Ethical concerns while using artificial intelligence in recruitment of employees
Open accessAbstract
Artificial Intelligence has evolved as an alternative to human intelligence. It affects the lives of billions of people. It mimics humans by solving problems and understanding the task. These Artificial Intelligence technologies must have some moral values and ethics incorporated within itself. The usage of AI is growing worldwide, posing more ethical issues to consider. In recent years, many companies have used various Artificial Intelligence tools such as chatbots and face recognition software for fulfilling their hiring needs. This research work will focus on such devices that help manage one of the important functions of human resources: recruitment. It will identify various challenges and ethical issues that a firm faces while assimilating Artificial Intelligence tools in the process of Recruitment. The hiring companies need to make the job seekers realize that AI-powered tools would be free from discrimination and safeguard privacy. The purpose of the study is to identify the ethical issues while incorporating Artificial Intelligence into hiring needs. The study will be based on reviews and features of applications. The study mentions various applications whose features might be unethical for job seekers. Findings reveal that the significant unethical issues faced by the hiring companies are Data privacy and unconscious biasness. The biasness is due to the algorithm that works according to the inputs fed to build it, and the programmer might have subconscious biasness in his mind. AI has restored concerns regarding privacy and data protection. According to a report by UNESCO, Women make up only 22% of all AI professionals. Gender prejudices and stereotyping are perpetuated in AI technologies due to their underrepresentation in the sector. Virtual personal assistants like Siri, Alexa, and Cortana are “female” by default, which is no accident. The submissiveness they display is an illustration of how Artificial Intelligence (AI) might continue to support and extend gender bias in our society.
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AI helps in matching resumes with job description based on skills and speeds up hiring process.
“AI helps in matching resumes with the job description based on the skills and speeds up the hiring process [8].”
From Mitigating Bias in Retail AI Hiring Tools: A Human-Centered H-A-I-R-E Governance Framework for Low-Wage Hires (2026) · cites this paper as [8]
The Literature Review says AI can screen CVs and save recruiters time, supporting the screening and speed aspects of the claim. It does not say that AI matches resumes to job descriptions based on skills; the passages found describe screening and selecting candidates more generally. (LLM, conf=0.87)
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Research works printed but not linked: 17
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Chopra, Y., & Hashemi, S. (2026) · 2026 ASEE- NE Section Conference Proceedings · doi:10.18260/1-2--58593
- Authors
- Gupta, A., & Mishra, M.
- Affiliations
- Lovely Professional University (IN)
- Venue
- Business Ethics and Leadership
- Published
- 2022
- Volume
- 6
- Issue
- 2
- Pages
- 6-11
- ISSN
- 2520-6311 (ISSN-L)
- 2520-6761
- OpenAlex
- W4285113288
- Cited by
- 30
- References
- 0
- Citations by year
- 2026: 3 · 2025: 11 · 2024: 11 · 2023: 4 · 2022: 1
- FWCI
- 7.82
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by
- Locations
- Business Ethics and Leadership (publishedVersion, cc-by)
- Electronic Sumy State University Institutional Repository (Sumy State University) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › AI and HR Technologies
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Keywords
- artificial intelligence in recruitment, AI ethics, algorithmic bias, implicit bias, data privacy, hiring discrimination, gender bias, stereotyping, chatbots, human resource management
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