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OpenAI and Anthropic race to recruit former Trump administration officials as AI industry ramps up push for Washington support

BlockBeats news, October 9 — According to CNBC, OpenAI and Anthropic are recruiting former officials from the Trump administration for senior positions to strengthen their ties with the U.S. government. As frontier AI technology is increasingly viewed as a national security issue, both companies are ramping up their political affairs operations to address policy impacts including regulation, federal government procurement, supply chain risk designations, and export controls.


Since the start of this year, Anthropic has hired at least two former Trump administration officials: former White House Deputy Chief of Staff Chris Liddell joined the board in February, and Sihao Huang, who previously served as a senior policy advisor at the White House Office of Science and Technology Policy (OSTP), joined the company in September to oversee frontier compute strategy.


OpenAI has also recently hired several former government officials, including Thomas Lind, who previously oversaw AI policy at the White House Office of the National Cyber Director, Dean Ball, who participated in drafting the Trump administration's "America's AI Action Plan," and Peter Bowman-Davis, who previously served as Chief AI Officer at the U.S. Department of Health and Human Services.


Anthropic previously had a public conflict with the U.S. Department of Defense and in September had its supply chain risk designation upheld by a U.S. appeals court. Since then, Anthropic CEO Dario Amodei has recently sought to ease tensions between the two sides through meetings with Trump and other AI company executives.


Analysts say that as AI companies face increasingly complex regulatory and national security requirements, government relations are becoming an important part of industry competition. Both companies are currently recruiting for multiple political affairs-related positions, seeking greater influence in the U.S. AI policymaking process.

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