[2607.29380] The Tragedy of the Cognitive Commons: How AI Could Disrupt the Regeneration of Professional Expertise
Skip to main content
Search arXiv
Press Enter to search · Advanced search
-->
Computer Science > Computers and Society
arXiv:2607.29380 (cs)
[Submitted on 31 Jul 2026]
Title:The Tragedy of the Cognitive Commons: How AI Could Disrupt the Regeneration of Professional Expertise
Authors:Nolan Lovett<br>View a PDF of the paper titled The Tragedy of the Cognitive Commons: How AI Could Disrupt the Regeneration of Professional Expertise, by Nolan Lovett
View PDF
Abstract:Artificial intelligence is reshaping cognitive work, but Human Resource Development scholarship has treated this transformation as an organizational training challenge, leaving the collective regeneration of professional expertise unexamined. This conceptual paper introduces the Cognitive Commons framework, integrating commons theory, HRD scholarship, and distributed cognition to explain how rational AI adoption decisions can deplete the shared expertise pool professions require for renewal. The framework distinguishes Internalized Mastery (deep domain knowledge from sustained practice) from Distributed Mastery (orchestrating human-AI systems), and develops the Validation Tether: effective AI oversight depends on the expertise AI adoption may undermine. Early labor market and clinical evidence suggests possible disruption to expertise-regeneration pathways in highly AI-exposed sectors, though adoption is recent and the strongest signals come from leading sectors rather than all professions. Five factors determine occupational vulnerability, and governance arrangements may form across organizational, professional-association, and policy levels. The paper reframes expertise development as collective stewardship rather than organizational optimization, with implications for HRD theory and workforce policy.
Comments:<br>Author accepted manuscript. Published in Human Resource Development Review; the version of record is available at the DOI. Submitted 2 November 2025, accepted 6 July 2026, published online 26 July 2026. This is a work of the United States Government and is not subject to copyright protection in the United States (17 U.S.C. 105)
Subjects:
Computers and Society (cs.CY); General Economics (econ.GN)
Cite as:<br>arXiv:2607.29380 [cs.CY]
(or<br>arXiv:2607.29380v1 [cs.CY] for this version)
https://doi.org/10.48550/arXiv.2607.29380
Focus to learn more
arXiv-issued DOI via DataCite (pending registration)
Journal reference:<br>Human Resource Development Review, advance online publication (2026)
Related DOI:
https://doi.org/10.1177/15344843261470602
Focus to learn more
DOI(s) linking to related resources
Submission history<br>From: Nolan Lovett [view email]<br>[v1]<br>Fri, 31 Jul 2026 13:04:07 UTC (401 KB)
Full-text links:<br>Access Paper:
View a PDF of the paper titled The Tragedy of the Cognitive Commons: How AI Could Disrupt the Regeneration of Professional Expertise, by Nolan Lovett<br>View PDF
view license
Current browse context:
cs.CY
next >
new<br>recent<br>| 2026-07
Change to browse by:
cs<br>econ<br>econ.GN<br>q-fin<br>q-fin.EC
References & Citations
NASA ADS<br>Google Scholar
Semantic Scholar
export BibTeX citation<br>Loading...
BibTeX formatted citation
×
loading...
Data provided by:
Bookmark
Bibliographic Tools
Bibliographic and Citation Tools
Bibliographic Explorer Toggle
Bibliographic Explorer (What is the Explorer?)
Connected Papers Toggle
Connected Papers (What is Connected Papers?)
Litmaps Toggle
Litmaps (What is Litmaps?)
scite.ai Toggle
scite Smart Citations (What are Smart Citations?)
Code, Data, Media
Code, Data and Media Associated with this Article
alphaXiv Toggle
alphaXiv (What is alphaXiv?)
Links to Code Toggle
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub Toggle
DagsHub (What is DagsHub?)
GotitPub Toggle
Gotit.pub (What is GotitPub?)
Huggingface Toggle
Hugging Face (What is Huggingface?)
ScienceCast Toggle
ScienceCast (What is ScienceCast?)
Demos
Demos
Replicate Toggle
Replicate (What is Replicate?)
Spaces Toggle
Hugging Face Spaces (What is Spaces?)
Spaces Toggle
TXYZ.AI (What is TXYZ.AI?)
Related Papers
Recommenders and Search Tools
Link to Influence Flower
Influence Flower (What are Influence Flowers?)
Core recommender toggle
CORE Recommender (What is CORE?)
Author
Venue
Institution
Topic
About arXivLabs
arXivLabs: experimental projects with community collaborators
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.
Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs .
Which authors of this...