請雙擊下方英文字幕播放視頻。
00:00
Translator: Joseph Geni
Reviewer: Morton Bast
0
0
7000
譯者: Yu-Sheng Lin
審譯者: Yuguo Zhang
00:15
As it turns out, when tens of millions
of people are unemployed
1
15648
3580
當數以千萬計的勞工
處於失業或是低度就業的狀況發生時
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
就會有不少人會對科技如何影響勞工這個議題有興趣
00:24
to the labor force.
4
24000
1162
而當我開始檢視這個議題, 赫然發現
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
大家關切的主題是正確的
00:30
and at the same time,
it's missing the point entirely.
7
30803
2825
但又同時全然的地忽視了關鍵要點。
00:33
The topic that it's focused on,
8
33652
1541
在這個主題上所提出的問題, 是關於
00:35
the question is whether or not all these
digital technologies are affecting
9
35217
4483
這些數位科技是否影響了人們謀生的能力?
00:39
people's ability to earn a living,
10
39724
2017
或者, 換個說法就是
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
機器人是否正在搶走人類的工作機會?
00:45
And there's some evidence that they are.
13
45887
1937
有一些證據顯示的確如此
00:47
The Great Recession ended
when American GDP resumed
14
47848
4045
大蕭條(2008~2012)結束時, 美國的 GDP 恢復了
00:51
its kind of slow, steady march upward,
15
51917
2867
緩慢步調的上昇, 其他的一些
00:54
and some other economic indicators
also started to rebound,
16
54808
3270
經濟指標也開始反彈,看起來
00:58
and they got kind of healthy
kind of quickly.
17
58102
2293
比較健康也比較迅速了。企業的獲利
01:00
Corporate profits are quite high;
18
60419
2167
是相當高的。事實上,如果把銀行業也包含進來
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
這些數值比以往任何時候都來得高。
01:06
And business investment
in gear -- in equipment
21
66545
3487
企業在工具與設備的投資
還有硬體和軟體方面, 都處於歷史新高。
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
所以企業都在拿出支票本花錢投資
01:16
What they're not really doing is hiring.
24
76263
1999
但是他們並沒有真正的擴大招募員工
01:18
So this red line
25
78661
1151
這條紅線是就業人口的比率,
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
換句話說,就是處於就業年齡的美國人
真的有工作的比例
01:26
who have work.
28
86551
1386
01:27
And we see that it cratered
during the Great Recession,
29
87961
3106
我們可以看到這個比例在大蕭條時萎靡
01:31
and it hasn't started
to bounce back at all.
30
91091
2897
但是到現在都還沒有開始反彈回來
01:34
But the story is not
just a recession story.
31
94012
2919
但是這個故事並不只是關於大蕭條
01:36
The decade that we've
just been through had
32
96955
2080
十年來,我們剛剛經歷了持續性的
01:39
relatively anemic job growth
all throughout,
33
99059
3213
相對低落的就業增長,尤其是當我們
01:42
especially when we compare it
to other decades,
34
102296
2623
與過去的幾個十年進行比較時, 2000年這個十年
01:44
and the 2000s are the only time
we have on record
35
104943
3030
是唯一的一次我們經歷到,
01:47
where there were fewer people working
at the end of the decade
36
107997
3532
在十年期間的結束時的工作人口, 比十年剛開始的時候
01:51
than at the beginning.
37
111553
1402
還少的狀況. 這不是大家樂見的
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
當你用潛在就業人口的數據
01:58
versus the number of jobs in the country,
40
118391
2556
來對照國內工作數量作圖,您會看到之間的差距
02:00
you see the gap gets bigger
and bigger over time,
41
120971
3850
隨著時間越來越大,,
02:04
and then, during the Great Recession,
it opened up in a huge way.
42
124845
3310
而在大蕭條的時候差距特別顯著
我做了一些簡單的計算。我把過去的 20 年的國內生產總值增長
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
和同一期間的勞動生產率的增長
02:15
and used those in a fairly
straightforward way
46
135415
2718
用相當簡單直接的方式
02:18
to try to project how many jobs
the economy was going to need
47
138157
3023
嘗試預測維持經濟持續成長
所需要工作機會的數量, 而這是我算出的數據畫出的線
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
這是好事還是壞事?來看看政府預測的數據
02:26
This is the government's projection
51
146446
1911
關於就業人口的未來預測
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
所以如果這些預測是準確的, 這個差距不會被弭平
02:36
The problem is, I don't think
these projections are accurate.
