0:00:00.800,0:00:03.136
I'm going to talk[br]about the strategizing brain.

0:00:03.160,0:00:05.536
We're going to use[br]an unusual combination of tools

0:00:05.560,0:00:07.176
from game theory and neuroscience

0:00:07.200,0:00:10.456
to understand how people interact socially[br]when value is on the line.

0:00:10.480,0:00:14.016
So game theory is a branch[br]of, originally, applied mathematics,

0:00:14.040,0:00:16.256
used mostly in economics[br]and political science,

0:00:16.280,0:00:17.536
a little bit in biology,

0:00:17.560,0:00:20.336
that gives us a mathematical[br]taxonomy of social life

0:00:20.360,0:00:22.656
and it predicts[br]what people are likely to do

0:00:22.680,0:00:23.976
and believe others will do

0:00:24.000,0:00:27.016
in cases where everyone's actions[br]affect everyone else.

0:00:27.040,0:00:30.696
That's a lot of things:[br]competition, cooperation, bargaining,

0:00:30.720,0:00:33.280
games like hide-and-seek and poker.

0:00:33.920,0:00:35.856
Here's a simple game to get us started.

0:00:35.880,0:00:38.296
Everyone chooses a number[br]from zero to 100,

0:00:38.320,0:00:40.776
we're going to compute[br]the average of those numbers,

0:00:40.800,0:00:44.816
and whoever's closest to two-thirds[br]of the average wins a fixed prize.

0:00:44.840,0:00:47.616
So you want to be[br]a little bit below the average number,

0:00:47.640,0:00:48.896
but not too far below,

0:00:48.920,0:00:50.336
and everyone else wants to be

0:00:50.360,0:00:52.536
a little bit below[br]the average number as well.

0:00:52.560,0:00:54.136
Think about what you might pick.

0:00:54.160,0:00:55.376
As you're thinking,

0:00:55.400,0:00:58.456
this is a toy model of something[br]like selling in the stock market

0:00:58.480,0:00:59.936
during a rising market. Right?

0:00:59.960,0:01:02.656
You don't want to sell too early[br]and miss out on profits,

0:01:02.680,0:01:04.376
but you don't want to wait too late

0:01:04.400,0:01:06.639
to when everyone else sells,[br]triggering a crash.

0:01:06.663,0:01:09.159
You want to be a little bit[br]ahead of the competition,

0:01:09.183,0:01:10.376
but not too far ahead.

0:01:10.400,0:01:13.416
OK, here's two theories[br]about how people might think about this,

0:01:13.440,0:01:14.656
then we'll see some data.

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Some of these will sound familiar

0:01:16.320,0:01:18.376
because you probably[br]are thinking that way.

0:01:18.400,0:01:20.000
I'm using my brain theory to see.

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

0:01:24.160,0:01:25.856
so I think the average will be 50."

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They're not being really strategic at all.

0:01:27.920,0:01:30.936
"And I'll pick two-thirds of 50.[br]That's 33." That's a start.

0:01:30.960,0:01:33.296
Other people who are[br]a little more sophisticated,

0:01:33.320,0:01:34.616
using more working memory,

0:01:34.640,0:01:36.256
say, "I think people will pick 33

0:01:36.280,0:01:38.496
because they're going to pick[br]a response to 50,

0:01:38.520,0:01:40.856
and so I'll pick 22,[br]which is two-thirds of 33."

0:01:40.880,0:01:43.816
They're doing one extra step[br]of thinking, two steps.

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That's better.

0:01:45.040,0:01:47.776
And in principle,[br]you could do three, four or more,

0:01:47.800,0:01:49.736
but it starts to get very difficult.

0:01:49.760,0:01:51.696
Just like in language and other domains,

0:01:51.720,0:01:54.576
we know it's hard for people[br]to parse very complex sentences

0:01:54.600,0:01:55.936
with a recursive structure.

0:01:55.960,0:01:58.136
This is called the cognitive[br]hierarchy theory.

0:01:58.160,0:02:00.896
It's something that I've worked on[br]and a few other people,

0:02:00.920,0:02:03.576
and it indicates a hierarchy[br]along with some assumptions

0:02:03.600,0:02:05.736
about how many people[br]stop at different steps

0:02:05.760,0:02:09.295
and how the steps of thinking are affected[br]by lots of interesting variables

0:02:09.320,0:02:11.456
and variant people,[br]as we'll see in a minute.

