speaker 1: they thought. Um. I think there was an episode of 110 00:05:55,440 --> 00:05:59,360 Speaker 1: Threes Company back you know in the day, in which 111 00:05:59,560 --> 00:06:02,719 Speaker 1: Don character is ordering like a fine scotch at a 112 00:06:02,720 --> 00:06:04,520 Speaker 1: bar and he's really talking it up like he knows 113 00:06:04,520 --> 00:06:06,680 Speaker 1: what he's talking about, exactly what kind of scotch he wants, 114 00:06:06,680 --> 00:06:09,160 Speaker 1: and then when the bartender finally serves it to him, 115 00:06:09,279 --> 00:06:11,320 Speaker 1: he requests that the rest of the glass be filled 116 00:06:11,360 --> 00:06:15,000 Speaker 1: up with root beer. You know, it's like like that's 117 00:06:15,040 --> 00:06:17,440 Speaker 1: that's so that's hilarious because he turns out he's not 118 00:06:17,480 --> 00:06:19,719 Speaker 1: as as refined as he thought. But then it's also 119 00:06:20,000 --> 00:06:23,880 Speaker 1: like we were being snobbish in making that judgment. Uh, 120 00:06:23,920 --> 00:06:26,680 Speaker 1: And it's and that's always kind of a dick move right, 121 00:06:26,720 --> 00:06:29,359 Speaker 1: because in anything like whatever your thing is, that you 122 00:06:29,360 --> 00:06:32,160 Speaker 1: feel like you're refined and be at food or drinks 123 00:06:32,279 --> 00:06:35,160 Speaker 1: or film or literature, there was a point in your 124 00:06:35,200 --> 00:06:37,599 Speaker 1: life when you were not when you were the person 125 00:06:37,640 --> 00:06:40,120 Speaker 1: that was the subject of scorn, And you know, ultimately 126 00:06:40,160 --> 00:06:42,760 Speaker 1: we're being fair. You should celebrate that they are at 127 00:06:42,760 --> 00:06:45,200 Speaker 1: all interested in the in this thing at all, and 128 00:06:45,240 --> 00:06:48,600 Speaker 1: that they are on hopefully on some sort of the 129 00:06:48,640 --> 00:06:52,279 Speaker 1: same journey that you are. But instead we often laugh 130 00:06:52,320 --> 00:06:54,560 Speaker 1: and said, can you believe that guy just put root 131 00:06:54,600 --> 00:06:59,040 Speaker 1: beer all in that scotch. I think that's a really 132 00:06:59,040 --> 00:07:01,440 Speaker 1: good point. So I don't know. I would say I 133 00:07:01,480 --> 00:07:04,680 Speaker 1: definitely see something going on here that there are definitely 134 00:07:04,760 --> 00:07:06,599 Speaker 1: elements of this in humor, but I don't think it 135 00:07:06,640 --> 00:07:10,440 Speaker 1: explains all humor. I don't know if maybe maybe maybe not. 136 00:07:10,520 --> 00:07:12,000 Speaker 1: I don't know if it's a good fit for why 137 00:07:12,080 --> 00:07:15,640 Speaker 1: machines are funny, because obviously machines aren't people exactly, but 138 00:07:15,720 --> 00:07:18,160 Speaker 1: maybe we sort of see them as people when we 139 00:07:18,240 --> 00:07:20,720 Speaker 1: think they're funny. Yeah, I think if we If you 140 00:07:20,760 --> 00:07:24,440 Speaker 1: factor in the actual and or perceived abilities of AI 141 00:07:24,520 --> 00:07:28,000 Speaker 1: and robots, either either what they can actually do or 142 00:07:28,160 --> 00:07:30,880 Speaker 1: more I think to the point what our science fiction 143 00:07:30,960 --> 00:07:35,080 Speaker 1: and our futurist scenarios have proposed that they will do 144 00:07:35,320 --> 00:07:38,040 Speaker 1: or do one day, because then we end up with 145 00:07:38,040 --> 00:07:40,960 Speaker 1: this situation where like we watch our room but do 146 00:07:41,040 --> 00:07:44,560 Speaker 1: something stupid, and there's it's hilarious because like, ha, you're 147 00:07:44,600 --> 00:07:47,040 Speaker 1: never going to terminate or me um if you can't 148 00:07:47,040 --> 00:07:49,560 Speaker 1: even you can't even deal with the h with this 149 00:07:49,680 --> 00:07:53,400 Speaker 1: rug or this pile of cat vomit. Well, actually, though, 150 00:07:53,440 --> 00:07:56,440 Speaker 1: I would say another reason this does kind of connect 151 00:07:56,520 --> 00:07:58,720 Speaker 1: is it does kind of connect to Plato's thing about 152 00:07:58,760 --> 00:08:02,680 Speaker 1: laughing atself ignorance because one of the funniest things that 153 00:08:02,800 --> 00:08:04,840 Speaker 1: I sort of identified earlier about like the D two 154 00:08:04,840 --> 00:08:07,320 Speaker 1: O nine scene and all that, one of the funniest 155 00:08:07,320 --> 00:08:10,120 Speaker 1: things about the ways that machines fail is the way 156 00:08:10,160 --> 00:08:14,200 Speaker 1: that they are just so completely oblivious to their own shortcomings, 157 00:08:14,240 --> 00:08:16,600 Speaker 1: the way they just uh, the way I think of 158 00:08:16,600 --> 00:08:20,200 Speaker 1: it is that they fail and then plow straight ahead. 159 00:08:20,400 --> 00:08:23,560 Speaker 1: You know they have they have done something crucially wrong, 160 00:08:23,640 --> 00:08:26,640 Speaker 1: and they do not appreciate this fact. All right, let's 161 00:08:26,680 --> 00:08:29,160 Speaker 1: keep Roland. What are some other theories we can discuss? Okay, 162 00:08:29,240 --> 00:08:32,160 Speaker 1: next one would be like the nervous energy release theory, 163 00:08:32,240 --> 00:08:34,439 Speaker 1: and this is not surprisingly at all to take that 164 00:08:34,520 --> 00:08:37,880 Speaker 1: was popular with Freudians. Under this model, laughter is sort 165 00:08:37,920 --> 00:08:41,800 Speaker 1: of a pleasurable release of built up psychic tension caused 166 00:08:41,840 --> 00:08:44,800 Speaker 1: by fear or apprehension. Uh. And there's just a certain 167 00:08:44,880 --> 00:08:46,680 Speaker 1: kind of logic to this, right in the way that's 168 00:08:46,679 --> 00:08:50,680 Speaker 1: a good Comedians repeatedly build tension and then dissipated in 169 00:08:50,800 --> 00:08:54,040 Speaker 1: various ways. I bet this also goes with the laughing 170 00:08:54,120 --> 00:08:57,080 Speaker 1: during horror movies thing, you know, Yeah, for sure, like 171 00:08:57,160 --> 00:08:59,680 Speaker 1: you you get your tension built up when there's something 172 00:08:59,720 --> 00:09:01,840 Speaker 1: scared he's about to happen, and then after it's over 173 00:09:02,000 --> 00:09:04,640 Speaker 1: you you release the tension and you can laugh. Yeah, 174 00:09:04,720 --> 00:09:08,600 Speaker 1: certainly with with comedians who really leaned into like the 175 00:09:08,640 --> 00:09:11,200 Speaker 1: awkwardness and the tension, like say like an Andy Kaufman, 176 00:09:11,480 --> 00:09:14,520 Speaker 1: you know where their whole their whole bits or if 177 00:09:14,559 --> 00:09:16,760 Speaker 1: you want to call them bits, where it's really just 178 00:09:16,880 --> 00:09:20,640 Speaker 1: making everyone uncomfortable. It's not even about punchlines. It's about 179 00:09:20,640 --> 00:09:24,280 Speaker 1: just creating this this tension that at some point has 180 00:09:24,320 --> 00:09:25,720 Speaker 1: to be relief. Like at some point all you can 181 00:09:25,720 --> 00:09:28,600 Speaker 1: do is laugh. Yeah, So there's something there. It clearly 182 00:09:28,679 --> 00:09:31,040 Speaker 1: doesn't account for everything that's funny you know, it doesn't 183 00:09:31,040 --> 00:09:33,520 Speaker 1: account for puns and all that kind of thing. Uh It, 184 00:09:34,040 --> 00:09:35,880 Speaker 1: I don't know if I can see a way that 185 00:09:35,920 --> 00:09:40,240 Speaker 1: it really fits with why technology failing is all that funny. No, Yeah, 186 00:09:40,240 --> 00:09:42,439 Speaker 1: I don't think. I don't think there's anything particularly insightful 187 00:09:42,600 --> 00:09:45,800 Speaker 1: about this theory regarding what we're talking about here today. Okay, 188 00:09:45,800 --> 00:09:50,640 Speaker 1: here's another one. How about the adaptation, uh to signal play, 189 00:09:50,679 --> 00:09:53,720 Speaker 1: So that laughter would be an evolutionary adaptation that occurs 190 00:09:53,800 --> 00:09:58,160 Speaker 1: when we're engaged in pretend aggression during play behaviors. It 191 00:09:58,200 --> 00:10:01,319 Speaker 1: occurs as a signal to help every body involved understand 192 00:10:01,360 --> 00:10:04,720 Speaker 1: the fact the behaviors like chasing and wrestling and stuff 193 00:10:04,760 --> 00:10:08,240 Speaker 1: are meant as play rather than as genuine aggression or harm. Yeah, 194 00:10:08,280 --> 00:10:11,640 Speaker 1: this one I think is important to mention here, if 195 00:10:11,720 --> 00:10:13,680 Speaker 1: only for the reason that it touches on the social 196 00:10:13,800 --> 00:10:18,719 Speaker 1: nature of laughter, that that laughter is also about communicating 197 00:10:18,760 --> 00:10:23,679 Speaker 1: with other people regarding various threats, etcetera. Um. It's also 198 00:10:23,760 --> 00:10:26,640 Speaker 1: I wonder if this is one where our storytelling has 199 00:10:26,679 --> 00:10:28,720 Speaker 1: kind of kind of led us astray as well, though, 200 00:10:29,080 --> 00:10:35,240 Speaker 1: because how many um, individuals that actually intend as harm 201 00:10:35,280 --> 00:10:40,600 Speaker 1: are laughing hysterically or sardonically like I'm sure it happens. 