Human Versus Machine: NIST Study Investigates AI’s Role in Forensic Face Recognition

 In Forensic Science

The debate of human versus machine continues to increase with rapidly changing technology. A new study by the National Institute of Standards and Technology confronts this conflict head-on with an investigation of accuracy in forensic face examination.

A photo from a security camera can play a critical role in criminal cases, determining the fate of the suspect. Trained forensic face examiners provide courtroom testimony, informing a jury whether that still image actually represents the accused.

NIST researchers and three university partners have combined the disciplines of forensic science, psychology and computer vision to determine just how good facial recognition experts really are. For the first time, researchers reveal the science behind the work of forensic face examiners, and raise the question of artificial intelligence’s role.

Researchers at NIST and organizations like CSAFE have revealed that algorithm performance has steadily increased over the past few years, and has valuable applications to forensic investigations. When comparing algorithms to human experts, the NIST study showed the highest accuracy in facial recognition was achieved with a collaboration of both the strengths of a human and a machine.

As a NIST Center of Excellence, CSAFE uses similar algorithmic approaches in other forensic disciplines to develop new tools to come alongside the human experts. Explore how our team is working to improve evidence analysis accuracy using algorithms in the comparison of cartridge cases and bullets.



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