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Expressing stigma and inappropriate responses prevents LLMs from safely replacing mental health providers.

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Resumen del artículo

Título de Paperzilla
LLMs Express Stigma and Respond Inappropriately in Mental Health Scenarios

This study investigates the suitability of large language models (LLMs) as replacements for mental health providers. The authors find that LLMs exhibit stigma towards certain mental health conditions and often respond inappropriately to sensitive situations, even with safety guidelines and training. The research highlights the potential harm of deploying LLMs as therapists and emphasizes the need for caution and further research.

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Scientists found that computer programs aren't ready to be therapists because they sometimes say mean or unhelpful things about people's feelings. This means we need to be very careful before letting them help people with their mental health.

Posibles conflictos de intereses

One author is a psychiatrist, and the study acknowledges funding from Microsoft and the Toyota Research Institute.

Limitaciones identificadas

Limited scope of mental health conditions
The study focuses on a limited set of mental health conditions and symptoms, which may not generalize to the full spectrum of mental health issues encountered in clinical practice.
Limited evaluation methods
While the study draws on established clinical guidelines, the evaluation of LLM responses is based on a limited set of experiments and benchmarks.
Focus on CBT
The study primarily uses cognitive behavioral therapy (CBT) manuals as guidance, which may not represent the diversity of therapeutic approaches used in practice.
Limitations of transcripts and stimuli
The study acknowledges potential limitations in the representativeness of therapy transcripts used and the potential for non-sequiturs in the experimental setup.
Limited to current text-based LLMs
The study focuses on current LLMs and may not be applicable to future AI systems or those with different modalities (e.g., voice).

Explicación de la calificación

This paper presents a well-structured and important investigation into the limitations of current LLMs in mental health applications. It combines a review of clinical guidelines with targeted experiments, highlighting significant concerns about stigma and inappropriate responses. While the study acknowledges its limitations in scope and methodology, the findings are valuable and contribute to a growing body of literature on the responsible development of AI for mental health.

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Jerarquía temática

Campo: Psicología

Información del archivo

Título original: Expressing stigma and inappropriate responses prevents LLMs from safely replacing mental health providers.
Subido: 19 jul 2025, 12:53:21
Privacidad: Público