Artificial intelligence, the knowledge problem, and academic judgment: an Austrian perspective

Abstract

Recent advances in generative artificial intelligence have renewed claims that university teaching and research can be largely automated. This article argues that such claims confuse information processing with judgment. Drawing on Hayek’s theory of dispersed and tacit knowledge, Huerta de Soto’s analysis of computation and entrepreneurial discovery, and the theory of judgment under Knightian uncertainty, it explains why greater computational capacity does not eliminate the knowledge problem.