Urges governments to align AI practices with human rights laws, assess and monitor high-risk AI systems for impacts on equity, fairness, and safety. Requires public disclosure for risks, remedies for harms, support for personnel training, and secure AI procurement processes.
Good coverage — Comprehensive governance measures or mitigations with clear procedures relating to the risk subdomain are explicitly described.
Minimal coverage — Brief mention but no specific mitigations, recommendations or governance measures relating to the risk subdomain are described.
All other risk subdomains had no coverage in this document.
Risk Coverage Summary
The document has good coverage of approximately 10-12 subdomains, with strong focus on discrimination and toxicity (1.1, 1.2, 1.3), privacy compromise (2.1), AI system security (2.2), misinformation (3.1), malicious actors (4.1, 4.3), human-computer interaction (5.1, 5.2), and system safety failures (7.3, 7.4). Coverage is concentrated in human rights impacts, fairness, and safety domains.
Good coverage — Comprehensive governance measures or mitigations with clear procedures relating to the sector are explicitly described.
Minimal coverage — Brief mention but no specific mitigations, recommendations or governance measures relating to the sector are described.
All other sectors had no coverage in this document.
Sectors Summary
The document primarily governs AI use across all public sector activities and government services, with explicit mention of healthcare, law enforcement and justice, and public benefits provision as high-risk sectors. The governance applies broadly to government operations across multiple sectors rather than being sector-specific.
Soft Law
Legislative Status Summary
This is a non-binding joint statement by the Freedom Online Coalition member states that uses voluntary language ('call on governments to', 'pledge to') and lacks enforcement mechanisms or legal penalties. It represents voluntary commitments and recommendations rather than legally binding obligations.
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Enforcer
Monitor
Lifecycle stages covered by the documents, as defined in the OECD Framework for the Classification of AI Systems
AI Lifecycle Summary
The document comprehensively covers all AI lifecycle stages from planning through monitoring. It explicitly addresses design, data collection and processing, model building, verification and validation, deployment, and ongoing monitoring with detailed requirements for each stage.
Terms relating to technical scope that are mentioned or implicitly referenced in the document
Technical Scope Summary
The document uses the general term 'AI systems' throughout and does not explicitly define or distinguish between AI models, AI systems, frontier AI, general purpose AI, task-specific AI, foundation models, generative AI, predictive AI, open-weight models, or compute thresholds. The focus is on AI systems broadly defined by their impact on human rights and safety rather than technical characteristics.
Document data from AGORA, CSET Emerging Technology Observatory.