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.