Structural bias and geographical imbalances in AI ethics: A review

This study conducts a systematic literature review (SLR) and bibliometric analysis on global research in artificial intelligence (AI) ethics. The study systematically synthesizes the latest developments and focuses on the thematic area in the field by drawing on the PICOC protocol and the PRISMA framework. Above all, it underscores that algorithmic bias arises from embedded social structures, institutional power relations, and data limitations. Additionally, it demonstrates that academic production is geographically imbalanced, with the North overwhelmingly producing the academic output, and the South contributing at a very low level. To focus on key areas for improvement, this study utilizes literature screening and data visualization techniques to identify research gaps and recommends a paradigm shift from equity adjustment at the algorithmic level to a broader sociotechnical system reconstruction.

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Publication Details

Journal
International Journal of Innovative Research and Scientific Studies
Published
2025-08-08
DOI
https://doi.org/10.53894/ijirss.v8i5.9202
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
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article

Structural bias and geographical imbalances in AI ethics: A review

Rajermani Thinakaran, J. Somasekar, Panli Sun, Jayalakshmi Murugan
International Journal of Innovative Research and Scientific Studies
Ethics and Social Impacts of AI
article

Structural bias and geographical imbalances in AI ethics: A review

Rajermani Thinakaran, J. Somasekar, Panli Sun, Jayalakshmi Murugan
article en

Abstract

This study conducts a systematic literature review (SLR) and bibliometric analysis on global research in artificial intelligence (AI) ethics. The study systematically synthesizes the latest developments and focuses on the thematic area in the field by drawing on the PICOC protocol and the PRISMA framework. Above all, it underscores that algorithmic bias arises from embedded social structures, institutional power relations, and data limitations. Additionally, it demonstrates that academic production is geographically imbalanced, with the North overwhelmingly producing the academic output, and the South contributing at a very low level. To focus on key areas for improvement, this study utilizes literature screening and data visualization techniques to identify research gaps and recommends a paradigm shift from equity adjustment at the algorithmic level to a broader sociotechnical system reconstruction.

International Journal of Innovative Research and Scientific StudiesVol. 8(5)
Jain University (IN), INTI International University (MY), Kalasalingam Academy of Research and Education (IN)
Openalex Percentile: Top 79%
Ethics and Social Impacts of AI
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