Medical AI privacy risks fall hardest on minorities and outliers

A study published in Nature on August 4, 2026 shows that privacy risks from medical AI tools are distributed unequally. Membership-inference attacks can reveal whether a specific person's medical data was used to train an AI model. People who differ from the majority — minorities and patients with rare conditions — face the highest vulnerability to such attacks.