Big data privacy: The datafication of personal information
本文提出大数据时代需要从隐私定义转向隐私模型，并引入新的“数位化模型”，即通过预测分析从已有数据中推断新个人信息，从而补充传统的监视模型和捕获模型。
In the age of big data we need to think differently about privacy. We need to shift our thinking from definitions of privacy (characteristics of privacy) to models of privacy (how privacy works). Moreover, in addition to the existing models of privacy—the surveillance model and capture model—we need to also consider a new model: the datafication model presented in this article, wherein new personal information is deduced by employing predictive analytics on already-gathered data. These three models of privacy supplement each other; they are not competing understandings of privacy. This broadened approach will take our thinking beyond current preoccupation with whether or not individuals’ consent was secured for data collection to privacy issues arising from the development of new information on individuals' likely behavior through analysis of already collected data—this new information can violate privacy but does not call for consent.