GOVGOV-001 — Accountability Framework Gaps
Benchmark Annotation Contamination Invalidates AI Capability Evaluations
3/5Sector: OtherGeography: GlobalStage: DevelopIngested: —
Executive Summary
AI models exposed to benchmark labels during training learn correct outputs rather than genuine capability, rendering standard evaluations meaningless. Regulators and procurers relying on contaminated benchmarks cannot accurately assess model safety or fitness for deployment.
Domain
Governance & Compliance
Blindspots in accountability, regulatory compliance, ethics, risk management, data governance, and audit.
Source
MIT AI Risk Repository — Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems (Gipiškis2024) ↗https://airisk.mit.edu/
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