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 --> 00:00:13,600 Speaker 1: Works dot com. Hey, you're welcome to stuff to blow 3 00:00:13,680 --> 00:00:15,840 Speaker 1: your mind. My name is Robert Lamb and I'm Julie. 4 00:00:16,560 --> 00:00:19,960 Speaker 1: We were just looking at an Onion article, weren't we were? Yeah. 5 00:00:19,960 --> 00:00:27,360 Speaker 1: It was from classic from seven. Uh, babies are stupid, Yeah, 6 00:00:27,760 --> 00:00:30,120 Speaker 1: which which was a phenomenally funny piece of the time 7 00:00:30,200 --> 00:00:33,040 Speaker 1: because you know, you read all this stuff about, oh, 8 00:00:33,120 --> 00:00:35,159 Speaker 1: babies are really you know, there's a lot going on 9 00:00:35,200 --> 00:00:36,640 Speaker 1: with the with the mind of an infant, and this 10 00:00:36,880 --> 00:00:38,479 Speaker 1: sort of turned that on its head by saying, you know, 11 00:00:38,680 --> 00:00:42,080 Speaker 1: actually babies are really stupid, because it's easy to to 12 00:00:42,159 --> 00:00:44,680 Speaker 1: sort of think think that on the surface because they 13 00:00:44,720 --> 00:00:49,319 Speaker 1: are they are helpless. Uh, they don't really don't really 14 00:00:49,400 --> 00:00:52,320 Speaker 1: understand how things work. They can't talk. They can't talk. 15 00:00:52,479 --> 00:00:57,440 Speaker 1: They're just crapping themselves like crazy, drooling and and and 16 00:00:57,520 --> 00:01:00,280 Speaker 1: just having intense emotional reactions to things, be at a 17 00:01:00,280 --> 00:01:05,160 Speaker 1: peekaboo game, Uh, some shiny object or um, uh, you know, 18 00:01:05,360 --> 00:01:09,280 Speaker 1: just or something even mildly unpleasant just set them off. 19 00:01:10,160 --> 00:01:14,640 Speaker 1: But turns out that they are learning machines. Yes, the 20 00:01:14,760 --> 00:01:18,319 Speaker 1: larval human is pretty amazing. They Yeah, they're absolutely amazing 21 00:01:18,480 --> 00:01:21,080 Speaker 1: in the same way that like a larval insight like it. 22 00:01:21,080 --> 00:01:22,959 Speaker 1: It doesn't look like much, but its whole thing is 23 00:01:23,080 --> 00:01:26,000 Speaker 1: eat and grow, eat and grow. Similar thing with the 24 00:01:26,120 --> 00:01:29,039 Speaker 1: with the larval human. It's it's it's whole mission is 25 00:01:29,080 --> 00:01:31,400 Speaker 1: to learn and grow, learn and grow and eat and 26 00:01:31,440 --> 00:01:34,960 Speaker 1: poop a lot. But learn, grow and think that. I think, yeah, 27 00:01:35,360 --> 00:01:38,280 Speaker 1: and this is very different for our species. Um. There 28 00:01:38,280 --> 00:01:41,319 Speaker 1: are some really good uh articles out there about this 29 00:01:41,440 --> 00:01:44,679 Speaker 1: extended childhood that we have, Like why in the world 30 00:01:44,720 --> 00:01:49,000 Speaker 1: does it take it so long to acquire language to 31 00:01:49,160 --> 00:01:52,880 Speaker 1: grow up to fend for ourselves? Yeah, because there are 32 00:01:52,920 --> 00:01:56,040 Speaker 1: their prey and most prey animals out there, such as 33 00:01:56,120 --> 00:02:00,080 Speaker 1: you know, deer, antelope, what have you. They're born and 34 00:02:00,080 --> 00:02:02,320 Speaker 1: they have to be on their feet and uh and 35 00:02:02,320 --> 00:02:05,320 Speaker 1: and running in pretty short order in order to survive. 36 00:02:05,400 --> 00:02:10,160 Speaker 1: There's no sticking around the nest necessarily or you know, 37 00:02:10,200 --> 00:02:14,519 Speaker 1: they just they have to turn into the adults very fast. Um. Likewise, 38 00:02:14,720 --> 00:02:18,400 Speaker 1: the kitten that my wife found is currently in a 39 00:02:18,440 --> 00:02:24,400 Speaker 1: box in our house. Bean, but like, uh, like pretty 40 00:02:24,440 --> 00:02:26,280 Speaker 1: pretty quickly, like we first got him. You know, he's 41 00:02:26,320 --> 00:02:29,239 Speaker 1: all you know, awkward and falling down and all and 42 00:02:29,240 --> 00:02:32,000 Speaker 1: and but and he's still awkward and falling down, but 43 00:02:32,080 --> 00:02:35,400 Speaker 1: you can already see him doing the things that cats 44 00:02:35,440 --> 00:02:38,000 Speaker 1: have to do. He's already running through the exercises of 45 00:02:38,080 --> 00:02:41,280 Speaker 1: hunting and pouncing and and you know, it's like all 46 00:02:41,320 --> 00:02:43,840 Speaker 1: the programming is there. And as soon as his body 47 00:02:43,880 --> 00:02:47,160 Speaker 1: catches up in just you know, a matter of you know, 48 00:02:47,480 --> 00:02:50,240 Speaker 1: months or weeks, he's gonna be good to go. He'll 49 00:02:50,240 --> 00:02:51,919 Speaker 1: be up and running. He doesn't need to be put 50 00:02:51,919 --> 00:02:54,519 Speaker 1: in a sling for ten months, right and carry it 51 00:02:54,520 --> 00:02:57,280 Speaker 1: all right. He also doesn't need to learn all that much, right, 52 00:02:57,400 --> 00:02:59,560 Speaker 1: So compared to other species, we humans, we have a 53 00:02:59,639 --> 00:03:03,200 Speaker 1: lunch a much longer period of immaturity, and psychologist Alice 54 00:03:03,320 --> 00:03:06,120 Speaker 1: and Gothnik actually says that there's a reason for that, 55 00:03:06,120 --> 00:03:10,239 Speaker 1: that long periods of immaturity are correlated to higher degree 56 00:03:10,240 --> 00:03:13,920 Speaker 1: of flexibility, intelligence, and learning. So, in other words, it's 57 00:03:13,960 --> 00:03:17,000 Speaker 1: neo cortex that we got, you know, thousands of thousands 58 00:03:17,040 --> 00:03:18,840 Speaker 1: of years ago that that that helps us so much 59 00:03:18,880 --> 00:03:22,280 Speaker 1: in our communication. Really takes a lot of effort, a 60 00:03:22,280 --> 00:03:24,880 Speaker 1: lot of resources to sort of feed that before we 61 00:03:24,919 --> 00:03:29,440 Speaker 1: can become uh, totally cognizance in a way that we 62 00:03:29,480 --> 00:03:31,840 Speaker 1: think of ourselves as adults. Right, And we see the 63 00:03:31,840 --> 00:03:35,960 Speaker 1: scenario in the classic crow versus chicken um argument, right, 64 00:03:36,240 --> 00:03:39,440 Speaker 1: because the chicken is is pretty stupid. There's not a 65 00:03:39,480 --> 00:03:41,520 Speaker 1: lot going on with the chicken, and they're up and 66 00:03:41,560 --> 00:03:44,120 Speaker 1: running pretty soon. They're up and running pretty soon, pretty fast. 67 00:03:44,800 --> 00:03:46,720 Speaker 1: You know, chick doesn't say a chicken very long. Pretty 68 00:03:46,760 --> 00:03:49,640 Speaker 1: soon it's a stupid chicken. Not so the crow. The 69 00:03:49,680 --> 00:03:52,480 Speaker 1: crow is pretty brilliant. I mean, the crow is a mean. 70 00:03:52,520 --> 00:03:55,960 Speaker 1: There have been all these fabulous studies about crow intelligence. 71 00:03:55,960 --> 00:03:57,640 Speaker 1: We could, we could and probably should do a whole 72 00:03:57,680 --> 00:04:00,520 Speaker 1: episode on crowl intelligence because their tool user they can 73 00:04:00,520 --> 00:04:03,040 Speaker 1: be trained to put coins, to collect coins and put 74 00:04:03,040 --> 00:04:08,280 Speaker 1: them into machines. Um. They're they're, they're they're just incredible, 75 00:04:09,360 --> 00:04:14,120 Speaker 1: incredible birds. But they also have a longer period of development. Well, 76 00:04:14,160 --> 00:04:16,599 Speaker 1: and as Alison up Nick says, one one of those 77 00:04:16,640 --> 00:04:18,920 Speaker 1: creatures ends up on the cover of Science and one 78 00:04:19,160 --> 00:04:22,039 Speaker 1: ends up in your soup pot. So there's there's a 79 00:04:22,080 --> 00:04:25,520 Speaker 1: reason for that. Right. Again, crows do have a longer 80 00:04:25,560 --> 00:04:28,880 Speaker 1: period of immaturity. Uh. But one of the things that 81 00:04:28,920 --> 00:04:31,799 Speaker 1: I think is really interesting is again this idea of 82 00:04:32,279 --> 00:04:36,080 Speaker 1: building up the neo cortex is communication centers in the 83 00:04:36,120 --> 00:04:40,280 Speaker 1: brain and um, we have touched on this a bit 84 00:04:40,400 --> 00:04:44,080 Speaker 1: in terms of babies, in their ability to mimic even 85 00:04:44,279 --> 00:04:48,840 Speaker 1: um they're crying. We talked about this German accent, yeah, 86 00:04:48,880 --> 00:04:52,520 Speaker 1: German accent or a French accent days after they're born, 87 00:04:52,960 --> 00:04:57,000 Speaker 1: such as their ability to to really absorb information about 88 00:04:57,160 --> 00:05:01,160 Speaker 1: how language works. And I thought that it was really 89 00:05:01,200 --> 00:05:05,160 Speaker 1: interesting to start this talk off with UM with language 90 00:05:05,320 --> 00:05:08,719 Speaker 1: sort of like the crux of our being, and I 91 00:05:08,800 --> 00:05:11,520 Speaker 1: wanted I've heard it described as the the operating system 92 00:05:11,600 --> 00:05:13,719 Speaker 1: for the human brain. Yeah, I mean, we're the We're 93 00:05:13,720 --> 00:05:16,520 Speaker 1: the hardware that you need windows on their right to 94 00:05:16,600 --> 00:05:20,039 Speaker 1: run it. Well, languages are windows. Yeah. Elizabeth Balky, she's 95 00:05:20,040 --> 00:05:22,640 Speaker 1: a cognitive psychologist. She has actually said like, this is 96 00:05:22,680 --> 00:05:25,240 Speaker 1: the reason why why we can do what we can do. 97 00:05:25,600 --> 00:05:31,320 Speaker 1: We have this competentive, comgnitorial approach to life because of language. 