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

186,287 views ใƒป 2013-03-28

TED


์•„๋ž˜ ์˜๋ฌธ์ž๋ง‰์„ ๋”๋ธ”ํด๋ฆญํ•˜์‹œ๋ฉด ์˜์ƒ์ด ์žฌ์ƒ๋ฉ๋‹ˆ๋‹ค.

00:00
Transcriber: Joseph Geni Reviewer: Thu-Huong Ha
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๋ฒˆ์—ญ: K Bang ๊ฒ€ํ† : Gyeyoung Choi
00:12
I'm going to talk about the strategizing brain.
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๋‘๋‡Œ์˜ ์ „๋žตํ™”์— ๋Œ€ํ•˜์—ฌ ๋ง์”€๋“œ๋ฆฌ๊ฒ ์Šต๋‹ˆ๋‹ค.
์šฐ๋ฆฌ๋Š” ๊ฒŒ์ž„ ์ด๋ก ๋ถ€ํ„ฐ ์‹ ๊ฒฝ๊ณผํ•™๊นŒ์ง€
00:15
We're going to use an unusual combination of tools
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00:17
from game theory and neuroscience
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์ผ๋ฐ˜์ ์ธ ์ˆ˜์ค€์„ ๋„˜์–ด์„œ๋Š” ๋„๊ตฌ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ
00:19
to understand how people interact socially when value is on the line.
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๊ฐ€์น˜๊ฐ€ ์œ„ํ˜‘๋ฐ›์„ ๋•Œ, ์‚ฌ๋žŒ๋“ค์ด ์‚ฌํšŒ์ ์œผ๋กœ ์–ด๋–ป๊ฒŒ ์ƒํ˜ธ์ž‘์šฉํ•˜๋Š”์ง€ ์•Œ์•„๋ณด๊ณ ์ž ํ•ฉ๋‹ˆ๋‹ค.
00:22
So game theory is a branch of, originally, applied mathematics,
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๊ฒŒ์ž„ ์ด๋ก ์€ ์›๋ž˜ ์‘์šฉ ์ˆ˜ํ•™์˜ ํ•œ ๋ถ„์•ผ์ฃ ,
00:26
used mostly in economics and political science, a little bit in biology,
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๋Œ€์ฒด๋กœ ๊ฒฝ์ œํ•™์ด๋‚˜ ์ •์น˜ํ•™, ์ผ๋ถ€๋Š” ์ƒ๋ฌผํ•™์—๋„ ์‚ฌ์šฉ๋˜๋Š”๋ฐ
๊ฒŒ์ž„ ์ด๋ก ์„ ์ด์šฉํ•˜์—ฌ ์‚ฌํšŒ ์ƒํ™œ์„ ์ˆ˜ํ•™์ ์œผ๋กœ ๋ถ„๋ฅ˜ํ•˜๊ณ 
00:29
that gives us a mathematical taxonomy of social life,
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00:32
and it predicts what people are likely to do
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์‚ฌ๋žŒ๋“ค์˜ ํ–‰๋™์ด ๋‹ค๋ฅธ ์‚ฌ๋žŒ๋“ค์—๊ฒŒ
00:34
and believe others will do
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์˜ํ–ฅ์„ ๋ฏธ์น  ๋•Œ,
์‚ฌ๋žŒ๋“ค์ด ์–ด๋–ป๊ฒŒ ํ–‰๋™ํ•˜๋Š”์ง€ ์˜ˆ์ธกํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
00:36
in cases where everyone's actions affect everyone else.
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์ด๋Ÿฐ ์‚ฌํšŒ ์ƒํ™œ์—๋Š” ๊ฒฝ์Ÿ, ํ˜‘๋™, ํ˜‘์ƒ
00:39
That's a lot of things: competition, cooperation, bargaining,
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00:42
games like hide-and-seek and poker.
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์ˆ ๋ž˜์žก๊ธฐ๋‚˜ ํฌ์ปค์™€ ๊ฐ™์€ ๊ฒŒ์ž„ ๋“ฑ์ด ์žˆ์ง€์š”.
00:45
Here's a simple game to get us started.
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์šฐ๋ฆฌ๊ฐ€ ํ•จ๊ป˜ ์‹œ์ž‘ํ•ด ๋ณผ ์ˆ˜ ์žˆ๋Š” ๊ฐ„๋‹จํ•œ ๊ฒŒ์ž„์ด ์žˆ์–ด์š”.
00:47
Everyone chooses a number from zero to 100.
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๋ชจ๋“  ์‚ฌ๋žŒ๋“ค์ด 0์—์„œ 100๊นŒ์ง€ ์ˆ˜์—์„œ ํ•˜๋‚˜์˜ ์ˆซ์ž๋ฅผ ๊ณ ๋ฆ…๋‹ˆ๋‹ค.
00:50
We're going to compute the average of those numbers,
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๊ณ ๋ฅธ ์ˆซ์ž๋“ค์˜ ํ‰๊ท ์„ ๋‚ด์„œ
00:52
and whoever's closest to two-thirds of the average wins a fixed prize.
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ํ‰๊ท ์˜ 2/3์— ๊ฐ€์žฅ ๊ฐ€๊นŒ์šด ๋‘ ์‚ฌ๋žŒ์—๊ฒŒ ์ƒ์„ ์ฃผ๊ธฐ๋กœ ํ•ด๋ณด์ฃ .
00:56
So you want to be a little bit below the average number
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๊ทธ๋Ÿฌ๋‹ˆ๊นŒ ์‚ฌ๋žŒ๋“ค์€ ํ‰๊ท ๋ณด๋‹ค ์•ฝ๊ฐ„ ๋‚ฎ์€ ์ˆซ์ž๋ฅผ ์›ํ•˜์ง€๋งŒ
00:59
but not too far below,
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๋„ˆ๋ฌด ๋‚ฎ์œผ๋ฉด ์•ˆ๋˜๊ณ , ๋‹ค๋ฅธ ์‚ฌ๋žŒ๋“ค ๋ชจ๋‘
01:00
and everyone else wants to be a little bit below the average number as well.
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ํ‰๊ท ๋ณด๋‹ค ์•ก๊ฐ„ ์ ์€ ์ˆซ์ž๋ฅผ ์›ํ•ฉ๋‹ˆ๋‹ค.
์—ฌ๋Ÿฌ๋ถ„์€ ๋ฌด์—‡์„ ํƒํ• ์ง€ ์ƒ๊ฐํ•ด๋ณด์„ธ์š”.
01:04
Think about what you might pick.
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์ƒ๊ฐํ•ด๋ณด๋ฉด, ์ด๊ฒƒ์€ ์ฃผ๊ฐ€ ์‹œ์žฅ์—์„œ
01:06
As you're thinking,
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01:07
this is a toy model of something like selling in the stock market
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์ƒ์Šน์žฅ์—์„œ ์ฃผ์‹์„ ํŒŒ๋Š” ๊ฒƒ๊ณผ ๊ฐ™์€ ์˜ˆ์‹œ๊ฐ€ ๋˜๋Š”๊ฑฐ์ฃ .
01:10
during a rising market:
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์ด์œค์—์„œ ์†ํ•ด๋ฅผ ๋ณด๊ธฐ ๋•Œ๋ฌธ์— ๋„ˆ๋ฌด ์ผ์ฐ ํŒ”๊ณ  ์‹ถ์ง€ ์•Š์ง€๋งŒ
01:12
You don't want to sell too early, because you miss out on profits,
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๋„ˆ๋ฌด ์˜ค๋ž˜ ๊ธฐ๋‹ค๋ฆฌ๋‹ค๊ฐ€
01:15
but you don't want to wait too late, to when everyone else sells,
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๋ชจ๋“  ์‚ฌ๋žŒ๋“ค์ด ํŒ”์•„์น˜์šฐ๋Š” ์ถฉ๊ฒฉ์  ์žฅ์„ธ๊นŒ์ง€ ๋‚จ๊ณ  ์‹ถ์ง€๋Š” ์•Š์€๊ฒ๋‹ˆ๋‹ค.
01:18
triggering a crash.
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๊ฒฝ์Ÿ๋ณด๋‹ค ์กฐ๊ธˆ์€ ์•ž์„œ๊ณ  ์‹ถ์ง€๋งŒ ๋„ˆ๋ฌด ์•ž์„œ ๋‚˜๊ฐ€๋„ ์‹ถ์ง€๋Š” ์•Š์€๊ฑฐ์ฃ .
01:19
You want to be a little bit ahead of the competition, but not too far ahead.
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์ด๋Ÿฐ ๊ฒฝ์šฐ์— ์‚ฌ๋žŒ๋“ค์ด ์ƒ๊ฐํ•˜๋Š” ๋ฐฉ๋ฒ•์— ๋Œ€ํ•œ ๋‘๊ฐ€์ง€ ์ด๋ก ์ด ์žˆ์Šต๋‹ˆ๋‹ค.
01:23
OK, here's two theories about how people might think about this,
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์šฐ๋ฆฌ๋Š” ์ž๋ฃŒ๋„ ์ข€ ์‚ดํŽด๋ณด๋ ค๊ณ  ํ•ด์š”.
01:26
then we'll see some data.
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์ด๋“ค ๊ฐ€์šด๋ฐ ๋ช‡๋ช‡์€ ์ต์ˆ™ํ•˜์‹ค๊ฒ๋‹ˆ๋‹ค ์™œ๋ƒํ•˜๋ฉด ์—ฌ๋Ÿฌ๋ถ„๋“ค๋„ ์•„๋งˆ ๊ทธ๋Ÿฐ ๋ฐฉ์‹์œผ๋กœ
01:27
Some of these will sound familiar
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์ƒ๊ฐํ•˜์‹คํ…Œ๋‹ˆ๊นŒ์š”. ์ €๋Š” ์ œ ๋‘๋‡Œ ์ด๋ก ์„ ์‚ฌ์šฉํ•ด ๋ณด๋ ค๊ณ  ํ•ฉ๋‹ˆ๋‹ค.
01:29
because you probably are thinking that way.
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01:31
I'm using my brain theory to see.
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01:32
A lot of people say, "I really don't know what people are going to pick,
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๋งŽ์€ ์‚ฌ๋žŒ๋“ค์ด ์ด๋ ‡๊ฒŒ ๋งํ•˜๊ฒ ์ฃ . "๋‚œ ์‚ฌ๋žŒ๋“ค์ด ๋ญ˜ ํƒํ• ์ง€ ๋ชจ๋ฅด๊ฒ ์–ด.
๊ทธ๋Ÿฌ๋‹ˆ๊นŒ ํ‰๊ท ์€ ์•„๋งˆ 50์ผ๊ฑฐ๋ผ๊ณ  ์ƒ๊ฐํ•ด."
01:36
so I think the average will be 50" -- they're not being strategic at all --
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์ด๋Ÿฐ ์‚ฌ๋žŒ๋“ค์€ ์ „ํ˜€ ์ „๋žต์ ์ด์ง€ ๋ชปํ•œ ๊ฒ๋‹ˆ๋‹ค.
01:39
and "I'll pick two-thirds of 50, that's 33."
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"๋‚˜๋Š” 50์˜ 2/3์ธ 33์„ ํƒํ•ด์•ผ์ง€." ๋ผ๊ณ  ํ•œ๋‹ค๋ฉด ๊ทธ๊ฑด ์ด์ œ ์‹œ์ž‘์ธ๊ฑฐ๊ตฌ์š”.
01:41
That's a start.
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์กฐ๊ธˆ ๋” ๋ณต์žกํ•˜๊ฒŒ ์ƒ๊ฐํ•˜๋Š” ๋‹ค๋ฅธ ์‚ฌ๋žŒ๋“ค์€
01:43
Other people, who are a little more sophisticated,
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๋” ๋งŽ์€ ์ž‘์—… ๊ธฐ์–ต์„ ์‚ฌ์šฉํ•˜์—ฌ ์ด๋ ‡๊ฒŒ ๋งํ•ฉ๋‹ˆ๋‹ค.
01:45
using more working memory,
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01:46
say, "I think people will pick 33,
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"๋‚˜๋Š” ์‚ฌ๋žŒ๋“ค์ด 33์„ ํƒํ• ๊ฑฐ๋ผ๊ณ  ์ƒ๊ฐํ•ด. ์™œ๋ƒํ•˜๋ฉด ์‚ฌ๋žŒ๋“ค์€ 50์— ๋Œ€ํ•ด ๋ฐ˜์‘์„ ๋ณด์ผ๊ฑฐ๊ฑฐ๋“ ,
01:48
because they're going to pick a response to 50,
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๊ทธ๋Ÿฌ๋‹ˆ๊นŒ ๋‚˜๋Š” 33์˜ 2/3์ธ 22๋ฅผ ํƒํ•ด์•ผ์ง€."
01:50
and so I'll pick 22, which is two-thirds of 33."
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01:52
They're doing one extra step of thinking, two steps.
