At the Vector Institute, there's a two-pronged approach that we use. The main one is to get people hands-on. First of all, we found that's the most effective way to do skills transfers in AI. Second of all, for companies that are just beginning their AI journey, doing a low-level AI use case implementation is the best way to start to get them familiar with it. It reduces the apprehension level, and it has a relatively easier to achieve ROI. We always encourage companies to start with small-scale AI implementation first, to get them started on their trust journey and transformation journey in AI.
The other part is where we direct the corporation's efforts on a strategic level. Early on in the Vector Institute's life, we recognized that AI is a topic that provokes quite a visceral reaction in the general population. We thought about that in two ways.
The first was the extent to which and to acknowledge that we receive a large amount of public funding. We looked at the government as a corporation that spends money. Where should that corporation want to use AI to improve the efficiencies and outcomes of its operations? The largest expense line in public expenses is, unequivocally, health care. The extension of that thought is, to the extent that AI as a topic is a topic that can provoke fear in the general population, if we advance health AI projects, explaining to the general public that we have used AI to improve health outcomes to reduce mortality, reduce waiting times, reduce comorbidities and increase detection of disease so that we can do early intervention would be one of the best ways to encourage greater levels of trust in AI adoption.