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Talk
in
Workshop: XAI in Action: Past, Present, and Future Applications

Theoretical guarantees for explainable AI?

Ulrike Luxburg


Abstract:

Explainable machine learning is often discussed as a tool to increase trust in machine learning systems. In my opinion, this can only work if the explanations are trustworthy themselves: we should be able to prove strong guarantees on the explanations provided. In my presentation I will argue that strong explanations in interesting scenarios might be difficult to achieve.

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