Data Governance and Privacy
Data governance and privacy need to be thoughtfully addressed if we are to enable smart cities. Data privacy discussions focus on app based data. Yet, in the smart city everything a person interacts with could be a potential collector of data. The sidewalk, the street, the light poles, buildings, and parks and open spaces, for example, become data collectors. This is an emerging topic of research and one I feel passionate about. If we are to realize the a truly connected city with the internet of things, proper management of data and privacy policies are necessary.
Smart City Governance: Examining data trusts
Lauren N. McCarthy and David Morar
Forthcoming whitepaper
Abstract: Multiple smart cities plans have proposed the use of a data trust to govern the massive amounts of anticipated public data. Data trusts are gaining prominence as the optimal model of smart city data governance and are being adopted by smart city plans. A data trust applies the concept of a legal trust to data. In other words, it is a legal structure that provides third party oversight for data. In theory, data trusts give the public greater control over personal data, an attractive proposition for a city government looking to calm public concerns over privacy and commercialization of public data. This paper asks if civic data trusts are indeed the optimal data governance model for the smart city. Looking at the six dimensions of the smart city, this paper first identifies what kind of data will be collected. Through this, a taxonomy of data types is created. Using existing theory and examples from the EU, UK, Canada and the US, various governance regimes will be evaluated to recommend a governance model best suited to addressing the various data dimensions of the smart city.
Safeguarding Privacy While Sharing: The Prospects of an Autonomous Fleet
Lauren N. McCarthy and David Morar
Presented at the Automated Vehicle Symposium 2016
Autonomous Vehicle (AV) technology, at level 4 -full autonomy, promises a reduction in social costs. Social costs include accidents, congestion, noise, air pollution, and greenhouse gas (GHG) emissions. AVs are estimated to produce benefits across the board, by reducing the number of cars needed, thus minimizing traffic jams, therefore cutting emissions, and creating a more efficient transportation network. However, some transportation experts (Fagnant and Kockelman, 2014, 2016) have contended that autonomous vehicles will provide the most substantial benefits for society if the fleet is shared.
While AVs alone raise a variety of privacy issues, the notion of a shared fleet of AVs complicates things even further. A shared fleet removes the power and ownership of an individual operating a private vehicle and transposes that into a mechanism with a shared car that is owned or used by multiple people. Thus, our impetus to consider how the renegotiation of the concept of ownership spills over into the area of privacy when dealing with a fleet of AVs. Privacy issues in such a configuration abound and span from sharing Bluetooth, Wi-Fi, and personalized settings to more serious concerns like GPS routes, and other elements that could easily be used to identify the previous or a regular user of the car.
Who owns the data that are collected in a shared vehicle? We believe that it is crucial to address these issues, and consider a preliminary framework for fleet management that keeps privacy as an important design element rather than an afterthought. The poster framed these questions while highlighting current literature on the topic, reviews similar issues across several sectors, as well as sketches policy recommendations drawn from our research.