Growth is not dead.
经济增长并未死去。
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Let's start the story 120 years ago, when American factories began to electrify their operations, igniting the Second Industrial Revolution. The amazing thing is that productivity did not increase in those factories for 30 years. Thirty years. That's long enough for a generation of managers to retire. You see, the first wave of managers simply replaced their steam engines with electric motors, but they didn't redesign the factories to take advantage of electricity's flexibility. It fell to the next generation to invent new work processes, and then productivity soared, often doubling or even tripling in those factories.
让我们回到120年前, 那时,美国工厂开始将生产电气化, 点燃了第二次工业革命。 令人惊讶的是, 三十年内,生产力并没有提升。 三十年啊! 这段时间都足够让一代经理人退休了。 第一代的经理人 仅仅是用电动机取代了蒸汽机, 但他们并没有重新设计工厂使之充分利用 电力所带来的灵活性。 到第二代经理人改进运作过程后, 生产力才开始飙升, 达到之前的两倍甚至三倍。
Electricity is an example of a general purpose technology, like the steam engine before it. General purpose technologies drive most economic growth, because they unleash cascades of complementary innovations, like lightbulbs and, yes, factory redesign. Is there a general purpose technology of our era? Sure. It's the computer. But technology alone is not enough. Technology is not destiny. We shape our destiny, and just as the earlier generations of managers needed to redesign their factories, we're going to need to reinvent our organizations and even our whole economic system. We're not doing as well at that job as we should be. As we'll see in a moment, productivity is actually doing all right, but it has become decoupled from jobs, and the income of the typical worker is stagnating. These troubles are sometimes misdiagnosed as the end of innovation, but they are actually the growing pains of what Andrew McAfee and I call the new machine age.
电力是通用技术的代表之一, 就像之前的蒸汽机一样。 通用技术推动了多方面的经济增长, 因为它们释放了其它各级创新的潜能, 例如电灯泡,还有工厂的重新设计。 我们这个年代有没有通用技术? 当然有,那就是电脑。 但是仅有技术是不够的。 技术并不是终极目标。 我们自己塑造我们的目标, 正如早期的经理人 需要重新设计工厂, 我们也需要重新改造我们的体制, 甚至整个经济系统。 在这方面,我们的表现有些差强人意。 我会在接下来给大家展现, 生产效率目前发展良好, 但是这已经和工作岗位脱节, 而且普通工人的收入也正在停止增长。 这些问题有的时候被误认为是 创新的终结, 但实际上,它们是我和安德鲁·麦克菲 称作的新机器时代的“成长的烦恼”。
Let's look at some data. So here's GDP per person in America. There's some bumps along the way, but the big story is you could practically fit a ruler to it. This is a log scale, so what looks like steady growth is actually an acceleration in real terms. And here's productivity. You can see a little bit of a slowdown there in the mid-'70s, but it matches up pretty well with the Second Industrial Revolution, when factories were learning how to electrify their operations. After a lag, productivity accelerated again. So maybe "history doesn't repeat itself, but sometimes it rhymes." Today, productivity is at an all-time high, and despite the Great Recession, it grew faster in the 2000s than it did in the 1990s, the roaring 1990s, and that was faster than the '70s or '80s. It's growing faster than it did during the Second Industrial Revolution. And that's just the United States. The global news is even better. Worldwide incomes have grown at a faster rate in the past decade than ever in history.
