CALL FOR PAPERS
Sixth Workshop on XCBR: Case-Based Reasoning for the Explanation of Intelligent Systems
July 1 Merida, Yucatan, Mexico
www.iccbr24.org/workshops
XCBR workshop aims to provide a medium of exchange for information about trends, research issues and practical experiences in the use of Case-Based Reasoning (CBR) for the inclusion of explanations to several AI techniques (including CBR itself). CBR provides opportunities for exploiting memory-based techniques to generate these explanations that can be successfully applied to the explanation of emerging AI and machine learning techniques.
The problem of explainability in Artificial Intelligence is not new but the rise of the autonomous intelligent systems has created the necessity to understand how these intelligent systems achieve a solution, make a prediction or a recommendation or reason to support a decision to increase users’ trust in these systems.
The goal of Explainable Artificial Intelligence (XAI) is “to create a suite of new or modified machine learning techniques that produce explainable models that, when combined with effective explanation techniques, enable end users to understand, appropriately trust, and effectively manage the emerging generation of Artificial Intelligence (AI) systems”.
For this purpose, the XCBR workshop helps an exchange of ideas and interaction, suited to highlight the main bottlenecks and challenges, as well as the more promising research lines, for CBR research related to the explanation of intelligent systems.
