Andrew McAfee: Are droids taking our jobs?

162,289 views ・ 2012-09-24

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00:00
Translator: Joseph Geni Reviewer: Morton Bast
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翻译人员: Yi Shao 校对人员: Gao Popol
00:15
As it turns out, when tens of millions of people are unemployed
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事实上,当成千上万的人
没有工作或者被大材小用时
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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人们就去关注科技对劳动力的影响。
00:24
to the labor force.
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我看到这方面的新闻与报导之后发现
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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它们关注的主题都没有问题
00:30
and at the same time, it's missing the point entirely.
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但却彻底错过了重点。
00:33
The topic that it's focused on,
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它们关注的主题是,
00:35
the question is whether or not all these digital technologies are affecting
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数码科技会不会影响人们
00:39
people's ability to earn a living,
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谋生的能力,换句话说,
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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就是机器是不是抢走了我们的工作?
00:45
And there's some evidence that they are.
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有证据显示这样的情况的确存在。
00:47
The Great Recession ended when American GDP resumed
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大萧条结束时
00:51
its kind of slow, steady march upward,
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美国的GDP恢复了缓慢稳定的增长,
00:54
and some other economic indicators also started to rebound,
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一些其它经济指标也开始快速健康地回升,
00:58
and they got kind of healthy kind of quickly.
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企业利润很高。
01:00
Corporate profits are quite high;
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事实上,如果算上银行利润,
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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企业利润处于有史以来的最高水平。
01:06
And business investment in gear -- in equipment
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企业在设备、机械、硬件和软件的投资
也处于历史最高水平。
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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所以企业虽然在花钱
01:16
What they're not really doing is hiring.
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却没有雇人。
01:18
So this red line
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这条红线是就业人数和人口的比例,
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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换句话说就是美国处于工作年龄的人口中
有工作人数的比例。
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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我们可以看到大萧条期间这一比例显著下降,
01:31
and it hasn't started to bounce back at all.
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完全没有开始回升的迹象。
01:34
But the story is not just a recession story.
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这一现象不仅仅存在于萧条时期。
01:36
The decade that we've just been through had
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十年之内工作数量的增长微乎其微
01:39
relatively anemic job growth all throughout,
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和其它的十年比尤其如此
01:42
especially when we compare it to other decades,
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事实上,在二十一世纪的第一个十年中
01:44
and the 2000s are the only time we have on record
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2009年的就业人数少于2000年
01:47
where there were fewer people working at the end of the decade
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这种情况有记录以来第一次发生。
01:51
than at the beginning.
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是我们不希望看到的趋势。
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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如果比较潜在雇员和
01:58
versus the number of jobs in the country,
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工作机会的数量,你会发现
02:00
you see the gap gets bigger and bigger over time,
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两者之间的差距随着时间的推移越来越大
02:04
and then, during the Great Recession, it opened up in a huge way.
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在大萧条期间,这种距离更是显著拉大。
我进行了一些计算。我直接运用过去二十年GDP增长
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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和劳动生产率增长的数据
02:15
and used those in a fairly straightforward way
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尝试预测
02:18
to try to project how many jobs the economy was going to need
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我们需要多少工作机会才能保证
经济的持续增长,最终的结果就是这条曲线。
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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这个结果是好是坏?这是政府
02:26
This is the government's projection
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对适龄工作人口增长的预测。
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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如果这些预测是准确的,两者之间的差距会保持下去。
02:36
The problem is, I don't think these projections are accurate.
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问题是,我认为这些预测并不准确。
02:39
In particular, I think my projection is way too optimistic,
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不幸的是,我认为我的预测过于乐观了
02:43
because when I did it,
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因为我的预测建立在
02:44
I was assuming that the future was kind of going to look like the past,
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劳动生产率增长速率和过去持平的假设上
02:49
with labor productivity growth,
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但我不认为事情会这样发展
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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因为当我环顾四周时,我认为我们还没有意识到
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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科技对劳动力的影响。
02:59
Just in the past couple years, we've seen digital tools
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近些年来,我们见证了数码工具
03:03
display skills and abilities that they never, ever had before,
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展示出以前从未有过的技能和能力
并且对人类生活影响很大。
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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请允许我举几个例子。
03:13
Let me give you a couple examples.
