EU AI Act - High-Risk Classification and Requirements
EU AI Act EUAI-Art.10: Data and data governance
High-risk AI systems that make use of techniques involving the training of AI models shall use training, validation and testing data that meet the quality criteria in Art.10(2)-(5): appropriate data governance, examination for possible biases, identification of data gaps/shortcomings, statistically relevant datasets to the intended purpose, and considerations specific to the geographical, contextual, behavioural or functional setting of intended use.
Maintained by Gerard Blokdyk·Verified against the published standard ·Control text last updated
What else in your programme already covers this
This control maps to 22 controls across 7 other frameworks. If you already hold one of them, the evidence you collected for it is the starting point here rather than new work.
AIRMF-MP-1.1 Intended purpose, potentially beneficial uses, context-specific laws, norms and expectations, and prospective settings in which the AI system will be deployed are understood and documented
AIRMF-MP-2.3 Scientific integrity and TEVV considerations are identified and documented, including those related to experimental design, data collection and selection, system trustworthiness, and construct validation
AIRMF-MS-2.11 Fairness and bias as identified in the MAP function is evaluated and results are documented
You are reading one control. How much of EU AI Act have you already done?
EU AI Act EUAI-Art.10 is one control. If you already hold one of the frameworks below, a reviewed crosswalk already says how much of EU AI Act your existing evidence covers. Hold ISO/IEC 42001:2023 and 17 of 43 EU AI Act controls already carry evidence.
Each report names every control your existing framework evidences, every one it does not, the reasoning behind each claim, and the claims that were argued against and rejected. 0 were rejected on the ISO/IEC 42001:2023 pair alone.