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Ethics Guidelines for Using AI-based Algorithms in Recruiting : Learnings from a Systematic Literature Review
Hofeditz, Lennart; Mirbabaie, Milad; Luther, Audrey; u. a. (2025): Ethics Guidelines for Using AI-based Algorithms in Recruiting : Learnings from a Systematic Literature Review, in: Bamberg: Otto-Friedrich-Universität, S. 145–154.
Publisher Information:
Year of publication:
2025
Pages:
Source/Other editions:
Tung X. Bui (Hrsg.), Proceedings of the 55th Annual Hawaii International Conference on System Sciences : January 3-7, 2022, Honolulu, HI: Department of IT Management, Shidler College of Business, University of Hawaii at Manoa, 2022, S. 145–154, ISBN: 978-0-9981331-5-7
Year of first publication:
2022
Language:
English
Abstract:
To reduce the workload of employees working in Human Resource departments and to avoid bias in pre-selection of applicants, an increasing number of companies deploy Artificial Intelligence (AI)-based algorithms. Some examples such as Amazon’s discriminating recruiting algorithm showed that algorithms are not free of unethical decision making. Although there already exists a variety of ethics principles for AI-based systems, those are usually hardly being applicable to specific use cases such as using AI-based algorithms in recruiting processes. To address this issue and to provide guidance for researchers and practitioners, we conducted a systematic literature review (keyword and backwards search) on existing ethics guidelines and principles for AI and extracted aspects that seemed applicable to guide recruiting processed. Based on 28 relevant papers we derived actionable guidelines for using AI-based algorithms in recruiting processes. We categorized our guidelines into the aspects of fairness, avoidance of discrimination and avoidance of bias.
Keywords: ; ; ; ;
AI and Future of Work
artificial intelligence
ethics
future of work
hr
Peer Reviewed:
Yes:
International Distribution:
Yes:
Open Access Journal:
Yes:
Type:
Conferenceobject
Activation date:
November 10, 2025
Permalink
https://fis.uni-bamberg.de/handle/uniba/110503