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Predictive Policing - Research Paper Example

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Undoubtedly, in the context of the increasing threats of terrorism and organised crimes, predictive policing is an excellent approach to address law and order. This paper will discuss various aspects of predictive policing and how tools like COMPSTAT increased the efficiency of police departments…
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Predictive Policing
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? Predictive Policing Predictive Policing Introduction Predictive policing is an innovative concept applied by police departments to take proactive measures to prevent future crimes through the application of advanced technological tools and data analysis techniques. Under this technique, historical crime data are analyzed using advanced technologies in order to identify ‘hotspots’ and map problem areas. Experts suggest that predictive policing significantly increases the responsiveness of police departments. Undoubtedly, in the context of the increasing threats of terrorism and organised crimes, predictive policing is an excellent approach to address law and order. This paper will discuss various aspects of predictive policing and how tools like COMPSTAT increased the efficiency of police departments. Information technology to reduce crime Vs random patrols Reports indicate that the application of information technology greatly assists police departments to take proactive measures against future crimes and thereby reduce crime rates. The recidivism rate for parolees, probationers, and sex offenders is on the rise in the United States and this issue has generated intense public scrutiny. Currently, the US police departments widely use advancements in information technology to optimize their performance and thereby reduce crime rates. Application of Global positioning system or GPS is currently used as an effective way to reduce the rate of recidivism. As Navarro (2007) points out, in Florida, micro global positioning chips are implanted in the body of child sexual predators to monitor them continuously. In addition, micro GPS chips are also used to accurately map the location of parolees and probationers so as to prevent them from committing crimes in future. A network of databases containing historical crime data has been established in the US for enabling police departments to get faster access to past crime information. This system improves the communication between police departments across the country and this strong policing network reduces crimes rates to a great extent. Similarly, application of information technology is of great help for police departments to reduce random patrol of the streets. As discussed earlier, the development of GPS greatly benefited the police to reduce random patrolling. The satellite based radar system and surveillance camera systems aid US police departments to monitor streets from control rooms. To illustrate, traffic rule violations including over speed and signal jumping are captured and recorded by radar and surveillance camera systems and hence the law violators are identified using their vehicles’ registration numbers. The radar systems are also helpful to observe gangsters and other problem makers. In short, IT assists police departments to prevent crimes effectively without random patrol of the streets. IS functions of COMPSTAT Input, processing, output, and feedback are the four basic IS functions of COMPSTAT, a law enforcement crime fighting strategy adopted by the New York City Police Department. Four IS functions Four COMPSTAT principles Input Accurate and timely intelligence Processing Effective tactics Output Rapid deployment Feedback Relentless follow-up and assessment (Source: Godown, 2009) As the input, computer generated and other statistical data are collected and gathered timely to present in various formats such as charts, maps, and graphs at COMPSTAT meetings. The process is initiated by timely given accurate information and data. At the primary level, “information is gathered from an agency’s statistical archives on crimes and arrests” and which is produced to the U. S. Federal Bureau of Investigation (FBI) Uniform Crime Reporting program (Godown, 2009). At the processing stage, effective tactics are developed to manage a particular situation. Once the staff officers are provided with timely and accurate information, they have to design, develop, and implement crime management policies and action plans in order to minimize the chances of the identified crime. Rapid deployment of the developed strategies and actions plans is the output of the COMPSTAT process. Rapid deployment assists police departments to obtain the desired outcomes before their target moves. Evidences suggest that taking overtime to implement an action plan is likely to affect the effectiveness of the results. Finally, in the feedback stage, a critical assessment of implementation plan is carried out to evaluate the impacts the plan has had on the targeted outcomes (Godown, 2009). If the assessment reflects that the plan had failed to meet its targeted outcomes, the