1 00:00:03,800 --> 00:00:06,680 Speaker 1: Welcome to Stuff to Blow Your Mind from how Stuff 2 00:00:06,680 --> 00:00:13,920 Speaker 1: Works dot com. Hey, welcome to Stuff to Blow your Mind. 3 00:00:13,960 --> 00:00:16,759 Speaker 1: My name is Robert Lamb and I'm Julie Douglas. And 4 00:00:17,079 --> 00:00:21,160 Speaker 1: you know, Julie, the title of today's podcast is does 5 00:00:21,239 --> 00:00:25,560 Speaker 1: my dog really Love Me? Or something to that effects. Yeah, 6 00:00:25,600 --> 00:00:27,520 Speaker 1: we just nailed it down, but over forgot it. But 7 00:00:27,520 --> 00:00:30,480 Speaker 1: but the original title that I had pitched was your 8 00:00:30,520 --> 00:00:32,280 Speaker 1: dog doesn't love you? And we decided not to go 9 00:00:32,320 --> 00:00:35,520 Speaker 1: with that because, uh, it's it's a little anti dog 10 00:00:35,560 --> 00:00:37,000 Speaker 1: and I didn't want to come up with this dog 11 00:00:37,040 --> 00:00:39,440 Speaker 1: hating cat person. Well, and the jury is a little 12 00:00:39,479 --> 00:00:42,240 Speaker 1: bit out on that, right. Yeah, we can't definitively say 13 00:00:42,280 --> 00:00:45,160 Speaker 1: your dog doesn't love you, because there's some interesting data. 14 00:00:45,320 --> 00:00:46,680 Speaker 1: So I just want to point out that if you're 15 00:00:46,720 --> 00:00:49,839 Speaker 1: Josh Clark, you can apparently definitively say that dogs are 16 00:00:49,920 --> 00:00:52,800 Speaker 1: man's best friend and quote, even if you're strictly a 17 00:00:52,840 --> 00:00:55,600 Speaker 1: bona fied cat lover, it's nearly impossible not to be 18 00:00:55,680 --> 00:00:58,600 Speaker 1: moved by the brand of loyalty unique to dogs. That's 19 00:00:58,640 --> 00:01:02,760 Speaker 1: from Josh's How to Work's article um is Our Dogs 20 00:01:02,800 --> 00:01:06,000 Speaker 1: trully Man's Best Friends, which is worth reading but but, 21 00:01:06,000 --> 00:01:08,080 Speaker 1: but Josh has a bit of a thing and for cats. 22 00:01:08,080 --> 00:01:09,520 Speaker 1: I think he was licked by them as a child 23 00:01:09,600 --> 00:01:11,920 Speaker 1: or something. I think so too, he was afraid they 24 00:01:11,920 --> 00:01:14,039 Speaker 1: were going to steal his breath. Yeah, but but I 25 00:01:14,080 --> 00:01:16,560 Speaker 1: admit I I tend to side more with the with 26 00:01:16,600 --> 00:01:20,160 Speaker 1: the cat uh on the on the cat's side of 27 00:01:20,160 --> 00:01:22,480 Speaker 1: of the old dogs versus cat's argument. And I'm not 28 00:01:22,480 --> 00:01:24,200 Speaker 1: trying to stir up a big debate because I think 29 00:01:24,200 --> 00:01:27,000 Speaker 1: there's a lot of crossover between the affinity we have 30 00:01:27,480 --> 00:01:33,040 Speaker 1: for our animals and the the the the often ridiculous 31 00:01:33,120 --> 00:01:35,120 Speaker 1: ideas we get in our head about what they are 32 00:01:35,200 --> 00:01:38,119 Speaker 1: and what our relationship with him consists of. Oh, you're 33 00:01:38,120 --> 00:01:41,880 Speaker 1: talking about anthropomorphosizing, where we project all of our feelings 34 00:01:41,959 --> 00:01:46,280 Speaker 1: onto cat, dogs, sometimes a robot you name it. Yeah, 35 00:01:46,360 --> 00:01:48,400 Speaker 1: And there's but the interesting things, there's been a lot 36 00:01:48,400 --> 00:01:51,520 Speaker 1: of studies and exactly what's going on beyond beyond the 37 00:01:51,560 --> 00:01:56,280 Speaker 1: whole This dog is my child, this dog is my friend, um, 38 00:01:56,320 --> 00:01:58,560 Speaker 1: you know that they're There's been some actual studies into 39 00:01:58,560 --> 00:02:00,200 Speaker 1: what's going on in the brain when we inter act 40 00:02:00,240 --> 00:02:02,800 Speaker 1: with dogs. What's what's going on in the dog's brain 41 00:02:02,840 --> 00:02:06,200 Speaker 1: when it's interacting with us, and uh and and and 42 00:02:06,520 --> 00:02:08,920 Speaker 1: you know, there's no denying that these are amazing creatures. 43 00:02:08,960 --> 00:02:11,120 Speaker 1: And in the relationship they have with us is is 44 00:02:11,160 --> 00:02:16,400 Speaker 1: pretty bizarre. Uh and and and pretty incredible. They've You 45 00:02:16,480 --> 00:02:19,680 Speaker 1: have you have a a a species that just lives 46 00:02:19,720 --> 00:02:24,200 Speaker 1: throughout the world, often in luxurious environment. Well sometimes they're 47 00:02:24,200 --> 00:02:26,960 Speaker 1: not so luxurious environments. But but you have some dogs 48 00:02:26,960 --> 00:02:30,200 Speaker 1: that are really living well and and really benefiting from 49 00:02:30,240 --> 00:02:33,280 Speaker 1: from all the fruits of human culture without actually having 50 00:02:33,360 --> 00:02:35,680 Speaker 1: to do any work. Yeah, well, let me just spring 51 00:02:35,680 --> 00:02:38,280 Speaker 1: this little stat on you. According to the Nova documentary 52 00:02:38,320 --> 00:02:41,280 Speaker 1: Dogs Decoded, there are more pet dogs than babies in 53 00:02:41,280 --> 00:02:46,200 Speaker 1: the world, nearly half a billion. So yeah, of course 54 00:02:46,240 --> 00:02:49,880 Speaker 1: they've got their own clothes and furniture, and you know, 55 00:02:50,000 --> 00:02:53,080 Speaker 1: they've got their own little dinner plates. And according to 56 00:02:53,360 --> 00:02:58,079 Speaker 1: um Um The World Without Us author Alan Wiseman, if 57 00:02:58,240 --> 00:03:01,160 Speaker 1: humans civilization were to stop, tom most of these dogs 58 00:03:01,160 --> 00:03:04,760 Speaker 1: would just vanish, because it's it's we'll not vanished, you know, 59 00:03:04,880 --> 00:03:06,920 Speaker 1: like it's not like not like the you know, the 60 00:03:06,960 --> 00:03:09,280 Speaker 1: Second Coming and the Rapture and all that. But but 61 00:03:09,320 --> 00:03:11,480 Speaker 1: they would they would die out pretty because pretty steadily 62 00:03:11,560 --> 00:03:14,160 Speaker 1: in most cases, because they wouldn't be able to support themselves. 63 00:03:14,200 --> 00:03:16,359 Speaker 1: They wouldn't be able to feed themselves in the environment 64 00:03:16,680 --> 00:03:19,160 Speaker 1: like that depend on Yeah, they depended on us. I 65 00:03:19,160 --> 00:03:21,720 Speaker 1: mean likewise with the cats, most a lot of the 66 00:03:21,720 --> 00:03:24,200 Speaker 1: cats would die and others would just become feral because 67 00:03:24,240 --> 00:03:27,040 Speaker 1: we've created these these artificial environments and we've propped up 68 00:03:27,080 --> 00:03:30,000 Speaker 1: these these species and allow them to just run wild, 69 00:03:30,440 --> 00:03:32,560 Speaker 1: you know, around the world, even if running wild is 70 00:03:32,560 --> 00:03:34,840 Speaker 1: only in your living room, in your backyard, right right, 71 00:03:35,120 --> 00:03:37,000 Speaker 1: I mean we can't help it because we look at 72 00:03:37,040 --> 00:03:39,920 Speaker 1: these dogs, we look at puppies, and we instantly feel 73 00:03:39,920 --> 00:03:44,440 Speaker 1: a connection. Right. We already know that this is scientifically proven. Yes, 74 00:03:44,760 --> 00:03:48,400 Speaker 1: we've in fact, we've we've seen the release of oxytocin 75 00:03:48,480 --> 00:03:52,440 Speaker 1: in the brain when well in two cases. One when 76 00:03:52,440 --> 00:03:54,400 Speaker 1: we're just interacting with their dogs and we're making a 77 00:03:55,920 --> 00:04:01,360 Speaker 1: long gaze um eye interaction, which is like we lock eyes. Yeah. 78 00:04:01,400 --> 00:04:04,320 Speaker 1: There's a two thousand and nine um Japanese study and 79 00:04:04,360 --> 00:04:06,680 Speaker 1: they took fifty five dog owners, all right, they brought 80 00:04:06,720 --> 00:04:09,080 Speaker 1: them in and they had all the dog owners peanut 81 00:04:09,120 --> 00:04:11,920 Speaker 1: up and then they tested that sounds nice, tested the 82 00:04:12,040 --> 00:04:15,920 Speaker 1: urine for oxytocin levels, and then they put them in 83 00:04:15,960 --> 00:04:18,080 Speaker 1: the playroom, let them play with their dogs all right, 84 00:04:18,080 --> 00:04:20,400 Speaker 1: and then they observed how they're interacting with their pets. 85 00:04:20,839 --> 00:04:22,640 Speaker 1: Then the dog owners came back in and they took 86 00:04:22,640 --> 00:04:25,400 Speaker 1: another yearine sample um which I guess they had to 87 00:04:25,440 --> 00:04:27,359 Speaker 1: have a drink while they're in there playing with their dogs. 88 00:04:27,960 --> 00:04:30,080 Speaker 1: I don't think i'd be able to go twice like that. 89 00:04:30,560 --> 00:04:33,719 Speaker 1: And and and they were able. And they also had 90 00:04:33,760 --> 00:04:36,360 Speaker 1: a control group where some owners sat in a room 91 00:04:36,400 --> 00:04:38,480 Speaker 1: with their dog and we're told to completely avoid looking 92 00:04:38,520 --> 00:04:41,760 Speaker 1: at their animal. So uh so that that they found 93 00:04:41,760 --> 00:04:46,160 Speaker 1: that that there was a increase in oxytocin levels. And 94 00:04:46,160 --> 00:04:49,240 Speaker 1: the people who made long gaze eye contact with their dog, 95 00:04:49,320 --> 00:04:52,200 Speaker 1: that's where they're looking on average, you know, two and 96 00:04:52,200 --> 00:04:56,040 Speaker 1: a half minutes of eye contact during play. And uh 97 00:04:56,240 --> 00:04:59,080 Speaker 1: and and so the people were benefiting from this, from 98 00:04:59,080 --> 00:05:02,040 Speaker 1: this this relation ship. They're feeling really good about it. 99 00:05:02,040 --> 00:05:04,760 Speaker 1: It's mutually beneficial to them. And then also we should 100 00:05:04,760 --> 00:05:06,960 Speaker 1: talk a little bit about oxytocin. This is that feel 101 00:05:06,960 --> 00:05:10,320 Speaker 1: good hormone that is released and a lot of people 102 00:05:10,560 --> 00:05:13,000 Speaker 1: think about it more in the example of an infant 103 00:05:13,160 --> 00:05:15,880 Speaker 1: and its mother during the breastfeeding process, because that's when 104 00:05:15,880 --> 00:05:19,640 Speaker 1: oxytocin is released for for both um for both the 105 00:05:20,040 --> 00:05:22,880 Speaker 1: mom and the baby, and they're both feeling all lovey 106 00:05:22,960 --> 00:05:26,320 Speaker 1: dovey and content. And oxytocin is great because it's an 107 00:05:26,360 --> 00:05:29,840 Speaker 1: incredible stress reducer. And they have actually found that people 108 00:05:29,960 --> 00:05:33,479 Speaker 1: who are dog owners are less likely to have heart attacks. 