Artificial intelligence (AI) is transforming societies and economies around the world at a rapid pace. However, Quebec risks falling behind in leveraging the opportunities of AI due to several gaps in its ecosystem. In this comprehensive blog post, I analyze the current limitations around AI development, adoption, and governance in Quebec across the public, private, and academic sectors. Based on this diagnosis, I then provide targeted, actionable recommendations on how Quebec can build understanding, expertise, collaboration, and oversight to unlock the full potential of AI as a force for economic and social good. Read on for insights into the seven key areas requiring intervention and over 40 proposed solutions to propel Quebec into a leadership position in the global AI landscape.

We are now firmly in a world where organizations are beginning to see returns from their investments in AI adoption within their organizations. At the same time, they are also experiencing growing pains, such as the emergence of shadow AI, that raises cybersecurity concerns. While useful as a North Star, guidelines need accompanying details that help implement them in practice. Right now, we have an unmitigated intention-action gap that needs to be addressed - it can help strengthen the UGAI and enhance its impact as organizations adopt this as their de facto set of guidelines.

It is important to recognize that AI systems often provide a poor representation and imitation of a person's true identity. As a reference, it can be compared to a blurry JPEG image, lacking depth and accuracy. AI systems are also limited by the information that has been published and captured in their training datasets. The responses they provide can only be as accurate as the data they have been trained on. It is crucial to have extensive and detailed data in order to capture the relevant tone and authentic views of the person being represented.

"Move fast and break things" is broken. But we've all said that many times before. Instead, I believe we need to adopt the "Move fast and fix things" approach. Given the rapid pace of innovation and its distributed nature across many diverse actors in the ecosystem building new capabilities, realistically, it is infeasible to hope to course-correct at the same pace. Because course correction is a much harder and slow-yielding activity, this ends up amplifying the magnitude of the impact of negative consequences.

The recent voluntary commitments secured by the White House from the core developers of advanced AI systems (OpenAI, Microsoft, Anthropic, Inflection, Amazon, Google, and Meta) presents an important first step in building and using safe, secure, and trustworthy AI. While it is easy to shrug aside voluntary commitments as "ethics washing," we believe that they are a welcome change.