This article summarizes the proceedings from a Predictive Policing Symposium, which examined the enabling of police agencies to anticipate and prevent crime instead of simply responding to it.
"Predictive policing" involves taking data from various sources, analyzing them, and then using results in order to anticipate, prevent, and respond more effectively to the types of crime predicted to occur in excess under the circumstances identified by the data analysis. This enables police agencies in a particular jurisdiction to provide the training and strategic deployment of resources to prevent and/or respond effectively to anticipated crimes. Predictive policing borrows from the principles of problem-oriented policing, community policing, evidence-based policing, intelligence-led policing, and other proven policing models. Predictive policing uses such analytical tools and techniques as the identification of existing and future "hot spots" for particular crime types, data mining that identifies crime patterns and trends, crime mapping for the identification of geographic trends in various crimes, and social network analysis for the identification of societal variables related to various types of criminal behavior. Predictive policing efforts do not involve the pre-emptive targeting of individuals prior to their committing a crime, so as to violate their privacy and civil liberties. Rather, it involves the deployment and management of police resources so as to provide a police presence and action that involves a deterrence, readiness, and effectiveness in police efforts.
- Importance of culture in measuring tribal crime seriousness: scoping review of crime seriousness indices
- Facilitators and Impediments to Designing, Implementing, and Evaluating Risk-Based Policing Strategies Using Risk Terrain Modeling: Insights From a Multi-City Evaluation in the United States
- Effective Game-Based Training for Police Officer Decision-Making: Linking Missions, Skills, and Virtual Content