The IEEE Global Initiative on EthicsEthics of Autonomous and Intelligent Systems is a program of the IEEE initiated to address ethical issues raised by the development and dissemination of these systems. It identified over one hundred and twenty key issues and provided candidate recommendations to address them. In addition, it has provided the inspiration for fourteen approved standardization projects that are currently under development with the IEEE StandardsStandards Association.

-/- Artificial intelligence powers Google’s search engine, enables Facebook to target advertising, and allows Alexa and Siri to do their jobs. AI is also behind self-driving cars, predictive policing, and autonomous weapons that can kill without human intervention. These and other AI applications raise complex ethical issues that are the subject of ongoing debate. This volume in the MIT Press Essential Knowledge series offers an accessible synthesis of these issues. Written by a philosopher of technology, AI Ethics goes beyond the (...) usual hype and nightmare scenarios to address concrete questions. -/- Mark Coeckelbergh describes influential AI narratives, ranging from Frankenstein’s monster to transhumanism and the technological singularity. He surveys relevant philosophical discussions: questions about the fundamental differences between humans and machines and debates over the moral status of AI. He explains the technology of AI, describing different approaches and focusing on machine learning and data science. He offers an overview of important ethical issues, including privacy concerns, responsibility and the delegation of decision making, transparency, and bias as it arises at all stages of data science processes. He also considers the future of work in an AI economy. Finally, he analyzes a range of policy proposals and discusses challenges for policymakers. He argues for ethical practices that embed values in design, translate democratic values into practices and include a vision of the good life and the good society . (shrink)

This paper discusses the problem of responsibility attribution raised by the use of artificial intelligence technologies. It is assumed that only humans can be responsible agents; yet this alone already raises many issues, which are discussed starting from two Aristotelian conditions for responsibility. Next to the well-known problem of many hands, the issue of “many things” is identified and the temporal dimension is emphasized when it comes to the control condition. Special attention is given to the epistemic condition, which draws (...) attention to the issues of transparency and explainability. In contrast to standard discussions, however, it is then argued that this knowledge problem regarding agents of responsibility is linked to the other side of the responsibility relation: the addressees or “patients” of responsibility, who may demand reasons for actions and decisions made by using AI. Inspired by a relational approach, responsibility as answerability thus offers an important additional, if not primary, justification for explainability based, not on agency, but on patiency. (shrink)

Luciano Floridi was not the first to discuss the idea of group privacy, but he was perhaps the first to discuss it in relation to the insights derived from big data analytics. He has argued that it is important to investigate the possibility that groups have rights to privacy that are not reducible to the privacy of individuals forming such groups. In this paper, we introduce a distinction between two concepts of group privacy. The first, the “what happens in Vegas (...) stays in Vegas” privacy (in the following: WHVSV privacy), deals with confidential information shared with the member of a group and inaccessible to (all or a specific group of) outsiders. The second, to which we shall refer as inferential privacy, deals with the inferences that can be made about a group of people defined by a feature, or combination thereof, shared by all individuals in the group. We show why we unreservedly agree with Floridi that groups can have a form of privacy that amounts to more than the mere fact of being sets of individuals each of whom has individual privacy; moreover, like Floridi, we find it plausible that at least some groups (those satisfying our definition of type-a groups) may have a right to a species of group privacy (that is, WHVSV privacy) as groups (and not just as individuals who belong to those groups). However, by turning our attention to the context of big data analytics, we show that the relevant, new notion of group privacy is one of inferential privacy. We argue that an absolute right (either of individuals or groups) to inferential privacy is implausible. We also show that many groups generated algorithmically (those satisfying our definition of type-b groups) cannot be right holders as groups (unless they become type-a groups). (shrink)

Der vorliegende Artikel untersucht moderne Mensch-Maschine-Interaktion im Kontext verbreiteter Hard- und Softwareoberflächen und diskutiert davon ausgehend die Frage nach Aufklärung und Gegenaufklärung im digitalen Zeitalter. Er nimmt das Feld des »User Experience Designs« in den Blick - dies ist ein stilprägender Fachdiskurs, in dem verhaltenswissenschaftliche Erkenntnisse und massendatenbasierte Analysen zur Optimierung von Benutzeroberflächen und Interaktionsdesigns eingesetzt werden. Anhand von Beispielstudien wird argumentiert, dass dieser Gestaltung systematisch drei implizite anthropologische Annahmen zugrunde liegen: Nutzerverhalten gilt als durch prä-reflexive Stimuli beeinflussbar; es gilt (...) als statistisch ausmessbar und vorhersagbar; und Nutzer_innen wollen vermeintlich keine Einblicke in die technischen Abläufe hinter den bunten Bedienoberflächen digitaler Dienste erhalten. Die Diagnose der digitalen Entmündigung verweist sodann auf eine Gesamtheit von strukturellen Tendenzen, durch die Individuen der Fähigkeit zur selbstbestimmten Nutzung ihres Verstands in der Interaktion mit digitalen Artefakten beraubt werden. (shrink)

