Volume 20, Issue 1

Fools rush in. A LEXANDER P OPE , A N E SSAY ON C RITICISM (London, 1711). The full quotation is, “For Fools rush in where Angels fear to tread.” Id . at 66. She who hesitates is lost. Adaptation of the line, “The woman that deliberates is lost.” J OSEPH A DDISON , C ATO : A T RAGEDY , AND S ELECTED E SSAYS 30 (2004). See also O LIVER W ENDALL H OLMES , S R ., T HE A UTOCRAT AT THE B REAKFAST T ABLE 29 (1858) (“The woman who ‘calculates’ is lost.”). American legal realism numbers among the most important theoretical contributions of legal academia to date. Given the movement’s influence, as well as the common centrality of certain key figures, it is surprising that privacy scholarship in the United States has paid next to no attention to the movement. This inattention is unfortunate for several reasons, including that privacy law furnishes rich examples of the indeterminacy thesis — a key concept of American legal realism — and because the interdisciplinary efforts of privacy scholars to explore extra-legal influences on privacy law arguably further the plot of legal realism itself.

The problem of theorizing privacy moves on two levels, the first consisting of an inadequate conceptual vocabulary and the second consisting of an inadequate institutional grammar. Privacy rights are supposed to protect individual subjects, and so conventional ways of understanding privacy are subject-centered, but subject-centered approaches to theorizing privacy also wrestle with deeply embedded contradictions. And privacy’s most enduring institutional failure modes flow from its insistence on placing the individual and individualized control at the center. Strategies for rescuing privacy from irrelevance involve inverting both established ways of talking about privacy rights and established conventions for designing institutions to protect them. In terms of theory, turning privacy inside out entails focusing on the conditions that are needed to produce sufficiently private and privacy-valuing subjects. Institutionally, turning privacy inside out entails focusing on the design, production, and operational practices most likely to instantiate and preserve those conditions .

Alan Westin’s work Privacy and Freedom remains foundational to the field of privacy, and Westin is frequently cited for his definition of privacy as control over personal information. However, Westin’s full definition of privacy is much more complex than this statement, describing four states of privacy (solitude, intimacy, anonymity, and reserve) that one achieves through physical or psychological means. The “claim” of privacy involves negotiating a balance between a desire for disclosure and social participation and a desire for withdrawal into one of the “states” of privacy. Influencing this adjustment process are social norms (and surveillance to enforce social norms), environmental conditions, and the curiosity of others. In this Article, I draw upon this complexity in order to reread Westin’s definition of privacy as a claim of control over personal information and use this rereading to understand how the law should protect and promote privacy in the twenty-first century. I argue that the law should focus on securing meaningful privacy choices rather than on individual control over personal information. Meaningful choice requires that our informational infrastructure, and the social practices that it enables, make states of privacy available for choice along with the means of attaining them. To enable such meaningful individual choice, we need to shift our attention from a focus on individuals to a more systemic focus on our public norms and built infrastructure. Otherwise we risk protecting a narrow understanding of individual control, while ignoring a more general and systematic erosion of privacy .

This Article takes the perspective of law and philosophy, integrating insights from computer science. First, I will argue that in the era of big data analytics we need an understanding of privacy that is capable of protecting what is uncountable, incalculable or incomputable about individual persons. To instigate this new dimension of the right to privacy, I expand previous work on the relational nature of privacy, and the productive indeterminacy of human identity it implies, into an ecological understanding of privacy, taking into account the technological environment that mediates the constitution of human identity. Second, I will investigate how machine learning actually works, detecting a series of design choices that inform the accuracy of the outcome, each entailing trade-offs that determine the relevance, validity and reliability of the algorithm’s accuracy for real life problems. I argue that incomputability does not call for a rejection of machine learning per se but calls for a research design that enables those who will be affected by the algorithms to become involved and to learn how machines learn — resulting in a better understanding of their potential and limitations. A better understanding of the limitations that are inherent in machine learning will deflate some of the eschatological expectations, and provide for better decision-making about whether and if so how to implement machine learning in specific domains or contexts. I will highlight how a reliable research design aligns with purpose limitation as core to its methodological integrity. This Article, then, advocates a practice of “agonistic machine learning” that will contribute to responsible decisions about the integration of data-driven applications into our environments while simultaneously bringing them under the Rule of Law. This should also provide the best means to achieve effective protection against overdetermination of individuals by machine inferences .

