Abstract Generative AI (GenAI) is rapidly transforming children’s education, unlocking unprecedented opportunities for personalized learning while simultaneously introducing significant risks related to data privacy and information integrity. A critical question emerges: How can we empower young learners to navigate this complex digital landscape safely and critically? While the discourse on AI literacy is growing, there remains a pronounced gap in frameworks designed specifically for children, particularly ones that address the ethical dimensions of the GenAI era. This paper introduces a novel educational framework that leverages blockchain’s pedagogical affordances specifically its transparency, immutability, and traceability as a teaching tool to help children understand trust, provenance, and critical evaluation in AI-generated content. Rather than using blockchain for administrative purposes (e.g., credentials), this framework transforms it into an interactive learning interface where children visually trace content origins and verify information sources in a trustworthy and privacy-centric learning environment. We argue that the architectural principles of blockchain decentralization, immutability, and transparency can serve as a pedagogical tool to make abstract AI concepts tangible for children. Our framework utilizes blockchain to create verifiable, tamper-proof records for educational content and learning pathways, directly addressing concerns of misinformation and data vulnerability. This paper offers a pedagogical blueprint fostering critical AI literacy through three core principles: Tangible Trust (blockchain-anchored provenance verification), Experiential Privacy (visible federated learning), and Explainable Systems (progressive disclosure demystifying AI’s opacity). This work presents more than a technical solution; it offers a pedagogical blueprint to foster a deeper, more critical AI literacy, equipping children to become responsible and empowered digital citizens.
Abedi et al. (Tue,) studied this question.