109 00:05:33,480 --> 00:05:35,840 Speaker 1: And if they do have a heart attack and they 110 00:05:35,839 --> 00:05:38,440 Speaker 1: are a dog owner, they're three to four times more 111 00:05:38,560 --> 00:05:42,200 Speaker 1: likely to actually survive that heart attack. That's how powerful 112 00:05:42,960 --> 00:05:46,760 Speaker 1: oxytocin is and a possible reason why we feel such 113 00:05:46,800 --> 00:05:51,440 Speaker 1: a bond to our animals, in particular dogs. Now, of 114 00:05:51,480 --> 00:05:53,880 Speaker 1: course it's worth knowing that if you don't survive that 115 00:05:53,920 --> 00:05:57,480 Speaker 1: heart attack, dogs are cats will probably eat your feet. 116 00:05:57,800 --> 00:06:00,400 Speaker 1: But that's that just goes with the territory. Yeah, yeah, 117 00:06:00,400 --> 00:06:02,599 Speaker 1: a very at least lick them. Yeah, well it starts 118 00:06:02,600 --> 00:06:04,480 Speaker 1: with licking and then it becomes eating because they can't 119 00:06:04,520 --> 00:06:07,880 Speaker 1: help themselves. This is the situation where they just then 120 00:06:07,920 --> 00:06:10,520 Speaker 1: I'll go ferrell and yeah, and then then they go 121 00:06:10,680 --> 00:06:13,880 Speaker 1: they go ferrell in the living room. Yeah, they run around. 122 00:06:14,120 --> 00:06:17,400 Speaker 1: So you know, we know that the oxytocin and and 123 00:06:17,520 --> 00:06:19,760 Speaker 1: this sort of connection makes us want to cuddle and 124 00:06:19,800 --> 00:06:24,040 Speaker 1: care for them. And again and Nova's dogs decoded. There 125 00:06:24,120 --> 00:06:28,080 Speaker 1: was a section um in which they featured psychologists Morton Kringelbach, 126 00:06:28,279 --> 00:06:30,320 Speaker 1: and he put adults in a make scanner, which is 127 00:06:30,320 --> 00:06:34,599 Speaker 1: like a supercharged neuroimager, and then he showed them photos 128 00:06:34,640 --> 00:06:38,680 Speaker 1: of adult faces, infant faces, and puppy faces, nothing else, 129 00:06:38,760 --> 00:06:41,360 Speaker 1: just like the big face looming in the background or 130 00:06:41,400 --> 00:06:44,760 Speaker 1: without dark background. And what he found is that within 131 00:06:45,120 --> 00:06:48,800 Speaker 1: one seventh of a second, their orbital frontal cortex, which 132 00:06:48,880 --> 00:06:52,480 Speaker 1: is involved in emotional responses, started to light up. And 133 00:06:52,720 --> 00:06:56,480 Speaker 1: it showed activation only when people looked at infants and puppies, 134 00:06:56,680 --> 00:07:01,200 Speaker 1: not other adults. And he called this that the parent instinct. Yeah, 135 00:07:01,360 --> 00:07:03,480 Speaker 1: or it's I mean, it's basically the cute factor. It's 136 00:07:03,480 --> 00:07:07,159 Speaker 1: why people love like cute overload. It's why if you're 137 00:07:07,640 --> 00:07:09,640 Speaker 1: if you like Peter or somebody, you're gonna put a 138 00:07:09,680 --> 00:07:12,920 Speaker 1: baby seal on the cover of your your promotional material, 139 00:07:13,760 --> 00:07:16,200 Speaker 1: or a half naked woman. But but but in many 140 00:07:16,200 --> 00:07:19,720 Speaker 1: cases Green Piece or various organizations, you'll see that like 141 00:07:19,760 --> 00:07:22,200 Speaker 1: the white baby seal is the one to put on 142 00:07:22,240 --> 00:07:24,280 Speaker 1: because its face looks so much like an infant. You 143 00:07:24,280 --> 00:07:26,640 Speaker 1: look at cute cartoon characters and you can see like 144 00:07:26,680 --> 00:07:29,920 Speaker 1: the big eyes and the you know, in the small 145 00:07:30,000 --> 00:07:34,239 Speaker 1: head and in the various uh um, some measurements that 146 00:07:34,280 --> 00:07:37,120 Speaker 1: didn map up with a with a baby's face. Yeah. 147 00:07:37,160 --> 00:07:39,160 Speaker 1: And you've actually even mentioned this when we've talked about 148 00:07:39,200 --> 00:07:43,200 Speaker 1: robots and and having robots in the service industry, that 149 00:07:43,480 --> 00:07:46,640 Speaker 1: they're in Japan, that they've got the really super cute 150 00:07:46,640 --> 00:07:49,800 Speaker 1: looking robots that actually to us, look, you know us 151 00:07:49,840 --> 00:07:51,640 Speaker 1: here in the West look kind of creepy because it 152 00:07:51,640 --> 00:07:55,560 Speaker 1: does look like cartoon character giant robots. Um. But so yeah, 153 00:07:55,560 --> 00:07:59,200 Speaker 1: there's there's definitely something to that. Um. So, I mean, 154 00:07:59,240 --> 00:08:02,120 Speaker 1: there you go that the basis a very good scientific 155 00:08:02,160 --> 00:08:06,360 Speaker 1: basis for why we feel the way we do about dogs. 156 00:08:06,400 --> 00:08:10,200 Speaker 1: So Okay, we've got the bond with them, right, Um, 157 00:08:10,240 --> 00:08:12,520 Speaker 1: and we know from fossil records that we have a 158 00:08:12,560 --> 00:08:16,480 Speaker 1: really long history with dogs, right this, This didn't just 159 00:08:16,480 --> 00:08:18,400 Speaker 1: start up in the last hundred years. Yeah, yeah, no, 160 00:08:18,480 --> 00:08:20,120 Speaker 1: this is like a hundred thousand years ago. We can 161 00:08:20,200 --> 00:08:22,040 Speaker 1: we know that we started to hang out with them, 162 00:08:22,200 --> 00:08:25,880 Speaker 1: But why would we hook up with canine familiars anyway? Well, 163 00:08:25,920 --> 00:08:28,840 Speaker 1: the most immediate um answer that comes to mind is 164 00:08:28,880 --> 00:08:31,280 Speaker 1: that we're we're probably in a situation where we were 165 00:08:31,360 --> 00:08:34,720 Speaker 1: either competing with the wolves for food, or the wolf 166 00:08:34,880 --> 00:08:38,360 Speaker 1: or the wolves were food or both. And uh, and 167 00:08:38,400 --> 00:08:40,720 Speaker 1: after you've killed a whole bunch of the adult wolves, 168 00:08:40,720 --> 00:08:43,560 Speaker 1: you might find all these little baby, cuddly wolves, all right, 169 00:08:44,040 --> 00:08:46,520 Speaker 1: and you go there and your first instinct, well, you 170 00:08:46,600 --> 00:08:49,800 Speaker 1: probably have two competing instincts. One is, hey, let's fry 171 00:08:49,840 --> 00:08:54,520 Speaker 1: these puppies up because there because because the tribe is hungry, 172 00:08:54,600 --> 00:08:56,520 Speaker 1: and these look delicious. But then on the other hand, 173 00:08:56,800 --> 00:08:58,800 Speaker 1: they look kind of like human babies. So it's your 174 00:08:58,840 --> 00:09:00,840 Speaker 1: belly is full and your bellies full, and they're harmed. 