让我们看一些数据。 这是美国人均GDP(国内生产总值)变化图。 中间有些颠簸起伏回落,但从整体上看 我们可以用一把尺子(直线)来比量发展趋势。 从对数比例的角度来看,这表面上是在稳步增长 但实际上是加速度。 这里显示的是生产率。 大家可以看到在上世纪70年代中叶有一点停顿, 但这趋势与第二次工业革命的发展很像, 那时工厂都在学习如何让操作电气化。 在一个停顿之后,生产率又加速发展了。 也许“历史虽然不会简单重复, 但有时却也有规律可循。” 现在,生产率是有史以来最高的, 尽管有大萧条, 2000年代的生产率还是要比上世纪90年代的发展得要快, 繁荣的90年代的生产率又比70或者80年代的发展快。 它比第二次工业革命的生产率发展的要快。 而这仅仅是美国的数据。 全球的情况更好。 全球收入增长比之前 任意一个时代的发展都要快。
If anything, all these numbers actually understate our progress, because the new machine age is more about knowledge creation than just physical production. It's mind not matter, brain not brawn, ideas not things. That creates a problem for standard metrics, because we're getting more and more stuff for free, like Wikipedia, Google, Skype, and if they post it on the web, even this TED Talk. Now getting stuff for free is a good thing, right? Sure, of course it is. But that's not how economists measure GDP. Zero price means zero weight in the GDP statistics. According to the numbers, the music industry is half the size that it was 10 years ago, but I'm listening to more and better music than ever. You know, I bet you are too. In total, my research estimates that the GDP numbers miss over 300 billion dollars per year in free goods and services on the Internet. Now let's look to the future. There are some super smart people who are arguing that we've reached the end of growth, but to understand the future of growth, we need to make predictions about the underlying drivers of growth. I'm optimistic, because the new machine age is digital, exponential and combinatorial.
这些数字实际上低估了我们所取得的进步, 因为新机器时代 更多的是知识创造 而不是具体的物质生产。 它是思想不是事实,是头脑不是体力, 是想法而不是具体事物。 这为那些标准化的测量指标提出了挑战, 因为我们正在免费的获得越来越多的信息, 比如维基大百科、谷歌、Skype, 以及发布在网上的内容,比如这个TED演讲。 免费获得东西是好事,对吧? 当然,那还用说。 但那不是经济学家如何测算GDP的。 免费的东西意味着在GDP统计里没有任何权重。 根据这些数据来看,音乐工业 只是过去十年的一半的规模, 但我正在听比过去更多和更好的音乐。 我相信大家也有同感。 我的研究预测 我们每年总共少计算三千亿美元的GDP, 也就是免费在互联网上获得的商品和服务。 让我们展望未来。 有些非常聪明的人们 认为我们的经济增长已经停滞, 但是,为了理解未来发展的走势, 我们要预测经济发展的 深层动力是什么。 我是乐观的,因为新机器时代是 数字化的、指数化(增长)的和组合性的。
When goods are digital, they can be replicated with perfect quality at nearly zero cost, and they can be delivered almost instantaneously. Welcome to the economics of abundance. But there's a subtler benefit to the digitization of the world. Measurement is the lifeblood of science and progress. In the age of big data, we can measure the world in ways we never could before.
当商品是数字化的时候,它们可以 被近乎无附加值的完美复制, 而且它们几乎可以在瞬间传送。 欢迎来到丰饶经济学。 但是还有一个全球电子化带来的微妙好处。 测量是科学与进步的生命线。 在大数据时代, 我们可以用从未有过的方式来测量世界。
Secondly, the new machine age is exponential. Computers get better faster than anything else ever. A child's Playstation today is more powerful than a military supercomputer from 1996. But our brains are wired for a linear world. As a result, exponential trends take us by surprise. I used to teach my students that there are some things, you know, computers just aren't good at, like driving a car through traffic. (Laughter) That's right, here's Andy and me grinning like madmen because we just rode down Route 101 in, yes, a driverless car.
其次,新机器时代是指数化(发展)的。 电脑正比任何事物都发展得更快更好。 今天一个孩子的Playstation比 1996年的军事超级计算机还要强大。 但是我们习惯了一个线性发展的世界。 因此,我们都惊讶于指数形式的发展趋势。 我以前告诉我的学生, 有些事情是电脑做不好的, 比如说开车。 (笑声) 对,这是我和安迪笑得像个傻子, 因为我们刚在一辆无人驾驶的汽车里 穿过了101大道。
Thirdly, the new machine age is combinatorial. The stagnationist view is that ideas get used up, like low-hanging fruit, but the reality is that each innovation creates building blocks for even more innovations. Here's an example. In just a matter of a few weeks, an undergraduate student of mine built an app that ultimately reached 1.3 million users. He was able to do that so easily because he built it on top of Facebook, and Facebook was built on top of the web, and that was built on top of the Internet, and so on and so forth.
