Security Industry Association Strongly Opposes the Facial Recognition and Biometric Technology Moratorium Act
- By Kara Klein
- Jun 29, 2020
The Security Industry Association (SIA), the leading trade association representing security solutions providers, today announced its strong opposition to the recently introduced bicameral Facial Recognition and Biometric Technology Moratorium Act.
The bill would impose a blanket ban on most federal use of nearly all biometric and related image analytics technologies, incorrectly labeling all such technologies as surveillance regardless of application, while forcing essentially all state and local governments to do the same. The legislation 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 and unbiased technology.
Speaking about the use of facial recognition by the public sector, Don Erickson, CEO of SIA, said, “When used effectively and responsibly, facial recognition technology keeps people safe and brings value to our everyday lives. 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.”
The technology behind facial recognition is highly accurate and has vastly improved in the past few years. 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 in identification process that result in consequential decisions. 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.
Examples of the value of facial recognition technology include:
Kansas Department of Revenue. Use of facial recognition software led to the investigation of the largest forced labor trafficking case in the region, all through identifying cases of driver license fraud in their facial recognition database.
New York City. Facial recognition technology was used by NYPD to identify a man who had left suspected bombs in rice cookers in and around a subway station.
Facial recognition technology is deployed in dozens of airports across the United States and continues to grow. Customs and Border Protection and airport officials match passport photos to a database to verify the identity of thousands of travelers entering and leaving the United States each week. The technology is proving to be an important tool for border security. As of June 2020, nearly 300 people have been intercepted attempting to enter the United States under a fraudulent identity.
Since 2015, the nonprofit group Thorn has used facial recognition as part of a tool used to help rescue 15,000 children and identify 17,000 human traffickers. For example, after seeing an online post about a missing child from the National Center for Missing and Exploited Children, a law enforcement officer used Spotlight to return a list of sex ads featuring the girl. According to a WIRED story, the girl had been “sold for weeks,” and the officer’s actions initiated a process that “recovered and removed [her] from trauma.”
Kara Klein is the manager of communications at the Security Industry Association.