A study by a U.S. agency has found that facial recognition technology often performs unevenly based on a personās race, gender or age.
But the nuanced report published Thursday is unlikely to allay the concerns of critics who worry about bias in face-scanning applications that are increasingly beingĀ adopted by law enforcement, airports and a variety of businesses.
The National Institute of Standards and Technology has been studying facial recognition for nearly two decades, but this is the first time it has investigated demographic differences in how face-scanning algorithms are able to identify people.
The study was prompted in part by growing concern among lawmakers and privacy advocates that biased results in commercial face recognition software could entrench racial discrimination in the criminal justice system and elsewhere.
The report cautions against āincompleteā previous research alleging biased facial recognition that has alarmed the public, but also confirms similar trends showing higher error rates for women, the youngest and oldest people, and for certain racial groups depending on which image database or software is being used.
āThere is a wide range of performance and thereās certainly work to be done,ā said Craig Watson, manager of NISTās research group that studies biometric technology. āThe main message is donāt try to generalize the results across all the technology. Know your use case, the algorithm thatās being used.ā
NIST, which is a part of the Commerce Department, tested the algorithms of 99 mostly commercial software providers that voluntarily submitted their technology for review. It ran those algorithms on millions of FBI mugshots, visa application photos and other government-held portrait images such as those taken at border crossings.
Microsoft was among the major tech companies that participated in the research, along with dozens of lesser-known video surveillance providers and numerous China-based companies such as SenseTime, Hikvision and Tencent. Amazon, which markets face-scanning software to U.S. police agencies, did not participate.
Watson said thatās because Amazonās cloud-based software doesnāt work with NISTās testing procedures, though the agency is in talks with the company about how to test its algorithms in the future.
The agencyās report creditsĀ two widely-cited studiesĀ of facial recognition bias by Massachusetts Institute of Technology researchers for serving as a ācautionary taleā about uneven results across race and gender boundaries, though it also suggests they sowed public confusion in the way they sought to measure performance.
Joy Buolamwini, who led those studies and has urged a halt to the technologyās proliferation, said in an email Thursday that NISTās study is āa sobering reminder that facial recognition technology has consequential technical limitations.ā
āWhile some biometric researchers and vendors have attempted to claim algorithmic bias is not an issue or has been overcome, this study provides a comprehensive rebuttal,ā she wrote.
She was echoed by the American Civil Liberties Union, which in a statement Thursday said that government agencies like the FBI and U.S. Customs and Border Protection should take heed of the report and halt their deployment of face-scanning software.
āEven government scientists are now confirming that this surveillance technology is flawed and biased,ā said ACLU policy analyst Jay Stanley.