Can robots or AIs operating independently of human intervention or oversight diminish our privacy? There are two equal and opposite reactions to this issue. On the robot side, machines are starting to outperform human experts in an increasing array of narrow tasks, including driving, surgery, and medical diagnostics. This is fueling a growing optimism that robots and AIs will exceed humans more generally and spectacularly; some think, to the point where we will have to consider their moral and legal status. On the privacy side, one sees the very opposite: robots and AIs are, in a legal sense, nothing . The received view is that since robots and AIs are neither sentient nor capable of human-level cognition, they are of no consequence to privacy law. This article argues that robots and AIs operating independently of human intervention can and, in some cases, already do diminish our privacy. Epistemic privacy offers a useful analytic framework for understanding the kind of cognizance that gives rise to diminished privacy. Because machines can actuate on the basis of the beliefs they form in ways that affect people’s life chances and opportunities, I argue that they demonstrate the kind of cognizance that definitively implicates privacy. Consequently, I conclude that legal theory and doctrine will have to expand their understanding of privacy relationships to include robots and AIs that meet these epistemic conditions. An increasing number of machines possess epistemic qualities that force us to rethink our understanding of privacy relationships with robots and AIs .

The digital age brings with it novel forms of data flow. As a result, individuals are constantly being monitored while consuming products, services and content. These abilities have given rise to a variety of concerns, which are most often framed using “privacy” and “data protection”-related paradigms. An important, oft-noted yet undertheorized concern is that these dynamics might facilitate the manipulation of subjects; a process in which firms strive to motivate and influence individuals to take specific steps and make particular decisions in a manner considered to be socially unacceptable. That it is important and imperative to battle manipulation carries with it a strong intuitive appeal. Intuition, however, does not always indicate the existence of a sound justification or policy option. For that, a deeper analytic and academic discussion is called for . This Article begins by emphasizing the importance of addressing the manipulation-based argument, which derives from several crucial problems and flaws in the legal and policy setting currently striving to meet the challenges of the digital age. Next, the Article examines whether the manipulation-based concerns are sustainable, or are merely a visceral response to changing technologies which cannot be provided with substantial analytical backing. Here the Article details the reasons for striving to block manipulative conduct and, on the other hand, reasons why legal intervention should be, in the best case, limited. The Article concludes with some general implications of this discussion for the broader themes and future directions of privacy law, while trying to ascertain whether the rise of the manipulation-based discourse will lead to information privacy’s expansion or perhaps its demise .

The power exercised by technology companies is attracting the attention of policymakers, regulatory bodies and the general public. This power can be categorized in several ways, ranging from the “soft power” of technology companies to influence public policy agendas to the “market power” they may wield to exclude equally efficient competitors from the marketplace. This Article is concerned with the “data power” exercised by technology companies occupying strategic positions in the digital ecosystem. This data power is a multifaceted power that may overlap with economic (market) power but primarily entails the power to profile and the power to influence opinion formation. While the current legal framework for data protection and privacy in the EU imposes constraints on personal data processing by technology companies, it ostensibly does so without regard to whether or not they have “data power.” This Article probes this assumption. It argues that although this legal framework does not explicitly impose additional legal responsibilities on entities with “data power,” it provides a clear normative indication to do so. The volume and variety of data and the reach of data-processing operations seem to be relevant when assessing both the extent of obligations on technology companies and the impact of data processing on individual rights. The Article suggests that this finding provides the normative foundation for the imposition of a “special responsibility” on such firms, analogous to the “special responsibility” imposed by competition law on dominant companies with market power. What such a “special responsibility” might entail in practice will be briefly outlined and relevant questions for future research will be identified.

According to the theory of contextual integrity (CI), privacy norms prescribe information flows with reference to five parameters — sender, recipient, subject, information type, and transmission principle. Because privacy is grasped contextually (e.g., health, education, civic life, etc.), the values of these parameters range over contextually meaningful ontologies — of information types (or topics) and actors (subjects, senders, and recipients), in contextually defined capacities. As an alternative to predominant approaches to privacy, which were ineffective against novel information practices enabled by IT, CI was able both to pinpoint sources of disruption and provide grounds for either accepting or rejecting them. Mounting challenges from a burgeoning array of networked, sensor-enabled devices (IoT) and data-ravenous machine learning systems, similar in form though magnified in scope, call for renewed attention to theory. This Article introduces the metaphor of a data (food) chain to capture the nature of these challenges. With motion up the chain, where data of higher order is inferred from lower-order data, the crucial question is whether privacy norms governing lower-order data are sufficient for the inferred higher-order data. While CI has a response to this question, a greater challenge comes from data primitives, such as digital impulses of mouse clicks, motion detectors, and bare GPS coordinates, because they appear to have no meaning. Absent a semantics, they escape CI’s privacy norms entirely .

