Privacy, Bias, and Fairness in AI

This course examines how AI's use of large-scale data creates privacy concerns and how biases emerge throughout AI system lifecycles. You'll analyze real examples of biased AI outcomes and explore frameworks to measure and mitigate bias. Focus areas include fairness in algorithmic design and practical steps for responsible data handling across regulatory environments.