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03:15
Throughout all of history,
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有史以来,如果你需要把一些文字
03:16
if you wanted something translated from one language into another,
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从一种语言翻译成另外一种语言,
03:19
you had to involve a human being.
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必须有人类参与。
03:21
Now we have multi-language, instantaneous,
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现在我们可以通过包括智能手机在内的
03:25
automatic translation services available for free
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各种电子设备
03:29
via many of our devices, all the way down to smartphones.
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使用免费的多语言的即时自动翻译服务。
03:32
And if any of us have used these,
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如果你使用过这这种服务,你就会知道
03:34
we know that they're not perfect, but they're decent.
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尽管并不完美,他们已经非常不错了。
03:38
Throughout all of history, if you wanted something written,
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有史以来,如果你想写一篇
03:41
a report or an article, you had to involve a person.
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报告或者文章,必须有人类参与。
现在不用了。这是一篇不久以前
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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《福布斯》杂志刊登的有关苹果公司收益的文章。
03:49
about Apple's earnings.
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03:50
It was written by an algorithm.
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由一个算法撰写。
03:52
And it's not decent -- it's perfect.
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这回不仅是不错了,简直是完美。
很多人看到这一现象以后说,“好吧,
03:57
A lot of people look at this and they say,
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03:59
"OK, but those are very specific, narrow tasks,
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但这些都是具体的、针对性强的任务,
04:01
and most knowledge workers are actually generalists.
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而大多数知识型人才都是通才,
04:04
And what they do is sit on top of a very large body of expertise and knowledge
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他们拥有很多
技能和知识并运用它们
04:08
and they use that to react on the fly to kind of unpredictable demands,
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随时随地地应对不可预测的要求,
04:12
and that's very, very hard to automate."
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这一点机器很难做到。“
最近最令人印象深刻的
04:15
One of the most impressive knowledge workers in recent memory
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知识型人才名叫Ken Jennings。
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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他连续74次在答题节目”抢答(Jeopardy!)“中取得胜利,
04:24
Took home three million dollars.
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赢得了三百万美金。
右边的这位就是Ken,在和IBM的超级机器人Watson
04:27
That's Ken on the right, getting beat three-to-one
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04:30
by Watson, the Jeopardy-playing supercomputer from IBM.
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一同参加”抢答“比赛时,他以三比一败北。
04:35
So when we look at what technology can do to general knowledge workers,
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看到科技产品胜过这样的通才
我开始思考
04:39
I start to think there might not be something so special
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通才的概念可能也没有多么特别
04:42
about this idea of a generalist,
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尤其是现在,如果我们把Siri
04:44
particularly when we start doing things like hooking Siri up to Watson,
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和Watson的技术相结合
04:48
and having technologies that can understand what we're saying
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就会得到可以理解人类语言
04:51
and repeat speech back to us.
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并得到自然语言反馈的技术。
04:53
Now, Siri is far from perfect, and we can make fun of her flaws,
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现在,Siri还远不完美,所以我们可以嘲笑
她的缺陷,但是我们也应该想到
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Siri和Watson的技术
也按照摩尔定律发展,那么
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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六年之后,他们不是提高2倍
或者4倍,他们会比现在先进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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所以我认为很多知识型的工作会受到这一发展趋势的影响。
05:17
And digital technologies are not just impacting knowledge work,
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数码技术并非只对知识型的工作有影响。
他们在体力工作方面也开始展现实力。
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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最近有有机会乘坐了
谷歌自动汽车,它就像它的名字一样酷。(笑声)
05:28
which is as cool as it sounds.
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05:30
(Laughter)
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我可以确定的说它有能力自如应对
05:33
And I will vouch that it handled the stop-and-go traffic on US 101
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美国101公路上走走停停的交通。
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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美国有三百五十万人
开卡车为生。
05:42
in the United States;
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我认为这项技术可能会影响
05:43
I think some of them are going to be affected by this technology.
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他们中的一部分人。现在,拟人机器人
05:46
And right now, humanoid robots are still incredibly primitive.
