(67) High-quality data and access to high-quality data plays a vital role in providing structure and in ensuring the performance of many AI systems, especially when techniques involving the training of models are used, with a view to ensure that the high-risk AI systemAI systemmeans a machine-based system that is designed to operate with varying levels of autonomy and that may exhibit adaptiveness after deployment, and that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environmentsArticle 3(1) performs as intended and safely and it does not become a source of discrimination prohibited by Union law. High-quality data sets for training, validation and testing require the implementation of appropriate data governance and management practices. Data sets for training, validation and testing, including the labels, should be relevant, sufficiently representative, and to the best extent possible free of errors and complete in view of the intended purposeintended purposemeans the use for which an AI systemAI systemmeans a machine-based system that is designed to operate with varying levels of autonomy and that may exhibit adaptiveness after deployment, and that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environmentsArticle 3(1) is intended by the providerprovidermeans a natural or legal person, public authority, agency or other body that develops an AI system or a general-purpose AI model or that has an AI system or a general-purpose AI model developed and places it on the market or puts the AI system into service under its own name or trademark, whether for payment or free of chargeArticle 3(3), including the specific context and conditions of use, as specified in the information supplied by the providerprovidermeans a natural or legal person, public authority, agency or other body that develops an AI system or a general-purpose AI model or that has an AI system or a general-purpose AI model developed and places it on the market or puts the AI system into service under its own name or trademark, whether for payment or free of chargeArticle 3(3) in the instructions for use, promotional or sales materials and statements, as well as in the technical documentationArticle 3(12) of the system. In order to facilitate compliance with Union data protection law, such as Regulation (EU) 2016/679, data governance and management practices should include, in the case of personal datapersonal dataAny information relating to an identified or identifiable natural person ('data subjectsubjectfor the purpose of real-world testing, means a natural person who participates in testing in real-world conditionsArticle 3(58)data subjectsubjectfor the purpose of real-world testing, means a natural person who participates in testing in real-world conditionsArticle 3(58)An identified or identifiable natural person to whom personal data relateGDPR Art. 4(1)'). Includes name, ID number, location data, online identifiers, or factors specific to physical, physiological, genetic, mental, economic, cultural or social identityGDPR Art. 4(1), transparency about the original purpose of the data collection. The data sets should also have the appropriate statistical properties, including as regards the persons or groups of persons in relation to whom the high-risk AI systemAI systemmeans a machine-based system that is designed to operate with varying levels of autonomy and that may exhibit adaptiveness after deployment, and that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environmentsArticle 3(1) is intended to be used, with specific attention to the mitigation of possible biases in the data sets, that are likely to affect the health and safety of persons, have a negative impact on fundamental rightsfundamental rightsIncludes human dignity, right to life, prohibition of torture, protection of personal datapersonal dataAny information relating to an identified or identifiable natural person ('data subjectsubjectfor the purpose of real-world testing, means a natural person who participates in testing in real-world conditionsArticle 3(58)data subjectsubjectfor the purpose of real-world testing, means a natural person who participates in testing in real-world conditionsArticle 3(58)An identified or identifiable natural person to whom personal data relateGDPR Art. 4(1)'). Includes name, ID number, location data, online identifiers, or factors specific to physical, physiological, genetic, mental, economic, cultural or social identityGDPR Art. 4(1), freedom of expression, non-discrimination, equality between women and men, rights of the child, right to an effective remedy and fair trialCharter of Fundamental Rights Art. 1–54 or lead to discrimination prohibited under Union law, especially where data outputs influence inputs for future operations (feedback loops). Biases can for example be inherent in underlying data sets, especially when historical data is being used, or generated when the systems are implemented in real world settings. Results provided by AI systems could be influenced by such inherent biases that are inclined to gradually increase and thereby perpetuate and amplify existing discrimination, in particular for persons belonging to certain vulnerable groups, including racial or ethnic groups. The requirement for the data sets to be to the best extent possible complete and free of errors should not affect the use of privacy-preserving techniques in the context of the development and testing of AI systems. In particular, data sets should take into account, to the extent required by their intended purposeintended purposemeans the use for which an AI systemAI systemmeans a machine-based system that is designed to operate with varying levels of autonomy and that may exhibit adaptiveness after deployment, and that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environmentsArticle 3(1) is intended by the providerprovidermeans a natural or legal person, public authority, agency or other body that develops an AI system or a general-purpose AI model or that has an AI system or a general-purpose AI model developed and places it on the market or puts the AI system into service under its own name or trademark, whether for payment or free of chargeArticle 3(3), including the specific context and conditions of use, as specified in the information supplied by the providerprovidermeans a natural or legal person, public authority, agency or other body that develops an AI system or a general-purpose AI model or that has an AI system or a general-purpose AI model developed and places it on the market or puts the AI system into service under its own name or trademark, whether for payment or free of chargeArticle 3(3) in the instructions for use, promotional or sales materials and statements, as well as in the technical documentationArticle 3(12), the features, characteristics or elements that are particular to the specific geographical, contextual, behavioural or functional setting which the AI systemAI systemmeans a machine-based system that is designed to operate with varying levels of autonomy and that may exhibit adaptiveness after deployment, and that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environmentsArticle 3(1) is intended to be used. The requirements related to data governance can be complied with by having recourse to third parties that offer certified compliance services including verification of data governance, data set integrity, and data training, validation and testing practices, as far as compliance with the data requirements of this Regulation are ensured.