AI, Human Cognition and Knowledge Collapse.

Autor/inn/en	Acemoglu, Daron; Kong, Dingwen; Ozdaglar, Asuman E.
Institution	National Bureau of Economic Research
Titel	AI, Human Cognition and Knowledge Collapse.
Quelle	Cambridge, Mass: National Bureau of Economic Research (2026) PDF als Volltext (1); PDF als Volltext (2) Link als defekt meldenVerfügbarkeit
Reihe	NBER working paper series. w34910
Beigaben	Illustrationen
Sprache	englisch
Dokumenttyp	online; Monografie; Graue Literatur
DOI	10.3386/w34910
Schlagwörter	Wissen; Kognition; Kommunikation; Lernpsychologie; Künstliche Intelligenz; Lernen; Glaube; Arbeitspapier
Abstract	We study how generative AI, and in particular agentic AI, shapes human learning incentives and the long-run evolution of society's information ecosystem. We build a dynamic model of learning and decision-making in which successful decisions require combining shared, community-level general knowledge with individual-level, context-specific knowledge; these two inputs are complements. Learning exhibits economies of scope: costly human effort jointly produces a private signal about their own context and a "thin" public signal that accumulates into the community's stock of general knowledge, generating a learning externality. Agentic AI delivers context-specific recommendations that substitute for human effort. By contrast, a richer stock of general knowledge complements human effort by raising its marginal return. The model highlights a sharp dynamic tension: while agentic AI can improve contemporaneous decision quality, it can also erode learning incentives that sustain long-run collective knowledge. When human effort is sufficiently elastic and agentic recommendations exceed an accuracy threshold, the economy can tip into a knowledge-collapse steady state in which general knowledge vanishes ultimately, despite high-quality personalized advice. Welfare is generally non-monotone in agentic accuracy, implying an interior, welfare-maximizing level of agentic precision and motivating information-design regulations. In contrast, greater aggregation capacity for general knowledge--meaning more effective sharing and pooling of human-generated general knowledge--unambiguously raises welfare and increases resilience to knowledge collapse.
Erfasst von	ZBW - Leibniz-Informationszentrum Wirtschaft, Kiel
Update	2026/3