AI and the Collapse of the www

Alex Chan

No 35344, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: 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.

JEL-codes: D4 D43 D47 D49 D62 D8 D82 D83 L82 L86 O3 O33 (search for similar items in EconPapers)
Date: 2026-06
Note: IO PR
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