Andrew McAfee: Are droids taking our jobs?

162,347 views ・ 2012-09-24

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00:00
Translator: Joseph Geni Reviewer: Morton Bast
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譯者: Yu-Sheng Lin 審譯者: Yuguo Zhang
00:15
As it turns out, when tens of millions of people are unemployed
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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,
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00:20
there's a fair amount of interest in what technology might be doing
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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.
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而當我開始檢視這個議題, 赫然發現
00:25
And as I look at the conversation,
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00:27
it strikes me that it's focused on exactly the right topic,
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大家關切的主題是正確的
00:30
and at the same time, it's missing the point entirely.
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但又同時全然的地忽視了關鍵要點。
00:33
The topic that it's focused on,
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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
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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,
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或者, 換個說法就是
00:41
or, to say it a little bit different way,
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00:43
are the droids taking our jobs?
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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.
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有一些證據顯示的確如此
00:47
The Great Recession ended when American GDP resumed
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大蕭條(2008~2012)結束時, 美國的 GDP 恢復了
00:51
its kind of slow, steady march upward,
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緩慢步調的上昇, 其他的一些
00:54
and some other economic indicators also started to rebound,
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經濟指標也開始反彈,看起來
00:58
and they got kind of healthy kind of quickly.
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比較健康也比較迅速了。企業的獲利
01:00
Corporate profits are quite high;
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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,
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01:04
they're higher than they've ever been.
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這些數值比以往任何時候都來得高。
01:06
And business investment in gear -- in equipment
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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.
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01:12
So the businesses are getting out their checkbooks.
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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.
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但是他們並沒有真正的擴大招募員工
01:18
So this red line
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這條紅線是就業人口的比率,
01:19
is the employment-to-population ratio,
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01:22
in other words, the percentage of working-age people in America
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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.
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01:27
And we see that it cratered during the Great Recession,
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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.
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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.
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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
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十年來,我們剛剛經歷了持續性的
01:39
relatively anemic job growth all throughout,
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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,
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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
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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
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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.
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還少的狀況. 這不是大家樂見的
01:52
This is not what you want to see.
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01:54
When you graph the number of potential employees
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當你用潛在就業人口的數據
01:58
versus the number of jobs in the country,
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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,
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隨著時間越來越大,,
02:04
and then, during the Great Recession, it opened up in a huge way.
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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.
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02:09
I took the last 20 years of GDP growth
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02:12
and the last 20 years of labor-productivity growth
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和同一期間的勞動生產率的增長
02:15
and used those in a fairly straightforward way
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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
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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,
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02:22
and this is the line that I came up with.
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02:24
Is that good or bad?
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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
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關於就業人口的未來預測
02:28
for the working-age population going forward.
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02:31
So if these predictions are accurate, that gap is not going to close.
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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.
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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,
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明白地說,我認為我的預測是太樂觀的
02:43
because when I did it,
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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,
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跟過去是相像的
02:49
with labor productivity growth,
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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.
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02:52
Because when I look around,
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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
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02:56
when it comes to technology's impact on the labor force.
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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
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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,
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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
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03:11
do for a living.
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就業領域. 讓我舉幾個例子。
03:13
Let me give you a couple examples.
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03:15
Throughout all of history,
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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,
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從一種語言翻譯成另一種,
03:19
you had to involve a human being.
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必須要靠人類來做
03:21
Now we have multi-language, instantaneous,
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現在我們有了多國語言的,即時的
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automatic translation services available for free
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自動翻譯服務, 還是免費的
03:29
via many of our devices, all the way down to smartphones.
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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,
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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.
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做得並不是完美, 但也夠得體了。
03:38
Throughout all of history, if you wanted something written,
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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.
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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.
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03:46
This is an article that appeared in Forbes online a while back,
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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.
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03:50
It was written by an algorithm.
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這篇文章是用演算法寫出來的
03:52
And it's not decent -- it's perfect.
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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,
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"OK, but those are very specific, narrow tasks,
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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.
