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 |
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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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📧 Request an updateProject Name | Sussex Project Number | Funder | Funder Ref |
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BayesianGDPR - Bayesian Models and Algorithms for Fairness and Transparency | G2903 | EUROPEAN UNION | Unset |