FAT

Keyphrases

Publications

2019

Margaret Mitchell, Simone Wu, Andrew Zaldivar, Parker Barnes, Lucy Vasserman, Ben Hutchinson, Elena Spitzer, Inioluwa Deborah Raji, Timnit Gebru
Model Cards for Model Reporting. FAT (2019)
Ziad Obermeyer, Sendhil Mullainathan
Dissecting Racial Bias in an Algorithm that Guides Health Decisions for 70 Million People. FAT (2019)
Sampath Kannan, Aaron Roth, Juba Ziani
Downstream Effects of Affirmative Action. FAT (2019)
Meg Young, Luke Rodriguez, Emily Keller, Feiyang Sun, Boyang Sa, Jan Whittington, Bill Howe
Beyond Open vs. Closed: Balancing Individual Privacy and Public Accountability in Data Sharing. FAT (2019)
Abhijnan Chakraborty, Gourab K. Patro, Niloy Ganguly, Krishna P. Gummadi, Patrick Loiseau
Equality of Voice: Towards Fair Representation in Crowdsourced Top-K Recommendations. FAT (2019)
Sorelle A. Friedler, Carlos Scheidegger, Suresh Venkatasubramanian, Sonam Choudhary, Evan P. Hamilton, Derek Roth
A comparative study of fairness-enhancing interventions in machine learning. FAT (2019)
Hussein Mouzannar, Mesrob I. Ohannessian, Nathan Srebro
From Fair Decision Making To Social Equality. FAT (2019)
Smitha Milli, Ludwig Schmidt, Anca D. Dragan, Moritz Hardt
Model Reconstruction from Model Explanations. FAT (2019)
Berk Ustun, Alexander Spangher, Yang Liu
Actionable Recourse in Linear Classification. FAT (2019)
Ben Green, Yiling Chen
Disparate Interactions: An Algorithm-in-the-Loop Analysis of Fairness in Risk Assessments. FAT (2019)
David Madras, Elliot Creager, Toniann Pitassi, Richard S. Zemel
Fairness through Causal Awareness: Learning Causal Latent-Variable Models for Biased Data. FAT (2019)
Brenda Leong, Evan Selinger
Robot Eyes Wide Shut: Understanding Dishonest Anthropomorphism. FAT (2019)
Dallas Card, Michael Zhang, Noah A. Smith
Deep Weighted Averaging Classifiers. FAT (2019)
Nicole Immorlica, Katrina Ligett, Juba Ziani
Access to Population-Level Signaling as a Source of Inequality. FAT (2019)
Michael J. Kearns, Seth Neel, Aaron Roth, Zhiwei Steven Wu
An Empirical Study of Rich Subgroup Fairness for Machine Learning. FAT (2019)
Hoda Heidari, Michele Loi, Krishna P. Gummadi, Andreas Krause
A Moral Framework for Understanding Fair ML through Economic Models of Equality of Opportunity. FAT (2019)
Andrew D. Selbst, danah boyd, Sorelle A. Friedler, Suresh Venkatasubramanian, Janet Vertesi
Fairness and Abstraction in Sociotechnical Systems. FAT (2019)
Mahmoudreza Babaei, Abhijnan Chakraborty, Juhi Kulshrestha, Elissa M. Redmiles, Meeyoung Cha, Krishna P. Gummadi
Analyzing Biases in Perception of Truth in News Stories and Their Implications for Fact Checking. FAT (2019)
Brent D. Mittelstadt, Chris Russell, Sandra Wachter
Explaining Explanations in AI. FAT (2019)
Samir Passi, Solon Barocas
Problem Formulation and Fairness. FAT (2019)
Aws Albarghouthi, Samuel Vinitsky
Fairness-Aware Programming. FAT (2019)
Shan Jiang, John Martin, Christo Wilson
Who's the Guinea Pig?: Investigating Online A/B/n Tests in-the-Wild. FAT (2019)
Dimitrios Bountouridis, Jaron Harambam, Mykola Makhortykh, Mónica Marrero, Nava Tintarev, Claudia Hauff
