Why we think it's OK to cheat and steal (sometimes) | Dan Ariely

777,228 views ใƒป 2009-03-18

TED


ืื ื ืœื—ืฅ ืคืขืžื™ื™ื ืขืœ ื”ื›ืชื•ื‘ื™ื•ืช ื‘ืื ื’ืœื™ืช ืœืžื˜ื” ื›ื“ื™ ืœื”ืคืขื™ืœ ืืช ื”ืกืจื˜ื•ืŸ.

ืžืชืจื’ื: Ran Amitay ืžื‘ืงืจ: Sigal Tifferet
00:19
I want to talk to you today a little bit
0
19330
2000
ืื ื™ ืจื•ืฆื” ืœื“ื‘ืจ ื”ื™ื•ื ืžืขื˜
00:21
about predictable irrationality.
1
21330
3000
ืขืœ ืื™ ืจืฆื™ื•ื ืืœื™ื•ืช ืฆืคื•ื™ื” ืžืจืืฉ.
00:24
And my interest in irrational behavior
2
24330
4000
ื•ื”ืขื ื™ื™ืŸ ืฉืœื™ ื‘ื”ืชื ื”ื’ื•ืช ืื™-ืจืฆื™ื•ื ืืœื™ืช
00:28
started many years ago in the hospital.
3
28330
3000
ื”ืชื—ื™ืœ ืœืคื ื™ ืฉื ื™ื ืจื‘ื•ืช ื‘ื‘ื™ืช ื”ื—ื•ืœื™ื.
00:31
I was burned very badly.
4
31330
4000
ื ื›ื•ื•ื™ืชื™ ืงืฉื” ืžืื•ื“.
00:35
And if you spend a lot of time in hospital,
5
35330
3000
ื•ืื ืชื‘ืœื• ื”ืจื‘ื” ื–ืžืŸ ื‘ื‘ื™ืช ื—ื•ืœื™ื,
00:38
you'll see a lot of types of irrationalities.
6
38330
3000
ืชืจืื• ื”ืจื‘ื” ืกื•ื’ื™ื ืฉืœ ื—ื•ืกืจ ื”ื’ื™ื•ืŸ.
00:41
And the one that particularly bothered me in the burn department
7
41330
5000
ื•ื”ืกื•ื’ ืฉื”ืคืจื™ืข ืœื™ ื‘ื™ื•ืชืจ ื‘ืžื—ืœืงืช ื”ื›ื•ื•ื™ื•ืช
00:46
was the process by which the nurses took the bandage off me.
8
46330
4000
ื”ื™ื” ื”ืชื”ืœื™ืš ืฉื‘ื• ื”ืื—ื™ื•ืช ื”ืกื™ืจื• ืžืขืœื™ื™ ืืช ื”ืชื—ื‘ื•ืฉื•ืช.
00:51
Now, you must have all taken a Band-Aid off at some point,
9
51330
2000
ื•ื•ื“ืื™ ื™ืฆื ืœื›ื ืœื”ื•ืจื™ื“ ืคืœืกื˜ืจ,
00:53
and you must have wondered what's the right approach.
10
53330
3000
ื•ืชื”ื™ืชื, ื‘ื•ื•ื“ืื™, ืžื”ื™ ื”ื’ื™ืฉื” ื”ื ื›ื•ื ื”.
00:56
Do you rip it off quickly -- short duration but high intensity --
11
56330
4000
ื”ืื ืœืชืœื•ืฉ ืื•ืชื• ื‘ืžื”ื™ืจื•ืช -- ืžืฉืš ื–ืžืŸ ืงืฆืจ, ืืš ืขื•ืฆืžืช ื›ืื‘ ื’ื‘ื•ื”ื” --
01:00
or do you take your Band-Aid off slowly --
12
60330
2000
ืื• ืœื”ื•ืจื™ื“ ืืช ื”ืคืœืกื˜ืจ ืœืื˜ --
01:02
you take a long time, but each second is not as painful --
13
62330
4000
ืœื•ืงื— ื™ื•ืชืจ ื–ืžืŸ, ืืš ื›ืœ ืฉื ื™ื™ื” ื›ื•ืื‘ืช ืคื—ื•ืช --
01:06
which one of those is the right approach?
14
66330
3000
ืžื”ื™ ื”ื’ื™ืฉื” ื”ื ื›ื•ื ื”?
01:09
The nurses in my department thought that the right approach
15
69330
4000
ืื—ื™ื•ืช ื”ืžื—ืœืงื” ื—ืฉื‘ื• ืฉื”ื’ื™ืฉื” ื”ื ื›ื•ื ื”
01:13
was the ripping one, so they would grab hold and they would rip,
16
73330
3000
ื”ื™ื ื’ื™ืฉืช ื”ืชืœื™ืฉื”, ืื– ื”ืŸ ื”ื™ื• ืื•ื—ื–ื•ืช ื•ืชื•ืœืฉื•ืช.
01:16
and they would grab hold and they would rip.
17
76330
2000
ื•ืื•ื—ื–ื•ืช ื•ืชื•ืœืฉื•ืช.
01:18
And because I had 70 percent of my body burned, it would take about an hour.
18
78330
4000
ื•ื‘ื’ืœืœ ืฉ70 ืื—ื•ื–ื™ื ืžื’ื•ืคื™ ื”ื™ื• ืฉืจื•ืคื™ื, ื–ื” ืœืงื— ื›ืฉืขื”.
01:22
And as you can imagine,
19
82330
3000
ื›ืžื• ืฉื ื™ืชืŸ ืœื“ืžื™ื™ืŸ,
01:25
I hated that moment of ripping with incredible intensity.
20
85330
4000
ืฉื ืืชื™ ืืช ืจื’ืข ื”ืชืœื™ืฉื” ื‘ืขืœ ืขื•ืฆืžืช ื”ื›ืื‘ ื”ื’ื‘ื•ื”ื”.
01:29
And I would try to reason with them and say,
21
89330
2000
ื ื™ืกื™ืชื™ ืœื“ื‘ืจ ืื™ืชืŸ ื‘ื”ื’ื™ื•ืŸ ื•ืืžืจืชื™,
01:31
"Why don't we try something else?
22
91330
1000
"ืœืžื” ืฉืœื ื ื ืกื” ืžืฉื”ื• ืื—ืจ?
01:32
Why don't we take it a little longer --
23
92330
2000
ืœืžื” ืฉืœื ื ืขืฉื” ืืช ื–ื” ืžืขื˜ ืžืžื•ืฉืš ื™ื•ืชืจ --
01:34
maybe two hours instead of an hour -- and have less of this intensity?"
24
94330
5000
ืื•ืœื™ ืฉืขืชื™ื™ื ื‘ืžืงื•ื ืฉืขื” -- ื•ื ืกื‘ื•ืœ ืคื—ื•ืช ืžืขื•ืฆืžืช ื”ื›ืื‘ ื”ื–ืืช?
01:39
And the nurses told me two things.
25
99330
2000
ื•ื”ืื—ื™ื•ืช ืืžืจื• ืœื™ ืฉื ื™ ื“ื‘ืจื™ื:
01:41
They told me that they had the right model of the patient --
26
101330
4000
ื”ืŸ ืืžืจื• ืฉื™ืฉ ืœื”ืŸ ืืช ื”ืžื•ื“ืœ ื”ื ื›ื•ืŸ ืฉืœ ื”ื—ื•ืœื” --
01:45
that they knew what was the right thing to do to minimize my pain --
27
105330
3000
ืฉื”ืŸ ื™ื•ื“ืขื•ืช ืžื” ืฆืจื™ืš ืœืขืฉื•ืช ืขืœ-ืžื ืช ืœื”ืงื˜ื™ืŸ ืืช ื”ื›ืื‘ ืฉืœื™ --
01:48
and they also told me that the word patient doesn't mean
28
108330
3000
ื•ื”ืŸ ื’ื ืืžืจื• ืœื™ ืฉื”ืžื™ืœื” "ื—ื•ืœื”", ืคื™ืจื•ืฉื” ืื™ื ื•
01:51
to make suggestions or to interfere or ...
29
111330
2000
ืœื”ืฆื™ืข ื”ืฆืขื•ืช ืื• ืœื”ืคืจื™ืข ืื• ...
01:53
This is not just in Hebrew, by the way.
30
113330
3000
ื–ื” ืœื ืจืง ื‘ืขื‘ืจื™ืช, ืื’ื‘.
01:56
It's in every language I've had experience with so far.
31
116330
3000
ื–ื” ื‘ื›ืœ ืฉืคื” ืฉืคื’ืฉืชื™ ืขื“ ื›ื”.
01:59
And, you know, there's not much -- there wasn't much I could do,
32
119330
4000
ื•ืืชื ื™ื•ื“ืขื™ื, ืื™ืŸ ื”ืจื‘ื” -- ืœื ื”ื™ื” ื”ืจื‘ื” ืฉื™ื›ืœืชื™ ืœืขืฉื•ืช,
02:03
and they kept on doing what they were doing.
33
123330
3000
ื•ื”ืŸ ื”ืžืฉื™ื›ื• ืœืขืฉื•ืช ืžื” ืฉื”ืŸ ืขืฉื•.
02:06
And about three years later, when I left the hospital,
34
126330
2000
ื•ื›-3 ืฉื ื™ื ืœืื—ืจ ืžื›ืŸ, ื›ืฉืขื–ื‘ืชื™ ืืช ื‘ื™ืช ื”ื—ื•ืœื™ื,
02:08
I started studying at the university.
35
128330
3000
ื”ืชื—ืœืชื™ ืœืœืžื•ื“ ื‘ืื•ื ื™ื‘ืจืกื™ื˜ื”.
02:11
And one of the most interesting lessons I learned
36
131330
3000
ื•ืื—ื“ ื”ืฉื™ืขื•ืจื™ื ื”ืžืขื ื™ื™ื ื™ื ื‘ื™ื•ืชืจ ืฉืœืžื“ืชื™
02:14
was that there is an experimental method
37
134330
2000
ื”ื™ื” ื›ื™ ื™ืฉื ื” ืฉื™ื˜ื” ื ื™ืกื™ื•ื ื™ืช
02:16
that if you have a question you can create a replica of this question
38
136330
4000
ืฉืื ื™ืฉ ืœืš ืฉืืœื”, ืืชื” ื™ื›ื•ืœ ืœื™ืฆื•ืจ ืขื•ืชืง ืฉืœ ืื•ืชื” ืฉืืœื”
02:20
in some abstract way, and you can try to examine this question,
39
140330
4000
ื‘ืื•ืคืŸ ืžื•ืคืฉื˜, ื•ืืชื” ื™ื›ื•ืœ ืœื‘ื—ื•ืŸ ืืช ื”ืฉืืœื”,
02:24
maybe learn something about the world.
40
144330
2000
ื•ืื•ืœื™ ืœืœืžื•ื“ ืžืฉื”ื• ืขืœ ื”ืขื•ืœื.
02:26
So that's what I did.
41
146330
2000
ืื– ื–ื” ืžื” ืฉืขืฉื™ืชื™.
