SALARAHandbook

The Evidence

Research Library

The Research Library connects handbook observations to public evidence. Each record separates what the source reports from why it matters and how the handbook interprets it.

Canonical evidence objects

ai governance

Public sources only. The records are intentionally concise so future chapters, topic search, and Knowledge CI/CD integrations can reuse the same model.

National Institute of Standards and TechnologyJanuary 2023

Artificial Intelligence Risk Management Framework (AI RMF 1.0)

NIST provides a voluntary framework for identifying, assessing, and managing AI risks across the AI lifecycle.

What the source reports

  • The AI RMF frames trustworthy AI as a risk-management challenge requiring governance, mapping, measurement, and management.
  • It emphasizes context, impacts, documentation, and structured risk practices.
  • It treats trustworthiness as something organizations must operationalize, not merely assert.

Why it matters here

Chapter 4 identifies governance as an important contribution in a technology landscape where capability and accountability remain distinct.

Guided Intelligence interpretation

The source does not endorse Guided Intelligence. It informs the handbook principle that AI-assisted guidance needs context, evidence, and accountability.

FrameworkLast verified 2026-07-10
Original public source
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