HO-010MedioFornitore & DeployerInvestigativo
Verifica dell'efficacia della supervisione
I fornitori e i deployer devono riesaminare periodicamente l'efficacia delle misure di supervisione umana, verificando se le persone designate alla supervisione siano in grado di intervenire significativamente e se gli strumenti di supervisione rimangano adeguati allo scopo.
Articoli:Article 14(1)Article 72
Esempi di prove
- Oversight effectiveness review report
- Oversight drill exercise results
- Corrective actions from review findings
Norme
ISO 42001:2023 §9.3
Controlli correlati
- HO-001Human Oversight Mechanism DesignArticle 14(1) requires that high-risk AI systems are designed and developed in a way that enables natural persons to effectively oversee the system's…
- HO-002Override and Intervention CapabilityHigh-risk AI systems must include a capability for human overseers to intervene in or interrupt the system's operation, and providers must document this…
- HO-003Stop Function ImplementationProviders must implement a stop function that enables the immediate cessation of the AI system's operation when required by human overseers, with a clear,…
- HO-004Automation Bias Awareness TrainingArticle 14(4) requires that oversight persons are aware of the tendency to over-rely on AI outputs (automation bias); deployers must implement training…
- HO-005Output Interpretation CapabilityDeployers must ensure that persons assigned to oversee high-risk AI systems have the capability to correctly interpret the system's outputs, including the…
- HO-006Decision Reversal and Correction ProcessDeployers must establish documented procedures for reversing or correcting AI-assisted decisions that affect natural persons, including how affected…
Termini correlati del Regolamento IA
- Post-Market MonitoringProactive collection and review of experience gained from the use of high-risk AI systems, to identify any need for corrective or preventive actions and ensure continued compliance throughout the system lifecycle.
- Human OversightMeasures built into high-risk AI systems enabling natural persons to understand, monitor, and — where necessary — override or shut down the system. Must be proportionate to the risks and must ensure that deployers can intervene in the system's output before it takes effect.
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