Ethics Guidelines for Using AI-based Algorithms in Recruiting: Learnings from a Systematic Literature Review

dc.contributor.authorHofeditz, Lennart
dc.contributor.authorMirbabaie, Milad
dc.contributor.authorLuther, Audrey
dc.contributor.authorMauth, Riccarda
dc.contributor.authorRentemeister, Ina
dc.date.accessioned2021-12-24T17:16:52Z
dc.date.available2021-12-24T17:16:52Z
dc.date.issued2022-01-04
dc.description.abstractTo 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.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2022.018
dc.identifier.isbn978-0-9981331-5-7
dc.identifier.urihttp://hdl.handle.net/10125/79348
dc.language.isoeng
dc.relation.ispartofProceedings of the 55th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectAI and Future of Work
dc.subjectartificial intelligence
dc.subjectethics
dc.subjectfuture of work
dc.subjecthr
dc.titleEthics Guidelines for Using AI-based Algorithms in Recruiting: Learnings from a Systematic Literature Review
dc.type.dcmitext

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