Article 10

Article 10 — Data and Data Governance

1. High-risk AI systems which make use of techniques involving the training of AI models with data shall be developed on the basis of training, validation and testing data sets that meet the quality criteria referred to in paragraphs 2 to 5.

2. Training, validation and testing data sets shall be subject to appropriate data governance and management practices. Those practices shall concern in particular: (a) the relevant design choices; (b) data collection processes and the origin of data; (c) relevant data preparation processing operations; (d) the formulation of relevant assumptions; (e) an assessment of the availability, quantity, and suitability of the data sets; (f) examination in view of possible biases that are likely to affect health and safety or lead to discrimination; (g) the identification of any possible data gaps or shortcomings.

3. Training, validation and testing data sets shall be relevant, sufficiently representative, and to the best extent possible, free of errors and complete in view of the intended purpose. They shall have the appropriate statistical properties, including as regards the persons or groups of persons on whom the high-risk AI system is intended to be used.

4. To the extent strictly necessary for the purposes of ensuring bias monitoring, detection and correction in relation to the high-risk AI systems, the providers may process special categories of personal data, subject to appropriate safeguards for the fundamental rights and freedoms of natural persons.