@inproceedings{varadarajan-etal-2025-consistent,
    title = "The Consistent Lack of Variance of Psychological Factors Expressed by {LLM}s and Spambots",
    author = "Varadarajan, Vasudha  and
      Giorgi, Salvatore  and
      Mangalik, Siddharth  and
      Soni, Nikita  and
      Markowitz, Dave M.  and
      Schwartz, H. Andrew",
    editor = "Alam, Firoj  and
      Nakov, Preslav  and
      Habash, Nizar  and
      Gurevych, Iryna  and
      Chowdhury, Shammur  and
      Shelmanov, Artem  and
      Wang, Yuxia  and
      Artemova, Ekaterina  and
      Kutlu, Mucahid  and
      Mikros, George",
    booktitle = "Proceedings of the 1stWorkshop on GenAI Content Detection (GenAIDetect)",
    month = jan,
    year = "2025",
    address = "Abu Dhabi, UAE",
    publisher = "International Conference on Computational Linguistics",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/2025.genaidetect-1.8/",
    pages = "111--119",
    abstract = "In recent years, the proliferation of chatbots like ChatGPT and Claude has led to an increasing volume of AI-generated text. While the text itself is convincingly coherent and human-like, the variety of expressed of human attributes may still be limited. Using theoretical individual differences, the fundamental psychological traits which distinguish people, this study reveals a distinctive characteristic of such content: AI-generations exhibit remarkably limited variation in inferrable psychological traits compared to human-authored texts. We present a review and study across multiple datasets spanning various domains. We find that AI-generated text consistently models the authorship of an {\textquotedblleft}average{\textquotedblright} human with such little variation that, on aggregate, it is clearly distinguishable from human-written texts using unsupervised methods (i.e., without using ground truth labels). Our results show that (1) fundamental human traits are able to accurately distinguish human- and machine-generated text and (2) current generation capabilities fail to capture a diverse range of human traits"
}