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PROFESSOR: Last time I was
talking about cognition and I'm

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framing the argument in part in
saying that we're not like

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computers, even though
computer's a nice metaphor for

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various secure aspects
of cognitive function.

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We could continue that today.
 

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When you get an off-the-shelf
computer, you expect that its

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basic way of thinking is
going to be -- it's there.

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You might have to put some
programs on it to teach it to

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do specific things, but you
don't have to educate its

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motherboard or something
of that sort.

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With kids it's not clear
that that's the case.

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That if you take an
off-the-shelf baby, it's not

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clear that that baby is
thinking the way that

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an adult is thinking.
 

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That's really what I want
to talk about today.

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Let me put up a picture
that I can then return

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to multiple times.
 

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If this is age, and we're
interested in development, what

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we were talking about last time
is the adult state -- something

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about the adult state.
 

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What we want to know in
studying cognitive development

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or any sort of development is
what's the starting point?

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If you have a newborn baby, is
that starting at zero or does

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that baby come with some sort
of innate endowment that gets

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them on the way towards
the adults state.

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Then what does the transition
from the kid state to the

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adult state look like?
 

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Does it look like some sort
of gradual improvement?

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Does it look like some
sort of step function?

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It might be useful to describe
from the realm of vision, a

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couple of examples just to
show you what this means.

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If you want to know what a baby
sees, get yourself a newborn

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off-the-shelf baby and give
them -- well, you can't give

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them an eye chart to read
because they can't read, so you

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give them the illiterate E
chart, as it's called in the

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trade, and you ask them which
way do the letters point, the

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kid doesn't tell you anything
useful, because the kid

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can't answer that question.
 

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However, conveniently enough if
you take even a newborn baby,

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young as you can test them, and
put them in front of a couple

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of screens -- little
peephole here.

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You guys can all be babies and
the experiment, if you're

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looking out at you through this
peephole, if you put black and

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white bars on one screen and
you put on the other screen a

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grey of the same average
luminance, so if this is zero

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and that's 100, this is
50 all over the place.

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If the baby can see the bars,
conveniently enough that

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baby will look at the bars.
 

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If you are looking at the baby,
you can figure out, you move

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the bars from side-to-side from
child-to-child, you can figure

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out where that baby is looking
and you can figure out where

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the bars are based on where
the baby is looking.

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That's known as a preferential
looking method, very

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useful in infant research.
 

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What you discover, if you do
experiments like this studying

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infant visual aquity, is that
babies don't start at zero.

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A newborn baby isn't blind.
 

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Newborn baby can see something.
 

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If normal adult vision's around
20/20, newborn baby vision is

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around 20/400 -- the big E at
the top of the eye

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chart roughly.
 

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The progression from the infant
state to the adult state is a

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gradual, relatively steady
increase over about the first

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couple of years of life.
 

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Every month you get roughly the
same kind of improvement until

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you hit the adult level.
 

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So, not a zero starting point
and a gradual improvement

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to adult level.
 

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Now let's take a different
example from the same realm.

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Remember you've got two eyes,
the differences in those two

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eyes are a depth cue -- known
as binocular stereopsis.

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Well the cue is binocular
disparity, the ability is

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stereoscopic depth perception.
 

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If you test a baby, so baby's
it turns out also like things

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that stand out in depth better
than they like flat stuff, so

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if you show a baby bars
standing out in depth, a

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newborn baby gives you squat.
 

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To all appearances there is
no binocular stereovision

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in a newborn baby.
 

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For about the first three to
five months, nothing happens.

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Then over a very short period
of time, performance rises to

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essentially the adult level,
as if this was waiting for

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something to get wired
up in the brain.

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When it got wired up in the
brain, bingo, the kid is fine.

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Oh, by the way, if you
are a woman person

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you got there first.
 

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It turns out to be a reliable
sex difference that females

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get binocular stereovision
a month or so before males.

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Does this make any
difference to anything?

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No, but we found it years and
years ago when I was a grad

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student so I still remember it.
 

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So these are two of the
various possibilities for

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a function like this for
a developmental course.

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We're going to talk about three
specific realms of cognitive

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development in which there are
classic demonstrations of

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children doing things
differently than

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adults do them.
 

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I will try to take each of
those apart and to give you

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some idea of what's the
starting point, what's the

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ending point and how do
we get between those.

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The three, which are outlined
on the handout have to do with

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so-called childhood, animism
and egocentric behavior.

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Let me describe each of these
problems to you in turn and

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then we'll take each
of them apart.

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These are all demonstrations
that originally come from the

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work of Jean Piaget, the great
early mid-20th century

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developmental psychologist, who
among other things, bequeathed

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to us a great collection of
phenomena that shows striking

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differences between the way
kids behaving and the way

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adults behave and that
cry out for explanation.

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So here would be one of them.
 

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These are M&M's, let us say.
 

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This is another one of those
forced choice kind of things,

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so think hard about this.
 

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Are there more M&M's
here or here?

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How many vote up?
 

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That's good.
 

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However, if you were 3, 4, 5,
maybe even 6, you'd say here.

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You would be perfectly happy.
 

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So the first obvious thought is
well, the kid's just not quite

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understanding the question.
 

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It a languagy kind of thing.
 

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We're saying where's more and
they're saying which is longer.

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So that's why it's important
that you use M&M's.

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You say OK, kid, which
pile would you like?

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Kid says I want this pile.
 

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Why do you want this pile?
 

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Well there's more there.
 

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In fact, this is why you
shouldn't be born to a

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psychologist because your
psychologist dad is always

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tricking you out of the candy
by playing this game on you.

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It works.
 

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You teach this stuff
long enough and you say

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is this really true?
 

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And then you've got yourself
like a three-year old kid and

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you mess with his brain
-- yeah, it's true.

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This is good stuff.
 

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The question here, of course,
is then what's going on?

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This is part of a
general problem.

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So let's take a fat beaker.
 

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Here's a big fat beaker with
this much fluid in it.

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Now I pour that into
a narrow beaker.

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The fluid level is?
 

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AUDIENCE: Higher.
 

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PROFESSOR: Higher.
 

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Is there more fluid now than
there was when it was here?

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No.
 

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Does a little kid
think there is?

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Yes.
 

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If you let the little kid pour
it back into the big bowl, now

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he thinks there's less now.
 

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Take a ball of clay, roll it
out into a snake, there's more

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clay says the little kid.
 

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Squish it back together,
now there's less.

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These are so-called
conservation problems.

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We're particularly interested
in the version that has to do

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with number -- how come they
think, in this case, that

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five is bigger than six.
 

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Second problem is what's
called childhood animism.

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The classic Piagethian version
would involve something exactly

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like his so-called three
mountain apparatus where e had

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sort of a table top -- he's
from Switzerland, so

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he's into the Alps.
 

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It's a table top version of the
Alps, on the Alps are things

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like, that's a river
and that's a hut.

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The point is that you're
sitting here looking

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at this thing.
 

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You're like a three-year old or
something looking at this, and

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mom's over there on
the other side.

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You can see mom.
 

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The question that you're
asked is can your

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mother see the river?
 

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And you say, yeah sure.
 

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As if the fact that you could
see the river makes you think

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that she can see the river.
 

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As if you couldn't take
her point of view.

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At least Piaget thought that
the problem here is that you

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can't quite take somebody
else's point of view.

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My favorite anecdotal version
of this is a story of a little

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kid out to eat with his
brother at some burger place.

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Little kid wants more French
fries, and so he does this, on

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the theory, presumably, if I
can't see what I'm doing, you

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can't see what I'm doing.
 

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Most people don't do that by
the time they reach adulthood.

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So there's something
to explain there.

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That's not childhood
animism at all.

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Actually, that's
egocentric behavior.

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Sorry, I misspoke.
 

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That's the third example
that we'll get to.

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So, egocentric
makes more sense.

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Ecocentric is the inability
to see things from somebody

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else's vantage point.
 

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So I've just described
to you the problem of

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childhood egocentrism.
 

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Childhood animism is a tendency
to declare things to be

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alive that you would not
declare to be alive.

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Is the cat alive?
 

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Yeah, fine.
 

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Is the sun alive?
 

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Yes.
 

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Are the clouds alive?
 

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Yes.
 

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Little kids will assert that
and you typically will not.

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That's animism.
 

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Piaget understood that as a
problem with mapping concepts

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onto a discrete set of entities
out in the world, and so we'll

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take a look at that, too.
 

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So, number, animism, you
egocentric behavior, those

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are the things that I
want to talk about today.

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Let's start with number, and
let's start by taking apart

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the idea of number a bit.
 

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Because you an I tend to think
of number as there's five of

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those things and six
of those things.

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The concept of number, the idea
of number can be broken down

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into three different
bits at least.

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Let's see if I can
do this right.

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Oh, well they went by.
 

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How many warthogs were there?
 

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AUDIENCE: [INAUDIBLE].
 

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PROFESSOR: Let's
try this again.

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AUDIENCE: 7.
 

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8.
 

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PROFESSOR: 9, 8, 7.
 

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Some number like that.
 

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It wasn't 150.
 

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But how about this?
 

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AUDIENCE: 2.
 

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PROFESSOR: OK, that's good.
 

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How about this?
 

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AUDIENCE: 3.
 

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PROFESSOR: How about this?
 

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This is data.
 

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If you do this task, what you
find is that people are

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essentially perfect for 1, 2
and 3, maybe 4, and

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then it falls off.
 

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I think the answer was 8
before, but sometimes you say

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7, sometimes you say 9, and so
your percent correct, being

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absolutely correct will
systematically fall off.

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If I put 1,500 wart hogs
up there you'll just not

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get it right at all.
 

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Similarly, if I was to measure
not percent correct but

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reaction time, the reaction
time for 1, 2, 3, 4 would be

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essentially flat, and
then start to roughly

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linearly increase.
 

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That linear increase could be,
for a number like 8, could

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either be due to some sort
of counting operation.

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Somebody who thinks they
saw 8 of them, tell me how

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they figured that out?
 

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Yeah?
 

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AUDIENCE: You saw a line
of 5 and then 2 and 1.

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PROFESSOR: A line
of 5 and 2 and 1.

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OK.
 

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Yeah?
 

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AUDIENCE: I couldn't get a
count because they went away.

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PROFESSOR: OK, yes.
 

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If I was doing this as a proper
experiment I would have masked

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it so you couldn't count like
the after-image or

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the iconic memory.
 

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Yup?
 

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AUDIENCE: Just
recall the picture.

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PROFESSOR: OK, so you were
also dumping it out of iconic

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00:16:30 --> 00:16:31
memory in some fashion.
 

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The answer I was fishing
for is something like

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the 5, 2 and 1 thing.
 

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That you can count those
displays, and in fact, the

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people who got them back later
might have done this, too -- by

280
00:16:40 --> 00:16:43
more typically saying oh,
there's one group of 4,

281
00:16:43 --> 00:16:45
there's another group of 4.
 

282
00:16:45 --> 00:16:49
This ability to handle small
numbers is called subitizing,

283
00:16:49 --> 00:16:53
and it works for small
numbers like 1, 2, 3, 4.

