The integration of Generative Artificial Intelligence (AI) in education has gained considerable attention, driven by rapid advancements in artificial intelligence and the increasing demand for innovative educational tools. This study investigates the ethical considerations of implementing Generative AI in educational settings through a bibliometric mapping review analysis. The results reveal a significant rise in research on this topic over the past five years, highlighting the growing awareness of ethical issues. Key nations, including the United States, the United Kingdom, Spain, Australia, and China, have made notable contributions, shaping the discourse. Leading educational institutions such as The University of Hong Kong, The University of Sheffield, and the University of South Africa, along with prominent researchers like Aras Bozkurt, Samuel Kai Wah Chu, and Wayne Holmes, have advanced our understanding of critical ethical issues. These include data privacy, algorithmic bias, and accountability in AI systems. The analysis of research terms identifies “artificial intelligence,” “machin,” “ethics,” “chatbots,” and “data privacy” as central themes, reflecting the interdisciplinary nature of the research. The study underscores the importance of developing comprehensive ethical frameworks to ensure the responsible and equitable use of AI technologies in education. By fostering global collaboration and dialogue, we can address these ethical challenges and promote fairness, transparency, and accountability in AI-driven educational tools.