The traditional emphasis of law enforcement has been to apprehend criminals. However, the advent of new technologies – including Open-Source data gathering and analysis, including Artificial Intelligence (AI) applications – has ushered in a new era of unique opportunities to help law enforcement agencies actually prevent crimes.
AI is increasingly being used successfully by law enforcement for high-impact crime prevention measures. New technologies allow overworked and understaffed law enforcement agencies to gather, process, analyze, and highlight relevant data for investigators of any and all types of crime. This includes AI solutions for gathering and interpreting connections and patterns in financial records, geospatial imagery, surveillance camera footage, social media data, public records, news feeds, and many other open and proprietary sources.
One of the most useful applications of AI for preventing and lowering crime is in resource allocation. Since virtually all law enforcement agencies are challenged by shortages of personnel, and funds, the value and importance of resource allocations and deployments plays a vital role in crime prevention. Sophisticated algorithms have been demonstrably proven to have rapid, high-impact success in helping criminal justice organizations better understand the “who, what, when, where, how, and why” of crime in their jurisdictions. AI can determine and identify relevant patterns of crime that can best be addressed through adjustment in resource allocations such as timing of police car patrols, walking patrols, security guards, physical barriers, alarms, or the response times of emergency services and First Responders. Patterns may reflect seasonal, geographical, or demographic trends that are rapidly identified from all-source intelligence analysis powered by AI, in ways that cannot be obtained from traditional analytic means.
Another application of AI for crime prevention analyzes metadata to examine the efficacy of crime prevention efforts. Various campaigns have been conducted globally to combat a host of illegal activities, including serious violent crimes and the trafficking of humans, drugs, and weapons. Given the range, scope, and sheer number of crime prevention programs, determining which efforts work best is a major challenge. The application of sophisticated and well-designed algorithms has helped researchers comb through these mountains of data to get accurate indications of the utility and impact of various crime prevention programs. This type of insight is critical for leveraging AI for optimal crime prevention strategies.
