What Toronto’s Quayside project has taught us about smart cities and data

An artist's impression of Sidewalk Lab's Quayside smart-city project in Toronto. Image: Sidewalk Labs.

Toronto’s proposed Quayside community was supposed to be a brag-worthy global showcase for what a smart city, “built from the internet up,” would look like. Instead, the joint partnership between Waterfront Toronto and U.S.-based Sidewalk Labs swiftly got caught in a 12-month, $50m negotiation and consultation process. Those involved in Quayside have been surprised by the concerns raised about the project and the resistance to it.

A public meeting in March — only their second in five months — failed to fill in basic details about the nature of the partnership, including how the for-profit Sidewalk Labs would actually generate income from the project. Perhaps most surprisingly, officials at the meeting revealed that they were still privately negotiating the most fundamental components of their partnership, namely what data would be collected, who would control and own this data, where it would be stored and how it would be used.

The two sides are also negotiating who will control the intellectual property (IP) that comes from a project that has been designed to produce lots of IP.

Coming to terms with a data-driven world

These are not trivial issues. Smart-city infrastructure requires data collection — in fact, data is best conceived of as the fuel that powers smart cities. Without a constant stream of new data, smart cities cannot be as responsive in delivering public services.

In this respect, Quayside is not unique. Infrastructure projects will increasingly include data components, and municipalities and other levels of government — to say nothing of the citizens whose data these projects will collect — will face challenges similar to those currently encountered by Waterfront Toronto.

Government officials and our fellow citizens can learn a great deal about how not to approach such projects by examining Waterfront Toronto’s negotiations with Sidewalk Labs.

We suggest three key principles to consider for future smart city infrastructure projects:


1. In data-intensive projects, data is the whole game

Most of the flat-footedness related to the Quayside project to date can be traced back to Waterfront Toronto’s original request for proposals (RFP). The document treats data instrumentally, focusing on what it can enable rather than treating it as the main product.

There is very little in the RFP that directly references the issue of data control, and the RFP is silent on who will determine what data will be generated. Instead, these and other related issues are left to be determined after the fact, with the RFP requiring only that “the Partner will work closely with Waterfront Toronto to... create the required governance constructs to stimulate the growth of an urban innovation cluster, including legal frameworks (e.g., Intellectual Property, privacy, data sharing)... deployment testbeds and project monitoring... reporting requirements and tools to capture data.”

2. Set your governance policies in advance

Here, we cannot do better than Bianca Wylie, head of the Open Data Institute Toronto: “You don’t write policy with a vendor.”

By not knowing — or not thinking through — what it wanted on data and IP governance, Waterfront Toronto has left itself to negotiate a deal that has fundamental implications for privacy and data security, and that may lead to de facto privatisation of formerly public services.

While issues such as privatisation are potentially legitimate policy options, typically they are decided upon before the fact.

3. Focus on data collection, control and use

Everything about data — from the decision to collect it to the way it is used — has a societal impact and therefore requires careful thought. Data-governance policies should, at the very minimum, answer the following questions:

Who controls the decision over what data is generated, its direct and indirect uses, the data itself and the platform through which the data is collected, including access to that platform?

How are decisions about the generation, collection and use of data made?

How will the data be used?

What are the social and economic consequences of these actions?

A national data-governance strategy

Not all of the blame for this situation rests with Waterfront Toronto.

Canada, as others have noted, lacks a data-governance strategy.

As Wylie has remarked in the context of the Quayside project, our entire legislative framework is woefully out of date, and “we haven’t had a national discussion about our data, related public infrastructure, and the degree to which we want big tech influencing our governance and public services”.

Nonetheless, Waterfront Toronto should have set their data-governance demands in advance, and then sought out vendors. Much of the resulting confusion about Quayside can be traced to this initial mistake.

Fortunately, this is a learning opportunity for other governments. Almost everything government does now has a data component. This understanding must be built into their procurement prior to engaging with vendors.

The ConversationBetter yet, governments should create an overarching data governance plan and use that to guide interactions with various stakeholders. The stakes are too high to leave such consequential policies to chance.

Blayne Haggart, Associate Professor of Political Science, Brock University and Zachary Spicer, Visiting Researcher, University of Toronto.

This article was originally published on The Conversation. Read the original article.

