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Fight for the Future, digital rights group, today launched BanFacialRecognition.com to call for a federal ban on the use of facial recognition surveillance.
Facial recognition, which is used extensively in China, "enables automated and ubiquitous monitoring of an entire population, and is nearly impossible to avoid," according to the site.
The group calls facial recognition systems "hallmarks of authoritarian states," used not to promote safety but to control and oppress a population.
It could and is already happening here.
The Washington Post reported July 7 that Federal Bureau of Investigation and Immigration and Customs Enforcement agents have turned databases of state driver's licenses "into a facial-recognition gold mine scanning through millions of Americans’ photos without their knowledge or consent."
The Feds have transformed Departments of Motor Vehicles "into the bedrock of an unprecedented surveillance infrastructure."
George Orwell would be proud.
Unlike fingerprints, DNA or other biometric data taken from criminal suspects, the Post noted that "DMV records contain the photos of a vast majority of a state’s residents, most of whom have never been charged with a crime."
Pushback against the survelliance state has begun.
In May, San Francisco became the first city to ban the use of facial recognition systems by its police and other agencies. Oakland followed its Bay Area neighbor as its Public Safety Committee on July 3 recommended approval of a proposal to ban facial recognition technology.
Axon, which supplies body cameras and software to 47 of the country's 69 largest police forces, announced last month that it would ban facial recognition devices on its equipment.
The company determined that facial recognition systems just don't work well "on people of color compared to whites, on women compared to men, or young people compared to older people.”
Barry Friedman, a member of Axon's ethics board, simply said the tech is just not accurate enough.
That's another reason why Congress should put the kibosh on facial recognition.
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