第三,新机器时代是组合性的。 停滞的观点认为所有的创新都用完了, 比如那些显而易见的, 但事实是每个创新 都为更多的创新奠定了基石。 举个例子。在几周内, 我的一个学生 开发了一个吸引了大概一百三十万用户的应用。 他可以这么轻松的完成 是因为这个应用是在脸书上搭建起来的, 而脸书又依托于网络, 而网络又是在互联网上建造起来的, 等等等等。
Now individually, digital, exponential and combinatorial would each be game-changers. Put them together, and we're seeing a wave of astonishing breakthroughs, like robots that do factory work or run as fast as a cheetah or leap tall buildings in a single bound. You know, robots are even revolutionizing cat transportation.
电子化、指数化(发展)和组合化, 任何一个都会带来翻天覆地的变化。 把它们结合起来,我们就会看到 新一轮的惊人突破, 比如机器人来做工厂的工作或者跑得像猎豹一样快 或者一个飞跃就跃过高楼大厦。 机器人甚至正在变革 对猫的运输方式。
(Laughter)
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But perhaps the most important invention, the most important invention is machine learning. Consider one project: IBM's Watson. These little dots here, those are all the champions on the quiz show "Jeopardy." At first, Watson wasn't very good, but it improved at a rate faster than any human could, and shortly after Dave Ferrucci showed this chart to my class at MIT, Watson beat the world "Jeopardy" champion. At age seven, Watson is still kind of in its childhood. Recently, its teachers let it surf the Internet unsupervised. The next day, it started answering questions with profanities. Damn. (Laughter)
但也许最重要的发明, 就是机器学习。 看看IBM的沃森项目。 这些小圆点们, 这些是益智游戏“杰帕迪”的冠军们。 最初,沃森变现得并不出色, 但是它比任何人类改进得都快, 很快,在大卫·费鲁奇(沃森项目负责人)给我在MIT 的学生看这张图之后不久, 沃森就击败了“杰帕迪”的世界冠军。 那时沃森只有7岁,还是个孩子。 最近,它的老师们让它自行上网。 第二天,它就开始用脏话来回答问题了。 糟糕。(笑声)
But you know, Watson is growing up fast. It's being tested for jobs in call centers, and it's getting them. It's applying for legal, banking and medical jobs, and getting some of them. Isn't it ironic that at the very moment we are building intelligent machines, perhaps the most important invention in human history, some people are arguing that innovation is stagnating? Like the first two industrial revolutions, the full implications of the new machine age are going to take at least a century to fully play out, but they are staggering.
但是,沃森正在快速的成长。 它应聘了客服类的工作,而且它很胜任。 它正在应聘法律、银行和医药类的工作, 而且也拿到了一些工作。 是不是很讽刺,我们在这个非常时期 正在建造可能是 人类历史上最重要的发明--智能机器, 而一些人还在说创新停滞不前了? 就像之前的两次工业革命, 新机器时代的全面影响 至少会用一个世纪才能完全发挥出来, 但这将会是惊人的。
So does that mean we have nothing to worry about? No. Technology is not destiny. Productivity is at an all time high, but fewer people now have jobs. We have created more wealth in the past decade than ever, but for a majority of Americans, their income has fallen. This is the great decoupling of productivity from employment, of wealth from work. You know, it's not surprising that millions of people have become disillusioned by the great decoupling, but like too many others, they misunderstand its basic causes. Technology is racing ahead, but it's leaving more and more people behind. Today, we can take a routine job, codify it in a set of machine-readable instructions, and then replicate it a million times.
