At the 2024 Local Government Reimagined Conference in Palm Desert, Thomas Wieczorek, director of the Center for Public Safety Management, shared with attendees the strides that AI is making in local government in assisting with emergency medical services (EMS). 

In the United States, the state of EMS systems is described as “in critical condition” and continues to struggle. Emergency call centers are severally understaffed, with low pay adding to the issue of filling vacancies.

Thirty percent of EMT positions in large cities such as Chicago remain vacant, with 47% of jobs at emergency dispatch centers across the United States on average being unfilled. With police officer hiring in the country only making an uptick in 2023 after years of decline in the force, and only a small increase of 100,000 officers joining the ranks across the country, communities have started to look to AI to fill the void in emergency services.

Cities such as Arlington, Virginia, have implemented AI to assist with their emergency switchboards, making emergency call centers more efficient. Using Amazon Web Services, the city has been able to resolve problems such as unanswered calls being hung up on after 30 seconds, allowing the call to ring until answered. EMS workers monitor body camera video and audio. Having the audio in review allows EMS to make sure first responders are taking appropriate procedures and that patients are treated accordingly. In addition, AI allows dispatch to work from home, creating a greater incentive for potential emergency dispatch workers.

Crime prediction, traffic prediction, and live crime reporting has also benefited from the integration of AI and the human workforce. EMS is able to conduct heat mapping in potentially crime-ridden areas to prevent crimes in progress. By following patterns of behavior, such as an increase in unusual activity occuring in one area, EMS can help prevent and alleviate crime. Investigators can also use AI to share crime patterns nationally to better understand and identify criminal behaviors and possibly stop crime before it happens.

In Arlington, AI was also used to break down silos in reporting crime. AI was used to identify minor incidents and cut down on human labor by dividing the reports by what could be reported online. Non-urgent incidents have reports generated online by AI, giving investigators more time to handle urgent reports.

With AI creating time-saving measures for EMS and predicative algorithms and maps for crime, local government continues to look for ways to utilize this technology to its fullest potential.

Learn more about AI for local government on ICMA's Generative AI resource page.