1
00:00:00,388 --> 00:00:03,968
As it turns out, when tens of millions
of people are unemployed

2
00:00:03,992 --> 00:00:05,526
or underemployed,

3
00:00:05,550 --> 00:00:08,716
there's a fair amount of interest
in what technology might be doing

4
00:00:08,740 --> 00:00:09,902
to the labor force.

5
00:00:09,926 --> 00:00:11,815
And as I look at the conversation,

6
00:00:11,839 --> 00:00:15,519
it strikes me that it's focused
on exactly the right topic,

7
00:00:15,543 --> 00:00:18,368
and at the same time,
it's missing the point entirely.

8
00:00:18,392 --> 00:00:19,933
The topic that it's focused on,

9
00:00:19,957 --> 00:00:24,440
the question is whether or not all these
digital technologies are affecting

10
00:00:24,464 --> 00:00:26,481
people's ability to earn a living,

11
00:00:26,505 --> 00:00:28,490
or, to say it a little bit different way,

12
00:00:28,514 --> 00:00:30,603
are the droids taking our jobs?

13
00:00:30,627 --> 00:00:32,564
And there's some evidence that they are.

14
00:00:32,588 --> 00:00:36,633
The Great Recession ended
when American GDP resumed

15
00:00:36,657 --> 00:00:39,524
its kind of slow, steady march upward,

16
00:00:39,548 --> 00:00:42,818
and some other economic indicators
also started to rebound,

17
00:00:42,842 --> 00:00:45,135
and they got kind of healthy
kind of quickly.

18
00:00:45,159 --> 00:00:47,326
Corporate profits are quite high;

19
00:00:47,350 --> 00:00:49,246
in fact, if you include bank profits,

20
00:00:49,270 --> 00:00:51,261
they're higher than they've ever been.

21
00:00:51,285 --> 00:00:54,772
And business investment
in gear -- in equipment

22
00:00:54,796 --> 00:00:57,640
and hardware and software --
is at an all-time high.

23
00:00:57,664 --> 00:01:00,979
So the businesses are getting
out their checkbooks.

24
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What they're not really doing is hiring.

25
00:01:03,401 --> 00:01:04,552
So this red line

26
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is the employment-to-population ratio,

27
00:01:07,138 --> 00:01:11,267
in other words, the percentage
of working-age people in America

28
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who have work.

29
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And we see that it cratered
during the Great Recession,

30
00:01:15,831 --> 00:01:18,728
and it hasn't started
to bounce back at all.

31
00:01:18,752 --> 00:01:21,671
But the story is not
just a recession story.

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00:01:21,695 --> 00:01:23,775
The decade that we've
just been through had

33
00:01:23,799 --> 00:01:27,012
relatively anemic job growth
all throughout,

34
00:01:27,036 --> 00:01:29,659
especially when we compare it
to other decades,

35
00:01:29,683 --> 00:01:32,713
and the 2000s are the only time
we have on record

36
00:01:32,737 --> 00:01:36,269
where there were fewer people working
at the end of the decade

37
00:01:36,293 --> 00:01:37,695
than at the beginning.

38
00:01:37,719 --> 00:01:39,392
This is not what you want to see.

39
00:01:39,724 --> 00:01:43,107
When you graph the number
of potential employees

40
00:01:43,131 --> 00:01:45,687
versus the number of jobs in the country,

41
00:01:45,711 --> 00:01:49,561
you see the gap gets bigger
and bigger over time,

42
00:01:49,585 --> 00:01:52,895
and then, during the Great Recession,
it opened up in a huge way.

43
00:01:52,919 --> 00:01:54,379
I did some quick calculations.

44
00:01:54,403 --> 00:01:56,835
I took the last 20 years of GDP growth

45
00:01:56,859 --> 00:02:00,131
and the last 20 years
of labor-productivity growth

46
00:02:00,155 --> 00:02:02,873
and used those in a fairly
straightforward way

47
00:02:02,897 --> 00:02:05,920
to try to project how many jobs
the economy was going to need

48
00:02:05,944 --> 00:02:07,247
to keep growing,

49
00:02:07,271 --> 00:02:09,396
and this is the line that I came up with.

