@inbook{62709,
  author       = {{Reijers, Wessel and Alpsancar, Suzana}},
  booktitle    = {{Social explainable AI. Communications of NII Shonan Meetings}},
  editor       = {{Rohlfing, Katharina and Främling, Kary and Lim, Brian and Alpsancar, Suzana and Thommes, Kirsten}},
  pages        = {{179--195}},
  publisher    = {{Springer}},
  title        = {{{Values and Norms in sXAI}}},
  year         = {{2026}},
}

@book{57167,
  editor       = {{Alpsancar, Suzana and Friedrich, Alexander and Gehring, Petra and Kaminski, Andreas and Nordmann, Alfred}},
  isbn         = {{978-3-7560-1830-7}},
  publisher    = {{Nomos}},
  title        = {{{Jahrbuch Technikphilosophie. Täuschung und Illusion. 10. Jahrgang 2025}}},
  year         = {{2026}},
}

@book{65065,
  abstract     = {{<jats:title>Abstract</jats:title>
                  <jats:p>This introduction sets the stage for the present book. Whereas research in eXplainable AI (XAI) is motivated by societal changes and values, technology development largely ignores social aspects. This book aims to address this research gap with a systematic and comprehensive social view on explainable AI. Besides introducing many relevant concepts, the book offers first access to their possible implementation, thus advancing the development of more social XAI. The introduction starts by connecting the topic to the general research field of XAI. The second part defines the novel approach of social eXplainable AI (sXAI) along the three characteristics of social interaction such as patternedness, incrementality, and multimodality. Finally, the third part explains the structure followed by each chapter. The book offers insights not only for readers who work on technology development but also for those working in sociotechnical fields. Addressing an interdisciplinary readership, the book is an invitation for more exchange and further development of the sXAI field.</jats:p>}},
  editor       = {{Rohlfing, Katharina J. and Främling, Kary and Lim, Brian and Alpsancar, Suzana and Thommes, Kirsten}},
  isbn         = {{9789819652891}},
  publisher    = {{Springer Nature Singapore}},
  title        = {{{Social Explainable AI}}},
  doi          = {{10.1007/978-981-96-5290-7_1}},
  year         = {{2026}},
}

@inbook{61323,
  author       = {{Wrede, Britta and Buschmeier, Hendrik and Rohlfing, Katharina Justine and Booshehri, Meisam and Grimminger, Angela}},
  booktitle    = {{Social Explainable AI}},
  editor       = {{Rohlfing, Katharina J. and Främling, Kary and Alpsancar, Suzana and Thommes, Kirsten and Lim, Brian Y.}},
  pages        = {{227--245}},
  publisher    = {{Springer}},
  title        = {{{Incremental communication}}},
  doi          = {{10.1007/978-981-96-5290-7_12}},
  year         = {{2026}},
}

@inbook{61321,
  author       = {{Grimminger, Angela and Buschmeier, Hendrik}},
  booktitle    = {{Social Explainable AI}},
  editor       = {{Rohlfing, Katharina J. and Främling, Kary and Alpsancar, Suzana and Thommes, Kirsten and Lim, Brian Y.}},
  pages        = {{351--365}},
  publisher    = {{Springer}},
  title        = {{{Theoretical aspects of multimodal processing}}},
  doi          = {{10.1007/978-981-96-5290-7_18}},
  year         = {{2026}},
}

@article{65066,
  abstract     = {{<jats:title>Abstract</jats:title>
                  <jats:p>We investigate whether the recently approved reforms of the apportionment of parliamentary seats to parties in the German Bundestag affects the parties’ political influence measured by power indices. We find that under neither reform the underlying simple game, which describes the possibilities to form governments, remains unchanged and as a result the Shapley-Shubik and the Banzhaf index are unaltered. As a consequence, the major change resulting from the reforms is the reduction of the Bundestag’s size to 630 seats.</jats:p>}},
  author       = {{Duman, Papatya and Haake, Claus-Jochen}},
  issn         = {{0948-5139}},
  journal      = {{Review of Economics}},
  keywords     = {{Bundestag reform, Banzhaf power index, Shapley-Shubik power index}},
  number       = {{3}},
  pages        = {{241--270}},
  publisher    = {{Walter de Gruyter GmbH}},
  title        = {{{A Note on the Size Reduction Reform in the German Parliament: A Game Theoretic Analysis of Power Indices}}},
  doi          = {{10.1515/roe-2024-0048}},
  volume       = {{76}},
  year         = {{2026}},
}

