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Training for Obsolescence? The AI-Driven Education Trap

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  • Andrew J. Peterson

Abstract

Artificial intelligence is simultaneously transforming the production function of human capital in schools and the return to skills in the labor market. We develop a theoretical model to analyze the potential for misallocation when these two forces are considered in isolation. We study an educational planner who observes AI's immediate productivity benefits in teaching specific skills but fails to fully internalize the technology's future wage-suppressing effects on those same skills. Motivated by a pre-registered pilot study suggesting a positive correlation between a skill's "teachability" by AI and its vulnerability to automation, we show that this information friction leads to a systematic skill mismatch. The planner over-invests in skills destined for obsolescence, a distortion that increases monotonically with AI prevalence. Extensions demonstrate that this mismatch is exacerbated by the neglect of unpriced non-cognitive skills and by the endogenous over-adoption of educational technology. Our findings caution that policies promoting AI in education, if not paired with forward-looking labor market signals, may paradoxically undermine students' long-term human capital, such as by crowding out skills like persistence that are forged through intellectual struggle.

Suggested Citation

  • Andrew J. Peterson, 2025. "Training for Obsolescence? The AI-Driven Education Trap," Papers 2508.19625, arXiv.org, revised Nov 2025.
    • Handle: RePEc:arx:papers:2508.19625
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    1. Trieu H. Trinh & Yuhuai Wu & Quoc V. Le & He He & Thang Luong, 2024. "Solving olympiad geometry without human demonstrations," Nature, Nature, vol. 625(7995), pages 476-482, January.
    2. Erik Brynjolfsson & Tom Mitchell & Daniel Rock, 2018. "What Can Machines Learn, and What Does It Mean for Occupations and the Economy?," AEA Papers and Proceedings, American Economic Association, vol. 108, pages 43-47, May.
    3. Heckman, James J. & Kautz, Tim, 2012. "Hard evidence on soft skills," Labour Economics, Elsevier, vol. 19(4), pages 451-464.
    4. Daron Acemoglu & Todd Lensman, 2024. "Regulating Transformative Technologies," American Economic Review: Insights, American Economic Association, vol. 6(3), pages 359-376, September.
    5. David H. Autor, 2015. "Why Are There Still So Many Jobs? The History and Future of Workplace Automation," Journal of Economic Perspectives, American Economic Association, vol. 29(3), pages 3-30, Summer.
    6. Heckman, James J. & Kautz, Tim, 2013. "Fostering and Measuring Skills: Interventions That Improve Character and Cognition," IZA Discussion Papers 7750, IZA Network @ LISER.
    7. Richard B. Freeman, 1976. "A Cobweb Model of the Supply and Starting Salary of New Engineers," ILR Review, Cornell University, ILR School, vol. 29(2), pages 236-248, January.
    8. Jaewoo Ryoo & Sherwin Rosen, 2004. "The Engineering Labor Market," Journal of Political Economy, University of Chicago Press, vol. 112(S1), pages 110-140, February.
    9. Carter, Susan Payne & Greenberg, Kyle & Walker, Michael S., 2017. "The impact of computer usage on academic performance: Evidence from a randomized trial at the United States Military Academy," Economics of Education Review, Elsevier, vol. 56(C), pages 118-132.
    10. Maya Escueta & Vincent Quan & Andre Joshua Nickow & Philip Oreopoulos, 2017. "Education Technology: An Evidence-Based Review," NBER Working Papers 23744, National Bureau of Economic Research, Inc.
    11. Trieu H. Trinh & Yuhuai Wu & Quoc V. Le & He He & Thang Luong, 2024. "Author Correction: Solving olympiad geometry without human demonstrations," Nature, Nature, vol. 627(8004), pages 8-8, March.
    12. Daron Acemoglu & Pascual Restrepo, 2019. "Automation and New Tasks: How Technology Displaces and Reinstates Labor," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 3-30, Spring.
    13. Giorgio Brunello & Patricia Wruuck, 2021. "Skill shortages and skill mismatch: A review of the literature," Journal of Economic Surveys, Wiley Blackwell, vol. 35(4), pages 1145-1167, September.
    14. Bresnahan, Timothy F. & Trajtenberg, M., 1995. "General purpose technologies 'Engines of growth'?," Journal of Econometrics, Elsevier, vol. 65(1), pages 83-108, January.
    15. Daron Acemoglu & Jonas Loebbing, 2022. "Automation and Polarization," NBER Working Papers 30528, National Bureau of Economic Research, Inc.
    16. C. Kirabo Jackson, 2018. "What Do Test Scores Miss? The Importance of Teacher Effects on Non–Test Score Outcomes," Journal of Political Economy, University of Chicago Press, vol. 126(5), pages 2072-2107.
    17. Michael Gerlich, 2025. "AI Tools in Society: Impacts on Cognitive Offloading and the Future of Critical Thinking," Societies, MDPI, vol. 15(1), pages 1-28, January.
    18. Charles F. Manski, 2004. "Measuring Expectations," Econometrica, Econometric Society, vol. 72(5), pages 1329-1376, September.
    19. Holmstrom, Bengt & Milgrom, Paul, 1991. "Multitask Principal-Agent Analyses: Incentive Contracts, Asset Ownership, and Job Design," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 7(0), pages 24-52, Special I.
    20. De Simone, Martin Elias & Tiberti, Federico Hernan & Barron Rodriguez, Maria Rebeca & Manolio, Federico Alfredo & Mosuro, Wuraola & Dikoru, Eliot Jolomi, 2025. "From Chalkboards to Chatbots : Evaluating the Impact of Generative AI on Learning Outcomes in Nigeria," Policy Research Working Paper Series 11125, The World Bank.
    21. Edward Felten & Manav Raj & Robert Seamans, 2021. "Occupational, industry, and geographic exposure to artificial intelligence: A novel dataset and its potential uses," Strategic Management Journal, Wiley Blackwell, vol. 42(12), pages 2195-2217, December.
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