Explainers' Mental Representations of Explainees' Needs in Everyday Explanations

no code implementations • 13 Nov 2024 • Michael Erol Schaffer, Lutz Terfloth, Carsten Schulte, Heike M. Buhl

In explanations, explainers have mental representations of explainees' developing knowledge and shifting interests regarding the explanandum.

Forms of Understanding of XAI-Explanations

no code implementations • 15 Nov 2023 • Hendrik Buschmeier, Heike M. Buhl, Friederike Kern, Angela Grimminger, Helen Beierling, Josephine Fisher, André Groß, Ilona Horwath, Nils Klowait, Stefan Lazarov, Michael Lenke, Vivien Lohmer, Katharina Rohlfing, Ingrid Scharlau, Amit Singh, Lutz Terfloth, Anna-Lisa Vollmer, Yu Wang, Annedore Wilmes, Britta Wrede

Explainability has become an important topic in computer science and artificial intelligence, leading to a subfield called Explainable Artificial Intelligence (XAI).

Explainable artificial intelligence Explainable Artificial Intelligence (XAI) +1

Adding Why to What? Analyses of an Everyday Explanation

no code implementations • 8 Aug 2023 • Lutz Terfloth, Michael Schaffer, Heike M. Buhl, Carsten Schulte

According to it, one can explain, for example, an XAI's decision by addressing its dual nature: by focusing on the Architecture (e. g., the logic of its algorithms) or the Relevance (e. g., the severity of a decision, the implications of a recommendation).