Innovating responsibly: ethical considerations for AI in early childhood education

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.