When you're making a deal, what's going on in your brain?

When two people are trying to make a deal -- whether they’re competing or cooperating -- what’s really going on inside their brains? Behavioral economist Colin Camerer shows research that reveals just how little we’re able to predict what others are thinking. And he presents an unexpected study that shows chimpanzees might just be better at it than we are. (Filmed at TEDxCalTech.)

I'm going to talk
about the strategizing brain.

We're going to use
an unusual combination of tools

from game theory and neuroscience

to understand how people interact socially
when value is on the line.

So game theory is a branch
of, originally, applied mathematics,

used mostly in economics
and political science,

a little bit in biology,

that gives us a mathematical
taxonomy of social life

and it predicts
what people are likely to do

and believe others will do

in cases where everyone's actions
affect everyone else.

That's a lot of things:
competition, cooperation, bargaining,

games like hide-and-seek and poker.

Here's a simple game to get us started.

Everyone chooses a number
from zero to 100,

we're going to compute
the average of those numbers,

and whoever's closest to two-thirds
of the average wins a fixed prize.

So you want to be
a little bit below the average number,

but not too far below,

and everyone else wants to be

a little bit below
the average number as well.

Think about what you might pick.

As you're thinking,

this is a toy model of something
like selling in the stock market

during a rising market. Right?

You don't want to sell too early
and miss out on profits,

but you don't want to wait too late

to when everyone else sells,
triggering a crash.

You want to be a little bit
ahead of the competition,

but not too far ahead.

OK, here's two theories
about how people might think about this,

then we'll see some data.

Some of these will sound familiar

because you probably
are thinking that way.

I'm using my brain theory to see.

A lot of people say, "I really don't know
what people are going to pick,

so I think the average will be 50."

They're not being really strategic at all.

"And I'll pick two-thirds of 50.
That's 33." That's a start.

Other people who are
a little more sophisticated,

using more working memory,

say, "I think people will pick 33

because they're going to pick
a response to 50,

and so I'll pick 22,
which is two-thirds of 33."

They're doing one extra step
of thinking, two steps.

That's better.

And in principle,
you could do three, four or more,

but it starts to get very difficult.

Just like in language and other domains,

we know it's hard for people
to parse very complex sentences

with a recursive structure.

This is called the cognitive
hierarchy theory.

It's something that I've worked on
and a few other people,

and it indicates a hierarchy
along with some assumptions

about how many people
stop at different steps

and how the steps of thinking are affected
by lots of interesting variables

and variant people,
as we'll see in a minute.

A very different theory,
a much more popular one, and an older one,

due largely to John Nash
of "A Beautiful Mind" fame,

is what's called equilibrium analysis.

So if you've ever taken
a game theory course at any level,

you will have learned
a little bit about this.

An equilibrium is a mathematical state

in which everybody has figured out
exactly what everyone else will do.

It is a very useful concept,

but behaviorally, it may not
exactly explain what people do

the first time they play
these types of economic games

or in situations in the outside world.

In this case, the equilibrium
makes a very bold prediction,

which is everyone wants
to be below everyone else,

therefore they'll play zero.

Let's see what happens.

This experiment's been done
many, many times.

Some of the earliest ones
were done in the '90s

by me and Rosemarie Nagel and others.

This is a beautiful data set
of 9,000 people

who wrote in to three newspapers
and magazines that had a contest.

The contest said, send in your numbers

and whoever is closer to two-thirds
of the average will win a big prize.

And as you can see,
there's so much data here,

you can see the spikes very visibly.

There's a spike at 33.
Those are people doing one step.

There is another spike visible at 22.

And notice that most people
pick numbers right around there.

They don't necessarily pick
exactly 33 and 22.

There's something
a little bit noisy around it.

But you can see those spikes.

There's another group of people

who seem to have
a firm grip on equilibrium analysis,

because they're picking zero or one.

But they lose, right?

Because picking a number that low
is actually a bad choice

if other people aren't
doing equilibrium analysis as well.

So they're smart, but poor.

(Laughter)

Where are these things
happening in the brain?

One study by Coricelli and Nagel
gives a really sharp, interesting answer.

So they had people play this game
while they were being scanned in an fMRI,

and two conditions:
in some trials, they're told

you're playing another person
who's playing right now

and we're going to match up your behavior
and pay you if you win.

In the other trials, they're told,
you're playing a computer.

They're just choosing randomly.

So what you see
here is a subtraction of areas

in which there's more brain activity
when you're playing people

compared to playing the computer.

