AI and Gender Bias in Banking Hiring Practices

Camila Magallanes Caballero Morlesin, Gunjan Rajkumar Lund, Sara Maria de Sousa Martinho Raposo, Zaruhi Snedker Mkrtchyan, Rob Gleasure*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Gender bias in hiring is a significant problem in the banking sector. This study explores how individuals’ bias towards hiring males is impacted when those individuals are exposed to existing recommendations with embedded bias towards hiring either males or females. We also investigate whether the impact of these recommendations changes when individuals believe they come from Artificial Intelligence (AI), male partners, or female partners. We perform a 2 × 3 between-subjects experiment that asks subjects to rank candidates under each condition (existing recommendations favor male candidates vs. existing recommendations favor female candidates, and recommendations come from AI vs. recommendations come from male partners vs. recommendations come from female partners). The results show that subjects tend to imitate the male or female favoring bias in the existing recommendations. Results further show that male and female subjects tended to ignore a bias towards hiring males when it came from the opposite sex. Further, subjects with positive perceptions toward AI were more likely to favor male candidates, reflecting the dynamic of perception of credibility, gender bias, and social identity. These results underline the importance of collaboration between AI developers and HR to mitigate biases and address systemic disparities in recruitment in the banking sector.
Original languageEnglish
Title of host publicationEnterprise Applications, Markets and Services in the Finance Industry : 12th International Workshop, FinanceCom 2024, Copenhagen, Denmark, October 10, 2024, Revised Selected Papers
EditorsJonas Hedman, Rob Gleasure, Madhushi Bandara
Number of pages12
Place of PublicationCham
PublisherSpringer
Publication date2025
Pages89–100
ISBN (Print)9783031899324
ISBN (Electronic)9783031899331
DOIs
Publication statusPublished - 2025
EventFinanceCom 2024 - 12th International Workshop: Enterprise Applications, Markets and Services in the Finance Industry - Copenhagen Business School, Frederiksberg, Denmark
Duration: 10 Oct 202410 Oct 2024
Conference number: 12
https://www.tilmeld.dk/financecom2024/conference

Workshop

WorkshopFinanceCom 2024 - 12th International Workshop
Number12
LocationCopenhagen Business School
Country/TerritoryDenmark
CityFrederiksberg
Period10/10/202410/10/2024
Internet address
SeriesLecture Notes in Business Information Processing
Volume541
ISSN1865-1348

Keywords

  • Gender bias
  • Banking, hiring
  • Artificial intelligence

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