Cognitive biases in developing biased Artificial Intelligence recruitment system

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dc.contributor.authorSoleimani, Melika
dc.contributor.authorIntezari, Ali
dc.contributor.authorTaskin, Nazim
dc.contributor.authorPauleen, David
dc.date.accessioned2020-12-24T20:03:55Z
dc.date.available2020-12-24T20:03:55Z
dc.date.issued2021-01-05
dc.description.abstractArtificial Intelligence (AI) in a business context is designed to provide organizations with valuable insight into decision-making and planning. Although AI can help managers make decisions, it may pose unprecedented issues, such as datasets and implicit biases built into algorithms. To assist managers with making unbiased effective decisions, AI needs to be unbiased too. Therefore, it is important to identify biases that may arise in the design and use of AI. One of the areas where AI is increasingly used is the Human Resources recruitment process. This article reports on the preliminary findings of an empirical study answering the question: how do cognitive biases arise in AI? We propose a model to determine people’s role in developing AI recruitment systems. Identifying the sources of cognitive biases can provide insight into how to develop unbiased AI. The academic and practical implications of the study are discussed.
dc.format.extent9 pages
dc.identifier.doi10.24251/HICSS.2021.620
dc.identifier.isbn978-0-9981331-4-0
dc.identifier.urihttp://hdl.handle.net/10125/71238
dc.language.isoEnglish
dc.relation.ispartofProceedings of the 54th 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.subjectJudgement, Big Data-Analytics and Decision-making
dc.subjectartificial intelligence
dc.subjectcognitive biases
dc.subjectdecision-making
dc.titleCognitive biases in developing biased Artificial Intelligence recruitment system
prism.startingpage5091

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