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Smart devices, such as smart speakers, are becoming ubiquitous, and usersexpect these devices to act in accordance with their preferences. Inparticular, since these devices gather and manage personal data, users expectthem to adhere to their privacy preferences. However, the current approach ofgathering these preferences consists in asking the users directly, whichusually triggers automatic responses failing to capture their true preferences.In response, in this paper we present a collaborative filtering approach topredict user preferences as norms. These preference predictions can be readilyadopted or can serve to assist users in determining their own preferences.Using a dataset of privacy preferences of smart assistant users, we test theaccuracy of our predictions.

Predicting Privacy Preferences for Smart Devices as Norms