Previous research in Explainable Artificial Intelligence (XAI) suggests that a main aim of explainability approaches is to satisfy specific interests, goals, expectations, needs, and demands regarding artificial systems (we call these 'stakeholders' desiderata') in a variety of contexts. However, the literature on XAI is vast, spreads out across multiple largely disconnected disciplines, and it often remains unclear how explainability approaches are supposed to achieve the goal of satisfying stakeholders' desiderata. This paper discusses the main classes of stakeholders calling for explainability of artificial systems and reviews their desiderata.

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This paper presents a counterexample to the principle that all epistemic reasons for doxastic attitudes towards p are provided by evidence concerning p. I begin by motivating and clarifying the principle and the associated picture of epistemic reasons, including the notion of evidence concerning a proposition, which comprises both first- and second-order evidence. I then introduce the counterexample from incoherent doxastic attitudes by presenting three example cases. In each case, the fact that the subject’s doxastic attitudes are incoherent is an epistemic reason to suspend, which is not provided by evidence. I argue that this incoherence fact is a reason for the subject to take a step back and reassess her evidence for her conflicting attitudes, and thus a reason to suspend all of them. Suspending judgment enables the subject to revise attitudes where appropriate and thus (typically) to arrive at a set of coherent and well-supported attitudes. I then address a dilemma for my proposal and, in conclusion, briefly suggest a picture of epistemic reasons on which they are to be understood against the background of the subject’s virtuous intellectual conduct.

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