Policy Enforcement
The automated or manual mechanisms that ensure AI operations adhere to organizational policies, regulatory rules, and ethical guidelines.
Definition
The set of technical controls (e.g., policy-as-code gates, admission controllers, automated audits) and human-review processes that validate compliance at runtime and deployment. Policy enforcement tools intercept model builds, deployments, and API calls—checking against policy definitions (data usage rules, model-risk thresholds) and blocking or flagging any deviations for review.
Real-World Example
A financial-services firm codifies its data-retention policy in a policy engine: any storage operation older than the TTL defined for PII fields is automatically purged. If a model-training job attempts to load wiped data, the engine rejects the job and notifies the data-governance team.
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