1 00:00:03,120 --> 00:00:06,000 Speaker 1: Welcome to Stuff to Blow your Mind from how Stuff 2 00:00:06,040 --> 00:00:14,360 Speaker 1: Works dot com. Hey, welcome to Stuff to Blow your Mind. 3 00:00:14,400 --> 00:00:16,920 Speaker 1: My name is Robert Lamb and I'm Julie Douglas. Julie. 4 00:00:17,040 --> 00:00:21,080 Speaker 1: Two questions. First of all, should humans love their technology? 5 00:00:21,239 --> 00:00:27,320 Speaker 1: That's the first question. Second question, should technology love humans? Okay, um, 6 00:00:27,360 --> 00:00:29,880 Speaker 1: I'm gonna say yes and yes because I think that 7 00:00:29,960 --> 00:00:35,120 Speaker 1: you can't stop love in any form, right, yeah, yeah, 8 00:00:35,159 --> 00:00:36,920 Speaker 1: I think that we and I think we we'll maybe 9 00:00:37,000 --> 00:00:39,239 Speaker 1: make this case today. I don't know, or we'll just 10 00:00:39,320 --> 00:00:42,200 Speaker 1: muddle the whole concept of love. But I do think 11 00:00:42,240 --> 00:00:44,920 Speaker 1: that we can't help but to to love our technology 12 00:00:44,920 --> 00:00:48,760 Speaker 1: and be attached to it, and eventually that will become 13 00:00:48,800 --> 00:00:51,839 Speaker 1: this idea that robots will be programmed to love us 14 00:00:51,840 --> 00:00:56,120 Speaker 1: because we just love love. Well, that that sounds sweet. 15 00:00:56,160 --> 00:00:59,000 Speaker 1: But I think you can stop love. I think love 16 00:00:59,080 --> 00:01:02,520 Speaker 1: is a very stoppable force. I think it's a virus. Yeah, 17 00:01:02,640 --> 00:01:05,920 Speaker 1: it persists. The viruses are stoppable, some of them. So 18 00:01:06,040 --> 00:01:10,120 Speaker 1: if we have the ability to to stop some forms 19 00:01:10,160 --> 00:01:11,800 Speaker 1: of love in their tracks. Because the first thing we 20 00:01:11,840 --> 00:01:14,160 Speaker 1: need to discuss is, of course, the nature of love. 21 00:01:14,680 --> 00:01:17,880 Speaker 1: What is love? Because love is a is just a 22 00:01:17,959 --> 00:01:20,560 Speaker 1: word like love is a big tent that encompasses a 23 00:01:20,640 --> 00:01:23,800 Speaker 1: lot of things. I mean, because you know, obviously there's 24 00:01:23,840 --> 00:01:26,240 Speaker 1: a loved one feels for one's wife, there's a loved 25 00:01:26,240 --> 00:01:29,720 Speaker 1: one feels for one's child. There's the love one feels 26 00:01:29,760 --> 00:01:34,000 Speaker 1: for like a really good sandwich, And these are vastly 27 00:01:34,160 --> 00:01:38,679 Speaker 1: different emotional states. Oh yeah, I think that Aristotle had 28 00:01:38,880 --> 00:01:41,959 Speaker 1: a sandwich love category. Yeah. Yeah. You can kill a 29 00:01:42,000 --> 00:01:43,920 Speaker 1: love for a sandwich if you just say, oh, well 30 00:01:43,959 --> 00:01:46,240 Speaker 1: that actually that sandwich isn't very good for you, or 31 00:01:46,480 --> 00:01:49,560 Speaker 1: those ingredients are really foul, or that restaurant got a 32 00:01:49,560 --> 00:01:51,960 Speaker 1: really crippling and a health rating. Uh, And then you 33 00:01:52,040 --> 00:01:54,040 Speaker 1: might be, oh, well, maybe I don't love this sandwich 34 00:01:54,120 --> 00:01:56,520 Speaker 1: is much, or you could over indulge in the sandwich. 35 00:01:56,880 --> 00:01:59,720 Speaker 1: Whereas it's harder to kill the love safe for you know, 36 00:01:59,760 --> 00:02:02,200 Speaker 1: for a spouse or a child or something. Just because 37 00:02:02,240 --> 00:02:04,200 Speaker 1: someone says, well, that kid's hair is a little weird. 