Ethical principles are foundations of medicine and should guide the integration and implementation of health AI but are often considered in isolation, typically at deployment. The authors argue that ethical principles are fundamental constructs across the full AI development-deployment life cycle and show how trade-offs and dependencies between principles shape feasible and ethically robust development and use of health AI, particularly in low-resource settings.
Biological foundation models promise generalization. The authors argue that the field needs a community-driven evaluation that tests generalization through prospective validation across biological and experimental contexts.