SIREN: A Simulation Framework for Understanding the Effects of Recommender Systems in Online News Environments. FAT (2019)
Lily Hu, Nicole Immorlica, Jennifer Wortman Vaughan
The Disparate Effects of Strategic Manipulation. FAT (2019)
Ben Hutchinson, Margaret Mitchell
50 Years of Test (Un)fairness: Lessons for Machine Learning. FAT (2019)
Vivian Lai, Chenhao Tan
On Human Predictions with Explanations and Predictions of Machine Learning Models: A Case Study on Deception Detection. FAT (2019)
Chris Russell
Efficient Search for Diverse Coherent Explanations. FAT (2019)
Jake Goldenfein
The Profiling Potential of Computer Vision and the Challenge of Computational Empiricism. FAT (2019)
Maria De-Arteaga, Alexey Romanov, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Adam Tauman Kalai
Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting. FAT (2019)
Moshe Babaioff, Noam Nisan, Inbal Talgam-Cohen
Fair Allocation through Competitive Equilibrium from Generic Incomes. FAT (2019)
Hadi Elzayn, Shahin Jabbari, Christopher Jung, Michael J. Kearns, Seth Neel, Aaron Roth, Zachary Schutzman
Fair Algorithms for Learning in Allocation Problems. FAT (2019)
Stevie Chancellor, Michael L. Birnbaum, Eric D. Caine, Vincent M. B. Silenzio, Munmun De Choudhury
A Taxonomy of Ethical Tensions in Inferring Mental Health States from Social Media. FAT (2019)
Jiahao Chen, Nathan Kallus, Xiaojie Mao, Geoffry Svacha, Madeleine Udell
Fairness Under Unawareness: Assessing Disparity When Protected Class Is Unobserved. FAT (2019)
L. Elisa Celis, Sayash Kapoor, Farnood Salehi, Nisheeth K. Vishnoi
Controlling Polarization in Personalization: An Algorithmic Framework. FAT (2019)
Severin Engelmann, Mo Chen, Felix Fischer, Ching-yu Kao, Jens Grossklags
Clear Sanctions, Vague Rewards: How China's Social Credit System Currently Defines "Good" and "Bad" Behavior. FAT (2019)
Filipe Nunes Ribeiro, Koustuv Saha, Mahmoudreza Babaei, Lucas Henrique C. Lima, Johnnatan Messias, Fabrício Benevenuto, Oana Goga, Krishna P. Gummadi, Elissa M. Redmiles
On Microtargeting Socially Divisive Ads: A Case Study of Russia-Linked Ad Campaigns on Facebook. FAT (2019)
Smitha Milli, John Miller, Anca D. Dragan, Moritz Hardt
The Social Cost of Strategic Classification. FAT (2019)
Proceedings of the Conference on Fairness, Accountability, and Transparency, FAT* 2019, Atlanta, GA, USA, January 29-31, 2019 FAT (2019)
Sebastian Benthall, Bruce D. Haynes
Racial categories in machine learning. FAT (2019)
Bruce Glymour, Jonathan Herington
Measuring the Biases that Matter: The Ethical and Casual Foundations for Measures of Fairness in Algorithms. FAT (2019)
Ran Canetti, Aloni Cohen, Nishanth Dikkala, Govind Ramnarayan, Sarah Scheffler, Adam D. Smith
From Soft Classifiers to Hard Decisions: How fair can we be? FAT (2019)
L. Elisa Celis, Lingxiao Huang, Vijay Keswani, Nisheeth K. Vishnoi
Classification with Fairness Constraints: A Meta-Algorithm with Provable Guarantees. FAT (2019)

2018

volume 81, 2018

Conference on Fairness, Accountability and Transparency, FAT 2018, 23-24 February 2018, New York, NY, USA FAT 81 (2018)