@inbook{64624,
  author       = {{Lehberger, Regine}},
  booktitle    = {{Handlungsorientierung in der Ausbildung von Fachkräften und pädagogischen Fachkräften. Konzeptionen und Forschungsperspektiven}},
  editor       = {{Vogelsang, Christoph and Grotegut, Lea and Bruns, Julia and Riese, Josef and Sabine, Fechner}},
  pages        = {{185--193}},
  publisher    = {{Waxmann}},
  title        = {{{Reflexion von individuellen Selbstregulationsfähigkeiten zur Professionalisierung im bildungswissenschaftlichen Begleitseminar des Praxissemesters}}},
  volume       = {{2}},
  year         = {{2026}},
}

@inbook{61322,
  author       = {{Lazarov, Stefan Teodorov and Tchappi, Igor and Grimminger, Angela}},
  booktitle    = {{Social Explainable AI}},
  editor       = {{Rohlfing, Katharina J. and Främling, Kary and Alpsancar, Suzana and Thommes, Kirsten and Lim, Brian Y.}},
  pages        = {{367--390}},
  publisher    = {{Springer}},
  title        = {{{Characteristics of nonverbal behavior}}},
  doi          = {{10.1007/978-981-96-5290-7_19}},
  year         = {{2026}},
}

@inbook{61324,
  author       = {{Wagner, Petra and Kopp, Stefan}},
  booktitle    = {{Social Explainable AI}},
  editor       = {{Rohlfing, Katharina J. and Främling, Kary and Alpsancar, Suzana and Thommes, Kirsten and Lim, Brian Y.}},
  pages        = {{433--446}},
  publisher    = {{Springer}},
  title        = {{{Timing and synchronization of multimodal signals in explanations}}},
  doi          = {{10.1007/978-981-96-5290-7_22}},
  year         = {{2026}},
}

@inbook{61112,
  author       = {{Rohlfing, Katharina J. and Vollmer, Anna-Lisa and Grimminger, Angela}},
  booktitle    = {{Social Explainable AI}},
  editor       = {{Rohlfing, Katharina and Främling, Kary and Thommes, Kirsten and Alpsancar, Suzana and Lim, Brian Y.}},
  publisher    = {{Springer}},
  title        = {{{Practices: How to establish an explaining practice}}},
  doi          = {{10.1007/978-981-96-5290-7_5}},
  year         = {{2026}},
}

@inbook{65069,
  author       = {{Främling, Kary and Alami, Rachid and Hulstijn, Joris and Tchappi, Igor and Grimminger, Angela and Wrede, Britta and Buschmeier, Hendrik and Kubler, Sylvain}},
  booktitle    = {{Social Explainable AI}},
  editor       = {{Rohlfing, Katharina J. and Främling, Kary and Alpsancar, Suzana and Thommes, Kirsten and Lim, Brian Y.}},
  isbn         = {{9789819652891}},
  pages        = {{19--38}},
  publisher    = {{Springer}},
  title        = {{{Scenarios of Social Explainable AI in practice}}},
  doi          = {{10.1007/978-981-96-5290-7_2}},
  year         = {{2026}},
}

@inproceedings{63031,
  author       = {{Menne, Anna Lena and Schulz, Christian}},
  booktitle    = {{HCI International 2026 Posters: 28th International Conference on Human-Computer Interaction, HCI 2026, Montreal, Canada, July 26-31, 2026, Proceedings}},
  editor       = {{Stephanidis, Constantine  and Antona, Margherita and Ntoa, Stavroula and Salvendy, Gavriel}},
  location     = {{Montreal}},
  publisher    = {{Springer International Publishing}},
  title        = {{{Social Context in Human-AI Interaction (HAI): Towards a Theoretical Framework Based on Multi-Perspectival Imaginaries}}},
  year         = {{2026}},
}

