Towards trustworthy personal assistants for privacy
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Date
2023
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Thesis (Ph.D.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2023.
Abstract
Many software systems, such as online social networks, enable their users to share information about themselves online. However, users worry about the privacy implications of sharing content. It’s a tedious process to make privacy decisions and it makes managing privacy difficult. Recent approaches to help users manage their privacy involve building personal assistants that can recommend whether a user’s content is private or not. However, privacy’s ambiguous nature and difficulties in explaining assistants’ decision-making are challenges hampering users’ trust in these systems and therefore also widespread user adoption. In this dissertation we design trustworthy privacy assistants that can help tackle both challenges. We first propose a personal assistant called PURE that integrates machine learning to make predictions on whether a user would identify an image as private or not. An important characteristic of PURE is its ability to model uncertainty in its decisions explicitly. When uncertainty is high, no prediction is made and the decision is delegated to the user. By factoring in user’s own understanding of privacy, PURE is able to personalize its recommendations. A second crucial factor in fostering trust in personal assistants is their ability to explain their decision-making processes. Our second assistant PEAK is capable of generating such explanations for its recommendations, using latent topics and predefined explanation categories to do so. A user study shows users find PEAK’s explanations useful and easy to understand. Additionally, privacy assistants can use the explanations to improve their own decision-making, with the incorporation of PEAK into PURE resulting in less uncertain images delegated to the user whilst model performance is not compromised. Overall, our work makes an important contribution towards the development of trustworthy personal assistants capable of preserving users’ privacy. NOTE Keywords : Personal information management, Artificial intelligence, Right of privacy and its protection, Breach of confidentiality, Handling uncertainty, Explainable artificial intelligence.