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

@article{Liao2021ThePP,
  title={The Privacy Paradox and Optimal Bias-Variance Trade-offs in Data Acquisition},
  author={Guocheng Liao and Yu Su and Juba Ziani and Adam Wierman and Jianwei Huang},
  journal={Proceedings of the 22nd ACM Conference on Economics and Computation},
  year={2021}
}
  • Guocheng Liao, Yu Su, +2 authors Jianwei Huang
  • Published 2021
  • Computer Science
  • Proceedings of the 22nd ACM Conference on Economics and Computation
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… Expand

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