Privacy Asymmetries in Digital Public Mobility: Trust and the Perceived Value of Personal Data

As algorithmic platforms increasingly mediate public service delivery, data-driven systems shape how citizens experience trust and privacy while generating digital traces that inform policy decisions. In the context of public mobility, these dynamics manifest through routine interactions with systems that track movement, log behavior, and process personal information, transforming everyday travel into a site of data extraction with policy implications. This study investigates how individuals in Chile interpret and respond to digital transport systems, focusing on their concerns about data privacy, institutional trust, and the value of the data they generate. Drawing on interviews (N = 27) and six focus groups (N = 48), the paper uses the notion of privacy asymmetries to characterize the uneven dispositions users hold across three dimensions: (1) between functionality trust in digital platforms and data privacy concerns; (2) between acceptance of data collection practices by private companies and by the state, and (3) across demographic lines, particularly gender. These asymmetries reflect how historical legacies, political context, and sociodemographic categories shape trust and skepticism toward data use in public systems.