Learn AI / Learning Paths /Understand AI governance
Understand AI governance
Who writes the rules, what kind of rules they are, and why "not binding" is not the same as "no effect".
AI governance
The rules, institutions and processes used to guide how AI is built, used and overseen so its benefits and risks are handled in the public interest.
Regulation
A regulation is a binding rule made by a competent authority under rule-making powers granted by law for those within its scope.
Normative instrument
A formally issued or adopted text that sets shared principles, expectations or guidance for behaviour, often without creating the same binding legal duties as a regulation or treaty.
International standard
A document approved through a recognised international standards process that sets common requirements, guidance or methods for repeated use.
Risk-based regulation
A way to set stricter rules for uses more likely to cause serious harm, while applying lighter duties to lower-risk uses.
Technology-neutral regulation
An approach to rule-making that sets obligations by function, outcome or risk, rather than by naming one specific technology.
Regulatory sandbox
A regulatory sandbox is a limited testing programme run by a public authority under defined conditions to learn, manage risks and shape future rules.
AI audit and assurance
A structured check of how an AI system is governed, tested and used, producing evidence-based confidence that stated requirements are met and risks are controlled.
Multi-stakeholder governance
A way of shaping rules or shared practices with several kinds of actors, such as governments, companies, experts, civil society and affected communities.