175 00:09:00,840 --> 00:09:04,040 Speaker 1: They're unlike the adult wolves you just strangled to death 176 00:09:04,080 --> 00:09:08,160 Speaker 1: on the primeval plane, you know, or you know, are 177 00:09:08,200 --> 00:09:10,720 Speaker 1: beat to death with a stone. Um. These things aren't 178 00:09:10,720 --> 00:09:13,320 Speaker 1: attacking you. There may be licking your hand, and that 179 00:09:13,440 --> 00:09:15,160 Speaker 1: they look cute. So you've been like, all right, let's 180 00:09:15,160 --> 00:09:16,679 Speaker 1: take these back to the camp and play with them 181 00:09:16,679 --> 00:09:20,120 Speaker 1: for a little bit. Yeah, and so this and then 182 00:09:20,520 --> 00:09:23,760 Speaker 1: this sort of bond could have developed. And then all obviously, 183 00:09:24,000 --> 00:09:27,920 Speaker 1: wolves we know are the closest relative to dogs, right, 184 00:09:28,120 --> 00:09:32,440 Speaker 1: so at some point dogs separated from wolves. Um, so 185 00:09:32,480 --> 00:09:35,880 Speaker 1: it's very likely that we began to see the wharf 186 00:09:35,920 --> 00:09:39,840 Speaker 1: and having these little pups around that then became really 187 00:09:39,840 --> 00:09:42,760 Speaker 1: good hunters along with us. And if you look at 188 00:09:42,800 --> 00:09:45,960 Speaker 1: dog domestication, which happened around fift years ago, that's about 189 00:09:45,960 --> 00:09:49,600 Speaker 1: the same time that we quit doing the whole nomadic 190 00:09:49,679 --> 00:09:52,800 Speaker 1: hunter gatherer thing and switched over to being a grarian's 191 00:09:53,559 --> 00:09:56,200 Speaker 1: so you know, then we're much more localized and it 192 00:09:56,320 --> 00:09:58,400 Speaker 1: makes sense to have a dog around that can help 193 00:09:58,440 --> 00:10:02,600 Speaker 1: you hunt. That's really fat us inefficient with with their 194 00:10:02,640 --> 00:10:05,679 Speaker 1: own food consumption and how they use it as fuel, right, 195 00:10:05,720 --> 00:10:07,640 Speaker 1: so they don't have to eat a whole lot themselves 196 00:10:08,040 --> 00:10:10,720 Speaker 1: and they can guard right, right, and that in turn 197 00:10:10,880 --> 00:10:14,360 Speaker 1: makes us much more successful as a species, right and 198 00:10:14,400 --> 00:10:17,520 Speaker 1: you can and uh, it's also worth noting that there's 199 00:10:17,520 --> 00:10:20,600 Speaker 1: a show on Discovery and BBC called Human Planet, and 200 00:10:20,640 --> 00:10:23,839 Speaker 1: it's a great example of this whole um hunting and 201 00:10:24,200 --> 00:10:28,439 Speaker 1: then raising the young kind of situation with the Owa 202 00:10:28,440 --> 00:10:33,120 Speaker 1: Guagi Guaga people of the eastern Amazon, and they hunt 203 00:10:33,160 --> 00:10:36,040 Speaker 1: and kill monkeys, which they eat and they make them 204 00:10:36,080 --> 00:10:40,760 Speaker 1: do a delicious looking stewins. Well that's I don't know 205 00:10:40,760 --> 00:10:43,400 Speaker 1: about eating brains, but they're definitely stewing up some monkeys. 206 00:10:43,920 --> 00:10:45,880 Speaker 1: But then they'll bring the baby monkeys back to camp 207 00:10:45,920 --> 00:10:47,920 Speaker 1: and they'll they'll not only raise them as pets, but 208 00:10:47,960 --> 00:10:50,880 Speaker 1: in some cases they'll actually breastfeed the really young baby 209 00:10:50,920 --> 00:10:54,520 Speaker 1: monkeys um, which is you know, even more than more 210 00:10:54,600 --> 00:10:58,880 Speaker 1: oxy uh toastin released into the system through that. But 211 00:10:58,880 --> 00:11:01,800 Speaker 1: but it's an interesting it's such an interesting glimpse into 212 00:11:02,080 --> 00:11:04,280 Speaker 1: how humans work. Just the idea that you could on 213 00:11:04,280 --> 00:11:07,760 Speaker 1: one hand kill and eat this particular species, but then 214 00:11:07,800 --> 00:11:09,560 Speaker 1: also raise it up as a pet. And then they 215 00:11:09,720 --> 00:11:13,160 Speaker 1: in this case, they don't actually eat um eat the 216 00:11:13,200 --> 00:11:16,120 Speaker 1: monkeys that they raise pets, so there's a difference there. 217 00:11:16,120 --> 00:11:18,520 Speaker 1: But but then you have situations, I mean, clearly you 218 00:11:18,559 --> 00:11:20,960 Speaker 1: have people who are really attached to baby goats that 219 00:11:21,160 --> 00:11:23,880 Speaker 1: may grow up to be become a food source. So 220 00:11:23,960 --> 00:11:26,040 Speaker 1: that you see plenty of examples in human culture where 221 00:11:26,160 --> 00:11:29,079 Speaker 1: where there's even this divide between the baby and the 222 00:11:29,440 --> 00:11:32,480 Speaker 1: edible adult, it will become right. Yeah, And just to 223 00:11:32,480 --> 00:11:35,120 Speaker 1: go back to oxytocin again, and I have read this 224 00:11:35,160 --> 00:11:40,080 Speaker 1: before that it's it's actually pretty addictive um apparently for 225 00:11:40,080 --> 00:11:42,040 Speaker 1: for new moms, and then it does give you a 226 00:11:42,040 --> 00:11:44,800 Speaker 1: big rush. So it's sort of interesting that you know, 227 00:11:45,240 --> 00:11:50,319 Speaker 1: you see those instances of surrogate um breastfeeding happening like 228 00:11:50,320 --> 00:11:53,280 Speaker 1: like a wet nurse is could be an oxytocin addict. 229 00:11:53,280 --> 00:11:55,520 Speaker 1: Really yeah, yeah, I mean you think it is an 230 00:11:55,559 --> 00:11:58,600 Speaker 1: altruistic doct but you have to wonder, you know, if 231 00:11:58,640 --> 00:12:01,480 Speaker 1: they're just doing it for the rush. So maybe you know, 232 00:12:01,600 --> 00:12:04,600 Speaker 1: this is completely unproven, but but maybe the situation was 233 00:12:04,640 --> 00:12:08,559 Speaker 1: we domesticated um dogs and are working on monkeys because 234 00:12:08,559 --> 00:12:11,720 Speaker 1: you have, like you have these these oxytocin addicted nurse 235 00:12:11,720 --> 00:12:13,800 Speaker 1: maids who are running wild through the woods and give 236 00:12:13,840 --> 00:12:16,280 Speaker 1: me some puppies. Let me breastfeed some puppies, you know, 237 00:12:16,280 --> 00:12:18,680 Speaker 1: because I gotta get that rush. Wow, I'm saying, like 238 00:12:18,720 --> 00:12:22,720 Speaker 1: this pulp fiction movie like set fift years ago, I'm yeah, 239 00:12:22,920 --> 00:12:27,120 Speaker 1: thinking about Darryl Hannah now as as a crazy wit nurse. 240 00:12:27,240 --> 00:12:29,360 Speaker 1: This is not good. Yeah, and we gotta get back. Yeah, 241 00:12:29,400 --> 00:12:31,400 Speaker 1: that's totally unproven. Do not use that as an answer. 242 00:12:31,600 --> 00:12:35,600 Speaker 1: We gotta get back your students. Yeah. But but then 243 00:12:35,640 --> 00:12:38,600 Speaker 1: another reason that we would hang out with canines and 244 00:12:38,640 --> 00:12:41,120 Speaker 1: domesticate them is their sense of smell, which again would 245 00:12:41,120 --> 00:12:45,040 Speaker 1: help with hunting um and in fact, cancers apparently have 246 00:12:45,320 --> 00:12:48,440 Speaker 1: a smell that dogs can be trained to detect according 247 00:12:48,480 --> 00:12:53,000 Speaker 1: to a growing body of research. Um and actually they've 248 00:12:53,080 --> 00:12:55,600 Speaker 1: had some small trials which have shown canines capable of 249 00:12:55,640 --> 00:12:58,480 Speaker 1: detecting melanoma in a person's skin and lung and breast 250 00:12:58,520 --> 00:13:02,160 Speaker 1: cancers by chemical que was in the person's breath. The trick, 251 00:13:02,240 --> 00:13:06,480 Speaker 1: according to Auburn University veterinarian Larry Myers, is the ability 252 00:13:06,520 --> 00:13:09,640 Speaker 1: of dogs to smell the multiple layers of chemicals. So 253 00:13:09,720 --> 00:13:12,880 Speaker 1: it's so much more nuanced and sophisticated rather than the 254 00:13:12,880 --> 00:13:15,480 Speaker 1: way that we detect smells. They've they've got a lot 255 00:13:15,480 --> 00:13:19,360 Speaker 1: more parts to their system, so to speak. So all 256 00:13:19,400 --> 00:13:21,120 Speaker 1: of this adds up to the fact that we that 257 00:13:21,120 --> 00:13:23,960 Speaker 1: that dogs have definitely helped us to become successful and 258 00:13:24,000 --> 00:13:27,640 Speaker 1: our survival and and certainly dogs themselves have become very 259 00:13:27,679 --> 00:13:31,000 Speaker 1: successful in their survival right. And it's it's interesting to 260 00:13:31,000 --> 00:13:33,920 Speaker 1: to look at, Okay, just on the surface things. Dogs 261 00:13:33,960 --> 00:13:38,199 Speaker 1: definitely have emotion, whether whether or not they can there's 262 00:13:38,240 --> 00:13:40,640 Speaker 1: this thing called love, and they can feel it. That's 263 00:13:40,720 --> 00:13:44,439 Speaker 1: that's a different issue. But but definitely emotion is it 264 00:13:44,559 --> 00:13:47,840 Speaker 1: has evolved as an adaptation and numerous species. Uh. It 265 00:13:47,920 --> 00:13:52,280 Speaker 1: bonds animals to one another. It catalyzes and regulates a 266 00:13:52,320 --> 00:13:55,920 Speaker 1: wide variety of social encounters among both friends and competitors, 267 00:13:56,040 --> 00:14:00,079 Speaker 1: and it permits animals to protect themselves adaptively. And with 268 00:14:00,120 --> 00:14:03,200 Speaker 1: the dogs that the curious thing is that dogs have 269 00:14:03,360 --> 00:14:06,760 Speaker 1: are much more social and say cats because I mean, 270 00:14:07,120 --> 00:14:09,400 Speaker 1: like my cat doesn't want any part of another cat 271 00:14:10,120 --> 00:14:12,880 Speaker 1: except to chase them off and uh, and they're just 272 00:14:12,920 --> 00:14:15,240 Speaker 1: not social for some reason. It may want to live 273 00:14:15,280 --> 00:14:17,520 Speaker 1: with she man want to live with humans. But the 274 00:14:17,520 --> 00:14:20,000 Speaker 1: heck with all the cats, dogs however, much more social. 