Edward Conard

Top Ten New York Times Bestselling Author

  • “…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
  • “A full-throated defense of economic dynamism.” - The Wall Street Journal
  • “…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
  • “Unintended Consequences represents the most cogent and persuasive analysis of the Financial Crisis to date.” - Andrei Shleifer, 1999 John Bates Clark Medal Winner
  • “…a very valuable contribution.” - Larry Summers, former Secretary of the Treasury and director of the National Economic Council, president emeritus, Harvard University
  • “There are an amazing number of good ideas and interesting points made in Unintended Consequences. The thinking underlying it, and the obvious depth of understanding of the author, are very impressive.” - Steven Levitt, coauthor of Freakonomics; 2004 John Bates Clark Medal
  • “Unintended Consequences is full of substance, it is one of the must-read books of the year, and once I finish it I will be giving it a second read through right away.” - Tyler Cowen, Professor, George Mason University
  • “…reminds us that inequality sends a signal of what society lacks most, in America’s case, entrepreneurship and risk taking.” - Lawrence Lindsey, CEO, The Lindsey Group, former Director of the National Economic Council
  • “Unintended Consequences offers deep and well-argued analyses on almost every issue.” - The New York Times
  • “Unintended Consequences provides a provocative interpretation of the causes of the global financial crisis and the policies needed to return to rapid growth. Whether you agree or not, this analysis is well worth reading.” - Nouriel Roubini, New York University; Chairman, Roubini Global Economics
  • “…a must-read for serious students of economic policy.” - Glenn Hubbard, Dean, Columbia Business School, and former Chairman of the Council of Economic Advisers
  • “…reminds us that inequality sends a signal of what society lacks most, in America’s case, entrepreneurship and risk taking.” - Lawrence Lindsey, CEO, The Lindsey Group, former Director of the National Economic Council
Upside of Inequality Oxford Unintended Consequences

AI Summary. US labor force survey data show occupational stability rather than economy-wide disruption from generative artificial intelligence, with the dissimilarity in occupational mix between older and more recent college graduates rarely deviating outside a 30–33% range. The authors note this limited early impact resembles the pace of change in previous periods of technological disruption.

Martha Gimbel, Molly Kinder, Joshua Kendall, and Maddie Lee Yale University
Date Posted:

An index of dissimilarity of occupational mix between college grads aged 20–24 and those 25–34 showed a modest uptick in March relative to November 2022, but remains within its historical range, suggesting at most a modest labor market effect from AI.

Is artificial intelligence reshaping the labor market for recent graduates?

Core argument: The dissimilarity in occupational mix between older and more recent college graduates has rarely moved outside the 30–33% range since January 2021, which the authors argue is inconsistent with generative AI substantially changing the labor market for recent graduates.

Overall, the March 2026 CPS releases do not indicate a meaningful shift from December in most categories. If generative AI were in fact substantially changing the labor market for recent college graduates, we would expect to see a growing dissimilarity in the occupational mix between these two groups [Figure 8]. Taking a closer look at the trend since January 2021, the dissimilarity between older and more recent college graduates rarely deviates outside of the 30-33% range [Figure 9]. The picture of AI’s impact on the labor market that emerges from our data is one that largely reflects stability, not major disruption at an economy-wide level. The lack of widespread impacts at this early stage is not unlike the pace of change with previous periods of technological disruption. [As a prospective research strategy], preregistering areas where we would expect to see the impact and continuing to monitor monthly impacts will help us distinguish rumor from fact.

Takeaways by Macro Roundup® AI

  1. The dissimilarity in occupational mix between older and more recent college graduates has rarely moved outside the 30–33% range since January 2021, which the authors argue is inconsistent with generative AI substantially changing the labor market for recent graduates.
  2. The March 2026 Current Population Survey releases show no meaningful shift from December in most categories, a picture the authors characterize as stability rather than major economy-wide disruption from AI.
  3. The authors note that the absence of widespread AI impacts at this early stage resembles the pace of change in previous periods of technological disruption, and propose preregistering expected impact areas and monitoring monthly data to distinguish rumor from fact.

Related Articles:

  • Looking for the Ladder — The article argues that the hiring downturn in occupations most exposed to generative AI reflects interest-rate sensitivity rather than AI itself, since roughly 38% of workers in the most AI-exposed quintile work in information, finance and insurance, and professional and technical services, versus under 2% in the least-exposed quintile.
  • AI and Young-adult Jobs: The Real Mystery — Employment rates have declined for young adults both with and without college degrees, with non-degree holders faring marginally worse, and employment growth for young workers of all education levels has lagged that of other workers. Artificial intelligence can replace some lower-skilled jobs, but those jobs are too few to drive youth labor market weakness.
  • AI and the Fable of the ATMs — Bank tellers per branch fell steadily as automated teller machines spread, and total teller employment held up only because banking deregulation drove a rise in branch numbers; teller jobs are down nearly 40% from their peak. The author argues invoking this case for AI requires identifying an equivalent offsetting source of labor demand.
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