The Research Group is Moving!

During winter term 2021/22, we move to University of Bamberg. From Oct. 15, 2021, Fabian Beck holds a full professor position on Information Visualization.

New webpage of the research group: https://www.uni-bamberg.de/vis

Publications

Publications of the research group since 2016. For earlier publications, please visit Fabian Beck's Google Scholar or DBLP profile.

Going beyond Visualization: Verbalization as Complementary Medium to Explain Machine Learning Models

Type of Publication: Article in Collected Edition

Going beyond Visualization: Verbalization as Complementary Medium to Explain Machine Learning Models

Author(s):
Sevastjanova, Rita; Beck, Fabian; Ell, Basil; Turkay, Cagatay; Henkin, Rafael; Butt, Miriam; Keim, Daniel; El-Assady, Mennatallah
Title of Anthology:
Workshop on Visualization for AI Explainability at IEEE VIS
Publication Date:
2018
Fulltext:
Going beyond Visualization: Verbalization as Complementary Medium to Explain Machine Learning Models (351 KB)
Citation:
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Abstract

In this position paper, we argue that a combination of visualization and verbalization techniques is beneficial for creating broad and versatile insights into the structure and decision-making processes of machine learning models. Explainability of machine learning models is emerging as an important area of research. Hence, insights into the inner workings of a trained model allow users and analysts, alike, to understand the models, develop justifications, and gain trust in the systems they inform. Explanations can be generated through different types of media, such as visualization and verbalization. Both are powerful tools that enable model interpretability. However, while their combination is arguably more powerful than each medium separately, they are currently applied and researched independently. To support our position that the combination of the two techniques is beneficial to explain machine learning models, we describe the design space of such a combination and discuss arising research questions, gaps, and opportunities.