Posthumous health data donation: an emerging framework for equitable healthcare AI.

OBJECTIVE: To examine posthumous health data donation as a pathway toward more representative datasets used to develop healthcare artificial intelligence (AI). PERSPECTIVE: Healthcare AI systems are increasingly deployed in clinical settings, yet the datasets underlying these systems remain narrow, fragmented, and systematically underrepresenting key patient populations. Current consent frameworks, designed for living patients, create structural barriers to assembling diverse training data. Death meaningfully shifts the ethical risk-benefit calculus, substantially reducing harms, employment discrimination, insurance denial, social stigma, that presuppose a living subject. This creates a unique opportunity for individuals to contribute their health data posthumously through informed, opt-in consent established during life. CONCLUSION: Posthumous health data donation warrants serious exploration by the informatics, policy, and governance communities as a complementary mechanism for reducing structural barriers to inclusion, one that does not guarantee representativeness but may address gaps that living-patient consent frameworks cannot reach.