Use seven trustworthiness lenses before you score readiness
Use trustworthiness characteristics as evidence categories in an AI readiness assessment.
The principle: trust is evidence, not tone. Trustworthy AI sounds abstract until you turn it into assessment questions. NIST gives practical lenses: valid and reliable, safe, secure and resilient, accountable and transparent, explainable and interpretable, privacy-enhanced, and fair with harmful bias managed. OECD's AI Principles point in the same direction: human-centered values, transparency, robustness, security, safety, and accountability. The evidence move Do not ask, "Do we trust this system?" Ask, "What evidence would make trust reasonable for this use case?" A low-impact drafting assistant may need source boundaries and review. A high-impact recommendation system may need subgroup testing, appeal rights,…
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