Ethical Machine Learning in Healthcare
Irene Y. Chen, Emma Pierson, Sherri Rose, Shalmali Joshi, Kadija Ferryman, Marzyeh Ghassemi
Abstract
The use of machine learning (ML) in healthcare raises numerous ethical concerns, especially as models can amplify existing health inequities. Here, we outline ethical considerations for equitable ML in the advancement of healthcare. Specifically, we frame ethics of ML in healthcare through the lens of social justice. We describe ongoing efforts and outline challenges in a proposed pipeline of ethical ML in health, ranging from problem selection to postdeployment considerations. We close by summarizing recommendations to address these challenges.
Topics & Concepts
Health carePipeline (software)Engineering ethicsEthical issuesSelection (genetic algorithm)Computer scienceArtificial intelligenceFrame (networking)PsychologyData scienceSociologyResearch ethicsHealthcare systemEthics of carePatient careInformed consentSocial careMedicineKnowledge managementMachine learningMedical ethicsArtificial Intelligence in Healthcare and EducationMachine Learning in HealthcareEthics and Social Impacts of AI