50
00:02:09,420 --> 00:02:11,162
Is that good or bad?

51
00:02:11,186 --> 00:02:13,097
This is the government's projection

52
00:02:13,121 --> 00:02:16,457
for the working-age
population going forward.

53
00:02:16,481 --> 00:02:21,579
So if these predictions are accurate,
that gap is not going to close.

54
00:02:21,603 --> 00:02:24,629
The problem is, I don't think
these projections are accurate.

55
00:02:24,653 --> 00:02:28,132
In particular, I think my projection
is way too optimistic,

56
00:02:28,156 --> 00:02:29,603
because when I did it,

57
00:02:29,627 --> 00:02:33,845
I was assuming that the future
was kind of going to look like the past,

58
00:02:33,869 --> 00:02:35,538
with labor productivity growth,

59
00:02:35,562 --> 00:02:37,433
and that's actually not what I believe.

60
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Because when I look around,

61
00:02:38,830 --> 00:02:41,050
I think that we ain't seen nothing yet

62
00:02:41,074 --> 00:02:44,310
when it comes to technology's
impact on the labor force.

63
00:02:44,702 --> 00:02:48,673
Just in the past couple years,
we've seen digital tools

64
00:02:48,697 --> 00:02:52,930
display skills and abilities
that they never, ever had before,

65
00:02:52,954 --> 00:02:56,464
and that kind of eat deeply
into what we human beings

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do for a living.

67
00:02:57,794 --> 00:02:59,720
Let me give you a couple examples.

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00:02:59,744 --> 00:03:00,996
Throughout all of history,

69
00:03:01,020 --> 00:03:04,570
if you wanted something translated
from one language into another,

70
00:03:04,594 --> 00:03:06,319
you had to involve a human being.

71
00:03:06,670 --> 00:03:09,798
Now we have multi-language, instantaneous,

72
00:03:09,822 --> 00:03:14,242
automatic translation services
available for free

73
00:03:14,266 --> 00:03:17,409
via many of our devices,
all the way down to smartphones.

74
00:03:17,433 --> 00:03:19,229
And if any of us have used these,

75
00:03:19,253 --> 00:03:22,768
we know that they're not perfect,
but they're decent.

76
00:03:23,280 --> 00:03:26,252
Throughout all of history,
if you wanted something written,

77
00:03:26,276 --> 00:03:29,613
a report or an article,
you had to involve a person.

78
00:03:30,158 --> 00:03:31,311
Not anymore.

79
00:03:31,335 --> 00:03:34,308
This is an article that appeared
in Forbes online a while back,

80
00:03:34,332 --> 00:03:35,508
about Apple's earnings.

81
00:03:35,532 --> 00:03:37,150
It was written by an algorithm.

82
00:03:37,720 --> 00:03:40,577
And it's not decent -- it's perfect.

83
00:03:41,749 --> 00:03:43,778
A lot of people look at this and they say,

84
00:03:43,802 --> 00:03:46,107
"OK, but those are very
specific, narrow tasks,

85
00:03:46,131 --> 00:03:49,042
and most knowledge workers
are actually generalists.

86
00:03:49,066 --> 00:03:53,258
And what they do is sit on top of a very
large body of expertise and knowledge

87
00:03:53,282 --> 00:03:57,079
and they use that to react on the fly
to kind of unpredictable demands,

88
00:03:57,103 --> 00:03:59,223
and that's very, very hard to automate."

89
00:03:59,803 --> 00:04:02,708
One of the most impressive
knowledge workers in recent memory

90
00:04:02,732 --> 00:04:04,253
is a guy named Ken Jennings.

91
00:04:04,277 --> 00:04:09,011
He won the quiz show
"Jeopardy!" 74 times in a row.

92
00:04:09,610 --> 00:04:11,800
Took home three million dollars.

93
00:04:11,824 --> 00:04:15,595
That's Ken on the right,
getting beat three-to-one

94
00:04:15,619 --> 00:04:19,996
by Watson, the Jeopardy-playing
supercomputer from IBM.

