Artificial Intelligence, Algorithmic Ethics, and Digital Inequality: A Bibliometric Mapping in the Digital Media Era

The accelerated expansion of advanced technologies—particularly artificial intelligence, intelligent systems, and interactive digital environments—is influencing contemporary media ecosystems and contributing to changes in educational practices. This study provides a systematic and descriptive bibliometric mapping of recent scientific production on artificial intelligence in education, algorithmic ethics, and digital inequality. A total of 229 Scopus-indexed documents published between 2021 and 2026 were analyzed using Biblioshiny and VOSviewer to examine publication patterns, influential authors and sources, and the conceptual structure of the field. Results indicate a marked increase in research output since 2024, with an annual growth rate of 47.58%, an average of 8.68 citations per document, and an international co-authorship rate of 24.45%. These indicators reflect an expanding and increasingly collaborative research landscape, accompanied by a diversification of thematic priorities within the field. The analysis identifies five thematic clusters: (1) the technical foundations of AI and digital transformation; (2) intelligent and immersive learning environments; (3) personalized and adaptive learning systems; (4) AI literacy and pedagogical integration; and (5) ethical considerations, including algorithmic bias and educational robotics. The findings highlight the need for explicit justification of database selection, strengthened critical AI literacy, and context-sensitive strategies that address disparities in access, skills, and institutional capacity. Overall, this study offers a coherent overview of a research area that is currently expanding and undergoing conceptual reorganization, providing evidence-informed insights for future research, policy development, and the design of equitable AI-driven educational technologies.

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Publication Details

Journal
Applied Sciences
Published
2026-03-22
DOI
https://doi.org/10.3390/app16063056
Primary Topic
Digital Education and Society
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial Intelligence, Algorithmic Ethics, and Digital Inequality: A Bibliometric Mapping in the Digital Media Era

ELOY LÓPEZ-MENESES, José Javier Galán Hernández, Jesús Cáceres-Tello, Soledad Zabala et al.
Applied Sciences
Digital Education and Society
article

Artificial Intelligence, Algorithmic Ethics, and Digital Inequality: A Bibliometric Mapping in the Digital Media Era

ELOY LÓPEZ-MENESES, José Javier Galán Hernández, Jesús Cáceres-Tello, Soledad Zabala, María Belén Morales Cevallos
article en

Abstract

The accelerated expansion of advanced technologies—particularly artificial intelligence, intelligent systems, and interactive digital environments—is influencing contemporary media ecosystems and contributing to changes in educational practices. This study provides a systematic and descriptive bibliometric mapping of recent scientific production on artificial intelligence in education, algorithmic ethics, and digital inequality. A total of 229 Scopus-indexed documents published between 2021 and 2026 were analyzed using Biblioshiny and VOSviewer to examine publication patterns, influential authors and sources, and the conceptual structure of the field. Results indicate a marked increase in research output since 2024, with an annual growth rate of 47.58%, an average of 8.68 citations per document, and an international co-authorship rate of 24.45%. These indicators reflect an expanding and increasingly collaborative research landscape, accompanied by a diversification of thematic priorities within the field. The analysis identifies five thematic clusters: (1) the technical foundations of AI and digital transformation; (2) intelligent and immersive learning environments; (3) personalized and adaptive learning systems; (4) AI literacy and pedagogical integration; and (5) ethical considerations, including algorithmic bias and educational robotics. The findings highlight the need for explicit justification of database selection, strengthened critical AI literacy, and context-sensitive strategies that address disparities in access, skills, and institutional capacity. Overall, this study offers a coherent overview of a research area that is currently expanding and undergoing conceptual reorganization, providing evidence-informed insights for future research, policy development, and the design of equitable AI-driven educational technologies.

Applied SciencesVol. 16(6)
Universidad Complutense de Madrid (ES), Universidad de Alcalá (ES), Universidad Ecotec (EC), Universidad Pablo de Olavide (ES)
Quality Education
Openalex Percentile: Top 11%
Digital Education and Society
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