S3E24: David Autor, Labor Economist, MIT

Welcome to this week’s episode of "The Mixtape with Scott”! This podcast is dedicated to capturing the personal stories of living economists and creating an oral history of the profession through these narratives. This week, I’m excited to welcome David Autor, an esteemed labor economist from MIT, where he serves as the Daniel (1972) and Gail Rubinfeld Professor, as well as the Margaret MacVicar Faculty Fellow. He was also last year's VP of the AEA, is on the Foreign Affairs board of the US State Department, and is a Digital Fellow at Stanford Digital Economy Lab. The number of accolades is too numerous to list, though, so I will just say that David's pioneering work in labor economics, particularly on the impact of trade, technological change, and the computerization of work, has significantly shaped and re-shaped our understanding of these critical areas.

David Autor is perhaps best known for his influential research on the economic impacts of globalization and technological advancements. His groundbreaking study with David Dorn and Gordon Hanson on the effects of Chinese trade on U.S. labor markets highlighted the deep and often painful economic adjustments faced by local labor markets exposed to import competition. Additionally, his work on the computerization of labor, including studies on skill-biased technological change, has provided crucial insights into how technological advancements reshape the labor market and wage structures.

One of the things you’ll learn in the interview, just as a teaser, is that David was mentored by Lawrence Katz and Alan Krueger, and that mentorship had a lasting effect. Not only did it changed his own human capital and trajectory, it seems also that it changed David’s own attitudes about mentorship. And although we couldn't delve into artificial intelligence in our conversation, Autor’s extensive research on the computerization of labor probably positions him as one of a handful of working economists at the moment whose voice will be kay in understanding the future intersections of AI and labor economics, and probably more than that. So with that I’ll stop, but thanks again to everyone for all your support. If you like the podcast, please share it!

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