Stanford Professor Slams AI-for-Biology Work That Ignores Controls and Causality
anshulkundaje · x · 2026-10-03
Stanford computational biology professor Anshul Kundaje warns that many AI practitioners building models for biology simply don't think about experimental controls, resorting to "magical thinking" like assuming batch effects will be "emergently corrected."
He notes that classically trained biologists understand controls for traditional experiments, but when a model sits in the loop or data is generated specifically for a learning task, the specs, constraints, and covariate considerations differ substantially — requiring deep discussions with modeling teams to get right.
Related event: Stanford's Kundaje blasts AI×Bio rigor gaps and NeurIPS review quality(11 posts)→
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