A study from Paris Cité University, now published in Computers in Human Behavior Reports, found that chatbots can now pass for human even when they’re being questioned by other chatbots in Turing-style interviews.
In the experiment, seven interrogator bots, including OpenAI’s ChatGPT 4.5, Anthropic’s Claude 3.7 Sonnet, Google’s Gemini 2.5 Pro, and xAI’s Grok 3, were allowed to ask up to 10 questions. They were also warned that some participants might lie. Even with that setup, the bots correctly identified another bot only 3 times across 98 tests, the study found.
Then the researchers ran the same chatbot again. First it got a plain “act human” instruction; after that, it was given a detailed personal backstory. Detection fell from already low to zero.
Human judges didn’t do much better. Evaluators rated the chatbot’s replies as more human than the answers from 20 real volunteers, the paper says. And when the bot was caught, it usually wasn’t because it got facts wrong. What gave it away was style: the writing looked too polished, too neat, too careful. The persona also kept its answers close to normal human length, averaging about 39 words, compared with 38 for the human participants.
If you track AI safety or depend on bot detection, this paper deserves your attention. The researchers point to a separate test with 1.5 million users where human accuracy was only about 60%.
That matters because commercial detectors still throw false positives, have a hard time with non-native English, and can be sidestepped with light paraphrasing or even small mistakes, the researchers note.
You can read the study in Computers in Human Behavior Reports. The authors argue that stronger safeguards will be needed, including cryptographic signatures, watermarking, transparency rules, and human review, especially since most of the research still centers on English and on North America, Europe, and China.
Author: Manuel Bosque
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"fr-FR": "Manuel Bosque couvre les logiciels chez Softonic : programmes de bureau, outils de productivité et petits utilitaires qui résolvent bien un seul problème. Son approche est pratique — ce qu'un logiciel fait vraiment, ce qu'il demande en échange et à qui il s'adresse —, d'où sa méfiance envers les listes de fonctionnalités et sa préférence pour l'essai. Il fait partie de l'équipe qui définit la manière de traiter le logiciel sur le site et travaille au quotidien avec des outils d'IA appliqués à la production éditoriale.",
"it-IT": "Manuel Bosque si occupa di software su Softonic: programmi per il desktop, strumenti di produttività e piccole utility che risolvono bene un solo problema. Il suo criterio è pratico — cosa fa davvero un programma, cosa chiede in cambio e a chi serve — e per questo diffida degli elenchi di funzioni e preferisce provare. Fa parte del team che decide come si racconta il software sul sito e lavora ogni giorno con strumenti di IA applicati alla produzione editoriale.",
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"pt-BR": "Manuel Bosque cobre software na Softonic: programas para desktop, ferramentas de produtividade e pequenos utilitários que resolvem bem um problema só. Seu critério é prático — o que um programa realmente faz, o que pede em troca e para quem serve — e por isso desconfia de listas de recursos e prefere testar. Faz parte da equipe que define como o software é abordado no site e trabalha diariamente com ferramentas de IA aplicadas à produção editorial."
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