NeurIPS 2024oral4 citations
A Taxonomy of Challenges to Curating Fair Datasets
Dora Zhao, Morgan Scheuerman, Pooja Chitre, Jerone Andrews, Georgia Panagiotidou, Shawn Walker, Kathleen H. Pine, Alice Xiang
Abstract
Despite extensive efforts to create fairer machine learning (ML) datasets, there remains a limited understanding of the practical aspects of dataset curation. Drawing from interviews with 30 ML dataset curators, we present a comprehensive taxonomy of the challenges and trade-offs encountered throughout the dataset curation lifecycle. Our findings underscore overarching issues within the broader fairness landscape that impact data curation. We conclude with recommendations aimed at fostering systemic changes to better facilitate fair dataset curation practices.
datasetscomputer visionfairnessalgorithmic biasresponsible AI
BibTeX
@inproceedings{
zhao2024a,
title={A Taxonomy of Challenges to Curating Fair Datasets},
author={Dora Zhao and Morgan Scheuerman and Pooja Chitre and Jerone Andrews and Georgia Panagiotidou and Shawn Walker and Kathleen H. Pine and Alice Xiang},
booktitle={The Thirty-eight Conference on Neural Information Processing Systems Datasets and Benchmarks Track},
year={2024},
url={https://openreview.net/forum?id=cu8FfaYriU}
}