platform-guideline checked
Transparency Note for Azure OpenAI
Documents transparency notes for understanding model capabilities, limitations, system context, owner choices, performance behavior, people affected, and deployment environment.
Pattern Decisions This Source Supports
| Pattern | Supported decision | Required contract | Claim note |
|---|---|---|---|
| AI confidence shown as fake precision | Flag this anti-pattern when an AI or automated surface shows a precise score without calibration scope, decision threshold, freshness, uncertainty reason, or safe next action. | The interface distinguishes raw internal scores from user-facing calibrated confidence. | Supports communicating capabilities, limitations, performance behavior, and deployment context for AI systems. |
| AI limitation onboarding | Choose AI limitation onboarding when the user needs first-use or changed-capability orientation about AI benefits, limits, data scope, uncertainty, feedback, human responsibility, and fallback. | The onboarding explains what the AI can help with and what it is not able to do before the first risky use. | Supports explaining model capabilities, limitations, system context, performance behavior, and deployment choices. |
Evidence Role
This source is treated as platform-guideline evidence. Use it to validate the decision rules above, not as a visual style reference.
Publisher: Microsoft Learn. Last checked: .