Below are some articles recently uploaded to SSRN. Clicking on the links will take you to SSRN where you can download the full paper or book.
Drones and Privacy Governance
Gregory S. McNeal
Pepperdine University School of Law ; Pepperdine University – School of Public Policy
Abstract:
Unmanned systems (drones) and other technological innovations raise serious questions about modern conceptions of privacy. This paper examines the constitutional doctrine related to aerial surveillance and technology, and finds that current doctrine is unlikely to prevent the use of unmanned systems. The paper next addresses calls to create a statutory requirement that will subject the use of unmanned systems to the warrant requirement. These calls are rejected because they fail to protect privacy, while unnecessarily hampering legitimate law enforcement efforts. To best protect privacy, the paper suggests various mechanisms of democratically centered privacy governance, and a regulatory regime to govern the use of unmanned systems. The paper’s appendix includes a model bill appropriate for adoption by cities, states, and the federal government. The bill outlines the various privacy governance measures discussed in the body of the paper.
Law, Dissonance and Remote Computer Searches
Susan W. Brenner
University of Dayton – School of Law
Abstract:
This article examines the conflict – the dissonance – that arises when law enforcement officers from one jurisdiction remotely search a computer that is physically located in another jurisdiction. It reviews the current status of remote computer searches in Europe, noting that such searches are legal under United Kingdom law but are, for most purposes, outlawed by German law.
The article then explains that because U.S. state supreme courts have used their constitutions to impose search and seizure requirements that exceed those of the Fourth Amendment, similar dissonance has arisen between U.S. states. It uses this domestic dissonance to analyze the issues transnational searches are likely to create and to consider how those issues might be resolved.
Surveillance and the Individual’s Expectation of Privacy Under the Fourth Amendment
Eoin Carolan
University College Dublin (UCD) – School of Law
Abstract:
This piece examines the US Supreme Court’s decision in US v Jones 565 U.S. (2012) with a particular focus on the question of what the decision might mean for the Court’s future attitude to technologies that facilitate privacy intrusion. Comparisons are drawn between the evolution of Fourth Amendment jurisprudence and developments on privacy protection in Europe, especially in the United Kingdom and under Article 8 of the European Convention on Human Rights.
Open Book: The Failed Promise of Information Privacy in America
James P. Nehf
Indiana University Robert H. McKinney School of Law
Abstract:
With financial and other personal information about us in countless databases, and with companies such as Facebook and Google collecting data about their users to drive profits and satisfy expectations of shareholders, there is a pervasive concern that we have little control over access to potentially harmful uses of that information. Moreover, many consumers believe that little can be done to address the problem except to give out as little information as possible and try our best to monitor our credit reports and financial accounts in an effort to detect unexpected activity if it occurs. By not enacting strong information privacy laws in the non-governmental sector, the U.S. Congress and the fifty states have effectively defaulted to a market-based model of privacy protection that relies heavily on individual self-policing and market incentives as the primary means of information control. A self-policing privacy protection model could be effective if a market for information privacy were possible — if well informed individuals could shop their privacy preferences effectively. This book-length paper examines the reasons why this is highly unlikely and why privacy laws in the United States (or the lack thereof) will not protect legitimate consumer interests in the years to come. Part 1 shows why information privacy is a social or societal value and not just an individual concern. Part 2 examines in more detail why individualist, market approaches to privacy protection are destined to fail. Part 3 continues this theme and examines research in behavioral sciences about how consumers make decisions in market transactions. Part 4 concludes by critiquing the “new” privacy framework released by the Federal Trade Commission. While the framework contains hopeful rhetoric calling for greater emphasis on societal solutions to privacy concerns, most of the framework continues to rely heavily on individual notice and choice in transactions that involve exchanges of personal information.
Online Advertising and Privacy
Alexandre De Corniere, Oxford University and
Romain De Nijs, University of California, Berkeley – Haas School of Business and Ecole des Ponts ParisTech
Abstract:
An online platform makes a profit by auctioning an advertising slot that appears whenever a consumer visits its website. Several firms compete in the auction, and consumers differ in their preferences. Prior to the auction, the platform gathers data which is statistically correlated with consumers’ tastes for products. We study the implications of the platform’s decision to allow potential advertisers to access the data about consumers’ characteristics before they bid. On top of the familiar trade-off between rent extraction and efficiency, we identify a new trade-off: the disclosure of information leads to a better matching between firms and consumers, but results in a higher equilibrium price on the product market. We find that the equilibrium price is an increasing function of the number of firms. As the number of firms becomes large, it is always profitable for the platform to disclose the information, but this need not be efficient, because of the distortion caused by the higher prices. When the quality of the match represents vertical shifts in the demand function, we provide conditions under which disclosure is optimal.