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  4. The Challenges of Algorithm-based HR Decision-making for Personal Integrity
 
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The Challenges of Algorithm-based HR Decision-making for Personal Integrity

Journal
Journal of business ethics : JOBE
ISSN
0167-4544
Type
journal article
Date Issued
2019-06
Author(s)
Leicht-Deobald, Ulrich
Busch, Thorsten
Schank, Christoph
Weibel, Antoinette
Schafheitle, Simon Daniel
Wildhaber, Isabelle
Kasper, Gabriel
DOI
10.1007/s10551-019-04204-w
Abstract
Organizations increasingly rely on algorithm-based HR decision-making to monitor their employees. This trend is reinforced by the technology industry claiming that its decision-making tools are efficient and objective, downplaying their potential biases. In our manuscript, we identify an important challenge arising from the efficiency-driven logic of algorithm-based HR decision-making, namely that it shifts the delicate balance between employees’ personal integrity and compliance toward favoring compliance. The reason is that algorithm-based HR decision-making may marginalize human sense-making, promote blind trust in rules, and replace moral imagination. We suggest that critical data literacy, ethical awareness, the use of participatory design methods, and private regulatory regimes within civil society can help overcome these challenges. Our paper contributes to literature on workplace monitoring, critical data studies, personal integrity and literature at the intersection between HR management and corporate responsibility.
Project(s)
Big Data or Big Brother ? - Big Data HR Control Practices and Employee Trust
Language
English
Keywords
Algorithm-based decision-making
personal integrity
moral imagination
critical algorithm studies
workplace monitoring
HSG Classification
contribution to scientific community
HSG Profile Area
SoM - Responsible Corporate Competitiveness (RoCC)
Refereed
Yes
Publisher
Springer
Volume
160
Number
2
Start page
377
End page
392
URL
https://www.alexandria.unisg.ch/handle/20.500.14171/98608
Subject(s)
  • social sciences

  • business studies

Division(s)
  • I.FPM - Institute for...

  • IWE - Institute for B...

  • FAA - Institute for W...

Contact Email Address
ulrich.leicht-deobald@unisg.ch
Eprints ID
257096
File(s)
Leicht-Deobald2019_Article_TheChallengesOfAlgorithm-Based.pdf (664.86 KB)
Scopus© citations
101
Acquisition Date
Jun 3, 2023
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