Connectionists: XKDD 2023 Deadline Extended

[Francesca NARETTO]

XKDD 2023 Deadline Extended!

Due to the high number of requests we decided to extend the submission
deadline to the 27th of June.

Do not miss this chance!



XKDD 2023 - Call for Papers

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5th ECML-PKDD International Workshop on eXplainable Knowledge Discovery in
Data Mining

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CONTEXT & OBJECTIVES

In the past decade, machine learning based decision systems have been
widely used in a wide range of application domains,  like credit score,
insurance risk, and health monitoring, in which accuracy is of the utmost
importance.

Although the support of these systems has an immense potential to improve
the decision in different fields, their use may present ethical and legal
risks, such as codifying biases, jeopardizing transparency and privacy, and
reducing accountability.

Unfortunately, these risks arise in different applications. They are made
even more serious and subtly by the opacity of recent decision support
systems, which are often complex and their internal logic is usually
inaccessible to humans.



Nowadays, most Artificial Intelligence (AI) systems are based on Machine
Learning algorithms.

The relevance and need for ethics in AI are supported and highlighted by
various initiatives arising from the researchers to provide recommendations
and guidelines in the direction of making AI-based decision systems
explainable and compliant with legal and ethical issues.

These include the EU's GDPR regulation which introduces, to some extent, a
right for all individuals to obtain ``meaningful explanations of the logic
involved'' when automated decision making takes place, the ``ACM Statement
on Algorithmic Transparency and Accountability'', the Informatics Europe's
``European Recommendations on Machine-Learned Automated Decision Making''
and ``The ethics guidelines for trustworthy  AI'' provided by the  EU
High-Level Expert Group on AI.



The challenge to design and develop trustworthy AI-based decision systems
is still open and requires a joint effort across technical, legal,
sociological and ethical domains.



The purpose of XKDD, eXaplaining Knowledge Discovery in Data Mining, is to
encourage principled research that will lead to the advancement of
explainable, transparent, ethical and fair data mining and machine learning.

Also, this year the workshop will seek submissions addressing uncovered
important issues in specific fields related to eXplainable AI (XAI), such
as XAI for a more Social and Responsible AI, XAI as a tool to align AI with
human values, XAI for Outlier and Anomaly Detection, quantitative and
qualitative evaluation of XAI approaches, and XAI case studies.

The workshop will seek top-quality submissions related to ethical, fair,
explainable and transparent data mining and machine learning approaches.

Papers should present research results in any of the topics of interest for
the workshop, as well as tools and promising preliminary ideas.

XKDD asks for contributions from researchers, academia and industries,
working on topics addressing these challenges primarily from a technical
point of view but also from a legal, ethical or sociological perspective.



Topics of interest include, but are not limited to:



TOPICS

-   XAI for Social AI

 -   XAI for Responsible AI

-   XAI to Align AI with Human Values

-   XAI for Outlier and Anomaly Detection

-   Quantitative and Qualitative Evaluation of XAI approaches

-   Transparent-by Design Models

 -   XAI Case studies

-   XAI for Privacy-Preserving Systems

-   XAI for Federated Learning

-   XAI for Time Series based Approaches

-   XAI for Graph based Approaches

-   XAI for Visualization

-   XAI in Human-Machine Interaction

-   XAI in Human-in-the-Loop Interactions

-   Counterfactual Explanations

-   Human-Model Interfaces for XAI approaches

-   Explainable Artificial Intelligence (XAI)

-   Interpretable Machine Learning

-   Transparent Data Mining

-   XAI for Fairness Checking

-   Explanation, Accountability and Liability from an Ethical and Legal
Perspective



XKDD 2023 is a Workshop of the ECML-PKDD Conference:
https://2023.ecmlpkdd.org/





SUBMISSION & PUBLICATION

All contributions will be reviewed by at least three members of the Program
Committee. As regards size, contributions can be up to is 14 pages
references excluded in LNCS format, i.e., the ECML PKDD 2023 submission
format. All papers should be written in English. The following kinds of
submissions will be considered: research papers, tool papers, case study
papers and position papers. Detailed information on the submission
procedure is available at the workshop web page:



http://xkdd2023.isti.cnr.it/



If pandemic conditions permit, the workshop will be held in an on-site
format. Recordings of the lectures will be made available to all registered
participants.



