Artificial intelligence - and social responsibility. Two topics that are at the top of the business agenda. This book discusses in theory and practice how both topics influence each other. In addition to impulses from the current often controversial scientific discussion, it presents case studies from companies dealing with the specific challenges of artificial intelligence. Particular emphasis is placed on the opportunities that artificial intelligence (AI) offers for companies from different industries. The book shows how dealing with the tension between AI and challenges caused by new corporate social responsibility creates strategic opportunities and also innovation opportunities. It highlights the active involvement of stakeholders in the design process, which is meant to build trust among customers and the public and thus contributes to the innovation and acceptance of artificial intelligence. The book is aimed at researchers and practitioners in the fields of corporate social responsibility as well as artificial intelligence and digitalization. The chapter "Exploring AI with purpose" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

As the interplay of environmental, social, and governance factors becomes increasingly crucial, the global business landscape faces a monumental challenge. Climate change, social inequities, and economic uncertainties loom large, demanding immediate attention. The integration of Environmental Social Governance (ESG) principles and Artificial Intelligence (AI) technologies emerges as a powerful solution to these challenges. However, navigating the complexities of this integration, understanding its implications, and harnessing its full potential is a formidable task. Academic scholars, policymakers, and practitioners are grappling with a critical question: How can we leverage the convergence of ESG and AI to drive sustainable practices and address pressing global issues? The answer lies in comprehending the multifaceted dimensions of this integration, its ethical considerations, and its transformative potential. To gain these insights, a comprehensive resource is needed, one that offers a deep dive into ESG-AI integration, delving into empirical research, practical applications, and ethical concerns.Intersecting Environmental Social Governance and AI for Business Sustainability is a book that answers the call to action for this pressing challenge with an in-depth exploration of the evolving field of ESG and AI integration.

The crucial challenge of integrating sustainability into business and investment decisions is compounded by the complexity of analyzing vast and intricate datasets to make informed choices. Traditional approaches often fail to provide timely and accurate insights into environmental, social, and governance (ESG) factors, hindering progress toward a greener future. Additionally, the rapid evolution of AI and machine learning in finance has left many professionals needing help to grasp their full potential in advancing sustainability goals. With a comprehensive understanding and practical guidance, organizations can stay caught up in adopting sustainable practices and leveraging AI for financial and environmental benefits. Social and Ethical Implications of AI in Finance for Sustainability offers a timely and comprehensive solution to these challenges by thoroughly examining how AI can safely enhance sustainability in finance. The book bridges the gap between theory and practice, offering practical insights and real-world applications to empower academics, practitioners, policymakers, and students. Through a series of expertly curated chapters, readers will gain a deep understanding of the role AI plays in reshaping finance for a sustainable future. The book's instructional elements, including case studies and expert analysis, provide a roadmap for incorporating AI into sustainability strategies, enabling organizations to make informed decisions and drive positive change.

A number of articles are increasingly raising awareness on the different uses of artificial intelligence (AI) technologies for customers and businesses. Many authors discuss about their benefits and possible challenges. However, for the time being, there is still limited research focused on AI principles and regulatory guidelines for the developers of expert systems like machine learning (ML) and/or deep learning (DL) technologies. This research addresses this knowledge gap in the academic literature. The objectives of this contribution are threefold: (i) It describes AI governance frameworks that were put forward by technology conglomerates, policy makers and by intergovernmental organizations, (ii) It sheds light on the extant literature on “AI governance” as well as on the intersection of “AI” and “corporate social responsibility” (CSR), (iii) It identifies key dimensions of AI governance, and elaborates about the promotion of accountability and transparency; explainability, interpretability and reproducibility; fairness and inclusiveness; privacy and safety of end users, as well as on the prevention of risks and of cyber security issues from AI systems. This research implies that all those who are involved in the research, development and maintenance of AI systems, have social and ethical responsibilities to bear toward their consumers as well as to other stakeholders in society.