Safety & Reliability
Operational controls for safety & reliability, with maturity levels, evidence requirements, and implementation guidance.
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6 controls
Hallucination Detection and Mitigation
Implement controls to detect, reduce, and manage AI-generated factual errors and fabrications before they reach end users or inform decisions.
AI Output Validation
Check AI outputs against quality, safety, and format criteria before users or other systems receive them.
AI Graceful Degradation
Define and implement fallback behavior for AI systems when they are unavailable, underperforming, or producing outputs below acceptable quality thresholds.
AI Reliability Testing
Systematically test AI systems for consistency, repeatability, handling of unusual inputs, and behavior under heavy use before deployment and on a recurring basis.
Harmful Content Filtering
Apply input and output filtering to prevent AI systems from generating or acting on harmful, toxic, illegal, or policy-violating content.
Post-Deployment Adversarial Testing Cadence
Schedule recurring red-teaming (simulated attacks) of live systems by risk tier. Continue this testing after pre-deployment assessments.