Enhancing Transparency and Control when Drawing Data-Driven Inferences about Individuals

26 Jun 2016Daizhuo ChenSamuel P. FraibergerRobert MoaklerFoster Provost

Recent studies have shown that information disclosed on social network sites (such as Facebook) can be used to predict personal characteristics with surprisingly high accuracy. In this paper we examine a method to give online users transparency into why certain inferences are made about them by statistical models, and control to inhibit those inferences by hiding ("cloaking") certain personal information from inference... (read more)

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