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### Talk by [Frank Rudzicz](http://www.cs.toronto.edu/~frank/): "Explainable AI — Interpretability, brains, policies and politics"
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* When: 25th July 2019, at 11:00 am
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* Where: INM seminar room, building 15.9, room 4001b
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In this talk, we take a path through several different approaches to explainability in machine learning. First, we talk about categories of explainability, then we discuss approaches to relevance ranking in terms of engineered features and in terms of heat maps in images through deep Taylor expansion. We then provide a use case of a recent publication on using machine learning with MEG data, and suggest that explainability in brain data has room for improvement. Time permitting, we will briefly cover how explainable AI may help to overcome regulatory and cultural issues in healthcare and therefore accelerate the use of AI methods in practice.
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[Archive Events](Archive Events)
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