Andrew McAfee: Are droids taking our jobs?

162,453 views ใƒป 2012-09-24

TED


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

00:00
Translator: Joseph Geni Reviewer: Morton Bast
0
0
7000
ืžืชืจื’ื: Yael BST ืžื‘ืงืจ: Ido Dekkers
00:15
As it turns out, when tens of millions of people are unemployed
1
15648
3580
ื›ืคื™ ืฉืžืกืชื‘ืจ, ื›ืืฉืจ ืขืฉืจื•ืช ืžื™ืœื™ื•ื ื™ ืื ืฉื™ื
ืžื•ื‘ื˜ืœื™ื ืื• ืžื•ืขืกืงื™ื ื—ืœืงื™ืช ื‘ืœื‘ื“,
00:19
or underemployed,
2
19252
1534
00:20
there's a fair amount of interest in what technology might be doing
3
20810
3166
ื™ืฉ ืขื ื™ื™ืŸ ืœื ืžื‘ื•ื˜ืœ ื‘ืฉืืœื” ื‘ืื™ื–ื” ืื•ืคืŸ ื”ื˜ื›ื ื•ืœื•ื’ื™ื” ืžืฉืคื™ืขื” ืื•ืœื™ ืขืœ ื›ื•ื— ื”ืขื‘ื•ื“ื”.
00:24
to the labor force.
4
24000
1162
ื•ื›ืฉืื ื™ ื‘ื•ื—ืŸ ืืช ื”ื“ื™ื•ืŸ ื”ื–ื”,
00:25
And as I look at the conversation,
5
25186
1889
00:27
it strikes me that it's focused on exactly the right topic,
6
27099
3680
ืื ื™ ืžื‘ื™ืŸ ืฉื”ื•ื ืžืชืžืงื“ ื‘ื ื•ืฉื ื”ื ื›ื•ืŸ,
00:30
and at the same time, it's missing the point entirely.
7
30803
2825
ื•ื™ื—ื“ ืขื ื–ืืช, ื”ื•ื ืœื’ืžืจื™ ืžืคืกืคืก ืืช ื”ืขื™ืงืจ.
00:33
The topic that it's focused on,
8
33652
1541
ื”ื ื•ืฉื ืฉื”ื“ื™ื•ืŸ ืžืชืžืงื“ ื‘ื•, ื”ืฉืืœื” ื”ื™ื
00:35
the question is whether or not all these digital technologies are affecting
9
35217
4483
ื”ืื ื›ืœ ื”ื˜ื›ื ื•ืœื•ื’ื™ื•ืช ื”ื“ื™ื’ื™ื˜ืœื™ื•ืช ื”ืืœื• ืžืฉืคื™ืขื•ืช ืขืœ ื™ื›ื•ืœืชื ืฉืœ ืื ืฉื™ื
00:39
people's ability to earn a living,
10
39724
2017
ืœื”ืชืคืจื ืก ืœืžื—ื™ื™ืชื, ืื• ืื ืœื•ืžืจ ืืช ื–ื” ืžืขื˜ ืื—ืจืช,
00:41
or, to say it a little bit different way,
11
41765
1985
00:43
are the droids taking our jobs?
12
43774
2089
ื”ืื ื”ื“ืจื•ืื™ื“ื™ื ืœื•ืงื—ื™ื ืœื ื• ืืช ื”ืขื‘ื•ื“ื•ืช?
00:45
And there's some evidence that they are.
13
45887
1937
ื•ื™ืฉ ื›ืžื” ืจืื™ื•ืช ืฉื–ื” ืื›ืŸ ื›ืš.
00:47
The Great Recession ended when American GDP resumed
14
47848
4045
"ื”ืžื™ืชื•ืŸ ื”ื’ื“ื•ืœ" ื”ืกืชื™ื™ื ื›ืืฉืจ ื”ืชืž"ื’ ื”ืืžืจื™ืงืื™ ื—ื–ืจ
00:51
its kind of slow, steady march upward,
15
51917
2867
ืœืžื’ืžืช ื”ื˜ื™ืคื•ืก ื”ืื™ื˜ื™ ื•ื”ื™ืฆื™ื‘ ื›ืœืคื™ ืžืขืœื”, ื•ื›ืžื”
00:54
and some other economic indicators also started to rebound,
16
54808
3270
ืื™ื ื“ื™ืงื˜ื•ืจื™ื ื›ืœื›ืœื™ื™ื ืื—ืจื™ื ื”ืชื—ื™ืœื• ื’ื ื‘ื”ืชืื•ืฉืฉื•ืช,
00:58
and they got kind of healthy kind of quickly.
17
58102
2293
ื•ื”ื ืคื—ื•ืช ืื• ื™ื•ืชืจ ื”ื‘ืจื™ืื• ื“ื™ ืžื”ืจ. ืจื•ื•ื—ื™ ื”ืชืื’ื™ื“ื™ื
01:00
Corporate profits are quite high;
18
60419
2167
ื“ื™ ื’ื‘ื•ื”ื™ื. ืœืžืขืฉื”, ืื ื›ื•ืœืœื™ื ื’ื ืืช ืจื•ื•ื—ื™ ื”ื‘ื ืงื™ื,
01:02
in fact, if you include bank profits,
19
62610
1896
01:04
they're higher than they've ever been.
20
64530
1991
ื”ื ื’ื‘ื•ื”ื™ื ืžืฉื”ื™ื• ืื™ ืคืขื.
01:06
And business investment in gear -- in equipment
21
66545
3487
ื•ื”ืฉืงืขื•ืช ื”ืขืกืงื™ื ื‘ืฆื™ื•ื“, ื‘ื›ืœื™ื
ื‘ื—ื•ืžืจื” ื•ื‘ืชื•ื›ื ื” - ื ืžืฆื ื‘ืฉื™ื ืฉืœ ื›ืœ ื”ื–ืžื ื™ื.
01:10
and hardware and software -- is at an all-time high.
22
70056
2844
01:12
So the businesses are getting out their checkbooks.
23
72924
3315
ืื– ื”ืขืกืงื™ื ื›ืŸ ืฉื•ืœืคื™ื ืคื ืงืกื™ ืฆ'ืงื™ื.
01:16
What they're not really doing is hiring.
24
76263
1999
ืžื” ืฉื”ื ืœื ืžืžืฉ ืขื•ืฉื™ื ื–ื” ืœื’ื™ื™ืก ืขื•ื‘ื“ื™ื.
01:18
So this red line
25
78661
1151
ืื– ื”ืงื• ื”ืื“ื•ื ื”ื–ื” ื”ื•ื ื™ื—ืก ืชืขืกื•ืงื”-ืื•ื›ืœื•ืกื™ื™ื”,
01:19
is the employment-to-population ratio,
26
79836
2538
01:22
in other words, the percentage of working-age people in America
27
82398
4129
ื‘ืžื™ืœื™ื ืื—ืจื•ืช, ืื—ื•ื– ื”ืื ืฉื™ื ื‘ื’ื™ืœืื™ ื”ืขื‘ื•ื“ื” ื‘ืืžืจื™ืงื”
ืฉื™ืฉ ืœื”ื ืขื‘ื•ื“ื”.
01:26
who have work.
28
86551
1386
01:27
And we see that it cratered during the Great Recession,
29
87961
3106
ื•ืื ื—ื ื• ืจื•ืื™ื ืืช ื”ืงื™ืžื•ืจ ืฉื ื•ืฆืจ ื‘"ืžื™ืชื•ืŸ ื”ื’ื“ื•ืœ",
01:31
and it hasn't started to bounce back at all.
30
91091
2897
ื•ื”ื•ื ืœื ื”ืชื—ื™ืœ ืœื—ื–ื•ืจ ืœืขืฆืžื• ื‘ื›ืœืœ.
01:34
But the story is not just a recession story.
31
94012
2919
ืื‘ืœ ื”ืกื™ืคื•ืจ ื”ื•ื ืœื ืจืง ืกื™ืคื•ืจ ืฉืœ ืžื™ืชื•ืŸ.
01:36
The decade that we've just been through had
32
96955
2080
ื‘ืขืฉื•ืจ ืฉื—ื•ื•ื™ื ื• ืขื›ืฉื™ื•, ื”ื™ื” ื‘ืื•ืคืŸ ื™ื—ืกื™
01:39
relatively anemic job growth all throughout,
33
99059
3213
ื’ื™ื“ื•ืœ ื“ื™ ืื ืžื™ ื‘ืชืขืกื•ืงื” ืœื›ืœ ืื•ืจื›ื•, ื‘ืžื™ื•ื—ื“ ื›ืืฉืจ
01:42
especially when we compare it to other decades,
34
102296
2623
ืžืฉื•ื•ื™ื ืื•ืชื• ืœืขืฉื•ืจื™ื ืื—ืจื™ื, ื•ืฉื ื•ืช ื”- 2000,
01:44
and the 2000s are the only time we have on record
35
104943
3030
ื”ื ื”ืคืขื ื”ื™ื—ื™ื“ื” ื”ืžืชื•ืขื“ืช ืฉื‘ื” ื”ื™ื•
01:47
where there were fewer people working at the end of the decade
36
107997
3532
ืคื—ื•ืช ืื ืฉื™ื ืฉืขื‘ื“ื• ื‘ืกื•ืฃ ื”ืขืฉื•ืจ
01:51
than at the beginning.
37
111553
1402
ืžืืฉืจ ื‘ืชื—ื™ืœืชื•. ื–ื” ืœื ืžื” ืฉืื ื—ื ื• ืจื•ืฆื™ื ืœืจืื•ืช.
01:52
This is not what you want to see.
