Background: _ With its promise of efficiency, personalization, and creative teaching techniques, artificial intelligence (AI) is becoming a more prevalent component of education. However, this integration raises significant ethical concerns about equity, transparency, and data privacy. Recent studies suggest that these problems need to be examined methodically and impartially. Goal: The proposed work identifies underreported and understudied areas while mapping the trends in global AI ethics in education policy and technology. It examines how researchers address ethical dilemmas and finds any gaps that could be applied to future practice and policy. Methodology: _ Using a bibliometric approach, we analyzed 342 peer-reviewed articles from 2020 to 2025 that were stored in Scopus. Using VOSviewer, the current study looked at author collaboration networks, citation patterns, and keyword co-occurrence in literature pertaining to ethics, governance, and standards in AI in education. Findings: _ Among the main ethical issues are data privacy, academic integrity, and equity in the application of AI. Additionally, there are research gaps in understudied fields such as child-centered AI ethics, blockchain technologies, and algorithmic bias. China, the United Kingdom, and the United States control academic output and collaboration chains. Despite widespread interest, research is unevenly distributed across fields and geographical areas. Conclusion: _ The study shows that there is still a dearth of interdisciplinary and policy-focused research on AI ethics in education. Strong ethical frameworks should be combined with technological innovation to ensure the equitable and long-term advancement of educational practices.
Rismani et al. (Tue,) studied this question.