Data protection law has a linear logic, in that it purports to trace the lifecycle of personal data from creation to collection, processing, transfer, and ultimately its demise, and to regulate each step so as to promote the data subject’s control thereof. Big data defies this linear logic, in that it decontextualizes data from its original environment and conducts an algorithmic nonlinear mix, match, and mine analysis. Applying data protection law to the processing of big data does not work well, to say the least . This Article examines the case of big medical data. A survey of emerging research practices indicates that studies either ignore data protection law altogether or assume an ex post position, namely that because they are conducted after the data has already been created in the course of providing medical care, and they use de-identified data, they go under the radar of data protection law. These studies focus on the end-point of the lifecycle of big data: if sufficiently anonymous at publication, the previous steps are overlooked, on the claim that they enjoy immunity. I argue that this answer is too crude. To portray data protection law in its best light, we should view it as a process-based attempt to equip data subjects with some power to control personal data about them, in all phases of data processing . Such control reflects the underlying justification of data protection law as an implementation of human dignity. The process-based approach fits current legal practices and is justified by reflecting dignitarian conceptions of informational privacy .

In the European Union, the General Data Protection Regulation (GDPR) provides comprehensive rules for the processing of personal data. In addition, the EU lawmaker intends to adopt specific rules to protect confidentiality of communications, in a separate ePrivacy Regulation. Some have argued that there is no need for such additional rules for communications confidentiality . This Article discusses the protection of the right to confidentiality of communications in Europe. We look at the right’s origins to assess the rationale for protecting it. We also analyze how the right is currently protected under the European Convention on Human Rights and under EU law . We show that at its core the right to communications confidentiality protects three individual and collective values: privacy, freedom of expression, and trust in communication services. The right aims to ensure that individuals and organizations can safely entrust communication to service providers. Initially, the right protected only postal letters, but it has gradually developed into a strong safeguard for the protection of confidentiality of communications, regardless of the technology used . Hence, the right does not merely serve individual privacy interests, but also other more collective interests that are crucial for the functioning of our information society. We conclude that separate EU rules to protect communications confidentiality, next to the GDPR, are justified and necessary .

The creation of new search powers in the Canadian Anti-Terrorism Act post-9/11 to make citizens more transparent to state surveillance was less a new phenomenon than an extension of preexisting tendencies to make citizens transparent to the state, so the risks they pose can be efficiently managed. However, 9/11 brought about a shift in the ways in which the Supreme Court of Canada talked about terrorism; terrorism was no longer placed on a continuum of criminal activity but was elevated to a threat to Canadian values as a whole. I argue that, paradoxically, this shift reconnected the Court to earlier discourses about privacy as an essential element of democratic governance and reinvigorated narratives around the importance of the public-private boundary to democratic relationships by situating privacy within narratives informed by social memory. From this perspective, privacy can be conceptualized as a status claim: as citizens, we are entitled to privacy because privacy is the boundary that creates right relationships between citizens and between citizens and the state. This avoids pitting privacy as an individual right against societal interests in transparency because it more fully actualizes Priscilla Regan’s call to theorize the value of privacy as a public good central to liberal democratic governance. This conception also reconnects Alan Westin’s original understanding of privacy as an element of liberal democracy to the sociological research he drew on, enriching the liberal conception of privacy by locating it in the intersubjective communication of cultural actors living in community .

Privacy and technology clash in the courts. I elaborate the example of Puttaswamy v Union of India (2017), an example from the High Court of India, whose sweeping and inclusive jurisprudential style raises starkly the question of the influence that academic philosophers and other scholars have over how legitimate societal interests in exploiting information technology and protecting personal privacy are “balanced” by the courts. Philosophers will be satisfied to see that their theories are acknowledged in a landmark national decision finding that India’s 1.3 billion people have a constitutional, fundamental right to privacy that constrains a challenged government biometric identification system. Some scholars will appreciate the inclusive definition of privacy, which included decisional privacy, combined with the treatment of privacy as a paramount human good meriting the protection of fundamental rights. But some academic philosophers are potentially disappointed that the Court synthesizes rather than differentiates among their competing theories, concepts, and definitions, and, in the end, relies upon liberal Enlightenment ideals that some scholars have argued are singularly ill-suited for the twenty-first century .