An AI-based framework for improving efficiency and fairness in the interview process
<p>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 inte...
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| Format: | Article |
| Language: | English |
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Academy Publishing Center
2025-06-01
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| Series: | Advances in Computing and Engineering |
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| Online Access: | http://apc.aast.edu/ojs/index.php/ACE/article/view/1317 |
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| _version_ | 1849320447466799104 |
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| author | Mohannad Taman Yahia Khaled Dalia Sobhy |
| author_facet | Mohannad Taman Yahia Khaled Dalia Sobhy |
| author_sort | Mohannad Taman |
| collection | DOAJ |
| description | <p>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.</p><p><strong>Received on, 27 April 2025</strong></p><p><strong>Accepted on, 25 May 2025</strong></p><p><strong>Published on, 18 June 2025</strong></p> |
| format | Article |
| id | doaj-art-c6381971fcbe409eae1ba8f7f69de136 |
| institution | Kabale University |
| issn | 2735-5977 2735-5985 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Academy Publishing Center |
| record_format | Article |
| series | Advances in Computing and Engineering |
| spelling | doaj-art-c6381971fcbe409eae1ba8f7f69de1362025-08-20T03:50:06ZengAcademy Publishing CenterAdvances in Computing and Engineering2735-59772735-59852025-06-0151203410.21622/ACE.2025.05.1.1317520An AI-based framework for improving efficiency and fairness in the interview processMohannad Taman0Yahia Khaled1Dalia Sobhy2Obeikan Digital Solutions Arab Academy of Science and Technology and Maritime TransportBanque MisrArab Academy of Science and Technology and Maritime Transport<p>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.</p><p><strong>Received on, 27 April 2025</strong></p><p><strong>Accepted on, 25 May 2025</strong></p><p><strong>Published on, 18 June 2025</strong></p>http://apc.aast.edu/ojs/index.php/ACE/article/view/1317artificial intelligence, virtual interviews, facial emotion recognition, speech processing, deep learning applications. |
| spellingShingle | Mohannad Taman Yahia Khaled Dalia Sobhy An AI-based framework for improving efficiency and fairness in the interview process Advances in Computing and Engineering artificial intelligence, virtual interviews, facial emotion recognition, speech processing, deep learning applications. |
| title | An AI-based framework for improving efficiency and fairness in the interview process |
| title_full | An AI-based framework for improving efficiency and fairness in the interview process |
| title_fullStr | An AI-based framework for improving efficiency and fairness in the interview process |
| title_full_unstemmed | An AI-based framework for improving efficiency and fairness in the interview process |
| title_short | An AI-based framework for improving efficiency and fairness in the interview process |
| title_sort | ai based framework for improving efficiency and fairness in the interview process |
| topic | artificial intelligence, virtual interviews, facial emotion recognition, speech processing, deep learning applications. |
| url | http://apc.aast.edu/ojs/index.php/ACE/article/view/1317 |
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