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还处在非常原始的状态。它们所能完成的任务十分有限。
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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但性能在快速提高。
05:53
and DARPA, which is the investment arm of the Defense Department,
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美国国防部的投资机构高级研究计划局(DARPA)
05:57
is trying to accelerate their trajectory.
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正在尝试推进此类研究的发展。
05:59
So, in short, yeah, the droids are coming for our jobs.
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简而言之,是的,机器人就要来和我们争夺工作机会了。
短期内,我们可以通过鼓励创业和
06:05
In the short term, we can stimulate job growth
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投资基础设施建设来促进工作机会的增长
06:08
by encouraging entrepreneurship
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06:10
and by investing in infrastructure,
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因为现在的机器人
06:12
because the robots today still aren't very good at fixing bridges.
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并不擅长修建桥梁。
06:15
But in the not-too-long-term,
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然而,在不远的将来,
06:17
I think within the lifetimes of most of the people in this room,
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我想今天的大部分观众有生之年都有可能见证
06:21
we're going to transition into an economy that is very productive,
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我们将进入一个生产力非常高
06:25
but that just doesn't need a lot of human workers.
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却不需要很多人类员工的时代,
06:28
And managing that transition is going to be the greatest challenge
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应对这样的转变
则是我们的社会所面临的最大挑战。
06:31
that our society faces.
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06:32
Voltaire summarized why; he said,
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伏尔泰(Voltaire)总结了原因。他说:
06:34
"Work saves us from three great evils: boredom, vice and need."
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"工作撵跑三个魔鬼:无聊,堕落和贫穷。"
06:40
But despite this challenge --
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尽管如此,我个人
06:42
personally, I'm still a huge digital optimist,
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仍是一个数码技术乐观主义者,
06:45
and I am supremely confident
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我坚信我们现在正在开发的数码技术
06:47
that the digital technologies that we're developing now
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会带我们进入一个大同社会,
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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而不是可怕的灾难。为了解释我为什么这样乐观
06:54
And to explain why,
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06:55
I want to pose a ridiculously broad question.
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我想要问一个宽泛到有些荒唐的问题。
06:58
I want to ask:
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我的问题是:人类历史上
06:59
what have been the most important developments in human history?
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最重要的发展是什么?
07:03
Now, I want to share some of the answers that I've gotten
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现在我想与你们分享一些就这个问题
我所得到的答案。这是一个很棒的问题,
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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问出来可以引起无休止的辩论,
07:10
because some people are going to bring up
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有些人会提起
07:12
systems of philosophy in both the West and the East
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改变很多人对世界看法的
07:15
that have changed how a lot of people think about the world.
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各种东西方哲学体系。
07:19
And then other people will say,
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其他人则会说。“不,真正重要的发展
07:20
"No, actually, the big stories, the big developments
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是世界主要宗教的建立,
07:23
are the founding of the world's major religions,
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它们改变了各国文明
07:25
which have changed civilizations and have changed and influenced
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改变和影响力了无数人的
07:29
how countless people are living their lives."
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生活方式。“还有人会说,
07:31
And then some other folk will say,
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07:33
"Actually, what changes civilizations,
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”事实上,改变文明
07:35
what modifies them and what changes people's lives are empires,
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和人类生活的
是帝国,所以人类历史上最重要的发展
07:40
so the great developments in human history
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是征服和战争。”
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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还有些生性欢快的人物常常会跳起来说
07:48
"Hey, don't forget about plagues!"
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“嗨,别忘了瘟疫。”(笑声)
07:50
(Laughter)
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我也得到了一些积极的答案,
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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有些人提起了地理大发现时代
和对世界的探索。
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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有人认为是包括数学在内的一些学科上的
学术进步帮助我们更好的
08:04
that have helped us get a better handle on the world,
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应对世界,也有人说到艺术和科学
08:07
and other folk will talk about periods when there was a deep flourishing
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繁荣发展的时代
08:10
of the arts and sciences.
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所以这场辩论可以一直进行下去。
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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这是永远不会结束的争论,也没有
08:15
and there's no conclusive, single answer to it.
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明确的唯一答案。但是,如果你和我一样是技术宅,
08:18
But if you're a geek like me,
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你就会问,“那么,数据会给出什么样的答案呢?”
