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.
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.
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Posted by: Andreea Hirica
Posted on: Contagious Ideas
