Abel, E. orcid.org/0000-0002-3694-5116 and Siraj, S. orcid.org/0000-0002-7962-9930 (2024) An approach to investigate fairness using Dominance-based Rough Sets Analysis—How fair were the COVID-19 restriction decisions in the UK? Applied Soft Computing, 151. 111121. ISSN 1568-4946
Abstract
Fairness is a crucial aspect to consider within decision support systems, to seek to strive for equitable decision outcomes. Therefore, in this work, we introduce an approach to investigate fairness in data-driven decisions. The Dominance-based Rough Sets Approach (DRSA) has been widely used to extract a single set of if-then types of rules from data. Conversely, our approach investigates fairness by extracting multiple separate if-then rule sets for separate groups. The proposed approach facilitates fairness analysis to be performed amongst groups represented by these rule-sets.
During the COVID-19 pandemic, several countries have taken the approach of tiered restrictions, which has remained a point of debate due to a lack of transparency. Using our proposed approach, we explore fairness analysis with regards to the UK government’s COVID-19 tiered restrictions allocation system. These insights from the analysis are translated into “if-then” type rules, which can easily be interpreted by policy makers. The differences in the rules extracted from different geographical areas suggest inconsistencies in the allocations of tiers in these areas. We found that the differences delineated an overall north south divide in England, however, this divide was driven mostly by London. Such analysis could provide a more transparent approach to localised public health restrictions, which can help ensure greater conformity to the public safety rules. Our analysis demonstrates the usefulness of our approach, to explore fairness analysis in terms of equal-treatment within data-driven decisions, which could be applied in numerous other domains, for investigating the fairness and explainabilty of decisions.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 The Author(s). This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | Multi-criteria data analysis, Dominance-based rough sets, COVID-19, Data wrangling, Data-driven decision making |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Business (Leeds) > Management Division (LUBS) (Leeds) > Management Division Decision Research (LUBS) |
Depositing User: | Symplectic Publications |
Date Deposited: | 07 Dec 2023 14:39 |
Last Modified: | 18 Oct 2024 13:31 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.asoc.2023.111121 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:206297 |