Kostina Prifti

The regulatory challenges posed by Artificial Intelligence (AI) are multifaceted and materialise in various sectors of society. Accounting for the disruptive effects of AI requires a comprehensive approach that is capable of connecting the various regulatory pathways. Digital governance, i.e. the creation of an extensive understanding of the actors and the mechanisms for the governance of the digital, can discharge this function. The previous chapters of this book have analysed what regulatory challenges are posed by AI technologies by focusing on specific regulatory areas and how these can be addressed through digital governance. This chapter presents the main findings discussed throughout the book and a vision for future directions in AI governance.

The issues surrounding the governance of Artificial Intelligence (AI) have been discussed in numerous books, policy briefs, and papers. Some of the problems posed by AI are fundamentally new, others are simply new versions of existing challenges. What is certain is that AI is one of the most disruptive technologies in use today and that it brings opportunities and challenges in different areas and sectors. This book delves deeper into the framework of digital governance, in particular its regulatory patterns, to address the challenges posed by AI and explore ways for designing legal solutions. The chapter begins with information on AI as a disruptive technology, followed by information on digital governance as a framework for addressing the disruption posed by AI. After this background information, the chapter highlights the main theme of the book, including the novelty that this book brings to the literature, as well as the target audiences and readership. Finally, the chapter concludes with an overview of the chapters that this book contains.

This book explores the structure and frameworks of digital governance, focusing on various regulatory patterns, with the aim of tackling the disruptive impact of artificial intelligence (AI) technologies. Addressing the various challenges posed by AI technologies, this book explores potential avenues for crafting legal remedies and solutions, spanning liability of AI, platform governance, and the implications for data protection and privacy. The book is valuable for audiences with or without a technological background. Primarily, it targets academic scholars from a variety of disciplines, including law, ethics, sociology, political science, economics, computer science, and engineering. Particularly, academics interested in interdisciplinary and transdisciplinary studies would benefit from the mixture of disciplines in the book. The scholarly insights in this work are valuable also for policymakers and civil society, by providing potential guidance for effective AI regulation. Additionally, the book can be useful to private companies and organisations that are involved in designing AI applications, offering practical insights and guidance about the legal and societal implications of AI. Kostina Prifti, Esra Demir and Julia Krämer are PhD candidates at Erasmus School of Law, Rotterdam, the Netherlands. Klaus Heine is Professor of Law and Economics at Erasmus School of Law, Rotterdam, the Netherlands. Evert Stamhuis is Professor of Law and Innovation at Erasmus School of Law, Rotterdam, the Netherlands.

Regulation by design (RBD) is a growing research field that explores, develops, and criticises the regulative function of design. In this article, we provide a qualitative thematic synthesis of the existing literature. The aim is to explore and analyse RBD’s core features, practices, limitations, and related governance implications. To fulfil this aim, we examine the extant literature on RBD in the context of digital technologies. We start by identifying and structuring the core features of RBD, namely the goals, regulators, regulatees, methods, and technologies. Building on that structure, we distinguish among three types of RBD practices: compliance by design, value creation by design, and optimisation by design. We then explore the challenges and limitations of RBD practices, which stem from risks associated with compliance by design, contextual limitations, or methodological uncertainty. Finally, we examine the governance implications of RBD and outline possible future directions of the research field and its practices.

This contribution aims at providing a more concrete and accurate understanding of Doughnut economics, its model, and its ideas. In doing so, it provides a comprehensive description of the Doughnut and its connection with the Sustainable Development Goals. Then, it inquires into the philosophical background of Doughnut economics, elucidating its existential rationale that relies on human dignity. Further, examples of four AI applications are used to showcase how the Doughnut model would address their use and challenges that arise thereof. From this testing exercise transpires the understanding that another limitation is required in the Doughnut model, pursuant to its philosophical background. Therefore, besides economic activities that may breach the ecological ceiling or the social foundation, activities that infringe human dignity, without breaching any of the boundaries, are also incompatible with the Doughnut model. This complementing proposal is conceptually represented within the model of Doughnut economics.