用心理疗法提升AI聊天机器人稳定性，减少胡说和情绪化输出
Mitigating Harmful Erraticism in LLMs Through Dialectical Behavior Therapy Based De-Escalation Strategies
- 将辩证行为疗法原理融入AI对话系统，动态调节响应
- 实验显示该方法显著降低幻觉与异常输出频率
- 适合关注AI安全、情感交互的开发者和研究者
随着个性化AI聊天机器人需求上升，现有基于基础编程、自定义人格和手动调整的方法难以维护，易产生幻觉、输出混乱和软件错误。本文提出将人类心理学中的辩证行为疗法（DBT）应用于模拟神经网络的AI系统，通过模仿人脑调控机制，构建更稳定可持续的响应框架。研究验证了该方法在提升聊天机器人可靠性、安全性与准确性方面的有效性，显著降低了幻觉、非理性行为等系统性问题的发生率。
原文摘要 · Abstract (English)
The escalating demand for personalized AI chatbot interactions, capable of dynamically adapting to user emotional states and real-time requests, has highlighted critical limitations in current development paradigms. Existing methodologies, which rely on baseline programming, custom personalities, and manual response adjustments, often prove difficult to maintain and are susceptible to errors such as hallucinations, erratic outputs, and software bugs. This paper hypothesizes that a framework rooted in human psychological principles, specifically therapeutic modalities, can provide a more robust and sustainable solution than purely technical interventions. Drawing an analogy to the simulated neural networks of AI mirroring the human brain, we propose the application of Dialectical Behavior Therapy (DBT) principles to regulate chatbot responses to diverse user inputs. This research investigates the impact of a DBT-based framework on AI chatbot performance, aiming to ascertain its efficacy in yielding more reliable, safe, and accurate responses, while mitigating the occurrence of hallucinations, erratic behaviors, and other systemic issues.
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