Nicolas Perony: Puppies! Now that I've got your attention, complexity theory

129,045 views

2014-01-30 ใƒป TED


New videos

Nicolas Perony: Puppies! Now that I've got your attention, complexity theory

129,045 views ใƒป 2014-01-30

TED


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

๋ฒˆ์—ญ: Jihyeon J. Kim ๊ฒ€ํ† : Kwangmin Lee
00:15
Science,
0
15393
1228
๊ณผํ•™์€
00:16
science has allowed us to know so much
1
16621
3337
์šฐ์ฃผ์˜ ๋จผ ๊ตฌ์„๊นŒ์ง€๋„
00:19
about the far reaches of the universe,
2
19958
3026
์šฐ๋ฆฌ์—๊ฒŒ ๋งŽ์€ ๊ฒƒ์„ ์•Œ๋ ค์ค๋‹ˆ๋‹ค.
00:22
which is at the same time tremendously important
3
22984
3195
๊ต‰์žฅํžˆ ์ค‘์š”ํ•˜๋ฉด์„œ ๋™์‹œ์—
00:26
and extremely remote,
4
26179
2066
๋„ˆ๋ฌด๋‚˜ ๋จผ ์šฐ์ฃผ์— ๋Œ€ํ•ด์„œ์š”.
00:28
and yet much, much closer,
5
28245
2459
ํ•˜์ง€๋งŒ ์šฐ๋ฆฌ์™€ ๋” ๊ฐ€๊นŒ์ด์— ์žˆ๋Š” ๊ฒƒ๋“ค
00:30
much more directly related to us,
6
30704
2091
์šฐ๋ฆฌ์—๊ฒŒ ๋” ์ง์ ‘์ ์œผ๋กœ ๊ด€๋ จ๋˜์–ด ์žˆ๋Š”
00:32
there are many things we don't really understand.
7
32795
2468
๋งŽ์€ ๊ฒƒ๋“ค์€ ์ž˜ ์•Œ์ง€ ๋ชปํ•ฉ๋‹ˆ๋‹ค.
00:35
And one of them is the extraordinary
8
35263
2129
๊ทธ ์ค‘ ํ•˜๋‚˜๊ฐ€ ์ฃผ๋ณ€์˜ ๋™๋ฌผ์—๊ฒŒ ์žˆ๋Š”
00:37
social complexity of the animals around us,
9
37392
3326
ํŠน๋ณ„ํ•œ ์‚ฌํšŒ์  ๋ณตํ•ฉ์„ฑ์ž…๋‹ˆ๋‹ค.
00:40
and today I want to tell you a few stories
10
40718
2016
์˜ค๋Š˜ ์ €๋Š” ๋™๋ฌผ์˜ ๋ณตํ•ฉ์„ฑ์— ๋Œ€ํ•œ
00:42
of animal complexity.
11
42734
2008
์ด์•ผ๊ธฐ๋ฅผ ํ•˜๋ ค๊ณ  ํ•ฉ๋‹ˆ๋‹ค.
00:44
But first, what do we call complexity?
12
44742
3350
๋จผ์ €, ๋ฌด์—‡์„ ๋ณตํ•ฉ์„ฑ์ด๋ผ๊ณ  ํ• ๊นŒ์š”?
00:48
What is complex?
13
48092
1487
๋ณตํ•ฉ์ ์ด๋ž€ ๋ฌด์—‡์ผ๊นŒ์š”?
00:49
Well, complex is not complicated.
14
49579
3427
์Œ, ๋ณตํ•ฉ์ ์ด๋ผ๋Š” ๊ฒƒ์€ ๋ณต์žกํ•œ ๊ฒƒ์ด ์•„๋‹™๋‹ˆ๋‹ค.
00:53
Something complicated comprises many small parts,
15
53006
3448
๋ณต์žกํ•œ ๊ฒƒ์€ ์ˆ˜ ๋งŽ์€ ์ž‘์€ ๋ถ€๋ถ„๋“ค๋กœ ์ด๋ฃจ์–ด์ ธ ์žˆ๋Š”๋ฐ,
00:56
all different, and each of them
16
56454
2430
๋‹ค๋ฅธ ๊ฐ๊ฐ์˜ ๋ถ€๋ถ„๋“ค์€
00:58
has its own precise role in the machinery.
17
58899
3104
์กฐ์ง ์•ˆ์—์„œ ๋ถ„๋ช…ํžˆ ๊ทธ๊ฒƒ๋งŒ์˜ ์—ญํ• ์ด ์žˆ์Šต๋‹ˆ๋‹ค.
01:02
On the opposite, a complex system
18
62003
2811
๋ฐ˜๋Œ€๋กœ ๋ณตํ•ฉ์ ์ธ ์‹œ์Šคํ…œ์€
01:04
is made of many, many similar parts,
19
64814
2641
๋งŽ์€ ์œ ์‚ฌํ•œ ๋ถ€๋ถ„๋“ค๋กœ ์ด๋ฃจ์–ด์ ธ ์žˆ๊ณ ,
01:07
and it is their interaction
20
67455
2008
์ด ์œ ์‚ฌํ•œ ๋ถ€๋ถ„๋“ค์˜ ์ƒํ˜ธ์ž‘์šฉ์ด
01:09
that produces a globally coherent behavior.
21
69463
3320
์ „์ฒด์ ์œผ๋กœ ์ผ๊ด€์ ์ธ ํ–‰๋™์„ ๋งŒ๋“ค์–ด๋ƒ…๋‹ˆ๋‹ค.
01:12
Complex systems have many interacting parts
22
72783
3836
๋ณตํ•ฉ์‹œ์Šคํ…œ์€ ์ƒํ˜ธ์ž‘์šฉํ•˜๋Š” ๋งŽ์€ ๋ถ€๋ถ„๋“ค์ด ์žˆ์–ด
01:16
which behave according to simple, individual rules,
23
76619
3426
๋‹จ์ˆœํ•œ ๊ฐœ๋ณ„์ ์ธ ๋ฒ•์น™์„ ๋”ฐ๋ผ ์›€์ง์ด๋ฉฐ
01:20
and this results in emergent properties.
24
80045
3349
์ด๊ฒƒ์ด ์ƒˆ๋กœ์šด ํŠน์„ฑ์„ ๋งŒ๋“ค์–ด ๋ƒ…๋‹ˆ๋‹ค.
01:23
The behavior of the system as a whole
25
83394
1888
์ „์ฒด ์‹œ์Šคํ…œ์˜ ํ–‰๋™์€
01:25
cannot be predicted
26
85282
1668
๊ฐœ๋ณ„์ ์ธ ๋ฒ•์น™๋งŒ์œผ๋กœ๋Š”
01:26
from the individual rules only.
27
86950
2152
์˜ˆ์ธกํ•  ์ˆ˜ ์—†์Šต๋‹ˆ๋‹ค.
01:29
As Aristotle wrote,
28
89102
1810
์•„๋ฆฌ์Šคํ† ํ…”๋ ˆ์Šค๊ฐ€ ๋งํ–ˆ๋“ฏ์ด,
01:30
the whole is greater than the sum of its parts.
29
90912
3060
์ „์ฒด๋Š” ๋ถ€๋ถ„์˜ ์ดํ•ฉ๋ณด๋‹ค ํฝ๋‹ˆ๋‹ค.
01:33
But from Aristotle, let's move onto
30
93972
2462
์•„๋ฆฌ์Šคํ† ํ…”๋ ˆ์Šค๋Š” ๋‘๊ณ 
01:36
a more concrete example of complex systems.
31
96434
3690
๋ณตํ•ฉ์  ์‹œ์Šคํ…œ์˜ ๊ตฌ์ฒด์ ์ธ ์‚ฌ๋ก€๋ฅผ ๋ณด๊ฒ ์Šต๋‹ˆ๋‹ค.
01:40
These are Scottish terriers.
32
100124
1956
์ด๊ฒƒ์€ ์Šค์นด์น˜ ํ…Œ๋ฆฌ์–ด์ž…๋‹ˆ๋‹ค.
01:42
In the beginning, the system is disorganized.
33
102080
3751
์ฒ˜์Œ์—๋Š” ์‹œ์Šคํ…œ์ด ๋ฌด์งˆ์„œํ•ฉ๋‹ˆ๋‹ค.
01:45
Then comes a perturbation: milk.
34
105831
3801
๊ทธ๋Ÿฌ๋‹ค ์šฐ์œ ๋ผ๋Š” ๋ถˆ์•ˆ์š”์ธ์ด ์ƒ๊น๋‹ˆ๋‹ค.
