🤖 AI Summary
This study investigates whether privacy-enhancing technologies (PETs) meaningfully reduce consumers’ perceived privacy violation (PPV) from online advertising. Method: Drawing on the dual-privacy theoretical framework, we conducted an online experiment with U.S. users to compare PPV across distinct data practices—behavioral targeting, on-device processing, cohort-based targeting, and context-based targeting—while varying tracking and personalization mechanisms. Contribution/Results: We provide the first empirical evidence of substantial consumer misperceptions regarding technically defined privacy protections: on-device processing yields only marginal PPV reduction; cohort-based targeting confers no advantage over individual-level behavioral targeting; and tracker-free contextual targeting significantly lowers PPV—approaching levels observed with no ads at all. Notably, users exhibit no statistically significant preference difference between tracker-free non-targeted ads and ad-free browsing. These findings challenge prevailing assumptions about PET efficacy and offer critical empirical grounding for privacy-by-design principles and regulatory policy.
📝 Abstract
In response to privacy concerns about collecting and using personal data, the online advertising industry has been developing privacy-enhancing technologies (PETs), e.g., under Google's Privacy Sandbox initiative. In this research, we use the dual-privacy framework, which postulates that consumers have intrinsic and instrumental preferences for privacy, to understand consumers' perceived privacy violations (PPVs) for current and proposed online advertising practices. The key idea is that different practices differ in whether individual data leaves the consumer's machine or not and in how they track and target consumers; these affect, respectively, the intrinsic and instrumental components of privacy preferences differently, leading to different PPVs for different practices. We conducted online studies focused on consumers in the United States to elicit PPVs for various advertising practices. Our findings confirm the intuition that tracking and targeting consumers under the industry status quo of behavioral targeting leads to high PPV. New technologies or proposals that ensure that data are kept on the consumer's machine lower PPV relative to behavioral targeting but, importantly, this decrease is small. Furthermore, group-level targeting does not differ significantly from individual-level targeting in reducing PPV. Under contextual targeting, where there is no tracking, PPV is significantly reduced. Interestingly, with respect to PPV, consumers are indifferent between seeing untargeted ads and no ads when they are not being tracked. We find that consumer perceptions of privacy violations under different tracking and targeting practices may differ from what technical definitions suggest. Therefore, rather than relying solely on technical perspectives, a consumer-centric approach to privacy is needed, based on, for instance, the dual-privacy framework.