Calling 911 has traditionally meant one thing: Somewhere on the other end of the line, a human being answers.
New Orleans is experimenting with a somewhat different arrangement.
The Orleans Parish Communication District is introducing artificial intelligence into its emergency communications system in an effort to identify duplicate reports and keep human dispatchers available for callers who actually need them, according to the Shreveport Times and WVUE-TV.
To be clear, New Orleans isn’t handing emergency dispatch entirely over to a chatbot. The AI is being used as a triage system, determining when certain calls appear to concern incidents that have already been reported and routing callers accordingly.
Still, when you’re dealing with 911, even putting an algorithm between a caller and a human dispatcher is going to attract attention.
New Orleans began using AI this spring on its non-emergency 311 line. The technology is now being expanded into an agency receiving roughly 1,000 calls each day.
One system, Carbyne’s AI Emergency Call Triage, attempts to identify multiple calls concerning the same incident. If the system determines that someone is reporting an event already known to dispatchers, that caller can receive an automated response. If the call appears to involve a new incident, it is transferred to a human.
The problem the city is trying to solve isn’t difficult to understand.
“If somebody calls about a relative having a heart attack, when that call is coming in, we don’t know what it is,” OPCD Executive Director Karl Fasold explained.
Calls normally arrive in order. When dispatchers are available, they answer. When they aren’t, callers wait.
That becomes particularly problematic during sudden surges.
A single traffic accident during rush hour might generate 20 separate 911 calls, Fasold said. Every person may be reporting exactly the same crash while another caller with a completely unrelated emergency is stuck waiting for someone to answer.
“You can’t really staff for those occurrences of surges,” Fasold said. “It’s impossible, both fiscally and practically.”
That’s where the AI comes in.
According to Fasold, the system can determine whether a caller is within approximately 200 meters of a location where dispatchers already know an accident has occurred. If so, AI can handle the duplicate report rather than requiring another dispatcher to spend time processing the same information.
“With the AI handling your incoming calls about the [motor vehicle accident], you get instant service,” Fasold said.
The theory is straightforward enough: Let software deal with the twentieth report of the same wreck so the available human can answer the person calling about a heart attack.
But New Orleans isn’t the only city experimenting with AI inside emergency response systems, and experiences elsewhere illustrate why the technology deserves scrutiny.
Seattle has used AI-assisted technology for roughly two years. Its fire department uses the system as part of determining how certain medical calls should be handled, including whether some callers can be directed to a nurse-staffed call center in Texas rather than receiving the fastest emergency response.
That has raised transparency concerns.
“The potential that this company could be a part of the experience that Seattle 911 callers have and they don’t know it, that raises serious concerns,” University of Washington law professor Ryan Calo told the Seattle Times.
“I’m troubled on a number of levels.”
Seattle officials and the technology provider emphasize that AI doesn’t get the final word.
“The dispatcher still has the ultimate authority,” Seattle Fire Department Assistant Chief Chris Lombard said.
Corti, which supplies the technology used by Seattle, similarly said that every final determination is made by a trained dispatcher operating under fire department protocols.
“Corti’s role is to support that work, not replace or override clinical judgment,” a company representative said.
That’s an important safeguard, but it also points directly to the question cities adopting these systems will have to answer.
AI doesn’t have to replace a 911 dispatcher to influence what happens after someone calls.
If software helps determine whether a report is a duplicate, whether a caller reaches a dispatcher or whether a medical situation should be routed elsewhere, then it has become part of a chain of decisions where mistakes can carry considerably greater consequences than a bad restaurant recommendation or an incorrect chatbot response.
There is a compelling argument for using technology to eliminate obvious duplication. Having trained emergency personnel repeatedly process 20 reports of the same fender-bender while other callers wait isn’t an efficient use of limited resources.
The test will come with the unusual cases — the caller standing near an existing accident who is actually reporting something different, the poorly explained emergency that doesn’t fit the algorithm’s assumptions, or the situation that sounds routine until a human begins asking the right questions.
That is why the most important feature of these systems may not be how sophisticated the AI becomes.
It is how quickly a human being can take over when the computer gets it wrong.
