Comparing the Humanness of Machine-Generated and Human-Authored Text
Year: 2026
Type: article
Abstract: As chatbots have become more commonplace writing tools, a need exists to understand the breadth of research about the humanness of machine-generated text via techniques that extend beyond the traditional Turing Test, in both dialogue (e.g., conversing with a chatbot) and non-dialogue (e.g., reading a news article) scenarios. To fill this gap and support future work, we survey current literature that examines and identifies humanness features of written communication generated with the state-of-the-art generative pre-trained transformer language models, provide a working definition of humanness, propose a text-based humanness taxonomy based on linguistic properties, and identify current research gaps.
Source: ACM Computing Surveys
DOI: 10.1145/3806206
Institutions: Georgetown University, Maastricht University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7143616784