As artificial intelligence becomes increasingly integrated into decision-making, understanding its ethical implications is more important than ever.
Join our course on Data, Ethics & AI, scheduled for October 21st, 2026. This online, day-long training goes beyond theory where participants will examine real AI use cases to identify where bias can enter a system, learn to distinguish privacy risk from ethical risk, and apply a practical ethical-review checklist to a real dataset or tool. Through a structured debate on the trade-off between speed and safeguards, participants will leave with one concrete step they can apply to a real risk in their own work.
Learning Objectives
By the end of this course, participants will be able to:
- Analyze a real or hypothetical AI use case to surface where bias could enter the pipeline (data, model, deployment)
- Differentiate between privacy risk and ethical risk in a data workflow, using concrete examples
- Apply an ethical-review checklist to a dataset or tool and identify specific gaps
- Debate the efficiency-vs-safeguard trade-off in a structured group exercise, taking and defending a position
- Propose one practical mitigation for a bias or privacy risk identified during the session
Faculty
Shanze Fatima Rauf
PhD Candidate & Teaching Assistant (Department of Political Science)
Shanze Fatima Rauf is a PhD candidate in the Department of Political Science at the University of Pennsylvania, where she has served as a teaching assistant for courses including Global Development: Data, Politics and Practice and International Political Economy. Before joining Penn, she worked as a Research Associate on projects examining women’s political participation and mobility in Pakistan, including Metaketa V and DFID’s A4EA research programme. She holds a Master’s degree in Politics from New York University, where she was a recipient of the Fulbright Master’s Scholarship and the GSAS Tuition Scholarship.
Deadlines
- Early Bird: 30 September 2026
- Regular: 14 October 2026