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