38
112979
1673
01:54
When you graph the number of potential employees
39
114984
3383
ื›ืฉืฉืžื™ื ืขืœ ื’ืจืฃ ืืช ืžืกืคืจ ื”ืขื•ื‘ื“ื™ื ื”ืคื•ื˜ื ืฆื™ืืœื™ื™ื
01:58
versus the number of jobs in the country,
40
118391
2556
ืœืขื•ืžืช ืžืกืคืจ ืžืงื•ืžื•ืช ื”ืขื‘ื•ื“ื” ื‘ืžื“ื™ื ื”, ืจื•ืื™ื ืืช ื”ืคืขืจ ื”ื–ื”
02:00
you see the gap gets bigger and bigger over time,
41
120971
3850
ืฉื’ื“ืœ ื•ื’ื“ืœ ื‘ืžืฉืš ื”ื–ืžืŸ, ื•ืื–,
02:04
and then, during the Great Recession, it opened up in a huge way.
42
124845
3310
ื‘ืžื”ืœืš ื”"ืžื™ืชื•ืŸ ื”ื’ื“ื•ืœ", ื”ื•ื ืžืžืฉ ื ืคืขืจ ื‘ืฆื•ืจื” ืื“ื™ืจื”.
ืขืฉื™ืชื™ ื›ืžื” ื—ื™ืฉื•ื‘ื™ื ืžื”ื™ืจื™ื. ืœืงื—ืชื™ ืืช ื’ื™ื“ื•ืœ ื”ืชืž"ื’ ื‘-20 ื”ืฉื ื™ื ื”ืื—ืจื•ื ื•ืช
02:08
I did some quick calculations.
43
128179
1460
02:09
I took the last 20 years of GDP growth
44
129663
2432
02:12
and the last 20 years of labor-productivity growth
45
132119
3272
ื•ืืช ื”ืฆืžื™ื—ื” ื‘ืคืจื™ื•ืŸ ื”ืขื‘ื•ื“ื” ื‘-20 ื”ืฉื ื™ื ื”ืื—ืจื•ื ื•ืช
02:15
and used those in a fairly straightforward way
46
135415
2718
ื•ื”ืฉืชืžืฉืชื™ ื‘ื ืชื•ื ื™ื ื”ืืœื• ื‘ืฆื•ืจื” ื“ื™ ืคืฉื•ื˜ื”
02:18
to try to project how many jobs the economy was going to need
47
138157
3023
ื›ื“ื™ ืœื ืกื•ืช ืœื”ืฉืœื™ืš ืžื›ืš ื›ืžื” ืžืงื•ืžื•ืช ืขื‘ื•ื“ื” ื”ื›ืœื›ืœื”
ืชืฆื˜ืจืš ื›ื“ื™ ืœื”ืžืฉื™ืš ื‘ืฆืžื™ื—ื”, ื•ื–ื” ื”ืงื• ืฉืงื™ื‘ืœืชื™.
02:21
to keep growing,
48
141204
1303
02:22
and this is the line that I came up with.
49
142531
2125
02:24
Is that good or bad?
50
144680
1742
ื”ืื ื–ื” ื˜ื•ื‘ ืื• ืจืข? ื–ื•ื”ื™ ื”ืชื—ื–ื™ืช ืฉืœ ื”ืžืžืฉืœ
02:26
This is the government's projection
51
146446
1911
ืœืฉื™ืขื•ืจ ื”ืื•ื›ืœื•ืกื™ื™ื” ื‘ื’ื™ืœืื™ ื”ืขื‘ื•ื“ื” ื‘ืขืชื™ื“.
02:28
for the working-age population going forward.
52
148381
3336
02:31
So if these predictions are accurate, that gap is not going to close.
53
151741
5098
ืื– ืื ื”ืชื—ื–ื™ื•ืช ื”ืืœื• ืžื“ื•ื™ืงื•ืช, ื”ืคืขืจ ื”ื–ื” ืœื ืขื•ืžื“ ืœื”ื™ืกื’ืจ.
02:36
The problem is, I don't think these projections are accurate.
54
156863
3026
ื”ื‘ืขื™ื” ื”ื™ื, ืฉืื ื™ ืœื ื—ื•ืฉื‘ ืฉื”ืชื—ื–ื™ื•ืช ื”ืืœื• ืžื“ื•ื™ืงื•ืช
02:39
In particular, I think my projection is way too optimistic,
55
159913
3479
ื•ื‘ืžื™ื•ื—ื“, ืื ื™ ื—ื•ืฉื‘ ืฉื”ืชื—ื–ื™ืช ืฉืœื™ ื™ื•ืชืจ ืžื“ื™ ืื•ืคื˜ื™ืžื™ืช,
02:43
because when I did it,
56
163416
1447
ื›ื™ ื›ืฉืขืฉื™ืชื™ ืืช ื–ื”, ื”ื ื—ืชื™ ืฉื”ืขืชื™ื“
02:44
I was assuming that the future was kind of going to look like the past,
57
164887
4218
ื”ื•ืœืš ืœื”ื™ืจืื•ืช ื‘ืขืจืš ื›ืžื• ื”ืขื‘ืจ
02:49
with labor productivity growth,
58
169129
1669
ืขื ื”ืฆืžื™ื—ื” ื‘ืคืจื™ื•ืŸ ื”ืขื‘ื•ื“ื”, ื•ืื ื™ ืœืžืขืฉื” ืœื ืžืืžื™ืŸ ื‘ื–ื”,
02:50
and that's actually not what I believe.
59
170822
1871
02:52
Because when I look around,
60
172717
1349
ื›ื™ ื›ืฉืื ื™ ืžืกืชื›ืœ ืกื‘ื™ื‘ื™, ืื ื™ ื—ื•ืฉื‘ ืฉืขื•ื“ ืœื ืจืื™ื ื• ื›ืœื•ื
02:54
I think that we ain't seen nothing yet
61
174090
2220
02:56
when it comes to technology's impact on the labor force.
62
176334
3236
ื‘ื›ืœ ืžื” ืฉื ื•ื’ืข ืœื”ืฉืคืขืช ื”ื˜ื›ื ื•ืœื•ื’ื™ื” ืขืœ ื›ื•ื— ื”ืขื‘ื•ื“ื”.
02:59
Just in the past couple years, we've seen digital tools
63
179962
3971
ืจืง ื‘ืฉื ืชื™ื™ื ื”ืื—ืจื•ื ื•ืช, ืจืื™ื ื• ื›ืœื™ื ื“ื™ื’ื™ื˜ืœื™ื™ื
03:03
display skills and abilities that they never, ever had before,
64
183957
4233
ืฉืžืฆื™ื’ื™ื ื™ื›ื•ืœื•ืช ื•ื›ื™ืฉื•ืจื™ื ืฉืžืขื•ืœื, ืืฃ ืคืขื ืœื ื”ื™ื• ืœื”ื,
ื•ื”ื ื›ืื™ืœื• ื ื•ื’ืกื™ื ืขืžื•ืง ื‘ืžื” ืฉืื ื—ื ื• ื›ื‘ื ื™ ืื“ื
03:08
and that kind of eat deeply into what we human beings
65
188214
3510
03:11
do for a living.
66
191748
1282
ืขื•ืฉื™ื ืœืžื—ื™ื™ืชื ื•. ื”ืจืฉื• ืœื™ ืœืชืช ืœื›ื ื›ืžื” ื“ื•ื’ืžืื•ืช.
03:13
Let me give you a couple examples.
67
193054
1926
03:15
Throughout all of history,
68
195004
1252
ืœืื•ืจืš ื›ืœ ื”ื”ื™ืกื˜ื•ืจื™ื”, ืื ืจืฆื™ืชื ืฉืžืฉื”ื•
03:16
if you wanted something translated from one language into another,
69
196280
3550
ื™ืชื•ืจื’ื ืžืฉืคื” ืื—ืช ืœืฉืคื” ืื—ืจืช,
03:19
you had to involve a human being.
70
199854
1725
ื”ื™ื™ืชื ื—ื™ื™ื‘ื™ื ืœืขืจื‘ ื‘ืŸ ืื“ื.
03:21
Now we have multi-language, instantaneous,
71
201930
3128
ื”ื™ื•ื ื™ืฉ ืœื ื• ืฉื™ืจื•ืชื™ ืชืจื’ื•ื ืžืจื•ื‘ื™ ืฉืคื•ืช,
03:25
automatic translation services available for free
72
205082
4420
ืžื™ื™ื“ื™ื™ื ื•ืื•ื˜ื•ืžื˜ื™ื™ื ืฉื–ืžื™ื ื™ื ืœื ื• ื‘ื—ื™ื ื
03:29
via many of our devices, all the way down to smartphones.
73
209526
3143
ื“ืจืš ื”ืจื‘ื” ืžื”ืžื›ืฉื™ืจื™ื ืฉืœื ื•, ืืคื™ืœื• ืขื“ ื”ืกืžืืจื˜ืคื•ืŸ.
03:32
And if any of us have used these,
74
212693
1796
ื•ืื ืžื™ืฉื”ื• ืžืื™ืชื ื• ื”ืฉืชืžืฉ ื‘ื”ื, ื”ื•ื ื™ื•ื“ืข
03:34
we know that they're not perfect, but they're decent.
75
214513
3515
ืฉื”ื ืื•ืžื ื ืœื ืžื•ืฉืœืžื™ื, ืื‘ืœ ื”ื ืกื‘ื™ืจื™ื.
03:38
Throughout all of history, if you wanted something written,
76
218540
2972
ืœืื•ืจืš ื›ืœ ื”ื”ื™ืกื˜ื•ืจื™ื”, ืื ืจืฆื™ืชื ืžืฉื”ื• ื›ืชื•ื‘,
03:41
a report or an article, you had to involve a person.
77
221536
3337
ื“ื•"ื— ืื• ืžืืžืจ, ื”ื™ื™ืชื ื—ื™ื™ื‘ื™ื ืœืขืจื‘ ื‘ืŸ ืื“ื.
ื”ื™ื•ื ื›ื‘ืจ ืœื. ื–ื” ืžืืžืจ ืฉื”ื•ืคื™ืข
03:45
Not anymore.
