The goal of this project was to determine how insights from mobile data might be used to maximum effect in support of policy planning and crisis response with minimal risk to privacy. The project aimed to determine the impact that aggregating mobile data to protect privacy has upon the utility of the data for (i) transportation planning and (ii) pandemic control and prevention. Utility of each data set was evaluated by surveying transportation experts and epidemiologists; re-identification risk for each data set was also assessed. Risk of re-identification was subsequently considered together with data utility to determine which level of aggregation is the minimum required to adequately protect individual privacy while preserving its value for policy planning and crisis response. Results of the analysis indicate that the relationship between privacy risk and utility is complex and is highly dependent on the context and purpose of use. Nevertheless, there is a risk of re-identification in applying mobile data for the public good, and a better understanding is needed of the critical thresholds for acceptable risk. This project lays the groundwork for the development of evidence-based data standards and policy frameworks to ensure proportionality between the risk of harm resulting from the misuse of mobile data and the risk of harm resulting from a failure to use it.
Mapping the Risk-Utility Landscape of Mobile Data for Sustainable Development and Humanitarian Action
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