Identifying Unconscious Human Bias in Employee Retention Using Artificial Intelligence: IT Sector

Abstract

In human resource management, unconscious human bias weakens the outcomes of managerial decision-making during recruitment, retention, performance management, promotion, client relations, work schedule, and many more. One of the primary requirements in modern H.R. practices is dealing with these types of unconscious bias in the workplace and developing strategies to reduce the impact of human bias on decision-making Artificial Intelligence (AI) is becoming one of the essential requirements of 21^st-century business. It disrupts many traditionally managed or managed HR functional areas through non-intelligent IT infrastructure. The proposed research focuses on developing an AI-based strategy to deal with an unconscious human bias specific to employee retention activity. The research focuses on identifying the probable reasons for unconscious human bias and its influence on the retention of employees, followed by analyzing the effectiveness of IT organizations' present measures to minimize human bias. Finally, to propose an AI-based conceptual model to deal with unconscious human bias during employee retention, along with a few results from trained machine learning models for predicting the chance of unconscious human bias in managerial staff.