And you see activity
in some regions we've seen today,

medial prefrontal cortex,
dorsomedial, up here,

ventromedial prefrontal cortex,
anterior cingulate,

an area that's involved
in lots of types of conflict resolution,

like if you're playing "Simon Says,"

and also the right and left
temporoparietal junction.

And these are all areas
which are fairly reliably known

to be part of what's called
a "theory of mind" circuit,

or "mentalizing circuit."

That is, it's a circuit that's used
to imagine what other people might do.

So these were some
of the first studies to see this

tied in to game theory.

What happens with these
one- and two-step types?

So we classify people by what they picked

and then we look at the difference between
playing humans versus playing computers,

which brain areas
are differentially active.

On the top you see the one-step players.
Almost no difference.

They're treating other people
like a computer, and the brain is too.

The bottom players, you see
all the activity in dorsomedial PFC.

So those two-step players
are doing something differently.

You could say, "What can we do
with this information?"

You might be able to say,

"This person's going to be
a good poker player,"

or, "This person's socially naive,"

and we might also be able to study things

like development of adolescent brains

once we have an idea
of where this circuitry exists.

OK. Get ready.

I'm saving you some brain activity,

because you don't need
to use your hair detector cells.

You should use those cells
to think carefully about this game.

This is a bargaining game.

Two players who are being scanned
using EEG electrodes

are going to bargain
over one to six dollars.

If they can do it in 10 seconds,
they're going to actually earn that money.

If they don't make a deal,
they get nothing.

That's a mistake together.

The twist is that one player, on the left,

is informed about how much
on each trial there is.

They play lots of trials
with different amounts each time.

In this case, they know
there's four dollars.

The uninformed player doesn't know,
but they know the informed player knows.

So the uninformed player's
challenge is to say,

"Is this guy really being fair
or are they giving me a very low offer

in order to get me to think

that there's only one
or two dollars available to split?"

In which case they might reject it
and not come to a deal.

So there's some tension
between trying to get the most money

but trying to goad the other player
into giving you more.

And the way they bargain
is to point on a number line

that goes from zero to six dollars,

and they're bargaining
over how much the uninformed player gets,

and the informed player gets the rest.

So this is like
a management-labor negotiation

in which the workers don't know

how much profits
the privately held company has,

and they want to maybe
hold out for more money,

but the company might want
to create the impression

that there's little to split:
"I'm giving you the most that I can."

First some behavior.

So a bunch of the subject pairs
play face to face.

We have other data
where they play across computers.

That's an interesting difference.

But a bunch of the face-to-face pairs

agree to divide the money evenly
every single time.

Boring. It's just
not interesting neurally.

It's good for them.
They make a lot of money.

But we're interested in,

can we say something about when
disagreements occur versus don't occur?

So this is the other group of subjects
who often disagree.

So they have a chance of --

they bicker and disagree
and end up with less money.

They might be eligible
to be on "Real Housewives," the TV show.

You see on the left,

when the amount to divide
is one, two or three dollars,

they disagree about half the time,

and when the amount is four, five, six,
they agree quite often.

This turns out to be
something that's predicted

by a very complicated type of game theory

you should come to graduate school
at CalTech and learn about.

It's a little too complicated
to explain right now,

but the theory tells you
that this shape kind of should occur.

Your intuition might tell you that too.

Now I'll show you
the results from the EEG recording.

Very complicated. The right brain
schematic is the uninformed person,

and the left is the informed.

Remember that we scanned
both brains at the same time,

so we can ask about time-synced activity

in similar or different
areas simultaneously,

just like if you wanted
to study a conversation

and you were scanning
two people talking to each other

and you'd expect common activity
in language regions

when they're actually
listening and communicating.

So the arrows connect regions
that are active at the same time,

and the direction of the arrows flows

from the region
that's active first in time,

and the arrowhead goes
to the region that's active later.

So in this case, if you look carefully,

most of the arrows
flow from right to left.

That is, it looks as if the uninformed
brain activity is happening first

and then it's followed
by activity in the informed brain.

And by the way, these were trials
where their deals were made.

This is from the first two seconds.

We haven't finished analyzing this data,
we're still peeking in,

but the hope is that we can say
something in the first couple of seconds

about whether they'll make a deal or not,

which could be useful
in avoiding litigation,

ugly divorces and things like that.

Those are all cases

in which a lot of value
is lost by delay and strikes.

Here's the case
where the disagreements occur.

You can see it looks different
than the one before.

There's a lot more arrows.