01:49
Every individual starts pushing in one direction
35
109632
3850
๋ชจ๋‘ ํ•œ ๋ฐฉํ–ฅ์œผ๋กœ ๋ฐ€๊ธฐ ์‹œ์ž‘ํ•ฉ๋‹ˆ๋‹ค.
01:53
and this is what happens.
36
113482
3309
์ด๋Ÿฐ ์ผ์ด ์ƒ๊ธฐ์ฃ .
01:56
The pinwheel is an emergent property
37
116791
2826
๋ฐ”๋žŒ๊ฐœ๋น„์˜ ํ˜•ํƒœ๋Š”
01:59
of the interactions between puppies
38
119617
1903
์šฐ์œ ์ชฝ์œผ๋กœ ๊ฐ€๋ ค๊ณ  ์•„๋ฌด๋ ‡๊ฒŒ๋‚˜ ์›€์ง์ด๋Š”
02:01
whose only rule is to try to keep access to the milk
39
121520
3910
๊ฐ•์•„์ง€๋“ค ์‚ฌ์ด์˜ ์ƒํ˜ธ์ž‘์šฉ์œผ๋กœ
02:05
and therefore to push in a random direction.
40
125430
3607
๋‚˜ํƒ€๋‚˜๋Š” ํŠน์ง•์ž…๋‹ˆ๋‹ค.
02:09
So it's all about finding the simple rules
41
129037
3975
๊ฒฐ๊ตญ ์ค‘์š”ํ•œ ๊ฒƒ์€ ๋ณตํ•ฉ์„ฑ์ด ๋‚˜ํƒ€๋‚˜๋„๋ก ํ•˜๋Š”
02:13
from which complexity emerges.
42
133012
2758
๋‹จ์ˆœํ•œ ๋ฒ•์น™์„ ์ฐพ์•„๋‚ด๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค.
02:15
I call this simplifying complexity,
43
135770
2940
์ €๋Š” ์ด๊ฒƒ์„ ๋‹จ์ˆœํ™”ํ•œ ๋ณตํ•ฉ์„ฑ์ด๋ผ๊ณ  ํ•˜๋Š”๋ฐ
02:18
and it's what we do at the chair of systems design
44
138710
2135
ETH ์ทจ๋ฆฌํžˆ์˜
02:20
at ETH Zurich.
45
140845
1977
์‹œ์Šคํ…œ ๋””์ž์ธ์—์„œ ํ•˜๋Š” ์ผ์ž…๋‹ˆ๋‹ค.
02:22
We collect data on animal populations,
46
142822
3705
๋™๋ฌผ ์ง‘๋‹จ์—์„œ ์ •๋ณด๋ฅผ ์ˆ˜์ง‘ํ•˜๊ณ 
02:26
analyze complex patterns, try to explain them.
47
146527
3811
๋ณตํ•ฉ์ ์ธ ํŒจํ„ด์„ ๋ถ„์„ํ•ด์„œ ์„ค๋ช…ํ•ฉ๋‹ˆ๋‹ค.
02:30
It requires physicists who work with biologists,
48
150338
2619
๋ฌผ๋ฆฌํ•™์ž, ์ƒ๋ฌผํ•™์ž,
02:32
with mathematicians and computer scientists,
49
152957
2723
์ˆ˜ํ•™์ž์™€ ์ปดํ“จํ„ฐ ๊ณตํ•™์ž๋“ค์ด ํ•„์š”ํ•˜๊ณ 
02:35
and it is their interaction that produces
50
155680
2820
๊ทธ๋“ค์ด ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด
02:38
cross-boundary competence
51
158500
1714
๋ถ„์•ผ๋ฅผ ๋„˜๋‚˜๋“œ๋Š” ์ง€์‹์„
02:40
to solve these problems.
52
160214
1578
์ƒํ˜ธ๊ต๋ฅ˜ํ•˜๋ฉฐ ๋งŒ๋“ค์–ด ๋ƒ…๋‹ˆ๋‹ค.
02:41
So again, the whole is greater
53
161792
2272
๊ทธ๋ž˜์„œ ๋‹ค์‹œ ๋งํ•˜๋ฉด,
์ „์ฒด๋Š” ๋ถ€๋ถ„์˜ ์ดํ•ฉ๋ณด๋‹ค ํฝ๋‹ˆ๋‹ค.
02:44
than the sum of the parts.
54
164064
1400
02:45
In a way, collaboration
55
165464
2150
์–ด๋–ป๊ฒŒ ๋ณด๋ฉด, ํ˜‘๋ ฅ์ด๋ž€
02:47
is another example of a complex system.
56
167614
3491
๋ณตํ•ฉ ์‹œ์Šคํ…œ์˜ ๋‹ค๋ฅธ ์˜ˆ์‹œ์ž…๋‹ˆ๋‹ค.
02:51
And you may be asking yourself
57
171105
1876
์—ฌ๋Ÿฌ๋ถ„์€ ํ˜ผ์ž ์ƒ๊ฐํ•˜์‹œ๊ฒ ์ฃ .
02:52
which side I'm on, biology or physics?
58
172981
2817
๋‚˜๋Š” ์ƒ๋ฌผ๊ณผ ๋ฌผ๋ฆฌ ์ค‘ ์–ด๋Š ์ชฝ์ผ๊นŒ?
02:55
In fact, it's a little different,
59
175798
2111
์‚ฌ์‹ค, ์ด๊ฒƒ์€ ์กฐ๊ธˆ ๋‹ค๋ฆ…๋‹ˆ๋‹ค.
02:57
and to explain, I need to tell you
60
177909
1589
์„ค๋ช…๋“œ๋ฆฌ๊ธฐ ์œ„ํ•ด์„œ,
02:59
a short story about myself.
61
179498
2342
์‚ด์ง ์ œ ์ด์•ผ๊ธฐ๋ฅผ ํ•˜๊ฒ ์Šต๋‹ˆ๋‹ค.
03:01
When I was a child,
62
181840
1727
์ œ๊ฐ€ ์–ด๋ ธ์„ ๋•Œ,
03:03
I loved to build stuff, to create complicated machines.
63
183567
4109
๋ญ”๊ฐ€ ๋ณต์žกํ•œ ๊ธฐ๊ณ„ ๋งŒ๋“œ๋Š” ๊ฒƒ์„ ์ข‹์•„ํ–ˆ์Šต๋‹ˆ๋‹ค.
03:07
So I set out to study electrical engineering
64
187676
2737
๊ทธ๋ž˜์„œ ์ „๊ธฐ ๊ณตํ•™๊ณผ
03:10
and robotics,
65
190413
1552
๋กœ๋ด‡๊ณตํ•™์„ ๊ณต๋ถ€ํ•˜๊ธฐ๋กœ ํ–ˆ์ฃ .
03:11
and my end-of-studies project
66
191965
2093
์กธ์—… ๊ณผ์ œ๊ฐ€
03:14
was about building a robot called ER-1 --
67
194058
2926
ER-1์ด๋ผ๋Š” ๋กœ๋ด‡์„ ๋งŒ๋“œ๋Š” ๊ฒƒ์ด์—ˆ๋Š”๋ฐ
03:16
it looked like thisโ€”
68
196984
1930
์ด๋ ‡๊ฒŒ ์ƒ๊ฒผ์Šต๋‹ˆ๋‹ค.
03:18
that would collect information from its environment
69
198914
2371
์ž์‹ ์˜ ํ™˜๊ฒฝ์—์„œ ์ •๋ณด๋ฅผ ์ˆ˜์ง‘ํ•œ ๋‹ค์Œ
03:21
and proceed to follow a white line on the ground.
70
201285
3498
๋ฐ”๋‹ฅ์— ์žˆ๋Š” ํฐ ์„ ์„ ๋”ฐ๋ผ ๊ฐ€๋Š” ๊ฒƒ์ด์—ˆ์Šต๋‹ˆ๋‹ค.
03:24
It was very, very complicated,
71
204783
2379
๋„ˆ๋ฌด ๋„ˆ๋ฌด ๋ณต์žกํ–ˆ์ง€๋งŒ
03:27
but it worked beautifully in our test room,
72
207162
2984
์‹คํ—˜์‹ค์—์„œ๋Š” ํ›Œ๋ฅญํ•˜๊ฒŒ ์ž‘๋™ํ–ˆ์Šต๋‹ˆ๋‹ค.
03:30
and on demo day, professors had assembled to grade the project.
73
210146
3453
์‹œ์—ฐํ•˜๋Š” ๋‚ , ๊ณผ์ œ๋ฅผ ์ฑ„์ ํ•˜๋Ÿฌ ๊ต์ˆ˜๋‹˜๋“ค์ด ์˜ค์…จ์Šต๋‹ˆ๋‹ค.
