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Conference papers

Explain to whom? Putting the User in the Center of Explainable AI

Abstract : The ability to explain actions and decisions is often regarded as a basic ingredient of cognitive systems. But when researchers propose methods for making AI systems understandable, users are usually not involved or even mentioned. However, the purpose is to make people willing to accept the decision of a machine or to be better able to interact with it. Therefore, I argue that the evaluation of explanations must involve some form of user testing.
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Contributor : Alexandra Kirsch Connect in order to contact the contributor
Submitted on : Friday, July 20, 2018 - 10:41:59 AM
Last modification on : Thursday, January 6, 2022 - 11:38:05 AM
Long-term archiving on: : Sunday, October 21, 2018 - 3:47:27 PM


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  • HAL Id : hal-01845135, version 1


Alexandra Kirsch. Explain to whom? Putting the User in the Center of Explainable AI. Proceedings of the First International Workshop on Comprehensibility and Explanation in AI and ML 2017 co-located with 16th International Conference of the Italian Association for Artificial Intelligence (AI*IA 2017), 2017, Bari, Italy. ⟨hal-01845135⟩



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