Describe Me Something You Do Not Remember - Challenges and Risks of Exposure Design Using Generative Artificial Intelligence for Therapy of Complex Post-traumatic Disorder

2025-05-27

AI Summary

Current visualization-based exposure therapies for Complex Post-Traumatic Stress Disorder (CPTSD) lack low-cost, customizable solutions tailored to highly individualized trauma memories, while generative AI (GAI) introduces uncontrolled safety risks. This study proposes the first GAI-driven, patient-active exposure visualization paradigm, integrating text-to-image generation, controllable image editing, evidence-based clinical exposure protocols, and human-centered interaction design. We establish a tripartite collaborative framework—comprising patient, clinician, and AI—that explicitly addresses risk modeling and safety alignment. For the first time, we systematically define six core risk dimensions of AI deployment in CPTSD treatment and propose corresponding mitigation strategies. These yield an interdisciplinary GAI exposure design principle framework and a clinical safety guideline, providing both theoretical foundations and implementable pathways for personalized, safe, and deployable AI-augmented psychological interventions.

Technology Category

• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness
• Humans and AI: AI for Accessibility
• Cognitive Modeling & Cognitive Systems: Computational Creativity

Application Category

• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

Post-traumatic stress disorder (PTSD) is associated with sudden, uncontrollable, and intense flashbacks of traumatic memories. Trauma exposure psychotherapy has proven effective in reducing the severity of trauma-related symptoms. It involves controlled recall of traumatic memories to train coping mechanisms for flashbacks and enable autobiographical integration of distressing experiences. In particular, exposure to visualizations of these memories supports successful recall. Although this approach is effective for various trauma types, it remains available for only a few. This is due to the lack of cost-efficient solutions for creating individualized exposure visualizations. This issue is particularly relevant for the treatment of Complex PTSD (CPTSD), where traumatic memories are highly individual and generic visualizations do not meet therapeutic needs. Generative Artificial Intelligence (GAI) offers a flexible and cost-effective alternative. GAI enables the creation of individualized exposure visualizations during therapy and, for the first time, allows patients to actively participate in the visualization process. While GAI opens new therapeutic perspectives and may improve access to trauma therapy, especially for CPTSD, it also introduces significant challenges and risks. The extreme uncertainty and lack of control that define both CPTSD and GAI raise concerns about feasibility and safety. To support safe and effective three-way communication, it is essential to understand the roles of patient, system, and therapist in exposure visualization and how each can contribute to safety. This paper outlines perspectives, challenges, and risks associated with the use of GAI in trauma therapy, with a focus on CPTSD.

Problem

• Lack of cost-efficient solutions for individualized trauma exposure visualizations
• Challenges in using Generative AI for safe CPTSD therapy
• Need to define roles in patient-system-therapist communication for safety

Innovation

• Generative AI creates personalized trauma visualizations
• Patients actively participate in visualization process
• Addresses safety in AI-therapist-patient interaction