Algorithmic management systems are increasingly common, taking over key functions like evaluation, direction, and discipline. This automation leads to concerns about fairness with the shift to algorithmic oversight. This paper aims to utilize the theories of algorithmic control and fairness monitoring to investigate the relationship between perceived algorithmic controls and focused fairness monitoring. By examining the different forms of algorithmic control that influence specific types of fairness monitoring, the study can contribute both theoretically and practically to algorithmic management. The findings can offer insights for achieving balance between control and fairness and enhancing employee engagement and acceptance.