In a new publication in PLOS Digital Health, experts in bioethics and law call for immediate standardization of methods for collection of race and ethnicity data, and for developers to warranty race and ethnicity data quality in medical AI systems. The research synthesizes concerns about why patient race data in electronic health records may not be accurate, identifies best practices for healthcare systems and medical AI researchers to improve data accuracy, and provides a new template for medical AI developers to transparently warrant the quality of their race and ethnicity data. Authors include Alexandra Tsalidis, MBE, Lakshmi Bharadwaj, MBE, and Francis Shen, JD, PhD. The research was supported by the NIH Bridge to Artificial Intelligence (Bridge2AI) program, and by an NIH BRAIN Neuroethics grant (R01MH134144).