98 00:05:31,400 --> 00:05:35,080 Speaker 1: We can um, you know, enter into these scenarios where 99 00:05:35,200 --> 00:05:38,279 Speaker 1: let's say you're you're year old and you're trying to 100 00:05:38,320 --> 00:05:42,159 Speaker 1: figure out three dimensional areas. Um. But then you begin 101 00:05:42,240 --> 00:05:45,000 Speaker 1: to name things, and then you start to be able 102 00:05:45,040 --> 00:05:49,240 Speaker 1: to put this again, languages at the bedrock of this ability. 103 00:05:49,560 --> 00:05:52,240 Speaker 1: You begin to put these concepts with words, and you're 104 00:05:52,279 --> 00:05:55,920 Speaker 1: just lapping on more and more knowledge. Without this ability, 105 00:05:55,920 --> 00:05:59,720 Speaker 1: this language, then, which makes us uniquely human in terms 106 00:05:59,720 --> 00:06:03,800 Speaker 1: of its complexity, we wouldn't be the people we are today, 107 00:06:03,839 --> 00:06:06,680 Speaker 1: even just sitting here talking about this. Right, Like you 108 00:06:06,720 --> 00:06:09,800 Speaker 1: think of like what words do for us? Um, Like 109 00:06:10,040 --> 00:06:14,200 Speaker 1: you think of a word like genocide, one word that 110 00:06:14,200 --> 00:06:18,160 Speaker 1: that summons an intense amount of information about something that's 111 00:06:18,240 --> 00:06:21,080 Speaker 1: very complicated. Um Like, if I'm just if I don't 112 00:06:21,120 --> 00:06:24,800 Speaker 1: have a word for genocide, then they're trying to think 113 00:06:24,839 --> 00:06:28,640 Speaker 1: about it, like would occupy the entire mind, you know, 114 00:06:28,720 --> 00:06:30,760 Speaker 1: and you still wouldn't be able to grasp it. You 115 00:06:30,760 --> 00:06:32,800 Speaker 1: can sort of wrap it up in that term. And 116 00:06:32,839 --> 00:06:36,120 Speaker 1: then something like ballet is pretty complicated as well, but 117 00:06:36,160 --> 00:06:38,159 Speaker 1: I can wrap it up under the term ballet, and 118 00:06:38,200 --> 00:06:41,599 Speaker 1: then I can simultaneously hold both the word ballet and 119 00:06:41,600 --> 00:06:46,279 Speaker 1: genocide in my mind and collide those ideas, which you 120 00:06:46,279 --> 00:06:48,840 Speaker 1: can't do unless you have words for them. Right, And 121 00:06:48,920 --> 00:06:51,039 Speaker 1: this is an amazing thing that we can do. And 122 00:06:51,080 --> 00:06:54,640 Speaker 1: it turns out that, um, that the seeds for that 123 00:06:54,760 --> 00:06:57,360 Speaker 1: are present at birth. But before I want to talk 124 00:06:57,400 --> 00:06:59,080 Speaker 1: a little bit more about language, I did want to 125 00:06:59,080 --> 00:07:02,520 Speaker 1: mention Sean pj At this one in the century. He 126 00:07:02,560 --> 00:07:05,880 Speaker 1: wrote a book called Origins of Intelligence and Children, which 127 00:07:05,920 --> 00:07:08,480 Speaker 1: in and of itself is sort of like a revelation, 128 00:07:08,560 --> 00:07:11,520 Speaker 1: because what intelligence and children at that time period. Yeah, 129 00:07:11,560 --> 00:07:14,120 Speaker 1: just the idea that they're just bumbling buffoons that still 130 00:07:14,160 --> 00:07:17,000 Speaker 1: have everything in the world to learn and then under 131 00:07:17,000 --> 00:07:19,680 Speaker 1: certain definitions, aren't even real people yet, right They're not 132 00:07:19,800 --> 00:07:23,080 Speaker 1: exactly they're not they don't quite have a personhood right yet. Um, 133 00:07:23,160 --> 00:07:25,760 Speaker 1: they haven't acquired enough information. So that's what they used 134 00:07:25,760 --> 00:07:29,320 Speaker 1: to think of as as children. Just who are you know, 135 00:07:29,720 --> 00:07:33,600 Speaker 1: soon to be adults that haven't acquired enough information? Um. 136 00:07:33,640 --> 00:07:36,360 Speaker 1: But what he found is that qualitative thinking changes. In 137 00:07:36,400 --> 00:07:39,000 Speaker 1: other words, different kinds of learning comes online at different 138 00:07:39,000 --> 00:07:41,480 Speaker 1: points in development, and so you kind of think of 139 00:07:41,520 --> 00:07:44,200 Speaker 1: it as like we're preloaded with these modules in our brain, 140 00:07:44,240 --> 00:07:46,480 Speaker 1: but they don't fully develop until they get the cues 141 00:07:46,560 --> 00:07:49,120 Speaker 1: that they need. So I did want to flip over 142 00:07:49,320 --> 00:07:53,680 Speaker 1: really quickly and talk about Patricia Cool. She has a 143 00:07:53,800 --> 00:07:57,600 Speaker 1: great talk called The Linguistic Genius of Babies, and she 144 00:07:57,720 --> 00:08:02,200 Speaker 1: says that from zero to six months, babies are quote 145 00:08:02,560 --> 00:08:06,280 Speaker 1: citizens of the world, and they can distinguish between pronunciations 146 00:08:06,440 --> 00:08:09,640 Speaker 1: in every language, something that no adult brain can do, 147 00:08:10,280 --> 00:08:13,360 Speaker 1: because we eventually get pretty specialized in our language right 148 00:08:13,360 --> 00:08:16,280 Speaker 1: in our abilities. And she says that between eight and 149 00:08:16,360 --> 00:08:20,560 Speaker 1: ten months, babies exhibits statistical computation skills and their ability 150 00:08:20,600 --> 00:08:23,120 Speaker 1: to pick up and analyze language. So in other words, 151 00:08:23,160 --> 00:08:26,520 Speaker 1: they can take into account the relative frequency of the 152 00:08:26,560 --> 00:08:31,560 Speaker 1: sounds they hear and the transitional probabilities between syllables, and 153 00:08:31,640 --> 00:08:34,760 Speaker 1: this is what she says is statistical learning. So this 154 00:08:34,800 --> 00:08:37,360 Speaker 1: is all happening in their minds as we adults throw 155 00:08:37,400 --> 00:08:41,559 Speaker 1: a bunch of baby talk at them. Parentees, it's actually 156 00:08:41,720 --> 00:08:46,040 Speaker 1: called the parentees, although also called mothery'se uh. But it's 157 00:08:46,040 --> 00:08:50,599 Speaker 1: actually really important because there's that that sort of this 158 00:08:50,679 --> 00:08:53,760 Speaker 1: sort of changes in tone are important for the child 159 00:08:53,800 --> 00:08:58,280 Speaker 1: to begin to understand these different melodies of language. But 160 00:08:58,400 --> 00:09:01,440 Speaker 1: that zero to six months they is really fascinating to 161 00:09:01,480 --> 00:09:04,199 Speaker 1: me because if I hear Mandarin, I'm not going to 162 00:09:04,280 --> 00:09:07,920 Speaker 1: be able to distinguish between certain syllables because it is 163 00:09:07,920 --> 00:09:11,560 Speaker 1: not native to our standing. Yes, it's just an orange 164 00:09:11,559 --> 00:09:14,600 Speaker 1: to me, it's not a language barely making a sound, 165 00:09:14,800 --> 00:09:18,280 Speaker 1: but yeah, and why or are people always going I 166 00:09:18,360 --> 00:09:21,880 Speaker 1: was gonna make a really badgeck, but throwing ranges at 167 00:09:21,880 --> 00:09:27,000 Speaker 1: each other and trying to communicate instrument. I'm sorry, no, 168 00:09:27,040 --> 00:09:30,960 Speaker 1: not the manteline nice but no, I mean this is fascinating, 169 00:09:31,000 --> 00:09:33,440 Speaker 1: like how my ear has shut that out, that ability. 170 00:09:33,600 --> 00:09:37,080 Speaker 1: But these year to six month old kids, these infants 171 00:09:37,160 --> 00:09:41,079 Speaker 1: can actually just distinguish between these sounds, and she a. 172 00:09:41,160 --> 00:09:45,439 Speaker 1: Patricia Kool also says that kids by age seven begin 173 00:09:45,520 --> 00:09:48,120 Speaker 1: to fall off of linguistic map. What she means to 174 00:09:48,160 --> 00:09:53,640 Speaker 1: say is that language acquisition is absolutely open and optimal 175 00:09:53,880 --> 00:09:57,240 Speaker 1: before age seven. So and of course, you know, most 176 00:09:57,240 --> 00:10:01,160 Speaker 1: people our age didn't begin language lessons until later on 177 00:10:01,200 --> 00:10:03,160 Speaker 1: in their lives, which is sort of the wrong thing 178 00:10:03,200 --> 00:10:06,560 Speaker 1: to do, um. But that because by the time year seven, 179 00:10:06,640 --> 00:10:09,520 Speaker 1: your brain changes is and you're you're pruning a lot 180 00:10:09,559 --> 00:10:12,400 Speaker 1: of the neural connections that you don't necessarily need. So 181 00:10:12,440 --> 00:10:15,120 Speaker 1: we kind of lose that ability, um to some extent. 