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Speaker 1: Welcome to Stuff to Blow Your Mind from how Stuff

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Speaker 1: Works dot com. Hey, welcome to Stuff to Blow your Mind.

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Speaker 1: My name is Christian Sager, and I'm Joe McCormick. And

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Speaker 1: our regular host Robert Lamb is not with us today.

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Speaker 1: Where is he? He is on the beach somewhere, a beach.

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Speaker 1: I don't know which beach, but he just referred to

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Speaker 1: it Stephen King's Beach World. I think it might be

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Speaker 1: the beach from that Leonardo DiCaprio movie where he punches

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Speaker 1: the shark in the face. Did you ever read that book?

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Speaker 1: I didn't read the book, but I like, um, what's

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Speaker 1: the guy who wrote that? Alex Garland? Yeah, Alex twenty

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Speaker 1: eight days later, I think he did. Yeah, and he

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Speaker 1: also just worked on X makin A that movie that

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Speaker 1: came out it's a good one, and directed it. Yeah. Okay,

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Speaker 1: so we're already off on a tangent. But what are

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Speaker 1: we gonna be talking about today? Well, this is going

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Speaker 1: to be the first part of a two part episode

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Speaker 1: on animal cognition. Animal intelligen exactly how smart are all

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Speaker 1: the beasts that occupied this planet? Yeah? So, uh, Joe

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Speaker 1: and I both have dogs, and sometimes our dogs get

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Speaker 1: together and play. We have plain aids. Joe's dog is

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Speaker 1: named Charlie, and my dogs are Winchester and see Blue,

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Speaker 1: and we like our dogs a lot. I think it's

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Speaker 1: fair to say we love our dogs. I hate my dog.

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Speaker 1: I know I love my dog, and my dog loves

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Speaker 1: your dog. So if you this is a thing you

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Speaker 1: should know out there. If Christian loans me a book

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Speaker 1: and I bring the book into my house and I'm

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Speaker 1: sitting on the couch reading it, my dog Charlie will

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Speaker 1: come sit next to me. Then he will get a

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Speaker 1: crazy look in his eye and begin to sniff the

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Speaker 1: book vigorously and sniff all over it. And what we

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Speaker 1: figured out is that probably it's that this book has

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Speaker 1: been in Christian's house and it smells like Christian's dog

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Speaker 1: is Charlie's friend. Yeah, so right there, just in a

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Speaker 1: very personal anecdote situation between the two of us, have

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Speaker 1: a example of animal emotion and or intelligence it could be.

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Speaker 1: And so whenever you see an animal behavior, there's always

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Speaker 1: gonna be questions about how that behavior is brought about.

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Speaker 1: Is the animal acting purely on instinct? Is the animal

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Speaker 1: having thoughts? Is it putting things together in its head?

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Speaker 1: In a conscious way, and in a lot of cases,

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Speaker 1: it's difficult for us to know, right, Like, we always

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Speaker 1: want to know what the minds of our pets are like,

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Speaker 1: but it can it can be a black box to us.

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Speaker 1: Sometimes we we just perceive behaviors and we can't see

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Speaker 1: inside the box to know what's triggering the behaviors. Yeah,

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Speaker 1: So that leads us to our main expert that we're

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Speaker 1: going to be consulting for these episodes. And he's a

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Speaker 1: guy named and this is how I'm gonna pronounce it

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Speaker 1: for this episode, Franz Davol. He's a Dutch primatologist and pathologist,

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Speaker 1: but he refers to himself as we're going to discuss

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Speaker 1: through this episode, as a researcher of evolutionary cognition. And

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Speaker 1: he's actually based here in Atlanta at Emory University. He's

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Speaker 1: also a director at the Yerkeys National Primate Research Center,

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Speaker 1: which is also based out of here, UH and he

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Speaker 1: studies primate social behavior. Now, we're gonna be talking about

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Speaker 1: Dr Duvall's work in today's episode and then the next episode,

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Speaker 1: but we're also going to be bringing him on the

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Speaker 1: show to chat with us in the next episode, So

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Speaker 1: be sure to come back for that next time. So

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Speaker 1: the reason why we're talking about Devol specifically and his

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Speaker 1: his work but also his survey of the history of

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Speaker 1: animal intelligence is because he came out with a book

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Speaker 1: last year called Are We Smart Enough To Know? How

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Speaker 1: Smart Animals Are? So not the catchiest title in the world,

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Speaker 1: but it's a really good title because it very well

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Speaker 1: encapsulates the core question of the book. Um, It's not

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Speaker 1: just how smart animals are, though that is a primary

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Speaker 1: concern of of the book and and his research, but

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Speaker 1: it's also about if they are smart, how would we

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Speaker 1: know it. Would we be clever enough to figure out

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Speaker 1: ways to detect complex intelligence and cognition and animals or

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Speaker 1: are we so limited by our own narrow worldview that

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Speaker 1: we are unable to find the ways to see the

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Speaker 1: intelligence in these other creatures? Right? And he says right upfront,

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Speaker 1: probably in the like first five pages, the answer is yes,

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Speaker 1: but there are some qualifiers, right, which is basically, uh,

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Speaker 1: that we're getting there, we're working on we're getting better

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Speaker 1: at it. Um. Now, some background on him. He got

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Speaker 1: his doctorate in biology in nineteen seven, and he's most

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Speaker 1: known for his research on empathy in primates. Which is

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Speaker 1: something we're gonna be covering in the episode after this. UH.

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Speaker 1: He published fifteen books and has over a dozen articles.

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Speaker 1: This guy's I think it's fair to say prolific, UH.

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Speaker 1: And his focus has been on research related to primate

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Speaker 1: alliance formation, reconciliation, and quote the roots of moral behavior

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Speaker 1: in the most political of animals, meaning us, right. So yeah.

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Speaker 1: One of one of his early books was, for example,

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Speaker 1: about Machiavellian behavior in chimpanzees, which is UH, which is great,

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Speaker 1: like the idea of looking at the politics of chimpanzee

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Speaker 1: behavior through the eyes of jockeying for position, forming alliances,

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Speaker 1: trying to gain power, seeing the will to power in

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Speaker 1: our in our closest ape cousins. So have you heard

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Speaker 1: another anecdote? Have you heard this anecdote about Daval and

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Speaker 1: Jimmy Carter and new Gingrich? No, I've heard about UH.

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Speaker 1: I think that new Gingrich put one of Duval's books

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Speaker 1: on a reading list for his UH for I don't

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Speaker 1: know who, for people, for people in Congress, or for somebody. Yeah,

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Speaker 1: it might have just been his staff, I'm not sure.

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Speaker 1: But the story the way that I read it through

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Speaker 1: Daval in an interview was essentially I can't remember which

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Speaker 1: books were which, but Carter read one of his books

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Speaker 1: and Gingrich read one of his books and both of

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Speaker 1: them liked it. And Duval was basically like, I really

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Speaker 1: wish that they had swapped the books because I think

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Speaker 1: they both would have gotten something else. Oh so, like

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Speaker 1: one is about jockeying for power among primates and another

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Speaker 1: one is about empathy among primate Yeah, yeah, yeah, exactly,

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Speaker 1: So it's kind of fun, like little anecdote. And he

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Speaker 1: said he met with Jimmy Carter. Actually, I wonder if

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Speaker 1: you told him that when he met with him. But uh,

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Speaker 1: so he had to go to the dark side Carter,

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Speaker 1: I don't. That's not the impression that I get from him. Actually,

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Speaker 1: and we're not going to talk about it a ton,

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Speaker 1: uh in these episodes applying his work to modern politics,

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Speaker 1: but he that is something he does with his work. Um,

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Speaker 1: what we're more going to focus on is this book

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Speaker 1: and how it summarizes between case studies and a history

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Speaker 1: of the discipline. I guess i'll call it of looking

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Speaker 1: at animal intelligence, uh, specifically how it is coming to

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Speaker 1: defy the notion that humans are alone as moral in

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Speaker 1: thinking animals. Yeah, I think one of the central things

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Speaker 1: we want to talk about, and I'll revisit this later

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Speaker 1: in this episode. I'm sure is the idea of claims

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Speaker 1: of uniqueness about humans that that's central to this book.

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Speaker 1: And uh an idea that is that the devol attacks

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Speaker 1: with two swords in each hand. I would say he's

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Speaker 1: a dual handed attacker. Yeah. Nice, I like that. I

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Speaker 1: think I've read that actually, if you hold swords in

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Speaker 1: each hand, it's not actually an advantage in battle, like

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Speaker 1: you can't balance well. By D and D rules, you

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Speaker 1: get a negative two to one hand attack something along

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Speaker 1: those lines. I did not know that unless you have

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Speaker 1: a special feat. Okay, well let's go back to we

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Speaker 1: started with the idea of our pets. You know, we

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Speaker 1: want to get in their minds, but sometimes they can

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Speaker 1: feel like a black box. Um. So, when you see

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Speaker 1: an animal perform of behavior, an animal does something, I'd

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Speaker 1: say that there are three main explanations you can go to,

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Speaker 1: and it's not like the explanation is just one or

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Speaker 1: the other. Usually complex behaviors might be explained by combinations

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Speaker 1: of the following, but they're they're basically three wells you

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Speaker 1: can draw from to explain behaviors. One is instinct responding

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Speaker 1: to instinct. An instinct is a hardwired behavior. It's an

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Speaker 1: activity that we imagine being done automatically and programmed by

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Speaker 1: your genes. It's without much adaptive flexibility or applicability to

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Speaker 1: solving new problems. So birds fly south for the winter.

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Speaker 1: There are just natural triggers that hit their brains in

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Speaker 1: a certain way. When those triggers hit their brains, they

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Speaker 1: fly south. When I think of instinct in my human brain,

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Speaker 1: when I think about my brain and how it reacts,

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Speaker 1: it's like that my my brain has that certain wiring right,

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Speaker 1: and that those pathways are aligned to respond a certain way,

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Speaker 1: to react a certain way to things. But you can

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Speaker 1: theoretically train those pathways to change right right. And that's

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Speaker 1: the second thing that would be conden stioning. So first,

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Speaker 1: you've got instinct that's inborn, it's determined by your genes.

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Speaker 1: But you've also had conditioning, which is learned behaviors. You've

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Speaker 1: had experiences. Some experiences turned out good, some turned out bad.

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Speaker 1: You can think of those results as rewards and punishments,

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Speaker 1: and thus conditioning also leads us to cause new behaviors.

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Speaker 1: If you've done something that has gotten you a reward

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Speaker 1: in the past, you'll become conditioned to do that behavior

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Speaker 1: more in the future. Now, I wouldn't say that these

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Speaker 1: things are like one to one in an analogy, but

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Speaker 1: it's sort of the nature nurture argument, right, No, I

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Speaker 1: think it totally is. Yeah, So instinct is nature, uh,

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Speaker 1: conditioning is nurture. It's your environment, it's what you've been

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Speaker 1: conditioned to do. But then there's a third explanation you

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Speaker 1: can talk about. And the third explanation is more complex

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Speaker 1: than the other two. It's cognition. So humans do things

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Speaker 1: all the time that are not easily explicable, or at

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Speaker 1: least we would say some some you know, behaviorist or

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Speaker 1: somebody might disagree with us, but at least I would say,

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Speaker 1: are not silly explicable as either instinct or conditioned uh,

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Speaker 1: conditioned responses their complex behaviors that seem to emerge from

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Speaker 1: patterns of thinking. Right right, So before we get like

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Speaker 1: way too far down the rabbit hole here, let's like

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Speaker 1: stop and define what we mean here when we're talking

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Speaker 1: about intelligence and cognition. What are these at leasts? And

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Speaker 1: let's keep in mind too, we're keeping this within Duvol's framework.

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Speaker 1: So maybe, um, you're out there listening and you've got

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Speaker 1: experience in psychology or in biology and some other uh

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Speaker 1: part of the discipline, and you might disagree that we

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Speaker 1: would love to hear from you on that, But we're

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Speaker 1: specifically we're not saying this is the absolute truth. We're

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Speaker 1: saying this is Duval's UH schema that he presents us

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Speaker 1: with in this book. Right. Sure. So cognition, well, it's

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Speaker 1: basically information processing, right. His direct quote is it's the

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Speaker 1: mental transformation of sensory input in to knowledge about the

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Speaker 1: environment and the flexible application of this knowledge. So that

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Speaker 1: would be sort of like, um, I think for example

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Speaker 1: of a multi use tool, an example of cognition might be, uh,

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Speaker 1: you pick up a tool like a hammer, and you

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Speaker 1: figure out that with a hammer, you can drive nails,

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Speaker 1: you can crack nuts, you can smash windows if you

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Speaker 1: want to, you could maybe uh you can maybe throw

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Speaker 1: the hammer at somebody and get a laugh out of

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Speaker 1: your buddies. Depending on the hammer, you can pull nails out, right, Yeah,

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Speaker 1: certainly if it's a claw hammer, that's a good word.

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Speaker 1: It's great one word or a phrase. I don't know anyway,

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Speaker 1: but this is this is flexible application of knowledge. You

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Speaker 1: you take some knowledge about your environment, in this case,

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Speaker 1: about the uses of a tool. You understand the affordances

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Speaker 1: of this tool, the different things it can do, and

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Speaker 1: then you can apply it to new situations that you've

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Speaker 1: never been presented before. That would probably be an example

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Speaker 1: of cognition. So then we get to intelligence. And I've

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Speaker 1: already used some D and D analogies and here you know,

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Speaker 1: out there listeners, if you're you know, you've been around

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Speaker 1: in our audience for a while, we kind of throw

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Speaker 1: that stuff out there. Intelligence and D and D is

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Speaker 1: basically like your your aptitude at certain things, how much

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Speaker 1: we mean by intelligence is processing that information from cognition successfully.