That means that the brains are synced up

more closely in terms
of simultaneous activity,

and the arrows flow clearly
from left to right.

That is, the informed brain
seems to be deciding,

"We're probably
not going to make a deal here."

And then later there's activity
in the uninformed brain.

Next I'm going to introduce you
to some relatives.

They're hairy, smelly, fast and strong.

You might be thinking back
to your last Thanksgiving.

(Laughter)

Maybe if you had a chimpanzee with you.

Charles Darwin and I and you broke off
from the family tree, from chimpanzees,

about five million years ago.

They're still our closest genetic kin.

We share 98.8 percent of the genes.

We share more genes with them
than zebras do with horses.

And we're also their closest cousin.

They have more genetic relation
to us than to gorillas.

So how humans and chimpanzees
behave differently

might tell us a lot about brain evolution.

So this is an amazing memory test

from Nagoya, Japan,
Primate Research Institute,

where they've done a lot of this research.

This goes back quite a ways.

They're interested in working memory.

The chimp is going to see
200 milliseconds' exposure --

that's fast, that's eight movie frames --

of numbers one, two, three, four, five.

Then they disappear
and they're replaced by squares,

and they have to press the squares

that correspond to the numbers
from low to high to get an apple reward.

Let's see how they can do it.

This is a young chimp.

The young ones are better
than the old ones, just like humans.

And they're highly experienced,

so they've done this
thousands and thousands of time.

Obviously there's a big training effect,
as you can imagine.

(Laughter)

You can see they're very blasé
and kind of effortless.

Not only can they do it very well,
they do it in a sort of lazy way.

Who thinks you could beat the chimps?

(Laughter)

Wrong.

(Laughter)

We can try. Maybe we'll try.

OK, so the next part of this study
I'm going to go quickly through

is based on an idea of Tetsuro Matsuzawa.

He had a bold idea --

what he called the cognitive
trade-off hypothesis.

We know chimps are faster and stronger.
They're also very obsessed with status.

His thought was, maybe
they've preserved brain activities,

and they practice them in development,

that are really important to them
to negotiate status and to win,

which is something like strategic thinking
during competition.

So we're going to check that out
by having the chimps actually play a game

by touching two touch screens.

The chimps are interacting
with each other through the computers.

They're going to press left or right.
One chimp is called a matcher.

They win if they press left, left,

like a seeker finding someone
in hide-and-seek, or right, right.

The mismatcher wants to mismatch.

They want to press
the opposite screen of the chimp.

And the rewards are apple cube rewards.

So here's how game theorists
look at these data.

This is a graph of the percentage of times
the matcher picked right on the x-axis,

and the percentage of times
they predicted right

by the mismatcher on the y-axis.

So a point here is the behavior
by a pair of players,

one trying to match,
one trying to mismatch.

The NE square in the middle --
actually NE, CH and QRE --

those are three different theories
of Nash equilibrium, and others --

tells you what the theory predicts,

which is that they should match 50-50,

because if you play
left too much, for example,

I can exploit that if I'm the mismatcher
by then playing right.

And as you can see, the chimps --
each chimp is one triangle --

are circled around,
hovering around that prediction.

Now we move the payoffs.

We're going to make the left, left payoff
for the matcher higher.

Now they get three apple cubes.

Game theoretically, that should
make the mismatcher's behavior shift,

because the mismatcher will think,

this guy's going to go for the big reward,

so I'm going to go to the right,
make sure he doesn't get it.

And their behavior moves up

in the direction of this change
in the Nash equilibrium.

Finally, we changed
the payoffs one more time.

Now it's four apple cubes,

and their behavior again
moves towards the Nash equilibrium.

It's sprinkled around,
but if you average the chimps out,

they're really close, within .01.

They're actually closer
than any species we've observed.

What about humans?

You think you're smarter
than a chimpanzee?

Here's two human groups in green and blue.

They're closer to 50-50.

They're not responding
to payoffs as closely,

and if you study their learning,

they aren't as sensitive
to previous rewards.

The chimps are playing better
than the humans,

in the sense of adhering to game theory.

These are two different groups
of humans from Japan and Africa.

They replicate quite nicely.

None of them are close
to where the chimps are.

OK, so here are some things
we learned today.

People seem to do a limited
amount of strategic thinking

using theory of mind.

We have some evidence from bargaining

that early warning signs in the brain
might be used to predict

whether there will be
a bad disagreement that costs money,

and chimps are better
competitors than humans,

as judged by game theory.

Thank you.

(Applause)