Emerging Issues in Security

Artificial Intelligence Makes a Vital Contribution to Security

The debate over the danger of impending doom from artificial intelligence (AI) rages on, but AI or machine learning is already being applied and developed across several security technologies.

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While the chief executive of electric-car maker Tesla, Inc., and rocket maker Space Exploration Technologies Corporation, Elon Musk, and Facebook CEO, Mark Zuckerberg, go at it with different views on the benefits of AI, the security industry offers some real-world applications.

First, let’s get to the drama between the billionaires. Last month, at the U.S. National Governors Association in Rhode Island, Musk warned about the future of AI and laid out several worst-case scenarios. The technology will threaten all human jobs and could even spark a war, according to Musk. “I have exposure to the very cutting edge AI, and I think people should be really concerned about it,” he said.

“I keep sounding the alarm bell, but until people see robots going down the street killing people, they don’t know how to react, because it seems so ethereal,” Musk continued. “AI is a fundamental risk to the existence of human civilization.”

A few days later, on Facebook Live, Zuckerberg offered his views on AI in a response to a viewer’s question on the subject. “I have pretty strong opinions on this,” Zuckerberg said. “I am optimistic. And I think people who are naysayers and try to drum up these doomsday scenarios—I just, I don’t understand it. It’s really negative and in some ways I actually think it is pretty irresponsible.”

Whether robots scare the wits out of you or they can or cannot swim, the fact remains that AI is already being successfully used in security applications. Advanced AI capabilities train devices to gather, analyze, and retain information similar to the human brain.

AI is a powerful tool that significantly reduces the time and manpower needed to search surveillance footage. AI sorts through hours of video data and quickly locates images of suspects and other persons of interest across all cameras connected to a network.

One of the fastest-growing areas in AI is analyzing video content. Machine learning in video surveillance applications enables computers to interpret large amounts of data in the form of images, sound, and text with improved accuracy and speed. AI automatically identifies and detects problematic and criminal behavior as it happens.

Beyond forensic benefits, intelligent video analysis capabilities make site security more effective and efficient by receiving detailed information to determine the proper response to anything from public intoxication to trespassing. A variety of capabilities include crowd density monitoring, facial recognition, people counting, behavior analysis to monitor criminal behavior before it takes place, license plate recognition, and detection of suspicious or illegally parked vehicles.

AI recognizes a trained pattern that may be associated with a crime like casing a joint, people hanging around where they should not be, someone looking into back entrances to buildings, etc. In an example using facial recognition, AI can compare objects with hundreds and thousands of stored images to detect gender, whether a subject is wearing glasses, age range, or specific clothing, etc., and, basically, find anything.