Facial Recognition Technology (FRT) has been deployed in the U.S. Government substantially post-9/11. The groundwork was laid in 2003 when the State Department mandated fingerprint collection and a digital photograph for each visa applicant in the United States, and it has been steadily building up since. The last two years especially have seen widespread adoption of FRT in the federal government due primarily to the dramatic improvement in FRT accuracy and the issuance of practical use guidelines from the GAO.
Despite this favorable shift in attitudes toward FRT by some of the world’s most important public institutions, there is still healthy skepticism toward the technology which we in the industry must do our best to address through facts and science.
Concerns about accuracy are usually the first mentioned by doubters. On that front, testimony given by Dr. Charles Romine, NIST’s Information Technology Laboratory Director, to the House Homeland Security Committee on February 6, 2020, has been widely overlooked and is essential to understanding just how accurate FRT algorithms have become when used to make bias-free positive identifications in one-to-many applications. According to Dr. Romine, NIST’s testing revealed “undetectable bias in demographic differentials” and that there is “no statistical level of significance”  to support any claim of bias among the highest performing algorithms the agency has tested – and that was more than two years ago.
Policies around appropriate use are another concern. Last year, in 2021, a series of reports by the GAO laid out guidelines for any federal agency to purchase facial recognition for law enforcement applications and a wide range of other uses. Their findings were extensive enough to merit the publication of a 90-page document offering guidelines and recommendations for the use of AI across the federal government which, among other things, expounded on four tenets: accountability through governance, data security, effective auditing, and the adoption of performance standards.
Indeed, more than two dozen agencies now employ some form of FRT to perform necessary security and enforcement tasks, with more agencies finalizing their policies in 2022 in line with the GAO report’s recommendations.
Significantly for law enforcement investigations, the Department of Justice’s Criminal Intelligence Systems Operating Policies (28 CFR Part 23) that establishes intelligence systems guidelines for law enforcement has provisions that specifically allow the use of publicly available information from the internet or other public records in criminal investigations.
The culmination of these developments clearly indicates that the debate surrounding the government’s use of facial recognition is moving beyond controversy and is beginning to be widely adopted. In 2021, the GAO report noted that 24 federal agencies reported using FRT, with more agencies planning to expand their usage.
As for privacy concerns, the U.S. government is well positioned to continue embracing FRT for the benefit of its citizenry while maintaining appropriate checks and balances that safeguard against invasive and abusive misuses. By contrast, China and other authoritarian states have deployed FRT in a real-time manner, unlike the United States, with no controls in place; and although some in the EU want to ban FRT outright, it is recognized for its importance for law enforcement and public safety.
It's a careful balancing act, to be sure, which is why we offer the following recommendations that go above and beyond those from the previously mentioned GAO report:
Enhanced training for all users should be thoughtfully mandated. (Many federal agencies already have FRT training regimens, but these should be integrated with provider training, a service that some companies including ours offer.)
Prescribed guidelines should regulate which uses are permissible by specific agencies, and which are prohibited.
Regular check audit trails for administrators of FRT programs across all agencies.
The United States Government and its partners in the private sector have always been at the vanguard of technical innovation. We are proud this is also proving true with the advancement and evolution of FRT, which has made tremendous leaps forward under the development of American companies that employ hundreds of Americans who all have American interests at heart.
Founder & CEO of Clearview AI
A self taught engineer, Hoan Ton-That is of Vietnamese and Australian heritage. His father's family descended from the Royal Family of Vietnam. As a student, Hoan was ranked #1 solo competitor in Australia’s Informatics Olympiad. He was ranked #2 guitarist under age 16 in Australia’s National Eisteddfod Music Competition. At the age of 19, Hoan moved from Australia to San Francisco to focus on his career in technology. He created over twenty iPhone and Facebook applications with over 10 million installations, some of which ranked in the App Store’s Top 10. Hoan moved to New York City in 2016. In 2017, he co-founded Clearview AI and focused his energy on developing the core technology, raising capital, and building the team and product.