An online world exists in which businesses have become burdened with managerial and legal duties regarding the seeking of informed consent and the protection of privacy and personal data, while growing public cynicism regarding personal data collection threatens the healthy development of marketing and e-commerce. This research seeks to address such cynicism by assisting organisations to devise ethical consent management processes that consider an individual’s attitudes, their subjective norms and their perceived sense of control during the elicitation of consent. It (...) does so by developing an original conceptual model for online informed consent, argued through logical reasoning, and supported by an illustrative example, which brings together the autonomous authorisation (AA) model of informed consent and the theory of planned behaviour (TPB). Accordingly, it constructs a model for online informed consent, rooted in the ethic of autonomy, which employs behavioural theory to facilitate a mode of consent elicitation that prioritises users’ interests and supports ethical information management and marketing practices. The model also introduces a novel concept, the informed attitude, which must be present for informed consent to be valid. It also reveals that, under certain tolerated conditions, it is possible for informed consent to be provided unwillingly and to remain valid: this has significant ethical, information management and marketing implications. (shrink)

Social Networking Services provide services in return for rights to commercialize users’ personal data. We argue that what makes this transaction permissible is not users’ autonomous consent but the provision of sufficiently valuable opportunities to exchange data for services. We argue that the value of these opportunities should be assessed for both (a) a range of users with different decision-making abilities and (b) third parties. We conclude that regulation should shift from aiming to ensure autonomous consent towards ensuring that users (...) face options that they will use to advance individual and common interests. (shrink)

Online service providers —such as AOL, Facebook, Google, Microsoft, and Twitter—significantly shape the informational environment and influence users’ experiences and interactions within it. There is a general agreement on the centrality of OSPs in information societies, but little consensus about what principles should shape their moral responsibilities and practices. In this article, we analyse the main contributions to the debate on the moral responsibilities of OSPs. By endorsing the method of the levels of abstract, we first analyse the moral responsibilities (...) of OSPs in the web. These concern the management of online information, which includes information filtering, Internet censorship, the circulation of harmful content, and the implementation and fostering of human rights. We then consider the moral responsibilities ascribed to OSPs on the web and focus on the existing legal regulation of access to users’ data. The overall analysis provides an overview of the current state of the debate and highlights two main results. First, topics related to OSPs’ public role—especially their gatekeeping function, their corporate social responsibilities, and their role in implementing and fostering human rights—have acquired increasing relevance in the specialised literature. Second, there is a lack of an ethical framework that can define OSPs’ responsibilities, and provide the fundamental sharable principles necessary to guide OSPs’ conduct within the multicultural and international context in which they operate. This article contributes to the ethical framework necessary to deal with and by endorsing a LoA enabling the definition of the responsibilities of OSPs with respect to the well-being of the infosphere and of the entities inhabiting it. (shrink)

In recent years, insurance companies have begun tracking their customers’ behaviors and price premiums accordingly. Based on the Market-Failures Approach as well as the Justice-Failures Approach, I provide an ethical analysis of the use of tracking technologies in the insurance industry. I focus on the use of telematics in car insurance and on the use of fitness tracking in life insurance. The use of tracking has some important benefits to policyholders and insurers alike: it reduces moral hazard and fraud, increases (...) actuarial fairness, and incentivizes safe behavior. These benefits, however, are outweighed by significant moral objections. First, the use of tracking technologies significantly undermines the fairness of the interaction between insurance companies and policyholders. Specifically, the use of tracking eliminates information asymmetries, but in such a way that favors insurers exclusively. Furthermore, tracked behaviors and the ability to choose to behave safely are highly correlated with other variables such as income. Therefore, tracking-based insurance relies on and exacerbates existing inequalities and injustices, which undermines the benefits that tracking is supposed to introduce. (shrink)

Personal data use is increasingly permeating our everyday life. Informed consent for personal data use is a central instrument for ensuring the protection of personal data. However, current informed consent practices often fail to actually inform data subjects about the use of personal data. This article presents the results of a requirements analysis for informed consent from both a legal and usability perspective, considering the application context of educational assessment. The requirements analysis is based on European Union law and a (...) review of current practices. As the main outcome, the article presents a blueprint which will be the basis for the development of an informed consent template that supports data controllers in establishing an effective and efficient informed consent form. Because the blueprint, and subsequently, the template, distinguishes between legal and usability requirements, it also provides the basis for the mapping of legal requirements in other contexts. (shrink)

