@article{61156,
  abstract     = {{Explainability has become an important topic in computer science and artificial intelligence, leading to a subfield called Explainable Artificial Intelligence (XAI). The goal of providing or seeking explanations is to achieve (better) ‘understanding’ on the part of the explainee. However, what it means to ‘understand’ is still not clearly defined, and the concept itself is rarely the subject of scientific investigation. This conceptual article aims to present a model of forms of understanding for XAI-explanations and beyond. From an interdisciplinary perspective bringing together computer science, linguistics, sociology, philosophy and psychology, a definition of understanding and its forms, assessment, and dynamics during the process of giving everyday explanations are explored. Two types of understanding are considered as possible outcomes of explanations, namely enabledness, ‘knowing how’ to do or decide something, and comprehension, ‘knowing that’ – both in different degrees (from shallow to deep). Explanations regularly start with shallow understanding in a specific domain and can lead to deep comprehension and enabledness of the explanandum, which we see as a prerequisite for human users to gain agency. In this process, the increase of comprehension and enabledness are highly interdependent. Against the background of this systematization, special challenges of understanding in XAI are discussed.}},
  author       = {{Buschmeier, Hendrik and Buhl, Heike M. and Kern, Friederike and Grimminger, Angela and Beierling, Helen and Fisher, Josephine Beryl and Groß, André and Horwath, Ilona and Klowait, Nils and Lazarov, Stefan Teodorov and Lenke, Michael and Lohmer, Vivien and Rohlfing, Katharina and Scharlau, Ingrid and Singh, Amit and Terfloth, Lutz and Vollmer, Anna-Lisa and Wang, Yu and Wilmes, Annedore and Wrede, Britta}},
  journal      = {{Cognitive Systems Research}},
  keywords     = {{understanding, explaining, explanations, explainable, AI, interdisciplinarity, comprehension, enabledness, agency}},
  title        = {{{Forms of Understanding for XAI-Explanations}}},
  doi          = {{10.1016/j.cogsys.2025.101419}},
  volume       = {{94}},
  year         = {{2025}},
}

@inproceedings{61403,
  author       = {{Lohmer, Vivien and Kern, Friederike}},
  booktitle    = {{Second International Multimodal Communication Symposium (MMSYM) - Book of Abstract}},
  keywords     = {{gesture, explanations, conversation analysis}},
  location     = {{Goethe-Universität Frankfurt, Deutschland}},
  title        = {{{The role of interactive gestures in explanatory interactions}}},
  year         = {{2024}},
}

@article{59888,
  abstract     = {{Everyday explanations are interactive processes with the aim to provide a less knowledgeable person with reasonable information about other people, objects, or events. Because explanations are interactive communicative processes, the topical structure of an explanation may vary dynamically depending on the immediate feedback of the explainee. In this paper, we analyse topical transitions in medical explanations organised by different physicians (explainers) related to different forms of multimodal behaviour of caregivers (explainees) attending an explanation about the procedures of
an upcoming surgery of a child. The analyses reveal that explainees’ multimodal behaviour with gaze shifts (and particularly gaze aversion) can predict a transition from an elaborated topic to a new one, whereas explainees’ forms of multimodal behaviour with static gaze cannot be related to changes of the topical structure.}},
  author       = {{Lazarov, Stefan Teodorov and Biermeier, Kai and Grimminger, Angela}},
  issn         = {{1572-0381}},
  journal      = {{Interaction Studies}},
  keywords     = {{explanations, multimodal behaviour, elaborations, conditional probabilities}},
  number       = {{3}},
  pages        = {{257 -- 280}},
  publisher    = {{John Benjamins}},
  title        = {{{Changes in the topical structure of explanations are related to explainees’ multimodal behaviour}}},
  doi          = {{10.1075/is.23033.laz}},
  volume       = {{25}},
  year         = {{2024}},
}

@inproceedings{56477,
  abstract     = {{We describe a prototype of a Clinical Decision Support System (CDSS) that provides (counterfactual) explanations to support accurate medical diagnosis. The prototype is based on an inherently interpretable Bayesian network (BN). Our research aims to investigate which explanations are most useful for medical experts and whether co-constructing explanations can foster trust and acceptance of CDSS.}},
  author       = {{Liedeker, Felix and Cimiano, Philipp}},
  keywords     = {{Explainable AI, Clinical decision support, Bayesian network, Counterfactual explanations}},
  location     = {{Lissabon}},
  title        = {{{A Prototype of an Interactive Clinical Decision Support System with Counterfactual Explanations}}},
  year         = {{2023}},
}

@inproceedings{61402,
  author       = {{Lohmer, Vivien and Terfloth, Lutz and Kern, Friederike}},
  booktitle    = {{First International Multimodal Communication Symposium - Book of Abstract}},
  keywords     = {{gesture, dual nature, explanations, architecture, relevance}},
  location     = {{Universität Pompeu Fabra, Barcelona}},
  title        = {{{Explaining the Technical Artifact Quarto!: How Gestures are used in Everyday Explanations}}},
  year         = {{2023}},
}