03:33
So we took ER-1 to the evaluation room.
74
213607
2902
ER-1์„ ํ‰๊ฐ€์‹ค์— ๊ฐ€์ ธ๊ฐ”์ฃ .
03:36
It turned out, the light in that room
75
216509
2310
์•Œ๊ณ  ๋ณด๋‹ˆ, ๊ทธ ๊ณณ์˜ ์กฐ๋ช…์ด
03:38
was slightly different.
76
218819
1819
์‚ด์ง ๋‹ฌ๋ž์Šต๋‹ˆ๋‹ค.
03:40
The robot's vision system got confused.
77
220638
2331
๋กœ๋ด‡์˜ ์‹œ๊ฐ์‹œ์Šคํ…œ์ด ์˜ค๋ฅ˜๋ฅผ ์ผ์œผ์ผฐ์ฃ .
03:42
At the first bend in the line,
78
222969
1761
์ฒซ ๋ฒˆ์งธ ๊ตฌ๋ถ€๋Ÿฌ์ง„ ์„ ์—์„œ
03:44
it left its course, and crashed into a wall.
79
224730
3739
๊ฒฝ๋กœ๋ฅผ ์ดํƒˆํ•˜๊ณ  ๋ฒฝ์— ๋ถ€๋”ชํ˜”์Šต๋‹ˆ๋‹ค.
03:48
We had spent weeks building it,
80
228469
2087
๋ช‡ ์ฃผ๋™์•ˆ ๋งŒ๋“ค์—ˆ๋Š”๋ฐ
03:50
and all it took to destroy it
81
230556
1673
์กฐ๋ช… ์ƒ‰๊น”์ด ์‚ด์ง
03:52
was a subtle change in the color of the light
82
232229
2656
๋‹ค๋ฅผ ๋ฟ์ด์–ด์„œ
03:54
in the room.
83
234885
1596
๊ทธ๊ฒŒ ๋ง๊ฐ€์ง„ ๊ฒ๋‹ˆ๋‹ค.
03:56
That's when I realized that
84
236481
1515
๊ทธ ๋•Œ ์ €๋Š” ์•Œ๊ฒŒ๋์Šต๋‹ˆ๋‹ค.
03:57
the more complicated you make a machine,
85
237996
2327
๊ธฐ๊ณ„๋ฅผ ๋ณต์žกํ•˜๊ฒŒ ๋งŒ๋“ค์ˆ˜๋ก
04:00
the more likely that it will fail
86
240323
2039
์˜ˆ์ƒ์น˜ ๋ชปํ•œ ๊ฒƒ ๋•Œ๋ฌธ์—
04:02
due to something absolutely unexpected.
87
242362
2563
์‹คํŒจํ•  ๊ฐ€๋Šฅ์„ฑ์ด ๋†’๋‹ค๋Š” ๊ฒƒ์„์š”.
04:04
And I decided that, in fact,
88
244925
1830
๊ทธ๋ž˜์„œ ์ €๋Š”,
04:06
I didn't really want to create complicated stuff.
89
246755
3013
๋ณต์žกํ•œ ๊ฒƒ์„ ๋งŒ๋“ค์ง€ ์•Š๊ธฐ๋กœ ํ–ˆ์Šต๋‹ˆ๋‹ค.
04:09
I wanted to understand complexity,
90
249768
2942
์šฐ๋ฆฌ๋ฅผ ๋‘˜๋Ÿฌ์‹ผ ๋ณตํ•ฉ์„ฑ์— ๋Œ€ํ•ด
04:12
the complexity of the world around us
91
252710
1988
์ดํ•ดํ•˜๊ณ  ์‹ถ์—ˆ์Šต๋‹ˆ๋‹ค.
04:14
and especially in the animal kingdom.
92
254698
2405
ํŠนํžˆ ๋™๋ฌผ์˜ ์„ธ๊ณ„๋ฅผ์š”.
04:17
Which brings us to bats.
93
257103
3320
๋ฐ•์ฅ๋ฅผ ์‚ดํŽด๋ณด๊ฒŒ ๋์Šต๋‹ˆ๋‹ค.
04:20
Bechstein's bats are a common species of European bats.
94
260423
3051
๋ฒก์Šคํƒ€์ธ ๋ฐ•์ฅ๋Š” ํ”ํ•œ ์œ ๋Ÿฝ ๋ฐ•์ฅ์ž…๋‹ˆ๋‹ค.
04:23
They are very social animals.
95
263474
1413
๋งค์šฐ ์‚ฌํšŒ์ ์ธ ๋™๋ฌผ์ž…๋‹ˆ๋‹ค.
04:24
Mostly they roost, or sleep, together.
96
264887
3291
๋Œ€๊ฐœ ํ•จ๊ป˜ ๋ฌด๋ฆฌ์ง“๊ฑฐ๋‚˜ ์ž ์„ ์žก๋‹ˆ๋‹ค.
04:28
And they live in maternity colonies,
97
268178
1679
๋˜ํ•œ ๋ชจ์„ฑ ์ง‘๋‹จ์ด ์žˆ๋Š”๋ฐ
04:29
which means that every spring,
98
269857
1540
๋งค๋…„ ๋ด„์ด ๋˜๋ฉด
04:31
the females meet after the winter hibernation,
99
271397
3258
๋™๋ฉด ์ดํ›„์— ์•”์ปท๋“ค์ด ๋ชจ์—ฌ
04:34
and they stay together for about six months
100
274655
2089
6๊ฐœ์›”๋™์•ˆ ํ•จ๊ป˜ ์ง€๋‚ด๋ฉฐ
04:36
to rear their young,
101
276744
2486
์ƒˆ๋ผ๋ฅผ ๊ธฐ๋ฆ…๋‹ˆ๋‹ค.
04:39
and they all carry a very small chip,
102
279230
2805
๋ชจ๋‘ ์ž‘์€ ์นฉ์„ ๋‹ฌ๊ณ  ์žˆ์–ด์„œ
04:42
which means that every time one of them
103
282035
1871
ํŠน์ˆ˜ ์ œ์ž‘๋œ ๋ฐ•์ฅ์ƒ์ž์—
04:43
enters one of these specially equipped bat boxes,
104
283906
3057
๋“ค์–ด์˜ค๋ฉด
04:46
we know where she is,
105
286963
1643
์œ„์น˜๋ฅผ ์•Œ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
04:48
and more importantly,
106
288606
1169
๋”์šฑ ์ค‘์š”ํ•œ ๊ฒƒ์€,
04:49
we know with whom she is.
107
289775
2563
๋ˆ„๊ตฌ์™€ ๊ฐ™์ด ์žˆ๋Š”์ง€ ์••๋‹ˆ๋‹ค.
04:52
So I study roosting associations in bats,
108
292338
3694
์ €๋Š” ๋ฐ•์ฅ์˜ ๋ฌด๋ฆฌ๊ด€๋ จ์„ฑ์„ ์—ฐ๊ตฌํ–ˆ๊ณ 
04:56
and this is what it looks like.
109
296032
2445
์ด๋Ÿฐ ๋ชจ์–‘์„ ๊ฐ–๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
04:58
During the day, the bats roost
110
298477
2442
๋‚ฎ์—๋Š” ์—ฌ๋Ÿฌ ์ƒ์ž์—
05:00
in a number of sub-groups in different boxes.
111
300919
2304
ํ•˜์œ„ ์ง‘๋‹จ์œผ๋กœ ๋ฌด๋ฆฌ์ง“์Šต๋‹ˆ๋‹ค.
05:03
It could be that on one day,
112
303223
1929
์–ด๋Š ๋‚ ์€
05:05
the colony is split between two boxes,
113
305152
2220
๋‘ ๊ฐœ์˜ ์ƒ์ž๋กœ ๋‚˜๋‰  ์ˆ˜๋„ ์žˆ๊ณ 
05:07
but on another day,
114
307372
1300
์–ด๋–ค ๋‚ ์€
05:08
it could be together in a single box,
115
308672
2241
ํ•œ ์ƒ์ž์— ํ•จ๊ป˜ ์žˆ๊ฑฐ๋‚˜
05:10
or split between three or more boxes,
116
310913
2316
์„ธ ๊ฐœ์ด์ƒ์˜ ์ƒ์ž์— ์žˆ์„ ์ˆ˜๋„ ์žˆ์Šต๋‹ˆ๋‹ค.
05:13
and that all seems rather erratic, really.
117
313229
2927
์ •๋ง ๋ณ€๋•์Šค๋Ÿฝ๊ฒŒ ๋ณด์ž…๋‹ˆ๋‹ค.
