As facial recognition technology grows more affordable and advanced, casinos are increasingly using it to detect potential threats, as an increasing number of venues in Las Vegas are implementing the technology.
Why Are Casinos Adopting Facial Recognition?
Casinos typically operate hundreds of cameras across large properties, making it impossible for human staff to monitor and identify every potential issue in real time. Mehmet Erdem, a hospitality professor at the University of Nevada, Las Vegas, explained that such software is used more frequently in places where a large amount of money is being transferred, such as casinos.
He also said that facial recognition software can interpret behavioral cues, including a person’s mood and whether a player appears happy or upset. Erdem added that if someone is about to start a fight or brandishes a gun, the system should immediately alert security, potentially preventing the situation from escalating into something undesirable.
Many companies are working on facial recognition tech as well. One of them, Xallient, made headlines last year when it revealed its intent to put its software into slot machines. The company claimed this could improve casino operations and provide real-time tracking of the players who are targeted by the casino.
What Potential Issues Could Such Systems Have?
George Bebis, director of the University of Nevada, Reno’s Computer Vision Laboratory, believes the technology has value, but notes that casinos are not ideal environments for precise identification. He explained that comparisons are often made using low-resolution security footage captured in poor lighting conditions.
Bebis also explained that a human should still always be present in the process. He stated that once an AI system flags an individual, a verification process must follow, and it should be conducted by an expert rather than a security employee or a responding police officer. He added that only a forensic investigator specializing in facial recognition can reliably determine whether a software-generated match is accurate.
Cases where a facial recognition system has wrongfully flagged a person are not unheard of. Such is the case of a Reno truck driver who was arrested back in 2023 when the system of the Peppermill Casino in Reno, Nevada, matched him as someone who had previously been banned from the property.
Despite such cases and concerns pointed out by his colleagues, Erdem noted that human judgment could produce even more errors, despite the software inevitably producing false positives. He pointed out that there are numerous cases in which juries have wrongly convicted individuals based on eyewitness testimony, adding that humans tend to make more mistakes than technology.
