Responsible
WHO ethics · NIST AI RMF · UNESCO · FDA · EU AI Act
CREED.AIPrimum non nocereCREED.AI institutional foundation
Global Guidance
Library.
Authoritative principles, standards and frameworks that shape CREED.AI’s work.
Explore the collection ↓18guiding resources
11institutions & collaborations
4areas of guidance
Official-source links · Curated by CREED.AI · Reviewed August 2026
From principles to practice
Guidance is useful when it changes decisions.
This library is not an endorsement list or a substitute for applicable law. It shows the external foundations CREED.AI uses to ask better questions, design evaluations and support responsible implementation.
Every source is linked to its official publisher so visitors can find the authoritative version and future updates.
The CREED lens
Four commitments.
A global foundation.
Evidence-based
WHO evidence framework · NIH Bridge2AI · lifecycle evaluation
Equitable
WHO ethics · Health Canada · NIH AIM-AHEAD · UNESCO
Deployment
WHO AI for Health · CDC strategy · international transparency principles
Foundational collection
Start with WHO.
The WHO collection anchors CREED.AI’s approach to ethics, evidence, regulation and country-level implementation.
01
2021 · Global guidance
↗02Ethics and Governance of Artificial Intelligence for Health
2021 · Evaluation framework
↗03Generating Evidence for AI-Based Medical Devices
2023 · Regulatory resource
↗04Regulatory Considerations on Artificial Intelligence for Health
2025 · Global guidance
↗Ethics and Governance of AI for Health: Large Multi-Modal Models
Living collection
Explore guiding documents.
18resources shown
WHOFoundational
Ethics and Governance of Artificial Intelligence for Health
Six consensus principles place autonomy, safety, transparency, accountability, inclusion and sustainability at the center of health AI.
View official source ↗WHOFoundational
Generating Evidence for AI-Based Medical Devices
A lifecycle framework for training, validation, evaluation and post-market evidence for AI-based medical devices.
View official source ↗WHOCurrent
Regulatory Considerations on Artificial Intelligence for Health
A global overview of risk-benefit assessment, performance evaluation, collaboration and monitoring considerations.
View official source ↗WHOCurrent
Ethics and Governance of AI for Health: Large Multi-Modal Models
Specific governance recommendations for foundation and generative models used in care, research, public health and drug development.
View official source ↗WHOCurrent
Artificial Intelligence for Health
WHO’s vision for science-based adoption, country capacity, equitable ecosystems and sustainable AI deployment.
View official source ↗WHOCurrent
Artificial Intelligence and Evidence-Informed Policy
Practical guidance for using AI across the health-policy cycle while preserving human judgment, plurality and trust.
View official source ↗CDCCurrent
CDC Artificial Intelligence Strategy
A public-health blueprint for responsible AI adoption, disease detection, operational improvement, workforce readiness and partnerships.
View official source ↗CDCCurrent
Considerations for Generative AI in Public Health
Practical steps for mission alignment, human oversight, safety, scientific integrity, privacy and transparent use in public-health agencies.
View official source ↗ECDCContext & foresight
Digital Technologies for Infectious-Disease Surveillance, Prevention and Control
Maps AI and other digital technologies to surveillance, signal detection, forecasting and outbreak-response functions.
View official source ↗ECDCContext & foresight
Future Challenges for Infectious-Disease Prevention and Control
Identifies AI, data capability, public trust, vulnerable-community engagement and international cooperation as future public-health priorities.
View official source ↗NIHCurrent
Bridge to Artificial Intelligence
Resources and best practices for ethically sourced AI-ready biomedical data, trustworthy research and interdisciplinary workforce development.
View official source ↗NIHCurrent
AIM-AHEAD Health Equity Report
Community-informed priorities for using AI and health data to address disparities and broaden participation in AI research.
View official source ↗HCCurrent
Pan-Canadian AI for Health Guiding Principles
Shared principles for equitable access, transparency, privacy, safety, lifecycle oversight and accountability across Canadian health systems.
View official source ↗3RACurrent
Transparency for Machine Learning-Enabled Medical Devices
International principles for communicating intended use, performance, limitations, bias, workflow fit and lifecycle monitoring.
View official source ↗NISTFoundational
Artificial Intelligence Risk Management Framework 1.0
A voluntary structure for governing, mapping, measuring and managing AI risks and trustworthiness across the lifecycle.
View official source ↗EUCurrent
European Union Artificial Intelligence Act
A risk-based legal framework with requirements for data quality, documentation, oversight, robustness, transparency and accountability.
View official source ↗UNESCOFoundational
Recommendation on the Ethics of Artificial Intelligence
A human-rights-centered global standard addressing dignity, fairness, inclusion, oversight and health and social well-being.
View official source ↗OECDFoundational
OECD Artificial Intelligence Principles
Human-centered principles for innovative and trustworthy AI that respects human rights and democratic values.
View official source ↗Living governance
Current, transparent and open to contribution.
CREED.AI will review this collection regularly, identify drafts and superseded versions, and distinguish formal guidance from research programs, strategies and foresight reports.
Recommend an authoritative resource ↗