05:16
It's called fission-fusion dynamics,
118
316156
3203
๋ถ„์—ด-์œตํ•ฉ ์—ญ๋™์„ฑ์ด๋ผ๊ณ  ํ•˜๋Š”๋ฐ,
05:19
the property for an animal group
119
319359
1713
๋™๋ฌผ ์ง‘๋‹จ์ด ์„œ๋กœ ๋‹ค๋ฅธ ํ•˜๋ถ€์ง‘๋‹จ์œผ๋กœ
05:21
of regularly splitting and merging
120
321072
2178
๊ทœ์น™์ ์œผ๋กœ ํฉ์–ด์กŒ๋‹ค ๋ชจ์˜€๋‹คํ•˜๋Š”
05:23
into different subgroups.
121
323250
1661
ํŠน์„ฑ์„ ๊ฐ€๋ฆฌํ‚ต๋‹ˆ๋‹ค.
05:24
So what we do is take all these data
122
324911
2562
์ €ํฌ๋Š” ๊ฐ๊ธฐ ๋‹ค๋ฅธ ๋‚ ์˜
05:27
from all these different days
123
327473
1662
๋ชจ๋“  ์ •๋ณด๋ฅผ ๊ฐ€์ ธ์™€
05:29
and pool them together
124
329135
1504
๋ชจ์•„์„œ
05:30
to extract a long-term association pattern
125
330639
2617
๊ตฐ์ง‘์ ์ธ ์‚ฌํšŒ๊ตฌ์กฐ์˜
05:33
by applying techniques with network analysis
126
333256
2505
์ „์ฒด ๊ทธ๋ฆผ์„ ์–ป์„ ์ˆ˜ ์žˆ๋Š”
05:35
to get a complete picture
127
335761
1621
๊ด€๊ณ„ ๋ถ„์„ ๊ธฐ์ˆ ์„ ์ ์šฉํ•จ์œผ๋กœ์จ
05:37
of the social structure of the colony.
128
337382
2537
์žฅ๊ธฐ์ ์ธ ์—ฐํ•ฉํ˜•ํƒœ๋ฅผ ๋„์ง‘์–ด ๋ƒ…๋‹ˆ๋‹ค.
05:39
Okay? So that's what this picture looks like.
129
339919
4265
์•„์…จ์ฃ ? ๊ทธ๊ฒŒ ์ด๊ฒ๋‹ˆ๋‹ค.
05:44
In this network, all the circles
130
344184
2394
์ด ๊ด€๊ณ„์—์„œ, ๋ชจ๋“  ์›๋“ค์€
05:46
are nodes, individual bats,
131
346578
2777
๊ฐœ๋ณ„์ ์ธ ๋ฐ•์ฅ๋“ค์ธ ๊ต์ ๋“ค์ž…๋‹ˆ๋‹ค.
05:49
and the lines between them
132
349355
1583
๊ทธ ์‚ฌ์ด์˜ ์„ ๋“ค์€
05:50
are social bonds, associations between individuals.
133
350938
3664
๊ฐœ์ฒด ์‚ฌ์ด์˜ ์‚ฌํšŒ์  ์œ ๋Œ€์™€ ๊ด€๊ณ„์„ฑ์ž…๋‹ˆ๋‹ค.
05:54
It turns out this is a very interesting picture.
134
354602
2678
์•„์ฃผ ํฅ๋ฏธ๋กœ์šด ๊ทธ๋ฆผ์ž…๋‹ˆ๋‹ค.
05:57
This bat colony is organized
135
357280
1982
์ด ๋ฐ•์ฅ ๊ตฐ์ง‘์€
05:59
in two different communities
136
359262
1868
๋‘๊ฐœ์˜ ๋‹ค๋ฅธ ๊ณต๋™์ฒด๋กœ ์ด๋ฃจ์–ด์ ธ ์žˆ๋Š”๋ฐ
06:01
which cannot be predicted
137
361130
1839
ํ•˜๋ฃจ ๋‹จ์œ„์˜ ๋ถ„์—ด-์œตํ•ฉ ์—ญ๋™์„ฑ์œผ๋กœ๋Š”
06:02
from the daily fission-fusion dynamics.
138
362969
2249
์˜ˆ์ธกํ•  ์ˆ˜๊ฐ€ ์—†์Šต๋‹ˆ๋‹ค.
06:05
We call them cryptic social units.
139
365218
3550
์ €ํฌ๋Š” ์ด๊ฒƒ์„ ๋ชจํ˜ธํ•œ ์‚ฌํšŒ๋‹จ์œ„๋ผ๊ณ  ํ•ฉ๋‹ˆ๋‹ค.
06:08
Even more interesting, in fact:
140
368768
1616
๋”์šฑ ํฅ๋ฏธ๋กœ์šด ๊ฒƒ์€
06:10
Every year, around October,
141
370384
2364
๋งค๋…„ 10์›”๊ฒฝ์—,
06:12
the colony splits up,
142
372748
1561
๊ตฐ์ง‘์ด ๋ถ„์—ดํ•ฉ๋‹ˆ๋‹ค.
06:14
and all bats hibernate separately,
143
374309
2698
๋ชจ๋“  ๋ฐ•์ฅ๋“ค์ด ๋”ฐ๋กœ ๋™๋ฉดํ•˜๋Š”๋ฐ
06:17
but year after year,
144
377007
1461
์—ฌ๋Ÿฌ ํ•ด๊ฐ€ ์ง€๋‚˜๋„
06:18
when the bats come together again in the spring,
145
378468
3073
๋ด„์— ๋‹ค์‹œ ๋ชจ์˜€์„ ๋•Œ
06:21
the communities stay the same.
146
381541
2590
์ง‘๋‹จ์€ ๋™์งˆ์„ฑ์„ ์œ ์ง€ํ•ฉ๋‹ˆ๋‹ค.
06:24
So these bats remember their friends
147
384131
2720
์ด ๋ฐ•์ฅ๋“ค์€ ๋™๋ฃŒ๋“ค์„
06:26
for a really long time.
148
386851
1830
์ƒ๋‹นํžˆ ์˜ค๋žซ๋™์•ˆ ๊ธฐ์–ตํ•ฉ๋‹ˆ๋‹ค.
06:28
With a brain the size of a peanut,
149
388681
2474
๋•…์ฝฉ๋งŒํ•œ ๋‘๋‡Œ๋กœ
06:31
they maintain individualized,
150
391155
2125
๊ฐœ๋ณ„ํ™”๋œ
06:33
long-term social bonds,
151
393280
2142
์žฅ๊ธฐ์  ์‚ฌํšŒ๊ฒฐ์†์„ ์œ ์ง€ํ•ฉ๋‹ˆ๋‹ค.
06:35
We didn't know that was possible.
152
395422
1724
๊ทธ๊ฒŒ ๊ฐ€๋Šฅํ•œ์ง€ ๋ชฐ๋ž์Šต๋‹ˆ๋‹ค.
06:37
We knew that primates
153
397146
1759
์˜์žฅ๋ฅ˜๋‚˜ ์ฝ”๋ผ๋ฆฌ,
06:38
and elephants and dolphins could do that,
154
398905
2568
๋Œ๊ณ ๋ž˜๋“ค์€ ๊ทธ๋Ÿฐ ์ค„ ์•Œ์•˜์ง€๋งŒ
06:41
but compared to bats, they have huge brains.
155
401473
2628
๊ทธ๋“ค์€ ๋ฐ•์ฅ์— ๋น„ํ•˜๋ฉด ๋‡Œ๊ฐ€ ๊ต‰์žฅํžˆ ํฌ๊ฑฐ๋“ ์š”.
06:44
So how could it be
156
404101
2399
์–ด๋–ป๊ฒŒ ๋ฐ•์ฅ๋Š”
06:46
that the bats maintain this complex,
157
406500
1951
๊ทธ๋ ‡๊ฒŒ ์ œํ•œ์ ์ธ ์ธ์ง€๋Šฅ๋ ฅ์œผ๋กœ
06:48
stable social structure
158
408451
1688
์ด๋ ‡๊ฒŒ ๋ณตํ•ฉ์ ์ด๊ณ  ์•ˆ์ •์ ์ธ
06:50
with such limited cognitive abilities?
159
410139
3532
์‚ฌํšŒ๊ตฌ์กฐ๋ฅผ ์œ ์ง€ํ•  ์ˆ˜ ์žˆ์„๊นŒ์š”?
06:53
And this is where complexity brings an answer.
