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When Privacy Is a Public Good

Shared private information creates a common resource, much like a public park, where individual contribution of private data adds up to a data pool that has vast social and community benefits. Just as taxes pay for public goods such as parks, shared data “pay” for common resources or public goods. Connections across the network economy make the benefits of sharing apparent so cooperation is elicited.

Large, detailed private data are more valuable when shared because they provide the information for improved transportation and public health systems. Common traffic patterns in congested cities and movement patterns in infected areas can be analyzed by data downloaded from personal databanks on smartphones. For example, in 2014 when Ebola raged in West Africa, doctors traced geolocation capabilities on mobile phones to contain spread of the virus. Orange Telecom in Senegal cooperated by giving the data to the Swedish non-profit Flowminder, which aided in drawing up population movement maps. Doctors then set up treatment areas and quarantine areas. Similarly, the US Centers for Disease Control is collecting activity data from mobile phone operators to view where most helpline calls are coming from, since an increase in mobile calls from a single area would alert authorities about a potential disease [108].

Drone technologies manifested in unmanned aircraft systems (UAS) are basically surveillance platforms that enhance observational capabilities. They are used for environmental monitoring of pollution in cities and tracking wildlife in National Parks, for example. They are also used by the media as a safe platform for news gathering and by package delivery services such as Amazon. However, there are also malevolent privacy invasion possibilities such as when an UAS flies over private property and collects personal data. The Federal Aviation Administration requires all UAS weighing between 0.55 and 55 lbs to be registered, which suggests an incremental approach to UAS regulation [109].

Private sites collect the vast majority of personal data and these data sets are more valuable as a common resource since their social value far exceeds their private value. For example, Nextdoor is a social networking site for neighborhoods, founded in 2011, and enables connections between neighbors for sharing community-related information. Nextdoor Now can help residents find local services and neighbors’ reviews. The content on this site is crowd sourced with personal information, but to the benefit of all. Malevolent use, such as racial profiling, is an unforeseen outcome of the original intent of the neighborhood crime watch. “Rather than bridging gaps between neighbors, Nextdoor can become a forum for paranoid racialism” [110]. While there is the potential for any private crowd sourcing site to marginalize and exclude, Seattle police department practices “micro-community policing” by using local data to tailor law enforcement to the relevant community [111].

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