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 6

The notion of AI system in this Regulation should be clearly defined and closely aligned with the work of international organisations working on artificial intelligence to ensure legal certainty, facilitate international convergence and wide acceptance, while providing the flexibility to accommodate the rapid technological developments in this field. Moreover, it should be based on key characteristics of artificial intelligence systems, that distinguish it from simpler traditional software systems or programming approaches and should not cover systems that are based on the rules defined solely by natural persons to automatically execute operations. A key characteristic of AI systems is their capability to infer. This inference refers to the process of obtaining the outputs, such as predictions, content, recommendations, or decisions, which can influence physical and virtual environments and to a capability of AI systems to derive models and/or algorithms from inputs/data. The techniques that enable inference while building an AI system include machine learning approaches that learn from data how to achieve certain objectives; and logic- and knowledge-based approaches that infer from encoded knowledge or symbolic representation of the task to be solved. The capacity of an AI system to infer goes beyond basic data processing, enable learning, reasoning or modelling. The term “machine-based” refers to the fact that AI systems run on machines. The reference to explicit or implicit objectives underscores that AI systems can operate according to explicit defined objectives or to implicit objectives. The objectives of the AI system may be different from the intended purpose of the AI system in a specific context. For the purposes of this Regulation, environments should be understood as the contexts in which the AI systems operate, whereas outputs generated by the AI system, reflect different functions performed by AI systems and include predictions, content, recommendations or decisions. AI systems are designed to operate with varying levels of autonomy, meaning that they have some degree of independence of actions from human involvement and of capabilities to operate without human intervention. The adaptiveness that an AI system could exhibit after deployment, refers to self-learning capabilities, allowing the system to change while in use. AI systems can be used on a stand-alone basis or as a component of a product, irrespective of whether the system is physically integrated into the product (embedded) or serve the functionality of the product without being integrated therein (non-embedded).