{
  "id": 19128,
  "url": "https://arxiv.org/abs/2603.00048",
  "title": "MOSAIC: Unveiling the Moral, Social and Individual Dimensions of Large Language Models",
  "summary": "arXiv:2603.00048v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly deployed in sensitive applications including psychological support, healthcare, and high-stakes decision-making. This expansion has motivated growing research into the ethical and moral foundations underlying LLM behavior, raising critical questions about their reliability in ethical reasoning. However, existing studies and benchmarks rely almost exclusively on Moral Foundation Theory (MFT), largely",
  "authors": "Erica Coppolillo, Emilio Ferrara",
  "category": "research",
  "topics": "healthcare",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-14T04:00:00.000Z",
  "fetched_at": "2026-08-14T05:10:49.168Z",
  "source_slug": "arxiv-cscy",
  "source_name": "arXiv cs.CY",
  "source_homepage": "https://arxiv.org/list/cs.CY/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/19128",
  "original_url": "https://arxiv.org/abs/2603.00048",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}