Artificial intelligence (AI) is rapidly transforming how businesses operate. Law enforcement is no exception. Federal agencies are adopting and integrating AI capabilities although slower than some desire. Understanding AI's impact on data management, discovering crucial insights, and processing efficiency are essential to AI implementation. With AI still glimmering with some newness, educating users about its value to government agencies is essential.
From enhancing investigative efficiency to addressing national security threats, AI offers extensive opportunities for police departments and federal agencies to streamline operations and discover critical insights for investigations faster than ever before.
The current landscape of AI in law enforcement is evolving quickly.
Today, AI technology is utilized in various ways across law enforcement agencies to increase security measures and process improvement and is critical in data-heavy environments.
Here are a few of the well-known use cases for AI in law enforcement:
- Predictive Policing: Using historical data and algorithms to predict potential criminal activities and allocate resources accordingly.
- Facial Recognition: Identifying suspects and missing persons by matching images from surveillance footage against databases.
- Crime Mapping: Visualizing crime patterns to help law enforcement agencies focus on high-risk areas.
While these law enforcement AI applications have been around for years, the use of AI for more complex crimes like human trafficking and counterterrorism has not kept the same pace.
The power of AI lies in its ability to process and analyze vast amounts of data swiftly, which is invaluable to law enforcement.
AI helps find criminals faster.
Law enforcement agencies face the same problem large companies and other national security entities battle – an overload of data that produces an analytic burden, resulting in missed insights.
AI tools quickly process and analyze extensive amounts of data, helping law enforcement agencies reveal critical insights that are inaccessible through traditional methods. In specific cases like human trafficking and exploitation, AI is pivotal in identifying patterns and networks used by criminals. Take human trafficking, for example. It is often tightly intertwined with other forms of crime like drug trafficking and money laundering, and AI is crucial in understanding these complex networks. Simply put, AI helps investigators find criminals faster, which ultimately limits harm.
Here are a few examples of how AI can benefit complex investigations:
- Handling Massive Data Volumes: Some AI platforms, like Accrete’s Argus, can process and tag vast amounts of data, reducing the need for manual data entry and analysis. Allowing the subject matter experts to direct their attention to more pressing issues.
- Combining Siloed Data Sources: AI can integrate data from different sources, providing a holistic view of the situation and reducing the "swivel chair" effect, where analysts switch between systems to piece together information.
- Empowering Human Analysts: Instead of replacing human analysts, AI augments their capabilities, allowing them to make more informed decisions and focus on complex tasks that require human judgment.
- Faster Crime Resolution: AI can automatically analyze data to identify patterns and connections, helping investigators solve cases more rapidly and efficiently.
A path forward with AI requires human intellect.
Law enforcement professionals are trained with specific skill sets and have on-the-job experience and intuition that cannot be replicated. AI is simply an amplification tool for these human characteristics and training. AI applied to investigations is a much faster way to streamline the data required for the job. The first step to adopting AI into investigative processes is to understand that AI must be trained, customized, and run by subject matter experts.
Here are a few other several steps needed for successful AI integration:
- Education and Training: Law enforcement personnel need to understand AI technology and its implications fully.
- Collaborative Partnerships: Building partnerships between law enforcement agencies, AI companies, and academic institutions can facilitate sharing of knowledge and best practices.
- Transparent AI Systems: Transparent and explainable AI systems can help build trust and ensure that AI-generated insights are reliable and accurate.
- Embrace Ethical AI Development: AI systems must be designed and implemented with ethical considerations, ensuring they respect human rights and civil liberties.
AI presents a unique opportunity for law enforcement agencies to enhance their investigative capabilities and effectively address national security threats. It's time for agencies to explore AI's potential and lead the way toward a future where technology and human expertise work hand in hand to maintain public safety.