SIA opposes act to ban biometric, image analytic technologies
By SSN Staff
Updated Mon July 6, 2020
SILVER SPRING, Md.—The Security Industry Association (SIA) has announced its strong opposition to the recently introduced bicameral Facial Recognition and Biometric Technology Moratorium Act that would impose a blanket ban on most federal use of nearly all biometric and related image analytics technologies.
The legislation incorrectly labels all such technologies as surveillance regardless of application and forces essentially all state and local governments to do the same. This threatens the safety of Americans by eliminating certain tools that have been in use for a decade or more to solve thousands of crimes, prevent fraud, allow access to critical infrastructure and, overall, keep Americans safe, while negating the research put into improving and developing safe, reliable, unbiased technology.
“When used effectively and responsibly, facial recognition technology keeps people safe and brings value to our everyday lives,” Don Erickson, CEO of SIA, said in the announcement. “While SIA welcomes a constructive dialogue over the use of facial recognition technology, the Facial Recognition and Biometric Technology Moratorium Act is regrettably not a workable solution to address reasonable concerns about the use of facial recognition. Alternatively, SIA would enthusiastically support legislation that ensures appropriate transparency, procedures and oversight.”
Government must use high-performing facial recognition technology for a given application, validated using sound, scientific methods, such as through the National Institute of Standards and Technology’s Facial Recognition Vendor Test program across demographic groups.
SIA encourages facial recognition to be used transparently, accurately, securely and always with a human in the loop when used in an identification process that results in consequential decision. As a matter of principle, its use in law enforcement must be as a secondary tool in investigations to assist personnel, who ultimately use other means to make an identification. Facial recognition increases the effectiveness and accuracy of this work, and can actually limit the effects of inherent human bias in such applications.
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