02:28
I was still interested
42
148330
1000
ืขื“ื™ื™ืŸ ื”ืชืขื ื™ื™ื ืชื™
02:29
in this question of how do you take bandages off burn patients.
43
149330
2000
ื‘ืฉืืœื” ื”ื–ื• ืฉืœ ืื™ืš ืœื”ื•ืจื™ื“ ืชื—ื‘ื•ืฉื•ืช ืžืคืฆื•ืขื™ ื›ื•ื•ื™ื•ืช.
02:31
So originally I didn't have much money,
44
151330
3000
ืื– ืœื ื”ื™ื” ืœื™ ื”ืจื‘ื” ื›ืกืฃ,
02:34
so I went to a hardware store and I bought a carpenter's vice.
45
154330
4000
ืื– ื”ืœื›ืชื™ ืœื—ื ื•ืช ื—ื•ืžืจื™ ื‘ื ื™ื™ืŸ ื•ืงื ื™ืชื™ ืžืœื—ืฆื™ื™ื, ื›ืžื• ืฉืœ ื ื’ืจื™ื.
02:38
And I would bring people to the lab and I would put their finger in it,
46
158330
4000
ื•ื”ื‘ืืชื™ ืื ืฉื™ื ืœืžืขื‘ื“ื” ื•ื”ื›ื ืกืชื™ ืืช ื”ืืฆื‘ืข ืฉืœื”ื ืืœ ืชื•ืš ื”ืžืœื—ืฆื™ื™ื,
02:42
and I would crunch it a little bit.
47
162330
2000
ื•ืžืขื›ืชื™ ืื•ืชื” ืงืฆืช.
02:44
(Laughter)
48
164330
2000
(ืฆื—ื•ืง)
02:46
And I would crunch it for long periods and short periods,
49
166330
3000
ื•ืžืขื›ืชื™ ืื•ืชื” ืœืžืฉื›ื™ ื–ืžืŸ ืืจื•ื›ื™ื ื•ืžืฉื›ื™ ื–ืžืŸ ืงืฆืจื™ื,
02:49
and pain that went up and pain that went down,
50
169330
2000
ื•ื›ืื‘ ืฉืขืœื” ื•ื›ืื‘ ืฉื™ืจื“,
02:51
and with breaks and without breaks -- all kinds of versions of pain.
51
171330
4000
ื•ืขื ื”ืคืกืงื•ืช ื•ืœืœื ื”ืคืกืงื•ืช -- ืžื‘ื—ืจ ื’ืจืกืื•ืช ืฉืœ ื›ืื‘.
02:55
And when I finished hurting people a little bit, I would ask them,
52
175330
2000
ื•ื›ืฉืกื™ื™ืžืชื™ ืœื”ื›ืื™ื‘ ืœืื ืฉื™ื ืงืฆืช, ื”ื™ื™ืชื™ ืฉื•ืืœ ืื•ืชื,
02:57
so, how painful was this? Or, how painful was this?
53
177330
2000
ื•ื‘ื›ืŸ, ื›ืžื” ื–ื” ื›ืื‘? ืื• ื›ืžื” ื–ื” ื›ืื‘?
02:59
Or, if you had to choose between the last two,
54
179330
2000
ืื•, ืื ื”ื™ื™ืช ืฆืจื™ืš ืœื‘ื—ื•ืจ ืžื‘ื™ืŸ ืฉื ื™ ื”ืื—ืจื•ื ื™ื,
03:01
which one would you choose?
55
181330
2000
ื‘ืžื” ื”ื™ื™ืช ื‘ื•ื—ืจ?
03:03
(Laughter)
56
183330
3000
(ืฆื—ื•ืง)
03:06
I kept on doing this for a while.
57
186330
3000
ื”ืžืฉื›ืชื™ ืœืขืฉื•ืช ืืช ื–ื” ื‘ืžืฉืš ื–ืžืŸ ืžื”.
03:09
(Laughter)
58
189330
2000
(ืฆื—ื•ืง)
03:11
And then, like all good academic projects, I got more funding.
59
191330
4000
ื•ืื–, ื›ืžื• ื‘ื›ืœ ืžื—ืงืจ ืืงื“ืžืื™ ืžื•ืฆืœื—, ืงื™ื‘ืœืชื™ ืขื•ื“ ืžื™ืžื•ืŸ.
03:15
I moved to sounds, electrical shocks --
60
195330
2000
ื”ืชืงื“ืžืชื™ ืœืฆืœื™ืœ, ืฉื•ืง ื—ืฉืžืœื™ --
03:17
I even had a pain suit that I could get people to feel much more pain.
61
197330
5000
ืืคื™ืœื• ื”ื™ืชื” ืœื™ ื—ืœื™ืคืช ื›ืื‘ ืฉื™ื›ืœื” ืœื’ืจื•ื ืœืื ืฉื™ื ื”ืจื‘ื” ื™ื•ืชืจ ื›ืื‘.
03:22
But at the end of this process,
62
202330
4000
ืื‘ืœ ื‘ืกื•ืฃ ื”ืชื”ืœื™ืš,
03:26
what I learned was that the nurses were wrong.
63
206330
3000
ืžื” ืฉืœืžื“ืชื™ ื”ื™ื” ืฉื”ืื—ื™ื•ืช ื˜ืขื•.
03:29
Here were wonderful people with good intentions
64
209330
3000
ื”ืŸ ื”ื™ื• ื ืฉื™ื ืžื“ื”ื™ืžื•ืช ืขื ื›ื•ื•ื ื•ืช ื˜ื•ื‘ื•ืช
03:32
and plenty of experience, and nevertheless
65
212330
2000
ื•ืฉืคืข ืฉืœ ื ื™ืกื™ื•ืŸ, ืื‘ืœ ื‘ื›ืœ-ื–ืืช
03:34
they were getting things wrong predictably all the time.
66
214330
4000
ื”ืŸ ื˜ืขื• ื‘ืื•ืคืŸ ื ื™ืชืŸ ืœื—ื™ื–ื•ื™ ื›ืœ ื”ื–ืžืŸ.
03:38
It turns out that because we don't encode duration
67
218330
3000
ืžืกืชื‘ืจ, ืฉื‘ื’ืœืœ ืฉืื ื—ื ื• ืœื ืžื•ื“ื“ื™ื ืžืฉืš ื–ืžืŸ
03:41
in the way that we encode intensity,
68
221330
2000
ื‘ืื•ืชื” ื“ืจืš ื‘ื” ืื ื—ื ื• ืžื•ื“ื“ื™ื ืขื•ืฆืžื”,
03:43
I would have had less pain if the duration would have been longer
69
223330
4000
ื”ื™ื™ืชื™ ื—ื•ื•ื” ืคื—ื•ืช ื›ืื‘ ืื ืžืฉืš ื”ื–ืžืŸ ื”ื™ื” ืืจื•ืš ื™ื•ืชืจ
03:47
and the intensity was lower.
70
227330
2000
ื•ื”ืขื•ืฆืžื” ื ืžื•ื›ื” ื™ื•ืชืจ.
03:49
It turns out it would have been better to start with my face,
71
229330
3000
ืžืกืชื‘ืจ, ืฉื”ื™ื” ื˜ื•ื‘ ื™ื•ืชืจ ืื™ืœื• ื”ื™ื• ืžืชื—ื™ืœื™ื ืžื”ืคื ื™ื ืฉืœื™,
03:52
which was much more painful, and move toward my legs,
72
232330
2000
ืฉื”ื™ื” ื”ืจื‘ื” ื™ื•ืชืจ ื›ื•ืื‘ ื•ืื– ื”ื™ื• ืžืชืงื“ืžื™ื ืœื›ื™ื•ื•ืŸ ื”ืจื’ืœื™ื™ื,
03:54
giving me a trend of improvement over time --
73
234330
3000
ื•ื”ื™ื™ืชื™ ื—ื•ื•ื” ืžื’ืžืช ืฉื™ืคื•ืจ ืขื ื”ื–ืžืŸ.
03:57
that would have been also less painful.
74
237330
1000
ื–ื” ื’ื ื”ื™ื” ื›ื•ืื‘ ืคื—ื•ืช.
03:58
And it also turns out that it would have been good
75
238330
2000
ื•ื‘ื ื•ืกืฃ, ืžืกืชื‘ืจ ืฉื”ื™ื” ื˜ื•ื‘ ืื™ืœื•
04:00
to give me breaks in the middle to kind of recuperate from the pain.
76
240330
2000
ื”ื™ื• ืขื•ืฉื™ื ื”ืคืกืงื•ืช ื‘ืืžืฆืข ื›ื“ื™ ืœื”ืชืื•ืฉืฉ ืžื”ื›ืื‘.
04:02
All of these would have been great things to do,
77
242330
2000
ื›ืœ ืืœื” ื”ื™ื• ื“ื‘ืจื™ื ืฉื”ื™ื• ืžืื•ื“ ืจืฆื•ื™ื™ื,
04:04
and my nurses had no idea.
78
244330
3000
ื•ืœืื—ื™ื•ืช ืฉืœื™ ืœื ื”ื™ื” ืžื•ืฉื’.
04:07
And from that point on I started thinking,
79
247330
1000
ื•ืžื”ื ืงื•ื“ื” ื”ื–ืืช ื”ืชื—ืœืชื™ ืœื—ืฉื•ื‘,
04:08
are the nurses the only people in the world who get things wrong
80
248330
3000
ื”ืื ื”ืื—ื™ื•ืช ื”ืŸ ื”ืื ืฉื™ื ื”ื™ื—ื™ื“ื™ื ื‘ืขื•ืœื ืืฉืจ ื™ื˜ืขื•
04:11
in this particular decision, or is it a more general case?
81
251330
3000
ื‘ื”ื—ืœื˜ื” ื”ืกืคืฆื™ืคื™ืช ื”ื–ืืช, ืื• ื”ืื ืžื“ื•ื‘ืจ ื‘ืžืงืจื” ื›ืœืœื™ ื™ื•ืชืจ?
04:14
And it turns out it's a more general case --
82
254330
2000
ื•ืžืกืชื‘ืจ ืฉืžื“ื•ื‘ืจ ื‘ืžืงืจื” ื›ืœืœื™ ื™ื•ืชืจ --
04:16
there's a lot of mistakes we do.
83
256330
3000
ื™ืฉื ืŸ ื”ืจื‘ื” ื˜ืขื•ื™ื•ืช ืฉืื ื—ื ื• ืขื•ืฉื™ื.
04:19
And I want to give you one example of one of these irrationalities,
84
259330
5000
ื•ืื ื™ ืจื•ืฆื” ืœืชืช ืœื›ื ื“ื•ื’ืžื” ืฉืœ ืื—ืช ืžืื•ืชืŸ ื”ื—ืœื˜ื•ืช ืœื ื”ื’ื™ื•ื ื™ื•ืช,
04:24
and I want to talk to you about cheating.
85
264330
3000
ื•ืื ื™ ืจื•ืฆื” ืœื“ื‘ืจ ืื™ืชื›ื ืขืœ ืจืžืื•ืช.