38 00:02:04,240 --> 00:02:06,320 Speaker 1: You're not gonna be like, oh well, okay, love removed 39 00:02:07,480 --> 00:02:11,840 Speaker 1: generally generally speaking, sometimes how bad the hair is. Yeah, um, 40 00:02:11,960 --> 00:02:14,440 Speaker 1: did you know that what is love? Was the most 41 00:02:14,480 --> 00:02:17,919 Speaker 1: searched phrase on Google in two thousand and twelve. Really, 42 00:02:18,320 --> 00:02:19,959 Speaker 1: people want to know, were they looking for that song? 43 00:02:20,760 --> 00:02:24,760 Speaker 1: Isn't that what is love? Baby don't hurt? That song? 44 00:02:24,919 --> 00:02:28,679 Speaker 1: That what keeps saying it baby don't hurt me? Mm hmm, 45 00:02:28,840 --> 00:02:31,560 Speaker 1: that's all I know. Yeah, No, I don't think it 46 00:02:31,600 --> 00:02:33,680 Speaker 1: was that song, but I'm glad that we got to 47 00:02:33,800 --> 00:02:36,440 Speaker 1: get you. That might have been the searches. We're just 48 00:02:36,440 --> 00:02:40,280 Speaker 1: looking for those lyrics. It's possible, It's possible. But well, this, 49 00:02:40,280 --> 00:02:43,440 Speaker 1: this idea that people are searching for the meaning of 50 00:02:43,680 --> 00:02:48,600 Speaker 1: love had one Guardian article called what is Love talked 51 00:02:48,639 --> 00:02:52,200 Speaker 1: to several different experts about their take on love, which 52 00:02:52,240 --> 00:02:55,639 Speaker 1: was sort of interesting because again, here's this big, huge 53 00:02:55,680 --> 00:02:58,959 Speaker 1: concept that has so many different meanings and so many 54 00:02:58,960 --> 00:03:01,600 Speaker 1: different categories, and to the point where the word itself 55 00:03:01,720 --> 00:03:05,440 Speaker 1: tends to lose meaning. You know, like when someone says, oh, 56 00:03:05,480 --> 00:03:08,760 Speaker 1: I love something, it almost is a pointless thing to 57 00:03:08,840 --> 00:03:12,560 Speaker 1: say because it's such an overused word that it we've 58 00:03:12,600 --> 00:03:15,799 Speaker 1: we've just stripped it of all its power. That is true. 59 00:03:15,800 --> 00:03:18,239 Speaker 1: I was just thinking that with my daughter, I don't 60 00:03:18,280 --> 00:03:21,440 Speaker 1: like her to say the word hate. I oftentimes will say, 61 00:03:21,560 --> 00:03:23,960 Speaker 1: do you truly hate that? You know? Is it just 62 00:03:24,040 --> 00:03:27,200 Speaker 1: that you dislike it? Because that's a word that's very strong. 63 00:03:27,440 --> 00:03:30,040 Speaker 1: But I never say do you really love that? Are 64 00:03:30,040 --> 00:03:34,080 Speaker 1: you sure you love that? Because there's so much positivity 65 00:03:34,120 --> 00:03:39,400 Speaker 1: associated with it. Uh. Theoretical physicist and science writer Jim 66 00:03:39,400 --> 00:03:43,000 Speaker 1: Al Khalil had said that while lust is a temporary, 67 00:03:43,080 --> 00:03:47,120 Speaker 1: passionate sexual desire involving the increased release of chemicals like 68 00:03:47,200 --> 00:03:51,120 Speaker 1: testosterone and estrogen, he says that in true love or attachment, 69 00:03:51,160 --> 00:03:53,280 Speaker 1: in bonding, the brain can release a whole set of 70 00:03:53,320 --> 00:03:59,520 Speaker 1: chemicals pheromones, dopamine, nor epinephrin, UH, serotonin, oxytocin, embasso, pressant. So, 71 00:03:59,560 --> 00:04:02,400 Speaker 1: he says, from an evolutionary perspective, love can be viewed 72 00:04:02,520 --> 00:04:05,640 Speaker 1: as a survival tool, a mechanism that we evolve to 73 00:04:05,640 --> 00:04:09,880 Speaker 1: promote long term relationships, mutual defense and parental support of children, 74 00:04:09,960 --> 00:04:13,880 Speaker 1: and to promote feelings of safe safety insecurity. Yeah. So 75 00:04:13,920 --> 00:04:17,120 Speaker 1: it's basically a chemical bond to things that enable us 76 00:04:17,160 --> 00:04:20,880 Speaker 1: to better perform our genetic mission as organisms. There are 77 00:04:20,960 --> 00:04:23,680 Speaker 1: several different versions of love. They're laid out in this 78 00:04:23,920 --> 00:04:28,000 Speaker 1: this particular article. For instance, there's philia, the deep non 79 00:04:28,120 --> 00:04:32,520 Speaker 1: sexual intimacy between close friends or family members or soldiers 80 00:04:32,520 --> 00:04:35,600 Speaker 1: in the trench. You know, it's uh, it's this this 81 00:04:35,720 --> 00:04:39,040 Speaker 1: bond of love that's you