Ethical Considerations in the Use of AI in Primary Education: Privacy, Bias, and Inclusivity

Abstract

The integration of Artificial Intelligence (AI) in primary education has ushered in transformative possibilities but simultaneously raises pressing ethical concerns. This paper meticulously examines the ethical dimensions of AI implementation in primary education, with a particular focus on the pivotal aspects of privacy, bias, and inclusivity. In response to the escalating need for ethical considerations in this domain, we propose a comprehensive framework that amalgamates privacy-preserving protocols, bias mitigation strategies, and inclusivity measures. Through an extensive literature survey, we identify the gaps in the current discourse and position our framework as a pioneering solution to guide educators, developers, and policymakers. The methodology employed encompasses both qualitative and quantitative approaches, involving interviews with stakeholders and a meticulous analysis of AI algorithms utilized in educational setting. Our implementation model delineates the practical steps required for the seamless integration of ethical considerations into AI systems for primary education. The results of our study underscore the efficacy of our proposed framework, showcasing tangible improvements in addressing privacy concerns, mitigating biases, and promoting inclusivity. This paper contributes a crucial perspective to the ongoing discourse, providing actionable insights that lay the groundwork for a responsible and equitable future for $A I$ in primary education.