78
225418
1153
03:46
This is an article that appeared in Forbes online a while back,
79
226595
2973
ื‘ืžื’ื–ื™ืŸ "ืคื•ืจื‘ืก ืื•ืŸ ืœื™ื™ืŸ" ืœื ืžื–ืžืŸ, ืขืœ ืจื•ื•ื—ื™ื” ืฉืœ ืืคืœ.
03:49
about Apple's earnings.
80
229592
1176
03:50
It was written by an algorithm.
81
230792
1618
ื”ื•ื ื ื›ืชื‘ ืข"ื™ ืืœื’ื•ืจื™ืชื.
03:52
And it's not decent -- it's perfect.
82
232980
2857
ื•ื”ื•ื ืœื ืกื‘ื™ืจ, ื”ื•ื ืžื•ืฉืœื.
ื”ืจื‘ื” ืื ืฉื™ื ืžืกืชื›ืœื™ื ืขืœ ื–ื” ื•ืื•ืžืจื™ื, "ืื•.ืงื™ื™.,
03:57
A lot of people look at this and they say,
83
237009
2029
03:59
"OK, but those are very specific, narrow tasks,
84
239062
2305
ืื‘ืœ ืืœื• ื”ืŸ ืžืฉื™ืžื•ืช ืžืื•ื“ ืกืคืฆื™ืคื™ื•ืช, ืฆืจื•ืช,
04:01
and most knowledge workers are actually generalists.
85
241391
2911
ื•ืจื•ื‘ ืขื•ื‘ื“ื™ ื”ื™ื“ืข ื”ื ืœืžืขืฉื” ืขื•ื‘ื“ื™ื ื›ืœืœื™ื™ื,
04:04
And what they do is sit on top of a very large body of expertise and knowledge
86
244326
4192
ื•ื”ืขื‘ื•ื“ื” ืฉืœื”ื ืžืชื‘ืกืกืช ืขืœ ื›ืžื•ืช ืžืื•ื“ ื’ื“ื•ืœื”
ืฉืœ ืžื•ืžื—ื™ื•ืช ื•ื™ื“ืข ืฉื‘ื” ื”ื ืžืฉืชืžืฉื™ื
04:08
and they use that to react on the fly to kind of unpredictable demands,
87
248542
3797
ื›ื“ื™ ืœื”ื’ื™ื‘ ื‘ื–ืžืŸ ืืžืช ืœืžืขื™ืŸ ื“ืจื™ืฉื•ืช ื‘ืœืชื™ ืฆืคื™ื•ืช,
04:12
and that's very, very hard to automate."
88
252363
2120
ื•ื–ื” ืžืฉื”ื• ืฉืžืื•ื“ ืžืื•ื“ ืงืฉื” ืœืžื›ืŸ."
ืื—ื“ ืžืขื•ื‘ื“ื™ ื”ื™ื“ืข ื”ื›ื™ ืžืจืฉื™ืžื™ื
04:15
One of the most impressive knowledge workers in recent memory
89
255063
2905
ืฉื–ื›ื•ืจ ืœื ื• ืžื”ืชืงื•ืคื” ื”ืื—ืจื•ื ื” ื”ื•ื ื‘ื—ื•ืจ ื‘ืฉื ืงืŸ ื’'ื ื™ื ื’ืก.
04:17
is a guy named Ken Jennings.
90
257992
1521
04:19
He won the quiz show "Jeopardy!" 74 times in a row.
91
259537
4734
ื”ื•ื ื–ื›ื” ื‘ื—ื™ื“ื•ืŸ ื”ื˜ืจื™ื•ื•ื™ื” "Jeopardy!" 74 ืคืขืžื™ื ื‘ืจืฆื™ืคื•ืช,
04:24
Took home three million dollars.
92
264870
2190
ืœืงื— ืคืจืกื™ื ื‘ืฉื•ื•ื™ ืฉืœื•ืฉื” ืžื™ืœื•ืŸ ื“ื•ืœืจ.
ื–ื”ื• ืงืŸ ืคื” ืžื™ืžื™ืŸ ืฉืžืคืกื™ื“ 3:1
04:27
That's Ken on the right, getting beat three-to-one
93
267084
3771
04:30
by Watson, the Jeopardy-playing supercomputer from IBM.
94
270879
4377
ืœื•ื•ื˜ืกื•ืŸ, ืฉื—ืงืŸ ื˜ืจื™ื•ื•ื™ื” ืกื•ืคืจ-ืงื•ืžืคื™ื•ื˜ืจ ืžื‘ื™ืช IBM.
04:35
So when we look at what technology can do to general knowledge workers,
95
275902
3515
ืื– ื›ืฉืื ื—ื ื• ื‘ื•ื—ื ื™ื ืžื” ื”ื˜ื›ื ื•ืœื•ื’ื™ื” ื™ื›ื•ืœื” ืœืขืฉื•ืช
ืœืขื•ื‘ื“ื™ ื”ื™ื“ืข ื”ื›ืœืœื™, ืื ื™ ืžืชื—ื™ืœ ืœื—ืฉื•ื‘
04:39
I start to think there might not be something so special
96
279441
3078
ืฉืื•ืœื™ ืื™ืŸ ืžืฉื”ื• ื›ืœ-ื›ืš ืžื™ื•ื—ื“ ื‘ืจืขื™ื•ืŸ ื”ื–ื” ืฉืœ
04:42
about this idea of a generalist,
97
282543
1768
ื™ื“ืข ื›ืœืœื™, ื‘ืžื™ื•ื—ื“ ื›ืฉืžืชื—ืœื™ื ืœืขืฉื•ืช ื“ื‘ืจื™ื
04:44
particularly when we start doing things like hooking Siri up to Watson,
98
284335
4330
ื›ืžื• ืœื—ื‘ืจ ื‘ื™ืŸ "ืกื™ืจื™" ืœ"ื•ื•ื˜ืกื•ืŸ" ื•ืžืงื‘ืœื™ื ื˜ื›ื ื•ืœื•ื’ื™ื•ืช
04:48
and having technologies that can understand what we're saying
99
288689
3269
ืฉื™ื›ื•ืœื•ืช ืœื”ื‘ื™ืŸ ืžื” ืื ื—ื ื• ืื•ืžืจื™ื
04:51
and repeat speech back to us.
100
291982
1984
ื•ืœื”ื’ื™ื“ ืœื ื• ืืช ื–ื” ื‘ื—ื–ืจื”.
04:53
Now, Siri is far from perfect, and we can make fun of her flaws,
101
293990
3903
ืขื›ืฉื™ื•, "ืกื™ืจื™" ืจื—ื•ืงื” ืžืœื”ื™ื•ืช ืžื•ืฉืœืžืช, ื•ืืคืฉืจ ืœืฆื—ื•ืง
ืขืœ ื”ืคื’ืžื™ื ืฉืœื”, ืื‘ืœ ื›ื“ืื™ ื’ื ืœื–ื›ื•ืจ
04:57
but we should also keep in mind
102
297917
1499
04:59
that if technologies like Siri and Watson improve along a Moore's law trajectory,
103
299440
5364
ืฉืื ื˜ื›ื ื•ืœื•ื’ื™ื•ืช ื›ืžื• "ืกื™ืจื™" ื•"ื•ื•ื˜ืกื•ืŸ" ื™ืฉืชืคืจื•
ื‘ื”ืชืื ืœื—ื•ืง ืžื•ืจ, ื•ื›ืš ื™ืงืจื”,
05:04
which they will,
104
304828
1522
05:06
in six years, they're not going to be two times better or four times better,
105
306374
3590
ืชื•ืš 6 ืฉื ื™ื, ื”ื ืœื ื™ื”ื™ื• ืคื™ 2 ื™ื•ืชืจ ื˜ื•ื‘ื™ื ืื• ืคื™ 4,
ื”ื ื™ื”ื™ื• ืคื™ 16 ื™ื•ืชืจ ื˜ื•ื‘ื™ื ืžืžื” ืฉื”ื ืขื›ืฉื™ื•.
05:09
they'll be 16 times better than they are right now.
106
309988
3470
05:13
So I start to think a lot of knowledge work is going to be affected by this.
107
313482
3846
ืื– ืื ื™ ืžืชื—ื™ืœ ืœื—ืฉื•ื‘ ืฉื”ืจื‘ื” ืžืขื‘ื•ื“ื•ืช ื”ื™ื“ืข ื™ื•ืฉืคืขื• ืžื–ื”.
05:17
And digital technologies are not just impacting knowledge work,
108
317352
3736
ื•ื”ื˜ื›ื ื•ืœื•ื’ื™ื•ืช ื”ื“ื™ื’ื™ื˜ืœื™ื•ืช ืœื ืจืง ืžืฉืคื™ืขื•ืช ืขืœ ืขื‘ื•ื“ื•ืช ื”ื™ื“ืข.
ื”ืŸ ืžืชื—ื™ืœื•ืช ืœื”ืชืืžืŸ ื‘ื™ื›ื•ืœืช ื’ื ื‘ืขื•ืœื ื”ืคื™ื–ื™.
05:21
they're starting to flex their muscles in the physical world as well.
109
321112
3739
05:24
I had the chance a little while back to ride in the Google autonomous car,
110
324875
3725
ื”ื–ื“ืžืŸ ืœื™ ืœืคื ื™ ื›ืžื” ื–ืžืŸ ืœื ืกื•ืข
ื‘ืจื›ื‘ ื”ืื•ื˜ื•ื ื•ืžื™ ืฉืœ ื’ื•ื’ืœ ื•ื”ื•ื ืžื’ื ื™ื‘ ื‘ื“ื™ื•ืง ื›ืžื• ืฉื”ื•ื ื ืฉืžืข (ืฆื—ื•ืง)
05:28
which is as cool as it sounds.
