Like many sectors, health care has benefited from the rising use of artificial intelligence, but it has sometimes happened at the expense of minority patients. In fact, health care AI might amplify and worsen disparities (racial/ethnic and others) because the data sources that "teach" AI are not representative and/or are based on data from current unequal care, says University of Michigan law professor Nicholson Price, who also is a member of U-M's Institute for Healthcare Policy & Innovation. In a recent Science article, Price and colleagues Ana Bracic of Michigan State University and Shawneequa Callier of George Washington University say these disparities are happening despite efforts in medicine by physicians and health systems trying strategies focused on diverse workforce recruitment or implicit bias training. What is an example of anti-minority culture? There are depressingly many examples of cultures that include deeply embedded biases against minoritized populations (that is, populations constructed as minorities by a dominant group).