Ethical Machine Learning in Health Care
Chen, Irene Y., Pierson, Emma, Rose, Sherri, Joshi, Shalmali, Ferryman, Kadija, Ghassemi, Marzyeh
–arXiv.org Artificial Intelligence
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.
arXiv.org Artificial Intelligence
Sep-23-2020
- Country:
- Africa > Sub-Saharan Africa (0.04)
- Asia
- India (0.04)
- Middle East > Israel (0.04)
- Europe
- Denmark (0.04)
- France (0.04)
- United Kingdom > England
- Oxfordshire > Oxford (0.14)
- North America
- Canada > Ontario
- Toronto (0.14)
- United States
- California > Santa Clara County
- Stanford (0.04)
- District of Columbia > Washington (0.04)
- Massachusetts > Middlesex County
- Cambridge (0.14)
- New York
- Kings County > New York City (0.14)
- New York County > New York City (0.04)
- California > Santa Clara County
- Canada > Ontario
- Genre:
- Overview (0.93)
- Research Report
- Experimental Study (1.00)
- New Finding (1.00)
- Strength High (1.00)
- Industry:
- Government
- Health & Medicine
- Government Relations & Public Policy (1.00)
- Health Care Technology > Medical Record (0.94)
- Diagnostic Medicine > Imaging (0.93)
- Pharmaceuticals & Biotechnology (1.00)
- Public Health (1.00)
- Epidemiology (0.92)
- Therapeutic Area
- Cardiology/Vascular Diseases (1.00)
- Hematology (0.68)
- Immunology (0.67)
- Infections and Infectious Diseases (0.93)
- Obstetrics/Gynecology (1.00)
- Health Care Providers & Services (1.00)
- Consumer Health (1.00)
- Law > Civil Rights & Constitutional Law (1.00)
- Technology: