Trustworthy AI
What is Trustworthy AI?
AI systems that are lawful, ethical, and robust throughout their lifecycle. The concept, promoted by the EU's High-Level Expert Group on AI, encompasses seven key requirements including human agency, technical robustness, privacy, transparency, diversity, societal wellbeing, and accountability.
Terms that appear alongside trustworthy ai
Each of these is named in at least one of the same controls as trustworthy ai. The number is how many controls name both.
- accountability 4 shared controls
- transparency 4 shared controls
- use case 3 shared controls
- audit 3 shared controls
- eu ai act 3 shared controls
- governance 3 shared controls
- nist 2 shared controls
- ai incident 2 shared controls
Frameworks that govern trustworthy ai
What the standards actually require on trustworthy ai
Requirements naming trustworthy ai across 6 standards, quoted from the control text.
Operate third-party AI audit + impact assessments + metrics per OECD AI Principles + emerging assurance standards. Third-party AI audit must (a) engage independent assessors for high-risk AI systems per applicable regulation + voluntary assurance scheme (EU AI...
OECDAI-7 · Third-Party AI Audit, Impact Assessments, and Metrics for Trustworthy AI →The characteristics of trustworthy AI are integrated into organizational policies, processes, and procedures. Validity, reliability, safety, security, resilience, accountability, transparency, explainability, privacy and fairness appear as named obligations in...
AIRMF-GV-1.2 · The characteristics of trustworthy AI are integrated into organizational policies, processes, and procedures →Research from cognitive science on how people perceive, trust and interact with automated systems informs the design of trustworthy AI and its explanations.
iso-iec-tr-24028-2020::9.11.4 · Cognitive science research →A reporting framework under which developers of advanced AI systems voluntarily check and report their adherence to the Code of Conduct was agreed by the G7 with the OECD and has operated since February 2025;
japan-ai-guidelines::HP.RF · HAIP Reporting Framework participation (developers of advanced AI systems) →Review IT, security, procurement and software development lifecycle processes so they interoperate with AI due diligence; promote diverse decision-making on AI risk; develop incident monitoring and response systems;
oecd-due-diligence-guidance-for-responsible-ai-2026::1.2.8-16 · 1.2.8-16 Management systems: process integration, incidents, grievances, decommissioning and contingency →Engage proactively in responsible stewardship of trustworthy AI aimed at beneficial outcomes for people and the planet, such as augmenting human capabilities and creativity, including underrepresented populations, reducing economic, social, gender and other in...
oecd-recommendation-on-artificial-intelligence-2024-update::1.1 · 1.1 Inclusive growth, sustainable development and well-being →Questions people ask about trustworthy ai
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