182 00:10:15,600 --> 00:10:17,480 Speaker 1: But one of the things that she points out is 183 00:10:17,559 --> 00:10:21,160 Speaker 1: that this one to one interaction is really important. You 184 00:10:21,240 --> 00:10:24,840 Speaker 1: have to see someone else's eyes in order to acquire language. 185 00:10:25,400 --> 00:10:27,560 Speaker 1: And we'll talk about the eyes and the importance about 186 00:10:27,600 --> 00:10:29,880 Speaker 1: that a little bit. So we we did a whole 187 00:10:29,880 --> 00:10:32,880 Speaker 1: episode I think more than one on math. And in 188 00:10:32,960 --> 00:10:37,599 Speaker 1: that we mentioned that the babies are capable of algorithmic 189 00:10:37,679 --> 00:10:39,880 Speaker 1: thinking even in early age. They don't have they don't 190 00:10:39,880 --> 00:10:42,640 Speaker 1: have numbers. They don't have this and this gets into 191 00:10:42,640 --> 00:10:44,839 Speaker 1: the whole question of his again his math a human 192 00:10:44,920 --> 00:10:47,960 Speaker 1: invention or a human discovery or something else. But the 193 00:10:48,000 --> 00:10:51,480 Speaker 1: idea here is that even though babies can't rattle off 194 00:10:51,480 --> 00:10:55,840 Speaker 1: one through ten, they have numbers. Since they can, they 195 00:10:55,840 --> 00:10:59,240 Speaker 1: can think algorithmically about the world around them, which is 196 00:11:00,000 --> 00:11:01,520 Speaker 1: which if you stop and think about that, I mean, 197 00:11:01,520 --> 00:11:07,360 Speaker 1: it's pretty phenomenal. Versus are sort of accepted mainstream viewing 198 00:11:07,440 --> 00:11:10,160 Speaker 1: of Oh, the child must be taught language, it must 199 00:11:10,200 --> 00:11:13,800 Speaker 1: be taught math, but it already has math. Yeah, And 200 00:11:13,840 --> 00:11:17,360 Speaker 1: this is why artificial intelligence is interested in babies because 201 00:11:17,960 --> 00:11:21,400 Speaker 1: in this way, as Elizabeth spoke, he says, they are root. 202 00:11:22,080 --> 00:11:26,200 Speaker 1: UM it's where human cognition and organization of the human 203 00:11:26,240 --> 00:11:28,080 Speaker 1: mind begins. And of course we want to try to 204 00:11:28,120 --> 00:11:31,760 Speaker 1: do this with computers as best that we can. UM. 205 00:11:31,800 --> 00:11:35,480 Speaker 1: I wanted to mention the world's first stored program electronic 206 00:11:35,520 --> 00:11:39,120 Speaker 1: digital computer. UH. This was in and it was called 207 00:11:39,160 --> 00:11:43,400 Speaker 1: the Small Scale Experimental Machine. It was also nicknamed Baby 208 00:11:44,440 --> 00:11:46,640 Speaker 1: and one of the programs that ran on it was 209 00:11:46,720 --> 00:11:49,640 Speaker 1: designed by Alan Turning. And we've talked about Alan Turning 210 00:11:49,679 --> 00:11:52,400 Speaker 1: before in terms of AI. He's a pioneer UM in 211 00:11:52,520 --> 00:11:57,800 Speaker 1: artificial intelligence and very I know, I was just thinking 212 00:11:57,840 --> 00:12:00,800 Speaker 1: about that yesterday. I was when I was revisiting some material. Yeah, 213 00:12:00,880 --> 00:12:03,440 Speaker 1: there's a great Radio Lab episode. I think it's shorty 214 00:12:03,600 --> 00:12:05,160 Speaker 1: or maybe it was a long I don't know, but 215 00:12:05,200 --> 00:12:09,079 Speaker 1: there was a reason Radio episode about him. That's really heartbreaking. Yeah, 216 00:12:09,120 --> 00:12:11,600 Speaker 1: he is a is an individual, is very very interesting 217 00:12:11,640 --> 00:12:16,480 Speaker 1: and UM certainly brilliant. He was. But Alison Gothnick talks 218 00:12:16,520 --> 00:12:19,480 Speaker 1: about Touring. She says that the classic Turing palm is 219 00:12:19,520 --> 00:12:22,040 Speaker 1: could you get a computer to be so sophisticated that 220 00:12:22,080 --> 00:12:24,199 Speaker 1: you couldn't tell the difference between the computer and a person. 221 00:12:25,160 --> 00:12:27,080 Speaker 1: But then Touring said that there was an even more 222 00:12:27,160 --> 00:12:31,880 Speaker 1: profound question, which was could you get a computer give 223 00:12:31,920 --> 00:12:34,360 Speaker 1: it the kind of data that every human being gets 224 00:12:34,400 --> 00:12:36,200 Speaker 1: as a child, and have it learned the kinds of 225 00:12:36,240 --> 00:12:39,320 Speaker 1: things things that a child can learn. Again, this is 226 00:12:39,360 --> 00:12:43,320 Speaker 1: the root uh brain that we're talking about, and certainly 227 00:12:43,360 --> 00:12:45,920 Speaker 1: machine learning is a is a huge part of our 228 00:12:46,080 --> 00:12:50,240 Speaker 1: ongoing development of AI. You know, like in creating machines 229 00:12:50,280 --> 00:12:52,640 Speaker 1: that work alongside humans. We want to do that so 230 00:12:52,679 --> 00:12:55,199 Speaker 1: that they can they can learn from their environment. So 231 00:12:55,320 --> 00:12:57,920 Speaker 1: machine learning is is key. And if you want to learn, 232 00:12:58,480 --> 00:13:02,040 Speaker 1: you learn to discover how something earns. The infant is 233 00:13:02,080 --> 00:13:04,559 Speaker 1: the place to look, right, And she says because they 234 00:13:04,600 --> 00:13:08,280 Speaker 1: have inductive learning techniques as well, just like computers. And 235 00:13:08,360 --> 00:13:10,360 Speaker 1: she even brings up the point that about fifteen years 236 00:13:10,360 --> 00:13:16,400 Speaker 1: ago researchers created Baiesian causal graphical models. Baisian is basically 237 00:13:16,440 --> 00:13:20,720 Speaker 1: like this inductive learning, right um. And these models map 238 00:13:20,760 --> 00:13:24,640 Speaker 1: out the way the world works for computers and also 239 00:13:24,679 --> 00:13:27,920 Speaker 1: mapped out patterns of probability. And this was really an 240 00:13:27,960 --> 00:13:33,680 Speaker 1: advance in computational um formal computation, I should say. In 241 00:13:33,720 --> 00:13:37,400 Speaker 1: about that same time, uh, that these computational systems were 242 00:13:37,400 --> 00:13:41,040 Speaker 1: coming online, cognitive psychologists began to form the idea that 243 00:13:41,080 --> 00:13:44,280 Speaker 1: babies are doing very much the same thing. So you 244 00:13:44,360 --> 00:13:46,920 Speaker 1: brought up this number sense that that kids have. And 245 00:13:46,920 --> 00:13:50,000 Speaker 1: what we're talking about here is Baiesian reasoning. That they 246 00:13:50,000 --> 00:13:53,080 Speaker 1: can take a random sample and understand the relationship between 247 00:13:53,160 --> 00:13:56,840 Speaker 1: that sample and the population is drawn from right, so 248 00:13:56,880 --> 00:14:00,000 Speaker 1: they can tell they can tell the difference between um, 249 00:14:00,320 --> 00:14:03,560 Speaker 1: three red balls and nine red balls. Yeah, not so much. 250 00:14:03,600 --> 00:14:06,440 Speaker 1: Maybe three red balls and four red balls. You know, 251 00:14:06,480 --> 00:14:10,600 Speaker 1: it becomes an algorithmic distinction there. But but yeah, they've 252 00:14:10,600 --> 00:14:13,120 Speaker 1: they've already got that hard wired in. Yeah. I mean 253 00:14:13,120 --> 00:14:15,360 Speaker 1: they are kind of like born accountants. Because if you 254 00:14:15,400 --> 00:14:19,000 Speaker 1: give a baby a picture an array of dots, and 255 00:14:19,040 --> 00:14:21,520 Speaker 1: there are four dots, and you have another array of 256 00:14:21,640 --> 00:14:25,840 Speaker 1: twelve dots, and you play sounds that four sounds, they 257 00:14:25,880 --> 00:14:28,120 Speaker 1: will begin to look at the four dots. If you 258 00:14:28,200 --> 00:14:32,920 Speaker 1: play twelve sounds, they look at the array of twelve dots. 259 00:14:33,320 --> 00:14:35,640 Speaker 1: And it doesn't matter how much time or the length 260 00:14:35,720 --> 00:14:37,800 Speaker 1: of the sound, as long as there are four of them, right, 261 00:14:37,920 --> 00:14:39,800 Speaker 1: or twelve of them, they will still do this. They 262 00:14:39,840 --> 00:14:42,880 Speaker 1: still have this understanding of more and less. As you say, so, 263 00:14:42,960 --> 00:14:45,080 Speaker 1: babies come preloaded with a little bit of math, and 264 00:14:45,120 --> 00:14:47,000 Speaker 1: they