In the 60+ years that the modern concept of informed consent has been around, researchers in various fields of practice, especially medical ethics, have developed new models to overcome theoretical and practical problems. While (systematic) literature reviews of such models exist within given fields (e.g., genetic screening), this article breaks ground by analyzing academic literature on consent models across fields. Three electronic research databases (Scopus, Google Scholar, and Web of Science) were searched for publications mentioning informed consent models. The titles, (...) abstracts, and if applicable, full publications were screened and coded. The resulting data on fields, models, and themes were then analyzed. We scanned 300 sources from three databases to find 207 uniquely named consent models, and created a network visualization displaying which models occur primarily in one field, and which models overlap between fields. This analysis identifies trends in the consent debate in different fields, as well as common goals of consent models. The most frequently occurring consent models are identified and defined. The analysis contributes toward a cross-disciplinary “consent design toolkit” and highlights that there are more interrelationships between models and fields than are acknowledged in the literature. Where some models are designed to solve distinctively field-specific issues and are specific to biomedical ethics, some may be adaptable and applicable for other fields including engineering and design. (shrink)

Increasing numbers of decisions about everyday life are made using algorithms. By algorithms we mean predictive models captured from historical data using data mining. Such models often decide prices we pay, select ads we see and news we read online, match job descriptions and candidate CVs, decide who gets a loan, who goes through an extra airport security check, or who gets released on parole. Yet growing evidence suggests that decision making by algorithms may discriminate people, even if the computing (...) process is fair and well-intentioned. This happens due to biased or non-representative learning data in combination with inadvertent modeling procedures. From the regulatory perspective there are two tendencies in relation to this issue: to ensure that data-driven decision making is not discriminatory, and to restrict overall collecting and storing of private data to a necessary minimum. This paper shows that from the computing perspective these two goals are contradictory. We demonstrate empirically and theoretically with standard regression models that in order to make sure that decision models are non-discriminatory, for instance, with respect to race, the sensitive racial information needs to be used in the model building process. Of course, after the model is ready, race should not be required as an input variable for decision making. From the regulatory perspective this has an important implication: collecting sensitive personal data is necessary in order to guarantee fairness of algorithms, and law making needs to find sensible ways to allow using such data in the modeling process. (shrink)

Through the exponential growth in digital devices and computational capabilities, big data technologies are putting pressure upon the boundaries of what can or cannot be considered acceptable from an ethical perspective. Much of the literature on ethical issues related to big data and big data technologies focuses on separate values such as privacy, human dignity, justice or autonomy. More holistic approaches, allowing a more comprehensive view and better balancing of values, usually focus on either a design-based approach, in which it (...) is tried to implement values into the design of new technologies, or an application-based approach, in which it is tried to address the ways in which new technologies are used. Some integrated approaches do exist, but typically are more general in nature. This offers a broad scope of application, but may not always be tailored to the specific nature of big data related ethical issues. In this paper we distil a comprehensive set of ethical values from existing design-based and application-based ethical approaches for new technologies and further focus these values to the context of emerging big data technologies. A total of four value lists were selected for this. The integrated list consists of a total of ten values: human welfare, autonomy, non-maleficence, justice, accountability, trustworthiness, privacy, dignity, solidarity and environmental welfare. Together, this set of values provides a comprehensive and in-depth overview of the values that are to be taken into account for emerging big data technologies. (shrink)

The “privacy paradox” refers to the discrepancy between the concern individuals express for their privacy and the apparently low value they actually assign to it when they readily trade personal information for low-value goods online. In this paper, I argue that the privacy paradox masks a more important paradox: the self-management model of privacy embedded in notice-and-consent pages on websites and other, analogous practices can be readily shown to underprotect privacy, even in the economic terms favored by its advocates. The (...) real question, then, is why privacy self-management occupies such a prominent position in privacy law and regulation. Borrowing from Foucault’s late writings, I argue that this failure to protect privacy is also a success in ethical subject formation, as it actively pushes privacy norms and practices in a neoliberal direction. In other words, privacy self-management isn’t about protecting people’s privacy; it’s about inculcating the idea that privacy is an individual, commodified good that can be traded for other market goods. Along the way, the self-management regime forces privacy into the market, obstructs the functioning of other, more social, understandings of privacy, and occludes the various ways that individuals attempt to resist adopting the market-based view of themselves and their privacy. Throughout, I use the analytics practices of Facebook and social networking sites as a sustained case study of the point. (shrink)