OLYA
designing trust in AI-mediated diagnosis
Overview
Reimagining mental health evaluations through VR pass-through & AI clarity.
Mental health assessment feels inaccessible—expensive, intimidating, and requiring you to admit you need help before you even know what's wrong.
Traditional clinical assessments demand vulnerability with strangers in unfamiliar settings. But introducing AI raises new questions: How do you design an AI system people will trust with their mental health? What does trustworthy AI actually look like?
So, what exactly did we make?
Our final design combines a pass-through VR evaluation with a clear two-layer report.
People move through the evaluation in their own physical space while tasks appear one at a time, and clinicians get a structured summary that supports their workflow.
Once the psychiatrists and providers have completed their review, patients receive a version of the same information written in language they can act on as well as the diagnosis.
Everything lives inside MyChart, so nothing about adoption relies on a brand-new tool.
Before we get ahead of ourselves, how did we get here?
We conducted a lot of research. I won't go into it all here but you can find more on my blog.
Methods
- Secondary research into clinical workflows
- Interviews with patients and clinicians
- Multimodal concept exploration
- Competitive and precedent analysis (incl. VR tools for children’s vision therapy)
Key Insights
- People hesitate before scheduling care because the process feels unpredictable.
- Clinicians lose flow switching between tools during evaluation.
- Patients need clarity, not medical volume.
- AR is unreliable; VR pass-through provides consistent visibility.
Solution
Let's break the design down real quick.
Traditional clinical assessments demand vulnerability with strangers in unfamiliar settings. But introducing AI raises new questions: How do you design an AI system people will trust with their mental health? What does trustworthy AI actually look like?
Decisions
Three critical points of decision.
Traditional clinical assessments demand vulnerability with strangers in unfamiliar settings. But introducing AI raises new questions: How do you design an AI system people will trust with their mental health? What does trustworthy AI actually look like?
Decision 1: Why VR over a traditional app or how things are done right now?
Decision 2: Translating Clinical Protocols to AI Delivery
THE CHALLENGE:
How do you maintain clinical standardization while making the
AI feel supportive rather than robotic?
OUR APPROACH:
We studied actual WAIS-IV administration protocols and designed
a three-layer system:
1. PROTOCOL LAYER (invisible to user)
• AI follows exact timing, question sequencing, scoring rules
• No deviation from clinical standards
2. GUIDANCE LAYER (visible when needed)
• "Take your time—there's no wrong answer"
• Contextual encouragement without influencing responses