What is it about?
Organizations are using AI to take over routine junior work. That work was also how people learned their profession. This paper argues that because every organization draws experienced staff from a shared pool that nobody owns, each one has a reason to cut developmental work, and the collective result is that the pool stops being replenished. It also argues that reliable human oversight of AI depends on independent expertise produced by exactly the work being automated.
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Why is it important?
Most discussion of AI and work focuses on job losses or on retraining. This paper identifies a different risk that neither approach can address, because it is a collective action problem rather than an organizational one. No single employer can solve it alone. It also connects directly to AI governance: proposals that rely on a human in the loop assume a continuing supply of independently competent humans, and do not explain how those humans will be developed.
Perspectives
I work on how professions build expertise, and I kept seeing the same pattern described as a hiring problem or a training problem when it looked structural to me. The paper is an attempt to name that structure and to specify where the effect should show up first, so the claim can be tested rather than just asserted. I am careful to separate what has been measured, the gap between assisted performance and independent capability, from what I am predicting, which is depletion at the level of a whole profession.
Dr. Nolan Lovett
Old Dominion University
Read the Original
This page is a summary of: The Tragedy of the Cognitive Commons: How AI Could Disrupt the Regeneration of Professional Expertise, Human Resource Development Review, July 2026, SAGE Publications,
DOI: 10.1177/15344843261470602.
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