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As artificial intelligence (AI) technologies are increasingly integrated into hiring processes, concerns about AI-driven bias issues have become prominent across disciplines. This paper presents a systematic literature review of 37 Human-Computer Interaction (HCI) studies on the topic of AI-driven hiring bias, published between 2018 and 2024. Using both qualitative and quantitative approaches, we identify and summarize the trends and focus of HCI research on this topic. We also uncover how regional affiliation influences the prioritization of research globally. We conclude the article by outlining future research opportunities for the HCI community to support more equitable and governable AI-driven hiring systems.

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Tackling Global AI-Driven Hiring Bias: A Literature Review from an HCI Perspective

  • 会议论文

  • 发表日期：

    2026年

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  • Huaigu Li,
  • Sanjay Damodaran,
  • Michael L. Best

摘要

As artificial intelligence (AI) technologies are increasingly integrated into hiring processes, concerns about AI-driven bias issues have become prominent across disciplines. This paper presents a systematic literature review of 37 Human-Computer Interaction (HCI) studies on the topic of AI-driven hiring bias, published between 2018 and 2024. Using both qualitative and quantitative approaches, we identify and summarize the trends and focus of HCI research on this topic. We also uncover how regional affiliation influences the prioritization of research globally. We conclude the article by outlining future research opportunities for the HCI community to support more equitable and governable AI-driven hiring systems.