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Utah Valley Times

Monday, December 30, 2024

Bipartisan bill aims to mitigate extreme risks posed by advanced artificial intelligence

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Sen. Mitt Romney, U.S. Senator for Utah | Official U.S. Senate headshot

Sen. Mitt Romney, U.S. Senator for Utah | Official U.S. Senate headshot

U.S. Senators Mitt Romney, Jack Reed, Jerry Moran, Angus King, and Maggie Hassan have introduced new legislation aimed at protecting national security from potential threats posed by advanced artificial intelligence (AI) models. The bipartisan Preserving American Dominance in AI Act seeks to establish the Artificial Intelligence Safety Review Office within the Department of Commerce. This office will collaborate with industry to prevent misuse of frontier AI models by foreign adversaries.

The proposed legislation focuses on addressing risks associated with chemical, biological, radiological, nuclear, and cyber threats that could arise from future developments in AI technology. Senator Romney emphasized the importance of safeguarding advanced technology from potential misuse by terrorists and adversaries while maintaining America's competitive edge in AI innovation.

Senator Reed highlighted the dual nature of AI as both beneficial and risky, advocating for measures to prevent its exploitation against American security interests. Senator Moran underscored the need for responsible harnessing of AI's power to mitigate extreme risks threatening national security.

Senator King pointed out the necessity for federal oversight to ensure AI is not misused by bad actors. He stressed careful navigation into an AI-driven future to protect national interests both domestically and internationally.

Senator Hassan called for bipartisan efforts to proactively address national security threats posed by advancing AI technologies. She advocated for balanced oversight to maintain U.S. leadership in responsible AI development while safeguarding public safety.

The act proposes working with frontier AI companies and infrastructure providers to prevent exploitation by adversaries and ensure pre-deployment evaluations similar to those conducted by CFIUS for high-risk models.

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