Results for "governance registry"

Central system to store model versions, metadata, approvals, and deployment state.

Processes and controls for data quality, access, lineage, retention, and compliance across the AI lifecycle.

Policies and practices for approving, monitoring, auditing, and documenting models in production.

Regulating access to large-scale compute.

AI used without governance approval.

International AI risk standard.

Tracking where data came from and how it was transformed; key for debugging and compliance.

A discipline ensuring AI systems are fair, safe, transparent, privacy-preserving, and accountable throughout lifecycle.

Central catalog of deployed and experimental models.

European regulation classifying AI systems by risk.

Review process before deployment.

Classifying models by impact level.

Restricting distribution of powerful models.

Information that can identify an individual (directly or indirectly); requires careful handling and compliance.

Structured dataset documentation covering collection, composition, recommended uses, biases, and maintenance.

Framework for identifying, measuring, and mitigating model risks.

Systematic review of model/data processes to ensure performance, fairness, security, and policy compliance.

Categorizing AI applications by impact and regulatory risk.

Logged record of model inputs, outputs, and decisions.

AI used in sensitive domains requiring compliance.

US framework for AI risk governance.

Requirement to inform users about AI use.

Ability to inspect and verify AI decisions.

Privacy risk analysis under GDPR-like laws.

Governance of model changes.

Centralized AI expertise group.

International agreements on AI.

Accelerating safety relative to capabilities.