Press Releases

Rep. Don Beyer (D-VA), a member of the bipartisan House Task Force on Artificial Intelligence, today issued the following statement on the release of the Task Force’s comprehensive report and key findings, including guiding principles and forward-looking recommendations to advance American leadership and innovation on AI:

“This report is a series of timely, productive, bipartisan recommendations on artificial intelligence, one of the most pressing issues of our time.

“The report issues warnings about potential pitfalls in AI use, which I am proud to see includes a section on implications for civil rights and civil liberties, including harmful bias and discrimination. The report also highlights the need for model transparency in AI uses across sectors including government and health care, and stresses the importance of digital literacy. It also recommends codifying the National AI Research Resource (NAIRR), an end that would be accomplished with bipartisan legislation, the CREATE AI Act, that I am proud to co-lead.

“This report is a roadmap for policymakers, including the upcoming Congress, to meet the national imperative for response to the emergence of new challenges posed by AI. I thank our House leadership, the Task Force co-chairs and my colleagues on the committee for their faithful diligence in crafting these policy recommendations. With this Task Force, we offer our colleagues a reminder that we can still do big, important things in a bipartisan way.”

Rep. Don Beyer (D-VA) was appointed to serve on the bipartisan Task Force on Artificial Intelligence, is Vice Chair of the bipartisan Congressional Artificial Intelligence Caucus and Vice Chair of the New Democrat Coalition’s AI Working Group. He is the author of the AI Foundation Model Transparency Act and a lead cosponsor of the CREATE AI Act, the Secure AI Act,and the Federal Artificial Intelligence Risk Management Act.

Beyer served for eight years on the House Committee on Science, Space, and Technology. He is currently attending George Mason University as a part time student completing coursework towards the pursuit of a master’s degree in machine learning, in part to help inform his work on AI in Congress.