Technology successfully solves current challenges in law enforcement investigations. Law enforcement agencies face staffing shortages, declining morale, data accuracy problems, issues about officer accountability, and the ongoing need to build community trust.
Let’s look at how technology is helping to solve these five challenges.
1. Law enforcement staffing shortages
The Police Executive Research Forum surveyed law enforcement agencies across the United States to assess their current staffing conditions and other workforce trends.
The main concerns of the 194 responders to the survey were the same. They included the pandemic, the general climate for police, local reform efforts, and the Great Resignation, where millions of Americans quit their jobs, including many law enforcement officers.
A key finding from this research is that agencies, on average, are currently filling only 93% of the authorized law enforcement position available. There were fewer new hires of officers than the previous year. Resignations increased by 18%, and retirements increased by 45%.
The lack of staffing forced some agencies to reduce proactive police work to be able to respond to the volume of 9-1-1- calls. Detectives who normally investigate criminal cases have to suit up and go out into the field as part of the regular force.
Technology to conduct crime analysis that is useful for deploying the limited resources has become a vital necessity.
In response to reduced staff and increased caseloads, CLEAR helps investigative officers improve efficiency and effectiveness with access to billions of data points in the public records.
2. Declining officer morale
The survey also found that officers have pandemic fatigue and are depressed over the negative national sentiment about the police. Many police are being encouraged by their spouses to leave the profession. Nearly all resignations leave the profession completely and not for a transfer to another agency.
Recruits for police academies in some parts of the country are down by about half. Sworn officers seek positions outside of major urban centers to avoid working the streets as patrol officers or in schools.
Officers seek retirement at the first possible moment after serving for 20 years instead of continuing on the force for 30 or 40 years.
Nevertheless, communities that are supportive of police still exist. The use of technology such as systems for proactive and predictive policing combined with surveillance cameras helps reduce the crime rates, boosting community support. The morale of officers in such communities is very good.
3. Data accuracy for crime prevention and active investigations
Advanced use of information technology helps predict and prevent crime. An example is crime mapping software that integrates with resource allocation systems. Another example is a GPS-based system used to track suspects and the locations of police vehicles.
Social media can disseminate information about persons sought for questioning and ask the public for tips. Social media also frequently becomes part of the digital evidence of a case.
To cross-check data accuracy against billions of public records, agencies use the CLEAR system to help with active investigations.
4. Officer accountability and community trust
Video recording has become a vital tool for monitoring police office accountability. This equipment includes in-dash vehicle cams and wearable officer cams. Advanced systems use wireless streaming to send an encrypted signal back to the base for real-time monitoring with artificial intelligence (AI) driven software.
The AI monitors all incoming video feeds to compare the images to its visual imagery database for trigger matches, such as the facial recognition of a known criminal suspect. The AI-driven system triggers appropriate human intervention when identifying suspicious video content.
5. Adoption of new law enforcement technology
Police agencies rapidly adopt new technologies to identify crime using artificial intelligence (AI). One technique is to collect social media, analyze it for inter-personal connections, cross-reference this data with private data, and create a person’s profile that might identify those who may pose a risk.
However, one problem is the inaccuracy and inherent bias of the AI systems. Facial recognition does not work equally as well on people of different skin color. It has a significantly poorer success rate with the faces of people of color. A suspect wrongly identified by an AI system might experience significant and unwarranted coercive action, such as being arrested and detained without justification.
Despite the problems with AI-driven technology, law enforcement will increasingly use these systems.
The future of law enforcement technology
The law enforcement agency of the future might use automation to answer and dispatch 9-1-1 calls. It may have autonomous police vehicles and AI robots for patrols with potentially dangerous encounters. It may use biometric monitoring for human officers’ health and safety. Officers may use smartphone apps to link over the Internet of Things (IoT) with smart city centers for real-time monitoring.
Law enforcement agencies can get the data accuracy needed by using CLEAR investigation software to work with the vast trove of public records while conducting investigations.