54
156863
3026
問題是,我不認為這些預測是準確的。
02:39
In particular, I think my projection
is way too optimistic,
55
159913
3479
明白地說,我認為我的預測是太樂觀的
02:43
because when I did it,
56
163416
1447
因為當我做預測時, 我假設了未來應該會
02:44
I was assuming that the future
was kind of going to look like the past,
57
164887
4218
跟過去是相像的
02:49
with labor productivity growth,
58
169129
1669
在關於勞動生產力的成長方面,這是我不相信的會成立的假設
02:50
and that's actually not what I believe.
59
170822
1871
02:52
Because when I look around,
60
172717
1349
因為當我環顧四周,我認為我們並未考慮到那些
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
關於技術對勞動力市場的衝擊。
02:59
Just in the past couple years,
we've seen digital tools
63
179962
3971
只是在過去的幾年中,我們已經看到數位工具
03:03
display skills and abilities
that they never, ever had before,
64
183957
4233
顯示的技能和能力,遠超過以往
而且從某種角度來說, 已經吃進了人類的賴以為生的
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
就業領域. 讓我舉幾個例子。
03:13
Let me give you a couple examples.
67
193054
1926
03:15
Throughout all of history,
68
195004
1252
在過去的所有的歷史年代,如果你想要把某個文章
03:16
if you wanted something translated
from one language into another,
69
196280
3550
從一種語言翻譯成另一種,
03:19
you had to involve a human being.
70
199854
1725
必須要靠人類來做
03:21
Now we have multi-language, instantaneous,
71
201930
3128
現在我們有了多國語言的,即時的
03:25
automatic translation services
available for free
72
205082
4420
自動翻譯服務, 還是免費的
03:29
via many of our devices,
all the way down to smartphones.
73
209526
3143
經由我們使用的終端裝置, 直接在智慧手機就能用到
03:32
And if any of us have used these,
74
212693
1796
而如果有使用過這些翻譯服務,我們就會知道,
03:34
we know that they're not perfect,
but they're decent.
75
214513
3515
做得並不是完美, 但也夠得體了。
03:38
Throughout all of history,
if you wanted something written,
76
218540
2972
在過去的所有的歷史年代,如果你想要寫下一些東西,
03:41
a report or an article,
you had to involve a person.
77
221536
3337
比如一份報告或一篇文章,你必須透過人來做
不再是這樣了。這裡有一篇文章,
03:45
Not anymore.
78
225418
1153
03:46
This is an article that appeared
in Forbes online a while back,
79
226595
2973
不久前發表在富比世雜誌上, 是關於蘋果公司的收益的
03:49
about Apple's earnings.
80
229592
1176
03:50
It was written by an algorithm.
81
230792
1618
這篇文章是用演算法寫出來的
03:52
And it's not decent -- it's perfect.
82
232980
2857
寫的不止是得體而已, 而是到了完美
很多人看到這些事情會說, "那又怎樣?
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
這些都只是非常特定、 狹窄領域的任務,
04:01
and most knowledge workers
are actually generalists.
85
241391
2911
大多數的知識工作者實際上是通才,
04:04
And what they do is sit on top of a very
large body of expertise and knowledge
86
244326
4192
他們做的是, 坐擁一個由專業技能和知識組成的
龐然巨物, 這些人運用龐大的技能與知識
04:08
and they use that to react on the fly
to kind of unpredictable demands,
87
248542
3797
來隨時對無法預測的要求, 馬上做出反應
04:12
and that's very, very hard to automate."
88
252363
2120
這是非常、 非常難以自動化的工作"
就以一個最令人印象深刻的知識工作者
04:15
One of the most impressive
knowledge workers in recent memory
89
255063
2905
大家可能記得最近有一個人, 名叫肯恩 詹寧斯。
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
他在益智問答節目 "Jeopardy!" 連續贏了74次
04:24
Took home three million dollars.
