EFF Testifies to Congress on Protecting Americans’ Rights from Government AI

Electronic Frontier Foundation
Published
EFF Testifies to Congress on Protecting Americans’ Rights from Government AI

The short version

  • Matthew Guariglia testified today to the House Homeland Security Subcommittee on Cybersecurity and Infrastructure Protection.
  • You can read his full testimony as prepared here .

The story

Governments must not adopt emerging and powerful AI technologies without also adopting strong and clear safeguards to protect Constitutional rights, EFF Senior Policy Analyst Dr. Matthew Guariglia testified today to the House Homeland Security Subcommittee on Cybersecurity and Infrastructure Protection. 

During the hearing on “The AI Security Landscape: How Frontier Models, Agentic AI, and AI Coding Tools Are Reshaping Cybersecurity and Critical Infrastructure Resilience,” he explained that the use of generative AI for the purposes of mass government surveillance would supercharge unconstitutional violations of civil liberties. He also highlighted how government secrecy, in addition to the black box of for-profit proprietary technology, prevents the public and lawmakers from knowing when AI models make mistakes, including errors that seriously impact the cybersecurity of critical infrastructure and the lives of individuals.  

“AI also has a track record of getting things wrong—from false citations on legal briefs to a major AI mistake that sent DHS recruits to the field without proper training. There are likely more consequential examples that we do not even know about because of classification that would prevent a more thorough accounting," he said in his opening remarks.

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“At this level the question is not how do we rein in AI, it’s how do we rein in the agencies that would unleash AI on the American public,” Matthew said in response to a question by Subcommittee Ranking Member Delia Ramirez, D-Ill.  

You can read his full testimony as prepared here. 

Read the full story at Electronic Frontier FoundationOriginal

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