LAUSR

While using statistics in law enforcement is nothing new,1 cutting-edge technology that uses big data is changing the face of law enforcement (Buchholtz 2020; Degeling and Berendt 2018; Egbert and Krasmann 2019; Ferguson 2017b; Sheehey 2019; Nissan 2017; Perry et al. 2013). As data and statistical tools have improved over time, a new police strategy called “predictive policing” (hereafter, PP) has come into practice (Saunders et al. 2016; Kreutzer and Sirrenberg 2020; Kulkarn and Akhilesh 2020). Based on the assumptions that certain aspects of the physical and social environment encourage predictable acts of criminal wrongdoing, and that interfering with that environment would deter the would-be crimes, PP aims to “forecast where and when the next crime or series of crimes will take place” by identifying trends and relationships that may not be readily apparent to us among the collected data (Uchida 2014, p. 3871; see also Ferguson 2017a; Moses and Chan 2018). Techniques involving large quantities of digital information have been evolving at a rapid rate. As Ferguson (2017a) notes, while the social scientific research supports the insights behind PP, police adoption of the strategy has outpaced established scientific findings. More significantly, when a police department declares its adoption of PP, it could be doing things that vary greatly in their technical sophistication, effectiveness, and ethical concerns. As such, while there is an increasingly heated debate about the effectiveness and potential impacts of the emerging techniques involving large quantities of digital information, the discussion is easily conducted without careful awareness of the differences among various methods and practices of PP (Egbert and Krasmann 2019; Ferguson 2017b). Besides, myths and pitfalls may hinder proper evaluation of PP’s development and deployment, such as assuming that AI actually knows the future, or focusing on prediction accuracy rather than tactical utility (Perry et al. 2013). As a proactive policing model, the targeted units of crime predictions of PP can range from different sizes of geographical areas to individual people. Based on its focuses, PP can be divided into three subdivisions: