Journal of Political Philosophy, EarlyView.

Journal of Political Philosophy, EarlyView.

Governments around the world collect huge amounts of personal data from their citizens for counterterrorist purposes. While mining this data has arguably increased the security of populations, the practices through which these data are currently collected in many countries have been criticised for violating individuals’ rights to privacy. Yet it is not clear what a permissible data collection regime would look like and thus also how we could reform existing regimes to make them morally acceptable. This article explores a number (...) of ways in which we might justify a data collection regime to those affected in spite of the setbacks to their privacy. In contrast to existing justifications, I argue that individuals can be asked to surrender their personal data as a requirement of reciprocity in a cooperative system in which they gain security from others doing likewise. Relying on this justification, though, has significant implications for how we should reform existing data collection regimes. In particular, more stringent limits will need to be placed on the forms which these regimes can legitimately take. (shrink)

Traditional arguments for privacy in public suggest that intentionally public activities, such as political speech, do not deserve privacy protection. In this article, I develop a new argument for the view that surveillance of intentionally public activities should be limited to protect the specific good that this context provides, namely democratic legitimacy. Combining insights from Helen Nissenbaum’s contextualism and Jürgen Habermas’s theory of the public sphere, I argue that strategic surveillance of the public sphere can undermine the capacity of citizens (...) to freely deliberate in public and therefore conflicts with democratic self-determination. (shrink)

Recent disclosures suggest that many governments apply indiscriminate mass surveillance technologies that allow them to capture and store a massive amount of communications data belonging to citizens and non-citizens alike. This article argues that traditional liberal critiques of government surveillance that center on an individual right to privacy cannot completely capture the harm that is caused by such surveillance because they ignore its distinctive political dimension. As a complement to standard liberal approaches to privacy, the article develops a critique of (...) surveillance that focuses on the question of political power in the public sphere. (shrink)

Clients may feel trapped into sharing their private digital data with insurance companies to get a desired insurance product or premium. However, private insurance must collect some data to offer products and premiums appropriate to the client’s level of risk. This situation creates tension between the value of privacy and common insurance business practice. We argue for three main claims: first, coercion to share private data with insurers is pro tanto wrong because it violates the autonomous choice of a privacy-valuing (...) client. Second, we maintain that irrespective of being coerced, the choice of accepting digital surveillance by insurers makes it harder for the client to protect his or her autonomy. The violation of autonomy also makes coercing customers into digital surveillance pro tanto morally wrong. Third, having identified an economically plausible process involving no direct coercion by insurers, leading to the adoption of digital surveillance, we argue that such an outcome generates further threats against autonomy. This threat provides individuals with a pro tanto reason to prevent this process. We highlight the freedom dilemma faced by regulators who aim to prevent this outcome by constraining market freedoms and argue for the need for further moral and empirical research on this question. (shrink)

Nudges can pose serious threats to citizens’ privacy. The essay discusses several examples of nudges that must appear problematic to anyone valuing privacy. The paper also re-draws a well established connection between privacy and autonomy and argues that insofar as nudges incur too great a loss of privacy, they are incompatible with the libertarianism that libertarian paternalism is committed to by virtue of its very name.

In recent years, educational institutions have started using the tools of commercial data analytics in higher education. By gathering information about students as they navigate campus information systems, learning analytics “uses analytic techniques to help target instructional, curricular, and support resources” to examine student learning behaviors and change students’ learning environments. As a result, the information educators and educational institutions have at their disposal is no longer demarcated by course content and assessments, and old boundaries between information used for assessment (...) and information about how students live and work are blurring. Our goal in this paper is to provide a systematic discussion of the ways in which privacy and learning analytics conflict and to provide a framework for understanding those conflicts. -/- We argue that there are five crucial issues about student privacy that we must address in order to ensure that whatever the laudable goals and gains of learning analytics, they are commensurate with respecting students’ privacy and associated rights, including (but not limited to) autonomy interests. First, we argue that we must distinguish among different entities with respect to whom students have, or lack, privacy. Second, we argue that we need clear criteria for what information may justifiably be collected in the name of learning analytics. Third, we need to address whether purported consequences of learning analytics (e.g., better learning outcomes) are justified and what the distributions of those consequences are. Fourth, we argue that regardless of how robust the benefits of learning analytics turn out to be, students have important autonomy interests in how information about them is collected. Finally, we argue that it is an open question whether the goods that justify higher education are advanced by learning analytics, or whether collection of information actually runs counter to those goods. (shrink)