Week Date Lecture Topics Location Assigned Due (1:00 pm on the given day)
1 Apr 1
Apr 3 		Introduction [slides]
Operationalized Fairness Criteria [slides, slides-a ] 		380-380X HW 1 release (Apr 3)
2 Apr 8
Apr 10		 NO CLASS
Calibration & Fairness [slides-a], Learning Group "Fair Models" [slides-a] 		380-380X Exploratory project release (Apr 10)
3 Apr 15
Apr 17		 Guest Lecture by Dan Ho
Fair Models via Constrained Optimization [slides-a], Individual Fairness [slides-a] 		380-380X
HW 1 (Apr 17)
4 Apr 22
Apr 24		 Fairness Socio-Technical Analysis
Bias in NLP [slides-a], Fairness and Causality [slides-a] 		380-380X HW 2 release (Apr 24)
Socio-tech summary (Apr 24)
5 Apr 29
May 1		 Guest Lecture by Bo Li
Explainability and Transparency, Feature Attribution and LIME Shapley Values & SHAP, 		380-380X Exploratory project (Apr 29)
Final project proposal (May 3)
6 May 6
May 8		 Saliency Maps, Exemplar-Based Explanations, Concept-Based Explanations,
Explainability Socio-Technical Analysis		 380-380X
7 May 13
May 15 		Counterfactual Explanations, Privacy and ML
Differential Privacy 		380-380X
HW 3 release (May 15) HW 2 (May 13)
Socio-tech summary (May 15)
8 May 20
May 22		 Differential Privacy -- continued
Learning with Differential privacy, Federated Learning 		380-380X Final project milestone (May 22)
9 May 27
May 29		 Memorial Day -- No class
Large Language Models and the Ethics of AI: Impact, Gaps and Opportunities
HW 3 (May 29)
10 June 3
June 5		 Privacy Socio-Technical Analysis
Closing Discussion -- Trust in AI 		380-380X Socio-tech summary (June 5)
Poster session on June 6, 2:00 pm - 4:00 pm. AT&T Patio, Gates Building.
Project final report due June 10, 1:00 pm.