Moral Safety in LLMs: Exposing Performative Compliance with Puzzled Cues
As large language models take on morally consequential roles in healthcare, legal, and hiring contexts, we need to examine whether their ethical behaviors are genuine or superficial. We show that current fairness evaluations substantially overestimate moral safety. Models appear fair when demographic identity is stated as an explicit label, yet become measurably less fair when the same identity must be inferred. We term this failure performative compliance, where a model is fair when the presentation resembles a fairness evaluation and less fair as that cue weakens. We introduce a cue-variation methodology that holds the moral dilemma and the demographic identity fixed and varies only how...
| Authors | Mohammadamin Shafiei, Shuyue Stella Li, Yulia Tsvetkov |
|---|---|
| Primary category | cs.CL |
| Published | 30 June 2026 |
| Last updated at source | 3 July 2026 |
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