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

129,310 views ・ 2014-01-30

TED


Please double-click on the English subtitles below to play the video.

00:15
Science,
0
15393
1228
00:16
science has allowed us to know so much
1
16621
3337
00:19
about the far reaches of the universe,
2
19958
3026
00:22
which is at the same time tremendously important
3
22984
3195
00:26
and extremely remote,
4
26179
2066
00:28
and yet much, much closer,
5
28245
2459
00:30
much more directly related to us,
6
30704
2091
00:32
there are many things we don't really understand.
7
32795
2468
00:35
And one of them is the extraordinary
8
35263
2129
00:37
social complexity of the animals around us,
9
37392
3326
00:40
and today I want to tell you a few stories
10
40718
2016
00:42
of animal complexity.
11
42734
2008
00:44
But first, what do we call complexity?
12
44742
3350
00:48
What is complex?
13
48092
1487
00:49
Well, complex is not complicated.
14
49579
3427
00:53
Something complicated comprises many small parts,
15
53006
3448
00:56
all different, and each of them
16
56454
2430
00:58
has its own precise role in the machinery.
17
58899
3104
01:02
On the opposite, a complex system
18
62003
2811
01:04
is made of many, many similar parts,
19
64814
2641
01:07
and it is their interaction
20
67455
2008
01:09
that produces a globally coherent behavior.
21
69463
3320
01:12
Complex systems have many interacting parts
22
72783
3836
01:16
which behave according to simple, individual rules,
23
76619
3426
01:20
and this results in emergent properties.
24
80045
3349
01:23
The behavior of the system as a whole
25
83394
1888
01:25
cannot be predicted
26
85282
1668
01:26
from the individual rules only.
27
86950
2152
01:29
As Aristotle wrote,
28
89102
1810
01:30
the whole is greater than the sum of its parts.
29
90912
3060
01:33
But from Aristotle, let's move onto
30
93972
2462
01:36
a more concrete example of complex systems.
31
96434
3690
01:40
These are Scottish terriers.
32
100124
1956
01:42
In the beginning, the system is disorganized.
33
102080
3751
01:45
Then comes a perturbation: milk.
34
105831
3801
01:49
Every individual starts pushing in one direction
35
109632
3850
01:53
and this is what happens.
36
113482
3309
01:56
The pinwheel is an emergent property
37
116791
2826
01:59
of the interactions between puppies
38
119617
1903
02:01
whose only rule is to try to keep access to the milk
39
121520
3910
02:05
and therefore to push in a random direction.
40
125430
3607
02:09
So it's all about finding the simple rules
41
129037
3975
02:13
from which complexity emerges.
42
133012
2758
02:15
I call this simplifying complexity,
43
135770
2940
02:18
and it's what we do at the chair of systems design
44
138710
2135
02:20
at ETH Zurich.
45
140845
1977
02:22
We collect data on animal populations,
46
142822
3705
02:26
analyze complex patterns, try to explain them.
47
146527
3811
02:30
It requires physicists who work with biologists,
48
150338
2619
02:32
with mathematicians and computer scientists,
49
152957
2723
02:35
and it is their interaction that produces
50
155680
2820
02:38
cross-boundary competence
51
158500
1714
02:40
to solve these problems.
52
160214
1578
02:41
So again, the whole is greater
53
161792
2272
02:44
than the sum of the parts.
54
164064
1400
02:45
In a way, collaboration
55
165464
2150
02:47
is another example of a complex system.
56
167614
3491
02:51
And you may be asking yourself
57
171105
1876
02:52
which side I'm on, biology or physics?
58
172981
2817
02:55
In fact, it's a little different,
59
175798
2111
02:57
and to explain, I need to tell you
60
177909
1589
02:59
a short story about myself.
61
179498
2342
03:01
When I was a child,
62
181840
1727
03:03
I loved to build stuff, to create complicated machines.