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Speaker 1: So you're intelligent if you can successfully process that information right,

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Speaker 1: it's doing cognition good. Yeah. I like that. That's the

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Speaker 1: quote of the episode. One of I called the episode

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Speaker 1: that do cognition good? Do cognition good? I'd say, we

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Speaker 1: do cognition okay, uh no. I. So there are a

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Speaker 1: lot of different definitions of intelligence. One that I think

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Speaker 1: goes pretty much along with this, but that I really

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Speaker 1: like is that intelligent. And Robert and I just talked

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Speaker 1: definition is of intelligent and says, uh, the tendency of

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Speaker 1: a system to accelerate the solution of problems. So like

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Speaker 1: when you solve problems better than chance, when you start

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Speaker 1: to do better than random behavior, that is degrees of intelligence. Um.

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Speaker 1: But I think I think the key to understanding this

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Speaker 1: idea of cognition, and the key in this book is flexibility. Right. Okay,

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Speaker 1: so animals can, as we've said, performed tasks that seem

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Speaker 1: very complex, but they are still acting on coded instinct.

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Speaker 1: Cognition happens when animals show the flexible application of knowledge,

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Speaker 1: and that's what to keep in mind. The animal knows

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Speaker 1: something and is able to put that knowledge to use

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Speaker 1: in a novel way. So an example of this would

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Speaker 1: be the episode that Robert and I just published previous

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Speaker 1: to this about Pomp Pomp crabs or the Boxer crab.

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Speaker 1: Do you know about this well, I've seen you guys

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Speaker 1: talking about it a little bit. Yeah. So the we

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Speaker 1: have just discovered, and we did a whole episode on it,

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Speaker 1: that these crabs, um, they use seeing them and these

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Speaker 1: as weapons and tools in their claws. And not only

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Speaker 1: that but if they only have one of them, because

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Speaker 1: they like to duel wield, they will take the other

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Speaker 1: one and they will very purposely rip it in half

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Speaker 1: so that it causes it to regenerate into two different anemonies. Again,

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Speaker 1: so they're forcing reproduction upon these anemonies. That is theoretically

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Speaker 1: an example of animal intelligence, because not only are they

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Speaker 1: tool using animals, but they know how to exactly rip

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Speaker 1: apart another living being to turn them into like a tool.

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Speaker 1: Now we're brought back to the initial problem here, the

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Speaker 1: black box problem, because I could look at that and say,

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Speaker 1: that's very impressive behavior. That almost makes me want to think, Wow,

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Speaker 1: maybe crabs are much smarter than we thought. But then again,

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Speaker 1: on the other hand, I'm like, well, I mean, that's

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Speaker 1: an invertebrate. It doesn't have much brain to speak of.

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Speaker 1: Uh So is that really cognition or is that just

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Speaker 1: some kind of weird application of an instinctual, hard coded

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Speaker 1: behavior that we're not understanding, some kind of like u

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Speaker 1: um uh symbiotic relationship between these two species that's just developed, instinctually,

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Speaker 1: fully evolved, and that it's not like the crab has

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Speaker 1: to think it through. Uh. And I I don't know

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Speaker 1: I mean, it's hard to tell there. The fact that

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Speaker 1: the crab has such a simple nervous system would tend

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Speaker 1: to make me want to assume that that it's more

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Speaker 1: likely to be instinctual, But I don't know. That's what

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Speaker 1: we're We're in the black box. This is exactly where

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Speaker 1: we land with this current like area of the discipline.

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Speaker 1: It's like, you see a study like that, we don't

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Speaker 1: exactly know how to approach it in terms of saying,

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Speaker 1: is that animal intelligent or not? Right? And that gets

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Speaker 1: us to one of the ideas that I think is

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Speaker 1: underpinning the discussion of this book. So, when we talk

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Speaker 1: about animal cognition and a scientific context, I want to

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Speaker 1: ask a question of you Christ Yes, this is something

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Speaker 1: I think we should consider throughout these episodes. What is

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Speaker 1: the correct position of a scientific skeptic on the subject, Like, so,

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Speaker 1: if you are being skeptical of new claims, what is

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Speaker 1: the default assumption before any tests are done about animal cognition?

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Speaker 1: Uh So, back up and give some context. Default assumptions,

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Speaker 1: we use them all the time. Generally are default assumptions

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Speaker 1: are things that seem most in line with what we'd

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Speaker 1: expect given the rest of nature. And natural law. It's

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Speaker 1: what you'd think was true if you hadn't done any

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Speaker 1: experiments yet. Okay, but see, it's interesting that you're using

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Speaker 1: the term skeptic because devol uses that term um and

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Speaker 1: it's more along alignes that. How I think of it,

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Speaker 1: based on his book, is that these skeptics are looking

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Speaker 1: for evidence in laboratory and experimental settings exactly that that's

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Speaker 1: what a skeptic would do. I'm saying, like, what's the

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Speaker 1: skeptical starting assumption. You don't have any evidence yet, which

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Speaker 1: would you just assume is true? Would you assume that

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Speaker 1: animals do have cognition or would you just assume that

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Speaker 1: they don't? Uh So, Obviously, if somebody, if somebody publishes

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Speaker 1: a study zoology papers saying we found a Siberian freshwater

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Speaker 1: fish that can die and then spontaneously come back to

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Speaker 1: life twelve days later, you're going to be resistant to

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Speaker 1: that idea, even if it's published in a good journal, Right,

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Speaker 1: You're gonna be like, I don't know, I you know,

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Speaker 1: I want to understand more about this. I'm skeptical of

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Speaker 1: the findings. You'd want to see it replicated. Just one

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Speaker 1: person's first hand testimony is probably not going to be

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Speaker 1: good enough. Likewise, if you had other crazy stuff, you know,

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Speaker 1: I found a tree frog in the rainforest that poop's

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Speaker 1: weapons grade plutonium, you would just think, like I don't

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Speaker 1: quite believe that. I'd want really, really good evidence before

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Speaker 1: I believe that's true. Um, you definitely have to click

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Speaker 1: through the headline, like, that's not one way you can

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Speaker 1: just read the headline and Facebook and just trust it, right. Uh,

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Speaker 1: And so that's because a joke everybody. You should click

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Speaker 1: on everything. Oh, I don't know, Well, you should click

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Speaker 1: on everything you're interested in. That's what I mean. You

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Speaker 1: should click on all the melts. You shouldn't just read

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Speaker 1: headlines and assume that they're true. Yeah. Also side note,

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Speaker 1: if you're going to argue with an article, read the

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Speaker 1: article first. Don't argue with the headline. In fact that

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Speaker 1: we're going to get to that later on. But Daval

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Speaker 1: has strong feelings about that. Right. But so there's the question.

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Speaker 1: You you've got this standard skeptical assumption, the starting place,

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Speaker 1: the default assumption. Which way should it go with the

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Speaker 1: idea of animal cognition? Should we just assume that animals

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Speaker 1: are stimulus response machines without anything going on? Inside unless

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Speaker 1: somebody proves otherwise. Or should we assume that they process

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Speaker 1: information and have interiority just like us and arrive at

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Speaker 1: new ideas unless somebody proves otherwise. Um. So they're actually

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Speaker 1: historically totally different ways to go on this. So one

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Speaker 1: way that I think is much more in line with

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Speaker 1: Devall's thinking is the famously skeptical eighteenth century Scottish philosopher

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Speaker 1: David Hume. Right, he brings him up in this book. Yeah,

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Speaker 1: and so Hume says, the natural starting position is animals

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Speaker 1: do think it's obvious. And what Hume says is, um quote,

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Speaker 1: no truth appears to me more evident than that beasts

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Speaker 1: are endowed with thought and reason as well as man.

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Speaker 1: So I think it's important to note here that Hume,

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Speaker 1: let's repeat that again, he's an eighteenth century Scottish philosopher. Right,

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Speaker 1: So there's this understanding, at least, this is what I

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Speaker 1: got from Duval's book, that this kind of thinking was

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Speaker 1: actually common leading up to and a little bit after Darwin. Um. Yeah,

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Speaker 1: I mean this kind of thinking I think was there

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Speaker 1: with Darwin. Darwin believe, yeah, Darwin did too. Yeah, But

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Speaker 1: then we got into a mode I would say Uh.

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Speaker 1: In the second half of the nineteenth century that leaned

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Speaker 1: more toward the idea what we we're going to be

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Speaker 1: referring to as behaviorism here. Uh yeah, or um, well,

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Speaker 1: just denying animal cognition in general, but it's often associated

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Speaker 1: with the behavior at school of psycho oology. Right, So

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Speaker 1: what's the reasoning behind Hume's default assumption than animals think?

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Speaker 1: He says, this quote tis from the resemblance of the

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Speaker 1: external actions of animals to those we ourselves perform. So

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Speaker 1: because animals behave like humans behave, that we judge their

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Speaker 1: internal likewise to resemble ours. And the same principle of reasoning,

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Speaker 1: carried one step farther, will make us conclude that since

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Speaker 1: our internal actions resemble each other, the causes from which

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Speaker 1: they're derived must also be resembling. When any hypothesis therefore

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Speaker 1: is advanced to explain a mental operation which is common

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Speaker 1: to men and beasts, we must apply the same hypothesis

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Speaker 1: to both. So there he's saying, like, Okay, humans have cognition,

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Speaker 1: they have behavior. Animals have behavior that seems parallel to

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Speaker 1: human behavior, so we just extend back and say they

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Speaker 1: probably have cognition too. And I would say that's like

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Speaker 1: generally before like researching for this episode, where I sort

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Speaker 1: of landed on these lines, right, Like I I see

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Speaker 1: my dogs every day and interact with other animals in

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Speaker 1: my life. That's how I feel about them. Surely they

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Speaker 1: must be thinking and having emotions because it resembles my

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Speaker 1: own experience. Yeah, that's totally my default, my intuitive assumption.

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Speaker 1: Then again, I think our our intuitions we should be

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Speaker 1: strongly suspicious of. We we want to feel certain ways.

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Speaker 1: We like our pets, we want to think they're like us,

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Speaker 1: so we should be open to the opposite idea too.

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Speaker 1: But I think that's also my natural starting place is

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Speaker 1: that I don't know. We're animals. We think other animals,

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Speaker 1: and even if in some rudimentary way, probably do in

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Speaker 1: some sense kind of think. And that could have something

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Speaker 1: to do with where you and I fall in terms

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Speaker 1: of like where we live in history, you know. I mean, like,

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Speaker 1: if if we were recording this podcast in the late

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Speaker 1: nineteenth century, I don't know how we do that, it

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Speaker 1: would be like a crank and a pulley. But but anyways,

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Speaker 1: somebody taking really crappy dictation exactly we would we would

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Speaker 1: probably have different assumptions. Based on cultural expectations. Sure, this

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Speaker 1: idea has been it wasn't just you know, later after

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Speaker 1: Jar when it wasn't just like people in the behavior

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Speaker 1: at school that didn't like this idea of animal cognition.

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Speaker 1: For example, you go way back to the philosopher Renee

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Speaker 1: de cart Descartes famously Decartes he were so he thinks, well,

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Speaker 1: I think, therefore I am, but animals don't think he

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Speaker 1: regarded animals as automata or machines. Essentially, there's some scholarly

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Speaker 1: back and forth. I tried to find what's the best

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Speaker 1: interpretation of what Descartes's position was. Uh, did he deny

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Speaker 1: them all possible interiority of any kind? It's not exactly clear.

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Speaker 1: But in any case, he did not think that animals

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Speaker 1: could think. This is interesting to me, because like you know,

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Speaker 1: I got the like very general philosophy one oh one

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Speaker 1: approach to decart when I was an undergraduate. You know,

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Speaker 1: decart had that that theory that he thought hard on

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Speaker 1: about whether or not he was just a brain in

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Speaker 1: a jar that like a demon was torturing by like

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Speaker 1: providing him like a matrix like sort of virtual reality

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Speaker 1: that he thought was the real world. It was his

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Speaker 1: total doubt about empiricism is that I can't believe anything

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Speaker 1: of my senses because it could be the case that

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Speaker 1: some magical being is is just giving me illusions. Yeah,

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Speaker 1: but he would not think the same thing as possible

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Speaker 1: for a dog or a chimpanzee that maybe they're because

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Speaker 1: they're not even perceiving and he's part of their imagination, right,

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Speaker 1: He wouldn't even consider that. And that goes right back

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Speaker 1: to the heart of all of this, which Duval comes

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Speaker 1: back to a lot, which is human centrism. Yeah, and anthropocentrism. Uh.