92
264870
2190
把 300 萬美金的獎金帶回家。
在右邊的就是 肯恩, 比數是 三比一,
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
在與 IBM 的超級電腦 華生(Watson) 進行的
"Jeopardy!" 遊戲中被打敗了
04:35
So when we look at what technology can do
to general knowledge workers,
95
275902
3515
所以當我們在看技術會怎樣影響到
一般知識工作者的時候,我開始思考
04:39
I start to think there might not be
something so special
96
279441
3078
也許所謂的通才的特殊之處並不存在
04:42
about this idea of a generalist,
97
282543
1768
尤其是當我們開始能夠做到例如
04:44
particularly when we start doing things
like hooking Siri up to Watson,
98
284335
4330
把 Siri (蘋果手機的語音助理) 連結到 華生 (IBM的超級電腦)
04:48
and having technologies
that can understand what we're saying
99
288689
3269
並且逐漸發展一些技術, 能了解人類說話內容
04:51
and repeat speech back to us.
100
291982
1984
並且用人類語音回答我們
04:53
Now, Siri is far from perfect,
and we can make fun of her flaws,
101
293990
3903
現在,Siri 還撐不上完美, 我們也常拿它的一些差錯
來開玩笑,但是我們仍應該記住,
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
如果像 Siri 和 華生 這樣的技術的改進
是沿著 摩爾法則 的預測軌跡,他們將
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
在六年中,這些技術將不只是進步兩倍
或進步四倍,他們會比現在進步 16 倍。
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
所以我開始覺得, 很多知識工作都將會受到技術的影響
05:17
And digital technologies are not
just impacting knowledge work,
108
317352
3736
而且 數位技術不只影響知識工作而已
它們也開始在實體世界大展身手了
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
前一陣子我有機會坐上了 Google 的自動駕駛汽車
它坐起來跟聽起來一樣的酷
05:28
which is as cool as it sounds.
111
328624
2277
05:30
(Laughter)
112
330925
2188
我可以做證, 它能夠處理走走停停的路況
05:33
And I will vouch that it handled
the stop-and-go traffic on US 101
113
333137
4421
在101號公路上面, 開得非常平穩
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
總共大概有 350萬的人
在美國這裡, 以開卡車為職業謀生
05:42
in the United States;
116
342534
1151
我想這些人中, 有一部份會受到這項科技的影響
05:43
I think some of them are going
to be affected by this technology.
117
343709
3068
在目前, 人形機器人仍然還
05:46
And right now, humanoid robots
are still incredibly primitive.
118
346801
3100
非常的原始。它們會做的事情不多
05:49
They can't do very much.
119
349925
1957
05:51
But they're getting better quite quickly
120
351906
1972
但是它們發展得很快, 而且 DARPA,
05:53
and DARPA, which is the investment arm
of the Defense Department,
121
353902
3537
就是國防部的投資部門,
05:57
is trying to accelerate their trajectory.
122
357463
1977
一直試著讓他們的發展更加速。
05:59
So, in short, yeah, the droids
are coming for our jobs.
123
359464
4442
所以,簡單地說,對啦,機器人就要來搶我們的工作了。
在短期內,我們可以刺激就業增長
06:05
In the short term, we can
stimulate job growth
124
365105
2892
透過鼓勵創業, 還有投資在基礎建設上
06:08
by encouraging entrepreneurship
125
368021
2137
06:10
and by investing in infrastructure,
126
370182
1914
因為機器人目前仍然不是
06:12
because the robots today
still aren't very good at fixing bridges.
127
372120
3538
很擅長修復橋樑。
06:15
But in the not-too-long-term,
128
375682
1898
但在不用太久,我想在場的各位
06:17
I think within the lifetimes
of most of the people in this room,
129
377604
3902
在有生之年,我們將會經歷到
06:21
we're going to transition into an economy
that is very productive,
130
381530
3548
經濟型態的轉變, 一種非常具有生產力
06:25
but that just doesn't need
a lot of human workers.
131
385102
2894
但是不需要許多的人類工作者的狀況
06:28
And managing that transition
is going to be the greatest challenge
132
388020
3112
而如何管理這個轉變的發生, 將會是
我們的社會所面臨的最大挑戰。
06:31
that our society faces.