95
00:04:20,642 --> 00:04:24,157
So when we look at what technology can do
to general knowledge workers,

96
00:04:24,181 --> 00:04:27,259
I start to think there might not be
something so special

97
00:04:27,283 --> 00:04:29,051
about this idea of a generalist,

98
00:04:29,075 --> 00:04:33,405
particularly when we start doing things
like hooking Siri up to Watson,

99
00:04:33,429 --> 00:04:36,698
and having technologies
that can understand what we're saying

100
00:04:36,722 --> 00:04:38,706
and repeat speech back to us.

101
00:04:38,730 --> 00:04:42,633
Now, Siri is far from perfect,
and we can make fun of her flaws,

102
00:04:42,657 --> 00:04:44,156
but we should also keep in mind

103
00:04:44,180 --> 00:04:49,544
that if technologies like Siri and Watson
improve along a Moore's law trajectory,

104
00:04:49,568 --> 00:04:51,090
which they will,

105
00:04:51,114 --> 00:04:54,704
in six years, they're not going to be two
times better or four times better,

106
00:04:54,728 --> 00:04:58,198
they'll be 16 times better
than they are right now.

107
00:04:58,222 --> 00:05:02,068
So I start to think a lot of knowledge
work is going to be affected by this.

108
00:05:02,092 --> 00:05:05,828
And digital technologies are not
just impacting knowledge work,

109
00:05:05,852 --> 00:05:09,591
they're starting to flex their muscles
in the physical world as well.

110
00:05:09,615 --> 00:05:13,340
I had the chance a little while back
to ride in the Google autonomous car,

111
00:05:13,364 --> 00:05:15,641
which is as cool as it sounds.

112
00:05:15,665 --> 00:05:17,853
(Laughter)

113
00:05:17,877 --> 00:05:22,298
And I will vouch that it handled
the stop-and-go traffic on US 101

114
00:05:22,322 --> 00:05:23,575
very smoothly.

115
00:05:23,599 --> 00:05:27,250
There are about three and a half million
people who drive trucks for a living

116
00:05:27,274 --> 00:05:28,425
in the United States;

117
00:05:28,449 --> 00:05:31,517
I think some of them are going
to be affected by this technology.

118
00:05:31,541 --> 00:05:34,641
And right now, humanoid robots
are still incredibly primitive.

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00:05:34,665 --> 00:05:36,622
They can't do very much.

120
00:05:36,646 --> 00:05:38,618
But they're getting better quite quickly

121
00:05:38,642 --> 00:05:42,179
and DARPA, which is the investment arm
of the Defense Department,

122
00:05:42,203 --> 00:05:44,180
is trying to accelerate their trajectory.

123
00:05:44,204 --> 00:05:48,646
So, in short, yeah, the droids
are coming for our jobs.

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00:05:49,845 --> 00:05:52,737
In the short term, we can
stimulate job growth

125
00:05:52,761 --> 00:05:54,898
by encouraging entrepreneurship

126
00:05:54,922 --> 00:05:56,836
and by investing in infrastructure,

127
00:05:56,860 --> 00:06:00,398
because the robots today
still aren't very good at fixing bridges.

128
00:06:00,422 --> 00:06:02,320
But in the not-too-long-term,

129
00:06:02,344 --> 00:06:06,246
I think within the lifetimes
of most of the people in this room,

130
00:06:06,270 --> 00:06:09,818
we're going to transition into an economy
that is very productive,

131
00:06:09,842 --> 00:06:12,736
but that just doesn't need
a lot of human workers.

132
00:06:12,760 --> 00:06:15,872
And managing that transition
is going to be the greatest challenge

133
00:06:15,896 --> 00:06:17,434
that our society faces.

134
00:06:17,458 --> 00:06:19,408
Voltaire summarized why; he said,

135
00:06:19,432 --> 00:06:24,611
"Work saves us from three great evils:
boredom, vice and need."

