@article{Richter2024, author = {Richter, Florian}, title = {From human-system interaction to human-system co-action and back: ethical assessment of generative AI and mutual theory of mind}, volume = {5}, journal = {AI and Ethics}, number = {1}, publisher = {Springer}, address = {Cham}, issn = {2730-5961}, doi = {https://doi.org/10.1007/s43681-024-00626-z}, pages = {19 -- 28}, year = {2024}, abstract = {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.}, language = {en} } @article{FreierBockletHeltenetal.2023, author = {Freier, Carolin and Bocklet, Tobias and Helten, Anne-Kathrin and Hoffmann, Franziska and Hunger, Marianne and Kov{\´a}cs, L{\´a}szl{\´o} and Richter, Florian and Riedhammer, Korbinian and Schmohl, Tobias and Simon, Claudia}, title = {Wie kann videogest{\"u}tztes Lernen die Erwartungen Studierender und Dozierender erf{\"u}llen?}, volume = {15}, journal = {Soziale Passagen}, number = {2}, publisher = {Springer}, address = {Wiesbaden}, issn = {1867-0199}, doi = {https://doi.org/10.1007/s12592-023-00478-0}, pages = {631 -- 635}, year = {2023}, abstract = {Im BMBF-Verbundprojekt HAnS entwickeln und implementieren neun Hochschulen sowie drei hochschul{\"u}bergreifende Einrichtungen ein intelligentes Hochschul-Assistenz-System als Open-Source-L{\"o}sung. Videobasierte Lehrmaterialien werden verschriftlicht und durch eine Indexierung Stichwortsuchen erm{\"o}glicht; geplant ist, {\"u}ber einen KI-Tutor automatisiert {\"U}bungsaufgaben zu generieren. Studierende sollen so in ihrem Selbststudium digital unterst{\"u}tzt werden. Die technische Entwicklung wird interdisziplin{\"a}r - auch sozialwissenschaftlich und p{\"a}dagogisch - 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.}, language = {de} } @inproceedings{KruegelRichterUhl2025, author = {Kr{\"u}gel, Sebastian and Richter, Florian and Uhl, Matthias}, title = {Context-Dependency of Trust in AI-based Systems}, booktitle = {2025 IEEE International Symposium on Technology and Society (ISTAS 2025)}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3315-9597-5}, doi = {https://doi.org/10.1109/ISTAS65609.2025.11269654}, year = {2025}, language = {en} } @article{GlahnHaghoferDonovanetal.2024, author = {Glahn, Imaine and Haghofer, Andreas and Donovan, Taryn and Degasperi, Brigitte and Bartel, Alexander and Kreilmeier-Berger, Theresa and Hyndman, Philip S. and Janout, Hannah and Assenmacher, Charles-Antoine and Bartenschlager, Florian and Bolfa, Pompei and Dark, Michael and Klang, Andrea and Klopfleisch, Robert and Merz, Sophie and Richter, Barbara and Schulman, F. Yvonne and Ganz, Jonathan and Scharinger, Josef and Aubreville, Marc and Winkler, Stephan M. and Bertram, Christof}, title = {Automated Nuclear Morphometry: A Deep Learning Approach for Prognostication in Canine Pulmonary Carcinoma to Enhance Reproducibility}, volume = {11}, pages = {278}, journal = {Veterinary Sciences}, number = {6}, publisher = {MDPI}, address = {Basel}, issn = {2306-7381}, doi = {https://doi.org/10.3390/vetsci11060278}, year = {2024}, abstract = {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.}, language = {en} } @article{HaidenRichter2025, author = {Haiden, Michael and Richter, Florian}, title = {Autonomous weapons: considering the rights and interests of soldiers}, volume = {27}, pages = {53}, journal = {Ethics and Information Technology}, number = {4}, publisher = {Springer}, address = {Dordrecht}, issn = {1388-1957}, doi = {https://doi.org/10.1007/s10676-025-09859-w}, year = {2025}, abstract = {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.}, language = {en} } @inbook{Richter2025, author = {Richter, Florian}, title = {Justice and Smart Societies: Conceptual Foundations, Limitations, and Conditions of Algorithmizing Fairness}, booktitle = {Engineering and Value Change}, editor = {Didier, Christelle and B{\´e}ranger, Aur{\´e}lien and Bouzin, Antoine and Paris, Hugo and Supiot, J{\´e}r{\´e}mie}, publisher = {Springer}, address = {Cham}, isbn = {978-3-031-83549-0}, doi = {https://doi.org/10.1007/978-3-031-83549-0_6}, pages = {83 -- 100}, year = {2025}, language = {en} }