Human AI Interaction and UX

Human AI Interaction and UX

Explanation and Evidence Presentation

34 of 57 in this book · 2 min read

Domain: Human–AI Interaction & Application UX
Status: Implementation guidance / design checklist
Applicability: Depends on product architecture and risk

Concept

Explanation and Evidence Presentation is the capability concerned with explanation and evidence presentation in the broader domain of safe, clear human interaction with AI workflows. Its purpose is to make this concern explicit, testable, governable, and reusable across AI-powered workflows. State what a user must understand, control, and recover from when using Explanation and Evidence Presentation.

Recommended Practices

  • Show status, provenance, and errors clearly; provide confirmation for meaningful side effects; usability-test failures.
  • Define an owner, API/schema contract, failure response, and acceptance criteria for explanation and evidence presentation.
  • Add automated positive, negative, boundary, and permission tests for explanation and evidence presentation; review metrics in staging and production.

Example Use Cases

  • A reviewer previews agent-written changes, rejects parts, and resumes the workflow.
  • Apply explanation and evidence presentation in a high-volume enterprise workflow while recording the user, project scope, input contract, and observable outcome.

Common Implementation Pitfalls

  • Displaying fabricated completion or trapping users in a process they cannot cancel.
  • No documented fallback, operational owner, or signal showing when explanation and evidence presentation is failing.
  • Testing only happy paths while ignoring missing data, revoked access, malformed outputs, and partial outages.

Production Readiness Checklist

  • An accountable owner and technical contract for explanation and evidence presentation are documented.
  • At least one successful and one failing end-to-end scenario is reproducible.
  • Access controls, retention, and audit requirements are verified where relevant.
  • Release monitoring includes a measurable success or failure signal for this capability.

Design Questions

  1. What concrete risk or business requirement requires Explanation and Evidence Presentation?
  2. What happens when it is unavailable, wrong, stale, or slow?
  3. How is its success evaluated against a trusted reference or observed outcome?
  4. Who can change its configuration, and how are changes released and rolled back?

Related Areas