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Speaker 1: He talks a lot in the book about anthropocentrism, the

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Speaker 1: idea of of humans being the you know, the center

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Speaker 1: of the universe, or humans being totally unique, humans being

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Speaker 1: the one thing that's different than everything else. Uh. And

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Speaker 1: and I think we can talk about that a little

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Speaker 1: more towards the very end of this episode. But we

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Speaker 1: should come back to this, uh, this behaviorism, ethology and

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Speaker 1: and and cognition divide. All right, let's take a quick

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Speaker 1: break and when we get back, we'll talk more about

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Speaker 1: animals and of all, so the way that devolve defines it,

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Speaker 1: as he says, you know, up until I don't know, like,

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Speaker 1: what would you say, maybe thirty years ago in the

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Speaker 1: discipline even shorter, possibly that we've really been living in

425
00:24:18,720 --> 00:24:24,600
Speaker 1: a behaviorist influenced society when it comes to thinking about

426
00:24:24,760 --> 00:24:28,280
Speaker 1: animal intelligence or emotion. So the basic split that he

427
00:24:28,359 --> 00:24:32,560
Speaker 1: defines here in thinking about human to animal cognition comes

428
00:24:32,800 --> 00:24:36,840
Speaker 1: from the move from a hunter gatherer society to an

429
00:24:36,920 --> 00:24:41,480
Speaker 1: agricultural one. This is interesting because we're well into agricultural

430
00:24:41,560 --> 00:24:44,480
Speaker 1: society by the time, you know, behavioral thinking comes around,

431
00:24:44,600 --> 00:24:48,080
Speaker 1: but for years. Yeah, but he says, this is why

432
00:24:48,160 --> 00:24:51,280
Speaker 1: science hast thought of animals as being subservient rather than

433
00:24:51,400 --> 00:24:54,040
Speaker 1: us having an empathy for a view of the world

434
00:24:54,119 --> 00:24:56,320
Speaker 1: from their perspective in the way that we used to

435
00:24:56,400 --> 00:24:58,399
Speaker 1: have to when we would run around in the woods

436
00:24:58,440 --> 00:25:01,120
Speaker 1: and either try to hunt them down own or avoid

437
00:25:01,200 --> 00:25:04,280
Speaker 1: being their prey. That's really interesting because so if you're

438
00:25:04,280 --> 00:25:07,880
Speaker 1: a hunter, an animal is almost like an enemy. It's

439
00:25:07,920 --> 00:25:09,440
Speaker 1: like a thing that you have to you have to

440
00:25:09,480 --> 00:25:11,960
Speaker 1: empathize with, you have to understand its mode of thinking,

441
00:25:12,040 --> 00:25:15,159
Speaker 1: and it's a very active agent that you're in competition with,

442
00:25:15,840 --> 00:25:19,560
Speaker 1: whereas an agricultural animal is a tool. It's the thing

443
00:25:19,680 --> 00:25:25,080
Speaker 1: you use. Yeah, exactly, So the two dominant states of

444
00:25:25,160 --> 00:25:29,119
Speaker 1: thought that have we've really viewed animals with during this

445
00:25:29,359 --> 00:25:33,760
Speaker 1: time have been either like Joe mentioned that their stimulus

446
00:25:33,800 --> 00:25:37,800
Speaker 1: response machines or and this is devolves wording that they're

447
00:25:37,960 --> 00:25:41,520
Speaker 1: quote robots that are endowed with instincts. He doesn't actually

448
00:25:41,640 --> 00:25:44,840
Speaker 1: think they're mechanical robots. He means robots and sort of

449
00:25:44,880 --> 00:25:49,040
Speaker 1: the metaphorical sense, right. Uh. And anyone who thought about

450
00:25:49,080 --> 00:25:54,160
Speaker 1: animal emotions at all was just deemed unscientific and kind

451
00:25:54,200 --> 00:25:59,359
Speaker 1: of blacklisted almost, right. And so skeptics, for instance, believe

452
00:25:59,480 --> 00:26:02,720
Speaker 1: that animal alls are trapped in the present, right, that

453
00:26:02,840 --> 00:26:05,520
Speaker 1: they don't make plans for the future. One example he

454
00:26:05,640 --> 00:26:09,320
Speaker 1: gives is that they couldn't possibly say goodbye to each other.

455
00:26:09,840 --> 00:26:14,080
Speaker 1: But Duval argues otherwise, and he provides examples in this book,

456
00:26:14,359 --> 00:26:17,680
Speaker 1: especially from his own experience working with primates. Right, he

457
00:26:17,960 --> 00:26:20,960
Speaker 1: comes across this idea of or not comes across. I'd

458
00:26:20,960 --> 00:26:24,639
Speaker 1: say he coins this term. I believe the term anthropo denial,

459
00:26:25,440 --> 00:26:28,080
Speaker 1: which I found is a very interesting principle, and I

460
00:26:28,119 --> 00:26:29,840
Speaker 1: wanted to stop and linger on that for a second.

461
00:26:30,119 --> 00:26:33,560
Speaker 1: That's cool with you. So it's related to the idea

462
00:26:33,560 --> 00:26:37,960
Speaker 1: of anthropomorphism, which is this concept that we often employee

463
00:26:38,000 --> 00:26:41,879
Speaker 1: in a really accusatory way. You know, I'm saying, uh,

464
00:26:42,359 --> 00:26:45,040
Speaker 1: if you think your dog thinks like a human, if

465
00:26:45,080 --> 00:26:48,480
Speaker 1: you think your dog loves you, you're being anthropomorphic. You're

466
00:26:48,840 --> 00:26:51,280
Speaker 1: you're turning the dog into a human in your mind,

467
00:26:51,359 --> 00:26:55,520
Speaker 1: and that's that's bad behavior. That's being irrational. The dog

468
00:26:55,720 --> 00:26:57,639
Speaker 1: is not like a human. Yeah, it would even be

469
00:26:57,840 --> 00:27:00,320
Speaker 1: like it's seen as like the person of aation of

470
00:27:00,320 --> 00:27:03,359
Speaker 1: an inanimate object in some sense, right, like when when

471
00:27:03,359 --> 00:27:06,000
Speaker 1: you get mad at your computer, my microphone. I've named

472
00:27:06,040 --> 00:27:08,960
Speaker 1: my microphone Jimmy, and Jimmy doesn't like it when I

473
00:27:09,040 --> 00:27:11,479
Speaker 1: get too close and breathe into him like this, right,

474
00:27:11,600 --> 00:27:14,600
Speaker 1: something like that. They would go, oh, like, why would

475
00:27:14,600 --> 00:27:16,840
Speaker 1: you possibly think about a dog or an ape like that?

476
00:27:17,040 --> 00:27:18,960
Speaker 1: But that's not like a human at all, because humans

477
00:27:19,040 --> 00:27:21,560
Speaker 1: love it when you breathe into them. They do. That's

478
00:27:21,600 --> 00:27:24,320
Speaker 1: how I express my love to human. What else is

479
00:27:24,359 --> 00:27:29,119
Speaker 1: CPR for? That's recreational, right yeah? Uh no. But so

480
00:27:29,359 --> 00:27:32,240
Speaker 1: a lot of times the charge of anthropomorphism, I think

481
00:27:32,400 --> 00:27:34,440
Speaker 1: is a fair one. Like a lot of times people

482
00:27:34,520 --> 00:27:38,600
Speaker 1: do draw unjustified parallels between humans and something that isn't human.

483
00:27:38,680 --> 00:27:41,240
Speaker 1: One example would be If you have some fish in

484
00:27:41,280 --> 00:27:44,600
Speaker 1: a bowl and you see the fish touching their mouths together,

485
00:27:45,000 --> 00:27:49,800
Speaker 1: and you characterize that as kissing, you're probably anthropomorphizing, right,

486
00:27:49,840 --> 00:27:52,720
Speaker 1: because the similarity of the action to our human mouth

487
00:27:52,840 --> 00:27:57,000
Speaker 1: touching behavior. It's incidental. Like, it's not that the fish

488
00:27:57,080 --> 00:28:00,560
Speaker 1: are having an emotional connection and they're sharing a passionate

489
00:28:00,680 --> 00:28:03,240
Speaker 1: kiss to show how much they love each other. It's

490
00:28:03,320 --> 00:28:07,040
Speaker 1: just a behavior that involves mouth touching that's unrelated to

491
00:28:07,160 --> 00:28:10,680
Speaker 1: our behavior that involves mouth touching. And fish don't use

492
00:28:10,760 --> 00:28:13,359
Speaker 1: tongue like they're not familiar with the French method. But

493
00:28:13,440 --> 00:28:17,440
Speaker 1: according to duvol but nobos do do indeed French kiss. Yeah.

494
00:28:17,960 --> 00:28:21,120
Speaker 1: On the other hand, Dval says that you can practice

495
00:28:21,200 --> 00:28:24,480
Speaker 1: the opposite of anthropomorphism, or maybe not the opposite, the inverse,

496
00:28:25,040 --> 00:28:29,840
Speaker 1: which is anthropo denial. It's an unjustified ape a priori

497
00:28:30,040 --> 00:28:34,160
Speaker 1: rejection of analogies between humans and non human animals when

498
00:28:34,280 --> 00:28:38,320
Speaker 1: those analogies are in fact apt. It's just being prejudiced

499
00:28:38,360 --> 00:28:42,440
Speaker 1: against comparing human and animal behaviors, even in situations where

500
00:28:42,480 --> 00:28:46,800
Speaker 1: those comparisons probably are in some sense justified. The example

501
00:28:46,880 --> 00:28:49,560
Speaker 1: here would be apes kissing, and this is not like

502
00:28:49,680 --> 00:28:52,800
Speaker 1: fish kissing. No, not at all, And Duval has both

503
00:28:52,880 --> 00:28:58,040
Speaker 1: experience with ape kissing and anthropo denial, right like he

504
00:28:59,080 --> 00:29:01,440
Speaker 1: through much of his career and the work that he's done,

505
00:29:01,480 --> 00:29:04,160
Speaker 1: has had people say to him, Uh, this is clearly

506
00:29:04,240 --> 00:29:07,160
Speaker 1: not real science, like the things that you're saying about

507
00:29:07,200 --> 00:29:09,640
Speaker 1: these animals. And yet let's let's look at one of

508
00:29:09,680 --> 00:29:13,120
Speaker 1: his case studies with these apes. What you mean like tickling, well,

509
00:29:13,200 --> 00:29:16,080
Speaker 1: tickling and kissing. Yeah, yeah, kissing is one. Tickling is

510
00:29:16,120 --> 00:29:19,320
Speaker 1: another one. So when you when you say, uh, so

511
00:29:19,480 --> 00:29:22,120
Speaker 1: a young ape gets tickled, right, you got a chimpanzee baby,

512
00:29:22,280 --> 00:29:24,680
Speaker 1: you tickle it and it makes rapid in and out

513
00:29:24,800 --> 00:29:29,840
Speaker 1: breathing noises. Should you call that laughter? Uh? If you did,

514
00:29:30,000 --> 00:29:33,120
Speaker 1: some people might scold you as being anthropomorphic, saying, how

515
00:29:33,160 --> 00:29:36,240
Speaker 1: can you know that this ape is laughing? Uh? Maybe

516
00:29:36,320 --> 00:29:38,880
Speaker 1: you don't know, But it does seem like a fair

517
00:29:38,920 --> 00:29:43,720
Speaker 1: analogy because humans in chimpanzees or phylogenetically extremely close and

518
00:29:44,080 --> 00:29:47,600
Speaker 1: humans exhibit this behavior pretty much in the same context

519
00:29:47,800 --> 00:29:51,280
Speaker 1: being tickled, and so it just sort of does make

520
00:29:51,360 --> 00:29:53,920
Speaker 1: sense that you could say this is pretty much laughter. Right.

521
00:29:53,960 --> 00:29:56,560
Speaker 1: It might not be laughter in exactly the same way

522
00:29:56,560 --> 00:30:00,080
Speaker 1: as human laughter. There might be very important differences, but

523
00:30:00,160 --> 00:30:03,760
Speaker 1: it's also a close enough analogy that the human comparison

524
00:30:03,840 --> 00:30:06,960
Speaker 1: does make biological sense. Right. And then his other example

525
00:30:07,080 --> 00:30:09,160
Speaker 1: was the kissing that we've referred to, and if I

526
00:30:09,240 --> 00:30:12,320
Speaker 1: remember correctly, it was something along the lines of uh.

527
00:30:12,560 --> 00:30:17,360
Speaker 1: There was a researcher observing this practice between their banobo's right,

528
00:30:17,720 --> 00:30:20,200
Speaker 1: and then themselves sort of said, well, let's see what

529
00:30:20,280 --> 00:30:22,000
Speaker 1: this is like. I'll show some affection to this and

530
00:30:22,080 --> 00:30:25,640
Speaker 1: I'll kiss this epe uh, and then got a mouthful

531
00:30:25,680 --> 00:30:28,920
Speaker 1: a tongue because it was just it was a powerful kisser.

532
00:30:29,040 --> 00:30:31,880
Speaker 1: The bonobos have a different kissing culture. The bonobos. He

533
00:30:31,960 --> 00:30:34,920
Speaker 1: was more tongue than the chimpanzees doing. Apparently, this is

534
00:30:35,080 --> 00:30:38,320
Speaker 1: this is what we've learned, so we haven't always thought

535
00:30:38,440 --> 00:30:42,400
Speaker 1: like this though, like I mentioned earlier, Darwin himself wrote

536
00:30:42,440 --> 00:30:48,000
Speaker 1: about animal emotions, for instance, and Aristotle actually classified animals

537
00:30:48,080 --> 00:30:51,800
Speaker 1: in his Scala not try. I think that's terrible Greek,

538
00:30:51,960 --> 00:30:54,040
Speaker 1: but I think that's what it was. It was like

539
00:30:54,160 --> 00:30:56,520
Speaker 1: his great chain of being. Yeah, it was his simple

540
00:30:56,560 --> 00:31:00,640
Speaker 1: way of measuring like animals by human standards. The application, though,

541
00:31:00,720 --> 00:31:04,320
Speaker 1: until recently, has been that we study animal cognition only

542
00:31:04,400 --> 00:31:06,960
Speaker 1: so we can better understand ourselves. Why would we possibly

543
00:31:07,000 --> 00:31:09,760
Speaker 1: want to know what's going inside going on inside the

544
00:31:09,800 --> 00:31:13,840
Speaker 1: minds of fish? Right? Uh So Deval lays the blame

545
00:31:14,040 --> 00:31:16,920
Speaker 1: for this kind of thinking on the rise of behavior

546
00:31:16,960 --> 00:31:20,640
Speaker 1: of psychology. So he provides us with an example here,

547
00:31:21,080 --> 00:31:25,040
Speaker 1: specifically looking at these birds called kittie wakes. Right. So

548
00:31:25,160 --> 00:31:27,400
Speaker 1: these are birds in the gull family, and he talks

549
00:31:27,400 --> 00:31:30,760
Speaker 1: about how these birds nest on narrow cliffs, and they're

550
00:31:30,800 --> 00:31:32,600
Speaker 1: different than a lot of other birds because a lot

551
00:31:32,640 --> 00:31:36,120
Speaker 1: of like gulls, other seabirds might nest in open areas

552
00:31:36,800 --> 00:31:41,160
Speaker 1: where their nests are open to invasion and predation and

553
00:31:41,200 --> 00:31:43,360
Speaker 1: stuff like that. So these nests are like really high

554
00:31:43,480 --> 00:31:45,800
Speaker 1: up right, yeah. Yeah, And so the the other seabirds

555
00:31:45,880 --> 00:31:48,000
Speaker 1: might need to keep a close eye on their offspring

556
00:31:48,040 --> 00:31:50,440
Speaker 1: and make sure others don't try to come into the nest.

