Key Takeaways
- Canada faces a "compute gap" due to a lack of artificial intelligence (AI) infrastructure, leading to a brain drain of researchers and innovators.
- The country has the opportunity to develop a unique approach to AI that prioritizes sustainability, sovereignty, and responsibility.
- Canada’s clean energy grid and cold climate give it a natural advantage in developing efficient AI infrastructure.
- A "third path" approach to AI development, focusing on sustainable, sovereign, and responsible AI, can help Canada close its compute gap and achieve its climate goals.
- This approach requires alignment across governments, utilities, and industry, as well as a focus on engineering trust and verifiable governance.
Introduction to the Compute Gap
Canada is facing a significant challenge in the field of artificial intelligence (AI) due to a lack of infrastructure, known as a "compute gap." This gap is causing a brain drain of researchers and innovators, who are forced to seek opportunities abroad where they can access more advanced computational capacity. As a result, Canada is losing its talent and struggling to develop its own AI capabilities. Furthermore, researchers who remain in Canada often have to send their work and data to the United States to be processed on AI infrastructure, which raises concerns about data sovereignty and security.
The Wrong Paths
Other countries, such as the United States and those in Europe, have taken different approaches to developing AI infrastructure. The United States has prioritized a market-first approach, allowing large tech companies to grow quickly and dominate the market. However, this approach has led to concerns about the environmental impact of AI, as well as issues with data privacy and security. Europe, on the other hand, has taken a regulation-first approach, implementing stricter rules for AI development and deployment. However, this approach has also been criticized for being overly restrictive and limiting innovation. Neither of these approaches has successfully addressed the core paradox of AI development: the need to balance the growth of AI with the need to reduce its environmental impact.
A Third Path: Sovereign, Sustainable, Responsible AI
Canada has the opportunity to develop a unique approach to AI that prioritizes sustainability, sovereignty, and responsibility. This approach, known as the "third path," focuses on developing AI infrastructure that is designed to be sustainable from the outset, using clean energy and minimizing waste. It also prioritizes sovereignty, ensuring that Canadian data and infrastructure remain under Canadian control. Finally, it emphasizes responsibility, incorporating ethics and governance into the development and deployment of AI. This approach is built on three pillars: sustainability-by-design, sovereignty-by-design, and responsibility-by-design. By prioritizing these principles, Canada can develop AI infrastructure that is not only more efficient and effective but also more trustworthy and secure.
The Advantages of the Third Path
Canada has several advantages that make it well-suited to develop this third path approach to AI. The country’s clean energy grid, which is powered by hydro, nuclear, wind, and solar energy, provides a reliable and sustainable source of power for AI infrastructure. Additionally, Canada’s cold climate reduces the need for cooling systems, making AI data centers more efficient. The country’s stable public institutions and strong governance framework also provide a solid foundation for developing trustworthy and secure AI infrastructure. Furthermore, Canada’s unique approach to AI development can help to attract and retain top talent in the field, reducing the brain drain and promoting innovation and growth.
From Crisis to Catalyst
The development of AI infrastructure is often seen as a crisis, due to its high energy demands and potential environmental impact. However, it can also be a catalyst for positive change, driving innovation and growth in the clean energy sector. AI can be used to optimize energy systems, predict energy demand, and improve the efficiency of energy storage and transmission. By developing AI infrastructure that is designed to be sustainable and responsible, Canada can help to drive this transition and promote a cleaner, more efficient energy system. For example, AI can be used to optimize the performance of wind turbines and solar panels, reducing energy waste and increasing the overall efficiency of renewable energy systems.
Engineering Trust
One of the key challenges in developing AI infrastructure is building trust. This requires not only ensuring that AI systems are secure and reliable but also that they are transparent and accountable. Canada can achieve this by engineering trust into the design of its AI infrastructure, incorporating principles such as explainability, fairness, and transparency. This can be done through the development of standards and guidelines for AI development and deployment, as well as through the creation of independent oversight bodies to monitor and regulate the use of AI. By prioritizing trust and transparency, Canada can build a foundation for AI development that is not only sustainable and responsible but also trustworthy and secure.
Policy Pathways
To develop a third path approach to AI, Canada will need to take a number of policy steps. These include defining a "twin standard" for AI procurement that merges green compute certification with sovereign control standards, making AI data centers "good grid citizens" by requiring them to participate in demand response and publish transparent metrics, and backing Canadian pilots in NRCan’s Energy Innovation Program. Additionally, the government can provide funding and support for research and development in AI, as well as for the creation of new AI infrastructure and technologies. By taking these steps, Canada can promote the development of sustainable, sovereign, and responsible AI infrastructure and drive innovation and growth in the sector.
Conclusion
Canada has a unique opportunity to develop a third path approach to AI that prioritizes sustainability, sovereignty, and responsibility. By leveraging its clean energy grid, cold climate, and stable public institutions, Canada can develop AI infrastructure that is not only more efficient and effective but also more trustworthy and secure. This approach can help to drive innovation and growth in the clean energy sector, promote a cleaner and more efficient energy system, and build a foundation for AI development that is sustainable, responsible, and trustworthy. By taking a proactive and strategic approach to AI development, Canada can ensure that it remains a leader in the field and that its AI infrastructure is aligned with its values and priorities.