04:27
And the reason I picked cheating is because it's interesting,
86
267330
2000
ื•ื”ืกื™ื‘ื” ืฉื‘ื—ืจืชื™ ื‘ืจืžืื•ืช ื”ื™ื ื›ื™ ื–ื” ื ื•ืฉื ืžืขื ื™ื™ืŸ,
04:29
but also it tells us something, I think,
87
269330
2000
ืื‘ืœ ื’ื ืžื’ืœื” ืœื ื• ื“ื‘ืจ ืžื”, ืื ื™ ื—ื•ืฉื‘,
04:31
about the stock market situation we're in.
88
271330
3000
ืขืœ ืžืฆื‘ ื”ื‘ื•ืจืกื” ื”ื ื•ื›ื—ื™.
04:34
So, my interest in cheating started
89
274330
3000
ืื– ื”ืขื ื™ื™ืŸ ืฉืœื™ ื‘ืจืžืื•ืช ื”ืชื—ื™ืœ
04:37
when Enron came on the scene, exploded all of a sudden,
90
277330
2000
ื›ืฉ"ืื ืจื•ืŸ" ืขืœืชื” ืœื‘ืžื”, ื”ืชืคื•ืฆืฆื” ืœืคืชืข,
04:39
and I started thinking about what is happening here.
91
279330
3000
ื•ืื ื™ ื”ืชื—ืœืชื™ ืœื—ืฉื•ื‘ ืขืœ ืžื” ืฉืงื•ืจื”.
04:42
Is it the case that there was kind of
92
282330
1000
ื”ืื ื–ื” ืžืงืจื” ืฉืœ
04:43
a few apples who are capable of doing these things,
93
283330
3000
ื›ืžื” ืชืคื•ื—ื™ื ืจืงื•ื‘ื™ื ืฉื”ื™ื• ืžืกื•ื’ืœื™ื ืœืขืฉื•ืช ืืช ื›ืœ ื–ื”?
04:46
or are we talking a more endemic situation,
94
286330
2000
ืื• ืฉืžื“ื•ื‘ืจ ื‘ืžืฆื‘ ื™ื•ืชืจ ืžื”ื•ืชื™,
04:48
that many people are actually capable of behaving this way?
95
288330
4000
ืฉื‘ื• ื”ืจื‘ื” ืื ืฉื™ื ืžืกื•ื’ืœื™ื ืœื”ืชื ื”ื’ ื‘ืื•ืคืŸ ื›ื–ื”?
04:52
So, like we usually do, I decided to do a simple experiment.
96
292330
4000
ืื–, ื›ืžื• ืฉื‘ื“"ื› ืื ื—ื ื• ืขื•ืฉื™ื, ื”ื—ืœื˜ืชื™ ืœืขืจื•ืš ื ื™ืกื•ื™ ืคืฉื•ื˜.
04:56
And here's how it went.
97
296330
1000
ื•ื›ืš ื”ื•ื ื”ืชื ื”ืœ:
04:57
If you were in the experiment, I would pass you a sheet of paper
98
297330
3000
ืื ื”ื™ื™ืชื ืžืฉืชืชืคื™ื ื‘ื ื™ืกื•ื™, ื”ื™ื™ืชื™ ื ื•ืชืŸ ืœื›ื ืคื™ืกืช ื ื™ื™ืจ
05:00
with 20 simple math problems that everybody could solve,
99
300330
4000
ืขื 20 ื‘ืขื™ื•ืช ืคืฉื•ื˜ื•ืช ื‘ืžืชืžื˜ื™ืงื” ืฉื›ืœ ืื—ื“ ื™ื›ื•ืœ ืœืคืชื•ืจ,
05:04
but I wouldn't give you enough time.
100
304330
2000
ืื‘ืœ ืœื ื”ื™ื™ืชื™ ื ื•ืชืŸ ืœื›ื ืžืกืคื™ืง ื–ืžืŸ.
05:06
When the five minutes were over, I would say,
101
306330
2000
ืื—ืจื™ ืฉ5 ื”ื“ืงื•ืช ื”ื™ื• ืขื•ื‘ืจื•ืช
05:08
"Pass me the sheets of paper, and I'll pay you a dollar per question."
102
308330
3000
"ื”ื—ื–ื™ืจื• ืืช ื”ื ื™ื™ืจื•ืช ื•ืืฉืœื ืœื›ื ื“ื•ืœืจ ืœื›ืœ ืฉืืœื”."
05:11
People did this. I would pay people four dollars for their task --
103
311330
4000
ืื ืฉื™ื ืขืฉื• ื›ืŸ, ื•ืฉื™ืœืžืชื™ ืœื”ื 4 ื“ื•ืœืจื™ื ืขืœ ื”ืžืฉื™ืžื” -
05:15
on average people would solve four problems.
104
315330
2000
ื‘ืžืžื•ืฆืข, ืื ืฉื™ื ืคืชืจื• 4 ืฉืืœื•ืช.
05:17
Other people I would tempt to cheat.
105
317330
3000
ืœืื—ืจื™ื ื ื™ืกื™ืชื™ ืœื’ืจื•ื ืœืจืžื•ืช.
05:20
I would pass their sheet of paper.
106
320330
1000
ื—ื™ืœืงืชื™ ืืช ื ื™ื™ืจื•ืช ื”ื‘ื—ื™ื ื” ืฉืœื”ื
05:21
When the five minutes were over, I would say,
107
321330
2000
ื•ืื—ืจื™ 5 ื“ืงื•ืช, ืืžืจืชื™:
05:23
"Please shred the piece of paper.
108
323330
1000
"ื‘ื‘ืงืฉื”, ืงืจืขื• ืืช ื”ื ื™ื™ืจื•ืช ืฉืœื›ื.
05:24
Put the little pieces in your pocket or in your backpack,
109
324330
3000
ืฉื™ืžื• ืืช ื—ืชื™ื›ื•ืช ื”ื ื™ื™ืจ ื‘ื›ื™ืก ืื• ื‘ืชื™ืง ืฉืœื›ื.
05:27
and tell me how many questions you got correctly."
110
327330
3000
ื•ืืžืจื• ืœื™, ื‘ื›ืžื” ืชืฉื•ื‘ื•ืช ืฆื“ืงืชื."
05:30
People now solved seven questions on average.
111
330330
3000
ืขื›ืฉื™ื• ืื ืฉื™ื ืคืชืจื• 7 ืฉืืœื•ืช ื‘ืžืžื•ืฆืข.
05:33
Now, it wasn't as if there was a few bad apples --
112
333330
5000
ื•ื–ื” ืœื ืฉื›ื‘ื™ื›ื•ืœ ื”ื™ื• ื›ืžื” ืชืคื•ื—ื™ื ืจืงื•ื‘ื™ื --
05:38
a few people cheated a lot.
113
338330
3000
ืžืขื˜ ืื ืฉื™ื ืฉืจื™ืžื• ื”ืจื‘ื”,
05:41
Instead, what we saw is a lot of people who cheat a little bit.
114
341330
3000
ื‘ืžืงื•ื ื–ืืช, ืจืื™ื ื• ื”ืจื‘ื” ืื ืฉื™ื ืฉืจื™ืžื• ืžืขื˜.
05:44
Now, in economic theory,
115
344330
3000
ืขื›ืฉื™ื•, ื‘ืชื™ืื•ืจื™ื” ื›ืœื›ืœื™ืช,
05:47
cheating is a very simple cost-benefit analysis.
116
347330
3000
ืจืžืื•ืช ื”ื™ื ื—ื™ืฉื•ื‘ ืคืฉื•ื˜ ืžืื•ื“ ืฉืœ ืขืœื•ืช-ืชื•ืขืœืช.
05:50
You say, what's the probability of being caught?
117
350330
2000
ืืชื” ื—ื•ืฉื‘, ืžื” ื”ืกื™ื›ื•ื™ ืœื”ื™ืชืคืก?
05:52
How much do I stand to gain from cheating?
118
352330
3000
ื›ืžื” ืื ื™ ืฆืคื•ื™ ืœื”ืจื•ื•ื™ื— ืžื”ืจืžืื•ืช?
05:55
And how much punishment would I get if I get caught?
119
355330
2000
ื•ื›ืžื” ืื™ืขื ืฉ ืื ืืชืคืก?
05:57
And you weigh these options out --
120
357330
2000
ื•ืืชื” ืฉื•ืงืœ ืืช ื”ืืคืฉืจื•ื™ื•ืช ื”ืืœื” --
05:59
you do the simple cost-benefit analysis,
121
359330
2000
ืืชื” ืขื•ืจืš ืืช ื”ื—ื™ืฉื•ื‘ ื”ืคืฉื•ื˜ ืฉืœ ืขืœื•ืช-ืชื•ืขืœืช,
06:01
and you decide whether it's worthwhile to commit the crime or not.
122
361330
3000
ื•ืืชื” ืžื—ืœื™ื˜ ืื ืžืฉืชืœื ืœืš ืœื‘ืฆืข ืืช ื”ืคืฉืข ืื• ืœื.
06:04
So, we try to test this.
123
364330
2000
ืื– ืื ื—ื ื• ืžื ืกื™ื ืœื‘ื—ื•ืŸ ืืช ื–ื”.
06:06
For some people, we varied how much money they could get away with --
124
366330
4000
ืœื—ืœืง ืžื”ืื ืฉื™ื, ืฉื™ื ื™ื ื• ืืช ื›ืžื•ืช ื”ื›ืกืฃ ืฉื”ื ื™ื›ืœื• ืœื”ืจื•ื•ื™ื— --
06:10
how much money they could steal.
125
370330
1000
ื›ืžื” ื›ืกืฃ ื”ื ื™ื•ื›ืœื• ืœื’ื ื•ื‘.
06:11
We paid them 10 cents per correct question, 50 cents,
126
371330
3000
ืฉื™ืœืžื ื• ืœื”ื 10 ืกื ื˜ ืขื‘ื•ืจ ื›ืœ ืชืฉื•ื‘ื” ื ื›ื•ื ื”, 50 ืกื ื˜,
06:14
a dollar, five dollars, 10 dollars per correct question.
127
374330
3000
ื“ื•ืœืจ ืื—ื“, 5 ื“ื•ืœืจื™ื, 10 ื“ื•ืœืจื™ื ืขื‘ื•ืจ ืชืฉื•ื‘ื” ื ื›ื•ื ื”.
06:17
You would expect that as the amount of money on the table increases,
128
377330
4000
ื ื™ืชืŸ ืœืฆืคื•ืช ืฉื›ื›ืœ ืฉื”ืกื›ื•ื "ืขืœ ื”ืฉื•ืœื—ืŸ" ืขื•ืœื”,
06:21
people would cheat more, but in fact it wasn't the case.
129
381330
3000
ืื ืฉื™ื ื™ืจืžื• ื™ื•ืชืจ. ืื‘ืœ ืœืžืขืฉื”, ืœื ื›ืš ื”ื™ื”.
06:24
We got a lot of people cheating by stealing by a little bit.
130
384330
3000
ืงื™ื‘ืœื ื• ื”ืจื‘ื” ืื ืฉื™ื ืฉืžืจืžื™ื ืข"ื™ ื’ื ื™ื‘ืช ืžืขื˜.
