Depth and deference: When and why we attribute understanding

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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): “…2014), to experimental philosophy examining the distinction between knowing and understanding and what it means to understand (Wilkenfeld, 2016; Wilkenfeld et al. 2016ab), to applied research on education and learning examining factors that influence understanding (e.g., Chi et al., 1994);…”
What Do We Want From Explainable Artificial Intelligence (XAI)? - A Stakeholder Perspective on XAI and a Conceptual Model Guiding Interdisciplinary XAI Research (2021, background): “Providing explanatory information of a given phenomenon is the default procedure to facilitate its understanding [147, 172, 173].”
Explanation-seeking curiosity in childhood (2020, background): “Explanation search often involves consultation with and deference to experts [108,109], suggesting thirdperson cues may be especially powerful in triggering ESC.”
Artificial intelligence and illusions of understanding in scientific research (2024, unknown): “To benefit from communities of knowledge, people need to track how knowledge clusters in other minds 75,79 and determine who deserves epistemic trust 69,77,78,80 in order to consult and defer to them for advice 81 .”