@inbook{55598,
  author       = {{Schulz, Christian}},
  booktitle    = {{Handbuch Social Media: Geschichte – Kultur – Ästhetik}},
  editor       = {{Dörre, Robert and Tuschling, Anna }},
  publisher    = {{Metzler Verlag}},
  title        = {{{Feeds. Ein zentrales Strukturprinzip sozialer Medien}}},
  year         = {{2026}},
}

@article{65082,
  abstract     = {{<jats:p>Encoding information in molecular arrangements on DNA origami nanostructures (DONs) provides the basis for novel concepts in molecular data storage and computing. To preserve their integrity over long timescales, the information‐carrying DONs are often stored in a frozen state. Here, we investigate the effect of repeated freeze–thaw (F/T) cycles on the structural and functional integrity of DONs carrying biotin (Bt) modifications. Streptavidin (SAv) binding is used to visualize the stored information by atomic force microscopy (AFM) before and after 40 F/T cycles. Two strategies are compared by F/T cycling of (I) SAv‐bound DONs and (II) SAv‐free DONs that are exposed to SAv directly before AFM imaging. Our results reveal that while the DONs retain their overall shape, F/T cycling induces a small amount of damage, leading to slightly reduced SAv binding. Adding glycerol at mM concentrations efficiently protects the DONs and restores the original SAv binding yields. Nevertheless, SAv exposure after F/T cycling leads to slightly higher and more consistent SAv binding yields and a lower background of nonspecifically adsorbed SAv compared to Strategy I. This makes information readout by AFM more efficient and renders Strategy II more convenient for long‐term storage of information‐carrying DONs with repeated information readout.</jats:p>}},
  author       = {{Li, Xinyang and Rabbe, Lukas and Linneweber, Jacqueline and Grundmeier, Guido and Keller, Adrian Clemens}},
  issn         = {{2628-9725}},
  journal      = {{Chemistry–Methods}},
  number       = {{3}},
  publisher    = {{Wiley}},
  title        = {{{Stability of Information‐Carrying DNA Origami Nanostructures During Repeated Freeze–Thaw Cycles}}},
  doi          = {{10.1002/cmtd.202500161}},
  volume       = {{6}},
  year         = {{2026}},
}

@article{65081,
  author       = {{Schwede, Jana}},
  journal      = {{berufsbildung}},
  number       = {{1}},
  pages        = {{44--46}},
  publisher    = {{wbv}},
  title        = {{{Drei Lernorte, (k)ein Zusammenwirken? Lernortkooperation im Spannungsfeld von Anspruch und Wirklichkeit}}},
  doi          = {{https://doi.org/10.3278/BB2601W}},
  volume       = {{80}},
  year         = {{2026}},
}

@inbook{65078,
  author       = {{Schroeter-Wittke, Harald}},
  booktitle    = {{Auf der Suche nach Frieden. Evangelische Kirchentage in Ost und West seit 1949}},
  editor       = {{Kuhn, Thomas K. and David, Philipp}},
  pages        = {{253--271}},
  publisher    = {{Evangelische Verlagsanstalt}},
  title        = {{{"Mitten unter euch"?! Frieden und Bibelarbeit auf Kirchentagen}}},
  year         = {{2026}},
}

@article{65077,
  author       = {{Schroeter-Wittke, Harald}},
  journal      = {{Praktische Theologie}},
  pages        = {{82--84}},
  title        = {{{Amor mio, perche piangi? Meine Liebe, warum weinst du? Zum 450. Geburtstag von Vittoria/Raffaella Aleotti (1575 - um 1646)}}},
  volume       = {{61}},
  year         = {{2026}},
}