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. (shrink)

This paper is about an overlooked aspect—the cognitive or epistemic aspect—of the moral demand we place on one another to be treated well. We care not only how people act towards us and what they say of us, but also what they believe of us. That we can feel hurt by what others believe of us suggests both that beliefs can wrong and that there is something we epistemically owe to each other. This proposal, however, surprises many theorists who claim (...) it lacks both intuitive and theoretical support. This paper argues that the proposal has intuitive support and is not at odds with much contemporary theorizing about what we owe to each other. (shrink)

Mature information societies are characterised by mass production of data that provide insight into human behaviour. Analytics has arisen as a practice to make sense of the data trails generated through interactions with networked devices, platforms and organisations. Persistent knowledge describing the behaviours and characteristics of people can be constructed over time, linking individuals into groups or classes of interest to the platform. Analytics allows for a new type of algorithmically assembled group to be formed that does not necessarily align (...) with classes or attributes already protected by privacy and anti-discrimination law or addressed in fairness- and discrimination-aware analytics. Individuals are linked according to offline identifiers and shared behavioural identity tokens, allowing for predictions and decisions to be taken at a group rather than individual level. This article examines the ethical significance of such ad hoc groups in analytics and argues that the privacy interests of algorithmically assembled groups in inviolate personality must be recognised alongside individual privacy rights. Algorithmically grouped individuals have a collective interest in the creation of information about the group, and actions taken on its behalf. Group privacy is proposed as a third interest to balance alongside individual privacy and social, commercial and epistemic benefits when assessing the ethical acceptability of analytics platforms. (shrink)

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. (shrink)

One of Ian Hacking's earliest publications, this book showcases his early ideas on the central concepts and questions surrounding statistical reasoning. He explores the basic principles of statistical reasoning and tests them, both at a philosophical level and in terms of their practical consequences for statisticians. Presented in a fresh twenty-first-century series livery, and including a specially commissioned preface written by Jan-Willem Romeijn, illuminating its enduring importance and relevance to philosophical enquiry, Hacking's influential and original work has been revived for (...) a new generation of readers. (shrink)

This paper sets out the notion of a current “biopolitical turn of digital capitalism” resulting from the increasing deployment of AI and data analytics technologies in the public sector. With applications of AI-based automated decisions currently shifting from the domain of business to customer (B2C) relations to government to citizen (G2C) relations, a new form of governance arises that operates through “algorithmic social selection”. Moreover, the paper describes how the ethics of AI is at an impasse concerning these larger societal (...) and socioeconomic trends and calls for an ethics of AI that includes, and acts in close alliance with, social and political philosophy. As an example, the problem of Predictive Analytics is debated to make the point that data-driven AI (Machine Learning) is currently one of the main ethical challenges in the ethics of AI. (shrink)

The paper investigates the rise of Big Data in contemporary society. It examines the most prominent epistemological claims made by Big Data proponents, calls attention to the potential socio-political consequences of blind data trust, and proposes a possible way forward. The paper’s main focus is on the interplay between an emerging new empiricism and an increasingly opaque algorithmic environment that challenges democratic demands for transparency and accountability. It concludes that a responsible culture of quantification requires epistemic vigilance as well as (...) a greater awareness of the potential dangers and pitfalls of an ever more data-driven society. (shrink)

KDD (Knowledge Discovery in Databases) confronts us withphenomena that can intuitively be grasped as highly problematic, but arenevertheless difficult to understand and articulate. Many of theseproblems have to do with what I call the ``deindividualization of theperson'': a tendency of judging and treating persons on the basis ofgroup characteristics instead of on their own individual characteristicsand merits. This tendency will be one of the consequences of theproduction and use of group profiles with the help of KDD. Currentprivacy law and regulations, (...) as well as current ethical theoryconcerning privacy, start from too narrow a definition of ``personaldata'' to capture these problems. In this paper, I introduce the notionof ``categorical privacy'' as a starting point for a possible remedy forthe failures of the current conceptions of privacy. I discuss some waysin which the problems relating to group profiles definitely cannot besolved and I suggest a possible way out of these problems. Finally, Isuggest that it may take us a step forward if we would begin to questionthe predominance of privacy norms in the social debate on informationtechnologies and if we would be prepared to introduce normativeprinciples other than privacy rules for the assessment of newinformation technologies. If we do not succeed in articulating theproblems relating to KDD clearly, one day we may find ourselves in asituation where KDD appears to have undermined the methodic andnormative individualism which pervades the mainstream of morality andmoral theory. (shrink)