AI + UX · 6 min read
Honest AI confidence & errors
Help people know when to trust AI — and how to recover when it’s wrong.
Explained like for kids
Sometimes a classmate sounds very sure but is totally wrong. Good AI UX is like a classmate who says “I’m pretty sure” or “I might be guessing” — and helps you fix mistakes fast.
Examples
Each example has a kid-friendly “why,” then a clear Don't and Do with a real UI mock so you can see the difference.
Guesses shouldn’t look final
Like for kids: Writing in permanent marker feels final. Pencil says “we can still change this.”
Don’t
Bold final copy for uncertain AI output
People accept hallucinations as truth.
Your competitor’s churn is exactly 12.4%.
Stated as fact — may be hallucinated
Do
Draft styling + “Verify before sending”
Visual tone matches uncertainty. Invites review.
Draft · verify before sharing
Estimated churn ~10–15% based on public reviews — confirm with your data.
Easy reject / undo
Like for kids: If the helper paints the wall the wrong color, you need a big eraser — not a scavenger hunt.
Don’t
AI change applied with no undo
Fear of trying AI. One bad edit ruins trust.
AI rewrote your entire brief.
Old version is gone
Do
Clear Undo + Keep side by side
Safe to experiment. Mistakes stay cheap.
AI suggested a shorter brief.
Human error messages
Like for kids: “Error 429 rate_limit_exceeded” is robot talk. “Too many requests — try again in a minute” is kid talk.
Don’t
Raw API / model error strings
Scary and useless for non-engineers.
Do
Plain language + what to do next
People recover without leaving the flow.
Too many requests right now
Wait about a minute, then try again.
High-stakes need a check
Like for kids: You wouldn’t take medicine because a cartoon character suggested it. Important answers need a grown-up check.
Don’t
One-click “Send invoice” from raw AI text
Financial / legal mistakes get expensive fast.
Invoice total: $48,200 — ready to send.
Send invoice nowDo
Review checklist before the final action
Human-in-the-loop for irreversible steps.
- ☐ Amount matches quote
- ☐ Client email correct
- ☐ Tax line reviewed
Remember these
- Don’t dress guesses as certain facts.
- Offer “check this” paths for high-stakes answers.
- Make undo / reject easy when AI is wrong.
- Explain errors in human language, not model codes.
Trust and hallucination patterns for AI product interfaces. Rewritten in plain language for learning — not a reprint of the originals.