Table of contents

Section 1: Classification of AI Systems as High-Risk

Article 6: Classification Rules for High-Risk AI Systems

Article 7: Amendments to Annex III

Section 2: Requirements for High-Risk AI Systems

Article 8: Compliance with the Requirements

Article 9: Risk Management System

Article 10: Data and Data Governance

Article 11: Technical Documentation

Article 12: Record-Keeping

Article 13: Transparency and Provision of Information to Deployers

Article 14: Human Oversight

Article 15: Accuracy, Robustness and Cybersecurity

Section 3: Obligations of Providers and Deployers of High-Risk AI Systems and Other Parties

Article 16: Obligations of Providers of High-Risk AI Systems

Article 17: Quality Management System

Article 18: Documentation Keeping

Article 19: Automatically Generated Logs

Article 20: Corrective Actions and Duty of Information

Article 21: Cooperation with Competent Authorities

Article 22: Authorised Representatives of providers of high-risk AI systems

Article 23: Obligations of Importers

Article 24: Obligations of Distributors

Article 25: Responsibilities Along the AI Value Chain

Article 26: Obligations of Deployers of High-Risk AI Systems

Article 27: Fundamental Rights Impact Assessment for High-Risk AI Systems

Section 4: Notifying Authorities and Notified Bodies

Article 28: Notifying Authorities

Article 29: Application of a Conformity Assessment Body for Notification

Article 30: Notification Procedure

Article 31: Requirements Relating to Notified Bodies

Article 32: Presumption of Conformity with Requirements Relating to Notified Bodies

Article 33: Subsidiaries of and Subcontracting by Notified Bodies

Article 34: Operational Obligations of Notified Bodies

Article 35: Identification Numbers and Lists of Notified Bodies Designated Under this Regulation

Article 36: Changes to Notifications

Article 37: Challenge to the Competence of Notified Bodies

Article 38: Coordination of Notified Bodies

Article 39: Conformity Assessment Bodies of Third Countries

Section 5: Standards, Conformity Assessment, Certificates, Registration

Article 40: Harmonised Standards and Standardisation Deliverables

Article 41: Common Specifications

Article 42: Presumption of Conformity with Certain Requirements

Article 43: Conformity Assessment

Article 44: Certificates

Article 45: Information Obligations of Notified Bodies

Article 46: Derogation from Conformity Assessment Procedure

Article 47: EU Declaration of Conformity

Article 48: CE Marking

Article 49: Registration

Section 1: Post-Market Monitoring

Article 72: Post-Market Monitoring by Providers and Post-Market Monitoring Plan for High-Risk AI Systems

Section 2: Sharing of Information on Serious Incidents

Article 73: Reporting of Serious Incidents

Section 3: Enforcement

Article 74: Market Surveillance and Control of AI Systems in the Union Market

Article 75: Mutual Assistance, Market Surveillance and Control of General Purpose AI Systems

Article 76: Supervision of Testing in Real World Conditions by Market Surveillance Authorities

Article 77: Powers of Authorities Protecting Fundamental Rights

Article 78: Confidentiality

Article 79: Procedure for Dealing with AI Systems Presenting a Risk at National Level

Article 80: Procedure for Dealing with AI Systems Classified by the Provider as a Not High-Risk in Application of Annex III

Article 81: Union Safeguard Procedure

Article 82: Compliant AI Systems Which Present a Risk

Article 83: Formal Non-Compliance

Article 84: Union AI Testing Support Structures

Section 4: Remedies

Article 85: Right to Lodge a Complaint with a Market Surveillance Authority

Article 86: A Right to Explanation of Individual Decision-Making

Article 87: Reporting of Breaches and Protection of Reporting Persons

Section 5: Supervision, Investigation, Enforcement and Monitoring in Respect of Providers of General Purpose AI Models

Article 88: Enforcement of Obligations on Providers of General Purpose AI Models

Article 89 : Monitoring Actions

Article 90: Alerts of Systemic Risks by the Scientific Panel

Article 91: Power to Request Documentation and Information

Article 92: Power to Conduct Evaluations

Article 93: Power to Request Measures

Article 94: Procedural Rights of Economic Operators of the General Purpose AI Model

Recitals

Annexes

Search within the Act

Article 10: Data and Data Governance

Date of entry into force:

July 2026

According to:

Article 113

Note: This date is an estimate based on the expected date of entry into force. See here for a full implementation timeline.

Summary

This article states that high-risk AI systems must be developed using high-quality data sets for training, validation, and testing. These data sets should be managed properly, considering factors like data collection processes, data preparation, potential biases, and data gaps. The data sets should be relevant, representative, error-free, and complete as much as possible. They should also consider the specific context in which the AI system will be used. In some cases, providers may process special categories of personal data to detect and correct biases, but they must follow strict conditions to protect individuals' rights and freedoms.

Generated by CLaiRK, edited by us.

NOTE: This translation is a machine-generated translation. It is not the official translation provided by the European Parliament. When the AI Act is published in the official journal, the machine-generated translations will be replaced by the official translations.

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 whenever such data sets are used.

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.

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, where applicable, as regards the persons or groups of persons in relation to whom the high-risk AI system is intended to be used. Those characteristics of the data sets may be met at the level of individual data sets or at the level of a combination thereof.

4. Data sets shall take into account, to the extent required by the intended purpose, the characteristics or elements that are particular to the specific geographical, contextual, behavioural or functional setting within which the high-risk AI system is intended to be used.

5. To the extent that it is strictly necessary for the purpose of ensuring bias detection and correction in relation to the high-risk AI systems in accordance with paragraph (2), points (f) and (g) of this Article, the providers of such systems may exceptionally process special categories of personal data, subject to appropriate safeguards for the fundamental rights and freedoms of natural persons. In addition to the provisions set out in Regulations (EU) 2016/679 and (EU) 2018/1725 and Directive (EU) 2016/680, all the following conditions must be met in order for such processing to occur:

(a) the bias detection and correction cannot be effectively fulfilled by processing other data, including synthetic or anonymised data;

(b) the special categories of personal data are subject to technical limitations on the re-use of the personal data, and state-of-the-art security and privacy-preserving measures, including pseudonymisation;

(c) the special categories of personal data are subject to measures to ensure that the personal data processed are secured, protected, subject to suitable safeguards, including strict controls and documentation of the access, to avoid misuse and ensure that only authorised persons have access to those personal data with appropriate confidentiality obligations;

(d) the special categories of personal data are not to be transmitted, transferred or otherwise accessed by other parties;

(e) the special categories of personal data are deleted once the bias has been corrected or the personal data has reached the end of its retention period, whichever comes first;

(f) the records of processing activities pursuant to Regulations (EU) 2016/679 and (EU) 2018/1725 and Directive (EU) 2016/680 include the reasons why the processing of special categories of personal data was strictly necessary to detect and correct biases, and why that objective could not be achieved by processing other data.

6. For the development of high-risk AI systems not using techniques involving the training of AI models, paragraphs 2 to 5 apply only to the testing data sets.

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The text used in this tool is the ‘Artificial Intelligence Act, Corrigendum, 19 April 2024’. Interinstitutional File: 2021/0106(COD)