Artificial Intelligence in Human Resources Management: Challenges and a Path Forward
识别了数据科学用于人力资源管理的四大挑战：现象复杂、数据量小、公平问责、员工抵触，并基于因果推理、随机实验和员工贡献三原则提出应对方案。
There is a substantial gap between the promise and reality of artificial intelligence in human resource (HR) management. This article identifies four challenges in using data science techniques for HR tasks: complexity of HR phenomena, constraints imposed by small data sets, accountability questions associated with fairness and other ethical and legal constraints, and possible adverse employee reactions to management decisions via data-based algorithms. It then proposes practical responses to these challenges based on three overlapping principles—causal reasoning, randomization and experiments, and employee contribution—that would be both economically efficient and socially appropriate for using data science in the management of employees.