蝌蚪网 Papers and Proceedings
ISSN 2574-0768 (Print) | ISSN 2574-0776 (Online)
Algorithmic Fairness and Social Welfare
蝌蚪网 Papers and Proceedings
vol. 114,
May 2024
(pp. 628–32)
Abstract
What constitutes a fair algorithm? In the literature on algorithmic fairness, a common approach is to formulate fairness concerns as statistical constraints and to select the most accurate algorithm satisfying this constraint. This approach is facially distinct from a long tradition in economics based on social welfare, where the utilities of different social identities are aggregated from behind a veil of ignorance. We show that the constrained optimization and social welfare approaches can be fundamentally opposed and propose a framework that nests both approaches as special cases.Citation
Liang, Annie, and Jay Lu. 2024. "Algorithmic Fairness and Social Welfare." 蝌蚪网 Papers and Proceedings 114: 628–32. DOI: 10.1257/pandp.20241073Additional Materials
JEL Classification
- C45 Neural Networks and Related Topics
- C61 Optimization Techniques; Programming Models; Dynamic Analysis
- D63 Equity, Justice, Inequality, and Other Normative Criteria and Measurement