The Return of Human Judgment: Why Interpretation Still Matters in the Age of Artificial Intelligence

Abstract

Generative artificial intelligence can summarize, translate, classify, synthesize, and produce interpretations that are fluent and plausible. This development encourages a misleading question: what work will remain for human scholars when machines perform so many intellectual operations? This commentary argues that the more consequential question concerns responsibility that cannot be reduced to generation. Drawing on hermeneutics, recent work on generative AI and epistemic agency, and debates over academic authorship, it distinguishes four epistemic levels: information, synthesis, interpretation, and judgment. Information concerns what can be retrieved; synthesis organizes materials; interpretation situates meaning in context; judgment evaluates significance and accepts responsibility for a claim. These levels can be connected without becoming interchangeable. The article develops two propositions. First, plausible language generation is not equivalent to historically and culturally adequate interpretation. Second, generation can be distributed, but accountability cannot. Human scholars therefore retain a distinctive role in framing questions, criticizing sources, choosing interpretations, and defending publication. The goal is a human--AI division of epistemic labor in which AI expands possibilities while human epistemic ownership remains attached to reasons, significance, and conclusions.