Predictive Policing: Intelligence-Led Policing for Law Enforcement Managers Research Paper

It is important to note that policing is a complex and multifaceted set of measures designed to enforce the law and safeguard people. Predictive policing is a policing approach that uses “algorithms to analyze massive amounts of inform­a­tion in order to predict and help prevent poten­tial future crimes” (Lau, 2020, para. 4). Crime maps support law enforcement efforts by revealing a pattern or trends, and thus, it “can be an effective way to analyze where crime occurs” (Hunt, 2019, para. 1). The predictive policing in the case was able to successfully predict a pattern in term of both high-risk timeframes as well as locations more likely to experience a burglary. The type of data used is comprised of “reported incidents of crime that have occurred in the City of Chicago over the past year, minus the most recent seven days of data” (Chicago Data Portal, 2022, para. 1). The key factors of interest were the regions, where the crimes occurred, and timeframes.

However, one should be aware that predictive policing is not limited to the mapping of locations or time. There is a multitude of additional tools available to conduct policing predictively. Some examples of these instruments include international mobile subscriber identity or IMSI catchers and facial recognition technologies. The former is “a device that locates and then tracks all mobile phones that are connected to a phone network in its vicinity, by ‘catching’ the unique IMSI number” (Privacy International, 2021, para. 7). The latter utilizes security camera footages to identify and predict crime likelihoods. IMSI uses phone numbers and network data, whereas facial recognition primarily relies on visual video information, such as footage. IMSI allows to effectively surveil and track mobile phones, and facial recognition technologies enable to scan and monitor people’s faces to identify potential suspects or high-risk individuals.

The key advantage of predictive policing is that it is focused on prevention, whereas reactive policing waits for a crime to happen first. It is stated that “standard law enforcement practices of reactive policing and rapid response do not alleviate crime. The reality of reactive policing is that an incident or some sort of damage already has occurred” (Huber, 2019, para. 3). In other words, communities might benefit from predictive policing by avoiding experiencing crime altogether instead of seeking retribution. The major problem with predictive policing lies in civil liberties and privacy rights, where communities and individuals are always under the threat of breach by intelligence-led policing measures. The investigation can be assisted with the use of social media platforms to find the suspects or discourage crime by calling for vigilance. Some useful technologies would include IMSI, facial recognition, and social media applications. As stated above, IMSI is useful to track mobile phones, facial recognition technology can be applied to face tracking, and social media is powerful for communication, user data analysis, and possibly location tracking.

It should be noted that some case laws can be relevant to the scenario. One of them is Freedom of Information Law (FOIL), which can limit the practice of predictive policing by “seeking records relating to the acquisition, testing, and use of predictive policing technologies” (Levinson-Waldman, 2017, para. 3). In other words, the law enforcement might be mandated to share its sensitive data, which would inform the public, including criminals, about the methods. The current lawsuits on predictive policing are concerned with the constitutional rights to privacy (Levinson-Waldman, 2017). Bias can be introduced into predictive policing, such as racial bias, where specific groups could be targeted by the instruments more than others.

References

Chicago Data Portal. (2022). Crimes – Map.

Huber, N. (2019). Intelligence-led policing for law enforcement managers. FBI Law Enforcement Bulletin.

Hunt, J. (2019). From crime mapping to crime forecasting: The evolution of place-based policing.National Institute of Justice.

Lau, T. (2020). Predictive policing explained. Brennan Center for Justice.

Levinson-Waldman, R. (2017). Predictive policing goes to court. Brennan Center for Justice.

Privacy International. (2021). How IMSI catchers can be used at a protest.