AI-Enhanced Creative Interaction for Personalized Music-Based Mental Wellness Support
Keywords:
artificial intelligence, music information retrieval, mental wellness, creative interaction, personalization, socio-technical systems, digital mental healthAbstract
The convergence of artificial intelligence, music information retrieval, and digital mental health has created new possibilities for personalized wellness support that extend beyond passive music listening. This paper examines AI-enhanced creative interaction for music-based mental wellness from a systems perspective, focusing on architectural trade-offs, personalization mechanisms, affective interaction, governance, and deployment sustainability. Rather than treating generative music or recommendation as isolated technical tasks, the analysis emphasizes how creative co-creation, real-time adaptation, and human-AI interaction can support emotional regulation, engagement, and self-expression. The paper discusses structural tensions between clinical validity and creative openness, personalization and privacy, low-latency interactivity and model complexity, and equitable access and algorithmic fairness. Drawing on socio-technical systems research, ethical AI frameworks, and human-computer interaction literature, the paper develops a conceptual architecture for personalized music-based wellness support that integrates affective modeling, generative music systems, creative interaction loops, and governance mechanisms. It further examines deployment considerations across university counseling settings, community mental health services, and consumer wellness platforms, highlighting the importance of transparent evaluation, data stewardship, and multi-stakeholder oversight. The paper argues that sustainable AI-enhanced music wellness systems must be designed not only for technical performance but also for trustworthiness, interpretability, fairness, and long-term organizational embedding. Future research directions include longitudinal evaluation of creative interaction outcomes, cross-cultural adaptation, and the development of certification frameworks for AI-mediated wellness technologies.
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