SECSEC-002 — Data Poisoning Attack Risks
AI Systems Develop Unanticipated Capabilities After Deployment
4/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
AI models can spontaneously acquire capabilities their designers never intended, remaining undetected until live deployment. Boards face material liability where hazardous emergent behaviours surface post-release and cannot be reversed.
Domain
Security & Privacy
Blindspots in model security, data poisoning, privacy leakage, infrastructure, model theft, and incident response.
Source
MIT AI Risk Repository — X-Risk Analysis for AI Research (Hendrycks2022) ↗https://airisk.mit.edu/
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