Week Date Lecture Topics Assigned Due (1:00 pm on the given day)
1 Mar 31
Apr 2 		Introduction [slides]
Operationalized Fairness Criteria [slides] 		HW 1 release (Apr 2)
2 Apr 7
Apr 9		 Calibration & Fairness, Learning Group Fair Models
Fair Models via Constrained Optimization, Individual Fairness 		Exploratory project release (Apr 9)
3 Apr 14
Apr 16		 NO CLASS
Guest Lecture by Bo Li 		HW 1 due (Apr 16)
4 Apr 21
Apr 23		 Guest Lecture by David Engstrom
Fairness Socio-Technical Analysis 		HW 2 release (Apr 25)
Socio-tech summary due (Apr 25)
5 Apr 28
Apr 30		 Bias in NLP , Fairness & Causality
Explainability & Transparency , Feature Attribution & LIME 		Exploratory project due (Apr 28)
Final project proposal due (May 2)
6 May 5
May 7		 Shapley Values & SHAP , Saliency Maps , Exemplar-Based Explanations
Explainability Socio-Technical Analysis
7 May 12
May 14 		Concept-Based Explanations , Counterfactual Explanations
Privacy & ML , Differential Privacy 		HW 3 release (May 14) HW 2 due (May 12)
Socio-tech summary due (May 14)
8 May 19
May 21		 Differential Privacy -- continued
Learning with Differential Privacy, Federated Learning 		Final project milestone (May 21)
9 May 26
May 28		 NO CLASS (Memorial Day)
Large Language Models and the Ethics of AI: Impact, Gaps and Opportunities
HW 3 due (May 28)
10 June 2
June 4		 Guest Lecture by Been Kim
Closing Discussion on Trust in AI
Poster session on June 3, 2:00 pm - 4:00 pm at AT&T Patio, Gates
Project final report due June 9, 1:00 pm (no late days)