By Rohan Galloway-Dawkins
Public safety agencies are in a time of significant change brought about by industry-wide challenges in service to their communities. Local and state agencies face staff recruitment and retention obstacles, declining public perception of police, and legacy processes that can’t meet the needs of an increasingly digital world.
At the same time, new technologies are emerging to address these challenges, particularly artificial intelligence (AI), which has become impossible to ignore over the last year. In a Deloitte survey of 2,620 global business leaders, an overwhelming 94% reported that AI will be critical to their success over the next five years. As AI remains at the top of business leaders’ minds, public safety professionals must also explore potential applications to meet their community members’ service expectations while understanding the principles of successful usage.
AI transforms engagement for community members, agency staff
While the public safety industry is often rife with hyperboles of revolutionary technologies, agencies can realize meaningful outcomes through the innovative use of AI. One key area where AI can make an impact is the handling of non-emergency reports.
Non-emergency calls and service requests represent a significant workload for call centers, patrol officers and investigators. Due to reduced staffing and limited hours of operation across all departments, many governments have shifted their off-hour call loads to Public Safety Answering Points (PSAPs) since they are staffed 24/7. The number of lower-priority calls on these phone lines can overwhelm operators. Agency leaders can consider introducing Conversational AI-powered virtual investigators that can augment short-handed communications centers by triaging non-emergency calls and managing the non-emergency reporting from community members via web or text.
Conversational AI allows non-emergency reporting parties to quickly and easily explain their situation in their own words. Based on this information, callers are routed to the appropriate resource to respond to the need. To help prevent oversights, the intelligent triage system will also help recognize if a situation is an actual emergency that requires immediate escalation to a human operator for assistance. This workflow ensures that true emergencies are prioritized and promptly addressed, significantly reducing the risk of overlooked critical incidents. If critical situations, such as lives in danger, weapons, or immediate threats, are mentioned, the system tells the caller to dial 9-1-1.
Once the initial call triage determines a non-emergency situation, the conversation seamlessly transitions to an online platform. Through Natural Language Processing (NLP), the virtual investigators will process the community members’ explanations, ask clarifying questions, and capture all relevant information needed to file a complete report in compliance with the National Incident-Based Reporting System (NIBRS) or Canadian Centre for Justice Statistics (CCJS) standards. This technology also facilitates better communication — and multilingual support — with the public by answering frequently asked questions, providing updates, and guiding individuals through service requests, reducing the burden on human operators and ensuring consistent communication.
The guided call process facilitated by conversational AI reduces hold times and improves call resolution. This automation substantially decreases administrative call volumes, allowing agents to work more efficiently and effectively. The result is almost instant access to the help or resources that the public needs, including priority needs.
To this end, leveraging AI represents a win-win for agencies and the community. Non-emergency reporting parties appreciate the prompt response and having another convenient way of interacting with local law enforcement, improving public perception of police work. For agency personnel, the technology reduces the workload on operators and frees their capacity to address emergencies and prioritize the safety and well-being of all community members.
Top considerations for successful AI implementations
Fears may persist about AI displacing agency staff. While AI can augment low-risk, repetitive tasks, human intuition and decision-making are irreplaceable. Public safety requires managing unpredictable human behaviors and making nuanced judgments, which AI cannot fully replicate. Effective public safety work also depends on strong communication skills, empathy, and moral judgments, often demanding quick thinking and adaptability. Successful implementations integrate AI as a supportive tool intended to expand communication options to the public and enhance agency services.
While AI will not replace public safety staff in the near future, it will continue to augment humans with unique skill sets. By actively involving personnel and addressing their concerns, we can create a collaborative environment where AI is seen as a valuable tool rather than a threat. To alleviate fears of job displacement, it’s important to emphasize that AI complements human abilities, handling repetitive tasks and freeing public safety staff to focus on complex work requiring creativity and emotional intelligence.
Transparent communication about AI’s impact on daily operations and roles helps reduce uncertainty and foster understanding. Investing in training programs ensures that staff can adapt to new roles and remain competitive in an AI-driven landscape. Inclusive decision-making, through feedback sessions and discussions, allows staff to voice concerns and contribute to the AI integration process, making them feel included and valued.
Agencies should focus on purposeful AI integrations with targeted, specific outcomes. For instance, large language models (LLMs) can rapidly identify patterns between datasets, enabling accelerated, large-scale data analysis that would otherwise take human investigators weeks or months. As agencies must now deal with more information than ever, orienting LLMs to support crime prevention and detection can empower more just outcomes for their community.
Prioritizing the accuracy and security of AI in public safety is also critical, as the nature of police work involves sensitive data. AI technology must inherit this responsibility and operate within the highest security standards. Like other computer systems, conversational AI systems require adherence to high software development and environment management standards to ensure all necessary controls are in place. This includes implementing robust network security, stringent access control, and comprehensive testing and monitoring protocols for public service agencies. The risk of data breaches and privacy issues are also real threats that have implications for the safety and well-being of agencies’ communities. Leaders must adopt a proactive stance on security and work with their solution vendors to fortify their digital infrastructure as AI technology evolves.
Developing clear guidelines for AI use, regularly auditing systems for biases, and making necessary adjustments are important steps for ethical implementation. Community involvement is also key - engaging with the public to explain AI’s benefits and address concerns directly can build trust. Training and education for public safety staff and the community about AI’s role and limitations are vital to enhancing understanding and acceptance.
Successful implementations — the ones that will make a real difference — will center on people and creating safer, more secure, and better-prepared communities.
Conversational AI might need distinct or additional education compared to generative AI. To ensure the public feels secure with AI, laws that set clear ethical guidelines and follow data protection laws are important. Regular security checks and highlighting AI’s benefits of making services more efficient can help build public trust. Highlighting AI’s benefits is how it can make services more efficient, improve decision-making, and enhance public services.
AI and the future
Some public safety technology companies use agency feedback to continually improve their systems, which helps the company design solutions responsive to the agency’s and community’s needs as they become more comfortable with AI.
AI still faces skepticism, and people will need time to become comfortable with it. AI is a tool. Like any tool, it excels at specific tasks while less suited to others. Over time, AI will likely be able to handle a broader range of situations, but human interactions will remain important in critical situations.
As forward-thinking agencies explore and embrace AI’s possibilities, it is essential to remember that technology is not the sole driver of change. Public safety requires managing unpredictable human behaviors and making nuanced judgments, which AI cannot fully replicate.
Conversational AI can significantly enhance efficiency and effectiveness in law enforcement. The technology can bolster community safety by improving crime detection and prevention, optimizing resource allocation, and enabling quicker response times.
AI will evolve through customer feedback. The technology will be adapted to address today’s challenges and the public’s needs in the future. By addressing ethical concerns, involving the community, and ensuring clear communication, AI can help build trust and strengthen the relationship between public safety agencies and the communities they serve.
About the author
Rohan Galloway-Dawkins is the Chief Product Officer at Versaterm and is responsible for developing an ecosystem of solutions focused on improving workflows for more efficient and effective operations, better service, and more just outcomes. Galloway-Dawkins joined Versaterm in February 2022 and brings 19+ years of experience in the public safety communications and software solutions industry. Before joining Versaterm, Galloway-Dawkins started his career at Motorola in 2005. He was instrumental in developing Motorola’s Command Central public safety solutions and driving the company’s shift toward software-centric operations.