275 00:14:20,120 --> 00:14:22,840 Speaker 1: They have a much more social mind and uh. And 276 00:14:22,880 --> 00:14:26,880 Speaker 1: therefore there's this they have this whole alpha uh situation 277 00:14:26,920 --> 00:14:29,120 Speaker 1: where one alpha can dominate the others and there's this 278 00:14:29,200 --> 00:14:31,360 Speaker 1: dominant and passive thing in there. And then the way 279 00:14:31,360 --> 00:14:35,080 Speaker 1: they behave so we've been able to interject ourselves into 280 00:14:35,120 --> 00:14:39,160 Speaker 1: their into this this uh, this this system where we 281 00:14:39,200 --> 00:14:41,880 Speaker 1: can eat where we either become the dominant master of 282 00:14:41,920 --> 00:14:44,520 Speaker 1: the dogs or we become this thing that the dog 283 00:14:44,640 --> 00:14:49,480 Speaker 1: is possessive of. Um, which is generally not the ideal situation, 284 00:14:49,520 --> 00:14:51,960 Speaker 1: but you see it all the time. Yeah, and that's 285 00:14:51,960 --> 00:14:54,720 Speaker 1: interesting again to draw those parallels and see how we 286 00:14:54,800 --> 00:14:57,680 Speaker 1: are more alike than different than dogs in the sense 287 00:14:57,680 --> 00:15:01,240 Speaker 1: that we are really social creatures, and certainly fifteen years 288 00:15:01,240 --> 00:15:04,240 Speaker 1: ago we were you know, carnivorous. Um, not all of 289 00:15:04,320 --> 00:15:08,920 Speaker 1: us are now, but and we really relied on hunting. Yeah. 290 00:15:09,040 --> 00:15:11,280 Speaker 1: So same thing with dogs, right, Yeah, you had this 291 00:15:11,440 --> 00:15:14,080 Speaker 1: suddenly this dogs like growing up among people, and there's 292 00:15:14,120 --> 00:15:15,960 Speaker 1: this this guy and he's like saying, hey, I'm the 293 00:15:16,000 --> 00:15:18,200 Speaker 1: pack leader. Let's go catch ourselves some food, and the 294 00:15:18,240 --> 00:15:20,120 Speaker 1: dogs like, yeah, I'm game for that. That's totally what 295 00:15:20,160 --> 00:15:22,280 Speaker 1: I've evolved to do. So let's yeah, let's let's make 296 00:15:22,280 --> 00:15:24,600 Speaker 1: it happen. And by the wather like thirty of you guys, 297 00:15:24,880 --> 00:15:27,840 Speaker 1: five of us. Yeah, you guys have the clubs, you 298 00:15:27,880 --> 00:15:30,760 Speaker 1: can be the pack master. Fine, you know so part 299 00:15:30,760 --> 00:15:32,160 Speaker 1: of it is like you kind of wonder how much 300 00:15:32,160 --> 00:15:34,960 Speaker 1: the dogs are going along in their own survival. Yeah, 301 00:15:35,240 --> 00:15:37,440 Speaker 1: and then you you get into all this uh, this, 302 00:15:37,440 --> 00:15:39,440 Speaker 1: this these other weird areas who were like you take 303 00:15:39,480 --> 00:15:42,720 Speaker 1: a dog's natural hunting instinct and then you you you 304 00:15:42,800 --> 00:15:45,880 Speaker 1: kind of perverted over the over the ages to to 305 00:15:45,960 --> 00:15:48,240 Speaker 1: create say a hurting animal where you're like saying, hey, 306 00:15:48,240 --> 00:15:50,720 Speaker 1: you guys are really good at catching these animals, but 307 00:15:51,080 --> 00:15:54,920 Speaker 1: let's work on you not killing them, but just moving 308 00:15:54,920 --> 00:15:57,720 Speaker 1: them around, uh, in exactly the place I want them 309 00:15:57,760 --> 00:16:01,160 Speaker 1: to be, right, yeah, when you're talking you gent x right, 310 00:16:01,240 --> 00:16:04,160 Speaker 1: yeah yeah, so yeah, I mean actually eugenics became pretty 311 00:16:04,200 --> 00:16:07,520 Speaker 1: popular in nineteenth century Europe, right, So there's this drive 312 00:16:07,600 --> 00:16:11,920 Speaker 1: to perfect and design our environments, including pets, and of 313 00:16:11,920 --> 00:16:15,920 Speaker 1: course you have this sort of newish technology too, and eugenics, um, 314 00:16:15,960 --> 00:16:19,120 Speaker 1: so they applied that to dogs through selective breeding. So 315 00:16:19,320 --> 00:16:21,640 Speaker 1: you're like, in the scenario you were talking about, that's 316 00:16:21,640 --> 00:16:26,160 Speaker 1: like a border collie, right, um. And so this allowed 317 00:16:26,240 --> 00:16:29,480 Speaker 1: us to to basically breed out traits and breeding traits 318 00:16:29,520 --> 00:16:32,760 Speaker 1: as you said, and and and you know, of course 319 00:16:32,800 --> 00:16:36,200 Speaker 1: now we have our little tiny um toy poodles and 320 00:16:36,280 --> 00:16:38,520 Speaker 1: every from that to like a mastiff, right, and you 321 00:16:38,560 --> 00:16:40,600 Speaker 1: can take everything in between and sort of mush it 322 00:16:40,680 --> 00:16:42,800 Speaker 1: up and see which you can get. So it is 323 00:16:42,840 --> 00:16:47,400 Speaker 1: amazing to think that right now, um, of dog breeds 324 00:16:47,400 --> 00:16:50,840 Speaker 1: are modern breeds that we created. So that's four hundred 325 00:16:50,920 --> 00:16:59,280 Speaker 1: genetically distinct dog breeds. This presentation is brought to you 326 00:16:59,320 --> 00:17:07,120 Speaker 1: by Intel Sponsors of Tomorrow. So in many of these cases, 327 00:17:07,160 --> 00:17:11,719 Speaker 1: we are breeding, selectively breeding animals to encourage particular traits 328 00:17:12,359 --> 00:17:15,760 Speaker 1: that that allow them to perform a task, and as 329 00:17:15,800 --> 00:17:20,280 Speaker 1: those tasks disappear, we end up then in breeding them 330 00:17:20,320 --> 00:17:25,159 Speaker 1: selectively to encourage physical traits that we identify with that 331 00:17:25,240 --> 00:17:28,840 Speaker 1: particular breed. Right, so you have like situations like with boxers, 332 00:17:28,840 --> 00:17:31,560 Speaker 1: where you no longer actually need boxers to perform the 333 00:17:31,760 --> 00:17:34,080 Speaker 1: task they were bred for, and instead you just breathe 334 00:17:34,119 --> 00:17:36,680 Speaker 1: them to look even more and more like a cartoon 335 00:17:36,840 --> 00:17:40,640 Speaker 1: character of themselves in the ring. Yeah, and then there's 336 00:17:40,680 --> 00:17:43,960 Speaker 1: the there's the whole the longer the ring. Um. I 337 00:17:43,960 --> 00:17:48,280 Speaker 1: believe they were used to control cattle and like, I 338 00:17:48,280 --> 00:17:51,560 Speaker 1: think it's like slaughterhouse situation. Um, so we have robots 339 00:17:51,600 --> 00:17:53,160 Speaker 1: for that now, So instead you're just like, hey, let's 340 00:17:53,160 --> 00:17:54,560 Speaker 1: breed them, make them look funny and stand on the 341 00:17:54,560 --> 00:17:58,360 Speaker 1: side of a football field. Likewise, even with with with 342 00:17:58,400 --> 00:18:02,880 Speaker 1: the with with sheep herding dog, like my my family 343 00:18:02,960 --> 00:18:05,719 Speaker 1: has a as a herding dog and they don't have 344 00:18:05,920 --> 00:18:08,360 Speaker 1: sheep or anything. So the dog just loves to run 345 00:18:08,359 --> 00:18:10,760 Speaker 1: around and barket trees and attempt to herd things like 346 00:18:10,800 --> 00:18:16,080 Speaker 1: tractors or or branches in a tree or hawks flying overhead, 347 00:18:16,520 --> 00:18:18,879 Speaker 1: and and you just think, wow, we've really screwed this 348 00:18:18,880 --> 00:18:21,479 Speaker 1: one up. We we we've we've we've taken this animal's 349 00:18:21,520 --> 00:18:24,720 Speaker 1: natural hunting instinct turned it into something that benefits us 350 00:18:24,800 --> 00:18:27,840 Speaker 1: and then say all right, we're eliminating that job. But 351 00:18:27,960 --> 00:18:31,800 Speaker 1: you guys stick around and uh and just go crazy. Yeah, 352 00:18:31,880 --> 00:18:34,040 Speaker 1: And that's actually where the problem comes in, right, because 353 00:18:34,400 --> 00:18:35,959 Speaker 1: I mean, you know, it sounds like in this scenario, 354 00:18:36,040 --> 00:18:38,479 Speaker 1: at least your dog can go out and hang out 355 00:18:38,520 --> 00:18:40,800 Speaker 1: in the yard, but some of those types of dogs 356 00:18:40,800 --> 00:18:42,800 Speaker 1: are you know, confined to apartments and they just go 357 00:18:42,920 --> 00:18:46,000 Speaker 1: run and running circles and basically then the next thing 358 00:18:46,040 --> 00:18:49,000 Speaker 1: you know, they're on zoloft. So um. But what allows 359 00:18:49,040 --> 00:18:51,119 Speaker 1: us to do this to to breed these traits is 360 00:18:51,160 --> 00:18:54,959 Speaker 1: that they have such a great plasticity of jeans, and 361 00:18:55,080 --> 00:18:58,040 Speaker 1: it takes just twenty five years to create some sort 362 00:18:58,040 --> 00:19:01,480 Speaker 1: of breed that you want, which, if you've get evolutionary terms, 363 00:19:01,560 --> 00:19:06,280 Speaker 1: is like supercharged evolution in a sense, right. Um. And 364 00:19:06,680 --> 00:19:08,960 Speaker 1: there's actually a good example of this is a dog 365 00:19:09,000 --> 00:19:12,959 Speaker 1: called the dogo Argentino and it has something like, you know, 366 00:19:13,160 --> 00:19:16,600 Speaker 1: twelve different breeds that they tinkered with over two and 367 00:19:16,680 --> 00:19:20,160 Speaker 1: a half decades to create the perfect dog that could 368 00:19:20,160 --> 00:19:23,560 Speaker 1: take down wild boars. Without killing the boars, but could 369 00:19:23,560 --> 00:19:27,440 Speaker 1: also hang out with kids, you know, and be all cuddly. Wow, 370 00:19:27,440 --> 00:19:29,800 Speaker 1: that was an interesting checklist when they were putting that 371 00:19:29,800 --> 00:19:31,800 Speaker 1: one together. It's like, I needed to be able to 372 00:19:31,840 --> 00:19:34,120 Speaker 1: take down a boar, but I wanted to hang out 373 00:19:34,119 --> 00:19:36,400 Speaker 1: with my kid too. Yeah, And in twenty five years 374 00:19:36,440 --> 00:19:39,040 Speaker 1: and and and and taking everything from like a mastiff too. 375 00:19:39,560 --> 00:19:42,520 Speaker 1: I think there was actually, um, maybe a bull terrier 376 00:19:42,520 --> 00:19:45,159 Speaker 1: in there somewhere in the mix, and just tinkering around 377 00:19:45,200 --> 00:19:47,879 Speaker 1: with it, and then finally they had something that Again, 378 00:19:48,240 --> 00:19:50,880 Speaker 1: this was helping them at the time because they really 379 00:19:50,920 --> 00:19:53,320 Speaker 1: didn't have this wild boar problem that was eating all 380 00:19:53,359 --> 00:19:55,160 Speaker 1: the crops, and so they wanted to take them down 381 00:19:55,160 --> 00:19:58,040 Speaker 1: without killing them. And this was a good solution. But 382 00:19:58,080 --> 00:20:00,480 Speaker 1: it's also a little bit frightening to that we could 383 00:20:00,720 --> 00:20:03,880 Speaker 1: do this to such a degree, right, hence the eugenics part, 384 00:20:03,920 --> 00:20:07,760 Speaker 1: which you know, that's a whole other two sides to 385 00:20:07,800 --> 00:20:10,399 Speaker 1: the eugenics coin for sure. Yeah. Yeah. And then of 386 00:20:10,400 --> 00:20:13,040 Speaker 1: course the other problem with this, or you know, a 387 00:20:13,040 --> 00:20:17,280 Speaker 1: problem in the sense when it's not used, um perhaps 388 00:20:17,280 --> 00:20:20,880 Speaker 1: with the best of ethical intentions, is when you have 389 00:20:20,960 --> 00:20:24,680 Speaker 1: someone who's a disreputable breeder who is continuing to breed 390 00:20:25,040 --> 00:20:28,439 Speaker 1: so aggressively that there are a lot of defects that 391 00:20:29,040 --> 00:20:31,560 Speaker 1: the dog might be born with. Right do you end 392 00:20:31,640 --> 00:20:37,480 Speaker 1: up with in some cases a genetic neurological problems? Um, Like, 393 00:20:37,560 --> 00:20:40,080 Speaker 1: for instance, there's the whole feigning goat thing. Um if 394 00:20:40,080 --> 00:20:42,439 Speaker 1: you're anyone familiar with the feigning goat, these are goats 395 00:20:42,480 --> 00:20:45,800 Speaker 1: that they just happened to uh through breathing. They have 396 00:20:45,880 --> 00:20:49,040 Speaker 1: this neurological condition where they'll you'll frighten them and they'll 397 00:20:49,040 --> 00:20:53,359 Speaker 1: fall over. And for a number of reasons, people decided 398 00:20:53,359 --> 00:20:55,560 Speaker 1: that the breeders decided, hey, let's keep let's keep this. 399 00:20:55,560 --> 00:20:57,440 Speaker 1: This is a good trait to having a dog, even 400 00:20:57,440 --> 00:20:59,399 Speaker 1: though it's it's not really i mean, in a goat, 401 00:20:59,440 --> 00:21:01,480 Speaker 1: even though it's not really good trait. And there are 402 00:21:01,520 --> 00:21:04,520 Speaker 1: some but there are some breeds of dogs that have 403 00:21:04,640 --> 00:21:08,120 Speaker 1: similar conditions just because they've been they've been they've been 404 00:21:08,119 --> 00:21:11,480 Speaker 1: this sort of narrow branch on the tree as they've 405 00:21:11,600 --> 00:21:17,040 Speaker 1: continually bread to encourage various various traits that are part 406 00:21:17,080 --> 00:21:20,040 Speaker 1: of that breed. Yeah. So, I mean, there's there's a 407 00:21:20,080 --> 00:21:22,400 Speaker 1: lot going on here that can actually tell us about 408 00:21:22,400 --> 00:21:25,320 Speaker 1: ourselves too. Of course, we always as humans figure out 409 00:21:25,359 --> 00:21:28,119 Speaker 1: how we can get some data off of you know, 410 00:21:28,160 --> 00:21:31,840 Speaker 1: other scenarios and so if there are certain diseases and dogs, 411 00:21:31,840 --> 00:21:34,240 Speaker 1: like the boxer genome has been decoded, so that's been 412 00:21:34,240 --> 00:21:36,480 Speaker 1: really helpful and saying, okay, on this marker we find 413 00:21:36,520 --> 00:21:39,439 Speaker 1: this disease, let's now flip over to the human genome 414 00:21:39,440 --> 00:21:40,880 Speaker 1: and see if we can find it there and see 415 00:21:40,920 --> 00:21:42,760 Speaker 1: what it can tell us about this disease. So that's 416 00:21:42,760 --> 00:21:46,199 Speaker 1: actually helpful. Yeah, So okay, so we know this, we 417 00:21:46,200 --> 00:21:48,160 Speaker 1: know about the genics part, we know why we hooked 418 00:21:48,240 --> 00:21:51,200 Speaker 1: up with them. But my question is, you know, how 419 00:21:51,280 --> 00:21:54,320 Speaker 1: well do dogs really know us and how well do 420 00:21:54,400 --> 00:21:57,000 Speaker 1: we actually know them? Is their data there? You know, 421 00:21:57,040 --> 00:21:59,959 Speaker 1: our our dogs at good as reading our emotions as 422 00:22:00,080 --> 00:22:02,440 Speaker 1: we think they are. Well, it's interesting that they can 423 00:22:02,480 --> 00:22:06,240 Speaker 1: definitely communicate with us that they are a that I 424 00:22:06,240 --> 00:22:09,800 Speaker 1: mean not every species can do this. Um. For instance, 425 00:22:09,840 --> 00:22:12,000 Speaker 1: you have the case of Chaser, the border collie from 426 00:22:12,760 --> 00:22:16,480 Speaker 1: Spartan Bird, South Carolina that apparently knows A thousand and 427 00:22:16,560 --> 00:22:19,480 Speaker 1: twenty two perhaps more. Now, who knows this is? I 428 00:22:19,480 --> 00:22:21,480 Speaker 1: think this article is from like a year ago. A 429 00:22:21,520 --> 00:22:25,240 Speaker 1: thousand and twenty two nouns um and and it can 430 00:22:25,240 --> 00:22:28,159 Speaker 1: also identify verbs like like the owner was able to 431 00:22:28,160 --> 00:22:32,000 Speaker 1: teach it to understand commands like fetch ball, fetch frisbee, 432 00:22:32,040 --> 00:22:35,160 Speaker 1: fetch it all and and and it was understanding both 433 00:22:35,200 --> 00:22:38,440 Speaker 1: the verb and the noun. So that's I mean, that's 434 00:22:38,480 --> 00:22:41,359 Speaker 1: that's pretty amazing. And she knew categories to right, yes, 435 00:22:41,440 --> 00:22:43,680 Speaker 1: like you know, she knew like the balls, the toys 436 00:22:43,760 --> 00:22:45,480 Speaker 1: and so on and so forth, so she could be 437 00:22:45,480 --> 00:22:48,720 Speaker 1: directed even at a greater level. And then from what 438 00:22:48,760 --> 00:22:52,080 Speaker 1: I remember to in that article, the owner had worked 439 00:22:52,119 --> 00:22:54,359 Speaker 1: with her for like five to six hours a day, 440 00:22:54,880 --> 00:22:58,919 Speaker 1: repeating words sometimes forty times, like a new word forty 441 00:22:58,920 --> 00:23:03,120 Speaker 1: times every which is insane. And if you think about 442 00:23:03,160 --> 00:23:07,520 Speaker 1: this too, um, we as humans learned something like ten 443 00:23:07,560 --> 00:23:10,760 Speaker 1: new words a day until we reach I believe, the 444 00:23:10,800 --> 00:23:13,719 Speaker 1: twelfth grade, in which case we then have something like 445 00:23:14,560 --> 00:23:18,040 Speaker 1: sixty thousand words at our disposal. That here's this border 446 00:23:18,080 --> 00:23:20,840 Speaker 1: collie getting forty new words a day to our ten 447 00:23:20,880 --> 00:23:24,440 Speaker 1: words a day. So that is actually a a particularly 448 00:23:25,080 --> 00:23:27,600 Speaker 1: strange situation. This is, you know, most dogs know something 449 00:23:27,600 --> 00:23:29,880 Speaker 1: around the order of a hundred and fifty words. Yeah, 450 00:23:30,000 --> 00:23:32,000 Speaker 1: but but then again, six like six hours a day 451 00:23:32,040 --> 00:23:35,080 Speaker 1: with this uh, with this old dude in his apartment. Yeah. 452 00:23:35,119 --> 00:23:36,960 Speaker 1: You know, it's like if if I was stuck with 453 00:23:37,080 --> 00:23:39,439 Speaker 1: him and he was coaching me on vocabulary, I'm sure 454 00:23:39,480 --> 00:23:42,680 Speaker 1: I would learn all these fabulous new words. And I know, 455 00:23:42,920 --> 00:23:44,960 Speaker 1: I know, I think we all should just go spend 456 00:23:44,960 --> 00:23:48,119 Speaker 1: a week with them. Um. But the other thing about dogs, 457 00:23:48,160 --> 00:23:50,000 Speaker 1: and this is something that's been proven out, is that 458 00:23:50,080 --> 00:23:53,400 Speaker 1: they really have learned to read our emotions. Uh. And 459 00:23:53,400 --> 00:23:56,000 Speaker 1: and this is was found again in the Nova Dogs 460 00:23:56,040 --> 00:24:00,000 Speaker 1: Decoded documentary. Uh. What they said is that when humans 461 00:24:00,000 --> 00:24:03,480 Speaker 1: spress emotions, they do so asymmetrically. And what that means 462 00:24:03,560 --> 00:24:06,760 Speaker 1: is if I express anger or joy, if you if 463 00:24:06,760 --> 00:24:08,560 Speaker 1: you go down the middle of my face and cut 464 00:24:08,600 --> 00:24:11,160 Speaker 1: it in half and and examine it, you'll see that 465 00:24:11,320 --> 00:24:15,040 Speaker 1: it's not symmetrical in the way that I expressed those emotions. 