Follow the Norm: Accounting for Fine-Tuning and Prompt Effects on Model Rationales
Normative datasets are often used to train and align AI systems, but the norms they contain can function as action-guiding patterns rather than neutral moral knowledge. We propose treating the AI system as a proxy actor and test whether dataset-level norms can shift it away from its baseline safety behavior when it faces high-conflict dilemmas. We make three contributions. First, we demonstrate in controlled experiments that norm-breaking fine-tuning yields norm-divergent actions justified by self-interested rationales, suggesting a systematic shift in patterns of justification. Second, we establish a practical audit trail linking downstream justifications to upstream norms using mixed me...
| Authors | Long Hoang Nguyen, Brice Valentin Kok-Shun, Guangyu Du et al. |
|---|---|
| Primary category | cs.CY |
| Published | 13 August 2026 |
| Last updated at source | 13 August 2026 |
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