557
00:31:51,000 --> 00:31:53,480
Speaker 1: The kitty wakes don't. The kitty wakes, you can you

558
00:31:53,560 --> 00:31:56,720
Speaker 1: can put a strange young ling in their nests and

559
00:31:57,240 --> 00:31:59,160
Speaker 1: they don't seem they'll treat it just like it's one

560
00:31:59,200 --> 00:32:01,560
Speaker 1: of their own. They don't recognize that it's an invader.

561
00:32:01,600 --> 00:32:04,280
Speaker 1: And this seems to be because the kitty wakes leave

562
00:32:04,600 --> 00:32:07,080
Speaker 1: live on these little narrow cliffs where there's just not

563
00:32:07,200 --> 00:32:10,400
Speaker 1: really much opportunity for something else to get into the nest. Yeah,

564
00:32:10,440 --> 00:32:13,960
Speaker 1: So why would they have developed the capacity to recognize

565
00:32:13,960 --> 00:32:16,480
Speaker 1: the difference between they're young and somebody else is young. Yeah,

566
00:32:16,880 --> 00:32:20,760
Speaker 1: So he says, for the behaviorist though, such findings like

567
00:32:20,880 --> 00:32:25,040
Speaker 1: this are thoroughly puzzling. Two similar birds differing so starkly,

568
00:32:25,120 --> 00:32:27,840
Speaker 1: and what they learn makes no sense because learning is

569
00:32:27,920 --> 00:32:31,600
Speaker 1: supposedly universal. Right. So from the behaviorist perspective of the

570
00:32:31,680 --> 00:32:34,239
Speaker 1: kitty wakes should be the same as any other bird, right, right.

571
00:32:34,280 --> 00:32:38,040
Speaker 1: So the behaviorist idea is that behavior is explained by

572
00:32:38,080 --> 00:32:42,600
Speaker 1: these universal principles of reward and punishment reinforcement. It's all

573
00:32:42,680 --> 00:32:45,840
Speaker 1: conditioning based on what has rewarded you or punished you

574
00:32:45,920 --> 00:32:48,320
Speaker 1: in the past. Yeah. So he draws the line, and

575
00:32:48,360 --> 00:32:51,200
Speaker 1: he says, the difference between behaviorism and then this other

576
00:32:51,240 --> 00:32:53,280
Speaker 1: school of thought called ethology that we're going to get

577
00:32:53,320 --> 00:32:59,719
Speaker 1: into has always been one of human controlled versus natural behavior. Uh.

578
00:32:59,800 --> 00:33:04,600
Speaker 1: And tenant here is that comparative psychologists had animals perform

579
00:33:05,240 --> 00:33:08,240
Speaker 1: arbitrary tasks unrelated to the problems that they actually face

580
00:33:08,320 --> 00:33:11,760
Speaker 1: in their natural environment. And this was how we gathered

581
00:33:11,880 --> 00:33:15,960
Speaker 1: and tested their intelligence. So, using the kittywake example, we

582
00:33:16,080 --> 00:33:18,440
Speaker 1: weren't you know, if you took them out of their

583
00:33:18,480 --> 00:33:21,600
Speaker 1: natural environment and you noticed that they didn't happen to

584
00:33:21,760 --> 00:33:24,880
Speaker 1: understand the difference between their young and somebody else's young,

585
00:33:25,040 --> 00:33:27,840
Speaker 1: some other birds young, then you would go, what's wrong

586
00:33:27,880 --> 00:33:32,200
Speaker 1: with this bird? Right? But when you understand the context

587
00:33:32,280 --> 00:33:35,040
Speaker 1: that the bird lives within, it makes more sense. This

588
00:33:35,200 --> 00:33:37,920
Speaker 1: is a big theme of Duvall's book is the idea

589
00:33:38,000 --> 00:33:41,480
Speaker 1: of understanding uh. It's a It's a term that's known

590
00:33:41,520 --> 00:33:44,400
Speaker 1: as an animal's um velt, and the um velt is

591
00:33:44,560 --> 00:33:47,800
Speaker 1: the idea of it's an animal's world view from its

592
00:33:47,920 --> 00:33:51,280
Speaker 1: natural place in the world. So each animal has its

593
00:33:51,320 --> 00:33:54,640
Speaker 1: own niche has its own way of interacting with its environment,

594
00:33:54,720 --> 00:33:58,880
Speaker 1: the things that naturally has to do. And sometimes we

595
00:33:59,040 --> 00:34:02,880
Speaker 1: might be totally unable to appreciate why an animal behaves

596
00:34:02,920 --> 00:34:05,640
Speaker 1: the way it does if we don't appreciate what its

597
00:34:05,800 --> 00:34:08,640
Speaker 1: role within its natural environment is, what does it normally

598
00:34:08,760 --> 00:34:11,359
Speaker 1: have to do to survive and those are the things

599
00:34:11,440 --> 00:34:14,839
Speaker 1: that define that animal's mentality. It would also be things

600
00:34:14,920 --> 00:34:18,879
Speaker 1: like that animals particular types of heightened senses, its peak

601
00:34:19,040 --> 00:34:22,920
Speaker 1: specialization in the environment is the animal's oom velt. And

602
00:34:22,960 --> 00:34:25,880
Speaker 1: if you don't understand that, you're probably going to be

603
00:34:26,040 --> 00:34:28,920
Speaker 1: testing the animal in ways that are not appropriate for

604
00:34:29,080 --> 00:34:31,840
Speaker 1: that animal. Yeah, and he gets this term from a

605
00:34:31,920 --> 00:34:36,560
Speaker 1: guy named Ya cub Funks Cull. This is a tough

606
00:34:36,680 --> 00:34:38,239
Speaker 1: name for me to pronounce. Man, if you look at

607
00:34:38,280 --> 00:34:41,080
Speaker 1: all the consonants in front of me here. Uh, but

608
00:34:41,320 --> 00:34:46,520
Speaker 1: uh oom velt translates into surviving world, and it's essentially

609
00:34:46,640 --> 00:34:50,560
Speaker 1: describing an animal sensory context. Dv All calls this in

610
00:34:50,680 --> 00:34:52,799
Speaker 1: his book. He refers to it as the magic well

611
00:34:53,080 --> 00:34:55,640
Speaker 1: of the life of animals, right, and each each species

612
00:34:55,680 --> 00:34:58,280
Speaker 1: has its own magic well. The magic well is another

613
00:34:58,320 --> 00:35:01,080
Speaker 1: really interesting idea that he draws on in the book repeatedly.

614
00:35:01,520 --> 00:35:03,840
Speaker 1: That's a it's a metaphor for the idea of a

615
00:35:04,000 --> 00:35:06,600
Speaker 1: well that the more you draw out of it, the

616
00:35:06,719 --> 00:35:10,000
Speaker 1: more it produces a well that never goes dry. Right.

617
00:35:10,719 --> 00:35:13,279
Speaker 1: It's like the well wouldn't be like the golden goose,

618
00:35:13,280 --> 00:35:15,200
Speaker 1: because if you keep if you try to get the

619
00:35:15,239 --> 00:35:16,920
Speaker 1: gold out of the goose, it dies. This would be

620
00:35:16,920 --> 00:35:18,759
Speaker 1: the opposite of that. This would be like the more

621
00:35:18,840 --> 00:35:20,680
Speaker 1: you kill the goose and pull the gold out, the

622
00:35:20,760 --> 00:35:22,840
Speaker 1: more gold is in it. I didn't know that the

623
00:35:22,920 --> 00:35:25,239
Speaker 1: golden goose died if you just kept taking gold out

624
00:35:25,280 --> 00:35:27,040
Speaker 1: of it. Is that the myth? Well, no, I think

625
00:35:27,080 --> 00:35:29,200
Speaker 1: it's that the goose lays golden eggs and then somebody

626
00:35:29,239 --> 00:35:30,759
Speaker 1: wants to get the gold out of the middle of it.

627
00:35:30,880 --> 00:35:35,080
Speaker 1: They kill it, and then there's no gold inside. Yeah,

628
00:35:35,160 --> 00:35:37,440
Speaker 1: that's the story. It's to punish you for being greedy

629
00:35:37,480 --> 00:35:39,520
Speaker 1: and not being happy with what you have. But but

630
00:35:39,719 --> 00:35:41,719
Speaker 1: the analogy is the golden egg once a day and

631
00:35:41,800 --> 00:35:45,840
Speaker 1: you want right and so I stretched this analogy to

632
00:35:45,920 --> 00:35:48,640
Speaker 1: a really torture rack position. But this would be the

633
00:35:49,040 --> 00:35:50,640
Speaker 1: goose that you kill it and you open it up

634
00:35:50,719 --> 00:35:53,160
Speaker 1: and it just keeps producing more and more gold from

635
00:35:53,200 --> 00:35:57,200
Speaker 1: the inside. It is a magically re replenishing source. And

636
00:35:57,320 --> 00:36:00,080
Speaker 1: the idea here would be a magically replenishing source of

637
00:36:00,200 --> 00:36:03,960
Speaker 1: new ideas and information. Interesting things to learn about an animal.

638
00:36:04,080 --> 00:36:07,239
Speaker 1: One example would be the b But with many species,

639
00:36:07,520 --> 00:36:11,160
Speaker 1: you can find their magic well. And once you have

640
00:36:11,280 --> 00:36:13,760
Speaker 1: found their magic well, you know they're sort of area

641
00:36:13,800 --> 00:36:16,960
Speaker 1: of specialization. You can you continue to find more and

642
00:36:17,040 --> 00:36:19,759
Speaker 1: more surprising and interesting things about them. Yeah. The way

643
00:36:19,800 --> 00:36:22,480
Speaker 1: he says it is that animals are driven to learn

644
00:36:22,960 --> 00:36:26,160
Speaker 1: based on their context. So once we immerse ourselves within that,

645
00:36:26,719 --> 00:36:29,439
Speaker 1: there's a whole magic well of things to learn about

646
00:36:29,480 --> 00:36:33,239
Speaker 1: that animal and their intelligence. Uh. He gives one example here,

647
00:36:33,320 --> 00:36:36,480
Speaker 1: I like, as like bringing it back to the behaviorism

648
00:36:36,600 --> 00:36:41,040
Speaker 1: versus ethology sort of schism. He says, one can train

649
00:36:41,200 --> 00:36:44,960
Speaker 1: goldfish to play soccer and bears to dance. I knew

650
00:36:45,000 --> 00:36:46,520
Speaker 1: about the dancing. I didn't know you could train gold

651
00:36:46,520 --> 00:36:48,640
Speaker 1: fish to play soccer. But it sounds right, he says,

652
00:36:48,680 --> 00:36:51,000
Speaker 1: it sounds like one of those good studies. But does

653
00:36:51,080 --> 00:36:54,480
Speaker 1: anyone believe that this tells us much about the skills

654
00:36:54,680 --> 00:36:58,560
Speaker 1: of human soccer stars or dancers? Makes a good point there, right,

655
00:36:58,719 --> 00:37:01,000
Speaker 1: you know, like, yeah, through conditioning, you can get a

656
00:37:01,040 --> 00:37:02,439
Speaker 1: fish to do this, or you can get a bear

657
00:37:02,520 --> 00:37:04,360
Speaker 1: to do this. But what does that say about the

658
00:37:04,440 --> 00:37:07,120
Speaker 1: human condition? Not a whole lot. And what does that

659
00:37:07,239 --> 00:37:09,879
Speaker 1: say about bears or fish? Benga, Probably not much about

660
00:37:09,880 --> 00:37:12,200
Speaker 1: them either. Yeah, So I think, as we mentioned at

661
00:37:12,239 --> 00:37:15,240
Speaker 1: the top, he is a director at the Yerkes Center,

662
00:37:15,440 --> 00:37:18,920
Speaker 1: which is here in Atlanta, that's a primate study facility,

663
00:37:19,640 --> 00:37:21,800
Speaker 1: and he says that in the nineteen fifties, actually the

664
00:37:21,880 --> 00:37:24,840
Speaker 1: center was founded in Florida, and so there was a

665
00:37:24,880 --> 00:37:29,440
Speaker 1: lot of tension there between their staff and the behaviorists

666
00:37:29,520 --> 00:37:32,360
Speaker 1: who came in and worked there, because the behaviorists wanted

667
00:37:32,400 --> 00:37:35,200
Speaker 1: to starve the chimpanzees that they were testing so that

668
00:37:35,320 --> 00:37:40,239
Speaker 1: they would be more likely to respond to reward based conditioning.

