Companies are increasingly adopting artificial intelligence (AI) technology to manage talent recruitment because of its potential to make recruitment easier, more accurate, and ef icient. Despite its benefits, AI-based recruitment system can raise fairness concerns, such as the gender discrimination scandal of Amazon’s AI-based recruiting system. Part of the problem is that no comprehensive framework has been developed to systematically address the fairness issue in AI-based recruitment system. This study intends to address this research void by embedding the fairness mechanism into the system development process using design science research method. Building on a systematic literature review on the source of fairness in AI- based recruitment system, this study has the potential to generate important theoretical and practical implications for designing and implementing a fair AI-based recruitment system.
Zhao, Yuqing; Zhang, Xi; Tang, Xinlin; Qin, Chuan; and Zhu, Hengshu, "Embedding Fairness into the AI-Based Talent Recruitment Systems：The Perspective of Environment Cycle and Knowledge Cycle" (2021). PACIS 2021 Proceedings. 15.
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