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AI and the Collapse of the www
Alex Chan
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Working Paper 35344
DOI 10.3386/w35344
Issue Date June 2026
This paper studies market design for generative AI intermediation. AI answer systems can improve user experience while diverting visits that finance publisher content and generate source-level quality signals. I show that an AI platform that underinternalizes future content reproduction retains too little referral traffic and can make costly open-web information subcritical, even with truthful content, accurate answers, and rational users. The mechanism can be self-reinforcing: less source-level measurement weakens conventional search, inducing further AI reliance. Sustainable repair requires replacing displaced revenue and deleted measurement through visitor-replacement royalties, audited provenance, human-information audits, and keystone-topic compensation.
Acknowledgements and Disclosures
I thank various seminar and workshop participants for their comments. Funding was provided by Harvard Business School AI Institute. Valuable research assistance was provided by Daniel Kornbluth and Ce Li. The views expressed herein are those of the author and do not necessarily reflect the views of the National Bureau of Economic Research.
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Alex Chan, "AI and the Collapse of the www," NBER Working Paper 35344 (2026), https://doi.org/10.3386/w35344.
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Microeconomics
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