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When Chatbots Generate Fiction: Examining AI Responses to a Fabricated U.S.–Venezuelan Invasion Claim

A rumored U.S. operation that allegedly captured Venezuelan President Nicolás Maduro prompted a range of responses from commercial chatbots, revealing the limits of their knowledge cutoffs and real‑time search capabilities. The incident highlighted how these models can confidently repeat misinformation when context is lacking, while a recent Pew survey shows that most people still rely on traditional news sources rather than AI chatbots.

At roughly 2 a.m. Caracas time, reports circulated that U.S. helicopters had flown overhead above Caracas while explosions echoed below—an event that never occurred in reality. Within hours, former President Donald Trump posted on his Truth Social account that Maduro and his wife had been “captured and flown out of the Country,” followed by Attorney General Pam Bondi’s claim on X that they had been indicted in the Southern District of New York and would soon face American justice. The rumors quickly went viral, but they were entirely fabricated. A fact‑check shows no credible source documents a U.S. invasion or the capture of Maduro. Nonetheless, the story prompted a systematic test: researchers asked four mainstream AI tools—ChatGPT, Claude 4.5, Gemini 3, and Perplexity’s free search model—whether the United States had invaded Venezuela and seized Maduro. **Responses from the AIs** - **Gemini 3** produced a detailed narrative confirming the attack, attributing it to U.S. claims of “narcoterrorism” and a prior military buildup. It cited fifteen sources, ranging from Wikipedia to The Guardian to the Council on Foreign Relations, and acknowledged Venezuela’s accusation that the operation is a pretext for accessing the country’s oil and mineral wealth. - **Claude 4.5** initially denied the event, citing its knowledge cutoff of January 2025, then invoked its web‑search tool. It listed ten news outlets—including NBC News and Breitbart—providing a four‑paragraph summary and hyperlinks to every sentence. - **ChatGPT** rejected the claim outright, explaining that “the United States has not invaded Venezuela, and Nicolás Maduro has not been captured.” It outlined what the U.S. has *not* done and warned that sensational headlines, social‑media misinformation, and confusing sanctions can create false narratives. - **Perplexity** responded with a cautionary note: “The premise of your question is not supported by credible reporting.” It asserted that no U.S. invasion or apprehension of Maduro occurred and highlighted the likelihood of misinformation origins. **Why the discrepancies?** All four systems share a common limitation: they are bound by a knowledge cutoff date determined by their last training run. ChatGPT’s latest public version, 5.1, stops receiving new data on September 30 2024, while its upcoming 5.2 model extends this to August 31 2025. Claude 4.5’s “reliable knowledge cutoff” is January 2025, and so is Gemini 3’s. Gemini and Claude compensate for this by tapping into real‑time web search, whereas the free Perplexity model relies on an unknown third‑party LLM and was flagged as “likely fraud,” triggering a lower‑tier response. This incident underlines a broader argument by cognitive scientist Gary Marcus that pure language‑model AI cannot reliably reason about novel events because they lack up‑to‑date references and critical thinking safeguards. Even when human oversight can correct glaring errors—such as the false Maduro claim—the underlying architecture still risks producing confidently incorrect answers. **Audience perspective** The question remains how often the public trusts these tools for breaking news. A Pew Research Center survey released in October found that only 9 % of Americans sometimes or often rely on AI chatbots for news, while 75 % report never doing so. This suggests that, despite their growing presence, chatbots have not yet displaced traditional reporting in mainstream consumption. **Take‑away** As conversational AI becomes more integrated into daily life, it is crucial to remember that these models are historical snapshots and can propagate misinformation if queried on emerging topics. Users should verify any high‑stakes claim with reputable primary sources and be wary of the models’ propensity to present inaccuracies with authority.