Artificial intelligence, distributional fairness, and pivotality
Victor Klockmann,
Alicia von Schenk and
Marie Villeval ()
Additional contact information
Victor Klockmann: JMU - Julius-Maximilians-Universität Würzburg = University of Würzburg [Würsburg, Germany], Goethe University Frankfurt = Goethe-Universität Frankfurt am Main, Max Planck Institute for Human Development - Max-Planck-Gesellschaft
Alicia von Schenk: JMU - Julius-Maximilians-Universität Würzburg = University of Würzburg [Würsburg, Germany], Goethe University Frankfurt = Goethe-Universität Frankfurt am Main, Max Planck Institute for Human Development - Max-Planck-Gesellschaft
Marie Villeval: GATE Lyon Saint-Étienne - Groupe d'Analyse et de Théorie Economique Lyon - Saint-Etienne - UL2 - Université Lumière - Lyon 2 - UJM - Université Jean Monnet - Saint-Étienne - EM - EMLyon Business School - CNRS - Centre National de la Recherche Scientifique
Post-Print from HAL
Abstract:
In the field of machine learning, the decisions of algorithms depend on extensive training data contributed by numerous, often human, sources. How does this property affect the social nature of human decisions that serve to train these algorithms? By experimentally manipulating the pivotality of individual decisions for a supervised machine learning algorithm, we show that the diffusion of responsibility weakened revealed social preferences, leading to algorithmic models favoring selfish decisions. Importantly, this phenomenon cannot be attributed to shifts in incentive structures or the presence of externalities. Rather, our results suggest that the expansive nature of Big Data fosters a sense of diminished responsibility and serves as an excuse for selfish behavior that impacts individuals and the whole society.
Keywords: Artificial intelligence; Big data; Pivotality; Distributional fairness; Experiment (search for similar items in EconPapers)
Date: 2025
New Economics Papers: this item is included in nep-ain, nep-big, nep-exp and nep-hpe
Note: View the original document on HAL open archive server: https://hal.science/hal-05165240v1
References: Add references at CitEc
Citations:
Published in European Economic Review, 2025, 178, pp.105098. ⟨10.1016/j.euroecorev.2025.105098⟩
Downloads: (external link)
https://hal.science/hal-05165240v1/document (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:hal:journl:hal-05165240
DOI: 10.1016/j.euroecorev.2025.105098
Access Statistics for this paper
More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().