{
  "id": 4267,
  "url": "https://arxiv.org/abs/2606.12432v1",
  "title": "AI Debris: Residual Risk and the Afterlife of Failed AI Systems",
  "summary": "AI governance frameworks primarily focus on risks during the development and deployment phases, implicitly treating system withdrawal as a technical shutdown. This paper argues that decommissioned AI systems generate residual risk, termed AI debris, that persists after model removal and continues to shape institutional behaviour, accountability, and trust. AI debris is defined as the post-withdrawal socio-technical residue of AI systems, including workflow dependency, data contamination, capabil",
  "authors": "Victor Frimpong",
  "category": "research",
  "topics": "regulation,transparency",
  "orgs": null,
  "regions": null,
  "published_at": "2026-05-15T14:59:15.000Z",
  "fetched_at": "2026-07-14T16:30:54.918Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/4267",
  "original_url": "https://arxiv.org/abs/2606.12432v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}