GOVGOV-006 — Audit and Assurance Gaps
Unexplained In-Context Learning Creates Safety Guarantees Gap in General-Purpose AI
3/5Sector: TechnologyGeography: GlobalStage: OperateIngested: —
Executive Summary
Large language models adapt behaviour through prompt-based examples via a mechanism that researchers cannot yet fully explain, undermining safety assurances. Regulators and deployers cannot credibly certify compliance or bound misuse risk without a verified theoretical account of this capability.
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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