669
00:37:40,840 --> 00:37:44,160
Speaker 1: Uh and he said the rumor was that the staff

670
00:37:44,200 --> 00:37:48,080
Speaker 1: would sabotage the lab by feeding the animals at night,

671
00:37:48,120 --> 00:37:51,480
Speaker 1: and the behaviorists just basically we're totally disgusted and threw

672
00:37:51,520 --> 00:37:53,360
Speaker 1: their hands up. We're like, we can't do anything with this.

673
00:37:54,280 --> 00:37:56,800
Speaker 1: It's fascinating. You won't properly starve, you know what it

674
00:37:56,880 --> 00:37:59,439
Speaker 1: reminds me of. Have you seen any of the current

675
00:37:59,520 --> 00:38:01,719
Speaker 1: batch of Planet of the Apes movies? Oh? Yeah, I have.

676
00:38:02,040 --> 00:38:05,040
Speaker 1: Like the first one with James Franco. I thought that

677
00:38:05,200 --> 00:38:08,400
Speaker 1: movie was bad until all the human actors left and

678
00:38:08,480 --> 00:38:10,640
Speaker 1: it just became about the apes, And once it was

679
00:38:10,680 --> 00:38:13,560
Speaker 1: about the apes, it was great. Yeah. Yeah, I kind

680
00:38:13,600 --> 00:38:15,200
Speaker 1: of like them. I haven't seen the second one yet.

681
00:38:15,239 --> 00:38:17,080
Speaker 1: I think I think the third one is coming out soon.

682
00:38:17,239 --> 00:38:19,120
Speaker 1: I don't know the second one. I thought the second

683
00:38:19,160 --> 00:38:21,080
Speaker 1: one was kind of good. Yeah, okay, well I need

684
00:38:21,160 --> 00:38:22,840
Speaker 1: to check it out. But that this is what was

685
00:38:22,960 --> 00:38:24,640
Speaker 1: kemping up in my head as I was reading. I

686
00:38:24,680 --> 00:38:29,080
Speaker 1: can't totally vouch for scientific accuracy. Yeah I don't. We'll

687
00:38:29,120 --> 00:38:33,200
Speaker 1: have to ask what he thinks. It's a good ape storytelling.

688
00:38:34,000 --> 00:38:35,680
Speaker 1: So all right, I'm gonna take us on a tangent

689
00:38:35,800 --> 00:38:39,040
Speaker 1: here for a second, because many of you may hear

690
00:38:39,120 --> 00:38:42,000
Speaker 1: behaviorism or operating conditioning and the first thing that pops

691
00:38:42,040 --> 00:38:44,560
Speaker 1: into your head is B. F. Skinner, because he's the

692
00:38:44,600 --> 00:38:47,640
Speaker 1: guy we're all taught about in high school basic basic

693
00:38:47,760 --> 00:38:52,239
Speaker 1: psychology usually involved some kind of Skinner research, right, The

694
00:38:52,280 --> 00:38:56,359
Speaker 1: Skinner was massively influential in twentieth century psychology. Now, I've

695
00:38:56,400 --> 00:38:59,759
Speaker 1: got a weird example here about Skinner's thought process, but

696
00:38:59,840 --> 00:39:05,920
Speaker 1: it's also related to my own education. Okay, so you

697
00:39:06,040 --> 00:39:09,400
Speaker 1: were put in a box with electric shocks, yes, but

698
00:39:09,520 --> 00:39:12,000
Speaker 1: that doesn't have anything to do with this. No. Uh.

699
00:39:12,840 --> 00:39:17,359
Speaker 1: I had heard this whole story from my psychology teacher

700
00:39:17,440 --> 00:39:20,720
Speaker 1: in high school that Skinner put one of his children

701
00:39:20,800 --> 00:39:23,920
Speaker 1: in a Skinner box. Hold on, you got to explain

702
00:39:23,960 --> 00:39:26,239
Speaker 1: the concept of a Skinner box. I'm going to I

703
00:39:26,320 --> 00:39:30,719
Speaker 1: remember I remember being like really, like that's allowed, Like

704
00:39:30,800 --> 00:39:34,959
Speaker 1: I couldn't believe it, And here it is and it isn't,

705
00:39:35,080 --> 00:39:37,920
Speaker 1: and I'll explain why so, but I'm using this as

706
00:39:37,960 --> 00:39:39,800
Speaker 1: an example. It's a little bit of a diversion, but

707
00:39:39,920 --> 00:39:43,440
Speaker 1: it shows you the kind of thought processes that Skinner

708
00:39:43,520 --> 00:39:48,120
Speaker 1: had when he was testing. Okay, so, uh, there's confusion

709
00:39:48,120 --> 00:39:51,600
Speaker 1: about skinner boxes. The ones we typically recognize are the

710
00:39:51,719 --> 00:39:55,160
Speaker 1: metal boxes that he invented to test rats by giving

711
00:39:55,200 --> 00:39:58,759
Speaker 1: them rewards for training and operating conditioning in which any

712
00:39:58,840 --> 00:40:02,200
Speaker 1: behavior could be train using variable reinforcement, right, teaching a

713
00:40:02,239 --> 00:40:04,240
Speaker 1: bear how to dance, teaching a fish how to play soccer,

714
00:40:04,440 --> 00:40:06,120
Speaker 1: teaching a rat to you know, I don't know what

715
00:40:06,239 --> 00:40:08,200
Speaker 1: they were doing, like pushing panels and stuff like that.

716
00:40:09,600 --> 00:40:14,600
Speaker 1: Skinner also invented something called the air crib, which is

717
00:40:14,719 --> 00:40:18,320
Speaker 1: also sometimes referred to as a skinner box or a

718
00:40:18,480 --> 00:40:23,800
Speaker 1: baby tender. It sound like a chicken tender. Close, and

719
00:40:24,360 --> 00:40:26,480
Speaker 1: he put his daughter in it. It's true he did

720
00:40:26,560 --> 00:40:28,239
Speaker 1: put his daughter in this thing, but it was not

721
00:40:28,560 --> 00:40:31,800
Speaker 1: anything like what we commonly think of as skinner boxes.

722
00:40:31,840 --> 00:40:36,040
Speaker 1: So this is where my my high school teacher got confused. Uh.

723
00:40:36,320 --> 00:40:38,960
Speaker 1: It was a spacious compartment that was mounted on a

724
00:40:39,080 --> 00:40:42,120
Speaker 1: wheeled table, and it had a window in it and

725
00:40:42,360 --> 00:40:44,960
Speaker 1: temperature and air control, and you would put these babies

726
00:40:45,000 --> 00:40:48,319
Speaker 1: inside it and the baby could move freely around within

727
00:40:48,440 --> 00:40:51,399
Speaker 1: it while it's mother was within visual context. So, say

728
00:40:51,480 --> 00:40:54,120
Speaker 1: like the mother needed to go cook in the kitchen

729
00:40:54,239 --> 00:40:56,800
Speaker 1: or something like that, she couldn't constantly, you know, be

730
00:40:57,719 --> 00:40:59,840
Speaker 1: holding the baby while she was cooking. She put it

731
00:40:59,880 --> 00:41:03,879
Speaker 1: inside the baby tender wheel the baby tender over near

732
00:41:03,880 --> 00:41:05,759
Speaker 1: the kitchen, and she'd cook and kind of keep one

733
00:41:05,840 --> 00:41:09,240
Speaker 1: eye on the baby. Uh. This was Skinner's like solution.

734
00:41:09,320 --> 00:41:12,200
Speaker 1: It was specifically because his wife was like, they had

735
00:41:12,239 --> 00:41:14,479
Speaker 1: a second child, and his wife was like, oh my god,

736
00:41:14,560 --> 00:41:17,320
Speaker 1: it's so difficult to do all these things for the

737
00:41:17,440 --> 00:41:21,399
Speaker 1: first year of the baby's life. Okay, so other people

738
00:41:21,440 --> 00:41:24,600
Speaker 1: actually used this device like he. I think it was

739
00:41:24,640 --> 00:41:28,359
Speaker 1: commercially available, but it didn't really take off per se um.

740
00:41:28,719 --> 00:41:30,400
Speaker 1: There are a lot of critics of it though, and

741
00:41:30,520 --> 00:41:34,200
Speaker 1: they said that babies would be socially starved by being

742
00:41:34,239 --> 00:41:38,279
Speaker 1: put in these boxes. Skinner himself argued, that's not true.

743
00:41:38,600 --> 00:41:41,759
Speaker 1: The baby receives the same amount of attention, if not more,

744
00:41:42,000 --> 00:41:46,880
Speaker 1: inside of my baby tender slash aircrib. Wow. Yeah, so

745
00:41:47,320 --> 00:41:50,600
Speaker 1: another trivia question about Skinner. Do you know? Skinner wrote

746
00:41:50,680 --> 00:41:55,080
Speaker 1: like a utopian novel. Yeah, it's called Walden two. I

747
00:41:55,120 --> 00:41:57,400
Speaker 1: didn't know about this until I have heard about that

748
00:41:57,880 --> 00:41:59,799
Speaker 1: reading about this for the episode, and apparently it has

749
00:41:59,840 --> 00:42:03,919
Speaker 1: been the inspiration for some real like planned communities, something

750
00:42:04,000 --> 00:42:07,120
Speaker 1: that Peter Teal would be into. I don't know about him.

751
00:42:07,200 --> 00:42:09,400
Speaker 1: But no, actually no, I think it is not a

752
00:42:09,719 --> 00:42:13,759
Speaker 1: it's not a rapture libertarian right. Uh. No, it's more

753
00:42:13,840 --> 00:42:18,560
Speaker 1: like utopia. It is more like a thing where you

754
00:42:18,680 --> 00:42:22,320
Speaker 1: have it's essentially I think behaviorism put into practice. So

755
00:42:22,400 --> 00:42:25,759
Speaker 1: it's like top down control of culture in a way

756
00:42:25,880 --> 00:42:30,640
Speaker 1: that is maximizing people's you know, good tendencies or something

757
00:42:30,760 --> 00:42:33,120
Speaker 1: like that. I don't know that much about it, so

758
00:42:33,160 --> 00:42:34,600
Speaker 1: I can't speak about it. But he did write a

759
00:42:34,680 --> 00:42:37,920
Speaker 1: utopian novel, and as people going to this planned community

760
00:42:37,960 --> 00:42:40,040
Speaker 1: is sort of like a novel of ideas where people

761
00:42:40,120 --> 00:42:43,960
Speaker 1: like debate about things. Well, he was certainly a renaissance man.

762
00:42:44,080 --> 00:42:46,920
Speaker 1: I think we can say that about B. F. Skinner Um.

763
00:42:47,280 --> 00:42:50,839
Speaker 1: But just to clarify, hear all these rumors about him

764
00:42:50,880 --> 00:42:52,919
Speaker 1: putting his daughter in a skinner box, they're not true.

765
00:42:53,200 --> 00:42:56,400
Speaker 1: In fact, there were the rumors turned into urban myths

766
00:42:56,520 --> 00:42:59,200
Speaker 1: about him doing experiments on her and that she eventually

767
00:42:59,239 --> 00:43:02,000
Speaker 1: committed suice side because of her lack of social conditioning.

768
00:43:02,239 --> 00:43:04,279
Speaker 1: None of that is true. She went on to lead

769
00:43:04,320 --> 00:43:07,200
Speaker 1: a life and lived in London, I believe, um, But yeah,

770
00:43:07,280 --> 00:43:10,080
Speaker 1: I learned this in ap psych in high school. You know,

771
00:43:10,200 --> 00:43:12,680
Speaker 1: we we learned the basics of operat conditioning. And then

772
00:43:12,760 --> 00:43:15,319
Speaker 1: my teacher just told us that story, like oh yeah,

773
00:43:15,360 --> 00:43:17,279
Speaker 1: he even put his kit inside of skinner box and

774
00:43:17,360 --> 00:43:22,080
Speaker 1: I was like, anyways, uh, le's get back too, Yeah,

775
00:43:22,160 --> 00:43:24,320
Speaker 1: let's come back from this diversion. That was me just

776
00:43:24,400 --> 00:43:29,000
Speaker 1: sort of showing you the methodology of behavioral thinking. Yeah,

777
00:43:29,960 --> 00:43:32,000
Speaker 1: but so yeah, so we are. We're back to this

778
00:43:32,120 --> 00:43:34,920
Speaker 1: idea that the behaviorists, according to Daval, you know, he

779
00:43:35,000 --> 00:43:37,880
Speaker 1: made this charge that they treated all animals kind of

780
00:43:37,920 --> 00:43:41,520
Speaker 1: the same. They didn't want to think about instincts so much.

781
00:43:41,680 --> 00:43:43,800
Speaker 1: They didn't want to think about what was natural for

782
00:43:44,000 --> 00:43:47,080
Speaker 1: this animal in their environment, and it was all just conditioning.

783
00:43:47,200 --> 00:43:50,239
Speaker 1: You could apply the standing animal and that that's not

784
00:43:50,440 --> 00:43:54,480
Speaker 1: what Dvol is down with, right, and he especially hates

785
00:43:54,560 --> 00:43:57,279
Speaker 1: it to sort of the opposite side of this, when

786
00:43:57,360 --> 00:44:01,799
Speaker 1: people use the term non huge uman animals when they're

787
00:44:01,840 --> 00:44:04,800
Speaker 1: doing current research and you're grinning. I think you know

788
00:44:04,880 --> 00:44:07,319
Speaker 1: where I'm going with this here at how stuff works

789
00:44:07,400 --> 00:44:11,359
Speaker 1: when we write scripts for videos or sometimes for podcasts, uh,

790
00:44:11,520 --> 00:44:14,279
Speaker 1: talking about animal research. I don't know about you, but

791
00:44:14,400 --> 00:44:17,120
Speaker 1: some of our colleagues use the term non human animals.

