<html><head><meta http-equiv="content-type" content="text/html; charset=utf-8"></head><body style="overflow-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);">We apologize if you receive this e-mail several times</div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"><br></div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);">***********************Call for papers*****************************************************</div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);">3rd Workshop on Explainable and Ethical AI jointly with ICPR’2024 </div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"><a href="https://xaie.sciencesconf.org/">https://xaie.sciencesconf.org/</a></div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);">*******************************************************************************************</div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);">The third edition of WS XAI-E follows two successful editions at ICPR’2020( <a href="https://edl-ai-icpr.labri.fr/">https://edl-ai-icpr.labri.fr/</a> ) and ICPR’2022 (<a href="https://xaie-icpr.labri.fr/">https://xaie-icpr.labri.fr/</a>).</div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);">The WS will be held on December 1st 2024 in Kolkata, India jointly with the ICPR’2024 conference <a href="https://icpr2024.org/">https://icpr2024.org/</a>. </div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"><br></div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);">**The topics covered by the workshop are: </div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"><span class="Apple-tab-span" style="white-space: pre;"> </span>- Naturally explainable AI methods, </div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"><span class="Apple-tab-span" style="white-space: pre;"> </span>- Post-Hoc Explanation methods of Deep Neural Networks, including transformers and Generative AI, </div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"><span class="Apple-tab-span" style="white-space: pre;"> </span>- Evaluation metrics for Explanation methods,</div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"><span class="Apple-tab-span" style="white-space: pre;"> </span>- Hybrid XAI, </div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"><span class="Apple-tab-span" style="white-space: pre;"> </span>- XAI in generative AI,</div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"><span class="Apple-tab-span" style="white-space: pre;"> </span>- Visualization of Explanations and user interfaces,</div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"><span class="Apple-tab-span" style="white-space: pre;"> </span>- Image-to-text explanations,</div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"><span class="Apple-tab-span" style="white-space: pre;"> </span>- Concept-based explanations,</div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"><span class="Apple-tab-span" style="white-space: pre;"> </span>- Use of explanation methods for Deep NN models in training and generalization.</div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"><span class="Apple-tab-span" style="white-space: pre;"> </span>- Ethical considerations when using pattern recognition models,</div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"><span class="Apple-tab-span" style="white-space: pre;"> </span>- Real-World Application of XAI methods </div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"><br></div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);">Methodology in explainability is related to the creation of explanations, their representation, as well as the quantification of their confidence, while those in AI ethics include automated audits, detection of bias in data and models, ability to control AI systems to prevent harm…. and others methods to improve AI explainability in general and trustfulness to AI. </div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"><br></div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);">We are witnessing the emergence of an “AI economy and society” where AI technologies are increasingly impacting many aspects of business as well as of everyday life. We read with great interest about recent advances in AI medical diagnostic systems, self-driving cars, and the ability of AI technology to automate many aspects of business decisions like loan approvals, hiring, policing etc. In the last years, generative AI is emerging as a major topic promising great benefits but also raising well-founded fears of significant disruption to all aspects of society. Its problems like “hallucinations” and bias are also well known. However, as evident by recent experiences, AI systems may produce errors, can exhibit overt or subtle bias, may be sensitive to noise in the data, and often lack technical and judicial transparency and explainability. These shortcomings have been reported in scientific but also and importantly in general press (accidents with self-driving cars, biases in AI-based policing, hiring and loan systems, biases in face recognition, seemingly correct medical diagnoses later found to be made due to wrong reasons etc.). These shortcomings are raising many ethical and policy concerns not only in technological and research communities, but also among policymakers and general public, and will inevitably impede wider adoption of AI in society.</div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"> </div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);">The problems related to Ethical AI are complex and broad. They encompass not only technical issues but also legal, political and ethical ones. One of the key components of Ethical AI systems is explainability or transparency, but other issues like detecting bias, ability to control the outcomes, ability to objectively audit AI systems for ethics are also critical for successful applications and adoption of AI in society. Consequently, explainable and Ethical AI are very urgent and popular topics both in IT as well as in business, legal and philosophy communities. Many workshops in this field are held at top conferences. </div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);">The third workshop on explainable AI at ICPR aims to address methodological aspects of explainable and ethical AI in general, and include related applications and case studies with the aim to address these very important problems from a broad research perspective.</div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"><br></div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);">** Organizing committee: </div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);">Prof. J. Benois-Pineau, University of Bordeaux, <a href="mailto:jenny.benois-pineau@u-bordeaux.fr">jenny.benois-pineau@u-bordeaux.fr</a></div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);">Dr. R. Bourqui, University of Bordeaux, <a href="mailto:romain.bourqui@u-bordeaux.fr">romain.bourqui@u-bordeaux.fr</a></div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);">Dr. R. Giot, University of Bordeaux, <a href="mailto:romain.giot@u-bordeaux.fr">romain.giot@u-bordeaux.fr</a></div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);">Prof. D. Petkovic, CS Department, San Francisco State University, <a href="mailto:petkovic@sfsu.edu">petkovic@sfsu.edu</a></div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"><br></div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);">**Important dates: </div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"><span class="Apple-tab-span" style="white-space: pre;"> </span>-July 14 , 2024: paper submission : Extended July 30</div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"><span class="Apple-tab-span" style="white-space: pre;"> </span>-September 20, 2024: Notification to authors</div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"><span class="Apple-tab-span" style="white-space: pre;"> </span>-September 27, 2024: Camera ready versions</div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"><br></div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"><br></div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);">The WS papers will be published in the proceedings of ICPR’2024.</div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"> </div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);">Romain Giot, Jenny Benois-Pineau, Romain Bourqui, Dragutin Petkovic </div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);">WS organizers </div></div><div style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"><br></div><br><div>
<meta charset="UTF-8"><div dir="auto" style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); letter-spacing: normal; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; word-spacing: 0px; -webkit-text-stroke-width: 0px; text-decoration: none; overflow-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); letter-spacing: normal; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; word-spacing: 0px; -webkit-text-stroke-width: 0px; text-decoration: none; overflow-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); letter-spacing: normal; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; word-spacing: 0px; -webkit-text-stroke-width: 0px; text-decoration: none; overflow-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div dir="auto" style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); letter-spacing: normal; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; word-spacing: 0px; -webkit-text-stroke-width: 0px; text-decoration: none; overflow-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;">—</div><div dir="auto" style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); letter-spacing: normal; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; word-spacing: 0px; -webkit-text-stroke-width: 0px; text-decoration: none; overflow-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;">Romain Bourqui<div>Maître de conférences / Associate Professor, IUT de Bordeaux & LaBRI UMR CNRS 5800</div><div>Responsable de l’équipe Bench to Knowledge and Beyond / Head of Bench to Knowledge and Beyond research team<br><div><br></div></div></div><br class="Apple-interchange-newline"></div><br class="Apple-interchange-newline"></div><br class="Apple-interchange-newline"></div><br class="Apple-interchange-newline"><br class="Apple-interchange-newline">
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