202 00:10:40,880 --> 00:10:43,520 Speaker 1: I mean, and maybe one or two scenarios even come 203 00:10:43,559 --> 00:10:46,960 Speaker 1: to mind where someone was did something horrible and violent 204 00:10:47,000 --> 00:10:49,480 Speaker 1: and it was seen laughing. But I don't feel like 205 00:10:49,520 --> 00:10:52,880 Speaker 1: it probably occurs anywhere as near as often as it 206 00:10:52,920 --> 00:10:56,679 Speaker 1: does in movies where villains are constantly laughing. Be it 207 00:10:56,880 --> 00:11:00,000 Speaker 1: you know, an extreme example like the Joker, or or 208 00:11:00,120 --> 00:11:03,240 Speaker 1: just any you know, you know sardonic villain who just 209 00:11:03,280 --> 00:11:07,800 Speaker 1: doing maniacally laughs while attempting to destroy the world. Uh yeah, 210 00:11:07,840 --> 00:11:10,199 Speaker 1: I mean I would say this probably does go along 211 00:11:10,200 --> 00:11:13,240 Speaker 1: with the theory then. I mean, if it if somebody 212 00:11:13,360 --> 00:11:15,960 Speaker 1: is laughing while they're actually attempting harm, they're you know, 213 00:11:16,000 --> 00:11:19,480 Speaker 1: their victim is not laughing, so like, So yeah, I 214 00:11:19,720 --> 00:11:21,600 Speaker 1: think this goes along, they're like, And if they are, 215 00:11:21,760 --> 00:11:24,560 Speaker 1: then it's like that scene in the original um what 216 00:11:24,600 --> 00:11:27,320 Speaker 1: was a Little Shop of Horrors? Yeah, where or maybe 217 00:11:27,320 --> 00:11:29,840 Speaker 1: it was in the remake as well too, where the uh, 218 00:11:30,240 --> 00:11:33,320 Speaker 1: the the the the the evil dentist is going to 219 00:11:33,360 --> 00:11:35,240 Speaker 1: work on this person and this person just wants it, 220 00:11:35,280 --> 00:11:38,120 Speaker 1: they want the pain, and it just totally messes up 221 00:11:38,160 --> 00:11:40,400 Speaker 1: his his vibe. Yeah, I haven't thought how it would 222 00:11:40,400 --> 00:11:43,160 Speaker 1: accommodate the idea of like villains laughing while they do 223 00:11:43,200 --> 00:11:44,520 Speaker 1: what they do. But I mean, I think this is 224 00:11:44,559 --> 00:11:47,960 Speaker 1: clearly true in some cases that people laugh during mock 225 00:11:48,080 --> 00:11:51,720 Speaker 1: aggressive play behaviors, that dogs wag their tails during mock 226 00:11:51,760 --> 00:11:55,080 Speaker 1: aggressive play behaviors. It's like, you know, they're growling and 227 00:11:55,120 --> 00:11:57,840 Speaker 1: snarling and tumbling, but you can tell they're not really 228 00:11:57,880 --> 00:12:00,200 Speaker 1: fighting because their tails are wagging. And this is a 229 00:12:00,280 --> 00:12:02,960 Speaker 1: nice lead into one of one of my favorite theories, 230 00:12:03,000 --> 00:12:04,680 Speaker 1: and this is one that we discussed on the show 231 00:12:05,880 --> 00:12:09,000 Speaker 1: before in the past, and that's the benign violation theory. Yeah, 232 00:12:09,280 --> 00:12:11,880 Speaker 1: and this theory is very popular now. This theory proposes 233 00:12:11,920 --> 00:12:16,080 Speaker 1: that humor occurs when one we perceive a way in 234 00:12:16,120 --> 00:12:19,360 Speaker 1: which rules or norms of some kind are broken. And 235 00:12:19,360 --> 00:12:21,679 Speaker 1: these rules can be any, you know, all kinds of things. 236 00:12:21,720 --> 00:12:26,000 Speaker 1: They can be grammatical rules, they could be biological classifications, 237 00:12:26,040 --> 00:12:28,480 Speaker 1: that can be the rules of making sense, they can 238 00:12:28,559 --> 00:12:33,040 Speaker 1: be moral norms. Uh. And then second, we recognize that 239 00:12:33,080 --> 00:12:36,320 Speaker 1: there has been a violation, but it's not harmful, it's 240 00:12:36,400 --> 00:12:40,040 Speaker 1: benign in nature. And then third we see this contradiction 241 00:12:40,120 --> 00:12:42,760 Speaker 1: between the fact that there's a violation and the fact 242 00:12:42,840 --> 00:12:46,720 Speaker 1: that it's harmless, and that contradiction triggers humor. Like we said, 243 00:12:46,720 --> 00:12:50,160 Speaker 1: this one's very popular. It's supported by some empirical research. 244 00:12:50,240 --> 00:12:52,959 Speaker 1: Just one example of research and support that I came 245 00:12:53,000 --> 00:12:55,720 Speaker 1: across as a two thousand ten study in Psychological Science 246 00:12:55,760 --> 00:12:59,960 Speaker 1: by McGraw and Warren called benign violations making a moral 247 00:13:00,080 --> 00:13:03,040 Speaker 1: behavior funny and too so to just cite one example 248 00:13:03,480 --> 00:13:06,760 Speaker 1: that they talk about within that study quote, people who 249 00:13:06,760 --> 00:13:10,600 Speaker 1: are more weakly committed to a norm can recognize the violation, 250 00:13:10,720 --> 00:13:13,720 Speaker 1: but are less likely to be threatened or to directly 251 00:13:13,760 --> 00:13:18,320 Speaker 1: experience the violation's repercussions. Consider a news story about a 252 00:13:18,400 --> 00:13:22,120 Speaker 1: church that raffles off a Hummer suv as part of 253 00:13:22,120 --> 00:13:25,400 Speaker 1: a promotion for its members. Engaging in such a secular 254 00:13:25,440 --> 00:13:29,280 Speaker 1: promotion jeopardizes the sanctity of the church, and although most 255 00:13:29,320 --> 00:13:33,640 Speaker 1: people consider churches sacred, churchgoers should be more strongly committed 256 00:13:33,679 --> 00:13:36,680 Speaker 1: to this belief than are people who do not attend church. 257 00:13:37,800 --> 00:13:40,240 Speaker 1: So the researchers looked at this and they found that 258 00:13:40,280 --> 00:13:44,640 Speaker 1: while churchgoers and non churchgoers alike were about equally disgusted 259 00:13:44,760 --> 00:13:46,600 Speaker 1: with this story. You know, the idea that a church 260 00:13:46,600 --> 00:13:48,640 Speaker 1: would be trying to get people to join by giving 261 00:13:48,679 --> 00:13:52,160 Speaker 1: them a chance to win a car. Non churchgoers more 262 00:13:52,200 --> 00:13:55,800 Speaker 1: often found the story humorous, and so that was like 263 00:13:56,240 --> 00:13:59,920 Speaker 1: non churchgoers to churchgoers finding it humorous was nine two 264 00:14:00,040 --> 00:14:02,800 Speaker 1: percent to sixty two percent. So the idea is that 265 00:14:02,920 --> 00:14:06,880 Speaker 1: non churchgoers saw this as a benign violation and thus funny, 266 00:14:07,320 --> 00:14:10,640 Speaker 1: and churchgoers saw it as a real harmful violation and 267 00:14:10,679 --> 00:14:13,280 Speaker 1: thus not funny. Yeah, And I think that's something that's 268 00:14:13,280 --> 00:14:15,679 Speaker 1: important to keep in mind. And you know, when when 269 00:14:15,720 --> 00:14:19,200 Speaker 1: looking at the benign violation theory is that how ultimately 270 00:14:19,200 --> 00:14:22,360 Speaker 1: subjective it is going to be. And of course that 271 00:14:22,840 --> 00:14:26,440 Speaker 1: is comedy as well, so it matches up in that regard. Right, 272 00:14:26,480 --> 00:14:28,640 Speaker 1: It depends on whether you actually see something as a 273 00:14:28,720 --> 00:14:32,120 Speaker 1: violation and whether you actually see something as harmful or not. Now, 274 00:14:32,240 --> 00:14:33,960 Speaker 1: there are different ways you could play around with the 275 00:14:34,000 --> 00:14:36,720 Speaker 1: definitions and of this theory to like, like, you could 276 00:14:36,760 --> 00:14:39,960 Speaker 