Shaping Trustworthy AI: An Introduction to This Issue
Kuhl U (2024)
In: Proceedings of the DataNinja sAIOnARA 2024 Conference. Kuhl U (Ed); , 2024. Bielefeld: BieColl: 1-9.
Ulrike Kuhl
postdoc
ukuhl@techfak.uni-bielefeld.de +49 521 106-12125Room: CITEC 2-412
As a postodoctoral researcher, I seek to provide empirical evidence to inform the design, development, and deployment of explainable artifical intelligence (xAI) systems that effectively meet user needs and enhance user trust. Specifically, I focus on the usability of counterfactual explanations, simplified ‘what-if’ scenarios that explore how changes to input variables trigger different model outcomes.
In this way, I aspire to contribute to a more comprehensive understanding of the human factors involved in explainable AI, ultimately fostering the development of more user-centered and actionable explanations in AI systems.
In conjunction with my research work, I serve as the scientific coordinator of the Data-NInJA research training group, supporting young AI researchers to build trustworthy AI for seamless problem solving.
Publications:
CL-XAI: Toward Enriched Cognitive Learning with Explainable Artificial Intelligence
Suffian M, Kuhl U, Alonso-Moral JM, Bogliolo A (2024)
In: Software Engineering and Formal Methods. SEFM 2023 Collocated Workshops. CIFMA 2023 and OpenCERT 2023, Eindhoven, The Netherlands, November 6–10, 2023, Revised Selected Papers. Aldini A (Ed); Lecture Notes in Computer Science, 14568. Cham: Springer : 5-27.
Automatic Matchmaking in Two-Versus-Two Sports
Rüttgers S, Kuhl U, Paaßen B (2024)
In: Proceedings of the 17th International Conference on Educational Data Mining. Paaßen B, Demmans Epp C (Eds); International Educational Data Mining Society: 458--468.
Kuhl U, Artelt A, Hammer B (2023)
In: Explainable Artificial Intelligence. First World Conference, xAI 2023, Lisbon, Portugal, July 26–28, 2023, Proceedings, Part III. Longo L (Ed); Communications in Computer and Information Science. Cham: Springer Nature Switzerland: 280-300.
Kuhl U, Artelt A, Hammer B (2023)
Frontiers in Computer Science 5: 1087929.
Behavioral Economics and Neuroeconomics of Environmental Values
Koundouri P, Hammer B, Kuhl U, Velias A (2023)
Annual Review of Resource Economics 15(1): 153-176.
Kuhl U, Artelt A, Hammer B (2022)
In: 2022 ACM Conference on Fairness, Accountability, and Transparency. New York, NY, USA: ACM: 2125-2137.
Hammer B, Hüllermeier E, Lohweg V, Schneider A, Schenck W, Kuhl U, Braun M, Pfeifer A, Holst C-A, Schmidt M, Schomaker G, et al. (2022)
Bielefeld: Univ. Bielefeld, Forschungsinstitut für Kognition und Robotik.
Kuhl U, Sobotta S, Skeide MA (2021)
PLOS Biology 19(9): e3001407.
Intuitiveness in Active Teaching
Göpfert JP, Kuhl U, Hindemith L, Wersing H, Hammer B (2021)
IEEE Transactions on Human-Machine Systems: 1-10.
Resting-State Functional Connectivity in Mathematical Expertise
Shim M, Hwang H-J, Kuhl U, Jeon H-A (2021)
Brain Sciences 11(4): 430.
Early cortical surface plasticity relates to basic mathematical learning
Kuhl U, Friederici AD, Emmrich F, Brauer J, Wilcke A, Neef N, Boltze J, Kirsten H, Schaadt G, Müller B, Kraft I, et al. (2020)
NeuroImage 204: 116235.
The emergence of dyslexia in the developing brain
Kuhl U, Neef NE, Kraft I, Schaadt G, Dörr L, Brauer J, Czepezauer I, Müller B, Wilcke A, Kirsten H, Emmrich F, et al. (2020)
NeuroImage 211: 116633.
Mathematical expertise modulates the architecture of dorsal and cortico-thalamic white matter tracts
Jeon H-A, Kuhl U, Friederici AD (2019)
Scientific Reports 9(1): 6825.
Kuhl U (2019)
Leipzig: Universität Leipzig.