Judge Says Trump Administration Lacks Evidence to Label Anthropic a Supply-Chain Risk

A federal judge said Thursday that the Trump administration has not presented sufficient evidence to justify labeling AI company Anthropic a supply-chain risk — casting doubt on the government’s ban on federal use of the company’s technology.

U.S. District Judge Rita Lin made the remarks during a hearing in one of two lawsuits Anthropic filed against the Department of Defense in March 2026, challenging both the ban and the risk designation. A separate case is being heard in Washington. Lin had temporarily blocked the ban in March and is now weighing whether to make that order permanent.

The dispute traces back to stalled contract negotiations between Anthropic and the DOD. Anthropic objected to its AI being used for mass surveillance of Americans or for targeting and firing decisions involving lethal weapons, arguing the technology was not ready for such applications. The Pentagon pushed back, asserting that a private company should not dictate how the military uses its technologies, and said it would deploy the tools in “lawful” ways.

The government also argued that Anthropic’s public criticism of the DOD independently justified the ban — a line of reasoning Lin described as “really troubling,” warning it could set a precedent for retaliating against federal contractors who disagree with the administration.

The DOD additionally claimed Anthropic could potentially disable or alter its AI models during warfighting operations. Lin rejected that argument as well, saying she saw no proof Anthropic could alter a delivered model or “flip some kind of kill switch” — a conclusion that aligns with assessments from outside experts cited in reports by Bloomberg and Axios.

The outcome of Lin’s ruling could have broader implications for how the government designates technology companies as security risks and whether contractors can face restrictions for publicly criticizing federal agencies.

Source: TechCrunch

This article was generated by AI and cites original sources.
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