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EFF Unveils State Legislative Agenda to End ALPR Mass Surveillance

By EFF Updates1 min read

The Electronic Frontier Foundation has outlined a state-level legislative agenda aimed at curbing mass surveillance enabled by Automated License Plate Readers, according to EFF Updates. The group warns that AI advances and nationwide data sharing have turned police ALPR networks into an interconnected tracking system.

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The Electronic Frontier Foundation (EFF) has announced a state legislative agenda focused on ending mass surveillance carried out through Automated License Plate Readers (ALPRs), according to EFF Updates.

Police agencies across the United States have deployed ALPRs to capture images of passing vehicles along with the time, date, and GPS coordinates of each scan. While the technology itself is not new — ALPRs have existed in various forms for more than 50 years and have been used in the U.S. since 1998 — the EFF argues that the surveillance landscape has shifted dramatically in recent years.

According to the EFF, rapid advances in artificial intelligence and national data sharing have transformed police ALPR deployments into an interconnected, nationwide tracking network. What were once isolated cameras logging plate numbers can now feed into systems capable of following vehicle movements at scale, the group says.

The EFF notes that these systems are pitched to city councils by law enforcement agencies alongside private vendors, naming Flock Safety and Motorola among the companies marketing the technology to local governments.

The newly announced agenda is aimed at state lawmakers, reflecting the EFF's view that legislation at the state level is a key lever for reining in ALPR-driven surveillance. The initiative fits into the organization's broader advocacy around location privacy and government surveillance, where it has long argued that persistent, warrantless tracking of drivers poses civil liberties risks.

Details of the specific legislative proposals were drawn from the EFF's announcement, published by EFF Updates.

Source: EFF Updates

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AI-written summary Source: EFF Updates · Fetched

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