1: make it very elastic to accommodate a lot of stuff, 277 00:14:40,080 --> 00:14:43,680 Speaker 1: or you could more narrowly tailor it. I would say 278 00:14:43,720 --> 00:14:47,400 Speaker 1: one problem potentially with it is that lots of things 279 00:14:47,520 --> 00:14:51,800 Speaker 1: that are benign violations aren't funny at all. Uh. An 280 00:14:51,800 --> 00:14:53,720 Speaker 1: example I came up with is imagine you are not 281 00:14:53,800 --> 00:14:56,560 Speaker 1: supposed to take home office supplies, but you do you 282 00:14:56,600 --> 00:15:00,000 Speaker 1: take home a pin. Well, that's a violation of the rules, 283 00:15:00,080 --> 00:15:03,120 Speaker 1: doesn't It's not really harmful, it's benign, and it's not 284 00:15:03,160 --> 00:15:06,400 Speaker 1: really funny. Right. But on the other hand, I would 285 00:15:06,520 --> 00:15:09,120 Speaker 1: I think the counter argument here would be, okay, taking 286 00:15:09,120 --> 00:15:11,440 Speaker 1: one pin home from work, like that's I do that 287 00:15:11,480 --> 00:15:13,840 Speaker 1: all the time, most of us do. It's one thing 288 00:15:13,880 --> 00:15:16,800 Speaker 1: to take a pen home, even accident accidentally take one 289 00:15:16,840 --> 00:15:19,880 Speaker 1: home to you know, purposely take one home. But what 290 00:15:19,960 --> 00:15:22,480 Speaker 1: if we upped it? What have instead of accidentally taking 291 00:15:22,520 --> 00:15:25,320 Speaker 1: a pin home from work, you accidentally took all the 292 00:15:25,400 --> 00:15:28,160 Speaker 1: pins home from work. That's funny. Now that you're getting 293 00:15:28,160 --> 00:15:30,200 Speaker 1: into you know a little more, And I'm not saying 294 00:15:30,240 --> 00:15:33,400 Speaker 1: that there's it's the funniest gag of all time, but 295 00:15:33,480 --> 00:15:36,320 Speaker 1: certainly there's more room for hilarity in this scenario. Well, 296 00:15:36,360 --> 00:15:39,880 Speaker 1: that starts to be more like a machine type comedic 297 00:15:40,000 --> 00:15:43,480 Speaker 1: mistake because it's so uh, it's so over the top. 298 00:15:43,520 --> 00:15:46,320 Speaker 1: It seems to kind of like not just violate a norm, 299 00:15:46,400 --> 00:15:48,920 Speaker 1: but just plows straight through it and goes all the 300 00:15:48,960 --> 00:15:52,000 Speaker 1: way down right where I guess Another way that would 301 00:15:52,000 --> 00:15:55,840 Speaker 1: work is if one meant to steal something of greater value, 302 00:15:55,920 --> 00:16:00,400 Speaker 1: like one intended to to um to perfect rate some 303 00:16:00,520 --> 00:16:03,240 Speaker 1: greater violation of office norms and then in the end 304 00:16:03,280 --> 00:16:05,560 Speaker 1: you only stole a pin, but even in a dune 305 00:16:05,720 --> 00:16:06,880 Speaker 1: land as well, and it really needs to be a 306 00:16:06,920 --> 00:16:09,360 Speaker 1: box of pins or all the pins. Yeah, I guess 307 00:16:09,400 --> 00:16:11,080 Speaker 1: you could say. I mean, I think you could probably 308 00:16:11,120 --> 00:16:14,000 Speaker 1: play around with exactly how you define the terms of 309 00:16:14,000 --> 00:16:18,760 Speaker 1: benign violation to maybe accommodate those counterexamples. I would say, also, though, 310 00:16:19,000 --> 00:16:21,520 Speaker 1: lots of things that are funny too, people can feel 311 00:16:21,520 --> 00:16:23,720 Speaker 1: like they're not at all benign, and like think of 312 00:16:23,800 --> 00:16:27,040 Speaker 1: videos of people falling off skateboards and smashing their faces, 313 00:16:27,160 --> 00:16:30,480 Speaker 1: or the crotches and the handrails and brick walls and stuff. 314 00:16:30,520 --> 00:16:33,160 Speaker 1: People find these things quite funny, and people can get 315 00:16:33,200 --> 00:16:35,920 Speaker 1: really hurt in them. Yeah, I think with with that, 316 00:16:36,640 --> 00:16:38,400 Speaker 1: I think part of it is that we generally see 317 00:16:38,600 --> 00:16:42,080 Speaker 1: confirmation that they survived, or if we don't see confirmation, 318 00:16:42,120 --> 00:16:45,640 Speaker 1: then they survived whatever they're horrible, you know, skateboarding accident was, 319 00:16:45,920 --> 00:16:48,280 Speaker 1: then we at least don't see them going to the 320 00:16:48,320 --> 00:16:51,040 Speaker 1: e er, you know, like we have no additional information 321 00:16:51,040 --> 00:16:53,920 Speaker 1: to go on, no additional context, and we can just 322 00:16:54,000 --> 00:16:57,360 Speaker 1: kind of assume that they were okay. Uh so, and 323 00:16:57,520 --> 00:17:01,040 Speaker 1: I also was wondering about this. I wondered what comedic 324 00:17:01,080 --> 00:17:05,440 Speaker 1: interpretations of slapstick injuries and which harm generally doesn't extend 325 00:17:05,480 --> 00:17:10,040 Speaker 1: beyond the punchline. Um, if these program us to to 326 00:17:10,160 --> 00:17:14,359 Speaker 1: make these kind of comedic interpretations. For instance, you know, 327 00:17:14,560 --> 00:17:16,600 Speaker 1: when you think about comedic violence, you think about the 328 00:17:16,600 --> 00:17:20,280 Speaker 1: Three Stooges, and certainly they're just always brutalizing each other 329 00:17:20,560 --> 00:17:23,360 Speaker 1: and then they're fine, and then they're back for another adventure. 330 00:17:23,480 --> 00:17:26,919 Speaker 1: They're fine. You don't worry about their health. Take a 331 00:17:26,920 --> 00:17:30,560 Speaker 1: good old fashioned Three Stooges fingerpoke. Um, you know we 332 00:17:30,600 --> 00:17:32,879 Speaker 1: have in the eye. Do you have two fingers and 333 00:17:32,880 --> 00:17:34,679 Speaker 1: then you go right for the eyes and if nobody 334 00:17:34,680 --> 00:17:37,600 Speaker 1: gets the block up, bam, there's like a it's more 335 00:17:37,600 --> 00:17:41,560 Speaker 1: of a blink noise. Right. So yeah, so when the 336 00:17:41,600 --> 00:17:44,800 Speaker 1: Stooges do it, uh, it's hilarious. Right, there's a lot 337 00:17:44,840 --> 00:17:49,800 Speaker 1: of slapstick hilarity with with the double fingerpoke. But uh, 338 00:17:49,920 --> 00:17:52,160 Speaker 1: and then likewise, you look at something like pro wrestling. 339 00:17:52,960 --> 00:17:55,960 Speaker 1: In pro wrestling, which of course is this like sports 340 00:17:56,000 --> 00:18:00,879 Speaker 1: theater thing, Uh, the fingerpoke is a common spot, you know, 341 00:18:00,920 --> 00:18:03,080 Speaker 1: it's it's if someone goes for the double eye poke, 342 00:18:03,560 --> 00:18:05,680 Speaker 1: it's going to be a moment of hilarity as well. 343 00:18:06,200 --> 00:18:08,640 Speaker 1: But if somebody does it in a basketball game, that's 344 00:18:08,680 --> 00:18:11,240 Speaker 1: not really funny, right, or or if someone does it 345 00:18:11,320 --> 00:18:15,200 Speaker 1: in most, if not all, combat sports, it is it 346 00:18:15,320 --> 00:18:18,399 Speaker 1: is a band maneuver. Like generally, if you're going for 347 00:18:18,520 --> 00:18:22,240 Speaker 1: somebody's eyes, like, that's either it's either really evil or 348 00:18:22,240 --> 00:18:25,160 Speaker 1: it's a move of desperation. Yeah, this does certainly make 349 00:18:25,160 --> 00:18:27,960 Speaker 1: that to whatever extent of benign violation theory is true, 350 00:18:28,040 --> 00:18:32,480 Speaker 1: it's highly context dependent and and maybe the truth there, 351 00:18:32,560 --> 00:18:35,360 Speaker 1: if there is something to this theory is that um 352 00:18:35,520 --> 00:18:39,600 Speaker 1: is that the context makes us determine what's benign and 353 00:18:39,680 --> 00:18:42,439 Speaker 1: what's not right, and it's gonna be highly dependent on 354 00:18:42,760 --> 00:18:45,640 Speaker 1: the culture you're in the time you live in. I mean, certainly, 355 00:18:45,680 --> 00:18:48,280 Speaker 1: just thinking of workplace humor, there are a lot of 356 00:18:48,720 --> 00:18:52,920 Speaker 1: violations today that are serious that may have been perceived 357 00:18:53,040 --> 00:18:55,880 Speaker 1: as more benign in days past, or as or seen 358 00:18:55,920 --> 00:18:59,080 Speaker 1: as not violations at all. Oh yeah, this go back 359 00:18:59,080 --> 00:19:02,800 Speaker 1: to like the nineteen eighties, and like workplace sexual harassment 360 00:19:02,960 --> 00:19:06,520 Speaker 1: was a common like