Mapping the intersection of ethics, AI, and higher education: a bibliometric approach

Abstract

This bibliometric study systematically maps the intersection of ethics, artificial intelligence (AI), and higher education using data sourced from the Scopus database and analyzed through bibliometric tools such as VOSviewer and CiteSpace. The analysis reveals a notable increase in publication trends since 2019, with major contributions from Springer Nature and leading institutions such as University College London and the University of Oxford. Keyword co-occurrence analysis identifies central themes such as "artificial intelligence," "machine learning," and "ethical technology," reflecting a growing research emphasis on human-centered AI applications and the need for robust ethical frameworks. Unlike previous studies that largely focused on conceptual discussions, this study quantitatively maps the global research landscape and highlights emerging thematic areas, including recent topics like "ChatGPT" and "generative AI." The findings provide practical insights for curriculum development and higher education policy, while also contributing to the broader discourse on ethical frameworks for the implementation of AI in academic settings.