Question 1

What is AI measurement science?

Accepted Answer

AI measurement science is the discipline of creating standardized, reproducible methods to evaluate AI system capabilities, safety, and compliance. It translates ambiguous governance requirements into technical executables that produce audit-ready evidence.

Question 2

Why does AI governance need measurement infrastructure?

Accepted Answer

AI governance requires measurement infrastructure because trust claims need verifiable evidence. Without standardized measurement, AI safety remains a marketing claim rather than a proven fact. Measurement infrastructure enables audit-ready documentation, interoperable compliance tools, and reproducible safety evaluations.

Question 3

What is the Public Logic Layer for AI?

Accepted Answer

The Public Logic Layer is IAIMS' approach to AI governance that provides open-source, standardized measurement tools between AI systems and regulatory requirements. It translates frameworks like NIST AI RMF, ISO 42001, and the EU AI Act into executable technical specifications.

Question 4

How does IAIMS approach AI audit and compliance?

Accepted Answer

IAIMS provides measurement infrastructure that produces audit-ready evidence for AI compliance. This includes standardized evaluation protocols, interoperable data formats, and open-source tools that work across regulatory frameworks including NIST, ISO, and EU AI Act requirements.

Question 5

What AI governance frameworks does IAIMS support?

Accepted Answer

IAIMS measurement infrastructure supports major AI governance frameworks including NIST AI Risk Management Framework (AI RMF), ISO/IEC 42001 AI Management Systems, the EU AI Act, and emerging international standards for AI safety and compliance.

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