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AI-based recruitment software transforms the way recruiting is done, including screening of resumes and assessment of applicants. However, this has brought a lot of exciting changes along with it, and ethical concerns related to how biases are generated in these systems are emerging increasingly. Explaining AI (XAI) makes this process transparent and accountable while keeping track of how AI decides. The case study highlights the dilemma that AI-orientated hiring faces, the generation of bias in algorithms, and how XAI can be used as a means of mitigating some of the biases. We analyze the potential of XAI in making hiring practices fairer and more inclusive through examples from real-world businesses, the legal context in which this will be applied, and technical solutions.

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Mitigating Bias in AI Recruitment Through Explainable AI for Fair and Inclusive Hiring Practices

  • 章节

  • 发表日期：

    2025年

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  • P. Jayadharshini,
  • P. Karunakaran,
  • S. Santhiya,
  • A. S. Renugadevi,
  • G. Dhanush,
  • E. Pavithra

摘要

AI-based recruitment software transforms the way recruiting is done, including screening of resumes and assessment of applicants. However, this has brought a lot of exciting changes along with it, and ethical concerns related to how biases are generated in these systems are emerging increasingly. Explaining AI (XAI) makes this process transparent and accountable while keeping track of how AI decides. The case study highlights the dilemma that AI-orientated hiring faces, the generation of bias in algorithms, and how XAI can be used as a means of mitigating some of the biases. We analyze the potential of XAI in making hiring practices fairer and more inclusive through examples from real-world businesses, the legal context in which this will be applied, and technical solutions.