Investigating How Types of Data Associated With Smart Home Devices Influence Privacy Concerns and Perceived Benefits

Domestic appliances and objects are increasingly augmented with data-driven “smart” capabilities. Such Smart Home Devices (SHDs) may receive data directly from users, observe their surroundings with sensors, or infer/predict information through computation. We conducted a scenario-based questionnaire study across multiple regions to investigate user perceptions and expectations regarding the handling of these three types of data associated with SHDs. We systematically varied the scenarios across participants to examine whether the level of ambiguity in the description of an SHD influences user perceptions and expectations regarding its data-handling operations. The study included four SHDs that differed in complexity (two complex and two simple) as a within-subjects treatment. We found that reducing ambiguity in describing SHD operations fosters greater user understanding while increasing privacy concerns about data handling, with notable variations in effects across data types, device complexity, and region. Our findings can be applied to enhance user awareness and control of data handling in the SHD context and inform SHD-specific data protection regulation.