Abstract is missing.
- Preface1-2 [doi]
- Keynote 1Latanya Sweeney. 3 [doi]
- Keynote 2Deborah Hellman. 4 [doi]
- Potential for Discrimination in Online Targeted AdvertisingTill Speicher, Muhammad Ali, Giridhari Venkatadri, Filipe Nunes Ribeiro, George Arvanitakis, FabrÃcio Benevenuto, Krishna P. Gummadi, Patrick Loiseau, Alan Mislove. 5-19 [doi]
- Discrimination in Online Personalization: A Multidisciplinary InquiryAmit Datta, Anupam Datta, Jael Makagon, Deirdre K. Mulligan, Michael Carl Tschantz. 20-34 [doi]
- Privacy for All: Ensuring Fair and Equitable Privacy ProtectionsMichael D. Ekstrand, Rezvan Joshaghani, Hoda Mehrpouyan. 35-47 [doi]
- "Meaningful Information" and the Right to ExplanationAndrew Selbst, Julia Powles. 48 [doi]
- Interpretable Active LearningRichard L. Phillips, Kyu Hyun Chang, Sorelle A. Friedler. 49-61 [doi]
- Interventions over Predictions: Reframing the Ethical Debate for Actuarial Risk AssessmentChelsea Barabas, Madars Virza, Karthik Dinakar, Joichi Ito, Jonathan Zittrain. 62-76 [doi]
- Gender Shades: Intersectional Accuracy Disparities in Commercial Gender ClassificationJoy Buolamwini, Timnit Gebru. 77-91 [doi]
- Analyze, Detect and Remove Gender Stereotyping from Bollywood MoviesNishtha Madaan, Sameep Mehta, Taneea S. Agrawaal, Vrinda Malhotra, Aditi Aggarwal, Yatin Gupta, Mayank Saxena. 92-105 [doi]
- Mixed Messages? The Limits of Automated Social Media Content AnalysisNatasha Duarte, Emma Llanso, Anna Loup. 106 [doi]
- The cost of fairness in binary classificationAditya Krishna Menon, Robert C. Williamson. 107-118 [doi]
- Decoupled Classifiers for Group-Fair and Efficient Machine LearningCynthia Dwork, Nicole Immorlica, Adam Tauman Kalai, Mark D. M. Leiserson. 119-133 [doi]
- A case study of algorithm-assisted decision making in child maltreatment hotline screening decisionsAlexandra Chouldechova, Diana Benavides Prado, Oleksandr Fialko, Rhema Vaithianathan. 134-148 [doi]
- Fairness in Machine Learning: Lessons from Political PhilosophyReuben Binns. 149-159 [doi]
- Runaway Feedback Loops in Predictive PolicingDanielle Ensign, Sorelle A. Friedler, Scott Neville, Carlos Scheidegger, Suresh Venkatasubramanian. 160-171 [doi]
- All The Cool Kids, How Do They Fit In?: Popularity and Demographic Biases in Recommender Evaluation and EffectivenessMichael D. Ekstrand, Mucun Tian, Ion Madrazo Azpiazu, Jennifer D. Ekstrand, Oghenemaro Anuyah, David McNeill, Maria Soledad Pera. 172-186 [doi]
- Recommendation IndependenceToshihiro Kamishima, Shotaro Akaho, Hideki Asoh, Jun Sakuma. 187-201 [doi]
- Balanced Neighborhoods for Multi-sided Fairness in RecommendationRobin Burke, Nasim Sonboli, Aldo Ordonez-Gauger. 202-214 [doi]