Original version
Automating Crime Prevention, Surveillance, and Military.. 2021, 69-83, DOI: https://doi.org/10.1007/978-3-030-73276-9_4
Abstract
Many aspects of law enforcement increasingly rely on algorithmic processing of digital data. Whereas most recent critical scholarship focuses on the algorithm as the decisive factor in the production of knowledge and decisions, we foreground the data that feed into algorithms. Based on insights gained from empirical studies on predictive policing software, we forward a theorization of “information in-formation”. In bringing together new materialist thinking and approaches about the liveliness of data, we conceptualize data as matter that is in-formation due to both human and non-human capacities. We develop the analytic notion of the life cycle of data to better understand the liveliness and agency of data in any type of data-based environment, and illustrate the life cycle of data in the case of predictive policing. We show how data come into being, how they are selected and cleaned, how they multiply in distinct database systems and according to different logics of speed and urgency and how they inform the workings of algorithms.