To date, many important threads of information privacy research have developed, but these threads have not been woven together into a cohesive fabric. This paper provides an interdisciplinary review of privacy-related research in order to enable a more cohesive treatment. With a sample of 320 privacy articles and 128 books and book sections, we classify previous literature in two ways: (1) using an ethics-based nomenclature of normative, purely descriptive, and empirically descriptive, and (2) based on their level of analysis: individual, group, organizational, and societal.

Based upon our analyses via these two classification approaches, we identify three major areas in which previous research contributions reside: the conceptualization of information privacy, the relationship between information privacy and other constructs, and the contextual nature of these relationships.

As we consider these major areas, we draw three overarching conclusions. First, there are many theoretical developments in the body of normative and purely descriptive studies that have not been addressed in empirical research on privacy. Rigorous studies that either trace processes associated with, or test implied assertions from, these value-laden arguments could add great value. Second, some of the levels of analysis have received less attention in certain contexts than have others in the research to date. Future empirical studies-both positivist and interpretive--could profitably be targeted to these under-researched levels of analysis. Third, positivist empirical studies will add the greatest value if they focus on antecedents to privacy concerns and on actual outcomes. In that light, we recommend that researchers be alert to an overarching macro model that we term APCO (Antecedents → Privacy Concerns → Outcomes).

/pdf/information-privacy-research-an-interdisciplinary-review-3ozmykcimw.pdf

Information privacy research: an interdisciplinary review

Delete looks at the surprising phenomenon of perfect remembering in the digital age, and reveals why we must reintroduce our capacity to forget. Digital technology empowers us as never before, yet it has unforeseen consequences as well. Potentially humiliating content on Facebook is enshrined in cyberspace for future employers to see. Google remembers everything we've searched for and when. The digital realm remembers what is sometimes better forgotten, and this has profound implications for us all. In Delete, Viktor Mayer-Schnberger traces the important role that forgetting has played throughout human history, from the ability to make sound decisions unencumbered by the past to the possibility of second chances. The written word made it possible for humans to remember across generations and time, yet now digital technology and global networks are overriding our natural ability to forget--the past is ever present, ready to be called up at the click of a mouse. Mayer-Schnberger examines the technology that's facilitating the end of forgetting--digitization, cheap storage and easy retrieval, global access, and increasingly powerful software--and describes the dangers of everlasting digital memory, whether it's outdated information taken out of context or compromising photos the Web won't let us forget. He explains why information privacy rights and other fixes can't help us, and proposes an ingeniously simple solution--expiration dates on information--that may. Delete is an eye-opening book that will help us remember how to forget in the digital age.

Delete: The Virtue of Forgetting in the Digital Age

Principles of emergency planning and management , Principles of emergency planning and management , کتابخانه الکترونیک و دیجیتال - آذرسا

Principles of Emergency Planning and Management

Recent media revelations have demonstrated the extent of third-party tracking and monitoring online, much of it spurred by data aggregation, profiling, and selective targeting. How to protect privacy online is a frequent question in public discourse and has reignited the interest of government actors. In the United States, notice-and-consent remains the fallback approach in online privacy policies, despite its weaknesses. This essay presents an alternative approach, rooted in the theory of contextual integrity. Proposals to improve and fortify notice-and-consent, such as clearer privacy policies and fairer information practices, will not overcome a fundamental flaw in the model, namely, its assumption that individuals can understand all facts relevant to true choice at the moment of pair-wise contracting between individuals and data gatherers. Instead, we must articulate a backdrop of context-specific substantive norms that constrain what information websites can collect, with whom they can share it, and under what conditions it can be shared. In developing this approach, the paper warns that the current bias in conceiving of the Net as a predominantly commercial enterprise seriously limits the privacy agenda.

A Contextual Approach to Privacy Online

Predictive policing is the use of analytical techniques to identify targets for police intervention with the goal of preventing crime, solving past crimes, or identifying potential offenders and victims. These tools are not a substitute for integrated approaches to policing, nor are they a crystal ball. This guide assesses some of the most promising technical tools and tactical approaches for acting on predictions in an effective way.

/pdf/predictive-policing-the-role-of-crime-forecasting-in-law-184zvfaw0n.pdf

Predictive Policing: The Role of Crime Forecasting in Law Enforcement Operations

Data sharing models designed to facilitate global business provide insights for improving transborder genomic data sharing. We argue that a flexible, externally endorsed, multilateral arrangement, combined with an objective third-party assurance mechanism, can effectively balance privacy with the need to share genomic data globally.

/pdf/building-a-data-sharing-model-for-global-genomic-research-hn03jsl7nx.pdf

Building a data sharing model for global genomic research

The article examines the government's growing appetite for collecting personal data. Often justified on the basis of protecting national security, government data mining programs sweep up data collected through hundreds of regulatory and administrative programs, and combine them with huge datasets obtained from industry. The result is an aggregation of personal data - the "digital footprints" of individual lives - never before seen. These data warehouses are then used to determine who can work and participate in Social Security programs, who can board airplanes and enter government buildings, and who is likely to pose a threat in the future, even though they have done nothing wrong to date. The article describes the extraordinary volume and variety of personal data to which the government has routine access, directly and through industry, and examines the absence of any meaningful limits on that access. So-called privacy statutes are often so outdated and inadequate that they fail to limit the government's access to our most personal data, or they have been amended in the post-9/11 world to reduce those limits. And the Fourth Amendment, the primary constitutional guarantee of individual privacy, has been interpreted by the Supreme Court to not apply to routine data collection, accessing data from third parties, or sharing data, even if illegally gathered. The result is not only that individual privacy goes unprotected, but that national security is compromised because it is increasingly based on data mining initiatives that are untested, ill focused, and rely on inaccurate or incomplete data. These shortcomings, and the urgent need for Congress to act to address them, have been widely recognized by numerous public and private commissions, but largely ignored by members of Congress - republicans and democrats alike. The article concludes that there is wide agreement about both the need to restore some limits on the government's use of personal data and the form that those limits should take. The problem is the unwillingness - or inability - of Congress to act.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID1151435_code286645.pdf?abstractid=1151435&mirid=1&type=2

Government Data Mining:The Need for a Legal Framework

/pdf/data-protection-principles-for-the-21st-century-2nt86x2hl8.pdf

Data Protection Principles for the 21st Century

/pdf/the-eu-data-protection-directive-information-privacy-and-the-1gsrozsugy.pdf

The EU Data Protection Directive, Information Privacy, and the Public Interest

/pdf/machine-learning-with-personal-data-is-data-protection-law-484ty5wsw8.pdf

Fred H. Cate

Papers

Building a data sharing model for global genomic research

Government Data Mining:The Need for a Legal Framework

Data Protection Principles for the 21st Century

The EU Data Protection Directive, Information Privacy, and the Public Interest

Machine learning with personal data: is data protection law smart enough to meet the challenge?