GOVGOV-001 — Accountability Framework Gaps
Training Data Contamination Undermines AI Benchmark Reliability
3/5Sector: OtherGeography: GlobalStage: DevelopIngested: —
Executive Summary
AI models trained on raw benchmark data produce inflated performance scores that misrepresent true capability. Regulators and procurement bodies relying on contaminated benchmarks risk making flawed policy and safety decisions.
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/
Could this happen in your organisation?
A Velinor AI Audit maps your active AI portfolio against the 50+ blindspots and benchmarks against documented sector failures like this one. A board-ready foresight document in 5 weeks.