GOVGOV-001 — Accountability Framework Gaps
Opaque Training Data Provenance Undermines Model Explainability
3/5Sector: OtherGeography: GlobalStage: DevelopIngested: —
Executive Summary
AI models trained without documented data collection and curation processes cannot be reliably explained or audited. Regulators and boards lose the assurance needed to approve deployment or defend decisions under scrutiny.
Domain
Governance & Compliance
Blindspots in accountability, regulatory compliance, ethics, risk management, data governance, and audit.
Source
MIT AI Risk Repository — AI Risk Atlas (IBM2025) ↗https://airisk.mit.edu/
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