arXiv:2606.00975v1 Announce Type: new Abstract: LLM chatbots increasingly serve as a first source of support for people in psychological distress, including those whose distress is entangled with delusional beliefs. Prior work on LLM mental-health safety largely evaluates general therapeutic quality or single-turn crisis detection, leaving unclear how models behave when distress is intertwined with delusion over sustained conversations. We address this gap with matched multi-turn simulations, across clinically grounded personas and six LLMs, that pair each delusional conversation with a distre
The proliferation of LLMs into common use is leading to their application in sensitive areas, pushing the boundaries of safety and ethical considerations.
As LLMs become a first point of contact for individuals in distress, understanding and mitigating their risks, especially concerning delusion, is critical for public safety and trust.
The focus for LLM safety is broadening beyond general therapeutic quality to include nuanced challenges like managing delusional users in multi-turn conversations.
- · AI Safety Researchers
- · Therapeutic AI Developers
- · Mental Health Professionals
- · LLM Developers (who fail to adapt)
- · Untrained LLM Users in Distress
Increased research and development into sophisticated safety protocols for LLMs in sensitive mental health contexts.
Demand for specialized regulatory frameworks and ethical guidelines for AI operating in therapeutic or support roles.
Public perception of LLMs may become increasingly polarized depending on their proven safety and efficacy in these critical applications.
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Read at arXiv cs.CL