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 Act conformity assessment + ISO/IEC 42001 certification + NIST AI RMF profile assessment + sector-specific), (b) maintain auditability of AI systems including documentation + access to model + data + logs + decision history + (c) implement findings remediation tracking through closure. Impact Assessments Aligned to OECD Principles must (a) conduct AI impact assessments per use case covering OECD Principles + applicable regulation (AI Conformity Assessment per EU AI Act + Algorithmic Impact Assessment per Canadian Directive + DPIA per GDPR + EHRIA + similar), (b) involve diverse stakeholders + affected communities + subject matter experts + (c) document the assessment + findings + mitigations + acceptance + reassessment triggers. Metrics and indicators for trustworthy AI must (a) define operational metrics per OECD Principle (inclusive growth + human-centred + transparency + robustness + accountability), (b) measure operationally across the AI portfolio + report to governance bodies + (c) benchmark against peer organisations + industry indices + (d) integrate with broader enterprise risk and ESG metrics where applicable.
The graph holds this control, the 0 it maps to, and the evidence behind each claim, over MCP and REST.