Direct answer
Public Trust, in this source register, is limited to the following inspected scope. Disclosure, meaningful information, and ability to challenge AI outcomes. Documentation, communication of impacts, limits, transparency, and accountability. The answer carries the source boundaries forward and does not infer authority from a neighboring topic.
Authority hierarchy and version notes
Order authorities by role, version, jurisdiction, and freshness rather than treating every link as interchangeable.
A source list is useful only when each source’s scope and boundary remain attached.
Applied scope: Disclosure, meaningful information, and ability to challenge AI outcomes. Documentation, communication of impacts, limits, transparency, and accountability.
Definition and operating context
The canonical concept owner is maha-policy. This route may apply governance; it cannot redefine or inherit the authority of its canonical owner.
This property may publish current-law summaries, policy evidence, Maha proposals labelled as proposals. It must not publish legal advice or proposal presented as enacted law.
Evidence and exact locators
OECD AI Principle 1.3: Transparency and explainability — Principle 1.3. Establishes: Disclosure, meaningful information, and ability to challenge AI outcomes.
Artificial Intelligence Risk Management Framework (AI RMF 1.0) — GOVERN 4.2; MAP 2.2; MEASURE 2.8–2.9. Establishes: Documentation, communication of impacts, limits, transparency, and accountability.
What the evidence does not establish
A principle is not evidence that public trust increased.
AI RMF is voluntary and trustworthiness characteristics can conflict.
This route must not claim legal advice.
This route must not claim proposal presented as enacted law.
Related definitions and applications
same-topic-application: https://policy.mahastrategies.com/policy/public-trust/definition
canonical-family-owner-definition-first: https://policy.mahastrategies.com/policy/tool-governance/definition
same-topic-application: https://policy.mahastrategies.com/policy/public-trust/uncertainty
same-topic-application: https://policy.mahastrategies.com/policy/public-trust/mechanisms
property-home: https://policy.mahastrategies.com/
same-topic-application: https://policy.mahastrategies.com/policy/public-trust/comparison
same-topic-application: https://policy.mahastrategies.com/policy/public-trust/current-law
Questions this page can answer
What does Public Trust mean in this bounded context?
Public Trust, in this source register, is limited to the following inspected scope. Disclosure, meaningful information, and ability to challenge AI outcomes. Documentation, communication of impacts, limits, transparency, and accountability. The answer carries the source boundaries forward and does not infer authority from a neighboring topic.
Which inspected sources support this sources answer?
OECD AI Principle 1.3: Transparency and explainability (principle page inspected 2026-09-05), at Principle 1.3, supports disclosure, meaningful information, and ability to challenge AI outcomes. Artificial Intelligence Risk Management Framework (AI RMF 1.0) (NIST AI 100-1, January 2023), at GOVERN 4.2; MAP 2.2; MEASURE 2.8–2.9, supports documentation, communication of impacts, limits, transparency, and accountability.
What does the evidence not establish?
A principle is not evidence that public trust increased. AI RMF is voluntary and trustworthiness characteristics can conflict. Property boundary: This route may apply governance; it cannot redefine or inherit the authority of its canonical owner.
Which definition or canonical owner must be read first?
Read the maha-policy definition at https://policy.mahastrategies.com/policy/tool-governance/definition first. The present page applies that definition through its narrower route role.
What source, policy, implementation, or release change would require revision?
Re-evaluate this page when a cited source, locator, governing instrument, local implementation, or canonical definition changes. Publication also requires a matching exact-revision review and active canonical release.