Growth is not dead.
成長還沒停止
(Applause)
(掌聲)
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.
故事從 120 年前說起 美國工廠開始電器化運作 帶動了第二次工業革命 但驚人的是 三十年中,那些工廠的生產力並沒有提升 整整三十年 這段時間足以讓一代的經理退休了 我們可以看到,第一批經理 只不過是把蒸汽機換成電動機而已 他們並沒有重新設計工廠 讓它利用電的多變性 下個世代開始發明新的工作程序 生產力因此大增 常常是原來工廠的兩倍,甚至是三倍
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.
電力是一種通用目的技術的例子 出現較早的蒸汽機也是一樣 通用目的技術是帶動經濟發展的主力 因為它能帶動一連串有互補性的創新 像是燈泡,沒錯,工廠因而改頭換面 那現代有通用目的技術存在嗎? 當然有,就是電腦 但只靠科技還不夠 科技不能主導命運 是我們掌握自己的命運 就像早期的經理 需要重新打造他們的工廠一樣 我們也需要重建一個組織 甚至是重塑整個經濟體制 我們並沒有達到應有的水準 我們馬上就會了解 生產力是完全沒有問題的 但生產力與工作背道而馳 而且,一般工人的收入也減少了 有時候我們在創新的盡頭 會對這些問題有錯誤的判斷 但事實上這是一種成長必要的代價 我和安德魯.邁克菲 (Andrew McAfee) 將其稱為「新機器時代」
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.
我們來看看一些資料 這是美國每人的國內生產毛額 線上有些高低起伏,但重點是 你會發現它的路徑與直線符合 這是對數比例尺,所以看起來是穩定成長 但事實上,它是加速進行著 而這是生產力 大家可以看到在 70 年代中期,成長漸緩 但這和第二次工業革命的時間吻合 當時工廠正在學著如何電器化運作 漸緩一段時間後,生產力再度急遽上升 所以或許「歷史不會自己重演 但有時不可否認會有幾分相似。」 現在,生產力是前所未有的高 儘管是在經濟大蕭條的期間 2000 年以來還是比 90 年代成長得更快 喧囂動盪的 90 年代還是比 70 或 80 年代增加更快 比第二次工業革命時成長更快 而這只是美國而已 全球的表現更是優秀 全球所得在過去十年 以前所未有的驚人速度成長
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.
不過,這些數據事實上低估了我們進步的程度 因為新機器時代 強調的是知識的創造 而非只是實際的產量 怎麼想比怎麼做來得重要 要動腦而不是靠蠻力 想法大於產物本身 而這產生了測量標準的問題 因為免費的東西越來越多 像是維基百科、谷歌、網路電話(Skype) 他們把東西放到網路上 甚至是現在這篇 TED 演講 有免費的東西是好事,對吧? 當然是好事 但經濟學家可不是這樣衡量國內生產毛額的 免費,在國內生產毛額統計上代表權重為零 根據調查顯示,音樂產業的規模 只有十年前的二分之一 但我現在聽到的音樂,比起以前進步很多 我想你們也有這種感覺 整體來說,我的研究估計 國內生產毛額每年少算超過三千億美元 忽略了網路上提供的免費產品及服務 現在我們放眼未來 有些非常聰明的人 認為我們已經發展到了窮途末路 但要了解未來的發展 我們必須對成長潛在的驅動力 做些預測 我抱持樂觀的態度,因為新機器時代 是數位化、指數化及組合化的時代
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.
當產品數位化,就能夠複製 幾乎不用花半毛錢,就能有很好的品質 而且可以立即傳送 歡迎來到經濟蓬勃的時代 世界數位化有個比較其次的好處 測量是科學及進步的重要指標 在充斥大量資料的時代 我們可以用過去辦不到的方法 來衡量現在的世界
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.
第二,新機器時代是指數化的時代 電腦比任何東西跑得更快 現在小朋友的遊戲機(Playstation) 比 1996 年軍隊的超級電腦更進步 但我們的大腦是習慣線性世界的 因此,指數化的趨勢讓我們大吃 一驚 過去我都教學生說,有些事 你知道嗎?電腦根本做不來 像開車通過擁擠的車潮 (笑聲) 沒錯,這張照片是我和安迪,像瘋子一樣在大笑 因為我們剛下國道 101 沒錯,就在一台無人駕駛的車子裡
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,新機器時代是組合化的時代 想法停滯就是想法用完了 輕而易舉 但事實上,每一種創新 都是激盪出更多創新的墊腳石 舉例來說,大約幾個禮拜前 我的一位大學生 開發了一個應用程式,最後使用者高達 130 萬 他輕而易舉就能辦到 因為他是在臉書上建立的 而臉書是個網站 網站又建立在網路之上 等等的關聯
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.
