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cs.HC2021★ 19 cited
Explanation Strategies as an Empirical-Analytical Lens for Socio-Technical Contextualization of Machine Learning Interpretability
Jesse Josua Benjamin, Christoph Kinkeldey, Claudia Müller-Birn +2
During a research project in which we developed a machine learning (ML) driven visualization system for non-ML experts, we reflected on interpretability research in ML, computer-su…
cs.HC2021★ 121 cited
Machine Learning Uncertainty as a Design Material: A Post-Phenomenological Inquiry
Jesse Josua Benjamin, Arne Berger, Nick Merrill +1
Design research is important for understanding and interrogating how emerging technologies shape human experience. However, design research with Machine Learning (ML) is relatively…