Once Upon an AI: Six Scaffolds for Child-AI Interaction Design, Inspired by Disney

• URL: http://arxiv.org/abs/2504.08670v3
• Date: Fri, 15 Aug 2025 17:35:49 GMT
• Title: Once Upon an AI: Six Scaffolds for Child-AI Interaction Design, Inspired by Disney
• Authors: Nomisha Kurian,
• Abstract summary: This paper bridges artificial intelligence design for children and animation.<n>The paper presents a six scaffold framework that integrates design insights transferable to child centred AI design.<n>By reframing cinematic storytelling and child development theory as design logic for AI, the paper offers accessibles for AI that align with the cognitive stages and emotional needs of young users.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: To build AI that children can intuitively understand and benefit from, designers need a design grammar that serves their developmental needs. This paper bridges artificial intelligence design for children - an emerging field still defining its best practices - and animation, a well established field with decades of experience in engaging children through accessible storytelling. Pairing Piagetian developmental theory with design pattern extraction from 52 works of animation, the paper presents a six scaffold framework that integrates design insights transferable to child centred AI design: (1) signals for visual animacy and clarity, (2) sound for musical and auditory scaffolding, (3) synchrony in audiovisual cues, (4) sidekick style personas, (5) storyplay that supports symbolic play and imaginative exploration, and (6) structure in the form of predictable narratives. These strategies, long refined in animation, function as multimodal scaffolds for attention, understanding, and attunement, supporting learning and comfort. This structured design grammar is transferable to AI design. By reframing cinematic storytelling and child development theory as design logic for AI, the paper offers heuristics for AI that aligns with the cognitive stages and emotional needs of young users. The work contributes to design theory by showing how sensory, affective, and narrative techniques can inform developmentally attuned AI design. Future directions include empirical testing, cultural adaptation, and participatory co design.

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