A much-needed movement is underway in the statistical sciences to incorporate diversity, equity, and inclusion (DEI) into curricula. One can imagine many different approaches to achieve this goal; in this talk we will discuss using an ethics course as a gateway to DEI discussions in biostatistics. Specifically, we first describe a graduate-level course that examines ethical challenges related to research design, data collection, data integrity/stewardship, data analysis and interpretation, and data reporting in the conduct of public health and biomedical research. Then we reflect on how this discussion-based course creates a natural pathway into difficult DEI topics such as challenges in measuring gender and race and considerations for inclusion of race in multivariable models. We find that by entering these discussions through a statistical lens ( i.e., by starting with the theory and numbers that students are more comfortable with) students at multiple levels (MS, PhD) are able to reflect on the DEI implications of statistical decision-making. Mixing the familiar with the at-times uncomfortable enables robust discussions and allows for self-reflection on students’ own biases.