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大多數的知識工作者實際上是通才,
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And what they do is sit on top of a very large body of expertise and knowledge
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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,
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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."
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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
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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.
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04:19
He won the quiz show "Jeopardy!" 74 times in a row.
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他在益智問答節目 "Jeopardy!" 連續贏了74次
04:24
Took home three million dollars.
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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
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by Watson, the Jeopardy-playing supercomputer from IBM.
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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,
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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
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也許所謂的通才的特殊之處並不存在
04:42
about this idea of a generalist,
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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,
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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
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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.
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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,
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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
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04:59
that if technologies like Siri and Watson improve along a Moore's law trajectory,
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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,
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05:06
in six years, they're not going to be two times better or four times better,
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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.
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05:13
So I start to think a lot of knowledge work is going to be affected by this.
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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,
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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.
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05:24
I had the chance a little while back to ride in the Google autonomous car,
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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.
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05:30
(Laughter)
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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
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在101號公路上面, 開得非常平穩
05:37
very smoothly.
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05:38
There are about three and a half million people who drive trucks for a living
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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;
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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.
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在目前, 人形機器人仍然還
05:46
And right now, humanoid robots are still incredibly primitive.
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非常的原始。它們會做的事情不多
05:49
They can't do very much.
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05:51
But they're getting better quite quickly
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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,
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就是國防部的投資部門,
05:57
is trying to accelerate their trajectory.
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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.
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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
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透過鼓勵創業, 還有投資在基礎建設上
06:08
by encouraging entrepreneurship
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06:10
and by investing in infrastructure,
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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.
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很擅長修復橋樑。
06:15
But in the not-too-long-term,
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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,
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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,
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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.
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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
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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.
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06:32
Voltaire summarized why; he said,
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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."
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三個魔鬼: 無聊、 墮落, 和需要。"
06:40
But despite this challenge --
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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,
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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
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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
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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,
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06:52
not a dystopian future.
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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,
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06:55
I want to pose a ridiculously broad question.
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我想要丟出一個有些過度誇張大的問題。
06:58
I want to ask:
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我想問的是, 在人類歷史上
06:59
what have been the most important developments in human history?
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最重要的發展是什麼?
07:03
Now, I want to share some of the answers that I've gotten
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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.
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07:07
It's a wonderful question to ask and start an endless debate about,
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一問了就會展開無窮無盡的爭論
07:10
because some people are going to bring up
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因為有些人會搬出
07:12
systems of philosophy in both the West and the East
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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.
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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,
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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
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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,
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宗教改變了各地的文明
07:25
which have changed civilizations and have changed and influenced
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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."
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然後一些其他人會說,
07:31
And then some other folk will say,
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07:33
"Actually, what changes civilizations,
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"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,
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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
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主要是關於征服與戰爭的故事"
07:43
are stories of conquest and of war."
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07:45
And then some cheery soul usually always pipes up and says,
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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!"
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"嘿,別忘了還有那些瘟疫。"(笑聲)
07:50
(Laughter)
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對這個問題,有一些樂觀的答案
07:54
There are some optimistic answers to this question,
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07:56
so some people will bring up the Age of Exploration
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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.
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08:00
Others will talk about intellectual achievements in disciplines like math
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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,
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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
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那個 藝術與科學 深度繁榮發展
08:10
of the arts and sciences.
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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.
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08:13
It's an endless debate
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這個辯論談不完, 也不會有結論
08:15
and there's no conclusive, single answer to it.
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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,
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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?"
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08:22
And you start to do things
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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 --
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比方全世界的人口總數,
08:26
the total worldwide population, for example,
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或是某些社會發展的數據,
08:30
or some measure of social development
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08:32
or the state of advancement of a society.
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或是社會進步的狀態
08:34
And you start to plot the data, because, by this approach,
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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,
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08:41
are the ones that will bend these curves a lot.
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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,
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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.
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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,
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08:50
that none of these things have mattered very much.
