Examples
Worked examples
- Is an instance
An academic medical center runs an investigator-initiated Phase 2 trial of an already-approved drug for a new (off-label) indication under its own IND. Because the study is regulated by FDA under an IND, the informed consent form and process must satisfy 21 CFR 50.20 and 50.25 (basic elements of consent), even though no NIH grant is funding the study.
- Is an instance
An NIH-funded multi-site trial testing a novel investigational device (studied under an IDE) is subject to BOTH 45 CFR 46 (because it is federally funded and conducted by a Common Rule-signatory institution) AND 21 CFR Part 50 (because the device is FDA-regulated). The consent document and IRB review process must independently satisfy both regulations' requirements -- where they differ, the study must meet the stricter standard, and the IRB reviewing the protocol typically documents dual-track compliance explicitly.
Counter-examples
Looks similar, but isn't
- Not an instance
An NSF-funded behavioral-science survey study that does not involve any FDA-regulated drug, biologic, or device is subject to 45 CFR 46 (as a federally funded, non-exempt human subjects study) but NOT to 21 CFR Part 50 -- FDA has no jurisdictional hook because no FDA-regulated product is involved.
Editorial commentary
The OECD AI Principles are a set of intergovernmental standards for trustworthy artificial intelligence, adopted by the Organisation for Economic Co-operation and Development’s Council at Ministerial level in May 2019 and updated in May 2024. They were the first AI principles endorsed at the intergovernmental level and were later reflected in the G20 AI Principles. As of the 2024 update, 47 countries and jurisdictions adhere to them, including every OECD member state, the European Union, and a number of non-member adherents (source: OECD, AI principles and OECD.AI, AI Principles overview).
The five values-based principles
- Inclusive growth, sustainable development and well-being — AI should benefit people and the planet.
- Human rights and democratic values, including fairness and privacy — AI actors should respect the rule of law, human rights, and democratic values throughout the AI system lifecycle.
- Transparency and explainability — AI actors should provide meaningful information appropriate to the context, enabling those affected to understand and, where appropriate, challenge outcomes.
- Robustness, security and safety — AI systems should function appropriately and not pose unreasonable safety risk throughout their lifecycle.
- Accountability — AI actors should be accountable for the proper functioning of AI systems, in line with the other four principles.
The five recommendations for policymakers
- Investing in AI research and development.
- Fostering an inclusive AI-enabling ecosystem.
- Shaping an enabling, interoperable governance and policy environment for AI.
- Building human capacity and preparing for labour-market transition.
- International co-operation for trustworthy AI.
The 2024 update
The May 2024 revision responded directly to the emergence of general-purpose and generative AI. It expanded the human-centred-values principle to address AI-amplified misinformation and disinformation while respecting freedom of expression, and sharpened language on privacy, intellectual property, and safety in light of generative-AI-specific risks (source: OECD press release, May 2024).
Why this differs from the EU AI Act
The OECD AI Principles are voluntary, non-binding policy guidance adopted by governments — they set a shared normative baseline and inform national AI strategies, but they create no legal obligations of their own and no enforcement mechanism. The EU AI Act is binding EU law with defined obligations, exemptions (including specific carve-outs relevant to research), and penalties. In practice the two are closely related: the EU AI Act’s own risk-based, human-rights-oriented framing draws on the same normative ground the OECD Principles established in 2019. A research organization operating in the EU needs to track AI Act compliance as a legal matter; the OECD Principles are useful as the broader governance vocabulary and as the operative standard where no binding law yet applies (most jurisdictions outside the EU).
How research organizations apply the Principles
The OECD Principles are not sector-specific, but research institutions, funders, and research-performing organizations increasingly use them as a reference point for institutional AI-governance policy, alongside more technical frameworks like the NIST AI Risk Management Framework and ISO/IEC 42001. Concretely, this typically means: documented accountability for AI systems used in research workflows (from AI-assisted literature review to AI-assisted data analysis); disclosure to affected parties (co-authors, reviewers, study participants, research subjects) when AI materially shaped a research output or decision; and testing/validation proportionate to the AI system’s role, rather than a single blanket sign-off. See also Responsible AI and Trustworthy AI for the related concepts these Principles operationalize, and Generative-AI disclosure statement for the specific mechanism most journals and funders now use to satisfy the transparency principle at the point of publication or proposal submission.
Sources
- OECD — AI principles
- OECD.AI — AI Principles overview
- OECD press release, 8 May 2024 — OECD updates AI Principles
Frequently Asked Questions
What are the five OECD AI Principles?
The five values-based principles are: inclusive growth, sustainable development and well-being; human rights and democratic values, including fairness and privacy; transparency and explainability; robustness, security and safety; and accountability. They were adopted by the OECD Council at Ministerial level in May 2019 and updated in May 2024.
How are the G20 AI Principles related to the OECD AI Principles?
The OECD AI Principles were the first AI principles endorsed at the intergovernmental level, and the G20 AI Principles were adopted afterward, reflecting the same framework. The OECD Principles are the originating standard rather than a parallel or independent one.
What changed in the OECD AI Principles’ 2024 update?
The May 2024 revision responded directly to the emergence of general-purpose and generative AI. It expanded the human-centred-values principle to address AI-amplified misinformation and disinformation while respecting freedom of expression, and sharpened language on privacy, intellectual property, and safety in light of generative-AI-specific risks.
Are the OECD AI Principles legally binding?
No. They are voluntary, non-binding policy guidance adopted by governments, creating no legal obligations of their own and no enforcement mechanism. This differs from the EU AI Act, which is binding EU law with defined obligations, exemptions, and penalties.
How many countries have adopted the OECD AI Principles?
As of the 2024 update, 47 countries and jurisdictions adhere to the OECD AI Principles, including every OECD member state, the European Union, and a number of non-member adherents.
How do research organizations use the OECD AI Principles?
Research institutions, funders, and research-performing organizations use the Principles as a reference point for institutional AI-governance policy, often alongside more technical frameworks like the NIST AI Risk Management Framework and ISO/IEC 42001. In practice this means documented accountability for AI systems used in research workflows, disclosure to affected parties when AI materially shaped a research output, and testing or validation proportionate to the system’s role.
Machine-readable encodings
Use in your systems
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