A special session dedicated to advancing the understanding of explainable deep neural networks in AI at IJCNN 2025 in Rome.

The growing significance of artificial intelligence in various sectors brings forth critical discussions about transparency and accountability in machine learning models. The DeepXplain 2025 workshop aims to address these concerns by focusing on explainable deep neural networks, which are vital for fostering trust and ensuring ethical AI practices. As advancements in AI continue to shape our society, the need for responsible AI becomes paramount, making this session highly relevant to researchers and practitioners alike.

Scheduled to take place in Rome from June 30 to July 5, 2025, this event invites researchers to share their findings on post-hoc and self-explaining approaches in neural networks. The session seeks to explore innovative methods that enhance model interpretability and facilitate better decision-making processes in AI applications. Participants are encouraged to submit original research papers, case studies, and methodological advancements that contribute to the discourse surrounding responsible AI.

With the rapid integration of deep learning technologies across sectors such as healthcare, finance, and autonomous systems, the implications of explainable AI cannot be overstated. Research has shown that over 70% of AI practitioners recognize the importance of model explainability, highlighting a paradigm shift towards more transparent AI systems. The DeepXplain 2025 session will serve as a pivotal platform for collaboration, paving the way for innovative solutions that align AI capabilities with ethical standards and societal norms.