Fairness and Equity in AI for Societal Decision Making
Published in Encyclopedia of GIS, 2026
Overview
This invited chapter provides a comprehensive overview of fairness and equity considerations in AI systems used for societal decision-making, drawing from research in public health, urban planning, and transportation domains.
Status
In Press - Expected publication in 2026
Key Topics Covered
- Fairness definitions and metrics in high-stakes AI applications
- Sources of bias in data and models
- Auditing frameworks for AI systems
- Mitigation strategies across the modeling lifecycle
- Case studies in public health and urban computing
Significance
This work synthesizes insights from multiple research streams to provide practical guidance for researchers and practitioners working on AI systems that impact communities and policy decisions.
Venue
Encyclopedia of GIS - A comprehensive reference work in geographic information science Editors: Shekhar, Xiong, Zhou, and Xie
Recommended Citation
Abrar, S. M., & Frias-Martinez, V. (2026). Fairness and Equity in AI for Societal Decision Making. In Encyclopedia of GIS (Eds. Shekhar, Xiong, Zhou, and Xie). (In Press)
[Link to be available upon publication]
Recommended citation: Abrar, S. M., & Frias-Martinez, V. (2026). Fairness and Equity in AI for Societal Decision Making. In Encyclopedia of GIS (Eds. Shekhar, Xiong, Zhou, and Xie). (In Press)
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