133
391156
1538
06:32
Voltaire summarized why; he said,
134
392718
1950
伏爾泰總結了其中的原因。他說,"工作讓我們避開了
06:34
"Work saves us from three great evils:
boredom, vice and need."
135
394692
5179
三個魔鬼: 無聊、 墮落, 和需要。"
06:40
But despite this challenge --
136
400430
2057
縱使有這樣的挑戰,至少就我個人來說,
06:42
personally, I'm still
a huge digital optimist,
137
402511
2912
我仍然是個超級的數位樂觀主義者,我也同時
06:45
and I am supremely confident
138
405447
2204
十分自信地認為,我們現在發展的數位技術
06:47
that the digital technologies
that we're developing now
139
407675
2588
將會帶領我們進入一個烏托邦的未來,
06:50
are going to take us
into a Utopian future,
140
410287
2650
06:52
not a dystopian future.
141
412961
1712
而不是一個 反烏托邦式的未來。要解釋為什麼,
06:54
And to explain why,
142
414697
1151
06:55
I want to pose a ridiculously
broad question.
143
415872
2579
我想要丟出一個有些過度誇張大的問題。
06:58
I want to ask:
144
418475
1151
我想問的是, 在人類歷史上
06:59
what have been the most important
developments in human history?
145
419650
3346
最重要的發展是什麼?
07:03
Now, I want to share some
of the answers that I've gotten
146
423020
2961
現在,我想分享一些我所找到的答案
來回答這個問題。這是一個很棒的問題
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
一問了就會展開無窮無盡的爭論
07:10
because some people are going to bring up
149
430618
1974
因為有些人會搬出
07:12
systems of philosophy
in both the West and the East
150
432616
3300
西方和東方的哲學的系統,
07:15
that have changed how a lot
of people think about the world.
151
435940
3223
這些的確改變了很多人看待世界的方式
07:19
And then other people will say,
152
439187
1493
然後其他人會說:"才不是這樣,真正重大的
07:20
"No, actually, the big stories,
the big developments
153
440704
2461
關鍵的發展, 是世界上主要宗教的建立
07:23
are the founding
of the world's major religions,
154
443189
2583
宗教改變了各地的文明
07:25
which have changed civilizations
and have changed and influenced
155
445796
3226
也改變並影響了無數人的一生如何度過
07:29
how countless people
are living their lives."
156
449046
2594
然後一些其他人會說,
07:31
And then some other folk will say,
157
451664
1697
07:33
"Actually, what changes civilizations,
158
453385
2390
"其實,改變文明的,改變人們觀點的,
07:35
what modifies them and what changes
people's lives are empires,
159
455799
4785
改變人們生活的
其實是帝國,在人類歷史上的重大發展
07:40
so the great developments in human history
160
460608
2405
主要是關於征服與戰爭的故事"
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
然後一些愛開玩笑的人就會跟著提出說
07:48
"Hey, don't forget about plagues!"
163
468628
1682
"嘿,別忘了還有那些瘟疫。"(笑聲)
07:50
(Laughter)
164
470334
3909
對這個問題,有一些樂觀的答案
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
比如有些人會提出的是 探索的年代(十五世紀)
對整個世界的開拓
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
其他人則將提出: 智慧方面的成就
在一些學科, 例如 數學, 就幫助人類對於
08:04
that have helped us get
a better handle on the world,
169
484623
2494
世界有更好的理解, 還有一些人會提出
08:07
and other folk will talk about periods
when there was a deep flourishing
170
487141
3440
那個 藝術與科學 深度繁榮發展
08:10
of the arts and sciences.
171
490605
1605
的時期。所以像這樣的辯論可以一直談下去
08:12
So this debate will go on and on.
172
492234
1587
08:13
It's an endless debate
173
493845
1461
這個辯論談不完, 也不會有結論
08:15
and there's no conclusive,
single answer to it.
174
495330
3233
也沒有唯一的答案。但如果你像我一樣,是個阿宅工程師
08:18
But if you're a geek like me,
175
498587
1517
你會問,"嗯,有沒有實際的資料, 資料怎麼說?"