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์ด๋Ÿฐ ์‚ฌ๋žŒ๋“ค์€ ํ•œ ๋‹จ๊ณ„์˜ ์ƒ๊ฐ์„ ๋”ํ•ด ๋‘ ๋‹จ๊ณ„์˜ ์ƒ๊ฐ์„ ํ•˜๋Š”๊ฒ๋‹ˆ๋‹ค.
01:55
That's better.
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๊ทธ๊ฒŒ ๋‚ซ์ฃ . ๋ฌผ๋ก  ์›์น™์ ์œผ๋กœ
01:57
Of course, in principle, you could do three, four or more,
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3๋‹จ๊ณ„๋‚˜ 4๋‹จ๊ณ„, ๊ทธ๋ณด๋‹ค ๋” ์ƒ๊ฐํ•  ์ˆ˜ ์žˆ์ง€๋งŒ
01:59
but it starts to get very difficult.
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์ด์ œ ๋ฌธ์ œ๋Š” ๋ณต์žกํ•ด์ง€๊ธฐ ์‹œ์ž‘ํ•ฉ๋‹ˆ๋‹ค.
02:01
Just like in language and other domains,
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์–ธ์–ด๋‚˜ ๊ทธ ๋น„์Šทํ•œ ์˜์—ญ์—์„œ ์ฒ˜๋Ÿผ,
02:03
we know that it's hard for people to parse very complex sentences
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๋ฐ˜๋ณต์ ์ธ ๊ตฌ์กฐ๋ฅผ ๊ฐ€์ง„ ์•„์ฃผ ๋ณต์žกํ•œ ๋ฌธ์žฅ์„ ๋ถ„์„ํ•˜๊ธฐ๋ž€ ๋งค์šฐ ์–ด๋ ต์Šต๋‹ˆ๋‹ค.
02:06
with a recursive structure.
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์ด๋Ÿฐ๊ฑธ ์ธ์ง€์  ๊ณ„์ธต ์ด๋ก ์ด๋ผ๊ณ  ํ•ฉ๋‹ˆ๋‹ค.
02:08
This is called the cognitive hierarchy theory,
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์ด๊ฒƒ์ด ์ €์™€ ๋‹ค๋ฅธ ๋ช‡๋ช‡ ์‚ฌ๋žŒ๋“ค์ด ์—ฐ๊ตฌํ•ด์˜จ ๊ฒƒ์ธ๋ฐ์š”,
02:10
something I've worked on and a few other people,
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02:12
and it indicates a kind of hierarchy,
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๋ช‡ ์‚ฌ๋žŒ์ด ์–ด๋Š ๋‹จ๊ณ„์—์„œ ํฌ๊ธฐํ•˜๋Š”์ง€
02:14
along with some assumptions about how many people stop at different steps
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๊ทธ๋ฆฌ๊ณ  ์ˆ˜๋งŽ์€ ํฅ๋ฏธ๋กœ์šด ๋ณ€์ˆ˜์™€
๋‹ค์–‘ํ•œ ์‚ฌ๋žŒ๋“ค์— ๋”ฐ๋ผ ์ƒ๊ฐ์˜ ๋‹จ๊ณ„๊ฐ€ ์–ด๋–ป๊ฒŒ ์˜ํ–ฅ์„ ๋ฐ›์„์ง€์— ๋Œ€ํ•œ
02:17
and how the steps of thinking are affected
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๋ช‡๊ฐ€์ง€ ๊ฐ€์ •์„ ํ•˜๋ฉด ์ด ์ด๋ก ์€ ์ผ์ข…์˜ ๊ณ„์ธต์„ ๋‚˜ํƒ€๋ƒ…๋‹ˆ๋‹ค.
02:19
by lots of interesting variables and variant people,
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02:22
as we'll see in a minute.
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์™„์ „ํžˆ ๋‹ค๋ฅด์ง€๋งŒ ๋” ์˜ค๋ž˜๋˜๊ณ  ํ›จ์”ฌ ๋„๋ฆฌ ์•Œ๋ ค์ง„ ์ด๋ก ์€
02:23
A very different theory, a much more popular one and an older one,
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์กด ๋‚ด์‰ฌ์˜ "๋ทฐํ‹ฐํ”Œ ๋งˆ์ธ๋“œ"์˜ ์œ ๋ช…์„ธ ๋•ํƒ์ธ๋ฐ์š”,
02:26
due largely to John Nash of "A Beautiful Mind" fame,
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02:29
is what's called "equilibrium analysis."
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์†Œ์œ„ ๋งํ•˜๋Š” ํ‰ํ˜• ์ด๋ก ์ž…๋‹ˆ๋‹ค.
02:31
So if you've ever taken a game theory course at any level,
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์–ด๋–ค ์ˆ˜์ค€์ด์—ˆ๊ฑด ๊ฒŒ์ž„ ์ด๋ก ์— ๊ด€ํ•œ ๊ฐ•์˜๋ฅผ ๋“ค์–ด๋ณด์‹  ์ ์ด ์žˆ๋‹ค๋ฉด
์ด ์ด๋ก ์— ๋Œ€ํ•ด์„œ ์กฐ๊ธˆ์€ ๋ฐฐ์šฐ์…จ์„๊ฒ๋‹ˆ๋‹ค.
02:34
you'll have learned a bit about this.
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ํ‰ํ˜•์ ์ด๋ž€ ๋ชจ๋“  ์‚ฌ๋žŒ์ด ๋‹ค๋ฅธ ์‚ฌ๋žŒ๋“ค์€ ์–ด๋–ป๊ฒŒ ํ• ์ง€
02:36
An equilibrium is a mathematical state
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02:37
in which everybody has figured out exactly what everyone else will do.
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์ •ํ™•ํ•˜๊ฒŒ ์ธ์ง€ํ•œ ์ˆ˜ํ•™์ ์ธ ์ƒํƒœ์—์š”.
์ด๊ฑด ์•„์ฃผ ์œ ์šฉํ•œ ์ด๋ก ์ด์ง€๋งŒ, ํ–‰๋™์  ์ธก๋ณ€์—์„œ ๋ณด๋ฉด
02:41
It is a very useful concept,
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02:42
but behaviorally, it may not exactly explain
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์ด๋Ÿฐ ํ˜•ํƒœ์˜ ๊ฒฝ์ œ ๊ด€๋ จ ๊ฒŒ์ž„์„ ์ฒ˜์Œ ํ•ด๋ณด๋Š” ์‚ฌ๋žŒ๋“ค์ด๋‚˜
02:44
what people do the first time they play these types of economic games
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๊ทธ ์˜์—ญ์˜ ๋ฐ”๊นฅ ์„ธ์ƒ์— ์ผ์–ด๋‚˜๋Š” ์ƒํ™ฉ์—์„œ ์‚ฌ๋žŒ๋“ค์˜ ํ–‰๋™์„
02:47
or in situations in the outside world.
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์ •ํ™•ํ•˜๊ฒŒ ์„ค๋ช…ํ•˜์ง€๋Š” ๋ชปํ•˜๋Š” ๊ฒฝ์šฐ๋„ ์žˆ์Šต๋‹ˆ๋‹ค.
02:49
In this case, the equilibrium makes a very bold prediction,
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์ด๋Ÿฐ ๊ฒฝ์šฐ์—, ํ‰ํ˜•์ ์€ ์•„์ฃผ ์ด์ƒํ•œ ์˜ˆ์ธก์„ ๋‚ด๋†“๊ธฐ๋„ ํ•˜์ฃ .
02:52
which is: everyone wants to be below everyone else,
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๋ชจ๋“  ์‚ฌ๋žŒ์ด ๋‹ค๋ฅธ ๋ชจ๋“  ์‚ฌ๋žŒ๋“ค ๋ณด๋‹ค ๋‚ฎ์€ ์ˆ˜๋ฅผ ์›ํ•˜๋‹ˆ๊นŒ
02:55
therefore, they'll play zero.
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์‚ฌ๋žŒ๋“ค์€ 0 ์„ ์จ๋‚ผ๊ฑฐ๋ผ๋Š” ๊ฒƒ์ด์ฃ .
02:57
Let's see what happens.
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์–ด๋–ค ์ผ์ด ์ƒ๊ธฐ๋Š”์ง€ ๋ณผ๊นŒ์š”. ์ด ์‹คํ—˜์€ ์ˆ˜๋„ ์—†์ด ์—ฌ๋Ÿฌ ๋ฒˆ ๋ฐ˜๋ณต๋˜์—ˆ์–ด์š”.
02:58
This experiment's been done many, many times.
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์ผ๋ถ€ ์ดˆ๊ธฐ ์‹คํ—˜์€ 90๋…„๋Œ€์—
03:01
Some of the earliest ones were done in the '90s
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์ €์™€ ๋กœ์ฆˆ๋งˆ๋ฆฌ ๋„ค์ด๊ฑธ ๋“ฑ์ด ์ˆ˜ํ–‰ํ–ˆ์ฃ .
03:03
by me and Rosemarie Nagel and others.
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์ด๊ฑด 3๊ฐœ์˜ ์‹ ๋ฌธ์‚ฌ์™€ ์žก์ง€์‚ฌ์˜ ๊ฒฝํ’ˆ ํ–‰์‚ฌ์— ์‘๋ชจํ•œ
03:05
This is a beautiful data set of 9,000 people
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03:07
who wrote in to three newspapers and magazines that had a contest.
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9์ฒœ๋ช…์ด ์ ์–ด๋‚ธ, ์ •๋ง ์•„๋ฆ„๋‹ค์šด ์ž๋ฃŒ์ž…๋‹ˆ๋‹ค.
03:10
The contest said, send in your numbers,
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๊ฒฝํ’ˆ ํ–‰์‚ฌ์—์„œ ์ˆซ์ž๋ฅผ ์ ์–ด๋‚ด๋ฉด
03:12
and whoever is close to two-thirds of the average will win a big prize.
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์ „์ฒด ํ‰๊ท ์˜ 2/3์— ๊ฐ€์žฅ ๊ฐ€๊นŒ์šด ์‚ฌ๋žŒ์—๊ฒŒ ๋Œ€๋‹จํ•œ ์ƒํ’ˆ์„ ์ค„๊ฑฐ๋ผ๊ณ  ํ–ˆ์–ด์š”.
๋ณด์‹œ๋‹ค์‹œํ”ผ ์•„์ฃผ ๋งŽ์€ ์ž๋ฃŒ๊ฐ€ ์žˆ๋Š”๋ฐ, ๋พฐ์กฑํ•œ ์ง€์ ์„ ๋ถ„๋ช…ํžˆ ๋ณด์‹ค ์ˆ˜ ์žˆ์ฃ .
03:16
As you can see, there's so much data here, you can see the spikes very visibly.
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33์ด ๊ทธ๋Ÿฐ ์ง€์ ์ด์—ˆ๊ณ  ๊ทธ ์‚ฌ๋žŒ๋“ค์€ ํ•œ ๋‹จ๊ณ„ ๋” ๋‚˜์•„๊ฐ„ ์‚ฌ๋žŒ๋“ค์ด์—์š”.
03:20
There's a spike at 33 -- those are people doing one step.
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03:22
There is another spike visible at 22.
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22์— ๋˜ ๋‹ค๋ฅธ ๋พฐ์กฑ์ ์„ ๋ณผ ์ˆ˜ ์žˆ์ฃ .
์–ด์จ‹๋“ , ๋Œ€๋ถ€๋ถ„์˜ ์‚ฌ๋žŒ๋“ค์ด ๊ทธ ๊ทผ์ฒ˜์˜ ์ˆซ์ž๋ฅผ ํƒํ•œ ๊ฒƒ์„ ๋ณด์„ธ์š”.
03:25
Notice, by the way, most people pick numbers right around there;
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๊ทธ ์‚ฌ๋žŒ๋“ค์ด ๋ฌด์กฐ๊ฑด 33์ด๋‚˜ 22๋ฅผ ์„ ํƒํ•œ ๊ฒƒ์€ ์•„๋‹ˆ์—์š”.
03:28
they don't necessarily pick exactly 33 and 22.
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๊ทธ ์ˆซ์ž๋“ค ์ฃผ๋ณ€์— ์•ฝ๊ฐ„ ๋ถ„์‚ฐ๋˜์–ด ๋‚˜ํƒ€๋‚˜์ฃ .
03:30
There's something a bit noisy around it.
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์–ด์จŒ๋“  ๊ทธ๋Ÿฐ ๋พฐ์กฑ์ ๋“ค์ด ๋‚˜ํƒ€๋‚ฉ๋‹ˆ๋‹ค.
03:32
But you can see those spikes on that end.
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๋˜๋‹ค๋ฅธ ๋ฌด๋ฆฌ์˜ ์‚ฌ๋žŒ๋“ค์€ ํ‰ํ˜• ๋ถ„์„์—
03:34
There's another group of people
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ํ™•์‹ ์„ ๊ฐ–๊ณ  ์žˆ๋Š” ๋“ฏ์ด ๋ณด์ด์ฃ .
