Privacy preferences in automotive data collection

Abstract

Connected cars are becoming commonplace, creating vast volumes of data that may contain or reveal information about drivers. It is imperative to understand drivers' perspectives on such data being collected and used by car manufacturers. Applying the Human-Data Interaction (HDI) framework - which centres the user and their experience - to this context, we conducted semi-structured interviews with 15 drivers. Interview transcripts revealed issues with understanding of car data (Legibility) and drivers’ sense of control over automotive data (Agency), across different circumstances (Negotiability). Our findings suggest that car manufacturers should enable learning, access, and control over car data via the mobile app in a coordinated fashion, as the privacy preferences of drivers are often based on perceived benefit or threat resulting from data collection. The ability to set data-sharing preferences in a time- and location- sensitive manner can help drivers navigate data sharing consent based on circumstances. These findings have implications for the consent procedures in modern cars as well as for the development of data-sharing programmes aimed at creation of climate-smart cities.

Keywords

• Connected cars
• Privacy
• Automotive data
• Human-data interaction
• Data protection
• Data disclosure behaviour