Recent Developments in Research on Fairness

Program

Summer Cluster: Fairness

Location

Calvin Lab auditorium

Date

Monday, July 8 – Wednesday, July 10, 2019

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9 – 9:25 a.m.

Coffee and Check-In

9:25 – 9:30 a.m.

Opening Remarks

9:30 – 10:15 a.m.

What is Your Data Worth? Equitable Data Valuation in Machine Learning

James Zou (Stanford University)

10:15 – 11 a.m.

What It Takes to Control Societal Bias in Natural Language Processing

Kai-Wei Chang (UCLA)

11 – 11:30 a.m.

Break

11:30 a.m. – 12 p.m.

Flexibly Fair Representation Learning by Disentanglement

Rich Zemel (University of Toronto)

12 – 1:30 p.m.

Lunch

1:30 – 2:15 p.m.

Bridging AI and HCI: Incorporating Human Values into the Development of AI Technologies

Haiyi Zhu (University of Minnesota)

2:15 – 3 p.m.

Procedural Justice in Algorithmic Fairness: Transparency, Control and Participation Perspectives

Min Kyung Lee (Carnegie Mellon University)

3 – 3:30 p.m.

Break

3:45 – 4:15 p.m.

Discrimination Through Optimization: How Facebook's Ad Delivery Can Lead to Skewed Outcomes

Alan Mislove (Northeastern University)

4:15 – 5 p.m.

Moderating Discrimination in Online Ad Auctions

Elisa Celis (Yale University)

8:30 – 9 a.m.

Coffee and Check-In

9 – 9:45 a.m.

A Multi-Group Perspective on Fairness

Guy Rothblum (Weizmann Institute)

9:45 – 10:30 a.m.

Evidence-Based Rankings

Michael Kim (Stanford University)

10:30 – 11 a.m.

Break

11 – 11:45 a.m.

The Measure and Mismeasure of Fairness

Sharad Goel (Stanford University)

11:45 a.m. – 12:30 p.m.

Disentangling Influence: Using Disentangled Representations to Audit Model Predictions

Charlie Marx (Haverford College)

12:30 – 2 p.m.

Lunch

2 – 2:45 p.m.

Representation via Representations: Improving Generalization to Unseen Populations

Frances Ding (Harvard University)

2:45 – 3:30 p.m.

The Social Cost of Strategic Classification

John Miller (UC Berkeley)

3:30 – 4 p.m.

Break

4 – 4:45 p.m.

Panel Discussion

4:45 – 6 p.m.

Reception

8:30 – 9 a.m.

Coffee and Check-In

9 – 9:45 a.m.

Biased Programmers? Or Biased Data? A Field Experiment about Algorithmic Bias

Bo Cowgill (Columbia Business School)

9:45 – 10:30 a.m.

Welfare-Maximizing Decision Rules: An Application to Consumer Credit

Joshua Blumenstock (UC Berkeley)

10:30 – 11 a.m.

Break

11 – 11:45 a.m.

Eliciting and Enforcing Subjective Individual Fairness

Aaron Roth (University of Pennsylvania)

11:45 a.m. – 12:30 p.m.

Individual Fairness in Hindsight

Swati Gupta (Georgia Tech)

12:30 – 2 p.m.

Lunch

2 – 2:45 p.m.

(Improving) Muddled Information

Alex Frankel (Chicago Booth)

2:45 – 3:30 p.m.

Equal Opportunity in Online Classification with Partial Feedback

Yahav Bechavod (Hebrew University)

3:30 – 4 p.m.

Break

4 – 4:45 p.m.

Journalist-in-Residence Talk: The Limits of Fairness

Konstantin Kakaes (Simons Institute)