792
00:44:17,160 --> 00:44:20,040
Speaker 1: I use the term, and uh, man, do we get

793
00:44:20,160 --> 00:44:22,840
Speaker 1: negative feedback about that? Like in the comments and stuff.

794
00:44:22,920 --> 00:44:26,320
Speaker 1: People really get rubbed the wrong way. And apparently the

795
00:44:26,440 --> 00:44:29,080
Speaker 1: vol also hates it. But I think for different reasons. Yeah,

796
00:44:29,160 --> 00:44:32,080
Speaker 1: I mean the idea. When I mean I use that term,

797
00:44:33,080 --> 00:44:37,080
Speaker 1: I'm just using it to say, like animals other than humans.

798
00:44:37,360 --> 00:44:39,800
Speaker 1: I think. I think his problem with it is that

799
00:44:40,920 --> 00:44:44,279
Speaker 1: in some ways that it's used, it implies that it's like, well,

800
00:44:44,520 --> 00:44:46,960
Speaker 1: there's humans and then there's all these other animals and

801
00:44:47,280 --> 00:44:50,759
Speaker 1: they're all fundamentally different. I'm just trying to use it pragmatically.

802
00:44:50,880 --> 00:44:53,000
Speaker 1: When I use it, I think to say, like research

803
00:44:53,080 --> 00:44:56,920
Speaker 1: on non human animals, meaning research on animals that aren't

804
00:44:56,960 --> 00:44:59,840
Speaker 1: Homo sapiens. Yeah, I tend to agree. He says that

805
00:44:59,880 --> 00:45:03,360
Speaker 1: the implies an absence of humanity within the animal kingdom,

806
00:45:03,440 --> 00:45:06,680
Speaker 1: which he's you know, he firmly wants to ground ground

807
00:45:06,960 --> 00:45:10,439
Speaker 1: us in thinking of ourselves as being animals and being

808
00:45:10,480 --> 00:45:13,720
Speaker 1: part of the animal kingdom. Uh. And so this leads

809
00:45:13,840 --> 00:45:16,239
Speaker 1: us to actually the naming of his other field, which

810
00:45:16,239 --> 00:45:18,800
Speaker 1: we're gonna get into later. But he says, really, what

811
00:45:18,920 --> 00:45:22,640
Speaker 1: we're talking about here now is evolutionary cognition, and this

812
00:45:22,800 --> 00:45:25,120
Speaker 1: is where we look at the world from the animal's

813
00:45:25,200 --> 00:45:29,640
Speaker 1: viewpoint the velt so we can appreciate their intelligence. And

814
00:45:29,800 --> 00:45:31,880
Speaker 1: this is where he comes up with that rule for

815
00:45:32,000 --> 00:45:35,440
Speaker 1: research that I was telling you about earlier, and probably

816
00:45:35,480 --> 00:45:38,880
Speaker 1: would apply this as well to your criticism of articles

817
00:45:38,960 --> 00:45:41,439
Speaker 1: that you read online or maybe on Facebook or something

818
00:45:41,520 --> 00:45:44,000
Speaker 1: like that. Okay, So he calls it to know thy

819
00:45:44,080 --> 00:45:47,240
Speaker 1: Animal rule, and he says, anyone who wishes to stress

820
00:45:47,280 --> 00:45:51,319
Speaker 1: an alternative claim about an animal's cognitive capacities either needs

821
00:45:51,360 --> 00:45:55,360
Speaker 1: to familiarize him or herself with the species in question

822
00:45:55,920 --> 00:45:58,480
Speaker 1: or make a genuine effort to back his or her

823
00:45:58,560 --> 00:46:02,760
Speaker 1: counterclaim with data. And then he says, anyone who intends

824
00:46:02,800 --> 00:46:06,600
Speaker 1: to conduct experiments on animal cognitions should first spend a

825
00:46:06,719 --> 00:46:11,200
Speaker 1: couple thousand hours observing the spontaneous behavior of the species

826
00:46:11,239 --> 00:46:14,000
Speaker 1: in question. Now this is interesting because a lot of

827
00:46:14,040 --> 00:46:15,640
Speaker 1: people would say, like, wait a minute, why do I

828
00:46:15,719 --> 00:46:17,800
Speaker 1: need to study that I mean, in many cases, what

829
00:46:17,960 --> 00:46:22,319
Speaker 1: you'd want is somebody who dispassionately observes an animal, uh

830
00:46:22,680 --> 00:46:25,400
Speaker 1: with you know, with a little baggage as possible, to

831
00:46:25,520 --> 00:46:28,920
Speaker 1: just come in and strictly observed behaviors in the test environment.

832
00:46:29,880 --> 00:46:31,600
Speaker 1: And there's some truth to that. I mean, you don't

833
00:46:31,640 --> 00:46:34,520
Speaker 1: want to let your biases and your feelings about an

834
00:46:34,520 --> 00:46:37,760
Speaker 1: animal guide what kind of observations you make in a test.

835
00:46:38,440 --> 00:46:42,120
Speaker 1: But at the same time, when you're designing a test

836
00:46:42,360 --> 00:46:46,720
Speaker 1: of animal intelligence, if you don't totally understand that animal

837
00:46:46,800 --> 00:46:51,040
Speaker 1: and how it naturally behaves, you're very likely overlooking something

838
00:46:51,160 --> 00:46:55,040
Speaker 1: absolutely crucial that could change the way your tests should

839
00:46:55,080 --> 00:46:57,520
Speaker 1: work or how to interpret your results. Going back to

840
00:46:57,600 --> 00:47:01,279
Speaker 1: the bird example, knowing that these birds live in such

841
00:47:01,360 --> 00:47:05,280
Speaker 1: a high, out of reach places, why would they possibly

842
00:47:05,440 --> 00:47:09,239
Speaker 1: care if another bird of the same species fell into

843
00:47:09,280 --> 00:47:11,680
Speaker 1: their nest? Right? Yeah, And this is another theme that

844
00:47:11,800 --> 00:47:15,480
Speaker 1: comes up, the idea of observing animals in their natural behaviors,

845
00:47:15,520 --> 00:47:19,399
Speaker 1: in their natural habitats um. This comes up I think

846
00:47:19,640 --> 00:47:21,960
Speaker 1: in the the idea of like, okay, so how should

847
00:47:22,000 --> 00:47:25,560
Speaker 1: we do science with respect to the idea of anecdotes?

848
00:47:25,840 --> 00:47:28,200
Speaker 1: This is a disgust A lot of the book it's

849
00:47:28,200 --> 00:47:32,040
Speaker 1: another conflict between two different desiderata in in getting the

850
00:47:32,120 --> 00:47:36,239
Speaker 1: best scientific view of an animal. So one thing would

851
00:47:36,239 --> 00:47:38,880
Speaker 1: be that we don't want to just have our scientific

852
00:47:39,400 --> 00:47:43,879
Speaker 1: ideas about animals completely informed by anecdotes where somebody says, hey,

853
00:47:44,000 --> 00:47:47,600
Speaker 1: one time I saw a chimpanzee do X right, well,

854
00:47:47,680 --> 00:47:49,920
Speaker 1: and that that's going back to our example from the

855
00:47:50,000 --> 00:47:54,400
Speaker 1: beginning of the episode. You and I have experienced anecdotal

856
00:47:54,480 --> 00:47:58,120
Speaker 1: experiences with our dogs, right, but they're not under laboratory conditions, right,

857
00:47:58,200 --> 00:48:01,400
Speaker 1: So you have anecdotal rances. But then again, on the

858
00:48:01,480 --> 00:48:04,040
Speaker 1: other side, you could have this mentality that says, well,

859
00:48:04,120 --> 00:48:07,759
Speaker 1: I'm not interested in anecdotes about what animals have done

860
00:48:07,800 --> 00:48:09,560
Speaker 1: in the wild. You know, you may have been observing

861
00:48:09,640 --> 00:48:11,880
Speaker 1: chimpanzees in the wild and you think you saw them

862
00:48:12,000 --> 00:48:14,880
Speaker 1: do something once that indicates a certain type of cognition.

863
00:48:15,400 --> 00:48:17,920
Speaker 1: You may have seen them do something that you think

864
00:48:17,960 --> 00:48:20,919
Speaker 1: indicates that they understand how other minds work, or something

865
00:48:21,040 --> 00:48:23,719
Speaker 1: like that. But that's just a story you have that's

866
00:48:23,760 --> 00:48:27,800
Speaker 1: not like something that we have repeatedly tested. There's validity

867
00:48:27,880 --> 00:48:30,520
Speaker 1: to that point of view, but only to a certain extent.

868
00:48:30,760 --> 00:48:34,759
Speaker 1: And duval Uh doesn't think that anecdotes should comprise our

869
00:48:34,800 --> 00:48:37,800
Speaker 1: scientific knowledge, but he does strongly think that they should

870
00:48:37,880 --> 00:48:42,040
Speaker 1: inspire our scientific exploration. Yeah, he sees value to them. Yeah,

871
00:48:42,120 --> 00:48:45,560
Speaker 1: So you start with an anecdote. You observe animals, for example,

872
00:48:45,760 --> 00:48:49,239
Speaker 1: in their wild behavior, and you see one do something interesting,

873
00:48:49,719 --> 00:48:53,880
Speaker 1: and that observation of one doing something unexpected or interesting

874
00:48:54,000 --> 00:48:57,839
Speaker 1: forms the basis of a controlled test. You say, Okay, now,

875
00:48:57,880 --> 00:49:00,120
Speaker 1: I wonder if we can isolate the variables he or

876
00:49:00,160 --> 00:49:02,560
Speaker 1: and get them to do the same thing. So let's

877
00:49:02,640 --> 00:49:06,000
Speaker 1: bring that around to one of my favorite lines in

878
00:49:06,080 --> 00:49:08,279
Speaker 1: the book. This is this is I laughed out loud

879
00:49:08,360 --> 00:49:12,200
Speaker 1: at this. Okay, he said, would anyone test the memory

880
00:49:12,400 --> 00:49:15,960
Speaker 1: of human children by throwing them into a swimming pool

881
00:49:16,080 --> 00:49:18,120
Speaker 1: to see if they could remember where to get out?

882
00:49:19,680 --> 00:49:22,040
Speaker 1: And he's using this example because this is actually how

883
00:49:22,120 --> 00:49:24,960
Speaker 1: many rats are tested with with what is called Morris's

884
00:49:25,040 --> 00:49:27,960
Speaker 1: water maze, right, to see if the rats can figure

885
00:49:28,000 --> 00:49:31,400
Speaker 1: it out? So would we? I mean I immediately was like,

886
00:49:31,520 --> 00:49:35,440
Speaker 1: this is like a perfect example of humor at work, right,

887
00:49:35,520 --> 00:49:38,279
Speaker 1: Like the idea of taking something as taboo is just

888
00:49:38,360 --> 00:49:42,040
Speaker 1: throwing a child into a pool. But then it's it's

889
00:49:42,080 --> 00:49:45,000
Speaker 1: along the lines of what we're doing it for research, right,

890
00:49:45,080 --> 00:49:47,840
Speaker 1: and the babies somehow kind of figure out how to

891
00:49:48,000 --> 00:49:50,520
Speaker 1: climb out of the pool. It's the same kind of

892
00:49:50,600 --> 00:49:53,200
Speaker 1: thing he says about the rats. Well, like, how many

893
00:49:53,280 --> 00:49:56,200
Speaker 1: situations would these rats be in where they just get

894
00:49:56,280 --> 00:49:58,840
Speaker 1: thrown into a pool. Let's see, I can think of

895
00:49:58,880 --> 00:50:01,040
Speaker 1: lots of scenes in movie Is where they're like surging

896
00:50:01,080 --> 00:50:04,440
Speaker 1: currents of water with rats in them. Yeah, there's like

897
00:50:04,560 --> 00:50:06,919
Speaker 1: one in the Indiana Jones in the Last Crusade. There's

898
00:50:06,920 --> 00:50:08,839
Speaker 1: like a rat flood in there, and that's not really

899
00:50:08,880 --> 00:50:15,320
Speaker 1: their natural habitat though. Right. Another thing he says to

900
00:50:15,440 --> 00:50:17,680
Speaker 1: keep in mind about most labs, and I didn't know this,

901
00:50:19,080 --> 00:50:22,600
Speaker 1: is that most labs keep their test animals at eight

902
00:50:23,520 --> 00:50:26,040
Speaker 1: of their typical body weight. And this is so that

903
00:50:26,120 --> 00:50:29,520
Speaker 1: they'll be more motivated by food as a reward. Yeah,

904
00:50:29,600 --> 00:50:31,839
Speaker 1: but this could also go the other way. I mean,

905
00:50:31,920 --> 00:50:35,600
Speaker 1: it could also be causing problems for test results, because

906
00:50:35,680 --> 00:50:38,799
Speaker 1: what if animals don't behave the way they normally would

907
00:50:38,960 --> 00:50:41,880
Speaker 1: be if they're hungry. Yeah. It was criticized by the

908
00:50:41,920 --> 00:50:45,200
Speaker 1: well known primatologist Harry Harlow actually, and he argued that

909
00:50:45,320 --> 00:50:50,520
Speaker 1: animals learn from curiosity and free exploration. Uh, and that

910
00:50:50,560 --> 00:50:54,400
Speaker 1: would be stifled by making them fixated on food. Yeah. So,

911
00:50:55,719 --> 00:50:59,359
Speaker 1: but basically, what we're looking at is a variation on intelligence.

