UnitedHealthcare Shooter Caught Thanks to Video Surveillance Technology
In the early hours of December 4th, the CEO of UnitedHealthcare, Brian Thompson, was shot on his way to a shareholder meeting in Midtown Manhattan. The shooting has since gone viral, sparking a heated discussion on the American for-profit health insurance industry and the ethical implications of denying insurance claims for critically necessary medical care.
Despite the relative obscurity of the suspected shooter, the police were able to apprehend 26-year-old Luigi Mangione just five days later at a Pennsylvania McDonald’s–roughly 4.5 hours away from where the shooting took place.
Just a few years ago, a manhunt of this magnitude would have taken weeks, if not months, to resolve. However, thanks to advances in video surveillance technology, the case was cracked in record time.
As surveillance cameras are becoming more and more commonplace, law enforcement officers were able to single out the alleged suspect by combing through surveillance images from street cams, taxis, Starbucks, and a youth hostel. The massive amount of surveillance footage allowed them to share multiple images of the suspect from a variety of angles with the public. Eventually, Mangione was arrested when a McDonald’s employee recognized him from these images and turned him in to authorities. Law enforcement denies advanced facial recognition technology being responsible for the arrest, however, given that the images shared with the public were obtained via video cameras, surveillance technology arguably played a rather large role.
The abundance of footage mapped a video trail of the suspect’s actions in the days leading up to the shooting, allowing police to get a head start on identifying his whereabouts. CNN reports that Mangione arrived in New York City on November 24th, citing images pulled from buses and taxis. They then tracked him to a hostel whose cameras captured a clear image of the suspect’s face during the check-in process. This photo has since gone viral as one of the most important images responsible for Mangione’s identification ans subsequent arrest. Thanks to Starbucks video surveillance and street cam footage, the suspect was tracked making his way towards the scene of the crime on December 4th. The shooting itself was captured on video taken from right outside the Hilton Hotel where Brian Thompson was staying, effectively providing a completely documented scenario that helped speed up law enforcement’s response.
While already a hot-topic, this case has sparked a more intense debate on whether the use of video surveillance, specifically the use of facial recognition and artificial intelligence, to solve crimes constitutes an invasion of privacy. However, on the other side of the debate, the use of this technology can drastically reduce the amount of time potentially dangerous criminals are on the run, which can in turn reduce the likelihood of repeated offenses and potentially save lives.
It is also important to note that this technology is not just limited to catching criminals. Advanced video surveillance, including highly-controversial use of artificial intelligence, has been instrumental in risk prevention in healthcare, education and commercial environments. AI surveillance cameras can provide real-time analysis of potential fall risks in assisted living facilities and send immediate alerts to relevant caregivers and authorities when an accident occurs, saving precious minutes in an emergency situation.
Similarly, with staff shortages plaguing a number of industries, those working alone in dangerous environments can be at risk. This was the case in 2021 when two correctional officers were attacked in two separate incidents within the same prison. While prisons typically have live video monitoring, this proved to be ineffective when it mattered most. Unfortunately, human-monitored surveillance is often too costly to implement 24/7. Additionally, human-powered surveillance means a higher likelihood of human-error which, when combined with already limited manpower from ever-prevalent staff shortages, can lead to dangerous and even deadly outcomes. With AI video surveillance, the risk can be monitored constantly and dangerous scenarios can be automatically flagged, reducing the risk of preventable tragedies from oversight or ignorance.
While it is wise to be wary of intelligent technology systems, particularly those capable of self-learning, using them as a tool to deescalate dangerous situations or reduce risk can do more good than harm. With any advanced technology, surveillance should be used responsibly and results obtained from artificial intelligence should always be questioned, fact-checked, and verified by human experts. If used in this manner, modern advances in surveillance technology can be instrumental in risk mitigation, leading to more positive outcomes in emergency situations.
