期刊
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
卷 27, 期 12, 页码 2020-2023出版社
OXFORD UNIV PRESS
DOI: 10.1093/jamia/ocaa094
关键词
artificial intelligence; machine learning; bias; clinical decision support; health informatics
类别
资金
- Cambia Health Foundation Sojourns Scholar Leadership Program
Increasing recognition of biases in artificial intelligence (AI) algorithms has motivated the quest to build fair models, free of biases. However, building fair models may be only half the challenge. A seemingly fair model could involve, directly or indirectly, what we call latent biases. Just as latent errors are generally described as errors waiting to happen in complex systems, latent biases are biases waiting to happen. Here we describe 3 major challenges related to bias in Al algorithms and propose several ways of managing them. There is an urgent need to address latent biases before the widespread implementation of Al algorithms in clinical practice.
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