Explainable Artificial Intelligence for Sustainable Development

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Advancing Social and Economic Transformations

Edited By Ewa Wanda Ziemba, Wioletta Grzenda, Michal Ramsza

ISBN13: 9781032985435
Published: September 30, 2025
Format: Hardback
Pages: 314. 73 B/W Illustrations
Publisher: Routledge

Description:  

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.

Table of Contents:

Acknowledgments

Perface 

Part 1. Foundations of Explainable Artificial Intelligence for Sustainable Development

1. The Rise, Core Principles, and Applications of Explainable Artificial Intelligence in Sustainable Development

Ewa Wanda Ziemba

2. Interpretable and Explainable Machine Learning: Towards Sustainable Development Goals

Wioletta Grzenda

Part 2. Explainable Artificial Intelligence in Business Decisions for Future Sustainable Solutions

3. Artificial Intelligence in Achieving Sustainable Development Goals in the Banking Sector

Aleksandra Nocoń

4. Implementing Responsible AI in Online Marketplaces for Sustainable Development

Dariusz Grabara

5. Explainable AI in the Attestation of Sustainability Reporting

Anna Karmańska

6. Explainable Machine Learning Methods for Probability of Default in Credit Risk Modelling

Aneta Ptak-Chmielewska and Paweł Kopciuszewski

7. Adding Explainability to LSTM Modeling of Business Tendency Survey Results

Michał Bernardelli

8. Cognitive Technologies for Explainable AI in Sustainable Decision Support

Marcin Hernes, Ewa Walaszczyk and Agata Kozina

Part 3. Artificial Intelligence in Societal Transformation for Future Sustainable Solutions

9. Artificial Intelligence for Explaining Credibility of Information

Krzysztof Węcel, Milena Stróżyna and Elżbieta Lewańska

10. Time and Content Domain Analysis of Managerial Actions Aimed at Introducing Artificial Management

Olaf Flak

11. The Determinants of Electricity Prices Through Explainable Machine Learning

Michał Ramsza and Mariusz Kozakiewicz

12. Household Indebtedness in the Face of Unscheduled Events: Variable Importance Analysis

Olga Momot

13. Exploring AI Adoption in Visual Arts Education: Insights From the Polish Sector

Urszula Świerczyńska-Kaczor, Magdalena Kubacka and Małgorzata Kotlińska

14. Explainable AI in Psychiatry: Exploring Obstacles and Biased Credibility – A Review

Barbara Probierz, Aleksandra Straś, Patryk Rodek and Jan Kozak

15. Robotic Arm Digital Twin for Pathomorphological Diagnosis Process

Małgorzata Pańkowska, Mariusz Żytniewski, Mateusz Kozak, Krzysztof Tomaszek, Wacław Banaś and Krzysztof Herbuś

Why Buy This Book?

This book bridges AI innovation and sustainability, offering both theory and practice. With real-world case studies across multiple sectors, it equips readers to apply explainable AI responsibly. It is an indispensable tool for academics seeking research depth, professionals aiming for ethical business strategies, and policymakers committed to aligning AI with the UN Sustainable Development Goals.

Keywords:

explainable AI, sustainable development, artificial intelligence, XAI, ethics in AI, interpretable machine learning, responsible AI, business transformation, UN SDGs, AI education

Target Audience:

Researchers, Academics, Policymakers, AI professionals, Business leaders, NGO practitioners, Educators, Graduate students, Economists, Technology strategists

Genre:

Artificial Intelligence, Sustainable Development, Business & Management, Information Systems, Social Sciences

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