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Like most organizations, cities are now summoned to use conclusive data in their decision-making processes and within the context of their operations. However, as local governments, cities are also guarantors of dynamic living environments and, in particular, of the definition of a quality public space.

In a study conducted on the social acceptability of Internet of Things technologies, the City of Montreal and CIRAIG highlighted 11 areas of interest: individual freedom, protection of the common good, equity and inclusion, etc. These issues are mainly related to the collection of data in public space, in which the notion of individual consent becomes obsolete.

These numerous issues could lead us to simply oppose any data collection in public spaces and more generally to not use the data generated by cities. However, it is obvious that the cost of having a data deficit is also difficult to accept as a society. The challenge is to balance benefits and risks and to collect and use data responsibly. To strike such balances, we already have the necessary tools: democratic processes.

It is not just about making this an election issue - although it would be an interesting point, regardless of the level of government. The goal is to use fine mechanisms, based on deliberation, ideally including experts, citizens, and elected officials, to assess issues. These processes, which exist in many cities, will have to be adapted for this subject, which is very technical, but which also has a direct bearing on the daily lives of citizens. In particular, they should enable impact monitoring and transparency at all times.

It is for all these reasons that the City of Montreal has collaborated with the Métropole de Nantes to develop a data charter making these principles rules that the City will undertake to follow.

In order to limit data deficits, this charter also defines the notion of data of territorial interest: cities should be able to request data from public and private actors having an impact on the territory (transportation, housing, access to food etc.) and whose impact could be evaluated by data collected by these actors. Examples include the debates surrounding data access for platforms like Uber or Airbnb.

Fears of government surveillance and profiling or of the risks of self-censorship and self-restraint of behavior when “machines” observe us, are real and complex questions that will not find a simple solution or miracle cure. It will be a slow and tense process requiring the development of solid democratic processes, adapted and based on the commitment of many stakeholders. This process should start now.