現在個人數位化、指數化及組合化 分別都能改變這場遊戲 把這些通通集結起來,我們會看到 一連串驚人的突破 像是機器人,能在工廠工作 跑得跟印度豹一樣快 或是一躍就能上高樓 其實,機器人甚至改變了 貓的運輸方式
(Laughter)
(笑聲)
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)
但或許最重要的發明 最重要的發明是讓機器學習 想想這個計畫:IBM 的沃森(Watson) 這些點顯示的是 智力節目《危險邊緣》裡所有的冠軍選手 一開始,沃森表現不佳 但它進步的速度超乎常人 就在戴維.費魯奇 (Dave Ferrucci) 給我在麻省理工學院的學生 看這張圖的不久後 沃森打敗了《危險邊緣》的世界冠軍 七歲,沃森差不多還在童年時期 最近,沃森的老師讓它在 無人指導的情況下上網 隔天,它開始以髒話回答問題 該死!(笑聲)
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.
但你們知道嗎?沃森長得很快 它參加客服中心工作的考試,全數通過 它申請法律、銀行及醫療方面的工作 有一些通過了 這種情況下 我們發明了智慧型機器 或許還是人類史上最重要的發明 卻有人說創新停滯了,這不是很諷刺嗎? 像第一及第二次工業革命 新機器時代涵蓋的所有層面 至少要一個世紀才會完全落幕 但這樣的革命是很驚人的
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.
所以這代表我們沒有後顧之憂了嗎? 不,科技不能主導命運 生產力是前所未有的高 但有工作的人變少了 過去十年來,我們創造了史無前例的財富 但多數的美國人,所得卻下降了 這是很嚴重的排擠效應 生產力排擠就業率 財富排擠了工作 其實,這種情況不意外,幾百萬人 對於這樣的排擠效應感到失望 但就像大多數人一樣 他們誤解了基本的原因 科技發展神速 把越來越多人拋諸腦後 現在的例行公事,我們都可以 將其改編成一組機器可讀的指令 然後複製一百萬遍
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.
最近我偶然聽到一則對話 可以象徵這些經濟狀況 有個男的說:「不,我不要再請稅務公司了 報稅軟體能完成所有報稅員該做的事 而且更快、更便宜還更精確。」 一個專業的工作人員 要怎麼跟一個 39 塊美金的軟體競爭呢? 她沒辦法比 現在,的確有幾百萬美國人 能更快、更便宜又更精確的報稅 這報稅軟體的創辦人 他們自己也做得很好 但是 17% 的報稅員丟了工作 這只是一部分的縮影 不只是軟體和服務方面 還包括媒體及音樂 財務及製造業,零售及貿易 簡單來說,是所有產業 人類在跟機器比速度 大部分都輸了
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.
該怎麼做才能共同創造繁榮的社會? 答案不會是放慢科技發展的速度 我們不要去對抗機器 而是應該學會去跟機器一起競爭 這是很大的挑戰
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."
新機器時代 可以回朔到 15 年前的某一天 國際西洋棋世界冠軍 加里.卡斯帕羅夫(Gary Kasparov) 跟一台超級電腦:深藍(Deep Blue),一起比賽 那天電腦贏了 而現在,一支手機裡的西洋棋遊戲 都可以打敗一位西洋棋大師 這種情況真慘,當被問到 他會用什麼方法來對抗電腦 荷蘭西洋棋大師 約翰.唐納(Jan Donner)回答: 「我會帶鐵鎚去。」
(Laughter)
(笑聲)
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.
但現在電腦已經不是西洋棋世界冠軍了 冠軍也不是人 因為卡斯帕羅夫舉辦了一種自由式比賽 這種比賽讓人類和電腦 可以一起合作 贏家不是大師 也不是超級電腦 冠軍有的是團隊合作 他們展現了人類和電腦 是如何並肩作戰,打敗任何一台電腦 或是任何一個人孤軍奮戰 和電腦一起競爭 比對抗電腦來得有效 科技不能主導我們的命運 是我們主導自己的命運
Thank you.
謝謝大家
(Applause)
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