As we have witnessed in recent years, there has been a lot of confusion around the use of race and ethnicity in medicine and medical algorithms. We are focusing on how race and ethnicity informs and biases precision medicine* diagnostics and therapeutics. We are also addressing how machine learning has the potential to both accentuate and reduce existing bias in these precision medicine tasks. At this year’s conference, we will provide expert-led discussions of how identity is used in care and how to best advance precision medicine for all populations. As we have done over the past several years, we will center on elevating the patient voice and building patient engagement.