When the AI Statistician Gets It Right (and Why That's the Dangerous Part)
A few months ago, I asked an LLM to design my clinical trial. It recommended a Bayesian borrowing design for a Phase 2 single-arm oncology trial. The response was fluent, well-organized, and cited the right methods. It was also wrong—in ways that would survive a casual review. That post