06:27
What about the probability of being caught?
131
387330
3000
ืžื” ืœื’ื‘ื™ ื”ืกื‘ื™ืจื•ืช ืœื”ื™ืชืคืก?
06:30
Some people shredded half the sheet of paper,
132
390330
2000
ื—ืœืง ืžื”ืื ืฉื™ื ืงืจืขื• ื—ืฆื™ ืžื”ื ื™ื™ืจ ืฉืœื”ื,
06:32
so there was some evidence left.
133
392330
1000
ื›ืš ืฉื ืฉืืจื• ืจืื™ื•ืช.
06:33
Some people shredded the whole sheet of paper.
134
393330
2000
ื—ืœืง ืžื”ืื ืฉื™ื ืงืจืขื• ืืช ื›ืœ ื”ื ื™ื™ืจ ืฉืœื”ื.
06:35
Some people shredded everything, went out of the room,
135
395330
3000
ื—ืœืง ืžื”ืื ืฉื™ื ืงืจืขื• ื”ื›ืœ, ื™ืฆืื• ืžื”ื—ื“ืจ,
06:38
and paid themselves from the bowl of money that had over 100 dollars.
136
398330
3000
ื•ืฉื™ืœืžื• ืœืขืฆืžื ืžืงืขืจืช ื”ื›ืกืฃ ืฉื”ื›ื™ืœื” ื™ื•ืชืจ ืž100 ื“ื•ืœืจ.
06:41
You would expect that as the probability of being caught goes down,
137
401330
3000
ื ื™ืชืŸ ื”ื™ื” ืœืฆืคื•ืช, ืฉื›ื›ืœ ืฉื”ืกื‘ื™ืจื•ืช ืœื”ื™ืชืคืก ื™ื•ืจื“ืช,
06:44
people would cheat more, but again, this was not the case.
138
404330
3000
ืื ืฉื™ื ื™ืจืžื• ื™ื•ืชืจ, ืื‘ืœ, ืฉื•ื‘, ืœื ื›ืš ื”ื™ื”.
06:47
Again, a lot of people cheated by just by a little bit,
139
407330
3000
ืฉื•ื‘, ื”ืจื‘ื” ืื ืฉื™ื ืจื™ืžื• ืืš ื‘ืžืขื˜.
06:50
and they were insensitive to these economic incentives.
140
410330
3000
ื•ื”ื ื”ื™ื• ืื“ื™ืฉื™ื ืœืชืžืจื™ืฆื™ื ื”ื›ืœื›ืœื™ื™ื ื”ืืœื”.
06:53
So we said, "If people are not sensitive
141
413330
1000
ืื– ืืžืจื ื•, "ืื ืื ืฉื™ื ืื“ื™ืฉื™ื
06:54
to the economic rational theory explanations, to these forces,
142
414330
5000
ืœื”ืกื‘ืจื™ื ื”ื”ื’ื™ื•ื ื™ื™ื ืฉืœ ื”ืชื•ืจื” ื”ื›ืœื›ืœื™ืช, ืœื›ื•ื—ื•ืช ื”ืืœื”,
06:59
what could be going on?"
143
419330
3000
ืžื” ื‘ืขืฆื ืงื•ืจื” ืคื”?"
07:02
And we thought maybe what is happening is that there are two forces.
144
422330
3000
ื•ื—ืฉื‘ื ื• ืฉืื•ืœื™ ืžื” ืฉืงื•ืจื” ื–ื” ืฉื™ืฉื ื ืฉื ื™ ื›ื•ื—ื•ืช.
07:05
At one hand, we all want to look at ourselves in the mirror
145
425330
2000
ืžืฆื“ ืื—ื“, ื›ื•ืœื ื• ืจื•ืฆื™ื ืœื”ื‘ื™ื˜ ื‘ืžืจืื”
07:07
and feel good about ourselves, so we don't want to cheat.
146
427330
3000
ื•ืœื”ืจื’ื™ืฉ ื˜ื•ื‘ ืขื ืขืฆืžื ื•, ืื– ืื ื—ื ื• ืœื ืจื•ืฆื™ื ืœืจืžื•ืช.
07:10
On the other hand, we can cheat a little bit,
147
430330
2000
ืžืฆื“ ืฉื ื™, ืื ื—ื ื• ื™ื›ื•ืœื™ื ืœืจืžื•ืช ืงืฆืช,
07:12
and still feel good about ourselves.
148
432330
2000
ื•ืขื“ื™ื™ืŸ ืœื”ืจื’ื™ืฉ ื˜ื•ื‘ ืขื ืขืฆืžื ื•.
07:14
So, maybe what is happening is that
149
434330
1000
ืื– ืื•ืœื™, ืžื” ืฉืงื•ืจื” ื”ื•ื
07:15
there's a level of cheating we can't go over,
150
435330
2000
ืฉื™ืฉ ืจืžืช ืจืžืื•ืช ืฉืื ื—ื ื• ืœื ื™ื›ื•ืœื™ื ืœืขื‘ื•ืจ,
07:17
but we can still benefit from cheating at a low degree,
151
437330
4000
ืื‘ืœ ืื ื—ื ื• ื‘ื›"ื– ื™ื›ื•ืœื™ื ืœื”ืจื•ื•ื™ื— ืžืจืžืื•ืช ื‘ืจืžื” ื ืžื•ื›ื”,
07:21
as long as it doesn't change our impressions about ourselves.
152
441330
3000
ื›ืœ ืขื•ื“ ื”ืจืžืื•ืช ืœื ืžืฉื ื” ืืช ื”ื“ื™ืžื•ื™ ื”ืขืฆืžื™ ืฉืœื ื•.
07:24
We call this like a personal fudge factor.
153
444330
3000
ืื ื—ื ื• ืงื•ืจืื™ื ืœื–ื” "ื’ื•ืจื ืืœืชื•ืจ".
07:28
Now, how would you test a personal fudge factor?
154
448330
4000
ืขื›ืฉื™ื•, ืื™ืš ื‘ื•ื“ืงื™ื ื’ื•ืจื ืืœืชื•ืจ ืื™ืฉื™?
07:32
Initially we said, what can we do to shrink the fudge factor?
155
452330
4000
ื‘ืชื—ื™ืœื” ืฉืืœื ื• ืื™ืš ื ื•ื›ืœ ืœืฆืžืฆื ืืช ื’ื•ืจื ื”ืืœืชื•ืจ?
07:36
So, we got people to the lab, and we said,
156
456330
2000
ืื– ื”ื‘ืื ื• ืื ืฉื™ื ืœืžืขื‘ื“ื” ื•ืืžืจื ื•:
07:38
"We have two tasks for you today."
157
458330
2000
"ื™ืฉ ืœื ื• ืฉืชื™ ืžืฉื™ืžื•ืช ื‘ืฉื‘ื™ืœื›ื ื”ื™ื•ื."
07:40
First, we asked half the people
158
460330
1000
ืจืืฉื™ืช, ื‘ื™ืงืฉื ื• ืžืžื—ืฆื™ืช ืžื”ืื ืฉื™ื
07:41
to recall either 10 books they read in high school,
159
461330
2000
ืœื”ื™ื–ื›ืจ ื‘10 ืกืคืจื™ื ืฉืงืจืื• ื‘ืชื™ื›ื•ืŸ,
07:43
or to recall The Ten Commandments,
160
463330
3000
ืื• ืœื”ื™ื–ื›ืจ ื‘10 ื”ื“ื™ื‘ืจื•ืช,
07:46
and then we tempted them with cheating.
161
466330
2000
ื•ืื– ืคื™ืชื™ื ื• ืื•ืชื ืขื ืจืžืื•ืช.
07:48
Turns out the people who tried to recall The Ten Commandments --
162
468330
3000
ื”ืกืชื‘ืจ, ืฉื”ืื ืฉื™ื ืฉื ื™ืกื• ืœื”ื™ื–ื›ืจ ื‘10 ื”ื“ื™ื‘ืจื•ืช --
07:51
and in our sample nobody could recall all of The Ten Commandments --
163
471330
2000
ื•ื‘ืžืงืจื” ืฉืœื ื• ืืฃ-ืื—ื“ ืœื ื”ืฆืœื™ื— ืœื”ื™ื–ื›ืจ ื‘10 ื”ื“ื™ื‘ืจื•ืช --
07:54
but those people who tried to recall The Ten Commandments,
164
474330
4000
ืื‘ืœ, ืื•ืชื ืื ืฉื™ื ืฉื ื™ืกื• ืœื”ื™ื–ื›ืจ ื‘10 ื”ื“ื™ื‘ืจื•ืช
07:58
given the opportunity to cheat, did not cheat at all.
165
478330
3000
ื‘ื”ื™ื ืชืŸ ื”ื”ื–ื“ืžื ื•ืช ืœืจืžื•ืช - ืœื ืจื™ืžื• ื›ืœืœ.
08:01
It wasn't that the more religious people --
166
481330
2000
ื–ื” ืœื ืฉื”ืื ืฉื™ื ื”ื“ืชื™ื™ื ื™ื•ืชืจ --
08:03
the people who remembered more of the Commandments -- cheated less,
167
483330
1000
ืืœื” ืฉื–ื›ืจื• ื™ื•ืชืจ ืžื”ื“ื™ื‘ืจื•ืช -- ืจื™ืžื• ืคื—ื•ืช,
08:04
and the less religious people --
168
484330
2000
ื•ืฉื”ืื ืฉื™ื ื”ื“ืชื™ื™ื ืคื—ื•ืช --
08:06
the people who couldn't remember almost any Commandments --
169
486330
1000
ืืœื” ืฉื›ืžืขื˜ ื•ืœื ื”ืฆืœื™ื—ื• ืœื”ื™ื–ื›ืจ ื‘ื“ื™ื‘ืจื•ืช --
08:07
cheated more.
170
487330
2000
ืจื™ืžื• ื™ื•ืชืจ.
08:09
The moment people thought about trying to recall The Ten Commandments,
171
489330
4000
ื‘ืจื’ืข ืฉืื ืฉื™ื ื—ืฉื‘ื• ืขืœ ืœื ืกื•ืช ื•ืœื”ื™ื–ื›ืจ ื‘10 ื”ื“ื™ื‘ืจื•ืช
08:13
they stopped cheating.
172
493330
1000
ื”ื ื”ืคืกื™ืงื• ืœืจืžื•ืช.
08:14
In fact, even when we gave self-declared atheists
173
494330
2000
ืœืžืขืฉื”, ืืคื™ืœื• ื›ืฉื ืชื ื• ืœืืชื™ืื™ืกื˜ื™ื ืžื•ืฆื”ืจื™ื
08:16
the task of swearing on the Bible and we give them a chance to cheat,
174
496330
4000
ืืช ื”ืžืฉื™ืžื” ืœื”ื™ืฉื‘ืข ืขืœ ืกืคืจ ื”ืชื "ืš ื•ืื– ื ืชื ื• ืœื”ื ื”ื–ื“ืžื ื•ืช ืœืจืžื•ืช,
08:20
they don't cheat at all.
