AI hallucination of Chinese nuclear components almost led to US military attack

The US narrowly avoided boarding a Chinese ship based on an “entirely false” US intelligence report generated with the help of AI tools, according to a CNN report.

That erroneous intelligence, submitted by a US Special Operations Command analyst, suggested the Chinese ship was transporting nuclear arms program components through the Middle East, according to “four sources familiar with the episode” cited by CNN. The US military was preparing to intercept and board the ship, with air support, before officials discovered a chatbot used in generating the report had “inaccurately identified the material the ship was carrying.”

One source told CNN the AI-powered fiasco “almost started a war.”

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CNN’s report said the analyst in question used a chatbot to analyze intelligence reports regarding the Chinese ship’s manifest, leading to the near-disastrous result. That chatbot “fused together open-source intelligence with secret signals intelligence in government holdings,” and that information was packaged into an intelligence report that almost set off a disastrous chain of events, according to CNN.

The near-miss is one of the more potent and consequential instances of a hallucinating AI ruining the reliability of a professional report. Since “hallucinating” became the Cambridge Dictionary’s word of the year in 2023, we’ve seen prominent examples of non-fiction authors, journalists, academic researchers, judges, doctors, police departments, corporate call centers, and more getting taken in by AI tools that simply make something up when their training data doesn’t provide sufficient context. And despite some adorable attempts at “do not hallucinate” prompts, some researchers suggest that it may be impossible to prevent LLMs from hallucinating altogether.

One would hope the US military would be aware of these kinds of problems when relying on AI for analysis of intelligence reports. But the Department of Defense in January rolled out an “AI acceleration strategy” that sought to “make all appropriate data available across federated IT systems for AI exploitation, including mission systems across every service and component.”