=Paper=
{{Paper
|id=Vol-3389/xcbrpreface
|storemode=property
|title=None
|pdfUrl=https://ceur-ws.org/Vol-3389/xcbrpreface.pdf
|volume=Vol-3389
}}
==None==
Case-Based Reasoning for the Explanation of Intelligent Systems
Organizers:
Juan A. Recio García (University Complutense of Madrid, Spain)
Belén Díaz Agudo (University Complutense of Madrid, Spain)
Anjana Wijekoon (Robert Gordon University, Scotland)
Program Committee:
David Aha Derek Bridge Mark Keane
David Leake Rosina Weber Enric Plaza
Jakob Schönborn Kyle Martin Nirmalie Wiratunga
Bruno Fleisch Anne Liret David Corsar
Ike Nkisi-Orji
XCBR is a workshop aiming to provide a medium of exchange for information about trends,
research issues and practical experiences in the use of Case-Based Reasoning (CBR) methods
for the inclusion of explanations to several AI techniques (including CBR itself).
The success of intelligent systems has led to an explosion of the generation of new autonomous
systems with new capabilities like perception, reasoning, decision support and self-action.
Despite the tremendous benefits of these systems, they work as black-box systems and their
effectiveness is limited by their inability to explain their decisions and actions to human users.
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 in order
to increase users’ trust in these systems. Additionally, the European Union included in their
regulation about the protection of natural persons with regard to the processing of personal
data a new directive about the need of explanations to ensure fair and transparent processing
in automated decision-making systems.