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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然后我们就开始以感兴趣的东西为主题
08:24
like graph things that we might be interested in --
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制作图标,比如世界人口
08:26
the total worldwide population, for example,
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或者是某钟衡量社会发展的标准,
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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或者社会进步的状态,
08:34
And you start to plot the data, because, by this approach,
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将这些数据转化为图标之后,
就可以看到人类历史上的重要事件和伟大发展,
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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都会对这些曲线造成明显的变化。
08:44
So when you do this and when you plot the data,
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将数据转化成图形之后
08:46
you pretty quickly come to some weird conclusions.
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你很快就会得到一些奇怪的结论。
事实上,你的结论是这些因素
08:49
You conclude, actually,
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08:50
that none of these things have mattered very much.
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其实没有一个真正重要。(笑声)
08:53
(Laughter)
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它们对曲线的走势毫无影响。
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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人类历史上只有一个事件,一个发展
改变了这条曲线,让它发生了近90度的上升
09:05
that bent the curve, bent it just about 90 degrees,
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这就是科学技术。
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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蒸汽机以及工业革命期间出现的其它相关技术
09:14
of the Industrial Revolution
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改变了世界
09:16
changed the world and influenced human history so much,
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对人类历史产生了深远的影响,
09:19
that in the words of the historian Ian Morris,
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用历史学家Ian Morris的话说
09:21
"... they made mockery out of all that had come before."
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它们简直是对人类此前所取得的所有成就的嘲弄。
09:25
And they did this by infinitely multiplying the power of our muscles,
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这些技术带来了人类无法企及的力量
解放了人们的双手。
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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现在,我们所经历的
09:34
is overcoming the limitations of our individual brains
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则是对人类智力的超越
09:37
and infinitely multiplying our mental power.
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解放人们的大脑。
09:40
How can this not be as big a deal
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这和超越体力极限一样
09:43
as overcoming the limitations of our muscles?
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是人类历史上的一件大事。
09:46
So at the risk of repeating myself a little bit,
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因此请允许我再次强调
09:48
when I look at what's going on with digital technology these days,
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从当今数码科技发展的趋势来看
09:52
we are not anywhere near through with this journey.
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我们还远未到达这趟旅程的终点,
09:55
And when I look at what is happening to our economies and our societies,
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从当今的经济和社会发展趋势来看
我认为我们尚未见证
09:59
my single conclusion is that we ain't seen nothing yet.
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真正的变革。未来充满了激动人心的可能性。
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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请允许我举几个例子。
经济发展靠的不是能源、不是资本
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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也不是劳动力。经济发展靠的是理念。
10:11
Economies run on ideas.
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所以带来创新的工作
10:14
So the work of innovation, the work of coming up with new ideas,
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是最重要的,
10:17
is some of the most powerful, most fundamental work that we can do
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是经济发展中最基础的工作。
我们过去是这样从事创新工作的。
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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我们找一群长的差不多的人
10:25
We'd find a bunch of fairly similar-looking people ...
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10:28
(Laughter)
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(笑声)
他们来自精英组织,我们再让他们进入
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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其它的精英组织,然后等待创新的到来。
10:36
and we'd wait for the innovation.
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10:37
Now --
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现在(笑声)
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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作为一个整个职业生涯都在麻省理工
10:44
I've got no problem with this.
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和哈佛工作的白人,我对此没有意见。(笑声)
10:46
(Laughter)
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10:50
But some other people do,
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但是其他人不这样想,他们闯进
10:51
and they've kind of crashed the party
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创新世界的派对,降低了进入的门槛。
10:53
and loosened up the dress code of innovation.
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10:55
(Laughter)
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(笑声)
10:56
So here are the winners of a Topcoder programming challenge,
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这是Top Coder编程比赛的获胜者,
11:00
and I assure you that nobody cares
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我相信没有人在意
11:02
where these kids grew up, where they went to school,
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这些孩子在哪里长大,他们在什么地方上学,
11:06
or what they look like.
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以及他们的长相。我们在乎的只有
11:08
All anyone cares about is the quality of the work, the quality of the ideas.
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他们作品和想法的质量。
11:11
And over and over again, we see this happening
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我们一次又一次的在技术驱动的世界中
11:14
in the technology-facilitated world.