63
183567
4109
03:07
So I set out to study electrical engineering
64
187676
2737
03:10
and robotics,
65
190413
1552
03:11
and my end-of-studies project
66
191965
2093
03:14
was about building a robot called ER-1 --
67
194058
2926
03:16
it looked like this—
68
196984
1930
03:18
that would collect information from its environment
69
198914
2371
03:21
and proceed to follow a white line on the ground.
70
201285
3498
03:24
It was very, very complicated,
71
204783
2379
03:27
but it worked beautifully in our test room,
72
207162
2984
03:30
and on demo day, professors had assembled to grade the project.
73
210146
3453
03:33
So we took ER-1 to the evaluation room.
74
213607
2902
03:36
It turned out, the light in that room
75
216509
2310
03:38
was slightly different.
76
218819
1819
03:40
The robot's vision system got confused.
77
220638
2331
03:42
At the first bend in the line,
78
222969
1761
03:44
it left its course, and crashed into a wall.
79
224730
3739
03:48
We had spent weeks building it,
80
228469
2087
03:50
and all it took to destroy it
81
230556
1673
03:52
was a subtle change in the color of the light
82
232229
2656
03:54
in the room.
83
234885
1596
03:56
That's when I realized that
84
236481
1515
03:57
the more complicated you make a machine,
85
237996
2327
04:00
the more likely that it will fail
86
240323
2039
04:02
due to something absolutely unexpected.
87
242362
2563
04:04
And I decided that, in fact,
88
244925
1830
04:06
I didn't really want to create complicated stuff.
89
246755
3013
04:09
I wanted to understand complexity,
90
249768
2942
04:12
the complexity of the world around us
91
252710
1988
04:14
and especially in the animal kingdom.
92
254698
2405
04:17
Which brings us to bats.
93
257103
3320
04:20
Bechstein's bats are a common species of European bats.
94
260423
3051
04:23
They are very social animals.
95
263474
1413
04:24
Mostly they roost, or sleep, together.
96
264887
3291
04:28
And they live in maternity colonies,
97
268178
1679
04:29
which means that every spring,
98
269857
1540
04:31
the females meet after the winter hibernation,
99
271397
3258
04:34
and they stay together for about six months
100
274655
2089
04:36
to rear their young,
101
276744
2486
04:39
and they all carry a very small chip,
102
279230
2805
04:42
which means that every time one of them
103
282035
1871
04:43
enters one of these specially equipped bat boxes,
104
283906
3057
04:46
we know where she is,
105
286963
1643
04:48
and more importantly,
106
288606
1169
04:49
we know with whom she is.
107
289775
2563
04:52
So I study roosting associations in bats,
108
292338
3694
04:56
and this is what it looks like.
109
296032
2445
04:58
During the day, the bats roost
110
298477
2442
05:00
in a number of sub-groups in different boxes.
111
300919
2304
05:03
It could be that on one day,
112
303223
1929
05:05
the colony is split between two boxes,
113
305152
2220
05:07
but on another day,
114
307372
1300
05:08
it could be together in a single box,
115
308672
2241
05:10
or split between three or more boxes,
116
310913
2316
05:13
and that all seems rather erratic, really.
117
313229
2927
05:16
It's called fission-fusion dynamics,
118
316156
3203
05:19
the property for an animal group
119
319359
1713
05:21
of regularly splitting and merging
120
321072
2178
05:23
into different subgroups.
121
323250
1661
05:24
So what we do is take all these data
122
324911
2562
05:27
from all these different days
123
327473
1662
05:29
and pool them together
124
329135
1504
05:30
to extract a long-term association pattern
125
330639
2617
05:33
by applying techniques with network analysis
126
333256
2505
05:35
to get a complete picture
127
335761
1621
05:37
of the social structure of the colony.
128
337382
2537
05:39
Okay? So that's what this picture looks like.
