IJCAI 2021poster8 citations
Towards an Explainer-agnostic Conversational XAI
Navid Nobani, Fabio Mercorio, Mario Mezzanzanica
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.
Natural Language Processing: DialogueHumans and AI: Intelligent User InterfacesAI Ethics, Trust, Fairness: ExplainabilityHumans and AI: Human-Computer Interaction
BibTeX
@inproceedings{ijcai2021p686,
title = {Towards an Explainer-agnostic Conversational XAI},
author = {Nobani, Navid and Mercorio, Fabio and Mezzanzanica, Mario},
booktitle = {Proceedings of the Thirtieth International Joint Conference on
Artificial Intelligence, {IJCAI-21}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Zhi-Hua Zhou},
pages = {4909--4910},
year = {2021},
month = {8},
note = {Doctoral Consortium},
doi = {10.24963/ijcai.2021/686},
url = {https://doi.org/10.24963/ijcai.2021/686},
}