Volume 81: Conference on Fairness, Accountability and Transparency, 23-24 February 2018, New York, NY, USA

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Editors: Sorelle A. Friedler, Christo Wilson

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Contents:

Preface

Preface

Sorelle A. Friedler, Christo Wilson ; PMLR 81:1-2

Keynotes

Keynote 1

Latanya Sweeney ; PMLR 81:3-3

Keynote 2

Deborah Hellman ; PMLR 81:4-4

Contributed Papers

Potential for Discrimination in Online Targeted Advertising

Till Speicher, Muhammad Ali, Giridhari Venkatadri, Filipe Nunes Ribeiro, George Arvanitakis, Fabrício Benevenuto, Krishna P. Gummadi, Patrick Loiseau, Alan Mislove ; PMLR 81:5-19

Discrimination in Online Advertising: A Multidisciplinary Inquiry

Amit Datta, Anupam Datta, Jael Makagon, Deirdre K. Mulligan, Michael Carl Tschantz ; PMLR 81:20-34

Privacy for All: Ensuring Fair and Equitable Privacy Protections

Michael D. Ekstrand, Rezvan Joshaghani, Hoda Mehrpouyan ; PMLR 81:35-47

“Meaningful Information” and the Right to Explanation

Andrew Selbst, Julia Powles ; PMLR 81:48-48

Interpretable Active Learning

Richard Phillips, Kyu Hyun Chang, Sorelle A. Friedler ; PMLR 81:49-61

Interventions over Predictions: Reframing the Ethical Debate for Actuarial Risk Assessment

Chelsea Barabas, Madars Virza, Karthik Dinakar, Joichi Ito, Jonathan Zittrain ; PMLR 81:62-76

Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification

Joy Buolamwini, Timnit Gebru ; PMLR 81:77-91

Analyze, Detect and Remove Gender Stereotyping from Bollywood Movies

Nishtha Madaan, Sameep Mehta, Taneea Agrawaal, Vrinda Malhotra, Aditi Aggarwal, Yatin Gupta, Mayank Saxena ; PMLR 81:92-105

Mixed Messages? The Limits of Automated Social Media Content Analysis

Natasha Duarte, Emma Llanso, Anna Loup ; PMLR 81:106-106

The cost of fairness in binary classification

Aditya Krishna Menon, Robert C Williamson ; PMLR 81:107-118

Decoupled Classifiers for Group-Fair and Efficient Machine Learning

Cynthia Dwork, Nicole Immorlica, Adam Tauman Kalai, Mark DM Leiserson ; PMLR 81:119-133

A case study of algorithm-assisted decision making in child maltreatment hotline screening decisions

Alexandra Chouldechova, Diana Benavides-Prado, Oleksandr Fialko, Rhema Vaithianathan ; PMLR 81:134-148

Fairness in Machine Learning: Lessons from Political Philosophy

Reuben Binns ; PMLR 81:149-159

Runaway Feedback Loops in Predictive Policing

Danielle Ensign, Sorelle A. Friedler, Scott Neville, Carlos Scheidegger, Suresh Venkatasubramanian ; PMLR 81:160-171

All The Cool Kids, How Do They Fit In?: Popularity and Demographic Biases in Recommender Evaluation and Effectiveness

Michael D. Ekstrand, Mucun Tian, Ion Madrazo Azpiazu, Jennifer D. Ekstrand, Oghenemaro Anuyah, David McNeill, Maria Soledad Pera ; PMLR 81:172-186

Recommendation Independence

Toshihiro Kamishima, Shotaro Akaho, Hideki Asoh, Jun Sakuma ; PMLR 81:187-201

Balanced Neighborhoods for Multi-sided Fairness in Recommendation

Robin Burke, Nasim Sonboli, Aldo Ordonez-Gauger ; PMLR 81:202-214

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