07 September 2017


The short 'Death to the Privacy Calculus?' by Bart P. Knijnenburg, Elaine M. Raybourn, David Cherry, Daricia Wilkinson, Saadhika Sivakumar and Henry Sloan comments 
The “privacy calculus” has been used extensively to describe how people make privacy-related decisions. At the same time, many researchers have found that such decisions are often anything but calculated. More recently, the privacy calculus has been used in service of machine learning approaches to privacy. This position paper discusses the practical and ethical questions that arise from this use of the privacy calculus. ...
Laufer and Wolfe coined the term “calculus of behavior” to refer to the cognitive process that under- lies people’s disclosure decisions. Many researchers have since used the term “privacy calculus” to describe privacy-related decision behaviors, and it has become a well-established concept in privacy research. Other researchers, however, have demonstrated that people rarely take a truly calculative approach to privacy decision making, and are often prone to take mental shortcuts instead. We discuss these departures from rationality, how they come about, and the impact they have on the presumed normative justifications for existing privacy solutions. This will lead us to a relatively new type of privacy solution, user-tailored privacy, which addresses some of the ethical questions raised by existing solutions. User-tailored privacy uses the privacy calculus prescriptively, with the risk/benefit tradeoff serving as an objective function for machine learning algorithms. We will argue that this use of the privacy calculus raises its own set of practical and ethical questions that may cause ethical dilemmas. In outlining these questions, we hope to spark a discussion of the ethical concerns regarding user-tailored privacy