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hardUI/UX Designer interview question

How do you design an AI-powered feature whose outputs are sometimes wrong, so users trust it the right amount?

What the interviewer wants to hear

  • Match the use case to the risk of errors
  • Set expectations and label AI content
  • Show sources, confidence or reasoning to verify
  • Easy editing, undo and human control
  • Feedback loops and measuring trust and accuracy

Model answer

I start with risk: what happens when the AI is wrong? For low-risk tasks like suggesting a title, errors are cheap. For contracts or medical notes, the design must make verification easy. I set expectations clearly, label AI content and explain what it can and cannot do. Where possible I show sources or the input behind each claim so users can check quickly. The user stays in control: suggestions can be edited, accepted or undone, and high-stakes actions need confirmation. I design error and empty states for when the model fails or refuses. I add lightweight feedback like thumbs or corrections, which helps both users and the model team. Finally, I measure not just usage but whether users catch errors and whether their trust matches actual accuracy.

Can you answer it under time pressure?

Take a timed hard round and get scored on every answer.

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