EconPapers    
Economics at your fingertips  
 

From risk mitigation to employee action along the machine learning pipeline: A paradigm shift in European regulatory perspectives on automated decision-making systems in the workplace

Anne Mollen and Lukas Hondrich

No 278, Working Paper Forschungsförderung from Hans-Böckler-Stiftung, Düsseldorf

Abstract: Automated decision-making (ADM) systems in the workplace aggravate the power imbalance between employees and employers by making potentially crucial decisions about employees. Current approaches focus on risk mitigation to safeguard employee interests. While limiting risks remains important, employee representatives should be able to include their interests in the decision-making of ADM systems. This paper introduces the concept of the Machine Learning Pipeline to demonstrate how these interests can be implemented in practice and point to necessary structural transformations.

Keywords: Artificial Intelligence; EU regulation; workplace; democracy; employee representatives (search for similar items in EconPapers)
Date: 2023
New Economics Papers: this item is included in nep-big and nep-cmp
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.econstor.eu/bitstream/10419/271012/1/1840613254.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:zbw:hbsfof:278

Access Statistics for this paper

More papers in Working Paper Forschungsförderung from Hans-Böckler-Stiftung, Düsseldorf Contact information at EDIRC.
Bibliographic data for series maintained by ZBW - Leibniz Information Centre for Economics (econstor@zbw-workspace.eu).

 
Page updated 2024-12-28
Handle: RePEc:zbw:hbsfof:278