160
413671
2889
๋ณตํ•ฉ์„ฑ์ด๋ก ์ด ๋‹ต์„ ์ค„ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
06:56
To understand this system,
161
416560
2141
์ด ์‹œ์Šคํ…œ์„ ์ดํ•ดํ•˜๊ธฐ์œ„ํ•ด
06:58
we built a computer model of roosting,
162
418701
2797
๊ฐ„๋‹จํ•˜๊ณ  ๊ฐœ๋ณ„์ ์ธ ๊ทœ์น™์— ๊ธฐ์ดˆํ•œ
07:01
based on simple, individual rules,
163
421498
2018
๋ฌด๋ฆฌ์ง“๊ธฐ ์ปดํ“จํ„ฐ ๋ชจ๋ธ์„ ๋งŒ๋“ค๊ณ 
07:03
and simulated thousands and thousands of days
164
423516
2435
๊ฐ€์ƒ ๋ฐ•์ฅ ๊ตฐ์ง‘์œผ๋กœ
07:05
in the virtual bat colony.
165
425951
2019
์ˆ˜์—†์ด ๋งŽ์€ ๋‚ ์„ ๋ชจ์˜์‹คํ—˜ํ–ˆ์Šต๋‹ˆ๋‹ค.
07:07
It's a mathematical model,
166
427970
2124
์ˆ˜ํ•™์  ๋ชจ๋ธ์ž…๋‹ˆ๋‹ค๋งŒ
07:10
but it's not complicated.
167
430094
1954
๋ณต์žกํ•˜์ง€๋Š” ์•Š์Šต๋‹ˆ๋‹ค.
07:12
What the model told us is that, in a nutshell,
168
432048
3098
๋ชจ๋ธ์„ ํ†ตํ•ด ์•Œ๊ฒŒ ๋œ ๊ฒƒ์„ ์š”์•ฝํ•˜๋ฉด,
07:15
each bat knows a few other colony members
169
435146
3186
๊ฐ๊ฐ์˜ ๋ฐ•์ฅ๋Š” ๋ช‡ ๋งˆ๋ฆฌ์˜ ๋™๋ฃŒ๋ฅผ ์•Œ๊ณ  ์žˆ์–ด์„œ
07:18
as her friends, and is just slightly more likely
170
438332
2488
์ƒ์ž์— ํ•จ๊ป˜ ๋ชจ์ผ ๊ฐ€๋Šฅ์„ฑ์ด
07:20
to roost in a box with them.
171
440820
2510
์•ฝ๊ฐ„ ๋” ์žˆ์Šต๋‹ˆ๋‹ค.
07:23
Simple, individual rules.
172
443330
2444
๋‹จ์ˆœํ•˜๊ณ  ๊ฐœ๋ณ„์ ์ธ ๊ทœ์น™์ž…๋‹ˆ๋‹ค.
07:25
This is all it takes to explain
173
445774
1712
์ด ๋ฐ•์ฅ๋“ค์˜ ์‚ฌํšŒ์  ๋ณตํ•ฉ์„ฑ์„
07:27
the social complexity of these bats.
174
447486
2389
์„ค๋ช…ํ•˜๋Š” ์ „๋ถ€์ž…๋‹ˆ๋‹ค.
07:29
But it gets better.
175
449875
1718
ํ•˜์ง€๋งŒ ๋” ๋‚˜์•„์ง‘๋‹ˆ๋‹ค.
07:31
Between 2010 and 2011,
176
451593
2848
2010๋…„๊ณผ 2011๋…„ ์‚ฌ์ด์—
07:34
the colony lost more than two thirds of its members,
177
454441
3453
ํ˜น๋…ํ•œ ๊ฒจ์šธ ๋‚ ์”จ ๋•Œ๋ฌธ์—
07:37
probably due to the very cold winter.
178
457894
2986
๊ตฐ์ง‘์˜ 3๋ถ„์˜ 2์ด์ƒ์ด ์ฃฝ์Šต๋‹ˆ๋‹ค.
07:40
The next spring, it didn't form two communities
179
460880
3144
๋‹ค์Œํ•ด ๋ด„์—, ๋งค๋…„ ๊ทธ๋žฌ๋˜ ๋Œ€๋กœ
07:44
like every year,
180
464024
1271
๋‘ ๊ฐœ์˜ ์ง‘๋‹จ์„ ์ด๋ฃจ์ง€ ์•Š์Šต๋‹ˆ๋‹ค.
07:45
which may have led the whole colony to die
181
465295
2203
๊ทธ๋Ÿผ ์ง‘๋‹จ์ด ๋„ˆ๋ฌด ์ž‘์•„์ ธ์„œ
07:47
because it had become too small.
182
467498
2095
๋ชจ๋‘ ์ฃฝ๊ฒŒ ๋งŒ๋“ค์ˆ˜๋„ ์žˆ๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค.
07:49
Instead, it formed a single, cohesive social unit,
183
469593
5373
๋Œ€์‹ , ๊ฒฐ์†๋ ฅ ์žˆ๋Š” ๋‹จ์ผํ•œ ์ง‘๋‹จ์„ ๋งŒ๋“ค์–ด
07:54
which allowed the colony to survive that season
184
474966
2732
๊ณ„์ ˆ์„ ์‚ด์•„๋‚จ์•„
07:57
and thrive again in the next two years.
185
477698
3104
๋‹ค์Œ ๋‘ ํ•ด๋™์•ˆ ๋‹ค์‹œ ๋ฒˆ์„ฑํ•˜๊ฒŒ ํ•ฉ๋‹ˆ๋‹ค.
08:00
What we know is that the bats
186
480802
1778
๋ฐ•์ฅ๋“ค์€ ์ž์‹ ๋“ค์ด ์ด๋ ‡๊ฒŒ ํ•˜๋Š”์ง€
08:02
are not aware that their colony is doing this.
187
482580
2907
๋ชจ๋ฅธ๋‹ค๋Š” ๊ฒƒ์„ ์•Œ๊ฒŒ ๋์Šต๋‹ˆ๋‹ค.
08:05
All they do is follow simple association rules,
188
485487
3546
์˜ค์ง ๋‹จ์ˆœํ•œ ๊ฒฐํ•ฉ ๋ฒ•์น™์„ ๋”ฐ๋ฅด๋Š” ๊ฒƒ์ด๊ณ 
08:09
and from this simplicity
189
489033
1349
์ด ๋‹จ์ˆœ์„ฑ์ด
08:10
emerges social complexity
190
490382
2441
์‚ฌํšŒ์  ๋ณตํ•ฉ์„ฑ์„ ๋‚˜ํƒ€๋‚ด๊ฒŒ ํ•˜๋Š”๋ฐ
08:12
which allows the colony to be resilient
191
492823
2840
๊ฐœ์ฒด๊ตฌ์กฐ์— ์ƒ๊ธฐ๋Š” ๊ฐ‘์ž‘์Šค๋Ÿฐ ๋ณ€ํ™”๋กœ๋ถ€ํ„ฐ
08:15
against dramatic changes in the population structure.
192
495663
2981
ํšŒ๋ณตํ•  ์ˆ˜ ์žˆ๊ฒŒ ํ•ด์ฃผ๋Š” ๊ฒ๋‹ˆ๋‹ค.
08:18
And I find this incredible.
193
498644
2694
์ •๋ง ๋†€๋ž๋‹ค๊ณ  ์ƒ๊ฐํ•ฉ๋‹ˆ๋‹ค.
08:21
Now I want to tell you another story,
194
501338
2084
๋‹ค๋ฅธ ์ด์•ผ๊ธฐ๋ฅผ ๋“ค๋ ค๋“œ๋ฆฌ๊ฒ ์Šต๋‹ˆ๋‹ค.
08:23
but for this we have to travel from Europe
195
503422
1555
์œ ๋Ÿฝ์—์„œ ๋‚จ์•„ํ”„๋ฆฌ์นด์— ์žˆ๋Š”
08:24
to the Kalahari Desert in South Africa.
196
504977
3048
์นผ๋ผํ•˜๋ฆฌ ์‚ฌ๋ง‰์œผ๋กœ ๊ฐ€๊ฒ ์Šต๋‹ˆ๋‹ค.
08:28
This is where meerkats live.
197
508025
2027
๋ฏธ์–ด์บฃ์ด ์‚ฌ๋Š” ๊ณณ์ด์ฃ .
08:30
I'm sure you know meerkats.
198
510052
1500
๋ฏธ์–ด์บฃ์„ ์•„์‹ค ๊ฒ๋‹ˆ๋‹ค.
08:31
They're fascinating creatures.
199
511552
2106
์ •๋ง ๋ฉ‹์ง„ ์ƒ๋ฌผ์ด์ฃ .
08:33
They live in groups with a very strict social hierarchy.
