Abstract
Consumers are often willing to contribute their personal data for analytics projects that may create new insights into societal problems. However, consumers also have justified privacy concerns about the release of their data.
We study the trade-off between privacy concerns related to data release and the incentives to contribute to the estimation of a population average of a private attribute. Consumers may decide whether to participate in the analytics project, and what level of data precision they are willing to provide. We show that setting a minimum precision level for participating users leads to a strict improvement of the estimation.
Keywords
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Acknowledgements
This work was funded by the French Government (National Research Agency, ANR) through the “Investments for the Future” Program reference # ANR-11-LABX-0031-01. We would like to thank the anonymous reviewers and Alvaro Cardenas for their helpful comments.
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Chessa, M., Grossklags, J., Loiseau, P. (2015). A Short Paper on the Incentives to Share Private Information for Population Estimates. In: Böhme, R., Okamoto, T. (eds) Financial Cryptography and Data Security. FC 2015. Lecture Notes in Computer Science(), vol 8975. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-47854-7_25
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DOI: https://doi.org/10.1007/978-3-662-47854-7_25
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