Sensor-enabled wearable devices and smartphones collect data about users’ movements, location, and private spaces and activities. As with many ubiquitous computing technologies, this data collection happens in the background and appears “seamless” or invisible to the user. Despite this, users are still expected to make informed choices regarding consent to data collection. Folk theories are sets of beliefs and understandings that arise informally and guide decision-making. To investigate folk theories regarding sensor data collection that might guide privacy self-management decisions, we conducted qualitative free list activities with 30 activity tracker users in which we asked them to list “information that an activity tracker knows”. We found that folk theories regarding the data that activity trackers collect depend on interactions between the users and their trackers that provide visibility into dependencies among data types, evidence about what trackers are able to record, and feedback that inspires speculation about how trackers work. Our findings suggest opportunities for designing interfaces that intentionally support the development of folk theories about how sensor data are produced and how they might be used, which may enable users to make more informed privacy self-management decisions.

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