Luciano Floridi

This open access book presents an ethical approach to utilizing personal medical data. It features essays that combine academic argument with practical application of ethical principles. The contributors are experts in ethics and law. They address the challenges in the re-use of medical data of the deceased on a voluntary basis. This pioneering study looks at the many factors involved when individuals and organizations wish to share information for research, policy-making, and humanitarian purposes. Today, it is easy to donate blood or even organs, but it is virtually impossible to donate one’s own medical data. This is seen as ethically unacceptable. Yet, data donation can greatly benefit the welfare of our societies. This collection provides timely interdisciplinary research on biomedical big data. Topics include the ethics of data donation, the legal and regulatory challenges, and the current and future collaborations. Readers will learn about the ethical and regulatory challenges associated with medical data donations. They will also better understand the special nature of using deceased data for research purposes with regard to ethical principles of autonomy, beneficence, and justice. In addition, the contributors identify the key governance issues of such a scheme. The essays also look at what we can learn in terms of best practice from existing medical data schemes.

The proposed European Artificial Intelligence Act (AIA) is the first attempt to elaborate a general legal framework for AI carried out by any major global economy. As such, the AIA is likely to become a point of reference in the larger discourse on how AI systems can (and should) be regulated. In this article, we describe and discuss the two primary enforcement mechanisms proposed in the AIA: the _conformity assessments_ that providers of high-risk AI systems are expected to conduct, and the _post-market monitoring plans_ that providers must establish to document the performance of high-risk AI systems throughout their lifetimes. We argue that the AIA can be interpreted as a proposal to establish a Europe-wide ecosystem for conducting AI auditing, albeit in other words. Our analysis offers two main contributions. First, by describing the enforcement mechanisms included in the AIA in terminology borrowed from existing literature on AI auditing, we help providers of AI systems understand how they can prove adherence to the requirements set out in the AIA in practice. Second, by examining the AIA from an auditing perspective, we seek to provide transferable lessons from previous research about how to refine further the regulatory approach outlined in the AIA. We conclude by highlighting seven aspects of the AIA where amendments (or simply clarifications) would be helpful. These include, above all, the need to translate vague concepts into verifiable criteria and to strengthen the institutional safeguards concerning conformity assessments based on internal checks.

Over the past few years, there has been a proliferation of artificial intelligence strategies, released by governments around the world, that seek to maximise the benefits of AI and minimise potential harms. This article provides a comparative analysis of the European Union and the United States’ AI strategies and considers the visions of a ‘Good AI Society’ that are forwarded in key policy documents and their opportunity costs, the extent to which the implementation of each vision is living up to stated aims and the consequences that these differing visions of a ‘Good AI Society’ have for transatlantic cooperation. The article concludes by comparing the ethical desirability of each vision and identifies areas where the EU, and especially the US, need to improve in order to achieve ethical outcomes and deepen cooperation.

Computational and information‐theoretic research in philosophy has become increasingly fertile and pervasive, giving rise to a wealth of interesting results. In consequence, a new and vitally important field has emerged, the philosophy of information (PI). This essay is the first attempt to analyse the nature of PI systematically. PI is defined as the philosophical field concerned with the critical investigation of the conceptual nature and basic principles of information, including its dynamics, utilisation, and sciences, and the elaboration and application of information‐theoretic and computational methodologies to philosophical problems. I argue that PI is a mature discipline for three reasons: it represents an autonomous field of research; it provides an innovative approach to both traditional and new philosophical topics; and it can stand beside other branches of philosophy, offering a systematic treatment of the conceptual foundations of the world of information and the information society.

This paper considers a host of definitions and labels attached to the concept of smart cities to identify four dimensions that ground a review of ethical concerns emerging from the current debate. These are: network infrastructure, with the corresponding concerns of control, surveillance, and data privacy and ownership; post-political governance, embodied in the tensions between public and private decision-making and cities as post-political entities; social inclusion, expressed in the aspects of citizen participation and inclusion, and inequality and discrimination; and sustainability, with a specific focus on the environment as an element to protect but also as a strategic element for the future. Given the persisting disagreements around the definition of a smart city, the article identifies in these four dimensions a more stable reference framework within which ethical concerns can be clustered and discussed. Identifying these dimensions makes possible a review of the ethical implications of smart cities that is transversal to their different types and resilient towards the unsettled debate over their definition.

Necessity and sufficiency are the building blocks of all successful explanations. Yet despite their importance, these notions have been conceptually underdeveloped and inconsistently applied in explainable artificial intelligence, a fast-growing research area that is so far lacking in firm theoretical foundations. In this article, an expanded version of a paper originally presented at the 37th Conference on Uncertainty in Artificial Intelligence, we attempt to fill this gap. Building on work in logic, probability, and causality, we establish the central role of necessity and sufficiency in XAI, unifying seemingly disparate methods in a single formal framework. We propose a novel formulation of these concepts, and demonstrate its advantages over leading alternatives. We present a sound and complete algorithm for computing explanatory factors with respect to a given context and set of agentive preferences, allowing users to identify necessary and sufficient conditions for desired outcomes at minimal cost. Experiments on real and simulated data confirm our method’s competitive performance against state of the art XAI tools on a diverse array of tasks.

