{
  "id": 3374,
  "url": "https://arxiv.org/abs/2606.00873v1",
  "title": "Prompts for Public-Sector LLMs Should Be Governed as Commons",
  "summary": "This paper argues that prompts used to deploy large language models (LLMs) in public-sector settings should be treated as governed artefacts rather than private, transient inputs. Prompts encode role instructions, decision framings, and value claims; prompt choice can materially shift outputs even when model weights and input records are held fixed. Existing governance tools, including model and dataset documentation, organisation-level policies, and post-training alignment, rarely make the loca",
  "authors": "Rashid Mushkani",
  "category": "research",
  "topics": "regulation,safety-alignment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-05-30T20:01:53.000Z",
  "fetched_at": "2026-07-14T16:30:14.367Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/3374",
  "original_url": "https://arxiv.org/abs/2606.00873v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}