Guardrails
Establishing practical boundaries, safeguards and operational controls for AI systems.
Safety by design
AI safety requires more than policies. It requires enforceable technical and procedural controls throughout the system lifecycle.
Input Controls
Protect systems from malicious input, injection attacks and unauthorised data exposure.
Output Controls
Validate AI outputs before they reach users, business processes or external systems.
Human Intervention
Provide escalation, supervision and override mechanisms for higher-risk operations.
Continuous Monitoring
Capture meaningful operational evidence, failures and deviations.
Proposed assurance controls
- Documented risk and threat assessments.
- Identity, authentication and authorisation.
- Data minimisation and privacy safeguards.
- Logging, monitoring and incident reporting.
- Testing against misuse and adversarial behaviour.
- Human approval for consequential actions.
- Model change control and rollback procedures.
Transparency of safeguards
AI providers should disclose appropriate information about the safeguards implemented, their limitations and the means of reporting failures, without exposing exploitable security details.