Review Before Trust: Source-Grounded Integrity Gates for AI-Assisted Personal Health Records
This episode discusses the paper "Review Before Trust," which proposes integrity gates for AI-assisted personal health records. The hosts explore a system where raw AI data is treated as untrusted input until specific checks are passed. They detail how deterministic monitoring ensures data integrity, not clinical correctness, concluding that this framework creates a verifiable boundary against tampering.