AI Safety Training Can be Clinically Harmful
Large language models are being deployed as mental health support agents at scale, yet only 16% of LLM-based chatbot interventions have undergone rigorous clinical efficacy testing, and simulations reveal psychological deterioration in over one-third of cases. We evaluate four generative models on 250 Prolonged Exposure (PE) therapy scenarios and 146 CBT cognitive restructuring exercises (plus 29 severity-escalated variants), scored by a three-judge LLM panel. All models scored near-perfectly on surface acknowledgment (~0.91-1.00) while therapeutic appropriateness collapsed to 0.22-0.33 at the highest severity for three of four models, with protocol fidelity reaching zero for two. Under C...
| Authors | Suhas BN, Andrew M. Sherrill, Rosa I. Arriaga et al. |
|---|---|
| Primary category | cs.CL |
| Published | 25 April 2026 |
| Last updated at source | 25 April 2026 |
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