Model Privacy Risks (Membership Inference)

This lesson introduces membership inference attacks and other privacy risks that can emerge when AI systems unintentionally reveal information about their training data. Learners explore how attackers analyze model outputs to determine whether specific records were used during training, why this creates privacy concerns, and the safeguards organizations use to reduce exposure. The lesson also introduces privacy-preserving techniques such as differential privacy and responsible model design practices that help protect sensitive information.