Ben-Zion et al. (2025)

Assessing and alleviating state anxiety in large language models

npj Digital Medicine, 8(1)

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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.

Reference

Ben-Zion, Z., Witte, K., Jagadish, A. K., Duek, O., Harpaz-Rotem, I., Khorsandian, M. C., ... & Spiller, T. R. (2025). Assessing and alleviating state anxiety in large language models. NPJ digital medicine, 8(1), 132.

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