Facial Recognition Technology Current Capabilities, Future Prospects, and Governance (2024) / Chapter Skim
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It then compares these templates to compute a similarity score. In one-to-one comparison, the claimed identity of a single individual is verified by comparing the template of a captured probe image with an existing reference image (is this person who they say they are?
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• FRT can be a powerful aid for law enforcement in criminal and missing person investigations because it enables investigators to generate leads using images captured at a crime scene. A number of law enforcement agencies have reported successful use of FRT to generate otherwise unavailable leads.
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The fact that all the reported wrongful arrests associated with the use of FRT have involved Black defendants exacer bates distrust of this technology. Concerningly, testing has demonstrated that FP match rates for Black individuals and members of some other demographic groups are relatively higher (albeit low in absolute terms)
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Tests show that FN rate differentials are extremely small, especially with the most accurate algorithms and if both the probe and reference images are of high quality, but can become significant if they are not. FN matches occur when the similarity score between two different images of the same person is low.
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Tests also show that for identify verification (one-to-one comparison) algorithms, the FP match rates for certain demographic groups when using even the best-performing facial recognition algorithms designed in Western countries and trained mostly on White faces are relatively higher (albeit quite low in absolute terms)
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However, the committee is in full agree ment with the following recommendations. MITIGATING POTENTIAL HARMS AND LAYING THE GROUNDWORK FOR MORE COMPREHENSIVE ACTION RECOMMENDATION 1: The federal government should take prompt action along the lines of Recommendations 1-1 through 1-6 to mitigate against potential harms of facial recognition technology and lay the groundwork for more comprehensive action.
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c. Methods for evaluating false positive match rates for probe images captured by closed-circuit television or other low-resolution cameras (which have been implicated in erroneous arrests of several Black individuals)
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f. Policies and procedures to address law enforcement failures to adhere to procedures or failure to attain appropriate certification.
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RECOMMENDATION 1-4: Federal grants and other types of support for state and local law enforcement use of facial recognition technology (FRT) should require that recipients adhere to the following technical, procedural, and disclosure requirements: a.
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Even if not subject to federal grant conditions, state and local agencies should adopt these standards. RECOMMENDATION 1-5: The federal government should establish a program to develop and refine a risk management framework to help organizations identify and mitigate the risks of proposed facial recognition technology applications with regard to performance, equity, privacy, civil liberties, and effective governance.
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• Data collection, disclosure, use, and retention policies for both subject and reference images and templates -- including data retention policies to limit, for example, inappropriate use of probe images for searches beyond pre-defined operational needs. • Data security and integrity -- including adequately protecting information in FRT training data sets and reference databases from exfiltration and misuse.
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RECOMMENDATION 1-6: The federal government should support research to improve the accuracy and minimize demographic biases and to further explore the sociotechnical dimensions of current and potential facial recognition technology uses. Public research organizations, such as NIST, already undertake important work in setting benchmarks and evaluating the performance of FRT systems.
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• The performance of FRT with very large galleries (i.e., tens or hundreds of millions of entries) , to better understand the impacts of FP and FN match rates as the size of galleries used continues to grow.
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FOSTERING TRUST AND MITIGATING BIAS AND OTHER RISKS RECOMMENDATION 2: Developers and deployers of facial recognition technology should employ a risk management framework and take steps to identify and mitigate bias and cultivate greater community trust. RECOMMENDATION 2-1: Organizations deploying facial recognition technology (FRT)
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RECOMMENDATION 4: New legislation should be considered to address equity, privacy, and civil liberties concerns raised by facial recognition technology, to limit harms to individual rights by both private and public actors, and to protect against its misuse. Legislation should consider the following: a.
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Such uses might, for example, include the following: • Commercial practices that implicate privacy (through either broader pri vacy legislation addressing FRT risks or an FRT-specific federal privacy law) ; • Harassment or blackmail; • Unwarranted exclusion from public or quasi-public places; • Especially sensitive government FRT uses (e.g., pertaining to law enforcement or access to public benefits or federally subsidized housing)
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* FRT is a powerful tool with profound societal implications.
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