RESEARCH · RESEARCH · #722
InterviewPlayground paper (arXiv:2609.21149v1) pilots clinician-grounded QA for AI psychiatric intake
The authors introduce InterviewPlayground, a clinician-grounded evaluation platform built around a memory-augmented patient simulator for open-ended AI interviewing, and report a pilot 25-minute assessment with 6 clinicians comparing the platform to a GPT-based LLM interviewer. In the pilot the LLM recovered more embedded clinically relevant items (88.0% vs 38.9%) but made more unsupported clinical inferences (56.8% vs 27.8%) and identified fewer safety concerns (33.3% vs 66.7%).
KEY POINTS
- The authors introduce InterviewPlayground, a clinician-grounded evaluation platform built around a memory-augmented patient simulator for open-ended AI interviewing, and report a pilot 25-minute assessment with 6 clinicians comparing the platform to a GPT-based LLM interviewer.
- In the pilot the LLM recovered more embedded clinically relevant items (88.0% vs 38.9%) but made more unsupported clinical inferences (56.8% vs 27.8%) and identified fewer safety concerns (33.3% vs 66.7%).
- Provides a practical, clinician-centered QA method and pilot data showing trade-offs (better item recovery but more unsupported inferences and weaker safety flagging) important for health systems evaluating AI intake tools.
WHY IT MATTERS
Provides a practical, clinician-centered QA method and pilot data showing trade-offs (better item recovery but more unsupported inferences and weaker safety flagging) important for health systems evaluating AI intake tools.