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Artificial Intelligence is being used today to solve a myriad of problems. While there is significant promise that AI can help us address many healthcare issues, there is also concern that health inequities can be exacerbated. This article looks specifically at predictive models in regards to racial bias. Each phase of the model building process including raw data collection and processing, data labelling, and implementation of the model can be subject to racial bias. This article aims to explore some of the ways in which this occurs.