111
328624
2277
05:30
(Laughter)
112
330925
2188
ื•ืื ื™ ื™ื›ื•ืœ ืœื”ื™ื•ืช ืขืจื‘ ืœื›ืš ืฉื”ื•ื ืžืชืžื•ื“ื“ ืขื ืคืงืงื™ ืชื ื•ืขื”
05:33
And I will vouch that it handled the stop-and-go traffic on US 101
113
333137
4421
ื‘ื›ื‘ื™ืฉ 101 .U.S ื‘ืฆื•ืจื” ื—ืœืงื” ื‘ื™ื•ืชืจ.
05:37
very smoothly.
114
337582
1253
05:38
There are about three and a half million people who drive trucks for a living
115
338859
3651
ื™ืฉื ื ื›ืฉืœื•ืฉื” ื•ื—ืฆื™ ืžื™ืœื™ื•ืŸ ืื ืฉื™ื
ืฉืขื•ื‘ื“ื™ื ื›ื ื”ื’ื™ ืžืฉืื™ื•ืช ืœืžื—ื™ื™ืชื ื‘ืืจื”"ื‘.
05:42
in the United States;
116
342534
1151
ืื ื™ ื—ื•ืฉื‘ ืฉื—ืœืงื ื™ื•ืฉืคืข ืžื”ื˜ื›ื ื•ืœื•ื’ื™ื” ื”ื–ื•.
05:43
I think some of them are going to be affected by this technology.
117
343709
3068
ื•ื›ืจื’ืข, ืจื•ื‘ื•ื˜ื™ื ื“ืžื•ื™ื™-ืื“ื ืขื“ื™ื™ืŸ
05:46
And right now, humanoid robots are still incredibly primitive.
118
346801
3100
ืžืื•ื“ ืคืจื™ืžื™ื˜ื™ื•ื•ื™ื™ื. ื”ื ืœื ื™ื›ื•ืœื™ื ืœืขืฉื•ืช ื”ืจื‘ื”.
05:49
They can't do very much.
119
349925
1957
05:51
But they're getting better quite quickly
120
351906
1972
ืื‘ืœ ื”ื ืžืฉืชืคืจื™ื ื“ื™ ืžื”ืจ, ื•- DARPA,
05:53
and DARPA, which is the investment arm of the Defense Department,
121
353902
3537
ืฉื”ื™ื ื”ื–ืจื•ืข ื”ืื—ืจืื™ืช ืขืœ ื”ืฉืงืขื•ืช ื‘ืžื—ืœืงืช ื”ื‘ื™ื˜ื—ื•ืŸ,
05:57
is trying to accelerate their trajectory.
122
357463
1977
ืžื ืกื” ืœื”ืื™ืฅ ืืช ืžืกืœื•ืœ ื”ื”ืชืงื“ืžื•ืช ืฉืœื”ื.
05:59
So, in short, yeah, the droids are coming for our jobs.
123
359464
4442
ืื– ื‘ืงื™ืฆื•ืจ, ื›ืŸ, ื”ื“ืจื•ืื™ื“ื™ื ืื›ืŸ ื‘ืื™ื ืœื”ืฉืชืœื˜ ืœื ื• ืขืœ ื”ืขื‘ื•ื“ื•ืช.
ื‘ื˜ื•ื•ื— ื”ืงืฆืจ, ืื ื—ื ื• ื™ื›ื•ืœื™ื ืœื”ืžืจื™ืฅ ืืช ื”ื’ื™ื“ื•ืœ ื‘ืžืงื•ืžื•ืช ืชืขืกื•ืงื”
06:05
In the short term, we can stimulate job growth
124
365105
2892
ืข"ื™ ืขื™ื“ื•ื“ ื™ื–ืžื•ืช ื•ืข"ื™ ื”ืฉืงืขื•ืช
06:08
by encouraging entrepreneurship
125
368021
2137
06:10
and by investing in infrastructure,
126
370182
1914
ื‘ืชืฉืชื™ื•ืช, ื›ื™ ื”ืจื•ื‘ื•ื˜ื™ื ื”ื™ื•ื ืขื“ื™ื™ืŸ
06:12
because the robots today still aren't very good at fixing bridges.
127
372120
3538
ืœื ื›"ื› ื˜ื•ื‘ื™ื ื‘ืชื™ืงื•ืŸ ื’ืฉืจื™ื.
06:15
But in the not-too-long-term,
128
375682
1898
ืื‘ืœ ื‘ื˜ื•ื•ื— ื”ืœื ืžืื•ื“ ืจื—ื•ืง, ืื ื™ ื—ื•ืฉื‘ ืฉืขื•ื“ ื‘ืชืงื•ืคืช ื”ื—ื™ื™ื
06:17
I think within the lifetimes of most of the people in this room,
129
377604
3902
ืฉืœ ืจื•ื‘ ื”ืื ืฉื™ื ื‘ื—ื“ืจ ื”ื–ื”, ืื ื—ื ื• ื ืขืฉื” ืžืขื‘ืจ
06:21
we're going to transition into an economy that is very productive,
130
381530
3548
ืœื›ืœื›ืœื” ืฉื”ื™ื ืžืื•ื“ ื™ืฆืจื ื™ืช, ืื‘ืœ
06:25
but that just doesn't need a lot of human workers.
131
385102
2894
ืฉืคืฉื•ื˜ ืœื ืฆืจื™ื›ื” ื”ืจื‘ื” ืขื•ื‘ื“ื™ื ืื ื•ืฉื™ื™ื,
06:28
And managing that transition is going to be the greatest challenge
132
388020
3112
ื•ืœื ื”ืœ ืืช ื”ืžืขื‘ืจ ื”ื–ื” ื”ื•ืœืš ืœื”ื™ื•ืช
ื”ืืชื’ืจ ื”ื›ื™ ื’ื“ื•ืœ ืฉื ื™ืฆื‘ ื‘ืคื ื™ ื”ื—ื‘ืจื” ืฉืœื ื•.
06:31
that our society faces.
133
391156
1538
06:32
Voltaire summarized why; he said,
134
392718
1950
ื•ื•ืœื˜ื™ื™ืจ ืชื™ืžืฆืช ืืช ื”ืกื™ื‘ื” ืœื›ืš. ื”ื•ื ืืžืจ
06:34
"Work saves us from three great evils: boredom, vice and need."
135
394692
5179
"ื”ืขื‘ื•ื“ื” ืžืฆื™ืœื” ืื•ืชื ื• ืžืฉืœื•ืฉ ืจืขื•ืช: ืžืŸ ื”ืฉืขืžื•ื, ืžืŸ ื”ื—ื˜ื ื•ืžืŸ ื”ืžื—ืกื•ืจ."
06:40
But despite this challenge --
136
400430
2057
ืื‘ืœ ืœืžืจื•ืช ื”ืืชื’ืจ ื”ื–ื”, ืื™ืฉื™ืช ืื ื™
06:42
personally, I'm still a huge digital optimist,
137
402511
2912
ืขื“ื™ื™ืŸ ืื“ื ืื•ืคื˜ื™ืžื™ ื“ื™ื’ื™ื˜ืœื™ืช, ื•ืื ื™
06:45
and I am supremely confident
138
405447
2204
ืžืฉื•ื›ื ืข ืœื—ืœื•ื˜ื™ืŸ ืฉื”ื˜ื›ื ื•ืœื•ื’ื™ื” ื”ื“ื™ื’ื™ื˜ืœื™ืช ืฉืื ื—ื ื•
06:47
that the digital technologies that we're developing now
139
407675
2588
ืžืคืชื—ื™ื ืขื›ืฉื™ื• ืชื™ืงื— ืื•ืชื ื• ืืœ ืขืชื™ื“ ืื•ื˜ื•ืคื™,
06:50
are going to take us into a Utopian future,
140
410287
2650
06:52
not a dystopian future.
141
412961
1712
ื•ืœื ืœืขืชื™ื“ ื“ื™ืกื˜ื•ืคื™. ื•ื›ื“ื™ ืœื”ืกื‘ื™ืจ ืžื“ื•ืข,
06:54
And to explain why,
142
414697
1151
06:55
I want to pose a ridiculously broad question.
143
415872
2579
ืื ื™ ืจื•ืฆื” ืœื”ืขืœื•ืช ืฉืืœื” ืจื—ื‘ื” ืขื“ ื›ื“ื™ ื’ื™ื—ื•ืš.
06:58
I want to ask:
144
418475
1151
ืื ื™ ืจื•ืฆื” ืœืฉืื•ืœ ืžื” ื”ื™ืชื” ื”ื”ืชืคืชื—ื•ืช ื”ื›ื™ ื—ืฉื•ื‘ื”
06:59
what have been the most important developments in human history?
145
419650
3346
ื‘ื”ื™ืกื˜ื•ืจื™ื” ื”ืื ื•ืฉื™ืช?
07:03
Now, I want to share some of the answers that I've gotten
146
423020
2961
ืขื›ืฉื™ื•, ืื ื™ ืจื•ืฆื” ืœืฉืชืฃ ืืชื›ื ื‘ื›ืžื” ืžื”ืชืฉื•ื‘ื•ืช ืฉืงื™ื‘ืœืชื™
ื‘ืชื’ื•ื‘ื” ืœืฉืืœื” ื”ื–ื”. ื–ื• ืฉืืœื” ื ืคืœืื”
07:06
in response to this question.
147
426005
1397
07:07
It's a wonderful question to ask and start an endless debate about,
148
427426
3168
ืœืฉืื•ืœ ื›ื“ื™ ืœืคืชื•ื— ื‘ื“ื™ื•ืŸ ืื™ืŸ ืกื•ืคื™ ืกื‘ื™ื‘ื”,
07:10
because some people are going to bring up
149
430618
1974
ื›ื™ ื™ืฉ ืื ืฉื™ื ืฉื™ืขืœื•
07:12
systems of philosophy in both the West and the East
150
432616
3300
ืžืขืจื›ื•ืช ื•ืคื™ืœื•ืกื•ืคื™ื•ืช ื”ืŸ ื‘ืžืขืจื‘ ื•ื”ืŸ ื‘ืžื–ืจื—
07:15
that have changed how a lot of people think about the world.