@inbook{65090,
  abstract     = {{<jats:title>Abstract</jats:title>
                  <jats:p>If XAI are to become social XAI, XAI methods must have capabilities enabling them to ‘extract’ information about the underlying AI model and to generate explanatory content based on that information. In a dialog between explainer and explainee, the explanans presented in every explanation move have to relate to each other understandably and coherently in order to remain trustworthy. This signifies that the generated explanantia have to be consistent—independently of what question is answered by each explanans, in what modality, in what vocabulary, and at what level of abstraction. Moreover, it is advantageous to be able to provide a rich palette of different kinds of explanantia in order to be able to have a fluent dialog in which the explanantia can be generated and adapted to the context, the explainee, feedback, reactions during the interaction with the explainee, and so forth. This chapter attempts to identify relevant questions that an explainee might ask during an explanatory dialog, and it assesses to what extent different XAI methods are capable of addressing these questions in a coherent way. The Contextual Importance and Utility (CIU) method is used to illustrate how an XAI method can generate explanantia for most of the identified questions. CIU also provides a flexibility in how explanatory content is generated that makes it possible to create a meaningful dialog with the explainee.</jats:p>}},
  author       = {{Främling, Kary and Thommes, Kirsten and Wrede, Britta}},
  booktitle    = {{Social Explainable AI}},
  isbn         = {{9789819652891}},
  publisher    = {{Springer Nature Singapore}},
  title        = {{{Generation of Explanatory Content and Requirements for Social XAI}}},
  doi          = {{10.1007/978-981-96-5290-7_15}},
  year         = {{2026}},
}

@inbook{65088,
  abstract     = {{<jats:title>Abstract</jats:title>
                  <jats:p>Quantitatively evaluating the benefits of eXplainable Artificial Intelligence (XAI) and social XAI for humans is not a trivial pursuit. Therefore, we categorize the potential measures in terms of subjective and objective outcomes and short- and long-term outcomes of interactive social XAI. When reviewing the current state of the art, we observed some measurement problems in the literature: (a) Researchers do not clearly state whether they want to measure the inner state of users, users’ behavioral response, or the overall AI-human collaborative performance. (b) Moreover, most measures implicitly assume that all humans either do not react or improve in attitudes or performance. Psychological reactance (feeling or doing the opposite) is usually not captured. (c) Many researchers invent their own scale when measuring psychological constructs, thereby jeopardizing the validity of their measures and slowing down progress in the field, because general evidence and subsequent learning can be achieved only by collecting many compatible pieces of evidence. (d) Most studies look into short-term outcomes and neglect that experiences in social interactions with XAI may evolve and have long-term outcomes not only for the individual but also for groups or society at large.</jats:p>}},
  author       = {{Thommes, Kirsten}},
  booktitle    = {{Social Explainable AI}},
  isbn         = {{9789819652891}},
  publisher    = {{Springer Nature Singapore}},
  title        = {{{Measuring the Outcome of sXAI}}},
  doi          = {{10.1007/978-981-96-5290-7_28}},
  year         = {{2026}},
}

@inbook{65086,
  abstract     = {{<jats:title>Abstract</jats:title>
                  <jats:p>Explainable AI (XAI) aims to make the decisions and behavior of an AI understandable to the people interacting with it and to those affected by its outcomes. To make XAI social, real-world XAI systems need to simulate not only the ways in which human explainers behave within explanatory dialogs but also the ways in which such dialogs can successfully achieve the intended understanding on the explainee’s side. This, in turn, requires an operationalization of the three core aspects of social XAI: multimodality, incrementality, and patterns. This chapter lays the ground for this goal by defining a basic operational model of social interactions that can be refined and extended to account for the specificities of any explanatory real-world setting. This serves as a basis for summarizing and discussing existing ideas from explainability research and related areas in order to operationalize each core aspect. Selected examples and case studies illustrate how to concretely realize such an operationalization, thereby serving as a starting point for future research on social interaction with XAI.</jats:p>}},
  author       = {{Wachsmuth, Henning and Thommes, Kirsten and Alshomary, Milad}},
  booktitle    = {{Social Explainable AI}},
  isbn         = {{9789819652891}},
  publisher    = {{Springer Nature Singapore}},
  title        = {{{Operationalizing Social Interaction}}},
  doi          = {{10.1007/978-981-96-5290-7_27}},
  year         = {{2026}},
}