Tove Helldin
Senior Lecturer in Informatics
School of Informatics
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The course highlights the application of data-driven Explainable AI (XAI) approaches to understand AI models and their results. The main emphasis lies on post hoc explanations and how to use them as a basis for appropriate decisions. Moreover, the course focuses on how to avoid uncertainties in the predictions as well an understanding of the value of transparency and explainability for the decision-maker. The course incorporates theories and methods of XAI and discusses the benefits and limitations of XAI.