{
  "id": 11773,
  "url": "https://arxiv.org/abs/2607.15704v1",
  "title": "The CRAFT principles for the responsible use of large language models in policymaking",
  "summary": "Policymakers around the world face the question of how to use artificial intelligence in general, and large language models in particular, to improve the policymaking process. Used well, large language models can strengthen the collection, interpretation and synthesis of policy-relevant information and the drafting of policy-relevant output. Yet the use of large language models in policymaking is associated with risks. Output that is plausible but not necessarily correct, bias resulting from unr",
  "authors": "Willem Fourie, Gray Manicom, Tanya de Villiers-Botha",
  "category": "research",
  "topics": "bias-fairness,regulation",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-17T07:29:59.000Z",
  "fetched_at": "2026-07-20T05:10:09.534Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/11773",
  "original_url": "https://arxiv.org/abs/2607.15704v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}