From Responsibility to Reason-Giving Explainable Artificial Intelligence

Philosophy and Technology 35 (1):1-30 (2022)
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Abstract

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.

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Author Profiles

Kevin Baum
German Research Center for Artificial Intelligence
Susanne Mantel
Universität des Saarlandes
Eva Schmidt
TU Dortmund

References found in this work

Models in Science (2nd edition).Roman Frigg & Stephan Hartmann - 2021 - The Stanford Encyclopedia of Philosophy.
Intention.G. E. M. Anscombe - 1957 - Cambridge, Mass.: Harvard University Press.
Responsibility and Control: A Theory of Moral Responsibility.John Martin Fischer & Mark Ravizza - 1998 - New York: Cambridge University Press. Edited by Mark Ravizza.
Freedom and Resentment.Peter Strawson - 1962 - Proceedings of the British Academy 48:187-211.
Free Will, Agency, and Meaning in Life.Derk Pereboom - 2014 - New York: Oxford University Press.

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