When people make decisions using the results of the machine learning algorithms that power AI systems, it’s vitally important that they are able to interpret and understand the results correctly. These are often communicated in the form of data visualizations and can sometimes be very complex to give meaning to. The central research question in visual analytics is how to design data visualisations that can be correctly understood by users to help them to make the right decisions. This question lies in the intersection of human-computer interaction, machine learning and data visualization.
This short workshop will include 4 talks and individual meetings with the speakers.
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