Privacy-Accuracy Consideration in Devices That Collect Sensor-Based Information

Accurately tailored support such as advice or assistance can increase user satisfaction from interactions with smart devices; however, in order to achieve high accuracy, the device must obtain and exploit private user data and thus confidential user information might be jeopardized. We provide an analysis of this privacy-accuracy trade-off. We assume two positive correlations: a user's utility from a device is positively correlated with the user's privacy risk and also with the quality of the advice or assistance offered by the device. The extent of the privacy risk is unknown to the user. Thus, privacy concerned users might choose not to interact with devices they deem as unsafe. We suggest that at the first period of usage, the device should choose not to employ the full capability of its advice or assistance capabilities, since this may intimidate users from adopting it. Using three analytical propositions, we further offer an optimal policy for smart device exploitation of private data for the purpose of interactions with users.