Causal Bayesian Networks: A flexible tool to enable fairer machine learning

Decisions based on machine learning (ML) are potentially advantageous over human decisions, as they do not suffer from the same subjectivity, and can be more accurate and easier to analyse. At the same time, data used to train ML systems often contain human and societal biases that can lead to harmful decisions: extensive evidence in areas such as hiring, criminal justice, surveillance, and healthcare suggests that ML decision systems can treat individuals unfavorably (unfairly) on the basis of characteristics such as race, gender, disabilities, and sexual orientation – referred to as sensitiv

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