also come preloaded with a little bit of physics, 265 00:14:47,120 --> 00:14:49,840 Speaker 1: which is pretty crazy because it's it's again, it's easy 266 00:14:49,920 --> 00:14:51,400 Speaker 1: to think of the babies like the baby has no 267 00:14:51,480 --> 00:14:54,840 Speaker 1: idea how the world works. You know, it's this everything 268 00:14:54,920 --> 00:14:57,960 Speaker 1: is magical to this creature. Right. Uh, you know, he 269 00:14:58,200 --> 00:15:00,760 Speaker 1: thinks I disappear when I do my uh my my 270 00:15:00,800 --> 00:15:05,200 Speaker 1: peekaboot hands. But that's not the case, because ultimately this 271 00:15:05,320 --> 00:15:09,520 Speaker 1: child is born into a world again of of a 272 00:15:09,640 --> 00:15:13,800 Speaker 1: three D world, uh actually forty three spatial dimensions in 273 00:15:13,840 --> 00:15:17,160 Speaker 1: one of time. It's full of fixed and movable objects 274 00:15:17,280 --> 00:15:20,520 Speaker 1: they have to navigate, and so they have the the 275 00:15:20,640 --> 00:15:23,120 Speaker 1: gear in their head already to deal with this kind 276 00:15:23,120 --> 00:15:26,040 Speaker 1: of world. And so they intrinsically know things such as 277 00:15:26,840 --> 00:15:28,280 Speaker 1: and this was kind of heartbreaking in a way, the 278 00:15:28,320 --> 00:15:32,280 Speaker 1: teleportation is impossible. That they know that an object cannot 279 00:15:32,320 --> 00:15:36,200 Speaker 1: disappear from put point A in appearing point B without 280 00:15:36,320 --> 00:15:40,920 Speaker 1: physically traversing the distance between. Yeah, they know about object permanence. 281 00:15:40,920 --> 00:15:43,200 Speaker 1: They get that, and they get that that one object 282 00:15:43,280 --> 00:15:46,200 Speaker 1: can only occupy that time and space at that at 283 00:15:46,240 --> 00:15:49,480 Speaker 1: that moment. Uh. Spelky says that babies as early as 284 00:15:49,560 --> 00:15:52,600 Speaker 1: two months can begin to understand this. And what they 285 00:15:52,640 --> 00:15:55,200 Speaker 1: did is they took two cups. In one cup they 286 00:15:55,200 --> 00:15:58,880 Speaker 1: put one cracker, and but they did these these hand 287 00:15:58,920 --> 00:16:01,680 Speaker 1: motions like they were innuit to put put a cracker 288 00:16:01,720 --> 00:16:05,200 Speaker 1: in it. And then in another cup they put two crackers. 289 00:16:05,200 --> 00:16:08,080 Speaker 1: But they didn't do multiple hand motions. And what they 290 00:16:08,120 --> 00:16:10,320 Speaker 1: found is that over and over again, the baby kept 291 00:16:10,320 --> 00:16:12,920 Speaker 1: reaching for the one with more crackers in it, even 292 00:16:12,960 --> 00:16:16,800 Speaker 1: though they had sort of done this sleight of hand. Hey, look, 293 00:16:16,880 --> 00:16:19,400 Speaker 1: doesn't it look like I'm putting a ton more crackers 294 00:16:19,440 --> 00:16:23,600 Speaker 1: in here. So she's saying like that that ability is present, 295 00:16:24,600 --> 00:16:27,440 Speaker 1: you know, two months, which is amazing. So you need 296 00:16:27,520 --> 00:16:29,680 Speaker 1: to bring a baby with you to the the con 297 00:16:29,760 --> 00:16:33,080 Speaker 1: man with the cup game, Bring a baby, he'll see 298 00:16:33,160 --> 00:16:35,600 Speaker 1: right there, taken for always work, all right, and then 299 00:16:35,640 --> 00:16:37,440 Speaker 1: after that, like the baby, I don't know it turns 300 00:16:37,480 --> 00:16:39,560 Speaker 1: one or something, forget it now. I don't know what 301 00:16:39,640 --> 00:16:41,720 Speaker 1: time limit that has. Actually, I think that we just 302 00:16:41,720 --> 00:16:44,520 Speaker 1: build on that. And that's sort of her point. And 303 00:16:44,640 --> 00:16:47,120 Speaker 1: she also says that there are born Euclideans and they 304 00:16:47,200 --> 00:16:50,960 Speaker 1: use geometric clues to navigate through rooms. For instance, they're 305 00:16:51,000 --> 00:16:53,360 Speaker 1: more likely to use the lengths of walls in the 306 00:16:53,440 --> 00:16:56,160 Speaker 1: room to remember where a toy is hidden. And even 307 00:16:56,200 --> 00:16:58,920 Speaker 1: when they get older and they're three or four years old, um, 308 00:16:59,160 --> 00:17:02,080 Speaker 1: and they can name like, oh, that's a red wall, 309 00:17:02,600 --> 00:17:07,080 Speaker 1: they still will use that the actual um geometric clues 310 00:17:07,160 --> 00:17:09,560 Speaker 1: the length of the wall, rather than naming the color 311 00:17:09,840 --> 00:17:13,280 Speaker 1: as a way to navigate. All right. Now here's another question. 312 00:17:13,320 --> 00:17:16,760 Speaker 1: I mean we were with babies. Um, we with older children, 313 00:17:16,800 --> 00:17:18,880 Speaker 1: we're you know, we're often it's often easy to sort 314 00:17:18,880 --> 00:17:22,119 Speaker 1: of judge them. Is sort of like non moral, self 315 00:17:22,119 --> 00:17:26,560 Speaker 1: centered monsters. Uh, you know, so it doesn't. Yeah, so 316 00:17:26,640 --> 00:17:28,280 Speaker 1: you look at a baby and you're like, that baby 317 00:17:28,280 --> 00:17:30,800 Speaker 1: doesn't have morals. It doesn't know right from wrong, It 318 00:17:30,840 --> 00:17:34,440 Speaker 1: doesn't know what a you know, a criminal is. But 319 00:17:35,320 --> 00:17:38,680 Speaker 1: the research has actually shown different. Yeah, there's an article 320 00:17:38,760 --> 00:17:42,320 Speaker 1: from I O nine. Uh, it's babies are already superior 321 00:17:42,400 --> 00:17:44,879 Speaker 1: to us, to the rest of us by fifteen months. 322 00:17:44,880 --> 00:17:47,720 Speaker 1: The title of the article and what they were saying 323 00:17:47,840 --> 00:17:50,040 Speaker 1: is that until recently, it was thought that that children 324 00:17:50,080 --> 00:17:54,040 Speaker 1: didn't understand altruism until at least two years of age, 325 00:17:54,280 --> 00:17:56,560 Speaker 1: and that they didn't have a sense of fairness until 326 00:17:56,600 --> 00:17:59,000 Speaker 1: they were six or seven. But it turns out they 327 00:17:59,040 --> 00:18:01,440 Speaker 1: do have a sense of fair and us and altruism. 328 00:18:01,680 --> 00:18:06,720 Speaker 1: University of Wisconsin researcher Jessica Somerville had forty seven fifteen 329 00:18:06,840 --> 00:18:09,320 Speaker 1: month old children sit on their parents laps while they 330 00:18:09,320 --> 00:18:13,040 Speaker 1: were shown to videos. The first video had three characters, 331 00:18:13,160 --> 00:18:15,679 Speaker 1: one of whom had a bowl of crackers. See the 332 00:18:15,680 --> 00:18:20,239 Speaker 1: food thing is really important to these kids. That's right there. 333 00:18:20,760 --> 00:18:24,280 Speaker 1: This um laser focused on the food. The person shared 334 00:18:24,359 --> 00:18:27,400 Speaker 1: the crackers with the other two once in equal portions, 335 00:18:27,640 --> 00:18:31,080 Speaker 1: and then with one person getting more crackers than the 336 00:18:31,119 --> 00:18:33,880 Speaker 1: other people. So they see this the sense of finding 337 00:18:34,160 --> 00:18:37,720 Speaker 1: unfairness unfolding. The second video was exactly the same thing, 338 00:18:37,800 --> 00:18:41,600 Speaker 1: only this time around with milk substituted for crackers. So 339 00:18:41,640 --> 00:18:46,040 Speaker 1: the researchers were on the lookout for something called violation expectancy, 340 00:18:46,240 --> 00:18:49,240 Speaker 1: and this basically means the baby's paying more attention when 341 00:18:49,240 --> 00:18:52,600 Speaker 1: they're surprised, and this is important to Spelky. Elizabeth spell 342 00:18:52,640 --> 00:18:56,439 Speaker 1: Ky really keyed into this gaze um that infants have, 343 00:18:56,680 --> 00:18:59,200 Speaker 1: and it's really important because we talked about the eyes 344 00:18:59,240 --> 00:19:02,840 Speaker 1: in learning, and there are ways that you can actually 345 00:19:02,880 --> 00:19:06,600 Speaker 1: determine what a baby is thinking or reacting to with 346 00:19:06,600 --> 00:19:11,600 Speaker 1: with the their facial gestures. So if anybody's like, well, 347 00:19:11,600 --> 00:19:13,159 Speaker 1: how in the world, and I know this is happening, 348 00:19:13,240 --> 00:19:16,040 Speaker 1: is because they they're basically bidding and videoing these kids 349 00:19:16,119 --> 00:19:19,960 Speaker 1: and um tagging these looks of surprises. So anyway, the 350 00:19:20,000 --> 00:19:22,760 Speaker 1: baby's attention tended to park up really a lot when 351 00:19:22,760 --> 00:19:25,919 Speaker 1: the milk and crackers were unevenly shared. Then when they 352 00:19:25,960 --> 00:19:29,520 Speaker 1: were distributed equally because and that plays into algorithmic thinking. 353 00:19:29,520 --> 00:19:32,240 Speaker 1: They can definitely tell if someone's being slided by a 354 00:19:32,640 --> 00:19:36,080 Speaker 1: significant margin. Yes, because they expected it to be equal. 355 00:19:36,280 --> 00:19:38,760 Speaker 1: That was their expectation. Again, we talked about our brains. 356 00:19:39,880 --> 00:19:42,000 Speaker 1: They know what housing says, they we have have these 357 00:19:42,119 --> 00:19:46,040 Speaker 1: this pattern recognition hard baked into our brains. Um. So 358 00:19:46,119 --> 00:19:48,399 Speaker 1: another experiment was then done with the babies. They were 359 00:19:48,440 --> 00:19:51,800 Speaker 1: offered two toys. One was really fancy, one wasn't. And 360 00:19:52,000 --> 00:19:55,199 Speaker 1: so they then selected the toy that they preferred, and 361 00:19:55,240 --> 00:19:58,439 Speaker 1: then an unseen experiment or came into the room and 362 00:19:58,520 --> 00:20:02,600 Speaker 1: asked to share the boy. Okay, only one third of 363 00:20:02,640 --> 00:20:06,240 Speaker 1: the kids did. But here is the kicker. Of the 364 00:20:06,240 --> 00:20:09,280 Speaker 1: babies who shared their preferred toy also paid more attention 365 00:20:09,320 --> 00:20:13,920 Speaker 1: to the unequal sharing video. Okay. So in other words, 366 00:20:13,920 --> 00:20:16,040 Speaker 1: the vast majority of babies who gave up the toy 367 00:20:16,080 --> 00:20:19,480 Speaker 1: they liked an act of altruism were the ones who 368 00:20:19,600 --> 00:20:23,080 Speaker 1: were surprised by the act of unfairness. This is pointing 369 00:20:23,160 --> 00:20:26,639 Speaker 1: to like clear perception of as you say, have these 370 00:20:26,760 --> 00:20:32,159 Speaker 1: or unfairness injustices or injustices of the world. Wow and uh, 371 00:20:32,240 --> 00:20:35,080 Speaker 1: And I've also seen some experiments that involved like colored blocks, 372 00:20:35,080 --> 00:20:39,439 Speaker 1: where colored blocks are are being villainous to one another, 373 00:20:39,800 --> 00:20:43,480 Speaker 1: or even puppets, which which needately brought to mind Punch 374 00:20:43,520 --> 00:20:46,760 Speaker 1: and Judy. But but I'm trying to think of anybody's 375 00:20:46,800 --> 00:20:49,600 Speaker 1: really moral and Punch and Judy, I mean, because Punch 376 00:20:49,640 --> 00:20:51,879 Speaker 1: is awful and then he runs a foul of the 377 00:20:51,920 --> 00:20:54,720 Speaker 1: police who was kind of awful, and then the devil 378 00:20:54,840 --> 00:20:57,560 Speaker 1: and death I guess death. Yeah, Punch and Judy is 379 00:20:57,600 --> 00:21:01,920 Speaker 1: actually really um it's kind of heavy stuff for a kid. Yeah, 380 00:21:02,160 --> 00:21:06,040 Speaker 1: it's dark stuff. But anyway, I always think about it 381 00:21:06,280 --> 00:21:08,200 Speaker 1: for the Center of Puppet Roots here in Atlanta, because 382 00:21:08,240 --> 00:21:10,240 Speaker 1: they have a museum and they've got the Punch and 383 00:21:10,320 --> 00:21:12,520 Speaker 1: Judy and they always the scare the heck out of 384 00:21:12,520 --> 00:21:15,119 Speaker 1: me for some reason. We my my wife and I 385 00:21:15,160 --> 00:21:16,920 Speaker 1: went there once when they had just for I think 386 00:21:16,960 --> 00:21:19,640 Speaker 1: two nights they had a Punch and Judy Modern Punch 387 00:21:19,640 --> 00:21:22,800 Speaker 1: and Judy at come in that market themselves as the 388 00:21:22,800 --> 00:21:24,720 Speaker 1: world's best Punch and Judy show. If you do a 389 00:21:24,720 --> 00:21:27,840 Speaker 1: search for that online you'll find them. And uh and 390 00:21:27,960 --> 00:21:30,520 Speaker 1: they there. These are like a young couple. I don't 391 00:21:30,520 --> 00:21:32,040 Speaker 1: know they're a couple, but a young man and a 392 00:21:32,160 --> 00:21:36,080 Speaker 1: woman who like, learned Punch and Judy, which has a 393 00:21:36,080 --> 00:21:37,960 Speaker 1: different name in French, but I can't remember. Like each 394 00:21:37,960 --> 00:21:40,080 Speaker 1: country at European country has Punch and Judy, but they 395 00:21:40,160 --> 00:21:42,840 Speaker 1: have different names. But they learned that their puppetry craft 396 00:21:42,840 --> 00:21:45,880 Speaker 1: on the streets of Paris, like sleeping on the streets 397 00:21:46,000 --> 00:21:48,800 Speaker 1: in there in the puppet theater turned on its side, 398 00:21:49,359 --> 00:21:52,399 Speaker 1: and so they were just masters of the old school 399 00:21:52,440 --> 00:21:54,159 Speaker 1: Punch and Judy show. And they put it on and 400 00:21:54,200 --> 00:21:57,399 Speaker 1: it was phenomenal. It was just hilarious and and they 401 00:21:57,520 --> 00:22:02,040 Speaker 1: and just expertly done. So so Punch and Judy. It's 402 00:22:02,040 --> 00:22:03,880 Speaker 1: easy to look at and think, oh, well that's that's 403 00:22:03,880 --> 00:22:06,360 Speaker 1: a low puppetry, that's that's nothing, but it's it's quite 404 00:22:06,400 --> 00:22:10,560 Speaker 1: an art form. It's babies might appreciate. I think that 405 00:22:10,640 --> 00:22:14,000 Speaker 1: they would for sure. Uh So, speaking of Punch and 406 00:22:14,080 --> 00:22:17,119 Speaker 1: Judy in Paris and babies, when we get back, we 407 00:22:17,160 --> 00:22:19,560 Speaker 1: will actually find out what babies have to do with 408 00:22:19,600 --> 00:22:29,520 Speaker 1: Paris and even cappuccinos. All right, we're back. Babies need cappuccinos. 409 00:22:29,600 --> 00:22:32,200 Speaker 1: Is that where we're going with this? Yes, fuel them 410 00:22:32,200 --> 00:22:34,720 Speaker 1: with lots and we forget them milk. Just fill it 411 00:22:34,800 --> 00:22:38,720 Speaker 1: up with cappuccino. Um, Okay, no, we're we're gonna get 412 00:22:38,720 --> 00:22:41,040 Speaker 1: to this idea of babies and cappuccino in Paris in 413 00:22:41,080 --> 00:22:43,679 Speaker 1: a moment, but Alice and Gopnick again and wanted to 414 00:22:43,720 --> 00:22:46,720 Speaker 1: bring her up. Um. She has a talk called what 415 00:22:46,760 --> 00:22:50,719 Speaker 1: do Babies Think? Which is very interesting and she talks 416 00:22:50,760 --> 00:22:56,639 Speaker 1: about how babies have a different consciousness than us. And 417 00:22:56,680 --> 00:22:59,000 Speaker 1: I think it's a really interesting idea because she says, 418 00:22:59,119 --> 00:23:02,080 Speaker 1: if you look at an adult, an adult is basically 419 00:23:02,160 --> 00:23:05,560 Speaker 1: using sort of like a flashlight to laser focus on something. Right, 420 00:23:05,600 --> 00:23:07,399 Speaker 1: there's something we want to look at and think about, 421 00:23:07,480 --> 00:23:09,760 Speaker 1: we point the light on it. We block everything else up. 422 00:23:09,960 --> 00:23:13,680 Speaker 1: I'm thinking about my work, I'm thinking about my life, 423 00:23:13,720 --> 00:23:16,840 Speaker 1: I'm thinking about what that guy in the subway is doing. 424 00:23:16,880 --> 00:23:19,720 Speaker 1: It's it's just one thing after after another. We have 425 00:23:19,760 --> 00:23:21,720 Speaker 1: to focus on something and everything else sort of fades, 426 00:23:22,200 --> 00:23:25,280 Speaker 1: uh into the peripheral vision. Babies use more of this 427 00:23:25,400 --> 00:23:29,640 Speaker 1: sort of lantern to to fill their consciousness up with. 428 00:23:29,920 --> 00:23:32,080 Speaker 1: So I'm not focusing on any one particular thing. The 429 00:23:32,200 --> 00:23:35,280 Speaker 1: light is illuminating the room. Yes, And so she's saying 430 00:23:35,280 --> 00:23:39,320 Speaker 1: it's not that they don't pay attention. Well, they can't 431 00:23:39,400 --> 00:23:42,879 Speaker 1: not pay attention is the problem, and they're saying that 432 00:23:42,960 --> 00:23:45,960 Speaker 1: it's driven how it's driven by how information rich their 433 00:23:46,040 --> 00:23:48,679 Speaker 1: world is around them, and that when you look at 434 00:23:48,680 --> 00:23:51,480 Speaker 1: their brains, instead of just squirting a little bit of 435 00:23:51,520 --> 00:23:54,199 Speaker 1: trans neuro transmitter on the part of the brain that 436 00:23:54,280 --> 00:23:58,560 Speaker 1: they want to learn, their whole brain is soaked in neurotransmitters. 437 00:23:59,520 --> 00:24:02,320 Speaker 1: So they're like they're they're sponges. They're just they're like 438 00:24:02,400 --> 00:24:05,720 Speaker 1: hyper conscious of the world around them, blocking nothing out. Yeah, 439 00:24:05,760 --> 00:24:07,359 Speaker 1: you have to think about it this way because this 440 00:24:07,440 --> 00:24:10,879 Speaker 1: is really when the brain is like crazy active, and 441 00:24:10,920 --> 00:24:13,720 Speaker 1: as you get older, of course those neural connections begin 442 00:24:13,800 --> 00:24:15,960 Speaker 1: to get pruned away the stuff that you use, stuff 443 00:24:15,960 --> 00:24:18,440 Speaker 1: you don't use, and you get a more selective brain. 