sitcom gag at the time. It's 361 00:19:06,560 --> 00:19:09,320 Speaker 1: just like Oh, it's hilarious. You know, he's he's harassing 362 00:19:09,359 --> 00:19:12,600 Speaker 1: Tina again. Uh. And now like that's not really funny 363 00:19:12,640 --> 00:19:14,680 Speaker 1: at all anymore because we see that, I think, I 364 00:19:14,760 --> 00:19:17,960 Speaker 1: think because people see that as a more genuine violation, 365 00:19:18,080 --> 00:19:20,560 Speaker 1: not as something that's just a harmless you can wave 366 00:19:20,600 --> 00:19:22,679 Speaker 1: it off, that's just Ted being ted. So how do 367 00:19:22,720 --> 00:19:27,960 Speaker 1: you feel about about benign violation and neural networks? Well, strangely, 368 00:19:28,000 --> 00:19:30,960 Speaker 1: I do see part of a fit here um because 369 00:19:31,119 --> 00:19:35,000 Speaker 1: I along the lines of the Church suv example, the 370 00:19:35,040 --> 00:19:38,960 Speaker 1: more serious and reverent the context in which the technology 371 00:19:39,080 --> 00:19:42,399 Speaker 1: is presented, the funnier it is when it fails. I 372 00:19:42,440 --> 00:19:44,879 Speaker 1: think about like ED two oh nine, this the scene 373 00:19:44,960 --> 00:19:47,159 Speaker 1: is sort of made by the fact that Dick Jones 374 00:19:47,200 --> 00:19:50,879 Speaker 1: and all the bisbros. Are proudly boasting about this marvelous 375 00:19:50,880 --> 00:19:54,080 Speaker 1: new technology that will be the future, and then it 376 00:19:54,160 --> 00:19:57,480 Speaker 1: fails in such a spectacular way. I think in general, 377 00:19:57,520 --> 00:20:00,000 Speaker 1: the failures of AI are much funnier when they're pretty 378 00:20:00,080 --> 00:20:03,920 Speaker 1: zented within a context of us knowing about people who 379 00:20:03,920 --> 00:20:07,520 Speaker 1: believe in AI messiahs and you know, AI Basilisks and 380 00:20:07,920 --> 00:20:11,080 Speaker 1: Satan's and all that. Who who uh see this great 381 00:20:11,160 --> 00:20:15,240 Speaker 1: future of of power and dominance among Aiyes, watching them 382 00:20:15,240 --> 00:20:19,119 Speaker 1: mess up in hilarious ways becomes all the more poignant 383 00:20:19,119 --> 00:20:21,960 Speaker 1: and perfect. All right, time to take a quick break 384 00:20:22,000 --> 00:20:26,399 Speaker 1: when we will be right back. All right, we're back. 385 00:20:26,760 --> 00:20:30,159 Speaker 1: So one more theory is the incongruity resolution theory. This 386 00:20:30,240 --> 00:20:32,520 Speaker 1: is a theory that's had various forms over the years, 387 00:20:32,760 --> 00:20:37,120 Speaker 1: for example, advocated by Emmanuel Kant and others, but essentially 388 00:20:37,119 --> 00:20:40,159 Speaker 1: the idea here is that there is an incongruity between 389 00:20:40,240 --> 00:20:45,600 Speaker 1: expectations and reality. Laughter occurs when we realize this incongruity 390 00:20:45,640 --> 00:20:49,240 Speaker 1: can be resolved. And this is there's clearly a strong 391 00:20:49,240 --> 00:20:51,920 Speaker 1: element of this in lots of humors. Again, what joke 392 00:20:52,000 --> 00:20:54,080 Speaker 1: involves a set up and then a punch line, and 393 00:20:54,520 --> 00:20:58,000 Speaker 1: most often the set up sets you up to expect 394 00:20:58,040 --> 00:21:01,480 Speaker 1: one type of thing. The punch lines so verts your expectations. 395 00:21:01,520 --> 00:21:04,320 Speaker 1: So that's clearly there. But then again, there are lots 396 00:21:04,320 --> 00:21:07,119 Speaker 1: of things that are surprising and turn our expectations on 397 00:21:07,160 --> 00:21:10,200 Speaker 1: their heads, and they're not funny. Yeah, like we incongruity 398 00:21:10,240 --> 00:21:12,720 Speaker 1: has to be novel. Yeah, you know, it can't be 399 00:21:12,760 --> 00:21:15,359 Speaker 1: a situation where I thought I was buying mozzarella, but 400 00:21:15,400 --> 00:21:19,600 Speaker 1: I really got monster. That's not that that's really not funny. Now, 401 00:21:19,680 --> 00:21:22,200 Speaker 1: it would be funny if you thought you were buying mozzarella, 402 00:21:22,320 --> 00:21:25,960 Speaker 1: you got home and it was like rat eggs, especially 403 00:21:26,000 --> 00:21:28,920 Speaker 1: because rats don't lay eggs. Yeah, it's like that. Yeah, 404 00:21:28,960 --> 00:21:31,840 Speaker 1: that would be that would be a lot more hilarious. 405 00:21:31,960 --> 00:21:35,199 Speaker 1: One different but somewhat similar theory. I was reading about that. 406 00:21:35,280 --> 00:21:37,479 Speaker 1: I'd like to read this book now that I know 407 00:21:37,520 --> 00:21:41,119 Speaker 1: it exists. It's a two thousand eleven book from M I. 408 00:21:41,160 --> 00:21:44,600 Speaker 1: T Press called Inside Jokes by the author's Matthew Hurley, 409 00:21:44,680 --> 00:21:49,120 Speaker 1: Daniel Dinnett, and Reginald Adams Reginald Adams Jr. And they 410 00:21:49,240 --> 00:21:52,160 Speaker 1: argue against the sufficiency of any of these models we've 411 00:21:52,160 --> 00:21:55,680 Speaker 1: talked about already. They proposed instead that humor is an 412 00:21:55,680 --> 00:22:00,600 Speaker 1: evolutionary reward system. It's a pleasurable reward feeling that we 413 00:22:00,720 --> 00:22:05,080 Speaker 1: get when we recognize the inappropriateness of a mental representation 414 00:22:05,280 --> 00:22:08,760 Speaker 1: and then fix it. So it's the brains. It's it's 415 00:22:08,760 --> 00:22:11,320 Speaker 1: an internal reward system like we get from other things 416 00:22:11,359 --> 00:22:14,440 Speaker 1: that are good for the body, like eating or something. Uh, 417 00:22:14,480 --> 00:22:19,159 Speaker 1: it's the brain's reward system for debugging itself. And so 418 00:22:19,200 --> 00:22:21,080 Speaker 1: you can imagine this is why many jokes have a 419 00:22:21,160 --> 00:22:24,919 Speaker 1: set up. The setup prepares you to establish an inappropriate 420 00:22:25,000 --> 00:22:30,000 Speaker 1: or incongruous mental representation. The punch line suddenly creates that 421 00:22:30,040 --> 00:22:34,720 Speaker 1: inappropriate representation, and then the debugging that immediately happens in 422 00:22:34,760 --> 00:22:39,679 Speaker 1: your brain following is rewarded with this pleasurable feeling of humor. Interesting. 423 00:22:39,720 --> 00:22:41,879 Speaker 1: I think that's something that that probably matches as a 424 00:22:41,920 --> 00:22:44,720 Speaker 1: model that matches with a lot of our experience of 425 00:22:44,720 --> 00:22:49,879 Speaker 1: of having hilarious or ridiculous notions enter our head and 426 00:22:49,920 --> 00:22:52,000 Speaker 1: then you just miss them, or you even don't you're 427 00:22:52,000 --> 00:22:55,800 Speaker 1: not even considering them, but they just rise up from 428 00:22:55,840 --> 00:22:57,960 Speaker 1: the depths of your psyche. Yeah, and I think it 429 00:22:58,080 --> 00:23:00,840 Speaker 1: kind of fits well with what's funny about each entry 430 00:23:00,960 --> 00:23:04,720 Speaker 1: in these like machine generated pieces of text, because each 431 00:23:04,840 --> 00:23:07,520 Speaker 1: moment you're going through this text, you're sort of being 432 00:23:07,640 --> 00:23:10,879 Speaker 1: set up to think about the text in a certain 433 00:23:10,880 --> 00:23:13,920 Speaker 1: way given the category you're already looking for, like names 434 00:23:13,960 --> 00:23:17,080 Speaker 1: of spells and stuff. Then constantly you're given something that 435 00:23:17,160 --> 00:23:20,080 Speaker 1: doesn't really fit, and then your brain has to debug 436 00:23:20,160 --> 00:23:22,880 Speaker 1: why it doesn't really fit, and that feels good. I'm 437 00:23:22,880 --> 00:23:24,960 Speaker 1: not sure it's a perfect theory that covers all of 438 00:23:25,040 --> 00:23:27,960 Speaker 1: humor either, but I am interested in. Maybe you know, 439 00:23:28,000 --> 00:23:31,040 Speaker 1: another thing is that, like you said earlier, it's possible 440 00:23:31,080 --> 00:23:35,639 Speaker 1: there's no single, perfect, overarching theory of humor, Like what 441 00:23:35,720 --> 00:23:38,840 Speaker 1: if humor is a category held together not by a 442 00:23:38,880 --> 00:23:42,480 Speaker 1: single all inclusive set of criteria, but by a Wittgensteinian 443 00:23:42,640 --> 00:23:47,000 Speaker 1: kind of family