Accounting for Bias in Medical Data Helps Prevent AI From Amplifying Racial Disparity

A new study from the University of Michigan reveals that racial disparities in medical testing could be influencing the accuracy of AI models used in healthcare. Black patients are less likely to receive critical tests, which may lead to biased data and inaccurate predictions. The article discusses how researchers have developed a groundbreaking method to correct this bias, potentially improving the fairness and reliability of AI in diagnosing serious conditions.