TY - JOUR A1 - Richter, Florian T1 - From human-system interaction to human-system co-action and back: ethical assessment of generative AI and mutual theory of mind JF - AI and Ethics N2 - Human-machine ethics has emerged as a rapidly growing research field in recent years. However, it seems that Generative Artificial Intelligence (AI) leads to a paradigm shift from human-machine interaction to co-action. The ethical assessment of such relationships is still in the making and needs further scrutiny. First, studies about the influence of technology in human-system interactions and manipulation are reviewed. Second, the “mutual theory of mind” approach is critically examined to identify its shortcomings. Third, creating user models is reconstruced to demonstrate the strategies of systems. Finally, use cases are discussed and assessed to outline ethical implications. UR - https://doi.org/10.1007/s43681-024-00626-z Y1 - 2024 UR - https://doi.org/10.1007/s43681-024-00626-z UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-56557 SN - 2730-5961 VL - 5 IS - 1 SP - 19 EP - 28 PB - Springer CY - Cham ER - TY - JOUR A1 - Freier, Carolin A1 - Bocklet, Tobias A1 - Helten, Anne-Kathrin A1 - Hoffmann, Franziska A1 - Hunger, Marianne A1 - Kovács, László A1 - Richter, Florian A1 - Riedhammer, Korbinian A1 - Schmohl, Tobias A1 - Simon, Claudia T1 - Wie kann videogestütztes Lernen die Erwartungen Studierender und Dozierender erfüllen? JF - Soziale Passagen N2 - Im BMBF-Verbundprojekt HAnS entwickeln und implementieren neun Hochschulen sowie drei hochschulübergreifende Einrichtungen ein intelligentes Hochschul-Assistenz-System als Open-Source-Lösung. Videobasierte Lehrmaterialien werden verschriftlicht und durch eine Indexierung Stichwortsuchen ermöglicht; geplant ist, über einen KI-Tutor automatisiert Übungsaufgaben zu generieren. Studierende sollen so in ihrem Selbststudium digital unterstützt werden. Die technische Entwicklung wird interdisziplinär – auch sozialwissenschaftlich und pädagogisch – begleitet und in einem iterativen Vorgehen evidenzbasiert entsprechend Design-Based-Research angepasst. Wissen und Wertesystem der Anwender*innen, Didaktik, Ethik, Akzeptanz und Datenschutz werden dabei im Entwicklungsprozess einbezogen. N2 - In the Project HAnS nine universities and three cross-institutional initiatives have teamed up on behalf of the German Federal Ministry of Education and Research (BMBF) to design and implement an intelligent university assistance system as open source. The goal is to develop an artificial intelligence (AI) tutor for higher education that transcribes video-based teaching material and enables keyword searches via indexing, but furthermore automatically generates exercises. As a result, students will be digitally assisted in their self-study. According to the design-based research idea, technological development is accompanied by an interdisciplinary approach and is checked and continuously altered throughout the developmental process in terms of user knowledge and values, pedagogical knowledge, ethics, acceptability and data protection. T2 - How can video-assisted learning fulfil the expectations of students and lecturers? UR - https://doi.org/10.1007/s12592-023-00478-0 Y1 - 2023 UR - https://doi.org/10.1007/s12592-023-00478-0 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-44077 SN - 1867-0199 VL - 15 IS - 2 SP - 631 EP - 635 PB - Springer CY - Wiesbaden ER - TY - CHAP A1 - Krügel, Sebastian A1 - Richter, Florian A1 - Uhl, Matthias T1 - Context-Dependency of Trust in AI-based Systems T2 - 2025 IEEE International Symposium on Technology and Society (ISTAS 2025) UR - https://doi.org/10.1109/ISTAS65609.2025.11269654 Y1 - 2025 UR - https://doi.org/10.1109/ISTAS65609.2025.11269654 SN - 979-8-3315-9597-5 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Glahn, Imaine A1 - Haghofer, Andreas A1 - Donovan, Taryn A1 - Degasperi, Brigitte A1 - Bartel, Alexander A1 - Kreilmeier-Berger, Theresa A1 - Hyndman, Philip S. A1 - Janout, Hannah A1 - Assenmacher, Charles-Antoine A1 - Bartenschlager, Florian A1 - Bolfa, Pompei A1 - Dark, Michael A1 - Klang, Andrea A1 - Klopfleisch, Robert A1 - Merz, Sophie A1 - Richter, Barbara A1 - Schulman, F. Yvonne