03:35
who seem to have a firm grip on equilibrium analysis,
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์ด ์‚ฌ๋žŒ๋“ค์€ 0 ์ด๋‚˜ 1 ์„ ํƒํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
03:38
because they're picking zero or one.
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03:39
But they lose, right?
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ํ•˜์ง€๋งŒ ์ด ์‚ฌ๋žŒ๋“ค์€ ํƒˆ๋ฝํ•˜์ฃ .
03:41
Because picking a number that low is actually a bad choice
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์™œ๋ƒํ•˜๋ฉด ๊ทธ๋ ‡๊ฒŒ ์ž‘์€ ์ˆซ์ž๋Š”
๋‹ค๋ฅธ ์‚ฌ๋žŒ๋“ค๋„ ํ‰ํ˜• ๋ถ„์„์„ ํ•˜์ง€ ์•Š์œผ๋ฉด ์‚ฌ์‹ค ์•„์ฃผ ์ข‹์ง€์•Š์€ ์„ ํƒ์ด์—์š”.
03:45
if other people aren't doing equilibrium analysis as well.
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03:47
So they're smart, but poor.
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์ด๋Ÿฐ ์‚ฌ๋žŒ๋“ค์€ ์•ฝ์ง€๋งŒ ์•ˆ๋ฌ์Šต๋‹ˆ๋‹ค.
03:49
(Laughter)
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(์›ƒ์Œ)
03:51
Where are these things happening in the brain?
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์ด๋Ÿฐ ์ผ๋“ค์ด ๋จธ๋ฆฟ ์† ์–ด๋””์„œ ์ผ์–ด๋‚ ๊นŒ์š”?
์ฝ”๋ฆฌ์ฒผ๋ฆฌ์™€ ๋„ค์ด๊ฑธ์˜ ์—ฐ๊ตฌ์— ๋”ฐ๋ฅด๋ฉด ์ •๋ง ์˜ˆ๋ฆฌํ•˜๊ณ  ํฅ๋ฏธ๋กœ์šด ๋‹ต์ด ์žˆ์Šต๋‹ˆ๋‹ค.
03:54
One study by Coricelli and Nagel gives a really sharp, interesting answer.
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03:57
They had people play this game while they were being scanned in an fMRI,
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๊ทธ๋ž˜์„œ ์ด๋“ค์€ ์‚ฌ๋žŒ๋“ค๋กœ ํ•˜์—ฌ๊ธˆ ๊ฒŒ์ž„์„ ํ•˜๋„๋ก ํ•˜๊ณ 
๊ธฐ๋Šฅ์„ฑ ์ž๊ธฐ ๊ณต๋ช… ์ดฌ์˜์„ ํ–ˆ์Šต๋‹ˆ๋‹ค.
04:01
and two conditions:
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๋‘ ๊ฐ€์ง€์˜ ์กฐ๊ฑด์—์„œ ํ•ด๋ดค์–ด์š”: ๋ช‡ ๋ฒˆ์€ ์ด๋Ÿฐ ์‹์ด์—ˆ์Šต๋‹ˆ๋‹ค.
04:02
in some trials, they're told,
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์‚ฌ๋žŒ๋“ค์—๊ฒŒ ๋‹ค๋ฅธ ์‚ฌ๋žŒ๋“ค๊ณผ ๊ฒŒ์ž„์„ ํ•˜๊ณ  ์žˆ๋Š”๋ฐ
04:04
"You're playing another person who's playing right now.
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๊ทธ ์‚ฌ๋žŒ๋“ค๋„ ์ง€๊ธˆ ๊ฒŒ์ž„์„ ํ•˜๊ณ  ์žˆ๊ณ  ๋งˆ์ง€๋ง‰์—๋Š”
04:06
We'll match up your behavior at the end and pay you if you win."
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์ž์‹ ๋“ค์˜ ํ–‰๋™์„ ๊ทธ๋“ค๊ณผ ๊ฒฝํ•ฉ์‹œํ‚จ ๋‹ค์Œ, ์ด๊ธฐ๋Š” ๊ฒฝ์šฐ์— ๋ˆ์„ ์ค€๋‹ค๊ณ  ํ–ˆ์ฃ .
๋‹ค๋ฅธ ์‹คํ—˜์—์„œ๋Š”, ์ปดํ“จํ„ฐ์™€ ๊ฒŒ์ž„์„ ํ•œ๋‹ค๊ณ  ํ–ˆ์–ด์š”.
04:09
In other trials, they're told, "You're playing a computer,
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์ปดํ“จํ„ฐ๋Š” ๊ทธ๋ƒฅ ๋ฌด์ž‘์œ„๋กœ ์„ ํƒํ•˜์ฃ .
04:12
they're just choosing randomly."
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์—ฌ๊ธฐ ๋ณด์‹œ๋Š” ๊ฒƒ์€ ์ปดํ“จํ„ฐ์™€ ๊ฒŒ์ž„์„ ํ•˜๋Š” ๊ฒƒ์—
04:14
So what you see here is a subtraction of areas
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๋Œ€๋น„ํ•˜์—ฌ ์‚ฌ๋žŒ๋“ค์„ ์ƒ๋Œ€๋กœ ๊ฒŒ์ž„์„ ํ–ˆ์„ ๋•Œ
04:16
in which there's more brain activity when you're playing people
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๋” ๋งŽ์€ ๋‘๋˜ ํ™œ๋™์ด ์žˆ์—ˆ๋˜ ์˜์—ญ์„ ๋บธ ๊ฒฐ๊ณผ์—์š”.
04:19
compared to playing the computer.
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04:20
And you see activity in some regions we've seen today,
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์˜ค๋Š˜ ์šฐ๋ฆฌ๊ฐ€ ๋ดค๋˜ ์ „๋‘์—ฝ ์ค‘์•™๋ถ€์™€ ๋ฐฐ๋‚ด ์ธก๋ฉด๊ณผ ๊ฐ™์€
์ผ๋ถ€ ์˜์—ญ์—์„œ ํ™œ๋™์ด ์ผ์–ด๋‚ฌ์ง€๋งŒ, ์—ฌ๊ธฐ ์œ„์ชฝ์—๋„,
04:23
medial prefrontal cortex, dorsomedial, up here,
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04:25
ventromedial prefrontal cortex, anterior cingulate,
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๋ณต๋‚ด์ธก์‹œ์ƒํ•˜ํ•ต ์ „์ „๋‘์—ฝ ํ”ผ์งˆ์ด๋‚˜
์ „์ธก ๋Œ€์ƒํšŒ, ์ด๊ฑด ์ˆ˜๋งŽ์€ ๊ฐˆ๋“ฑ ํ•ด๊ฒฐ ๋ฌธ์ œ์™€
04:28
an area that's involved in lots of types of conflict resolution,
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๊ด€๋ จ์ด ์žˆ๋Š” ๋ถ€๋ถ„์ด์—์š”. ๋งˆ์น˜ "์‚ฌ์ด๋ชฌ ๊ฐ€๋ผ์‚ฌ๋Œ€" ๊ฒŒ์ž„์„ ํ•  ๋•Œ์™€ ๋งˆ์ฐฌ๊ฐ€์ง€๋กœ์š”,
04:31
like if you're playing "Simon Says,"
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์ขŒ์šฐ์ธก์˜ ์ธก๋‘๋‘์ • ์ ‘ํ•ฉ์—์„œ๋„ ๋งŽ์€ ํ™œ๋™์ด ์ผ์–ด๋‚ฌ์Šต๋‹ˆ๋‹ค.
04:33
and also the right and left temporoparietal junction.
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04:36
And these are all areas which are fairly reliably known to be
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์ด๋Ÿฐ ๊ฒƒ๋“ค์€ ๋ชจ๋‘"๋งˆ์Œ์˜ ์ด๋ก " ํšŒ๋กœ ๋˜๋Š”
"์ •์‹ ํ™” ํšŒ๋กœ"๋ผ๊ณ  ๋ถˆ๋ฆฌ๋Š” ๊ฒƒ์˜ ์ผ๋ถ€์ž„์ด
04:39
part of what's called a "theory of mind" circuit
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์•„์ฃผ ์ž˜ ์•Œ๋ ค์ง„ ์˜์—ญ์ด์ฃ .
04:41
or "mentalizing circuit."
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04:42
That is, it's a circuit that's used to imagine what other people might do.
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๊ทธ๋Ÿฌ๋‹ˆ๊นŒ, ์ด ์˜์—ญ์€ ๋‹ค๋ฅธ ์‚ฌ๋žŒ๋“ค์ด ๋ฌด์—‡์„ ์ƒ๊ฐํ•˜๋Š”์ง€ ์ถ”์ธกํ•˜๋Š”๋ฐ ์“ฐ์ด๋Š” ํšŒ๋กœ์—์š”.
04:46
These were some of the first studies to see this tied in to game theory.
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์ด๊ฒƒ๋“ค์€ ์ด ๋ถ€๋ถ„์ด ๊ฒŒ์ž„ ์ด๋ก ๊ณผ ๊ด€๋ จ์ด ์žˆ๋Š” ๊ฒƒ์„
์•Œ ์ˆ˜ ์žˆ๋Š” ์ฒซ ์—ฐ๊ตฌ์˜ ์ผ๋ถ€ ๊ฒฐ๊ณผ์ž…๋‹ˆ๋‹ค.
04:50
What happens with these one- and two-step types?
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์—ฌ๊ธฐ ์ด ๋‹จ๊ณ„๋ณ„ ํ˜•ํƒœ์— ๋ฌด์Šจ ์ผ์ด ์ผ์–ด๋‚˜์ฃ ?
์ €ํฌ๋Š” ์‚ฌ๋žŒ๋“ค์„ ๊ทธ๋“ค์ด ์„ ํƒํ•˜๋Š” ์ˆ˜์— ๋”ฐ๋ผ ๋ถ„๋ฅ˜ํ•ฉ๋‹ˆ๋‹ค.
04:53
So, we classify people by what they picked,
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๊ทธ๋ฆฌ๊ณ ๋Š” ์ธ๊ฐ„๊ณผ ๊ฒฝํ•ฉํ•˜๋Š” ๊ฒƒ๊ณผ ์ปดํ“จํ„ฐ์™€ ๊ฒฝํ•ฉํ•˜๋Š” ๊ฒƒ์˜
04:55
and then we look at the difference between playing humans versus computers,
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์ฐจ์ด๋ฅผ ๊ด€์ฐฐํ•ฉ๋‹ˆ๋‹ค.
04:58
which brain areas are differentially active.
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๋‘๋‡Œ์˜ ์–ด๋Š ๋ถ€๋ถ„์ด ๋‹ค๋ฅด๊ฒŒ ํ™œ์„ฑํ™”๋˜๋Š”์ง€ ๋ณด๋Š”๊ฑฐ์ฃ .
05:00
On the top, you see the one-step players.
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์œ„์ชฝ์— 1 ๋‹จ๊ณ„์— ์†ํ•˜๋Š” ์‚ฌ๋žŒ๋“ค์ด ๋ณด์ž…๋‹ˆ๋‹ค.
๊ฑฐ์˜ ์ฐจ์ด๊ฐ€ ์—†์ฃ .
05:02
There's almost no difference.
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๊ทธ ์ด์œ ๋Š”, ์ด ์‚ฌ๋žŒ๋“ค์€ ๋‹ค๋ฅธ ์‚ฌ๋žŒ๋“ค์„ ๊ฑฐ์˜ ์ปดํ“จํ„ฐ์ฒ˜๋Ÿผ ์ทจ๊ธ‰ํ•ฉ๋‹ˆ๋‹ค. ๋‘๋‡Œ๋„ ๊ทธ๋ ‡์ฃ .
05:04
The reason is, they're treating other people like a computer,
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์•„๋žซ์ชฝ ์‚ฌ๋žŒ๋“ค์—๊ฒŒ์„œ๋Š”, ์—ฌ๋Ÿฌ๋ถ„๋“ค๋„ ๋ฐฐ๋‚ด ์ธก๋ฉด ์˜์—ญ์— ์ผ์–ด๋‚˜๋Š” ํ™œ๋™์ด ๋ณด์ด์‹œ์ฃ .
05:07
and the brain is too.
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05:08
The bottom players, you see all the activity in dorsomedial PFC.
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์šฐ๋ฆฌ๋Š” ์ด 2 ๋‹จ๊ณ„์— ์†ํ•˜๋Š” ์‚ฌ๋žŒ๋“ค์ด ๋ญ”๊ฐ€ ์กฐ๊ธˆ ๋‹ค๋ฅด๋‹ค๋Š” ๊ฒƒ์„ ์•Œ๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
05:11
So we know the two-step players are doing something differently.
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์ด์ œ ๋’ค๋กœ ํ•œ๋ฐœ์ง ๋ฌผ๋Ÿฌ๋‚˜์„œ "์ด ์ •๋ณด๋กœ ๋ญ˜ํ•  ์ˆ˜ ์žˆ์ง€?" ๋ผ๊ณ  ๋ง์”€ํ•˜์‹ ๋‹ค๋ฉด
05:14
Now, what can we do with this information?
