Governing Authorities

A state law governing developers and deployers of high-risk artificial intelligence systems used in consequential decisions.

An enterprise risk management framework integrating risk with strategy and organizational performance.

A risk-based legal framework governing the development, placement on the market, deployment, and use of artificial intelligence systems in the European Union.

European data-protection requirements governing personal data processing, profiling, transparency, and certain solely automated decisions.

A body of consumer-protection guidance and enforcement messaging addressing deceptive, unfair, discriminatory, and unsupported AI practices.

A standard process for identifying and addressing ethical values and concerns during system and software design.

General principles, framework, and process guidance for managing risk across organizations.

An international standard establishing concepts and terminology used across artificial intelligence systems and related standards.

A framework describing machine-learning-based AI systems and their components, functions, and relationships.

International guidance for organizations seeking to identify, assess, treat, monitor, and communicate risks related to artificial intelligence.

Guidance for governing bodies on the organizational implications of using artificial intelligence.

A knowledge base of adversary tactics and techniques targeting machine-learning and AI systems.

A companion profile to the NIST AI RMF addressing risks and actions specific to generative artificial intelligence.

A voluntary framework for managing risks associated with artificial intelligence across organizational and system lifecycles.

A local law regulating certain automated employment decision tools used in hiring and promotion decisions.

Federal agency guidance establishing governance, innovation, inventory, and risk-management expectations for agency use of artificial intelligence.

International principles promoting innovative and trustworthy artificial intelligence that respects human rights and democratic values.

A community-developed list of significant security risks affecting applications built with large language models.

A proposed Canadian legislative framework intended to regulate high-impact artificial intelligence systems.

Practices for identifying, triaging, containing, investigating, documenting, and resolving AI incidents.

Governance practices covering model approval, versioning, validation, monitoring, retirement, and accountability.

Governance applied while AI systems are executing rather than only before deployment.

An evidence-bound governance architecture that determines whether a proposed action is admissible before execution and preserves the resulting outcome evidence.

A governance chain expressed as Reality, Record, Continuity, Admissibility, Binding, Commit, Execution, and Outcome.

A global normative instrument addressing the ethical development and use of artificial intelligence.

A global framework defining state duties and corporate responsibilities regarding business-related human-rights impacts.

A nonbinding framework describing protections for people affected by automated systems.