人员数据与分析 • 8 分钟阅读
算法如何改变 HR 的工作方式
JUN 14, 2026
Algorithmic tools are being applied to recruitment, performance evaluation, and retention prediction. Here is what HR needs to know to use them responsibly.
算法已经在哪些地方被使用
Algorithmic tools are more prevalent in HR than many practitioners realise. CV screening tools that rank applicants based on keyword matching or past successful hire profiles are widespread in ATS platforms. Performance prediction models flag employees at risk of leaving or underperforming. Scheduling algorithms optimise shift patterns for hourly workers. Compensation tools benchmark pay against market data using statistical models. Each of these applications has genuine utility, but also risks that HR must understand and manage.
The bias problem
算法化 HR 工具中最显著的风险是偏见放大。如果 CV 筛选算法使用过去成功录用者的数据进行训练，而这些录用者由于招聘流程中的历史偏见而主要来自某一特定人口群体，那么算法就会学会偏好该群体。算法并不会引入新的偏见；它只是放大并系统化了过去原本不一致、因此部分可自我纠正的既有偏见。HR 领导者必须像审计人工决策流程一样，审计算法工具是否具有歧视性影响。
负责任地使用算法
算法化 HR 工具的指导原则是人工监督。使用算法来辅助决策，而不是让它们自主决定任何会影响员工雇佣状态、薪资或发展的重大结果。要求供应商透明说明其模型如何工作以及用什么数据训练而成。按人口群体定期审计结果。确保员工有权要求对任何受算法影响的决策进行人工复核，这在某些司法辖区是法律要求。
