Position: Scarce Resource Allocations That Rely On Machine Learning Should Be Randomized

Shomik Jain; Kathleen Creel; Ashia Camage Wilson

ICML 2024poster4 citations

Position: Scarce Resource Allocations That Rely On Machine Learning Should Be Randomized

Shomik Jain, Kathleen Creel, Ashia Camage Wilson

Abstract

Contrary to traditional deterministic notions of algorithmic fairness, this paper argues that fairly allocating scarce resources using machine learning often requires randomness. We address why, when, and how to randomize by offering a set of stochastic procedures that more adequately account for all of the claims individuals have to allocations of social goods or opportunities and effectively balances their interests.

BibTeX

@inproceedings{
jain2024position,
title={Position: Scarce Resource Allocations That Rely On Machine Learning Should Be Randomized},
author={Shomik Jain and Kathleen Creel and Ashia Camage Wilson},
booktitle={Forty-first International Conference on Machine Learning},
year={2024},
url={https://openreview.net/forum?id=44qxX6Ty6F}
}