know, not sexual, not romantic, 82 00:04:39,080 --> 00:04:42,440 Speaker 1: but it's it's you know, it's your your your bros 83 00:04:42,560 --> 00:04:46,240 Speaker 1: kind of you know kind of love, bras bras bra love. 84 00:04:46,720 --> 00:04:50,240 Speaker 1: I guess, Okay, Yeah, then there's a there's a lotus 85 00:04:50,480 --> 00:04:54,080 Speaker 1: playful affection that found in fooling around or flirting. Now 86 00:04:54,120 --> 00:04:57,159 Speaker 1: this one is I guess a little harder to like 87 00:04:57,279 --> 00:04:58,760 Speaker 1: nail that. I mean, I guess I can think of 88 00:04:58,920 --> 00:05:01,120 Speaker 1: some past example to that, you know, where you're kind 89 00:05:01,160 --> 00:05:04,400 Speaker 1: of like flirty with somebody, but you're not really going 90 00:05:04,480 --> 00:05:07,039 Speaker 1: after them per se. You know that it doesn't seem 91 00:05:07,040 --> 00:05:08,920 Speaker 1: to be much to that one, right, because that's such 92 00:05:08,920 --> 00:05:11,640 Speaker 1: an ephemeral stage. Yeah, it's kind of like like that 93 00:05:11,680 --> 00:05:13,920 Speaker 1: one's just like I mean, that one can be killed 94 00:05:13,920 --> 00:05:16,040 Speaker 1: by the sobering up a bit. I think, you know, 95 00:05:16,160 --> 00:05:19,160 Speaker 1: like that's not it's barely love. It seems a little 96 00:05:19,200 --> 00:05:21,440 Speaker 1: cheap to even classify it as a form of love, 97 00:05:21,520 --> 00:05:25,360 Speaker 1: doesn't it. Yeah, then there's a pragma, the mature love 98 00:05:25,360 --> 00:05:27,960 Speaker 1: that develops over a long period of time between long 99 00:05:28,080 --> 00:05:31,479 Speaker 1: term couples. Uh. And this and this is really you know, 100 00:05:31,520 --> 00:05:33,640 Speaker 1: when people talk about all that deep love that grows 101 00:05:33,680 --> 00:05:36,800 Speaker 1: out of relationship because the relationship maybe may begin with 102 00:05:36,960 --> 00:05:39,400 Speaker 1: lust or even this lootus thing we're talking about, or 103 00:05:39,400 --> 00:05:42,200 Speaker 1: it may be begin with philia, but over time it 104 00:05:42,240 --> 00:05:46,320 Speaker 1: develops into this strong bond, this bond where it's it's 105 00:05:46,400 --> 00:05:48,640 Speaker 1: built over time and in a way that it just 106 00:05:48,680 --> 00:05:51,680 Speaker 1: can't be uh, you know, pulled off a shelf, and 107 00:05:51,880 --> 00:05:56,200 Speaker 1: it involves just a lot of goodwill towards another person. 108 00:05:56,279 --> 00:05:59,479 Speaker 1: It's like wanting the best for someone regardless of the cost. 109 00:05:59,680 --> 00:06:02,280 Speaker 1: So you might not have a huge surge in dopamine 110 00:06:02,560 --> 00:06:06,560 Speaker 1: or vasopressin um or even oxytocin, but it's there. It's 111 00:06:06,560 --> 00:06:09,400 Speaker 1: still you know, from from a chemical level, is still 112 00:06:09,440 --> 00:06:12,200 Speaker 1: sort of running behind the scenes. Uh. Then there's a 113 00:06:12,200 --> 00:06:16,440 Speaker 1: cape the more generalized love that I remember hearing a 114 00:06:16,440 --> 00:06:18,240 Speaker 1: lot about in church. That's kind of like this sort 115 00:06:18,240 --> 00:06:21,440 Speaker 1: of universal love love everybody, love your neighbor, right, even 116 00:06:21,480 --> 00:06:24,320 Speaker 1: if it doesn't seem practical. Uh, it's just kind of 117 00:06:24,320 --> 00:06:28,680 Speaker 1: an idealized, good natured, be cool of everyone, which you know, 118 00:06:29,400 --> 00:06:30,720 Speaker 1: there is a good, good way to look at the 119 00:06:30,720 --> 00:06:32,360 Speaker 1: world if you can, if you can do it, Yeah, 120 00:06:32,400 --> 00:06:34,880 Speaker 1: it's kind of the seventies love hug. Then there is 121 00:06:34,960 --> 00:06:40,400 Speaker 1: self love or philapia, which is uh is maybe not 122 00:06:40,440 --> 00:06:42,880 Speaker 1: as selfish as it sounds, to be clear, and not 123 00:06:43,000 --> 00:06:46,040 Speaker 1: