From prevention to repression: The unexpected consequences of crime prediction

• In Event: The digitalisation of police work and its consequences for citizens

Abstract

With the help of predictive technology, particularly artificial intelligence (AI), society increasingly turns towards preventing unwanted events before they get out of control. In such a ‘preventive world’, the aim is for unwanted events not to happen in the first place by, as it were, being there before a problem materializes. This, consequently, brings about new questions around the role of absence in core societal topics such as crime prevention. In my more than eight years of fieldwork at the Dutch police – studying the development, implementation, and use of a predictive policing AI system – it is exactly the phenomenon of absence and its influence on organizational practices that I spent most of my time trying to understand.
In this panel, I will present insights from a study focused on how the use of AI to prevent crime and the connected importance of absence led to two conflicting managerial demands: (1) prevent predicted crimes before they happen (i.e., the technological demand), and (2) observe predicted crimes when they happen (i.e., the managerial demand). In an effort to overcome the inability to satisfy both demands, the police implemented multiple street-level interventions that became increasingly forceful, as they moved from preventive appearance, to preventive surveillance, to preventive repression. Hence, the paper shows that, when using AI to prevent future crimes, managing absence can become an escalating and inescapable pattern with relevant consequences for citizens.

Author

• Lauren Waardenburg, ESSEC Business School