Designing Child-Friendly AI Interfaces: Six Developmentally-Appropriate Design Insights from Analysing Disney Animation

• URL: http://arxiv.org/abs/2504.08670v2
• Date: Tue, 15 Apr 2025 12:07:00 GMT
• Title: Designing Child-Friendly AI Interfaces: Six Developmentally-Appropriate Design Insights from Analysing Disney Animation
• Authors: Nomisha Kurian,
• Abstract summary: This paper bridges Artificial Intelligence design for children and children's animation.<n>The paper presents six design insights transferable to child-centred AI interface design.<n>Future directions include empirical testing, cultural adaptation, and participatory co-design.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: To build AI interfaces that children can intuitively understand and use, designers need a design grammar that truly serves children's developmental needs. This paper bridges Artificial Intelligence design for children -- an emerging field still defining its best practices -- and children's animation, a well-established field with decades of experience in engaging young viewers through emotionally resonant, cognitively accessible storytelling. Pairing Piagetian developmental theory with design pattern extraction from 52 works of Disney animation, the paper presents six design insights transferable to child-centred AI interface design: (1) emotional expressiveness and visual clarity, (2) musical and auditory scaffolding, (3) audiovisual synchrony for emotional comfort, (4) sidekick-style personas, (5) support for symbolic play and imaginative exploration, and (6) predictable and scaffolded interaction structures. These strategies -- long refined in Disney animation -- function as multimodal scaffolds for attention, understanding, and emotional attunement, thereby forming a structured design grammar familiar to children and transferable to AI interface design. By reframing cinematic storytelling as design logic for AI, the paper offers heuristics for crafting intuitive AI interfaces that align with children's cognitive stages and emotional needs. The work contributes to design theory by showing how sensory, affective and narrative techniques can inform developmentally attuned AI design for children. Future directions include empirical testing, cultural adaptation, and participatory co-design.

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