Predictive policing in and of itself is nothing new. It’s the straightforward evolution of intelligence-driven techniques, based on long established criminology principles that have been used by law enforcement for decades. The idea of forecasting crimes started back in 1931 when University of Chicago sociologist Clifford R. Shaw and Henry D. McKay, a criminologist at Chicago’s Institute for Juvenile Research, published a book examining why juvenile crime persisted in specific neighborhoods.
By the 1990s, organizations like the National Institute of Justice (NIJ) began leveraging geographic information system tools to map crime data and advanced mathematical models to guess where crime was most likely to occur. Today, law enforcement agencies and the private companies who develop predictive algorithms utilize cutting edge, computer driven models that can tap into massive stores of data and information. This is the era of big data policing.