175
500330
2000
ื”ื ืœื ืจื™ืžื• ื›ืœืœ.
08:24
Now, Ten Commandments is something that is hard
176
504330
2000
ืขื›ืฉื™ื•, 10 ื”ื“ื™ื‘ืจื•ืช ื”ืŸ ื“ื‘ืจ ืฉืงืฉื”
08:26
to bring into the education system, so we said,
177
506330
2000
ืœื”ื›ื ื™ืก ืœืžืขืจื›ืช ื”ื—ื™ื ื•ืš, ืื– ืืžืจื ื•
08:28
"Why don't we get people to sign the honor code?"
178
508330
2000
"ืœืžื” ืฉืœื ื ื’ืจื•ื ืœืื ืฉื™ื ืœื—ืชื•ื ืขืœ 'ืงื•ื“ ืืชื™'?"
08:30
So, we got people to sign,
179
510330
2000
ืื– ื’ืจืžื ื• ืœื”ื ืœื—ืชื•ื:
08:32
"I understand that this short survey falls under the MIT Honor Code."
180
512330
4000
"ืื ื™ ืžื‘ื™ืŸ ืฉื”ืกืงืจ ื”ืงืฆืจ ื”ื–ื” ื™ืขืจืš ื‘ื”ืชืื ืœืงื•ื“ ื”ืืชื™ ืฉืœ MIT ."
08:36
Then they shredded it. No cheating whatsoever.
181
516330
3000
ื•ืื– ื”ื ืงืจืขื• ืืช ื–ื” ืœื’ื–ืจื™ื. ืฉื•ื ืจืžืื•ืช ื‘ื›ืœืœ.
08:39
And this is particularly interesting,
182
519330
1000
ื•ื–ื” ืžืื•ื“ ืžืขื ื™ื™ืŸ
08:40
because MIT doesn't have an honor code.
183
520330
2000
ื›ื™ ืœืื•ื ื™ื‘ืจืกื™ื˜ืช MIT ื›ืœืœ ืื™ืŸ "ืงื•ื“ ืืชื™".
08:42
(Laughter)
184
522330
5000
(ืฆื—ื•ืง)
08:47
So, all this was about decreasing the fudge factor.
185
527330
4000
ืื–, ื›ืœ ื–ื” ืžืงื˜ื™ืŸ ืืช "ื’ื•ืจื ื”ืืœืชื•ืจ."
08:51
What about increasing the fudge factor?
186
531330
3000
ื•ืžื” ื‘ื“ื‘ืจ ื”ื’ื“ืœืช "ื’ื•ืจื ื”ืืœืชื•ืจ"?
08:54
The first experiment -- I walked around MIT
187
534330
2000
ื”ื ื™ืกื•ื™ ื”ืจืืฉื•ืŸ -- ื”ืกืชื•ื‘ื‘ืชื™ ื‘MIT
08:56
and I distributed six-packs of Cokes in the refrigerators --
188
536330
3000
ื•ืคื™ื–ืจืชื™ ืฉื™ืฉื™ื•ืช ืฉืœ ืงื•ืœื” ื‘ืžืงืจืจื™ื --
08:59
these were common refrigerators for the undergrads.
189
539330
2000
ืืœื” ื”ื™ื• ืžืงืจืจื™ื ืžืฉื•ืชืคื™ื ืœืชืœืžื™ื“ื™ ื”ืชื•ืืจ ื”ืจืืฉื•ืŸ.
09:01
And I came back to measure what we technically call
190
541330
3000
ื•ื—ื–ืจืชื™ ืœืžื“ื•ื“ ืืช ืžื” ืฉืื ื—ื ื• ืงื•ืจืื™ื ืœื•
09:04
the half-lifetime of Coke -- how long does it last in the refrigerators?
191
544330
4000
"ื–ืžืŸ ืžื—ืฆื™ืช ื”ื—ื™ื™ื" ืฉืœ ืงื•ืœื” -- ื›ืžื” ื–ืžืŸ ื”ื™ื ืชืฉืจื•ื“ ื‘ืžืงืจืจื™ื?
09:08
As you can expect it doesn't last very long; people take it.
192
548330
3000
ื•ื›ืžื• ืฉื ื™ืชืŸ ืœืฆืคื•ืช, ื”ื™ื ืœื ืฉื•ืจื“ืช ื”ืจื‘ื” ื–ืžืŸ. ืื ืฉื™ื ืœื•ืงื—ื™ื ืื•ืชื”.
09:11
In contrast, I took a plate with six one-dollar bills,
193
551330
4000
ืœื”ื‘ื“ื™ืœ, ืœืงื—ืชื™ ืฆืœื—ืช ืขื 6 ืฉื˜ืจื•ืช ื‘ื ื™ ื“ื•ืœืจ ืื—ื“,
09:15
and I left those plates in the same refrigerators.
194
555330
3000
ื•ื”ืฉืืจืชื™ ืื•ืชื ื‘ืื•ืชื ืžืงืจืจื™ื.
09:18
No bill ever disappeared.
195
558330
1000
ืืฃ ืฉื˜ืจ ืœื ื ืขืœื.
09:19
Now, this is not a good social science experiment,
196
559330
3000
ืื‘ืœ, ื–ื” ืื™ื ื• ื ื™ืกื•ื™ ื˜ื•ื‘ ื‘ืžื“ืขื™ ื”ื—ื‘ืจื”,
09:22
so to do it better I did the same experiment
197
562330
3000
ืื– ื›ื“ื™ ืœืฉืคืจ ืื•ืชื•, ืขืจื›ืชื™ ืืช ืื•ืชื• ื”ื ื™ืกื•ื™
09:25
as I described to you before.
198
565330
2000
ื›ืคื™ ืฉืชื™ืืจืชื™ ืœื›ื ื”ืจื’ืข.
09:27
A third of the people we passed the sheet, they gave it back to us.
199
567330
3000
ืฉืœื™ืฉ ืžื”ืื ืฉื™ื ืฉืงื™ื‘ืœื• ืืช ื“ืคื™ ื”ื ื™ื™ืจ - ื”ื—ื–ื™ืจื• ืื•ืชื,
09:30
A third of the people we passed it to, they shredded it,
200
570330
3000
ืฉืœื™ืฉ ืžื”ืื ืฉื™ื ืฉืงื™ื‘ืœื• ืืช ื”ื“ืคื™ื - ืงืจืขื• ืื•ืชื, 202 00:09:15,000 --> 00:09:16,000 ื”ื ืคื ื• ืืœื™ื ื• ื•ืืžืจื•:
09:33
they came to us and said,
201
573330
1000
ื”ื ืคื ื• ืืœื™ื ื• ื•ืืžืจื•
09:34
"Mr. Experimenter, I solved X problems. Give me X dollars."
202
574330
3000
"ืžืจ ื ืกื™ื™ืŸ, ืคืชืจืชื™ X ืฉืืœื•ืช. ืชืŸ ืœื™ X ื“ื•ืœืจื™ื."
09:37
A third of the people, when they finished shredding the piece of paper,
203
577330
3000
ืฉืœื™ืฉ ืžื”ืื ืฉื™ื ื›ืฉืกื™ื™ืžื• ืœืงืจื•ืข ืืช ื”ื ื™ื™ืจื•ืช
09:40
they came to us and said,
204
580330
2000
ื‘ืื• ืืœื™ื ื• ื•ืืžืจื•:
09:42
"Mr Experimenter, I solved X problems. Give me X tokens."
205
582330
6000
"ืžืจ ื ืกื™ื™ืŸ, ืคืชืจืชื™ X ืฉืืœื•ืช, ืชืŸ ืœื™ X ืืกื™ืžื•ื ื™ื."
09:48
We did not pay them with dollars; we paid them with something else.
206
588330
3000
ืœื ืฉื™ืœืžื ื• ืœื”ื ื‘ื“ื•ืœืจื™ื. ืฉื™ืœืžื ื• ืœื”ื ื‘ืžืฉื”ื• ืื—ืจ.
09:51
And then they took the something else, they walked 12 feet to the side,
207
591330
3000
ื•ืื– ื”ื ืœืงื—ื• ืืช ื”ืžืฉื”ื• ื”ืื—ืจ, ื”ืœื›ื• 4 ืžื˜ืจ ื”ืฆื™ื“ื”,
09:54
and exchanged it for dollars.
208
594330
2000
ื•ื”ื—ืœื™ืคื• ืืช ื”ืžืฉื”ื• ื”ื–ื” ื‘ื“ื•ืœืจื™ื.
09:56
Think about the following intuition.
209
596330
2000
ืชื—ืฉื‘ื• ืขืœ ื”ืชืคื™ืกื” ื”ืื™ื ื˜ื•ืื™ื˜ื™ื‘ื™ืช ื”ื‘ืื”:
09:58
How bad would you feel about taking a pencil from work home,
210
598330
3000
ื›ืžื” ืจืข ืชืจื’ื™ืฉื• ืื ืชื™ืงื—ื• ืขื™ืคืจื•ืŸ ืžื”ืขื‘ื•ื“ื” ื”ื‘ื™ืชื”,
10:01
compared to how bad would you feel
211
601330
2000
ื‘ื”ืฉื•ื•ืื” ืœื›ืžื” ืจืข ืชืจื’ื™ืฉื•
10:03
about taking 10 cents from a petty cash box?
212
603330
2000
ืื ืชื™ืงื—ื• 10 ืกื ื˜ ืžื”ืงื•ืคื” ื”ืงื˜ื ื” ื‘ืžืฉืจื“?
10:05
These things feel very differently.
213
605330
3000
ื”ื“ื‘ืจื™ื ื”ืœืœื• ื ื•ืชื ื™ื ืชื—ื•ืฉื” ืฉื•ื ื” ืœื’ืžืจื™.
10:08
Would being a step removed from cash for a few seconds
214
608330
3000
ื”ืื ื”ืจื—ืงืช ื”ืื ืฉื™ื ืžื”ื›ืกืฃ ื”ืžื–ื•ืžืŸ ืœืžืฉืš ื›ืžื” ืฉื ื™ื•ืช
10:11
by being paid by token make a difference?
215
611330
3000
ืข"ื™ ืชืฉืœื•ื ื‘ืืกื™ืžื•ื ื™ื ืชืฉืคื™ืข?
10:14
Our subjects doubled their cheating.
216
614330
2000
ื”ืžืฉืชืชืคื™ื ื”ื›ืคื™ืœื• ืืช ื”ืจืžืื•ืช ืฉืœื”ื.
10:16
I'll tell you what I think
217
616330
2000
ืื•ืžืจ ืœื›ื ืžื” ืื ื™ ื—ื•ืฉื‘
10:18
about this and the stock market in a minute.
218
618330
2000
ืœื’ื‘ื™ ื–ื” ื•ื”ื‘ื•ืจืกื” ื‘ืขื•ื“ ืจื’ืข.
10:21
But this did not solve the big problem I had with Enron yet,
219
621330
4000
ืื‘ืœ ื–ื” ืขื“ื™ื™ืŸ ืœื ืคืชืจ ืืช ื”ื‘ืขื™ื” ื”ื’ื“ื•ืœื” ืฉื”ื™ืชื” ืœื™ ืขื "ืื ืจื•ืŸ,"
10:25
because in Enron, there's also a social element.