466 00:24:15,119 --> 00:24:16,720 Speaker 1: So one part of my face is gonna be different 467 00:24:16,720 --> 00:24:18,680 Speaker 1: than the other. Okay, it's not going to be, of course, 468 00:24:18,720 --> 00:24:21,920 Speaker 1: like too crazy looking. It's it's pretty nuanced, like like 469 00:24:22,200 --> 00:24:24,159 Speaker 1: whatever the face is when like if you smile on 470 00:24:24,160 --> 00:24:25,880 Speaker 1: one side of your face and frown on the other, 471 00:24:26,480 --> 00:24:28,879 Speaker 1: you're talking like even a normal what we might on 472 00:24:28,920 --> 00:24:31,120 Speaker 1: the surface think of as a normal smile is still 473 00:24:31,160 --> 00:24:34,720 Speaker 1: not a completely symmetrical Yeah, what looks cohesive really isn't. 474 00:24:35,280 --> 00:24:38,760 Speaker 1: Um So, and that's that's again, that's such a nuanced thing. 475 00:24:39,119 --> 00:24:41,760 Speaker 1: But what they did is they said, Okay, for humans, 476 00:24:41,760 --> 00:24:44,119 Speaker 1: when we're looking at the emotions, are reading emotions, we 477 00:24:44,200 --> 00:24:45,840 Speaker 1: start on the left hand side, and then we got 478 00:24:45,920 --> 00:24:47,560 Speaker 1: left to right, so we have a left hand bias. 479 00:24:48,080 --> 00:24:49,320 Speaker 1: So what they did is they want to see if 480 00:24:49,320 --> 00:24:51,679 Speaker 1: dogs did the same thing. So low and behold. They 481 00:24:51,720 --> 00:24:54,760 Speaker 1: put them in front of a screen and they watched 482 00:24:54,760 --> 00:24:57,320 Speaker 1: the dog's reactions. They filmed the dog, and they saw 483 00:24:57,400 --> 00:24:59,240 Speaker 1: that the dogs did the same thing. They went from 484 00:24:59,320 --> 00:25:01,920 Speaker 1: left to right, although when dogs look at each other, 485 00:25:02,160 --> 00:25:04,360 Speaker 1: they do not read from left to right. And as 486 00:25:04,400 --> 00:25:07,719 Speaker 1: far as they know, dogs are the only species that 487 00:25:07,760 --> 00:25:10,360 Speaker 1: can read human emotions in that way and the way 488 00:25:10,359 --> 00:25:13,159 Speaker 1: that we do. So they know they know that, like 489 00:25:13,200 --> 00:25:15,119 Speaker 1: this is how you read a human space. You have 490 00:25:15,160 --> 00:25:17,400 Speaker 1: to look left or right. Yeah, yeah, in order to 491 00:25:17,400 --> 00:25:19,840 Speaker 1: to pick up on the nuance of okay, well that's 492 00:25:19,840 --> 00:25:22,680 Speaker 1: the emotion that I think that is being expressed by 493 00:25:22,720 --> 00:25:26,920 Speaker 1: my owner right now, which is really pretty interesting. Um So, again, 494 00:25:26,960 --> 00:25:29,280 Speaker 1: there's this idea that dogs have evolved to read a 495 00:25:29,359 --> 00:25:33,000 Speaker 1: human space and that that makes dogs understand us in 496 00:25:33,000 --> 00:25:35,359 Speaker 1: a way that other species don't. And again hence the 497 00:25:36,119 --> 00:25:38,280 Speaker 1: bomb that we feel with them, that they can actually 498 00:25:38,320 --> 00:25:41,840 Speaker 1: feel our emotions. Um. And they also respond to gestural 499 00:25:41,960 --> 00:25:45,879 Speaker 1: cues like pointing yes though it's it's it's interesting that 500 00:25:45,920 --> 00:25:49,480 Speaker 1: there was a study UM from the Department of Comparative 501 00:25:49,480 --> 00:25:53,560 Speaker 1: and Developmental Psychology at the the map Plank Institute for 502 00:25:53,600 --> 00:25:57,280 Speaker 1: Revolutionary Anthropology in Germany Max Plank. Yeah, they have, they've 503 00:25:57,320 --> 00:25:59,879 Speaker 1: come out before UM where they looked at a ra 504 00:26:00,080 --> 00:26:03,080 Speaker 1: tional and rational acts UM. Here like, here's the example 505 00:26:03,320 --> 00:26:07,640 Speaker 1: you have in human infants and a mother. Like if 506 00:26:07,640 --> 00:26:11,439 Speaker 1: the mother is is say, I don't know turning on 507 00:26:11,480 --> 00:26:13,760 Speaker 1: the coffee maker, we know, well, I guess nothing to pay. Well, 508 00:26:13,760 --> 00:26:15,560 Speaker 1: we're gonna roll with this analogy, all right. So the 509 00:26:15,560 --> 00:26:18,040 Speaker 1: baby sees the mom using her hand to turn on 510 00:26:18,040 --> 00:26:20,680 Speaker 1: the coffee maker, all right, and then that they'll on 511 00:26:21,000 --> 00:26:22,920 Speaker 1: some mobile connect and say that's that's a good use 512 00:26:22,920 --> 00:26:25,439 Speaker 1: of that hand. That's irrational use. But and then they 513 00:26:25,480 --> 00:26:28,640 Speaker 1: see the mother, well, say, with an armload of clothing, 514 00:26:29,400 --> 00:26:30,680 Speaker 1: she doesn't have a free hand, but she needs to 515 00:26:30,680 --> 00:26:32,879 Speaker 1: turn on the coffee maker. So she uses her forehead 516 00:26:32,920 --> 00:26:35,399 Speaker 1: to do it or knows I don't know. Um, and 517 00:26:35,440 --> 00:26:37,040 Speaker 1: then the child will be like, all right, we'll give 518 00:26:37,040 --> 00:26:39,560 Speaker 1: them this situation. That makes total sense. But if the 519 00:26:39,680 --> 00:26:41,520 Speaker 1: if the mother were to walk in with nothing in 520 00:26:41,520 --> 00:26:44,240 Speaker 1: her hands too free hands, and then reached over and 521 00:26:44,240 --> 00:26:46,200 Speaker 1: turned on the coffee maker where there with her forehead 522 00:26:46,280 --> 00:26:49,720 Speaker 1: or nose, that the child would not see this as irrational. 523 00:26:50,320 --> 00:26:54,080 Speaker 1: That's coconuts. Yeah, but the dog, there's no coconuts with 524 00:26:54,240 --> 00:26:56,440 Speaker 1: with the dog. The dog would just accept either act. 525 00:26:56,520 --> 00:26:59,120 Speaker 1: There's no difference between irrational and irrational. Okay, So that's 526 00:26:59,119 --> 00:27:03,440 Speaker 1: a case in which we might be projecting ourselves onto 527 00:27:04,160 --> 00:27:06,480 Speaker 1: whether or not a dog can can make those sort 528 00:27:06,480 --> 00:27:08,919 Speaker 1: of judgments, right, I mean, and another thing is the 529 00:27:08,920 --> 00:27:12,000 Speaker 1: whole like, oh my dog did something bad and uh 530 00:27:12,080 --> 00:27:15,160 Speaker 1: and and and now he's sorry or she's she's sorry 531 00:27:15,160 --> 00:27:17,680 Speaker 1: a little catter, she's so ashamed of herself. But that's 532 00:27:17,720 --> 00:27:20,720 Speaker 1: just a submissive behavior. They're not really ashamed of anything. 533 00:27:21,240 --> 00:27:23,160 Speaker 1: There was an interesting study into that that was actually 534 00:27:23,200 --> 00:27:26,960 Speaker 1: profiled on the Radio Lab episode Animal Minds, which is 535 00:27:27,000 --> 00:27:30,560 Speaker 1: a good listen for more of a broader animal emotional 536 00:27:31,080 --> 00:27:35,040 Speaker 1: uh um thing and uh and but but you had 537 00:27:35,119 --> 00:27:37,120 Speaker 1: these people that you know, we're claiming all my dog 538 00:27:37,280 --> 00:27:39,399 Speaker 1: thinks that thinks it did something bad. He knows it 539 00:27:39,440 --> 00:27:41,479 Speaker 1: did something bad, and that's why it's ashamed. But they 540 00:27:41,520 --> 00:27:44,560 Speaker 1: found that that that that dogs in a control group 541 00:27:44,600 --> 00:27:46,880 Speaker 1: would behave the same way even if there had been 542 00:27:46,880 --> 00:27:50,400 Speaker 1: no mischief in the living room, um et cetera. Yeah, 543 00:27:50,400 --> 00:27:53,600 Speaker 1: and that's why animal behavior is so tricky, right, because 544 00:27:54,040 --> 00:27:56,120 Speaker 1: you've got the whole fact that your dog is so 545 00:27:56,200 --> 00:27:58,320 Speaker 1: tuned into you that you can't help but think that 546 00:27:58,359 --> 00:28:01,520 Speaker 1: the dog is with you in lockstep and the way 547 00:28:01,520 --> 00:28:04,320 Speaker 1: that you're thinking and acting. And in fact, that they 548 00:28:04,359 --> 00:28:08,080 Speaker 1: called the Clever Hans effect. And Clever Hans was actually 549 00:28:08,160 --> 00:28:10,359 Speaker 1: a horse in the nineteen hundreds that could use his 550 00:28:10,400 --> 00:28:15,639 Speaker 1: hoof to count um and answer mathematical questions. And he 551 00:28:15,760 --> 00:28:17,760 Speaker 1: was just like the star of the animal world. Right, 552 00:28:17,800 --> 00:28:21,600 Speaker 1: everybody was astounded by his knowledge. But a psychologist picked 553 00:28:21,640 --> 00:28:23,840 Speaker 1: up on the fact that the horse answered correctly only 554 00:28:23,920 --> 00:28:27,320 Speaker 1: when the questioner knew the answer. So what was happening 555 00:28:27,400 --> 00:28:29,800 Speaker 1: is that the horse would count up until the point 556 00:28:29,880 --> 00:28:34,359 Speaker 1: in which they observed that the questioner began to relax 557 00:28:35,040 --> 00:28:37,840 Speaker 1: when when when they had read when clever Hans had 558 00:28:37,880 --> 00:28:41,120 Speaker 1: reached the correct number. And again it's that that nuance 559 00:28:41,200 --> 00:28:44,640 Speaker 1: of being able to read body language and say, okay 560 00:28:44,680 --> 00:28:47,520 Speaker 1: that the human is fine, Now this must be the 561 00:28:47,600 --> 00:28:50,520 Speaker 1: right answer and all quit you know, stomping my hoof. 562 00:28:51,160 --> 00:28:53,920 Speaker 1: So they've they've talked about that with dogs as well. 563 00:28:54,040 --> 00:28:56,440 Speaker 1: Is that, you know, there's there's that fine line of 564 00:28:56,600 --> 00:28:58,320 Speaker 1: you know, how much is the dog just trying to 565 00:28:58,320 --> 00:29:03,320 Speaker 1: read your your um emotions and your your gestures as 566 00:29:03,320 --> 00:29:06,120 Speaker 1: opposed to really cogitating. Yeah, there's it's like there's this 567 00:29:06,200 --> 00:29:08,520 Speaker 1: fiction we create with this with this dog, is this 568 00:29:08,600 --> 00:29:13,080 Speaker 1: friend or this this this child in our lives? And uh, 569 00:29:13,800 --> 00:29:18,440 Speaker 1: but the animals participating in this fiction as well. And 570 00:29:18,600 --> 00:29:20,720 Speaker 1: I find that really fascinating. I mean, it's not I 571 00:29:20,720 --> 00:29:25,600 Speaker 1: don't think it it downplays the what's amazing about the relationship. 