人工智能招聘的风险管理研究OA

With the deep integration of artificial intelligence and big data technology into enterprise human resource management,intelligent recruitment has become an important application scenario promoting the transformation of"digital-intelligent human resources".AI recruitment shows significant advantages in improving screening efficiency and reducing labor costs,but in practice,it has gradually exposed systemic risks such as algorithm bias and discrimination,data privacy infringement,and algorithm black box.Based on typical Chinese and foreign practical cases,this paper systematically combs the management risks caused by AI recruitment and their causes,and finds that:algorithm training relying on historical data is easy to internalize structural bias;the vague boundary of personal information collection intensifies privacy concerns;the lack of interpretability in the decision-making process leads to difficulties in responsibility attribution.In response to the above problems,enterprises can adopt coping strategies such as improving algorithm regulation and review mechanisms,formulating unified data quality standards,setting up manual review and algorithm audit systems,and strengthening technical ethics training for human resource management teams,so as to promote the balance between efficiency improvement and fairness and justice in AI recruitment,and provide theoretical reference and practical guidance for enterprises to build a credible,compliant and sustainable intelligent recruitment system in digital transformation.