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Navigating the social dilemma of autonomous systems: normative and applied arguments
(2025) Bodenschatz, Anja
Autonomous systems (ASs) become ubiquitous in society. For one specific ethical challenge, normative discussions are scarce: the social dilemma of autonomous systems (SDAS). This dilemma was assessed in empirical studies on autonomous vehicles (AVs). Many people generally agree to a utilitarian programming of ASs, but do not want to buy a machine that might sacrifice them deterministically. One possible way to mitigate the SDAS would be for ASs to randomize between options of action. This would bridge between a socially accepted program and the urge of potential AS users for some sense of self-protection. However, the normativity of randomization has not yet been evaluated for dilemmas between self-preservation and self-sacrifice for the “greater good” of saving several other lives. This paper closes this gap. It provides an overview of the most prominent normative and applied arguments for all three options of action in the dilemmas of interest: self-sacrifice, self-preservation, and randomization. As a prerequisite for inclusion in societal discussions on AS programming, it is ascertained that a normative argument can be elicited for each potential course of action in abstract thought experiments. The paper then progresses to discuss factors that may shift the normative claim between self-sacrifice, self-preservation, and randomization in the case of AV programming. The factors identified in this comparison are generalized into guiding dimensions for moral considerations along which all three options of action should be evaluated when programming ASs for dilemmas involving their users.
Order from entropy: big data from FAIR data cohorts in the digital age of plant breeding
(2025) Gogna, Abhishek; Arend, Daniel; Beier, Sebastian; Rezaei, Ehsan Eyshi; Würschum, Tobias; Zhao, Yusheng; Chu, Jianting; Reif, Jochen C.
Lack of interoperable datasets in plant breeding research creates an innovation bottleneck, requiring additional effort to integrate diverse datasets—if access is possible at all. Handling of plant breeding data and metadata must, therefore, change toward adopting practices that promote openness, collaboration, standardization, ethical data sharing, sustainability, and transparency of provenance and methodology. FAIR Digital Objects, which build on research data infrastructures and FAIR principles, offer a path to address this interoperability crisis, yet their adoption remains in its infancy. In the present work, we identify data sharing practices in the plant breeding domain as Data Cohorts and establish their connection to FAIR Digital Objects. We further link these cohorts to broader research infrastructures and propose a Data Trustee model for federated data sharing. With this we aim to push the boundaries of data management, often viewed as the last step in plant breeding research, to an ongoing process to enable future innovations in the field.
Quantification of soil microbial functional genes as potential new method in environmental risk assessment of pesticides
(2025) Stache, Fabian; Ditterich, Franziska; Hochmanová, Zuzana; Hofman, Jakub; Poll, Christian; Kandeler, Ellen
Pesticides can have adverse effects on soil microorganisms, but they are underrepresented in the currently required OECD 216 test for environmental risk assessment of plant protection products (PPP). The guideline monitors soil microbial nitrogen transformation over 28 days, potentially missing long-term effects of persistent pesticides. Additionally, nitrate alone may be not sensitive enough to detect disruptions in microbial functions. We investigated whether functional gene analysis could provide a more sensitive bioindicator of pesticide impact. To compare this method with the standard test, we conducted a microcosm experiment following the OECD 216 experimental setup. To capture long-term effects beyond the typical test period, we extended the incubation duration to 56 days. Four different concentrations of the persistent fungicide boscalid were added based on predicted environmental concentration. We also assessed microbial responses to fungicide exposure by measuring classical soil microbial parameters. According to the standard test, boscalid had no harmful long-term effects on soil microbiota. In contrast, our analysis of functional genes found an overall reduction in the acid phosphatase-encoding phoN gene abundance on Day 56, and correspondingly, in acid phosphatase activity in the highest fungicide treatment. Simultaneously, we observed a tendency towards lower fungal abundance based on measured copy numbers of an ITS region of nuclear ribosomal DNA (rDNA) and increased cumulative CO2 production. These results indicate a fungicide-related response of the microbial community and impaired microbial phosphorus cycling. Extending the experimental period to 56 days revealed long-term effects that would have otherwise been undetected under the typical 28-day test duration.