talking about self love in the sexual context either, no, no, no, 124 00:06:46,040 --> 00:06:49,799 Speaker 1: no no no. Um and uh yeah, this just means uh, 125 00:06:50,200 --> 00:06:51,560 Speaker 1: I mean you can break it down to the fact 126 00:06:51,600 --> 00:06:52,880 Speaker 1: that if you're gonna care about others, you need to 127 00:06:52,920 --> 00:06:55,040 Speaker 1: be able to care about yourself. And then there's of 128 00:06:55,040 --> 00:06:59,480 Speaker 1: course eros sexual passion and desire. Uh. And you know, 129 00:06:59,600 --> 00:07:02,120 Speaker 1: and this is again when people talk about love at 130 00:07:02,120 --> 00:07:06,160 Speaker 1: first sight in terms of a male female romantic relationship, 131 00:07:06,440 --> 00:07:09,200 Speaker 1: this is often what they're actually talking about. I believe 132 00:07:09,240 --> 00:07:11,320 Speaker 1: you know, they're they're talking about arrows. They're talking about 133 00:07:11,520 --> 00:07:16,160 Speaker 1: lust and physical attraction, sexual attraction that may again eventually 134 00:07:16,240 --> 00:07:18,600 Speaker 1: morph into some other form of love or just fall 135 00:07:18,640 --> 00:07:20,760 Speaker 1: off entirely. Yeah. That's what I feel it should be 136 00:07:20,800 --> 00:07:23,239 Speaker 1: astrict like, it's not really a form of love unless 137 00:07:23,280 --> 00:07:26,960 Speaker 1: it becomes philia or pragma, yeah, or some other type 138 00:07:26,960 --> 00:07:30,800 Speaker 1: of love. It's more like a pre love secretion or 139 00:07:30,840 --> 00:07:33,200 Speaker 1: something I don't know, depends that you want to secretion. Yeah, 140 00:07:34,000 --> 00:07:37,960 Speaker 1: Because again we're talking a lot about about hormones flowing 141 00:07:38,080 --> 00:07:41,320 Speaker 1: about about you know, your hormonal response to a potential 142 00:07:41,360 --> 00:07:45,040 Speaker 1: may your hormonal response to um, you know, an infant, 143 00:07:45,040 --> 00:07:48,560 Speaker 1: a child, you know, some sort of offspring. There's there's 144 00:07:48,560 --> 00:07:50,160 Speaker 1: a lot of secreting going on. There is a lot 145 00:07:50,160 --> 00:07:52,600 Speaker 1: of secreting, and you can't really secrete all of those 146 00:07:52,640 --> 00:07:54,920 Speaker 1: for just one person, right, all those different types of love. 147 00:07:55,200 --> 00:07:57,720 Speaker 1: I mean, perhaps there's that one rare person in your 148 00:07:57,800 --> 00:08:00,760 Speaker 1: life that can take on all those roles of love, 149 00:08:00,880 --> 00:08:04,960 Speaker 1: but most likely your family, your friends, your community take 150 00:08:05,040 --> 00:08:08,360 Speaker 1: on all these different aspects of it. In this article, 151 00:08:08,360 --> 00:08:10,600 Speaker 1: they also talk to a philosopher to talk about love 152 00:08:10,640 --> 00:08:13,760 Speaker 1: as a passionate commitment, which really kind of flows in 153 00:08:13,840 --> 00:08:16,760 Speaker 1: with the with the progment we were talking about. Yep, 154 00:08:16,800 --> 00:08:19,000 Speaker 1: it says that we have to This is from Julian Baggini. 155 00:08:19,040 --> 00:08:21,720 Speaker 1: The philosopher said that we need to nurture and develop it, 156 00:08:21,840 --> 00:08:25,880 Speaker 1: even though it usually arrives in our lives unbidden. So 157 00:08:26,360 --> 00:08:29,480 Speaker 1: you take this idea of what love could be, and 158 00:08:29,520 --> 00:08:33,200 Speaker 1: then you begin to think about how we love objects 159 00:08:33,320 --> 00:08:36,680 Speaker 1: or things, and I started to think about this idea 160 00:08:36,760 --> 00:08:41,960 Speaker 1: of apophenia. Now, apophenia is um this sort of unmotivated 161 00:08:42,000 --> 00:08:47,800 Speaker 1: seeing of a connection and a specific feeling of abnormal meaningfulness. 