Creating an Explainable AI Tool for First Impression Enhancement in Job Interviews

Abstract

In the world of job interviews, first impression plays a big role in candidate selection. However, current Human Resources (HR) technology tends to lack tools that can both provide candidates with meaningful feedback on their first impression and offer transparent, actionable advice for performance improvement. This thesis introduces an explainable artificial intelligence (AI) tool designed to provide advice to candidates for improving their first impressions during job interviews. The proposed tool uses the Big Five personality traits for evaluating and improving job candidates’ interview performances. The thesis focuses on demonstrating the potential of such a tool to provide automated, yet specialized feedback to candidates. The validation of this tool’s effectiveness is showcased through a series of experiments. It was observed that candidates exhibited enhanced performance after engaging with the tool. The findings suggest that this AI tool holds practical value, indicating a promising direction for future integration into HR software platforms. Such integration would not only augment the functionality of these platforms but also advance the goal of improving job interview outcomes through informed data-driven feedback. Further development and refinement are envisioned to fully realize the potential of this tool in professional settings, paving the way for an innovation in HR technology where first impressions are not just evaluated, but systematically improved.