AI discrimination trap? - Recommendations for combating discrimination against women through AI

The current overrepresentation of men in the development of AI technologies and the associated one-sided gender perspective is one of the reasons for discrimination against women in AI applications. In this context, AI exacerbates such overrepresentation, thus presenting a new discriminatory risk against women. Today´s omnipresence of AI makes the need for fair algorithms even more crucial. Thus, this study analyzes five application areas of AI (i.e. virtual private assistance, public and private transport and safety, precision medicine, employment area, and credit rating) and discusses potential biases against women identified and proposes anti-discrimination suggestions to overcome this kind of invisibility of women in many AI applications.

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Publication Details

Journal
London Journal of Social Sciences
Published
2025-05-03
DOI
https://doi.org/10.31039/ljss.2025.9.319
Citations
1
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
2.37
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article

AI discrimination trap? - Recommendations for combating discrimination against women through AI

Christina Schabasser
1 citations
London Journal of Social Sciences
Ethics and Social Impacts of AI
2.37
article

AI discrimination trap? - Recommendations for combating discrimination against women through AI

Christina Schabasser
article en
1 citations

Abstract

The current overrepresentation of men in the development of AI technologies and the associated one-sided gender perspective is one of the reasons for discrimination against women in AI applications. In this context, AI exacerbates such overrepresentation, thus presenting a new discriminatory risk against women. Today´s omnipresence of AI makes the need for fair algorithms even more crucial. Thus, this study analyzes five application areas of AI (i.e. virtual private assistance, public and private transport and safety, precision medicine, employment area, and credit rating) and discusses potential biases against women identified and proposes anti-discrimination suggestions to overcome this kind of invisibility of women in many AI applications.

London Journal of Social Sciences(9)
University of Applied Sciences Burgenland (AT)
Openalex Percentile: Top 12%
Ethics and Social Impacts of AI
2.37
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