Consensus Statement on Red Lines in Artificial Intelligence

• Authority: Other multinational
• Jurisdiction: Multinational
• Collections: Multinational
• Most recent activity: Enacted
• Most recent activity date: 2024-03-11

Risk subdomain coverage

Good coverage — Comprehensive governance measures or mitigations with clear procedures relating to the risk subdomain are explicitly described.

• AI system security vulnerabilities
• Cyberattacks, weapon development or use
• Competitive dynamics
• Governance failure
• AI pursuing its own goals
• AI possessing dangerous capabilities

Minimal coverage — Brief mention but no specific mitigations, recommendations or governance measures relating to the risk subdomain are described.

• Disinformation, surveillance, and influence at scale
• Fraud, scams, and targeted manipulation
• Loss of human agency and autonomy
• Power centralization and unfair distribution
• Lack of capability or robustness
• Lack of transparency or interpretability

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 malicious actors (4.1, 4.2), AI system security (2.2), competitive dynamics (6.4), governance failure (6.5), and AI safety failures (7.1, 7.2, 7.3). Coverage is concentrated in security, misuse prevention, and AI safety domains.

Sector coverage

Good coverage — Comprehensive governance measures or mitigations with clear procedures relating to the sector are explicitly described.

• Scientific Research & Development Services
• Public Administration (excl. National Security)

Minimal coverage — Brief mention but no specific mitigations, recommendations or governance measures relating to the sector are described.

• Information
• National Security

All other sectors had no coverage in this document.

Sectors Summary

This is a cross-sectoral governance framework that applies broadly to AI development and deployment across all sectors. The document does not target specific industries but rather establishes universal red lines for AI systems regardless of application domain. The governance mechanisms (registration, evaluation, international coordination) would apply to AI developers and deployers across all economic sectors.

Legislative Status

Soft Law

Legislative Status Summary

This is a consensus statement proposing voluntary red lines and recommendations for AI governance. It uses predominantly voluntary language ('should', 'ought to', 'encourage') and lacks binding enforcement mechanisms or legal penalties.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Summary: The document is presented as a consensus statement from participants in International Dialogues, representing international scientific and governmental coordination on AI safety.

Target

• Entity Types: AI_Developer, AI_Deployer, AI_Governance_Actor
• Summary: The document targets AI developers who must demonstrate compliance with red lines, domestic regulators who should adopt aligned requirements, and governments that should implement registration and funding requirements.

Enforcer

• Entity Types: AI_Governance_Actor
• Summary: The document proposes that domestic regulators enforce red lines through registration and requirements, with international audits determining compliance with global standards, and future multilateral institutions providing enforcement mechanisms.

Monitor

• Entity Types: AI_Governance_Actor, AI_Developer
• Summary: The document proposes monitoring through domestic registration systems that provide government visibility, red teaming and automated model evaluation, and international scientific collaboration to track AI development.

AI Lifecycle Stages

Lifecycle stages covered by the documents, as defined in the OECD Framework for the Classification of AI Systems

• Plan and Design
• Build and Use Model
• Verify and Validate
• Deploy
• Operate and Monitor

AI Lifecycle Summary

The document addresses multiple lifecycle stages with primary focus on Build and Use Model, Verify and Validate, Deploy, and Operate and Monitor stages. It emphasizes evaluation, testing, and ongoing monitoring of AI systems to ensure red lines are not crossed.

Technical Scope

Terms relating to technical scope that are mentioned or implicitly referenced in the document

• AI Models
• Frontier AI
• AI Systems
• Compute Threshold
• General Purpose AI

Technical Scope Summary

The document explicitly mentions AI systems and models, with focus on advanced AI and AGI. It references compute thresholds for registration but does not specify exact FLOP values. No explicit mention of foundation models, generative AI, or open-weight models.