Overview
The 4th World Conference on Explainable Artificial Intelligence (xAI) invites researchers and practitioners to submit their research articles. This conference aims to foster discussions on the interpretability and explainability of AI systems, a crucial area as AI technologies become more complex and integrated into various sectors.
Background & Relevance
Explainable AI is an emerging field that seeks to enhance the transparency of AI systems, allowing users to understand the reasoning behind AI decisions. As AI continues to permeate various industries, the need for systems that can explain their outputs becomes increasingly important. This conference serves as a platform for interdisciplinary collaboration, bringing together experts from computer science, psychology, law, and more to address the challenges and advancements in xAI.
Key Details
- Conference Dates: September/October 2026
- Location: Not specified
- Important Submission Dates:
- Authors/title registration: January 15, 2026
- Article upload deadline: February 1, 2026
- Paper bidding for reviewers: February 2-4, 2026
- Review submission deadlines: February 20, 2026
- Notification of acceptance: February 22, 2026
- Registration and camera-ready submission: February 28, 2026
- Article presentation instructions: June 2026
- Publication: Springer CCIS series
Eligibility & Participation
The conference encourages submissions from researchers, industry professionals, and academics interested in the field of explainable AI. It targets those who are exploring novel approaches and addressing open challenges related to AI interpretability.
Submission or Application Guidelines
Submissions must be made through the EasyChair platform. Authors are required to register their paper title and provide necessary details such as author names, affiliations, and keywords. Manuscripts should adhere to the Springer Lecture Notes in Computer Science format. The conference accepts both full articles (14-24 pages) and short articles (10-14 pages).
Additional Context / Real-World Relevance
The focus on explainability in AI is critical as these systems are increasingly used in sensitive applications, including healthcare, finance, and law enforcement. Understanding AI’s decision-making processes can help mitigate risks and enhance trust among users and stakeholders. This conference provides an essential forum for discussing the implications of AI explainability across various domains.
Conclusion
Researchers and practitioners are encouraged to explore this opportunity to contribute to the growing body of knowledge in explainable AI. By submitting your work, you can engage with a community dedicated to advancing the understanding and application of AI technologies. For more details, visit the conference website and prepare your submissions accordingly.
Category: CFP & Deadlines
Tags: explainable ai, xai, conference, call for papers, machine learning, artificial intelligence, interpretability, ethical ai
