ACM DIS 2026 Workshop

Human-Centered AI for Expressive Arts Therapy

Designing for Mental Well-Being and Creativity

Workshop Overview

Expressive arts therapy supports creative expression through visual art, music, dance, and drama, fostering emotional awareness, regulation, and personal growth. Recent advances in generative AI, particularly multimodal models that produce images, music, text, and soundscapes, create new opportunities to scaffold creative exploration, provide adaptive prompts, and support reflective dialogue in therapeutic contexts. At the same time, integrating AI into expressive arts therapy raises important challenges around agency, authorship, emotional alignment, ethics, data privacy, and preserving therapeutic relationships.

This workshop brings together researchers, designers, therapists, and practitioners to explore how human-centered AI can support creativity in art and music therapy while respecting therapeutic values. We focus on insights from AI-enabled therapy systems, design approaches balancing creativity and emotional well-being, and evaluation methods that extend beyond usability and traditional clinical outcomes. Through interdisciplinary discussion, the workshop aims to surface open research questions and design considerations for AI use in expressive arts therapy.

🎨 Creative Expression
đź§  Mental Well-being
🤝 Human-AI Collaboration

Call for Participation: Human-Centered AI for Expressive Arts Therapy

Advances in generative and multimodal AI are opening new possibilities for supporting creativity, emotional expression, and mental well-being. At the same time, integrating AI into expressive arts therapy raises critical questions about agency, ethics, evaluation, and the role of human care. This workshop brings together researchers, designers, artists, and therapists to critically examine how human-centered AI can support—rather than undermine—creative therapeutic practices.

We invite participants to submit short position papers, case studies describing completed, ongoing, or planned work, or reflective pieces on prior research (2–4 pages, ACM format). We also welcome alternative contributions, such as interactive or video demos and posters, that engage with topics including, but not limited to:

Submissions should describe the contributor’s perspective, experience, or open questions rather than polished results. Selected participants will be invited to give a lightning talk and/or present a poster or demo during the workshop.

Please submit materials via the workshop website by May 25, 2026 (AOE). At least one author of each accepted submission must attend the workshop in person . We welcome interdisciplinary and exploratory contributions and encourage submissions from both academic and practitioner communities.

Submission Link The registration code will be provided upon submission of your work.

Important Dates

Submission: May 25, 2026
Notification: June 1, 2026
Workshop: June 14, 2026 (Full day)

Organizers

Yucheng Jin portrait

Yucheng Jin

Assistant Professor
Duke Kunshan University
Research on human-AI collaboration and creativity support for mental well-being.
Pengcheng An portrait

Pengcheng An

Assistant Professor
SUSTech
Human-AI interaction and user-centered design for education and well-being.
Wanling Cai portrait

Wanling Cai

Assistant Professor
University College Dublin
Human-centered AI systems for decision-making and mental health contexts.
Jingyi Yang portrait

Jingyi Yang

Lecturer and Therapist
Beijing University of Chemical Technology
Arts therapy and mental health education with clinical and research focus.
Li Chen portrait

Li Chen

Professor
Hong Kong Baptist University
Personalized AI, explainability, and applications for mental well-being.
Kayley Moylan portrait

Kayley Moylan

PhD Researcher
University College Dublin
PhD research on integrating psychotherapy principles into digital technologies.
Kevin Doherty portrait

Kevin Doherty

Assistant Professor
University College Dublin
Design and clinical implementation of mental health technologies.
Gavin Doherty portrait

Gavin Doherty

Professor
Trinity College Dublin
HCI research focused on healthcare and mental health technologies.
Jiangtao Gong portrait

Jiangtao Gong

Associate Professor
Shanghai Jiao Tong University
Cognitive augmentation AI for enhancing human capabilities and well-being.

Workshop Schedule

The workshop is designed as a highly interactive, one-day event (approximately 6–8 hours), emphasizing dialogue, reflection, and hands-on engagement.

Session Description
Welcome and Introductions
15 minutes
The organizers will introduce the workshop’s motivation, goals, and structure. Participants will briefly introduce themselves and share their backgrounds and interests to establish an inclusive, interdisciplinary atmosphere.
Keynote Talks
1 hour
Two invited keynote speakers from complementary backgrounds (e.g., HCI, art therapy, music therapy, or digital mental health) will offer reflective perspectives on current practices, challenges, and emerging directions for AI-supported creative therapies.
Lightning Talks
2 hours
Accepted contributors will give short lightning talks (10 minutes each) to present ongoing projects, design cases, clinical experiences, provocations, or open questions. These talks are intended to surface diverse perspectives and tensions rather than polished results.
Group Discussions with Posters and Demos
1 hour
Participants will join small groups organized around core themes, research questions, or technologies. Groups will engage in structured co-creation activities, such as mapping aspirations, challenges, opportunities, and open questions using scaffolded visual methods. Posters and demos will serve as anchors for discussion, and outcomes will be synthesized into shared visual artifacts.
Hands-on Experiences with AI-Supported Expressive Arts Therapy Prototypes
1.5 hours
Participants will engage directly with research prototypes, interactive demos, or speculative tools. These hands-on experiences aim to ground discussion in lived interaction and embodied experience, moving beyond abstract debate.