Achieving Fairness through Adversarial Learning: an Application to Recidivism Prediction
Christina Wadsworth, Francesca Vera and Chris Piech

Actionable Recourse in Linear Classification
Alexander Spangler and Berk Ustun

Axiomatic Characterization of Data-Driven Influence Measures for Classification
Jakub Sliwinski, Martin Strobel and Yair Zick

Blind Justice: Fairness with Encrypted Sensitive Attributes
Niki Kilbertus, Adria Gascon, Matt Kusner, Michael Veale, Krishna Gummadi and Adrian Weller

Darling or Babygirl? Investigating Stylistic Bias in Sentiment Analysis
Judy Hanwen Shen, Lauren Fratamico, Iyad Rahwan and Alexander M. Rush

Datasheets for Datasets
Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé III and Kate Crawford

Debiasing Representations by Removing Unwanted Variation Due to Protected Attributes
Amanda Bower, Laura Niss, Yuekai Sun and Alexander Vargo

Does Removing Stereotype Priming Remove Bias? A Pilot Human-Robot Interaction Study
Tobi Ogunyale, De'Aira Bryant and Ayanna Howard

Enhancing Human Decision Making via Assignment Optimization
Isabel Valera, Adish Singla and Manuel Gomez-Rodriguez

Equal Protection Under the Algorithm: A Legal-Inspired Framework for Identifying Discrimination in Machine Learning
Sucheta Soundarajan and Daniel Clausen

"Fair" Risk Assessments: A Precarious Approach for Criminal Justice Reform
Ben Green

Fairness Through Computationally-Bounded Awareness
Michael P. Kim, Omer Reingold and Guy Rothblum

Game-theoretic Interpretability for Temporal Modeling
Guang-He Lee, David Alvarez-Melis and Tommi Jaakkola

Gradient Reversal Against Discrimination
Edward Raff and Jared Sylvester

Group Fairness Under Composition
Christina Ilvento and Cynthia Dwork

Individual Fairness Under Composition
Christina Ilvento and Cynthia Dwork

InclusiveFaceNet: Improving Face Attribute Detection with Race and Gender Diversity
Hee Jung Ryu, Margaret Mitchell and Hartwig Adam

Learning under selective labels in the presence of expert consistency
Maria De-Arteaga, Artur Dubrawski and Alexandra Chouldechova

Modelling Mistrust in End-of-Life Care
Willie Boag, Harini Suresh, Leo Celi, Peter Szolovits and Marzyeh Ghassemi

On Formalizing Fairness in Prediction with ML
Pratik Gajane and Mykola Pechenizkiy

Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness
Seth Neel, Michael Kearns, Aaron Roth and Zhiwei Steven Wu

Probably Approximately Metric-Fair Learning
Gal Yona and Guy Rothblum

A Broader View on Bias in Automated Decision-Making: Reflecting on Epistemology and Dynamics
Roel Dobbe, Sarah Dean, Thomas Gilbert and Nitin Kohli

Training Fairness-Constrained Classifiers To Generalize
Andrew Cotter, Maya Gupta, Heinrich Jiang, Nathan Srebro, Karthik Sridharan, Serena Wang, Blake Woodworth and Seungil You

Turing Box: An Experimental Platform for the Evaluation of AI Systems
Ziv Epstein, Blakeley H. Payne, Judy Hanwen Shen, Casey Jisoo Hong, Bjarke Felbo, Abhimanyu Dubey, Matthew Groh, Nick Obradovich, Manuel Cebrian and Iyad Rahwan

Using image fairness representations in diversity-based re-ranking for recommendations
Chen Karako and Putra Manggala

Welfare and Distributional Impacts of Fair Classification
Lily Hu and Yiling Chen

Women also Snowboard: Overcoming Bias in Captioning Models
Lisa Anne Hendricks, Anna Rohrbach, Kaylee Burns, Trevor Darrell and Kate Saenko