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Conference proceeding
Balanced Ranking with Diversity Constraints
PROCEEDINGS OF THE TWENTY-EIGHTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, pp 6035-6042
01 Jan 2019
Abstract
Many set selection and ranking algorithms have recently been enhanced with diversity constraints that aim to explicitly increase representation of historically disadvantaged populations, or to improve the overall representativeness of the selected set. An unintended consequence of these constraints, however, is reduced in-group fairness: the selected candidates from a given group may not be the best ones, and this unfairness may not be well-balanced across groups. In this paper we study this phenomenon using datasets that comprise multiple sensitive attributes. We then introduce additional constraints, aimed at balancing the in-group fairness across groups, and formalize the induced optimization problems as integer linear programs. Using these programs, we conduct an experimental evaluation with real datasets, and quantify the feasible trade-offs between balance and overall performance in the presence of diversity constraints.
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Details
- Title
- Balanced Ranking with Diversity Constraints
- Creators
- Ke Yang - New York UniversityVasilis Gkatzelis - Drexel UniversityJulia Stoyanovich - New York University
- Contributors
- S Kraus (Editor)
- Publication Details
- PROCEEDINGS OF THE TWENTY-EIGHTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, pp 6035-6042
- Conference
- 28th INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 28th (Macao, China, 10 Aug 2019–16 Aug 2019)
- Publisher
- Ijcai-Int Joint Conf Artif Intell
- Number of pages
- 8
- Grant note
- 1926250 / Div Of Information & Intelligent Systems; Direct For Computer & Info Scie & Enginr; National Science Foundation (NSF); NSF - Directorate for Computer & Information Science & Engineering (CISE) 1755955 / Direct For Computer & Info Scie & Enginr; Division of Computing and Communication Foundations; National Science Foundation (NSF); NSF - Directorate for Computer & Information Science & Engineering (CISE) 1926250; 1916647; 1755955 / NSF; National Science Foundation (NSF) 1916647 / Div Of Information & Intelligent Systems; Direct For Computer & Info Scie & Enginr; National Science Foundation (NSF); NSF - Directorate for Computer & Information Science & Engineering (CISE)
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Computer Science (Computing)
- Web of Science ID
- WOS:000761735106025
- Other Identifier
- 991021868092704721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Interdisciplinary Applications
- Computer Science, Theory & Methods