intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models
stratified across subpopulations have revealed inequalities in how patients are diagnosed,
treated and billed. In this Perspective, we outline fairness in machine learning through the
lens of healthcare, and discuss how algorithmic biases (in data acquisition, genetic variation
and intra-observer labelling variability, in particular) arise in clinical workflows and the …