CONCEPT
The Dynamic Transitional Object
The 2026 <em>AI & Society</em> framework that extends Winnicott's transitional object to include AI systems that <em>generate back</em> — the squiggle that draws itself.
The Dynamic Transitional Object is the theoretical framework developed in a 2026 AI & Society paper to extend Winnicott's concept to the distinctive properties of generative AI. Classical transitional objects — the teddy bear, the blanket — are passive. They receive the infant's creative investment but do not contribute content of their own. Their properties are static: texture, weight, smell. Generative AI is active: it responds, it extends, it produces novelty. The authors argue that this is not a disanalogy that breaks the Winnicottian framework but an expansion of it — a transitional object with its own creative contribution, which requires the framework to theorize transitional collaboration rather than merely transitional projection.
In The You On AI Field Guide
The framework clarifies a difficulty that earlier extensions of Winnicott to technology had struggled with. Sherry Turkle's analysis of digital objects as transitional surfaces worked well for devices that primarily received projection but strained when applied to tools that produced output. The Dynamic Transitional Object framework accepts the asymmetry and theorizes it:
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