Peer-reviewed article
Innovating responsibly: ethical considerations for AI in early childhood education
Ilene R. Berson, Michael J. Berson, Wenwei Luo ·
Summary
Written by AI, not yet AICS's view · claude-haiku-4-5-20251001This scoping review of 42 studies examines ethical challenges arising from the use of artificial intelligence in early childhood education. The research identifies four major concerns: inadequate data privacy protections for children, risks from emotional AI tools that may undermine relational learning, algorithmic bias that perpetuates inequities, and fragmented regulatory frameworks. The authors call for global frameworks that prioritize transparency, data minimization, and the involvement of educators, parents, and children in AI design decisions.
Key points
- Significant gaps exist in safeguarding children's sensitive data, with inadequate protections against breaches, profiling, and misuse
- Emotional AI tools such as social robots and emotion-recognition technologies risk undermining relational learning and fostering overreliance, manipulation, or loss of autonomy
- AI systems often lack developmentally appropriate design, failing to align with the unique needs of young learners
- Algorithmic bias driven by non-representative datasets perpetuates systemic inequities and disproportionately affects marginalized communities
- Regulatory frameworks are fragmented and inconsistent, often lacking provisions tailored to children's vulnerabilities
Limitations
This is a scoping review synthesizing findings from existing studies rather than empirical research, so it cannot provide definitive evidence about the extent or severity of these ethical issues in practice. The review does not evaluate the effectiveness of any specific interventions or solutions to address these challenges.
Abstract
Abstract The rapid integration of artificial intelligence (AI) into early childhood education (ECE) presents transformative possibilities but raises urgent ethical challenges that demand immediate attention. This scoping review examines 42 studies to explore key ethical concerns in four interconnected areas: data privacy, impacts on child development, algorithmic bias, and regulatory frameworks. Findings reveal significant gaps in safeguarding children’s sensitive data, with inadequate protections against breaches, profiling, and misuse. Emotional AI tools, such as social robots and emotion-recognition technologies, offer novel learning opportunities but risk undermining relational learning and fostering overreliance, manipulation, or loss of autonomy. The lack of developmentally appropriate design in AI systems further exacerbates these risks, failing to align technological solutions with the unique needs of young learners. Algorithmic bias, driven by non-representative datasets, perpetuates systemic inequities, disproportionately affecting marginalized communities and eroding fairness. Regulatory frameworks are fragmented and inconsistent, often lacking provisions tailored to the vulnerabilities of children or mechanisms for global enforcement. To address these challenges, this study highlights the urgency of establishing global frameworks that prioritize transparency, data minimization, and cultural inclusivity. Engaging educators, parents, and children in participatory governance is essential to align AI design with developmental needs and uphold children’s rights. These findings underscore the need for immediate and sustained efforts to ensure that AI systems in ECE foster equitable and ethical learning environments, safeguarding the well-being of young learners while advancing innovation responsibly.