08:20
you say, "Well, what do the data say?"
176
500128
2681
08:22
And you start to do things
177
502833
1332
那你就會開始做一些我們有興趣的事情, 像是畫圖表
08:24
like graph things
that we might be interested in --
178
504189
2684
比方全世界的人口總數,
08:26
the total worldwide
population, for example,
179
506897
3079
或是某些社會發展的數據,
08:30
or some measure of social development
180
510000
2365
08:32
or the state of advancement of a society.
181
512389
2488
或是社會進步的狀態
08:34
And you start to plot the data,
because, by this approach,
182
514901
4123
然後你開始繪製這些資料,因為,通過這樣的方式,
整個故事的全貌,在人類歷史上的大發展
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
應該會是那些造成這些圖表曲線變彎很多的
08:44
So when you do this
and when you plot the data,
185
524211
2220
所以當你這樣做了,把資料畫出圖表了
08:46
you pretty quickly come
to some weird conclusions.
186
526455
2692
你很快就會得到一些奇怪的結論
你做出的結論是,事實上,前面講的這些答案
08:49
You conclude, actually,
187
529171
1396
08:50
that none of these things
have mattered very much.
188
530591
2563
沒有一個是真正重要的。(笑聲)
08:53
(Laughter)
189
533178
3594
這些答案根本對這些圖表曲線沒有影響。(笑聲)
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
事實上只有一個故事, 一項發展
在人類的歷史上, 真正折彎了那些曲線, 而且彎了
09:05
that bent the curve,
bent it just about 90 degrees,
192
545331
3209
將近90 度,這個故事, 就是 技術。
09:08
and it is a technology story.
193
548564
2135
09:11
The steam engine and the other
associated technologies
194
551223
2770
像是蒸汽引擎, 還有其它的相關技術
09:14
of the Industrial Revolution
195
554017
2031
帶動了工業革命, 改變了整個世界
09:16
changed the world and influenced
human history so much,
196
556072
3276
對人類歷史產生的重大的影響
09:19
that in the words
of the historian Ian Morris,
197
559372
2402
套用 歷史學家 伊恩 · 莫里斯 (Ian Morris) 的話說,
09:21
"... they made mockery out of all
that had come before."
198
561798
3791
這項發展讓先前發生的其它事情都變得微不足道了
09:25
And they did this by infinitely
multiplying the power of our muscles,
199
565613
3527
這項發展, 把我們的肌肉力量 放大了無窮倍
克服了人類身體肌肉的限制
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
而現在, 我們正經歷著
09:34
is overcoming the limitations
of our individual brains
202
574104
3033
超越人類個別大腦的限制的時機
09:37
and infinitely multiplying
our mental power.
203
577161
2911
將我們的心智能力放大無窮多倍的時候
09:40
How can this not be as big a deal
204
580096
3177
這必然也是一個至少 跟克服人類的肌肉力量限制
09:43
as overcoming the limitations
of our muscles?
205
583297
2704
一樣重大的發展吧?
09:46
So at the risk of repeating
myself a little bit,
206
586025
2860
所以請原諒我又再重覆了,當我觀察到
09:48
when I look at what's going on
with digital technology these days,
207
588909
3753
這段期間內數位科技的發展
09:52
we are not anywhere near
through with this journey.
208
592686
3110
我們離這段期間的終點還很遠
09:55
And when I look at what is happening
to our economies and our societies,
209
595820
3506
而當我看到所發生的事情, 對我們經濟
還有社會所發生的影響, 我的唯一結論是
09:59
my single conclusion is that
we ain't seen nothing yet.
210
599350
3089
我們還沒看到重大的里程碑, 最好的日子還在未來。
10:02
The best days are really ahead.
211
602463
1726
10:04
Let me give you a couple examples.
212
604213
2001
讓我舉幾個例子。
經濟體並不是靠能源運作的, 也不是靠資本
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
也不是靠勞力。經濟體的運行靠的是想法。
10:11
Economies run on ideas.