200
513658
2989
์—„๊ฒฉํ•œ ์‚ฌํšŒ์  ์œ„๊ณ„๋ฅผ ๊ฐ€์ง€๊ณ  ์ง‘๋‹จ์ƒํ™œ์„ ํ•ฉ๋‹ˆ๋‹ค.
08:36
There is one dominant pair,
201
516647
1459
์ง€๋ฐฐ๊ณ„๊ธ‰ ํ•œ ์Œ์ด ์žˆ๊ณ 
08:38
and many subordinates,
202
518106
1382
๋งŽ์€ ํ•˜์œ„๊ณ„๊ธ‰๋“ค์ด ์žˆ์Šต๋‹ˆ๋‹ค.
08:39
some acting as sentinels,
203
519488
1714
์–ด๋–ค ๋ฏธ์–ด์บฃ์€ ๋ณด์ดˆ๋ณ‘์œผ๋กœ,
08:41
some acting as babysitters,
204
521202
1337
๋ณด๋ชจ๋กœ,
08:42
some teaching pups, and so on.
205
522539
1897
์ƒˆ๋ผ๋“ค์„ ๊ฐ€๋ฅด์น˜๋Š” ๋“ฑ์˜ ์—ญํ• ์„ ํ•ฉ๋‹ˆ๋‹ค.
08:44
What we do is put very small GPS collars
206
524436
3321
์ด ๋™๋ฌผ๋“ค์—๊ฒŒ ์†Œํ˜• GPS ๋ชฉ์ค„์„
08:47
on these animals
207
527757
1525
๋‹ฌ์•„์„œ
08:49
to study how they move together,
208
529282
1875
์ด๋“ค์˜ ์›€์ง์ž„์ด
08:51
and what this has to do with their social structure.
209
531157
3717
์‚ฌํšŒ๊ตฌ์กฐ์™€ ๋ฌด์Šจ ๊ด€๊ณ„๊ฐ€ ์žˆ๋Š”์ง€ ์—ฐ๊ตฌํ–ˆ์Šต๋‹ˆ๋‹ค.
08:54
And there's a very interesting example
210
534874
1490
๋ฏธ์–ด์บฃ์˜ ์ง‘ํ•ฉ์  ํ–‰๋™์—
08:56
of collective movement in meerkats.
211
536364
2716
๋งค์šฐ ํฅ๋ฏธ๋กœ์šด ์˜ˆ๊ฐ€ ์žˆ์Šต๋‹ˆ๋‹ค.
08:59
In the middle of the reserve which they live in
212
539080
2367
๋ฏธ์–ด์บฃ๋“ค์ด ์‚ฌ๋Š” ๋ณดํ˜ธ์ง€์—ญ ํ•œ ๊ฐ€์šด๋ฐ์—
09:01
lies a road.
213
541447
1209
๋„๋กœ๊ฐ€ ์žˆ์Šต๋‹ˆ๋‹ค.
09:02
On this road there are cars, so it's dangerous.
214
542656
3233
๋„๋กœ์—๋Š” ์ฐจ๊ฐ€ ์žˆ์–ด์„œ ์œ„ํ—˜ํ•ฉ๋‹ˆ๋‹ค.
09:05
But the meerkats have to cross it
215
545889
2284
๋ฏธ์–ด์บฃ๋“ค์€ ๋จน์ด๋ฅผ ์œ„ํ•œ ์ด๋™์„ ํ•ด์•ผ ํ•ด์„œ
09:08
to get from one feeding place to another.
216
548173
2574
๊ฑด๋„ˆ๊ฐ€์•ผ ํ•ฉ๋‹ˆ๋‹ค.
09:10
So we asked, how exactly do they do this?
217
550747
4751
์˜๋ฌธ์ด ์ƒ๊ฒผ์Šต๋‹ˆ๋‹ค. ์–ด๋–ป๊ฒŒ ํ•˜๋Š” ๊ฑธ๊นŒ์š”?
09:15
We found that the dominant female
218
555498
1836
์ง€๋ฐฐ๊ณ„๊ธ‰ ์•”์ปท์ด ์ง‘๋‹จ์„ ์ด๋Œ๊ณ 
09:17
is mostly the one who leads the group to the road,
219
557334
2621
๊ธธ์„ ๊ฑด๋„Œ๋‹ค๋Š” ๊ฒƒ์„ ์•Œ๊ฒŒ ๋์Šต๋‹ˆ๋‹ค.
09:19
but when it comes to crossing it, crossing the road,
220
559955
3272
ํ•˜์ง€๋งŒ ๊ฑด๋„ˆ๊ฐ€๋Š” ํ–‰๋™์„ ํ•  ๋•Œ๋Š”
09:23
she gives way to the subordinates,
221
563227
2351
ํ•˜์œ„๊ณ„๊ธ‰๋“ค์—๊ฒŒ ์–‘๋ณดํ•ฉ๋‹ˆ๋‹ค.
09:25
a manner of saying,
222
565578
1777
๋งˆ์น˜ ์ด๋ ‡๊ฒŒ ๋งํ•˜๋Š” ๊ฒƒ ๊ฐ™์Šต๋‹ˆ๋‹ค.
09:27
"Go ahead, tell me if it's safe."
223
567355
2682
"๊ฐ€์„œ ๊ดœ์ฐฎ์€๊ฐ€ ๋ด."
09:30
What I didn't know, in fact,
224
570037
1664
์ œ๊ฐ€ ๋ชฐ๋ž๋˜ ๊ฒƒ์€,
09:31
was what rules in their behavior the meerkats follow
225
571701
3142
๋ฏธ์–ด์บฃ๋“ค์ด ์ง‘๋‹จ์˜ ๊ฒฝ๊ณ„์—์„œ ๋ฒŒ์–ด์ง€๋Š”
09:34
for this change at the edge of the group to happen
226
574843
2925
๋ณ€ํ™”๋ฅผ ์œ„ํ•ด ์–ด๋–ค ๋ฒ•์น™์„ ๋”ฐ๋ฅด๊ณ 
09:37
and if simple rules were sufficient to explain it.
227
577768
3850
๊ทธ๊ฒƒ์„ ์„ค๋ช…ํ•  ๊ฐ„๋‹จํ•œ ๋ฒ•์น™์ด ์žˆ๋Š๋ƒ๋Š” ๊ฒƒ์ด์—ˆ์Šต๋‹ˆ๋‹ค.
09:41
So I built a model, a model of simulated meerkats
228
581618
3991
๊ฐ€์ƒ์˜ ๋„๋กœ๋ฅผ ๊ฑด๋„ˆ๊ฐ€๋Š”
09:45
crossing a simulated road.
229
585609
1913
๋ฏธ์–ด์บฃ ๋ชจ์˜์‹คํ—˜์„ ์œ„ํ•œ ๋ชจ๋ธ์„ ๋งŒ๋“ค์—ˆ์Šต๋‹ˆ๋‹ค.
09:47
It's a simplistic model.
230
587522
1872
๋‹จ์ˆœํ™”๋œ ๋ชจ๋ธ์ž…๋‹ˆ๋‹ค.
09:49
Moving meerkats are like random particles
231
589394
2840
์›€์ง์ด๋Š” ๋ฏธ์–ด์บฃ์€ ์ž„์˜์˜ ์ ๋“ค๋กœ
09:52
whose unique rule is one of alignment.
232
592234
2222
์ •๋ ฌํ•˜๋Š” ๋…ํŠนํ•œ ๊ทœ์น™์„ ๊ฐ–๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
09:54
They simply move together.
233
594456
2406
๊ทธ์ € ํ•จ๊ป˜ ์›€์ง์ด๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค.
09:56
When these particles get to the road,
234
596862
3184
์ ๋“ค์ด ๋„๋กœ์— ์˜ค๋ฉด,
10:00
they sense some kind of obstacle,
235
600046
1942
์žฅ์• ๋ฌผ์„ ๊ฐ์ง€ํ•ฉ๋‹ˆ๋‹ค.
10:01
and they bounce against it.
236
601988
2084
๊ฑฐ๊ธฐ์—์„œ ๋˜ํŠ•๊ฒจ ๋‚˜์˜ต๋‹ˆ๋‹ค.
10:04
The only difference
237
604072
1156
์—ฌ๊ธฐ ๋นจ๊ฐ„ ์ ์˜ ์ง€๋ฐฐ๊ณ„๊ธ‰ ์•”์ปท๊ณผ
10:05
between the dominant female, here in red,
238
605228
2042
๋‹ค๋ฅธ ๊ฐœ์ฒด๋“ค๊ฐ„์˜
10:07
and the other individuals,
239
607270
1485
์œ ์ผํ•œ ์ฐจ์ด์ ์€
10:08
is that for her, the height of the obstacle,
240
608755
2554
์žฅ์• ๋ฌผ์˜ ๋†’์ด๋กœ
10:11
which is in fact the risk perceived from the road,
241
611309
2505
๋„๋กœ์—์„œ๋ถ€ํ„ฐ ๊ฐ์ง€๋˜๋Š” ์œ„ํ—˜์„ฑ์ด
10:13
is just slightly higher,
242
613814
1949
๊ทธ ์•”์ปท์—๊ฒŒ๋Š” ์•ฝ๊ฐ„ ๋” ๋†’๋‹ค๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค.