resemblances principle. There's no one thing that 444 00:23:47,000 --> 00:23:51,359 Speaker 1: that all humor is. Humor is instead multiple different related 445 00:23:51,520 --> 00:23:55,520 Speaker 1: sets of things, none of which are entirely contained in 446 00:23:55,520 --> 00:23:57,439 Speaker 1: a single box. By the way, you know, if you 447 00:23:57,440 --> 00:23:58,920 Speaker 1: open that box, it's going to be one of those 448 00:23:58,920 --> 00:24:03,320 Speaker 1: spring snakes comes flying out, like open the fake cannon nuts. 449 00:24:03,440 --> 00:24:05,520 Speaker 1: Which one does that fit in? Um? I guess you 450 00:24:05,560 --> 00:24:07,400 Speaker 1: know it has to do with expectation, but also it's 451 00:24:07,400 --> 00:24:10,840 Speaker 1: benign violation. So if you're expecting nuts, not snakes, but 452 00:24:10,880 --> 00:24:12,679 Speaker 1: you've got a snake. But then, well, it's not a 453 00:24:12,680 --> 00:24:16,000 Speaker 1: real snake, which is a perfect animal to include in 454 00:24:16,000 --> 00:24:20,359 Speaker 1: that gag given our you know, our our evolutionary response 455 00:24:20,560 --> 00:24:23,920 Speaker 1: to a serpentine form. What if it's a real snake 456 00:24:24,000 --> 00:24:25,960 Speaker 1: that bites you on the throat, I would like to 457 00:24:26,000 --> 00:24:28,240 Speaker 1: see that happen more? Or what one of my favorite 458 00:24:28,240 --> 00:24:31,120 Speaker 1: gags that I did this is at a workplace at 459 00:24:31,119 --> 00:24:33,119 Speaker 1: some point there was this I had to like kind 460 00:24:33,119 --> 00:24:36,359 Speaker 1: of this lame boss who had a can. He had 461 00:24:36,400 --> 00:24:39,359 Speaker 1: this exact gag of fake nuts, fake peanuts, and if 462 00:24:39,359 --> 00:24:42,600 Speaker 1: you opened it, a snake jumped out. Um So, one 463 00:24:42,680 --> 00:24:44,520 Speaker 1: day he was gone for the day and so I 464 00:24:44,560 --> 00:24:47,000 Speaker 1: took the snake, got rid of the snake, and I 465 00:24:47,040 --> 00:24:50,280 Speaker 1: filled it with actual peanuts, and they gave me so 466 00:24:50,359 --> 00:24:52,280 Speaker 1: much pleasure. I don't I never even got to witness 467 00:24:52,359 --> 00:24:54,800 Speaker 1: the payoff, but I just love the idea of him 468 00:24:54,840 --> 00:24:57,200 Speaker 1: going to like pull this out on somebody or to 469 00:24:57,320 --> 00:24:59,760 Speaker 1: just amuse himself, and then it's actually filled with nuts. 470 00:25:00,040 --> 00:25:01,800 Speaker 1: And I don't know how lame the boss was. This 471 00:25:01,880 --> 00:25:03,520 Speaker 1: was This is kind of a time in my life 472 00:25:03,520 --> 00:25:06,080 Speaker 1: when all bosses were laying So if any of my 473 00:25:06,119 --> 00:25:09,240 Speaker 1: previous bosses are listening to me, I'm probably not talking 474 00:25:09,280 --> 00:25:11,720 Speaker 1: about you. Well, there's another theory of humor that kind 475 00:25:11,720 --> 00:25:14,840 Speaker 1: of fits that because of the way in which humor 476 00:25:15,040 --> 00:25:18,080 Speaker 1: sort of interlocks with our expectations of people based on 477 00:25:18,119 --> 00:25:22,359 Speaker 1: their individual characteristics. Uh So, this next one clearly doesn't 478 00:25:22,359 --> 00:25:24,720 Speaker 1: account for everything that's funny, but it does have a 479 00:25:24,760 --> 00:25:27,440 Speaker 1: kind of elegant elegant connection to what we're talking about. 480 00:25:27,440 --> 00:25:29,240 Speaker 1: So this is a theory of humor put forward by 481 00:25:30,320 --> 00:25:33,359 Speaker 1: a philosopher named Henri Bergson in a book called Laughter, 482 00:25:33,520 --> 00:25:36,760 Speaker 1: published in nineteen hundred and One of the ideas Bergson 483 00:25:36,840 --> 00:25:40,160 Speaker 1: puts forward here is that laughter is often our response 484 00:25:40,280 --> 00:25:45,720 Speaker 1: to rigidity, inflexibility, and failure to adapt. And this is 485 00:25:45,760 --> 00:25:49,520 Speaker 1: one of the reasons why comedies involve us being aware of, 486 00:25:49,560 --> 00:25:53,360 Speaker 1: like the particular flaws of a character and then seeing 487 00:25:53,400 --> 00:25:56,600 Speaker 1: those same flaws acted out over and over again. Think 488 00:25:56,640 --> 00:25:59,480 Speaker 1: about sitcoms like it's not just that the characters have 489 00:25:59,640 --> 00:26:03,280 Speaker 1: failed years, but they tend to fail repeatedly in in 490 00:26:03,280 --> 00:26:08,320 Speaker 1: individually characteristic ways. Homer Simpson is lazy and he's thoughtless, 491 00:26:08,359 --> 00:26:11,000 Speaker 1: and he's motivated by donuts and gluttony and all that. 492 00:26:11,640 --> 00:26:14,880 Speaker 1: Michael Scott in the office is needy and attention seeking 493 00:26:14,880 --> 00:26:18,119 Speaker 1: and unaware of how he's perceived by others. Characters have 494 00:26:18,200 --> 00:26:21,680 Speaker 1: these sort of trademarks and they keep making the same 495 00:26:21,800 --> 00:26:25,960 Speaker 1: kinds of mistakes over and over, and it's their inability 496 00:26:26,040 --> 00:26:29,760 Speaker 1: to adapt that makes it humorous in this point of view. Now, 497 00:26:29,760 --> 00:26:32,399 Speaker 1: clearly this doesn't account for everything that's funny, but it 498 00:26:32,520 --> 00:26:35,040 Speaker 1: sort of ties in loosely with the Hurley Dinnett Adams 499 00:26:35,080 --> 00:26:39,119 Speaker 1: theory that humor rewards adaptation and mental debugging. These people, 500 00:26:39,400 --> 00:26:42,000 Speaker 1: if they're making the same mistakes over and over, there 501 00:26:42,040 --> 00:26:45,480 Speaker 1: not debugging, and you're like debugging by watching them. But 502 00:26:45,520 --> 00:26:46,800 Speaker 1: then again, of course we have to come back to 503 00:26:46,800 --> 00:26:48,879 Speaker 1: sort of the benign violation theory a little bit here, 504 00:26:48,920 --> 00:26:53,040 Speaker 1: because we don't want characters that uh failed too much, 505 00:26:53,200 --> 00:26:54,560 Speaker 1: you know, like you don't want it to be like 506 00:26:54,600 --> 00:26:57,600 Speaker 1: a tragic level of failure. Oh right, yeah, And of 507 00:26:57,640 --> 00:27:00,600 Speaker 1: course in reality people fail to adapt all all the 508 00:27:00,640 --> 00:27:02,679 Speaker 1: time and ways that aren't funny but are actually like 509 00:27:02,720 --> 00:27:05,000 Speaker 1: sad or tragic or you know, it's something very bad 510 00:27:05,040 --> 00:27:06,879 Speaker 1: about it. And then there's that whole sliding scale too, 511 00:27:06,920 --> 00:27:10,399 Speaker 1: because especially with something like like Michael Scott, especially like 512 00:27:10,560 --> 00:27:15,240 Speaker 1: the Office got into so much awkward territory just every week, 513 00:27:15,280 --> 00:27:19,040 Speaker 1: week after week, and um, a lot of that really 514 00:27:19,040 --> 00:27:24,440 Speaker 1: got into sort of painful, pitiful territory, so that they 515 00:27:24,520 --> 00:27:28,040 Speaker 1: definitely changed exactly where the line was in the sand, 516 00:27:28,760 --> 00:27:31,639 Speaker 1: but but still ultimately, like you know, Michael Scott didn't 517 00:27:31,680 --> 00:27:33,600 Speaker 1: die at the end of an episode, well, it helped 518 00:27:33,640 --> 00:27:36,399 Speaker 1: by coming back and making the character lovable like he 519 00:27:36,520 --> 00:27:40,320 Speaker 1: wasn't getting into that like sad awkwardness, and then just 520 00:27:40,520 --> 00:27:43,800 Speaker 1: ending in a place where you hate him. Right. Yeah, 521 00:27:43,880 --> 00:27:46,800 Speaker 1: But anyway, I think this theory about like rigidity and 522 00:27:46,880 --> 00:27:51,560 Speaker 1: inflexibility and like repeating the same types of mistakes without adapting, 523 00:27:52,160 --> 00:27:55,480 Speaker 1: has some strong purchase on the funniest features of machine 524 00:27:55,560 --> 00:27:58,800 Speaker 1: failure comedy. It's not just that the machine fails, but 525 00:27:58,880 --> 00:28:04,600 Speaker 1: that the machine failed repeatedly mechanically according to inflexible guidelines, 526 00:28:04,640 --> 00:28:07,360 Speaker 1: Like the way it just keeps following the rules. When 527 00:28:07,359 --> 00:28:10,200 Speaker 1: a neural net text generator spits out not just one 528 00:28:10,240 --> 00:28:14,359 Speaker 1: nonsensical phrase, but like reams and reams of text without 529 00:28:14,400 --> 00:28:17,199 Speaker 1: acknowledging or knowing it all that the first few words 530 00:28:17,240 --> 00:28:19,640 Speaker 1: didn't make any sense. Or when I think about when 531 00:28:19,640 --> 00:28:23,359 Speaker 1: a glitching video game character is stuck inside a table 532 00:28:23,560 --> 00:28:27,320 Speaker 1: and just keeps running in place and talking, that's one 533 00:28:27,320 --> 00:28:30,480 Speaker 1: of my favorites. Or it's that lack of contacts, lack 534 00:28:30,520 --> 00:28:33,840 Speaker 1: of context, lack of self awareness, and lack of adaptability. 