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

0:02:14.680,0:02:17.176
due largely to John Nash[br]of "A Beautiful Mind" fame,

0:02:17.200,0:02:19.376
is what's called equilibrium analysis.

0:02:19.400,0:02:22.136
So if you've ever taken[br]a game theory course at any level,

0:02:22.160,0:02:24.336
you will have learned[br]a little bit about this.

0:02:24.360,0:02:26.216
An equilibrium is a mathematical state

0:02:26.240,0:02:29.576
in which everybody has figured out[br]exactly what everyone else will do.

0:02:29.600,0:02:30.976
It is a very useful concept,

0:02:31.000,0:02:33.776
but behaviorally, it may not[br]exactly explain what people do

0:02:33.800,0:02:36.336
the first time they play[br]these types of economic games

0:02:36.360,0:02:38.216
or in situations in the outside world.

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In this case, the equilibrium[br]makes a very bold prediction,

0:02:41.040,0:02:43.416
which is everyone wants[br]to be below everyone else,

0:02:43.440,0:02:45.000
therefore they'll play zero.

0:02:45.680,0:02:46.896
Let's see what happens.

0:02:46.920,0:02:49.056
This experiment's been done[br]many, many times.

0:02:49.080,0:02:51.296
Some of the earliest ones[br]were done in the '90s

0:02:51.320,0:02:53.136
by me and Rosemarie Nagel and others.

0:02:53.160,0:02:55.616
This is a beautiful data set[br]of 9,000 people

0:02:55.640,0:02:58.816
who wrote in to three newspapers[br]and magazines that had a contest.

0:02:58.840,0:03:00.856
The contest said, send in your numbers

0:03:00.880,0:03:04.296
and whoever is closer to two-thirds[br]of the average will win a big prize.

0:03:04.320,0:03:06.496
And as you can see,[br]there's so much data here,

0:03:06.520,0:03:08.256
you can see the spikes very visibly.

0:03:08.280,0:03:10.896
There's a spike at 33.[br]Those are people doing one step.

0:03:10.920,0:03:12.936
There is another spike visible at 22.

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And notice that most people[br]pick numbers right around there.

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They don't necessarily pick[br]exactly 33 and 22.

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There's something[br]a little bit noisy around it.

0:03:20.280,0:03:21.696
But you can see those spikes.

0:03:21.720,0:03:23.256
There's another group of people

0:03:23.280,0:03:25.776
who seem to have[br]a firm grip on equilibrium analysis,

0:03:25.800,0:03:27.536
because they're picking zero or one.

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But they lose, right?

0:03:29.600,0:03:32.896
Because picking a number that low[br]is actually a bad choice

0:03:32.920,0:03:35.656
if other people aren't[br]doing equilibrium analysis as well.

0:03:35.680,0:03:37.096
So they're smart, but poor.

0:03:37.120,0:03:39.496
(Laughter)

0:03:39.520,0:03:42.056
Where are these things[br]happening in the brain?

0:03:42.080,0:03:45.736
One study by Coricelli and Nagel[br]gives a really sharp, interesting answer.

0:03:45.760,0:03:49.536
So they had people play this game[br]while they were being scanned in an fMRI,

0:03:49.560,0:03:51.816
and two conditions:[br]in some trials, they're told

0:03:51.840,0:03:54.336
you're playing another person[br]who's playing right now

0:03:54.360,0:03:57.456
and we're going to match up your behavior[br]and pay you if you win.

0:03:57.480,0:04:00.376
In the other trials, they're told,[br]you're playing a computer.

0:04:00.400,0:04:01.936
They're just choosing randomly.

0:04:01.960,0:04:04.136
So what you see[br]here is a subtraction of areas

0:04:04.160,0:04:07.136
in which there's more brain activity[br]when you're playing people

0:04:07.160,0:04:08.776
compared to playing the computer.

0:04:08.800,0:04:11.336
And you see activity[br]in some regions we've seen today,

0:04:11.360,0:04:13.696
medial prefrontal cortex,[br]dorsomedial, up here,

0:04:13.720,0:04:16.136
ventromedial prefrontal cortex,[br]anterior cingulate,

0:04:16.160,0:04:19.176
an area that's involved[br]in lots of types of conflict resolution,

0:04:19.200,0:04:21.055
like if you're playing "Simon Says,"

0:04:21.079,0:04:24.256
and also the right and left[br]temporoparietal junction.

0:04:24.280,0:04:26.896
And these are all areas[br]which are fairly reliably known

0:04:26.920,0:04:29.536
to be part of what's called[br]a "theory of mind" circuit,

0:04:29.560,0:04:30.816
or "mentalizing circuit."

