Algorithmic Surveillance in the UK Welfare System: The Case of Universal Credit and the Rise of Digital Conditionality

Abstract

This paper examines the proliferation of algorithmic surveillance within the UK welfare state and employs the implementation of Universal Credit (UC) as an exemplar of digital welfare provision. Combining qualitative policy analysis with current, up-to-date research (2016–2025) it analyses how automation, digital conditionality, and digitally-monitored practices impact the daily lives of claimants and the practices of the welfare services. It applies theory from surveillance studies and algorithmic governance literature to demonstrate the increasing regulation of welfare eligibility, conditionality and behaviour by the digital infrastructures that underpin modern welfare services. It finds that Universal Credit further extends conditionality through constant digital monitoring, automated anti-fraud measures and the creation of data-driven assessments of the capacity of claimants to engage with welfare, disproportionately affecting marginalised claimants and the digitally excluded. This paper argues that these systems may reduce professional judgement, increase bureaucratic burdens and expand state capacity for surveillance under the logic of efficiency and modernization. In turn it provides new theoretical insights into digital welfare governance by conceptualizing Universal Credit as a holistic system of algorithmic governance restructuring relations of power between the institution and the claimant.