220
625330
3000
ื›ื™ื•ื•ืŸ ืฉื‘"ืื ืจื•ืŸ" ื™ืฉื ื• ื’ื ืžืจื›ื™ื‘ ื—ื‘ืจืชื™.
10:28
People see each other behaving.
221
628330
1000
ืื ืฉื™ื ืจื•ืื™ื ืืช ื”ื”ืชื ื”ื’ื•ืช ืฉืœ ื”ืฉืืจ.
10:29
In fact, every day when we open the news
222
629330
2000
ืœืžืขืฉื”, ื‘ื›ืœ ื™ื•ื, ื›ืฉืื ื—ื ื• ืคื•ืชื—ื™ื ืืช ื”ืขื™ืชื•ืŸ
10:31
we see examples of people cheating.
223
631330
2000
ืื ื—ื ื• ืจื•ืื™ื ื“ื•ื’ืžืื•ืช ืฉืœ ืื ืฉื™ื ืžืจืžื™ื.
10:33
What does this cause us?
224
633330
3000
ืื™ืš ื–ื” ืžืฉืคื™ืข ืขืœื™ื ื•?
10:36
So, we did another experiment.
225
636330
1000
ืื– ืขืจื›ื ื• ื ื™ืกื•ื™ ื ื•ืกืฃ.
10:37
We got a big group of students to be in the experiment,
226
637330
3000
ืื™ืจื’ื ื• ืงื‘ื•ืฆืช ืกื˜ื•ื“ื ื˜ื™ื ื’ื“ื•ืœื” ืœื ื™ืกื•ื™
10:40
and we prepaid them.
227
640330
1000
ื•ืฉื™ืœืžื ื• ืœื”ื ืžืจืืฉ,
10:41
So everybody got an envelope with all the money for the experiment,
228
641330
3000
ื›ืš ืฉื›ืœ ืื—ื“ ืงื™ื‘ืœ ืžืขื˜ืคื” ืขื ื”ืชืฉืœื•ื ืขื‘ื•ืจ ื”ื ื™ืกื•ื™.
10:44
and we told them that at the end, we asked them
229
644330
2000
ื•ืืžืจื ื• ืœื”ื ืฉื‘ืกื•ืฃ, ื‘ื™ืงืฉื ื• ืžื”ื
10:46
to pay us back the money they didn't make. OK?
230
646330
4000
ืœืฉืœื ืœื ื• ื‘ื—ื–ืจื” ืืช ื”ื›ืกืฃ ืฉืœื ื”ืจื•ื•ื™ื—ื•. ื™ืฉ?
10:50
The same thing happens.
231
650330
1000
ืื•ืชื• ื”ื“ื‘ืจ ืงืจื”.
10:51
When we give people the opportunity to cheat, they cheat.
232
651330
2000
ื›ืฉืื ื—ื ื• ื ื•ืชื ื™ื ืœืื ืฉื™ื ืืช ื”ื”ื–ื“ืžื ื•ืช ืœืจืžื•ืช, ื”ื ืžืจืžื™ื.
10:53
They cheat just by a little bit, all the same.
233
653330
3000
ื”ื ืžืจืžื™ื ื‘ืงืฆืช, ืื‘ืœ ืžืจืžื™ื.
10:56
But in this experiment we also hired an acting student.
234
656330
3000
ืื‘ืœ ื‘ืžืงืจื” ื”ื–ื” ืฉื›ืจื ื• ื’ื ืกื˜ื•ื“ื ื˜ ืœืžืฉื—ืง.
10:59
This acting student stood up after 30 seconds, and said,
235
659330
4000
ื”ืกื˜ื•ื“ื ื˜ ืœืžืฉื—ืง ื ืขืžื“ ืœืื—ืจ 30 ืฉื ื™ื•ืช ื•ืืžืจ:
11:03
"I solved everything. What do I do now?"
236
663330
3000
"ืคืชืจืชื™ ื”ื›ืœ, ืžื” ืœืขืฉื•ืช?"
11:06
And the experimenter said, "If you've finished everything, go home.
237
666330
4000
ื•ื”ื ืกื™ื™ืŸ ืืžืจ: "ืื ืคืชืจืช ื”ื›ืœ, ืœืš ื”ื‘ื™ืชื”,
11:10
That's it. The task is finished."
238
670330
1000
ื–ื”ื• ื–ื”, ื”ืžืฉื™ืžื” ื ื’ืžืจื”."
11:11
So, now we had a student -- an acting student --
239
671330
4000
ืื– ืขื›ืฉื™ื• ื”ื™ื” ืœื ื• ืกื˜ื•ื“ื ื˜ -- ืกื˜ื•ื“ื ื˜ ืœืžืฉื—ืง --
11:15
that was a part of the group.
240
675330
2000
ืฉื”ื™ื” ื—ืœืง ืžื”ืงื‘ื•ืฆื”.
11:17
Nobody knew it was an actor.
241
677330
2000
ืืฃ ืื—ื“ ืœื ื™ื“ืข ืฉื”ื•ื ืฉื—ืงืŸ.
11:19
And they clearly cheated in a very, very serious way.
242
679330
4000
ื•ื”ื™ื” ื‘ืจื•ืจ ืฉื”ื•ื ืจื™ืžื” ื‘ื“ืจืš ืžืื•ื“ ืžืื•ื“ ื—ืžื•ืจื”.
11:23
What would happen to the other people in the group?
243
683330
3000
ืžื” ื™ืงืจื” ืœืฉืืจ ื—ื‘ืจื™ ื”ืงื‘ื•ืฆื”?
11:26
Will they cheat more, or will they cheat less?
244
686330
3000
ื”ืื ื™ืจืžื• ื™ื•ืชืจ ืื• ืฉืžื ืคื—ื•ืช?
11:29
Here is what happens.
245
689330
2000
ื”ื ื” ืžื” ืฉืงืจื”:
11:31
It turns out it depends on what kind of sweatshirt they're wearing.
246
691330
4000
ืžืกืชื‘ืจ ืฉื–ื” ืชืœื•ื™ ื‘ืื™ื–ื• ื—ื•ืœืฆื” ื”ื ืœื‘ืฉื•.
11:35
Here is the thing.
247
695330
2000
ื”ื ื” ื”ืงื˜ืข,
11:37
We ran this at Carnegie Mellon and Pittsburgh.
248
697330
3000
ื”ืขื‘ืจื ื• ืืช ื”ื ื™ืกื•ื™ ื‘ืงืจื ื’ื™-ืžืœื•ืŸ ื•ื‘ืคื™ื˜ืกื‘ื•ืจื’.
11:40
And at Pittsburgh there are two big universities,
249
700330
2000
ื‘ืคื™ื˜ืกื‘ื•ืจื’ ื™ืฉ ืฉืชื™ ืื•ื ื™ื‘ืจืกื™ื˜ืื•ืช ื’ื“ื•ืœื•ืช:
11:42
Carnegie Mellon and University of Pittsburgh.
250
702330
3000
ืงืจื ื’ื™-ืžืœื•ืŸ ื•ื”ืื•ื ื™ื‘ืจืกื™ื˜ื” ืฉืœ ืคื™ื˜ืกื‘ื•ืจื’.
11:45
All of the subjects sitting in the experiment
251
705330
2000
ื›ืœ ื”ืžืฉืชืชืคื™ื ื‘ื ื™ืกื•ื™
11:47
were Carnegie Mellon students.
252
707330
2000
ื”ื™ื• ืชืœืžื™ื“ื™ ืงืจื ื’ื™-ืžืœื•ืŸ
11:49
When the actor who was getting up was a Carnegie Mellon student --
253
709330
4000
ื•ื›ืืฉืจ ื”ืฉื—ืงืŸ ืืฉืจ ื ืขืžื“ ื”ื™ื” ื’ื ืชืœืžื™ื“ ืฉืœ ืงืจืžื’ื™-ืžืœื•ืŸ --
11:53
he was actually a Carnegie Mellon student --
254
713330
2000
ื”ื•ื ื‘ืืžืช ื”ื™ื” ืชืœืžื™ื“ ืฉืœ ืงืจื ื’ื™-ืžืœื•ืŸ --
11:55
but he was a part of their group, cheating went up.
255
715330
4000
ืื‘ืœ ื”ื•ื ื”ื™ื” ื—ืœืง ืžื”ืงื‘ื•ืฆื”, ื”ืจืžืื•ืช ืขืœืชื”.
11:59
But when he actually had a University of Pittsburgh sweatshirt,
256
719330
4000
ืื‘ืœ ื›ืืฉืจ ื”ื•ื ืœื‘ืฉ ื—ื•ืœืฆื” ืฉืœ ืื•ื ื™ื‘ืจืกื™ื˜ืช ืคื™ื˜ืกื‘ื•ืจื’
12:03
cheating went down.
257
723330
2000
ื”ืจืžืื•ืช ื™ืจื“ื”.
12:05
(Laughter)
258
725330
3000
(ืฆื—ื•ืง)
12:08
Now, this is important, because remember,
259
728330
3000
ืขื›ืฉื™ื•, ื–ื” ื—ืฉื•ื‘, ื›ื™ื•ื•ืŸ ืฉื™ืฉ ืœื–ื›ื•ืจ
12:11
when the moment the student stood up,
260
731330
2000
ืฉื‘ืจื’ืข ืฉื”ืกื˜ื•ื“ื ื˜ ื ืขืžื“
12:13
it made it clear to everybody that they could get away with cheating,
261
733330
3000
ื”ื™ื” ื‘ืจื•ืจ ืœื›ื•ืœื ืฉื”ื ื™ื›ื•ืœื™ื ืœื”ืชื—ืžืง ืขื ื”ืจืžืื•ืช,
12:16
because the experimenter said,
262
736330
2000
ื›ื™ื•ื•ืŸ ืฉื”ื ืกื™ื™ืŸ ืืžืจ:
12:18
"You've finished everything. Go home," and they went with the money.
263
738330
2000
"ืกื™ื™ืžืช ื”ื›ืœ. ืœืš ื”ื‘ื™ืชื”" ื•ื”ืฉื—ืงืŸ ื”ืœืš ืขื ื”ื›ืกืฃ.
12:20
So it wasn't so much about the probability of being caught again.
264
740330
3000
ืื– ื”ืขื ื™ื™ืŸ ืœื ื”ื™ื” ืžืžืฉ ื”ืกื™ื›ื•ืŸ ืœื”ื™ืชืคืก.
12:23
It was about the norms for cheating.
265
743330
3000
ื–ื” ื”ื™ื” ื™ื•ืชืจ ืขืœ ื”ื ื•ืจืžื•ืช ืฉืœ ืจืžืื•ืช.
12:26
If somebody from our in-group cheats and we see them cheating,
266
746330
3000
ืื ืžื™ืฉื”ื• ืžืชื•ืš ื”ืงื‘ื•ืฆื” ืฉืœื ื• ืžืจืžื” ื•ืื ื—ื ื• ืจื•ืื™ื ืื•ืชื• ืžืจืžื”
12:29
we feel it's more appropriate, as a group, to behave this way.
