というNBER論文(原題は「Applying AI to Rebuild Middle Class Jobs」)をMITのDavid Autorが上げている(H/T Mostly Economics;cf. 同内容のNOEMA記事に関する本人のツイート)。

While the utopian vision of the current Information Age was that computerization would flatten economic hierarchies by democratizing information, the opposite has occurred. Information, it turns out, is merely an input into a more consequential economic function, decision-making, which is the province of elite experts. The unique opportunity that AI offers to the labor market is to extend the relevance, reach, and value of human expertise. Because of AI’s capacity to weave information and rules with acquired experience to support decision-making, it can be applied to enable a larger set of workers possessing complementary knowledge to perform some of the higher-stakes decision-making tasks that are currently arrogated to elite experts, e.g., medical care to doctors, document production to lawyers, software coding to computer engineers, and undergraduate education to professors. My thesis is not a forecast but an argument about what is possible: AI, if used well, can assist with restoring the middle-skill, middle-class heart of the US labor market that has been hollowed out by automation and globalization.

以下はMostly Economicsの本文からの引用の孫引き。

Most “experts” of our era would be at a loss if teleported back to the 18th century. Prior to the Industrial Revolution, goods were handmade by skilled artisans: wagon wheels by wheelwrights; clothing by tailors; shoes by cobblers; timepieces by clockmakers; firearms by blacksmiths. Artisans spent years acquiring at least two broad forms of expertise: procedural expertise, meaning following highly practiced steps to produce an outcome; and expert judgment, meaning adapting those procedures to variable instances.

Although artisanal expertise was revered, its value was ultimately decimated by the rise of mass production in the 18th and 19th centuries (Hounshell, 1984). Mass production meant breaking the complex work of artisans into discrete, self-contained and often quite simple steps that could be carried out mechanistically by a team of production workers, aided by machinery and overseen by managers with higher education levels. Mass production was vastly more productive than artisanal work, but conditions for rank-and-file workers were typically hazardous and grueling, requiring no specialized expertise beyond a willingness to labor under punishing conditions for extremely low pay.
職人の専門性は尊敬されていたが、その価値は最終的に18世紀と19世紀の大量生産の台頭によって消滅した(Hounshell, 1984)。大量生産は、職人の複雑な仕事を、自己完結していて、しばしば極めて単純な個々の*1段階に分解することを意味していた。そのように分解された仕事は、教育程度の高い管理者の監督下で、機械の助けを得つつ、生産労働者のチームによって機械的に遂行できるようになった。大量生産は職人の仕事よりも遥かに生産的であったが、一般の労働者の環境は危険かつ激務なのが普通で、極めて低い賃金のために過酷な環境下で働く意思以外の特別な専門性は要求されなかった。

As the tools, processes and products of modern industry gained sophistication, demand for a new form of worker expertise — “mass expertise” — burgeoned (Goldin and Katz, 1998; Buyst et al., 2018). Workers operating and maintaining complex equipment required training and experience in machining, fitting, welding, processing chemicals, handling textiles, dyeing and calibrating precision instruments, etc. Away from the factory floor, telephone operators, typists, bookkeepers and inventory clerks, served as information conduits — the information technology of their era.
近代産業の道具、プロセス、および製品が洗練されるのに伴い、労働者の新たな形の専門性である「大量生産の専門性」への需要が急増した(Goldin and Katz, 1998; Buyst et al., 2018)。複雑な装置を操作し維持する労働者は、機械加工、取り付け、溶接、薬品加工、織物の取り扱い、染色、精密機械の較正などに訓練と経験が要求された。工場の現場以外では、電話交換手、簿記係、在庫係が情報の導管――その時代の情報技術――として機能した。

Stemming from the innovations pioneered during World War II, the Computer Era (AKA the Information Age) ultimately extinguished much of the demand for mass expertise that the Industrial Revolution had fostered. The unique power of the digital computer, relative to all technologies that preceded it, was its ability to cheaply, reliably and rapidly execute cognitive and manual tasks encoded in explicit, deterministic rules, i.e., what economists called “routine tasks” and what software engineers call programs.

Like the Industrial and Computer revolutions before it, Artificial Intelligence marks an inflection point in the economic value of human expertise. To appreciate why, consider what distinguishes AI from the computing era that we’re now leaving behind. Pre-AI, computing’s core capability was its faultless and nearly costless execution of routine, procedural tasks. Its Achilles’ heel was its inability to master non-routine tasks requiring tacit knowledge. Artificial Intelligence’s capabilities are precisely the inverse.

Artificial Intelligence is this inversion technology. By providing decision support in the form of real-time guidance and guardrails, AI could enable a larger set of workers possessing complementary knowledge to perform some of the higher-stakes decision-making tasks currently arrogated to elite experts like doctors, lawyers, coders and educators. This would improve the quality of jobs for workers without college degrees, moderate earnings inequality, and — akin to what the Industrial Revolution did for consumer goods — lower the cost of key services such as healthcare, education and legal expertise.

*1:Mostly Economicsの引用ではdiscreetとなっていたが、NOEMA記事ではdiscreteになっていたので、ここでは後者に修正した。