AI Debris: Residual Risk and the Afterlife of Failed AI Systems
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
Record details
Published: 15 May 2026
Source: arXiv
Category: Research
Topics: Regulation · Transparency
Retrieved: 14 July 2026
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ethics.ai (15 May 2026), “AI Debris: Residual Risk and the Afterlife of Failed AI Systems,” evidence record 4267, https://ethics.ai/record/4267 (originally published by arXiv).
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