Getting away with murder in 2024 isn't easy thanks to the multitude of cameras posted throughout New York City, and the NYPD's specialized task force focused on solving crimes using facial recognition technology.

That's according to Pat Brosnan, a former New York Police Department detective and founder of Brosnan Risk Consultants, LTD, the largest privately-held provider of technology-driven security services. 

Officials are still investigating the murder of UnitedHealthcare CEO Brian Thompson, who was gunned down outside a New York City hotel early Wednesday in what police are calling a "pre-mediated, targeted attack." 

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The NYPD released several surveillance photos shortly after the incident, including images of the perpetrator with a hooded sweatshirt hiding his face, pointing a gun in front of the hotel and then fleeing on an electric bicycle. On Thursday, they posted additional images of someone they are referring to as a "person of interest" they are trying to track down and question. 

But Brosnan is confident that facial recognition technology will play a big role in this case.

Since 2011, he said the NYPD has a dedicated unit, known as the Facial Identification Section, which uses facial recognition technology to compare images from a crime scene or investigation with a database of known individuals, such as mugshots, pistol permit images, and gang member photos.

The "Facial Identification Section has extraordinary modeling software that copy and paste, different lips and eyes, etc., and other facial features to mitigate the mask," Brosnan added.

He said the NYPD leverages the Domain Awareness System, which is composed of numerous physical and software components, including over 18,000 closed-circuit television (CCTV) cameras. 

Not only would criminals have to avoid being captured on thousands of CCTV cameras, but they'd also have to attempt to dodge the "unbelievable array of other cameras, including Amazon trucks, UPS delivery trucks, bus back-up cameras, and an endless amount of private cameras," Brosnan added. 

"New York City is the city of cameras. And of all the places in the country to commit a crime like this, Manhattan would be the dead last location on my list," Brosnan said. 

To underscore this, two hours before the attack, Brosnan said the suspect was picked up on camera near the Frederick Douglass Houses, which is a public housing project located in the borough of Manhattan.

"There was no escaping the unblinking eye of an army of cameras," he said.

The NYPD said on its website that a facial recognition match "does not establish probable cause to arrest or obtain a search warrant." 

However, it provides a valuable lead for additional investigation. If there is a match, the detective handling the case still has to get additional corroborating evidence to confirm the suspect identifies through the photo match is the perpetrator. 

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The NYPD said no one has ever been arrested solely based on a facial recognition search, but when its "used in combination with human analysis and additional investigation, facial recognition technology is a valuable tool in solving crimes and increasing public safety." 

Since the unit's inception, the NYPD has successfully used facial recognition to identify suspects whose images have been captured by cameras during various crimes such as robberies, burglaries, assaults and shootings.

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In 2019, the Facial Identification Section received 9,850 requests for comparison. Out of those requests, the unit identified 2,510 possible matches for suspects. This includes possible matches in 68 murders, 66 rapes, 277 felony assaults, 386 robberies and 525 grand larcenies. 

To date, the NYPD has said they aren't aware of any cases in NYC in which someone was falsely arrested on the basis of a facial recognition match.

Dr. Joan Palmiter Bajorek, the CEO of Clarity AI, argued that "this case is a great testing ground for AI in legislation and law enforcement."

Bajorek said AI has come so far that investigators can go as far as using his posture in the video to try and identify him.