The Privacy Paradox and Optimal Bias-Variance Trade-offs in Data Acquisition

Understand

While users claim to be concerned about privacy, often they do little to protect their privacy in their online actions.

• One prominent explanation for this "privacy paradox" is that when an individual shares her data, it is not just her privacy that is compromised; the privacy of other individuals with correlated data is also compromised.
• This information leakage encourages oversharing of data and significantly impacts the incentives of individuals in online platforms.
• In this paper, we study the design of mechanisms for data acquisition in settings with information leakage and verifiable data.