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Title:

Rethinking People Analytics With Inverse Transparency by Design

Document type:
Zeitschriftenaufsatz
Author(s):
Zieglmeier, Valentin; Pretschner, Alexander
Abstract:
Employees work in increasingly digital environments that enable advanced analytics. Yet, they lack oversight over the systems that process their data. That means that potential analysis errors or hidden biases are hard to uncover. Recent data protection legislation tries to tackle these issues, but it is inadequate. It does not prevent data misusage while at the same time stifling sensible use cases for data. We think the conflict between data protection and increasingly data-driven systems s...     »
Journal title:
Proceedings of the ACM on Human-Computer Interaction
Year:
2023
Journal volume:
7
Journal issue:
CSCW2
Pages contribution:
292:1–29
Fulltext / DOI:
doi:10.1145/3610083
WWW:
arXiv version
Publisher:
ACM
Submitted:
13.07.2022
Accepted:
16.03.2023
Date of publication:
04.10.2023
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