This paper critically examines the extent to which health promoting wearable technologies can provide people with greater autonomy over their health. These devices are frequently presented as a means of expanding the possibilities people have for making healthier decisions and living healthier lives. We accept that by collecting, monitoring, analysing and displaying biomedical data, and by helping to underpin motivation, wearable technologies can support autonomy over health. However, we argue that their contribution in this regard is limited and that—even with (...) respect to their ‘autonomy enhancing’ potential—these devices may deliver costs as well as benefits. We proceed by rehearsing the distinction that can be drawn between procedural autonomy and substantive-relational autonomy. While the information provided by wearable technologies may support deliberation and decision-making, in isolation these technologies do little to provide substantive opportunities to act and achieve better health. As a consequence, wearable technologies risk generating burdens of anxiety and stigma for their users and reproducing existing health inequalities. We then reexamine the extent to which wearable technologies actually support autonomous deliberation. We argue that wearable technologies that subject their users to biomedical and consumerist epistemologies, norms and values also risk undermining processes of genuinely autonomous deliberation. (shrink)

The capacity to collect and analyse data is growing exponentially. Referred to as ‘Big Data’, this scientific, social and technological trend has helped create destabilising amounts of information, which can challenge accepted social and ethical norms. Big Data remains a fuzzy idea, emerging across social, scientific, and business contexts sometimes seemingly related only by the gigantic size of the datasets being considered. As is often the case with the cutting edge of scientific and technological progress, understanding of the ethical implications (...) of Big Data lags behind. In order to bridge such a gap, this article systematically and comprehensively analyses academic literature concerning the ethical implications of Big Data, providing a watershed for future ethical investigations and regulations. Particular attention is paid to biomedical Big Data due to the inherent sensitivity of medical information. By means of a meta-analysis of the literature, a thematic narrative is provided to guide ethicists, data scientists, regulators and other stakeholders through what is already known or hypothesised about the ethical risks of this emerging and innovative phenomenon. Five key areas of concern are identified: informed consent, privacy, ownership, epistemology and objectivity, and ‘Big Data Divides’ created between those who have or lack the necessary resources to analyse increasingly large datasets. Critical gaps in the treatment of these themes are identified with suggestions for future research. Six additional areas of concern are then suggested which, although related have not yet attracted extensive debate in the existing literature. It is argued that they will require much closer scrutiny in the immediate future: the dangers of ignoring group-level ethical harms; the importance of epistemology in assessing the ethics of Big Data; the changing nature of fiduciary relationships that become increasingly data saturated; the need to distinguish between ‘academic’ and ‘commercial’ Big Data practices in terms of potential harm to data subjects; future problems with ownership of intellectual property generated from analysis of aggregated datasets; and the difficulty of providing meaningful access rights to individual data subjects that lack necessary resources. Considered together, these eleven themes provide a thorough critical framework to guide ethical assessment and governance of emerging Big Data practices. (shrink)

This paper critically engages with new self-tracking technologies. In particular, it focuses on a conceptual tension between the idea that disclosing personal information increases one’s autonomy and the idea that informational privacy is a condition for autonomous personhood. I argue that while self-tracking may sometimes prove to be an adequate method to shed light on particular aspects of oneself and can be used to strengthen one’s autonomy, self-tracking technologies often cancel out these benefits by exposing too much about oneself to (...) an unspecified audience, thus undermining the informational privacy boundaries necessary for living an autonomous life. (shrink)

In the Formula of Humanity, Kant embraces the principle that it is wrong for us to treat others merely as means. For contemporary Kantian ethicists, this Mere Means Principle plays the role of a moral constraint: it limits what we may do, even in the service of promoting the overall good. But substantive interpretations of the principle generate implausible results in relatively ordinary cases. On one interpretation, for example, you treat your opponent in a tennis tournament merely as a means (...) and thus wrongly when you try, through defeating him, to win first place. The article aims to develop a reconstruction of the Mere Means Principle that has more plausible implications than do rival reconstructions. It sets out a sufficient condition for an agent's treating another merely as a means. This condition is intended to be Kantian, but not necessarily one that Kant endorses. (shrink)

This paper aims to provide an overview of surveillance theories and concepts that can help to understand and debate surveillance in its many forms. As scholars from an increasingly wide range of disciplines are discussing surveillance, this literature review can offer much-needed common ground for the debate. We structure surveillance theory in three roughly chronological/thematic phases. The first two conceptualise surveillance through comprehensive theoretical frameworks which are elaborated in the third phase. The first phase, featuring Bentham and Foucault, offers architectural (...) theories of surveillance, where surveillance is often physical and spatial, involving centralised mechanisms of watching over subjects. Panoptic structures function as architectures of power, not only directly but also through disciplining of the watched subjects. The second phase offers infrastructural theories of surveillance, where surveillance is networked and relies primarily on digital rather than physical technologies. It involves distributed forms of watching over people, with increasing distance to the watched and often dealing with data doubles rather than physical persons. Deleuze, Haggerty and Ericson, and Zuboff develop different theoretical frameworks than panopticism to conceptualise the power play involved in networked surveillance. The third phase of scholarship refines, combines or extends the main conceptual frameworks developed earlier. Surveillance theory branches out to conceptualise surveillance through concepts such as dataveillance, access control, social sorting, peer-to-peer surveillance and resistance. With the datafication of society, surveillance combines the physical with the digital, government with corporate surveillance and top-down with self-surveillance. (shrink)

