4th Workshop on Explainable and Ethical AI jointly with ICPR’2026 

https://xaie4.sciencesconf.org/

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The fourth edition of WS XAI-E follows three successful editions at ICPR’2020, ICPR’2022 and ICPR’2024.  The WS will be held on August 21, 2026 in Lyon, France jointly with the ICPR’2026 conference https://icpr2026.org/. 

** The topics covered by the workshop are: 

• Naturally explainable AI methods

• Post-Hoc Explanation methods of Deep Neural Networks and Transformers

• Technical issues in AI ethics including automated audits, detection of bias, ability to control AI systems to prevent harm and others

• Methods to improve AI explainability in general, including algorithms and evaluation methods

• User interface and visualization for achieving more explainable and ethical AI

• Real world applications and case studies

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. 

We are witnessing the emergence of an “AI economy and society” where AI technologies are increasingly impacting many aspects of business as well as 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. 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 documented 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 systems for people of color, 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 technical and academic communities, but also among policymakers and general public, and will inevitably impede wider adoption of AI in society.

The problems related to Ethical AI are complex and broad and 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 current and popular topics both in technical as well as in business, legal and philosophy communities. Many workshops in this field are held at top conferences, and we believe ICPR has to address this topic broadly and focus on its technical aspects. Our proposed workshop aims to address technical 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 technical perspective.

** Organizing committee: 

Marco Angelini, Univ Rome 3, Italy

Jenny Benois Pineau, Univ. Bordeaux, France

Romain Bourqui, Univ. Bordeaux, France, 

Romain Giot, Univ. Bordeaux, France

Sebastian Lapuschkin, Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute, Germany

** Important dates: 

• May 1, 2026: paper submission 

• June 10, 2026: Notification to authors

• June 20, 2026:: Camera ready versions

• August 21, 2026: Workshop

The WS papers will be published in the proceedings of ICPR’2026.

Marco Angelini, Jenny Benois-Pineau, Romain Bourqui, Romain Giot  and Sebastian Lapuschkin

WS organizers