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AI and responsibility : no gap, but abundance
Citation Link: https://doi.org/10.15480/882.13767
Publikationstyp
Journal Article
Date Issued
2024-09-12
Sprache
English
TORE-DOI
Journal
Volume
42
Issue
1
Start Page
357
End Page
374
Citation
Journal of Applied Philosophy 42 (1): 357-374 (2024)
Publisher DOI
Scopus ID
Publisher
Wiley
The best-performing AI systems, such as deep neural networks, tend to be the ones that are most difficult to control and understand. For this reason, scholars worry that the use of AI would lead to so-called responsibility gaps, that is, situations in which no one is morally responsible for the harm caused by AI, because no one satisfies the so-called control condition and epistemic condition of moral responsibility. In this article, I acknowledge that there is a significant challenge around responsibility and AI. Yet I don't think that this challenge is best captured in terms of a responsibility gap. Instead, I argue for the opposite view, namely that there is responsibility abundance, that is, a situation in which numerous agents are responsible for the harm caused by AI, and that the challenge comes from the difficulties of dealing with such abundance in practice. I conclude by arguing that reframing the challenge in this way offers distinct dialectic and theoretical advantages, promising to help overcome some obstacles in the current debate surrounding ‘responsibility gaps’.
Subjects
MLE@TUHH
DDC Class
004: Computer Sciences
Publication version
publishedVersion
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J Applied Philosophy - 2024 - Kiener - AI and Responsibility No Gap but Abundance.pdf
Type
Main Article
Size
225.73 KB
Format
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