Compliance & AssessmentArticle 3(25)Article 72
Surveillance après commercialisation
Collecte et examen proactifs de l’expérience acquise lors de l’utilisation de systèmes d’IA à haut risque, afin d’identifier tout besoin d’actions correctives ou préventives et d’assurer la conformité continue tout au long du cycle de vie du système.
Termes associés
- Conformity AssessmentThe process of verifying whether a high-risk AI system complies with the requirements set out in Chapter III Section 2 of the Regulation. Can be conducted…
- CE MarkingThe marking by which a provider indicates that a high-risk AI system is in conformity with the requirements set out in Chapter III Section 2 of the…
- EU Declaration of ConformityA statement made by the provider affirming that a high-risk AI system is in conformity with the provisions of the Regulation and all applicable Union…
- Fundamental Rights Impact AssessmentA structured assessment required under Article 27 for deployers of high-risk AI systems that are bodies governed by public law, or private operators…
- Quality Management SystemA documented system that providers of high-risk AI systems must establish, implement, document, and maintain covering: the regulatory compliance strategy,…
- AI Regulatory SandboxA controlled environment established by a competent authority that offers providers and prospective providers of AI systems the possibility to develop,…
Contrôles de conformité associés
- RM-008Continuous Risk MonitoringThe risk management system must continuously monitor the AI system in operation to identify new or evolving risks and trigger appropriate reassessment when substantial modifications occur or when post-market data indicates new hazards.
- TD-005System Monitoring Plan DocumentationTechnical documentation must include a plan describing the measures for monitoring the AI system in operation, the data to be collected, the performance thresholds, and the procedures for responding to performance deviations.
- 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 performance degradation and triggering corrective action procedures.
- HO-010Oversight Effectiveness ReviewProviders and deployers must periodically review the effectiveness of human oversight measures, including assessing whether the designated oversight persons are able to meaningfully intervene and whether oversight tools remain fit for purpose.
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