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From Responsibility to Reason-Giving Explainable Artificial Intelligence

Title data

Baum, Kevin ; Mantel, Susanne ; Schmidt, Eva ; Speith, Timo:
From Responsibility to Reason-Giving Explainable Artificial Intelligence.
In: Philosophy & Technology. Vol. 35 (March 2022) Issue 1 . - 12.
ISSN 2210-5441
DOI: https://doi.org/10.1007/s13347-022-00510-w

Project information

Project financing: Deutsche Forschungsgemeinschaft
VolkswagenStiftung

Abstract in another language

We argue that explainable artificial intelligence (XAI), specifically reason-giving XAI, often constitutes the most suitable way of ensuring that someone can properly be held responsible for decisions that are based on the outputs of artificial intelligent (AI) systems. We first show that, to close moral responsibility gaps (Matthias 2004), often a human in the loop is needed who is directly responsible for particular AI-supported decisions. Second, we appeal to the epistemic condition on moral responsibility to argue that, in order to be responsible for her decision, the human in the loop has to have an explanation available of the system’s recommendation. Reason explanations are especially well-suited to this end, and we examine whether—and how—it might be possible to make such explanations fit with AI systems. We support our claims by focusing on a case of disagreement between human in the loop and AI system.

Further data

Item Type: Article in a journal
Refereed: Yes
Keywords: Explainable artificial intelligence; Reasons; Reason explanations; Moral responsibility; Responsibility gap; Decision support systems
Institutions of the University: Faculties > Faculty of Cultural Studies > Department of Philosophy
Faculties
Faculties > Faculty of Cultural Studies
Result of work at the UBT: No
DDC Subjects: 100 Philosophy and psychology > 100 Philosophy
Date Deposited: 27 Feb 2023 08:19
Last Modified: 28 Feb 2023 06:27
URI: https://eref.uni-bayreuth.de/id/eprint/73034