The influence of explanation designs on user understanding differential privacy and making data-sharing decision

Differential privacy (DP) technologies are being promoted by organizations to encourage data sharing, but without a proper understanding of how these technologies work, individuals may make incorrect data-sharing decisions. A design gap exists in effectively communicating the workings of DP technologies, such as Local DP, to users. Our research aimed to fill this gap through the use of an explanatory illustration. We conducted an online survey with 228 participants to assess the impact of different explanation designs on understanding DP and data-sharing decisions. Our study found that the visual explanatory illustration was more effective in assisting individuals to comprehend Local DP’s privacy protection against large organizations as compared to the textual description, with the illustration group exhibiting an increase of 51.4% in their comprehension. The study also found that improved knowledge of privacy-enhancing technologies does not guarantee willingness to share protected data. To prevent misinformed decisions, future research could focus on designing a more effective way of communicating the privacy protections of these technologies to users, building on the insights gained from our study.