Haber Yuval, Hadar Shoval Dorit, Levkovich Inbar, Yinon Dror, Gigi Karny, Pen Oori, Angert Tal, Elyoseph Zohar
The Program of Hermeneutics and Cultural Studies, Interdisciplinary Studies Unit, Bar-Ilan University, Jerusalem, Israel.
Department of Psychology, Max Stern Academic College of Emek Yezreel, Yezreel Valley, Israel.
Front Digit Health. 2025 Feb 4;7:1512273. doi: 10.3389/fdgth.2025.1512273. eCollection 2025.
Externalization techniques are well established in psychotherapy approaches, including narrative therapy and cognitive behavioral therapy. These methods elicit internal experiences such as emotions and make them tangible through external representations. Recent advances in generative artificial intelligence (GenAI), specifically large language models (LLMs), present new possibilities for therapeutic interventions; however, their integration into core psychotherapy practices remains largely unexplored. This study aimed to examine the clinical, ethical, and theoretical implications of integrating GenAI into the therapeutic space through a proof-of-concept (POC) of AI-driven externalization techniques, while emphasizing the essential role of the human therapist.
To this end, we developed two customized GPTs agents: VIVI (visual externalization), which uses DALL-E 3 to create images reflecting patients' internal experiences (e.g., depression or hope), and DIVI (dialogic role-play-based externalization), which simulates conversations with aspects of patients' internal content. These tools were implemented and evaluated through a clinical case study under professional psychological guidance.
The integration of VIVI and DIVI demonstrated that GenAI can serve as an "artificial third", creating a Winnicottian playful space that enhances, rather than supplants, the dyadic therapist-patient relationship. The tools successfully externalized complex internal dynamics, offering new therapeutic avenues, while also revealing challenges such as empathic failures and cultural biases.
These findings highlight both the promise and the ethical complexities of AI-enhanced therapy, including concerns about data security, representation accuracy, and the balance of clinical authority. To address these challenges, we propose the SAFE-AI protocol, offering clinicians structured guidelines for responsible AI integration in therapy. Future research should systematically evaluate the generalizability, efficacy, and ethical implications of these tools across diverse populations and therapeutic contexts.
外化技术在心理治疗方法中已得到广泛应用，包括叙事疗法和认知行为疗法。这些方法激发诸如情感等内在体验，并通过外部表征使其变得具体可感。生成式人工智能（GenAI），特别是大语言模型（LLMs）的最新进展为治疗干预带来了新的可能性；然而，它们在核心心理治疗实践中的整合在很大程度上仍未得到探索。本研究旨在通过人工智能驱动的外化技术的概念验证（POC）来检验将GenAI整合到治疗空间中的临床、伦理和理论意义，同时强调人类治疗师的重要作用。
为此，我们开发了两个定制的GPT代理：VIVI（视觉外化），它使用DALL-E 3创建反映患者内在体验（如抑郁或希望）的图像，以及DIVI（基于对话角色扮演的外化），它模拟与患者内在内容各方面的对话。这些工具在专业心理指导下通过临床案例研究进行实施和评估。
VIVI和DIVI的整合表明，GenAI可以充当“人工第三者”，创造一个温尼科特式的游戏空间，增强而不是取代治疗师与患者的二元关系。这些工具成功地将复杂的内在动态外化，提供了新的治疗途径，同时也揭示了诸如共情失败和文化偏见等挑战。
这些发现凸显了人工智能增强治疗的前景和伦理复杂性，包括对数据安全、表征准确性和临床权威平衡的担忧。为应对这些挑战，我们提出了SAFE-AI协议，为临床医生在治疗中负责任地整合人工智能提供结构化指导方针。未来的研究应该系统地评估这些工具在不同人群和治疗背景下的普遍性、有效性和伦理意义。