444 00:24:18,520 --> 00:24:21,439 Speaker 1: But for the time being, um, you do have this 445 00:24:21,640 --> 00:24:24,960 Speaker 1: no transmitter soaked brain. And this is why that they 446 00:24:24,960 --> 00:24:27,960 Speaker 1: have that sort of lantern vision of everything. They can't 447 00:24:28,320 --> 00:24:32,240 Speaker 1: really get anything out of their heads because they're considering everything. Um. 448 00:24:32,320 --> 00:24:34,240 Speaker 1: So she says, what's it like to be a baby? 449 00:24:34,320 --> 00:24:36,760 Speaker 1: It's like being in love in Paris for the first 450 00:24:36,800 --> 00:24:42,000 Speaker 1: time after you've had three double espressos doses. But I 451 00:24:42,000 --> 00:24:44,479 Speaker 1: mean this also plays right into I mean just one 452 00:24:44,560 --> 00:24:47,800 Speaker 1: of one of many reasons for why stimulation and uh, 453 00:24:48,200 --> 00:24:51,640 Speaker 1: and both on a like a physical level but also 454 00:24:51,640 --> 00:24:54,840 Speaker 1: an emotional level is important. Uh, young child because they're 455 00:24:54,920 --> 00:24:57,240 Speaker 1: they're sponges. They need to absorb, they need a world 456 00:24:57,240 --> 00:24:59,760 Speaker 1: to absorb. They need to see the sky, they need 457 00:25:00,119 --> 00:25:05,040 Speaker 1: interact with people. Um. And that's I mean, that's I'm one. 458 00:25:05,160 --> 00:25:07,720 Speaker 1: That's kind of funny. But there are children out there, um, 459 00:25:07,760 --> 00:25:10,000 Speaker 1: you know, particularly in an orphanage situations, who do not 460 00:25:10,080 --> 00:25:13,399 Speaker 1: get to see the sky. They stuff for sensory deprivation 461 00:25:14,240 --> 00:25:17,080 Speaker 1: and and it has a profound effect on them. And 462 00:25:17,160 --> 00:25:20,080 Speaker 1: conversely too, if if there is too much stimulation, that's 463 00:25:20,080 --> 00:25:22,440 Speaker 1: obviously when the brain gets overload. And we talked about 464 00:25:22,440 --> 00:25:25,280 Speaker 1: that too just in the scream episode have it. You know, 465 00:25:25,320 --> 00:25:27,440 Speaker 1: sometimes we have to scream because we all are over 466 00:25:27,480 --> 00:25:30,000 Speaker 1: stimulated at some point. Yeah, Like you show a baby 467 00:25:30,080 --> 00:25:33,840 Speaker 1: Baraka and Mike cries too much. They can much for 468 00:25:33,880 --> 00:25:37,200 Speaker 1: an adult to take him. I didn't cry, you didn't cry. No, 469 00:25:37,440 --> 00:25:41,080 Speaker 1: I might not be human. Everyone I know Christ the 470 00:25:41,119 --> 00:25:43,639 Speaker 1: scene with the homeless people and they're playing like that 471 00:25:43,760 --> 00:25:47,399 Speaker 1: can dance in the background. Sorry, the baby chicks getting 472 00:25:47,600 --> 00:25:53,959 Speaker 1: sexed and their beaks burned a tough nut. Um okay. 473 00:25:54,160 --> 00:26:00,000 Speaker 1: So god Nick says that that this different consciousness she thinks, 474 00:26:00,200 --> 00:26:03,119 Speaker 1: in some ways more conscious than adults are, and she 475 00:26:03,160 --> 00:26:05,520 Speaker 1: says that she just has empirical evidence at this point, 476 00:26:05,880 --> 00:26:09,920 Speaker 1: but she thinks that this, this is a real possibility 477 00:26:09,960 --> 00:26:12,480 Speaker 1: that kids are actually more conscious than we are. But 478 00:26:12,480 --> 00:26:14,359 Speaker 1: then we'll never be able to really answer that until 479 00:26:14,359 --> 00:26:17,680 Speaker 1: we actually can define consciousness and how it works, which 480 00:26:17,720 --> 00:26:24,520 Speaker 1: is always the big first step one define human consciousness. Right, yeah, 481 00:26:24,600 --> 00:26:27,359 Speaker 1: So there's this idea that creative people retain some of 482 00:26:27,400 --> 00:26:30,520 Speaker 1: the same kind of different consciousness, as she calls it, 483 00:26:30,960 --> 00:26:34,399 Speaker 1: and are able to tap into all these uh different 484 00:26:34,440 --> 00:26:39,480 Speaker 1: stimuli and think differently they which which plays him nicely 485 00:26:39,520 --> 00:26:42,000 Speaker 1: to be like, I always loved the CS Lewis quote 486 00:26:42,040 --> 00:26:44,080 Speaker 1: quote about when I was you know, about when I 487 00:26:44,119 --> 00:26:46,840 Speaker 1: was young, I just wanted to appear a very grown 488 00:26:46,920 --> 00:26:50,119 Speaker 1: up and all and and uh and and and now 489 00:26:50,200 --> 00:26:53,440 Speaker 1: as an adult, he celebrates the you know, the imagination 490 00:26:53,440 --> 00:26:56,160 Speaker 1: of childhood and wants to keep it alive in him 491 00:26:56,240 --> 00:26:59,840 Speaker 1: as as long as possible. You know. Yeah, well Picasso, right, 492 00:27:00,240 --> 00:27:02,800 Speaker 1: the same thing you think of like thoroughly grown up people, 493 00:27:02,880 --> 00:27:05,400 Speaker 1: and they are the most boring individuals on the planet. 494 00:27:05,720 --> 00:27:09,680 Speaker 1: I mean just push them over, you know, they just 495 00:27:09,680 --> 00:27:11,720 Speaker 1: just push him over. I don't push him over, but 496 00:27:11,760 --> 00:27:13,840 Speaker 1: you just want to. You're just like, oh, look, you've 497 00:27:13,880 --> 00:27:16,800 Speaker 1: just completely It's like an orange that's just been squeezed 498 00:27:16,800 --> 00:27:20,000 Speaker 1: out of all juice. You know, they're just a husk 499 00:27:20,280 --> 00:27:22,239 Speaker 1: and they're just like, that's just I don't even want 500 00:27:22,280 --> 00:27:24,560 Speaker 1: to know that person. So if you're feeling bored, you 501 00:27:24,600 --> 00:27:26,880 Speaker 1: have to go into your baby brain and you will 502 00:27:26,880 --> 00:27:30,359 Speaker 1: find liberation. Yeah. I feel like anybody worth throwing baby 503 00:27:30,359 --> 00:27:33,560 Speaker 1: brain still going on at least a little little nugget 504 00:27:33,600 --> 00:27:35,480 Speaker 1: of it in some area of their life. Baby brain 505 00:27:35,600 --> 00:27:38,639 Speaker 1: is good. Gothnik has a great take on this and 506 00:27:38,960 --> 00:27:42,800 Speaker 1: creativity and and the world does an illusion. She says, 507 00:27:42,880 --> 00:27:47,520 Speaker 1: if you think about that from the perspective of human evolution, 508 00:27:47,680 --> 00:27:50,120 Speaker 1: this idea of the of the baby brain, our great 509 00:27:50,160 --> 00:27:52,879 Speaker 1: capacity is not just that we learn about the world. 510 00:27:52,880 --> 00:27:55,320 Speaker 1: The thing that really makes us distinctive is that we 511 00:27:55,359 --> 00:27:58,680 Speaker 1: can imagine other ways that the world could be. That's 512 00:27:58,680 --> 00:28:02,320 Speaker 1: really where are enormous evolutionary juice comes from. We understand 513 00:28:02,320 --> 00:28:05,160 Speaker 1: the world, but that also lets us imagine other ways 514 00:28:05,200 --> 00:28:08,119 Speaker 1: it could be, and actually make those other worlds come true. 515 00:28:08,720 --> 00:28:12,800 Speaker 1: That's what's innovation technology, or that's what innovation technology and 516 00:28:12,800 --> 00:28:15,159 Speaker 1: science are all about. Think about everything that's in this 517 00:28:15,280 --> 00:28:18,320 Speaker 1: room right now. There's a right angle desk and electric 518 00:28:18,400 --> 00:28:20,840 Speaker 1: light in computers and window panes. Every single thing in 519 00:28:20,880 --> 00:28:24,000 Speaker 1: this room is imaginary. From the perspective of hunter gatherer, 520 00:28:24,359 --> 00:28:26,960 Speaker 1: we live in imaginary worlds. Yeah, I mean, we have 521 00:28:27,080 --> 00:28:31,920 Speaker 1: this profound ability to simulate possible futures and act accordingly. Yeah, 522 00:28:31,920 --> 00:28:33,560 Speaker 1: So it makes sense that the baby brain would need 523 00:28:33,600 --> 00:28:35,199 Speaker 1: to do this, that we would from the get go 524 00:28:36,080 --> 00:28:39,280 Speaker 1: start to try to do pattern recognition and and name 525 00:28:39,360 --> 00:28:44,320 Speaker 1: things and dream up things, uh, and be innovators. Um. 526 00:28:44,320 --> 00:28:47,200 Speaker 1: Which I think all of this to me is going 527 00:28:47,240 --> 00:28:51,720 Speaker 1: back to again language language, language acquisition, and this importance 528 00:28:52,000 --> 00:28:55,600 Speaker 1: of being able to