While companies are increasingly moving towards the ‘pay for privacy’ model, it is unclear how consumers make privacy decisions under this model. Toward that, we conducted an incentive-compatible lottery study on Prolific to understand the factors behind users’ choice to have additional data privacy controls. With 265 United States participants across two device risk conditions (High-risk: camera vs. Low-risk: light bulb) and three cash conditions ($9.99 vs. $19.99 vs. $29.99), results reveal that device risk and cash offerings influence participants’ lottery choice. We further observed an interaction effect between participants’ technical literacy and cash option. Specifically, technical participants chose the data privacy controls instead of cash at a higher rate when the cash condition was $29.99. In contrast, less technical participants favored the privacy option at a higher rate when the cash condition was $9.99. Implications of our findings for user data privacy are discussed in the paper.
https://dl.acm.org/doi/10.1145/3706598.3713251
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)