912
00:50:59,400 --> 00:51:03,720
Speaker 1: We're not looking different topics of intelligence. So Duval argues

913
00:51:03,800 --> 00:51:07,239
Speaker 1: that if we fail to find cognitive capacity in a species,

914
00:51:07,840 --> 00:51:10,920
Speaker 1: well there's something wrong in our approach as human beings,

915
00:51:11,040 --> 00:51:14,799
Speaker 1: not with the actual species itself. Right. So, going back

916
00:51:14,840 --> 00:51:19,000
Speaker 1: to the crab example, you know, uh, we haven't come

917
00:51:19,080 --> 00:51:22,040
Speaker 1: up with an approach yet to quite understand what's going

918
00:51:22,200 --> 00:51:25,200
Speaker 1: on with the crabs that are ripping these anemones apart

919
00:51:25,280 --> 00:51:27,840
Speaker 1: and using them as a two handed weapons. You know,

920
00:51:29,120 --> 00:51:31,319
Speaker 1: I don't know what that approach would be. I need

921
00:51:31,400 --> 00:51:33,560
Speaker 1: to spend a couple of thousand hours with these crabs

922
00:51:33,800 --> 00:51:35,600
Speaker 1: before I could do that. I guess it could be.

923
00:51:35,719 --> 00:51:39,120
Speaker 1: I mean, a way of testing what kind of thing

924
00:51:39,239 --> 00:51:41,000
Speaker 1: leads to this would be trying to put them in

925
00:51:41,120 --> 00:51:45,120
Speaker 1: situations where they could, uh, where they could create new

926
00:51:45,520 --> 00:51:48,880
Speaker 1: advantages of tool use that might be similar but wouldn't

927
00:51:48,880 --> 00:51:51,440
Speaker 1: necessarily play on the same instincts if it is instinct

928
00:51:51,560 --> 00:51:55,239
Speaker 1: driven uh. And then he says the challenge is to

929
00:51:55,360 --> 00:51:59,920
Speaker 1: find tests that fit an animal's temperament, their interests, at

930
00:52:00,000 --> 00:52:04,799
Speaker 1: anatomy and sensory capacities. Faced with negative outcomes, we need

931
00:52:04,880 --> 00:52:09,040
Speaker 1: to pay close attention to differences in motivation and attention.

932
00:52:09,120 --> 00:52:11,680
Speaker 1: He's referring to the animals here. All right, we need

933
00:52:11,719 --> 00:52:13,439
Speaker 1: to take a quick break and when we come back

934
00:52:13,560 --> 00:52:22,120
Speaker 1: there will be more on animal intelligence and cognition. Okay,

935
00:52:22,200 --> 00:52:25,640
Speaker 1: So counter to this behaviorist mode of thinking that has

936
00:52:25,680 --> 00:52:30,080
Speaker 1: really dominated our thought about animal intelligence for at least

937
00:52:30,120 --> 00:52:34,920
Speaker 1: a century or more, uh Duval talks about the discipline

938
00:52:34,960 --> 00:52:39,040
Speaker 1: of ethology. Ethology the study of animal behavior, but specifically,

939
00:52:39,360 --> 00:52:42,920
Speaker 1: uh sort of instinctual animal behavior that is common to

940
00:52:43,160 --> 00:52:46,200
Speaker 1: all of the members of a species. Yeah, he refers

941
00:52:46,200 --> 00:52:49,920
Speaker 1: to it as being about spontaneous behavior. So going back

942
00:52:50,000 --> 00:52:54,520
Speaker 1: to our examples from the beginning, right, it's more instinctual. Um. So,

943
00:52:54,640 --> 00:52:57,080
Speaker 1: I have a question for you and and maybe for

944
00:52:57,200 --> 00:53:01,160
Speaker 1: del I'm a little confused here. Did this spin out

945
00:53:01,280 --> 00:53:05,680
Speaker 1: of evolutionary theory from Darwin? Uh? Well, yeah, I would

946
00:53:05,680 --> 00:53:08,160
Speaker 1: think so. I mean it seemed like it, but I

947
00:53:08,200 --> 00:53:13,040
Speaker 1: couldn't draw a direct line. I mean, all all modern

948
00:53:13,120 --> 00:53:16,600
Speaker 1: biological theories are in some way rooted in in the

949
00:53:16,719 --> 00:53:20,799
Speaker 1: modern synthesis of evolution. But you, I guess you could

950
00:53:20,800 --> 00:53:24,040
Speaker 1: say that this is very specifically based on thinking about

951
00:53:24,520 --> 00:53:28,759
Speaker 1: how behaviors are evolved traits, because I guess with behaviorism

952
00:53:28,800 --> 00:53:31,680
Speaker 1: you would say that the capacity to learn is an

953
00:53:31,719 --> 00:53:34,200
Speaker 1: evolved trade. But that can just be applied to anything

954
00:53:34,560 --> 00:53:39,840
Speaker 1: I asked, because you know, evolutionary theory predicts cognitive similarities

955
00:53:39,880 --> 00:53:43,040
Speaker 1: based on the relations between a species and their habitat.

956
00:53:43,440 --> 00:53:47,239
Speaker 1: It sounds like velt to me. Uh so, okay, yeah,

957
00:53:47,320 --> 00:53:49,520
Speaker 1: we're we're shaped by our environments and so yeah, our

958
00:53:49,560 --> 00:53:53,440
Speaker 1: behaviors are shaped by our environments. Well, ethology actually started

959
00:53:53,480 --> 00:53:56,440
Speaker 1: in the eighteenth century, and that it was started by

960
00:53:56,600 --> 00:53:59,640
Speaker 1: French researchers and they used the term ethos, which you

961
00:53:59,760 --> 00:54:01,640
Speaker 1: probably heard me throw around on the show a lot

962
00:54:02,280 --> 00:54:06,719
Speaker 1: because of my background in rhetorical theory. But ethos is

963
00:54:06,840 --> 00:54:09,800
Speaker 1: the Greek word for character, and they used that to

964
00:54:10,000 --> 00:54:16,000
Speaker 1: describe species typical characteristics. Now, William Morton Wheeler is the

965
00:54:16,040 --> 00:54:19,320
Speaker 1: guy who made it popular in English speaking study. This

966
00:54:19,480 --> 00:54:21,920
Speaker 1: was in nineteen o two, and he called it a

967
00:54:22,080 --> 00:54:27,600
Speaker 1: study of habits and instincts. Uh So, ethology, you know,

968
00:54:27,680 --> 00:54:29,600
Speaker 1: without diving too deep into this, well, it has its

969
00:54:29,640 --> 00:54:34,000
Speaker 1: own language to talk about instincts, stereotypical behaviors, stimuli that

970
00:54:34,040 --> 00:54:38,520
Speaker 1: illicit specific behaviors, etcetera. Similar things to behaviorism. Now, the

971
00:54:38,680 --> 00:54:43,439
Speaker 1: two people that that Devol really mentions heavily in his book,

972
00:54:43,760 --> 00:54:48,040
Speaker 1: and I gather are inspirations for his own work, our

973
00:54:48,200 --> 00:54:52,600
Speaker 1: Lorenz and tin Bergen Uh And they were partners within

974
00:54:52,719 --> 00:54:57,160
Speaker 1: this discipline. They were actually separated by opposite sides during

975
00:54:57,239 --> 00:55:00,160
Speaker 1: World War Two. Just fascinating. One of them was what

976
00:55:00,280 --> 00:55:03,480
Speaker 1: like a medic for Nazi Germany, and the other one

977
00:55:04,000 --> 00:55:07,319
Speaker 1: was where was it in the Netherlands. I don't think

978
00:55:07,360 --> 00:55:11,560
Speaker 1: he was in the Netherlands anyways. It's fascinating they knew

979
00:55:11,600 --> 00:55:13,600
Speaker 1: each other before this, they were separated by the war,

980
00:55:13,719 --> 00:55:16,359
Speaker 1: and then afterwards they got over their differences and work

981
00:55:16,440 --> 00:55:19,359
Speaker 1: together again. It's really fascinating. He this is a great

982
00:55:19,440 --> 00:55:20,960
Speaker 1: part of the book where he just goes into this

983
00:55:21,120 --> 00:55:23,880
Speaker 1: history between these two guys and and kind of how

984
00:55:24,000 --> 00:55:31,000
Speaker 1: they've inspired an entire generation of people who study animal intelligence. Yeah. Now,

985
00:55:31,080 --> 00:55:37,440
Speaker 1: he says, mythologists are usually zoologists, while behaviorists are usually psychologists.

986
00:55:37,600 --> 00:55:39,120
Speaker 1: That makes a lot of sense to me. I mean,

987
00:55:39,200 --> 00:55:41,719
Speaker 1: if you're an mythologist and you're trying to understand an

988
00:55:41,760 --> 00:55:45,120
Speaker 1: animal's role in its environment, you're thinking about the animal

989
00:55:45,200 --> 00:55:50,640
Speaker 1: itself and how that informs potential behavior, and thinking if

990
00:55:50,719 --> 00:55:54,279
Speaker 1: you're if you are a behaviorist, like the animal is

991
00:55:54,320 --> 00:55:57,279
Speaker 1: almost incidental. You're just thinking about the animal is a

992
00:55:57,400 --> 00:56:01,759
Speaker 1: substrate for behavior, and any animal really could be a

993
00:56:01,840 --> 00:56:06,239
Speaker 1: substrate for behavior. And I wonder if, uh, you know,

994
00:56:06,400 --> 00:56:09,200
Speaker 1: as we're moving along towards a sort of chronological history

995
00:56:09,239 --> 00:56:12,839
Speaker 1: of this of this discipline, if as they're coming together more,

996
00:56:13,360 --> 00:56:17,040
Speaker 1: if we're seeing a blend of zoology and psychology, you know, yeah,

997
00:56:17,080 --> 00:56:20,000
Speaker 1: I think so. I mean this division as he'll, as

998
00:56:20,160 --> 00:56:22,799
Speaker 1: ud All talks about in the book, is it's less

999
00:56:22,840 --> 00:56:25,120
Speaker 1: of a division today and it's more of a synthesis.

1000
00:56:25,760 --> 00:56:29,759
Speaker 1: So both ethology and behaviorism were actually a reaction to

1001
00:56:30,200 --> 00:56:33,920
Speaker 1: what we're folk explanation of animals, right, just kind of

1002
00:56:34,960 --> 00:56:37,879
Speaker 1: I guess what we would call urban myths today, right,

1003
00:56:38,480 --> 00:56:40,799
Speaker 1: or even people who you know might have been thought

1004
00:56:40,840 --> 00:56:43,400
Speaker 1: of as scientists of the time, but we're sort of

1005
00:56:43,480 --> 00:56:47,640
Speaker 1: being scientists by anecdote, like not super rigorous scientists saying

1006
00:56:47,719 --> 00:56:50,960
Speaker 1: like I once saw you know, bird do this, this

1007
00:56:51,120 --> 00:56:53,000
Speaker 1: is what birds can do well. Actually he gives a

1008
00:56:53,120 --> 00:56:56,480
Speaker 1: very good example of this, uh, and he blames it

1009
00:56:56,560 --> 00:56:59,919
Speaker 1: all on the guy who followed Darwin, who Darwin chose

1010
00:57:00,080 --> 00:57:04,440
Speaker 1: to be like his successor in this theory of evolution. Uh.

1011
00:57:04,560 --> 00:57:07,880
Speaker 1: And a lot of misinformation came out of scientific anecdotes

1012
00:57:07,920 --> 00:57:10,440
Speaker 1: like you're talking about. The guy's name was George Romanez

1013
00:57:10,600 --> 00:57:12,759
Speaker 1: I believe is how you pronounce it, uh, And he

1014
00:57:12,840 --> 00:57:14,800
Speaker 1: was a perpetrator of this. Here are two things that

1015
00:57:14,920 --> 00:57:19,000
Speaker 1: he said. He said that rats would form supply lines

1016
00:57:19,600 --> 00:57:23,200
Speaker 1: to hand down stolen eggs from like a you know,

1017
00:57:23,360 --> 00:57:26,720
Speaker 1: either like a farm or like just a chicken's nest,

1018
00:57:27,400 --> 00:57:29,640
Speaker 1: that they would pass these eggs down to their holes.

1019
00:57:29,920 --> 00:57:32,200
Speaker 1: This sounds like a Disney cartoon to me, like the

1020
00:57:32,360 --> 00:57:36,200
Speaker 1: idea of them, like they're in a little like assembly line, right,

1021
00:57:36,200 --> 00:57:38,080
Speaker 1: and they're just passing the egg back and forth, singing

1022
00:57:38,120 --> 00:57:40,640
Speaker 1: a song or something. Uh. And then the other one,

1023
00:57:40,880 --> 00:57:44,800
Speaker 1: this one's nuts. Uh. He told the story about a

1024
00:57:44,960 --> 00:57:48,120
Speaker 1: monkey that was hit by a hunter's bullet and then

1025
00:57:48,160 --> 00:57:51,800
Speaker 1: the monkey smeared the blood on its hand and held

1026
00:57:51,920 --> 00:57:54,600
Speaker 1: that hand, the bloody hand up to the hunter to

1027
00:57:54,800 --> 00:57:58,680
Speaker 1: make the hunter feel guilty. Now, even as somebody who

1028
00:57:59,000 --> 00:58:03,160
Speaker 1: is uh sympathetic to the idea of complex animal cognition,

1029
00:58:03,320 --> 00:58:05,840
Speaker 1: that seems like a stretch. How do you know even

1030
00:58:05,920 --> 00:58:08,440
Speaker 1: if that's really what happened, how do you know the

1031
00:58:08,640 --> 00:58:11,400
Speaker 1: ape was trying to make the hunter feel guilty. That

1032
00:58:11,440 --> 00:58:16,280
Speaker 1: seems a little crazy, right yeah? Um So. Romanez subsequently

1033
00:58:16,400 --> 00:58:19,840
Speaker 1: led to a guy named Lloyd Morgan, and Morgan had

1034
00:58:19,840 --> 00:58:23,440
Speaker 1: an interpretation that animals are mainly stimulus response machine. So

1035
00:58:23,560 --> 00:58:28,160
Speaker 1: that's basically how we got to that behaviorist thinking because

1036
00:58:28,200 --> 00:58:31,000
Speaker 1: of this this one guy who kind of just went rogue,

1037
00:58:31,720 --> 00:58:34,800
Speaker 1: and then there was a response within the discipline to him.

