Transparency Policy

Data artifactGovernance & ComplianceSafety, Security & Governancearc:TransparencyPolicy

An organizational policy specifying how disclosure, data governance, decision-logic, outcome-explanation and ethical-governance transparency are implemented across contexts.

Responsibility. Operationalizes transparency obligations into concrete, context-specific requirements.

Also known as: Comprehensive transparency policy, Calibrated disclosure policy

Direct neighbourhood (hover for relationship types)

Relationships

configures structural

constrains control

Agent Controller abstract Ch9.3
Summary Explanation View Ch10.5

Design guidance

SHOULD disclose data sources, storage and retention, intentional data exclusions, training objectives, known limitations, error rates and uncertainty handling.
SHOULD describe discrimination safeguards, bias monitoring and harmful-output procedures specifically rather than vaguely.
SHOULD disclose which factors mattered and roughly how much weight they carried without exposing exact scoring formulas or thresholds that adversaries could exploit.

Quantitative guidance

As stated by the sources; verify before use.

Example: diagnostic AI 95% accurate for common conditions but 60% for rare diseases should be disclosed (Ch9.3).

Classification

Patterns: Multi-layered transparency (notification, explainability, traceability, accountability)
Frameworks & regulations: EU AI ActGDPRHIPAASOC 2

Sources

Ch9.3: T. Nguyen, "Sandboxing and Transparency Foundations," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 9.3. ISBN: 9798244538229.
Ch10.5: T. Nguyen, "Human-over-the-Loop," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 10.5. ISBN: 9798244538229.