Artificial Intelligence for Fair Hiring: A Critical Review of Diversity and Inclusion Outcomes

Year : 2026 | Volume : 13 | Issue : 02 | Page : 9 15
By

Sadique Nayeem,

  1. Assistant Professor, Department of Computer Science and Engineering, Sitamarhi Institute of Technology, Bihar, India

Abstract

Artificial Intelligence has become one of the most innovative technologies to sweep across industries over recent years and recruitment is no exception. In light of recruitment being powered by Artificial Intelligence technologies, including machine learning algorithms and Natural Language Processing, there is great potential for impacting the future of diversity and inclusion within our workplaces. From automated screening of candidates to sourcing new talent, AI presents many opportunities and challenges when it comes to increasing diversity among your talent pool. Opportunities include limiting human error and bias when assessing candidates by standardizing interviews and hiding candidate screening. Challenges including unconscious bias built into your algorithm or lack of transparency (leading to unconscious bias) can harm your diversity efforts. With technology rapidly changing every day and AI continuing to heat up in the recruitment world, it’s important to understand where these opportunities and challenges lie to help move diversity forward in your organization. This paper will highlight examples of both AI-powered recruitment harming (Amazon’s AI rejected female candidates) and increasing (Unilever’s AI reached 16% more diverse pool of candidates) diversity among candidates to show where we stand with AI today. We will then discuss some opportunities for future research to continue moving AI forward with diversity in mind, such as creating auditing measures, inclusion conscious algorithms, and even regulations.

Keywords: Artificial intelligence (AI), machine learning, recruitment, AI-driven systems, re-skilling

[This article belongs to Journal of Artificial Intelligence Research & Advances ]

How to cite this article: Sadique Nayeem. Artificial Intelligence for Fair Hiring: A Critical Review of Diversity and Inclusion Outcomes. Journal of Artificial Intelligence Research & Advances. 2026; 13(02):9-15.
How to cite this URL: Sadique Nayeem. Artificial Intelligence for Fair Hiring: A Critical Review of Diversity and Inclusion Outcomes. Journal of Artificial Intelligence Research & Advances. 2026; 13(02):9-15. Available from: https://journals.stmjournals.com/joaira/article=2026/view=260203

References

  1. Shneiderman B. Human-centered artificial intelligence: reliable, safe & trustworthy. International Journal of Human–Computer Interaction. 2020;36(6):495-504. doi:10.1080/10447318.2020.1741118.
  2. Haesevoets T, De Cremer D, Dierckx K, Van Hiel A. Human-machine collaboration in managerial decision making. Computers in Human Behavior. 2021;119:106730. doi:10.1016/j.chb.2021.106730.
  3. Lacroux A, Martin-Lacroux C. Should I trust the artificial intelligence to recruit? Recruiters’ perceptions and behavior when faced with algorithm-based recommendation systems during resume screening. Frontiers in Psychology. 2022;13:895997. doi:10.3389/fpsyg.2022.895997.
  4. Awad E, Balafoutas L, Chen L, Ip E, Vecci J. Artificial intelligence and debiasing in hiring: impact on applicant quality and gender diversity. 2023. Available from: doi:10.2139/ssrn.4626059.
  5. Will P, Krpan D, Lordan G. People versus machines: introducing the HIRE framework. Artificial Intelligence Review. 2023;56:1071-1100. doi:10.1007/s10462-022-10193-6.
  6. Wilkens U, Lupp D, Langholf V. Configurations of human-centered AI at work: seven actor-structure engagements in organizations. Frontiers in Artificial Intelligence. 2023;6:1272159. doi:10.3389/frai.2023.1272159.
  7. Bursell M, Roumbanis L. After the algorithms: a study of meta-algorithmic judgments and diversity in the hiring process at a large multisite company. Big Data & Society. 2024;11(1). doi:10.1177/20539517231221758.
  8. Bano M, Zowghi D, Mourao F, Kaur S, Zhang T. Diversity and inclusion in AI for recruitment: lessons from industry workshop. arXiv. 2024.
  9. Pant N, Joshi M. The impact of artificial intelligence on workforce diversity and inclusion: An HR perspective. Educational Administration: Theory and Practice. 2024;30(1):4503-12.
  10. Zhang P. Application of artificial intelligence (AI) in recruitment and selection: the case of Company A and Company B. Journal of Business and Management Studies. 2024;6(3):224-225. doi:10.32996/jbms.2024.6.3.18.
  11. Wilkens U, Lutzeyer I, Zheng C, Beser A, Prilla M. Augmenting diversity in hiring decisions with artificial intelligence tools. The International Journal of Human Resource Management. 2025;36(14):2585-2622. doi:10.1080/09585192.2025.2492867.
Regular Issue Subscription Review Article
Volume 13
Issue 02
Received 26/12/2025
Accepted 13/05/2026
Published 15/05/2026
Publication Time 140 Days

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