Explainable Artificial Intelligence (XAI) is gaining interests in both academia and industry, mainly thanks to the proliferation of darker more complex black-box solutions which are replacing their more transparent ancestors. Believing that the overall performance of an XAI system can be augmented by considering the end-user as a human being, we are studying the ways we can improve the explanations by making them more informative and easier to use from one hand, and interactive and customisable from the other hand.

Nobani, N., Mercorio, F., Mezzanzanica, M. (2021). Towards an Explainer-agnostic Conversational XAI. In IJCAI International Joint Conference on Artificial Intelligence (pp.4909-4910). International Joint Conferences on Artificial Intelligence.

Towards an Explainer-agnostic Conversational XAI

Nobani N.;Mercorio F.
;
Mezzanzanica M.
2021

Abstract

Explainable Artificial Intelligence (XAI) is gaining interests in both academia and industry, mainly thanks to the proliferation of darker more complex black-box solutions which are replacing their more transparent ancestors. Believing that the overall performance of an XAI system can be augmented by considering the end-user as a human being, we are studying the ways we can improve the explanations by making them more informative and easier to use from one hand, and interactive and customisable from the other hand.
No
paper
XAI, human-AI teaming, natural language explanations
English
International Joint Conference on Artificial Intelligence, IJCAI 2021
9780999241196
Nobani, N., Mercorio, F., Mezzanzanica, M. (2021). Towards an Explainer-agnostic Conversational XAI. In IJCAI International Joint Conference on Artificial Intelligence (pp.4909-4910). International Joint Conferences on Artificial Intelligence.
Nobani, N; Mercorio, F; Mezzanzanica, M
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/362349
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