535 00:28:34,080 --> 00:28:38,000 Speaker 1: The way machines just plow ahead despite problems that are 536 00:28:38,040 --> 00:28:41,080 Speaker 1: obvious to us that they're clearly not aware of. I 537 00:28:41,120 --> 00:28:44,240 Speaker 1: think that's key to what makes them so especially funny, 538 00:28:44,560 --> 00:28:46,960 Speaker 1: and in this sense, they're kind of like the Homer 539 00:28:47,000 --> 00:28:50,840 Speaker 1: Simpsons and the Michael Scott's, the characters with inflexible, repetitive 540 00:28:50,880 --> 00:28:54,360 Speaker 1: behaviors that lead to disaster, but which they never learned 541 00:28:54,440 --> 00:28:57,080 Speaker 1: from or change. You know, I can't help but come 542 00:28:57,120 --> 00:28:59,800 Speaker 1: back to the idea of a child and all of 543 00:28:59,800 --> 00:29:02,440 Speaker 1: this the child analogy here, so you know, we can 544 00:29:02,520 --> 00:29:05,000 Speaker 1: we can laugh at our own children's mistakes are weird 545 00:29:05,040 --> 00:29:08,960 Speaker 1: interpretations because we know that they're they're largely going to adapt, 546 00:29:09,360 --> 00:29:12,080 Speaker 1: they're going to grow up, uh, and that they're gonna 547 00:29:12,160 --> 00:29:16,040 Speaker 1: leave behind their their dragons or hopefully they're just gonna 548 00:29:16,040 --> 00:29:19,320 Speaker 1: remember how to summon them in appropriate ways now. But 549 00:29:19,360 --> 00:29:22,240 Speaker 1: if they're the robot is hilarious because it continues to fail, 550 00:29:22,280 --> 00:29:24,080 Speaker 1: and of course also because it is a machine and 551 00:29:24,120 --> 00:29:27,120 Speaker 1: not a human child. Perhaps part of the issue too 552 00:29:27,240 --> 00:29:30,000 Speaker 1: is that a machine is but a prototype, and it's 553 00:29:30,160 --> 00:29:34,320 Speaker 1: next phase of advancement does not necessarily exist within itself, 554 00:29:34,720 --> 00:29:38,240 Speaker 1: but in the next prototype and another individual, if you will. 555 00:29:38,440 --> 00:29:40,800 Speaker 1: I think that's a really good point. Yes, Like, so 556 00:29:40,840 --> 00:29:44,080 Speaker 1: a child can make a funny mistake, but then the 557 00:29:44,200 --> 00:29:49,400 Speaker 1: child immediately within themselves learn something and or you know, 558 00:29:49,480 --> 00:29:52,120 Speaker 1: at least as the potential learn something and grow and 559 00:29:52,160 --> 00:29:54,560 Speaker 1: get better at not making that kind of mistake anymore, 560 00:29:54,640 --> 00:29:57,040 Speaker 1: which in some cases kind of tragic because the mistakes 561 00:29:57,040 --> 00:30:00,240 Speaker 1: are glorious. Oh yeah, like half the in joke that 562 00:30:00,360 --> 00:30:03,400 Speaker 1: my wife and I make are two things that my 563 00:30:03,400 --> 00:30:06,200 Speaker 1: my son has not said in years, but he said 564 00:30:06,200 --> 00:30:08,400 Speaker 1: it was and it was hilarious, and now we repeat 565 00:30:08,440 --> 00:30:10,920 Speaker 1: it to each other. But like most of these machines, 566 00:30:11,440 --> 00:30:13,920 Speaker 1: even though they might have the ability to learn from 567 00:30:13,960 --> 00:30:17,200 Speaker 1: their mistakes, they learn from their their mistakes in like 568 00:30:17,320 --> 00:30:20,800 Speaker 1: new instantiations of one of themselves, like you're saying, it's 569 00:30:20,840 --> 00:30:24,200 Speaker 1: the next prototype. They don't automatically learn from their mistakes. 570 00:30:24,280 --> 00:30:27,200 Speaker 1: You have to do something to them to reboot them 571 00:30:27,280 --> 00:30:29,680 Speaker 1: or retrain them or something. Right. And if it's a 572 00:30:29,760 --> 00:30:32,920 Speaker 1: video game, yeah, this this character is gonna keep getting 573 00:30:32,960 --> 00:30:34,920 Speaker 1: stuck in that table. Maybe there'll be a patch that 574 00:30:35,000 --> 00:30:36,800 Speaker 1: fixes it, but for the most part, it's going to 575 00:30:36,880 --> 00:30:39,160 Speaker 1: be the sequel that tries to get it right. All right, 576 00:30:39,200 --> 00:30:41,080 Speaker 1: we're gonna take a quick break, but we'll be right back, 577 00:30:43,880 --> 00:30:46,440 Speaker 1: and we're back now. I think this is all one 578 00:30:46,480 --> 00:30:49,400 Speaker 1: of one of the reasons that the Black Mirror episode 579 00:30:49,480 --> 00:30:54,400 Speaker 1: Metal Head from seen is so effective, haven't Oh, it's 580 00:30:54,480 --> 00:30:57,680 Speaker 1: it's it's one of my favorites. Um. This was This 581 00:30:57,720 --> 00:31:00,680 Speaker 1: was again seventeen, and this came after years of us 582 00:31:00,760 --> 00:31:06,200 Speaker 1: watching impressive, yet ultimately clumsy and imperfect Boston Dynamics walking 583 00:31:06,280 --> 00:31:10,960 Speaker 1: robot videos. Videos of such you know entities as Big Dog, 584 00:31:11,600 --> 00:31:14,560 Speaker 1: you know, which kind of has this springy brant brant 585 00:31:14,640 --> 00:31:17,560 Speaker 1: kind of a sound as it prances along, and it's 586 00:31:17,640 --> 00:31:20,400 Speaker 1: very impressive to look at. And yet at the same time, 587 00:31:20,560 --> 00:31:23,560 Speaker 1: you know their videos of being kicked around, and you know, 588 00:31:23,600 --> 00:31:26,440 Speaker 1: certainly if it's succeeding a lot, but also not quite 589 00:31:27,040 --> 00:31:30,920 Speaker 1: it's not reaching that level of like mature technology. Yeah, 590 00:31:30,920 --> 00:31:34,120 Speaker 1: though I worry how much I already sympathize with it, 591 00:31:34,200 --> 00:31:37,520 Speaker 1: Like watching those Boston Dynamics robots when somebody kicks the dog. 592 00:31:37,600 --> 00:31:39,440 Speaker 1: I know it's just a robot, but I don't like 593 00:31:39,560 --> 00:31:42,480 Speaker 1: that person who kicked it. Yeah, I'm like, that's cruel. 594 00:31:42,600 --> 00:31:47,520 Speaker 1: How could you do that? Well? In the Metal Head, Uh, basically, 595 00:31:47,520 --> 00:31:51,840 Speaker 1: the whole thing is kind of a post um apocalyptic scenario, 596 00:31:52,320 --> 00:31:55,720 Speaker 1: killer robot scenario, and the killer robot we see is 597 00:31:55,720 --> 00:31:59,560 Speaker 1: not a juvenile prototype, but what you might classify as 598 00:31:59,600 --> 00:32:03,720 Speaker 1: an old that the technology in a proceed at a 599 00:32:03,760 --> 00:32:08,040 Speaker 1: perceived level of maturity. So the Boston Dynamics Big Dog 600 00:32:08,840 --> 00:32:14,600 Speaker 1: all grown up into a terrifying, lethal, quadrupedal killing machine 601 00:32:14,640 --> 00:32:18,280 Speaker 1: that it overcomes every challenge in the natural or man 602 00:32:18,360 --> 00:32:21,880 Speaker 1: made world that it is presented with. Uh And I 603 00:32:21,880 --> 00:32:24,040 Speaker 1: think that's that's one of the reasons it is terrifying, 604 00:32:24,080 --> 00:32:26,400 Speaker 1: because it's kind of like, oh, yeah, these things are 605 00:32:26,440 --> 00:32:28,600 Speaker 1: going to grow up. We're we're putting a lot of 606 00:32:28,640 --> 00:32:31,720 Speaker 1: money and effort into making them grow up. And uh 607 00:32:31,960 --> 00:32:33,600 Speaker 1: and and how are we going to relate to that 608 00:32:33,640 --> 00:32:36,080 Speaker 1: technology when it reaches that point? Well, that brings us 609 00:32:36,080 --> 00:32:38,320 Speaker 1: back to something you were saying earlier about like the C. S. 610 00:32:38,400 --> 00:32:41,840 Speaker 1: Lewis quote, Like clearly our machines and their failures I 611 00:32:41,880 --> 00:32:46,440 Speaker 1: think are becoming