{"id":17171,"date":"2026-05-02T17:00:00","date_gmt":"2026-05-02T15:00:00","guid":{"rendered":"https:\/\/holistic.news\/en\/?p=17171"},"modified":"2026-04-30T14:47:52","modified_gmt":"2026-04-30T12:47:52","slug":"does-ai-understand-this-illusion-is-dangerous","status":"publish","type":"post","link":"https:\/\/holistic.news\/en\/does-ai-understand-this-illusion-is-dangerous\/","title":{"rendered":"You Think AI Knows What It\u2019s Doing. That Illusion Can Be Dangerous"},"content":{"rendered":"\n

Does AI understand? Or do we only think it does?<\/h2>\n\n\n\n

Talking to a chatbot often feels like interacting with a human. Users say the machine \u201cknows,\u201d \u201cunderstands,\u201d even \u201cremembers.\u201d<\/strong> Researchers from Iowa State University warn, however, that such language can distort what artificial intelligence actually is.<\/p>\n\n\n\n

A team led by Professor Jo Mackiewicz analysed<\/a> more than 20 billion words <\/strong>from news articles across 20 countries. They searched for expressions such as \u201cthinks,\u201d \u201cknows,\u201d and \u201cunderstands\u201d used alongside terms like \u201cAI\u201d and \u201cChatGPT.\u201d The results suggest that journalists are more cautious than one might expect. Most avoid attributing human qualities to machines. But when they do, the effect can be misleading.<\/p>\n\n\n\n

Words that distort reality<\/h3>\n\n\n\n
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AI needs data\u2014this sounds like describing a car that needs fuel. But \u2018AI must understand the world\u2019\u2014that is an entirely different story.<\/p>\n\n\n\n

\u2014 explains Jo Mackiewicz in ScienceDaily<\/em><\/p>\n<\/blockquote>\n\n\n\n

The second statement assigns something the machine does not possess: intention, curiosity, even a hint of consciousness<\/strong>. Such phrases can settle in readers\u2019 minds. Expectations toward AI begin to rise beyond what these systems can actually do. At the same time, they obscure those who are truly<\/strong> responsible for the technology<\/strong>: programmers, engineers, and the companies behind it.<\/p>\n\n\n\n

Do journalists know what they are doing?<\/h2>\n\n\n\n

In everyday speech, it is easy to say that \u201cSiri knows.\u201d In journalism, such expressions are far less common. The most frequent word associated with AI in the study was \u201cneeds,\u201d appearing 661 times<\/strong>\u2014typically in neutral contexts such as \u201cAI needs large amounts of data.\u201d This is an example of careful language that avoids suggesting human traits.<\/p>\n\n\n\n

By contrast, the phrase \u201cChatGPT knows\u201d appeared only 32 times. That may seem insignificant, but researchers stress that even a few strong expressions can shape how people perceive technology<\/strong>. This may help explain why public discourse swings so easily between extremes: apocalyptic fears of AI and utopian visions of a machine that will solve all problems.<\/p>\n\n\n\n

Language and AI: not a simple binary<\/h2>\n\n\n\n

Researchers from Iowa State note that anthropomorphism in artificial intelligence<\/a> is not a black-and-white issue. It is a spectrum of expressions, ranging from neutral to suggestive: from ordinary descriptions of technical requirements, through neutral statements, to sentences implying that a machine thinks.<\/p>\n\n\n\n

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Anthropomorphism in press articles is far less common than one might expect. Even in cases where it appears, we can see different degrees of intensity in its use,<\/p>\n\n\n\n

– Mackiewicz says.<\/p>\n<\/blockquote>\n\n\n\n

These findings matter because the way we write shapes how we understand artificial intelligence \u2014 including whether we believe AI thinks like a human. In turn, this influences readers\u2019 imagination and may shape their attitude toward technology. It may even lead people to organise their lives around the mistaken assumption that AI \u201cdecides\u201d for them.<\/p>\n\n\n\n

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