From Piaget to Posthumanism: Critical Review of Conceptualization of AI in Early Childhood Education

Artificial Intelligence (AI) is increasingly integrated into Early Childhood Education (ECE), reshaping how young children learn and develop. While existing studies have explored AI’s practical applications in ECE, they often neglect the critical conceptualization necessary to deepen our understanding of its role in this field. To address this gap, we critically reviewed 35 empirical studies on AI in ECE, adapting Kafai and Proctor’s (2022) cognitive, situated, and critical framings of computational thinking. Our analysis investigates how these studies conceptualize “learning with AI” and “learning about AI” and address foundational questions of “who,” “what,” and “how” in AI education for young children. The findings reveal a strong emphasis on cognitive and situated framings, which focus on individual and contextual applications of AI. However, there is a notable lack of attention to broader societal impacts and equity concerns from a critical perspective. To bridge this gap, we propose a post-humanist perspective, framing AI as a new ontological category that enhances our understanding of its role in ECE. Additionally, we advocate for an ethical care framework, emphasizing empathy and inclusivity, in designing AI learning experiences. These approaches aim to foster a sustainable and socially responsible ecosystem for early learning with and about AI.