platform-guideline 2 linked patterns 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.
Read with a purpose
What this source can teach
Use this source to understand a platform convention and the setting it was designed for.
- Start with the original. Open the source and find the guidance or example relevant to your task.
- Trace the connection. Use the claim notes below to see how this site applies the source to specific patterns.
- Check the setting. Compare the source's platform, people, and constraints with your own decision.
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. |
Comparisons supported by this source
- AI confidence shown as fake precision vs confidence / uncertainty display vs meter vs source grounding display vs warning text vs human approval gate
Supports explaining AI capabilities, limitations, performance behavior, and deployment context.
- AI limitation onboarding vs onboarding vs inline message vs warning text vs confidence uncertainty display vs source grounding display vs scope clarification vs human approval gate
Supports transparency around capabilities, limitations, system context, and performance behavior.
Evidence Role
This source is treated as platform-guideline evidence. Its value comes from the specific claims and setting described above.
Publisher: Microsoft Learn. Last checked: .