136
00:06:25,170 --> 00:06:27,227
But despite this challenge --

137
00:06:27,251 --> 00:06:30,163
personally, I'm still
a huge digital optimist,

138
00:06:30,187 --> 00:06:32,391
and I am supremely confident

139
00:06:32,415 --> 00:06:35,003
that the digital technologies
that we're developing now

140
00:06:35,027 --> 00:06:37,677
are going to take us
into a Utopian future,

141
00:06:37,701 --> 00:06:39,413
not a dystopian future.

142
00:06:39,437 --> 00:06:40,588
And to explain why,

143
00:06:40,612 --> 00:06:43,191
I want to pose a ridiculously
broad question.

144
00:06:43,215 --> 00:06:44,366
I want to ask:

145
00:06:44,390 --> 00:06:47,736
what have been the most important
developments in human history?

146
00:06:47,760 --> 00:06:50,721
Now, I want to share some
of the answers that I've gotten

147
00:06:50,745 --> 00:06:52,142
in response to this question.

148
00:06:52,166 --> 00:06:55,334
It's a wonderful question to ask
and start an endless debate about,

149
00:06:55,358 --> 00:06:57,332
because some people are going to bring up

150
00:06:57,356 --> 00:07:00,656
systems of philosophy
in both the West and the East

151
00:07:00,680 --> 00:07:03,903
that have changed how a lot
of people think about the world.

152
00:07:03,927 --> 00:07:05,420
And then other people will say,

153
00:07:05,444 --> 00:07:07,905
"No, actually, the big stories,
the big developments

154
00:07:07,929 --> 00:07:10,512
are the founding
of the world's major religions,

155
00:07:10,536 --> 00:07:13,762
which have changed civilizations
and have changed and influenced

156
00:07:13,786 --> 00:07:16,380
how countless people
are living their lives."

157
00:07:16,404 --> 00:07:18,101
And then some other folk will say,

158
00:07:18,125 --> 00:07:20,515
"Actually, what changes civilizations,

159
00:07:20,539 --> 00:07:25,324
what modifies them and what changes
people's lives are empires,

160
00:07:25,348 --> 00:07:27,753
so the great developments in human history

161
00:07:27,777 --> 00:07:30,539
are stories of conquest and of war."

162
00:07:30,563 --> 00:07:33,344
And then some cheery soul
usually always pipes up and says,

163
00:07:33,368 --> 00:07:35,050
"Hey, don't forget about plagues!"

164
00:07:35,074 --> 00:07:38,983
(Laughter)

165
00:07:39,007 --> 00:07:41,530
There are some optimistic
answers to this question,

166
00:07:41,554 --> 00:07:43,968
so some people will bring up
the Age of Exploration

167
00:07:43,992 --> 00:07:45,537
and the opening up of the world.

168
00:07:45,561 --> 00:07:49,339
Others will talk about intellectual
achievements in disciplines like math

169
00:07:49,363 --> 00:07:51,857
that have helped us get
a better handle on the world,

170
00:07:51,881 --> 00:07:55,321
and other folk will talk about periods
when there was a deep flourishing

171
00:07:55,345 --> 00:07:56,950
of the arts and sciences.

172
00:07:56,974 --> 00:07:58,561
So this debate will go on and on.

173
00:07:58,585 --> 00:08:00,046
It's an endless debate

174
00:08:00,070 --> 00:08:03,303
and there's no conclusive,
single answer to it.

175
00:08:03,327 --> 00:08:04,844
But if you're a geek like me,

176
00:08:04,868 --> 00:08:07,549
you say, "Well, what do the data say?"

177
00:08:07,573 --> 00:08:08,905
And you start to do things

178
00:08:08,929 --> 00:08:11,613
like graph things
that we might be interested in --

179
00:08:11,637 --> 00:08:14,716
the total worldwide
population, for example,

180
00:08:14,740 --> 00:08:17,105
or some measure of social development

181
00:08:17,129 --> 00:08:19,617
or the state of advancement of a society.