One of the most noticeable trends in recent years has been the increasing reliance of public decision-making processes on algorithms, i.e. computer-programmed step-by-step instructions for taking a given set of inputs and producing an output. The question raised by this article is whether the rise of such algorithmic governance creates problems for the moral or political legitimacy of our public decision-making processes. Ignoring common concerns with data protection and privacy, it is argued that algorithmic governance does pose a significant threat (...) to the legitimacy of such processes. Modelling my argument on Estlund’s threat of epistocracy, I call this the ‘threat of algocracy’. The article clarifies the nature of this threat and addresses two possible solutions. It is argued that neither solution is likely to be successful, at least not without risking many other things we value about social decision-making. The result is a somewhat pessimistic conclusion in which we confront the possibility that we are creating decision-making processes that constrain and limit opportunities for human participation. (shrink)

This article considers the issue of opacity as a problem for socially consequential mechanisms of classification and ranking, such as spam filters, credit card fraud detection, search engines, news trends, market segmentation and advertising, insurance or loan qualification, and credit scoring. These mechanisms of classification all frequently rely on computational algorithms, and in many cases on machine learning algorithms to do this work. In this article, I draw a distinction between three forms of opacity: opacity as intentional corporate or state (...) secrecy, opacity as technical illiteracy, and an opacity that arises from the characteristics of machine learning algorithms and the scale required to apply them usefully. The analysis in this article gets inside the algorithms themselves. I cite existing literatures in computer science, known industry practices, and do some testing and manipulation of code as a form of lightweight code audit. I argue that recognizing the distinct forms of opacity that may be coming into play in a given application is a key to determining which of a variety of technical and non-technical solutions could help to prevent harm. (shrink)

This paper analyzes ethical aspects of the new paradigm of Ambient Intelligence, which is a combination of Ubiquitous Computing and Intelligent User Interfaces (IUI’s). After an introduction to the approach, two key ethical dimensions will be analyzed: freedom and privacy. It is argued that Ambient Intelligence, though often designed to enhance freedom and control, has the potential to limit freedom and autonomy as well. Ambient Intelligence also harbors great privacy risks, and these are explored as well.

'Anita L. Allen breaks new ground...A stunning indictment of women's status in contemporary society, her book provides vital original scholarly research and insight.' |s-NEW DIRECTIONS FOR WOMEN.

This new book by Beate Rossler is a work of real quality and originality on an extremely topical issue: the issue of privacy and the relations between the private and the public. Rossler investigates the reasons why we value privacy and why we ought to value it. In the context of modern, liberal societies, Rossler develops a theory of the private which links privacy and autonomy in a constitutive way: privacy is a necessary condition to lead an autonomous life. The (...) book develops a theory of freedom and autonomy which sees the ability to pose the "practical question" of how one wants to live, of what a person strives to be, at the centre of the modern idea of autonomy. The question of privacy is emerging as an increasingly important topic in social and political theory and is central to many current debates in law, the media and politics. The Value of Privacy will be widely recognised to be a classic contribution to the subject. (shrink)

Since approval of the EU General Data Protection Regulation (GDPR) in 2016, it has been widely and repeatedly claimed that the GDPR will legally mandate a ‘right to explanation’ of all decisions made by automated or artificially intelligent algorithmic systems. This right to explanation is viewed as an ideal mechanism to enhance the accountability and transparency of automated decision-making. However, there are several reasons to doubt both the legal existence and the feasibility of such a right. In contrast to the (...) right to explanation of specific automated decisions claimed elsewhere, the GDPR only mandates that data subjects receive meaningful, but properly limited, information (Articles 13-15) about the logic involved, as well as the significance and the envisaged consequences of automated decision-making systems, what we term a ‘right to be informed’. Further, the ambiguity and limited scope of the ‘right not to be subject to automated decision-making’ contained in Article 22 (from which the alleged ‘right to explanation’ stems) raises questions over the protection actually afforded to data subjects. These problems show that the GDPR lacks precise language as well as explicit and well-defined rights and safeguards against automated decision-making, and therefore runs the risk of being toothless. We propose a number of legislative and policy steps that, if taken, may improve the transparency and accountability of automated decision-making when the GDPR comes into force in 2018. (shrink)