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9 Publications


2025 | Journal Article | LibreCat-ID: 59756
Visser, Roel, et al. “Trust, Distrust, and Appropriate Reliance in (X)AI: A Conceptual Clarification of User Trust and Survey of Its Empirical Evaluation.” Cognitive Systems Research, 101357, Elsevier BV, 2025, doi:10.1016/j.cogsys.2025.101357.
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2025 | Journal Article | LibreCat-ID: 59755
Peters, Tobias Martin, and Ingrid Scharlau. “Interacting with Fallible AI: Is Distrust Helpful When Receiving AI Misclassifications?” Frontiers in Psychology, vol. 16, 2025, doi:10.3389/fpsyg.2025.1574809.
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2025 | Preprint | LibreCat-ID: 61159 | OA
Peters, Tobias Martin, et al. Assessing Healthy Distrust in Human-AI Interaction: Interpreting Changes in Visual Attention. Center for Open Science, 2025.
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2025 | Conference Paper | LibreCat-ID: 61232
Visser, Roel, et al. “Explaining Outliers Using Isolation Forest and Shapley Interactions.” Proceedings of the European Symposium on Artificial Neural Networks (ESANN), 2025.
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2025 | Preprint | LibreCat-ID: 59917 | OA
Paaßen, Benjamin, et al. “Healthy Distrust in AI Systems.” ArXiv, 2025.
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2023 | Conference Paper | LibreCat-ID: 48595
Peters, Tobias Martin, and Roel W. Visser. “The Importance of Distrust in AI.” Communications in Computer and Information Science, Springer Nature Switzerland, 2023, doi:10.1007/978-3-031-44070-0_15.
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2023 | Journal Article | LibreCat-ID: 61301
Artelt, André, et al. “‘I Do Not Know! But Why?’ — Local Model-Agnostic Example-Based Explanations of Reject.” Neurocomputing, vol. 558, 126722, Elsevier BV, 2023, doi:10.1016/j.neucom.2023.126722.
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2022 | Conference Paper | LibreCat-ID: 61303
Artelt, André, et al. “Explaining Reject Options of Learning Vector Quantization Classifiers.” Proceedings of the 14th International Joint Conference on Computational Intelligence, SCITEPRESS - Science and Technology Publications, 2022, doi:10.5220/0011389600003332.
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2022 | Conference Paper | LibreCat-ID: 61302
Artelt, André, et al. “Model Agnostic Local Explanations of Reject.” ESANN 2022 Proceedings, Ciaco - i6doc.com, 2022, doi:10.14428/esann/2022.es2022-34.
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