Home Artificial Intelligence Manhattan high schooler creates astoundingly accurate AI algorithm that predicts resources needed for 911 calls

Manhattan high schooler creates astoundingly accurate AI algorithm that predicts resources needed for 911 calls

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A Manhattan high schooler has designed an AI algorithm to help 911 callers get the aid they actually need — which would, in turn, cut down on response times and eventually save cities millions, he told The Post.

Pierce Wright — a soft-spoken 17-year-old junior at The Browning School in Manhattan — said his intricate model could assist emergency dispatchers by, for instance, predicting when a caller is enduring a mental health episode.

“If the algorithm says, ‘I think it’s a mental health call,’ then you can send a psychiatrist or a mental health professional with the EMS crew to assist the patient and provide the more appropriate care” — instead of simply rushing police to the scene, Wright said in a Wednesday interview.

Pierce Wright, 17, has invented an AI model that correctly predicts what kind of resources will be needed on a given 911 call. Gabriella Bass

“It’s saving time for the patient — and the city as well,” he said. “And it’s also able to free up an ambulance much faster.”

To design the algorithm, Wright combined his experience as an EMS worker with his data science prowess.

He spent the past year painstakingly coding the AI, then training it with nearly two decades’ worth of statistics gleaned from New York City’s massive online database of about 24 million emergency calls.

His work paid off, he says, because his model can predict what resources are needed based solely on factors such as the incoming call’s zip code, time of day, police precinct and initial severity level.

The kicker? The model has an uncanny 94.5% success rate — 2.2% higher than its human counterparts, he said.

Wright has already won several accolades for the model, which he says is correct 94.5% of the time. Gabriella Bass
The model could eventually improve responses and save cities millions, he said. Gabriella Bass

“You need very little input from the actual caller,” Wright said as he sat at a table in his family’s Upper East Side dining room, which overlooks Park Avenue.

“You can really just say, ‘This is what it looks like.’ And the 911 operator has the zip code, police precinct, time of day, etc. They put that all in there, and in a couple of seconds, the model outputs what it believes the call will be within about 94% accuracy,” he continued.

“It essentially predicts … what it believes the call will be,” the teen said. “Based off that, you can send the appropriate response.”

The model is 2.2% more accurate than human dispatchers, Wright said. Gabriella Bass

Wright said he was inspired to create the program after fielding calls on his own shifts as a volunteer EMS worker in Westport, Connecticut.

Many times, the crew was sent to respond to what turned out to be a mental health or substance abuse call — not the true medical emergencies for which they are trained, he said.

It’s also not helpful to the patient, who is often brought to a local emergency room and left to languish.

“That’s not providing care for the patient, and it’s also wasting the resources of the city,” he said, adding that his model would help eliminate patients “waiting at a hospital just to be let out.”

Wright is also a volunteer emergency medical responder in Westport, Connecticut. Gabriella Bass
The adaptable model can be used for mental health calls or a variety of other things, he said. Gabriella Bass

Wright’s mom, Melanie, marveled at her son’s ability to put in the mammoth amount of work needed to create the model.

“I was like, ‘I just I hope it works,’” she said with a laugh. “Because I would hate for him to feel like he put all this time into something, and it didn’t work!”

“But it was so thrilling — seeing those light-bulb moments when he would have a breakthrough,” she added. “And that would carry him into the next phase.”

Wright said his program can also be used for other kinds of emergency calls — for instance, if the model thinks a victim has suffered trauma, it could prepare to dispatch a paramedic instead of only EMTs.

Still, the creator was quick to say the program is meant to help dispatchers, not replace them.

But one day — after he makes it more customizable and accessible to the average person — the model could save cities millions of dollars and drastically cut down on response times, he said.

Wright at the TerraNYC STEM Fair, where he placed first for his medicine and health sciences project. Wright Family

The remarkable project — which took about 200 hours to complete — has already earned the studious teen several accolades, including a first-place prize at the TerraNYC STEM Fair at New York University’s Tandon School of Engineering on April 7 and a second-place trophy at the New York State Science and Engineering Fair in Queens.

And it could connect to his future career — even though he’s not sure what that will be just yet.

Wright said he’d like to eventually work in either public health, computer science or some mixture of both.

“Whatever I decide to do, I’m really just looking to be able to create something that can help people,” he said.

“That is definitely my goal.”


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4/17/24



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