151
435940
3223
ืฉืฉื™ื ื• ืืช ื”ืื•ืคืŸ ืฉื‘ื• ื”ืจื‘ื” ืื ืฉื™ื ื—ื•ืฉื‘ื™ื ืขืœ ื”ืขื•ืœื.
07:19
And then other people will say,
152
439187
1493
ื•ื™ื”ื™ื• ืื ืฉื™ื ืื—ืจื™ื ืฉื™ื’ื™ื“ื•, "ืœื, ื”ืืžืช ื”ื™ื ืฉื”ื“ื‘ืจื™ื ื”ื›ื™ ื’ื“ื•ืœื™ื,
07:20
"No, actually, the big stories, the big developments
153
440704
2461
ื”ื”ืชืคืชื—ื•ื™ื•ืช ื”ื›ื™ ื’ื“ื•ืœื•ืช ื”ืŸ ื™ืกื•ื“ืŸ
07:23
are the founding of the world's major religions,
154
443189
2583
ืฉืœ ื”ื“ืชื•ืช ื”ื’ื“ื•ืœื•ืช ื‘ืขื•ืœื, ืฉืฉื™ื ื• ืฆื™ื•ื•ื™ืœื™ื–ืฆื™ื•ืช
07:25
which have changed civilizations and have changed and influenced
155
445796
3226
ื•ืฉื™ื ื• ื•ื”ืฉืคื™ืขื• ืขืœ ื”ืื•ืคืŸ ื‘ื• ืื™ืŸ ืกืคื•ืจ ืื ืฉื™ื
07:29
how countless people are living their lives."
156
449046
2594
ื—ื™ื™ื ืืช ื—ื™ื™ื”ื." ื•ื™ื”ื™ื• ื›ืžื” ืื ืฉื™ื ืื—ืจื™ื ืฉื™ื’ื™ื“ื•,
07:31
And then some other folk will say,
157
451664
1697
07:33
"Actually, what changes civilizations,
158
453385
2390
"ืœืžืขืฉื”, ืžื” ืฉืฉื™ื ื” ืฆื™ื•ื•ื™ืœื™ื–ืฆื™ื•ืช, ืžื” ืฉืขื™ืฆื‘ ืื•ืชืŸ
07:35
what modifies them and what changes people's lives are empires,
159
455799
4785
ื•ืžื” ืฉืฉื™ื ื” ืืช ื—ื™ื™ ื”ืื ืฉื™ื
ื”ืŸ ื”ืื™ืžืคืจื™ื•ืช, ืื– ื”ื”ืชืคืชื—ื•ื™ื•ืช ื”ื’ื“ื•ืœื•ืช ื‘ื”ื™ืกื˜ื•ืจื™ื” ื”ืื ื•ืฉื™ืช
07:40
so the great developments in human history
160
460608
2405
ื”ื ืกื™ืคื•ืจื™ื ืฉืœ ื›ื™ื‘ื•ืฉ ื•ืžืœื—ืžื”."
07:43
are stories of conquest and of war."
161
463037
2762
07:45
And then some cheery soul usually always pipes up and says,
162
465823
2781
ื•ื™ืฉ ื’ื ื›ืžื” ื ืคืฉื•ืช ืขืœื™ื–ื•ืช ืฉื‘ื“"ื› ืฆืฆื•ืช ื•ืื•ืžืจื•ืช
07:48
"Hey, don't forget about plagues!"
163
468628
1682
"ื”ื™ื™, ืืœ ืชืฉื›ื—ื• ืืช ื”ืžื’ืคื•ืช." (ืฆื—ื•ืง)
07:50
(Laughter)
164
470334
3909
ื™ืฉ ื›ืžื” ืชืฉื•ื‘ื•ืช ืื•ืคื˜ื™ืžื™ื•ืช ืœืฉืืœื” ื”ื–ื•,
07:54
There are some optimistic answers to this question,
165
474267
2523
07:56
so some people will bring up the Age of Exploration
166
476814
2414
ืื– ื—ืœืง ืžื”ืื ืฉื™ื ื™ืขืœื• ืืช ื”ื ื•ืฉื
ืฉืœ ืขื™ื“ืŸ ื”ืชื’ืœื™ื•ืช ื•ืืช ื”ื”ื™ืคืชื—ื•ืช ืฉืœ ื”ืขื•ืœื.
07:59
and the opening up of the world.
167
479252
1545
08:00
Others will talk about intellectual achievements in disciplines like math
168
480821
3778
ืื—ืจื™ื ื™ื“ื‘ืจื• ืขืœ ื”ื™ืฉื’ื™ื ืื™ื ื˜ืœืงื˜ื•ืืœื™ื™ื
ื‘ืชื—ื•ืžื™ื ื›ืžื• ืžืชืžื˜ื™ืงื” ืฉืขื–ืจื• ืœื ื• ืœื”ื’ื™ืข
08:04
that have helped us get a better handle on the world,
169
484623
2494
ืœื”ื‘ื ื” ื˜ื•ื‘ื” ื™ื•ืชืจ ืฉืœ ื”ืขื•ืœื, ื•ืื—ืจื™ื ื™ื“ื‘ืจื•
08:07
and other folk will talk about periods when there was a deep flourishing
170
487141
3440
ืขืœ ืชืงื•ืคื•ืช ืฉื”ื™ืชื” ื‘ื”ื ืคืจื™ื—ื” ื’ื“ื•ืœื”
08:10
of the arts and sciences.
171
490605
1605
ืฉืœ ื”ืื•ืžื ื•ืช ื•ื”ืžื“ืขื™ื. ืื– ื”ื“ื™ื•ืŸ ื”ื–ื” ื™ืžืฉืš ืขื•ื“ ื•ืขื•ื“
08:12
So this debate will go on and on.
172
492234
1587
08:13
It's an endless debate
173
493845
1461
ื–ื” ื“ื™ื•ืŸ ืื™ืŸ ืกื•ืคื™, ื•ืื™ืŸ ืชืฉื•ื‘ื” ื—ื“ ืžืฉืžืขื™ืช,
08:15
and there's no conclusive, single answer to it.
174
495330
3233
ืื™ืŸ ืชืฉื•ื‘ื” ื™ื—ื™ื“ื” ืœื–ื”. ืื‘ืœ ืื ืืชื ื—ื ื•ื ื™ื ื›ืžื•ื ื™,
08:18
But if you're a geek like me,
175
498587
1517
ืืชื ืื•ืžืจื™ื, "ื ื•, ืื– ืžื” ื”ื ืชื•ื ื™ื ืื•ืžืจื™ื?"
08:20
you say, "Well, what do the data say?"
176
500128
2681
08:22
And you start to do things
177
502833
1332
ื•ืื– ืžืชื—ื™ืœื™ื ืœืขืฉื•ืช ื“ื‘ืจื™ื ื›ืžื• ืœื™ืฆื•ืจ ื’ืจืคื™ื ืžื“ื‘ืจื™ื
08:24
like graph things that we might be interested in --
178
504189
2684
ืฉืื•ืœื™ ืžืขื ื™ื™ื ื™ื ืื•ืชื ื•, ื›ืœ ืื•ื›ืœื•ืกื™ื™ืช ื”ืขื•ืœื ืœืžืฉืœ,
08:26
the total worldwide population, for example,
179
506897
3079
ืื• ืžื“ื“ื™ื ืžืกื•ื™ืžื™ื ืฉืœ ืคื™ืชื•ื—ื™ื ื—ื‘ืจืชื™ื™ื,
08:30
or some measure of social development
180
510000
2365
08:32
or the state of advancement of a society.
181
512389
2488
ืื• ืžืฆื‘ื™ ื”ืงื™ื“ืžื” ื‘ื—ื‘ืจื”,
08:34
And you start to plot the data, because, by this approach,
182
514901
4123
ื•ืืชื” ืžืชื—ื™ืœ ืœื”ืฆื™ื’ ืืช ื”ื ืชื•ื ื™ื ื”ืืœื• ื‘ืฆื•ืจื” ื’ืจืคื™ืช, ื›ื™ ื‘ืฆื•ืจื” ื”ื–ื•
ื”ืกื™ืคื•ืจื™ื ื”ื’ื“ื•ืœื™ื, ื”ื”ืชืคืชื—ื•ื™ื•ืช ื”ื’ื“ื•ืœื•ืช ื‘ื”ื™ืกื˜ื•ืจื™ื” ื”ืื ื•ืฉื™ืช,
08:39
the big stories, the big developments in human history,
183
519048
2605
08:41
are the ones that will bend these curves a lot.
184
521677
2510
ื”ื ืืœื• ืฉื™ืฆืจื• ืืช ื”ืงื™ืžื•ืจื™ื ื”ื’ื“ื•ืœื™ื ื‘ืขืงื•ืžื•ืช ื”ืืœื•.
08:44
So when you do this and when you plot the data,
185
524211
2220
ืื– ื›ืฉืขื•ืฉื™ื ืืช ื–ื”, ื•ื›ืฉื™ื•ืฆืจื™ื ืชืจืฉื™ื ืžื”ื ืชื•ื ื™ื ื”ืืœื•,
08:46
you pretty quickly come to some weird conclusions.
186
526455
2692
ื“ื™ ืžื”ืจ ืžื’ื™ืขื™ื ืœื›ืžื” ืžืกืงื ื•ืช ื“ื™ ืžื•ื–ืจื•ืช.
ืžืกื™ืงื™ื, ืœืžืขืฉื”, ืฉืืฃ ืื—ื“ ืžื”ื“ื‘ืจื™ื ื”ืืœื•
08:49
You conclude, actually,
187
529171
1396
08:50
that none of these things have mattered very much.
