Abstract
Understanding of artificial intelligence (AI) systems becomes more important as their use cases in real-world applications growth. Today’s AI systems are increasingly complex and ubiquitous. They will be responsible for making decisions that directly affect individuals. Explainable AI can potentially help by explaining actions, decisions and behaviours of AI systems to users. Our approach is to provide a tool with an interactive user interface in 3D. The tool visualizes deep learning network layers and allows interactive exploration on different levels of detail. The visualization then improves transparency and opacity of AI systems for experts and non-experts.
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Schreiber, A., Bock, M. (2019). Visualization and Exploration of Deep Learning Networks in 3D and Virtual Reality. In: Stephanidis, C. (eds) HCI International 2019 - Posters. HCII 2019. Communications in Computer and Information Science, vol 1033. Springer, Cham. https://doi.org/10.1007/978-3-030-23528-4_29
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DOI: https://doi.org/10.1007/978-3-030-23528-4_29
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