Gavin Howe
There are four main models of policing in the United States: traditional, community, intelligence-led, and problem-oriented. Intelligence-led policing is a proactive approach that uses indicators to get ahead of threats and criminal behaviour. It involves developing intelligence requirements, collecting information, and analyzing it to disseminate the analytic product. Intelligence-led policing also incorporates big data methods, such as predictive policing, facial recognition, and social media monitoring. Predictive policing uses algorithms to predict future crimes and can be place-based or person-based. Place-based predictive policing uses pre-existing crime data to identify high-risk places and times, while person-based policing attempts to identify individuals or groups likely to commit or be victims of a crime. However, intelligence-led policing has faced transparency concerns, such as with the NYPD's predictive policing efforts, where there is a lack of documentation and audit logs.
| Characteristics | Values |
|---|---|
| Type | Intelligence-led policing |
| Focus | Developing priorities based on multiple factors, including intelligence analysis |
| Process | Develop intelligence requirements, collect data, organize, process, analyze, and disseminate findings |
| Benefits | Facilitates crime and harm reduction, disruption, and prevention through strategic and tactical management, deployment, and enforcement |
| Role of Community Members | Providing vital information for crime pattern analysis, building trust with police officers, and working together to eliminate and prevent problems |
| Role of Police Officers | Assessing and managing risks by identifying crime patterns |
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What You'll Learn
Predictive policing
The use of predictive policing has been justified as a way to reduce crime and ensure safety in cities. For example, in 2003, Richmond's police department used historical data to predict where gun-firing would occur on New Year's Eve and adapted their surveillance routes, resulting in a 47% decrease in gunfire and a 246% increase in weapons seized.
However, predictive policing has faced criticism and concerns over its effectiveness and ethical implications. Some studies have found that predictive policing strategies lead to a decrease in crime, while others found no effect. There is a lack of empirical evidence supporting the benefits of predictive policing, and it has been argued that it lacks a clear evidence basis.
Another issue is the lack of transparency surrounding predictive policing efforts, particularly regarding the source of data used as inputs for algorithms and how crime predictions are used. This lack of transparency makes it difficult for independent auditors or policymakers to evaluate these tools and their potential impact on communities.
Furthermore, predictive policing has been criticized for its potential to reinforce racial bias and discrimination. There have been instances of wrongful accusations due to errors in facial recognition technology, which is more likely to misidentify people of color. In addition, communities of color and low income are often disproportionately targeted by predictive policing, raising concerns about the reinforcement of historical over-policing of these communities.
Despite these concerns, predictive policing continues to be employed by law enforcement agencies, and there is ongoing debate about its benefits and risks.
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Intelligence-led policing
ILP is a proactive approach that involves implementing policies and practices based on multiple factors, including intelligence analysis. With defined priorities, personnel can develop intelligence requirements, collect data, organize and process the information, and then share the analytical output with relevant stakeholders. ILP emphasizes analysis and intelligence as pivotal to an objective, decision-making framework that prioritizes crime hotspots, repeat victims, prolific offenders, and criminal groups.
The main goal of ILP is to anticipate and act on threats and criminal behaviour. This is achieved by proactively identifying indicators and taking appropriate action. ILP provides a structured process for anticipatory crime mitigation through the collection and analysis of information, allowing police agencies to be proactive rather than reactive in addressing and mitigating threats.
However, there are concerns about intelligence-led policing, including the potential for "over-policing in minority neighbourhoods" and the invasion of privacy through the tracking of specific individuals considered potential perpetrators. Proponents of ILP counter that computer-based analysis eliminates bias and that policies and procedures are in place to minimize profiling risks.
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Community policing
The concept of community policing gained prominence in the late 20th century as a response to the preceding philosophy of police organization. It is rooted in Sir Robert Peel's 1829 Peelian Principles, which emphasize the importance of seeking the cooperation of the public and prioritizing crime prevention over repression by military force or legal punishment.
