The Relational Governance Of Artificial Intelligence

This book addresses the development and adoption of artificial intelligence (AI) in and by companies and the consequent need for private sector AI regulation. Highlighting the challenges to responsible business conduct and considering stakeholder interests, it identifies ethical concerns and discusses AI standards and AI norms. Based on this needs-based analysis, the author chooses relational economics as a suitable approach to develop a theoretical AI governance model. In doing so, AI is conceptualized within relational economics in the form of an autopoietic system. Building on this theoretical contribution, the book specifies the governance adaptivity of the relational AI governance approach for an unregulated AI market and for the case of the pending E.U. AI regulation, and complements it with inductively conducted categories that summarize the main research streams in AI ethics.

This book addresses the development and adoption of artificial intelligence (AI) in and by companies and the consequent need for private sector AI regulation. Highlighting the challenges to responsible business conduct and considering stakeholder interests, it identifies ethical concerns and discusses AI standards and AI norms. Based on this needs-based analysis, the author chooses relational economics as a suitable approach to develop a theoretical AI governance model. In doing so, AI is conceptualized within relational economics in the form of an autopoietic system. Building on this theoretical contribution, the book specifies the governance adaptivity of the relational AI governance approach for an unregulated AI market and for the case of the pending E.U. AI regulation, and complements it with inductively conducted categories that summarize the main research streams in AI ethics.

This book argues that ethical evaluation of AI should be an integral part of public service ethics and that an effective normative framework is needed to provide ethical principles and evaluation for decision-making in the public sphere, at both local and international levels. It introduces how the tenets of prudential rationality ethics, through critical engagement with intersectionality, can contribute to a more successful negotiation of the challenges created by technological innovations in AI and afford a relational, interactive, flexible and fluid framework that meets the features of AI research projects, so that core public and individual values are still honoured in the face of technological development. This book will be of key interest to scholars, students, and professionals engaged in public management and ethics management, AI ethics, public organizations, public service leadership and more broadly to public administration and policy, as well as applied ethics and philosophy.

This book introduces the research agenda of relational economics as a political economy for the governance of local and global economic transactions in modern societies. It analyses the mechanisms of global value creation and production networks by studying cooperation in intra- and inter-firm networks, intersectoral stakeholder management, and transcultural leadership. The author develops a categorical taxonomy for private and public value creation based on the effective and efficient interlinking of, and interaction between, a range of resources and abilities. In contrast to mainstream economics, which largely focuses on the laws of discrete and dyadic exchange transactions, this book assesses the polyvalent characteristics of relational transactions. The chief categories involved in an economic theory of the relations between events are the relational transactions and their various forms of governance; the polycontextual cooperation between economic, political and civil society agents; and the factor incomes and relational rents that relational transactions produce. Today, relational transactions are the rule, not the exception, in modern economies and their global value creation networks. Given its scope and focus, this book will appeal to scholars of economics, economic sociology, organisational studies and related fields.

It is predicted that artificial intelligence [Al], and the “big data” on which Al is based, will become one of the most challenging board issues in the next ten years. This book, AI Leadership for Boards – The Future of Corporate Governance, offers to provide guidance on how corporate boards should respond to this challenge. The findings indicate that while boards are aware of the importance of Al implementation as a key competitive advantage, they will need to develop two competence areas to successfully steward their firms into an Al-based future: [1] guiding Al operational capability and [2] supervising Al governance capability. These areas are combined to create the Boards 4 AI Leadership Matrix – a practical tool for boards to map and develop their Al implementation. The matrix is accompanied by a set of questions to help boards develop a better understanding of where they are today in terms of the development of their Al competences as well as set an ambition for future development. Table of Contents: Acknowledgements Executive Summary Chapter 1. Introduction Chapter 2. Background Chapter 3. Guiding AI operational capability Chapter 3.1. Guiding the gathering, harvesting and analysis of big data in a data strategy Chapter 3.2. Guiding AI-driven innovation strategy Chapter 3.3. Guiding the participation and growth on a business ecosystem Chapter 4. Supervising AI governance Chapter 4.1. Supervising data management, ethics and black box decision-making Chapter 4.2. Supervising AI cybersecurity Chapter 4.3. Supervising business ecosystem participation and leadership Chapter 5. Boards 4 AI leadership matrix– a tool for developing board competence Chapter 6. Beyond competence to the future of board work Chapter 7. Conclusion References The Authors

This timely book investigates emerging efforts to govern artificial intelligence (AI) at an international level. It aptly emphasizes the complex interactions involved when creating international laws, exploring potential and current developments in AI regulation.

Artificial Intelligence Governance is a simple to read and understand book about the needs and potential solutions for human to take control of the most powerful species in the work - Artificial Intelligence. The main advantage of AI regulation, however, will be the ability to put a stop to business operations or close it down entirely if it is found in violation in its use or development of AI. Companies that try to rush an autonomous vehicle to market before it is fully tested for safety or who work on an AI that will violate traffic laws so that it can deliver goods more quickly can be stopped before their products put people at risk.

This book explores the ethical governance of Artificial Intelligence (AI) & Machine Learning (ML) in healthcare. AI/ML usage in healthcare as well as our daily lives is not new. However, the direct, and oftentimes long-term effects of current technologies, in addition to the onset of future innovations, have caused much debate about the safety of AI/ML. On the one hand, AI/ML has the potential to provide effective and efficient care to patients, and this sways the argument in favor of continuing to use AI/ML; but on the other hand, the dangers (including unforeseen future consequences of the further development of the technology) leads to vehement disagreement with further AI/ML usage. Due to its potential for beneficial outcomes, the book opts to push for ethical AI/ML to be developed and examines various areas in healthcare, such as big data analytics and clinical decision-making, to uncover and discuss the importance of developing ethical governance for AI/ML in this setting.