267
749330
4000
ืื ื—ื ื• ืžืจื’ื™ืฉื™ื ืฉื–ื” ื™ื•ืชืจ ืจืื•ื™, ื›ืงื‘ื•ืฆื”, ืœื”ืชื ื”ื’ ื›ืš.
12:33
But if it's somebody from another group, these terrible people --
268
753330
2000
ืื‘ืœ ืื ื–ื” ืžื™ืฉื”ื• ืžืงื‘ื•ืฆื” ืื—ืจืช, ืื•ืชื ืื ืฉื™ื ื ื•ืจืื™ื™ื --
12:35
I mean, not terrible in this --
269
755330
2000
ืื ื™ ืžืชื›ื•ื•ืŸ, ืœื ื ื•ืจืื™ื™ื ื‘ --
12:37
but somebody we don't want to associate ourselves with,
270
757330
2000
ืื‘ืœ ืื ืฉื™ื ืฉืื ื—ื ื• ืœื ืจื•ืฆื™ื ืœื”ื–ื“ื”ื•ืช ืื™ืชื
12:39
from another university, another group,
271
759330
2000
ืžืื•ื ื™ื‘ืจืกื™ื˜ื” ืื—ืจืช, ืงื‘ื•ืฆื” ืื—ืจืช,
12:41
all of a sudden people's awareness of honesty goes up --
272
761330
3000
ืœืคืชืข ืคืชืื•ื ื”ืžื•ื“ืขื•ืช ืฉืœ ื”ืื ืฉื™ื ืœื™ื•ืฉืจ ืขื•ืœื” --
12:44
a little bit like The Ten Commandments experiment --
273
764330
2000
ืงืฆืช ื›ืžื• ื”ื ื™ืกื•ื™ ืขื 10 ื”ื“ื™ื‘ืจื•ืช --
12:46
and people cheat even less.
274
766330
4000
ื•ื”ื ืžืจืžื™ื ืขื•ื“ ืคื—ื•ืช.
12:50
So, what have we learned from this about cheating?
275
770330
4000
ืื– ืžื” ืœืžื“ื ื• ืขืœ ืจืžืื•ืช ืžื›ืœ ื–ื”?
12:54
We've learned that a lot of people can cheat.
276
774330
3000
ืœืžื“ื ื• ืฉื”ืจื‘ื” ืื ืฉื™ื ื™ื›ื•ืœื™ื ืœืจืžื•ืช.
12:57
They cheat just by a little bit.
277
777330
3000
ื”ื ืžืจืžื™ื ืจืง ื‘ืžืขื˜.
13:00
When we remind people about their morality, they cheat less.
278
780330
4000
ื›ืฉืื ื—ื ื• ืžื–ื›ื™ืจื™ื ืœื”ื ืืช ื”ืžื•ืกืจ ืฉืœื”ื, ื”ื ืžืจืžื™ื ืคื—ื•ืช.
13:04
When we get bigger distance from cheating,
279
784330
3000
ื›ืฉืื ื—ื ื• ืžืชืจื—ืงื™ื ืžื”ืจืžืื•ืช,
13:07
from the object of money, for example, people cheat more.
280
787330
4000
ืžืื•ื‘ื™ื™ืงื˜ ื”ื›ืกืฃ, ืœืžืฉืœ, ื”ื ืžืจืžื™ื ื™ื•ืชืจ.
13:11
And when we see cheating around us,
281
791330
2000
ื•ื›ืฉืื ื—ื ื• ืจื•ืื™ื ืจืžืื•ืช ืžืกื‘ื™ื‘ื ื•,
13:13
particularly if it's a part of our in-group, cheating goes up.
282
793330
4000
ื‘ื™ื™ื—ื•ื“ ืื ื–ื” ืžืชื•ืš ื”ืงื‘ื•ืฆื” ืฉืœื ื•, ื”ืจืžืื•ืช ืขื•ืœื”.
13:17
Now, if we think about this in terms of the stock market,
283
797330
3000
ืขื›ืฉื™ื•, ืื ื ื—ืฉื•ื‘ ืขืœ ื–ื” ื‘ืžื•ื ื—ื™ื ืฉืœ ื”ื‘ื•ืจืกื”,
13:20
think about what happens.
284
800330
1000
ื—ืฉื‘ื• ืžื” ืงื•ืจื”.
13:21
What happens in a situation when you create something
285
801330
3000
ืžื” ืงื•ืจื” ื›ืฉื™ื•ืฆืจื™ื ืžืฉื”ื•,
13:24
where you pay people a lot of money
286
804330
2000
ื›ืฉืžืฉืœืžื™ื ืœืื ืฉื™ื ื”ืจื‘ื” ื›ืกืฃ
13:26
to see reality in a slightly distorted way?
287
806330
3000
ื›ื“ื™ ืœืจืื•ืช ืืช ื”ืžืฆื™ืื•ืช ื‘ืฆื•ืจื” ืžืขื˜ ืžืขื•ื•ืชืช.
13:29
Would they not be able to see it this way?
288
809330
3000
ื”ืื ื”ื ืœื ื™ืฆืœื™ื—ื• ืœืจืื•ืช ืืช ื”ืžืฆื™ืื•ืช ื›ืš?
13:32
Of course they would.
289
812330
1000
ื‘ื•ื•ื“ืื™ ืฉื™ืฆืœื™ื—ื•.
13:33
What happens when you do other things,
290
813330
1000
ืžื” ืงื•ืจื” ื›ืฉืขื•ืฉื™ื ื“ื‘ืจื™ื ืื—ืจื™ื,
13:34
like you remove things from money?
291
814330
2000
ื›ืฉืžืคืจื™ื“ื™ื ื“ื‘ืจื™ื ืžื›ืกืฃ?
13:36
You call them stock, or stock options, derivatives,
292
816330
3000
ืงื•ืจืื™ื ืœื–ื” ืžื ื™ื•ืช, ืื•ืคืฆื™ื•ืช, ื ื’ื–ืจื™ื,
13:39
mortgage-backed securities.
293
819330
1000
ื ื™ื™ืจื•ืช ืขืจืš ืžื’ื•ื‘ื™ ืžืฉื›ื ืชืื•ืช.
13:40
Could it be that with those more distant things,
294
820330
3000
ื”ื™ืชื›ืŸ ืฉืขื ื“ื‘ืจื™ื ื™ื•ืชืจ ืžืจื•ื—ืงื™ื ื›ืืœื”,
13:43
it's not a token for one second,
295
823330
2000
ืฉืื™ื ื ืืกื™ืžื•ืŸ ืœืฉื ื™ื™ื” ืื—ืช,
13:45
it's something that is many steps removed from money
296
825330
2000
ืืœื ื“ื‘ืจ ืฉืžืจื•ื—ืง ืฆืขื“ื™ื ืจื‘ื™ื ืžื›ืกืฃ
13:47
for a much longer time -- could it be that people will cheat even more?
297
827330
4000
ืœืžืฉืš ื–ืžืŸ ืืจื•ืš ื”ืจื‘ื” ื™ื•ืชืจ -- ื”ื™ื™ืชื›ืŸ ืฉืื ืฉื™ื ื™ืจืžื• ืืคื™ืœื• ื™ื•ืชืจ?
13:51
And what happens to the social environment
298
831330
2000
ื•ืžื” ืงื•ืจื” ืœืกื‘ื™ื‘ื” ื”ื—ื‘ืจืชื™ืช
13:53
when people see other people behave around them?
299
833330
3000
ื›ืฉืื ืฉื™ื ืจื•ืื™ื ืื—ืจื™ื ืžืชื ื”ื’ื™ื ื›ืš ืกื‘ื™ื‘ื?
13:56
I think all of those forces worked in a very bad way
300
836330
4000
ืื ื™ ื—ื•ืฉื‘ ืฉื›ืœ ื”ื›ื•ื—ื•ืช ื”ืืœื” ืคื•ืขืœื™ื ื‘ืฆื•ืจื” ืจืขื”
14:00
in the stock market.
301
840330
2000
ื‘ื‘ื•ืจืกื”.
14:02
More generally, I want to tell you something
302
842330
3000
ื•ื‘ืื•ืคืŸ ื›ืœืœื™, ืื ื™ ืจื•ืฆื” ืœื”ื’ื™ื“ ืœื›ื ืžืฉื”ื•
14:05
about behavioral economics.
303
845330
3000
ืขืœ ื›ืœื›ืœื” ื”ืชื ื”ื’ื•ืชื™ืช.
14:08
We have many intuitions in our life,
304
848330
4000
ื™ืฉ ื‘ื—ื™ื™ื ื• ื”ืจื‘ื” ืื™ื ื˜ื•ืื™ืฆื™ื•ืช,
14:12
and the point is that many of these intuitions are wrong.
305
852330
3000
ื•ื”ื ืงื•ื“ื” ื”ื™ื ืฉื”ืจื‘ื” ืžื”ืื™ื ื˜ื•ืื™ืฆื™ื•ืช ื”ืœืœื• ืฉื’ื•ื™ื•ืช.
14:15
The question is, are we going to test those intuitions?
306
855330
3000
ื”ืฉืืœื” ื”ื™ื, ื”ืื ื ื‘ื—ืŸ ืืช ื”ืื™ื ื˜ื•ืื™ืฆื™ื•ืช ื”ืืœื”?
14:18
We can think about how we're going to test this intuition
307
858330
2000
ืื ื—ื ื• ื™ื›ื•ืœื™ื ืœื—ืฉื•ื‘ ืื™ืš ืœื‘ื—ื•ืŸ ืืช ื”ืื™ื ื˜ื•ืื™ืฆื™ื•ืช ื”ืืœื”
14:20
in our private life, in our business life,
308
860330
2000
ื‘ื—ื™ื™ื ื• ื”ืคืจื˜ื™ื™ื, ื‘ื—ื™ื™ื ื• ื”ืขืกืงื™ื™ื,
14:22
and most particularly when it goes to policy,
309
862330
3000
ื•ื‘ื™ื™ื—ื•ื“ ื›ืฉื–ื” ื ื•ื’ืข ืœื ื•ืฉืื™ ืžื“ื™ื ื™ื•ืช,
14:25
when we think about things like No Child Left Behind,
310
865330
3000
ื›ืฉืื ื—ื ื• ื—ื•ืฉื‘ื™ื ืขืœ ื“ื‘ืจื™ื ื›ืžื• "ืœื ืžืฉืื™ืจื™ื ืืฃ ื™ืœื“ ืžืื—ื•ืจ,"
14:28
when you create new stock markets, when you create other policies --
311
868330
3000
ื›ืฉื™ื•ืฆืจื™ื ืฉื•ื•ืงื™ ืžื ื™ื•ืช ื—ื“ืฉื™ื, ื™ื•ืฆืจื™ื ืžื“ื™ื ื™ื•ืช ื—ื“ืฉื” --
14:31
taxation, health care and so on.
312
871330
3000
ืžื™ืกื•ื™, ื‘ื™ื˜ื•ื— ื‘ืจื™ืื•ืช ื•ืขื•ื“.
