What is Covered Automated Decision-Making System Governance?
This refers to the policies, controls, and oversight processes used to manage an automated decision-making system that falls within a regulated or otherwise covered category. It matters because covered systems typically require stronger governance, testing, documentation, and accountability than general-purpose AI tools.
In Depth
In practice, governance covers inventorying the system, defining decision scope, assigning owners, documenting model purpose and limitations, testing for bias and performance, and tracking changes over time. It also includes escalation paths, audit evidence, record retention, and approval gates for deployment, retraining, or material modification.
For compliance teams, this creates a structured way to prove the system is being operated within legal and policy boundaries. The concept aligns with high-risk AI governance under the EU AI Act, broader AI management system expectations in ISO/IEC 42001, and risk-management controls in NIST AI RMF and sector-specific automated decision rules.
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