129
339919
4265
05:44
In this network, all the circles
130
344184
2394
05:46
are nodes, individual bats,
131
346578
2777
05:49
and the lines between them
132
349355
1583
05:50
are social bonds, associations between individuals.
133
350938
3664
05:54
It turns out this is a very interesting picture.
134
354602
2678
05:57
This bat colony is organized
135
357280
1982
05:59
in two different communities
136
359262
1868
06:01
which cannot be predicted
137
361130
1839
06:02
from the daily fission-fusion dynamics.
138
362969
2249
06:05
We call them cryptic social units.
139
365218
3550
06:08
Even more interesting, in fact:
140
368768
1616
06:10
Every year, around October,
141
370384
2364
06:12
the colony splits up,
142
372748
1561
06:14
and all bats hibernate separately,
143
374309
2698
06:17
but year after year,
144
377007
1461
06:18
when the bats come together again in the spring,
145
378468
3073
06:21
the communities stay the same.
146
381541
2590
06:24
So these bats remember their friends
147
384131
2720
06:26
for a really long time.
148
386851
1830
06:28
With a brain the size of a peanut,
149
388681
2474
06:31
they maintain individualized,
150
391155
2125
06:33
long-term social bonds,
151
393280
2142
06:35
We didn't know that was possible.
152
395422
1724
06:37
We knew that primates
153
397146
1759
06:38
and elephants and dolphins could do that,
154
398905
2568
06:41
but compared to bats, they have huge brains.
155
401473
2628
06:44
So how could it be
156
404101
2399
06:46
that the bats maintain this complex,
157
406500
1951
06:48
stable social structure
158
408451
1688
06:50
with such limited cognitive abilities?
159
410139
3532
06:53
And this is where complexity brings an answer.
160
413671
2889
06:56
To understand this system,
161
416560
2141
06:58
we built a computer model of roosting,
162
418701
2797
07:01
based on simple, individual rules,
163
421498
2018
07:03
and simulated thousands and thousands of days
164
423516
2435
07:05
in the virtual bat colony.
165
425951
2019
07:07
It's a mathematical model,
166
427970
2124
07:10
but it's not complicated.
167
430094
1954
07:12
What the model told us is that, in a nutshell,
168
432048
3098
07:15
each bat knows a few other colony members
169
435146
3186
07:18
as her friends, and is just slightly more likely
170
438332
2488
07:20
to roost in a box with them.
171
440820
2510
07:23
Simple, individual rules.
172
443330
2444
07:25
This is all it takes to explain
173
445774
1712
07:27
the social complexity of these bats.
174
447486
2389
07:29
But it gets better.
175
449875
1718
07:31
Between 2010 and 2011,
176
451593
2848
07:34
the colony lost more than two thirds of its members,
177
454441
3453
07:37
probably due to the very cold winter.
178
457894
2986
07:40
The next spring, it didn't form two communities
179
460880
3144
07:44
like every year,
180
464024
1271
07:45
which may have led the whole colony to die
181
465295
2203
07:47
because it had become too small.
182
467498
2095
07:49
Instead, it formed a single, cohesive social unit,
183
469593
5373
07:54
which allowed the colony to survive that season
184
474966
2732
07:57
and thrive again in the next two years.
185
477698
3104
08:00
What we know is that the bats
186
480802
1778
08:02
are not aware that their colony is doing this.
187
482580
2907
08:05
All they do is follow simple association rules,
188
485487
3546
08:09
and from this simplicity
189
489033
1349
08:10
emerges social complexity
190
490382
2441
08:12
which allows the colony to be resilient
191
492823
2840
08:15
against dramatic changes in the population structure.
192
495663
2981
08:18
And I find this incredible.
193
498644
2694
08:21
Now I want to tell you another story,
194
501338
2084
08:23
but for this we have to travel from Europe
195
503422
1555
08:24
to the Kalahari Desert in South Africa.
196
504977
3048
08:28
This is where meerkats live.
