EU AI Act Art. 11: technical documentation (Annex IV)

Documentation and transparency

• EU AI Act Art. 13 Transparency and provision of information to deployers (core)
• EU AI Act Art. 53 Obligations for providers of general-purpose AI models (core)
• ISO 42001 7.5 Documented information (core)
• ISO 42001 A.6 AI system life cycle (core)
• ISO 42001 A.8 Information for interested parties (core)
• China AI Labelling Label Art. 4 Explicit labels for generated content (core)
• China AI Labelling Label Art. 5 Implicit (metadata) labels (core)
• China GenAI Measures GenAI Art. 12 Labelling of generated content (core)
• China Deep Synthesis DeepSyn Art. 16 Implicit technical labels (core)
• China Deep Synthesis DeepSyn Art. 17 Conspicuous labels for confusable content (core)
• GPAI Code Transparency 1.1 Drawing up and keeping up-to-date model documentation (core)
• GDPR Arts. 13–14 Information to be provided to the data subject (core)
• CSA AICM MDS-03 Model Documentation (core)
• Korea AI Act Art. 31 Transparency: prior notice, output labelling, realistic synthetic content (core)
• UK ATRS ATRS Tier 1 Summary information (core)
• Singapore GenAI GenAI 3 Trusted Development and Deployment (core)
• CoE Convention CoE Art. 14(2) Documentation sufficient to contest decisions; complaint to authorities (core)
• OECD AI Principles OECD 1.3 Transparency and explainability (core)
• G7 Code G7 Action 3 Publicly report capabilities, limitations and domains of use (core)
• GAO AI Accountability 1.9 Transparency: enable external stakeholders to access information on the design, operation, and limitations of the AI system (core)
• GAO AI Accountability 3.5 Documentation: document the methods for assessment, performance metrics, and outcomes of the AI system (core)
• EU AI Act Art. 50 Transparency obligations for providers and deployers of certain AI systems
• NIST AI RMF MAP 1 MAP 1: Context is established and understood
• NIST AI RMF MEASURE 2.8 MEASURE 2.8: Risks associated with transparency and accountability are examined and documented
• China GenAI Measures GenAI Art. 19 Disclosure to regulators
• China Algo. Rec. AlgoRec Art. 16 Notice that recommendation is used
• GB/T 45654 GB/T 45654 Content labelling Generated-content labelling requirements (clause not verified)
• EU AI Act Art. 86 Right to explanation of individual decision-making
• EU AI Act Art. 18 Documentation keeping
• EU AI Act Art. 43 Conformity assessment
• EU AI Act Art. 53(1)(d) Public summary of the content used for training
• EU AI Act Art. 50(2), 50(4) Machine-readable marking of synthetic content; disclosure of deep fakes
• GPAI Code Transparency 1.2 Providing relevant information
• GDPR Art. 30 Records of processing activities
• NIST AI RMF MAP 1.6 MAP 1.6: System requirements are elicited from and understood by relevant AI actors. Design decisions take socio-technical implications into account to address AI risks
• NIST AI RMF MEASURE 2.9 MEASURE 2.9: The AI model is explained, validated, and documented, and AI system output is interpreted within its context as identified in the MAP function to inform responsible use and governance
• CSA AICM MDS-04 Model Documentation Requirements
• Korea AI Act Art. 34(1)(2) Explanation plan: result, main criteria, training-data overview
• UK ATRS ATRS 2.2 Description and rationale
• CoE Convention CoE Art. 15(2) Notification of interaction with an AI system
• GAO AI Accountability 1.7 Specifications: establish and document technical specifications