Accepted papers will be published after the workshop by Springer in a
volume of Lecture Notes in Computer Science (LNCS). The condition for
inclusion in the post-proceedings is that at least one of the co-authors
registered to ECML-PKDD and presented the paper at the workshop.
Pre-proceedings will be available online before the workshop. We also allow
accepted papers to be presented without publication in the conference
proceedings if the authors choose to do so. Some of the full paper
submissions may be accepted as short papers after review by the Program
Committee. A special issue of a relevant international journal with
extended versions of selected papers is under consideration.



The submission link is:
https://cmt3.research.microsoft.com/ECMLPKDDworkshop2023/Track/16/Submission/Create





IMPORTANT DATES

Paper Submission deadline: June 27, 2023

Accept/Reject Notification: July 13, 2023

Camera-ready deadline: July 31, 2023

Workshop: September 18, 2023





PROGRAM CO-CHAIRS

* Przemyslaw Biecek, Warsaw University of Technology, Poland

* Tania Cerquitelli, Politecnico di Torino, Torino, Italy

* Riccardo Guidotti, University of Pisa, Italy

* Francesca Naretto, Scuola Normale Superiore, Pisa, Italy

* Daniele Regoli, Instesa San Paolo, Italy





PROGRAM COMMITEE



* Miguel Couceiro, Université de Lorraine, France

* Alessandro Castelnovo, Intesa San Paolo, Italy

* Riccardo Crupi, Intesa San Paolo, Italy

* Josep Domingo-Ferrer, Universitat Rovira i Virgili, Spain

* Françoise Fessant, Orange Labs, France

* Salvatore Greco, Politecnico di Torino, Italy

* Andreas Holzinger, Medical University of Graz, Austria

* Paulo Lisboa, Liverpool John Moores University, UK

* Marcin Luckner, Warsaw University of Technology, Poland

* Amedeo Napoli, CNRS, France

* John Mollas, Aristotle University of Thessaloniki, Greece

* Enea Parimbelli, University of Pavia, Italy

* Francesca Pratesi, ISTI-CNR, Italy

* Roberto Prevete, University of Napoli, Italy

* Antonio Rago, Imperial College London, UK

* Eliana Pastor, Politecnico di Torino, Italy

* Jan Ramon, Inria, France

* Xavier Renard, AXA, France

* Mahtab Sarvmaili, Dalhousie University, Canada

* Udo Schlegel, Konstanz University, Germany

* Mattia Setzu, University of Pisa, Italy

* Dominik Slezak, University of Warsaw, Poland

* Myra Spiliopoulou, University Magdeburg, Germany

* Francesco Spinnato, Scuola Noramle Superiore, Italy

* Grigorios Tsoumakas, Aristotle University of Thessaloniki, Greece

* Genoveva Vargas-Solar, CNRS, LIRIS, France

* Albrecht Zimmermann, Université de Caen, France





INVITED SPEAKERS

* Andreas Theissler, Aalen University of Applied Sciences, Aalen, Germany

* Dino Pedreschi, University of Pisa, Italy (tentative)





STEERING COMMITTEE

* Riccardo Guidotti, University of Pisa

* Anna Monreale, University of Pisa

* Salvatore Rinzivillo, ISTI-CNR, Pisa



VENUE

The event will take place at the ECML-PKDD 2023 Conference at the Officine
Grandi Riparazioni (OGR).


CONTACT

All inquiries should be sent to francesca.naretto at di.unipi.it,
riccardo.guidotti at unipi.it
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