Which countries address AI bias and discrimination?

Rules on algorithmic discrimination, bias and fairness in AI systems and automated decisions.

13 of 109 reviewed jurisdictions address this in at least one tracked instrument. Updated 2026-10-04.

Each answer cites the instrument it rests on; open it for the provision and the full analysis. Whether a rule is binding law, a bill or guidance comes from the instrument's type and status, not from wording.

“Not found” means none of the instruments we track for that jurisdiction addresses the topic. It is not a finding that no such rule exists.

Yes — binding law in force (8)

Partly — regional, framework or general (non-AI) law (4)

Proposed (16)

Guidance or policy only (42)

Not found in the instruments we track (15)

  • Croatia

    Not found in the instruments we track

    As an EU member state, the EU AI Act also applies here.

  • Czech Republic

    Not found in the instruments we track

    As an EU member state, the EU AI Act also applies here.

  • Hungary

    Not found in the instruments we track

    As an EU member state, the EU AI Act also applies here.

  • Iran

    Not found in the instruments we track

  • Iraq

    Not found in the instruments we track

  • Norway

    Not found in the instruments we track

  • Pakistan

    Not found in the instruments we track

  • Panama

    Not found in the instruments we track

  • Poland

    Not found in the instruments we track

    As an EU member state, the EU AI Act also applies here.

  • Senegal

    Not found in the instruments we track

  • Slovenia

    Not found in the instruments we track

    As an EU member state, the EU AI Act also applies here.

  • South Africa

    Not found in the instruments we track

  • Tunisia

    Not found in the instruments we track

  • Uruguay

    Not found in the instruments we track

  • Uzbekistan

    Not found in the instruments we track

International organisations (24)

  • African Union

    Not found in the instruments we track

  • APEC

    Not found in the instruments we track

  • ASEAN

    Guidance or policy only

    Organizations are advised to align AI systems with principles including fairness and equity.

    Status verified 2026-09-07

  • BRICS

    Not found in the instruments we track

  • Council of Europe

    Not found in the instruments we track

  • European Union

    Yes — binding law in force

    It requires high-quality training datasets to reduce risks of discriminatory outcomes, especially for high-risk AI.

    A possible change to a cited instrument is not yet verified.

    Status verified 2026-09-11

  • G7

    Guidance or policy only

    It expects iterative red-teaming, which is described as identifying biases in AI models.

    Status verified 2026-09-09

  • GPAI

    Not found in the instruments we track

  • IAEA

    Guidance or policy only

    It recommends that human-centred AI avoid discrimination and maintain fairness and justice.

    Status verified 2026-09-09

  • ICAO

    Not found in the instruments we track

  • IEEE

    Guidance or policy only

    Organizations must document bias considerations throughout an AI system’s lifecycle.

    Status verified 2026-09-09

  • ILO

    Guidance or policy only

    It prohibits using workplace AI systems for discriminatory practices.

    Status verified 2026-09-09

  • International

    Not found in the instruments we track

  • Interpol

    Guidance or policy only

    It recommends adherence to fairness principles and identifies discriminatory outcomes as AI risks to monitor.

    Status verified 2026-09-07

  • ISO

    Guidance or policy only

    Organizations must monitor AI performance using metrics that include fairness.

    Status verified 2026-09-09

  • ITU

    Guidance or policy only

    It recommends diverse datasets and benchmarks to prevent reinforcement of bias in AI health data.

    Status verified 2026-09-07

  • NATO

    Guidance or policy only

    AI developers and users must take proactive steps to minimize unintended bias in applications and datasets.

    Status verified 2026-09-07

  • OAS

    Not found in the instruments we track

  • OECD

    Guidance or policy only

    Enterprises must identify AI lifecycle risks, including impacts on fairness.

    Status verified 2026-09-09

  • UNESCO

    Not found in the instruments we track

  • United Nations

    Guidance or policy only

    It urges UN entities to prevent bias and stigmatization in AI models.

    Status verified 2026-09-07

  • WHO

    Guidance or policy only

    It requires AI to be accessible regardless of personal characteristics and to reduce digital exclusion.

    Status verified 2026-09-09

  • World Bank

    Not found in the instruments we track

  • World Economic Forum

    Not found in the instruments we track