The AI boom: lessons from history

It can take a little imagination to see how some innovations might change an economy. Not so with the latest ai tools. It is easy—from a writer’s perspective, uncomfortably so—to think of contexts in which something like Chatgpt, a clever chatbot which has taken the web by storm since its release in November, could either dramatically boost a human worker’s productivity or replace them outright. The gpt in its name stands for “generative pre-trained transformer”, which is a particular kind of language model. It might well stand for general-purpose technology: an earth-shaking sort of innovation which stands to boost productivity across a wide-range of industries and occupations, in the manner of steam engines, electricity and computing. The economic revolutions powered by those earlier gpts can give us some idea how powerful ai might transform economies in the years ahead.

In a paper published in 1995, Timothy Bresnahan of Stanford University and Manuel Trajtenberg of Tel Aviv University set out what they saw as the characteristics of a general-purpose technology. It must be used in many industries, have an inherent potential for continued improvement and give rise to “innovational complementarities”—that is, induce knock-on innovation in the industries which use it. ai is being adopted widely, seems to get better by the day and is being deployed in ever more r&d contexts. So when does the economic revolution begin?