A1 - Ganz, Jonathan A1 - Scharinger, Josef A1 - Aubreville, Marc A1 - Winkler, Stephan M. A1 - Bertram, Christof T1 - Automated Nuclear Morphometry: A Deep Learning Approach for Prognostication in Canine Pulmonary Carcinoma to Enhance Reproducibility JF - Veterinary Sciences N2 - The integration of deep learning-based tools into diagnostic workflows is increasingly prevalent due to their efficiency and reproducibility in various settings. We investigated the utility of automated nuclear morphometry for assessing nuclear pleomorphism (NP), a criterion of malignancy in the current grading system in canine pulmonary carcinoma (cPC), and its prognostic implications. We developed a deep learning-based algorithm for evaluating NP (variation in size, i.e., anisokaryosis and/or shape) using a segmentation model. Its performance was evaluated on 46 cPC cases with comprehensive follow-up data regarding its accuracy in nuclear segmentation and its prognostic ability. Its assessment of NP was compared to manual morphometry and established prognostic tests (pathologists’ NP estimates (n = 11), mitotic count, histological grading, and TNM-stage). The standard deviation (SD) of the nuclear area, indicative of anisokaryosis, exhibited good discriminatory ability for tumor-specific survival, with an area under the curve (AUC) of 0.80 and a hazard ratio (HR) of 3.38. The algorithm achieved values comparable to manual morphometry. In contrast, the pathologists’ estimates of anisokaryosis resulted in HR values ranging from 0.86 to 34.8, with slight inter-observer reproducibility (k = 0.204). Other conventional tests had no significant prognostic value in our study cohort. Fully automated morphometry promises a time-efficient and reproducible assessment of NP with a high prognostic value. Further refinement of the algorithm, particularly to address undersegmentation, and application to a larger study population are required. UR - https://doi.org/10.3390/vetsci11060278 Y1 - 2024 UR - https://doi.org/10.3390/vetsci11060278 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-48612 SN - 2306-7381 VL - 11 IS - 6 PB - MDPI CY - Basel ER - TY - JOUR A1 - Haiden, Michael A1 - Richter, Florian T1 - Autonomous weapons: considering the rights and interests of soldiers JF - Ethics and Information Technology N2 - The development of autonomous weapons systems (AWSs), which would make decisions on the battlefield without direct input from humans, has the potential to dramatically change the nature of war. Due to the revolutionary potential of these technologies, it is essential to discuss their moral implications. While the academic literature often highlights their morally problematic nature, with some proposing outright banning them, this paper highlights an important benefit of AWSs: protecting the lives, as well as the mental and physical health of soldiers. If militaries can avoid sending humans into dangerous situations or relieve drone operators from tasks that lead to lifelong trauma, this obviously appears morally desirable – especially in a world where many soldiers are still drafted against their will. Nonetheless, there are many arguments against AWSs. However, we show that although AWSs are potentially dangerous, criticisms apply equally to human soldiers and weapons steered by them. The combination of both claims makes a strong case against a ban on AWSs where it is possible. Instead, researchers should focus on mitigating their drawbacks and refining their benefits. UR - https://doi.org/10.1007/s10676-025-09859-w Y1 - 2025 UR - https://doi.org/10.1007/s10676-025-09859-w UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-63280 SN - 1388-1957 SN - 1572-8439 VL - 27 IS - 4 PB - Springer CY - Dordrecht ER - TY - CHAP A1 - Richter, Florian ED - Didier, Christelle ED - Béranger, Aurélien ED - Bouzin, Antoine ED - Paris, Hugo ED - Supiot, Jérémie T1 - Justice and Smart Societies: Conceptual Foundations, Limitations, and Conditions of Algorithmizing Fairness T2 - Engineering and Value Change UR - https://doi.org/10.1007/978-3-031-83549-0_6 Y1 - 2025 UR - https://doi.org/10.1007/978-3-031-83549-0_6 SN - 978-3-031-83549-0 SP - 83 EP - 100 PB - Springer CY - Cham ER -