Cis 500 Predictive Policing

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Assignment 1: Predictive Policing
Jermaine Johnson
Dr. Edwin Otto
CIS 500
April 20, 2013

“Predictive policing, in essence, is taking data from disparate sources, analyzing them and then using the results to anticipate, prevent and respond more effectively to future crime.” (Pearsall, 2010) “The Arlington, Texas, Police Department used data on residential burglaries to identify hot spots and then compared these locations to areas with code violations. According to Chief Theron Bowman, officers found that every unit increase of physical decay resulted in almost six more residential burglaries in the city. Thus, neighborhoods with greater physical decay could expect greater increases in residential burglaries. Arlington subsequently developed a formula to help identify characteristics of these "fragile neighborhoods." The police department and other city agencies now work more efficiently in the neighborhoods to help prevent crime.” (Pearsall, 2010) Predictive policing has proven to be a great thing that and now that it is being used in more cities and locations we can expect an even wider acceptance of this new tactic. These following pages will examine this new predictive policing as a whole including strengths as well as weaknesses. The application of information technology to optimize police department’s performance to reduce crime versus random patrols of the streets is a great addition to helping problem areas of a community. With this new application the police department can now save more money, time and effort while focusing on the areas that need more help than others. Most people would just assume that it’s all the urban areas that have all the problems. With this new technology it can be written up and documented to show that there isn’t a biased opinion about certain areas of a community. “In July,(2011) Santa Cruz began testing the prediction method for property crimes like car and home burglaries and car thefts”, so when these 2 officers “were directed to the parking structure by a computer program that had predicted that car burglaries were especially likely there that day”(Goode, E. 2011, August 15)it wasn’t a huge surprise. Without this technology, these 2 women probably would have gotten away with whatever it was they were doing. A technology like this is a great addition to the police department but it’s not good to put all your eggs in one basket.

Although predictive policing is proving to be a great addition, it should not be the only thing relied upon. It saves money time and effort but if it were to be the only source that determined where police patrolled then the police would never catch those random acts of violence or crimes when police just happen to be “in the right place at the right time.” Random patrols save lives maybe even a little better than this new technology. In October of 2012 a 78 year old man was having coffee with his wife when he then began to feel dizzy and then fainted fell to the ground opening a large gash on his head. “Luckily for him, 32 division´s Const. Vildan Jahjefendic was in the coffee shop lineup, heard the commotion and rushed to the man’s side. Wagerer was unconscious but breathing and Jahjefendic jumped into action holding Wagerer´s head to control the bleeding, while calling radio dispatch for an ambulance. He asked staff to get paper towels and talked to Wagerer to keep him calm until paramedics arrived.” (Clarke, 2012) The police officer was obviously on a random patrol when he stopped for a coffee when this took place. If we begin to only relay on predictive policing and rid all random patrols, then who knows what happens to this poor man while an ambulance is being dispatched. The way predictive policing should be used is it should be in addition to what we use currently so that random acts of kindness by police, such as this Toronto officer, don’t go out the window. Predictive policing can also be seen as an attempt to justify the fact that there are...
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