2013年1月8日 星期二

Is Growth Over? (By PAUL KRUGMAN )

 這篇議題與H. A. Simon的想法有些關連. 有機會再討論


Is Growth Over?

The great bulk of the economic commentary you read in the papers is focused on the short run: the effects of the “fiscal cliff” on U.S. recovery, the stresses on the euro, Japan’s latest attempt to break out of deflation. This focus is understandable, since one global depression can ruin your whole day. But our current travails will eventually end. What do we know about the prospects for long-run prosperity?
The answer is: less than we think.
The long-term projections produced by official agencies, like the Congressional Budget Office, generally make two big assumptions. One is that economic growth over the next few decades will resemble growth over the past few decades. In particular, productivity — the key driver of growth — is projected to rise at a rate not too different from its average growth since the 1970s. On the other side, however, these projections generally assume that income inequality, which soared over the past three decades, will increase only modestly looking forward.
It’s not hard to understand why agencies make these assumptions. Given how little we know about long-run growth, simply assuming that the future will resemble the past is a natural guess. On the other hand, if income inequality continues to soar, we’re looking at a dystopian, class-warfare future — not the kind of thing government agencies want to contemplate.
Yet this conventional wisdom is very likely to be wrong on one or both dimensions.
Recently, Robert Gordon of Northwestern University created a stir by arguing that economic growth is likely to slow sharply — indeed, that the age of growth that began in the 18th century may well be drawing to an end.
Mr. Gordon points out that long-term economic growth hasn’t been a steady process; it has been driven by several discrete “industrial revolutions,” each based on a particular set of technologies. The first industrial revolution, based largely on the steam engine, drove growth in the late 18th and early 19th centuries. The second, made possible, in large part, by the application of science to technologies such as electrification, internal combustion and chemical engineering, began circa 1870 and drove growth into the 1960s. The third, centered around information technology, defines our current era.
And, as Mr. Gordon correctly notes, the payoffs so far to the third industrial revolution, while real, have been far smaller than those to the second. Electrification, for example, was a much bigger deal than the Internet.
It’s an interesting thesis, and a useful counterweight to all the gee-whiz glorification of the latest tech. And while I don’t think he’s right, the way in which he’s probably wrong has implications equally destructive of conventional wisdom. For the case against Mr. Gordon’s techno-pessimism rests largely on the assertion that the big payoff to information technology, which is just getting started, will come from the rise of smart machines.
If you follow these things, you know that the field of artificial intelligence has for decades been a frustrating underachiever, as it proved incredibly hard for computers to do things every human being finds easy, like understanding ordinary speech or recognizing different objects in a picture. Lately, however, the barriers seem to have fallen — not because we’ve learned to replicate human understanding, but because computers can now yield seemingly intelligent results by searching for patterns in huge databases.
True, speech recognition is still imperfect; according to the software, one irate caller informed me that I was “fall issue yet.” But it’s vastly better than it was just a few years ago, and has already become a seriously useful tool. Object recognition is a bit further behind: it’s still a source of excitement that a computer network fed images from YouTube spontaneously learned to identify cats. But it’s not a large step from there to a host of economically important applications.
So machines may soon be ready to perform many tasks that currently require large amounts of human labor. This will mean rapid productivity growth and, therefore, high overall economic growth.
But — and this is the crucial question — who will benefit from that growth? Unfortunately, it’s all too easy to make the case that most Americans will be left behind, because smart machines will end up devaluing the contribution of workers, including highly skilled workers whose skills suddenly become redundant. The point is that there’s good reason to believe that the conventional wisdom embodied in long-run budget projections — projections that shape almost every aspect of current policy discussion — is all wrong.
What, then, are the implications of this alternative vision for policy? Well, I’ll have to address that topic in a future column.



你在報紙上讀到的經濟評論中,很大一部分討論的都是短期問題:“財政懸崖”對美國經濟復 蘇的影響,歐元面臨的壓力,日本最近想要擺脫通貨緊縮而做的努力。關注這些問題是可以理解的,若發生一場全球經濟危機,你的生活就被毀了。然而,我們現在 的這些煎熬最終會結束。對於長期發展的前景,我們又知道多少呢?
美國國會預算辦公室(Congressional Budget Office)等官方機構所做的長期預測,通常都基於兩個假定。其中一個假定是,接下來數十年內,經濟增長狀況將和過去數十年內相仿。比如,生產力這一驅 動經濟發展的主要動力,其增長速度將差不多保持它自20世紀70年代以來的平均水平。然而,另一方面,這些預測通常會假定,過去30年以來嚴重加劇的收入 差距,在未來只會稍微擴大。
最近,西北大學(Northwestern University)的羅伯特·戈登(Robert Gordon)發表言論稱,經濟增長速度可能會大幅下滑——事實上,18世紀以來的增長時代可能將要終結。他的這一觀點引發了極大爭議。
戈登指出,長期經濟增長並非一個持續穩定的過程;它受到了幾次的“工業革命”的驅動,而每次工業革命都以一系列特定的技術為基礎。18世紀末19世 紀初,以蒸汽機為主要標誌的第一次工業革命,推動了經濟的發展。而第二次工業革命則主要得益於科學在技術領域的應用,比如電氣化、內燃機技術以及化學工 程。這場革命大約出現在1870年,它對經濟增長的推動作用一直持續到20世紀60年代。而圍繞着信息技術發生的第三次工業革命,則定義了我們當前的時 代。
如果你密切關注這個領域,你就會知道,幾十年來,人工智能領域的表現一直不盡如人意,成績寥寥。因為結果證明,每個人都能輕而易舉做到的事情,電腦 卻難以完成,比如理解平常的話語或者辨識圖片中的不同物體。然而,不久前,這些屏障似乎開始被推倒——不是因為我們學會了如何複製人類的智力,而是因為電 腦現在可以通過在龐大數據庫中搜索規律性的東西,得出看似智能的結果。
的確,語音識別技術仍然不完善,根據軟件,一個怒氣沖沖的聲音對我說,我“真雨春”。但這種技術比起幾年前已經進步得多了,而且已經成為非常有用的 工具。物體識別功能更落後:計算機網絡學會通過從YouTube上的圖像來識別貓,這仍然值得我們激動。但從當前水平發展到具有重要經濟意義的應用程序並 非遙不可及。
但關鍵問題是,誰會從這樣增長中受益?不幸的是,認為大多數美國人將會因此落伍,因為智能機器最終會致使勞動者貢獻的價值降低,包括那些高級技工, 他們的技能會突然之間變得多餘,我們太容易得出這樣的結論了。重點是,我們有充分理由相信,那些對當前政策討論幾乎每一方面都產生影響的長期預算預測所體 現的傳統思維,是完全錯誤的。