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Introducing a multi-stakeholder perspective on opacity,transparency and strategies to reduce opacity in algorithm-based human resource management
Affiliation:Fachrichtung Psychologie, Universität des Saarlandes, Saarbrücken, Germany
Abstract:Artificial Intelligence and algorithmic technologies support or even automate a large variety of human resource management (HRM) activities. This affects a range of stakeholders with different, partially conflicting perspectives on the opacity and transparency of algorithm-based HRM. In this paper, we explain why opacity is a key characteristic of algorithm-based HRM, describe reasons for opaque algorithm-based HRM, and highlight the implications of opacity from the perspective of the main stakeholders involved (users, affected people, deployers, developers, and regulators). We also review strategies to reduce opacity and promote transparency of algorithm-based HRM (technical solutions, education and training, regulation and guidelines), and emphasize that opacity and transparency in algorithm-based HRM can simultaneously have beneficial and detrimental consequences that warrant taking a multi-stakeholder view when considering these consequences. We conclude with a research agenda highlighting stakeholders' interests regarding opacity, strategies to reduce opacity, and consequences of opacity and transparency in algorithm-based HRM.
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