284
00:16:53 --> 00:16:57
You have some immediate
appreciation of those small

285
00:16:57 --> 00:17:01
numbers that's different
than your appreciation

286
00:17:01 --> 00:17:06
of 8 or 17 or 150.
 

287
00:17:06 --> 00:17:11
That's one wart hog
demonstration.

288
00:17:11 --> 00:17:14
How about which one
has more wart hogs?

289
00:17:14 --> 00:17:17
 
 

290
00:17:17 --> 00:17:21
How many vote that
there were more here?

291
00:17:21 --> 00:17:22
How many vote that
there were more here?

292
00:17:22 --> 00:17:24
OK, you got that.
 

293
00:17:24 --> 00:17:26
How many wart hogs
were there here?

294
00:17:26 --> 00:17:29
 
 

295
00:17:29 --> 00:17:31
A lot, yes.
 

296
00:17:31 --> 00:17:34
And how many wart
hogs were here?

297
00:17:34 --> 00:17:37
A lot but not as many.
 

298
00:17:37 --> 00:17:39
You could count
these, obviously.

299
00:17:39 --> 00:17:42
But you didn't count them and
you didn't subitize them.

300
00:17:42 --> 00:17:45
What you did was you got some
sort of general impression

301
00:17:45 --> 00:17:45
of their numerosity.
 

302
00:17:45 --> 00:17:52
 
 

303
00:17:52 --> 00:17:55
This is if you go back to
perception chapter, this is

304
00:17:55 --> 00:17:58
another Weber's law kind
of thing, or the money

305
00:17:58 --> 00:18:00
example from last time.
 

306
00:18:00 --> 00:18:04
You can also decide something
about how many things there

307
00:18:04 --> 00:18:09
are there by a sort of
a ratio comparison.

308
00:18:09 --> 00:18:12
There's more here than here.
 

309
00:18:12 --> 00:18:18
If there were 750 here and 745
here you wouldn't know that.

310
00:18:18 --> 00:18:21
There has to be a critical
proportional difference

311
00:18:21 --> 00:18:22
between the two.
 

312
00:18:22 --> 00:18:24
But given a proportion
difference, that this is

313
00:18:24 --> 00:18:27
something like 2:1, like that,
it doesn't matter how many

314
00:18:27 --> 00:18:29
things there are, you simply
know that there's more

315
00:18:29 --> 00:18:31
here and less here.
 

316
00:18:31 --> 00:18:34
That's sort of a crude
sense of numerosity.

317
00:18:34 --> 00:18:38
 
 

318
00:18:38 --> 00:18:41
What we typically think of when
we think about number is

319
00:18:41 --> 00:18:44
counting things, and that's
the third property.

320
00:18:44 --> 00:18:45
So here, you can count them.
 

321
00:18:45 --> 00:18:48
Somebody can go and figure
out exactly how many wart

322
00:18:48 --> 00:18:49
hogs there are there.
 

323
00:18:49 --> 00:18:53
You just have to go through
and use your counting

324
00:18:53 --> 00:18:58
ability to figure that out.
 

325
00:18:58 --> 00:19:00
You have that ability.
 

326
00:19:00 --> 00:19:05
It seems to be critically
piggybacked on

327
00:19:05 --> 00:19:07
linguistic ability.
 

328
00:19:07 --> 00:19:11
Recent interesting evidence for
that comes from -- I don't know

329
00:19:11 --> 00:19:13
how to pronounce it properly,
but something like the Bari

330
00:19:13 --> 00:19:16
Rahua tribe in the Amazon.
 

331
00:19:16 --> 00:19:22
Their number terms consist
of 1, 2 and more than that.

332
00:19:22 --> 00:19:25
 
 

333
00:19:25 --> 00:19:32
The result is that they bomb
tasks that require counting.

334
00:19:32 --> 00:19:38
They can do subitizing tasks,
they can do numerosity tasks,

335
00:19:38 --> 00:19:41
but they don't do
counting tasks.

336
00:19:41 --> 00:19:46
They fail versions of
the M&M task in effect.

337
00:19:46 --> 00:19:51
You say which of these boxes do
you want -- the got fish in

338
00:19:51 --> 00:19:53
them or something like that,
and one has a little label with

339
00:19:53 --> 00:19:56
4 fish on the top and another
has 5 fish on the top and as

340
00:19:56 --> 00:19:58
far as these guys are
concerned, it's all

341
00:19:58 --> 00:20:01
just got lots of fish.
 

342
00:20:01 --> 00:20:06
What you see here is a
task where this was the

343
00:20:06 --> 00:20:12
experimenter's marks, and the
Bari Rahua person was asked

344
00:20:12 --> 00:20:13
to just copy it.
 

345
00:20:13 --> 00:20:16
So, one mark, make one
mark, two, I can make

346
00:20:16 --> 00:20:17
two marks, three, three.
 

347
00:20:17 --> 00:20:21
That's just a bunch, I'll
make a bunch of marks.

348
00:20:21 --> 00:20:23
Once you got out of the
subitizing range they

349
00:20:23 --> 00:20:26
simply didn't do the task.
 

350
00:20:26 --> 00:20:31
I think I'd put these guys
on this article from which

351
00:20:31 --> 00:20:33
I stole -- this picture
may live on the website.

352
00:20:33 --> 00:20:36
I seem to remember that
that was one of the things

353
00:20:36 --> 00:20:38
that I posted there.
 

354
00:20:38 --> 00:20:41
So, what to kids have
and how does that tie

355
00:20:41 --> 00:20:44
into the M&M problem.
 

356
00:20:44 --> 00:20:52
Well, turns out that little
kids have babies, have this

357
00:20:52 --> 00:20:57
numerosity -- Weber's law,
comparison kind of numerosity

358
00:20:57 --> 00:21:01
ability, and here's an
experiment done by [? Shew ?]

359
00:21:01 --> 00:21:06
and Liz Spelke up at Harvard
that illustrates that.

360
00:21:06 --> 00:21:10
You're a baby, you're looking
at this, and every now and

361
00:21:10 --> 00:21:13
then the display changes.
 

362
00:21:13 --> 00:21:16
OK, there's another
bunch of dots.

363
00:21:16 --> 00:21:19
And another bunch of dots.
 

364
00:21:19 --> 00:21:21
What I'm doing is I, the
experimenter am measuring

365
00:21:21 --> 00:21:24
how long you look at this.
 

366
00:21:24 --> 00:21:27
I'm changing the shape and the
distribution of these guys, but

367
00:21:27 --> 00:21:30
I'm not changing the number.
 

368
00:21:30 --> 00:21:35
You are slowly getting bored,
or to be more technical about

369
00:21:35 --> 00:21:37
it, you're habituating.
 

370
00:21:37 --> 00:21:42
You may recall that from
the learning chapter.

371
00:21:42 --> 00:21:44
I don't think we talked
about it in the chapter.

372
00:21:44 --> 00:21:47
Well, we can talk
about it right now.

373
00:21:47 --> 00:21:50
A bunch of people
oriented to that.

374
00:21:50 --> 00:21:54
 
 

375
00:21:54 --> 00:21:57
Now those people are
having no problem at all

376
00:21:57 --> 00:21:59
veeing back out again.
 

377
00:21:59 --> 00:22:00
That's habituation.
 

378
00:22:00 --> 00:22:03
You do it, babies do it, slugs
do it, everybody does it.

379
00:22:03 --> 00:22:04
Great.
 

380
00:22:04 --> 00:22:07
Useful technique, because the
baby's sitting here saying this

381
00:22:07 --> 00:22:10
is all kind of more or less the
same and it's just not

382
00:22:10 --> 00:22:14
that interesting.
 

383
00:22:14 --> 00:22:18
Wait a second, that's
interesting, says the baby.

384
00:22:18 --> 00:22:21
And the baby says it
by looking more.

385
00:22:21 --> 00:22:27
What happens here is that
looking time goes down, down,

386
00:22:27 --> 00:22:30
down, down as the number on
each trial stays the same.

387
00:22:30 --> 00:22:33
Then when you jump from 8
to 16, the baby says hey,

388
00:22:33 --> 00:22:35
something's happened, I
gotta take a look at this.

389
00:22:35 --> 00:22:37
Do 16 for awhile, blah,
blah, blah, blah, blah,

390
00:22:37 --> 00:22:39
blah, blah, blah.
 

391
00:22:39 --> 00:22:42
What this tells you is that
the baby could tell the

392
00:22:42 --> 00:22:44
difference between 8 and 16.
 

393
00:22:44 --> 00:22:47
The reason for changing the
shape and the distribution and

394
00:22:47 --> 00:22:51
the density and stuff like that
is to make sure that that's not

395
00:22:51 --> 00:22:53
what you're picking up on.
 

396
00:22:53 --> 00:22:53
[? Shew ?]
 

397
00:22:53 --> 00:22:55
and Spelke were
careful about that.

398
00:22:55 --> 00:23:01
So what you're picking
on here is numerosity.

399
00:23:01 --> 00:23:07
Babies can do that, but
if you go from 8 to 9,

400
00:23:07 --> 00:23:09
nothing happens here.
 

401
00:23:09 --> 00:23:13
In fact, if you go from 8 to
12, a 50% increase in dots,

402
00:23:13 --> 00:23:17
nothing happens here with,
how old are these babies

403
00:23:17 --> 00:23:19
-- six month old babies.
 

404
00:23:19 --> 00:23:23
So, 8 to 16, a 2:1 change
-- that babies pick up on.

405
00:23:23 --> 00:23:38
So, one thing we know that if
we're talking about number, the

406
00:23:38 --> 00:23:49
starting spot isn't zero for
number sense in infants.

407
00:23:49 --> 00:23:54
The numerosity piece, some
chunk of the numerosity piece

408
00:23:54 --> 00:23:56
is there for starters.
 

409
00:23:56 --> 00:24:02
Perhaps more dramatically, the
subitizing piece is there, and

410
00:24:02 --> 00:24:09
the subitizing piece is there
along with what seems to be an

411
00:24:09 --> 00:24:11
innate mathematical ability.
 

412
00:24:11 --> 00:24:14
Little kids can
add and subtract.

413
00:24:14 --> 00:24:17
Babies can add and subtract.
 

414
00:24:17 --> 00:24:19
This was a surprise.
 

415
00:24:19 --> 00:24:22
 
 

416
00:24:22 --> 00:24:26
This is work done by karen
Wynn, and it is worth making

417
00:24:26 --> 00:24:30
the historical note that she
was a TA for this course once

418
00:24:30 --> 00:24:33
upon a time, now a
professor at Yale.

419
00:24:33 --> 00:24:37
But in any case, she figured
out that babies can

420
00:24:37 --> 00:24:39
add and subtract.
 

421
00:24:39 --> 00:24:42
Look, if you ask a baby what's
one plus one, you get much the

422
00:24:42 --> 00:24:45
same answer as if you asked the
baby which way is

423
00:24:45 --> 00:24:45
the E pointing.
 

424
00:24:45 --> 00:24:49
You gotta get clever about
this sort of thing.

425
00:24:49 --> 00:24:52
Here's how Karen got
clever about it.

426
00:24:52 --> 00:24:53
So, you're looking at a screen.
 

427
00:24:53 --> 00:24:59
You're a little baby looking at
a screen like this and you see

428
00:24:59 --> 00:25:01
a hand come in with an object.
 

