Evaluating the Use of Artificial Intelligence in Recruitment and Selection: A Four-Dimensional Framework

Abstract

Artificial intelligence is increasingly used across recruitment and selection. Existing research has mainly examined its applications at different stages of recruitment and the trade-off between efficiency and fairness. However, a framework for assessing the appropriate boundaries of AI use across the recruitment process remains undeveloped. This paper develops a four-dimensional framework based on standardization, future-oriented judgment, opportunity visibility, and explainability. It applies the framework to the early, middle, and late stages of recruitment and selection. The analysis shows that AI should play different roles across stages. In the early stage, it can support job definition and attraction strategies. In the middle stage, AI may support sourcing and initial screening, but it also raises concerns about opportunity visibility and screening fairness, which require close attention. In the later stage, AI should not be used as a black-box tool to infer personality, potential, or future performance, nor should it make independent hiring decisions. The key issue in AI recruitment is therefore not efficiency alone, but its implications for candidate opportunity, procedural fairness, and accountability.