Humans tend towards bias, but are our algorithms objective? Today I discuss fairness and bias in machine learning for healthcare with Professor Maryzeh Ghassemi of the University of Toronto. We delve into the ways in which bias pops up in the data that are used to train computational models, the particular dangers of systemic inequalities in healthcare being perpetuated by algorithms, and some of the steps needed to combat these deeply rooted issues.

Check out the glossary of terms, definitions, and resources (and get a sneak peak of the future conversations lined up!) here: bit.ly/datapulse-glossary