美军因使用人工智能生成虚假情报险些酿成事故
US Military had close call after using AI for hallucinated intelligence report

原始链接: https://www.cnn.com/2026/09/18/politics/us-military-ai-false-intelligence-china-ship

近期一份美国情报报告几乎引发了一场武装冲突,起因是一名分析员利用人工智能误判了一艘中国货船上的货物。人工智能错误地标记该船只运载了核武器部件,导致美军准备采取登船行动并调动了飞机。这一错误在干预行动开始前夕被发现。 此次事件凸显了将人工智能整合进军事和情报行动中存在的潜在风险。尽管五角大楼为保持战略优势正积极加速应用人工智能,但目前的部署方式相对分散,缺乏统一的安全标准或验证协议。专家警告称,随着分析员越来越依赖人工智能来处理海量数据,他们面临着“幻觉”的风险——即机器在处理劣质或损坏数据时出现的错误。 此案例揭示了人类操作员盲目信任自动化系统所带来的直接危险。随着人工智能越来越多地被用于战场瞄准和快速决策,军方正面临一项严峻挑战:确保对速度的追求不会导致灾难性且不可逆转的误判。

本帖讨论了近期发生的一起事件:美国军方因依赖一份由人工智能生成的、对船只货物识别错误的简报,差点引发冲突升级。 讨论主要集中在以下几个核心议题: * **可靠性与“幻觉”:** 评论者就大语言模型(LLM)的本质展开争论。一些人认为,“幻觉”这一说法掩盖了此类统计文本拼接引擎固有的、可预测的错误;另一些人则认为,由于我们无法从根本上理解神经网络如何做出特定决策,这些工具在军事行动等关键的高风险环境中本质上是不适用的。 * **问责制:** 大家达成共识,认为责任在于人类——特别是那些将关键决策权下放给不透明、不可靠工具的人。用户将其与过去的“情报失误”相提并论,指出人工智能常被用作推卸责任的借口,使组织能将错误归咎于不可避免的技术故障,而非政策失误,从而逃避问责。 * **对人工智能效用的质疑:** 许多参与者对人工智能所谓的“超高实用性”表示深切怀疑。他们认为人工智能主要是一种用于创作肤浅内容或“愚弄”人类的工具,而非获取真理或进行高水平战略推理的可靠引擎。
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原文

The intelligence report, circulated across the US military this spring in the midst of the war with Iran, immediately set off alarm bells: A Chinese ship in the Middle East was transporting components of a nuclear weapons program.

The US military swung into action with plans to intercept the vessel, according to four sources familiar with the episode. According to two of the sources, armed members of the US military were preparing to board the ship. Military planes were in the air, one of those sources and another source familiar with the incident said.

It was only just before the planned operation that officials dug deeper into the report put together by a special operations command analyst and found it had been generated with the help of artificial intelligence (AI) — and that a chatbot the analyst had used inaccurately identified the material the ship was carrying. CNN was not able to learn what the misidentified cargo was.

The report, according to one of the sources, was “entirely false.” But it also “almost started a war,” the source said. Any US operation against a Chinese vessel could have risked spiraling into an armed conflict between the two nations.

Across the US military and the intelligence community, officials are pushing to weave AI into nearly every facet of their work, from analyzing the huge volumes of raw intelligence the US collects and selecting targets for strikes, to more mundane applications like managing budgeting, logistics and supply chains.

But the episode underscores the profound risks of using this powerful, new and relatively poorly understood technology for targeting in the middle of a war. Analysts have long feared that AI could lead to a catastrophic miscalculation if nation states are relying on poor or corrupted data — the kind of miscalculation that might lead the United States to fire on a Chinese ship based on inaccurate information.

In this particular instance, the analyst queried a chatbot about some intelligence reporting on the ship’s manifest that originated with US Special Operations Command Pacific, based in Hawaii. It was not clear whether the chatbot was a commercially available one or a US government product.

“The internal tools are mostly just copies of the commercial stuff wearing lipstick,” a former senior US official familiar with the AI systems used by military and intelligence analysts.

The bot fused together open-source intelligence with secret signals intelligence in government holdings and reached its fateful conclusion about the material the ship was carrying.

The analyst then used AI again to package the findings into a standard intelligence report — the kind that is trusted by military officials — and disseminated it.

US Special Operations Command Pacific and the Pentagon did not respond to a request for comment.

The rationale for the rapid adoption of AI is that it can help the military make battlefield decisions, like which targets to strike or which military assets to move where, faster. Officials say the US can’t afford to fall behind in integrating AI in case it must one day fight China or another adversary who would potentially be able to stay one step ahead of the US.

In January, Defense Secretary Pete Hegseth released his agency’s “Artificial Intelligence Acceleration Strategy” in a bid to speed up the military’s use of AI.

“We will unleash experimentation, eliminate bureaucratic barriers, focus our investments and demonstrate the execution approach needed to ensure we lead in military AI,” Hegseth said in a speech announcing the strategy.

The strategy also pushes for its broad use across the military, ordering the department to make AI available via several programs with the aim of “democratizing AI experimentation and transformation across the Department by putting America’s world-leading AI models directly in the hands of our three million civilian and military personnel, at all classification levels,” a memo announcing the strategy said.

But the effort is decentralized, multiple US officials familiar with the dynamic said, with different parts of the government using different tools under different orders and safety standards. There’s no one set of standards for how the US verifies the information generated by these tools. The constellation of different AI systems being deployed by disparate corners of the military and intelligence community means that the relative reliability and functionality vary widely.

For weeks, Washington policymakers have been intensely debating AI after a series of dire warnings from Silicon Valley engineers and tech CEOs of the possibility that AI could break free of human constraints, with potentially civilization-ending consequences.

But the episode with the Chinese ship underscores a different, and more immediate risk: human beings making disastrous decisions based on inaccurate or misleading information generated by AI or other automated systems. Sources said that the military is rapidly turning to AI to help with targeting, an area which holds the obvious risk of fatal mistakes.

“AI in targeting is definitely something that is ramping up and there is no real guidance for how having a human in the loop will prevent civilian casualties or fratricide,” another source familiar with the military’s current policies said.

The kind of “hallucination” that the tool used by the analyst in this case conjured has not been an isolated incident across the intelligence community since these tools began proliferating across government, according to one of the sources.

For some older intelligence officials — even those who broadly support the use of AI inside the military — AI has put pressure on analysts to produce and disseminate intelligence faster, opening the door for mistakes. Young analysts in particular, several sources said, are natives on these tools and more likely to trust them uncritically.

“AI allows you to get to a bad idea faster,” one of the sources said.

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