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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Panli Sun
Qingdao University of Science and Technology
Rajermani Thinakaran
INTI International University
Waldemar Wójcik
Lublin University of Technology
International Journal of Innovative Research and Scientific Studies
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Sun et al. (Fri,) studied this question.
synapsesocial.com/papers/68af5bc1ad7bf08b1eadfdce — DOI: https://doi.org/10.53894/ijirss.v8i5.9202
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