Detecting Machine-Generated Texts: Not Just "AI vs Humans" and Explainability is Complicated

Understand

As LLMs rapidly advance, increasing concerns arise regarding risks about actual authorship of texts we see online and in real world.

• The task of distinguishing LLM-authored texts is complicated by the nuanced and overlapping behaviors of both machines and humans.
• In this paper, we challenge the current practice of considering LLM-generated text detection a binary classification task of differentiating human from AI.
• Instead, we introduce a novel ternary text classification scheme, adding an "undecided" category for texts that could be attributed to either source, and we show that this new category is crucial to understand how to make the detection result more explainable to lay users.