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 Notified Bodies and Subcontracting

Article 34: Operational Obligations of Notified Bodies

Article 35: Identification Numbers and Lists of Notified Bodies

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 at National Level for Dealing with AI Systems Presenting a Risk

Article 80: Procedure for Dealing with AI Systems Classified by the Provider as Non-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: Right to Explanation of Individual Decision-Making

Article 87: Reporting of Infringements 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 the Obligations of 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

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Recital 27

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.

While the risk-based approach is the basis for a proportionate and effective set of binding rules, it is important to recall the 2019 Ethics guidelines for trustworthy AI developed by the independent AI HLEG appointed by the Commission. In those guidelines, the AI HLEG developed seven non-binding ethical principles for AI which are intended to help ensure that AI is trustworthy and ethically sound. The seven principles include human agency and oversight; technical robustness and safety; privacy and data governance; transparency; diversity, non-discrimination and fairness; societal and environmental well-being and accountability. Without prejudice to the legally binding requirements of this Regulation and any other applicable Union law, those guidelines contribute to the design of coherent, trustworthy and human-centric AI, in line with the Charter and with the values on which the Union is founded. According to the guidelines of the AI HLEG, human agency and oversight means that AI systems are developed and used as a tool that serves people, respects human dignity and personal autonomy, and that is functioning in a way that can be appropriately controlled and overseen by humans. Technical robustness and safety means that AI systems are developed and used in a way that allows robustness in the case of problems and resilience against attempts to alter the use or performance of the AI system so as to allow unlawful use by third parties, and minimise unintended harm. Privacy and data governance means that AI systems are developed and used in accordance with privacy and data protection rules, while processing data that meets high standards in terms of quality and integrity. Transparency means that AI systems are developed and used in a way that allows appropriate traceability and explainability, while making humans aware that they communicate or interact with an AI system, as well as duly informing deployers of the capabilities and limitations of that AI system and affected persons about their rights. Diversity, non-discrimination and fairness means that AI systems are developed and used in a way that includes diverse actors and promotes equal access, gender equality and cultural diversity, while avoiding discriminatory impacts and unfair biases that are prohibited by Union or national law. Social and environmental well-being means that AI systems are developed and used in a sustainable and environmentally friendly manner as well as in a way to benefit all human beings, while monitoring and assessing the longterm impacts on the individual, society and democracy. The application of those principles should be translated, when possible, in the design and use of AI models. They should in any case serve as a basis for the drafting of codes of conduct under this Regulation. All stakeholders, including industry, academia, civil society and standardisation organisations, are encouraged to take into account, as appropriate, the ethical principles for the development of voluntary best practices and standards.

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View the official text, or browse it online using our AI Act Explorer. The text used in this tool is the ‘Artificial Intelligence Act (Regulation (EU) 2024/1689), Official Journal version of 13 June 2024’. Interinstitutional File: 2021/0106(COD)