10:15
and this tiny difference
243
615763
1661
๊ฐœ์ฒด๋“ค์˜ ์ด๋™๋ฒ•์น™์—์„œ์˜
10:17
in the individual's rule of movement
244
617424
1838
์ด ๋ฏธ์„ธํ•œ ์ฐจ์ด๊ฐ€
10:19
is sufficient to explain what we observe,
245
619262
2446
๊ด€์ฐฐํ•œ ๋‚ด์šฉ์„ ์ถฉ๋ถ„ํžˆ ์•Œ๋ ค์ฃผ๋Š”๋ฐ
10:21
that the dominant female
246
621708
2560
์ง€๋ฐฐ๊ณ„๊ธ‰ ์•”์ปท์€
10:24
leads her group to the road
247
624268
1434
๋„๋กœ์— ์ง‘๋‹จ์„ ์ด๋Œ๊ณ  ๊ฐ€์„œ
10:25
and then gives way to the others
248
625702
1670
๋‹ค๋ฅธ ๊ฐœ์ฒด๋“ค์ด ๋จผ์ € ๊ฑด๋„ˆ๋„๋ก
10:27
for them to cross first.
249
627372
2863
์–‘๋ณดํ•˜๋Š” ๊ฒ๋‹ˆ๋‹ค.
10:30
George Box, who was an English statistician,
250
630235
3651
์˜๊ตญ ํ†ต๊ณ„ํ•™์ž์ธ ์ฃ ์ง€ ๋ฐ•์Šค๊ฐ€,
10:33
once wrote, "All models are false,
251
633886
2962
"๋ชจ๋“  ๋ชจ๋ธ์€ ๊ฑฐ์ง“์ด์ง€๋งŒ,
10:36
but some models are useful."
252
636848
2059
์–ด๋–ค ๋ชจ๋ธ์€ ์œ ์šฉํ•˜๋‹ค." ๋ผ๊ณ  ํ–ˆ์Šต๋‹ˆ๋‹ค.
10:38
And in fact, this model is obviously false,
253
638907
3197
์‚ฌ์‹ค ์ด ๋ชจ๋ธ์€ ํ™•์‹คํžˆ ์ž˜๋ชป๋œ ๊ฒƒ์ž…๋‹ˆ๋‹ค.
10:42
because in reality, meerkats are anything but random particles.
254
642104
3968
์‹ค์ œ๋กœ ๋ฏธ์–ด์บฃ์€ ์ž„์˜์˜ ์ ์ด ์•„๋‹ˆ๋‹ˆ๊นŒ์š”.
10:46
But it's also useful,
255
646072
1637
ํ•˜์ง€๋งŒ ์œ ์šฉํ•ฉ๋‹ˆ๋‹ค.
10:47
because it tells us that extreme simplicity
256
647709
2749
๊ฐœ์ฒด ์ˆ˜์ค€์˜ ์ด๋™ ๋ฒ•์น™์— ์žˆ์–ด์„œ
10:50
in movement rules at the individual level
257
650458
3358
์ง€๊ทนํžˆ ๋‹จ์ˆœํ•œ ๊ฒƒ์ด
10:53
can result in a great deal of complexity
258
653816
2351
์ง‘๋‹จ ์ˆ˜์ค€์˜ ์—„์ฒญ๋‚œ ๋ณตํ•ฉ์„ฑ์„
10:56
at the level of the group.
259
656167
1938
์•ผ๊ธฐํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ๊ฒƒ์„ ์•Œ๋ ค์ฃผ๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค.
10:58
So again, that's simplifying complexity.
260
658105
4056
๋‹ค์‹œ ๋ง์”€๋“œ๋ฆฌ๋ฉด, ๋‹จ์ˆœํ™”ํ•œ ๋ณตํ•ฉ์„ฑ์ž…๋‹ˆ๋‹ค.
11:02
I would like to conclude
261
662161
1448
์ด๊ฒƒ์ด ์ „์ฒด ์ข…์—๊ฒŒ ์–ด๋–ค ์˜๋ฏธ์ธ์ง€
11:03
on what this means for the whole species.
262
663609
2817
๊ฒฐ๋ก ์„ ๋ง์”€๋“œ๋ฆฌ๊ฒ ์Šต๋‹ˆ๋‹ค.
11:06
When the dominant female
263
666426
1664
์ง€๋ฐฐ๊ณ„๊ธ‰ ์•”์ปท์ด ํ•˜์œ„๊ณ„๊ธ‰์—๊ฒŒ
11:08
gives way to a subordinate,
264
668090
1566
์–‘๋ณดํ•  ๋•Œ,
11:09
it's not out of courtesy.
265
669656
2117
์˜ˆ์˜๋กœ ๊ทธ๋Ÿฌ๋Š” ๊ฒƒ์ด ์•„๋‹™๋‹ˆ๋‹ค.
11:11
In fact, the dominant female
266
671773
1507
์ง€๋ฐฐ๊ณ„๊ธ‰ ์•”์ปท์€
11:13
is extremely important for the cohesion of the group.
267
673280
2519
์ง‘๋‹จ์˜ ๊ฒฐ์†์— ๋Œ€๋‹จํžˆ ์ค‘์š”ํ•œ ์กด์žฌ์ž…๋‹ˆ๋‹ค.
11:15
If she dies on the road, the whole group is at risk.
268
675799
3512
๊ทธ ์•”์ปท์ด ์ฃฝ์œผ๋ฉด, ์ „์ฒด๊ฐ€ ์œ„ํ—˜์— ๋น ์ง‘๋‹ˆ๋‹ค.
11:19
So this behavior of risk avoidance
269
679311
2236
์ด ์œ„ํ—˜ํšŒํ”ผ ํ–‰๋™์€
11:21
is a very old evolutionary response.
270
681547
2801
์•„์ฃผ ์˜ค๋žœ ์ง„ํ™” ๋ฐ˜์‘์ธ ๊ฒƒ์ž…๋‹ˆ๋‹ค.
11:24
These meerkats are replicating an evolved tactic
271
684348
3869
๋ฏธ์–ด์บฃ๋“ค์€ ์ˆ˜์ฒœ ์„ธ๋Œ€์— ์„ค์นœ
11:28
that is thousands of generations old,
272
688217
2233
์ง„ํ™”๋œ ์ „๋žต์„ ๋˜ํ’€์ด ํ•˜๋Š” ๊ฒ๋‹ˆ๋‹ค.
11:30
and they're adapting it to a modern risk,
273
690450
2414
์ด ๊ฒฝ์šฐ์—๋Š” ์ธ๊ฐ„์ด ์ง€์€ ๋„๋กœ๋ผ๋Š”
11:32
in this case a road built by humans.
274
692864
3325
ํ˜„๋Œ€์  ์œ„ํ—˜์— ์ ์‘ํ•˜๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค.
11:36
They adapt very simple rules,
275
696189
2395
๋งค์šฐ ๋‹จ์ˆœํ•œ ๊ทœ์น™์„ ์ ์šฉํ•˜๊ณ 
11:38
and the resulting complex behavior
276
698584
2289
๊ฒฐ๊ณผ์ ์ธ ๋ณตํ•ฉ ํ–‰๋™์€
11:40
allows them to resist human encroachment
277
700873
2956
๊ทธ๋“ค์˜ ์ž์—ฐ ์„œ์‹์ง€ ์•ˆ์œผ๋กœ ๋“ค์–ด์˜ค๋Š”
11:43
into their natural habitat.
278
703829
2448
์ธ๊ฐ„์˜ ์นจ์ž…์— ๋Œ€ํ•ญํ•˜๊ฒŒ ํ•ด ์ค๋‹ˆ๋‹ค.
11:46
In the end,
279
706277
1802
๊ฒฐ๊ตญ์€
11:48
it may be bats which change their social structure
280
708079
2700
๊ฐœ์ฒด์ˆ˜ ๊ธ‰๊ฐ์— ๋Œ€์ฒ˜ํ•˜์—ฌ
11:50
in response to a population crash,
281
710779
2384
์‚ฌํšŒ๊ตฌ์กฐ๋ฅผ ๋ฐ”๊พธ๋Š” ๋ฐ•์ฅ๋‚˜,
11:53
or it may be meerkats
282
713163
1399
๋„๋กœ์— ์ƒˆ๋กญ๊ฒŒ ์ ์‘ํ•˜๋Š”
11:54
who show a novel adaptation to a human road,
283
714562
3202
๋ฏธ์–ด์บฃ์ด๊ฑฐ๋‚˜,
11:57
or it may be another species.
