TEDxBoston 2012
Andrew McAfee: Are droids taking our jobs?
Andrew McAfee：机器人会抢走我们的工作吗？
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机器人和算法越来越擅长汽车制造、文章撰写和语言翻译之类从前必须有人类参与的工作。那么人类做些什么工作呢？Andrew McAfee评估了近期的劳动力数据之后得出结论：真正的影响尚未到来。然而随后他反观历史，对未来做出了令人惊讶和激动的预测。（录制于TEDxBoston）。
Andrew McAfee - Management theorist
Andrew McAfee studies how information technology affects businesses and society. Full bio
Andrew McAfee studies how information technology affects businesses and society. Full bio
Double-click the English transcript below to play the video.
00:16
As it turns out, when tens of millions of people
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事实上，当成千上万的人
00:19
are unemployed or underemployed,
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没有工作或者被大材小用时
00:21
there's a fair amount of interest in what technology might be doing to the labor force.
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人们就去关注科技对劳动力的影响。
00:25
And as I look at the conversation, it strikes me
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我看到这方面的新闻与报导之后发现
00:28
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
00:31
and at the same time, it's missing the point entirely.
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但却彻底错过了重点。
00:34
The topic that it's focused on, the question is whether or not
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它们关注的主题是，
00:37
all these digital technologies are affecting people's ability
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数码科技会不会影响人们
00:40
to earn a living, or, to say it a little bit different way,
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谋生的能力，换句话说，
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？
00:46
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。
00:48
The Great Recession ended when American GDP resumed
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大萧条结束时
00:52
its kind of slow, steady march upward, and some other
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美国的GDP恢复了缓慢稳定的增长，
00:56
economic indicators also started to rebound, and they got
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一些其它经济指标也开始快速健康地回升，
00:58
kind of healthy kind of quickly. Corporate profits
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企业利润很高。
01:01
are quite high. In fact, if you include bank profits,
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事实上，如果算上银行利润，
01:05
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。
01:07
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
01:10
and hardware and software is at an all-time high.
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也处于历史最高水平。
01:13
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。
01:19
So this red line is the employment-to-population ratio,
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这条红线是就业人数和人口的比例，
01:22
in other words, the percentage of working age people
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换句话说就是美国处于工作年龄的人口中
01:26
in America who have work.
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有工作人数的比例。
01:28
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。
01:37
The decade that we've just been through had relatively
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十年之内工作数量的增长微乎其微
01:40
anemic job growth all throughout, especially when we
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和其它的十年比尤其如此
01:43
compare it to other decades, and the 2000s
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事实上，在二十一世纪的第一个十年中
01:46
are the only time we have on record where there were
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2009年的就业人数少于2000年
01:48
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。
01:52
than at the beginning. This is not what you want to see.
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是我们不希望看到的趋势。
01:55
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, you see the gap
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工作机会的数量，你会发现
02:02
gets bigger and bigger over time, and then,
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两者之间的差距随着时间的推移越来越大
02:05
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。
02:08
I did some quick calculations. I took the last 20 years of GDP growth
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我进行了一些计算。我直接运用过去二十年GDP增长
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
02:16
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
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我们需要多少工作机会才能保证
02:21
to need to keep growing, and this is the line that I came up with.
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经济的持续增长，最终的结果就是这条曲线。
02:25
Is that good or bad? This is the government's projection
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这个结果是好是坏？这是政府
02:28
for the working age population going forward.
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对适龄工作人口增长的预测。
02:32
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。
02:37
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。
02:40
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, I was assuming that the future
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因为我的预测建立在
02:47
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, and that's actually not what I believe,
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但我不认为事情会这样发展
02:53
because when I look around, I think that we ain't seen nothing yet
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因为当我环顾四周时，我认为我们还没有意识到
02:56
when it comes to technology's impact on the labor force.
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科技对劳动力的影响。
03:00
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
03:04
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
03:08
and that, kind of, eat deeply into what we human beings
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并且对人类生活影响很大。
03:12
do for a living. Let me give you a couple examples.
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请允许我举几个例子。
03:15
Throughout all of history, if you wanted something
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有史以来，如果你需要把一些文字
03:17
translated from one language into another,
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从一种语言翻译成另外一种语言，
03:20
you had to involve a human being.
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必须有人类参与。
03:22
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。
03:33
And if any of us have used these, we know that
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如果你使用过这这种服务，你就会知道
03:35
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
03:42
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。
03:45
Not anymore. This is an article that appeared
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现在不用了。这是一篇不久以前
03:47
in Forbes online a while back about Apple's earnings.
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《福布斯》杂志刊登的有关苹果公司收益的文章。
03:51
It was written by an algorithm.