188
530591
2563
ืœื ืžืžืฉ ืžืฉื ื”. (ืฆื—ื•ืง)
08:53
(Laughter)
189
533178
3594
ื”ื ืžืžืฉ ืœื ืขืฉื• ื›ืœื•ื ืœืขืงื•ืžื•ืช ื”ืืœื•. (ืฆื—ื•ืง)
08:57
They haven't done a darn thing to the curves.
190
537240
3353
09:00
There has been one story, one development in human history
191
540617
4690
ื”ื™ื” ืกื™ืคื•ืจ ืื—ื“, ื”ืชืคืชื—ื•ืช ืื—ืช
ื‘ื”ื™ืกื˜ื•ืจื™ื” ื”ืื ื•ืฉื™ืช ืฉื™ืฆืจื” ืงื™ืžื•ืจ ื‘ืขืงื•ืžื” ื”ื–ื•, ืงื™ืžื•ืจ ืฉืœ ื‘ืขืจืš
09:05
that bent the curve, bent it just about 90 degrees,
192
545331
3209
90 ืžืขืœื•ืช, ื•ื–ื” ื”ืกื™ืคื•ืจ ืฉืœ ื”ื˜ื›ื ื•ืœื•ื’ื™ื”.
09:08
and it is a technology story.
193
548564
2135
09:11
The steam engine and the other associated technologies
194
551223
2770
ืžื ื•ืข ื”ืงื™ื˜ื•ืจ, ื•ื”ื˜ื›ื ื•ืœื•ื’ื™ื•ืช ื”ืื—ืจื•ืช ืฉืงืฉื•ืจื•ืช ื‘ื–ื”
09:14
of the Industrial Revolution
195
554017
2031
ืžืชืงื•ืคืช ื”ืžื”ืคื›ื” ื”ืชืขืฉื™ื™ืชื™ืช ืฉื™ื ื• ืืช ื”ืขื•ืœื
09:16
changed the world and influenced human history so much,
196
556072
3276
ื•ื”ืฉืคื™ืขื• ืขืœ ื”ื”ื™ืกื˜ื•ืจื™ื” ื”ืื ื•ืฉื™ืช ื‘ืžื™ื“ื” ื›ื” ืจื‘ื”,
09:19
that in the words of the historian Ian Morris,
197
559372
2402
ืฉื‘ืžื™ืœื•ืชื™ื• ืฉืœ ื”ื”ื™ืกื˜ื•ืจื™ื•ืŸ ืื™ืืŸ ืžื•ืจื™ืก,
09:21
"... they made mockery out of all that had come before."
198
561798
3791
ื”ื ืฉืžื• ืœืœืขื’ ืืช ื›ืœ ืžื” ืฉืงื“ื ืœื”ื.
09:25
And they did this by infinitely multiplying the power of our muscles,
199
565613
3527
ื•ื”ื ืขืฉื• ื–ืืช ื‘ื›ืš ืฉื”ื›ืคื™ืœื• ื‘ืื•ืคืŸ ืื™ื ืกื•ืคื™ ืืช ื”ื›ื•ื—
ืฉืœ ื”ืฉืจื™ืจื™ื ืฉืœื ื•, ื”ืชื’ื‘ืจื• ืขืœ ืžื’ื‘ืœื•ืช ื”ืฉืจื™ืจื™ื ืฉืœื ื•.
09:29
overcoming the limitations of our muscles.
200
569164
2394
09:31
Now, what we're in the middle of now
201
571582
2498
ืขื›ืฉื™ื•, ืื ื—ื ื• ื ืžืฆืื™ื ื›ื™ื•ื ื‘ืชื•ืš ืชื”ืœื™ืš
09:34
is overcoming the limitations of our individual brains
202
574104
3033
ืฉืœ ื”ืชื’ื‘ืจื•ืช ืขืœ ืžื’ื‘ืœื•ืช ื”ืžื•ื— ื”ืื™ื ื“ื™ื‘ื™ื“ื•ืืœื™
09:37
and infinitely multiplying our mental power.
203
577161
2911
ื•ืžื›ืคื™ืœื™ื ื‘ืื•ืคืŸ ืื™ื ืกื•ืคื™ ืืช ื”ื›ื•ืฉืจ ื”ืฉื›ืœื™ ืฉืœื ื•.
09:40
How can this not be as big a deal
204
580096
3177
ืื™ืš ื™ื›ื•ืœ ืœื”ื™ื•ืช ืฉื–ื” ืœื ืขื ื™ื™ืŸ ืจืฆื™ื ื™ ื‘ื“ื™ื•ืง ื›ืžื•
09:43
as overcoming the limitations of our muscles?
205
583297
2704
ื”ื”ืชื’ื‘ืจื•ืช ืขืœ ืžื’ื‘ืœื•ืช ื”ืฉืจื™ืจื™ื ืฉืœื ื•?
09:46
So at the risk of repeating myself a little bit,
206
586025
2860
ืื–, ืœืžืจื•ืช ืฉืื ื™ ืงืฆืช ื—ื•ื–ืจ ืขืœ ืขืฆืžื™, ื›ืฉืื ื™ ืžืกืชื›ืœ
09:48
when I look at what's going on with digital technology these days,
207
588909
3753
ืขืœ ืžื” ืฉืงื•ืจื” ื‘ื™ืžื™ื ื”ืืœื• ืขื ื”ื˜ื›ื ื•ืœื•ื’ื™ื” ื”ื“ื™ื’ื™ื˜ืœื™ืช,
09:52
we are not anywhere near through with this journey.
208
592686
3110
ืื ื—ื ื• ืืคื™ืœื• ืœื ืงืจื•ื‘ื™ื ืœืกื•ืฃ ื”ืžืกืข,
09:55
And when I look at what is happening to our economies and our societies,
209
595820
3506
ื•ื›ืฉืื ื™ ืžืกืชื›ืœ ืขืœ ืžื” ืฉืงื•ืจื” ืขื ื”ื›ืœื›ืœื•ืช ืฉืœื ื•
ื•ืขื ื”ื—ื‘ืจื•ืช ืฉืœื ื•, ื”ืžืกืงื ื” ื”ื™ื—ื™ื“ื” ืฉืœื™
09:59
my single conclusion is that we ain't seen nothing yet.
210
599350
3089
ื”ื™ื ืฉืขื•ื“ ืœื ืจืื™ื ื• ื›ืœื•ื. ื”ื™ืžื™ื ื”ื›ื™ ื˜ื•ื‘ื™ื ื‘ืืžืช ืขื•ื“ ืœืคื ื™ื ื•.
10:02
The best days are really ahead.
211
602463
1726
10:04
Let me give you a couple examples.
212
604213
2001
ื”ืจืฉื• ืœื™ ืœืชืช ืœื›ื ื›ืžื” ื“ื•ื’ืžืื•ืช.
ื›ืœื›ืœื•ืช ืœื ืžื•ื ืขื•ืช ืข"ื™ ืื ืจื’ื™ื”. ื•ื”ืŸ ืœื ืžื•ื ืขื•ืช ืข"ื™ ื”ื•ืŸ,
10:06
Economies don't run on energy.
213
606238
2373
10:08
They don't run on capital, they don't run on labor.
214
608635
3039
ื”ืŸ ืœื ืžื•ื ืขื•ืช ืข"ื™ ื›ื•ื— ืขื‘ื•ื“ื”. ื›ืœื›ืœื•ืช ืžื•ื ืขื•ืช ืข"ื™ ืจืขื™ื•ื ื•ืช.
10:11
Economies run on ideas.
215
611698
2405
ืื– ื”ืชืคืงื™ื“ ืฉืœ ื”ื—ื“ืฉื ื•ืช, ื”ืขื‘ื•ื“ื” ืฉืœ ืœื”ืžืฆื™ื
10:14
So the work of innovation, the work of coming up with new ideas,
216
614127
3341
ืจืขื™ื•ื ื•ืช ื—ื“ืฉื™ื, ื–ื” ืื—ื“ ืžื”ื“ื‘ืจื™ื ื”ื›ื™ ื—ื–ืงื™ื,
10:17
is some of the most powerful, most fundamental work that we can do
217
617492
3698
ื–ื• ื”ืขื‘ื•ื“ื” ื”ื›ื™ ื‘ืกื™ืกื™ืช ืฉืื ื—ื ื• ื™ื›ื•ืœื™ื ืœืขืฉื•ืช
ื‘ื›ืœื›ืœื”. ื•ื›ื›ื” ื‘ืขืจืš ื”ื™ื™ื ื• ืžื™ื™ืฆืจื™ื ื—ื“ืฉื ื•ืช ื‘ืขื‘ืจ.
10:21
in an economy.
218
621214
1151
10:22
And this is kind of how we used to do innovation.
219
622389
3118
ื”ื™ื™ื ื• ืžืืชืจื™ื ื›ืžื” ืื ืฉื™ื ืฉื ืจืื™ื ื“ื™ ืื•ืชื• ื“ื‘ืจ,
10:25
We'd find a bunch of fairly similar-looking people ...
220
625531
2976
10:28
(Laughter)
221
628531
3496
(ืฆื—ื•ืง)
ื”ื™ื™ื ื• ืžื•ืฆื™ืื™ื ืื•ืชื ืžืžื•ืกื“ื•ืช ืขื™ืœื™ืช, ืฉืžื™ื ืื•ืชื
10:32
We'd take them out of elite institutions,
222
632051
1993
10:34
we'd put them into other elite institutions
223
634068
2079
ื‘ืžื•ืกื“ื•ืช ืขื™ืœื™ืช ืื—ืจื™ื, ื•ืžื—ื›ื™ื ืœื”ืžืฆืื•ืช.
10:36
and we'd wait for the innovation.
