Can We Explain Privacy?

Abstract

Web users want to protect their privacy while sharing content online. This can be done through automated privacy assistants that are capable of taking actions by detecting privacy violations and recommending privacy settings for content that the user intends to share. While these approaches are promising in terms of the accuracy of their privacy decisions, they lack the ability to explain to the end user why certain decisions are being made. In this work, we study how privacy assistants can be enhanced through explanations generated in the context of privacy decisions for the user content. We outline a methodology to create explanations of privacy decisions, discuss core challenges, and show example explanations that are generated by our approach.