197
508025
2027
08:30
I'm sure you know meerkats.
198
510052
1500
08:31
They're fascinating creatures.
199
511552
2106
08:33
They live in groups with a very strict social hierarchy.
200
513658
2989
08:36
There is one dominant pair,
201
516647
1459
08:38
and many subordinates,
202
518106
1382
08:39
some acting as sentinels,
203
519488
1714
08:41
some acting as babysitters,
204
521202
1337
08:42
some teaching pups, and so on.
205
522539
1897
08:44
What we do is put very small GPS collars
206
524436
3321
08:47
on these animals
207
527757
1525
08:49
to study how they move together,
208
529282
1875
08:51
and what this has to do with their social structure.
209
531157
3717
08:54
And there's a very interesting example
210
534874
1490
08:56
of collective movement in meerkats.
211
536364
2716
08:59
In the middle of the reserve which they live in
212
539080
2367
09:01
lies a road.
213
541447
1209
09:02
On this road there are cars, so it's dangerous.
214
542656
3233
09:05
But the meerkats have to cross it
215
545889
2284
09:08
to get from one feeding place to another.
216
548173
2574
09:10
So we asked, how exactly do they do this?
217
550747
4751
09:15
We found that the dominant female
218
555498
1836
09:17
is mostly the one who leads the group to the road,
219
557334
2621
09:19
but when it comes to crossing it, crossing the road,
220
559955
3272
09:23
she gives way to the subordinates,
221
563227
2351
09:25
a manner of saying,
222
565578
1777
09:27
"Go ahead, tell me if it's safe."
223
567355
2682
09:30
What I didn't know, in fact,
224
570037
1664
09:31
was what rules in their behavior the meerkats follow
225
571701
3142
09:34
for this change at the edge of the group to happen
226
574843
2925
09:37
and if simple rules were sufficient to explain it.
227
577768
3850
09:41
So I built a model, a model of simulated meerkats
228
581618
3991
09:45
crossing a simulated road.
229
585609
1913
09:47
It's a simplistic model.
230
587522
1872
09:49
Moving meerkats are like random particles
231
589394
2840
09:52
whose unique rule is one of alignment.
232
592234
2222
09:54
They simply move together.
233
594456
2406
09:56
When these particles get to the road,
234
596862
3184
10:00
they sense some kind of obstacle,
235
600046
1942
10:01
and they bounce against it.
236
601988
2084
10:04
The only difference
237
604072
1156
10:05
between the dominant female, here in red,
238
605228
2042
10:07
and the other individuals,
239
607270
1485
10:08
is that for her, the height of the obstacle,
240
608755
2554
10:11
which is in fact the risk perceived from the road,
241
611309
2505
10:13
is just slightly higher,
242
613814
1949
10:15
and this tiny difference
243
615763
1661
10:17
in the individual's rule of movement
244
617424
1838
10:19
is sufficient to explain what we observe,
245
619262
2446
10:21
that the dominant female
246
621708
2560
10:24
leads her group to the road
247
624268
1434
10:25
and then gives way to the others
248
625702
1670
10:27
for them to cross first.
249
627372
2863
10:30
George Box, who was an English statistician,
250
630235
3651
10:33
once wrote, "All models are false,
251
633886
2962
10:36
but some models are useful."
252
636848
2059
10:38
And in fact, this model is obviously false,
253
638907
3197
10:42
because in reality, meerkats are anything but random particles.
254
642104
3968
10:46
But it's also useful,
255
646072
1637
10:47
because it tells us that extreme simplicity
256
647709
2749
10:50
in movement rules at the individual level
257
650458
3358
10:53
can result in a great deal of complexity
258
653816
2351
10:56
at the level of the group.
259
656167
1938
10:58
So again, that's simplifying complexity.
260
658105
4056
11:02
I would like to conclude
261
662161
1448
11:03
on what this means for the whole species.