162 00:08:47,800 --> 00:08:50,480 Speaker 1: That we ascribed to an object, and this was defined 163 00:08:50,520 --> 00:08:54,120 Speaker 1: by German neurologists and psychologist Clause Conrad. So that means 164 00:08:54,120 --> 00:08:56,200 Speaker 1: when you look at an inanimate object and you see 165 00:08:56,240 --> 00:08:58,480 Speaker 1: what looks like a pair of eyes and a nose 166 00:08:58,520 --> 00:09:00,760 Speaker 1: in the mouth, you're unconsciously try to make sense of 167 00:09:00,760 --> 00:09:03,240 Speaker 1: the data in front of you, and you're describing it 168 00:09:03,280 --> 00:09:06,679 Speaker 1: with something that is not what it actually is. Right, 169 00:09:06,679 --> 00:09:09,720 Speaker 1: But it's our human context that we're bringing with us 170 00:09:09,760 --> 00:09:11,560 Speaker 1: all the time, So we can't help to sort of 171 00:09:11,600 --> 00:09:16,160 Speaker 1: project those humanness feelings onto something. Yeah, and um, as 172 00:09:16,160 --> 00:09:19,679 Speaker 1: you've brought up before, the we have this surprising ability 173 00:09:19,720 --> 00:09:21,920 Speaker 1: to see faces like you really you don't have to 174 00:09:21,960 --> 00:09:24,640 Speaker 1: put a smiley face even on something to give it 175 00:09:24,679 --> 00:09:26,600 Speaker 1: this sense of person and give it, I mean we can. 176 00:09:26,800 --> 00:09:29,200 Speaker 1: We We glimpse faces in the clouds, we glimpse faces 177 00:09:29,240 --> 00:09:31,560 Speaker 1: on the moon, and it's all just kind of this, uh, 178 00:09:31,640 --> 00:09:35,800 Speaker 1: you know, this atavistic resonance where our pattern seeking brains 179 00:09:36,040 --> 00:09:38,360 Speaker 1: are looking for things that affect us and what would 180 00:09:38,360 --> 00:09:40,720 Speaker 1: affect us more than it's ap peering into the night 181 00:09:40,800 --> 00:09:43,440 Speaker 1: and seeing the face of man or beast, you know, 182 00:09:43,760 --> 00:09:46,319 Speaker 1: lurching there in the dark, that would be some vital 183 00:09:46,360 --> 00:09:49,040 Speaker 1: information you need to know because friend or foe is 184 00:09:49,040 --> 00:09:52,839 Speaker 1: is right upon you. Yeah. Actually, Sonia Wynn Hager, she's 185 00:09:52,840 --> 00:09:55,480 Speaker 1: an anthropologist at the University of Vienna, said in an 186 00:09:55,480 --> 00:09:58,840 Speaker 1: interview with Life Science that this tendency would have likely 187 00:09:58,960 --> 00:10:01,520 Speaker 1: protected our ants susters and she said taking a bear 188 00:10:01,559 --> 00:10:05,320 Speaker 1: for a stone might be lethal, but the opposite does 189 00:10:05,400 --> 00:10:07,480 Speaker 1: no harm. Yeah, you get down to that whole thing 190 00:10:07,520 --> 00:10:10,119 Speaker 1: of that whole situation with type one and type two airs. 191 00:10:10,200 --> 00:10:12,800 Speaker 1: You know, one air means that, oh, you got me, 192 00:10:12,840 --> 00:10:14,880 Speaker 1: You're not actually a bear trying to eat me, and 193 00:10:14,920 --> 00:10:18,240 Speaker 1: the other air is, um, oh you're actually a bear 194 00:10:18,320 --> 00:10:21,160 Speaker 1: and you just devoured me. So which one, obviously does 195 00:10:21,240 --> 00:10:23,400 Speaker 1: evolution end up selected? Yeah, what's the error that you're 196 00:10:23,400 --> 00:10:25,640 Speaker 1: going to have? And so then you have this apophenia, 197 00:10:25,760 --> 00:10:29,080 Speaker 1: this pattern recognition, seeing patterns everywhere, and you meld that 198 00:10:29,160 --> 00:10:33,680 Speaker 1: together with anthropomorphism, and that's giving human characteristics to animals 199 00:10:33,679 --> 00:10:39,160 Speaker 1: and inanimate objects, and you begin to see that as humans, 200 00:10:39,200 --> 00:10:42,040 Speaker 1: we are going to maybe shovel off some of our 201 00:10:42,200 --> 00:10:45,839 Speaker 1: emotions onto these objects. And I wanted to bring up 202 00:10:45,960 --> 00:10:50,120 Speaker 1: this study that wind Hagger and her colleagues UH conducted 203 00:10:50,160 --> 00:10:54,079 Speaker 1: this this tendency for us to actually personify cars. Now, 