Table of contents

Article 6: Classification Rules for High-Risk AI Systems

Article 7: Amendments to Annex III

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

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

Article 17: Quality Management System

Article 18: Documentation Keeping

Article 19: deleted

Article 20: Automatically Generated Logs

Article 21: Corrective Actions and Duty of Information

Article 22: deleted

Article 23: Cooperation with Competent Authorities

Article 25: Authorised Representatives

Article 26: Obligations of Importers

Article 27: Obligations of Distributors

Article 28: Responsibilities Along the AI Value Chain

Article 29: Obligations of Deployers of High-Risk AI Systems

Article 29a: Fundamental Rights Impact Assessment for High-Risk AI Systems

Article 30: Notifying Authorities

Article 31: Application of a Conformity Assessment Body for Notification

Article 32: Notification Procedure

Article 33: Requirements Relating to Notified Bodies

Article 33a: Presumption of Conformity with Requirements Relating to Notified Bodies

Article 34: Subsidiaries of and Subcontracting by Notified Bodies

Article 34a: 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

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 46: Information Obligations of Notified Bodies

Article 47: Derogation from Conformity Assessment Procedure

Article 48: EU Declaration of Conformity

Article 49: CE Marking of Conformity

Article 50: Moved to Article 18

Article 51: Registration

Article 61: Post-Market Monitoring by Providers and Post-Market Monitoring Plan for High-Risk AI Systems

Article 62: Reporting of Serious Incidents

Article 63: Market Surveillance and Control of AI Systems in the Union Market

Article 63a: Mutual Assistance, Market Surveillance and Control of General Purpose AI Systems

Article 63b: Supervision of Testing in Real World Conditions by Market Surveillance Authorities

Article 64: Powers of Authorities Protecting Fundamental Rights

Article 65: Procedure for Dealing with AI Systems Presenting a Risk at National Level

Article 65a: Procedure for Dealing with AI Systems Classified by the Provider as a Not High-Risk in Application of Annex III

Article 66: Union Safeguard Procedure

Article 67: Compliant AI Systems Which Present a Risk

Article 68: Formal Non-Compliance

Article 68a: EU AI Testing Support Structures in the Area of Artificial Intelligence

Article 68a(1): Right to Lodge a Complaint with a Market Surveillance Authority

Article 68c: A Right to Explanation of Individual Decision-Making

Article 68d: Amendment to Directive (EU) 2020/1828

Article 68e: Reporting of Breaches and Protection of Reporting Persons

Article 68f: Enforcement of Obligations on Providers of General Purpose AI Models

Article 68g : Monitoring Actions

Article 68h: Alerts of Systemic Risks by the Scientific Panel

Article 68i: Power to Request Documentation and Information

Article 68j: Power to Conduct Evaluations

Article 68k: Power to Request Measures

Article 68m: Procedural Rights of Economic Operators of the General Purpose AI Model

Recital 14a

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 High-Level Expert Group on AI (HLEG) appointed by the Commission. In those Guidelines the HLEG developed seven non-binding ethical principles for AI which should 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, these Guidelines contribute to the design of a coherent, trustworthy and human-centric Artificial Intelligence, in line with the Charter and with the values on which the Union is founded. According to the Guidelines of 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 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 compliance with existing 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 long-term impacts on the individual, society and democracy. The application of these 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.