The AI ​​boom: lessons from history

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It can take a little imagination to see how some innovations could transform an economy. Not so with the latest ones hey Tool. It’s easy – uncomfortable from an author’s perspective – to think of contexts where something like chatgpt, a clever chatbot that has taken the web by storm since its release in November, could either dramatically increase a human worker’s productivity or replace it entirely. The gpt in its name stands for “Generative Pre-Trained Transformer”, which is a special kind of language model. It could well stand for all-purpose technology: an earth-shattering innovation designed to increase productivity in a variety of industries and professions, such as steam engines, electricity, and computers. The economic revolutions fueled by those in the past gpts can give us an idea of ​​how powerful hey could transform economies in the coming years.

In an article published in 1995, Timothy Bresnahan of Stanford University and Manuel Trajtenberg of Tel Aviv University outlined what they saw as characteristics of a general-purpose technology. It must be used across many industries, have an inherent potential for continuous improvement, and generate “innovative complementarities” – that is, generate follow-on innovations in the industries in which it is used. hey widespread seems to be getting better during the day and is used in more and more R&D contexts. When will the economic revolution begin?

The first lesson from history is that even the most powerful new technology takes time to transform an economy. James Watt patented his steam engine in 1769, but steam power did not overtake water as an industrial source of horsepower until the 1830s in Britain and the 1860s in America. In Britain, according to Nicholas Crafts of the University of Sussex, steam’s contribution to productivity growth peaked after 1850, almost a century after Watt’s patent. In the case of electrification, the major technological advances had all been made before 1880, but American productivity growth actually slowed from 1888 to 1907. Almost three decades after the first silicon integrated circuits, Robert Solow, a Nobel Prize-winning economist, was still observing that Computer age was everywhere but in productivity statistics. It wasn’t until the mid-1990s that America finally experienced a computer-aided productivity boom.

The gap between innovation and economic impact is partly due to fine-tuning. Early steam engines were extremely inefficient, consuming prohibitively expensive heaps of coal. Likewise the stunning performance of the last ones hey Tools is a big improvement over those that triggered a boomlet from hey enthusiasm about a decade ago. (Siri, Apple’s virtual assistant, for example, was released in 2011.) Capital constraints can also slow deployment. Robert Allen of New York University Abu Dhabi argues that the slow rise in productivity growth in industrialized Britain reflected a lack of capital to build plant and machinery, which was gradually overcome as capitalists reinvested their hefty profits.

Recent work emphasizes the time required to accumulate so-called intangible capital, or the fundamental know-how required to use new technologies effectively. In fact, Stanford University’s Erik Brynjolfsson, Massachusetts Institute of Technology’s Daniel Rock, and University of Chicago’s Chad Syverson suggest that a disruptive new technology could be associated with a “productivity J-curve.” Measured productivity growth may actually decline in the years or decades after a new technology appears, as firms and workers devote time and resources to studying the technology and designing business processes around it. Only later, when these investments bear fruit, does the J shoot up. That’s what the authors are counting on hey-related investment in intangible capital can already dampen productivity growth, albeit not by much.

Of course, many people have questions about the effects hey on growth give way to concerns about the impact on workers. Here the messages of history are mixed. There is good news: Despite the epoch-making technological and economic change, the fear of technological mass unemployment has never come true. However, tech can and does take a toll on individual professions, in ways that can prove socially disruptive. At the start of the Industrial Revolution, mechanization dramatically increased demand for relatively unskilled workers, but crushed the earnings of craftsmen who had previously done much of the work, leading some to choose to join machine-destroying Luddite movements. And in the 1980s and 1990s, the automation of routine jobs on factory floors and offices displaced many workers of modest means, while encouraging the employment of high- and low-skilled workers.

Gee, pretty awesome

hey could boost the productivity of workers of all skill levels, even writers. But what that means for an occupation as a whole depends on whether improved productivity and lower costs result in a large or small jump in demand. If the assembly line – a process innovation with gpt-similar characteristics – allowed Henry Ford to reduce the cost of manufacturing cars, demand increased, and workers benefited. If hey For example, increases productivity and lowers costs in medicine, which could lead to much higher demand for medical services and professionals.

There is a chance that is powerful hey will break the historical form. A technology capable of accomplishing almost any task that the typical human can do would take humanity into uncharted economic territory. But even in such a scenario, the past holds some lessons. The continued economic growth that accompanied the steam revolution and the further acceleration that came with electrification and other later innovations were themselves unprecedented. They sparked a tremendous scramble to invent new ideas and institutions to ensure that radical economic change led to widespread prosperity and not chaos. Maybe it’s time to climb again soon.

Read more from Free Exchange, our column on business:
Have economists misunderstood inflation? (January 26)
Could Europe end up with a worse inflation problem than America? (January 19)
Warnings from history of a new era in industrial policy (11th January)

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