King J

Anna-Maria Gueorguieva, Jennifer King, Apoorva Panidapu et al.

California's consumer privacy law is widely deemed to be the most protected in the United States, one of the few to expressly regulate third party entities that buy and sell consumer data (data brokers). We offer the first empirical assessment of data broker compliance with the 2018 California Consumer Privacy Act (CCPA) and the 2023 Delete Act, which requires data brokers to register with the state and report consumer rights requests metrics annually. First, we demonstrate that only 9% of 522 registered data brokers were fully compliant with transparency requirements after the Delete Act took effect, although we do identify slight improvements over time. Second, we descriptively characterize wide heterogeneity across data brokers in the volume of consumer rights requests received, with many reporting none. We bring in external business data to explore correlates associated with this variation, a challenge given the general lack of opacity into broker business practices. Third, in an audit of a sample of 250 data brokers' consumers request processes, we find that 43% make it impossible for consumers to exercise all privacy rights and 64% introduce at least one design feature that creates substantial friction into the consumer request process. Last, we show how these deficiencies stem from the decentralization of compliance decisions to brokers themselves, enforcement limitations, and regulatory ambiguity. We articulate reforms that could improve consumer privacy, transparency in broker practices, and compliance with these laws.

Tianshi Li, Jackie, Yang et al.

Contact-tracing apps have potential benefits in helping health authorities to act swiftly to halt the spread of COVID-19. However, their effectiveness is heavily dependent on their installation rate, which may be influenced by people's perceptions of the utility of these apps and any potential privacy risks due to the collection and releasing of sensitive user data (e.g., user identity and location). In this paper, we present a survey study that examined people's willingness to install six different contact-tracing apps after informing them of the risks and benefits of each design option (with a U.S.-only sample on Amazon Mechanical Turk, $N=208$). The six app designs covered two major design dimensions (centralized vs decentralized, basic contact tracing vs. also providing hotspot information), grounded in our analysis of existing contact-tracing app proposals. Contrary to assumptions of some prior work, we found that the majority of people in our sample preferred to install apps that use a centralized server for contact tracing, as they are more willing to allow a centralized authority to access the identity of app users rather than allowing tech-savvy users to infer the identity of diagnosed users. We also found that the majority of our sample preferred to install apps that share diagnosed users' recent locations in public places to show hotspots of infection. Our results suggest that apps using a centralized architecture with strong security protection to do basic contact tracing and providing users with other useful information such as hotspots of infection in public places may achieve a high adoption rate in the U.S.