ISSP 2185 FATE: FAIRNESS, ACCOUNTABILITY, TRANSPARENCY, AND ETHICS IN AI

Data-driven models are increasingly used in many domains to assist in human decision-making with a significant impact on people's lives -- from hiring and promotion, college admissions, and judicial decisions to business or public services delivery. Industry, government, and nonprofit sections recognize data and AI ethics as essential capabilities for future Data Scientists. Will offer students the knowledge and tools to apply ethics to data and AI applications. Focuses on both concepts and practice to understand ethical challenges in data science and data-driven decision-making. Introduces the core concepts of fairness and interpretability mechanisms, and analytical and technical tools to mitigate emerging problems in the real world.

Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SNC Basis
Minimum Credits: 3
Maximum Credits: 3