TD-006HighProviderPreventive
Accuracy Metrics and Performance Documentation
Providers 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.
Articles:Article 11(1)Article 15Annex IV §3
Evidence Examples
- Accuracy benchmarking report
- Performance metrics definition
- Contextualised test results
Standards
ISO 42001:2023 §8.4ISO/IEC 24029-1
Related controls
- TD-001AI System Description and General InformationArticle 11 and Annex IV require that technical documentation includes a general description of the AI system covering its intended purpose, the persons…
- TD-002Design Specifications and ArchitectureProviders must document the overall design logic of the AI system, including the algorithms and associated design choices, the key design parameters, and…
- TD-003Development Process DocumentationTechnical documentation must describe the methods and steps performed for the development of the AI system, including data collection, labelling, model…
- TD-004Validation and Testing Approach DocumentationProviders must document the validation and testing procedures applied to the AI system prior to placing it on the market, including the metrics used, the…
- 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…
- TD-007Known Limitations DocumentationArticle 11 and Annex IV require explicit documentation of known or foreseeable limitations of the AI system, including performance degradation conditions,…
Related EU AI Act terms
- Technical DocumentationThe documentation that providers of high-risk AI systems must draw up before placing the system on the market, containing all necessary information to assess compliance with the Regulation, including a general description, design specifications, training data information, risk management records, and performance metrics. Content requirements are set out in Annex IV.
- AccuracyThe requirement that high-risk AI systems achieve an appropriate level of accuracy in relation to their intended purpose, as specified in the technical documentation. Providers must declare the level of accuracy in the instructions for use.
- RobustnessThe ability of a high-risk AI system to maintain its level of performance under adverse conditions — including technical limitations, adversarial inputs, errors, or unexpected situations — or within foreseeable operating conditions outside the intended purpose.
- 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 result in risks to health, safety, or fundamental rights, including protection against data poisoning, adversarial examples, and model evasion attacks.
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