Collection of Open Source GIScience Projects
Privacy is defined as “The claim of individuals, groups, or institutions to determine for themselves when, how, and to what extent information about them is communicated to others” (Westin 1970, c.b. Kerski, 2016). This extends to spatial data with regard to location privacy: “the claim of individuals to determine when, how, and to what extent location information about them is communicated to others. It refers to the ability of an individual to move in public spaces with a reasonable expectation that their location will not be recorded without permission for later use by a third party” (Kerski and Clark, 2012, c.b. Kerski, 2016).
This blog post is informed by a talk by Xun Shi that focuses on a bottom-up approach to epidemic modeling in the context of the COVID-19 pandemic. It must first be acknowledged that this endeavor and others similar to it are highly useful and can help save lives and prevent devastating consequences. This analysis relies on human mobility data that is sourced from the government, which is strictly limited in terms of accessibility and permitted use (with good reason). The data are also de-identified. However, the fact that the identified versions of the data exist raises interesting questions about how data like these may be used in more sinister contexts than disease outbreak modeling. For instance, location data could be used to crack down on protesters or “undesirable” gatherings, as illustrated by the ease with which a party event was pinpointed in the example given in the webinar. This can lead to further ethical quandaries about the use of advancement of government policies that may not be in the best interests of citizenry (DiBiase, 2017) Additionally, inferences about individuals and their movements can be made from aggregated location data. It is also interesting to consider the misrepresentation of data (intentional or not) in big datasets that can do real damage to individuals (Poorthuis, 2018).
In addition, it is interesting that personal data about individuals is controlled by outside parties and likely is not accessible to the individual themselves. Indeed, access to and use of the data is controlled by those in power. This is similar to the example of disaster data in Haiti being controlled by a third party while those generating the data are dispossessed of it (Crawford and Finn, 2014).
The use of personal disease case data is also interesting. Healthcare records contain particularly sensitive information and can be used to discriminate against or target vulnerable individuals. The delicate balance between using data “for the greater good” and respecting the rights of individuals is a difficult one to strike, as we saw in Crawford and Finn (2014). Individuals should be given the opportunity to provide informed consent regarding how their data will be collected and used, in order to align with the principle of location privacy. A great deal of moral responsibility falls on GIS analysts in cases like these (DiBiase, 2017), which educating GIS analysts in moral considerations of the ethics of data use and representation an essential facet of studying GIS and geography.
Ultimately, there needs to be greater accountability by data controllers and a stronger framework of informed consent with regard to data use. This seems to be the case in Xun Shi’s research specifically, as the government limits access to and use of the data quite rigorously. However, there needs to be strict accountability for the government’s own use of the data that holds, in addition to controls on those who are allowed to use it. As the Kerski (2016) reading states, GIS has advanced far more quickly than the frameworks that govern the use of spatial data. It is imperative that the use of spatial data be curtailed somewhat until a better framework of fair use of personal spatial data has been legally developed. There should be an emphasis on informed consent, a right to decline to have disaggregate (individual-level) data used, and controls placed on data controllers themselves. Public education about data collection and its use ought to be a fundamental human right as we move forward in this age of big data.
Readings:
Crawford, K., and M. Finn. 2014. The limits of crisis data: analytical and ethical challenges of using social and mobile data to understand disasters. GeoJournal 80 (4):491–502. DOI:10.1007/s10708-014-9597-z
DiBiase, D. (2017). Professional and Practical Ethics of GIS&T. The Geographic Information Science & Technology Body of Knowledge (2nd Quarter 2017 Edition), John P. Wilson (ed.). doi: 10.22224/gistbok/2017.2.2
Kerski, J. (2016). Location Privacy. The Geographic Information Science & Technology Body of Knowledge (3rd Quarter 2016 Edition), John P. Wilson (ed.). DOI: 10.22224/gistbok/2016.3.2
Poorthuis, A. (2018). Big Data Visualization. The Geographic Information Science & Technology Body of Knowledge (3rd Quarter 2018 Edition), John P. Wilson (Ed.). DOI: 10.22224/gistbok/2018.3.5