The Impact Of AI-Driven Recruitment Tools on Diversity, Equity, And Inclusion (DEI) Outcomes in Hiring Practices
Article Sidebar
Main Article Content
Abstract: The integration of artificial intelligence (AI) in recruitment has transformed traditional hiring practices, offering efficiency, scalability, and data-driven decision-making. However, the implications of AI on Diversity, Equity, and Inclusion (DEI) remain complex and multifaceted. This paper investigates how AI-driven recruitment tools affect DEI outcomes, examining both the potential benefits and inherent risks. Through an analysis of current literature and emerging trends, this research identifies the key challenges and opportunities for aligning AI recruitment technologies with DEI goals. Recommendations for ethical implementation and the role of human oversight are also explored.
Downloads
References
Accenture. (2020). Inclusion and diversity in the age of AI. https://www.accenture.com
Amazing workplaces (2024). Top 7 Companies in India Leading the Way in DEI: Initiatives and Impact. https://amazingworkplaces.co/top-7-companies-in-india-leading-the-way-in-dei-initiatives-and-impact/
Binns, R. (2020). On the apparent conflict between individual and group fairness. Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, 514–524. https://doi.org/10.1145/3351095.3372864
Binns, R., Veale, M., Van Kleek, M., & Shadbolt, N. (2018). 'It's reducing a human being to a percentage': Perceptions of justice in algorithmic decisions. Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, 1-14.
Bogen, M., & Rieke, A. (2018). Help wanted: An examination of hiring algorithms, equity, and bias. Upturn. https://www.upturn.org
Dastin, J. (2018). Amazon scrapped 'sexist AI' recruiting tool. Reuters. https://www.reuters.com
Dastin, J. (2018). Amazon scraps secret AI recruiting tool that showed bias against women. Reuters. https://www.reuters.com/article/world/insight-amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK0AG/
European Commission. (2021). Proposal for a Regulation laying down harmonised rules on artificial intelligence (Artificial Intelligence Act). https://eur-lex.europa.eu
Liem, C. C. S., Langer, M., Demetriou, A., Kumar, K., & Shankar, S. (2018). Psychology meets machine learning: Interdisciplinary perspectives on algorithmic job candidate screening. Nature Human Behaviour, 2(6), 319–327. https://doi.org/10.1038/s41562-018-0352-2
Mehrabi, N., Morstatter, F., Saxena, N., Lerman, K., & Galstyan, A. (2021). A survey on bias and fairness in machine learning. ACM Computing Surveys, 54(6), 1–35. https://doi.org/10.1145/3457607
O'Neil, C. (2016). Weapons of math destruction: How big data increases inequality and threatens democracy. Crown Publishing Group.
Raghavan, M., Barocas, S., Kleinberg, J., & Levy, K. (2020). Mitigating bias in algorithmic hiring: Evaluating claims and practices. Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, 469–481.
Raji, I. D., & Buolamwini, J. (2019). Actionable auditing: Investigating the impact of publicly naming biased performance results of commercial AI products. Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 429-435.
Roberson, Q. M. (2019). Diversity in the workplace: A review, synthesis, and future research agenda. Annual Review of Organizational Psychology and Organizational Behavior, 6, 69-88.
Upadhyay, A. K., & Khandelwal, K. (2018). Applying artificial intelligence: Implications for recruitment. Strategic HR Review, 17(5), , 255-258.
Whittaker, M., Crawford, K., Dobbe, R., Fried, G., Kaziunas, E., Mathur, V., ... & Schwartz, O. (2018). AI Now Report 2018. AI Now Institute. https://ainowinstitute.org/AI_Now_2018_Report.pdf
Zliobaite, I. (2017). Measuring discrimination in algorithmic decision making. Data Mining and Knowledge Discovery, 31, 1060–1089. https://doi.org/10.1007/s10618-017-0506-1

This work is licensed under a Creative Commons Attribution 4.0 International License.
All articles published in our journal are licensed under CC-BY 4.0, which permits authors to retain copyright of their work. This license allows for unrestricted use, sharing, and reproduction of the articles, provided that proper credit is given to the original authors and the source.