Carlos Carrasco-Farré

Carlos Carrasco-Farré

Carlos Carrasco-Farré
Position

Lecturer at Toulouse Business School (France), member of the editorial team at PLoS ONE (Social Sciences) and Doctor of Management Sciences (ESADE Business School)

The language models used by tools such as ChatGPT fail to identify users' erroneous beliefs

Large language models (LLMs) do not reliably identify people's false beliefs, according to research published in Nature Machine Intelligence. The study asked 24 such models – including DeepSeek and GPT-4o, which uses ChatGPT – to respond to a series of facts and personal beliefs through 13,000 questions. The most recent LLMs were more than 90% reliable when comparing whether data was true or false, but they found it difficult to distinguish between true and false beliefs when responding to a sentence beginning with ‘I believe that’.

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In online debates, GPT-4 can be more persuasive than humans

In online debates, Large Language Models (LLMs, i.e. Artificial Intelligence systems such as ChatGPT) are more persuasive than humans when they can personalise their arguments based on their opponents’ characteristics, says a study published in Nature Human Behaviour which analysed GPT-4. The authors urge researchers and online platforms to ‘seriously consider the threat posed by LLMs fuelling division, spreading malicious propaganda and developing adequate countermeasures'.

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