Large Language Models (LLMs) have become valuable assets in mental health, showing promise in both classification tasks and counseling applications. This paper offers a perspective on using LLMs in mental health applications. It discusses the instability of generative models for prediction and the potential for generating hallucinatory outputs, underscoring the need for ongoing audits and evaluations to maintain their reliability and dependability. The paper also distinguishes between the often interchangeable terms ``explainability'' and ``interpretability'', advocating for developing inherently interpretable methods instead of relying on potentially hallucinated self-explanations generated by LLMs. Despite the advancements in LLMs, human counselors' empathetic understanding, nuanced interpretation, and contextual awareness remain irreplaceable in the sensitive and complex realm of mental health counseling. The use of LLMs should be approached with a judicious and considerate mindset, viewing them as tools that complement human expertise rather than seeking to replace it.

翻译：大语言模型已成为心理健康领域的重要工具，在分类任务和咨询应用中展现出潜力。本文从视角层面探讨了大语言模型在心理健康应用中的使用，分析了生成模型在预测时的不稳定性及产生幻觉输出的可能性，强调需持续进行审计与评估以保障其可靠性与可信度。论文还区分了常被混用的"可解释性"与"可理解性"概念，主张发展内在可解释的方法，而非依赖大语言模型可能产生的幻觉式自解释。尽管大语言模型取得显著进展，但人类咨询师的情感理解、细腻诠释和情境感知能力在敏感复杂的心理健康咨询领域中仍不可替代。使用大语言模型时需秉持审慎思考的态度，将其视为补充人类专业知识的工具，而非寻求替代人类。