这是不是说我们没有什么可担心的了? 不!技术不是目的。 生产率是史上最高的, 但是更少的人现在还有工作。 我们在过去十年创造了比过去更多的财富, 但是大部分的美国家庭,他们的收入却降低了。 这是生产率和就业率, 财富和工作的 严重脱节, 要知道,有数百万人受到 被这种严重脱节的现象所迷惑,这并不让人惊讶, 但是像很多其他的人一样, 人们误解了这种现象的根本原因。 科技正在领跑, 但它把越来越多的人甩在了后面。 今天,我们可以把一个日常工作 编译成一组机器可读的指令, 然后就可以把它复制百万次。
You know, I recently overheard a conversation that epitomizes these new economics. This guy says, "Nah, I don't use H&R Block anymore. TurboTax does everything that my tax preparer did, but it's faster, cheaper and more accurate." How can a skilled worker compete with a $39 piece of software? She can't. Today, millions of Americans do have faster, cheaper, more accurate tax preparation, and the founders of Intuit have done very well for themselves. But 17 percent of tax preparers no longer have jobs. That is a microcosm of what's happening, not just in software and services, but in media and music, in finance and manufacturing, in retailing and trade -- in short, in every industry. People are racing against the machine, and many of them are losing that race.
我最近就听到了一段 反映这些新经济现象的对话。 有个人说,“我不再用布洛克税务公司的专人服务了。 波税务软件可以我的报税员做的任何工作, 但它更快、更便宜也更准确。“ 一个专业人士 怎么能和一个售价只有39美元的软件相比? 不可能的。 今天,数百万的美国人有了更快、 更便宜和更准确的税款准备, 而且Intuit公司(创造TurboTax软件的公司)创始人 也为自己收获颇丰。 但17%的报税员却失去了工作。 这只是正在发生着的改变的一个缩影。 不仅是在软件和服务领域,也在媒体和音乐界, 在金融、制造业、零售和外贸 - 总而言之,在每个行业中都在发生着。 人类在和机器较量, 很多人都在失去这场较量。
What can we do to create shared prosperity? The answer is not to try to slow down technology. Instead of racing against the machine, we need to learn to race with the machine. That is our grand challenge.
我们怎样才能达到共同繁荣? 答案绝对不是试图减缓科技发展。 与其和机器赛跑, 我们应该学着如何与机器一同进步。 这是我们最大的挑战。
The new machine age can be dated to a day 15 years ago when Garry Kasparov, the world chess champion, played Deep Blue, a supercomputer. The machine won that day, and today, a chess program running on a cell phone can beat a human grandmaster. It got so bad that, when he was asked what strategy he would use against a computer, Jan Donner, the Dutch grandmaster, replied, "I'd bring a hammer."
新机器时代 可以从15年前的一天开始算起, 当世界国际象棋冠军加里·卡斯帕罗夫 和一台叫做深蓝的超级计算机下棋的时候。 当时机器赢了, 而现在,一个在手机上的国际象棋程序 也可以打败一个人类大师。 事情糟糕到,当被问到如果和一台电脑 下棋他会使用什么样的战术时, 约翰·唐纳,荷兰象棋大师,回应道, “我会带个锤子。”
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But today a computer is no longer the world chess champion. Neither is a human, because Kasparov organized a freestyle tournament where teams of humans and computers could work together, and the winning team had no grandmaster, and it had no supercomputer. What they had was better teamwork, and they showed that a team of humans and computers, working together, could beat any computer or any human working alone. Racing with the machine beats racing against the machine. Technology is not destiny. We shape our destiny.
但今天电脑不再是世界国际象棋大赛冠军。 也不是一个人, 因为卡斯帕罗夫组织了一个自由式比赛 人类和电脑可以组团 一起合作, 最终的获胜者团队里既没有大师, 也没有超级电脑。 他们有的是更好的团队合作, 这证明了一个由人和电脑共同协作的团队, 可以打败任何一个单一作战的电脑 或者个人。 和机器一同前进 要远远好过和机器竞赛。 技术不是终极目标。 我们塑造自己的目标。
Thank you.
谢谢大家。
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