Unlike humans in law enforcement, AI technology doesn’t get tired, let emotions fog its judgment, work on “a hunch,” or make mistakes (unless components or the human who programmed it caused the error). Those reasons alone make a case for the government to consider taking the next big step in terms of using AI to prevent and solve crimes.
We’ve asked our in-house experts to identify 3 ways in which AI will eventually be used by police to solve crimes:
1) Rapid database scanning
Remember the old days when detectives had nothing but mounds of physical files to sift through when attempting to solve crimes? Imagine the hours spent combing through paperwork, all while assailants were putting distance between themselves and the crime.
Although law enforcement networks are certainly more connected and streamlined than in the past, there’s massive room for improvement in terms of automation. For example, the Integrated Automated Fingerprint Identification System (IAFIS) maintains the largest biometric database in the world, containing the fingerprints and corresponding criminal history information for more than 55 million subjects. Not bad, right? However, it takes up to 24 hours for agencies to receive responses on civil fingerprint submissions. With a world-class AI system in place, processes that take hours or days can be reduced to seconds—and every second counts in crime.
2) Facial recognition
Has a social media application has ever identified you in a photo, based on facial recognition alone? Once your face is “in the system,” advanced algorithms can recognize you with remarkable precision. Facial key points are detected and the best facial recognition application can identify you with up to 97% accuracy.
Combining AI, deep learning and IoT, facial recognition technology is now being marketed to law enforcement for video surveillance. Since it’s already demonstrated the ability to identify escaped convicts who appear on security cameras while on the run, police departments are certainly showing interest.
Amazon’s facial recognition software can track individuals in a video even when their faces aren’t visible. Detractors identify this as a major surveillance issue that goes beyond catching bad guys. They’re concerned that AI-enabled facial recognition capabilities will be used as government mass surveillance tools for tracking innocent citizens.
3) Cognitive crime scene investigation
One problem with crime scenes, in terms of forensics, is that they eventually become contaminated and restored. At the risk of sounding morbid, blood is cleaned up, bodies are removed and people can eventually walk freely through the space again. Traditional 2D video of the original crime scene is helpful for future study, but it doesn’t provide a fully immersive or high-sensory experience.
Imagine detectives transporting back to the scene of a horrific murder and being fully immersed in it—days, weeks or years later. Powered by AI software and VR headsets, what sounds like a video game scenario can become a high-sensory, crime-solving reality. At the original crime scene, 360° VR-enabled cameras would record comprehensive 3D video that enable detectives to actually return to the scene of the crime like never before.
If you care about AI, you probably care about IoT. Here are 4 IoT assumptions that consumers get wrong.