Mitigating algorithmic bias in the UK civil service: Challenges and implications for practice

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Authors: Hadley Beresford
Cited by: 0
References: 21

Abstract

This article examines algorithmic bias mitigation in the context of the UK's civil service, specifically the Department of Work and Pensions (DWP). Despite various algorithmic bias mitigation approaches being suggested in the literature, little research has examined how these might work in complex organisational contexts such as the DWP. In this article, I explore the perception of civil service practitioners of three sociotechnical bias mitigation methods, particularly their perceptions of the applicability of these methods and how they might be implemented. To do this I draw on data gathered through workshop series on algorithmic bias with DWP practitioners and follow up interviews. The findings suggest that: (1) it is difficult for practitioners to align technologies to the social justice values that underpin sociotechnical mitigation approaches when servicing a large heterogenous public; (2) practitioners’ perception of a lack of clarity in anti-discrimination legislation make it difficult for them to move beyond statistical framings of fairness and (3) participants perceived workforce diversity as important to algorithmic bias mitigation efforts; however, this was not considered a short-term solution.

Fields of Study & Subjects

Ethics and Social Impacts of AI Artificial Intelligence in Healthcare and Education Qualitative Comparative Analysis Research

Publication details

Journal / source
Big Data & Society
Publisher
SAGE Publications
Volume
13
Issue
3
Publication date
27 August 2026
Language
EN