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

0:04:34.360,0:04:36.776
So these were some[br]of the first studies to see this

0:04:36.800,0:04:38.000
tied in to game theory.

0:04:38.720,0:04:40.976
What happens with these[br]one- and two-step types?

0:04:41.000,0:04:43.216
So we classify people by what they picked

0:04:43.240,0:04:47.176
and then we look at the difference between[br]playing humans versus playing computers,

0:04:47.200,0:04:49.296
which brain areas[br]are differentially active.

0:04:49.320,0:04:52.256
On the top you see the one-step players.[br]Almost no difference.

0:04:52.280,0:04:55.496
They're treating other people[br]like a computer, and the brain is too.

0:04:55.520,0:04:58.656
The bottom players, you see[br]all the activity in dorsomedial PFC.

0:04:58.680,0:05:01.416
So those two-step players[br]are doing something differently.

0:05:01.440,0:05:03.976
You could say, "What can we do[br]with this information?"

0:05:04.000,0:05:05.496
You might be able to say,

0:05:05.520,0:05:07.776
"This person's going to be[br]a good poker player,"

0:05:07.800,0:05:09.496
or, "This person's socially naive,"

0:05:09.520,0:05:11.473
and we might also be able to study things

0:05:11.497,0:05:13.296
like development of adolescent brains

0:05:13.320,0:05:15.776
once we have an idea[br]of where this circuitry exists.

0:05:15.800,0:05:17.896
OK. Get ready.

0:05:17.920,0:05:19.936
I'm saving you some brain activity,

0:05:19.960,0:05:22.696
because you don't need[br]to use your hair detector cells.

0:05:22.720,0:05:25.976
You should use those cells[br]to think carefully about this game.

0:05:26.000,0:05:27.496
This is a bargaining game.

0:05:27.520,0:05:30.536
Two players who are being scanned[br]using EEG electrodes

0:05:30.560,0:05:33.336
are going to bargain[br]over one to six dollars.

0:05:33.360,0:05:36.896
If they can do it in 10 seconds,[br]they're going to actually earn that money.

0:05:36.920,0:05:38.976
If they don't make a deal,[br]they get nothing.

0:05:39.000,0:05:40.616
That's a mistake together.

0:05:40.640,0:05:43.456
The twist is that one player, on the left,

0:05:43.480,0:05:45.856
is informed about how much[br]on each trial there is.

0:05:45.880,0:05:48.616
They play lots of trials[br]with different amounts each time.

0:05:48.640,0:05:50.776
In this case, they know[br]there's four dollars.

0:05:50.800,0:05:54.416
The uninformed player doesn't know,[br]but they know the informed player knows.

0:05:54.440,0:05:56.656
So the uninformed player's[br]challenge is to say,

0:05:56.680,0:05:59.936
"Is this guy really being fair[br]or are they giving me a very low offer

0:05:59.960,0:06:01.296
in order to get me to think

0:06:01.320,0:06:04.016
that there's only one[br]or two dollars available to split?"

0:06:04.040,0:06:06.776
In which case they might reject it[br]and not come to a deal.

0:06:06.800,0:06:09.656
So there's some tension[br]between trying to get the most money

0:06:09.680,0:06:12.376
but trying to goad the other player[br]into giving you more.

0:06:12.400,0:06:14.896
And the way they bargain[br]is to point on a number line

0:06:14.920,0:06:16.616
that goes from zero to six dollars,

0:06:16.640,0:06:19.656
and they're bargaining[br]over how much the uninformed player gets,

0:06:19.680,0:06:21.496
and the informed player gets the rest.

0:06:21.520,0:06:23.696
So this is like[br]a management-labor negotiation

0:06:23.720,0:06:25.216
in which the workers don't know

0:06:25.240,0:06:28.216
how much profits[br]the privately held company has,

0:06:28.240,0:06:30.776
and they want to maybe[br]hold out for more money,

0:06:30.800,0:06:33.216
but the company might want[br]to create the impression

0:06:33.240,0:06:36.416
that there's little to split:[br]"I'm giving you the most that I can."

0:06:36.440,0:06:37.696
First some behavior.

0:06:37.720,0:06:40.096
So a bunch of the subject pairs[br]play face to face.

0:06:40.120,0:06:42.576
We have other data[br]where they play across computers.

0:06:42.600,0:06:44.216
That's an interesting difference.

