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Balancing Privacy With Data Sharing for the Public Good


The data sharing norms established by the Bermuda Principles greatly sped up the development of the mRNA coronavirus vaccines. A Chinese lab announced the discovery of the novel coronavirus on Jan. 9, 2020; sequenced it over the next weekend; and released the genome sequence to the public immediately thereafter. By the end of January, labs around the world were developing vaccines based on the genome sequence, despite not yet having an actual sample. Without a commitment to open data, coronavirus vaccines might still be months away.

To be sure, the use of consumers’ genetic data raises serious privacy concerns. While it is common practice to remove identifiers such as surnames from genetic data before releasing it to the public, researchers have sometimes managed to identify individuals anyway by combining anonymous gene sequences with genealogical databases and other public information such as age and state of residence. These problems can be solved with further protections, but they require constant vigilance.

Privacy can never be guaranteed with absolute certainty. The risks should always be minimized, and balanced against the benefits of the innovations that may arise from increased data availability.

Similar logic applies to economic data. Consider the U.S. policy response to the coronavirus. The Paycheck Protection Program provision of the Coronavirus Aid, Relief and Economic Security (CARES) Act provided hundreds of billions of dollars in forgivable loans to small businesses. Despite the large amount of relief available, demand for loans greatly exceeded supply. Ideally, loans would have been based on expected need, but the Treasury had no information about firms’ financial health.

In the absence of good data, the loans were based on expediency rather than expected need, using local banks as intermediaries, and they made loans disproportionately to firms with which they had strong connections. Economists estimate that the program spent between $150,000 and $377,000 per job saved, a high price for a program that was guaranteed for only a few months.

A better program would target aid to business sectors and geographies that most need help, using real-time data from the businesses themselves. This data already exists, but only behind company walls. It should be anonymized as carefully as possible and assembled for public use, so that local policymakers and entrepreneurs can direct the relief to those who need it most.

One promising model is the Opportunity Insights Economic Tracker, a publicly available repository of anonymized data contributed by private companies. The tracker was started in May by researchers at Harvard and Brown. (I collaborate with Opportunity Insights, although I was not part of the work on the tracker.) Real-time analysis of economic effects — enabled by better data sharing — can improve the targeting of policies to those in greatest need.

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