Article 10 › 2

Training, validation and testing data sets shall be subject to data governance and management practices appropriate for the intended purpose of the high-risk AI system. Those practices shall concern in particular: (a) the relevant design choices; (b) data collection processes and the origin of data, and in the case of personal data, the original purpose of the data collection; (c) relevant data-preparation processing operations, such as annotation, labelling, cleaning, updating, enrichment and aggregation; (d) the formulation of assumptions, in particular with respect to the information that the data are supposed to measure and represent; (e) an assessment of the availability, quantity and suitability of the data sets that are needed; (f) examination in view of possible biases that are likely to affect the health and safety of persons, have a negative impact on fundamental rights or lead to discrimination prohibited under Union law, especially where data outputs influence inputs for future operations; (g) appropriate measures to detect, prevent and mitigate possible biases identified according to point (f); (h) the identification of relevant data gaps or shortcomings that prevent compliance with this Regulation, and how those gaps and shortcomings can be addressed.

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Source: EUR-Lex CELLAR · retrieved 2026-08-26