0:06:44.240,0:06:46.056
But a bunch of the face-to-face pairs

0:06:46.080,0:06:48.480
agree to divide the money evenly[br]every single time.

0:06:49.200,0:06:52.216
Boring. It's just[br]not interesting neurally.

0:06:52.240,0:06:54.456
It's good for them.[br]They make a lot of money.

0:06:54.480,0:06:55.976
But we're interested in,

0:06:56.000,0:06:59.360
can we say something about when[br]disagreements occur versus don't occur?

0:06:59.880,0:07:02.616
So this is the other group of subjects[br]who often disagree.

0:07:02.640,0:07:03.976
So they have a chance of --

0:07:04.000,0:07:06.456
they bicker and disagree[br]and end up with less money.

0:07:06.480,0:07:09.440
They might be eligible[br]to be on "Real Housewives," the TV show.

0:07:10.240,0:07:11.896
You see on the left,

0:07:11.920,0:07:14.536
when the amount to divide[br]is one, two or three dollars,

0:07:14.560,0:07:16.216
they disagree about half the time,

0:07:16.240,0:07:19.216
and when the amount is four, five, six,[br]they agree quite often.

0:07:19.240,0:07:21.456
This turns out to be[br]something that's predicted

0:07:21.480,0:07:23.433
by a very complicated type of game theory

0:07:23.457,0:07:26.376
you should come to graduate school[br]at CalTech and learn about.

0:07:26.400,0:07:28.816
It's a little too complicated[br]to explain right now,

0:07:28.840,0:07:31.776
but the theory tells you[br]that this shape kind of should occur.

0:07:31.800,0:07:33.696
Your intuition might tell you that too.

0:07:33.720,0:07:36.216
Now I'll show you[br]the results from the EEG recording.

0:07:36.240,0:07:39.496
Very complicated. The right brain[br]schematic is the uninformed person,

0:07:39.520,0:07:40.936
and the left is the informed.

0:07:40.960,0:07:43.736
Remember that we scanned[br]both brains at the same time,

0:07:43.760,0:07:46.056
so we can ask about time-synced activity

0:07:46.080,0:07:49.096
in similar or different[br]areas simultaneously,

0:07:49.120,0:07:51.336
just like if you wanted[br]to study a conversation

0:07:51.360,0:07:53.936
and you were scanning[br]two people talking to each other

0:07:53.960,0:07:56.416
and you'd expect common activity[br]in language regions

0:07:56.440,0:07:58.816
when they're actually[br]listening and communicating.

0:07:58.840,0:08:02.096
So the arrows connect regions[br]that are active at the same time,

0:08:02.120,0:08:03.936
and the direction of the arrows flows

0:08:03.960,0:08:06.256
from the region[br]that's active first in time,

0:08:06.280,0:08:10.056
and the arrowhead goes[br]to the region that's active later.

0:08:10.080,0:08:12.136
So in this case, if you look carefully,

0:08:12.160,0:08:14.176
most of the arrows[br]flow from right to left.

0:08:14.200,0:08:19.136
That is, it looks as if the uninformed[br]brain activity is happening first

0:08:19.160,0:08:23.016
and then it's followed[br]by activity in the informed brain.

0:08:23.040,0:08:26.456
And by the way, these were trials[br]where their deals were made.

0:08:26.480,0:08:28.256
This is from the first two seconds.

0:08:28.280,0:08:31.376
We haven't finished analyzing this data,[br]we're still peeking in,

0:08:31.400,0:08:34.816
but the hope is that we can say[br]something in the first couple of seconds

0:08:34.840,0:08:36.816
about whether they'll make a deal or not,

0:08:36.840,0:08:38.976
which could be useful[br]in avoiding litigation,

0:08:39.000,0:08:40.696
ugly divorces and things like that.

0:08:40.720,0:08:41.936
Those are all cases

0:08:41.960,0:08:45.200
in which a lot of value[br]is lost by delay and strikes.

0:08:46.560,0:08:48.736
Here's the case[br]where the disagreements occur.

0:08:48.760,0:08:51.176
You can see it looks different[br]than the one before.

0:08:51.200,0:08:52.536
There's a lot more arrows.

0:08:52.560,0:08:54.496
That means that the brains are synced up

0:08:54.520,0:08:56.776
more closely in terms[br]of simultaneous activity,

0:08:56.800,0:08:59.016
and the arrows flow clearly[br]from left to right.

