AI素养决定HR如何理解招聘推荐系统的解释功能
Explained, yet misunderstood: How AI Literacy shapes HR Managers' interpretation of User Interfaces in Recruiting Recommender Systems
- 测试不同可解释性设计对HR管理者的影响
- 高素养者仅在特征重要性提示下理解更准
- 复杂解释可能降低真实理解，需因人施教
基于AI的推荐系统正日益影响招聘决策，因此人力资源管理（HRM）中的透明度与负责任采纳至关重要。本研究考察了德国410名HR管理者在使用招聘推荐仪表板时，其AI素养如何影响对可解释AI（XAI）元素的主观感知与客观理解。实验对比了基础版与三种增强版仪表板：关键特征、反事实说明和模型标准。结果表明，实际使用的仪表板并未真正解释AI结果，反而使AI机制保持模糊。尽管加入XAI元素提升了中高素养用户的主观帮助感与信任度，但未提升其客观理解能力，甚至在复杂解释下反而降低准确理解。仅有关键特征提示显著帮助了高素养用户。研究强调，XAI在招聘中的价值取决于用户AI素养，需制定个性化解释策略与针对性培训，以确保AI在人力资源管理中公平、透明且有效应用。
原文摘要 · Abstract (English)
AI-based recommender systems increasingly influence recruitment decisions. Thus, transparency and responsible adoption in Human Resource Management (HRM) are critical. This study examines how HR managers' AI literacy influences their subjective perception and objective understanding of explainable AI (XAI) elements in recruiting recommender dashboards. In an online experiment, 410 German-based HR managers compared baseline dashboards to versions enriched with three XAI styles: important features, counterfactuals, and model criteria. Our results show that the dashboards used in practice do not explain AI results and even keep AI elements opaque. However, while adding XAI features improves subjective perceptions of helpfulness and trust among users with moderate or high AI literacy, it does not increase their objective understanding. It may even reduce accurate understanding, especially with complex explanations. Only overlays of important features significantly aided the interpretations of high-literacy users. Our findings highlight that the benefits of XAI in recruitment depend on users' AI literacy, emphasizing the need for tailored explanation strategies and targeted literacy training in HRM to ensure fair, transparent, and effective adoption of AI.
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