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The integration of automated decision-making systems has transformed police work and our understanding of security and surveillance. Despite a growing theoretical literature on shifts in policing due to widespread analytical platform adoption, the public's understanding and perception of these changes are largely unexplored. This study aims to bridge this gap by empirically examining citizens’ perspectives on the new dynamics of police work in two societies with varying levels of experience with automation in the public sector: Estonia and Sweden. By combining data from a representative, scenario-based quantitative survey conducted among the general population (n = 2500) and qualitative storytelling techniques implemented in classroom settings with students (n = 23) who take classes with a focus on critical data studies, this research seeks to investigate people’s imaginaries, concerns, and expectations regarding predictive policing. The findings shed light on the observation that, in the era of data, the police are not solely perceived as an institution ensuring security or as a source of citizen apprehension related to surveillance. Rather, the transformations in police work are understood as ‘distant technologies’, wherein individuals, be they, citizens, or police officers, are increasingly removed from the direct application of these technologies. This article uncovers that when citizens possess low levels of trust in the police, the implementation of automation can further exacerbate the disconnect between citizens and the state. Furthermore, this research proposes an innovative approach to studying automated systems by combining scenario-based and storytelling methods, thereby making a valuable contribution to methodologies employed in the study of data.
Masso et al. (Fri,) studied this question.