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由一个算法撰写。
03:53
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。
03:56
A lot of people look at this and they say, "Okay,
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很多人看到这一现象以后说，“好吧，
03:59
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，
04:02
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
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他们拥有很多
04:07
of expertise and knowledge and they use that
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技能和知识并运用它们
04:09
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，
04:13
and that's very, very hard to automate."
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这一点机器很难做到。“
04:15
One of the most impressive knowledge workers
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最近最令人印象深刻的
04:17
in recent memory is a guy named Ken Jennings.
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知识型人才名叫Ken Jennings。
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。
04:27
That's Ken on the right getting beat three to one by
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右边的这位就是Ken,在和IBM的超级机器人Watson
04:31
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。
04:36
So when we look at what technology can do
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看到科技产品胜过这样的通才
04:38
to general knowledge workers, I start to think
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我开始思考
04:40
there might not be something so special about this idea
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通才的概念可能也没有多么特别
04:43
of a generalist, particularly when we start doing things
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尤其是现在，如果我们把Siri
04:46
like hooking Siri up to Watson and having technologies
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和Watson的技术相结合
04:50
that can understand what we're saying
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就会得到可以理解人类语言
04:52
and repeat speech back to us.
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并得到自然语言反馈的技术。
04:54
Now, Siri is far from perfect, and we can make fun
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现在，Siri还远不完美，所以我们可以嘲笑
04:57
of her flaws, but we should also keep in mind that
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她的缺陷，但是我们也应该想到
05:00
if technologies like Siri and Watson improve
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如果Siri和Watson的技术
05:02
along a Moore's Law trajectory, which they will,
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也按照摩尔定律发展，那么
05:06
in six years, they're not going to be two times better
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六年之后，他们不是提高2倍
05:09
or four times better, they'll be 16 times better than they are right now.
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或者4倍，他们会比现在先进16倍。
05:14
So I start to think that 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。
05:21
They're starting to flex their muscles in the physical world as well.
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他们在体力工作方面也开始展现实力。
05:25
I had the chance a little while back to ride in the Google
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最近有有机会乘坐了
05:27
autonomous car, which is as cool as it sounds. (Laughter)
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谷歌自动汽车，它就像它的名字一样酷。（笑声）
05:33
And I will vouch that it handled the stop-and-go traffic
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我可以确定的说它有能力自如应对
05:36
on U.S. 101 very smoothly.
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美国101公路上走走停停的交通。
05:39
There are about three and a half million people
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美国有三百五十万人
05:41
who drive trucks for a living in the United States.
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开卡车为生。
05:43
I think some of them are going to be affected by this
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我认为这项技术可能会影响
05:45
technology. And right now, humanoid robots are still
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他们中的一部分人。现在，拟人机器人
05:49
incredibly primitive. They can't do very much.
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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。
05:52
But they're getting better quite quickly, and DARPA,
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但性能在快速提高。
05:54
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）
05:58
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。
06:04
In the short term, we can stimulate job growth
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短期内，我们可以通过鼓励创业和
06:08
by encouraging entrepreneurship and by investing
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投资基础设施建设来促进工作机会的增长
06:11
in infrastructure, because the robots today still aren't
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因为现在的机器人
06:14
very good at fixing bridges.
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并不擅长修建桥梁。
06:16
But in the not-too-long-term, I think within the lifetimes
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然而，在不远的将来，
06:19
of most of the people in this room, we're going to transition
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我想今天的大部分观众有生之年都有可能见证
06:22
into an economy that is very productive but that
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我们将进入一个生产力非常高
06:25
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
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应对这样的转变
06:30
the greatest challenge that our society faces.
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则是我们的社会所面临的最大挑战。
06:33
Voltaire summarized why. He said, "Work saves us
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伏尔泰（Voltaire）总结了原因。他说：
06:35
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。"
06:41
But despite this challenge, I'm personally,
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尽管如此，我个人
06:43
I'm still a huge digital optimist, and I am
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仍是一个数码技术乐观主义者，
06:46
supremely confident that the digital technologies that we're
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我坚信我们现在正在开发的数码技术
06:49
developing now are going to take us into a utopian future,
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会带我们进入一个大同社会，
06:53
not a dystopian future. And to explain why,
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而不是可怕的灾难。为了解释我为什么这样乐观
06:56
I want to pose kind of 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 what have been the most important
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我的问题是：人类历史上
07:01
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
07:06
in response to this question. It's a wonderful question
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我所得到的答案。这是一个很棒的问题，
07:08
to ask and to 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
07:13
systems of philosophy in both the West and the East that
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改变很多人对世界看法的
07:16
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, "No, actually, the big stories,
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其他人则会说。“不，真正重要的发展
07:22
the big developments are the founding of the world's
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是世界主要宗教的建立，
07:24
major religions, which have changed civilizations
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它们改变了各国文明
07:28
and have changed and influenced how countless people
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改变和影响力了无数人的
07:30
are living their lives." And then some other folk will say,
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生活方式。“还有人会说，
07:33
"Actually, what changes civilizations, what modifies them
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”事实上，改变文明
07:37
and what changes people's lives
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和人类生活的
07:39
are empires, so the great developments in human history
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是帝国，所以人类历史上最重要的发展
07:43
are stories of conquest and of war."
