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:

You don't want to sell too early,
because you 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 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.

Of course, 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 that it's hard for people
to parse very complex sentences

with a recursive structure.

This is called the cognitive
hierarchy theory,

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

and it indicates a kind of 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'll have learned a 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 close to two-thirds
of the average will win a big prize.

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.

Notice, by the way, most people
pick numbers right around there;

they don't necessarily
pick exactly 33 and 22.

There's something a bit noisy around it.

But you can see those spikes on that end.

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.

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.

We'll match up your behavior
at the end and pay you if you win."

In 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.

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 computers,

which brain areas
are differentially active.

On the top, you see the one-step players.

There's almost no difference.

The reason is, 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 we know the two-step players
are doing something differently.

Now, what can we do with this information?

You might be able to look
at brain activity and say,

"This person will be a good poker player,"
or "This person's socially naive."

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'll earn that money.

If 10 seconds go by and they haven't
made a deal, they get nothing.

That's kind of 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 being fair,

or are they giving me a very low offer

in order to get me to think 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 here
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.

They're bargaining over how much
the uninformed player gets,

and the informed player will get 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 very little to split:
"I'm giving the most I can."

First, some behavior: a bunch
of the subject pairs play face-to-face.

We have other data
where they play across computers.

That's an interesting difference,
as you might imagine.

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.

They bicker and disagree
and end up with less money.

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

(Laughter)

You see on the left,

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

they disagree about half the time;

when it's 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 should occur.

Your intuition might tell you that, too.

Now I'm going to 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.

You'd expect common
activity in language regions

when they're listening and communicating.

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

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 are trials
where their deals were made.

This is from the first two seconds.

We haven't finished analyzing this data,
so 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 very useful in thinking
about avoiding litigation

and 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.

This is an amazing memory test

from [Kyoto], Japan,
the Primate Research Institute,

where they've done a lot of this research.

This goes back a ways.
They're interested in working memory.

The chimp will see, watch carefully,

they'll see 200 milliseconds' exposure --
that's fast, eight movie frames --

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

Then they disappear
and are 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.

(Laughter)

And they're highly experienced,

they've done this thousands of times.

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

(Laughter)

You can see they're very
blasé and effortless.

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

(Laughter)

Who thinks you could beat the chimps?

(Laughter)

Wrong. (Laughter)

We can try. We'll try. Maybe we'll try.

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

is based on an idea of Tetsuro Matsuzawa.

He had a bold idea he called
the "cognitive trade-off hypothesis."

We know chimps are faster and stronger;
they're also obsessed with status.

His thought was, maybe
they've preserved brain activities

and practice them in development

that are really, 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'll 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 picked 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 a little higher.

Now they get three apple cubes.

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

the mismatcher will think, "Oh, this guy's
going to go for the big reward,

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

And as you can see,
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 also if you study
their learning in the game,

they aren't as sensitive
to previous rewards.

The chimps play better than the humans,
in terms of adhering to game theory.

And 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.

So, some things we learned:

people seem to do a limited amount of
strategic thinking using theory of mind.

We have preliminary
evidence from bargaining

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

whether there'll be a bad
disagreement that costs money,

and chimps are "better"
competitors than humans,

as judged by game theory.

Thank you.

(Applause)