{"oa":"1","date_updated":"2026-03-19T11:53:01Z","publisher":"Springer Nature Singapore","date_created":"2026-03-19T10:59:18Z","author":[{"first_name":"Katharina J.","last_name":"Rohlfing","orcid":"0000-0002-5676-8233","id":"50352","full_name":"Rohlfing, Katharina J."},{"first_name":"Suzana","id":"93637","full_name":"Alpsancar, Suzana","last_name":"Alpsancar"},{"first_name":"Carsten","last_name":"Schulte","id":"60311","full_name":"Schulte, Carsten"}],"title":"Responsibilities in sXAI","doi":"10.1007/978-981-96-5290-7_9","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1007/978-981-96-5290-7_9"}],"publication_identifier":{"isbn":["9789819652891","9789819652907"]},"publication_status":"published","year":"2026","place":"Singapore","page":"157-177","citation":{"bibtex":"@inbook{Rohlfing_Alpsancar_Schulte_2026, place={Singapore}, title={Responsibilities in sXAI}, DOI={10.1007/978-981-96-5290-7_9}, booktitle={Social Explainable AI}, publisher={Springer Nature Singapore}, author={Rohlfing, Katharina J. and Alpsancar, Suzana and Schulte, Carsten}, year={2026}, pages={157–177} }","short":"K.J. Rohlfing, S. Alpsancar, C. Schulte, in: Social Explainable AI, Springer Nature Singapore, Singapore, 2026, pp. 157–177.","mla":"Rohlfing, Katharina J., et al. “Responsibilities in SXAI.” Social Explainable AI, Springer Nature Singapore, 2026, pp. 157–77, doi:10.1007/978-981-96-5290-7_9.","apa":"Rohlfing, K. J., Alpsancar, S., & Schulte, C. (2026). Responsibilities in sXAI. In Social Explainable AI (pp. 157–177). Springer Nature Singapore. https://doi.org/10.1007/978-981-96-5290-7_9","ieee":"K. J. Rohlfing, S. Alpsancar, and C. Schulte, “Responsibilities in sXAI,” in Social Explainable AI, Singapore: Springer Nature Singapore, 2026, pp. 157–177.","chicago":"Rohlfing, Katharina J., Suzana Alpsancar, and Carsten Schulte. “Responsibilities in SXAI.” In Social Explainable AI, 157–77. Singapore: Springer Nature Singapore, 2026. https://doi.org/10.1007/978-981-96-5290-7_9.","ama":"Rohlfing KJ, Alpsancar S, Schulte C. Responsibilities in sXAI. In: Social Explainable AI. Springer Nature Singapore; 2026:157-177. doi:10.1007/978-981-96-5290-7_9"},"_id":"65061","project":[{"_id":"109","name":"TRR 318: Erklärbarkeit konstruieren"},{"_id":"370","name":"TRR 318; TP B06: Ethik und Normativität der erklärbaren KI"}],"department":[{"_id":"26"},{"_id":"756"}],"user_id":"93637","language":[{"iso":"eng"}],"publication":"Social Explainable AI","type":"book_chapter","abstract":[{"text":"Abstract\r\n \r\n One of the purposes for which XAI is often brought into play is to enable a user to act responsibly. However, responsibility is a complex normative and social phenomenon that we unfold in this chapter. We consider that the classical concepts of agency and responsibility do not fully capture what is needed for meaningful collaboration between human users and XAI. Advocating the perspective of sXAI, we argue that the growing adaptivity of AI systems will result in sXAI being considered as partners. Both partners adopt particular (dialogical) roles within a collaborative process and take responsibility for them. We expect that these roles lead to reactive attitudes toward the sXAI on the side of the human partners that make these roles relational. They resemble those reactive attitudes that we hold toward other human agents. For agents to exercise their responsibility, they need to possess agential capacities to fulfill their role with respect to the structure of a social interaction. Hence, sXAI can be expected to act responsibly. But because of XAI’s limited normative capacities, it might rather act as a marginal agent. We refer to marginal agents and show they can be scaffolded with regard to their agential capacities and their knowledge about the structure of a social interaction. The structure links the actions of the partners to each other in terms of a set of stimuli and responses to it in pursuit of a particular goal. Hence, it is important to differentiate between the different goals that a structure can impose for exercising responsibility. Therefore, we follow (Responsibility from the margins. Oxford University Press; 2015.\r\n https://doi.org/10.1093/acprof:oso/9780198715672.24001.0001\r\n ) and offer three structures that can help to organize responsibility for\r\n decisions made\r\n with the assistance of AI systems. These structures are attributability, answerability, and accountability. Our insights will inform the development and design process of XAI to meet the guiding principles of responsible research and innovation as well as trustworthy AI.\r\n ","lang":"eng"}],"status":"public"}