182
00:08:19,641 --> 00:08:23,764
And you start to plot the data,
because, by this approach,

183
00:08:23,788 --> 00:08:26,393
the big stories, the big
developments in human history,

184
00:08:26,417 --> 00:08:28,927
are the ones that will bend
these curves a lot.

185
00:08:28,951 --> 00:08:31,171
So when you do this
and when you plot the data,

186
00:08:31,195 --> 00:08:33,887
you pretty quickly come
to some weird conclusions.

187
00:08:33,911 --> 00:08:35,307
You conclude, actually,

188
00:08:35,331 --> 00:08:37,894
that none of these things
have mattered very much.

189
00:08:37,918 --> 00:08:41,512
(Laughter)

190
00:08:41,980 --> 00:08:45,333
They haven't done
a darn thing to the curves.

191
00:08:45,357 --> 00:08:50,047
There has been one story,
one development in human history

192
00:08:50,071 --> 00:08:53,280
that bent the curve,
bent it just about 90 degrees,

193
00:08:53,304 --> 00:08:55,439
and it is a technology story.

194
00:08:55,963 --> 00:08:58,733
The steam engine and the other
associated technologies

195
00:08:58,757 --> 00:09:00,788
of the Industrial Revolution

196
00:09:00,812 --> 00:09:04,088
changed the world and influenced
human history so much,

197
00:09:04,112 --> 00:09:06,514
that in the words
of the historian Ian Morris,

198
00:09:06,538 --> 00:09:10,329
"... they made mockery out of all
that had come before."

199
00:09:10,353 --> 00:09:13,880
And they did this by infinitely
multiplying the power of our muscles,

200
00:09:13,904 --> 00:09:16,298
overcoming the limitations of our muscles.

201
00:09:16,322 --> 00:09:18,820
Now, what we're in the middle of now

202
00:09:18,844 --> 00:09:21,877
is overcoming the limitations
of our individual brains

203
00:09:21,901 --> 00:09:24,812
and infinitely multiplying
our mental power.

204
00:09:24,836 --> 00:09:28,013
How can this not be as big a deal

205
00:09:28,037 --> 00:09:30,741
as overcoming the limitations
of our muscles?

206
00:09:30,765 --> 00:09:33,625
So at the risk of repeating
myself a little bit,

207
00:09:33,649 --> 00:09:37,402
when I look at what's going on
with digital technology these days,

208
00:09:37,426 --> 00:09:40,536
we are not anywhere near
through with this journey.

209
00:09:40,560 --> 00:09:44,066
And when I look at what is happening
to our economies and our societies,

210
00:09:44,090 --> 00:09:47,179
my single conclusion is that
we ain't seen nothing yet.

211
00:09:47,203 --> 00:09:48,929
The best days are really ahead.

212
00:09:48,953 --> 00:09:50,954
Let me give you a couple examples.

213
00:09:50,978 --> 00:09:53,351
Economies don't run on energy.

214
00:09:53,375 --> 00:09:56,414
They don't run on capital,
they don't run on labor.

215
00:09:56,438 --> 00:09:58,843
Economies run on ideas.

216
00:09:58,867 --> 00:10:02,208
So the work of innovation,
the work of coming up with new ideas,

217
00:10:02,232 --> 00:10:05,930
is some of the most powerful, most
fundamental work that we can do

218
00:10:05,954 --> 00:10:07,105
in an economy.

219
00:10:07,129 --> 00:10:10,247
And this is kind of how
we used to do innovation.

220
00:10:10,271 --> 00:10:13,247
We'd find a bunch of fairly
similar-looking people ...

221
00:10:13,271 --> 00:10:16,767
(Laughter)

222
00:10:16,791 --> 00:10:18,784
We'd take them out of elite institutions,

223
00:10:18,808 --> 00:10:20,887
we'd put them into other
elite institutions

224
00:10:20,911 --> 00:10:22,497
and we'd wait for the innovation.

225
00:10:22,521 --> 00:10:23,690
Now --

226
00:10:23,714 --> 00:10:26,143
(Laughter)

227
00:10:26,167 --> 00:10:29,655
as a white guy who spent
his whole career at MIT and Harvard,

228
00:10:29,679 --> 00:10:31,705
I've got no problem with this.

