Governing Epistemic Risk in Large Language Model Use for Art History and Art Criticism Instruction: A Policy Analysis

The integration of large language models (LLMs) into higher education has proceeded faster than the development of discipline-sensitive governance. This gap is especially consequential in art history and art criticism instruction, where learning depends not only on factual accuracy but also on source fidelity, context reconstruction, interpretive plurality, and accountable judgment. This article develops a policy-centered analysis of the epistemic risks posed by LLM use in these domains. Drawing on international governance instruments and policy guidance from UNESCO, the OECD, NIST, and the European Union, as well as recent scholarship on hallucination, bias, automation, academic integrity, and higher education governance, the article argues that the distinctive epistemic structure of art-historical and critical inquiry makes these subjects vulnerable to a specific cluster of harms: fabricated attributions and references, canon-reinforcing bias, decontextualized summaries, interpretive flattening, and the outsourcing of judgment to systems whose outputs carry an unwarranted aura of authority. Existing higher-education policies on generative artificial intelligence often remain overly generic, framing risk in terms of plagiarism or disclosure while failing to address the epistemic conditions of disciplines organized around contested interpretation, visual evidence, and historically situated argument. In response, the article proposes a governance framework for art history and art criticism instruction organized around six principles: task classification by epistemic sensitivity; evidence-traceability requirements; assessment redesign to privilege documented reasoning; mandatory disclosure as pedagogical metadata rather than merely as compliance; procurement and tool approval standards for educational uses; and procedural safeguards to protect students from biased detection and opaque sanctions. The article concludes that policy for LLM use in art education should move beyond permissive tool adoption or blanket prohibition toward an institutional model of epistemic stewardship.