Algorithmic policing: an exploratory study of the algorithmically mediated construction of individual risk in a UK police force

Abstract

ABSTRACT Predictive policing has captured the imagination of both enthusiasts hoping to improve public safety and opponents raising concerns around algorithmic bias and opacity. Based on seven in-depth interviews with officers in a UK police force, this article examines the dynamics of how automated risk scores institutionalise an individual-focussed threat-harm-risk strategy aimed at preventing repeat offending. Born out of the need to prioritise work given budget cuts, the risk scores alleviate fears of missing opportunities for prevention and render professional decision-making defendable. Rather than replacing professional judgement, the article finds that officers maintain discretion in a process of co-construction by scrutinising the risk scores and weighing them against other priorities and operational constraints. In a climate of austerity, a concern arises from the scores’ potential to drive short-term selective incapacitation rather than prevention through supportive measures.