 
 
 
 

Businesses need less office and retail space than ever. So what does this mean for cities?

Boarded up shops in Quebec City. Image: Getty.

As policymakers develop scenarios for Brexit, researchers speculate about its impact on knowledge-intensive business services. There is some suggestion that higher performing cities and regions will face significant structural changes.

Financial services in particular are expected to face up to £38bn in losses, putting over 65,000 jobs at risk. London is likely to see the back of large finance firms – or at least, sizable components of them – as they seek alternatives for their office functions. Indeed, Goldman Sachs has informed its employees of impending relocation, JP Morgan has purchased office space in Dublin’s docklands, and banks are considering geographical dispersion rather concentration at a specific location.

Depending on the type of business, some high-order service firms will behave differently. After all, depreciation of sterling against the euro can be an opportunity for firms seeking to take advantage of London’s relative affordability and its highly qualified labour. Still, it is difficult to predict how knowledge-intensive sectors will behave in aggregate.

Strategies other than relocation are feasible. Faced with economic uncertainty, knowledge-intensive businesses in the UK may accelerate the current trend of reducing office space, of encouraging employees to work from a variety of locations, and of employing them on short-term contracts or project-based work. Although this type of work arrangement has been steadily rising, it is only now beginning to affect the core workforce.

In Canada – also facing uncertainty as NAFTA is up-ended – companies are digitising work processes and virtualising workspace. The benefits are threefold: shifting to flexible workspaces can reduce real-estate costs; be attractive to millennial workers who balk at sitting in an office all day; and reduces tension between contractual and permanent staff, since the distinction cannot be read off their location in an office. While in Canada these shifts are usually portrayed as positive, a mark of keeping up with the times, the same changes can also reflect a grimmer reality.  

These changes have been made possible by the rise in mobile communication technologies. Whereas physical presence in an office has historically been key to communication, coordination and team monitoring, these ends can now be achieved without real-estate. Of course, offices – now places to meet rather than places to perform the substance of consulting, writing and analysing – remain necessary. But they can be down-sized, with workers performing many tasks at home, in cafés, in co-working spaces or on the move. This shifts the cost of workspace from employer to employee, without affecting the capacity to oversee, access information, communicate and coordinate.

What does this mean for UK cities? The extent to which such structural shifts could be beneficial or detrimental is dependent upon the ability of local governments to manage the situation.


This entails understanding the changes companies are making and thinking through their consequences: it is still assumed, by planners and in many urban bylaws and regulations, that buildings have specific uses, that economic activity occurs in specific neighbourhoods and clusters, and that this can be understood and regulated. But as increasing numbers of workers perform their economic activities across the city and along its transport networks, new concepts are needed to understand how the economy permeates cities, how ubiquitous economic activity can be coordinated with other city functions, such as housing, public space, transport, entertainment, and culture; and, crucially, how it can translate into revenue for local governments, who by-and-large rely on property taxes.

It’s worth noting that changes in the role of real-estate are also endemic in the retail sector, as shopping shifts on-line, and as many physical stores downsize or close. While top flight office and retail space may remain attractive as a symbolic façade, the ensuing surplus of Class B (older, less well located) facilities may kill off town-centres.

On the other hand, it could provide new settings within which artists and creators, evicted from their decaying nineteenth century industrial spaces (now transformed into expensive lofts), can engage in their imaginative and innovative pursuits. Other types of creative and knowledge work can also be encouraged to use this space collectively to counter isolation and precarity as they move from project to project.

Planners and policymakers should take stock of these changes – not merely reacting to them as they arise, but rethinking the assumptions that govern how they believe economic activity interacts with, and shapes, cities. Brexit and other fomenters of economic uncertainty exacerbate these trends, which reduce fixed costs for employers, but which also shift costs and uncertainty on to employees and cities.

But those who manage and study cities need to think through what these changes will mean for urban spaces. As the display, coordination and supervision functions enabled by real-estate – and, by extension, by city neighbourhoods – Increasingly transfer on-line, it’s worth asking: what roles do fixed locations now play in the knowledge economy?

Filipa Pajević is a PhD student at the School of Urban Planning, McGill University, researching the spatial underpinnings of mobile knowledge. She tweets as @filipouris. Richard Shearmur is currently director of the School, and has published extensively on the geography of innovation and on location in the urban economy.