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์‚ฌ๋žŒ๋“ค์€ ๋‘๋‡Œ์˜ ํ™œ๋™์„ ๋ณด๊ณ  ์ด๋ ‡๊ฒŒ ๋งํ• ์ง€๋„ ๋ชฐ๋ผ์š”,
05:16
You might be able to look at brain activity and say,
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"์ด ์‚ฌ๋žŒ์€ ํฌ์ปค ๊ฒŒ์ž„์„ ์ž˜ ํ•˜๊ฒ ๊ตฐ."
05:19
"This person will be a good poker player," or "This person's socially naive."
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์•„๋‹ˆ๋ฉด "์ด ์‚ฌ๋žŒ์€ ์‚ฌํšŒ์ ์œผ๋กœ ์•„์ฃผ ๋‹จ์ˆœํ•˜๊ตฐ."
์šฐ๋ฆฌ๊ฐ€ ์ด๋Ÿฐ ํšŒ๋กœ๋Š” ์–ด๋””์— ์žˆ๋Š”์ง€
05:22
We might also be able to study things like development of adolescent brains
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์•Œ ์ˆ˜๋งŒ ์žˆ๋‹ค๋ฉด, ์ €ํฌ๋Š” ์•„๋งˆ
์ฒญ์†Œ๋…„์˜ ๋‡Œ ๋ฐœ๋‹ฌ๊ณผ ๊ฐ™์€ ๊ฒƒ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋ฅผ ํ•  ์ˆ˜ ์žˆ์„๊ฒ๋‹ˆ๋‹ค.
05:26
once we have an idea of where this circuitry exists.
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์ข‹์Šต๋‹ˆ๋‹ค. ์ค€๋น„๋˜์…จ์ฃ .
05:28
OK. Get ready.
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05:29
I'm saving you some brain activity,
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์ œ๊ฐ€ ์—ฌ๋Ÿฌ๋ถ„๋“ค์˜ ๋‘๋‡Œ ํ™œ๋™์„ ์กฐ๊ธˆ ๋œ์–ด๋“œ๋ฆฌ๋„๋ก ํ•˜์ฃ .
05:31
because you don't need to use your hair detector cells.
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๋จธ๋ฆฌ์นด๋ฝ ๊ฐ์ง€ ์„ธํฌ๊นŒ์ง€ ์‚ฌ์šฉํ•  ํ•„์š”๋Š” ์—†์œผ๋‹ˆ๊นŒ์š”.
05:34
You should use those cells to think carefully about this game.
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๊ทธ ์„ธํฌ๋Š” ์ด ๊ฒŒ์ž„์—์„œ ์‹ ์ค‘ํ•˜๊ฒŒ ์ƒ๊ฐํ•˜๋Š”๋ฐ ์‚ฌ์šฉํ•˜์…”์•ผ ํ•˜๋‹ˆ๊นŒ์š”.
์ด๊ฑด ํ˜‘์ƒ ๊ฒŒ์ž„์ž…๋‹ˆ๋‹ค.
05:38
This is a bargaining game.
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05:39
Two players who are being scanned using EEG electrodes
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๋‡Œ์ „๋„๊ธฐ๋กœ ๋‘ ๋ช…์˜ ์ฐธ๊ฐ€์ž๋ฅผ ์Šค์บ”ํ•˜๋ฉด์„œ
05:42
are going to bargain over one to six dollars.
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์ด ์‚ฌ๋žŒ๋“ค์ด 1 ์—์„œ 6๋‹ฌ๋Ÿฌ๊นŒ์ง€ ํฅ์ •์„ ํ•˜๋„๋ก ํ•ฉ๋‹ˆ๋‹ค.
05:45
If they can do it in 10 seconds, they'll earn that money.
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์ด ์‚ฌ๋žŒ๋“ค์ด 10์ดˆ์•ˆ์— ํฅ์ •์„ ๋งˆ์น˜๋ฉด ์‹ค์ œ๋กœ ๋ˆ์„ ๋ฐ›๊ฒŒ ๋˜๋Š” ๊ฒ๋‹ˆ๋‹ค.
10์ดˆ๊ฐ€ ์ง€๋‚˜๊ณ ๋„ ํ˜‘์ƒ์ด ๋˜์ง€ ์•Š์œผ๋ฉด ์ „ํ˜€ ๋ˆ์„ ๋ฐ›์ง€ ๋ชปํ•˜๊ณ ์š”.
05:48
If 10 seconds go by and they haven't made a deal, they get nothing.
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๊ทธ๊ฑด ๋‘˜ ๋‹ค ์ผ์ข…์˜ ์‹ค์ˆ˜๋ฅผ ํ•˜๋Š”๊ฑฐ์ฃ .
05:51
That's kind of a mistake together.
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05:52
The twist is that one player, on the left,
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์ค‘์š”ํ•œ ์ ์€ ์™ผ์ชฝ์— ์žˆ๋Š” ์ฐธ์—ฌ์ž์—๊ฒŒ
05:55
is informed about how much on each trial there is.
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๋งค๋ฒˆ ์ด์•ก์ด ์–ผ๋งˆ๋‚˜ ๋˜๋Š”์ง€ ์•Œ๋ ค์ฃผ๋Š” ๊ฒ๋‹ˆ๋‹ค.
05:57
They play lots of trials with different amounts each time.
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์ด ์‚ฌ๋žŒ๋“ค์€ ๋งค๋ฒˆ ๋‹ค๋ฅธ ์•ก์ˆ˜๋ฅผ ๋†“๊ณ  ์‹คํ—˜์„ ํ•˜๊ฒŒ ๋ฉ๋‹ˆ๋‹ค.
06:00
In this case, they know there's four dollars.
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์ด ๊ฒฝ์šฐ์—” ์ด๋“ค์€ 4๋‹ฌ๋Ÿฌ๊ฐ€ ์žˆ๋‹ค๋Š” ๊ฑธ ์••๋‹ˆ๋‹ค.
06:02
The uninformed player doesn't know, but they know the informed player knows.
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์ •๋ณด๋ฅผ ๋ชจ๋ฅด๋Š” ์ฐธ์—ฌ์ž๋Š” ์•Œ ๋ฐ”๊ฐ€ ์—†๊ฒ ์ฃ .
ํ•˜์ง€๋งŒ ๋‘ ์‚ฌ๋žŒ์ด ๋ชจ๋‘ ์ •๋ณด๋ฅผ ๋ฐ›๋Š” ์‚ฌ๋žŒ์€ ์•ก์ˆ˜๋ฅผ ์•Œ๊ณ  ์žˆ๋‹ค๋Š” ์ ์„ ์ธ์ง€ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
06:06
So the uninformed player's challenge is to say,
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๊ทธ๋Ÿฌ๋‹ˆ๊นŒ, ์ •๋ณด๋ฅผ ๋ชจ๋ฅด๋Š” ์ฐธ์—ฌ์ž์˜ ๋ฌธ์ œ๋Š” ์ด๋Ÿฐ๊ฑฐ์ฃ .
06:08
"Is this guy being fair,
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"์ด ์‚ฌ๋žŒ์ด ์ •๋ง ๊ณต์ •ํ•œ๊ฑด์ง€
06:09
or are they giving me a very low offer
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์•„๋‹ˆ๋ฉด ๋‚˜๋ˆŒ ์ˆ˜ ์žˆ๋Š” ๋ˆ์ด
06:11
in order to get me to think there's only one or two dollars available to split?"
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๊ฒจ์šฐ 1, 2๋‹ฌ๋Ÿฌ๋ผ๊ณ  ๋‚ด๊ฐ€ ์ƒ๊ฐํ•˜๊ฒŒ ํ•˜๋ ค๊ณ  ๋„ˆ๋ฌด ๋‚ฎ์€ ์ œ์•ˆ์„ ํ•˜๋Š” ๊ฒƒ์€ ์•„๋‹Œ๊ฐ€? "
๊ทธ๋Ÿฐ ๊ฒฝ์šฐ์— ์ด๋“ค์€ ์ œ์•ˆ์„ ๊ฑฐ๋ถ€ํ•˜๊ณ  ํ˜‘์ƒ์€ ๊ฒฐ๋ ฌ๋ฉ๋‹ˆ๋‹ค.
06:15
in which case they might reject it and not come to a deal.
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์—ฌ๊ธฐ์—๋Š” ๋” ๋งŽ์€ ๋ˆ์„ ์–ป์œผ๋ ค๋Š” ์ธก๊ณผ
06:18
So there's some tension here between trying to get the most money
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๋‹ค๋ฅธ ์‚ฌ๋žŒ์„ ๊ณค๋ž€ํ•˜๊ฒŒ ํ•ด์„œ ๋” ๋งŽ์€ ๋ˆ์„ ์–ป์œผ๋ ค๋Š” ์ธก ์‚ฌ์ด์— ๊ฐˆ๋“ฑ์ด ์ƒ๊ธฐ๊ฒŒ ๋ฉ๋‹ˆ๋‹ค.
06:21
but trying to goad the other player into giving you more.
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์ด ์‚ฌ๋žŒ๋“ค์ด ํ˜‘์ƒํ•˜๋Š” ๋ฐฉ๋ฒ•์€
06:24
And the way they bargain is to point on a number line
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0์—์„œ 6๋‹ฌ๋Ÿฌ ์‚ฌ์ด์˜ ์ˆซ์ž๋ฅผ ํƒํ•˜๋Š” ๊ฒƒ์ด๊ณ 
06:26
that goes from zero to six dollars.
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์ด๋“ค์€ ์ •๋ณด๊ฐ€ ์—†๋Š” ์ธก์ด ์–ผ๋งˆ๋‚˜ ๋ˆ์„ ๋ฐ›๋Š”์ง€ ๊ทธ๋ฆฌ๊ณ  ์ •๋ณด๋ฅผ ๊ฐ€์ง„ ์ธก์ด ๋‚˜๋จธ์ง€๋ฅผ ๊ฐ€์ ธ๊ฐ€๋Š”
06:28
They're bargaining over how much the uninformed player gets,
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๋ฐฉ๋ฒ•์— ๋Œ€ํ•œ ํ˜‘์ƒ์„ ๋ฒŒ์ด๋Š” ๊ฑฐ์—์š”.
06:31
and the informed player will get the rest.
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์ด๊ฑด ๋งˆ์น˜ ๋…ธ์‚ฌ ํ˜‘์ƒ๊ณผ ๊ฐ™์€๋ฐ,
06:33
So this is like a management-labor negotiation
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๋…ธ์‚ฌ ํ˜‘์ƒ์—์„œ ๋…ธ๋™์ž๋Š” ๊ฐœ์ธ ๊ธฐ์—…์ด
06:35
in which the workers don't know
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06:37
how much profits the privately held company has,
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์–ผ๋งˆ๋‚˜ ์ด์œค์„ ๋‚ด๋Š”์ง€ ์•Œ์ง€๋„ ๋ชปํ•˜๊ณ 
06:40
and they want to maybe hold out for more money,
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์‚ฌ์—…์ž ์ธก์—์„œ ๋ˆ์„ ๋–ผ์–ด ๋†“๊ธฐ๋ฅผ ์›ํ•˜๋Š”์ง€๋„ ์•Œ ์ˆ˜๊ฐ€ ์—†์Šต๋‹ˆ๋‹ค.
06:42
but the company might want to create the impression
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ํ•˜์ง€๋งŒ ํšŒ์‚ฌ๋Š” ๋‚˜๋ˆŒ ๋ˆ์ด ์•„์ฃผ ๋งŽ์ง€ ์•Š๋‹ค๋Š”
์ธ์ƒ์„ ์ฃผ๋ ค๊ณ  ํ•  ์ˆ˜ ์žˆ์–ด์š”. "์šฐ๋ฆฌ๊ฐ€ ์ค„ ์ˆ˜ ์žˆ๋Š” ํ•œ ์ตœ๋Œ€ํ•œ ์ฃผ๊ฒ ๋„ค."๋ผ๊ณ  ํ•˜๋Š”๊ฑฐ์ฃ .
06:45
that there's very little to split: "I'm giving the most I can."
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์ฒ˜์Œ์—๋Š” ๋ช‡๊ฐ€์ง€ ํ–‰๋™ ์–‘์‹์„ ๋ณด์—ฌ์š”. ๋งŽ์€ ๊ฒฝ์šฐ๋ฅผ ๋†“๊ณ  ์ด๋“ค์€ ์–ผ๊ตด์„ ๋งž๋Œ€๊ณ  ๋…ผ์˜ํ•ฉ๋‹ˆ๋‹ค.
06:48
First, some behavior: a bunch of the subject pairs play face-to-face.
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06:51
We have other data where they play across computers.
