Anchoring Autonomy: Understanding Seafarers’ Interaction with Energy Efficiency Decision Support Systems for Route Planning and the Role of Basic Psychological Needs Zoubir, M. , Schwarz, B. , Heidinger, J. , Gruner, M. , Jetter, H. , & Franke, T. (2025)Anchoring Autonomy: Understanding Seafarers’ Interaction with Energy Efficiency Decision Support Systems for Route Planning and the Role of Basic Psychological NeedsCognition, Technology & Work. https://doi.org/10.1007/s10111-025-00789-7Zitieren
Effects of user experience in automated information processing on perceived usefulness of digital contact-tracing apps: cross-sectional survey study Schrills, T. , Kojan, L. , Gruner, M. , Calero Valdez, A. , & Franke, T. (2024)Effects of user experience in automated information processing on perceived usefulness of digital contact-tracing apps: cross-sectional survey studyJMIR Human Factors. https://doi.org/10.2196/53940Zitieren
Was KI der öffentlichen Verwaltung bringt Heine, M. , Dhungel, A. , & Beute, E. (2023)Was KI der öffentlichen Verwaltung bringtInnovative Verwaltung. https://doi.org/10.1007/s35114-023-1607-xZitieren
How Gender is Understood and Analyzed in Current E-Government Research – A Scoping Literature Review Dhungel, A. (2022)How Gender is Understood and Analyzed in Current E-Government Research – A Scoping Literature ReviewProceedings of the INFORMATIK 2022. https://doi.org/10.18420/inf2022_111Zitieren
“Siri, How Long Should this Offender Stay in Prison?” Considerations about the Use of Algorithms for Judgments in Criminal Proceedings Dhungel, A. (2022)“Siri, How Long Should this Offender Stay in Prison?” Considerations about the Use of Algorithms for Judgments in Criminal ProceedingsProceedings of the IEEE International Conference on Big Data (Big Data). https://doi.org/10.1109/BigData55660.2022.10020323Zitieren
Deepfakes als Gefahr für die Demokratie – eine rechtliche Einordnung Dhungel, A. , & Beute, E. (2023)Deepfakes als Gefahr für die Demokratie – eine rechtliche EinordnungCologne Technology Review & Law (CTRL), 3, 40-54. Zitieren
“This Verdict was Created with the Help of Generative AI…” – On the Use of Large Language Models by Judges Dhungel, A. (2024)“This Verdict was Created with the Help of Generative AI…” – On the Use of Large Language Models by JudgesDigital Government Research and Practice (DGOV), Special Issue: ChatGPT and other Generative AI Commentaries. https://doi.org/10.1145/3696319Zitieren
Using Machine Learning for Anomaly Detection in German Public Budgeting Data Dhungel, A. , Watermann, L. , Wegner, C. , & Heine, M. (2024)Using Machine Learning for Anomaly Detection in German Public Budgeting DataProceedings of the Intelligent Human Systems Integration (IHSI). Zitieren
Cui bono? Judicial Decision-Making in the Era of AI: A Qualitative Study on the Expectations of Judges in Germany Dhungel, A. , & Heine, M. (2024)Cui bono? Judicial Decision-Making in the Era of AI: A Qualitative Study on the Expectations of Judges in GermanyJournal for Technology Assessment in Theory and Practice (TATuP), 33, 14-20. https://doi.org/10.14512/tatup.33.1.14Zitieren
AI Systems in the Judiciary: Amicus Curiae? Interviews with Judges on Acceptance and Potential Use of Intelligent Algorithms. Dhungel, A. , & Beute, E. (2024)AI Systems in the Judiciary: Amicus Curiae? Interviews with Judges on Acceptance and Potential Use of Intelligent Algorithms.roceedings of the European Conference on Information Systems (ECIS). Zitieren
