The Impact of Explainability on Trust in AI in Entry Sheet Selection

Abstract

This paper focuses on the trust in AI technology in the entry sheet (ES) selection process for new graduates, and examines the impact of explainability. In recent years, an increasing number of companies have been using AI in ES selection to improve the efficiency of the selection process. While the demand for AI selection from companies is increasing, there are many negative opinions about AI selection from students, and some students consider the black box nature of the selection process to be a problem. Many of these are due to distrust of AI technology. Explainable AI (XAI) is attracting attention as a way to eliminate such distrust of AI technology. In this paper, XAI is defined as AI that can provide details or reasons for people to understand the function of the system. In the fields of medicine and automated driving, XAI has been shown to have a positive influence on trust from users. We conducted a survey experiment assuming that the same effect can be obtained by explainability in ES selection for new graduate recruitment. This paper provides some implications for efforts to introduce AI into the ES selection process for new graduate recruitment.