Explainer: Predictive Policing

Explainer: Predictive Policing

Predictive policing involves the use of analytical techniques to identify potential criminal activity and promote public safety. Developments in technology, particularly advancements in computer science and data science, have propelled the application of predictive policing.

What Is Predictive Policing: A Thorough Definition

Predictive policing is both a theoretical concept and a technology-driven practice in law enforcement. As a concept, it centers on crime prevention through prediction crime using mathematical models and statistical techniques, predictive analytics, and other analytical techniques. It is essentially about preventing crime before it happens based on a data-driven approach.

On the other hand, as a technology-driven practice, predictive policing uses data analytics, as well as other technologies such as artificial intelligence, including machine learning, and Big Data applications, to provide law enforcers with relevant insights and targets for police intervention.

It is worth mentioning that the concept and practice traces its from business analytics or BA. Remember that by definition, BA corresponds to the competencies, technologies, and practices for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning.

The Four General Categories of Predictive Policing Methods

The following are the four general categories of predictive policing methods that also correspond to the goals and objectives of the practice:

• Methods for Predicting Crime: Focuses on the analysis of crime patterns across time and space using data inputs such as frequency and location, among others to deter criminal activities and better manage the availability and presence of law enforcers.

• Methods for Predicting Offender: Involves the use of data analytics to determine the level of threat an individual has to public safety, as well as to predict the degree at which a person is susceptible to commit a crime.

• Methods for Predicting Identity: Centers on the analysis of large amounts of data from various sources such as the database of agencies, social media, and other publicly accessible databases to predict the identities of possible perpetrators.

• Methods for Predicting Victims: Focuses on the use of data analytics to determine the degree at which a person is susceptible to becoming a victim of a crime, as well as the risk of a particular geographic location or specific timestamp toward criminal activities.