officials concerned must conduct deep enquiry into the case so as to clearly identify the pitfalls and to improve for the future. Application of information systems in crime control It is identified that information systems have allowed police departments to implement tools such as COMPSTAT to respond to crime faster. As experts point out, IT systems like COMPSTAT are very effective while addressing criminality of places. As Dorriety (2005, as cited in Issac, 2010) indicates, the implementation of COMPSTAT assisted the New York policing agencies to reduce the state’s crime rate by 27% over a two year period from 1993 to 1995 whereas the drop in the national average was a mere 2% during the same period. As the New York Times reporter Goode (2011) reports, preventive policing is an effective strategy to send police before there is a crime, Goode reports that an IT powered computer program aided the Santa Cruz Police Department to arrest two women for an attempted car burglary. The computer program predicted that car burglaries were more likely to happen there that day. Computer Aided Dispatch (CAD) systems facilitate prioritization of phone calls for police service on the basis of whether or not an emergency response is needed. Crime mapping is another IT powered technology that helps police departments identify and track patterns of crime and thereby respond to crimes faster. Crime mapping software work based on Geographic Information Systems (GIS) technology. As Chandek (1999) points out, by tracking the patters of crime under their jurisdictions, police departments can predict the probabilities of future crimes and hence take proactive measures to prevent them (RCPI). According to Pearsall (2010), by using predictive policing techniques, the Richmond police could reduce the random gunfire in the city. Based on the data gathered and analyzed, the Richmond police aligned officers at ‘hotspots’ to respond more rapidly; and as a result of this proactive plan, the Richmond police could achieve a 47% decline in gunfire and a 246% increase in weapons seized (Pearsall, 2010). SWOT analysis of predictive policing SWOT analysis is a potential tool to analyze the feasibility of police departments that intend to implement predictive policing. Rapid advancement in technology is one of the major strengths of predictive policing because this concept is centered on technological applications. In addition, successful past experiences also add to the viability of this concept. The major identified weakness of this approach is that it uses many assumptions and hence desired results may not be achieved sometimes. Likewise, the element of corruption may weaken the feasibility of predictive policing. However, the concept of predictive policing raises an array of opportunities to police departments. As discussed earlier, significant reduction in crimes rates can be achieved through the application of predictive policing strategy. Probably, this concept will reduce operational costs because it proactively takes measures to prevent future crimes. In addition, it is a better tool to reduce the rate of recidivism as predictive policing approach employs numerous technological advancements to monitor parolees, probationers, and sexual offenders. Development of artificially intelligent computer programs definitely contributes to the applicability of predictive policing. As discussed already, the concept of predictive policing is powered by a network of police databases containing historical crime data. Therefore, it is very easy for police departments to deal with crime investigations and to respond to various emergencies quickly. Evidently, this concept adds to the efficiency and scope of policing. Currently, no threat to predictive policing is identified. Conclusion From the above discussion, it is clear that the concept of predictive policing has been successful since its development. This approach is effective to reduce recidivism, crime rates, and operational costs. Fast developments in technology, particularly information technology, facilitate the widespread application of predictive policing. References Chandek, M. S. (1999). Technology to Enhance Community and Problem-Oriented Policing. School of Criminal Justice, Michigan State University, E. Lansing, Michigan 48824. Retrieved from http://www.cj.msu.edu/~outreach/cp/techtoenhance.pdf Issac. (2010). To compstat or not to compstat. JusticeGuy.com. retrieved from http://www.justiceguy.com/?p=43 Goode, E. (2011). Sending the police before there’s a crime. New York Times, Aug 15. Retrieved from http://www.freerepublic.com/focus/f-news/2766717/posts Godown, J. (2009). Police Chief, LXXVI (8). Retrieved from http://www.policechiefmagazine.org/magazine/index.cfm?fuseaction=display_arch&article_id=1859&issue_id=82009 Navarro, R. (2007). “How Technology Can Reduce Crime and Impact the Criminal Justice System.” Marin County Sheriff’s Department. Retrieved from http://libcat.post.ca.gov/dbtw-wpd/documents/cc/40-navarro.pdf Pearsall, B. (2010). Predictive Policing: The Future of Law Enforcement? National Institute of Justice. Retrieved from http://www.nij.gov/journals/266/predictive.htm Read More
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