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์ €ํฌ๋Š” ์ด๋“ค์ด ์ปดํ“จํ„ฐ๋ฅผ ๋†“๊ณ  ํ˜‘์ƒ์„ ํ•˜๋Š” ๋˜ ๋‹ค๋ฅธ ์ž๋ฃŒ๋„ ๊ฐ€์ง€๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
๊ฑฐ๊ธฐ์—” ์˜ˆ์ƒํ•˜์‹œ๋‹ค์‹œํ”ผ ์•„์ฃผ ํฅ๋ฏธ๋กœ์šด ์ฐจ์ด๊ฐ€ ์žˆ์–ด์š”.
06:54
That's an interesting difference, as you might imagine.
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์–ผ๊ตด์„ ๋งž๋Œ€๊ณ  ํ•˜๋Š” ์ˆ˜ ๋งŽ์€ ๊ฒฝ์šฐ์—๋Š”
06:56
But a bunch of the face-to-face pairs
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๋งค๋ฒˆ ์–‘์ชฝ์ด ๋˜‘๊ฐ™์ด ๋ˆ์„ ๋‚˜๋ˆ„๋Š”๋ฐ ํ•ฉ์˜ํ•˜์ฃ .
06:58
agree to divide the money evenly every single time.
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์ง€๋ฃจํ•˜์ฃ . ์ค‘๊ฐ„์ž์˜ ์ž…์žฅ์—์„  ๋ณ„ ์žฌ๋ฏธ๊ฐ€ ์—†์Šต๋‹ˆ๋‹ค.
07:01
Boring. It's just not interesting neurally.
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๊ทธ ์‚ฌ๋žŒ๋“ค์—๊ฒ ์ข‹์ฃ , ๋ˆ์„ ๋งŽ์ด ๋ฐ›์œผ๋‹ˆ๊นŒ์š”.
07:04
It's good for them -- they make a lot of money.
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07:06
But we're interested in:
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ํ•˜์ง€๋งŒ ์ €ํžˆ๋„ ํฅ๋ฏธ๊ฐ€ ์žˆ์Šต๋‹ˆ๋‹ค. ํ˜‘์ƒ์ด ์ด๋ฃจ์–ด์งˆ ๋•Œ์™€
07:08
Can we say something about when disagreements occur versus don't occur?
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๊ฒฐ๋ ฌ๋  ๋•Œ์— ๋Œ€ํ•ด์„œ ๋ญ”๊ฐ€ ์•Œ ์ˆ˜ ์žˆ๋Š”๊ฒŒ ์žˆ๋ƒ๋Š”๊ฑฐ์ฃ .
07:11
So this is the other group of subjects, who often disagree.
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์ด๊ฑด ํ˜‘์ƒ์ด ์ž์ฃผ ๊ฒฐ๋ ฌ๋˜๋Š” ๋˜ ๋‹ค๋ฅธ ๊ทธ๋ฃน์ž…๋‹ˆ๋‹ค.
์ด๋“ค์—๊ฒŒ๋Š” ์‹ธ์›€์ด ์ผ์–ด๋‚˜์„œ ํ˜‘์ƒ์ด ๊ฒฐ๋ ฌ๋˜๊ณ 
07:14
They bicker and disagree and end up with less money.
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๋ˆ์„ ์ ๊ฒŒ ๋ฐ›๊ณ  ๋๋‚  ํ™•๋ฅ ์ด ์žˆ์–ด์š”.
07:18
They might be eligible to be on "Real Housewives," the TV show.
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์ด๋“ค์€ ์–ด์ฉŒ๋ฉด "์ง„์งœ ์ฃผ๋ถ€๋“ค(Real Housewives)"์ด๋ผ๋Š” TV ํ”„๋กœ๊ทธ๋žจ์— ๋‚˜์˜ฌ ์ž์งˆ์ด ์žˆ์„์ง€๋„ ๋ชฐ๋ผ์š”.
07:21
(Laughter)
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์™ผ์ชฝ์„ ๋ณด์„ธ์š”.
07:22
You see on the left,
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07:23
when the amount to divide is one, two or three dollars,
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๋‚˜๋ˆŒ ๋ˆ์ด 1, 2, 3 ๋‹ฌ๋Ÿฌ์ธ ๊ฒฝ์šฐ์—
07:26
they disagree about half the time;
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์ด๋“ค์€ ๊ฑฐ์˜ ๋ฐ˜ ์ •๋„ ํ˜‘์ƒ์— ์‹คํŒจํ•ฉ๋‹ˆ๋‹ค.
07:28
when it's four, five, six, they agree quite often.
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4, 5, 6 ๋‹ฌ๋Ÿฌ์ธ ๊ฒฝ์šฐ์—๋Š” ๋Œ€๋ถ€๋ถ„ ํ˜‘์ƒ์— ์„ฑ๊ณตํ•˜์ฃ .
07:30
This turns out to be something that's predicted
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์ด๊ฑด ๊ฝค๋‚˜ ๋ณต์žกํ•œ ํ˜•ํƒœ์˜ ๊ฒŒ์ž„ ์ด๋ก ์— ์˜ํ•ด์„œ
07:32
by a very complicated type of game theory
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์ด๋ฏธ ์˜ˆ๊ฒฌ๋œ ๊ฒฐ๊ณผ์—์š”.
07:34
you should come to graduate school at CalTech and learn about.
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์บ˜๋ฆฌํฌ๋‹ˆ์•„ ๊ณต๋Œ€(CalTech) ๋Œ€ํ•™์›์— ์˜ค์…”์„œ ๋ฐฐ์›Œ์•ผ ํ•˜๋Š” ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.
์—ฌ๊ธฐ์„œ ๋ฐ”๋กœ ์„ค๋ช…ํ•˜๊ธฐ์—” ๋„ˆ๋ฌด ๋ณต์žกํ•ฉ๋‹ˆ๋‹ค.
07:38
It's a little too complicated to explain right now,
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ํ•˜์ง€๋งŒ ์ด๋ก ์— ์˜ํ•˜๋ฉด ์ด๋Ÿฐ ๊ฒฝ์šฐ๊ฐ€ ์ข…์ข… ๋ฐœ์ƒํ•œ๋‹ค๋Š” ๊ฒƒ์ด์ง€์š”.
07:40
but the theory tells you that this shape should occur.
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ํ•™๊ต์— ์˜ค์‹œ๋ฉด ์ด๋Ÿฐ ๊ฒฝ์šฐ๋„ ์•Œ๋ ค๋“œ๋ฆด ๊ฒ๋‹ˆ๋‹ค.
07:43
Your intuition might tell you that, too.
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07:45
Now I'm going to show you the results from the EEG recording.
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์ด์ œ ๋‡ŒํŒŒ ๊ธฐ๋ก์˜ ๊ฒฐ๊ณผ๋ฅผ ๋ณด์—ฌ๋“œ๋ฆฌ๊ฒŸ์Šต๋‹ˆ๋‹ค.
์•„์ฃผ ๋ณต์žกํ•œ๋ฐ์š”, ์˜ค๋ฅธ์ชฝ์— ์žˆ๋Š” ๋‡Œ์˜ ๋„ํ‘œ๋Š”
07:48
Very complicated.
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07:49
The right brain schematic is the uninformed person,
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์ •๋ณด๊ฐ€ ์—†๋˜ ์‚ฌ๋žŒ์ด๊ณ ์š”, ์™ผ์ชฝ์€ ์ •๋ณด๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ๋˜ ์‚ฌ๋žŒ์˜ ๊ฒƒ์ž…๋‹ˆ๋‹ค.
07:51
and the left is the informed.
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์–‘์ธก์„ ๋ชจ๋‘ ํ•œ๋ฒˆ์— ์Šค์บ”ํ–ˆ๋‹ค๋Š” ์ ์„ ๊ธฐ์–ตํ•ด์ฃผ์„ธ์š”.
07:53
Remember that we scanned both brains at the same time,
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07:55
so we can ask about time-synced activity
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๊ทธ๋Ÿฌ๋‹ˆ๊นŒ ์šฐ๋ฆฌ๋Š” ์‹ค์‹œ๊ฐ„์œผ๋กœ
๋น„์Šทํ•˜๊ฑฐ๋‚˜ ๋‹ค๋ฅธ ์˜์—ญ์—์„œ์˜ ํ™œ๋™์„ ๋น„๊ตํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
07:58
in similar or different areas simultaneously,
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๋งˆ์น˜ ๋Œ€ํ™”์— ๋Œ€ํ•ด ์—ฐ๊ตฌํ•  ๋•Œ,
08:01
just like if you wanted to study a conversation,
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08:03
and you were scanning two people talking to each other.
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๋‘ ์‚ฌ๋žŒ์ด ์„œ๋กœ ์ด์•ผ๊ธฐํ•˜๋Š” ๊ฒƒ์„ ์Šค์บ”ํ•˜๋Š” ๊ฒƒ๊ณผ ๊ฐ™์ฃ ,
๊ทธ๋ฆฌ๊ณ ๋Š” ๊ทธ ์‚ฌ๋žŒ๋“ค์ด ์‹ค์ œ๋กœ ๋“ฃ๊ฑฐ๋‚˜ ์†Œํ†ต์„ ํ•˜๋Š” ์ˆœ๊ฐ„
08:06
You'd expect common activity in language regions
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์–ธ์–ด ์˜์—ญ์—์„œ ๊ณตํ†ต์  ํ™œ๋™์ด ์žˆ์„ ๊ฒƒ์„ ์˜ˆ์ƒํ•˜๋Š” ๊ฒƒ๊ณผ ์œ ์‚ฌํ•ฉ๋‹ˆ๋‹ค.
08:08
when they're listening and communicating.
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ํ™”์‚ดํ‘œ๋Š” ๋™์‹œ์— ํ™œ๋™์ด ์žˆ๋Š” ์˜์—ญ์„ ์—ฐ๊ฒฐํ•˜๊ณ 
08:10
So the arrows connect regions that are active at the same time.
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๊ทธ ๋ฐฉํ–ฅ์€ ์‹œ๊ฐ„์ƒ ๋จผ์ € ํ™œ๋™์ด ์žˆ๋˜
08:14
The direction of the arrows
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08:15
flows from the region that's active first in time,
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์˜์—ญ์—์„œ ์‹œ์ž‘ํ•˜์—ฌ
08:18
and the arrowhead goes to the region that's active later.
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๋‚˜์ค‘์— ํ™œ๋™์„ ๋ณด์ธ ์˜์—ญ์œผ๋กœ ๋ฐฉํ–ฅ์ด ๋˜์–ด ์žˆ์Šต๋‹ˆ๋‹ค.
๊ทธ๋Ÿฌ๋‹ˆ๊นŒ ์ด ๊ฒฝ์šฐ๋ฅผ ์ž์„ธํžˆ ๋ณด์‹œ๋ฉด
08:22
So in this case, if you look carefully,
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08:24
most of the arrows flow from right to left.
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๋Œ€๋ถ€๋ถ„์˜ ํ™”์‚ด์ด ์˜ค๋ฅธ์ชฝ์—์„œ ์™ผ์ชฝ์œผ๋กœ ๊ฐ€์ฃ .
์ฆ‰, ์ •๋ณด๊ฐ€ ์—†๋Š” ์ชฝ์˜ ๋‘๋‡Œ ํ™œ๋™์ด ๋จผ์ € ์ผ์–ด๋‚˜๋Š” ๊ฒƒ์œผ๋กœ
08:26
That is, it looks as if the uninformed brain activity
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08:29
is happening first,
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๋ณด์ด๊ณ 
08:31
and then it's followed by activity in the informed brain.
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๊ทธ ๋‹ค์Œ์—๋Š”, ์ •๋ณด๋ฅผ ๊ฐ€์ง„ ์ชฝ์˜ ๋‘๋‡Œ ํ™œ๋™์ด ์ผ์–ด๋‚ฉ๋‹ˆ๋‹ค.
์–ด์จŒ๋“ , ์ด๊ฒƒ๋“ค์€ ํ˜‘์ƒ์ด ํƒ€๊ฒฐ๋œ ๊ฒฝ์šฐ๋“ค์ด์—ˆ์–ด์š”.
08:35
And by the way, these are trials where their deals were made.
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08:38
This is from the first two seconds.
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์ด๊ฑด ์ฒ˜์Œ 2์ดˆ๊ฐ„์˜ ๋ชจ์Šต์ž…๋‹ˆ๋‹ค.