572 00:29:25,840 --> 00:29:28,600 Speaker 1: But but it's it's it's kind of like blind men 573 00:29:28,640 --> 00:29:31,160 Speaker 1: and elephants, or one is touching one part of the 574 00:29:31,200 --> 00:29:32,640 Speaker 1: elephant and the others touch in the other and they 575 00:29:32,640 --> 00:29:34,760 Speaker 1: both have certain ideas about what's going on, but neither 576 00:29:34,760 --> 00:29:37,600 Speaker 1: one is the correct. Uh, neither one is the the 577 00:29:37,600 --> 00:29:40,360 Speaker 1: the actual image of the elephant. Well, and we we've 578 00:29:40,360 --> 00:29:44,640 Speaker 1: talked about symbiosis before, right, and parasites, and this reminds 579 00:29:44,640 --> 00:29:46,600 Speaker 1: me of that this is sort of like the mutually 580 00:29:46,600 --> 00:29:51,280 Speaker 1: beneficial parasitic relationship, right right. I mean, your your dog 581 00:29:51,360 --> 00:29:55,120 Speaker 1: is pretty much like, well, you know, I'm sure that 582 00:29:55,160 --> 00:29:57,800 Speaker 1: your dog gives you a lot of love or perceived love, 583 00:29:58,480 --> 00:30:01,320 Speaker 1: but your dog is really kind of you know, just 584 00:30:01,400 --> 00:30:05,360 Speaker 1: hanging out on your couch, eating your food, watching your TV. Uh, 585 00:30:05,480 --> 00:30:09,720 Speaker 1: not necessarily contributing to the household income, right right, but 586 00:30:09,720 --> 00:30:14,640 Speaker 1: but maybe participating to your feeling of of of of 587 00:30:14,640 --> 00:30:18,080 Speaker 1: of safety in your house, or or elevating your emotions. 588 00:30:18,120 --> 00:30:20,400 Speaker 1: So there, I mean there's a different benefit. Maybe it's 589 00:30:20,400 --> 00:30:22,760 Speaker 1: barking at strangers, or if you're really on the ball, 590 00:30:22,800 --> 00:30:25,040 Speaker 1: maybe it actually does work around the house overthing you 591 00:30:25,080 --> 00:30:28,680 Speaker 1: have like seeing eye dogs and helper animals, where there's 592 00:30:28,720 --> 00:30:31,560 Speaker 1: a definite case to be made for this. This and 593 00:30:31,720 --> 00:30:35,120 Speaker 1: this symbiotic relationship is really um, you know, working on 594 00:30:35,160 --> 00:30:37,560 Speaker 1: all cylinders. Yeah, and see, I think that the two 595 00:30:37,560 --> 00:30:40,680 Speaker 1: are so entangled. That's really hard to look at this 596 00:30:40,760 --> 00:30:44,080 Speaker 1: and say, you know, is there a definitive love or 597 00:30:44,120 --> 00:30:48,120 Speaker 1: you know or not? Right? And what complicates it is 598 00:30:48,240 --> 00:30:52,800 Speaker 1: the way that we actually react to dogs as well. Uh. 599 00:30:52,920 --> 00:30:56,320 Speaker 1: Dr Adam mcclowsky, at a research center in Hungary recorded 600 00:30:56,440 --> 00:30:59,520 Speaker 1: six different scenarios in which a dog was barking. And 601 00:30:59,560 --> 00:31:03,000 Speaker 1: this isn't parton because dog barks, we often hear and 602 00:31:03,040 --> 00:31:04,840 Speaker 1: then we think, oh, the dog is feeling this way 603 00:31:04,920 --> 00:31:07,240 Speaker 1: or that way. And so what he had observed a 604 00:31:07,320 --> 00:31:09,360 Speaker 1: lot of humans saying, oh, well, my dog does this 605 00:31:09,560 --> 00:31:12,760 Speaker 1: mewing sound or actually it's like a cat, right, but 606 00:31:12,880 --> 00:31:16,080 Speaker 1: this complaining kind of whiney sound. You know, she's she's 607 00:31:16,120 --> 00:31:18,120 Speaker 1: hungry or so on and so forth. So he wanted 608 00:31:18,120 --> 00:31:21,120 Speaker 1: to see if he could actually corroborate that. So he 609 00:31:21,240 --> 00:31:23,640 Speaker 1: had these six different scenarios in which a dog was barking, 610 00:31:23,680 --> 00:31:26,719 Speaker 1: and a couple examples is as you actually mentioned, is 611 00:31:27,160 --> 00:31:30,600 Speaker 1: um barking at the door, barking at the gate when 612 00:31:30,600 --> 00:31:33,640 Speaker 1: they're a stranger approached, and he recorded that bark. And 613 00:31:33,680 --> 00:31:37,160 Speaker 1: then another example was when the owner put the dog 614 00:31:37,200 --> 00:31:39,120 Speaker 1: on a leash and then left the dog and the 615 00:31:39,200 --> 00:31:42,080 Speaker 1: dog started barking as to say, you know, don't leave 616 00:31:42,200 --> 00:31:46,360 Speaker 1: or whatnot. And he took these six different recordings and 617 00:31:46,400 --> 00:31:49,440 Speaker 1: played them for dog owners, not the dog owners that 618 00:31:49,600 --> 00:31:53,000 Speaker 1: the dogs are attached to but totally random dog owners, 619 00:31:53,440 --> 00:31:58,760 Speaker 1: and those dog owners could, almost without fail, each time, say, oh, 620 00:31:58,920 --> 00:32:01,120 Speaker 1: I can you know I think that that dog is 621 00:32:01,200 --> 00:32:04,120 Speaker 1: going to be lonely, or that dog wants to play fetch, 622 00:32:04,200 --> 00:32:06,520 Speaker 1: but someone is withholding the ball. I mean, they got 623 00:32:06,560 --> 00:32:10,680 Speaker 1: it really very you know, these specific details right, which 624 00:32:10,720 --> 00:32:14,360 Speaker 1: amazed him that they could map the emotion to the bark, 625 00:32:14,560 --> 00:32:18,760 Speaker 1: which begs the question, are we so now like fine 626 00:32:18,760 --> 00:32:21,720 Speaker 1: tuned with them that we're reading their cues just as 627 00:32:21,800 --> 00:32:25,120 Speaker 1: much as they're reading ours. It's kind of like it's say, 628 00:32:26,000 --> 00:32:27,520 Speaker 1: it's kind of like we're both actors in a play 629 00:32:27,600 --> 00:32:31,120 Speaker 1: and we've both forgotten that it's a play. It's an 630 00:32:31,120 --> 00:32:33,760 Speaker 1: imperfect metaphor. But no, no, I'm going with it. I'm 631 00:32:33,760 --> 00:32:36,640 Speaker 1: going with it. Um. Yeah, you're like Dustin Hoffman, and 632 00:32:36,920 --> 00:32:41,320 Speaker 1: for weeks after when your roles you continue to to 633 00:32:41,400 --> 00:32:44,920 Speaker 1: act as though you're autistic. Yeah, that's right. You argue 634 00:32:44,920 --> 00:32:46,800 Speaker 1: that he never got over the rain Man thing. Now, 635 00:32:46,840 --> 00:32:48,760 Speaker 1: I know, I think it comes out in spurts sometimes. 636 00:32:49,560 --> 00:32:51,480 Speaker 1: I mean, it was a fine performance, don't get me wrong, 637 00:32:52,320 --> 00:32:55,240 Speaker 1: but anyway to to your knowledge, so, I don't know 638 00:32:55,360 --> 00:32:56,880 Speaker 1: that it gets us to this point where we can't 639 00:32:56,920 --> 00:33:00,240 Speaker 1: definitively say does your dog actually love you? We know 640 00:33:00,280 --> 00:33:04,880 Speaker 1: there's a lot of oxytose in flowing. Yeah, the the 641 00:33:04,640 --> 00:33:07,840 Speaker 1: the naturally generated drugs in our body kind of complicate things. 642 00:33:07,880 --> 00:33:10,440 Speaker 1: But yeah, but that can be said pretty much everything 643 00:33:10,640 --> 00:33:12,800 Speaker 1: that we do. Yeah, And on a personal level, I 644 00:33:12,840 --> 00:33:17,120 Speaker 1: can say that my my my dog Ted, I certainly 645 00:33:17,160 --> 00:33:19,600 Speaker 1: loved she was a wonderful dog, and I felt that 646 00:33:19,600 --> 00:33:21,360 Speaker 1: way to her. And I think as a child even 647 00:33:21,360 --> 00:33:23,400 Speaker 1: read to her. I loved her so much. Did she 648 00:33:23,440 --> 00:33:26,719 Speaker 1: pick up anything? Were you able to? No? She was? 649 00:33:26,840 --> 00:33:30,160 Speaker 1: She was no clever Hans or what was the other 650 00:33:30,200 --> 00:33:33,360 Speaker 1: dog's name, chase Er? She was. Yeah. Now there's that. 651 00:33:33,400 --> 00:33:36,840 Speaker 1: There's that cat that writes mystery novels with its owner. 