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2020 – today
- 2021
[b1]Michael Chromik:
Human-centric explanation facilities: explainable AI for the pragmatic understanding of non-expert end users. Ludwig Maximilian University of Munich, Germany, 2021- [c8]Michael Chromik, Andreas Butz:
Human-XAI Interaction: A Review and Design Principles for Explanation User Interfaces. INTERACT (2) 2021: 619-640 - [c7]Michael Chromik:
Making SHAP Rap: Bridging Local and Global Insights Through Interaction and Narratives. INTERACT (2) 2021: 641-651 - [c6]Michael Chromik, Malin Eiband, Felicitas Buchner, Adrian Krüger, Andreas Butz:
I Think I Get Your Point, AI! The Illusion of Explanatory Depth in Explainable AI. IUI 2021: 307-317 - 2020
- [c5]Michael Chromik:
reSHAPe: A Framework for Interactive Explanations in XAI Based on SHAP. ECSCW 2020 - [c4]Michael Chromik, Florian Fincke, Andreas Butz:
Mind the (persuasion) gap: contrasting predictions of intelligent DSS with user beliefs to improve interpretability. EICS 2020: 2:1-2:6 - [c3]Michael Chromik, Martin Schuessler:
A Taxonomy for Human Subject Evaluation of Black-Box Explanations in XAI. ExSS-ATEC@IUI 2020 - [c2]Michael Chromik, Florian Lachner, Andreas Butz:
ML for UX? - An Inventory and Predictions on the Use of Machine Learning Techniques for UX Research. NordiCHI 2020: 57:1-57:11
2010 – 2019
- 2019
- [c1]Michael Chromik, Malin Eiband, Sarah Theres Völkel, Daniel Buschek:
Dark Patterns of Explainability, Transparency, and User Control for Intelligent Systems. IUI Workshops 2019
Coauthor Index
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