The growing presence of Artificial Intelligence (AI) in society increases the exposure of children and youth to these technologies. In response, recent research introduced educational programs that foster AI knowledge and competencies, collectively comprising AI literacy. This study presents a systematic review of 23 articles published up to 2023 describing AI literacy programs for children and youth. We examined: (1) motivations for teaching AI literacy, (2) conceptualizations of AI literacy that informed program design, and (3) learning theories and pedagogical methods employed. The analysis identified five motivational themes: workforce, informed users, purposeful creators, advocacy, and social good. Seventeen AI literacy frameworks and conceptual models were identified and grouped into four themes: competency-based, computational, sociotechnical, and practice-based. Application of a three-dimensional model of literacy (operational, sociocultural, and critical), shows that the operational dimension predominates in both frameworks and program designs, the sociocultural dimension is less accentuated, and the critical dimension is least evident. Cognitive constructivism emerged as the dominant learning theory guiding program design, often supported by hands-on activities and project-based learning methods. This systematic review advances understanding of the conceptual drivers shaping AI literacy programs for children and youth. The findings highlight the need for stronger conceptualizations of sociocultural and critical AI literacies and for their more balanced integration into educational programs. Addressing these gaps would better support broad motivations for teaching AI to children and youth, such as fostering social and ethical understanding and agency, and guide future research towards more comprehensive and critically informed frameworks.
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