Using data collected from over 600,000 safety inspections completed over the course of a decade, the City of Edmonton has trained an AI model to predict whether single-family home builders will pass low-risk inspections.
And they’ve put this data to work by enabling the City to automatically pass inspections for builders with a good track record and for those inspections posing limited risk to public (homeowner) safety. This model has reduced builder delays and allowed the City to focus resources on higher risk inspections.
In fact, the use of this AI model and the new inspection process in Edmonton has resulted in a 37% decrease in eligible inspections – a staggering efficiency pickup – and an economic boost from faster development with fewer roadblocks.
With finite resources and variable risk for building projects, this shift to more data-driven resource allocation seems logical, but has proven tougher to implement across agencies and departments for various reasons such as data silos and staffing limitations.
Towards better decisioning-making
The City is bringing in new data constantly as builders continue to apply for permits and new scenarios are run through the model. The next step for Edmonton is to expand the model outside single-family residences and increase the scope of impact.
And while the buzz around smarter use of data continues to grow, Edmonton mayor Don Iveson stresses the importance of creating policies around this data.
“I truly believe the next frontier for governments is how we can use data and AI to make better evidence-based decisions. To know that we’re leading the way in this rapidly-evolving field while making things easier for businesses is very encouraging,” Iveson said.