FIRST RESPONDERSArtificial Intelligence Means Better, Faster and More for First Responders

Artificial intelligence (AI) and machine learning (ML) hold tremendous potential to enable first responders to better process information and drive faster and more precise response. However, these capabilities present certain risks. The Science and Technology Directorate (S&T) is working diligently to identify the best ways to help the responder community strike that balance, while incorporating AI in a meaningful way into technologies used in daily operations.

The appeal of applying AI to emergency operations is that these emerging technologies offer advanced capabilities to process information faster and enhance decision making. S&T is taking a multi-disciplined research and development (R&D) approach where AI is concerned; this means consulting directly with first responder stakeholders to gather their operational needs, as well as identifying ways to leverage cutting-edge sensors and communications channels to provide clear, quick and actionable data to establish accurate situational awareness. 

For instance, S&T is partnering with the WIFIRE Edge program at the University of California in San Diego, providing technologies to support generation of high-resolution information on the fire environment, where weather and location information can quickly change. Development of AI/ML technologies alongside Homeland Security Investigations (HSI) contributed to Operation Renewed Hope in 2023, which resulted in the identification and rescue of 311 previously unknown victims of sexual exploitation from active abuse and the arrests of suspected perpetrators. S&T also developed AI-based tools for HSI to help counter the flow of fentanyl, which the agency says contributed to a 50% increase in seizures and 8% increase in arrests. 

S&T aims to apply lessons learned from these successes by providing AI-based tools to aid law enforcement and first responders nationally. 

“We’re looking at decision support tools with the human-in the-loop, because our responders are pretty confident that they do not want to turn it all over to AI yet,” said First Responder Portfolio Manager Paul McDonagh. “With the rapid increase in capabilities, we are adjusting to the needs of our customers and their demands.”

Assessing the Needs of Those on the Frontline
S&T is currently gathering requirements to inform a gap analysis that will soon be published, entitled: “Gap Decomposition: Automated Alert and Execution System for Responders,” that recommended two phases of AI/ML development activities in support of first responders.