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是征服和战争。”
07:46
And then some cheery soul usually always pipes up
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还有些生性欢快的人物常常会跳起来说
07:48
and says, "Hey, don't forget about plagues." (Laughter)
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“嗨，别忘了瘟疫。”（笑声）
07:54
There are some optimistic answers to this question,
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我也得到了一些积极的答案，
07:57
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
07:59
and the opening up of the world.
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和对世界的探索。
08:01
Others will talk about intellectual achievements
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有人认为是包括数学在内的一些学科上的
08:03
in disciplines like math that have helped us get
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学术进步帮助我们更好的
08:05
a better handle on the world, and other folk will talk about
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应对世界，也有人说到艺术和科学
08:08
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. So this debate will go on and on.
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所以这场辩论可以一直进行下去。
08:14
It's an endless debate, and there's no conclusive,
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这是永远不会结束的争论，也没有
08:17
no single answer to it. But if you're a geek like me,
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明确的唯一答案。但是，如果你和我一样是技术宅，
08:20
you say, "Well, what do the data say?"
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你就会问，“那么，数据会给出什么样的答案呢？”
08:23
And you start to do things like graph things that we might
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然后我们就开始以感兴趣的东西为主题
08:26
be interested in, the total worldwide population, for example,
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制作图标，比如世界人口
08:30
or some measure of social development,
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或者是某钟衡量社会发展的标准，
08:33
or the state of advancement of a society,
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或者社会进步的状态，
08:35
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，
08:39
the big stories, the big developments in human history,
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就可以看到人类历史上的重要事件和伟大发展，
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。
08:49
You conclude, actually, that none of these things
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事实上，你的结论是这些因素
08:52
have mattered very much. (Laughter)
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其实没有一个真正重要。（笑声）
08:57
They haven't done a darn thing to the curves. (Laughter)
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它们对曲线的走势毫无影响。
09:01
There has been one story, one development
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人类历史上只有一个事件，一个发展
09:05
in human history that bent the curve, bent it just about
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改变了这条曲线，让它发生了近90度的上升
09:07
90 degrees, and it is a technology story.
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这就是科学技术。
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 changed the world
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改变了世界
09:17
and influenced human history so much,
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对人类历史产生了深远的影响，
09:20
that in the words of the historian Ian Morris,
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用历史学家Ian Morris的话说
09:22
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。
09:26
And they did this by infinitely multiplying the power
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这些技术带来了人类无法企及的力量
09:29
of our muscles, overcoming the limitations of our muscles.
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解放了人们的双手。
09:32
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 as overcoming
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这和超越体力极限一样
09:44
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, when I look
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因此请允许我再次强调
09:50
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
09:53
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
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从当今的经济和社会发展趋势来看
09:58
and our societies, my single conclusion is that
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我认为我们尚未见证
10:01
we ain't seen nothing yet. The best days are really ahead.
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真正的变革。未来充满了激动人心的可能性。
10:04
Let me give you a couple examples.
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请允许我举几个例子。
10:06
Economies don't run on energy. They don't run on capital,
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经济发展靠的不是能源、不是资本
10:10
they don't run on labor. Economies run on ideas.
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也不是劳动力。经济发展靠的是理念。
10:14
So the work of innovation, the work of coming up with
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所以带来创新的工作
10:17
new ideas, is some of the most powerful,
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是最重要的，
10:19
some of the most fundamental work that we can do
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是经济发展中最基础的工作。
10:21
in an economy. And this is kind of how we used to do innovation.
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我们过去是这样从事创新工作的。
10:25
We'd find a bunch of fairly similar-looking people
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我们找一群长的差不多的人
10:29
— (Laughter) —
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（笑声）
10:32
we'd take them out of elite institutions, we'd put them into
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他们来自精英组织，我们再让他们进入
10:35
other elite institutions, and we'd wait for the innovation.
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其它的精英组织，然后等待创新的到来。
10:38
Now — (Laughter) —
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现在（笑声）
10:42
as a white guy who spent his whole career at MIT
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作为一个整个职业生涯都在麻省理工
10:44
and Harvard, I got no problem with this. (Laughter)
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和哈佛工作的白人，我对此没有意见。（笑声）
10:51
But some other people do, and they've kind of crashed
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但是其他人不这样想，他们闯进
10:53
the party and loosened up the dress code of innovation.
