Hayashi Yoichi    Department   Undergraduate School  , School of Science and Technology    Position   Professor
Language	English
Publication Date	2024/02
Type	Academic Journal
Title	Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directions
Contribution Type	Co-authored (other than first author)
Journal	Information Fusion
Journal Type	Another Country
Publisher	Elsevier
Volume, Issue, Page	106(102301),pp.1-22
Total page number	22
Responsible for	Conceptualizations, Investigation, Methodology, Validation, Writing-review & editing
International coauthorship	International coauthorship
Author and coauthor	Luca Longo, Mario Brcic, Federico Cabitza, Jaesik Choi, Roberto Confalonieri, Javier Del Ser, Riccardo Guidotti, Yoichi Hayashi, Francisco Herrera, Andreas Holzinger, Richard Jiang, Hassan Khosravi, Freddy Lecue, Gianclaudio Malgieri, Andrés Páez, Wojciech Samek, Johannes Schneider, Timo Speith, Simone Stumpf
Details	This paper not only highlights the advancements in XAI and its application in real-world scenarios but also addresses the ongoing challenges within XAI, emphasizing the need for broader perspectives and collaborative efforts. We bring together experts from diverse fields to identify open problems, striving to synchronize research agendas and accelerate XAI in practical applications. By fostering collaborative discussion and interdisciplinary cooperation, we aim to propel XAI forward, contributing to its continued success. Our goal is to put forward a comprehensive proposal for advancing XAI. To achieve this goal, we present a manifesto of 27 open problems categorized into nine categories. These challenges encapsulate the complexities and nuances of XAI and offer a road map for future research. For each problem, we provide promising research directions in the hope of harnessing the collective intelligence of interested stakeholders.
URL for researchmap	https://doi.org/10.1016/j.inffus.2024.102301