Andre, how-- can, can you tell us a bit more about how, uh, Statistics Canada is relating to the topic of artificial intelligence and maybe how you're thinking about this topic?

Sure can.

Um, I, I like to think about, uh, AI in, in, in really five dif- different spaces, um, in, in our approach to sort of, uh, de- dealing with all these issues.

Uh, the, the first one i- is really how we as an organization can use AI to generate operational efficiencies.

Of course, we're, um, we're a, a public sector organization, so we do really have to think about budgets and effective use of, of resources and so on, so really trying to leverage, um, AI to become a more efficient organization.

Being a statistical organization, we're also reflecting quite a bit, we're doing a bit of re- a lot of research actually on embedding AI into our statistical methods.

So in, in, in traditional statistics, we are able to put quality measures around the statistics that we produce, and, and now we're trying to think about, well, how do we, how do we embed AI into our statistical methods and be able to produce, uh, similar quality measures around the statistics that we put out? So really trying to shift from algorithmic AI, the machine learning, to more inferential use of AI, uh, inferring, uh, information about, uh, statistical populations.

... things like that that we need to think about?