@inbook{65084,
  author       = {{Buhl, Heike M. and Vollmer, Anna-Lisa and Alami, Rachid and Booshehri, Meisam and Främling, Kary}},
  booktitle    = {{Social explainable AI}},
  editor       = {{Rohlfing, Katharina J. and Främling, Kary and Lim, Brian and Alpsancar, Suzana and Thommes, Kisten}},
  pages        = {{269--295}},
  publisher    = {{Springer}},
  title        = {{{Models of the situation, the explanandum, and the interaction partner}}},
  doi          = {{https://doi.org/10.1007/978-981-96-5290-7_14}},
  year         = {{2026}},
}

@inbook{61150,
  abstract     = {{Since the emergence of the field of eXplainable Artificial Intelligence (XAI), a growing number of researchers have argued that XAI should consider insights from the social sciences in order to adapt explanations to the expectations and needs of human users. This has led to the emergence of a field called Social XAI, which is concerned with understanding how explanations are actively shaped in the interaction between a human user and an AI system. Recognizing this turn in XAI toward making XAI systems more “social” by providing explanations that focus on human information needs and incorporating insights from human–human explanatory interactions, in this paper we provide a formal foundation for Social XAI. We do so by proposing novel ontological accounts of the key terms used in Social XAI based on Basic Formal Ontology (BFO). Specifically, we provide novel ontological accounts for explanandum, explanans, understanding, explanation, explainer, explainee, and context. In doing so, we discuss multifaceted entities in Social XAI (having both continuant and occurrent facets; e.g., explanation) and the relationship between understanding and explanation. Additionally, we propose solutions to seemingly paradoxical views on some terms (e.g., social constructivist vs. individual constructivist perspective on explanandum).}},
  author       = {{Booshehri, Meisam and Buschmeier, Hendrik and Cimiano, Philipp}},
  booktitle    = {{Proceedings of the 15th International Conference on Formal Ontology in Information Systems}},
  isbn         = {{9781643686172}},
  issn         = {{0922-6389}},
  location     = {{Catania, Italy}},
  pages        = {{255–268}},
  publisher    = {{IOS Press}},
  title        = {{{A BFO-based ontological analysis of entities in Social XAI}}},
  doi          = {{10.3233/faia250498}},
  year         = {{2025}},
}

@inproceedings{61153,
  author       = {{Booshehri, Meisam and Buschmeier, Hendrik and Cimiano, Philipp}},
  booktitle    = {{Abstracts of the 3rd TRR 318 Conference: Contextualizing Explanations}},
  location     = {{Bielefeld, Germany}},
  title        = {{{A BFO-based ontology of context for Social XAI}}},
  year         = {{2025}},
}

@inproceedings{55403,
  abstract     = {{In this paper we consider the interactive processes by which an explainer and an explainee cooperate to produce an explanation, which we refer to as co-construction. Explainable Artificial Intelligence (XAI) is concerned with the development of intelligent systems and robots that can explain and justify their actions, decisions, recommendations, and so on. However, the cooperative construction of explanations remains a key but under-explored issue. This short paper proposes an architecture for intelligent systems that promotes a co-constructive and interactive approach to explanation generation. By outlining its basic components and their specific roles, we aim to contribute to the advancement of XAI computational frameworks that actively engage users in the explanation process.}},
  author       = {{Buschmeier, Hendrik and Cimiano, Philipp and Kopp, Stefan and Kornowicz, Jaroslaw and Lammert, Olesja and Matarese, Marco and Mindlin, Dimitry and Robrecht, Amelie Sophie and Vollmer, Anna-Lisa and Wagner, Petra and Wrede, Britta and Booshehri, Meisam}},
  booktitle    = {{Proceedings of the 2024 Workshop on Explainability Engineering}},
  location     = {{Lisbon, Portugal}},
  pages        = {{20--25}},
  publisher    = {{ACM}},
  title        = {{{Towards a Computational Architecture for Co-Constructive Explainable Systems}}},
  doi          = {{10.1145/3648505.3648509}},
  year         = {{2024}},
}