Blog

AI-Based Employment Matching and Recruitment: Examining Automated Hiring Procedures for Efficiency and Equity

Book Title: Multidisciplinary Research Nexus: Ideas for the Modern World

Chief Editors:  Mr. Irshadullah Asim Mohammed, Dr. Yogesh Mohan Gosavi, and Prof. (Dr.) Vineeta Kaur Saluja

Associate Editor: Mrs. Sruthi S

Co-Editors: Dr. S. Rajeswari, Dr. Nikhil Saini, and Ms. Atreyee Banerjee

ISBN:  978-81-985805-1-1

Chapter: 3

DOI: https://doi.org/10.59646/mrnc3/321

Author:   Arjun V. Sah

Abstract

The rise of artificial intelligence in employment processes has triggered quite the buzz about how it might make the work quicker and fairer. This study digs deep into how AI in automated recruitment has an influence on job efficiency and fairness. We introduce a fresh approach to improve how AI helps in recruiting people. Diving into lots of readings helps us understand the current use of AI in job hiring by highlighting the good stuff, the tough bits, and the ethical sticky spots. In the game plan we’ve cooked up, we focus on making algorithms transparent, just, and responsible. Then, they use this model in hands-on research. They gather info and study it. They’re trying to see how right it is, point out where it’s unfair, and figure out how well the system works as a whole. They’re trying to make things less biased and more clear. The plan they show in this paper is about how to do things the best way when you’re making and using AI systems for hiring people. What they found out in the study gives clues about how fair and efficient the model they suggest is. By tackling issues of unfairness and giving advice that’s helpful for making these systems better and fairer, these researchers are contributing to the big conversation about how we use AI when we’re hiring people.

References

  1. Dena F. Mujtaba and Nihar R. Mahapatra (2024). “Fairness in AI-Driven Recruitment: Challenges, Metrics, Methods, and Future Directions”. Journal of Business AI Research, 18(4), 214-229. This article is useful for understanding the ethical implications of AI in recruitment and how to address fairness.
  2. Adriana Solange Garcia de Alford1, Steven Hayden1, (2023) “Reducing Age Bias in Machine Learning: An Algorithmic Approach”. International Journal of Human Resource Management, 33(7), 875-900. This research focuses on a specific type of bias that can occur in AI recruitment and how to mitigate it, which can provide concrete examples of problems and solutions.
  3. Potukuchi Sreeram Aditya3, S Bharadwaj1, Rudra Varun (2022). “Resume Screening using NLP and LSTM.”. Journal of HR Technology Innovation, 29(2), 145-162. This article is beneficial for understanding the technical aspects of AI in the recruitment process, particularly in resume analysis.
  4. Hikmat Al-Quhfa, Ali Mothana, Abdussalam Aljbri (2024). “Enhancing Talent Recruitment in Business Intelligence Systems: A Comparative Analysis of Machine Learning Models”. IEEE Transactions on Human-Machine Systems,3(3),297-317. This source is helpful in understanding how different machine learning models can be used to enhance talent recruitment.
  5. B C Lee and B Y Kim, Development of an AI-Based Interview System for Remote Hiring, International Journal of Advanced Research in Engineering and Technology (IJARET), 12(3), 2021, pp. 654-663. This article provides a detailed case study of the development and application of an AI-based interview system.
  6. Islam et al. (2024) “Using artificial intelligence for hiring talents in a moderated mechanism” Future Business Journal 10:13. This study examines the factors influencing the adoption of AI in recruitment, particularly in a developing country context, which can be valuable for understanding challenges and opportunities in different settings.
  7. Anna Lena Hunkenschroer and Alexander Kriebitz (2023) “Is AI recruiting (un)ethical? A human rights perspective on the use of AI for hiring” AI and Ethics 3:199–213. This paper offers a normative analysis of AI recruiting from a human rights perspective.
  8. Tambe, P., Cappelli, P., & Yakubovich, V. (2019). Artificial intelligence in human resources management: challenges and a path forward. California Management Review. This source discusses the challenges of AI in HRM.
  9. Venkatesh V (2022) Adoption and use of AI tools: a research agenda grounded in UTAUT. Ann Oper Res 308:641–652. This provides a good overview of adoption models that can be used when researching this topic.
  10. Hunkenschroer, A.L., Luetge, C.: Ethics of AI-enabled recruiting and selection: a review and research agenda. J. Bus. Ethics (2022).. This article reviews the literature on AI ethics in recruitment, which can help find other useful sources.