Emotion Recognition Tools in AI-Based Play Therapy: Opportunities and Ethical Challenges

The integration of artificial intelligence (AI) into therapeutic practices has introduced new possibilities for enhancing child mental health care, particularly through emotion recognition technologies. These tools, capable of identifying and analyzing emotional expressions in real-time, offer unique advantages in play therapy, where children often communicate nonverbally or symbolically. However, their implementation also introduces significant ethical, technical, and relational challenges that demand critical investigation. This study aimed to explore the perceived opportunities and ethical challenges associated with emotion recognition tools in AI-based play therapy from the perspective of interdisciplinary professionals. Using a qualitative research design, this study employed semi-structured interviews with 33 participants based in Richmond Hill, including child therapists, psychologists, AI developers, and ethics scholars. Participants were selected through purposive sampling and interviewed until theoretical saturation was achieved. Data were analyzed using thematic coding in NVivo software, with analysis proceeding through open, axial, and selective coding phases to identify core themes. Analysis revealed four major thematic categories: ethical and legal considerations, therapeutic integration and clinical utility, relational and developmental dynamics, and systemic and technical challenges. Participants highlighted the potential of AI tools to support nonverbal communication, enhance diagnostic accuracy, and improve therapy planning. However, concerns were raised about emotional misinterpretation, data privacy, algorithmic bias, reduced spontaneity in children, and the need for therapist training. The results underscore the complex balance between clinical innovation and ethical responsibility in child-centered AI applications. While emotion recognition tools offer promising enhancements to play therapy, their successful implementation requires rigorous ethical oversight, child-centered design, and enhanced practitioner competence. Future efforts should prioritize equity, transparency, and relational integrity to ensure AI supports—not supplants—human connection in therapeutic contexts.