An_Algorithmic_Framework_for_Positive_Action (3).pdf (2.48 MB)
An algorithmic framework for positive action
conference contribution
posted on 2023-06-10, 00:57 authored by Oliver ThomasOliver Thomas, Miri Zilka, Adrian Weller, Novi QuadriantoNovi QuadriantoPositive 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.
Funding
BayesianGDPR - Bayesian Models and Algorithms for Fairness and Transparency; G2903; EUROPEAN UNION
History
Publication status
- Published
File Version
- Accepted version
Journal
Proceedings of Equity and Access in Algorithms, Mechanisms, and OptimizationPublisher
Association for Computing MachineryExternal DOI
Page range
1-13Article number
a18Event name
ACM conference on Equity and Access in Algorithms, Mechanisms, and OptimizationEvent location
VirtualEvent type
conferenceEvent date
October 5-9, 2021ISBN
9781450385534Department affiliated with
- Informatics Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2021-09-13First Open Access (FOA) Date
2021-09-13First Compliant Deposit (FCD) Date
2021-09-13Usage metrics
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