204 00:10:54,280 --> 00:10:59,040 Speaker 1: she conducted this this study, and auto never understood. You know, 205 00:10:59,080 --> 00:11:01,520 Speaker 1: it happens all the time, especially in TV shows where 206 00:11:01,520 --> 00:11:03,959 Speaker 1: someone's got a car and it's got this this lady's 207 00:11:04,040 --> 00:11:08,319 Speaker 1: name night Rider. Well but that was what kit I think, yes, 208 00:11:08,480 --> 00:11:11,960 Speaker 1: that that car actually talked and had personality and uh, 209 00:11:12,040 --> 00:11:13,760 Speaker 1: and they loved each other. But it's that that's the 210 00:11:13,800 --> 00:11:16,240 Speaker 1: fantasy of the relationship that some people want to have 211 00:11:16,360 --> 00:11:19,600 Speaker 1: with their cars. I guess it comes off kind of 212 00:11:19,600 --> 00:11:22,960 Speaker 1: cree creepy though, sometimes because it's like talking about his 213 00:11:23,040 --> 00:11:25,680 Speaker 1: car in his fancy car has like a lady's name, 214 00:11:25,880 --> 00:11:29,079 Speaker 1: and it's like there's an implied relationship there. That's kind 215 00:11:29,080 --> 00:11:32,360 Speaker 1: of weird. Do do do do do? Do? Do? Do? Do? 216 00:11:32,440 --> 00:11:35,520 Speaker 1: Do do do? All right, So, I mean people do 217 00:11:35,559 --> 00:11:38,400 Speaker 1: have relationship with her with their cars. My daughter loves 218 00:11:38,480 --> 00:11:40,920 Speaker 1: our car and she kisses it. It's very odd. Does 219 00:11:40,920 --> 00:11:44,360 Speaker 1: it have a name though? Yeah? What Lightning the queen 220 00:11:45,400 --> 00:11:48,160 Speaker 1: from the movie Cars, which probably has something to do 221 00:11:48,160 --> 00:11:51,000 Speaker 1: with it. Right, Actually, the whole movie is that the 222 00:11:51,080 --> 00:11:54,880 Speaker 1: animation is a great example of anthropomorphizing. Oh yeah, yeah, totally. 223 00:11:55,240 --> 00:11:59,440 Speaker 1: Um alright, so whin Haggar's study in Austria that she 224 00:11:59,559 --> 00:12:02,080 Speaker 1: reported in two thousand and eight that people attribute human 225 00:12:02,080 --> 00:12:04,440 Speaker 1: traits to vehicles based on factors such as the shape 226 00:12:04,440 --> 00:12:07,160 Speaker 1: of the headlights and the size of the windshield because 227 00:12:07,400 --> 00:12:11,360 Speaker 1: as you've got the mouth there with the grill. She 228 00:12:11,480 --> 00:12:14,320 Speaker 1: then took the study to rural Ethiopia where there would 229 00:12:14,320 --> 00:12:16,800 Speaker 1: be less of a context right for for some of 230 00:12:16,840 --> 00:12:20,840 Speaker 1: the ways that we operate in terms of car commercials 231 00:12:20,840 --> 00:12:23,880 Speaker 1: and all all that sorts of stuff, And she found 232 00:12:23,960 --> 00:12:28,000 Speaker 1: out that the eighty nine Ethiopians who compared forty nine 233 00:12:28,040 --> 00:12:31,640 Speaker 1: renderings of cars along with nineteen different human traits including gender, 234 00:12:32,120 --> 00:12:35,959 Speaker 1: also saw the cars in a very human way, and 235 00:12:36,440 --> 00:12:40,320 Speaker 1: cars with slit like wide set headlights were judged as male, 236 00:12:40,840 --> 00:12:45,600 Speaker 1: adult and dominant by both Austrians and Ethiopians, as were 237 00:12:45,679 --> 00:12:50,440 Speaker 1: cars with smaller windshields and wider faces and smaller eyes 238 00:12:50,480 --> 00:12:54,800 Speaker 1: and foreheads. Again, the foreheads equivalent to the car windshield 239 00:12:55,040 --> 00:12:58,400 Speaker 1: were considered to be more masculine features and human faces. 