Simple idealized models seem to provide more understanding than opaque, complex, and
hyper-realistic models. However, an increasing number of scientists are going in the …

The counterfactual approach to explainable AI (XAI) seeks to provide understanding of AI
systems through the provision of counterfactual explanations. In a recent systematic review …

One way to delineate the concept of epistemically rational belief is to locate it in relation to
other core concepts of epistemology, especially those of knowledge and justified belief …

Explainable artificial intelligence (XAI) is an emerging, multidisciplinary field of research that
seeks to develop methods and tools for making AI systems more explainable or …

The philosophical interest in the nature, value, and varieties of human understanding has
swelled in recent years. This article will provide an overview of new research in the …

Many AI systems that make important decisions are black boxes: how they function is
opaque even to their developers. This is due to their high complexity and to the fact that they …

To understand why a phenomenon occurs, it is not enough to possess a correct explanation
of the phenomenon: you must grasp the explanation. In this formulation,“grasp” is a …

Among contemporary epistemologists and scholars of ancient philosophy, one often hears
that transmitting propositional knowledge by testimony is easy, while transmitting …

In a recent paper, Erasmus et al.(2021) defend the idea that the ambiguity of the term"
explanation" in explainable AI (XAI) can be solved by adopting any of four different extant …

In this paper, I present an account of group competence that is explicitly framed for cases of
epistemic performances. According to it, we must consider group epistemic competence as …