much funnier over time. Like a steam 612 00:32:46,440 --> 00:32:48,840 Speaker 1: engine designed to pump water out of a coal mine 613 00:32:48,960 --> 00:32:51,600 Speaker 1: is really not funny when it malfunctions. Maybe it like 614 00:32:51,680 --> 00:32:56,000 Speaker 1: cut somebody's arm off, Like it's it's not hilarious. Automatic 615 00:32:56,040 --> 00:32:58,920 Speaker 1: doors are still not very funny, maybe a little bit funnier, 616 00:32:59,000 --> 00:33:00,640 Speaker 1: like I was saying, when they're trying trying to close 617 00:33:00,680 --> 00:33:02,680 Speaker 1: on something over and over and you know when it 618 00:33:02,720 --> 00:33:07,360 Speaker 1: gets repetitive like that room buzz are funnier anything attempting 619 00:33:07,400 --> 00:33:11,640 Speaker 1: to generate real human language or simulate direct human behaviors, 620 00:33:11,680 --> 00:33:15,680 Speaker 1: like say the DARPA Challenge bipedal robots. You know when 621 00:33:15,680 --> 00:33:17,920 Speaker 1: you watch them like collapsing in the sand, or like 622 00:33:18,600 --> 00:33:20,800 Speaker 1: when one of them like opens a door and the 623 00:33:20,800 --> 00:33:23,160 Speaker 1: door goes open and then they just crumple in a 624 00:33:23,160 --> 00:33:26,880 Speaker 1: heap on the ground, and that kind of thing. It 625 00:33:26,960 --> 00:33:30,280 Speaker 1: is definitely even funnier, Like machines seem to get funnier. 626 00:33:30,480 --> 00:33:34,280 Speaker 1: The closer they get too resembling real human behaviors, the 627 00:33:34,360 --> 00:33:37,240 Speaker 1: better they simulate. And I wonder, so it's almost like 628 00:33:37,240 --> 00:33:40,000 Speaker 1: there's an uncanny Valley of humor in a way. Yeah, 629 00:33:40,040 --> 00:33:42,920 Speaker 1: I think I'm canny Valley definitely gets into this territory. 630 00:33:43,200 --> 00:33:47,560 Speaker 1: I'm specifically reminded of Sophia, the smiling humanoid robot. It's 631 00:33:47,560 --> 00:33:50,320 Speaker 1: becomes something of a meme and it's very impressive, like 632 00:33:50,360 --> 00:33:53,360 Speaker 1: that's the thing. At the same time it is amazing, 633 00:33:53,480 --> 00:33:55,320 Speaker 1: like this thing that he worshiped as a god in 634 00:33:55,360 --> 00:33:58,560 Speaker 1: the previous dage that it smiles too fast, smiles too fast, 635 00:33:58,640 --> 00:34:01,280 Speaker 1: and it's just it's not right and you can't help 636 00:34:01,320 --> 00:34:03,680 Speaker 1: but either look away or laugh. But yeah, I mean, 637 00:34:03,720 --> 00:34:05,880 Speaker 1: I wonder if there there is an element. I don't 638 00:34:05,880 --> 00:34:07,680 Speaker 1: think it's the whole thing, but I do wonder if 639 00:34:07,680 --> 00:34:10,759 Speaker 1: it's there's sort of an undercurrent in machine humor, of 640 00:34:10,760 --> 00:34:14,400 Speaker 1: a kind of nervous laughter at you know, in machines 641 00:34:14,800 --> 00:34:18,080 Speaker 1: potentially becoming more human, more threatening to our sense of 642 00:34:18,160 --> 00:34:22,319 Speaker 1: species specialness, and potentially more threatening to our safety, like 643 00:34:22,360 --> 00:34:25,399 Speaker 1: we were talking about. You know, I'm reminded of something 644 00:34:25,400 --> 00:34:27,560 Speaker 1: we mentioned fairly often on the show. Actually, ever since 645 00:34:27,600 --> 00:34:30,120 Speaker 1: our conversation with our Scott Baker about this about how 646 00:34:30,440 --> 00:34:35,320 Speaker 1: you don't need terminators or matrix agents or other evil 647 00:34:35,440 --> 00:34:40,080 Speaker 1: super intelligent villains who want to exterminate humans for AI 648 00:34:40,160 --> 00:34:43,240 Speaker 1: to represent a threat to humanity. In fact, I'm much 649 00:34:43,320 --> 00:34:46,799 Speaker 1: more worried about the threat from stupid AI that is 650 00:34:46,920 --> 00:34:49,919 Speaker 1: powerful before it is wise, sort of like the way 651 00:34:49,960 --> 00:34:53,480 Speaker 1: that so many examples we've discussed already just plow ahead 652 00:34:54,000 --> 00:34:57,480 Speaker 1: carrying out their functions without realizing they're going the wrong way, 653 00:34:57,560 --> 00:34:59,920 Speaker 1: or they're they're stuck, or they're not making any sense. 654 00:35:00,040 --> 00:35:04,480 Speaker 1: Uh Like, attached that kind of logic to practical functions 655 00:35:04,520 --> 00:35:06,960 Speaker 1: that have power over our lives and there can be 656 00:35:07,080 --> 00:35:10,120 Speaker 1: terrible consequences, which also kind of comes back to children. 657 00:35:10,160 --> 00:35:12,319 Speaker 1: It's like, these are the these are the humans that 658 00:35:12,360 --> 00:35:15,440 Speaker 1: will one day rule the world and uh and and 659 00:35:15,560 --> 00:35:19,719 Speaker 1: just listen to the weird things that keep saying to us, right, yeah, well, 660 00:35:19,760 --> 00:35:21,520 Speaker 1: I guess there's always kind of a terror at the 661 00:35:21,600 --> 00:35:24,359 Speaker 1: upcoming generations in there because there's always a little bit 662 00:35:24,360 --> 00:35:26,640 Speaker 1: of lack of understanding. Oh yeah, for sure. I mean 663 00:35:26,760 --> 00:35:30,120 Speaker 1: kids are always going to be amusing, but also yeah, 664 00:35:30,160 --> 00:35:32,040 Speaker 1: you want you wonder, you know, if they're going to 665 00:35:32,120 --> 00:35:34,120 Speaker 1: be able to really grow out of this, and then likewise, 666 00:35:34,120 --> 00:35:37,200 Speaker 1: teenagers are always going to be terrifying to the older generations. 667 00:35:37,480 --> 00:35:41,440 Speaker 1: Right well, So, bringing back to neural networks generating text, 668 00:35:41,560 --> 00:35:43,200 Speaker 1: one of the things that I see come up most 669 00:35:43,239 --> 00:35:46,920 Speaker 1: often in like articles about the subject is fears about 670 00:35:47,640 --> 00:35:52,880 Speaker 1: machine generated news articles, like specifically machine generated fake news 671 00:35:52,960 --> 00:35:56,080 Speaker 1: or hoax news articles. Of course, I'm not talking about 672 00:35:56,080 --> 00:35:58,799 Speaker 1: the version of fake news that has become a politicized term. 673 00:35:58,840 --> 00:36:02,960 Speaker 1: I mean like articles that are generated to contain false information, right, 674 00:36:03,200 --> 00:36:08,440 Speaker 1: even intentionally uh created it's a propaganda or misinformation, yeah, 675 00:36:08,680 --> 00:36:11,600 Speaker 1: or just nonsense, And so it shouldn't come as a 676 00:36:11,600 --> 00:36:14,360 Speaker 1: shock that they are already programs that can and do 677 00:36:14,640 --> 00:36:18,920 Speaker 1: right fake articles from AI generated text. The problem is 678 00:36:18,960 --> 00:36:22,480 Speaker 1: not that these programs exist like humans, right, hoax and 679 00:36:22,560 --> 00:36:25,200 Speaker 1: propaganda articles all the time. It's not that we couldn't 680 00:36:25,320 --> 00:36:29,200 Speaker 1: create them without machines. My fear is maybe about volume. 681 00:36:29,400 --> 00:36:33,800 Speaker 1: Like if the process of putting out hoax nonsense articles 682 00:36:33,800 --> 00:36:37,320 Speaker 1: and stuff can be automated, you can just do so 683 00:36:37,440 --> 00:36:40,239 Speaker 1: much of it. And one of the keys is that 684 00:36:40,280 --> 00:36:44,200 Speaker 1: it doesn't have to be good or convincing to be damaging. 685 00:36:44,520 --> 00:36:48,480 Speaker 1: If you simply flood the zone of people's Internet experience 686 00:36:48,520 --> 00:36:52,600 Speaker 1: with obvious nonsense and trash, they don't have to believe it. 687 00:36:52,600 --> 00:36:54,800 Speaker 1: It can just do lots of damage to a culture 688 00:36:55,400 --> 00:36:59,040 Speaker 1: simply by flooding out everything else, right, I mean you 689 00:36:59,040 --> 00:37:01,520 Speaker 1: can you can almost image in a future generation looking 690 00:37:01,560 --> 00:37:04,040 Speaker 1: back at a time like that and saying, well, you know, 691 00:37:04,200 --> 00:37:06,640 Speaker 1: it's really difficult to know exactly what they felt in 692 00:37:06,719 --> 00:37:10,719 Speaker 1: thought because of all the nonsense that was created, say, 693 00:37:10,760 --> 00:37:15,560 Speaker 1: not not just textual but video nonsense, photoshop nonsense like 694 00:37:15,680 --> 00:37:18,440 Speaker 1: we know where are the real people and their actual 695 00:37:18,440 --> 00:37:21,360 Speaker 1: concerns and all of this. Yeah, I really worry about 696 00:37:21,400 --> 00:37:26,760 Speaker 1: the potential for dumb, context ignorant algorithms that seemed perfectly 697 00:37:26,760 --> 00:37:30,280 Speaker 1: capable of steering users intellectably into more and more horrible 698 00:37:30,360 --> 00:37:33,400 Speaker 1: in mind destroying content on platforms like YouTube, you know, 699 00:37:33,640 --> 00:37:38,560 Speaker 1: and YouTube content serving algorithms that's already the world destroying AI. 700 00:37:38,680 --> 00:37:40,720 Speaker 1: But here's the thing, Joe, what if it's all funny? 