Override a Low-Confidence Model Decision
Design a review queue that helps an operator understand uncertain classifications, make a human decision, and record downstream effects.
The brief
Understand the problem
Background
A confidence value is only useful when reviewers know what decision it refers to, how the threshold was set, and what evidence was missing. An override also needs more than a button because it may affect routing, customer treatment, and later evaluation.
User context
Luis reviews expense reports routed by a classification model. One report is labeled personal expense at 54 percent confidence even though the receipt shows a client dinner and the calendar contains a matching meeting.
Product problem
Operators need to examine case evidence and uncertainty without anchoring on a score, then make a reversible decision with a clear rationale and accountable effect.
Objective
Create queue prioritization, evidence review, override, and outcome monitoring for one low-confidence expense classification.
What to design
Define the experience
Required experience
- Find cases that require review based on uncertainty and operational impact
- Inspect inputs, missing signals, alternative labels, and policy context
- Confirm or override the proposed label with a reason
- Review downstream actions and flag the case for quality analysis
Screens and states
- Review queue
- Case evidence
- Decision and override
- Outcome audit
Core user flow
Follow the critical path
- 01
Luis opens the queue sorted by payment deadline and review need
- 02
He sees the proposed label only after reviewing receipt, merchant, attendee, and policy context
- 03
He selects client meal and records the matching calendar event
- 04
The interface previews that the change will resume reimbursement and remove a manager exception
- 05
Luis confirms the override and sends the case to a sampled quality set
Product rules
Requirements and constraints
Requirements
- Pair confidence with calibration context, decision threshold, alternatives, and missing inputs
- Avoid visual treatment that makes the proposed label appear authoritative by default
- Show policy evidence and case evidence separately
- Require rationale proportionate to the impact of an override
- Record downstream state changes, reversibility, reviewer, and later quality outcome
Constraints
- Reviewers must not infer protected characteristics from unrelated profile data
- Confidence values from different model versions are not directly comparable
- An override cannot silently update policy or retrain a model
Reality check
States worth considering
Finish line
What to deliver
- Four desktop screens showing evidence-first review, a human override, and downstream audit
Optional direction
Visual resources
Use these as a starting constraint if you want one. They are not part of the required solution.
Amatic SC & Josefin Sans
Clear interface writing gives people the confidence to understand what changed and decide what to do next.
Amatic SC & Josefin Sans
Clear interface writing gives people the confidence to understand what changed and decide what to do next.
Theory to review
UX principles for this brief
Use these as decision lenses, then validate the design with the people and context in the brief.
