xxAI - Beyond Explainable AI: International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers

Statistical machine learning (ML) has improved predictivity but has become complex, leading to the emergence of explainable AI (xAI) to create tools and models that are predictive, interpretable, and understandable for humans. This volume aims to accelerate the development of successful explainable AI applications in diverse areas such as image processing, natural language, law, fairness, and climate science.

Format: Paperback / softback
Length: 397 pages
Publication date: 17 April 2022
Publisher: Springer International Publishing AG

Statistical machine learning (ML) has sparked a remarkable resurgence of artificial intelligence (AI), leading to enhanced predictive capabilities. However, the complexity of these models, particularly Deep Neural Networks (DNN), has come at the cost of human interpretability. To address this, the field of explainable AI (xAI) has emerged, aiming to develop tools and models that are both predictive and comprehensible to humans. This burgeoning field is attracting significant attention from researchers, industry professionals, and government agencies, creating a prime opportunity to advance successful explainable AI applications.

This comprehensive volume serves as a valuable resource for the research community, guiding them toward accelerating the development of explainable AI. It promotes a more systematic approach to incorporating explainability into models across diverse domains, ultimately improving their performance. The editors have assembled chapters from esteemed researchers, drawn from both academia and industry, who adopt an interdisciplinary approach to problem-solving. The concepts explored include explainability, causality, and the interaction between AI and humans, with applications spanning image processing, natural language, law, fairness, and climate science.

By delving into current methods, challenges, and emerging developments, this book provides a comprehensive understanding of explainable AI. It serves as a valuable guide for researchers, practitioners, and policymakers seeking to harness the power of AI while ensuring its ethical and responsible deployment. As the field continues to evolve, this volume will remain a pivotal resource for advancing the theory and practice of explainable AI, paving the way for a more transparent and interpretable future.

Weight: 623g
Dimension: 235 x 155 (mm)
ISBN-13: 9783031040825
Edition number: 1st ed. 2022