224
636171
1586
10:37
Now --
225
637781
1169
ืขื›ืฉื™ื• (ืฆื—ื•ืง)
10:38
(Laughter)
226
638974
2429
10:41
as a white guy who spent his whole career at MIT and Harvard,
227
641427
3488
ื‘ืชื•ืจ ื‘ื—ื•ืจ ืœื‘ืŸ ืฉื‘ื™ืœื” ืืช ื›ืœ ื”ืงืจื™ื™ืจื” ืฉืœื• ื‘- MIT
10:44
I've got no problem with this.
228
644939
2026
ื•ื‘ืื•ื ' ื”ืจื•ื•ืืจื“, ืื™ืŸ ืœื™ ืฉื•ื ื‘ืขื™ื” ืขื ื–ื”. (ืฆื—ื•ืง)
10:46
(Laughter)
229
646989
2305
10:50
But some other people do,
230
650605
1207
ืื‘ืœ ืœืื ืฉื™ื ืื—ืจื™ื ื›ืŸ ื™ืฉ ื‘ืขื™ื” ืขื ื–ื”,
10:51
and they've kind of crashed the party
231
651836
1785
ืื– ื”ื ื‘ืขื˜ื• ื‘ืžืกื’ืจื•ืช ื•ืฉื—ืจื•ืจื• ืืช ืงื•ื“ ื”ืœื‘ื•ืฉ ืฉืœ ื”ื—ื“ืฉื ื•ืช.
10:53
and loosened up the dress code of innovation.
232
653645
2145
10:55
(Laughter)
233
655814
1032
(ืฆื—ื•ืง)
10:56
So here are the winners of a Topcoder programming challenge,
234
656870
3200
ื•ื”ื ื” ื”ื ื”ื–ื•ื›ื™ื ืฉืœ "ืืชื’ืจ ื”ืชื›ื ื•ืช ืฉืœ ื”ืžืงื•ื“ื“ ื”ื˜ื•ื‘ ื‘ื™ื•ืชืจ",
11:00
and I assure you that nobody cares
235
660094
2692
ื•ืื ื™ ืžื‘ื˜ื™ื— ืœื›ื ืฉืœืืฃ ืื—ื“ ืœื ืื›ืคืช
11:02
where these kids grew up, where they went to school,
236
662810
3756
ืื™ืคื” ื’ื“ืœื• ื”ื™ืœื“ื™ื ื”ืืœื•, ื‘ืื™ื–ื” ื‘ื™"ืก ื”ื ืœืžื“ื•,
11:06
or what they look like.
237
666590
1500
ืื• ืื™ืš ื”ื ื ืจืื™ื. ื›ืœ ืžื” ืฉืžืขื ื™ื™ืŸ
11:08
All anyone cares about is the quality of the work, the quality of the ideas.
238
668114
3843
ื”ื•ื ืื™ื›ื•ืช ื”ืขื‘ื•ื“ื” ืฉืœื”ื, ืื™ื›ื•ืช ื”ืจืขื™ื•ื ื•ืช.
11:11
And over and over again, we see this happening
239
671981
2236
ื•ืคืขื ืื—ืจื™ ืคืขื, ืื ื—ื ื• ืจื•ืื™ื ืืช ื–ื” ืงื•ืจื”
11:14
in the technology-facilitated world.
240
674241
2524
ื‘ืขื•ืœื ืฉื”ื˜ื›ื ื•ืœื•ื’ื™ื” ืžื•ื‘ื ื™ืช ื‘ื•.
11:16
The work of innovation is becoming more open,
241
676789
2497
ื”ืขื‘ื•ื“ื” ื‘ื—ื“ืฉื ื•ืช ื”ื•ืคื›ืช ืœื™ื•ืชืจ ืคืชื•ื—ื”,
ื™ื•ืชืจ ืžืงื™ืคื”, ื™ื•ืชืจ ืฉืงื•ืคื”, ื•ื™ื•ืชืจ ืžื‘ื•ืกืกืช ืขืœ ื›ืฉืจื•ืŸ,
11:19
more inclusive, more transparent and more merit-based,
242
679310
3649
11:22
and that's going to continue no matter what MIT and Harvard think of it,
243
682983
3698
ื•ื–ื” ื™ื™ืžืฉืš ื›ื›ื” ืœื ืžืฉื ื” ืžื” MIT ื•ื”ืจื•ื•ืืจื“
ื—ื•ืฉื‘ื™ื ืขืœ ื–ื”, ื•ืื ื™ ืœื’ืžืจื™ ืฉืžื— ืขืœ ื”ื”ืชืคืชื—ื•ืช ื”ื–ื•.
11:26
and I couldn't be happier about that development.
244
686705
2565
11:29
I hear once in a while, "OK, I'll grant you that,
245
689609
2455
ืื ื™ ืฉื•ืžืข ืžื“ื™ ืคืขื, "ืื•.ืงื™ื™., ืื ื™ ืžืกื›ื™ื ืื™ืชืš ื‘ื ืงื•ื“ื” ื”ื–ื•,
ืื‘ืœ ื˜ื›ื ื•ืœื•ื’ื™ื” ื”ื™ื ืขื“ื™ื™ืŸ ื›ืœื™ ืฉืœ ื”ืขื•ืœื ื”ืขืฉื™ืจ,
11:32
but technology is still a tool for the rich world,
246
692088
3019
11:35
and what's not happening,
247
695131
1399
ื•ืžื” ืฉืœื ืงื•ืจื”, ื–ื” ืฉื”ื›ืœื™ื ื”ื“ื™ื’ื™ื˜ืœื™ื™ื ื”ืืœื•
11:36
these digital tools are not improving the lives
248
696554
2611
ืœื ืžืฉืคืจื™ื ืืช ื—ื™ื™ื”ื ืฉืœ ื”ืื ืฉื™ื ื‘ืชื—ืชื™ืช ื”ืคื™ืจืžื™ื“ื”."
11:39
of people at the bottom of the pyramid."
249
699189
2149
11:41
And I want to say to that very clearly: nonsense.
250
701362
2666
ื•ืื ื™ ืจื•ืฆื” ืœื”ื’ื™ื“ ื‘ืฆื•ืจื” ืžืื•ื“ ื‘ืจื•ืจื”: ืฉื˜ื•ื™ื•ืช.
ืชื—ืชื™ืช ื”ืคื™ืจืžื™ื“ื” ื ื”ื ื™ืช ื‘ืฆื•ืจื” ืื“ื™ืจื” ืžื”ื˜ื›ื ื•ืœื•ื’ื™ื”.
11:44
The bottom of the pyramid is benefiting hugely from technology.
251
704052
3493
11:47
The economist Robert Jensen did this wonderful study a while back
252
707569
3560
ื”ื›ืœื›ืœืŸ ืจื•ื‘ืจื˜ ื’'ื ืกืŸ ืขืจืš ืžื—ืงืจ ื ืคืœื
ืœื ืžื–ืžืŸ, ืฉื‘ื• ื”ื•ื ืขืงื‘ ื‘ืคื™ืจื•ื˜ ืจื‘,
11:51
where he watched, in great detail,
253
711153
1933
11:53
what happened to the fishing villages of Kerala, India,
254
713110
3618
ืื—ืจื™ ืžื” ืฉืงืจื” ืœื›ืคืจื™ ื”ื“ื™ื™ื’ื™ื ืฉืœ ืงืจืœื” ืฉื‘ื”ื•ื“ื•,
11:56
when they got mobile phones for the very first time.
255
716752
2881
ื›ืืฉืจ ื”ื’ื™ืขื• ืืœื™ื”ื ื˜ืœืคื•ื ื™ื ื ื™ื™ื“ื™ื ื‘ืคืขื ื”ืจืืฉื•ื ื”,
11:59
And when you write for the Quarterly Journal of Economics,
256
719657
2809
ื•ื›ืฉื›ื•ืชื‘ื™ื ืœ"ื›ืชื‘-ื”ืขื˜ ื”ืจื‘ืขื•ื ื™ ืœื›ืœื›ืœื”",
12:02
you have to use very dry and very circumspect language.
257
722490
2882
ืืชื” ื—ื™ื™ื‘ ืœื”ืฉืชืžืฉ ื‘ืฉืคื” ืžืื•ื“ ื™ื‘ืฉื” ื•ื–ื”ื™ืจื”,
12:05
But when I read his paper,
258
725396
1262
ืื‘ืœ ื›ืฉืื ื™ ืงื•ืจื ืืช ื”ืžืืžืจ ืฉืœื•, ืื ื™ ืžืจื’ื™ืฉ ื›ืื™ืœื• ื’'ื ืกืŸ ืžื ืกื”
12:06
I kind of feel Jensen is trying to scream at us
259
726682
2207
ืœื–ืขื•ืง ืืœื™ื ื•, ื•ืœื”ื’ื™ื“, ืชืจืื•, ื–ื” ื”ื™ื” ื—ืชื™ื›ืช ืื™ืจื•ืข.
12:08
and say, "Look, this was a big deal.
260
728913
2324
ืžื—ื™ืจื™ื ื”ืชื™ื™ืฆื‘ื•, ืื– ืื ืฉื™ื ื™ื›ืœื• ืœืชื›ื ืŸ ืืช ื—ื™ื™ื”ื ื”ื›ืœื›ืœื™ื™ื.
12:11
Prices stabilized, so people could plan their economic lives.
261
731261
3651
12:14
Waste was not reduced -- it was eliminated.
262
734936
3674
ื”ื‘ื–ื‘ื•ื– ืœื ืคื—ืช; ื”ื•ื ื—ื•ืกืœ.
ื•ื”ื—ื™ื™ื, ื”ืŸ ืฉืœ ื”ืงื•ื ื™ื ื•ื”ืŸ ืฉืœ ื”ืžื•ื›ืจื™ื
12:19
And the lives of both the buyers and the sellers
263
739007
2241
12:21
in these villages measurably improved."
