XKDD 2020 - Call for Papers ------------------------------------------------------------------------- 2nd International Workshop on eXplainable Knowledge Discovery in Data Mining ------------------------------------------------------------------------- Deadline Extension!!! New deadline is 19 June 2020. Notification 14 July. COVID-19 PLAN In line with the organization of ECML-PKDD 2020, the organizers of XKDD 2020 have decided to take the workshop fully virtual. The events of the past few months and the continued safety concerns have led us to make this difficult decision. Our focus now is on creating a virtual conference with the vibrancy, excellence and sense of community that ECML-PKDD has become known for. Thus, all accepted contributions will be published, presented, etc, as normal (although presentations might take a different form). In the coming weeks, the agenda and more programmatic details will be announced, watch the website and our social media posts. CONTEXT & OBJECTIVES In the past decade, machine learning based decision systems have been widely used in a plethora of applications ranging from credit score, insurance risk, and health monitoring, in which accuracy is of the utmost importance. Although the application of these systems may bring myriad benefits, their use might involve some ethical and legal risks, such as codifying biases; jeopardizing transparency and privacy, reducing accountability. Unfortunately, these risks increase and are made more serious by the opacity of these systems, which often are complex and their internal logic is usually inaccessible to humans. Nowadays most of the Artificial Intelligence (AI) systems are based on machine learning algorithms. The relevance and need of ethics in AI is supported and highlighted by the various initiatives that in the world 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. The workshop will seek top-quality submissions addressing uncovered important issues related to ethical, explainable and transparent data mining and machine learning. Papers should present research results in any of the topics of interest for the workshop as well as application experiences, 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 - Explainable Artificial Intelligence - Interpretable Machine Learning - Transparent Data Mining - Explainability in Clustering Analysis - Technical Aspects of Algorithms for Explanation - Explaining Black Box Decision Systems - Adversarial Attack-based Models - Counterfactual and Prototype-based Explanations - Causal Discovery for Machine Learning Explanation - Fairness Checking - Fair Machine Learning - Explanation for Privacy Risk - Ethics Discovery for Explainable AI - Privacy-Preserving Explanations - Transparent Classification Approaches - Anonymity and Information Hiding Problems in Comprehensible Models - Case Study Analysis - Experiments on Simulated and Real Decision Systems - Monitoring and Understanding System Behavior - Privacy Risk Assessment - Privacy by Design Approaches for Human Data - Statistical Aspects, Bias Detection and Causal Inference - Explanation, Accountability and Liability from an Ethical and Legal Perspective - Benchmarking and measuring explanation - Visualization-based explanations - Iterative dialogue explanations SUBMISSION & PUBLICATION All contributions will be reviewed by at least three members of the Program Committee. As regards size, contributions can be up to 16 pages in LNCS format, i.e., the ECML PKDD 2020 submission format. All papers should be written in English and be in LNCS format. The following kinds of submissions will be considered: research papers, tool papers, case study papers, and position papers. Detailed information on the submission procedure are available at the workshop web page: https://kdd.isti.cnr.it/xkdd2020/ Accepted papers will be published after the workshop by Springer in a volume of Lecture Notes in Computer Science (LNCS). Condition for inclusion in the post-proceedings is that at least one of the co-authors has 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 the following: https://easychair.org/conferences/?conf=xkdd2020 IMPORTANT DATES Paper Submission deadline: Thursday, 19 June, 2020 Accept/Reject Notification: Tuesday, 14 July, 2020 Camera-ready deadline: Tuesday, 21 July, 2020 Workshop: Monday, 14 September, 2020 PROGRAM CO-CHAIRS * Riccardo Guidotti, University of Pisa, Italy * Anna Monreale, University of Pisa, Italy * Salvatore Rinzivillo, ISTI-CNR, Pisa,  Italy * Przemyslaw Biecek, Warsaw University of Technology, Poland INVITED SPEAKERS * Francesco Bonchi, ISI Foundation, Italy * Christoph Molnar, Ludwig-Maximilians-University of Munich, Germany PROGRAM COMMITTEE Osbert Bastani, University of Pennsylvania, US Livio Bioglio, University of Turin, Italy Tobias Blanke, King's College London, UK Francesco Bonchi, ISI Foundation, Italy Giuseppe Casalicchio, Ludwig-Maximilians-University of Munich, Germany Chaofan Chen, Duke University, UK Luca Costabello, Accenture Labs Dublin, Ireland Mark Coté, King's College London, UK Miguel Couceiro, LORIA CNRS, France Josep Domingo-Ferrer, Universitat Rovira i Virgili, Spain Boxiang Dong, Montclair State University, US Alex Freitas, University of Kent, US Luis Galárraga, Aalborg University, France Giannotti Fosca, ISTI-CNR Pisa, Italy Aristides Gionis, KTH Royal Institute of Technology, Sweden Thibault Laugel, Sorbonne University, France Paulo Lisboa, Liverpool John Moores University, UK Pasquale Minervini, University College London, UK Ioannis Mollas, Aristotle University of Thessaloniki, Greece Christoph Molnar, Ludwig-Maximilians-University of Munich, Germany Cecilia Panigutti, Scuola Normale Superiore Pisa, Italy András Pataricza, Technical University of Budapest, Hungary Dino Pedreschi, University of Pisa, Italy Francesca Pratesi, University of Pisa, Italy Xavier Renard, AXA - LinkedIn, Frances Fabrizio Sebastiani, ISTI-CNR, Italy Dylan Slack, University of California Irvine, US Dominik Slezak, University of Warsaw, Poland Vicenc Torra, Umeå University, Sweden Grigorios Tsoumakas, Aristotle University of Thessaloniki, Greece Franco Turini, University of Pisa, Italy Cagatay Turkay, University of Warwick, UK CONTACT All inquires should be sent to xkdd2020@easychair.org