240 00:12:58,480 --> 00:13:02,080 Speaker 1: So they down that the cars that were considered childlike 241 00:13:02,160 --> 00:13:06,760 Speaker 1: we're also considered more feminine, and this included closer set 242 00:13:06,800 --> 00:13:10,440 Speaker 1: headlights and larger windshields. So interesting to see these two 243 00:13:10,440 --> 00:13:15,680 Speaker 1: different cultures both ascribing human qualities to this. So yeah, 244 00:13:15,720 --> 00:13:20,360 Speaker 1: there's there's all sorts of weird emotional landscape here wrapped 245 00:13:20,440 --> 00:13:23,640 Speaker 1: up and and de humanization and anthropomorphism, and those are 246 00:13:23,640 --> 00:13:27,000 Speaker 1: really that's the same movement in different directions. I am 247 00:13:27,000 --> 00:13:30,040 Speaker 1: either adding personhood to something that is not a person, 248 00:13:30,120 --> 00:13:32,880 Speaker 1: or am I taking personhood away from something that is 249 00:13:33,360 --> 00:13:35,480 Speaker 1: uh is a person or a head to some degree 250 00:13:35,520 --> 00:13:37,560 Speaker 1: as a person. And then there's the whole person's head 251 00:13:37,559 --> 00:13:41,320 Speaker 1: thing and yeah, which we all right, let's take a 252 00:13:41,320 --> 00:13:43,520 Speaker 1: break and when we get back, we will talk about 253 00:13:43,840 --> 00:13:59,280 Speaker 1: loving robots. All right, Hey, we're back. We're talking about anthromorphism, uh, 254 00:13:59,520 --> 00:14:04,040 Speaker 1: persona vacation. We're taking objects and we're making them worthy 255 00:14:04,040 --> 00:14:08,520 Speaker 1: of concern, protection, punishment, reward. Um we can as humans, 256 00:14:08,640 --> 00:14:11,959 Speaker 1: we have this innate ability to personify anything. A pencil, 257 00:14:12,040 --> 00:14:14,440 Speaker 1: a computer, a coffee table. We you know, we we 258 00:14:14,480 --> 00:14:16,840 Speaker 1: get mad at a computer that's misbehaving on us. We 259 00:14:16,880 --> 00:14:20,800 Speaker 1: start the shouting at it, calling it names. Uh, I've 260 00:14:20,960 --> 00:14:23,120 Speaker 1: stubbed my toe on a coffee table, and I treat 261 00:14:23,160 --> 00:14:25,040 Speaker 1: the coffee table like it's an enemy, Like I want 262 00:14:25,040 --> 00:14:28,640 Speaker 1: to attack it for attacking me. Many coffee tables are 263 00:14:28,680 --> 00:14:31,320 Speaker 1: the enemy. Yeah, um yeah, And if you look at 264 00:14:31,360 --> 00:14:34,680 Speaker 1: that car study, then you can easily extrapolate that that, 265 00:14:35,000 --> 00:14:38,400 Speaker 1: you know, us us humans connecting with robots would just 266 00:14:38,480 --> 00:14:42,560 Speaker 1: be a logical conclusion, right exactly. But yeah, but we're 267 00:14:42,560 --> 00:14:45,880 Speaker 1: getting into this stage where we are using robots. I 268 00:14:45,880 --> 00:14:48,360 Speaker 1: mean already I have a robot vacuum cleaner in my house, 269 00:14:48,920 --> 00:14:51,680 Speaker 1: you know, and uh and in their robot mont lawn mowers. 270 00:14:51,680 --> 00:14:53,760 Speaker 1: We're looking at a future where robots will help care 271 00:14:53,800 --> 00:14:56,200 Speaker 1: for our elderly. They're going to be in our hospitals, 272 00:14:56,200 --> 00:14:58,840 Speaker 1: they're gonna be on our streets, and we're gonna be 273 00:14:58,880 --> 00:15:02,200 Speaker 1: interacting with them all the time. So the same model applies. 274 00:15:02,360 --> 00:15:05,040 Speaker 1: We We don't need to become more like robots to 275 00:15:05,120 --> 00:15:08,080 Speaker 1: interact with the robots that care for us and and 276 00:15:08,080 --> 00:15:10,880 Speaker 1: and do all these tasks. We want the robots to 277 00:15:11,000 --> 00:15:14,200 Speaker 1: at least meet us halfway well and meeting us halfway. 278 00:15:14,200 --> 00:15:16,240 Speaker 1: I'm glad you brought that up because it reminded me 279 00:15:16,400 --> 00:15:19,200 Speaker 1: of an episode that we did called Living with Robots, 280 00:15:19,200 --> 00:15:23,080 Speaker 1: and which we talked about the Lyric Project. And in 281 00:15:23,120 --> 00:15:26,680 Speaker 1: the Lyric Project, they had something called the Robot House. 