652 00:33:37,200 --> 00:33:40,560 Speaker 1: I forget the author's name. Oh my goodness. That is 653 00:33:41,080 --> 00:33:43,920 Speaker 1: probably the best case of ampomorphization I've ever. I wish 654 00:33:43,920 --> 00:33:45,400 Speaker 1: I could remember her name. I have not read any 655 00:33:45,400 --> 00:33:47,600 Speaker 1: of her work, but if I remember correctly, she used 656 00:33:47,640 --> 00:33:50,560 Speaker 1: to write like kind of saucy literature. Of course, and 657 00:33:50,600 --> 00:33:53,800 Speaker 1: then suddenly she did she started writing, and then she 658 00:33:53,840 --> 00:33:56,880 Speaker 1: started writing mystery novels with her cat, and and has 659 00:33:56,920 --> 00:33:59,120 Speaker 1: continued ever since. Been a great one of those great 660 00:33:59,160 --> 00:34:03,680 Speaker 1: literary partnerships. So yeah, there you go. Well, hey, you know, 661 00:34:03,720 --> 00:34:07,880 Speaker 1: I think I have a little listener mail here. Let's 662 00:34:07,880 --> 00:34:09,759 Speaker 1: see what we have. Ah. Yes, both of these are 663 00:34:09,760 --> 00:34:13,240 Speaker 1: related to our Germ Free Dirty Hippies episode which recently 664 00:34:13,560 --> 00:34:18,200 Speaker 1: went live. Um first we heard from Luke, and Luke writes, Hey, 665 00:34:18,280 --> 00:34:20,279 Speaker 1: Julian Robert, I just listened to the Germ Free Dirty 666 00:34:20,320 --> 00:34:22,840 Speaker 1: Hippies episode. You guys touched on the idea that of 667 00:34:22,920 --> 00:34:24,799 Speaker 1: not using shampoo. I wanted to let you know that 668 00:34:24,880 --> 00:34:28,560 Speaker 1: I haven't used Sam shampoo since November seventeen, two thousand seven, 669 00:34:29,200 --> 00:34:31,680 Speaker 1: and my hair has never been healthier. I used to 670 00:34:31,719 --> 00:34:33,720 Speaker 1: have lots of dandruff and a very since their scalp. 671 00:34:33,960 --> 00:34:36,360 Speaker 1: Now my hair looks healthy, doesn't itch, isn't oily, and 672 00:34:36,440 --> 00:34:39,160 Speaker 1: doesn't smell. It got really oily for the first three 673 00:34:39,160 --> 00:34:41,080 Speaker 1: weeks or so of not using shampoo, but then it 674 00:34:41,120 --> 00:34:43,399 Speaker 1: seemed to balance out. I have so much shorter hair, 675 00:34:43,440 --> 00:34:45,239 Speaker 1: and it's about two inches long on top, so I'm 676 00:34:45,239 --> 00:34:47,239 Speaker 1: sure this makes it easier than if I had had 677 00:34:47,320 --> 00:34:49,480 Speaker 1: really long hair. I know some people who don't use 678 00:34:49,480 --> 00:34:51,560 Speaker 1: shampoo rents it out every so often with a mix 679 00:34:51,560 --> 00:34:53,920 Speaker 1: of apple cider, vinegar and water. I'm not sure what 680 00:34:54,040 --> 00:34:57,200 Speaker 1: this does. Maybe it helps, uh get rid of oil. Anyway, 681 00:34:57,480 --> 00:35:00,680 Speaker 1: I've never thanked YouTube for the awesome show, so I 682 00:35:00,680 --> 00:35:02,520 Speaker 1: thought i'd take this opportunity to write in and say 683 00:35:02,560 --> 00:35:06,200 Speaker 1: thanks for making me smarter. Well, if you're welcome, that's stuff. 684 00:35:06,920 --> 00:35:08,880 Speaker 1: That's great. Yeah, and actually we've got a lot of 685 00:35:08,920 --> 00:35:12,239 Speaker 1: anecdotal evidence about this, I would say, if you can 686 00:35:12,239 --> 00:35:15,080 Speaker 1: call it evidence. And um, it was actually really hurtening. 687 00:35:15,120 --> 00:35:17,680 Speaker 1: I was like, wow, people are really it's not just me. 688 00:35:17,800 --> 00:35:21,560 Speaker 1: Who's who's interested in this shampoo question. Yeah, I've cut down. 689 00:35:22,239 --> 00:35:25,480 Speaker 1: I'm going like two days at a time without actually 690 00:35:26,120 --> 00:35:28,640 Speaker 1: shampooing my hair. Her coat looks very shiny, I mean 691 00:35:28,680 --> 00:35:30,239 Speaker 1: in a good way. Look, well that I also had 692 00:35:30,239 --> 00:35:32,400 Speaker 1: bacon this morning. You know, well that'll do. That's a 693 00:35:32,480 --> 00:35:35,399 Speaker 1: machine they can do. But um oh, and we also 694 00:35:35,400 --> 00:35:38,000 Speaker 1: have another email. This one is from Thomas, and Thomas 695 00:35:38,040 --> 00:35:41,680 Speaker 1: writes in about this and uh, this is a rather 696 00:35:41,680 --> 00:35:43,319 Speaker 1: long email, so I'm just gonna read part of it. 697 00:35:43,600 --> 00:35:46,800 Speaker 1: He says. Anyway, let's just say that in the past 698 00:35:46,840 --> 00:35:49,800 Speaker 1: twelve months, I've probably used shampoo maybe six or seven times. 699 00:35:50,080 --> 00:35:52,200 Speaker 1: Until two weeks ago, I had a use shampoo and 700 00:35:52,239 --> 00:35:55,239 Speaker 1: probably six months. Generally speaking, I only use shampoo if 701 00:35:55,239 --> 00:35:57,360 Speaker 1: I go to the beach or swimming a heavily chlorinated pool, 702 00:35:57,600 --> 00:35:59,879 Speaker 1: though I do use condition about once a month. Let 703 00:35:59,880 --> 00:36:02,520 Speaker 1: me just say my hair is a gorgeous That's probably 704 00:36:02,520 --> 00:36:05,799 Speaker 1: the most narcissistic sentence the twenty year old male can either. 705 00:36:06,040 --> 00:36:09,280 Speaker 1: But it is random. Women, that's right, plural have stopped 706 00:36:09,320 --> 00:36:11,400 Speaker 1: me just to say, hey, I've seen you around the 707 00:36:11,440 --> 00:36:13,200 Speaker 1: office and I just wanted to say, I don't know 708 00:36:13,239 --> 00:36:15,759 Speaker 1: what you do, but you have gorgeous hair. Well, I 709 00:36:16,040 --> 00:36:19,840 Speaker 1: think we both can can relate to that absolutely. Yeah, 710 00:36:20,600 --> 00:36:22,239 Speaker 1: get it in the break room all the time. Yeah, 711 00:36:22,320 --> 00:36:24,040 Speaker 1: Jerry had to lock the door to keep the women 712 00:36:24,160 --> 00:36:26,520 Speaker 1: out the otherwise they'd be in here complimenting us on 713 00:36:26,560 --> 00:36:30,839 Speaker 1: our hair right now anyway, um Thomas continues, you can't 714 00:36:30,840 --> 00:36:33,759 Speaker 1: imagine the speed with which a human face can transition 715 00:36:33,800 --> 00:36:35,759 Speaker 1: to object horror. When I quote how long it's been 716 00:36:35,760 --> 00:36:38,279 Speaker 1: since I've used shampoo, it's quite a site. The worst 717 00:36:38,320 --> 00:36:40,520 Speaker 1: part of terminating your relationship with shampoo is the first 718 00:36:40,520 --> 00:36:43,160 Speaker 1: two months or so. During that two month period, your 719 00:36:43,160 --> 00:36:46,040 Speaker 1: scalp seems to freak out and overproduce oils lots of 720 00:36:46,040 --> 00:36:49,640 Speaker 1: warm showers and scalp massaging, like Julie mentioned, help a 721 00:36:49,640 --> 00:36:52,440 Speaker 1: great deal, but it's still kind of grows there. You go, 722 00:36:52,840 --> 00:36:56,359 Speaker 1: that's the secret to healthy hair. Yeah, so you know, 723 00:36:56,520 --> 00:37:00,680 Speaker 1: if you have any more anecdotes of your own experiences 724 00:37:00,719 --> 00:37:03,880 Speaker 1: going with the No Pooh method of hair care, UM, 725 00:37:04,000 --> 00:37:06,720 Speaker 1: let us know. I mean, we can't. That's short for shampoose. 726 00:37:06,760 --> 00:37:09,319 Speaker 1: Anybody's confused about that. Um, if you have any other 727 00:37:09,680 --> 00:37:12,080 Speaker 1: No Pooh situations, let us know about that. We're always 728 00:37:12,080 --> 00:37:16,640 Speaker 1: game for scatological content. Uh and uh and uh. And 729 00:37:16,640 --> 00:37:19,719 Speaker 1: if you have anything to add about this dog episode, 730 00:37:19,840 --> 00:37:22,520 Speaker 1: let us know. I'm sure, I'm I know that a 731 00:37:22,600 --> 00:37:25,520 Speaker 1: number of you were dog owners and uh and and 732 00:37:25,600 --> 00:37:28,040 Speaker 1: if you're like me as a cat owner, then you 733 00:37:28,040 --> 00:37:29,759 Speaker 1: you probably spend a lot of time just trying to 734 00:37:29,760 --> 00:37:33,000 Speaker 1: figure out this weird situation in which a furry quadruped 735 00:37:33,360 --> 00:37:36,839 Speaker 1: lives in your home, sleeps on your bed and uh 736 00:37:36,840 --> 00:37:39,160 Speaker 1: and we act like it's the most normal thing in 737 00:37:39,200 --> 00:37:41,600 Speaker 1: the world. It's not. It's pretty weird. And you occasionally 738 00:37:41,640 --> 00:37:45,440 Speaker 1: dressed up as a pirate. I mean that's yeah, they 739 00:37:45,560 --> 00:37:47,480 Speaker 1: want to hear about that. Yes, So so let us know. 740 00:37:47,560 --> 00:37:51,160 Speaker 1: It's it's fascinating and uh uh, and I'm curious to 741 00:37:51,160 --> 00:37:54,200 Speaker 1: see what everybody's in particular thoughts on it are. You 742 00:37:54,200 --> 00:37:56,160 Speaker 1: can also find us on Facebook and Twitter. We're blow 743 00:37:56,200 --> 00:37:58,520 Speaker 1: the Mind on both of those, and you can drop 744 00:37:58,560 --> 00:38:00,319 Speaker 1: us a line at blow the Mind at how stuff 745 00:38:00,320 --> 00:38:06,239 Speaker 1: works dot com. For more on this and thousands of 746 00:38:06,239 --> 00:38:09,040 Speaker 1: other topics, visit how stuff works dot com. To learn 747 00:38:09,040 --> 00:38:11,880 Speaker 1: more about the podcast, click on the podcast icon in 748 00:38:11,920 --> 00:38:14,920 Speaker 1: the upper right corner of our homepage. The How Stuff 749 00:38:14,920 --> 00:38:18,440 Speaker 1: Works iPhone app has a RYE. Download it today on iTunes.