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AI-Assisted Review Workstation·Human-AI decision systems

AI could find the moment. Reviewers still had to own the judgment.

I designed an evidence-centered review workstation that uses model signals to narrow attention while keeping interpretation, escalation, and the final decision with accountable people.

AI-Assisted Review Workstation showing reviewer video, evidence, and decision controls
Hero proof · Shipped reviewer workflow
// RoleProduct Designer · end-to-end UX/UI
// AudienceReviewers · investigators · QA
// TeamProduct · architecture · engineering · quality
// Timeframe0→1 product · two validation rounds
// MaturityShipped reviewer workflow
// Signal~10× faster review · 4.5/5 usability
// Three product decisionsInterface first

Three decisions defined the review workflow.

Package AI flags with the evidence a reviewer needs without letting the model become the decision-maker.

AI-Assisted Review dashboard and review interface shown together
Queue · AI narrows attention before review.
Decision 01

Use the signal as a pointer, not an answer.

A risk flag opens the exact moment and its evidence.

AI-Assisted Review workstation and supporting comparison
Evidence · reason, moment, and action stay connected.
Decision 02

Keep the evidence attached to the moment.

Reason, timestamp, screenshot, event type, video context, and accommodations stay together so the reviewer does not rebuild the case from separate tools.

AI-Assisted Review decision and confirmation states
Recovery · a failed search preserves the path back to the work.
Decision 03

Make the decision state unmistakable.

Clear, revoke, escalate, reviewed, and unresolved states use explicit language and semantics.

// UI evidenceAdditional product evidence

More of the review workstation

Queue states, decision states, status feedback, and interface components from the working review product.

Product walkthrough
Legacy review workflow before the AI-assisted workstation
Earlier review workflow baseline
Smart Review investigator and reviewer context
Reviewer context · workflow validation evidence
Evidence and outcome

Testing showed that reviewers valued having the evidence together.

Two rounds with experienced internal users shaped the product. The later study rated the dashboard 4.6/5, video experience 4.3/5, and overall experience 4.5/5.

// ReflectionLimits and next questions

The workflow still has clear limits.

Tradeoff

Tradeoff

Faster triage could create automation bias.

Limitation

Evidence boundary

Future manager and reporting concepts are shown as direction, not represented as shipped capabilities.

Next step

Next test

Measure where reviewers override or correct model signals and use those moments to improve both workflow and model feedback.

// Protected deep caseDecisions · evidence · edge cases

See the evidence behind the decisions.

Includes the role breakdown, evidence, edge cases, outcomes, and lessons.

// Talk about a complex product

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