Emotive Journeys
AI-Powered experience that connects therapeutic arts with emotional expression
Project Scope
Target Learning Audience: Young adults who are struggling with mental health issues, and a secondary target audience for individuals who are particularly interested in therapeutic arts
Identified Learning Need For our project, we would like our target audience to be young adults who are struggling with emotional mental health issues. Mental health awareness is a pivotal issue among young adults. The National Institute of Mental Health (NIMH) statistics shows that young adults (age 18–25) have the highest rates of mental illness. We would like to address these issues through the lens of art inquiry and creative arts therapy. We will create an interactive virtual art experience, which will include an in-person component that can be implemented by a young adult icon to create engagement and enhance reliability or a tour guide. We hope this app will support young adults by equipping them with therapeutic skills on how to navigate their emotional issues through creativity and art (visual art, poems, music, and digital takeaways).
Rationale for AI Assistance • Recommendation of content tailored to user emotions via sentiment analysis algorithms (e.g., comforting poetry, color-based art suggestions, music generation) • Detection of negative emotional patterns and guidance on emotion regulation techniques to facilitate creative shifts • Establishment of a human-AI collaborative socio-emotional learning environment to enhance interaction between users and offline components (guides or leaders) AI can provide enhanced digital support, such as offering positive content for users. This will allow AI to create algorithms to identify and analyze emotional cues from user input. AI can guide users through therapeutic techniques that help manage and reduce negative emotions and thought patterns by applying creative art outlets. We also want to implement a social-emotional element within our app that will work as a human-AI collaborative learning experience. This will allow the user to interact with the in-person component to enhance engagement and socio-emotional awareness and development.
References: • Shojaei F, Shojaei F, Osorio Torres J, Shih PC. Insights From Art Therapists on Using AI-Generated Art in Art Therapy: Mixed Methods Study. JMIR Form Res. 2024 Dec 4;8:e63038. • Li, X., Kim, J., & Patel, S. (2024). Exploring the Use of ChatGPT as an AI-Based Emotional Support Agent for Mental Health Assistance. Computers in Human Behavior, 158, 108–122. • National Institute of Mental Health. (2024). [Mental Illness]. U.S. Department of Health and Human Services, National Institutes of Health [Internet]. Retrieved October 6, 2025, from [https://www.nimh.nih.gov/health/statistics/mental-illness]
Needfinding
Learner Needs
- There is a need to detect negative emotional patterns to address and help identify recurring negative thoughts and behaviors.
- There is a need to enhance interaction between users and digital support content and identify which digital support elements should be implemented to address this need. This will help to create progress tracking and personalized activities for a more personalized and effective experience.
- There is a need to implement a social emotional element to work as a social emotional element that will provide an impactful human AI collaborative experience for users. Implementing a social element through dialogue and social interactions promotes collaborative learning because this allows users to have the opportunity to use communication as an expression of their independent thoughts. The collaboration creates connections and a flow for users to engage with digital content and acquire meaning making.
- There is a need to build trust and emotional continuity between users and AI systems to sustain long-term engagement and authentic emotional expression. Immediate empathy is beneficial, but users also require consistent tone, memory of prior interactions, and emotional reliability to feel safe sharing their thoughts over time.
##Literature Review
- Insights From Art Therapists on Using AI-Generated Art in Art Therapy (Shih et al., 2024)
Art therapists affiliated with the American Art Therapy Association participated in this study evaluating how AI can be integrated as a digital tool in therapy. They developed a prototype using cards with emotion-based keywords (emotions, feelings, relation, companion, environment, visual) and AI-generated images via ChatGPT and Adobe Express. Participants found that this tool helped them visualize and express emotions, improving confidence and creative expression throughout their emotional journey. Similar to this study, our project uses AI as a tool for emotional regulation, helping users feel secure as they process feelings and express themselves creatively.
- Exploring the Use of ChatGPT as an AI-Based Emotional Support Agent for Mental Health Assistance (Li et al., 2024)
This study explores ChatGPT’s role as an emotional support tool, identifying both its potential and limitations. Researchers found that ChatGPT’s empathetic language and immediate feedback enhanced users’ ability to articulate emotions and reflect on their thoughts. However, the study also noted the lack of emotional persistence and relational trust. These insights inform our project’s design: building a system that remembers emotional context, responds consistently with empathy, and promotes emotional continuity.
###Pain Points Identified: 1. Lack of emotional continuity — short-term empathy but no long-term memory of emotional context. 2. Limited trust-building — users hesitate to open up repeatedly without relational consistency. 3. Surface-level understanding — AI struggles with complex emotional nuances.
###Relevance to Our Project: I think this literature directly supports our project’s focus on AI-assisted emotional expression and poetic creation. It shows how ChatGPT helps users verbalize and externalize emotions, aligning with our goal of transforming emotional states into poetic language. It also points out that AI lacks emotional persistence and relational depth, reinforcing our design direction to build a system that remembers emotional context and responds with consistent empathy. Overall, I think this research provides a solid foundation for positioning AI not just as a tool, but as an emotional collaborator that co-creates meaning with users through dialogue, reflection, and shared creativity.
Team contributions We are a group of two and will divide the work on an as needed basis. The contributions below are indications of who will be leading the action item but both group members will be participating in every step.
- Latisha: Research, creative arts therapy, UI/UX design and project management.
- Jenn Choi: UI/UX design, visual storytelling, prototyping and service blueprint.
