A new dialectical theory of explanation

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Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of Key Ideas and Publications, and Bibliography for Explainable AI (2019, background): “Walton (2004, 2007, 2011) Argues that explanation systems in AI need to be founded on the dialectical concept, that is, explanation is a process of dialog to achieve shared understanding.”
Explanation in Artificial Intelligence: Insights from the Social Sciences (2017, neutral): “Walton [179] proposed a dialectical theory of explanation, putting forward similar ideas to that of Antaki and Leudar [3] in that some parts of an explanatory dialogue require the explainer to provide backing arguments to claims.”
Explaining Explanations in AI (2018, background): “Walton (2004, 2007) takes a similar approach in proposing a dialectical theory of everyday explanations, which suggests that giving explanations involves not only transfer of information or causal claims, but also argumentative support for these claims.”
Dialogical Models of Explanation (2007, methodology): “Complicating the distinction between argument and explanation is the existence of abductive reasoning, or inference to the best explanation (Walton, 2004a).”
Human-Centered Explainable AI (XAI): From Algorithms to User Experiences (2021, background): “Walton [98] further extended this line of work into a formal dialogue model of explanation, including a set of speech act rules.”