Artificial intelligence in recruitment: Assessing flipside
Artificial Intelligence is used for various business processes including hiring employees. The purpose of this article is to assess the flip-side of Artificial Intelligence applied in recruitment software. Its insufficiency of delivering the expected results in terms of the right match for the hirin...
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| Format: | Article |
| Language: | English |
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Northern Negros State College of Science and Technology (NONESCOST)
2021-08-01
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| Series: | International Research Journal of Science, Technology, Education, and Management |
| Subjects: | |
| Online Access: | https://irjstem.com/wp-content/uploads/2021/08/IRJSTEM-Volume1_No1_Paper9.pdf |
| _version_ | 1811343422818091008 |
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| author | Hema Mirji |
| author_facet | Hema Mirji |
| author_sort | Hema Mirji |
| collection | DOAJ |
| description | Artificial Intelligence is used for various business processes including hiring employees. The purpose of this article is to assess the flip-side of Artificial Intelligence applied in recruitment software. Its insufficiency of delivering the expected results in terms of the right match for the hiring, difficulty in language processing. The paper reviews the literature available to understand the principles of Socio-technical systems design requirements and on Artificial Intelligence’s usage in the recruitment process. The research is qualitative, has followed the phenomenology approach, and uses the interview technique for understanding the opinions of the users. The results reveal that, though AI in recruitment provides ease in searching the candidate’s barriers in language and recognition, low turn-in ratio, incorrect recommendations due to Data inadequacy, skepticism among HR professionals due to lack of human intelligence, need for budgets for acquiring and training are issues. It is proposed to incorporate the guidelines of Socio-Technical System Design and Human-machine teaming for designing the Artificial Intelligence tools. Further studies could be conducted to understand the limitations of the frameworks available for designing such tools. |
| first_indexed | 2024-04-13T19:29:12Z |
| format | Article |
| id | doaj.art-9c91f19085eb4b418a8471380ab3ae05 |
| institution | Directory Open Access Journal |
| issn | 2799-063X 2799-0648 |
| language | English |
| last_indexed | 2024-04-13T19:29:12Z |
| publishDate | 2021-08-01 |
| publisher | Northern Negros State College of Science and Technology (NONESCOST) |
| record_format | Article |
| series | International Research Journal of Science, Technology, Education, and Management |
| spelling | doaj.art-9c91f19085eb4b418a8471380ab3ae052022-12-22T02:33:15ZengNorthern Negros State College of Science and Technology (NONESCOST)International Research Journal of Science, Technology, Education, and Management2799-063X2799-06482021-08-0111798710.5281/zenodo.5195766Artificial intelligence in recruitment: Assessing flipsideHema Mirji0Bharati Vidyapeeth (Deemed to be University), Pune, IndiaArtificial Intelligence is used for various business processes including hiring employees. The purpose of this article is to assess the flip-side of Artificial Intelligence applied in recruitment software. Its insufficiency of delivering the expected results in terms of the right match for the hiring, difficulty in language processing. The paper reviews the literature available to understand the principles of Socio-technical systems design requirements and on Artificial Intelligence’s usage in the recruitment process. The research is qualitative, has followed the phenomenology approach, and uses the interview technique for understanding the opinions of the users. The results reveal that, though AI in recruitment provides ease in searching the candidate’s barriers in language and recognition, low turn-in ratio, incorrect recommendations due to Data inadequacy, skepticism among HR professionals due to lack of human intelligence, need for budgets for acquiring and training are issues. It is proposed to incorporate the guidelines of Socio-Technical System Design and Human-machine teaming for designing the Artificial Intelligence tools. Further studies could be conducted to understand the limitations of the frameworks available for designing such tools.https://irjstem.com/wp-content/uploads/2021/08/IRJSTEM-Volume1_No1_Paper9.pdfartificial intelligenceassessing flipsiderecruitment |
| spellingShingle | Hema Mirji Artificial intelligence in recruitment: Assessing flipside International Research Journal of Science, Technology, Education, and Management artificial intelligence assessing flipside recruitment |
| title | Artificial intelligence in recruitment: Assessing flipside |
| title_full | Artificial intelligence in recruitment: Assessing flipside |
| title_fullStr | Artificial intelligence in recruitment: Assessing flipside |
| title_full_unstemmed | Artificial intelligence in recruitment: Assessing flipside |
| title_short | Artificial intelligence in recruitment: Assessing flipside |
| title_sort | artificial intelligence in recruitment assessing flipside |
| topic | artificial intelligence assessing flipside recruitment |
| url | https://irjstem.com/wp-content/uploads/2021/08/IRJSTEM-Volume1_No1_Paper9.pdf |
| work_keys_str_mv | AT hemamirji artificialintelligenceinrecruitmentassessingflipside |