215
611698
2405
所以創新的工作, 產生新的想法的工作
10:14
So the work of innovation,
the work of coming up with new ideas,
216
614127
3341
是人類所能做的 多種 最強大的
10:17
is some of the most powerful, most
fundamental work that we can do
217
617492
3698
最基本的 工作之一,這些工作是人類在經濟體裡
能做的。而這也是我們過去如何創新的方式
10:21
in an economy.
218
621214
1151
10:22
And this is kind of how
we used to do innovation.
219
622389
3118
我們會發現一大群看起來相當類似的人
10:25
We'd find a bunch of fairly
similar-looking people ...
220
625531
2976
10:28
(Laughter)
221
628531
3496
— — (笑聲) — —
我們帶他們離開原本的精英的機構,把他們放到
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
另一個精英的機構,然後等著創新的發生
10:36
and we'd wait for the innovation.
224
636171
1586
10:37
Now --
225
637781
1169
現在 — — (笑聲) — —
10:38
(Laughter)
226
638974
2429
10:41
as a white guy who spent
his whole career at MIT and Harvard,
227
641427
3488
作為一個在麻省理工學院還有哈佛度過整個職涯的白種人
10:44
I've got no problem with this.
228
644939
2026
我對這沒有什麼問題。(笑聲)
10:46
(Laughter)
229
646989
2305
10:50
But some other people do,
230
650605
1207
但一些其他人遇到了問題,他們有點像是
10:51
and they've kind of crashed the party
231
651836
1785
搞砸了派對, 而且放鬆了創新應有的規範
10:53
and loosened up
the dress code of innovation.
232
653645
2145
10:55
(Laughter)
233
655814
1032
(笑聲)
10:56
So here are the winners of a Topcoder
programming challenge,
234
656870
3200
這裡是一些 頂尖程式員寫程式大賽的優勝者
11:00
and I assure you that nobody cares
235
660094
2692
我向你保證沒有人在意
11:02
where these kids grew up,
where they went to school,
236
662810
3756
這些孩子是在哪裡長大, 在哪裡念書,
11:06
or what they look like.
237
666590
1500
或是他們的長相。所有人只會在意
11:08
All anyone cares about is the quality
of the work, the quality of the ideas.
238
668114
3843
他們工作產出的品質, 他們的點子的品質。
11:11
And over and over again,
we see this happening
239
671981
2236
一次又一次的,我們看到這種情況發生
11:14
in the technology-facilitated world.
240
674241
2524
在這個科技推動的世界
11:16
The work of innovation
is becoming more open,
241
676789
2497
創新的工作越來越開放,
更具包容性、 更透明、 和更以志業為基礎,
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
這會繼續下去, 不管 麻省理工學院和哈佛大學
的觀點,而我對這樣感到非常的快樂。
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
我偶爾會聽到,"好吧,我同意你的這個說法,
但技術仍是富裕世界的工具
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
有些事情仍不會發生,這些數位工具也不會
11:36
these digital tools are not
improving the lives
248
696554
2611
改善金字塔底部的人民的生活"。
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
我對這樣的說法有個清楚的回應: 一派胡言。
金字塔的底部的人民, 正大大受益於技術的發展。
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
經濟學家 羅伯特 · 詹森 (Robert Jensen) 做了這項很棒的研究
在前一陣子,他詳細的研究了
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
在 印度喀拉拉邦的漁村發生的事情
11:56
when they got mobile phones
for the very first time.
255
716752
2881
當行動電話第一次交到當地人手上的時候
11:59
And when you write for the Quarterly
Journal of Economics,
256
719657
2809
若你寫的文章是要刊在 經濟學季刊雜誌 的時候
12:02
you have to use very dry
and very circumspect language.
257
722490
2882
您必須使用非常乏味和非常周到的語言,
12:05
But when I read his paper,
258
725396
1262
但當我讀他的論文的時候,我覺得詹森試圖
12:06
I kind of feel Jensen
is trying to scream at us
259
726682
2207
對我們尖叫,說,你看,這是一個大題目啊。
12:08
and say, "Look, this was a big deal.
260
728913
2324
價格變穩定了,因此人們可以計畫他們的經濟生活。
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
廢棄物不僅是減少而已;根本就是沒有廢棄物。
這些村莊裡的買家和賣家的生活
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
都被明顯地改善了
現在,我不認為 詹森 只是很幸運的
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
剛好遇上了一群的村莊
碰巧在這些村莊裡 科技讓生活變得更好了
12:30
where technology made things better.
