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Can AI Help Cities With 911 Staff Shortages?

A government call center in California is among those grappling with the nationwide staffing shortage and an influx in demand, and implementing artificial intelligence tools to improve wait times and accessibility for callers.

Large cities in California and elsewhere are looking to artificial intelligence to combat call center staffing shortages and a backlog of resident calls.

The ongoing U.S. staffing crisis has impacted the workforce across many organizations in what has been dubbed the “Great Resignation.” No sector seems immune; 911 centers have been facing severe shortages that are causing both mistakes and delays in some areas.
A desk phone and attached headset.

Some call centers, however, see AI as a way to bridge the gap between callers and the services they seek.

The city of San Jose is farther along with its use of AI to address call center challenges, with the city’s multiyear effort to improve the 311 experience well underway.

Over the last year, the city has worked to reduce 911 call times by routing non-emergency calls to the Customer Contact Center. However, this adjustment increased the workload for the center.

By adding Google’s Dialogflow AI-based virtual agent to sort incoming calls and route them to the proper channel, the city was able to free up human call takers for more complex requests.

AI now acts as a touch point for high-volume calls and can answer simple questions. For example, if a resident wants to connect to the trash pickup channel or enter a request for junk removal, they can do so without having to talk to someone, freeing up call takers for requests that require more back-and-forth communication.

The key to successful implementation was having a road map of the city’s goals and the support of city leadership, explained German Sedano, project manager for IT products.

A major need of the city was language translation, according to Arti Tangri, a data architect with the city’s IT department who has been working on the 311 project since the beginning of the pandemic. Now, real-time translation is available for requests in two languages, with the potential to add other languages in the future.

Between 16 and 17 percent of the city’s population have limited English proficiency, so public response to the language translation piece has been positive, Sedano said.

Tangri said the process of training the model involved input of over 1,000 translation pairs. The team used localized, customer-specific terms to improve accuracy.

In regard to spreading public awareness about the AI tool, Sedano noted the significance of a marketing campaign that was conducted through channels like community outreach, mailed flyers, radio and more.

“We’re never going to lose our human touch,” said Kia O’Hara, program manager for the SJ 311 Customer Contact Center. “Even though artificial intelligence is great, we do note that it does have its issues, and so these [tools] will never replace our live agents.”

As Sedano noted, meeting the increased demand on call centers is a journey. As the capabilities of available technology evolve, the city will evolve with them, Tangri said.

A longer version of this article first appeared in Government Technology magazine, sister publication of Techwire.
Julia Edinger is a staff writer for Government Technology. She has a bachelor's degree in English from the University of Toledo and has since worked in publishing and media. She's currently located in Southern California.