Research
Consumer AI as Health Plan Decision Support
A benchmark of the July 2026 consumer AI lineup from OpenAI and Anthropic on a realistic health plan selection task, scored against a claims-based pricing engine. We test what models optimize, how accurate their recommendations are, and whether richer consumer information or better insurance data improves performance. The results suggest consumer AI may be approaching a point where it can provide genuinely useful plan-selection support.
Explore the findings →In progress
Can we design a decision support algorithm that improves consumer welfare and minimizes selection?
What happens to the risk pool if everyone gets good advice? A claims-based simulation quantifies the trade-off between consumer welfare and insurance market selection under different decision-support designs — including a reimplementation of the HealthCare.gov cost estimator as a benchmark.
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