1038
00:58:35,120 --> 00:58:38,160
Speaker 1: Another example is a great story and I had heard

1039
00:58:38,240 --> 00:58:41,600
Speaker 1: this story before reading the book, but it's a wonderful story.

1040
00:58:41,920 --> 00:58:44,959
Speaker 1: The story of Clever Hans, Right, the horse, Clever Hans

1041
00:58:45,000 --> 00:58:47,560
Speaker 1: who could do he was a math genius. Yes. The

1042
00:58:47,680 --> 00:58:51,880
Speaker 1: idea here was that apparently Hans would literally be trotted

1043
00:58:51,880 --> 00:58:56,480
Speaker 1: out to crowds and his owner would ask it to

1044
00:58:56,560 --> 00:59:01,520
Speaker 1: perform math problems and it would get that answer right, clump,

1045
00:59:01,600 --> 00:59:04,920
Speaker 1: it's hoof. I think to count off a number, that

1046
00:59:04,960 --> 00:59:08,000
Speaker 1: would be the answer, and everybody's like, wow, this horse,

1047
00:59:08,120 --> 00:59:10,840
Speaker 1: it's got an amazing brain. It can do square roots.

1048
00:59:11,240 --> 00:59:14,280
Speaker 1: Can a horse do that? Yeah? Exactly? And they figured

1049
00:59:14,320 --> 00:59:17,520
Speaker 1: out that it was actually through conditioning right that the

1050
00:59:17,920 --> 00:59:21,000
Speaker 1: horse was. Probably what they think happened was the horse

1051
00:59:21,120 --> 00:59:24,720
Speaker 1: was responding to cues from its owner, so it would

1052
00:59:24,720 --> 00:59:28,080
Speaker 1: start clumping a number, and then the when owner got

1053
00:59:28,160 --> 00:59:29,720
Speaker 1: to the when it got to the right one, he

1054
00:59:29,760 --> 00:59:32,959
Speaker 1: would be like, ah, yes, yeah. The owner would show

1055
00:59:33,280 --> 00:59:36,840
Speaker 1: like either positive body language or I think they said

1056
00:59:36,880 --> 00:59:39,160
Speaker 1: something about a hat with a big brim. Yes, he

1057
00:59:39,200 --> 00:59:40,920
Speaker 1: would he had a hat with a brim that he

1058
00:59:40,960 --> 00:59:43,080
Speaker 1: would be looking down at the horse's hoof while the

1059
00:59:43,120 --> 00:59:45,240
Speaker 1: hoof was tapping, and then when it got to the

1060
00:59:45,320 --> 00:59:47,840
Speaker 1: right number, he would stop looking at the hoof and

1061
00:59:48,080 --> 00:59:51,200
Speaker 1: lift his head up, so the horse would subsequently stop.

1062
00:59:52,000 --> 00:59:54,040
Speaker 1: That was what was going on, basically to the point

1063
00:59:54,120 --> 00:59:56,120
Speaker 1: where when this was revealed, it wasn't like the owner

1064
00:59:56,240 --> 00:59:59,480
Speaker 1: was duplicitous and like trying to trick everybody. He himself

1065
00:59:59,560 --> 01:00:03,160
Speaker 1: thought the this horse this yeah, and but this serves

1066
01:00:03,280 --> 01:00:06,600
Speaker 1: as a great cautionary tale about about these kind of

1067
01:00:06,920 --> 01:00:10,280
Speaker 1: anecdotes where we attribute to we're too credulous, we attribute

1068
01:00:10,320 --> 01:00:15,320
Speaker 1: too much cognition too readily to animals without being scientifically rigorous.

1069
01:00:16,440 --> 01:00:20,000
Speaker 1: This actually led us to using blind studies with animals

1070
01:00:20,160 --> 01:00:23,000
Speaker 1: because they because of the whole clever Hans incident, and

1071
01:00:23,120 --> 01:00:26,720
Speaker 1: Duval actually argues he says, you know, it's interesting, though

1072
01:00:27,040 --> 01:00:28,840
Speaker 1: we don't do the same thing when we test the

1073
01:00:28,880 --> 01:00:31,920
Speaker 1: cognition of human children. Though there's a whole section about

1074
01:00:31,960 --> 01:00:35,960
Speaker 1: this in the book Improper Analogies Between They're all these

1075
01:00:36,040 --> 01:00:38,520
Speaker 1: tests that try to say, oh, is a chimpanzee smarter

1076
01:00:38,680 --> 01:00:41,760
Speaker 1: than a three year old child? Is a chimpanzee smarter

1077
01:00:41,840 --> 01:00:45,520
Speaker 1: than a five year old child in different domains of knowledge? Um,

1078
01:00:45,840 --> 01:00:48,880
Speaker 1: but a very common problem with this is the the

1079
01:00:49,040 --> 01:00:51,640
Speaker 1: chimpanzee and the child, the human child are just not

1080
01:00:51,960 --> 01:00:54,960
Speaker 1: on an equal playing field in terms of test environments.

1081
01:00:55,400 --> 01:00:58,520
Speaker 1: Children are surrounded by members of their own species. They're

1082
01:00:58,560 --> 01:01:01,520
Speaker 1: probably much more at ease and comfortable, maybe with their

1083
01:01:01,560 --> 01:01:04,680
Speaker 1: parents in the room. Uh. They're just all kinds of

1084
01:01:04,760 --> 01:01:09,080
Speaker 1: ways in which these testing scenarios are not equivalent, and

1085
01:01:09,200 --> 01:01:11,720
Speaker 1: yet there the results are being treated as if they're

1086
01:01:11,760 --> 01:01:14,480
Speaker 1: done across an even playing field. Yeah. Like his example

1087
01:01:14,640 --> 01:01:16,360
Speaker 1: is in the same way that we wouldn't have clever

1088
01:01:16,520 --> 01:01:19,720
Speaker 1: Hans being a room with his owner and his brimmed hat,

1089
01:01:20,320 --> 01:01:23,040
Speaker 1: we shouldn't necessarily have these children be in the same

1090
01:01:23,120 --> 01:01:25,439
Speaker 1: room as their mothers. Like they're literally testing these children

1091
01:01:25,480 --> 01:01:28,160
Speaker 1: while they're in their mother's laps. So it's interesting he

1092
01:01:28,200 --> 01:01:32,840
Speaker 1: points out the contradiction there. Now these two schools finally

1093
01:01:32,960 --> 01:01:36,120
Speaker 1: come together, and I think this is where we're gonna

1094
01:01:36,160 --> 01:01:40,640
Speaker 1: cap off this episode. But basically, behaviorists and mythologists started

1095
01:01:40,680 --> 01:01:44,000
Speaker 1: working together in nineteen fifty three, and this is when

1096
01:01:44,120 --> 01:01:48,320
Speaker 1: Daniel Lerman and Tim Bergen started a friendship, and it

1097
01:01:48,480 --> 01:01:52,840
Speaker 1: started ongoing criticism not of each other's camps, but within

1098
01:01:53,200 --> 01:01:56,439
Speaker 1: each camp of its own tenants. And I think each

1099
01:01:56,640 --> 01:01:59,560
Speaker 1: each camp obviously had legitimate things to say about the

1100
01:01:59,640 --> 01:02:01,919
Speaker 1: other one, right, I mean today, if you would try

1101
01:02:01,960 --> 01:02:04,640
Speaker 1: to if you try to be a chauvinist about you know,

1102
01:02:04,840 --> 01:02:07,720
Speaker 1: it's it's all instinct or it's all learned behavior. I mean,

1103
01:02:07,760 --> 01:02:10,000
Speaker 1: I think either of those positions is silly today. I mean,

1104
01:02:10,160 --> 01:02:15,280
Speaker 1: obviously animal behaviors or combinations of instincts and learned behaviors.

1105
01:02:15,400 --> 01:02:17,280
Speaker 1: As we outlined at the beginning, it's like saying that

1106
01:02:17,360 --> 01:02:20,040
Speaker 1: it's only nature, it's only nurture. Try to use a

1107
01:02:20,080 --> 01:02:23,040
Speaker 1: little bit of both, right. But then also this leaves

1108
01:02:23,080 --> 01:02:25,520
Speaker 1: the question, even even if you're you're talking about an

1109
01:02:25,560 --> 01:02:28,480
Speaker 1: acknowledgement of the influence of both these things, there is

1110
01:02:28,520 --> 01:02:32,080
Speaker 1: still the question, what's the role of complex cognition, what's

1111
01:02:32,120 --> 01:02:35,760
Speaker 1: the role of thinking. Well, let's get to that in

1112
01:02:35,840 --> 01:02:40,640
Speaker 1: our next episode. We've basically covered the gamut of where

1113
01:02:40,720 --> 01:02:44,520
Speaker 1: the discipline of looking at animal intelligence was, but we're

1114
01:02:44,520 --> 01:02:48,080
Speaker 1: gonna look forward in another episode to talking about where

1115
01:02:48,160 --> 01:02:51,480
Speaker 1: it is and where it's going. Now, my question for

1116
01:02:51,600 --> 01:02:54,320
Speaker 1: you out there you're listening to this, maybe you have pets,

1117
01:02:54,360 --> 01:02:58,480
Speaker 1: Maybe you've interact with animals in various capacities, cows. Maybe.

1118
01:02:58,680 --> 01:03:00,440
Speaker 1: We had a lot of people right into us recently

1119
01:03:00,560 --> 01:03:03,200
Speaker 1: about our butter episode with the cow with the window

1120
01:03:03,280 --> 01:03:05,560
Speaker 1: in it. Yeah, exactly, the cow with the window in it,

1121
01:03:05,600 --> 01:03:07,600
Speaker 1: because I mentioned that in the episode, and a lot

1122
01:03:07,600 --> 01:03:10,160
Speaker 1: of people who had worked with them before. So have

1123
01:03:10,480 --> 01:03:14,640
Speaker 1: you seen, uh, your own versions of this play out

1124
01:03:14,760 --> 01:03:17,120
Speaker 1: with animals. Have you seen what you think of as

1125
01:03:17,200 --> 01:03:20,200
Speaker 1: only instinctual responses with these animals, or maybe have you

1126
01:03:20,280 --> 01:03:24,000
Speaker 1: seen examples of them learning from conditioning, like giving them

1127
01:03:24,080 --> 01:03:26,320
Speaker 1: treats for instance, to make your dogs sit down, which

1128
01:03:26,400 --> 01:03:28,320
Speaker 1: is something I'm working on with my dogs right now.

1129
01:03:28,920 --> 01:03:31,080
Speaker 1: Let us know, there's a lot of different ways to

1130
01:03:31,080 --> 01:03:33,240
Speaker 1: get in touch with us. We're on social media all

1131
01:03:33,320 --> 01:03:36,640
Speaker 1: over the place you can find us on Facebook, Twitter, Tumbler.

1132
01:03:37,080 --> 01:03:39,640
Speaker 1: We are also on Instagram, although I don't know that

1133
01:03:39,720 --> 01:03:42,040
Speaker 1: that's the best way to ask questions. But you can

1134
01:03:42,080 --> 01:03:45,560
Speaker 1: look at very pretty pictures of us. Uh. And what

1135
01:03:45,600 --> 01:03:47,640
Speaker 1: about stuff to blow your mind dot com? Well, of

1136
01:03:47,720 --> 01:03:52,040
Speaker 1: course that's our website where you can find blog posts, articles, videos,

1137
01:03:52,200 --> 01:03:56,000
Speaker 1: other past podcasts, and our vast archive with some more

1138
01:03:56,080 --> 01:03:59,200
Speaker 1: pretty pictures. Probably, yeah, there are lots of pretty pictures.

1139
01:03:59,360 --> 01:04:01,480
Speaker 1: You know what. Robert Lamb isn't in the room with

1140
01:04:01,600 --> 01:04:03,560
Speaker 1: us right now, so let's just honor him by saying,

1141
01:04:04,080 --> 01:04:07,880
Speaker 1: Robert Lamb has a singular talent for finding the best

1142
01:04:08,000 --> 01:04:11,320
Speaker 1: possible image to go along with the podcast episode. I

1143
01:04:11,400 --> 01:04:13,880
Speaker 1: am very good at our selection. Yeah, he's so good

1144
01:04:13,960 --> 01:04:17,080
Speaker 1: at it. I'm always surprised at the images that he's

1145
01:04:17,120 --> 01:04:20,520
Speaker 1: able to pull together. But of course, also you can

1146
01:04:20,600 --> 01:04:22,520
Speaker 1: always email us if you want to let us snow

1147
01:04:22,560 --> 01:04:24,520
Speaker 1: feedback on this episode or any other, or to give

1148
01:04:24,560 --> 01:04:27,160
Speaker 1: us ideas for future episodes that blow the mind. At

1149
01:04:27,200 --> 01:04:38,800
Speaker 1: how stuff works dot com, well more on this and

1150
01:04:38,920 --> 01:04:41,680
Speaker 1: thousands of other topics. Is that how stuff works dot com.

1151
01:05:00,000 --> 01:05:01,880
Speaker 1: She was twenty times to the bot