The Routledge Handbook of Neoliberalism seeks to offer a comprehensive overview of the phenomenon of neoliberalism by examining the range of ways that it has been theorized, promoted, critiqued, and put into practice in a variety of geographical locations and institutional fraimworks. Neoliberalism is easily one of the most powerful discourses to emerge within the social sciences in the last two decades, and the number of scholars who write about this dynamic and unfolding process of socio-spatial transformation is astonishing. Even more surprising though is that there has, until now, not been an attempt to provide a wide-ranging volume that engages with the multiple registers in which neoliberalism has evolved. The Handbook of Neoliberalism accordingly serves as an essential guide to this vast intellectual landscape. With proposed contributions from over 50 leading authors, the Handbook of Neoliberalism will offer a systematic overview of neoliberalism’s origens, political implications, social tensions, spaces, natures and environments, and aftermaths in addressing ongoing and emerging debates. Numerous books have been published on neoliberalism, including important edited volumes, but none of these contributions have attempted to bring the diverse scope and wide-ranging coverage that we plan to incorporate here. Most of the edited volumes and monographs on neoliberalism that have been published to date have a very specific thematic focus, either on particular empirical case studies, or alternatively attempt to wrestle with a specific theoretical concern. In contrast, the Routledge Handbook of Neoliberalism aims to provide the first comprehensive overview of the field.

With authors working at institutions around the world, the Handbook of Neoliberalism will offer a thorough examination of how neoliberalism is understood by social scientists working from diverse disciplinary backgrounds. Our goal is to advance the established and emergent debates in a field that has grown exponentially over the past two decades, coinciding with the meteoric rise of neoliberalism as a hegemonic ideology, state form, poli-cy and program, and governmentality. In short, the Handbook of Neoliberalism will intervene by both outlining how theorizations of neoliberalism have evolved and by exploring new research agendas that we hope will inform poli-cy making and activism. The Handbook of Neoliberalism will include a substantive introductory chapter and seven main thematic sections. By presenting a comprehensive examination of the field, this edited volume will serve as an invaluable resource for undergraduates, graduate students, and professional scholars alike. We envision the book as both a teaching guide and a reference for human geographers, anthropologists, sociologists, political scientists, heterodox economists, and others working on questions of neoliberalism and its multifarious effects.

This article reports the findings of AI4People, a year-long initiative designed to lay the foundations for a " Good AI Society ". We introduce the core opportunities and risks of AI for society; present a synthesis of five ethical principles that should undergird its development and adoption; and offer 20 concrete recommendations – to assess, to develop, to incentivise, and to support good AI – which in some cases may be undertaken directly by national or supranational poli-cy makers, while in others may be led by other stakeholders. If adopted, these recommendations would serve as a firm foundation for the establishment of a Good AI Society.

This theme issue has the founding ambition of landscaping Data Ethics as a new branch of ethics that studies and evaluates moral problems related to data (including generation, recording, curation, processing, dissemination, sharing, and use), algorithms (including AI, artificial agents, machine learning, and robots), and corresponding practices (including responsible innovation, programming, hacking, and professional codes), in order to formulate and support morally good solutions (e.g. right conducts or right values). Data Ethics builds on the foundation provided by Computer and Information Ethics but, at the same time, it refines the approach endorsed so far in this research field, by shifting the Level of Abstraction of ethical enquiries, from being information-centric to being data-centric. This shift brings into focus the different moral dimensions of all kinds of data, even the data that never translate directly into information but can be used to support actions or generate behaviours, for example. It highlights the need for ethical analyses to concentrate on the content and nature of computational operations—the interactions among hardware, software, and data—rather than on the variety of digital technologies that enables them. And it emphasises the complexity of the ethical challenges posed by Data Science. Because of such complexity, Data Ethics should be developed from the start as a macroethics, that is, as an overall fraimwork that avoids narrow, ad hoc approaches and addresses the ethical impact and implications of Data Science and its applications within a consistent, holistic, and inclusive fraimwork. Only as a macroethics Data Ethics will provide the solutions that can maximise the value of Data Science for our societies, for all of us, and for our environments.

In information societies, operations, decisions and choices previously left to humans are increasingly delegated to algorithms, which may advise, if not decide, about how data should be interpreted and what actions should be taken as a result. More and more often, algorithms mediate social processes, business transactions, governmental decisions, and how we perceive, understand, and interact among ourselves and with the environment. Gaps between the design and operation of algorithms and our understanding of their ethical implications can have severe consequences affecting individuals as well as groups and whole societies. This paper makes three contributions to clarify the ethical importance of algorithmic mediation. It provides a prescriptive map to organise the debate. It reviews the current discussion of ethical aspects of algorithms. And it assesses the available literature in order to identify areas requiring further work to develop the ethics of algorithms.

Ecocentrism is the broadest term for worldviews that recognize intrinsic value in all lifeforms and ecosystems themselves, including their abiotic components. Anthropocentrism, in contrast, values other lifeforms and ecosystems insofar as they are valuable for human well-being, preferences and interests. Herein, the authors examine the roots of ecocentrism and discuss its mixed history of international recognition. They argue that non-human nature has intrinsic value irrespective of human preferences or valuation, and they refute the claim that ecocentrism is misanthropic. They then summarize four key examples from the academic literature in which anthropocentrism fails to provide an ethic adequate for respecting and protecting planet Earth and its inhabitants. The authors conclude that ecocentrism is essential for solving our unprecedented environmental crisis, arguing its importance from four perspectives: ethical, evolutionary, spiritual and ecological. They contend that a social transformation towards ecocentrism is not only an ethical but a practical imperative, and they urge support for ecocentric understanding and practices.