429
00:25:01 --> 00:25:12
 
 

430
00:25:12 --> 00:25:15
And you see a hand come
in with another one.

431
00:25:15 --> 00:25:19
You got a pretty good idea
what's going on here, right.

432
00:25:19 --> 00:25:24
So, if I lift the screen,
what do you expect to see?

433
00:25:24 --> 00:25:29
 
 

434
00:25:29 --> 00:25:34
Now, we're going
to do this again.

435
00:25:34 --> 00:25:35
The speed would be the same, of
course, I just didn't want to

436
00:25:35 --> 00:25:38
keep sliding them in slowly.
 

437
00:25:38 --> 00:25:46
 
 

438
00:25:46 --> 00:25:51
The baby will respond to
this by looking longer.

439
00:25:51 --> 00:25:55
The baby will say -- who knows
what the baby will say, but the

440
00:25:55 --> 00:25:59
baby is apparently in effect
saying put one thing in this,

441
00:25:59 --> 00:26:05
two things in here, two stuff,
two wart hogs back there.

442
00:26:05 --> 00:26:08
Now there's only one wart hog
and this violates the rules of

443
00:26:08 --> 00:26:11
the universe and I said better
look at this for a while to

444
00:26:11 --> 00:26:14
figure out what's going on.
 

445
00:26:14 --> 00:26:23
You can use this technique to
show that babies can do -- do

446
00:26:23 --> 00:26:25
I have a subtraction
one here, I forget.

447
00:26:25 --> 00:26:33
 
 

448
00:26:33 --> 00:26:35
It works for monkeys, too.
 

449
00:26:35 --> 00:26:37
We'll talk about
that in a minute.

450
00:26:37 --> 00:26:40
But you can do addition,
you can do subtraction.

451
00:26:40 --> 00:26:44
So, subtraction, you have the
two things here, you put down

452
00:26:44 --> 00:26:49
the screen, the hand comes
in and pulls one out.

453
00:26:49 --> 00:26:52
When the screen comes up the
baby expects to see one.

454
00:26:52 --> 00:26:56
If the babiy sees zero or the
baby sees two, the baby says

455
00:26:56 --> 00:27:00
something weird's going
on here, I need to think

456
00:27:00 --> 00:27:03
about this for a while.
 

457
00:27:03 --> 00:27:06
Now, if you do this with
big numbers outside of

458
00:27:06 --> 00:27:09
the subitizing range, you
don't get the result.

459
00:27:09 --> 00:27:13
So, you stick 15 wart hogs back
there and you lift up the

460
00:27:13 --> 00:27:18
screen and there's 13 wart hogs
and the kid says I don't care.

461
00:27:18 --> 00:27:23
Once you get above about
3 with babies, it

462
00:27:23 --> 00:27:24
doesn't work anymore.
 

463
00:27:24 --> 00:27:34
So, what you get is evidence
for subitizing being present

464
00:27:34 --> 00:27:40
and some sort of addition and
subtraction kind of operation

465
00:27:40 --> 00:27:42
for, essentially as early
as you want to test it.

466
00:27:42 --> 00:27:45
You can also get these
abilities in animals -- that's

467
00:27:45 --> 00:27:51
what this slide is intended to
remind me to tell you.

468
00:27:51 --> 00:27:54
Animals, certainly Macaque
monkeys will show numerosity

469
00:27:54 --> 00:27:59
effects, and they can also do
this sort of Karen

470
00:27:59 --> 00:28:01
Wynn style math.
 

471
00:28:01 --> 00:28:05
They prefer eggplants -- at
least Marc Hauser's monkeys

472
00:28:05 --> 00:28:08
like eggplant, so that's why
there are eggplants here.

473
00:28:08 --> 00:28:11
And you worry about doing this
in the lab, because maybe your

474
00:28:11 --> 00:28:16
lab monkeys have led this
elaborately studied life

475
00:28:16 --> 00:28:18
and are kind of smart.
 

476
00:28:18 --> 00:28:21
Hauser went down to this island
in the Caribbean where he's

477
00:28:21 --> 00:28:24
got a free-ranging
troop of monkeys.

478
00:28:24 --> 00:28:29
Then you kind of have to coax
them into playing your game.

479
00:28:29 --> 00:28:33
There's this great video that
Marc has of monkeys -- he's

480
00:28:33 --> 00:28:37
hanging out with his eggplants,
then he's starting to do this

481
00:28:37 --> 00:28:41
eggplant puppet show with the
Macaque's looking longer

482
00:28:41 --> 00:28:42
at the weird ones.
 

483
00:28:42 --> 00:28:45
The guy put two eggplants
there, there's only

484
00:28:45 --> 00:28:45
one there now.
 

485
00:28:45 --> 00:28:49
Hope he's going to feed me some
of these eggplants eventually.

486
00:28:49 --> 00:28:52
But in any case, monkeys
can do the task.

487
00:28:52 --> 00:28:56
Monkeys will look longer
at things that violate

488
00:28:56 --> 00:28:58
their expectation.
 

489
00:28:58 --> 00:29:01
However, monkeys don't count.
 

490
00:29:01 --> 00:29:05
At least they don't count the
way that you and I count.

491
00:29:05 --> 00:29:07
This goes for great apes.
 

492
00:29:07 --> 00:29:10
Fine, let's go find the
brightest beast other

493
00:29:10 --> 00:29:13
than humans that we can.
 

494
00:29:13 --> 00:29:18
There's at least one chimp
who's been trained for 20 years

495
00:29:18 --> 00:29:22
-- oh, I misspoke when I talked
about this in Concourse.

496
00:29:22 --> 00:29:23
I'd said he'd been trained
for nine years and

497
00:29:23 --> 00:29:25
never gotten past 20.
 

498
00:29:25 --> 00:29:26
It's worse than that.
 

499
00:29:26 --> 00:29:28
He's been trained for 20
years you never gotten

500
00:29:28 --> 00:29:30
past nine counting.
 

501
00:29:30 --> 00:29:33
He can count to nine, do
pretty good stuff up to nine.

502
00:29:33 --> 00:29:38
But he's doing this by
basically association learning.

503
00:29:38 --> 00:29:44
 
 

504
00:29:44 --> 00:29:48
You can train the monkey to
realize that this sign or

505
00:29:48 --> 00:29:54
this graphic or something
means nine things.

506
00:29:54 --> 00:29:58
But this is very different
from what you and I can do.

507
00:29:58 --> 00:30:03
It didn't take you 20 years
and you got well beyond nine.

508
00:30:03 --> 00:30:08
Counting seems to be heavily
dependent on two things.

509
00:30:08 --> 00:30:13
One is language, and
the other is an act of

510
00:30:13 --> 00:30:14
inductive reasoning.
 

511
00:30:14 --> 00:30:18
You can sort of see counting
happening, the development of

512
00:30:18 --> 00:30:26
counting in a series of steps.
 

513
00:30:26 --> 00:30:34
Kids, as they are learning
language, learn that there is

514
00:30:34 --> 00:30:44
this kind of game about saying
1, 2, 3, four and so on, that

515
00:30:44 --> 00:30:47
parents really like to play.
 

516
00:30:47 --> 00:30:52
If you start counting they'll
give you the cookies and stuff.

517
00:30:52 --> 00:30:56
Good things happen.
 

518
00:30:56 --> 00:30:59
They don't have any particular
clue initially that this maps

519
00:30:59 --> 00:31:04
on to anything in particular.
 

520
00:31:04 --> 00:31:08
 
 

521
00:31:08 --> 00:31:11
So, what you get with like two
and a half year old kids is a

522
00:31:11 --> 00:31:16
two and a half year old kid,
if you ask for one cookie

523
00:31:16 --> 00:31:18
will give you one cookie.
 

524
00:31:18 --> 00:31:20
But if you ask for anything
else -- give me two cookies,

525
00:31:20 --> 00:31:22
give me four cookies, give me
whatever, they'll give you

526
00:31:22 --> 00:31:25
some random -- here,
have some cookies.

527
00:31:25 --> 00:31:28
It's one and other stuff.
 

528
00:31:28 --> 00:31:36
Eventually they learn to
map the counting onto the

529
00:31:36 --> 00:31:42
subitizing range and then
start blowing it later.

530
00:31:42 --> 00:31:45
If you have little sibs or
cousins or stuff that you've

531
00:31:45 --> 00:31:49
hung around with, you may have
seen them counting things

532
00:31:49 --> 00:31:56
-- 1, 2, 3, 4, 5, 7, 12.
 

533
00:31:56 --> 00:31:59
They got this notion that the
numbers keep going in some

534
00:31:59 --> 00:32:02
fashion, but once you get out
of the small numbers it's not

535
00:32:02 --> 00:32:05
terribly clear what's
going on there.

536
00:32:05 --> 00:32:09
But even in this stage you can
start to see the development of

537
00:32:09 --> 00:32:12
something more sophisticated.
 

538
00:32:12 --> 00:32:15
Six -- they may not know
how many six's, they know

539
00:32:15 --> 00:32:17
six is a lot of stuff.
 

540
00:32:17 --> 00:32:20
If you ask for six cookies
you'll get some arbitrary

541
00:32:20 --> 00:32:23
number of cookies.
 

542
00:32:23 --> 00:32:33
But if you ask a little kid if
I take a lot of cookies and

543
00:32:33 --> 00:32:38
I add a few, do I still
have a lot of cookies?

544
00:32:38 --> 00:32:42
Kid says yeah, it works.
 

545
00:32:42 --> 00:32:44
So, alright, so we know that.
 

546
00:32:44 --> 00:32:49
Now, if I have six cookies,
can you give me six cookies?

547
00:32:49 --> 00:32:51
Some random number of cookies.
 

548
00:32:51 --> 00:32:55
If I have six cookies and I
add some more cookies, do

549
00:32:55 --> 00:32:58
I still have six cookies?
 

550
00:32:58 --> 00:32:58
No.
 

551
00:32:58 --> 00:33:02
You got a lot of cookies but
it's not the same a lotta.

552
00:33:02 --> 00:33:05
So, even when they don't really
know how many cookies you've

553
00:33:05 --> 00:33:14
got, they have the notion that
the number names are naming

554
00:33:14 --> 00:33:16
something specific.
 

555
00:33:16 --> 00:33:18
They don't quite get what
it is, but it's something

556
00:33:18 --> 00:33:23
specific in a way that a
term like a lot is not.

557
00:33:23 --> 00:33:30
Eventually, you make the
breakthrough that you can

558
00:33:30 --> 00:33:36
count, basically, and if you
add one to each of them you can

559
00:33:36 --> 00:33:39
just keep doing this forever.
 

560
00:33:39 --> 00:33:41
Again, I don't know how much
you hang around with little

561
00:33:41 --> 00:33:45
kids or remember your own
experience, because this is

562
00:33:45 --> 00:33:47
getting old enough that you
might actually remember this

563
00:33:47 --> 00:33:52
state yourself, of asking
what the biggest number

564
00:33:52 --> 00:33:53
in the world is.
 

565
00:33:53 --> 00:33:55
Anybody remember asking
what the biggest number

566
00:33:55 --> 00:33:58
in the world is?
 

