(p. A2) For centuries, new waves of automation have been greeted by predictions of widespread job loss and convulsive disruption. For centuries, the predictions have been wrong.
. . .
Predictions of technology’s labor-market impacts are notoriously flawed. Experiments like those involving AI often fail to replicate in the real world. Nearly two decades ago, the advent of international fiber-optic connections led some scholars to estimate a fifth of U.S. jobs, such as radiologist, could be offshored. Nothing even close to that happened. A decade ago, economists began warning that self-driving trucks would deprive millions of high-school graduates of good-paying jobs. Today, there are more truck drivers than ever and employers are begging for more.
Often, the technology isn’t good enough or human tasks are too complicated to be replaced. Regulation and inertia get in the way, so the impact unfolds over many years and can’t be detected amid countless other forces at work.
Joshua Gans, an economist specializing in AI at the University of Toronto, said: “Technological changes turn something that was scarce into something that is abundant,” and in the process, “reveal to us what the real value of that stuff is.” Journalists’ greatest value, he said, will be in asking good questions and judging the quality of the answers, not writing up the results.
Spreadsheets made math-intensive analysis easy and cheap, and as a result, led to the creation of countless new tasks and occupations. Large language models could similarly lead to an explosion in applications requiring the synthesis of large amounts of information into serviceable prose.
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(Note: ellipsis added.)
(Note: the online version of the commentary has the date April 5, 2023, and has the same title as the print version.)