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|pdfUrl=https://ceur-ws.org/Vol-2567/XCBR_preface.pdf
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|dblpUrl=https://dblp.org/rec/conf/iccbr/Diaz-AgudoRW19
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<pdf width="1500px">https://ceur-ws.org/Vol-2567/XCBR_preface.pdf</pdf>
<pre>
   XCBR: Second Workshop on
   Case-Based Reasoning for the
Explanation of Intelligent Systems.


              Workshop at the
      27th International Conference on
           Case-Based Reasoning
               (ICCBR 2019)

  September, 2019, in Otzenhausen, Germany

            Belén Dı́az-Agudo,
           Juan A. Recio-Garcı́a,
               Ian Watson
Co-Chairs

Belén Dı́az-Agudo
University Complutense of Madrid, Spain

Juan A. Recio-Garcı́a
University Complutense of Madrid, Spain

Ian Watson, University of Auckland, New Zealand

Programme Committee

Derek Bridge, University College Cork, Ireland
Stelios Kapetanakis, University of Brighton, UK
David Leake, Indiana University, USA
Santiago Ontan, Drexel University, USA
Antonio A. Snchez Ruiz-Granados, UCM, Spain
Barry Smyth, University College Dublin, Ireland
David W. Aha Naval Research Laboratory, USA
                                   Preface

    The problem of explainability in Artificial Intelligence is not new but the rise
of autonomous intelligent systems has created the necessity to understand how
these intelligent systems achieve a solution, make a prediction or a recommenda-
tion or reason to support a decision in order to increase users reliability in these
systems. The goal of Explainable Artificial Intelligence (XAI) is to create a suite
of new or modified AI techniques that produce explainable models that, when
combined with e↵ective explanation techniques, enable end users to understand,
appropriately trust, and e↵ectively manage the emerging generation of Artificial
Intelligence systems. Case-Based Reasoning (CBR) systems have previous expe-
riences in interactive explanations and in exploiting memory-based techniques to
generate these explanations that can be successfully applied to the explanation
of other AI techniques.
    The workshop program includes an invited talk by David Aha introducing
what’s happening in XAI today. Then we have organized 2 sessions with 5 pre-
sentations and one discussion panel. This year most of the contributions are
oriented to the practical experience of CBR for explanation in recommender
systems including issues like explanation interfaces, evaluation and applications.
Besides, we have a contribution summarizing the recent trends in XAI, providing
an overview on current approaches, methodologies and interactions.
    We wish to thank all who contributed to the success of this workshop, es-
pecially the authors, the Program Committee, and the editors of the workshop
proceedings!

Belén Dı́az-Agudo                                                 September 2019
Juan A. Recio-Garcı́a
Ian Watson

</pre>