08:40
We haven't finished analyzing this data, so we're still peeking in,
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์•„์ง ์ด ์ž๋ฃŒ์— ๋Œ€ํ•œ ๋ถ„์„์ด ๋๋‚˜์ง€ ์•Š์•„์„œ
์—ฌ์ „ํžˆ ๋“ค์—ฌ๋‹ค ๋ณด๊ณ  ์žˆ์–ด์š”. ์ €ํฌ๊ฐ€ ๋ฐ”๋ผ๋Š” ๊ฒƒ์€
08:43
but the hope is that we can say something in the first couple of seconds
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์ด ์‚ฌ๋žŒ๋“ค์ด ํ˜‘์ƒ์„ ๋ฐ›์•„๋“ค์ผ ๊ฒƒ์ธ์ง€ ๋ง ๊ฒƒ์ธ์ง€์— ๋Œ€ํ•ด ์ƒ๊ฐํ•˜๋Š” ์ฒ˜์Œ ๋ช‡ ์ดˆ ์‚ฌ์ด์—
08:46
about whether they'll make a deal or not,
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๋ญ”๊ฐ€ ๊ฒฐ๋ก ์„ ๋Œ์–ด๋‚ผ ์ˆ˜ ์žˆ๋Š” ๊ฒƒ์ด ์žˆ์—ˆ์œผ๋ฉด ํ•ฉ๋‹ˆ๋‹ค.
08:48
which could be very useful in thinking about avoiding litigation
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๊ทธ๋Ÿฐ ๊ฒฐ๊ณผ๋Š” ๋ณต์žกํ•œ ์ดํ˜ผ ๊ฐ™์€ ์†Œ์†ก์„ ํ”ผํ•˜๋Š”๋ฐ ์žˆ์–ด์„œ
๋งค์šฐ ์œ ์šฉํ•  ์ˆ˜ ์ž‡์Šต๋‹ˆ๋‹ค.
08:51
and ugly divorces and things like that.
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๊ทธ๋Ÿฐ ์‚ฌ๊ฑด๋“ค์€ ์ง€์—ฐ๋˜๊ฑฐ๋‚˜ ๊ฑฐ๋ถ€ํ•˜๋Š” ๊ฒƒ์œผ๋กœ ์ธํ•˜์—ฌ
08:53
Those are all cases in which a lot of value is lost by delay and strikes.
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์ˆ˜๋งŽ์€ ๊ฐ€์น˜๋ฅผ ์žƒ๊ฒŒ ๋˜๋Š” ๊ฒฝ์šฐ์ง€์š”.
08:58
Here's the case where the disagreements occur.
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์—ฌ๊ธฐ ์ด ๊ฒฝ์šฐ๋Š” ํ˜‘์ƒ์ด ๊ฒฐ๋ ฌ๋œ ๊ฒฝ์šฐ์—์š”.
09:00
You can see it looks different than the one before.
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์ด์ „ ๊ฒƒ๊ณผ๋Š” ๋‹ค๋ฅธ ์ ์„ ๋ณด์‹ค ์ˆ˜ ์žˆ์ฃ .
ํ›จ์”ฌ ๋” ๋งŽ์€ ํ™”์‚ดํ‘œ๊ฐ€ ์žˆ์Šต๋‹ˆ๋‹ค.
09:03
There's a lot more arrows.
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09:04
That means that the brains are synced up more closely
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๊ทธ๊ฑด ๋ฐ”๋กœ ๋‘๋‡Œ๊ฐ€ ๋™์‹œ์  ํ™œ๋™์— ํ›จ์”ฌ ๋” ๋งŽ์ด
์‹ค์‹œ๊ฐ„์œผ๋กœ ์ž‘๋™ํ•˜๊ณ  ์žˆ๋‹ค๋Š” ๋œป์ด์—์š”.
09:07
in terms of simultaneous activity,
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09:08
and the arrows flow clearly from left to right.
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ํ™”์‚ดํ‘œ๋“ค์€ ๋ถ„๋ช…ํžˆ ์™ผ์ชฝ์—์„œ ์˜ค๋ฅธ์ชฝ์„ ํ–ฅํ•ฉ๋‹ˆ๋‹ค.
์ฆ‰, ์ •๋ณด๋ฅผ ๊ฐ€์ง„ ๋‘๋‡Œ๊ฐ€ ๊ฒฐ์ •ํ•˜๋Š” ๊ฒƒ์ฒ˜๋Ÿผ ๋ณด์ด์ฃ .
09:11
That is, the informed brain seems to be deciding,
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"์ง€๊ธˆ์€ ํ˜‘์ƒํ•˜์ง€ ์•Š์„๊ฑฐ ๊ฐ™์€๋ฐ."
09:13
"We're probably not going to make a deal here."
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09:15
And then later, there's activity in the uninformed brain.
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๊ทธ๋ฆฌ๊ณ ๋Š” ๋‚˜์ค‘์— ์ •๋ณด๊ฐ€ ์—†๋Š” ์ชฝ์˜ ๋‘๋‡Œ์— ํ™œ๋™์ด ์ผ์–ด๋‚ฉ๋‹ˆ๋‹ค.
09:18
Next, I'm going to introduce you to some relatives.
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๋‹ค์Œ์€ ์—ฌ๋Ÿฌ๋ถ„๋“ค๊ป˜ ๋น„์Šทํ•œ ๊ฒƒ๋“ค์„ ๋ณด์—ฌ๋“œ๋ฆฌ์ฃ .
์ด๊ฒƒ๋“ค์€ ํ„ธ์ด ์žˆ๊ณ , ๋ƒ‰์ƒˆ๋„ ๋‚˜์ง€๋งŒ ๋น ๋ฅด๊ณ  ๊ฐ•ํ•ฉ๋‹ˆ๋‹ค.
09:21
They're hairy, smelly, fast and strong.
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09:23
You might be thinking back to your last Thanksgiving.
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์—ฌ๋Ÿฌ๋ถ„๋“ค์€ ์–ด์ฉŒ๋ฉด ์ง€๋‚œ ์ถ”์ˆ˜๊ฐ์‚ฌ์ ˆ์„ ์ƒ๊ฐํ•˜๊ณ  ๊ณ„์‹ค์ง€๋„ ๋ชจ๋ฅด๊ฒ ๊ตฐ์š”.
09:25
(Laughter)
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09:26
Maybe, if you had a chimpanzee with you.
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์—ฌ๋Ÿฌ๋ถ„๋“ค์—๊ฒŒ ์นจํŒฌ์ง€์™€ ๊ฐ™์€ ๋ฉด์ด ์žˆ์„์ง€๋„ ๋ชจ๋ฅด์ฃ .
09:29
Charles Darwin and I and you broke off from the family tree from chimpanzees
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์ €์™€ ์ฑจ์Šค ๋‹ค์œˆ, ๊ทธ๋ฆฌ๊ณ  ์—ฌ๋Ÿฌ๋ถ„์€ ๋ชจ๋‘ ์•ฝ 5๋ฐฑ๋งŒ๋…„ ์ „์—
์นจํŒฌ์ง€์˜ ๊ฐ€๊ณ„๋กœ๋ถ€ํ„ฐ ๊ฐˆ๋ผ์ ธ ๋‚˜์™”์Šต๋‹ˆ๋‹ค.
09:33
about five million years ago.
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09:34
They're still our closest genetic kin.
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์นจํŒฌ์ง€๋Š” ์œ ์ „์ ์œผ๋กœ ์—ฌ์ „ํžˆ ์šฐ๋ฆฌ์—๊ฒŒ ๊ฐ€์žฅ ๊ฐ€๊นŒ์šด ์นœ์ฒ™๋ป˜์ฏค ๋ฉ๋‹ˆ๋‹ค.
09:36
We share 98.8 percent of the genes.
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์นจํŒฌ์ง€์™€ ์ธ๊ฐ„์€ ์œ ์ „์ž์˜ 98.8%๋ฅผ ๊ณต์œ ํ•˜์ฃ .
09:38
We share more genes with them than zebras do with horses.
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์ด ๋‘ ์ข…์€ ์–ผ๋ฃฉ๋ง๊ณผ ๋ง์ด ๊ณต์œ ํ•˜๋Š” ์œ ์ „์ž๋ณด๋‹ค ๋” ๋งŽ์€ ์œ ์ „์ž๋ฅผ ๊ณต์œ ํ•˜๊ณ  ์žˆ์–ด์š”.
09:41
And we're also their closest cousin.
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์ธ๊ฐ„๊ณผ ์นจํŒฌ์ง€๋Š” ๊ฐ€์žฅ ๊ฐ€๊นŒ์šด ์‚ฌ์ดŒ์ž…๋‹ˆ๋‹ค.
09:43
They have more genetic relation to us than to gorillas.
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์นจํŒฌ์ง€๋Š” ๊ณ ๋ฆด๋ผ๋ณด๋‹ค๋„ ์ธ๊ฐ„๊ณผ ๋” ๋ฐ€์ ‘ํ•œ ๊ด€๊ณ„๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ์–ด์š”.
09:46
So, how humans and chimpanzees behave differently
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๊ทธ๋ž˜์„œ ์ธ๊ฐ„๊ณผ ์นจํŒฌ์ง€๊ฐ€ ์–ผ๋งˆ๋‚˜ ๋‹ค๋ฅด๊ฒŒ ํ–‰๋™ํ•˜๋Š”๊ฐ€๋ฅผ ๋ณด๋ฉด
09:48
might tell us a lot about brain evolution.
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๋‘๋‡Œ์˜ ์ง„ํ™”์— ๋Œ€ํ•ด์„œ ๋งŽ์€ ๊ฒƒ์„ ์•Œ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
09:51
This is an amazing memory test
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์ด๊ฒƒ์€ ์ผ๋ณธ์˜ ๋‚˜๊ณ ์•ผ์— ์žˆ๋Š”
09:53
from [Kyoto], Japan, the Primate Research Institute,
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์˜์žฅ๋ฅ˜ ์—ฐ๊ตฌ์†Œ์—์„œ ์ˆ˜ํ–‰ํ•œ ๋†€๋ž„๋งŒํ•œ ๊ธฐ์–ต๋ ฅ ์‹คํ—˜์ž…๋‹ˆ๋‹ค.
09:56
where they've done a lot of this research.
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์ด ์—ฐ๊ตฌ์†Œ์—์„œ๋Š” ์ด๋Ÿฐ ์—ฐ๊ตฌ๋ฅผ ์ƒ๋‹นํžˆ ๋งŽ์ด ํ•˜์ฃ .
09:58
This goes back a ways. They're interested in working memory.
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์ด๊ฑด ๊ฝค ์˜ค๋ž˜์ „ ์ผ์ธ๋ฐ์š”, ์—ฐ๊ตฌ์†Œ์—์„œ๋Š” ์ž‘์—… ๊ธฐ์–ต์— ๊ด€์‹ฌ์„ ๊ฐ€์กŒ์Šต๋‹ˆ๋‹ค.
์นจํŒฌ์ง€๊ฐ€ ๋ณด์ฃ , ์กฐ์‹ฌ์Šค๋Ÿฝ๊ฒŒ ๊ด€์ฐฐํ•ฉ๋‹ˆ๋‹ค.
10:01
The chimp will see, watch carefully,
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์นจํŒฌ์ง€๋Š” 2๋ฐฑ๋งŒ๋ถ„์˜ 1์ดˆ ์ •๋„์˜ ์ˆœ๊ฐ„ ๋™์•ˆ์—
10:03
they'll see 200 milliseconds' exposure -- that's fast, eight movie frames --
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-- ๊ต‰์žฅํžˆ ๋น ๋ฅธ๊ฑฐ์ฃ , ๊ทธ๊ฑด 8๊ฐœ์˜ ์˜ํ™” ์žฅ๋ฉด์ด์—์š”. --
10:06
of numbers one, two, three, four, five.
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1, 2, 3, 4, 5 ๋ผ๋Š” ์ˆซ์ž๋ฅผ ๋ด…๋‹ˆ๋‹ค.
10:08
Then they disappear and are replaced by squares,
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๊ทธ ๋‹ค์Œ์— ์ˆซ์ž๊ฐ€ ์‚ฌ๋ผ์ง€๊ณ  ๋Œ€์‹ ์— 4๊ฐํ˜•์„ ๊ฐ€์ ธ๋‹ค ๋†“์ฃ .
10:10
and they have to press the squares
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์นจํŒฌ์ง€๋Š” ๋‚ฎ์€ ๊ฒƒ์—์„œ ๋†’์€ ์ˆœ์„œ๋กœ
10:12
that correspond to the numbers from low to high
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์ˆซ์ž์— ๋Œ€์‘ํ•˜๋Š” 4๊ฐํ˜•์„ ๋ˆŒ๋Ÿฌ์•ผ ํ•ฉ๋‹ˆ๋‹ค.
10:14
to get an apple reward.
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๊ทธ๋Ÿฌ๋ฉด ์‚ฌ๊ณผ๋ฅผ ์ƒ์œผ๋กœ ๋ฐ›์•„์š”.
์นจํŒฌ์ง€๋“ค์ด ์–ด๋–ป๊ฒŒ ํ•˜๋Š”์ง€ ๋ณด์ฃ .
10:16
Let's see how they can do it.
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10:28
This is a young chimp.
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์ Š์€ ์นจํŒฌ์ง€๋„ค์š”. ์‚ฌ๋žŒ๋“ค์ฒ˜๋Ÿผ,
10:29
The young ones are better than the old ones, just like humans.
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์ Š์€ ์นจํŒฌ์ง€๋“ค์ด ๋‚˜์ด๋“  ์นจํŒฌ์ง€๋ณด๋‹ค ์ž˜ ํ•ฉ๋‹ˆ๋‹ค.
