{
  "id": 293,
  "url": "https://arxiv.org/abs/2607.02972v1",
  "title": "A Scalable Approach to Evaluating Moral Sensitivity in LLMs",
  "summary": "Moral sensitivity is the ability to identify the morally relevant features of a decision situation and use them as the basis for action. It is the foundation of broader moral competence: any other moral reasoning capabilities will be irrelevant if an agent lacks sensitivity to the relevant facts. In this paper, we offer a new evaluation of LLM moral sensitivity and in doing so, we address and resolve a central problem in AI alignment research: how to scale behavioural evaluations beyond expensiv",
  "authors": "Daniel Kilov, Secil Yanik Guyot, Caroline Hendy, Sichao Li, Seth Lazar",
  "category": "research",
  "topics": "safety-alignment,agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-03T05:28:43.000Z",
  "fetched_at": "2026-07-14T14:14:24.249Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/293",
  "original_url": "https://arxiv.org/abs/2607.02972v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}