In UrbanLogiq's deployments, I have seen the dynamic models we put forward enable the addressing of geohazard risk, for example. In the city of Edmonton, as I mentioned in my opening statement, we provided a dynamic scenario modelling device and platform for city planners to determine, with climate change impacts out to 2040 and beyond, where wildfire risks would be in order to ensure that when they're building in a built environment...where they should build housing. We recognize from the lessons of Lytton, Kelowna, Hinton and Jasper, and from the wildfire damage to public safety and housing, that government has data that it can map out and utilize in a more predictive, proactive form.
This is not about relying on static reports. We know that hazard, risk and vulnerability assessments and LCCAPs—local climate adaptation plans—are examples of government-required reports that need to be done at the municipal level. We also know that with national integrated emergency management systems, we need to integrate the various jurisdictions—federal, provincial, first nations and local—in an emergency-type situation. These are examples of where we can plan better, understand where evacuation routes might be and recognize where traffic congestion and critical infrastructure demands from wildfires, flooding or earthquakes might be. These are public safety risks.
I'd also like to say, to the many comments Mr. Mullin stated to this committee, that the Government of Canada clearly needs to be using these tools. In order to properly regulate the responsive use of AI, government needs to be utilizing these tools and adopting and adapting them in a responsible way. There are federal directives for the public service around algorithmic impact assessments in order for them to be used, so there are definite regulatory requirements already established. We can do more, though.