EFF Voices Opposition to California Facial Recognition Bill

The Electronic Frontier Foundation (EFF) has allied with several other civil rights and labor advocates to oppose California’s proposed A.B. 2261 legislation, which is currently in front of the state’s Assembly Appropriations Committee. The legislation is ostensibly designed to regulate the use of face-based surveillance so it can be used to slow the spread of COVID-19.

However, those opposed to the bill believe that it does not have sufficient safeguards to protect the privacy and civil liberties of people under surveillance. With that in mind, the EFF argues that the bill will instead lead to widespread abuses of facial recognition technology, since governments and other organizations will be able to “pay lip service to privacy without actually preventing the harms of face surveillance.”

The EFF notes that facial recognition will disproportionately affect minority communities, especially in the wake of the recent protests against police brutality. The organization suggests that increased surveillance will likely be used to target activists in an effort to suppress first amendment rights to speech and assembly. If that proves to be the case, surveillance would only exacerbate the law enforcement bias that motivated the protests in the first place.

According to the EFF, the current moment is particularly precarious because it is difficult to roll back surveillance tools that are implemented during a time of crisis. That’s why the organization is urging California citizens to fight against the bill, and to convey that opposition to their representatives.   

The California ACLU, Oakland Privacy, the California Employment Lawyers Association, the Service Employees International Union (SEIU) of California, and the California Teamsters are the other organizations standing with the EFF against A.B. 2261. The EFF itself has repeatedly called for much stricter facial recognition regulations, and has pointed out that government agencies already have access to a massive number of facial images.

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June 3, 2020 – by Eric Weiss