A governance principle aiming for no errors or policy violations in AI outputs, supported by rigorous testing, monitoring, and continuous improvement cycles.
A “no-tolerance” stance toward defects - accuracy lapses, bias incidents, security breaches - backed by multi-layered safeguards: exhaustive test suites, real-time monitoring with automated rollback, and root-cause analysis for even minor anomalies. Governance sets strict SLAs (e.g., 100% pass rate on critical QA tests), mandates immediate remediation of any defect, and fosters a culture of continuous improvement to uphold zero-defect standards.
A financial AI that authorizes trades must pass a 100% compliance-test pass rate before each trading session. Any test failure - no matter how minor - triggers an automatic halt and rollback to the last known good version, followed by an immediate incident review and correction before resuming operations.