The goal of the book is to present the latest research on the new challenges of data technologies. It will offer an overview of the social, ethical and legal problems posed by group profiling, big data and predictive analysis and of the different approaches and methods that can be used to address them. In doing so, it will help the reader to gain a better grasp of the ethical and legal conundrums posed by group profiling. The volume first maps the current and emerging uses of new data technologies and clarifies the promises and dangers of group profiling in real life situations. It then balances this with an analysis of how far the current legal paradigm grants group rights to privacy and data protection, and discusses possible routes to addressing these problems. Finally, an afterword gathers the conclusions reached by the different authors and discuss future perspectives on regulating new data technologies.

This book offers an overview of the ethical problems posed by Information Warfare, and of the different approaches and methods used to solve them, in order to provide the reader with a better grasp of the ethical conundrums posed by this new form of warfare. The volume is divided into three parts, each comprising four chapters. The first part focuses on issues pertaining to the concept of Information Warfare and the clarifications that need to be made in order to address its ethical implications. The second part collects contributions focusing on Just War Theory and its application to the case of Information Warfare. The third part adopts alternative approaches to Just War Theory for analysing the ethical implications of this phenomenon. Finally, an afterword by Neelie Kroes - Vice President of the European Commission and European Digital Agenda Commissioner - concludes the volume. Her contribution describes the interests and commitments of the European Digital Agenda with respect to research for the development and deployment of robots in various circumstances, including warfare.

We propose a formal framework for interpretable machine learning. Combining elements from statistical learning, causal interventionism, and decision theory, we design an idealisedexplanation gamein which players collaborate to find the best explanation(s) for a given algorithmic prediction. Through an iterative procedure of questions and answers, the players establish a three-dimensional Pareto frontier that describes the optimal trade-offs between explanatory accuracy, simplicity, and relevance. Multiple rounds are played at different levels of abstraction, allowing the players to explore overlapping causal patterns of variable granularity and scope. We characterise the conditions under which such a game is almost surely guaranteed to converge on a (conditionally) optimal explanation surface in polynomial time, and highlight obstacles that will tend to prevent the players from advancing beyond certain explanatory thresholds. The game serves a descriptive and a normative function, establishing a conceptual space in which to analyse and compare existing proposals, as well as design new and improved solutions.

Information and communication technology occupies a central place in the modern world, with society becoming increasingly dependent on it every day. It is therefore unsurprising that it has become a growing subject area in contemporary philosophy, which relies heavily on informational concepts. _The Routledge Handbook of Philosophy of Information_ is an outstanding reference source to the key topics and debates in this exciting subject and is the first collection of its kind. Comprising over thirty chapters by a team of international contributors the _Handbook_ is divided into four parts: basic ideas quantitative and formal aspects natural and physical aspects human and semantic aspects. Within these sections central issues are examined, including probability, the logic of information, informational metaphysics, the philosophy of data and evidence, and the epistemic value of information. The Routledge Handbook of Philosophy of Information is essential reading for students and researchers in philosophy, computer science and communication studies.

In this article, we analyse the role that artificial intelligence (AI) could play, and is playing, to combat global climate change. We identify two crucial opportunities that AI offers in this domain: it can help improve and expand current understanding of climate change, and it can contribute to combatting the climate crisis effectively. However, the development of AI also raises two sets of problems when considering climate change: the possible exacerbation of social and ethical challenges already associated with AI, and the contribution to climate change of the greenhouse gases emitted by training data and computation-intensive AI systems. We assess the carbon footprint of AI research, and the factors that influence AI’s greenhouse gas (GHG) emissions in this domain. We find that the carbon footprint of AI research may be significant and highlight the need for more evidence concerning the trade-off between the GHG emissions generated by AI research and the energy and resource efficiency gains that AI can offer. In light of our analysis, we argue that leveraging the opportunities offered by AI for global climate change whilst limiting its risks is a gambit which requires responsive, evidence-based, and effective governance to become a winning strategy. We conclude by identifying the European Union as being especially well-placed to play a leading role in this policy response and provide 13 recommendations that are designed to identify and harness the opportunities of AI for combatting climate change, while reducing its impact on the environment.

This chapter provides an overview of six topics related to governance, ethical, legal, and social implications of artificial intelligence (AI) for sustainable development goals (SDGs) initiatives. We identified six common challenges and related opportunities to mitigate such challenges, as referred to by the authors analysing the chapters provided in the book The Ethics of Artificial Intelligence for the Sustainable Development Goals. They are (1) governance and collaboration, (2) private investments and the role of big tech companies, (3) AI and communities, (4) AI and individuals, (5) jobs and skills, and (6) impact assessment.