267
750122
2309
12:32
What happened instead
is he very carefully documented
268
752455
2647
實際上發生的狀況, 是他詳細地記錄了
這些一再重複發生的現像, 當技術
12:35
what happens over and over again
when technology comes for the first time
269
755126
4079
第一次進到一個環境和社會。
12:39
to an environment and a community:
270
759229
1937
人民的生活, 人民的幸福, 都顯著地提高了。
12:41
the lives of people, the welfares
of people, improve dramatically.
271
761190
3837
所以,當我看到這些證據, 我想到
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
未來我們可以有的發展空間, 我當然會變成一個
12:49
I become a huge digital optimist
274
769417
1828
超級的數位樂觀主義者, 我開始覺得,
12:51
and I start to think that this wonderful
statement from the physicist Freeman Dyson
275
771269
4576
物理學家 福利曼 戴森 說的這句話很棒
12:55
is actually not hyperbole.
276
775869
1738
他說的話並不誇張, 而是對於目前正在發生的現象的一個精準的描述。
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
我們面臨的數位化 還有科技, 都是偉大的恩賜
13:02
and we, right now,
have the great good fortune
279
782886
3047
處於這個時代的我們, 是非常幸運的
13:05
to be living at a time when
digital technology is flourishing,
280
785957
3730
能夠活在這個數位技術蓬勃發展的時期
13:09
when it is broadening and deepening
and becoming more profound
281
789711
3395
這些技術的影響越來越廣, 也越來越深
深刻地影響了整個世界
13:13
all around the world.
282
793130
1278
13:14
So, yeah, the droids are taking our jobs,
283
794432
3275
所以,是啊,機器人正在搶走我們的工作,
13:17
but focusing on that fact
misses the point entirely.
284
797731
3571
但若只著重這件事情, 就會漏掉了整件事情的重點了
13:21
The point is that then we
are freed up to do other things,
285
801326
3500
真正的重點是, 人類可以被解放出來, 做其他的事情
13:24
and what we're going to do,
I am very confident,
286
804850
2287
而我們可以做的事情, 我非常確定的說
13:27
what we're going to do is reduce poverty
287
807161
2516
我們會去做的是減少貧困和苦差事
13:29
and drudgery and misery around the world.
288
809701
2469
減少世界各地的苦難。我很有信心
13:32
I'm very confident we're going to learn
to live more lightly on the planet,
289
812194
4005
我們會學習如何在這個星球上更輕鬆的過活
我也非常的確信, 我們將會運用
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
我們的全新的數位化工具, 非常深切的
13:41
is going to be so profound
and so beneficial
292
821071
2992
並且非常良善的用它, 讓先前發生過的每個改變
13:44
that it's going to make a mockery
out of everything that came before.
293
824087
3484
相較之下都變得微不足道了。
13:47
I'm going to leave the last word
294
827595
1556
我最後有一句話, 要留給一個人
13:49
to a guy who had a front-row seat
for digital progress,
295
829175
2654
這個人在數位時代的演進, 是先驅者的地位
13:51
our old friend Ken Jennings.
296
831853
1572
就是我們的老朋友, 肯恩 詹寧斯, 我同意他的看法
13:53
I'm with him; I'm going to echo his words:
297
833449
2243
我打算這樣回應他的話:
13:55
"I, for one, welcome our new
computer overlords."
298
835716
2916
"我,代表我自己,歡迎我們的新電腦領主"。(笑聲)
13:58
(Laughter)
299
838656
1081
13:59
Thanks very much.
300
839761
1484
非常感謝。(掌聲)
14:01
(Applause)
301
841269
1158
New videos
關於本網站
本網站將向您介紹對學習英語有用的 YouTube 視頻。 您將看到來自世界各地的一流教師教授的英語課程。 雙擊每個視頻頁面上顯示的英文字幕,從那裡播放視頻。 字幕與視頻播放同步滾動。 如果您有任何意見或要求,請使用此聯繫表與我們聯繫。