Ethical Machine Learning in Health Care
It tackles ethical issues in health care ML to promote equity, but is incremental as it outlines existing considerations without new methods or data.
The paper addresses ethical concerns in machine learning for health care, focusing on how models can exacerbate health inequities, and proposes a social justice framework and recommendations for an ethical ML pipeline.
The use of machine learning (ML) in health care raises numerous ethical concerns, especially as models can amplify existing health inequities. Here, we outline ethical considerations for equitable ML in the advancement of health care. Specifically, we frame ethics of ML in health care 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 post-deployment considerations. We close by summarizing recommendations to address these challenges.