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沒有一個是真正重要的。(笑聲)
08:53
(Laughter)
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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.
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09:00
There has been one story, one development in human history
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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,
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將近90 度,這個故事, 就是 技術。
09:08
and it is a technology story.
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09:11
The steam engine and the other associated technologies
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像是蒸汽引擎, 還有其它的相關技術
09:14
of the Industrial Revolution
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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,
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對人類歷史產生的重大的影響
09:19
that in the words of the historian Ian Morris,
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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."
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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,
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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.
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09:31
Now, what we're in the middle of now
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而現在, 我們正經歷著
09:34
is overcoming the limitations of our individual brains
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超越人類個別大腦的限制的時機
09:37
and infinitely multiplying our mental power.
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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
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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?
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一樣重大的發展吧?
09:46
So at the risk of repeating myself a little bit,
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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,
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這段期間內數位科技的發展
09:52
we are not anywhere near through with this journey.
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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,
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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.
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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.
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10:04
Let me give you a couple examples.
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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.
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10:08
They don't run on capital, they don't run on labor.
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也不是靠勞力。經濟體的運行靠的是想法。
10:11
Economies run on ideas.
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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,
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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
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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.
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10:22
And this is kind of how we used to do innovation.
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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 ...
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10:28
(Laughter)
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— — (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,
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10:34
we'd put them into other elite institutions
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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.
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10:37
Now --
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現在 — — (笑聲) — —
10:38
(Laughter)
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10:41
as a white guy who spent his whole career at MIT and Harvard,
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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.
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我對這沒有什麼問題。(笑聲)
10:46
(Laughter)
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10:50
But some other people do,
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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
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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.
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10:55
(Laughter)
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(笑聲)
10:56
So here are the winners of a Topcoder programming challenge,
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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
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我向你保證沒有人在意
11:02
where these kids grew up, where they went to school,
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這些孩子是在哪裡長大, 在哪裡念書,
11:06
or what they look like.
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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.
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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
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一次又一次的,我們看到這種情況發生
11:14
in the technology-facilitated world.
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在這個科技推動的世界
11:16
The work of innovation is becoming more open,
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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,
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11:22
and that's going to continue no matter what MIT and Harvard think of it,
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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.
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11:29
I hear once in a while, "OK, I'll grant you that,
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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,
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11:35
and what's not happening,
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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
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改善金字塔底部的人民的生活"。
11:39
of people at the bottom of the pyramid."
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11:41
And I want to say to that very clearly: nonsense.
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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.
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11:47
The economist Robert Jensen did this wonderful study a while back
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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,
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11:53
what happened to the fishing villages of Kerala, India,
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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.
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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,
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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.
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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,
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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
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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.
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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.
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12:14
Waste was not reduced -- it was eliminated.
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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
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12:21
in these villages measurably improved."
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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
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12:27
and happened to land in the one set of villages
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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.
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12:32
What happened instead is he very carefully documented
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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
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第一次進到一個環境和社會。
12:39
to an environment and a community:
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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.
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所以,當我看到這些證據, 我想到
12:45
So as I look around at all the evidence
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12:46
and I think about the room that we have ahead of us,
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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
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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
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物理學家 福利曼 戴森 說的這句話很棒
12:55
is actually not hyperbole.
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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.
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13:00
Our technologies are great gifts,
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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
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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,
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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
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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.
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13:14
So, yeah, the droids are taking our jobs,
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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.
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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,
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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,
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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
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我們會去做的是減少貧困和苦差事
13:29
and drudgery and misery around the world.
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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,
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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
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13:39
with our new digital tools
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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
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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.
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相較之下都變得微不足道了。
13:47
I'm going to leave the last word
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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,
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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.
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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:
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我打算這樣回應他的話:
13:55
"I, for one, welcome our new computer overlords."
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"我,代表我自己,歡迎我們的新電腦領主"。(笑聲)
13:58
(Laughter)
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13:59
Thanks very much.
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非常感謝。(掌聲)
14:01
(Applause)
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