This article explains how bias in AI systems is contributing to the exacerbation of racial health disparities. There is a huge issue with the misrepresentation of our data sets, which could result in health systems that do not correctly identify nor treat illnesses in non-white patients. For example, skin-cancer detection algorithms trained on light-skinned individuals, and x-rays trained with gender imbalanced data. It calls for diversity not only within our data sets, but also diversity among the developers and funders of AI tools. High-quality data and diversity training is needed to eliminate biases within the healthcare system.