ux-research checked
People + AI Guidebook
Practical guidance for human-centered AI products, including user trust, expectations, explanation, feedback, and uncertainty-aware AI product decisions.
Pattern Decisions This Source Supports
| Pattern | Supported decision | Required contract | Claim note |
|---|---|---|---|
| Confidence / uncertainty display | Choose confidence / uncertainty display when users need to judge prediction reliability before acting on AI or automation output. | The display names the task, prediction, source of the confidence estimate, calibration scope, and last calibration or update time when available. | Supports human-centered AI design guidance around expectations, explanation, feedback, and trust. |
| Correction feedback | Choose correction feedback when users need to correct AI output, source use, assumptions, recommendations, safety behavior, or answer quality after an AI response is shown. | A correction feedback action preserves answer ID, response version, claim span, source ID, user reason, expected correction, submitter, timestamp, and chosen scope. | Supports human-centered AI feedback, expectations, explanation, and trust decisions. |
| Scope clarification | Choose scope clarification when the AI needs a missing boundary before producing a reliable answer, plan, retrieval query, or tool action. | The system identifies what boundary is missing before asking the user to clarify. | Supports expectation setting, trust, explanation, and uncertainty-aware AI decisions. |
Evidence Role
This source is treated as ux-research evidence. Use it to validate the decision rules above, not as a visual style reference.
Publisher: Google PAIR. Last checked: .