10:32
(Laughter)
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์นจํŒฌ์ง€๋Š” ๊ฝค๋‚˜ ๊ฒฝํ—˜์ด ๋งŽ์•„์š”, ์ด๋Ÿฐ๊ฑด
10:33
And they're highly experienced,
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์ˆ˜์ฒœ๋ฒˆ๋„ ๋” ๋ฐ˜๋ณตํ–ˆ์œผ๋‹ˆ๊นŒ์š”.
10:35
they've done this thousands of times.
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์˜ˆ์ƒํ•  ์ˆ˜ ์žˆ๋“ฏ์ด, ๋ถ„๋ช…ํžˆ ๋Œ€๋‹จํ•œ ํ›ˆ๋ จ์˜ ํšจ๊ณผ๊ฐ€ ์žˆ์–ด์š”.
10:37
Obviously there's a big training effect, as you can imagine.
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(์›ƒ์Œ)
10:40
(Laughter)
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10:41
You can see they're very blasรฉ and effortless.
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๋ณด์‹œ๋‹ค์‹œํ”ผ ์นจํŒฌ์ง€๋“ค์€ ๋ฌด์‹ฌํ•˜๊ธฐ๋„ ํ•˜๊ณ  ๋˜ ํ•œํŽธ ๊ทธ๋ฆฌ ๋…ธ๋ ฅ์„ ๋“ค์ด์ง€๋„ ์•Š์Šต๋‹ˆ๋‹ค.
10:43
Not only can they do it very well, they do it in a sort of lazy way.
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์ด๋Ÿฐ๊ฑธ ์ž˜ ํ•  ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์•„์ฃผ ๊ท€์ฐฎ๋‹ค๋Š” ๋“ฏ์ด ํ•ด๋‚ด์ฃ .
10:46
(Laughter)
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10:47
Who thinks you could beat the chimps?
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๊ทธ๋ ‡์ฃ ? ์นจํŒฌ์ง€๋ฅผ ์ด๊ธธ ์ˆ˜ ์žˆ๋‹ค๊ณ  ์ƒ๊ฐํ•˜์‹œ๋Š” ๋ถ„์ด ๊ณ„์‹ ๊ฐ€์š”?
10:49
(Laughter)
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10:50
Wrong. (Laughter)
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ํ‹€๋ ธ์Šต๋‹ˆ๋‹ค. (์›ƒ์Œ)
10:52
We can try. We'll try. Maybe we'll try.
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์šฐ๋ฆฌ๊ฐ€ ํ•ด๋ณด์ฃ . ์•„๋งˆ ์‹œ๋„๋Š” ํ•ด๋ณผ ์ˆ˜ ์žˆ์„๊ฒ๋‹ˆ๋‹ค.
10:54
OK, so the next part of the study I'm going to go quickly through
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์ข‹์Šต๋‹ˆ๋‹ค. ์ œ๊ฐ€ ๋น ๋ฅด๊ฒŒ ์ง€๋‚˜๊ฐˆ
์ด ์—ฐ๊ตฌ์˜ ๋‹ค์Œ ๋ถ€๋ถ„์€
10:58
is based on an idea of Tetsuro Matsuzawa.
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ํ…Œ์ธ ๋กœ ๋งˆ์ธ ์ž์™€(Tetsuro Matsuzawa)์˜ ์•„์ด๋””์–ด์— ๊ธฐ๋ฐ˜์„ ๋‘๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
11:01
He had a bold idea he called the "cognitive trade-off hypothesis."
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๊ทธ๋Š” ์•„์ฃผ ๋Œ€๋‹ดํ•œ ์•„์ด๋””์–ด๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ์—ˆ์ฃ . -- ๊ทธ๋Š” ๊ทธ๊ฒƒ์„ ์ธ์ง€์  ๊ท ํ˜• ๊ฐ€์ •์ด๋ผ๊ณ  ๋ถˆ๋ €์Šต๋‹ˆ๋‹ค.
์šฐ๋ฆฌ๋Š” ์นจํŒฌ์ง€๊ฐ€ ๋น ๋ฅด๊ณ  ๊ฐ•ํ•˜๋‹ค๋Š” ๊ฒƒ์„ ์•Œ๊ณ  ์žˆ์–ด์š”.
11:05
We know chimps are faster and stronger; they're also obsessed with status.
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์นจํŒฌ์ง€๋Š” ๋˜ํ•œ ์ƒ๋Œ€์  ์ง€์œ„์— ๊ฐ•ํ•˜๊ฒŒ ์ง‘์ฐฉํ•ฉ๋‹ˆ๋‹ค.
ํ…Œ์ธ ๋กœ์˜ ์ƒ๊ฐ์€ ์–ด์ฉŒ๋ฉด ์นจํŒฌ์ง€๋“ค์€ ๋‘๋‡Œ์˜ ํ™œ๋™์„ ๋ณด์กดํ•˜๊ณ  ์žˆ์–ด์„œ
11:08
His thought was, maybe they've preserved brain activities
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์ž๊ธฐ๋“ค์ด ์ƒ๋Œ€์  ์ง€์œ„์— ๋Œ€ํ•ด ํ˜‘์ƒํ•˜๋Š”๋ฐ
11:11
and practice them in development
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11:12
that are really, really important to them to negotiate status and to win,
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์—„์ฒญ๋‚˜๊ฒŒ ์ค‘์š”ํ•œ ๋‹จ๊ณ„์—์„œ
๊ทธ๊ฒƒ์„ ์‚ฌ์šฉํ• ์ง€๋„ ๋ชจ๋ฅธ๋‹ค๊ณ  ์ƒ๊ฐํ–ˆ์ฃ .
11:16
which is something like strategic thinking during competition.
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์ด๋Ÿฐ ๊ฒƒ์€ ๊ฒฝ์Ÿ์— ์žˆ์–ด์„œ ์ „๋žต์ ์ธ ์‚ฌ๊ณ ์™€ ์œ ์‚ฌํ•ฉ๋‹ˆ๋‹ค.
11:19
So we're going to check that out
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๊ทธ๋ž˜์„œ ์ €ํฌ๊ฐ€ ๊ทธ๊ฒƒ์„ ํ™•์ธํ•˜๋ ค๊ณ  ํ•ฉ๋‹ˆ๋‹ค.
11:21
by having the chimps actually play a game
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๊ทธ ๋ฐฉ๋ฒ•์€ ์นจํŒฌ์ง€์—๊ฒŒ ์‹ค์ œ๋กœ
11:23
by touching two touch screens.
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๋‘๊ฐœ์˜ ์Šคํฌ๋ฆฐ์„ ํ„ฐ์น˜ํ•˜๋Š” ๊ฒŒ์ž„์„ ํ•˜๋„๋ก ํ•˜๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค.
11:26
The chimps are interacting with each other through the computers.
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์นจํŒฌ์ง€๋“ค์€ ์‹ค์ œ๋กœ ์ปดํ“จํ„ฐ๋ฅผ ํ†ตํ•ด ์„œ๋กœ ์ƒํ˜ธ ์ž‘์šฉ์„ ํ•ฉ๋‹ˆ๋‹ค.
์˜ค๋ฅธ์ชฝ์ด๋‚˜ ์™ผ์ชฝ์„ ๋ˆ„๋ฅด๋Š” ๊ฒ๋‹ˆ๋‹ค.
11:29
They'll press left or right.
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11:30
One chimp is called a matcher; they win if they press left-left,
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ํ•œ ์นจํŒจ์ง€๋Š” "๋งž์ถ”๋Š” ์ชฝ"๋ผ๊ณ  ๋ถˆ๋ฆฝ๋‹ˆ๋‹ค.
์นจํŒฌ์ง€๊ฐ€ ์™ผ์ชฝ์„ ๋‘๋ฒˆ, ๋˜๋Š” ์˜ค๋ฅธ์ชฝ์„ ๋‘๋ฒˆ ๋ˆ„๋ฅด๋ฉด ์ด๊ธฐ๋Š” ๊ฑฐ์—์š”.
11:34
like a seeker finding someone in hide-and-seek, or right-right.
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์ˆ ๋ž˜์žก๊ธฐ์—์„œ ๋ˆ„๊ตฐ๊ฐ€๋ฅผ ์ฐพ๋Š” ์‚ฌ๋žŒ์ฒ˜๋Ÿผ ๋ง์ด์ฃ .
11:37
The mismatcher wants to mismatch;
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"๋งž์ถ”๊ธฐ ์‹ซ์€ ์ชฝ"์€ ์–ด๊ธ‹๋‚ด๋ ค๊ณ  ํ•ฉ๋‹ˆ๋‹ค.
์ด๋“ค์€ ์ƒ๋Œ€ ์นจํŒฌ์ง€์˜ ๋ฐ˜๋Œ€์ชฝ ํ™”๋ฉด์„ ๋ˆ„๋ฅด๋ ค๊ณ  ํ•ด์š”.
11:39
they want to press the opposite screen of the chimp.
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11:41
And the rewards are apple cube rewards.
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๋งž์ถœ ๊ฒฝ์šฐ ์ƒ์œผ๋กœ๋Š” ์‚ฌ๊ณผ ์กฐ๊ฐ์„ ์ค๋‹ˆ๋‹ค.
11:44
So here's how game theorists look at these data.
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์ด๊ฒƒ์€ ๊ฒŒ์ž„์ด๋ก ๊ฐ€๋“ค์ด ์ด๋Ÿฐ ๊ฒฐ๊ณผ ์ž๋ฃŒ๋ฅผ ๋ณด๋Š” ๋ฐฉ๋ฒ•์ž…๋‹ˆ๋‹ค.
11:46
This is a graph of the percentage of times
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๊ทธ๋ž˜ํ”„์˜ x-์ถ•์€ "๋งž์ถ”๋Š” ์ชฝ"์ด ์˜ณ์€ ์„ ํƒ์„ ํ•˜๋Š”
11:48
the matcher picked right on the x-axis
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ํšŸ์ˆ˜๋ฅผ ๋ฐฑ๋ถ„์œจ๋กœ ๋‚˜ํƒ€๋‚ธ ๊ฒƒ์ด๊ณ 
11:51
and the percentage of times they picked right
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"๋งž์ถ”๊ธฐ ์‹ซ์€ ์ชฝ"์ด ์˜ณ๊ฒŒ ์„ ํƒํ•˜๋Š” ๊ฒƒ์„
์˜ˆ์ƒํ•œ ๋ฐฑ๋ถ„์œจ์„ y-์ถ•์— ๋‚˜ํƒ€๋‚ธ ๊ฒƒ์ด์ฃ .
11:53
by the mismatcher on the y-axis.
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11:55
So a point here is the behavior by a pair of players,
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์—ฌ๊ธฐ์„œ ์š”์ ์€ ๊ฒŒ์ž„์„ ํ•˜๋Š” ์นจํŒฌ์ง€ ํ•œ ์Œ์˜ ํ–‰๋™์ž…๋‹ˆ๋‹ค.
11:58
one trying to match, one trying to mismatch.
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ํ•˜๋‚˜๋Š” ๋งž์ถฐ๋ณด๋ ค๊ณ  ํ•˜๊ณ  ๋‹ค๋ฅธ ํ•˜๋‚˜๋Š” ์–ด๊ธ‹๋‚˜๊ฒŒ ํ•˜๋ ค๊ณ  ํ•ฉ๋‹ˆ๋‹ค.
12:01
The NE square in the middle -- actually, NE, CH and QRE --
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์ค‘๊ฐ„์— ์žˆ๋Š” NE ๋Š” -- ์‚ฌ์‹ค NE, CH, QRE ๋Š”
12:04
those are three different theories of Nash equilibrium and others,
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๋‚ด์‰ฌ ํ‰ํ˜•์ด๋ก ๊ณผ ๊ฐ™์€ 3๊ฐœ์˜ ๋‹ค๋ฅธ ์ด๋ก ๋“ค์ž…๋‹ˆ๋‹ค.
์ด๊ฒƒ๋“ค์€ ์ด๋ก ์ด ์˜ˆ์ธกํ•˜๋Š” ๋ฐ”๋ฅผ ๋‚˜ํƒ€๋‚ด์ฃ .
12:07
tells you what the theory predicts,
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12:09
which is that they should match 50-50,
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์˜ˆ์ธก์— ์˜ํ•˜๋ฉด ์นจํŒฌ์ง€๋“ค์€ 50-50 ์œผ๋กœ ์ด๊ฒจ์•ผ ํ•ฉ๋‹ˆ๋‹ค.
12:11
because if you play left too much, for example,
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์™œ๋ƒํ•˜๋ฉด, ์˜ˆ๋ฅผ ๋“ค์–ด ์ง€๋‚˜์น˜๊ฒŒ ์™ผ์ชฝ์„ ๋งŽ์ด ๋ˆ„๋ฅด๋ฉด,
12:13
I can exploit that if I'm the mismatcher by then playing right.
