Kris Andreychuk, Supervisor of Community Safety in the City of Edmonton's Neighbourhood Empowerment Team, was frustrated. His teams of social workers, police officers and youth workers were great at helping move criminals or juvenile offenders onto a better path after they'd been involved in a crime, but he wanted to predict areas where crime would be most likely to be brewing so they could work to improve those neighborhoods before crimes happened. We discuss how they did it, some surprising results, and the need to combine powerful machine learning algorithms with human intelligence.

That led him to contact Stephane Contre, Chief Analytics Officer of Edmonton's Open City Team, to see how they could use the masses of data the City had access to in order to identify patterns that are likely to cause crime in a particular area.