When AI summarizes the web instead of sending you to it, the economics of online information quietly unravel.
AI search results like Google’s AI Overview are easy to like. Instead of dodging ads, closing pop-ups, scanning a half-dozen pages, and stitching together an answer yourself, you can often get a speedy AI-generated answer at the top of the page. But frictionless is rarely free: this seamless experience masks a profound economic tension that threatens the very source material AI relies upon. In the new working paper “AI and the Collapse of the www,” HBS AI Institute Associate Alex Chan develops a rigorous, theoretical market-design framework to analyze this potential crisis. Chan’s research shows that even with rational users, accurate AI information, and hardworking publishers, the current internet model could be facing structural collapse.
Why This Matters
Business leaders and executives might recognize some of what Chan is describing through the classic tragedy of the commons. The open web’s stock of human information has functioned as a shared resource, mostly free to anyone with an internet connection, and now to any AI system trained on or retrieving from it. Like a shared fishery or public aquifer, it replenishes only if participants take less than what it needs to regenerate. Meanwhile, an over-harvester reaps the immediate resource rewards but does not bear the full long-term cost of depleting it. The solution to a commons problem lies in designing institutions that use prices, rights, and royalties to align private incentives with the reproduction of the shared resource. That is exactly what Chan’s market design prescriptions attempt to do, and why they deserve serious attention from anyone who depends, as almost every business does today, on the web remaining worth searching.
Link to the HBS AI Institute Insight Article
Link to the Research Paper
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