The Ethical Algorithm: The Science of Socially Aware Algorithm Design 

Michael Kearns (University of Pennsylvania)

Unconscious Selection: Data-Driven Social Evolution, Disparity, and Intervention 

Reilly Raab (University of California, Santa Cruz)

Breaking Fair Classification with Optimal Poisoning Attacks

Changhun Jo (University of Wisconsin - Madison)

A Superquantile Approach to Federated Learning with Heterogeneous Devices

Krishna Pillutla (University of Washington)

Fairness Evaluation in Pre-trained Multimodal Representations

Jialu Wang (University of California, Santa Cruz)

Sequential Fair Allocation: Achieving the Optimal Envy-Efficiency Tradeoff Curve

Christina Lee Yu (Cornell University)

Improving Fairness via Federated Learning

Yuchen Zeng (University of Wisconsin-Madison)

Trustworthy AI: Fairness in Machine Learning

Golnoosh Farnadi (HEC Montréal)

Rethinking Dataset Construction: The Role of Generative Modeling and Annotator Perspectives

Swabha Swayamdipta (Allen Institute for AI)

Social Bias Meets Data Bias: Towards Evaluating and Correcting for the Impacts of Biased Training Data 

Parinaz Naghizadeh (Ohio State University)

Toward a Unified Approach for Explainable AI and Fairness Through Causal Reasoning

Babak Salimi (University of California, San Diego)

A Formal Notion of Coverage for Explainable AI Methods

Daniel Paul Pena (University of California, Santa Cruz)

Trustworthy Machine Learning in Complex Environments

Furong Huang (University of Maryland)