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看到这种情况的发生。
11:16
The work of innovation is becoming more open,
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创新工作正在变的更加开放,
更具包容性,更加透明,更加注重成绩,
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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无论麻省理工和哈佛怎么想,这种趋势
都将继续,令我感到非常开心。
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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我时不时听到这样的说法,“好,这些我可以接受,
但是科技依然是富裕阶层的工具,
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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现实的缺失是,这些数码工具没有
11:36
these digital tools are not improving the lives
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提高处于金字塔底层人们的生活。”
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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对于这种说法,我的答案非常简单:无稽之谈。
科技大大改善了底层人民的生活。
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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经济学家Robert Jensen有一项出色的研究
不久之前,他仔细观察了
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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印度喀拉拉邦地区小渔村居民得到手机后
11:56
when they got mobile phones for the very first time.
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生活发生的变化。
11:59
And when you write for the Quarterly Journal of Economics,
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《经济学季刊》刊登的文章
12:02
you have to use very dry and very circumspect language.
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语言一向干涩谨慎
12:05
But when I read his paper,
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然而读到Jensen的文章时,
12:06
I kind of feel Jensen is trying to scream at us
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却感觉他向我们疾呼:看,这真的非常了不起。
12:08
and say, "Look, this was a big deal.
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物价稳定,所以人们可以做好经济计划。
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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浪费不是减少了,而是彻底被消灭了。
在这些村庄里,卖方和买方
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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的生活水平都提高了。
我不认为Jensen运气过人,
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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碰巧遇到了一些生活水平
因科技而大大改善的村子。
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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事实上,他只是非常详细的记录了
新技术被引进新的环境和社区时
12:35
what happens over and over again when technology comes for the first time
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普遍会发生的情况。
12:39
to an environment and a community:
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居民的生活和福利会得到显著改善。
12:41
the lives of people, the welfares of people, improve dramatically.
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因此,对各方证据进行评估
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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并考虑未来发展空间之后,我对数码技术
12:49
I become a huge digital optimist
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持乐观态度,我开始认为物理学家Freeman Dyson
12:51
and I start to think that this wonderful statement from the physicist Freeman Dyson
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所提出的精彩观点
12:55
is actually not hyperbole.
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并不夸张,而是对当前形势的精确评估。
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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我们的数码技术是上天伟大的礼物,
13:02
and we, right now, have the great good fortune
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如今数码技术繁荣发展
13:05
to be living at a time when digital technology is flourishing,
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涉及范围不断拓宽加深
13:09
when it is broadening and deepening and becoming more profound
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在世界上的影响也越来越深远
能生活在这样一个时代是我们莫大的幸运。
13:13
all around the world.
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13:14
So, yeah, the droids are taking our jobs,
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因此,机器人确实在侵蚀我们的工作
13:17
but focusing on that fact misses the point entirely.
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然而这并不是值得关注的重点。
13:21
The point is that then we are freed up to do other things,
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真正值得关注的是技术给我们自由从事其他活动的机会
13:24
and what we're going to do, I am very confident,
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以及我们如何利用这样的机会,我坚信
13:27
what we're going to do is reduce poverty
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我们将会减少世界上的贫困、单调乏味的工作
13:29
and drudgery and misery around the world.
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和苦痛。我相信
13:32
I'm very confident we're going to learn to live more lightly on the planet,
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我们可以降低对地球资源的需求,
我相信我们未来对数码工具会有更深刻运用
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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造福世界,
13:41
is going to be so profound and so beneficial
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让此前的人类成就
13:44
that it's going to make a mockery out of everything that came before.
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都显得微不足道。
13:47
I'm going to leave the last word
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最后我将引用Ken Jennings
13:49
to a guy who had a front-row seat for digital progress,
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一位紧密关注数码技术进步的
13:51
our old friend Ken Jennings.
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老朋友所说的一句话。我认同他的观点。
13:53
I'm with him; I'm going to echo his words:
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我直接转述他的原话:
13:55
"I, for one, welcome our new computer overlords."
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“我,欢迎我们的新一代机器人领主。”(笑声)
13:58
(Laughter)
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13:59
Thanks very much.
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非常感谢。(掌声)
14:01
(Applause)
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