look in another person's eyes and 529 00:28:55,720 --> 00:29:00,280 Speaker 1: learn from them. Specifically language acquisition. It putres a cool 530 00:29:00,560 --> 00:29:03,200 Speaker 1: cool has done a bunch of studies about this, that 531 00:29:03,480 --> 00:29:06,640 Speaker 1: kids who are taught other languages do not acquire through 532 00:29:06,760 --> 00:29:10,320 Speaker 1: CDs or television or other forms of media. One to 533 00:29:10,440 --> 00:29:13,120 Speaker 1: one is really important, which then sort of puts a 534 00:29:13,160 --> 00:29:19,040 Speaker 1: spotlight on the relationship between a caregiver and a child. Um. 535 00:29:19,160 --> 00:29:21,760 Speaker 1: This interaction between them. So you're looking at a baby's 536 00:29:21,760 --> 00:29:26,920 Speaker 1: face and the baby's looking in your face, and there's 537 00:29:26,960 --> 00:29:31,280 Speaker 1: facial recognition going on there. Obviously, a baby can identify 538 00:29:31,400 --> 00:29:35,800 Speaker 1: its mother by looking in the mother's face, which sounds 539 00:29:35,880 --> 00:29:38,760 Speaker 1: kind of like an overstatement of the obvious. But but 540 00:29:39,880 --> 00:29:42,880 Speaker 1: when you get into into neurologically looking at how how 541 00:29:42,920 --> 00:29:45,200 Speaker 1: it all works, it's it's pretty pretty phenomenal. And it's 542 00:29:45,200 --> 00:29:47,560 Speaker 1: the kind of thing that we're again trying to replicate 543 00:29:47,600 --> 00:29:50,840 Speaker 1: and are replicating to a large extents in computers. But 544 00:29:50,920 --> 00:29:53,840 Speaker 1: the baby has it programmed in from the start. So, yeah, 545 00:29:53,840 --> 00:29:56,000 Speaker 1: what's probably one of the most important things to you 546 00:29:56,040 --> 00:29:59,560 Speaker 1: as a child your caregiver staring at you and giving 547 00:29:59,600 --> 00:30:02,560 Speaker 1: you visu cues about language, about the world around you. 548 00:30:03,040 --> 00:30:06,760 Speaker 1: And yet when you're a really young infant, you're completely 549 00:30:06,800 --> 00:30:10,000 Speaker 1: hamstrung by your vision at that point, right, And this 550 00:30:10,000 --> 00:30:13,280 Speaker 1: this leads right into which a really mind blowing idea. 551 00:30:13,480 --> 00:30:17,440 Speaker 1: It's not this is not a settled theory by any stretch, 552 00:30:17,520 --> 00:30:20,480 Speaker 1: but it's a fascinating area to think about. Ran across 553 00:30:20,560 --> 00:30:24,960 Speaker 1: this article um Skeptic Magazine, which, if you're not familiar, 554 00:30:25,080 --> 00:30:28,720 Speaker 1: Skeptic Magazine is the publication. It's put together by a 555 00:30:29,240 --> 00:30:33,640 Speaker 1: Michael A. Schermer who we mentioned in the UFO abduction episode. 556 00:30:33,680 --> 00:30:37,760 Speaker 1: He's the cyclist who had an abduction experience due to 557 00:30:37,800 --> 00:30:42,200 Speaker 1: exhaustion and uh and uh and and then he went 558 00:30:42,200 --> 00:30:44,440 Speaker 1: on to study it and explained it in scientific terms. 559 00:30:44,600 --> 00:30:46,320 Speaker 1: And he's really really big into taking things that are 560 00:30:46,320 --> 00:30:49,720 Speaker 1: seemingly paranormal and then and then let's examine it from 561 00:30:49,720 --> 00:30:54,160 Speaker 1: a scientific point of view and figure out what's actually happening. Uh, 562 00:30:54,240 --> 00:30:56,360 Speaker 1: you know, not alien. So he's not like a conspiracy 563 00:30:56,400 --> 00:30:58,520 Speaker 1: not or anything. He's he's a dude that's grounded in 564 00:30:58,600 --> 00:31:01,200 Speaker 1: science and turning the gay of science on things that 565 00:31:01,240 --> 00:31:05,360 Speaker 1: are phenomenal. So, unsurprisingly, there was an article on Scriptic 566 00:31:05,400 --> 00:31:08,960 Speaker 1: Magazine by an author by the name of Frederick V. Momstrom, 567 00:31:09,600 --> 00:31:13,120 Speaker 1: and he wrote an arcohol close encounters of the facial 568 00:31:13,200 --> 00:31:17,880 Speaker 1: kind are UFO alien faces an inborn facial recognition template. 569 00:31:18,520 --> 00:31:23,360 Speaker 1: His argument here, all right, So, okay, so aliens, gray 570 00:31:23,520 --> 00:31:29,600 Speaker 1: aliens UM like UFO like unsolved mysteries, um close encounters 571 00:31:29,600 --> 00:31:31,320 Speaker 1: of the third kind kind of alien? You know what 572 00:31:31,360 --> 00:31:35,360 Speaker 1: I'm talking about? This Uh, this big gray head with 573 00:31:35,520 --> 00:31:38,680 Speaker 1: large black eyes and a a little mouth and a little nose. 574 00:31:39,240 --> 00:31:44,320 Speaker 1: And in these abduction uh experiences, the individuals perceiving these 575 00:31:44,320 --> 00:31:47,400 Speaker 1: things like looming over them. Uh. And there's generally like 576 00:31:47,440 --> 00:31:51,640 Speaker 1: there's something surgical or or you know, or or probe 577 00:31:51,640 --> 00:31:54,960 Speaker 1: related going on in these scenarios, you know, and there's 578 00:31:55,040 --> 00:31:57,840 Speaker 1: a sense of you know, there's some sleep paralysis or something, 579 00:31:57,880 --> 00:31:59,960 Speaker 1: and there's a sense of of of being of loose 580 00:32:00,040 --> 00:32:03,360 Speaker 1: in control and uh. Uh you know, listen to our 581 00:32:03,360 --> 00:32:06,040 Speaker 1: episode on the UFO deduction experiences for for a little 582 00:32:06,080 --> 00:32:08,440 Speaker 1: more about the science of what is actually going on 583 00:32:08,520 --> 00:32:12,600 Speaker 1: in these encounters. But the author here is focusing in 584 00:32:12,640 --> 00:32:15,440 Speaker 1: particularly on that face, like why why would we see 585 00:32:15,480 --> 00:32:18,520 Speaker 1: this gray alien face? And why do so many people 586 00:32:18,520 --> 00:32:21,520 Speaker 1: see it? Well, there are the same type of face. Now, 587 00:32:22,120 --> 00:32:25,600 Speaker 1: one really good explanation for that is that we saw 588 00:32:25,640 --> 00:32:29,120 Speaker 1: it on Unsolved Mysteries. We saw it faces, and we've 589 00:32:29,120 --> 00:32:31,880 Speaker 1: been primed to see that. That is, we've we've encountered 590 00:32:31,880 --> 00:32:35,080 Speaker 1: this story before in our fiction and uh, and so 591 00:32:35,160 --> 00:32:39,040 Speaker 1: it's ready to go when we actually encounter a paranormal 592 00:32:39,440 --> 00:32:44,440 Speaker 1: experience on a neurological level. But uh, Malmstrom's theory is 593 00:32:44,440 --> 00:32:48,840 Speaker 1: that what we're actually too tapping into here is the 594 00:32:48,960 --> 00:32:53,680 Speaker 1: infant facial recognition software that that that we have not 595 00:32:53,800 --> 00:32:56,200 Speaker 1: used in a long time but is still present. Uh. 596 00:32:56,240 --> 00:33:00,480 Speaker 1: The ideas that the baby's vision, uh, baby's vision, an 597 00:33:00,480 --> 00:33:04,680 Speaker 1: infants vision is is imperfect. You know, it's like they're 598 00:33:04,880 --> 00:33:08,240 Speaker 1: they're far they're near sighted. Everything's blurry and bright. So 599 00:33:08,320 --> 00:33:12,400 Speaker 1: what does mother's face look like to an infant with 600 00:33:12,480 --> 00:33:17,040 Speaker 1: that kind of vision? Bulbous head, right, and two long 601 00:33:17,080 --> 00:33:22,959 Speaker 1: slits fries and a little tiny nose holes and a 602 00:33:22,960 --> 00:33:25,560 Speaker 1: bit of a slash of a mouth. And this is 603 00:33:25,600 --> 00:33:31,320 Speaker 1: actually something that um that was borne out right by 604 00:33:31,320 --> 00:33:34,520 Speaker 1: this attempt to try to mimic, as you call it, 605 00:33:34,640 --> 00:33:38,160 Speaker 1: baby vision at this point, like what would this graphically 606 00:33:38,200 --> 00:33:41,440 Speaker 1: look like to us? Yeah, and he explored it by 607 00:33:41,480 --> 00:33:46,720 Speaker 1: taking taking this up, this prototypical female face, blurring it out, 608 00:33:46,760 --> 00:33:48,840 Speaker 1: blurring the images out and uh and just applying these 609 00:33:48,880 --> 00:33:53,760 Speaker 1: different layers that attempt to replicate infant site and you 610 00:33:53,840 --> 00:33:56,920 Speaker 1: get something that looks a lot like you know, Encounters 611 00:33:56,920 --> 00:34:00,760 Speaker 1: of the Third kind Unsolved Mysteries, gray alien. That's that's 612 00:34:00,800 --> 00:34:04,880 Speaker 1: stereotypical alien head. Yeah, and yeah, you guys should definitely 613 00:34:04,920 --> 00:34:07,280 Speaker 1: check it out. Just take a look at this, and 614 00:34:07,320 --> 00:34:10,040 Speaker 1: it begins to really make sense. And then of course 615 00:34:10,120 --> 00:34:12,680 