567
00:33:58 --> 00:34:00
That's the problem with MIT
students, right, they figured

568
00:34:00 --> 00:34:03
all this stuff out when
they were like two.

569
00:34:03 --> 00:34:07
So anyway, little kids want to
know what the biggest number in

570
00:34:07 --> 00:34:09
the world is, and so you say to
the little kid, well what

571
00:34:09 --> 00:34:11
do you think the biggest
number in the world is?

572
00:34:11 --> 00:34:14
Well, it's a million.
 

573
00:34:14 --> 00:34:15
OK.
 

574
00:34:15 --> 00:34:19
What happens if we had
a million plus one, is

575
00:34:19 --> 00:34:22
there a number for that?
 

576
00:34:22 --> 00:34:26
I guess a million and one's the
biggest number in the world.

577
00:34:26 --> 00:34:26
Well, [UNINTELLIGIBLE]
 

578
00:34:26 --> 00:34:27
add a million and two.
 

579
00:34:27 --> 00:34:28
You can keep doing
this for a while.

580
00:34:28 --> 00:34:31
Eventually, around the time
when you get in this

581
00:34:31 --> 00:34:37
conversation, the kid catches
on to the notion that you can

582
00:34:37 --> 00:34:40
always get a bigger one.
 

583
00:34:40 --> 00:34:46
This is really the very
boring car rides sometimes.

584
00:34:46 --> 00:34:47
Do you want to see how
high I can count?

585
00:34:47 --> 00:34:50
That's a kind of cute game
with a three-year old.

586
00:34:50 --> 00:34:53
Aw, look, he can get
all the way to 20.

587
00:34:53 --> 00:34:56
By the time you get a 4 or
5 year old, million and

588
00:34:56 --> 00:34:58
one, million and two,
million and three.

589
00:34:58 --> 00:35:03
OK, we've made it to
California kid, shutup.

590
00:35:03 --> 00:35:10
What you get is you've got this
basic numeric competence or

591
00:35:10 --> 00:35:13
core knowledge, as Liz
Spelke would call it.

592
00:35:13 --> 00:35:19
Then you're waiting for the
development of language.

593
00:35:19 --> 00:35:22
When you get language
you can then get this

594
00:35:22 --> 00:35:23
counting piece to work.
 

595
00:35:23 --> 00:35:26
When you got the counting piece
to work, you can combine it

596
00:35:26 --> 00:35:29
with your ability to make
the inductive leap that

597
00:35:29 --> 00:35:31
numbers go on forever.
 

598
00:35:31 --> 00:35:33
Then you're in a position
to go off to school

599
00:35:33 --> 00:35:34
and learn some math.
 

600
00:35:34 --> 00:35:38
 
 

601
00:35:38 --> 00:35:39
There's, in a sense,
not an adult level of

602
00:35:39 --> 00:35:41
numerical competence.
 

603
00:35:41 --> 00:35:44
You guys know more about
numbers than I know,

604
00:35:44 --> 00:35:45
I would imagine.
 

605
00:35:45 --> 00:35:50
But the ability to go off and
learn that kind of math is

606
00:35:50 --> 00:35:54
based on this core knowledge,
then waiting on language before

607
00:35:54 --> 00:36:03
you can make the leap to an
ability to do 180 whatever.

608
00:36:03 --> 00:36:08
So, it's an example, if you
like, of the synergistic

609
00:36:08 --> 00:36:11
combination of information from
a couple of different realms.

610
00:36:11 --> 00:36:20
Let's switch to the problem of
childhood animism that, if

611
00:36:20 --> 00:36:23
you're not completely confused
from my earlier mis-speaking,

612
00:36:23 --> 00:36:27
animism is the tendency
to say is the sun alive?

613
00:36:27 --> 00:36:27
Yes.
 

614
00:36:27 --> 00:36:29
Are clouds alive?
 

615
00:36:29 --> 00:36:30
Yes.
 

616
00:36:30 --> 00:36:36
That seems quite different
from what you and I do.

617
00:36:36 --> 00:36:42
One might wonder exactly how
different it really is.

618
00:36:42 --> 00:36:45
Does it really reflect a
fundamental problem with

619
00:36:45 --> 00:36:49
the concept alive?
 

620
00:36:49 --> 00:36:53
It's not that's obvious how
you map the concept like

621
00:36:53 --> 00:36:55
that, even as an adult.
 

622
00:36:55 --> 00:37:03
This is perhaps easier to think
about in connection with dead.

623
00:37:03 --> 00:37:06
Mapping dead onto a
discrete set of things

624
00:37:06 --> 00:37:07
is not that trivial.
 

625
00:37:07 --> 00:37:10
Is a rock dead?
 

626
00:37:10 --> 00:37:13
Probably not because it
was never alive, right.

627
00:37:13 --> 00:37:16
Is George Washington dead?
 

628
00:37:16 --> 00:37:17
Seems about right.
 

629
00:37:17 --> 00:37:23
Is he dead in the same way that
something that you can, like a

630
00:37:23 --> 00:37:27
cat that just recently died
-- the here, dead, now.

631
00:37:27 --> 00:37:28
Is that's the same?
 

632
00:37:28 --> 00:37:31
How about a dinosaur?
 

633
00:37:31 --> 00:37:33
Or the dinosaurs, are
the dinosaur's dead?

634
00:37:33 --> 00:37:35
Well yes, they're dead but
they're also extinction, which

635
00:37:35 --> 00:37:38
is somehow kind of different.
 

636
00:37:38 --> 00:37:42
Or to use an example from
driving around, now that my

637
00:37:42 --> 00:37:46
kids have gotten out of the
counting to a million stage --

638
00:37:46 --> 00:37:51
I don't know how we got on the
subject of what is alive.

639
00:37:51 --> 00:37:53
Maybe because I was thinking
about this lecture.

640
00:37:53 --> 00:37:58
But anyway, my 10th grader
asked my 3rd grader

641
00:37:58 --> 00:37:59
is fire alive?
 

642
00:37:59 --> 00:38:02
 
 

643
00:38:02 --> 00:38:05
Well, I don't know about the
3rd grader, but it took dad in

644
00:38:05 --> 00:38:10
the front seat a surprisingly
long time to figure -- dad knew

645
00:38:10 --> 00:38:15
that the answer is no, but the
principled reason why it's no,

646
00:38:15 --> 00:38:18
took me a couple of
beats to get to.

647
00:38:18 --> 00:38:23
Because fire breathes, right,
it grows, it reproduces, it

648
00:38:23 --> 00:38:26
can die, it can do all
those good things.

649
00:38:26 --> 00:38:29
Turns out that in 10th grade
biology they teach you that if

650
00:38:29 --> 00:38:34
you're going to be alive you've
gotta be made of cells, and

651
00:38:34 --> 00:38:39
fire's not made of cells,
except that then you get into

652
00:38:39 --> 00:38:42
11th grade English and you read
some sci fi novel where this

653
00:38:42 --> 00:38:47
thing is alive but it's just a
forcefield in deep space

654
00:38:47 --> 00:38:48
or something like that.
 

655
00:38:48 --> 00:38:52
I don't know what
to do about that.

656
00:38:52 --> 00:38:57
Concepts like alive are pretty
complex stuff, and the fact

657
00:38:57 --> 00:39:00
that a kid doesn't map it
exactly the same way you map it

658
00:39:00 --> 00:39:02
may not be that definitive.
 

659
00:39:02 --> 00:39:05
Does the kid have a concept
at all that they can use?

660
00:39:05 --> 00:39:05
That's what
 

661
00:39:05 --> 00:39:06
we really want to know.
 

662
00:39:06 --> 00:39:08
What's really going on there?
 

663
00:39:08 --> 00:39:12
So maybe we ought to ask
the question a little

664
00:39:12 --> 00:39:13
bit differently.
 

665
00:39:13 --> 00:39:17
Kid had some notion of
what alive things do.

666
00:39:17 --> 00:39:24
So suppose we ask a kid
does a cat breathe?

667
00:39:24 --> 00:39:26
Yeah, a cat breathes.
 

668
00:39:26 --> 00:39:27
How about a cow?
 

669
00:39:27 --> 00:39:29
Yeah, a cow breathes.
 

670
00:39:29 --> 00:39:31
How about the sun?
 

671
00:39:31 --> 00:39:32
I don't think so.
 

672
00:39:32 --> 00:39:33
The moon?
 

673
00:39:33 --> 00:39:33
No.
 

674
00:39:33 --> 00:39:34
The clouds?
 

675
00:39:34 --> 00:39:35
No.
 

676
00:39:35 --> 00:39:38
And you can do the same
thing with babies.

677
00:39:38 --> 00:39:42
Not asking the babies,
but talking about can

678
00:39:42 --> 00:39:44
a cat have babies?
 

679
00:39:44 --> 00:39:45
Yeah, sure.
 

680
00:39:45 --> 00:39:47
Can the sun have babies?
 

681
00:39:47 --> 00:39:49
No.
 

682
00:39:49 --> 00:39:52
You get the feeling that
there's a concept there that

683
00:39:52 --> 00:39:57
they're just not using the
word alive the way that

684
00:39:57 --> 00:39:59
you and I are using it.
 

685
00:39:59 --> 00:40:03
Well, maybe all you're looking
at here is the fact that they

686
00:40:03 --> 00:40:04
don't actually have a concept.
 

687
00:40:04 --> 00:40:06
What they have is a long
list of learned instances.

688
00:40:06 --> 00:40:09
They are hang out at these
fancy upper middle class

689
00:40:09 --> 00:40:13
preschools where they get
taught kitty has babies, cow

690
00:40:13 --> 00:40:16
has babies, and they never gets
taught sun has babies, because

691
00:40:16 --> 00:40:18
the sun doesn't have babies.
 

692
00:40:18 --> 00:40:19
And so they learn
all this stuff.

693
00:40:19 --> 00:40:22
Maybe it's not a concept, maybe
it's just a list of instances.

694
00:40:22 --> 00:40:23
How can we figure this out?
 

695
00:40:23 --> 00:40:28
Well, Sue Carey did an
experiment where what

696
00:40:28 --> 00:40:32
she did was she taught
kids something new.

697
00:40:32 --> 00:40:36
She said see this cat?
 

698
00:40:36 --> 00:40:38
This cat has an omentum.
 

699
00:40:38 --> 00:40:40
And you have an omentum.
 

700
00:40:40 --> 00:40:43
And the cow has an omentum.
 

701
00:40:43 --> 00:40:46
Now, how about the sheep?
 

702
00:40:46 --> 00:40:48
Think it's got omentum?
 

703
00:40:48 --> 00:40:50
Probaby got no mentum.
 

704
00:40:50 --> 00:40:51
And the dog?
 

705
00:40:51 --> 00:40:53
Yeah, the dog's
probably got one.

706
00:40:53 --> 00:40:56
How about a fish?
 

707
00:40:56 --> 00:40:57
Yeah, probably, could be.
 

708
00:40:57 --> 00:40:58
Worm?
 

709
00:40:58 --> 00:41:00
I don't know.
 

710
00:41:00 --> 00:41:00
Rock?
 

711
00:41:00 --> 00:41:02
No, rock doesn't an omentum.
 

