@misc{10312,
  author       = {{Potthast, Jonas and Grimm, Valentin and Rubart, Jessica}},
  booktitle    = {{Mensch und Computer 2023 – Workshopband, MCI-WS16 - UCAI 2023: Workshop on User-Centered Artificial Intelligence}},
  editor       = {{Fröhlich, Peter and Cobus, Vanessa}},
  location     = {{Rapperswil, Schweiz}},
  publisher    = {{Gesellschaft für Informatik e.V.}},
  title        = {{{Immersive Exploration of Machine Learning Data Combining Visual Analytics with Explainable AI}}},
  doi          = {{10.18420/muc2023-mci-ws16-389}},
  year         = {{2023}},
}

@misc{10789,
  abstract     = {{Explainable AI (XAI) provides approaches and techniques for building trust in AI models. This paper presents and explores XAI approaches focusing on user interface concepts in predictive maintenance. The underlying AI model is based on an open dataset for wind turbines. An enhanced multi-class self-conceived labeling strategy improves the model and, thus, supports the XAI approaches. Previous research in user-centered XAI shows that users do not exploit the possibilities of XAI methods and instead rely on their intuition. To counter this tendency, we present user interfaces incorporating gamification elements to enhance understanding of AI outputs. We highlight our approach via two examples, demonstrating a local and a global XAI technique respectively. A preliminary user study was conducted to assess the value added by these gamification aspects. While the findings were inconclusive, they provided an initial insight into the potential of these design elements to foster user engagement in the realm of XAI.}},
  author       = {{Grimm, Valentin and Potthast, Jonas and Rubart, Jessica}},
  booktitle    = {{2023 IEEE 21st International Conference on Industrial Informatics (INDIN)}},
  keywords     = {{XAI, Industrial Analytics, Motivational Exploration, SHAP}},
  location     = {{Lemgo}},
  pages        = {{1--6}},
  publisher    = {{IEEE}},
  title        = {{{Motivational Exploration of Explanations in Industrial Analytics}}},
  doi          = {{10.1109/INDIN51400.2023.10217864}},
  year         = {{2023}},
}

@misc{9162,
  abstract     = {{The German manufacturing industry has been carrying out new developments towards the next industrial revolution, focusing on smart manufacturing environments. Our work emphasizes human-centered control rooms in the context of production plants. Increased automation does not have to come with less human control. Therefore, we report on multimodal collaborative interaction techniques to augment industrial control rooms. In particular, we include mobile workers who use the control room while being in the production hall using tablets or specifically mixed reality glasses. Collaborative annotation dashboards support discussions and a shared understanding among analysts. Manufacturing-related data can be integrated into business analytics environments so that holistic analyses can be performed. Multimodal interaction techniques can support effective interaction with the control room based on the users’ preferences. Immersive experience through mixed reality-based three-dimensional visualizations and interaction possibilities support users in obtaining a clear understanding of the underlying data.}},
  author       = {{Rubart, Jessica and Grimm, Valentin and Potthast, Jonas}},
  booktitle    = {{Journal Future Internet}},
  issn         = {{1999-5903 }},
  keywords     = {{control room, multimodel interaction, augmented reality, mixed reality}},
  number       = {{8}},
  pages        = {{1--18}},
  publisher    = {{MDPI}},
  title        = {{{Augmenting Industrial Control Rooms with Multimodal Collaborative Interaction Techniques}}},
  doi          = {{https://doi.org/10.3390/fi14080224}},
  volume       = {{14}},
  year         = {{2022}},
}

@misc{9163,
  author       = {{Potthast, Jonas and Grimm, Valentin and Rubart, Jessica}},
  booktitle    = {{Proceedings of Mensch und Computer 2022}},
  editor       = {{Mühlhäuser, Max}},
  location     = {{Darmstadt, DE}},
  pages        = {{594 -- 596}},
  publisher    = {{ACM Press}},
  title        = {{{Immersive Experience of Multidimensional Data using Mixed Reality based Scatterplots}}},
  doi          = {{https://doi.org/10.1145/3543758.3547515}},
  year         = {{2022}},
}