Position: Evaluations of AI Moral Reasoning Still Miss Half of the Picture
Recent work on evaluating the moral competence of large language models (LLMs) has focused primarily on what we call the moral value problem, i.e., whether model outputs align with human moral values. In contrast, the moral norm problem, i.e., whether models can identify and correctly apply context-sensitive moral norms, remains underexplored. We posit that this imbalance stems from the field's reliance on descriptive ethics frameworks, such as Moral Foundations Theory and Kohlberg's stages of moral development, which emphasize value representation over normative application. We review existing benchmarks and evaluation methods, and show that they cluster heavily around the value problem,...
| Authors | Aidan Kierans, Ritam Dutt, Kaley Rittichier et al. |
|---|---|
| Primary category | cs.AI |
| Published | 29 May 2026 |
| Last updated at source | 29 May 2026 |
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