RequirementsArticle 15(3)
Robustesse
La capacité d’un système d’IA à haut risque à maintenir son niveau de performance dans des conditions défavorables — y compris limitations techniques, entrées contradictoires, erreurs ou situations inattendues — ou dans des conditions de fonctionnement prévisibles hors de la finalité prévue.
Termes associés
- Risk Management SystemA continuous iterative process that must be established, implemented, documented, and maintained by providers of high-risk AI systems throughout the…
- Data GovernancePractices and policies applicable to training, validation, and testing data sets used for high-risk AI systems, covering the design choices, data…
- Human OversightMeasures built into high-risk AI systems enabling natural persons to understand, monitor, and — where necessary — override or shut down the system. Must…
- AccuracyThe requirement that high-risk AI systems achieve an appropriate level of accuracy in relation to their intended purpose, as specified in the technical…
- CybersecurityThe requirement that high-risk AI systems are resilient against attempts by third parties to alter their use, behaviour, or performance in ways that could…
- Transparency RequirementsObligations under Article 13 requiring that high-risk AI systems are designed to ensure that their operation is sufficiently transparent to enable…
Contrôles de conformité associés
- DG-009Statistical Testing and ValidationProviders must apply appropriate statistical methods to validate that training data meets quality thresholds and that the resulting model generalises appropriately to the intended deployment distribution.
- TD-006Accuracy Metrics and Performance DocumentationProviders must document the accuracy, robustness, and cybersecurity metrics for which the high-risk AI system was designed and the relevant testing methodologies, including the context in which these metrics were measured.
- 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 technical documentation, including accuracy and response time indicators.
- TR-003Performance Metrics Disclosure to DeployersThe instructions for use must include the performance metrics for which the system has been designed and the level of accuracy that the provider committed to achieving, enabling deployers to assess whether the system meets their operational requirements.
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