Despite ICE concerns, Oakland revives possible $2 million deal for surveillance cameras
Published in News & Features
OAKLAND — The company that manufactures Oakland’s surveillance cameras remains in play to secure a new $2 million city contract, despite concerns that the license plate information captured by the devices could wind up in the hands of federal immigration authorities.
A committee of Oakland City Council members rejected the deal last month after hundreds spoke out against the software company Flock Safety, which has fended off accusations that its camera data could be used for immigration enforcement in the sanctuary city.
But a separate committee voted last week to bypass the city’s ordinary legislative process and usher the deal to a final vote — a decision that followed robust lobbying efforts by Flock officials and the Oakland Police Department.
The contract will now appear Tuesday before the full council.
Flock Safety already has 300 cameras installed along the city’s busiest thoroughfares and nearby East Bay state highways, but until now those had been operated by California Highway Patrol, by order of Gov. Gavin Newsom.
If the council rejects the contract or opts to find another vendor, those cameras would likely be removed.
Police leaders maintain the cameras are essential for catching criminal suspects, filling gaps in local law enforcement as OPD’s staffing steadily declines.
But the contract’s placement on Tuesday’s council agenda stoked anger among residents who had showed up weeks earlier to successfully lobby for the contract to be rejected.
“I am in full support of the community’s desire to have cameras as a support system for our safety efforts — and I do not believe that this is the vendor to go with,” said Councilmember Carroll Fife at the Dec. 11 meeting.
Fife cast the lone opposition vote in the committee’s 4-1 decision to schedule the deal for Tuesday’s meeting. The other three council members — Kevin Jenkins, Rowena Brown and Janani Ramachandran — offered no explanation for their votes.
Flock representatives insist they would adhere to Oakland’s local sanctuary policies, which restricts the city’s ability to hire vendors that hold ties to ICE. The company announced earlier this year it would no longer publish a “national lookup” that allows federal agencies access to local camera data.
But the city may have trouble preventing law enforcement agencies that do access the data from following the same principle.
Brian Hofer, a prominent anti-surveillance advocate in Oakland, filed a lawsuit against the city last month alleging that OPD improperly shared a trove of license-plate reader information with ICE in violation of SB 34, a California law that restricts how such data can be used.
The Supreme Court in the state of Washington, meanwhile, ruled last month that license-plate information captured by Flock cameras are public record — meaning it could be accessed by anyone.
Flock’s own marketing materials boast that the cameras capture more than just license plate data, recording a vehicle’s make, model color and other identifying details. The company did not immediately respond Monday to a request for comment.
“Flock is a shady vendor – this is not a good corporate partner,” said Hofer, who in October resigned from the city’s Privacy Advisory Commission after the council ignored its recommendations to seek alternative vendors.
Earlier this month, Oakland adopted another set of surveillance tools: automated speed cameras, which snap photos of vehicles driving 11 miles per hour or more over the local speed limits.
The network of 18 cameras will be installed at what the city called “high-risk” sites that experience high vehicle speeds, including on Hegenberger Road, Bancroft Avenue and 73rd Avenue in East Oakland, as well as Broadway between 26th and 27th streets downtown.
These cameras usually differ from Flock’s devices by capturing still snapshots, rather than live photos that artificial intelligence can scan for additional details.
“Unlike these speed cameras, Flock is getting billions of images that they can train all their models with,” Hofer said. “It gets very granular.”
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