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创新世界的派对，降低了进入的门槛。
10:56
(Laughter)
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（笑声）
10:57
So here are the winners of a Top Coder 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
11:03
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，
11:07
or what they look like. All anyone cares about
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以及他们的长相。我们在乎的只有
11:09
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。
11:12
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。
11:17
The work of innovation is becoming more open,
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创新工作正在变的更加开放，
11:19
more inclusive, more transparent, and more merit-based,
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更具包容性，更加透明，更加注重成绩，
11:23
and that's going to continue no matter what MIT and Harvard
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无论麻省理工和哈佛怎么想，这种趋势
11:26
think of it, and I couldn't be happier about that development.
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都将继续，令我感到非常开心。
11:29
I hear once in a while, "Okay, 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，
11:32
but technology is still a tool for the rich world,
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但是科技依然是富裕阶层的工具，
11:35
and what's not happening, these digital tools are not
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现实的缺失是，这些数码工具没有
11:38
improving the lives of people at the bottom of the pyramid."
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提高处于金字塔底层人们的生活。”
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。
11:44
The bottom of the pyramid is benefiting hugely from technology.
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科技大大改善了底层人民的生活。
11:47
The economist Robert Jensen did this wonderful study
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经济学家Robert Jensen有一项出色的研究
11:50
a while back where he watched, in great detail,
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不久之前，他仔细观察了
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
11:57
when they got mobile phones for the very first time,
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生活发生的变化。
12:00
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, I kind of feel Jensen is trying
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然而读到Jensen的文章时，
12:08
to scream at us, and say, look, this was a big deal.
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却感觉他向我们疾呼：看，这真的非常了不起。
12:11
Prices stabilized, so people could plan their economic lives.
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物价稳定，所以人们可以做好经济计划。
12:15
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。
12:19
And the lives of both the buyers and the sellers
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在这些村庄里，卖方和买方
12:21
in these villages measurably improved.
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的生活水平都提高了。
12:24
Now, what I don't think is that Jensen got extremely lucky
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我不认为Jensen运气过人，
12:28
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
12:30
where technology made things better.
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因科技而大大改善的村子。
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
12:35
what happens over and over again when technology
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新技术被引进新的环境和社区时
12:38
comes for the first time to an environment and a community.
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普遍会发生的情况。
12:41
The lives of people, the welfares of people, improve dramatically.
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居民的生活和福利会得到显著改善。
12:45
So as I look around at all the evidence, and I think about
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因此，对各方证据进行评估
12:47
the room that we have ahead of us, I become a huge
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并考虑未来发展空间之后，我对数码技术
12:50
digital optimist, and I start to think that this wonderful
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持乐观态度，我开始认为物理学家Freeman Dyson
12:53
statement from the physicist Freeman Dyson
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所提出的精彩观点
12:56
is actually not hyperbole. This is an accurate assessment of what's going on.
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并不夸张，而是对当前形势的精确评估。
13:00
Our digital -- our technologies are great gifts,
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我们的数码技术是上天伟大的礼物，
13:03
and we, right now, have the great good fortune
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如今数码技术繁荣发展
13:06
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
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在世界上的影响也越来越深远
13:11
becoming more profound all around the world.
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能生活在这样一个时代是我们莫大的幸运。
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
13:18
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
13:25
and what we are 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 and drudgery
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我们将会减少世界上的贫困、单调乏味的工作
13:30
and misery around the world. I'm very confident
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和苦痛。我相信
13:33
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，
13:36
and I am extremely confident that what we're going to do
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我相信我们未来对数码工具会有更深刻运用
13:40
with our new digital tools is going to be so profound
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造福世界，
13:43
and so beneficial that it's going to make a mockery
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让此前的人类成就
13:45
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 to a guy who had
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最后我将引用Ken Jennings
13:50
a front row seat for digital progress,
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一位紧密关注数码技术进步的
13:52
our old friend Ken Jennings. I'm with him.
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老朋友所说的一句话。我认同他的观点。
13:54
I'm going to echo his words:
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我直接转述他的原话：
13:56
"I, for one, welcome our new computer overlords." (Laughter)
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“我，欢迎我们的新一代机器人领主。”（笑声）
14:00
Thanks very much. (Applause)
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非常感谢。（掌声）
ABOUT THE SPEAKER
Andrew McAfee - Management theoristAndrew McAfee studies how information technology affects businesses and society.
Why you should listen
Andrew McAfee studies the ways that information technology (IT) affects businesses, business as a whole, and the larger society. His research investigates how IT changes the way companies perform, organize themselves and compete. At a higher level, his work also investigates how computerization affects competition, society, the economy and the workforce.
He's a principal research scientist at the Center for Digital Business at the MIT Sloan School of Management. His books include Enterprise 2.0 and Race Against the Machine (with Erik Brynjolfsson). Read more on his blog.
Andrew McAfee | Speaker | TED.com