Source: STAT
A researcher used Claude to interpret genomic data in half an hour—work that typically requires credentialed geneticists and weeks of validation—exposing how LLMs can produce plausible-sounding medical interpretations without the institutional guardrails that protect patients from misdiagnosis. The core problem is not AI capability versus human expertise, but speed of adoption outpacing regulatory frameworks, clinical validation protocols, and liability structures. As these tools migrate from research into consumer or clinical settings, individuals risk making irreversible health decisions based on confident but unvetted machine analysis. Binding standards for AI-assisted genomic interpretation do not yet exist.