284
717764
2685
๋˜ ๋‹ค๋ฅธ ์ข…์ผ์ˆ˜๋„ ์žˆ์Šต๋‹ˆ๋‹ค.
12:00
My message here -- and it's not a complicated one,
285
720449
2793
์ œ๊ฐ€ ๋“œ๋ฆฌ๋Š” ๋ง์”€์€, ๋ณต์žกํ•œ ๊ฒƒ์ด ์•„๋‹ˆ๋ผ
12:03
but a simple one of wonder and hope --
286
723242
2764
๊ฒฝ์ด๋กœ์›€๊ณผ ํฌ๋ง์˜ ๋‹จ์ˆœํ•œ ๊ฒƒ์ž…๋‹ˆ๋‹ค.
12:06
my message here is that animals
287
726006
3093
๋™๋ฌผ๋“ค์€
12:09
show extraordinary social complexity,
288
729099
2424
ํƒ์›”ํ•œ ์‚ฌํšŒ์  ๋ณตํ•ฉ์„ฑ์„ ๊ฐ€์ง€๊ณ 
12:11
and this allows them to adapt
289
731523
2441
์ ์‘ํ•˜๋ฉฐ
12:13
and respond to changes in their environment.
290
733964
3481
ํ™˜๊ฒฝ ๋ณ€ํ™”์— ๋Œ€์‘ํ•ฉ๋‹ˆ๋‹ค.
12:17
In three words, in the animal kingdom,
291
737445
2768
์„ธ ๋‹จ์–ด๋กœ, ๋™๋ฌผ์˜ ์„ธ๊ณ„์—์„œ๋Š”
12:20
simplicity leads to complexity
292
740213
2774
๋‹จ์ˆœ์„ฑ์ด ๋ณตํ•ฉ์„ฑ์„ ๋งŒ๋“ค๊ณ 
12:22
which leads to resilience.
293
742987
1483
๊ทธ๊ฒƒ์ด ํšŒ๋ณต๋ ฅ์„ ๋งŒ๋“ญ๋‹ˆ๋‹ค.
12:24
Thank you.
294
744470
2284
๊ฐ์‚ฌํ•ฉ๋‹ˆ๋‹ค.
12:26
(Applause)
295
746754
6680
(๋ฐ•์ˆ˜)
12:42
Dania Gerhardt: Thank you very much, Nicolas,
296
762694
1953
๋ฐ๋‹ˆ์•„: ๋‹ˆ์ฝœ๋ผ์Šค์”จ, ๋ฉ‹์ง„ ์‹œ์ž‘์„ ํ•ด์ฃผ์…”์„œ
12:44
for this great start. Little bit nervous?
297
764647
3279
๋Œ€๋‹จํžˆ ๊ฐ์‚ฌํ•ฉ๋‹ˆ๋‹ค. ์กฐ๊ธˆ ๊ธด์žฅํ•˜์Šต๋‹ˆ๊นŒ?
12:47
Nicolas Perony: I'm okay, thanks.
298
767926
1644
๋‹ˆ์ฝœ๋ผ์Šค: ๊ดœ์ฐฎ์Šต๋‹ˆ๋‹ค. ๊ฐ์‚ฌํ•ฉ๋‹ˆ๋‹ค.
12:49
DG: Okay, great. I'm sure a lot of people in the audience
299
769570
2460
๋ฐ๋‹ˆ์•„: ์ข‹์Šต๋‹ˆ๋‹ค. ๋ถ„๋ช… ์ฒญ์ค‘๋“ค๊ป˜์„œ
12:52
somehow tried to make associations
300
772030
1864
๋‹น์‹ ์ด ๋ง์”€ํ•ด ์ฃผ์‹  ๋ฐ•์ฅ, ๋ฏธ์–ด์บฃ ๊ฐ™์€ ๋™๋ฌผ๋“ค๊ณผ
12:53
between the animals you were talking about --
301
773894
1824
์ธ๊ฐ„์„ ์—ฐ๊ฒฐ์‹œ์ผœ ๋ณด๋ ค๊ณ 
12:55
the bats, meerkats -- and humans.
302
775718
2056
ํ–ˆ์„ ํ…๋ฐ์š”.
12:57
You brought some examples:
303
777774
1208
์˜ˆ์‹œ๋“ค์„ ๋ง์”€ํ•ด์ฃผ์…จ์Šต๋‹ˆ๋‹ค.
12:58
The females are the social ones,
304
778982
1735
์•”์ปท๋“ค์€ ์‚ฌํšŒ์ ์ธ ์กด์žฌ์ด๊ณ ,
13:00
the females are the dominant ones,
305
780717
1713
์ง€๋ฐฐ์ ์ธ ์กด์žฌ๋ผ๊ณ  ํ•˜์…จ์Šต๋‹ˆ๋‹ค.
13:02
I'm not sure who thinks how.
306
782430
1673
์–ด๋–ป๊ฒŒ ์ƒ๊ฐํ•˜์‹ค์ง€ ๋ชจ๋ฅด๊ฒ ์ง€๋งŒ,
13:04
But is it okay to do these associations?
307
784103
2895
์ด๋ ‡๊ฒŒ ์—ฐ๊ด€์‹œ์ผœ๋„ ๋ ๊นŒ์š”?
13:06
Are there stereotypes you can confirm in this regard
308
786998
2800
๋ชจ๋“  ์ข…๋“ค์„ ํ†ตํ‹€์–ด ํ•ด๋‹น๋˜๋Š”
13:09
that can be valid across all species?
309
789798
3273
ํ™•์‹ ํ•  ์ˆ˜ ์žˆ๋Š” ์ „ํ˜•์ ์ธ ํ˜•ํƒœ๊ฐ€ ์žˆ์Šต๋‹ˆ๊นŒ?
13:13
NP: Well, I would say there are also
310
793071
1603
๋‹ˆ์ฝœ๋ผ์Šค: ์ด๋ ‡๊ฒŒ ๋ง์”€๋“œ๋ฆฌ๊ฒ ์Šต๋‹ˆ๋‹ค.
13:14
counter-examples to these stereotypes.
311
794674
1952
์ด๋Ÿฐ ์ „ํ˜•์ ์ธ ํ˜•ํƒœ์— ๋ฐ˜๋Œ€๋˜๋Š” ์‚ฌ๋ก€๋„ ์žˆ์Šต๋‹ˆ๋‹ค.
13:16
For examples, in sea horses or in koalas, in fact,
312
796626
3140
์˜ˆ๋ฅผ ๋“ค์–ด, ํ•ด๋งˆ, ์ฝ”์•Œ๋ผ๋“ค์€ ์‚ฌ์‹ค
13:19
it is the males who take care of the young always.
313
799766
3698
ํ•ญ์ƒ ์ˆ˜์ปท์ด ์ƒˆ๋ผ๋ฅผ ๋Œ๋ด…๋‹ˆ๋‹ค.
13:23
And the lesson is that it's often difficult,
314
803464
5041
๋ฐฐ์šด ์ ์€ ์ธ๊ฐ„๊ณผ ๋™๋ฌผ์ด ํ‰ํ–‰์„ ์œ ์ง€ํ•˜๋Š”๊ฒŒ
13:28
and sometimes even a bit dangerous,
315
808505
1752
์ž์ฃผ ์–ด๋ ต๊ณ 
13:30
to draw parallels between humans and animals.
316
810257
2672
๋•Œ๋กœ๋Š” ์กฐ๊ธˆ ์œ„ํ—˜ํ•˜๊ธฐ๊นŒ์ง€ ํ•˜๋‹ค๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค.
13:32
So that's it.
317
812929
2106
๊ทธ๊ฒ๋‹ˆ๋‹ค.
13:35
DG: Okay. Thank you very much for this great start.
318
815035
2846
๋„ค, ํ›Œ๋ฅญํ•œ ์‹œ์ž‘์— ๊ฐ์‚ฌํ•ฉ๋‹ˆ๋‹ค.
13:37
Thank you, Nicolas Perony.
319
817881
2080
๊ฐ์‚ฌํ•ฉ๋‹ˆ๋‹ค. ๋‹ˆ์ฝœ๋ผ์Šค ํŽ˜๋กœ๋‹ˆ์”จ.
์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.

https://forms.gle/WvT1wiN1qDtmnspy7