701 00:37:40,760 --> 00:37:43,400 Speaker 1: What if it's all really funny. Well, in some cases 702 00:37:43,440 --> 00:37:46,800 Speaker 1: it is like top shelf ClickHole funny. Then then I 703 00:37:46,840 --> 00:37:49,160 Speaker 1: don't know, maybe them all in for the the age 704 00:37:49,160 --> 00:37:52,200 Speaker 1: of unreasoned. I worry about this more than the kind 705 00:37:52,200 --> 00:37:55,239 Speaker 1: of mind ravaging dumb AI weigh more than I worry 706 00:37:55,280 --> 00:37:58,799 Speaker 1: about the great basilisk I agree with you there, all right, Well, 707 00:37:58,840 --> 00:38:01,560 Speaker 1: well I want to bring it back to lighter territory here. Um, 708 00:38:01,600 --> 00:38:05,239 Speaker 1: the joke telling capabilities of Siri on an iPhone. Now 709 00:38:05,239 --> 00:38:08,200 Speaker 1: imagine anyone out there who has an iPhone, and probably 710 00:38:08,600 --> 00:38:11,239 Speaker 1: there's some degree of this in any kind of you know, 711 00:38:11,400 --> 00:38:15,399 Speaker 1: voice interface system Alexa or or what have you. But 712 00:38:15,600 --> 00:38:17,400 Speaker 1: when you when you ask Syria to tell you a 713 00:38:17,440 --> 00:38:20,040 Speaker 1: knockdoc joke, she will tell you a knockdot joke, and 714 00:38:20,080 --> 00:38:22,960 Speaker 1: some of them are pretty funny. Um, and then she 715 00:38:23,000 --> 00:38:25,040 Speaker 1: all you ask her other things, so they'll be a 716 00:38:25,120 --> 00:38:27,840 Speaker 1: hilarious response. Like if you ask her about how nine thousand, 717 00:38:27,960 --> 00:38:30,479 Speaker 1: she has a funny response that's you know, preprogrammed. Again, 718 00:38:30,520 --> 00:38:33,360 Speaker 1: it's it's something that somebody wrote and created. This is human, 719 00:38:33,600 --> 00:38:37,560 Speaker 1: human augmented humor. Yeah, but one of my favorites is 720 00:38:37,560 --> 00:38:40,279 Speaker 1: is one that Siri told me where clearly it was 721 00:38:40,520 --> 00:38:42,799 Speaker 1: there was an error that took place, and I'm not 722 00:38:42,840 --> 00:38:46,479 Speaker 1: perfectly replicating it here, but it was something like this, uh, 723 00:38:46,680 --> 00:38:50,759 Speaker 1: knock knock. I say who's there? And then Siri says Sophia, 724 00:38:51,280 --> 00:38:54,440 Speaker 1: And I say Sophia, who and then she says, I'm sorry, 725 00:38:54,440 --> 00:38:57,200 Speaker 1: there's nobody in your call list or your contact listener, 726 00:38:57,360 --> 00:39:00,000 Speaker 1: Sofia like, and so I never get to find out 727 00:39:00,040 --> 00:39:02,880 Speaker 1: what the rest of that joke is because in asking, 728 00:39:03,280 --> 00:39:06,600 Speaker 1: in responding to the knock knock joke, she thinks I'm 729 00:39:06,600 --> 00:39:10,759 Speaker 1: trying to make a call. And so that that makes 730 00:39:10,800 --> 00:39:13,160 Speaker 1: me laugh every time that I've heard it. That's really good. 731 00:39:13,239 --> 00:39:15,640 Speaker 1: It's like a performance art kind of joke. Yeah, So 732 00:39:15,680 --> 00:39:18,800 Speaker 1: it's it's trying to be you know, actual funny joke telling, 733 00:39:18,800 --> 00:39:21,600 Speaker 1: but then it gets into this machine error level of 734 00:39:21,640 --> 00:39:25,520 Speaker 1: joke telling and it's probably the more hilarious outcome of 735 00:39:25,600 --> 00:39:28,040 Speaker 1: the two. There is no one called big Cat, big Cat, 736 00:39:28,120 --> 00:39:31,279 Speaker 1: big Cat big Cat in your address, but there should be, 737 00:39:31,360 --> 00:39:34,279 Speaker 1: though I should create that. All right, Well, there you 738 00:39:34,320 --> 00:39:37,759 Speaker 1: have it. Um, I feel like we have completely explained 739 00:39:37,880 --> 00:39:43,000 Speaker 1: humor and artificial intelligence. We hope you never find anything 740 00:39:43,040 --> 00:39:47,480 Speaker 1: funny again. Uh yeah, as so. As always, if you 741 00:39:47,520 --> 00:39:49,400 Speaker 1: want more content, you want more episodes of Stuff to 742 00:39:49,400 --> 00:39:51,480 Speaker 1: blow your mind, head on over to Stuff to Blow 743 00:39:51,520 --> 00:39:53,520 Speaker 1: your Mind dot com. That is the mother ship. That's 744 00:39:53,520 --> 00:39:55,200 Speaker 1: where we'll find all the episodes. That's where we'll find 745 00:39:55,239 --> 00:39:57,600 Speaker 1: links out to social media accounts. That's where we'll find 746 00:39:57,640 --> 00:40:00,399 Speaker 1: a link to our t shirt store where you can 747 00:40:00,400 --> 00:40:03,839 Speaker 1: get the all Hail the Great Basilist t shirt. Uh. 748 00:40:03,960 --> 00:40:06,080 Speaker 1: So you can. You can have a little fun, have 749 00:40:06,160 --> 00:40:08,760 Speaker 1: a little uh find a little humor in the idea 750 00:40:08,760 --> 00:40:12,960 Speaker 1: of future of Hyper Powerful AI Overlord scoring the machines. 751 00:40:13,200 --> 00:40:15,279 Speaker 1: That's right, it's a fun way to support the show. 752 00:40:15,520 --> 00:40:17,239 Speaker 1: You can also support us in the best way to 753 00:40:17,280 --> 00:40:19,600 Speaker 1: support us is just to rate and review us wherever 754 00:40:19,640 --> 00:40:21,960 Speaker 1: you have the power to do so. Like whatever platform 755 00:40:22,000 --> 00:40:24,799 Speaker 1: you're using to listen to podcasts, make sure you've thrown 756 00:40:24,840 --> 00:40:26,799 Speaker 1: a few stars in a nice review our way. Hey, 757 00:40:26,920 --> 00:40:30,160 Speaker 1: you subscribe to Invention yet if you haven't, that's our 758 00:40:30,239 --> 00:40:32,759 Speaker 1: other podcast. We bring the same kind of approach we 759 00:40:32,800 --> 00:40:34,319 Speaker 1: bring on stuff to blow your mind, but we talk 760 00:40:34,400 --> 00:40:37,480 Speaker 1: about inventions from history. If you like this show, we're 761 00:40:37,480 --> 00:40:39,240 Speaker 1: pretty sure you'll like that one too, so you should 762 00:40:39,239 --> 00:40:42,200 Speaker 1: go check it out and subscribe. Yeah, two whole episodes 763 00:40:42,239 --> 00:40:44,719 Speaker 1: on toilets, for instance, Oh man, that was fun. Never 764 00:40:44,719 --> 00:40:46,720 Speaker 1: look at a toilet the same way as way again, 765 00:40:46,840 --> 00:40:49,760 Speaker 1: honestly I don't. I have way more appreciation of toilet 766 00:40:49,840 --> 00:40:51,920 Speaker 1: kind than I did before. And there's an example of 767 00:40:51,920 --> 00:40:56,200 Speaker 1: technology that is inherently funny and inherently good. Yeah, it's 768 00:40:56,280 --> 00:40:59,160 Speaker 1: very good, very important anyway, huge thanks to our excellent 769 00:40:59,200 --> 00:41:02,719 Speaker 1: audio produce series Alex Williams and Tor Harrison. If you 770 00:41:02,760 --> 00:41:05,680 Speaker 1: would like to reach out to us, to send us 771 00:41:05,680 --> 00:41:08,000 Speaker 1: an email and let us know what you think about 772 00:41:08,040 --> 00:41:10,920 Speaker 1: the show, feedback on this episode or any other suggestions 773 00:41:10,920 --> 00:41:13,600 Speaker 1: for future topics, or just let us know maybe how 774 00:41:13,640 --> 00:41:15,440 Speaker 1: you found out about us where you listen from that 775 00:41:15,520 --> 00:41:17,960 Speaker 1: kind of stuff. You can email us at blow the 776 00:41:18,040 --> 00:41:31,000 Speaker 1: Mind at how stuff works dot com for more on 777 00:41:31,120 --> 00:41:33,600 Speaker 1: this and thousands of other topics. Does it. How stuff 778 00:41:33,600 --> 00:41:41,560 Speaker 1: Works dot Com b b b b b b b 779 00:41:41,640 --> 00:41:42,880 Speaker 1: b bl bl bl