712
00:41:02 --> 00:41:03
How about sun?
 

713
00:41:03 --> 00:41:05
No, sun doesn't
have an omentum.

714
00:41:05 --> 00:41:07
You don't have one
either it turns out.

715
00:41:07 --> 00:41:11
She wanted a real biological
term, but I think it's some

716
00:41:11 --> 00:41:13
weird membrane that an insect
has or something like that.

717
00:41:13 --> 00:41:16
But the point was that it
wasn't something that you

718
00:41:16 --> 00:41:17
would have ever learned.
 

719
00:41:17 --> 00:41:21
It's a new piece of knowledge,
and if you say that things in

720
00:41:21 --> 00:41:25
this category, things in the
category that are encompassed

721
00:41:25 --> 00:41:31
by cats, cows and you all
have this, who else has it?

722
00:41:31 --> 00:41:35
And little kids, three,
four-year old kids, map this

723
00:41:35 --> 00:41:37
in a plausible kind of a way.
 

724
00:41:37 --> 00:41:40
It might map something
like mammal, it might map

725
00:41:40 --> 00:41:42
something like animal.
 

726
00:41:42 --> 00:41:44
I don't remember if any of her
kids mapped something like

727
00:41:44 --> 00:41:47
alive in which case they would
assert that a tree had

728
00:41:47 --> 00:41:48
it too or something.
 

729
00:41:48 --> 00:41:56
But it maps a concept that
has a biological ring to it.

730
00:41:56 --> 00:41:59
What's the difference between
the childhood use of these

731
00:41:59 --> 00:42:01
concepts and the adult
use of these concepts?

732
00:42:01 --> 00:42:04
It seems to be, in
this case, education.

733
00:42:04 --> 00:42:08
You go to school to learn
the right concepts.

734
00:42:08 --> 00:42:13
In this sense, there is
no firm adult state.

735
00:42:13 --> 00:42:18
My job here is to teach you a
collection of facts and the

736
00:42:18 --> 00:42:21
right concepts in psychology.
 

737
00:42:21 --> 00:42:25
But I can teach you some of
them and I keep learning new

738
00:42:25 --> 00:42:30
ones, and the adult par keeps
sort of drifting there.

739
00:42:30 --> 00:42:33
You sort of go off to learn
these sort of concepts.

740
00:42:33 --> 00:42:37
But you don't learn to
have a concept per se.

741
00:42:37 --> 00:42:41
What the kid is doing -- well,
actually it's rather similar

742
00:42:41 --> 00:42:42
to what we're doing here.
 

743
00:42:42 --> 00:42:52
The kid is mustering the data
that is available to him, and

744
00:42:52 --> 00:42:53
working with the concept--.
 

745
00:42:53 --> 00:42:56
So what do you think the
concept of alive is

746
00:42:56 --> 00:42:58
for a little kid?
 

747
00:42:58 --> 00:43:02
What do you think goes into it
that causes little kids to give

748
00:43:02 --> 00:43:06
the wrong answer when asked by
Piaget what's alive

749
00:43:06 --> 00:43:07
and what's not?
 

750
00:43:07 --> 00:43:10
What's the critical difference
between your notion of alive

751
00:43:10 --> 00:43:15
that you picked up in 10th
grade biology and a four-year

752
00:43:15 --> 00:43:18
old's notion of alive?
 

753
00:43:18 --> 00:43:19
Anybody?
 

754
00:43:19 --> 00:43:19
Yup?
 

755
00:43:19 --> 00:43:23
AUDIENCE: Something alive is
something that moves and you

756
00:43:23 --> 00:43:24
didn't see how [INAUDIBLE].
 

757
00:43:24 --> 00:43:25
PROFESSOR: Yeah.
 

758
00:43:25 --> 00:43:28
So moving on its own seems
to be an important--.

759
00:43:28 --> 00:43:32
So cars aren't alive because
you've got to make them move in

760
00:43:32 --> 00:43:39
some fashion, but self-produced
motion seems to be an important

761
00:43:39 --> 00:43:42
part of the definition, and the
sun and the clouds and the moon

762
00:43:42 --> 00:43:45
seem to scootch around in the
sky, particularly if you're

763
00:43:45 --> 00:43:49
driving in that car, in
ways that suggest that

764
00:43:49 --> 00:43:50
it might be alive.
 

765
00:43:50 --> 00:43:52
It gets a little more
complicated because kids have

766
00:43:52 --> 00:43:56
also learned that trees are
alive, and outside of Lord of

767
00:43:56 --> 00:44:01
the Rings, trees don't do much
in the way of wandering around,

768
00:44:01 --> 00:44:05
but growing on your
own is good, too.

769
00:44:05 --> 00:44:07
But that would be part of
the biological definition.

770
00:44:07 --> 00:44:13
It's the self-produced motion
thing that kids overuse in

771
00:44:13 --> 00:44:17
their definition, seemingly,
that you don't use.

772
00:44:17 --> 00:44:20
You can see if you get
transcripts of little kids

773
00:44:20 --> 00:44:25
using language, you get a
feeling for this little

774
00:44:25 --> 00:44:30
scientist aspect of
childhood concept.

775
00:44:30 --> 00:44:34
Well, concept formation,
concept verification.

776
00:44:34 --> 00:44:44
So, here from the what is alive
literature is a kid who is

777
00:44:44 --> 00:44:50
asked are rocks alive, and the
answer is yes, rocks are alive.

778
00:44:50 --> 00:44:53
But they're only alive until
you step on them and then

779
00:44:53 --> 00:44:57
they die, which is kind
of reasonable, right.

780
00:44:57 --> 00:44:59
The kid's got presumably
some experience with

781
00:44:59 --> 00:45:01
other things like that.
 

782
00:45:01 --> 00:45:03
This ant -- the ant's
alive, I step on it,

783
00:45:03 --> 00:45:05
it's not alive anymore.
 

784
00:45:05 --> 00:45:07
 
 

785
00:45:07 --> 00:45:11
And this kid produces some
evidence in favor of this

786
00:45:11 --> 00:45:17
theory, which is if you look
on a path, how big are

787
00:45:17 --> 00:45:21
the rocks on average?
 

788
00:45:21 --> 00:45:24
You could take a walk in the
woods down a rocky kind of

789
00:45:24 --> 00:45:26
path, there are rocks on it,
they're kind of small rocks.

790
00:45:26 --> 00:45:30
You look off across at
the mountains, how

791
00:45:30 --> 00:45:32
big are the rocks?
 

792
00:45:32 --> 00:45:33
They're huge.
 

793
00:45:33 --> 00:45:34
What's going on here?
 

794
00:45:34 --> 00:45:36
Well, on a path people are
walking all the time so the

795
00:45:36 --> 00:45:41
rocks die real young and
they never get to grow big.

796
00:45:41 --> 00:45:44
Whereas the rocks off the path
out in the mountains, they got

797
00:45:44 --> 00:45:46
to grow to be really big rocks.
 

798
00:45:46 --> 00:45:50
It's not a correct theory,
but you can see the kid

799
00:45:50 --> 00:45:52
using the data he's got.
 

800
00:45:52 --> 00:45:54
right, a certain
amount of data there.

801
00:45:54 --> 00:45:57
If I step on it, it dies.
 

802
00:45:57 --> 00:46:00
Maybe that's what happens to
rocks and people step more

803
00:46:00 --> 00:46:03
here than they step there,
so big rocks, little rocks.

804
00:46:03 --> 00:46:04
It all hangs together.
 

805
00:46:04 --> 00:46:06
I got a great theory here.
 

806
00:46:06 --> 00:46:09
 
 

807
00:46:09 --> 00:46:11
Another one, are rocks alive?
 

808
00:46:11 --> 00:46:12
Yes.
 

809
00:46:12 --> 00:46:13
Can they have babies?
 

810
00:46:13 --> 00:46:14
Yes.
 

811
00:46:14 --> 00:46:15
Are all rocks alive?
 

812
00:46:15 --> 00:46:16
No, some rocks are dead.
 

813
00:46:16 --> 00:46:19
How can you tell if
a rock is dead?

814
00:46:19 --> 00:46:22
Well, the dead ones
just lie there.

815
00:46:22 --> 00:46:28
This is capturing the notion
that motion is important in

816
00:46:28 --> 00:46:32
little kids' definitions of
the notion of aliveness.

817
00:46:32 --> 00:46:36
 
 

818
00:46:36 --> 00:46:38
I don't know how many rocks
you saw moving under

819
00:46:38 --> 00:46:40
their own power.
 

820
00:46:40 --> 00:46:44
In any case, you can see
the little scientist

821
00:46:44 --> 00:46:45
aspect of this.
 

822
00:46:45 --> 00:46:47
OK, so what's the
starting point here?

823
00:46:47 --> 00:46:50
 
 

824
00:46:50 --> 00:46:57
The concepts that you're
building seem to have some

825
00:46:57 --> 00:46:59
foundations that can be
picked up very early and

826
00:46:59 --> 00:47:01
are probably innate.
 

827
00:47:01 --> 00:47:04
I'll just talk about
two of them here.

828
00:47:04 --> 00:47:08
So concepts like about
things like aliveness.

829
00:47:08 --> 00:47:12
If you're going to decide that
a thing is alive, you need

830
00:47:12 --> 00:47:14
for starters to know
that it is a thing.

831
00:47:14 --> 00:47:19
So you need to have some
notion of an object.

832
00:47:19 --> 00:47:21
 
 

833
00:47:21 --> 00:47:26
The other thing you need is
some notion that objects,

834
00:47:26 --> 00:47:30
classes of objects, have
essences -- I think it's on the

835
00:47:30 --> 00:47:38
handout somewhere as -- towards
the bottom of page 2 says

836
00:47:38 --> 00:47:41
essence and there's a reference
of Susan Gelman's work on

837
00:47:41 --> 00:47:45
psychological essentialism --
the notion of an essence is a

838
00:47:45 --> 00:47:53
property that's not visible or
at least not currently visible.

839
00:47:53 --> 00:47:56
In order to have these sort of
category things, you've got to

840
00:47:56 --> 00:48:02
have the notion that objects
continue to have properties

841
00:48:02 --> 00:48:04
even if you can't see that.
 

842
00:48:04 --> 00:48:09
So, for example -- well, I
won't embarrass anybody -- but

843
00:48:09 --> 00:48:14
there are people here presently
who are not moving,

844
00:48:14 --> 00:48:17
who are not, to all
appearances, growing.

845
00:48:17 --> 00:48:20
I can't tell from this distance
whether they're made of cells

846
00:48:20 --> 00:48:21
and they don't appear to
be having babies or

847
00:48:21 --> 00:48:23
anything like that.
 

848
00:48:23 --> 00:48:29
Nevertheless, I assume
that they are alive.

849
00:48:29 --> 00:48:32
That's part of their essence.
 

850
00:48:32 --> 00:48:36
That this aliveness is
something that I attribute

851
00:48:36 --> 00:48:38
to that object without
being able to see it.

852
00:48:38 --> 00:48:43
Now what's the evidence that
little kids have that?

853
00:48:43 --> 00:48:46
Well, I'll tell you that and
then we'll have a break and

854
00:48:46 --> 00:48:49
then we'll go on to the problem
of egocentric behavior.

