RK-005HighProviderDetective
Event Traceability and Reconstruction
Logs must enable the tracing and reconstruction of decision events to understand the inputs processed, the outputs generated, and the conditions under which the AI system operated at any given point in time.
Articles:Article 12(1)Article 12(2)(a)
Evidence Examples
- Event reconstruction test procedure
- Trace log sample for decision events
- Input-output correlation capability
Standards
ISO 42001:2023 §9.1ISO/IEC 27001:2022 A.8.15
Related controls
- RK-001Automatic Event Logging CapabilityArticle 12(1) requires that high-risk AI systems are designed and developed with automatic logging capabilities, enabling the reconstruction of events…
- RK-002Log Integrity and Tamper ProtectionProviders must ensure that logs are protected against tampering, unauthorised deletion, or modification, using cryptographic integrity controls,…
- RK-003Log Retention for Minimum 10 YearsArticle 18(1) requires that providers retain technical documentation and logs for at least 10 years after the high-risk AI system is placed on the market…
- RK-004Log Accessibility for Competent AuthoritiesProviders must ensure that event logs are accessible to competent national authorities and market surveillance authorities upon request, with procedures…
- RK-006Performance and Operational Metrics LoggingProviders must log performance and operational metrics relevant to verifying that the AI system operates within the parameters established in the…
- RK-007Anomaly and Error Detection LoggingThe logging system must capture anomalous behaviour, errors, and unexpected outputs from the AI system in operation, enabling timely detection of…
Related EU AI Act terms
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