Schedule
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Embedded Files
Tutorial
09:20 AM - 09:47 AM
A Brief Tutorial on Causality and Fair Decision Making
A Brief Tutorial on Causality and Fair Decision Making
Moritz Hardt
Q&A
09:47 AM - 09:55 AM
Questions: Tutorial, Moritz Hardt
Questions: Tutorial, Moritz Hardt
Invited Talk
09:55 AM - 10:25 AM
On Prediction, Action and Interference
On Prediction, Action and Interference
Ricardo Silva
Q&A
10:25 AM - 10:30 AM
Questions: Invited talk, Ricardo Silva
Questions: Invited talk, Ricardo Silva
Short break: Join us on Gathertown
Contributed Talks
10:40 AM - 10:50 AM
Contributed talk 1: The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective
Contributed talk 1: The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective
Naman Goel, Alfonso Amayuelas, Amit Deshpande, Amit Sharma
10:50 AM - 11:00 AM
Contributed talk 2: Foundations for Languages for Interpretability and Bias Detection
Contributed talk 2: Foundations for Languages for Interpretability and Bias Detection
Bernardo Subercaseaux, Jorge PĂ©rez, Pablo BarcelĂł
11:00 AM - 11:10 AM
Contributed talk 3: Fairness in Risk Assessment: Post-Processing to Achieve Counterfactual Equalized Odds
Contributed talk 3: Fairness in Risk Assessment: Post-Processing to Achieve Counterfactual Equalized Odds
Alan Mishler, Edward H Kennedy, Alexandra Chouldechova
Invited Talk
11:10 AM - 11:38 AM
Fairness through the lens of equality of opportunity and its connection to causality
Fairness through the lens of equality of opportunity and its connection to causality
Hoda Heidari
Q&A
11:38 AM - 11:45 AM
Questions: Invited talk, Hoda Heidari
Questions: Invited talk, Hoda Heidari
Short break
Discussions
11:55 AM - 12:55 PM
Virtual Breakout Session 1
Virtual Breakout Session 1
- Fairness in Health
- Discussion with Ricardo Silva
- Discussion with Hoda Heidari
01:00 PM - 02:00 PM
Poster Session 1
Poster Session 1
Long break
Invited Talk
04:00 PM - 04:30 PM
The Roles of Simplicity and Interpretability in Fairness Guarantees
The Roles of Simplicity and Interpretability in Fairness Guarantees
Jon Kleinberg
Q&A
04:30 PM - 04:40 PM
Questions: Invited Talk, Jon Kleinberg
Questions: Invited Talk, Jon Kleinberg
Contributed Talks
04:40 PM - 04:50 PM
Contributed talk 4: Counterfactual Learning of Fair Interventions
Contributed talk 4: Counterfactual Learning of Fair Interventions
Yuzi He, Keith Burghardt, Kristina Lerman
04:50 PM - 05:00 PM
Contributed talk 5: Fairness and Robustness in Invariant Learning:
Contributed talk 5: Fairness and Robustness in Invariant Learning:
A Case Study in Toxicity Classification
A Case Study in Toxicity Classification
Robert Adragna, Elliot Creager, David Madras, Richard Zemel
05:00 PM - 05:10 PM
Contributed talk 6: Group Fairness by Probabilistic Modeling with Latent Fair Decisions
Contributed talk 6: Group Fairness by Probabilistic Modeling with Latent Fair Decisions
YooJung Choi, Meihua Dang, Guy Van den Broeck
Short break
Invited Talk
05:15 PM - 05:40 PM
Does Causal Thinking About Discrimination Assume a Can Opener?
Does Causal Thinking About Discrimination Assume a Can Opener?
Lily Hu
Q&A
05:40 PM - 05:55 PM
Questions: Invited Talk, Lily Hu
Questions: Invited Talk, Lily Hu
Discussions
05:55 PM - 06:55 PM
Virtual Breakout Session 2
Virtual Breakout Session 2
- Counterfactual Fairness
- Discussion with Jon Kleinberg
- Discussion with Lily Hu
06:55 PM - 07:55 PM
Poster Session 2
Poster Session 2
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