A scoping review on gender bias in AI-based decision making systems

Artificial intelligence (AI)-based decision-making systems may display gender prejudice, according to industry studies and literature, which could have detrimental effects on both people and society as a whole. The control of gender bias in these systems and its negative repercussions are not well studied, despite the fact that the information systems area recognizes the important contributions of AI outcomes and their ramifications. As such, there is a rising concern about gender bias in AI decision-making, which is garnering more attention. In particular, there is an urgent need to comprehend the variables that contribute to gender bias in AI-based systems and to find practical solutions. The review's conclusions show that there is still a dearth of study on gender bias in AI decision-making, suggesting that there are a lot of untapped research opportunities in this area.

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Publication Details

Journal
Integration of Mankind and Society
Published
2025-08-20
DOI
https://doi.org/10.56770/ims2025222
Primary Topic
Salmonella and Campylobacter epidemiology
Type
article
Field-Weighted Citation Impact
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article

A scoping review on gender bias in AI-based decision making systems

Integration of Mankind and Society
Salmonella and Campylobacter epidemiology
article

A scoping review on gender bias in AI-based decision making systems

article en

Abstract

Artificial intelligence (AI)-based decision-making systems may display gender prejudice, according to industry studies and literature, which could have detrimental effects on both people and society as a whole. The control of gender bias in these systems and its negative repercussions are not well studied, despite the fact that the information systems area recognizes the important contributions of AI outcomes and their ramifications. As such, there is a rising concern about gender bias in AI decision-making, which is garnering more attention. In particular, there is an urgent need to comprehend the variables that contribute to gender bias in AI-based systems and to find practical solutions. The review's conclusions show that there is still a dearth of study on gender bias in AI decision-making, suggesting that there are a lot of untapped research opportunities in this area.

Integration of Mankind and SocietyVol. 2(2)
University of the Punjab (PK)
Gender equality
Openalex Percentile: Top 44%
Salmonella and Campylobacter epidemiology
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