855
00:48:49 --> 00:48:57
 
 

856
00:48:57 --> 00:49:00
Let's start with evidence
that babies know

857
00:49:00 --> 00:49:04
something about objects.
 

858
00:49:04 --> 00:49:06
Here's a tube.
 

859
00:49:06 --> 00:49:08
If I was doing this right,
I'd show you that there's

860
00:49:08 --> 00:49:09
nothing in the tube.
 

861
00:49:09 --> 00:49:12
 
 

862
00:49:12 --> 00:49:26
And then I would take a stuffed
animal -- he's a duck.

863
00:49:26 --> 00:49:32
we take the duck and he's a
squishy duck, so I'm going

864
00:49:32 --> 00:49:34
to stuff him in the tube.
 

865
00:49:34 --> 00:49:37
 
 

866
00:49:37 --> 00:49:39
So the baby's watching all this
cool stuff happening here.

867
00:49:39 --> 00:49:42
There's little babies
watching this stuff.

868
00:49:42 --> 00:49:50
Then I take Nemo or whatever,
my little plush Nemo, and

869
00:49:50 --> 00:49:54
I stuff him in the tube.
 

870
00:49:54 --> 00:49:57
You with me so far babies?
 

871
00:49:57 --> 00:50:12
Now, I reach into the tube
and I pull out the fish.

872
00:50:12 --> 00:50:16
And you, being good
babies, stare at this.

873
00:50:16 --> 00:50:21
You say this is weird stuff
because I saw the duck go in

874
00:50:21 --> 00:50:26
first -- this is not quite
Spelke's experiment.

875
00:50:26 --> 00:50:28
I realize I'm getting the
methods a little screwed up

876
00:50:28 --> 00:50:30
but the principle is right.
 

877
00:50:30 --> 00:50:33
I saw the duck go in, then
the fish went in, and

878
00:50:33 --> 00:50:35
I know about objects.
 

879
00:50:35 --> 00:50:39
Objects do not interpenetrate.
 

880
00:50:39 --> 00:50:43
Objects are solid things.
 

881
00:50:43 --> 00:50:48
If the fish is out here,
where'd the duck go?

882
00:50:48 --> 00:50:50
Spelke's done a series of
experiments like this that

883
00:50:50 --> 00:50:55
suggest that kids know about
object -- babies, young

884
00:50:55 --> 00:50:58
babies, as early as you can
successfully test them, so

885
00:50:58 --> 00:51:02
getting very close to being at
the starting point -- know

886
00:51:02 --> 00:51:07
about objects, and know a few
things about those objects.

887
00:51:07 --> 00:51:10
Notably things like that
objects don't interpenetrate.

888
00:51:10 --> 00:51:13
They don't know everything
about objects, so they don't,

889
00:51:13 --> 00:51:17
for instance, if you set up
some fish and ducky kind of

890
00:51:17 --> 00:51:22
thing that violates the law of
gravity, kid doesn't care.

891
00:51:22 --> 00:51:24
They don't seem to be
particularly sensitive

892
00:51:24 --> 00:51:25
to gravity.
 

893
00:51:25 --> 00:51:29
Yet a two-year old in his high
chair -- two-year old in the

894
00:51:29 --> 00:51:32
high chair thinks
gravity's great.

895
00:51:32 --> 00:51:34
Here's the hot dog.
 

896
00:51:34 --> 00:51:38
OK, so dad picks up the hot dog
and puts it back on the plate

897
00:51:38 --> 00:51:41
and the kid drops it again,
because he's a little

898
00:51:41 --> 00:51:44
scientist, right, you gotta
check that gravity is still

899
00:51:44 --> 00:51:47
-- you'll get there.
 

900
00:51:47 --> 00:51:52
Marrah knows about gravity
but her baby doesn't

901
00:51:52 --> 00:51:52
know about it yet.
 

902
00:51:52 --> 00:51:55
Her baby looks at gravity
demonstrations and says

903
00:51:55 --> 00:51:56
this is really boring.
 

904
00:51:56 --> 00:52:01
But her baby knows that
the fish cannot go

905
00:52:01 --> 00:52:03
through the duck.
 

906
00:52:03 --> 00:52:07
It just would be bad
news for the duck.

907
00:52:07 --> 00:52:09
Babies don't care
about inertia either.

908
00:52:09 --> 00:52:12
Things like object in
motion continue in motion

909
00:52:12 --> 00:52:13
unless acted on by--.
 

910
00:52:13 --> 00:52:16
Tell that to a baby, the
baby says yeah, right.

911
00:52:16 --> 00:52:17
Don't care about that.
 

912
00:52:17 --> 00:52:22
But I know that that fish does
not go through the duck.

913
00:52:22 --> 00:52:24
So that's this
notion of objects.

914
00:52:24 --> 00:52:25
What about essence?
 

915
00:52:25 --> 00:52:32
Well essence is harder to
get to in early childhood.

916
00:52:32 --> 00:52:35
It's harder to ask the
question, but by the time you

917
00:52:35 --> 00:52:42
get to -- how old are we in
this experiment -- you're

918
00:52:42 --> 00:52:44
like two or three years
old, but you're doing

919
00:52:44 --> 00:52:45
something like this.
 

920
00:52:45 --> 00:52:53
You take the duck and you say
see this duck, what we're going

921
00:52:53 --> 00:52:55
to do is we're going to do
an operation on the duck.

922
00:52:55 --> 00:52:58
I promise it's not going
to hurt the duck.

923
00:52:58 --> 00:53:00
But we're going to take off
his skin and we're going to

924
00:53:00 --> 00:53:03
put raccoon skin on him.
 

925
00:53:03 --> 00:53:05
He's going to look
just like a raccoon.

926
00:53:05 --> 00:53:11
 
 

927
00:53:11 --> 00:53:15
OK, is this a duck
or a raccoon?

928
00:53:15 --> 00:53:17
As soon as the kid can
meaningfully answer the

929
00:53:17 --> 00:53:20
question for you, to kid
will say that's a duck.

930
00:53:20 --> 00:53:23
I mean you dressed him up like
a raccoon but he's a duck.

931
00:53:23 --> 00:53:26
Inside he's got duck essence --
he doesn't say anything about

932
00:53:26 --> 00:53:30
duck essence, but he knows that
there's a core of duckness that

933
00:53:30 --> 00:53:34
is not dependent on looking
exactly like a duck.

934
00:53:34 --> 00:53:40
 
 

935
00:53:40 --> 00:53:44
How many of you are familiar
with the classic Pepe

936
00:53:44 --> 00:53:47
Le Pew cartoons?
 

937
00:53:47 --> 00:53:49
Yeah, it's Cartoon
Network stuff.

938
00:53:49 --> 00:53:51
The basic plot, there's a whole
bunch of these, but the basic

939
00:53:51 --> 00:53:52
plot is always the same.
 

940
00:53:52 --> 00:54:01
Pepe Le Pew is a French
skunk, a French lover skunk.

941
00:54:01 --> 00:54:07
And this cat, female cat, gets
a white stripe down her back by

942
00:54:07 --> 00:54:11
some paint or something like
that and Pepe spends the next

943
00:54:11 --> 00:54:15
five minutes of the cartoon
chasing her around trying to

944
00:54:15 --> 00:54:17
get her to fall in love and she
doesn't want to fall in love

945
00:54:17 --> 00:54:20
because she knows he's a skunk
and she knows that

946
00:54:20 --> 00:54:20
she's not a skunk.
 

947
00:54:20 --> 00:54:24
What's funny about this, the
reason this is funny for little

948
00:54:24 --> 00:54:28
kids, is that little kids know
that the fact that she's got a

949
00:54:28 --> 00:54:32
white stripe down her doesn't
make her into a skunk.

950
00:54:32 --> 00:54:36
She's still a cat who happens
to look like a skunk and isn't

951
00:54:36 --> 00:54:40
that funny because the skunk is
chasing around after her and

952
00:54:40 --> 00:54:42
getting hit in the head with
bats and stuff like that, and

953
00:54:42 --> 00:54:46
all the good things that
happen in cartoons.

954
00:54:46 --> 00:54:50
So, not only do kids know that
things have an essence like

955
00:54:50 --> 00:54:55
that, they are also, to be a
little recursive here, they're

956
00:54:55 --> 00:54:58
innate nativists it appears.
 

957
00:54:58 --> 00:55:01
They believe that these
properties came with the

958
00:55:01 --> 00:55:03
system and were not learned.
 

959
00:55:03 --> 00:55:07
So, Susan Gelman did a clever
experiment where what she did

960
00:55:07 --> 00:55:13
was she said, see
this kangaroo?

961
00:55:13 --> 00:55:18
Take this kangaroo -- this is a
baby kangaroo, it's a newborn

962
00:55:18 --> 00:55:21
kangaroo, and you know what
we're going to do, we're going

963
00:55:21 --> 00:55:25
to take care her and we're
going to give her to the goats

964
00:55:25 --> 00:55:30
and she's going to get
raised by the goats.

965
00:55:30 --> 00:55:32
Now she's all grown up.
 

966
00:55:32 --> 00:55:35
Let me ask you a few
questions about her.

967
00:55:35 --> 00:55:38
Does she have a pouch?
 

968
00:55:38 --> 00:55:41
Well, yeah sure, that's
pretty straightforward.

969
00:55:41 --> 00:55:42
That's not the
interesting question.

970
00:55:42 --> 00:55:46
The interesting question
is is she going to be

971
00:55:46 --> 00:55:49
hopper or a climber?
 

972
00:55:49 --> 00:55:54
And little kids -- two, three
year old kids will say

973
00:55:54 --> 00:55:57
it's going to be a hopper.
 

974
00:55:57 --> 00:56:01
 
 

975
00:56:01 --> 00:56:05
It was a kangaroo at
birth, kangaroo's hop.

976
00:56:05 --> 00:56:06
It's part of their essence.
 

977
00:56:06 --> 00:56:13
The fact that she lived
with the goats isn't

978
00:56:13 --> 00:56:15
going to change that.
 

979
00:56:15 --> 00:56:21
This is the amusement value
of the Disney Tarzan

980
00:56:21 --> 00:56:22
cartoon, right.
 

981
00:56:22 --> 00:56:26
Tarzan gets raised
by the gorillas.

982
00:56:26 --> 00:56:29
Have you seen that?
 

983
00:56:29 --> 00:56:30
Oh man, when did that come out?
 

984
00:56:30 --> 00:56:33
 
 

985
00:56:33 --> 00:56:36
I got to calibrate
my Disneyness here.

986
00:56:36 --> 00:56:38
Which Disney movies came
out when you were of

987
00:56:38 --> 00:56:40
an age to watch them?
 

988
00:56:40 --> 00:56:42
AUDIENCE: Alladin.
 

989
00:56:42 --> 00:56:43
PROFESSOR: Alladin.
 

990
00:56:43 --> 00:56:46
Oh, you were too old
when Tarzan came out.

991
00:56:46 --> 00:56:49
 
 

992
00:56:49 --> 00:56:54
You're the Alladin cohort.
 

993
00:56:54 --> 00:56:56
Jungle Book came out
when I was a kid.

