The accuracy of facial recognition tools has improved by leaps and bounds in recent years, but according to experts, it may be impossible to fully remedy the technology’s demographic bias.
Facial recognition tools tend to work less effectively for women, people of color and the elderly, but those demographic differences are shrinking as the technology improves, according to Charles Romine, director of the Information Technology Lab at the National Institute of Standards and Technology.
In 2017, NIST expanded a program to help government vendors test and improve their facial recognition systems, and algorithms’ overall performance has made “significant progress” since then, Romine said. Though accuracy still varies widely from system to system, he said, some of today’s best algorithms correctly identifying subjects some 99.7% of the time.
But while a rising tide lifts all boats, Romine said, technologists may never be able to build a system that identifies every type of person with the same level of accuracy.
“It’s unlikely that we will ever achieve a point where every single demographic is identical in performance across the board, whether that’s age, race or sex,” he told the House Homeland Security Committee on Tuesday. “We want to know just exactly how much the difference is.”
Today, NIST is finalizing a report on demographic differences in facial recognition based on data collected during their vendor testing program. Romine told the committee the results will be released sometime this fall.
Romine joined a trio of Homeland Security Department officials discuss the scope and scale of the agency’s efforts to use facial recognition and other biometric technology. While some lawmakers were interested in the technical limitations of the tools, much of the hearing revol ..
Support the originator by clicking the read the rest link below.
