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- W3194314025 abstract "Despite being the fastest-growing field because of its ability to enhance competitive advantage, there are concerns about the inherent fairness in Artificial Intelligence (AI) algorithms. In this study, a systematic review was performed on AI and the fairness of AI algorithms. 47 articles were reviewed for their focus, method of research, sectors, practices, and location. The key findings, summarized in a table, suggest that there is a lack of formalised AI terminology and definitions which subsequently results in contrasting views of AI algorithmic fairness. Most of the research is conceptual and focused on the technical aspects of narrow AI, compared to general AI or super AI. The public services sector is the target of most research, particularly criminal justice and immigration, followed by the health sector. AI algorithmic fairness is currently more focused on the technical and social/human aspects compared to the economic aspects. There was very little research from Asia, Middle East, Oceania, and Africa. The study makes suggestions for further research." @default.
- W3194314025 created "2021-08-30" @default.
- W3194314025 creator A5030973419 @default.
- W3194314025 creator A5083962004 @default.
- W3194314025 date "2021-01-01" @default.
- W3194314025 modified "2023-09-27" @default.
- W3194314025 title "A Systematic Review of Fairness in Artificial Intelligence Algorithms" @default.
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- W3194314025 doi "https://doi.org/10.1007/978-3-030-85447-8_24" @default.
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