Edward Conard

Top Ten New York Times Bestselling Author

  • “…serious thinking for serious thinkers. …a thought-provoking blueprint for growing middle- and working-class incomes.” - Mitt Romney, former Governor of Massachusetts
  • “…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
  • “…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
  • “Unintended Consequences should be read by anyone who takes for granted the superiority of progressive taxation and has not thought carefully about the trade-offs involved.” - The New Republic
  • “…a must-read for serious students of economic policy.” - Glenn Hubbard, Dean, Columbia Business School, and former Chairman of the Council of Economic Advisers
  • “Unintended Consequences offers deep and well-argued analyses on almost every issue.” - The New York Times
  • “Unintended Consequences is far smarter and more thought-provoking than most economics written for the general public” - Greg Mankiw, Harvard University, Former Chairman of the Council of Economic Advisors
  • “…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
  • “…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 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
  • “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
  • “…a very valuable contribution.” - Larry Summers, former Secretary of the Treasury and director of the National Economic Council, president emeritus, Harvard University
Upside of Inequality Oxford Unintended Consequences

AI Summary. By allowing senior workers to complete tasks independently, artificial intelligence may reduce entry-level opportunities and impede younger workers' acquisition of tacit knowledge, the practical expertise that resists codification. The authors estimate this could lower the long-run annual growth rate of U.S. per capita output by 0.05 to 0.35 percentage points, depending on scale.

Enrique Ide arXiv
Date Posted:

“By enabling senior workers to accomplish more tasks independently, AI may inadvertently reduce entry-level opportunities, raising concerns about how future generations will acquire essential expertise” and potentially lowering growth in per capita GDP.

Does automating entry-level work slow long-run growth by blocking knowledge transfer?

Core argument: Back-of-the-envelope calculations suggest AI-driven automation of entry-level work could lower the long-run annual growth rate of U.S. per capita output by 0.05 to 0.35 percentage points, depending on the scale of automation.

By enabling senior workers to accomplish more tasks independently, AI may inadvertently reduce entry-level opportunities, raising concerns about how future generations will acquire essential expertise, [in particular] tacit knowledge—practical insights that resist codification and are critical for workplace success. While automation delivers immediate productivity gains, it can undermine long-term growth by hindering younger workers’ acquisition of tacit skills. Back-of-the-envelope calculations suggest AI-driven entry-level automation could lower the long-run annual growth rate of U.S. per capita output by 0.05 to 0.35 percentage points, depending on its scale. AI co-pilots—systems providing access to tacit-like expertise once obtained only through direct experience—can partially offset these losses by assisting individuals who fail to develop adequate skills early in their careers, but may also weaken junior workers’ incentives to engage in hands-on learning. These findings challenge the view that AI will automatically lead to higher economic growth, highlighting the need to safeguard—or deliberately create—entry-level opportunities to fully realize AI’s potential.

Takeaways by Macro Roundup® AI

  1. Back-of-the-envelope calculations suggest AI-driven automation of entry-level work could lower the long-run annual growth rate of U.S. per capita output by 0.05 to 0.35 percentage points, depending on the scale of automation.
  2. By enabling senior workers to complete more tasks independently, AI may reduce the entry-level opportunities through which younger workers acquire tacit knowledge—practical insights that resist codification and are critical for workplace success.
  3. AI co-pilots can partially offset these losses by giving workers who fail to build skills early access to tacit-like expertise, but may also weaken junior workers' incentives to engage in hands-on learning.

Related Articles:

  • Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence — Using payroll records covering millions of US workers, the authors find employment for workers aged 22–25 in occupations most exposed to artificial intelligence, such as software developers and customer service representatives, declined 6%, while employment for older workers in those occupations rose 6–9%. Employment in less-exposed occupations grew comparably across age groups.
  • Artificial Intelligence in the Knowledge Economy — The authors model artificial intelligence in the knowledge economy and find that non-autonomous AI acting only as a co-pilot tends to benefit the least knowledgeable workers most, while autonomous AI that can also act as a co-worker primarily benefits the most knowledgeable. Job-posting evidence shows declines in low-knowledge white-collar postings alongside increases in high-knowledge roles.
  • Generative AI at Work — A study of 5,179 customer support agents finds that access to a generative AI conversational assistant raised issues resolved per hour by 14% on average, with the largest gains for novice and low-skilled workers and minimal effect on experienced, highly skilled ones. The authors also find AI assistance improved customer sentiment, reduced requests for managerial intervention, and improved employee retention.
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