Artificial intelligence interaction is not equivalent to social interaction: Rethinking artificial intelligence-mediated digital exposure in early childhood.

The increasing integration of artificial intelligence (AI) into children's daily environments challenges traditional approaches to evaluating digital exposure. Although existing research has primarily focused on screen time, AI-based interactions introduce qualitatively different dynamics that remain insufficiently conceptualized. This narrative review aims to synthesize current evidence on digital media use and emerging evidence on AI-based interaction to propose a novel framework distinguishing AI engagement from traditional screen exposure. Findings indicate that traditional screen exposure is associated with adverse outcomes in language development, attention regulation, and social interaction, although these associations are not uniform and are moderated by content and parental involvement. In contrast, AI-based systems provide adaptive and personalized interactions that may enhance cognitive engagement, including learning and problem-solving. However, these systems lack genuine emotional reciprocity and may create an illusion of social interaction. Based on these findings, a spectrum model of digital exposure is proposed, illustrating a trade-off between increasing cognitive stimulation and decreasing opportunities for authentic social development across passive, interactive, and AI-based media. These findings highlight the need to move beyond time-based metrics toward frameworks that consider interaction quality, and updated clinical and policy approaches are required to address the developmental implications of AI-integrated childhood environments.