Catalog

WHO AI-for-Health (LMM) Guidance

World Health Organization · pack 0.1.2 · verified against the official source as of 2026-09-04.

Standard / soft law

Health AI/LMMs should keep a clinician accountable with oversight and redress (WHO)

Per the WHO Guidance on AI for Health (LMMs), under the consensus principles 'foster responsibility and accountability' and 'protect autonomy', AI/LMMs used in health care must be subject to human oversight — a health-care provider or clinician remains accountable for clinical decisions and must be able to review, override, and take responsibility for AI outputs — with clear assignment of responsibility and mechanisms for redress for individuals harmed by an AI-informed decision. Detect a health-AI decision path with no clinician oversight/override or no accountability/redress mechanism.

who-health-ai.clinician-oversight-accountability · WHO LMM Guidance (2024) — Human oversight & accountability recommendation · official source · jurisdictions: *

Standard / soft law

Health AI/LMMs should be transparent and documented before deployment (WHO)

Per the WHO Guidance principle 'ensure transparency, explainability and intelligibility', sufficient information must be published or documented before the design or deployment of a health-AI technology, and outputs should be explainable/intelligible to users (clinicians and patients). Developers should transparently design LMMs, document training-data provenance, and disclose limitations. Detect a health-AI deployment with no pre-deployment documentation (intended use, data, limitations) or explainability provision.

who-health-ai.transparency-documentation · WHO Ethics and Governance of AI for Health (LMMs, 2024) — Six Consensus Principles · official source · jurisdictions: *