AIORG-W024 Standards & frameworks

OECD AI Principles

OECD Recommendation of the Council on Artificial Intelligence · updated OECD AI Principles 2024

official intergovernmental principles

Recorded claims
2
coded from the inspected source
Evidence classes
1
normative-authority
Recorded limitations
3
stated, never hidden

From the wave-0 evidence ledger

Recorded claims

Each claim states what the inspected source says, at the recorded location—bounded by its scope and graded by its confidence. Nothing here is a synthesis across works.

The updated principles call for human agency and oversight, transparency and meaningful information, and the ability for affected people to understand and challenge AI-related outcomes where appropriate.

confidence: high for stated principles normative-authority

Scope: High-level policy principles across AI systems and actors.

The principles also call for robustness, security and safety, traceability, systematic risk management, and mechanisms to override, repair, or safely decommission systems that risk undue harm or undesired behavior.

confidence: high for stated principles normative-authority

Scope: Principle-level organizational obligations to operationalize by context.

Boundaries

Limitations & independence

Recorded at coding time, carried with the work forever. A claim without its limits is not evidence.

Recorded limitations

  • High-level principles require local operationalization
  • No adoption or effectiveness inference
  • National legal duties differ and were out of scope

Source independence

Intergovernmental normative instrument; not an empirical compliance study.