The immense economic importance of data presents one of the most important policy challenges of our time. Yet to many, the nature of the problem remains opaque. The processes by which data gives rise to value differ from the processes by which value was produced in the 20th century. Therefore, traditional ways of thinking about property, investment, and productivity often serve us poorly in this context.Yet we cannot afford to remain confused. Because data nearly always contains information about groups, communities, and networks (in addition to individuals), it cannot be treated as conventional personal property without leading to distortions and market failures. This difficulty has resulted in an imbalanced economy in which powerful private businesses wield inappropriate power over millions by harnessing their information.The power dynamic regarding data mirrors our society’s growing inequality. It is time for legislators to address the policy vacuum that has allowed millions to be denied their rightful share in the data economy.
When a user shares her data with an online platform, she typically reveals relevant information about other users. We model a data market in the presence of this type of externality in a setup where one or multiple platforms estimate a user’s type with data they acquire from all users and (some) users value their privacy. We demonstrate that the data externalities depress the price of data because once a user’s information is leaked by others, she has less reason to protect her data and privacy. These depressed prices lead to excessive data sharing. We characterize conditions under which shutting down data markets improves (utilitarian) welfare. Competition between platforms does not redress the problem of excessively low price for data and too much data sharing, and may further reduce welfare. We propose a scheme based on mediated data-sharing that improves efficiency.