282 00:15:26,720 --> 00:15:29,480 Speaker 1: Not to be confused with Robot House from Futurama, which 283 00:15:29,480 --> 00:15:33,920 Speaker 1: was a robot the fraternity, right, and this is not 284 00:15:34,040 --> 00:15:36,080 Speaker 1: also a new reality show by the way, at least 285 00:15:36,280 --> 00:15:38,360 Speaker 1: not yet. It would be great, they should do it, 286 00:15:38,560 --> 00:15:41,000 Speaker 1: but yeah, five weeks in the Robot House. Some some 287 00:15:41,040 --> 00:15:45,240 Speaker 1: study participants took uh their place in this house and 288 00:15:45,360 --> 00:15:47,640 Speaker 1: what they tried to figure out in this domestic setting 289 00:15:47,840 --> 00:15:52,920 Speaker 1: is how annoyed with humans get when robots were programmed 290 00:15:52,920 --> 00:15:56,440 Speaker 1: to sort of get in their space or not hand 291 00:15:56,440 --> 00:15:59,560 Speaker 1: them something in the time that they expected the human 292 00:15:59,600 --> 00:16:02,200 Speaker 1: expected the robot to hand them something. Yeah. Well, one 293 00:16:02,240 --> 00:16:04,080 Speaker 1: great example is when we came back from our break, 294 00:16:04,120 --> 00:16:07,800 Speaker 1: we both spoke at the same time, and our typical responses, oh, 295 00:16:07,840 --> 00:16:10,120 Speaker 1: I'm sorry, you go first, and you're like, oh no, no, 296 00:16:10,160 --> 00:16:12,480 Speaker 1: you go first, but you finished. But did try to 297 00:16:12,520 --> 00:16:15,160 Speaker 1: match you there for a bit. But with a robot. 298 00:16:15,560 --> 00:16:17,360 Speaker 1: One of the examples that often pointed out like, say 299 00:16:17,400 --> 00:16:19,440 Speaker 1: you and a robot reach for the same object at 300 00:16:19,480 --> 00:16:23,600 Speaker 1: the same time. Now, when humans do this, the typical 301 00:16:23,680 --> 00:16:26,000 Speaker 1: response is going to be, oh, I'm sorry, you were 302 00:16:26,000 --> 00:16:28,080 Speaker 1: reaching for that. You go ahead, you go ahead and 303 00:16:28,120 --> 00:16:30,360 Speaker 1: have some of those snacks. I'll hold up. And then 304 00:16:30,400 --> 00:16:31,760 Speaker 1: the other person will say no, no no, no, you do 305 00:16:31,800 --> 00:16:33,800 Speaker 1: it now the robot. Is the robot gonna have any 306 00:16:33,840 --> 00:16:36,920 Speaker 1: kind of programming that allows for that kind of consideration, 307 00:16:37,000 --> 00:16:39,440 Speaker 1: or the robot simply gonna grab the snacks and then 308 00:16:39,480 --> 00:16:43,760 Speaker 1: the human not realizing and you know, certainly the human 309 00:16:43,840 --> 00:16:47,240 Speaker 1: is anthromomorphizing. They're they're they're regarding this machine as some 310 00:16:47,280 --> 00:16:49,880 Speaker 1: sort of a human entity to some degree. How are 311 00:16:49,880 --> 00:16:51,360 Speaker 1: they going to react? They're gonna think, oh, well, that's 312 00:16:51,360 --> 00:16:53,920 Speaker 1: stinchy robot trying to get these snacks before I can 313 00:16:53,960 --> 00:16:56,560 Speaker 1: have some. That's totally rude. So how do you You 314 00:16:56,600 --> 00:16:59,280 Speaker 1: have to start thinking of ways to program the robot 315 00:16:59,400 --> 00:17:03,560 Speaker 1: to behave in a human capacity and even these small 316 00:17:04,119 --> 00:17:10,040 Speaker 1: little interactions just to avoid sort of subliminal hostility blossoming up. Yeah, 317 00:17:10,080 --> 00:17:11,840 Speaker 1: because what they found in this study is that people 318 00:17:11,920 --> 00:17:13,960 Speaker 1: did start to think that the robots were doing things 319 00:17:14,080 --> 00:17:17,760 Speaker 1: on purpose and and really starting to get angry with them. 320 00:17:17,800 --> 00:17:20,679 Speaker 1: And this is not just a crazy one off experiment. 321 00:17:20,720 --> 00:17:25,719 Speaker 1: That's really this This field of human robotics interaction, uh, 322 00:17:26,080 --> 00:17:28,520 Speaker 1: is something that's only like a decade old. But the 323 00:17:28,520 --> 00:17:32,080 Speaker 1: reason is there is because it is forthcoming, and you know, 324 00:17:32,240 --> 00:17:33,280 Speaker 1: you do want some