262
663609
2817
11:06
When the dominant female
263
666426
1664
11:08
gives way to a subordinate,
264
668090
1566
11:09
it's not out of courtesy.
265
669656
2117
11:11
In fact, the dominant female
266
671773
1507
11:13
is extremely important for the cohesion of the group.
267
673280
2519
11:15
If she dies on the road, the whole group is at risk.
268
675799
3512
11:19
So this behavior of risk avoidance
269
679311
2236
11:21
is a very old evolutionary response.
270
681547
2801
11:24
These meerkats are replicating an evolved tactic
271
684348
3869
11:28
that is thousands of generations old,
272
688217
2233
11:30
and they're adapting it to a modern risk,
273
690450
2414
11:32
in this case a road built by humans.
274
692864
3325
11:36
They adapt very simple rules,
275
696189
2395
11:38
and the resulting complex behavior
276
698584
2289
11:40
allows them to resist human encroachment
277
700873
2956
11:43
into their natural habitat.
278
703829
2448
11:46
In the end,
279
706277
1802
11:48
it may be bats which change their social structure
280
708079
2700
11:50
in response to a population crash,
281
710779
2384
11:53
or it may be meerkats
282
713163
1399
11:54
who show a novel adaptation to a human road,
283
714562
3202
11:57
or it may be another species.
284
717764
2685
12:00
My message here -- and it's not a complicated one,
285
720449
2793
12:03
but a simple one of wonder and hope --
286
723242
2764
12:06
my message here is that animals
287
726006
3093
12:09
show extraordinary social complexity,
288
729099
2424
12:11
and this allows them to adapt
289
731523
2441
12:13
and respond to changes in their environment.
290
733964
3481
12:17
In three words, in the animal kingdom,
291
737445
2768
12:20
simplicity leads to complexity
292
740213
2774
12:22
which leads to resilience.
293
742987
1483
12:24
Thank you.
294
744470
2284
12:26
(Applause)
295
746754
6680
12:42
Dania Gerhardt: Thank you very much, Nicolas,
296
762694
1953
12:44
for this great start. Little bit nervous?
297
764647
3279
12:47
Nicolas Perony: I'm okay, thanks.
298
767926
1644
12:49
DG: Okay, great. I'm sure a lot of people in the audience
299
769570
2460
12:52
somehow tried to make associations
300
772030
1864
12:53
between the animals you were talking about --
301
773894
1824
12:55
the bats, meerkats -- and humans.
302
775718
2056
12:57
You brought some examples:
303
777774
1208
12:58
The females are the social ones,
304
778982
1735
13:00
the females are the dominant ones,
305
780717
1713
13:02
I'm not sure who thinks how.
306
782430
1673
13:04
But is it okay to do these associations?
307
784103
2895
13:06
Are there stereotypes you can confirm in this regard
308
786998
2800
13:09
that can be valid across all species?
309
789798
3273
13:13
NP: Well, I would say there are also
310
793071
1603
13:14
counter-examples to these stereotypes.
311
794674
1952
13:16
For examples, in sea horses or in koalas, in fact,
312
796626
3140
13:19
it is the males who take care of the young always.
313
799766
3698
13:23
And the lesson is that it's often difficult,
314
803464
5041
13:28
and sometimes even a bit dangerous,
315
808505
1752
13:30
to draw parallels between humans and animals.
316
810257
2672
13:32
So that's it.
317
812929
2106
13:35
DG: Okay. Thank you very much for this great start.
318
815035
2846
13:37
Thank you, Nicolas Perony.
319
817881
2080
About this website

This site will introduce you to YouTube videos that are useful for learning English. You will see English lessons taught by top-notch teachers from around the world. Double-click on the English subtitles displayed on each video page to play the video from there. The subtitles scroll in sync with the video playback. If you have any comments or requests, please contact us using this contact form.

https://forms.gle/WvT1wiN1qDtmnspy7