Explainability UX Patterns
The short answer · 16 words
In short
Design explainability patterns as users see reasons, uncertainty and options for action of an AI system.
Flow-alerta.cab (2026): Explainability UX Patterns. https://flow-alerta.cab/en/glossar/explainability-ux-patterns. Editorially reviewed on: 10 October 2026.
How much detail would you like?
Practical
Good UX can promote adequate trust; poor presentation creates overconfidence or confusion.
Hypothetical example: A risk score first shows main reasons and uncertainty, if necessary data origin and objection possibility.
SMEs should test explanations with actual user roles, not just generate them technically.
At a glance
- Core
- Explanations should fit the user role, task and decision. For example, you can show reasons, comparative examples and uncertainty in an understandable order and check with users whether meaningful actions follow.
- Use
- Good UX can promote adequate trust; poor presentation creates overconfidence or confusion.
- Example
- Hypothetical example: A risk score first shows main reasons and uncertainty, if necessary data origin and objection possibility.
- Limits
- For technical graphics; apparent accuracy; manipulative safety signals; no possibility of correction or escalation.
In context
Explainable AI (XAI)
XAI includes methods by which people can retrace AI results or model behavior.
Progressive Disclosure
UX design pattern, in which information is gradually disclosed as needed by the user to avoid overburdening.
Human-in-the-Loop
Human-in-the-loop means that people decide or examine in important places.
Questions about this term
What is the best explanation?
There is no universal; goal and users determine it.
Is Feature Importance Enough?
Often not.
All details and background
Explanations should fit the user role, task and decision. For example, you can show reasons, comparative examples and uncertainty in an understandable order and check with users whether meaningful actions follow.
ELI5 – Explained simply
The explanation is presented in such a way that people can understand it and act meaningfully.
Why it matters in practice
Good UX can promote adequate trust; poor presentation creates overconfidence or confusion.
Example
Hypothetical example: A risk score first shows main reasons and uncertainty, if necessary data origin and objection possibility.
Pitfalls and limits
- For technical graphics; apparent accuracy; manipulative safety signals; no possibility of correction or escalation.
Origin & history
Wang et al. published a theory-driven, user-centred XAI framework in 2019 and tested it with a clinical diagnostic interface.
Use in mid-sized companies
- SMEs should test explanations with actual user roles, not just generate them technically.
Related terms
- XAI
- Progressive disclosures
- Uncertainty
- Human-in-the-loop
- Trust Calibration
Matching Flow-alerta service
Websites & web applicationsWebsites & Web Applications: Examine explanations, uncertainty and corrective paths for a possible AI user process.Matching tool / use case
View use casesUse Case: Tested Explanatory View with Sources, Uncertainty and Corrective PathSources
Quellenprüfung: 10.10.2026. Definition und dokumentierte Einordnung abgeglichen; Beispiele beschreiben mögliche Anwendungen.
Editorially reviewed on: