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Friday, May 22, 2009

Alison Gopnik - Everything We Think We Know About Babies Is Wrong


I was lucky to see Alison Gopnik at the U of A consciousness conference last year - she is blazing new ground in what we know about the intelligence of infants. She is the new Margaret Mahler, and she is revising a lot of what has been taken for granted about infant minds, just as Mahler did.

This is a great article from Seed Magazine.

To Be a Baby

Bibliolog / by Evan Lerner / May 5, 2009

Alison Gopnik describes new experiments in developmental psychology that show everything we think we know about babies is wrong.

Thomas Nagel famously asked, “What is it like to be a bat?” That question has become a staple of Philosophy 101 courses, but we might be better served asking a more basic one: What is it like to be a baby? Though all of us experience life as a baby firsthand, we’ve long held misconceptions about what babies are capable of thinking, feeling, and understanding. Only recently have we overturned dominant theories of development in which very young children were thought to be barely conscious at all.


Out Aug 4 | Buy

In The Philosophical Baby developmental psychologist Alison Gopnik compiles the latest in her field’s research to paint a new picture of our inner lives at inception — one in which we are, in some ways, more conscious than adults. Gopnik spoke with Seed’s Evan Lerner about how babies and young children learn from us and what we can learn from them.

Seed:
How does a better understanding of what’s going on in the minds of babies help us as adults?
Alison Gopnik:
One of the things we discovered is that imagination, which we often think of as a special adult ability, is actually in place in very young children, as early as 18 months old. That ability is very closely related to children’s ability to figure out how the world works. Imagination isn’t just something we develop for our amusement; it seems to be something innate and connected to how we understand the causal structure of the real world. In fact, the new computational model of development we’ve created —  using what computer scientists call Bayesian networks — shows systematically how understanding causation lets you imagine new possibilities. If children are computing in this way, then we’d expect imagination and learning to go hand in hand.

Seed: You describe children as being “useless on purpose.” What do you mean by that?
AG:
It’s related to one of the basic things that came out of our research: Why do children exist at all? It doesn’t make tremendous evolutionary sense to have these creatures that can’t even keep themselves alive and require an enormous investment of time on the part of adults. That period of dependence is longer for us than it is for any other species, and historically that period has become longer and longer.

The evolutionary answer seems to be that there is a tradeoff between the ability to learn and imagine — which is our great evolutionary advantage as a species — and our ability to apply what we’ve learned and put it to use. So one of the ideas in the book is that children are like the R&D department of the human species. They’re the ones who are always learning about the world. But if you’re always learning, imagining, and finding out, you need a kind of freedom that you don’t have if you’re actually making things happen in the world. And when you’re making things happen, it helps if those actions are based on all of the things you have learned and imagined. The way that evolution seems to have solved this problem is by giving us this period of childhood where we don’t have to do anything, where we are completely useless. We’re free to explore the physical world, as well as possible worlds through imaginative play. And when we’re adults, we can use that information to actually change the world.

Seed: You think Freud’s and Piaget’s conceptions of young children’s theory of mind are wrong. What do we know that they didn’t?
AG: Both Piaget and Freud thought that the reason children produced so much fantastic, unreal play was that they couldn’t tell the difference between imagination and reality. But a lot of the more recent work in children’s theory of mind has shown quite the contrary. Children have a very good idea of how to distinguish between fantasies and realities. It’s just they are equally interested in exploring both. The picture we used to have of children was that they spent all of this time doing pretend play because they had these very limited minds, but in fact what we’ve now discovered is that children have more powerful learning abilities than we do as adults. A lot of their characteristic traits, like their pretend play, are signs of how powerful their imaginative abilities are.

Seed: So is this just a matter of a changing frame of reference, where we now value imagination more?
AG: Well, the science has changed, too. For Freud and Piaget, it was a perfectly good hypothesis. If you just looked at young children and babies, they just did not seem very smart. We have new techniques we use to get more subtle measurements of what’s going on in children’s minds, and that’s the thing that has overturned that earlier view. When we take more than a superficial look at what children are doing, it turns out that they both know much more and learn much more than we ever thought before.

Seed: What are these techniques? How can we interrogate the minds of people who can’t yet fully communicate?
AG:
Children are not very good at spontaneously telling you what they are thinking. With adults, we give them a questionnaire and have them give us answers. That doesn’t work for babies, who can’t talk, and for young children, who can only give a kind of stream-of-consciousness response. So one thing is to look at what they do rather than what they say. This works if you give them very focused questions with very simple answers. Rather than ask a child to explain how a toy machine works, we’ll ask, “Do you think this block or that block will make the machine go?”

Seed: What have you found?
AG: These techniques show that children can work with very complex statistical information. In the machine example, we show children’s patterns of conditional probability, the relationship between certain blocks and the machine turning on or off. If I tried to give you just a description of the sequence of events in one of these experiments in a conversation, I’d probably get it wrong and you wouldn’t be able to remember it — it’s pretty complicated for even adults to describe. But when you give kids these complicated sets of relationships and then just ask them to make the machine go or make the machine stop, they do the right things. Although they can’t consciously track how these conditional probabilities work, they are unconsciously taking that information into account. And they do this in the same way that sophisticated Bayesian network machine-learning programs do.


Credit: crimfants

Seed: What about less objective causal inferences, such as ones dealing with morality?
AG: One of my favorites of these experiments is one that’s been around for quite awhile but hasn’t been fully appreciated. Two-and-a-half-year-olds already recognize the difference between moral principles and conventional principles. You can ask them if it would be okay to hit someone at daycare if everyone said it would be okay, versus asking them whether it would be okay to not hang up your coat in the cubby if everyone said it would be okay. These children say it’s never okay to hit someone, but whether or not you have to put your clothes in the cubby could change from daycare to daycare. They already seem to appreciate the difference between the kinds of morality that comes from empathy and the kind that comes from our conventional rules. From the time they are two, they recognize both are important but in different ways. That’s pretty amazing.

Seed: So where do adult philosophers go from here?
AG: Back to the 18th century, in some ways. If you look at someone like David Hume, he thought he was doing a kind of theoretical science — he didn’t think there was a line between what we find out from science and what we find out from philosophy. Increasingly, modern philosophers say that we can learn about the big questions by looking at science. But science, especially developmental psychology, can also tell us about philosophy; it can tell us about what we start with, what we learn, and what the basic facets of human nature are. The kind of picture you often get from scientifically oriented philosophy is often very much in the vein of evolutionary psychology, with everything innate and genetically determined. But one of the more important things that has come out of developmental work is that there’s also a powerful capacity for change. And we’re starting to understand how that change takes place at a very detailed neurological and computational level.

And the same is true when we look at our moral development. A lot of moral psychology has been saying that we have these innate moral instincts, or innate moral grammars. When we look at children, we do see some of these innate moral intuitions, but there is also this tremendous capacity for moral revision. In some ways, I think those are some of the most distinctively human abilities. They give us the ability to say, “Oh wait, the way that we’ve been operating is not working, and that’s wrong.” And this gives us the ability to change those things that are wrong and get to better moral principles than we started out with.


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