0:08:59.040,0:09:01.376
That is, the informed brain[br]seems to be deciding,

0:09:01.400,0:09:03.616
"We're probably[br]not going to make a deal here."

0:09:03.640,0:09:06.280
And then later there's activity[br]in the uninformed brain.

0:09:06.800,0:09:09.176
Next I'm going to introduce you[br]to some relatives.

0:09:09.200,0:09:11.336
They're hairy, smelly, fast and strong.

0:09:11.360,0:09:13.856
You might be thinking back[br]to your last Thanksgiving.

0:09:13.880,0:09:14.896
(Laughter)

0:09:14.920,0:09:17.336
Maybe if you had a chimpanzee with you.

0:09:17.360,0:09:21.296
Charles Darwin and I and you broke off[br]from the family tree, from chimpanzees,

0:09:21.320,0:09:22.896
about five million years ago.

0:09:22.920,0:09:24.776
They're still our closest genetic kin.

0:09:24.800,0:09:26.496
We share 98.8 percent of the genes.

0:09:26.520,0:09:29.376
We share more genes with them[br]than zebras do with horses.

0:09:29.400,0:09:31.296
And we're also their closest cousin.

0:09:31.320,0:09:34.016
They have more genetic relation[br]to us than to gorillas.

0:09:34.040,0:09:36.696
So how humans and chimpanzees[br]behave differently

0:09:36.720,0:09:38.760
might tell us a lot about brain evolution.

0:09:39.320,0:09:41.696
So this is an amazing memory test

0:09:41.720,0:09:44.456
from Nagoya, Japan,[br]Primate Research Institute,

0:09:44.480,0:09:46.496
where they've done a lot of this research.

0:09:46.520,0:09:47.896
This goes back quite a ways.

0:09:47.920,0:09:49.736
They're interested in working memory.

0:09:49.760,0:09:52.616
The chimp is going to see[br]200 milliseconds' exposure --

0:09:52.640,0:09:54.696
that's fast, that's eight movie frames --

0:09:54.720,0:09:56.616
of numbers one, two, three, four, five.

0:09:56.640,0:09:59.096
Then they disappear[br]and they're replaced by squares,

0:09:59.120,0:10:00.776
and they have to press the squares

0:10:00.800,0:10:04.176
that correspond to the numbers[br]from low to high to get an apple reward.

0:10:04.200,0:10:05.600
Let's see how they can do it.

0:10:16.400,0:10:17.656
This is a young chimp.

0:10:17.680,0:10:20.776
The young ones are better[br]than the old ones, just like humans.

0:10:20.800,0:10:22.336
And they're highly experienced,

0:10:22.360,0:10:24.856
so they've done this[br]thousands and thousands of time.

0:10:24.880,0:10:27.896
Obviously there's a big training effect,[br]as you can imagine.

0:10:27.920,0:10:29.416
(Laughter)

0:10:29.440,0:10:32.016
You can see they're very blasé[br]and kind of effortless.

0:10:32.040,0:10:35.256
Not only can they do it very well,[br]they do it in a sort of lazy way.

0:10:35.280,0:10:37.096
Who thinks you could beat the chimps?

0:10:37.120,0:10:38.536
(Laughter)

0:10:38.560,0:10:39.776
Wrong.

0:10:39.800,0:10:40.816
(Laughter)

0:10:40.840,0:10:42.816
We can try. Maybe we'll try.

0:10:42.840,0:10:46.856
OK, so the next part of this study[br]I'm going to go quickly through

0:10:46.880,0:10:49.816
is based on an idea of Tetsuro Matsuzawa.

0:10:49.840,0:10:51.096
He had a bold idea --

0:10:51.120,0:10:53.496
what he called the cognitive[br]trade-off hypothesis.

0:10:53.520,0:10:57.256
We know chimps are faster and stronger.[br]They're also very obsessed with status.

0:10:57.280,0:11:00.016
His thought was, maybe[br]they've preserved brain activities,

0:11:00.040,0:11:01.896
and they practice them in development,

0:11:01.920,0:11:04.976
that are really important to them[br]to negotiate status and to win,

0:11:05.000,0:11:07.936
which is something like strategic thinking[br]during competition.

0:11:07.960,0:11:11.896
So we're going to check that out[br]by having the chimps actually play a game

0:11:11.920,0:11:14.416
by touching two touch screens.

0:11:14.440,0:11:17.496
The chimps are interacting[br]with each other through the computers.

0:11:17.520,0:11:20.736
They're going to press left or right.[br]One chimp is called a matcher.

