Thomas, Oliver, Zilka, Miri, Weller, Adrian and Quadrianto, Novi (2021) An algorithmic framework for positive action. ACM conference on Equity and Access in Algorithms, Mechanisms, and Optimization, Virtual, October 5-9, 2021. Published in: Proceedings of Equity and Access in Algorithms, Mechanisms, and Optimization. a18 1-13. Association for Computing Machinery ISBN 9781450385534

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Abstract

Positive action is defined within anti-discrimination legislation as voluntary, legal action taken to address an imbalance of opportunity affecting individuals belonging to under-represented groups. Within this theme, we propose a novel algorithmic fairness framework to advance equal representation while respecting anti-discrimination legislation and equal-treatment rights. We use a counterfactual fairness approach to assign one of three outcomes to each candidate: accept; reject; or flagged as a positive action candidate.

Item Type:	Conference Proceedings
Keywords:	Algorithmic Fairness, Auditing, Causal Inference
Schools and Departments:	School of Engineering and Informatics > Informatics
SWORD Depositor:	Mx Elements Account
Depositing User:	Mx Elements Account
Date Deposited:	13 Sep 2021 08:19
Last Modified:	01 Mar 2022 13:19
URI:	http://sro.sussex.ac.uk/id/eprint/101653

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