arXiv:2601.06875cs.AIcs.CL2026-01被引 1

用非洲的集体主义哲学重构心理对话AI,让算法更懂当地人心。

An Ubuntu-Guided Large Language Model Framework for Cognitive Behavioral Mental Health Dialogue

  • 将认知行为疗法与非洲'乌班图'哲学结合,重塑心理对话框架
  • 模型在专家评估中展现共情与文化契合度,符合治疗目标
  • 适合需要本土化心理健康支持的非洲地区或跨文化研究者

南非日益严峻的心理健康危机,因缺乏文化适配的护理服务而加剧。尽管大语言模型在心理支持方面前景广阔,但其主要基于西方数据训练,难以适应非洲语境。本研究提出一个概念验证框架,将认知行为疗法(CBT)与非洲哲学‘乌班图’(Ubuntu)融合,构建具有文化敏感性与情感智能的AI心理对话系统。采用设计科学方法,实现深层理论与治疗层面、以及表层语言与交流方式的文化适配。关键CBT技术如行为激活和认知重构,通过强调集体福祉、精神根基与相互关联性的乌班图理念重新诠释。通过迭代的语言简化、精神语境化与乌班图式重构,开发了文化适配的数据集。微调后的模型经临床心理学专家指导的案例研究评估,使用UniEval进行对话质量评估,并结合CBT可靠性与文化语言契合度指标。结果表明,模型能有效开展具同理心、情境感知的对话,符合治疗与文化双重目标。虽尚未开展实时用户测试,但模型已接受领域专家的严格审查与监督。研究凸显文化嵌入的情感智能对提升AI心理干预在非洲场景中的情境相关性、包容性与有效性的重要潜力。

原文摘要 · Abstract (English)

South Africa's escalating mental health crisis, compounded by limited access to culturally responsive care, calls for innovative and contextually grounded interventions. While large language models show considerable promise for mental health support, their predominantly Western-centric training data limit cultural and linguistic applicability in African contexts. This study introduces a proof-of-concept framework that integrates cognitive behavioral therapy with the African philosophy of Ubuntu to create a culturally sensitive, emotionally intelligent, AI-driven mental health dialogue system. Guided by a design science research methodology, the framework applies both deep theoretical and therapeutic adaptations as well as surface-level linguistic and communicative cultural adaptations. Key CBT techniques, including behavioral activation and cognitive restructuring, were reinterpreted through Ubuntu principles that emphasize communal well-being, spiritual grounding, and interconnectedness. A culturally adapted dataset was developed through iterative processes of language simplification, spiritual contextualization, and Ubuntu-based reframing. The fine-tuned model was evaluated through expert-informed case studies, employing UniEval for conversational quality assessment alongside additional measures of CBT reliability and cultural linguistic alignment. Results demonstrate that the model effectively engages in empathetic, context-aware dialogue aligned with both therapeutic and cultural objectives. Although real-time end-user testing has not yet been conducted, the model underwent rigorous review and supervision by domain specialist clinical psychologists. The findings highlight the potential of culturally embedded emotional intelligence to enhance the contextual relevance, inclusivity, and effectiveness of AI-driven mental health interventions across African settings.

心理AI乌班图文化适配对话系统

Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品;中文卡片由大模型生成,请以原文为准。