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ORCIDEAAMO 2022: Arlington, VA, USA
- Equity and Access in Algorithms, Mechanisms, and Optimization, EAAMO 2022, Arlington, VA, USA, October 6-9, 2022. ACM 2022, ISBN 978-1-4503-9477-2
- Mona Sloane, Emanuel Moss, Olaitan Awomolo, Laura Forlano:
Participation Is not a Design Fix for Machine Learning. 1:1-1:6 - Alessandro Fabris
, Stefano Messina, Gianmaria Silvello, Gian Antonio Susto:
Tackling Documentation Debt: A Survey on Algorithmic Fairness Datasets. 2:1-2:13 - Sean Current, Yuntian He, Saket Gurukar, Srinivasan Parthasarathy:
FairEGM: Fair Link Prediction and Recommendation via Emulated Graph Modification. 3:1-3:14 - Vyoma Raman, Catherine Vera, Charles J. Manna:
Bias, Consistency, and Partisanship in U.S. Asylum Cases: A Machine Learning Analysis of Extraneous Factors in Immigration Court Decisions. 4:1-4:14 - Shubham Singh, Bhuvni Shah, Chris Kanich, Ian A. Kash:
Fair Decision-Making for Food Inspections. 5:1-5:11 - Abeba Birhane, William Isaac, Vinodkumar Prabhakaran, Mark Diaz, Madeleine Clare Elish, Iason Gabriel, Shakir Mohamed:
Power to the People? Opportunities and Challenges for Participatory AI. 6:1-6:8 - Niclas Boehmer, Robert Bredereck, Piotr Faliszewski, Rolf Niedermeier:
A Quantitative and Qualitative Analysis of the Robustness of (Real-World) Election Winners. 7:1-7:10 - Zhanzhan Zhao, Dana Randall:
A Heterogeneous Schelling Model for Wealth Disparity and its Effect on Segregation. 8:1-8:10 - Chiara Ullstein, Severin Engelmann, Orestis Papakyriakopoulos, Michel Hohendanner, Jens Grossklags:
AI-Competent Individuals and Laypeople Tend to Oppose Facial Analysis AI. 9:1-9:12 - Lodewijk L. Gelauff, Ashish Goel:
Opinion Change or Differential Turnout: Austin's Budget Feedback Exercise and the Police Department. 10:1-10:19 - Benjamin Fish, Luke Stark:
It's Not Fairness, and It's Not Fair: The Failure of Distributional Equality and the Promise of Relational Equality in Complete-Information Hiring Games. 11:1-11:15 - Florian Evéquoz, Johan Rochel, Vijay Keswani, L. Elisa Celis:
Diverse Representation via Computational Participatory Elections - Lessons from a Case Study. 12:1-12:11 - Yongsu Ahn, Eliana Beigel, Noah Braun, Collin Griffin, Sera Linardi, Blair Mickles, Emmaline Rial:
Improving Citizen-initiated Police Reform Efforts through Interactive Design: A Case Study in Allegheny County. 13:1-13:10 - Harsh Nisar, Deepak Gupta, Pankaj Kumar, Srinivasa Rao Murapaka, A. V. Rajesh, Alka Upadhyaya:
Algorithmic Rural Road Planning in India: Constrained Capacities and Choices in Public Sector. 14:1-14:11 - Zhanzhan Zhao, Cyrus Hettle, Swati Gupta, Jonathan Christopher Mattingly, Dana Randall, Gregory Joseph Herschlag:
Mathematically Quantifying Non-responsiveness of the 2021 Georgia Congressional Districting Plan. 15:1-15:11 - Jiyoo Chang, Christine Custis:
Understanding Implementation Challenges in Machine Learning Documentation. 16:1-16:8 - Kenya S. Andrews, Mesrob I. Ohannessian, Tanya Y. Berger-Wolf:
Modeling Access Differences to Reduce Disparity in Resource Allocation. 17:1-17:11 - Falaah Arif Khan, Eleni Manis, Julia Stoyanovich:
Towards Substantive Conceptions of Algorithmic Fairness: Normative Guidance from Equal Opportunity Doctrines. 18:1-18:10 - Jeffrey Brown, Tina M. Park, Jiyoo Chang, McKane Andrus, Alice Xiang, Christine Custis:
Attrition of Workers with Minoritized Identities on AI Teams. 19:1-19:9 - Thomas Kleine Buening, Meirav Segal, Debabrota Basu, Anne-Marie George, Christos Dimitrakakis:
On Meritocracy in Optimal Set Selection. 20:1-20:14 - Nina Grgic-Hlaca, Gabriel Lima, Adrian Weller, Elissa M. Redmiles:
Dimensions of Diversity in Human Perceptions of Algorithmic Fairness. 21:1-21:12
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