264
741272
2474
ื‘ื›ืคืจื™ื ื”ืืœื• ื”ืฉืชืคืจื• ื‘ืฆื•ืจื” ื‘ืจื•ืจื”.
ืขื›ืฉื™ื•, ืื ื™ ืœื ื—ื•ืฉื‘ ืฉืœื’'ื ืกืŸ ืกืชื ื”ื™ื” ื”ืจื‘ื” ืžื–ืœ
12:24
Now, what I don't think is that Jensen got extremely lucky
265
744073
3790
12:27
and happened to land in the one set of villages
266
747887
2211
ื•ื”ื•ื ื‘ืžืงืจื” ื ื—ืช ื‘ื“ื™ื•ืง ื‘ืงื‘ื•ืฆืช ื”ื›ืคืจื™ื
ืฉื‘ื” ื”ื˜ื›ื ื•ืœื•ื’ื™ื” ื”ื‘ื™ืื” ืœืฉื™ืคื•ืจ.
12:30
where technology made things better.
267
750122
2309
12:32
What happened instead is he very carefully documented
268
752455
2647
ืžื” ืฉืงืจื” ื–ื” ืฉื”ื•ื ืชื™ืขื“ ื‘ืฆื•ืจื” ืงืคื“ื ื™ืช
ืžื” ืฉืžืชืจื—ืฉ ืคืขื ืื—ืจื™ ืคืขื ื›ืฉื˜ื›ื ื•ืœื•ื’ื™ื”
12:35
what happens over and over again when technology comes for the first time
269
755126
4079
ืžื’ื™ืขื” ื‘ืคืขื ื”ืจืืฉื•ื ื” ืœืกื‘ื™ื‘ื” ื•ืœืงื”ื™ืœื”.
12:39
to an environment and a community:
270
759229
1937
ื—ื™ื™ื”ื ืฉืœ ืื ืฉื™ื, ื”ืจื•ื•ื—ื” ืฉืœ ื”ืื ืฉื™ื, ืžืฉืชืคืจื™ื ื‘ืฆื•ืจื” ื“ืจืžื˜ื™ืช.
12:41
the lives of people, the welfares of people, improve dramatically.
271
761190
3837
ืื– ื›ืฉืื ื™ ืžืกืชื›ืœ ืกื‘ื™ื‘ ืขืœ ื›ืœ ื”ืจืื™ื•ืช, ื•ืื ื™ ื—ื•ืฉื‘
12:45
So as I look around at all the evidence
272
765051
1881
12:46
and I think about the room that we have ahead of us,
273
766956
2437
ืขืœ ื”ืžืจื•ื•ื— ืฉืขื•ื“ ื™ืฉ ืœืคื ื™ื ื•,
12:49
I become a huge digital optimist
274
769417
1828
ืื ื™ ื ื”ื™ื” ืื•ืคื˜ื™ืžื™ืกื˜ ื“ื™ื’ื™ื˜ืœื™ ื’ื“ื•ืœ, ื•ืื ื™ ืžืชื—ื™ืœ ืœื—ืฉื•ื‘
12:51
and I start to think that this wonderful statement from the physicist Freeman Dyson
275
771269
4576
ืฉื”ืืžืจื” ื”ื ืคืœืื” ืฉืœ ื”ืคื™ื–ื™ืงืื™ ืคืจื™ืžืŸ ื“ื™ื™ืกื•ืŸ
12:55
is actually not hyperbole.
276
775869
1738
ื”ื™ื ืœืžืขืฉื” ืœื ืžื•ืคืจื–ืช. ื–ื•ื”ื™ ื”ืขืจื›ื” ืžื“ื•ื™ืงืช ืฉืœ ื”ืžืชืจื—ืฉ.
12:57
This is an accurate assessment of what's going on.
277
777631
2509
13:00
Our technologies are great gifts,
278
780164
2698
ื”ื˜ื›ื ื•ืœื•ื’ื™ื” ืฉืœื ื• ื”ื™ื ืžืชื ื” ื ืคืœืื”,
13:02
and we, right now, have the great good fortune
279
782886
3047
ื•ืื ื—ื ื•, ื”ื™ื•ื, ื‘ืจื™-ืžื–ืœ
13:05
to be living at a time when digital technology is flourishing,
280
785957
3730
ืฉืื ื—ื ื• ื—ื™ื™ื ื‘ืชืงื•ืคื” ืฉื”ื˜ื›ื ื•ืœื•ื’ื™ื” ื”ื“ื™ื’ื™ื˜ืœื™ืช ื‘ื” ืคื•ืจื—ืช,
13:09
when it is broadening and deepening and becoming more profound
281
789711
3395
ืฉื”ื™ื ืžืชืจื—ื‘ืช ื•ืžืขืžื™ืงื”
ื•ืžืงื‘ืœืช ืžืฉืžืขื•ืช ืขืžื•ืงื” ื™ื•ืชืจ ื‘ื›ืœ ืจื—ื‘ื™ ื”ืขื•ืœื.
13:13
all around the world.
282
793130
1278
13:14
So, yeah, the droids are taking our jobs,
283
794432
3275
ืื–, ื›ืŸ, ื”ื“ืจื•ืื™ื“ื™ื ืื›ืŸ ืœื•ืงื—ื™ื ืœื ื• ืืช ื”ืขื‘ื•ื“ื”,
13:17
but focusing on that fact misses the point entirely.
284
797731
3571
ืื‘ืœ ืื ืžืชืžืงื“ื™ื ื‘ื–ื” ืžืคืกืคืกื™ื ืœื’ืžืจื™ ืืช ื”ื ืงื•ื“ื”.
13:21
The point is that then we are freed up to do other things,
285
801326
3500
ื”ื ืงื•ื“ื” ื”ื™ื ืฉืื– ืื ื—ื ื• ืžืฉื•ื—ืจืจื™ื ืœืขืฉื•ืช ื“ื‘ืจื™ื ืื—ืจื™ื,
13:24
and what we're going to do, I am very confident,
286
804850
2287
ื•ืžื” ืฉืื ื—ื ื• ื ืขืฉื”, ืื ื™ ืžืฉื•ื›ื ืข ื‘ื›ืš,
13:27
what we're going to do is reduce poverty
287
807161
2516
ืžื” ืฉืื ื—ื ื• ื ืขืฉื” ื™ื”ื™ื” ืœื”ืคื—ื™ืช ืืช ื”ืขื•ื ื™ ื•ื”ืขื‘ื•ื“ื” ื”ืฉื—ื•ืจื”
13:29
and drudgery and misery around the world.
288
809701
2469
ื•ืืช ื”ืื•ืžืœืœื•ืช ื‘ื›ืœ ืจื—ื‘ื™ ื”ืขื•ืœื. ืื ื™ ืžืฉื•ื›ื ืข
13:32
I'm very confident we're going to learn to live more lightly on the planet,
289
812194
4005
ืฉืื ื—ื ื• ื ืœืžื“ ืœื—ื™ื•ืช ื—ื™ื™ื ืงืœื™ืœื™ื ื™ื•ืชืจ ื‘ืขื•ืœื,
ื•ืื ื™ ื‘ื˜ื•ื— ืœื—ืœื•ื˜ื™ืŸ ืฉืžื” ืฉืื ื—ื ื• ื ืขืฉื”
13:36
and I am extremely confident that what we're going to do
290
816223
3425
13:39
with our new digital tools
291
819672
1375
ื‘ืขื–ืจืช ื”ื›ืœื™ื ื”ื“ื™ื’ื™ื˜ืœื™ื™ื ื”ื—ื“ืฉื™ื ืฉืœื ื• ื™ื”ื™ื” ื›ืœ-ื›ืš ืขืžื•ืง
13:41
is going to be so profound and so beneficial
292
821071
2992
ื•ื›ืœ-ื›ืš ืชื•ืจื ื•ืžื•ืขื™ืœ ืฉื–ื” ื™ืฉื™ื ืœืœืขื’
13:44
that it's going to make a mockery out of everything that came before.
293
824087
3484
ืืช ื›ืœ ืžื” ืฉื”ื™ื” ืงื•ื“ื.
13:47
I'm going to leave the last word
294
827595
1556
ืืช ื”ืžื™ืœื™ื ื”ืื—ืจื•ื ื•ืช ืื ื™ ืืฉืื™ืจ ืœื‘ื—ื•ืจ
13:49
to a guy who had a front-row seat for digital progress,
295
829175
2654
ืฉื”ื™ื” ืœื• ื›ืจื˜ื™ืก ื‘ืฉื•ืจื” ื”ืจืืฉื•ื ื” ืœืงื™ื“ืžื” ื”ื“ื™ื’ื™ื˜ืœื™ืช,
13:51
our old friend Ken Jennings.
296
831853
1572
ื™ื“ื™ื“ื™ื ื• ื”ื•ื•ืชื™ืง ืงืŸ ื’'ื ื™ื ื’ืก. ืื ื™ ืื™ืชื•.
13:53
I'm with him; I'm going to echo his words:
297
833449
2243
ืื ื™ ืจืง ืื—ื–ื•ืจ ืขืœ ืžื™ืœื•ืชื™ื•:
13:55
"I, for one, welcome our new computer overlords."
298
835716
2916
"ืื ื™ ื›ืฉืœืขืฆืžื™, ืžืงื‘ืœ ื‘ื‘ืจื›ื” ืืช ื”ืžื—ืฉื‘ื™ื - ืื“ื•ื ื™ื ื• ื”ื—ื“ืฉื™ื." (ืฆื—ื•ืง)
13:58
(Laughter)
299
838656
1081
13:59
Thanks very much.
300
839761
1484
ืชื•ื“ื” ืจื‘ื” ืœื›ื. (ืžื—ื™ืื•ืช ื›ืคื™ื™ื)
14:01
(Applause)
301
841269
1158
ื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