Trust but Not Verify: Data Governance, Smart Cities, and The Public Interest—a Case Study of Sidewalk Toronto, Canada

As a pilot site for computational approaches to sustainable urban development, the 2017 Sidewalk Toronto project envisioned a mixed-use neighborhood that integrated physical infrastructure with digital networked technologies. The potential for ubiquitous collection, use, and sharing of diverse types of data, across different spaces and stakeholders, raised concerns about how to govern data in the public interest.

While previous research emphasized the need to govern data holistically to generate public value, little has been said of the complex and political exercise to define guiding principles to design data governance institutions, standards, and processes. Thus, this thesis asks: in Sidewalk Toronto, how were these data governance constructs sites of public-private contestation over the public interest? In this context, civil society denotes participants in the public consultation, and the private sector perspective denotes that of Google’s sister company, Sidewalk Labs, who designed data governance in the project.

To answer this question, I examined how these two stakeholders sought to gain leverage over design considerations by articulating their view of the public interest, and how the private sector sought to constrain the public interest through the design outcomes themselves. I analyzed public consultation materials, corporate documents, media articles, and secondary analysis between 2017-2020 and conducted expert interviews.

I found that the public and the private sector had starkly different perceptions of what modalities and levels of control were legitimate, what types of values data should generate for the local community, and what data should fall under local governance. These findings suggest the need to ground local data governance in collective ownership over the public’s physical and digital existence. To do so, communities must account for regulatory gaps governing behavioral data, and address public-private power asymmetries in the digital infrastructural ecosystem and the global data economy.