Speaker 1: you you look at this information and you begin to wonder, 616 00:34:12,760 --> 00:34:14,560 Speaker 1: and this is a little bit wacky, but you begin 617 00:34:14,640 --> 00:34:20,160 Speaker 1: to wonder our alien abductions or sightings. Um. It's particularly 618 00:34:20,160 --> 00:34:23,600 Speaker 1: in the context of false awakenings that we've talked about before, 619 00:34:23,600 --> 00:34:28,040 Speaker 1: where your brain is coming back online too consciousness, but 620 00:34:28,160 --> 00:34:34,359 Speaker 1: your body is still in sleep paralysis. Is could this 621 00:34:34,920 --> 00:34:38,480 Speaker 1: idea that you see something that is other just a 622 00:34:38,600 --> 00:34:42,320 Speaker 1: ghost memory of your mother's face when in your earliest 623 00:34:42,400 --> 00:34:47,120 Speaker 1: memories as a baby. Because we have access presumably to 624 00:34:47,880 --> 00:34:52,240 Speaker 1: all of our memories, just not all the time, so 625 00:34:52,480 --> 00:34:56,719 Speaker 1: potentially in this kind of sleep situation, you might be 626 00:34:56,760 --> 00:35:00,080 Speaker 1: able to retrieve that. I know it's wacky, but it 627 00:35:00,160 --> 00:35:04,560 Speaker 1: is very interesting. Yeah, I found it, found it really fascinating. Again, 628 00:35:04,600 --> 00:35:09,120 Speaker 1: it's taking some you know, a paranormal experience and uh 629 00:35:09,160 --> 00:35:12,200 Speaker 1: and then trying to to understand it through science. And 630 00:35:12,239 --> 00:35:14,480 Speaker 1: it's just like I said, who knows if this holds up, 631 00:35:14,480 --> 00:35:16,279 Speaker 1: but it's a really interesting way of looking at it well, 632 00:35:16,280 --> 00:35:18,640 Speaker 1: and it underlines again what's some of the things amazing 633 00:35:18,680 --> 00:35:21,920 Speaker 1: that are amazing about how the infant mind works. Yeah, 634 00:35:21,960 --> 00:35:24,359 Speaker 1: and I think this idea too, of can can we 635 00:35:24,400 --> 00:35:27,879 Speaker 1: revisit our infant minds at some time. Is it through 636 00:35:28,080 --> 00:35:32,600 Speaker 1: just these specialized periods of disrupted sleep um or are 637 00:35:32,640 --> 00:35:36,200 Speaker 1: we way past those those memories? And to what extent 638 00:35:36,400 --> 00:35:38,959 Speaker 1: can we actually tap into it and make it work 639 00:35:39,040 --> 00:35:41,080 Speaker 1: for us so to speak? Because I mean, if you 640 00:35:41,120 --> 00:35:44,040 Speaker 1: think about it, we are statistical machines. We just have 641 00:35:44,320 --> 00:35:47,080 Speaker 1: these overlays of our experiences which sort of shut out 642 00:35:47,160 --> 00:35:49,799 Speaker 1: some possibilities for us in terms of what we can 643 00:35:49,880 --> 00:35:52,960 Speaker 1: dream for ourselves or understand. So if we could take 644 00:35:52,960 --> 00:35:56,440 Speaker 1: it back to our roots system and still be access 645 00:35:56,440 --> 00:35:59,120 Speaker 1: for are fully formed adult brains, that would be great. 646 00:35:59,640 --> 00:36:03,000 Speaker 1: More in forrrantly that the next time you're you're leaning 647 00:36:03,040 --> 00:36:07,680 Speaker 1: over the baby's cradle in your life, uh, and imagine 648 00:36:07,680 --> 00:36:10,440 Speaker 1: that that that the infant sees you as a as 649 00:36:10,480 --> 00:36:13,440 Speaker 1: a gray alien. And the next time you find yourself 650 00:36:13,719 --> 00:36:16,399 Speaker 1: curiously unable to move in your bed and you look 651 00:36:16,480 --> 00:36:19,279 Speaker 1: up and you see this, uh, this strange gray head 652 00:36:19,320 --> 00:36:22,919 Speaker 1: with big black eyes. Embrace it well, and that makes 653 00:36:22,920 --> 00:36:25,320 Speaker 1: you realize why some people are terrified if if that 654 00:36:25,360 --> 00:36:27,319 Speaker 1: were the case, that there was just a ghost memory 655 00:36:27,360 --> 00:36:30,080 Speaker 1: of their mother, because it's your mom, but it's not right, 656 00:36:31,120 --> 00:36:33,560 Speaker 1: So it's the other of course you're going to be like, 657 00:36:33,600 --> 00:36:37,080 Speaker 1: whoa alien? Yeah, Um, I wanted to mention real quick 658 00:36:37,440 --> 00:36:43,280 Speaker 1: that Elizabeth Falky fascinating uh cognitive psychologists. She if anybody 659 00:36:43,320 --> 00:36:45,720 Speaker 1: is interested. She actually took a lot of her data 660 00:36:46,400 --> 00:36:50,279 Speaker 1: and she pitted it against Lawrence Lawrence H. Summers, that 661 00:36:50,400 --> 00:36:53,120 Speaker 1: then president of Harvard who in two thousand and five 662 00:36:53,120 --> 00:36:57,239 Speaker 1: suggested that the shortage of women and um physical sciences 663 00:36:57,440 --> 00:37:01,000 Speaker 1: could be due to innate shortcome things and math. She 664 00:37:01,120 --> 00:37:05,720 Speaker 1: took all her statistical data from forty years and combed 665 00:37:05,760 --> 00:37:10,080 Speaker 1: through it to to actually make the point that it um, 666 00:37:10,239 --> 00:37:12,040 Speaker 1: that was not the case at all. There was no 667 00:37:12,480 --> 00:37:17,279 Speaker 1: different differentiation at all in terms of gender when it 668 00:37:17,360 --> 00:37:22,000 Speaker 1: came to babies, children, and science, and and this uh 669 00:37:22,200 --> 00:37:26,319 Speaker 1: innate or not innate ability to grasp math in a 670 00:37:26,360 --> 00:37:30,680 Speaker 1: meaningful way. So if anybody is interested in this. She 671 00:37:30,760 --> 00:37:34,080 Speaker 1: has a debate with her friend, actually, Stephen Pinker. We've 672 00:37:34,080 --> 00:37:36,520 Speaker 1: talked about him before. He is a neuroscientist, and that 673 00:37:36,640 --> 00:37:38,760 Speaker 1: we know him more in the context of him calling 674 00:37:39,120 --> 00:37:44,279 Speaker 1: musical abilities cheesecake, right, auditory cheesecake like it's just sort 675 00:37:44,280 --> 00:37:48,120 Speaker 1: of happened by accident. Um. But anyway, they have a 676 00:37:48,239 --> 00:37:51,960 Speaker 1: very very interesting debate on this topic. And uh, Spelky 677 00:37:52,040 --> 00:37:57,160 Speaker 1: is amazing. She has very um interesting takes on this topic. 678 00:37:57,760 --> 00:37:59,440 Speaker 1: And uh, and what are what are the books that 679 00:37:59,520 --> 00:38:03,120 Speaker 1: individuals can check out? Individuals listeners can check out if 680 00:38:03,160 --> 00:38:05,680 Speaker 1: they want to want to hear more. Gottenick as a book, 681 00:38:05,760 --> 00:38:08,920 Speaker 1: right she does. I believe I'm going to probably get 682 00:38:08,920 --> 00:38:11,680 Speaker 1: this wrong, but I think it's called The Psychology of Babies. 683 00:38:12,320 --> 00:38:14,799 Speaker 1: But you can just search for Alison Gothnik check her 684 00:38:14,840 --> 00:38:17,560 Speaker 1: out on TED. Also Elizabeth S. Bucky. Um, there are 685 00:38:17,600 --> 00:38:23,040 Speaker 1: two great resources if you want to learn more. All right, Well, um, 686 00:38:23,120 --> 00:38:25,640 Speaker 1: we're gonna skip the robe at today because he's got 687 00:38:25,640 --> 00:38:27,440 Speaker 1: a busted wheel. It's it's rough. He's all the way 688 00:38:27,480 --> 00:38:28,680 Speaker 1: through the side of the room and I'm not gonna 689 00:38:28,680 --> 00:38:31,200 Speaker 1: get up and walk over there to get mail. But 690 00:38:31,200 --> 00:38:34,560 Speaker 1: by all means, send us more mail you can. You 691 00:38:34,600 --> 00:38:37,760 Speaker 1: can reach out to us on Facebook. We were stuff 692 00:38:37,840 --> 00:38:39,120 Speaker 1: to blow your mind there. You can find us on 693 00:38:39,160 --> 00:38:42,680 Speaker 1: Twitter where we are blow the mind. We'd love to hear. Uh, 694 00:38:42,920 --> 00:38:45,720 Speaker 1: what are your observations with babies? I know the number 695 00:38:45,719 --> 00:38:48,120 Speaker 1: of you out there, our parents or you've at least 696 00:38:48,680 --> 00:38:50,680 Speaker 1: you know baby said, or you've you've had to or 697 00:38:50,719 --> 00:38:53,920 Speaker 1: you had an infant sibling or something. What are your 698 00:38:53,960 --> 00:38:56,200 Speaker 1: what were your interactions like, tell us what you think 699 00:38:56,239 --> 00:38:59,120 Speaker 1: about the infant mind and and have you glimpsed some 700 00:38:59,200 --> 00:39:02,400 Speaker 1: of what we're talking about in that child? And you 701 00:39:02,440 --> 00:39:04,800 Speaker 1: can always drop us a line at blew the Mind 702 00:39:05,040 --> 00:39:14,320 Speaker 1: at discovery dot com. For more on this and thousands 703 00:39:14,360 --> 00:39:21,320 Speaker 1: of other topics, visit how Stuff Works dot com