Why are toilets not used? Using system effects modelling to understand stakeholder perceptions on the impacts and barriers to Taenia solium control in Eastern and Western Uganda
(2025) Ngwili, Nicholas; Ahimbisibwe, Salaviriuse; Sentamu, Derrick N.; Craven, Luke; Thomas, Lian F.; Roesel, Kristina; Ngwili, Nicholas; Health program, International Livestock Research Institute, Nairobi, Kenya; Ahimbisibwe, Salaviriuse; Health program, International Livestock Research Institute, Nairobi, Kenya; Sentamu, Derrick N.; Department of Public Health Pharmacology and Toxicology, Faculty of Veterinary Sciences, University of Nairobi, Nairobi, Kenya; Craven, Luke; Partnerships for Local Action and Community Empowerment, Melbourne, Australia; Thomas, Lian F.; Health program, International Livestock Research Institute, Nairobi, Kenya; Roesel, Kristina; Health program, International Livestock Research Institute, Nairobi, Kenya
Taenia solium taeniasis/cysticercosis in humans and pigs remains endemic to Uganda. Although, looking at the lifecycle of the parasite, the risk factors are well known, and many biomedical control options exist – no substantial progress has been made in the eradication of T. solium infections in Uganda to date. Contextual factors including socioeconomic, cultural and infrastructural factors, may influence the adoption of interventions. A community-based study using mixed methods and relying on system effects modelling approach was carried out between March and April 2021 in Kamuli district, Eastern Uganda, and Hoima district, Western Uganda. System effects modelling is a non-linear methodology that captures the varied nature of the unique, individually lived experiences and aggregates them to reflect what is experienced at a population level. The aim of the study was to capture individual stakeholder perceptions on the consequences of T. solium infections and barriers to practice known control options. Overall, 27 factors were identified by 192 participants as consequences of being infected with neurocysticercosis (NCC). For taeniasis, 35 factors were identified with 700 edges/connections made by the participants. Enlargement of stomach, weight loss, diarrhoea, weakness, and stunted growth were the most important consequences. Although porcine cysticercosis (PCC) seemed to be poorly understood by the participants, 14 factors were identified which included poor pig growth, loss of market for pig/pork, and poor pork quality. The study also identified important barriers hindering the adoption of control practices, including lack of knowledge on transmission, sociocultural factors, and resource constraints. For women, lack of knowledge on the mode of transmission and lack of a toilet in the compound ranked highly as important barriers with a weighted degree of 31 and 21, respectively, meaning they were identified by more participants unlike men who ranked lack of a toilet first with a weighted degree of 39, followed by lack of knowledge at 24. Different barriers are associated with the adoption of T. solium control practices among community members, stakeholders, and farmers. Despite efforts to address T. solium infections, misconceptions and limited understanding persist among stakeholders, particularly regarding NCC and its associated consequences. The system effects approach supports developing contextualized interventions to help in the control of the diseases associated with this parasite.
Generative KI in der Finanzbranche: strategische, technologische und organisationale Implementierung am Beispiel der DZ BANK AG
(2025) Breiter, Katharina; Lohmann, Tobias; Stahl, Bastian; Zilmans, Carolin; Reischl-Lenz, Birgit; Gimpel, Henner
Generative Künstliche Intelligenz (KI) ist ein entscheidender Wertschöpfungsfaktor in der Finanzbranche, da sie bestehende Prozesse optimiert und neue Geschäftsmodelle ermöglicht. Während zahlreiche Forschungsbeiträge technische, soziale und ethische Aspekte generativer KI untersuchen, adressiert dieser Beitrag insbesondere die strategischen, technologischen und organisationalen Herausforderungen bei der Implementierung generativer KI. Anhand einer Fallstudie bei der DZ BANK AG wird untersucht, wie ein hybrider Plattformansatz eine strategisch fundierte Einführung generativer KI ermöglicht. Technologisch stellt die zentrale IT standardisierte und wiederverwendbare Komponenten bereit, während die Fachbereiche eigenständig KI-basierte Lösungen entwickeln und anpassen. Organisational erfordert dies eine enge Abstimmung zwischen zentraler Steuerung und dezentraler Nutzung, um sowohl Skalierbarkeit als auch Flexibilität zu gewährleisten. Ein iterativer Rollout in „Wellen“ kombiniert technologische Absicherung mit einer stufenweisen Integration in bestehende Geschäftsprozesse. Die Plattform bietet nicht nur eine kontrollierte und sichere Infrastruktur, sondern adressiert auch Herausforderungen wie regulatorische Anforderungen, Datenqualität und die notwendige Qualifikation der MitarbeiterInnen. Die Ergebnisse zeigen, dass der Plattformansatz technologische Komplexität reduziert und gleichzeitig organisationale Agilität fördert. Finanzunternehmen profitieren von kürzeren Entwicklungszyklen, einer effizienteren Prozessgestaltung und einer breiteren Einbindung der MitarbeiterInnen. Abschließend werden praxisorientierte Handlungsempfehlungen für eine erfolgreiche Implementierung generativer KI in der Finanzbranche abgeleitet.