Pushing the Limits of Fairness in Algorithmic Decision-Making

Nisarg Shah

IJCAI 2023poster1 citations

Pushing the Limits of Fairness in Algorithmic Decision-Making

Abstract

Designing provably fair decision-making algorithms is a task of growing interest and importance. In this article, I argue that preference-based notions of fairness proposed decades ago in the economics literature and subsequently explored in-depth within computer science (specifically, within the field of computational social choice) are aptly suited for a wide range of modern decision-making systems, from conference peer review to recommender systems to participatory budgeting.

EC: Algorithmic Fairness

BibTeX

@inproceedings{ijcai2023p806,
  title     = {Pushing the Limits of Fairness in Algorithmic Decision-Making},
  author    = {Shah, Nisarg},
  booktitle = {Proceedings of the Thirty-Second International Joint Conference on
               Artificial Intelligence, {IJCAI-23}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Edith Elkind},
  pages     = {7051--7056},
  year      = {2023},
  month     = {8},
  note      = {Early Career},
  doi       = {10.24963/ijcai.2023/806},
  url       = {https://doi.org/10.24963/ijcai.2023/806},
}