|
Household Internet-of-Things (IoT) devices are intended to collect information in the home and to communicate with each other, to create powerful new applications that support our day-to-day activities. Existing research suggests that users have a difficult time selecting their privacy settings on such devices. The goal of this project is to investigate how, why and when privacy decisions of household IoT users are suboptimal, and to use the insights from this research to create and test a simple single user interface that integrates privacy settings across all devices within a household. This interface will have a flexible set of privacy profiles that fits a wide range of privacy preferences and also helps US companies to comply with EU privacy regulations when they operate in the European market.
Unlike existing privacy research, which assumes that users employ limited but essentially rational decision-making practices, this project aims to understand consumers' actual decision processes. In this way we can improve theories about privacy decision making using part-worth utility mapping and process tracing (including eye-tracking). The results of these efforts are used to develop a data-driven set of privacy profiles that cover the privacy preferences of most users. These profiles are then integrated into a privacy management interface (an open-source contribution to an existing IoT management platform) that does not overload users with information and control, but instead leverages their existing decision processes and avoids their biases.
|
EAGER: Collaborative: PRICE: Using process tracing to improve household IoT users' privacy decisions