An AI-based framework for improving efficiency and fairness in the interview process - Taman, Mohannad; Khaled, Yahia; Sobhy, Dalia (Advances in Computing and Engineering, 2025)
Artificial intelligence (AI) technologies have advanced to the point where they can help human resource specialists, such as recruiters, by automating major parts of the hiring process and filtering the list of candidates. However, little research has evaluated the use of AI in virtual interviews. This paper presents InstaJob, an AI-powered framework designed to improve efficiency and fairness in the hiring process. It uses deep learning models for face emotion detection, text emotion analysis, and filler word detection in interviews to evaluate candidates’ soft skills, ensuring unbiased assessments. The proposed face emotion detection model achieved a validation accuracy of 77%, which outperforms the other state-of-the-art approaches.Received on, 27 April 2025Accepted on, 25 May 2025Published on, 18 June 2025