This book explores how transparent, interpretable AI technologies can support sustainable progress across industries and societies. It brings together theoretical foundations and practical applications of explainable AI (XAI) aligned with the UN's Sustainable Development Goals (SDGs), offering insights into its potential for responsible innovation.
It provides a comprehensive understanding of how explainable AI enhances trust, ethics, and accountability in AI-driven decisions. Through diverse case studies - from banking, e-commerce, and sustainability reporting, to psychiatry, education, and energy-the book demonstrates XAI's transformative role in driving sustainable business practices and societal well-being. Each chapter merges cutting-edge research with real-world examples, making complex AI systems more accessible and socially relevant. The book bridges gaps between disciplines, offering a holistic and actionable perspective on AI for sustainability.
This book is a vital resource for researchers, professionals, and policymakers seeking to harness AI responsibly. Academics in social sciences, economics, and information systems will find a strong theoretical base, while practitioners in business, government, and NGOs gain practical tools for implementing XAI in real contexts. It is also well-suited for students, educators, and AI enthusiasts aiming to align innovation with sustainable, ethical transformation.
Autorentext
Ewa Wanda Ziemba is a Full Professor of Management at the University of Economics in Katowice, Poland, and an ordinary member of the European Academy of Sciences and Arts in Salzburg, Austria. Her research focuses on digital transformation for sustainable development, and she is internationally recognized for developing a multi-dimensional framework for a sustainable information society. She has led more than 40 research projects and currently coordinates an EU-funded initiative TOP4HoneyChains focused on developing sustainable smart honey value chains.
Wioletta Grzenda is an Associate Professor at the Institute of Statistics and Demography, Collegium of Economic Analysis at the SGH Warsaw School of Economics, Poland. She holds a PhD in Mathematics from Maria Curie-Sklodowska University in Lublin, Poland, and a D.Sc. degree in economics and finance from SGH Warsaw School of Economics for her works on Bayesian modeling of family and occupational careers. She is the head of the Statistical Methods and Business Analytics Unit.
Michal Ramsza is an Associate Professor at the Institute of Mathematical Economics, Collegium of Economic Analysis at the SGH Warsaw School of Economics, Poland. He holds an M.Sc. in Mathematics from the University of Warsaw, a Ph.D., and a D.Sc. in mathematical economics from SGH Warsaw School of Economics for his works on the theory of learning in games. He is the head of the Algorithms and Applications Unit.