14:34
And the difficulty of testing our intuition
313
874330
2000
ื•ื”ืงื•ืฉื™ ืฉื‘ื‘ื—ื™ื ืช ื”ืื™ื ื˜ื•ืื™ืฆื™ื” ืฉืœื ื•
14:36
was the big lesson I learned
314
876330
2000
ื”ื™ื” ื”ืฉื™ืขื•ืจ ืฉืœืžื“ืชื™
14:38
when I went back to the nurses to talk to them.
315
878330
2000
ื›ืฉื—ื–ืจืชื™ ืœื“ื‘ืจ ืขื ื”ืื—ื™ื•ืช.
14:40
So I went back to talk to them
316
880330
2000
ืื– ื—ื–ืจืชื™ ืœื“ื‘ืจ ืื™ืชืŸ,
14:42
and tell them what I found out about removing bandages.
317
882330
3000
ื•ืœืกืคืจ ืœื”ืŸ ืžื” ืฉื’ื™ืœื™ืชื™ ืœื’ื‘ื™ ื”ืกืจืช ื”ืชื—ื‘ื•ืฉื•ืช.
14:45
And I learned two interesting things.
318
885330
2000
ื•ืœืžื“ืชื™ ืฉื ื™ ื“ื‘ืจื™ื ืžืขื ื™ื™ื ื™ื,
14:47
One was that my favorite nurse, Ettie,
319
887330
2000
ืื—ื“ ื”ื™ื”, ืฉื”ืื—ื•ืช ื”ื—ื‘ื™ื‘ื” ืขืœื™ ื‘ื™ื•ืชืจ, ืืชื™,
14:49
told me that I did not take her pain into consideration.
320
889330
4000
ืืžืจื” ืœื™ ืฉืœื ื”ื—ืฉื‘ืชื™ ืืช ื”ื›ืื‘ ืฉืœื” ื‘ืฉื™ืงื•ืœื™.
14:53
She said, "Of course, you know, it was very painful for you.
321
893330
2000
ื”ื™ื ืืžืจื”: "ื›ืžื•ื‘ืŸ, ืืชื” ื™ื•ื“ืข, ื–ื” ื”ื™ื” ืžืื•ื“ ื›ื•ืื‘ ืขื‘ื•ืจืš.
14:55
But think about me as a nurse,
322
895330
2000
ืื‘ืœ ื—ืฉื•ื‘ ืขืœื™ ื›ืื—ื•ืช,
14:57
taking, removing the bandages of somebody I liked,
323
897330
2000
ืœื”ืœื‘ื™ืฉ ื•ืœื”ื•ืจื™ื“ ืชื—ื‘ื•ืฉื•ืช ืžืžื™ืฉื”ื• ืฉื—ื™ื‘ื‘ืชื™,
14:59
and had to do it repeatedly over a long period of time.
324
899330
3000
ื•ื”ื™ื™ืชื™ ืฆืจื™ื›ื” ืœืขืฉื•ืช ื–ืืช ืฉื•ื‘ ื•ืฉื•ื‘ ืœืื•ืจืš ื–ืžืŸ ืจื‘.
15:02
Creating so much torture was not something that was good for me, too."
325
902330
3000
ื™ืฆื™ืจืช ืกื‘ืœ ื›ื” ืจื‘ ื”ื™ื ืžืฉื”ื• ืฉืงืฉื” ื’ื ืœื™."
15:05
And she said maybe part of the reason was it was difficult for her.
326
905330
5000
ื•ื”ื™ื ืืžืจื”, ืื•ืœื™ ื–ื” ื—ืœืง ืžื”ืกื™ื‘ื” ืฉื‘ื’ืœืœื” ื–ื” ื”ื™ื” ืงืฉื” ืขื‘ื•ืจื”
15:10
But it was actually more interesting than that, because she said,
327
910330
3000
ืื‘ืœ ื–ื” ื”ื™ื” ื™ื•ืชืจ ืžืขื ื™ื™ืŸ ืžื–ื”, ื›ื™ ื”ื™ื ืืžืจื”:
15:13
"I did not think that your intuition was right.
328
913330
5000
"ืื ื™ ืœื ื—ืฉื‘ืชื™ ืฉื”ืื™ื ื˜ื•ืื™ืฆื™ื” ืฉืœืš ื”ื™ืชื” ื ื›ื•ื ื”.
15:18
I felt my intuition was correct."
329
918330
1000
ืื ื™ ื”ืจื’ืฉืชื™ ืฉื”ืื™ื ื˜ื•ืื™ืฆื™ื” ืฉืœื™ ื ื›ื•ื ื”."
15:19
So, if you think about all of your intuitions,
330
919330
2000
ืื– ืื ืชื—ืฉื‘ื• ืขืœ ื›ืœ ื”ืื™ื ื˜ื•ืื™ืฆื™ื•ืช ืฉื™ืฉ ืœื›ื,
15:21
it's very hard to believe that your intuition is wrong.
331
921330
4000
ื–ื” ืžืื•ื“ ืงืฉื” ืœื—ืฉื•ื‘ ืฉื”ืื™ื ื˜ื•ืื™ืฆื™ื” ืฉืœื›ื ืฉื’ื•ื™ื”.
15:25
And she said, "Given the fact that I thought my intuition was right ..." --
332
925330
3000
ื•ื”ื™ื ืืžืจื”: "ื‘ื”ืชื—ืฉื‘ ื‘ืขื•ื‘ื“ื” ืฉื—ืฉื‘ืชื™ ืฉื”ืื™ื ื˜ื•ืื™ืฆื™ื” ืฉืœื™ ื ื›ื•ื ื”" --
15:28
she thought her intuition was right --
333
928330
2000
ื”ื™ื ื—ืฉื‘ื” ืฉื”ืื™ื ื˜ื•ืื™ืฆื™ื” ืฉืœื” ื ื›ื•ื ื” --
15:30
it was very difficult for her to accept doing a difficult experiment
334
930330
5000
ื”ื™ื” ืœื” ืžืื•ื“ ืงืฉื” ืœืงื‘ืœ ืืช ื”ืฆื•ืจืš ืœืขืจื•ืš ื ื™ืกื•ื™ ืงืฉื”
15:35
to try and check whether she was wrong.
335
935330
2000
ืฉื™ื‘ื“ื•ืง ืื ื”ื™ื ื˜ื•ืขื”.
15:37
But in fact, this is the situation we're all in all the time.
336
937330
4000
ืื‘ืœ ืœืžืขืฉื”, ื–ื” ื”ืžืฆื‘ ืฉื‘ื• ืื ื—ื ื• ื ืžืฆืื™ื ื›ืœ ื”ื–ืžืŸ.
15:41
We have very strong intuitions about all kinds of things --
337
941330
3000
ื™ืฉ ืœื ื• ืื™ื ื˜ื•ืื™ืฆื™ื•ืช ื—ื–ืงื•ืช ืœื’ื‘ื™ ื›ืœ ืžื™ื ื™ ื“ื‘ืจื™ื --
15:44
our own ability, how the economy works,
338
944330
3000
ื”ื™ื›ื•ืœื•ืช ืฉืœื ื•, ืื™ืš ืฉื”ื›ืœื›ืœื” ืขื•ื‘ื“ืช,
15:47
how we should pay school teachers.
339
947330
2000
ื›ืžื” ืฆืจื™ืš ืœืฉืœื ืœืžื•ืจื™ื ื‘ื‘ืชื™ ื”ืกืคืจ.
15:49
But unless we start testing those intuitions,
340
949330
3000
ืื‘ืœ ืื ืœื ื ืชื—ื™ืœ ืœื‘ื“ื•ืง ืืช ื”ืื™ื ื˜ื•ืื™ืฆื™ื•ืช ื”ืืœื”
15:52
we're not going to do better.
341
952330
2000
ืื ื—ื ื• ืœื ื ืฉืชืคืจ.
15:54
And just think about how better my life would have been
342
954330
2000
ื•ืชื—ืฉื‘ื• ื›ืžื” ื—ื™ื™ ื”ื™ื• ื™ื›ื•ืœื™ื ืœื”ื™ื•ืช ื™ื•ืชืจ ื˜ื•ื‘ื™ื
15:56
if these nurses would have been willing to check their intuition,
343
956330
2000
ืื ืื•ืชืŸ ืื—ื™ื•ืช ื”ื™ื• ืžื•ื›ื ื•ืช ืœื‘ื“ื•ืง ืืช ื”ืื™ื ื˜ื•ืื™ืฆื™ื•ืช ืฉืœื”ืŸ
15:58
and how everything would have been better
344
958330
1000
ื•ืื™ืš ื”ื›ืœ ื”ื™ื” ื™ื•ืชืจ ื˜ื•ื‘
15:59
if we just start doing more systematic experimentation of our intuitions.
345
959330
5000
ืื ืจืง ื”ื™ื™ื ื• ืขื•ืฉื™ื ื™ื•ืชืจ ื‘ื“ื™ืงื•ืช ืฉื™ื˜ืชื™ื•ืช ืฉืœ ื”ืื™ื ื˜ื•ืื™ืฆื™ื•ืช ืฉืœื ื•
16:04
Thank you very much.
346
964330
2000
ืชื•ื“ื” ืจื‘ื”.
ืขืœ ืืชืจ ื–ื”

ืืชืจ ื–ื” ื™ืฆื™ื’ ื‘ืคื ื™ื›ื ืกืจื˜ื•ื ื™ YouTube ื”ืžื•ืขื™ืœื™ื ืœืœื™ืžื•ื“ ืื ื’ืœื™ืช. ืชื•ื›ืœื• ืœืจืื•ืช ืฉื™ืขื•ืจื™ ืื ื’ืœื™ืช ื”ืžื•ืขื‘ืจื™ื ืขืœ ื™ื“ื™ ืžื•ืจื™ื ืžื”ืฉื•ืจื” ื”ืจืืฉื•ื ื” ืžืจื—ื‘ื™ ื”ืขื•ืœื. ืœื—ืฅ ืคืขืžื™ื™ื ืขืœ ื”ื›ืชื•ื‘ื™ื•ืช ื‘ืื ื’ืœื™ืช ื”ืžื•ืฆื’ื•ืช ื‘ื›ืœ ื“ืฃ ื•ื™ื“ืื• ื›ื“ื™ ืœื”ืคืขื™ืœ ืืช ื”ืกืจื˜ื•ืŸ ืžืฉื. ื”ื›ืชื•ื‘ื™ื•ืช ื’ื•ืœืœื•ืช ื‘ืกื ื›ืจื•ืŸ ืขื ื”ืคืขืœืช ื”ื•ื•ื™ื“ืื•. ืื ื™ืฉ ืœืš ื”ืขืจื•ืช ืื• ื‘ืงืฉื•ืช, ืื ื ืฆื•ืจ ืื™ืชื ื• ืงืฉืจ ื‘ืืžืฆืขื•ืช ื˜ื•ืคืก ื™ืฆื™ืจืช ืงืฉืจ ื–ื”.

https://forms.gle/WvT1wiN1qDtmnspy7