Revolutionizing Proactive Policing: How Technology Can Transform Law Enforcement Beyond Discretion

This article is part of a study done through the CA POST Command College. It’s a look into a growing issue within law enforcement, focusing on possible future scenarios to help plan for changes in policing.

The outcome of this work is based on the future forecasting methods used at Command College. Taking charge of the future means adapting to new trends while maximizing opportunities and minimizing risks for police work.

By Captain Matt Lethin

What if your officers were involved in activities that didn’t really help reduce crime, used up their personal time, and strained relationships with the community? And what if your department strained to keep enough officers on the street just so they could keep doing it?

Proactive policing involves officers taking action beyond just responding to calls for help. It’s part of police work and can include strategies like problem-oriented policing (POP), community policing (COP), hotspot patrols, and focused deterrence. However, during the COVID-19 pandemic and the “defund the police” movement, many agencies backed off on proactive enforcement. Since then, many police departments have tried to ramp it back up, thinking it can help reduce crime and improve relationships with the community.

For many departments, proactive policing means officers using their judgment to decide when and how to enforce the law. Even though the leadership often promotes data-driven strategies, they often fall short on providing clear direction and follow-up to make sure officers stick to these methods. Many officers rely on their gut feelings instead of these strategies. Unfortunately, research shows that this kind of discretionary policing isn’t as effective in reducing crime and can hurt police credibility in the eyes of the community.

As we move forward, the police need to change how they operate. Transitioning from discretion-based to data-backed strategies is challenging, but technology can guide this shift. By using tools like surveillance cameras, automated license plate readers (ALPRs), drones, and predictive policing algorithms, officers can more effectively tackle crime while preserving community trust. Adopting this approach represents a smarter model for policing—one that benefits both officers and the neighborhoods they serve.

The pitfalls of discretionary proactive enforcement

Meet Officer Rodriguez, who has been on the force for five years. She works hard, often going above and beyond by stopping vehicles and conducting foot patrols during her time off. However, her proactive efforts sometimes don’t yield the results she hopes for.

One night, she stops a car for a minor violation. The driver, frustrated and feeling targeted, reacts poorly. Tensions rise quickly, leading to a confrontation that spirals out of control. This event causes Rodriguez to reassess her approach to proactive policing.

Around the same time, her department starts using new technologies, including ALPR cameras and predictive policing tools. These tools provide real-time data and help Rodriguez understand where and when crime is happening. For example, one day, the predictive tool alerts her to a string of car thefts in a certain area. With the data from the ALPR, she spots a suspicious vehicle and makes an arrest. This successful bust makes a real difference in the community.

This experience changes the way Rodriguez thinks: she sees that technology can make proactive policing more effective. With the right tools, she can achieve more and build better relationships with the community.

This scenario sheds light on the downsides of discretionary policing. While officers like Rodriguez aim to do well, relying solely on intuition can lead to negative outcomes. Evidence suggests that discretionary enforcement often lacks real effectiveness in reducing crime. It can also lead to inefficient use of officer time and further erode trust, especially in communities of color. Concerns about such practices have led to new laws in places like California and Oregon to limit proactive stops.

Why surveillance technology is key for proactive policing

Technologies, like those that aided Officer Rodriguez, are paving a better path ahead. Studies reveal that surveillance cameras and ALPRs can reduce crime dramatically—sometimes by as much as 80%. Meanwhile, technology-assisted investigations see higher success rates, often solving cases 66% more effectively.

Seeing the advantages, some police departments have changed their resource allocation. For example, a department in California has opted to use RTIC operators instead of filling officer positions, leading to better results in fighting vehicle theft. Many agencies now use predictive policing, sharing real-time alerts about crime hotspots, which has shown significant success in cities like Los Angeles and Newark. The NYPD employs a comprehensive monitoring system that has saved around $50 million annually while also contributing to a 6% drop in crime.

Overall, utilizing surveillance technologies can significantly cut crime rates. With the help of algorithms and AI, police can focus on areas that need attention without compromising community trust. However, it is crucial to combine these technologies with strong community-based policies.

Community trust is vital. Public opinions on police technology can be mixed. Concerns about privacy and bias are common. To address these issues, police departments must prioritize transparency and community involvement.

It’s essential for agencies to bring community members into discussions about technology usage. Whether through formal committees or informal groups, the public should be invited to share their views. By including community input on policies regarding facial recognition or data use, police can ensure that their practices align with community values and do not perpetuate bias.

Clear guidelines for surveillance technology use and data security should be in place. The public needs to know that their personal information will be protected and used responsibly. Establishing independently audited processes creates trust and accountability. Openly sharing data on technology effectiveness will also help everyone understand its impact.

Recommendations for future policing

As we consider the future, proactive policing should be shaped by thoughtful technology integration and community partnerships. Here are some practical steps to help with this transition:

1. Limit discretionary proactive enforcement

Agencies should encourage the use of proven, data-driven strategies instead of relying on intuition alone.

2. Adopt surveillance technologies

Implement tools like surveillance cameras, ALPRs, and predictive policing systems to enhance officer effectiveness and efficiency.

3. Build community partnerships

Engage with community members to co-create policies and ensure alignment with public values.

4. Revise officer training and recruitment

Focus on recruiting tech-savvy officers and provide ongoing training to keep up with technological advancements.

5. Increase civilian staff

Employ civilians to manage tech resources, allowing officers more time for essential policing tasks.

6. Explore regional partnerships

Collaborate with other agencies and organizations to enhance resource sharing and effectiveness.

A new era of smarter policing

Officer Rodriguez’s story exemplifies how surveillance technology can transform proactive policing. By moving beyond purely discretionary stops, agencies can harness technology to better direct their efforts. This shift allows officers to blend their skills with data-driven insights that can strengthen community relations and ultimately reduce crime.

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About the author

Matt Lethin is a captain with the San Mateo (California) Police Department. He has 24 years of experience in law enforcement, starting with the Marin County Sheriff’s Office before joining SMPD. He also teaches criminal justice at the College of San Mateo.