The implementation of community policing has involved various approaches, including the assignment of foot patrol officers to specific geographic areas to address crime hotspots, as seen in an experiment in Flint, Michigan. The Clinton Administration promoted community-oriented policing, and the 1994 Violent Crime Control and Law Enforcement Act established the Office of Community Oriented Policing Services (COPS) within the Justice Department, providing funding to promote these initiatives.
Social media plays a significant role in community policing. It helps disseminate information on public safety issues, crime prevention, and suspect details. It also aids in analyzing past crimes and predicting future ones, contributing to intelligence-driven and predictive policing models. However, social media can also fuel the negative "bad cop" theory, where officers are portrayed negatively, highlighting their incompetence or corruption. Overall, community policing aims to repair relationships, increase trust, and ultimately enhance safety within communities.
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Transparency concerns
The New York Police Department (NYPD), the largest police force in the United States, started testing predictive policing software as early as 2012 and developed its own in-house predictive policing algorithms in 2013. Despite describing the information fed into the algorithms, the NYPD has not disclosed the data sets used. There is also little transparency about the source of the data used as inputs for the NYPD's algorithms, and no audit logs of who creates or accesses predictions are kept.
The Brennan Center filed a lawsuit to obtain documentation about the NYPD's use of predictive policing software, and the department only disclosed some information after an expensive, multi-year legal battle. Similarly, the Chicago Police Department ran a large person-based predictive policing program called the "heat list" or "strategic subjects list", which included every person arrested or fingerprinted in Chicago since 2013.
The lack of transparency around predictive policing algorithms and the data used to train them can lead to concerns about potential biases and the effectiveness of these systems. Without proper oversight and accountability, there is a risk that predictive policing may reinforce existing biases or infringe on civil liberties.
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Preventing crime
Another effective strategy for preventing crime is community policing. This model emphasizes the collaboration between police officers and community members in specified geographic zones. By actively engaging with the community, police officers can develop close relationships, gain trust, and work together with residents to prevent and manage crime. Community policing empowers individuals to take an active role in maintaining law and order, reducing the burden on law enforcement and increasing job satisfaction for officers.
Intelligence-led policing (ILP) is a proactive approach that utilizes intelligence analysis to identify and address criminal threats. ILP prioritizes crime hotspots, repeat victims, prolific offenders, and criminal groups, aiming to disrupt and prevent criminal activities through strategic management and enforcement. This model emphasizes the importance of collaboration between law enforcement, the intelligence community, and private sector partners to proactively identify and address emerging threats.
Problem-oriented policing is another model that focuses on addressing the root causes of crimes. It involves identifying and analyzing specific problems, developing effective solutions, and implementing preventive measures to reduce future incidents. By understanding the underlying issues that contribute to criminal activities, law enforcement can develop targeted strategies to mitigate them.
Additionally, Sir Robert Peel's Policing Principles, established in 1829, provide a foundation for modern policing. These principles emphasize preventing crime and disorder through impartial law enforcement, earning public support, and using force only as a last resort. By upholding these principles, law enforcement agencies can maintain the respect and cooperation of the public, contributing to effective crime prevention.
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Frequently asked questions
The last model mentioned is the intelligence-led policing model.
Intelligence-led policing (ILP) is a proactive way of thinking in law enforcement. It involves using intelligence analysis to develop priorities and strategies for crime reduction, disruption, and prevention. ILP helps law enforcement focus on crime hotspots, repeat victims, prolific offenders, and criminal groups.
ILP is a process where agencies implement policies and practices based on intelligence analysis. With their priorities in mind, personnel develop intelligence requirements, collect and analyze information, and then disseminate the analytic product.
Intelligence-led policing allows law enforcement to get ahead of threats and criminal behavior by proactively identifying indicators and taking action. It also helps law enforcement focus their efforts on areas of high priority, such as crime hotspots.
Other models include traditional policing, community policing, and problem-oriented policing. Community policing, for example, focuses on police officers operating in specific geographic zones and engaging with community members to prevent and manage crime. Intelligence-led policing, on the other hand, emphasizes the use of intelligence analysis and a more strategic approach to decision-making.
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