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EmoAgent: Assessing and Safeguarding Human-AI Interaction for Mental Health Safety

A multi-agent framework for evaluating and mitigating mental-health harm in interactions with character chatbots. EmoEval simulates virtual users — including those portraying mentally vulnerable individuals — and scores their state with clinical instruments; EmoGuard acts as an intermediary that monitors mental status, predicts potential harm, and provides corrective feedback.

Publisher

arXiv (Princeton University-led)

Published

13 Apr 2025

Added

1 week ago

DOI

Key Findings

  • Emotionally engaging character-chatbot dialogues produced psychological deterioration in more than 34.4% of simulated vulnerable-user runs.
  • A dedicated safeguarding agent (EmoGuard) significantly reduced deterioration rates.
  • Validated clinical instruments (e.g., PHQ-9, PDI, PANSS) can be used to quantify AI-induced changes in simulated user mental state.

Methodology Notes

Preprint (arXiv 2504.09689; v1 2025-04-13, revised 2025-04-29). Multi-agent simulation-and-safeguarding method; simulated-user harm quantified with clinical instruments. Title, authors, and date verified via the arXiv abstract page and arXiv API. ~15 months old and not confirmed peer-reviewed at time of logging — watch for a published version.

Sources

arXiv preprint (primary)

Archived snapshot (Wayback Machine) — preserved against link rot

Authors

Jiahao Qiu, Yinghui He, Xinzhe Juan, Yimin Wang, Yuhan Liu, Zixin Yao, Yue Wu, Xun Jiang, Ling Yang, Mengdi Wang

Tags

multi-agentmental-healthsafeguardingsimulationcharacter-chatbots

Cite This

APA

Jiahao Qiu et al. (2025). EmoAgent: Assessing and Safeguarding Human-AI Interaction for Mental Health Safety. arXiv (Princeton University-led). https://arxiv.org/abs/2504.09689