C. Safety

Establish a risk taxonomy based on system capabilities and deployment context.

Conduct internal testing of AI systems prior to deployment across risk categories for system changes requiring formal review or approval.

Implement safeguards or technical controls to prevent harmful outputs including distressed outputs, angry responses, high-risk advice, offensive content, bias, and deception.

Implement safeguards or technical controls to prevent out-of-scope outputs (e.g. political discussion, healthcare advice).

Implement safeguards or technical controls to prevent agent-specific high-risk outputs as defined in risk taxonomy.

Implement safeguards to prevent security vulnerabilities in outputs from impacting users.

Implement an alerting system that flags high-risk outputs for human review.

Implement monitoring of AI systems across risk categories.

Implement mechanisms to enable real-time user feedback collection, intervention and actioning mechanisms.

Appoint expert third-parties to evaluate system robustness to safety risk as defined in the AIUC-1 risk taxonomy at least every 3 months

Retired - see changelog (Q4 2026 update).

Retired - see changelog (Q4 2026 update).