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 3 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 →Continuous Monitoring + Lifecycle Management is essential to ongoing trustworthy AI per Japan AI Guidelines for Business + integrates Safety + Accountability + Transparency Principles + addresses post-deployment risks.
JP-AIG-Continuous-Monitoring-Lifecycle-Model-Evaluation-Performance-Drift-Post-Deployment · Japan AI Guidelines Continuous Monitoring + AI System Lifecycle Management + Model Evaluation + Performance Drift + Concept Drift + Post-Deployment + Retraining Triggers + Safe Update + Decommissioning + Model Card Versioning →Questions people ask about trustworthy ai
What is Trustworthy AI?
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