Over the last two years or so, the Canadian Government has been openly exploring the issue of how some government processes, such as the processing of lower risk or routine immigration files can be made more efficient through the use of AI (machine learning) algorithmic processes.
The good news is that the adoption of these systems has so far been guided by a digital framework which includes making the processes and software open by default whenever possible. These guidelines hint at a transparency that is necessary to mitigate algorithmic bias.
I usually only post to this blog once per week, but a news story caught my eye today since it concerns my sector (higher education), my country (Canada) and my passion (technology critique).
Mount Royal University in Calgary, Alberta is going to be the first organization in Canada to install an AI system for the purposes of security. This system consists of a network of cameras and a machine learning algorithm that spends the first few weeks learning what “normal” movement looks like on campus, then uses that baseline to detect if there might be a security issue. Deviations from normal in this case, signal a potential “threat” or at least an event worth looking into. As described by the Vice-President, Securities management in a recent CBC article:
“when that pattern breaks, what it does, that screen comes to life and it shows the people in the security office where the pattern is now different and then it’s up to a human being to decide what to do about it,”