First Published on 28 June 2023.

Background:

Predictive policing has emerged as a powerful tool in law enforcement, aiming to enhance crime prevention and solve cases more efficiently. Through the use of data analytics and algorithms, police departments attempt to predict where and when crimes are likely to occur. However, this practice has stirred significant controversy, with concerns about bias, racial disparities, and potential infringements on civil liberties.

Predictive Policing: What is It?

Here is some background. Predictive policing originated from the visionary ideas of William J. Bratton, the former police chief of the Los Angeles Police Department. By analyzing crime data, predictive policing algorithms generate hotspots and patterns, enabling law enforcement agencies to allocate resources effectively and deploy officers to high-risk areas. The concept gained traction globally, captivating police departments seeking innovative solutions to combat crime.

This seems great right? Well.. now I’ll explain why this practice can be negative.

The Cons: Ethnic Bias

Crime statistics and historical data often reflect existing racial disparities in arrests and convictions. Consequently, predictive algorithms tend to associate higher crime likelihood with areas predominantly inhabited by people of color. This perpetuates systemic discrimination and reinforces biased policing practices.

Another challenge associated with predictive policing is confirmation bias. When officers are informed about high-risk areas, there is a tendency to make more arrests, even for minor offenses, in an effort to validate the accuracy of the predictions. This over-policing phenomenon can disproportionately impact marginalized communities, leading to a cycle of surveillance and further entrenching the biases embedded in the data. Research has shown that predictive policing software, when implemented in the Los Angeles Police Department, resulted in a significant increase in arrests.

The story of Robert McDaniel illustrates the potential dangers of predictive policing. Labeled as a future gun crime suspect by the algorithm, McDaniel was subjected to constant surveillance. The increased police presence made his neighbors suspicious, damaging community trust. Tragically, McDaniel was eventually shot twice in his neighborhood but survived surprisingly.

Thus, acknowledging the limitations and potential risks of these algorithms is paramount to avoid perpetuating systemic biases and over-policing vulnerable communities.

San Jose’s Incorporation:

San Jose, known for its technological advancements, embraced predictive policing as a means to enhance its law enforcement capabilities. The San Jose Police Department (SJPD) procured a “Crime and Mobile Predictive Analytics Software Suite” from The Omega Group in 2015. However, the specific details of how predictive policing is implemented in San Jose such as surveillance remain undisclosed. We must keep a close eye on our own communities to reduce biased usage of this practice.