It's interesting because one of the areas that I've done a lot of work on over the years is technology adoption. Right now, a lot of my research is on AI and the gap between Canada's excellence in AI research and Canada's lagging in AI adoption, especially some of the ethical and other considerations.
I think that there are huge opportunities to improve the efficiency of a lot of things that we do at post-secondary institutions with technology. At the same time, we have to be mindful that not everything that is important can be measured with numbers. Again, if we're looking at impact, I think that some of the tools that are available for understanding what happens to the research after it's published are really promising. We're seeing some new areas of focus that include, for example, looking at knowledge mobilization more seriously, looking at impact on certain communities and looking at commercialization results. I'm really interested in that broader range.
The only other thing I'll mention is that I was on an OECD committee looking at rural innovation. One of the things that we found was that the traditional measures of innovation—patents, IP and stuff like that—had no relevance in rural communities even though in agriculture we see some of the most innovative practices in the adoption of AI sensors and things like that. I think what's really important is the notion of excellence, and this, perhaps, is partly what Professor Gingras was saying. One uniform measure of excellence doesn't make any sense to me. We really have to respect fundamental research and what it's trying to accomplish. We also have to respect applied research, some of the work that's done in community colleges and everything in between.