Assessing and alleviating state anxiety in large language models.

Ben-Zion, Ziv; Witte, Kristin; Jagadish, Akshay K; Duek, Or; Harpaz-Rotem, Ilan; Khorsandian, Marie-Christine; Burrer, Achim; Seifritz, Erich et al. · NPJ Digit Med · 2025

basic_science · Level V

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Abstract

The use of Large Language Models (LLMs) in mental health highlights the need to understand their responses to emotional content. Previous research shows that emotion-inducing prompts can elevate "anxiety" in LLMs, affecting behavior and amplifying biases. Here, we found that traumatic narratives increased Chat-GPT-4's reported anxiety while mindfulness-based exercises reduced it, though not to baseline. These findings suggest managing LLMs' "emotional states" can foster safer and more ethical human-AI interactions.