994
00:56:56 --> 00:56:59
Well, no not quite.
 

995
00:56:59 --> 00:57:02
 
 

996
00:57:02 --> 00:57:04
The ones that came out when I
was a kid were things like

997
00:57:04 --> 00:57:08
Sword and the Stone, I
thought that was great.

998
00:57:08 --> 00:57:10
That was good stuff.
 

999
00:57:10 --> 00:57:13
And don't claim that I was
a kid when Snow White came

1000
00:57:13 --> 00:57:14
out -- that was my father.
 

1001
00:57:14 --> 00:57:17
 
 

1002
00:57:17 --> 00:57:26
So, Jungle Book works, right,
and you get raised by the wild

1003
00:57:26 --> 00:57:32
animals, but you're essentially
a human and that eventually

1004
00:57:32 --> 00:57:35
catches up with you.
 

1005
00:57:35 --> 00:57:42
Actually, kids are incorrect
nativists because they believe

1006
00:57:42 --> 00:57:44
things that turn out -- and
it's true that the kangaroo

1007
00:57:44 --> 00:57:50
will probably hop even if
it gets raised by a goat.

1008
00:57:50 --> 00:57:57
But suppose we have here a
Chinese baby and we take this

1009
00:57:57 --> 00:58:03
Chinese baby and we bring
it to the United States and

1010
00:58:03 --> 00:58:06
it's raised in California.
 

1011
00:58:06 --> 00:58:09
 
 

1012
00:58:09 --> 00:58:14
When that kid grows up, will
she be able to speak Chinese?

1013
00:58:14 --> 00:58:15
It depends on the--.
 

1014
00:58:15 --> 00:58:15
What?
 

1015
00:58:15 --> 00:58:16
AUDIENCE: [INAUDIBLE].
 

1016
00:58:16 --> 00:58:19
 
 

1017
00:58:19 --> 00:58:21
PROFESSOR: It depends
on the neighborhood.

1018
00:58:21 --> 00:58:26
But kids aren't quite clear
on these demographic

1019
00:58:26 --> 00:58:27
issues in the same way.
 

1020
00:58:27 --> 00:58:33
But a little kid will figure
incorrectly that language is

1021
00:58:33 --> 00:58:35
one of these essential
properties.

1022
00:58:35 --> 00:58:38
That if you're Chinese, that
means you can speak --

1023
00:58:38 --> 00:58:39
you might be able to
speak English, too.

1024
00:58:39 --> 00:58:41
You could learn that, they
can figure that out.

1025
00:58:41 --> 00:58:46
But you'd have a privileged
ability to speak Chinese

1026
00:58:46 --> 00:58:50
because after all, you
were a Chinese kid and

1027
00:58:50 --> 00:58:51
that ought to work.
 

1028
00:58:51 --> 00:58:56
If you're a Chinese kids who
grew up in an Anglo linguistic

1029
00:58:56 --> 00:58:58
environment, you may have
discovered that there were

1030
00:58:58 --> 00:59:00
plenty of your relatives who
also thought you should be

1031
00:59:00 --> 00:59:04
able to speak Chinese, but
that's a different issue.

1032
00:59:04 --> 00:59:09
In any case, little kids start
certainly with the notion of

1033
00:59:09 --> 00:59:15
objectness and probably quite
early with the notion that

1034
00:59:15 --> 00:59:19
objects have essences, and then
they bild on that in this

1035
00:59:19 --> 00:59:26
little scientist kind of a way
to get closer and closer to

1036
00:59:26 --> 00:59:29
what we consider to be the
adult concept of whatever,

1037
00:59:29 --> 00:59:37
alive or kangaroo or any
of those sorts of things.

1038
00:59:37 --> 00:59:40
Here's the case where the adult
state is not particularly

1039
00:59:40 --> 00:59:46
fixed, but we're nevertheless,
what you're doing is you're

1040
00:59:46 --> 00:59:49
elaborating on juvenile
concepts, not suddenly

1041
00:59:49 --> 00:59:51
discovering the notion
that there is such a

1042
00:59:51 --> 00:59:54
thing as a concept.
 

1043
00:59:54 --> 00:59:58
OK, I want to do egocentrism
still, but I will start doing

1044
00:59:58 --> 00:59:59
that when that thing says 3:10.
 

1045
00:59:59 --> 01:03:16
BREAK IN LECTURE
 

1046
01:03:16 --> 01:03:18
Let us talk about egocentrism.
 

1047
01:03:18 --> 01:03:25
So, you will recall that the
basic problem here was that the

1048
01:03:25 --> 01:03:29
kid seemed unable to take the
point of view of another, in

1049
01:03:29 --> 01:03:32
this case, the mother on the
other side of this table.

1050
01:03:32 --> 01:03:38
The kid asked about things like
the river and the hut, claimed

1051
01:03:38 --> 01:03:41
that the mom could see them,
even though mom couldn't see

1052
01:03:41 --> 01:03:43
them, only the kid
could see them.

1053
01:03:43 --> 01:03:46
 
 

1054
01:03:46 --> 01:03:50
You can get kids to perform
quite well on this task if you

1055
01:03:50 --> 01:03:55
come from like Nebraska instead
of coming from the Alps.

1056
01:03:55 --> 01:04:02
So, in one version of this
experiment -- so I think

1057
01:04:02 --> 01:04:06
the answer is that four
year olds failed this.

1058
01:04:06 --> 01:04:11
You can get three-year olds to
be successful in an equivalent

1059
01:04:11 --> 01:04:16
task, if what you do is just
simplify the situation.

1060
01:04:16 --> 01:04:18
So there's a version of this
that may have a picture in the

1061
01:04:18 --> 01:04:22
book still, I don't remember,
of sort of a city block with a

1062
01:04:22 --> 01:04:26
car in it and a Sesame
Street character.

1063
01:04:26 --> 01:04:29
You drive Grover around the
block or something and

1064
01:04:29 --> 01:04:32
ask questions about that
much simpler situation.

1065
01:04:32 --> 01:04:38
Then the kid can successfully
answer questions from the

1066
01:04:38 --> 01:04:45
vantage point of the mother, as
if part of the issue here was

1067
01:04:45 --> 01:04:48
that the task was just
too complicated.

1068
01:04:48 --> 01:04:50
Oh, I never mentioned the M&M's
are under there somewhere.

1069
01:04:50 --> 01:04:52
I never mentioned well
why is that the kids

1070
01:04:52 --> 01:04:53
bombed the M&M task.
 

1071
01:04:53 --> 01:04:59
That seems to be an issue where
you're asking kids who haven't

1072
01:04:59 --> 01:05:03
gotten to the successful
counting stage to do this and

1073
01:05:03 --> 01:05:05
they can't do it either with
the numerosity or the

1074
01:05:05 --> 01:05:07
subitizing piece, so
they fail the task.

1075
01:05:07 --> 01:05:11
If you make the M&M task, if
you put that into either the

1076
01:05:11 --> 01:05:14
numerosity range or the
subitizing range, little kids

1077
01:05:14 --> 01:05:16
will succeed in doing the task.
 

1078
01:05:16 --> 01:05:20
So if you say would you rather
have this pile with two M&Ms

1079
01:05:20 --> 01:05:24
or three M&Ms, little
kids don't bomb that.

1080
01:05:24 --> 01:05:28
They bomb five versus six
or six versus eight,

1081
01:05:28 --> 01:05:29
things like that.
 

1082
01:05:29 --> 01:05:32
And a similar sort of thing
seems to be going on here that

1083
01:05:32 --> 01:05:37
the task is in some fashion a
little too complicated

1084
01:05:37 --> 01:05:37
for them.
 

1085
01:05:37 --> 01:05:39
How far can we push this back?
 

1086
01:05:39 --> 01:05:43
Well, if you take two year
olds, suppose you take two

1087
01:05:43 --> 01:05:46
year olds and you give
them a pair of sunglasses.

1088
01:05:46 --> 01:05:49
Put the sunglasses on the kid,
kid looks around for a while.

1089
01:05:49 --> 01:05:52
Now we take the sunglasses,
they may have been

1090
01:05:52 --> 01:05:53
mirrored shades even.
 

1091
01:05:53 --> 01:05:59
Put the sunglasses on mommy and
you ask can mommy see you?

1092
01:05:59 --> 01:06:02
Well, you can't see mommy's
eyes anymore because of the

1093
01:06:02 --> 01:06:05
glasses, but the kid, even a
two year old will be able to

1094
01:06:05 --> 01:06:08
say yes, indeed mommy can see
me, even though I cannot

1095
01:06:08 --> 01:06:09
see mommy's eyes.
 

1096
01:06:09 --> 01:06:13
Normally, if mommy is doing
this, it's a pretty good bet

1097
01:06:13 --> 01:06:15
that mommy can't see you.
 

1098
01:06:15 --> 01:06:19
That's the root of a lot
of entertaining games.

1099
01:06:19 --> 01:06:28
But they can manage to
solve the problem, if it's

1100
01:06:28 --> 01:06:34
simplified to the point of
sunglasses on or off.

1101
01:06:34 --> 01:06:39
This if I can see you, can you
see me thing, you can see, as

1102
01:06:39 --> 01:06:44
you get more and more
complicated, that it takes you

1103
01:06:44 --> 01:06:47
longer and longer to solve the
more and more complicated

1104
01:06:47 --> 01:06:49
versions of it.
 

1105
01:06:49 --> 01:06:52
You don't remember what it was
like to be thinking when you

1106
01:06:52 --> 01:06:55
were a two year old, but you
may remember a stage later in

1107
01:06:55 --> 01:07:00
your life when it was not clear
to you how mirrors worked.

1108
01:07:00 --> 01:07:04
That if a can see b, b
can see a in a mirror.

1109
01:07:04 --> 01:07:08
This is the sort of
thing that amuses early

1110
01:07:08 --> 01:07:10
school age kids often.
 

1111
01:07:10 --> 01:07:11
I can see around the corner.
 

1112
01:07:11 --> 01:07:14
I can see dad around
the corner there.

1113
01:07:14 --> 01:07:18
I bet he can't see me, and it
comes as a shock that dad can

1114
01:07:18 --> 01:07:22
see you, because the mirror
kind of works both ways, and

1115
01:07:22 --> 01:07:26
then there are more complicated
arrangements with keyholes and

1116
01:07:26 --> 01:07:30
stuff like that where it takes
even longer to be able to take

1117
01:07:30 --> 01:07:31
the point of the person
on the other side.

1118
01:07:31 --> 01:07:38
So, some aspect of this is
simply a matter of complexity.

1119
01:07:38 --> 01:07:42
In fact, Paul Bloom and his
student -- actually, I should

1120
01:07:42 --> 01:07:45
mention Paul Bloom is
married to Karen Wynn.

1121
01:07:45 --> 01:07:50
They were both TAs for this
course and are now both

1122
01:07:50 --> 01:07:51
professors at Yale.
 

1123
01:07:51 --> 01:07:54
Anyway, Paul works on similar
sorts of problems and

1124
01:07:54 --> 01:07:58
talks about the curse of
knowledge that shows up

1125
01:07:58 --> 01:08:00
in adult behavior, too.
 