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์—‰ํ„ฐ๋ฆฌ ์นจํŒฌ์ง€๊ฐ€ ์˜ค๋ฅธ์ชฝ์„ ๋ˆ„๋ฅธ๋‹ค๋Š” ์ ์„ ์ด์šฉํ•  ์ˆ˜ ์žˆ๊ธฐ ๋•Œ๋ฌธ์ด์ฃ .
12:16
And as you can see, the chimps -- each chimp is one triangle --
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๋ณด์‹œ๋‹ค์‹œํ”ผ ๊ฐ๊ฐ์˜ ์นจํŒฌ์ง€๋Š” ์‚ผ๊ฐํ˜•์œผ๋กœ ํ‘œ์‹œ๋˜๋ฉฐ
12:19
are circled around, hovering around that prediction.
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์›ํ˜•์œผ๋กœ ๋ฌด๋ฆฌ์ง€์–ด ๊ทธ ์˜ˆ์ƒ๋Œ€๋กœ ์›€์ง์ž…๋‹ˆ๋‹ค.
์ด์ œ ์ƒ์œผ๋กœ ์ฃผ๋Š” ๊ฒƒ์„ ๋ฐ”๊ฟ”๋ณด์ฃ .
12:23
Now we move the payoffs.
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12:24
We're going to make the left-left payoff for the matcher a little higher.
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์™ผ์ชฝ, ์™ผ์ชฝ์œผ๋กœ ๋งž์ถœ ๊ฒฝ์šฐ ์ƒ์„ ์กฐ๊ธˆ ๋” ๋Š˜๋ ค๋ณด๋Š” ๊ฒ๋‹ˆ๋‹ค.
12:28
Now they get three apple cubes.
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์ด์ œ ๊ทธ๋“ค์€ 3๊ฐœ์˜ ์‚ฌ๊ณผ ์กฐ๊ฐ์„ ๊ฐ€์ ธ๊ฐ€์ฃ .
12:29
Game theoretically, that should make the mismatcher's behavior shift:
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๊ฒŒ์ž„์ด๋ก ์— ๋”ฐ๋ฅด๋ฉด, ๋งž์ถ”๊ธฐ ์‹ซ์€ ์ชฝ์˜ ํ–‰๋™์ด ๋ฐ”๋€Œ์–ด์•ผ ํ•ฉ๋‹ˆ๋‹ค.
์™œ๋ƒํ•˜๋ฉด ์‹คํŒจํ•˜๋Š” ์ชฝ๋„ ์ƒ๊ฐ์„ ํ•˜๊ฑฐ๋“ ์š”,
12:33
the mismatcher will think, "Oh, this guy's going to go for the big reward,
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์•„ ์ด ์นœ๊ตฌ๊ฐ€ ์ปค๋‹ค๋ž€ ์ƒ์„ ๋ฐ›์„ ๊ฒƒ ๊ฐ™์œผ๋‹ˆ
๋‚˜๋Š” ์˜ค๋ฅธ์ชฝ์œผ๋กœ ๊ฐ€์„œ, ์ € ์นœ๊ตฌ๊ฐ€ ๊ทธ ์ƒ์„ ๋ชป ๋ฐ›๊ฒŒ ํ•ด์•ผ๊ฒ ๋‹ค๋ผ๊ณ  ์ƒ๊ฐํ•˜๋Š”๊ฑฐ์ฃ .
12:36
so I'll go to the right, make sure he doesn't get it."
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๋ณด์‹œ๋‹ค์‹œํ”ผ, ์ด๋“ค์˜ ํ–‰๋™์€ ๋‚ด์‰ฌ ํ‰ํ˜•์ ์˜
12:39
And as you can see, their behavior moves up
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์ด๋Ÿฐ ๋ณ€ํ™”์˜ ๋ฐฉํ–ฅ์œผ๋กœ ์˜ฌ๋ผ๊ฐ‘๋‹ˆ๋‹ค.
12:41
in the direction of this change in the Nash equilibrium.
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12:44
Finally, we changed the payoffs one more time.
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๊ฒฐ๊ตญ, ์šฐ๋ฆฌ๋Š” ์ƒ์„ ํ•œ๋ฒˆ ๋” ๋ฐ”๋€Œ๋ดค์Šต๋‹ˆ๋‹ค.
12:46
Now it's four apple cubes,
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์ด์ œ ์ƒ์€ ์‚ฌ๊ณผ ๋„ค ์ชฝ์ด์—์š”.
12:47
and their behavior again moves towards the Nash equilibrium.
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๊ทธ๋Ÿฌ์ž ์นจํŒฌ์ง€๋“ค์˜ ํ–‰๋™์€ ๋‹ค์‹œ ๋‚ด์‰ฌ ํ‰ํ˜•์ ์ชฝ์œผ๋กœ ์›€์ง์—ฌ ๊ฐ‘๋‹ˆ๋‹ค.
๋Œ€๋‹จํ•˜์ฃ , ๊ทธ๋ ‡์ง€๋งŒ ์นจํŒฌ์ง€ ๋“ค์˜ ํ‰๊ท ์„ ๋‚ด๋ฉด
12:50
It's sprinkled around, but if you average the chimps out,
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์‚ฌ์‹ค ์•„์ฃผ ๋น„์Šทํ•ด์„œ 0.01์˜ ๋ฒ”์œ„์•ˆ์— ๋“ญ๋‹ˆ๋‹ค.
12:53
they're really close, within .01.
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์นจํŒฌ์ง€๋“ค์€ ์ €ํฌ๊ฐ€ ๊ด€์ฐฐํ•œ ๋‹ค๋ฅธ ์–ด๋–ค ์ข…๋ณด๋‹ค ๊ฐ€๊น์Šต๋‹ˆ๋‹ค.
12:54
They're actually closer than any species we've observed.
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12:57
What about humans? You think you're smarter than a chimpanzee?
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์ธ๊ฐ„์€ ์–ด๋–จ๊นŒ์š”? ์ธ๊ฐ„์ด ์นจํŒฌ์ง€๋ณด๋‹ค ์˜๋ฆฌํ•˜๋‹ค๊ณ  ์ƒ๊ฐํ•˜์‹œ์ฃ ?
์—ฌ๊ธฐ ๋…น์ƒ‰๊ณผ ํŒŒ๋ž€์ƒ‰ ๋ฌด๋ฆฌ์˜ ์‚ฌ๋žŒ๋“ค์ด ์žˆ์Šต๋‹ˆ๋‹ค.
13:01
Here's two human groups in green and blue.
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์ด๋“ค์€ ๊ฑฐ์˜ 50 ๋Œ€ 50์ธ๋ฐ, ์‚ฌ๋žŒ๋“ค์€ ์ƒํ’ˆ์— ๋Œ€ํ•ด์„œ ๊ทธ๋ ‡๊ฒŒ ๋ฏผ๊ฐํ•˜๊ฒŒ ๋Œ€์‘ํ•˜์ง€ ์•Š์•„์š”.
13:04
They're closer to 50-50; they're not responding to payoffs as closely.
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13:07
And also if you study their learning in the game,
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๊ฒŒ์ž„์—์„œ ์‚ฌ๋žŒ๋“ค์ด ํ•™์Šตํ•˜๋Š” ๊ฒƒ์„ ์—ฐ๊ตฌํ•ด๋ณด๋ฉด
์‚ฌ๋žŒ๋“ค์€ ์•ž์˜ ๊ฒฝ์šฐ์ฒ˜๋Ÿผ ๊ทธ๋ ‡๊ฒŒ ๋ฏผ๊ฐํ•˜์ง€ ์•Š์Šต๋‹ˆ๋‹ค.
13:10
they aren't as sensitive to previous rewards.
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์นจํŒฌ์ง€๋“ค์ด ์ธ๊ฐ„๋ณด๋‹ค ๋” ์ž˜ ํ•ด์š”.
13:12
The chimps play better than the humans, in terms of adhering to game theory.
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๊ฒŒ์ž„ ์ด๋ก ์— ๋” ์ถฉ์‹คํ•˜๋‹ค๋Š” ๋ฉด์—์„œ ์ž˜ ํ•œ๋‹ค๋Š” ๋œป์ž…๋‹ˆ๋‹ค.
์ด๋“ค์€ ์ผ๋ณธ๊ณผ ์•„ํ”„๋ฆฌ์นด์ธ์˜
13:16
And these are two different groups of humans, from Japan and Africa;
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์„œ๋กœ ๋‹ค๋ฅธ ๋‘ ๋ชจ์ž„์ž…๋‹ˆ๋‹ค. ์ด๋“ค์€ ๊ฝค ์ž˜ ํ‰๋‚ด๋ฅผ ๋‚ด์ง€๋งŒ
13:19
they replicate quite nicely.
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์–ด๋Š ์ชฝ๋„ ์นจํŒฌ์ง€๊ฐ€ ๋„๋‹ฌํ–ˆ๋˜ ๊ณณ๊นŒ์ง€ ๊ฐ€๊นŒ์ด ๊ฐ€์ง€๋Š” ๋ชปํ•ฉ๋‹ˆ๋‹ค.
13:20
None of them are close to where the chimps are.
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์ด์ œ ์˜ค๋Š˜ ์šฐ๋ฆฌ๊ฐ€ ์•Œ์•„๋‚ธ ๊ฒƒ๋“ค์ด ์žˆ์Šต๋‹ˆ๋‹ค.
13:23
So, some things we learned:
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13:24
people seem to do a limited amount of strategic thinking using theory of mind.
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์ธ๊ฐ„์€ ๋งˆ์Œ์˜ ์ด๋ก ์„ ์ด์šฉํ•œ ์ „๋žต์  ์‚ฌ๊ณ ์˜ ๋ฒ”์œ„๊ฐ€
์ œํ•œ์ ์ž…๋‹ˆ๋‹ค.
13:28
We have preliminary evidence from bargaining
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์šฐ๋ฆฌ๋Š” ๋‘๋‡Œ์—์„œ์˜ ์ดˆ๊ธฐ ๊ฒฝ๊ณ  ์‹ ํ˜ธ๊ฐ€
13:30
that early warning signs in the brain might be used to predict
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๋ˆ์ด ๋“œ๋Š” ๋‚˜์œ ๋ถˆํ˜‘์ด ์ผ์–ด๋‚ ์ง€ ์˜ˆ์ธกํ•˜๋Š” ํ˜‘์ƒ์—์„œ
์ด๋ฏธ ์ „์ดˆ์ ์ธ ์ฆ๊ฑฐ๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
13:33
whether there'll be a bad disagreement that costs money,
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๊ทธ๋ฆฌ๊ณ  ๊ฒŒ์ž„ ์ด๋ก ์— ๋”ฐ๋ฅด๋ฉด,
13:36
and chimps are "better" competitors than humans,
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์นจํŒฌ์ง€๊ฐ€ ์ธ๊ฐ„๋ณด๋‹ค ๋” ์šฐ์ˆ˜ํ•œ ๊ฒฝ์Ÿ์ž์ž…๋‹ˆ๋‹ค..
13:38
as judged by game theory.
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13:39
Thank you.
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๊ฐ์‚ฌํ•ฉ๋‹ˆ๋‹ค.
13:41
(Applause)
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(๋ฐ•์ˆ˜)
์ด ์›น์‚ฌ์ดํŠธ ์ •๋ณด

์ด ์‚ฌ์ดํŠธ๋Š” ์˜์–ด ํ•™์Šต์— ์œ ์šฉํ•œ YouTube ๋™์˜์ƒ์„ ์†Œ๊ฐœํ•ฉ๋‹ˆ๋‹ค. ์ „ ์„ธ๊ณ„ ์ตœ๊ณ ์˜ ์„ ์ƒ๋‹˜๋“ค์ด ๊ฐ€๋ฅด์น˜๋Š” ์˜์–ด ์ˆ˜์—…์„ ๋ณด๊ฒŒ ๋  ๊ฒƒ์ž…๋‹ˆ๋‹ค. ๊ฐ ๋™์˜์ƒ ํŽ˜์ด์ง€์— ํ‘œ์‹œ๋˜๋Š” ์˜์–ด ์ž๋ง‰์„ ๋”๋ธ” ํด๋ฆญํ•˜๋ฉด ๊ทธ๊ณณ์—์„œ ๋™์˜์ƒ์ด ์žฌ์ƒ๋ฉ๋‹ˆ๋‹ค. ๋น„๋””์˜ค ์žฌ์ƒ์— ๋งž์ถฐ ์ž๋ง‰์ด ์Šคํฌ๋กค๋ฉ๋‹ˆ๋‹ค. ์˜๊ฒฌ์ด๋‚˜ ์š”์ฒญ์ด ์žˆ๋Š” ๊ฒฝ์šฐ ์ด ๋ฌธ์˜ ์–‘์‹์„ ์‚ฌ์šฉํ•˜์—ฌ ๋ฌธ์˜ํ•˜์‹ญ์‹œ์˜ค.

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