Robustness tests for biomedical foundation models should tailor to specification

R. Patrick Xian, Noah R. Baker, Tom David, Qiming Cui, A. Jay Holmgren, Stefan Bauer, Madhumita Sushil, Reza Abbasi-Asl

Abstract: Existing regulatory frameworks for biomedical AI include robustness as a key component but lack detailed implementational guidance. The recent rise of biomedical foundation models creates new hurdles in testing and certification given their broad capabilities and susceptibility to complex distribution shifts. To balance test feasibility and effectiveness, we suggest a priority-based, task-oriented approach to tailor robustness evaluation objectives to a predefined specification. We urge concrete policies to adopt a granular categorization of robustness concepts in the specification. Our approach promotes the standardization of risk assessment and monitoring, which guides technical developments and mitigation efforts.