1126
01:08:00 --> 01:08:03
That it's very difficult, it's
often very difficult to

1127
01:08:03 --> 01:08:09
remember that somebody else
doesn't know what you know.

1128
01:08:09 --> 01:08:16
So, it's a problem
for me teaching.

1129
01:08:16 --> 01:08:18
The things that are hardest to
teach are the things that I

1130
01:08:18 --> 01:08:19
don't know anything about.
 

1131
01:08:19 --> 01:08:20
That's not surprising.
 

1132
01:08:20 --> 01:08:23
The second hardest category are
things that I know too much

1133
01:08:23 --> 01:08:28
about, because it's hard to
remember how little you

1134
01:08:28 --> 01:08:29
know about vision.
 

1135
01:08:29 --> 01:08:33
How can it be that you haven't
actually spent the last 18

1136
01:08:33 --> 01:08:39
years of your life bathed
in visual phenomenology.

1137
01:08:39 --> 01:08:41
You can try using that
as an excuse on the

1138
01:08:41 --> 01:08:42
exam but forget it.
 

1139
01:08:42 --> 01:08:44
We'll still take
the points off.

1140
01:08:44 --> 01:08:48
That turns out to be an example
of the curse of knowledge.

1141
01:08:48 --> 01:08:53
Or another example would be if
you've ever been giving

1142
01:08:53 --> 01:08:56
somebody directions while
you're sitting next to them in

1143
01:08:56 --> 01:09:00
the car, you might discover
that you go past the street

1144
01:09:00 --> 01:09:01
where they were supposed to
turn because you knew you were

1145
01:09:01 --> 01:09:05
supposed to turn there, and you
just kind of forgot that they

1146
01:09:05 --> 01:09:07
wouldn't know that and that's
why you were sitting there

1147
01:09:07 --> 01:09:10
supposedly giving
them directions.

1148
01:09:10 --> 01:09:14
It's hard, even for
adults necessarily.

1149
01:09:14 --> 01:09:17
It's hard for adults sometimes
to take the vantage

1150
01:09:17 --> 01:09:22
point of another person.
 

1151
01:09:22 --> 01:09:31
Now one of the great examples
of this in kid behavior, a

1152
01:09:31 --> 01:09:34
paradigm that's yielded an
awful lot of research.

1153
01:09:34 --> 01:09:37
This gives you some insight
into this, if you like this

1154
01:09:37 --> 01:09:40
curse of knowledge problem,
is what's known as the

1155
01:09:40 --> 01:09:44
false beliefs task.
 

1156
01:09:44 --> 01:09:47
The first false belief you
need is that this is Big

1157
01:09:47 --> 01:09:51
Bird from Sesame Street.
 

1158
01:09:51 --> 01:09:57
So here's how a typical false
belief task experiment

1159
01:09:57 --> 01:09:59
might work.
 

1160
01:09:59 --> 01:10:00
You're watching this.
 

1161
01:10:00 --> 01:10:06
Big Bird comes in to the
scene and he has candy.

1162
01:10:06 --> 01:10:13
He puts the candy in the
refrigerator and he goes out.

1163
01:10:13 --> 01:10:17
 
 

1164
01:10:17 --> 01:10:25
Now, I didn't draw Grover or
whatever, but Grover comes

1165
01:10:25 --> 01:10:30
in, takes the candy out of
the refrigerator and

1166
01:10:30 --> 01:10:34
puts in the drawer.
 

1167
01:10:34 --> 01:10:38
Now, Big Bird comes back
in -- he didn't see

1168
01:10:38 --> 01:10:40
this abut you saw this.
 

1169
01:10:40 --> 01:10:46
Big Bird comes back in and
you are asked where will Big

1170
01:10:46 --> 01:10:49
Bird look for the candy?
 

1171
01:10:49 --> 01:10:54
And your answer, if you're like
a four year old, is that Big

1172
01:10:54 --> 01:10:56
Bird will look in the drawer.
 

1173
01:10:56 --> 01:11:03
You cannot somehow access the
fact that Big Bird thinks

1174
01:11:03 --> 01:11:12
in his brain that the
candy's in the fridge.

1175
01:11:12 --> 01:11:18
When you updated your knowledge
about the candy, you updated

1176
01:11:18 --> 01:11:25
his knowledge about the
candy, too, in some fashion.

1177
01:11:25 --> 01:11:30
Now there are endless
versions of this experiment.

1178
01:11:30 --> 01:11:36
This is a task that younger
than four will fail, older than

1179
01:11:36 --> 01:11:40
four roughly will tend to get.
 

1180
01:11:40 --> 01:11:43
There are endless tasks that
look at this and try to break

1181
01:11:43 --> 01:11:47
it apart, see what's going on
here in developing this ability

1182
01:11:47 --> 01:11:53
to take into account what is in
the mind of another person or

1183
01:11:53 --> 01:11:57
bird, as the case may be.
 

1184
01:11:57 --> 01:12:00
This is sometimes talked about
as mind reading and is

1185
01:12:00 --> 01:12:05
sometimes described as the
major social problem in autism.

1186
01:12:05 --> 01:12:11
That maybe one of the reasons
that autistic kids and adults

1187
01:12:11 --> 01:12:17
have a real problem relating to
other people is an inability to

1188
01:12:17 --> 01:12:22
understand that other people
have mental states, which you

1189
01:12:22 --> 01:12:27
have that ability, but here,
you as a four year old, have

1190
01:12:27 --> 01:12:31
failed to manage to keep track
of Big Bird's mental state.

1191
01:12:31 --> 01:12:34
Let's do a variation on this.
 

1192
01:12:34 --> 01:12:37
So, here's a variation
where you don't see

1193
01:12:37 --> 01:12:38
that initial scene.
 

1194
01:12:38 --> 01:12:43
 
 

1195
01:12:43 --> 01:12:50
Now you are asked to
guess -- the candy is

1196
01:12:50 --> 01:12:53
either here or here.
 

1197
01:12:53 --> 01:12:58
Where do you think that
the candy might be?

1198
01:12:58 --> 01:13:01
Well, you say 50/50.
 

1199
01:13:01 --> 01:13:04
Oh, I think the candy's
in the drawer.

1200
01:13:04 --> 01:13:08
OK, now Big Bird comes in and
you're told well, you know, Big

1201
01:13:08 --> 01:13:09
Bird thinks it's in the fridge.
 

1202
01:13:09 --> 01:13:12
 
 

1203
01:13:12 --> 01:13:15
Where's Big Bird going to look?
 

1204
01:13:15 --> 01:13:18
The answer now is, even if
you're as young as three, that

1205
01:13:18 --> 01:13:22
you say Big Bird's going
to look in the fridge.

1206
01:13:22 --> 01:13:28
Your guess isn't strong enough
to overwrite your understanding

1207
01:13:28 --> 01:13:29
of what's going on
in Big Bird's head.

1208
01:13:29 --> 01:13:30
This tells you
something important.

1209
01:13:30 --> 01:13:38
This tells you immediately that
you're capable of understanding

1210
01:13:38 --> 01:13:41
something about the contents
of Big Bird's head.

1211
01:13:41 --> 01:13:45
It's not a complete
blank to you.

1212
01:13:45 --> 01:13:50
Even younger than that, little
kids can see somebody playing

1213
01:13:50 --> 01:13:55
with a banana pretending it's a
phone, right, and you ask does

1214
01:13:55 --> 01:13:59
he know that it's not a phone?
 

1215
01:13:59 --> 01:13:59
Yeah, yeah.
 

1216
01:13:59 --> 01:14:02
The two year old will tell you,
yeah, he's just pretending.

1217
01:14:02 --> 01:14:05
And that you have the notion
that somebody else could

1218
01:14:05 --> 01:14:10
pretend to pretend something.
 

1219
01:14:10 --> 01:14:12
So again, you can push this
notion of being able to

1220
01:14:12 --> 01:14:17
read minds back earlier
if it gets simpler.

1221
01:14:17 --> 01:14:21
And maybe this isn't really
about the contents of

1222
01:14:21 --> 01:14:23
Big Bird's mind it all.
 

1223
01:14:23 --> 01:14:25
Here's a cute version of
the experiment done by

1224
01:14:25 --> 01:14:26
Debbie [? Zicheck ?]
 

1225
01:14:26 --> 01:14:28
once upon a time.
 

1226
01:14:28 --> 01:14:33
Big Bird comes in, it's the
original false belief game. big

1227
01:14:33 --> 01:14:38
Bird comes in, puts the candy
in the fridge, but this time

1228
01:14:38 --> 01:14:42
Big Bird takes out his camera
and he photographs it.

1229
01:14:42 --> 01:14:48
He's got a picture of it.
 

1230
01:14:48 --> 01:14:51
There's the candy
in the fridge.

1231
01:14:51 --> 01:14:58
Now, Big Bird goes out and
Grover comes in, moves the

1232
01:14:58 --> 01:15:01
candy to the drawer, you
now know that the candy

1233
01:15:01 --> 01:15:02
is in the drawer.
 

1234
01:15:02 --> 01:15:05
Big Bird comes in, you are
asked where's Big Bird going

1235
01:15:05 --> 01:15:07
to look for the candy?
 

1236
01:15:07 --> 01:15:11
Even though Big Bird has taken
a picture of it, even though

1237
01:15:11 --> 01:15:15
there's now a physical
instantiation of the contents

1238
01:15:15 --> 01:15:18
of Big Bird's mind, you still
say it's in the drawer.

1239
01:15:18 --> 01:15:20
You as a four year old
are still unable to

1240
01:15:20 --> 01:15:22
keep track of this.
 

1241
01:15:22 --> 01:15:26
This suggests that maybe the
problem is less with your

1242
01:15:26 --> 01:15:30
ability to see into somebody
else's mind, and more with

1243
01:15:30 --> 01:15:34
something like the capacity
of your working memory.

1244
01:15:34 --> 01:15:36
So, if you think about it
this is very parallel

1245
01:15:36 --> 01:15:37
to [? Lofta's ?]
 

1246
01:15:37 --> 01:15:38
experiment I talked about
either last time or

1247
01:15:38 --> 01:15:40
the time before.
 

1248
01:15:40 --> 01:15:42
You see somebody go
through a yield sign.

1249
01:15:42 --> 01:15:48
You later hear that it was a
stop sign, and you believe, you

1250
01:15:48 --> 01:15:51
come to have a false memory or
a false belief, if you like,

1251
01:15:51 --> 01:15:54
that it really was a stop sign,
because we've managed to

1252
01:15:54 --> 01:15:57
somehow overwrite
your memory here.

1253
01:15:57 --> 01:16:02
Maybe in this case what you're
dealing with is not a

1254
01:16:02 --> 01:16:06
qualitative change where you're
seeing a change in the ability

1255
01:16:06 --> 01:16:09
to see into somebody else's
mind, but a big enough working

1256
01:16:09 --> 01:16:13
memory that you can keep
track of the task.

1257
01:16:13 --> 01:16:19
So, another case where the
development here waits on the

1258
01:16:19 --> 01:16:23
development of another ability,
a separate ability in this

1259
01:16:23 --> 01:16:26
case, working memory.
 

1260
01:16:26 --> 01:16:29
OK, that's as good a
place to stop as any.

1261
01:16:29 --> 01:16:31