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Tuesday, 14 February 2017 14:11
Note: the following are my speaking notes for my appearance before the Standing Committee on Transport, Infrastructure and Communities, February 14, 2017. The Committee is exploring issues relating Infrastructure and Smart Communities. I have added hyperlinks to relevant research papers or reports.
Thank you for the opportunity to address the Standing Committee on Transport, Infrastructure and Communities on the issue of smart cities. My research on smart cities is from a law and policy perspective. I have focused on issues around data ownership and control and the related issues of transparency, accountability and privacy.
The “smart” in “smart cities” is shorthand for the generation and analysis of data from sensor-laden cities. The data and its accompanying analytics are meant to enable better decision-making around planning and resource-allocation. But the smart city does not arise in a public policy vacuum. Almost in parallel to the development of so-called smart cities, is the growing open government movement that champions open data and open information as keys to greater transparency, civic engagement and innovation. My comments speak to the importance of ensuring that the development of smart cities is consistent with the goals of open government.
In the big data environment, data is a resource. Where the collection or generation of data is paid by taxpayers it is surely a public resource. My research has considered the location of rights of ownership and control over data in a variety of smart-cities contexts, and raises concerns over the potential loss of control over such data, particularly rights to re-use the data whether it is for innovation, civic engagement or transparency purposes.
Smart cities innovation will result in the collection of massive quantities of data and these data will be analyzed to generate predictions, visualizations, and other analytics. For the purposes of this very brief presentation, I will characterize this data as having 3 potential sources: 1) newly embedded sensor technologies that become part of smart cities infrastructure; 2) already existing systems by which cities collect and process data; and 3) citizen-generated data (in other words, data that is produced by citizens as a result of their daily activities and captured by some form of portable technology).
Let me briefly provide examples of these three situations.
The first scenario involves newly embedded sensors that become part of smart cities infrastructure. Assume that a municipal transit authority contracts with a private sector company for hardware and software services for the collection and processing of real-time GPS data from public transit vehicles. Who will own the data that is generated through these services? Will it be the municipality that owns and operates the fleet of vehicles, or the company that owns the sensors and the proprietary algorithms that process the data? The answer, which will be governed by the terms of the contract between the parties, will determine whether the transit authority is able to share this data with the public as open data. This example raises the issue of the extent to which ‘data sovereignty’ should be part of any smart cities plan. In other words, should policies be in place to ensure that cities own and/or control the data which they collect in relation to their operations. To go a step further, should federal funding for smart infrastructure be tied to obligations to make non-personal data available as open data?
The second scenario is where cities take their existing data and contract with the private sector for its analysis. For example, a municipal police service provides their crime incident data to a private sector company that offers analytics services such as publicly accessible crime maps. Opting to use the pre-packaged private sector platform may have implications for the availability of the same data as open data (which in turn has implications for transparency, civic engagement and innovation). It may also result in the use of data analytics services that are not appropriately customized to the particular Canadian local, regional or national contexts.
In the third scenario, a government contracts for data that has been gathered by sensors owned by private sector companies. The data may come from GPS systems installed in cars, from smart phones or their associated apps, from fitness devices, and so on. Depending upon the terms of the contract, the municipality may not be allowed to share the data upon which it is making its planning decisions. This will have important implications for the transparency of planning processes. There are also other issues. Is the city responsible for vetting the privacy policies and practices of the app companies from which they will be purchasing their data? Is there a minimum privacy standard that governments should insist upon when contracting for data collected from individuals by private sector companies? How can we reconcile private sector and public sector data protection laws where the public sector increasingly relies upon the private sector for the collection and processing of its smart cities data? Which normative regime should prevail and in what circumstances?
Finally, I would like to touch on a different yet related issue. This involves the situation where a city that collects a large volume of data – including personal information – through its operation of smart services is approached by the private sector to share or sell that data in exchange for either money or services. This could be very tempting for cash-strapped municipalities. For example, a large volume of data about the movement and daily travel habits of urban residents is collected through smart card payment systems. Under what circumstances is it appropriate for governments to monetize this type of data?
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