8 citations · 16 across the 5 of their papers we have counts for
5 papers
To Classify is to Interpret: Building Taxonomies from Heterogeneous Data through Human-AI Collaboration
Sebastian Meier, Katrin Glinka
Taxonomy building is a task that requires interpreting and classifying data within a given frame of reference, which comes to play in many areas of application that deal with knowl…
Identifying Explanation Needs of End-users: Applying and Extending the XAI Question Bank
Lars Sipos, Ulrike Schäfer, Katrin Glinka +1
Explanations in XAI are typically developed by AI experts and focus on algorithmic transparency and the inner workings of AI systems. Research has shown that such explanations do n…
Critical-Reflective Human-AI Collaboration: Exploring Computational Tools for Art Historical Image Retrieval
Katrin Glinka, Claudia Müller-Birn
Just as other disciplines, the humanities explore how computational research approaches and tools can meaningfully contribute to scholarly knowledge production. We approach the des…
Investigating Modes of Activity and Guidance for Mediating Museum Exhibits in Mixed Reality
Katrin Glinka, Patrick Tobias Fischer, Claudia Müller-Birn +1
We present an exploratory case study describing the design and realisation of a ''pure mixed reality'' application in a museum setting, where we investigate the potential of using…
Situated Case Studies for a Human-Centered Design of Explanation User Interfaces
Claudia Müller-Birn, Katrin Glinka, Peter Sörries +2
Researchers and practitioners increasingly consider a human-centered perspective in the design of machine learning-based applications, especially in the context of Explainable Arti…