A Process Framework for Ethically Deploying Artificial Intelligence in Oncology
Andrew Hantel, Dillon D. Clancy, Kenneth L. Kehl, Jonathan M. Marron, Eliezer M. Van Allen, Gregory A. Abel
Abstract
2] 4] Oncology AI tools apply to not one but two genomes (germline and somatic); can greatly complicate the existing weight of bias, discrimination, and structural racism in cancer care; and can subtly undermine patient and physician autonomy, leading to cancer care that is algorithmic rather than patientcentered. These diverse concerns, in the context of unreserved enthusiasm for AI, challenge a future where oncology AI is both widely implemented and ethically acceptable. We propose that adapting a processfocused approach for deploying AI in cancer care, such as the accountability for reasonableness framework (A4R), 6 can address these concerns and realize a future where oncology AI is ethically deployed.