229
00:10:31,729 --> 00:10:34,034
(Laughter)

230
00:10:35,345 --> 00:10:36,552
But some other people do,

231
00:10:36,576 --> 00:10:38,361
and they've kind of crashed the party

232
00:10:38,385 --> 00:10:40,530
and loosened up
the dress code of innovation.

233
00:10:40,554 --> 00:10:41,586
(Laughter)

234
00:10:41,610 --> 00:10:44,810
So here are the winners of a Topcoder
programming challenge,

235
00:10:44,834 --> 00:10:47,526
and I assure you that nobody cares

236
00:10:47,550 --> 00:10:51,306
where these kids grew up,
where they went to school,

237
00:10:51,330 --> 00:10:52,830
or what they look like.

238
00:10:52,854 --> 00:10:56,697
All anyone cares about is the quality
of the work, the quality of the ideas.

239
00:10:56,721 --> 00:10:58,957
And over and over again,
we see this happening

240
00:10:58,981 --> 00:11:01,505
in the technology-facilitated world.

241
00:11:01,529 --> 00:11:04,026
The work of innovation
is becoming more open,

242
00:11:04,050 --> 00:11:07,699
more inclusive, more transparent
and more merit-based,

243
00:11:07,723 --> 00:11:11,421
and that's going to continue no matter
what MIT and Harvard think of it,

244
00:11:11,445 --> 00:11:14,010
and I couldn't be happier
about that development.

245
00:11:14,349 --> 00:11:16,804
I hear once in a while,
"OK, I'll grant you that,

246
00:11:16,828 --> 00:11:19,847
but technology is still a tool
for the rich world,

247
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and what's not happening,

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these digital tools are not
improving the lives

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of people at the bottom of the pyramid."

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And I want to say to that
very clearly: nonsense.

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The bottom of the pyramid is benefiting
hugely from technology.

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The economist Robert Jensen
did this wonderful study a while back

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where he watched, in great detail,

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what happened to the fishing
villages of Kerala, India,

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when they got mobile phones
for the very first time.

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And when you write for the Quarterly
Journal of Economics,

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you have to use very dry
and very circumspect language.

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But when I read his paper,

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I kind of feel Jensen
is trying to scream at us

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and say, "Look, this was a big deal.

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Prices stabilized, so people
could plan their economic lives.

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Waste was not reduced --
it was eliminated.

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And the lives of both
the buyers and the sellers

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in these villages measurably improved."

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Now, what I don't think
is that Jensen got extremely lucky

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and happened to land
in the one set of villages

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where technology made things better.

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What happened instead
is he very carefully documented

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what happens over and over again
when technology comes for the first time

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to an environment and a community:

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the lives of people, the welfares
of people, improve dramatically.

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So as I look around at all the evidence

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and I think about the room
that we have ahead of us,

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I become a huge digital optimist

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and I start to think that this wonderful
statement from the physicist Freeman Dyson

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is actually not hyperbole.

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This is an accurate assessment
of what's going on.

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Our technologies are great gifts,

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and we, right now,
have the great good fortune

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to be living at a time when
digital technology is flourishing,

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when it is broadening and deepening
and becoming more profound

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all around the world.

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So, yeah, the droids are taking our jobs,

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but focusing on that fact
misses the point entirely.

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The point is that then we
are freed up to do other things,

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and what we're going to do,
I am very confident,

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what we're going to do is reduce poverty

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and drudgery and misery around the world.

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I'm very confident we're going to learn
to live more lightly on the planet,

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and I am extremely confident
that what we're going to do

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with our new digital tools

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is going to be so profound
and so beneficial

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that it's going to make a mockery
out of everything that came before.

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I'm going to leave the last word

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to a guy who had a front-row seat
for digital progress,

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our old friend Ken Jennings.

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I'm with him; I'm going to echo his words:

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"I, for one, welcome our new
computer overlords."

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(Laughter)

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Thanks very much.

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(Applause)