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Design Exploration of AI-Assisted Personal Affective Physicalization.

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    AI aids in designing tangible personal emotion representations, called personal affective physicalization. This study explores AI-human co-creation, revealing insights into creative processes and future research directions for emotion-driven design.

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    Area of Science:

    • Human-Computer Interaction
    • Affective Computing
    • Design Research

    Background:

    • Personal Affective Physicalization involves expressing emotions through tangible forms.
    • Designing these physical data representations is challenging due to the abstract nature of emotions.
    • Artificial Intelligence (AI) shows potential in emotion detection and design assistance.

    Purpose of the Study:

    • To explore AI-assisted design opportunities for personal affective physicalization.
    • To investigate AI-human co-creation dynamics in emotion representation design.
    • To identify challenges and future research agendas in this domain.

    Main Methods:

    • Employed a Research-through-Design methodology.
    • Developed PhEmotion, a tool integrating LLM-extracted emotion values into parametric artifact design.
    • Conducted a lab study with 14 participants, comparing AI-supported and unsupported artifact creation.

    Main Results:

    • Observed variations in participants' creative strategies and meaning-making processes.
    • Documented participants' perceptions of AI support during co-creation.
    • Identified key tensions in the AI-human co-creation process.

    Conclusions:

    • AI can assist in designing personal affective physicalizations.
    • AI-human co-creation presents nuanced challenges and opportunities.
    • Findings inform future research in AI-assisted emotion representation design.