0:11:20.760,0:11:22.416
They win if they press left, left,

0:11:22.440,0:11:25.536
like a seeker finding someone[br]in hide-and-seek, or right, right.

0:11:25.560,0:11:27.176
The mismatcher wants to mismatch.

0:11:27.200,0:11:29.896
They want to press[br]the opposite screen of the chimp.

0:11:29.920,0:11:31.800
And the rewards are apple cube rewards.

0:11:32.400,0:11:34.736
So here's how game theorists[br]look at these data.

0:11:34.760,0:11:39.016
This is a graph of the percentage of times[br]the matcher picked right on the x-axis,

0:11:39.040,0:11:41.296
and the percentage of times[br]they predicted right

0:11:41.320,0:11:43.416
by the mismatcher on the y-axis.

0:11:43.440,0:11:46.776
So a point here is the behavior[br]by a pair of players,

0:11:46.800,0:11:49.016
one trying to match,[br]one trying to mismatch.

0:11:49.040,0:11:52.376
The NE square in the middle --[br]actually NE, CH and QRE --

0:11:52.400,0:11:55.656
those are three different theories[br]of Nash equilibrium, and others --

0:11:55.680,0:11:57.376
tells you what the theory predicts,

0:11:57.400,0:11:59.376
which is that they should match 50-50,

0:11:59.400,0:12:01.696
because if you play[br]left too much, for example,

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

0:12:04.800,0:12:07.776
And as you can see, the chimps --[br]each chimp is one triangle --

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are circled around,[br]hovering around that prediction.

0:12:11.120,0:12:12.856
Now we move the payoffs.

0:12:12.880,0:12:15.976
We're going to make the left, left payoff[br]for the matcher higher.

0:12:16.000,0:12:17.496
Now they get three apple cubes.

0:12:17.520,0:12:20.776
Game theoretically, that should[br]make the mismatcher's behavior shift,

0:12:20.800,0:12:22.456
because the mismatcher will think,

0:12:22.480,0:12:24.480
this guy's going to go for the big reward,

0:12:24.504,0:12:27.376
so I'm going to go to the right,[br]make sure he doesn't get it.

0:12:27.400,0:12:28.736
And their behavior moves up

0:12:28.760,0:12:32.056
in the direction of this change[br]in the Nash equilibrium.

0:12:32.080,0:12:34.296
Finally, we changed[br]the payoffs one more time.

0:12:34.320,0:12:35.576
Now it's four apple cubes,

0:12:35.600,0:12:38.456
and their behavior again[br]moves towards the Nash equilibrium.

0:12:38.480,0:12:41.176
It's sprinkled around,[br]but if you average the chimps out,

0:12:41.200,0:12:42.816
they're really close, within .01.

0:12:42.840,0:12:45.496
They're actually closer[br]than any species we've observed.

0:12:45.520,0:12:46.736
What about humans?

0:12:46.760,0:12:48.800
You think you're smarter[br]than a chimpanzee?

0:12:49.320,0:12:51.920
Here's two human groups in green and blue.

0:12:52.600,0:12:53.816
They're closer to 50-50.

0:12:53.840,0:12:55.976
They're not responding[br]to payoffs as closely,

0:12:56.000,0:12:57.576
and if you study their learning,

0:12:57.600,0:12:59.736
they aren't as sensitive[br]to previous rewards.

0:12:59.760,0:13:01.936
The chimps are playing better[br]than the humans,

0:13:01.960,0:13:03.896
in the sense of adhering to game theory.

0:13:03.920,0:13:06.896
These are two different groups[br]of humans from Japan and Africa.

0:13:06.920,0:13:08.296
They replicate quite nicely.

0:13:08.320,0:13:10.536
None of them are close[br]to where the chimps are.

0:13:10.560,0:13:12.696
OK, so here are some things[br]we learned today.

0:13:12.720,0:13:15.376
People seem to do a limited[br]amount of strategic thinking

0:13:15.400,0:13:16.656
using theory of mind.

0:13:16.680,0:13:18.496
We have some evidence from bargaining

0:13:18.520,0:13:21.456
that early warning signs in the brain[br]might be used to predict

0:13:21.480,0:13:24.216
whether there will be[br]a bad disagreement that costs money,

0:13:24.240,0:13:26.416
and chimps are better[br]competitors than humans,

0:13:26.440,0:13:27.656
as judged by game theory.

0:13:27.680,0:13:28.896
Thank you.

0:13:28.920,0:13:32.480
(Applause)